diff --git a/CHANGELOG.md b/CHANGELOG.md
index d7b14eda..2dab53ac 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -9,7 +9,7 @@
   
 ## Changelog
   
-### **HEAD -> main** 2022/07/26 mandic00@live.com
+### **HEAD -> main** 2022/07/29 mandic00@live.com
 
 
 ### **release: 2.9.1** 2022/07/25 mandic00@live.com
diff --git a/demo/typescript/index.html b/demo/typescript/index.html
index 47296bfb..a74a14bc 100644
--- a/demo/typescript/index.html
+++ b/demo/typescript/index.html
@@ -25,6 +25,6 @@
     <video id="video" playsinline style="display: none"></video>
     <pre id="status" style="position: absolute; top: 12px; right: 20px; background-color: grey; padding: 8px; box-shadow: 2px 2px black"></pre>
     <pre id="log" style="padding: 8px"></pre>
-    <div id="performance" style="position: absolute; bottom: 1rem; width: 100%; padding: 8px; font-size: 0.8rem;"></div>
+    <div id="performance" style="position: absolute; bottom: 0; width: 100%; padding: 8px; font-size: 0.8rem;"></div>
   </body>
 </html>
diff --git a/demo/typescript/index.js b/demo/typescript/index.js
index f01ad6bd..042f59ee 100644
--- a/demo/typescript/index.js
+++ b/demo/typescript/index.js
@@ -4,6 +4,6 @@
   author: <https://github.com/vladmandic>'
 */
 
-import{Human as p}from"../../dist/human.esm.js";var w={async:!0,modelBasePath:"../../models",filter:{enabled:!0,equalization:!1,flip:!1},face:{enabled:!0,detector:{rotation:!1},mesh:{enabled:!0},attention:{enabled:!1},iris:{enabled:!0},description:{enabled:!0},emotion:{enabled:!0}},body:{enabled:!0},hand:{enabled:!0},object:{enabled:!1},gesture:{enabled:!0}},t=new p(w);t.env.perfadd=!1;t.draw.options.font='small-caps 18px "Lato"';t.draw.options.lineHeight=20;var e={video:document.getElementById("video"),canvas:document.getElementById("canvas"),log:document.getElementById("log"),fps:document.getElementById("status"),perf:document.getElementById("performance")},o={detect:0,draw:0,tensors:0},d={detect:0,draw:0},s=(...a)=>{e.log.innerText+=a.join(" ")+`
-`,console.log(...a)},r=a=>e.fps.innerText=a,b=a=>e.perf.innerText="tensors:"+t.tf.memory().numTensors+" | performance: "+JSON.stringify(a).replace(/"|{|}/g,"").replace(/,/g," | ");async function h(){r("starting webcam...");let a={audio:!1,video:{facingMode:"user",resizeMode:"none",width:{ideal:document.body.clientWidth},height:{ideal:document.body.clientHeight}}},n=await navigator.mediaDevices.getUserMedia(a),m=new Promise(u=>{e.video.onloadeddata=()=>u(!0)});e.video.srcObject=n,e.video.play(),await m,e.canvas.width=e.video.videoWidth,e.canvas.height=e.video.videoHeight;let i=n.getVideoTracks()[0],f=i.getCapabilities?i.getCapabilities():"",v=i.getSettings?i.getSettings():"",g=i.getConstraints?i.getConstraints():"";s("video:",e.video.videoWidth,e.video.videoHeight,i.label,{stream:n,track:i,settings:v,constraints:g,capabilities:f}),e.canvas.onclick=()=>{e.video.paused?e.video.play():e.video.pause()}}async function c(){if(!e.video.paused){await t.detect(e.video);let n=t.tf.memory().numTensors;n-o.tensors!==0&&s("allocated tensors:",n-o.tensors),o.tensors=n}let a=t.now();d.detect=1e3/(a-o.detect),o.detect=a,requestAnimationFrame(c)}async function l(){if(!e.video.paused){let n=await t.next(t.result);t.config.filter.flip?await t.draw.canvas(n.canvas,e.canvas):await t.draw.canvas(e.video,e.canvas),await t.draw.all(e.canvas,n),b(n.performance)}let a=t.now();d.draw=1e3/(a-o.draw),o.draw=a,r(e.video.paused?"paused":`fps: ${d.detect.toFixed(1).padStart(5," ")} detect | ${d.draw.toFixed(1).padStart(5," ")} draw`),setTimeout(l,30)}async function y(){s("human version:",t.version,"| tfjs version:",t.tf.version["tfjs-core"]),s("platform:",t.env.platform,"| agent:",t.env.agent),r("loading..."),await t.load(),s("backend:",t.tf.getBackend(),"| available:",t.env.backends),s("models stats:",t.getModelStats()),s("models loaded:",Object.values(t.models).filter(a=>a!==null).length),r("initializing..."),await t.warmup(),await h(),await c(),await l()}window.onload=y;
+import{Human as p}from"../../dist/human.esm.js";var w={async:!0,modelBasePath:"../../models",filter:{enabled:!0,equalization:!1,flip:!1},face:{enabled:!0,detector:{rotation:!1},mesh:{enabled:!0},attention:{enabled:!1},iris:{enabled:!0},description:{enabled:!0},emotion:{enabled:!0}},body:{enabled:!0},hand:{enabled:!0},object:{enabled:!1},gesture:{enabled:!0}},e=new p(w);e.env.perfadd=!1;e.draw.options.font='small-caps 18px "Lato"';e.draw.options.lineHeight=20;var t={video:document.getElementById("video"),canvas:document.getElementById("canvas"),log:document.getElementById("log"),fps:document.getElementById("status"),perf:document.getElementById("performance")},n={detect:0,draw:0,tensors:0,start:0},o={detectFPS:0,drawFPS:0,frames:0,averageMs:0},i=(...a)=>{t.log.innerText+=a.join(" ")+`
+`,console.log(...a)},r=a=>t.fps.innerText=a,b=a=>t.perf.innerText="tensors:"+e.tf.memory().numTensors+" | performance: "+JSON.stringify(a).replace(/"|{|}/g,"").replace(/,/g," | ");async function h(){r("starting webcam...");let a={audio:!1,video:{facingMode:"user",resizeMode:"none",width:{ideal:document.body.clientWidth},height:{ideal:document.body.clientHeight}}},d=await navigator.mediaDevices.getUserMedia(a),m=new Promise(u=>{t.video.onloadeddata=()=>u(!0)});t.video.srcObject=d,t.video.play(),await m,t.canvas.width=t.video.videoWidth,t.canvas.height=t.video.videoHeight;let s=d.getVideoTracks()[0],f=s.getCapabilities?s.getCapabilities():"",v=s.getSettings?s.getSettings():"",g=s.getConstraints?s.getConstraints():"";i("video:",t.video.videoWidth,t.video.videoHeight,s.label,{stream:d,track:s,settings:v,constraints:g,capabilities:f}),t.canvas.onclick=()=>{t.video.paused?t.video.play():t.video.pause()}}async function c(){if(!t.video.paused){n.start===0&&(n.start=e.now()),await e.detect(t.video);let a=e.tf.memory().numTensors;a-n.tensors!==0&&i("allocated tensors:",a-n.tensors),n.tensors=a,o.detectFPS=Math.round(1e3*1e3/(e.now()-n.detect))/1e3,o.frames++,o.averageMs=Math.round(1e3*(e.now()-n.start)/o.frames)/1e3,o.frames%100===0&&!t.video.paused&&i("performance",{...o,tensors:n.tensors})}n.detect=e.now(),requestAnimationFrame(c)}async function l(){if(!t.video.paused){let d=await e.next(e.result);e.config.filter.flip?await e.draw.canvas(d.canvas,t.canvas):await e.draw.canvas(t.video,t.canvas),await e.draw.all(t.canvas,d),b(d.performance)}let a=e.now();o.drawFPS=Math.round(1e3*1e3/(a-n.draw))/1e3,n.draw=a,r(t.video.paused?"paused":`fps: ${o.detectFPS.toFixed(1).padStart(5," ")} detect | ${o.drawFPS.toFixed(1).padStart(5," ")} draw`),setTimeout(l,30)}async function M(){i("human version:",e.version,"| tfjs version:",e.tf.version["tfjs-core"]),i("platform:",e.env.platform,"| agent:",e.env.agent),r("loading..."),await e.load(),i("backend:",e.tf.getBackend(),"| available:",e.env.backends),i("models stats:",e.getModelStats()),i("models loaded:",Object.values(e.models).filter(a=>a!==null).length),r("initializing..."),await e.warmup(),await h(),await c(),await l()}window.onload=M;
 //# sourceMappingURL=index.js.map
diff --git a/demo/typescript/index.js.map b/demo/typescript/index.js.map
index 3f5a5d0c..f410639d 100644
--- a/demo/typescript/index.js.map
+++ b/demo/typescript/index.js.map
@@ -1,7 +1,7 @@
 {
   "version": 3,
   "sources": ["index.ts"],
-  "sourcesContent": ["/**\n * Human demo for browsers\n * @default Human Library\n * @summary <https://github.com/vladmandic/human>\n * @author <https://github.com/vladmandic>\n * @copyright <https://github.com/vladmandic>\n * @license MIT\n */\n\nimport { Human, Config } from '../../dist/human.esm.js'; // equivalent of @vladmandic/Human\n\nconst humanConfig: Partial<Config> = { // user configuration for human, used to fine-tune behavior\n  // backend: 'wasm' as const,\n  // wasmPath: 'https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@3.18.0/dist/',\n  // cacheSensitivity: 0,\n  async: true,\n  modelBasePath: '../../models',\n  filter: { enabled: true, equalization: false, flip: false },\n  face: { enabled: true, detector: { rotation: false }, mesh: { enabled: true }, attention: { enabled: false }, iris: { enabled: true }, description: { enabled: true }, emotion: { enabled: true } },\n  body: { enabled: true },\n  hand: { enabled: true },\n  object: { enabled: false },\n  gesture: { enabled: true },\n};\n\nconst human = new Human(humanConfig); // create instance of human with overrides from user configuration\n\nhuman.env['perfadd'] = false; // is performance data showing instant or total values\nhuman.draw.options.font = 'small-caps 18px \"Lato\"'; // set font used to draw labels when using draw methods\nhuman.draw.options.lineHeight = 20;\n// human.draw.options.fillPolygons = true;\n\nconst dom = { // grab instances of dom objects so we dont have to look them up later\n  video: document.getElementById('video') as HTMLVideoElement,\n  canvas: document.getElementById('canvas') as HTMLCanvasElement,\n  log: document.getElementById('log') as HTMLPreElement,\n  fps: document.getElementById('status') as HTMLPreElement,\n  perf: document.getElementById('performance') as HTMLDivElement,\n};\nconst timestamp = { detect: 0, draw: 0, tensors: 0 }; // holds information used to calculate performance and possible memory leaks\nconst fps = { detect: 0, draw: 0 }; // holds calculated fps information for both detect and screen refresh\n\nconst log = (...msg) => { // helper method to output messages\n  dom.log.innerText += msg.join(' ') + '\\n';\n  // eslint-disable-next-line no-console\n  console.log(...msg);\n};\nconst status = (msg) => dom.fps.innerText = msg; // print status element\nconst perf = (msg) => dom.perf.innerText = 'tensors:' + human.tf.memory().numTensors + ' | performance: ' + JSON.stringify(msg).replace(/\"|{|}/g, '').replace(/,/g, ' | '); // print performance element\n\nasync function webCam() { // initialize webcam\n  status('starting webcam...');\n  // @ts-ignore resizeMode is not yet defined in tslib\n  const options: MediaStreamConstraints = { audio: false, video: { facingMode: 'user', resizeMode: 'none', width: { ideal: document.body.clientWidth }, height: { ideal: document.body.clientHeight } } };\n  const stream: MediaStream = await navigator.mediaDevices.getUserMedia(options);\n  const ready = new Promise((resolve) => { dom.video.onloadeddata = () => resolve(true); });\n  dom.video.srcObject = stream;\n  dom.video.play();\n  await ready;\n  dom.canvas.width = dom.video.videoWidth;\n  dom.canvas.height = dom.video.videoHeight;\n  const track: MediaStreamTrack = stream.getVideoTracks()[0];\n  const capabilities: MediaTrackCapabilities | string = track.getCapabilities ? track.getCapabilities() : '';\n  const settings: MediaTrackSettings | string = track.getSettings ? track.getSettings() : '';\n  const constraints: MediaTrackConstraints | string = track.getConstraints ? track.getConstraints() : '';\n  log('video:', dom.video.videoWidth, dom.video.videoHeight, track.label, { stream, track, settings, constraints, capabilities });\n  dom.canvas.onclick = () => { // pause when clicked on screen and resume on next click\n    if (dom.video.paused) dom.video.play();\n    else dom.video.pause();\n  };\n}\n\nasync function detectionLoop() { // main detection loop\n  if (!dom.video.paused) {\n    // console.log('profiling data:', await human.profile(dom.video));\n    await human.detect(dom.video); // actual detection; were not capturing output in a local variable as it can also be reached via human.result\n    const tensors = human.tf.memory().numTensors; // check current tensor usage for memory leaks\n    if (tensors - timestamp.tensors !== 0) log('allocated tensors:', tensors - timestamp.tensors); // printed on start and each time there is a tensor leak\n    timestamp.tensors = tensors;\n  }\n  const now = human.now();\n  fps.detect = 1000 / (now - timestamp.detect);\n  timestamp.detect = now;\n  requestAnimationFrame(detectionLoop); // start new frame immediately\n}\n\nasync function drawLoop() { // main screen refresh loop\n  if (!dom.video.paused) {\n    const interpolated = await human.next(human.result); // smoothen result using last-known results\n    if (human.config.filter.flip) await human.draw.canvas(interpolated.canvas as HTMLCanvasElement, dom.canvas); // draw processed image to screen canvas\n    else await human.draw.canvas(dom.video, dom.canvas); // draw original video to screen canvas // better than using procesed image as this loop happens faster than processing loop\n    await human.draw.all(dom.canvas, interpolated); // draw labels, boxes, lines, etc.\n    perf(interpolated.performance); // write performance data\n  }\n  const now = human.now();\n  fps.draw = 1000 / (now - timestamp.draw);\n  timestamp.draw = now;\n  status(dom.video.paused ? 'paused' : `fps: ${fps.detect.toFixed(1).padStart(5, ' ')} detect | ${fps.draw.toFixed(1).padStart(5, ' ')} draw`); // write status\n  // requestAnimationFrame(drawLoop); // refresh at screen refresh rate\n  setTimeout(drawLoop, 30); // use to slow down refresh from max refresh rate to target of 30 fps\n}\n\nasync function main() { // main entry point\n  log('human version:', human.version, '| tfjs version:', human.tf.version['tfjs-core']);\n  log('platform:', human.env.platform, '| agent:', human.env.agent);\n  status('loading...');\n  await human.load(); // preload all models\n  log('backend:', human.tf.getBackend(), '| available:', human.env.backends);\n  log('models stats:', human.getModelStats());\n  log('models loaded:', Object.values(human.models).filter((model) => model !== null).length);\n  status('initializing...');\n  await human.warmup(); // warmup function to initialize backend for future faster detection\n  await webCam(); // start webcam\n  await detectionLoop(); // start detection loop\n  await drawLoop(); // start draw loop\n}\n\nwindow.onload = main;\n"],
-  "mappings": ";;;;;;AASA,OAAS,SAAAA,MAAqB,0BAE9B,IAAMC,EAA+B,CAInC,MAAO,GACP,cAAe,eACf,OAAQ,CAAE,QAAS,GAAM,aAAc,GAAO,KAAM,EAAM,EAC1D,KAAM,CAAE,QAAS,GAAM,SAAU,CAAE,SAAU,EAAM,EAAG,KAAM,CAAE,QAAS,EAAK,EAAG,UAAW,CAAE,QAAS,EAAM,EAAG,KAAM,CAAE,QAAS,EAAK,EAAG,YAAa,CAAE,QAAS,EAAK,EAAG,QAAS,CAAE,QAAS,EAAK,CAAE,EAClM,KAAM,CAAE,QAAS,EAAK,EACtB,KAAM,CAAE,QAAS,EAAK,EACtB,OAAQ,CAAE,QAAS,EAAM,EACzB,QAAS,CAAE,QAAS,EAAK,CAC3B,EAEMC,EAAQ,IAAIF,EAAMC,CAAW,EAEnCC,EAAM,IAAI,QAAa,GACvBA,EAAM,KAAK,QAAQ,KAAO,yBAC1BA,EAAM,KAAK,QAAQ,WAAa,GAGhC,IAAMC,EAAM,CACV,MAAO,SAAS,eAAe,OAAO,EACtC,OAAQ,SAAS,eAAe,QAAQ,EACxC,IAAK,SAAS,eAAe,KAAK,EAClC,IAAK,SAAS,eAAe,QAAQ,EACrC,KAAM,SAAS,eAAe,aAAa,CAC7C,EACMC,EAAY,CAAE,OAAQ,EAAG,KAAM,EAAG,QAAS,CAAE,EAC7CC,EAAM,CAAE,OAAQ,EAAG,KAAM,CAAE,EAE3BC,EAAM,IAAIC,IAAQ,CACtBJ,EAAI,IAAI,WAAaI,EAAI,KAAK,GAAG,EAAI;AAAA,EAErC,QAAQ,IAAI,GAAGA,CAAG,CACpB,EACMC,EAAUD,GAAQJ,EAAI,IAAI,UAAYI,EACtCE,EAAQF,GAAQJ,EAAI,KAAK,UAAY,WAAaD,EAAM,GAAG,OAAO,EAAE,WAAa,mBAAqB,KAAK,UAAUK,CAAG,EAAE,QAAQ,SAAU,EAAE,EAAE,QAAQ,KAAM,KAAK,EAEzK,eAAeG,GAAS,CACtBF,EAAO,oBAAoB,EAE3B,IAAMG,EAAkC,CAAE,MAAO,GAAO,MAAO,CAAE,WAAY,OAAQ,WAAY,OAAQ,MAAO,CAAE,MAAO,SAAS,KAAK,WAAY,EAAG,OAAQ,CAAE,MAAO,SAAS,KAAK,YAAa,CAAE,CAAE,EAChMC,EAAsB,MAAM,UAAU,aAAa,aAAaD,CAAO,EACvEE,EAAQ,IAAI,QAASC,GAAY,CAAEX,EAAI,MAAM,aAAe,IAAMW,EAAQ,EAAI,CAAG,CAAC,EACxFX,EAAI,MAAM,UAAYS,EACtBT,EAAI,MAAM,KAAK,EACf,MAAMU,EACNV,EAAI,OAAO,MAAQA,EAAI,MAAM,WAC7BA,EAAI,OAAO,OAASA,EAAI,MAAM,YAC9B,IAAMY,EAA0BH,EAAO,eAAe,EAAE,GAClDI,EAAgDD,EAAM,gBAAkBA,EAAM,gBAAgB,EAAI,GAClGE,EAAwCF,EAAM,YAAcA,EAAM,YAAY,EAAI,GAClFG,EAA8CH,EAAM,eAAiBA,EAAM,eAAe,EAAI,GACpGT,EAAI,SAAUH,EAAI,MAAM,WAAYA,EAAI,MAAM,YAAaY,EAAM,MAAO,CAAE,OAAAH,EAAQ,MAAAG,EAAO,SAAAE,EAAU,YAAAC,EAAa,aAAAF,CAAa,CAAC,EAC9Hb,EAAI,OAAO,QAAU,IAAM,CACrBA,EAAI,MAAM,OAAQA,EAAI,MAAM,KAAK,EAChCA,EAAI,MAAM,MAAM,CACvB,CACF,CAEA,eAAegB,GAAgB,CAC7B,GAAI,CAAChB,EAAI,MAAM,OAAQ,CAErB,MAAMD,EAAM,OAAOC,EAAI,KAAK,EAC5B,IAAMiB,EAAUlB,EAAM,GAAG,OAAO,EAAE,WAC9BkB,EAAUhB,EAAU,UAAY,GAAGE,EAAI,qBAAsBc,EAAUhB,EAAU,OAAO,EAC5FA,EAAU,QAAUgB,CACtB,CACA,IAAMC,EAAMnB,EAAM,IAAI,EACtBG,EAAI,OAAS,KAAQgB,EAAMjB,EAAU,QACrCA,EAAU,OAASiB,EACnB,sBAAsBF,CAAa,CACrC,CAEA,eAAeG,GAAW,CACxB,GAAI,CAACnB,EAAI,MAAM,OAAQ,CACrB,IAAMoB,EAAe,MAAMrB,EAAM,KAAKA,EAAM,MAAM,EAC9CA,EAAM,OAAO,OAAO,KAAM,MAAMA,EAAM,KAAK,OAAOqB,EAAa,OAA6BpB,EAAI,MAAM,EACrG,MAAMD,EAAM,KAAK,OAAOC,EAAI,MAAOA,EAAI,MAAM,EAClD,MAAMD,EAAM,KAAK,IAAIC,EAAI,OAAQoB,CAAY,EAC7Cd,EAAKc,EAAa,WAAW,CAC/B,CACA,IAAMF,EAAMnB,EAAM,IAAI,EACtBG,EAAI,KAAO,KAAQgB,EAAMjB,EAAU,MACnCA,EAAU,KAAOiB,EACjBb,EAAOL,EAAI,MAAM,OAAS,SAAW,QAAQE,EAAI,OAAO,QAAQ,CAAC,EAAE,SAAS,EAAG,GAAG,cAAcA,EAAI,KAAK,QAAQ,CAAC,EAAE,SAAS,EAAG,GAAG,QAAQ,EAE3I,WAAWiB,EAAU,EAAE,CACzB,CAEA,eAAeE,GAAO,CACpBlB,EAAI,iBAAkBJ,EAAM,QAAS,kBAAmBA,EAAM,GAAG,QAAQ,YAAY,EACrFI,EAAI,YAAaJ,EAAM,IAAI,SAAU,WAAYA,EAAM,IAAI,KAAK,EAChEM,EAAO,YAAY,EACnB,MAAMN,EAAM,KAAK,EACjBI,EAAI,WAAYJ,EAAM,GAAG,WAAW,EAAG,eAAgBA,EAAM,IAAI,QAAQ,EACzEI,EAAI,gBAAiBJ,EAAM,cAAc,CAAC,EAC1CI,EAAI,iBAAkB,OAAO,OAAOJ,EAAM,MAAM,EAAE,OAAQuB,GAAUA,IAAU,IAAI,EAAE,MAAM,EAC1FjB,EAAO,iBAAiB,EACxB,MAAMN,EAAM,OAAO,EACnB,MAAMQ,EAAO,EACb,MAAMS,EAAc,EACpB,MAAMG,EAAS,CACjB,CAEA,OAAO,OAASE",
-  "names": ["Human", "humanConfig", "human", "dom", "timestamp", "fps", "log", "msg", "status", "perf", "webCam", "options", "stream", "ready", "resolve", "track", "capabilities", "settings", "constraints", "detectionLoop", "tensors", "now", "drawLoop", "interpolated", "main", "model"]
+  "sourcesContent": ["/**\n * Human demo for browsers\n * @default Human Library\n * @summary <https://github.com/vladmandic/human>\n * @author <https://github.com/vladmandic>\n * @copyright <https://github.com/vladmandic>\n * @license MIT\n */\n\nimport { Human, Config } from '../../dist/human.esm.js'; // equivalent of @vladmandic/Human\n\nconst humanConfig: Partial<Config> = { // user configuration for human, used to fine-tune behavior\n  // backend: 'wasm' as const,\n  // wasmPath: 'https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@3.18.0/dist/',\n  // cacheSensitivity: 0,\n  async: true,\n  modelBasePath: '../../models',\n  filter: { enabled: true, equalization: false, flip: false },\n  face: { enabled: true, detector: { rotation: false }, mesh: { enabled: true }, attention: { enabled: false }, iris: { enabled: true }, description: { enabled: true }, emotion: { enabled: true } },\n  body: { enabled: true },\n  hand: { enabled: true },\n  object: { enabled: false },\n  gesture: { enabled: true },\n};\n\nconst human = new Human(humanConfig); // create instance of human with overrides from user configuration\n\nhuman.env['perfadd'] = false; // is performance data showing instant or total values\nhuman.draw.options.font = 'small-caps 18px \"Lato\"'; // set font used to draw labels when using draw methods\nhuman.draw.options.lineHeight = 20;\n// human.draw.options.fillPolygons = true;\n\nconst dom = { // grab instances of dom objects so we dont have to look them up later\n  video: document.getElementById('video') as HTMLVideoElement,\n  canvas: document.getElementById('canvas') as HTMLCanvasElement,\n  log: document.getElementById('log') as HTMLPreElement,\n  fps: document.getElementById('status') as HTMLPreElement,\n  perf: document.getElementById('performance') as HTMLDivElement,\n};\nconst timestamp = { detect: 0, draw: 0, tensors: 0, start: 0 }; // holds information used to calculate performance and possible memory leaks\nconst fps = { detectFPS: 0, drawFPS: 0, frames: 0, averageMs: 0 }; // holds calculated fps information for both detect and screen refresh\n\nconst log = (...msg) => { // helper method to output messages\n  dom.log.innerText += msg.join(' ') + '\\n';\n  // eslint-disable-next-line no-console\n  console.log(...msg);\n};\nconst status = (msg) => dom.fps.innerText = msg; // print status element\nconst perf = (msg) => dom.perf.innerText = 'tensors:' + human.tf.memory().numTensors + ' | performance: ' + JSON.stringify(msg).replace(/\"|{|}/g, '').replace(/,/g, ' | '); // print performance element\n\nasync function webCam() { // initialize webcam\n  status('starting webcam...');\n  // @ts-ignore resizeMode is not yet defined in tslib\n  const options: MediaStreamConstraints = { audio: false, video: { facingMode: 'user', resizeMode: 'none', width: { ideal: document.body.clientWidth }, height: { ideal: document.body.clientHeight } } };\n  const stream: MediaStream = await navigator.mediaDevices.getUserMedia(options);\n  const ready = new Promise((resolve) => { dom.video.onloadeddata = () => resolve(true); });\n  dom.video.srcObject = stream;\n  dom.video.play();\n  await ready;\n  dom.canvas.width = dom.video.videoWidth;\n  dom.canvas.height = dom.video.videoHeight;\n  const track: MediaStreamTrack = stream.getVideoTracks()[0];\n  const capabilities: MediaTrackCapabilities | string = track.getCapabilities ? track.getCapabilities() : '';\n  const settings: MediaTrackSettings | string = track.getSettings ? track.getSettings() : '';\n  const constraints: MediaTrackConstraints | string = track.getConstraints ? track.getConstraints() : '';\n  log('video:', dom.video.videoWidth, dom.video.videoHeight, track.label, { stream, track, settings, constraints, capabilities });\n  dom.canvas.onclick = () => { // pause when clicked on screen and resume on next click\n    if (dom.video.paused) dom.video.play();\n    else dom.video.pause();\n  };\n}\n\nasync function detectionLoop() { // main detection loop\n  if (!dom.video.paused) {\n    if (timestamp.start === 0) timestamp.start = human.now();\n    // log('profiling data:', await human.profile(dom.video));\n    await human.detect(dom.video); // actual detection; were not capturing output in a local variable as it can also be reached via human.result\n    const tensors = human.tf.memory().numTensors; // check current tensor usage for memory leaks\n    if (tensors - timestamp.tensors !== 0) log('allocated tensors:', tensors - timestamp.tensors); // printed on start and each time there is a tensor leak\n    timestamp.tensors = tensors;\n    fps.detectFPS = Math.round(1000 * 1000 / (human.now() - timestamp.detect)) / 1000;\n    fps.frames++;\n    fps.averageMs = Math.round(1000 * (human.now() - timestamp.start) / fps.frames) / 1000;\n    if (fps.frames % 100 === 0 && !dom.video.paused) log('performance', { ...fps, tensors: timestamp.tensors });\n  }\n  timestamp.detect = human.now();\n  requestAnimationFrame(detectionLoop); // start new frame immediately\n}\n\nasync function drawLoop() { // main screen refresh loop\n  if (!dom.video.paused) {\n    const interpolated = await human.next(human.result); // smoothen result using last-known results\n    if (human.config.filter.flip) await human.draw.canvas(interpolated.canvas as HTMLCanvasElement, dom.canvas); // draw processed image to screen canvas\n    else await human.draw.canvas(dom.video, dom.canvas); // draw original video to screen canvas // better than using procesed image as this loop happens faster than processing loop\n    await human.draw.all(dom.canvas, interpolated); // draw labels, boxes, lines, etc.\n    perf(interpolated.performance); // write performance data\n  }\n  const now = human.now();\n  fps.drawFPS = Math.round(1000 * 1000 / (now - timestamp.draw)) / 1000;\n  timestamp.draw = now;\n  status(dom.video.paused ? 'paused' : `fps: ${fps.detectFPS.toFixed(1).padStart(5, ' ')} detect | ${fps.drawFPS.toFixed(1).padStart(5, ' ')} draw`); // write status\n  // requestAnimationFrame(drawLoop); // refresh at screen refresh rate\n  setTimeout(drawLoop, 30); // use to slow down refresh from max refresh rate to target of 30 fps\n}\n\nasync function main() { // main entry point\n  log('human version:', human.version, '| tfjs version:', human.tf.version['tfjs-core']);\n  log('platform:', human.env.platform, '| agent:', human.env.agent);\n  status('loading...');\n  await human.load(); // preload all models\n  log('backend:', human.tf.getBackend(), '| available:', human.env.backends);\n  log('models stats:', human.getModelStats());\n  log('models loaded:', Object.values(human.models).filter((model) => model !== null).length);\n  status('initializing...');\n  await human.warmup(); // warmup function to initialize backend for future faster detection\n  await webCam(); // start webcam\n  await detectionLoop(); // start detection loop\n  await drawLoop(); // start draw loop\n}\n\nwindow.onload = main;\n"],
+  "mappings": ";;;;;;AASA,OAAS,SAAAA,MAAqB,0BAE9B,IAAMC,EAA+B,CAInC,MAAO,GACP,cAAe,eACf,OAAQ,CAAE,QAAS,GAAM,aAAc,GAAO,KAAM,EAAM,EAC1D,KAAM,CAAE,QAAS,GAAM,SAAU,CAAE,SAAU,EAAM,EAAG,KAAM,CAAE,QAAS,EAAK,EAAG,UAAW,CAAE,QAAS,EAAM,EAAG,KAAM,CAAE,QAAS,EAAK,EAAG,YAAa,CAAE,QAAS,EAAK,EAAG,QAAS,CAAE,QAAS,EAAK,CAAE,EAClM,KAAM,CAAE,QAAS,EAAK,EACtB,KAAM,CAAE,QAAS,EAAK,EACtB,OAAQ,CAAE,QAAS,EAAM,EACzB,QAAS,CAAE,QAAS,EAAK,CAC3B,EAEMC,EAAQ,IAAIF,EAAMC,CAAW,EAEnCC,EAAM,IAAI,QAAa,GACvBA,EAAM,KAAK,QAAQ,KAAO,yBAC1BA,EAAM,KAAK,QAAQ,WAAa,GAGhC,IAAMC,EAAM,CACV,MAAO,SAAS,eAAe,OAAO,EACtC,OAAQ,SAAS,eAAe,QAAQ,EACxC,IAAK,SAAS,eAAe,KAAK,EAClC,IAAK,SAAS,eAAe,QAAQ,EACrC,KAAM,SAAS,eAAe,aAAa,CAC7C,EACMC,EAAY,CAAE,OAAQ,EAAG,KAAM,EAAG,QAAS,EAAG,MAAO,CAAE,EACvDC,EAAM,CAAE,UAAW,EAAG,QAAS,EAAG,OAAQ,EAAG,UAAW,CAAE,EAE1DC,EAAM,IAAIC,IAAQ,CACtBJ,EAAI,IAAI,WAAaI,EAAI,KAAK,GAAG,EAAI;AAAA,EAErC,QAAQ,IAAI,GAAGA,CAAG,CACpB,EACMC,EAAUD,GAAQJ,EAAI,IAAI,UAAYI,EACtCE,EAAQF,GAAQJ,EAAI,KAAK,UAAY,WAAaD,EAAM,GAAG,OAAO,EAAE,WAAa,mBAAqB,KAAK,UAAUK,CAAG,EAAE,QAAQ,SAAU,EAAE,EAAE,QAAQ,KAAM,KAAK,EAEzK,eAAeG,GAAS,CACtBF,EAAO,oBAAoB,EAE3B,IAAMG,EAAkC,CAAE,MAAO,GAAO,MAAO,CAAE,WAAY,OAAQ,WAAY,OAAQ,MAAO,CAAE,MAAO,SAAS,KAAK,WAAY,EAAG,OAAQ,CAAE,MAAO,SAAS,KAAK,YAAa,CAAE,CAAE,EAChMC,EAAsB,MAAM,UAAU,aAAa,aAAaD,CAAO,EACvEE,EAAQ,IAAI,QAASC,GAAY,CAAEX,EAAI,MAAM,aAAe,IAAMW,EAAQ,EAAI,CAAG,CAAC,EACxFX,EAAI,MAAM,UAAYS,EACtBT,EAAI,MAAM,KAAK,EACf,MAAMU,EACNV,EAAI,OAAO,MAAQA,EAAI,MAAM,WAC7BA,EAAI,OAAO,OAASA,EAAI,MAAM,YAC9B,IAAMY,EAA0BH,EAAO,eAAe,EAAE,GAClDI,EAAgDD,EAAM,gBAAkBA,EAAM,gBAAgB,EAAI,GAClGE,EAAwCF,EAAM,YAAcA,EAAM,YAAY,EAAI,GAClFG,EAA8CH,EAAM,eAAiBA,EAAM,eAAe,EAAI,GACpGT,EAAI,SAAUH,EAAI,MAAM,WAAYA,EAAI,MAAM,YAAaY,EAAM,MAAO,CAAE,OAAAH,EAAQ,MAAAG,EAAO,SAAAE,EAAU,YAAAC,EAAa,aAAAF,CAAa,CAAC,EAC9Hb,EAAI,OAAO,QAAU,IAAM,CACrBA,EAAI,MAAM,OAAQA,EAAI,MAAM,KAAK,EAChCA,EAAI,MAAM,MAAM,CACvB,CACF,CAEA,eAAegB,GAAgB,CAC7B,GAAI,CAAChB,EAAI,MAAM,OAAQ,CACjBC,EAAU,QAAU,IAAGA,EAAU,MAAQF,EAAM,IAAI,GAEvD,MAAMA,EAAM,OAAOC,EAAI,KAAK,EAC5B,IAAMiB,EAAUlB,EAAM,GAAG,OAAO,EAAE,WAC9BkB,EAAUhB,EAAU,UAAY,GAAGE,EAAI,qBAAsBc,EAAUhB,EAAU,OAAO,EAC5FA,EAAU,QAAUgB,EACpBf,EAAI,UAAY,KAAK,MAAM,IAAO,KAAQH,EAAM,IAAI,EAAIE,EAAU,OAAO,EAAI,IAC7EC,EAAI,SACJA,EAAI,UAAY,KAAK,MAAM,KAAQH,EAAM,IAAI,EAAIE,EAAU,OAASC,EAAI,MAAM,EAAI,IAC9EA,EAAI,OAAS,MAAQ,GAAK,CAACF,EAAI,MAAM,QAAQG,EAAI,cAAe,CAAE,GAAGD,EAAK,QAASD,EAAU,OAAQ,CAAC,CAC5G,CACAA,EAAU,OAASF,EAAM,IAAI,EAC7B,sBAAsBiB,CAAa,CACrC,CAEA,eAAeE,GAAW,CACxB,GAAI,CAAClB,EAAI,MAAM,OAAQ,CACrB,IAAMmB,EAAe,MAAMpB,EAAM,KAAKA,EAAM,MAAM,EAC9CA,EAAM,OAAO,OAAO,KAAM,MAAMA,EAAM,KAAK,OAAOoB,EAAa,OAA6BnB,EAAI,MAAM,EACrG,MAAMD,EAAM,KAAK,OAAOC,EAAI,MAAOA,EAAI,MAAM,EAClD,MAAMD,EAAM,KAAK,IAAIC,EAAI,OAAQmB,CAAY,EAC7Cb,EAAKa,EAAa,WAAW,CAC/B,CACA,IAAMC,EAAMrB,EAAM,IAAI,EACtBG,EAAI,QAAU,KAAK,MAAM,IAAO,KAAQkB,EAAMnB,EAAU,KAAK,EAAI,IACjEA,EAAU,KAAOmB,EACjBf,EAAOL,EAAI,MAAM,OAAS,SAAW,QAAQE,EAAI,UAAU,QAAQ,CAAC,EAAE,SAAS,EAAG,GAAG,cAAcA,EAAI,QAAQ,QAAQ,CAAC,EAAE,SAAS,EAAG,GAAG,QAAQ,EAEjJ,WAAWgB,EAAU,EAAE,CACzB,CAEA,eAAeG,GAAO,CACpBlB,EAAI,iBAAkBJ,EAAM,QAAS,kBAAmBA,EAAM,GAAG,QAAQ,YAAY,EACrFI,EAAI,YAAaJ,EAAM,IAAI,SAAU,WAAYA,EAAM,IAAI,KAAK,EAChEM,EAAO,YAAY,EACnB,MAAMN,EAAM,KAAK,EACjBI,EAAI,WAAYJ,EAAM,GAAG,WAAW,EAAG,eAAgBA,EAAM,IAAI,QAAQ,EACzEI,EAAI,gBAAiBJ,EAAM,cAAc,CAAC,EAC1CI,EAAI,iBAAkB,OAAO,OAAOJ,EAAM,MAAM,EAAE,OAAQuB,GAAUA,IAAU,IAAI,EAAE,MAAM,EAC1FjB,EAAO,iBAAiB,EACxB,MAAMN,EAAM,OAAO,EACnB,MAAMQ,EAAO,EACb,MAAMS,EAAc,EACpB,MAAME,EAAS,CACjB,CAEA,OAAO,OAASG",
+  "names": ["Human", "humanConfig", "human", "dom", "timestamp", "fps", "log", "msg", "status", "perf", "webCam", "options", "stream", "ready", "resolve", "track", "capabilities", "settings", "constraints", "detectionLoop", "tensors", "drawLoop", "interpolated", "now", "main", "model"]
 }
diff --git a/demo/typescript/index.ts b/demo/typescript/index.ts
index ca7f28c8..4107cd10 100644
--- a/demo/typescript/index.ts
+++ b/demo/typescript/index.ts
@@ -37,8 +37,8 @@ const dom = { // grab instances of dom objects so we dont have to look them up l
   fps: document.getElementById('status') as HTMLPreElement,
   perf: document.getElementById('performance') as HTMLDivElement,
 };
-const timestamp = { detect: 0, draw: 0, tensors: 0 }; // holds information used to calculate performance and possible memory leaks
-const fps = { detect: 0, draw: 0 }; // holds calculated fps information for both detect and screen refresh
+const timestamp = { detect: 0, draw: 0, tensors: 0, start: 0 }; // holds information used to calculate performance and possible memory leaks
+const fps = { detectFPS: 0, drawFPS: 0, frames: 0, averageMs: 0 }; // holds calculated fps information for both detect and screen refresh
 
 const log = (...msg) => { // helper method to output messages
   dom.log.innerText += msg.join(' ') + '\n';
@@ -72,15 +72,18 @@ async function webCam() { // initialize webcam
 
 async function detectionLoop() { // main detection loop
   if (!dom.video.paused) {
-    // console.log('profiling data:', await human.profile(dom.video));
+    if (timestamp.start === 0) timestamp.start = human.now();
+    // log('profiling data:', await human.profile(dom.video));
     await human.detect(dom.video); // actual detection; were not capturing output in a local variable as it can also be reached via human.result
     const tensors = human.tf.memory().numTensors; // check current tensor usage for memory leaks
     if (tensors - timestamp.tensors !== 0) log('allocated tensors:', tensors - timestamp.tensors); // printed on start and each time there is a tensor leak
     timestamp.tensors = tensors;
+    fps.detectFPS = Math.round(1000 * 1000 / (human.now() - timestamp.detect)) / 1000;
+    fps.frames++;
+    fps.averageMs = Math.round(1000 * (human.now() - timestamp.start) / fps.frames) / 1000;
+    if (fps.frames % 100 === 0 && !dom.video.paused) log('performance', { ...fps, tensors: timestamp.tensors });
   }
-  const now = human.now();
-  fps.detect = 1000 / (now - timestamp.detect);
-  timestamp.detect = now;
+  timestamp.detect = human.now();
   requestAnimationFrame(detectionLoop); // start new frame immediately
 }
 
@@ -93,9 +96,9 @@ async function drawLoop() { // main screen refresh loop
     perf(interpolated.performance); // write performance data
   }
   const now = human.now();
-  fps.draw = 1000 / (now - timestamp.draw);
+  fps.drawFPS = Math.round(1000 * 1000 / (now - timestamp.draw)) / 1000;
   timestamp.draw = now;
-  status(dom.video.paused ? 'paused' : `fps: ${fps.detect.toFixed(1).padStart(5, ' ')} detect | ${fps.draw.toFixed(1).padStart(5, ' ')} draw`); // write status
+  status(dom.video.paused ? 'paused' : `fps: ${fps.detectFPS.toFixed(1).padStart(5, ' ')} detect | ${fps.drawFPS.toFixed(1).padStart(5, ' ')} draw`); // write status
   // requestAnimationFrame(drawLoop); // refresh at screen refresh rate
   setTimeout(drawLoop, 30); // use to slow down refresh from max refresh rate to target of 30 fps
 }
diff --git a/dist/human.d.ts b/dist/human.d.ts
index 4f1e9723..925302ef 100644
--- a/dist/human.d.ts
+++ b/dist/human.d.ts
@@ -1330,7 +1330,11 @@ declare class Human {
      * - result object will contain total exeuction time information for top-20 kernels
      * - actual detection object can be accessed via `human.result`
      */
-    profile(input: Input, userConfig?: Partial<Config>): Promise<Record<string, number>>;
+    profile(input: Input, userConfig?: Partial<Config>): Promise<Array<{
+        kernel: string;
+        time: number;
+        perc: number;
+    }>>;
     /** Main detection method
      * - Analyze configuration: {@link Config}
      * - Pre-process input: {@link Input}
diff --git a/dist/human.esm-nobundle.d.ts b/dist/human.esm-nobundle.d.ts
index 4f1e9723..925302ef 100644
--- a/dist/human.esm-nobundle.d.ts
+++ b/dist/human.esm-nobundle.d.ts
@@ -1330,7 +1330,11 @@ declare class Human {
      * - result object will contain total exeuction time information for top-20 kernels
      * - actual detection object can be accessed via `human.result`
      */
-    profile(input: Input, userConfig?: Partial<Config>): Promise<Record<string, number>>;
+    profile(input: Input, userConfig?: Partial<Config>): Promise<Array<{
+        kernel: string;
+        time: number;
+        perc: number;
+    }>>;
     /** Main detection method
      * - Analyze configuration: {@link Config}
      * - Pre-process input: {@link Input}
diff --git a/dist/human.esm-nobundle.js b/dist/human.esm-nobundle.js
index a791ccf9..8c95fdd4 100644
--- a/dist/human.esm-nobundle.js
+++ b/dist/human.esm-nobundle.js
@@ -4,7 +4,7 @@
   author: <https://github.com/vladmandic>'
 */
 
-var J2=Object.defineProperty;var Po=Object.getOwnPropertyDescriptor;var Ro=Object.getOwnPropertyNames;var vo=Object.prototype.hasOwnProperty;var To=(e,t,o)=>t in e?J2(e,t,{enumerable:!0,configurable:!0,writable:!0,value:o}):e[t]=o;var U0=(e,t)=>{for(var o in t)J2(e,o,{get:t[o],enumerable:!0})},I1=(e,t,o,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of Ro(t))!vo.call(e,r)&&r!==o&&J2(e,r,{get:()=>t[r],enumerable:!(n=Po(t,r))||n.enumerable});return e},q=(e,t,o)=>(I1(e,t,"default"),o&&I1(o,t,"default"));var w=(e,t,o)=>(To(e,typeof t!="symbol"?t+"":t,o),o),N1=(e,t,o)=>{if(!t.has(e))throw TypeError("Cannot "+o)};var Xe=(e,t,o)=>(N1(e,t,"read from private field"),o?o.call(e):t.get(e)),qe=(e,t,o)=>{if(t.has(e))throw TypeError("Cannot add the same private member more than once");t instanceof WeakSet?t.add(e):t.set(e,o)},Ue=(e,t,o,n)=>(N1(e,t,"write to private field"),n?n.call(e,o):t.set(e,o),o);function u(...e){let t=new Date,o=`${t.getHours().toString().padStart(2,"0")}:${t.getMinutes().toString().padStart(2,"0")}:${t.getSeconds().toString().padStart(2,"0")}.${t.getMilliseconds().toString().padStart(3,"0")}`;e&&console.log(o,"Human:",...e)}function O1(e,t){let o=e.endsWith("/")?"":"/",r=t.startsWith(".")||t.startsWith("/")||t.startsWith("http:")||t.startsWith("https:")||t.startsWith("file:")?`${t}`:`${e}${o}${t}`;if(!r.toLocaleLowerCase().includes(".json"))throw new Error(`modelpath error: expecting json file: ${r}`);return r}var b=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function Q2(e,t,o="config",n=[]){for(let r of Object.keys(t))if(typeof t[r]=="object")Q2(e[r],t[r],r,n);else{let s=e&&typeof e[r]!="undefined";s||n.push({reason:"unknown property",where:`${o}.${r} = ${t[r]}`});let a=e&&typeof e[r]==typeof t[r];s&&!a&&n.push({reason:"property type mismatch",where:`${o}.${r} = ${t[r]}`,expected:typeof e[r]})}return t.debug&&o==="config"&&n.length>0&&u("invalid configuration",n),n}function J(...e){let t=o=>o&&typeof o=="object";return e.reduce((o,n)=>(Object.keys(n||{}).forEach(r=>{let s=o[r],a=n[r];Array.isArray(s)&&Array.isArray(a)?o[r]=s.concat(...a):t(s)&&t(a)?o[r]=J(s,a):o[r]=a}),o),{})}var se={backend:"",modelBasePath:"",cacheModels:!0,wasmPath:"",wasmPlatformFetch:!1,debug:!1,async:!0,warmup:"full",cacheSensitivity:.7,skipAllowed:!1,deallocate:!1,filter:{enabled:!0,equalization:!1,width:0,height:0,flip:!1,return:!0,brightness:0,contrast:0,sharpness:0,blur:0,saturation:0,hue:0,negative:!1,sepia:!1,vintage:!1,kodachrome:!1,technicolor:!1,polaroid:!1,pixelate:0},gesture:{enabled:!0},face:{enabled:!0,detector:{modelPath:"blazeface.json",rotation:!0,maxDetected:1,skipFrames:99,skipTime:2500,minConfidence:.2,iouThreshold:.1,mask:!1,return:!1},mesh:{enabled:!0,modelPath:"facemesh.json",keepInvalid:!1},attention:{enabled:!1,modelPath:"facemesh-attention.json"},iris:{enabled:!0,modelPath:"iris.json"},emotion:{enabled:!0,minConfidence:.1,skipFrames:99,skipTime:1500,modelPath:"emotion.json"},description:{enabled:!0,modelPath:"faceres.json",skipFrames:99,skipTime:3e3,minConfidence:.1},antispoof:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"antispoof.json"},liveness:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"liveness.json"}},body:{enabled:!0,modelPath:"movenet-lightning.json",maxDetected:-1,minConfidence:.3,skipFrames:1,skipTime:200},hand:{enabled:!0,rotation:!0,skipFrames:99,skipTime:1e3,minConfidence:.5,iouThreshold:.2,maxDetected:-1,landmarks:!0,detector:{modelPath:"handtrack.json"},skeleton:{modelPath:"handlandmark-full.json"}},object:{enabled:!1,modelPath:"mb3-centernet.json",minConfidence:.2,iouThreshold:.4,maxDetected:10,skipFrames:99,skipTime:2e3},segmentation:{enabled:!1,modelPath:"selfie.json",blur:8}};var A={};U0(A,{GraphModel:()=>_2,Tensor:()=>ge,version:()=>Ye});q(A,SA);q(A,CA);import*as SA from"@tensorflow/tfjs/dist/index.js";import*as CA from"@tensorflow/tfjs-backend-webgl/dist/index.js";import{Tensor as ge}from"@tensorflow/tfjs/dist/index.js";import{GraphModel as _2}from"@tensorflow/tfjs-converter/dist/index";var wo="3.19.0",ko="3.19.0",Eo="3.19.0",zo="3.19.0",So="3.19.0",Co="3.19.0",jo="3.19.0",Ye={tfjs:wo,"tfjs-core":ko,"tfjs-data":Eo,"tfjs-layers":zo,"tfjs-converter":So,"tfjs-backend-webgl":Co,"tfjs-backend-wasm":jo};var L1=`
+var J2=Object.defineProperty;var Po=Object.getOwnPropertyDescriptor;var Ro=Object.getOwnPropertyNames;var vo=Object.prototype.hasOwnProperty;var To=(e,t,o)=>t in e?J2(e,t,{enumerable:!0,configurable:!0,writable:!0,value:o}):e[t]=o;var U0=(e,t)=>{for(var o in t)J2(e,o,{get:t[o],enumerable:!0})},j1=(e,t,o,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of Ro(t))!vo.call(e,r)&&r!==o&&J2(e,r,{get:()=>t[r],enumerable:!(n=Po(t,r))||n.enumerable});return e},q=(e,t,o)=>(j1(e,t,"default"),o&&j1(o,t,"default"));var w=(e,t,o)=>(To(e,typeof t!="symbol"?t+"":t,o),o),N1=(e,t,o)=>{if(!t.has(e))throw TypeError("Cannot "+o)};var Xe=(e,t,o)=>(N1(e,t,"read from private field"),o?o.call(e):t.get(e)),qe=(e,t,o)=>{if(t.has(e))throw TypeError("Cannot add the same private member more than once");t instanceof WeakSet?t.add(e):t.set(e,o)},Ue=(e,t,o,n)=>(N1(e,t,"write to private field"),n?n.call(e,o):t.set(e,o),o);function u(...e){let t=new Date,o=`${t.getHours().toString().padStart(2,"0")}:${t.getMinutes().toString().padStart(2,"0")}:${t.getSeconds().toString().padStart(2,"0")}.${t.getMilliseconds().toString().padStart(3,"0")}`;e&&console.log(o,"Human:",...e)}function O1(e,t){let o=e.endsWith("/")?"":"/",r=t.startsWith(".")||t.startsWith("/")||t.startsWith("http:")||t.startsWith("https:")||t.startsWith("file:")?`${t}`:`${e}${o}${t}`;if(!r.toLocaleLowerCase().includes(".json"))throw new Error(`modelpath error: expecting json file: ${r}`);return r}var b=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function Q2(e,t,o="config",n=[]){for(let r of Object.keys(t))if(typeof t[r]=="object")Q2(e[r],t[r],r,n);else{let s=e&&typeof e[r]!="undefined";s||n.push({reason:"unknown property",where:`${o}.${r} = ${t[r]}`});let a=e&&typeof e[r]==typeof t[r];s&&!a&&n.push({reason:"property type mismatch",where:`${o}.${r} = ${t[r]}`,expected:typeof e[r]})}return t.debug&&o==="config"&&n.length>0&&u("invalid configuration",n),n}function J(...e){let t=o=>o&&typeof o=="object";return e.reduce((o,n)=>(Object.keys(n||{}).forEach(r=>{let s=o[r],a=n[r];Array.isArray(s)&&Array.isArray(a)?o[r]=s.concat(...a):t(s)&&t(a)?o[r]=J(s,a):o[r]=a}),o),{})}var se={backend:"",modelBasePath:"",cacheModels:!0,wasmPath:"",wasmPlatformFetch:!1,debug:!1,async:!0,warmup:"full",cacheSensitivity:.7,skipAllowed:!1,deallocate:!1,filter:{enabled:!0,equalization:!1,width:0,height:0,flip:!1,return:!0,brightness:0,contrast:0,sharpness:0,blur:0,saturation:0,hue:0,negative:!1,sepia:!1,vintage:!1,kodachrome:!1,technicolor:!1,polaroid:!1,pixelate:0},gesture:{enabled:!0},face:{enabled:!0,detector:{modelPath:"blazeface.json",rotation:!0,maxDetected:1,skipFrames:99,skipTime:2500,minConfidence:.2,iouThreshold:.1,mask:!1,return:!1},mesh:{enabled:!0,modelPath:"facemesh.json",keepInvalid:!1},attention:{enabled:!1,modelPath:"facemesh-attention.json"},iris:{enabled:!0,modelPath:"iris.json"},emotion:{enabled:!0,minConfidence:.1,skipFrames:99,skipTime:1500,modelPath:"emotion.json"},description:{enabled:!0,modelPath:"faceres.json",skipFrames:99,skipTime:3e3,minConfidence:.1},antispoof:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"antispoof.json"},liveness:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"liveness.json"}},body:{enabled:!0,modelPath:"movenet-lightning.json",maxDetected:-1,minConfidence:.3,skipFrames:1,skipTime:200},hand:{enabled:!0,rotation:!0,skipFrames:99,skipTime:1e3,minConfidence:.5,iouThreshold:.2,maxDetected:-1,landmarks:!0,detector:{modelPath:"handtrack.json"},skeleton:{modelPath:"handlandmark-full.json"}},object:{enabled:!1,modelPath:"mb3-centernet.json",minConfidence:.2,iouThreshold:.4,maxDetected:10,skipFrames:99,skipTime:2e3},segmentation:{enabled:!1,modelPath:"selfie.json",blur:8}};var A={};U0(A,{GraphModel:()=>_2,Tensor:()=>ge,version:()=>Ye});q(A,SA);q(A,CA);import*as SA from"@tensorflow/tfjs/dist/index.js";import*as CA from"@tensorflow/tfjs-backend-webgl/dist/index.js";import{Tensor as ge}from"@tensorflow/tfjs/dist/index.js";import{GraphModel as _2}from"@tensorflow/tfjs-converter/dist/index";var wo="3.19.0",ko="3.19.0",Eo="3.19.0",zo="3.19.0",So="3.19.0",Co="3.19.0",Io="3.19.0",Ye={tfjs:wo,"tfjs-core":ko,"tfjs-data":Eo,"tfjs-layers":zo,"tfjs-converter":So,"tfjs-backend-webgl":Co,"tfjs-backend-wasm":Io};var L1=`
   precision highp float;
   attribute vec2 pos;
   attribute vec2 uv;
@@ -96,7 +96,7 @@ var J2=Object.defineProperty;var Po=Object.getOwnPropertyDescriptor;var Ro=Objec
     c31 * m[6] + c32 * m[7] + c33 * m[8];
     gl_FragColor.a = c22.a;
   }
-`;var $2=(e,t,o)=>{let n=new RegExp("\\b"+t+" \\w+ (\\w+)","ig");e.replace(n,(r,s)=>(o[s]=0,r))},e5=class{constructor(t,o,n){w(this,"uniform",{});w(this,"attribute",{});w(this,"gl");w(this,"id");w(this,"compile",(t,o)=>{let n=this.gl.createShader(o);return n?(this.gl.shaderSource(n,t),this.gl.compileShader(n),this.gl.getShaderParameter(n,this.gl.COMPILE_STATUS)?n:(u(`filter: gl compile failed: ${this.gl.getShaderInfoLog(n)}`),null)):(u("filter: could not create shader"),null)});this.gl=t;let r=this.compile(o,this.gl.VERTEX_SHADER),s=this.compile(n,this.gl.FRAGMENT_SHADER);if(this.id=this.gl.createProgram(),!(!r||!s)){if(!this.id){u("filter: could not create webgl program");return}if(this.gl.attachShader(this.id,r),this.gl.attachShader(this.id,s),this.gl.linkProgram(this.id),!this.gl.getProgramParameter(this.id,this.gl.LINK_STATUS)){u(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);return}this.gl.useProgram(this.id),$2(o,"attribute",this.attribute);for(let a in this.attribute)this.attribute[a]=this.gl.getAttribLocation(this.id,a);$2(o,"uniform",this.uniform),$2(n,"uniform",this.uniform);for(let a in this.uniform)this.uniform[a]=this.gl.getUniformLocation(this.id,a)}}};function V1(){let e=0,t=null,o=!1,n=-1,r=[null,null],s=[],a=null,i=null,l=y0(100,100),c={},d={INTERMEDIATE:1},y=l.getContext("webgl");if(!y){u("filter: cannot get webgl context");return}this.gl=y;function x(g,f){if(!(g===l.width&&f===l.height)){if(l.width=g,l.height=f,!a){let P=new Float32Array([-1,-1,0,1,1,-1,1,1,-1,1,0,0,-1,1,0,0,1,-1,1,1,1,1,1,0]);a=y.createBuffer(),y.bindBuffer(y.ARRAY_BUFFER,a),y.bufferData(y.ARRAY_BUFFER,P,y.STATIC_DRAW),y.pixelStorei(y.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}y.viewport(0,0,l.width,l.height),r=[null,null]}}function m(g,f){let P=y.createFramebuffer();y.bindFramebuffer(y.FRAMEBUFFER,P);let C=y.createRenderbuffer();y.bindRenderbuffer(y.RENDERBUFFER,C);let k=y.createTexture();return y.bindTexture(y.TEXTURE_2D,k),y.texImage2D(y.TEXTURE_2D,0,y.RGBA,g,f,0,y.RGBA,y.UNSIGNED_BYTE,null),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_MAG_FILTER,y.LINEAR),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_MIN_FILTER,y.LINEAR),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_WRAP_S,y.CLAMP_TO_EDGE),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_WRAP_T,y.CLAMP_TO_EDGE),y.framebufferTexture2D(y.FRAMEBUFFER,y.COLOR_ATTACHMENT0,y.TEXTURE_2D,k,0),y.bindTexture(y.TEXTURE_2D,null),y.bindFramebuffer(y.FRAMEBUFFER,null),{fbo:P,texture:k}}function h(g){return r[g]=r[g]||m(l.width,l.height),r[g]}function p(g=0){if(!i)return;let f=null,P=null,C=!1;e===0?f=t:f=h(n).texture||null,e++,o&&!(g&d.INTERMEDIATE)?(P=null,C=e%2===0):(n=(n+1)%2,P=h(n).fbo||null),y.bindTexture(y.TEXTURE_2D,f),y.bindFramebuffer(y.FRAMEBUFFER,P),y.uniform1f(i.uniform.flipY,C?-1:1),y.drawArrays(y.TRIANGLES,0,6)}function R(g){if(c[g])return i=c[g],y.useProgram((i?i.id:null)||null),i;if(i=new e5(y,L1,g),!i)return u("filter: could not get webgl program"),null;let f=Float32Array.BYTES_PER_ELEMENT,P=4*f;return y.enableVertexAttribArray(i.attribute.pos),y.vertexAttribPointer(i.attribute.pos,2,y.FLOAT,!1,P,0*f),y.enableVertexAttribArray(i.attribute.uv),y.vertexAttribPointer(i.attribute.uv,2,y.FLOAT,!1,P,2*f),c[g]=i,i}let M={colorMatrix:g=>{let f=new Float32Array(g);f[4]/=255,f[9]/=255,f[14]/=255,f[19]/=255;let P=f[18]===1&&f[3]===0&&f[8]===0&&f[13]===0&&f[15]===0&&f[16]===0&&f[17]===0&&f[19]===0?F1:W1,C=R(P);!C||(y.uniform1fv(C.uniform.m,f),p())},brightness:g=>{let f=(g||0)+1;M.colorMatrix([f,0,0,0,0,0,f,0,0,0,0,0,f,0,0,0,0,0,1,0])},saturation:g=>{let f=(g||0)*2/3+1,P=(f-1)*-.5;M.colorMatrix([f,P,P,0,0,P,f,P,0,0,P,P,f,0,0,0,0,0,1,0])},desaturate:()=>{M.saturation(-1)},contrast:g=>{let f=(g||0)+1,P=-128*(f-1);M.colorMatrix([f,0,0,0,P,0,f,0,0,P,0,0,f,0,P,0,0,0,1,0])},negative:()=>{M.contrast(-2)},hue:g=>{g=(g||0)/180*Math.PI;let f=Math.cos(g),P=Math.sin(g),C=.213,k=.715,I=.072;M.colorMatrix([C+f*(1-C)+P*-C,k+f*-k+P*-k,I+f*-I+P*(1-I),0,0,C+f*-C+P*.143,k+f*(1-k)+P*.14,I+f*-I+P*-.283,0,0,C+f*-C+P*-(1-C),k+f*-k+P*k,I+f*(1-I)+P*I,0,0,0,0,0,1,0])},desaturateLuminance:()=>{M.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},sepia:()=>{M.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},brownie:()=>{M.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},vintagePinhole:()=>{M.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},kodachrome:()=>{M.colorMatrix([1.1285582396593525,-.3967382283601348,-.03992559172921793,0,63.72958762196502,-.16404339962244616,1.0835251566291304,-.05498805115633132,0,24.732407896706203,-.16786010706155763,-.5603416277695248,1.6014850761964943,0,35.62982807460946,0,0,0,1,0])},technicolor:()=>{M.colorMatrix([1.9125277891456083,-.8545344976951645,-.09155508482755585,0,11.793603434377337,-.3087833385928097,1.7658908555458428,-.10601743074722245,0,-70.35205161461398,-.231103377548616,-.7501899197440212,1.847597816108189,0,30.950940869491138,0,0,0,1,0])},polaroid:()=>{M.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},shiftToBGR:()=>{M.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},convolution:g=>{let f=new Float32Array(g),P=1/l.width,C=1/l.height,k=R(H1);!k||(y.uniform1fv(k.uniform.m,f),y.uniform2f(k.uniform.px,P,C),p())},detectEdges:()=>{M.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},sobelX:()=>{M.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},sobelY:()=>{M.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},sharpen:g=>{let f=g||1;M.convolution.call(this,[0,-1*f,0,-1*f,1+4*f,-1*f,0,-1*f,0])},emboss:g=>{let f=g||1;M.convolution.call(this,[-2*f,-1*f,0,-1*f,1,1*f,0,1*f,2*f])},blur:g=>{let f=g/7/l.width,P=g/7/l.height,C=R(B1);!C||(y.uniform2f(C.uniform.px,0,P),p(d.INTERMEDIATE),y.uniform2f(C.uniform.px,f,0),p())},pixelate:g=>{let f=g/l.width,P=g/l.height,C=R(G1);!C||(y.uniform2f(C.uniform.size,f,P),p())}};this.add=function(g){let f=Array.prototype.slice.call(arguments,1),P=M[g];s.push({func:P,args:f})},this.reset=function(){s=[]},this.get=function(){return s},this.apply=function(g){x(g.width,g.height),e=0,t||(t=y.createTexture()),y.bindTexture(y.TEXTURE_2D,t),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_WRAP_S,y.CLAMP_TO_EDGE),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_WRAP_T,y.CLAMP_TO_EDGE),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_MIN_FILTER,y.NEAREST),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_MAG_FILTER,y.NEAREST),y.texImage2D(y.TEXTURE_2D,0,y.RGBA,y.RGBA,y.UNSIGNED_BYTE,g);for(let f=0;f<s.length;f++){o=f===s.length-1;let P=s[f];P.func.apply(this,P.args||[])}return l},this.draw=function(g){return this.add("brightness",0),this.apply(g)}}async function i2(e){let t=e.shape.length===4?A.squeeze(e):e,o=A.split(t,3,2),n=[A.min(o[0]),A.min(o[1]),A.min(o[2])],r=[A.max(o[0]),A.max(o[1]),A.max(o[2])],s=await Promise.all(r.map(m=>m.data())),a=.99*Math.max(s[0][0],s[1][0],s[2][0]),i=[A.sub(o[0],n[0]),A.sub(o[1],n[1]),A.sub(o[2],n[2])],l=[A.sub(r[0],n[0]),A.sub(r[1],n[1]),A.sub(r[2],n[2])],c=[A.div(a,l[0]),A.div(a,l[1]),A.div(a,l[2])],d=[A.mul(i[0],c[0]),A.mul(i[1],c[1]),A.mul(i[2],c[2])],y=A.stack([d[0],d[1],d[2]],2),x=A.reshape(y,[1,t.shape[0],t.shape[1],3]);return A.dispose([...o,...n,...r,...i,...l,...c,...d,y,t]),x}var l2=3840,B=null,$=null,Me=null,U,F0={inputSum:0,cacheDiff:1,sumMethod:0,inputTensor:void 0};function y0(e,t){let o;if(T.browser)if(T.worker){if(typeof OffscreenCanvas=="undefined")throw new Error("canvas error: attempted to run in web worker but OffscreenCanvas is not supported");o=new OffscreenCanvas(e,t)}else{if(typeof document=="undefined")throw new Error("canvas error: attempted to run in browser but DOM is not defined");o=document.createElement("canvas"),o.width=e,o.height=t}else typeof T.Canvas!="undefined"?o=new T.Canvas(e,t):typeof globalThis.Canvas!="undefined"&&(o=new globalThis.Canvas(e,t));return o}function y2(e,t){let o=t||y0(e.width,e.height);return o.getContext("2d").drawImage(e,0,0),o}async function Pe(e,t,o=!0){if(!e)return t.debug&&u("input error: input is missing"),{tensor:null,canvas:null};if(!(e instanceof ge)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(typeof T.Canvas!="undefined"&&e instanceof T.Canvas)&&!(typeof globalThis.Canvas!="undefined"&&e instanceof globalThis.Canvas)&&!(typeof ImageData!="undefined"&&e instanceof ImageData)&&!(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)&&!(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)&&!(typeof HTMLMediaElement!="undefined"&&e instanceof HTMLMediaElement)&&!(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)&&!(typeof HTMLCanvasElement!="undefined"&&e instanceof HTMLCanvasElement)&&!(typeof OffscreenCanvas!="undefined"&&e instanceof OffscreenCanvas))throw new Error("input error: type is not recognized");if(e instanceof ge){let n=null;if(e.isDisposedInternal)throw new Error("input error: attempted to use tensor but it is disposed");if(!e.shape)throw new Error("input error: attempted to use tensor without a shape");if(e.shape.length===3){if(e.shape[2]===3)n=A.expandDims(e,0);else if(e.shape[2]===4){let r=A.slice3d(e,[0,0,0],[-1,-1,3]);n=A.expandDims(r,0),A.dispose(r)}}else e.shape.length===4&&(e.shape[3]===3?n=A.clone(e):e.shape[3]===4&&(n=A.slice4d(e,[0,0,0,0],[-1,-1,-1,3])));if(n==null||n.shape.length!==4||n.shape[0]!==1||n.shape[3]!==3)throw new Error(`input error: attempted to use tensor with unrecognized shape: ${e.shape}`);if(n.dtype==="int32"){let r=A.cast(n,"float32");A.dispose(n),n=r}return{tensor:n,canvas:t.filter.return?$:null}}else{if(typeof e.readyState!="undefined"&&e.readyState<=2)return t.debug&&u("input stream is not ready"),{tensor:null,canvas:B};let n=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,r=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0;if(!n||!r)return t.debug&&u("cannot determine input dimensions"),{tensor:null,canvas:B};let s=n,a=r;if(s>l2&&(s=l2,a=Math.trunc(s*r/n)),a>l2&&(a=l2,s=Math.trunc(a*n/r)),(t.filter.width||0)>0?s=t.filter.width:(t.filter.height||0)>0&&(s=n*((t.filter.height||0)/r)),(t.filter.height||0)>0?a=t.filter.height:(t.filter.width||0)>0&&(a=r*((t.filter.width||0)/n)),!s||!a)throw new Error("input error: cannot determine dimension");(!B||(B==null?void 0:B.width)!==s||(B==null?void 0:B.height)!==a)&&(B=y0(s,a));let i=B.getContext("2d");if(typeof ImageData!="undefined"&&e instanceof ImageData?i.putImageData(e,0,0):t.filter.flip&&typeof i.translate!="undefined"?(i.translate(n,0),i.scale(-1,1),i.drawImage(e,0,0,n,r,0,0,B==null?void 0:B.width,B==null?void 0:B.height),i.setTransform(1,0,0,1,0,0)):i.drawImage(e,0,0,n,r,0,0,B==null?void 0:B.width,B==null?void 0:B.height),(!$||B.width!==$.width||(B==null?void 0:B.height)!==($==null?void 0:$.height))&&($=y0(B.width,B.height)),t.filter.enabled&&T.webgl.supported?(U||(U=T.browser?new V1:null),T.filter=!!U,!U||!U.add?(t.debug&&u("input process error: cannot initialize filters"),T.webgl.supported=!1,t.filter.enabled=!1,y2(B,$)):(U.reset(),t.filter.brightness!==0&&U.add("brightness",t.filter.brightness),t.filter.contrast!==0&&U.add("contrast",t.filter.contrast),t.filter.sharpness!==0&&U.add("sharpen",t.filter.sharpness),t.filter.blur!==0&&U.add("blur",t.filter.blur),t.filter.saturation!==0&&U.add("saturation",t.filter.saturation),t.filter.hue!==0&&U.add("hue",t.filter.hue),t.filter.negative&&U.add("negative"),t.filter.sepia&&U.add("sepia"),t.filter.vintage&&U.add("brownie"),t.filter.sepia&&U.add("sepia"),t.filter.kodachrome&&U.add("kodachrome"),t.filter.technicolor&&U.add("technicolor"),t.filter.polaroid&&U.add("polaroid"),t.filter.pixelate!==0&&U.add("pixelate",t.filter.pixelate),U.get()>0?$=U.apply(B):$=U.draw(B))):(y2(B,$),U&&(U=null),T.filter=!!U),!o)return{tensor:null,canvas:$};if(!$)throw new Error("canvas error: cannot create output");let l,c=3;if(typeof ImageData!="undefined"&&e instanceof ImageData||e.data&&e.width&&e.height)if(T.browser&&A.browser)l=A.browser?A.browser.fromPixels(e):null;else{c=e.data.length/e.height/e.width;let x=new Uint8Array(e.data.buffer);l=A.tensor(x,[e.height,e.width,c],"int32")}else if((!Me||$.width!==Me.width||$.height!==Me.height)&&(Me=y0($.width,$.height)),A.browser&&T.browser)t.backend==="webgl"||t.backend==="humangl"||t.backend==="webgpu"?l=A.browser.fromPixels($):(Me=y2($),l=A.browser.fromPixels(Me));else{let h=y2($).getContext("2d").getImageData(0,0,s,a);c=h.data.length/s/a;let p=new Uint8Array(h.data.buffer);l=A.tensor(p,[s,a,c])}if(c===4){let x=A.slice3d(l,[0,0,0],[-1,-1,3]);A.dispose(l),l=x}if(!l)throw new Error("input error: cannot create tensor");let d=A.cast(l,"float32"),y=t.filter.equalization?await i2(d):A.expandDims(d,0);return A.dispose([l,d]),{tensor:y,canvas:t.filter.return?$:null}}}async function D1(e,t){let o=!1;if(e.cacheSensitivity===0||!t.shape||t.shape.length!==4||t.shape[1]>2048||t.shape[2]>2048)return o;if(!F0.inputTensor)F0.inputTensor=A.clone(t);else if(F0.inputTensor.shape[1]!==t.shape[1]||F0.inputTensor.shape[2]!==t.shape[2])A.dispose(F0.inputTensor),F0.inputTensor=A.clone(t);else{let n={};n.diff=A.sub(t,F0.inputTensor),n.squared=A.mul(n.diff,n.diff),n.sum=A.sum(n.squared);let s=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;A.dispose([F0.inputTensor,n.diff,n.squared,n.sum]),F0.inputTensor=A.clone(t),o=s<=(e.cacheSensitivity||0)}return o}async function Z1(e,t,o){let n={};if(!t||!o||t.shape.length!==4||t.shape.length!==o.shape.length)return e.debug||u("invalid input tensor or tensor shapes do not match:",t.shape,o.shape),0;if(t.shape[0]!==1||o.shape[0]!==1||t.shape[3]!==3||o.shape[3]!==3)return e.debug||u("input tensors must be of shape [1, height, width, 3]:",t.shape,o.shape),0;n.input1=A.clone(t),n.input2=t.shape[1]!==o.shape[1]||t.shape[2]!==o.shape[2]?A.image.resizeBilinear(o,[t.shape[1],t.shape[2]]):A.clone(o),n.diff=A.sub(n.input1,n.input2),n.squared=A.mul(n.diff,n.diff),n.sum=A.sum(n.squared);let s=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;return A.dispose([n.input1,n.input2,n.diff,n.squared,n.sum]),s}var t5=class{constructor(){w(this,"browser");w(this,"node");w(this,"worker");w(this,"platform","");w(this,"agent","");w(this,"backends",[]);w(this,"initial");w(this,"filter");w(this,"tfjs");w(this,"offscreen");w(this,"perfadd",!1);w(this,"wasm",{supported:void 0,backend:void 0,simd:void 0,multithread:void 0});w(this,"webgl",{supported:void 0,backend:void 0,version:void 0,renderer:void 0});w(this,"webgpu",{supported:void 0,backend:void 0,adapter:void 0});w(this,"cpu",{model:void 0,flags:[]});w(this,"kernels",[]);w(this,"Canvas");w(this,"Image");w(this,"ImageData");if(this.browser=typeof navigator!="undefined",this.node=typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined",this.tfjs={version:Ye["tfjs-core"]},this.offscreen=typeof OffscreenCanvas!="undefined",this.initial=!0,this.worker=this.browser&&this.offscreen?typeof WorkerGlobalScope!="undefined":void 0,typeof navigator!="undefined"){let t=navigator.userAgent.match(/\(([^()]+)\)/g);if(t&&t[0]){let o=t[0].match(/\(([^()]+)\)/g);this.platform=o&&o[0]?o[0].replace(/\(|\)/g,""):"",this.agent=navigator.userAgent.replace(t[0],""),this.platform[1]&&(this.agent=this.agent.replace(t[1],"")),this.agent=this.agent.replace(/  /g," ")}}else typeof process!="undefined"&&(this.platform=`${process.platform} ${process.arch}`,this.agent=`NodeJS ${process.version}`)}async updateBackend(){this.backends=Object.keys(A.engine().registryFactory),this.wasm.supported=typeof WebAssembly!="undefined",this.wasm.backend=this.backends.includes("wasm"),this.wasm.supported&&this.wasm.backend&&A.getBackend()==="wasm"&&(this.wasm.simd=await A.env().getAsync("WASM_HAS_SIMD_SUPPORT"),this.wasm.multithread=await A.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT"));let t=y0(100,100),o=t?t.getContext("webgl2"):void 0;if(this.webgl.supported=typeof o!="undefined",this.webgl.backend=this.backends.includes("webgl"),this.webgl.supported&&this.webgl.backend&&(A.getBackend()==="webgl"||A.getBackend()==="humangl")){let n=A.backend().gpgpu!=="undefined"?await A.backend().getGPGPUContext().gl:null;n&&(this.webgl.version=n.getParameter(n.VERSION),this.webgl.renderer=n.getParameter(n.RENDERER))}this.webgpu.supported=this.browser&&typeof navigator.gpu!="undefined",this.webgpu.backend=this.backends.includes("webgpu");try{this.webgpu.supported&&(this.webgpu.adapter=(await navigator.gpu.requestAdapter()).name)}catch(n){this.webgpu.supported=!1}try{this.kernels=A.getKernelsForBackend(A.getBackend()).map(n=>n.kernelName.toLowerCase())}catch(n){}}async updateCPU(){let t={model:"",flags:[]};this.node&&this.platform.startsWith("linux"),this.cpu?this.cpu=t:Object.defineProperty(this,"cpu",{value:t})}},T=new t5;var o5={};U0(o5,{age:()=>Lo,antispoof:()=>Wo,blazeface:()=>Bo,"blazeface-back":()=>Fo,"blazeface-front":()=>Go,"blazepose-detector2d":()=>Ho,"blazepose-detector3d":()=>Vo,"blazepose-full":()=>Do,"blazepose-heavy":()=>Zo,"blazepose-lite":()=>Xo,default:()=>Tn,efficientpose:()=>qo,emotion:()=>Uo,faceboxes:()=>Yo,facemesh:()=>en,"facemesh-attention":()=>Jo,"facemesh-attention-alt":()=>Ko,"facemesh-detection-full":()=>Qo,"facemesh-detection-short":()=>_o,"facemesh-orig":()=>$o,faceres:()=>on,"faceres-deep":()=>tn,gear:()=>nn,gender:()=>An,"gender-ssrnet-imdb":()=>rn,handdetect:()=>sn,"handlandmark-full":()=>an,"handlandmark-lite":()=>ln,"handlandmark-sparse":()=>yn,handskeleton:()=>xn,handtrack:()=>cn,iris:()=>dn,liveness:()=>fn,"mb3-centernet":()=>mn,meet:()=>pn,mobileface:()=>un,mobilefacenet:()=>hn,"movenet-lightning":()=>bn,"movenet-multipose":()=>gn,"movenet-thunder":()=>Mn,nanodet:()=>Pn,posenet:()=>Rn,selfie:()=>vn});var Lo=161240,Wo=853098,Fo=538928,Go=402048,Bo=538928,Ho=7499400,Vo=5928856,Do=6338290,Zo=27501554,Xo=2725490,qo=5651240,Uo=820516,Yo=2013002,Ko=2387598,Jo=2382414,Qo=1026192,_o=201268,$o=2955780,en=1477958,tn=13957620,on=6978814,nn=1498916,rn=161236,An=201808,sn=3515612,an=5431368,ln=2023432,yn=5286322,xn=5502280,cn=2964837,dn=2599092,fn=592976,mn=4030290,pn=372228,un=2183192,hn=5171976,bn=4650216,gn=9448838,Mn=12477112,Pn=7574558,Rn=5032780,vn=212886,Tn={age:Lo,antispoof:Wo,"blazeface-back":Fo,"blazeface-front":Go,blazeface:Bo,"blazepose-detector2d":Ho,"blazepose-detector3d":Vo,"blazepose-full":Do,"blazepose-heavy":Zo,"blazepose-lite":Xo,efficientpose:qo,emotion:Uo,faceboxes:Yo,"facemesh-attention-alt":Ko,"facemesh-attention":Jo,"facemesh-detection-full":Qo,"facemesh-detection-short":_o,"facemesh-orig":$o,facemesh:en,"faceres-deep":tn,faceres:on,gear:nn,"gender-ssrnet-imdb":rn,gender:An,handdetect:sn,"handlandmark-full":an,"handlandmark-lite":ln,"handlandmark-sparse":yn,handskeleton:xn,handtrack:cn,iris:dn,liveness:fn,"mb3-centernet":mn,meet:pn,mobileface:un,mobilefacenet:hn,"movenet-lightning":bn,"movenet-multipose":gn,"movenet-thunder":Mn,nanodet:Pn,posenet:Rn,selfie:vn};var x0={cacheModels:!0,cacheSupported:!0,verbose:!0,debug:!1,modelBasePath:""},k0={};async function wn(e,t){return x0.debug&&u("load model fetch:",e,t),fetch(e,t)}function X1(e){x0.cacheModels=e.cacheModels,x0.verbose=e.debug,x0.modelBasePath=e.modelBasePath}async function L(e){var c,d,y;let t=O1(x0.modelBasePath,e||"");t.toLowerCase().endsWith(".json")||(t+=".json");let o=t.includes("/")?t.split("/"):t.split("\\"),n=o[o.length-1].replace(".json",""),r="indexeddb://"+n;k0[n]={name:n,sizeFromManifest:0,sizeLoadedWeights:0,sizeDesired:o5[n],inCache:!1},x0.cacheSupported=typeof window!="undefined"&&typeof window.localStorage!="undefined"&&typeof window.indexedDB!="undefined";let s={};try{s=x0.cacheSupported&&x0.cacheModels?await A.io.listModels():{}}catch(x){x0.cacheSupported=!1}k0[n].inCache=x0.cacheSupported&&x0.cacheModels&&Object.keys(s).includes(r);let a=typeof fetch=="undefined"?{}:{fetchFunc:(x,m)=>wn(x,m)},i=new _2(k0[n].inCache?r:t,a),l=!1;try{i.findIOHandler(),x0.debug&&u("model load handler:",i.handler);let x=await i.handler.load();k0[n].sizeFromManifest=((c=x==null?void 0:x.weightData)==null?void 0:c.byteLength)||0,i.loadSync(x),k0[n].sizeLoadedWeights=((y=(d=i==null?void 0:i.artifacts)==null?void 0:d.weightData)==null?void 0:y.byteLength)||0,x0.verbose&&u("load model:",i.modelUrl,{bytes:k0[n].sizeLoadedWeights},x0),l=!0}catch(x){u("error loading model:",t,x)}if(l&&x0.cacheModels&&x0.cacheSupported&&!k0[n].inCache)try{let x=await i.save(r);u("model saved:",r,x)}catch(x){u("error saving model:",t,x)}return i}var n5="2.9.1";var u1={};U0(u1,{Models:()=>r2,getModelStats:()=>f1,load:()=>m1,reset:()=>X2,validate:()=>p1});var v0,r5=[],zn=["white","black","asian","indian","other"],Sn=[15,23,28,35.5,45.5,55.5,65],q1=0,U1=0,A5=Number.MAX_SAFE_INTEGER;async function Y1(e){var t;return T.initial&&(v0=null),v0?e.debug&&u("cached model:",v0.modelUrl):v0=await L((t=e.face.gear)==null?void 0:t.modelPath),v0}async function s5(e,t,o,n){var a,i;if(!v0)return{age:0,gender:"unknown",genderScore:0,race:[]};let r=A5<(((a=t.face.gear)==null?void 0:a.skipFrames)||0),s=(((i=t.face.gear)==null?void 0:i.skipTime)||0)>b()-U1;return t.skipAllowed&&s&&r&&q1===n&&r5[o]?(A5++,r5[o]):(A5=0,new Promise(async l=>{var M,g;if(!(v0!=null&&v0.inputs[0].shape))return;let c={},d=[[0,.1,.9,.9]];c.resize=A.image.cropAndResize(e,d,[0],[v0.inputs[0].shape[2],v0.inputs[0].shape[1]]);let y={age:0,gender:"unknown",genderScore:0,race:[]};(M=t.face.gear)!=null&&M.enabled&&([c.age,c.gender,c.race]=v0.execute(c.resize,["age_output","gender_output","race_output"]));let x=await c.gender.data();y.gender=x[0]>x[1]?"male":"female",y.genderScore=Math.round(100*(x[0]>x[1]?x[0]:x[1]))/100;let m=await c.race.data();for(let f=0;f<m.length;f++)m[f]>(((g=t.face.gear)==null?void 0:g.minConfidence)||.2)&&y.race.push({score:Math.round(100*m[f])/100,race:zn[f]});y.race.sort((f,P)=>P.score-f.score);let p=Array.from(await c.age.data()).map((f,P)=>[Sn[P],f]).sort((f,P)=>P[1]-f[1]),R=p[0][0];for(let f=1;f<p.length;f++)R+=p[f][1]*(p[f][0]-R);y.age=Math.round(10*R)/10,Object.keys(c).forEach(f=>A.dispose(c[f])),r5[o]=y,q1=n,U1=b(),l(y)}))}var G={tf255:255,tf1:1,tf2:2,tf05:.5,tf127:127.5,rgb:[.2989,.587,.114]};function J1(){G.tf255=A.scalar(255,"float32"),G.tf1=A.scalar(1,"float32"),G.tf2=A.scalar(2,"float32"),G.tf05=A.scalar(.5,"float32"),G.tf127=A.scalar(127.5,"float32"),G.rgb=A.tensor1d([.2989,.587,.114],"float32")}var f0,x2=[],Q1=0,_1=0,a5=Number.MAX_SAFE_INTEGER;async function $1(e){return T.initial&&(f0=null),f0?e.debug&&u("cached model:",f0.modelUrl):f0=await L(e.face.ssrnet.modelPathAge),f0}async function i5(e,t,o,n){var a,i,l,c;if(!f0)return{age:0};let r=a5<(((a=t.face.ssrnet)==null?void 0:a.skipFrames)||0),s=(((i=t.face.ssrnet)==null?void 0:i.skipTime)||0)>b()-_1;return t.skipAllowed&&r&&s&&Q1===n&&((l=x2[o])==null?void 0:l.age)&&((c=x2[o])==null?void 0:c.age)>0?(a5++,x2[o]):(a5=0,new Promise(async d=>{if(!(f0!=null&&f0.inputs)||!f0.inputs[0]||!f0.inputs[0].shape)return;let y={};y.resize=A.image.resizeBilinear(e,[f0.inputs[0].shape[2],f0.inputs[0].shape[1]],!1),y.enhance=A.mul(y.resize,G.tf255);let x={age:0};if(t.face.ssrnet.enabled&&(y.age=f0.execute(y.enhance)),y.age){let m=await y.age.data();x.age=Math.trunc(10*m[0])/10}Object.keys(y).forEach(m=>A.dispose(y[m])),x2[o]=x,Q1=n,_1=b(),d(x)}))}var T0,c2=[],tt=0,ot=0,l5=Number.MAX_SAFE_INTEGER,y5=[.2989,.587,.114];async function nt(e){return T.initial&&(T0=null),T0?e.debug&&u("cached model:",T0.modelUrl):T0=await L(e.face.ssrnet.modelPathGender),T0}async function x5(e,t,o,n){var a,i,l,c;if(!T0)return{gender:"unknown",genderScore:0};let r=l5<(((a=t.face.ssrnet)==null?void 0:a.skipFrames)||0),s=(((i=t.face.ssrnet)==null?void 0:i.skipTime)||0)>b()-ot;return t.skipAllowed&&r&&s&&tt===n&&((l=c2[o])==null?void 0:l.gender)&&((c=c2[o])==null?void 0:c.genderScore)>0?(l5++,c2[o]):(l5=0,new Promise(async d=>{if(!(T0!=null&&T0.inputs[0].shape))return;let y={};y.resize=A.image.resizeBilinear(e,[T0.inputs[0].shape[2],T0.inputs[0].shape[1]],!1),y.enhance=A.tidy(()=>{let[h,p,R]=A.split(y.resize,3,3),M=A.mul(h,y5[0]),g=A.mul(p,y5[1]),f=A.mul(R,y5[2]),P=A.addN([M,g,f]);return A.mul(A.sub(P,G.tf05),2)});let x={gender:"unknown",genderScore:0};t.face.ssrnet.enabled&&(y.gender=T0.execute(y.enhance));let m=await y.gender.data();x.gender=m[0]>m[1]?"female":"male",x.genderScore=m[0]>m[1]?Math.trunc(100*m[0])/100:Math.trunc(100*m[1])/100,Object.keys(y).forEach(h=>A.dispose(y[h])),c2[o]=x,tt=n,ot=b(),d(x)}))}var A0,d2=[],c5=Number.MAX_SAFE_INTEGER,At=0,st=0;async function at(e){var t;return T.initial&&(A0=null),A0?e.debug&&u("cached model:",A0.modelUrl):A0=await L((t=e.face.antispoof)==null?void 0:t.modelPath),A0}async function d5(e,t,o,n){var a,i;if(!A0)return 0;let r=(((a=t.face.antispoof)==null?void 0:a.skipTime)||0)>b()-st,s=c5<(((i=t.face.antispoof)==null?void 0:i.skipFrames)||0);return t.skipAllowed&&r&&s&&At===n&&d2[o]?(c5++,d2[o]):(c5=0,new Promise(async l=>{let c=A.image.resizeBilinear(e,[A0!=null&&A0.inputs[0].shape?A0.inputs[0].shape[2]:0,A0!=null&&A0.inputs[0].shape?A0.inputs[0].shape[1]:0],!1),d=A0==null?void 0:A0.execute(c),y=(await d.data())[0];d2[o]=Math.round(100*y)/100,At=n,st=b(),A.dispose([c,d]),l(d2[o])}))}var w0={silhouette:[10,338,297,332,284,251,389,356,454,323,361,288,397,365,379,378,400,377,152,148,176,149,150,136,172,58,132,93,234,127,162,21,54,103,67,109],lipsUpperOuter:[185,40,39,37,0,267,269,270,409],lipsLowerOuter:[61,146,91,181,84,17,314,405,321,375,291],lipsUpperInner:[191,80,81,82,13,312,311,310,415],lipsLowerInner:[78,95,88,178,87,14,317,402,318,324,308],lipsLowerSemiOuter:[76,77,90,180,85,16,315,404,320,307,306],lipsUpperSemiOuter:[184,74,73,72,11,302,303,304,408],lipsLowerSemiInner:[62,96,89,179,86,15,316,403,319,325,292],lipsUpperSemiInner:[183,42,41,38,12,268,271,272,407],rightEyeUpper0:[246,161,160,159,158,157,173],rightEyeLower0:[33,7,163,144,145,153,154,155,133],rightEyeUpper1:[247,30,29,27,28,56,190],rightEyeLower1:[130,25,110,24,23,22,26,112,243],rightEyeUpper2:[113,225,224,223,222,221,189],rightEyeLower2:[226,31,228,229,230,231,232,233,244],rightEyeLower3:[143,111,117,118,119,120,121,128,245],rightEyebrowUpper:[156,70,63,105,66,107,55,193],rightEyebrowLower:[35,124,46,53,52,65],rightEyeIris:[473,474,475,476,477],leftEyeUpper0:[466,388,387,386,385,384,398],leftEyeLower0:[263,249,390,373,374,380,381,382,362],leftEyeUpper1:[467,260,259,257,258,286,414],leftEyeLower1:[359,255,339,254,253,252,256,341,463],leftEyeUpper2:[342,445,444,443,442,441,413],leftEyeLower2:[446,261,448,449,450,451,452,453,464],leftEyeLower3:[372,340,346,347,348,349,350,357,465],leftEyebrowUpper:[383,300,293,334,296,336,285,417],leftEyebrowLower:[265,353,276,283,282,295],leftEyeIris:[468,469,470,471,472],midwayBetweenEyes:[168],noseTip:[1],noseBottom:[2],noseRightCorner:[98],noseLeftCorner:[327],rightCheek:[205],leftCheek:[425]},f5={count:468,mouth:13,symmetryLine:[13,w0.midwayBetweenEyes[0]]},ae={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},m5=[{key:"EyeUpper0",indices:[9,10,11,12,13,14,15]},{key:"EyeUpper1",indices:[25,26,27,28,29,30,31]},{key:"EyeUpper2",indices:[41,42,43,44,45,46,47]},{key:"EyeLower0",indices:[0,1,2,3,4,5,6,7,8]},{key:"EyeLower1",indices:[16,17,18,19,20,21,22,23,24]},{key:"EyeLower2",indices:[32,33,34,35,36,37,38,39,40]},{key:"EyeLower3",indices:[54,55,56,57,58,59,60,61,62]},{key:"EyebrowUpper",indices:[63,64,65,66,67,68,69,70]},{key:"EyebrowLower",indices:[48,49,50,51,52,53]}],Je=[[.499976992607117,.652534008026123],[.500025987625122,.547487020492554],[.499974012374878,.602371990680695],[.482113003730774,.471979022026062],[.500150978565216,.527155995368958],[.499909996986389,.498252987861633],[.499523013830185,.40106201171875],[.289712011814117,.380764007568359],[.499954998493195,.312398016452789],[.499987006187439,.269918978214264],[.500023007392883,.107050001621246],[.500023007392883,.666234016418457],[.5000159740448,.679224014282227],[.500023007392883,.692348003387451],[.499976992607117,.695277988910675],[.499976992607117,.70593398809433],[.499976992607117,.719385027885437],[.499976992607117,.737019002437592],[.499967992305756,.781370997428894],[.499816000461578,.562981009483337],[.473773002624512,.573909997940063],[.104906998574734,.254140973091125],[.365929991006851,.409575998783112],[.338757991790771,.41302502155304],[.311120003461838,.409460008144379],[.274657994508743,.389131009578705],[.393361985683441,.403706014156342],[.345234006643295,.344011008739471],[.370094001293182,.346076011657715],[.319321990013123,.347265005111694],[.297903001308441,.353591024875641],[.24779200553894,.410809993743896],[.396889001131058,.842755019664764],[.280097991228104,.375599980354309],[.106310002505779,.399955987930298],[.2099249958992,.391353011131287],[.355807989835739,.534406006336212],[.471751004457474,.65040397644043],[.474155008792877,.680191993713379],[.439785003662109,.657229006290436],[.414617002010345,.66654098033905],[.450374007225037,.680860996246338],[.428770989179611,.682690978050232],[.374971002340317,.727805018424988],[.486716985702515,.547628998756409],[.485300987958908,.527395009994507],[.257764995098114,.314490020275116],[.401223003864288,.455172002315521],[.429818987846375,.548614978790283],[.421351999044418,.533740997314453],[.276895999908447,.532056987285614],[.483370006084442,.499586999416351],[.33721199631691,.282882988452911],[.296391993761063,.293242990970612],[.169294998049736,.193813979625702],[.447580009698868,.302609980106354],[.392390012741089,.353887975215912],[.354490011930466,.696784019470215],[.067304998636246,.730105042457581],[.442739009857178,.572826027870178],[.457098007202148,.584792017936707],[.381974011659622,.694710969924927],[.392388999462128,.694203019142151],[.277076005935669,.271932005882263],[.422551989555359,.563233017921448],[.385919004678726,.281364023685455],[.383103013038635,.255840003490448],[.331431001424789,.119714021682739],[.229923993349075,.232002973556519],[.364500999450684,.189113974571228],[.229622006416321,.299540996551514],[.173287004232407,.278747975826263],[.472878992557526,.666198015213013],[.446828007698059,.668527007102966],[.422762006521225,.673889994621277],[.445307999849319,.580065965652466],[.388103008270264,.693961024284363],[.403039008378983,.706539988517761],[.403629004955292,.693953037261963],[.460041999816895,.557139039039612],[.431158006191254,.692366003990173],[.452181994915009,.692366003990173],[.475387006998062,.692366003990173],[.465828001499176,.779190003871918],[.472328990697861,.736225962638855],[.473087012767792,.717857003211975],[.473122000694275,.704625964164734],[.473033010959625,.695277988910675],[.427942007780075,.695277988910675],[.426479011774063,.703539967536926],[.423162013292313,.711845993995667],[.4183090031147,.720062971115112],[.390094995498657,.639572978019714],[.013953999616206,.560034036636353],[.499913990497589,.58014702796936],[.413199990987778,.69539999961853],[.409626007080078,.701822996139526],[.468080013990402,.601534962654114],[.422728985548019,.585985004901886],[.463079988956451,.593783974647522],[.37211999297142,.47341400384903],[.334562003612518,.496073007583618],[.411671012639999,.546965003013611],[.242175996303558,.14767599105835],[.290776997804642,.201445996761322],[.327338010072708,.256527006626129],[.399509996175766,.748921036720276],[.441727995872498,.261676013469696],[.429764986038208,.187834024429321],[.412198007106781,.108901023864746],[.288955003023148,.398952007293701],[.218936994671822,.435410976409912],[.41278201341629,.398970007896423],[.257135003805161,.355440020561218],[.427684992551804,.437960982322693],[.448339998722076,.536936044692993],[.178560003638268,.45755398273468],[.247308000922203,.457193970680237],[.286267012357712,.467674970626831],[.332827985286713,.460712015628815],[.368755996227264,.447206974029541],[.398963987827301,.432654976844788],[.476410001516342,.405806005001068],[.189241006970406,.523923993110657],[.228962004184723,.348950982093811],[.490725994110107,.562400996685028],[.404670000076294,.485132992267609],[.019469000399113,.401564002037048],[.426243007183075,.420431017875671],[.396993011236191,.548797011375427],[.266469985246658,.376977026462555],[.439121007919312,.51895797252655],[.032313998788595,.644356966018677],[.419054001569748,.387154996395111],[.462783008813858,.505746960639954],[.238978996872902,.779744982719421],[.198220998048782,.831938028335571],[.107550002634525,.540755033493042],[.183610007166862,.740257024765015],[.134409993886948,.333683013916016],[.385764002799988,.883153975009918],[.490967005491257,.579378008842468],[.382384985685349,.508572995662689],[.174399003386497,.397670984268188],[.318785011768341,.39623498916626],[.343364000320435,.400596976280212],[.396100014448166,.710216999053955],[.187885001301765,.588537991046906],[.430987000465393,.944064974784851],[.318993002176285,.898285031318665],[.266247987747192,.869701027870178],[.500023007392883,.190576016902924],[.499976992607117,.954452991485596],[.366169989109039,.398822009563446],[.393207013607025,.39553701877594],[.410373002290726,.391080021858215],[.194993004202843,.342101991176605],[.388664990663528,.362284004688263],[.365961998701096,.355970978736877],[.343364000320435,.355356991291046],[.318785011768341,.35834002494812],[.301414996385574,.363156020641327],[.058132998645306,.319076001644135],[.301414996385574,.387449026107788],[.499987989664078,.618434011936188],[.415838003158569,.624195992946625],[.445681989192963,.566076993942261],[.465844005346298,.620640993118286],[.49992299079895,.351523995399475],[.288718998432159,.819945991039276],[.335278987884521,.852819979190826],[.440512001514435,.902418971061707],[.128294005990028,.791940987110138],[.408771991729736,.373893976211548],[.455606997013092,.451801002025604],[.499877005815506,.908990025520325],[.375436991453171,.924192011356354],[.11421000212431,.615022003650665],[.448662012815475,.695277988910675],[.4480200111866,.704632043838501],[.447111994028091,.715808033943176],[.444831997156143,.730794012546539],[.430011987686157,.766808986663818],[.406787008047104,.685672998428345],[.400738000869751,.681069016456604],[.392399996519089,.677703022956848],[.367855995893478,.663918972015381],[.247923001646996,.601333022117615],[.452769994735718,.420849978923798],[.43639200925827,.359887003898621],[.416164010763168,.368713974952698],[.413385987281799,.692366003990173],[.228018000721931,.683571994304657],[.468268007040024,.352671027183533],[.411361992359161,.804327011108398],[.499989002943039,.469825029373169],[.479153990745544,.442654013633728],[.499974012374878,.439637005329132],[.432112008333206,.493588984012604],[.499886006116867,.866917014122009],[.49991300702095,.821729004383087],[.456548988819122,.819200992584229],[.344549000263214,.745438992977142],[.37890899181366,.574010014533997],[.374292999505997,.780184984207153],[.319687992334366,.570737957954407],[.357154995203018,.604269981384277],[.295284003019333,.621580958366394],[.447750002145767,.862477004528046],[.410986006259918,.508723020553589],[.31395098567009,.775308012962341],[.354128003120422,.812552988529205],[.324548006057739,.703992962837219],[.189096003770828,.646299958229065],[.279776990413666,.71465802192688],[.1338230073452,.682700991630554],[.336768001317978,.644733011722565],[.429883986711502,.466521978378296],[.455527991056442,.548622965812683],[.437114000320435,.558896005153656],[.467287987470627,.529924988746643],[.414712011814117,.335219979286194],[.37704598903656,.322777986526489],[.344107985496521,.320150971412659],[.312875986099243,.32233202457428],[.283526003360748,.333190023899078],[.241245999932289,.382785975933075],[.102986000478268,.468762993812561],[.267612010240555,.424560010433197],[.297879010438919,.433175981044769],[.333433985710144,.433878004550934],[.366427004337311,.426115989685059],[.396012008190155,.416696012020111],[.420121014118195,.41022801399231],[.007561000064015,.480777025222778],[.432949006557465,.569517970085144],[.458638995885849,.479089021682739],[.473466008901596,.545744001865387],[.476087987422943,.563830018043518],[.468472003936768,.555056989192963],[.433990985155106,.582361996173859],[.483518004417419,.562983989715576],[.482482999563217,.57784903049469],[.42645001411438,.389798998832703],[.438998997211456,.39649498462677],[.450067013502121,.400434017181396],[.289712011814117,.368252992630005],[.276670008897781,.363372981548309],[.517862021923065,.471948027610779],[.710287988185883,.380764007568359],[.526226997375488,.573909997940063],[.895093023777008,.254140973091125],[.634069979190826,.409575998783112],[.661242008209229,.41302502155304],[.688880026340485,.409460008144379],[.725341975688934,.389131009578705],[.606630027294159,.40370500087738],[.654766023159027,.344011008739471],[.629905998706818,.346076011657715],[.680678009986877,.347265005111694],[.702096998691559,.353591024875641],[.75221198797226,.410804986953735],[.602918028831482,.842862963676453],[.719901978969574,.375599980354309],[.893692970275879,.399959981441498],[.790081977844238,.391354024410248],[.643998026847839,.534487962722778],[.528249025344849,.65040397644043],[.525849997997284,.680191040039062],[.560214996337891,.657229006290436],[.585384011268616,.66654098033905],[.549625992774963,.680860996246338],[.57122802734375,.682691991329193],[.624852001667023,.72809898853302],[.513050019741058,.547281980514526],[.51509702205658,.527251958847046],[.742246985435486,.314507007598877],[.598631024360657,.454979002475739],[.570338010787964,.548575043678284],[.578631997108459,.533622980117798],[.723087012767792,.532054007053375],[.516445994377136,.499638974666595],[.662801027297974,.282917976379395],[.70362401008606,.293271005153656],[.830704987049103,.193813979625702],[.552385985851288,.302568018436432],[.607609987258911,.353887975215912],[.645429015159607,.696707010269165],[.932694971561432,.730105042457581],[.557260990142822,.572826027870178],[.542901992797852,.584792017936707],[.6180260181427,.694710969924927],[.607590973377228,.694203019142151],[.722943007946014,.271963000297546],[.577413976192474,.563166975975037],[.614082992076874,.281386971473694],[.616907000541687,.255886018276215],[.668509006500244,.119913995265961],[.770092010498047,.232020974159241],[.635536015033722,.189248979091644],[.77039098739624,.299556016921997],[.826722025871277,.278755009174347],[.527121007442474,.666198015213013],[.553171992301941,.668527007102966],[.577238023281097,.673889994621277],[.554691970348358,.580065965652466],[.611896991729736,.693961024284363],[.59696102142334,.706539988517761],[.596370995044708,.693953037261963],[.539958000183105,.557139039039612],[.568841993808746,.692366003990173],[.547818005084991,.692366003990173],[.52461302280426,.692366003990173],[.534089982509613,.779141008853912],[.527670979499817,.736225962638855],[.526912987232208,.717857003211975],[.526877999305725,.704625964164734],[.526966989040375,.695277988910675],[.572058022022247,.695277988910675],[.573521018028259,.703539967536926],[.57683801651001,.711845993995667],[.581691026687622,.720062971115112],[.609944999217987,.639909982681274],[.986046016216278,.560034036636353],[.5867999792099,.69539999961853],[.590372025966644,.701822996139526],[.531915009021759,.601536989212036],[.577268004417419,.585934996604919],[.536915004253387,.593786001205444],[.627542972564697,.473352015018463],[.665585994720459,.495950996875763],[.588353991508484,.546862006187439],[.757824003696442,.14767599105835],[.709249973297119,.201507985591888],[.672684013843536,.256581008434296],[.600408971309662,.74900496006012],[.55826598405838,.261672019958496],[.570303976535797,.187870979309082],[.588165998458862,.109044015407562],[.711045026779175,.398952007293701],[.781069993972778,.435405015945435],[.587247014045715,.398931980133057],[.742869973182678,.355445981025696],[.572156012058258,.437651991844177],[.55186802148819,.536570012569427],[.821442008018494,.457556009292603],[.752701997756958,.457181990146637],[.71375697851181,.467626988887787],[.66711300611496,.460672974586487],[.631101012229919,.447153985500336],[.6008620262146,.432473003864288],[.523481011390686,.405627012252808],[.810747981071472,.523926019668579],[.771045982837677,.348959028720856],[.509127020835876,.562718033790588],[.595292985439301,.485023975372314],[.980530977249146,.401564002037048],[.573499977588654,.420000016689301],[.602994978427887,.548687994480133],[.733529984951019,.376977026462555],[.560611009597778,.519016981124878],[.967685997486115,.644356966018677],[.580985009670258,.387160003185272],[.537728011608124,.505385041236877],[.760966002941132,.779752969741821],[.801778972148895,.831938028335571],[.892440974712372,.54076099395752],[.816350996494293,.740260004997253],[.865594983100891,.333687007427216],[.614073991775513,.883246004581451],[.508952975273132,.579437971115112],[.617941975593567,.508316040039062],[.825608015060425,.397674977779388],[.681214988231659,.39623498916626],[.656635999679565,.400596976280212],[.603900015354156,.710216999053955],[.81208598613739,.588539004325867],[.56801301240921,.944564998149872],[.681007981300354,.898285031318665],[.733752012252808,.869701027870178],[.633830010890961,.398822009563446],[.606792986392975,.39553701877594],[.589659988880157,.391062021255493],[.805015981197357,.342108011245728],[.611334979534149,.362284004688263],[.634037971496582,.355970978736877],[.656635999679565,.355356991291046],[.681214988231659,.35834002494812],[.698584973812103,.363156020641327],[.941866993904114,.319076001644135],[.698584973812103,.387449026107788],[.584177017211914,.624107003211975],[.554318010807037,.566076993942261],[.534153997898102,.62064003944397],[.711217999458313,.819975018501282],[.664629995822906,.852871000766754],[.559099972248077,.902631998062134],[.871706008911133,.791940987110138],[.591234028339386,.373893976211548],[.544341027736664,.451583981513977],[.624562978744507,.924192011356354],[.88577002286911,.615028977394104],[.551338016986847,.695277988910675],[.551980018615723,.704632043838501],[.552887976169586,.715808033943176],[.555167973041534,.730794012546539],[.569944024085999,.767035007476807],[.593203008174896,.685675978660583],[.599261999130249,.681069016456604],[.607599973678589,.677703022956848],[.631937980651855,.663500010967255],[.752032995223999,.601315021514893],[.547226011753082,.420395016670227],[.563543975353241,.359827995300293],[.583841025829315,.368713974952698],[.586614012718201,.692366003990173],[.771915018558502,.683578014373779],[.531597018241882,.352482974529266],[.588370978832245,.804440975189209],[.52079701423645,.442565023899078],[.567984998226166,.493479013442993],[.543282985687256,.819254994392395],[.655317008495331,.745514988899231],[.621008992195129,.574018001556396],[.625559985637665,.78031200170517],[.680198013782501,.570719003677368],[.64276397228241,.604337990283966],[.704662978649139,.621529996395111],[.552012026309967,.862591981887817],[.589071989059448,.508637011051178],[.685944974422455,.775357007980347],[.645735025405884,.812640011310577],[.675342977046967,.703978002071381],[.810858011245728,.646304965019226],[.72012197971344,.714666962623596],[.866151988506317,.682704985141754],[.663187026977539,.644596993923187],[.570082008838654,.466325998306274],[.544561982154846,.548375964164734],[.562758982181549,.558784961700439],[.531987011432648,.530140042304993],[.585271000862122,.335177004337311],[.622952997684479,.32277899980545],[.655896008014679,.320163011550903],[.687132000923157,.322345972061157],[.716481983661652,.333200991153717],[.758756995201111,.382786989212036],[.897013008594513,.468769013881683],[.732392013072968,.424547016620636],[.70211398601532,.433162987232208],[.66652500629425,.433866024017334],[.633504986763,.426087975502014],[.603875994682312,.416586995124817],[.579657971858978,.409945011138916],[.992439985275269,.480777025222778],[.567192018032074,.569419980049133],[.54136598110199,.478899002075195],[.526564002037048,.546118021011353],[.523913025856018,.563830018043518],[.531529009342194,.555056989192963],[.566035985946655,.582329034805298],[.51631098985672,.563053965568542],[.5174720287323,.577877044677734],[.573594987392426,.389806985855103],[.560697972774506,.395331978797913],[.549755990505219,.399751007556915],[.710287988185883,.368252992630005],[.723330020904541,.363372981548309]],ie=[127,34,139,11,0,37,232,231,120,72,37,39,128,121,47,232,121,128,104,69,67,175,171,148,157,154,155,118,50,101,73,39,40,9,151,108,48,115,131,194,204,211,74,40,185,80,42,183,40,92,186,230,229,118,202,212,214,83,18,17,76,61,146,160,29,30,56,157,173,106,204,194,135,214,192,203,165,98,21,71,68,51,45,4,144,24,23,77,146,91,205,50,187,201,200,18,91,106,182,90,91,181,85,84,17,206,203,36,148,171,140,92,40,39,193,189,244,159,158,28,247,246,161,236,3,196,54,68,104,193,168,8,117,228,31,189,193,55,98,97,99,126,47,100,166,79,218,155,154,26,209,49,131,135,136,150,47,126,217,223,52,53,45,51,134,211,170,140,67,69,108,43,106,91,230,119,120,226,130,247,63,53,52,238,20,242,46,70,156,78,62,96,46,53,63,143,34,227,173,155,133,123,117,111,44,125,19,236,134,51,216,206,205,154,153,22,39,37,167,200,201,208,36,142,100,57,212,202,20,60,99,28,158,157,35,226,113,160,159,27,204,202,210,113,225,46,43,202,204,62,76,77,137,123,116,41,38,72,203,129,142,64,98,240,49,102,64,41,73,74,212,216,207,42,74,184,169,170,211,170,149,176,105,66,69,122,6,168,123,147,187,96,77,90,65,55,107,89,90,180,101,100,120,63,105,104,93,137,227,15,86,85,129,102,49,14,87,86,55,8,9,100,47,121,145,23,22,88,89,179,6,122,196,88,95,96,138,172,136,215,58,172,115,48,219,42,80,81,195,3,51,43,146,61,171,175,199,81,82,38,53,46,225,144,163,110,246,33,7,52,65,66,229,228,117,34,127,234,107,108,69,109,108,151,48,64,235,62,78,191,129,209,126,111,35,143,163,161,246,117,123,50,222,65,52,19,125,141,221,55,65,3,195,197,25,7,33,220,237,44,70,71,139,122,193,245,247,130,33,71,21,162,153,158,159,170,169,150,188,174,196,216,186,92,144,160,161,2,97,167,141,125,241,164,167,37,72,38,12,145,159,160,38,82,13,63,68,71,226,35,111,158,153,154,101,50,205,206,92,165,209,198,217,165,167,97,220,115,218,133,112,243,239,238,241,214,135,169,190,173,133,171,208,32,125,44,237,86,87,178,85,86,179,84,85,180,83,84,181,201,83,182,137,93,132,76,62,183,61,76,184,57,61,185,212,57,186,214,207,187,34,143,156,79,239,237,123,137,177,44,1,4,201,194,32,64,102,129,213,215,138,59,166,219,242,99,97,2,94,141,75,59,235,24,110,228,25,130,226,23,24,229,22,23,230,26,22,231,112,26,232,189,190,243,221,56,190,28,56,221,27,28,222,29,27,223,30,29,224,247,30,225,238,79,20,166,59,75,60,75,240,147,177,215,20,79,166,187,147,213,112,233,244,233,128,245,128,114,188,114,217,174,131,115,220,217,198,236,198,131,134,177,132,58,143,35,124,110,163,7,228,110,25,356,389,368,11,302,267,452,350,349,302,303,269,357,343,277,452,453,357,333,332,297,175,152,377,384,398,382,347,348,330,303,304,270,9,336,337,278,279,360,418,262,431,304,408,409,310,415,407,270,409,410,450,348,347,422,430,434,313,314,17,306,307,375,387,388,260,286,414,398,335,406,418,364,367,416,423,358,327,251,284,298,281,5,4,373,374,253,307,320,321,425,427,411,421,313,18,321,405,406,320,404,405,315,16,17,426,425,266,377,400,369,322,391,269,417,465,464,386,257,258,466,260,388,456,399,419,284,332,333,417,285,8,346,340,261,413,441,285,327,460,328,355,371,329,392,439,438,382,341,256,429,420,360,364,394,379,277,343,437,443,444,283,275,440,363,431,262,369,297,338,337,273,375,321,450,451,349,446,342,467,293,334,282,458,461,462,276,353,383,308,324,325,276,300,293,372,345,447,382,398,362,352,345,340,274,1,19,456,248,281,436,427,425,381,256,252,269,391,393,200,199,428,266,330,329,287,273,422,250,462,328,258,286,384,265,353,342,387,259,257,424,431,430,342,353,276,273,335,424,292,325,307,366,447,345,271,303,302,423,266,371,294,455,460,279,278,294,271,272,304,432,434,427,272,407,408,394,430,431,395,369,400,334,333,299,351,417,168,352,280,411,325,319,320,295,296,336,319,403,404,330,348,349,293,298,333,323,454,447,15,16,315,358,429,279,14,15,316,285,336,9,329,349,350,374,380,252,318,402,403,6,197,419,318,319,325,367,364,365,435,367,397,344,438,439,272,271,311,195,5,281,273,287,291,396,428,199,311,271,268,283,444,445,373,254,339,263,466,249,282,334,296,449,347,346,264,447,454,336,296,299,338,10,151,278,439,455,292,407,415,358,371,355,340,345,372,390,249,466,346,347,280,442,443,282,19,94,370,441,442,295,248,419,197,263,255,359,440,275,274,300,383,368,351,412,465,263,467,466,301,368,389,380,374,386,395,378,379,412,351,419,436,426,322,373,390,388,2,164,393,370,462,461,164,0,267,302,11,12,374,373,387,268,12,13,293,300,301,446,261,340,385,384,381,330,266,425,426,423,391,429,355,437,391,327,326,440,457,438,341,382,362,459,457,461,434,430,394,414,463,362,396,369,262,354,461,457,316,403,402,315,404,403,314,405,404,313,406,405,421,418,406,366,401,361,306,408,407,291,409,408,287,410,409,432,436,410,434,416,411,264,368,383,309,438,457,352,376,401,274,275,4,421,428,262,294,327,358,433,416,367,289,455,439,462,370,326,2,326,370,305,460,455,254,449,448,255,261,446,253,450,449,252,451,450,256,452,451,341,453,452,413,464,463,441,413,414,258,442,441,257,443,442,259,444,443,260,445,444,467,342,445,459,458,250,289,392,290,290,328,460,376,433,435,250,290,392,411,416,433,341,463,464,453,464,465,357,465,412,343,412,399,360,363,440,437,399,456,420,456,363,401,435,288,372,383,353,339,255,249,448,261,255,133,243,190,133,155,112,33,246,247,33,130,25,398,384,286,362,398,414,362,463,341,263,359,467,263,249,255,466,467,260,75,60,166,238,239,79,162,127,139,72,11,37,121,232,120,73,72,39,114,128,47,233,232,128,103,104,67,152,175,148,173,157,155,119,118,101,74,73,40,107,9,108,49,48,131,32,194,211,184,74,185,191,80,183,185,40,186,119,230,118,210,202,214,84,83,17,77,76,146,161,160,30,190,56,173,182,106,194,138,135,192,129,203,98,54,21,68,5,51,4,145,144,23,90,77,91,207,205,187,83,201,18,181,91,182,180,90,181,16,85,17,205,206,36,176,148,140,165,92,39,245,193,244,27,159,28,30,247,161,174,236,196,103,54,104,55,193,8,111,117,31,221,189,55,240,98,99,142,126,100,219,166,218,112,155,26,198,209,131,169,135,150,114,47,217,224,223,53,220,45,134,32,211,140,109,67,108,146,43,91,231,230,120,113,226,247,105,63,52,241,238,242,124,46,156,95,78,96,70,46,63,116,143,227,116,123,111,1,44,19,3,236,51,207,216,205,26,154,22,165,39,167,199,200,208,101,36,100,43,57,202,242,20,99,56,28,157,124,35,113,29,160,27,211,204,210,124,113,46,106,43,204,96,62,77,227,137,116,73,41,72,36,203,142,235,64,240,48,49,64,42,41,74,214,212,207,183,42,184,210,169,211,140,170,176,104,105,69,193,122,168,50,123,187,89,96,90,66,65,107,179,89,180,119,101,120,68,63,104,234,93,227,16,15,85,209,129,49,15,14,86,107,55,9,120,100,121,153,145,22,178,88,179,197,6,196,89,88,96,135,138,136,138,215,172,218,115,219,41,42,81,5,195,51,57,43,61,208,171,199,41,81,38,224,53,225,24,144,110,105,52,66,118,229,117,227,34,234,66,107,69,10,109,151,219,48,235,183,62,191,142,129,126,116,111,143,7,163,246,118,117,50,223,222,52,94,19,141,222,221,65,196,3,197,45,220,44,156,70,139,188,122,245,139,71,162,145,153,159,149,170,150,122,188,196,206,216,92,163,144,161,164,2,167,242,141,241,0,164,37,11,72,12,144,145,160,12,38,13,70,63,71,31,226,111,157,158,154,36,101,205,203,206,165,126,209,217,98,165,97,237,220,218,237,239,241,210,214,169,140,171,32,241,125,237,179,86,178,180,85,179,181,84,180,182,83,181,194,201,182,177,137,132,184,76,183,185,61,184,186,57,185,216,212,186,192,214,187,139,34,156,218,79,237,147,123,177,45,44,4,208,201,32,98,64,129,192,213,138,235,59,219,141,242,97,97,2,141,240,75,235,229,24,228,31,25,226,230,23,229,231,22,230,232,26,231,233,112,232,244,189,243,189,221,190,222,28,221,223,27,222,224,29,223,225,30,224,113,247,225,99,60,240,213,147,215,60,20,166,192,187,213,243,112,244,244,233,245,245,128,188,188,114,174,134,131,220,174,217,236,236,198,134,215,177,58,156,143,124,25,110,7,31,228,25,264,356,368,0,11,267,451,452,349,267,302,269,350,357,277,350,452,357,299,333,297,396,175,377,381,384,382,280,347,330,269,303,270,151,9,337,344,278,360,424,418,431,270,304,409,272,310,407,322,270,410,449,450,347,432,422,434,18,313,17,291,306,375,259,387,260,424,335,418,434,364,416,391,423,327,301,251,298,275,281,4,254,373,253,375,307,321,280,425,411,200,421,18,335,321,406,321,320,405,314,315,17,423,426,266,396,377,369,270,322,269,413,417,464,385,386,258,248,456,419,298,284,333,168,417,8,448,346,261,417,413,285,326,327,328,277,355,329,309,392,438,381,382,256,279,429,360,365,364,379,355,277,437,282,443,283,281,275,363,395,431,369,299,297,337,335,273,321,348,450,349,359,446,467,283,293,282,250,458,462,300,276,383,292,308,325,283,276,293,264,372,447,346,352,340,354,274,19,363,456,281,426,436,425,380,381,252,267,269,393,421,200,428,371,266,329,432,287,422,290,250,328,385,258,384,446,265,342,386,387,257,422,424,430,445,342,276,422,273,424,306,292,307,352,366,345,268,271,302,358,423,371,327,294,460,331,279,294,303,271,304,436,432,427,304,272,408,395,394,431,378,395,400,296,334,299,6,351,168,376,352,411,307,325,320,285,295,336,320,319,404,329,330,349,334,293,333,366,323,447,316,15,315,331,358,279,317,14,316,8,285,9,277,329,350,253,374,252,319,318,403,351,6,419,324,318,325,397,367,365,288,435,397,278,344,439,310,272,311,248,195,281,375,273,291,175,396,199,312,311,268,276,283,445,390,373,339,295,282,296,448,449,346,356,264,454,337,336,299,337,338,151,294,278,455,308,292,415,429,358,355,265,340,372,388,390,466,352,346,280,295,442,282,354,19,370,285,441,295,195,248,197,457,440,274,301,300,368,417,351,465,251,301,389,385,380,386,394,395,379,399,412,419,410,436,322,387,373,388,326,2,393,354,370,461,393,164,267,268,302,12,386,374,387,312,268,13,298,293,301,265,446,340,380,385,381,280,330,425,322,426,391,420,429,437,393,391,326,344,440,438,458,459,461,364,434,394,428,396,262,274,354,457,317,316,402,316,315,403,315,314,404,314,313,405,313,421,406,323,366,361,292,306,407,306,291,408,291,287,409,287,432,410,427,434,411,372,264,383,459,309,457,366,352,401,1,274,4,418,421,262,331,294,358,435,433,367,392,289,439,328,462,326,94,2,370,289,305,455,339,254,448,359,255,446,254,253,449,253,252,450,252,256,451,256,341,452,414,413,463,286,441,414,286,258,441,258,257,442,257,259,443,259,260,444,260,467,445,309,459,250,305,289,290,305,290,460,401,376,435,309,250,392,376,411,433,453,341,464,357,453,465,343,357,412,437,343,399,344,360,440,420,437,456,360,420,363,361,401,288,265,372,353,390,339,249,339,448,255];var jn=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],In=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],Nn=[33,133,362,263,1,78,308],$A=jn.map(e=>Je[e]),e7=In.map(e=>Je[e]),t7=Nn.map(e=>Je[e]);function Y0(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var On=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Ln=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Wn=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],Fn=[[474,475],[475,476],[476,477],[477,474]],Gn=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],Bn=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],Hn=[[469,470],[470,471],[471,472],[472,469]],Vn=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]],o7={lips:Y0(On),leftEye:Y0(Ln),leftEyebrow:Y0(Wn),leftIris:Y0(Fn),rightEye:Y0(Gn),rightEyebrow:Y0(Bn),rightIris:Y0(Hn),faceOval:Y0(Vn)};var Re=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],f2=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],m2=(e,t)=>e?[Math.trunc(Math.max(0,e.startPoint[0])),Math.trunc(Math.max(0,e.startPoint[1])),Math.trunc(Math.min(t.shape[2]||0,e.endPoint[0])-Math.max(0,e.startPoint[0])),Math.trunc(Math.min(t.shape[1]||0,e.endPoint[1])-Math.max(0,e.startPoint[1]))]:[0,0,0,0],p2=(e,t)=>e?[e.startPoint[0]/(t.shape[2]||0),e.startPoint[1]/(t.shape[1]||0),(e.endPoint[0]-e.startPoint[0])/(t.shape[2]||0),(e.endPoint[1]-e.startPoint[1])/(t.shape[1]||0)]:[0,0,0,0],xt=(e,t)=>{let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]];return{startPoint:o,endPoint:n,landmarks:e.landmarks,confidence:e.confidence}},u5=(e,t,o)=>{let n=t.shape[1],r=t.shape[2],s=[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r],a=A.image.cropAndResize(t,[s],[0],o),i=A.div(a,G.tf255);return A.dispose(a),i},u2=(e,t)=>{let o=f2(e),n=Re(e),r=[t*n[0]/2,t*n[1]/2];return{startPoint:[o[0]-r[0],o[1]-r[1]],endPoint:[o[0]+r[0],o[1]+r[1]],landmarks:e.landmarks,confidence:e.confidence}},h2=e=>{let t=f2(e),o=Re(e),n=Math.max(...o)/2;return{startPoint:[Math.round(t[0]-n),Math.round(t[1]-n)],endPoint:[Math.round(t[0]+n),Math.round(t[1]+n)],landmarks:e.landmarks,confidence:e.confidence}},ct=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return{startPoint:[Math.min(...t),Math.min(...o)],endPoint:[Math.max(...t),Math.max(...o)],landmarks:e}},h5=[[1,0,0],[0,1,0],[0,0,1]],Dn=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),Zn=(e,t)=>Dn(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var lt=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],le=(e,t)=>{let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o},Xn=(e,t)=>{let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o},yt=(e,t)=>{let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let s=0;s<n;s++)o[r].push(le(e[r],Xn(t,s)))}return o},dt=(e,t)=>{let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],s=lt(t[0],t[1]),a=yt(s,r),i=lt(-t[0],-t[1]);return yt(a,i)},qn=e=>{let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-le(t[0],o),-le(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]},Un=(e,t)=>[le(e,t[0]),le(e,t[1])];function ft(e){let t=e===192?{strides:[4],anchors:[1]}:{strides:[e/16,e/8],anchors:[2,6]},o=[];for(let n=0;n<t.strides.length;n++){let r=t.strides[n],s=Math.floor((e+r-1)/r),a=Math.floor((e+r-1)/r),i=t.anchors[n];for(let l=0;l<s;l++){let c=r*(l+.5);for(let d=0;d<a;d++){let y=r*(d+.5);for(let x=0;x<i;x++)o.push([y,c])}}}return o}function mt(e,t,o,n,r){let s=Re(t),a=e.map(m=>[s[0]/r*(m[0]-r/2),s[1]/r*(m[1]-r/2),m[2]||0]),i=o&&o!==0&&Math.abs(o)>.2,l=i?dt(o,[0,0]):h5,c=i?a.map(m=>[...Un(m,l),m[2]]):a,d=i?qn(n):h5,y=f2(t),x=[le(y,d[0]),le(y,d[1])];return c.map(m=>[Math.trunc(m[0]+x[0]),Math.trunc(m[1]+x[1]),Math.trunc(m[2]||0)])}function pt(e,t,o,n){let r=t.landmarks.length>=f5.count?f5.symmetryLine:ae.symmetryLine,s=0,a=h5,i;if(e&&T.kernels.includes("rotatewithoffset"))if(s=Zn(t.landmarks[r[0]],t.landmarks[r[1]]),s&&s!==0&&Math.abs(s)>.2){let c=f2(t),d=[c[0]/o.shape[2],c[1]/o.shape[1]],y=A.image.rotateWithOffset(o,s,0,d);a=dt(-s,c),i=u5(t,y,[n,n]),A.dispose(y)}else i=u5(t,o,[n,n]);else i=u5(t,o,[n,n]);return[s,a,i]}var Yn=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return[Math.min(...t)+(Math.max(...t)-Math.min(...t))/2,Math.min(...o)+(Math.max(...o)-Math.min(...o))/2]},ut=(e,t)=>{let o=Yn(e),n=Re(t);return{startPoint:[o[0]-n[0]/2,o[1]-n[1]/2],endPoint:[o[0]+n[0]/2,o[1]+n[1]/2]}};var ht=6,Kn=1.4,j0,bt=null,K0=0,Qe=null,ve=()=>K0;async function gt(e){var t;return T.initial&&(j0=null),j0?e.debug&&u("cached model:",j0.modelUrl):j0=await L((t=e.face.detector)==null?void 0:t.modelPath),K0=j0.inputs[0].shape?j0.inputs[0].shape[2]:0,Qe=A.scalar(K0,"int32"),bt=A.tensor2d(ft(K0)),j0}function Jn(e){let t={};t.boxStarts=A.slice(e,[0,1],[-1,2]),t.centers=A.add(t.boxStarts,bt),t.boxSizes=A.slice(e,[0,3],[-1,2]),t.boxSizesNormalized=A.div(t.boxSizes,Qe),t.centersNormalized=A.div(t.centers,Qe),t.halfBoxSize=A.div(t.boxSizesNormalized,G.tf2),t.starts=A.sub(t.centersNormalized,t.halfBoxSize),t.ends=A.add(t.centersNormalized,t.halfBoxSize),t.startNormalized=A.mul(t.starts,Qe),t.endNormalized=A.mul(t.ends,Qe);let o=A.concat2d([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(n=>A.dispose(t[n])),o}async function Mt(e,t){var i,l,c,d;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let o={};o.resized=A.image.resizeBilinear(e,[K0,K0]),o.div=A.div(o.resized,G.tf127),o.normalized=A.sub(o.div,G.tf05);let n=j0==null?void 0:j0.execute(o.normalized);if(Array.isArray(n)&&n.length>2){let y=n.sort((x,m)=>x.size-m.size);o.concat384=A.concat([y[0],y[2]],2),o.concat512=A.concat([y[1],y[3]],2),o.concat=A.concat([o.concat512,o.concat384],1),o.batch=A.squeeze(o.concat,0)}else Array.isArray(n)?o.batch=A.squeeze(n[0]):o.batch=A.squeeze(n);A.dispose(n),o.boxes=Jn(o.batch),o.logits=A.slice(o.batch,[0,0],[-1,1]),o.sigmoid=A.sigmoid(o.logits),o.scores=A.squeeze(o.sigmoid),o.nms=await A.image.nonMaxSuppressionAsync(o.boxes,o.scores,((i=t.face.detector)==null?void 0:i.maxDetected)||0,((l=t.face.detector)==null?void 0:l.iouThreshold)||0,((c=t.face.detector)==null?void 0:c.minConfidence)||0);let r=await o.nms.array(),s=[],a=await o.scores.data();for(let y=0;y<r.length;y++){let x=a[r[y]];if(x>(((d=t.face.detector)==null?void 0:d.minConfidence)||0)){let m={};m.bbox=A.slice(o.boxes,[r[y],0],[1,-1]),m.slice=A.slice(o.batch,[r[y],ht-1],[1,-1]),m.squeeze=A.squeeze(m.slice),m.landmarks=A.reshape(m.squeeze,[ht,-1]);let h=await m.bbox.data(),p={startPoint:[h[0],h[1]],endPoint:[h[2],h[3]],landmarks:await m.landmarks.array(),confidence:x},R=xt(p,[(e.shape[2]||0)/K0,(e.shape[1]||0)/K0]),M=u2(R,t.face.scale||Kn),g=h2(M);s.push(g),Object.keys(m).forEach(f=>A.dispose(m[f]))}}return Object.keys(o).forEach(y=>A.dispose(o[y])),s}var b2={};U0(b2,{connected:()=>M5,kpt:()=>g5});var g5=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPinky","rightPinky","leftIndex","rightIndex","leftThumb","rightThumb","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","bodyCenter","bodyTop","leftPalm","leftHand","rightPalm","rightHand"],M5={shoulders:["leftShoulder","rightShoulder"],hips:["rightHip","leftHip"],mouth:["leftMouth","rightMouth"],leftLegUpper:["leftHip","leftKnee"],leftLegLower:["leftKnee","leftAnkle"],leftFoot:["leftAnkle","leftHeel","leftFoot"],leftTorso:["leftShoulder","leftHip"],leftArmUpper:["leftShoulder","leftElbow"],leftArmLower:["leftElbow","leftWrist"],leftHand:["leftWrist","leftPalm"],leftHandPinky:["leftPalm","leftPinky"],leftHandIndex:["leftPalm","leftIndex"],leftHandThumb:["leftPalm","leftThumb"],leftEyeOutline:["leftEyeInside","leftEyeOutside"],rightLegUpper:["rightHip","rightKnee"],rightLegLower:["rightKnee","rightAnkle"],rightFoot:["rightAnkle","rightHeel","rightFoot"],rightTorso:["rightShoulder","rightHip"],rightArmUpper:["rightShoulder","rightElbow"],rightArmLower:["rightElbow","rightWrist"],rightHand:["rightWrist","rightPalm"],rightHandPinky:["rightPalm","rightPinky"],rightHandIndex:["rightPalm","rightIndex"],rightHandThumb:["rightPalm","rightThumb"],rightEyeOutline:["rightEyeInside","rightEyeOutside"]};var Rt=224,Qn,_n=5,g2=[8,16,32,32,32];async function vt(){let e=[],t=0;for(;t<_n;){let o=0,n=t;for(;n<g2.length&&g2[n]===g2[t];)o+=2,n++;let r=g2[t],s=Math.ceil(Rt/r),a=Math.ceil(Rt/r);for(let i=0;i<s;++i)for(let l=0;l<a;++l)for(let c=0;c<o;++c)e.push({x:(l+.5)/a,y:(i+.5)/s});t=n}Qn={x:A.tensor1d(e.map(o=>o.x)),y:A.tensor1d(e.map(o=>o.y))}}function G0(e,t=[1,1]){let o=[e.map(i=>i[0]),e.map(i=>i[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],s=[n[0],n[1],r[0]-n[0],r[1]-n[1]],a=[s[0]/t[0],s[1]/t[1],s[2]/t[0],s[3]/t[1]];return{box:s,boxRaw:a}}function Tt(e,t=[1,1]){let o=[e.map(c=>c[0]),e.map(c=>c[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],s=[(n[0]+r[0])/2,(n[1]+r[1])/2],a=Math.max(s[0]-n[0],s[1]-n[1],-s[0]+r[0],-s[1]+r[1]),i=[Math.trunc(s[0]-a),Math.trunc(s[1]-a),Math.trunc(2*a),Math.trunc(2*a)],l=[i[0]/t[0],i[1]/t[1],i[2]/t[0],i[3]/t[1]];return{box:i,boxRaw:l}}function M2(e,t){let o=[e[2]*t,e[3]*t];return[e[0]-(o[0]-e[2])/2,e[1]-(o[1]-e[3])/2,o[0],o[1]]}var Et={initial:!0},m0={detector:null,landmarks:null},Te={detector:[224,224],landmarks:[256,256]},P5=Number.MAX_SAFE_INTEGER,er={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},R2=null,_e,J0=[[0,0],[0,0],[0,0],[0,0]],wt=0,kt=e=>1-1/(1+Math.exp(e));async function zt(e){if(Et.initial&&(m0.detector=null),!m0.detector&&e.body.detector&&e.body.detector.modelPath){m0.detector=await L(e.body.detector.modelPath);let t=Object.values(m0.detector.modelSignature.inputs);Te.detector[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,Te.detector[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&m0.detector&&u("cached model:",m0.detector.modelUrl);return await vt(),m0.detector}async function St(e){if(Et.initial&&(m0.landmarks=null),m0.landmarks)e.debug&&u("cached model:",m0.landmarks.modelUrl);else{m0.landmarks=await L(e.body.modelPath);let t=Object.values(m0.landmarks.modelSignature.inputs);Te.landmarks[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,Te.landmarks[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return m0.landmarks}async function tr(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;let n;if(_e&&(o.cropped=A.image.cropAndResize(e,[_e],[0],[e.shape[1],e.shape[2]])),e.shape[1]!==e.shape[2]){let r=[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],s=[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0];J0=[[0,0],r,s,[0,0]],o.pad=A.pad(o.cropped||e,J0),o.resize=A.image.resizeBilinear(o.pad,[t,t]),n=A.div(o.resize,G.tf255)}else e.shape[1]!==t?(o.resize=A.image.resizeBilinear(o.cropped||e,[t,t]),n=A.div(o.resize,G.tf255)):n=A.div(o.cropped||e,G.tf255);return Object.keys(o).forEach(r=>A.dispose(o[r])),n}function or(e,t){for(let o of e)o.position=[Math.trunc(o.position[0]*(t[0]+J0[2][0]+J0[2][1])/t[0]-J0[2][0]),Math.trunc(o.position[1]*(t[1]+J0[1][0]+J0[1][1])/t[1]-J0[1][0]),o.position[2]],o.positionRaw=[o.position[0]/t[0],o.position[1]/t[1],2*o.position[2]/(t[0]+t[1])];if(_e)for(let o of e)o.positionRaw=[o.positionRaw[0]+_e[1],o.positionRaw[1]+_e[0],o.positionRaw[2]],o.position=[Math.trunc(o.positionRaw[0]*t[0]),Math.trunc(o.positionRaw[1]*t[1]),o.positionRaw[2]];return e}async function nr(e){let t=e.find(i=>i.part==="leftPalm"),o=e.find(i=>i.part==="leftWrist"),n=e.find(i=>i.part==="leftIndex");t.position[2]=((o.position[2]||0)+(n.position[2]||0))/2;let r=e.find(i=>i.part==="rightPalm"),s=e.find(i=>i.part==="rightWrist"),a=e.find(i=>i.part==="rightIndex");r.position[2]=((s.position[2]||0)+(a.position[2]||0))/2}async function rr(e,t,o){var h;let n={};[n.ld,n.segmentation,n.heatmap,n.world,n.poseflag]=(h=m0.landmarks)==null?void 0:h.execute(e,er.landmarks);let r=(await n.poseflag.data())[0],s=await n.ld.data(),a=await n.world.data();Object.keys(n).forEach(p=>A.dispose(n[p]));let i=[],l=5;for(let p=0;p<s.length/l;p++){let R=kt(s[l*p+3]),M=kt(s[l*p+4]),g=Math.trunc(100*R*M*r)/100,f=[s[l*p+0]/Te.landmarks[0],s[l*p+1]/Te.landmarks[1],s[l*p+2]+0],P=[Math.trunc(o[0]*f[0]),Math.trunc(o[1]*f[1]),f[2]],C=[a[l*p+0],a[l*p+1],a[l*p+2]+0];i.push({part:g5[p],positionRaw:f,position:P,distance:C,score:g})}if(r<(t.body.minConfidence||0))return null;nr(i);let c=or(i,o),d=c.map(p=>p.position),y=G0(d,[o[0],o[1]]),x={};for(let[p,R]of Object.entries(M5)){let M=[];for(let g=0;g<R.length-1;g++){let f=c.find(C=>C.part===R[g]),P=c.find(C=>C.part===R[g+1]);f&&P&&M.push([f.position,P.position])}x[p]=M}return{id:0,score:Math.trunc(100*r)/100,box:y.box,boxRaw:y.boxRaw,keypoints:c,annotations:x}}async function R5(e,t){let o=[e.shape[2]||0,e.shape[1]||0],n=(t.body.skipTime||0)>b()-wt,r=P5<(t.body.skipFrames||0);if(t.skipAllowed&&n&&r&&R2!==null)P5++;else{let s={};s.landmarks=await tr(e,256),R2=await rr(s.landmarks,t,o),Object.keys(s).forEach(a=>A.dispose(s[a])),wt=b(),P5=0}return R2?[R2]:[]}var we=[{class:1,label:"person"},{class:2,label:"bicycle"},{class:3,label:"car"},{class:4,label:"motorcycle"},{class:5,label:"airplane"},{class:6,label:"bus"},{class:7,label:"train"},{class:8,label:"truck"},{class:9,label:"boat"},{class:10,label:"traffic light"},{class:11,label:"fire hydrant"},{class:12,label:"stop sign"},{class:13,label:"parking meter"},{class:14,label:"bench"},{class:15,label:"bird"},{class:16,label:"cat"},{class:17,label:"dog"},{class:18,label:"horse"},{class:19,label:"sheep"},{class:20,label:"cow"},{class:21,label:"elephant"},{class:22,label:"bear"},{class:23,label:"zebra"},{class:24,label:"giraffe"},{class:25,label:"backpack"},{class:26,label:"umbrella"},{class:27,label:"handbag"},{class:28,label:"tie"},{class:29,label:"suitcase"},{class:30,label:"frisbee"},{class:31,label:"skis"},{class:32,label:"snowboard"},{class:33,label:"sports ball"},{class:34,label:"kite"},{class:35,label:"baseball bat"},{class:36,label:"baseball glove"},{class:37,label:"skateboard"},{class:38,label:"surfboard"},{class:39,label:"tennis racket"},{class:40,label:"bottle"},{class:41,label:"wine glass"},{class:42,label:"cup"},{class:43,label:"fork"},{class:44,label:"knife"},{class:45,label:"spoon"},{class:46,label:"bowl"},{class:47,label:"banana"},{class:48,label:"apple"},{class:49,label:"sandwich"},{class:50,label:"orange"},{class:51,label:"broccoli"},{class:52,label:"carrot"},{class:53,label:"hot dog"},{class:54,label:"pizza"},{class:55,label:"donut"},{class:56,label:"cake"},{class:57,label:"chair"},{class:58,label:"couch"},{class:59,label:"potted plant"},{class:60,label:"bed"},{class:61,label:"dining table"},{class:62,label:"toilet"},{class:63,label:"tv"},{class:64,label:"laptop"},{class:65,label:"mouse"},{class:66,label:"remote"},{class:67,label:"keyboard"},{class:68,label:"cell phone"},{class:69,label:"microwave"},{class:70,label:"oven"},{class:71,label:"toaster"},{class:72,label:"sink"},{class:73,label:"refrigerator"},{class:74,label:"book"},{class:75,label:"clock"},{class:76,label:"vase"},{class:77,label:"scissors"},{class:78,label:"teddy bear"},{class:79,label:"hair drier"},{class:80,label:"toothbrush"}];var B0,ye=0,v5=[],jt=0,T5=Number.MAX_SAFE_INTEGER;async function It(e){if(T.initial&&(B0=null),B0)e.debug&&u("cached model:",B0.modelUrl);else{B0=await L(e.object.modelPath);let t=Object.values(B0.modelSignature.inputs);ye=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return B0}async function Ar(e,t,o){if(!e)return[];let n={},r=[],s=await e.array();n.squeeze=A.squeeze(e);let a=A.split(n.squeeze,6,1);n.stack=A.stack([a[1],a[0],a[3],a[2]],1),n.boxes=A.squeeze(n.stack),n.scores=A.squeeze(a[4]),n.classes=A.squeeze(a[5]),A.dispose([e,...a]),n.nms=await A.image.nonMaxSuppressionAsync(n.boxes,n.scores,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence||0);let i=await n.nms.data(),l=0;for(let c of Array.from(i)){let d=Math.trunc(100*s[0][c][4])/100,y=s[0][c][5],x=we[y].label,[m,h]=[s[0][c][0]/ye,s[0][c][1]/ye],p=[m,h,s[0][c][2]/ye-m,s[0][c][3]/ye-h],R=[Math.trunc(p[0]*t[0]),Math.trunc(p[1]*t[1]),Math.trunc(p[2]*t[0]),Math.trunc(p[3]*t[1])];r.push({id:l++,score:d,class:y,label:x,box:R,boxRaw:p})}return Object.keys(n).forEach(c=>A.dispose(n[c])),r}async function w5(e,t){let o=(t.object.skipTime||0)>b()-jt,n=T5<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&v5.length>0?(T5++,v5):(T5=0,new Promise(async r=>{let s=[e.shape[2]||0,e.shape[1]||0],a=A.image.resizeBilinear(e,[ye,ye]),i=t.object.enabled?B0==null?void 0:B0.execute(a,["tower_0/detections"]):null;jt=b(),A.dispose(a);let l=await Ar(i,s,t);v5=l,r(l)}))}var v2={};U0(v2,{connected:()=>E5,kpt:()=>k5});var k5=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],E5={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var s0,Ot=0,c0={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},z5=Number.MAX_SAFE_INTEGER;async function Lt(e){return T.initial&&(s0=null),s0?e.debug&&u("cached model:",s0.modelUrl):s0=await L(e.body.modelPath),s0}async function sr(e,t){let[o,n]=e.shape,r=A.reshape(e,[n*o]),s=A.max(r,0),a=(await s.data())[0];if(A.dispose([r,s]),a>t){let i=A.argMax(r,0),l=A.mod(i,o),c=(await l.data())[0],d=A.div(i,A.scalar(o,"int32")),y=(await d.data())[0];return A.dispose([l,d]),[c,y,a]}return[0,0,a]}async function S5(e,t){let o=(t.body.skipTime||0)>b()-Ot,n=z5<(t.body.skipFrames||0);return t.skipAllowed&&o&&n&&Object.keys(c0.keypoints).length>0?(z5++,[c0]):(z5=0,new Promise(async r=>{var y;let s=A.tidy(()=>{if(!(s0!=null&&s0.inputs[0].shape))return null;let x=A.image.resizeBilinear(e,[s0.inputs[0].shape[2],s0.inputs[0].shape[1]],!1),m=A.mul(x,G.tf2);return A.sub(m,G.tf1)}),a;if(t.body.enabled&&(a=s0==null?void 0:s0.execute(s)),Ot=b(),A.dispose(s),a){c0.keypoints.length=0;let x=a.squeeze();A.dispose(a);let m=x.unstack(2);A.dispose(x);for(let h=0;h<m.length;h++){let[p,R,M]=await sr(m[h],t.body.minConfidence);M>(((y=t.body)==null?void 0:y.minConfidence)||0)&&c0.keypoints.push({score:Math.round(100*M)/100,part:k5[h],positionRaw:[p/s0.inputs[0].shape[2],R/s0.inputs[0].shape[1]],position:[Math.round(e.shape[2]*p/s0.inputs[0].shape[2]),Math.round(e.shape[1]*R/s0.inputs[0].shape[1])]})}m.forEach(h=>A.dispose(h))}c0.score=c0.keypoints.reduce((x,m)=>m.score>x?m.score:x,0);let i=c0.keypoints.map(x=>x.position[0]),l=c0.keypoints.map(x=>x.position[1]);c0.box=[Math.min(...i),Math.min(...l),Math.max(...i)-Math.min(...i),Math.max(...l)-Math.min(...l)];let c=c0.keypoints.map(x=>x.positionRaw[0]),d=c0.keypoints.map(x=>x.positionRaw[1]);c0.boxRaw=[Math.min(...c),Math.min(...d),Math.max(...c)-Math.min(...c),Math.max(...d)-Math.min(...d)];for(let[x,m]of Object.entries(E5)){let h=[];for(let p=0;p<m.length-1;p++){let R=c0.keypoints.find(g=>g.part===m[p]),M=c0.keypoints.find(g=>g.part===m[p+1]);R&&M&&R.score>(t.body.minConfidence||0)&&M.score>(t.body.minConfidence||0)&&h.push([R.position,M.position])}c0.annotations[x]=h}r([c0])}))}var ar=["angry","disgust","fear","happy","sad","surprise","neutral"],P0,T2=[],Ft=0,Gt=0,C5=Number.MAX_SAFE_INTEGER;async function Bt(e){var t;return T.initial&&(P0=null),P0?e.debug&&u("cached model:",P0.modelUrl):P0=await L((t=e.face.emotion)==null?void 0:t.modelPath),P0}async function j5(e,t,o,n){var a,i;if(!P0)return[];let r=C5<(((a=t.face.emotion)==null?void 0:a.skipFrames)||0),s=(((i=t.face.emotion)==null?void 0:i.skipTime)||0)>b()-Gt;return t.skipAllowed&&s&&r&&Ft===n&&T2[o]&&T2[o].length>0?(C5++,T2[o]):(C5=0,new Promise(async l=>{var d,y;let c=[];if((d=t.face.emotion)!=null&&d.enabled){let x={},m=P0!=null&&P0.inputs[0].shape?P0.inputs[0].shape[2]:0;x.resize=A.image.resizeBilinear(e,[m,m],!1),x.channels=A.mul(x.resize,G.rgb),x.grayscale=A.sum(x.channels,3,!0),x.grayscaleSub=A.sub(x.grayscale,G.tf05),x.grayscaleMul=A.mul(x.grayscaleSub,G.tf2),x.emotion=P0==null?void 0:P0.execute(x.grayscaleMul),Gt=b();let h=await x.emotion.data();for(let p=0;p<h.length;p++)h[p]>(((y=t.face.emotion)==null?void 0:y.minConfidence)||0)&&c.push({score:Math.min(.99,Math.trunc(100*h[p])/100),emotion:ar[p]});c.sort((p,R)=>R.score-p.score),Object.keys(x).forEach(p=>A.dispose(x[p]))}T2[o]=c,Ft=n,l(c)}))}var p0,I5=[],Vt=0,Dt=0,Zt=Number.MAX_SAFE_INTEGER;async function Xt(e){return T.initial&&(p0=null),p0?e.debug&&u("cached model:",p0.modelUrl):p0=await L(e.face.mobilefacenet.modelPath),p0}async function N5(e,t,o,n){var a,i;if(!p0)return[];let r=Zt<(((a=t.face.embedding)==null?void 0:a.skipFrames)||0),s=(((i=t.face.embedding)==null?void 0:i.skipTime)||0)>b()-Dt;return t.skipAllowed&&s&&r&&Vt===n&&I5[o]?(Zt++,I5[o]):new Promise(async l=>{var d;let c=[];if(((d=t.face.embedding)==null?void 0:d.enabled)&&(p0==null?void 0:p0.inputs[0].shape)){let y={};y.crop=A.image.resizeBilinear(e,[p0.inputs[0].shape[2],p0.inputs[0].shape[1]],!1),y.data=p0==null?void 0:p0.execute(y.crop);let x=await y.data.data();c=Array.from(x)}I5[o]=c,Vt=n,Dt=b(),l(c)})}var H0,Q0=0,ir=2.3,O5=w0.leftEyeLower0,L5=w0.rightEyeLower0,ke={leftBounds:[O5[0],O5[O5.length-1]],rightBounds:[L5[0],L5[L5.length-1]]},Ee={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function Jt(e){var t;return T.initial&&(H0=null),H0?e.debug&&u("cached model:",H0.modelUrl):H0=await L((t=e.face.iris)==null?void 0:t.modelPath),Q0=H0.inputs[0].shape?H0.inputs[0].shape[2]:0,Q0===-1&&(Q0=64),H0}function w2(e,t,o,n){for(let r=0;r<m5.length;r++){let{key:s,indices:a}=m5[r],i=w0[`${o}${s}`];if(!n||n.includes(s))for(let l=0;l<a.length;l++){let c=a[l];e[i[l]]=[t[c][0],t[c][1],(t[c][2]+e[i[l]][2])/2]}}}var lr=e=>{let t=e[ke.leftBounds[0]][2],o=e[ke.rightBounds[0]][2];return t-o},Ut=(e,t,o,n,r,s=!1)=>{let a=h2(u2(ct([e[o],e[n]]),ir)),i=Re(a),l=A.image.cropAndResize(t,[[a.startPoint[1]/r,a.startPoint[0]/r,a.endPoint[1]/r,a.endPoint[0]/r]],[0],[Q0,Q0]);if(s&&T.kernels.includes("flipleftright")){let c=A.image.flipLeftRight(l);A.dispose(l),l=c}return{box:a,boxSize:i,crop:l}},Yt=(e,t,o,n=!1)=>{let r=[];for(let s=0;s<Ee.numCoordinates;s++){let a=e[s*3],i=e[s*3+1],l=e[s*3+2];r.push([(n?1-a/Q0:a/Q0)*o[0]+t.startPoint[0],i/Q0*o[1]+t.startPoint[1],l])}return{rawCoords:r,iris:r.slice(Ee.index)}},Kt=(e,t,o)=>{let n=e[w0[`${o}EyeUpper0`][Ee.upperCenter]][2],r=e[w0[`${o}EyeLower0`][Ee.lowerCenter]][2],s=(n+r)/2;return t.map((a,i)=>{let l=s;return i===2?l=n:i===4&&(l=r),[a[0],a[1],l]})};async function Qt(e,t,o,n){if(!H0)return o.debug&&u("face mesh iris detection requested, but model is not loaded"),e;let{box:r,boxSize:s,crop:a}=Ut(e,t,ke.leftBounds[0],ke.leftBounds[1],n,!0),{box:i,boxSize:l,crop:c}=Ut(e,t,ke.rightBounds[0],ke.rightBounds[1],n,!0),d=A.concat([a,c]);A.dispose(a),A.dispose(c);let y=H0.execute(d);A.dispose(d);let x=await y.data();A.dispose(y);let m=x.slice(0,Ee.numCoordinates*3),{rawCoords:h,iris:p}=Yt(m,r,s,!0),R=x.slice(Ee.numCoordinates*3),{rawCoords:M,iris:g}=Yt(R,i,l,!1),f=lr(e);Math.abs(f)<30?(w2(e,h,"left",null),w2(e,M,"right",null)):f<1?w2(e,h,"left",["EyeUpper0","EyeLower0"]):w2(e,M,"right",["EyeUpper0","EyeLower0"]);let P=Kt(e,p,"left"),C=Kt(e,g,"right");return e.concat(P).concat(C)}var yr=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],xr=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],cr=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],dr=[[474,475],[475,476],[476,477],[477,474]],fr=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],mr=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],pr=[[469,470],[470,471],[471,472],[472,469]],ur=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]];function _0(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var hr={lips:_0(yr),leftEye:_0(xr),leftEyebrow:_0(cr),leftIris:_0(dr),rightEye:_0(fr),rightEyebrow:_0(mr),rightIris:_0(pr),faceOval:_0(ur)},br=Object.entries(hr).map(([e,t])=>t.map(o=>[o,e])).flat(),C7=new Map(br),$e=[61,146,91,181,84,17,314,405,321,375,291,185,40,39,37,0,267,269,270,409,78,95,88,178,87,14,317,402,318,324,308,191,80,81,82,13,312,311,310,415,76,77,90,180,85,16,315,404,320,307,306,184,74,73,72,11,302,303,304,408,62,96,89,179,86,15,316,403,319,325,292,183,42,41,38,12,268,271,272,407],xe=[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173,130,25,110,24,23,22,26,112,243,247,30,29,27,28,56,190,226,31,228,229,230,231,232,233,244,113,225,224,223,222,221,189,35,124,46,53,52,65,143,111,117,118,119,120,121,128,245,156,70,63,105,66,107,55,193],ce=[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398,359,255,339,254,253,252,256,341,463,467,260,259,257,258,286,414,446,261,448,449,450,451,452,453,464,342,445,444,443,442,441,413,265,353,276,283,282,295,372,340,346,347,348,349,350,357,465,383,300,293,334,296,336,285,417];async function e3(e,t){let o={lips:await t.filter(s=>s.size===160)[0].data(),irisL:await t.filter(s=>s.size===10)[0].data(),eyeL:await t.filter(s=>s.size===142)[0].data(),irisR:await t.filter(s=>s.size===10)[1].data(),eyeR:await t.filter(s=>s.size===142)[1].data()},n=xe.reduce((s,a)=>s+=e[a][2],0)/xe.length;for(let s=0;s<o.irisL.length/2;s++)e.push([o.irisL[2*s+0],o.irisL[2*s+1],n]);let r=ce.reduce((s,a)=>s+=e[a][2],0)/ce.length;for(let s=0;s<o.irisR.length/2;s++)e.push([o.irisR[2*s+0],o.irisR[2*s+1],r]);for(let s=0;s<o.eyeL.length/2;s++)e[xe[s]]=[o.eyeL[2*s+0],o.eyeL[2*s+1],e[xe[s]][2]];for(let s=0;s<o.eyeR.length/2;s++)e[ce[s]]=[o.eyeR[2*s+0],o.eyeR[2*s+1],e[ce[s]][2]];for(let s=0;s<o.lips.length/2;s++)e[$e[s]]=[o.lips[2*s+0],o.lips[2*s+1],e[$e[s]][2]];return e}var I0={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},a0=null,de=0;async function t3(e,t){var i,l,c,d,y,x,m,h,p,R,M;let o=(((i=t.face.detector)==null?void 0:i.skipTime)||0)>b()-I0.timestamp,n=I0.skipped<(((l=t.face.detector)==null?void 0:l.skipFrames)||0);!t.skipAllowed||!o||!n||I0.boxes.length===0?(I0.boxes=await Mt(e,t),I0.timestamp=b(),I0.skipped=0):I0.skipped++;let r=[],s=[],a=0;for(let g=0;g<I0.boxes.length;g++){let f=I0.boxes[g],P=0,C,k={id:a++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,annotations:{}};if([P,C,k.tensor]=pt((c=t.face.detector)==null?void 0:c.rotation,f,e,(d=t.face.mesh)!=null&&d.enabled?de:ve()),(y=t==null?void 0:t.filter)!=null&&y.equalization){let I=await i2(k.tensor);A.dispose(k.tensor),k.tensor=I}if(k.boxScore=Math.round(100*f.confidence)/100,(x=t.face.mesh)!=null&&x.enabled)if(!a0)t.debug&&u("face mesh detection requested, but model is not loaded");else{let I=a0.execute(k.tensor),O=await I.find(F=>F.shape[F.shape.length-1]===1).data();if(k.faceScore=Math.round(100*O[0])/100,k.faceScore<(((m=t.face.detector)==null?void 0:m.minConfidence)||1)){if(f.confidence=k.faceScore,(h=t.face.mesh)!=null&&h.keepInvalid){k.box=m2(f,e),k.boxRaw=p2(f,e),k.score=k.boxScore,k.mesh=f.landmarks.map(F=>[(f.startPoint[0]+f.endPoint[0])/2+(f.endPoint[0]+f.startPoint[0])*F[0]/ve(),(f.startPoint[1]+f.endPoint[1])/2+(f.endPoint[1]+f.startPoint[1])*F[1]/ve()]),k.meshRaw=k.mesh.map(F=>[F[0]/(e.shape[2]||1),F[1]/(e.shape[1]||1),(F[2]||0)/de]);for(let F of Object.keys(ae))k.annotations[F]=[k.mesh[ae[F]]]}}else{let F=I.find(z=>z.shape[z.shape.length-1]===1404),V=A.reshape(F,[-1,3]),Z=await V.array();A.dispose(V),(p=t.face.attention)!=null&&p.enabled?Z=await e3(Z,I):(R=t.face.iris)!=null&&R.enabled&&(Z=await Qt(Z,k.tensor,t,de)),k.mesh=mt(Z,f,P,C,de),k.meshRaw=k.mesh.map(z=>[z[0]/(e.shape[2]||0),z[1]/(e.shape[1]||0),(z[2]||0)/de]);for(let z of Object.keys(w0))k.annotations[z]=w0[z].map(g0=>k.mesh[g0]);k.score=k.faceScore;let t0={...ut(k.mesh,f),confidence:f.confidence,landmarks:f.landmarks};k.box=m2(t0,e),k.boxRaw=p2(t0,e),s.push(t0)}A.dispose(I)}else{k.box=m2(f,e),k.boxRaw=p2(f,e),k.score=k.boxScore,k.mesh=f.landmarks.map(I=>[(f.startPoint[0]+f.endPoint[0])/2+(f.endPoint[0]+f.startPoint[0])*I[0]/ve(),(f.startPoint[1]+f.endPoint[1])/2+(f.endPoint[1]+f.startPoint[1])*I[1]/ve()]),k.meshRaw=k.mesh.map(I=>[I[0]/(e.shape[2]||0),I[1]/(e.shape[1]||0),(I[2]||0)/de]);for(let I of Object.keys(ae))k.annotations[I]=[k.mesh[ae[I]]]}k.score>(((M=t.face.detector)==null?void 0:M.minConfidence)||1)?r.push(k):A.dispose(k.tensor)}return I0.boxes=s,r}async function o3(e){var t,o,n,r,s,a;return T.initial&&(a0=null),((o=(t=e==null?void 0:e.face)==null?void 0:t.attention)==null?void 0:o.enabled)&&(a0==null?void 0:a0.signature)&&Object.keys(((n=a0==null?void 0:a0.signature)==null?void 0:n.outputs)||{}).length<6&&(a0=null),a0?e.debug&&u("cached model:",a0.modelUrl):(r=e.face.attention)!=null&&r.enabled?a0=await L((s=e.face.attention)==null?void 0:s.modelPath):a0=await L((a=e.face.mesh)==null?void 0:a.modelPath),de=a0.inputs[0].shape?a0.inputs[0].shape[2]:0,a0}var n3=ie,r3=Je;var u0,k2=[],A3=0,s3=0,F5=Number.MAX_SAFE_INTEGER;async function a3(e){var t;return T.initial&&(u0=null),u0?e.debug&&u("cached model:",u0.modelUrl):u0=await L((t=e.face.description)==null?void 0:t.modelPath),u0}function G5(e){let t=e.image||e.tensor||e;if(!(u0!=null&&u0.inputs[0].shape))return t;let o=A.image.resizeBilinear(t,[u0.inputs[0].shape[2],u0.inputs[0].shape[1]],!1),n=A.mul(o,G.tf255);return A.dispose(o),n}async function B5(e,t,o,n){var a,i,l,c;if(!u0)return{age:0,gender:"unknown",genderScore:0,descriptor:[]};let r=F5<(((a=t.face.description)==null?void 0:a.skipFrames)||0),s=(((i=t.face.description)==null?void 0:i.skipTime)||0)>b()-A3;return t.skipAllowed&&r&&s&&s3===n&&((l=k2[o])==null?void 0:l.age)&&((c=k2[o])==null?void 0:c.age)>0?(F5++,k2[o]):(F5=0,new Promise(async d=>{var x,m;let y={age:0,gender:"unknown",genderScore:0,descriptor:[]};if((x=t.face.description)!=null&&x.enabled){let h=G5(e),p=u0==null?void 0:u0.execute(h);A3=b(),A.dispose(h);let M=await(await p.find(O=>O.shape[1]===1)).data(),g=Math.trunc(200*Math.abs(M[0]-.5))/100;g>(((m=t.face.description)==null?void 0:m.minConfidence)||0)&&(y.gender=M[0]<=.5?"female":"male",y.genderScore=Math.min(.99,g));let f=A.argMax(p.find(O=>O.shape[1]===100),1),P=(await f.data())[0];A.dispose(f);let k=await p.find(O=>O.shape[1]===100).data();y.age=Math.round(k[P-1]>k[P+1]?10*P-100*k[P-1]:10*P+100*k[P+1])/10;let I=p.find(O=>O.shape[1]===1024),j=I?await I.data():[];y.descriptor=Array.from(j),p.forEach(O=>A.dispose(O))}k2[o]=y,s3=n,d(y)}))}function E2(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function e2(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function y3(e,t,o){let n=t.shape[1],r=t.shape[2],s=[[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r]];return A.image.cropAndResize(t,s,[0],o)}function x3(e,t){let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],r=e.palmLandmarks.map(s=>[s[0]*t[0],s[1]*t[1]]);return{startPoint:o,endPoint:n,palmLandmarks:r,confidence:e.confidence}}function z2(e,t=1.5){let o=e2(e),n=E2(e),r=[t*n[0]/2,t*n[1]/2],s=[o[0]-r[0],o[1]-r[1]],a=[o[0]+r[0],o[1]+r[1]];return{startPoint:s,endPoint:a,palmLandmarks:e.palmLandmarks}}function S2(e){let t=e2(e),o=E2(e),r=Math.max(...o)/2,s=[t[0]-r,t[1]-r],a=[t[0]+r,t[1]+r];return{startPoint:s,endPoint:a,palmLandmarks:e.palmLandmarks}}function Mr(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function c3(e,t){let o=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return Mr(o)}var i3=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function $0(e,t){let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o}function Pr(e,t){let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o}function l3(e,t){let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let s=0;s<n;s++)o[r].push($0(e[r],Pr(t,s)))}return o}function V5(e,t){let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],s=i3(t[0],t[1]),a=l3(s,r),i=i3(-t[0],-t[1]);return l3(a,i)}function d3(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-$0(t[0],o),-$0(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]}function D5(e,t){return[$0(e,t[0]),$0(e,t[1])]}var m3=[{x:.015625,y:.015625},{x:.015625,y:.015625},{x:.046875,y:.015625},{x:.046875,y:.015625},{x:.078125,y:.015625},{x:.078125,y:.015625},{x:.109375,y:.015625},{x:.109375,y:.015625},{x:.140625,y:.015625},{x:.140625,y:.015625},{x:.171875,y:.015625},{x:.171875,y:.015625},{x:.203125,y:.015625},{x:.203125,y:.015625},{x:.234375,y:.015625},{x:.234375,y:.015625},{x:.265625,y:.015625},{x:.265625,y:.015625},{x:.296875,y:.015625},{x:.296875,y:.015625},{x:.328125,y:.015625},{x:.328125,y:.015625},{x:.359375,y:.015625},{x:.359375,y:.015625},{x:.390625,y:.015625},{x:.390625,y:.015625},{x:.421875,y:.015625},{x:.421875,y:.015625},{x:.453125,y:.015625},{x:.453125,y:.015625},{x:.484375,y:.015625},{x:.484375,y:.015625},{x:.515625,y:.015625},{x:.515625,y:.015625},{x:.546875,y:.015625},{x:.546875,y:.015625},{x:.578125,y:.015625},{x:.578125,y:.015625},{x:.609375,y:.015625},{x:.609375,y:.015625},{x:.640625,y:.015625},{x:.640625,y:.015625},{x:.671875,y:.015625},{x:.671875,y:.015625},{x:.703125,y:.015625},{x:.703125,y:.015625},{x:.734375,y:.015625},{x:.734375,y:.015625},{x:.765625,y:.015625},{x:.765625,y:.015625},{x:.796875,y:.015625},{x:.796875,y:.015625},{x:.828125,y:.015625},{x:.828125,y:.015625},{x:.859375,y:.015625},{x:.859375,y:.015625},{x:.890625,y:.015625},{x:.890625,y:.015625},{x:.921875,y:.015625},{x:.921875,y:.015625},{x:.953125,y:.015625},{x:.953125,y:.015625},{x:.984375,y:.015625},{x:.984375,y:.015625},{x:.015625,y:.046875},{x:.015625,y:.046875},{x:.046875,y:.046875},{x:.046875,y:.046875},{x:.078125,y:.046875},{x:.078125,y:.046875},{x:.109375,y:.046875},{x:.109375,y:.046875},{x:.140625,y:.046875},{x:.140625,y:.046875},{x:.171875,y:.046875},{x:.171875,y:.046875},{x:.203125,y:.046875},{x:.203125,y:.046875},{x:.234375,y:.046875},{x:.234375,y:.046875},{x:.265625,y:.046875},{x:.265625,y:.046875},{x:.296875,y:.046875},{x:.296875,y:.046875},{x:.328125,y:.046875},{x:.328125,y:.046875},{x:.359375,y:.046875},{x:.359375,y:.046875},{x:.390625,y:.046875},{x:.390625,y:.046875},{x:.421875,y:.046875},{x:.421875,y:.046875},{x:.453125,y:.046875},{x:.453125,y:.046875},{x:.484375,y:.046875},{x:.484375,y:.046875},{x:.515625,y:.046875},{x:.515625,y:.046875},{x:.546875,y:.046875},{x:.546875,y:.046875},{x:.578125,y:.046875},{x:.578125,y:.046875},{x:.609375,y:.046875},{x:.609375,y:.046875},{x:.640625,y:.046875},{x:.640625,y:.046875},{x:.671875,y:.046875},{x:.671875,y:.046875},{x:.703125,y:.046875},{x:.703125,y:.046875},{x:.734375,y:.046875},{x:.734375,y:.046875},{x:.765625,y:.046875},{x:.765625,y:.046875},{x:.796875,y:.046875},{x:.796875,y:.046875},{x:.828125,y:.046875},{x:.828125,y:.046875},{x:.859375,y:.046875},{x:.859375,y:.046875},{x:.890625,y:.046875},{x:.890625,y:.046875},{x:.921875,y:.046875},{x:.921875,y:.046875},{x:.953125,y:.046875},{x:.953125,y:.046875},{x:.984375,y:.046875},{x:.984375,y:.046875},{x:.015625,y:.078125},{x:.015625,y:.078125},{x:.046875,y:.078125},{x:.046875,y:.078125},{x:.078125,y:.078125},{x:.078125,y:.078125},{x:.109375,y:.078125},{x:.109375,y:.078125},{x:.140625,y:.078125},{x:.140625,y:.078125},{x:.171875,y:.078125},{x:.171875,y:.078125},{x:.203125,y:.078125},{x:.203125,y:.078125},{x:.234375,y:.078125},{x:.234375,y:.078125},{x:.265625,y:.078125},{x:.265625,y:.078125},{x:.296875,y:.078125},{x:.296875,y:.078125},{x:.328125,y:.078125},{x:.328125,y:.078125},{x:.359375,y:.078125},{x:.359375,y:.078125},{x:.390625,y:.078125},{x:.390625,y:.078125},{x:.421875,y:.078125},{x:.421875,y:.078125},{x:.453125,y:.078125},{x:.453125,y:.078125},{x:.484375,y:.078125},{x:.484375,y:.078125},{x:.515625,y:.078125},{x:.515625,y:.078125},{x:.546875,y:.078125},{x:.546875,y:.078125},{x:.578125,y:.078125},{x:.578125,y:.078125},{x:.609375,y:.078125},{x:.609375,y:.078125},{x:.640625,y:.078125},{x:.640625,y:.078125},{x:.671875,y:.078125},{x:.671875,y:.078125},{x:.703125,y:.078125},{x:.703125,y:.078125},{x:.734375,y:.078125},{x:.734375,y:.078125},{x:.765625,y:.078125},{x:.765625,y:.078125},{x:.796875,y:.078125},{x:.796875,y:.078125},{x:.828125,y:.078125},{x:.828125,y:.078125},{x:.859375,y:.078125},{x:.859375,y:.078125},{x:.890625,y:.078125},{x:.890625,y:.078125},{x:.921875,y:.078125},{x:.921875,y:.078125},{x:.953125,y:.078125},{x:.953125,y:.078125},{x:.984375,y:.078125},{x:.984375,y:.078125},{x:.015625,y:.109375},{x:.015625,y:.109375},{x:.046875,y:.109375},{x:.046875,y:.109375},{x:.078125,y:.109375},{x:.078125,y:.109375},{x:.109375,y:.109375},{x:.109375,y:.109375},{x:.140625,y:.109375},{x:.140625,y:.109375},{x:.171875,y:.109375},{x:.171875,y:.109375},{x:.203125,y:.109375},{x:.203125,y:.109375},{x:.234375,y:.109375},{x:.234375,y:.109375},{x:.265625,y:.109375},{x:.265625,y:.109375},{x:.296875,y:.109375},{x:.296875,y:.109375},{x:.328125,y:.109375},{x:.328125,y:.109375},{x:.359375,y:.109375},{x:.359375,y:.109375},{x:.390625,y:.109375},{x:.390625,y:.109375},{x:.421875,y:.109375},{x:.421875,y:.109375},{x:.453125,y:.109375},{x:.453125,y:.109375},{x:.484375,y:.109375},{x:.484375,y:.109375},{x:.515625,y:.109375},{x:.515625,y:.109375},{x:.546875,y:.109375},{x:.546875,y:.109375},{x:.578125,y:.109375},{x:.578125,y:.109375},{x:.609375,y:.109375},{x:.609375,y:.109375},{x:.640625,y:.109375},{x:.640625,y:.109375},{x:.671875,y:.109375},{x:.671875,y:.109375},{x:.703125,y:.109375},{x:.703125,y:.109375},{x:.734375,y:.109375},{x:.734375,y:.109375},{x:.765625,y:.109375},{x:.765625,y:.109375},{x:.796875,y:.109375},{x:.796875,y:.109375},{x:.828125,y:.109375},{x:.828125,y:.109375},{x:.859375,y:.109375},{x:.859375,y:.109375},{x:.890625,y:.109375},{x:.890625,y:.109375},{x:.921875,y:.109375},{x:.921875,y:.109375},{x:.953125,y:.109375},{x:.953125,y:.109375},{x:.984375,y:.109375},{x:.984375,y:.109375},{x:.015625,y:.140625},{x:.015625,y:.140625},{x:.046875,y:.140625},{x:.046875,y:.140625},{x:.078125,y:.140625},{x:.078125,y:.140625},{x:.109375,y:.140625},{x:.109375,y:.140625},{x:.140625,y:.140625},{x:.140625,y:.140625},{x:.171875,y:.140625},{x:.171875,y:.140625},{x:.203125,y:.140625},{x:.203125,y:.140625},{x:.234375,y:.140625},{x:.234375,y:.140625},{x:.265625,y:.140625},{x:.265625,y:.140625},{x:.296875,y:.140625},{x:.296875,y:.140625},{x:.328125,y:.140625},{x:.328125,y:.140625},{x:.359375,y:.140625},{x:.359375,y:.140625},{x:.390625,y:.140625},{x:.390625,y:.140625},{x:.421875,y:.140625},{x:.421875,y:.140625},{x:.453125,y:.140625},{x:.453125,y:.140625},{x:.484375,y:.140625},{x:.484375,y:.140625},{x:.515625,y:.140625},{x:.515625,y:.140625},{x:.546875,y:.140625},{x:.546875,y:.140625},{x:.578125,y:.140625},{x:.578125,y:.140625},{x:.609375,y:.140625},{x:.609375,y:.140625},{x:.640625,y:.140625},{x:.640625,y:.140625},{x:.671875,y:.140625},{x:.671875,y:.140625},{x:.703125,y:.140625},{x:.703125,y:.140625},{x:.734375,y:.140625},{x:.734375,y:.140625},{x:.765625,y:.140625},{x:.765625,y:.140625},{x:.796875,y:.140625},{x:.796875,y:.140625},{x:.828125,y:.140625},{x:.828125,y:.140625},{x:.859375,y:.140625},{x:.859375,y:.140625},{x:.890625,y:.140625},{x:.890625,y:.140625},{x:.921875,y:.140625},{x:.921875,y:.140625},{x:.953125,y:.140625},{x:.953125,y:.140625},{x:.984375,y:.140625},{x:.984375,y:.140625},{x:.015625,y:.171875},{x:.015625,y:.171875},{x:.046875,y:.171875},{x:.046875,y:.171875},{x:.078125,y:.171875},{x:.078125,y:.171875},{x:.109375,y:.171875},{x:.109375,y:.171875},{x:.140625,y:.171875},{x:.140625,y:.171875},{x:.171875,y:.171875},{x:.171875,y:.171875},{x:.203125,y:.171875},{x:.203125,y:.171875},{x:.234375,y:.171875},{x:.234375,y:.171875},{x:.265625,y:.171875},{x:.265625,y:.171875},{x:.296875,y:.171875},{x:.296875,y:.171875},{x:.328125,y:.171875},{x:.328125,y:.171875},{x:.359375,y:.171875},{x:.359375,y:.171875},{x:.390625,y:.171875},{x:.390625,y:.171875},{x:.421875,y:.171875},{x:.421875,y:.171875},{x:.453125,y:.171875},{x:.453125,y:.171875},{x:.484375,y:.171875},{x:.484375,y:.171875},{x:.515625,y:.171875},{x:.515625,y:.171875},{x:.546875,y:.171875},{x:.546875,y:.171875},{x:.578125,y:.171875},{x:.578125,y:.171875},{x:.609375,y:.171875},{x:.609375,y:.171875},{x:.640625,y:.171875},{x:.640625,y:.171875},{x:.671875,y:.171875},{x:.671875,y:.171875},{x:.703125,y:.171875},{x:.703125,y:.171875},{x:.734375,y:.171875},{x:.734375,y:.171875},{x:.765625,y:.171875},{x:.765625,y:.171875},{x:.796875,y:.171875},{x:.796875,y:.171875},{x:.828125,y:.171875},{x:.828125,y:.171875},{x:.859375,y:.171875},{x:.859375,y:.171875},{x:.890625,y:.171875},{x:.890625,y:.171875},{x:.921875,y:.171875},{x:.921875,y:.171875},{x:.953125,y:.171875},{x:.953125,y:.171875},{x:.984375,y:.171875},{x:.984375,y:.171875},{x:.015625,y:.203125},{x:.015625,y:.203125},{x:.046875,y:.203125},{x:.046875,y:.203125},{x:.078125,y:.203125},{x:.078125,y:.203125},{x:.109375,y:.203125},{x:.109375,y:.203125},{x:.140625,y:.203125},{x:.140625,y:.203125},{x:.171875,y:.203125},{x:.171875,y:.203125},{x:.203125,y:.203125},{x:.203125,y:.203125},{x:.234375,y:.203125},{x:.234375,y:.203125},{x:.265625,y:.203125},{x:.265625,y:.203125},{x:.296875,y:.203125},{x:.296875,y:.203125},{x:.328125,y:.203125},{x:.328125,y:.203125},{x:.359375,y:.203125},{x:.359375,y:.203125},{x:.390625,y:.203125},{x:.390625,y:.203125},{x:.421875,y:.203125},{x:.421875,y:.203125},{x:.453125,y:.203125},{x:.453125,y:.203125},{x:.484375,y:.203125},{x:.484375,y:.203125},{x:.515625,y:.203125},{x:.515625,y:.203125},{x:.546875,y:.203125},{x:.546875,y:.203125},{x:.578125,y:.203125},{x:.578125,y:.203125},{x:.609375,y:.203125},{x:.609375,y:.203125},{x:.640625,y:.203125},{x:.640625,y:.203125},{x:.671875,y:.203125},{x:.671875,y:.203125},{x:.703125,y:.203125},{x:.703125,y:.203125},{x:.734375,y:.203125},{x:.734375,y:.203125},{x:.765625,y:.203125},{x:.765625,y:.203125},{x:.796875,y:.203125},{x:.796875,y:.203125},{x:.828125,y:.203125},{x:.828125,y:.203125},{x:.859375,y:.203125},{x:.859375,y:.203125},{x:.890625,y:.203125},{x:.890625,y:.203125},{x:.921875,y:.203125},{x:.921875,y:.203125},{x:.953125,y:.203125},{x:.953125,y:.203125},{x:.984375,y:.203125},{x:.984375,y:.203125},{x:.015625,y:.234375},{x:.015625,y:.234375},{x:.046875,y:.234375},{x:.046875,y:.234375},{x:.078125,y:.234375},{x:.078125,y:.234375},{x:.109375,y:.234375},{x:.109375,y:.234375},{x:.140625,y:.234375},{x:.140625,y:.234375},{x:.171875,y:.234375},{x:.171875,y:.234375},{x:.203125,y:.234375},{x:.203125,y:.234375},{x:.234375,y:.234375},{x:.234375,y:.234375},{x:.265625,y:.234375},{x:.265625,y:.234375},{x:.296875,y:.234375},{x:.296875,y:.234375},{x:.328125,y:.234375},{x:.328125,y:.234375},{x:.359375,y:.234375},{x:.359375,y:.234375},{x:.390625,y:.234375},{x:.390625,y:.234375},{x:.421875,y:.234375},{x:.421875,y:.234375},{x:.453125,y:.234375},{x:.453125,y:.234375},{x:.484375,y:.234375},{x:.484375,y:.234375},{x:.515625,y:.234375},{x:.515625,y:.234375},{x:.546875,y:.234375},{x:.546875,y:.234375},{x:.578125,y:.234375},{x:.578125,y:.234375},{x:.609375,y:.234375},{x:.609375,y:.234375},{x:.640625,y:.234375},{x:.640625,y:.234375},{x:.671875,y:.234375},{x:.671875,y:.234375},{x:.703125,y:.234375},{x:.703125,y:.234375},{x:.734375,y:.234375},{x:.734375,y:.234375},{x:.765625,y:.234375},{x:.765625,y:.234375},{x:.796875,y:.234375},{x:.796875,y:.234375},{x:.828125,y:.234375},{x:.828125,y:.234375},{x:.859375,y:.234375},{x:.859375,y:.234375},{x:.890625,y:.234375},{x:.890625,y:.234375},{x:.921875,y:.234375},{x:.921875,y:.234375},{x:.953125,y:.234375},{x:.953125,y:.234375},{x:.984375,y:.234375},{x:.984375,y:.234375},{x:.015625,y:.265625},{x:.015625,y:.265625},{x:.046875,y:.265625},{x:.046875,y:.265625},{x:.078125,y:.265625},{x:.078125,y:.265625},{x:.109375,y:.265625},{x:.109375,y:.265625},{x:.140625,y:.265625},{x:.140625,y:.265625},{x:.171875,y:.265625},{x:.171875,y:.265625},{x:.203125,y:.265625},{x:.203125,y:.265625},{x:.234375,y:.265625},{x:.234375,y:.265625},{x:.265625,y:.265625},{x:.265625,y:.265625},{x:.296875,y:.265625},{x:.296875,y:.265625},{x:.328125,y:.265625},{x:.328125,y:.265625},{x:.359375,y:.265625},{x:.359375,y:.265625},{x:.390625,y:.265625},{x:.390625,y:.265625},{x:.421875,y:.265625},{x:.421875,y:.265625},{x:.453125,y:.265625},{x:.453125,y:.265625},{x:.484375,y:.265625},{x:.484375,y:.265625},{x:.515625,y:.265625},{x:.515625,y:.265625},{x:.546875,y:.265625},{x:.546875,y:.265625},{x:.578125,y:.265625},{x:.578125,y:.265625},{x:.609375,y:.265625},{x:.609375,y:.265625},{x:.640625,y:.265625},{x:.640625,y:.265625},{x:.671875,y:.265625},{x:.671875,y:.265625},{x:.703125,y:.265625},{x:.703125,y:.265625},{x:.734375,y:.265625},{x:.734375,y:.265625},{x:.765625,y:.265625},{x:.765625,y:.265625},{x:.796875,y:.265625},{x:.796875,y:.265625},{x:.828125,y:.265625},{x:.828125,y:.265625},{x:.859375,y:.265625},{x:.859375,y:.265625},{x:.890625,y:.265625},{x:.890625,y:.265625},{x:.921875,y:.265625},{x:.921875,y:.265625},{x:.953125,y:.265625},{x:.953125,y:.265625},{x:.984375,y:.265625},{x:.984375,y:.265625},{x:.015625,y:.296875},{x:.015625,y:.296875},{x:.046875,y:.296875},{x:.046875,y:.296875},{x:.078125,y:.296875},{x:.078125,y:.296875},{x:.109375,y:.296875},{x:.109375,y:.296875},{x:.140625,y:.296875},{x:.140625,y:.296875},{x:.171875,y:.296875},{x:.171875,y:.296875},{x:.203125,y:.296875},{x:.203125,y:.296875},{x:.234375,y:.296875},{x:.234375,y:.296875},{x:.265625,y:.296875},{x:.265625,y:.296875},{x:.296875,y:.296875},{x:.296875,y:.296875},{x:.328125,y:.296875},{x:.328125,y:.296875},{x:.359375,y:.296875},{x:.359375,y:.296875},{x:.390625,y:.296875},{x:.390625,y:.296875},{x:.421875,y:.296875},{x:.421875,y:.296875},{x:.453125,y:.296875},{x:.453125,y:.296875},{x:.484375,y:.296875},{x:.484375,y:.296875},{x:.515625,y:.296875},{x:.515625,y:.296875},{x:.546875,y:.296875},{x:.546875,y:.296875},{x:.578125,y:.296875},{x:.578125,y:.296875},{x:.609375,y:.296875},{x:.609375,y:.296875},{x:.640625,y:.296875},{x:.640625,y:.296875},{x:.671875,y:.296875},{x:.671875,y:.296875},{x:.703125,y:.296875},{x:.703125,y:.296875},{x:.734375,y:.296875},{x:.734375,y:.296875},{x:.765625,y:.296875},{x:.765625,y:.296875},{x:.796875,y:.296875},{x:.796875,y:.296875},{x:.828125,y:.296875},{x:.828125,y:.296875},{x:.859375,y:.296875},{x:.859375,y:.296875},{x:.890625,y:.296875},{x:.890625,y:.296875},{x:.921875,y:.296875},{x:.921875,y:.296875},{x:.953125,y:.296875},{x:.953125,y:.296875},{x:.984375,y:.296875},{x:.984375,y:.296875},{x:.015625,y:.328125},{x:.015625,y:.328125},{x:.046875,y:.328125},{x:.046875,y:.328125},{x:.078125,y:.328125},{x:.078125,y:.328125},{x:.109375,y:.328125},{x:.109375,y:.328125},{x:.140625,y:.328125},{x:.140625,y:.328125},{x:.171875,y:.328125},{x:.171875,y:.328125},{x:.203125,y:.328125},{x:.203125,y:.328125},{x:.234375,y:.328125},{x:.234375,y:.328125},{x:.265625,y:.328125},{x:.265625,y:.328125},{x:.296875,y:.328125},{x:.296875,y:.328125},{x:.328125,y:.328125},{x:.328125,y:.328125},{x:.359375,y:.328125},{x:.359375,y:.328125},{x:.390625,y:.328125},{x:.390625,y:.328125},{x:.421875,y:.328125},{x:.421875,y:.328125},{x:.453125,y:.328125},{x:.453125,y:.328125},{x:.484375,y:.328125},{x:.484375,y:.328125},{x:.515625,y:.328125},{x:.515625,y:.328125},{x:.546875,y:.328125},{x:.546875,y:.328125},{x:.578125,y:.328125},{x:.578125,y:.328125},{x:.609375,y:.328125},{x:.609375,y:.328125},{x:.640625,y:.328125},{x:.640625,y:.328125},{x:.671875,y:.328125},{x:.671875,y:.328125},{x:.703125,y:.328125},{x:.703125,y:.328125},{x:.734375,y:.328125},{x:.734375,y:.328125},{x:.765625,y:.328125},{x:.765625,y:.328125},{x:.796875,y:.328125},{x:.796875,y:.328125},{x:.828125,y:.328125},{x:.828125,y:.328125},{x:.859375,y:.328125},{x:.859375,y:.328125},{x:.890625,y:.328125},{x:.890625,y:.328125},{x:.921875,y:.328125},{x:.921875,y:.328125},{x:.953125,y:.328125},{x:.953125,y:.328125},{x:.984375,y:.328125},{x:.984375,y:.328125},{x:.015625,y:.359375},{x:.015625,y:.359375},{x:.046875,y:.359375},{x:.046875,y:.359375},{x:.078125,y:.359375},{x:.078125,y:.359375},{x:.109375,y:.359375},{x:.109375,y:.359375},{x:.140625,y:.359375},{x:.140625,y:.359375},{x:.171875,y:.359375},{x:.171875,y:.359375},{x:.203125,y:.359375},{x:.203125,y:.359375},{x:.234375,y:.359375},{x:.234375,y:.359375},{x:.265625,y:.359375},{x:.265625,y:.359375},{x:.296875,y:.359375},{x:.296875,y:.359375},{x:.328125,y:.359375},{x:.328125,y:.359375},{x:.359375,y:.359375},{x:.359375,y:.359375},{x:.390625,y:.359375},{x:.390625,y:.359375},{x:.421875,y:.359375},{x:.421875,y:.359375},{x:.453125,y:.359375},{x:.453125,y:.359375},{x:.484375,y:.359375},{x:.484375,y:.359375},{x:.515625,y:.359375},{x:.515625,y:.359375},{x:.546875,y:.359375},{x:.546875,y:.359375},{x:.578125,y:.359375},{x:.578125,y:.359375},{x:.609375,y:.359375},{x:.609375,y:.359375},{x:.640625,y:.359375},{x:.640625,y:.359375},{x:.671875,y:.359375},{x:.671875,y:.359375},{x:.703125,y:.359375},{x:.703125,y:.359375},{x:.734375,y:.359375},{x:.734375,y:.359375},{x:.765625,y:.359375},{x:.765625,y:.359375},{x:.796875,y:.359375},{x:.796875,y:.359375},{x:.828125,y:.359375},{x:.828125,y:.359375},{x:.859375,y:.359375},{x:.859375,y:.359375},{x:.890625,y:.359375},{x:.890625,y:.359375},{x:.921875,y:.359375},{x:.921875,y:.359375},{x:.953125,y:.359375},{x:.953125,y:.359375},{x:.984375,y:.359375},{x:.984375,y:.359375},{x:.015625,y:.390625},{x:.015625,y:.390625},{x:.046875,y:.390625},{x:.046875,y:.390625},{x:.078125,y:.390625},{x:.078125,y:.390625},{x:.109375,y:.390625},{x:.109375,y:.390625},{x:.140625,y:.390625},{x:.140625,y:.390625},{x:.171875,y:.390625},{x:.171875,y:.390625},{x:.203125,y:.390625},{x:.203125,y:.390625},{x:.234375,y:.390625},{x:.234375,y:.390625},{x:.265625,y:.390625},{x:.265625,y:.390625},{x:.296875,y:.390625},{x:.296875,y:.390625},{x:.328125,y:.390625},{x:.328125,y:.390625},{x:.359375,y:.390625},{x:.359375,y:.390625},{x:.390625,y:.390625},{x:.390625,y:.390625},{x:.421875,y:.390625},{x:.421875,y:.390625},{x:.453125,y:.390625},{x:.453125,y:.390625},{x:.484375,y:.390625},{x:.484375,y:.390625},{x:.515625,y:.390625},{x:.515625,y:.390625},{x:.546875,y:.390625},{x:.546875,y:.390625},{x:.578125,y:.390625},{x:.578125,y:.390625},{x:.609375,y:.390625},{x:.609375,y:.390625},{x:.640625,y:.390625},{x:.640625,y:.390625},{x:.671875,y:.390625},{x:.671875,y:.390625},{x:.703125,y:.390625},{x:.703125,y:.390625},{x:.734375,y:.390625},{x:.734375,y:.390625},{x:.765625,y:.390625},{x:.765625,y:.390625},{x:.796875,y:.390625},{x:.796875,y:.390625},{x:.828125,y:.390625},{x:.828125,y:.390625},{x:.859375,y:.390625},{x:.859375,y:.390625},{x:.890625,y:.390625},{x:.890625,y:.390625},{x:.921875,y:.390625},{x:.921875,y:.390625},{x:.953125,y:.390625},{x:.953125,y:.390625},{x:.984375,y:.390625},{x:.984375,y:.390625},{x:.015625,y:.421875},{x:.015625,y:.421875},{x:.046875,y:.421875},{x:.046875,y:.421875},{x:.078125,y:.421875},{x:.078125,y:.421875},{x:.109375,y:.421875},{x:.109375,y:.421875},{x:.140625,y:.421875},{x:.140625,y:.421875},{x:.171875,y:.421875},{x:.171875,y:.421875},{x:.203125,y:.421875},{x:.203125,y:.421875},{x:.234375,y:.421875},{x:.234375,y:.421875},{x:.265625,y:.421875},{x:.265625,y:.421875},{x:.296875,y:.421875},{x:.296875,y:.421875},{x:.328125,y:.421875},{x:.328125,y:.421875},{x:.359375,y:.421875},{x:.359375,y:.421875},{x:.390625,y:.421875},{x:.390625,y:.421875},{x:.421875,y:.421875},{x:.421875,y:.421875},{x:.453125,y:.421875},{x:.453125,y:.421875},{x:.484375,y:.421875},{x:.484375,y:.421875},{x:.515625,y:.421875},{x:.515625,y:.421875},{x:.546875,y:.421875},{x:.546875,y:.421875},{x:.578125,y:.421875},{x:.578125,y:.421875},{x:.609375,y:.421875},{x:.609375,y:.421875},{x:.640625,y:.421875},{x:.640625,y:.421875},{x:.671875,y:.421875},{x:.671875,y:.421875},{x:.703125,y:.421875},{x:.703125,y:.421875},{x:.734375,y:.421875},{x:.734375,y:.421875},{x:.765625,y:.421875},{x:.765625,y:.421875},{x:.796875,y:.421875},{x:.796875,y:.421875},{x:.828125,y:.421875},{x:.828125,y:.421875},{x:.859375,y:.421875},{x:.859375,y:.421875},{x:.890625,y:.421875},{x:.890625,y:.421875},{x:.921875,y:.421875},{x:.921875,y:.421875},{x:.953125,y:.421875},{x:.953125,y:.421875},{x:.984375,y:.421875},{x:.984375,y:.421875},{x:.015625,y:.453125},{x:.015625,y:.453125},{x:.046875,y:.453125},{x:.046875,y:.453125},{x:.078125,y:.453125},{x:.078125,y:.453125},{x:.109375,y:.453125},{x:.109375,y:.453125},{x:.140625,y:.453125},{x:.140625,y:.453125},{x:.171875,y:.453125},{x:.171875,y:.453125},{x:.203125,y:.453125},{x:.203125,y:.453125},{x:.234375,y:.453125},{x:.234375,y:.453125},{x:.265625,y:.453125},{x:.265625,y:.453125},{x:.296875,y:.453125},{x:.296875,y:.453125},{x:.328125,y:.453125},{x:.328125,y:.453125},{x:.359375,y:.453125},{x:.359375,y:.453125},{x:.390625,y:.453125},{x:.390625,y:.453125},{x:.421875,y:.453125},{x:.421875,y:.453125},{x:.453125,y:.453125},{x:.453125,y:.453125},{x:.484375,y:.453125},{x:.484375,y:.453125},{x:.515625,y:.453125},{x:.515625,y:.453125},{x:.546875,y:.453125},{x:.546875,y:.453125},{x:.578125,y:.453125},{x:.578125,y:.453125},{x:.609375,y:.453125},{x:.609375,y:.453125},{x:.640625,y:.453125},{x:.640625,y:.453125},{x:.671875,y:.453125},{x:.671875,y:.453125},{x:.703125,y:.453125},{x:.703125,y:.453125},{x:.734375,y:.453125},{x:.734375,y:.453125},{x:.765625,y:.453125},{x:.765625,y:.453125},{x:.796875,y:.453125},{x:.796875,y:.453125},{x:.828125,y:.453125},{x:.828125,y:.453125},{x:.859375,y:.453125},{x:.859375,y:.453125},{x:.890625,y:.453125},{x:.890625,y:.453125},{x:.921875,y:.453125},{x:.921875,y:.453125},{x:.953125,y:.453125},{x:.953125,y:.453125},{x:.984375,y:.453125},{x:.984375,y:.453125},{x:.015625,y:.484375},{x:.015625,y:.484375},{x:.046875,y:.484375},{x:.046875,y:.484375},{x:.078125,y:.484375},{x:.078125,y:.484375},{x:.109375,y:.484375},{x:.109375,y:.484375},{x:.140625,y:.484375},{x:.140625,y:.484375},{x:.171875,y:.484375},{x:.171875,y:.484375},{x:.203125,y:.484375},{x:.203125,y:.484375},{x:.234375,y:.484375},{x:.234375,y:.484375},{x:.265625,y:.484375},{x:.265625,y:.484375},{x:.296875,y:.484375},{x:.296875,y:.484375},{x:.328125,y:.484375},{x:.328125,y:.484375},{x:.359375,y:.484375},{x:.359375,y:.484375},{x:.390625,y:.484375},{x:.390625,y:.484375},{x:.421875,y:.484375},{x:.421875,y:.484375},{x:.453125,y:.484375},{x:.453125,y:.484375},{x:.484375,y:.484375},{x:.484375,y:.484375},{x:.515625,y:.484375},{x:.515625,y:.484375},{x:.546875,y:.484375},{x:.546875,y:.484375},{x:.578125,y:.484375},{x:.578125,y:.484375},{x:.609375,y:.484375},{x:.609375,y:.484375},{x:.640625,y:.484375},{x:.640625,y:.484375},{x:.671875,y:.484375},{x:.671875,y:.484375},{x:.703125,y:.484375},{x:.703125,y:.484375},{x:.734375,y:.484375},{x:.734375,y:.484375},{x:.765625,y:.484375},{x:.765625,y:.484375},{x:.796875,y:.484375},{x:.796875,y:.484375},{x:.828125,y:.484375},{x:.828125,y:.484375},{x:.859375,y:.484375},{x:.859375,y:.484375},{x:.890625,y:.484375},{x:.890625,y:.484375},{x:.921875,y:.484375},{x:.921875,y:.484375},{x:.953125,y:.484375},{x:.953125,y:.484375},{x:.984375,y:.484375},{x:.984375,y:.484375},{x:.015625,y:.515625},{x:.015625,y:.515625},{x:.046875,y:.515625},{x:.046875,y:.515625},{x:.078125,y:.515625},{x:.078125,y:.515625},{x:.109375,y:.515625},{x:.109375,y:.515625},{x:.140625,y:.515625},{x:.140625,y:.515625},{x:.171875,y:.515625},{x:.171875,y:.515625},{x:.203125,y:.515625},{x:.203125,y:.515625},{x:.234375,y:.515625},{x:.234375,y:.515625},{x:.265625,y:.515625},{x:.265625,y:.515625},{x:.296875,y:.515625},{x:.296875,y:.515625},{x:.328125,y:.515625},{x:.328125,y:.515625},{x:.359375,y:.515625},{x:.359375,y:.515625},{x:.390625,y:.515625},{x:.390625,y:.515625},{x:.421875,y:.515625},{x:.421875,y:.515625},{x:.453125,y:.515625},{x:.453125,y:.515625},{x:.484375,y:.515625},{x:.484375,y:.515625},{x:.515625,y:.515625},{x:.515625,y:.515625},{x:.546875,y:.515625},{x:.546875,y:.515625},{x:.578125,y:.515625},{x:.578125,y:.515625},{x:.609375,y:.515625},{x:.609375,y:.515625},{x:.640625,y:.515625},{x:.640625,y:.515625},{x:.671875,y:.515625},{x:.671875,y:.515625},{x:.703125,y:.515625},{x:.703125,y:.515625},{x:.734375,y:.515625},{x:.734375,y:.515625},{x:.765625,y:.515625},{x:.765625,y:.515625},{x:.796875,y:.515625},{x:.796875,y:.515625},{x:.828125,y:.515625},{x:.828125,y:.515625},{x:.859375,y:.515625},{x:.859375,y:.515625},{x:.890625,y:.515625},{x:.890625,y:.515625},{x:.921875,y:.515625},{x:.921875,y:.515625},{x:.953125,y:.515625},{x:.953125,y:.515625},{x:.984375,y:.515625},{x:.984375,y:.515625},{x:.015625,y:.546875},{x:.015625,y:.546875},{x:.046875,y:.546875},{x:.046875,y:.546875},{x:.078125,y:.546875},{x:.078125,y:.546875},{x:.109375,y:.546875},{x:.109375,y:.546875},{x:.140625,y:.546875},{x:.140625,y:.546875},{x:.171875,y:.546875},{x:.171875,y:.546875},{x:.203125,y:.546875},{x:.203125,y:.546875},{x:.234375,y:.546875},{x:.234375,y:.546875},{x:.265625,y:.546875},{x:.265625,y:.546875},{x:.296875,y:.546875},{x:.296875,y:.546875},{x:.328125,y:.546875},{x:.328125,y:.546875},{x:.359375,y:.546875},{x:.359375,y:.546875},{x:.390625,y:.546875},{x:.390625,y:.546875},{x:.421875,y:.546875},{x:.421875,y:.546875},{x:.453125,y:.546875},{x:.453125,y:.546875},{x:.484375,y:.546875},{x:.484375,y:.546875},{x:.515625,y:.546875},{x:.515625,y:.546875},{x:.546875,y:.546875},{x:.546875,y:.546875},{x:.578125,y:.546875},{x:.578125,y:.546875},{x:.609375,y:.546875},{x:.609375,y:.546875},{x:.640625,y:.546875},{x:.640625,y:.546875},{x:.671875,y:.546875},{x:.671875,y:.546875},{x:.703125,y:.546875},{x:.703125,y:.546875},{x:.734375,y:.546875},{x:.734375,y:.546875},{x:.765625,y:.546875},{x:.765625,y:.546875},{x:.796875,y:.546875},{x:.796875,y:.546875},{x:.828125,y:.546875},{x:.828125,y:.546875},{x:.859375,y:.546875},{x:.859375,y:.546875},{x:.890625,y:.546875},{x:.890625,y:.546875},{x:.921875,y:.546875},{x:.921875,y:.546875},{x:.953125,y:.546875},{x:.953125,y:.546875},{x:.984375,y:.546875},{x:.984375,y:.546875},{x:.015625,y:.578125},{x:.015625,y:.578125},{x:.046875,y:.578125},{x:.046875,y:.578125},{x:.078125,y:.578125},{x:.078125,y:.578125},{x:.109375,y:.578125},{x:.109375,y:.578125},{x:.140625,y:.578125},{x:.140625,y:.578125},{x:.171875,y:.578125},{x:.171875,y:.578125},{x:.203125,y:.578125},{x:.203125,y:.578125},{x:.234375,y:.578125},{x:.234375,y:.578125},{x:.265625,y:.578125},{x:.265625,y:.578125},{x:.296875,y:.578125},{x:.296875,y:.578125},{x:.328125,y:.578125},{x:.328125,y:.578125},{x:.359375,y:.578125},{x:.359375,y:.578125},{x:.390625,y:.578125},{x:.390625,y:.578125},{x:.421875,y:.578125},{x:.421875,y:.578125},{x:.453125,y:.578125},{x:.453125,y:.578125},{x:.484375,y:.578125},{x:.484375,y:.578125},{x:.515625,y:.578125},{x:.515625,y:.578125},{x:.546875,y:.578125},{x:.546875,y:.578125},{x:.578125,y:.578125},{x:.578125,y:.578125},{x:.609375,y:.578125},{x:.609375,y:.578125},{x:.640625,y:.578125},{x:.640625,y:.578125},{x:.671875,y:.578125},{x:.671875,y:.578125},{x:.703125,y:.578125},{x:.703125,y:.578125},{x:.734375,y:.578125},{x:.734375,y:.578125},{x:.765625,y:.578125},{x:.765625,y:.578125},{x:.796875,y:.578125},{x:.796875,y:.578125},{x:.828125,y:.578125},{x:.828125,y:.578125},{x:.859375,y:.578125},{x:.859375,y:.578125},{x:.890625,y:.578125},{x:.890625,y:.578125},{x:.921875,y:.578125},{x:.921875,y:.578125},{x:.953125,y:.578125},{x:.953125,y:.578125},{x:.984375,y:.578125},{x:.984375,y:.578125},{x:.015625,y:.609375},{x:.015625,y:.609375},{x:.046875,y:.609375},{x:.046875,y:.609375},{x:.078125,y:.609375},{x:.078125,y:.609375},{x:.109375,y:.609375},{x:.109375,y:.609375},{x:.140625,y:.609375},{x:.140625,y:.609375},{x:.171875,y:.609375},{x:.171875,y:.609375},{x:.203125,y:.609375},{x:.203125,y:.609375},{x:.234375,y:.609375},{x:.234375,y:.609375},{x:.265625,y:.609375},{x:.265625,y:.609375},{x:.296875,y:.609375},{x:.296875,y:.609375},{x:.328125,y:.609375},{x:.328125,y:.609375},{x:.359375,y:.609375},{x:.359375,y:.609375},{x:.390625,y:.609375},{x:.390625,y:.609375},{x:.421875,y:.609375},{x:.421875,y:.609375},{x:.453125,y:.609375},{x:.453125,y:.609375},{x:.484375,y:.609375},{x:.484375,y:.609375},{x:.515625,y:.609375},{x:.515625,y:.609375},{x:.546875,y:.609375},{x:.546875,y:.609375},{x:.578125,y:.609375},{x:.578125,y:.609375},{x:.609375,y:.609375},{x:.609375,y:.609375},{x:.640625,y:.609375},{x:.640625,y:.609375},{x:.671875,y:.609375},{x:.671875,y:.609375},{x:.703125,y:.609375},{x:.703125,y:.609375},{x:.734375,y:.609375},{x:.734375,y:.609375},{x:.765625,y:.609375},{x:.765625,y:.609375},{x:.796875,y:.609375},{x:.796875,y:.609375},{x:.828125,y:.609375},{x:.828125,y:.609375},{x:.859375,y:.609375},{x:.859375,y:.609375},{x:.890625,y:.609375},{x:.890625,y:.609375},{x:.921875,y:.609375},{x:.921875,y:.609375},{x:.953125,y:.609375},{x:.953125,y:.609375},{x:.984375,y:.609375},{x:.984375,y:.609375},{x:.015625,y:.640625},{x:.015625,y:.640625},{x:.046875,y:.640625},{x:.046875,y:.640625},{x:.078125,y:.640625},{x:.078125,y:.640625},{x:.109375,y:.640625},{x:.109375,y:.640625},{x:.140625,y:.640625},{x:.140625,y:.640625},{x:.171875,y:.640625},{x:.171875,y:.640625},{x:.203125,y:.640625},{x:.203125,y:.640625},{x:.234375,y:.640625},{x:.234375,y:.640625},{x:.265625,y:.640625},{x:.265625,y:.640625},{x:.296875,y:.640625},{x:.296875,y:.640625},{x:.328125,y:.640625},{x:.328125,y:.640625},{x:.359375,y:.640625},{x:.359375,y:.640625},{x:.390625,y:.640625},{x:.390625,y:.640625},{x:.421875,y:.640625},{x:.421875,y:.640625},{x:.453125,y:.640625},{x:.453125,y:.640625},{x:.484375,y:.640625},{x:.484375,y:.640625},{x:.515625,y:.640625},{x:.515625,y:.640625},{x:.546875,y:.640625},{x:.546875,y:.640625},{x:.578125,y:.640625},{x:.578125,y:.640625},{x:.609375,y:.640625},{x:.609375,y:.640625},{x:.640625,y:.640625},{x:.640625,y:.640625},{x:.671875,y:.640625},{x:.671875,y:.640625},{x:.703125,y:.640625},{x:.703125,y:.640625},{x:.734375,y:.640625},{x:.734375,y:.640625},{x:.765625,y:.640625},{x:.765625,y:.640625},{x:.796875,y:.640625},{x:.796875,y:.640625},{x:.828125,y:.640625},{x:.828125,y:.640625},{x:.859375,y:.640625},{x:.859375,y:.640625},{x:.890625,y:.640625},{x:.890625,y:.640625},{x:.921875,y:.640625},{x:.921875,y:.640625},{x:.953125,y:.640625},{x:.953125,y:.640625},{x:.984375,y:.640625},{x:.984375,y:.640625},{x:.015625,y:.671875},{x:.015625,y:.671875},{x:.046875,y:.671875},{x:.046875,y:.671875},{x:.078125,y:.671875},{x:.078125,y:.671875},{x:.109375,y:.671875},{x:.109375,y:.671875},{x:.140625,y:.671875},{x:.140625,y:.671875},{x:.171875,y:.671875},{x:.171875,y:.671875},{x:.203125,y:.671875},{x:.203125,y:.671875},{x:.234375,y:.671875},{x:.234375,y:.671875},{x:.265625,y:.671875},{x:.265625,y:.671875},{x:.296875,y:.671875},{x:.296875,y:.671875},{x:.328125,y:.671875},{x:.328125,y:.671875},{x:.359375,y:.671875},{x:.359375,y:.671875},{x:.390625,y:.671875},{x:.390625,y:.671875},{x:.421875,y:.671875},{x:.421875,y:.671875},{x:.453125,y:.671875},{x:.453125,y:.671875},{x:.484375,y:.671875},{x:.484375,y:.671875},{x:.515625,y:.671875},{x:.515625,y:.671875},{x:.546875,y:.671875},{x:.546875,y:.671875},{x:.578125,y:.671875},{x:.578125,y:.671875},{x:.609375,y:.671875},{x:.609375,y:.671875},{x:.640625,y:.671875},{x:.640625,y:.671875},{x:.671875,y:.671875},{x:.671875,y:.671875},{x:.703125,y:.671875},{x:.703125,y:.671875},{x:.734375,y:.671875},{x:.734375,y:.671875},{x:.765625,y:.671875},{x:.765625,y:.671875},{x:.796875,y:.671875},{x:.796875,y:.671875},{x:.828125,y:.671875},{x:.828125,y:.671875},{x:.859375,y:.671875},{x:.859375,y:.671875},{x:.890625,y:.671875},{x:.890625,y:.671875},{x:.921875,y:.671875},{x:.921875,y:.671875},{x:.953125,y:.671875},{x:.953125,y:.671875},{x:.984375,y:.671875},{x:.984375,y:.671875},{x:.015625,y:.703125},{x:.015625,y:.703125},{x:.046875,y:.703125},{x:.046875,y:.703125},{x:.078125,y:.703125},{x:.078125,y:.703125},{x:.109375,y:.703125},{x:.109375,y:.703125},{x:.140625,y:.703125},{x:.140625,y:.703125},{x:.171875,y:.703125},{x:.171875,y:.703125},{x:.203125,y:.703125},{x:.203125,y:.703125},{x:.234375,y:.703125},{x:.234375,y:.703125},{x:.265625,y:.703125},{x:.265625,y:.703125},{x:.296875,y:.703125},{x:.296875,y:.703125},{x:.328125,y:.703125},{x:.328125,y:.703125},{x:.359375,y:.703125},{x:.359375,y:.703125},{x:.390625,y:.703125},{x:.390625,y:.703125},{x:.421875,y:.703125},{x:.421875,y:.703125},{x:.453125,y:.703125},{x:.453125,y:.703125},{x:.484375,y:.703125},{x:.484375,y:.703125},{x:.515625,y:.703125},{x:.515625,y:.703125},{x:.546875,y:.703125},{x:.546875,y:.703125},{x:.578125,y:.703125},{x:.578125,y:.703125},{x:.609375,y:.703125},{x:.609375,y:.703125},{x:.640625,y:.703125},{x:.640625,y:.703125},{x:.671875,y:.703125},{x:.671875,y:.703125},{x:.703125,y:.703125},{x:.703125,y:.703125},{x:.734375,y:.703125},{x:.734375,y:.703125},{x:.765625,y:.703125},{x:.765625,y:.703125},{x:.796875,y:.703125},{x:.796875,y:.703125},{x:.828125,y:.703125},{x:.828125,y:.703125},{x:.859375,y:.703125},{x:.859375,y:.703125},{x:.890625,y:.703125},{x:.890625,y:.703125},{x:.921875,y:.703125},{x:.921875,y:.703125},{x:.953125,y:.703125},{x:.953125,y:.703125},{x:.984375,y:.703125},{x:.984375,y:.703125},{x:.015625,y:.734375},{x:.015625,y:.734375},{x:.046875,y:.734375},{x:.046875,y:.734375},{x:.078125,y:.734375},{x:.078125,y:.734375},{x:.109375,y:.734375},{x:.109375,y:.734375},{x:.140625,y:.734375},{x:.140625,y:.734375},{x:.171875,y:.734375},{x:.171875,y:.734375},{x:.203125,y:.734375},{x:.203125,y:.734375},{x:.234375,y:.734375},{x:.234375,y:.734375},{x:.265625,y:.734375},{x:.265625,y:.734375},{x:.296875,y:.734375},{x:.296875,y:.734375},{x:.328125,y:.734375},{x:.328125,y:.734375},{x:.359375,y:.734375},{x:.359375,y:.734375},{x:.390625,y:.734375},{x:.390625,y:.734375},{x:.421875,y:.734375},{x:.421875,y:.734375},{x:.453125,y:.734375},{x:.453125,y:.734375},{x:.484375,y:.734375},{x:.484375,y:.734375},{x:.515625,y:.734375},{x:.515625,y:.734375},{x:.546875,y:.734375},{x:.546875,y:.734375},{x:.578125,y:.734375},{x:.578125,y:.734375},{x:.609375,y:.734375},{x:.609375,y:.734375},{x:.640625,y:.734375},{x:.640625,y:.734375},{x:.671875,y:.734375},{x:.671875,y:.734375},{x:.703125,y:.734375},{x:.703125,y:.734375},{x:.734375,y:.734375},{x:.734375,y:.734375},{x:.765625,y:.734375},{x:.765625,y:.734375},{x:.796875,y:.734375},{x:.796875,y:.734375},{x:.828125,y:.734375},{x:.828125,y:.734375},{x:.859375,y:.734375},{x:.859375,y:.734375},{x:.890625,y:.734375},{x:.890625,y:.734375},{x:.921875,y:.734375},{x:.921875,y:.734375},{x:.953125,y:.734375},{x:.953125,y:.734375},{x:.984375,y:.734375},{x:.984375,y:.734375},{x:.015625,y:.765625},{x:.015625,y:.765625},{x:.046875,y:.765625},{x:.046875,y:.765625},{x:.078125,y:.765625},{x:.078125,y:.765625},{x:.109375,y:.765625},{x:.109375,y:.765625},{x:.140625,y:.765625},{x:.140625,y:.765625},{x:.171875,y:.765625},{x:.171875,y:.765625},{x:.203125,y:.765625},{x:.203125,y:.765625},{x:.234375,y:.765625},{x:.234375,y:.765625},{x:.265625,y:.765625},{x:.265625,y:.765625},{x:.296875,y:.765625},{x:.296875,y:.765625},{x:.328125,y:.765625},{x:.328125,y:.765625},{x:.359375,y:.765625},{x:.359375,y:.765625},{x:.390625,y:.765625},{x:.390625,y:.765625},{x:.421875,y:.765625},{x:.421875,y:.765625},{x:.453125,y:.765625},{x:.453125,y:.765625},{x:.484375,y:.765625},{x:.484375,y:.765625},{x:.515625,y:.765625},{x:.515625,y:.765625},{x:.546875,y:.765625},{x:.546875,y:.765625},{x:.578125,y:.765625},{x:.578125,y:.765625},{x:.609375,y:.765625},{x:.609375,y:.765625},{x:.640625,y:.765625},{x:.640625,y:.765625},{x:.671875,y:.765625},{x:.671875,y:.765625},{x:.703125,y:.765625},{x:.703125,y:.765625},{x:.734375,y:.765625},{x:.734375,y:.765625},{x:.765625,y:.765625},{x:.765625,y:.765625},{x:.796875,y:.765625},{x:.796875,y:.765625},{x:.828125,y:.765625},{x:.828125,y:.765625},{x:.859375,y:.765625},{x:.859375,y:.765625},{x:.890625,y:.765625},{x:.890625,y:.765625},{x:.921875,y:.765625},{x:.921875,y:.765625},{x:.953125,y:.765625},{x:.953125,y:.765625},{x:.984375,y:.765625},{x:.984375,y:.765625},{x:.015625,y:.796875},{x:.015625,y:.796875},{x:.046875,y:.796875},{x:.046875,y:.796875},{x:.078125,y:.796875},{x:.078125,y:.796875},{x:.109375,y:.796875},{x:.109375,y:.796875},{x:.140625,y:.796875},{x:.140625,y:.796875},{x:.171875,y:.796875},{x:.171875,y:.796875},{x:.203125,y:.796875},{x:.203125,y:.796875},{x:.234375,y:.796875},{x:.234375,y:.796875},{x:.265625,y:.796875},{x:.265625,y:.796875},{x:.296875,y:.796875},{x:.296875,y:.796875},{x:.328125,y:.796875},{x:.328125,y:.796875},{x:.359375,y:.796875},{x:.359375,y:.796875},{x:.390625,y:.796875},{x:.390625,y:.796875},{x:.421875,y:.796875},{x:.421875,y:.796875},{x:.453125,y:.796875},{x:.453125,y:.796875},{x:.484375,y:.796875},{x:.484375,y:.796875},{x:.515625,y:.796875},{x:.515625,y:.796875},{x:.546875,y:.796875},{x:.546875,y:.796875},{x:.578125,y:.796875},{x:.578125,y:.796875},{x:.609375,y:.796875},{x:.609375,y:.796875},{x:.640625,y:.796875},{x:.640625,y:.796875},{x:.671875,y:.796875},{x:.671875,y:.796875},{x:.703125,y:.796875},{x:.703125,y:.796875},{x:.734375,y:.796875},{x:.734375,y:.796875},{x:.765625,y:.796875},{x:.765625,y:.796875},{x:.796875,y:.796875},{x:.796875,y:.796875},{x:.828125,y:.796875},{x:.828125,y:.796875},{x:.859375,y:.796875},{x:.859375,y:.796875},{x:.890625,y:.796875},{x:.890625,y:.796875},{x:.921875,y:.796875},{x:.921875,y:.796875},{x:.953125,y:.796875},{x:.953125,y:.796875},{x:.984375,y:.796875},{x:.984375,y:.796875},{x:.015625,y:.828125},{x:.015625,y:.828125},{x:.046875,y:.828125},{x:.046875,y:.828125},{x:.078125,y:.828125},{x:.078125,y:.828125},{x:.109375,y:.828125},{x:.109375,y:.828125},{x:.140625,y:.828125},{x:.140625,y:.828125},{x:.171875,y:.828125},{x:.171875,y:.828125},{x:.203125,y:.828125},{x:.203125,y:.828125},{x:.234375,y:.828125},{x:.234375,y:.828125},{x:.265625,y:.828125},{x:.265625,y:.828125},{x:.296875,y:.828125},{x:.296875,y:.828125},{x:.328125,y:.828125},{x:.328125,y:.828125},{x:.359375,y:.828125},{x:.359375,y:.828125},{x:.390625,y:.828125},{x:.390625,y:.828125},{x:.421875,y:.828125},{x:.421875,y:.828125},{x:.453125,y:.828125},{x:.453125,y:.828125},{x:.484375,y:.828125},{x:.484375,y:.828125},{x:.515625,y:.828125},{x:.515625,y:.828125},{x:.546875,y:.828125},{x:.546875,y:.828125},{x:.578125,y:.828125},{x:.578125,y:.828125},{x:.609375,y:.828125},{x:.609375,y:.828125},{x:.640625,y:.828125},{x:.640625,y:.828125},{x:.671875,y:.828125},{x:.671875,y:.828125},{x:.703125,y:.828125},{x:.703125,y:.828125},{x:.734375,y:.828125},{x:.734375,y:.828125},{x:.765625,y:.828125},{x:.765625,y:.828125},{x:.796875,y:.828125},{x:.796875,y:.828125},{x:.828125,y:.828125},{x:.828125,y:.828125},{x:.859375,y:.828125},{x:.859375,y:.828125},{x:.890625,y:.828125},{x:.890625,y:.828125},{x:.921875,y:.828125},{x:.921875,y:.828125},{x:.953125,y:.828125},{x:.953125,y:.828125},{x:.984375,y:.828125},{x:.984375,y:.828125},{x:.015625,y:.859375},{x:.015625,y:.859375},{x:.046875,y:.859375},{x:.046875,y:.859375},{x:.078125,y:.859375},{x:.078125,y:.859375},{x:.109375,y:.859375},{x:.109375,y:.859375},{x:.140625,y:.859375},{x:.140625,y:.859375},{x:.171875,y:.859375},{x:.171875,y:.859375},{x:.203125,y:.859375},{x:.203125,y:.859375},{x:.234375,y:.859375},{x:.234375,y:.859375},{x:.265625,y:.859375},{x:.265625,y:.859375},{x:.296875,y:.859375},{x:.296875,y:.859375},{x:.328125,y:.859375},{x:.328125,y:.859375},{x:.359375,y:.859375},{x:.359375,y:.859375},{x:.390625,y:.859375},{x:.390625,y:.859375},{x:.421875,y:.859375},{x:.421875,y:.859375},{x:.453125,y:.859375},{x:.453125,y:.859375},{x:.484375,y:.859375},{x:.484375,y:.859375},{x:.515625,y:.859375},{x:.515625,y:.859375},{x:.546875,y:.859375},{x:.546875,y:.859375},{x:.578125,y:.859375},{x:.578125,y:.859375},{x:.609375,y:.859375},{x:.609375,y:.859375},{x:.640625,y:.859375},{x:.640625,y:.859375},{x:.671875,y:.859375},{x:.671875,y:.859375},{x:.703125,y:.859375},{x:.703125,y:.859375},{x:.734375,y:.859375},{x:.734375,y:.859375},{x:.765625,y:.859375},{x:.765625,y:.859375},{x:.796875,y:.859375},{x:.796875,y:.859375},{x:.828125,y:.859375},{x:.828125,y:.859375},{x:.859375,y:.859375},{x:.859375,y:.859375},{x:.890625,y:.859375},{x:.890625,y:.859375},{x:.921875,y:.859375},{x:.921875,y:.859375},{x:.953125,y:.859375},{x:.953125,y:.859375},{x:.984375,y:.859375},{x:.984375,y:.859375},{x:.015625,y:.890625},{x:.015625,y:.890625},{x:.046875,y:.890625},{x:.046875,y:.890625},{x:.078125,y:.890625},{x:.078125,y:.890625},{x:.109375,y:.890625},{x:.109375,y:.890625},{x:.140625,y:.890625},{x:.140625,y:.890625},{x:.171875,y:.890625},{x:.171875,y:.890625},{x:.203125,y:.890625},{x:.203125,y:.890625},{x:.234375,y:.890625},{x:.234375,y:.890625},{x:.265625,y:.890625},{x:.265625,y:.890625},{x:.296875,y:.890625},{x:.296875,y:.890625},{x:.328125,y:.890625},{x:.328125,y:.890625},{x:.359375,y:.890625},{x:.359375,y:.890625},{x:.390625,y:.890625},{x:.390625,y:.890625},{x:.421875,y:.890625},{x:.421875,y:.890625},{x:.453125,y:.890625},{x:.453125,y:.890625},{x:.484375,y:.890625},{x:.484375,y:.890625},{x:.515625,y:.890625},{x:.515625,y:.890625},{x:.546875,y:.890625},{x:.546875,y:.890625},{x:.578125,y:.890625},{x:.578125,y:.890625},{x:.609375,y:.890625},{x:.609375,y:.890625},{x:.640625,y:.890625},{x:.640625,y:.890625},{x:.671875,y:.890625},{x:.671875,y:.890625},{x:.703125,y:.890625},{x:.703125,y:.890625},{x:.734375,y:.890625},{x:.734375,y:.890625},{x:.765625,y:.890625},{x:.765625,y:.890625},{x:.796875,y:.890625},{x:.796875,y:.890625},{x:.828125,y:.890625},{x:.828125,y:.890625},{x:.859375,y:.890625},{x:.859375,y:.890625},{x:.890625,y:.890625},{x:.890625,y:.890625},{x:.921875,y:.890625},{x:.921875,y:.890625},{x:.953125,y:.890625},{x:.953125,y:.890625},{x:.984375,y:.890625},{x:.984375,y:.890625},{x:.015625,y:.921875},{x:.015625,y:.921875},{x:.046875,y:.921875},{x:.046875,y:.921875},{x:.078125,y:.921875},{x:.078125,y:.921875},{x:.109375,y:.921875},{x:.109375,y:.921875},{x:.140625,y:.921875},{x:.140625,y:.921875},{x:.171875,y:.921875},{x:.171875,y:.921875},{x:.203125,y:.921875},{x:.203125,y:.921875},{x:.234375,y:.921875},{x:.234375,y:.921875},{x:.265625,y:.921875},{x:.265625,y:.921875},{x:.296875,y:.921875},{x:.296875,y:.921875},{x:.328125,y:.921875},{x:.328125,y:.921875},{x:.359375,y:.921875},{x:.359375,y:.921875},{x:.390625,y:.921875},{x:.390625,y:.921875},{x:.421875,y:.921875},{x:.421875,y:.921875},{x:.453125,y:.921875},{x:.453125,y:.921875},{x:.484375,y:.921875},{x:.484375,y:.921875},{x:.515625,y:.921875},{x:.515625,y:.921875},{x:.546875,y:.921875},{x:.546875,y:.921875},{x:.578125,y:.921875},{x:.578125,y:.921875},{x:.609375,y:.921875},{x:.609375,y:.921875},{x:.640625,y:.921875},{x:.640625,y:.921875},{x:.671875,y:.921875},{x:.671875,y:.921875},{x:.703125,y:.921875},{x:.703125,y:.921875},{x:.734375,y:.921875},{x:.734375,y:.921875},{x:.765625,y:.921875},{x:.765625,y:.921875},{x:.796875,y:.921875},{x:.796875,y:.921875},{x:.828125,y:.921875},{x:.828125,y:.921875},{x:.859375,y:.921875},{x:.859375,y:.921875},{x:.890625,y:.921875},{x:.890625,y:.921875},{x:.921875,y:.921875},{x:.921875,y:.921875},{x:.953125,y:.921875},{x:.953125,y:.921875},{x:.984375,y:.921875},{x:.984375,y:.921875},{x:.015625,y:.953125},{x:.015625,y:.953125},{x:.046875,y:.953125},{x:.046875,y:.953125},{x:.078125,y:.953125},{x:.078125,y:.953125},{x:.109375,y:.953125},{x:.109375,y:.953125},{x:.140625,y:.953125},{x:.140625,y:.953125},{x:.171875,y:.953125},{x:.171875,y:.953125},{x:.203125,y:.953125},{x:.203125,y:.953125},{x:.234375,y:.953125},{x:.234375,y:.953125},{x:.265625,y:.953125},{x:.265625,y:.953125},{x:.296875,y:.953125},{x:.296875,y:.953125},{x:.328125,y:.953125},{x:.328125,y:.953125},{x:.359375,y:.953125},{x:.359375,y:.953125},{x:.390625,y:.953125},{x:.390625,y:.953125},{x:.421875,y:.953125},{x:.421875,y:.953125},{x:.453125,y:.953125},{x:.453125,y:.953125},{x:.484375,y:.953125},{x:.484375,y:.953125},{x:.515625,y:.953125},{x:.515625,y:.953125},{x:.546875,y:.953125},{x:.546875,y:.953125},{x:.578125,y:.953125},{x:.578125,y:.953125},{x:.609375,y:.953125},{x:.609375,y:.953125},{x:.640625,y:.953125},{x:.640625,y:.953125},{x:.671875,y:.953125},{x:.671875,y:.953125},{x:.703125,y:.953125},{x:.703125,y:.953125},{x:.734375,y:.953125},{x:.734375,y:.953125},{x:.765625,y:.953125},{x:.765625,y:.953125},{x:.796875,y:.953125},{x:.796875,y:.953125},{x:.828125,y:.953125},{x:.828125,y:.953125},{x:.859375,y:.953125},{x:.859375,y:.953125},{x:.890625,y:.953125},{x:.890625,y:.953125},{x:.921875,y:.953125},{x:.921875,y:.953125},{x:.953125,y:.953125},{x:.953125,y:.953125},{x:.984375,y:.953125},{x:.984375,y:.953125},{x:.015625,y:.984375},{x:.015625,y:.984375},{x:.046875,y:.984375},{x:.046875,y:.984375},{x:.078125,y:.984375},{x:.078125,y:.984375},{x:.109375,y:.984375},{x:.109375,y:.984375},{x:.140625,y:.984375},{x:.140625,y:.984375},{x:.171875,y:.984375},{x:.171875,y:.984375},{x:.203125,y:.984375},{x:.203125,y:.984375},{x:.234375,y:.984375},{x:.234375,y:.984375},{x:.265625,y:.984375},{x:.265625,y:.984375},{x:.296875,y:.984375},{x:.296875,y:.984375},{x:.328125,y:.984375},{x:.328125,y:.984375},{x:.359375,y:.984375},{x:.359375,y:.984375},{x:.390625,y:.984375},{x:.390625,y:.984375},{x:.421875,y:.984375},{x:.421875,y:.984375},{x:.453125,y:.984375},{x:.453125,y:.984375},{x:.484375,y:.984375},{x:.484375,y:.984375},{x:.515625,y:.984375},{x:.515625,y:.984375},{x:.546875,y:.984375},{x:.546875,y:.984375},{x:.578125,y:.984375},{x:.578125,y:.984375},{x:.609375,y:.984375},{x:.609375,y:.984375},{x:.640625,y:.984375},{x:.640625,y:.984375},{x:.671875,y:.984375},{x:.671875,y:.984375},{x:.703125,y:.984375},{x:.703125,y:.984375},{x:.734375,y:.984375},{x:.734375,y:.984375},{x:.765625,y:.984375},{x:.765625,y:.984375},{x:.796875,y:.984375},{x:.796875,y:.984375},{x:.828125,y:.984375},{x:.828125,y:.984375},{x:.859375,y:.984375},{x:.859375,y:.984375},{x:.890625,y:.984375},{x:.890625,y:.984375},{x:.921875,y:.984375},{x:.921875,y:.984375},{x:.953125,y:.984375},{x:.953125,y:.984375},{x:.984375,y:.984375},{x:.984375,y:.984375},{x:.03125,y:.03125},{x:.03125,y:.03125},{x:.09375,y:.03125},{x:.09375,y:.03125},{x:.15625,y:.03125},{x:.15625,y:.03125},{x:.21875,y:.03125},{x:.21875,y:.03125},{x:.28125,y:.03125},{x:.28125,y:.03125},{x:.34375,y:.03125},{x:.34375,y:.03125},{x:.40625,y:.03125},{x:.40625,y:.03125},{x:.46875,y:.03125},{x:.46875,y:.03125},{x:.53125,y:.03125},{x:.53125,y:.03125},{x:.59375,y:.03125},{x:.59375,y:.03125},{x:.65625,y:.03125},{x:.65625,y:.03125},{x:.71875,y:.03125},{x:.71875,y:.03125},{x:.78125,y:.03125},{x:.78125,y:.03125},{x:.84375,y:.03125},{x:.84375,y:.03125},{x:.90625,y:.03125},{x:.90625,y:.03125},{x:.96875,y:.03125},{x:.96875,y:.03125},{x:.03125,y:.09375},{x:.03125,y:.09375},{x:.09375,y:.09375},{x:.09375,y:.09375},{x:.15625,y:.09375},{x:.15625,y:.09375},{x:.21875,y:.09375},{x:.21875,y:.09375},{x:.28125,y:.09375},{x:.28125,y:.09375},{x:.34375,y:.09375},{x:.34375,y:.09375},{x:.40625,y:.09375},{x:.40625,y:.09375},{x:.46875,y:.09375},{x:.46875,y:.09375},{x:.53125,y:.09375},{x:.53125,y:.09375},{x:.59375,y:.09375},{x:.59375,y:.09375},{x:.65625,y:.09375},{x:.65625,y:.09375},{x:.71875,y:.09375},{x:.71875,y:.09375},{x:.78125,y:.09375},{x:.78125,y:.09375},{x:.84375,y:.09375},{x:.84375,y:.09375},{x:.90625,y:.09375},{x:.90625,y:.09375},{x:.96875,y:.09375},{x:.96875,y:.09375},{x:.03125,y:.15625},{x:.03125,y:.15625},{x:.09375,y:.15625},{x:.09375,y:.15625},{x:.15625,y:.15625},{x:.15625,y:.15625},{x:.21875,y:.15625},{x:.21875,y:.15625},{x:.28125,y:.15625},{x:.28125,y:.15625},{x:.34375,y:.15625},{x:.34375,y:.15625},{x:.40625,y:.15625},{x:.40625,y:.15625},{x:.46875,y:.15625},{x:.46875,y:.15625},{x:.53125,y:.15625},{x:.53125,y:.15625},{x:.59375,y:.15625},{x:.59375,y:.15625},{x:.65625,y:.15625},{x:.65625,y:.15625},{x:.71875,y:.15625},{x:.71875,y:.15625},{x:.78125,y:.15625},{x:.78125,y:.15625},{x:.84375,y:.15625},{x:.84375,y:.15625},{x:.90625,y:.15625},{x:.90625,y:.15625},{x:.96875,y:.15625},{x:.96875,y:.15625},{x:.03125,y:.21875},{x:.03125,y:.21875},{x:.09375,y:.21875},{x:.09375,y:.21875},{x:.15625,y:.21875},{x:.15625,y:.21875},{x:.21875,y:.21875},{x:.21875,y:.21875},{x:.28125,y:.21875},{x:.28125,y:.21875},{x:.34375,y:.21875},{x:.34375,y:.21875},{x:.40625,y:.21875},{x:.40625,y:.21875},{x:.46875,y:.21875},{x:.46875,y:.21875},{x:.53125,y:.21875},{x:.53125,y:.21875},{x:.59375,y:.21875},{x:.59375,y:.21875},{x:.65625,y:.21875},{x:.65625,y:.21875},{x:.71875,y:.21875},{x:.71875,y:.21875},{x:.78125,y:.21875},{x:.78125,y:.21875},{x:.84375,y:.21875},{x:.84375,y:.21875},{x:.90625,y:.21875},{x:.90625,y:.21875},{x:.96875,y:.21875},{x:.96875,y:.21875},{x:.03125,y:.28125},{x:.03125,y:.28125},{x:.09375,y:.28125},{x:.09375,y:.28125},{x:.15625,y:.28125},{x:.15625,y:.28125},{x:.21875,y:.28125},{x:.21875,y:.28125},{x:.28125,y:.28125},{x:.28125,y:.28125},{x:.34375,y:.28125},{x:.34375,y:.28125},{x:.40625,y:.28125},{x:.40625,y:.28125},{x:.46875,y:.28125},{x:.46875,y:.28125},{x:.53125,y:.28125},{x:.53125,y:.28125},{x:.59375,y:.28125},{x:.59375,y:.28125},{x:.65625,y:.28125},{x:.65625,y:.28125},{x:.71875,y:.28125},{x:.71875,y:.28125},{x:.78125,y:.28125},{x:.78125,y:.28125},{x:.84375,y:.28125},{x:.84375,y:.28125},{x:.90625,y:.28125},{x:.90625,y:.28125},{x:.96875,y:.28125},{x:.96875,y:.28125},{x:.03125,y:.34375},{x:.03125,y:.34375},{x:.09375,y:.34375},{x:.09375,y:.34375},{x:.15625,y:.34375},{x:.15625,y:.34375},{x:.21875,y:.34375},{x:.21875,y:.34375},{x:.28125,y:.34375},{x:.28125,y:.34375},{x:.34375,y:.34375},{x:.34375,y:.34375},{x:.40625,y:.34375},{x:.40625,y:.34375},{x:.46875,y:.34375},{x:.46875,y:.34375},{x:.53125,y:.34375},{x:.53125,y:.34375},{x:.59375,y:.34375},{x:.59375,y:.34375},{x:.65625,y:.34375},{x:.65625,y:.34375},{x:.71875,y:.34375},{x:.71875,y:.34375},{x:.78125,y:.34375},{x:.78125,y:.34375},{x:.84375,y:.34375},{x:.84375,y:.34375},{x:.90625,y:.34375},{x:.90625,y:.34375},{x:.96875,y:.34375},{x:.96875,y:.34375},{x:.03125,y:.40625},{x:.03125,y:.40625},{x:.09375,y:.40625},{x:.09375,y:.40625},{x:.15625,y:.40625},{x:.15625,y:.40625},{x:.21875,y:.40625},{x:.21875,y:.40625},{x:.28125,y:.40625},{x:.28125,y:.40625},{x:.34375,y:.40625},{x:.34375,y:.40625},{x:.40625,y:.40625},{x:.40625,y:.40625},{x:.46875,y:.40625},{x:.46875,y:.40625},{x:.53125,y:.40625},{x:.53125,y:.40625},{x:.59375,y:.40625},{x:.59375,y:.40625},{x:.65625,y:.40625},{x:.65625,y:.40625},{x:.71875,y:.40625},{x:.71875,y:.40625},{x:.78125,y:.40625},{x:.78125,y:.40625},{x:.84375,y:.40625},{x:.84375,y:.40625},{x:.90625,y:.40625},{x:.90625,y:.40625},{x:.96875,y:.40625},{x:.96875,y:.40625},{x:.03125,y:.46875},{x:.03125,y:.46875},{x:.09375,y:.46875},{x:.09375,y:.46875},{x:.15625,y:.46875},{x:.15625,y:.46875},{x:.21875,y:.46875},{x:.21875,y:.46875},{x:.28125,y:.46875},{x:.28125,y:.46875},{x:.34375,y:.46875},{x:.34375,y:.46875},{x:.40625,y:.46875},{x:.40625,y:.46875},{x:.46875,y:.46875},{x:.46875,y:.46875},{x:.53125,y:.46875},{x:.53125,y:.46875},{x:.59375,y:.46875},{x:.59375,y:.46875},{x:.65625,y:.46875},{x:.65625,y:.46875},{x:.71875,y:.46875},{x:.71875,y:.46875},{x:.78125,y:.46875},{x:.78125,y:.46875},{x:.84375,y:.46875},{x:.84375,y:.46875},{x:.90625,y:.46875},{x:.90625,y:.46875},{x:.96875,y:.46875},{x:.96875,y:.46875},{x:.03125,y:.53125},{x:.03125,y:.53125},{x:.09375,y:.53125},{x:.09375,y:.53125},{x:.15625,y:.53125},{x:.15625,y:.53125},{x:.21875,y:.53125},{x:.21875,y:.53125},{x:.28125,y:.53125},{x:.28125,y:.53125},{x:.34375,y:.53125},{x:.34375,y:.53125},{x:.40625,y:.53125},{x:.40625,y:.53125},{x:.46875,y:.53125},{x:.46875,y:.53125},{x:.53125,y:.53125},{x:.53125,y:.53125},{x:.59375,y:.53125},{x:.59375,y:.53125},{x:.65625,y:.53125},{x:.65625,y:.53125},{x:.71875,y:.53125},{x:.71875,y:.53125},{x:.78125,y:.53125},{x:.78125,y:.53125},{x:.84375,y:.53125},{x:.84375,y:.53125},{x:.90625,y:.53125},{x:.90625,y:.53125},{x:.96875,y:.53125},{x:.96875,y:.53125},{x:.03125,y:.59375},{x:.03125,y:.59375},{x:.09375,y:.59375},{x:.09375,y:.59375},{x:.15625,y:.59375},{x:.15625,y:.59375},{x:.21875,y:.59375},{x:.21875,y:.59375},{x:.28125,y:.59375},{x:.28125,y:.59375},{x:.34375,y:.59375},{x:.34375,y:.59375},{x:.40625,y:.59375},{x:.40625,y:.59375},{x:.46875,y:.59375},{x:.46875,y:.59375},{x:.53125,y:.59375},{x:.53125,y:.59375},{x:.59375,y:.59375},{x:.59375,y:.59375},{x:.65625,y:.59375},{x:.65625,y:.59375},{x:.71875,y:.59375},{x:.71875,y:.59375},{x:.78125,y:.59375},{x:.78125,y:.59375},{x:.84375,y:.59375},{x:.84375,y:.59375},{x:.90625,y:.59375},{x:.90625,y:.59375},{x:.96875,y:.59375},{x:.96875,y:.59375},{x:.03125,y:.65625},{x:.03125,y:.65625},{x:.09375,y:.65625},{x:.09375,y:.65625},{x:.15625,y:.65625},{x:.15625,y:.65625},{x:.21875,y:.65625},{x:.21875,y:.65625},{x:.28125,y:.65625},{x:.28125,y:.65625},{x:.34375,y:.65625},{x:.34375,y:.65625},{x:.40625,y:.65625},{x:.40625,y:.65625},{x:.46875,y:.65625},{x:.46875,y:.65625},{x:.53125,y:.65625},{x:.53125,y:.65625},{x:.59375,y:.65625},{x:.59375,y:.65625},{x:.65625,y:.65625},{x:.65625,y:.65625},{x:.71875,y:.65625},{x:.71875,y:.65625},{x:.78125,y:.65625},{x:.78125,y:.65625},{x:.84375,y:.65625},{x:.84375,y:.65625},{x:.90625,y:.65625},{x:.90625,y:.65625},{x:.96875,y:.65625},{x:.96875,y:.65625},{x:.03125,y:.71875},{x:.03125,y:.71875},{x:.09375,y:.71875},{x:.09375,y:.71875},{x:.15625,y:.71875},{x:.15625,y:.71875},{x:.21875,y:.71875},{x:.21875,y:.71875},{x:.28125,y:.71875},{x:.28125,y:.71875},{x:.34375,y:.71875},{x:.34375,y:.71875},{x:.40625,y:.71875},{x:.40625,y:.71875},{x:.46875,y:.71875},{x:.46875,y:.71875},{x:.53125,y:.71875},{x:.53125,y:.71875},{x:.59375,y:.71875},{x:.59375,y:.71875},{x:.65625,y:.71875},{x:.65625,y:.71875},{x:.71875,y:.71875},{x:.71875,y:.71875},{x:.78125,y:.71875},{x:.78125,y:.71875},{x:.84375,y:.71875},{x:.84375,y:.71875},{x:.90625,y:.71875},{x:.90625,y:.71875},{x:.96875,y:.71875},{x:.96875,y:.71875},{x:.03125,y:.78125},{x:.03125,y:.78125},{x:.09375,y:.78125},{x:.09375,y:.78125},{x:.15625,y:.78125},{x:.15625,y:.78125},{x:.21875,y:.78125},{x:.21875,y:.78125},{x:.28125,y:.78125},{x:.28125,y:.78125},{x:.34375,y:.78125},{x:.34375,y:.78125},{x:.40625,y:.78125},{x:.40625,y:.78125},{x:.46875,y:.78125},{x:.46875,y:.78125},{x:.53125,y:.78125},{x:.53125,y:.78125},{x:.59375,y:.78125},{x:.59375,y:.78125},{x:.65625,y:.78125},{x:.65625,y:.78125},{x:.71875,y:.78125},{x:.71875,y:.78125},{x:.78125,y:.78125},{x:.78125,y:.78125},{x:.84375,y:.78125},{x:.84375,y:.78125},{x:.90625,y:.78125},{x:.90625,y:.78125},{x:.96875,y:.78125},{x:.96875,y:.78125},{x:.03125,y:.84375},{x:.03125,y:.84375},{x:.09375,y:.84375},{x:.09375,y:.84375},{x:.15625,y:.84375},{x:.15625,y:.84375},{x:.21875,y:.84375},{x:.21875,y:.84375},{x:.28125,y:.84375},{x:.28125,y:.84375},{x:.34375,y:.84375},{x:.34375,y:.84375},{x:.40625,y:.84375},{x:.40625,y:.84375},{x:.46875,y:.84375},{x:.46875,y:.84375},{x:.53125,y:.84375},{x:.53125,y:.84375},{x:.59375,y:.84375},{x:.59375,y:.84375},{x:.65625,y:.84375},{x:.65625,y:.84375},{x:.71875,y:.84375},{x:.71875,y:.84375},{x:.78125,y:.84375},{x:.78125,y:.84375},{x:.84375,y:.84375},{x:.84375,y:.84375},{x:.90625,y:.84375},{x:.90625,y:.84375},{x:.96875,y:.84375},{x:.96875,y:.84375},{x:.03125,y:.90625},{x:.03125,y:.90625},{x:.09375,y:.90625},{x:.09375,y:.90625},{x:.15625,y:.90625},{x:.15625,y:.90625},{x:.21875,y:.90625},{x:.21875,y:.90625},{x:.28125,y:.90625},{x:.28125,y:.90625},{x:.34375,y:.90625},{x:.34375,y:.90625},{x:.40625,y:.90625},{x:.40625,y:.90625},{x:.46875,y:.90625},{x:.46875,y:.90625},{x:.53125,y:.90625},{x:.53125,y:.90625},{x:.59375,y:.90625},{x:.59375,y:.90625},{x:.65625,y:.90625},{x:.65625,y:.90625},{x:.71875,y:.90625},{x:.71875,y:.90625},{x:.78125,y:.90625},{x:.78125,y:.90625},{x:.84375,y:.90625},{x:.84375,y:.90625},{x:.90625,y:.90625},{x:.90625,y:.90625},{x:.96875,y:.90625},{x:.96875,y:.90625},{x:.03125,y:.96875},{x:.03125,y:.96875},{x:.09375,y:.96875},{x:.09375,y:.96875},{x:.15625,y:.96875},{x:.15625,y:.96875},{x:.21875,y:.96875},{x:.21875,y:.96875},{x:.28125,y:.96875},{x:.28125,y:.96875},{x:.34375,y:.96875},{x:.34375,y:.96875},{x:.40625,y:.96875},{x:.40625,y:.96875},{x:.46875,y:.96875},{x:.46875,y:.96875},{x:.53125,y:.96875},{x:.53125,y:.96875},{x:.59375,y:.96875},{x:.59375,y:.96875},{x:.65625,y:.96875},{x:.65625,y:.96875},{x:.71875,y:.96875},{x:.71875,y:.96875},{x:.78125,y:.96875},{x:.78125,y:.96875},{x:.84375,y:.96875},{x:.84375,y:.96875},{x:.90625,y:.96875},{x:.90625,y:.96875},{x:.96875,y:.96875},{x:.96875,y:.96875},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375}];var C2=class{constructor(t){w(this,"model");w(this,"anchors");w(this,"anchorsTensor");w(this,"inputSize");w(this,"inputSizeTensor");w(this,"doubleInputSizeTensor");this.model=t,this.anchors=m3.map(o=>[o.x,o.y]),this.anchorsTensor=A.tensor2d(this.anchors),this.inputSize=this.model&&this.model.inputs&&this.model.inputs[0].shape?this.model.inputs[0].shape[2]:0,this.inputSizeTensor=A.tensor1d([this.inputSize,this.inputSize]),this.doubleInputSizeTensor=A.tensor1d([this.inputSize*2,this.inputSize*2])}normalizeBoxes(t){let o={};o.boxOffsets=A.slice(t,[0,0],[-1,2]),o.boxSizes=A.slice(t,[0,2],[-1,2]),o.div=A.div(o.boxOffsets,this.inputSizeTensor),o.boxCenterPoints=A.add(o.div,this.anchorsTensor),o.halfBoxSizes=A.div(o.boxSizes,this.doubleInputSizeTensor),o.sub=A.sub(o.boxCenterPoints,o.halfBoxSizes),o.startPoints=A.mul(o.sub,this.inputSizeTensor),o.add=A.add(o.boxCenterPoints,o.halfBoxSizes),o.endPoints=A.mul(o.add,this.inputSizeTensor);let n=A.concat2d([o.startPoints,o.endPoints],1);return Object.keys(o).forEach(r=>A.dispose(o[r])),n}normalizeLandmarks(t,o){let n={};n.reshape=A.reshape(t,[-1,7,2]),n.div=A.div(n.reshape,this.inputSizeTensor),n.landmarks=A.add(n.div,this.anchors[o]);let r=A.mul(n.landmarks,this.inputSizeTensor);return Object.keys(n).forEach(s=>A.dispose(n[s])),r}async predict(t,o){let n={};n.resize=A.image.resizeBilinear(t,[this.inputSize,this.inputSize]),n.div=A.div(n.resize,G.tf127),n.image=A.sub(n.div,G.tf1),n.batched=this.model.execute(n.image),n.predictions=A.squeeze(n.batched),n.slice=A.slice(n.predictions,[0,0],[-1,1]),n.sigmoid=A.sigmoid(n.slice),n.scores=A.squeeze(n.sigmoid);let r=await n.scores.data();n.boxes=A.slice(n.predictions,[0,1],[-1,4]),n.norm=this.normalizeBoxes(n.boxes),n.nms=await A.image.nonMaxSuppressionAsync(n.norm,n.scores,3*o.hand.maxDetected,o.hand.iouThreshold,o.hand.minConfidence);let s=await n.nms.array(),a=[];for(let i of s){let l={};l.box=A.slice(n.norm,[i,0],[1,-1]),l.slice=A.slice(n.predictions,[i,5],[1,14]),l.norm=this.normalizeLandmarks(l.slice,i),l.palmLandmarks=A.reshape(l.norm,[-1,2]);let c=await l.box.data(),d=c.slice(0,2),y=c.slice(2,4),x=await l.palmLandmarks.array(),m={startPoint:d,endPoint:y,palmLandmarks:x,confidence:r[i]},h=x3(m,[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]);a.push(h),Object.keys(l).forEach(p=>A.dispose(l[p]))}return Object.keys(n).forEach(i=>A.dispose(n[i])),a}};var Tr=5,p3=1.65,u3=[0,5,9,13,17,1,2],wr=0,kr=2,h3=0,j2=class{constructor(t,o){w(this,"handDetector");w(this,"handPoseModel");w(this,"inputSize");w(this,"storedBoxes");w(this,"skipped");w(this,"detectedHands");this.handDetector=t,this.handPoseModel=o,this.inputSize=this.handPoseModel&&this.handPoseModel.inputs[0].shape?this.handPoseModel.inputs[0].shape[2]:0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let o=t.map(a=>a[0]),n=t.map(a=>a[1]),r=[Math.min(...o),Math.min(...n)],s=[Math.max(...o),Math.max(...n)];return{startPoint:r,endPoint:s}}getBoxForPalmLandmarks(t,o){let n=t.map(s=>D5([...s,1],o)),r=this.calculateLandmarksBoundingBox(n);return z2(S2(r),Tr)}getBoxForHandLandmarks(t){let o=this.calculateLandmarksBoundingBox(t),n=z2(S2(o),p3);n.palmLandmarks=[];for(let r=0;r<u3.length;r++)n.palmLandmarks.push(t[u3[r]].slice(0,2));return n}transformRawCoords(t,o,n,r){let s=E2(o),a=[s[0]/this.inputSize,s[1]/this.inputSize,(s[0]+s[1])/this.inputSize/2],i=t.map(m=>[a[0]*(m[0]-this.inputSize/2),a[1]*(m[1]-this.inputSize/2),a[2]*m[2]]),l=V5(n,[0,0]),c=i.map(m=>[...D5(m,l),m[2]]),d=d3(r),y=[...e2(o),1],x=[$0(y,d[0]),$0(y,d[1])];return c.map(m=>[Math.trunc(m[0]+x[0]),Math.trunc(m[1]+x[1]),Math.trunc(m[2])])}async estimateHands(t,o){let n=!1,r,s=(o.hand.skipTime||0)>b()-h3,a=this.skipped<(o.hand.skipFrames||0);o.skipAllowed&&s&&a&&(r=await this.handDetector.predict(t,o),this.skipped=0),o.skipAllowed&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==o.hand.maxDetected||!o.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(n=!0));let i=[];for(let l=0;l<this.storedBoxes.length;l++){let c=this.storedBoxes[l];if(!!c)if(o.hand.landmarks){let d=o.hand.rotation?c3(c.palmLandmarks[wr],c.palmLandmarks[kr]):0,y=e2(c),x=[y[0]/t.shape[2],y[1]/t.shape[1]],m=o.hand.rotation&&T.kernels.includes("rotatewithoffset")?A.image.rotateWithOffset(t,d,0,x):t.clone(),h=V5(-d,y),p=n?this.getBoxForPalmLandmarks(c.palmLandmarks,h):c,R=y3(p,m,[this.inputSize,this.inputSize]),M=A.div(R,G.tf255);A.dispose(R),A.dispose(m);let[g,f]=this.handPoseModel.execute(M);h3=b(),A.dispose(M);let P=(await g.data())[0];if(A.dispose(g),P>=o.hand.minConfidence/4){let C=A.reshape(f,[-1,3]),k=await C.array();A.dispose(f),A.dispose(C);let I=this.transformRawCoords(k,p,d,h),j=this.getBoxForHandLandmarks(I);this.storedBoxes[l]={...j,confidence:P};let O={landmarks:I,confidence:P,boxConfidence:c.confidence,fingerConfidence:P,box:{topLeft:j.startPoint,bottomRight:j.endPoint}};i.push(O)}else this.storedBoxes[l]=null;A.dispose(f)}else{let d=z2(S2(c),p3),y={confidence:c.confidence,boxConfidence:c.confidence,fingerConfidence:0,box:{topLeft:d.startPoint,bottomRight:d.endPoint},landmarks:[]};i.push(y)}}return this.storedBoxes=this.storedBoxes.filter(l=>l!==null),this.detectedHands=i.length,i.length>o.hand.maxDetected&&(i.length=o.hand.maxDetected),i}};var d0={thumb:0,index:1,middle:2,ring:3,pinky:4,all:[0,1,2,3,4],nameMapping:{0:"thumb",1:"index",2:"middle",3:"ring",4:"pinky"},pointsMapping:{0:[[0,1],[1,2],[2,3],[3,4]],1:[[0,5],[5,6],[6,7],[7,8]],2:[[0,9],[9,10],[10,11],[11,12]],3:[[0,13],[13,14],[14,15],[15,16]],4:[[0,17],[17,18],[18,19],[19,20]]},getName:e=>d0.nameMapping[e],getPoints:e=>d0.pointsMapping[e]},te={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>te.nameMapping[e]},K={verticalUp:0,verticalDown:1,horizontalLeft:2,horizontalRight:3,diagonalUpRight:4,diagonalUpLeft:5,diagonalDownRight:6,diagonalDownLeft:7,nameMapping:{0:"verticalUp",1:"verticalDown",2:"horizontalLeft",3:"horizontalRight",4:"diagonalUpRight",5:"diagonalUpLeft",6:"diagonalDownRight",7:"diagonalDownLeft"},getName:e=>K.nameMapping[e]},ee=class{constructor(t){w(this,"name");w(this,"curls");w(this,"directions");w(this,"weights");w(this,"weightsRelative");this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}curl(t,o,n){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([o,n])}direction(t,o,n){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([o,n])}weight(t,o){this.weights[t]=o;let n=this.weights.reduce((r,s)=>r+s,0);this.weightsRelative=this.weights.map(r=>r*5/n)}matchAgainst(t,o){let n=0;for(let r in t){let s=t[r],a=this.curls[r];if(typeof a=="undefined"){n+=this.weightsRelative[r];continue}for(let[i,l]of a)if(s===i){n+=l*this.weightsRelative[r];break}}for(let r in o){let s=o[r],a=this.directions[r];if(typeof a=="undefined"){n+=this.weightsRelative[r];continue}for(let[i,l]of a)if(s===i){n+=l*this.weightsRelative[r];break}}return n/10}};var{thumb:E0,index:V0,middle:D0,ring:fe,pinky:me}=d0,{none:z0,half:zr,full:S0}=te,{verticalUp:ze,verticalDown:q7,horizontalLeft:Z5,horizontalRight:Sr,diagonalUpRight:Cr,diagonalUpLeft:Se,diagonalDownRight:U7,diagonalDownLeft:Y7}=K,oe=new ee("thumbs up");oe.curl(E0,z0,1);oe.direction(E0,ze,1);oe.direction(E0,Se,.25);oe.direction(E0,Cr,.25);for(let e of[d0.index,d0.middle,d0.ring,d0.pinky])oe.curl(e,S0,1),oe.direction(e,Z5,1),oe.direction(e,Sr,1);var e0=new ee("victory");e0.curl(E0,zr,.5);e0.curl(E0,z0,.5);e0.direction(E0,ze,1);e0.direction(E0,Se,1);e0.curl(V0,z0,1);e0.direction(V0,ze,.75);e0.direction(V0,Se,1);e0.curl(D0,z0,1);e0.direction(D0,ze,1);e0.direction(D0,Se,.75);e0.curl(fe,S0,1);e0.direction(fe,ze,.2);e0.direction(fe,Se,1);e0.direction(fe,Z5,.2);e0.curl(me,S0,1);e0.direction(me,ze,.2);e0.direction(me,Se,1);e0.direction(me,Z5,.2);e0.weight(V0,2);e0.weight(D0,2);var ne=new ee("point");ne.curl(E0,S0,1);ne.curl(V0,z0,.5);ne.curl(D0,S0,.5);ne.curl(fe,S0,.5);ne.curl(me,S0,.5);ne.weight(V0,2);ne.weight(D0,2);var re=new ee("middle finger");re.curl(E0,z0,1);re.curl(V0,S0,.5);re.curl(D0,S0,.5);re.curl(fe,S0,.5);re.curl(me,S0,.5);re.weight(V0,2);re.weight(D0,2);var Ce=new ee("open palm");Ce.curl(E0,z0,.75);Ce.curl(V0,z0,.75);Ce.curl(D0,z0,.75);Ce.curl(fe,z0,.75);Ce.curl(me,z0,.75);var b3=[oe,e0,ne,re,Ce];var jr=.7,pe={HALF_CURL_START_LIMIT:60,NO_CURL_START_LIMIT:130,DISTANCE_VOTE_POWER:1.1,SINGLE_ANGLE_VOTE_POWER:.9,TOTAL_ANGLE_VOTE_POWER:1.6};function g3(e,t,o,n){let r=(t-n)/(e-o),s=Math.atan(r)*180/Math.PI;return s<=0?s=-s:s>0&&(s=180-s),s}function P3(e,t){if(!e||!t)return[0,0];let o=g3(e[0],e[1],t[0],t[1]);if(e.length===2)return o;let n=g3(e[1],e[2],t[1],t[2]);return[o,n]}function M3(e,t=1){let o=0,n=0,r=0;return e>=75&&e<=105?o=1*t:e>=25&&e<=155?n=1*t:r=1*t,[o,n,r]}function Ir(e,t,o){let n=e[0]-t[0],r=e[0]-o[0],s=t[0]-o[0],a=e[1]-t[1],i=e[1]-o[1],l=t[1]-o[1],c=e[2]-t[2],d=e[2]-o[2],y=t[2]-o[2],x=Math.sqrt(n*n+a*a+c*c),m=Math.sqrt(r*r+i*i+d*d),h=Math.sqrt(s*s+l*l+y*y),p=(h*h+x*x-m*m)/(2*h*x);p>1?p=1:p<-1&&(p=-1);let R=Math.acos(p);R=57.2958*R%180;let M;return R>pe.NO_CURL_START_LIMIT?M=te.none:R>pe.HALF_CURL_START_LIMIT?M=te.half:M=te.full,M}function R3(e,t,o,n){let r;return n===Math.abs(e)?e>0?r=K.horizontalLeft:r=K.horizontalRight:n===Math.abs(t)?t>0?r=K.horizontalLeft:r=K.horizontalRight:o>0?r=K.horizontalLeft:r=K.horizontalRight,r}function v3(e,t,o,n){let r;return n===Math.abs(e)?e<0?r=K.verticalDown:r=K.verticalUp:n===Math.abs(t)?t<0?r=K.verticalDown:r=K.verticalUp:o<0?r=K.verticalDown:r=K.verticalUp,r}function Nr(e,t,o,n,r,s,a,i){let l,c=v3(e,t,o,n),d=R3(r,s,a,i);return c===K.verticalUp?d===K.horizontalLeft?l=K.diagonalUpLeft:l=K.diagonalUpRight:d===K.horizontalLeft?l=K.diagonalDownLeft:l=K.diagonalDownRight,l}function Or(e,t,o,n){let r=e[0]-t[0],s=e[0]-o[0],a=t[0]-o[0],i=e[1]-t[1],l=e[1]-o[1],c=t[1]-o[1],d=Math.max(Math.abs(r),Math.abs(s),Math.abs(a)),y=Math.max(Math.abs(i),Math.abs(l),Math.abs(c)),x=0,m=0,h=0,p=y/(d+1e-5);p>1.5?x+=pe.DISTANCE_VOTE_POWER:p>.66?m+=pe.DISTANCE_VOTE_POWER:h+=pe.DISTANCE_VOTE_POWER;let R=Math.sqrt(r*r+i*i),M=Math.sqrt(s*s+l*l),g=Math.sqrt(a*a+c*c),f=Math.max(R,M,g),P=e[0],C=e[1],k=o[0],I=o[1];f===R?(k=o[0],I=o[1]):f===g&&(P=t[0],C=t[1]);let F=P3([P,C],[k,I]),V=M3(F,pe.TOTAL_ANGLE_VOTE_POWER);x+=V[0],m+=V[1],h+=V[2];for(let t0 of n){let z=M3(t0,pe.SINGLE_ANGLE_VOTE_POWER);x+=z[0],m+=z[1],h+=z[2]}let Z;return x===Math.max(x,m,h)?Z=v3(l,i,c,y):h===Math.max(m,h)?Z=R3(s,r,a,d):Z=Nr(l,i,c,y,s,r,a,d),Z}function T3(e){let t=[],o=[],n=[],r=[];if(!e)return{curls:n,directions:r};for(let s of d0.all){let a=d0.getPoints(s),i=[],l=[];for(let c of a){let d=e[c[0]],y=e[c[1]],x=P3(d,y),m=x[0],h=x[1];i.push(m),l.push(h)}t.push(i),o.push(l)}for(let s of d0.all){let a=s===d0.thumb?1:0,i=d0.getPoints(s),l=e[i[a][0]],c=e[i[a+1][1]],d=e[i[3][1]],y=Ir(l,c,d),x=Or(l,c,d,t[s].slice(a));n[s]=y,r[s]=x}return{curls:n,directions:r}}function I2(e){if(!e||e.length===0)return null;let t=T3(e),o={};for(let n of d0.all)o[d0.getName(n)]={curl:te.getName(t.curls[n]),direction:K.getName(t.directions[n])};return o}function w3(e){let t=[];if(!e||e.length===0)return t;let o=T3(e);for(let n of b3){let r=n.matchAgainst(o.curls,o.directions);r>=jr&&t.push({name:n.name,confidence:r})}return t}var k3={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],palm:[0]},je,Ie,E3;async function q5(e,t){let o=await E3.estimateHands(e,t);if(!o)return[];let n=[];for(let r=0;r<o.length;r++){let s={};if(o[r].landmarks)for(let d of Object.keys(k3))s[d]=k3[d].map(y=>o[r].landmarks[y]);let a=o[r].landmarks,i=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],l=[0,0,0,0];if(a&&a.length>0){for(let d of a)d[0]<i[0]&&(i[0]=d[0]),d[1]<i[1]&&(i[1]=d[1]),d[0]>i[2]&&(i[2]=d[0]),d[1]>i[3]&&(i[3]=d[1]);i[2]-=i[0],i[3]-=i[1],l=[i[0]/(e.shape[2]||0),i[1]/(e.shape[1]||0),i[2]/(e.shape[2]||0),i[3]/(e.shape[1]||0)]}else i=o[r].box?[Math.trunc(Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.max(0,o[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,o[r].box.bottomRight[0])-Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,o[r].box.bottomRight[1])-Math.max(0,o[r].box.topLeft[1]))]:[0,0,0,0],l=[o[r].box.topLeft[0]/(e.shape[2]||0),o[r].box.topLeft[1]/(e.shape[1]||0),(o[r].box.bottomRight[0]-o[r].box.topLeft[0])/(e.shape[2]||0),(o[r].box.bottomRight[1]-o[r].box.topLeft[1])/(e.shape[1]||0)];let c=I2(a);n.push({id:r,score:Math.round(100*o[r].confidence)/100,boxScore:Math.round(100*o[r].boxConfidence)/100,fingerScore:Math.round(100*o[r].fingerConfidence)/100,label:"hand",box:i,boxRaw:l,keypoints:a,annotations:s,landmarks:c})}return n}async function U5(e){var o,n;T.initial&&(je=null,Ie=null),!je||!Ie?[je,Ie]=await Promise.all([e.hand.enabled?L((o=e.hand.detector)==null?void 0:o.modelPath):null,e.hand.landmarks?L((n=e.hand.skeleton)==null?void 0:n.modelPath):null]):(e.debug&&u("cached model:",je.modelUrl),e.debug&&u("cached model:",Ie.modelUrl));let t=new C2(je);return E3=new j2(t,Ie),[je,Ie]}var n0=[null,null],Lr=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],Ae=[[0,0],[0,0]],Wr=["hand","fist","pinch","point","face","tip","pinchtip"],S3=4,C3=1.6,Fr=512,Gr=1.4,N2=Number.MAX_SAFE_INTEGER,Y5=0,Z0=[0,0],Q={boxes:[],hands:[]},j3={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],base:[0],palm:[0,17,13,9,5,1,0]};async function I3(e){var t;if(T.initial&&(n0[0]=null),n0[0])e.debug&&u("cached model:",n0[0].modelUrl);else{O2(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),n0[0]=await L((t=e.hand.detector)==null?void 0:t.modelPath);let o=Object.values(n0[0].modelSignature.inputs);Ae[0][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ae[0][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return n0[0]}async function N3(e){var t;if(T.initial&&(n0[1]=null),n0[1])e.debug&&u("cached model:",n0[1].modelUrl);else{n0[1]=await L((t=e.hand.skeleton)==null?void 0:t.modelPath);let o=Object.values(n0[1].modelSignature.inputs);Ae[1][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ae[1][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return n0[1]}async function Br(e,t){let o=[];if(!e||!n0[0])return o;let n={},r=(e.shape[2]||1)/(e.shape[1]||1),s=Math.min(Math.round((e.shape[1]||0)/8)*8,Fr),a=Math.round(s*r/8)*8;n.resize=A.image.resizeBilinear(e,[s,a]),n.cast=A.cast(n.resize,"int32"),[n.rawScores,n.rawBoxes]=await n0[0].executeAsync(n.cast,Lr),n.boxes=A.squeeze(n.rawBoxes,[0,2]),n.scores=A.squeeze(n.rawScores,[0]);let i=A.unstack(n.scores,1);A.dispose(i[S3]),i.splice(S3,1),n.filtered=A.stack(i,1),A.dispose(i),n.max=A.max(n.filtered,1),n.argmax=A.argMax(n.filtered,1);let l=0;n.nms=await A.image.nonMaxSuppressionAsync(n.boxes,n.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let c=await n.nms.data(),d=await n.max.data(),y=await n.argmax.data();for(let x of Array.from(c)){let m=A.slice(n.boxes,x,1),h=await m.data();A.dispose(m);let p=[h[1],h[0],h[3]-h[1],h[2]-h[0]],R=M2(p,Gr),M=[Math.trunc(p[0]*Z0[0]),Math.trunc(p[1]*Z0[1]),Math.trunc(p[2]*Z0[0]),Math.trunc(p[3]*Z0[1])],g=d[x],f=Wr[y[x]],P={id:l++,score:g,box:M,boxRaw:R,label:f};o.push(P)}return Object.keys(n).forEach(x=>A.dispose(n[x])),o.sort((x,m)=>m.score-x.score),o.length>(t.hand.maxDetected||1)&&(o.length=t.hand.maxDetected||1),o}async function K5(e,t,o){let n={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&n0[1]&&o.hand.landmarks&&t.score>(o.hand.minConfidence||0)){let r={},s=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=A.image.cropAndResize(e,[s],[0],[Ae[1][0],Ae[1][1]],"bilinear"),r.div=A.div(r.crop,G.tf255),[r.score,r.keypoints]=n0[1].execute(r.div,["Identity_1","Identity"]);let a=(await r.score.data())[0],i=(100-Math.trunc(100/(1+Math.exp(a))))/100;if(i>=(o.hand.minConfidence||0)){n.fingerScore=i,r.reshaped=A.reshape(r.keypoints,[-1,3]);let d=(await r.reshaped.array()).map(y=>[y[0]/Ae[1][1],y[1]/Ae[1][0],y[2]||0]).map(y=>[y[0]*t.boxRaw[2],y[1]*t.boxRaw[3],y[2]||0]);n.keypoints=d.map(y=>[Z0[0]*(y[0]+t.boxRaw[0]),Z0[1]*(y[1]+t.boxRaw[1]),y[2]||0]),n.landmarks=I2(n.keypoints);for(let y of Object.keys(j3))n.annotations[y]=j3[y].map(x=>n.landmarks&&n.keypoints[x]?n.keypoints[x]:null)}Object.keys(r).forEach(l=>A.dispose(r[l]))}return n}async function J5(e,t){var r,s;if(!n0[0]||!n0[1]||!((r=n0[0])!=null&&r.inputs[0].shape)||!((s=n0[1])!=null&&s.inputs[0].shape))return[];Z0=[e.shape[2]||0,e.shape[1]||0],N2++;let o=(t.hand.skipTime||0)>b()-Y5,n=N2<(t.hand.skipFrames||0);return t.skipAllowed&&o&&n?Q.hands:new Promise(async a=>{let i=3*(t.hand.skipTime||0)>b()-Y5,l=N2<3*(t.hand.skipFrames||0);t.skipAllowed&&Q.hands.length===t.hand.maxDetected?Q.hands=await Promise.all(Q.boxes.map(d=>K5(e,d,t))):t.skipAllowed&&i&&l&&Q.hands.length>0?Q.hands=await Promise.all(Q.boxes.map(d=>K5(e,d,t))):(Q.boxes=await Br(e,t),Y5=b(),Q.hands=await Promise.all(Q.boxes.map(d=>K5(e,d,t))),N2=0);let c=[...Q.boxes];if(Q.boxes.length=0,t.cacheSensitivity>0)for(let d=0;d<Q.hands.length;d++){let y=Tt(Q.hands[d].keypoints,Z0);if(y.box[2]/(e.shape[2]||1)>.05&&y.box[3]/(e.shape[1]||1)>.05&&Q.hands[d].fingerScore&&Q.hands[d].fingerScore>(t.hand.minConfidence||0)){let x=M2(y.box,C3),m=M2(y.boxRaw,C3);Q.boxes.push({...c[d],box:x,boxRaw:m})}}for(let d=0;d<Q.hands.length;d++){let y=G0(Q.hands[d].keypoints,Z0);Q.hands[d].box=y.box,Q.hands[d].boxRaw=y.boxRaw}a(Q.hands)})}var i0,L2=[],Q5=Number.MAX_SAFE_INTEGER,L3=0,W3=0;async function F3(e){var t;return T.initial&&(i0=null),i0?e.debug&&u("cached model:",i0.modelUrl):i0=await L((t=e.face.liveness)==null?void 0:t.modelPath),i0}async function _5(e,t,o,n){var a,i;if(!i0)return 0;let r=(((a=t.face.liveness)==null?void 0:a.skipTime)||0)>b()-W3,s=Q5<(((i=t.face.liveness)==null?void 0:i.skipFrames)||0);return t.skipAllowed&&r&&s&&L3===n&&L2[o]?(Q5++,L2[o]):(Q5=0,new Promise(async l=>{let c=A.image.resizeBilinear(e,[i0!=null&&i0.inputs[0].shape?i0.inputs[0].shape[2]:0,i0!=null&&i0.inputs[0].shape?i0.inputs[0].shape[1]:0],!1),d=i0==null?void 0:i0.execute(c),y=(await d.data())[0];L2[o]=Math.round(100*y)/100,L3=n,W3=b(),A.dispose([c,d]),l(L2[o])}))}var t2={};U0(t2,{connected:()=>F2,horizontal:()=>$5,kpt:()=>W2,relative:()=>t1,vertical:()=>e1});var W2=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],$5=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],e1=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],t1=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],F2={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var B3=.005,h0={keypoints:[],padding:[[0,0],[0,0],[0,0],[0,0]]};function o1(e){for(let t of $5){let o=e.keypoints.findIndex(r=>r.part===t[0]),n=e.keypoints.findIndex(r=>r.part===t[1]);if(e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[0]<e.keypoints[n].position[0]){let r=e.keypoints[o];e.keypoints[o]=e.keypoints[n],e.keypoints[n]=r}}for(let t of e1){let o=e.keypoints.findIndex(r=>r&&r.part===t[0]),n=e.keypoints.findIndex(r=>r&&r.part===t[1]);e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[1]<e.keypoints[n].position[1]&&e.keypoints.splice(o,1)}for(let[t,o]of t1){let n=e.keypoints.findIndex(c=>c&&c.part===t[0]),r=e.keypoints.findIndex(c=>c&&c.part===t[1]),s=e.keypoints.findIndex(c=>c&&c.part===o[0]),a=e.keypoints.findIndex(c=>c&&c.part===o[1]);if(!e.keypoints[s]||!e.keypoints[a])continue;let i=e.keypoints[n]?[Math.abs(e.keypoints[s].position[0]-e.keypoints[n].position[0]),Math.abs(e.keypoints[a].position[0]-e.keypoints[n].position[0])]:[0,0],l=e.keypoints[r]?[Math.abs(e.keypoints[a].position[0]-e.keypoints[r].position[0]),Math.abs(e.keypoints[s].position[0]-e.keypoints[r].position[0])]:[0,0];if(i[0]>i[1]||l[0]>l[1]){let c=e.keypoints[n];e.keypoints[n]=e.keypoints[r],e.keypoints[r]=c}}}function H3(e){for(let t=0;t<e.length;t++)if(e[t]&&h0.keypoints[t]){let o=[Math.abs(e[t].positionRaw[0]-h0.keypoints[t].positionRaw[0]),Math.abs(e[t].positionRaw[1]-h0.keypoints[t].positionRaw[1])];o[0]<B3&&o[1]<B3?e[t]=h0.keypoints[t]:h0.keypoints[t]=e[t]}else h0.keypoints[t]=e[t];return e}function V3(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;h0.padding=[[0,0],[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0],[0,0]],o.pad=A.pad(e,h0.padding),o.resize=A.image.resizeBilinear(o.pad,[t,t]);let n=A.cast(o.resize,"int32");return Object.keys(o).forEach(r=>A.dispose(o[r])),n}function D3(e,t){e.keypoints=e.keypoints.filter(n=>n&&n.position);for(let n of e.keypoints)n.position=[n.position[0]*(t[0]+h0.padding[2][0]+h0.padding[2][1])/t[0]-h0.padding[2][0],n.position[1]*(t[1]+h0.padding[1][0]+h0.padding[1][1])/t[1]-h0.padding[1][0]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1]];let o=G0(e.keypoints.map(n=>n.position),t);return e.box=o.box,e.boxRaw=o.boxRaw,e}var b0,G2=0,n1=Number.MAX_SAFE_INTEGER,ue={boxes:[],bodies:[],last:0};async function Z3(e){return T.initial&&(b0=null),b0?e.debug&&u("cached model:",b0.modelUrl):(O2(["size"],e),b0=await L(e.body.modelPath)),G2=b0.inputs[0].shape?b0.inputs[0].shape[2]:0,G2<64&&(G2=256),b0}async function Vr(e,t,o){let n=e[0][0],r=[],s=0;for(let d=0;d<n.length;d++)if(s=n[d][2],s>t.body.minConfidence){let y=[n[d][1],n[d][0]];r.push({score:Math.round(100*s)/100,part:W2[d],positionRaw:y,position:[Math.round((o.shape[2]||0)*y[0]),Math.round((o.shape[1]||0)*y[1])]})}s=r.reduce((d,y)=>y.score>d?y.score:d,0);let a=[],i=G0(r.map(d=>d.position),[o.shape[2],o.shape[1]]),l={};for(let[d,y]of Object.entries(F2)){let x=[];for(let m=0;m<y.length-1;m++){let h=r.find(R=>R.part===y[m]),p=r.find(R=>R.part===y[m+1]);h&&p&&h.score>(t.body.minConfidence||0)&&p.score>(t.body.minConfidence||0)&&x.push([h.position,p.position])}l[d]=x}let c={id:0,score:s,box:i.box,boxRaw:i.boxRaw,keypoints:r,annotations:l};return o1(c),a.push(c),a}async function Dr(e,t,o){let n=[];for(let r=0;r<e[0].length;r++){let s=e[0][r],a=Math.round(100*s[51+4])/100;if(a>t.body.minConfidence){let i=[];for(let y=0;y<17;y++){let x=s[3*y+2];if(x>t.body.minConfidence){let m=[s[3*y+1],s[3*y+0]];i.push({part:W2[y],score:Math.round(100*x)/100,positionRaw:m,position:[Math.round((o.shape[2]||0)*m[0]),Math.round((o.shape[1]||0)*m[1])]})}}let l=G0(i.map(y=>y.position),[o.shape[2],o.shape[1]]),c={};for(let[y,x]of Object.entries(F2)){let m=[];for(let h=0;h<x.length-1;h++){let p=i.find(M=>M.part===x[h]),R=i.find(M=>M.part===x[h+1]);p&&R&&p.score>(t.body.minConfidence||0)&&R.score>(t.body.minConfidence||0)&&m.push([p.position,R.position])}c[y]=m}let d={id:r,score:a,box:l.box,boxRaw:l.boxRaw,keypoints:[...i],annotations:c};o1(d),n.push(d)}}return n.sort((r,s)=>s.score-r.score),n.length>t.body.maxDetected&&(n.length=t.body.maxDetected),n}async function r1(e,t){if(!b0||!(b0!=null&&b0.inputs[0].shape))return[];t.skipAllowed||(ue.boxes.length=0),n1++;let o=(t.body.skipTime||0)>b()-ue.last,n=n1<(t.body.skipFrames||0);return t.skipAllowed&&o&&n?ue.bodies:new Promise(async r=>{let s={};n1=0,s.input=V3(e,G2),s.res=b0==null?void 0:b0.execute(s.input),ue.last=b();let a=await s.res.array();ue.bodies=s.res.shape[2]===17?await Vr(a,t,e):await Dr(a,t,e);for(let i of ue.bodies)D3(i,[e.shape[2]||1,e.shape[1]||1]),H3(i.keypoints);Object.keys(s).forEach(i=>A.dispose(s[i])),r(ue.bodies)})}var Ne,B2=[],q3=0,A1=Number.MAX_SAFE_INTEGER,V2=0,H2=2.5;async function U3(e){if(!Ne||T.initial){Ne=await L(e.object.modelPath);let t=Object.values(Ne.modelSignature.inputs);V2=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&u("cached model:",Ne.modelUrl);return Ne}async function Zr(e,t,o){let n=0,r=[];for(let l of[1,2,4])A.tidy(async()=>{let c=l*13,d=A.squeeze(e.find(p=>p.shape[1]===c**2&&(p.shape[2]||0)===we.length)),y=A.squeeze(e.find(p=>p.shape[1]===c**2&&(p.shape[2]||0)<we.length)),m=await y.reshape([-1,4,y.shape[1]/4]).argMax(2).array(),h=await d.array();for(let p=0;p<d.shape[0];p++)for(let R=0;R<d.shape[1];R++){let M=h[p][R];if(M>(o.object.minConfidence||0)&&R!==61){let g=(.5+Math.trunc(p%c))/c,f=(.5+Math.trunc(p/c))/c,P=m[p].map(Z=>Z*(c/l/V2)),[C,k]=[g-H2/l*P[0],f-H2/l*P[1]],[I,j]=[g+H2/l*P[2]-C,f+H2/l*P[3]-k],O=[C,k,I,j];O=O.map(Z=>Math.max(0,Math.min(Z,1)));let F=[O[0]*t[0],O[1]*t[1],O[2]*t[0],O[3]*t[1]],V={id:n++,score:Math.round(100*M)/100,class:R+1,label:we[R].label,box:F.map(Z=>Math.trunc(Z)),boxRaw:O};r.push(V)}}});e.forEach(l=>A.dispose(l));let s=r.map(l=>[l.boxRaw[1],l.boxRaw[0],l.boxRaw[3],l.boxRaw[2]]),a=r.map(l=>l.score),i=[];if(s&&s.length>0){let l=await A.image.nonMaxSuppressionAsync(s,a,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence);i=await l.data(),A.dispose(l)}return r=r.filter((l,c)=>i.includes(c)).sort((l,c)=>c.score-l.score),r}async function s1(e,t){let o=(t.object.skipTime||0)>b()-q3,n=A1<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&B2.length>0?(A1++,B2):(A1=0,!T.kernels.includes("mod")||!T.kernels.includes("sparsetodense")?B2:new Promise(async r=>{let s=[e.shape[2]||0,e.shape[1]||0],a=A.image.resizeBilinear(e,[V2,V2],!1),i=A.div(a,G.tf255),l=i.transpose([0,3,1,2]);A.dispose(i),A.dispose(a);let c;t.object.enabled&&(c=Ne.execute(l)),q3=b(),A.dispose(l);let d=await Zr(c,s,t);B2=d,r(d)}))}var n2=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],Xr=n2.length,o2=n2.reduce((e,t,o)=>(e[t]=o,e),{}),qr=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],h4=qr.map(([e,t])=>[o2[e],o2[t]]),K3=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function J3(e){let t=e.reduce(({maxX:o,maxY:n,minX:r,minY:s},{position:{x:a,y:i}})=>({maxX:Math.max(o,a),maxY:Math.max(n,i),minX:Math.min(r,a),minY:Math.min(s,i)}),{maxX:Number.NEGATIVE_INFINITY,maxY:Number.NEGATIVE_INFINITY,minX:Number.POSITIVE_INFINITY,minY:Number.POSITIVE_INFINITY});return[t.minX,t.minY,t.maxX-t.minX,t.maxY-t.minY]}function Q3(e,[t,o],[n,r]){let s=t/n,a=o/r,i=(c,d)=>({id:d,score:c.score,boxRaw:[c.box[0]/r,c.box[1]/n,c.box[2]/r,c.box[3]/n],box:[Math.trunc(c.box[0]*a),Math.trunc(c.box[1]*s),Math.trunc(c.box[2]*a),Math.trunc(c.box[3]*s)],keypoints:c.keypoints.map(({score:y,part:x,position:m})=>({score:y,part:x,position:[Math.trunc(m.x*a),Math.trunc(m.y*s)],positionRaw:[m.x/n,m.y/n]})),annotations:{}});return e.map((c,d)=>i(c,d))}var D2=class{constructor(t,o){w(this,"priorityQueue");w(this,"numberOfElements");w(this,"getElementValue");this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=o}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(Math.floor(t/2),t);)this.exchange(t,Math.floor(t/2)),t=Math.floor(t/2)}sink(t){for(;2*t<=this.numberOfElements;){let o=2*t;if(o<this.numberOfElements&&this.less(o,o+1)&&o++,!this.less(t,o))break;this.exchange(t,o),t=o}}getValueAt(t){return this.getElementValue(this.priorityQueue[t])}less(t,o){return this.getValueAt(t)<this.getValueAt(o)}exchange(t,o){let n=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[o],this.priorityQueue[o]=n}};function a1(e,t,o,n){return{y:n.get(e,t,o),x:n.get(e,t,o+Xr)}}function i1(e,t,o){let{heatmapY:n,heatmapX:r,id:s}=e,{y:a,x:i}=a1(n,r,s,o);return{x:e.heatmapX*t+i,y:e.heatmapY*t+a}}function l1(e,t,o){return e<t?t:e>o?o:e}function _3(e,t,o,n){let r=o-e,s=n-t;return r*r+s*s}function y1(e,t){return{x:e.x+t.x,y:e.y+t.y}}var C0,Yr=["MobilenetV1/offset_2/BiasAdd","MobilenetV1/heatmap_2/BiasAdd","MobilenetV1/displacement_fwd_2/BiasAdd","MobilenetV1/displacement_bwd_2/BiasAdd"],Z2=1,Oe=16,Kr=50**2;function $3(e,t,o,n,r,s,a=2){let i=M=>({y:s.get(M.y,M.x,e),x:s.get(M.y,M.x,s.shape[2]/2+e)}),l=(M,g,f)=>({y:l1(Math.round(M.y/Oe),0,g-1),x:l1(Math.round(M.x/Oe),0,f-1)}),[c,d]=n.shape,y=l(t.position,c,d),x=i(y),h=y1(t.position,x);for(let M=0;M<a;M++){let g=l(h,c,d),f=a1(g.y,g.x,o,r);h=y1({x:g.x*Oe,y:g.y*Oe},{x:f.x,y:f.y})}let p=l(h,c,d),R=n.get(p.y,p.x,o);return{position:h,part:n2[o],score:R}}function Jr(e,t,o,n,r){let s=K3.map(([x,m])=>[o2[x],o2[m]]),a=s.map(([,x])=>x),i=s.map(([x])=>x),l=t.shape[2],c=a.length,d=new Array(l),y=i1(e.part,Oe,o);d[e.part.id]={score:e.score,part:n2[e.part.id],position:y};for(let x=c-1;x>=0;--x){let m=a[x],h=i[x];d[m]&&!d[h]&&(d[h]=$3(x,d[m],h,t,o,r))}for(let x=0;x<c;++x){let m=i[x],h=a[x];d[m]&&!d[h]&&(d[h]=$3(x,d[m],h,t,o,n))}return d}function Qr(e,t,o,n,r){let[s,a]=r.shape,i=!0,l=Math.max(o-Z2,0),c=Math.min(o+Z2+1,s);for(let d=l;d<c;++d){let y=Math.max(n-Z2,0),x=Math.min(n+Z2+1,a);for(let m=y;m<x;++m)if(r.get(d,m,e)>t){i=!1;break}if(!i)break}return i}function _r(e,t){let[o,n,r]=t.shape,s=new D2(o*n*r,({score:a})=>a);for(let a=0;a<o;++a)for(let i=0;i<n;++i)for(let l=0;l<r;++l){let c=t.get(a,i,l);c<e||Qr(l,c,a,i,t)&&s.enqueue({score:c,part:{heatmapY:a,heatmapX:i,id:l}})}return s}function eo(e,{x:t,y:o},n){return e.some(({keypoints:r})=>{var a;let s=(a=r[n])==null?void 0:a.position;return s?_3(o,t,s.y,s.x)<=Kr:!1})}function $r(e,t){return t.reduce((n,{position:r,score:s},a)=>(eo(e,r,a)||(n+=s),n),0)/t.length}function eA(e,t,o,n,r,s){let a=[],i=_r(s,t);for(;a.length<r&&!i.empty();){let l=i.dequeue(),c=i1(l.part,Oe,e);if(eo(a,c,l.part.id))continue;let d=Jr(l,t,e,o,n);d=d.filter(m=>m.score>s);let y=$r(a,d),x=J3(d);y>s&&a.push({keypoints:d,box:x,score:Math.round(100*y)/100})}return a}async function x1(e,t){let o=A.tidy(()=>{if(!C0.inputs[0].shape)return[];let a=A.image.resizeBilinear(e,[C0.inputs[0].shape[2],C0.inputs[0].shape[1]]),i=A.sub(A.div(A.cast(a,"float32"),127.5),1),c=C0.execute(i,Yr).map(d=>A.squeeze(d,[0]));return c[1]=A.sigmoid(c[1]),c}),n=await Promise.all(o.map(a=>a.buffer()));for(let a of o)A.dispose(a);let r=await eA(n[0],n[1],n[2],n[3],t.body.maxDetected,t.body.minConfidence);return C0.inputs[0].shape?Q3(r,[e.shape[1],e.shape[2]],[C0.inputs[0].shape[2],C0.inputs[0].shape[1]]):[]}async function to(e){return!C0||T.initial?C0=await L(e.body.modelPath):e.debug&&u("cached model:",C0.modelUrl),C0}var N0,c1=!1;async function d1(e){return!N0||T.initial?N0=await L(e.segmentation.modelPath):e.debug&&u("cached model:",N0.modelUrl),N0}async function no(e,t,o){var p,R;if(c1)return{data:[],canvas:null,alpha:null};c1=!0,N0||await d1(o);let n=await Pe(e,o),r=((p=n.tensor)==null?void 0:p.shape[2])||0,s=((R=n.tensor)==null?void 0:R.shape[1])||0;if(!n.tensor)return{data:[],canvas:null,alpha:null};let a={};a.resize=A.image.resizeBilinear(n.tensor,[N0.inputs[0].shape?N0.inputs[0].shape[1]:0,N0.inputs[0].shape?N0.inputs[0].shape[2]:0],!1),A.dispose(n.tensor),a.norm=A.div(a.resize,G.tf255),a.res=N0.execute(a.norm),a.squeeze=A.squeeze(a.res,0),a.squeeze.shape[2]===2?(a.softmax=A.softmax(a.squeeze),[a.bg,a.fg]=A.unstack(a.softmax,2),a.expand=A.expandDims(a.fg,2),a.pad=A.expandDims(a.expand,0),a.crop=A.image.cropAndResize(a.pad,[[0,0,.5,.5]],[0],[r,s]),a.data=A.squeeze(a.crop,0)):a.data=A.image.resizeBilinear(a.squeeze,[s,r]);let i=Array.from(await a.data.data());if(T.node&&!T.Canvas&&typeof ImageData=="undefined")return o.debug&&u("canvas support missing"),Object.keys(a).forEach(M=>A.dispose(a[M])),{data:i,canvas:null,alpha:null};let l=y0(r,s);A.browser&&await A.browser.toPixels(a.data,l);let c=l.getContext("2d");o.segmentation.blur&&o.segmentation.blur>0&&(c.filter=`blur(${o.segmentation.blur}px)`);let d=c.getImageData(0,0,r,s),y=y0(r,s),x=y.getContext("2d");n.canvas&&x.drawImage(n.canvas,0,0),x.globalCompositeOperation="darken",o.segmentation.blur&&o.segmentation.blur>0&&(x.filter=`blur(${o.segmentation.blur}px)`),x.drawImage(l,0,0),x.globalCompositeOperation="source-over",x.filter="none";let m=x.getImageData(0,0,r,s);for(let M=0;M<r*s;M++)m.data[4*M+3]=d.data[4*M+0];x.putImageData(m,0,0);let h=null;if(t&&y){h=y0(r,s);let M=await Pe(t,o);A.dispose(M.tensor);let g=h.getContext("2d");g.drawImage(M.canvas,0,0,h.width,h.height),g.drawImage(y,0,0)}return Object.keys(a).forEach(M=>A.dispose(a[M])),c1=!1,{data:i,canvas:y,alpha:l}}var r2=class{constructor(){w(this,"ssrnetage",null);w(this,"gear",null);w(this,"blazeposedetect",null);w(this,"blazepose",null);w(this,"centernet",null);w(this,"efficientpose",null);w(this,"mobilefacenet",null);w(this,"emotion",null);w(this,"facedetect",null);w(this,"faceiris",null);w(this,"facemesh",null);w(this,"faceres",null);w(this,"ssrnetgender",null);w(this,"handpose",null);w(this,"handskeleton",null);w(this,"handtrack",null);w(this,"liveness",null);w(this,"movenet",null);w(this,"nanodet",null);w(this,"posenet",null);w(this,"segmentation",null);w(this,"antispoof",null)}},f1=e=>{let t=0,o=0,n=0;for(let s of Object.values(k0))t+=s.sizeFromManifest,o+=s.sizeLoadedWeights,n+=s.sizeDesired;let r=n>0?o/n:0;return{numLoadedModels:Object.values(k0).length,numEnabledModels:void 0,numDefinedModels:Object.keys(e.models).length,percentageLoaded:r,totalSizeFromManifest:t,totalSizeWeights:o,totalSizeLoading:n,totalSizeEnabled:void 0,modelStats:Object.values(k0)}};function X2(e){for(let t of Object.keys(e.models))e.models[t]=null}async function m1(e){var t,o,n,r,s,a,i,l,c,d,y,x,m,h,p,R,M,g,f,P,C,k,I,j,O,F,V,Z,t0,z,g0;T.initial&&X2(e),e.config.hand.enabled&&(!e.models.handpose&&((o=(t=e.config.hand.detector)==null?void 0:t.modelPath)==null?void 0:o.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await U5(e.config)),!e.models.handskeleton&&e.config.hand.landmarks&&((r=(n=e.config.hand.detector)==null?void 0:n.modelPath)==null?void 0:r.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await U5(e.config))),e.config.body.enabled&&!e.models.blazepose&&((a=(s=e.config.body)==null?void 0:s.modelPath)==null?void 0:a.includes("blazepose"))&&(e.models.blazepose=St(e.config)),e.config.body.enabled&&!e.models.blazeposedetect&&e.config.body.detector&&e.config.body.detector.modelPath&&(e.models.blazeposedetect=zt(e.config)),e.config.body.enabled&&!e.models.efficientpose&&((l=(i=e.config.body)==null?void 0:i.modelPath)==null?void 0:l.includes("efficientpose"))&&(e.models.efficientpose=Lt(e.config)),e.config.body.enabled&&!e.models.movenet&&((d=(c=e.config.body)==null?void 0:c.modelPath)==null?void 0:d.includes("movenet"))&&(e.models.movenet=Z3(e.config)),e.config.body.enabled&&!e.models.posenet&&((x=(y=e.config.body)==null?void 0:y.modelPath)==null?void 0:x.includes("posenet"))&&(e.models.posenet=to(e.config)),e.config.face.enabled&&!e.models.facedetect&&(e.models.facedetect=gt(e.config)),e.config.face.enabled&&((m=e.config.face.antispoof)==null?void 0:m.enabled)&&!e.models.antispoof&&(e.models.antispoof=at(e.config)),e.config.face.enabled&&((h=e.config.face.liveness)==null?void 0:h.enabled)&&!e.models.liveness&&(e.models.liveness=F3(e.config)),e.config.face.enabled&&((p=e.config.face.description)==null?void 0:p.enabled)&&!e.models.faceres&&(e.models.faceres=a3(e.config)),e.config.face.enabled&&((R=e.config.face.emotion)==null?void 0:R.enabled)&&!e.models.emotion&&(e.models.emotion=Bt(e.config)),e.config.face.enabled&&((M=e.config.face.iris)==null?void 0:M.enabled)&&!((g=e.config.face.attention)!=null&&g.enabled)&&!e.models.faceiris&&(e.models.faceiris=Jt(e.config)),e.config.face.enabled&&((f=e.config.face.mesh)==null?void 0:f.enabled)&&!e.models.facemesh&&(e.models.facemesh=o3(e.config)),e.config.face.enabled&&((P=e.config.face.gear)==null?void 0:P.enabled)&&!e.models.gear&&(e.models.gear=Y1(e.config)),e.config.face.enabled&&((C=e.config.face.ssrnet)==null?void 0:C.enabled)&&!e.models.ssrnetage&&(e.models.ssrnetage=$1(e.config)),e.config.face.enabled&&((k=e.config.face.ssrnet)==null?void 0:k.enabled)&&!e.models.ssrnetgender&&(e.models.ssrnetgender=nt(e.config)),e.config.face.enabled&&((I=e.config.face.mobilefacenet)==null?void 0:I.enabled)&&!e.models.mobilefacenet&&(e.models.mobilefacenet=Xt(e.config)),e.config.hand.enabled&&!e.models.handtrack&&((O=(j=e.config.hand.detector)==null?void 0:j.modelPath)==null?void 0:O.includes("handtrack"))&&(e.models.handtrack=I3(e.config)),e.config.hand.enabled&&e.config.hand.landmarks&&!e.models.handskeleton&&((V=(F=e.config.hand.detector)==null?void 0:F.modelPath)==null?void 0:V.includes("handtrack"))&&(e.models.handskeleton=N3(e.config)),e.config.object.enabled&&!e.models.centernet&&((t0=(Z=e.config.object)==null?void 0:Z.modelPath)==null?void 0:t0.includes("centernet"))&&(e.models.centernet=It(e.config)),e.config.object.enabled&&!e.models.nanodet&&((g0=(z=e.config.object)==null?void 0:z.modelPath)==null?void 0:g0.includes("nanodet"))&&(e.models.nanodet=U3(e.config)),e.config.segmentation.enabled&&!e.models.segmentation&&(e.models.segmentation=d1(e.config));for await(let M0 of Object.keys(e.models))e.models[M0]&&typeof e.models[M0]!="undefined"&&(e.models[M0]=await e.models[M0])}async function p1(e){let t=["const","placeholder","noop","pad","squeeze","add","sub","mul","div"];for(let o of Object.keys(e.models)){let n=e.models[o];if(!n)continue;let r=[],s=n==null?void 0:n.executor;if(s&&s.graph.nodes)for(let i of Object.values(s.graph.nodes)){let l=i.op.toLowerCase();r.includes(l)||r.push(l)}else!s&&e.config.debug&&u("model signature not determined:",o);let a=[];for(let i of r)!t.includes(i)&&!e.env.kernels.includes(i)&&!e.env.kernels.includes(i.replace("_",""))&&!e.env.kernels.includes(i.replace("native",""))&&!e.env.kernels.includes(i.replace("v2",""))&&a.push(i);e.config.debug&&a.length>0&&u("model validation failed:",o,a)}}var Y={name:"humangl",priority:999,canvas:null,gl:null,extensions:[],webGLattr:{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!1,desynchronized:!0}};function tA(){let e=Y.gl;!e||(Y.extensions=e.getSupportedExtensions())}async function Ao(e){var t;if(e.config.backend==="humangl"&&(Y.name in A.engine().registry&&(!Y.gl||!Y.gl.getParameter(Y.gl.VERSION))&&(u("error: humangl backend invalid context"),X2(e)),!A.findBackend(Y.name))){try{Y.canvas=await y0(100,100)}catch(n){u("error: cannot create canvas:",n);return}try{if(Y.gl=(t=Y.canvas)==null?void 0:t.getContext("webgl2",Y.webGLattr),!Y.gl.getParameter(Y.gl.VERSION).includes("2.0")){u("override: using fallback webgl backend as webgl 2.0 is not detected"),e.config.backend="webgl";return}Y.canvas&&(Y.canvas.addEventListener("webglcontextlost",async r=>{throw u("error: humangl:",r.type),u("possible browser memory leak using webgl or conflict with multiple backend registrations"),e.emit("error"),new Error("backend error: webgl context lost")}),Y.canvas.addEventListener("webglcontextrestored",r=>{u("error: humangl context restored:",r)}),Y.canvas.addEventListener("webglcontextcreationerror",r=>{u("error: humangl context create:",r)}))}catch(n){u("error: cannot get WebGL context:",n);return}try{A.setWebGLContext(2,Y.gl)}catch(n){u("error: cannot set WebGL context:",n);return}try{let n=new A.GPGPUContext(Y.gl);A.registerBackend(Y.name,()=>new A.MathBackendWebGL(n),Y.priority)}catch(n){u("error: cannot register WebGL backend:",n);return}try{A.getKernelsForBackend("webgl").forEach(r=>{let s={...r,backendName:Y.name};A.registerKernel(s)})}catch(n){u("error: cannot update WebGL backend registration:",n);return}let o=A.backend().getGPGPUContext?A.backend().getGPGPUContext().gl:null;if(o)u(`humangl webgl version:${o.getParameter(o.VERSION)} renderer:${o.getParameter(o.RENDERER)}`);else{u("error: no current gl context:",o,Y.gl);return}try{A.ENV.set("WEBGL_VERSION",2)}catch(n){u("error: cannot set WebGL backend flags:",n);return}tA(),u("backend registered:",Y.name)}}function oA(){if(!T.kernels.includes("mod")){let e={kernelName:"Mod",backendName:A.getBackend(),kernelFunc:t=>A.tidy(()=>A.sub(t.inputs.a,A.mul(A.div(t.inputs.a,t.inputs.b),t.inputs.b)))};A.registerKernel(e),T.kernels.push("mod")}if(!T.kernels.includes("floormod")){let e={kernelName:"FloorMod",backendName:A.getBackend(),kernelFunc:t=>A.tidy(()=>A.floorDiv(t.inputs.a/t.inputs.b)*t.inputs.b+A.mod(t.inputs.a,t.inputs.b))};A.registerKernel(e),T.kernels.push("floormod")}}async function q2(e,t=!1){if(e.state="backend",t||T.initial||e.config.backend&&e.config.backend.length>0&&A.getBackend()!==e.config.backend){let o=b();if(e.config.backend&&e.config.backend.length>0){if(typeof window=="undefined"&&typeof WorkerGlobalScope!="undefined"&&e.config.debug&&e.config.debug&&u("running inside web worker"),T.browser&&e.config.backend==="tensorflow"&&(e.config.debug&&u("override: backend set to tensorflow while running in browser"),e.config.backend="humangl"),T.node&&(e.config.backend==="webgl"||e.config.backend==="humangl")&&(e.config.debug&&u(`override: backend set to ${e.config.backend} while running in nodejs`),e.config.backend="tensorflow"),T.browser&&e.config.backend==="webgpu")if(typeof navigator=="undefined"||typeof navigator.gpu=="undefined")u("override: backend set to webgpu but browser does not support webgpu"),e.config.backend="humangl";else{let r=await navigator.gpu.requestAdapter();if(e.config.debug&&u("enumerated webgpu adapter:",r),!r)u("override: backend set to webgpu but browser reports no available gpu"),e.config.backend="humangl";else{let s="requestAdapterInfo"in r?await r.requestAdapterInfo():void 0;u("webgpu adapter info:",s)}}e.config.backend==="humangl"&&await Ao(e);let n=Object.keys(A.engine().registryFactory);if(e.config.debug&&u("available backends:",n),n.includes(e.config.backend)||(u(`error: backend ${e.config.backend} not found in registry`),e.config.backend=T.node?"tensorflow":"webgl",e.config.debug&&u(`override: setting backend ${e.config.backend}`)),e.config.debug&&u("setting backend:",e.config.backend),e.config.backend==="wasm"){try{A.env().set("CANVAS2D_WILL_READ_FREQUENTLY",!0)}catch(a){}if(e.config.debug&&u("wasm path:",e.config.wasmPath),typeof(A==null?void 0:A.setWasmPaths)!="undefined")await A.setWasmPaths(e.config.wasmPath,e.config.wasmPlatformFetch);else throw new Error("backend error: attempting to use wasm backend but wasm path is not set");let r=await A.env().getAsync("WASM_HAS_SIMD_SUPPORT"),s=await A.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");e.config.debug&&u(`wasm execution: ${r?"SIMD":"no SIMD"} ${s?"multithreaded":"singlethreaded"}`),e.config.debug&&!r&&u("warning: wasm simd support is not enabled")}try{await A.setBackend(e.config.backend),await A.ready(),J1()}catch(r){return u("error: cannot set backend:",e.config.backend,r),!1}}if(A.getBackend()==="humangl"&&(A.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),A.ENV.set("WEBGL_CPU_FORWARD",!0),A.ENV.set("WEBGL_USE_SHAPES_UNIFORMS",!0),A.ENV.set("CPU_HANDOFF_SIZE_THRESHOLD",256),typeof e.config.deallocate!="undefined"&&e.config.deallocate&&(u("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),A.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",0)),A.backend().getGPGPUContext)){let n=await A.backend().getGPGPUContext().gl;e.config.debug&&u(`gl version:${n.getParameter(n.VERSION)} renderer:${n.getParameter(n.RENDERER)}`)}A.getBackend(),A.enableProdMode(),await A.ready(),e.performance.initBackend=Math.trunc(b()-o),e.config.backend=A.getBackend(),await T.updateBackend(),oA()}return!0}function O2(e,t){for(let o of e){let n={kernelName:o,backendName:t.backend,kernelFunc:()=>{t.debug&&u("kernelFunc",o,t.backend)}};A.registerKernel(n)}T.kernels=A.getKernelsForBackend(A.getBackend()).map(o=>o.kernelName.toLowerCase())}var io={};U0(io,{all:()=>R1,body:()=>We,canvas:()=>P1,face:()=>Le,gesture:()=>Be,hand:()=>Fe,object:()=>Ge,options:()=>l0,person:()=>M1});var R0=e=>{if(!e)u("draw error: invalid canvas");else if(!e.getContext)u("draw error: canvas context not defined");else{let t=e.getContext("2d");if(!t)u("draw error: cannot get canvas context");else return t}return null},he=e=>Math.round(e*180/Math.PI),X0=(e,t)=>{if(!t.useDepth||typeof e=="undefined")return t.color;let o=Uint8ClampedArray.from([127+2*e,127-2*e,255]);return`rgba(${o[0]}, ${o[1]}, ${o[2]}, ${t.alpha})`};function q0(e,t,o,n,r){e.fillStyle=X0(n,r),e.beginPath(),e.arc(t,o,r.pointSize,0,2*Math.PI),e.fill()}function O0(e,t,o,n,r,s){if(e.beginPath(),e.lineWidth=s.lineWidth,s.useCurves){let a=(t+t+n)/2,i=(o+o+r)/2;e.ellipse(a,i,n/2,r/2,0,0,2*Math.PI)}else e.moveTo(t+s.roundRect,o),e.lineTo(t+n-s.roundRect,o),e.quadraticCurveTo(t+n,o,t+n,o+s.roundRect),e.lineTo(t+n,o+r-s.roundRect),e.quadraticCurveTo(t+n,o+r,t+n-s.roundRect,o+r),e.lineTo(t+s.roundRect,o+r),e.quadraticCurveTo(t,o+r,t,o+r-s.roundRect),e.lineTo(t,o+s.roundRect),e.quadraticCurveTo(t,o,t+s.roundRect,o),e.closePath();e.stroke()}function h1(e,t,o){if(!(t.length<2)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let n of t)e.strokeStyle=X0(n[2]||0,o),e.lineTo(Math.trunc(n[0]),Math.trunc(n[1]));e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function ao(e,t,o){if(!(t.length<2)){if(e.lineWidth=o.lineWidth,!o.useCurves||t.length<=2){h1(e,t,o);return}e.moveTo(t[0][0],t[0][1]);for(let n=0;n<t.length-2;n++){let r=(t[n][0]+t[n+1][0])/2,s=(t[n][1]+t[n+1][1])/2;e.quadraticCurveTo(t[n][0],t[n][1],r,s)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function b1(e,t,o,n=5){let r,s,a;e.beginPath(),e.moveTo(t[0],t[1]),e.lineTo(o[0],o[1]),r=Math.atan2(o[1]-t[1],o[0]-t[0]),s=n*Math.cos(r)+o[0],a=n*Math.sin(r)+o[1],e.moveTo(s,a),r+=1/3*(2*Math.PI),s=n*Math.cos(r)+o[0],a=n*Math.sin(r)+o[1],e.lineTo(s,a),r+=1/3*(2*Math.PI),s=n*Math.cos(r)+o[0],a=n*Math.sin(r)+o[1],e.lineTo(s,a),e.closePath(),e.stroke(),e.fill()}var l0={color:"rgba(173, 216, 230, 0.6)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",alpha:.5,font:'small-caps 16px "Segoe UI"',lineHeight:18,lineWidth:4,pointSize:2,roundRect:8,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawAttention:!0,drawGestures:!0,drawPolygons:!0,drawGaze:!0,fillPolygons:!1,useDepth:!0,useCurves:!1};var H;function rA(e,t){if(H.drawLabels){let o=[];if(o.push(`face: ${Math.trunc(100*e.score)}%`),e.genderScore&&o.push(`${e.gender||""} ${Math.trunc(100*e.genderScore)}%`),e.age&&o.push(`age: ${e.age||""}`),e.iris&&o.push(`distance: ${e.iris}`),e.real&&o.push(`real: ${Math.trunc(100*e.real)}%`),e.live&&o.push(`live: ${Math.trunc(100*e.live)}%`),e.emotion&&e.emotion.length>0){let n=e.emotion.map(r=>`${Math.trunc(100*r.score)}% ${r.emotion}`);n.length>3&&(n.length=3),o.push(n.join(" "))}e.rotation&&e.rotation.angle&&e.rotation.gaze&&(e.rotation.angle.roll&&o.push(`roll: ${he(e.rotation.angle.roll)}\xB0 yaw:${he(e.rotation.angle.yaw)}\xB0 pitch:${he(e.rotation.angle.pitch)}\xB0`),e.rotation.gaze.bearing&&o.push(`gaze: ${he(e.rotation.gaze.bearing)}\xB0`)),o.length===0&&o.push("face"),t.fillStyle=H.color;for(let n=o.length-1;n>=0;n--){let r=Math.max(e.box[0],0),s=n*H.lineHeight+e.box[1];H.shadowColor&&H.shadowColor!==""&&(t.fillStyle=H.shadowColor,t.fillText(o[n],r+5,s+16)),t.fillStyle=H.labelColor,t.fillText(o[n],r+4,s+15)}}}function AA(e,t){if(e.annotations&&e.annotations.leftEyeIris&&e.annotations.leftEyeIris[0]){t.strokeStyle=H.useDepth?"rgba(255, 200, 255, 0.3)":H.color,t.beginPath();let o=Math.abs(e.annotations.leftEyeIris[3][0]-e.annotations.leftEyeIris[1][0])/2,n=Math.abs(e.annotations.leftEyeIris[4][1]-e.annotations.leftEyeIris[2][1])/2;t.ellipse(e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),H.fillPolygons&&(t.fillStyle=H.useDepth?"rgba(255, 255, 200, 0.3)":H.color,t.fill())}if(e.annotations&&e.annotations.rightEyeIris&&e.annotations.rightEyeIris[0]){t.strokeStyle=H.useDepth?"rgba(255, 200, 255, 0.3)":H.color,t.beginPath();let o=Math.abs(e.annotations.rightEyeIris[3][0]-e.annotations.rightEyeIris[1][0])/2,n=Math.abs(e.annotations.rightEyeIris[4][1]-e.annotations.rightEyeIris[2][1])/2;t.ellipse(e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),H.fillPolygons&&(t.fillStyle=H.useDepth?"rgba(255, 255, 200, 0.3)":H.color,t.fill())}}function sA(e,t){var o;if(H.drawGaze&&((o=e.rotation)==null?void 0:o.angle)&&typeof Path2D!="undefined"){t.strokeStyle="pink";let n=e.box[0]+e.box[2]/2-e.box[3]*he(e.rotation.angle.yaw)/90,r=e.box[1]+e.box[3]/2+e.box[2]*he(e.rotation.angle.pitch)/90,s=new Path2D(`
+`;var $2=(e,t,o)=>{let n=new RegExp("\\b"+t+" \\w+ (\\w+)","ig");e.replace(n,(r,s)=>(o[s]=0,r))},e5=class{constructor(t,o,n){w(this,"uniform",{});w(this,"attribute",{});w(this,"gl");w(this,"id");w(this,"compile",(t,o)=>{let n=this.gl.createShader(o);return n?(this.gl.shaderSource(n,t),this.gl.compileShader(n),this.gl.getShaderParameter(n,this.gl.COMPILE_STATUS)?n:(u(`filter: gl compile failed: ${this.gl.getShaderInfoLog(n)}`),null)):(u("filter: could not create shader"),null)});this.gl=t;let r=this.compile(o,this.gl.VERTEX_SHADER),s=this.compile(n,this.gl.FRAGMENT_SHADER);if(this.id=this.gl.createProgram(),!(!r||!s)){if(!this.id){u("filter: could not create webgl program");return}if(this.gl.attachShader(this.id,r),this.gl.attachShader(this.id,s),this.gl.linkProgram(this.id),!this.gl.getProgramParameter(this.id,this.gl.LINK_STATUS)){u(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);return}this.gl.useProgram(this.id),$2(o,"attribute",this.attribute);for(let a in this.attribute)this.attribute[a]=this.gl.getAttribLocation(this.id,a);$2(o,"uniform",this.uniform),$2(n,"uniform",this.uniform);for(let a in this.uniform)this.uniform[a]=this.gl.getUniformLocation(this.id,a)}}};function V1(){let e=0,t=null,o=!1,n=-1,r=[null,null],s=[],a=null,i=null,l=y0(100,100),c={},d={INTERMEDIATE:1},y=l.getContext("webgl");if(!y){u("filter: cannot get webgl context");return}this.gl=y;function x(g,f){if(!(g===l.width&&f===l.height)){if(l.width=g,l.height=f,!a){let P=new Float32Array([-1,-1,0,1,1,-1,1,1,-1,1,0,0,-1,1,0,0,1,-1,1,1,1,1,1,0]);a=y.createBuffer(),y.bindBuffer(y.ARRAY_BUFFER,a),y.bufferData(y.ARRAY_BUFFER,P,y.STATIC_DRAW),y.pixelStorei(y.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}y.viewport(0,0,l.width,l.height),r=[null,null]}}function m(g,f){let P=y.createFramebuffer();y.bindFramebuffer(y.FRAMEBUFFER,P);let C=y.createRenderbuffer();y.bindRenderbuffer(y.RENDERBUFFER,C);let k=y.createTexture();return y.bindTexture(y.TEXTURE_2D,k),y.texImage2D(y.TEXTURE_2D,0,y.RGBA,g,f,0,y.RGBA,y.UNSIGNED_BYTE,null),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_MAG_FILTER,y.LINEAR),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_MIN_FILTER,y.LINEAR),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_WRAP_S,y.CLAMP_TO_EDGE),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_WRAP_T,y.CLAMP_TO_EDGE),y.framebufferTexture2D(y.FRAMEBUFFER,y.COLOR_ATTACHMENT0,y.TEXTURE_2D,k,0),y.bindTexture(y.TEXTURE_2D,null),y.bindFramebuffer(y.FRAMEBUFFER,null),{fbo:P,texture:k}}function h(g){return r[g]=r[g]||m(l.width,l.height),r[g]}function p(g=0){if(!i)return;let f=null,P=null,C=!1;e===0?f=t:f=h(n).texture||null,e++,o&&!(g&d.INTERMEDIATE)?(P=null,C=e%2===0):(n=(n+1)%2,P=h(n).fbo||null),y.bindTexture(y.TEXTURE_2D,f),y.bindFramebuffer(y.FRAMEBUFFER,P),y.uniform1f(i.uniform.flipY,C?-1:1),y.drawArrays(y.TRIANGLES,0,6)}function R(g){if(c[g])return i=c[g],y.useProgram((i?i.id:null)||null),i;if(i=new e5(y,L1,g),!i)return u("filter: could not get webgl program"),null;let f=Float32Array.BYTES_PER_ELEMENT,P=4*f;return y.enableVertexAttribArray(i.attribute.pos),y.vertexAttribPointer(i.attribute.pos,2,y.FLOAT,!1,P,0*f),y.enableVertexAttribArray(i.attribute.uv),y.vertexAttribPointer(i.attribute.uv,2,y.FLOAT,!1,P,2*f),c[g]=i,i}let M={colorMatrix:g=>{let f=new Float32Array(g);f[4]/=255,f[9]/=255,f[14]/=255,f[19]/=255;let P=f[18]===1&&f[3]===0&&f[8]===0&&f[13]===0&&f[15]===0&&f[16]===0&&f[17]===0&&f[19]===0?F1:W1,C=R(P);!C||(y.uniform1fv(C.uniform.m,f),p())},brightness:g=>{let f=(g||0)+1;M.colorMatrix([f,0,0,0,0,0,f,0,0,0,0,0,f,0,0,0,0,0,1,0])},saturation:g=>{let f=(g||0)*2/3+1,P=(f-1)*-.5;M.colorMatrix([f,P,P,0,0,P,f,P,0,0,P,P,f,0,0,0,0,0,1,0])},desaturate:()=>{M.saturation(-1)},contrast:g=>{let f=(g||0)+1,P=-128*(f-1);M.colorMatrix([f,0,0,0,P,0,f,0,0,P,0,0,f,0,P,0,0,0,1,0])},negative:()=>{M.contrast(-2)},hue:g=>{g=(g||0)/180*Math.PI;let f=Math.cos(g),P=Math.sin(g),C=.213,k=.715,j=.072;M.colorMatrix([C+f*(1-C)+P*-C,k+f*-k+P*-k,j+f*-j+P*(1-j),0,0,C+f*-C+P*.143,k+f*(1-k)+P*.14,j+f*-j+P*-.283,0,0,C+f*-C+P*-(1-C),k+f*-k+P*k,j+f*(1-j)+P*j,0,0,0,0,0,1,0])},desaturateLuminance:()=>{M.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},sepia:()=>{M.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},brownie:()=>{M.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},vintagePinhole:()=>{M.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},kodachrome:()=>{M.colorMatrix([1.1285582396593525,-.3967382283601348,-.03992559172921793,0,63.72958762196502,-.16404339962244616,1.0835251566291304,-.05498805115633132,0,24.732407896706203,-.16786010706155763,-.5603416277695248,1.6014850761964943,0,35.62982807460946,0,0,0,1,0])},technicolor:()=>{M.colorMatrix([1.9125277891456083,-.8545344976951645,-.09155508482755585,0,11.793603434377337,-.3087833385928097,1.7658908555458428,-.10601743074722245,0,-70.35205161461398,-.231103377548616,-.7501899197440212,1.847597816108189,0,30.950940869491138,0,0,0,1,0])},polaroid:()=>{M.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},shiftToBGR:()=>{M.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},convolution:g=>{let f=new Float32Array(g),P=1/l.width,C=1/l.height,k=R(H1);!k||(y.uniform1fv(k.uniform.m,f),y.uniform2f(k.uniform.px,P,C),p())},detectEdges:()=>{M.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},sobelX:()=>{M.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},sobelY:()=>{M.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},sharpen:g=>{let f=g||1;M.convolution.call(this,[0,-1*f,0,-1*f,1+4*f,-1*f,0,-1*f,0])},emboss:g=>{let f=g||1;M.convolution.call(this,[-2*f,-1*f,0,-1*f,1,1*f,0,1*f,2*f])},blur:g=>{let f=g/7/l.width,P=g/7/l.height,C=R(B1);!C||(y.uniform2f(C.uniform.px,0,P),p(d.INTERMEDIATE),y.uniform2f(C.uniform.px,f,0),p())},pixelate:g=>{let f=g/l.width,P=g/l.height,C=R(G1);!C||(y.uniform2f(C.uniform.size,f,P),p())}};this.add=function(g){let f=Array.prototype.slice.call(arguments,1),P=M[g];s.push({func:P,args:f})},this.reset=function(){s=[]},this.get=function(){return s},this.apply=function(g){x(g.width,g.height),e=0,t||(t=y.createTexture()),y.bindTexture(y.TEXTURE_2D,t),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_WRAP_S,y.CLAMP_TO_EDGE),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_WRAP_T,y.CLAMP_TO_EDGE),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_MIN_FILTER,y.NEAREST),y.texParameteri(y.TEXTURE_2D,y.TEXTURE_MAG_FILTER,y.NEAREST),y.texImage2D(y.TEXTURE_2D,0,y.RGBA,y.RGBA,y.UNSIGNED_BYTE,g);for(let f=0;f<s.length;f++){o=f===s.length-1;let P=s[f];P.func.apply(this,P.args||[])}return l},this.draw=function(g){return this.add("brightness",0),this.apply(g)}}async function i2(e){let t=e.shape.length===4?A.squeeze(e):e,o=A.split(t,3,2),n=[A.min(o[0]),A.min(o[1]),A.min(o[2])],r=[A.max(o[0]),A.max(o[1]),A.max(o[2])],s=await Promise.all(r.map(m=>m.data())),a=.99*Math.max(s[0][0],s[1][0],s[2][0]),i=[A.sub(o[0],n[0]),A.sub(o[1],n[1]),A.sub(o[2],n[2])],l=[A.sub(r[0],n[0]),A.sub(r[1],n[1]),A.sub(r[2],n[2])],c=[A.div(a,l[0]),A.div(a,l[1]),A.div(a,l[2])],d=[A.mul(i[0],c[0]),A.mul(i[1],c[1]),A.mul(i[2],c[2])],y=A.stack([d[0],d[1],d[2]],2),x=A.reshape(y,[1,t.shape[0],t.shape[1],3]);return A.dispose([...o,...n,...r,...i,...l,...c,...d,y,t]),x}var l2=3840,B=null,$=null,Me=null,U,F0={inputSum:0,cacheDiff:1,sumMethod:0,inputTensor:void 0};function y0(e,t){let o;if(T.browser)if(T.worker){if(typeof OffscreenCanvas=="undefined")throw new Error("canvas error: attempted to run in web worker but OffscreenCanvas is not supported");o=new OffscreenCanvas(e,t)}else{if(typeof document=="undefined")throw new Error("canvas error: attempted to run in browser but DOM is not defined");o=document.createElement("canvas"),o.width=e,o.height=t}else typeof T.Canvas!="undefined"?o=new T.Canvas(e,t):typeof globalThis.Canvas!="undefined"&&(o=new globalThis.Canvas(e,t));return o}function y2(e,t){let o=t||y0(e.width,e.height);return o.getContext("2d").drawImage(e,0,0),o}async function Pe(e,t,o=!0){if(!e)return t.debug&&u("input error: input is missing"),{tensor:null,canvas:null};if(!(e instanceof ge)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(typeof T.Canvas!="undefined"&&e instanceof T.Canvas)&&!(typeof globalThis.Canvas!="undefined"&&e instanceof globalThis.Canvas)&&!(typeof ImageData!="undefined"&&e instanceof ImageData)&&!(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)&&!(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)&&!(typeof HTMLMediaElement!="undefined"&&e instanceof HTMLMediaElement)&&!(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)&&!(typeof HTMLCanvasElement!="undefined"&&e instanceof HTMLCanvasElement)&&!(typeof OffscreenCanvas!="undefined"&&e instanceof OffscreenCanvas))throw new Error("input error: type is not recognized");if(e instanceof ge){let n=null;if(e.isDisposedInternal)throw new Error("input error: attempted to use tensor but it is disposed");if(!e.shape)throw new Error("input error: attempted to use tensor without a shape");if(e.shape.length===3){if(e.shape[2]===3)n=A.expandDims(e,0);else if(e.shape[2]===4){let r=A.slice3d(e,[0,0,0],[-1,-1,3]);n=A.expandDims(r,0),A.dispose(r)}}else e.shape.length===4&&(e.shape[3]===3?n=A.clone(e):e.shape[3]===4&&(n=A.slice4d(e,[0,0,0,0],[-1,-1,-1,3])));if(n==null||n.shape.length!==4||n.shape[0]!==1||n.shape[3]!==3)throw new Error(`input error: attempted to use tensor with unrecognized shape: ${e.shape}`);if(n.dtype==="int32"){let r=A.cast(n,"float32");A.dispose(n),n=r}return{tensor:n,canvas:t.filter.return?$:null}}else{if(typeof e.readyState!="undefined"&&e.readyState<=2)return t.debug&&u("input stream is not ready"),{tensor:null,canvas:B};let n=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,r=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0;if(!n||!r)return t.debug&&u("cannot determine input dimensions"),{tensor:null,canvas:B};let s=n,a=r;if(s>l2&&(s=l2,a=Math.trunc(s*r/n)),a>l2&&(a=l2,s=Math.trunc(a*n/r)),(t.filter.width||0)>0?s=t.filter.width:(t.filter.height||0)>0&&(s=n*((t.filter.height||0)/r)),(t.filter.height||0)>0?a=t.filter.height:(t.filter.width||0)>0&&(a=r*((t.filter.width||0)/n)),!s||!a)throw new Error("input error: cannot determine dimension");(!B||(B==null?void 0:B.width)!==s||(B==null?void 0:B.height)!==a)&&(B=y0(s,a));let i=B.getContext("2d");if(typeof ImageData!="undefined"&&e instanceof ImageData?i.putImageData(e,0,0):t.filter.flip&&typeof i.translate!="undefined"?(i.translate(n,0),i.scale(-1,1),i.drawImage(e,0,0,n,r,0,0,B==null?void 0:B.width,B==null?void 0:B.height),i.setTransform(1,0,0,1,0,0)):i.drawImage(e,0,0,n,r,0,0,B==null?void 0:B.width,B==null?void 0:B.height),(!$||B.width!==$.width||(B==null?void 0:B.height)!==($==null?void 0:$.height))&&($=y0(B.width,B.height)),t.filter.enabled&&T.webgl.supported?(U||(U=T.browser?new V1:null),T.filter=!!U,!U||!U.add?(t.debug&&u("input process error: cannot initialize filters"),T.webgl.supported=!1,t.filter.enabled=!1,y2(B,$)):(U.reset(),t.filter.brightness!==0&&U.add("brightness",t.filter.brightness),t.filter.contrast!==0&&U.add("contrast",t.filter.contrast),t.filter.sharpness!==0&&U.add("sharpen",t.filter.sharpness),t.filter.blur!==0&&U.add("blur",t.filter.blur),t.filter.saturation!==0&&U.add("saturation",t.filter.saturation),t.filter.hue!==0&&U.add("hue",t.filter.hue),t.filter.negative&&U.add("negative"),t.filter.sepia&&U.add("sepia"),t.filter.vintage&&U.add("brownie"),t.filter.sepia&&U.add("sepia"),t.filter.kodachrome&&U.add("kodachrome"),t.filter.technicolor&&U.add("technicolor"),t.filter.polaroid&&U.add("polaroid"),t.filter.pixelate!==0&&U.add("pixelate",t.filter.pixelate),U.get()>0?$=U.apply(B):$=U.draw(B))):(y2(B,$),U&&(U=null),T.filter=!!U),!o)return{tensor:null,canvas:$};if(!$)throw new Error("canvas error: cannot create output");let l,c=3;if(typeof ImageData!="undefined"&&e instanceof ImageData||e.data&&e.width&&e.height)if(T.browser&&A.browser)l=A.browser?A.browser.fromPixels(e):null;else{c=e.data.length/e.height/e.width;let x=new Uint8Array(e.data.buffer);l=A.tensor(x,[e.height,e.width,c],"int32")}else if((!Me||$.width!==Me.width||$.height!==Me.height)&&(Me=y0($.width,$.height)),A.browser&&T.browser)t.backend==="webgl"||t.backend==="humangl"||t.backend==="webgpu"?l=A.browser.fromPixels($):(Me=y2($),l=A.browser.fromPixels(Me));else{let h=y2($).getContext("2d").getImageData(0,0,s,a);c=h.data.length/s/a;let p=new Uint8Array(h.data.buffer);l=A.tensor(p,[s,a,c])}if(c===4){let x=A.slice3d(l,[0,0,0],[-1,-1,3]);A.dispose(l),l=x}if(!l)throw new Error("input error: cannot create tensor");let d=A.cast(l,"float32"),y=t.filter.equalization?await i2(d):A.expandDims(d,0);return A.dispose([l,d]),{tensor:y,canvas:t.filter.return?$:null}}}async function D1(e,t){let o=!1;if(e.cacheSensitivity===0||!t.shape||t.shape.length!==4||t.shape[1]>2048||t.shape[2]>2048)return o;if(!F0.inputTensor)F0.inputTensor=A.clone(t);else if(F0.inputTensor.shape[1]!==t.shape[1]||F0.inputTensor.shape[2]!==t.shape[2])A.dispose(F0.inputTensor),F0.inputTensor=A.clone(t);else{let n={};n.diff=A.sub(t,F0.inputTensor),n.squared=A.mul(n.diff,n.diff),n.sum=A.sum(n.squared);let s=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;A.dispose([F0.inputTensor,n.diff,n.squared,n.sum]),F0.inputTensor=A.clone(t),o=s<=(e.cacheSensitivity||0)}return o}async function Z1(e,t,o){let n={};if(!t||!o||t.shape.length!==4||t.shape.length!==o.shape.length)return e.debug||u("invalid input tensor or tensor shapes do not match:",t.shape,o.shape),0;if(t.shape[0]!==1||o.shape[0]!==1||t.shape[3]!==3||o.shape[3]!==3)return e.debug||u("input tensors must be of shape [1, height, width, 3]:",t.shape,o.shape),0;n.input1=A.clone(t),n.input2=t.shape[1]!==o.shape[1]||t.shape[2]!==o.shape[2]?A.image.resizeBilinear(o,[t.shape[1],t.shape[2]]):A.clone(o),n.diff=A.sub(n.input1,n.input2),n.squared=A.mul(n.diff,n.diff),n.sum=A.sum(n.squared);let s=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;return A.dispose([n.input1,n.input2,n.diff,n.squared,n.sum]),s}var t5=class{constructor(){w(this,"browser");w(this,"node");w(this,"worker");w(this,"platform","");w(this,"agent","");w(this,"backends",[]);w(this,"initial");w(this,"filter");w(this,"tfjs");w(this,"offscreen");w(this,"perfadd",!1);w(this,"wasm",{supported:void 0,backend:void 0,simd:void 0,multithread:void 0});w(this,"webgl",{supported:void 0,backend:void 0,version:void 0,renderer:void 0});w(this,"webgpu",{supported:void 0,backend:void 0,adapter:void 0});w(this,"cpu",{model:void 0,flags:[]});w(this,"kernels",[]);w(this,"Canvas");w(this,"Image");w(this,"ImageData");if(this.browser=typeof navigator!="undefined",this.node=typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined",this.tfjs={version:Ye["tfjs-core"]},this.offscreen=typeof OffscreenCanvas!="undefined",this.initial=!0,this.worker=this.browser&&this.offscreen?typeof WorkerGlobalScope!="undefined":void 0,typeof navigator!="undefined"){let t=navigator.userAgent.match(/\(([^()]+)\)/g);if(t&&t[0]){let o=t[0].match(/\(([^()]+)\)/g);this.platform=o&&o[0]?o[0].replace(/\(|\)/g,""):"",this.agent=navigator.userAgent.replace(t[0],""),this.platform[1]&&(this.agent=this.agent.replace(t[1],"")),this.agent=this.agent.replace(/  /g," ")}}else typeof process!="undefined"&&(this.platform=`${process.platform} ${process.arch}`,this.agent=`NodeJS ${process.version}`)}async updateBackend(){this.backends=Object.keys(A.engine().registryFactory),this.wasm.supported=typeof WebAssembly!="undefined",this.wasm.backend=this.backends.includes("wasm"),this.wasm.supported&&this.wasm.backend&&A.getBackend()==="wasm"&&(this.wasm.simd=await A.env().getAsync("WASM_HAS_SIMD_SUPPORT"),this.wasm.multithread=await A.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT"));let t=y0(100,100),o=t?t.getContext("webgl2"):void 0;if(this.webgl.supported=typeof o!="undefined",this.webgl.backend=this.backends.includes("webgl"),this.webgl.supported&&this.webgl.backend&&(A.getBackend()==="webgl"||A.getBackend()==="humangl")){let n=A.backend().gpgpu!=="undefined"?await A.backend().getGPGPUContext().gl:null;n&&(this.webgl.version=n.getParameter(n.VERSION),this.webgl.renderer=n.getParameter(n.RENDERER))}this.webgpu.supported=this.browser&&typeof navigator.gpu!="undefined",this.webgpu.backend=this.backends.includes("webgpu");try{this.webgpu.supported&&(this.webgpu.adapter=(await navigator.gpu.requestAdapter()).name)}catch(n){this.webgpu.supported=!1}try{this.kernels=A.getKernelsForBackend(A.getBackend()).map(n=>n.kernelName.toLowerCase())}catch(n){}}async updateCPU(){let t={model:"",flags:[]};this.node&&this.platform.startsWith("linux"),this.cpu?this.cpu=t:Object.defineProperty(this,"cpu",{value:t})}},T=new t5;var o5={};U0(o5,{age:()=>Lo,antispoof:()=>Wo,blazeface:()=>Bo,"blazeface-back":()=>Fo,"blazeface-front":()=>Go,"blazepose-detector2d":()=>Ho,"blazepose-detector3d":()=>Vo,"blazepose-full":()=>Do,"blazepose-heavy":()=>Zo,"blazepose-lite":()=>Xo,default:()=>Tn,efficientpose:()=>qo,emotion:()=>Uo,faceboxes:()=>Yo,facemesh:()=>en,"facemesh-attention":()=>Jo,"facemesh-attention-alt":()=>Ko,"facemesh-detection-full":()=>Qo,"facemesh-detection-short":()=>_o,"facemesh-orig":()=>$o,faceres:()=>on,"faceres-deep":()=>tn,gear:()=>nn,gender:()=>An,"gender-ssrnet-imdb":()=>rn,handdetect:()=>sn,"handlandmark-full":()=>an,"handlandmark-lite":()=>ln,"handlandmark-sparse":()=>yn,handskeleton:()=>xn,handtrack:()=>cn,iris:()=>dn,liveness:()=>fn,"mb3-centernet":()=>mn,meet:()=>pn,mobileface:()=>un,mobilefacenet:()=>hn,"movenet-lightning":()=>bn,"movenet-multipose":()=>gn,"movenet-thunder":()=>Mn,nanodet:()=>Pn,posenet:()=>Rn,selfie:()=>vn});var Lo=161240,Wo=853098,Fo=538928,Go=402048,Bo=538928,Ho=7499400,Vo=5928856,Do=6338290,Zo=27501554,Xo=2725490,qo=5651240,Uo=820516,Yo=2013002,Ko=2387598,Jo=2382414,Qo=1026192,_o=201268,$o=2955780,en=1477958,tn=13957620,on=6978814,nn=1498916,rn=161236,An=201808,sn=3515612,an=5431368,ln=2023432,yn=5286322,xn=5502280,cn=2964837,dn=2599092,fn=592976,mn=4030290,pn=372228,un=2183192,hn=5171976,bn=4650216,gn=9448838,Mn=12477112,Pn=7574558,Rn=5032780,vn=212886,Tn={age:Lo,antispoof:Wo,"blazeface-back":Fo,"blazeface-front":Go,blazeface:Bo,"blazepose-detector2d":Ho,"blazepose-detector3d":Vo,"blazepose-full":Do,"blazepose-heavy":Zo,"blazepose-lite":Xo,efficientpose:qo,emotion:Uo,faceboxes:Yo,"facemesh-attention-alt":Ko,"facemesh-attention":Jo,"facemesh-detection-full":Qo,"facemesh-detection-short":_o,"facemesh-orig":$o,facemesh:en,"faceres-deep":tn,faceres:on,gear:nn,"gender-ssrnet-imdb":rn,gender:An,handdetect:sn,"handlandmark-full":an,"handlandmark-lite":ln,"handlandmark-sparse":yn,handskeleton:xn,handtrack:cn,iris:dn,liveness:fn,"mb3-centernet":mn,meet:pn,mobileface:un,mobilefacenet:hn,"movenet-lightning":bn,"movenet-multipose":gn,"movenet-thunder":Mn,nanodet:Pn,posenet:Rn,selfie:vn};var x0={cacheModels:!0,cacheSupported:!0,verbose:!0,debug:!1,modelBasePath:""},k0={};async function wn(e,t){return x0.debug&&u("load model fetch:",e,t),fetch(e,t)}function X1(e){x0.cacheModels=e.cacheModels,x0.verbose=e.debug,x0.modelBasePath=e.modelBasePath}async function L(e){var c,d,y;let t=O1(x0.modelBasePath,e||"");t.toLowerCase().endsWith(".json")||(t+=".json");let o=t.includes("/")?t.split("/"):t.split("\\"),n=o[o.length-1].replace(".json",""),r="indexeddb://"+n;k0[n]={name:n,sizeFromManifest:0,sizeLoadedWeights:0,sizeDesired:o5[n],inCache:!1},x0.cacheSupported=typeof window!="undefined"&&typeof window.localStorage!="undefined"&&typeof window.indexedDB!="undefined";let s={};try{s=x0.cacheSupported&&x0.cacheModels?await A.io.listModels():{}}catch(x){x0.cacheSupported=!1}k0[n].inCache=x0.cacheSupported&&x0.cacheModels&&Object.keys(s).includes(r);let a=typeof fetch=="undefined"?{}:{fetchFunc:(x,m)=>wn(x,m)},i=new _2(k0[n].inCache?r:t,a),l=!1;try{i.findIOHandler(),x0.debug&&u("model load handler:",i.handler);let x=await i.handler.load();k0[n].sizeFromManifest=((c=x==null?void 0:x.weightData)==null?void 0:c.byteLength)||0,i.loadSync(x),k0[n].sizeLoadedWeights=((y=(d=i==null?void 0:i.artifacts)==null?void 0:d.weightData)==null?void 0:y.byteLength)||0,x0.verbose&&u("load model:",i.modelUrl,{bytes:k0[n].sizeLoadedWeights},x0),l=!0}catch(x){u("error loading model:",t,x)}if(l&&x0.cacheModels&&x0.cacheSupported&&!k0[n].inCache)try{let x=await i.save(r);u("model saved:",r,x)}catch(x){u("error saving model:",t,x)}return i}var n5="2.9.1";var u1={};U0(u1,{Models:()=>r2,getModelStats:()=>f1,load:()=>m1,reset:()=>X2,validate:()=>p1});var v0,r5=[],zn=["white","black","asian","indian","other"],Sn=[15,23,28,35.5,45.5,55.5,65],q1=0,U1=0,A5=Number.MAX_SAFE_INTEGER;async function Y1(e){var t;return T.initial&&(v0=null),v0?e.debug&&u("cached model:",v0.modelUrl):v0=await L((t=e.face.gear)==null?void 0:t.modelPath),v0}async function s5(e,t,o,n){var a,i;if(!v0)return{age:0,gender:"unknown",genderScore:0,race:[]};let r=A5<(((a=t.face.gear)==null?void 0:a.skipFrames)||0),s=(((i=t.face.gear)==null?void 0:i.skipTime)||0)>b()-U1;return t.skipAllowed&&s&&r&&q1===n&&r5[o]?(A5++,r5[o]):(A5=0,new Promise(async l=>{var M,g;if(!(v0!=null&&v0.inputs[0].shape))return;let c={},d=[[0,.1,.9,.9]];c.resize=A.image.cropAndResize(e,d,[0],[v0.inputs[0].shape[2],v0.inputs[0].shape[1]]);let y={age:0,gender:"unknown",genderScore:0,race:[]};(M=t.face.gear)!=null&&M.enabled&&([c.age,c.gender,c.race]=v0.execute(c.resize,["age_output","gender_output","race_output"]));let x=await c.gender.data();y.gender=x[0]>x[1]?"male":"female",y.genderScore=Math.round(100*(x[0]>x[1]?x[0]:x[1]))/100;let m=await c.race.data();for(let f=0;f<m.length;f++)m[f]>(((g=t.face.gear)==null?void 0:g.minConfidence)||.2)&&y.race.push({score:Math.round(100*m[f])/100,race:zn[f]});y.race.sort((f,P)=>P.score-f.score);let p=Array.from(await c.age.data()).map((f,P)=>[Sn[P],f]).sort((f,P)=>P[1]-f[1]),R=p[0][0];for(let f=1;f<p.length;f++)R+=p[f][1]*(p[f][0]-R);y.age=Math.round(10*R)/10,Object.keys(c).forEach(f=>A.dispose(c[f])),r5[o]=y,q1=n,U1=b(),l(y)}))}var G={tf255:255,tf1:1,tf2:2,tf05:.5,tf127:127.5,rgb:[.2989,.587,.114]};function J1(){G.tf255=A.scalar(255,"float32"),G.tf1=A.scalar(1,"float32"),G.tf2=A.scalar(2,"float32"),G.tf05=A.scalar(.5,"float32"),G.tf127=A.scalar(127.5,"float32"),G.rgb=A.tensor1d([.2989,.587,.114],"float32")}var f0,x2=[],Q1=0,_1=0,a5=Number.MAX_SAFE_INTEGER;async function $1(e){return T.initial&&(f0=null),f0?e.debug&&u("cached model:",f0.modelUrl):f0=await L(e.face.ssrnet.modelPathAge),f0}async function i5(e,t,o,n){var a,i,l,c;if(!f0)return{age:0};let r=a5<(((a=t.face.ssrnet)==null?void 0:a.skipFrames)||0),s=(((i=t.face.ssrnet)==null?void 0:i.skipTime)||0)>b()-_1;return t.skipAllowed&&r&&s&&Q1===n&&((l=x2[o])==null?void 0:l.age)&&((c=x2[o])==null?void 0:c.age)>0?(a5++,x2[o]):(a5=0,new Promise(async d=>{if(!(f0!=null&&f0.inputs)||!f0.inputs[0]||!f0.inputs[0].shape)return;let y={};y.resize=A.image.resizeBilinear(e,[f0.inputs[0].shape[2],f0.inputs[0].shape[1]],!1),y.enhance=A.mul(y.resize,G.tf255);let x={age:0};if(t.face.ssrnet.enabled&&(y.age=f0.execute(y.enhance)),y.age){let m=await y.age.data();x.age=Math.trunc(10*m[0])/10}Object.keys(y).forEach(m=>A.dispose(y[m])),x2[o]=x,Q1=n,_1=b(),d(x)}))}var T0,c2=[],tt=0,ot=0,l5=Number.MAX_SAFE_INTEGER,y5=[.2989,.587,.114];async function nt(e){return T.initial&&(T0=null),T0?e.debug&&u("cached model:",T0.modelUrl):T0=await L(e.face.ssrnet.modelPathGender),T0}async function x5(e,t,o,n){var a,i,l,c;if(!T0)return{gender:"unknown",genderScore:0};let r=l5<(((a=t.face.ssrnet)==null?void 0:a.skipFrames)||0),s=(((i=t.face.ssrnet)==null?void 0:i.skipTime)||0)>b()-ot;return t.skipAllowed&&r&&s&&tt===n&&((l=c2[o])==null?void 0:l.gender)&&((c=c2[o])==null?void 0:c.genderScore)>0?(l5++,c2[o]):(l5=0,new Promise(async d=>{if(!(T0!=null&&T0.inputs[0].shape))return;let y={};y.resize=A.image.resizeBilinear(e,[T0.inputs[0].shape[2],T0.inputs[0].shape[1]],!1),y.enhance=A.tidy(()=>{let[h,p,R]=A.split(y.resize,3,3),M=A.mul(h,y5[0]),g=A.mul(p,y5[1]),f=A.mul(R,y5[2]),P=A.addN([M,g,f]);return A.mul(A.sub(P,G.tf05),2)});let x={gender:"unknown",genderScore:0};t.face.ssrnet.enabled&&(y.gender=T0.execute(y.enhance));let m=await y.gender.data();x.gender=m[0]>m[1]?"female":"male",x.genderScore=m[0]>m[1]?Math.trunc(100*m[0])/100:Math.trunc(100*m[1])/100,Object.keys(y).forEach(h=>A.dispose(y[h])),c2[o]=x,tt=n,ot=b(),d(x)}))}var A0,d2=[],c5=Number.MAX_SAFE_INTEGER,At=0,st=0;async function at(e){var t;return T.initial&&(A0=null),A0?e.debug&&u("cached model:",A0.modelUrl):A0=await L((t=e.face.antispoof)==null?void 0:t.modelPath),A0}async function d5(e,t,o,n){var a,i;if(!A0)return 0;let r=(((a=t.face.antispoof)==null?void 0:a.skipTime)||0)>b()-st,s=c5<(((i=t.face.antispoof)==null?void 0:i.skipFrames)||0);return t.skipAllowed&&r&&s&&At===n&&d2[o]?(c5++,d2[o]):(c5=0,new Promise(async l=>{let c=A.image.resizeBilinear(e,[A0!=null&&A0.inputs[0].shape?A0.inputs[0].shape[2]:0,A0!=null&&A0.inputs[0].shape?A0.inputs[0].shape[1]:0],!1),d=A0==null?void 0:A0.execute(c),y=(await d.data())[0];d2[o]=Math.round(100*y)/100,At=n,st=b(),A.dispose([c,d]),l(d2[o])}))}var w0={silhouette:[10,338,297,332,284,251,389,356,454,323,361,288,397,365,379,378,400,377,152,148,176,149,150,136,172,58,132,93,234,127,162,21,54,103,67,109],lipsUpperOuter:[185,40,39,37,0,267,269,270,409],lipsLowerOuter:[61,146,91,181,84,17,314,405,321,375,291],lipsUpperInner:[191,80,81,82,13,312,311,310,415],lipsLowerInner:[78,95,88,178,87,14,317,402,318,324,308],lipsLowerSemiOuter:[76,77,90,180,85,16,315,404,320,307,306],lipsUpperSemiOuter:[184,74,73,72,11,302,303,304,408],lipsLowerSemiInner:[62,96,89,179,86,15,316,403,319,325,292],lipsUpperSemiInner:[183,42,41,38,12,268,271,272,407],rightEyeUpper0:[246,161,160,159,158,157,173],rightEyeLower0:[33,7,163,144,145,153,154,155,133],rightEyeUpper1:[247,30,29,27,28,56,190],rightEyeLower1:[130,25,110,24,23,22,26,112,243],rightEyeUpper2:[113,225,224,223,222,221,189],rightEyeLower2:[226,31,228,229,230,231,232,233,244],rightEyeLower3:[143,111,117,118,119,120,121,128,245],rightEyebrowUpper:[156,70,63,105,66,107,55,193],rightEyebrowLower:[35,124,46,53,52,65],rightEyeIris:[473,474,475,476,477],leftEyeUpper0:[466,388,387,386,385,384,398],leftEyeLower0:[263,249,390,373,374,380,381,382,362],leftEyeUpper1:[467,260,259,257,258,286,414],leftEyeLower1:[359,255,339,254,253,252,256,341,463],leftEyeUpper2:[342,445,444,443,442,441,413],leftEyeLower2:[446,261,448,449,450,451,452,453,464],leftEyeLower3:[372,340,346,347,348,349,350,357,465],leftEyebrowUpper:[383,300,293,334,296,336,285,417],leftEyebrowLower:[265,353,276,283,282,295],leftEyeIris:[468,469,470,471,472],midwayBetweenEyes:[168],noseTip:[1],noseBottom:[2],noseRightCorner:[98],noseLeftCorner:[327],rightCheek:[205],leftCheek:[425]},f5={count:468,mouth:13,symmetryLine:[13,w0.midwayBetweenEyes[0]]},ae={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},m5=[{key:"EyeUpper0",indices:[9,10,11,12,13,14,15]},{key:"EyeUpper1",indices:[25,26,27,28,29,30,31]},{key:"EyeUpper2",indices:[41,42,43,44,45,46,47]},{key:"EyeLower0",indices:[0,1,2,3,4,5,6,7,8]},{key:"EyeLower1",indices:[16,17,18,19,20,21,22,23,24]},{key:"EyeLower2",indices:[32,33,34,35,36,37,38,39,40]},{key:"EyeLower3",indices:[54,55,56,57,58,59,60,61,62]},{key:"EyebrowUpper",indices:[63,64,65,66,67,68,69,70]},{key:"EyebrowLower",indices:[48,49,50,51,52,53]}],Je=[[.499976992607117,.652534008026123],[.500025987625122,.547487020492554],[.499974012374878,.602371990680695],[.482113003730774,.471979022026062],[.500150978565216,.527155995368958],[.499909996986389,.498252987861633],[.499523013830185,.40106201171875],[.289712011814117,.380764007568359],[.499954998493195,.312398016452789],[.499987006187439,.269918978214264],[.500023007392883,.107050001621246],[.500023007392883,.666234016418457],[.5000159740448,.679224014282227],[.500023007392883,.692348003387451],[.499976992607117,.695277988910675],[.499976992607117,.70593398809433],[.499976992607117,.719385027885437],[.499976992607117,.737019002437592],[.499967992305756,.781370997428894],[.499816000461578,.562981009483337],[.473773002624512,.573909997940063],[.104906998574734,.254140973091125],[.365929991006851,.409575998783112],[.338757991790771,.41302502155304],[.311120003461838,.409460008144379],[.274657994508743,.389131009578705],[.393361985683441,.403706014156342],[.345234006643295,.344011008739471],[.370094001293182,.346076011657715],[.319321990013123,.347265005111694],[.297903001308441,.353591024875641],[.24779200553894,.410809993743896],[.396889001131058,.842755019664764],[.280097991228104,.375599980354309],[.106310002505779,.399955987930298],[.2099249958992,.391353011131287],[.355807989835739,.534406006336212],[.471751004457474,.65040397644043],[.474155008792877,.680191993713379],[.439785003662109,.657229006290436],[.414617002010345,.66654098033905],[.450374007225037,.680860996246338],[.428770989179611,.682690978050232],[.374971002340317,.727805018424988],[.486716985702515,.547628998756409],[.485300987958908,.527395009994507],[.257764995098114,.314490020275116],[.401223003864288,.455172002315521],[.429818987846375,.548614978790283],[.421351999044418,.533740997314453],[.276895999908447,.532056987285614],[.483370006084442,.499586999416351],[.33721199631691,.282882988452911],[.296391993761063,.293242990970612],[.169294998049736,.193813979625702],[.447580009698868,.302609980106354],[.392390012741089,.353887975215912],[.354490011930466,.696784019470215],[.067304998636246,.730105042457581],[.442739009857178,.572826027870178],[.457098007202148,.584792017936707],[.381974011659622,.694710969924927],[.392388999462128,.694203019142151],[.277076005935669,.271932005882263],[.422551989555359,.563233017921448],[.385919004678726,.281364023685455],[.383103013038635,.255840003490448],[.331431001424789,.119714021682739],[.229923993349075,.232002973556519],[.364500999450684,.189113974571228],[.229622006416321,.299540996551514],[.173287004232407,.278747975826263],[.472878992557526,.666198015213013],[.446828007698059,.668527007102966],[.422762006521225,.673889994621277],[.445307999849319,.580065965652466],[.388103008270264,.693961024284363],[.403039008378983,.706539988517761],[.403629004955292,.693953037261963],[.460041999816895,.557139039039612],[.431158006191254,.692366003990173],[.452181994915009,.692366003990173],[.475387006998062,.692366003990173],[.465828001499176,.779190003871918],[.472328990697861,.736225962638855],[.473087012767792,.717857003211975],[.473122000694275,.704625964164734],[.473033010959625,.695277988910675],[.427942007780075,.695277988910675],[.426479011774063,.703539967536926],[.423162013292313,.711845993995667],[.4183090031147,.720062971115112],[.390094995498657,.639572978019714],[.013953999616206,.560034036636353],[.499913990497589,.58014702796936],[.413199990987778,.69539999961853],[.409626007080078,.701822996139526],[.468080013990402,.601534962654114],[.422728985548019,.585985004901886],[.463079988956451,.593783974647522],[.37211999297142,.47341400384903],[.334562003612518,.496073007583618],[.411671012639999,.546965003013611],[.242175996303558,.14767599105835],[.290776997804642,.201445996761322],[.327338010072708,.256527006626129],[.399509996175766,.748921036720276],[.441727995872498,.261676013469696],[.429764986038208,.187834024429321],[.412198007106781,.108901023864746],[.288955003023148,.398952007293701],[.218936994671822,.435410976409912],[.41278201341629,.398970007896423],[.257135003805161,.355440020561218],[.427684992551804,.437960982322693],[.448339998722076,.536936044692993],[.178560003638268,.45755398273468],[.247308000922203,.457193970680237],[.286267012357712,.467674970626831],[.332827985286713,.460712015628815],[.368755996227264,.447206974029541],[.398963987827301,.432654976844788],[.476410001516342,.405806005001068],[.189241006970406,.523923993110657],[.228962004184723,.348950982093811],[.490725994110107,.562400996685028],[.404670000076294,.485132992267609],[.019469000399113,.401564002037048],[.426243007183075,.420431017875671],[.396993011236191,.548797011375427],[.266469985246658,.376977026462555],[.439121007919312,.51895797252655],[.032313998788595,.644356966018677],[.419054001569748,.387154996395111],[.462783008813858,.505746960639954],[.238978996872902,.779744982719421],[.198220998048782,.831938028335571],[.107550002634525,.540755033493042],[.183610007166862,.740257024765015],[.134409993886948,.333683013916016],[.385764002799988,.883153975009918],[.490967005491257,.579378008842468],[.382384985685349,.508572995662689],[.174399003386497,.397670984268188],[.318785011768341,.39623498916626],[.343364000320435,.400596976280212],[.396100014448166,.710216999053955],[.187885001301765,.588537991046906],[.430987000465393,.944064974784851],[.318993002176285,.898285031318665],[.266247987747192,.869701027870178],[.500023007392883,.190576016902924],[.499976992607117,.954452991485596],[.366169989109039,.398822009563446],[.393207013607025,.39553701877594],[.410373002290726,.391080021858215],[.194993004202843,.342101991176605],[.388664990663528,.362284004688263],[.365961998701096,.355970978736877],[.343364000320435,.355356991291046],[.318785011768341,.35834002494812],[.301414996385574,.363156020641327],[.058132998645306,.319076001644135],[.301414996385574,.387449026107788],[.499987989664078,.618434011936188],[.415838003158569,.624195992946625],[.445681989192963,.566076993942261],[.465844005346298,.620640993118286],[.49992299079895,.351523995399475],[.288718998432159,.819945991039276],[.335278987884521,.852819979190826],[.440512001514435,.902418971061707],[.128294005990028,.791940987110138],[.408771991729736,.373893976211548],[.455606997013092,.451801002025604],[.499877005815506,.908990025520325],[.375436991453171,.924192011356354],[.11421000212431,.615022003650665],[.448662012815475,.695277988910675],[.4480200111866,.704632043838501],[.447111994028091,.715808033943176],[.444831997156143,.730794012546539],[.430011987686157,.766808986663818],[.406787008047104,.685672998428345],[.400738000869751,.681069016456604],[.392399996519089,.677703022956848],[.367855995893478,.663918972015381],[.247923001646996,.601333022117615],[.452769994735718,.420849978923798],[.43639200925827,.359887003898621],[.416164010763168,.368713974952698],[.413385987281799,.692366003990173],[.228018000721931,.683571994304657],[.468268007040024,.352671027183533],[.411361992359161,.804327011108398],[.499989002943039,.469825029373169],[.479153990745544,.442654013633728],[.499974012374878,.439637005329132],[.432112008333206,.493588984012604],[.499886006116867,.866917014122009],[.49991300702095,.821729004383087],[.456548988819122,.819200992584229],[.344549000263214,.745438992977142],[.37890899181366,.574010014533997],[.374292999505997,.780184984207153],[.319687992334366,.570737957954407],[.357154995203018,.604269981384277],[.295284003019333,.621580958366394],[.447750002145767,.862477004528046],[.410986006259918,.508723020553589],[.31395098567009,.775308012962341],[.354128003120422,.812552988529205],[.324548006057739,.703992962837219],[.189096003770828,.646299958229065],[.279776990413666,.71465802192688],[.1338230073452,.682700991630554],[.336768001317978,.644733011722565],[.429883986711502,.466521978378296],[.455527991056442,.548622965812683],[.437114000320435,.558896005153656],[.467287987470627,.529924988746643],[.414712011814117,.335219979286194],[.37704598903656,.322777986526489],[.344107985496521,.320150971412659],[.312875986099243,.32233202457428],[.283526003360748,.333190023899078],[.241245999932289,.382785975933075],[.102986000478268,.468762993812561],[.267612010240555,.424560010433197],[.297879010438919,.433175981044769],[.333433985710144,.433878004550934],[.366427004337311,.426115989685059],[.396012008190155,.416696012020111],[.420121014118195,.41022801399231],[.007561000064015,.480777025222778],[.432949006557465,.569517970085144],[.458638995885849,.479089021682739],[.473466008901596,.545744001865387],[.476087987422943,.563830018043518],[.468472003936768,.555056989192963],[.433990985155106,.582361996173859],[.483518004417419,.562983989715576],[.482482999563217,.57784903049469],[.42645001411438,.389798998832703],[.438998997211456,.39649498462677],[.450067013502121,.400434017181396],[.289712011814117,.368252992630005],[.276670008897781,.363372981548309],[.517862021923065,.471948027610779],[.710287988185883,.380764007568359],[.526226997375488,.573909997940063],[.895093023777008,.254140973091125],[.634069979190826,.409575998783112],[.661242008209229,.41302502155304],[.688880026340485,.409460008144379],[.725341975688934,.389131009578705],[.606630027294159,.40370500087738],[.654766023159027,.344011008739471],[.629905998706818,.346076011657715],[.680678009986877,.347265005111694],[.702096998691559,.353591024875641],[.75221198797226,.410804986953735],[.602918028831482,.842862963676453],[.719901978969574,.375599980354309],[.893692970275879,.399959981441498],[.790081977844238,.391354024410248],[.643998026847839,.534487962722778],[.528249025344849,.65040397644043],[.525849997997284,.680191040039062],[.560214996337891,.657229006290436],[.585384011268616,.66654098033905],[.549625992774963,.680860996246338],[.57122802734375,.682691991329193],[.624852001667023,.72809898853302],[.513050019741058,.547281980514526],[.51509702205658,.527251958847046],[.742246985435486,.314507007598877],[.598631024360657,.454979002475739],[.570338010787964,.548575043678284],[.578631997108459,.533622980117798],[.723087012767792,.532054007053375],[.516445994377136,.499638974666595],[.662801027297974,.282917976379395],[.70362401008606,.293271005153656],[.830704987049103,.193813979625702],[.552385985851288,.302568018436432],[.607609987258911,.353887975215912],[.645429015159607,.696707010269165],[.932694971561432,.730105042457581],[.557260990142822,.572826027870178],[.542901992797852,.584792017936707],[.6180260181427,.694710969924927],[.607590973377228,.694203019142151],[.722943007946014,.271963000297546],[.577413976192474,.563166975975037],[.614082992076874,.281386971473694],[.616907000541687,.255886018276215],[.668509006500244,.119913995265961],[.770092010498047,.232020974159241],[.635536015033722,.189248979091644],[.77039098739624,.299556016921997],[.826722025871277,.278755009174347],[.527121007442474,.666198015213013],[.553171992301941,.668527007102966],[.577238023281097,.673889994621277],[.554691970348358,.580065965652466],[.611896991729736,.693961024284363],[.59696102142334,.706539988517761],[.596370995044708,.693953037261963],[.539958000183105,.557139039039612],[.568841993808746,.692366003990173],[.547818005084991,.692366003990173],[.52461302280426,.692366003990173],[.534089982509613,.779141008853912],[.527670979499817,.736225962638855],[.526912987232208,.717857003211975],[.526877999305725,.704625964164734],[.526966989040375,.695277988910675],[.572058022022247,.695277988910675],[.573521018028259,.703539967536926],[.57683801651001,.711845993995667],[.581691026687622,.720062971115112],[.609944999217987,.639909982681274],[.986046016216278,.560034036636353],[.5867999792099,.69539999961853],[.590372025966644,.701822996139526],[.531915009021759,.601536989212036],[.577268004417419,.585934996604919],[.536915004253387,.593786001205444],[.627542972564697,.473352015018463],[.665585994720459,.495950996875763],[.588353991508484,.546862006187439],[.757824003696442,.14767599105835],[.709249973297119,.201507985591888],[.672684013843536,.256581008434296],[.600408971309662,.74900496006012],[.55826598405838,.261672019958496],[.570303976535797,.187870979309082],[.588165998458862,.109044015407562],[.711045026779175,.398952007293701],[.781069993972778,.435405015945435],[.587247014045715,.398931980133057],[.742869973182678,.355445981025696],[.572156012058258,.437651991844177],[.55186802148819,.536570012569427],[.821442008018494,.457556009292603],[.752701997756958,.457181990146637],[.71375697851181,.467626988887787],[.66711300611496,.460672974586487],[.631101012229919,.447153985500336],[.6008620262146,.432473003864288],[.523481011390686,.405627012252808],[.810747981071472,.523926019668579],[.771045982837677,.348959028720856],[.509127020835876,.562718033790588],[.595292985439301,.485023975372314],[.980530977249146,.401564002037048],[.573499977588654,.420000016689301],[.602994978427887,.548687994480133],[.733529984951019,.376977026462555],[.560611009597778,.519016981124878],[.967685997486115,.644356966018677],[.580985009670258,.387160003185272],[.537728011608124,.505385041236877],[.760966002941132,.779752969741821],[.801778972148895,.831938028335571],[.892440974712372,.54076099395752],[.816350996494293,.740260004997253],[.865594983100891,.333687007427216],[.614073991775513,.883246004581451],[.508952975273132,.579437971115112],[.617941975593567,.508316040039062],[.825608015060425,.397674977779388],[.681214988231659,.39623498916626],[.656635999679565,.400596976280212],[.603900015354156,.710216999053955],[.81208598613739,.588539004325867],[.56801301240921,.944564998149872],[.681007981300354,.898285031318665],[.733752012252808,.869701027870178],[.633830010890961,.398822009563446],[.606792986392975,.39553701877594],[.589659988880157,.391062021255493],[.805015981197357,.342108011245728],[.611334979534149,.362284004688263],[.634037971496582,.355970978736877],[.656635999679565,.355356991291046],[.681214988231659,.35834002494812],[.698584973812103,.363156020641327],[.941866993904114,.319076001644135],[.698584973812103,.387449026107788],[.584177017211914,.624107003211975],[.554318010807037,.566076993942261],[.534153997898102,.62064003944397],[.711217999458313,.819975018501282],[.664629995822906,.852871000766754],[.559099972248077,.902631998062134],[.871706008911133,.791940987110138],[.591234028339386,.373893976211548],[.544341027736664,.451583981513977],[.624562978744507,.924192011356354],[.88577002286911,.615028977394104],[.551338016986847,.695277988910675],[.551980018615723,.704632043838501],[.552887976169586,.715808033943176],[.555167973041534,.730794012546539],[.569944024085999,.767035007476807],[.593203008174896,.685675978660583],[.599261999130249,.681069016456604],[.607599973678589,.677703022956848],[.631937980651855,.663500010967255],[.752032995223999,.601315021514893],[.547226011753082,.420395016670227],[.563543975353241,.359827995300293],[.583841025829315,.368713974952698],[.586614012718201,.692366003990173],[.771915018558502,.683578014373779],[.531597018241882,.352482974529266],[.588370978832245,.804440975189209],[.52079701423645,.442565023899078],[.567984998226166,.493479013442993],[.543282985687256,.819254994392395],[.655317008495331,.745514988899231],[.621008992195129,.574018001556396],[.625559985637665,.78031200170517],[.680198013782501,.570719003677368],[.64276397228241,.604337990283966],[.704662978649139,.621529996395111],[.552012026309967,.862591981887817],[.589071989059448,.508637011051178],[.685944974422455,.775357007980347],[.645735025405884,.812640011310577],[.675342977046967,.703978002071381],[.810858011245728,.646304965019226],[.72012197971344,.714666962623596],[.866151988506317,.682704985141754],[.663187026977539,.644596993923187],[.570082008838654,.466325998306274],[.544561982154846,.548375964164734],[.562758982181549,.558784961700439],[.531987011432648,.530140042304993],[.585271000862122,.335177004337311],[.622952997684479,.32277899980545],[.655896008014679,.320163011550903],[.687132000923157,.322345972061157],[.716481983661652,.333200991153717],[.758756995201111,.382786989212036],[.897013008594513,.468769013881683],[.732392013072968,.424547016620636],[.70211398601532,.433162987232208],[.66652500629425,.433866024017334],[.633504986763,.426087975502014],[.603875994682312,.416586995124817],[.579657971858978,.409945011138916],[.992439985275269,.480777025222778],[.567192018032074,.569419980049133],[.54136598110199,.478899002075195],[.526564002037048,.546118021011353],[.523913025856018,.563830018043518],[.531529009342194,.555056989192963],[.566035985946655,.582329034805298],[.51631098985672,.563053965568542],[.5174720287323,.577877044677734],[.573594987392426,.389806985855103],[.560697972774506,.395331978797913],[.549755990505219,.399751007556915],[.710287988185883,.368252992630005],[.723330020904541,.363372981548309]],ie=[127,34,139,11,0,37,232,231,120,72,37,39,128,121,47,232,121,128,104,69,67,175,171,148,157,154,155,118,50,101,73,39,40,9,151,108,48,115,131,194,204,211,74,40,185,80,42,183,40,92,186,230,229,118,202,212,214,83,18,17,76,61,146,160,29,30,56,157,173,106,204,194,135,214,192,203,165,98,21,71,68,51,45,4,144,24,23,77,146,91,205,50,187,201,200,18,91,106,182,90,91,181,85,84,17,206,203,36,148,171,140,92,40,39,193,189,244,159,158,28,247,246,161,236,3,196,54,68,104,193,168,8,117,228,31,189,193,55,98,97,99,126,47,100,166,79,218,155,154,26,209,49,131,135,136,150,47,126,217,223,52,53,45,51,134,211,170,140,67,69,108,43,106,91,230,119,120,226,130,247,63,53,52,238,20,242,46,70,156,78,62,96,46,53,63,143,34,227,173,155,133,123,117,111,44,125,19,236,134,51,216,206,205,154,153,22,39,37,167,200,201,208,36,142,100,57,212,202,20,60,99,28,158,157,35,226,113,160,159,27,204,202,210,113,225,46,43,202,204,62,76,77,137,123,116,41,38,72,203,129,142,64,98,240,49,102,64,41,73,74,212,216,207,42,74,184,169,170,211,170,149,176,105,66,69,122,6,168,123,147,187,96,77,90,65,55,107,89,90,180,101,100,120,63,105,104,93,137,227,15,86,85,129,102,49,14,87,86,55,8,9,100,47,121,145,23,22,88,89,179,6,122,196,88,95,96,138,172,136,215,58,172,115,48,219,42,80,81,195,3,51,43,146,61,171,175,199,81,82,38,53,46,225,144,163,110,246,33,7,52,65,66,229,228,117,34,127,234,107,108,69,109,108,151,48,64,235,62,78,191,129,209,126,111,35,143,163,161,246,117,123,50,222,65,52,19,125,141,221,55,65,3,195,197,25,7,33,220,237,44,70,71,139,122,193,245,247,130,33,71,21,162,153,158,159,170,169,150,188,174,196,216,186,92,144,160,161,2,97,167,141,125,241,164,167,37,72,38,12,145,159,160,38,82,13,63,68,71,226,35,111,158,153,154,101,50,205,206,92,165,209,198,217,165,167,97,220,115,218,133,112,243,239,238,241,214,135,169,190,173,133,171,208,32,125,44,237,86,87,178,85,86,179,84,85,180,83,84,181,201,83,182,137,93,132,76,62,183,61,76,184,57,61,185,212,57,186,214,207,187,34,143,156,79,239,237,123,137,177,44,1,4,201,194,32,64,102,129,213,215,138,59,166,219,242,99,97,2,94,141,75,59,235,24,110,228,25,130,226,23,24,229,22,23,230,26,22,231,112,26,232,189,190,243,221,56,190,28,56,221,27,28,222,29,27,223,30,29,224,247,30,225,238,79,20,166,59,75,60,75,240,147,177,215,20,79,166,187,147,213,112,233,244,233,128,245,128,114,188,114,217,174,131,115,220,217,198,236,198,131,134,177,132,58,143,35,124,110,163,7,228,110,25,356,389,368,11,302,267,452,350,349,302,303,269,357,343,277,452,453,357,333,332,297,175,152,377,384,398,382,347,348,330,303,304,270,9,336,337,278,279,360,418,262,431,304,408,409,310,415,407,270,409,410,450,348,347,422,430,434,313,314,17,306,307,375,387,388,260,286,414,398,335,406,418,364,367,416,423,358,327,251,284,298,281,5,4,373,374,253,307,320,321,425,427,411,421,313,18,321,405,406,320,404,405,315,16,17,426,425,266,377,400,369,322,391,269,417,465,464,386,257,258,466,260,388,456,399,419,284,332,333,417,285,8,346,340,261,413,441,285,327,460,328,355,371,329,392,439,438,382,341,256,429,420,360,364,394,379,277,343,437,443,444,283,275,440,363,431,262,369,297,338,337,273,375,321,450,451,349,446,342,467,293,334,282,458,461,462,276,353,383,308,324,325,276,300,293,372,345,447,382,398,362,352,345,340,274,1,19,456,248,281,436,427,425,381,256,252,269,391,393,200,199,428,266,330,329,287,273,422,250,462,328,258,286,384,265,353,342,387,259,257,424,431,430,342,353,276,273,335,424,292,325,307,366,447,345,271,303,302,423,266,371,294,455,460,279,278,294,271,272,304,432,434,427,272,407,408,394,430,431,395,369,400,334,333,299,351,417,168,352,280,411,325,319,320,295,296,336,319,403,404,330,348,349,293,298,333,323,454,447,15,16,315,358,429,279,14,15,316,285,336,9,329,349,350,374,380,252,318,402,403,6,197,419,318,319,325,367,364,365,435,367,397,344,438,439,272,271,311,195,5,281,273,287,291,396,428,199,311,271,268,283,444,445,373,254,339,263,466,249,282,334,296,449,347,346,264,447,454,336,296,299,338,10,151,278,439,455,292,407,415,358,371,355,340,345,372,390,249,466,346,347,280,442,443,282,19,94,370,441,442,295,248,419,197,263,255,359,440,275,274,300,383,368,351,412,465,263,467,466,301,368,389,380,374,386,395,378,379,412,351,419,436,426,322,373,390,388,2,164,393,370,462,461,164,0,267,302,11,12,374,373,387,268,12,13,293,300,301,446,261,340,385,384,381,330,266,425,426,423,391,429,355,437,391,327,326,440,457,438,341,382,362,459,457,461,434,430,394,414,463,362,396,369,262,354,461,457,316,403,402,315,404,403,314,405,404,313,406,405,421,418,406,366,401,361,306,408,407,291,409,408,287,410,409,432,436,410,434,416,411,264,368,383,309,438,457,352,376,401,274,275,4,421,428,262,294,327,358,433,416,367,289,455,439,462,370,326,2,326,370,305,460,455,254,449,448,255,261,446,253,450,449,252,451,450,256,452,451,341,453,452,413,464,463,441,413,414,258,442,441,257,443,442,259,444,443,260,445,444,467,342,445,459,458,250,289,392,290,290,328,460,376,433,435,250,290,392,411,416,433,341,463,464,453,464,465,357,465,412,343,412,399,360,363,440,437,399,456,420,456,363,401,435,288,372,383,353,339,255,249,448,261,255,133,243,190,133,155,112,33,246,247,33,130,25,398,384,286,362,398,414,362,463,341,263,359,467,263,249,255,466,467,260,75,60,166,238,239,79,162,127,139,72,11,37,121,232,120,73,72,39,114,128,47,233,232,128,103,104,67,152,175,148,173,157,155,119,118,101,74,73,40,107,9,108,49,48,131,32,194,211,184,74,185,191,80,183,185,40,186,119,230,118,210,202,214,84,83,17,77,76,146,161,160,30,190,56,173,182,106,194,138,135,192,129,203,98,54,21,68,5,51,4,145,144,23,90,77,91,207,205,187,83,201,18,181,91,182,180,90,181,16,85,17,205,206,36,176,148,140,165,92,39,245,193,244,27,159,28,30,247,161,174,236,196,103,54,104,55,193,8,111,117,31,221,189,55,240,98,99,142,126,100,219,166,218,112,155,26,198,209,131,169,135,150,114,47,217,224,223,53,220,45,134,32,211,140,109,67,108,146,43,91,231,230,120,113,226,247,105,63,52,241,238,242,124,46,156,95,78,96,70,46,63,116,143,227,116,123,111,1,44,19,3,236,51,207,216,205,26,154,22,165,39,167,199,200,208,101,36,100,43,57,202,242,20,99,56,28,157,124,35,113,29,160,27,211,204,210,124,113,46,106,43,204,96,62,77,227,137,116,73,41,72,36,203,142,235,64,240,48,49,64,42,41,74,214,212,207,183,42,184,210,169,211,140,170,176,104,105,69,193,122,168,50,123,187,89,96,90,66,65,107,179,89,180,119,101,120,68,63,104,234,93,227,16,15,85,209,129,49,15,14,86,107,55,9,120,100,121,153,145,22,178,88,179,197,6,196,89,88,96,135,138,136,138,215,172,218,115,219,41,42,81,5,195,51,57,43,61,208,171,199,41,81,38,224,53,225,24,144,110,105,52,66,118,229,117,227,34,234,66,107,69,10,109,151,219,48,235,183,62,191,142,129,126,116,111,143,7,163,246,118,117,50,223,222,52,94,19,141,222,221,65,196,3,197,45,220,44,156,70,139,188,122,245,139,71,162,145,153,159,149,170,150,122,188,196,206,216,92,163,144,161,164,2,167,242,141,241,0,164,37,11,72,12,144,145,160,12,38,13,70,63,71,31,226,111,157,158,154,36,101,205,203,206,165,126,209,217,98,165,97,237,220,218,237,239,241,210,214,169,140,171,32,241,125,237,179,86,178,180,85,179,181,84,180,182,83,181,194,201,182,177,137,132,184,76,183,185,61,184,186,57,185,216,212,186,192,214,187,139,34,156,218,79,237,147,123,177,45,44,4,208,201,32,98,64,129,192,213,138,235,59,219,141,242,97,97,2,141,240,75,235,229,24,228,31,25,226,230,23,229,231,22,230,232,26,231,233,112,232,244,189,243,189,221,190,222,28,221,223,27,222,224,29,223,225,30,224,113,247,225,99,60,240,213,147,215,60,20,166,192,187,213,243,112,244,244,233,245,245,128,188,188,114,174,134,131,220,174,217,236,236,198,134,215,177,58,156,143,124,25,110,7,31,228,25,264,356,368,0,11,267,451,452,349,267,302,269,350,357,277,350,452,357,299,333,297,396,175,377,381,384,382,280,347,330,269,303,270,151,9,337,344,278,360,424,418,431,270,304,409,272,310,407,322,270,410,449,450,347,432,422,434,18,313,17,291,306,375,259,387,260,424,335,418,434,364,416,391,423,327,301,251,298,275,281,4,254,373,253,375,307,321,280,425,411,200,421,18,335,321,406,321,320,405,314,315,17,423,426,266,396,377,369,270,322,269,413,417,464,385,386,258,248,456,419,298,284,333,168,417,8,448,346,261,417,413,285,326,327,328,277,355,329,309,392,438,381,382,256,279,429,360,365,364,379,355,277,437,282,443,283,281,275,363,395,431,369,299,297,337,335,273,321,348,450,349,359,446,467,283,293,282,250,458,462,300,276,383,292,308,325,283,276,293,264,372,447,346,352,340,354,274,19,363,456,281,426,436,425,380,381,252,267,269,393,421,200,428,371,266,329,432,287,422,290,250,328,385,258,384,446,265,342,386,387,257,422,424,430,445,342,276,422,273,424,306,292,307,352,366,345,268,271,302,358,423,371,327,294,460,331,279,294,303,271,304,436,432,427,304,272,408,395,394,431,378,395,400,296,334,299,6,351,168,376,352,411,307,325,320,285,295,336,320,319,404,329,330,349,334,293,333,366,323,447,316,15,315,331,358,279,317,14,316,8,285,9,277,329,350,253,374,252,319,318,403,351,6,419,324,318,325,397,367,365,288,435,397,278,344,439,310,272,311,248,195,281,375,273,291,175,396,199,312,311,268,276,283,445,390,373,339,295,282,296,448,449,346,356,264,454,337,336,299,337,338,151,294,278,455,308,292,415,429,358,355,265,340,372,388,390,466,352,346,280,295,442,282,354,19,370,285,441,295,195,248,197,457,440,274,301,300,368,417,351,465,251,301,389,385,380,386,394,395,379,399,412,419,410,436,322,387,373,388,326,2,393,354,370,461,393,164,267,268,302,12,386,374,387,312,268,13,298,293,301,265,446,340,380,385,381,280,330,425,322,426,391,420,429,437,393,391,326,344,440,438,458,459,461,364,434,394,428,396,262,274,354,457,317,316,402,316,315,403,315,314,404,314,313,405,313,421,406,323,366,361,292,306,407,306,291,408,291,287,409,287,432,410,427,434,411,372,264,383,459,309,457,366,352,401,1,274,4,418,421,262,331,294,358,435,433,367,392,289,439,328,462,326,94,2,370,289,305,455,339,254,448,359,255,446,254,253,449,253,252,450,252,256,451,256,341,452,414,413,463,286,441,414,286,258,441,258,257,442,257,259,443,259,260,444,260,467,445,309,459,250,305,289,290,305,290,460,401,376,435,309,250,392,376,411,433,453,341,464,357,453,465,343,357,412,437,343,399,344,360,440,420,437,456,360,420,363,361,401,288,265,372,353,390,339,249,339,448,255];var In=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],jn=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],Nn=[33,133,362,263,1,78,308],$A=In.map(e=>Je[e]),e7=jn.map(e=>Je[e]),t7=Nn.map(e=>Je[e]);function Y0(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var On=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Ln=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Wn=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],Fn=[[474,475],[475,476],[476,477],[477,474]],Gn=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],Bn=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],Hn=[[469,470],[470,471],[471,472],[472,469]],Vn=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]],o7={lips:Y0(On),leftEye:Y0(Ln),leftEyebrow:Y0(Wn),leftIris:Y0(Fn),rightEye:Y0(Gn),rightEyebrow:Y0(Bn),rightIris:Y0(Hn),faceOval:Y0(Vn)};var Re=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],f2=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],m2=(e,t)=>e?[Math.trunc(Math.max(0,e.startPoint[0])),Math.trunc(Math.max(0,e.startPoint[1])),Math.trunc(Math.min(t.shape[2]||0,e.endPoint[0])-Math.max(0,e.startPoint[0])),Math.trunc(Math.min(t.shape[1]||0,e.endPoint[1])-Math.max(0,e.startPoint[1]))]:[0,0,0,0],p2=(e,t)=>e?[e.startPoint[0]/(t.shape[2]||0),e.startPoint[1]/(t.shape[1]||0),(e.endPoint[0]-e.startPoint[0])/(t.shape[2]||0),(e.endPoint[1]-e.startPoint[1])/(t.shape[1]||0)]:[0,0,0,0],xt=(e,t)=>{let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]];return{startPoint:o,endPoint:n,landmarks:e.landmarks,confidence:e.confidence}},u5=(e,t,o)=>{let n=t.shape[1],r=t.shape[2],s=[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r],a=A.image.cropAndResize(t,[s],[0],o),i=A.div(a,G.tf255);return A.dispose(a),i},u2=(e,t)=>{let o=f2(e),n=Re(e),r=[t*n[0]/2,t*n[1]/2];return{startPoint:[o[0]-r[0],o[1]-r[1]],endPoint:[o[0]+r[0],o[1]+r[1]],landmarks:e.landmarks,confidence:e.confidence}},h2=e=>{let t=f2(e),o=Re(e),n=Math.max(...o)/2;return{startPoint:[Math.round(t[0]-n),Math.round(t[1]-n)],endPoint:[Math.round(t[0]+n),Math.round(t[1]+n)],landmarks:e.landmarks,confidence:e.confidence}},ct=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return{startPoint:[Math.min(...t),Math.min(...o)],endPoint:[Math.max(...t),Math.max(...o)],landmarks:e}},h5=[[1,0,0],[0,1,0],[0,0,1]],Dn=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),Zn=(e,t)=>Dn(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var lt=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],le=(e,t)=>{let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o},Xn=(e,t)=>{let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o},yt=(e,t)=>{let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let s=0;s<n;s++)o[r].push(le(e[r],Xn(t,s)))}return o},dt=(e,t)=>{let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],s=lt(t[0],t[1]),a=yt(s,r),i=lt(-t[0],-t[1]);return yt(a,i)},qn=e=>{let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-le(t[0],o),-le(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]},Un=(e,t)=>[le(e,t[0]),le(e,t[1])];function ft(e){let t=e===192?{strides:[4],anchors:[1]}:{strides:[e/16,e/8],anchors:[2,6]},o=[];for(let n=0;n<t.strides.length;n++){let r=t.strides[n],s=Math.floor((e+r-1)/r),a=Math.floor((e+r-1)/r),i=t.anchors[n];for(let l=0;l<s;l++){let c=r*(l+.5);for(let d=0;d<a;d++){let y=r*(d+.5);for(let x=0;x<i;x++)o.push([y,c])}}}return o}function mt(e,t,o,n,r){let s=Re(t),a=e.map(m=>[s[0]/r*(m[0]-r/2),s[1]/r*(m[1]-r/2),m[2]||0]),i=o&&o!==0&&Math.abs(o)>.2,l=i?dt(o,[0,0]):h5,c=i?a.map(m=>[...Un(m,l),m[2]]):a,d=i?qn(n):h5,y=f2(t),x=[le(y,d[0]),le(y,d[1])];return c.map(m=>[Math.trunc(m[0]+x[0]),Math.trunc(m[1]+x[1]),Math.trunc(m[2]||0)])}function pt(e,t,o,n){let r=t.landmarks.length>=f5.count?f5.symmetryLine:ae.symmetryLine,s=0,a=h5,i;if(e&&T.kernels.includes("rotatewithoffset"))if(s=Zn(t.landmarks[r[0]],t.landmarks[r[1]]),s&&s!==0&&Math.abs(s)>.2){let c=f2(t),d=[c[0]/o.shape[2],c[1]/o.shape[1]],y=A.image.rotateWithOffset(o,s,0,d);a=dt(-s,c),i=u5(t,y,[n,n]),A.dispose(y)}else i=u5(t,o,[n,n]);else i=u5(t,o,[n,n]);return[s,a,i]}var Yn=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return[Math.min(...t)+(Math.max(...t)-Math.min(...t))/2,Math.min(...o)+(Math.max(...o)-Math.min(...o))/2]},ut=(e,t)=>{let o=Yn(e),n=Re(t);return{startPoint:[o[0]-n[0]/2,o[1]-n[1]/2],endPoint:[o[0]+n[0]/2,o[1]+n[1]/2]}};var ht=6,Kn=1.4,I0,bt=null,K0=0,Qe=null,ve=()=>K0;async function gt(e){var t;return T.initial&&(I0=null),I0?e.debug&&u("cached model:",I0.modelUrl):I0=await L((t=e.face.detector)==null?void 0:t.modelPath),K0=I0.inputs[0].shape?I0.inputs[0].shape[2]:0,Qe=A.scalar(K0,"int32"),bt=A.tensor2d(ft(K0)),I0}function Jn(e){let t={};t.boxStarts=A.slice(e,[0,1],[-1,2]),t.centers=A.add(t.boxStarts,bt),t.boxSizes=A.slice(e,[0,3],[-1,2]),t.boxSizesNormalized=A.div(t.boxSizes,Qe),t.centersNormalized=A.div(t.centers,Qe),t.halfBoxSize=A.div(t.boxSizesNormalized,G.tf2),t.starts=A.sub(t.centersNormalized,t.halfBoxSize),t.ends=A.add(t.centersNormalized,t.halfBoxSize),t.startNormalized=A.mul(t.starts,Qe),t.endNormalized=A.mul(t.ends,Qe);let o=A.concat2d([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(n=>A.dispose(t[n])),o}async function Mt(e,t){var i,l,c,d;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let o={};o.resized=A.image.resizeBilinear(e,[K0,K0]),o.div=A.div(o.resized,G.tf127),o.normalized=A.sub(o.div,G.tf05);let n=I0==null?void 0:I0.execute(o.normalized);if(Array.isArray(n)&&n.length>2){let y=n.sort((x,m)=>x.size-m.size);o.concat384=A.concat([y[0],y[2]],2),o.concat512=A.concat([y[1],y[3]],2),o.concat=A.concat([o.concat512,o.concat384],1),o.batch=A.squeeze(o.concat,0)}else Array.isArray(n)?o.batch=A.squeeze(n[0]):o.batch=A.squeeze(n);A.dispose(n),o.boxes=Jn(o.batch),o.logits=A.slice(o.batch,[0,0],[-1,1]),o.sigmoid=A.sigmoid(o.logits),o.scores=A.squeeze(o.sigmoid),o.nms=await A.image.nonMaxSuppressionAsync(o.boxes,o.scores,((i=t.face.detector)==null?void 0:i.maxDetected)||0,((l=t.face.detector)==null?void 0:l.iouThreshold)||0,((c=t.face.detector)==null?void 0:c.minConfidence)||0);let r=await o.nms.array(),s=[],a=await o.scores.data();for(let y=0;y<r.length;y++){let x=a[r[y]];if(x>(((d=t.face.detector)==null?void 0:d.minConfidence)||0)){let m={};m.bbox=A.slice(o.boxes,[r[y],0],[1,-1]),m.slice=A.slice(o.batch,[r[y],ht-1],[1,-1]),m.squeeze=A.squeeze(m.slice),m.landmarks=A.reshape(m.squeeze,[ht,-1]);let h=await m.bbox.data(),p={startPoint:[h[0],h[1]],endPoint:[h[2],h[3]],landmarks:await m.landmarks.array(),confidence:x},R=xt(p,[(e.shape[2]||0)/K0,(e.shape[1]||0)/K0]),M=u2(R,t.face.scale||Kn),g=h2(M);s.push(g),Object.keys(m).forEach(f=>A.dispose(m[f]))}}return Object.keys(o).forEach(y=>A.dispose(o[y])),s}var b2={};U0(b2,{connected:()=>M5,kpt:()=>g5});var g5=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPinky","rightPinky","leftIndex","rightIndex","leftThumb","rightThumb","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","bodyCenter","bodyTop","leftPalm","leftHand","rightPalm","rightHand"],M5={shoulders:["leftShoulder","rightShoulder"],hips:["rightHip","leftHip"],mouth:["leftMouth","rightMouth"],leftLegUpper:["leftHip","leftKnee"],leftLegLower:["leftKnee","leftAnkle"],leftFoot:["leftAnkle","leftHeel","leftFoot"],leftTorso:["leftShoulder","leftHip"],leftArmUpper:["leftShoulder","leftElbow"],leftArmLower:["leftElbow","leftWrist"],leftHand:["leftWrist","leftPalm"],leftHandPinky:["leftPalm","leftPinky"],leftHandIndex:["leftPalm","leftIndex"],leftHandThumb:["leftPalm","leftThumb"],leftEyeOutline:["leftEyeInside","leftEyeOutside"],rightLegUpper:["rightHip","rightKnee"],rightLegLower:["rightKnee","rightAnkle"],rightFoot:["rightAnkle","rightHeel","rightFoot"],rightTorso:["rightShoulder","rightHip"],rightArmUpper:["rightShoulder","rightElbow"],rightArmLower:["rightElbow","rightWrist"],rightHand:["rightWrist","rightPalm"],rightHandPinky:["rightPalm","rightPinky"],rightHandIndex:["rightPalm","rightIndex"],rightHandThumb:["rightPalm","rightThumb"],rightEyeOutline:["rightEyeInside","rightEyeOutside"]};var Rt=224,Qn,_n=5,g2=[8,16,32,32,32];async function vt(){let e=[],t=0;for(;t<_n;){let o=0,n=t;for(;n<g2.length&&g2[n]===g2[t];)o+=2,n++;let r=g2[t],s=Math.ceil(Rt/r),a=Math.ceil(Rt/r);for(let i=0;i<s;++i)for(let l=0;l<a;++l)for(let c=0;c<o;++c)e.push({x:(l+.5)/a,y:(i+.5)/s});t=n}Qn={x:A.tensor1d(e.map(o=>o.x)),y:A.tensor1d(e.map(o=>o.y))}}function G0(e,t=[1,1]){let o=[e.map(i=>i[0]),e.map(i=>i[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],s=[n[0],n[1],r[0]-n[0],r[1]-n[1]],a=[s[0]/t[0],s[1]/t[1],s[2]/t[0],s[3]/t[1]];return{box:s,boxRaw:a}}function Tt(e,t=[1,1]){let o=[e.map(c=>c[0]),e.map(c=>c[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],s=[(n[0]+r[0])/2,(n[1]+r[1])/2],a=Math.max(s[0]-n[0],s[1]-n[1],-s[0]+r[0],-s[1]+r[1]),i=[Math.trunc(s[0]-a),Math.trunc(s[1]-a),Math.trunc(2*a),Math.trunc(2*a)],l=[i[0]/t[0],i[1]/t[1],i[2]/t[0],i[3]/t[1]];return{box:i,boxRaw:l}}function M2(e,t){let o=[e[2]*t,e[3]*t];return[e[0]-(o[0]-e[2])/2,e[1]-(o[1]-e[3])/2,o[0],o[1]]}var Et={initial:!0},m0={detector:null,landmarks:null},Te={detector:[224,224],landmarks:[256,256]},P5=Number.MAX_SAFE_INTEGER,er={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},R2=null,_e,J0=[[0,0],[0,0],[0,0],[0,0]],wt=0,kt=e=>1-1/(1+Math.exp(e));async function zt(e){if(Et.initial&&(m0.detector=null),!m0.detector&&e.body.detector&&e.body.detector.modelPath){m0.detector=await L(e.body.detector.modelPath);let t=Object.values(m0.detector.modelSignature.inputs);Te.detector[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,Te.detector[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&m0.detector&&u("cached model:",m0.detector.modelUrl);return await vt(),m0.detector}async function St(e){if(Et.initial&&(m0.landmarks=null),m0.landmarks)e.debug&&u("cached model:",m0.landmarks.modelUrl);else{m0.landmarks=await L(e.body.modelPath);let t=Object.values(m0.landmarks.modelSignature.inputs);Te.landmarks[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,Te.landmarks[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return m0.landmarks}async function tr(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;let n;if(_e&&(o.cropped=A.image.cropAndResize(e,[_e],[0],[e.shape[1],e.shape[2]])),e.shape[1]!==e.shape[2]){let r=[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],s=[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0];J0=[[0,0],r,s,[0,0]],o.pad=A.pad(o.cropped||e,J0),o.resize=A.image.resizeBilinear(o.pad,[t,t]),n=A.div(o.resize,G.tf255)}else e.shape[1]!==t?(o.resize=A.image.resizeBilinear(o.cropped||e,[t,t]),n=A.div(o.resize,G.tf255)):n=A.div(o.cropped||e,G.tf255);return Object.keys(o).forEach(r=>A.dispose(o[r])),n}function or(e,t){for(let o of e)o.position=[Math.trunc(o.position[0]*(t[0]+J0[2][0]+J0[2][1])/t[0]-J0[2][0]),Math.trunc(o.position[1]*(t[1]+J0[1][0]+J0[1][1])/t[1]-J0[1][0]),o.position[2]],o.positionRaw=[o.position[0]/t[0],o.position[1]/t[1],2*o.position[2]/(t[0]+t[1])];if(_e)for(let o of e)o.positionRaw=[o.positionRaw[0]+_e[1],o.positionRaw[1]+_e[0],o.positionRaw[2]],o.position=[Math.trunc(o.positionRaw[0]*t[0]),Math.trunc(o.positionRaw[1]*t[1]),o.positionRaw[2]];return e}async function nr(e){let t=e.find(i=>i.part==="leftPalm"),o=e.find(i=>i.part==="leftWrist"),n=e.find(i=>i.part==="leftIndex");t.position[2]=((o.position[2]||0)+(n.position[2]||0))/2;let r=e.find(i=>i.part==="rightPalm"),s=e.find(i=>i.part==="rightWrist"),a=e.find(i=>i.part==="rightIndex");r.position[2]=((s.position[2]||0)+(a.position[2]||0))/2}async function rr(e,t,o){var h;let n={};[n.ld,n.segmentation,n.heatmap,n.world,n.poseflag]=(h=m0.landmarks)==null?void 0:h.execute(e,er.landmarks);let r=(await n.poseflag.data())[0],s=await n.ld.data(),a=await n.world.data();Object.keys(n).forEach(p=>A.dispose(n[p]));let i=[],l=5;for(let p=0;p<s.length/l;p++){let R=kt(s[l*p+3]),M=kt(s[l*p+4]),g=Math.trunc(100*R*M*r)/100,f=[s[l*p+0]/Te.landmarks[0],s[l*p+1]/Te.landmarks[1],s[l*p+2]+0],P=[Math.trunc(o[0]*f[0]),Math.trunc(o[1]*f[1]),f[2]],C=[a[l*p+0],a[l*p+1],a[l*p+2]+0];i.push({part:g5[p],positionRaw:f,position:P,distance:C,score:g})}if(r<(t.body.minConfidence||0))return null;nr(i);let c=or(i,o),d=c.map(p=>p.position),y=G0(d,[o[0],o[1]]),x={};for(let[p,R]of Object.entries(M5)){let M=[];for(let g=0;g<R.length-1;g++){let f=c.find(C=>C.part===R[g]),P=c.find(C=>C.part===R[g+1]);f&&P&&M.push([f.position,P.position])}x[p]=M}return{id:0,score:Math.trunc(100*r)/100,box:y.box,boxRaw:y.boxRaw,keypoints:c,annotations:x}}async function R5(e,t){let o=[e.shape[2]||0,e.shape[1]||0],n=(t.body.skipTime||0)>b()-wt,r=P5<(t.body.skipFrames||0);if(t.skipAllowed&&n&&r&&R2!==null)P5++;else{let s={};s.landmarks=await tr(e,256),R2=await rr(s.landmarks,t,o),Object.keys(s).forEach(a=>A.dispose(s[a])),wt=b(),P5=0}return R2?[R2]:[]}var we=[{class:1,label:"person"},{class:2,label:"bicycle"},{class:3,label:"car"},{class:4,label:"motorcycle"},{class:5,label:"airplane"},{class:6,label:"bus"},{class:7,label:"train"},{class:8,label:"truck"},{class:9,label:"boat"},{class:10,label:"traffic light"},{class:11,label:"fire hydrant"},{class:12,label:"stop sign"},{class:13,label:"parking meter"},{class:14,label:"bench"},{class:15,label:"bird"},{class:16,label:"cat"},{class:17,label:"dog"},{class:18,label:"horse"},{class:19,label:"sheep"},{class:20,label:"cow"},{class:21,label:"elephant"},{class:22,label:"bear"},{class:23,label:"zebra"},{class:24,label:"giraffe"},{class:25,label:"backpack"},{class:26,label:"umbrella"},{class:27,label:"handbag"},{class:28,label:"tie"},{class:29,label:"suitcase"},{class:30,label:"frisbee"},{class:31,label:"skis"},{class:32,label:"snowboard"},{class:33,label:"sports ball"},{class:34,label:"kite"},{class:35,label:"baseball bat"},{class:36,label:"baseball glove"},{class:37,label:"skateboard"},{class:38,label:"surfboard"},{class:39,label:"tennis racket"},{class:40,label:"bottle"},{class:41,label:"wine glass"},{class:42,label:"cup"},{class:43,label:"fork"},{class:44,label:"knife"},{class:45,label:"spoon"},{class:46,label:"bowl"},{class:47,label:"banana"},{class:48,label:"apple"},{class:49,label:"sandwich"},{class:50,label:"orange"},{class:51,label:"broccoli"},{class:52,label:"carrot"},{class:53,label:"hot dog"},{class:54,label:"pizza"},{class:55,label:"donut"},{class:56,label:"cake"},{class:57,label:"chair"},{class:58,label:"couch"},{class:59,label:"potted plant"},{class:60,label:"bed"},{class:61,label:"dining table"},{class:62,label:"toilet"},{class:63,label:"tv"},{class:64,label:"laptop"},{class:65,label:"mouse"},{class:66,label:"remote"},{class:67,label:"keyboard"},{class:68,label:"cell phone"},{class:69,label:"microwave"},{class:70,label:"oven"},{class:71,label:"toaster"},{class:72,label:"sink"},{class:73,label:"refrigerator"},{class:74,label:"book"},{class:75,label:"clock"},{class:76,label:"vase"},{class:77,label:"scissors"},{class:78,label:"teddy bear"},{class:79,label:"hair drier"},{class:80,label:"toothbrush"}];var B0,ye=0,v5=[],It=0,T5=Number.MAX_SAFE_INTEGER;async function jt(e){if(T.initial&&(B0=null),B0)e.debug&&u("cached model:",B0.modelUrl);else{B0=await L(e.object.modelPath);let t=Object.values(B0.modelSignature.inputs);ye=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return B0}async function Ar(e,t,o){if(!e)return[];let n={},r=[],s=await e.array();n.squeeze=A.squeeze(e);let a=A.split(n.squeeze,6,1);n.stack=A.stack([a[1],a[0],a[3],a[2]],1),n.boxes=A.squeeze(n.stack),n.scores=A.squeeze(a[4]),n.classes=A.squeeze(a[5]),A.dispose([e,...a]),n.nms=await A.image.nonMaxSuppressionAsync(n.boxes,n.scores,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence||0);let i=await n.nms.data(),l=0;for(let c of Array.from(i)){let d=Math.trunc(100*s[0][c][4])/100,y=s[0][c][5],x=we[y].label,[m,h]=[s[0][c][0]/ye,s[0][c][1]/ye],p=[m,h,s[0][c][2]/ye-m,s[0][c][3]/ye-h],R=[Math.trunc(p[0]*t[0]),Math.trunc(p[1]*t[1]),Math.trunc(p[2]*t[0]),Math.trunc(p[3]*t[1])];r.push({id:l++,score:d,class:y,label:x,box:R,boxRaw:p})}return Object.keys(n).forEach(c=>A.dispose(n[c])),r}async function w5(e,t){let o=(t.object.skipTime||0)>b()-It,n=T5<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&v5.length>0?(T5++,v5):(T5=0,new Promise(async r=>{let s=[e.shape[2]||0,e.shape[1]||0],a=A.image.resizeBilinear(e,[ye,ye]),i=t.object.enabled?B0==null?void 0:B0.execute(a,["tower_0/detections"]):null;It=b(),A.dispose(a);let l=await Ar(i,s,t);v5=l,r(l)}))}var v2={};U0(v2,{connected:()=>E5,kpt:()=>k5});var k5=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],E5={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var s0,Ot=0,c0={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},z5=Number.MAX_SAFE_INTEGER;async function Lt(e){return T.initial&&(s0=null),s0?e.debug&&u("cached model:",s0.modelUrl):s0=await L(e.body.modelPath),s0}async function sr(e,t){let[o,n]=e.shape,r=A.reshape(e,[n*o]),s=A.max(r,0),a=(await s.data())[0];if(A.dispose([r,s]),a>t){let i=A.argMax(r,0),l=A.mod(i,o),c=(await l.data())[0],d=A.div(i,A.scalar(o,"int32")),y=(await d.data())[0];return A.dispose([l,d]),[c,y,a]}return[0,0,a]}async function S5(e,t){let o=(t.body.skipTime||0)>b()-Ot,n=z5<(t.body.skipFrames||0);return t.skipAllowed&&o&&n&&Object.keys(c0.keypoints).length>0?(z5++,[c0]):(z5=0,new Promise(async r=>{var y;let s=A.tidy(()=>{if(!(s0!=null&&s0.inputs[0].shape))return null;let x=A.image.resizeBilinear(e,[s0.inputs[0].shape[2],s0.inputs[0].shape[1]],!1),m=A.mul(x,G.tf2);return A.sub(m,G.tf1)}),a;if(t.body.enabled&&(a=s0==null?void 0:s0.execute(s)),Ot=b(),A.dispose(s),a){c0.keypoints.length=0;let x=a.squeeze();A.dispose(a);let m=x.unstack(2);A.dispose(x);for(let h=0;h<m.length;h++){let[p,R,M]=await sr(m[h],t.body.minConfidence);M>(((y=t.body)==null?void 0:y.minConfidence)||0)&&c0.keypoints.push({score:Math.round(100*M)/100,part:k5[h],positionRaw:[p/s0.inputs[0].shape[2],R/s0.inputs[0].shape[1]],position:[Math.round(e.shape[2]*p/s0.inputs[0].shape[2]),Math.round(e.shape[1]*R/s0.inputs[0].shape[1])]})}m.forEach(h=>A.dispose(h))}c0.score=c0.keypoints.reduce((x,m)=>m.score>x?m.score:x,0);let i=c0.keypoints.map(x=>x.position[0]),l=c0.keypoints.map(x=>x.position[1]);c0.box=[Math.min(...i),Math.min(...l),Math.max(...i)-Math.min(...i),Math.max(...l)-Math.min(...l)];let c=c0.keypoints.map(x=>x.positionRaw[0]),d=c0.keypoints.map(x=>x.positionRaw[1]);c0.boxRaw=[Math.min(...c),Math.min(...d),Math.max(...c)-Math.min(...c),Math.max(...d)-Math.min(...d)];for(let[x,m]of Object.entries(E5)){let h=[];for(let p=0;p<m.length-1;p++){let R=c0.keypoints.find(g=>g.part===m[p]),M=c0.keypoints.find(g=>g.part===m[p+1]);R&&M&&R.score>(t.body.minConfidence||0)&&M.score>(t.body.minConfidence||0)&&h.push([R.position,M.position])}c0.annotations[x]=h}r([c0])}))}var ar=["angry","disgust","fear","happy","sad","surprise","neutral"],P0,T2=[],Ft=0,Gt=0,C5=Number.MAX_SAFE_INTEGER;async function Bt(e){var t;return T.initial&&(P0=null),P0?e.debug&&u("cached model:",P0.modelUrl):P0=await L((t=e.face.emotion)==null?void 0:t.modelPath),P0}async function I5(e,t,o,n){var a,i;if(!P0)return[];let r=C5<(((a=t.face.emotion)==null?void 0:a.skipFrames)||0),s=(((i=t.face.emotion)==null?void 0:i.skipTime)||0)>b()-Gt;return t.skipAllowed&&s&&r&&Ft===n&&T2[o]&&T2[o].length>0?(C5++,T2[o]):(C5=0,new Promise(async l=>{var d,y;let c=[];if((d=t.face.emotion)!=null&&d.enabled){let x={},m=P0!=null&&P0.inputs[0].shape?P0.inputs[0].shape[2]:0;x.resize=A.image.resizeBilinear(e,[m,m],!1),x.channels=A.mul(x.resize,G.rgb),x.grayscale=A.sum(x.channels,3,!0),x.grayscaleSub=A.sub(x.grayscale,G.tf05),x.grayscaleMul=A.mul(x.grayscaleSub,G.tf2),x.emotion=P0==null?void 0:P0.execute(x.grayscaleMul),Gt=b();let h=await x.emotion.data();for(let p=0;p<h.length;p++)h[p]>(((y=t.face.emotion)==null?void 0:y.minConfidence)||0)&&c.push({score:Math.min(.99,Math.trunc(100*h[p])/100),emotion:ar[p]});c.sort((p,R)=>R.score-p.score),Object.keys(x).forEach(p=>A.dispose(x[p]))}T2[o]=c,Ft=n,l(c)}))}var p0,j5=[],Vt=0,Dt=0,Zt=Number.MAX_SAFE_INTEGER;async function Xt(e){return T.initial&&(p0=null),p0?e.debug&&u("cached model:",p0.modelUrl):p0=await L(e.face.mobilefacenet.modelPath),p0}async function N5(e,t,o,n){var a,i;if(!p0)return[];let r=Zt<(((a=t.face.embedding)==null?void 0:a.skipFrames)||0),s=(((i=t.face.embedding)==null?void 0:i.skipTime)||0)>b()-Dt;return t.skipAllowed&&s&&r&&Vt===n&&j5[o]?(Zt++,j5[o]):new Promise(async l=>{var d;let c=[];if(((d=t.face.embedding)==null?void 0:d.enabled)&&(p0==null?void 0:p0.inputs[0].shape)){let y={};y.crop=A.image.resizeBilinear(e,[p0.inputs[0].shape[2],p0.inputs[0].shape[1]],!1),y.data=p0==null?void 0:p0.execute(y.crop);let x=await y.data.data();c=Array.from(x)}j5[o]=c,Vt=n,Dt=b(),l(c)})}var H0,Q0=0,ir=2.3,O5=w0.leftEyeLower0,L5=w0.rightEyeLower0,ke={leftBounds:[O5[0],O5[O5.length-1]],rightBounds:[L5[0],L5[L5.length-1]]},Ee={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function Jt(e){var t;return T.initial&&(H0=null),H0?e.debug&&u("cached model:",H0.modelUrl):H0=await L((t=e.face.iris)==null?void 0:t.modelPath),Q0=H0.inputs[0].shape?H0.inputs[0].shape[2]:0,Q0===-1&&(Q0=64),H0}function w2(e,t,o,n){for(let r=0;r<m5.length;r++){let{key:s,indices:a}=m5[r],i=w0[`${o}${s}`];if(!n||n.includes(s))for(let l=0;l<a.length;l++){let c=a[l];e[i[l]]=[t[c][0],t[c][1],(t[c][2]+e[i[l]][2])/2]}}}var lr=e=>{let t=e[ke.leftBounds[0]][2],o=e[ke.rightBounds[0]][2];return t-o},Ut=(e,t,o,n,r,s=!1)=>{let a=h2(u2(ct([e[o],e[n]]),ir)),i=Re(a),l=A.image.cropAndResize(t,[[a.startPoint[1]/r,a.startPoint[0]/r,a.endPoint[1]/r,a.endPoint[0]/r]],[0],[Q0,Q0]);if(s&&T.kernels.includes("flipleftright")){let c=A.image.flipLeftRight(l);A.dispose(l),l=c}return{box:a,boxSize:i,crop:l}},Yt=(e,t,o,n=!1)=>{let r=[];for(let s=0;s<Ee.numCoordinates;s++){let a=e[s*3],i=e[s*3+1],l=e[s*3+2];r.push([(n?1-a/Q0:a/Q0)*o[0]+t.startPoint[0],i/Q0*o[1]+t.startPoint[1],l])}return{rawCoords:r,iris:r.slice(Ee.index)}},Kt=(e,t,o)=>{let n=e[w0[`${o}EyeUpper0`][Ee.upperCenter]][2],r=e[w0[`${o}EyeLower0`][Ee.lowerCenter]][2],s=(n+r)/2;return t.map((a,i)=>{let l=s;return i===2?l=n:i===4&&(l=r),[a[0],a[1],l]})};async function Qt(e,t,o,n){if(!H0)return o.debug&&u("face mesh iris detection requested, but model is not loaded"),e;let{box:r,boxSize:s,crop:a}=Ut(e,t,ke.leftBounds[0],ke.leftBounds[1],n,!0),{box:i,boxSize:l,crop:c}=Ut(e,t,ke.rightBounds[0],ke.rightBounds[1],n,!0),d=A.concat([a,c]);A.dispose(a),A.dispose(c);let y=H0.execute(d);A.dispose(d);let x=await y.data();A.dispose(y);let m=x.slice(0,Ee.numCoordinates*3),{rawCoords:h,iris:p}=Yt(m,r,s,!0),R=x.slice(Ee.numCoordinates*3),{rawCoords:M,iris:g}=Yt(R,i,l,!1),f=lr(e);Math.abs(f)<30?(w2(e,h,"left",null),w2(e,M,"right",null)):f<1?w2(e,h,"left",["EyeUpper0","EyeLower0"]):w2(e,M,"right",["EyeUpper0","EyeLower0"]);let P=Kt(e,p,"left"),C=Kt(e,g,"right");return e.concat(P).concat(C)}var yr=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],xr=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],cr=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],dr=[[474,475],[475,476],[476,477],[477,474]],fr=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],mr=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],pr=[[469,470],[470,471],[471,472],[472,469]],ur=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]];function _0(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var hr={lips:_0(yr),leftEye:_0(xr),leftEyebrow:_0(cr),leftIris:_0(dr),rightEye:_0(fr),rightEyebrow:_0(mr),rightIris:_0(pr),faceOval:_0(ur)},br=Object.entries(hr).map(([e,t])=>t.map(o=>[o,e])).flat(),C7=new Map(br),$e=[61,146,91,181,84,17,314,405,321,375,291,185,40,39,37,0,267,269,270,409,78,95,88,178,87,14,317,402,318,324,308,191,80,81,82,13,312,311,310,415,76,77,90,180,85,16,315,404,320,307,306,184,74,73,72,11,302,303,304,408,62,96,89,179,86,15,316,403,319,325,292,183,42,41,38,12,268,271,272,407],xe=[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173,130,25,110,24,23,22,26,112,243,247,30,29,27,28,56,190,226,31,228,229,230,231,232,233,244,113,225,224,223,222,221,189,35,124,46,53,52,65,143,111,117,118,119,120,121,128,245,156,70,63,105,66,107,55,193],ce=[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398,359,255,339,254,253,252,256,341,463,467,260,259,257,258,286,414,446,261,448,449,450,451,452,453,464,342,445,444,443,442,441,413,265,353,276,283,282,295,372,340,346,347,348,349,350,357,465,383,300,293,334,296,336,285,417];async function e3(e,t){let o={lips:await t.filter(s=>s.size===160)[0].data(),irisL:await t.filter(s=>s.size===10)[0].data(),eyeL:await t.filter(s=>s.size===142)[0].data(),irisR:await t.filter(s=>s.size===10)[1].data(),eyeR:await t.filter(s=>s.size===142)[1].data()},n=xe.reduce((s,a)=>s+=e[a][2],0)/xe.length;for(let s=0;s<o.irisL.length/2;s++)e.push([o.irisL[2*s+0],o.irisL[2*s+1],n]);let r=ce.reduce((s,a)=>s+=e[a][2],0)/ce.length;for(let s=0;s<o.irisR.length/2;s++)e.push([o.irisR[2*s+0],o.irisR[2*s+1],r]);for(let s=0;s<o.eyeL.length/2;s++)e[xe[s]]=[o.eyeL[2*s+0],o.eyeL[2*s+1],e[xe[s]][2]];for(let s=0;s<o.eyeR.length/2;s++)e[ce[s]]=[o.eyeR[2*s+0],o.eyeR[2*s+1],e[ce[s]][2]];for(let s=0;s<o.lips.length/2;s++)e[$e[s]]=[o.lips[2*s+0],o.lips[2*s+1],e[$e[s]][2]];return e}var j0={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},a0=null,de=0;async function t3(e,t){var i,l,c,d,y,x,m,h,p,R,M;let o=(((i=t.face.detector)==null?void 0:i.skipTime)||0)>b()-j0.timestamp,n=j0.skipped<(((l=t.face.detector)==null?void 0:l.skipFrames)||0);!t.skipAllowed||!o||!n||j0.boxes.length===0?(j0.boxes=await Mt(e,t),j0.timestamp=b(),j0.skipped=0):j0.skipped++;let r=[],s=[],a=0;for(let g=0;g<j0.boxes.length;g++){let f=j0.boxes[g],P=0,C,k={id:a++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,annotations:{}};if([P,C,k.tensor]=pt((c=t.face.detector)==null?void 0:c.rotation,f,e,(d=t.face.mesh)!=null&&d.enabled?de:ve()),(y=t==null?void 0:t.filter)!=null&&y.equalization){let j=await i2(k.tensor);A.dispose(k.tensor),k.tensor=j}if(k.boxScore=Math.round(100*f.confidence)/100,(x=t.face.mesh)!=null&&x.enabled)if(!a0)t.debug&&u("face mesh detection requested, but model is not loaded");else{let j=a0.execute(k.tensor),O=await j.find(F=>F.shape[F.shape.length-1]===1).data();if(k.faceScore=Math.round(100*O[0])/100,k.faceScore<(((m=t.face.detector)==null?void 0:m.minConfidence)||1)){if(f.confidence=k.faceScore,(h=t.face.mesh)!=null&&h.keepInvalid){k.box=m2(f,e),k.boxRaw=p2(f,e),k.score=k.boxScore,k.mesh=f.landmarks.map(F=>[(f.startPoint[0]+f.endPoint[0])/2+(f.endPoint[0]+f.startPoint[0])*F[0]/ve(),(f.startPoint[1]+f.endPoint[1])/2+(f.endPoint[1]+f.startPoint[1])*F[1]/ve()]),k.meshRaw=k.mesh.map(F=>[F[0]/(e.shape[2]||1),F[1]/(e.shape[1]||1),(F[2]||0)/de]);for(let F of Object.keys(ae))k.annotations[F]=[k.mesh[ae[F]]]}}else{let F=j.find(z=>z.shape[z.shape.length-1]===1404),V=A.reshape(F,[-1,3]),Z=await V.array();A.dispose(V),(p=t.face.attention)!=null&&p.enabled?Z=await e3(Z,j):(R=t.face.iris)!=null&&R.enabled&&(Z=await Qt(Z,k.tensor,t,de)),k.mesh=mt(Z,f,P,C,de),k.meshRaw=k.mesh.map(z=>[z[0]/(e.shape[2]||0),z[1]/(e.shape[1]||0),(z[2]||0)/de]);for(let z of Object.keys(w0))k.annotations[z]=w0[z].map(g0=>k.mesh[g0]);k.score=k.faceScore;let t0={...ut(k.mesh,f),confidence:f.confidence,landmarks:f.landmarks};k.box=m2(t0,e),k.boxRaw=p2(t0,e),s.push(t0)}A.dispose(j)}else{k.box=m2(f,e),k.boxRaw=p2(f,e),k.score=k.boxScore,k.mesh=f.landmarks.map(j=>[(f.startPoint[0]+f.endPoint[0])/2+(f.endPoint[0]+f.startPoint[0])*j[0]/ve(),(f.startPoint[1]+f.endPoint[1])/2+(f.endPoint[1]+f.startPoint[1])*j[1]/ve()]),k.meshRaw=k.mesh.map(j=>[j[0]/(e.shape[2]||0),j[1]/(e.shape[1]||0),(j[2]||0)/de]);for(let j of Object.keys(ae))k.annotations[j]=[k.mesh[ae[j]]]}k.score>(((M=t.face.detector)==null?void 0:M.minConfidence)||1)?r.push(k):A.dispose(k.tensor)}return j0.boxes=s,r}async function o3(e){var t,o,n,r,s,a;return T.initial&&(a0=null),((o=(t=e==null?void 0:e.face)==null?void 0:t.attention)==null?void 0:o.enabled)&&(a0==null?void 0:a0.signature)&&Object.keys(((n=a0==null?void 0:a0.signature)==null?void 0:n.outputs)||{}).length<6&&(a0=null),a0?e.debug&&u("cached model:",a0.modelUrl):(r=e.face.attention)!=null&&r.enabled?a0=await L((s=e.face.attention)==null?void 0:s.modelPath):a0=await L((a=e.face.mesh)==null?void 0:a.modelPath),de=a0.inputs[0].shape?a0.inputs[0].shape[2]:0,a0}var n3=ie,r3=Je;var u0,k2=[],A3=0,s3=0,F5=Number.MAX_SAFE_INTEGER;async function a3(e){var t;return T.initial&&(u0=null),u0?e.debug&&u("cached model:",u0.modelUrl):u0=await L((t=e.face.description)==null?void 0:t.modelPath),u0}function G5(e){let t=e.image||e.tensor||e;if(!(u0!=null&&u0.inputs[0].shape))return t;let o=A.image.resizeBilinear(t,[u0.inputs[0].shape[2],u0.inputs[0].shape[1]],!1),n=A.mul(o,G.tf255);return A.dispose(o),n}async function B5(e,t,o,n){var a,i,l,c;if(!u0)return{age:0,gender:"unknown",genderScore:0,descriptor:[]};let r=F5<(((a=t.face.description)==null?void 0:a.skipFrames)||0),s=(((i=t.face.description)==null?void 0:i.skipTime)||0)>b()-A3;return t.skipAllowed&&r&&s&&s3===n&&((l=k2[o])==null?void 0:l.age)&&((c=k2[o])==null?void 0:c.age)>0?(F5++,k2[o]):(F5=0,new Promise(async d=>{var x,m;let y={age:0,gender:"unknown",genderScore:0,descriptor:[]};if((x=t.face.description)!=null&&x.enabled){let h=G5(e),p=u0==null?void 0:u0.execute(h);A3=b(),A.dispose(h);let M=await(await p.find(O=>O.shape[1]===1)).data(),g=Math.trunc(200*Math.abs(M[0]-.5))/100;g>(((m=t.face.description)==null?void 0:m.minConfidence)||0)&&(y.gender=M[0]<=.5?"female":"male",y.genderScore=Math.min(.99,g));let f=A.argMax(p.find(O=>O.shape[1]===100),1),P=(await f.data())[0];A.dispose(f);let k=await p.find(O=>O.shape[1]===100).data();y.age=Math.round(k[P-1]>k[P+1]?10*P-100*k[P-1]:10*P+100*k[P+1])/10;let j=p.find(O=>O.shape[1]===1024),I=j?await j.data():[];y.descriptor=Array.from(I),p.forEach(O=>A.dispose(O))}k2[o]=y,s3=n,d(y)}))}function E2(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function e2(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function y3(e,t,o){let n=t.shape[1],r=t.shape[2],s=[[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r]];return A.image.cropAndResize(t,s,[0],o)}function x3(e,t){let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],r=e.palmLandmarks.map(s=>[s[0]*t[0],s[1]*t[1]]);return{startPoint:o,endPoint:n,palmLandmarks:r,confidence:e.confidence}}function z2(e,t=1.5){let o=e2(e),n=E2(e),r=[t*n[0]/2,t*n[1]/2],s=[o[0]-r[0],o[1]-r[1]],a=[o[0]+r[0],o[1]+r[1]];return{startPoint:s,endPoint:a,palmLandmarks:e.palmLandmarks}}function S2(e){let t=e2(e),o=E2(e),r=Math.max(...o)/2,s=[t[0]-r,t[1]-r],a=[t[0]+r,t[1]+r];return{startPoint:s,endPoint:a,palmLandmarks:e.palmLandmarks}}function Mr(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function c3(e,t){let o=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return Mr(o)}var i3=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function $0(e,t){let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o}function Pr(e,t){let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o}function l3(e,t){let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let s=0;s<n;s++)o[r].push($0(e[r],Pr(t,s)))}return o}function V5(e,t){let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],s=i3(t[0],t[1]),a=l3(s,r),i=i3(-t[0],-t[1]);return l3(a,i)}function d3(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-$0(t[0],o),-$0(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]}function D5(e,t){return[$0(e,t[0]),$0(e,t[1])]}var m3=[{x:.015625,y:.015625},{x:.015625,y:.015625},{x:.046875,y:.015625},{x:.046875,y:.015625},{x:.078125,y:.015625},{x:.078125,y:.015625},{x:.109375,y:.015625},{x:.109375,y:.015625},{x:.140625,y:.015625},{x:.140625,y:.015625},{x:.171875,y:.015625},{x:.171875,y:.015625},{x:.203125,y:.015625},{x:.203125,y:.015625},{x:.234375,y:.015625},{x:.234375,y:.015625},{x:.265625,y:.015625},{x:.265625,y:.015625},{x:.296875,y:.015625},{x:.296875,y:.015625},{x:.328125,y:.015625},{x:.328125,y:.015625},{x:.359375,y:.015625},{x:.359375,y:.015625},{x:.390625,y:.015625},{x:.390625,y:.015625},{x:.421875,y:.015625},{x:.421875,y:.015625},{x:.453125,y:.015625},{x:.453125,y:.015625},{x:.484375,y:.015625},{x:.484375,y:.015625},{x:.515625,y:.015625},{x:.515625,y:.015625},{x:.546875,y:.015625},{x:.546875,y:.015625},{x:.578125,y:.015625},{x:.578125,y:.015625},{x:.609375,y:.015625},{x:.609375,y:.015625},{x:.640625,y:.015625},{x:.640625,y:.015625},{x:.671875,y:.015625},{x:.671875,y:.015625},{x:.703125,y:.015625},{x:.703125,y:.015625},{x:.734375,y:.015625},{x:.734375,y:.015625},{x:.765625,y:.015625},{x:.765625,y:.015625},{x:.796875,y:.015625},{x:.796875,y:.015625},{x:.828125,y:.015625},{x:.828125,y:.015625},{x:.859375,y:.015625},{x:.859375,y:.015625},{x:.890625,y:.015625},{x:.890625,y:.015625},{x:.921875,y:.015625},{x:.921875,y:.015625},{x:.953125,y:.015625},{x:.953125,y:.015625},{x:.984375,y:.015625},{x:.984375,y:.015625},{x:.015625,y:.046875},{x:.015625,y:.046875},{x:.046875,y:.046875},{x:.046875,y:.046875},{x:.078125,y:.046875},{x:.078125,y:.046875},{x:.109375,y:.046875},{x:.109375,y:.046875},{x:.140625,y:.046875},{x:.140625,y:.046875},{x:.171875,y:.046875},{x:.171875,y:.046875},{x:.203125,y:.046875},{x:.203125,y:.046875},{x:.234375,y:.046875},{x:.234375,y:.046875},{x:.265625,y:.046875},{x:.265625,y:.046875},{x:.296875,y:.046875},{x:.296875,y:.046875},{x:.328125,y:.046875},{x:.328125,y:.046875},{x:.359375,y:.046875},{x:.359375,y:.046875},{x:.390625,y:.046875},{x:.390625,y:.046875},{x:.421875,y:.046875},{x:.421875,y:.046875},{x:.453125,y:.046875},{x:.453125,y:.046875},{x:.484375,y:.046875},{x:.484375,y:.046875},{x:.515625,y:.046875},{x:.515625,y:.046875},{x:.546875,y:.046875},{x:.546875,y:.046875},{x:.578125,y:.046875},{x:.578125,y:.046875},{x:.609375,y:.046875},{x:.609375,y:.046875},{x:.640625,y:.046875},{x:.640625,y:.046875},{x:.671875,y:.046875},{x:.671875,y:.046875},{x:.703125,y:.046875},{x:.703125,y:.046875},{x:.734375,y:.046875},{x:.734375,y:.046875},{x:.765625,y:.046875},{x:.765625,y:.046875},{x:.796875,y:.046875},{x:.796875,y:.046875},{x:.828125,y:.046875},{x:.828125,y:.046875},{x:.859375,y:.046875},{x:.859375,y:.046875},{x:.890625,y:.046875},{x:.890625,y:.046875},{x:.921875,y:.046875},{x:.921875,y:.046875},{x:.953125,y:.046875},{x:.953125,y:.046875},{x:.984375,y:.046875},{x:.984375,y:.046875},{x:.015625,y:.078125},{x:.015625,y:.078125},{x:.046875,y:.078125},{x:.046875,y:.078125},{x:.078125,y:.078125},{x:.078125,y:.078125},{x:.109375,y:.078125},{x:.109375,y:.078125},{x:.140625,y:.078125},{x:.140625,y:.078125},{x:.171875,y:.078125},{x:.171875,y:.078125},{x:.203125,y:.078125},{x:.203125,y:.078125},{x:.234375,y:.078125},{x:.234375,y:.078125},{x:.265625,y:.078125},{x:.265625,y:.078125},{x:.296875,y:.078125},{x:.296875,y:.078125},{x:.328125,y:.078125},{x:.328125,y:.078125},{x:.359375,y:.078125},{x:.359375,y:.078125},{x:.390625,y:.078125},{x:.390625,y:.078125},{x:.421875,y:.078125},{x:.421875,y:.078125},{x:.453125,y:.078125},{x:.453125,y:.078125},{x:.484375,y:.078125},{x:.484375,y:.078125},{x:.515625,y:.078125},{x:.515625,y:.078125},{x:.546875,y:.078125},{x:.546875,y:.078125},{x:.578125,y:.078125},{x:.578125,y:.078125},{x:.609375,y:.078125},{x:.609375,y:.078125},{x:.640625,y:.078125},{x:.640625,y:.078125},{x:.671875,y:.078125},{x:.671875,y:.078125},{x:.703125,y:.078125},{x:.703125,y:.078125},{x:.734375,y:.078125},{x:.734375,y:.078125},{x:.765625,y:.078125},{x:.765625,y:.078125},{x:.796875,y:.078125},{x:.796875,y:.078125},{x:.828125,y:.078125},{x:.828125,y:.078125},{x:.859375,y:.078125},{x:.859375,y:.078125},{x:.890625,y:.078125},{x:.890625,y:.078125},{x:.921875,y:.078125},{x:.921875,y:.078125},{x:.953125,y:.078125},{x:.953125,y:.078125},{x:.984375,y:.078125},{x:.984375,y:.078125},{x:.015625,y:.109375},{x:.015625,y:.109375},{x:.046875,y:.109375},{x:.046875,y:.109375},{x:.078125,y:.109375},{x:.078125,y:.109375},{x:.109375,y:.109375},{x:.109375,y:.109375},{x:.140625,y:.109375},{x:.140625,y:.109375},{x:.171875,y:.109375},{x:.171875,y:.109375},{x:.203125,y:.109375},{x:.203125,y:.109375},{x:.234375,y:.109375},{x:.234375,y:.109375},{x:.265625,y:.109375},{x:.265625,y:.109375},{x:.296875,y:.109375},{x:.296875,y:.109375},{x:.328125,y:.109375},{x:.328125,y:.109375},{x:.359375,y:.109375},{x:.359375,y:.109375},{x:.390625,y:.109375},{x:.390625,y:.109375},{x:.421875,y:.109375},{x:.421875,y:.109375},{x:.453125,y:.109375},{x:.453125,y:.109375},{x:.484375,y:.109375},{x:.484375,y:.109375},{x:.515625,y:.109375},{x:.515625,y:.109375},{x:.546875,y:.109375},{x:.546875,y:.109375},{x:.578125,y:.109375},{x:.578125,y:.109375},{x:.609375,y:.109375},{x:.609375,y:.109375},{x:.640625,y:.109375},{x:.640625,y:.109375},{x:.671875,y:.109375},{x:.671875,y:.109375},{x:.703125,y:.109375},{x:.703125,y:.109375},{x:.734375,y:.109375},{x:.734375,y:.109375},{x:.765625,y:.109375},{x:.765625,y:.109375},{x:.796875,y:.109375},{x:.796875,y:.109375},{x:.828125,y:.109375},{x:.828125,y:.109375},{x:.859375,y:.109375},{x:.859375,y:.109375},{x:.890625,y:.109375},{x:.890625,y:.109375},{x:.921875,y:.109375},{x:.921875,y:.109375},{x:.953125,y:.109375},{x:.953125,y:.109375},{x:.984375,y:.109375},{x:.984375,y:.109375},{x:.015625,y:.140625},{x:.015625,y:.140625},{x:.046875,y:.140625},{x:.046875,y:.140625},{x:.078125,y:.140625},{x:.078125,y:.140625},{x:.109375,y:.140625},{x:.109375,y:.140625},{x:.140625,y:.140625},{x:.140625,y:.140625},{x:.171875,y:.140625},{x:.171875,y:.140625},{x:.203125,y:.140625},{x:.203125,y:.140625},{x:.234375,y:.140625},{x:.234375,y:.140625},{x:.265625,y:.140625},{x:.265625,y:.140625},{x:.296875,y:.140625},{x:.296875,y:.140625},{x:.328125,y:.140625},{x:.328125,y:.140625},{x:.359375,y:.140625},{x:.359375,y:.140625},{x:.390625,y:.140625},{x:.390625,y:.140625},{x:.421875,y:.140625},{x:.421875,y:.140625},{x:.453125,y:.140625},{x:.453125,y:.140625},{x:.484375,y:.140625},{x:.484375,y:.140625},{x:.515625,y:.140625},{x:.515625,y:.140625},{x:.546875,y:.140625},{x:.546875,y:.140625},{x:.578125,y:.140625},{x:.578125,y:.140625},{x:.609375,y:.140625},{x:.609375,y:.140625},{x:.640625,y:.140625},{x:.640625,y:.140625},{x:.671875,y:.140625},{x:.671875,y:.140625},{x:.703125,y:.140625},{x:.703125,y:.140625},{x:.734375,y:.140625},{x:.734375,y:.140625},{x:.765625,y:.140625},{x:.765625,y:.140625},{x:.796875,y:.140625},{x:.796875,y:.140625},{x:.828125,y:.140625},{x:.828125,y:.140625},{x:.859375,y:.140625},{x:.859375,y:.140625},{x:.890625,y:.140625},{x:.890625,y:.140625},{x:.921875,y:.140625},{x:.921875,y:.140625},{x:.953125,y:.140625},{x:.953125,y:.140625},{x:.984375,y:.140625},{x:.984375,y:.140625},{x:.015625,y:.171875},{x:.015625,y:.171875},{x:.046875,y:.171875},{x:.046875,y:.171875},{x:.078125,y:.171875},{x:.078125,y:.171875},{x:.109375,y:.171875},{x:.109375,y:.171875},{x:.140625,y:.171875},{x:.140625,y:.171875},{x:.171875,y:.171875},{x:.171875,y:.171875},{x:.203125,y:.171875},{x:.203125,y:.171875},{x:.234375,y:.171875},{x:.234375,y:.171875},{x:.265625,y:.171875},{x:.265625,y:.171875},{x:.296875,y:.171875},{x:.296875,y:.171875},{x:.328125,y:.171875},{x:.328125,y:.171875},{x:.359375,y:.171875},{x:.359375,y:.171875},{x:.390625,y:.171875},{x:.390625,y:.171875},{x:.421875,y:.171875},{x:.421875,y:.171875},{x:.453125,y:.171875},{x:.453125,y:.171875},{x:.484375,y:.171875},{x:.484375,y:.171875},{x:.515625,y:.171875},{x:.515625,y:.171875},{x:.546875,y:.171875},{x:.546875,y:.171875},{x:.578125,y:.171875},{x:.578125,y:.171875},{x:.609375,y:.171875},{x:.609375,y:.171875},{x:.640625,y:.171875},{x:.640625,y:.171875},{x:.671875,y:.171875},{x:.671875,y:.171875},{x:.703125,y:.171875},{x:.703125,y:.171875},{x:.734375,y:.171875},{x:.734375,y:.171875},{x:.765625,y:.171875},{x:.765625,y:.171875},{x:.796875,y:.171875},{x:.796875,y:.171875},{x:.828125,y:.171875},{x:.828125,y:.171875},{x:.859375,y:.171875},{x:.859375,y:.171875},{x:.890625,y:.171875},{x:.890625,y:.171875},{x:.921875,y:.171875},{x:.921875,y:.171875},{x:.953125,y:.171875},{x:.953125,y:.171875},{x:.984375,y:.171875},{x:.984375,y:.171875},{x:.015625,y:.203125},{x:.015625,y:.203125},{x:.046875,y:.203125},{x:.046875,y:.203125},{x:.078125,y:.203125},{x:.078125,y:.203125},{x:.109375,y:.203125},{x:.109375,y:.203125},{x:.140625,y:.203125},{x:.140625,y:.203125},{x:.171875,y:.203125},{x:.171875,y:.203125},{x:.203125,y:.203125},{x:.203125,y:.203125},{x:.234375,y:.203125},{x:.234375,y:.203125},{x:.265625,y:.203125},{x:.265625,y:.203125},{x:.296875,y:.203125},{x:.296875,y:.203125},{x:.328125,y:.203125},{x:.328125,y:.203125},{x:.359375,y:.203125},{x:.359375,y:.203125},{x:.390625,y:.203125},{x:.390625,y:.203125},{x:.421875,y:.203125},{x:.421875,y:.203125},{x:.453125,y:.203125},{x:.453125,y:.203125},{x:.484375,y:.203125},{x:.484375,y:.203125},{x:.515625,y:.203125},{x:.515625,y:.203125},{x:.546875,y:.203125},{x:.546875,y:.203125},{x:.578125,y:.203125},{x:.578125,y:.203125},{x:.609375,y:.203125},{x:.609375,y:.203125},{x:.640625,y:.203125},{x:.640625,y:.203125},{x:.671875,y:.203125},{x:.671875,y:.203125},{x:.703125,y:.203125},{x:.703125,y:.203125},{x:.734375,y:.203125},{x:.734375,y:.203125},{x:.765625,y:.203125},{x:.765625,y:.203125},{x:.796875,y:.203125},{x:.796875,y:.203125},{x:.828125,y:.203125},{x:.828125,y:.203125},{x:.859375,y:.203125},{x:.859375,y:.203125},{x:.890625,y:.203125},{x:.890625,y:.203125},{x:.921875,y:.203125},{x:.921875,y:.203125},{x:.953125,y:.203125},{x:.953125,y:.203125},{x:.984375,y:.203125},{x:.984375,y:.203125},{x:.015625,y:.234375},{x:.015625,y:.234375},{x:.046875,y:.234375},{x:.046875,y:.234375},{x:.078125,y:.234375},{x:.078125,y:.234375},{x:.109375,y:.234375},{x:.109375,y:.234375},{x:.140625,y:.234375},{x:.140625,y:.234375},{x:.171875,y:.234375},{x:.171875,y:.234375},{x:.203125,y:.234375},{x:.203125,y:.234375},{x:.234375,y:.234375},{x:.234375,y:.234375},{x:.265625,y:.234375},{x:.265625,y:.234375},{x:.296875,y:.234375},{x:.296875,y:.234375},{x:.328125,y:.234375},{x:.328125,y:.234375},{x:.359375,y:.234375},{x:.359375,y:.234375},{x:.390625,y:.234375},{x:.390625,y:.234375},{x:.421875,y:.234375},{x:.421875,y:.234375},{x:.453125,y:.234375},{x:.453125,y:.234375},{x:.484375,y:.234375},{x:.484375,y:.234375},{x:.515625,y:.234375},{x:.515625,y:.234375},{x:.546875,y:.234375},{x:.546875,y:.234375},{x:.578125,y:.234375},{x:.578125,y:.234375},{x:.609375,y:.234375},{x:.609375,y:.234375},{x:.640625,y:.234375},{x:.640625,y:.234375},{x:.671875,y:.234375},{x:.671875,y:.234375},{x:.703125,y:.234375},{x:.703125,y:.234375},{x:.734375,y:.234375},{x:.734375,y:.234375},{x:.765625,y:.234375},{x:.765625,y:.234375},{x:.796875,y:.234375},{x:.796875,y:.234375},{x:.828125,y:.234375},{x:.828125,y:.234375},{x:.859375,y:.234375},{x:.859375,y:.234375},{x:.890625,y:.234375},{x:.890625,y:.234375},{x:.921875,y:.234375},{x:.921875,y:.234375},{x:.953125,y:.234375},{x:.953125,y:.234375},{x:.984375,y:.234375},{x:.984375,y:.234375},{x:.015625,y:.265625},{x:.015625,y:.265625},{x:.046875,y:.265625},{x:.046875,y:.265625},{x:.078125,y:.265625},{x:.078125,y:.265625},{x:.109375,y:.265625},{x:.109375,y:.265625},{x:.140625,y:.265625},{x:.140625,y:.265625},{x:.171875,y:.265625},{x:.171875,y:.265625},{x:.203125,y:.265625},{x:.203125,y:.265625},{x:.234375,y:.265625},{x:.234375,y:.265625},{x:.265625,y:.265625},{x:.265625,y:.265625},{x:.296875,y:.265625},{x:.296875,y:.265625},{x:.328125,y:.265625},{x:.328125,y:.265625},{x:.359375,y:.265625},{x:.359375,y:.265625},{x:.390625,y:.265625},{x:.390625,y:.265625},{x:.421875,y:.265625},{x:.421875,y:.265625},{x:.453125,y:.265625},{x:.453125,y:.265625},{x:.484375,y:.265625},{x:.484375,y:.265625},{x:.515625,y:.265625},{x:.515625,y:.265625},{x:.546875,y:.265625},{x:.546875,y:.265625},{x:.578125,y:.265625},{x:.578125,y:.265625},{x:.609375,y:.265625},{x:.609375,y:.265625},{x:.640625,y:.265625},{x:.640625,y:.265625},{x:.671875,y:.265625},{x:.671875,y:.265625},{x:.703125,y:.265625},{x:.703125,y:.265625},{x:.734375,y:.265625},{x:.734375,y:.265625},{x:.765625,y:.265625},{x:.765625,y:.265625},{x:.796875,y:.265625},{x:.796875,y:.265625},{x:.828125,y:.265625},{x:.828125,y:.265625},{x:.859375,y:.265625},{x:.859375,y:.265625},{x:.890625,y:.265625},{x:.890625,y:.265625},{x:.921875,y:.265625},{x:.921875,y:.265625},{x:.953125,y:.265625},{x:.953125,y:.265625},{x:.984375,y:.265625},{x:.984375,y:.265625},{x:.015625,y:.296875},{x:.015625,y:.296875},{x:.046875,y:.296875},{x:.046875,y:.296875},{x:.078125,y:.296875},{x:.078125,y:.296875},{x:.109375,y:.296875},{x:.109375,y:.296875},{x:.140625,y:.296875},{x:.140625,y:.296875},{x:.171875,y:.296875},{x:.171875,y:.296875},{x:.203125,y:.296875},{x:.203125,y:.296875},{x:.234375,y:.296875},{x:.234375,y:.296875},{x:.265625,y:.296875},{x:.265625,y:.296875},{x:.296875,y:.296875},{x:.296875,y:.296875},{x:.328125,y:.296875},{x:.328125,y:.296875},{x:.359375,y:.296875},{x:.359375,y:.296875},{x:.390625,y:.296875},{x:.390625,y:.296875},{x:.421875,y:.296875},{x:.421875,y:.296875},{x:.453125,y:.296875},{x:.453125,y:.296875},{x:.484375,y:.296875},{x:.484375,y:.296875},{x:.515625,y:.296875},{x:.515625,y:.296875},{x:.546875,y:.296875},{x:.546875,y:.296875},{x:.578125,y:.296875},{x:.578125,y:.296875},{x:.609375,y:.296875},{x:.609375,y:.296875},{x:.640625,y:.296875},{x:.640625,y:.296875},{x:.671875,y:.296875},{x:.671875,y:.296875},{x:.703125,y:.296875},{x:.703125,y:.296875},{x:.734375,y:.296875},{x:.734375,y:.296875},{x:.765625,y:.296875},{x:.765625,y:.296875},{x:.796875,y:.296875},{x:.796875,y:.296875},{x:.828125,y:.296875},{x:.828125,y:.296875},{x:.859375,y:.296875},{x:.859375,y:.296875},{x:.890625,y:.296875},{x:.890625,y:.296875},{x:.921875,y:.296875},{x:.921875,y:.296875},{x:.953125,y:.296875},{x:.953125,y:.296875},{x:.984375,y:.296875},{x:.984375,y:.296875},{x:.015625,y:.328125},{x:.015625,y:.328125},{x:.046875,y:.328125},{x:.046875,y:.328125},{x:.078125,y:.328125},{x:.078125,y:.328125},{x:.109375,y:.328125},{x:.109375,y:.328125},{x:.140625,y:.328125},{x:.140625,y:.328125},{x:.171875,y:.328125},{x:.171875,y:.328125},{x:.203125,y:.328125},{x:.203125,y:.328125},{x:.234375,y:.328125},{x:.234375,y:.328125},{x:.265625,y:.328125},{x:.265625,y:.328125},{x:.296875,y:.328125},{x:.296875,y:.328125},{x:.328125,y:.328125},{x:.328125,y:.328125},{x:.359375,y:.328125},{x:.359375,y:.328125},{x:.390625,y:.328125},{x:.390625,y:.328125},{x:.421875,y:.328125},{x:.421875,y:.328125},{x:.453125,y:.328125},{x:.453125,y:.328125},{x:.484375,y:.328125},{x:.484375,y:.328125},{x:.515625,y:.328125},{x:.515625,y:.328125},{x:.546875,y:.328125},{x:.546875,y:.328125},{x:.578125,y:.328125},{x:.578125,y:.328125},{x:.609375,y:.328125},{x:.609375,y:.328125},{x:.640625,y:.328125},{x:.640625,y:.328125},{x:.671875,y:.328125},{x:.671875,y:.328125},{x:.703125,y:.328125},{x:.703125,y:.328125},{x:.734375,y:.328125},{x:.734375,y:.328125},{x:.765625,y:.328125},{x:.765625,y:.328125},{x:.796875,y:.328125},{x:.796875,y:.328125},{x:.828125,y:.328125},{x:.828125,y:.328125},{x:.859375,y:.328125},{x:.859375,y:.328125},{x:.890625,y:.328125},{x:.890625,y:.328125},{x:.921875,y:.328125},{x:.921875,y:.328125},{x:.953125,y:.328125},{x:.953125,y:.328125},{x:.984375,y:.328125},{x:.984375,y:.328125},{x:.015625,y:.359375},{x:.015625,y:.359375},{x:.046875,y:.359375},{x:.046875,y:.359375},{x:.078125,y:.359375},{x:.078125,y:.359375},{x:.109375,y:.359375},{x:.109375,y:.359375},{x:.140625,y:.359375},{x:.140625,y:.359375},{x:.171875,y:.359375},{x:.171875,y:.359375},{x:.203125,y:.359375},{x:.203125,y:.359375},{x:.234375,y:.359375},{x:.234375,y:.359375},{x:.265625,y:.359375},{x:.265625,y:.359375},{x:.296875,y:.359375},{x:.296875,y:.359375},{x:.328125,y:.359375},{x:.328125,y:.359375},{x:.359375,y:.359375},{x:.359375,y:.359375},{x:.390625,y:.359375},{x:.390625,y:.359375},{x:.421875,y:.359375},{x:.421875,y:.359375},{x:.453125,y:.359375},{x:.453125,y:.359375},{x:.484375,y:.359375},{x:.484375,y:.359375},{x:.515625,y:.359375},{x:.515625,y:.359375},{x:.546875,y:.359375},{x:.546875,y:.359375},{x:.578125,y:.359375},{x:.578125,y:.359375},{x:.609375,y:.359375},{x:.609375,y:.359375},{x:.640625,y:.359375},{x:.640625,y:.359375},{x:.671875,y:.359375},{x:.671875,y:.359375},{x:.703125,y:.359375},{x:.703125,y:.359375},{x:.734375,y:.359375},{x:.734375,y:.359375},{x:.765625,y:.359375},{x:.765625,y:.359375},{x:.796875,y:.359375},{x:.796875,y:.359375},{x:.828125,y:.359375},{x:.828125,y:.359375},{x:.859375,y:.359375},{x:.859375,y:.359375},{x:.890625,y:.359375},{x:.890625,y:.359375},{x:.921875,y:.359375},{x:.921875,y:.359375},{x:.953125,y:.359375},{x:.953125,y:.359375},{x:.984375,y:.359375},{x:.984375,y:.359375},{x:.015625,y:.390625},{x:.015625,y:.390625},{x:.046875,y:.390625},{x:.046875,y:.390625},{x:.078125,y:.390625},{x:.078125,y:.390625},{x:.109375,y:.390625},{x:.109375,y:.390625},{x:.140625,y:.390625},{x:.140625,y:.390625},{x:.171875,y:.390625},{x:.171875,y:.390625},{x:.203125,y:.390625},{x:.203125,y:.390625},{x:.234375,y:.390625},{x:.234375,y:.390625},{x:.265625,y:.390625},{x:.265625,y:.390625},{x:.296875,y:.390625},{x:.296875,y:.390625},{x:.328125,y:.390625},{x:.328125,y:.390625},{x:.359375,y:.390625},{x:.359375,y:.390625},{x:.390625,y:.390625},{x:.390625,y:.390625},{x:.421875,y:.390625},{x:.421875,y:.390625},{x:.453125,y:.390625},{x:.453125,y:.390625},{x:.484375,y:.390625},{x:.484375,y:.390625},{x:.515625,y:.390625},{x:.515625,y:.390625},{x:.546875,y:.390625},{x:.546875,y:.390625},{x:.578125,y:.390625},{x:.578125,y:.390625},{x:.609375,y:.390625},{x:.609375,y:.390625},{x:.640625,y:.390625},{x:.640625,y:.390625},{x:.671875,y:.390625},{x:.671875,y:.390625},{x:.703125,y:.390625},{x:.703125,y:.390625},{x:.734375,y:.390625},{x:.734375,y:.390625},{x:.765625,y:.390625},{x:.765625,y:.390625},{x:.796875,y:.390625},{x:.796875,y:.390625},{x:.828125,y:.390625},{x:.828125,y:.390625},{x:.859375,y:.390625},{x:.859375,y:.390625},{x:.890625,y:.390625},{x:.890625,y:.390625},{x:.921875,y:.390625},{x:.921875,y:.390625},{x:.953125,y:.390625},{x:.953125,y:.390625},{x:.984375,y:.390625},{x:.984375,y:.390625},{x:.015625,y:.421875},{x:.015625,y:.421875},{x:.046875,y:.421875},{x:.046875,y:.421875},{x:.078125,y:.421875},{x:.078125,y:.421875},{x:.109375,y:.421875},{x:.109375,y:.421875},{x:.140625,y:.421875},{x:.140625,y:.421875},{x:.171875,y:.421875},{x:.171875,y:.421875},{x:.203125,y:.421875},{x:.203125,y:.421875},{x:.234375,y:.421875},{x:.234375,y:.421875},{x:.265625,y:.421875},{x:.265625,y:.421875},{x:.296875,y:.421875},{x:.296875,y:.421875},{x:.328125,y:.421875},{x:.328125,y:.421875},{x:.359375,y:.421875},{x:.359375,y:.421875},{x:.390625,y:.421875},{x:.390625,y:.421875},{x:.421875,y:.421875},{x:.421875,y:.421875},{x:.453125,y:.421875},{x:.453125,y:.421875},{x:.484375,y:.421875},{x:.484375,y:.421875},{x:.515625,y:.421875},{x:.515625,y:.421875},{x:.546875,y:.421875},{x:.546875,y:.421875},{x:.578125,y:.421875},{x:.578125,y:.421875},{x:.609375,y:.421875},{x:.609375,y:.421875},{x:.640625,y:.421875},{x:.640625,y:.421875},{x:.671875,y:.421875},{x:.671875,y:.421875},{x:.703125,y:.421875},{x:.703125,y:.421875},{x:.734375,y:.421875},{x:.734375,y:.421875},{x:.765625,y:.421875},{x:.765625,y:.421875},{x:.796875,y:.421875},{x:.796875,y:.421875},{x:.828125,y:.421875},{x:.828125,y:.421875},{x:.859375,y:.421875},{x:.859375,y:.421875},{x:.890625,y:.421875},{x:.890625,y:.421875},{x:.921875,y:.421875},{x:.921875,y:.421875},{x:.953125,y:.421875},{x:.953125,y:.421875},{x:.984375,y:.421875},{x:.984375,y:.421875},{x:.015625,y:.453125},{x:.015625,y:.453125},{x:.046875,y:.453125},{x:.046875,y:.453125},{x:.078125,y:.453125},{x:.078125,y:.453125},{x:.109375,y:.453125},{x:.109375,y:.453125},{x:.140625,y:.453125},{x:.140625,y:.453125},{x:.171875,y:.453125},{x:.171875,y:.453125},{x:.203125,y:.453125},{x:.203125,y:.453125},{x:.234375,y:.453125},{x:.234375,y:.453125},{x:.265625,y:.453125},{x:.265625,y:.453125},{x:.296875,y:.453125},{x:.296875,y:.453125},{x:.328125,y:.453125},{x:.328125,y:.453125},{x:.359375,y:.453125},{x:.359375,y:.453125},{x:.390625,y:.453125},{x:.390625,y:.453125},{x:.421875,y:.453125},{x:.421875,y:.453125},{x:.453125,y:.453125},{x:.453125,y:.453125},{x:.484375,y:.453125},{x:.484375,y:.453125},{x:.515625,y:.453125},{x:.515625,y:.453125},{x:.546875,y:.453125},{x:.546875,y:.453125},{x:.578125,y:.453125},{x:.578125,y:.453125},{x:.609375,y:.453125},{x:.609375,y:.453125},{x:.640625,y:.453125},{x:.640625,y:.453125},{x:.671875,y:.453125},{x:.671875,y:.453125},{x:.703125,y:.453125},{x:.703125,y:.453125},{x:.734375,y:.453125},{x:.734375,y:.453125},{x:.765625,y:.453125},{x:.765625,y:.453125},{x:.796875,y:.453125},{x:.796875,y:.453125},{x:.828125,y:.453125},{x:.828125,y:.453125},{x:.859375,y:.453125},{x:.859375,y:.453125},{x:.890625,y:.453125},{x:.890625,y:.453125},{x:.921875,y:.453125},{x:.921875,y:.453125},{x:.953125,y:.453125},{x:.953125,y:.453125},{x:.984375,y:.453125},{x:.984375,y:.453125},{x:.015625,y:.484375},{x:.015625,y:.484375},{x:.046875,y:.484375},{x:.046875,y:.484375},{x:.078125,y:.484375},{x:.078125,y:.484375},{x:.109375,y:.484375},{x:.109375,y:.484375},{x:.140625,y:.484375},{x:.140625,y:.484375},{x:.171875,y:.484375},{x:.171875,y:.484375},{x:.203125,y:.484375},{x:.203125,y:.484375},{x:.234375,y:.484375},{x:.234375,y:.484375},{x:.265625,y:.484375},{x:.265625,y:.484375},{x:.296875,y:.484375},{x:.296875,y:.484375},{x:.328125,y:.484375},{x:.328125,y:.484375},{x:.359375,y:.484375},{x:.359375,y:.484375},{x:.390625,y:.484375},{x:.390625,y:.484375},{x:.421875,y:.484375},{x:.421875,y:.484375},{x:.453125,y:.484375},{x:.453125,y:.484375},{x:.484375,y:.484375},{x:.484375,y:.484375},{x:.515625,y:.484375},{x:.515625,y:.484375},{x:.546875,y:.484375},{x:.546875,y:.484375},{x:.578125,y:.484375},{x:.578125,y:.484375},{x:.609375,y:.484375},{x:.609375,y:.484375},{x:.640625,y:.484375},{x:.640625,y:.484375},{x:.671875,y:.484375},{x:.671875,y:.484375},{x:.703125,y:.484375},{x:.703125,y:.484375},{x:.734375,y:.484375},{x:.734375,y:.484375},{x:.765625,y:.484375},{x:.765625,y:.484375},{x:.796875,y:.484375},{x:.796875,y:.484375},{x:.828125,y:.484375},{x:.828125,y:.484375},{x:.859375,y:.484375},{x:.859375,y:.484375},{x:.890625,y:.484375},{x:.890625,y:.484375},{x:.921875,y:.484375},{x:.921875,y:.484375},{x:.953125,y:.484375},{x:.953125,y:.484375},{x:.984375,y:.484375},{x:.984375,y:.484375},{x:.015625,y:.515625},{x:.015625,y:.515625},{x:.046875,y:.515625},{x:.046875,y:.515625},{x:.078125,y:.515625},{x:.078125,y:.515625},{x:.109375,y:.515625},{x:.109375,y:.515625},{x:.140625,y:.515625},{x:.140625,y:.515625},{x:.171875,y:.515625},{x:.171875,y:.515625},{x:.203125,y:.515625},{x:.203125,y:.515625},{x:.234375,y:.515625},{x:.234375,y:.515625},{x:.265625,y:.515625},{x:.265625,y:.515625},{x:.296875,y:.515625},{x:.296875,y:.515625},{x:.328125,y:.515625},{x:.328125,y:.515625},{x:.359375,y:.515625},{x:.359375,y:.515625},{x:.390625,y:.515625},{x:.390625,y:.515625},{x:.421875,y:.515625},{x:.421875,y:.515625},{x:.453125,y:.515625},{x:.453125,y:.515625},{x:.484375,y:.515625},{x:.484375,y:.515625},{x:.515625,y:.515625},{x:.515625,y:.515625},{x:.546875,y:.515625},{x:.546875,y:.515625},{x:.578125,y:.515625},{x:.578125,y:.515625},{x:.609375,y:.515625},{x:.609375,y:.515625},{x:.640625,y:.515625},{x:.640625,y:.515625},{x:.671875,y:.515625},{x:.671875,y:.515625},{x:.703125,y:.515625},{x:.703125,y:.515625},{x:.734375,y:.515625},{x:.734375,y:.515625},{x:.765625,y:.515625},{x:.765625,y:.515625},{x:.796875,y:.515625},{x:.796875,y:.515625},{x:.828125,y:.515625},{x:.828125,y:.515625},{x:.859375,y:.515625},{x:.859375,y:.515625},{x:.890625,y:.515625},{x:.890625,y:.515625},{x:.921875,y:.515625},{x:.921875,y:.515625},{x:.953125,y:.515625},{x:.953125,y:.515625},{x:.984375,y:.515625},{x:.984375,y:.515625},{x:.015625,y:.546875},{x:.015625,y:.546875},{x:.046875,y:.546875},{x:.046875,y:.546875},{x:.078125,y:.546875},{x:.078125,y:.546875},{x:.109375,y:.546875},{x:.109375,y:.546875},{x:.140625,y:.546875},{x:.140625,y:.546875},{x:.171875,y:.546875},{x:.171875,y:.546875},{x:.203125,y:.546875},{x:.203125,y:.546875},{x:.234375,y:.546875},{x:.234375,y:.546875},{x:.265625,y:.546875},{x:.265625,y:.546875},{x:.296875,y:.546875},{x:.296875,y:.546875},{x:.328125,y:.546875},{x:.328125,y:.546875},{x:.359375,y:.546875},{x:.359375,y:.546875},{x:.390625,y:.546875},{x:.390625,y:.546875},{x:.421875,y:.546875},{x:.421875,y:.546875},{x:.453125,y:.546875},{x:.453125,y:.546875},{x:.484375,y:.546875},{x:.484375,y:.546875},{x:.515625,y:.546875},{x:.515625,y:.546875},{x:.546875,y:.546875},{x:.546875,y:.546875},{x:.578125,y:.546875},{x:.578125,y:.546875},{x:.609375,y:.546875},{x:.609375,y:.546875},{x:.640625,y:.546875},{x:.640625,y:.546875},{x:.671875,y:.546875},{x:.671875,y:.546875},{x:.703125,y:.546875},{x:.703125,y:.546875},{x:.734375,y:.546875},{x:.734375,y:.546875},{x:.765625,y:.546875},{x:.765625,y:.546875},{x:.796875,y:.546875},{x:.796875,y:.546875},{x:.828125,y:.546875},{x:.828125,y:.546875},{x:.859375,y:.546875},{x:.859375,y:.546875},{x:.890625,y:.546875},{x:.890625,y:.546875},{x:.921875,y:.546875},{x:.921875,y:.546875},{x:.953125,y:.546875},{x:.953125,y:.546875},{x:.984375,y:.546875},{x:.984375,y:.546875},{x:.015625,y:.578125},{x:.015625,y:.578125},{x:.046875,y:.578125},{x:.046875,y:.578125},{x:.078125,y:.578125},{x:.078125,y:.578125},{x:.109375,y:.578125},{x:.109375,y:.578125},{x:.140625,y:.578125},{x:.140625,y:.578125},{x:.171875,y:.578125},{x:.171875,y:.578125},{x:.203125,y:.578125},{x:.203125,y:.578125},{x:.234375,y:.578125},{x:.234375,y:.578125},{x:.265625,y:.578125},{x:.265625,y:.578125},{x:.296875,y:.578125},{x:.296875,y:.578125},{x:.328125,y:.578125},{x:.328125,y:.578125},{x:.359375,y:.578125},{x:.359375,y:.578125},{x:.390625,y:.578125},{x:.390625,y:.578125},{x:.421875,y:.578125},{x:.421875,y:.578125},{x:.453125,y:.578125},{x:.453125,y:.578125},{x:.484375,y:.578125},{x:.484375,y:.578125},{x:.515625,y:.578125},{x:.515625,y:.578125},{x:.546875,y:.578125},{x:.546875,y:.578125},{x:.578125,y:.578125},{x:.578125,y:.578125},{x:.609375,y:.578125},{x:.609375,y:.578125},{x:.640625,y:.578125},{x:.640625,y:.578125},{x:.671875,y:.578125},{x:.671875,y:.578125},{x:.703125,y:.578125},{x:.703125,y:.578125},{x:.734375,y:.578125},{x:.734375,y:.578125},{x:.765625,y:.578125},{x:.765625,y:.578125},{x:.796875,y:.578125},{x:.796875,y:.578125},{x:.828125,y:.578125},{x:.828125,y:.578125},{x:.859375,y:.578125},{x:.859375,y:.578125},{x:.890625,y:.578125},{x:.890625,y:.578125},{x:.921875,y:.578125},{x:.921875,y:.578125},{x:.953125,y:.578125},{x:.953125,y:.578125},{x:.984375,y:.578125},{x:.984375,y:.578125},{x:.015625,y:.609375},{x:.015625,y:.609375},{x:.046875,y:.609375},{x:.046875,y:.609375},{x:.078125,y:.609375},{x:.078125,y:.609375},{x:.109375,y:.609375},{x:.109375,y:.609375},{x:.140625,y:.609375},{x:.140625,y:.609375},{x:.171875,y:.609375},{x:.171875,y:.609375},{x:.203125,y:.609375},{x:.203125,y:.609375},{x:.234375,y:.609375},{x:.234375,y:.609375},{x:.265625,y:.609375},{x:.265625,y:.609375},{x:.296875,y:.609375},{x:.296875,y:.609375},{x:.328125,y:.609375},{x:.328125,y:.609375},{x:.359375,y:.609375},{x:.359375,y:.609375},{x:.390625,y:.609375},{x:.390625,y:.609375},{x:.421875,y:.609375},{x:.421875,y:.609375},{x:.453125,y:.609375},{x:.453125,y:.609375},{x:.484375,y:.609375},{x:.484375,y:.609375},{x:.515625,y:.609375},{x:.515625,y:.609375},{x:.546875,y:.609375},{x:.546875,y:.609375},{x:.578125,y:.609375},{x:.578125,y:.609375},{x:.609375,y:.609375},{x:.609375,y:.609375},{x:.640625,y:.609375},{x:.640625,y:.609375},{x:.671875,y:.609375},{x:.671875,y:.609375},{x:.703125,y:.609375},{x:.703125,y:.609375},{x:.734375,y:.609375},{x:.734375,y:.609375},{x:.765625,y:.609375},{x:.765625,y:.609375},{x:.796875,y:.609375},{x:.796875,y:.609375},{x:.828125,y:.609375},{x:.828125,y:.609375},{x:.859375,y:.609375},{x:.859375,y:.609375},{x:.890625,y:.609375},{x:.890625,y:.609375},{x:.921875,y:.609375},{x:.921875,y:.609375},{x:.953125,y:.609375},{x:.953125,y:.609375},{x:.984375,y:.609375},{x:.984375,y:.609375},{x:.015625,y:.640625},{x:.015625,y:.640625},{x:.046875,y:.640625},{x:.046875,y:.640625},{x:.078125,y:.640625},{x:.078125,y:.640625},{x:.109375,y:.640625},{x:.109375,y:.640625},{x:.140625,y:.640625},{x:.140625,y:.640625},{x:.171875,y:.640625},{x:.171875,y:.640625},{x:.203125,y:.640625},{x:.203125,y:.640625},{x:.234375,y:.640625},{x:.234375,y:.640625},{x:.265625,y:.640625},{x:.265625,y:.640625},{x:.296875,y:.640625},{x:.296875,y:.640625},{x:.328125,y:.640625},{x:.328125,y:.640625},{x:.359375,y:.640625},{x:.359375,y:.640625},{x:.390625,y:.640625},{x:.390625,y:.640625},{x:.421875,y:.640625},{x:.421875,y:.640625},{x:.453125,y:.640625},{x:.453125,y:.640625},{x:.484375,y:.640625},{x:.484375,y:.640625},{x:.515625,y:.640625},{x:.515625,y:.640625},{x:.546875,y:.640625},{x:.546875,y:.640625},{x:.578125,y:.640625},{x:.578125,y:.640625},{x:.609375,y:.640625},{x:.609375,y:.640625},{x:.640625,y:.640625},{x:.640625,y:.640625},{x:.671875,y:.640625},{x:.671875,y:.640625},{x:.703125,y:.640625},{x:.703125,y:.640625},{x:.734375,y:.640625},{x:.734375,y:.640625},{x:.765625,y:.640625},{x:.765625,y:.640625},{x:.796875,y:.640625},{x:.796875,y:.640625},{x:.828125,y:.640625},{x:.828125,y:.640625},{x:.859375,y:.640625},{x:.859375,y:.640625},{x:.890625,y:.640625},{x:.890625,y:.640625},{x:.921875,y:.640625},{x:.921875,y:.640625},{x:.953125,y:.640625},{x:.953125,y:.640625},{x:.984375,y:.640625},{x:.984375,y:.640625},{x:.015625,y:.671875},{x:.015625,y:.671875},{x:.046875,y:.671875},{x:.046875,y:.671875},{x:.078125,y:.671875},{x:.078125,y:.671875},{x:.109375,y:.671875},{x:.109375,y:.671875},{x:.140625,y:.671875},{x:.140625,y:.671875},{x:.171875,y:.671875},{x:.171875,y:.671875},{x:.203125,y:.671875},{x:.203125,y:.671875},{x:.234375,y:.671875},{x:.234375,y:.671875},{x:.265625,y:.671875},{x:.265625,y:.671875},{x:.296875,y:.671875},{x:.296875,y:.671875},{x:.328125,y:.671875},{x:.328125,y:.671875},{x:.359375,y:.671875},{x:.359375,y:.671875},{x:.390625,y:.671875},{x:.390625,y:.671875},{x:.421875,y:.671875},{x:.421875,y:.671875},{x:.453125,y:.671875},{x:.453125,y:.671875},{x:.484375,y:.671875},{x:.484375,y:.671875},{x:.515625,y:.671875},{x:.515625,y:.671875},{x:.546875,y:.671875},{x:.546875,y:.671875},{x:.578125,y:.671875},{x:.578125,y:.671875},{x:.609375,y:.671875},{x:.609375,y:.671875},{x:.640625,y:.671875},{x:.640625,y:.671875},{x:.671875,y:.671875},{x:.671875,y:.671875},{x:.703125,y:.671875},{x:.703125,y:.671875},{x:.734375,y:.671875},{x:.734375,y:.671875},{x:.765625,y:.671875},{x:.765625,y:.671875},{x:.796875,y:.671875},{x:.796875,y:.671875},{x:.828125,y:.671875},{x:.828125,y:.671875},{x:.859375,y:.671875},{x:.859375,y:.671875},{x:.890625,y:.671875},{x:.890625,y:.671875},{x:.921875,y:.671875},{x:.921875,y:.671875},{x:.953125,y:.671875},{x:.953125,y:.671875},{x:.984375,y:.671875},{x:.984375,y:.671875},{x:.015625,y:.703125},{x:.015625,y:.703125},{x:.046875,y:.703125},{x:.046875,y:.703125},{x:.078125,y:.703125},{x:.078125,y:.703125},{x:.109375,y:.703125},{x:.109375,y:.703125},{x:.140625,y:.703125},{x:.140625,y:.703125},{x:.171875,y:.703125},{x:.171875,y:.703125},{x:.203125,y:.703125},{x:.203125,y:.703125},{x:.234375,y:.703125},{x:.234375,y:.703125},{x:.265625,y:.703125},{x:.265625,y:.703125},{x:.296875,y:.703125},{x:.296875,y:.703125},{x:.328125,y:.703125},{x:.328125,y:.703125},{x:.359375,y:.703125},{x:.359375,y:.703125},{x:.390625,y:.703125},{x:.390625,y:.703125},{x:.421875,y:.703125},{x:.421875,y:.703125},{x:.453125,y:.703125},{x:.453125,y:.703125},{x:.484375,y:.703125},{x:.484375,y:.703125},{x:.515625,y:.703125},{x:.515625,y:.703125},{x:.546875,y:.703125},{x:.546875,y:.703125},{x:.578125,y:.703125},{x:.578125,y:.703125},{x:.609375,y:.703125},{x:.609375,y:.703125},{x:.640625,y:.703125},{x:.640625,y:.703125},{x:.671875,y:.703125},{x:.671875,y:.703125},{x:.703125,y:.703125},{x:.703125,y:.703125},{x:.734375,y:.703125},{x:.734375,y:.703125},{x:.765625,y:.703125},{x:.765625,y:.703125},{x:.796875,y:.703125},{x:.796875,y:.703125},{x:.828125,y:.703125},{x:.828125,y:.703125},{x:.859375,y:.703125},{x:.859375,y:.703125},{x:.890625,y:.703125},{x:.890625,y:.703125},{x:.921875,y:.703125},{x:.921875,y:.703125},{x:.953125,y:.703125},{x:.953125,y:.703125},{x:.984375,y:.703125},{x:.984375,y:.703125},{x:.015625,y:.734375},{x:.015625,y:.734375},{x:.046875,y:.734375},{x:.046875,y:.734375},{x:.078125,y:.734375},{x:.078125,y:.734375},{x:.109375,y:.734375},{x:.109375,y:.734375},{x:.140625,y:.734375},{x:.140625,y:.734375},{x:.171875,y:.734375},{x:.171875,y:.734375},{x:.203125,y:.734375},{x:.203125,y:.734375},{x:.234375,y:.734375},{x:.234375,y:.734375},{x:.265625,y:.734375},{x:.265625,y:.734375},{x:.296875,y:.734375},{x:.296875,y:.734375},{x:.328125,y:.734375},{x:.328125,y:.734375},{x:.359375,y:.734375},{x:.359375,y:.734375},{x:.390625,y:.734375},{x:.390625,y:.734375},{x:.421875,y:.734375},{x:.421875,y:.734375},{x:.453125,y:.734375},{x:.453125,y:.734375},{x:.484375,y:.734375},{x:.484375,y:.734375},{x:.515625,y:.734375},{x:.515625,y:.734375},{x:.546875,y:.734375},{x:.546875,y:.734375},{x:.578125,y:.734375},{x:.578125,y:.734375},{x:.609375,y:.734375},{x:.609375,y:.734375},{x:.640625,y:.734375},{x:.640625,y:.734375},{x:.671875,y:.734375},{x:.671875,y:.734375},{x:.703125,y:.734375},{x:.703125,y:.734375},{x:.734375,y:.734375},{x:.734375,y:.734375},{x:.765625,y:.734375},{x:.765625,y:.734375},{x:.796875,y:.734375},{x:.796875,y:.734375},{x:.828125,y:.734375},{x:.828125,y:.734375},{x:.859375,y:.734375},{x:.859375,y:.734375},{x:.890625,y:.734375},{x:.890625,y:.734375},{x:.921875,y:.734375},{x:.921875,y:.734375},{x:.953125,y:.734375},{x:.953125,y:.734375},{x:.984375,y:.734375},{x:.984375,y:.734375},{x:.015625,y:.765625},{x:.015625,y:.765625},{x:.046875,y:.765625},{x:.046875,y:.765625},{x:.078125,y:.765625},{x:.078125,y:.765625},{x:.109375,y:.765625},{x:.109375,y:.765625},{x:.140625,y:.765625},{x:.140625,y:.765625},{x:.171875,y:.765625},{x:.171875,y:.765625},{x:.203125,y:.765625},{x:.203125,y:.765625},{x:.234375,y:.765625},{x:.234375,y:.765625},{x:.265625,y:.765625},{x:.265625,y:.765625},{x:.296875,y:.765625},{x:.296875,y:.765625},{x:.328125,y:.765625},{x:.328125,y:.765625},{x:.359375,y:.765625},{x:.359375,y:.765625},{x:.390625,y:.765625},{x:.390625,y:.765625},{x:.421875,y:.765625},{x:.421875,y:.765625},{x:.453125,y:.765625},{x:.453125,y:.765625},{x:.484375,y:.765625},{x:.484375,y:.765625},{x:.515625,y:.765625},{x:.515625,y:.765625},{x:.546875,y:.765625},{x:.546875,y:.765625},{x:.578125,y:.765625},{x:.578125,y:.765625},{x:.609375,y:.765625},{x:.609375,y:.765625},{x:.640625,y:.765625},{x:.640625,y:.765625},{x:.671875,y:.765625},{x:.671875,y:.765625},{x:.703125,y:.765625},{x:.703125,y:.765625},{x:.734375,y:.765625},{x:.734375,y:.765625},{x:.765625,y:.765625},{x:.765625,y:.765625},{x:.796875,y:.765625},{x:.796875,y:.765625},{x:.828125,y:.765625},{x:.828125,y:.765625},{x:.859375,y:.765625},{x:.859375,y:.765625},{x:.890625,y:.765625},{x:.890625,y:.765625},{x:.921875,y:.765625},{x:.921875,y:.765625},{x:.953125,y:.765625},{x:.953125,y:.765625},{x:.984375,y:.765625},{x:.984375,y:.765625},{x:.015625,y:.796875},{x:.015625,y:.796875},{x:.046875,y:.796875},{x:.046875,y:.796875},{x:.078125,y:.796875},{x:.078125,y:.796875},{x:.109375,y:.796875},{x:.109375,y:.796875},{x:.140625,y:.796875},{x:.140625,y:.796875},{x:.171875,y:.796875},{x:.171875,y:.796875},{x:.203125,y:.796875},{x:.203125,y:.796875},{x:.234375,y:.796875},{x:.234375,y:.796875},{x:.265625,y:.796875},{x:.265625,y:.796875},{x:.296875,y:.796875},{x:.296875,y:.796875},{x:.328125,y:.796875},{x:.328125,y:.796875},{x:.359375,y:.796875},{x:.359375,y:.796875},{x:.390625,y:.796875},{x:.390625,y:.796875},{x:.421875,y:.796875},{x:.421875,y:.796875},{x:.453125,y:.796875},{x:.453125,y:.796875},{x:.484375,y:.796875},{x:.484375,y:.796875},{x:.515625,y:.796875},{x:.515625,y:.796875},{x:.546875,y:.796875},{x:.546875,y:.796875},{x:.578125,y:.796875},{x:.578125,y:.796875},{x:.609375,y:.796875},{x:.609375,y:.796875},{x:.640625,y:.796875},{x:.640625,y:.796875},{x:.671875,y:.796875},{x:.671875,y:.796875},{x:.703125,y:.796875},{x:.703125,y:.796875},{x:.734375,y:.796875},{x:.734375,y:.796875},{x:.765625,y:.796875},{x:.765625,y:.796875},{x:.796875,y:.796875},{x:.796875,y:.796875},{x:.828125,y:.796875},{x:.828125,y:.796875},{x:.859375,y:.796875},{x:.859375,y:.796875},{x:.890625,y:.796875},{x:.890625,y:.796875},{x:.921875,y:.796875},{x:.921875,y:.796875},{x:.953125,y:.796875},{x:.953125,y:.796875},{x:.984375,y:.796875},{x:.984375,y:.796875},{x:.015625,y:.828125},{x:.015625,y:.828125},{x:.046875,y:.828125},{x:.046875,y:.828125},{x:.078125,y:.828125},{x:.078125,y:.828125},{x:.109375,y:.828125},{x:.109375,y:.828125},{x:.140625,y:.828125},{x:.140625,y:.828125},{x:.171875,y:.828125},{x:.171875,y:.828125},{x:.203125,y:.828125},{x:.203125,y:.828125},{x:.234375,y:.828125},{x:.234375,y:.828125},{x:.265625,y:.828125},{x:.265625,y:.828125},{x:.296875,y:.828125},{x:.296875,y:.828125},{x:.328125,y:.828125},{x:.328125,y:.828125},{x:.359375,y:.828125},{x:.359375,y:.828125},{x:.390625,y:.828125},{x:.390625,y:.828125},{x:.421875,y:.828125},{x:.421875,y:.828125},{x:.453125,y:.828125},{x:.453125,y:.828125},{x:.484375,y:.828125},{x:.484375,y:.828125},{x:.515625,y:.828125},{x:.515625,y:.828125},{x:.546875,y:.828125},{x:.546875,y:.828125},{x:.578125,y:.828125},{x:.578125,y:.828125},{x:.609375,y:.828125},{x:.609375,y:.828125},{x:.640625,y:.828125},{x:.640625,y:.828125},{x:.671875,y:.828125},{x:.671875,y:.828125},{x:.703125,y:.828125},{x:.703125,y:.828125},{x:.734375,y:.828125},{x:.734375,y:.828125},{x:.765625,y:.828125},{x:.765625,y:.828125},{x:.796875,y:.828125},{x:.796875,y:.828125},{x:.828125,y:.828125},{x:.828125,y:.828125},{x:.859375,y:.828125},{x:.859375,y:.828125},{x:.890625,y:.828125},{x:.890625,y:.828125},{x:.921875,y:.828125},{x:.921875,y:.828125},{x:.953125,y:.828125},{x:.953125,y:.828125},{x:.984375,y:.828125},{x:.984375,y:.828125},{x:.015625,y:.859375},{x:.015625,y:.859375},{x:.046875,y:.859375},{x:.046875,y:.859375},{x:.078125,y:.859375},{x:.078125,y:.859375},{x:.109375,y:.859375},{x:.109375,y:.859375},{x:.140625,y:.859375},{x:.140625,y:.859375},{x:.171875,y:.859375},{x:.171875,y:.859375},{x:.203125,y:.859375},{x:.203125,y:.859375},{x:.234375,y:.859375},{x:.234375,y:.859375},{x:.265625,y:.859375},{x:.265625,y:.859375},{x:.296875,y:.859375},{x:.296875,y:.859375},{x:.328125,y:.859375},{x:.328125,y:.859375},{x:.359375,y:.859375},{x:.359375,y:.859375},{x:.390625,y:.859375},{x:.390625,y:.859375},{x:.421875,y:.859375},{x:.421875,y:.859375},{x:.453125,y:.859375},{x:.453125,y:.859375},{x:.484375,y:.859375},{x:.484375,y:.859375},{x:.515625,y:.859375},{x:.515625,y:.859375},{x:.546875,y:.859375},{x:.546875,y:.859375},{x:.578125,y:.859375},{x:.578125,y:.859375},{x:.609375,y:.859375},{x:.609375,y:.859375},{x:.640625,y:.859375},{x:.640625,y:.859375},{x:.671875,y:.859375},{x:.671875,y:.859375},{x:.703125,y:.859375},{x:.703125,y:.859375},{x:.734375,y:.859375},{x:.734375,y:.859375},{x:.765625,y:.859375},{x:.765625,y:.859375},{x:.796875,y:.859375},{x:.796875,y:.859375},{x:.828125,y:.859375},{x:.828125,y:.859375},{x:.859375,y:.859375},{x:.859375,y:.859375},{x:.890625,y:.859375},{x:.890625,y:.859375},{x:.921875,y:.859375},{x:.921875,y:.859375},{x:.953125,y:.859375},{x:.953125,y:.859375},{x:.984375,y:.859375},{x:.984375,y:.859375},{x:.015625,y:.890625},{x:.015625,y:.890625},{x:.046875,y:.890625},{x:.046875,y:.890625},{x:.078125,y:.890625},{x:.078125,y:.890625},{x:.109375,y:.890625},{x:.109375,y:.890625},{x:.140625,y:.890625},{x:.140625,y:.890625},{x:.171875,y:.890625},{x:.171875,y:.890625},{x:.203125,y:.890625},{x:.203125,y:.890625},{x:.234375,y:.890625},{x:.234375,y:.890625},{x:.265625,y:.890625},{x:.265625,y:.890625},{x:.296875,y:.890625},{x:.296875,y:.890625},{x:.328125,y:.890625},{x:.328125,y:.890625},{x:.359375,y:.890625},{x:.359375,y:.890625},{x:.390625,y:.890625},{x:.390625,y:.890625},{x:.421875,y:.890625},{x:.421875,y:.890625},{x:.453125,y:.890625},{x:.453125,y:.890625},{x:.484375,y:.890625},{x:.484375,y:.890625},{x:.515625,y:.890625},{x:.515625,y:.890625},{x:.546875,y:.890625},{x:.546875,y:.890625},{x:.578125,y:.890625},{x:.578125,y:.890625},{x:.609375,y:.890625},{x:.609375,y:.890625},{x:.640625,y:.890625},{x:.640625,y:.890625},{x:.671875,y:.890625},{x:.671875,y:.890625},{x:.703125,y:.890625},{x:.703125,y:.890625},{x:.734375,y:.890625},{x:.734375,y:.890625},{x:.765625,y:.890625},{x:.765625,y:.890625},{x:.796875,y:.890625},{x:.796875,y:.890625},{x:.828125,y:.890625},{x:.828125,y:.890625},{x:.859375,y:.890625},{x:.859375,y:.890625},{x:.890625,y:.890625},{x:.890625,y:.890625},{x:.921875,y:.890625},{x:.921875,y:.890625},{x:.953125,y:.890625},{x:.953125,y:.890625},{x:.984375,y:.890625},{x:.984375,y:.890625},{x:.015625,y:.921875},{x:.015625,y:.921875},{x:.046875,y:.921875},{x:.046875,y:.921875},{x:.078125,y:.921875},{x:.078125,y:.921875},{x:.109375,y:.921875},{x:.109375,y:.921875},{x:.140625,y:.921875},{x:.140625,y:.921875},{x:.171875,y:.921875},{x:.171875,y:.921875},{x:.203125,y:.921875},{x:.203125,y:.921875},{x:.234375,y:.921875},{x:.234375,y:.921875},{x:.265625,y:.921875},{x:.265625,y:.921875},{x:.296875,y:.921875},{x:.296875,y:.921875},{x:.328125,y:.921875},{x:.328125,y:.921875},{x:.359375,y:.921875},{x:.359375,y:.921875},{x:.390625,y:.921875},{x:.390625,y:.921875},{x:.421875,y:.921875},{x:.421875,y:.921875},{x:.453125,y:.921875},{x:.453125,y:.921875},{x:.484375,y:.921875},{x:.484375,y:.921875},{x:.515625,y:.921875},{x:.515625,y:.921875},{x:.546875,y:.921875},{x:.546875,y:.921875},{x:.578125,y:.921875},{x:.578125,y:.921875},{x:.609375,y:.921875},{x:.609375,y:.921875},{x:.640625,y:.921875},{x:.640625,y:.921875},{x:.671875,y:.921875},{x:.671875,y:.921875},{x:.703125,y:.921875},{x:.703125,y:.921875},{x:.734375,y:.921875},{x:.734375,y:.921875},{x:.765625,y:.921875},{x:.765625,y:.921875},{x:.796875,y:.921875},{x:.796875,y:.921875},{x:.828125,y:.921875},{x:.828125,y:.921875},{x:.859375,y:.921875},{x:.859375,y:.921875},{x:.890625,y:.921875},{x:.890625,y:.921875},{x:.921875,y:.921875},{x:.921875,y:.921875},{x:.953125,y:.921875},{x:.953125,y:.921875},{x:.984375,y:.921875},{x:.984375,y:.921875},{x:.015625,y:.953125},{x:.015625,y:.953125},{x:.046875,y:.953125},{x:.046875,y:.953125},{x:.078125,y:.953125},{x:.078125,y:.953125},{x:.109375,y:.953125},{x:.109375,y:.953125},{x:.140625,y:.953125},{x:.140625,y:.953125},{x:.171875,y:.953125},{x:.171875,y:.953125},{x:.203125,y:.953125},{x:.203125,y:.953125},{x:.234375,y:.953125},{x:.234375,y:.953125},{x:.265625,y:.953125},{x:.265625,y:.953125},{x:.296875,y:.953125},{x:.296875,y:.953125},{x:.328125,y:.953125},{x:.328125,y:.953125},{x:.359375,y:.953125},{x:.359375,y:.953125},{x:.390625,y:.953125},{x:.390625,y:.953125},{x:.421875,y:.953125},{x:.421875,y:.953125},{x:.453125,y:.953125},{x:.453125,y:.953125},{x:.484375,y:.953125},{x:.484375,y:.953125},{x:.515625,y:.953125},{x:.515625,y:.953125},{x:.546875,y:.953125},{x:.546875,y:.953125},{x:.578125,y:.953125},{x:.578125,y:.953125},{x:.609375,y:.953125},{x:.609375,y:.953125},{x:.640625,y:.953125},{x:.640625,y:.953125},{x:.671875,y:.953125},{x:.671875,y:.953125},{x:.703125,y:.953125},{x:.703125,y:.953125},{x:.734375,y:.953125},{x:.734375,y:.953125},{x:.765625,y:.953125},{x:.765625,y:.953125},{x:.796875,y:.953125},{x:.796875,y:.953125},{x:.828125,y:.953125},{x:.828125,y:.953125},{x:.859375,y:.953125},{x:.859375,y:.953125},{x:.890625,y:.953125},{x:.890625,y:.953125},{x:.921875,y:.953125},{x:.921875,y:.953125},{x:.953125,y:.953125},{x:.953125,y:.953125},{x:.984375,y:.953125},{x:.984375,y:.953125},{x:.015625,y:.984375},{x:.015625,y:.984375},{x:.046875,y:.984375},{x:.046875,y:.984375},{x:.078125,y:.984375},{x:.078125,y:.984375},{x:.109375,y:.984375},{x:.109375,y:.984375},{x:.140625,y:.984375},{x:.140625,y:.984375},{x:.171875,y:.984375},{x:.171875,y:.984375},{x:.203125,y:.984375},{x:.203125,y:.984375},{x:.234375,y:.984375},{x:.234375,y:.984375},{x:.265625,y:.984375},{x:.265625,y:.984375},{x:.296875,y:.984375},{x:.296875,y:.984375},{x:.328125,y:.984375},{x:.328125,y:.984375},{x:.359375,y:.984375},{x:.359375,y:.984375},{x:.390625,y:.984375},{x:.390625,y:.984375},{x:.421875,y:.984375},{x:.421875,y:.984375},{x:.453125,y:.984375},{x:.453125,y:.984375},{x:.484375,y:.984375},{x:.484375,y:.984375},{x:.515625,y:.984375},{x:.515625,y:.984375},{x:.546875,y:.984375},{x:.546875,y:.984375},{x:.578125,y:.984375},{x:.578125,y:.984375},{x:.609375,y:.984375},{x:.609375,y:.984375},{x:.640625,y:.984375},{x:.640625,y:.984375},{x:.671875,y:.984375},{x:.671875,y:.984375},{x:.703125,y:.984375},{x:.703125,y:.984375},{x:.734375,y:.984375},{x:.734375,y:.984375},{x:.765625,y:.984375},{x:.765625,y:.984375},{x:.796875,y:.984375},{x:.796875,y:.984375},{x:.828125,y:.984375},{x:.828125,y:.984375},{x:.859375,y:.984375},{x:.859375,y:.984375},{x:.890625,y:.984375},{x:.890625,y:.984375},{x:.921875,y:.984375},{x:.921875,y:.984375},{x:.953125,y:.984375},{x:.953125,y:.984375},{x:.984375,y:.984375},{x:.984375,y:.984375},{x:.03125,y:.03125},{x:.03125,y:.03125},{x:.09375,y:.03125},{x:.09375,y:.03125},{x:.15625,y:.03125},{x:.15625,y:.03125},{x:.21875,y:.03125},{x:.21875,y:.03125},{x:.28125,y:.03125},{x:.28125,y:.03125},{x:.34375,y:.03125},{x:.34375,y:.03125},{x:.40625,y:.03125},{x:.40625,y:.03125},{x:.46875,y:.03125},{x:.46875,y:.03125},{x:.53125,y:.03125},{x:.53125,y:.03125},{x:.59375,y:.03125},{x:.59375,y:.03125},{x:.65625,y:.03125},{x:.65625,y:.03125},{x:.71875,y:.03125},{x:.71875,y:.03125},{x:.78125,y:.03125},{x:.78125,y:.03125},{x:.84375,y:.03125},{x:.84375,y:.03125},{x:.90625,y:.03125},{x:.90625,y:.03125},{x:.96875,y:.03125},{x:.96875,y:.03125},{x:.03125,y:.09375},{x:.03125,y:.09375},{x:.09375,y:.09375},{x:.09375,y:.09375},{x:.15625,y:.09375},{x:.15625,y:.09375},{x:.21875,y:.09375},{x:.21875,y:.09375},{x:.28125,y:.09375},{x:.28125,y:.09375},{x:.34375,y:.09375},{x:.34375,y:.09375},{x:.40625,y:.09375},{x:.40625,y:.09375},{x:.46875,y:.09375},{x:.46875,y:.09375},{x:.53125,y:.09375},{x:.53125,y:.09375},{x:.59375,y:.09375},{x:.59375,y:.09375},{x:.65625,y:.09375},{x:.65625,y:.09375},{x:.71875,y:.09375},{x:.71875,y:.09375},{x:.78125,y:.09375},{x:.78125,y:.09375},{x:.84375,y:.09375},{x:.84375,y:.09375},{x:.90625,y:.09375},{x:.90625,y:.09375},{x:.96875,y:.09375},{x:.96875,y:.09375},{x:.03125,y:.15625},{x:.03125,y:.15625},{x:.09375,y:.15625},{x:.09375,y:.15625},{x:.15625,y:.15625},{x:.15625,y:.15625},{x:.21875,y:.15625},{x:.21875,y:.15625},{x:.28125,y:.15625},{x:.28125,y:.15625},{x:.34375,y:.15625},{x:.34375,y:.15625},{x:.40625,y:.15625},{x:.40625,y:.15625},{x:.46875,y:.15625},{x:.46875,y:.15625},{x:.53125,y:.15625},{x:.53125,y:.15625},{x:.59375,y:.15625},{x:.59375,y:.15625},{x:.65625,y:.15625},{x:.65625,y:.15625},{x:.71875,y:.15625},{x:.71875,y:.15625},{x:.78125,y:.15625},{x:.78125,y:.15625},{x:.84375,y:.15625},{x:.84375,y:.15625},{x:.90625,y:.15625},{x:.90625,y:.15625},{x:.96875,y:.15625},{x:.96875,y:.15625},{x:.03125,y:.21875},{x:.03125,y:.21875},{x:.09375,y:.21875},{x:.09375,y:.21875},{x:.15625,y:.21875},{x:.15625,y:.21875},{x:.21875,y:.21875},{x:.21875,y:.21875},{x:.28125,y:.21875},{x:.28125,y:.21875},{x:.34375,y:.21875},{x:.34375,y:.21875},{x:.40625,y:.21875},{x:.40625,y:.21875},{x:.46875,y:.21875},{x:.46875,y:.21875},{x:.53125,y:.21875},{x:.53125,y:.21875},{x:.59375,y:.21875},{x:.59375,y:.21875},{x:.65625,y:.21875},{x:.65625,y:.21875},{x:.71875,y:.21875},{x:.71875,y:.21875},{x:.78125,y:.21875},{x:.78125,y:.21875},{x:.84375,y:.21875},{x:.84375,y:.21875},{x:.90625,y:.21875},{x:.90625,y:.21875},{x:.96875,y:.21875},{x:.96875,y:.21875},{x:.03125,y:.28125},{x:.03125,y:.28125},{x:.09375,y:.28125},{x:.09375,y:.28125},{x:.15625,y:.28125},{x:.15625,y:.28125},{x:.21875,y:.28125},{x:.21875,y:.28125},{x:.28125,y:.28125},{x:.28125,y:.28125},{x:.34375,y:.28125},{x:.34375,y:.28125},{x:.40625,y:.28125},{x:.40625,y:.28125},{x:.46875,y:.28125},{x:.46875,y:.28125},{x:.53125,y:.28125},{x:.53125,y:.28125},{x:.59375,y:.28125},{x:.59375,y:.28125},{x:.65625,y:.28125},{x:.65625,y:.28125},{x:.71875,y:.28125},{x:.71875,y:.28125},{x:.78125,y:.28125},{x:.78125,y:.28125},{x:.84375,y:.28125},{x:.84375,y:.28125},{x:.90625,y:.28125},{x:.90625,y:.28125},{x:.96875,y:.28125},{x:.96875,y:.28125},{x:.03125,y:.34375},{x:.03125,y:.34375},{x:.09375,y:.34375},{x:.09375,y:.34375},{x:.15625,y:.34375},{x:.15625,y:.34375},{x:.21875,y:.34375},{x:.21875,y:.34375},{x:.28125,y:.34375},{x:.28125,y:.34375},{x:.34375,y:.34375},{x:.34375,y:.34375},{x:.40625,y:.34375},{x:.40625,y:.34375},{x:.46875,y:.34375},{x:.46875,y:.34375},{x:.53125,y:.34375},{x:.53125,y:.34375},{x:.59375,y:.34375},{x:.59375,y:.34375},{x:.65625,y:.34375},{x:.65625,y:.34375},{x:.71875,y:.34375},{x:.71875,y:.34375},{x:.78125,y:.34375},{x:.78125,y:.34375},{x:.84375,y:.34375},{x:.84375,y:.34375},{x:.90625,y:.34375},{x:.90625,y:.34375},{x:.96875,y:.34375},{x:.96875,y:.34375},{x:.03125,y:.40625},{x:.03125,y:.40625},{x:.09375,y:.40625},{x:.09375,y:.40625},{x:.15625,y:.40625},{x:.15625,y:.40625},{x:.21875,y:.40625},{x:.21875,y:.40625},{x:.28125,y:.40625},{x:.28125,y:.40625},{x:.34375,y:.40625},{x:.34375,y:.40625},{x:.40625,y:.40625},{x:.40625,y:.40625},{x:.46875,y:.40625},{x:.46875,y:.40625},{x:.53125,y:.40625},{x:.53125,y:.40625},{x:.59375,y:.40625},{x:.59375,y:.40625},{x:.65625,y:.40625},{x:.65625,y:.40625},{x:.71875,y:.40625},{x:.71875,y:.40625},{x:.78125,y:.40625},{x:.78125,y:.40625},{x:.84375,y:.40625},{x:.84375,y:.40625},{x:.90625,y:.40625},{x:.90625,y:.40625},{x:.96875,y:.40625},{x:.96875,y:.40625},{x:.03125,y:.46875},{x:.03125,y:.46875},{x:.09375,y:.46875},{x:.09375,y:.46875},{x:.15625,y:.46875},{x:.15625,y:.46875},{x:.21875,y:.46875},{x:.21875,y:.46875},{x:.28125,y:.46875},{x:.28125,y:.46875},{x:.34375,y:.46875},{x:.34375,y:.46875},{x:.40625,y:.46875},{x:.40625,y:.46875},{x:.46875,y:.46875},{x:.46875,y:.46875},{x:.53125,y:.46875},{x:.53125,y:.46875},{x:.59375,y:.46875},{x:.59375,y:.46875},{x:.65625,y:.46875},{x:.65625,y:.46875},{x:.71875,y:.46875},{x:.71875,y:.46875},{x:.78125,y:.46875},{x:.78125,y:.46875},{x:.84375,y:.46875},{x:.84375,y:.46875},{x:.90625,y:.46875},{x:.90625,y:.46875},{x:.96875,y:.46875},{x:.96875,y:.46875},{x:.03125,y:.53125},{x:.03125,y:.53125},{x:.09375,y:.53125},{x:.09375,y:.53125},{x:.15625,y:.53125},{x:.15625,y:.53125},{x:.21875,y:.53125},{x:.21875,y:.53125},{x:.28125,y:.53125},{x:.28125,y:.53125},{x:.34375,y:.53125},{x:.34375,y:.53125},{x:.40625,y:.53125},{x:.40625,y:.53125},{x:.46875,y:.53125},{x:.46875,y:.53125},{x:.53125,y:.53125},{x:.53125,y:.53125},{x:.59375,y:.53125},{x:.59375,y:.53125},{x:.65625,y:.53125},{x:.65625,y:.53125},{x:.71875,y:.53125},{x:.71875,y:.53125},{x:.78125,y:.53125},{x:.78125,y:.53125},{x:.84375,y:.53125},{x:.84375,y:.53125},{x:.90625,y:.53125},{x:.90625,y:.53125},{x:.96875,y:.53125},{x:.96875,y:.53125},{x:.03125,y:.59375},{x:.03125,y:.59375},{x:.09375,y:.59375},{x:.09375,y:.59375},{x:.15625,y:.59375},{x:.15625,y:.59375},{x:.21875,y:.59375},{x:.21875,y:.59375},{x:.28125,y:.59375},{x:.28125,y:.59375},{x:.34375,y:.59375},{x:.34375,y:.59375},{x:.40625,y:.59375},{x:.40625,y:.59375},{x:.46875,y:.59375},{x:.46875,y:.59375},{x:.53125,y:.59375},{x:.53125,y:.59375},{x:.59375,y:.59375},{x:.59375,y:.59375},{x:.65625,y:.59375},{x:.65625,y:.59375},{x:.71875,y:.59375},{x:.71875,y:.59375},{x:.78125,y:.59375},{x:.78125,y:.59375},{x:.84375,y:.59375},{x:.84375,y:.59375},{x:.90625,y:.59375},{x:.90625,y:.59375},{x:.96875,y:.59375},{x:.96875,y:.59375},{x:.03125,y:.65625},{x:.03125,y:.65625},{x:.09375,y:.65625},{x:.09375,y:.65625},{x:.15625,y:.65625},{x:.15625,y:.65625},{x:.21875,y:.65625},{x:.21875,y:.65625},{x:.28125,y:.65625},{x:.28125,y:.65625},{x:.34375,y:.65625},{x:.34375,y:.65625},{x:.40625,y:.65625},{x:.40625,y:.65625},{x:.46875,y:.65625},{x:.46875,y:.65625},{x:.53125,y:.65625},{x:.53125,y:.65625},{x:.59375,y:.65625},{x:.59375,y:.65625},{x:.65625,y:.65625},{x:.65625,y:.65625},{x:.71875,y:.65625},{x:.71875,y:.65625},{x:.78125,y:.65625},{x:.78125,y:.65625},{x:.84375,y:.65625},{x:.84375,y:.65625},{x:.90625,y:.65625},{x:.90625,y:.65625},{x:.96875,y:.65625},{x:.96875,y:.65625},{x:.03125,y:.71875},{x:.03125,y:.71875},{x:.09375,y:.71875},{x:.09375,y:.71875},{x:.15625,y:.71875},{x:.15625,y:.71875},{x:.21875,y:.71875},{x:.21875,y:.71875},{x:.28125,y:.71875},{x:.28125,y:.71875},{x:.34375,y:.71875},{x:.34375,y:.71875},{x:.40625,y:.71875},{x:.40625,y:.71875},{x:.46875,y:.71875},{x:.46875,y:.71875},{x:.53125,y:.71875},{x:.53125,y:.71875},{x:.59375,y:.71875},{x:.59375,y:.71875},{x:.65625,y:.71875},{x:.65625,y:.71875},{x:.71875,y:.71875},{x:.71875,y:.71875},{x:.78125,y:.71875},{x:.78125,y:.71875},{x:.84375,y:.71875},{x:.84375,y:.71875},{x:.90625,y:.71875},{x:.90625,y:.71875},{x:.96875,y:.71875},{x:.96875,y:.71875},{x:.03125,y:.78125},{x:.03125,y:.78125},{x:.09375,y:.78125},{x:.09375,y:.78125},{x:.15625,y:.78125},{x:.15625,y:.78125},{x:.21875,y:.78125},{x:.21875,y:.78125},{x:.28125,y:.78125},{x:.28125,y:.78125},{x:.34375,y:.78125},{x:.34375,y:.78125},{x:.40625,y:.78125},{x:.40625,y:.78125},{x:.46875,y:.78125},{x:.46875,y:.78125},{x:.53125,y:.78125},{x:.53125,y:.78125},{x:.59375,y:.78125},{x:.59375,y:.78125},{x:.65625,y:.78125},{x:.65625,y:.78125},{x:.71875,y:.78125},{x:.71875,y:.78125},{x:.78125,y:.78125},{x:.78125,y:.78125},{x:.84375,y:.78125},{x:.84375,y:.78125},{x:.90625,y:.78125},{x:.90625,y:.78125},{x:.96875,y:.78125},{x:.96875,y:.78125},{x:.03125,y:.84375},{x:.03125,y:.84375},{x:.09375,y:.84375},{x:.09375,y:.84375},{x:.15625,y:.84375},{x:.15625,y:.84375},{x:.21875,y:.84375},{x:.21875,y:.84375},{x:.28125,y:.84375},{x:.28125,y:.84375},{x:.34375,y:.84375},{x:.34375,y:.84375},{x:.40625,y:.84375},{x:.40625,y:.84375},{x:.46875,y:.84375},{x:.46875,y:.84375},{x:.53125,y:.84375},{x:.53125,y:.84375},{x:.59375,y:.84375},{x:.59375,y:.84375},{x:.65625,y:.84375},{x:.65625,y:.84375},{x:.71875,y:.84375},{x:.71875,y:.84375},{x:.78125,y:.84375},{x:.78125,y:.84375},{x:.84375,y:.84375},{x:.84375,y:.84375},{x:.90625,y:.84375},{x:.90625,y:.84375},{x:.96875,y:.84375},{x:.96875,y:.84375},{x:.03125,y:.90625},{x:.03125,y:.90625},{x:.09375,y:.90625},{x:.09375,y:.90625},{x:.15625,y:.90625},{x:.15625,y:.90625},{x:.21875,y:.90625},{x:.21875,y:.90625},{x:.28125,y:.90625},{x:.28125,y:.90625},{x:.34375,y:.90625},{x:.34375,y:.90625},{x:.40625,y:.90625},{x:.40625,y:.90625},{x:.46875,y:.90625},{x:.46875,y:.90625},{x:.53125,y:.90625},{x:.53125,y:.90625},{x:.59375,y:.90625},{x:.59375,y:.90625},{x:.65625,y:.90625},{x:.65625,y:.90625},{x:.71875,y:.90625},{x:.71875,y:.90625},{x:.78125,y:.90625},{x:.78125,y:.90625},{x:.84375,y:.90625},{x:.84375,y:.90625},{x:.90625,y:.90625},{x:.90625,y:.90625},{x:.96875,y:.90625},{x:.96875,y:.90625},{x:.03125,y:.96875},{x:.03125,y:.96875},{x:.09375,y:.96875},{x:.09375,y:.96875},{x:.15625,y:.96875},{x:.15625,y:.96875},{x:.21875,y:.96875},{x:.21875,y:.96875},{x:.28125,y:.96875},{x:.28125,y:.96875},{x:.34375,y:.96875},{x:.34375,y:.96875},{x:.40625,y:.96875},{x:.40625,y:.96875},{x:.46875,y:.96875},{x:.46875,y:.96875},{x:.53125,y:.96875},{x:.53125,y:.96875},{x:.59375,y:.96875},{x:.59375,y:.96875},{x:.65625,y:.96875},{x:.65625,y:.96875},{x:.71875,y:.96875},{x:.71875,y:.96875},{x:.78125,y:.96875},{x:.78125,y:.96875},{x:.84375,y:.96875},{x:.84375,y:.96875},{x:.90625,y:.96875},{x:.90625,y:.96875},{x:.96875,y:.96875},{x:.96875,y:.96875},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375}];var C2=class{constructor(t){w(this,"model");w(this,"anchors");w(this,"anchorsTensor");w(this,"inputSize");w(this,"inputSizeTensor");w(this,"doubleInputSizeTensor");this.model=t,this.anchors=m3.map(o=>[o.x,o.y]),this.anchorsTensor=A.tensor2d(this.anchors),this.inputSize=this.model&&this.model.inputs&&this.model.inputs[0].shape?this.model.inputs[0].shape[2]:0,this.inputSizeTensor=A.tensor1d([this.inputSize,this.inputSize]),this.doubleInputSizeTensor=A.tensor1d([this.inputSize*2,this.inputSize*2])}normalizeBoxes(t){let o={};o.boxOffsets=A.slice(t,[0,0],[-1,2]),o.boxSizes=A.slice(t,[0,2],[-1,2]),o.div=A.div(o.boxOffsets,this.inputSizeTensor),o.boxCenterPoints=A.add(o.div,this.anchorsTensor),o.halfBoxSizes=A.div(o.boxSizes,this.doubleInputSizeTensor),o.sub=A.sub(o.boxCenterPoints,o.halfBoxSizes),o.startPoints=A.mul(o.sub,this.inputSizeTensor),o.add=A.add(o.boxCenterPoints,o.halfBoxSizes),o.endPoints=A.mul(o.add,this.inputSizeTensor);let n=A.concat2d([o.startPoints,o.endPoints],1);return Object.keys(o).forEach(r=>A.dispose(o[r])),n}normalizeLandmarks(t,o){let n={};n.reshape=A.reshape(t,[-1,7,2]),n.div=A.div(n.reshape,this.inputSizeTensor),n.landmarks=A.add(n.div,this.anchors[o]);let r=A.mul(n.landmarks,this.inputSizeTensor);return Object.keys(n).forEach(s=>A.dispose(n[s])),r}async predict(t,o){let n={};n.resize=A.image.resizeBilinear(t,[this.inputSize,this.inputSize]),n.div=A.div(n.resize,G.tf127),n.image=A.sub(n.div,G.tf1),n.batched=this.model.execute(n.image),n.predictions=A.squeeze(n.batched),n.slice=A.slice(n.predictions,[0,0],[-1,1]),n.sigmoid=A.sigmoid(n.slice),n.scores=A.squeeze(n.sigmoid);let r=await n.scores.data();n.boxes=A.slice(n.predictions,[0,1],[-1,4]),n.norm=this.normalizeBoxes(n.boxes),n.nms=await A.image.nonMaxSuppressionAsync(n.norm,n.scores,3*o.hand.maxDetected,o.hand.iouThreshold,o.hand.minConfidence);let s=await n.nms.array(),a=[];for(let i of s){let l={};l.box=A.slice(n.norm,[i,0],[1,-1]),l.slice=A.slice(n.predictions,[i,5],[1,14]),l.norm=this.normalizeLandmarks(l.slice,i),l.palmLandmarks=A.reshape(l.norm,[-1,2]);let c=await l.box.data(),d=c.slice(0,2),y=c.slice(2,4),x=await l.palmLandmarks.array(),m={startPoint:d,endPoint:y,palmLandmarks:x,confidence:r[i]},h=x3(m,[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]);a.push(h),Object.keys(l).forEach(p=>A.dispose(l[p]))}return Object.keys(n).forEach(i=>A.dispose(n[i])),a}};var Tr=5,p3=1.65,u3=[0,5,9,13,17,1,2],wr=0,kr=2,h3=0,I2=class{constructor(t,o){w(this,"handDetector");w(this,"handPoseModel");w(this,"inputSize");w(this,"storedBoxes");w(this,"skipped");w(this,"detectedHands");this.handDetector=t,this.handPoseModel=o,this.inputSize=this.handPoseModel&&this.handPoseModel.inputs[0].shape?this.handPoseModel.inputs[0].shape[2]:0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let o=t.map(a=>a[0]),n=t.map(a=>a[1]),r=[Math.min(...o),Math.min(...n)],s=[Math.max(...o),Math.max(...n)];return{startPoint:r,endPoint:s}}getBoxForPalmLandmarks(t,o){let n=t.map(s=>D5([...s,1],o)),r=this.calculateLandmarksBoundingBox(n);return z2(S2(r),Tr)}getBoxForHandLandmarks(t){let o=this.calculateLandmarksBoundingBox(t),n=z2(S2(o),p3);n.palmLandmarks=[];for(let r=0;r<u3.length;r++)n.palmLandmarks.push(t[u3[r]].slice(0,2));return n}transformRawCoords(t,o,n,r){let s=E2(o),a=[s[0]/this.inputSize,s[1]/this.inputSize,(s[0]+s[1])/this.inputSize/2],i=t.map(m=>[a[0]*(m[0]-this.inputSize/2),a[1]*(m[1]-this.inputSize/2),a[2]*m[2]]),l=V5(n,[0,0]),c=i.map(m=>[...D5(m,l),m[2]]),d=d3(r),y=[...e2(o),1],x=[$0(y,d[0]),$0(y,d[1])];return c.map(m=>[Math.trunc(m[0]+x[0]),Math.trunc(m[1]+x[1]),Math.trunc(m[2])])}async estimateHands(t,o){let n=!1,r,s=(o.hand.skipTime||0)>b()-h3,a=this.skipped<(o.hand.skipFrames||0);o.skipAllowed&&s&&a&&(r=await this.handDetector.predict(t,o),this.skipped=0),o.skipAllowed&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==o.hand.maxDetected||!o.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(n=!0));let i=[];for(let l=0;l<this.storedBoxes.length;l++){let c=this.storedBoxes[l];if(!!c)if(o.hand.landmarks){let d=o.hand.rotation?c3(c.palmLandmarks[wr],c.palmLandmarks[kr]):0,y=e2(c),x=[y[0]/t.shape[2],y[1]/t.shape[1]],m=o.hand.rotation&&T.kernels.includes("rotatewithoffset")?A.image.rotateWithOffset(t,d,0,x):t.clone(),h=V5(-d,y),p=n?this.getBoxForPalmLandmarks(c.palmLandmarks,h):c,R=y3(p,m,[this.inputSize,this.inputSize]),M=A.div(R,G.tf255);A.dispose(R),A.dispose(m);let[g,f]=this.handPoseModel.execute(M);h3=b(),A.dispose(M);let P=(await g.data())[0];if(A.dispose(g),P>=o.hand.minConfidence/4){let C=A.reshape(f,[-1,3]),k=await C.array();A.dispose(f),A.dispose(C);let j=this.transformRawCoords(k,p,d,h),I=this.getBoxForHandLandmarks(j);this.storedBoxes[l]={...I,confidence:P};let O={landmarks:j,confidence:P,boxConfidence:c.confidence,fingerConfidence:P,box:{topLeft:I.startPoint,bottomRight:I.endPoint}};i.push(O)}else this.storedBoxes[l]=null;A.dispose(f)}else{let d=z2(S2(c),p3),y={confidence:c.confidence,boxConfidence:c.confidence,fingerConfidence:0,box:{topLeft:d.startPoint,bottomRight:d.endPoint},landmarks:[]};i.push(y)}}return this.storedBoxes=this.storedBoxes.filter(l=>l!==null),this.detectedHands=i.length,i.length>o.hand.maxDetected&&(i.length=o.hand.maxDetected),i}};var d0={thumb:0,index:1,middle:2,ring:3,pinky:4,all:[0,1,2,3,4],nameMapping:{0:"thumb",1:"index",2:"middle",3:"ring",4:"pinky"},pointsMapping:{0:[[0,1],[1,2],[2,3],[3,4]],1:[[0,5],[5,6],[6,7],[7,8]],2:[[0,9],[9,10],[10,11],[11,12]],3:[[0,13],[13,14],[14,15],[15,16]],4:[[0,17],[17,18],[18,19],[19,20]]},getName:e=>d0.nameMapping[e],getPoints:e=>d0.pointsMapping[e]},te={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>te.nameMapping[e]},K={verticalUp:0,verticalDown:1,horizontalLeft:2,horizontalRight:3,diagonalUpRight:4,diagonalUpLeft:5,diagonalDownRight:6,diagonalDownLeft:7,nameMapping:{0:"verticalUp",1:"verticalDown",2:"horizontalLeft",3:"horizontalRight",4:"diagonalUpRight",5:"diagonalUpLeft",6:"diagonalDownRight",7:"diagonalDownLeft"},getName:e=>K.nameMapping[e]},ee=class{constructor(t){w(this,"name");w(this,"curls");w(this,"directions");w(this,"weights");w(this,"weightsRelative");this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}curl(t,o,n){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([o,n])}direction(t,o,n){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([o,n])}weight(t,o){this.weights[t]=o;let n=this.weights.reduce((r,s)=>r+s,0);this.weightsRelative=this.weights.map(r=>r*5/n)}matchAgainst(t,o){let n=0;for(let r in t){let s=t[r],a=this.curls[r];if(typeof a=="undefined"){n+=this.weightsRelative[r];continue}for(let[i,l]of a)if(s===i){n+=l*this.weightsRelative[r];break}}for(let r in o){let s=o[r],a=this.directions[r];if(typeof a=="undefined"){n+=this.weightsRelative[r];continue}for(let[i,l]of a)if(s===i){n+=l*this.weightsRelative[r];break}}return n/10}};var{thumb:E0,index:V0,middle:D0,ring:fe,pinky:me}=d0,{none:z0,half:zr,full:S0}=te,{verticalUp:ze,verticalDown:q7,horizontalLeft:Z5,horizontalRight:Sr,diagonalUpRight:Cr,diagonalUpLeft:Se,diagonalDownRight:U7,diagonalDownLeft:Y7}=K,oe=new ee("thumbs up");oe.curl(E0,z0,1);oe.direction(E0,ze,1);oe.direction(E0,Se,.25);oe.direction(E0,Cr,.25);for(let e of[d0.index,d0.middle,d0.ring,d0.pinky])oe.curl(e,S0,1),oe.direction(e,Z5,1),oe.direction(e,Sr,1);var e0=new ee("victory");e0.curl(E0,zr,.5);e0.curl(E0,z0,.5);e0.direction(E0,ze,1);e0.direction(E0,Se,1);e0.curl(V0,z0,1);e0.direction(V0,ze,.75);e0.direction(V0,Se,1);e0.curl(D0,z0,1);e0.direction(D0,ze,1);e0.direction(D0,Se,.75);e0.curl(fe,S0,1);e0.direction(fe,ze,.2);e0.direction(fe,Se,1);e0.direction(fe,Z5,.2);e0.curl(me,S0,1);e0.direction(me,ze,.2);e0.direction(me,Se,1);e0.direction(me,Z5,.2);e0.weight(V0,2);e0.weight(D0,2);var ne=new ee("point");ne.curl(E0,S0,1);ne.curl(V0,z0,.5);ne.curl(D0,S0,.5);ne.curl(fe,S0,.5);ne.curl(me,S0,.5);ne.weight(V0,2);ne.weight(D0,2);var re=new ee("middle finger");re.curl(E0,z0,1);re.curl(V0,S0,.5);re.curl(D0,S0,.5);re.curl(fe,S0,.5);re.curl(me,S0,.5);re.weight(V0,2);re.weight(D0,2);var Ce=new ee("open palm");Ce.curl(E0,z0,.75);Ce.curl(V0,z0,.75);Ce.curl(D0,z0,.75);Ce.curl(fe,z0,.75);Ce.curl(me,z0,.75);var b3=[oe,e0,ne,re,Ce];var Ir=.7,pe={HALF_CURL_START_LIMIT:60,NO_CURL_START_LIMIT:130,DISTANCE_VOTE_POWER:1.1,SINGLE_ANGLE_VOTE_POWER:.9,TOTAL_ANGLE_VOTE_POWER:1.6};function g3(e,t,o,n){let r=(t-n)/(e-o),s=Math.atan(r)*180/Math.PI;return s<=0?s=-s:s>0&&(s=180-s),s}function P3(e,t){if(!e||!t)return[0,0];let o=g3(e[0],e[1],t[0],t[1]);if(e.length===2)return o;let n=g3(e[1],e[2],t[1],t[2]);return[o,n]}function M3(e,t=1){let o=0,n=0,r=0;return e>=75&&e<=105?o=1*t:e>=25&&e<=155?n=1*t:r=1*t,[o,n,r]}function jr(e,t,o){let n=e[0]-t[0],r=e[0]-o[0],s=t[0]-o[0],a=e[1]-t[1],i=e[1]-o[1],l=t[1]-o[1],c=e[2]-t[2],d=e[2]-o[2],y=t[2]-o[2],x=Math.sqrt(n*n+a*a+c*c),m=Math.sqrt(r*r+i*i+d*d),h=Math.sqrt(s*s+l*l+y*y),p=(h*h+x*x-m*m)/(2*h*x);p>1?p=1:p<-1&&(p=-1);let R=Math.acos(p);R=57.2958*R%180;let M;return R>pe.NO_CURL_START_LIMIT?M=te.none:R>pe.HALF_CURL_START_LIMIT?M=te.half:M=te.full,M}function R3(e,t,o,n){let r;return n===Math.abs(e)?e>0?r=K.horizontalLeft:r=K.horizontalRight:n===Math.abs(t)?t>0?r=K.horizontalLeft:r=K.horizontalRight:o>0?r=K.horizontalLeft:r=K.horizontalRight,r}function v3(e,t,o,n){let r;return n===Math.abs(e)?e<0?r=K.verticalDown:r=K.verticalUp:n===Math.abs(t)?t<0?r=K.verticalDown:r=K.verticalUp:o<0?r=K.verticalDown:r=K.verticalUp,r}function Nr(e,t,o,n,r,s,a,i){let l,c=v3(e,t,o,n),d=R3(r,s,a,i);return c===K.verticalUp?d===K.horizontalLeft?l=K.diagonalUpLeft:l=K.diagonalUpRight:d===K.horizontalLeft?l=K.diagonalDownLeft:l=K.diagonalDownRight,l}function Or(e,t,o,n){let r=e[0]-t[0],s=e[0]-o[0],a=t[0]-o[0],i=e[1]-t[1],l=e[1]-o[1],c=t[1]-o[1],d=Math.max(Math.abs(r),Math.abs(s),Math.abs(a)),y=Math.max(Math.abs(i),Math.abs(l),Math.abs(c)),x=0,m=0,h=0,p=y/(d+1e-5);p>1.5?x+=pe.DISTANCE_VOTE_POWER:p>.66?m+=pe.DISTANCE_VOTE_POWER:h+=pe.DISTANCE_VOTE_POWER;let R=Math.sqrt(r*r+i*i),M=Math.sqrt(s*s+l*l),g=Math.sqrt(a*a+c*c),f=Math.max(R,M,g),P=e[0],C=e[1],k=o[0],j=o[1];f===R?(k=o[0],j=o[1]):f===g&&(P=t[0],C=t[1]);let F=P3([P,C],[k,j]),V=M3(F,pe.TOTAL_ANGLE_VOTE_POWER);x+=V[0],m+=V[1],h+=V[2];for(let t0 of n){let z=M3(t0,pe.SINGLE_ANGLE_VOTE_POWER);x+=z[0],m+=z[1],h+=z[2]}let Z;return x===Math.max(x,m,h)?Z=v3(l,i,c,y):h===Math.max(m,h)?Z=R3(s,r,a,d):Z=Nr(l,i,c,y,s,r,a,d),Z}function T3(e){let t=[],o=[],n=[],r=[];if(!e)return{curls:n,directions:r};for(let s of d0.all){let a=d0.getPoints(s),i=[],l=[];for(let c of a){let d=e[c[0]],y=e[c[1]],x=P3(d,y),m=x[0],h=x[1];i.push(m),l.push(h)}t.push(i),o.push(l)}for(let s of d0.all){let a=s===d0.thumb?1:0,i=d0.getPoints(s),l=e[i[a][0]],c=e[i[a+1][1]],d=e[i[3][1]],y=jr(l,c,d),x=Or(l,c,d,t[s].slice(a));n[s]=y,r[s]=x}return{curls:n,directions:r}}function j2(e){if(!e||e.length===0)return null;let t=T3(e),o={};for(let n of d0.all)o[d0.getName(n)]={curl:te.getName(t.curls[n]),direction:K.getName(t.directions[n])};return o}function w3(e){let t=[];if(!e||e.length===0)return t;let o=T3(e);for(let n of b3){let r=n.matchAgainst(o.curls,o.directions);r>=Ir&&t.push({name:n.name,confidence:r})}return t}var k3={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],palm:[0]},Ie,je,E3;async function q5(e,t){let o=await E3.estimateHands(e,t);if(!o)return[];let n=[];for(let r=0;r<o.length;r++){let s={};if(o[r].landmarks)for(let d of Object.keys(k3))s[d]=k3[d].map(y=>o[r].landmarks[y]);let a=o[r].landmarks,i=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],l=[0,0,0,0];if(a&&a.length>0){for(let d of a)d[0]<i[0]&&(i[0]=d[0]),d[1]<i[1]&&(i[1]=d[1]),d[0]>i[2]&&(i[2]=d[0]),d[1]>i[3]&&(i[3]=d[1]);i[2]-=i[0],i[3]-=i[1],l=[i[0]/(e.shape[2]||0),i[1]/(e.shape[1]||0),i[2]/(e.shape[2]||0),i[3]/(e.shape[1]||0)]}else i=o[r].box?[Math.trunc(Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.max(0,o[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,o[r].box.bottomRight[0])-Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,o[r].box.bottomRight[1])-Math.max(0,o[r].box.topLeft[1]))]:[0,0,0,0],l=[o[r].box.topLeft[0]/(e.shape[2]||0),o[r].box.topLeft[1]/(e.shape[1]||0),(o[r].box.bottomRight[0]-o[r].box.topLeft[0])/(e.shape[2]||0),(o[r].box.bottomRight[1]-o[r].box.topLeft[1])/(e.shape[1]||0)];let c=j2(a);n.push({id:r,score:Math.round(100*o[r].confidence)/100,boxScore:Math.round(100*o[r].boxConfidence)/100,fingerScore:Math.round(100*o[r].fingerConfidence)/100,label:"hand",box:i,boxRaw:l,keypoints:a,annotations:s,landmarks:c})}return n}async function U5(e){var o,n;T.initial&&(Ie=null,je=null),!Ie||!je?[Ie,je]=await Promise.all([e.hand.enabled?L((o=e.hand.detector)==null?void 0:o.modelPath):null,e.hand.landmarks?L((n=e.hand.skeleton)==null?void 0:n.modelPath):null]):(e.debug&&u("cached model:",Ie.modelUrl),e.debug&&u("cached model:",je.modelUrl));let t=new C2(Ie);return E3=new I2(t,je),[Ie,je]}var n0=[null,null],Lr=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],Ae=[[0,0],[0,0]],Wr=["hand","fist","pinch","point","face","tip","pinchtip"],S3=4,C3=1.6,Fr=512,Gr=1.4,N2=Number.MAX_SAFE_INTEGER,Y5=0,Z0=[0,0],Q={boxes:[],hands:[]},I3={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],base:[0],palm:[0,17,13,9,5,1,0]};async function j3(e){var t;if(T.initial&&(n0[0]=null),n0[0])e.debug&&u("cached model:",n0[0].modelUrl);else{O2(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),n0[0]=await L((t=e.hand.detector)==null?void 0:t.modelPath);let o=Object.values(n0[0].modelSignature.inputs);Ae[0][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ae[0][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return n0[0]}async function N3(e){var t;if(T.initial&&(n0[1]=null),n0[1])e.debug&&u("cached model:",n0[1].modelUrl);else{n0[1]=await L((t=e.hand.skeleton)==null?void 0:t.modelPath);let o=Object.values(n0[1].modelSignature.inputs);Ae[1][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ae[1][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return n0[1]}async function Br(e,t){let o=[];if(!e||!n0[0])return o;let n={},r=(e.shape[2]||1)/(e.shape[1]||1),s=Math.min(Math.round((e.shape[1]||0)/8)*8,Fr),a=Math.round(s*r/8)*8;n.resize=A.image.resizeBilinear(e,[s,a]),n.cast=A.cast(n.resize,"int32"),[n.rawScores,n.rawBoxes]=await n0[0].executeAsync(n.cast,Lr),n.boxes=A.squeeze(n.rawBoxes,[0,2]),n.scores=A.squeeze(n.rawScores,[0]);let i=A.unstack(n.scores,1);A.dispose(i[S3]),i.splice(S3,1),n.filtered=A.stack(i,1),A.dispose(i),n.max=A.max(n.filtered,1),n.argmax=A.argMax(n.filtered,1);let l=0;n.nms=await A.image.nonMaxSuppressionAsync(n.boxes,n.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let c=await n.nms.data(),d=await n.max.data(),y=await n.argmax.data();for(let x of Array.from(c)){let m=A.slice(n.boxes,x,1),h=await m.data();A.dispose(m);let p=[h[1],h[0],h[3]-h[1],h[2]-h[0]],R=M2(p,Gr),M=[Math.trunc(p[0]*Z0[0]),Math.trunc(p[1]*Z0[1]),Math.trunc(p[2]*Z0[0]),Math.trunc(p[3]*Z0[1])],g=d[x],f=Wr[y[x]],P={id:l++,score:g,box:M,boxRaw:R,label:f};o.push(P)}return Object.keys(n).forEach(x=>A.dispose(n[x])),o.sort((x,m)=>m.score-x.score),o.length>(t.hand.maxDetected||1)&&(o.length=t.hand.maxDetected||1),o}async function K5(e,t,o){let n={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&n0[1]&&o.hand.landmarks&&t.score>(o.hand.minConfidence||0)){let r={},s=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=A.image.cropAndResize(e,[s],[0],[Ae[1][0],Ae[1][1]],"bilinear"),r.div=A.div(r.crop,G.tf255),[r.score,r.keypoints]=n0[1].execute(r.div,["Identity_1","Identity"]);let a=(await r.score.data())[0],i=(100-Math.trunc(100/(1+Math.exp(a))))/100;if(i>=(o.hand.minConfidence||0)){n.fingerScore=i,r.reshaped=A.reshape(r.keypoints,[-1,3]);let d=(await r.reshaped.array()).map(y=>[y[0]/Ae[1][1],y[1]/Ae[1][0],y[2]||0]).map(y=>[y[0]*t.boxRaw[2],y[1]*t.boxRaw[3],y[2]||0]);n.keypoints=d.map(y=>[Z0[0]*(y[0]+t.boxRaw[0]),Z0[1]*(y[1]+t.boxRaw[1]),y[2]||0]),n.landmarks=j2(n.keypoints);for(let y of Object.keys(I3))n.annotations[y]=I3[y].map(x=>n.landmarks&&n.keypoints[x]?n.keypoints[x]:null)}Object.keys(r).forEach(l=>A.dispose(r[l]))}return n}async function J5(e,t){var r,s;if(!n0[0]||!n0[1]||!((r=n0[0])!=null&&r.inputs[0].shape)||!((s=n0[1])!=null&&s.inputs[0].shape))return[];Z0=[e.shape[2]||0,e.shape[1]||0],N2++;let o=(t.hand.skipTime||0)>b()-Y5,n=N2<(t.hand.skipFrames||0);return t.skipAllowed&&o&&n?Q.hands:new Promise(async a=>{let i=3*(t.hand.skipTime||0)>b()-Y5,l=N2<3*(t.hand.skipFrames||0);t.skipAllowed&&Q.hands.length===t.hand.maxDetected?Q.hands=await Promise.all(Q.boxes.map(d=>K5(e,d,t))):t.skipAllowed&&i&&l&&Q.hands.length>0?Q.hands=await Promise.all(Q.boxes.map(d=>K5(e,d,t))):(Q.boxes=await Br(e,t),Y5=b(),Q.hands=await Promise.all(Q.boxes.map(d=>K5(e,d,t))),N2=0);let c=[...Q.boxes];if(Q.boxes.length=0,t.cacheSensitivity>0)for(let d=0;d<Q.hands.length;d++){let y=Tt(Q.hands[d].keypoints,Z0);if(y.box[2]/(e.shape[2]||1)>.05&&y.box[3]/(e.shape[1]||1)>.05&&Q.hands[d].fingerScore&&Q.hands[d].fingerScore>(t.hand.minConfidence||0)){let x=M2(y.box,C3),m=M2(y.boxRaw,C3);Q.boxes.push({...c[d],box:x,boxRaw:m})}}for(let d=0;d<Q.hands.length;d++){let y=G0(Q.hands[d].keypoints,Z0);Q.hands[d].box=y.box,Q.hands[d].boxRaw=y.boxRaw}a(Q.hands)})}var i0,L2=[],Q5=Number.MAX_SAFE_INTEGER,L3=0,W3=0;async function F3(e){var t;return T.initial&&(i0=null),i0?e.debug&&u("cached model:",i0.modelUrl):i0=await L((t=e.face.liveness)==null?void 0:t.modelPath),i0}async function _5(e,t,o,n){var a,i;if(!i0)return 0;let r=(((a=t.face.liveness)==null?void 0:a.skipTime)||0)>b()-W3,s=Q5<(((i=t.face.liveness)==null?void 0:i.skipFrames)||0);return t.skipAllowed&&r&&s&&L3===n&&L2[o]?(Q5++,L2[o]):(Q5=0,new Promise(async l=>{let c=A.image.resizeBilinear(e,[i0!=null&&i0.inputs[0].shape?i0.inputs[0].shape[2]:0,i0!=null&&i0.inputs[0].shape?i0.inputs[0].shape[1]:0],!1),d=i0==null?void 0:i0.execute(c),y=(await d.data())[0];L2[o]=Math.round(100*y)/100,L3=n,W3=b(),A.dispose([c,d]),l(L2[o])}))}var t2={};U0(t2,{connected:()=>F2,horizontal:()=>$5,kpt:()=>W2,relative:()=>t1,vertical:()=>e1});var W2=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],$5=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],e1=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],t1=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],F2={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var B3=.005,h0={keypoints:[],padding:[[0,0],[0,0],[0,0],[0,0]]};function o1(e){for(let t of $5){let o=e.keypoints.findIndex(r=>r.part===t[0]),n=e.keypoints.findIndex(r=>r.part===t[1]);if(e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[0]<e.keypoints[n].position[0]){let r=e.keypoints[o];e.keypoints[o]=e.keypoints[n],e.keypoints[n]=r}}for(let t of e1){let o=e.keypoints.findIndex(r=>r&&r.part===t[0]),n=e.keypoints.findIndex(r=>r&&r.part===t[1]);e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[1]<e.keypoints[n].position[1]&&e.keypoints.splice(o,1)}for(let[t,o]of t1){let n=e.keypoints.findIndex(c=>c&&c.part===t[0]),r=e.keypoints.findIndex(c=>c&&c.part===t[1]),s=e.keypoints.findIndex(c=>c&&c.part===o[0]),a=e.keypoints.findIndex(c=>c&&c.part===o[1]);if(!e.keypoints[s]||!e.keypoints[a])continue;let i=e.keypoints[n]?[Math.abs(e.keypoints[s].position[0]-e.keypoints[n].position[0]),Math.abs(e.keypoints[a].position[0]-e.keypoints[n].position[0])]:[0,0],l=e.keypoints[r]?[Math.abs(e.keypoints[a].position[0]-e.keypoints[r].position[0]),Math.abs(e.keypoints[s].position[0]-e.keypoints[r].position[0])]:[0,0];if(i[0]>i[1]||l[0]>l[1]){let c=e.keypoints[n];e.keypoints[n]=e.keypoints[r],e.keypoints[r]=c}}}function H3(e){for(let t=0;t<e.length;t++)if(e[t]&&h0.keypoints[t]){let o=[Math.abs(e[t].positionRaw[0]-h0.keypoints[t].positionRaw[0]),Math.abs(e[t].positionRaw[1]-h0.keypoints[t].positionRaw[1])];o[0]<B3&&o[1]<B3?e[t]=h0.keypoints[t]:h0.keypoints[t]=e[t]}else h0.keypoints[t]=e[t];return e}function V3(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;h0.padding=[[0,0],[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0],[0,0]],o.pad=A.pad(e,h0.padding),o.resize=A.image.resizeBilinear(o.pad,[t,t]);let n=A.cast(o.resize,"int32");return Object.keys(o).forEach(r=>A.dispose(o[r])),n}function D3(e,t){e.keypoints=e.keypoints.filter(n=>n&&n.position);for(let n of e.keypoints)n.position=[n.position[0]*(t[0]+h0.padding[2][0]+h0.padding[2][1])/t[0]-h0.padding[2][0],n.position[1]*(t[1]+h0.padding[1][0]+h0.padding[1][1])/t[1]-h0.padding[1][0]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1]];let o=G0(e.keypoints.map(n=>n.position),t);return e.box=o.box,e.boxRaw=o.boxRaw,e}var b0,G2=0,n1=Number.MAX_SAFE_INTEGER,ue={boxes:[],bodies:[],last:0};async function Z3(e){return T.initial&&(b0=null),b0?e.debug&&u("cached model:",b0.modelUrl):(O2(["size"],e),b0=await L(e.body.modelPath)),G2=b0.inputs[0].shape?b0.inputs[0].shape[2]:0,G2<64&&(G2=256),b0}async function Vr(e,t,o){let n=e[0][0],r=[],s=0;for(let d=0;d<n.length;d++)if(s=n[d][2],s>t.body.minConfidence){let y=[n[d][1],n[d][0]];r.push({score:Math.round(100*s)/100,part:W2[d],positionRaw:y,position:[Math.round((o.shape[2]||0)*y[0]),Math.round((o.shape[1]||0)*y[1])]})}s=r.reduce((d,y)=>y.score>d?y.score:d,0);let a=[],i=G0(r.map(d=>d.position),[o.shape[2],o.shape[1]]),l={};for(let[d,y]of Object.entries(F2)){let x=[];for(let m=0;m<y.length-1;m++){let h=r.find(R=>R.part===y[m]),p=r.find(R=>R.part===y[m+1]);h&&p&&h.score>(t.body.minConfidence||0)&&p.score>(t.body.minConfidence||0)&&x.push([h.position,p.position])}l[d]=x}let c={id:0,score:s,box:i.box,boxRaw:i.boxRaw,keypoints:r,annotations:l};return o1(c),a.push(c),a}async function Dr(e,t,o){let n=[];for(let r=0;r<e[0].length;r++){let s=e[0][r],a=Math.round(100*s[51+4])/100;if(a>t.body.minConfidence){let i=[];for(let y=0;y<17;y++){let x=s[3*y+2];if(x>t.body.minConfidence){let m=[s[3*y+1],s[3*y+0]];i.push({part:W2[y],score:Math.round(100*x)/100,positionRaw:m,position:[Math.round((o.shape[2]||0)*m[0]),Math.round((o.shape[1]||0)*m[1])]})}}let l=G0(i.map(y=>y.position),[o.shape[2],o.shape[1]]),c={};for(let[y,x]of Object.entries(F2)){let m=[];for(let h=0;h<x.length-1;h++){let p=i.find(M=>M.part===x[h]),R=i.find(M=>M.part===x[h+1]);p&&R&&p.score>(t.body.minConfidence||0)&&R.score>(t.body.minConfidence||0)&&m.push([p.position,R.position])}c[y]=m}let d={id:r,score:a,box:l.box,boxRaw:l.boxRaw,keypoints:[...i],annotations:c};o1(d),n.push(d)}}return n.sort((r,s)=>s.score-r.score),n.length>t.body.maxDetected&&(n.length=t.body.maxDetected),n}async function r1(e,t){if(!b0||!(b0!=null&&b0.inputs[0].shape))return[];t.skipAllowed||(ue.boxes.length=0),n1++;let o=(t.body.skipTime||0)>b()-ue.last,n=n1<(t.body.skipFrames||0);return t.skipAllowed&&o&&n?ue.bodies:new Promise(async r=>{let s={};n1=0,s.input=V3(e,G2),s.res=b0==null?void 0:b0.execute(s.input),ue.last=b();let a=await s.res.array();ue.bodies=s.res.shape[2]===17?await Vr(a,t,e):await Dr(a,t,e);for(let i of ue.bodies)D3(i,[e.shape[2]||1,e.shape[1]||1]),H3(i.keypoints);Object.keys(s).forEach(i=>A.dispose(s[i])),r(ue.bodies)})}var Ne,B2=[],q3=0,A1=Number.MAX_SAFE_INTEGER,V2=0,H2=2.5;async function U3(e){if(!Ne||T.initial){Ne=await L(e.object.modelPath);let t=Object.values(Ne.modelSignature.inputs);V2=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&u("cached model:",Ne.modelUrl);return Ne}async function Zr(e,t,o){let n=0,r=[];for(let l of[1,2,4])A.tidy(async()=>{let c=l*13,d=A.squeeze(e.find(p=>p.shape[1]===c**2&&(p.shape[2]||0)===we.length)),y=A.squeeze(e.find(p=>p.shape[1]===c**2&&(p.shape[2]||0)<we.length)),m=await y.reshape([-1,4,y.shape[1]/4]).argMax(2).array(),h=await d.array();for(let p=0;p<d.shape[0];p++)for(let R=0;R<d.shape[1];R++){let M=h[p][R];if(M>(o.object.minConfidence||0)&&R!==61){let g=(.5+Math.trunc(p%c))/c,f=(.5+Math.trunc(p/c))/c,P=m[p].map(Z=>Z*(c/l/V2)),[C,k]=[g-H2/l*P[0],f-H2/l*P[1]],[j,I]=[g+H2/l*P[2]-C,f+H2/l*P[3]-k],O=[C,k,j,I];O=O.map(Z=>Math.max(0,Math.min(Z,1)));let F=[O[0]*t[0],O[1]*t[1],O[2]*t[0],O[3]*t[1]],V={id:n++,score:Math.round(100*M)/100,class:R+1,label:we[R].label,box:F.map(Z=>Math.trunc(Z)),boxRaw:O};r.push(V)}}});e.forEach(l=>A.dispose(l));let s=r.map(l=>[l.boxRaw[1],l.boxRaw[0],l.boxRaw[3],l.boxRaw[2]]),a=r.map(l=>l.score),i=[];if(s&&s.length>0){let l=await A.image.nonMaxSuppressionAsync(s,a,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence);i=await l.data(),A.dispose(l)}return r=r.filter((l,c)=>i.includes(c)).sort((l,c)=>c.score-l.score),r}async function s1(e,t){let o=(t.object.skipTime||0)>b()-q3,n=A1<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&B2.length>0?(A1++,B2):(A1=0,!T.kernels.includes("mod")||!T.kernels.includes("sparsetodense")?B2:new Promise(async r=>{let s=[e.shape[2]||0,e.shape[1]||0],a=A.image.resizeBilinear(e,[V2,V2],!1),i=A.div(a,G.tf255),l=i.transpose([0,3,1,2]);A.dispose(i),A.dispose(a);let c;t.object.enabled&&(c=Ne.execute(l)),q3=b(),A.dispose(l);let d=await Zr(c,s,t);B2=d,r(d)}))}var n2=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],Xr=n2.length,o2=n2.reduce((e,t,o)=>(e[t]=o,e),{}),qr=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],h4=qr.map(([e,t])=>[o2[e],o2[t]]),K3=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function J3(e){let t=e.reduce(({maxX:o,maxY:n,minX:r,minY:s},{position:{x:a,y:i}})=>({maxX:Math.max(o,a),maxY:Math.max(n,i),minX:Math.min(r,a),minY:Math.min(s,i)}),{maxX:Number.NEGATIVE_INFINITY,maxY:Number.NEGATIVE_INFINITY,minX:Number.POSITIVE_INFINITY,minY:Number.POSITIVE_INFINITY});return[t.minX,t.minY,t.maxX-t.minX,t.maxY-t.minY]}function Q3(e,[t,o],[n,r]){let s=t/n,a=o/r,i=(c,d)=>({id:d,score:c.score,boxRaw:[c.box[0]/r,c.box[1]/n,c.box[2]/r,c.box[3]/n],box:[Math.trunc(c.box[0]*a),Math.trunc(c.box[1]*s),Math.trunc(c.box[2]*a),Math.trunc(c.box[3]*s)],keypoints:c.keypoints.map(({score:y,part:x,position:m})=>({score:y,part:x,position:[Math.trunc(m.x*a),Math.trunc(m.y*s)],positionRaw:[m.x/n,m.y/n]})),annotations:{}});return e.map((c,d)=>i(c,d))}var D2=class{constructor(t,o){w(this,"priorityQueue");w(this,"numberOfElements");w(this,"getElementValue");this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=o}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(Math.floor(t/2),t);)this.exchange(t,Math.floor(t/2)),t=Math.floor(t/2)}sink(t){for(;2*t<=this.numberOfElements;){let o=2*t;if(o<this.numberOfElements&&this.less(o,o+1)&&o++,!this.less(t,o))break;this.exchange(t,o),t=o}}getValueAt(t){return this.getElementValue(this.priorityQueue[t])}less(t,o){return this.getValueAt(t)<this.getValueAt(o)}exchange(t,o){let n=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[o],this.priorityQueue[o]=n}};function a1(e,t,o,n){return{y:n.get(e,t,o),x:n.get(e,t,o+Xr)}}function i1(e,t,o){let{heatmapY:n,heatmapX:r,id:s}=e,{y:a,x:i}=a1(n,r,s,o);return{x:e.heatmapX*t+i,y:e.heatmapY*t+a}}function l1(e,t,o){return e<t?t:e>o?o:e}function _3(e,t,o,n){let r=o-e,s=n-t;return r*r+s*s}function y1(e,t){return{x:e.x+t.x,y:e.y+t.y}}var C0,Yr=["MobilenetV1/offset_2/BiasAdd","MobilenetV1/heatmap_2/BiasAdd","MobilenetV1/displacement_fwd_2/BiasAdd","MobilenetV1/displacement_bwd_2/BiasAdd"],Z2=1,Oe=16,Kr=50**2;function $3(e,t,o,n,r,s,a=2){let i=M=>({y:s.get(M.y,M.x,e),x:s.get(M.y,M.x,s.shape[2]/2+e)}),l=(M,g,f)=>({y:l1(Math.round(M.y/Oe),0,g-1),x:l1(Math.round(M.x/Oe),0,f-1)}),[c,d]=n.shape,y=l(t.position,c,d),x=i(y),h=y1(t.position,x);for(let M=0;M<a;M++){let g=l(h,c,d),f=a1(g.y,g.x,o,r);h=y1({x:g.x*Oe,y:g.y*Oe},{x:f.x,y:f.y})}let p=l(h,c,d),R=n.get(p.y,p.x,o);return{position:h,part:n2[o],score:R}}function Jr(e,t,o,n,r){let s=K3.map(([x,m])=>[o2[x],o2[m]]),a=s.map(([,x])=>x),i=s.map(([x])=>x),l=t.shape[2],c=a.length,d=new Array(l),y=i1(e.part,Oe,o);d[e.part.id]={score:e.score,part:n2[e.part.id],position:y};for(let x=c-1;x>=0;--x){let m=a[x],h=i[x];d[m]&&!d[h]&&(d[h]=$3(x,d[m],h,t,o,r))}for(let x=0;x<c;++x){let m=i[x],h=a[x];d[m]&&!d[h]&&(d[h]=$3(x,d[m],h,t,o,n))}return d}function Qr(e,t,o,n,r){let[s,a]=r.shape,i=!0,l=Math.max(o-Z2,0),c=Math.min(o+Z2+1,s);for(let d=l;d<c;++d){let y=Math.max(n-Z2,0),x=Math.min(n+Z2+1,a);for(let m=y;m<x;++m)if(r.get(d,m,e)>t){i=!1;break}if(!i)break}return i}function _r(e,t){let[o,n,r]=t.shape,s=new D2(o*n*r,({score:a})=>a);for(let a=0;a<o;++a)for(let i=0;i<n;++i)for(let l=0;l<r;++l){let c=t.get(a,i,l);c<e||Qr(l,c,a,i,t)&&s.enqueue({score:c,part:{heatmapY:a,heatmapX:i,id:l}})}return s}function eo(e,{x:t,y:o},n){return e.some(({keypoints:r})=>{var a;let s=(a=r[n])==null?void 0:a.position;return s?_3(o,t,s.y,s.x)<=Kr:!1})}function $r(e,t){return t.reduce((n,{position:r,score:s},a)=>(eo(e,r,a)||(n+=s),n),0)/t.length}function eA(e,t,o,n,r,s){let a=[],i=_r(s,t);for(;a.length<r&&!i.empty();){let l=i.dequeue(),c=i1(l.part,Oe,e);if(eo(a,c,l.part.id))continue;let d=Jr(l,t,e,o,n);d=d.filter(m=>m.score>s);let y=$r(a,d),x=J3(d);y>s&&a.push({keypoints:d,box:x,score:Math.round(100*y)/100})}return a}async function x1(e,t){let o=A.tidy(()=>{if(!C0.inputs[0].shape)return[];let a=A.image.resizeBilinear(e,[C0.inputs[0].shape[2],C0.inputs[0].shape[1]]),i=A.sub(A.div(A.cast(a,"float32"),127.5),1),c=C0.execute(i,Yr).map(d=>A.squeeze(d,[0]));return c[1]=A.sigmoid(c[1]),c}),n=await Promise.all(o.map(a=>a.buffer()));for(let a of o)A.dispose(a);let r=await eA(n[0],n[1],n[2],n[3],t.body.maxDetected,t.body.minConfidence);return C0.inputs[0].shape?Q3(r,[e.shape[1],e.shape[2]],[C0.inputs[0].shape[2],C0.inputs[0].shape[1]]):[]}async function to(e){return!C0||T.initial?C0=await L(e.body.modelPath):e.debug&&u("cached model:",C0.modelUrl),C0}var N0,c1=!1;async function d1(e){return!N0||T.initial?N0=await L(e.segmentation.modelPath):e.debug&&u("cached model:",N0.modelUrl),N0}async function no(e,t,o){var p,R;if(c1)return{data:[],canvas:null,alpha:null};c1=!0,N0||await d1(o);let n=await Pe(e,o),r=((p=n.tensor)==null?void 0:p.shape[2])||0,s=((R=n.tensor)==null?void 0:R.shape[1])||0;if(!n.tensor)return{data:[],canvas:null,alpha:null};let a={};a.resize=A.image.resizeBilinear(n.tensor,[N0.inputs[0].shape?N0.inputs[0].shape[1]:0,N0.inputs[0].shape?N0.inputs[0].shape[2]:0],!1),A.dispose(n.tensor),a.norm=A.div(a.resize,G.tf255),a.res=N0.execute(a.norm),a.squeeze=A.squeeze(a.res,0),a.squeeze.shape[2]===2?(a.softmax=A.softmax(a.squeeze),[a.bg,a.fg]=A.unstack(a.softmax,2),a.expand=A.expandDims(a.fg,2),a.pad=A.expandDims(a.expand,0),a.crop=A.image.cropAndResize(a.pad,[[0,0,.5,.5]],[0],[r,s]),a.data=A.squeeze(a.crop,0)):a.data=A.image.resizeBilinear(a.squeeze,[s,r]);let i=Array.from(await a.data.data());if(T.node&&!T.Canvas&&typeof ImageData=="undefined")return o.debug&&u("canvas support missing"),Object.keys(a).forEach(M=>A.dispose(a[M])),{data:i,canvas:null,alpha:null};let l=y0(r,s);A.browser&&await A.browser.toPixels(a.data,l);let c=l.getContext("2d");o.segmentation.blur&&o.segmentation.blur>0&&(c.filter=`blur(${o.segmentation.blur}px)`);let d=c.getImageData(0,0,r,s),y=y0(r,s),x=y.getContext("2d");n.canvas&&x.drawImage(n.canvas,0,0),x.globalCompositeOperation="darken",o.segmentation.blur&&o.segmentation.blur>0&&(x.filter=`blur(${o.segmentation.blur}px)`),x.drawImage(l,0,0),x.globalCompositeOperation="source-over",x.filter="none";let m=x.getImageData(0,0,r,s);for(let M=0;M<r*s;M++)m.data[4*M+3]=d.data[4*M+0];x.putImageData(m,0,0);let h=null;if(t&&y){h=y0(r,s);let M=await Pe(t,o);A.dispose(M.tensor);let g=h.getContext("2d");g.drawImage(M.canvas,0,0,h.width,h.height),g.drawImage(y,0,0)}return Object.keys(a).forEach(M=>A.dispose(a[M])),c1=!1,{data:i,canvas:y,alpha:l}}var r2=class{constructor(){w(this,"ssrnetage",null);w(this,"gear",null);w(this,"blazeposedetect",null);w(this,"blazepose",null);w(this,"centernet",null);w(this,"efficientpose",null);w(this,"mobilefacenet",null);w(this,"emotion",null);w(this,"facedetect",null);w(this,"faceiris",null);w(this,"facemesh",null);w(this,"faceres",null);w(this,"ssrnetgender",null);w(this,"handpose",null);w(this,"handskeleton",null);w(this,"handtrack",null);w(this,"liveness",null);w(this,"movenet",null);w(this,"nanodet",null);w(this,"posenet",null);w(this,"segmentation",null);w(this,"antispoof",null)}},f1=e=>{let t=0,o=0,n=0;for(let s of Object.values(k0))t+=s.sizeFromManifest,o+=s.sizeLoadedWeights,n+=s.sizeDesired;let r=n>0?o/n:0;return{numLoadedModels:Object.values(k0).length,numEnabledModels:void 0,numDefinedModels:Object.keys(e.models).length,percentageLoaded:r,totalSizeFromManifest:t,totalSizeWeights:o,totalSizeLoading:n,totalSizeEnabled:void 0,modelStats:Object.values(k0)}};function X2(e){for(let t of Object.keys(e.models))e.models[t]=null}async function m1(e){var t,o,n,r,s,a,i,l,c,d,y,x,m,h,p,R,M,g,f,P,C,k,j,I,O,F,V,Z,t0,z,g0;T.initial&&X2(e),e.config.hand.enabled&&(!e.models.handpose&&((o=(t=e.config.hand.detector)==null?void 0:t.modelPath)==null?void 0:o.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await U5(e.config)),!e.models.handskeleton&&e.config.hand.landmarks&&((r=(n=e.config.hand.detector)==null?void 0:n.modelPath)==null?void 0:r.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await U5(e.config))),e.config.body.enabled&&!e.models.blazepose&&((a=(s=e.config.body)==null?void 0:s.modelPath)==null?void 0:a.includes("blazepose"))&&(e.models.blazepose=St(e.config)),e.config.body.enabled&&!e.models.blazeposedetect&&e.config.body.detector&&e.config.body.detector.modelPath&&(e.models.blazeposedetect=zt(e.config)),e.config.body.enabled&&!e.models.efficientpose&&((l=(i=e.config.body)==null?void 0:i.modelPath)==null?void 0:l.includes("efficientpose"))&&(e.models.efficientpose=Lt(e.config)),e.config.body.enabled&&!e.models.movenet&&((d=(c=e.config.body)==null?void 0:c.modelPath)==null?void 0:d.includes("movenet"))&&(e.models.movenet=Z3(e.config)),e.config.body.enabled&&!e.models.posenet&&((x=(y=e.config.body)==null?void 0:y.modelPath)==null?void 0:x.includes("posenet"))&&(e.models.posenet=to(e.config)),e.config.face.enabled&&!e.models.facedetect&&(e.models.facedetect=gt(e.config)),e.config.face.enabled&&((m=e.config.face.antispoof)==null?void 0:m.enabled)&&!e.models.antispoof&&(e.models.antispoof=at(e.config)),e.config.face.enabled&&((h=e.config.face.liveness)==null?void 0:h.enabled)&&!e.models.liveness&&(e.models.liveness=F3(e.config)),e.config.face.enabled&&((p=e.config.face.description)==null?void 0:p.enabled)&&!e.models.faceres&&(e.models.faceres=a3(e.config)),e.config.face.enabled&&((R=e.config.face.emotion)==null?void 0:R.enabled)&&!e.models.emotion&&(e.models.emotion=Bt(e.config)),e.config.face.enabled&&((M=e.config.face.iris)==null?void 0:M.enabled)&&!((g=e.config.face.attention)!=null&&g.enabled)&&!e.models.faceiris&&(e.models.faceiris=Jt(e.config)),e.config.face.enabled&&((f=e.config.face.mesh)==null?void 0:f.enabled)&&!e.models.facemesh&&(e.models.facemesh=o3(e.config)),e.config.face.enabled&&((P=e.config.face.gear)==null?void 0:P.enabled)&&!e.models.gear&&(e.models.gear=Y1(e.config)),e.config.face.enabled&&((C=e.config.face.ssrnet)==null?void 0:C.enabled)&&!e.models.ssrnetage&&(e.models.ssrnetage=$1(e.config)),e.config.face.enabled&&((k=e.config.face.ssrnet)==null?void 0:k.enabled)&&!e.models.ssrnetgender&&(e.models.ssrnetgender=nt(e.config)),e.config.face.enabled&&((j=e.config.face.mobilefacenet)==null?void 0:j.enabled)&&!e.models.mobilefacenet&&(e.models.mobilefacenet=Xt(e.config)),e.config.hand.enabled&&!e.models.handtrack&&((O=(I=e.config.hand.detector)==null?void 0:I.modelPath)==null?void 0:O.includes("handtrack"))&&(e.models.handtrack=j3(e.config)),e.config.hand.enabled&&e.config.hand.landmarks&&!e.models.handskeleton&&((V=(F=e.config.hand.detector)==null?void 0:F.modelPath)==null?void 0:V.includes("handtrack"))&&(e.models.handskeleton=N3(e.config)),e.config.object.enabled&&!e.models.centernet&&((t0=(Z=e.config.object)==null?void 0:Z.modelPath)==null?void 0:t0.includes("centernet"))&&(e.models.centernet=jt(e.config)),e.config.object.enabled&&!e.models.nanodet&&((g0=(z=e.config.object)==null?void 0:z.modelPath)==null?void 0:g0.includes("nanodet"))&&(e.models.nanodet=U3(e.config)),e.config.segmentation.enabled&&!e.models.segmentation&&(e.models.segmentation=d1(e.config));for await(let M0 of Object.keys(e.models))e.models[M0]&&typeof e.models[M0]!="undefined"&&(e.models[M0]=await e.models[M0])}async function p1(e){let t=["const","placeholder","noop","pad","squeeze","add","sub","mul","div"];for(let o of Object.keys(e.models)){let n=e.models[o];if(!n)continue;let r=[],s=n==null?void 0:n.executor;if(s&&s.graph.nodes)for(let i of Object.values(s.graph.nodes)){let l=i.op.toLowerCase();r.includes(l)||r.push(l)}else!s&&e.config.debug&&u("model signature not determined:",o);let a=[];for(let i of r)!t.includes(i)&&!e.env.kernels.includes(i)&&!e.env.kernels.includes(i.replace("_",""))&&!e.env.kernels.includes(i.replace("native",""))&&!e.env.kernels.includes(i.replace("v2",""))&&a.push(i);e.config.debug&&a.length>0&&u("model validation failed:",o,a)}}var Y={name:"humangl",priority:999,canvas:null,gl:null,extensions:[],webGLattr:{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!1,desynchronized:!0}};function tA(){let e=Y.gl;!e||(Y.extensions=e.getSupportedExtensions())}async function Ao(e){var t;if(e.config.backend==="humangl"&&(Y.name in A.engine().registry&&(!Y.gl||!Y.gl.getParameter(Y.gl.VERSION))&&(u("error: humangl backend invalid context"),X2(e)),!A.findBackend(Y.name))){try{Y.canvas=await y0(100,100)}catch(n){u("error: cannot create canvas:",n);return}try{if(Y.gl=(t=Y.canvas)==null?void 0:t.getContext("webgl2",Y.webGLattr),!Y.gl.getParameter(Y.gl.VERSION).includes("2.0")){u("override: using fallback webgl backend as webgl 2.0 is not detected"),e.config.backend="webgl";return}Y.canvas&&(Y.canvas.addEventListener("webglcontextlost",async r=>{throw u("error: humangl:",r.type),u("possible browser memory leak using webgl or conflict with multiple backend registrations"),e.emit("error"),new Error("backend error: webgl context lost")}),Y.canvas.addEventListener("webglcontextrestored",r=>{u("error: humangl context restored:",r)}),Y.canvas.addEventListener("webglcontextcreationerror",r=>{u("error: humangl context create:",r)}))}catch(n){u("error: cannot get WebGL context:",n);return}try{A.setWebGLContext(2,Y.gl)}catch(n){u("error: cannot set WebGL context:",n);return}try{let n=new A.GPGPUContext(Y.gl);A.registerBackend(Y.name,()=>new A.MathBackendWebGL(n),Y.priority)}catch(n){u("error: cannot register WebGL backend:",n);return}try{A.getKernelsForBackend("webgl").forEach(r=>{let s={...r,backendName:Y.name};A.registerKernel(s)})}catch(n){u("error: cannot update WebGL backend registration:",n);return}let o=A.backend().getGPGPUContext?A.backend().getGPGPUContext().gl:null;if(o)u(`humangl webgl version:${o.getParameter(o.VERSION)} renderer:${o.getParameter(o.RENDERER)}`);else{u("error: no current gl context:",o,Y.gl);return}try{A.env().flagRegistry.WEBGL_VERSION&&A.env().set("WEBGL_VERSION",2)}catch(n){u("error: cannot set WebGL backend flags:",n);return}tA(),u("backend registered:",Y.name)}}function oA(){if(!T.kernels.includes("mod")){let e={kernelName:"Mod",backendName:A.getBackend(),kernelFunc:t=>A.tidy(()=>A.sub(t.inputs.a,A.mul(A.div(t.inputs.a,t.inputs.b),t.inputs.b)))};A.registerKernel(e),T.kernels.push("mod")}if(!T.kernels.includes("floormod")){let e={kernelName:"FloorMod",backendName:A.getBackend(),kernelFunc:t=>A.tidy(()=>A.floorDiv(t.inputs.a/t.inputs.b)*t.inputs.b+A.mod(t.inputs.a,t.inputs.b))};A.registerKernel(e),T.kernels.push("floormod")}}async function q2(e,t=!1){if(e.state="backend",t||T.initial||e.config.backend&&e.config.backend.length>0&&A.getBackend()!==e.config.backend){let o=b();if(e.config.backend&&e.config.backend.length>0){if(typeof window=="undefined"&&typeof WorkerGlobalScope!="undefined"&&e.config.debug&&e.config.debug&&u("running inside web worker"),T.browser&&e.config.backend==="tensorflow"&&(e.config.debug&&u("override: backend set to tensorflow while running in browser"),e.config.backend="humangl"),T.node&&(e.config.backend==="webgl"||e.config.backend==="humangl")&&(e.config.debug&&u(`override: backend set to ${e.config.backend} while running in nodejs`),e.config.backend="tensorflow"),T.browser&&e.config.backend==="webgpu")if(typeof navigator=="undefined"||typeof navigator.gpu=="undefined")u("override: backend set to webgpu but browser does not support webgpu"),e.config.backend="humangl";else{let r=await navigator.gpu.requestAdapter();if(e.config.debug&&u("enumerated webgpu adapter:",r),!r)u("override: backend set to webgpu but browser reports no available gpu"),e.config.backend="humangl";else{let s="requestAdapterInfo"in r?await r.requestAdapterInfo():void 0;u("webgpu adapter info:",s)}}e.config.backend==="humangl"&&await Ao(e);let n=Object.keys(A.engine().registryFactory);if(e.config.debug&&u("available backends:",n),n.includes(e.config.backend)||(u(`error: backend ${e.config.backend} not found in registry`),e.config.backend=T.node?"tensorflow":"webgl",e.config.debug&&u(`override: setting backend ${e.config.backend}`)),e.config.debug&&u("setting backend:",e.config.backend),e.config.backend==="wasm"){if(A.env().flagRegistry.CANVAS2D_WILL_READ_FREQUENTLY&&A.env().set("CANVAS2D_WILL_READ_FREQUENTLY",!0),e.config.debug&&u("wasm path:",e.config.wasmPath),typeof(A==null?void 0:A.setWasmPaths)!="undefined")await A.setWasmPaths(e.config.wasmPath,e.config.wasmPlatformFetch);else throw new Error("backend error: attempting to use wasm backend but wasm path is not set");let r=await A.env().getAsync("WASM_HAS_SIMD_SUPPORT"),s=await A.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");e.config.debug&&u(`wasm execution: ${r?"SIMD":"no SIMD"} ${s?"multithreaded":"singlethreaded"}`),e.config.debug&&!r&&u("warning: wasm simd support is not enabled")}try{await A.setBackend(e.config.backend),await A.ready(),J1()}catch(r){return u("error: cannot set backend:",e.config.backend,r),!1}}if(A.getBackend()==="humangl"&&(A.env().flagRegistry.CHECK_COMPUTATION_FOR_ERRORS&&A.env().set("CHECK_COMPUTATION_FOR_ERRORS",!1),A.env().flagRegistry.WEBGL_CPU_FORWARD&&A.env().set("WEBGL_CPU_FORWARD",!0),A.env().flagRegistry.WEBGL_USE_SHAPES_UNIFORMS&&A.env().set("WEBGL_USE_SHAPES_UNIFORMS",!0),A.env().flagRegistry.CPU_HANDOFF_SIZE_THRESHOLD&&A.env().set("CPU_HANDOFF_SIZE_THRESHOLD",256),A.env().flagRegistry.WEBGL_EXP_CONV&&A.env().set("WEBGL_EXP_CONV",!0),A.env().flagRegistry.USE_SETTIMEOUTWPM&&A.env().set("USE_SETTIMEOUTWPM",!0),typeof e.config.deallocate!="undefined"&&e.config.deallocate&&(u("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),A.env().set("WEBGL_DELETE_TEXTURE_THRESHOLD",0)),A.backend().getGPGPUContext)){let n=await A.backend().getGPGPUContext().gl;e.config.debug&&u(`gl version:${n.getParameter(n.VERSION)} renderer:${n.getParameter(n.RENDERER)}`)}A.getBackend(),A.enableProdMode(),await A.ready(),e.performance.initBackend=Math.trunc(b()-o),e.config.backend=A.getBackend(),await T.updateBackend(),oA()}return!0}function O2(e,t){for(let o of e){let n={kernelName:o,backendName:t.backend,kernelFunc:()=>{t.debug&&u("kernelFunc",o,t.backend)}};A.registerKernel(n)}T.kernels=A.getKernelsForBackend(A.getBackend()).map(o=>o.kernelName.toLowerCase())}var io={};U0(io,{all:()=>R1,body:()=>We,canvas:()=>P1,face:()=>Le,gesture:()=>Be,hand:()=>Fe,object:()=>Ge,options:()=>l0,person:()=>M1});var R0=e=>{if(!e)u("draw error: invalid canvas");else if(!e.getContext)u("draw error: canvas context not defined");else{let t=e.getContext("2d");if(!t)u("draw error: cannot get canvas context");else return t}return null},he=e=>Math.round(e*180/Math.PI),X0=(e,t)=>{if(!t.useDepth||typeof e=="undefined")return t.color;let o=Uint8ClampedArray.from([127+2*e,127-2*e,255]);return`rgba(${o[0]}, ${o[1]}, ${o[2]}, ${t.alpha})`};function q0(e,t,o,n,r){e.fillStyle=X0(n,r),e.beginPath(),e.arc(t,o,r.pointSize,0,2*Math.PI),e.fill()}function O0(e,t,o,n,r,s){if(e.beginPath(),e.lineWidth=s.lineWidth,s.useCurves){let a=(t+t+n)/2,i=(o+o+r)/2;e.ellipse(a,i,n/2,r/2,0,0,2*Math.PI)}else e.moveTo(t+s.roundRect,o),e.lineTo(t+n-s.roundRect,o),e.quadraticCurveTo(t+n,o,t+n,o+s.roundRect),e.lineTo(t+n,o+r-s.roundRect),e.quadraticCurveTo(t+n,o+r,t+n-s.roundRect,o+r),e.lineTo(t+s.roundRect,o+r),e.quadraticCurveTo(t,o+r,t,o+r-s.roundRect),e.lineTo(t,o+s.roundRect),e.quadraticCurveTo(t,o,t+s.roundRect,o),e.closePath();e.stroke()}function h1(e,t,o){if(!(t.length<2)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let n of t)e.strokeStyle=X0(n[2]||0,o),e.lineTo(Math.trunc(n[0]),Math.trunc(n[1]));e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function ao(e,t,o){if(!(t.length<2)){if(e.lineWidth=o.lineWidth,!o.useCurves||t.length<=2){h1(e,t,o);return}e.moveTo(t[0][0],t[0][1]);for(let n=0;n<t.length-2;n++){let r=(t[n][0]+t[n+1][0])/2,s=(t[n][1]+t[n+1][1])/2;e.quadraticCurveTo(t[n][0],t[n][1],r,s)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function b1(e,t,o,n=5){let r,s,a;e.beginPath(),e.moveTo(t[0],t[1]),e.lineTo(o[0],o[1]),r=Math.atan2(o[1]-t[1],o[0]-t[0]),s=n*Math.cos(r)+o[0],a=n*Math.sin(r)+o[1],e.moveTo(s,a),r+=1/3*(2*Math.PI),s=n*Math.cos(r)+o[0],a=n*Math.sin(r)+o[1],e.lineTo(s,a),r+=1/3*(2*Math.PI),s=n*Math.cos(r)+o[0],a=n*Math.sin(r)+o[1],e.lineTo(s,a),e.closePath(),e.stroke(),e.fill()}var l0={color:"rgba(173, 216, 230, 0.6)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",alpha:.5,font:'small-caps 16px "Segoe UI"',lineHeight:18,lineWidth:4,pointSize:2,roundRect:8,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawAttention:!0,drawGestures:!0,drawPolygons:!0,drawGaze:!0,fillPolygons:!1,useDepth:!0,useCurves:!1};var H;function rA(e,t){if(H.drawLabels){let o=[];if(o.push(`face: ${Math.trunc(100*e.score)}%`),e.genderScore&&o.push(`${e.gender||""} ${Math.trunc(100*e.genderScore)}%`),e.age&&o.push(`age: ${e.age||""}`),e.iris&&o.push(`distance: ${e.iris}`),e.real&&o.push(`real: ${Math.trunc(100*e.real)}%`),e.live&&o.push(`live: ${Math.trunc(100*e.live)}%`),e.emotion&&e.emotion.length>0){let n=e.emotion.map(r=>`${Math.trunc(100*r.score)}% ${r.emotion}`);n.length>3&&(n.length=3),o.push(n.join(" "))}e.rotation&&e.rotation.angle&&e.rotation.gaze&&(e.rotation.angle.roll&&o.push(`roll: ${he(e.rotation.angle.roll)}\xB0 yaw:${he(e.rotation.angle.yaw)}\xB0 pitch:${he(e.rotation.angle.pitch)}\xB0`),e.rotation.gaze.bearing&&o.push(`gaze: ${he(e.rotation.gaze.bearing)}\xB0`)),o.length===0&&o.push("face"),t.fillStyle=H.color;for(let n=o.length-1;n>=0;n--){let r=Math.max(e.box[0],0),s=n*H.lineHeight+e.box[1];H.shadowColor&&H.shadowColor!==""&&(t.fillStyle=H.shadowColor,t.fillText(o[n],r+5,s+16)),t.fillStyle=H.labelColor,t.fillText(o[n],r+4,s+15)}}}function AA(e,t){if(e.annotations&&e.annotations.leftEyeIris&&e.annotations.leftEyeIris[0]){t.strokeStyle=H.useDepth?"rgba(255, 200, 255, 0.3)":H.color,t.beginPath();let o=Math.abs(e.annotations.leftEyeIris[3][0]-e.annotations.leftEyeIris[1][0])/2,n=Math.abs(e.annotations.leftEyeIris[4][1]-e.annotations.leftEyeIris[2][1])/2;t.ellipse(e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),H.fillPolygons&&(t.fillStyle=H.useDepth?"rgba(255, 255, 200, 0.3)":H.color,t.fill())}if(e.annotations&&e.annotations.rightEyeIris&&e.annotations.rightEyeIris[0]){t.strokeStyle=H.useDepth?"rgba(255, 200, 255, 0.3)":H.color,t.beginPath();let o=Math.abs(e.annotations.rightEyeIris[3][0]-e.annotations.rightEyeIris[1][0])/2,n=Math.abs(e.annotations.rightEyeIris[4][1]-e.annotations.rightEyeIris[2][1])/2;t.ellipse(e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),H.fillPolygons&&(t.fillStyle=H.useDepth?"rgba(255, 255, 200, 0.3)":H.color,t.fill())}}function sA(e,t){var o;if(H.drawGaze&&((o=e.rotation)==null?void 0:o.angle)&&typeof Path2D!="undefined"){t.strokeStyle="pink";let n=e.box[0]+e.box[2]/2-e.box[3]*he(e.rotation.angle.yaw)/90,r=e.box[1]+e.box[3]/2+e.box[2]*he(e.rotation.angle.pitch)/90,s=new Path2D(`
       M ${e.box[0]+e.box[2]/2} ${e.box[1]}
       C
         ${n} ${e.box[1]},
@@ -108,7 +108,7 @@ var J2=Object.defineProperty;var Po=Object.getOwnPropertyDescriptor;var Ro=Objec
         ${e.box[0]} ${r},
         ${e.box[0]+e.box[2]} ${r},
         ${e.box[0]+e.box[2]} ${e.box[1]+e.box[3]/2}
-    `);t.stroke(a),t.stroke(s)}}function aA(e,t){var o,n,r,s;if(H.drawGaze&&((n=(o=e.rotation)==null?void 0:o.gaze)==null?void 0:n.strength)&&((s=(r=e.rotation)==null?void 0:r.gaze)==null?void 0:s.bearing)&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let a=[e.annotations.leftEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.leftEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];b1(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[a[0],a[1]],4);let i=[e.annotations.rightEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.rightEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];b1(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[i[0],i[1]],4)}}function iA(e,t){if(H.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let o=0;o<ie.length/3;o++){let n=[ie[o*3+0],ie[o*3+1],ie[o*3+2]].map(r=>e.mesh[r]);h1(t,n,H)}AA(e,t)}}function lA(e,t){if(H.drawPoints&&e.mesh.length>=468)for(let o=0;o<e.mesh.length;o++)q0(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2],H),H.drawAttention&&($e.includes(o)&&q0(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]+127,H),xe.includes(o)&&q0(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,H),ce.includes(o)&&q0(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,H))}function yA(e,t){H.drawBoxes&&O0(t,e.box[0],e.box[1],e.box[2],e.box[3],H)}async function Le(e,t,o){if(H=J(l0,o),!t||!e)return;let n=R0(e);if(!!n){n.font=H.font,n.strokeStyle=H.color,n.fillStyle=H.color;for(let r of t)yA(r,n),rA(r,n),r.mesh&&r.mesh.length>0&&(lA(r,n),iA(r,n),sA(r,n),aA(r,n))}}async function We(e,t,o){var s;let n=J(l0,o);if(!t||!e)return;let r=R0(e);if(!!r){r.lineJoin="round";for(let a=0;a<t.length;a++){if(r.strokeStyle=n.color,r.fillStyle=n.color,r.lineWidth=n.lineWidth,r.font=n.font,n.drawBoxes&&t[a].box&&((s=t[a].box)==null?void 0:s.length)===4&&(O0(r,t[a].box[0],t[a].box[1],t[a].box[2],t[a].box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`body ${100*t[a].score}%`,t[a].box[0]+3,1+t[a].box[1]+n.lineHeight,t[a].box[2])),r.fillStyle=n.labelColor,r.fillText(`body ${100*t[a].score}%`,t[a].box[0]+2,0+t[a].box[1]+n.lineHeight,t[a].box[2]))),n.drawPoints&&t[a].keypoints)for(let i=0;i<t[a].keypoints.length;i++)!t[a].keypoints[i].score||t[a].keypoints[i].score===0||(r.fillStyle=X0(t[a].keypoints[i].position[2],n),q0(r,t[a].keypoints[i].position[0],t[a].keypoints[i].position[1],0,n));if(n.drawLabels&&t[a].keypoints){r.font=n.font;for(let i of t[a].keypoints)!i.score||i.score===0||(r.fillStyle=X0(i.position[2],n),r.fillText(`${i.part} ${Math.trunc(100*i.score)}%`,i.position[0]+4,i.position[1]+4))}if(n.drawPolygons&&t[a].keypoints&&t[a].annotations)for(let i of Object.values(t[a].annotations))for(let l of i)ao(r,l,n)}}}async function Fe(e,t,o){let n=J(l0,o);if(!t||!e)return;let r=R0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let s of t){if(n.drawBoxes&&(r.strokeStyle=n.color,r.fillStyle=n.color,O0(r,s.box[0],s.box[1],s.box[2],s.box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`hand:${Math.trunc(100*s.score)}%`,s.box[0]+3,1+s.box[1]+n.lineHeight,s.box[2])),r.fillStyle=n.labelColor,r.fillText(`hand:${Math.trunc(100*s.score)}%`,s.box[0]+2,0+s.box[1]+n.lineHeight,s.box[2])),r.stroke()),n.drawPoints&&s.keypoints&&s.keypoints.length>0)for(let a of s.keypoints)r.fillStyle=X0(a[2],n),q0(r,a[0],a[1],0,n);if(n.drawLabels&&s.annotations){let a=(i,l)=>{if(!i||i.length===0||!i[0])return;let c=i[i.length-1][2]||-256;r.fillStyle=X0(c,n),r.fillText(l,i[i.length-1][0]+4,i[i.length-1][1]+4)};r.font=n.font,a(s.annotations.index,"index"),a(s.annotations.middle,"middle"),a(s.annotations.ring,"ring"),a(s.annotations.pinky,"pinky"),a(s.annotations.thumb,"thumb"),a(s.annotations.palm,"palm")}if(n.drawPolygons&&s.annotations){let a=i=>{if(!(!i||i.length===0||!i[0]))for(let l=0;l<i.length;l++){r.beginPath();let c=i[l][2]||0;r.strokeStyle=X0(l*c,n),r.moveTo(i[l>0?l-1:0][0],i[l>0?l-1:0][1]),r.lineTo(i[l][0],i[l][1]),r.stroke()}};r.lineWidth=n.lineWidth,a(s.annotations.index),a(s.annotations.middle),a(s.annotations.ring),a(s.annotations.pinky),a(s.annotations.thumb)}}}}async function Ge(e,t,o){let n=J(l0,o);if(!t||!e)return;let r=R0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let s of t)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,O0(r,s.box[0],s.box[1],s.box[2],s.box[3],n),n.drawLabels){let a=`${s.label} ${Math.round(100*s.score)}%`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(a,s.box[0]+3,1+s.box[1]+n.lineHeight,s.box[2])),r.fillStyle=n.labelColor,r.fillText(a,s.box[0]+2,0+s.box[1]+n.lineHeight,s.box[2])}r.stroke()}}}async function Be(e,t,o){let n=J(l0,o);if(!(!t||!e)&&n.drawGestures){let r=R0(e);if(!r)return;r.font=n.font,r.fillStyle=n.color;let s=1;for(let a=0;a<t.length;a++){let i=[],l=[];if([i,l]=Object.entries(t[a]),l.length>1&&l[1].length>0){let c=i[1]>0?`#${i[1]}`:"",d=`${i[0]} ${c}: ${l[1]}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(d,8,2+s*n.lineHeight)),r.fillStyle=n.labelColor,r.fillText(d,6,0+s*n.lineHeight),s+=1}}}}var g1=0;async function M1(e,t,o){let n=J(l0,o);if(!t||!e)return;let r=R0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let s=0;s<t.length;s++)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,O0(r,t[s].box[0],t[s].box[1],t[s].box[2],t[s].box[3],n),n.drawLabels){let a=`person #${s}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(a,t[s].box[0]+3,1+t[s].box[1]+n.lineHeight,t[s].box[2])),r.fillStyle=n.labelColor,r.fillText(a,t[s].box[0]+2,0+t[s].box[1]+n.lineHeight,t[s].box[2])}r.stroke()}}}async function P1(e,t){if(!e||!t)return;let o=R0(t);!o||o.drawImage(e,0,0)}async function R1(e,t,o){if(!t||!t.performance||!t||!e)return null;let n=b(),r=J(l0,o),s=Promise.all([Le(e,t.face,r),We(e,t.body,r),Fe(e,t.hand,r),Ge(e,t.object,r),Be(e,t.gesture,r)]);return g1=T.perfadd?g1+Math.round(b()-n):Math.round(b()-n),t.performance.draw=g1,s}var He=.1,v1=.5;function xA(e,t,o){let n=!1,r=o.length-1;for(let s=0;s<o.length;r=s++)o[s].y>t!=o[r].y>t&&e<(o[r].x-o[s].x)*(t-o[s].y)/(o[r].y-o[s].y)+o[s].x&&(n=!n);return n}async function lo(e){if(!e.tensor||!e.mesh||e.mesh.length<100)return e.tensor;let t=e.tensor.shape[2]||0,o=e.tensor.shape[1]||0,n=await e.tensor.buffer(),r=[];for(let a of w0.silhouette)r.push({x:(e.mesh[a][0]-e.box[0])/e.box[2],y:(e.mesh[a][1]-e.box[1])/e.box[3]});He&&He>0&&(r=r.map(a=>({x:a.x>.5?a.x+He:a.x-He,y:a.y>.5?a.y+He:a.y-He})));for(let a=0;a<t;a++)for(let i=0;i<o;i++)xA(a/t,i/t,r)||(n.set(v1*n.get(0,i,a,0),0,i,a,0),n.set(v1*n.get(0,i,a,1),0,i,a,1),n.set(v1*n.get(0,i,a,2),0,i,a,2));let s=n.toTensor();return A.dispose(n),s}var dA=e=>{let t=(y,x)=>Math.atan2(y[1]-x[1],y[0]-x[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let o=[0,-.1],n=1,r=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),s=r?e.mesh[473]:e.mesh[468],a=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],i=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],l=[(a[0]-s[0])/i[0]-o[0],n*(s[1]-a[1])/i[1]-o[1]],c=Math.sqrt(l[0]*l[0]+l[1]*l[1]);return c=Math.min(c,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],l)+Math.PI/2)%Math.PI,strength:c}},yo=(e,t)=>{let o=p=>{let R=Math.sqrt(p[0]*p[0]+p[1]*p[1]+p[2]*p[2]);return p[0]/=R,p[1]/=R,p[2]/=R,p},n=(p,R)=>{let M=p[0]-R[0],g=p[1]-R[1],f=p[2]-R[2];return[M,g,f]},r=(p,R)=>{let M=p[1]*R[2]-p[2]*R[1],g=p[2]*R[0]-p[0]*R[2],f=p[0]*R[1]-p[1]*R[0];return[M,g,f]},s=p=>{let[R,M,g,f,P,C,k,I,j]=p,O,F,V;return f<1?f>-1?(V=Math.asin(f),F=Math.atan2(-k,R),O=Math.atan2(-C,P)):(V=-Math.PI/2,F=-Math.atan2(I,j),O=0):(V=Math.PI/2,F=Math.atan2(I,j),O=0),isNaN(O)&&(O=0),isNaN(F)&&(F=0),isNaN(V)&&(V=0),{pitch:2*-O,yaw:2*-F,roll:2*-V}},a=e.meshRaw;if(!a||a.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let i=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,l=[a[10],a[152],a[234],a[454]].map(p=>[p[0]*t[0]/i,p[1]*t[1]/i,p[2]]),c=o(n(l[1],l[0])),d=o(n(l[3],l[2])),y=o(r(d,c));d=r(c,y);let x=[d[0],d[1],d[2],c[0],c[1],c[2],y[0],y[1],y[2]],m=s(x),h=a.length===478?dA(e):{bearing:0,strength:0};return{angle:m,matrix:x,gaze:h}};var T1=async(e,t)=>{var m,h,p,R,M,g,f,P,C,k,I,j,O,F,V,Z,t0,z,g0,M0,v,o0;let o=b(),n,r,s,a,i,l,c,d,y=[];e.state="run:face";let x=await t3(t,e.config);if(e.performance.face=T.perfadd?(e.performance.face||0)+Math.trunc(b()-o):Math.trunc(b()-o),!t.shape||t.shape.length!==4)return[];if(!x)return[];for(let E=0;E<x.length;E++){if(e.analyze("Get Face"),!x[E].tensor||x[E].tensor.isDisposedInternal){u("Face object is disposed:",x[E].tensor);continue}if((m=e.config.face.detector)!=null&&m.mask){let D=await lo(x[E]);A.dispose(x[E].tensor),x[E].tensor=D}let X=x[E].mesh&&x[E].mesh.length>200?yo(x[E],[t.shape[2],t.shape[1]]):null;e.analyze("Start Emotion:"),e.config.async?a=(h=e.config.face.emotion)!=null&&h.enabled?j5(x[E].tensor||A.tensor([]),e.config,E,x.length):[]:(e.state="run:emotion",o=b(),a=(p=e.config.face.emotion)!=null&&p.enabled?await j5(x[E].tensor||A.tensor([]),e.config,E,x.length):[],e.performance.emotion=T.perfadd?(e.performance.emotion||0)+Math.trunc(b()-o):Math.trunc(b()-o)),e.analyze("End Emotion:"),e.analyze("Start AntiSpoof:"),e.config.async?l=(R=e.config.face.antispoof)!=null&&R.enabled?d5(x[E].tensor||A.tensor([]),e.config,E,x.length):0:(e.state="run:antispoof",o=b(),l=(M=e.config.face.antispoof)!=null&&M.enabled?await d5(x[E].tensor||A.tensor([]),e.config,E,x.length):0,e.performance.antispoof=T.perfadd?(e.performance.antispoof||0)+Math.trunc(b()-o):Math.trunc(b()-o)),e.analyze("End AntiSpoof:"),e.analyze("Start Liveness:"),e.config.async?c=(g=e.config.face.liveness)!=null&&g.enabled?_5(x[E].tensor||A.tensor([]),e.config,E,x.length):0:(e.state="run:liveness",o=b(),c=(f=e.config.face.liveness)!=null&&f.enabled?await _5(x[E].tensor||A.tensor([]),e.config,E,x.length):0,e.performance.liveness=T.perfadd?(e.performance.antispoof||0)+Math.trunc(b()-o):Math.trunc(b()-o)),e.analyze("End Liveness:"),e.analyze("Start GEAR:"),e.config.async?r=(P=e.config.face.gear)!=null&&P.enabled?s5(x[E].tensor||A.tensor([]),e.config,E,x.length):null:(e.state="run:gear",o=b(),r=(C=e.config.face.gear)!=null&&C.enabled?await s5(x[E].tensor||A.tensor([]),e.config,E,x.length):null,e.performance.gear=Math.trunc(b()-o)),e.analyze("End GEAR:"),e.analyze("Start SSRNet:"),e.config.async?(n=(k=e.config.face.ssrnet)!=null&&k.enabled?i5(x[E].tensor||A.tensor([]),e.config,E,x.length):null,s=(I=e.config.face.ssrnet)!=null&&I.enabled?x5(x[E].tensor||A.tensor([]),e.config,E,x.length):null):(e.state="run:ssrnet",o=b(),n=(j=e.config.face.ssrnet)!=null&&j.enabled?await i5(x[E].tensor||A.tensor([]),e.config,E,x.length):null,s=(O=e.config.face.ssrnet)!=null&&O.enabled?await x5(x[E].tensor||A.tensor([]),e.config,E,x.length):null,e.performance.ssrnet=Math.trunc(b()-o)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?i=(F=e.config.face.mobilefacenet)!=null&&F.enabled?N5(x[E].tensor||A.tensor([]),e.config,E,x.length):null:(e.state="run:mobilefacenet",o=b(),i=(V=e.config.face.mobilefacenet)!=null&&V.enabled?await N5(x[E].tensor||A.tensor([]),e.config,E,x.length):null,e.performance.mobilefacenet=Math.trunc(b()-o)),e.analyze("End MobileFaceNet:"),e.analyze("Start Description:"),e.config.async?d=(Z=e.config.face.description)!=null&&Z.enabled?B5(x[E].tensor||A.tensor([]),e.config,E,x.length):null:(e.state="run:description",o=b(),d=(t0=e.config.face.description)!=null&&t0.enabled?await B5(x[E].tensor||A.tensor([]),e.config,E,x.length):null,e.performance.description=T.perfadd?(e.performance.description||0)+Math.trunc(b()-o):Math.trunc(b()-o)),e.analyze("End Description:"),e.config.async&&([n,s,a,i,d,r,l,c]=await Promise.all([n,s,a,i,d,r,l,c])),e.analyze("Finish Face:"),((z=e.config.face.ssrnet)==null?void 0:z.enabled)&&n&&s&&(d={...d,age:n.age,gender:s.gender,genderScore:s.genderScore}),((g0=e.config.face.gear)==null?void 0:g0.enabled)&&r&&(d={...d,age:r.age,gender:r.gender,genderScore:r.genderScore,race:r.race}),((M0=e.config.face.mobilefacenet)==null?void 0:M0.enabled)&&i&&(d.descriptor=i),(v=e.config.face.iris)!=null&&v.enabled;let _=x[E].annotations&&x[E].annotations.leftEyeIris&&x[E].annotations.leftEyeIris[0]&&x[E].annotations.rightEyeIris&&x[E].annotations.rightEyeIris[0]&&x[E].annotations.leftEyeIris.length>0&&x[E].annotations.rightEyeIris.length>0&&x[E].annotations.leftEyeIris[0]!==null&&x[E].annotations.rightEyeIris[0]!==null?Math.max(Math.abs(x[E].annotations.leftEyeIris[3][0]-x[E].annotations.leftEyeIris[1][0]),Math.abs(x[E].annotations.rightEyeIris[4][1]-x[E].annotations.rightEyeIris[2][1]))/t.shape[2]:0,r0=(o0=e.config.face.detector)!=null&&o0.return?A.squeeze(x[E].tensor):null;A.dispose(x[E].tensor),x[E].tensor&&delete x[E].tensor;let N={...x[E],id:E};d!=null&&d.age&&(N.age=d.age),d!=null&&d.gender&&(N.gender=d.gender),d!=null&&d.genderScore&&(N.genderScore=d==null?void 0:d.genderScore),d!=null&&d.descriptor&&(N.embedding=d==null?void 0:d.descriptor),d!=null&&d.race&&(N.race=d==null?void 0:d.race),a&&(N.emotion=a),l&&(N.real=l),c&&(N.live=c),_&&_!==0&&(N.iris=Math.trunc(500/_/11.7)/100),X&&(N.rotation=X),r0&&(N.tensor=r0),y.push(N),e.analyze("End Face")}return e.analyze("End FaceMesh:"),e.config.async&&(e.performance.face&&delete e.performance.face,e.performance.age&&delete e.performance.age,e.performance.gender&&delete e.performance.gender,e.performance.emotion&&delete e.performance.emotion),y};var xo=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=e[o].keypoints.find(l=>l.part==="leftWrist"),r=e[o].keypoints.find(l=>l.part==="rightWrist"),s=e[o].keypoints.find(l=>l.part==="nose");s&&n&&r&&n.position[1]<s.position[1]&&r.position[1]<s.position[1]?t.push({body:o,gesture:"i give up"}):s&&n&&n.position[1]<s.position[1]?t.push({body:o,gesture:"raise left hand"}):s&&r&&r.position[1]<s.position[1]&&t.push({body:o,gesture:"raise right hand"});let a=e[o].keypoints.find(l=>l.part==="leftShoulder"),i=e[o].keypoints.find(l=>l.part==="rightShoulder");a&&i&&Math.abs(a.positionRaw[1]-i.positionRaw[1])>.1&&t.push({body:o,gesture:`leaning ${a.position[1]>i.position[1]?"left":"right"}`})}return t},co=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++)if(e[o].mesh&&e[o].mesh.length>450){let n=(e[o].mesh[33][2]||0)-(e[o].mesh[263][2]||0),r=e[o].mesh[33][0]-e[o].mesh[263][0];Math.abs(n/r)<=.15?t.push({face:o,gesture:"facing center"}):t.push({face:o,gesture:`facing ${n<0?"left":"right"}`}),Math.abs(e[o].mesh[374][1]-e[o].mesh[386][1])/Math.abs(e[o].mesh[443][1]-e[o].mesh[450][1])<.2&&t.push({face:o,gesture:"blink left eye"}),Math.abs(e[o].mesh[145][1]-e[o].mesh[159][1])/Math.abs(e[o].mesh[223][1]-e[o].mesh[230][1])<.2&&t.push({face:o,gesture:"blink right eye"});let i=Math.min(100,500*Math.abs(e[o].mesh[13][1]-e[o].mesh[14][1])/Math.abs(e[o].mesh[10][1]-e[o].mesh[152][1]));i>10&&t.push({face:o,gesture:`mouth ${Math.trunc(i)}% open`});let l=e[o].mesh[152][2]||0;Math.abs(l)>10&&t.push({face:o,gesture:`head ${l<0?"up":"down"}`})}return t},fo=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){if(!e[o].annotations||!e[o].annotations.leftEyeIris||!e[o].annotations.leftEyeIris[0]||!e[o].annotations.rightEyeIris||!e[o].annotations.rightEyeIris[0])continue;let n=e[o].annotations.leftEyeIris[3][0]-e[o].annotations.leftEyeIris[1][0],r=e[o].annotations.leftEyeIris[4][1]-e[o].annotations.leftEyeIris[2][1],s=Math.abs(n*r),a=e[o].annotations.rightEyeIris[3][0]-e[o].annotations.rightEyeIris[1][0],i=e[o].annotations.rightEyeIris[4][1]-e[o].annotations.rightEyeIris[2][1],l=Math.abs(a*i),c=!1;Math.abs(s-l)/Math.max(s,l)<.25&&(c=!0,t.push({iris:o,gesture:"facing center"}));let y=Math.abs(e[o].mesh[263][0]-e[o].annotations.leftEyeIris[0][0])/e[o].box[2],x=Math.abs(e[o].mesh[33][0]-e[o].annotations.rightEyeIris[0][0])/e[o].box[2];(y>.06||x>.06)&&(c=!1),y>x?y>.05&&t.push({iris:o,gesture:"looking right"}):x>.05&&t.push({iris:o,gesture:"looking left"});let m=Math.abs(e[o].mesh[145][1]-e[o].annotations.rightEyeIris[0][1])/e[o].box[3],h=Math.abs(e[o].mesh[374][1]-e[o].annotations.leftEyeIris[0][1])/e[o].box[3];(h<.01||m<.01||h>.022||m>.022)&&(c=!1),(h<.01||m<.01)&&t.push({iris:o,gesture:"looking down"}),(h>.022||m>.022)&&t.push({iris:o,gesture:"looking up"}),c&&t.push({iris:o,gesture:"looking center"})}return t},mo=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=[];if(e[o].annotations)for(let[r,s]of Object.entries(e[o].annotations))r!=="palmBase"&&Array.isArray(s)&&s[0]&&n.push({name:r.toLowerCase(),position:s[0]});if(n&&n.length>0){let r=n.reduce((a,i)=>(a.position[2]||0)<(i.position[2]||0)?a:i);t.push({hand:o,gesture:`${r.name} forward`});let s=n.reduce((a,i)=>a.position[1]<i.position[1]?a:i);t.push({hand:o,gesture:`${s.name} up`})}if(e[o].keypoints){let r=w3(e[o].keypoints);for(let s of r)t.push({hand:o,gesture:s.name})}}return t};var S={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null},w1=0;function po(e,t){var a,i,l,c,d,y,x,m,h,p,R,M,g,f,P,C,k,I,j,O,F,V,Z,t0,z,g0,M0;let o=b();if(!e)return{face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null};let n=Date.now()-e.timestamp,r=n<1e3?8-Math.log(n+1):1;if(e.canvas&&(S.canvas=e.canvas),e.error&&(S.error=e.error),!S.body||e.body.length!==S.body.length)S.body=JSON.parse(JSON.stringify(e.body));else for(let v=0;v<e.body.length;v++){let o0=e.body[v].box.map((N,D)=>((r-1)*S.body[v].box[D]+N)/r),E=e.body[v].boxRaw.map((N,D)=>((r-1)*S.body[v].boxRaw[D]+N)/r),X=e.body[v].keypoints.map((N,D)=>{var L0,W0,De,Ze,be,z1,S1,C1,j1;return{score:N.score,part:N.part,position:[S.body[v].keypoints[D]?((r-1)*(S.body[v].keypoints[D].position[0]||0)+(N.position[0]||0))/r:N.position[0],S.body[v].keypoints[D]?((r-1)*(S.body[v].keypoints[D].position[1]||0)+(N.position[1]||0))/r:N.position[1],S.body[v].keypoints[D]?((r-1)*(S.body[v].keypoints[D].position[2]||0)+(N.position[2]||0))/r:N.position[2]],positionRaw:[S.body[v].keypoints[D]?((r-1)*(S.body[v].keypoints[D].positionRaw[0]||0)+(N.positionRaw[0]||0))/r:N.positionRaw[0],S.body[v].keypoints[D]?((r-1)*(S.body[v].keypoints[D].positionRaw[1]||0)+(N.positionRaw[1]||0))/r:N.positionRaw[1],S.body[v].keypoints[D]?((r-1)*(S.body[v].keypoints[D].positionRaw[2]||0)+(N.positionRaw[2]||0))/r:N.positionRaw[2]],distance:[S.body[v].keypoints[D]?((r-1)*(((L0=S.body[v].keypoints[D].distance)==null?void 0:L0[0])||0)+(((W0=N.distance)==null?void 0:W0[0])||0))/r:(De=N.distance)==null?void 0:De[0],S.body[v].keypoints[D]?((r-1)*(((Ze=S.body[v].keypoints[D].distance)==null?void 0:Ze[1])||0)+(((be=N.distance)==null?void 0:be[1])||0))/r:(z1=N.distance)==null?void 0:z1[1],S.body[v].keypoints[D]?((r-1)*(((S1=S.body[v].keypoints[D].distance)==null?void 0:S1[2])||0)+(((C1=N.distance)==null?void 0:C1[2])||0))/r:(j1=N.distance)==null?void 0:j1[2]]}}),_={},r0={connected:{}};(i=(a=t.body)==null?void 0:a.modelPath)!=null&&i.includes("efficientpose")?r0=v2:(c=(l=t.body)==null?void 0:l.modelPath)!=null&&c.includes("blazepose")?r0=b2:(y=(d=t.body)==null?void 0:d.modelPath)!=null&&y.includes("movenet")&&(r0=t2);for(let[N,D]of Object.entries(r0.connected)){let L0=[];for(let W0=0;W0<D.length-1;W0++){let De=X.find(be=>be.part===D[W0]),Ze=X.find(be=>be.part===D[W0+1]);De&&Ze&&L0.push([De.position,Ze.position])}_[N]=L0}S.body[v]={...e.body[v],box:o0,boxRaw:E,keypoints:X,annotations:_}}if(!S.hand||e.hand.length!==S.hand.length)S.hand=JSON.parse(JSON.stringify(e.hand));else for(let v=0;v<e.hand.length;v++){let o0=e.hand[v].box.map((r0,N)=>((r-1)*S.hand[v].box[N]+r0)/r),E=e.hand[v].boxRaw.map((r0,N)=>((r-1)*S.hand[v].boxRaw[N]+r0)/r);S.hand[v].keypoints.length!==e.hand[v].keypoints.length&&(S.hand[v].keypoints=e.hand[v].keypoints);let X=e.hand[v].keypoints&&e.hand[v].keypoints.length>0?e.hand[v].keypoints.map((r0,N)=>r0.map((D,L0)=>((r-1)*(S.hand[v].keypoints[N][L0]||1)+(D||0))/r)):[],_={};if(Object.keys(S.hand[v].annotations).length!==Object.keys(e.hand[v].annotations).length)S.hand[v].annotations=e.hand[v].annotations,_=S.hand[v].annotations;else if(e.hand[v].annotations)for(let r0 of Object.keys(e.hand[v].annotations))_[r0]=e.hand[v].annotations[r0]&&e.hand[v].annotations[r0][0]?e.hand[v].annotations[r0].map((N,D)=>N.map((L0,W0)=>((r-1)*S.hand[v].annotations[r0][D][W0]+L0)/r)):null;S.hand[v]={...e.hand[v],box:o0,boxRaw:E,keypoints:X,annotations:_}}if(!S.face||e.face.length!==S.face.length)S.face=JSON.parse(JSON.stringify(e.face));else for(let v=0;v<e.face.length;v++){let o0=e.face[v].box.map((X,_)=>((r-1)*S.face[v].box[_]+X)/r),E=e.face[v].boxRaw.map((X,_)=>((r-1)*S.face[v].boxRaw[_]+X)/r);if(e.face[v].rotation){let X={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};X.matrix=(x=e.face[v].rotation)==null?void 0:x.matrix,X.angle={roll:((r-1)*(((h=(m=S.face[v].rotation)==null?void 0:m.angle)==null?void 0:h.roll)||0)+(((R=(p=e.face[v].rotation)==null?void 0:p.angle)==null?void 0:R.roll)||0))/r,yaw:((r-1)*(((g=(M=S.face[v].rotation)==null?void 0:M.angle)==null?void 0:g.yaw)||0)+(((P=(f=e.face[v].rotation)==null?void 0:f.angle)==null?void 0:P.yaw)||0))/r,pitch:((r-1)*(((k=(C=S.face[v].rotation)==null?void 0:C.angle)==null?void 0:k.pitch)||0)+(((j=(I=e.face[v].rotation)==null?void 0:I.angle)==null?void 0:j.pitch)||0))/r},X.gaze={bearing:((r-1)*(((F=(O=S.face[v].rotation)==null?void 0:O.gaze)==null?void 0:F.bearing)||0)+(((Z=(V=e.face[v].rotation)==null?void 0:V.gaze)==null?void 0:Z.bearing)||0))/r,strength:((r-1)*(((z=(t0=S.face[v].rotation)==null?void 0:t0.gaze)==null?void 0:z.strength)||0)+(((M0=(g0=e.face[v].rotation)==null?void 0:g0.gaze)==null?void 0:M0.strength)||0))/r},S.face[v]={...e.face[v],rotation:X,box:o0,boxRaw:E}}S.face[v]={...e.face[v],box:o0,boxRaw:E}}if(!S.object||e.object.length!==S.object.length)S.object=JSON.parse(JSON.stringify(e.object));else for(let v=0;v<e.object.length;v++){let o0=e.object[v].box.map((X,_)=>((r-1)*S.object[v].box[_]+X)/r),E=e.object[v].boxRaw.map((X,_)=>((r-1)*S.object[v].boxRaw[_]+X)/r);S.object[v]={...e.object[v],box:o0,boxRaw:E}}if(e.persons){let v=e.persons;if(!S.persons||v.length!==S.persons.length)S.persons=JSON.parse(JSON.stringify(v));else for(let o0=0;o0<v.length;o0++)S.persons[o0].box=v[o0].box.map((E,X)=>((r-1)*S.persons[o0].box[X]+E)/r)}e.gesture&&(S.gesture=e.gesture);let s=b();return w1=T.perfadd?w1+Math.round(s-o):Math.round(s-o),e.performance&&(S.performance={...e.performance,interpolate:w1}),S}var ho={};U0(ho,{distance:()=>A2,match:()=>E1,similarity:()=>k1});function A2(e,t,o={order:2,multiplier:25}){let n=0;for(let r=0;r<e.length;r++){let s=!o.order||o.order===2?e[r]-t[r]:Math.abs(e[r]-t[r]);n+=!o.order||o.order===2?s*s:s**o.order}return(o.multiplier||20)*n}var uo=(e,t,o,n)=>{if(e===0)return 1;let r=t===2?Math.sqrt(e):e**(1/t),s=(1-r/100-o)/(n-o);return Math.max(Math.min(s,1),0)};function k1(e,t,o={order:2,multiplier:25,min:.2,max:.8}){let n=A2(e,t,o);return uo(n,o.order||2,o.min||0,o.max||1)}function E1(e,t,o={order:2,multiplier:25,threshold:0,min:.2,max:.8}){if(!Array.isArray(e)||!Array.isArray(t)||e.length<64||t.length===0||e.length!==t[0].length)return{index:-1,distance:Number.POSITIVE_INFINITY,similarity:0};let n=Number.MAX_SAFE_INTEGER,r=-1;for(let a=0;a<t.length;a++){let i=A2(e,t[a],o);if(i<n&&(n=i,r=a),n<(o.threshold||0))break}let s=uo(n,o.order||2,o.min||0,o.max||1);return{index:r,distance:n,similarity:s}}function bo(e,t,o,n,r){var i,l,c,d,y,x,m,h,p,R,M,g,f,P,C,k;let s=0,a=[];for(let I of e){let j={id:s++,face:I,body:null,hands:{left:null,right:null},gestures:[],box:[0,0,0,0]};for(let z of t)I.box[0]>z.box[0]&&I.box[0]<z.box[0]+z.box[2]&&I.box[1]+I.box[3]>z.box[1]&&I.box[1]+I.box[3]<z.box[1]+z.box[3]&&(j.body=z);if(j.body)for(let z of o)z.box[0]+z.box[2]>j.body.box[0]&&z.box[0]+z.box[2]<j.body.box[0]+j.body.box[2]&&z.box[1]+z.box[3]>j.body.box[1]&&z.box[1]+z.box[3]<j.body.box[1]+j.body.box[3]&&j.hands&&(j.hands.left=z),z.box[0]<j.body.box[0]+j.body.box[2]&&z.box[0]>j.body.box[0]&&z.box[1]+z.box[3]>j.body.box[1]&&z.box[1]+z.box[3]<j.body.box[1]+j.body.box[3]&&j.hands&&(j.hands.right=z);for(let z of n)z.face!==void 0&&z.face===I.id?(i=j.gestures)==null||i.push(z):z.iris!==void 0&&z.iris===I.id?(l=j.gestures)==null||l.push(z):z.body!==void 0&&z.body===((c=j.body)==null?void 0:c.id)?(d=j.gestures)==null||d.push(z):z.hand!==void 0&&z.hand===((x=(y=j.hands)==null?void 0:y.left)==null?void 0:x.id)?(m=j.gestures)==null||m.push(z):z.hand!==void 0&&z.hand===((p=(h=j.hands)==null?void 0:h.right)==null?void 0:p.id)&&((R=j.gestures)==null||R.push(z));let O=[],F=[],V=z=>{z&&z.length===4&&(O.push(z[0],z[0]+z[2]),F.push(z[1],z[1]+z[3]))};V((M=j.face)==null?void 0:M.box),V((g=j.body)==null?void 0:g.box),V((P=(f=j.hands)==null?void 0:f.left)==null?void 0:P.box),V((k=(C=j.hands)==null?void 0:C.right)==null?void 0:k.box);let Z=Math.min(...O),t0=Math.min(...F);j.box=[Z,t0,Math.max(...O)-Z,Math.max(...F)-t0],r&&r[1]&&r[2]&&(j.boxRaw=[j.box[0]/r[2],j.box[1]/r[1],j.box[2]/r[2],j.box[3]/r[1]]),a.push(j)}return a}var U2=`
+    `);t.stroke(a),t.stroke(s)}}function aA(e,t){var o,n,r,s;if(H.drawGaze&&((n=(o=e.rotation)==null?void 0:o.gaze)==null?void 0:n.strength)&&((s=(r=e.rotation)==null?void 0:r.gaze)==null?void 0:s.bearing)&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let a=[e.annotations.leftEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.leftEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];b1(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[a[0],a[1]],4);let i=[e.annotations.rightEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.rightEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];b1(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[i[0],i[1]],4)}}function iA(e,t){if(H.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let o=0;o<ie.length/3;o++){let n=[ie[o*3+0],ie[o*3+1],ie[o*3+2]].map(r=>e.mesh[r]);h1(t,n,H)}AA(e,t)}}function lA(e,t){if(H.drawPoints&&e.mesh.length>=468)for(let o=0;o<e.mesh.length;o++)q0(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2],H),H.drawAttention&&($e.includes(o)&&q0(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]+127,H),xe.includes(o)&&q0(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,H),ce.includes(o)&&q0(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,H))}function yA(e,t){H.drawBoxes&&O0(t,e.box[0],e.box[1],e.box[2],e.box[3],H)}async function Le(e,t,o){if(H=J(l0,o),!t||!e)return;let n=R0(e);if(!!n){n.font=H.font,n.strokeStyle=H.color,n.fillStyle=H.color;for(let r of t)yA(r,n),rA(r,n),r.mesh&&r.mesh.length>0&&(lA(r,n),iA(r,n),sA(r,n),aA(r,n))}}async function We(e,t,o){var s;let n=J(l0,o);if(!t||!e)return;let r=R0(e);if(!!r){r.lineJoin="round";for(let a=0;a<t.length;a++){if(r.strokeStyle=n.color,r.fillStyle=n.color,r.lineWidth=n.lineWidth,r.font=n.font,n.drawBoxes&&t[a].box&&((s=t[a].box)==null?void 0:s.length)===4&&(O0(r,t[a].box[0],t[a].box[1],t[a].box[2],t[a].box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`body ${100*t[a].score}%`,t[a].box[0]+3,1+t[a].box[1]+n.lineHeight,t[a].box[2])),r.fillStyle=n.labelColor,r.fillText(`body ${100*t[a].score}%`,t[a].box[0]+2,0+t[a].box[1]+n.lineHeight,t[a].box[2]))),n.drawPoints&&t[a].keypoints)for(let i=0;i<t[a].keypoints.length;i++)!t[a].keypoints[i].score||t[a].keypoints[i].score===0||(r.fillStyle=X0(t[a].keypoints[i].position[2],n),q0(r,t[a].keypoints[i].position[0],t[a].keypoints[i].position[1],0,n));if(n.drawLabels&&t[a].keypoints){r.font=n.font;for(let i of t[a].keypoints)!i.score||i.score===0||(r.fillStyle=X0(i.position[2],n),r.fillText(`${i.part} ${Math.trunc(100*i.score)}%`,i.position[0]+4,i.position[1]+4))}if(n.drawPolygons&&t[a].keypoints&&t[a].annotations)for(let i of Object.values(t[a].annotations))for(let l of i)ao(r,l,n)}}}async function Fe(e,t,o){let n=J(l0,o);if(!t||!e)return;let r=R0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let s of t){if(n.drawBoxes&&(r.strokeStyle=n.color,r.fillStyle=n.color,O0(r,s.box[0],s.box[1],s.box[2],s.box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`hand:${Math.trunc(100*s.score)}%`,s.box[0]+3,1+s.box[1]+n.lineHeight,s.box[2])),r.fillStyle=n.labelColor,r.fillText(`hand:${Math.trunc(100*s.score)}%`,s.box[0]+2,0+s.box[1]+n.lineHeight,s.box[2])),r.stroke()),n.drawPoints&&s.keypoints&&s.keypoints.length>0)for(let a of s.keypoints)r.fillStyle=X0(a[2],n),q0(r,a[0],a[1],0,n);if(n.drawLabels&&s.annotations){let a=(i,l)=>{if(!i||i.length===0||!i[0])return;let c=i[i.length-1][2]||-256;r.fillStyle=X0(c,n),r.fillText(l,i[i.length-1][0]+4,i[i.length-1][1]+4)};r.font=n.font,a(s.annotations.index,"index"),a(s.annotations.middle,"middle"),a(s.annotations.ring,"ring"),a(s.annotations.pinky,"pinky"),a(s.annotations.thumb,"thumb"),a(s.annotations.palm,"palm")}if(n.drawPolygons&&s.annotations){let a=i=>{if(!(!i||i.length===0||!i[0]))for(let l=0;l<i.length;l++){r.beginPath();let c=i[l][2]||0;r.strokeStyle=X0(l*c,n),r.moveTo(i[l>0?l-1:0][0],i[l>0?l-1:0][1]),r.lineTo(i[l][0],i[l][1]),r.stroke()}};r.lineWidth=n.lineWidth,a(s.annotations.index),a(s.annotations.middle),a(s.annotations.ring),a(s.annotations.pinky),a(s.annotations.thumb)}}}}async function Ge(e,t,o){let n=J(l0,o);if(!t||!e)return;let r=R0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let s of t)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,O0(r,s.box[0],s.box[1],s.box[2],s.box[3],n),n.drawLabels){let a=`${s.label} ${Math.round(100*s.score)}%`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(a,s.box[0]+3,1+s.box[1]+n.lineHeight,s.box[2])),r.fillStyle=n.labelColor,r.fillText(a,s.box[0]+2,0+s.box[1]+n.lineHeight,s.box[2])}r.stroke()}}}async function Be(e,t,o){let n=J(l0,o);if(!(!t||!e)&&n.drawGestures){let r=R0(e);if(!r)return;r.font=n.font,r.fillStyle=n.color;let s=1;for(let a=0;a<t.length;a++){let i=[],l=[];if([i,l]=Object.entries(t[a]),l.length>1&&l[1].length>0){let c=i[1]>0?`#${i[1]}`:"",d=`${i[0]} ${c}: ${l[1]}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(d,8,2+s*n.lineHeight)),r.fillStyle=n.labelColor,r.fillText(d,6,0+s*n.lineHeight),s+=1}}}}var g1=0;async function M1(e,t,o){let n=J(l0,o);if(!t||!e)return;let r=R0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let s=0;s<t.length;s++)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,O0(r,t[s].box[0],t[s].box[1],t[s].box[2],t[s].box[3],n),n.drawLabels){let a=`person #${s}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(a,t[s].box[0]+3,1+t[s].box[1]+n.lineHeight,t[s].box[2])),r.fillStyle=n.labelColor,r.fillText(a,t[s].box[0]+2,0+t[s].box[1]+n.lineHeight,t[s].box[2])}r.stroke()}}}async function P1(e,t){if(!e||!t)return;let o=R0(t);!o||o.drawImage(e,0,0)}async function R1(e,t,o){if(!t||!t.performance||!t||!e)return null;let n=b(),r=J(l0,o),s=Promise.all([Le(e,t.face,r),We(e,t.body,r),Fe(e,t.hand,r),Ge(e,t.object,r),Be(e,t.gesture,r)]);return g1=T.perfadd?g1+Math.round(b()-n):Math.round(b()-n),t.performance.draw=g1,s}var He=.1,v1=.5;function xA(e,t,o){let n=!1,r=o.length-1;for(let s=0;s<o.length;r=s++)o[s].y>t!=o[r].y>t&&e<(o[r].x-o[s].x)*(t-o[s].y)/(o[r].y-o[s].y)+o[s].x&&(n=!n);return n}async function lo(e){if(!e.tensor||!e.mesh||e.mesh.length<100)return e.tensor;let t=e.tensor.shape[2]||0,o=e.tensor.shape[1]||0,n=await e.tensor.buffer(),r=[];for(let a of w0.silhouette)r.push({x:(e.mesh[a][0]-e.box[0])/e.box[2],y:(e.mesh[a][1]-e.box[1])/e.box[3]});He&&He>0&&(r=r.map(a=>({x:a.x>.5?a.x+He:a.x-He,y:a.y>.5?a.y+He:a.y-He})));for(let a=0;a<t;a++)for(let i=0;i<o;i++)xA(a/t,i/t,r)||(n.set(v1*n.get(0,i,a,0),0,i,a,0),n.set(v1*n.get(0,i,a,1),0,i,a,1),n.set(v1*n.get(0,i,a,2),0,i,a,2));let s=n.toTensor();return A.dispose(n),s}var dA=e=>{let t=(y,x)=>Math.atan2(y[1]-x[1],y[0]-x[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let o=[0,-.1],n=1,r=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),s=r?e.mesh[473]:e.mesh[468],a=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],i=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],l=[(a[0]-s[0])/i[0]-o[0],n*(s[1]-a[1])/i[1]-o[1]],c=Math.sqrt(l[0]*l[0]+l[1]*l[1]);return c=Math.min(c,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],l)+Math.PI/2)%Math.PI,strength:c}},yo=(e,t)=>{let o=p=>{let R=Math.sqrt(p[0]*p[0]+p[1]*p[1]+p[2]*p[2]);return p[0]/=R,p[1]/=R,p[2]/=R,p},n=(p,R)=>{let M=p[0]-R[0],g=p[1]-R[1],f=p[2]-R[2];return[M,g,f]},r=(p,R)=>{let M=p[1]*R[2]-p[2]*R[1],g=p[2]*R[0]-p[0]*R[2],f=p[0]*R[1]-p[1]*R[0];return[M,g,f]},s=p=>{let[R,M,g,f,P,C,k,j,I]=p,O,F,V;return f<1?f>-1?(V=Math.asin(f),F=Math.atan2(-k,R),O=Math.atan2(-C,P)):(V=-Math.PI/2,F=-Math.atan2(j,I),O=0):(V=Math.PI/2,F=Math.atan2(j,I),O=0),isNaN(O)&&(O=0),isNaN(F)&&(F=0),isNaN(V)&&(V=0),{pitch:2*-O,yaw:2*-F,roll:2*-V}},a=e.meshRaw;if(!a||a.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let i=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,l=[a[10],a[152],a[234],a[454]].map(p=>[p[0]*t[0]/i,p[1]*t[1]/i,p[2]]),c=o(n(l[1],l[0])),d=o(n(l[3],l[2])),y=o(r(d,c));d=r(c,y);let x=[d[0],d[1],d[2],c[0],c[1],c[2],y[0],y[1],y[2]],m=s(x),h=a.length===478?dA(e):{bearing:0,strength:0};return{angle:m,matrix:x,gaze:h}};var T1=async(e,t)=>{var m,h,p,R,M,g,f,P,C,k,j,I,O,F,V,Z,t0,z,g0,M0,v,o0;let o=b(),n,r,s,a,i,l,c,d,y=[];e.state="run:face";let x=await t3(t,e.config);if(e.performance.face=T.perfadd?(e.performance.face||0)+Math.trunc(b()-o):Math.trunc(b()-o),!t.shape||t.shape.length!==4)return[];if(!x)return[];for(let E=0;E<x.length;E++){if(e.analyze("Get Face"),!x[E].tensor||x[E].tensor.isDisposedInternal){u("Face object is disposed:",x[E].tensor);continue}if((m=e.config.face.detector)!=null&&m.mask){let D=await lo(x[E]);A.dispose(x[E].tensor),x[E].tensor=D}let X=x[E].mesh&&x[E].mesh.length>200?yo(x[E],[t.shape[2],t.shape[1]]):null;e.analyze("Start Emotion:"),e.config.async?a=(h=e.config.face.emotion)!=null&&h.enabled?I5(x[E].tensor||A.tensor([]),e.config,E,x.length):[]:(e.state="run:emotion",o=b(),a=(p=e.config.face.emotion)!=null&&p.enabled?await I5(x[E].tensor||A.tensor([]),e.config,E,x.length):[],e.performance.emotion=T.perfadd?(e.performance.emotion||0)+Math.trunc(b()-o):Math.trunc(b()-o)),e.analyze("End Emotion:"),e.analyze("Start AntiSpoof:"),e.config.async?l=(R=e.config.face.antispoof)!=null&&R.enabled?d5(x[E].tensor||A.tensor([]),e.config,E,x.length):0:(e.state="run:antispoof",o=b(),l=(M=e.config.face.antispoof)!=null&&M.enabled?await d5(x[E].tensor||A.tensor([]),e.config,E,x.length):0,e.performance.antispoof=T.perfadd?(e.performance.antispoof||0)+Math.trunc(b()-o):Math.trunc(b()-o)),e.analyze("End AntiSpoof:"),e.analyze("Start Liveness:"),e.config.async?c=(g=e.config.face.liveness)!=null&&g.enabled?_5(x[E].tensor||A.tensor([]),e.config,E,x.length):0:(e.state="run:liveness",o=b(),c=(f=e.config.face.liveness)!=null&&f.enabled?await _5(x[E].tensor||A.tensor([]),e.config,E,x.length):0,e.performance.liveness=T.perfadd?(e.performance.antispoof||0)+Math.trunc(b()-o):Math.trunc(b()-o)),e.analyze("End Liveness:"),e.analyze("Start GEAR:"),e.config.async?r=(P=e.config.face.gear)!=null&&P.enabled?s5(x[E].tensor||A.tensor([]),e.config,E,x.length):null:(e.state="run:gear",o=b(),r=(C=e.config.face.gear)!=null&&C.enabled?await s5(x[E].tensor||A.tensor([]),e.config,E,x.length):null,e.performance.gear=Math.trunc(b()-o)),e.analyze("End GEAR:"),e.analyze("Start SSRNet:"),e.config.async?(n=(k=e.config.face.ssrnet)!=null&&k.enabled?i5(x[E].tensor||A.tensor([]),e.config,E,x.length):null,s=(j=e.config.face.ssrnet)!=null&&j.enabled?x5(x[E].tensor||A.tensor([]),e.config,E,x.length):null):(e.state="run:ssrnet",o=b(),n=(I=e.config.face.ssrnet)!=null&&I.enabled?await i5(x[E].tensor||A.tensor([]),e.config,E,x.length):null,s=(O=e.config.face.ssrnet)!=null&&O.enabled?await x5(x[E].tensor||A.tensor([]),e.config,E,x.length):null,e.performance.ssrnet=Math.trunc(b()-o)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?i=(F=e.config.face.mobilefacenet)!=null&&F.enabled?N5(x[E].tensor||A.tensor([]),e.config,E,x.length):null:(e.state="run:mobilefacenet",o=b(),i=(V=e.config.face.mobilefacenet)!=null&&V.enabled?await N5(x[E].tensor||A.tensor([]),e.config,E,x.length):null,e.performance.mobilefacenet=Math.trunc(b()-o)),e.analyze("End MobileFaceNet:"),e.analyze("Start Description:"),e.config.async?d=(Z=e.config.face.description)!=null&&Z.enabled?B5(x[E].tensor||A.tensor([]),e.config,E,x.length):null:(e.state="run:description",o=b(),d=(t0=e.config.face.description)!=null&&t0.enabled?await B5(x[E].tensor||A.tensor([]),e.config,E,x.length):null,e.performance.description=T.perfadd?(e.performance.description||0)+Math.trunc(b()-o):Math.trunc(b()-o)),e.analyze("End Description:"),e.config.async&&([n,s,a,i,d,r,l,c]=await Promise.all([n,s,a,i,d,r,l,c])),e.analyze("Finish Face:"),((z=e.config.face.ssrnet)==null?void 0:z.enabled)&&n&&s&&(d={...d,age:n.age,gender:s.gender,genderScore:s.genderScore}),((g0=e.config.face.gear)==null?void 0:g0.enabled)&&r&&(d={...d,age:r.age,gender:r.gender,genderScore:r.genderScore,race:r.race}),((M0=e.config.face.mobilefacenet)==null?void 0:M0.enabled)&&i&&(d.descriptor=i),(v=e.config.face.iris)!=null&&v.enabled;let _=x[E].annotations&&x[E].annotations.leftEyeIris&&x[E].annotations.leftEyeIris[0]&&x[E].annotations.rightEyeIris&&x[E].annotations.rightEyeIris[0]&&x[E].annotations.leftEyeIris.length>0&&x[E].annotations.rightEyeIris.length>0&&x[E].annotations.leftEyeIris[0]!==null&&x[E].annotations.rightEyeIris[0]!==null?Math.max(Math.abs(x[E].annotations.leftEyeIris[3][0]-x[E].annotations.leftEyeIris[1][0]),Math.abs(x[E].annotations.rightEyeIris[4][1]-x[E].annotations.rightEyeIris[2][1]))/t.shape[2]:0,r0=(o0=e.config.face.detector)!=null&&o0.return?A.squeeze(x[E].tensor):null;A.dispose(x[E].tensor),x[E].tensor&&delete x[E].tensor;let N={...x[E],id:E};d!=null&&d.age&&(N.age=d.age),d!=null&&d.gender&&(N.gender=d.gender),d!=null&&d.genderScore&&(N.genderScore=d==null?void 0:d.genderScore),d!=null&&d.descriptor&&(N.embedding=d==null?void 0:d.descriptor),d!=null&&d.race&&(N.race=d==null?void 0:d.race),a&&(N.emotion=a),l&&(N.real=l),c&&(N.live=c),_&&_!==0&&(N.iris=Math.trunc(500/_/11.7)/100),X&&(N.rotation=X),r0&&(N.tensor=r0),y.push(N),e.analyze("End Face")}return e.analyze("End FaceMesh:"),e.config.async&&(e.performance.face&&delete e.performance.face,e.performance.age&&delete e.performance.age,e.performance.gender&&delete e.performance.gender,e.performance.emotion&&delete e.performance.emotion),y};var xo=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=e[o].keypoints.find(l=>l.part==="leftWrist"),r=e[o].keypoints.find(l=>l.part==="rightWrist"),s=e[o].keypoints.find(l=>l.part==="nose");s&&n&&r&&n.position[1]<s.position[1]&&r.position[1]<s.position[1]?t.push({body:o,gesture:"i give up"}):s&&n&&n.position[1]<s.position[1]?t.push({body:o,gesture:"raise left hand"}):s&&r&&r.position[1]<s.position[1]&&t.push({body:o,gesture:"raise right hand"});let a=e[o].keypoints.find(l=>l.part==="leftShoulder"),i=e[o].keypoints.find(l=>l.part==="rightShoulder");a&&i&&Math.abs(a.positionRaw[1]-i.positionRaw[1])>.1&&t.push({body:o,gesture:`leaning ${a.position[1]>i.position[1]?"left":"right"}`})}return t},co=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++)if(e[o].mesh&&e[o].mesh.length>450){let n=(e[o].mesh[33][2]||0)-(e[o].mesh[263][2]||0),r=e[o].mesh[33][0]-e[o].mesh[263][0];Math.abs(n/r)<=.15?t.push({face:o,gesture:"facing center"}):t.push({face:o,gesture:`facing ${n<0?"left":"right"}`}),Math.abs(e[o].mesh[374][1]-e[o].mesh[386][1])/Math.abs(e[o].mesh[443][1]-e[o].mesh[450][1])<.2&&t.push({face:o,gesture:"blink left eye"}),Math.abs(e[o].mesh[145][1]-e[o].mesh[159][1])/Math.abs(e[o].mesh[223][1]-e[o].mesh[230][1])<.2&&t.push({face:o,gesture:"blink right eye"});let i=Math.min(100,500*Math.abs(e[o].mesh[13][1]-e[o].mesh[14][1])/Math.abs(e[o].mesh[10][1]-e[o].mesh[152][1]));i>10&&t.push({face:o,gesture:`mouth ${Math.trunc(i)}% open`});let l=e[o].mesh[152][2]||0;Math.abs(l)>10&&t.push({face:o,gesture:`head ${l<0?"up":"down"}`})}return t},fo=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){if(!e[o].annotations||!e[o].annotations.leftEyeIris||!e[o].annotations.leftEyeIris[0]||!e[o].annotations.rightEyeIris||!e[o].annotations.rightEyeIris[0])continue;let n=e[o].annotations.leftEyeIris[3][0]-e[o].annotations.leftEyeIris[1][0],r=e[o].annotations.leftEyeIris[4][1]-e[o].annotations.leftEyeIris[2][1],s=Math.abs(n*r),a=e[o].annotations.rightEyeIris[3][0]-e[o].annotations.rightEyeIris[1][0],i=e[o].annotations.rightEyeIris[4][1]-e[o].annotations.rightEyeIris[2][1],l=Math.abs(a*i),c=!1;Math.abs(s-l)/Math.max(s,l)<.25&&(c=!0,t.push({iris:o,gesture:"facing center"}));let y=Math.abs(e[o].mesh[263][0]-e[o].annotations.leftEyeIris[0][0])/e[o].box[2],x=Math.abs(e[o].mesh[33][0]-e[o].annotations.rightEyeIris[0][0])/e[o].box[2];(y>.06||x>.06)&&(c=!1),y>x?y>.05&&t.push({iris:o,gesture:"looking right"}):x>.05&&t.push({iris:o,gesture:"looking left"});let m=Math.abs(e[o].mesh[145][1]-e[o].annotations.rightEyeIris[0][1])/e[o].box[3],h=Math.abs(e[o].mesh[374][1]-e[o].annotations.leftEyeIris[0][1])/e[o].box[3];(h<.01||m<.01||h>.022||m>.022)&&(c=!1),(h<.01||m<.01)&&t.push({iris:o,gesture:"looking down"}),(h>.022||m>.022)&&t.push({iris:o,gesture:"looking up"}),c&&t.push({iris:o,gesture:"looking center"})}return t},mo=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=[];if(e[o].annotations)for(let[r,s]of Object.entries(e[o].annotations))r!=="palmBase"&&Array.isArray(s)&&s[0]&&n.push({name:r.toLowerCase(),position:s[0]});if(n&&n.length>0){let r=n.reduce((a,i)=>(a.position[2]||0)<(i.position[2]||0)?a:i);t.push({hand:o,gesture:`${r.name} forward`});let s=n.reduce((a,i)=>a.position[1]<i.position[1]?a:i);t.push({hand:o,gesture:`${s.name} up`})}if(e[o].keypoints){let r=w3(e[o].keypoints);for(let s of r)t.push({hand:o,gesture:s.name})}}return t};var S={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null},w1=0;function po(e,t){var a,i,l,c,d,y,x,m,h,p,R,M,g,f,P,C,k,j,I,O,F,V,Z,t0,z,g0,M0;let o=b();if(!e)return{face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null};let n=Date.now()-e.timestamp,r=n<1e3?8-Math.log(n+1):1;if(e.canvas&&(S.canvas=e.canvas),e.error&&(S.error=e.error),!S.body||e.body.length!==S.body.length)S.body=JSON.parse(JSON.stringify(e.body));else for(let v=0;v<e.body.length;v++){let o0=e.body[v].box.map((N,D)=>((r-1)*S.body[v].box[D]+N)/r),E=e.body[v].boxRaw.map((N,D)=>((r-1)*S.body[v].boxRaw[D]+N)/r),X=e.body[v].keypoints.map((N,D)=>{var L0,W0,De,Ze,be,z1,S1,C1,I1;return{score:N.score,part:N.part,position:[S.body[v].keypoints[D]?((r-1)*(S.body[v].keypoints[D].position[0]||0)+(N.position[0]||0))/r:N.position[0],S.body[v].keypoints[D]?((r-1)*(S.body[v].keypoints[D].position[1]||0)+(N.position[1]||0))/r:N.position[1],S.body[v].keypoints[D]?((r-1)*(S.body[v].keypoints[D].position[2]||0)+(N.position[2]||0))/r:N.position[2]],positionRaw:[S.body[v].keypoints[D]?((r-1)*(S.body[v].keypoints[D].positionRaw[0]||0)+(N.positionRaw[0]||0))/r:N.positionRaw[0],S.body[v].keypoints[D]?((r-1)*(S.body[v].keypoints[D].positionRaw[1]||0)+(N.positionRaw[1]||0))/r:N.positionRaw[1],S.body[v].keypoints[D]?((r-1)*(S.body[v].keypoints[D].positionRaw[2]||0)+(N.positionRaw[2]||0))/r:N.positionRaw[2]],distance:[S.body[v].keypoints[D]?((r-1)*(((L0=S.body[v].keypoints[D].distance)==null?void 0:L0[0])||0)+(((W0=N.distance)==null?void 0:W0[0])||0))/r:(De=N.distance)==null?void 0:De[0],S.body[v].keypoints[D]?((r-1)*(((Ze=S.body[v].keypoints[D].distance)==null?void 0:Ze[1])||0)+(((be=N.distance)==null?void 0:be[1])||0))/r:(z1=N.distance)==null?void 0:z1[1],S.body[v].keypoints[D]?((r-1)*(((S1=S.body[v].keypoints[D].distance)==null?void 0:S1[2])||0)+(((C1=N.distance)==null?void 0:C1[2])||0))/r:(I1=N.distance)==null?void 0:I1[2]]}}),_={},r0={connected:{}};(i=(a=t.body)==null?void 0:a.modelPath)!=null&&i.includes("efficientpose")?r0=v2:(c=(l=t.body)==null?void 0:l.modelPath)!=null&&c.includes("blazepose")?r0=b2:(y=(d=t.body)==null?void 0:d.modelPath)!=null&&y.includes("movenet")&&(r0=t2);for(let[N,D]of Object.entries(r0.connected)){let L0=[];for(let W0=0;W0<D.length-1;W0++){let De=X.find(be=>be.part===D[W0]),Ze=X.find(be=>be.part===D[W0+1]);De&&Ze&&L0.push([De.position,Ze.position])}_[N]=L0}S.body[v]={...e.body[v],box:o0,boxRaw:E,keypoints:X,annotations:_}}if(!S.hand||e.hand.length!==S.hand.length)S.hand=JSON.parse(JSON.stringify(e.hand));else for(let v=0;v<e.hand.length;v++){let o0=e.hand[v].box.map((r0,N)=>((r-1)*S.hand[v].box[N]+r0)/r),E=e.hand[v].boxRaw.map((r0,N)=>((r-1)*S.hand[v].boxRaw[N]+r0)/r);S.hand[v].keypoints.length!==e.hand[v].keypoints.length&&(S.hand[v].keypoints=e.hand[v].keypoints);let X=e.hand[v].keypoints&&e.hand[v].keypoints.length>0?e.hand[v].keypoints.map((r0,N)=>r0.map((D,L0)=>((r-1)*(S.hand[v].keypoints[N][L0]||1)+(D||0))/r)):[],_={};if(Object.keys(S.hand[v].annotations).length!==Object.keys(e.hand[v].annotations).length)S.hand[v].annotations=e.hand[v].annotations,_=S.hand[v].annotations;else if(e.hand[v].annotations)for(let r0 of Object.keys(e.hand[v].annotations))_[r0]=e.hand[v].annotations[r0]&&e.hand[v].annotations[r0][0]?e.hand[v].annotations[r0].map((N,D)=>N.map((L0,W0)=>((r-1)*S.hand[v].annotations[r0][D][W0]+L0)/r)):null;S.hand[v]={...e.hand[v],box:o0,boxRaw:E,keypoints:X,annotations:_}}if(!S.face||e.face.length!==S.face.length)S.face=JSON.parse(JSON.stringify(e.face));else for(let v=0;v<e.face.length;v++){let o0=e.face[v].box.map((X,_)=>((r-1)*S.face[v].box[_]+X)/r),E=e.face[v].boxRaw.map((X,_)=>((r-1)*S.face[v].boxRaw[_]+X)/r);if(e.face[v].rotation){let X={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};X.matrix=(x=e.face[v].rotation)==null?void 0:x.matrix,X.angle={roll:((r-1)*(((h=(m=S.face[v].rotation)==null?void 0:m.angle)==null?void 0:h.roll)||0)+(((R=(p=e.face[v].rotation)==null?void 0:p.angle)==null?void 0:R.roll)||0))/r,yaw:((r-1)*(((g=(M=S.face[v].rotation)==null?void 0:M.angle)==null?void 0:g.yaw)||0)+(((P=(f=e.face[v].rotation)==null?void 0:f.angle)==null?void 0:P.yaw)||0))/r,pitch:((r-1)*(((k=(C=S.face[v].rotation)==null?void 0:C.angle)==null?void 0:k.pitch)||0)+(((I=(j=e.face[v].rotation)==null?void 0:j.angle)==null?void 0:I.pitch)||0))/r},X.gaze={bearing:((r-1)*(((F=(O=S.face[v].rotation)==null?void 0:O.gaze)==null?void 0:F.bearing)||0)+(((Z=(V=e.face[v].rotation)==null?void 0:V.gaze)==null?void 0:Z.bearing)||0))/r,strength:((r-1)*(((z=(t0=S.face[v].rotation)==null?void 0:t0.gaze)==null?void 0:z.strength)||0)+(((M0=(g0=e.face[v].rotation)==null?void 0:g0.gaze)==null?void 0:M0.strength)||0))/r},S.face[v]={...e.face[v],rotation:X,box:o0,boxRaw:E}}S.face[v]={...e.face[v],box:o0,boxRaw:E}}if(!S.object||e.object.length!==S.object.length)S.object=JSON.parse(JSON.stringify(e.object));else for(let v=0;v<e.object.length;v++){let o0=e.object[v].box.map((X,_)=>((r-1)*S.object[v].box[_]+X)/r),E=e.object[v].boxRaw.map((X,_)=>((r-1)*S.object[v].boxRaw[_]+X)/r);S.object[v]={...e.object[v],box:o0,boxRaw:E}}if(e.persons){let v=e.persons;if(!S.persons||v.length!==S.persons.length)S.persons=JSON.parse(JSON.stringify(v));else for(let o0=0;o0<v.length;o0++)S.persons[o0].box=v[o0].box.map((E,X)=>((r-1)*S.persons[o0].box[X]+E)/r)}e.gesture&&(S.gesture=e.gesture);let s=b();return w1=T.perfadd?w1+Math.round(s-o):Math.round(s-o),e.performance&&(S.performance={...e.performance,interpolate:w1}),S}var ho={};U0(ho,{distance:()=>A2,match:()=>E1,similarity:()=>k1});function A2(e,t,o={order:2,multiplier:25}){let n=0;for(let r=0;r<e.length;r++){let s=!o.order||o.order===2?e[r]-t[r]:Math.abs(e[r]-t[r]);n+=!o.order||o.order===2?s*s:s**o.order}return(o.multiplier||20)*n}var uo=(e,t,o,n)=>{if(e===0)return 1;let r=t===2?Math.sqrt(e):e**(1/t),s=(1-r/100-o)/(n-o);return Math.max(Math.min(s,1),0)};function k1(e,t,o={order:2,multiplier:25,min:.2,max:.8}){let n=A2(e,t,o);return uo(n,o.order||2,o.min||0,o.max||1)}function E1(e,t,o={order:2,multiplier:25,threshold:0,min:.2,max:.8}){if(!Array.isArray(e)||!Array.isArray(t)||e.length<64||t.length===0||e.length!==t[0].length)return{index:-1,distance:Number.POSITIVE_INFINITY,similarity:0};let n=Number.MAX_SAFE_INTEGER,r=-1;for(let a=0;a<t.length;a++){let i=A2(e,t[a],o);if(i<n&&(n=i,r=a),n<(o.threshold||0))break}let s=uo(n,o.order||2,o.min||0,o.max||1);return{index:r,distance:n,similarity:s}}function bo(e,t,o,n,r){var i,l,c,d,y,x,m,h,p,R,M,g,f,P,C,k;let s=0,a=[];for(let j of e){let I={id:s++,face:j,body:null,hands:{left:null,right:null},gestures:[],box:[0,0,0,0]};for(let z of t)j.box[0]>z.box[0]&&j.box[0]<z.box[0]+z.box[2]&&j.box[1]+j.box[3]>z.box[1]&&j.box[1]+j.box[3]<z.box[1]+z.box[3]&&(I.body=z);if(I.body)for(let z of o)z.box[0]+z.box[2]>I.body.box[0]&&z.box[0]+z.box[2]<I.body.box[0]+I.body.box[2]&&z.box[1]+z.box[3]>I.body.box[1]&&z.box[1]+z.box[3]<I.body.box[1]+I.body.box[3]&&I.hands&&(I.hands.left=z),z.box[0]<I.body.box[0]+I.body.box[2]&&z.box[0]>I.body.box[0]&&z.box[1]+z.box[3]>I.body.box[1]&&z.box[1]+z.box[3]<I.body.box[1]+I.body.box[3]&&I.hands&&(I.hands.right=z);for(let z of n)z.face!==void 0&&z.face===j.id?(i=I.gestures)==null||i.push(z):z.iris!==void 0&&z.iris===j.id?(l=I.gestures)==null||l.push(z):z.body!==void 0&&z.body===((c=I.body)==null?void 0:c.id)?(d=I.gestures)==null||d.push(z):z.hand!==void 0&&z.hand===((x=(y=I.hands)==null?void 0:y.left)==null?void 0:x.id)?(m=I.gestures)==null||m.push(z):z.hand!==void 0&&z.hand===((p=(h=I.hands)==null?void 0:h.right)==null?void 0:p.id)&&((R=I.gestures)==null||R.push(z));let O=[],F=[],V=z=>{z&&z.length===4&&(O.push(z[0],z[0]+z[2]),F.push(z[1],z[1]+z[3]))};V((M=I.face)==null?void 0:M.box),V((g=I.body)==null?void 0:g.box),V((P=(f=I.hands)==null?void 0:f.left)==null?void 0:P.box),V((k=(C=I.hands)==null?void 0:C.right)==null?void 0:k.box);let Z=Math.min(...O),t0=Math.min(...F);I.box=[Z,t0,Math.max(...O)-Z,Math.max(...F)-t0],r&&r[1]&&r[2]&&(I.boxRaw=[I.box[0]/r[2],I.box[1]/r[1],I.box[2]/r[2],I.box[3]/r[1]]),a.push(I)}return a}var U2=`
 /9j/4AAQSkZJRgABAQEAYABgAAD/4QBoRXhpZgAATU0AKgAAAAgABAEaAAUAAAABAAAAPgEbAAUA
 AAABAAAARgEoAAMAAAABAAIAAAExAAIAAAARAAAATgAAAAAAAABgAAAAAQAAAGAAAAABcGFpbnQu
 bmV0IDQuMi4xMwAA/9sAQwAGBAUGBQQGBgUGBwcGCAoQCgoJCQoUDg8MEBcUGBgXFBYWGh0lHxob
@@ -827,5 +827,5 @@ AAAAAAJAAAAAAAAAAAAAABAJEAAAAAAAAAAAAAAAIEoBKAAAAAAAAAAAAAAABAlAAAAAAAIAAAAA
 BAkBAkBAkBAlACEgMZjdjbFW8bWrEx8YWANb6Fp+bfwab+vLDKMFK9qxH5L0bAr8OPRPKz2AY7J2
 SbAjYZAI2E7AIEgIEgIEgMdkSy2NgY7MdlmyNoBXsxmFuyNgVTVjNV3KjlBRNTlXTVHKCrlIqt5T
 lBhEMohlFerLlBjEMohMVTEARDKCITsAk2AEgAAAkAAAAAAAAAAAAAAAAAAAAAAAASAAAAAAAAD/
-2Q==`;async function bA(e){let t=(r,s="application/octet-stream")=>fetch(`data:${s};base64,${r}`).then(a=>a.blob()),o,n;switch(e.config.warmup){case"face":o=await t(U2);break;case"body":case"full":o=await t(Y2);break;default:o=null}if(o){let r=await createImageBitmap(o);n=await e.detect(r,e.config),r.close()}return n}async function gA(e){return new Promise(t=>{let o;switch(e.config.warmup){case"face":o="data:image/jpeg;base64,"+U2;break;case"full":case"body":o="data:image/jpeg;base64,"+Y2;break;default:o=null}let n;if(typeof Image!="undefined")n=new Image;else if(T.Image)n=new T.Image;else return;n.onload=async()=>{let r=y0(n.naturalWidth,n.naturalHeight);if(!r)u("Warmup: Canvas not found"),t(void 0);else{let s=r.getContext("2d");s&&s.drawImage(n,0,0);let a=await e.image(r),i=await e.detect(a.tensor,e.config);t(i)}},o?n.src=o:t(void 0)})}async function MA(e){let t=r=>Buffer.from(r,"base64"),o;e.config.warmup==="face"?o=t(U2):o=t(Y2);let n;if("node"in A){let r=A.node.decodeJpeg(o),s=r.expandDims(0);e.tf.dispose(r),n=await e.detect(s,e.config),e.tf.dispose(s)}else e.config.debug&&u("Warmup tfjs-node not loaded");return n}async function PA(e){let t;return typeof createImageBitmap=="function"?t=await bA(e):typeof Image!="undefined"||T.Canvas!==void 0?t=await gA(e):t=await MA(e),t}async function RA(e){let t=A.getBackend(),o=A.backend();if(t!=="webgl"&&t!=="humangl"||!o||!o.checkCompileCompletion)return;A.env().set("ENGINE_COMPILE_ONLY",!0);let n=A.engine().state.numTensors,r=[];for(let[i,l]of Object.entries(e).filter(([c,d])=>c!==null&&d!==null)){let c=l.inputs&&l.inputs[0]&&l.inputs[0].shape?[...l.inputs[0].shape]:[1,64,64,3],d=l.inputs&&l.inputs[0]&&l.inputs[0].dtype?l.inputs[0].dtype:"float32";for(let x=0;x<c.length;x++)c[x]===-1&&(c[x]=x===0?1:64);let y=A.zeros(c,d);try{let x=l.execute(y);r.push(i),Array.isArray(x)?x.forEach(m=>A.dispose(m)):A.dispose(x)}catch(x){u("compile fail model:",i)}A.dispose(y)}let s=await o.checkCompileCompletionAsync();o.getUniformLocations(),u("compile pass models:",r),u("compile pass kernels:",s.length),A.env().set("ENGINE_COMPILE_ONLY",!1);let a=A.engine().state.numTensors;a-n>0&&u("tensor leak:",a-n)}async function go(e,t){let o=b();return e.state="warmup",t&&(e.config=J(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?{face:[],body:[],hand:[],gesture:[],object:[],performance:e.performance,timestamp:b(),persons:[],error:null}:new Promise(async n=>{await RA(e.models);let r=await PA(e),s=b();e.config.debug&&u("warmup",e.config.warmup,Math.round(s-o),"ms"),e.emit("warmup"),n(r)})}var Ve,s2,a2,K2,Mo=class{constructor(t){w(this,"version");w(this,"config");w(this,"result");w(this,"state");w(this,"process");w(this,"tf");w(this,"env");w(this,"draw");w(this,"models");w(this,"events");w(this,"faceTriangulation");w(this,"faceUVMap");w(this,"performance");qe(this,Ve,void 0);qe(this,s2,void 0);qe(this,a2,void 0);w(this,"gl");w(this,"analyze",(...t)=>{if(!Xe(this,s2))return;let o=this.tf.engine().state.numTensors,n=Xe(this,Ve);Ue(this,Ve,o);let r=o-n;r!==0&&u(...t,r)});qe(this,K2,t=>{if(!Xe(this,a2))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof ge))return"input must be a tensor";try{this.tf.getBackend()}catch(o){return"backend not loaded"}return null});w(this,"similarity",k1);w(this,"distance",A2);w(this,"match",E1);w(this,"emit",t=>{var o;this.events&&this.events.dispatchEvent&&((o=this.events)==null||o.dispatchEvent(new Event(t)))});var n;this.env=T;let o=(((n=Ye)==null?void 0:n.tfjs)||A.version_core).replace(/-(.*)/,"");se.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${o}/dist/`,se.modelBasePath=T.browser?"../models/":"file://models/",se.backend=T.browser?"humangl":"tensorflow",this.version=n5,Object.defineProperty(this,"version",{value:n5}),this.config=JSON.parse(JSON.stringify(se)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=J(this.config,t)),X1(this.config),this.tf=A,this.state="idle",Ue(this,Ve,0),Ue(this,s2,!1),Ue(this,a2,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new r2,this.draw={options:l0,canvas:(r,s)=>P1(r,s),face:(r,s,a)=>Le(r,s,a),body:(r,s,a)=>We(r,s,a),hand:(r,s,a)=>Fe(r,s,a),gesture:(r,s,a)=>Be(r,s,a),object:(r,s,a)=>Ge(r,s,a),person:(r,s,a)=>M1(r,s,a),all:(r,s,a)=>R1(r,s,a)},this.result={face:[],body:[],hand:[],gesture:[],object:[],performance:{},timestamp:0,persons:[],error:null},this.process={tensor:null,canvas:null},this.faceTriangulation=n3,this.faceUVMap=r3,this.gl=Y,this.emit("create")}reset(){let t=this.config.backend;this.config=JSON.parse(JSON.stringify(se)),this.config.backend=t}validate(t){return Q2(se,t||this.config)}now(){return b()}image(t,o=!0){return Pe(t,this.config,o)}async segmentation(t,o){return no(t,o,this.config)}enhance(t){return G5(t)}compare(t,o){return Z1(this.config,t,o)}async init(){await q2(this,!0),await this.tf.ready()}async load(t){this.state="load";let o=b(),n=Object.values(this.models).filter(a=>a).length;t&&(this.config=J(this.config,t)),this.env.initial&&(this.config.debug&&u(`version: ${this.version}`),this.config.debug&&u(`tfjs version: ${this.tf.version["tfjs-core"]}`),await q2(this)||u("error: backend check failed"),await A.ready(),this.env.browser&&(this.config.debug&&u("configuration:",this.config),this.config.debug&&u("environment:",this.env),this.config.debug&&u("tf flags:",this.tf.ENV.flags))),await m1(this),this.env.initial&&this.config.debug&&u("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.env.initial=!1,Object.values(this.models).filter(a=>a).length!==n&&(await p1(this),this.emit("load"));let s=Math.trunc(b()-o);s>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+s:s)}next(t=this.result){return po(t,this.config)}getModelStats(){return f1(this)}async warmup(t){let o=b(),n=await go(this,t),r=b();return this.performance.warmup=Math.trunc(r-o),n}async profile(t,o){let n=await this.tf.profile(()=>this.detect(t,o)),r={};for(let i of n.kernels)r[i.name]?r[i.name]+=i.kernelTimeMs:r[i.name]=i.kernelTimeMs;let s=[];Object.entries(r).forEach(i=>s.push({name:i[0],ms:i[1]})),s.sort((i,l)=>l.ms-i.ms),s.length=20;let a={};for(let i of s)a[i.name]=i.ms;return a}async detect(t,o){return this.state="detect",new Promise(async n=>{var R,M,g,f,P,C,k,I,j,O,F,V,Z,t0,z,g0,M0,v,o0,E,X,_;this.state="config";let r;this.config=J(this.config,o),this.state="check";let s=Xe(this,K2).call(this,t);s&&(u(s,t),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:b(),persons:[],error:s}));let a=b();await q2(this),await this.load(),r=b(),this.state="image";let i=await Pe(t,this.config);if(this.process=i,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(b()-r):Math.trunc(b()-r),this.analyze("Get Image:"),!i.tensor){this.config.debug&&u("could not convert input to tensor"),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:b(),persons:[],error:"could not convert input to tensor"});return}this.emit("image"),r=b(),this.config.skipAllowed=await D1(this.config,i.tensor),this.performance.totalFrames||(this.performance.totalFrames=0),this.performance.cachedFrames||(this.performance.cachedFrames=0),this.performance.totalFrames++,this.config.skipAllowed&&this.performance.cachedFrames++,this.performance.cacheCheck=this.env.perfadd?(this.performance.cacheCheck||0)+Math.trunc(b()-r):Math.trunc(b()-r),this.analyze("Check Changed:");let l=[],c=[],d=[],y=[];this.state="detect:face",this.config.async?(l=this.config.face.enabled?T1(this,i.tensor):[],this.performance.face&&delete this.performance.face):(r=b(),l=this.config.face.enabled?await T1(this,i.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(b()-r):Math.trunc(b()-r)),this.config.async&&(this.config.body.maxDetected===-1||this.config.hand.maxDetected===-1)&&(l=await l),this.analyze("Start Body:"),this.state="detect:body";let x=this.config.body.maxDetected===-1?J(this.config,{body:{maxDetected:this.config.face.enabled?1*l.length:1}}):this.config;this.config.async?((R=this.config.body.modelPath)!=null&&R.includes("posenet")?c=this.config.body.enabled?x1(i.tensor,x):[]:(M=this.config.body.modelPath)!=null&&M.includes("blazepose")?c=this.config.body.enabled?R5(i.tensor,x):[]:(g=this.config.body.modelPath)!=null&&g.includes("efficientpose")?c=this.config.body.enabled?S5(i.tensor,x):[]:(f=this.config.body.modelPath)!=null&&f.includes("movenet")&&(c=this.config.body.enabled?r1(i.tensor,x):[]),this.performance.body&&delete this.performance.body):(r=b(),(P=this.config.body.modelPath)!=null&&P.includes("posenet")?c=this.config.body.enabled?await x1(i.tensor,x):[]:(C=this.config.body.modelPath)!=null&&C.includes("blazepose")?c=this.config.body.enabled?await R5(i.tensor,x):[]:(k=this.config.body.modelPath)!=null&&k.includes("efficientpose")?c=this.config.body.enabled?await S5(i.tensor,x):[]:(I=this.config.body.modelPath)!=null&&I.includes("movenet")&&(c=this.config.body.enabled?await r1(i.tensor,x):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(b()-r):Math.trunc(b()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let m=this.config.hand.maxDetected===-1?J(this.config,{hand:{maxDetected:this.config.face.enabled?2*l.length:1}}):this.config;this.config.async?((O=(j=this.config.hand.detector)==null?void 0:j.modelPath)!=null&&O.includes("handdetect")?d=this.config.hand.enabled?q5(i.tensor,m):[]:(V=(F=this.config.hand.detector)==null?void 0:F.modelPath)!=null&&V.includes("handtrack")&&(d=this.config.hand.enabled?J5(i.tensor,m):[]),this.performance.hand&&delete this.performance.hand):(r=b(),(t0=(Z=this.config.hand.detector)==null?void 0:Z.modelPath)!=null&&t0.includes("handdetect")?d=this.config.hand.enabled?await q5(i.tensor,m):[]:(g0=(z=this.config.hand.detector)==null?void 0:z.modelPath)!=null&&g0.includes("handtrack")&&(d=this.config.hand.enabled?await J5(i.tensor,m):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(b()-r):Math.trunc(b()-r)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?((M0=this.config.object.modelPath)!=null&&M0.includes("nanodet")?y=this.config.object.enabled?s1(i.tensor,this.config):[]:(v=this.config.object.modelPath)!=null&&v.includes("centernet")&&(y=this.config.object.enabled?w5(i.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=b(),(o0=this.config.object.modelPath)!=null&&o0.includes("nanodet")?y=this.config.object.enabled?await s1(i.tensor,this.config):[]:(E=this.config.object.modelPath)!=null&&E.includes("centernet")&&(y=this.config.object.enabled?await w5(i.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(b()-r):Math.trunc(b()-r)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([l,c,d,y]=await Promise.all([l,c,d,y])),this.state="detect:gesture";let h=[];this.config.gesture.enabled&&(r=b(),h=[...co(l),...xo(c),...mo(d),...fo(l)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(b()-r):Math.trunc(b()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(b()-a):Math.trunc(b()-a);let p=((_=(X=this.process)==null?void 0:X.tensor)==null?void 0:_.shape)||[];this.result={face:l,body:c,hand:d,gesture:h,object:y,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,get persons(){return bo(l,c,d,h,p)}},A.dispose(i.tensor),this.emit("detect"),this.state="idle",n(this.result)})}};Ve=new WeakMap,s2=new WeakMap,a2=new WeakMap,K2=new WeakMap;export{Mo as Human,Mo as default,se as defaults,io as draw,T as env,ho as match,u1 as models};
+2Q==`;async function bA(e){let t=(r,s="application/octet-stream")=>fetch(`data:${s};base64,${r}`).then(a=>a.blob()),o,n;switch(e.config.warmup){case"face":o=await t(U2);break;case"body":case"full":o=await t(Y2);break;default:o=null}if(o){let r=await createImageBitmap(o);n=await e.detect(r,e.config),r.close()}return n}async function gA(e){return new Promise(t=>{let o;switch(e.config.warmup){case"face":o="data:image/jpeg;base64,"+U2;break;case"full":case"body":o="data:image/jpeg;base64,"+Y2;break;default:o=null}let n;if(typeof Image!="undefined")n=new Image;else if(T.Image)n=new T.Image;else return;n.onload=async()=>{let r=y0(n.naturalWidth,n.naturalHeight);if(!r)u("Warmup: Canvas not found"),t(void 0);else{let s=r.getContext("2d");s&&s.drawImage(n,0,0);let a=await e.image(r),i=await e.detect(a.tensor,e.config);t(i)}},o?n.src=o:t(void 0)})}async function MA(e){let t=r=>Buffer.from(r,"base64"),o;e.config.warmup==="face"?o=t(U2):o=t(Y2);let n;if("node"in A){let r=A.node.decodeJpeg(o),s=r.expandDims(0);e.tf.dispose(r),n=await e.detect(s,e.config),e.tf.dispose(s)}else e.config.debug&&u("Warmup tfjs-node not loaded");return n}async function PA(e){let t;return typeof createImageBitmap=="function"?t=await bA(e):typeof Image!="undefined"||T.Canvas!==void 0?t=await gA(e):t=await MA(e),t}async function RA(e){if(!A.env().flagRegistry.ENGINE_COMPILE_ONLY)return;let t=A.getBackend(),o=A.backend();if(t!=="webgl"&&t!=="humangl"||!o||!o.checkCompileCompletion)return;A.env().set("ENGINE_COMPILE_ONLY",!0);let n=A.engine().state.numTensors,r=[];for(let[i,l]of Object.entries(e).filter(([c,d])=>c!==null&&d!==null)){let c=l.inputs&&l.inputs[0]&&l.inputs[0].shape?[...l.inputs[0].shape]:[1,64,64,3],d=l.inputs&&l.inputs[0]&&l.inputs[0].dtype?l.inputs[0].dtype:"float32";for(let x=0;x<c.length;x++)c[x]===-1&&(c[x]=x===0?1:64);let y=A.zeros(c,d);try{let x=l.execute(y);r.push(i),Array.isArray(x)?x.forEach(m=>A.dispose(m)):A.dispose(x)}catch(x){u("compile fail model:",i)}A.dispose(y)}let s=await o.checkCompileCompletionAsync();o.getUniformLocations(),u("compile pass models:",r),u("compile pass kernels:",s.length),A.env().set("ENGINE_COMPILE_ONLY",!1);let a=A.engine().state.numTensors;a-n>0&&u("tensor leak:",a-n)}async function go(e,t){let o=b();return e.state="warmup",t&&(e.config=J(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?{face:[],body:[],hand:[],gesture:[],object:[],performance:e.performance,timestamp:b(),persons:[],error:null}:new Promise(async n=>{await RA(e.models);let r=await PA(e),s=b();e.config.debug&&u("warmup",e.config.warmup,Math.round(s-o),"ms"),e.emit("warmup"),n(r)})}var Ve,s2,a2,K2,Mo=class{constructor(t){w(this,"version");w(this,"config");w(this,"result");w(this,"state");w(this,"process");w(this,"tf");w(this,"env");w(this,"draw");w(this,"models");w(this,"events");w(this,"faceTriangulation");w(this,"faceUVMap");w(this,"performance");qe(this,Ve,void 0);qe(this,s2,void 0);qe(this,a2,void 0);w(this,"gl");w(this,"analyze",(...t)=>{if(!Xe(this,s2))return;let o=this.tf.engine().state.numTensors,n=Xe(this,Ve);Ue(this,Ve,o);let r=o-n;r!==0&&u(...t,r)});qe(this,K2,t=>{if(!Xe(this,a2))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof ge))return"input must be a tensor";try{this.tf.getBackend()}catch(o){return"backend not loaded"}return null});w(this,"similarity",k1);w(this,"distance",A2);w(this,"match",E1);w(this,"emit",t=>{var o;this.events&&this.events.dispatchEvent&&((o=this.events)==null||o.dispatchEvent(new Event(t)))});var n;this.env=T;let o=(((n=Ye)==null?void 0:n.tfjs)||A.version_core).replace(/-(.*)/,"");se.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${o}/dist/`,se.modelBasePath=T.browser?"../models/":"file://models/",se.backend=T.browser?"humangl":"tensorflow",this.version=n5,Object.defineProperty(this,"version",{value:n5}),this.config=JSON.parse(JSON.stringify(se)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=J(this.config,t)),X1(this.config),this.tf=A,this.state="idle",Ue(this,Ve,0),Ue(this,s2,!1),Ue(this,a2,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new r2,this.draw={options:l0,canvas:(r,s)=>P1(r,s),face:(r,s,a)=>Le(r,s,a),body:(r,s,a)=>We(r,s,a),hand:(r,s,a)=>Fe(r,s,a),gesture:(r,s,a)=>Be(r,s,a),object:(r,s,a)=>Ge(r,s,a),person:(r,s,a)=>M1(r,s,a),all:(r,s,a)=>R1(r,s,a)},this.result={face:[],body:[],hand:[],gesture:[],object:[],performance:{},timestamp:0,persons:[],error:null},this.process={tensor:null,canvas:null},this.faceTriangulation=n3,this.faceUVMap=r3,this.gl=Y,this.emit("create")}reset(){let t=this.config.backend;this.config=JSON.parse(JSON.stringify(se)),this.config.backend=t}validate(t){return Q2(se,t||this.config)}now(){return b()}image(t,o=!0){return Pe(t,this.config,o)}async segmentation(t,o){return no(t,o,this.config)}enhance(t){return G5(t)}compare(t,o){return Z1(this.config,t,o)}async init(){await q2(this,!0),await this.tf.ready()}async load(t){this.state="load";let o=b(),n=Object.values(this.models).filter(a=>a).length;t&&(this.config=J(this.config,t)),this.env.initial&&(this.config.debug&&u(`version: ${this.version}`),this.config.debug&&u(`tfjs version: ${this.tf.version["tfjs-core"]}`),await q2(this)||u("error: backend check failed"),await A.ready(),this.env.browser&&(this.config.debug&&u("configuration:",this.config),this.config.debug&&u("environment:",this.env),this.config.debug&&u("tf flags:",this.tf.ENV.flags))),await m1(this),this.env.initial&&this.config.debug&&u("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.env.initial=!1,Object.values(this.models).filter(a=>a).length!==n&&(await p1(this),this.emit("load"));let s=Math.trunc(b()-o);s>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+s:s)}next(t=this.result){return po(t,this.config)}getModelStats(){return f1(this)}async warmup(t){let o=b(),n=await go(this,t),r=b();return this.performance.warmup=Math.trunc(r-o),n}async profile(t,o){let n=await this.tf.profile(()=>this.detect(t,o)),r={},s=0;for(let i of n.kernels)r[i.name]?r[i.name]+=i.kernelTimeMs:r[i.name]=i.kernelTimeMs,s+=i.kernelTimeMs;let a=[];Object.entries(r).forEach(i=>a.push({kernel:i[0],time:i[1],perc:0}));for(let i of a)i.perc=Math.round(1e3*i.time/s)/1e3,i.time=Math.round(1e3*i.time)/1e3;return a.sort((i,l)=>l.time-i.time),a.length=20,a}async detect(t,o){return this.state="detect",new Promise(async n=>{var R,M,g,f,P,C,k,j,I,O,F,V,Z,t0,z,g0,M0,v,o0,E,X,_;this.state="config";let r;this.config=J(this.config,o),this.state="check";let s=Xe(this,K2).call(this,t);s&&(u(s,t),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:b(),persons:[],error:s}));let a=b();await q2(this),await this.load(),r=b(),this.state="image";let i=await Pe(t,this.config);if(this.process=i,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(b()-r):Math.trunc(b()-r),this.analyze("Get Image:"),!i.tensor){this.config.debug&&u("could not convert input to tensor"),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:b(),persons:[],error:"could not convert input to tensor"});return}this.emit("image"),r=b(),this.config.skipAllowed=await D1(this.config,i.tensor),this.performance.totalFrames||(this.performance.totalFrames=0),this.performance.cachedFrames||(this.performance.cachedFrames=0),this.performance.totalFrames++,this.config.skipAllowed&&this.performance.cachedFrames++,this.performance.cacheCheck=this.env.perfadd?(this.performance.cacheCheck||0)+Math.trunc(b()-r):Math.trunc(b()-r),this.analyze("Check Changed:");let l=[],c=[],d=[],y=[];this.state="detect:face",this.config.async?(l=this.config.face.enabled?T1(this,i.tensor):[],this.performance.face&&delete this.performance.face):(r=b(),l=this.config.face.enabled?await T1(this,i.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(b()-r):Math.trunc(b()-r)),this.config.async&&(this.config.body.maxDetected===-1||this.config.hand.maxDetected===-1)&&(l=await l),this.analyze("Start Body:"),this.state="detect:body";let x=this.config.body.maxDetected===-1?J(this.config,{body:{maxDetected:this.config.face.enabled?1*l.length:1}}):this.config;this.config.async?((R=this.config.body.modelPath)!=null&&R.includes("posenet")?c=this.config.body.enabled?x1(i.tensor,x):[]:(M=this.config.body.modelPath)!=null&&M.includes("blazepose")?c=this.config.body.enabled?R5(i.tensor,x):[]:(g=this.config.body.modelPath)!=null&&g.includes("efficientpose")?c=this.config.body.enabled?S5(i.tensor,x):[]:(f=this.config.body.modelPath)!=null&&f.includes("movenet")&&(c=this.config.body.enabled?r1(i.tensor,x):[]),this.performance.body&&delete this.performance.body):(r=b(),(P=this.config.body.modelPath)!=null&&P.includes("posenet")?c=this.config.body.enabled?await x1(i.tensor,x):[]:(C=this.config.body.modelPath)!=null&&C.includes("blazepose")?c=this.config.body.enabled?await R5(i.tensor,x):[]:(k=this.config.body.modelPath)!=null&&k.includes("efficientpose")?c=this.config.body.enabled?await S5(i.tensor,x):[]:(j=this.config.body.modelPath)!=null&&j.includes("movenet")&&(c=this.config.body.enabled?await r1(i.tensor,x):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(b()-r):Math.trunc(b()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let m=this.config.hand.maxDetected===-1?J(this.config,{hand:{maxDetected:this.config.face.enabled?2*l.length:1}}):this.config;this.config.async?((O=(I=this.config.hand.detector)==null?void 0:I.modelPath)!=null&&O.includes("handdetect")?d=this.config.hand.enabled?q5(i.tensor,m):[]:(V=(F=this.config.hand.detector)==null?void 0:F.modelPath)!=null&&V.includes("handtrack")&&(d=this.config.hand.enabled?J5(i.tensor,m):[]),this.performance.hand&&delete this.performance.hand):(r=b(),(t0=(Z=this.config.hand.detector)==null?void 0:Z.modelPath)!=null&&t0.includes("handdetect")?d=this.config.hand.enabled?await q5(i.tensor,m):[]:(g0=(z=this.config.hand.detector)==null?void 0:z.modelPath)!=null&&g0.includes("handtrack")&&(d=this.config.hand.enabled?await J5(i.tensor,m):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(b()-r):Math.trunc(b()-r)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?((M0=this.config.object.modelPath)!=null&&M0.includes("nanodet")?y=this.config.object.enabled?s1(i.tensor,this.config):[]:(v=this.config.object.modelPath)!=null&&v.includes("centernet")&&(y=this.config.object.enabled?w5(i.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=b(),(o0=this.config.object.modelPath)!=null&&o0.includes("nanodet")?y=this.config.object.enabled?await s1(i.tensor,this.config):[]:(E=this.config.object.modelPath)!=null&&E.includes("centernet")&&(y=this.config.object.enabled?await w5(i.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(b()-r):Math.trunc(b()-r)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([l,c,d,y]=await Promise.all([l,c,d,y])),this.state="detect:gesture";let h=[];this.config.gesture.enabled&&(r=b(),h=[...co(l),...xo(c),...mo(d),...fo(l)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(b()-r):Math.trunc(b()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(b()-a):Math.trunc(b()-a);let p=((_=(X=this.process)==null?void 0:X.tensor)==null?void 0:_.shape)||[];this.result={face:l,body:c,hand:d,gesture:h,object:y,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,get persons(){return bo(l,c,d,h,p)}},A.dispose(i.tensor),this.emit("detect"),this.state="idle",n(this.result)})}};Ve=new WeakMap,s2=new WeakMap,a2=new WeakMap,K2=new WeakMap;export{Mo as Human,Mo as default,se as defaults,io as draw,T as env,ho as match,u1 as models};
 //# sourceMappingURL=human.esm-nobundle.js.map
diff --git a/dist/human.esm-nobundle.js.map b/dist/human.esm-nobundle.js.map
index 35bf1ceb..d9d0919b 100644
--- a/dist/human.esm-nobundle.js.map
+++ b/dist/human.esm-nobundle.js.map
@@ -1,7 +1,7 @@
 {
   "version": 3,
   "sources": ["../src/util/util.ts", "../src/config.ts", "tfjs.esm.js", "../src/image/imagefxshaders.ts", "../src/image/imagefx.ts", "../src/image/enhance.ts", "../src/image/image.ts", "../src/util/env.ts", "../src/tfjs/load.ts", "../src/models.ts", "../src/gear/gear.ts", "../src/tfjs/constants.ts", "../src/gear/ssrnet-age.ts", "../src/gear/ssrnet-gender.ts", "../src/face/antispoof.ts", "../src/face/facemeshcoords.ts", "../src/face/facemeshutil.ts", "../src/face/blazeface.ts", "../src/body/blazeposecoords.ts", "../src/body/blazeposedetector.ts", "../src/util/box.ts", "../src/body/blazepose.ts", "../src/object/labels.ts", "../src/object/centernet.ts", "../src/body/efficientposecoords.ts", "../src/body/efficientpose.ts", "../src/gear/emotion.ts", "../src/face/mobilefacenet.ts", "../src/face/iris.ts", "../src/face/constants.ts", "../src/face/attention.ts", "../src/face/facemesh.ts", "../src/face/faceres.ts", "../src/hand/handposeutil.ts", "../src/hand/handposeanchors.ts", "../src/hand/handposedetector.ts", "../src/hand/handposepipeline.ts", "../src/hand/fingerdef.ts", "../src/hand/fingergesture.ts", "../src/hand/fingerpose.ts", "../src/hand/handpose.ts", "../src/hand/handtrack.ts", "../src/face/liveness.ts", "../src/body/movenetcoords.ts", "../src/body/movenetfix.ts", "../src/body/movenet.ts", "../src/object/nanodet.ts", "../src/body/posenetutils.ts", "../src/body/posenet.ts", "../src/segmentation/segmentation.ts", "../src/tfjs/humangl.ts", "../src/tfjs/backend.ts", "../src/draw/draw.ts", "../src/draw/primitives.ts", "../src/draw/options.ts", "../src/draw/face.ts", "../src/draw/body.ts", "../src/draw/hand.ts", "../src/draw/object.ts", "../src/draw/gesture.ts", "../src/face/mask.ts", "../src/face/angles.ts", "../src/face/face.ts", "../src/gesture/gesture.ts", "../src/util/interpolate.ts", "../src/face/match.ts", "../src/util/persons.ts", "../src/sample.ts", "../src/warmup.ts", "../src/human.ts"],
-  "sourcesContent": ["import type { Config } from '../exports';\n\n/**\n * Simple helper functions used accross codebase\n */\n\n// helper function: wrapper around console output\nexport function log(...msg): void {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n\n// helper function: join two paths\nexport function join(folder: string, file: string): string {\n  const separator = folder.endsWith('/') ? '' : '/';\n  const skipJoin = file.startsWith('.') || file.startsWith('/') || file.startsWith('http:') || file.startsWith('https:') || file.startsWith('file:');\n  const path = skipJoin ? `${file}` : `${folder}${separator}${file}`;\n  if (!path.toLocaleLowerCase().includes('.json')) throw new Error(`modelpath error: expecting json file: ${path}`);\n  return path;\n}\n\n// helper function: gets elapsed time on both browser and nodejs\nexport const now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\n// helper function: checks current config validity\nexport function validate(defaults: Partial<Config>, config: Partial<Config>, parent = 'config', msgs: Array<{ reason: string, where: string, expected?: string }> = []) {\n  for (const key of Object.keys(config)) {\n    if (typeof config[key] === 'object') {\n      validate(defaults[key], config[key], key, msgs);\n    } else {\n      const defined = defaults && (typeof defaults[key] !== 'undefined');\n      if (!defined) msgs.push({ reason: 'unknown property', where: `${parent}.${key} = ${config[key]}` });\n      const same = defaults && typeof defaults[key] === typeof config[key];\n      if (defined && !same) msgs.push({ reason: 'property type mismatch', where: `${parent}.${key} = ${config[key]}`, expected: typeof defaults[key] });\n    }\n    // ok = ok && defined && same;\n  }\n  if (config.debug && parent === 'config' && msgs.length > 0) log('invalid configuration', msgs);\n  return msgs;\n}\n\n// helper function: perform deep merge of multiple objects so it allows full inheritance with overrides\nexport function mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\n// helper function: return min and max from input array\nexport const minmax = (data: Array<number>) => data.reduce((acc: Array<number>, val) => {\n  acc[0] = (acc[0] === undefined || val < acc[0]) ? val : acc[0];\n  acc[1] = (acc[1] === undefined || val > acc[1]) ? val : acc[1];\n  return acc;\n}, []);\n\n// helper function: async wait\nexport async function wait(time: number) {\n  const waiting = new Promise((resolve) => { setTimeout(() => resolve(true), time); });\n  await waiting;\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\n/** Generic config type inherited by all module types */\nexport interface GenericConfig {\n  /** is module enabled? */\n  enabled: boolean,\n  /** path to model json file (relative to `modelBasePath` */\n  modelPath: string,\n  /** how many max frames to go without re-running model if cached results are acceptable\n   * for two-phase models such as face and hand caching applies to bounding boxes detection only */\n  skipFrames: number,\n  /** how many max milliseconds to go without re-running model if cached results are acceptable\n  * for two-phase models such as face and hand caching applies to bounding boxes detection only */\n  skipTime: number,\n}\n\n/** Detector part of face configuration */\nexport interface FaceDetectorConfig extends GenericConfig {\n  /** is face rotation correction performed after detecting face?\n   * used to correctly analyze faces under high angles\n  */\n  rotation: boolean,\n  /** maximum number of detected faces */\n  maxDetected: number,\n  /** minimum confidence for a detected face before results are discarded */\n  minConfidence: number,\n  /** minimum overlap between two detected faces before one is discarded */\n  iouThreshold: number,\n  /** should child models perform on masked image of a face */\n  mask: boolean,\n  /** should face detection return processed and cropped face tensor that can with an external model for addtional processing?\n   * if enabled it must be manually deallocated to avoid memory leak */\n  return: boolean,\n}\n\n/** Mesh part of face configuration */\nexport interface FaceMeshConfig extends GenericConfig {\n  /** Keep detected faces that cannot be verified using facemesh */\n  keepInvalid: boolean\n}\n\n/** Iris part of face configuration */\nexport interface FaceIrisConfig extends GenericConfig {}\n\n/** Attention part of face configuration */\nexport interface FaceAttentionConfig extends GenericConfig {}\n\n/** Description or face embedding part of face configuration\n * - also used by age and gender detection\n */\nexport interface FaceDescriptionConfig extends GenericConfig {\n  /** minimum confidence for a detected face before results are discarded */\n  minConfidence: number,\n}\n\n/** Emotion part of face configuration */\nexport interface FaceEmotionConfig extends GenericConfig {\n  /** minimum confidence for a detected face before results are discarded */\n  minConfidence: number,\n}\n\n/** Anti-spoofing part of face configuration */\nexport interface FaceAntiSpoofConfig extends GenericConfig {}\n\n/** Liveness part of face configuration */\nexport interface FaceLivenessConfig extends GenericConfig {}\n\n/** Gear part of face configuration */\nexport interface FaceGearConfig extends GenericConfig {\n  /** minimum confidence for a detected race before results are discarded */\n  minConfidence: number,\n}\n\n/** Configures all face-specific options: face detection, mesh analysis, age, gender, emotion detection and face description */\nexport interface FaceConfig extends GenericConfig {\n  detector: Partial<FaceDetectorConfig>,\n  mesh: Partial<FaceMeshConfig>,\n  attention: Partial<FaceAttentionConfig>,\n  iris: Partial<FaceIrisConfig>,\n  description: Partial<FaceDescriptionConfig>,\n  emotion: Partial<FaceEmotionConfig>,\n  antispoof: Partial<FaceAntiSpoofConfig>,\n  liveness: Partial<FaceLivenessConfig>,\n  gear: Partial<FaceGearConfig>,\n}\n\n/** Configures all body detection specific options */\nexport interface BodyConfig extends GenericConfig {\n  /** maximum number of detected bodies */\n  maxDetected: number,\n  /** minimum confidence for a detected body before results are discarded */\n  minConfidence: number,\n  /* experimental\n  /** experimental: detector used for body model before actual analysis\n  detector?: {\n    /** experimental: enable body detector before body landmarks\n    enabled: boolean,\n    /** experimental: path to optional body detector model json file\n    modelPath: string,\n    /** experimental: minimum confidence for a detected body before results are discarded\n    minConfidence: number,\n    /** experimental: minimum overlap between two detected bodies before one is discarded\n    iouThreshold: number\n  },\n  */\n}\n\n/** Configures all hand detection specific options */\nexport interface HandConfig extends GenericConfig {\n  /** should hand rotation correction be performed after hand detection? */\n  rotation: boolean,\n  /** minimum confidence for a detected hand before results are discarded */\n  minConfidence: number,\n  /** minimum overlap between two detected hands before one is discarded */\n  iouThreshold: number,\n  /** maximum number of detected hands */\n  maxDetected: number,\n  /** should hand landmarks be detected or just return detected hand box */\n  landmarks: boolean,\n  detector: {\n    /** path to hand detector model json */\n    modelPath?: string,\n  },\n  skeleton: {\n    /** path to hand skeleton model json */\n    modelPath?: string,\n  },\n}\n\n/** Configures all object detection specific options */\nexport interface ObjectConfig extends GenericConfig {\n  /** minimum confidence for a detected objects before results are discarded */\n  minConfidence: number,\n  /** minimum overlap between two detected objects before one is discarded */\n  iouThreshold: number,\n  /** maximum number of detected objects */\n  maxDetected: number,\n}\n\n/** Configures all body segmentation module\n * removes background from input containing person\n * if segmentation is enabled it will run as preprocessing task before any other model\n * alternatively leave it disabled and use it on-demand using human.segmentation method which can\n * remove background or replace it with user-provided background\n*/\nexport interface SegmentationConfig extends GenericConfig {\n  /** blur segmentation output by <number> pixels for more realistic image */\n  blur: number,\n}\n\n/** Run input through image filters before inference\n * - available only in Browser environments\n * - image filters run with near-zero latency as they are executed on the GPU using WebGL\n*/\nexport interface FilterConfig {\n  /** are image filters enabled? */\n  enabled: boolean,\n  /** perform image histogram equalization\n   * - equalization is performed on input as a whole and detected face before its passed for further analysis\n  */\n  equalization: boolean,\n  /** resize input width\n  * - if both width and height are set to 0, there is no resizing\n  * - if just one is set, second one is scaled automatically\n  * - if both are set, values are used as-is\n  */\n  width: number,\n  /** resize input height\n  * - if both width and height are set to 0, there is no resizing\n  * - if just one is set, second one is scaled automatically\n  * - if both are set, values are used as-is\n  */\n  height: number,\n  /** return processed canvas imagedata in result */\n  return: boolean,\n  /** flip input as mirror image */\n  flip: boolean,\n  /** range: -1 (darken) to 1 (lighten) */\n  brightness: number,\n  /** range: -1 (reduce contrast) to 1 (increase contrast) */\n  contrast: number,\n  /** range: 0 (no sharpening) to 1 (maximum sharpening) */\n  sharpness: number,\n  /** range: 0 (no blur) to N (blur radius in pixels) */\n  blur: number\n  /** range: -1 (reduce saturation) to 1 (increase saturation) */\n  saturation: number,\n  /** range: 0 (no change) to 360 (hue rotation in degrees) */\n  hue: number,\n  /** image negative */\n  negative: boolean,\n  /** image sepia colors */\n  sepia: boolean,\n  /** image vintage colors */\n  vintage: boolean,\n  /** image kodachrome colors */\n  kodachrome: boolean,\n  /** image technicolor colors */\n  technicolor: boolean,\n  /** image polaroid camera effect */\n  polaroid: boolean,\n  /** range: 0 (no pixelate) to N (number of pixels to pixelate) */\n  pixelate: number,\n}\n\n/** Controlls gesture detection */\nexport interface GestureConfig {\n  /** is gesture detection enabled? */\n  enabled: boolean,\n}\n/** Possible TensorFlow backends */\nexport type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu'];\n\n/** Possible values for `human.warmup` */\nexport type WarmupType = ['' | 'none' | 'face' | 'full' | 'body'];\n\n/**\n * Configuration interface definition for **Human** library\n * Contains all configurable parameters\n * Defaults: [config](https://github.com/vladmandic/human/blob/main/src/config.ts#L262)\n */\nexport interface Config {\n  /** Backend used for TFJS operations\n   * valid build-in backends are:\n   * - Browser: `cpu`, `wasm`, `webgl`, `humangl`, `webgpu`\n   * - NodeJS: `cpu`, `wasm`, `tensorflow`\n   * default: `humangl` for browser and `tensorflow` for nodejs\n  */\n  backend: '' | 'cpu' | 'wasm' | 'webgl' | 'humangl' | 'tensorflow' | 'webgpu',\n\n  /** Path to *.wasm files if backend is set to `wasm`\n   *\n   * default: auto-detects to link to CDN `jsdelivr` when running in browser\n  */\n  wasmPath: string,\n\n  /** Force WASM loader to use platform fetch\n   *\n   * default: auto-detects to link to CDN `jsdelivr` when running in browser\n  */\n  wasmPlatformFetch: boolean,\n\n  /** Print debug statements to console\n   *\n   * default: `true`\n  */\n  debug: boolean,\n\n  /** Perform model loading and inference concurrently or sequentially\n   *\n   * default: `true`\n  */\n  async: boolean,\n\n  /** What to use for `human.warmup()`\n   * - warmup pre-initializes all models for faster inference but can take significant time on startup\n   * - used by `webgl`, `humangl` and `webgpu` backends\n   *\n   * default: `full`\n  */\n  warmup: '' | 'none' | 'face' | 'full' | 'body',\n\n  /** Base model path (typically starting with file://, http:// or https://) for all models\n   * - individual modelPath values are relative to this path\n   *\n   * default: `../models/` for browsers and `file://models/` for nodejs\n  */\n  modelBasePath: string,\n\n  /** Cache models in IndexDB on first sucessfull load\n   * default: true if indexdb is available (browsers), false if its not (nodejs)\n   */\n  cacheModels: boolean,\n\n  /** Cache sensitivity\n   * - values 0..1 where 0.01 means reset cache if input changed more than 1%\n   * - set to 0 to disable caching\n   *\n   * default: 0.7\n  */\n  cacheSensitivity: number;\n\n  /** Perform immediate garbage collection on deallocated tensors instead of caching them */\n  deallocate: boolean;\n\n  /** Internal Variable */\n  skipAllowed: boolean;\n\n  /** Filter config {@link FilterConfig} */\n  filter: Partial<FilterConfig>,\n\n  /** Gesture config {@link GestureConfig} */\n  gesture: Partial<GestureConfig>;\n\n  /** Face config {@link FaceConfig} */\n  face: Partial<FaceConfig>,\n\n  /** Body config {@link BodyConfig} */\n  body: Partial<BodyConfig>,\n\n  /** Hand config {@link HandConfig} */\n  hand: Partial<HandConfig>,\n\n  /** Object config {@link ObjectConfig} */\n  object: Partial<ObjectConfig>,\n\n  /** Segmentation config {@link SegmentationConfig} */\n  segmentation: Partial<SegmentationConfig>,\n}\n\n/** - [See all default Config values...](https://github.com/vladmandic/human/blob/main/src/config.ts#L262) */\nconst config: Config = {\n  backend: '',\n  modelBasePath: '',\n  cacheModels: true,\n  wasmPath: '',\n  wasmPlatformFetch: false,\n  debug: false,\n  async: true,\n  warmup: 'full',\n  cacheSensitivity: 0.70,\n  skipAllowed: false,\n  deallocate: false,\n  filter: {\n    enabled: true,\n    equalization: false,\n    width: 0,\n    height: 0,\n    flip: false,\n    return: true,\n    brightness: 0,\n    contrast: 0,\n    sharpness: 0,\n    blur: 0,\n    saturation: 0,\n    hue: 0,\n    negative: false,\n    sepia: false,\n    vintage: false,\n    kodachrome: false,\n    technicolor: false,\n    polaroid: false,\n    pixelate: 0,\n  },\n  gesture: {\n    enabled: true,\n  },\n  face: {\n    enabled: true,\n    detector: {\n      modelPath: 'blazeface.json',\n      rotation: true,\n      maxDetected: 1,\n      skipFrames: 99,\n      skipTime: 2500,\n      minConfidence: 0.2,\n      iouThreshold: 0.1,\n      mask: false,\n      return: false,\n    },\n    mesh: {\n      enabled: true,\n      modelPath: 'facemesh.json',\n      keepInvalid: false,\n    },\n    attention: {\n      enabled: false,\n      modelPath: 'facemesh-attention.json',\n    },\n    iris: {\n      enabled: true,\n      modelPath: 'iris.json',\n    },\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,\n      skipFrames: 99,\n      skipTime: 1500,\n      modelPath: 'emotion.json',\n    },\n    description: {\n      enabled: true,\n      modelPath: 'faceres.json',\n      skipFrames: 99,\n      skipTime: 3000,\n      minConfidence: 0.1,\n    },\n    antispoof: {\n      enabled: false,\n      skipFrames: 99,\n      skipTime: 4000,\n      modelPath: 'antispoof.json',\n    },\n    liveness: {\n      enabled: false,\n      skipFrames: 99,\n      skipTime: 4000,\n      modelPath: 'liveness.json',\n    },\n  },\n  body: {\n    enabled: true,\n    modelPath: 'movenet-lightning.json',\n    maxDetected: -1,\n    minConfidence: 0.3,\n    skipFrames: 1,\n    skipTime: 200,\n  },\n  hand: {\n    enabled: true,\n    rotation: true,\n    skipFrames: 99,\n    skipTime: 1000,\n    minConfidence: 0.50,\n    iouThreshold: 0.2,\n    maxDetected: -1,\n    landmarks: true,\n    detector: {\n      modelPath: 'handtrack.json',\n    },\n    skeleton: {\n      modelPath: 'handlandmark-full.json',\n    },\n  },\n  object: {\n    enabled: false,\n    modelPath: 'mb3-centernet.json',\n    minConfidence: 0.2,\n    iouThreshold: 0.4,\n    maxDetected: 10,\n    skipFrames: 99,\n    skipTime: 2000,\n  },\n  segmentation: {\n    enabled: false,\n    modelPath: 'selfie.json',\n    blur: 8,\n  },\n};\n\nexport { config as defaults };\n", "/*\n  Human\n  homepage: <https://github.com/vladmandic/human>\n  author: <https://github.com/vladmandic>'\n*/\n\nexport*from\"@tensorflow/tfjs/dist/index.js\";export*from\"@tensorflow/tfjs-backend-webgl/dist/index.js\";var r=\"3.19.0\",e=\"3.19.0\",o=\"3.19.0\",a=\"3.19.0\",t=\"3.19.0\",s=\"3.19.0\",f=\"3.19.0\",v={tfjs:r,\"tfjs-core\":e,\"tfjs-data\":o,\"tfjs-layers\":a,\"tfjs-converter\":t,\"tfjs-backend-webgl\":s,\"tfjs-backend-wasm\":f};import{Tensor as d}from\"@tensorflow/tfjs/dist/index.js\";import{GraphModel as b}from\"@tensorflow/tfjs-converter/dist/index\";export{b as GraphModel,d as Tensor,v as version};\n", "export const vertexIdentity = `\n  precision highp float;\n  attribute vec2 pos;\n  attribute vec2 uv;\n  varying vec2 vUv;\n  uniform float flipY;\n  void main(void) {\n    vUv = uv;\n    gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);\n  }\n`;\n\nexport const fragmentIdentity = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  void main(void) {\n    gl_FragColor = texture2D(texture, vUv);\n  }\n`;\n\nexport const colorMatrixWithAlpha = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform float m[20];\n  void main(void) {\n    vec4 c = texture2D(texture, vUv);\n    gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];\n    gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];\n    gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];\n    gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];\n  }\n`;\n\nexport const colorMatrixWithoutAlpha = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform float m[20];\n  void main(void) {\n    vec4 c = texture2D(texture, vUv);\n    gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];\n    gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];\n    gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];\n    gl_FragColor.a = c.a;\n  }\n`;\n\nexport const pixelate = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform vec2 size;\n  uniform sampler2D texture;\n  vec2 pixelate(vec2 coord, vec2 size) {\n    return floor( coord / size ) * size;\n  }\n  void main(void) {\n    gl_FragColor = vec4(0.0);\n    vec2 coord = pixelate(vUv, size);\n    gl_FragColor += texture2D(texture, coord);\n  }\n`;\n\nexport const blur = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform vec2 px;\n  void main(void) {\n    gl_FragColor = vec4(0.0);\n    gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;\n    gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;\n    gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;\n    gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;\n    gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;\n    gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;\n    gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;\n    gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;\n    gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;\n    gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;\n    gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;\n    gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;\n    gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;\n    gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;\n    gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;\n  }\n`;\n\nexport const convolution = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform vec2 px;\n  uniform float m[9];\n  void main(void) {\n    vec4 c11 = texture2D(texture, vUv - px); // top left\n    vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y)); // top center\n    vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y)); // top right\n    vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) ); // mid left\n    vec4 c22 = texture2D(texture, vUv); // mid center\n    vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) ); // mid right\n    vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) ); // bottom left\n    vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) ); // bottom center\n    vec4 c33 = texture2D(texture, vUv + px ); // bottom right\n    gl_FragColor = \n    c11 * m[0] + c12 * m[1] + c22 * m[2] +\n    c21 * m[3] + c22 * m[4] + c23 * m[5] +\n    c31 * m[6] + c32 * m[7] + c33 * m[8];\n    gl_FragColor.a = c22.a;\n  }\n`;\n", "/**\n * Image Filters in WebGL algoritm implementation\n * Based on: [WebGLImageFilter](https://github.com/phoboslab/WebGLImageFilter)\n */\n\nimport * as shaders from './imagefxshaders';\nimport { canvas } from './image';\nimport { log } from '../util/util';\n\nconst collect = (source, prefix, collection) => {\n  const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n  source.replace(r, (match, name) => {\n    collection[name] = 0;\n    return match;\n  });\n};\n\nclass GLProgram {\n  uniform = {};\n  attribute = {};\n  gl: WebGLRenderingContext;\n  id: WebGLProgram;\n\n  constructor(gl, vertexSource, fragmentSource) {\n    this.gl = gl;\n    const vertexShader = this.compile(vertexSource, this.gl.VERTEX_SHADER);\n    const fragmentShader = this.compile(fragmentSource, this.gl.FRAGMENT_SHADER);\n    this.id = this.gl.createProgram() as WebGLProgram;\n    if (!vertexShader || !fragmentShader) return;\n    if (!this.id) {\n      log('filter: could not create webgl program');\n      return;\n    }\n    this.gl.attachShader(this.id, vertexShader);\n    this.gl.attachShader(this.id, fragmentShader);\n    this.gl.linkProgram(this.id);\n    if (!this.gl.getProgramParameter(this.id, this.gl.LINK_STATUS)) {\n      log(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);\n      return;\n    }\n    this.gl.useProgram(this.id);\n    collect(vertexSource, 'attribute', this.attribute); // Collect attributes\n    for (const a in this.attribute) this.attribute[a] = this.gl.getAttribLocation(this.id, a);\n    collect(vertexSource, 'uniform', this.uniform); // Collect uniforms\n    collect(fragmentSource, 'uniform', this.uniform);\n    for (const u in this.uniform) this.uniform[u] = this.gl.getUniformLocation(this.id, u);\n  }\n\n  compile = (source, type): WebGLShader | null => {\n    const shader = this.gl.createShader(type) as WebGLShader;\n    if (!shader) {\n      log('filter: could not create shader');\n      return null;\n    }\n    this.gl.shaderSource(shader, source);\n    this.gl.compileShader(shader);\n    if (!this.gl.getShaderParameter(shader, this.gl.COMPILE_STATUS)) {\n      log(`filter: gl compile failed: ${this.gl.getShaderInfoLog(shader)}`);\n      return null;\n    }\n    return shader;\n  };\n}\n\n// function that is instantiated as class so it has private this members\n/**\n * @class GLImageFilter\n * @property {function} reset reset current filter chain\n * @property {function} add add specified filter to filter chain\n * @property {function} apply execute filter chain and draw result\n * @property {function} draw just draw input to result\n */\n\nexport function GLImageFilter() {\n  let drawCount = 0;\n  let sourceTexture: WebGLTexture | null = null;\n  let lastInChain = false;\n  let currentFramebufferIndex = -1;\n  let tempFramebuffers: [null, null] | [{ fbo: WebGLFramebuffer | null, texture: WebGLTexture | null }] = [null, null];\n  let filterChain: Record<string, unknown>[] = [];\n  let vertexBuffer: WebGLBuffer | null = null;\n  let currentProgram: GLProgram | null = null;\n  const fxcanvas = canvas(100, 100);\n  const shaderProgramCache = { }; // key is the shader program source, value is the compiled program\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = fxcanvas.getContext('webgl') as WebGLRenderingContext;\n  if (!gl) {\n    log('filter: cannot get webgl context');\n    return;\n  }\n  // @ts-ignore used for sanity checks outside of imagefx\n  this.gl = gl;\n\n  function resize(width, height) {\n    if (width === fxcanvas.width && height === fxcanvas.height) return; // Same width/height? Nothing to do here\n    fxcanvas.width = width;\n    fxcanvas.height = height;\n    if (!vertexBuffer) { // Create the context if we don't have it yet\n      const vertices = new Float32Array([-1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0]); // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      vertexBuffer = gl.createBuffer();\n      gl.bindBuffer(gl.ARRAY_BUFFER, vertexBuffer);\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, fxcanvas.width, fxcanvas.height);\n    tempFramebuffers = [null, null]; // Delete old temp framebuffers\n  }\n\n  function createFramebufferTexture(width, height) {\n    const fbo = gl.createFramebuffer() as WebGLFramebuffer;\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture() as WebGLTexture;\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  }\n\n  function getTempFramebuffer(index): { fbo: WebGLFramebuffer | null, texture: WebGLTexture | null } {\n    tempFramebuffers[index] = tempFramebuffers[index] || createFramebufferTexture(fxcanvas.width, fxcanvas.height);\n    return tempFramebuffers[index] as { fbo: WebGLFramebuffer, texture: WebGLTexture };\n  }\n\n  function draw(flags = 0) {\n    if (!currentProgram) return;\n    let source: WebGLTexture | null = null;\n    let target: WebGLFramebuffer | null = null;\n    let flipY = false;\n    if (drawCount === 0) source = sourceTexture; // First draw call - use the source texture\n    else source = getTempFramebuffer(currentFramebufferIndex).texture || null; // All following draw calls use the temp buffer last drawn to\n    drawCount++;\n    if (lastInChain && !(flags & DRAW.INTERMEDIATE)) { // Last filter in our chain - draw directly to the WebGL Canvas. We may also have to flip the image vertically now\n      target = null;\n      flipY = drawCount % 2 === 0;\n    } else {\n      currentFramebufferIndex = (currentFramebufferIndex + 1) % 2;\n      target = getTempFramebuffer(currentFramebufferIndex).fbo || null; // Intermediate draw call - get a temp buffer to draw to\n    }\n    gl.bindTexture(gl.TEXTURE_2D, source); // Bind the source and target and draw the two triangles\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(currentProgram.uniform['flipY'], (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  }\n\n  function compileShader(fragmentSource): GLProgram | null {\n    if (shaderProgramCache[fragmentSource]) {\n      currentProgram = shaderProgramCache[fragmentSource];\n      gl.useProgram((currentProgram ? currentProgram.id : null) || null);\n      return currentProgram as GLProgram;\n    }\n    currentProgram = new GLProgram(gl, shaders.vertexIdentity, fragmentSource);\n    if (!currentProgram) {\n      log('filter: could not get webgl program');\n      return null;\n    }\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(currentProgram.attribute['pos']);\n    gl.vertexAttribPointer(currentProgram.attribute['pos'], 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(currentProgram.attribute['uv']);\n    gl.vertexAttribPointer(currentProgram.attribute['uv'], 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    shaderProgramCache[fragmentSource] = currentProgram;\n    return currentProgram as GLProgram;\n  }\n\n  const filter = {\n    colorMatrix: (matrix) => { // general color matrix filter\n      const m = new Float32Array(matrix);\n      m[4] /= 255;\n      m[9] /= 255;\n      m[14] /= 255;\n      m[19] /= 255;\n      const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0) // Can we ignore the alpha value? Makes things a bit faster.\n        ? shaders.colorMatrixWithoutAlpha\n        : shaders.colorMatrixWithAlpha;\n      const program = compileShader(shader);\n      if (!program) return;\n      gl.uniform1fv(program.uniform['m'], m);\n      draw();\n    },\n\n    brightness: (brightness) => {\n      const b = (brightness || 0) + 1;\n      filter.colorMatrix([\n        b, 0, 0, 0, 0,\n        0, b, 0, 0, 0,\n        0, 0, b, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    saturation: (amount) => {\n      const x = (amount || 0) * 2 / 3 + 1;\n      const y = ((x - 1) * -0.5);\n      filter.colorMatrix([\n        x, y, y, 0, 0,\n        y, x, y, 0, 0,\n        y, y, x, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    desaturate: () => {\n      filter.saturation(-1);\n    },\n\n    contrast: (amount) => {\n      const v = (amount || 0) + 1;\n      const o = -128 * (v - 1);\n      filter.colorMatrix([\n        v, 0, 0, 0, o,\n        0, v, 0, 0, o,\n        0, 0, v, 0, o,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    negative: () => {\n      filter.contrast(-2);\n    },\n\n    hue: (rotation) => {\n      rotation = (rotation || 0) / 180 * Math.PI;\n      const cos = Math.cos(rotation);\n      const sin = Math.sin(rotation);\n      const lumR = 0.213;\n      const lumG = 0.715;\n      const lumB = 0.072;\n      filter.colorMatrix([\n        lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n        lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n        lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    desaturateLuminance: () => {\n      filter.colorMatrix([\n        0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n        0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n        0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    sepia: () => {\n      filter.colorMatrix([\n        0.393, 0.7689999, 0.18899999, 0, 0,\n        0.349, 0.6859999, 0.16799999, 0, 0,\n        0.272, 0.5339999, 0.13099999, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    brownie: () => {\n      filter.colorMatrix([\n        0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n        -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n        0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    vintagePinhole: () => {\n      filter.colorMatrix([\n        0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n        0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n        0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    kodachrome: () => {\n      filter.colorMatrix([\n        1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n        -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n        -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    technicolor: () => {\n      filter.colorMatrix([\n        1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n        -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n        -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    polaroid: () => {\n      filter.colorMatrix([\n        1.438, -0.062, -0.062, 0, 0,\n        -0.122, 1.378, -0.122, 0, 0,\n        -0.016, -0.016, 1.483, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    shiftToBGR: () => {\n      filter.colorMatrix([\n        0, 0, 1, 0, 0,\n        0, 1, 0, 0, 0,\n        1, 0, 0, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    convolution: (matrix) => { // general convolution Filter\n      const m = new Float32Array(matrix);\n      const pixelSizeX = 1 / fxcanvas.width;\n      const pixelSizeY = 1 / fxcanvas.height;\n      const program = compileShader(shaders.convolution);\n      if (!program) return;\n      gl.uniform1fv(program.uniform['m'], m);\n      gl.uniform2f(program.uniform['px'], pixelSizeX, pixelSizeY);\n      draw();\n    },\n\n    detectEdges: () => {\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        0, 1, 0,\n        1, -4, 1,\n        0, 1, 0,\n      ]);\n    },\n\n    sobelX: () => {\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        -1, 0, 1,\n        -2, 0, 2,\n        -1, 0, 1,\n      ]);\n    },\n\n    sobelY: () => {\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        -1, -2, -1,\n        0, 0, 0,\n        1, 2, 1,\n      ]);\n    },\n\n    sharpen: (amount) => {\n      const a = amount || 1;\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        0, -1 * a, 0,\n        -1 * a, 1 + 4 * a, -1 * a,\n        0, -1 * a, 0,\n      ]);\n    },\n\n    emboss: (size) => {\n      const s = size || 1;\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        -2 * s, -1 * s, 0,\n        -1 * s, 1, 1 * s,\n        0, 1 * s, 2 * s,\n      ]);\n    },\n\n    blur: (size) => {\n      const blurSizeX = (size / 7) / fxcanvas.width;\n      const blurSizeY = (size / 7) / fxcanvas.height;\n      const program = compileShader(shaders.blur);\n      if (!program) return;\n      // Vertical\n      gl.uniform2f(program.uniform['px'], 0, blurSizeY);\n      draw(DRAW.INTERMEDIATE);\n      // Horizontal\n      gl.uniform2f(program.uniform['px'], blurSizeX, 0);\n      draw();\n    },\n\n    pixelate: (size) => {\n      const blurSizeX = (size) / fxcanvas.width;\n      const blurSizeY = (size) / fxcanvas.height;\n      const program = compileShader(shaders.pixelate);\n      if (!program) return;\n      gl.uniform2f(program.uniform['size'], blurSizeX, blurSizeY);\n      draw();\n    },\n  };\n\n  // @ts-ignore this\n  this.add = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const func = filter[name];\n    filterChain.push({ func, args });\n  };\n\n  // @ts-ignore this\n  this.reset = function () {\n    filterChain = [];\n  };\n\n  // @ts-ignore this\n  this.get = function () {\n    return filterChain;\n  };\n\n  // @ts-ignore this\n  this.apply = function (image) {\n    resize(image.width, image.height);\n    drawCount = 0;\n    if (!sourceTexture) sourceTexture = gl.createTexture(); // Create the texture for the input image if we haven't yet\n    gl.bindTexture(gl.TEXTURE_2D, sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    for (let i = 0; i < filterChain.length; i++) {\n      lastInChain = (i === filterChain.length - 1);\n      const f = filterChain[i];\n      // @ts-ignore function assigment\n      f.func.apply(this, f.args || []);\n    }\n    return fxcanvas;\n  };\n\n  // @ts-ignore this\n  this.draw = function (image) {\n    this.add('brightness', 0);\n    return this.apply(image);\n  };\n}\n", "/**\n * Image enhancements\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from '../exports';\n\nexport async function histogramEqualization(inputImage: Tensor): Promise<Tensor> {\n  // const maxValue = 254; // using 255 results in values slightly larger than 1 due to math rounding errors\n  const squeeze = inputImage.shape.length === 4 ? tf.squeeze(inputImage) : inputImage;\n  const channels = tf.split(squeeze, 3, 2);\n  const min: Tensor[] = [tf.min(channels[0]), tf.min(channels[1]), tf.min(channels[2])];\n  const max: Tensor[] = [tf.max(channels[0]), tf.max(channels[1]), tf.max(channels[2])];\n  const absMax = await Promise.all(max.map((channel) => channel.data()));\n  const maxValue = 0.99 * Math.max(absMax[0][0], absMax[1][0], absMax[2][0]);\n  const sub = [tf.sub(channels[0], min[0]), tf.sub(channels[1], min[1]), tf.sub(channels[2], min[2])];\n  const range = [tf.sub(max[0], min[0]), tf.sub(max[1], min[1]), tf.sub(max[2], min[2])];\n  const fact = [tf.div(maxValue, range[0]), tf.div(maxValue, range[1]), tf.div(maxValue, range[2])];\n  const enh = [tf.mul(sub[0], fact[0]), tf.mul(sub[1], fact[1]), tf.mul(sub[2], fact[2])];\n  const rgb = tf.stack([enh[0], enh[1], enh[2]], 2);\n  const reshape = tf.reshape(rgb, [1, squeeze.shape[0], squeeze.shape[1], 3]);\n  tf.dispose([...channels, ...min, ...max, ...sub, ...range, ...fact, ...enh, rgb, squeeze]);\n  return reshape; // output shape is [1, height, width, 3]\n}\n", "/**\n * Image Processing algorithm implementation\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\nimport type { Input, AnyCanvas, Tensor, Config } from '../exports';\nimport { env } from '../util/env';\nimport { log } from '../util/util';\nimport * as enhance from './enhance';\n\nconst maxSize = 3840;\n// internal temp canvases\nlet inCanvas: AnyCanvas | null = null; // use global variable to avoid recreating canvas on each frame\nlet outCanvas: AnyCanvas | null = null; // use global variable to avoid recreating canvas on each frame\nlet tmpCanvas: AnyCanvas | null = null; // use global variable to avoid recreating canvas on each frame\n// @ts-ignore // imagefx is js module that should be converted to a class\nlet fx: fxImage.GLImageFilter | null; // instance of imagefx\n\nconst last: { inputSum: number, cacheDiff: number, sumMethod: number, inputTensor: undefined | Tensor } = {\n  inputSum: 0,\n  cacheDiff: 1,\n  sumMethod: 0,\n  inputTensor: undefined,\n};\n\nexport function canvas(width: number, height: number): AnyCanvas {\n  let c;\n  if (env.browser) { // browser defines canvas object\n    if (env.worker) { // if runing in web  worker use OffscreenCanvas\n      if (typeof OffscreenCanvas === 'undefined') throw new Error('canvas error: attempted to run in web worker but OffscreenCanvas is not supported');\n      c = new OffscreenCanvas(width, height);\n    } else { // otherwise use DOM canvas\n      if (typeof document === 'undefined') throw new Error('canvas error: attempted to run in browser but DOM is not defined');\n      c = document.createElement('canvas');\n      c.width = width;\n      c.height = height;\n    }\n  } else { // if not running in browser, there is no \"default\" canvas object, so we need monkey patch or fail\n    // @ts-ignore // env.canvas is an external monkey-patch\n    if (typeof env.Canvas !== 'undefined') c = new env.Canvas(width, height);\n    else if (typeof globalThis.Canvas !== 'undefined') c = new globalThis.Canvas(width, height);\n    // else throw new Error('canvas error: attempted to use canvas in nodejs without canvas support installed');\n  }\n  return c;\n}\n\n// helper function to copy canvas from input to output\nexport function copy(input: AnyCanvas, output?: AnyCanvas) {\n  const outputCanvas = output || canvas(input.width, input.height);\n  const ctx = outputCanvas.getContext('2d') as CanvasRenderingContext2D;\n  ctx.drawImage(input, 0, 0);\n  return outputCanvas;\n}\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport async function process(input: Input, config: Config, getTensor: boolean = true): Promise<{ tensor: Tensor | null, canvas: AnyCanvas | null }> {\n  if (!input) {\n    // throw new Error('input is missing');\n    if (config.debug) log('input error: input is missing');\n    return { tensor: null, canvas: null }; // video may become temporarily unavailable due to onresize\n  }\n  // sanity checks since different browsers do not implement all dom elements\n  if (\n    !(input instanceof tf.Tensor)\n    && !(typeof Image !== 'undefined' && input instanceof Image)\n    && !(typeof env.Canvas !== 'undefined' && input instanceof env.Canvas)\n    && !(typeof globalThis.Canvas !== 'undefined' && input instanceof globalThis.Canvas)\n    && !(typeof ImageData !== 'undefined' && input instanceof ImageData)\n    && !(typeof ImageBitmap !== 'undefined' && input instanceof ImageBitmap)\n    && !(typeof HTMLImageElement !== 'undefined' && input instanceof HTMLImageElement)\n    && !(typeof HTMLMediaElement !== 'undefined' && input instanceof HTMLMediaElement)\n    && !(typeof HTMLVideoElement !== 'undefined' && input instanceof HTMLVideoElement)\n    && !(typeof HTMLCanvasElement !== 'undefined' && input instanceof HTMLCanvasElement)\n    && !(typeof OffscreenCanvas !== 'undefined' && input instanceof OffscreenCanvas)\n  ) {\n    throw new Error('input error: type is not recognized');\n  }\n  if (input instanceof tf.Tensor) { // if input is tensor use as-is without filters but correct shape as needed\n    let tensor: Tensor | null = null;\n    if ((input as Tensor)['isDisposedInternal']) throw new Error('input error: attempted to use tensor but it is disposed');\n    if (!(input as Tensor)['shape']) throw new Error('input error: attempted to use tensor without a shape');\n    if ((input as Tensor).shape.length === 3) { // [height, width, 3 || 4]\n      if ((input as Tensor).shape[2] === 3) { // [height, width, 3] so add batch\n        tensor = tf.expandDims(input, 0);\n      } else if ((input as Tensor).shape[2] === 4) { // [height, width, 4] so strip alpha and add batch\n        const rgb = tf.slice3d(input, [0, 0, 0], [-1, -1, 3]);\n        tensor = tf.expandDims(rgb, 0);\n        tf.dispose(rgb);\n      }\n    } else if ((input as Tensor).shape.length === 4) { // [1, width, height, 3 || 4]\n      if ((input as Tensor).shape[3] === 3) { // [1, width, height, 3] just clone\n        tensor = tf.clone(input);\n      } else if ((input as Tensor).shape[3] === 4) { // [1, width, height, 4] so strip alpha\n        tensor = tf.slice4d(input, [0, 0, 0, 0], [-1, -1, -1, 3]);\n      }\n    }\n    // at the end shape must be [1, height, width, 3]\n    if (tensor == null || tensor.shape.length !== 4 || tensor.shape[0] !== 1 || tensor.shape[3] !== 3) throw new Error(`input error: attempted to use tensor with unrecognized shape: ${input['shape']}`);\n    if ((tensor as Tensor).dtype === 'int32') {\n      const cast = tf.cast(tensor, 'float32');\n      tf.dispose(tensor);\n      tensor = cast;\n    }\n    return { tensor, canvas: (config.filter.return ? outCanvas : null) };\n  } else {\n    // check if resizing will be needed\n    if (typeof input['readyState'] !== 'undefined' && input['readyState'] <= 2) {\n      if (config.debug) log('input stream is not ready');\n      return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize\n    }\n    const originalWidth = input['naturalWidth'] || input['videoWidth'] || input['width'] || (input['shape'] && (input['shape'][1] > 0));\n    const originalHeight = input['naturalHeight'] || input['videoHeight'] || input['height'] || (input['shape'] && (input['shape'][2] > 0));\n    if (!originalWidth || !originalHeight) {\n      if (config.debug) log('cannot determine input dimensions');\n      return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize\n    }\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = Math.trunc(targetWidth * originalHeight / originalWidth);\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = Math.trunc(targetHeight * originalWidth / originalHeight);\n    }\n\n    // create our canvas and resize it if needed\n    if ((config.filter.width || 0) > 0) targetWidth = config.filter.width;\n    else if ((config.filter.height || 0) > 0) targetWidth = originalWidth * ((config.filter.height || 0) / originalHeight);\n    if ((config.filter.height || 0) > 0) targetHeight = config.filter.height;\n    else if ((config.filter.width || 0) > 0) targetHeight = originalHeight * ((config.filter.width || 0) / originalWidth);\n    if (!targetWidth || !targetHeight) throw new Error('input error: cannot determine dimension');\n    if (!inCanvas || (inCanvas?.width !== targetWidth) || (inCanvas?.height !== targetHeight)) inCanvas = canvas(targetWidth, targetHeight);\n\n    // draw input to our canvas\n    const inCtx = inCanvas.getContext('2d') as CanvasRenderingContext2D;\n    if ((typeof ImageData !== 'undefined') && (input instanceof ImageData)) {\n      inCtx.putImageData(input, 0, 0);\n    } else {\n      if (config.filter.flip && typeof inCtx.translate !== 'undefined') {\n        inCtx.translate(originalWidth, 0);\n        inCtx.scale(-1, 1);\n        inCtx.drawImage(input as AnyCanvas, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas?.width, inCanvas?.height);\n        inCtx.setTransform(1, 0, 0, 1, 0, 0); // resets transforms to defaults\n      } else {\n        inCtx.drawImage(input as AnyCanvas, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas?.width, inCanvas?.height);\n      }\n    }\n\n    if (!outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas?.height !== outCanvas?.height)) outCanvas = canvas(inCanvas.width, inCanvas.height); // init output canvas\n\n    // imagefx transforms using gl from input canvas to output canvas\n    if (config.filter.enabled && env.webgl.supported) {\n      if (!fx) fx = env.browser ? new fxImage.GLImageFilter() : null; // && (typeof document !== 'undefined')\n      env.filter = !!fx;\n      if (!fx || !fx.add) {\n        if (config.debug) log('input process error: cannot initialize filters');\n        env.webgl.supported = false;\n        config.filter.enabled = false;\n        copy(inCanvas, outCanvas); // filter failed to initialize\n        // return { tensor: null, canvas: inCanvas };\n      } else {\n        fx.reset();\n        if (config.filter.brightness !== 0) fx.add('brightness', config.filter.brightness);\n        if (config.filter.contrast !== 0) fx.add('contrast', config.filter.contrast);\n        if (config.filter.sharpness !== 0) fx.add('sharpen', config.filter.sharpness);\n        if (config.filter.blur !== 0) fx.add('blur', config.filter.blur);\n        if (config.filter.saturation !== 0) fx.add('saturation', config.filter.saturation);\n        if (config.filter.hue !== 0) fx.add('hue', config.filter.hue);\n        if (config.filter.negative) fx.add('negative');\n        if (config.filter.sepia) fx.add('sepia');\n        if (config.filter.vintage) fx.add('brownie');\n        if (config.filter.sepia) fx.add('sepia');\n        if (config.filter.kodachrome) fx.add('kodachrome');\n        if (config.filter.technicolor) fx.add('technicolor');\n        if (config.filter.polaroid) fx.add('polaroid');\n        if (config.filter.pixelate !== 0) fx.add('pixelate', config.filter.pixelate);\n        if (fx.get() > 0) outCanvas = fx.apply(inCanvas);\n        else outCanvas = fx.draw(inCanvas);\n      }\n    } else {\n      copy(inCanvas, outCanvas); // if no filters applied, output canvas is input canvas\n      if (fx) fx = null;\n      env.filter = !!fx;\n    }\n\n    if (!getTensor) return { tensor: null, canvas: outCanvas }; // just canvas was requested\n    if (!outCanvas) throw new Error('canvas error: cannot create output');\n\n    // create tensor from image unless input was a tensor already\n    let pixels;\n    let depth = 3;\n    if ((typeof ImageData !== 'undefined' && input instanceof ImageData) || (input['data'] && input['width'] && input['height'])) { // if input is imagedata, just use it\n      if (env.browser && tf.browser) {\n        pixels = tf.browser ? tf.browser.fromPixels(input) : null;\n      } else {\n        depth = input['data'].length / input['height'] / input['width'];\n        // const arr = Uint8Array.from(input['data']);\n        const arr = new Uint8Array(input['data']['buffer']);\n        pixels = tf.tensor(arr, [input['height'], input['width'], depth], 'int32');\n      }\n    } else {\n      if (!tmpCanvas || (outCanvas.width !== tmpCanvas.width) || (outCanvas.height !== tmpCanvas.height)) tmpCanvas = canvas(outCanvas.width, outCanvas.height); // init output canvas\n      if (tf.browser && env.browser) {\n        if (config.backend === 'webgl' || config.backend === 'humangl' || config.backend === 'webgpu') {\n          pixels = tf.browser.fromPixels(outCanvas); // safe to reuse since both backend and context are gl based\n        } else {\n          tmpCanvas = copy(outCanvas); // cannot use output canvas as it already has gl context so we do a silly one more canvas\n          pixels = tf.browser.fromPixels(tmpCanvas);\n        }\n      } else {\n        const tempCanvas = copy(outCanvas); // cannot use output canvas as it already has gl context so we do a silly one more canvas\n        const tempCtx = tempCanvas.getContext('2d') as CanvasRenderingContext2D;\n        const tempData = tempCtx.getImageData(0, 0, targetWidth, targetHeight);\n        depth = tempData.data.length / targetWidth / targetHeight;\n        const arr = new Uint8Array(tempData.data.buffer);\n        pixels = tf.tensor(arr, [targetWidth, targetHeight, depth]);\n      }\n    }\n    if (depth === 4) { // rgba to rgb\n      const rgb = tf.slice3d(pixels, [0, 0, 0], [-1, -1, 3]); // strip alpha channel\n      tf.dispose(pixels);\n      pixels = rgb;\n    }\n    if (!pixels) throw new Error('input error: cannot create tensor');\n    const casted = tf.cast(pixels, 'float32');\n    const tensor = config.filter.equalization ? await enhance.histogramEqualization(casted) : tf.expandDims(casted, 0);\n    tf.dispose([pixels, casted]);\n    return { tensor, canvas: (config.filter.return ? outCanvas : null) };\n  }\n}\n\n/*\nconst checksum = async (input: Tensor): Promise<number> => { // use tf sum or js based sum loop depending on which is faster\n  const resizeFact = 48;\n  const reduced: Tensor = tf.image.resizeBilinear(input, [Math.trunc((input.shape[1] || 1) / resizeFact), Math.trunc((input.shape[2] || 1) / resizeFact)]);\n  const tfSum = async (): Promise<number> => {\n    const sumT = tf.sum(reduced);\n    const sum0 = await sumT.data();\n    tf.dispose(sumT);\n    return sum0[0];\n  };\n  const jsSum = async (): Promise<number> => {\n    const reducedData = await reduced.data(); // raw image rgb array\n    let sum0 = 0;\n    for (let i = 0; i < reducedData.length / 3; i++) sum0 += reducedData[3 * i + 2]; // look only at green value of each pixel\n    return sum0;\n  };\n  if (last.sumMethod === 0) {\n    const t0 = now();\n    await jsSum();\n    const t1 = now();\n    await tfSum();\n    const t2 = now();\n    last.sumMethod = t1 - t0 < t2 - t1 ? 1 : 2;\n  }\n  const res = last.sumMethod === 1 ? await jsSum() : await tfSum();\n  tf.dispose(reduced);\n  return res;\n};\n*/\n\nexport async function skip(config: Partial<Config>, input: Tensor) {\n  let skipFrame = false;\n  if (config.cacheSensitivity === 0 || !input.shape || input.shape.length !== 4 || input.shape[1] > 2048 || input.shape[2] > 2048) return skipFrame; // cache disabled or input is invalid or too large for cache analysis\n\n  /*\n  const checkSum = await checksum(input);\n  const diff = 100 * (Math.max(checkSum, last.inputSum) / Math.min(checkSum, last.inputSum) - 1);\n  last.inputSum = checkSum;\n  // if previous frame was skipped, skip this frame if changed more than cacheSensitivity\n  // if previous frame was not skipped, then look for cacheSensitivity or difference larger than one in previous frame to avoid resetting cache in subsequent frames unnecessarily\n  let skipFrame = diff < Math.max(config.cacheSensitivity, last.cacheDiff);\n  // if difference is above 10x threshold, don't use last value to force reset cache for significant change of scenes or images\n  last.cacheDiff = diff > 10 * config.cacheSensitivity ? 0 : diff;\n  skipFrame = skipFrame && (last.cacheDiff > 0); // if no cached diff value then force no skip\n  */\n\n  if (!last.inputTensor) {\n    last.inputTensor = tf.clone(input);\n  } else if (last.inputTensor.shape[1] !== input.shape[1] || last.inputTensor.shape[2] !== input.shape[2]) { // input resolution changed\n    tf.dispose(last.inputTensor);\n    last.inputTensor = tf.clone(input);\n  } else {\n    const t: Record<string, Tensor> = {};\n    t.diff = tf.sub(input, last.inputTensor);\n    t.squared = tf.mul(t.diff, t.diff);\n    t.sum = tf.sum(t.squared);\n    const diffSum = await t.sum.data();\n    const diffRelative = diffSum[0] / (input.shape[1] || 1) / (input.shape[2] || 1) / 255 / 3; // squared difference relative to input resolution and averaged per channel\n    tf.dispose([last.inputTensor, t.diff, t.squared, t.sum]);\n    last.inputTensor = tf.clone(input);\n    skipFrame = diffRelative <= (config.cacheSensitivity || 0);\n  }\n  return skipFrame;\n}\n\nexport async function compare(config: Partial<Config>, input1: Tensor, input2: Tensor): Promise<number> {\n  const t: Record<string, Tensor> = {};\n  if (!input1 || !input2 || input1.shape.length !== 4 || input1.shape.length !== input2.shape.length) {\n    if (!config.debug) log('invalid input tensor or tensor shapes do not match:', input1.shape, input2.shape);\n    return 0;\n  }\n  if (input1.shape[0] !== 1 || input2.shape[0] !== 1 || input1.shape[3] !== 3 || input2.shape[3] !== 3) {\n    if (!config.debug) log('input tensors must be of shape [1, height, width, 3]:', input1.shape, input2.shape);\n    return 0;\n  }\n  t.input1 = tf.clone(input1);\n  t.input2 = (input1.shape[1] !== input2.shape[1] || input1.shape[2] !== input2.shape[2]) ? tf.image.resizeBilinear(input2, [input1.shape[1], input1.shape[2]]) : tf.clone(input2);\n  t.diff = tf.sub(t.input1, t.input2);\n  t.squared = tf.mul(t.diff, t.diff);\n  t.sum = tf.sum(t.squared);\n  const diffSum = await t.sum.data();\n  const diffRelative = diffSum[0] / (input1.shape[1] || 1) / (input1.shape[2] || 1) / 255 / 3;\n  tf.dispose([t.input1, t.input2, t.diff, t.squared, t.sum]);\n  return diffRelative;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as image from '../image/image';\n\n/** Env class that holds detected capabilities */\nexport class Env {\n  /** Running in Browser */\n  browser: boolean;\n  /** Running in NodeJS */\n  node: boolean;\n  /** Running in WebWorker thread */\n  worker: boolean;\n  /** Detected platform */\n  platform: string = '';\n  /** Detected agent */\n  agent: string = '';\n  /** List of supported backends */\n  backends: string[] = [];\n  /** Has any work been performed so far */\n  initial: boolean;\n  /** Are image filters supported? */\n  filter: boolean | undefined;\n  /** TFJS instance details */\n  tfjs: {\n    version: undefined | string,\n  };\n  /** Is offscreenCanvas supported? */\n  offscreen: undefined | boolean;\n  /** Are performance counter instant values or additive */\n  perfadd: boolean = false;\n  /** WASM detected capabilities */\n  wasm: {\n    supported: undefined | boolean,\n    backend: undefined | boolean,\n    simd: undefined | boolean,\n    multithread: undefined | boolean,\n  } = {\n      supported: undefined,\n      backend: undefined,\n      simd: undefined,\n      multithread: undefined,\n    };\n  /** WebGL detected capabilities */\n  webgl: {\n    supported: undefined | boolean,\n    backend: undefined | boolean,\n    version: undefined | string,\n    renderer: undefined | string,\n  } = {\n      supported: undefined,\n      backend: undefined,\n      version: undefined,\n      renderer: undefined,\n    };\n  /** WebGPU detected capabilities */\n  webgpu: {\n    supported: undefined | boolean,\n    backend: undefined | boolean,\n    adapter: undefined | string,\n  } = {\n      supported: undefined,\n      backend: undefined,\n      adapter: undefined,\n    };\n  /** CPU info */\n  cpu: {\n    model: undefined | string,\n    flags: string[],\n  } = {\n      model: undefined,\n      flags: [],\n    };\n  /** List of supported kernels for current backend */\n  kernels: string[] = [];\n  /** MonkeyPatch for Canvas */\n  Canvas: undefined;\n  /** MonkeyPatch for Image */\n  Image: undefined;\n  /** MonkeyPatch for ImageData */\n  ImageData: undefined;\n\n  constructor() {\n    this.browser = typeof navigator !== 'undefined';\n    this.node = (typeof process !== 'undefined') && (typeof process.versions !== 'undefined') && (typeof process.versions.node !== 'undefined');\n    this.tfjs = { version: tf.version['tfjs-core'] };\n    this.offscreen = typeof OffscreenCanvas !== 'undefined';\n    this.initial = true;\n    // @ts-ignore WorkerGlobalScope evaluated in browser only\n    this.worker = this.browser && this.offscreen ? (typeof WorkerGlobalScope !== 'undefined') : undefined;\n    if (typeof navigator !== 'undefined') {\n      const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n      if (raw && raw[0]) {\n        const platformMatch = raw[0].match(/\\(([^()]+)\\)/g);\n        this.platform = (platformMatch && platformMatch[0]) ? platformMatch[0].replace(/\\(|\\)/g, '') : '';\n        this.agent = navigator.userAgent.replace(raw[0], '');\n        if (this.platform[1]) this.agent = this.agent.replace(raw[1], '');\n        this.agent = this.agent.replace(/  /g, ' ');\n        // chrome offscreencanvas gpu memory leak\n        /*\n        const isChrome = env.agent.match(/Chrome\\/.[0-9]/g);\n        const verChrome = isChrome && isChrome[0] ? isChrome[0].split('/')[1] : 0;\n        if (verChrome > 92 && verChrome < 96) {\n          log('disabling offscreenCanvas due to browser error:', isChrome ? isChrome[0] : 'unknown');\n          this.offscreen = false;\n        }\n        */\n      }\n    } else if (typeof process !== 'undefined') {\n      this.platform = `${process.platform} ${process.arch}`;\n      this.agent = `NodeJS ${process.version}`;\n    }\n  }\n\n  /** update backend information */\n  async updateBackend() {\n    // analyze backends\n    this.backends = Object.keys(tf.engine().registryFactory);\n    this.wasm.supported = typeof WebAssembly !== 'undefined';\n    this.wasm.backend = this.backends.includes('wasm');\n    if (this.wasm.supported && this.wasm.backend && tf.getBackend() === 'wasm') {\n      this.wasm.simd = await tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n      this.wasm.multithread = await tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n    }\n    const c = image.canvas(100, 100);\n    const ctx = c ? c.getContext('webgl2') : undefined; // causes too many gl contexts\n    // const ctx = typeof tf.backend().getGPGPUContext !== undefined ? tf.backend().getGPGPUContext : null;\n    this.webgl.supported = typeof ctx !== 'undefined';\n    this.webgl.backend = this.backends.includes('webgl');\n    if (this.webgl.supported && this.webgl.backend && (tf.getBackend() === 'webgl' || tf.getBackend() === 'humangl')) {\n      // @ts-ignore getGPGPUContext only exists on WebGL backend\n      const gl = tf.backend().gpgpu !== 'undefined' ? await tf.backend().getGPGPUContext().gl : null;\n      if (gl) {\n        this.webgl.version = gl.getParameter(gl.VERSION);\n        this.webgl.renderer = gl.getParameter(gl.RENDERER);\n      }\n    }\n    // @ts-ignore navigator.gpu is only defined when webgpu is available in browser\n    this.webgpu.supported = this.browser && typeof navigator['gpu'] !== 'undefined';\n    this.webgpu.backend = this.backends.includes('webgpu');\n    try {\n      // @ts-ignore navigator.gpu is only defined when webgpu is available in browser\n      if (this.webgpu.supported) this.webgpu.adapter = (await navigator['gpu'].requestAdapter()).name;\n    } catch {\n      this.webgpu.supported = false;\n    }\n    try {\n      this.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => kernel.kernelName.toLowerCase());\n    } catch { /**/ }\n  }\n\n  /** update cpu information */\n  async updateCPU() {\n    const cpu = { model: '', flags: [] };\n    if (this.node && this.platform.startsWith('linux')) {\n      /*\n      const fs = require('fs');\n      try {\n        const data = fs.readFileSync('/proc/cpuinfo').toString();\n        for (const line of data.split('\\n')) {\n          if (line.startsWith('model name')) cpu.model = line.match(/:(.*)/g)[0].replace(':', '').trim();\n          if (line.startsWith('flags')) cpu.flags = line.match(/:(.*)/g)[0].replace(':', '').trim().split(' ').sort();\n        }\n      } catch { }\n      */\n    }\n    if (!this['cpu']) Object.defineProperty(this, 'cpu', { value: cpu });\n    else this['cpu'] = cpu;\n  }\n}\n\nexport const env = new Env();\n", "import { log, join } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { GraphModel } from './types';\nimport type { Config } from '../config';\nimport * as modelsDefs from '../../models/models.json';\n\nconst options = {\n  cacheModels: true,\n  cacheSupported: true,\n  verbose: true,\n  debug: false,\n  modelBasePath: '',\n};\n\nexport type ModelInfo = {\n  name: string,\n  inCache: boolean,\n  sizeDesired: number,\n  sizeFromManifest: number,\n  sizeLoadedWeights: number,\n}\n\nexport const modelStats: Record<string, ModelInfo> = {};\n\nasync function httpHandler(url, init?): Promise<Response | null> {\n  if (options.debug) log('load model fetch:', url, init);\n  return fetch(url, init);\n}\n\nexport function setModelLoadOptions(config: Config) {\n  options.cacheModels = config.cacheModels;\n  options.verbose = config.debug;\n  options.modelBasePath = config.modelBasePath;\n}\n\nexport async function loadModel(modelPath: string | undefined): Promise<GraphModel> {\n  let modelUrl = join(options.modelBasePath, modelPath || '');\n  if (!modelUrl.toLowerCase().endsWith('.json')) modelUrl += '.json';\n  const modelPathSegments = modelUrl.includes('/') ? modelUrl.split('/') : modelUrl.split('\\\\');\n  const shortModelName = modelPathSegments[modelPathSegments.length - 1].replace('.json', '');\n  const cachedModelName = 'indexeddb://' + shortModelName; // generate short model name for cache\n  modelStats[shortModelName] = {\n    name: shortModelName,\n    sizeFromManifest: 0,\n    sizeLoadedWeights: 0,\n    sizeDesired: modelsDefs[shortModelName],\n    inCache: false,\n  };\n  options.cacheSupported = (typeof window !== 'undefined') && (typeof window.localStorage !== 'undefined') && (typeof window.indexedDB !== 'undefined'); // check if running in browser and if indexedb is available\n  let cachedModels = {};\n  try {\n    cachedModels = (options.cacheSupported && options.cacheModels) ? await tf.io.listModels() : {}; // list all models already in cache // this fails for webview although localStorage is defined\n  } catch {\n    options.cacheSupported = false;\n  }\n  modelStats[shortModelName].inCache = (options.cacheSupported && options.cacheModels) && Object.keys(cachedModels).includes(cachedModelName); // is model found in cache\n  const tfLoadOptions = typeof fetch === 'undefined' ? {} : { fetchFunc: (url, init?) => httpHandler(url, init) };\n  const model: GraphModel = new tf.GraphModel(modelStats[shortModelName].inCache ? cachedModelName : modelUrl, tfLoadOptions) as unknown as GraphModel; // create model prototype and decide if load from cache or from original modelurl\n  let loaded = false;\n  try {\n    // @ts-ignore private function\n    model.findIOHandler(); // decide how to actually load a model\n    if (options.debug) log('model load handler:', model['handler']);\n    // @ts-ignore private property\n    const artifacts = await model.handler.load(); // load manifest\n    modelStats[shortModelName].sizeFromManifest = artifacts?.weightData?.byteLength || 0;\n    model.loadSync(artifacts); // load weights\n    // @ts-ignore private property\n    modelStats[shortModelName].sizeLoadedWeights = model?.artifacts?.weightData?.byteLength || 0;\n    if (options.verbose) log('load model:', model['modelUrl'], { bytes: modelStats[shortModelName].sizeLoadedWeights }, options);\n    loaded = true;\n  } catch (err) {\n    log('error loading model:', modelUrl, err);\n  }\n  if (loaded && options.cacheModels && options.cacheSupported && !modelStats[shortModelName].inCache) { // save model to cache\n    try {\n      const saveResult = await model.save(cachedModelName);\n      log('model saved:', cachedModelName, saveResult);\n    } catch (err) {\n      log('error saving model:', modelUrl, err);\n    }\n  }\n  return model;\n}\n", "/**\n * Loader and Validator for all models used by Human\n */\n\nimport { env } from './util/env';\nimport { log } from './util/util';\nimport * as gear from './gear/gear';\nimport * as ssrnetAge from './gear/ssrnet-age';\nimport * as ssrnetGender from './gear/ssrnet-gender';\nimport * as antispoof from './face/antispoof';\nimport * as blazeface from './face/blazeface';\nimport * as blazepose from './body/blazepose';\nimport * as centernet from './object/centernet';\nimport * as efficientpose from './body/efficientpose';\nimport * as emotion from './gear/emotion';\nimport * as mobilefacenet from './face/mobilefacenet';\nimport * as facemesh from './face/facemesh';\nimport * as faceres from './face/faceres';\nimport * as handpose from './hand/handpose';\nimport * as handtrack from './hand/handtrack';\nimport * as iris from './face/iris';\nimport * as liveness from './face/liveness';\nimport * as movenet from './body/movenet';\nimport * as nanodet from './object/nanodet';\nimport * as posenet from './body/posenet';\nimport * as segmentation from './segmentation/segmentation';\nimport { modelStats, ModelInfo } from './tfjs/load';\nimport type { GraphModel } from './tfjs/types';\nimport type { Human } from './human';\n\n/** Instances of all possible TFJS Graph Models used by Human\n * - loaded as needed based on configuration\n * - initialized explictly with `human.load()` method\n * - initialized implicity on first call to `human.detect()`\n * - each model can be `null` if not loaded, instance of `GraphModel` if loaded or `Promise` if loading\n */\nexport class Models {\n  ssrnetage: null | GraphModel | Promise<GraphModel> = null;\n  gear: null | GraphModel | Promise<GraphModel> = null;\n  blazeposedetect: null | GraphModel | Promise<GraphModel> = null;\n  blazepose: null | GraphModel | Promise<GraphModel> = null;\n  centernet: null | GraphModel | Promise<GraphModel> = null;\n  efficientpose: null | GraphModel | Promise<GraphModel> = null;\n  mobilefacenet: null | GraphModel | Promise<GraphModel> = null;\n  emotion: null | GraphModel | Promise<GraphModel> = null;\n  facedetect: null | GraphModel | Promise<GraphModel> = null;\n  faceiris: null | GraphModel | Promise<GraphModel> = null;\n  facemesh: null | GraphModel | Promise<GraphModel> = null;\n  faceres: null | GraphModel | Promise<GraphModel> = null;\n  ssrnetgender: null | GraphModel | Promise<GraphModel> = null;\n  handpose: null | GraphModel | Promise<GraphModel> = null;\n  handskeleton: null | GraphModel | Promise<GraphModel> = null;\n  handtrack: null | GraphModel | Promise<GraphModel> = null;\n  liveness: null | GraphModel | Promise<GraphModel> = null;\n  movenet: null | GraphModel | Promise<GraphModel> = null;\n  nanodet: null | GraphModel | Promise<GraphModel> = null;\n  posenet: null | GraphModel | Promise<GraphModel> = null;\n  segmentation: null | GraphModel | Promise<GraphModel> = null;\n  antispoof: null | GraphModel | Promise<GraphModel> = null;\n}\n\nexport type ModelStats = {\n  numLoadedModels: number,\n  numEnabledModels: undefined,\n  numDefinedModels: number,\n  percentageLoaded: number,\n  totalSizeFromManifest: number,\n  totalSizeWeights: number,\n  totalSizeLoading: number,\n  totalSizeEnabled: undefined,\n  modelStats: ModelInfo[],\n}\n\nexport const getModelStats = (instance: Human): ModelStats => {\n  let totalSizeFromManifest = 0;\n  let totalSizeWeights = 0;\n  let totalSizeLoading = 0;\n  for (const m of Object.values(modelStats)) {\n    totalSizeFromManifest += m.sizeFromManifest;\n    totalSizeWeights += m.sizeLoadedWeights;\n    totalSizeLoading += m.sizeDesired;\n  }\n  const percentageLoaded = totalSizeLoading > 0 ? totalSizeWeights / totalSizeLoading : 0;\n  return {\n    numLoadedModels: Object.values(modelStats).length,\n    numEnabledModels: undefined,\n    numDefinedModels: Object.keys(instance.models).length,\n    percentageLoaded,\n    totalSizeFromManifest,\n    totalSizeWeights,\n    totalSizeLoading,\n    totalSizeEnabled: undefined,\n    modelStats: Object.values(modelStats),\n  };\n};\n\nexport function reset(instance: Human): void {\n  // if (instance.config.debug) log('resetting loaded models');\n  for (const model of Object.keys(instance.models)) instance.models[model as keyof Models] = null;\n}\n\n/** Load method preloads all instance.configured models on-demand */\nexport async function load(instance: Human): Promise<void> {\n  if (env.initial) reset(instance);\n  if (instance.config.hand.enabled) { // handpose model is a combo that must be loaded as a whole\n    if (!instance.models.handpose && instance.config.hand.detector?.modelPath?.includes('handdetect')) {\n      [instance.models.handpose, instance.models.handskeleton] = await handpose.load(instance.config);\n    }\n    if (!instance.models.handskeleton && instance.config.hand.landmarks && instance.config.hand.detector?.modelPath?.includes('handdetect')) {\n      [instance.models.handpose, instance.models.handskeleton] = await handpose.load(instance.config);\n    }\n  }\n  if (instance.config.body.enabled && !instance.models.blazepose && instance.config.body?.modelPath?.includes('blazepose')) instance.models.blazepose = blazepose.loadPose(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.body.enabled && !instance.models.blazeposedetect && instance.config.body['detector'] && instance.config.body['detector']['modelPath']) instance.models.blazeposedetect = blazepose.loadDetect(instance.config);\n  if (instance.config.body.enabled && !instance.models.efficientpose && instance.config.body?.modelPath?.includes('efficientpose')) instance.models.efficientpose = efficientpose.load(instance.config);\n  if (instance.config.body.enabled && !instance.models.movenet && instance.config.body?.modelPath?.includes('movenet')) instance.models.movenet = movenet.load(instance.config);\n  if (instance.config.body.enabled && !instance.models.posenet && instance.config.body?.modelPath?.includes('posenet')) instance.models.posenet = posenet.load(instance.config);\n  if (instance.config.face.enabled && !instance.models.facedetect) instance.models.facedetect = blazeface.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.antispoof?.enabled && !instance.models.antispoof) instance.models.antispoof = antispoof.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.liveness?.enabled && !instance.models.liveness) instance.models.liveness = liveness.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.description?.enabled && !instance.models.faceres) instance.models.faceres = faceres.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.emotion?.enabled && !instance.models.emotion) instance.models.emotion = emotion.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.iris?.enabled && !instance.config.face.attention?.enabled && !instance.models.faceiris) instance.models.faceiris = iris.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.mesh?.enabled && !instance.models.facemesh) instance.models.facemesh = facemesh.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['gear']?.enabled && !instance.models.gear) instance.models.gear = gear.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['ssrnet']?.enabled && !instance.models.ssrnetage) instance.models.ssrnetage = ssrnetAge.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['ssrnet']?.enabled && !instance.models.ssrnetgender) instance.models.ssrnetgender = ssrnetGender.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['mobilefacenet']?.enabled && !instance.models.mobilefacenet) instance.models.mobilefacenet = mobilefacenet.load(instance.config);\n  if (instance.config.hand.enabled && !instance.models.handtrack && instance.config.hand.detector?.modelPath?.includes('handtrack')) instance.models.handtrack = handtrack.loadDetect(instance.config);\n  if (instance.config.hand.enabled && instance.config.hand.landmarks && !instance.models.handskeleton && instance.config.hand.detector?.modelPath?.includes('handtrack')) instance.models.handskeleton = handtrack.loadSkeleton(instance.config);\n  if (instance.config.object.enabled && !instance.models.centernet && instance.config.object?.modelPath?.includes('centernet')) instance.models.centernet = centernet.load(instance.config);\n  if (instance.config.object.enabled && !instance.models.nanodet && instance.config.object?.modelPath?.includes('nanodet')) instance.models.nanodet = nanodet.load(instance.config);\n  if (instance.config.segmentation.enabled && !instance.models.segmentation) instance.models.segmentation = segmentation.load(instance.config);\n\n  // models are loaded in parallel asynchronously so lets wait until they are actually loaded\n  for await (const model of Object.keys(instance.models)) {\n    if (instance.models[model as keyof Models] && typeof instance.models[model as keyof Models] !== 'undefined') {\n      instance.models[model as keyof Models] = await instance.models[model as keyof Models];\n    }\n  }\n}\n\nexport async function validate(instance: Human): Promise<void> {\n  interface Op { name: string, category: string, op: string }\n  const simpleOps = ['const', 'placeholder', 'noop', 'pad', 'squeeze', 'add', 'sub', 'mul', 'div'];\n  for (const defined of Object.keys(instance.models)) {\n    const model: GraphModel | null = instance.models[defined as keyof Models] as GraphModel | null;\n    if (!model) continue;\n    const ops: string[] = [];\n    // @ts-ignore // executor is a private method\n    const executor = model?.executor;\n    if (executor && executor.graph.nodes) {\n      for (const kernel of Object.values(executor.graph.nodes)) {\n        const op = (kernel as Op).op.toLowerCase();\n        if (!ops.includes(op)) ops.push(op);\n      }\n    } else {\n      if (!executor && instance.config.debug) log('model signature not determined:', defined);\n    }\n    const missing: string[] = [];\n    for (const op of ops) {\n      if (!simpleOps.includes(op) // exclude simple ops\n        && !instance.env.kernels.includes(op) // check actual kernel ops\n        && !instance.env.kernels.includes(op.replace('_', '')) // check variation without _\n        && !instance.env.kernels.includes(op.replace('native', '')) // check standard variation\n        && !instance.env.kernels.includes(op.replace('v2', ''))) { // check non-versioned variation\n        missing.push(op);\n      }\n    }\n    // log('model validation ops:', defined, ops);\n    if (instance.config.debug && missing.length > 0) log('model validation failed:', defined, missing);\n  }\n}\n", "/**\n * GEAR [gender/emotion/age/race] model implementation\n *\n * Based on: [**GEAR Predictor**](https://github.com/Udolf15/GEAR-Predictor)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { Gender, Race } from '../result';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport { env } from '../util/env';\n\nexport type GearType = { age: number, gender: Gender, genderScore: number, race: Array<{ score: number, race: Race }> }\nlet model: GraphModel | null;\nconst last: Array<GearType> = [];\nconst raceNames = ['white', 'black', 'asian', 'indian', 'other'];\nconst ageWeights = [15, 23, 28, 35.5, 45.5, 55.5, 65];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function load(config: Config) {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['gear']?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<GearType> {\n  if (!model) return { age: 0, gender: 'unknown', genderScore: 0, race: [] };\n  const skipFrame = skipped < (config.face['gear']?.skipFrames || 0);\n  const skipTime = (config.face['gear']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && last[idx]) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    if (!model?.inputs[0].shape) return;\n    const t: Record<string, Tensor> = {};\n    // t.resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape[2], model?.inputs[0].shape[1]], false);\n    const box = [[0.0, 0.10, 0.90, 0.90]]; // empyrical values for top, left, bottom, right\n    t.resize = tf.image.cropAndResize(image, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n    const obj: GearType = { age: 0, gender: 'unknown', genderScore: 0, race: [] };\n    if (config.face['gear']?.enabled) [t.age, t.gender, t.race] = model.execute(t.resize, ['age_output', 'gender_output', 'race_output']) as Tensor[];\n    const gender = await t.gender.data();\n    obj.gender = gender[0] > gender[1] ? 'male' : 'female';\n    obj.genderScore = Math.round(100 * (gender[0] > gender[1] ? gender[0] : gender[1])) / 100;\n    const race = await t.race.data();\n    for (let i = 0; i < race.length; i++) {\n      if (race[i] > (config.face['gear']?.minConfidence || 0.2)) obj.race.push({ score: Math.round(100 * race[i]) / 100, race: raceNames[i] as Race });\n    }\n    obj.race.sort((a, b) => b.score - a.score);\n    // {0: 'Below20', 1: '21-25', 2: '26-30', 3: '31-40',4: '41-50', 5: '51-60', 6: 'Above60'}\n    const ageDistribution = Array.from(await t.age.data());\n    const ageSorted = ageDistribution.map((a, i) => [ageWeights[i], a]).sort((a, b) => b[1] - a[1]);\n    let age = ageSorted[0][0]; // pick best starting point\n    for (let i = 1; i < ageSorted.length; i++) age += ageSorted[i][1] * (ageSorted[i][0] - age); // adjust with each other choice by weight\n    obj.age = Math.round(10 * age) / 10;\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    last[idx] = obj;\n    lastCount = count;\n    lastTime = now();\n    resolve(obj);\n  });\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from './types';\n\nexport const constants: Record<string, Tensor | number | number[]> = {\n  tf255: 255,\n  tf1: 1,\n  tf2: 2,\n  tf05: 0.5,\n  tf127: 127.5,\n  rgb: [0.2989, 0.5870, 0.1140],\n};\n\nexport function init() {\n  constants.tf255 = tf.scalar(255, 'float32');\n  constants.tf1 = tf.scalar(1, 'float32');\n  constants.tf2 = tf.scalar(2, 'float32');\n  constants.tf05 = tf.scalar(0.5, 'float32');\n  constants.tf127 = tf.scalar(127.5, 'float32');\n  constants.rgb = tf.tensor1d([0.2989, 0.5870, 0.1140], 'float32'); // factors for red/green/blue colors when converting to grayscale\n}\n", "/**\n * Age model implementation\n *\n * Based on: [**SSR-Net**](https://github.com/shamangary/SSR-Net)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { env } from '../util/env';\nimport { constants } from '../tfjs/constants';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\n\nlet model: GraphModel | null;\nconst last: Array<{ age: number }> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function load(config: Config) {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['ssrnet'].modelPathAge);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<{ age: number }> {\n  if (!model) return { age: 0 };\n  const skipFrame = skipped < (config.face['ssrnet']?.skipFrames || 0);\n  const skipTime = (config.face['ssrnet']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipFrame && skipTime && (lastCount === count) && last[idx]?.age && (last[idx]?.age > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    if (!model?.inputs || !model.inputs[0] || !model.inputs[0].shape) return;\n    const t: Record<string, Tensor> = {};\n    t.resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    t.enhance = tf.mul(t.resize, constants.tf255);\n    const obj = { age: 0 };\n    if (config.face['ssrnet'].enabled) t.age = model.execute(t.enhance) as Tensor;\n    if (t.age) {\n      const data = await t.age.data();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    last[idx] = obj;\n    lastCount = count;\n    lastTime = now();\n    resolve(obj);\n  });\n}\n", "/**\n * Gender model implementation\n *\n * Based on: [**SSR-Net**](https://github.com/shamangary/SSR-Net)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport type { Gender } from '../result';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst last: Array<{ gender: Gender, genderScore: number }> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function load(config: Config | any) {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['ssrnet'].modelPathGender);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function predict(image: Tensor, config: Config, idx, count): Promise<{ gender: Gender, genderScore: number }> {\n  if (!model) return { gender: 'unknown', genderScore: 0 };\n  const skipFrame = skipped < (config.face['ssrnet']?.skipFrames || 0);\n  const skipTime = (config.face['ssrnet']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipFrame && skipTime && (lastCount === count) && last[idx]?.gender && (last[idx]?.genderScore > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    if (!model?.inputs[0].shape) return;\n    const t: Record<string, Tensor> = {};\n    t.resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    t.enhance = tf.tidy(() => {\n      const [red, green, blue] = tf.split(t.resize, 3, 3);\n      const redNorm = tf.mul(red, rgb[0]);\n      const greenNorm = tf.mul(green, rgb[1]);\n      const blueNorm = tf.mul(blue, rgb[2]);\n      const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n      const normalize = tf.mul(tf.sub(grayscale, constants.tf05), 2); // range grayscale:-1..1\n      return normalize;\n    });\n    const obj: { gender: Gender, genderScore: number } = { gender: 'unknown', genderScore: 0 };\n    if (config.face['ssrnet'].enabled) t.gender = model.execute(t.enhance) as Tensor;\n    const data = await t.gender.data();\n    obj.gender = data[0] > data[1] ? 'female' : 'male'; // returns two values 0..1, bigger one is prediction\n    obj.genderScore = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    last[idx] = obj;\n    lastCount = count;\n    lastTime = now();\n    resolve(obj);\n  });\n}\n", "/**\n * Anti-spoofing model implementation\n */\n\nimport { log, now } from '../util/util';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst cached: Array<number> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet lastCount = 0;\nlet lastTime = 0;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.antispoof?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<number> {\n  if (!model) return 0;\n  const skipTime = (config.face.antispoof?.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.face.antispoof?.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && cached[idx]) {\n    skipped++;\n    return cached[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape ? model.inputs[0].shape[2] : 0, model?.inputs[0].shape ? model.inputs[0].shape[1] : 0], false);\n    const res = model?.execute(resize) as Tensor;\n    const num = (await res.data())[0];\n    cached[idx] = Math.round(100 * num) / 100;\n    lastCount = count;\n    lastTime = now();\n    tf.dispose([resize, res]);\n    resolve(cached[idx]);\n  });\n}\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n * See `facemesh.ts` for entry point\n */\n\nexport const meshAnnotations: Record<string, number[]> = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  // lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291], // 11\n  // lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291], // 10\n  // lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308], // 11\n  // lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308], // 11\n  lipsUpperOuter: [185, 40, 39, 37, 0, 267, 269, 270, 409],\n  lipsLowerOuter: [61, 146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [191, 80, 81, 82, 13, 312, 311, 310, 415],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  lipsLowerSemiOuter: [76, 77, 90, 180, 85, 16, 315, 404, 320, 307, 306],\n  lipsUpperSemiOuter: [184, 74, 73, 72, 11, 302, 303, 304, 408],\n  lipsLowerSemiInner: [62, 96, 89, 179, 86, 15, 316, 403, 319, 325, 292],\n  lipsUpperSemiInner: [183, 42, 41, 38, 12, 268, 271, 272, 407],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173], // 7\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133], // 9\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190], // 7\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243], // 9\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189], // 7\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244], // 9\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245], // 9\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193], // 8\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65], // 6\n  rightEyeIris: [473, 474, 475, 476, 477], // 5\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const meshLandmarks: Record<string, number | number[]> = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, meshAnnotations['midwayBetweenEyes'][0]],\n};\n\nexport const blazeFaceLandmarks: Record<string, number | number[]> = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nexport const irisIndices: Array<{ key: string, indices: number[] }> = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] }, // 7 x 3d\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] }, // 7 x 3d\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] }, // 7 x 3d\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] }, // 7 x 3d\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] }, // 9 x 3d\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] }, // 9 x 3d\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] }, // 9 x 3d\n  { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] }, // 8 x 3d\n  { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] }, // 6 x 3d\n];\n\nexport const UV468: [number, number][] = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 0.547487020492554],\n  [0.499974012374878, 0.602371990680695],\n  [0.482113003730774, 0.471979022026062],\n  [0.500150978565216, 0.527155995368958],\n  [0.499909996986389, 0.498252987861633],\n  [0.499523013830185, 0.40106201171875],\n  [0.289712011814117, 0.380764007568359],\n  [0.499954998493195, 0.312398016452789],\n  [0.499987006187439, 0.269918978214264],\n  [0.500023007392883, 0.107050001621246],\n  [0.500023007392883, 0.666234016418457],\n  [0.5000159740448, 0.679224014282227],\n  [0.500023007392883, 0.692348003387451],\n  [0.499976992607117, 0.695277988910675],\n  [0.499976992607117, 0.70593398809433],\n  [0.499976992607117, 0.719385027885437],\n  [0.499976992607117, 0.737019002437592],\n  [0.499967992305756, 0.781370997428894],\n  [0.499816000461578, 0.562981009483337],\n  [0.473773002624512, 0.573909997940063],\n  [0.104906998574734, 0.254140973091125],\n  [0.365929991006851, 0.409575998783112],\n  [0.338757991790771, 0.41302502155304],\n  [0.311120003461838, 0.409460008144379],\n  [0.274657994508743, 0.389131009578705],\n  [0.393361985683441, 0.403706014156342],\n  [0.345234006643295, 0.344011008739471],\n  [0.370094001293182, 0.346076011657715],\n  [0.319321990013123, 0.347265005111694],\n  [0.297903001308441, 0.353591024875641],\n  [0.24779200553894, 0.410809993743896],\n  [0.396889001131058, 0.842755019664764],\n  [0.280097991228104, 0.375599980354309],\n  [0.106310002505779, 0.399955987930298],\n  [0.2099249958992, 0.391353011131287],\n  [0.355807989835739, 0.534406006336212],\n  [0.471751004457474, 0.65040397644043],\n  [0.474155008792877, 0.680191993713379],\n  [0.439785003662109, 0.657229006290436],\n  [0.414617002010345, 0.66654098033905],\n  [0.450374007225037, 0.680860996246338],\n  [0.428770989179611, 0.682690978050232],\n  [0.374971002340317, 0.727805018424988],\n  [0.486716985702515, 0.547628998756409],\n  [0.485300987958908, 0.527395009994507],\n  [0.257764995098114, 0.314490020275116],\n  [0.401223003864288, 0.455172002315521],\n  [0.429818987846375, 0.548614978790283],\n  [0.421351999044418, 0.533740997314453],\n  [0.276895999908447, 0.532056987285614],\n  [0.483370006084442, 0.499586999416351],\n  [0.33721199631691, 0.282882988452911],\n  [0.296391993761063, 0.293242990970612],\n  [0.169294998049736, 0.193813979625702],\n  [0.447580009698868, 0.302609980106354],\n  [0.392390012741089, 0.353887975215912],\n  [0.354490011930466, 0.696784019470215],\n  [0.067304998636246, 0.730105042457581],\n  [0.442739009857178, 0.572826027870178],\n  [0.457098007202148, 0.584792017936707],\n  [0.381974011659622, 0.694710969924927],\n  [0.392388999462128, 0.694203019142151],\n  [0.277076005935669, 0.271932005882263],\n  [0.422551989555359, 0.563233017921448],\n  [0.385919004678726, 0.281364023685455],\n  [0.383103013038635, 0.255840003490448],\n  [0.331431001424789, 0.119714021682739],\n  [0.229923993349075, 0.232002973556519],\n  [0.364500999450684, 0.189113974571228],\n  [0.229622006416321, 0.299540996551514],\n  [0.173287004232407, 0.278747975826263],\n  [0.472878992557526, 0.666198015213013],\n  [0.446828007698059, 0.668527007102966],\n  [0.422762006521225, 0.673889994621277],\n  [0.445307999849319, 0.580065965652466],\n  [0.388103008270264, 0.693961024284363],\n  [0.403039008378983, 0.706539988517761],\n  [0.403629004955292, 0.693953037261963],\n  [0.460041999816895, 0.557139039039612],\n  [0.431158006191254, 0.692366003990173],\n  [0.452181994915009, 0.692366003990173],\n  [0.475387006998062, 0.692366003990173],\n  [0.465828001499176, 0.779190003871918],\n  [0.472328990697861, 0.736225962638855],\n  [0.473087012767792, 0.717857003211975],\n  [0.473122000694275, 0.704625964164734],\n  [0.473033010959625, 0.695277988910675],\n  [0.427942007780075, 0.695277988910675],\n  [0.426479011774063, 0.703539967536926],\n  [0.423162013292313, 0.711845993995667],\n  [0.4183090031147, 0.720062971115112],\n  [0.390094995498657, 0.639572978019714],\n  [0.013953999616206, 0.560034036636353],\n  [0.499913990497589, 0.58014702796936],\n  [0.413199990987778, 0.69539999961853],\n  [0.409626007080078, 0.701822996139526],\n  [0.468080013990402, 0.601534962654114],\n  [0.422728985548019, 0.585985004901886],\n  [0.463079988956451, 0.593783974647522],\n  [0.37211999297142, 0.47341400384903],\n  [0.334562003612518, 0.496073007583618],\n  [0.411671012639999, 0.546965003013611],\n  [0.242175996303558, 0.14767599105835],\n  [0.290776997804642, 0.201445996761322],\n  [0.327338010072708, 0.256527006626129],\n  [0.399509996175766, 0.748921036720276],\n  [0.441727995872498, 0.261676013469696],\n  [0.429764986038208, 0.187834024429321],\n  [0.412198007106781, 0.108901023864746],\n  [0.288955003023148, 0.398952007293701],\n  [0.218936994671822, 0.435410976409912],\n  [0.41278201341629, 0.398970007896423],\n  [0.257135003805161, 0.355440020561218],\n  [0.427684992551804, 0.437960982322693],\n  [0.448339998722076, 0.536936044692993],\n  [0.178560003638268, 0.45755398273468],\n  [0.247308000922203, 0.457193970680237],\n  [0.286267012357712, 0.467674970626831],\n  [0.332827985286713, 0.460712015628815],\n  [0.368755996227264, 0.447206974029541],\n  [0.398963987827301, 0.432654976844788],\n  [0.476410001516342, 0.405806005001068],\n  [0.189241006970406, 0.523923993110657],\n  [0.228962004184723, 0.348950982093811],\n  [0.490725994110107, 0.562400996685028],\n  [0.404670000076294, 0.485132992267609],\n  [0.019469000399113, 0.401564002037048],\n  [0.426243007183075, 0.420431017875671],\n  [0.396993011236191, 0.548797011375427],\n  [0.266469985246658, 0.376977026462555],\n  [0.439121007919312, 0.51895797252655],\n  [0.032313998788595, 0.644356966018677],\n  [0.419054001569748, 0.387154996395111],\n  [0.462783008813858, 0.505746960639954],\n  [0.238978996872902, 0.779744982719421],\n  [0.198220998048782, 0.831938028335571],\n  [0.107550002634525, 0.540755033493042],\n  [0.183610007166862, 0.740257024765015],\n  [0.134409993886948, 0.333683013916016],\n  [0.385764002799988, 0.883153975009918],\n  [0.490967005491257, 0.579378008842468],\n  [0.382384985685349, 0.508572995662689],\n  [0.174399003386497, 0.397670984268188],\n  [0.318785011768341, 0.39623498916626],\n  [0.343364000320435, 0.400596976280212],\n  [0.396100014448166, 0.710216999053955],\n  [0.187885001301765, 0.588537991046906],\n  [0.430987000465393, 0.944064974784851],\n  [0.318993002176285, 0.898285031318665],\n  [0.266247987747192, 0.869701027870178],\n  [0.500023007392883, 0.190576016902924],\n  [0.499976992607117, 0.954452991485596],\n  [0.366169989109039, 0.398822009563446],\n  [0.393207013607025, 0.39553701877594],\n  [0.410373002290726, 0.391080021858215],\n  [0.194993004202843, 0.342101991176605],\n  [0.388664990663528, 0.362284004688263],\n  [0.365961998701096, 0.355970978736877],\n  [0.343364000320435, 0.355356991291046],\n  [0.318785011768341, 0.35834002494812],\n  [0.301414996385574, 0.363156020641327],\n  [0.058132998645306, 0.319076001644135],\n  [0.301414996385574, 0.387449026107788],\n  [0.499987989664078, 0.618434011936188],\n  [0.415838003158569, 0.624195992946625],\n  [0.445681989192963, 0.566076993942261],\n  [0.465844005346298, 0.620640993118286],\n  [0.49992299079895, 0.351523995399475],\n  [0.288718998432159, 0.819945991039276],\n  [0.335278987884521, 0.852819979190826],\n  [0.440512001514435, 0.902418971061707],\n  [0.128294005990028, 0.791940987110138],\n  [0.408771991729736, 0.373893976211548],\n  [0.455606997013092, 0.451801002025604],\n  [0.499877005815506, 0.908990025520325],\n  [0.375436991453171, 0.924192011356354],\n  [0.11421000212431, 0.615022003650665],\n  [0.448662012815475, 0.695277988910675],\n  [0.4480200111866, 0.704632043838501],\n  [0.447111994028091, 0.715808033943176],\n  [0.444831997156143, 0.730794012546539],\n  [0.430011987686157, 0.766808986663818],\n  [0.406787008047104, 0.685672998428345],\n  [0.400738000869751, 0.681069016456604],\n  [0.392399996519089, 0.677703022956848],\n  [0.367855995893478, 0.663918972015381],\n  [0.247923001646996, 0.601333022117615],\n  [0.452769994735718, 0.420849978923798],\n  [0.43639200925827, 0.359887003898621],\n  [0.416164010763168, 0.368713974952698],\n  [0.413385987281799, 0.692366003990173],\n  [0.228018000721931, 0.683571994304657],\n  [0.468268007040024, 0.352671027183533],\n  [0.411361992359161, 0.804327011108398],\n  [0.499989002943039, 0.469825029373169],\n  [0.479153990745544, 0.442654013633728],\n  [0.499974012374878, 0.439637005329132],\n  [0.432112008333206, 0.493588984012604],\n  [0.499886006116867, 0.866917014122009],\n  [0.49991300702095, 0.821729004383087],\n  [0.456548988819122, 0.819200992584229],\n  [0.344549000263214, 0.745438992977142],\n  [0.37890899181366, 0.574010014533997],\n  [0.374292999505997, 0.780184984207153],\n  [0.319687992334366, 0.570737957954407],\n  [0.357154995203018, 0.604269981384277],\n  [0.295284003019333, 0.621580958366394],\n  [0.447750002145767, 0.862477004528046],\n  [0.410986006259918, 0.508723020553589],\n  [0.31395098567009, 0.775308012962341],\n  [0.354128003120422, 0.812552988529205],\n  [0.324548006057739, 0.703992962837219],\n  [0.189096003770828, 0.646299958229065],\n  [0.279776990413666, 0.71465802192688],\n  [0.1338230073452, 0.682700991630554],\n  [0.336768001317978, 0.644733011722565],\n  [0.429883986711502, 0.466521978378296],\n  [0.455527991056442, 0.548622965812683],\n  [0.437114000320435, 0.558896005153656],\n  [0.467287987470627, 0.529924988746643],\n  [0.414712011814117, 0.335219979286194],\n  [0.37704598903656, 0.322777986526489],\n  [0.344107985496521, 0.320150971412659],\n  [0.312875986099243, 0.32233202457428],\n  [0.283526003360748, 0.333190023899078],\n  [0.241245999932289, 0.382785975933075],\n  [0.102986000478268, 0.468762993812561],\n  [0.267612010240555, 0.424560010433197],\n  [0.297879010438919, 0.433175981044769],\n  [0.333433985710144, 0.433878004550934],\n  [0.366427004337311, 0.426115989685059],\n  [0.396012008190155, 0.416696012020111],\n  [0.420121014118195, 0.41022801399231],\n  [0.007561000064015, 0.480777025222778],\n  [0.432949006557465, 0.569517970085144],\n  [0.458638995885849, 0.479089021682739],\n  [0.473466008901596, 0.545744001865387],\n  [0.476087987422943, 0.563830018043518],\n  [0.468472003936768, 0.555056989192963],\n  [0.433990985155106, 0.582361996173859],\n  [0.483518004417419, 0.562983989715576],\n  [0.482482999563217, 0.57784903049469],\n  [0.42645001411438, 0.389798998832703],\n  [0.438998997211456, 0.39649498462677],\n  [0.450067013502121, 0.400434017181396],\n  [0.289712011814117, 0.368252992630005],\n  [0.276670008897781, 0.363372981548309],\n  [0.517862021923065, 0.471948027610779],\n  [0.710287988185883, 0.380764007568359],\n  [0.526226997375488, 0.573909997940063],\n  [0.895093023777008, 0.254140973091125],\n  [0.634069979190826, 0.409575998783112],\n  [0.661242008209229, 0.41302502155304],\n  [0.688880026340485, 0.409460008144379],\n  [0.725341975688934, 0.389131009578705],\n  [0.606630027294159, 0.40370500087738],\n  [0.654766023159027, 0.344011008739471],\n  [0.629905998706818, 0.346076011657715],\n  [0.680678009986877, 0.347265005111694],\n  [0.702096998691559, 0.353591024875641],\n  [0.75221198797226, 0.410804986953735],\n  [0.602918028831482, 0.842862963676453],\n  [0.719901978969574, 0.375599980354309],\n  [0.893692970275879, 0.399959981441498],\n  [0.790081977844238, 0.391354024410248],\n  [0.643998026847839, 0.534487962722778],\n  [0.528249025344849, 0.65040397644043],\n  [0.525849997997284, 0.680191040039062],\n  [0.560214996337891, 0.657229006290436],\n  [0.585384011268616, 0.66654098033905],\n  [0.549625992774963, 0.680860996246338],\n  [0.57122802734375, 0.682691991329193],\n  [0.624852001667023, 0.72809898853302],\n  [0.513050019741058, 0.547281980514526],\n  [0.51509702205658, 0.527251958847046],\n  [0.742246985435486, 0.314507007598877],\n  [0.598631024360657, 0.454979002475739],\n  [0.570338010787964, 0.548575043678284],\n  [0.578631997108459, 0.533622980117798],\n  [0.723087012767792, 0.532054007053375],\n  [0.516445994377136, 0.499638974666595],\n  [0.662801027297974, 0.282917976379395],\n  [0.70362401008606, 0.293271005153656],\n  [0.830704987049103, 0.193813979625702],\n  [0.552385985851288, 0.302568018436432],\n  [0.607609987258911, 0.353887975215912],\n  [0.645429015159607, 0.696707010269165],\n  [0.932694971561432, 0.730105042457581],\n  [0.557260990142822, 0.572826027870178],\n  [0.542901992797852, 0.584792017936707],\n  [0.6180260181427, 0.694710969924927],\n  [0.607590973377228, 0.694203019142151],\n  [0.722943007946014, 0.271963000297546],\n  [0.577413976192474, 0.563166975975037],\n  [0.614082992076874, 0.281386971473694],\n  [0.616907000541687, 0.255886018276215],\n  [0.668509006500244, 0.119913995265961],\n  [0.770092010498047, 0.232020974159241],\n  [0.635536015033722, 0.189248979091644],\n  [0.77039098739624, 0.299556016921997],\n  [0.826722025871277, 0.278755009174347],\n  [0.527121007442474, 0.666198015213013],\n  [0.553171992301941, 0.668527007102966],\n  [0.577238023281097, 0.673889994621277],\n  [0.554691970348358, 0.580065965652466],\n  [0.611896991729736, 0.693961024284363],\n  [0.59696102142334, 0.706539988517761],\n  [0.596370995044708, 0.693953037261963],\n  [0.539958000183105, 0.557139039039612],\n  [0.568841993808746, 0.692366003990173],\n  [0.547818005084991, 0.692366003990173],\n  [0.52461302280426, 0.692366003990173],\n  [0.534089982509613, 0.779141008853912],\n  [0.527670979499817, 0.736225962638855],\n  [0.526912987232208, 0.717857003211975],\n  [0.526877999305725, 0.704625964164734],\n  [0.526966989040375, 0.695277988910675],\n  [0.572058022022247, 0.695277988910675],\n  [0.573521018028259, 0.703539967536926],\n  [0.57683801651001, 0.711845993995667],\n  [0.581691026687622, 0.720062971115112],\n  [0.609944999217987, 0.639909982681274],\n  [0.986046016216278, 0.560034036636353],\n  [0.5867999792099, 0.69539999961853],\n  [0.590372025966644, 0.701822996139526],\n  [0.531915009021759, 0.601536989212036],\n  [0.577268004417419, 0.585934996604919],\n  [0.536915004253387, 0.593786001205444],\n  [0.627542972564697, 0.473352015018463],\n  [0.665585994720459, 0.495950996875763],\n  [0.588353991508484, 0.546862006187439],\n  [0.757824003696442, 0.14767599105835],\n  [0.709249973297119, 0.201507985591888],\n  [0.672684013843536, 0.256581008434296],\n  [0.600408971309662, 0.74900496006012],\n  [0.55826598405838, 0.261672019958496],\n  [0.570303976535797, 0.187870979309082],\n  [0.588165998458862, 0.109044015407562],\n  [0.711045026779175, 0.398952007293701],\n  [0.781069993972778, 0.435405015945435],\n  [0.587247014045715, 0.398931980133057],\n  [0.742869973182678, 0.355445981025696],\n  [0.572156012058258, 0.437651991844177],\n  [0.55186802148819, 0.536570012569427],\n  [0.821442008018494, 0.457556009292603],\n  [0.752701997756958, 0.457181990146637],\n  [0.71375697851181, 0.467626988887787],\n  [0.66711300611496, 0.460672974586487],\n  [0.631101012229919, 0.447153985500336],\n  [0.6008620262146, 0.432473003864288],\n  [0.523481011390686, 0.405627012252808],\n  [0.810747981071472, 0.523926019668579],\n  [0.771045982837677, 0.348959028720856],\n  [0.509127020835876, 0.562718033790588],\n  [0.595292985439301, 0.485023975372314],\n  [0.980530977249146, 0.401564002037048],\n  [0.573499977588654, 0.420000016689301],\n  [0.602994978427887, 0.548687994480133],\n  [0.733529984951019, 0.376977026462555],\n  [0.560611009597778, 0.519016981124878],\n  [0.967685997486115, 0.644356966018677],\n  [0.580985009670258, 0.387160003185272],\n  [0.537728011608124, 0.505385041236877],\n  [0.760966002941132, 0.779752969741821],\n  [0.801778972148895, 0.831938028335571],\n  [0.892440974712372, 0.54076099395752],\n  [0.816350996494293, 0.740260004997253],\n  [0.865594983100891, 0.333687007427216],\n  [0.614073991775513, 0.883246004581451],\n  [0.508952975273132, 0.579437971115112],\n  [0.617941975593567, 0.508316040039062],\n  [0.825608015060425, 0.397674977779388],\n  [0.681214988231659, 0.39623498916626],\n  [0.656635999679565, 0.400596976280212],\n  [0.603900015354156, 0.710216999053955],\n  [0.81208598613739, 0.588539004325867],\n  [0.56801301240921, 0.944564998149872],\n  [0.681007981300354, 0.898285031318665],\n  [0.733752012252808, 0.869701027870178],\n  [0.633830010890961, 0.398822009563446],\n  [0.606792986392975, 0.39553701877594],\n  [0.589659988880157, 0.391062021255493],\n  [0.805015981197357, 0.342108011245728],\n  [0.611334979534149, 0.362284004688263],\n  [0.634037971496582, 0.355970978736877],\n  [0.656635999679565, 0.355356991291046],\n  [0.681214988231659, 0.35834002494812],\n  [0.698584973812103, 0.363156020641327],\n  [0.941866993904114, 0.319076001644135],\n  [0.698584973812103, 0.387449026107788],\n  [0.584177017211914, 0.624107003211975],\n  [0.554318010807037, 0.566076993942261],\n  [0.534153997898102, 0.62064003944397],\n  [0.711217999458313, 0.819975018501282],\n  [0.664629995822906, 0.852871000766754],\n  [0.559099972248077, 0.902631998062134],\n  [0.871706008911133, 0.791940987110138],\n  [0.591234028339386, 0.373893976211548],\n  [0.544341027736664, 0.451583981513977],\n  [0.624562978744507, 0.924192011356354],\n  [0.88577002286911, 0.615028977394104],\n  [0.551338016986847, 0.695277988910675],\n  [0.551980018615723, 0.704632043838501],\n  [0.552887976169586, 0.715808033943176],\n  [0.555167973041534, 0.730794012546539],\n  [0.569944024085999, 0.767035007476807],\n  [0.593203008174896, 0.685675978660583],\n  [0.599261999130249, 0.681069016456604],\n  [0.607599973678589, 0.677703022956848],\n  [0.631937980651855, 0.663500010967255],\n  [0.752032995223999, 0.601315021514893],\n  [0.547226011753082, 0.420395016670227],\n  [0.563543975353241, 0.359827995300293],\n  [0.583841025829315, 0.368713974952698],\n  [0.586614012718201, 0.692366003990173],\n  [0.771915018558502, 0.683578014373779],\n  [0.531597018241882, 0.352482974529266],\n  [0.588370978832245, 0.804440975189209],\n  [0.52079701423645, 0.442565023899078],\n  [0.567984998226166, 0.493479013442993],\n  [0.543282985687256, 0.819254994392395],\n  [0.655317008495331, 0.745514988899231],\n  [0.621008992195129, 0.574018001556396],\n  [0.625559985637665, 0.78031200170517],\n  [0.680198013782501, 0.570719003677368],\n  [0.64276397228241, 0.604337990283966],\n  [0.704662978649139, 0.621529996395111],\n  [0.552012026309967, 0.862591981887817],\n  [0.589071989059448, 0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468: Array<number> = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68: Array<number> = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33: Array<number> = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7: Array<number> = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68: Array<number> = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33: Array<number> = [33, 133, 362, 263, 1, 62, 308, 159, 145, 386, 374, 6, 102, 331, 2, 13, 14, 70, 105, 107, 336, 334, 300, 54, 10, 284, 50, 280, 234, 454, 58, 288, 152];\n\nexport const VTX7: Array<number> = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n\n// https://github.com/tensorflow/tfjs-models/blob/master/face-landmarks-detection/src/constants.ts\n// https://github.com/google/mediapipe/mediapipe/python/solutions/face_mesh_connections.py\n\ntype PairArray = Array<[number, number]>;\n\nfunction connectionsToIndices(connections: PairArray) {\n  const indices = connections.map((connection) => connection[0]);\n  indices.push(connections[connections.length - 1][1]);\n  return indices;\n}\n\nexport const pairsLips: PairArray = [\n  [61, 146], [146, 91], [91, 181], [181, 84], [84, 17], [17, 314], [314, 405], [405, 321], [321, 375], [375, 291], [61, 185], [185, 40], [40, 39], [39, 37], [37, 0], [0, 267], [267, 269], [269, 270], [270, 409], [409, 291],\n  [78, 95], [95, 88], [88, 178], [178, 87], [87, 14], [14, 317], [317, 402], [402, 318], [318, 324], [324, 308], [78, 191], [191, 80], [80, 81], [81, 82], [82, 13], [13, 312], [312, 311], [311, 310], [310, 415], [415, 308],\n];\n\nexport const pairsLeftEye: PairArray = [[263, 249], [249, 390], [390, 373], [373, 374], [374, 380], [380, 381], [381, 382], [382, 362], [263, 466], [466, 388], [388, 387], [387, 386], [386, 385], [385, 384], [384, 398], [398, 362]];\n\nexport const pairsLeftEyebrow: PairArray = [[276, 283], [283, 282], [282, 295], [295, 285], [300, 293], [293, 334], [334, 296], [296, 336]];\n\nexport const pairsLeftIris: PairArray = [[474, 475], [475, 476], [476, 477], [477, 474]];\n\nexport const pairsRightEye: PairArray = [[33, 7], [7, 163], [163, 144], [144, 145], [145, 153], [153, 154], [154, 155], [155, 133], [33, 246], [246, 161], [161, 160], [160, 159], [159, 158], [158, 157], [157, 173], [173, 133]];\n\nexport const pairsRightEyebrow: PairArray = [[46, 53], [53, 52], [52, 65], [65, 55], [70, 63], [63, 105], [105, 66], [66, 107]];\n\nexport const pairsRightIris: PairArray = [[469, 470], [470, 471], [471, 472], [472, 469]];\n\nexport const pairsFaceContour: PairArray = [\n  [10, 338], [338, 297], [297, 332], [332, 284], [284, 251], [251, 389],\n  [389, 356], [356, 454], [454, 323], [323, 361], [361, 288], [288, 397],\n  [397, 365], [365, 379], [379, 378], [378, 400], [400, 377], [377, 152],\n  [152, 148], [148, 176], [176, 149], [149, 150], [150, 136], [136, 172],\n  [172, 58], [58, 132], [132, 93], [93, 234], [234, 127], [127, 162],\n  [162, 21], [21, 54], [54, 103], [103, 67], [67, 109], [109, 10],\n];\n\nexport const contourKeypoints = {\n  lips: connectionsToIndices(pairsLips),\n  leftEye: connectionsToIndices(pairsLeftEye),\n  leftEyebrow: connectionsToIndices(pairsLeftEyebrow),\n  leftIris: connectionsToIndices(pairsLeftIris),\n  rightEye: connectionsToIndices(pairsRightEye),\n  rightEyebrow: connectionsToIndices(pairsRightEyebrow),\n  rightIris: connectionsToIndices(pairsRightIris),\n  faceOval: connectionsToIndices(pairsFaceContour),\n};\n\nexport const pairsFaceMesh: PairArray = [\n  [127, 34], [34, 139], [139, 127], [11, 0], [0, 37], [37, 11],\n  [232, 231], [231, 120], [120, 232], [72, 37], [37, 39], [39, 72],\n  [128, 121], [121, 47], [47, 128], [232, 121], [121, 128], [128, 232],\n  [104, 69], [69, 67], [67, 104], [175, 171], [171, 148], [148, 175],\n  [118, 50], [50, 101], [101, 118], [73, 39], [39, 40], [40, 73],\n  [9, 151], [151, 108], [108, 9], [48, 115], [115, 131], [131, 48],\n  [194, 204], [204, 211], [211, 194], [74, 40], [40, 185], [185, 74],\n  [80, 42], [42, 183], [183, 80], [40, 92], [92, 186], [186, 40],\n  [230, 229], [229, 118], [118, 230], [202, 212], [212, 214], [214, 202],\n  [83, 18], [18, 17], [17, 83], [76, 61], [61, 146], [146, 76],\n  [160, 29], [29, 30], [30, 160], [56, 157], [157, 173], [173, 56],\n  [106, 204], [204, 194], [194, 106], [135, 214], [214, 192], [192, 135],\n  [203, 165], [165, 98], [98, 203], [21, 71], [71, 68], [68, 21],\n  [51, 45], [45, 4], [4, 51], [144, 24], [24, 23], [23, 144],\n  [77, 146], [146, 91], [91, 77], [205, 50], [50, 187], [187, 205],\n  [201, 200], [200, 18], [18, 201], [91, 106], [106, 182], [182, 91],\n  [90, 91], [91, 181], [181, 90], [85, 84], [84, 17], [17, 85],\n  [206, 203], [203, 36], [36, 206], [148, 171], [171, 140], [140, 148],\n  [92, 40], [40, 39], [39, 92], [193, 189], [189, 244], [244, 193],\n  [159, 158], [158, 28], [28, 159], [247, 246], [246, 161], [161, 247],\n  [236, 3], [3, 196], [196, 236], [54, 68], [68, 104], [104, 54],\n  [193, 168], [168, 8], [8, 193], [117, 228], [228, 31], [31, 117],\n  [189, 193], [193, 55], [55, 189], [98, 97], [97, 99], [99, 98],\n  [126, 47], [47, 100], [100, 126], [166, 79], [79, 218], [218, 166],\n  [155, 154], [154, 26], [26, 155], [209, 49], [49, 131], [131, 209],\n  [135, 136], [136, 150], [150, 135], [47, 126], [126, 217], [217, 47],\n  [223, 52], [52, 53], [53, 223], [45, 51], [51, 134], [134, 45],\n  [211, 170], [170, 140], [140, 211], [67, 69], [69, 108], [108, 67],\n  [43, 106], [106, 91], [91, 43], [230, 119], [119, 120], [120, 230],\n  [226, 130], [130, 247], [247, 226], [63, 53], [53, 52], [52, 63],\n  [238, 20], [20, 242], [242, 238], [46, 70], [70, 156], [156, 46],\n  [78, 62], [62, 96], [96, 78], [46, 53], [53, 63], [63, 46],\n  [143, 34], [34, 227], [227, 143], [123, 117], [117, 111], [111, 123],\n  [44, 125], [125, 19], [19, 44], [236, 134], [134, 51], [51, 236],\n  [216, 206], [206, 205], [205, 216], [154, 153], [153, 22], [22, 154],\n  [39, 37], [37, 167], [167, 39], [200, 201], [201, 208], [208, 200],\n  [36, 142], [142, 100], [100, 36], [57, 212], [212, 202], [202, 57],\n  [20, 60], [60, 99], [99, 20], [28, 158], [158, 157], [157, 28],\n  [35, 226], [226, 113], [113, 35], [160, 159], [159, 27], [27, 160],\n  [204, 202], [202, 210], [210, 204], [113, 225], [225, 46], [46, 113],\n  [43, 202], [202, 204], [204, 43], [62, 76], [76, 77], [77, 62],\n  [137, 123], [123, 116], [116, 137], [41, 38], [38, 72], [72, 41],\n  [203, 129], [129, 142], [142, 203], [64, 98], [98, 240], [240, 64],\n  [49, 102], [102, 64], [64, 49], [41, 73], [73, 74], [74, 41],\n  [212, 216], [216, 207], [207, 212], [42, 74], [74, 184], [184, 42],\n  [169, 170], [170, 211], [211, 169], [170, 149], [149, 176], [176, 170],\n  [105, 66], [66, 69], [69, 105], [122, 6], [6, 168], [168, 122],\n  [123, 147], [147, 187], [187, 123], [96, 77], [77, 90], [90, 96],\n  [65, 55], [55, 107], [107, 65], [89, 90], [90, 180], [180, 89],\n  [101, 100], [100, 120], [120, 101], [63, 105], [105, 104], [104, 63],\n  [93, 137], [137, 227], [227, 93], [15, 86], [86, 85], [85, 15],\n  [129, 102], [102, 49], [49, 129], [14, 87], [87, 86], [86, 14],\n  [55, 8], [8, 9], [9, 55], [100, 47], [47, 121], [121, 100],\n  [145, 23], [23, 22], [22, 145], [88, 89], [89, 179], [179, 88],\n  [6, 122], [122, 196], [196, 6], [88, 95], [95, 96], [96, 88],\n  [138, 172], [172, 136], [136, 138], [215, 58], [58, 172], [172, 215],\n  [115, 48], [48, 219], [219, 115], [42, 80], [80, 81], [81, 42],\n  [195, 3], [3, 51], [51, 195], [43, 146], [146, 61], [61, 43],\n  [171, 175], [175, 199], [199, 171], [81, 82], [82, 38], [38, 81],\n  [53, 46], [46, 225], [225, 53], [144, 163], [163, 110], [110, 144],\n  [52, 65], [65, 66], [66, 52], [229, 228], [228, 117], [117, 229],\n  [34, 127], [127, 234], [234, 34], [107, 108], [108, 69], [69, 107],\n  [109, 108], [108, 151], [151, 109], [48, 64], [64, 235], [235, 48],\n  [62, 78], [78, 191], [191, 62], [129, 209], [209, 126], [126, 129],\n  [111, 35], [35, 143], [143, 111], [117, 123], [123, 50], [50, 117],\n  [222, 65], [65, 52], [52, 222], [19, 125], [125, 141], [141, 19],\n  [221, 55], [55, 65], [65, 221], [3, 195], [195, 197], [197, 3],\n  [25, 7], [7, 33], [33, 25], [220, 237], [237, 44], [44, 220],\n  [70, 71], [71, 139], [139, 70], [122, 193], [193, 245], [245, 122],\n  [247, 130], [130, 33], [33, 247], [71, 21], [21, 162], [162, 71],\n  [170, 169], [169, 150], [150, 170], [188, 174], [174, 196], [196, 188],\n  [216, 186], [186, 92], [92, 216], [2, 97], [97, 167], [167, 2],\n  [141, 125], [125, 241], [241, 141], [164, 167], [167, 37], [37, 164],\n  [72, 38], [38, 12], [12, 72], [38, 82], [82, 13], [13, 38],\n  [63, 68], [68, 71], [71, 63], [226, 35], [35, 111], [111, 226],\n  [101, 50], [50, 205], [205, 101], [206, 92], [92, 165], [165, 206],\n  [209, 198], [198, 217], [217, 209], [165, 167], [167, 97], [97, 165],\n  [220, 115], [115, 218], [218, 220], [133, 112], [112, 243], [243, 133],\n  [239, 238], [238, 241], [241, 239], [214, 135], [135, 169], [169, 214],\n  [190, 173], [173, 133], [133, 190], [171, 208], [208, 32], [32, 171],\n  [125, 44], [44, 237], [237, 125], [86, 87], [87, 178], [178, 86],\n  [85, 86], [86, 179], [179, 85], [84, 85], [85, 180], [180, 84],\n  [83, 84], [84, 181], [181, 83], [201, 83], [83, 182], [182, 201],\n  [137, 93], [93, 132], [132, 137], [76, 62], [62, 183], [183, 76],\n  [61, 76], [76, 184], [184, 61], [57, 61], [61, 185], [185, 57],\n  [212, 57], [57, 186], [186, 212], [214, 207], [207, 187], [187, 214],\n  [34, 143], [143, 156], [156, 34], [79, 239], [239, 237], [237, 79],\n  [123, 137], [137, 177], [177, 123], [44, 1], [1, 4], [4, 44],\n  [201, 194], [194, 32], [32, 201], [64, 102], [102, 129], [129, 64],\n  [213, 215], [215, 138], [138, 213], [59, 166], [166, 219], [219, 59],\n  [242, 99], [99, 97], [97, 242], [2, 94], [94, 141], [141, 2],\n  [75, 59], [59, 235], [235, 75], [24, 110], [110, 228], [228, 24],\n  [25, 130], [130, 226], [226, 25], [23, 24], [24, 229], [229, 23],\n  [22, 23], [23, 230], [230, 22], [26, 22], [22, 231], [231, 26],\n  [112, 26], [26, 232], [232, 112], [189, 190], [190, 243], [243, 189],\n  [221, 56], [56, 190], [190, 221], [28, 56], [56, 221], [221, 28],\n  [27, 28], [28, 222], [222, 27], [29, 27], [27, 223], [223, 29],\n  [30, 29], [29, 224], [224, 30], [247, 30], [30, 225], [225, 247],\n  [238, 79], [79, 20], [20, 238], [166, 59], [59, 75], [75, 166],\n  [60, 75], [75, 240], [240, 60], [147, 177], [177, 215], [215, 147],\n  [20, 79], [79, 166], [166, 20], [187, 147], [147, 213], [213, 187],\n  [112, 233], [233, 244], [244, 112], [233, 128], [128, 245], [245, 233],\n  [128, 114], [114, 188], [188, 128], [114, 217], [217, 174], [174, 114],\n  [131, 115], [115, 220], [220, 131], [217, 198], [198, 236], [236, 217],\n  [198, 131], [131, 134], [134, 198], [177, 132], [132, 58], [58, 177],\n  [143, 35], [35, 124], [124, 143], [110, 163], [163, 7], [7, 110],\n  [228, 110], [110, 25], [25, 228], [356, 389], [389, 368], [368, 356],\n  [11, 302], [302, 267], [267, 11], [452, 350], [350, 349], [349, 452],\n  [302, 303], [303, 269], [269, 302], [357, 343], [343, 277], [277, 357],\n  [452, 453], [453, 357], [357, 452], [333, 332], [332, 297], [297, 333],\n  [175, 152], [152, 377], [377, 175], [347, 348], [348, 330], [330, 347],\n  [303, 304], [304, 270], [270, 303], [9, 336], [336, 337], [337, 9],\n  [278, 279], [279, 360], [360, 278], [418, 262], [262, 431], [431, 418],\n  [304, 408], [408, 409], [409, 304], [310, 415], [415, 407], [407, 310],\n  [270, 409], [409, 410], [410, 270], [450, 348], [348, 347], [347, 450],\n  [422, 430], [430, 434], [434, 422], [313, 314], [314, 17], [17, 313],\n  [306, 307], [307, 375], [375, 306], [387, 388], [388, 260], [260, 387],\n  [286, 414], [414, 398], [398, 286], [335, 406], [406, 418], [418, 335],\n  [364, 367], [367, 416], [416, 364], [423, 358], [358, 327], [327, 423],\n  [251, 284], [284, 298], [298, 251], [281, 5], [5, 4], [4, 281],\n  [373, 374], [374, 253], [253, 373], [307, 320], [320, 321], [321, 307],\n  [425, 427], [427, 411], [411, 425], [421, 313], [313, 18], [18, 421],\n  [321, 405], [405, 406], [406, 321], [320, 404], [404, 405], [405, 320],\n  [315, 16], [16, 17], [17, 315], [426, 425], [425, 266], [266, 426],\n  [377, 400], [400, 369], [369, 377], [322, 391], [391, 269], [269, 322],\n  [417, 465], [465, 464], [464, 417], [386, 257], [257, 258], [258, 386],\n  [466, 260], [260, 388], [388, 466], [456, 399], [399, 419], [419, 456],\n  [284, 332], [332, 333], [333, 284], [417, 285], [285, 8], [8, 417],\n  [346, 340], [340, 261], [261, 346], [413, 441], [441, 285], [285, 413],\n  [327, 460], [460, 328], [328, 327], [355, 371], [371, 329], [329, 355],\n  [392, 439], [439, 438], [438, 392], [382, 341], [341, 256], [256, 382],\n  [429, 420], [420, 360], [360, 429], [364, 394], [394, 379], [379, 364],\n  [277, 343], [343, 437], [437, 277], [443, 444], [444, 283], [283, 443],\n  [275, 440], [440, 363], [363, 275], [431, 262], [262, 369], [369, 431],\n  [297, 338], [338, 337], [337, 297], [273, 375], [375, 321], [321, 273],\n  [450, 451], [451, 349], [349, 450], [446, 342], [342, 467], [467, 446],\n  [293, 334], [334, 282], [282, 293], [458, 461], [461, 462], [462, 458],\n  [276, 353], [353, 383], [383, 276], [308, 324], [324, 325], [325, 308],\n  [276, 300], [300, 293], [293, 276], [372, 345], [345, 447], [447, 372],\n  [352, 345], [345, 340], [340, 352], [274, 1], [1, 19], [19, 274],\n  [456, 248], [248, 281], [281, 456], [436, 427], [427, 425], [425, 436],\n  [381, 256], [256, 252], [252, 381], [269, 391], [391, 393], [393, 269],\n  [200, 199], [199, 428], [428, 200], [266, 330], [330, 329], [329, 266],\n  [287, 273], [273, 422], [422, 287], [250, 462], [462, 328], [328, 250],\n  [258, 286], [286, 384], [384, 258], [265, 353], [353, 342], [342, 265],\n  [387, 259], [259, 257], [257, 387], [424, 431], [431, 430], [430, 424],\n  [342, 353], [353, 276], [276, 342], [273, 335], [335, 424], [424, 273],\n  [292, 325], [325, 307], [307, 292], [366, 447], [447, 345], [345, 366],\n  [271, 303], [303, 302], [302, 271], [423, 266], [266, 371], [371, 423],\n  [294, 455], [455, 460], [460, 294], [279, 278], [278, 294], [294, 279],\n  [271, 272], [272, 304], [304, 271], [432, 434], [434, 427], [427, 432],\n  [272, 407], [407, 408], [408, 272], [394, 430], [430, 431], [431, 394],\n  [395, 369], [369, 400], [400, 395], [334, 333], [333, 299], [299, 334],\n  [351, 417], [417, 168], [168, 351], [352, 280], [280, 411], [411, 352],\n  [325, 319], [319, 320], [320, 325], [295, 296], [296, 336], [336, 295],\n  [319, 403], [403, 404], [404, 319], [330, 348], [348, 349], [349, 330],\n  [293, 298], [298, 333], [333, 293], [323, 454], [454, 447], [447, 323],\n  [15, 16], [16, 315], [315, 15], [358, 429], [429, 279], [279, 358],\n  [14, 15], [15, 316], [316, 14], [285, 336], [336, 9], [9, 285],\n  [329, 349], [349, 350], [350, 329], [374, 380], [380, 252], [252, 374],\n  [318, 402], [402, 403], [403, 318], [6, 197], [197, 419], [419, 6],\n  [318, 319], [319, 325], [325, 318], [367, 364], [364, 365], [365, 367],\n  [435, 367], [367, 397], [397, 435], [344, 438], [438, 439], [439, 344],\n  [272, 271], [271, 311], [311, 272], [195, 5], [5, 281], [281, 195],\n  [273, 287], [287, 291], [291, 273], [396, 428], [428, 199], [199, 396],\n  [311, 271], [271, 268], [268, 311], [283, 444], [444, 445], [445, 283],\n  [373, 254], [254, 339], [339, 373], [282, 334], [334, 296], [296, 282],\n  [449, 347], [347, 346], [346, 449], [264, 447], [447, 454], [454, 264],\n  [336, 296], [296, 299], [299, 336], [338, 10], [10, 151], [151, 338],\n  [278, 439], [439, 455], [455, 278], [292, 407], [407, 415], [415, 292],\n  [358, 371], [371, 355], [355, 358], [340, 345], [345, 372], [372, 340],\n  [346, 347], [347, 280], [280, 346], [442, 443], [443, 282], [282, 442],\n  [19, 94], [94, 370], [370, 19], [441, 442], [442, 295], [295, 441],\n  [248, 419], [419, 197], [197, 248], [263, 255], [255, 359], [359, 263],\n  [440, 275], [275, 274], [274, 440], [300, 383], [383, 368], [368, 300],\n  [351, 412], [412, 465], [465, 351], [263, 467], [467, 466], [466, 263],\n  [301, 368], [368, 389], [389, 301], [395, 378], [378, 379], [379, 395],\n  [412, 351], [351, 419], [419, 412], [436, 426], [426, 322], [322, 436],\n  [2, 164], [164, 393], [393, 2], [370, 462], [462, 461], [461, 370],\n  [164, 0], [0, 267], [267, 164], [302, 11], [11, 12], [12, 302],\n  [268, 12], [12, 13], [13, 268], [293, 300], [300, 301], [301, 293],\n  [446, 261], [261, 340], [340, 446], [330, 266], [266, 425], [425, 330],\n  [426, 423], [423, 391], [391, 426], [429, 355], [355, 437], [437, 429],\n  [391, 327], [327, 326], [326, 391], [440, 457], [457, 438], [438, 440],\n  [341, 382], [382, 362], [362, 341], [459, 457], [457, 461], [461, 459],\n  [434, 430], [430, 394], [394, 434], [414, 463], [463, 362], [362, 414],\n  [396, 369], [369, 262], [262, 396], [354, 461], [461, 457], [457, 354],\n  [316, 403], [403, 402], [402, 316], [315, 404], [404, 403], [403, 315],\n  [314, 405], [405, 404], [404, 314], [313, 406], [406, 405], [405, 313],\n  [421, 418], [418, 406], [406, 421], [366, 401], [401, 361], [361, 366],\n  [306, 408], [408, 407], [407, 306], [291, 409], [409, 408], [408, 291],\n  [287, 410], [410, 409], [409, 287], [432, 436], [436, 410], [410, 432],\n  [434, 416], [416, 411], [411, 434], [264, 368], [368, 383], [383, 264],\n  [309, 438], [438, 457], [457, 309], [352, 376], [376, 401], [401, 352],\n  [274, 275], [275, 4], [4, 274], [421, 428], [428, 262], [262, 421],\n  [294, 327], [327, 358], [358, 294], [433, 416], [416, 367], [367, 433],\n  [289, 455], [455, 439], [439, 289], [462, 370], [370, 326], [326, 462],\n  [2, 326], [326, 370], [370, 2], [305, 460], [460, 455], [455, 305],\n  [254, 449], [449, 448], [448, 254], [255, 261], [261, 446], [446, 255],\n  [253, 450], [450, 449], [449, 253], [252, 451], [451, 450], [450, 252],\n  [256, 452], [452, 451], [451, 256], [341, 453], [453, 452], [452, 341],\n  [413, 464], [464, 463], [463, 413], [441, 413], [413, 414], [414, 441],\n  [258, 442], [442, 441], [441, 258], [257, 443], [443, 442], [442, 257],\n  [259, 444], [444, 443], [443, 259], [260, 445], [445, 444], [444, 260],\n  [467, 342], [342, 445], [445, 467], [459, 458], [458, 250], [250, 459],\n  [289, 392], [392, 290], [290, 289], [290, 328], [328, 460], [460, 290],\n  [376, 433], [433, 435], [435, 376], [250, 290], [290, 392], [392, 250],\n  [411, 416], [416, 433], [433, 411], [341, 463], [463, 464], [464, 341],\n  [453, 464], [464, 465], [465, 453], [357, 465], [465, 412], [412, 357],\n  [343, 412], [412, 399], [399, 343], [360, 363], [363, 440], [440, 360],\n  [437, 399], [399, 456], [456, 437], [420, 456], [456, 363], [363, 420],\n  [401, 435], [435, 288], [288, 401], [372, 383], [383, 353], [353, 372],\n  [339, 255], [255, 249], [249, 339], [448, 261], [261, 255], [255, 448],\n  [133, 243], [243, 190], [190, 133], [133, 155], [155, 112], [112, 133],\n  [33, 246], [246, 247], [247, 33], [33, 130], [130, 25], [25, 33],\n  [398, 384], [384, 286], [286, 398], [362, 398], [398, 414], [414, 362],\n  [362, 463], [463, 341], [341, 362], [263, 359], [359, 467], [467, 263],\n  [263, 249], [249, 255], [255, 263], [466, 467], [467, 260], [260, 466],\n  [75, 60], [60, 166], [166, 75], [238, 239], [239, 79], [79, 238],\n  [162, 127], [127, 139], [139, 162], [72, 11], [11, 37], [37, 72],\n  [121, 232], [232, 120], [120, 121], [73, 72], [72, 39], [39, 73],\n  [114, 128], [128, 47], [47, 114], [233, 232], [232, 128], [128, 233],\n  [103, 104], [104, 67], [67, 103], [152, 175], [175, 148], [148, 152],\n  [119, 118], [118, 101], [101, 119], [74, 73], [73, 40], [40, 74],\n  [107, 9], [9, 108], [108, 107], [49, 48], [48, 131], [131, 49],\n  [32, 194], [194, 211], [211, 32], [184, 74], [74, 185], [185, 184],\n  [191, 80], [80, 183], [183, 191], [185, 40], [40, 186], [186, 185],\n  [119, 230], [230, 118], [118, 119], [210, 202], [202, 214], [214, 210],\n  [84, 83], [83, 17], [17, 84], [77, 76], [76, 146], [146, 77],\n  [161, 160], [160, 30], [30, 161], [190, 56], [56, 173], [173, 190],\n  [182, 106], [106, 194], [194, 182], [138, 135], [135, 192], [192, 138],\n  [129, 203], [203, 98], [98, 129], [54, 21], [21, 68], [68, 54],\n  [5, 51], [51, 4], [4, 5], [145, 144], [144, 23], [23, 145],\n  [90, 77], [77, 91], [91, 90], [207, 205], [205, 187], [187, 207],\n  [83, 201], [201, 18], [18, 83], [181, 91], [91, 182], [182, 181],\n  [180, 90], [90, 181], [181, 180], [16, 85], [85, 17], [17, 16],\n  [205, 206], [206, 36], [36, 205], [176, 148], [148, 140], [140, 176],\n  [165, 92], [92, 39], [39, 165], [245, 193], [193, 244], [244, 245],\n  [27, 159], [159, 28], [28, 27], [30, 247], [247, 161], [161, 30],\n  [174, 236], [236, 196], [196, 174], [103, 54], [54, 104], [104, 103],\n  [55, 193], [193, 8], [8, 55], [111, 117], [117, 31], [31, 111],\n  [221, 189], [189, 55], [55, 221], [240, 98], [98, 99], [99, 240],\n  [142, 126], [126, 100], [100, 142], [219, 166], [166, 218], [218, 219],\n  [112, 155], [155, 26], [26, 112], [198, 209], [209, 131], [131, 198],\n  [169, 135], [135, 150], [150, 169], [114, 47], [47, 217], [217, 114],\n  [224, 223], [223, 53], [53, 224], [220, 45], [45, 134], [134, 220],\n  [32, 211], [211, 140], [140, 32], [109, 67], [67, 108], [108, 109],\n  [146, 43], [43, 91], [91, 146], [231, 230], [230, 120], [120, 231],\n  [113, 226], [226, 247], [247, 113], [105, 63], [63, 52], [52, 105],\n  [241, 238], [238, 242], [242, 241], [124, 46], [46, 156], [156, 124],\n  [95, 78], [78, 96], [96, 95], [70, 46], [46, 63], [63, 70],\n  [116, 143], [143, 227], [227, 116], [116, 123], [123, 111], [111, 116],\n  [1, 44], [44, 19], [19, 1], [3, 236], [236, 51], [51, 3],\n  [207, 216], [216, 205], [205, 207], [26, 154], [154, 22], [22, 26],\n  [165, 39], [39, 167], [167, 165], [199, 200], [200, 208], [208, 199],\n  [101, 36], [36, 100], [100, 101], [43, 57], [57, 202], [202, 43],\n  [242, 20], [20, 99], [99, 242], [56, 28], [28, 157], [157, 56],\n  [124, 35], [35, 113], [113, 124], [29, 160], [160, 27], [27, 29],\n  [211, 204], [204, 210], [210, 211], [124, 113], [113, 46], [46, 124],\n  [106, 43], [43, 204], [204, 106], [96, 62], [62, 77], [77, 96],\n  [227, 137], [137, 116], [116, 227], [73, 41], [41, 72], [72, 73],\n  [36, 203], [203, 142], [142, 36], [235, 64], [64, 240], [240, 235],\n  [48, 49], [49, 64], [64, 48], [42, 41], [41, 74], [74, 42],\n  [214, 212], [212, 207], [207, 214], [183, 42], [42, 184], [184, 183],\n  [210, 169], [169, 211], [211, 210], [140, 170], [170, 176], [176, 140],\n  [104, 105], [105, 69], [69, 104], [193, 122], [122, 168], [168, 193],\n  [50, 123], [123, 187], [187, 50], [89, 96], [96, 90], [90, 89],\n  [66, 65], [65, 107], [107, 66], [179, 89], [89, 180], [180, 179],\n  [119, 101], [101, 120], [120, 119], [68, 63], [63, 104], [104, 68],\n  [234, 93], [93, 227], [227, 234], [16, 15], [15, 85], [85, 16],\n  [209, 129], [129, 49], [49, 209], [15, 14], [14, 86], [86, 15],\n  [107, 55], [55, 9], [9, 107], [120, 100], [100, 121], [121, 120],\n  [153, 145], [145, 22], [22, 153], [178, 88], [88, 179], [179, 178],\n  [197, 6], [6, 196], [196, 197], [89, 88], [88, 96], [96, 89],\n  [135, 138], [138, 136], [136, 135], [138, 215], [215, 172], [172, 138],\n  [218, 115], [115, 219], [219, 218], [41, 42], [42, 81], [81, 41],\n  [5, 195], [195, 51], [51, 5], [57, 43], [43, 61], [61, 57],\n  [208, 171], [171, 199], [199, 208], [41, 81], [81, 38], [38, 41],\n  [224, 53], [53, 225], [225, 224], [24, 144], [144, 110], [110, 24],\n  [105, 52], [52, 66], [66, 105], [118, 229], [229, 117], [117, 118],\n  [227, 34], [34, 234], [234, 227], [66, 107], [107, 69], [69, 66],\n  [10, 109], [109, 151], [151, 10], [219, 48], [48, 235], [235, 219],\n  [183, 62], [62, 191], [191, 183], [142, 129], [129, 126], [126, 142],\n  [116, 111], [111, 143], [143, 116], [118, 117], [117, 50], [50, 118],\n  [223, 222], [222, 52], [52, 223], [94, 19], [19, 141], [141, 94],\n  [222, 221], [221, 65], [65, 222], [196, 3], [3, 197], [197, 196],\n  [45, 220], [220, 44], [44, 45], [156, 70], [70, 139], [139, 156],\n  [188, 122], [122, 245], [245, 188], [139, 71], [71, 162], [162, 139],\n  [149, 170], [170, 150], [150, 149], [122, 188], [188, 196], [196, 122],\n  [206, 216], [216, 92], [92, 206], [164, 2], [2, 167], [167, 164],\n  [242, 141], [141, 241], [241, 242], [0, 164], [164, 37], [37, 0],\n  [11, 72], [72, 12], [12, 11], [12, 38], [38, 13], [13, 12],\n  [70, 63], [63, 71], [71, 70], [31, 226], [226, 111], [111, 31],\n  [36, 101], [101, 205], [205, 36], [203, 206], [206, 165], [165, 203],\n  [126, 209], [209, 217], [217, 126], [98, 165], [165, 97], [97, 98],\n  [237, 220], [220, 218], [218, 237], [237, 239], [239, 241], [241, 237],\n  [210, 214], [214, 169], [169, 210], [140, 171], [171, 32], [32, 140],\n  [241, 125], [125, 237], [237, 241], [179, 86], [86, 178], [178, 179],\n  [180, 85], [85, 179], [179, 180], [181, 84], [84, 180], [180, 181],\n  [182, 83], [83, 181], [181, 182], [194, 201], [201, 182], [182, 194],\n  [177, 137], [137, 132], [132, 177], [184, 76], [76, 183], [183, 184],\n  [185, 61], [61, 184], [184, 185], [186, 57], [57, 185], [185, 186],\n  [216, 212], [212, 186], [186, 216], [192, 214], [214, 187], [187, 192],\n  [139, 34], [34, 156], [156, 139], [218, 79], [79, 237], [237, 218],\n  [147, 123], [123, 177], [177, 147], [45, 44], [44, 4], [4, 45],\n  [208, 201], [201, 32], [32, 208], [98, 64], [64, 129], [129, 98],\n  [192, 213], [213, 138], [138, 192], [235, 59], [59, 219], [219, 235],\n  [141, 242], [242, 97], [97, 141], [97, 2], [2, 141], [141, 97],\n  [240, 75], [75, 235], [235, 240], [229, 24], [24, 228], [228, 229],\n  [31, 25], [25, 226], [226, 31], [230, 23], [23, 229], [229, 230],\n  [231, 22], [22, 230], [230, 231], [232, 26], [26, 231], [231, 232],\n  [233, 112], [112, 232], [232, 233], [244, 189], [189, 243], [243, 244],\n  [189, 221], [221, 190], [190, 189], [222, 28], [28, 221], [221, 222],\n  [223, 27], [27, 222], [222, 223], [224, 29], [29, 223], [223, 224],\n  [225, 30], [30, 224], [224, 225], [113, 247], [247, 225], [225, 113],\n  [99, 60], [60, 240], [240, 99], [213, 147], [147, 215], [215, 213],\n  [60, 20], [20, 166], [166, 60], [192, 187], [187, 213], [213, 192],\n  [243, 112], [112, 244], [244, 243], [244, 233], [233, 245], [245, 244],\n  [245, 128], [128, 188], [188, 245], [188, 114], [114, 174], [174, 188],\n  [134, 131], [131, 220], [220, 134], [174, 217], [217, 236], [236, 174],\n  [236, 198], [198, 134], [134, 236], [215, 177], [177, 58], [58, 215],\n  [156, 143], [143, 124], [124, 156], [25, 110], [110, 7], [7, 25],\n  [31, 228], [228, 25], [25, 31], [264, 356], [356, 368], [368, 264],\n  [0, 11], [11, 267], [267, 0], [451, 452], [452, 349], [349, 451],\n  [267, 302], [302, 269], [269, 267], [350, 357], [357, 277], [277, 350],\n  [350, 452], [452, 357], [357, 350], [299, 333], [333, 297], [297, 299],\n  [396, 175], [175, 377], [377, 396], [280, 347], [347, 330], [330, 280],\n  [269, 303], [303, 270], [270, 269], [151, 9], [9, 337], [337, 151],\n  [344, 278], [278, 360], [360, 344], [424, 418], [418, 431], [431, 424],\n  [270, 304], [304, 409], [409, 270], [272, 310], [310, 407], [407, 272],\n  [322, 270], [270, 410], [410, 322], [449, 450], [450, 347], [347, 449],\n  [432, 422], [422, 434], [434, 432], [18, 313], [313, 17], [17, 18],\n  [291, 306], [306, 375], [375, 291], [259, 387], [387, 260], [260, 259],\n  [424, 335], [335, 418], [418, 424], [434, 364], [364, 416], [416, 434],\n  [391, 423], [423, 327], [327, 391], [301, 251], [251, 298], [298, 301],\n  [275, 281], [281, 4], [4, 275], [254, 373], [373, 253], [253, 254],\n  [375, 307], [307, 321], [321, 375], [280, 425], [425, 411], [411, 280],\n  [200, 421], [421, 18], [18, 200], [335, 321], [321, 406], [406, 335],\n  [321, 320], [320, 405], [405, 321], [314, 315], [315, 17], [17, 314],\n  [423, 426], [426, 266], [266, 423], [396, 377], [377, 369], [369, 396],\n  [270, 322], [322, 269], [269, 270], [413, 417], [417, 464], [464, 413],\n  [385, 386], [386, 258], [258, 385], [248, 456], [456, 419], [419, 248],\n  [298, 284], [284, 333], [333, 298], [168, 417], [417, 8], [8, 168],\n  [448, 346], [346, 261], [261, 448], [417, 413], [413, 285], [285, 417],\n  [326, 327], [327, 328], [328, 326], [277, 355], [355, 329], [329, 277],\n  [309, 392], [392, 438], [438, 309], [381, 382], [382, 256], [256, 381],\n  [279, 429], [429, 360], [360, 279], [365, 364], [364, 379], [379, 365],\n  [355, 277], [277, 437], [437, 355], [282, 443], [443, 283], [283, 282],\n  [281, 275], [275, 363], [363, 281], [395, 431], [431, 369], [369, 395],\n  [299, 297], [297, 337], [337, 299], [335, 273], [273, 321], [321, 335],\n  [348, 450], [450, 349], [349, 348], [359, 446], [446, 467], [467, 359],\n  [283, 293], [293, 282], [282, 283], [250, 458], [458, 462], [462, 250],\n  [300, 276], [276, 383], [383, 300], [292, 308], [308, 325], [325, 292],\n  [283, 276], [276, 293], [293, 283], [264, 372], [372, 447], [447, 264],\n  [346, 352], [352, 340], [340, 346], [354, 274], [274, 19], [19, 354],\n  [363, 456], [456, 281], [281, 363], [426, 436], [436, 425], [425, 426],\n  [380, 381], [381, 252], [252, 380], [267, 269], [269, 393], [393, 267],\n  [421, 200], [200, 428], [428, 421], [371, 266], [266, 329], [329, 371],\n  [432, 287], [287, 422], [422, 432], [290, 250], [250, 328], [328, 290],\n  [385, 258], [258, 384], [384, 385], [446, 265], [265, 342], [342, 446],\n  [386, 387], [387, 257], [257, 386], [422, 424], [424, 430], [430, 422],\n  [445, 342], [342, 276], [276, 445], [422, 273], [273, 424], [424, 422],\n  [306, 292], [292, 307], [307, 306], [352, 366], [366, 345], [345, 352],\n  [268, 271], [271, 302], [302, 268], [358, 423], [423, 371], [371, 358],\n  [327, 294], [294, 460], [460, 327], [331, 279], [279, 294], [294, 331],\n  [303, 271], [271, 304], [304, 303], [436, 432], [432, 427], [427, 436],\n  [304, 272], [272, 408], [408, 304], [395, 394], [394, 431], [431, 395],\n  [378, 395], [395, 400], [400, 378], [296, 334], [334, 299], [299, 296],\n  [6, 351], [351, 168], [168, 6], [376, 352], [352, 411], [411, 376],\n  [307, 325], [325, 320], [320, 307], [285, 295], [295, 336], [336, 285],\n  [320, 319], [319, 404], [404, 320], [329, 330], [330, 349], [349, 329],\n  [334, 293], [293, 333], [333, 334], [366, 323], [323, 447], [447, 366],\n  [316, 15], [15, 315], [315, 316], [331, 358], [358, 279], [279, 331],\n  [317, 14], [14, 316], [316, 317], [8, 285], [285, 9], [9, 8],\n  [277, 329], [329, 350], [350, 277], [253, 374], [374, 252], [252, 253],\n  [319, 318], [318, 403], [403, 319], [351, 6], [6, 419], [419, 351],\n  [324, 318], [318, 325], [325, 324], [397, 367], [367, 365], [365, 397],\n  [288, 435], [435, 397], [397, 288], [278, 344], [344, 439], [439, 278],\n  [310, 272], [272, 311], [311, 310], [248, 195], [195, 281], [281, 248],\n  [375, 273], [273, 291], [291, 375], [175, 396], [396, 199], [199, 175],\n  [312, 311], [311, 268], [268, 312], [276, 283], [283, 445], [445, 276],\n  [390, 373], [373, 339], [339, 390], [295, 282], [282, 296], [296, 295],\n  [448, 449], [449, 346], [346, 448], [356, 264], [264, 454], [454, 356],\n  [337, 336], [336, 299], [299, 337], [337, 338], [338, 151], [151, 337],\n  [294, 278], [278, 455], [455, 294], [308, 292], [292, 415], [415, 308],\n  [429, 358], [358, 355], [355, 429], [265, 340], [340, 372], [372, 265],\n  [352, 346], [346, 280], [280, 352], [295, 442], [442, 282], [282, 295],\n  [354, 19], [19, 370], [370, 354], [285, 441], [441, 295], [295, 285],\n  [195, 248], [248, 197], [197, 195], [457, 440], [440, 274], [274, 457],\n  [301, 300], [300, 368], [368, 301], [417, 351], [351, 465], [465, 417],\n  [251, 301], [301, 389], [389, 251], [394, 395], [395, 379], [379, 394],\n  [399, 412], [412, 419], [419, 399], [410, 436], [436, 322], [322, 410],\n  [326, 2], [2, 393], [393, 326], [354, 370], [370, 461], [461, 354],\n  [393, 164], [164, 267], [267, 393], [268, 302], [302, 12], [12, 268],\n  [312, 268], [268, 13], [13, 312], [298, 293], [293, 301], [301, 298],\n  [265, 446], [446, 340], [340, 265], [280, 330], [330, 425], [425, 280],\n  [322, 426], [426, 391], [391, 322], [420, 429], [429, 437], [437, 420],\n  [393, 391], [391, 326], [326, 393], [344, 440], [440, 438], [438, 344],\n  [458, 459], [459, 461], [461, 458], [364, 434], [434, 394], [394, 364],\n  [428, 396], [396, 262], [262, 428], [274, 354], [354, 457], [457, 274],\n  [317, 316], [316, 402], [402, 317], [316, 315], [315, 403], [403, 316],\n  [315, 314], [314, 404], [404, 315], [314, 313], [313, 405], [405, 314],\n  [313, 421], [421, 406], [406, 313], [323, 366], [366, 361], [361, 323],\n  [292, 306], [306, 407], [407, 292], [306, 291], [291, 408], [408, 306],\n  [291, 287], [287, 409], [409, 291], [287, 432], [432, 410], [410, 287],\n  [427, 434], [434, 411], [411, 427], [372, 264], [264, 383], [383, 372],\n  [459, 309], [309, 457], [457, 459], [366, 352], [352, 401], [401, 366],\n  [1, 274], [274, 4], [4, 1], [418, 421], [421, 262], [262, 418],\n  [331, 294], [294, 358], [358, 331], [435, 433], [433, 367], [367, 435],\n  [392, 289], [289, 439], [439, 392], [328, 462], [462, 326], [326, 328],\n  [94, 2], [2, 370], [370, 94], [289, 305], [305, 455], [455, 289],\n  [339, 254], [254, 448], [448, 339], [359, 255], [255, 446], [446, 359],\n  [254, 253], [253, 449], [449, 254], [253, 252], [252, 450], [450, 253],\n  [252, 256], [256, 451], [451, 252], [256, 341], [341, 452], [452, 256],\n  [414, 413], [413, 463], [463, 414], [286, 441], [441, 414], [414, 286],\n  [286, 258], [258, 441], [441, 286], [258, 257], [257, 442], [442, 258],\n  [257, 259], [259, 443], [443, 257], [259, 260], [260, 444], [444, 259],\n  [260, 467], [467, 445], [445, 260], [309, 459], [459, 250], [250, 309],\n  [305, 289], [289, 290], [290, 305], [305, 290], [290, 460], [460, 305],\n  [401, 376], [376, 435], [435, 401], [309, 250], [250, 392], [392, 309],\n  [376, 411], [411, 433], [433, 376], [453, 341], [341, 464], [464, 453],\n  [357, 453], [453, 465], [465, 357], [343, 357], [357, 412], [412, 343],\n  [437, 343], [343, 399], [399, 437], [344, 360], [360, 440], [440, 344],\n  [420, 437], [437, 456], [456, 420], [360, 420], [420, 363], [363, 360],\n  [361, 401], [401, 288], [288, 361], [265, 372], [372, 353], [353, 265],\n  [390, 339], [339, 249], [249, 390], [339, 448], [448, 255], [255, 339],\n];\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n * See `facemesh.ts` for entry point\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as coords from './facemeshcoords';\nimport { constants } from '../tfjs/constants';\nimport type { Box, Point } from '../result';\nimport { env } from '../util/env';\n\nexport const createBox = (startEndTensor) => ({ startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]), endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]) });\n\nexport const disposeBox = (t) => tf.dispose([t.startPoint, t.endPoint]);\n\nexport const getBoxSize = (box): [number, number] => [Math.abs(box.endPoint[0] - box.startPoint[0]), Math.abs(box.endPoint[1] - box.startPoint[1])];\n\nexport const getBoxCenter = (box): [number, number, number] => [box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2, box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2, 1];\n\nexport const clampBox = (box, input): Box => (box ? [\n  Math.trunc(Math.max(0, box.startPoint[0])),\n  Math.trunc(Math.max(0, box.startPoint[1])),\n  Math.trunc(Math.min((input.shape[2] || 0), box.endPoint[0]) - Math.max(0, box.startPoint[0])),\n  Math.trunc(Math.min((input.shape[1] || 0), box.endPoint[1]) - Math.max(0, box.startPoint[1])),\n] : [0, 0, 0, 0]);\n\nexport const getRawBox = (box, input): Box => (box ? [\n  box.startPoint[0] / (input.shape[2] || 0),\n  box.startPoint[1] / (input.shape[1] || 0),\n  (box.endPoint[0] - box.startPoint[0]) / (input.shape[2] || 0),\n  (box.endPoint[1] - box.startPoint[1]) / (input.shape[1] || 0),\n] : [0, 0, 0, 0]);\n\nexport const scaleBoxCoordinates = (box, factor) => {\n  const startPoint: Point = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint: Point = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks, confidence: box.confidence };\n};\n\nexport const cutAndResize = (box, image, cropSize) => {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const cutBox = [box.startPoint[1] / h, box.startPoint[0] / w, box.endPoint[1] / h, box.endPoint[0] / w];\n  const crop = tf.image.cropAndResize(image, [cutBox], [0], cropSize);\n  const norm = tf.div(crop, constants.tf255);\n  tf.dispose(crop);\n  return norm;\n};\n\nexport const enlargeBox = (box, factor) => {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const halfSize: [number, number] = [factor * size[0] / 2, factor * size[1] / 2];\n  return { startPoint: [center[0] - halfSize[0], center[1] - halfSize[1]] as Point, endPoint: [center[0] + halfSize[0], center[1] + halfSize[1]] as Point, landmarks: box.landmarks, confidence: box.confidence };\n};\n\nexport const squarifyBox = (box) => {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const halfSize = Math.max(...size) / 2;\n  return { startPoint: [Math.round(centers[0] - halfSize), Math.round(centers[1] - halfSize)] as Point, endPoint: [Math.round(centers[0] + halfSize), Math.round(centers[1] + halfSize)] as Point, landmarks: box.landmarks, confidence: box.confidence };\n};\n\nexport const calculateLandmarksBoundingBox = (landmarks) => {\n  const x = landmarks.map((d) => d[0]);\n  const y = landmarks.map((d) => d[1]);\n  return { startPoint: [Math.min(...x), Math.min(...y)] as Point, endPoint: [Math.max(...x), Math.max(...y)] as Point, landmarks };\n};\n\nexport const fixedRotationMatrix = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n\nexport const normalizeRadians = (angle) => angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n\nexport const computeRotation = (point1, point2) => normalizeRadians(Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]));\n\nexport const radToDegrees = (rad) => rad * 180 / Math.PI;\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport const dot = (v1: number[], v2: number[]) => {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) product += v1[i] * v2[i];\n  return product;\n};\n\nexport const getColumnFrom2DArr = (arr, columnIndex) => {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) column.push(arr[i][columnIndex]);\n  return column;\n};\n\nexport const multiplyTransformMatrices = (mat1, mat2) => {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n  }\n  return product;\n};\n\nexport const buildRotationMatrix = (rotation, center) => {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n};\n\nexport const invertTransformMatrix = (matrix) => {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [-dot(rotationComponent[0], translationComponent), -dot(rotationComponent[1], translationComponent)];\n  return [rotationComponent[0].concat(invertedTranslation[0]), rotationComponent[1].concat(invertedTranslation[1]), [0, 0, 1]];\n};\n\nexport const rotatePoint = (homogeneousCoordinate, rotationMatrix) => [dot(homogeneousCoordinate, rotationMatrix[0]), dot(homogeneousCoordinate, rotationMatrix[1])];\n\nexport const xyDistanceBetweenPoints = (a, b) => Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n\nexport function generateAnchors(inputSize) {\n  const spec = inputSize === 192\n    ? { strides: [4], anchors: [1] } // facemesh-detector\n    : { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] }; // blazeface\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) anchors.push([anchorX, anchorY]);\n      }\n    }\n  }\n  return anchors;\n}\n\nexport function transformRawCoords(coordsRaw, box, angle, rotationMatrix, inputSize) {\n  const boxSize = getBoxSize(box);\n  const coordsScaled = coordsRaw.map((coord) => ([ // scaled around zero-point\n    (boxSize[0] / inputSize) * (coord[0] - (inputSize / 2)),\n    (boxSize[1] / inputSize) * (coord[1] - (inputSize / 2)),\n    (coord[2] || 0),\n  ]));\n  const largeAngle = angle && (angle !== 0) && (Math.abs(angle) > 0.2);\n  const coordsRotationMatrix = largeAngle ? buildRotationMatrix(angle, [0, 0]) : fixedRotationMatrix;\n  const coordsRotated = largeAngle ? coordsScaled.map((coord) => ([...rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n  const inverseRotationMatrix = largeAngle ? invertTransformMatrix(rotationMatrix) : fixedRotationMatrix;\n  const boxCenter = getBoxCenter(box);\n  const offsets = [dot(boxCenter, inverseRotationMatrix[0]), dot(boxCenter, inverseRotationMatrix[1])];\n  return coordsRotated.map((coord) => ([\n    Math.trunc(coord[0] + offsets[0]),\n    Math.trunc(coord[1] + offsets[1]),\n    Math.trunc(coord[2] || 0),\n  ]));\n}\n\nexport function correctFaceRotation(rotate, box, input, inputSize) {\n  const symmetryLine = (box.landmarks.length >= coords.meshLandmarks.count)\n    ? coords.meshLandmarks.symmetryLine\n    : coords.blazeFaceLandmarks.symmetryLine;\n  let angle = 0; // default\n  let rotationMatrix = fixedRotationMatrix; // default\n  let face; // default\n\n  if (rotate && env.kernels.includes('rotatewithoffset')) { // rotateWithOffset is not defined for tfjs-node\n    angle = computeRotation(box.landmarks[symmetryLine[0]], box.landmarks[symmetryLine[1]]);\n    const largeAngle = angle && (angle !== 0) && (Math.abs(angle) > 0.2);\n    if (largeAngle) { // perform rotation only if angle is sufficiently high\n      const center: Point = getBoxCenter(box);\n      const centerRaw: Point = [center[0] / input.shape[2], center[1] / input.shape[1]];\n      const rotated = tf.image.rotateWithOffset(input, angle, 0, centerRaw);\n      rotationMatrix = buildRotationMatrix(-angle, center);\n      face = cutAndResize(box, rotated, [inputSize, inputSize]);\n      tf.dispose(rotated);\n    } else {\n      face = cutAndResize(box, input, [inputSize, inputSize]);\n    }\n  } else {\n    face = cutAndResize(box, input, [inputSize, inputSize]);\n  }\n  return [angle, rotationMatrix, face];\n}\n\nexport const findFaceCenter = (mesh) => {\n  const x = mesh.map((m) => m[0]);\n  const y = mesh.map((m) => m[1]);\n  // weighted center\n  /*\n  const sum = (arr: number[]) => arr.reduce((prev, curr) => prev + curr, 0);\n  return [sum(x) / mesh.length, sum(y) / mesh.length];\n  */\n  // absolute center\n  return [Math.min(...x) + (Math.max(...x) - Math.min(...x)) / 2, Math.min(...y) + (Math.max(...y) - Math.min(...y)) / 2];\n};\n\nexport const calculateFaceBox = (mesh, previousBox) => {\n  const center = findFaceCenter(mesh);\n  const boxSize = getBoxSize(previousBox);\n  const calculatedBox = {\n    startPoint: [center[0] - boxSize[0] / 2, center[1] - boxSize[1] / 2] as Point,\n    endPoint: [center[0] + boxSize[0] / 2, center[1] + boxSize[1] / 2] as Point,\n  };\n  return calculatedBox;\n};\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n * See `facemesh.ts` for entry point\n */\n\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as util from './facemeshutil';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport type { Config } from '../config';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport { env } from '../util/env';\nimport type { Point } from '../result';\n\nconst keypointsCount = 6;\nconst faceBoxScaleFactor = 1.4;\nlet model: GraphModel | null;\nlet anchors: Tensor | null = null;\nlet inputSize = 0;\nlet inputSizeT: Tensor | null = null;\n\ntype DetectBox = { startPoint: Point, endPoint: Point, landmarks: Array<Point>, confidence: number };\n\nexport const size = () => inputSize;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.detector?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  inputSizeT = tf.scalar(inputSize, 'int32') as Tensor;\n  anchors = tf.tensor2d(util.generateAnchors(inputSize)) as Tensor;\n  return model;\n}\n\nfunction decodeBoxes(boxOutputs: Tensor) {\n  const t: Record<string, Tensor> = {};\n  t.boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  t.centers = tf.add(t.boxStarts, anchors);\n  t.boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  t.boxSizesNormalized = tf.div(t.boxSizes, inputSizeT);\n  t.centersNormalized = tf.div(t.centers, inputSizeT);\n  t.halfBoxSize = tf.div(t.boxSizesNormalized, constants.tf2);\n  t.starts = tf.sub(t.centersNormalized, t.halfBoxSize);\n  t.ends = tf.add(t.centersNormalized, t.halfBoxSize);\n  t.startNormalized = tf.mul(t.starts, inputSizeT);\n  t.endNormalized = tf.mul(t.ends, inputSizeT);\n  const boxes = tf.concat2d([t.startNormalized, t.endNormalized], 1);\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return boxes;\n}\n\nexport async function getBoxes(inputImage: Tensor, config: Config) {\n  // sanity check on input\n  if ((!inputImage) || (inputImage['isDisposedInternal']) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return [];\n  const t: Record<string, Tensor> = {};\n  t.resized = tf.image.resizeBilinear(inputImage, [inputSize, inputSize]);\n  t.div = tf.div(t.resized, constants.tf127);\n  t.normalized = tf.sub(t.div, constants.tf05);\n  const res = model?.execute(t.normalized) as Tensor[];\n  if (Array.isArray(res) && res.length > 2) { // pinto converted model?\n    const sorted = res.sort((a, b) => a.size - b.size);\n    t.concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n    t.concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n    t.concat = tf.concat([t.concat512, t.concat384], 1);\n    t.batch = tf.squeeze(t.concat, 0);\n  } else if (Array.isArray(res)) { // new facemesh-detection tfhub model\n    t.batch = tf.squeeze(res[0]);\n  } else { // original blazeface tfhub model\n    t.batch = tf.squeeze(res);\n  }\n  tf.dispose(res);\n  t.boxes = decodeBoxes(t.batch);\n  t.logits = tf.slice(t.batch, [0, 0], [-1, 1]);\n  t.sigmoid = tf.sigmoid(t.logits);\n  t.scores = tf.squeeze(t.sigmoid);\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.scores, (config.face.detector?.maxDetected || 0), (config.face.detector?.iouThreshold || 0), (config.face.detector?.minConfidence || 0));\n  const nms = await t.nms.array() as number[];\n  const boxes: Array<DetectBox> = [];\n  const scores = await t.scores.data();\n  for (let i = 0; i < nms.length; i++) {\n    const confidence = scores[nms[i]];\n    if (confidence > (config.face.detector?.minConfidence || 0)) {\n      const b: Record<string, Tensor> = {};\n      b.bbox = tf.slice(t.boxes, [nms[i], 0], [1, -1]);\n      b.slice = tf.slice(t.batch, [nms[i], keypointsCount - 1], [1, -1]);\n      b.squeeze = tf.squeeze(b.slice);\n      b.landmarks = tf.reshape(b.squeeze, [keypointsCount, -1]);\n      const points = await b.bbox.data();\n      const rawBox = {\n        startPoint: [points[0], points[1]] as Point,\n        endPoint: [points[2], points[3]] as Point,\n        landmarks: (await b.landmarks.array()) as Point[],\n        confidence,\n      };\n      const scaledBox = util.scaleBoxCoordinates(rawBox, [(inputImage.shape[2] || 0) / inputSize, (inputImage.shape[1] || 0) / inputSize]);\n      const enlargedBox = util.enlargeBox(scaledBox, config.face['scale'] || faceBoxScaleFactor);\n      const squaredBox = util.squarifyBox(enlargedBox);\n      boxes.push(squaredBox);\n      Object.keys(b).forEach((tensor) => tf.dispose(b[tensor]));\n    }\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return boxes;\n}\n", "/* eslint-disable no-multi-spaces */\n\nexport const kpt: Array<string> = [\n  'nose',            //  0\n  'leftEyeInside',   //  1\n  'leftEye',         //  2\n  'leftEyeOutside',  //  3\n  'rightEyeInside',  //  4\n  'rightEye',        //  5\n  'rightEyeOutside', //  6\n  'leftEar',         //  7\n  'rightEar',        //  8\n  'leftMouth',       //  9\n  'rightMouth',      // 10\n  'leftShoulder',    // 11\n  'rightShoulder',   // 12\n  'leftElbow',       // 13\n  'rightElbow',      // 14\n  'leftWrist',       // 15\n  'rightWrist',      // 16\n  'leftPinky',       // 17\n  'rightPinky',      // 18\n  'leftIndex',       // 19\n  'rightIndex',      // 20\n  'leftThumb',       // 21\n  'rightThumb',      // 22\n  'leftHip',         // 23\n  'rightHip',        // 24\n  'leftKnee',        // 25\n  'rightKnee',       // 26\n  'leftAnkle',       // 27\n  'rightAnkle',      // 28\n  'leftHeel',        // 29\n  'rightHeel',       // 30\n  'leftFoot',        // 31\n  'rightFoot',       // 32\n  'bodyCenter',      // 33\n  'bodyTop',         // 34\n  'leftPalm',        // 35 // z-coord not ok\n  'leftHand',        // 36 // similar to wrist but z-coord not ok\n  'rightPalm',       // 37 // z-coord not ok\n  'rightHand',       // 38 // similar to wrist but z-coord not ok\n];\n\nexport const connected: Record<string, string[]> = {\n  shoulders: ['leftShoulder', 'rightShoulder'],\n  hips: ['rightHip', 'leftHip'],\n  mouth: ['leftMouth', 'rightMouth'],\n  leftLegUpper: ['leftHip', 'leftKnee'],\n  leftLegLower: ['leftKnee', 'leftAnkle'],\n  leftFoot: ['leftAnkle', 'leftHeel', 'leftFoot'],\n  leftTorso: ['leftShoulder', 'leftHip'],\n  leftArmUpper: ['leftShoulder', 'leftElbow'],\n  leftArmLower: ['leftElbow', 'leftWrist'],\n  leftHand: ['leftWrist', 'leftPalm'],\n  leftHandPinky: ['leftPalm', 'leftPinky'],\n  leftHandIndex: ['leftPalm', 'leftIndex'],\n  leftHandThumb: ['leftPalm', 'leftThumb'],\n  leftEyeOutline: ['leftEyeInside', 'leftEyeOutside'],\n  rightLegUpper: ['rightHip', 'rightKnee'],\n  rightLegLower: ['rightKnee', 'rightAnkle'],\n  rightFoot: ['rightAnkle', 'rightHeel', 'rightFoot'],\n  rightTorso: ['rightShoulder', 'rightHip'],\n  rightArmUpper: ['rightShoulder', 'rightElbow'],\n  rightArmLower: ['rightElbow', 'rightWrist'],\n  rightHand: ['rightWrist', 'rightPalm'],\n  rightHandPinky: ['rightPalm', 'rightPinky'],\n  rightHandIndex: ['rightPalm', 'rightIndex'],\n  rightHandThumb: ['rightPalm', 'rightThumb'],\n  rightEyeOutline: ['rightEyeInside', 'rightEyeOutside'],\n};\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from '../tfjs/types';\nimport type { Box } from '../result';\nimport type { Config } from '../config';\n\ninterface DetectedBox { box: Box, boxRaw: Box, score: number }\n\nconst inputSize = 224;\nlet anchorTensor: { x, y };\nconst numLayers = 5;\nconst strides = [8, 16, 32, 32, 32];\n\nexport async function createAnchors() {\n  const anchors: Array<{ x: number, y: number }> = [];\n  let layerId = 0;\n  while (layerId < numLayers) {\n    let anchorCount = 0;\n    let lastSameStrideLayer = layerId;\n    while (lastSameStrideLayer < strides.length && strides[lastSameStrideLayer] === strides[layerId]) {\n      anchorCount += 2;\n      lastSameStrideLayer++;\n    }\n    const stride = strides[layerId];\n    const featureMapHeight = Math.ceil(inputSize / stride);\n    const featureMapWidth = Math.ceil(inputSize / stride);\n    for (let y = 0; y < featureMapHeight; ++y) {\n      for (let x = 0; x < featureMapWidth; ++x) {\n        for (let anchorId = 0; anchorId < anchorCount; ++anchorId) {\n          anchors.push({ x: (x + 0.5) / featureMapWidth, y: (y + 0.5) / featureMapHeight });\n        }\n      }\n    }\n    layerId = lastSameStrideLayer;\n  }\n  anchorTensor = { x: tf.tensor1d(anchors.map((a) => a.x)), y: tf.tensor1d(anchors.map((a) => a.y)) };\n}\n\nconst cropFactor = [5.0, 5.0];\nfunction decodeBoxes(boxesTensor, anchor): Tensor {\n  return tf.tidy(() => {\n    const split = tf.split(boxesTensor, 12, 1); // first 4 are box data [x,y,w,h] and 4 are keypoints data [x,y] for total of 12\n    let xCenter = tf.squeeze(split[0]);\n    let yCenter = tf.squeeze(split[1]);\n    let width = tf.squeeze(split[2]);\n    let height = tf.squeeze(split[3]);\n    xCenter = tf.add(tf.div(xCenter, inputSize), anchor.x);\n    yCenter = tf.add(tf.div(yCenter, inputSize), anchor.y);\n    width = tf.mul(tf.div(width, inputSize), cropFactor[0]);\n    height = tf.mul(tf.div(height, inputSize), cropFactor[1]);\n    const xMin = tf.sub(xCenter, tf.div(width, 2));\n    const yMin = tf.sub(yCenter, tf.div(height, 2));\n    const boxes = tf.stack([xMin, yMin, width, height], 1);\n    return boxes;\n  });\n}\n\nexport async function decode(boxesTensor: Tensor, logitsTensor: Tensor, config: Config, outputSize: [number, number]): Promise<DetectedBox[]> {\n  const t: Record<string, Tensor> = {};\n  t.boxes = decodeBoxes(boxesTensor, anchorTensor);\n  t.scores = tf.sigmoid(logitsTensor);\n  t.argmax = tf.argMax(t.scores);\n  const i = (await t.argmax.data())[0] as number;\n  const scores = await t.scores.data();\n  const detected: Array<{ box: Box, boxRaw: Box, score: number }> = [];\n  const minScore = (config.body['detector'] && config.body['detector']['minConfidence']) ? config.body['detector']['minConfidence'] : 0;\n  if (scores[i] >= minScore) {\n    const boxes = await t.boxes.array();\n    const boxRaw: Box = boxes[i];\n    const box: Box = [boxRaw[0] * outputSize[0], boxRaw[1] * outputSize[1], boxRaw[2] * outputSize[0], boxRaw[3] * outputSize[1]];\n    // console.log(box);\n    detected.push({ box, boxRaw, score: scores[i] });\n  }\n  /*\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.scores, 1, config.body.detector?.minConfidence || 0.1, config.body.detector?.iouThreshold || 0.1);\n  const boxes = t.boxes.arraySync();\n  const scores = t.scores.dataSync();\n  const nms = t.nms.dataSync();\n  const detected: Array<DetectedBox> = [];\n  for (const i of Array.from(nms)) {\n    const boxRaw: Box = boxes[i];\n    const box: Box = [boxRaw[0] * outputSize[0], boxRaw[0] * outputSize[1], boxRaw[3] * outputSize[0], boxRaw[2] * outputSize[1]];\n    detected.push({ box, boxRaw, score: scores[i] });\n  }\n  */\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return detected;\n}\n", "import type { Point, Box } from '../result';\n\nexport function calc(keypoints: Array<Point>, outputSize: [number, number] = [1, 1]) {\n  const coords = [keypoints.map((pt) => pt[0]), keypoints.map((pt) => pt[1])]; // all x/y coords\n  const min = [Math.min(...coords[0]), Math.min(...coords[1])];\n  const max = [Math.max(...coords[0]), Math.max(...coords[1])];\n  const box: Box = [min[0], min[1], max[0] - min[0], max[1] - min[1]];\n  const boxRaw: Box = [box[0] / outputSize[0], box[1] / outputSize[1], box[2] / outputSize[0], box[3] / outputSize[1]];\n  return { box, boxRaw };\n}\n\nexport function square(keypoints: Array<Point>, outputSize: [number, number] = [1, 1]) {\n  const coords = [keypoints.map((pt) => pt[0]), keypoints.map((pt) => pt[1])]; // all x/y coords\n  const min = [Math.min(...coords[0]), Math.min(...coords[1])];\n  const max = [Math.max(...coords[0]), Math.max(...coords[1])];\n  const center = [(min[0] + max[0]) / 2, (min[1] + max[1]) / 2]; // find center x and y coord of all fingers\n  const dist = Math.max(center[0] - min[0], center[1] - min[1], -center[0] + max[0], -center[1] + max[1]); // largest distance from center in any direction\n  const box: Box = [Math.trunc(center[0] - dist), Math.trunc(center[1] - dist), Math.trunc(2 * dist), Math.trunc(2 * dist)];\n  const boxRaw: Box = [box[0] / outputSize[0], box[1] / outputSize[1], box[2] / outputSize[0], box[3] / outputSize[1]];\n  return { box, boxRaw };\n}\n\nexport function scale(box: Box, scaleFact: number) {\n  const dist = [box[2] * scaleFact, box[3] * scaleFact];\n  const newBox: Box = [\n    box[0] - (dist[0] - box[2]) / 2,\n    box[1] - (dist[1] - box[3]) / 2,\n    dist[0],\n    dist[1],\n  ];\n  return newBox;\n}\n\nexport function crop(box: Box) { // [y1, x1, y2, x2] clamped to 0..1\n  const yxBox: Box = [Math.max(0, box[1]), Math.max(0, box[0]), Math.min(1, box[3] + box[1]), Math.min(1, box[2] + box[0])];\n  return yxBox;\n}\n", "/**\n * BlazePose model implementation\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport { log, now } from '../util/util';\nimport type { BodyKeypoint, BodyResult, BodyLandmark, Box, Point, BodyAnnotation } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport * as coords from './blazeposecoords';\nimport * as detect from './blazeposedetector';\nimport * as box from '../util/box';\n\nconst env = { initial: true };\n// const models: [GraphModel | null, GraphModel | null] = [null, null];\nconst models: { detector: GraphModel | null, landmarks: GraphModel | null } = { detector: null, landmarks: null };\nconst inputSize: { detector: [number, number], landmarks: [number, number] } = { detector: [224, 224], landmarks: [256, 256] };\nlet skipped = Number.MAX_SAFE_INTEGER;\nconst outputNodes: { detector: string[], landmarks: string[] } = {\n  landmarks: ['ld_3d', 'activation_segmentation', 'activation_heatmap', 'world_3d', 'output_poseflag'],\n  detector: [],\n};\n\nlet cache: BodyResult | null = null;\nlet cropBox: Box | undefined;\nlet padding: [number, number][] = [[0, 0], [0, 0], [0, 0], [0, 0]];\nlet lastTime = 0;\n\nconst sigmoid = (x) => (1 - (1 / (1 + Math.exp(x))));\n\nexport async function loadDetect(config: Config): Promise<GraphModel> {\n  if (env.initial) models.detector = null;\n  if (!models.detector && config.body['detector'] && config.body['detector']['modelPath'] || '') {\n    models.detector = await loadModel(config.body['detector']['modelPath']);\n    const inputs = Object.values(models.detector.modelSignature['inputs']);\n    inputSize.detector[0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize.detector[1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug && models.detector) log('cached model:', models.detector['modelUrl']);\n  await detect.createAnchors();\n  return models.detector as GraphModel;\n}\n\nexport async function loadPose(config: Config): Promise<GraphModel> {\n  if (env.initial) models.landmarks = null;\n  if (!models.landmarks) {\n    models.landmarks = await loadModel(config.body.modelPath);\n    const inputs = Object.values(models.landmarks.modelSignature['inputs']);\n    inputSize.landmarks[0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize.landmarks[1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', models.landmarks['modelUrl']);\n  return models.landmarks;\n}\n\nexport async function load(config: Config): Promise<[GraphModel | null, GraphModel | null]> {\n  if (!models.detector) await loadDetect(config);\n  if (!models.landmarks) await loadPose(config);\n  return [models.detector, models.landmarks];\n}\n\nasync function prepareImage(input: Tensor, size: number): Promise<Tensor> {\n  const t: Record<string, Tensor> = {};\n  if (!input.shape || !input.shape[1] || !input.shape[2]) return input;\n  let final: Tensor;\n  if (cropBox) {\n    t.cropped = tf.image.cropAndResize(input, [cropBox], [0], [input.shape[1], input.shape[2]]); // if we have cached box use it to crop input\n  }\n  if (input.shape[1] !== input.shape[2]) { // only pad if width different than height\n    const height: [number, number] = [\n      input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0,\n      input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0,\n    ];\n    const width: [number, number] = [\n      input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0,\n      input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0,\n    ];\n    padding = [\n      [0, 0], // dont touch batch\n      height, // height before&after\n      width, // width before&after\n      [0, 0], // dont touch rbg\n    ];\n    t.pad = tf.pad(t.cropped || input, padding); // use cropped box if it exists\n    t.resize = tf.image.resizeBilinear(t.pad, [size, size]);\n    final = tf.div(t.resize, constants.tf255);\n  } else if (input.shape[1] !== size) { // if input needs resizing\n    t.resize = tf.image.resizeBilinear(t.cropped || input, [size, size]);\n    final = tf.div(t.resize, constants.tf255);\n  } else { // if input is already in a correct resolution just normalize it\n    final = tf.div(t.cropped || input, constants.tf255);\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return final;\n}\n\nfunction rescaleKeypoints(keypoints: Array<BodyKeypoint>, outputSize: [number, number]): Array<BodyKeypoint> {\n  for (const kpt of keypoints) { // first rescale due to padding\n    kpt.position = [\n      Math.trunc(kpt.position[0] * (outputSize[0] + padding[2][0] + padding[2][1]) / outputSize[0] - padding[2][0]),\n      Math.trunc(kpt.position[1] * (outputSize[1] + padding[1][0] + padding[1][1]) / outputSize[1] - padding[1][0]),\n      kpt.position[2] as number,\n    ];\n    kpt.positionRaw = [kpt.position[0] / outputSize[0], kpt.position[1] / outputSize[1], 2 * (kpt.position[2] as number) / (outputSize[0] + outputSize[1])];\n  }\n  if (cropBox) { // second rescale due to cropping\n    for (const kpt of keypoints) {\n      kpt.positionRaw = [\n        kpt.positionRaw[0] + cropBox[1], // correct offset due to crop\n        kpt.positionRaw[1] + cropBox[0], // correct offset due to crop\n        kpt.positionRaw[2] as number,\n      ];\n      kpt.position = [\n        Math.trunc(kpt.positionRaw[0] * outputSize[0]),\n        Math.trunc(kpt.positionRaw[1] * outputSize[1]),\n        kpt.positionRaw[2] as number,\n      ];\n    }\n  }\n  return keypoints;\n}\n\nasync function fixKeypoints(keypoints: Array<BodyKeypoint>) {\n  // palm z-coord is incorrect around near-zero so we approximate it\n  const leftPalm = keypoints.find((k) => k.part === 'leftPalm') as BodyKeypoint;\n  const leftWrist = keypoints.find((k) => k.part === 'leftWrist') as BodyKeypoint;\n  const leftIndex = keypoints.find((k) => k.part === 'leftIndex') as BodyKeypoint;\n  leftPalm.position[2] = ((leftWrist.position[2] || 0) + (leftIndex.position[2] || 0)) / 2;\n  const rightPalm = keypoints.find((k) => k.part === 'rightPalm') as BodyKeypoint;\n  const rightWrist = keypoints.find((k) => k.part === 'rightWrist') as BodyKeypoint;\n  const rightIndex = keypoints.find((k) => k.part === 'rightIndex') as BodyKeypoint;\n  rightPalm.position[2] = ((rightWrist.position[2] || 0) + (rightIndex.position[2] || 0)) / 2;\n}\n\nasync function detectLandmarks(input: Tensor, config: Config, outputSize: [number, number]): Promise<BodyResult | null> {\n  /**\n   * t.ld: 39 keypoints [x,y,z,score,presence] normalized to input size\n   * t.segmentation:\n   * t.heatmap:\n   * t.world: 39 keypoints [x,y,z] normalized to -1..1\n   * t.poseflag: body score\n  */\n  const t: Record<string, Tensor> = {};\n  [t.ld/* 1,195(39*5) */, t.segmentation/* 1,256,256,1 */, t.heatmap/* 1,64,64,39 */, t.world/* 1,117(39*3) */, t.poseflag/* 1,1 */] = models.landmarks?.execute(input, outputNodes.landmarks) as Tensor[]; // run model\n  const poseScore = (await t.poseflag.data())[0];\n  const points = await t.ld.data();\n  const distances = await t.world.data();\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor])); // dont need tensors after this\n  const keypointsRelative: Array<BodyKeypoint> = [];\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    const score = sigmoid(points[depth * i + 3]);\n    const presence = sigmoid(points[depth * i + 4]);\n    const adjScore = Math.trunc(100 * score * presence * poseScore) / 100;\n    const positionRaw: Point = [points[depth * i + 0] / inputSize.landmarks[0], points[depth * i + 1] / inputSize.landmarks[1], points[depth * i + 2] + 0];\n    const position: Point = [Math.trunc(outputSize[0] * positionRaw[0]), Math.trunc(outputSize[1] * positionRaw[1]), positionRaw[2] as number];\n    const distance: Point = [distances[depth * i + 0], distances[depth * i + 1], distances[depth * i + 2] + 0];\n    keypointsRelative.push({ part: coords.kpt[i] as BodyLandmark, positionRaw, position, distance, score: adjScore });\n  }\n  if (poseScore < (config.body.minConfidence || 0)) return null;\n  fixKeypoints(keypointsRelative);\n  const keypoints: Array<BodyKeypoint> = rescaleKeypoints(keypointsRelative, outputSize); // keypoints were relative to input image which is padded\n  const kpts = keypoints.map((k) => k.position);\n  const boxes = box.calc(kpts, [outputSize[0], outputSize[1]]); // now find boxes based on rescaled keypoints\n  const annotations: Record<BodyAnnotation, Point[][]> = {} as Record<BodyAnnotation, Point[][]>;\n  for (const [name, indexes] of Object.entries(coords.connected)) {\n    const pt: Array<Point[]> = [];\n    for (let i = 0; i < indexes.length - 1; i++) {\n      const pt0 = keypoints.find((kpt) => kpt.part === indexes[i]);\n      const pt1 = keypoints.find((kpt) => kpt.part === indexes[i + 1]);\n      if (pt0 && pt1) pt.push([pt0.position, pt1.position]);\n    }\n    annotations[name] = pt;\n  }\n  const body = { id: 0, score: Math.trunc(100 * poseScore) / 100, box: boxes.box, boxRaw: boxes.boxRaw, keypoints, annotations };\n  return body;\n}\n\n/*\ninterface DetectedBox { box: Box, boxRaw: Box, score: number }\n\nfunction rescaleBoxes(boxes: Array<DetectedBox>, outputSize: [number, number]): Array<DetectedBox> {\n  for (const b of boxes) {\n    b.box = [\n      Math.trunc(b.box[0] * (outputSize[0] + padding[2][0] + padding[2][1]) / outputSize[0]),\n      Math.trunc(b.box[1] * (outputSize[1] + padding[1][0] + padding[1][1]) / outputSize[1]),\n      Math.trunc(b.box[2] * (outputSize[0] + padding[2][0] + padding[2][1]) / outputSize[0]),\n      Math.trunc(b.box[3] * (outputSize[1] + padding[1][0] + padding[1][1]) / outputSize[1]),\n    ];\n    b.boxRaw = [b.box[0] / outputSize[0], b.box[1] / outputSize[1], b.box[2] / outputSize[0], b.box[3] / outputSize[1]];\n  }\n  return boxes;\n}\n\nasync function detectBoxes(input: Tensor, config: Config, outputSize: [number, number]) {\n  const t: Record<string, Tensor> = {};\n  t.res = models.detector?.execute(input, ['Identity']) as Tensor; //\n  t.logitsRaw = tf.slice(t.res, [0, 0, 0], [1, -1, 1]);\n  t.boxesRaw = tf.slice(t.res, [0, 0, 1], [1, -1, -1]);\n  t.logits = tf.squeeze(t.logitsRaw);\n  t.boxes = tf.squeeze(t.boxesRaw);\n  const boxes = await detect.decode(t.boxes, t.logits, config, outputSize);\n  rescaleBoxes(boxes, outputSize);\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return boxes;\n}\n*/\n\nexport async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {\n  const outputSize: [number, number] = [input.shape[2] || 0, input.shape[1] || 0];\n  const skipTime = (config.body.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.body.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && cache !== null) {\n    skipped++;\n  } else {\n    const t: Record<string, Tensor> = {};\n    /*\n    if (config.body['detector'] && config.body['detector']['enabled']) {\n      t.detector = await prepareImage(input, 224);\n      const boxes = await detectBoxes(t.detector, config, outputSize);\n    }\n    */\n    t.landmarks = await prepareImage(input, 256); // padded and resized\n    cache = await detectLandmarks(t.landmarks, config, outputSize);\n    /*\n    cropBox = [0, 0, 1, 1]; // reset crop coordinates\n    if (cache?.boxRaw && config.skipAllowed) {\n      const cx = (2.0 * cache.boxRaw[0] + cache.boxRaw[2]) / 2;\n      const cy = (2.0 * cache.boxRaw[1] + cache.boxRaw[3]) / 2;\n      let size = cache.boxRaw[2] > cache.boxRaw[3] ? cache.boxRaw[2] : cache.boxRaw[3];\n      size = (size * 1.0) / 2; // enlarge and half it\n      if (cx > 0.1 && cx < 0.9 && cy > 0.1 && cy < 0.9 && size > 0.1) { // only update if box is sane\n        const y = 0; // cy - size;\n        const x = cx - size;\n        cropBox = [y, x, y + 1, x + 1]; // [y0,x0,y1,x1] used for cropping but width/height are not yet implemented so we only reposition image to center of body\n      }\n    }\n    */\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    lastTime = now();\n    skipped = 0;\n  }\n  return cache ? [cache] : [];\n}\n", "/**\n * CoCo Labels used by object detection implementations\n */\nexport const labels = [\n  { class: 1, label: 'person' },\n  { class: 2, label: 'bicycle' },\n  { class: 3, label: 'car' },\n  { class: 4, label: 'motorcycle' },\n  { class: 5, label: 'airplane' },\n  { class: 6, label: 'bus' },\n  { class: 7, label: 'train' },\n  { class: 8, label: 'truck' },\n  { class: 9, label: 'boat' },\n  { class: 10, label: 'traffic light' },\n  { class: 11, label: 'fire hydrant' },\n  { class: 12, label: 'stop sign' },\n  { class: 13, label: 'parking meter' },\n  { class: 14, label: 'bench' },\n  { class: 15, label: 'bird' },\n  { class: 16, label: 'cat' },\n  { class: 17, label: 'dog' },\n  { class: 18, label: 'horse' },\n  { class: 19, label: 'sheep' },\n  { class: 20, label: 'cow' },\n  { class: 21, label: 'elephant' },\n  { class: 22, label: 'bear' },\n  { class: 23, label: 'zebra' },\n  { class: 24, label: 'giraffe' },\n  { class: 25, label: 'backpack' },\n  { class: 26, label: 'umbrella' },\n  { class: 27, label: 'handbag' },\n  { class: 28, label: 'tie' },\n  { class: 29, label: 'suitcase' },\n  { class: 30, label: 'frisbee' },\n  { class: 31, label: 'skis' },\n  { class: 32, label: 'snowboard' },\n  { class: 33, label: 'sports ball' },\n  { class: 34, label: 'kite' },\n  { class: 35, label: 'baseball bat' },\n  { class: 36, label: 'baseball glove' },\n  { class: 37, label: 'skateboard' },\n  { class: 38, label: 'surfboard' },\n  { class: 39, label: 'tennis racket' },\n  { class: 40, label: 'bottle' },\n  { class: 41, label: 'wine glass' },\n  { class: 42, label: 'cup' },\n  { class: 43, label: 'fork' },\n  { class: 44, label: 'knife' },\n  { class: 45, label: 'spoon' },\n  { class: 46, label: 'bowl' },\n  { class: 47, label: 'banana' },\n  { class: 48, label: 'apple' },\n  { class: 49, label: 'sandwich' },\n  { class: 50, label: 'orange' },\n  { class: 51, label: 'broccoli' },\n  { class: 52, label: 'carrot' },\n  { class: 53, label: 'hot dog' },\n  { class: 54, label: 'pizza' },\n  { class: 55, label: 'donut' },\n  { class: 56, label: 'cake' },\n  { class: 57, label: 'chair' },\n  { class: 58, label: 'couch' },\n  { class: 59, label: 'potted plant' },\n  { class: 60, label: 'bed' },\n  { class: 61, label: 'dining table' },\n  { class: 62, label: 'toilet' },\n  { class: 63, label: 'tv' },\n  { class: 64, label: 'laptop' },\n  { class: 65, label: 'mouse' },\n  { class: 66, label: 'remote' },\n  { class: 67, label: 'keyboard' },\n  { class: 68, label: 'cell phone' },\n  { class: 69, label: 'microwave' },\n  { class: 70, label: 'oven' },\n  { class: 71, label: 'toaster' },\n  { class: 72, label: 'sink' },\n  { class: 73, label: 'refrigerator' },\n  { class: 74, label: 'book' },\n  { class: 75, label: 'clock' },\n  { class: 76, label: 'vase' },\n  { class: 77, label: 'scissors' },\n  { class: 78, label: 'teddy bear' },\n  { class: 79, label: 'hair drier' },\n  { class: 80, label: 'toothbrush' },\n];\n", "/**\n * CenterNet object detection model implementation\n *\n * Based on: [**NanoDet**](https://github.com/RangiLyu/nanodet)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { labels } from './labels';\nimport type { ObjectResult, ObjectType, Box } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nlet inputSize = 0;\nlet last: ObjectResult[] = [];\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) {\n    // fakeOps(['floormod'], config);\n    model = await loadModel(config.object.modelPath);\n    const inputs = Object.values(model.modelSignature['inputs']);\n    inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nasync function process(res: Tensor | null, outputShape: [number, number], config: Config) {\n  if (!res) return [];\n  const t: Record<string, Tensor> = {};\n  const results: Array<ObjectResult> = [];\n  const detections = await res.array() as number[][][];\n  t.squeeze = tf.squeeze(res);\n  const arr = tf.split(t.squeeze, 6, 1) as Tensor[]; // x1, y1, x2, y2, score, class\n  t.stack = tf.stack([arr[1], arr[0], arr[3], arr[2]], 1); // reorder dims as tf.nms expects y, x\n  t.boxes = tf.squeeze(t.stack);\n  t.scores = tf.squeeze(arr[4]);\n  t.classes = tf.squeeze(arr[5]);\n  tf.dispose([res, ...arr]);\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.scores, config.object.maxDetected, config.object.iouThreshold, (config.object.minConfidence || 0));\n  const nms = await t.nms.data();\n  let i = 0;\n  for (const id of Array.from(nms)) {\n    const score = Math.trunc(100 * detections[0][id][4]) / 100;\n    const classVal = detections[0][id][5];\n    const label = labels[classVal].label as ObjectType;\n    const [x, y] = [\n      detections[0][id][0] / inputSize,\n      detections[0][id][1] / inputSize,\n    ];\n    const boxRaw: Box = [\n      x,\n      y,\n      detections[0][id][2] / inputSize - x,\n      detections[0][id][3] / inputSize - y,\n    ];\n    const box: Box = [\n      Math.trunc(boxRaw[0] * outputShape[0]),\n      Math.trunc(boxRaw[1] * outputShape[1]),\n      Math.trunc(boxRaw[2] * outputShape[0]),\n      Math.trunc(boxRaw[3] * outputShape[1]),\n    ];\n    results.push({ id: i++, score, class: classVal, label, box, boxRaw });\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return results;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<ObjectResult[]> {\n  const skipTime = (config.object.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.object.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const outputSize = [input.shape[2] || 0, input.shape[1] || 0] as [number, number];\n    const resize = tf.image.resizeBilinear(input, [inputSize, inputSize]);\n    const objectT = config.object.enabled ? model?.execute(resize, ['tower_0/detections']) as Tensor : null;\n    lastTime = now();\n    tf.dispose(resize);\n\n    const obj = await process(objectT, outputSize, config);\n    last = obj;\n\n    resolve(obj);\n  });\n}\n", "export const kpt: Array<string> = [\n  'head',\n  'neck',\n  'rightShoulder',\n  'rightElbow',\n  'rightWrist',\n  'chest',\n  'leftShoulder',\n  'leftElbow',\n  'leftWrist',\n  'bodyCenter',\n  'rightHip',\n  'rightKnee',\n  'rightAnkle',\n  'leftHip',\n  'leftKnee',\n  'leftAnkle',\n];\n\nexport const connected: Record<string, string[]> = {\n  leftLeg: ['leftHip', 'leftKnee', 'leftAnkle'],\n  rightLeg: ['rightHip', 'rightKnee', 'rightAnkle'],\n  torso: ['leftShoulder', 'rightShoulder', 'rightHip', 'leftHip', 'leftShoulder'],\n  leftArm: ['leftShoulder', 'leftElbow', 'leftWrist'],\n  rightArm: ['rightShoulder', 'rightElbow', 'rightWrist'],\n  head: [],\n};\n", "/**\n * EfficientPose model implementation\n *\n * Based on: [**EfficientPose**](https://github.com/daniegr/EfficientPose)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport * as coords from './efficientposecoords';\nimport { constants } from '../tfjs/constants';\nimport type { BodyResult, Point, BodyLandmark, BodyAnnotation } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nlet lastTime = 0;\nconst cache: BodyResult = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} as Record<BodyAnnotation, Point[][]> };\n\n// const keypoints: Array<BodyKeypoint> = [];\n// let box: Box = [0, 0, 0, 0];\n// let boxRaw: Box = [0, 0, 0, 0];\n// let score = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.body.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// performs argmax and max functions on a 2d tensor\nasync function max2d(inputs, minScore) {\n  const [width, height] = inputs.shape;\n  const reshaped = tf.reshape(inputs, [height * width]); // combine all data\n  const max = tf.max(reshaped, 0);\n  const newScore = (await max.data())[0]; // get highest score\n  tf.dispose([reshaped, max]);\n  if (newScore > minScore) { // skip coordinate calculation is score is too low\n    const coordinates = tf.argMax(reshaped, 0);\n    const mod = tf.mod(coordinates, width);\n    const x = (await mod.data())[0];\n    const div = tf.div(coordinates, tf.scalar(width, 'int32'));\n    const y = (await div.data())[0];\n    tf.dispose([mod, div]);\n    return [x, y, newScore];\n  }\n  return [0, 0, newScore];\n}\n\nexport async function predict(image: Tensor, config: Config): Promise<BodyResult[]> {\n  const skipTime = (config.body.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.body.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && Object.keys(cache.keypoints).length > 0) {\n    skipped++;\n    return [cache];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const tensor = tf.tidy(() => {\n      if (!model?.inputs[0].shape) return null;\n      const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n      const enhance = tf.mul(resize, constants.tf2);\n      const norm = tf.sub(enhance, constants.tf1);\n      return norm;\n    });\n\n    let resT;\n    if (config.body.enabled) resT = model?.execute(tensor);\n    lastTime = now();\n    tf.dispose(tensor);\n\n    if (resT) {\n      cache.keypoints.length = 0;\n      const squeeze = resT.squeeze();\n      tf.dispose(resT);\n      // body parts are basically just a stack of 2d tensors\n      const stack = squeeze.unstack(2);\n      tf.dispose(squeeze);\n      // process each unstacked tensor as a separate body part\n      for (let id = 0; id < stack.length; id++) {\n        // actual processing to get coordinates and score\n        const [x, y, partScore] = await max2d(stack[id], config.body.minConfidence);\n        if (partScore > (config.body?.minConfidence || 0)) {\n          cache.keypoints.push({\n            score: Math.round(100 * partScore) / 100,\n            part: coords.kpt[id] as BodyLandmark,\n            positionRaw: [ // normalized to 0..1\n              // @ts-ignore model is not undefined here\n              x / model.inputs[0].shape[2], y / model.inputs[0].shape[1],\n            ],\n            position: [ // normalized to input image size\n              // @ts-ignore model is not undefined here\n              Math.round(image.shape[2] * x / model.inputs[0].shape[2]), Math.round(image.shape[1] * y / model.inputs[0].shape[1]),\n            ],\n          });\n        }\n      }\n      stack.forEach((s) => tf.dispose(s));\n    }\n    cache.score = cache.keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n    const x = cache.keypoints.map((a) => a.position[0]);\n    const y = cache.keypoints.map((a) => a.position[1]);\n    cache.box = [\n      Math.min(...x),\n      Math.min(...y),\n      Math.max(...x) - Math.min(...x),\n      Math.max(...y) - Math.min(...y),\n    ];\n    const xRaw = cache.keypoints.map((a) => a.positionRaw[0]);\n    const yRaw = cache.keypoints.map((a) => a.positionRaw[1]);\n    cache.boxRaw = [\n      Math.min(...xRaw),\n      Math.min(...yRaw),\n      Math.max(...xRaw) - Math.min(...xRaw),\n      Math.max(...yRaw) - Math.min(...yRaw),\n    ];\n    for (const [name, indexes] of Object.entries(coords.connected)) {\n      const pt: Array<Point[]> = [];\n      for (let i = 0; i < indexes.length - 1; i++) {\n        const pt0 = cache.keypoints.find((kpt) => kpt.part === indexes[i]);\n        const pt1 = cache.keypoints.find((kpt) => kpt.part === indexes[i + 1]);\n        if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n      }\n      cache.annotations[name] = pt;\n    }\n    resolve([cache]);\n  });\n}\n", "/**\n * Emotion model implementation\n *\n * [**Oarriaga**](https://github.com/oarriaga/face_classification)\n */\n\nimport type { Emotion } from '../result';\nimport { log, now } from '../util/util';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { env } from '../util/env';\nimport { constants } from '../tfjs/constants';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model: GraphModel | null;\nconst last: Array<Array<{ score: number, emotion: Emotion }>> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.emotion?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<Array<{ score: number, emotion: Emotion }>> {\n  if (!model) return [];\n  const skipFrame = skipped < (config.face.emotion?.skipFrames || 0);\n  const skipTime = (config.face.emotion?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && last[idx] && (last[idx].length > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const obj: Array<{ score: number, emotion: Emotion }> = [];\n    if (config.face.emotion?.enabled) {\n      const t: Record<string, Tensor> = {};\n      const inputSize = model?.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n      t.resize = tf.image.resizeBilinear(image, [inputSize, inputSize], false);\n      // const box = [[0.15, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n      // const resize = tf.image.cropAndResize(image, box, [0], [inputSize, inputSize]);\n      // [t.red, t.green, t.blue] = tf.split(t.resize, 3, 3);\n      // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n      // t.redNorm = tf.mul(t.red, rgb[0]);\n      // t.greenNorm = tf.mul(t.green, rgb[1]);\n      // t.blueNorm = tf.mul(t.blue, rgb[2]);\n      // t.grayscale = tf.addN([t.redNorm, t.greenNorm, t.blueNorm]);\n      t.channels = tf.mul(t.resize, constants.rgb);\n      t.grayscale = tf.sum(t.channels, 3, true);\n      t.grayscaleSub = tf.sub(t.grayscale, constants.tf05);\n      t.grayscaleMul = tf.mul(t.grayscaleSub, constants.tf2);\n      t.emotion = model?.execute(t.grayscaleMul) as Tensor; // result is already in range 0..1, no need for additional activation\n      lastTime = now();\n      const data = await t.emotion.data();\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > (config.face.emotion?.minConfidence || 0)) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] as Emotion });\n      }\n      obj.sort((a, b) => b.score - a.score);\n      Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    }\n    last[idx] = obj;\n    lastCount = count;\n    resolve(obj);\n  });\n}\n", "/**\n * EfficientPose model implementation\n *\n * Based on: [**BecauseofAI MobileFace**](https://github.com/becauseofAI/MobileFace)\n *\n * Obsolete and replaced by `faceres` that performs age/gender/descriptor analysis\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst last: Array<number[]> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['mobilefacenet'].modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n/*\n// convert to black&white to avoid colorization impact\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\nconst [red, green, blue] = tf.split(crop, 3, 3);\nconst redNorm = tf.mul(red, rgb[0]);\nconst greenNorm = tf.mul(green, rgb[1]);\nconst blueNorm = tf.mul(blue, rgb[2]);\nconst grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\nconst merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n// optional increase image contrast\n// or do it per-channel so mean is done on each channel\n// or do it based on histogram\nconst mean = merge.mean();\nconst factor = 5;\nconst contrast = merge.sub(mean).mul(factor).add(mean);\n*/\n\nexport async function predict(input: Tensor, config: Config, idx, count): Promise<number[]> {\n  if (!model) return [];\n  const skipFrame = skipped < (config.face['embedding']?.skipFrames || 0);\n  const skipTime = (config.face['embedding']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && last[idx]) {\n    skipped++;\n    return last[idx];\n  }\n  return new Promise(async (resolve) => {\n    let data: Array<number> = [];\n    if (config.face['embedding']?.enabled && model?.inputs[0].shape) {\n      const t: Record<string, Tensor> = {};\n      t.crop = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n      // do a tight crop of image and resize it to fit the model\n      // const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n      // t.crop = tf.image.cropAndResize(input, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n      t.data = model?.execute(t.crop) as Tensor;\n      /*\n      // optional normalize outputs with l2 normalization\n      const scaled = tf.tidy(() => {\n        const l2 = res.norm('euclidean');\n        const scale = res.div(l2);\n        return scale;\n      });\n\n      // optional reduce feature vector complexity\n      const reshape = tf.reshape(res, [128, 2]); // split 256 vectors into 128 x 2\n      const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n      */\n      const output = await t.data.data();\n      data = Array.from(output); // convert typed array to simple array\n    }\n    last[idx] = data;\n    lastCount = count;\n    lastTime = now();\n    resolve(data);\n  });\n}\n", "import * as coords from './facemeshcoords';\nimport * as util from './facemeshutil';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport { env } from '../util/env';\nimport { log } from '../util/util';\nimport { loadModel } from '../tfjs/load';\nimport type { Config } from '../config';\nimport type { Point } from '../result';\n\nlet model: GraphModel | null;\nlet inputSize = 0;\n\nconst irisEnlarge = 2.3;\n\nconst leftOutline = coords.meshAnnotations['leftEyeLower0'];\nconst rightOutline = coords.meshAnnotations['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.iris?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  if (inputSize === -1) inputSize = 64;\n  return model;\n}\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates and update the z coordinate to be an average of the original and the new.\nexport function replaceIrisCoords(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.irisIndices.length; i++) {\n    const { key, indices } = coords.irisIndices[i];\n    const originalIndices = coords.meshAnnotations[`${prefix}${key}`];\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0],\n          newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n\nexport const getLeftToRightEyeDepthDifference = (rawCoords) => {\n  const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n  const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n  return leftEyeZ - rightEyeZ;\n};\n\n// Returns a box describing a cropped region around the eye fit for passing to the iris model.\nexport const getEyeBox = (rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, meshSize, flip = false) => {\n  const box = util.squarifyBox(util.enlargeBox(util.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), irisEnlarge));\n  const boxSize = util.getBoxSize(box);\n  let crop = tf.image.cropAndResize(face, [[\n    box.startPoint[1] / meshSize,\n    box.startPoint[0] / meshSize, box.endPoint[1] / meshSize,\n    box.endPoint[0] / meshSize,\n  ]], [0], [inputSize, inputSize]);\n  if (flip && env.kernels.includes('flipleftright')) {\n    const flipped = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    tf.dispose(crop);\n    crop = flipped;\n  }\n  return { box, boxSize, crop };\n};\n\n// Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\nexport const getEyeCoords = (eyeData, eyeBox, eyeBoxSize, flip = false) => {\n  const eyeRawCoords: Array<Point> = [];\n  for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n    const x = eyeData[i * 3];\n    const y = eyeData[i * 3 + 1];\n    const z = eyeData[i * 3 + 2];\n    eyeRawCoords.push([\n      (flip ? (1 - (x / inputSize)) : (x / inputSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n      (y / inputSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n    ]);\n  }\n  return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n};\n\n// The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\nexport const getAdjustedIrisCoords = (rawCoords, irisCoords, direction) => {\n  const upperCenterZ = rawCoords[coords.meshAnnotations[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n  const lowerCenterZ = rawCoords[coords.meshAnnotations[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n  const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n  // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n  return irisCoords.map((coord, i) => {\n    let z = averageZ;\n    if (i === 2) {\n      z = upperCenterZ;\n    } else if (i === 4) {\n      z = lowerCenterZ;\n    }\n    return [coord[0], coord[1], z];\n  });\n};\n\nexport async function augmentIris(rawCoords, face, config, meshSize) {\n  if (!model) {\n    if (config.debug) log('face mesh iris detection requested, but model is not loaded');\n    return rawCoords;\n  }\n  const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], meshSize, true);\n  const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1], meshSize, true);\n  const combined = tf.concat([leftEyeCrop, rightEyeCrop]);\n  tf.dispose(leftEyeCrop);\n  tf.dispose(rightEyeCrop);\n  const eyePredictions = model.execute(combined) as Tensor;\n  tf.dispose(combined);\n  const eyePredictionsData = await eyePredictions.data();\n  tf.dispose(eyePredictions);\n  const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n  const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n  const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n  const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize, false);\n  const leftToRightEyeDepthDifference = getLeftToRightEyeDepthDifference(rawCoords);\n  if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n    replaceIrisCoords(rawCoords, leftEyeRawCoords, 'left', null);\n    replaceIrisCoords(rawCoords, rightEyeRawCoords, 'right', null);\n    // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged so we only update a single contour line above and below the eye.\n  } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n    replaceIrisCoords(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n  } else { // User is looking towards the left.\n    replaceIrisCoords(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n  }\n  const adjustedLeftIrisCoords = getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n  const adjustedRightIrisCoords = getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n  const newCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n  return newCoords;\n}\n", "// @tensorflow/tfjs-models/face-landmark-detection/src/constants.ts\n// https://github.com/google/mediapipe/mediapipe/python/solutions/face_mesh_connections.py\n\ntype PairArray = Array<[number, number]>;\n\nconst LIPS_CONNECTIONS: PairArray = [\n  [61, 146], [146, 91], [91, 181], [181, 84], [84, 17], [17, 314], [314, 405], [405, 321], [321, 375], [375, 291], [61, 185], [185, 40], [40, 39], [39, 37], [37, 0], [0, 267], [267, 269], [269, 270], [270, 409], [409, 291],\n  [78, 95], [95, 88], [88, 178], [178, 87], [87, 14], [14, 317], [317, 402], [402, 318], [318, 324], [324, 308], [78, 191], [191, 80], [80, 81], [81, 82], [82, 13], [13, 312], [312, 311], [311, 310], [310, 415], [415, 308],\n];\n\nconst LEFT_EYE_CONNECTIONS: PairArray = [[263, 249], [249, 390], [390, 373], [373, 374], [374, 380], [380, 381], [381, 382], [382, 362], [263, 466], [466, 388], [388, 387], [387, 386], [386, 385], [385, 384], [384, 398], [398, 362]];\n\nconst LEFT_EYEBROW_CONNECTIONS: PairArray = [[276, 283], [283, 282], [282, 295], [295, 285], [300, 293], [293, 334], [334, 296], [296, 336]];\n\nconst LEFT_IRIS_CONNECTIONS: PairArray = [[474, 475], [475, 476], [476, 477], [477, 474]];\n\nconst RIGHT_EYE_CONNECTIONS: PairArray = [[33, 7], [7, 163], [163, 144], [144, 145], [145, 153], [153, 154], [154, 155], [155, 133], [33, 246], [246, 161], [161, 160], [160, 159], [159, 158], [158, 157], [157, 173], [173, 133]];\n\nconst RIGHT_EYEBROW_CONNECTIONS: PairArray = [[46, 53], [53, 52], [52, 65], [65, 55], [70, 63], [63, 105], [105, 66], [66, 107]];\n\nconst RIGHT_IRIS_CONNECTIONS: PairArray = [[469, 470], [470, 471], [471, 472], [472, 469]];\n\nconst FACE_OVAL_CONNECTIONS: PairArray = [\n  [10, 338], [338, 297], [297, 332], [332, 284], [284, 251], [251, 389], [389, 356], [356, 454], [454, 323], [323, 361], [361, 288], [288, 397], [397, 365], [365, 379], [379, 378], [378, 400], [400, 377], [377, 152],\n  [152, 148], [148, 176], [176, 149], [149, 150], [150, 136], [136, 172], [172, 58], [58, 132], [132, 93], [93, 234], [234, 127], [127, 162], [162, 21], [21, 54], [54, 103], [103, 67], [67, 109], [109, 10],\n];\n\nexport const MEDIAPIPE_FACE_MESH_CONNECTED_KEYPOINTS_PAIRS: PairArray = [\n  [127, 34], [34, 139], [139, 127], [11, 0], [0, 37], [37, 11], [232, 231], [231, 120], [120, 232], [72, 37], [37, 39], [39, 72], [128, 121], [121, 47], [47, 128], [232, 121], [121, 128], [128, 232],\n  [104, 69], [69, 67], [67, 104], [175, 171], [171, 148], [148, 175], [118, 50], [50, 101], [101, 118], [73, 39], [39, 40], [40, 73], [9, 151], [151, 108], [108, 9], [48, 115], [115, 131], [131, 48],\n  [194, 204], [204, 211], [211, 194], [74, 40], [40, 185], [185, 74], [80, 42], [42, 183], [183, 80], [40, 92], [92, 186], [186, 40], [230, 229], [229, 118], [118, 230], [202, 212], [212, 214], [214, 202],\n  [83, 18], [18, 17], [17, 83], [76, 61], [61, 146], [146, 76], [160, 29], [29, 30], [30, 160], [56, 157], [157, 173], [173, 56], [106, 204], [204, 194], [194, 106], [135, 214], [214, 192], [192, 135],\n  [203, 165], [165, 98], [98, 203], [21, 71], [71, 68], [68, 21], [51, 45], [45, 4], [4, 51], [144, 24], [24, 23], [23, 144], [77, 146], [146, 91], [91, 77], [205, 50], [50, 187], [187, 205],\n  [201, 200], [200, 18], [18, 201], [91, 106], [106, 182], [182, 91], [90, 91], [91, 181], [181, 90], [85, 84], [84, 17], [17, 85], [206, 203], [203, 36], [36, 206], [148, 171], [171, 140], [140, 148],\n  [92, 40], [40, 39], [39, 92], [193, 189], [189, 244], [244, 193], [159, 158], [158, 28], [28, 159], [247, 246], [246, 161], [161, 247], [236, 3], [3, 196], [196, 236], [54, 68], [68, 104], [104, 54],\n  [193, 168], [168, 8], [8, 193], [117, 228], [228, 31], [31, 117], [189, 193], [193, 55], [55, 189], [98, 97], [97, 99], [99, 98], [126, 47], [47, 100], [100, 126], [166, 79], [79, 218], [218, 166],\n  [155, 154], [154, 26], [26, 155], [209, 49], [49, 131], [131, 209], [135, 136], [136, 150], [150, 135], [47, 126], [126, 217], [217, 47], [223, 52], [52, 53], [53, 223], [45, 51], [51, 134], [134, 45],\n  [211, 170], [170, 140], [140, 211], [67, 69], [69, 108], [108, 67], [43, 106], [106, 91], [91, 43], [230, 119], [119, 120], [120, 230], [226, 130], [130, 247], [247, 226], [63, 53], [53, 52], [52, 63],\n  [238, 20], [20, 242], [242, 238], [46, 70], [70, 156], [156, 46], [78, 62], [62, 96], [96, 78], [46, 53], [53, 63], [63, 46], [143, 34], [34, 227], [227, 143], [123, 117], [117, 111], [111, 123],\n  [44, 125], [125, 19], [19, 44], [236, 134], [134, 51], [51, 236], [216, 206], [206, 205], [205, 216], [154, 153], [153, 22], [22, 154], [39, 37], [37, 167], [167, 39], [200, 201], [201, 208], [208, 200],\n  [36, 142], [142, 100], [100, 36], [57, 212], [212, 202], [202, 57], [20, 60], [60, 99], [99, 20], [28, 158], [158, 157], [157, 28], [35, 226], [226, 113], [113, 35], [160, 159], [159, 27], [27, 160],\n  [204, 202], [202, 210], [210, 204], [113, 225], [225, 46], [46, 113], [43, 202], [202, 204], [204, 43], [62, 76], [76, 77], [77, 62], [137, 123], [123, 116], [116, 137], [41, 38], [38, 72], [72, 41],\n  [203, 129], [129, 142], [142, 203], [64, 98], [98, 240], [240, 64], [49, 102], [102, 64], [64, 49], [41, 73], [73, 74], [74, 41], [212, 216], [216, 207], [207, 212], [42, 74], [74, 184], [184, 42],\n  [169, 170], [170, 211], [211, 169], [170, 149], [149, 176], [176, 170], [105, 66], [66, 69], [69, 105], [122, 6], [6, 168], [168, 122], [123, 147], [147, 187], [187, 123], [96, 77], [77, 90], [90, 96],\n  [65, 55], [55, 107], [107, 65], [89, 90], [90, 180], [180, 89], [101, 100], [100, 120], [120, 101], [63, 105], [105, 104], [104, 63], [93, 137], [137, 227], [227, 93], [15, 86], [86, 85], [85, 15],\n  [129, 102], [102, 49], [49, 129], [14, 87], [87, 86], [86, 14], [55, 8], [8, 9], [9, 55], [100, 47], [47, 121], [121, 100], [145, 23], [23, 22], [22, 145], [88, 89], [89, 179], [179, 88],\n  [6, 122], [122, 196], [196, 6], [88, 95], [95, 96], [96, 88], [138, 172], [172, 136], [136, 138], [215, 58], [58, 172], [172, 215], [115, 48], [48, 219], [219, 115], [42, 80], [80, 81], [81, 42],\n  [195, 3], [3, 51], [51, 195], [43, 146], [146, 61], [61, 43], [171, 175], [175, 199], [199, 171], [81, 82], [82, 38], [38, 81], [53, 46], [46, 225], [225, 53], [144, 163], [163, 110], [110, 144],\n  [52, 65], [65, 66], [66, 52], [229, 228], [228, 117], [117, 229], [34, 127], [127, 234], [234, 34], [107, 108], [108, 69], [69, 107], [109, 108], [108, 151], [151, 109], [48, 64], [64, 235], [235, 48],\n  [62, 78], [78, 191], [191, 62], [129, 209], [209, 126], [126, 129], [111, 35], [35, 143], [143, 111], [117, 123], [123, 50], [50, 117], [222, 65], [65, 52], [52, 222], [19, 125], [125, 141], [141, 19],\n  [221, 55], [55, 65], [65, 221], [3, 195], [195, 197], [197, 3], [25, 7], [7, 33], [33, 25], [220, 237], [237, 44], [44, 220], [70, 71], [71, 139], [139, 70], [122, 193], [193, 245], [245, 122],\n  [247, 130], [130, 33], [33, 247], [71, 21], [21, 162], [162, 71], [170, 169], [169, 150], [150, 170], [188, 174], [174, 196], [196, 188], [216, 186], [186, 92], [92, 216], [2, 97], [97, 167], [167, 2],\n  [141, 125], [125, 241], [241, 141], [164, 167], [167, 37], [37, 164], [72, 38], [38, 12], [12, 72], [38, 82], [82, 13], [13, 38], [63, 68], [68, 71], [71, 63], [226, 35], [35, 111], [111, 226],\n  [101, 50], [50, 205], [205, 101], [206, 92], [92, 165], [165, 206], [209, 198], [198, 217], [217, 209], [165, 167], [167, 97], [97, 165], [220, 115], [115, 218], [218, 220], [133, 112], [112, 243], [243, 133],\n  [239, 238], [238, 241], [241, 239], [214, 135], [135, 169], [169, 214], [190, 173], [173, 133], [133, 190], [171, 208], [208, 32], [32, 171], [125, 44], [44, 237], [237, 125], [86, 87], [87, 178], [178, 86],\n  [85, 86], [86, 179], [179, 85], [84, 85], [85, 180], [180, 84], [83, 84], [84, 181], [181, 83], [201, 83], [83, 182], [182, 201], [137, 93], [93, 132], [132, 137], [76, 62], [62, 183], [183, 76],\n  [61, 76], [76, 184], [184, 61], [57, 61], [61, 185], [185, 57], [212, 57], [57, 186], [186, 212], [214, 207], [207, 187], [187, 214], [34, 143], [143, 156], [156, 34], [79, 239], [239, 237], [237, 79],\n  [123, 137], [137, 177], [177, 123], [44, 1], [1, 4], [4, 44], [201, 194], [194, 32], [32, 201], [64, 102], [102, 129], [129, 64], [213, 215], [215, 138], [138, 213], [59, 166], [166, 219], [219, 59],\n  [242, 99], [99, 97], [97, 242], [2, 94], [94, 141], [141, 2], [75, 59], [59, 235], [235, 75], [24, 110], [110, 228], [228, 24], [25, 130], [130, 226], [226, 25], [23, 24], [24, 229], [229, 23],\n  [22, 23], [23, 230], [230, 22], [26, 22], [22, 231], [231, 26], [112, 26], [26, 232], [232, 112], [189, 190], [190, 243], [243, 189], [221, 56], [56, 190], [190, 221], [28, 56], [56, 221], [221, 28],\n  [27, 28], [28, 222], [222, 27], [29, 27], [27, 223], [223, 29], [30, 29], [29, 224], [224, 30], [247, 30], [30, 225], [225, 247], [238, 79], [79, 20], [20, 238], [166, 59], [59, 75], [75, 166],\n  [60, 75], [75, 240], [240, 60], [147, 177], [177, 215], [215, 147], [20, 79], [79, 166], [166, 20], [187, 147], [147, 213], [213, 187], [112, 233], [233, 244], [244, 112], [233, 128], [128, 245], [245, 233],\n  [128, 114], [114, 188], [188, 128], [114, 217], [217, 174], [174, 114], [131, 115], [115, 220], [220, 131], [217, 198], [198, 236], [236, 217], [198, 131], [131, 134], [134, 198], [177, 132], [132, 58], [58, 177],\n  [143, 35], [35, 124], [124, 143], [110, 163], [163, 7], [7, 110], [228, 110], [110, 25], [25, 228], [356, 389], [389, 368], [368, 356], [11, 302], [302, 267], [267, 11], [452, 350], [350, 349], [349, 452],\n  [302, 303], [303, 269], [269, 302], [357, 343], [343, 277], [277, 357], [452, 453], [453, 357], [357, 452], [333, 332], [332, 297], [297, 333], [175, 152], [152, 377], [377, 175], [347, 348], [348, 330], [330, 347],\n  [303, 304], [304, 270], [270, 303], [9, 336], [336, 337], [337, 9], [278, 279], [279, 360], [360, 278], [418, 262], [262, 431], [431, 418], [304, 408], [408, 409], [409, 304], [310, 415], [415, 407], [407, 310],\n  [270, 409], [409, 410], [410, 270], [450, 348], [348, 347], [347, 450], [422, 430], [430, 434], [434, 422], [313, 314], [314, 17], [17, 313], [306, 307], [307, 375], [375, 306], [387, 388], [388, 260], [260, 387],\n  [286, 414], [414, 398], [398, 286], [335, 406], [406, 418], [418, 335], [364, 367], [367, 416], [416, 364], [423, 358], [358, 327], [327, 423], [251, 284], [284, 298], [298, 251], [281, 5], [5, 4], [4, 281],\n  [373, 374], [374, 253], [253, 373], [307, 320], [320, 321], [321, 307], [425, 427], [427, 411], [411, 425], [421, 313], [313, 18], [18, 421], [321, 405], [405, 406], [406, 321], [320, 404], [404, 405], [405, 320],\n  [315, 16], [16, 17], [17, 315], [426, 425], [425, 266], [266, 426], [377, 400], [400, 369], [369, 377], [322, 391], [391, 269], [269, 322], [417, 465], [465, 464], [464, 417], [386, 257], [257, 258], [258, 386],\n  [466, 260], [260, 388], [388, 466], [456, 399], [399, 419], [419, 456], [284, 332], [332, 333], [333, 284], [417, 285], [285, 8], [8, 417], [346, 340], [340, 261], [261, 346], [413, 441], [441, 285], [285, 413],\n  [327, 460], [460, 328], [328, 327], [355, 371], [371, 329], [329, 355], [392, 439], [439, 438], [438, 392], [382, 341], [341, 256], [256, 382], [429, 420], [420, 360], [360, 429], [364, 394], [394, 379], [379, 364],\n  [277, 343], [343, 437], [437, 277], [443, 444], [444, 283], [283, 443], [275, 440], [440, 363], [363, 275], [431, 262], [262, 369], [369, 431], [297, 338], [338, 337], [337, 297], [273, 375], [375, 321], [321, 273],\n  [450, 451], [451, 349], [349, 450], [446, 342], [342, 467], [467, 446], [293, 334], [334, 282], [282, 293], [458, 461], [461, 462], [462, 458], [276, 353], [353, 383], [383, 276], [308, 324], [324, 325], [325, 308],\n  [276, 300], [300, 293], [293, 276], [372, 345], [345, 447], [447, 372], [352, 345], [345, 340], [340, 352], [274, 1], [1, 19], [19, 274], [456, 248], [248, 281], [281, 456], [436, 427], [427, 425], [425, 436],\n  [381, 256], [256, 252], [252, 381], [269, 391], [391, 393], [393, 269], [200, 199], [199, 428], [428, 200], [266, 330], [330, 329], [329, 266], [287, 273], [273, 422], [422, 287], [250, 462], [462, 328], [328, 250],\n  [258, 286], [286, 384], [384, 258], [265, 353], [353, 342], [342, 265], [387, 259], [259, 257], [257, 387], [424, 431], [431, 430], [430, 424], [342, 353], [353, 276], [276, 342], [273, 335], [335, 424], [424, 273],\n  [292, 325], [325, 307], [307, 292], [366, 447], [447, 345], [345, 366], [271, 303], [303, 302], [302, 271], [423, 266], [266, 371], [371, 423], [294, 455], [455, 460], [460, 294], [279, 278], [278, 294], [294, 279],\n  [271, 272], [272, 304], [304, 271], [432, 434], [434, 427], [427, 432], [272, 407], [407, 408], [408, 272], [394, 430], [430, 431], [431, 394], [395, 369], [369, 400], [400, 395], [334, 333], [333, 299], [299, 334],\n  [351, 417], [417, 168], [168, 351], [352, 280], [280, 411], [411, 352], [325, 319], [319, 320], [320, 325], [295, 296], [296, 336], [336, 295], [319, 403], [403, 404], [404, 319], [330, 348], [348, 349], [349, 330],\n  [293, 298], [298, 333], [333, 293], [323, 454], [454, 447], [447, 323], [15, 16], [16, 315], [315, 15], [358, 429], [429, 279], [279, 358], [14, 15], [15, 316], [316, 14], [285, 336], [336, 9], [9, 285],\n  [329, 349], [349, 350], [350, 329], [374, 380], [380, 252], [252, 374], [318, 402], [402, 403], [403, 318], [6, 197], [197, 419], [419, 6], [318, 319], [319, 325], [325, 318], [367, 364], [364, 365], [365, 367],\n  [435, 367], [367, 397], [397, 435], [344, 438], [438, 439], [439, 344], [272, 271], [271, 311], [311, 272], [195, 5], [5, 281], [281, 195], [273, 287], [287, 291], [291, 273], [396, 428], [428, 199], [199, 396],\n  [311, 271], [271, 268], [268, 311], [283, 444], [444, 445], [445, 283], [373, 254], [254, 339], [339, 373], [282, 334], [334, 296], [296, 282], [449, 347], [347, 346], [346, 449], [264, 447], [447, 454], [454, 264],\n  [336, 296], [296, 299], [299, 336], [338, 10], [10, 151], [151, 338], [278, 439], [439, 455], [455, 278], [292, 407], [407, 415], [415, 292], [358, 371], [371, 355], [355, 358], [340, 345], [345, 372], [372, 340],\n  [346, 347], [347, 280], [280, 346], [442, 443], [443, 282], [282, 442], [19, 94], [94, 370], [370, 19], [441, 442], [442, 295], [295, 441], [248, 419], [419, 197], [197, 248], [263, 255], [255, 359], [359, 263],\n  [440, 275], [275, 274], [274, 440], [300, 383], [383, 368], [368, 300], [351, 412], [412, 465], [465, 351], [263, 467], [467, 466], [466, 263], [301, 368], [368, 389], [389, 301], [395, 378], [378, 379], [379, 395],\n  [412, 351], [351, 419], [419, 412], [436, 426], [426, 322], [322, 436], [2, 164], [164, 393], [393, 2], [370, 462], [462, 461], [461, 370], [164, 0], [0, 267], [267, 164], [302, 11], [11, 12], [12, 302],\n  [268, 12], [12, 13], [13, 268], [293, 300], [300, 301], [301, 293], [446, 261], [261, 340], [340, 446], [330, 266], [266, 425], [425, 330], [426, 423], [423, 391], [391, 426], [429, 355], [355, 437], [437, 429],\n  [391, 327], [327, 326], [326, 391], [440, 457], [457, 438], [438, 440], [341, 382], [382, 362], [362, 341], [459, 457], [457, 461], [461, 459], [434, 430], [430, 394], [394, 434], [414, 463], [463, 362], [362, 414],\n  [396, 369], [369, 262], [262, 396], [354, 461], [461, 457], [457, 354], [316, 403], [403, 402], [402, 316], [315, 404], [404, 403], [403, 315], [314, 405], [405, 404], [404, 314], [313, 406], [406, 405], [405, 313],\n  [421, 418], [418, 406], [406, 421], [366, 401], [401, 361], [361, 366], [306, 408], [408, 407], [407, 306], [291, 409], [409, 408], [408, 291], [287, 410], [410, 409], [409, 287], [432, 436], [436, 410], [410, 432],\n  [434, 416], [416, 411], [411, 434], [264, 368], [368, 383], [383, 264], [309, 438], [438, 457], [457, 309], [352, 376], [376, 401], [401, 352], [274, 275], [275, 4], [4, 274], [421, 428], [428, 262], [262, 421],\n  [294, 327], [327, 358], [358, 294], [433, 416], [416, 367], [367, 433], [289, 455], [455, 439], [439, 289], [462, 370], [370, 326], [326, 462], [2, 326], [326, 370], [370, 2], [305, 460], [460, 455], [455, 305],\n  [254, 449], [449, 448], [448, 254], [255, 261], [261, 446], [446, 255], [253, 450], [450, 449], [449, 253], [252, 451], [451, 450], [450, 252], [256, 452], [452, 451], [451, 256], [341, 453], [453, 452], [452, 341],\n  [413, 464], [464, 463], [463, 413], [441, 413], [413, 414], [414, 441], [258, 442], [442, 441], [441, 258], [257, 443], [443, 442], [442, 257], [259, 444], [444, 443], [443, 259], [260, 445], [445, 444], [444, 260],\n  [467, 342], [342, 445], [445, 467], [459, 458], [458, 250], [250, 459], [289, 392], [392, 290], [290, 289], [290, 328], [328, 460], [460, 290], [376, 433], [433, 435], [435, 376], [250, 290], [290, 392], [392, 250],\n  [411, 416], [416, 433], [433, 411], [341, 463], [463, 464], [464, 341], [453, 464], [464, 465], [465, 453], [357, 465], [465, 412], [412, 357], [343, 412], [412, 399], [399, 343], [360, 363], [363, 440], [440, 360],\n  [437, 399], [399, 456], [456, 437], [420, 456], [456, 363], [363, 420], [401, 435], [435, 288], [288, 401], [372, 383], [383, 353], [353, 372], [339, 255], [255, 249], [249, 339], [448, 261], [261, 255], [255, 448],\n  [133, 243], [243, 190], [190, 133], [133, 155], [155, 112], [112, 133], [33, 246], [246, 247], [247, 33], [33, 130], [130, 25], [25, 33], [398, 384], [384, 286], [286, 398], [362, 398], [398, 414], [414, 362],\n  [362, 463], [463, 341], [341, 362], [263, 359], [359, 467], [467, 263], [263, 249], [249, 255], [255, 263], [466, 467], [467, 260], [260, 466], [75, 60], [60, 166], [166, 75], [238, 239], [239, 79], [79, 238],\n  [162, 127], [127, 139], [139, 162], [72, 11], [11, 37], [37, 72], [121, 232], [232, 120], [120, 121], [73, 72], [72, 39], [39, 73], [114, 128], [128, 47], [47, 114], [233, 232], [232, 128], [128, 233],\n  [103, 104], [104, 67], [67, 103], [152, 175], [175, 148], [148, 152], [119, 118], [118, 101], [101, 119], [74, 73], [73, 40], [40, 74], [107, 9], [9, 108], [108, 107], [49, 48], [48, 131], [131, 49],\n  [32, 194], [194, 211], [211, 32], [184, 74], [74, 185], [185, 184], [191, 80], [80, 183], [183, 191], [185, 40], [40, 186], [186, 185], [119, 230], [230, 118], [118, 119], [210, 202], [202, 214], [214, 210],\n  [84, 83], [83, 17], [17, 84], [77, 76], [76, 146], [146, 77], [161, 160], [160, 30], [30, 161], [190, 56], [56, 173], [173, 190], [182, 106], [106, 194], [194, 182], [138, 135], [135, 192], [192, 138],\n  [129, 203], [203, 98], [98, 129], [54, 21], [21, 68], [68, 54], [5, 51], [51, 4], [4, 5], [145, 144], [144, 23], [23, 145], [90, 77], [77, 91], [91, 90], [207, 205], [205, 187], [187, 207],\n  [83, 201], [201, 18], [18, 83], [181, 91], [91, 182], [182, 181], [180, 90], [90, 181], [181, 180], [16, 85], [85, 17], [17, 16], [205, 206], [206, 36], [36, 205], [176, 148], [148, 140], [140, 176],\n  [165, 92], [92, 39], [39, 165], [245, 193], [193, 244], [244, 245], [27, 159], [159, 28], [28, 27], [30, 247], [247, 161], [161, 30], [174, 236], [236, 196], [196, 174], [103, 54], [54, 104], [104, 103],\n  [55, 193], [193, 8], [8, 55], [111, 117], [117, 31], [31, 111], [221, 189], [189, 55], [55, 221], [240, 98], [98, 99], [99, 240], [142, 126], [126, 100], [100, 142], [219, 166], [166, 218], [218, 219],\n  [112, 155], [155, 26], [26, 112], [198, 209], [209, 131], [131, 198], [169, 135], [135, 150], [150, 169], [114, 47], [47, 217], [217, 114], [224, 223], [223, 53], [53, 224], [220, 45], [45, 134], [134, 220],\n  [32, 211], [211, 140], [140, 32], [109, 67], [67, 108], [108, 109], [146, 43], [43, 91], [91, 146], [231, 230], [230, 120], [120, 231], [113, 226], [226, 247], [247, 113], [105, 63], [63, 52], [52, 105],\n  [241, 238], [238, 242], [242, 241], [124, 46], [46, 156], [156, 124], [95, 78], [78, 96], [96, 95], [70, 46], [46, 63], [63, 70], [116, 143], [143, 227], [227, 116], [116, 123], [123, 111], [111, 116],\n  [1, 44], [44, 19], [19, 1], [3, 236], [236, 51], [51, 3], [207, 216], [216, 205], [205, 207], [26, 154], [154, 22], [22, 26], [165, 39], [39, 167], [167, 165], [199, 200], [200, 208], [208, 199],\n  [101, 36], [36, 100], [100, 101], [43, 57], [57, 202], [202, 43], [242, 20], [20, 99], [99, 242], [56, 28], [28, 157], [157, 56], [124, 35], [35, 113], [113, 124], [29, 160], [160, 27], [27, 29],\n  [211, 204], [204, 210], [210, 211], [124, 113], [113, 46], [46, 124], [106, 43], [43, 204], [204, 106], [96, 62], [62, 77], [77, 96], [227, 137], [137, 116], [116, 227], [73, 41], [41, 72], [72, 73],\n  [36, 203], [203, 142], [142, 36], [235, 64], [64, 240], [240, 235], [48, 49], [49, 64], [64, 48], [42, 41], [41, 74], [74, 42], [214, 212], [212, 207], [207, 214], [183, 42], [42, 184], [184, 183],\n  [210, 169], [169, 211], [211, 210], [140, 170], [170, 176], [176, 140], [104, 105], [105, 69], [69, 104], [193, 122], [122, 168], [168, 193], [50, 123], [123, 187], [187, 50], [89, 96], [96, 90], [90, 89],\n  [66, 65], [65, 107], [107, 66], [179, 89], [89, 180], [180, 179], [119, 101], [101, 120], [120, 119], [68, 63], [63, 104], [104, 68], [234, 93], [93, 227], [227, 234], [16, 15], [15, 85], [85, 16],\n  [209, 129], [129, 49], [49, 209], [15, 14], [14, 86], [86, 15], [107, 55], [55, 9], [9, 107], [120, 100], [100, 121], [121, 120], [153, 145], [145, 22], [22, 153], [178, 88], [88, 179], [179, 178],\n  [197, 6], [6, 196], [196, 197], [89, 88], [88, 96], [96, 89], [135, 138], [138, 136], [136, 135], [138, 215], [215, 172], [172, 138], [218, 115], [115, 219], [219, 218], [41, 42], [42, 81], [81, 41],\n  [5, 195], [195, 51], [51, 5], [57, 43], [43, 61], [61, 57], [208, 171], [171, 199], [199, 208], [41, 81], [81, 38], [38, 41], [224, 53], [53, 225], [225, 224], [24, 144], [144, 110], [110, 24],\n  [105, 52], [52, 66], [66, 105], [118, 229], [229, 117], [117, 118], [227, 34], [34, 234], [234, 227], [66, 107], [107, 69], [69, 66], [10, 109], [109, 151], [151, 10], [219, 48], [48, 235], [235, 219],\n  [183, 62], [62, 191], [191, 183], [142, 129], [129, 126], [126, 142], [116, 111], [111, 143], [143, 116], [118, 117], [117, 50], [50, 118], [223, 222], [222, 52], [52, 223], [94, 19], [19, 141], [141, 94],\n  [222, 221], [221, 65], [65, 222], [196, 3], [3, 197], [197, 196], [45, 220], [220, 44], [44, 45], [156, 70], [70, 139], [139, 156], [188, 122], [122, 245], [245, 188], [139, 71], [71, 162], [162, 139],\n  [149, 170], [170, 150], [150, 149], [122, 188], [188, 196], [196, 122], [206, 216], [216, 92], [92, 206], [164, 2], [2, 167], [167, 164], [242, 141], [141, 241], [241, 242], [0, 164], [164, 37], [37, 0],\n  [11, 72], [72, 12], [12, 11], [12, 38], [38, 13], [13, 12], [70, 63], [63, 71], [71, 70], [31, 226], [226, 111], [111, 31], [36, 101], [101, 205], [205, 36], [203, 206], [206, 165], [165, 203],\n  [126, 209], [209, 217], [217, 126], [98, 165], [165, 97], [97, 98], [237, 220], [220, 218], [218, 237], [237, 239], [239, 241], [241, 237], [210, 214], [214, 169], [169, 210], [140, 171], [171, 32], [32, 140],\n  [241, 125], [125, 237], [237, 241], [179, 86], [86, 178], [178, 179], [180, 85], [85, 179], [179, 180], [181, 84], [84, 180], [180, 181], [182, 83], [83, 181], [181, 182], [194, 201], [201, 182], [182, 194],\n  [177, 137], [137, 132], [132, 177], [184, 76], [76, 183], [183, 184], [185, 61], [61, 184], [184, 185], [186, 57], [57, 185], [185, 186], [216, 212], [212, 186], [186, 216], [192, 214], [214, 187], [187, 192],\n  [139, 34], [34, 156], [156, 139], [218, 79], [79, 237], [237, 218], [147, 123], [123, 177], [177, 147], [45, 44], [44, 4], [4, 45], [208, 201], [201, 32], [32, 208], [98, 64], [64, 129], [129, 98],\n  [192, 213], [213, 138], [138, 192], [235, 59], [59, 219], [219, 235], [141, 242], [242, 97], [97, 141], [97, 2], [2, 141], [141, 97], [240, 75], [75, 235], [235, 240], [229, 24], [24, 228], [228, 229],\n  [31, 25], [25, 226], [226, 31], [230, 23], [23, 229], [229, 230], [231, 22], [22, 230], [230, 231], [232, 26], [26, 231], [231, 232], [233, 112], [112, 232], [232, 233], [244, 189], [189, 243], [243, 244],\n  [189, 221], [221, 190], [190, 189], [222, 28], [28, 221], [221, 222], [223, 27], [27, 222], [222, 223], [224, 29], [29, 223], [223, 224], [225, 30], [30, 224], [224, 225], [113, 247], [247, 225], [225, 113],\n  [99, 60], [60, 240], [240, 99], [213, 147], [147, 215], [215, 213], [60, 20], [20, 166], [166, 60], [192, 187], [187, 213], [213, 192], [243, 112], [112, 244], [244, 243], [244, 233], [233, 245], [245, 244],\n  [245, 128], [128, 188], [188, 245], [188, 114], [114, 174], [174, 188], [134, 131], [131, 220], [220, 134], [174, 217], [217, 236], [236, 174], [236, 198], [198, 134], [134, 236], [215, 177], [177, 58], [58, 215],\n  [156, 143], [143, 124], [124, 156], [25, 110], [110, 7], [7, 25], [31, 228], [228, 25], [25, 31], [264, 356], [356, 368], [368, 264], [0, 11], [11, 267], [267, 0], [451, 452], [452, 349], [349, 451],\n  [267, 302], [302, 269], [269, 267], [350, 357], [357, 277], [277, 350], [350, 452], [452, 357], [357, 350], [299, 333], [333, 297], [297, 299], [396, 175], [175, 377], [377, 396], [280, 347], [347, 330], [330, 280],\n  [269, 303], [303, 270], [270, 269], [151, 9], [9, 337], [337, 151], [344, 278], [278, 360], [360, 344], [424, 418], [418, 431], [431, 424], [270, 304], [304, 409], [409, 270], [272, 310], [310, 407], [407, 272],\n  [322, 270], [270, 410], [410, 322], [449, 450], [450, 347], [347, 449], [432, 422], [422, 434], [434, 432], [18, 313], [313, 17], [17, 18], [291, 306], [306, 375], [375, 291], [259, 387], [387, 260], [260, 259],\n  [424, 335], [335, 418], [418, 424], [434, 364], [364, 416], [416, 434], [391, 423], [423, 327], [327, 391], [301, 251], [251, 298], [298, 301], [275, 281], [281, 4], [4, 275], [254, 373], [373, 253], [253, 254],\n  [375, 307], [307, 321], [321, 375], [280, 425], [425, 411], [411, 280], [200, 421], [421, 18], [18, 200], [335, 321], [321, 406], [406, 335], [321, 320], [320, 405], [405, 321], [314, 315], [315, 17], [17, 314],\n  [423, 426], [426, 266], [266, 423], [396, 377], [377, 369], [369, 396], [270, 322], [322, 269], [269, 270], [413, 417], [417, 464], [464, 413], [385, 386], [386, 258], [258, 385], [248, 456], [456, 419], [419, 248],\n  [298, 284], [284, 333], [333, 298], [168, 417], [417, 8], [8, 168], [448, 346], [346, 261], [261, 448], [417, 413], [413, 285], [285, 417], [326, 327], [327, 328], [328, 326], [277, 355], [355, 329], [329, 277],\n  [309, 392], [392, 438], [438, 309], [381, 382], [382, 256], [256, 381], [279, 429], [429, 360], [360, 279], [365, 364], [364, 379], [379, 365], [355, 277], [277, 437], [437, 355], [282, 443], [443, 283], [283, 282],\n  [281, 275], [275, 363], [363, 281], [395, 431], [431, 369], [369, 395], [299, 297], [297, 337], [337, 299], [335, 273], [273, 321], [321, 335], [348, 450], [450, 349], [349, 348], [359, 446], [446, 467], [467, 359],\n  [283, 293], [293, 282], [282, 283], [250, 458], [458, 462], [462, 250], [300, 276], [276, 383], [383, 300], [292, 308], [308, 325], [325, 292], [283, 276], [276, 293], [293, 283], [264, 372], [372, 447], [447, 264],\n  [346, 352], [352, 340], [340, 346], [354, 274], [274, 19], [19, 354], [363, 456], [456, 281], [281, 363], [426, 436], [436, 425], [425, 426], [380, 381], [381, 252], [252, 380], [267, 269], [269, 393], [393, 267],\n  [421, 200], [200, 428], [428, 421], [371, 266], [266, 329], [329, 371], [432, 287], [287, 422], [422, 432], [290, 250], [250, 328], [328, 290], [385, 258], [258, 384], [384, 385], [446, 265], [265, 342], [342, 446],\n  [386, 387], [387, 257], [257, 386], [422, 424], [424, 430], [430, 422], [445, 342], [342, 276], [276, 445], [422, 273], [273, 424], [424, 422], [306, 292], [292, 307], [307, 306], [352, 366], [366, 345], [345, 352],\n  [268, 271], [271, 302], [302, 268], [358, 423], [423, 371], [371, 358], [327, 294], [294, 460], [460, 327], [331, 279], [279, 294], [294, 331], [303, 271], [271, 304], [304, 303], [436, 432], [432, 427], [427, 436],\n  [304, 272], [272, 408], [408, 304], [395, 394], [394, 431], [431, 395], [378, 395], [395, 400], [400, 378], [296, 334], [334, 299], [299, 296], [6, 351], [351, 168], [168, 6], [376, 352], [352, 411], [411, 376],\n  [307, 325], [325, 320], [320, 307], [285, 295], [295, 336], [336, 285], [320, 319], [319, 404], [404, 320], [329, 330], [330, 349], [349, 329], [334, 293], [293, 333], [333, 334], [366, 323], [323, 447], [447, 366],\n  [316, 15], [15, 315], [315, 316], [331, 358], [358, 279], [279, 331], [317, 14], [14, 316], [316, 317], [8, 285], [285, 9], [9, 8], [277, 329], [329, 350], [350, 277], [253, 374], [374, 252], [252, 253],\n  [319, 318], [318, 403], [403, 319], [351, 6], [6, 419], [419, 351], [324, 318], [318, 325], [325, 324], [397, 367], [367, 365], [365, 397], [288, 435], [435, 397], [397, 288], [278, 344], [344, 439], [439, 278],\n  [310, 272], [272, 311], [311, 310], [248, 195], [195, 281], [281, 248], [375, 273], [273, 291], [291, 375], [175, 396], [396, 199], [199, 175], [312, 311], [311, 268], [268, 312], [276, 283], [283, 445], [445, 276],\n  [390, 373], [373, 339], [339, 390], [295, 282], [282, 296], [296, 295], [448, 449], [449, 346], [346, 448], [356, 264], [264, 454], [454, 356], [337, 336], [336, 299], [299, 337], [337, 338], [338, 151], [151, 337],\n  [294, 278], [278, 455], [455, 294], [308, 292], [292, 415], [415, 308], [429, 358], [358, 355], [355, 429], [265, 340], [340, 372], [372, 265], [352, 346], [346, 280], [280, 352], [295, 442], [442, 282], [282, 295],\n  [354, 19], [19, 370], [370, 354], [285, 441], [441, 295], [295, 285], [195, 248], [248, 197], [197, 195], [457, 440], [440, 274], [274, 457], [301, 300], [300, 368], [368, 301], [417, 351], [351, 465], [465, 417],\n  [251, 301], [301, 389], [389, 251], [394, 395], [395, 379], [379, 394], [399, 412], [412, 419], [419, 399], [410, 436], [436, 322], [322, 410], [326, 2], [2, 393], [393, 326], [354, 370], [370, 461], [461, 354],\n  [393, 164], [164, 267], [267, 393], [268, 302], [302, 12], [12, 268], [312, 268], [268, 13], [13, 312], [298, 293], [293, 301], [301, 298], [265, 446], [446, 340], [340, 265], [280, 330], [330, 425], [425, 280],\n  [322, 426], [426, 391], [391, 322], [420, 429], [429, 437], [437, 420], [393, 391], [391, 326], [326, 393], [344, 440], [440, 438], [438, 344], [458, 459], [459, 461], [461, 458], [364, 434], [434, 394], [394, 364],\n  [428, 396], [396, 262], [262, 428], [274, 354], [354, 457], [457, 274], [317, 316], [316, 402], [402, 317], [316, 315], [315, 403], [403, 316], [315, 314], [314, 404], [404, 315], [314, 313], [313, 405], [405, 314],\n  [313, 421], [421, 406], [406, 313], [323, 366], [366, 361], [361, 323], [292, 306], [306, 407], [407, 292], [306, 291], [291, 408], [408, 306], [291, 287], [287, 409], [409, 291], [287, 432], [432, 410], [410, 287],\n  [427, 434], [434, 411], [411, 427], [372, 264], [264, 383], [383, 372], [459, 309], [309, 457], [457, 459], [366, 352], [352, 401], [401, 366], [1, 274], [274, 4], [4, 1], [418, 421], [421, 262], [262, 418],\n  [331, 294], [294, 358], [358, 331], [435, 433], [433, 367], [367, 435], [392, 289], [289, 439], [439, 392], [328, 462], [462, 326], [326, 328], [94, 2], [2, 370], [370, 94], [289, 305], [305, 455], [455, 289],\n  [339, 254], [254, 448], [448, 339], [359, 255], [255, 446], [446, 359], [254, 253], [253, 449], [449, 254], [253, 252], [252, 450], [450, 253], [252, 256], [256, 451], [451, 252], [256, 341], [341, 452], [452, 256],\n  [414, 413], [413, 463], [463, 414], [286, 441], [441, 414], [414, 286], [286, 258], [258, 441], [441, 286], [258, 257], [257, 442], [442, 258], [257, 259], [259, 443], [443, 257], [259, 260], [260, 444], [444, 259],\n  [260, 467], [467, 445], [445, 260], [309, 459], [459, 250], [250, 309], [305, 289], [289, 290], [290, 305], [305, 290], [290, 460], [460, 305], [401, 376], [376, 435], [435, 401], [309, 250], [250, 392], [392, 309],\n  [376, 411], [411, 433], [433, 376], [453, 341], [341, 464], [464, 453], [357, 453], [453, 465], [465, 357], [343, 357], [357, 412], [412, 343], [437, 343], [343, 399], [399, 437], [344, 360], [360, 440], [440, 344],\n  [420, 437], [437, 456], [456, 420], [360, 420], [420, 363], [363, 360], [361, 401], [401, 288], [288, 361], [265, 372], [372, 353], [353, 265], [390, 339], [339, 249], [249, 390], [339, 448], [448, 255], [255, 339],\n];\n\nfunction connectionsToIndices(connections: PairArray) {\n  const indices = connections.map((connection) => connection[0]);\n  indices.push(connections[connections.length - 1][1]);\n  return indices;\n}\n\nexport const MEDIAPIPE_FACE_MESH_KEYPOINTS_BY_CONTOUR = {\n  lips: connectionsToIndices(LIPS_CONNECTIONS),\n  leftEye: connectionsToIndices(LEFT_EYE_CONNECTIONS),\n  leftEyebrow: connectionsToIndices(LEFT_EYEBROW_CONNECTIONS),\n  leftIris: connectionsToIndices(LEFT_IRIS_CONNECTIONS),\n  rightEye: connectionsToIndices(RIGHT_EYE_CONNECTIONS),\n  rightEyebrow: connectionsToIndices(RIGHT_EYEBROW_CONNECTIONS),\n  rightIris: connectionsToIndices(RIGHT_IRIS_CONNECTIONS),\n  faceOval: connectionsToIndices(FACE_OVAL_CONNECTIONS),\n};\n\nconst indexLabelPairs: Array<[number, string]> = Object.entries(MEDIAPIPE_FACE_MESH_KEYPOINTS_BY_CONTOUR)\n  .map(([label, indices]) => indices.map((index) => [index, label] as [number, string]))\n  .flat();\n\nexport const MEDIAPIPE_FACE_MESH_KEYPOINTS = new Map(indexLabelPairs);\n\ntype AssignAverage = number[];\nexport interface LandmarksRefinementConfig {\n  indexesMapping: number[]; // Maps indexes of the given set of landmarks to indexes of the resulting set of landmarks. Should be non empty and contain the same amount of indexes as landmarks in the corresponding input\n  zRefinement: 'none'|'copy'|AssignAverage; // Z refinement instructions.\n}\n\nexport const LANDMARKS_REFINEMENT_LIPS_CONFIG = [\n  61, 146, 91, 181, 84, 17, 314, 405, 321, 375, 291, // Lower outer.\n  185, 40, 39, 37, 0, 267, 269, 270, 409, // Upper outer(excluding corners).\n  78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308, // Lower inner.\n  191, 80, 81, 82, 13, 312, 311, 310, 415, // Upper inner(excluding corners).\n  76, 77, 90, 180, 85, 16, 315, 404, 320, 307, 306, // Lower semi - outer.\n  184, 74, 73, 72, 11, 302, 303, 304, 408, // Upper semi - outer(excluding corners).\n  62, 96, 89, 179, 86, 15, 316, 403, 319, 325, 292, // Lower semi - inner.\n  183, 42, 41, 38, 12, 268, 271, 272, 407, // Upper semi - inner(excluding corners).\n];\n\nexport const LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG = [\n  33, 7, 163, 144, 145, 153, 154, 155, 133, // Lower contour.\n  246, 161, 160, 159, 158, 157, 173, // upper contour (excluding corners).\n  130, 25, 110, 24, 23, 22, 26, 112, 243, // Halo x2 lower contour.\n  247, 30, 29, 27, 28, 56, 190, // Halo x2 upper contour (excluding corners).\n  226, 31, 228, 229, 230, 231, 232, 233, 244, // Halo x3 lower contour.\n  113, 225, 224, 223, 222, 221, 189, // Halo x3 upper contour (excluding corners).\n  35, 124, 46, 53, 52, 65, // Halo x4 upper contour (no lower because of mesh structure) or eyebrow inner contour.\n  143, 111, 117, 118, 119, 120, 121, 128, 245, // Halo x5 lower contour.\n  156, 70, 63, 105, 66, 107, 55, 193, // Halo x5 upper contour (excluding corners) or eyebrow outer contour.\n];\n\nexport const LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG = [\n  263, 249, 390, 373, 374, 380, 381, 382, 362, // Lower contour.\n  466, 388, 387, 386, 385, 384, 398, // Upper contour (excluding corners).\n  359, 255, 339, 254, 253, 252, 256, 341, 463, // Halo x2 lower contour.\n  467, 260, 259, 257, 258, 286, 414, // Halo x2 upper contour (excluding corners).\n  446, 261, 448, 449, 450, 451, 452, 453, 464, // Halo x3 lower contour.\n  342, 445, 444, 443, 442, 441, 413, // Halo x3 upper contour (excluding corners).\n  265, 353, 276, 283, 282, 295, // Halo x4 upper contour (no lower because of mesh structure) or/ eyebrow inner contour.\n  372, 340, 346, 347, 348, 349, 350, 357, 465, // Halo x5 lower contour.\n  383, 300, 293, 334, 296, 336, 285, 417, // Halo x5 upper contour (excluding corners) or eyebrow outer contour.\n];\n\nexport const LANDMARKS_REFINEMENT_LEFT_IRIS_CONFIG = [\n  468, // Center.\n  469, // Iris right edge.\n  470, // Iris top edge.\n  471, // Iris left edge.\n  472, // Iris bottom edge.\n];\n/*\nzRefinement: [\n  33, 7, 163, 144, 145, 153, 154, 155, 133, // Lower contour.\n  246, 161, 160, 159, 158, 157, 173, // Upper contour (excluding corners).\n];\n*/\n\nexport const LANDMARKS_REFINEMENT_RIGHT_IRIS_CONFIG = [\n  473, // Center.\n  474, // Iris right edge.\n  475, // Iris top edge.\n  476, // Iris left edge.\n  477, // Iris bottom edge.\n];\n/*\nzRefinement: [\n  263, 249, 390, 373, 374, 380, 381, 382, 362, // Lower contour.\n  466, 388, 387, 386, 385, 384, 398, // Upper contour (excluding corners).\n];\n*/\n", "import * as constants from './constants';\nimport type { Tensor } from '../tfjs/types';\n\nexport async function augment(rawCoords, results: Tensor[]) {\n  const t: Record<string, Float32Array> = { // all attention models produce 2d results so it needs to be later augmented with correct z-coords\n    // mesh: results[0], // already have it in rawCoords // output_mesh_identity\n    // flag: results[1], // already processed in parent // conv_faceflag\n    lips: await results.filter((r) => r.size === 160)[0].data() as Float32Array, // 80 x 2d = 160 // output_lips\n    irisL: await results.filter((r) => r.size === 10)[0].data() as Float32Array, // 5 x 2d = 10 // output_right_iris\n    eyeL: await results.filter((r) => r.size === 142)[0].data() as Float32Array, // 71 x 2d = 142 // output_right_eye\n    irisR: await results.filter((r) => r.size === 10)[1].data() as Float32Array, // 5 x 2d = 10 // output_left_iris\n    eyeR: await results.filter((r) => r.size === 142)[1].data() as Float32Array, // 71 x 2d = 142// output_left_eye\n  };\n\n  // augment iris: adds additional 5 keypoints per eye\n  const irisLDepth = constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG.reduce((prev, curr) => prev += rawCoords[curr][2], 0) / constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG.length; // get average z-coord for iris\n  for (let i = 0; i < t.irisL.length / 2; i++) rawCoords.push([t.irisL[2 * i + 0], t.irisL[2 * i + 1], irisLDepth]);\n  const irisRDepth = constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG.reduce((prev, curr) => prev += rawCoords[curr][2], 0) / constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG.length; // get average z-coord for iris\n  for (let i = 0; i < t.irisR.length / 2; i++) rawCoords.push([t.irisR[2 * i + 0], t.irisR[2 * i + 1], irisRDepth]);\n\n  // augment eyes: replaces eye keypoints based on heuristic mapping\n  for (let i = 0; i < t.eyeL.length / 2; i++) rawCoords[constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG[i]] = [t.eyeL[2 * i + 0], t.eyeL[2 * i + 1], rawCoords[constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG[i]][2]];\n  for (let i = 0; i < t.eyeR.length / 2; i++) rawCoords[constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG[i]] = [t.eyeR[2 * i + 0], t.eyeR[2 * i + 1], rawCoords[constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG[i]][2]];\n\n  // augment lips: replaces eye keypoints based on heuristic mapping\n  for (let i = 0; i < t.lips.length / 2; i++) rawCoords[constants.LANDMARKS_REFINEMENT_LIPS_CONFIG[i]] = [t.lips[2 * i + 0], t.lips[2 * i + 1], rawCoords[constants.LANDMARKS_REFINEMENT_LIPS_CONFIG[i]][2]];\n\n  return rawCoords;\n}\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n *\n * Based on:\n * - [**MediaPipe BlazeFace**](https://drive.google.com/file/d/1f39lSzU5Oq-j_OXgS67KfN5wNsoeAZ4V/view)\n * - Facial Spacial Geometry: [**MediaPipe FaceMesh**](https://drive.google.com/file/d/1VFC_wIpw4O7xBOiTgUldl79d9LA-LsnA/view)\n * - Eye Iris Details: [**MediaPipe Iris**](https://drive.google.com/file/d/1bsWbokp9AklH2ANjCfmjqEzzxO1CNbMu/view)\n */\n\nimport { log, now } from '../util/util';\nimport { loadModel } from '../tfjs/load';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as util from './facemeshutil';\nimport * as coords from './facemeshcoords';\nimport * as iris from './iris';\nimport * as attention from './attention';\nimport { histogramEqualization } from '../image/enhance';\nimport { env } from '../util/env';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { FaceResult, FaceLandmark, Point } from '../result';\nimport type { Config } from '../config';\n\ntype DetectBox = { startPoint: Point, endPoint: Point, landmarks: Array<Point>, confidence: number };\n\nconst cache = {\n  boxes: [] as DetectBox[],\n  skipped: Number.MAX_SAFE_INTEGER,\n  timestamp: 0,\n};\n\nlet model: GraphModel | null = null;\nlet inputSize = 0;\n\nexport async function predict(input: Tensor, config: Config): Promise<FaceResult[]> {\n  // reset cached boxes\n  const skipTime = (config.face.detector?.skipTime || 0) > (now() - cache.timestamp);\n  const skipFrame = cache.skipped < (config.face.detector?.skipFrames || 0);\n  if (!config.skipAllowed || !skipTime || !skipFrame || cache.boxes.length === 0) {\n    cache.boxes = await blazeface.getBoxes(input, config); // get results from blazeface detector\n    cache.timestamp = now();\n    cache.skipped = 0;\n  } else {\n    cache.skipped++;\n  }\n  const faces: Array<FaceResult> = [];\n  const newCache: Array<DetectBox> = [];\n  let id = 0;\n  for (let i = 0; i < cache.boxes.length; i++) {\n    const box = cache.boxes[i];\n    let angle = 0;\n    let rotationMatrix;\n    const face: FaceResult = { // init face result\n      id: id++,\n      mesh: [],\n      meshRaw: [],\n      box: [0, 0, 0, 0],\n      boxRaw: [0, 0, 0, 0],\n      score: 0,\n      boxScore: 0,\n      faceScore: 0,\n      // contoursRaw: [],\n      // contours: [],\n      annotations: {} as Record<FaceLandmark, Point[]>,\n    };\n\n    // optional rotation correction based on detector data only if mesh is disabled otherwise perform it later when we have more accurate mesh data. if no rotation correction this function performs crop\n    [angle, rotationMatrix, face.tensor] = util.correctFaceRotation(config.face.detector?.rotation, box, input, config.face.mesh?.enabled ? inputSize : blazeface.size());\n    if (config?.filter?.equalization) {\n      const equilized = await histogramEqualization(face.tensor as Tensor);\n      tf.dispose(face.tensor);\n      face.tensor = equilized;\n    }\n    face.boxScore = Math.round(100 * box.confidence) / 100;\n    if (!config.face.mesh?.enabled) { // mesh not enabled, return resuts from detector only\n      face.box = util.clampBox(box, input);\n      face.boxRaw = util.getRawBox(box, input);\n      face.score = face.boxScore;\n      face.mesh = box.landmarks.map((pt) => [\n        ((box.startPoint[0] + box.endPoint[0])) / 2 + ((box.endPoint[0] + box.startPoint[0]) * pt[0] / blazeface.size()),\n        ((box.startPoint[1] + box.endPoint[1])) / 2 + ((box.endPoint[1] + box.startPoint[1]) * pt[1] / blazeface.size()),\n      ]);\n      face.meshRaw = face.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize]);\n      for (const key of Object.keys(coords.blazeFaceLandmarks)) {\n        face.annotations[key] = [face.mesh[coords.blazeFaceLandmarks[key] as number]]; // add annotations\n      }\n    } else if (!model) { // mesh enabled, but not loaded\n      if (config.debug) log('face mesh detection requested, but model is not loaded');\n    } else { // mesh enabled\n      const results = model.execute(face.tensor as Tensor) as Array<Tensor>;\n      const confidenceT = results.find((t) => t.shape[t.shape.length - 1] === 1) as Tensor;\n      const faceConfidence = await confidenceT.data();\n      face.faceScore = Math.round(100 * faceConfidence[0]) / 100;\n\n      if (face.faceScore < (config.face.detector?.minConfidence || 1)) { // low confidence in detected mesh\n        box.confidence = face.faceScore; // reset confidence of cached box\n        if (config.face.mesh?.keepInvalid) {\n          face.box = util.clampBox(box, input);\n          face.boxRaw = util.getRawBox(box, input);\n          face.score = face.boxScore;\n          face.mesh = box.landmarks.map((pt) => [\n            ((box.startPoint[0] + box.endPoint[0])) / 2 + ((box.endPoint[0] + box.startPoint[0]) * pt[0] / blazeface.size()),\n            ((box.startPoint[1] + box.endPoint[1])) / 2 + ((box.endPoint[1] + box.startPoint[1]) * pt[1] / blazeface.size()),\n          ]);\n          face.meshRaw = face.mesh.map((pt) => [pt[0] / (input.shape[2] || 1), pt[1] / (input.shape[1] || 1), (pt[2] || 0) / inputSize]);\n          for (const key of Object.keys(coords.blazeFaceLandmarks)) {\n            face.annotations[key] = [face.mesh[coords.blazeFaceLandmarks[key] as number]]; // add annotations\n          }\n        }\n      } else {\n        const meshT = results.find((t) => t.shape[t.shape.length - 1] === 1404) as Tensor;\n        const coordsReshaped = tf.reshape(meshT, [-1, 3]);\n        let rawCoords = await coordsReshaped.array();\n        tf.dispose(coordsReshaped);\n        if (config.face.attention?.enabled) {\n          rawCoords = await attention.augment(rawCoords, results); // augment iris results using attention model results\n        } else if (config.face.iris?.enabled) {\n          rawCoords = await iris.augmentIris(rawCoords, face.tensor, config, inputSize); // run iris model and augment results\n        }\n        face.mesh = util.transformRawCoords(rawCoords, box, angle, rotationMatrix, inputSize); // get processed mesh\n        face.meshRaw = face.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize]);\n        for (const key of Object.keys(coords.meshAnnotations)) face.annotations[key] = coords.meshAnnotations[key].map((index) => face.mesh[index]); // add annotations\n        face.score = face.faceScore;\n        const calculatedBox = { ...util.calculateFaceBox(face.mesh, box), confidence: box.confidence, landmarks: box.landmarks };\n        face.box = util.clampBox(calculatedBox, input);\n        face.boxRaw = util.getRawBox(calculatedBox, input);\n        /*\n        const contoursT = results.find((t) => t.shape[t.shape.length - 1] === 266) as Tensor;\n        const contoursData = contoursT && await contoursT.data(); // 133 x 2d points\n        face.contoursRaw = [];\n        for (let j = 0; j < contoursData.length / 2; j++) face.contoursRaw.push([contoursData[2 * j + 0] / inputSize, contoursData[2 * j + 1] / inputSize]);\n        face.contours = face.contoursRaw.map((c) => [Math.trunc((input.shape[2] || 1) * c[0]), Math.trunc((input.shape[1] || 1) * c[1])]);\n        */\n        newCache.push(calculatedBox);\n      }\n      tf.dispose(results);\n    }\n    if (face.score > (config.face.detector?.minConfidence || 1)) faces.push(face);\n    else tf.dispose(face.tensor);\n  }\n  cache.boxes = newCache; // reset cache\n  return faces;\n}\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  // @ts-ignore private property\n  if (config?.face?.attention?.enabled && model?.signature) {\n    // @ts-ignore private property\n    if (Object.keys(model?.signature?.outputs || {}).length < 6) model = null;\n  }\n  if (!model) {\n    if (config.face.attention?.enabled) model = await loadModel(config.face.attention?.modelPath);\n    else model = await loadModel(config.face.mesh?.modelPath);\n  } else if (config.debug) {\n    log('cached model:', model['modelUrl']);\n  }\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  return model;\n}\n\nexport const triangulation = coords.TRI468;\nexport const uvmap = coords.UV468;\n", "/**\n * FaceRes model implementation\n *\n * Returns Age, Gender, Descriptor\n * Implements Face simmilarity function\n *\n * Based on: [**HSE-FaceRes**](https://github.com/HSE-asavchenko/HSE_FaceRec_tf)\n */\n\nimport { log, now } from '../util/util';\nimport { env } from '../util/env';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport type { Gender, Race } from '../result';\n\nexport type FaceRes = { age: number, gender: Gender, genderScore: number, descriptor: number[], race?: { score: number, race: Race }[] };\n\nlet model: GraphModel | null;\nconst last: Array<{\n  age: number,\n  gender: Gender,\n  genderScore: number,\n  descriptor: number[],\n}> = [];\n\nlet lastTime = 0;\nlet lastCount = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.description?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport function enhance(input): Tensor {\n  const tensor = (input.image || input.tensor || input) as Tensor; // input received from detector is already normalized to 0..1, input is also assumed to be straightened\n  if (!model?.inputs[0].shape) return tensor; // model has no shape so no point continuing\n  const crop = tf.image.resizeBilinear(tensor, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n  const norm = tf.mul(crop, constants.tf255);\n  tf.dispose(crop);\n  return norm;\n  /*\n  // do a tight crop of image and resize it to fit the model\n  const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n  const crop = (tensor.shape.length === 3)\n    ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n    : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n  */\n  /*\n  // convert to black&white to avoid colorization impact\n  const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n  const [red, green, blue] = tf.split(crop, 3, 3);\n  const redNorm = tf.mul(red, rgb[0]);\n  const greenNorm = tf.mul(green, rgb[1]);\n  const blueNorm = tf.mul(blue, rgb[2]);\n  const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n  const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n  */\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<FaceRes> {\n  if (!model) return { age: 0, gender: 'unknown', genderScore: 0, descriptor: [] };\n  const skipFrame = skipped < (config.face.description?.skipFrames || 0);\n  const skipTime = (config.face.description?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipFrame && skipTime && (lastCount === count) && last[idx]?.age && (last[idx]?.age > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const obj = {\n      age: <number>0,\n      gender: <Gender>'unknown',\n      genderScore: <number>0,\n      descriptor: <number[]>[],\n    };\n\n    if (config.face.description?.enabled) {\n      const enhanced = enhance(image);\n      const resT = model?.execute(enhanced) as Tensor[];\n      lastTime = now();\n      tf.dispose(enhanced);\n      const genderT = await resT.find((t) => t.shape[1] === 1) as Tensor;\n      const gender = await genderT.data();\n      const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n      if (confidence > (config.face.description?.minConfidence || 0)) {\n        obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n        obj.genderScore = Math.min(0.99, confidence);\n      }\n      const argmax = tf.argMax(resT.find((t) => t.shape[1] === 100), 1);\n      const age = (await argmax.data())[0];\n      tf.dispose(argmax);\n      const ageT = resT.find((t) => t.shape[1] === 100) as Tensor;\n      const all = await ageT.data();\n      obj.age = Math.round(all[age - 1] > all[age + 1] ? 10 * age - 100 * all[age - 1] : 10 * age + 100 * all[age + 1]) / 10;\n\n      const desc = resT.find((t) => t.shape[1] === 1024);\n      // const reshape = desc.reshape([128, 8]); // reshape large 1024-element descriptor to 128 x 8\n      // const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it which leaves us with 128-element descriptor\n      const descriptor = desc ? await desc.data() : <number[]>[];\n      obj.descriptor = Array.from(descriptor);\n      resT.forEach((t) => tf.dispose(t));\n    }\n    last[idx] = obj;\n    lastCount = count;\n    resolve(obj);\n  });\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport type { Point } from '../result';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]] as Point;\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]] as Point;\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]] as Point;\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]] as Point;\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize] as Point;\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize] as Point;\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]] as Point;\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]] as Point;\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "/**\n * HandPose model implementation constants\n * See `handpose.ts` for entry point\n */\n\nexport const anchors = [\n  { x: 0.015625, y: 0.015625 },\n  { x: 0.015625, y: 0.015625 },\n  { x: 0.046875, y: 0.015625 },\n  { x: 0.046875, y: 0.015625 },\n  { x: 0.078125, y: 0.015625 },\n  { x: 0.078125, y: 0.015625 },\n  { x: 0.109375, y: 0.015625 },\n  { x: 0.109375, y: 0.015625 },\n  { x: 0.140625, y: 0.015625 },\n  { x: 0.140625, y: 0.015625 },\n  { x: 0.171875, y: 0.015625 },\n  { x: 0.171875, y: 0.015625 },\n  { x: 0.203125, y: 0.015625 },\n  { x: 0.203125, y: 0.015625 },\n  { x: 0.234375, y: 0.015625 },\n  { x: 0.234375, y: 0.015625 },\n  { x: 0.265625, y: 0.015625 },\n  { x: 0.265625, y: 0.015625 },\n  { x: 0.296875, y: 0.015625 },\n  { x: 0.296875, y: 0.015625 },\n  { x: 0.328125, y: 0.015625 },\n  { x: 0.328125, y: 0.015625 },\n  { x: 0.359375, y: 0.015625 },\n  { x: 0.359375, y: 0.015625 },\n  { x: 0.390625, y: 0.015625 },\n  { x: 0.390625, y: 0.015625 },\n  { x: 0.421875, y: 0.015625 },\n  { x: 0.421875, y: 0.015625 },\n  { x: 0.453125, y: 0.015625 },\n  { x: 0.453125, y: 0.015625 },\n  { x: 0.484375, y: 0.015625 },\n  { x: 0.484375, y: 0.015625 },\n  { x: 0.515625, y: 0.015625 },\n  { x: 0.515625, y: 0.015625 },\n  { x: 0.546875, y: 0.015625 },\n  { x: 0.546875, y: 0.015625 },\n  { x: 0.578125, y: 0.015625 },\n  { x: 0.578125, y: 0.015625 },\n  { x: 0.609375, y: 0.015625 },\n  { x: 0.609375, y: 0.015625 },\n  { x: 0.640625, y: 0.015625 },\n  { x: 0.640625, y: 0.015625 },\n  { x: 0.671875, y: 0.015625 },\n  { x: 0.671875, y: 0.015625 },\n  { x: 0.703125, y: 0.015625 },\n  { x: 0.703125, y: 0.015625 },\n  { x: 0.734375, y: 0.015625 },\n  { x: 0.734375, y: 0.015625 },\n  { x: 0.765625, y: 0.015625 },\n  { x: 0.765625, y: 0.015625 },\n  { x: 0.796875, y: 0.015625 },\n  { x: 0.796875, y: 0.015625 },\n  { x: 0.828125, y: 0.015625 },\n  { x: 0.828125, y: 0.015625 },\n  { x: 0.859375, y: 0.015625 },\n  { x: 0.859375, y: 0.015625 },\n  { x: 0.890625, y: 0.015625 },\n  { x: 0.890625, y: 0.015625 },\n  { x: 0.921875, y: 0.015625 },\n  { x: 0.921875, y: 0.015625 },\n  { x: 0.953125, y: 0.015625 },\n  { x: 0.953125, y: 0.015625 },\n  { x: 0.984375, y: 0.015625 },\n  { x: 0.984375, y: 0.015625 },\n  { x: 0.015625, y: 0.046875 },\n  { x: 0.015625, y: 0.046875 },\n  { x: 0.046875, y: 0.046875 },\n  { x: 0.046875, y: 0.046875 },\n  { x: 0.078125, y: 0.046875 },\n  { x: 0.078125, y: 0.046875 },\n  { x: 0.109375, y: 0.046875 },\n  { x: 0.109375, y: 0.046875 },\n  { x: 0.140625, y: 0.046875 },\n  { x: 0.140625, y: 0.046875 },\n  { x: 0.171875, y: 0.046875 },\n  { x: 0.171875, y: 0.046875 },\n  { x: 0.203125, y: 0.046875 },\n  { x: 0.203125, y: 0.046875 },\n  { x: 0.234375, y: 0.046875 },\n  { x: 0.234375, y: 0.046875 },\n  { x: 0.265625, y: 0.046875 },\n  { x: 0.265625, y: 0.046875 },\n  { x: 0.296875, y: 0.046875 },\n  { x: 0.296875, y: 0.046875 },\n  { x: 0.328125, y: 0.046875 },\n  { x: 0.328125, y: 0.046875 },\n  { x: 0.359375, y: 0.046875 },\n  { x: 0.359375, y: 0.046875 },\n  { x: 0.390625, y: 0.046875 },\n  { x: 0.390625, y: 0.046875 },\n  { x: 0.421875, y: 0.046875 },\n  { x: 0.421875, y: 0.046875 },\n  { x: 0.453125, y: 0.046875 },\n  { x: 0.453125, y: 0.046875 },\n  { x: 0.484375, y: 0.046875 },\n  { x: 0.484375, y: 0.046875 },\n  { x: 0.515625, y: 0.046875 },\n  { x: 0.515625, y: 0.046875 },\n  { x: 0.546875, y: 0.046875 },\n  { x: 0.546875, y: 0.046875 },\n  { x: 0.578125, y: 0.046875 },\n  { x: 0.578125, y: 0.046875 },\n  { x: 0.609375, y: 0.046875 },\n  { x: 0.609375, y: 0.046875 },\n  { x: 0.640625, y: 0.046875 },\n  { x: 0.640625, y: 0.046875 },\n  { x: 0.671875, y: 0.046875 },\n  { x: 0.671875, y: 0.046875 },\n  { x: 0.703125, y: 0.046875 },\n  { x: 0.703125, y: 0.046875 },\n  { x: 0.734375, y: 0.046875 },\n  { x: 0.734375, y: 0.046875 },\n  { x: 0.765625, y: 0.046875 },\n  { x: 0.765625, y: 0.046875 },\n  { x: 0.796875, y: 0.046875 },\n  { x: 0.796875, y: 0.046875 },\n  { x: 0.828125, y: 0.046875 },\n  { x: 0.828125, y: 0.046875 },\n  { x: 0.859375, y: 0.046875 },\n  { x: 0.859375, y: 0.046875 },\n  { x: 0.890625, y: 0.046875 },\n  { x: 0.890625, y: 0.046875 },\n  { x: 0.921875, y: 0.046875 },\n  { x: 0.921875, y: 0.046875 },\n  { x: 0.953125, y: 0.046875 },\n  { x: 0.953125, y: 0.046875 },\n  { x: 0.984375, y: 0.046875 },\n  { x: 0.984375, y: 0.046875 },\n  { x: 0.015625, y: 0.078125 },\n  { x: 0.015625, y: 0.078125 },\n  { x: 0.046875, y: 0.078125 },\n  { x: 0.046875, y: 0.078125 },\n  { x: 0.078125, y: 0.078125 },\n  { x: 0.078125, y: 0.078125 },\n  { x: 0.109375, y: 0.078125 },\n  { x: 0.109375, y: 0.078125 },\n  { x: 0.140625, y: 0.078125 },\n  { x: 0.140625, y: 0.078125 },\n  { x: 0.171875, y: 0.078125 },\n  { x: 0.171875, y: 0.078125 },\n  { x: 0.203125, y: 0.078125 },\n  { x: 0.203125, y: 0.078125 },\n  { x: 0.234375, y: 0.078125 },\n  { x: 0.234375, y: 0.078125 },\n  { x: 0.265625, y: 0.078125 },\n  { x: 0.265625, y: 0.078125 },\n  { x: 0.296875, y: 0.078125 },\n  { x: 0.296875, y: 0.078125 },\n  { x: 0.328125, y: 0.078125 },\n  { x: 0.328125, y: 0.078125 },\n  { x: 0.359375, y: 0.078125 },\n  { x: 0.359375, y: 0.078125 },\n  { x: 0.390625, y: 0.078125 },\n  { x: 0.390625, y: 0.078125 },\n  { x: 0.421875, y: 0.078125 },\n  { x: 0.421875, y: 0.078125 },\n  { x: 0.453125, y: 0.078125 },\n  { x: 0.453125, y: 0.078125 },\n  { x: 0.484375, y: 0.078125 },\n  { x: 0.484375, y: 0.078125 },\n  { x: 0.515625, y: 0.078125 },\n  { x: 0.515625, y: 0.078125 },\n  { x: 0.546875, y: 0.078125 },\n  { x: 0.546875, y: 0.078125 },\n  { x: 0.578125, y: 0.078125 },\n  { x: 0.578125, y: 0.078125 },\n  { x: 0.609375, y: 0.078125 },\n  { x: 0.609375, y: 0.078125 },\n  { x: 0.640625, y: 0.078125 },\n  { x: 0.640625, y: 0.078125 },\n  { x: 0.671875, y: 0.078125 },\n  { x: 0.671875, y: 0.078125 },\n  { x: 0.703125, y: 0.078125 },\n  { x: 0.703125, y: 0.078125 },\n  { x: 0.734375, y: 0.078125 },\n  { x: 0.734375, y: 0.078125 },\n  { x: 0.765625, y: 0.078125 },\n  { x: 0.765625, y: 0.078125 },\n  { x: 0.796875, y: 0.078125 },\n  { x: 0.796875, y: 0.078125 },\n  { x: 0.828125, y: 0.078125 },\n  { x: 0.828125, y: 0.078125 },\n  { x: 0.859375, y: 0.078125 },\n  { x: 0.859375, y: 0.078125 },\n  { x: 0.890625, y: 0.078125 },\n  { x: 0.890625, y: 0.078125 },\n  { x: 0.921875, y: 0.078125 },\n  { x: 0.921875, y: 0.078125 },\n  { x: 0.953125, y: 0.078125 },\n  { x: 0.953125, y: 0.078125 },\n  { x: 0.984375, y: 0.078125 },\n  { x: 0.984375, y: 0.078125 },\n  { x: 0.015625, y: 0.109375 },\n  { x: 0.015625, y: 0.109375 },\n  { x: 0.046875, y: 0.109375 },\n  { x: 0.046875, y: 0.109375 },\n  { x: 0.078125, y: 0.109375 },\n  { x: 0.078125, y: 0.109375 },\n  { x: 0.109375, y: 0.109375 },\n  { x: 0.109375, y: 0.109375 },\n  { x: 0.140625, y: 0.109375 },\n  { x: 0.140625, y: 0.109375 },\n  { x: 0.171875, y: 0.109375 },\n  { x: 0.171875, y: 0.109375 },\n  { x: 0.203125, y: 0.109375 },\n  { x: 0.203125, y: 0.109375 },\n  { x: 0.234375, y: 0.109375 },\n  { x: 0.234375, y: 0.109375 },\n  { x: 0.265625, y: 0.109375 },\n  { x: 0.265625, y: 0.109375 },\n  { x: 0.296875, y: 0.109375 },\n  { x: 0.296875, y: 0.109375 },\n  { x: 0.328125, y: 0.109375 },\n  { x: 0.328125, y: 0.109375 },\n  { x: 0.359375, y: 0.109375 },\n  { x: 0.359375, y: 0.109375 },\n  { x: 0.390625, y: 0.109375 },\n  { x: 0.390625, y: 0.109375 },\n  { x: 0.421875, y: 0.109375 },\n  { x: 0.421875, y: 0.109375 },\n  { x: 0.453125, y: 0.109375 },\n  { x: 0.453125, y: 0.109375 },\n  { x: 0.484375, y: 0.109375 },\n  { x: 0.484375, y: 0.109375 },\n  { x: 0.515625, y: 0.109375 },\n  { x: 0.515625, y: 0.109375 },\n  { x: 0.546875, y: 0.109375 },\n  { x: 0.546875, y: 0.109375 },\n  { x: 0.578125, y: 0.109375 },\n  { x: 0.578125, y: 0.109375 },\n  { x: 0.609375, y: 0.109375 },\n  { x: 0.609375, y: 0.109375 },\n  { x: 0.640625, y: 0.109375 },\n  { x: 0.640625, y: 0.109375 },\n  { x: 0.671875, y: 0.109375 },\n  { x: 0.671875, y: 0.109375 },\n  { x: 0.703125, y: 0.109375 },\n  { x: 0.703125, y: 0.109375 },\n  { x: 0.734375, y: 0.109375 },\n  { x: 0.734375, y: 0.109375 },\n  { x: 0.765625, y: 0.109375 },\n  { x: 0.765625, y: 0.109375 },\n  { x: 0.796875, y: 0.109375 },\n  { x: 0.796875, y: 0.109375 },\n  { x: 0.828125, y: 0.109375 },\n  { x: 0.828125, y: 0.109375 },\n  { x: 0.859375, y: 0.109375 },\n  { x: 0.859375, y: 0.109375 },\n  { x: 0.890625, y: 0.109375 },\n  { x: 0.890625, y: 0.109375 },\n  { x: 0.921875, y: 0.109375 },\n  { x: 0.921875, y: 0.109375 },\n  { x: 0.953125, y: 0.109375 },\n  { x: 0.953125, y: 0.109375 },\n  { x: 0.984375, y: 0.109375 },\n  { x: 0.984375, y: 0.109375 },\n  { x: 0.015625, y: 0.140625 },\n  { x: 0.015625, y: 0.140625 },\n  { x: 0.046875, y: 0.140625 },\n  { x: 0.046875, y: 0.140625 },\n  { x: 0.078125, y: 0.140625 },\n  { x: 0.078125, y: 0.140625 },\n  { x: 0.109375, y: 0.140625 },\n  { x: 0.109375, y: 0.140625 },\n  { x: 0.140625, y: 0.140625 },\n  { x: 0.140625, y: 0.140625 },\n  { x: 0.171875, y: 0.140625 },\n  { x: 0.171875, y: 0.140625 },\n  { x: 0.203125, y: 0.140625 },\n  { x: 0.203125, y: 0.140625 },\n  { x: 0.234375, y: 0.140625 },\n  { x: 0.234375, y: 0.140625 },\n  { x: 0.265625, y: 0.140625 },\n  { x: 0.265625, y: 0.140625 },\n  { x: 0.296875, y: 0.140625 },\n  { x: 0.296875, y: 0.140625 },\n  { x: 0.328125, y: 0.140625 },\n  { x: 0.328125, y: 0.140625 },\n  { x: 0.359375, y: 0.140625 },\n  { x: 0.359375, y: 0.140625 },\n  { x: 0.390625, y: 0.140625 },\n  { x: 0.390625, y: 0.140625 },\n  { x: 0.421875, y: 0.140625 },\n  { x: 0.421875, y: 0.140625 },\n  { x: 0.453125, y: 0.140625 },\n  { x: 0.453125, y: 0.140625 },\n  { x: 0.484375, y: 0.140625 },\n  { x: 0.484375, y: 0.140625 },\n  { x: 0.515625, y: 0.140625 },\n  { x: 0.515625, y: 0.140625 },\n  { x: 0.546875, y: 0.140625 },\n  { x: 0.546875, y: 0.140625 },\n  { x: 0.578125, y: 0.140625 },\n  { x: 0.578125, y: 0.140625 },\n  { x: 0.609375, y: 0.140625 },\n  { x: 0.609375, y: 0.140625 },\n  { x: 0.640625, y: 0.140625 },\n  { x: 0.640625, y: 0.140625 },\n  { x: 0.671875, y: 0.140625 },\n  { x: 0.671875, y: 0.140625 },\n  { x: 0.703125, y: 0.140625 },\n  { x: 0.703125, y: 0.140625 },\n  { x: 0.734375, y: 0.140625 },\n  { x: 0.734375, y: 0.140625 },\n  { x: 0.765625, y: 0.140625 },\n  { x: 0.765625, y: 0.140625 },\n  { x: 0.796875, y: 0.140625 },\n  { x: 0.796875, y: 0.140625 },\n  { x: 0.828125, y: 0.140625 },\n  { x: 0.828125, y: 0.140625 },\n  { x: 0.859375, y: 0.140625 },\n  { x: 0.859375, y: 0.140625 },\n  { x: 0.890625, y: 0.140625 },\n  { x: 0.890625, y: 0.140625 },\n  { x: 0.921875, y: 0.140625 },\n  { x: 0.921875, y: 0.140625 },\n  { x: 0.953125, y: 0.140625 },\n  { x: 0.953125, y: 0.140625 },\n  { x: 0.984375, y: 0.140625 },\n  { x: 0.984375, y: 0.140625 },\n  { x: 0.015625, y: 0.171875 },\n  { x: 0.015625, y: 0.171875 },\n  { x: 0.046875, y: 0.171875 },\n  { x: 0.046875, y: 0.171875 },\n  { x: 0.078125, y: 0.171875 },\n  { x: 0.078125, y: 0.171875 },\n  { x: 0.109375, y: 0.171875 },\n  { x: 0.109375, y: 0.171875 },\n  { x: 0.140625, y: 0.171875 },\n  { x: 0.140625, y: 0.171875 },\n  { x: 0.171875, y: 0.171875 },\n  { x: 0.171875, y: 0.171875 },\n  { x: 0.203125, y: 0.171875 },\n  { x: 0.203125, y: 0.171875 },\n  { x: 0.234375, y: 0.171875 },\n  { x: 0.234375, y: 0.171875 },\n  { x: 0.265625, y: 0.171875 },\n  { x: 0.265625, y: 0.171875 },\n  { x: 0.296875, y: 0.171875 },\n  { x: 0.296875, y: 0.171875 },\n  { x: 0.328125, y: 0.171875 },\n  { x: 0.328125, y: 0.171875 },\n  { x: 0.359375, y: 0.171875 },\n  { x: 0.359375, y: 0.171875 },\n  { x: 0.390625, y: 0.171875 },\n  { x: 0.390625, y: 0.171875 },\n  { x: 0.421875, y: 0.171875 },\n  { x: 0.421875, y: 0.171875 },\n  { x: 0.453125, y: 0.171875 },\n  { x: 0.453125, y: 0.171875 },\n  { x: 0.484375, y: 0.171875 },\n  { x: 0.484375, y: 0.171875 },\n  { x: 0.515625, y: 0.171875 },\n  { x: 0.515625, y: 0.171875 },\n  { x: 0.546875, y: 0.171875 },\n  { x: 0.546875, y: 0.171875 },\n  { x: 0.578125, y: 0.171875 },\n  { x: 0.578125, y: 0.171875 },\n  { x: 0.609375, y: 0.171875 },\n  { x: 0.609375, y: 0.171875 },\n  { x: 0.640625, y: 0.171875 },\n  { x: 0.640625, y: 0.171875 },\n  { x: 0.671875, y: 0.171875 },\n  { x: 0.671875, y: 0.171875 },\n  { x: 0.703125, y: 0.171875 },\n  { x: 0.703125, y: 0.171875 },\n  { x: 0.734375, y: 0.171875 },\n  { x: 0.734375, y: 0.171875 },\n  { x: 0.765625, y: 0.171875 },\n  { x: 0.765625, y: 0.171875 },\n  { x: 0.796875, y: 0.171875 },\n  { x: 0.796875, y: 0.171875 },\n  { x: 0.828125, y: 0.171875 },\n  { x: 0.828125, y: 0.171875 },\n  { x: 0.859375, y: 0.171875 },\n  { x: 0.859375, y: 0.171875 },\n  { x: 0.890625, y: 0.171875 },\n  { x: 0.890625, y: 0.171875 },\n  { x: 0.921875, y: 0.171875 },\n  { x: 0.921875, y: 0.171875 },\n  { x: 0.953125, y: 0.171875 },\n  { x: 0.953125, y: 0.171875 },\n  { x: 0.984375, y: 0.171875 },\n  { x: 0.984375, y: 0.171875 },\n  { x: 0.015625, y: 0.203125 },\n  { x: 0.015625, y: 0.203125 },\n  { x: 0.046875, y: 0.203125 },\n  { x: 0.046875, y: 0.203125 },\n  { x: 0.078125, y: 0.203125 },\n  { x: 0.078125, y: 0.203125 },\n  { x: 0.109375, y: 0.203125 },\n  { x: 0.109375, y: 0.203125 },\n  { x: 0.140625, y: 0.203125 },\n  { x: 0.140625, y: 0.203125 },\n  { x: 0.171875, y: 0.203125 },\n  { x: 0.171875, y: 0.203125 },\n  { x: 0.203125, y: 0.203125 },\n  { x: 0.203125, y: 0.203125 },\n  { x: 0.234375, y: 0.203125 },\n  { x: 0.234375, y: 0.203125 },\n  { x: 0.265625, y: 0.203125 },\n  { x: 0.265625, y: 0.203125 },\n  { x: 0.296875, y: 0.203125 },\n  { x: 0.296875, y: 0.203125 },\n  { x: 0.328125, y: 0.203125 },\n  { x: 0.328125, y: 0.203125 },\n  { x: 0.359375, y: 0.203125 },\n  { x: 0.359375, y: 0.203125 },\n  { x: 0.390625, y: 0.203125 },\n  { x: 0.390625, y: 0.203125 },\n  { x: 0.421875, y: 0.203125 },\n  { x: 0.421875, y: 0.203125 },\n  { x: 0.453125, y: 0.203125 },\n  { x: 0.453125, y: 0.203125 },\n  { x: 0.484375, y: 0.203125 },\n  { x: 0.484375, y: 0.203125 },\n  { x: 0.515625, y: 0.203125 },\n  { x: 0.515625, y: 0.203125 },\n  { x: 0.546875, y: 0.203125 },\n  { x: 0.546875, y: 0.203125 },\n  { x: 0.578125, y: 0.203125 },\n  { x: 0.578125, y: 0.203125 },\n  { x: 0.609375, y: 0.203125 },\n  { x: 0.609375, y: 0.203125 },\n  { x: 0.640625, y: 0.203125 },\n  { x: 0.640625, y: 0.203125 },\n  { x: 0.671875, y: 0.203125 },\n  { x: 0.671875, y: 0.203125 },\n  { x: 0.703125, y: 0.203125 },\n  { x: 0.703125, y: 0.203125 },\n  { x: 0.734375, y: 0.203125 },\n  { x: 0.734375, y: 0.203125 },\n  { x: 0.765625, y: 0.203125 },\n  { x: 0.765625, y: 0.203125 },\n  { x: 0.796875, y: 0.203125 },\n  { x: 0.796875, y: 0.203125 },\n  { x: 0.828125, y: 0.203125 },\n  { x: 0.828125, y: 0.203125 },\n  { x: 0.859375, y: 0.203125 },\n  { x: 0.859375, y: 0.203125 },\n  { x: 0.890625, y: 0.203125 },\n  { x: 0.890625, y: 0.203125 },\n  { x: 0.921875, y: 0.203125 },\n  { x: 0.921875, y: 0.203125 },\n  { x: 0.953125, y: 0.203125 },\n  { x: 0.953125, y: 0.203125 },\n  { x: 0.984375, y: 0.203125 },\n  { x: 0.984375, y: 0.203125 },\n  { x: 0.015625, y: 0.234375 },\n  { x: 0.015625, y: 0.234375 },\n  { x: 0.046875, y: 0.234375 },\n  { x: 0.046875, y: 0.234375 },\n  { x: 0.078125, y: 0.234375 },\n  { x: 0.078125, y: 0.234375 },\n  { x: 0.109375, y: 0.234375 },\n  { x: 0.109375, y: 0.234375 },\n  { x: 0.140625, y: 0.234375 },\n  { x: 0.140625, y: 0.234375 },\n  { x: 0.171875, y: 0.234375 },\n  { x: 0.171875, y: 0.234375 },\n  { x: 0.203125, y: 0.234375 },\n  { x: 0.203125, y: 0.234375 },\n  { x: 0.234375, y: 0.234375 },\n  { x: 0.234375, y: 0.234375 },\n  { x: 0.265625, y: 0.234375 },\n  { x: 0.265625, y: 0.234375 },\n  { x: 0.296875, y: 0.234375 },\n  { x: 0.296875, y: 0.234375 },\n  { x: 0.328125, y: 0.234375 },\n  { x: 0.328125, y: 0.234375 },\n  { x: 0.359375, y: 0.234375 },\n  { x: 0.359375, y: 0.234375 },\n  { x: 0.390625, y: 0.234375 },\n  { x: 0.390625, y: 0.234375 },\n  { x: 0.421875, y: 0.234375 },\n  { x: 0.421875, y: 0.234375 },\n  { x: 0.453125, y: 0.234375 },\n  { x: 0.453125, y: 0.234375 },\n  { x: 0.484375, y: 0.234375 },\n  { x: 0.484375, y: 0.234375 },\n  { x: 0.515625, y: 0.234375 },\n  { x: 0.515625, y: 0.234375 },\n  { x: 0.546875, y: 0.234375 },\n  { x: 0.546875, y: 0.234375 },\n  { x: 0.578125, y: 0.234375 },\n  { x: 0.578125, y: 0.234375 },\n  { x: 0.609375, y: 0.234375 },\n  { x: 0.609375, y: 0.234375 },\n  { x: 0.640625, y: 0.234375 },\n  { x: 0.640625, y: 0.234375 },\n  { x: 0.671875, y: 0.234375 },\n  { x: 0.671875, y: 0.234375 },\n  { x: 0.703125, y: 0.234375 },\n  { x: 0.703125, y: 0.234375 },\n  { x: 0.734375, y: 0.234375 },\n  { x: 0.734375, y: 0.234375 },\n  { x: 0.765625, y: 0.234375 },\n  { x: 0.765625, y: 0.234375 },\n  { x: 0.796875, y: 0.234375 },\n  { x: 0.796875, y: 0.234375 },\n  { x: 0.828125, y: 0.234375 },\n  { x: 0.828125, y: 0.234375 },\n  { x: 0.859375, y: 0.234375 },\n  { x: 0.859375, y: 0.234375 },\n  { x: 0.890625, y: 0.234375 },\n  { x: 0.890625, y: 0.234375 },\n  { x: 0.921875, y: 0.234375 },\n  { x: 0.921875, y: 0.234375 },\n  { x: 0.953125, y: 0.234375 },\n  { x: 0.953125, y: 0.234375 },\n  { x: 0.984375, y: 0.234375 },\n  { x: 0.984375, y: 0.234375 },\n  { x: 0.015625, y: 0.265625 },\n  { x: 0.015625, y: 0.265625 },\n  { x: 0.046875, y: 0.265625 },\n  { x: 0.046875, y: 0.265625 },\n  { x: 0.078125, y: 0.265625 },\n  { x: 0.078125, y: 0.265625 },\n  { x: 0.109375, y: 0.265625 },\n  { x: 0.109375, y: 0.265625 },\n  { x: 0.140625, y: 0.265625 },\n  { x: 0.140625, y: 0.265625 },\n  { x: 0.171875, y: 0.265625 },\n  { x: 0.171875, y: 0.265625 },\n  { x: 0.203125, y: 0.265625 },\n  { x: 0.203125, y: 0.265625 },\n  { x: 0.234375, y: 0.265625 },\n  { x: 0.234375, y: 0.265625 },\n  { x: 0.265625, y: 0.265625 },\n  { x: 0.265625, y: 0.265625 },\n  { x: 0.296875, y: 0.265625 },\n  { x: 0.296875, y: 0.265625 },\n  { x: 0.328125, y: 0.265625 },\n  { x: 0.328125, y: 0.265625 },\n  { x: 0.359375, y: 0.265625 },\n  { x: 0.359375, y: 0.265625 },\n  { x: 0.390625, y: 0.265625 },\n  { x: 0.390625, y: 0.265625 },\n  { x: 0.421875, y: 0.265625 },\n  { x: 0.421875, y: 0.265625 },\n  { x: 0.453125, y: 0.265625 },\n  { x: 0.453125, y: 0.265625 },\n  { x: 0.484375, y: 0.265625 },\n  { x: 0.484375, y: 0.265625 },\n  { x: 0.515625, y: 0.265625 },\n  { x: 0.515625, y: 0.265625 },\n  { x: 0.546875, y: 0.265625 },\n  { x: 0.546875, y: 0.265625 },\n  { x: 0.578125, y: 0.265625 },\n  { x: 0.578125, y: 0.265625 },\n  { x: 0.609375, y: 0.265625 },\n  { x: 0.609375, y: 0.265625 },\n  { x: 0.640625, y: 0.265625 },\n  { x: 0.640625, y: 0.265625 },\n  { x: 0.671875, y: 0.265625 },\n  { x: 0.671875, y: 0.265625 },\n  { x: 0.703125, y: 0.265625 },\n  { x: 0.703125, y: 0.265625 },\n  { x: 0.734375, y: 0.265625 },\n  { x: 0.734375, y: 0.265625 },\n  { x: 0.765625, y: 0.265625 },\n  { x: 0.765625, y: 0.265625 },\n  { x: 0.796875, y: 0.265625 },\n  { x: 0.796875, y: 0.265625 },\n  { x: 0.828125, y: 0.265625 },\n  { x: 0.828125, y: 0.265625 },\n  { x: 0.859375, y: 0.265625 },\n  { x: 0.859375, y: 0.265625 },\n  { x: 0.890625, y: 0.265625 },\n  { x: 0.890625, y: 0.265625 },\n  { x: 0.921875, y: 0.265625 },\n  { x: 0.921875, y: 0.265625 },\n  { x: 0.953125, y: 0.265625 },\n  { x: 0.953125, y: 0.265625 },\n  { x: 0.984375, y: 0.265625 },\n  { x: 0.984375, y: 0.265625 },\n  { x: 0.015625, y: 0.296875 },\n  { x: 0.015625, y: 0.296875 },\n  { x: 0.046875, y: 0.296875 },\n  { x: 0.046875, y: 0.296875 },\n  { x: 0.078125, y: 0.296875 },\n  { x: 0.078125, y: 0.296875 },\n  { x: 0.109375, y: 0.296875 },\n  { x: 0.109375, y: 0.296875 },\n  { x: 0.140625, y: 0.296875 },\n  { x: 0.140625, y: 0.296875 },\n  { x: 0.171875, y: 0.296875 },\n  { x: 0.171875, y: 0.296875 },\n  { x: 0.203125, y: 0.296875 },\n  { x: 0.203125, y: 0.296875 },\n  { x: 0.234375, y: 0.296875 },\n  { x: 0.234375, y: 0.296875 },\n  { x: 0.265625, y: 0.296875 },\n  { x: 0.265625, y: 0.296875 },\n  { x: 0.296875, y: 0.296875 },\n  { x: 0.296875, y: 0.296875 },\n  { x: 0.328125, y: 0.296875 },\n  { x: 0.328125, y: 0.296875 },\n  { x: 0.359375, y: 0.296875 },\n  { x: 0.359375, y: 0.296875 },\n  { x: 0.390625, y: 0.296875 },\n  { x: 0.390625, y: 0.296875 },\n  { x: 0.421875, y: 0.296875 },\n  { x: 0.421875, y: 0.296875 },\n  { x: 0.453125, y: 0.296875 },\n  { x: 0.453125, y: 0.296875 },\n  { x: 0.484375, y: 0.296875 },\n  { x: 0.484375, y: 0.296875 },\n  { x: 0.515625, y: 0.296875 },\n  { x: 0.515625, y: 0.296875 },\n  { x: 0.546875, y: 0.296875 },\n  { x: 0.546875, y: 0.296875 },\n  { x: 0.578125, y: 0.296875 },\n  { x: 0.578125, y: 0.296875 },\n  { x: 0.609375, y: 0.296875 },\n  { x: 0.609375, y: 0.296875 },\n  { x: 0.640625, y: 0.296875 },\n  { x: 0.640625, y: 0.296875 },\n  { x: 0.671875, y: 0.296875 },\n  { x: 0.671875, y: 0.296875 },\n  { x: 0.703125, y: 0.296875 },\n  { x: 0.703125, y: 0.296875 },\n  { x: 0.734375, y: 0.296875 },\n  { x: 0.734375, y: 0.296875 },\n  { x: 0.765625, y: 0.296875 },\n  { x: 0.765625, y: 0.296875 },\n  { x: 0.796875, y: 0.296875 },\n  { x: 0.796875, y: 0.296875 },\n  { x: 0.828125, y: 0.296875 },\n  { x: 0.828125, y: 0.296875 },\n  { x: 0.859375, y: 0.296875 },\n  { x: 0.859375, y: 0.296875 },\n  { x: 0.890625, y: 0.296875 },\n  { x: 0.890625, y: 0.296875 },\n  { x: 0.921875, y: 0.296875 },\n  { x: 0.921875, y: 0.296875 },\n  { x: 0.953125, y: 0.296875 },\n  { x: 0.953125, y: 0.296875 },\n  { x: 0.984375, y: 0.296875 },\n  { x: 0.984375, y: 0.296875 },\n  { x: 0.015625, y: 0.328125 },\n  { x: 0.015625, y: 0.328125 },\n  { x: 0.046875, y: 0.328125 },\n  { x: 0.046875, y: 0.328125 },\n  { x: 0.078125, y: 0.328125 },\n  { x: 0.078125, y: 0.328125 },\n  { x: 0.109375, y: 0.328125 },\n  { x: 0.109375, y: 0.328125 },\n  { x: 0.140625, y: 0.328125 },\n  { x: 0.140625, y: 0.328125 },\n  { x: 0.171875, y: 0.328125 },\n  { x: 0.171875, y: 0.328125 },\n  { x: 0.203125, y: 0.328125 },\n  { x: 0.203125, y: 0.328125 },\n  { x: 0.234375, y: 0.328125 },\n  { x: 0.234375, y: 0.328125 },\n  { x: 0.265625, y: 0.328125 },\n  { x: 0.265625, y: 0.328125 },\n  { x: 0.296875, y: 0.328125 },\n  { x: 0.296875, y: 0.328125 },\n  { x: 0.328125, y: 0.328125 },\n  { x: 0.328125, y: 0.328125 },\n  { x: 0.359375, y: 0.328125 },\n  { x: 0.359375, y: 0.328125 },\n  { x: 0.390625, y: 0.328125 },\n  { x: 0.390625, y: 0.328125 },\n  { x: 0.421875, y: 0.328125 },\n  { x: 0.421875, y: 0.328125 },\n  { x: 0.453125, y: 0.328125 },\n  { x: 0.453125, y: 0.328125 },\n  { x: 0.484375, y: 0.328125 },\n  { x: 0.484375, y: 0.328125 },\n  { x: 0.515625, y: 0.328125 },\n  { x: 0.515625, y: 0.328125 },\n  { x: 0.546875, y: 0.328125 },\n  { x: 0.546875, y: 0.328125 },\n  { x: 0.578125, y: 0.328125 },\n  { x: 0.578125, y: 0.328125 },\n  { x: 0.609375, y: 0.328125 },\n  { x: 0.609375, y: 0.328125 },\n  { x: 0.640625, y: 0.328125 },\n  { x: 0.640625, y: 0.328125 },\n  { x: 0.671875, y: 0.328125 },\n  { x: 0.671875, y: 0.328125 },\n  { x: 0.703125, y: 0.328125 },\n  { x: 0.703125, y: 0.328125 },\n  { x: 0.734375, y: 0.328125 },\n  { x: 0.734375, y: 0.328125 },\n  { x: 0.765625, y: 0.328125 },\n  { x: 0.765625, y: 0.328125 },\n  { x: 0.796875, y: 0.328125 },\n  { x: 0.796875, y: 0.328125 },\n  { x: 0.828125, y: 0.328125 },\n  { x: 0.828125, y: 0.328125 },\n  { x: 0.859375, y: 0.328125 },\n  { x: 0.859375, y: 0.328125 },\n  { x: 0.890625, y: 0.328125 },\n  { x: 0.890625, y: 0.328125 },\n  { x: 0.921875, y: 0.328125 },\n  { x: 0.921875, y: 0.328125 },\n  { x: 0.953125, y: 0.328125 },\n  { x: 0.953125, y: 0.328125 },\n  { x: 0.984375, y: 0.328125 },\n  { x: 0.984375, y: 0.328125 },\n  { x: 0.015625, y: 0.359375 },\n  { x: 0.015625, y: 0.359375 },\n  { x: 0.046875, y: 0.359375 },\n  { x: 0.046875, y: 0.359375 },\n  { x: 0.078125, y: 0.359375 },\n  { x: 0.078125, y: 0.359375 },\n  { x: 0.109375, y: 0.359375 },\n  { x: 0.109375, y: 0.359375 },\n  { x: 0.140625, y: 0.359375 },\n  { x: 0.140625, y: 0.359375 },\n  { x: 0.171875, y: 0.359375 },\n  { x: 0.171875, y: 0.359375 },\n  { x: 0.203125, y: 0.359375 },\n  { x: 0.203125, y: 0.359375 },\n  { x: 0.234375, y: 0.359375 },\n  { x: 0.234375, y: 0.359375 },\n  { x: 0.265625, y: 0.359375 },\n  { x: 0.265625, y: 0.359375 },\n  { x: 0.296875, y: 0.359375 },\n  { x: 0.296875, y: 0.359375 },\n  { x: 0.328125, y: 0.359375 },\n  { x: 0.328125, y: 0.359375 },\n  { x: 0.359375, y: 0.359375 },\n  { x: 0.359375, y: 0.359375 },\n  { x: 0.390625, y: 0.359375 },\n  { x: 0.390625, y: 0.359375 },\n  { x: 0.421875, y: 0.359375 },\n  { x: 0.421875, y: 0.359375 },\n  { x: 0.453125, y: 0.359375 },\n  { x: 0.453125, y: 0.359375 },\n  { x: 0.484375, y: 0.359375 },\n  { x: 0.484375, y: 0.359375 },\n  { x: 0.515625, y: 0.359375 },\n  { x: 0.515625, y: 0.359375 },\n  { x: 0.546875, y: 0.359375 },\n  { x: 0.546875, y: 0.359375 },\n  { x: 0.578125, y: 0.359375 },\n  { x: 0.578125, y: 0.359375 },\n  { x: 0.609375, y: 0.359375 },\n  { x: 0.609375, y: 0.359375 },\n  { x: 0.640625, y: 0.359375 },\n  { x: 0.640625, y: 0.359375 },\n  { x: 0.671875, y: 0.359375 },\n  { x: 0.671875, y: 0.359375 },\n  { x: 0.703125, y: 0.359375 },\n  { x: 0.703125, y: 0.359375 },\n  { x: 0.734375, y: 0.359375 },\n  { x: 0.734375, y: 0.359375 },\n  { x: 0.765625, y: 0.359375 },\n  { x: 0.765625, y: 0.359375 },\n  { x: 0.796875, y: 0.359375 },\n  { x: 0.796875, y: 0.359375 },\n  { x: 0.828125, y: 0.359375 },\n  { x: 0.828125, y: 0.359375 },\n  { x: 0.859375, y: 0.359375 },\n  { x: 0.859375, y: 0.359375 },\n  { x: 0.890625, y: 0.359375 },\n  { x: 0.890625, y: 0.359375 },\n  { x: 0.921875, y: 0.359375 },\n  { x: 0.921875, y: 0.359375 },\n  { x: 0.953125, y: 0.359375 },\n  { x: 0.953125, y: 0.359375 },\n  { x: 0.984375, y: 0.359375 },\n  { x: 0.984375, y: 0.359375 },\n  { x: 0.015625, y: 0.390625 },\n  { x: 0.015625, y: 0.390625 },\n  { x: 0.046875, y: 0.390625 },\n  { x: 0.046875, y: 0.390625 },\n  { x: 0.078125, y: 0.390625 },\n  { x: 0.078125, y: 0.390625 },\n  { x: 0.109375, y: 0.390625 },\n  { x: 0.109375, y: 0.390625 },\n  { x: 0.140625, y: 0.390625 },\n  { x: 0.140625, y: 0.390625 },\n  { x: 0.171875, y: 0.390625 },\n  { x: 0.171875, y: 0.390625 },\n  { x: 0.203125, y: 0.390625 },\n  { x: 0.203125, y: 0.390625 },\n  { x: 0.234375, y: 0.390625 },\n  { x: 0.234375, y: 0.390625 },\n  { x: 0.265625, y: 0.390625 },\n  { x: 0.265625, y: 0.390625 },\n  { x: 0.296875, y: 0.390625 },\n  { x: 0.296875, y: 0.390625 },\n  { x: 0.328125, y: 0.390625 },\n  { x: 0.328125, y: 0.390625 },\n  { x: 0.359375, y: 0.390625 },\n  { x: 0.359375, y: 0.390625 },\n  { x: 0.390625, y: 0.390625 },\n  { x: 0.390625, y: 0.390625 },\n  { x: 0.421875, y: 0.390625 },\n  { x: 0.421875, y: 0.390625 },\n  { x: 0.453125, y: 0.390625 },\n  { x: 0.453125, y: 0.390625 },\n  { x: 0.484375, y: 0.390625 },\n  { x: 0.484375, y: 0.390625 },\n  { x: 0.515625, y: 0.390625 },\n  { x: 0.515625, y: 0.390625 },\n  { x: 0.546875, y: 0.390625 },\n  { x: 0.546875, y: 0.390625 },\n  { x: 0.578125, y: 0.390625 },\n  { x: 0.578125, y: 0.390625 },\n  { x: 0.609375, y: 0.390625 },\n  { x: 0.609375, y: 0.390625 },\n  { x: 0.640625, y: 0.390625 },\n  { x: 0.640625, y: 0.390625 },\n  { x: 0.671875, y: 0.390625 },\n  { x: 0.671875, y: 0.390625 },\n  { x: 0.703125, y: 0.390625 },\n  { x: 0.703125, y: 0.390625 },\n  { x: 0.734375, y: 0.390625 },\n  { x: 0.734375, y: 0.390625 },\n  { x: 0.765625, y: 0.390625 },\n  { x: 0.765625, y: 0.390625 },\n  { x: 0.796875, y: 0.390625 },\n  { x: 0.796875, y: 0.390625 },\n  { x: 0.828125, y: 0.390625 },\n  { x: 0.828125, y: 0.390625 },\n  { x: 0.859375, y: 0.390625 },\n  { x: 0.859375, y: 0.390625 },\n  { x: 0.890625, y: 0.390625 },\n  { x: 0.890625, y: 0.390625 },\n  { x: 0.921875, y: 0.390625 },\n  { x: 0.921875, y: 0.390625 },\n  { x: 0.953125, y: 0.390625 },\n  { x: 0.953125, y: 0.390625 },\n  { x: 0.984375, y: 0.390625 },\n  { x: 0.984375, y: 0.390625 },\n  { x: 0.015625, y: 0.421875 },\n  { x: 0.015625, y: 0.421875 },\n  { x: 0.046875, y: 0.421875 },\n  { x: 0.046875, y: 0.421875 },\n  { x: 0.078125, y: 0.421875 },\n  { x: 0.078125, y: 0.421875 },\n  { x: 0.109375, y: 0.421875 },\n  { x: 0.109375, y: 0.421875 },\n  { x: 0.140625, y: 0.421875 },\n  { x: 0.140625, y: 0.421875 },\n  { x: 0.171875, y: 0.421875 },\n  { x: 0.171875, y: 0.421875 },\n  { x: 0.203125, y: 0.421875 },\n  { x: 0.203125, y: 0.421875 },\n  { x: 0.234375, y: 0.421875 },\n  { x: 0.234375, y: 0.421875 },\n  { x: 0.265625, y: 0.421875 },\n  { x: 0.265625, y: 0.421875 },\n  { x: 0.296875, y: 0.421875 },\n  { x: 0.296875, y: 0.421875 },\n  { x: 0.328125, y: 0.421875 },\n  { x: 0.328125, y: 0.421875 },\n  { x: 0.359375, y: 0.421875 },\n  { x: 0.359375, y: 0.421875 },\n  { x: 0.390625, y: 0.421875 },\n  { x: 0.390625, y: 0.421875 },\n  { x: 0.421875, y: 0.421875 },\n  { x: 0.421875, y: 0.421875 },\n  { x: 0.453125, y: 0.421875 },\n  { x: 0.453125, y: 0.421875 },\n  { x: 0.484375, y: 0.421875 },\n  { x: 0.484375, y: 0.421875 },\n  { x: 0.515625, y: 0.421875 },\n  { x: 0.515625, y: 0.421875 },\n  { x: 0.546875, y: 0.421875 },\n  { x: 0.546875, y: 0.421875 },\n  { x: 0.578125, y: 0.421875 },\n  { x: 0.578125, y: 0.421875 },\n  { x: 0.609375, y: 0.421875 },\n  { x: 0.609375, y: 0.421875 },\n  { x: 0.640625, y: 0.421875 },\n  { x: 0.640625, y: 0.421875 },\n  { x: 0.671875, y: 0.421875 },\n  { x: 0.671875, y: 0.421875 },\n  { x: 0.703125, y: 0.421875 },\n  { x: 0.703125, y: 0.421875 },\n  { x: 0.734375, y: 0.421875 },\n  { x: 0.734375, y: 0.421875 },\n  { x: 0.765625, y: 0.421875 },\n  { x: 0.765625, y: 0.421875 },\n  { x: 0.796875, y: 0.421875 },\n  { x: 0.796875, y: 0.421875 },\n  { x: 0.828125, y: 0.421875 },\n  { x: 0.828125, y: 0.421875 },\n  { x: 0.859375, y: 0.421875 },\n  { x: 0.859375, y: 0.421875 },\n  { x: 0.890625, y: 0.421875 },\n  { x: 0.890625, y: 0.421875 },\n  { x: 0.921875, y: 0.421875 },\n  { x: 0.921875, y: 0.421875 },\n  { x: 0.953125, y: 0.421875 },\n  { x: 0.953125, y: 0.421875 },\n  { x: 0.984375, y: 0.421875 },\n  { x: 0.984375, y: 0.421875 },\n  { x: 0.015625, y: 0.453125 },\n  { x: 0.015625, y: 0.453125 },\n  { x: 0.046875, y: 0.453125 },\n  { x: 0.046875, y: 0.453125 },\n  { x: 0.078125, y: 0.453125 },\n  { x: 0.078125, y: 0.453125 },\n  { x: 0.109375, y: 0.453125 },\n  { x: 0.109375, y: 0.453125 },\n  { x: 0.140625, y: 0.453125 },\n  { x: 0.140625, y: 0.453125 },\n  { x: 0.171875, y: 0.453125 },\n  { x: 0.171875, y: 0.453125 },\n  { x: 0.203125, y: 0.453125 },\n  { x: 0.203125, y: 0.453125 },\n  { x: 0.234375, y: 0.453125 },\n  { x: 0.234375, y: 0.453125 },\n  { x: 0.265625, y: 0.453125 },\n  { x: 0.265625, y: 0.453125 },\n  { x: 0.296875, y: 0.453125 },\n  { x: 0.296875, y: 0.453125 },\n  { x: 0.328125, y: 0.453125 },\n  { x: 0.328125, y: 0.453125 },\n  { x: 0.359375, y: 0.453125 },\n  { x: 0.359375, y: 0.453125 },\n  { x: 0.390625, y: 0.453125 },\n  { x: 0.390625, y: 0.453125 },\n  { x: 0.421875, y: 0.453125 },\n  { x: 0.421875, y: 0.453125 },\n  { x: 0.453125, y: 0.453125 },\n  { x: 0.453125, y: 0.453125 },\n  { x: 0.484375, y: 0.453125 },\n  { x: 0.484375, y: 0.453125 },\n  { x: 0.515625, y: 0.453125 },\n  { x: 0.515625, y: 0.453125 },\n  { x: 0.546875, y: 0.453125 },\n  { x: 0.546875, y: 0.453125 },\n  { x: 0.578125, y: 0.453125 },\n  { x: 0.578125, y: 0.453125 },\n  { x: 0.609375, y: 0.453125 },\n  { x: 0.609375, y: 0.453125 },\n  { x: 0.640625, y: 0.453125 },\n  { x: 0.640625, y: 0.453125 },\n  { x: 0.671875, y: 0.453125 },\n  { x: 0.671875, y: 0.453125 },\n  { x: 0.703125, y: 0.453125 },\n  { x: 0.703125, y: 0.453125 },\n  { x: 0.734375, y: 0.453125 },\n  { x: 0.734375, y: 0.453125 },\n  { x: 0.765625, y: 0.453125 },\n  { x: 0.765625, y: 0.453125 },\n  { x: 0.796875, y: 0.453125 },\n  { x: 0.796875, y: 0.453125 },\n  { x: 0.828125, y: 0.453125 },\n  { x: 0.828125, y: 0.453125 },\n  { x: 0.859375, y: 0.453125 },\n  { x: 0.859375, y: 0.453125 },\n  { x: 0.890625, y: 0.453125 },\n  { x: 0.890625, y: 0.453125 },\n  { x: 0.921875, y: 0.453125 },\n  { x: 0.921875, y: 0.453125 },\n  { x: 0.953125, y: 0.453125 },\n  { x: 0.953125, y: 0.453125 },\n  { x: 0.984375, y: 0.453125 },\n  { x: 0.984375, y: 0.453125 },\n  { x: 0.015625, y: 0.484375 },\n  { x: 0.015625, y: 0.484375 },\n  { x: 0.046875, y: 0.484375 },\n  { x: 0.046875, y: 0.484375 },\n  { x: 0.078125, y: 0.484375 },\n  { x: 0.078125, y: 0.484375 },\n  { x: 0.109375, y: 0.484375 },\n  { x: 0.109375, y: 0.484375 },\n  { x: 0.140625, y: 0.484375 },\n  { x: 0.140625, y: 0.484375 },\n  { x: 0.171875, y: 0.484375 },\n  { x: 0.171875, y: 0.484375 },\n  { x: 0.203125, y: 0.484375 },\n  { x: 0.203125, y: 0.484375 },\n  { x: 0.234375, y: 0.484375 },\n  { x: 0.234375, y: 0.484375 },\n  { x: 0.265625, y: 0.484375 },\n  { x: 0.265625, y: 0.484375 },\n  { x: 0.296875, y: 0.484375 },\n  { x: 0.296875, y: 0.484375 },\n  { x: 0.328125, y: 0.484375 },\n  { x: 0.328125, y: 0.484375 },\n  { x: 0.359375, y: 0.484375 },\n  { x: 0.359375, y: 0.484375 },\n  { x: 0.390625, y: 0.484375 },\n  { x: 0.390625, y: 0.484375 },\n  { x: 0.421875, y: 0.484375 },\n  { x: 0.421875, y: 0.484375 },\n  { x: 0.453125, y: 0.484375 },\n  { x: 0.453125, y: 0.484375 },\n  { x: 0.484375, y: 0.484375 },\n  { x: 0.484375, y: 0.484375 },\n  { x: 0.515625, y: 0.484375 },\n  { x: 0.515625, y: 0.484375 },\n  { x: 0.546875, y: 0.484375 },\n  { x: 0.546875, y: 0.484375 },\n  { x: 0.578125, y: 0.484375 },\n  { x: 0.578125, y: 0.484375 },\n  { x: 0.609375, y: 0.484375 },\n  { x: 0.609375, y: 0.484375 },\n  { x: 0.640625, y: 0.484375 },\n  { x: 0.640625, y: 0.484375 },\n  { x: 0.671875, y: 0.484375 },\n  { x: 0.671875, y: 0.484375 },\n  { x: 0.703125, y: 0.484375 },\n  { x: 0.703125, y: 0.484375 },\n  { x: 0.734375, y: 0.484375 },\n  { x: 0.734375, y: 0.484375 },\n  { x: 0.765625, y: 0.484375 },\n  { x: 0.765625, y: 0.484375 },\n  { x: 0.796875, y: 0.484375 },\n  { x: 0.796875, y: 0.484375 },\n  { x: 0.828125, y: 0.484375 },\n  { x: 0.828125, y: 0.484375 },\n  { x: 0.859375, y: 0.484375 },\n  { x: 0.859375, y: 0.484375 },\n  { x: 0.890625, y: 0.484375 },\n  { x: 0.890625, y: 0.484375 },\n  { x: 0.921875, y: 0.484375 },\n  { x: 0.921875, y: 0.484375 },\n  { x: 0.953125, y: 0.484375 },\n  { x: 0.953125, y: 0.484375 },\n  { x: 0.984375, y: 0.484375 },\n  { x: 0.984375, y: 0.484375 },\n  { x: 0.015625, y: 0.515625 },\n  { x: 0.015625, y: 0.515625 },\n  { x: 0.046875, y: 0.515625 },\n  { x: 0.046875, y: 0.515625 },\n  { x: 0.078125, y: 0.515625 },\n  { x: 0.078125, y: 0.515625 },\n  { x: 0.109375, y: 0.515625 },\n  { x: 0.109375, y: 0.515625 },\n  { x: 0.140625, y: 0.515625 },\n  { x: 0.140625, y: 0.515625 },\n  { x: 0.171875, y: 0.515625 },\n  { x: 0.171875, y: 0.515625 },\n  { x: 0.203125, y: 0.515625 },\n  { x: 0.203125, y: 0.515625 },\n  { x: 0.234375, y: 0.515625 },\n  { x: 0.234375, y: 0.515625 },\n  { x: 0.265625, y: 0.515625 },\n  { x: 0.265625, y: 0.515625 },\n  { x: 0.296875, y: 0.515625 },\n  { x: 0.296875, y: 0.515625 },\n  { x: 0.328125, y: 0.515625 },\n  { x: 0.328125, y: 0.515625 },\n  { x: 0.359375, y: 0.515625 },\n  { x: 0.359375, y: 0.515625 },\n  { x: 0.390625, y: 0.515625 },\n  { x: 0.390625, y: 0.515625 },\n  { x: 0.421875, y: 0.515625 },\n  { x: 0.421875, y: 0.515625 },\n  { x: 0.453125, y: 0.515625 },\n  { x: 0.453125, y: 0.515625 },\n  { x: 0.484375, y: 0.515625 },\n  { x: 0.484375, y: 0.515625 },\n  { x: 0.515625, y: 0.515625 },\n  { x: 0.515625, y: 0.515625 },\n  { x: 0.546875, y: 0.515625 },\n  { x: 0.546875, y: 0.515625 },\n  { x: 0.578125, y: 0.515625 },\n  { x: 0.578125, y: 0.515625 },\n  { x: 0.609375, y: 0.515625 },\n  { x: 0.609375, y: 0.515625 },\n  { x: 0.640625, y: 0.515625 },\n  { x: 0.640625, y: 0.515625 },\n  { x: 0.671875, y: 0.515625 },\n  { x: 0.671875, y: 0.515625 },\n  { x: 0.703125, y: 0.515625 },\n  { x: 0.703125, y: 0.515625 },\n  { x: 0.734375, y: 0.515625 },\n  { x: 0.734375, y: 0.515625 },\n  { x: 0.765625, y: 0.515625 },\n  { x: 0.765625, y: 0.515625 },\n  { x: 0.796875, y: 0.515625 },\n  { x: 0.796875, y: 0.515625 },\n  { x: 0.828125, y: 0.515625 },\n  { x: 0.828125, y: 0.515625 },\n  { x: 0.859375, y: 0.515625 },\n  { x: 0.859375, y: 0.515625 },\n  { x: 0.890625, y: 0.515625 },\n  { x: 0.890625, y: 0.515625 },\n  { x: 0.921875, y: 0.515625 },\n  { x: 0.921875, y: 0.515625 },\n  { x: 0.953125, y: 0.515625 },\n  { x: 0.953125, y: 0.515625 },\n  { x: 0.984375, y: 0.515625 },\n  { x: 0.984375, y: 0.515625 },\n  { x: 0.015625, y: 0.546875 },\n  { x: 0.015625, y: 0.546875 },\n  { x: 0.046875, y: 0.546875 },\n  { x: 0.046875, y: 0.546875 },\n  { x: 0.078125, y: 0.546875 },\n  { x: 0.078125, y: 0.546875 },\n  { x: 0.109375, y: 0.546875 },\n  { x: 0.109375, y: 0.546875 },\n  { x: 0.140625, y: 0.546875 },\n  { x: 0.140625, y: 0.546875 },\n  { x: 0.171875, y: 0.546875 },\n  { x: 0.171875, y: 0.546875 },\n  { x: 0.203125, y: 0.546875 },\n  { x: 0.203125, y: 0.546875 },\n  { x: 0.234375, y: 0.546875 },\n  { x: 0.234375, y: 0.546875 },\n  { x: 0.265625, y: 0.546875 },\n  { x: 0.265625, y: 0.546875 },\n  { x: 0.296875, y: 0.546875 },\n  { x: 0.296875, y: 0.546875 },\n  { x: 0.328125, y: 0.546875 },\n  { x: 0.328125, y: 0.546875 },\n  { x: 0.359375, y: 0.546875 },\n  { x: 0.359375, y: 0.546875 },\n  { x: 0.390625, y: 0.546875 },\n  { x: 0.390625, y: 0.546875 },\n  { x: 0.421875, y: 0.546875 },\n  { x: 0.421875, y: 0.546875 },\n  { x: 0.453125, y: 0.546875 },\n  { x: 0.453125, y: 0.546875 },\n  { x: 0.484375, y: 0.546875 },\n  { x: 0.484375, y: 0.546875 },\n  { x: 0.515625, y: 0.546875 },\n  { x: 0.515625, y: 0.546875 },\n  { x: 0.546875, y: 0.546875 },\n  { x: 0.546875, y: 0.546875 },\n  { x: 0.578125, y: 0.546875 },\n  { x: 0.578125, y: 0.546875 },\n  { x: 0.609375, y: 0.546875 },\n  { x: 0.609375, y: 0.546875 },\n  { x: 0.640625, y: 0.546875 },\n  { x: 0.640625, y: 0.546875 },\n  { x: 0.671875, y: 0.546875 },\n  { x: 0.671875, y: 0.546875 },\n  { x: 0.703125, y: 0.546875 },\n  { x: 0.703125, y: 0.546875 },\n  { x: 0.734375, y: 0.546875 },\n  { x: 0.734375, y: 0.546875 },\n  { x: 0.765625, y: 0.546875 },\n  { x: 0.765625, y: 0.546875 },\n  { x: 0.796875, y: 0.546875 },\n  { x: 0.796875, y: 0.546875 },\n  { x: 0.828125, y: 0.546875 },\n  { x: 0.828125, y: 0.546875 },\n  { x: 0.859375, y: 0.546875 },\n  { x: 0.859375, y: 0.546875 },\n  { x: 0.890625, y: 0.546875 },\n  { x: 0.890625, y: 0.546875 },\n  { x: 0.921875, y: 0.546875 },\n  { x: 0.921875, y: 0.546875 },\n  { x: 0.953125, y: 0.546875 },\n  { x: 0.953125, y: 0.546875 },\n  { x: 0.984375, y: 0.546875 },\n  { x: 0.984375, y: 0.546875 },\n  { x: 0.015625, y: 0.578125 },\n  { x: 0.015625, y: 0.578125 },\n  { x: 0.046875, y: 0.578125 },\n  { x: 0.046875, y: 0.578125 },\n  { x: 0.078125, y: 0.578125 },\n  { x: 0.078125, y: 0.578125 },\n  { x: 0.109375, y: 0.578125 },\n  { x: 0.109375, y: 0.578125 },\n  { x: 0.140625, y: 0.578125 },\n  { x: 0.140625, y: 0.578125 },\n  { x: 0.171875, y: 0.578125 },\n  { x: 0.171875, y: 0.578125 },\n  { x: 0.203125, y: 0.578125 },\n  { x: 0.203125, y: 0.578125 },\n  { x: 0.234375, y: 0.578125 },\n  { x: 0.234375, y: 0.578125 },\n  { x: 0.265625, y: 0.578125 },\n  { x: 0.265625, y: 0.578125 },\n  { x: 0.296875, y: 0.578125 },\n  { x: 0.296875, y: 0.578125 },\n  { x: 0.328125, y: 0.578125 },\n  { x: 0.328125, y: 0.578125 },\n  { x: 0.359375, y: 0.578125 },\n  { x: 0.359375, y: 0.578125 },\n  { x: 0.390625, y: 0.578125 },\n  { x: 0.390625, y: 0.578125 },\n  { x: 0.421875, y: 0.578125 },\n  { x: 0.421875, y: 0.578125 },\n  { x: 0.453125, y: 0.578125 },\n  { x: 0.453125, y: 0.578125 },\n  { x: 0.484375, y: 0.578125 },\n  { x: 0.484375, y: 0.578125 },\n  { x: 0.515625, y: 0.578125 },\n  { x: 0.515625, y: 0.578125 },\n  { x: 0.546875, y: 0.578125 },\n  { x: 0.546875, y: 0.578125 },\n  { x: 0.578125, y: 0.578125 },\n  { x: 0.578125, y: 0.578125 },\n  { x: 0.609375, y: 0.578125 },\n  { x: 0.609375, y: 0.578125 },\n  { x: 0.640625, y: 0.578125 },\n  { x: 0.640625, y: 0.578125 },\n  { x: 0.671875, y: 0.578125 },\n  { x: 0.671875, y: 0.578125 },\n  { x: 0.703125, y: 0.578125 },\n  { x: 0.703125, y: 0.578125 },\n  { x: 0.734375, y: 0.578125 },\n  { x: 0.734375, y: 0.578125 },\n  { x: 0.765625, y: 0.578125 },\n  { x: 0.765625, y: 0.578125 },\n  { x: 0.796875, y: 0.578125 },\n  { x: 0.796875, y: 0.578125 },\n  { x: 0.828125, y: 0.578125 },\n  { x: 0.828125, y: 0.578125 },\n  { x: 0.859375, y: 0.578125 },\n  { x: 0.859375, y: 0.578125 },\n  { x: 0.890625, y: 0.578125 },\n  { x: 0.890625, y: 0.578125 },\n  { x: 0.921875, y: 0.578125 },\n  { x: 0.921875, y: 0.578125 },\n  { x: 0.953125, y: 0.578125 },\n  { x: 0.953125, y: 0.578125 },\n  { x: 0.984375, y: 0.578125 },\n  { x: 0.984375, y: 0.578125 },\n  { x: 0.015625, y: 0.609375 },\n  { x: 0.015625, y: 0.609375 },\n  { x: 0.046875, y: 0.609375 },\n  { x: 0.046875, y: 0.609375 },\n  { x: 0.078125, y: 0.609375 },\n  { x: 0.078125, y: 0.609375 },\n  { x: 0.109375, y: 0.609375 },\n  { x: 0.109375, y: 0.609375 },\n  { x: 0.140625, y: 0.609375 },\n  { x: 0.140625, y: 0.609375 },\n  { x: 0.171875, y: 0.609375 },\n  { x: 0.171875, y: 0.609375 },\n  { x: 0.203125, y: 0.609375 },\n  { x: 0.203125, y: 0.609375 },\n  { x: 0.234375, y: 0.609375 },\n  { x: 0.234375, y: 0.609375 },\n  { x: 0.265625, y: 0.609375 },\n  { x: 0.265625, y: 0.609375 },\n  { x: 0.296875, y: 0.609375 },\n  { x: 0.296875, y: 0.609375 },\n  { x: 0.328125, y: 0.609375 },\n  { x: 0.328125, y: 0.609375 },\n  { x: 0.359375, y: 0.609375 },\n  { x: 0.359375, y: 0.609375 },\n  { x: 0.390625, y: 0.609375 },\n  { x: 0.390625, y: 0.609375 },\n  { x: 0.421875, y: 0.609375 },\n  { x: 0.421875, y: 0.609375 },\n  { x: 0.453125, y: 0.609375 },\n  { x: 0.453125, y: 0.609375 },\n  { x: 0.484375, y: 0.609375 },\n  { x: 0.484375, y: 0.609375 },\n  { x: 0.515625, y: 0.609375 },\n  { x: 0.515625, y: 0.609375 },\n  { x: 0.546875, y: 0.609375 },\n  { x: 0.546875, y: 0.609375 },\n  { x: 0.578125, y: 0.609375 },\n  { x: 0.578125, y: 0.609375 },\n  { x: 0.609375, y: 0.609375 },\n  { x: 0.609375, y: 0.609375 },\n  { x: 0.640625, y: 0.609375 },\n  { x: 0.640625, y: 0.609375 },\n  { x: 0.671875, y: 0.609375 },\n  { x: 0.671875, y: 0.609375 },\n  { x: 0.703125, y: 0.609375 },\n  { x: 0.703125, y: 0.609375 },\n  { x: 0.734375, y: 0.609375 },\n  { x: 0.734375, y: 0.609375 },\n  { x: 0.765625, y: 0.609375 },\n  { x: 0.765625, y: 0.609375 },\n  { x: 0.796875, y: 0.609375 },\n  { x: 0.796875, y: 0.609375 },\n  { x: 0.828125, y: 0.609375 },\n  { x: 0.828125, y: 0.609375 },\n  { x: 0.859375, y: 0.609375 },\n  { x: 0.859375, y: 0.609375 },\n  { x: 0.890625, y: 0.609375 },\n  { x: 0.890625, y: 0.609375 },\n  { x: 0.921875, y: 0.609375 },\n  { x: 0.921875, y: 0.609375 },\n  { x: 0.953125, y: 0.609375 },\n  { x: 0.953125, y: 0.609375 },\n  { x: 0.984375, y: 0.609375 },\n  { x: 0.984375, y: 0.609375 },\n  { x: 0.015625, y: 0.640625 },\n  { x: 0.015625, y: 0.640625 },\n  { x: 0.046875, y: 0.640625 },\n  { x: 0.046875, y: 0.640625 },\n  { x: 0.078125, y: 0.640625 },\n  { x: 0.078125, y: 0.640625 },\n  { x: 0.109375, y: 0.640625 },\n  { x: 0.109375, y: 0.640625 },\n  { x: 0.140625, y: 0.640625 },\n  { x: 0.140625, y: 0.640625 },\n  { x: 0.171875, y: 0.640625 },\n  { x: 0.171875, y: 0.640625 },\n  { x: 0.203125, y: 0.640625 },\n  { x: 0.203125, y: 0.640625 },\n  { x: 0.234375, y: 0.640625 },\n  { x: 0.234375, y: 0.640625 },\n  { x: 0.265625, y: 0.640625 },\n  { x: 0.265625, y: 0.640625 },\n  { x: 0.296875, y: 0.640625 },\n  { x: 0.296875, y: 0.640625 },\n  { x: 0.328125, y: 0.640625 },\n  { x: 0.328125, y: 0.640625 },\n  { x: 0.359375, y: 0.640625 },\n  { x: 0.359375, y: 0.640625 },\n  { x: 0.390625, y: 0.640625 },\n  { x: 0.390625, y: 0.640625 },\n  { x: 0.421875, y: 0.640625 },\n  { x: 0.421875, y: 0.640625 },\n  { x: 0.453125, y: 0.640625 },\n  { x: 0.453125, y: 0.640625 },\n  { x: 0.484375, y: 0.640625 },\n  { x: 0.484375, y: 0.640625 },\n  { x: 0.515625, y: 0.640625 },\n  { x: 0.515625, y: 0.640625 },\n  { x: 0.546875, y: 0.640625 },\n  { x: 0.546875, y: 0.640625 },\n  { x: 0.578125, y: 0.640625 },\n  { x: 0.578125, y: 0.640625 },\n  { x: 0.609375, y: 0.640625 },\n  { x: 0.609375, y: 0.640625 },\n  { x: 0.640625, y: 0.640625 },\n  { x: 0.640625, y: 0.640625 },\n  { x: 0.671875, y: 0.640625 },\n  { x: 0.671875, y: 0.640625 },\n  { x: 0.703125, y: 0.640625 },\n  { x: 0.703125, y: 0.640625 },\n  { x: 0.734375, y: 0.640625 },\n  { x: 0.734375, y: 0.640625 },\n  { x: 0.765625, y: 0.640625 },\n  { x: 0.765625, y: 0.640625 },\n  { x: 0.796875, y: 0.640625 },\n  { x: 0.796875, y: 0.640625 },\n  { x: 0.828125, y: 0.640625 },\n  { x: 0.828125, y: 0.640625 },\n  { x: 0.859375, y: 0.640625 },\n  { x: 0.859375, y: 0.640625 },\n  { x: 0.890625, y: 0.640625 },\n  { x: 0.890625, y: 0.640625 },\n  { x: 0.921875, y: 0.640625 },\n  { x: 0.921875, y: 0.640625 },\n  { x: 0.953125, y: 0.640625 },\n  { x: 0.953125, y: 0.640625 },\n  { x: 0.984375, y: 0.640625 },\n  { x: 0.984375, y: 0.640625 },\n  { x: 0.015625, y: 0.671875 },\n  { x: 0.015625, y: 0.671875 },\n  { x: 0.046875, y: 0.671875 },\n  { x: 0.046875, y: 0.671875 },\n  { x: 0.078125, y: 0.671875 },\n  { x: 0.078125, y: 0.671875 },\n  { x: 0.109375, y: 0.671875 },\n  { x: 0.109375, y: 0.671875 },\n  { x: 0.140625, y: 0.671875 },\n  { x: 0.140625, y: 0.671875 },\n  { x: 0.171875, y: 0.671875 },\n  { x: 0.171875, y: 0.671875 },\n  { x: 0.203125, y: 0.671875 },\n  { x: 0.203125, y: 0.671875 },\n  { x: 0.234375, y: 0.671875 },\n  { x: 0.234375, y: 0.671875 },\n  { x: 0.265625, y: 0.671875 },\n  { x: 0.265625, y: 0.671875 },\n  { x: 0.296875, y: 0.671875 },\n  { x: 0.296875, y: 0.671875 },\n  { x: 0.328125, y: 0.671875 },\n  { x: 0.328125, y: 0.671875 },\n  { x: 0.359375, y: 0.671875 },\n  { x: 0.359375, y: 0.671875 },\n  { x: 0.390625, y: 0.671875 },\n  { x: 0.390625, y: 0.671875 },\n  { x: 0.421875, y: 0.671875 },\n  { x: 0.421875, y: 0.671875 },\n  { x: 0.453125, y: 0.671875 },\n  { x: 0.453125, y: 0.671875 },\n  { x: 0.484375, y: 0.671875 },\n  { x: 0.484375, y: 0.671875 },\n  { x: 0.515625, y: 0.671875 },\n  { x: 0.515625, y: 0.671875 },\n  { x: 0.546875, y: 0.671875 },\n  { x: 0.546875, y: 0.671875 },\n  { x: 0.578125, y: 0.671875 },\n  { x: 0.578125, y: 0.671875 },\n  { x: 0.609375, y: 0.671875 },\n  { x: 0.609375, y: 0.671875 },\n  { x: 0.640625, y: 0.671875 },\n  { x: 0.640625, y: 0.671875 },\n  { x: 0.671875, y: 0.671875 },\n  { x: 0.671875, y: 0.671875 },\n  { x: 0.703125, y: 0.671875 },\n  { x: 0.703125, y: 0.671875 },\n  { x: 0.734375, y: 0.671875 },\n  { x: 0.734375, y: 0.671875 },\n  { x: 0.765625, y: 0.671875 },\n  { x: 0.765625, y: 0.671875 },\n  { x: 0.796875, y: 0.671875 },\n  { x: 0.796875, y: 0.671875 },\n  { x: 0.828125, y: 0.671875 },\n  { x: 0.828125, y: 0.671875 },\n  { x: 0.859375, y: 0.671875 },\n  { x: 0.859375, y: 0.671875 },\n  { x: 0.890625, y: 0.671875 },\n  { x: 0.890625, y: 0.671875 },\n  { x: 0.921875, y: 0.671875 },\n  { x: 0.921875, y: 0.671875 },\n  { x: 0.953125, y: 0.671875 },\n  { x: 0.953125, y: 0.671875 },\n  { x: 0.984375, y: 0.671875 },\n  { x: 0.984375, y: 0.671875 },\n  { x: 0.015625, y: 0.703125 },\n  { x: 0.015625, y: 0.703125 },\n  { x: 0.046875, y: 0.703125 },\n  { x: 0.046875, y: 0.703125 },\n  { x: 0.078125, y: 0.703125 },\n  { x: 0.078125, y: 0.703125 },\n  { x: 0.109375, y: 0.703125 },\n  { x: 0.109375, y: 0.703125 },\n  { x: 0.140625, y: 0.703125 },\n  { x: 0.140625, y: 0.703125 },\n  { x: 0.171875, y: 0.703125 },\n  { x: 0.171875, y: 0.703125 },\n  { x: 0.203125, y: 0.703125 },\n  { x: 0.203125, y: 0.703125 },\n  { x: 0.234375, y: 0.703125 },\n  { x: 0.234375, y: 0.703125 },\n  { x: 0.265625, y: 0.703125 },\n  { x: 0.265625, y: 0.703125 },\n  { x: 0.296875, y: 0.703125 },\n  { x: 0.296875, y: 0.703125 },\n  { x: 0.328125, y: 0.703125 },\n  { x: 0.328125, y: 0.703125 },\n  { x: 0.359375, y: 0.703125 },\n  { x: 0.359375, y: 0.703125 },\n  { x: 0.390625, y: 0.703125 },\n  { x: 0.390625, y: 0.703125 },\n  { x: 0.421875, y: 0.703125 },\n  { x: 0.421875, y: 0.703125 },\n  { x: 0.453125, y: 0.703125 },\n  { x: 0.453125, y: 0.703125 },\n  { x: 0.484375, y: 0.703125 },\n  { x: 0.484375, y: 0.703125 },\n  { x: 0.515625, y: 0.703125 },\n  { x: 0.515625, y: 0.703125 },\n  { x: 0.546875, y: 0.703125 },\n  { x: 0.546875, y: 0.703125 },\n  { x: 0.578125, y: 0.703125 },\n  { x: 0.578125, y: 0.703125 },\n  { x: 0.609375, y: 0.703125 },\n  { x: 0.609375, y: 0.703125 },\n  { x: 0.640625, y: 0.703125 },\n  { x: 0.640625, y: 0.703125 },\n  { x: 0.671875, y: 0.703125 },\n  { x: 0.671875, y: 0.703125 },\n  { x: 0.703125, y: 0.703125 },\n  { x: 0.703125, y: 0.703125 },\n  { x: 0.734375, y: 0.703125 },\n  { x: 0.734375, y: 0.703125 },\n  { x: 0.765625, y: 0.703125 },\n  { x: 0.765625, y: 0.703125 },\n  { x: 0.796875, y: 0.703125 },\n  { x: 0.796875, y: 0.703125 },\n  { x: 0.828125, y: 0.703125 },\n  { x: 0.828125, y: 0.703125 },\n  { x: 0.859375, y: 0.703125 },\n  { x: 0.859375, y: 0.703125 },\n  { x: 0.890625, y: 0.703125 },\n  { x: 0.890625, y: 0.703125 },\n  { x: 0.921875, y: 0.703125 },\n  { x: 0.921875, y: 0.703125 },\n  { x: 0.953125, y: 0.703125 },\n  { x: 0.953125, y: 0.703125 },\n  { x: 0.984375, y: 0.703125 },\n  { x: 0.984375, y: 0.703125 },\n  { x: 0.015625, y: 0.734375 },\n  { x: 0.015625, y: 0.734375 },\n  { x: 0.046875, y: 0.734375 },\n  { x: 0.046875, y: 0.734375 },\n  { x: 0.078125, y: 0.734375 },\n  { x: 0.078125, y: 0.734375 },\n  { x: 0.109375, y: 0.734375 },\n  { x: 0.109375, y: 0.734375 },\n  { x: 0.140625, y: 0.734375 },\n  { x: 0.140625, y: 0.734375 },\n  { x: 0.171875, y: 0.734375 },\n  { x: 0.171875, y: 0.734375 },\n  { x: 0.203125, y: 0.734375 },\n  { x: 0.203125, y: 0.734375 },\n  { x: 0.234375, y: 0.734375 },\n  { x: 0.234375, y: 0.734375 },\n  { x: 0.265625, y: 0.734375 },\n  { x: 0.265625, y: 0.734375 },\n  { x: 0.296875, y: 0.734375 },\n  { x: 0.296875, y: 0.734375 },\n  { x: 0.328125, y: 0.734375 },\n  { x: 0.328125, y: 0.734375 },\n  { x: 0.359375, y: 0.734375 },\n  { x: 0.359375, y: 0.734375 },\n  { x: 0.390625, y: 0.734375 },\n  { x: 0.390625, y: 0.734375 },\n  { x: 0.421875, y: 0.734375 },\n  { x: 0.421875, y: 0.734375 },\n  { x: 0.453125, y: 0.734375 },\n  { x: 0.453125, y: 0.734375 },\n  { x: 0.484375, y: 0.734375 },\n  { x: 0.484375, y: 0.734375 },\n  { x: 0.515625, y: 0.734375 },\n  { x: 0.515625, y: 0.734375 },\n  { x: 0.546875, y: 0.734375 },\n  { x: 0.546875, y: 0.734375 },\n  { x: 0.578125, y: 0.734375 },\n  { x: 0.578125, y: 0.734375 },\n  { x: 0.609375, y: 0.734375 },\n  { x: 0.609375, y: 0.734375 },\n  { x: 0.640625, y: 0.734375 },\n  { x: 0.640625, y: 0.734375 },\n  { x: 0.671875, y: 0.734375 },\n  { x: 0.671875, y: 0.734375 },\n  { x: 0.703125, y: 0.734375 },\n  { x: 0.703125, y: 0.734375 },\n  { x: 0.734375, y: 0.734375 },\n  { x: 0.734375, y: 0.734375 },\n  { x: 0.765625, y: 0.734375 },\n  { x: 0.765625, y: 0.734375 },\n  { x: 0.796875, y: 0.734375 },\n  { x: 0.796875, y: 0.734375 },\n  { x: 0.828125, y: 0.734375 },\n  { x: 0.828125, y: 0.734375 },\n  { x: 0.859375, y: 0.734375 },\n  { x: 0.859375, y: 0.734375 },\n  { x: 0.890625, y: 0.734375 },\n  { x: 0.890625, y: 0.734375 },\n  { x: 0.921875, y: 0.734375 },\n  { x: 0.921875, y: 0.734375 },\n  { x: 0.953125, y: 0.734375 },\n  { x: 0.953125, y: 0.734375 },\n  { x: 0.984375, y: 0.734375 },\n  { x: 0.984375, y: 0.734375 },\n  { x: 0.015625, y: 0.765625 },\n  { x: 0.015625, y: 0.765625 },\n  { x: 0.046875, y: 0.765625 },\n  { x: 0.046875, y: 0.765625 },\n  { x: 0.078125, y: 0.765625 },\n  { x: 0.078125, y: 0.765625 },\n  { x: 0.109375, y: 0.765625 },\n  { x: 0.109375, y: 0.765625 },\n  { x: 0.140625, y: 0.765625 },\n  { x: 0.140625, y: 0.765625 },\n  { x: 0.171875, y: 0.765625 },\n  { x: 0.171875, y: 0.765625 },\n  { x: 0.203125, y: 0.765625 },\n  { x: 0.203125, y: 0.765625 },\n  { x: 0.234375, y: 0.765625 },\n  { x: 0.234375, y: 0.765625 },\n  { x: 0.265625, y: 0.765625 },\n  { x: 0.265625, y: 0.765625 },\n  { x: 0.296875, y: 0.765625 },\n  { x: 0.296875, y: 0.765625 },\n  { x: 0.328125, y: 0.765625 },\n  { x: 0.328125, y: 0.765625 },\n  { x: 0.359375, y: 0.765625 },\n  { x: 0.359375, y: 0.765625 },\n  { x: 0.390625, y: 0.765625 },\n  { x: 0.390625, y: 0.765625 },\n  { x: 0.421875, y: 0.765625 },\n  { x: 0.421875, y: 0.765625 },\n  { x: 0.453125, y: 0.765625 },\n  { x: 0.453125, y: 0.765625 },\n  { x: 0.484375, y: 0.765625 },\n  { x: 0.484375, y: 0.765625 },\n  { x: 0.515625, y: 0.765625 },\n  { x: 0.515625, y: 0.765625 },\n  { x: 0.546875, y: 0.765625 },\n  { x: 0.546875, y: 0.765625 },\n  { x: 0.578125, y: 0.765625 },\n  { x: 0.578125, y: 0.765625 },\n  { x: 0.609375, y: 0.765625 },\n  { x: 0.609375, y: 0.765625 },\n  { x: 0.640625, y: 0.765625 },\n  { x: 0.640625, y: 0.765625 },\n  { x: 0.671875, y: 0.765625 },\n  { x: 0.671875, y: 0.765625 },\n  { x: 0.703125, y: 0.765625 },\n  { x: 0.703125, y: 0.765625 },\n  { x: 0.734375, y: 0.765625 },\n  { x: 0.734375, y: 0.765625 },\n  { x: 0.765625, y: 0.765625 },\n  { x: 0.765625, y: 0.765625 },\n  { x: 0.796875, y: 0.765625 },\n  { x: 0.796875, y: 0.765625 },\n  { x: 0.828125, y: 0.765625 },\n  { x: 0.828125, y: 0.765625 },\n  { x: 0.859375, y: 0.765625 },\n  { x: 0.859375, y: 0.765625 },\n  { x: 0.890625, y: 0.765625 },\n  { x: 0.890625, y: 0.765625 },\n  { x: 0.921875, y: 0.765625 },\n  { x: 0.921875, y: 0.765625 },\n  { x: 0.953125, y: 0.765625 },\n  { x: 0.953125, y: 0.765625 },\n  { x: 0.984375, y: 0.765625 },\n  { x: 0.984375, y: 0.765625 },\n  { x: 0.015625, y: 0.796875 },\n  { x: 0.015625, y: 0.796875 },\n  { x: 0.046875, y: 0.796875 },\n  { x: 0.046875, y: 0.796875 },\n  { x: 0.078125, y: 0.796875 },\n  { x: 0.078125, y: 0.796875 },\n  { x: 0.109375, y: 0.796875 },\n  { x: 0.109375, y: 0.796875 },\n  { x: 0.140625, y: 0.796875 },\n  { x: 0.140625, y: 0.796875 },\n  { x: 0.171875, y: 0.796875 },\n  { x: 0.171875, y: 0.796875 },\n  { x: 0.203125, y: 0.796875 },\n  { x: 0.203125, y: 0.796875 },\n  { x: 0.234375, y: 0.796875 },\n  { x: 0.234375, y: 0.796875 },\n  { x: 0.265625, y: 0.796875 },\n  { x: 0.265625, y: 0.796875 },\n  { x: 0.296875, y: 0.796875 },\n  { x: 0.296875, y: 0.796875 },\n  { x: 0.328125, y: 0.796875 },\n  { x: 0.328125, y: 0.796875 },\n  { x: 0.359375, y: 0.796875 },\n  { x: 0.359375, y: 0.796875 },\n  { x: 0.390625, y: 0.796875 },\n  { x: 0.390625, y: 0.796875 },\n  { x: 0.421875, y: 0.796875 },\n  { x: 0.421875, y: 0.796875 },\n  { x: 0.453125, y: 0.796875 },\n  { x: 0.453125, y: 0.796875 },\n  { x: 0.484375, y: 0.796875 },\n  { x: 0.484375, y: 0.796875 },\n  { x: 0.515625, y: 0.796875 },\n  { x: 0.515625, y: 0.796875 },\n  { x: 0.546875, y: 0.796875 },\n  { x: 0.546875, y: 0.796875 },\n  { x: 0.578125, y: 0.796875 },\n  { x: 0.578125, y: 0.796875 },\n  { x: 0.609375, y: 0.796875 },\n  { x: 0.609375, y: 0.796875 },\n  { x: 0.640625, y: 0.796875 },\n  { x: 0.640625, y: 0.796875 },\n  { x: 0.671875, y: 0.796875 },\n  { x: 0.671875, y: 0.796875 },\n  { x: 0.703125, y: 0.796875 },\n  { x: 0.703125, y: 0.796875 },\n  { x: 0.734375, y: 0.796875 },\n  { x: 0.734375, y: 0.796875 },\n  { x: 0.765625, y: 0.796875 },\n  { x: 0.765625, y: 0.796875 },\n  { x: 0.796875, y: 0.796875 },\n  { x: 0.796875, y: 0.796875 },\n  { x: 0.828125, y: 0.796875 },\n  { x: 0.828125, y: 0.796875 },\n  { x: 0.859375, y: 0.796875 },\n  { x: 0.859375, y: 0.796875 },\n  { x: 0.890625, y: 0.796875 },\n  { x: 0.890625, y: 0.796875 },\n  { x: 0.921875, y: 0.796875 },\n  { x: 0.921875, y: 0.796875 },\n  { x: 0.953125, y: 0.796875 },\n  { x: 0.953125, y: 0.796875 },\n  { x: 0.984375, y: 0.796875 },\n  { x: 0.984375, y: 0.796875 },\n  { x: 0.015625, y: 0.828125 },\n  { x: 0.015625, y: 0.828125 },\n  { x: 0.046875, y: 0.828125 },\n  { x: 0.046875, y: 0.828125 },\n  { x: 0.078125, y: 0.828125 },\n  { x: 0.078125, y: 0.828125 },\n  { x: 0.109375, y: 0.828125 },\n  { x: 0.109375, y: 0.828125 },\n  { x: 0.140625, y: 0.828125 },\n  { x: 0.140625, y: 0.828125 },\n  { x: 0.171875, y: 0.828125 },\n  { x: 0.171875, y: 0.828125 },\n  { x: 0.203125, y: 0.828125 },\n  { x: 0.203125, y: 0.828125 },\n  { x: 0.234375, y: 0.828125 },\n  { x: 0.234375, y: 0.828125 },\n  { x: 0.265625, y: 0.828125 },\n  { x: 0.265625, y: 0.828125 },\n  { x: 0.296875, y: 0.828125 },\n  { x: 0.296875, y: 0.828125 },\n  { x: 0.328125, y: 0.828125 },\n  { x: 0.328125, y: 0.828125 },\n  { x: 0.359375, y: 0.828125 },\n  { x: 0.359375, y: 0.828125 },\n  { x: 0.390625, y: 0.828125 },\n  { x: 0.390625, y: 0.828125 },\n  { x: 0.421875, y: 0.828125 },\n  { x: 0.421875, y: 0.828125 },\n  { x: 0.453125, y: 0.828125 },\n  { x: 0.453125, y: 0.828125 },\n  { x: 0.484375, y: 0.828125 },\n  { x: 0.484375, y: 0.828125 },\n  { x: 0.515625, y: 0.828125 },\n  { x: 0.515625, y: 0.828125 },\n  { x: 0.546875, y: 0.828125 },\n  { x: 0.546875, y: 0.828125 },\n  { x: 0.578125, y: 0.828125 },\n  { x: 0.578125, y: 0.828125 },\n  { x: 0.609375, y: 0.828125 },\n  { x: 0.609375, y: 0.828125 },\n  { x: 0.640625, y: 0.828125 },\n  { x: 0.640625, y: 0.828125 },\n  { x: 0.671875, y: 0.828125 },\n  { x: 0.671875, y: 0.828125 },\n  { x: 0.703125, y: 0.828125 },\n  { x: 0.703125, y: 0.828125 },\n  { x: 0.734375, y: 0.828125 },\n  { x: 0.734375, y: 0.828125 },\n  { x: 0.765625, y: 0.828125 },\n  { x: 0.765625, y: 0.828125 },\n  { x: 0.796875, y: 0.828125 },\n  { x: 0.796875, y: 0.828125 },\n  { x: 0.828125, y: 0.828125 },\n  { x: 0.828125, y: 0.828125 },\n  { x: 0.859375, y: 0.828125 },\n  { x: 0.859375, y: 0.828125 },\n  { x: 0.890625, y: 0.828125 },\n  { x: 0.890625, y: 0.828125 },\n  { x: 0.921875, y: 0.828125 },\n  { x: 0.921875, y: 0.828125 },\n  { x: 0.953125, y: 0.828125 },\n  { x: 0.953125, y: 0.828125 },\n  { x: 0.984375, y: 0.828125 },\n  { x: 0.984375, y: 0.828125 },\n  { x: 0.015625, y: 0.859375 },\n  { x: 0.015625, y: 0.859375 },\n  { x: 0.046875, y: 0.859375 },\n  { x: 0.046875, y: 0.859375 },\n  { x: 0.078125, y: 0.859375 },\n  { x: 0.078125, y: 0.859375 },\n  { x: 0.109375, y: 0.859375 },\n  { x: 0.109375, y: 0.859375 },\n  { x: 0.140625, y: 0.859375 },\n  { x: 0.140625, y: 0.859375 },\n  { x: 0.171875, y: 0.859375 },\n  { x: 0.171875, y: 0.859375 },\n  { x: 0.203125, y: 0.859375 },\n  { x: 0.203125, y: 0.859375 },\n  { x: 0.234375, y: 0.859375 },\n  { x: 0.234375, y: 0.859375 },\n  { x: 0.265625, y: 0.859375 },\n  { x: 0.265625, y: 0.859375 },\n  { x: 0.296875, y: 0.859375 },\n  { x: 0.296875, y: 0.859375 },\n  { x: 0.328125, y: 0.859375 },\n  { x: 0.328125, y: 0.859375 },\n  { x: 0.359375, y: 0.859375 },\n  { x: 0.359375, y: 0.859375 },\n  { x: 0.390625, y: 0.859375 },\n  { x: 0.390625, y: 0.859375 },\n  { x: 0.421875, y: 0.859375 },\n  { x: 0.421875, y: 0.859375 },\n  { x: 0.453125, y: 0.859375 },\n  { x: 0.453125, y: 0.859375 },\n  { x: 0.484375, y: 0.859375 },\n  { x: 0.484375, y: 0.859375 },\n  { x: 0.515625, y: 0.859375 },\n  { x: 0.515625, y: 0.859375 },\n  { x: 0.546875, y: 0.859375 },\n  { x: 0.546875, y: 0.859375 },\n  { x: 0.578125, y: 0.859375 },\n  { x: 0.578125, y: 0.859375 },\n  { x: 0.609375, y: 0.859375 },\n  { x: 0.609375, y: 0.859375 },\n  { x: 0.640625, y: 0.859375 },\n  { x: 0.640625, y: 0.859375 },\n  { x: 0.671875, y: 0.859375 },\n  { x: 0.671875, y: 0.859375 },\n  { x: 0.703125, y: 0.859375 },\n  { x: 0.703125, y: 0.859375 },\n  { x: 0.734375, y: 0.859375 },\n  { x: 0.734375, y: 0.859375 },\n  { x: 0.765625, y: 0.859375 },\n  { x: 0.765625, y: 0.859375 },\n  { x: 0.796875, y: 0.859375 },\n  { x: 0.796875, y: 0.859375 },\n  { x: 0.828125, y: 0.859375 },\n  { x: 0.828125, y: 0.859375 },\n  { x: 0.859375, y: 0.859375 },\n  { x: 0.859375, y: 0.859375 },\n  { x: 0.890625, y: 0.859375 },\n  { x: 0.890625, y: 0.859375 },\n  { x: 0.921875, y: 0.859375 },\n  { x: 0.921875, y: 0.859375 },\n  { x: 0.953125, y: 0.859375 },\n  { x: 0.953125, y: 0.859375 },\n  { x: 0.984375, y: 0.859375 },\n  { x: 0.984375, y: 0.859375 },\n  { x: 0.015625, y: 0.890625 },\n  { x: 0.015625, y: 0.890625 },\n  { x: 0.046875, y: 0.890625 },\n  { x: 0.046875, y: 0.890625 },\n  { x: 0.078125, y: 0.890625 },\n  { x: 0.078125, y: 0.890625 },\n  { x: 0.109375, y: 0.890625 },\n  { x: 0.109375, y: 0.890625 },\n  { x: 0.140625, y: 0.890625 },\n  { x: 0.140625, y: 0.890625 },\n  { x: 0.171875, y: 0.890625 },\n  { x: 0.171875, y: 0.890625 },\n  { x: 0.203125, y: 0.890625 },\n  { x: 0.203125, y: 0.890625 },\n  { x: 0.234375, y: 0.890625 },\n  { x: 0.234375, y: 0.890625 },\n  { x: 0.265625, y: 0.890625 },\n  { x: 0.265625, y: 0.890625 },\n  { x: 0.296875, y: 0.890625 },\n  { x: 0.296875, y: 0.890625 },\n  { x: 0.328125, y: 0.890625 },\n  { x: 0.328125, y: 0.890625 },\n  { x: 0.359375, y: 0.890625 },\n  { x: 0.359375, y: 0.890625 },\n  { x: 0.390625, y: 0.890625 },\n  { x: 0.390625, y: 0.890625 },\n  { x: 0.421875, y: 0.890625 },\n  { x: 0.421875, y: 0.890625 },\n  { x: 0.453125, y: 0.890625 },\n  { x: 0.453125, y: 0.890625 },\n  { x: 0.484375, y: 0.890625 },\n  { x: 0.484375, y: 0.890625 },\n  { x: 0.515625, y: 0.890625 },\n  { x: 0.515625, y: 0.890625 },\n  { x: 0.546875, y: 0.890625 },\n  { x: 0.546875, y: 0.890625 },\n  { x: 0.578125, y: 0.890625 },\n  { x: 0.578125, y: 0.890625 },\n  { x: 0.609375, y: 0.890625 },\n  { x: 0.609375, y: 0.890625 },\n  { x: 0.640625, y: 0.890625 },\n  { x: 0.640625, y: 0.890625 },\n  { x: 0.671875, y: 0.890625 },\n  { x: 0.671875, y: 0.890625 },\n  { x: 0.703125, y: 0.890625 },\n  { x: 0.703125, y: 0.890625 },\n  { x: 0.734375, y: 0.890625 },\n  { x: 0.734375, y: 0.890625 },\n  { x: 0.765625, y: 0.890625 },\n  { x: 0.765625, y: 0.890625 },\n  { x: 0.796875, y: 0.890625 },\n  { x: 0.796875, y: 0.890625 },\n  { x: 0.828125, y: 0.890625 },\n  { x: 0.828125, y: 0.890625 },\n  { x: 0.859375, y: 0.890625 },\n  { x: 0.859375, y: 0.890625 },\n  { x: 0.890625, y: 0.890625 },\n  { x: 0.890625, y: 0.890625 },\n  { x: 0.921875, y: 0.890625 },\n  { x: 0.921875, y: 0.890625 },\n  { x: 0.953125, y: 0.890625 },\n  { x: 0.953125, y: 0.890625 },\n  { x: 0.984375, y: 0.890625 },\n  { x: 0.984375, y: 0.890625 },\n  { x: 0.015625, y: 0.921875 },\n  { x: 0.015625, y: 0.921875 },\n  { x: 0.046875, y: 0.921875 },\n  { x: 0.046875, y: 0.921875 },\n  { x: 0.078125, y: 0.921875 },\n  { x: 0.078125, y: 0.921875 },\n  { x: 0.109375, y: 0.921875 },\n  { x: 0.109375, y: 0.921875 },\n  { x: 0.140625, y: 0.921875 },\n  { x: 0.140625, y: 0.921875 },\n  { x: 0.171875, y: 0.921875 },\n  { x: 0.171875, y: 0.921875 },\n  { x: 0.203125, y: 0.921875 },\n  { x: 0.203125, y: 0.921875 },\n  { x: 0.234375, y: 0.921875 },\n  { x: 0.234375, y: 0.921875 },\n  { x: 0.265625, y: 0.921875 },\n  { x: 0.265625, y: 0.921875 },\n  { x: 0.296875, y: 0.921875 },\n  { x: 0.296875, y: 0.921875 },\n  { x: 0.328125, y: 0.921875 },\n  { x: 0.328125, y: 0.921875 },\n  { x: 0.359375, y: 0.921875 },\n  { x: 0.359375, y: 0.921875 },\n  { x: 0.390625, y: 0.921875 },\n  { x: 0.390625, y: 0.921875 },\n  { x: 0.421875, y: 0.921875 },\n  { x: 0.421875, y: 0.921875 },\n  { x: 0.453125, y: 0.921875 },\n  { x: 0.453125, y: 0.921875 },\n  { x: 0.484375, y: 0.921875 },\n  { x: 0.484375, y: 0.921875 },\n  { x: 0.515625, y: 0.921875 },\n  { x: 0.515625, y: 0.921875 },\n  { x: 0.546875, y: 0.921875 },\n  { x: 0.546875, y: 0.921875 },\n  { x: 0.578125, y: 0.921875 },\n  { x: 0.578125, y: 0.921875 },\n  { x: 0.609375, y: 0.921875 },\n  { x: 0.609375, y: 0.921875 },\n  { x: 0.640625, y: 0.921875 },\n  { x: 0.640625, y: 0.921875 },\n  { x: 0.671875, y: 0.921875 },\n  { x: 0.671875, y: 0.921875 },\n  { x: 0.703125, y: 0.921875 },\n  { x: 0.703125, y: 0.921875 },\n  { x: 0.734375, y: 0.921875 },\n  { x: 0.734375, y: 0.921875 },\n  { x: 0.765625, y: 0.921875 },\n  { x: 0.765625, y: 0.921875 },\n  { x: 0.796875, y: 0.921875 },\n  { x: 0.796875, y: 0.921875 },\n  { x: 0.828125, y: 0.921875 },\n  { x: 0.828125, y: 0.921875 },\n  { x: 0.859375, y: 0.921875 },\n  { x: 0.859375, y: 0.921875 },\n  { x: 0.890625, y: 0.921875 },\n  { x: 0.890625, y: 0.921875 },\n  { x: 0.921875, y: 0.921875 },\n  { x: 0.921875, y: 0.921875 },\n  { x: 0.953125, y: 0.921875 },\n  { x: 0.953125, y: 0.921875 },\n  { x: 0.984375, y: 0.921875 },\n  { x: 0.984375, y: 0.921875 },\n  { x: 0.015625, y: 0.953125 },\n  { x: 0.015625, y: 0.953125 },\n  { x: 0.046875, y: 0.953125 },\n  { x: 0.046875, y: 0.953125 },\n  { x: 0.078125, y: 0.953125 },\n  { x: 0.078125, y: 0.953125 },\n  { x: 0.109375, y: 0.953125 },\n  { x: 0.109375, y: 0.953125 },\n  { x: 0.140625, y: 0.953125 },\n  { x: 0.140625, y: 0.953125 },\n  { x: 0.171875, y: 0.953125 },\n  { x: 0.171875, y: 0.953125 },\n  { x: 0.203125, y: 0.953125 },\n  { x: 0.203125, y: 0.953125 },\n  { x: 0.234375, y: 0.953125 },\n  { x: 0.234375, y: 0.953125 },\n  { x: 0.265625, y: 0.953125 },\n  { x: 0.265625, y: 0.953125 },\n  { x: 0.296875, y: 0.953125 },\n  { x: 0.296875, y: 0.953125 },\n  { x: 0.328125, y: 0.953125 },\n  { x: 0.328125, y: 0.953125 },\n  { x: 0.359375, y: 0.953125 },\n  { x: 0.359375, y: 0.953125 },\n  { x: 0.390625, y: 0.953125 },\n  { x: 0.390625, y: 0.953125 },\n  { x: 0.421875, y: 0.953125 },\n  { x: 0.421875, y: 0.953125 },\n  { x: 0.453125, y: 0.953125 },\n  { x: 0.453125, y: 0.953125 },\n  { x: 0.484375, y: 0.953125 },\n  { x: 0.484375, y: 0.953125 },\n  { x: 0.515625, y: 0.953125 },\n  { x: 0.515625, y: 0.953125 },\n  { x: 0.546875, y: 0.953125 },\n  { x: 0.546875, y: 0.953125 },\n  { x: 0.578125, y: 0.953125 },\n  { x: 0.578125, y: 0.953125 },\n  { x: 0.609375, y: 0.953125 },\n  { x: 0.609375, y: 0.953125 },\n  { x: 0.640625, y: 0.953125 },\n  { x: 0.640625, y: 0.953125 },\n  { x: 0.671875, y: 0.953125 },\n  { x: 0.671875, y: 0.953125 },\n  { x: 0.703125, y: 0.953125 },\n  { x: 0.703125, y: 0.953125 },\n  { x: 0.734375, y: 0.953125 },\n  { x: 0.734375, y: 0.953125 },\n  { x: 0.765625, y: 0.953125 },\n  { x: 0.765625, y: 0.953125 },\n  { x: 0.796875, y: 0.953125 },\n  { x: 0.796875, y: 0.953125 },\n  { x: 0.828125, y: 0.953125 },\n  { x: 0.828125, y: 0.953125 },\n  { x: 0.859375, y: 0.953125 },\n  { x: 0.859375, y: 0.953125 },\n  { x: 0.890625, y: 0.953125 },\n  { x: 0.890625, y: 0.953125 },\n  { x: 0.921875, y: 0.953125 },\n  { x: 0.921875, y: 0.953125 },\n  { x: 0.953125, y: 0.953125 },\n  { x: 0.953125, y: 0.953125 },\n  { x: 0.984375, y: 0.953125 },\n  { x: 0.984375, y: 0.953125 },\n  { x: 0.015625, y: 0.984375 },\n  { x: 0.015625, y: 0.984375 },\n  { x: 0.046875, y: 0.984375 },\n  { x: 0.046875, y: 0.984375 },\n  { x: 0.078125, y: 0.984375 },\n  { x: 0.078125, y: 0.984375 },\n  { x: 0.109375, y: 0.984375 },\n  { x: 0.109375, y: 0.984375 },\n  { x: 0.140625, y: 0.984375 },\n  { x: 0.140625, y: 0.984375 },\n  { x: 0.171875, y: 0.984375 },\n  { x: 0.171875, y: 0.984375 },\n  { x: 0.203125, y: 0.984375 },\n  { x: 0.203125, y: 0.984375 },\n  { x: 0.234375, y: 0.984375 },\n  { x: 0.234375, y: 0.984375 },\n  { x: 0.265625, y: 0.984375 },\n  { x: 0.265625, y: 0.984375 },\n  { x: 0.296875, y: 0.984375 },\n  { x: 0.296875, y: 0.984375 },\n  { x: 0.328125, y: 0.984375 },\n  { x: 0.328125, y: 0.984375 },\n  { x: 0.359375, y: 0.984375 },\n  { x: 0.359375, y: 0.984375 },\n  { x: 0.390625, y: 0.984375 },\n  { x: 0.390625, y: 0.984375 },\n  { x: 0.421875, y: 0.984375 },\n  { x: 0.421875, y: 0.984375 },\n  { x: 0.453125, y: 0.984375 },\n  { x: 0.453125, y: 0.984375 },\n  { x: 0.484375, y: 0.984375 },\n  { x: 0.484375, y: 0.984375 },\n  { x: 0.515625, y: 0.984375 },\n  { x: 0.515625, y: 0.984375 },\n  { x: 0.546875, y: 0.984375 },\n  { x: 0.546875, y: 0.984375 },\n  { x: 0.578125, y: 0.984375 },\n  { x: 0.578125, y: 0.984375 },\n  { x: 0.609375, y: 0.984375 },\n  { x: 0.609375, y: 0.984375 },\n  { x: 0.640625, y: 0.984375 },\n  { x: 0.640625, y: 0.984375 },\n  { x: 0.671875, y: 0.984375 },\n  { x: 0.671875, y: 0.984375 },\n  { x: 0.703125, y: 0.984375 },\n  { x: 0.703125, y: 0.984375 },\n  { x: 0.734375, y: 0.984375 },\n  { x: 0.734375, y: 0.984375 },\n  { x: 0.765625, y: 0.984375 },\n  { x: 0.765625, y: 0.984375 },\n  { x: 0.796875, y: 0.984375 },\n  { x: 0.796875, y: 0.984375 },\n  { x: 0.828125, y: 0.984375 },\n  { x: 0.828125, y: 0.984375 },\n  { x: 0.859375, y: 0.984375 },\n  { x: 0.859375, y: 0.984375 },\n  { x: 0.890625, y: 0.984375 },\n  { x: 0.890625, y: 0.984375 },\n  { x: 0.921875, y: 0.984375 },\n  { x: 0.921875, y: 0.984375 },\n  { x: 0.953125, y: 0.984375 },\n  { x: 0.953125, y: 0.984375 },\n  { x: 0.984375, y: 0.984375 },\n  { x: 0.984375, y: 0.984375 },\n  { x: 0.03125, y: 0.03125 },\n  { x: 0.03125, y: 0.03125 },\n  { x: 0.09375, y: 0.03125 },\n  { x: 0.09375, y: 0.03125 },\n  { x: 0.15625, y: 0.03125 },\n  { x: 0.15625, y: 0.03125 },\n  { x: 0.21875, y: 0.03125 },\n  { x: 0.21875, y: 0.03125 },\n  { x: 0.28125, y: 0.03125 },\n  { x: 0.28125, y: 0.03125 },\n  { x: 0.34375, y: 0.03125 },\n  { x: 0.34375, y: 0.03125 },\n  { x: 0.40625, y: 0.03125 },\n  { x: 0.40625, y: 0.03125 },\n  { x: 0.46875, y: 0.03125 },\n  { x: 0.46875, y: 0.03125 },\n  { x: 0.53125, y: 0.03125 },\n  { x: 0.53125, y: 0.03125 },\n  { x: 0.59375, y: 0.03125 },\n  { x: 0.59375, y: 0.03125 },\n  { x: 0.65625, y: 0.03125 },\n  { x: 0.65625, y: 0.03125 },\n  { x: 0.71875, y: 0.03125 },\n  { x: 0.71875, y: 0.03125 },\n  { x: 0.78125, y: 0.03125 },\n  { x: 0.78125, y: 0.03125 },\n  { x: 0.84375, y: 0.03125 },\n  { x: 0.84375, y: 0.03125 },\n  { x: 0.90625, y: 0.03125 },\n  { x: 0.90625, y: 0.03125 },\n  { x: 0.96875, y: 0.03125 },\n  { x: 0.96875, y: 0.03125 },\n  { x: 0.03125, y: 0.09375 },\n  { x: 0.03125, y: 0.09375 },\n  { x: 0.09375, y: 0.09375 },\n  { x: 0.09375, y: 0.09375 },\n  { x: 0.15625, y: 0.09375 },\n  { x: 0.15625, y: 0.09375 },\n  { x: 0.21875, y: 0.09375 },\n  { x: 0.21875, y: 0.09375 },\n  { x: 0.28125, y: 0.09375 },\n  { x: 0.28125, y: 0.09375 },\n  { x: 0.34375, y: 0.09375 },\n  { x: 0.34375, y: 0.09375 },\n  { x: 0.40625, y: 0.09375 },\n  { x: 0.40625, y: 0.09375 },\n  { x: 0.46875, y: 0.09375 },\n  { x: 0.46875, y: 0.09375 },\n  { x: 0.53125, y: 0.09375 },\n  { x: 0.53125, y: 0.09375 },\n  { x: 0.59375, y: 0.09375 },\n  { x: 0.59375, y: 0.09375 },\n  { x: 0.65625, y: 0.09375 },\n  { x: 0.65625, y: 0.09375 },\n  { x: 0.71875, y: 0.09375 },\n  { x: 0.71875, y: 0.09375 },\n  { x: 0.78125, y: 0.09375 },\n  { x: 0.78125, y: 0.09375 },\n  { x: 0.84375, y: 0.09375 },\n  { x: 0.84375, y: 0.09375 },\n  { x: 0.90625, y: 0.09375 },\n  { x: 0.90625, y: 0.09375 },\n  { x: 0.96875, y: 0.09375 },\n  { x: 0.96875, y: 0.09375 },\n  { x: 0.03125, y: 0.15625 },\n  { x: 0.03125, y: 0.15625 },\n  { x: 0.09375, y: 0.15625 },\n  { x: 0.09375, y: 0.15625 },\n  { x: 0.15625, y: 0.15625 },\n  { x: 0.15625, y: 0.15625 },\n  { x: 0.21875, y: 0.15625 },\n  { x: 0.21875, y: 0.15625 },\n  { x: 0.28125, y: 0.15625 },\n  { x: 0.28125, y: 0.15625 },\n  { x: 0.34375, y: 0.15625 },\n  { x: 0.34375, y: 0.15625 },\n  { x: 0.40625, y: 0.15625 },\n  { x: 0.40625, y: 0.15625 },\n  { x: 0.46875, y: 0.15625 },\n  { x: 0.46875, y: 0.15625 },\n  { x: 0.53125, y: 0.15625 },\n  { x: 0.53125, y: 0.15625 },\n  { x: 0.59375, y: 0.15625 },\n  { x: 0.59375, y: 0.15625 },\n  { x: 0.65625, y: 0.15625 },\n  { x: 0.65625, y: 0.15625 },\n  { x: 0.71875, y: 0.15625 },\n  { x: 0.71875, y: 0.15625 },\n  { x: 0.78125, y: 0.15625 },\n  { x: 0.78125, y: 0.15625 },\n  { x: 0.84375, y: 0.15625 },\n  { x: 0.84375, y: 0.15625 },\n  { x: 0.90625, y: 0.15625 },\n  { x: 0.90625, y: 0.15625 },\n  { x: 0.96875, y: 0.15625 },\n  { x: 0.96875, y: 0.15625 },\n  { x: 0.03125, y: 0.21875 },\n  { x: 0.03125, y: 0.21875 },\n  { x: 0.09375, y: 0.21875 },\n  { x: 0.09375, y: 0.21875 },\n  { x: 0.15625, y: 0.21875 },\n  { x: 0.15625, y: 0.21875 },\n  { x: 0.21875, y: 0.21875 },\n  { x: 0.21875, y: 0.21875 },\n  { x: 0.28125, y: 0.21875 },\n  { x: 0.28125, y: 0.21875 },\n  { x: 0.34375, y: 0.21875 },\n  { x: 0.34375, y: 0.21875 },\n  { x: 0.40625, y: 0.21875 },\n  { x: 0.40625, y: 0.21875 },\n  { x: 0.46875, y: 0.21875 },\n  { x: 0.46875, y: 0.21875 },\n  { x: 0.53125, y: 0.21875 },\n  { x: 0.53125, y: 0.21875 },\n  { x: 0.59375, y: 0.21875 },\n  { x: 0.59375, y: 0.21875 },\n  { x: 0.65625, y: 0.21875 },\n  { x: 0.65625, y: 0.21875 },\n  { x: 0.71875, y: 0.21875 },\n  { x: 0.71875, y: 0.21875 },\n  { x: 0.78125, y: 0.21875 },\n  { x: 0.78125, y: 0.21875 },\n  { x: 0.84375, y: 0.21875 },\n  { x: 0.84375, y: 0.21875 },\n  { x: 0.90625, y: 0.21875 },\n  { x: 0.90625, y: 0.21875 },\n  { x: 0.96875, y: 0.21875 },\n  { x: 0.96875, y: 0.21875 },\n  { x: 0.03125, y: 0.28125 },\n  { x: 0.03125, y: 0.28125 },\n  { x: 0.09375, y: 0.28125 },\n  { x: 0.09375, y: 0.28125 },\n  { x: 0.15625, y: 0.28125 },\n  { x: 0.15625, y: 0.28125 },\n  { x: 0.21875, y: 0.28125 },\n  { x: 0.21875, y: 0.28125 },\n  { x: 0.28125, y: 0.28125 },\n  { x: 0.28125, y: 0.28125 },\n  { x: 0.34375, y: 0.28125 },\n  { x: 0.34375, y: 0.28125 },\n  { x: 0.40625, y: 0.28125 },\n  { x: 0.40625, y: 0.28125 },\n  { x: 0.46875, y: 0.28125 },\n  { x: 0.46875, y: 0.28125 },\n  { x: 0.53125, y: 0.28125 },\n  { x: 0.53125, y: 0.28125 },\n  { x: 0.59375, y: 0.28125 },\n  { x: 0.59375, y: 0.28125 },\n  { x: 0.65625, y: 0.28125 },\n  { x: 0.65625, y: 0.28125 },\n  { x: 0.71875, y: 0.28125 },\n  { x: 0.71875, y: 0.28125 },\n  { x: 0.78125, y: 0.28125 },\n  { x: 0.78125, y: 0.28125 },\n  { x: 0.84375, y: 0.28125 },\n  { x: 0.84375, y: 0.28125 },\n  { x: 0.90625, y: 0.28125 },\n  { x: 0.90625, y: 0.28125 },\n  { x: 0.96875, y: 0.28125 },\n  { x: 0.96875, y: 0.28125 },\n  { x: 0.03125, y: 0.34375 },\n  { x: 0.03125, y: 0.34375 },\n  { x: 0.09375, y: 0.34375 },\n  { x: 0.09375, y: 0.34375 },\n  { x: 0.15625, y: 0.34375 },\n  { x: 0.15625, y: 0.34375 },\n  { x: 0.21875, y: 0.34375 },\n  { x: 0.21875, y: 0.34375 },\n  { x: 0.28125, y: 0.34375 },\n  { x: 0.28125, y: 0.34375 },\n  { x: 0.34375, y: 0.34375 },\n  { x: 0.34375, y: 0.34375 },\n  { x: 0.40625, y: 0.34375 },\n  { x: 0.40625, y: 0.34375 },\n  { x: 0.46875, y: 0.34375 },\n  { x: 0.46875, y: 0.34375 },\n  { x: 0.53125, y: 0.34375 },\n  { x: 0.53125, y: 0.34375 },\n  { x: 0.59375, y: 0.34375 },\n  { x: 0.59375, y: 0.34375 },\n  { x: 0.65625, y: 0.34375 },\n  { x: 0.65625, y: 0.34375 },\n  { x: 0.71875, y: 0.34375 },\n  { x: 0.71875, y: 0.34375 },\n  { x: 0.78125, y: 0.34375 },\n  { x: 0.78125, y: 0.34375 },\n  { x: 0.84375, y: 0.34375 },\n  { x: 0.84375, y: 0.34375 },\n  { x: 0.90625, y: 0.34375 },\n  { x: 0.90625, y: 0.34375 },\n  { x: 0.96875, y: 0.34375 },\n  { x: 0.96875, y: 0.34375 },\n  { x: 0.03125, y: 0.40625 },\n  { x: 0.03125, y: 0.40625 },\n  { x: 0.09375, y: 0.40625 },\n  { x: 0.09375, y: 0.40625 },\n  { x: 0.15625, y: 0.40625 },\n  { x: 0.15625, y: 0.40625 },\n  { x: 0.21875, y: 0.40625 },\n  { x: 0.21875, y: 0.40625 },\n  { x: 0.28125, y: 0.40625 },\n  { x: 0.28125, y: 0.40625 },\n  { x: 0.34375, y: 0.40625 },\n  { x: 0.34375, y: 0.40625 },\n  { x: 0.40625, y: 0.40625 },\n  { x: 0.40625, y: 0.40625 },\n  { x: 0.46875, y: 0.40625 },\n  { x: 0.46875, y: 0.40625 },\n  { x: 0.53125, y: 0.40625 },\n  { x: 0.53125, y: 0.40625 },\n  { x: 0.59375, y: 0.40625 },\n  { x: 0.59375, y: 0.40625 },\n  { x: 0.65625, y: 0.40625 },\n  { x: 0.65625, y: 0.40625 },\n  { x: 0.71875, y: 0.40625 },\n  { x: 0.71875, y: 0.40625 },\n  { x: 0.78125, y: 0.40625 },\n  { x: 0.78125, y: 0.40625 },\n  { x: 0.84375, y: 0.40625 },\n  { x: 0.84375, y: 0.40625 },\n  { x: 0.90625, y: 0.40625 },\n  { x: 0.90625, y: 0.40625 },\n  { x: 0.96875, y: 0.40625 },\n  { x: 0.96875, y: 0.40625 },\n  { x: 0.03125, y: 0.46875 },\n  { x: 0.03125, y: 0.46875 },\n  { x: 0.09375, y: 0.46875 },\n  { x: 0.09375, y: 0.46875 },\n  { x: 0.15625, y: 0.46875 },\n  { x: 0.15625, y: 0.46875 },\n  { x: 0.21875, y: 0.46875 },\n  { x: 0.21875, y: 0.46875 },\n  { x: 0.28125, y: 0.46875 },\n  { x: 0.28125, y: 0.46875 },\n  { x: 0.34375, y: 0.46875 },\n  { x: 0.34375, y: 0.46875 },\n  { x: 0.40625, y: 0.46875 },\n  { x: 0.40625, y: 0.46875 },\n  { x: 0.46875, y: 0.46875 },\n  { x: 0.46875, y: 0.46875 },\n  { x: 0.53125, y: 0.46875 },\n  { x: 0.53125, y: 0.46875 },\n  { x: 0.59375, y: 0.46875 },\n  { x: 0.59375, y: 0.46875 },\n  { x: 0.65625, y: 0.46875 },\n  { x: 0.65625, y: 0.46875 },\n  { x: 0.71875, y: 0.46875 },\n  { x: 0.71875, y: 0.46875 },\n  { x: 0.78125, y: 0.46875 },\n  { x: 0.78125, y: 0.46875 },\n  { x: 0.84375, y: 0.46875 },\n  { x: 0.84375, y: 0.46875 },\n  { x: 0.90625, y: 0.46875 },\n  { x: 0.90625, y: 0.46875 },\n  { x: 0.96875, y: 0.46875 },\n  { x: 0.96875, y: 0.46875 },\n  { x: 0.03125, y: 0.53125 },\n  { x: 0.03125, y: 0.53125 },\n  { x: 0.09375, y: 0.53125 },\n  { x: 0.09375, y: 0.53125 },\n  { x: 0.15625, y: 0.53125 },\n  { x: 0.15625, y: 0.53125 },\n  { x: 0.21875, y: 0.53125 },\n  { x: 0.21875, y: 0.53125 },\n  { x: 0.28125, y: 0.53125 },\n  { x: 0.28125, y: 0.53125 },\n  { x: 0.34375, y: 0.53125 },\n  { x: 0.34375, y: 0.53125 },\n  { x: 0.40625, y: 0.53125 },\n  { x: 0.40625, y: 0.53125 },\n  { x: 0.46875, y: 0.53125 },\n  { x: 0.46875, y: 0.53125 },\n  { x: 0.53125, y: 0.53125 },\n  { x: 0.53125, y: 0.53125 },\n  { x: 0.59375, y: 0.53125 },\n  { x: 0.59375, y: 0.53125 },\n  { x: 0.65625, y: 0.53125 },\n  { x: 0.65625, y: 0.53125 },\n  { x: 0.71875, y: 0.53125 },\n  { x: 0.71875, y: 0.53125 },\n  { x: 0.78125, y: 0.53125 },\n  { x: 0.78125, y: 0.53125 },\n  { x: 0.84375, y: 0.53125 },\n  { x: 0.84375, y: 0.53125 },\n  { x: 0.90625, y: 0.53125 },\n  { x: 0.90625, y: 0.53125 },\n  { x: 0.96875, y: 0.53125 },\n  { x: 0.96875, y: 0.53125 },\n  { x: 0.03125, y: 0.59375 },\n  { x: 0.03125, y: 0.59375 },\n  { x: 0.09375, y: 0.59375 },\n  { x: 0.09375, y: 0.59375 },\n  { x: 0.15625, y: 0.59375 },\n  { x: 0.15625, y: 0.59375 },\n  { x: 0.21875, y: 0.59375 },\n  { x: 0.21875, y: 0.59375 },\n  { x: 0.28125, y: 0.59375 },\n  { x: 0.28125, y: 0.59375 },\n  { x: 0.34375, y: 0.59375 },\n  { x: 0.34375, y: 0.59375 },\n  { x: 0.40625, y: 0.59375 },\n  { x: 0.40625, y: 0.59375 },\n  { x: 0.46875, y: 0.59375 },\n  { x: 0.46875, y: 0.59375 },\n  { x: 0.53125, y: 0.59375 },\n  { x: 0.53125, y: 0.59375 },\n  { x: 0.59375, y: 0.59375 },\n  { x: 0.59375, y: 0.59375 },\n  { x: 0.65625, y: 0.59375 },\n  { x: 0.65625, y: 0.59375 },\n  { x: 0.71875, y: 0.59375 },\n  { x: 0.71875, y: 0.59375 },\n  { x: 0.78125, y: 0.59375 },\n  { x: 0.78125, y: 0.59375 },\n  { x: 0.84375, y: 0.59375 },\n  { x: 0.84375, y: 0.59375 },\n  { x: 0.90625, y: 0.59375 },\n  { x: 0.90625, y: 0.59375 },\n  { x: 0.96875, y: 0.59375 },\n  { x: 0.96875, y: 0.59375 },\n  { x: 0.03125, y: 0.65625 },\n  { x: 0.03125, y: 0.65625 },\n  { x: 0.09375, y: 0.65625 },\n  { x: 0.09375, y: 0.65625 },\n  { x: 0.15625, y: 0.65625 },\n  { x: 0.15625, y: 0.65625 },\n  { x: 0.21875, y: 0.65625 },\n  { x: 0.21875, y: 0.65625 },\n  { x: 0.28125, y: 0.65625 },\n  { x: 0.28125, y: 0.65625 },\n  { x: 0.34375, y: 0.65625 },\n  { x: 0.34375, y: 0.65625 },\n  { x: 0.40625, y: 0.65625 },\n  { x: 0.40625, y: 0.65625 },\n  { x: 0.46875, y: 0.65625 },\n  { x: 0.46875, y: 0.65625 },\n  { x: 0.53125, y: 0.65625 },\n  { x: 0.53125, y: 0.65625 },\n  { x: 0.59375, y: 0.65625 },\n  { x: 0.59375, y: 0.65625 },\n  { x: 0.65625, y: 0.65625 },\n  { x: 0.65625, y: 0.65625 },\n  { x: 0.71875, y: 0.65625 },\n  { x: 0.71875, y: 0.65625 },\n  { x: 0.78125, y: 0.65625 },\n  { x: 0.78125, y: 0.65625 },\n  { x: 0.84375, y: 0.65625 },\n  { x: 0.84375, y: 0.65625 },\n  { x: 0.90625, y: 0.65625 },\n  { x: 0.90625, y: 0.65625 },\n  { x: 0.96875, y: 0.65625 },\n  { x: 0.96875, y: 0.65625 },\n  { x: 0.03125, y: 0.71875 },\n  { x: 0.03125, y: 0.71875 },\n  { x: 0.09375, y: 0.71875 },\n  { x: 0.09375, y: 0.71875 },\n  { x: 0.15625, y: 0.71875 },\n  { x: 0.15625, y: 0.71875 },\n  { x: 0.21875, y: 0.71875 },\n  { x: 0.21875, y: 0.71875 },\n  { x: 0.28125, y: 0.71875 },\n  { x: 0.28125, y: 0.71875 },\n  { x: 0.34375, y: 0.71875 },\n  { x: 0.34375, y: 0.71875 },\n  { x: 0.40625, y: 0.71875 },\n  { x: 0.40625, y: 0.71875 },\n  { x: 0.46875, y: 0.71875 },\n  { x: 0.46875, y: 0.71875 },\n  { x: 0.53125, y: 0.71875 },\n  { x: 0.53125, y: 0.71875 },\n  { x: 0.59375, y: 0.71875 },\n  { x: 0.59375, y: 0.71875 },\n  { x: 0.65625, y: 0.71875 },\n  { x: 0.65625, y: 0.71875 },\n  { x: 0.71875, y: 0.71875 },\n  { x: 0.71875, y: 0.71875 },\n  { x: 0.78125, y: 0.71875 },\n  { x: 0.78125, y: 0.71875 },\n  { x: 0.84375, y: 0.71875 },\n  { x: 0.84375, y: 0.71875 },\n  { x: 0.90625, y: 0.71875 },\n  { x: 0.90625, y: 0.71875 },\n  { x: 0.96875, y: 0.71875 },\n  { x: 0.96875, y: 0.71875 },\n  { x: 0.03125, y: 0.78125 },\n  { x: 0.03125, y: 0.78125 },\n  { x: 0.09375, y: 0.78125 },\n  { x: 0.09375, y: 0.78125 },\n  { x: 0.15625, y: 0.78125 },\n  { x: 0.15625, y: 0.78125 },\n  { x: 0.21875, y: 0.78125 },\n  { x: 0.21875, y: 0.78125 },\n  { x: 0.28125, y: 0.78125 },\n  { x: 0.28125, y: 0.78125 },\n  { x: 0.34375, y: 0.78125 },\n  { x: 0.34375, y: 0.78125 },\n  { x: 0.40625, y: 0.78125 },\n  { x: 0.40625, y: 0.78125 },\n  { x: 0.46875, y: 0.78125 },\n  { x: 0.46875, y: 0.78125 },\n  { x: 0.53125, y: 0.78125 },\n  { x: 0.53125, y: 0.78125 },\n  { x: 0.59375, y: 0.78125 },\n  { x: 0.59375, y: 0.78125 },\n  { x: 0.65625, y: 0.78125 },\n  { x: 0.65625, y: 0.78125 },\n  { x: 0.71875, y: 0.78125 },\n  { x: 0.71875, y: 0.78125 },\n  { x: 0.78125, y: 0.78125 },\n  { x: 0.78125, y: 0.78125 },\n  { x: 0.84375, y: 0.78125 },\n  { x: 0.84375, y: 0.78125 },\n  { x: 0.90625, y: 0.78125 },\n  { x: 0.90625, y: 0.78125 },\n  { x: 0.96875, y: 0.78125 },\n  { x: 0.96875, y: 0.78125 },\n  { x: 0.03125, y: 0.84375 },\n  { x: 0.03125, y: 0.84375 },\n  { x: 0.09375, y: 0.84375 },\n  { x: 0.09375, y: 0.84375 },\n  { x: 0.15625, y: 0.84375 },\n  { x: 0.15625, y: 0.84375 },\n  { x: 0.21875, y: 0.84375 },\n  { x: 0.21875, y: 0.84375 },\n  { x: 0.28125, y: 0.84375 },\n  { x: 0.28125, y: 0.84375 },\n  { x: 0.34375, y: 0.84375 },\n  { x: 0.34375, y: 0.84375 },\n  { x: 0.40625, y: 0.84375 },\n  { x: 0.40625, y: 0.84375 },\n  { x: 0.46875, y: 0.84375 },\n  { x: 0.46875, y: 0.84375 },\n  { x: 0.53125, y: 0.84375 },\n  { x: 0.53125, y: 0.84375 },\n  { x: 0.59375, y: 0.84375 },\n  { x: 0.59375, y: 0.84375 },\n  { x: 0.65625, y: 0.84375 },\n  { x: 0.65625, y: 0.84375 },\n  { x: 0.71875, y: 0.84375 },\n  { x: 0.71875, y: 0.84375 },\n  { x: 0.78125, y: 0.84375 },\n  { x: 0.78125, y: 0.84375 },\n  { x: 0.84375, y: 0.84375 },\n  { x: 0.84375, y: 0.84375 },\n  { x: 0.90625, y: 0.84375 },\n  { x: 0.90625, y: 0.84375 },\n  { x: 0.96875, y: 0.84375 },\n  { x: 0.96875, y: 0.84375 },\n  { x: 0.03125, y: 0.90625 },\n  { x: 0.03125, y: 0.90625 },\n  { x: 0.09375, y: 0.90625 },\n  { x: 0.09375, y: 0.90625 },\n  { x: 0.15625, y: 0.90625 },\n  { x: 0.15625, y: 0.90625 },\n  { x: 0.21875, y: 0.90625 },\n  { x: 0.21875, y: 0.90625 },\n  { x: 0.28125, y: 0.90625 },\n  { x: 0.28125, y: 0.90625 },\n  { x: 0.34375, y: 0.90625 },\n  { x: 0.34375, y: 0.90625 },\n  { x: 0.40625, y: 0.90625 },\n  { x: 0.40625, y: 0.90625 },\n  { x: 0.46875, y: 0.90625 },\n  { x: 0.46875, y: 0.90625 },\n  { x: 0.53125, y: 0.90625 },\n  { x: 0.53125, y: 0.90625 },\n  { x: 0.59375, y: 0.90625 },\n  { x: 0.59375, y: 0.90625 },\n  { x: 0.65625, y: 0.90625 },\n  { x: 0.65625, y: 0.90625 },\n  { x: 0.71875, y: 0.90625 },\n  { x: 0.71875, y: 0.90625 },\n  { x: 0.78125, y: 0.90625 },\n  { x: 0.78125, y: 0.90625 },\n  { x: 0.84375, y: 0.90625 },\n  { x: 0.84375, y: 0.90625 },\n  { x: 0.90625, y: 0.90625 },\n  { x: 0.90625, y: 0.90625 },\n  { x: 0.96875, y: 0.90625 },\n  { x: 0.96875, y: 0.90625 },\n  { x: 0.03125, y: 0.96875 },\n  { x: 0.03125, y: 0.96875 },\n  { x: 0.09375, y: 0.96875 },\n  { x: 0.09375, y: 0.96875 },\n  { x: 0.15625, y: 0.96875 },\n  { x: 0.15625, y: 0.96875 },\n  { x: 0.21875, y: 0.96875 },\n  { x: 0.21875, y: 0.96875 },\n  { x: 0.28125, y: 0.96875 },\n  { x: 0.28125, y: 0.96875 },\n  { x: 0.34375, y: 0.96875 },\n  { x: 0.34375, y: 0.96875 },\n  { x: 0.40625, y: 0.96875 },\n  { x: 0.40625, y: 0.96875 },\n  { x: 0.46875, y: 0.96875 },\n  { x: 0.46875, y: 0.96875 },\n  { x: 0.53125, y: 0.96875 },\n  { x: 0.53125, y: 0.96875 },\n  { x: 0.59375, y: 0.96875 },\n  { x: 0.59375, y: 0.96875 },\n  { x: 0.65625, y: 0.96875 },\n  { x: 0.65625, y: 0.96875 },\n  { x: 0.71875, y: 0.96875 },\n  { x: 0.71875, y: 0.96875 },\n  { x: 0.78125, y: 0.96875 },\n  { x: 0.78125, y: 0.96875 },\n  { x: 0.84375, y: 0.96875 },\n  { x: 0.84375, y: 0.96875 },\n  { x: 0.90625, y: 0.96875 },\n  { x: 0.90625, y: 0.96875 },\n  { x: 0.96875, y: 0.96875 },\n  { x: 0.96875, y: 0.96875 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n];\n", "/**\n * HandPose model implementation\n * See `handpose.ts` for entry point\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as util from './handposeutil';\nimport * as anchors from './handposeanchors';\nimport { constants } from '../tfjs/constants';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Point } from '../result';\n\nexport class HandDetector {\n  model: GraphModel;\n  anchors: number[][];\n  anchorsTensor: Tensor;\n  inputSize: number;\n  inputSizeTensor: Tensor;\n  doubleInputSizeTensor: Tensor;\n\n  constructor(model) {\n    this.model = model;\n    this.anchors = anchors.anchors.map((anchor) => [anchor.x, anchor.y]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = (this.model && this.model.inputs && this.model.inputs[0].shape) ? this.model.inputs[0].shape[2] : 0;\n    this.inputSizeTensor = tf.tensor1d([this.inputSize, this.inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([this.inputSize * 2, this.inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    const t: Record<string, Tensor> = {};\n    t.boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n    t.boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n    t.div = tf.div(t.boxOffsets, this.inputSizeTensor);\n    t.boxCenterPoints = tf.add(t.div, this.anchorsTensor);\n    t.halfBoxSizes = tf.div(t.boxSizes, this.doubleInputSizeTensor);\n    t.sub = tf.sub(t.boxCenterPoints, t.halfBoxSizes);\n    t.startPoints = tf.mul(t.sub, this.inputSizeTensor);\n    t.add = tf.add(t.boxCenterPoints, t.halfBoxSizes);\n    t.endPoints = tf.mul(t.add, this.inputSizeTensor);\n    const res = tf.concat2d([t.startPoints, t.endPoints], 1);\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return res;\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    const t: Record<string, Tensor> = {};\n    t.reshape = tf.reshape(rawPalmLandmarks, [-1, 7, 2]);\n    t.div = tf.div(t.reshape, this.inputSizeTensor);\n    t.landmarks = tf.add(t.div, this.anchors[index]);\n    const res = tf.mul(t.landmarks, this.inputSizeTensor);\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return res;\n  }\n\n  async predict(input, config): Promise<{ startPoint: Point; endPoint: Point, palmLandmarks: Point[]; confidence: number }[]> {\n    const t: Record<string, Tensor> = {};\n    t.resize = tf.image.resizeBilinear(input, [this.inputSize, this.inputSize]);\n    t.div = tf.div(t.resize, constants.tf127);\n    t.image = tf.sub(t.div, constants.tf1);\n    t.batched = this.model.execute(t.image) as Tensor;\n    t.predictions = tf.squeeze(t.batched);\n    t.slice = tf.slice(t.predictions, [0, 0], [-1, 1]);\n    t.sigmoid = tf.sigmoid(t.slice);\n    t.scores = tf.squeeze(t.sigmoid);\n    const scores = await t.scores.data();\n    t.boxes = tf.slice(t.predictions, [0, 1], [-1, 4]);\n    t.norm = this.normalizeBoxes(t.boxes);\n    // box detection is flaky so we look for 3x boxes than we need results\n    t.nms = await tf.image.nonMaxSuppressionAsync(t.norm, t.scores, 3 * config.hand.maxDetected, config.hand.iouThreshold, config.hand.minConfidence);\n    const nms = await t.nms.array() as Array<number>;\n    const hands: Array<{ startPoint: Point; endPoint: Point; palmLandmarks: Point[]; confidence: number }> = [];\n    for (const index of nms) {\n      const p: Record<string, Tensor> = {};\n      p.box = tf.slice(t.norm, [index, 0], [1, -1]);\n      p.slice = tf.slice(t.predictions, [index, 5], [1, 14]);\n      p.norm = this.normalizeLandmarks(p.slice, index);\n      p.palmLandmarks = tf.reshape(p.norm, [-1, 2]);\n      const box = await p.box.data();\n      const startPoint = box.slice(0, 2) as unknown as Point;\n      const endPoint = box.slice(2, 4) as unknown as Point;\n      const palmLandmarks = await p.palmLandmarks.array();\n      const hand = { startPoint, endPoint, palmLandmarks, confidence: scores[index] };\n      const scaled = util.scaleBoxCoordinates(hand, [input.shape[2] / this.inputSize, input.shape[1] / this.inputSize]);\n      hands.push(scaled);\n      Object.keys(p).forEach((tensor) => tf.dispose(p[tensor]));\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return hands;\n  }\n}\n", "/**\n * HandPose model implementation\n * See `handpose.ts` for entry point\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as util from './handposeutil';\nimport type * as detector from './handposedetector';\nimport { constants } from '../tfjs/constants';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport { env } from '../util/env';\nimport { now } from '../util/util';\nimport type { Point } from '../result';\n\nconst palmBoxEnlargeFactor = 5; // default 3\nconst handBoxEnlargeFactor = 1.65; // default 1.65\nconst palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];\nconst palmLandmarksPalmBase = 0;\nconst palmLandmarksMiddleFingerBase = 2;\nlet lastTime = 0;\n\nexport class HandPipeline {\n  handDetector: detector.HandDetector;\n  handPoseModel: GraphModel;\n  inputSize: number;\n  storedBoxes: Array<{ startPoint: Point; endPoint: Point; palmLandmarks: Point[]; confidence: number } | null>;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, handPoseModel) {\n    this.handDetector = handDetector;\n    this.handPoseModel = handPoseModel;\n    this.inputSize = this.handPoseModel && this.handPoseModel.inputs[0].shape ? this.handPoseModel.inputs[0].shape[2] : 0;\n    this.storedBoxes = [];\n    this.skipped = Number.MAX_SAFE_INTEGER;\n    this.detectedHands = 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    return util.enlargeBox(util.squarifyBox(boxAroundPalm), palmBoxEnlargeFactor);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    const boxAroundHand = util.enlargeBox(util.squarifyBox(boundingBox), handBoxEnlargeFactor);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < palmLandmarkIds.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[palmLandmarkIds[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = util.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...util.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      Math.trunc(coord[0] + originalBoxCenter[0]),\n      Math.trunc(coord[1] + originalBoxCenter[1]),\n      Math.trunc(coord[2]),\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames\n    let boxes;\n    const skipTime = (config.hand.skipTime || 0) > (now() - lastTime);\n    const skipFrame = this.skipped < (config.hand.skipFrames || 0);\n    if (config.skipAllowed && skipTime && skipFrame) {\n      boxes = await this.handDetector.predict(image, config);\n      this.skipped = 0;\n    }\n    if (config.skipAllowed) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxDetected) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{ landmarks: Point[], confidence: number, boxConfidence: number, fingerConfidence: number, box: { topLeft: Point, bottomRight: Point } }> = [];\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[palmLandmarksPalmBase], currentBox.palmLandmarks[palmLandmarksMiddleFingerBase]) : 0;\n        const palmCenter = util.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation && env.kernels.includes('rotatewithoffset') ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = util.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = tf.div(croppedInput, constants.tf255);\n        tf.dispose(croppedInput);\n        tf.dispose(rotatedImage);\n        const [confidenceT, keypoints] = this.handPoseModel.execute(handImage) as Array<Tensor>;\n        lastTime = now();\n        tf.dispose(handImage);\n        const confidence = (await confidenceT.data())[0];\n        tf.dispose(confidenceT);\n        if (confidence >= config.hand.minConfidence / 4) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = await keypointsReshaped.array();\n          tf.dispose(keypoints);\n          tf.dispose(keypointsReshaped);\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = { ...nextBoundingBox, confidence };\n          const result = {\n            landmarks: coords,\n            confidence,\n            boxConfidence: currentBox.confidence,\n            fingerConfidence: confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        tf.dispose(keypoints);\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), handBoxEnlargeFactor);\n        const enlarged = util.enlargeBox(util.squarifyBox(currentBox), handBoxEnlargeFactor);\n        const result = {\n          confidence: currentBox.confidence,\n          boxConfidence: currentBox.confidence,\n          fingerConfidence: 0,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n          landmarks: [],\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    if (hands.length > config.hand.maxDetected) hands.length = config.hand.maxDetected;\n    return hands;\n  }\n}\n", "/**\n * FingerPose algorithm implementation\n * See `fingerpose.ts` for entry point\n */\n\nexport const Finger = {\n  thumb: 0,\n  index: 1,\n  middle: 2,\n  ring: 3,\n  pinky: 4,\n  all: [0, 1, 2, 3, 4], // just for convenience\n  nameMapping: { 0: 'thumb', 1: 'index', 2: 'middle', 3: 'ring', 4: 'pinky' },\n  // Describes mapping of joints based on the 21 points returned by handpose.\n  // [0]     Palm\n  // [1-4]   Thumb\n  // [5-8]   Index\n  // [9-12]  Middle\n  // [13-16] Ring\n  // [17-20] Pinky\n  pointsMapping: {\n    0: [[0, 1], [1, 2], [2, 3], [3, 4]],\n    1: [[0, 5], [5, 6], [6, 7], [7, 8]],\n    2: [[0, 9], [9, 10], [10, 11], [11, 12]],\n    3: [[0, 13], [13, 14], [14, 15], [15, 16]],\n    4: [[0, 17], [17, 18], [18, 19], [19, 20]],\n  },\n  getName: (value) => Finger.nameMapping[value],\n  getPoints: (value) => Finger.pointsMapping[value],\n};\n\nexport const FingerCurl = {\n  none: 0,\n  half: 1,\n  full: 2,\n  nameMapping: { 0: 'none', 1: 'half', 2: 'full' },\n  getName: (value) => FingerCurl.nameMapping[value],\n};\n\nexport const FingerDirection = {\n  verticalUp: 0,\n  verticalDown: 1,\n  horizontalLeft: 2,\n  horizontalRight: 3,\n  diagonalUpRight: 4,\n  diagonalUpLeft: 5,\n  diagonalDownRight: 6,\n  diagonalDownLeft: 7,\n  nameMapping: { 0: 'verticalUp', 1: 'verticalDown', 2: 'horizontalLeft', 3: 'horizontalRight', 4: 'diagonalUpRight', 5: 'diagonalUpLeft', 6: 'diagonalDownRight', 7: 'diagonalDownLeft' },\n  getName: (value) => FingerDirection.nameMapping[value],\n};\n\nexport class FingerGesture {\n  name;\n  curls;\n  directions;\n  weights;\n  weightsRelative;\n\n  constructor(name) {\n    // name (should be unique)\n    this.name = name;\n    this.curls = {};\n    this.directions = {};\n    this.weights = [1.0, 1.0, 1.0, 1.0, 1.0];\n    this.weightsRelative = [1.0, 1.0, 1.0, 1.0, 1.0];\n  }\n\n  curl(finger, curl, confidence) {\n    if (typeof this.curls[finger] === 'undefined') this.curls[finger] = [];\n    this.curls[finger].push([curl, confidence]);\n  }\n\n  direction(finger, position, confidence) {\n    if (!this.directions[finger]) this.directions[finger] = [];\n    this.directions[finger].push([position, confidence]);\n  }\n\n  weight(finger, weight) {\n    this.weights[finger] = weight;\n    // recalculate relative weights\n    const total = this.weights.reduce((a, b) => a + b, 0);\n    this.weightsRelative = this.weights.map((el) => el * 5 / total);\n  }\n\n  matchAgainst(detectedCurls, detectedDirections) {\n    let confidence = 0.0;\n    // look at the detected curl of each finger and compare with\n    // the expected curl of this finger inside current gesture\n    for (const fingerIdx in detectedCurls) {\n      const detectedCurl = detectedCurls[fingerIdx];\n      const expectedCurls = this.curls[fingerIdx];\n      if (typeof expectedCurls === 'undefined') {\n        // no curl description available for this finger\n        // add default confidence of \"1\"\n        confidence += this.weightsRelative[fingerIdx];\n        continue;\n      }\n      // compare to each possible curl of this specific finger\n      for (const [expectedCurl, score] of expectedCurls) {\n        if (detectedCurl === expectedCurl) {\n          confidence += score * this.weightsRelative[fingerIdx];\n          break;\n        }\n      }\n    }\n    // same for detected direction of each finger\n    for (const fingerIdx in detectedDirections) {\n      const detectedDirection = detectedDirections[fingerIdx];\n      const expectedDirections = this.directions[fingerIdx];\n      if (typeof expectedDirections === 'undefined') {\n        // no direction description available for this finger\n        // add default confidence of \"1\"\n        confidence += this.weightsRelative[fingerIdx];\n        continue;\n      }\n      // compare to each possible direction of this specific finger\n      for (const [expectedDirection, score] of expectedDirections) {\n        if (detectedDirection === expectedDirection) {\n          confidence += score * this.weightsRelative[fingerIdx];\n          break;\n        }\n      }\n    }\n    return confidence / 10;\n  }\n}\n", "/**\n * FingerPose algorithm implementation\n * See `fingerpose.ts` for entry point\n */\n\nimport { Finger, FingerCurl, FingerDirection, FingerGesture } from './fingerdef';\n\n// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\nexport const { thumb, index, middle, ring, pinky } = Finger;\n// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\nexport const { none, half, full } = FingerCurl;\n// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\nexport const { verticalUp, verticalDown, horizontalLeft, horizontalRight, diagonalUpRight, diagonalUpLeft, diagonalDownRight, diagonalDownLeft } = FingerDirection;\n\n// describe thumbs up gesture \uD83D\uDC4D\nconst ThumbsUp = new FingerGesture('thumbs up');\nThumbsUp.curl(thumb, none, 1.0);\nThumbsUp.direction(thumb, verticalUp, 1.0);\nThumbsUp.direction(thumb, diagonalUpLeft, 0.25);\nThumbsUp.direction(thumb, diagonalUpRight, 0.25);\nfor (const finger of [Finger.index, Finger.middle, Finger.ring, Finger.pinky]) {\n  ThumbsUp.curl(finger, full, 1.0);\n  ThumbsUp.direction(finger, horizontalLeft, 1.0);\n  ThumbsUp.direction(finger, horizontalRight, 1.0);\n}\n\n// describe Victory gesture \u270C\uFE0F\nconst Victory = new FingerGesture('victory');\nVictory.curl(thumb, half, 0.5);\nVictory.curl(thumb, none, 0.5);\nVictory.direction(thumb, verticalUp, 1.0);\nVictory.direction(thumb, diagonalUpLeft, 1.0);\nVictory.curl(index, none, 1.0);\nVictory.direction(index, verticalUp, 0.75);\nVictory.direction(index, diagonalUpLeft, 1.0);\nVictory.curl(middle, none, 1.0);\nVictory.direction(middle, verticalUp, 1.0);\nVictory.direction(middle, diagonalUpLeft, 0.75);\nVictory.curl(ring, full, 1.0);\nVictory.direction(ring, verticalUp, 0.2);\nVictory.direction(ring, diagonalUpLeft, 1.0);\nVictory.direction(ring, horizontalLeft, 0.2);\nVictory.curl(pinky, full, 1.0);\nVictory.direction(pinky, verticalUp, 0.2);\nVictory.direction(pinky, diagonalUpLeft, 1.0);\nVictory.direction(pinky, horizontalLeft, 0.2);\nVictory.weight(index, 2);\nVictory.weight(middle, 2);\n\n// describe Point gesture \u270C\uFE0F\nconst Point = new FingerGesture('point');\nPoint.curl(thumb, full, 1.0);\nPoint.curl(index, none, 0.5);\nPoint.curl(middle, full, 0.5);\nPoint.curl(ring, full, 0.5);\nPoint.curl(pinky, full, 0.5);\nPoint.weight(index, 2);\nPoint.weight(middle, 2);\n\n// describe Point gesture \u270C\uFE0F\nconst MiddleFinger = new FingerGesture('middle finger');\nMiddleFinger.curl(thumb, none, 1.0);\nMiddleFinger.curl(index, full, 0.5);\nMiddleFinger.curl(middle, full, 0.5);\nMiddleFinger.curl(ring, full, 0.5);\nMiddleFinger.curl(pinky, full, 0.5);\nMiddleFinger.weight(index, 2);\nMiddleFinger.weight(middle, 2);\n\n// describe Open Palm gesture \u270C\uFE0F\nconst OpenPalm = new FingerGesture('open palm');\nOpenPalm.curl(thumb, none, 0.75);\nOpenPalm.curl(index, none, 0.75);\nOpenPalm.curl(middle, none, 0.75);\nOpenPalm.curl(ring, none, 0.75);\nOpenPalm.curl(pinky, none, 0.75);\n\nexport default [ThumbsUp, Victory, Point, MiddleFinger, OpenPalm];\n", "/**\n * FingerPose algorithm implementation constants\n *\n * Based on: [**FingerPose***](https://github.com/andypotato/fingerpose)\n */\n\nimport { Finger, FingerCurl, FingerDirection } from './fingerdef';\nimport Gestures from '../hand/fingergesture';\n\nconst minConfidence = 0.7;\nconst options = {\n  // curl estimation\n  HALF_CURL_START_LIMIT: 60.0,\n  NO_CURL_START_LIMIT: 130.0,\n  // direction estimation\n  DISTANCE_VOTE_POWER: 1.1,\n  SINGLE_ANGLE_VOTE_POWER: 0.9,\n  TOTAL_ANGLE_VOTE_POWER: 1.6,\n};\n\nfunction calculateSlope(point1x, point1y, point2x, point2y) {\n  const value = (point1y - point2y) / (point1x - point2x);\n  let slope = Math.atan(value) * 180 / Math.PI;\n  if (slope <= 0) slope = -slope;\n  else if (slope > 0) slope = 180 - slope;\n  return slope;\n}\n\n// point1, point2 are 2d or 3d point arrays (xy[z])\n// returns either a single scalar (2d) or array of two slopes (3d)\nfunction getSlopes(point1, point2) {\n  if (!point1 || !point2) return [0, 0];\n  const slopeXY = calculateSlope(point1[0], point1[1], point2[0], point2[1]);\n  if (point1.length === 2) return slopeXY;\n  const slopeYZ = calculateSlope(point1[1], point1[2], point2[1], point2[2]);\n  return [slopeXY, slopeYZ];\n}\n\nfunction angleOrientationAt(angle, weightageAt = 1.0) {\n  let isVertical = 0;\n  let isDiagonal = 0;\n  let isHorizontal = 0;\n  if (angle >= 75.0 && angle <= 105.0) isVertical = 1 * weightageAt;\n  else if (angle >= 25.0 && angle <= 155.0) isDiagonal = 1 * weightageAt;\n  else isHorizontal = 1 * weightageAt;\n  return [isVertical, isDiagonal, isHorizontal];\n}\n\nfunction estimateFingerCurl(startPoint, midPoint, endPoint) {\n  const start_mid_x_dist = startPoint[0] - midPoint[0];\n  const start_end_x_dist = startPoint[0] - endPoint[0];\n  const mid_end_x_dist = midPoint[0] - endPoint[0];\n  const start_mid_y_dist = startPoint[1] - midPoint[1];\n  const start_end_y_dist = startPoint[1] - endPoint[1];\n  const mid_end_y_dist = midPoint[1] - endPoint[1];\n  const start_mid_z_dist = startPoint[2] - midPoint[2];\n  const start_end_z_dist = startPoint[2] - endPoint[2];\n  const mid_end_z_dist = midPoint[2] - endPoint[2];\n  const start_mid_dist = Math.sqrt(start_mid_x_dist * start_mid_x_dist + start_mid_y_dist * start_mid_y_dist + start_mid_z_dist * start_mid_z_dist);\n  const start_end_dist = Math.sqrt(start_end_x_dist * start_end_x_dist + start_end_y_dist * start_end_y_dist + start_end_z_dist * start_end_z_dist);\n  const mid_end_dist = Math.sqrt(mid_end_x_dist * mid_end_x_dist + mid_end_y_dist * mid_end_y_dist + mid_end_z_dist * mid_end_z_dist);\n  let cos_in = (mid_end_dist * mid_end_dist + start_mid_dist * start_mid_dist - start_end_dist * start_end_dist) / (2 * mid_end_dist * start_mid_dist);\n  if (cos_in > 1.0) cos_in = 1.0;\n  else if (cos_in < -1.0) cos_in = -1.0;\n  let angleOfCurve = Math.acos(cos_in);\n  angleOfCurve = (57.2958 * angleOfCurve) % 180;\n  let fingerCurl;\n  if (angleOfCurve > options.NO_CURL_START_LIMIT) fingerCurl = FingerCurl.none;\n  else if (angleOfCurve > options.HALF_CURL_START_LIMIT) fingerCurl = FingerCurl.half;\n  else fingerCurl = FingerCurl.full;\n  return fingerCurl;\n}\n\nfunction estimateHorizontalDirection(start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x) {\n  let estimatedDirection;\n  if (max_dist_x === Math.abs(start_end_x_dist)) {\n    if (start_end_x_dist > 0) estimatedDirection = FingerDirection.horizontalLeft;\n    else estimatedDirection = FingerDirection.horizontalRight;\n  } else if (max_dist_x === Math.abs(start_mid_x_dist)) {\n    if (start_mid_x_dist > 0) estimatedDirection = FingerDirection.horizontalLeft;\n    else estimatedDirection = FingerDirection.horizontalRight;\n  } else {\n    if (mid_end_x_dist > 0) estimatedDirection = FingerDirection.horizontalLeft;\n    else estimatedDirection = FingerDirection.horizontalRight;\n  }\n  return estimatedDirection;\n}\n\nfunction estimateVerticalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y) {\n  let estimatedDirection;\n  if (max_dist_y === Math.abs(start_end_y_dist)) {\n    if (start_end_y_dist < 0) estimatedDirection = FingerDirection.verticalDown;\n    else estimatedDirection = FingerDirection.verticalUp;\n  } else if (max_dist_y === Math.abs(start_mid_y_dist)) {\n    if (start_mid_y_dist < 0) estimatedDirection = FingerDirection.verticalDown;\n    else estimatedDirection = FingerDirection.verticalUp;\n  } else {\n    if (mid_end_y_dist < 0) estimatedDirection = FingerDirection.verticalDown;\n    else estimatedDirection = FingerDirection.verticalUp;\n  }\n  return estimatedDirection;\n}\n\nfunction estimateDiagonalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y, start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x) {\n  let estimatedDirection;\n  const reqd_vertical_direction = estimateVerticalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y);\n  const reqd_horizontal_direction = estimateHorizontalDirection(start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x);\n  if (reqd_vertical_direction === FingerDirection.verticalUp) {\n    if (reqd_horizontal_direction === FingerDirection.horizontalLeft) estimatedDirection = FingerDirection.diagonalUpLeft;\n    else estimatedDirection = FingerDirection.diagonalUpRight;\n  } else {\n    if (reqd_horizontal_direction === FingerDirection.horizontalLeft) estimatedDirection = FingerDirection.diagonalDownLeft;\n    else estimatedDirection = FingerDirection.diagonalDownRight;\n  }\n  return estimatedDirection;\n}\n\nfunction calculateFingerDirection(startPoint, midPoint, endPoint, fingerSlopes) {\n  const start_mid_x_dist = startPoint[0] - midPoint[0];\n  const start_end_x_dist = startPoint[0] - endPoint[0];\n  const mid_end_x_dist = midPoint[0] - endPoint[0];\n  const start_mid_y_dist = startPoint[1] - midPoint[1];\n  const start_end_y_dist = startPoint[1] - endPoint[1];\n  const mid_end_y_dist = midPoint[1] - endPoint[1];\n  const max_dist_x = Math.max(Math.abs(start_mid_x_dist), Math.abs(start_end_x_dist), Math.abs(mid_end_x_dist));\n  const max_dist_y = Math.max(Math.abs(start_mid_y_dist), Math.abs(start_end_y_dist), Math.abs(mid_end_y_dist));\n  let voteVertical = 0.0;\n  let voteDiagonal = 0.0;\n  let voteHorizontal = 0.0;\n  const start_end_x_y_dist_ratio = max_dist_y / (max_dist_x + 0.00001);\n  if (start_end_x_y_dist_ratio > 1.5) voteVertical += options.DISTANCE_VOTE_POWER;\n  else if (start_end_x_y_dist_ratio > 0.66) voteDiagonal += options.DISTANCE_VOTE_POWER;\n  else voteHorizontal += options.DISTANCE_VOTE_POWER;\n  const start_mid_dist = Math.sqrt(start_mid_x_dist * start_mid_x_dist + start_mid_y_dist * start_mid_y_dist);\n  const start_end_dist = Math.sqrt(start_end_x_dist * start_end_x_dist + start_end_y_dist * start_end_y_dist);\n  const mid_end_dist = Math.sqrt(mid_end_x_dist * mid_end_x_dist + mid_end_y_dist * mid_end_y_dist);\n  const max_dist = Math.max(start_mid_dist, start_end_dist, mid_end_dist);\n  let calc_start_point_x = startPoint[0];\n  let calc_start_point_y = startPoint[1];\n  let calc_end_point_x = endPoint[0];\n  let calc_end_point_y = endPoint[1];\n  if (max_dist === start_mid_dist) {\n    calc_end_point_x = endPoint[0];\n    calc_end_point_y = endPoint[1];\n  } else if (max_dist === mid_end_dist) {\n    calc_start_point_x = midPoint[0];\n    calc_start_point_y = midPoint[1];\n  }\n  const calcStartPoint = [calc_start_point_x, calc_start_point_y];\n  const calcEndPoint = [calc_end_point_x, calc_end_point_y];\n  const totalAngle = getSlopes(calcStartPoint, calcEndPoint);\n  const votes = angleOrientationAt(totalAngle, options.TOTAL_ANGLE_VOTE_POWER);\n  voteVertical += votes[0];\n  voteDiagonal += votes[1];\n  voteHorizontal += votes[2];\n  for (const fingerSlope of fingerSlopes) {\n    const fingerVotes = angleOrientationAt(fingerSlope, options.SINGLE_ANGLE_VOTE_POWER);\n    voteVertical += fingerVotes[0];\n    voteDiagonal += fingerVotes[1];\n    voteHorizontal += fingerVotes[2];\n  }\n  // in case of tie, highest preference goes to Vertical,\n  // followed by horizontal and then diagonal\n  let estimatedDirection;\n  if (voteVertical === Math.max(voteVertical, voteDiagonal, voteHorizontal)) {\n    estimatedDirection = estimateVerticalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y);\n  } else if (voteHorizontal === Math.max(voteDiagonal, voteHorizontal)) {\n    estimatedDirection = estimateHorizontalDirection(start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x);\n  } else {\n    estimatedDirection = estimateDiagonalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y, start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x);\n  }\n  return estimatedDirection;\n}\n\nfunction estimate(landmarks) {\n  // step 1: calculate slopes\n  const slopesXY: Array<number[]> = [];\n  const slopesYZ: Array<number[]> = [];\n  const fingerCurls: Array<number> = [];\n  const fingerDirections: Array<number> = [];\n  if (!landmarks) return { curls: fingerCurls, directions: fingerDirections };\n\n  // step 1: calculate slopes\n  for (const finger of Finger.all) {\n    const points = Finger.getPoints(finger);\n    const slopeAtXY: Array<number> = [];\n    const slopeAtYZ: Array<number> = [];\n    for (const point of points) {\n      const point1 = landmarks[point[0]];\n      const point2 = landmarks[point[1]];\n      // calculate single slope\n      const slopes = getSlopes(point1, point2);\n      const slopeXY = slopes[0];\n      const slopeYZ = slopes[1];\n      slopeAtXY.push(slopeXY);\n      slopeAtYZ.push(slopeYZ);\n    }\n    slopesXY.push(slopeAtXY);\n    slopesYZ.push(slopeAtYZ);\n  }\n\n  // step 2: calculate orientations\n  for (const finger of Finger.all) {\n    // start finger predictions from palm - except for thumb\n    const pointIndexAt = (finger === Finger.thumb) ? 1 : 0;\n    const fingerPointsAt = Finger.getPoints(finger);\n    const startPoint = landmarks[fingerPointsAt[pointIndexAt][0]];\n    const midPoint = landmarks[fingerPointsAt[pointIndexAt + 1][1]];\n    const endPoint = landmarks[fingerPointsAt[3][1]];\n    // check if finger is curled\n    const fingerCurled = estimateFingerCurl(startPoint, midPoint, endPoint);\n    const fingerPosition = calculateFingerDirection(startPoint, midPoint, endPoint, slopesXY[finger].slice(pointIndexAt));\n    fingerCurls[finger] = fingerCurled;\n    fingerDirections[finger] = fingerPosition;\n  }\n  return { curls: fingerCurls, directions: fingerDirections };\n}\n\nexport function analyze(keypoints) { // get estimations of curl / direction for each finger\n  if (!keypoints || keypoints.length === 0) return null;\n  const estimatorRes = estimate(keypoints);\n  const landmarks = {};\n  for (const fingerIdx of Finger.all) {\n    landmarks[Finger.getName(fingerIdx)] = {\n      curl: FingerCurl.getName(estimatorRes.curls[fingerIdx]),\n      direction: FingerDirection.getName(estimatorRes.directions[fingerIdx]),\n    };\n  }\n  return landmarks;\n}\n\nexport function match(keypoints) { // compare gesture description to each known gesture\n  const poses: Array<{ name: string, confidence: number }> = [];\n  if (!keypoints || keypoints.length === 0) return poses;\n  const estimatorRes = estimate(keypoints);\n  for (const gesture of Gestures) {\n    const confidence = gesture.matchAgainst(estimatorRes.curls, estimatorRes.directions);\n    if (confidence >= minConfidence) poses.push({ name: gesture.name, confidence });\n  }\n  return poses;\n}\n", "/**\n * HandPose model implementation\n *\n * Based on: [**MediaPipe HandPose**](https://drive.google.com/file/d/1sv4sSb9BSNVZhLzxXJ0jBv9DqD-4jnAz/view)\n */\n\nimport { log } from '../util/util';\nimport * as handdetector from './handposedetector';\nimport * as handpipeline from './handposepipeline';\nimport * as fingerPose from './fingerpose';\nimport { loadModel } from '../tfjs/load';\nimport type { HandResult, Box, Point } from '../result';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nconst meshAnnotations = {\n  thumb: [1, 2, 3, 4],\n  index: [5, 6, 7, 8],\n  middle: [9, 10, 11, 12],\n  ring: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palm: [0],\n};\n\nlet handDetectorModel: GraphModel | null;\nlet handPoseModel: GraphModel | null;\nlet handPipeline: handpipeline.HandPipeline;\n\nexport async function predict(input: Tensor, config: Config): Promise<HandResult[]> {\n  const predictions = await handPipeline.estimateHands(input, config);\n  if (!predictions) return [];\n  const hands: Array<HandResult> = [];\n  for (let i = 0; i < predictions.length; i++) {\n    const annotations = {};\n    if (predictions[i].landmarks) {\n      for (const key of Object.keys(meshAnnotations)) {\n        annotations[key] = meshAnnotations[key].map((index) => predictions[i].landmarks[index]);\n      }\n    }\n    const keypoints = predictions[i].landmarks as unknown as Array<Point>;\n    let box: Box = [Number.MAX_SAFE_INTEGER, Number.MAX_SAFE_INTEGER, 0, 0]; // maximums so conditionals work\n    let boxRaw: Box = [0, 0, 0, 0];\n    if (keypoints && keypoints.length > 0) { // if we have landmarks, calculate box based on landmarks\n      for (const pt of keypoints) {\n        if (pt[0] < box[0]) box[0] = pt[0];\n        if (pt[1] < box[1]) box[1] = pt[1];\n        if (pt[0] > box[2]) box[2] = pt[0];\n        if (pt[1] > box[3]) box[3] = pt[1];\n      }\n      box[2] -= box[0];\n      box[3] -= box[1];\n      boxRaw = [box[0] / (input.shape[2] || 0), box[1] / (input.shape[1] || 0), box[2] / (input.shape[2] || 0), box[3] / (input.shape[1] || 0)];\n    } else { // otherwise use box from prediction\n      box = predictions[i].box ? [\n        Math.trunc(Math.max(0, predictions[i].box.topLeft[0])),\n        Math.trunc(Math.max(0, predictions[i].box.topLeft[1])),\n        Math.trunc(Math.min((input.shape[2] || 0), predictions[i].box.bottomRight[0]) - Math.max(0, predictions[i].box.topLeft[0])),\n        Math.trunc(Math.min((input.shape[1] || 0), predictions[i].box.bottomRight[1]) - Math.max(0, predictions[i].box.topLeft[1])),\n      ] : [0, 0, 0, 0];\n      boxRaw = [\n        (predictions[i].box.topLeft[0]) / (input.shape[2] || 0),\n        (predictions[i].box.topLeft[1]) / (input.shape[1] || 0),\n        (predictions[i].box.bottomRight[0] - predictions[i].box.topLeft[0]) / (input.shape[2] || 0),\n        (predictions[i].box.bottomRight[1] - predictions[i].box.topLeft[1]) / (input.shape[1] || 0),\n      ];\n    }\n    const landmarks = fingerPose.analyze(keypoints);\n    hands.push({\n      id: i,\n      score: Math.round(100 * predictions[i].confidence) / 100,\n      boxScore: Math.round(100 * predictions[i].boxConfidence) / 100,\n      fingerScore: Math.round(100 * predictions[i].fingerConfidence) / 100,\n      label: 'hand',\n      box,\n      boxRaw,\n      keypoints,\n      annotations: annotations as HandResult['annotations'],\n      landmarks: landmarks as HandResult['landmarks'],\n    });\n  }\n  return hands;\n}\n\nexport async function load(config: Config): Promise<[GraphModel | null, GraphModel | null]> {\n  if (env.initial) {\n    handDetectorModel = null;\n    handPoseModel = null;\n  }\n  if (!handDetectorModel || !handPoseModel) {\n    [handDetectorModel, handPoseModel] = await Promise.all([\n      config.hand.enabled ? loadModel(config.hand.detector?.modelPath) : null,\n      config.hand.landmarks ? loadModel(config.hand.skeleton?.modelPath) : null,\n    ]);\n  } else {\n    if (config.debug) log('cached model:', handDetectorModel['modelUrl']);\n    if (config.debug) log('cached model:', handPoseModel['modelUrl']);\n  }\n  const handDetector = new handdetector.HandDetector(handDetectorModel);\n  handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel);\n  return [handDetectorModel, handPoseModel];\n}\n", "/**\n * HandTrack model implementation\n *\n * Based on:\n * - Hand Detection & Skeleton: [**MediaPipe HandPose**](https://drive.google.com/file/d/1sv4sSb9BSNVZhLzxXJ0jBv9DqD-4jnAz/view)\n * - Hand Tracking: [**HandTracking**](https://github.com/victordibia/handtracking)\n */\n\nimport { log, now } from '../util/util';\nimport * as box from '../util/box';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { HandResult, HandType, Box, Point } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\nimport * as fingerPose from './fingerpose';\nimport { fakeOps } from '../tfjs/backend';\nimport { constants } from '../tfjs/constants';\n\nconst models: [GraphModel | null, GraphModel | null] = [null, null];\nconst modelOutputNodes = ['StatefulPartitionedCall/Postprocessor/Slice', 'StatefulPartitionedCall/Postprocessor/ExpandDims_1'];\n\nconst inputSize = [[0, 0], [0, 0]];\n\nconst classes = ['hand', 'fist', 'pinch', 'point', 'face', 'tip', 'pinchtip'];\nconst faceIndex = 4;\n\nconst boxExpandFact = 1.6;\nconst maxDetectorResolution = 512;\nconst detectorExpandFact = 1.4;\n\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet lastTime = 0;\nlet outputSize: [number, number] = [0, 0];\n\ntype HandDetectResult = {\n  id: number,\n  score: number,\n  box: Box,\n  boxRaw: Box,\n  label: HandType,\n}\n\nconst cache: {\n  boxes: Array<HandDetectResult>,\n  hands: Array<HandResult>;\n} = {\n  boxes: [],\n  hands: [],\n};\n\nconst fingerMap = {\n  /*\n  thumb: [0, 1, 2, 3, 4],\n  index: [0, 5, 6, 7, 8],\n  middle: [0, 9, 10, 11, 12],\n  ring: [0, 13, 14, 15, 16],\n  pinky: [0, 17, 18, 19, 20],\n  palm: [0],\n  */\n  thumb: [1, 2, 3, 4],\n  index: [5, 6, 7, 8],\n  middle: [9, 10, 11, 12],\n  ring: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  base: [0],\n  palm: [0, 17, 13, 9, 5, 1, 0],\n};\n\nexport async function loadDetect(config: Config): Promise<GraphModel> {\n  // HandTrack Model: Original: <https://github.com/victordibia/handtracking> TFJS Port: <https://github.com/victordibia/handtrack.js/>\n  if (env.initial) models[0] = null;\n  if (!models[0]) {\n    // handtrack model has some kernel ops defined in model but those are never referenced and non-existent in tfjs\n    // ideally need to prune the model itself\n    fakeOps(['tensorlistreserve', 'enter', 'tensorlistfromtensor', 'merge', 'loopcond', 'switch', 'exit', 'tensorliststack', 'nextiteration', 'tensorlistsetitem', 'tensorlistgetitem', 'reciprocal', 'shape', 'split', 'where'], config);\n    models[0] = await loadModel(config.hand.detector?.modelPath);\n    const inputs = Object.values(models[0].modelSignature['inputs']);\n    inputSize[0][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize[0][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', models[0]['modelUrl']);\n  return models[0];\n}\n\nexport async function loadSkeleton(config: Config): Promise<GraphModel> {\n  if (env.initial) models[1] = null;\n  if (!models[1]) {\n    models[1] = await loadModel(config.hand.skeleton?.modelPath);\n    const inputs = Object.values(models[1].modelSignature['inputs']);\n    inputSize[1][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize[1][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', models[1]['modelUrl']);\n  return models[1];\n}\n\nexport async function load(config: Config): Promise<[GraphModel | null, GraphModel | null]> {\n  if (!models[0]) await loadDetect(config);\n  if (!models[1]) await loadSkeleton(config);\n  return models;\n}\n\nasync function detectHands(input: Tensor, config: Config): Promise<HandDetectResult[]> {\n  const hands: HandDetectResult[] = [];\n  if (!input || !models[0]) return hands;\n  const t: Record<string, Tensor> = {};\n  const ratio = (input.shape[2] || 1) / (input.shape[1] || 1);\n  const height = Math.min(Math.round((input.shape[1] || 0) / 8) * 8, maxDetectorResolution); // use dynamic input size but cap at 512\n  const width = Math.round(height * ratio / 8) * 8;\n  t.resize = tf.image.resizeBilinear(input, [height, width]); // todo: resize with padding\n  t.cast = tf.cast(t.resize, 'int32');\n  [t.rawScores, t.rawBoxes] = await models[0].executeAsync(t.cast, modelOutputNodes) as Tensor[];\n  t.boxes = tf.squeeze(t.rawBoxes, [0, 2]);\n  t.scores = tf.squeeze(t.rawScores, [0]);\n  const classScores: Array<Tensor> = tf.unstack(t.scores, 1); // unstack scores based on classes\n  tf.dispose(classScores[faceIndex]);\n  classScores.splice(faceIndex, 1); // remove faces\n  t.filtered = tf.stack(classScores, 1); // restack\n  tf.dispose(classScores);\n  // t.filtered = t.scores;\n  t.max = tf.max(t.filtered, 1); // max overall score\n  t.argmax = tf.argMax(t.filtered, 1); // class index of max overall score\n  let id = 0;\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.max, (config.hand.maxDetected || 0) + 1, config.hand.iouThreshold || 0, config.hand.minConfidence || 1);\n  const nms = await t.nms.data();\n  const scores = await t.max.data();\n  const classNum = await t.argmax.data();\n  for (const nmsIndex of Array.from(nms)) { // generates results for each class\n    const boxSlice = tf.slice(t.boxes, nmsIndex, 1);\n    const boxYX = await boxSlice.data();\n    tf.dispose(boxSlice);\n    const boxData: Box = [boxYX[1], boxYX[0], boxYX[3] - boxYX[1], boxYX[2] - boxYX[0]]; // yx box reshaped to standard box\n    const boxRaw: Box = box.scale(boxData, detectorExpandFact);\n    const boxFull: Box = [Math.trunc(boxData[0] * outputSize[0]), Math.trunc(boxData[1] * outputSize[1]), Math.trunc(boxData[2] * outputSize[0]), Math.trunc(boxData[3] * outputSize[1])];\n    const score = scores[nmsIndex];\n    const label = classes[classNum[nmsIndex]] as HandType;\n    const hand: HandDetectResult = { id: id++, score, box: boxFull, boxRaw, label };\n    hands.push(hand);\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  hands.sort((a, b) => b.score - a.score);\n  if (hands.length > (config.hand.maxDetected || 1)) hands.length = (config.hand.maxDetected || 1);\n  return hands;\n}\n\nasync function detectFingers(input: Tensor, h: HandDetectResult, config: Config): Promise<HandResult> {\n  const hand: HandResult = { // initial values inherited from hand detect\n    id: h.id,\n    score: Math.round(100 * h.score) / 100,\n    boxScore: Math.round(100 * h.score) / 100,\n    fingerScore: 0,\n    box: h.box,\n    boxRaw: h.boxRaw,\n    label: h.label,\n    keypoints: [],\n    landmarks: {} as HandResult['landmarks'],\n    annotations: {} as HandResult['annotations'],\n  };\n  if (input && models[1] && config.hand.landmarks && h.score > (config.hand.minConfidence || 0)) {\n    const t: Record<string, Tensor> = {};\n    const boxCrop = [h.boxRaw[1], h.boxRaw[0], h.boxRaw[3] + h.boxRaw[1], h.boxRaw[2] + h.boxRaw[0]] as Box;\n    t.crop = tf.image.cropAndResize(input, [boxCrop], [0], [inputSize[1][0], inputSize[1][1]], 'bilinear');\n    t.div = tf.div(t.crop, constants.tf255);\n    [t.score, t.keypoints] = models[1].execute(t.div, ['Identity_1', 'Identity']) as Tensor[];\n    const rawScore = (await t.score.data())[0];\n    const score = (100 - Math.trunc(100 / (1 + Math.exp(rawScore)))) / 100; // reverse sigmoid value\n    if (score >= (config.hand.minConfidence || 0)) {\n      hand.fingerScore = score;\n      t.reshaped = tf.reshape(t.keypoints, [-1, 3]);\n      const coordsData: Point[] = await t.reshaped.array() as Point[];\n      const coordsRaw: Point[] = coordsData.map((kpt) => [kpt[0] / inputSize[1][1], kpt[1] / inputSize[1][0], (kpt[2] || 0)]);\n      const coordsNorm: Point[] = coordsRaw.map((kpt) => [kpt[0] * h.boxRaw[2], kpt[1] * h.boxRaw[3], (kpt[2] || 0)]);\n      hand.keypoints = (coordsNorm).map((kpt) => [outputSize[0] * (kpt[0] + h.boxRaw[0]), outputSize[1] * (kpt[1] + h.boxRaw[1]), (kpt[2] || 0)]);\n      hand.landmarks = fingerPose.analyze(hand.keypoints) as HandResult['landmarks']; // calculate finger gestures\n      for (const key of Object.keys(fingerMap)) { // map keypoints to per-finger annotations\n        hand.annotations[key] = fingerMap[key].map((index: number) => (hand.landmarks && hand.keypoints[index] ? hand.keypoints[index] : null));\n      }\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  }\n  return hand;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<HandResult[]> {\n  if (!models[0] || !models[1] || !models[0]?.inputs[0].shape || !models[1]?.inputs[0].shape) return []; // something is wrong with the model\n  outputSize = [input.shape[2] || 0, input.shape[1] || 0];\n  skipped++; // increment skip frames\n  const skipTime = (config.hand.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.hand.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame) {\n    return cache.hands; // return cached results without running anything\n  }\n  return new Promise(async (resolve) => {\n    const skipTimeExtended = 3 * (config.hand.skipTime || 0) > (now() - lastTime);\n    const skipFrameExtended = skipped < 3 * (config.hand.skipFrames || 0);\n    if (config.skipAllowed && cache.hands.length === config.hand.maxDetected) { // we have all detected hands so we're definitely skipping\n      cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));\n    } else if (config.skipAllowed && skipTimeExtended && skipFrameExtended && cache.hands.length > 0) { // we have some cached results: maybe not enough but anyhow continue for bit longer\n      cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));\n    } else { // finally rerun detector\n      cache.boxes = await detectHands(input, config);\n      lastTime = now();\n      cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));\n      skipped = 0;\n    }\n\n    const oldCache = [...cache.boxes];\n    cache.boxes.length = 0; // reset cache\n    if (config.cacheSensitivity > 0) {\n      for (let i = 0; i < cache.hands.length; i++) {\n        const boxKpt = box.square(cache.hands[i].keypoints, outputSize);\n        if (boxKpt.box[2] / (input.shape[2] || 1) > 0.05 && boxKpt.box[3] / (input.shape[1] || 1) > 0.05 && cache.hands[i].fingerScore && cache.hands[i].fingerScore > (config.hand.minConfidence || 0)) {\n          const boxScale = box.scale(boxKpt.box, boxExpandFact);\n          const boxScaleRaw = box.scale(boxKpt.boxRaw, boxExpandFact);\n          // const boxCrop = box.crop(boxScaleRaw);\n          cache.boxes.push({ ...oldCache[i], box: boxScale, boxRaw: boxScaleRaw });\n        }\n      }\n    }\n    for (let i = 0; i < cache.hands.length; i++) { // replace detected boxes with calculated boxes in final output\n      const bbox = box.calc(cache.hands[i].keypoints, outputSize);\n      cache.hands[i].box = bbox.box;\n      cache.hands[i].boxRaw = bbox.boxRaw;\n    }\n    resolve(cache.hands);\n  });\n}\n", "/**\n * Anti-spoofing model implementation\n */\n\nimport { log, now } from '../util/util';\nimport { loadModel } from '../tfjs/load';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst cached: Array<number> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet lastCount = 0;\nlet lastTime = 0;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.liveness?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<number> {\n  if (!model) return 0;\n  const skipTime = (config.face.liveness?.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.face.liveness?.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && cached[idx]) {\n    skipped++;\n    return cached[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape ? model.inputs[0].shape[2] : 0, model?.inputs[0].shape ? model.inputs[0].shape[1] : 0], false);\n    const res = model?.execute(resize) as Tensor;\n    const num = (await res.data())[0];\n    cached[idx] = Math.round(100 * num) / 100;\n    lastCount = count;\n    lastTime = now();\n    tf.dispose([resize, res]);\n    resolve(cached[idx]);\n  });\n}\n", "export const kpt: Array<string> = [ // used to create part labels\n  'nose',\n  'leftEye',\n  'rightEye',\n  'leftEar',\n  'rightEar',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n];\n\nexport const horizontal: Array<string[]> = [ // used to fix left vs right\n  ['leftEye', 'rightEye'],\n  ['leftEar', 'rightEar'],\n  ['leftShoulder', 'rightShoulder'],\n  ['leftElbow', 'rightElbow'],\n  ['leftWrist', 'rightWrist'],\n  ['leftHip', 'rightHip'],\n  ['leftKnee', 'rightKnee'],\n  ['leftAnkle', 'rightAnkle'],\n];\n\nexport const vertical: Array<string[]> = [ // used to remove unlikely keypoint positions\n  ['leftKnee', 'leftShoulder'],\n  ['rightKnee', 'rightShoulder'],\n  ['leftAnkle', 'leftKnee'],\n  ['rightAnkle', 'rightKnee'],\n];\n\nexport const relative: Array<string[][]> = [ // used to match relative body parts\n  [['leftHip', 'rightHip'], ['leftShoulder', 'rightShoulder']],\n  [['leftElbow', 'rightElbow'], ['leftShoulder', 'rightShoulder']],\n];\n\nexport const connected: Record<string, string[]> = { // used to create body outline in annotations\n  leftLeg: ['leftHip', 'leftKnee', 'leftAnkle'],\n  rightLeg: ['rightHip', 'rightKnee', 'rightAnkle'],\n  torso: ['leftShoulder', 'rightShoulder', 'rightHip', 'leftHip', 'leftShoulder'],\n  leftArm: ['leftShoulder', 'leftElbow', 'leftWrist'],\n  rightArm: ['rightShoulder', 'rightElbow', 'rightWrist'],\n  head: [],\n};\n", "import type { BodyKeypoint, BodyResult } from '../result';\nimport * as box from '../util/box';\nimport * as coords from './movenetcoords';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from '../tfjs/types';\n\nconst maxJitter = 0.005; // default allowed jitter is within 0.5%\n\nconst cache: {\n  keypoints: Array<BodyKeypoint>,\n  padding: [number, number][];\n} = {\n  keypoints: [],\n  padding: [[0, 0], [0, 0], [0, 0], [0, 0]],\n};\n\nexport function bodyParts(body: BodyResult) { // model sometimes mixes up left vs right keypoints so we fix them\n  for (const pair of coords.horizontal) { // fix body parts left vs right\n    const left = body.keypoints.findIndex((kp) => kp.part === pair[0]);\n    const right = body.keypoints.findIndex((kp) => kp.part === pair[1]);\n    if (body.keypoints[left] && body.keypoints[right]) {\n      if (body.keypoints[left].position[0] < body.keypoints[right].position[0]) {\n        const tmp = body.keypoints[left];\n        body.keypoints[left] = body.keypoints[right];\n        body.keypoints[right] = tmp;\n      }\n    }\n  }\n  for (const pair of coords.vertical) { // remove body parts with improbable vertical position\n    const lower = body.keypoints.findIndex((kp) => (kp && kp.part === pair[0]));\n    const higher = body.keypoints.findIndex((kp) => (kp && kp.part === pair[1]));\n    if (body.keypoints[lower] && body.keypoints[higher]) {\n      if (body.keypoints[lower].position[1] < body.keypoints[higher].position[1]) {\n        body.keypoints.splice(lower, 1);\n      }\n    }\n  }\n  for (const [pair, compare] of coords.relative) { // rearrange body parts according to their relative position\n    const left = body.keypoints.findIndex((kp) => (kp && kp.part === pair[0]));\n    const right = body.keypoints.findIndex((kp) => (kp && kp.part === pair[1]));\n    const leftTo = body.keypoints.findIndex((kp) => (kp && kp.part === compare[0]));\n    const rightTo = body.keypoints.findIndex((kp) => (kp && kp.part === compare[1]));\n    if (!body.keypoints[leftTo] || !body.keypoints[rightTo]) continue; // only if we have both compare points\n    const distanceLeft = body.keypoints[left] ? [\n      Math.abs(body.keypoints[leftTo].position[0] - body.keypoints[left].position[0]),\n      Math.abs(body.keypoints[rightTo].position[0] - body.keypoints[left].position[0]),\n    ] : [0, 0];\n    const distanceRight = body.keypoints[right] ? [\n      Math.abs(body.keypoints[rightTo].position[0] - body.keypoints[right].position[0]),\n      Math.abs(body.keypoints[leftTo].position[0] - body.keypoints[right].position[0]),\n    ] : [0, 0];\n    if (distanceLeft[0] > distanceLeft[1] || distanceRight[0] > distanceRight[1]) { // should flip keypoints\n      const tmp = body.keypoints[left];\n      body.keypoints[left] = body.keypoints[right];\n      body.keypoints[right] = tmp;\n    }\n  }\n}\n\nexport function jitter(keypoints: Array<BodyKeypoint>): Array<BodyKeypoint> {\n  for (let i = 0; i < keypoints.length; i++) {\n    if (keypoints[i] && cache.keypoints[i]) {\n      const diff = [Math.abs(keypoints[i].positionRaw[0] - cache.keypoints[i].positionRaw[0]), Math.abs(keypoints[i].positionRaw[1] - cache.keypoints[i].positionRaw[1])];\n      if (diff[0] < maxJitter && diff[1] < maxJitter) {\n        keypoints[i] = cache.keypoints[i]; // below jitter so replace keypoint\n      } else {\n        cache.keypoints[i] = keypoints[i]; // above jitter so update cache\n      }\n    } else {\n      cache.keypoints[i] = keypoints[i]; // cache for keypoint doesnt exist so create it here\n    }\n  }\n  return keypoints;\n}\n\nexport function padInput(input: Tensor, inputSize: number): Tensor {\n  const t: Record<string, Tensor> = {};\n  if (!input.shape || !input.shape[1] || !input.shape[2]) return input;\n  cache.padding = [\n    [0, 0], // dont touch batch\n    [input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0, input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0], // height before&after\n    [input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0, input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0], // width before&after\n    [0, 0], // dont touch rbg\n  ];\n  t.pad = tf.pad(input, cache.padding);\n  t.resize = tf.image.resizeBilinear(t.pad, [inputSize, inputSize]);\n  const final = tf.cast(t.resize, 'int32');\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return final;\n}\n\nexport function rescaleBody(body: BodyResult, outputSize: [number, number]): BodyResult {\n  body.keypoints = body.keypoints.filter((kpt) => kpt && kpt.position); // filter invalid keypoints\n  for (const kpt of body.keypoints) {\n    kpt.position = [\n      kpt.position[0] * (outputSize[0] + cache.padding[2][0] + cache.padding[2][1]) / outputSize[0] - cache.padding[2][0],\n      kpt.position[1] * (outputSize[1] + cache.padding[1][0] + cache.padding[1][1]) / outputSize[1] - cache.padding[1][0],\n    ];\n    kpt.positionRaw = [\n      kpt.position[0] / outputSize[0], kpt.position[1] / outputSize[1],\n    ];\n  }\n  const rescaledBoxes = box.calc(body.keypoints.map((pt) => pt.position), outputSize);\n  body.box = rescaledBoxes.box;\n  body.boxRaw = rescaledBoxes.boxRaw;\n  return body;\n}\n", "/**\n * MoveNet model implementation\n *\n * Based on: [**MoveNet**](https://blog.tensorflow.org/2021/05/next-generation-pose-detection-with-movenet-and-tensorflowjs.html)\n */\n\nimport { log, now } from '../util/util';\nimport * as box from '../util/box';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as coords from './movenetcoords';\nimport * as fix from './movenetfix';\nimport { loadModel } from '../tfjs/load';\nimport type { BodyKeypoint, BodyResult, BodyLandmark, BodyAnnotation, Box, Point } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { fakeOps } from '../tfjs/backend';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nlet inputSize = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n// const boxExpandFact = 1.5; // increase to 150%\n\nconst cache: {\n  boxes: Array<Box>, // unused\n  bodies: Array<BodyResult>;\n  last: number,\n} = {\n  boxes: [],\n  bodies: [],\n  last: 0,\n};\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) {\n    fakeOps(['size'], config);\n    model = await loadModel(config.body.modelPath);\n  } else if (config.debug) log('cached model:', model['modelUrl']);\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  if (inputSize < 64) inputSize = 256;\n  return model;\n}\n\nasync function parseSinglePose(res, config, image) {\n  const kpt = res[0][0];\n  const keypoints: Array<BodyKeypoint> = [];\n  let score = 0;\n  for (let id = 0; id < kpt.length; id++) {\n    score = kpt[id][2];\n    if (score > config.body.minConfidence) {\n      const positionRaw: Point = [kpt[id][1], kpt[id][0]];\n      keypoints.push({\n        score: Math.round(100 * score) / 100,\n        part: coords.kpt[id] as BodyLandmark,\n        positionRaw,\n        position: [ // normalized to input image size\n          Math.round((image.shape[2] || 0) * positionRaw[0]),\n          Math.round((image.shape[1] || 0) * positionRaw[1]),\n        ],\n      });\n    }\n  }\n  score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n  const bodies: Array<BodyResult> = [];\n  const newBox = box.calc(keypoints.map((pt) => pt.position), [image.shape[2], image.shape[1]]);\n  const annotations: Record<string, Point[][]> = {};\n  for (const [name, indexes] of Object.entries(coords.connected)) {\n    const pt: Array<Point[]> = [];\n    for (let i = 0; i < indexes.length - 1; i++) {\n      const pt0 = keypoints.find((kp) => kp.part === indexes[i]);\n      const pt1 = keypoints.find((kp) => kp.part === indexes[i + 1]);\n      if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n    }\n    annotations[name] = pt;\n  }\n  const body: BodyResult = { id: 0, score, box: newBox.box, boxRaw: newBox.boxRaw, keypoints, annotations };\n  fix.bodyParts(body);\n  bodies.push(body);\n  return bodies;\n}\n\nasync function parseMultiPose(res, config, image) {\n  const bodies: Array<BodyResult> = [];\n  for (let id = 0; id < res[0].length; id++) {\n    const kpt = res[0][id];\n    const totalScore = Math.round(100 * kpt[51 + 4]) / 100;\n    if (totalScore > config.body.minConfidence) {\n      const keypoints: Array<BodyKeypoint> = [];\n      for (let i = 0; i < 17; i++) {\n        const score = kpt[3 * i + 2];\n        if (score > config.body.minConfidence) {\n          const positionRaw: Point = [kpt[3 * i + 1], kpt[3 * i + 0]];\n          keypoints.push({\n            part: coords.kpt[i] as BodyLandmark,\n            score: Math.round(100 * score) / 100,\n            positionRaw,\n            position: [Math.round((image.shape[2] || 0) * positionRaw[0]), Math.round((image.shape[1] || 0) * positionRaw[1])],\n          });\n        }\n      }\n      const newBox = box.calc(keypoints.map((pt) => pt.position), [image.shape[2], image.shape[1]]);\n      // movenet-multipose has built-in box details\n      // const boxRaw: Box = [kpt[51 + 1], kpt[51 + 0], kpt[51 + 3] - kpt[51 + 1], kpt[51 + 2] - kpt[51 + 0]];\n      // const box: Box = [Math.trunc(boxRaw[0] * (image.shape[2] || 0)), Math.trunc(boxRaw[1] * (image.shape[1] || 0)), Math.trunc(boxRaw[2] * (image.shape[2] || 0)), Math.trunc(boxRaw[3] * (image.shape[1] || 0))];\n      const annotations: Record<BodyAnnotation, Point[][]> = {} as Record<BodyAnnotation, Point[][]>;\n      for (const [name, indexes] of Object.entries(coords.connected)) {\n        const pt: Array<Point[]> = [];\n        for (let i = 0; i < indexes.length - 1; i++) {\n          const pt0 = keypoints.find((kp) => kp.part === indexes[i]);\n          const pt1 = keypoints.find((kp) => kp.part === indexes[i + 1]);\n          if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n        }\n        annotations[name] = pt;\n      }\n      const body: BodyResult = { id, score: totalScore, box: newBox.box, boxRaw: newBox.boxRaw, keypoints: [...keypoints], annotations };\n      fix.bodyParts(body);\n      bodies.push(body);\n    }\n  }\n  bodies.sort((a, b) => b.score - a.score);\n  if (bodies.length > config.body.maxDetected) bodies.length = config.body.maxDetected;\n  return bodies;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {\n  if (!model || !model?.inputs[0].shape) return []; // something is wrong with the model\n  if (!config.skipAllowed) cache.boxes.length = 0; // allowed to use cache or not\n  skipped++; // increment skip frames\n  const skipTime = (config.body.skipTime || 0) > (now() - cache.last);\n  const skipFrame = skipped < (config.body.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame) {\n    return cache.bodies; // return cached results without running anything\n  }\n  return new Promise(async (resolve) => {\n    const t: Record<string, Tensor> = {};\n    skipped = 0;\n    // run detection on squared input and cached boxes\n    /*\n    cache.bodies = []; // reset bodies result\n    if (cache.boxes.length >= (config.body.maxDetected || 0)) { // if we have enough cached boxes run detection using cache\n      for (let i = 0; i < cache.boxes.length; i++) { // run detection based on cached boxes\n        t.crop = tf.image.cropAndResize(input, [cache.boxes[i]], [0], [inputSize, inputSize], 'bilinear');\n        t.cast = tf.cast(t.crop, 'int32');\n        // t.input = prepareImage(input);\n        t.res = model?.execute(t.cast) as Tensor;\n        const res = await t.res.array();\n        const newBodies = (t.res.shape[2] === 17) ? await parseSinglePose(res, config, input, cache.boxes[i]) : await parseMultiPose(res, config, input, cache.boxes[i]);\n        cache.bodies = cache.bodies.concat(newBodies);\n        Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n      }\n    }\n    if (cache.bodies.length !== config.body.maxDetected) { // did not find enough bodies based on cached boxes so run detection on full frame\n      t.input = prepareImage(input);\n      t.res = model?.execute(t.input) as Tensor;\n      const res = await t.res.array();\n      cache.bodies = (t.res.shape[2] === 17) ? await parseSinglePose(res, config, input, [0, 0, 1, 1]) : await parseMultiPose(res, config, input, [0, 0, 1, 1]);\n      for (const body of cache.bodies) rescaleBody(body, [input.shape[2] || 1, input.shape[1] || 1]);\n      Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    }\n    cache.boxes.length = 0; // reset cache\n    for (let i = 0; i < cache.bodies.length; i++) {\n      if (cache.bodies[i].keypoints.length > (coords.kpt.length / 2)) { // only update cache if we detected at least half keypoints\n        const scaledBox = box.scale(cache.bodies[i].boxRaw, boxExpandFact);\n        const cropBox = box.crop(scaledBox);\n        cache.boxes.push(cropBox);\n      }\n    }\n    */\n\n    // run detection on squared input and no cached boxes\n    t.input = fix.padInput(input, inputSize);\n    t.res = model?.execute(t.input) as Tensor;\n    cache.last = now();\n    const res = await t.res.array();\n    cache.bodies = (t.res.shape[2] === 17)\n      ? await parseSinglePose(res, config, input)\n      : await parseMultiPose(res, config, input);\n    for (const body of cache.bodies) {\n      fix.rescaleBody(body, [input.shape[2] || 1, input.shape[1] || 1]);\n      fix.jitter(body.keypoints);\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n\n    resolve(cache.bodies);\n  });\n}\n", "/**\n * NanoDet object detection model implementation\n *\n * Based on: [**MB3-CenterNet**](https://github.com/610265158/mobilenetv3_centernet)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport { labels } from './labels';\nimport type { ObjectResult, ObjectType, Box } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel;\nlet last: Array<ObjectResult> = [];\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet inputSize = 0;\n\nconst scaleBox = 2.5; // increase box size\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (!model || env.initial) {\n    model = await loadModel(config.object.modelPath);\n    const inputs = Object.values(model.modelSignature['inputs']);\n    inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nasync function process(res: Tensor[], outputShape: [number, number], config: Config) {\n  let id = 0;\n  let results: Array<ObjectResult> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(async () => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      const scoresT = tf.squeeze(res.find((a: Tensor) => (a.shape[1] === (baseSize ** 2) && (a.shape[2] || 0) === labels.length)));\n      const featuresT = tf.squeeze(res.find((a: Tensor) => (a.shape[1] === (baseSize ** 2) && (a.shape[2] || 0) < labels.length)));\n      const boxesMax = featuresT.reshape([-1, 4, featuresT.shape[1] / 4]); // reshape [output] to [4, output / 4] where number is number of different features inside each stride\n      const boxIdx = await boxesMax.argMax(2).array(); // what we need is indexes of features with highest scores, not values itself\n      const scores = await scoresT.array(); // optionally use exponential scores or just as-is\n      for (let i = 0; i < scoresT.shape[0]; i++) { // total strides (x * y matrix)\n        for (let j = 0; j < scoresT.shape[1]; j++) { // one score for each class\n          const score = scores[i][j]; // get score for current position\n          if (score > (config.object.minConfidence || 0) && j !== 61) {\n            const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n            const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n            const boxOffset = boxIdx[i].map((a: number) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n            const [x, y] = [\n              cx - (scaleBox / strideSize * boxOffset[0]),\n              cy - (scaleBox / strideSize * boxOffset[1]),\n            ];\n            const [w, h] = [\n              cx + (scaleBox / strideSize * boxOffset[2]) - x,\n              cy + (scaleBox / strideSize * boxOffset[3]) - y,\n            ];\n            let boxRaw: Box = [x, y, w, h]; // results normalized to range 0..1\n            boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))) as Box; // fix out-of-bounds coords\n            const box = [ // results normalized to input image pixels\n              boxRaw[0] * outputShape[0],\n              boxRaw[1] * outputShape[1],\n              boxRaw[2] * outputShape[0],\n              boxRaw[3] * outputShape[1],\n            ];\n            const result = {\n              id: id++,\n              // strideSize,\n              score: Math.round(100 * score) / 100,\n              class: j + 1,\n              label: labels[j].label as ObjectType,\n              // center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n              // centerRaw: [cx, cy],\n              box: box.map((a) => Math.trunc(a)) as Box,\n              boxRaw,\n            };\n            results.push(result);\n          }\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => [a.boxRaw[1], a.boxRaw[0], a.boxRaw[3], a.boxRaw[2]]); // switches coordinates from x,y to y,x as expected by tf.nms\n  const nmsScores = results.map((a) => a.score);\n  let nmsIdx: Array<number> = [];\n  if (nmsBoxes && nmsBoxes.length > 0) {\n    const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxDetected, config.object.iouThreshold, config.object.minConfidence);\n    nmsIdx = await nms.data();\n    tf.dispose(nms);\n  }\n\n  // filter & sort results\n  results = results\n    .filter((_val, idx) => nmsIdx.includes(idx))\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image: Tensor, config: Config): Promise<ObjectResult[]> {\n  const skipTime = (config.object.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.object.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  skipped = 0;\n  if (!env.kernels.includes('mod') || !env.kernels.includes('sparsetodense')) return last;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2] || 0, image.shape[1] || 0];\n    const resize = tf.image.resizeBilinear(image, [inputSize, inputSize], false);\n    const norm = tf.div(resize, constants.tf255);\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    tf.dispose(norm);\n    tf.dispose(resize);\n\n    let objectT;\n    if (config.object.enabled) objectT = model.execute(transpose);\n    lastTime = now();\n    tf.dispose(transpose);\n\n    const obj = await process(objectT as Tensor[], outputSize as [number, number], config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "/**\n * PoseNet body detection model implementation constants\n * See `posenet.ts` for entry point\n */\n\nimport type { Point, BodyResult, BodyAnnotation, BodyLandmark } from '../result';\n\nexport const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const count = partNames.length; // 17 keypoints\n\nexport const partIds = partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport function eitherPointDoesntMeetConfidence(a: number, b: number, minConfidence: number) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence: number) {\n  return connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nexport function getBoundingBox(keypoints): [number, number, number, number] {\n  const coord = keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: Number.NEGATIVE_INFINITY,\n    maxY: Number.NEGATIVE_INFINITY,\n    minX: Number.POSITIVE_INFINITY,\n    minY: Number.POSITIVE_INFINITY,\n  });\n  return [coord.minX, coord.minY, coord.maxX - coord.minX, coord.maxY - coord.minY];\n}\n\nexport function scalePoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]): Array<BodyResult> {\n  const scaleY = height / inputResolutionHeight;\n  const scaleX = width / inputResolutionWidth;\n  const scalePose = (pose, i): BodyResult => ({\n    id: i,\n    score: pose.score,\n    boxRaw: [pose.box[0] / inputResolutionWidth, pose.box[1] / inputResolutionHeight, pose.box[2] / inputResolutionWidth, pose.box[3] / inputResolutionHeight],\n    box: [Math.trunc(pose.box[0] * scaleX), Math.trunc(pose.box[1] * scaleY), Math.trunc(pose.box[2] * scaleX), Math.trunc(pose.box[3] * scaleY)],\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score: score as number,\n      part: part as BodyLandmark,\n      position: [Math.trunc(position.x * scaleX), Math.trunc(position.y * scaleY)] as Point,\n      positionRaw: [position.x / inputResolutionHeight, position.y / inputResolutionHeight] as Point,\n    })),\n    annotations: {} as Record<BodyAnnotation, Point[][]>,\n  });\n  const scaledPoses = poses.map((pose, i) => scalePose(pose, i));\n  return scaledPoses;\n}\n\n// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nexport class MaxHeap {\n  priorityQueue: Array<unknown>; // don't touch\n  numberOfElements: number;\n  getElementValue: unknown; // function call\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() { return this.numberOfElements === -1; }\n\n  size() { return this.numberOfElements + 1; }\n\n  all() { return this.priorityQueue.slice(0, this.numberOfElements + 1); }\n\n  max() { return this.priorityQueue[0]; }\n\n  swim(k) {\n    while (k > 0 && this.less(Math.floor(k / 2), k)) {\n      this.exchange(k, Math.floor(k / 2));\n      k = Math.floor(k / 2);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    // @ts-ignore getter is of unknown type\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + count),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "/**\n * PoseNet body detection model implementation\n *\n * Based on: [**PoseNet**](https://medium.com/tensorflow/real-time-human-pose-estimation-in-the-browser-with-tensorflow-js-7dd0bc881cd5)\n */\n\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { BodyResult, BodyLandmark, Box } from '../result';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\nimport * as utils from './posenetutils';\n\nlet model: GraphModel;\nconst poseNetOutputs = ['MobilenetV1/offset_2/BiasAdd'/* offsets */, 'MobilenetV1/heatmap_2/BiasAdd'/* heatmapScores */, 'MobilenetV1/displacement_fwd_2/BiasAdd'/* displacementFwd */, 'MobilenetV1/displacement_bwd_2/BiasAdd'/* displacementBwd */];\nconst localMaximumRadius = 1;\nconst outputStride = 16;\nconst squaredNmsRadius = 50 ** 2;\n\nfunction traverse(edgeId, sourceKeypoint, targetId, scores, offsets, displacements, offsetRefineStep = 2) {\n  const getDisplacement = (point) => ({\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, (displacements.shape[2] / 2) + edgeId),\n  });\n  const getStridedIndexNearPoint = (point, height, width) => ({\n    y: utils.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: utils.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  });\n\n  const [height, width] = scores.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, height, width);\n  const displacement = getDisplacement(sourceKeypointIndices);\n  const displacedPoint = utils.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, height, width);\n    const offsetPoint = utils.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetId, offsets);\n    targetKeypoint = utils.addVectors(\n      { x: targetKeypointIndices.x * outputStride, y: targetKeypointIndices.y * outputStride },\n      { x: offsetPoint.x, y: offsetPoint.y },\n    );\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, height, width);\n  const score = scores.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetId);\n  return { position: targetKeypoint, part: utils.partNames[targetId], score };\n}\n\nexport function decodePose(root, scores, offsets, displacementsFwd, displacementsBwd) {\n  const tuples = utils.poseChain.map(([parentJoinName, childJoinName]) => ([utils.partIds[parentJoinName], utils.partIds[childJoinName]]));\n  const edgesFwd = tuples.map(([, childJointId]) => childJointId);\n  const edgesBwd = tuples.map(([parentJointId]) => parentJointId);\n  const numParts = scores.shape[2]; // [21,21,17]\n  const numEdges = edgesFwd.length;\n  const keypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const rootPoint = utils.getImageCoords(root.part, outputStride, offsets);\n  keypoints[root.part.id] = {\n    score: root.score,\n    part: utils.partNames[root.part.id] as BodyLandmark,\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceId = edgesFwd[edge];\n    const targetId = edgesBwd[edge];\n    if (keypoints[sourceId] && !keypoints[targetId]) {\n      keypoints[targetId] = traverse(edge, keypoints[sourceId], targetId, scores, offsets, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceId = edgesBwd[edge];\n    const targetId = edgesFwd[edge];\n    if (keypoints[sourceId] && !keypoints[targetId]) {\n      keypoints[targetId] = traverse(edge, keypoints[sourceId], targetId, scores, offsets, displacementsFwd);\n    }\n  }\n  return keypoints;\n}\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(minConfidence, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new utils.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < minConfidence) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, scores)) queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n      }\n    }\n  }\n  return queue;\n}\n\nfunction withinRadius(poses, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId]?.position;\n    if (!correspondingKeypoint) return false;\n    return utils.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, keypoints) {\n  const notOverlappedKeypointScores = keypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinRadius(existingPoses, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / keypoints.length;\n}\n\nexport function decode(offsets, scores, displacementsFwd, displacementsBwd, maxDetected, minConfidence) {\n  const poses: Array<{ keypoints, box: Box, score: number }> = [];\n  const queue = buildPartWithScoreQueue(minConfidence, scores);\n  // Generate at most maxDetected object instances per image in decreasing root part score order.\n  while (poses.length < maxDetected && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    // @ts-ignore this one is tree walk\n    const rootImageCoords = utils.getImageCoords(root.part, outputStride, offsets);\n    // @ts-ignore this one is tree walk\n    if (withinRadius(poses, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    let keypoints = decodePose(root, scores, offsets, displacementsFwd, displacementsBwd);\n    keypoints = keypoints.filter((a) => a.score > minConfidence);\n    const score = getInstanceScore(poses, keypoints);\n    const box = utils.getBoundingBox(keypoints);\n    if (score > minConfidence) poses.push({ keypoints, box, score: Math.round(100 * score) / 100 });\n  }\n  return poses;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {\n  /** posenet is mostly obsolete\n   * caching is not implemented\n   */\n  const res = tf.tidy(() => {\n    if (!model.inputs[0].shape) return [];\n    const resized = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n    const normalized = tf.sub(tf.div(tf.cast(resized, 'float32'), 127.5), 1.0);\n    const results: Array<Tensor> = model.execute(normalized, poseNetOutputs) as Array<Tensor>;\n    const results3d = results.map((y) => tf.squeeze(y, [0]));\n    results3d[1] = tf.sigmoid(results3d[1]); // apply sigmoid on scores\n    return results3d;\n  });\n\n  const buffers = await Promise.all(res.map((tensor: Tensor) => tensor.buffer()));\n  for (const t of res) tf.dispose(t);\n\n  const decoded = await decode(buffers[0], buffers[1], buffers[2], buffers[3], config.body.maxDetected, config.body.minConfidence);\n  if (!model.inputs[0].shape) return [];\n  const scaled = utils.scalePoses(decoded, [input.shape[1], input.shape[2]], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) as BodyResult[];\n  return scaled;\n}\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (!model || env.initial) model = await loadModel(config.body.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n", "/**\n * Image segmentation for body detection model\n *\n * Based on:\n * - [**MediaPipe Meet**](https://drive.google.com/file/d/1lnP1bRi9CSqQQXUHa13159vLELYDgDu0/preview)\n * - [**MediaPipe Selfie**](https://drive.google.com/file/d/1dCfozqknMa068vVsO2j_1FgZkW_e3VWv/preview)\n */\n\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport * as image from '../image/image';\nimport { constants } from '../tfjs/constants';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\nimport type { Input, AnyCanvas } from '../exports';\n\nlet model: GraphModel;\nlet busy = false;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (!model || env.initial) model = await loadModel(config.segmentation.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function process(input: Input, background: Input | undefined, config: Config)\n: Promise<{ data: Array<number> | Tensor, canvas: AnyCanvas | null, alpha: AnyCanvas | null }> {\n  if (busy) return { data: [], canvas: null, alpha: null };\n  busy = true;\n  if (!model) await load(config);\n  const inputImage = await image.process(input, config);\n  const width = inputImage.tensor?.shape[2] || 0;\n  const height = inputImage.tensor?.shape[1] || 0;\n  if (!inputImage.tensor) return { data: [], canvas: null, alpha: null };\n  const t: Record<string, Tensor> = {};\n\n  t.resize = tf.image.resizeBilinear(inputImage.tensor, [model.inputs[0].shape ? model.inputs[0].shape[1] : 0, model.inputs[0].shape ? model.inputs[0].shape[2] : 0], false);\n  tf.dispose(inputImage.tensor);\n  t.norm = tf.div(t.resize, constants.tf255);\n  t.res = model.execute(t.norm) as Tensor;\n\n  t.squeeze = tf.squeeze(t.res, 0); // meet.shape:[1,256,256,1], selfie.shape:[1,144,256,2]\n  if (t.squeeze.shape[2] === 2) {\n    t.softmax = tf.softmax(t.squeeze); // model meet has two channels for fg and bg\n    [t.bg, t.fg] = tf.unstack(t.softmax, 2);\n    t.expand = tf.expandDims(t.fg, 2);\n    t.pad = tf.expandDims(t.expand, 0);\n    t.crop = tf.image.cropAndResize(t.pad, [[0, 0, 0.5, 0.5]], [0], [width, height]);\n    // running sofmax before unstack creates 2x2 matrix so we only take upper-left quadrant\n    // otherwise run softmax after unstack and use standard resize\n    // resizeOutput = tf.image.resizeBilinear(expand, [input.tensor?.shape[1], input.tensor?.shape[2]]);\n    t.data = tf.squeeze(t.crop, 0);\n  } else {\n    t.data = tf.image.resizeBilinear(t.squeeze, [height, width]); // model selfie has a single channel that we can use directly\n  }\n  const data = Array.from(await t.data.data()) as number[];\n\n  if (env.node && !env.Canvas && (typeof ImageData === 'undefined')) {\n    if (config.debug) log('canvas support missing');\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return { data, canvas: null, alpha: null }; // running in nodejs so return alpha array as-is\n  }\n\n  const alphaCanvas = image.canvas(width, height);\n  // @ts-ignore browser is not defined in tfjs-node\n  if (tf.browser) await tf.browser.toPixels(t.data, alphaCanvas);\n  const alphaCtx = alphaCanvas.getContext('2d') as CanvasRenderingContext2D;\n  if (config.segmentation.blur && config.segmentation.blur > 0) alphaCtx.filter = `blur(${config.segmentation.blur}px)`; // use css filter for bluring, can be done with gaussian blur manually instead\n  const alphaData = alphaCtx.getImageData(0, 0, width, height);\n\n  const compositeCanvas = image.canvas(width, height);\n  const compositeCtx = compositeCanvas.getContext('2d') as CanvasRenderingContext2D;\n  if (inputImage.canvas) compositeCtx.drawImage(inputImage.canvas, 0, 0);\n  compositeCtx.globalCompositeOperation = 'darken'; // https://developer.mozilla.org/en-US/docs/Web/API/CanvasRenderingContext2D/globalCompositeOperation // best options are: darken, color-burn, multiply\n  if (config.segmentation.blur && config.segmentation.blur > 0) compositeCtx.filter = `blur(${config.segmentation.blur}px)`; // use css filter for bluring, can be done with gaussian blur manually instead\n  compositeCtx.drawImage(alphaCanvas, 0, 0);\n  compositeCtx.globalCompositeOperation = 'source-over'; // reset composite operation\n  compositeCtx.filter = 'none'; // reset css filter\n  const compositeData = compositeCtx.getImageData(0, 0, width, height);\n  for (let i = 0; i < width * height; i++) compositeData.data[4 * i + 3] = alphaData.data[4 * i + 0]; // copy original alpha value to new composite canvas\n  compositeCtx.putImageData(compositeData, 0, 0);\n\n  let mergedCanvas: AnyCanvas | null = null;\n  if (background && compositeCanvas) { // draw background with segmentation as overlay if background is present\n    mergedCanvas = image.canvas(width, height);\n    const bgImage = await image.process(background, config);\n    tf.dispose(bgImage.tensor);\n    const ctxMerge = mergedCanvas.getContext('2d') as CanvasRenderingContext2D;\n    ctxMerge.drawImage(bgImage.canvas as HTMLCanvasElement, 0, 0, mergedCanvas.width, mergedCanvas.height);\n    ctxMerge.drawImage(compositeCanvas, 0, 0);\n  }\n\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  busy = false;\n  // return { data, canvas: mergedCanvas || compositeCanvas, alpha: alphaCanvas };\n  return { data, canvas: compositeCanvas, alpha: alphaCanvas };\n}\n", "/** TFJS custom backend registration */\n\nimport type { Human } from '../human';\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as image from '../image/image';\nimport * as models from '../models';\nimport type { AnyCanvas } from '../exports';\n// import { env } from '../env';\n\nexport const config = {\n  name: 'humangl',\n  priority: 999,\n  canvas: <null | AnyCanvas>null,\n  gl: <null | WebGL2RenderingContext>null,\n  extensions: <string[]> [],\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nfunction extensions(): void {\n  /*\n  https://www.khronos.org/registry/webgl/extensions/\n  https://webglreport.com/?v=2\n  */\n  const gl = config.gl;\n  if (!gl) return;\n  config.extensions = gl.getSupportedExtensions() as string[];\n  // gl.getExtension('KHR_parallel_shader_compile');\n}\n\n/**\n * Registers custom WebGL2 backend to be used by Human library\n *\n * @returns void\n */\nexport async function register(instance: Human): Promise<void> {\n  // force backend reload if gl context is not valid\n  if (instance.config.backend !== 'humangl') return;\n  if ((config.name in tf.engine().registry) && (!config.gl || !config.gl.getParameter(config.gl.VERSION))) {\n    log('error: humangl backend invalid context');\n    models.reset(instance);\n    /*\n    log('resetting humangl backend');\n    await tf.removeBackend(config.name);\n    await register(instance); // re-register\n    */\n  }\n  if (!tf.findBackend(config.name)) {\n    try {\n      config.canvas = await image.canvas(100, 100);\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      config.gl = config.canvas?.getContext('webgl2', config.webGLattr) as WebGL2RenderingContext;\n      const glv2 = config.gl.getParameter(config.gl.VERSION).includes('2.0');\n      if (!glv2) {\n        log('override: using fallback webgl backend as webgl 2.0 is not detected');\n        instance.config.backend = 'webgl';\n        return;\n      }\n      if (config.canvas) {\n        config.canvas.addEventListener('webglcontextlost', async (e) => {\n          log('error: humangl:', e.type);\n          log('possible browser memory leak using webgl or conflict with multiple backend registrations');\n          instance.emit('error');\n          throw new Error('backend error: webgl context lost');\n          // log('resetting humangl backend');\n          // env.initial = true;\n          // models.reset(instance);\n          // await tf.removeBackend(config.name);\n          // await register(instance); // re-register\n        });\n        config.canvas.addEventListener('webglcontextrestored', (e) => {\n          log('error: humangl context restored:', e);\n        });\n        config.canvas.addEventListener('webglcontextcreationerror', (e) => {\n          log('error: humangl context create:', e);\n        });\n      }\n    } catch (err) {\n      log('error: cannot get WebGL context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    const current = tf.backend().getGPGPUContext ? tf.backend().getGPGPUContext().gl : null;\n    if (current) {\n      log(`humangl webgl version:${current.getParameter(current.VERSION)} renderer:${current.getParameter(current.RENDERER)}`);\n    } else {\n      log('error: no current gl context:', current, config.gl);\n      return;\n    }\n    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    extensions();\n    log('backend registered:', config.name);\n  }\n}\n", "/** TFJS backend initialization and customization */\n\nimport type { Human } from '../human';\nimport { log, now } from '../util/util';\nimport { env } from '../util/env';\nimport * as humangl from './humangl';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as constants from './constants';\n\nfunction registerCustomOps() {\n  if (!env.kernels.includes('mod')) {\n    const kernelMod = {\n      kernelName: 'Mod',\n      backendName: tf.getBackend(),\n      kernelFunc: (op) => tf.tidy(() => tf.sub(op.inputs.a, tf.mul(tf.div(op.inputs.a, op.inputs.b), op.inputs.b))),\n    };\n    tf.registerKernel(kernelMod);\n    env.kernels.push('mod');\n  }\n  if (!env.kernels.includes('floormod')) {\n    const kernelMod = {\n      kernelName: 'FloorMod',\n      backendName: tf.getBackend(),\n      kernelFunc: (op) => tf.tidy(() => tf.floorDiv(op.inputs.a / op.inputs.b) * op.inputs.b + tf.mod(op.inputs.a, op.inputs.b)),\n    };\n    tf.registerKernel(kernelMod);\n    env.kernels.push('floormod');\n  }\n}\n\nexport async function check(instance: Human, force = false) {\n  instance.state = 'backend';\n  if (force || env.initial || (instance.config.backend && (instance.config.backend.length > 0) && (tf.getBackend() !== instance.config.backend))) {\n    const timeStamp = now();\n\n    if (instance.config.backend && instance.config.backend.length > 0) {\n      // detect web worker\n      // @ts-ignore ignore missing type for WorkerGlobalScope as that is the point\n      if (typeof window === 'undefined' && typeof WorkerGlobalScope !== 'undefined' && instance.config.debug) {\n        if (instance.config.debug) log('running inside web worker');\n      }\n\n      // force browser vs node backend\n      if (env.browser && instance.config.backend === 'tensorflow') {\n        if (instance.config.debug) log('override: backend set to tensorflow while running in browser');\n        instance.config.backend = 'humangl';\n      }\n      if (env.node && (instance.config.backend === 'webgl' || instance.config.backend === 'humangl')) {\n        if (instance.config.debug) log(`override: backend set to ${instance.config.backend} while running in nodejs`);\n        instance.config.backend = 'tensorflow';\n      }\n\n      // handle webgpu\n      if (env.browser && instance.config.backend === 'webgpu') {\n        if (typeof navigator === 'undefined' || typeof navigator['gpu'] === 'undefined') {\n          log('override: backend set to webgpu but browser does not support webgpu');\n          instance.config.backend = 'humangl';\n        } else {\n          const adapter = await navigator['gpu'].requestAdapter();\n          if (instance.config.debug) log('enumerated webgpu adapter:', adapter);\n          if (!adapter) {\n            log('override: backend set to webgpu but browser reports no available gpu');\n            instance.config.backend = 'humangl';\n          } else {\n            // @ts-ignore requestAdapterInfo is not in tslib\n            // eslint-disable-next-line no-undef\n            const adapterInfo = 'requestAdapterInfo' in adapter ? await (adapter as GPUAdapter).requestAdapterInfo() : undefined;\n            // if (adapter.features) adapter.features.forEach((feature) => log('webgpu features:', feature));\n            log('webgpu adapter info:', adapterInfo);\n          }\n        }\n      }\n\n      // check available backends\n      if (instance.config.backend === 'humangl') await humangl.register(instance);\n      const available = Object.keys(tf.engine().registryFactory);\n      if (instance.config.debug) log('available backends:', available);\n\n      if (!available.includes(instance.config.backend)) {\n        log(`error: backend ${instance.config.backend} not found in registry`);\n        instance.config.backend = env.node ? 'tensorflow' : 'webgl';\n        if (instance.config.debug) log(`override: setting backend ${instance.config.backend}`);\n      }\n\n      if (instance.config.debug) log('setting backend:', instance.config.backend);\n\n      // customize wasm\n      if (instance.config.backend === 'wasm') {\n        try {\n          tf.env().set('CANVAS2D_WILL_READ_FREQUENTLY', true);\n        } catch { /**/ }\n        if (instance.config.debug) log('wasm path:', instance.config.wasmPath);\n        if (typeof tf?.setWasmPaths !== 'undefined') await tf.setWasmPaths(instance.config.wasmPath, instance.config.wasmPlatformFetch);\n        else throw new Error('backend error: attempting to use wasm backend but wasm path is not set');\n        const simd = await tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n        const mt = await tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n        if (instance.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n        if (instance.config.debug && !simd) log('warning: wasm simd support is not enabled');\n      }\n\n      try {\n        await tf.setBackend(instance.config.backend);\n        await tf.ready();\n        constants.init();\n      } catch (err) {\n        log('error: cannot set backend:', instance.config.backend, err);\n        return false;\n      }\n    }\n\n    // customize humangl\n    if (tf.getBackend() === 'humangl') {\n      tf.ENV.set('CHECK_COMPUTATION_FOR_ERRORS', false);\n      tf.ENV.set('WEBGL_CPU_FORWARD', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', false);\n      tf.ENV.set('WEBGL_USE_SHAPES_UNIFORMS', true);\n      tf.ENV.set('CPU_HANDOFF_SIZE_THRESHOLD', 256);\n      // if (!instance.config.object.enabled) tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true); // safe to use 16bit precision\n      if (typeof instance.config['deallocate'] !== 'undefined' && instance.config['deallocate']) { // hidden param\n        log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', true);\n        tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', 0);\n      }\n      if (tf.backend().getGPGPUContext) {\n        const gl = await tf.backend().getGPGPUContext().gl;\n        if (instance.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n    }\n\n    // customize webgpu\n    if (tf.getBackend() === 'webgpu') {\n      // tf.ENV.set('WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD', 512);\n      // tf.ENV.set('WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE', 0);\n      // tf.ENV.set('WEBGPU_CPU_FORWARD', true);\n    }\n\n    // wait for ready\n    tf.enableProdMode();\n    await tf.ready();\n\n    instance.performance.initBackend = Math.trunc(now() - timeStamp);\n    instance.config.backend = tf.getBackend();\n\n    await env.updateBackend(); // update env on backend init\n    registerCustomOps();\n    // await env.updateBackend(); // update env on backend init\n  }\n  return true;\n}\n\n// register fake missing tfjs ops\nexport function fakeOps(kernelNames: Array<string>, config) {\n  // if (config.debug) log('registerKernel:', kernelNames);\n  for (const kernelName of kernelNames) {\n    const kernelConfig = {\n      kernelName,\n      backendName: config.backend,\n      kernelFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },\n      // setupFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },\n      // disposeFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },\n    };\n    tf.registerKernel(kernelConfig);\n  }\n  env.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => kernel.kernelName.toLowerCase()); // re-scan registered ops\n}\n", "/**\n * Module that implements helper draw functions, exposed as human.draw\n */\n\nimport { mergeDeep, now } from '../util/util';\nimport { env } from '../util/env';\nimport { getCanvasContext, rect } from './primitives';\nimport { options } from './options';\nimport { face } from './face';\nimport { body } from './body';\nimport { hand } from './hand';\nimport { object } from './object';\nimport { gesture } from './gesture';\nimport type { Result, PersonResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\nlet drawTime = 0;\n\nexport { options } from './options';\nexport { face } from './face';\nexport { body } from './body';\nexport { hand } from './hand';\nexport { object } from './object';\nexport { gesture } from './gesture';\n\n/** draw combined person results instead of individual detection result objects */\nexport async function person(inCanvas: AnyCanvas, result: Array<PersonResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = localOptions.font;\n\n  for (let i = 0; i < result.length; i++) {\n    if (localOptions.drawBoxes) {\n      ctx.strokeStyle = localOptions.color;\n      ctx.fillStyle = localOptions.color;\n      rect(ctx, result[i].box[0], result[i].box[1], result[i].box[2], result[i].box[3], localOptions);\n      if (localOptions.drawLabels) {\n        const label = `person #${i}`;\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(label, result[i].box[0] + 3, 1 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(label, result[i].box[0] + 2, 0 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\n/** draw processed canvas */\nexport async function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas) {\n  if (!input || !output) return;\n  const ctx = getCanvasContext(output);\n  if (!ctx) return;\n  ctx.drawImage(input, 0, 0);\n}\n\n/** meta-function that performs draw for: canvas, face, body, hand */\nexport async function all(inCanvas: AnyCanvas, result: Result, drawOptions?: Partial<DrawOptions>) {\n  if (!result || !result.performance || !result || !inCanvas) return null;\n  const timeStamp = now();\n  const localOptions = mergeDeep(options, drawOptions);\n  const promise = Promise.all([\n    face(inCanvas, result.face, localOptions),\n    body(inCanvas, result.body, localOptions),\n    hand(inCanvas, result.hand, localOptions),\n    object(inCanvas, result.object, localOptions),\n    gesture(inCanvas, result.gesture, localOptions), // gestures do not have buffering\n    // person(inCanvas, result.persons, localOptions); // already included above\n  ]);\n  drawTime = env.perfadd ? drawTime + Math.round(now() - timeStamp) : Math.round(now() - timeStamp);\n  result.performance.draw = drawTime;\n  return promise;\n}\n", "import { log } from '../util/util';\nimport type { AnyCanvas } from '../exports';\nimport type { Point } from '../result';\nimport type { DrawOptions } from './options';\n\nexport const getCanvasContext = (input: AnyCanvas) => {\n  if (!input) log('draw error: invalid canvas');\n  else if (!input.getContext) log('draw error: canvas context not defined');\n  else {\n    const ctx = input.getContext('2d');\n    if (!ctx) log('draw error: cannot get canvas context');\n    else return ctx;\n  }\n  return null;\n};\n\nexport const rad2deg = (theta: number) => Math.round((theta * 180) / Math.PI);\n\nexport const colorDepth = (z: number | undefined, opt: DrawOptions): string => {\n  if (!opt.useDepth || typeof z === 'undefined') return opt.color;\n  const rgb = Uint8ClampedArray.from([127 + (2 * z), 127 - (2 * z), 255]);\n  const color = `rgba(${rgb[0]}, ${rgb[1]}, ${rgb[2]}, ${opt.alpha})`;\n  return color;\n};\n\nexport function point(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, x: number, y: number, z: number | undefined, localOptions: DrawOptions) {\n  ctx.fillStyle = colorDepth(z, localOptions);\n  ctx.beginPath();\n  ctx.arc(x, y, localOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nexport function rect(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, x: number, y: number, width: number, height: number, localOptions: DrawOptions) {\n  ctx.beginPath();\n  ctx.lineWidth = localOptions.lineWidth;\n  if (localOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.moveTo(x + localOptions.roundRect, y);\n    ctx.lineTo(x + width - localOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + localOptions.roundRect);\n    ctx.lineTo(x + width, y + height - localOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - localOptions.roundRect, y + height);\n    ctx.lineTo(x + localOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - localOptions.roundRect);\n    ctx.lineTo(x, y + localOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + localOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nexport function lines(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, points: Point[], localOptions: DrawOptions) {\n  if (points.length < 2) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = colorDepth(pt[2] || 0, localOptions);\n    ctx.lineTo(Math.trunc(pt[0]), Math.trunc(pt[1]));\n  }\n  ctx.stroke();\n  if (localOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport function curves(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, points: Point[], localOptions: DrawOptions) {\n  if (points.length < 2) return;\n  ctx.lineWidth = localOptions.lineWidth;\n  if (!localOptions.useCurves || points.length <= 2) {\n    lines(ctx, points, localOptions);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (localOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport function arrow(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, from: Point, to: Point, radius = 5) {\n  let angle;\n  let x;\n  let y;\n  ctx.beginPath();\n  ctx.moveTo(from[0], from[1]);\n  ctx.lineTo(to[0], to[1]);\n  angle = Math.atan2(to[1] - from[1], to[0] - from[0]);\n  x = radius * Math.cos(angle) + to[0];\n  y = radius * Math.sin(angle) + to[1];\n  ctx.moveTo(x, y);\n  angle += (1.0 / 3.0) * (2 * Math.PI);\n  x = radius * Math.cos(angle) + to[0];\n  y = radius * Math.sin(angle) + to[1];\n  ctx.lineTo(x, y);\n  angle += (1.0 / 3.0) * (2 * Math.PI);\n  x = radius * Math.cos(angle) + to[0];\n  y = radius * Math.sin(angle) + to[1];\n  ctx.lineTo(x, y);\n  ctx.closePath();\n  ctx.stroke();\n  ctx.fill();\n}\n", "/** Draw Options\n * - Accessed via `human.draw.options` or provided per each draw method as the drawOptions optional parameter\n */\nexport type DrawOptions = {\n  /** draw line color */\n  color: string,\n  /** alpha value used for lines */\n  alpha: number,\n  /** label color */\n  labelColor: string,\n  /** label shadow color */\n  shadowColor: string,\n  /** label font */\n  font: string,\n  /** line spacing between labels */\n  lineHeight: number,\n  /** line width for drawn lines */\n  lineWidth: number,\n  /** size of drawn points */\n  pointSize: number,\n  /** draw rounded boxes by n pixels */\n  roundRect: number,\n  /** should points be drawn? */\n  drawPoints: boolean,\n  /** should labels be drawn? */\n  drawLabels: boolean,\n  /** should face attention keypoints be highlighted */\n  drawAttention: boolean;\n  /** should detected gestures be drawn? */\n  drawGestures: boolean,\n  /** should draw boxes around detection results? */\n  drawBoxes: boolean,\n  /** should draw polygons from detection points? */\n  drawPolygons: boolean,\n  /** should draw gaze arrows? */\n  drawGaze: boolean,\n  /** should fill polygons? */\n  fillPolygons: boolean,\n  /** use z-coordinate when available */\n  useDepth: boolean,\n  /** should lines be curved? */\n  useCurves: boolean,\n}\n\n/** currently set draw options {@link DrawOptions} */\nexport const options: DrawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.6)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  alpha: 0.5,\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>18,\n  lineWidth: <number>4,\n  pointSize: <number>2,\n  roundRect: <number>8,\n  drawPoints: <boolean>false,\n  drawLabels: <boolean>true,\n  drawBoxes: <boolean>true,\n  drawAttention: <boolean>true,\n  drawGestures: <boolean>true,\n  drawPolygons: <boolean>true,\n  drawGaze: <boolean>true,\n  fillPolygons: <boolean>false,\n  useDepth: <boolean>true,\n  useCurves: <boolean>false,\n};\n", "import { TRI468 as triangulation } from '../face/facemeshcoords';\nimport { mergeDeep } from '../util/util';\nimport { getCanvasContext, rad2deg, rect, point, lines, arrow } from './primitives';\nimport { options } from './options';\nimport * as facemeshConstants from '../face/constants';\nimport type { FaceResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\nlet opt: DrawOptions;\n\nfunction drawLabels(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawLabels) {\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face: ${Math.trunc(100 * f.score)}%`);\n    if (f.genderScore) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderScore)}%`);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`distance: ${f.iris}`);\n    if (f.real) labels.push(`real: ${Math.trunc(100 * f.real)}%`);\n    if (f.live) labels.push(`live: ${Math.trunc(100 * f.live)}%`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      if (emotion.length > 3) emotion.length = 3;\n      labels.push(emotion.join(' '));\n    }\n    if (f.rotation && f.rotation.angle && f.rotation.gaze) {\n      if (f.rotation.angle.roll) labels.push(`roll: ${rad2deg(f.rotation.angle.roll)}\u00B0 yaw:${rad2deg(f.rotation.angle.yaw)}\u00B0 pitch:${rad2deg(f.rotation.angle.pitch)}\u00B0`);\n      if (f.rotation.gaze.bearing) labels.push(`gaze: ${rad2deg(f.rotation.gaze.bearing)}\u00B0`);\n    }\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = opt.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * opt.lineHeight + f.box[1];\n      if (opt.shadowColor && opt.shadowColor !== '') {\n        ctx.fillStyle = opt.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = opt.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n  }\n}\n\nfunction drawIrisElipse(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  // iris: array[center, left, top, right, bottom]\n  if (f.annotations && f.annotations['leftEyeIris'] && f.annotations['leftEyeIris'][0]) {\n    ctx.strokeStyle = opt.useDepth ? 'rgba(255, 200, 255, 0.3)' : opt.color;\n    ctx.beginPath();\n    const sizeX = Math.abs(f.annotations['leftEyeIris'][3][0] - f.annotations['leftEyeIris'][1][0]) / 2;\n    const sizeY = Math.abs(f.annotations['leftEyeIris'][4][1] - f.annotations['leftEyeIris'][2][1]) / 2;\n    ctx.ellipse(f.annotations['leftEyeIris'][0][0], f.annotations['leftEyeIris'][0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n    ctx.stroke();\n    if (opt.fillPolygons) {\n      ctx.fillStyle = opt.useDepth ? 'rgba(255, 255, 200, 0.3)' : opt.color;\n      ctx.fill();\n    }\n  }\n  if (f.annotations && f.annotations['rightEyeIris'] && f.annotations['rightEyeIris'][0]) {\n    ctx.strokeStyle = opt.useDepth ? 'rgba(255, 200, 255, 0.3)' : opt.color;\n    ctx.beginPath();\n    const sizeX = Math.abs(f.annotations['rightEyeIris'][3][0] - f.annotations['rightEyeIris'][1][0]) / 2;\n    const sizeY = Math.abs(f.annotations['rightEyeIris'][4][1] - f.annotations['rightEyeIris'][2][1]) / 2;\n    ctx.ellipse(f.annotations['rightEyeIris'][0][0], f.annotations['rightEyeIris'][0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n    ctx.stroke();\n    if (opt.fillPolygons) {\n      ctx.fillStyle = opt.useDepth ? 'rgba(255, 255, 200, 0.3)' : opt.color;\n      ctx.fill();\n    }\n  }\n}\n\nfunction drawGazeSpheres(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawGaze && f.rotation?.angle && typeof Path2D !== 'undefined') {\n    ctx.strokeStyle = 'pink';\n    const valX = (f.box[0] + f.box[2] / 2) - (f.box[3] * rad2deg(f.rotation.angle.yaw) / 90);\n    const valY = (f.box[1] + f.box[3] / 2) + (f.box[2] * rad2deg(f.rotation.angle.pitch) / 90);\n    const pathV = new Path2D(`\n      M ${f.box[0] + f.box[2] / 2} ${f.box[1]}\n      C\n        ${valX} ${f.box[1]},\n        ${valX} ${f.box[1] + f.box[3]},\n        ${f.box[0] + f.box[2] / 2} ${f.box[1] + f.box[3]}\n    `);\n    const pathH = new Path2D(`\n      M ${f.box[0]} ${f.box[1] + f.box[3] / 2}\n      C \n        ${f.box[0]} ${valY},\n        ${f.box[0] + f.box[2]} ${valY},\n        ${f.box[0] + f.box[2]} ${f.box[1] + f.box[3] / 2}\n    `);\n    ctx.stroke(pathH);\n    ctx.stroke(pathV);\n  }\n}\n\nfunction drawGazeArrows(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawGaze && f.rotation?.gaze?.strength && f.rotation?.gaze?.bearing && f.annotations['leftEyeIris'] && f.annotations['rightEyeIris'] && f.annotations['leftEyeIris'][0] && f.annotations['rightEyeIris'][0]) {\n    ctx.strokeStyle = 'pink';\n    ctx.fillStyle = 'pink';\n    const leftGaze = [\n      f.annotations['leftEyeIris'][0][0] + (Math.sin(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[3]),\n      f.annotations['leftEyeIris'][0][1] + (Math.cos(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[2]),\n    ];\n    arrow(ctx, [f.annotations['leftEyeIris'][0][0], f.annotations['leftEyeIris'][0][1]], [leftGaze[0], leftGaze[1]], 4);\n    const rightGaze = [\n      f.annotations['rightEyeIris'][0][0] + (Math.sin(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[3]),\n      f.annotations['rightEyeIris'][0][1] + (Math.cos(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[2]),\n    ];\n    arrow(ctx, [f.annotations['rightEyeIris'][0][0], f.annotations['rightEyeIris'][0][1]], [rightGaze[0], rightGaze[1]], 4);\n  }\n}\n\nfunction drawFacePolygons(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawPolygons && f.mesh.length >= 468) {\n    ctx.lineWidth = 1;\n    for (let i = 0; i < triangulation.length / 3; i++) {\n      const points = [triangulation[i * 3 + 0], triangulation[i * 3 + 1], triangulation[i * 3 + 2]].map((index) => f.mesh[index]);\n      lines(ctx, points, opt);\n    }\n    drawIrisElipse(f, ctx);\n  }\n  /*\n  if (opt.drawPolygons && f.contours.length > 1) {\n    ctx.lineWidth = 5;\n    lines(ctx, f.contours, opt);\n  }\n  ctx.lineWidth = 1;\n  */\n}\n\nfunction drawFacePoints(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawPoints && f.mesh.length >= 468) {\n    for (let i = 0; i < f.mesh.length; i++) {\n      point(ctx, f.mesh[i][0], f.mesh[i][1], f.mesh[i][2], opt);\n      if (opt.drawAttention) {\n        if (facemeshConstants.LANDMARKS_REFINEMENT_LIPS_CONFIG.includes(i)) point(ctx, f.mesh[i][0], f.mesh[i][1], (f.mesh[i][2] as number) + 127, opt);\n        if (facemeshConstants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG.includes(i)) point(ctx, f.mesh[i][0], f.mesh[i][1], (f.mesh[i][2] as number) - 127, opt);\n        if (facemeshConstants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG.includes(i)) point(ctx, f.mesh[i][0], f.mesh[i][1], (f.mesh[i][2] as number) - 127, opt);\n      }\n    }\n  }\n}\n\nfunction drawFaceBoxes(f: FaceResult, ctx) {\n  if (opt.drawBoxes) {\n    rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3], opt);\n  }\n}\n\n/** draw detected faces */\nexport async function face(inCanvas: AnyCanvas, result: Array<FaceResult>, drawOptions?: Partial<DrawOptions>) {\n  opt = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.font = opt.font;\n  ctx.strokeStyle = opt.color;\n  ctx.fillStyle = opt.color;\n  for (const f of result) {\n    drawFaceBoxes(f, ctx);\n    drawLabels(f, ctx);\n    if (f.mesh && f.mesh.length > 0) {\n      drawFacePoints(f, ctx);\n      drawFacePolygons(f, ctx);\n      drawGazeSpheres(f, ctx);\n      drawGazeArrows(f, ctx);\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext, rect, point, curves, colorDepth } from './primitives';\nimport { options } from './options';\nimport type { BodyResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\n/** draw detected bodies */\nexport async function body(inCanvas: AnyCanvas, result: Array<BodyResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    ctx.strokeStyle = localOptions.color;\n    ctx.fillStyle = localOptions.color;\n    ctx.lineWidth = localOptions.lineWidth;\n    ctx.font = localOptions.font;\n    if (localOptions.drawBoxes && result[i].box && result[i].box?.length === 4) {\n      rect(ctx, result[i].box[0], result[i].box[1], result[i].box[2], result[i].box[3], localOptions);\n      if (localOptions.drawLabels) {\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(`body ${100 * result[i].score}%`, result[i].box[0] + 3, 1 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(`body ${100 * result[i].score}%`, result[i].box[0] + 2, 0 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n      }\n    }\n    if (localOptions.drawPoints && result[i].keypoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        if (!result[i].keypoints[pt].score || (result[i].keypoints[pt].score === 0)) continue;\n        ctx.fillStyle = colorDepth(result[i].keypoints[pt].position[2], localOptions);\n        point(ctx, result[i].keypoints[pt].position[0], result[i].keypoints[pt].position[1], 0, localOptions);\n      }\n    }\n    if (localOptions.drawLabels && result[i].keypoints) {\n      ctx.font = localOptions.font;\n      for (const pt of result[i].keypoints) {\n        if (!pt.score || (pt.score === 0)) continue;\n        ctx.fillStyle = colorDepth(pt.position[2], localOptions);\n        ctx.fillText(`${pt.part} ${Math.trunc(100 * pt.score)}%`, pt.position[0] + 4, pt.position[1] + 4);\n      }\n    }\n    if (localOptions.drawPolygons && result[i].keypoints && result[i].annotations) {\n      for (const part of Object.values(result[i].annotations)) {\n        for (const connected of part) curves(ctx, connected, localOptions);\n      }\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext, rect, point, colorDepth } from './primitives';\nimport { options } from './options';\nimport type { HandResult } from '../result';\nimport type { AnyCanvas, DrawOptions, Point } from '../exports';\n\n/** draw detected hands */\nexport async function hand(inCanvas: AnyCanvas, result: Array<HandResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = localOptions.font;\n  for (const h of result) {\n    if (localOptions.drawBoxes) {\n      ctx.strokeStyle = localOptions.color;\n      ctx.fillStyle = localOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3], localOptions);\n      if (localOptions.drawLabels) {\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(`hand:${Math.trunc(100 * h.score)}%`, h.box[0] + 3, 1 + h.box[1] + localOptions.lineHeight, h.box[2]); // can use h.label\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(`hand:${Math.trunc(100 * h.score)}%`, h.box[0] + 2, 0 + h.box[1] + localOptions.lineHeight, h.box[2]); // can use h.label\n      }\n      ctx.stroke();\n    }\n    if (localOptions.drawPoints) {\n      if (h.keypoints && h.keypoints.length > 0) {\n        for (const pt of h.keypoints) {\n          ctx.fillStyle = colorDepth(pt[2], localOptions);\n          point(ctx, pt[0], pt[1], 0, localOptions);\n        }\n      }\n    }\n    if (localOptions.drawLabels && h.annotations) {\n      const addHandLabel = (part: Array<Point>, title: string) => {\n        if (!part || part.length === 0 || !part[0]) return;\n        const z = part[part.length - 1][2] || -256;\n        ctx.fillStyle = colorDepth(z, localOptions);\n        ctx.fillText(title, part[part.length - 1][0] + 4, part[part.length - 1][1] + 4);\n      };\n      ctx.font = localOptions.font;\n      addHandLabel(h.annotations['index'], 'index');\n      addHandLabel(h.annotations['middle'], 'middle');\n      addHandLabel(h.annotations['ring'], 'ring');\n      addHandLabel(h.annotations['pinky'], 'pinky');\n      addHandLabel(h.annotations['thumb'], 'thumb');\n      addHandLabel(h.annotations['palm'], 'palm');\n    }\n    if (localOptions.drawPolygons && h.annotations) {\n      const addHandLine = (part: Array<Point>) => {\n        if (!part || part.length === 0 || !part[0]) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.beginPath();\n          const z = part[i][2] || 0;\n          ctx.strokeStyle = colorDepth(i * z, localOptions);\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      ctx.lineWidth = localOptions.lineWidth;\n      addHandLine(h.annotations['index']);\n      addHandLine(h.annotations['middle']);\n      addHandLine(h.annotations['ring']);\n      addHandLine(h.annotations['pinky']);\n      addHandLine(h.annotations['thumb']);\n      // addPart(h.annotations.palm);\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext, rect } from './primitives';\nimport { options } from './options';\nimport type { ObjectResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\n/** draw detected objects */\nexport async function object(inCanvas: AnyCanvas, result: Array<ObjectResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = localOptions.font;\n  for (const h of result) {\n    if (localOptions.drawBoxes) {\n      ctx.strokeStyle = localOptions.color;\n      ctx.fillStyle = localOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3], localOptions);\n      if (localOptions.drawLabels) {\n        const label = `${h.label} ${Math.round(100 * h.score)}%`;\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + localOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + localOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext } from './primitives';\nimport { options } from './options';\nimport type { GestureResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\n/** draw detected gestures */\nexport async function gesture(inCanvas: AnyCanvas, result: Array<GestureResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  if (localOptions.drawGestures) {\n    const ctx = getCanvasContext(inCanvas);\n    if (!ctx) return;\n    ctx.font = localOptions.font;\n    ctx.fillStyle = localOptions.color;\n    let i = 1;\n    for (let j = 0; j < result.length; j++) {\n      let where: unknown[] = []; // what&where is a record\n      let what: unknown[] = []; // what&where is a record\n      [where, what] = Object.entries(result[j]);\n      if ((what.length > 1) && ((what[1] as string).length > 0)) {\n        const who = where[1] as number > 0 ? `#${where[1]}` : '';\n        const label = `${where[0]} ${who}: ${what[1]}`;\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(label, 8, 2 + (i * localOptions.lineHeight));\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(label, 6, 0 + (i * localOptions.lineHeight));\n        i += 1;\n      }\n    }\n  }\n}\n", "import type { Tensor } from '../tfjs/types';\nimport type { FaceResult } from '../result';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { meshAnnotations } from './facemeshcoords';\n\nconst expandFact = 0.1;\nconst alpha = 0.5;\n\n// point inclusion in polygon based on https://wrf.ecse.rpi.edu/Research/Short_Notes/pnpoly.html\nfunction insidePoly(x: number, y: number, polygon: Array<{ x: number, y: number }>): boolean {\n  let inside = false;\n  let j = polygon.length - 1;\n  for (let i = 0; i < polygon.length; j = i++) {\n    if (((polygon[i].y > y) !== (polygon[j].y > y)) && (x < (polygon[j].x - polygon[i].x) * (y - polygon[i].y) / (polygon[j].y - polygon[i].y) + polygon[i].x)) inside = !inside;\n  }\n  return inside;\n}\n\nexport async function mask(face: FaceResult): Promise<Tensor | undefined> {\n  if (!face.tensor) return face.tensor;\n  if (!face.mesh || face.mesh.length < 100) return face.tensor;\n  const width = face.tensor.shape[2] || 0;\n  const height = face.tensor.shape[1] || 0;\n  const buffer = await face.tensor.buffer();\n  let silhouette: Array<{ x: number, y: number }> = [];\n  for (const pt of meshAnnotations.silhouette) silhouette.push({ x: (face.mesh[pt][0] - face.box[0]) / face.box[2], y: (face.mesh[pt][1] - face.box[1]) / face.box[3] }); // add all silhouette points scaled to local box\n  if (expandFact && expandFact > 0) silhouette = silhouette.map((pt) => ({ x: pt.x > 0.5 ? pt.x + expandFact : pt.x - expandFact, y: pt.y > 0.5 ? pt.y + expandFact : pt.y - expandFact })); // expand silhouette\n  for (let x = 0; x < width; x++) {\n    for (let y = 0; y < height; y++) {\n      const inside = insidePoly(x / width, y / width, silhouette);\n      if (!inside) {\n        buffer.set(alpha * buffer.get(0, y, x, 0), 0, y, x, 0);\n        buffer.set(alpha * buffer.get(0, y, x, 1), 0, y, x, 1);\n        buffer.set(alpha * buffer.get(0, y, x, 2), 0, y, x, 2);\n      }\n    }\n  }\n  const output = buffer.toTensor();\n  tf.dispose(buffer);\n  return output;\n}\n", "import type { Point, FaceResult } from '../result';\n\ntype Vector = [number, number, number];\n\nconst calculateGaze = (face: FaceResult): { bearing: number, strength: number } => {\n  const radians = (pt1: Point, pt2: Point) => Math.atan2(pt1[1] - pt2[1], pt1[0] - pt2[0]); // function to calculate angle between any two points\n  if (!face.annotations['rightEyeIris'] || !face.annotations['leftEyeIris']) return { bearing: 0, strength: 0 };\n\n  const offsetIris = [0, -0.1]; // iris center may not align with average of eye extremes\n  const eyeRatio = 1; // factor to normalize changes x vs y\n\n  const left = (face.mesh[33][2] || 0) > (face.mesh[263][2] || 0); // pick left or right eye depending which one is closer bazed on outsize point z axis\n  const irisCenter = left ? face.mesh[473] : face.mesh[468];\n  const eyeCenter = left // eye center is average of extreme points on x axis for both x and y, ignoring y extreme points as eyelids naturally open/close more when gazing up/down so relative point is less precise\n    ? [(face.mesh[133][0] + face.mesh[33][0]) / 2, (face.mesh[133][1] + face.mesh[33][1]) / 2]\n    : [(face.mesh[263][0] + face.mesh[362][0]) / 2, (face.mesh[263][1] + face.mesh[362][1]) / 2];\n  const eyeSize = left // eye size is difference between extreme points for both x and y, used to normalize & squarify eye dimensions\n    ? [face.mesh[133][0] - face.mesh[33][0], face.mesh[23][1] - face.mesh[27][1]]\n    : [face.mesh[263][0] - face.mesh[362][0], face.mesh[253][1] - face.mesh[257][1]];\n  const eyeDiff: Point = [ // x distance between extreme point and center point normalized with eye size\n    (eyeCenter[0] - irisCenter[0]) / eyeSize[0] - offsetIris[0],\n    eyeRatio * (irisCenter[1] - eyeCenter[1]) / eyeSize[1] - offsetIris[1],\n  ];\n  let strength = Math.sqrt((eyeDiff[0] * eyeDiff[0]) + (eyeDiff[1] * eyeDiff[1])); // vector length is a diagonal between two differences\n  strength = Math.min(strength, face.boxRaw[2] / 2, face.boxRaw[3] / 2); // limit strength to half of box size to avoid clipping due to low precision\n  const bearing = (radians([0, 0], eyeDiff) + (Math.PI / 2)) % Math.PI; // using eyeDiff instead eyeCenter/irisCenter combo due to manual adjustments and rotate clockwise 90degrees\n  return { bearing, strength };\n};\n\nexport const calculateFaceAngle = (face: FaceResult, imageSize: [number, number]): {\n  angle: { pitch: number, yaw: number, roll: number },\n  matrix: [number, number, number, number, number, number, number, number, number],\n  gaze: { bearing: number, strength: number },\n} => {\n  // const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n  const normalize = (v: Vector): Vector => { // normalize vector\n    const length = Math.sqrt(v[0] * v[0] + v[1] * v[1] + v[2] * v[2]);\n    v[0] /= length;\n    v[1] /= length;\n    v[2] /= length;\n    return v;\n  };\n  const subVectors = (a: Vector, b: Vector): Vector => { // vector subtraction (a - b)\n    const x = a[0] - b[0];\n    const y = a[1] - b[1];\n    const z = a[2] - b[2];\n    return [x, y, z];\n  };\n  const crossVectors = (a: Vector, b: Vector): Vector => { // vector cross product (a x b)\n    const x = a[1] * b[2] - a[2] * b[1];\n    const y = a[2] * b[0] - a[0] * b[2];\n    const z = a[0] * b[1] - a[1] * b[0];\n    return [x, y, z];\n  };\n  // 3x3 rotation matrix to Euler angles based on https://www.geometrictools.com/Documentation/EulerAngles.pdf\n  const rotationMatrixToEulerAngle = (r: number[]): { pitch: number, yaw: number, roll: number } => {\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const [r00, _r01, _r02, r10, r11, r12, r20, r21, r22] = r;\n    let thetaX: number;\n    let thetaY: number;\n    let thetaZ: number;\n    if (r10 < 1) { // YZX calculation\n      if (r10 > -1) {\n        thetaZ = Math.asin(r10);\n        thetaY = Math.atan2(-r20, r00);\n        thetaX = Math.atan2(-r12, r11);\n      } else {\n        thetaZ = -Math.PI / 2;\n        thetaY = -Math.atan2(r21, r22);\n        thetaX = 0;\n      }\n    } else {\n      thetaZ = Math.PI / 2;\n      thetaY = Math.atan2(r21, r22);\n      thetaX = 0;\n    }\n    if (isNaN(thetaX)) thetaX = 0;\n    if (isNaN(thetaY)) thetaY = 0;\n    if (isNaN(thetaZ)) thetaZ = 0;\n    return { pitch: 2 * -thetaX, yaw: 2 * -thetaY, roll: 2 * -thetaZ };\n  };\n\n  /*\n  const meshToEulerAngle = (mesh) => { // simple Euler angle calculation based existing 3D mesh\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    return { // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees, value of 0 means center\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face // pitch is face move up/down\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye // yaw is face turn left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye // roll is face lean left/right\n    };\n  };\n  */\n\n  // initialize gaze and mesh\n  const mesh = face.meshRaw;\n  if (!mesh || mesh.length < 300) return { angle: { pitch: 0, yaw: 0, roll: 0 }, matrix: [1, 0, 0, 0, 1, 0, 0, 0, 1], gaze: { bearing: 0, strength: 0 } };\n\n  const size = Math.max(face.boxRaw[2] * imageSize[0], face.boxRaw[3] * imageSize[1]) / 1.5;\n  // top, bottom, left, right\n  const pts: Point[] = [mesh[10], mesh[152], mesh[234], mesh[454]].map((pt) => [pt[0] * imageSize[0] / size, pt[1] * imageSize[1] / size, pt[2]] as Point); // make the xyz coordinates proportional, independent of the image/box size\n\n  const y_axis = normalize(subVectors(pts[1] as Vector, pts[0] as Vector));\n  let x_axis = normalize(subVectors(pts[3] as Vector, pts[2] as Vector));\n  const z_axis = normalize(crossVectors(x_axis, y_axis));\n  // adjust x_axis to make sure that all axes are perpendicular to each other\n  x_axis = crossVectors(y_axis, z_axis);\n\n  // Rotation Matrix from Axis Vectors - http://renderdan.blogspot.com/2006/05/rotation-matrix-from-axis-vectors.html\n  // 3x3 rotation matrix is flatten to array in row-major order. Note that the rotation represented by this matrix is inverted.\n  const matrix: [number, number, number, number, number, number, number, number, number] = [\n    x_axis[0], x_axis[1], x_axis[2],\n    y_axis[0], y_axis[1], y_axis[2],\n    z_axis[0], z_axis[1], z_axis[2],\n  ];\n  const angle = rotationMatrixToEulerAngle(matrix);\n  // const angle = meshToEulerAngle(mesh);\n\n  // we have iris keypoints so we can calculate gaze direction\n  const gaze = mesh.length === 478 ? calculateGaze(face) : { bearing: 0, strength: 0 };\n\n  return { angle, matrix, gaze };\n};\n", "/**\n * Face algorithm implementation\n * Uses FaceMesh, Emotion and FaceRes models to create a unified pipeline\n */\n\nimport { log, now } from '../util/util';\nimport { env } from '../util/env';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as facemesh from './facemesh';\nimport * as emotion from '../gear/emotion';\nimport * as faceres from './faceres';\nimport * as mask from './mask';\nimport * as antispoof from './antispoof';\nimport * as liveness from './liveness';\nimport * as gear from '../gear/gear';\nimport * as ssrnetAge from '../gear/ssrnet-age';\nimport * as ssrnetGender from '../gear/ssrnet-gender';\nimport * as mobilefacenet from './mobilefacenet';\nimport type { FaceResult, Emotion, Gender, Race } from '../result';\nimport type { Tensor } from '../tfjs/types';\nimport type { Human } from '../human';\nimport { calculateFaceAngle } from './angles';\n\ntype DescRes = { age: number, gender: Gender, genderScore: number, descriptor: number[], race?: { score: number, race: Race }[] };\n\nexport const detectFace = async (instance: Human /* instance of human */, input: Tensor): Promise<FaceResult[]> => {\n  // run facemesh, includes blazeface and iris\n  // eslint-disable-next-line no-async-promise-executor\n  let timeStamp: number = now();\n  let ageRes: { age: number } | Promise<{ age: number }> | null;\n  let gearRes: gear.GearType | Promise<gear.GearType> | null;\n  let genderRes: { gender: string, genderScore: number } | Promise<{ gender: string, genderScore: number }> | null;\n  let emotionRes: { score: number, emotion: Emotion }[] | Promise<{ score: number, emotion: Emotion }[]>;\n  let mobilefacenetRes: number[] | Promise<number[]> | null;\n  let antispoofRes: number | Promise<number> | null;\n  let livenessRes: number | Promise<number> | null;\n  let descRes: DescRes | Promise<DescRes> | null;\n\n  const faceRes: Array<FaceResult> = [];\n  instance.state = 'run:face';\n\n  const faces = await facemesh.predict(input, instance.config);\n  instance.performance.face = env.perfadd ? (instance.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n  if (!input.shape || input.shape.length !== 4) return [];\n  if (!faces) return [];\n  // for (const face of faces) {\n  for (let i = 0; i < faces.length; i++) {\n    instance.analyze('Get Face');\n\n    // is something went wrong, skip the face\n    // @ts-ignore possibly undefied\n    if (!faces[i].tensor || faces[i].tensor['isDisposedInternal']) {\n      log('Face object is disposed:', faces[i].tensor);\n      continue;\n    }\n\n    // optional face mask\n    if (instance.config.face.detector?.mask) {\n      const masked = await mask.mask(faces[i]);\n      tf.dispose(faces[i].tensor);\n      faces[i].tensor = masked as Tensor;\n    }\n\n    // calculate face angles\n    const rotation = faces[i].mesh && (faces[i].mesh.length > 200) ? calculateFaceAngle(faces[i], [input.shape[2], input.shape[1]]) : null;\n\n    // run emotion, inherits face from blazeface\n    instance.analyze('Start Emotion:');\n    if (instance.config.async) {\n      emotionRes = instance.config.face.emotion?.enabled ? emotion.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : [];\n    } else {\n      instance.state = 'run:emotion';\n      timeStamp = now();\n      emotionRes = instance.config.face.emotion?.enabled ? await emotion.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : [];\n      instance.performance.emotion = env.perfadd ? (instance.performance.emotion || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End Emotion:');\n\n    // run antispoof, inherits face from blazeface\n    instance.analyze('Start AntiSpoof:');\n    if (instance.config.async) {\n      antispoofRes = instance.config.face.antispoof?.enabled ? antispoof.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n    } else {\n      instance.state = 'run:antispoof';\n      timeStamp = now();\n      antispoofRes = instance.config.face.antispoof?.enabled ? await antispoof.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n      instance.performance.antispoof = env.perfadd ? (instance.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End AntiSpoof:');\n\n    // run liveness, inherits face from blazeface\n    instance.analyze('Start Liveness:');\n    if (instance.config.async) {\n      livenessRes = instance.config.face.liveness?.enabled ? liveness.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n    } else {\n      instance.state = 'run:liveness';\n      timeStamp = now();\n      livenessRes = instance.config.face.liveness?.enabled ? await liveness.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n      instance.performance.liveness = env.perfadd ? (instance.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End Liveness:');\n\n    // run gear, inherits face from blazeface\n    instance.analyze('Start GEAR:');\n    if (instance.config.async) {\n      gearRes = instance.config.face['gear']?.enabled ? gear.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:gear';\n      timeStamp = now();\n      gearRes = instance.config.face['gear']?.enabled ? await gear.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.gear = Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End GEAR:');\n\n    // run gear, inherits face from blazeface\n    instance.analyze('Start SSRNet:');\n    if (instance.config.async) {\n      ageRes = instance.config.face['ssrnet']?.enabled ? ssrnetAge.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      genderRes = instance.config.face['ssrnet']?.enabled ? ssrnetGender.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:ssrnet';\n      timeStamp = now();\n      ageRes = instance.config.face['ssrnet']?.enabled ? await ssrnetAge.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      genderRes = instance.config.face['ssrnet']?.enabled ? await ssrnetGender.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.ssrnet = Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End SSRNet:');\n\n    // run gear, inherits face from blazeface\n    instance.analyze('Start MobileFaceNet:');\n    if (instance.config.async) {\n      mobilefacenetRes = instance.config.face['mobilefacenet']?.enabled ? mobilefacenet.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:mobilefacenet';\n      timeStamp = now();\n      mobilefacenetRes = instance.config.face['mobilefacenet']?.enabled ? await mobilefacenet.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.mobilefacenet = Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End MobileFaceNet:');\n\n    // run emotion, inherits face from blazeface\n    instance.analyze('Start Description:');\n    if (instance.config.async) {\n      descRes = instance.config.face.description?.enabled ? faceres.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:description';\n      timeStamp = now();\n      descRes = instance.config.face.description?.enabled ? await faceres.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.description = env.perfadd ? (instance.performance.description || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End Description:');\n\n    // if async wait for results\n    if (instance.config.async) {\n      [ageRes, genderRes, emotionRes, mobilefacenetRes, descRes, gearRes, antispoofRes, livenessRes] = await Promise.all([ageRes, genderRes, emotionRes, mobilefacenetRes, descRes, gearRes, antispoofRes, livenessRes]);\n    }\n    instance.analyze('Finish Face:');\n\n    if (instance.config.face['ssrnet']?.enabled && ageRes && genderRes) { // override age/gender if ssrnet model is used\n      descRes = {\n        ...(descRes as DescRes),\n        age: (ageRes as { age: number}).age,\n        gender: (genderRes as { gender: Gender, genderScore: number }).gender,\n        genderScore: (genderRes as { gender: Gender, genderScore: number }).genderScore,\n      };\n    }\n    if (instance.config.face['gear']?.enabled && gearRes) { // override age/gender/race if gear model is used\n      descRes = {\n        ...(descRes as DescRes),\n        age: (gearRes as gear.GearType).age,\n        gender: (gearRes as gear.GearType).gender,\n        genderScore: (gearRes as gear.GearType).genderScore,\n        race: (gearRes as gear.GearType).race,\n      };\n    }\n    if (instance.config.face['mobilefacenet']?.enabled && mobilefacenetRes) { // override descriptor if embedding model is used\n      (descRes as DescRes).descriptor = mobilefacenetRes as number[];\n    }\n\n    // calculate iris distance\n    // iris: array[ center, left, top, right, bottom]\n    if (!instance.config.face.iris?.enabled) {\n      // if (faces[i]?.annotations?.leftEyeIris) delete faces[i].annotations.leftEyeIris;\n      // if (faces[i]?.annotations?.rightEyeIris) delete faces[i].annotations.rightEyeIris;\n    }\n    const irisSize = (faces[i].annotations && faces[i].annotations.leftEyeIris && faces[i].annotations.leftEyeIris[0] && faces[i].annotations.rightEyeIris && faces[i].annotations.rightEyeIris[0]\n      && (faces[i].annotations.leftEyeIris.length > 0) && (faces[i].annotations.rightEyeIris.length > 0)\n      && (faces[i].annotations.leftEyeIris[0] !== null) && (faces[i].annotations.rightEyeIris[0] !== null))\n      ? Math.max(Math.abs(faces[i].annotations.leftEyeIris[3][0] - faces[i].annotations.leftEyeIris[1][0]), Math.abs(faces[i].annotations.rightEyeIris[4][1] - faces[i].annotations.rightEyeIris[2][1])) / input.shape[2]\n      : 0; // note: average human iris size is 11.7mm\n\n    // optionally return tensor\n    const tensor = instance.config.face.detector?.return ? tf.squeeze(faces[i].tensor) : null;\n    // dispose original face tensor\n    tf.dispose(faces[i].tensor);\n    // delete temp face image\n    if (faces[i].tensor) delete faces[i].tensor;\n    // combine results\n    const res: FaceResult = {\n      ...faces[i],\n      id: i,\n    };\n    if ((descRes as DescRes)?.age) res.age = (descRes as DescRes).age as number;\n    if ((descRes as DescRes)?.gender) res.gender = (descRes as DescRes).gender as Gender;\n    if ((descRes as DescRes)?.genderScore) res.genderScore = (descRes as DescRes)?.genderScore as number;\n    if ((descRes as DescRes)?.descriptor) res.embedding = (descRes as DescRes)?.descriptor as Array<number>;\n    if ((descRes as DescRes)?.race) res.race = (descRes as DescRes)?.race as { score: number, race: Race }[];\n    if (emotionRes) res.emotion = emotionRes as Array<{ score: number, emotion: Emotion }>;\n    if (antispoofRes) res.real = antispoofRes as number;\n    if (livenessRes) res.live = livenessRes as number;\n    if (irisSize && irisSize !== 0) res.iris = Math.trunc(500 / irisSize / 11.7) / 100;\n    if (rotation) res.rotation = rotation;\n    if (tensor) res.tensor = tensor;\n    faceRes.push(res);\n    instance.analyze('End Face');\n  }\n  instance.analyze('End FaceMesh:');\n  if (instance.config.async) {\n    if (instance.performance.face) delete instance.performance.face;\n    if (instance.performance.age) delete instance.performance.age;\n    if (instance.performance.gender) delete instance.performance.gender;\n    if (instance.performance.emotion) delete instance.performance.emotion;\n  }\n  return faceRes;\n};\n", "/**\n * Gesture detection algorithm\n */\n\nimport type { GestureResult, BodyResult, FaceResult, HandResult, Point } from '../result';\nimport * as fingerPose from '../hand/fingerpose';\n\n/** face gesture type */\nexport type FaceGesture =\n  `facing ${'left' | 'center' | 'right'}`\n  | `blink ${'left' | 'right'} eye`\n  | `mouth ${number}% open`\n  | `head ${'up' | 'down'}`;\n\n/** iris gesture type */\nexport type IrisGesture =\n  'facing center'\n  | `looking ${'left' | 'right' | 'up' | 'down'}`\n  | 'looking center';\n\n/** body gesture type */\nexport type BodyGesture =\n  `leaning ${'left' | 'right'}`\n  | `raise ${'left' | 'right'} hand`\n  | 'i give up';\n\n/** hand gesture type */\nexport type HandGesture =\n  `${'thumb' | 'index' | 'middle' | 'ring' | 'pinky'} forward`\n  | `${'thumb' | 'index' | 'middle' | 'ring' | 'pinky'} up`\n  | 'victory'\n  | 'thumbs up';\n\nexport const body = (res: BodyResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: BodyGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position[1] < nose.position[1]) && (rightWrist.position[1] < nose.position[1])) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position[1] < nose.position[1])) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position[1] < nose.position[1])) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder && Math.abs(leftShoulder.positionRaw[1] - rightShoulder.positionRaw[1]) > 0.1) {\n      gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position[1] > rightShoulder.position[1]) ? 'left' : 'right'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const face = (res: FaceResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: FaceGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 450) {\n      const zDiff = (res[i].mesh[33][2] || 0) - (res[i].mesh[263][2] || 0);\n      const xDiff = res[i].mesh[33][0] - res[i].mesh[263][0];\n      if (Math.abs(zDiff / xDiff) <= 0.15) gestures.push({ face: i, gesture: 'facing center' });\n      else gestures.push({ face: i, gesture: `facing ${zDiff < 0 ? 'left' : 'right'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2] || 0;\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res: FaceResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: IrisGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.leftEyeIris[0] || !res[i].annotations.rightEyeIris || !res[i].annotations.rightEyeIris[0]) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    let center = false;\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) {\n      center = true;\n      gestures.push({ iris: i, gesture: 'facing center' });\n    }\n\n    const leftIrisCenterX = Math.abs(res[i].mesh[263][0] - res[i].annotations.leftEyeIris[0][0]) / res[i].box[2];\n    const rightIrisCenterX = Math.abs(res[i].mesh[33][0] - res[i].annotations.rightEyeIris[0][0]) / res[i].box[2];\n    if (leftIrisCenterX > 0.06 || rightIrisCenterX > 0.06) center = false;\n    if (leftIrisCenterX > rightIrisCenterX) { // check eye with bigger offset\n      if (leftIrisCenterX > 0.05) gestures.push({ iris: i, gesture: 'looking right' });\n    } else {\n      if (rightIrisCenterX > 0.05) gestures.push({ iris: i, gesture: 'looking left' });\n    }\n\n    const rightIrisCenterY = Math.abs(res[i].mesh[145][1] - res[i].annotations.rightEyeIris[0][1]) / res[i].box[3];\n    const leftIrisCenterY = Math.abs(res[i].mesh[374][1] - res[i].annotations.leftEyeIris[0][1]) / res[i].box[3];\n    if (leftIrisCenterY < 0.01 || rightIrisCenterY < 0.01 || leftIrisCenterY > 0.022 || rightIrisCenterY > 0.022) center = false;\n    if (leftIrisCenterY < 0.01 || rightIrisCenterY < 0.01) gestures.push({ iris: i, gesture: 'looking down' });\n    if (leftIrisCenterY > 0.022 || rightIrisCenterY > 0.022) gestures.push({ iris: i, gesture: 'looking up' });\n\n    // still center;\n    if (center) gestures.push({ iris: i, gesture: 'looking center' });\n  }\n  return gestures;\n};\n\nexport const hand = (res: HandResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: HandGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: Point }> = [];\n    if (res[i]['annotations']) {\n      for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n        if (finger !== 'palmBase' && Array.isArray(pos) && pos[0]) fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n      }\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => ((best.position[2] || 0) < (a.position[2] || 0) ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward` as HandGesture });\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${highest.name} up` as HandGesture });\n    }\n    if (res[i]['keypoints']) {\n      const poses = fingerPose.match(res[i]['keypoints']);\n      for (const pose of poses) gestures.push({ hand: i, gesture: pose.name as HandGesture });\n    }\n  }\n  return gestures;\n};\n", "/**\n * Results interpolation for smoothening of video detection results inbetween detected frames\n */\n\nimport type { Result, FaceResult, BodyResult, HandResult, ObjectResult, GestureResult, PersonResult, Box, Point, BodyLandmark, BodyAnnotation } from '../result';\nimport type { Config } from '../config';\n\nimport * as moveNetCoords from '../body/movenetcoords';\nimport * as blazePoseCoords from '../body/blazeposecoords';\nimport * as efficientPoseCoords from '../body/efficientposecoords';\nimport { now } from './util';\nimport { env } from './env';\n\nconst bufferedResult: Result = { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0, error: null };\nlet interpolateTime = 0;\n\nexport function calc(newResult: Result, config: Config): Result {\n  const t0 = now();\n  if (!newResult) return { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0, error: null };\n  // each record is only updated using deep clone when number of detected record changes, otherwise it will converge by itself\n  // otherwise bufferedResult is a shallow clone of result plus updated local calculated values\n  // thus mixing by-reference and by-value assignments to minimize memory operations\n\n  const elapsed = Date.now() - newResult.timestamp;\n  // curve fitted: buffer = 8 - ln(delay)\n  // interpolation formula: current = ((buffer - 1) * previous + live) / buffer\n  // - at  50ms delay buffer = ~4.1 => 28% towards live data\n  // - at 250ms delay buffer = ~2.5 => 40% towards live data\n  // - at 500ms delay buffer = ~1.8 => 55% towards live data\n  // - at 750ms delay buffer = ~1.4 => 71% towards live data\n  // - at  1sec delay buffer = 1 which means live data is used\n  const bufferedFactor = elapsed < 1000 ? 8 - Math.log(elapsed + 1) : 1;\n\n  if (newResult.canvas) bufferedResult.canvas = newResult.canvas;\n  if (newResult.error) bufferedResult.error = newResult.error;\n\n  // interpolate body results\n  if (!bufferedResult.body || (newResult.body.length !== bufferedResult.body.length)) {\n    bufferedResult.body = JSON.parse(JSON.stringify(newResult.body as BodyResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.body.length; i++) {\n      const box = newResult.body[i].box // update box\n        .map((newBoxCoord, j) => ((bufferedFactor - 1) * bufferedResult.body[i].box[j] + newBoxCoord) / bufferedFactor) as Box;\n      const boxRaw = newResult.body[i].boxRaw // update boxRaw\n        .map((newBoxCoord, j) => ((bufferedFactor - 1) * bufferedResult.body[i].boxRaw[j] + newBoxCoord) / bufferedFactor) as Box;\n      const keypoints = (newResult.body[i].keypoints // update keypoints\n        .map((newKpt, j) => ({\n          score: newKpt.score,\n          part: newKpt.part as BodyLandmark,\n          position: [\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].position[0] || 0) + (newKpt.position[0] || 0)) / bufferedFactor : newKpt.position[0],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].position[1] || 0) + (newKpt.position[1] || 0)) / bufferedFactor : newKpt.position[1],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].position[2] || 0) + (newKpt.position[2] || 0)) / bufferedFactor : newKpt.position[2],\n          ],\n          positionRaw: [\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].positionRaw[0] || 0) + (newKpt.positionRaw[0] || 0)) / bufferedFactor : newKpt.positionRaw[0],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].positionRaw[1] || 0) + (newKpt.positionRaw[1] || 0)) / bufferedFactor : newKpt.positionRaw[1],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].positionRaw[2] || 0) + (newKpt.positionRaw[2] || 0)) / bufferedFactor : newKpt.positionRaw[2],\n          ],\n          distance: [\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].distance?.[0] || 0) + (newKpt.distance?.[0] || 0)) / bufferedFactor : newKpt.distance?.[0],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].distance?.[1] || 0) + (newKpt.distance?.[1] || 0)) / bufferedFactor : newKpt.distance?.[1],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].distance?.[2] || 0) + (newKpt.distance?.[2] || 0)) / bufferedFactor : newKpt.distance?.[2],\n          ],\n        }))) as Array<{ score: number, part: BodyLandmark, position: [number, number, number?], positionRaw: [number, number, number?] }>;\n\n      const annotations: Record<BodyAnnotation, Point[][]> = {} as Record<BodyAnnotation, Point[][]>; // recreate annotations\n      let coords = { connected: {} };\n      if (config.body?.modelPath?.includes('efficientpose')) coords = efficientPoseCoords;\n      else if (config.body?.modelPath?.includes('blazepose')) coords = blazePoseCoords;\n      else if (config.body?.modelPath?.includes('movenet')) coords = moveNetCoords;\n      for (const [name, indexes] of Object.entries(coords.connected as Record<string, string[]>)) {\n        const pt: Array<Point[]> = [];\n        for (let j = 0; j < indexes.length - 1; j++) {\n          const pt0 = keypoints.find((kp) => kp.part === indexes[j]);\n          const pt1 = keypoints.find((kp) => kp.part === indexes[j + 1]);\n          // if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n          if (pt0 && pt1) pt.push([pt0.position, pt1.position]);\n        }\n        annotations[name] = pt;\n      }\n      bufferedResult.body[i] = { ...newResult.body[i], box, boxRaw, keypoints, annotations: annotations as BodyResult['annotations'] }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate hand results\n  if (!bufferedResult.hand || (newResult.hand.length !== bufferedResult.hand.length)) {\n    bufferedResult.hand = JSON.parse(JSON.stringify(newResult.hand as HandResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.hand.length; i++) {\n      const box = (newResult.hand[i].box// update box\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.hand[i].box[j] + b) / bufferedFactor)) as Box;\n      const boxRaw = (newResult.hand[i].boxRaw // update boxRaw\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.hand[i].boxRaw[j] + b) / bufferedFactor)) as Box;\n      if (bufferedResult.hand[i].keypoints.length !== newResult.hand[i].keypoints.length) bufferedResult.hand[i].keypoints = newResult.hand[i].keypoints; // reset keypoints as previous frame did not have them\n      const keypoints = newResult.hand[i].keypoints && newResult.hand[i].keypoints.length > 0 ? newResult.hand[i].keypoints // update landmarks\n        .map((landmark, j) => landmark\n          .map((coord, k) => (((bufferedFactor - 1) * (bufferedResult.hand[i].keypoints[j][k] || 1) + (coord || 0)) / bufferedFactor)) as Point)\n        : [];\n      let annotations = {};\n      if (Object.keys(bufferedResult.hand[i].annotations).length !== Object.keys(newResult.hand[i].annotations).length) {\n        bufferedResult.hand[i].annotations = newResult.hand[i].annotations; // reset annotations as previous frame did not have them\n        annotations = bufferedResult.hand[i].annotations;\n      } else if (newResult.hand[i].annotations) {\n        for (const key of Object.keys(newResult.hand[i].annotations)) { // update annotations\n          annotations[key] = newResult.hand[i].annotations[key] && newResult.hand[i].annotations[key][0]\n            ? newResult.hand[i].annotations[key]\n              .map((val, j: number) => val\n                .map((coord: number, k: number) => ((bufferedFactor - 1) * bufferedResult.hand[i].annotations[key][j][k] + coord) / bufferedFactor))\n            : null;\n        }\n      }\n      bufferedResult.hand[i] = { ...newResult.hand[i], box, boxRaw, keypoints, annotations: annotations as HandResult['annotations'] }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate face results\n  if (!bufferedResult.face || (newResult.face.length !== bufferedResult.face.length)) {\n    bufferedResult.face = JSON.parse(JSON.stringify(newResult.face as FaceResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.face.length; i++) {\n      const box = (newResult.face[i].box // update box\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i].box[j] + b) / bufferedFactor)) as Box;\n      const boxRaw = (newResult.face[i].boxRaw // update boxRaw\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i].boxRaw[j] + b) / bufferedFactor)) as Box;\n      if (newResult.face[i].rotation) {\n        const rotation: {\n          matrix: [number, number, number, number, number, number, number, number, number],\n          angle: { roll: number, yaw: number, pitch: number },\n          gaze: { bearing: number, strength: number }\n        } = { matrix: [0, 0, 0, 0, 0, 0, 0, 0, 0], angle: { roll: 0, yaw: 0, pitch: 0 }, gaze: { bearing: 0, strength: 0 } };\n        rotation.matrix = newResult.face[i].rotation?.matrix as [number, number, number, number, number, number, number, number, number];\n        rotation.angle = {\n          roll: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.roll || 0) + (newResult.face[i].rotation?.angle?.roll || 0)) / bufferedFactor,\n          yaw: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.yaw || 0) + (newResult.face[i].rotation?.angle?.yaw || 0)) / bufferedFactor,\n          pitch: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.pitch || 0) + (newResult.face[i].rotation?.angle?.pitch || 0)) / bufferedFactor,\n        };\n        rotation.gaze = {\n          // not fully correct due projection on circle, also causes wrap-around draw on jump from negative to positive\n          bearing: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.gaze?.bearing || 0) + (newResult.face[i].rotation?.gaze?.bearing || 0)) / bufferedFactor,\n          strength: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.gaze?.strength || 0) + (newResult.face[i].rotation?.gaze?.strength || 0)) / bufferedFactor,\n        };\n        bufferedResult.face[i] = { ...newResult.face[i], rotation, box, boxRaw }; // shallow clone plus updated values\n      }\n      bufferedResult.face[i] = { ...newResult.face[i], box, boxRaw }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate object detection results\n  if (!bufferedResult.object || (newResult.object.length !== bufferedResult.object.length)) {\n    bufferedResult.object = JSON.parse(JSON.stringify(newResult.object as ObjectResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.object.length; i++) {\n      const box = (newResult.object[i].box // update box\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.object[i].box[j] + b) / bufferedFactor)) as Box;\n      const boxRaw = (newResult.object[i].boxRaw // update boxRaw\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.object[i].boxRaw[j] + b) / bufferedFactor)) as Box;\n      bufferedResult.object[i] = { ...newResult.object[i], box, boxRaw }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate person results\n  if (newResult.persons) {\n    const newPersons = newResult.persons; // trigger getter function\n    if (!bufferedResult.persons || (newPersons.length !== bufferedResult.persons.length)) {\n      bufferedResult.persons = JSON.parse(JSON.stringify(newPersons as PersonResult[]));\n    } else {\n      for (let i = 0; i < newPersons.length; i++) { // update person box, we don't update the rest as it's updated as reference anyhow\n        bufferedResult.persons[i].box = (newPersons[i].box\n          .map((box, j) => ((bufferedFactor - 1) * bufferedResult.persons[i].box[j] + box) / bufferedFactor)) as Box;\n      }\n    }\n  }\n\n  // just copy latest gestures without interpolation\n  if (newResult.gesture) bufferedResult.gesture = newResult.gesture as GestureResult[];\n\n  // append interpolation performance data\n  const t1 = now();\n  interpolateTime = env.perfadd ? interpolateTime + Math.round(t1 - t0) : Math.round(t1 - t0);\n  if (newResult.performance) bufferedResult.performance = { ...newResult.performance, interpolate: interpolateTime };\n\n  return bufferedResult;\n}\n", "/** Face descriptor type as number array */\nexport type Descriptor = Array<number>\nexport type MatchOptions = { order?: number, threshold?: number, multiplier?: number, min?: number, max?: number } | undefined;\n\n/** Calculates distance between two descriptors\n * @param options - calculation options\n * - order - algorithm to use\n *   Euclidean distance if `order` is 2 (default), Minkowski distance algorithm of nth order if `order` is higher than 2\n * - multiplier - by how much to enhance difference analysis in range of 1..100\n *   default is 20 which normalizes results to similarity above 0.5 can be considered a match\n */\nexport function distance(descriptor1: Descriptor, descriptor2: Descriptor, options: MatchOptions = { order: 2, multiplier: 25 }) {\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  let sum = 0;\n  for (let i = 0; i < descriptor1.length; i++) {\n    const diff = (!options.order || options.order === 2) ? (descriptor1[i] - descriptor2[i]) : (Math.abs(descriptor1[i] - descriptor2[i]));\n    sum += (!options.order || options.order === 2) ? (diff * diff) : (diff ** options.order);\n  }\n  return (options.multiplier || 20) * sum;\n}\n\n// invert distance to similarity, normalize to given range and clamp\nconst normalizeDistance = (dist, order, min, max) => {\n  if (dist === 0) return 1; // short circuit for identical inputs\n  const root = order === 2 ? Math.sqrt(dist) : dist ** (1 / order); // take root of distance\n  const norm = (1 - (root / 100) - min) / (max - min); // normalize to range\n  const clamp = Math.max(Math.min(norm, 1), 0); // clamp to 0..1\n  return clamp;\n};\n\n/** Calculates normalized similarity between two face descriptors based on their `distance`\n * @param options - calculation options\n * - order - algorithm to use\n *   Euclidean distance if `order` is 2 (default), Minkowski distance algorithm of nth order if `order` is higher than 2\n * - multiplier - by how much to enhance difference analysis in range of 1..100\n *   default is 20 which normalizes results to similarity above 0.5 can be considered a match\n * - min - normalize similarity result to a given range\n * - max - normalzie similarity resutl to a given range\n *   default is 0.2...0.8\n * Returns similarity between two face descriptors normalized to 0..1 range where 0 is no similarity and 1 is perfect similarity\n */\nexport function similarity(descriptor1: Descriptor, descriptor2: Descriptor, options: MatchOptions = { order: 2, multiplier: 25, min: 0.2, max: 0.8 }) {\n  const dist = distance(descriptor1, descriptor2, options);\n  return normalizeDistance(dist, options.order || 2, options.min || 0, options.max || 1);\n}\n\n/** Matches given descriptor to a closest entry in array of descriptors\n * @param descriptor - face descriptor\n * @param descriptors - array of face descriptors to commpare given descriptor to\n * @param options - see `similarity` method for options description\n * Returns\n * - `index` index array index where best match was found or -1 if no matches\n * - `distance` calculated `distance` of given descriptor to the best match\n * - `similarity` calculated normalized `similarity` of given descriptor to the best match\n*/\nexport function match(descriptor: Descriptor, descriptors: Array<Descriptor>, options: MatchOptions = { order: 2, multiplier: 25, threshold: 0, min: 0.2, max: 0.8 }) {\n  if (!Array.isArray(descriptor) || !Array.isArray(descriptors) || descriptor.length < 64 || descriptors.length === 0 || descriptor.length !== descriptors[0].length) { // validate input\n    return { index: -1, distance: Number.POSITIVE_INFINITY, similarity: 0 };\n  }\n  let lowestDistance = Number.MAX_SAFE_INTEGER;\n  let index = -1;\n  for (let i = 0; i < descriptors.length; i++) {\n    const res = distance(descriptor, descriptors[i], options);\n    if (res < lowestDistance) {\n      lowestDistance = res;\n      index = i;\n    }\n    if (lowestDistance < (options.threshold || 0)) break;\n  }\n  const normalizedSimilarity = normalizeDistance(lowestDistance, options.order || 2, options.min || 0, options.max || 1);\n  return { index, distance: lowestDistance, similarity: normalizedSimilarity };\n}\n", "/**\n * Analyze detection Results and sort&combine them into per-person view\n */\n\nimport type { FaceResult, BodyResult, HandResult, GestureResult, PersonResult, Box } from '../result';\n\nexport function join(faces: Array<FaceResult>, bodies: Array<BodyResult>, hands: Array<HandResult>, gestures: Array<GestureResult>, shape: Array<number> | undefined): Array<PersonResult> {\n  let id = 0;\n  const persons: Array<PersonResult> = [];\n  for (const face of faces) { // person is defined primarily by face and then we append other objects as found\n    const person: PersonResult = { id: id++, face, body: null, hands: { left: null, right: null }, gestures: [], box: [0, 0, 0, 0] };\n    for (const body of bodies) {\n      if (face.box[0] > body.box[0] // x within body\n        && face.box[0] < body.box[0] + body.box[2]\n        && face.box[1] + face.box[3] > body.box[1] // y within body\n        && face.box[1] + face.box[3] < body.box[1] + body.box[3]) {\n        person.body = body;\n      }\n    }\n    if (person.body) { // only try to join hands if body is found\n      for (const hand of hands) {\n        if (hand.box[0] + hand.box[2] > person.body.box[0] // x within body for left hand\n          && hand.box[0] + hand.box[2] < person.body.box[0] + person.body.box[2]\n          && hand.box[1] + hand.box[3] > person.body.box[1] // x within body for left hand\n          && hand.box[1] + hand.box[3] < person.body.box[1] + person.body.box[3]) {\n          if (person.hands) person.hands.left = hand;\n        }\n        if (hand.box[0] < person.body.box[0] + person.body.box[2] // x within body for right hand\n          && hand.box[0] > person.body.box[0]\n          && hand.box[1] + hand.box[3] > person.body.box[1] // x within body for right hand\n          && hand.box[1] + hand.box[3] < person.body.box[1] + person.body.box[3]) {\n          if (person.hands) person.hands.right = hand;\n        }\n      }\n    }\n    for (const gesture of gestures) { // append all gestures according to ids\n      if (gesture['face'] !== undefined && gesture['face'] === face.id) person.gestures?.push(gesture);\n      else if (gesture['iris'] !== undefined && gesture['iris'] === face.id) person.gestures?.push(gesture);\n      else if (gesture['body'] !== undefined && gesture['body'] === person.body?.id) person.gestures?.push(gesture);\n      else if (gesture['hand'] !== undefined && gesture['hand'] === person.hands?.left?.id) person.gestures?.push(gesture);\n      else if (gesture['hand'] !== undefined && gesture['hand'] === person.hands?.right?.id) person.gestures?.push(gesture);\n    }\n\n    // create new overarching box from all boxes belonging to person\n    const x: number[] = [];\n    const y: number[] = [];\n    const extractXY = (box: Box | undefined) => { // extract all [x, y] coordinates from boxes [x, y, width, height]\n      if (box && box.length === 4) {\n        x.push(box[0], box[0] + box[2]);\n        y.push(box[1], box[1] + box[3]);\n      }\n    };\n    extractXY(person.face?.box);\n    extractXY(person.body?.box);\n    extractXY(person.hands?.left?.box);\n    extractXY(person.hands?.right?.box);\n    const minX = Math.min(...x);\n    const minY = Math.min(...y);\n    person.box = [minX, minY, Math.max(...x) - minX, Math.max(...y) - minY]; // create new overarching box\n\n    // shape is known so we calculate boxRaw as well\n    if (shape && shape[1] && shape[2]) person.boxRaw = [person.box[0] / shape[2], person.box[1] / shape[1], person.box[2] / shape[2], person.box[3] / shape[1]];\n\n    persons.push(person);\n  }\n  return persons;\n}\n", "/**\n * Embedded sample images used during warmup in dataURL format\n */\n\n// data:image/jpeg;base64,\nexport const face = `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`;\n\n// data:image/jpeg;base64,\nexport const body = `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\n2Q==`;\n", "/**\n * Warmup algorithm that uses embedded images to exercise loaded models for faster future inference\n */\n\nimport { log, now, mergeDeep } from './util/util';\nimport * as sample from './sample';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as image from './image/image';\nimport { env } from './util/env';\nimport type { Config } from './config';\nimport type { Result } from './result';\nimport type { Human, Models } from './human';\nimport type { Tensor } from './tfjs/types';\n\nasync function warmupBitmap(instance: Human): Promise<Result | undefined> {\n  const b64toBlob = (base64: string, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n  let blob;\n  let res;\n  switch (instance.config.warmup) {\n    case 'face': blob = await b64toBlob(sample.face); break;\n    case 'body':\n    case 'full': blob = await b64toBlob(sample.body); break;\n    default: blob = null;\n  }\n  if (blob) {\n    const bitmap = await createImageBitmap(blob);\n    res = await instance.detect(bitmap, instance.config);\n    bitmap.close();\n  }\n  return res;\n}\n\nasync function warmupCanvas(instance: Human): Promise<Result | undefined> {\n  return new Promise((resolve) => {\n    let src;\n    // let size = 0;\n    switch (instance.config.warmup) {\n      case 'face':\n        // size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        // size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    let img: HTMLImageElement;\n    if (typeof Image !== 'undefined') img = new Image();\n    // @ts-ignore env.image is an external monkey-patch\n    else if (env.Image) img = new env.Image();\n    else return;\n    img.onload = async () => {\n      const canvas = image.canvas(img.naturalWidth, img.naturalHeight);\n      if (!canvas) {\n        log('Warmup: Canvas not found');\n        resolve(undefined);\n      } else {\n        const ctx = canvas.getContext('2d');\n        if (ctx) ctx.drawImage(img, 0, 0);\n        // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n        const tensor = await instance.image(canvas);\n        const res = await instance.detect(tensor.tensor as Tensor, instance.config);\n        resolve(res);\n      }\n    };\n    if (src) img.src = src;\n    else resolve(undefined);\n  });\n}\n\nasync function warmupNode(instance: Human): Promise<Result | undefined> {\n  const atob = (str: string) => Buffer.from(str, 'base64');\n  let img;\n  if (instance.config.warmup === 'face') img = atob(sample.face);\n  else img = atob(sample.body);\n  let res;\n  if ('node' in tf) {\n    // @ts-ignore tf.node may be undefined\n    const data = tf['node'].decodeJpeg(img);\n    const expanded = data.expandDims(0);\n    instance.tf.dispose(data);\n    // log('Input:', expanded);\n    res = await instance.detect(expanded, instance.config);\n    instance.tf.dispose(expanded);\n  } else {\n    if (instance.config.debug) log('Warmup tfjs-node not loaded');\n    /*\n    const input = await canvasJS.loadImage(img);\n    const canvas = canvasJS.createCanvas(input.width, input.height);\n    const ctx = canvas.getContext('2d');\n    ctx.drawImage(img, 0, 0, input.width, input.height);\n    res = await instance.detect(input, instance.config);\n    */\n  }\n  return res;\n}\n\nasync function runInference(instance: Human) {\n  let res: Result | undefined;\n  if (typeof createImageBitmap === 'function') res = await warmupBitmap(instance);\n  else if (typeof Image !== 'undefined' || env.Canvas !== undefined) res = await warmupCanvas(instance);\n  else res = await warmupNode(instance);\n  return res;\n}\n\n/** Runs pre-compile on all loaded models */\nexport async function runCompile(allModels: Models) {\n  const backendType = tf.getBackend();\n  const webGLBackend = tf.backend();\n  if ((backendType !== 'webgl' && backendType !== 'humangl') || (!webGLBackend || !webGLBackend.checkCompileCompletion)) {\n    // log('compile pass: skip');\n    return;\n  }\n  tf.env().set('ENGINE_COMPILE_ONLY', true);\n  const numTensorsStart = tf.engine().state.numTensors;\n  const compiledModels: string[] = [];\n  for (const [modelName, model] of Object.entries(allModels).filter(([key, val]) => (key !== null && val !== null))) {\n    const shape = (model.inputs && model.inputs[0] && model.inputs[0].shape) ? [...model.inputs[0].shape] : [1, 64, 64, 3];\n    const dtype = (model.inputs && model.inputs[0] && model.inputs[0].dtype) ? model.inputs[0].dtype : 'float32';\n    for (let dim = 0; dim < shape.length; dim++) {\n      if (shape[dim] === -1) shape[dim] = dim === 0 ? 1 : 64; // override batch number and any dynamic dimensions\n    }\n    const tensor = tf.zeros(shape, dtype);\n    // const res = await model.executeAsync(tensor); // fails with current tfjs\n    try {\n      const res = model.execute(tensor);\n      compiledModels.push(modelName);\n      if (Array.isArray(res)) res.forEach((t) => tf.dispose(t));\n      else tf.dispose(res);\n    } catch {\n      log('compile fail model:', modelName);\n    }\n    tf.dispose(tensor);\n  }\n  const kernels = await webGLBackend.checkCompileCompletionAsync();\n  webGLBackend.getUniformLocations();\n  log('compile pass models:', compiledModels);\n  log('compile pass kernels:', kernels.length);\n  tf.env().set('ENGINE_COMPILE_ONLY', false);\n  const numTensorsEnd = tf.engine().state.numTensors;\n  if ((numTensorsEnd - numTensorsStart) > 0) log('tensor leak:', numTensorsEnd - numTensorsStart);\n}\n\n/** Warmup method pre-initializes all configured models for faster inference\n * - can take significant time on startup\n * - only used in browser environments for `webgl` and `humangl` backends\n * @param userConfig?: Config\n*/\nexport async function warmup(instance: Human, userConfig?: Partial<Config>): Promise<Result | undefined> {\n  const t0 = now();\n  instance.state = 'warmup';\n  if (userConfig) instance.config = mergeDeep(instance.config, userConfig) as Config;\n  if (!instance.config.warmup || instance.config.warmup.length === 0 || instance.config.warmup === 'none') {\n    return { face: [], body: [], hand: [], gesture: [], object: [], performance: instance.performance, timestamp: now(), persons: [], error: null };\n  }\n  return new Promise(async (resolve) => {\n    await runCompile(instance.models);\n    const res = await runInference(instance);\n    const t1 = now();\n    if (instance.config.debug) log('warmup', instance.config.warmup, Math.round(t1 - t0), 'ms');\n    instance.emit('warmup');\n    resolve(res);\n  });\n}\n", "/**\n * Human main module\n * @default Human Library\n * @summary <https://github.com/vladmandic/human>\n * @author <https://github.com/vladmandic>\n * @copyright <https://github.com/vladmandic>\n * @license MIT\n */\n\n// module imports\nimport { log, now, mergeDeep, validate } from './util/util';\nimport { defaults } from './config';\nimport { env, Env } from './util/env';\nimport { setModelLoadOptions } from './tfjs/load';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as app from '../package.json';\nimport * as backend from './tfjs/backend';\nimport * as blazepose from './body/blazepose';\nimport * as centernet from './object/centernet';\nimport * as draw from './draw/draw';\nimport * as efficientpose from './body/efficientpose';\nimport * as face from './face/face';\nimport * as facemesh from './face/facemesh';\nimport * as faceres from './face/faceres';\nimport * as gesture from './gesture/gesture';\nimport * as handpose from './hand/handpose';\nimport * as handtrack from './hand/handtrack';\nimport * as humangl from './tfjs/humangl';\nimport * as image from './image/image';\nimport * as interpolate from './util/interpolate';\nimport * as match from './face/match';\nimport * as models from './models';\nimport * as movenet from './body/movenet';\nimport * as nanodet from './object/nanodet';\nimport * as persons from './util/persons';\nimport * as posenet from './body/posenet';\nimport * as segmentation from './segmentation/segmentation';\nimport * as warmups from './warmup';\n// type definitions\nimport type { Input, Tensor, DrawOptions, Config, Result, FaceResult, HandResult, BodyResult, ObjectResult, GestureResult, PersonResult, AnyCanvas, ModelStats } from './exports';\n// type exports\nexport * from './exports';\n\n/** **Human** library main class\n *\n * All methods and properties are available only as members of Human class\n *\n * - Configuration object definition: {@link Config}\n * - Results object definition: {@link Result}\n * - Possible inputs: {@link Input}\n *\n * @param userConfig - {@link Config}\n * @returns instance of {@link Human}\n */\nexport class Human {\n  /** Current version of Human library in *semver* format */\n  version: string;\n\n  /** Current configuration\n   * - Defaults: [config](https://github.com/vladmandic/human/blob/main/src/config.ts#L262)\n   */\n  config: Config;\n\n  /** Last known result of detect run\n   * - Can be accessed anytime after initial detection\n  */\n  result: Result;\n\n  /** Current state of Human library\n   * - Can be polled to determine operations that are currently executed\n   * - Progresses through: 'config', 'check', 'backend', 'load', 'run:<model>', 'idle'\n   */\n  state: string;\n\n  /** currenty processed image tensor and canvas */\n  process: { tensor: Tensor | null, canvas: AnyCanvas | null };\n\n  /** Instance of TensorFlow/JS used by Human\n   *  - Can be embedded or externally provided\n   * [TFJS API](https://js.tensorflow.org/api/latest/)\n   */\n  tf;\n\n  /** Object containing environment information used for diagnostics */\n  env: Env;\n\n  /** Draw helper classes that can draw detected objects on canvas using specified draw\n   * - canvas: draws input to canvas\n   * - options: are global settings for all draw operations, can be overriden for each draw method {@link DrawOptions}\n   * - face, body, hand, gesture, object, person: draws detected results as overlays on canvas\n   */\n  draw: { canvas: typeof draw.canvas, face: typeof draw.face, body: typeof draw.body, hand: typeof draw.hand, gesture: typeof draw.gesture, object: typeof draw.object, person: typeof draw.person, all: typeof draw.all, options: DrawOptions };\n\n  /** Currently loaded models\n   * @internal\n   * {@link Models}\n  */\n  models: models.Models;\n\n  /** Container for events dispatched by Human\n   * Possible events:\n   * - `create`: triggered when Human object is instantiated\n   * - `load`: triggered when models are loaded (explicitly or on-demand)\n   * - `image`: triggered when input image is processed\n   * - `result`: triggered when detection is complete\n   * - `warmup`: triggered when warmup is complete\n   * - `error`: triggered on some errors\n   */\n  events: EventTarget | undefined;\n  /** Reference face triangualtion array of 468 points, used for triangle references between points */\n  faceTriangulation: number[];\n  /** Refernce UV map of 468 values, used for 3D mapping of the face mesh */\n  faceUVMap: [number, number][];\n  /** Performance object that contains values for all recently performed operations */\n  performance: Record<string, number>; // perf members are dynamically defined as needed\n  #numTensors: number;\n  #analyzeMemoryLeaks: boolean;\n  #checkSanity: boolean;\n  /** WebGL debug info */\n  gl: Record<string, unknown>;\n  // definition end\n\n  /** Constructor for **Human** library that is futher used for all operations\n   * @param userConfig - user configuration object {@link Config}\n   */\n  constructor(userConfig?: Partial<Config>) {\n    this.env = env;\n    /*\n    defaults.wasmPath = tf.version['tfjs-core'].includes('-') // custom build or official build\n      ? 'https://vladmandic.github.io/tfjs/dist/'\n      : `https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${tf.version_core}/dist/`;\n    */\n    const tfVersion = (tf.version?.tfjs || tf.version_core).replace(/-(.*)/, '');\n    defaults.wasmPath = `https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${tfVersion}/dist/`;\n    defaults.modelBasePath = env.browser ? '../models/' : 'file://models/';\n    defaults.backend = env.browser ? 'humangl' : 'tensorflow';\n    this.version = app.version; // expose version property on instance of class\n    Object.defineProperty(this, 'version', { value: app.version }); // expose version property directly on class itself\n    this.config = JSON.parse(JSON.stringify(defaults));\n    Object.seal(this.config);\n    this.config.cacheModels = typeof indexedDB !== 'undefined';\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    setModelLoadOptions(this.config);\n    this.tf = tf;\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.performance = {};\n    this.events = (typeof EventTarget !== 'undefined') ? new EventTarget() : undefined;\n    // object that contains all initialized models\n    this.models = new models.Models();\n    // reexport draw methods\n    this.draw = {\n      options: draw.options as DrawOptions,\n      canvas: (input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas) => draw.canvas(input, output),\n      face: (output: AnyCanvas, result: FaceResult[], options?: Partial<DrawOptions>) => draw.face(output, result, options),\n      body: (output: AnyCanvas, result: BodyResult[], options?: Partial<DrawOptions>) => draw.body(output, result, options),\n      hand: (output: AnyCanvas, result: HandResult[], options?: Partial<DrawOptions>) => draw.hand(output, result, options),\n      gesture: (output: AnyCanvas, result: GestureResult[], options?: Partial<DrawOptions>) => draw.gesture(output, result, options),\n      object: (output: AnyCanvas, result: ObjectResult[], options?: Partial<DrawOptions>) => draw.object(output, result, options),\n      person: (output: AnyCanvas, result: PersonResult[], options?: Partial<DrawOptions>) => draw.person(output, result, options),\n      all: (output: AnyCanvas, result: Result, options?: Partial<DrawOptions>) => draw.all(output, result, options),\n    };\n    this.result = { face: [], body: [], hand: [], gesture: [], object: [], performance: {}, timestamp: 0, persons: [], error: null };\n    // export access to image processing\n    // @ts-ignore eslint-typescript cannot correctly infer type in anonymous function\n    this.process = { tensor: null, canvas: null };\n    // export raw access to underlying models\n    this.faceTriangulation = facemesh.triangulation;\n    this.faceUVMap = facemesh.uvmap;\n    // set gl info\n    this.gl = humangl.config;\n    // include platform info\n    this.emit('create');\n  }\n\n  /** internal function to measure tensor leaks */\n  analyze = (...msg: string[]) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const currentTensors = this.tf.engine().state.numTensors;\n    const previousTensors = this.#numTensors;\n    this.#numTensors = currentTensors;\n    const leaked = currentTensors - previousTensors;\n    if (leaked !== 0) log(...msg, leaked);\n  };\n\n  /** internal function for quick sanity check on inputs @hidden */\n  #sanity = (input: Input): null | string => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.env.node && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  };\n\n  /** Reset configuration to default values */\n  reset(): void {\n    const currentBackend = this.config.backend; // save backend;\n    this.config = JSON.parse(JSON.stringify(defaults));\n    this.config.backend = currentBackend;\n  }\n\n  /** Validate current configuration schema */\n  validate(userConfig?: Partial<Config>) {\n    return validate(defaults, userConfig || this.config);\n  }\n\n  /** Exports face matching methods {@link match#similarity} */\n  public similarity = match.similarity;\n  /** Exports face matching methods {@link match#distance} */\n  public distance = match.distance;\n  /** Exports face matching methods {@link match#match} */\n  public match = match.match;\n\n  /** Utility wrapper for performance.now() */\n  now(): number {\n    return now();\n  }\n\n  /** Process input as return canvas and tensor\n   *\n   * @param input - any input {@link Input}\n   * @param getTensor - should image processing also return tensor or just canvas\n   * Returns object with `tensor` and `canvas`\n   */\n  image(input: Input, getTensor: boolean = true) {\n    return image.process(input, this.config, getTensor);\n  }\n\n  /** Segmentation method takes any input and returns processed canvas with body segmentation\n   *  - Segmentation is not triggered as part of detect process\n   * @param input - {@link Input}\n   * @param background - {@link Input}\n   *  - Optional parameter background is used to fill the background with specific input\n   *  Returns:\n   *  - `data` as raw data array with per-pixel segmentation values\n   *  - `canvas` as canvas which is input image filtered with segementation data and optionally merged with background image. canvas alpha values are set to segmentation values for easy merging\n   *  - `alpha` as grayscale canvas that represents segmentation alpha values\n   */\n  async segmentation(input: Input, background?: Input): Promise<{ data: number[] | Tensor, canvas: AnyCanvas | null, alpha: AnyCanvas | null }> {\n    return segmentation.process(input, background, this.config);\n  }\n\n  /** Enhance method performs additional enhacements to face image previously detected for futher processing\n   *\n   * @param input - Tensor as provided in human.result.face[n].tensor\n   * @returns Tensor\n   */\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return faceres.enhance(input);\n  }\n\n  /** Compare two input tensors for pixel simmilarity\n   * - use `human.image` to process any valid input and get a tensor that can be used for compare\n   * - when passing manually generated tensors:\n   *  - both input tensors must be in format [1, height, width, 3]\n   *  - if resolution of tensors does not match, second tensor will be resized to match resolution of the first tensor\n   * - return value is pixel similarity score normalized by input resolution and rgb channels\n  */\n  compare(firstImageTensor: Tensor, secondImageTensor: Tensor): Promise<number> {\n    return image.compare(this.config, firstImageTensor, secondImageTensor);\n  }\n\n  /** Explicit backend initialization\n   *  - Normally done implicitly during initial load phase\n   *  - Call to explictly register and initialize TFJS backend without any other operations\n   *  - Use when changing backend during runtime\n   */\n  async init(): Promise<void> {\n    await backend.check(this, true);\n    await this.tf.ready();\n  }\n\n  /** Load method preloads all configured models on-demand\n   * - Not explicitly required as any required model is load implicitly on it's first run\n   *\n   * @param userConfig - {@link Config}\n  */\n  async load(userConfig?: Partial<Config>): Promise<void> {\n    this.state = 'load';\n    const timeStamp = now();\n    const count = Object.values(this.models).filter((model) => model).length;\n    if (userConfig) this.config = mergeDeep(this.config, userConfig) as Config;\n\n    if (this.env.initial) { // print version info on first run and check for correct backend setup\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version['tfjs-core']}`);\n      if (!await backend.check(this)) log('error: backend check failed');\n      await tf.ready();\n      if (this.env.browser) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('environment:', this.env);\n        if (this.config.debug) log('tf flags:', this.tf.ENV['flags']);\n      }\n    }\n\n    await models.load(this); // actually loads models\n    if (this.env.initial && this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors'); // print memory stats on first run\n    this.env.initial = false;\n\n    const loaded = Object.values(this.models).filter((model) => model).length;\n    if (loaded !== count) { // number of loaded models changed\n      await models.validate(this); // validate kernel ops used by model against current backend\n      this.emit('load');\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.performance.loadModels as number || 0)) this.performance.loadModels = this.env.perfadd ? (this.performance.loadModels || 0) + current : current;\n  }\n\n  /** emit event */\n  emit = (event: string) => {\n    if (this.events && this.events.dispatchEvent) this.events?.dispatchEvent(new Event(event));\n  };\n\n  /** Runs interpolation using last known result and returns smoothened result\n   * Interpolation is based on time since last known result so can be called independently\n   *\n   * @param result - {@link Result} optional use specific result set to run interpolation on\n   * @returns result - {@link Result}\n   */\n  next(result: Result = this.result): Result {\n    return interpolate.calc(result, this.config) as Result;\n  }\n\n  /** get model loading/loaded stats */\n  getModelStats(): ModelStats { return models.getModelStats(this); }\n\n  /** Warmup method pre-initializes all configured models for faster inference\n   * - can take significant time on startup\n   * - only used for `webgl` and `humangl` backends\n   * @param userConfig - {@link Config}\n   * @returns result - {@link Result}\n  */\n  async warmup(userConfig?: Partial<Config>) {\n    const t0 = now();\n    const res = await warmups.warmup(this, userConfig);\n    const t1 = now();\n    this.performance.warmup = Math.trunc(t1 - t0);\n    return res;\n  }\n\n  /** Run detect with tensorflow profiling\n   * - result object will contain total exeuction time information for top-20 kernels\n   * - actual detection object can be accessed via `human.result`\n  */\n  async profile(input: Input, userConfig?: Partial<Config>): Promise<Record<string, number>> {\n    const profile = await this.tf.profile(() => this.detect(input, userConfig));\n    const kernels: Record<string, number> = {};\n    for (const kernel of profile.kernels) { // sum kernel time values per kernel\n      if (kernels[kernel.name]) kernels[kernel.name] += kernel.kernelTimeMs;\n      else kernels[kernel.name] = kernel.kernelTimeMs;\n    }\n    const kernelArr: Array<{ name: string, ms: number }> = [];\n    Object.entries(kernels).forEach((key) => kernelArr.push({ name: key[0], ms: key[1] as unknown as number })); // convert to array\n    kernelArr.sort((a, b) => b.ms - a.ms); // sort\n    kernelArr.length = 20; // crop\n    const res: Record<string, number> = {};\n    for (const kernel of kernelArr) res[kernel.name] = kernel.ms; // create perf objects\n    return res;\n  }\n\n  /** Main detection method\n   * - Analyze configuration: {@link Config}\n   * - Pre-process input: {@link Input}\n   * - Run inference for all configured models\n   * - Process and return result: {@link Result}\n   *\n   * @param input - {@link Input}\n   * @param userConfig - {@link Config}\n   * @returns result - {@link Result}\n  */\n  async detect(input: Input, userConfig?: Partial<Config>): Promise<Result> {\n    // detection happens inside a promise\n    this.state = 'detect';\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig) as Config;\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        this.emit('error');\n        resolve({ face: [], body: [], hand: [], gesture: [], object: [], performance: this.performance, timestamp: now(), persons: [], error });\n      }\n\n      const timeStart = now();\n\n      // configure backend if needed\n      await backend.check(this);\n\n      // load models if enabled\n      await this.load();\n\n      timeStamp = now();\n      this.state = 'image';\n      const img = await image.process(input, this.config) as { canvas: AnyCanvas, tensor: Tensor };\n      this.process = img;\n      this.performance.inputProcess = this.env.perfadd ? (this.performance.inputProcess || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      this.analyze('Get Image:');\n\n      if (!img.tensor) {\n        if (this.config.debug) log('could not convert input to tensor');\n        this.emit('error');\n        resolve({ face: [], body: [], hand: [], gesture: [], object: [], performance: this.performance, timestamp: now(), persons: [], error: 'could not convert input to tensor' });\n        return;\n      }\n      this.emit('image');\n\n      timeStamp = now();\n      this.config.skipAllowed = await image.skip(this.config, img.tensor);\n      if (!this.performance.totalFrames) this.performance.totalFrames = 0;\n      if (!this.performance.cachedFrames) this.performance.cachedFrames = 0;\n      (this.performance.totalFrames as number)++;\n      if (this.config.skipAllowed) this.performance.cachedFrames++;\n      this.performance.cacheCheck = this.env.perfadd ? (this.performance.cacheCheck || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      this.analyze('Check Changed:');\n\n      // prepare where to store model results\n      // keep them with weak typing as it can be promise or not\n      let faceRes: FaceResult[] | Promise<FaceResult[]> | never[] = [];\n      let bodyRes: BodyResult[] | Promise<BodyResult[]> | never[] = [];\n      let handRes: HandResult[] | Promise<HandResult[]> | never[] = [];\n      let objectRes: ObjectResult[] | Promise<ObjectResult[]> | never[] = [];\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      this.state = 'detect:face';\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? face.detectFace(this, img.tensor) : [];\n        if (this.performance.face) delete this.performance.face;\n      } else {\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await face.detectFace(this, img.tensor) : [];\n        this.performance.face = this.env.perfadd ? (this.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n\n      if (this.config.async && (this.config.body.maxDetected === -1 || this.config.hand.maxDetected === -1)) faceRes = await faceRes; // need face result for auto-detect number of hands or bodies\n\n      // run body: can be posenet, blazepose, efficientpose, movenet\n      this.analyze('Start Body:');\n      this.state = 'detect:body';\n      const bodyConfig = this.config.body.maxDetected === -1 ? mergeDeep(this.config, { body: { maxDetected: this.config.face.enabled ? 1 * (faceRes as FaceResult[]).length : 1 } }) : this.config; // autodetect number of bodies\n      if (this.config.async) {\n        if (this.config.body.modelPath?.includes('posenet')) bodyRes = this.config.body.enabled ? posenet.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('blazepose')) bodyRes = this.config.body.enabled ? blazepose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('efficientpose')) bodyRes = this.config.body.enabled ? efficientpose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('movenet')) bodyRes = this.config.body.enabled ? movenet.predict(img.tensor, bodyConfig) : [];\n        if (this.performance.body) delete this.performance.body;\n      } else {\n        timeStamp = now();\n        if (this.config.body.modelPath?.includes('posenet')) bodyRes = this.config.body.enabled ? await posenet.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('blazepose')) bodyRes = this.config.body.enabled ? await blazepose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('efficientpose')) bodyRes = this.config.body.enabled ? await efficientpose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('movenet')) bodyRes = this.config.body.enabled ? await movenet.predict(img.tensor, bodyConfig) : [];\n        this.performance.body = this.env.perfadd ? (this.performance.body || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n      this.analyze('End Body:');\n\n      // run handpose\n      this.analyze('Start Hand:');\n      this.state = 'detect:hand';\n      const handConfig = this.config.hand.maxDetected === -1 ? mergeDeep(this.config, { hand: { maxDetected: this.config.face.enabled ? 2 * (faceRes as FaceResult[]).length : 1 } }) : this.config; // autodetect number of hands\n      if (this.config.async) {\n        if (this.config.hand.detector?.modelPath?.includes('handdetect')) handRes = this.config.hand.enabled ? handpose.predict(img.tensor, handConfig) : [];\n        else if (this.config.hand.detector?.modelPath?.includes('handtrack')) handRes = this.config.hand.enabled ? handtrack.predict(img.tensor, handConfig) : [];\n        if (this.performance.hand) delete this.performance.hand;\n      } else {\n        timeStamp = now();\n        if (this.config.hand.detector?.modelPath?.includes('handdetect')) handRes = this.config.hand.enabled ? await handpose.predict(img.tensor, handConfig) : [];\n        else if (this.config.hand.detector?.modelPath?.includes('handtrack')) handRes = this.config.hand.enabled ? await handtrack.predict(img.tensor, handConfig) : [];\n        this.performance.hand = this.env.perfadd ? (this.performance.hand || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n      this.analyze('End Hand:');\n\n      // run object detection\n      this.analyze('Start Object:');\n      this.state = 'detect:object';\n      if (this.config.async) {\n        if (this.config.object.modelPath?.includes('nanodet')) objectRes = this.config.object.enabled ? nanodet.predict(img.tensor, this.config) : [];\n        else if (this.config.object.modelPath?.includes('centernet')) objectRes = this.config.object.enabled ? centernet.predict(img.tensor, this.config) : [];\n        if (this.performance.object) delete this.performance.object;\n      } else {\n        timeStamp = now();\n        if (this.config.object.modelPath?.includes('nanodet')) objectRes = this.config.object.enabled ? await nanodet.predict(img.tensor, this.config) : [];\n        else if (this.config.object.modelPath?.includes('centernet')) objectRes = this.config.object.enabled ? await centernet.predict(img.tensor, this.config) : [];\n        this.performance.object = this.env.perfadd ? (this.performance.object || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n      this.analyze('End Object:');\n\n      // if async wait for results\n      this.state = 'detect:await';\n      if (this.config.async) [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n\n      // run gesture analysis last\n      this.state = 'detect:gesture';\n      let gestureRes: GestureResult[] = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        gestureRes = [...gesture.face(faceRes as FaceResult[]), ...gesture.body(bodyRes as BodyResult[]), ...gesture.hand(handRes as HandResult[]), ...gesture.iris(faceRes as FaceResult[])];\n        if (!this.config.async) this.performance.gesture = this.env.perfadd ? (this.performance.gesture || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n        else if (this.performance.gesture) delete this.performance.gesture;\n      }\n\n      this.performance.total = this.env.perfadd ? (this.performance.total || 0) + Math.trunc(now() - timeStart) : Math.trunc(now() - timeStart);\n      const shape = this.process?.tensor?.shape || [];\n      this.result = {\n        face: faceRes as FaceResult[],\n        body: bodyRes as BodyResult[],\n        hand: handRes as HandResult[],\n        gesture: gestureRes,\n        object: objectRes as ObjectResult[],\n        performance: this.performance,\n        canvas: this.process.canvas,\n        timestamp: Date.now(),\n        error: null,\n        get persons() { return persons.join(faceRes as FaceResult[], bodyRes as BodyResult[], handRes as HandResult[], gestureRes, shape); },\n      };\n\n      // finally dispose input tensor\n      tf.dispose(img.tensor);\n\n      // log('Result:', result);\n      this.emit('detect');\n      this.state = 'idle';\n      resolve(this.result);\n    });\n  }\n}\n\n/** Class Human as default export */\n/* eslint no-restricted-exports: [\"off\", { \"restrictedNamedExports\": [\"default\"] }] */\nexport { Human as default, match, draw, models };\n"],
-  "mappings": ";;;;;;m5BAOO,SAASA,KAAOC,EAAW,CAChC,IAAMC,EAAK,IAAI,KACTC,EAAK,GAAGD,EAAG,SAAS,EAAE,SAAS,EAAE,SAAS,EAAG,GAAG,KAAKA,EAAG,WAAW,EAAE,SAAS,EAAE,SAAS,EAAG,GAAG,KAAKA,EAAG,WAAW,EAAE,SAAS,EAAE,SAAS,EAAG,GAAG,KAAKA,EAAG,gBAAgB,EAAE,SAAS,EAAE,SAAS,EAAG,GAAG,IAEpMD,GAAK,QAAQ,IAAIE,EAAI,SAAU,GAAGF,CAAG,CAC3C,CAGO,SAASG,GAAKC,EAAgBC,EAAsB,CACzD,IAAMC,EAAYF,EAAO,SAAS,GAAG,EAAI,GAAK,IAExCG,EADWF,EAAK,WAAW,GAAG,GAAKA,EAAK,WAAW,GAAG,GAAKA,EAAK,WAAW,OAAO,GAAKA,EAAK,WAAW,QAAQ,GAAKA,EAAK,WAAW,OAAO,EACzH,GAAGA,IAAS,GAAGD,IAASE,IAAYD,IAC5D,GAAI,CAACE,EAAK,kBAAkB,EAAE,SAAS,OAAO,EAAG,MAAM,IAAI,MAAM,yCAAyCA,GAAM,EAChH,OAAOA,CACT,CAGO,IAAMC,EAAM,IACb,OAAO,aAAgB,YAAoB,YAAY,IAAI,EACxD,UAAU,OAAO,QAAQ,OAAO,OAAO,CAAC,EAAI,IAAO,KAAM,SAAS,CAAC,EAIrE,SAASC,GAASC,EAA2BC,EAAyBC,EAAS,SAAUC,EAAoE,CAAC,EAAG,CACtK,QAAWC,KAAO,OAAO,KAAKH,CAAM,EAClC,GAAI,OAAOA,EAAOG,IAAS,SACzBL,GAASC,EAASI,GAAMH,EAAOG,GAAMA,EAAKD,CAAI,MACzC,CACL,IAAME,EAAUL,GAAa,OAAOA,EAASI,IAAS,YACjDC,GAASF,EAAK,KAAK,CAAE,OAAQ,mBAAoB,MAAO,GAAGD,KAAUE,OAASH,EAAOG,IAAO,CAAC,EAClG,IAAME,EAAON,GAAY,OAAOA,EAASI,IAAS,OAAOH,EAAOG,GAC5DC,GAAW,CAACC,GAAMH,EAAK,KAAK,CAAE,OAAQ,yBAA0B,MAAO,GAAGD,KAAUE,OAASH,EAAOG,KAAQ,SAAU,OAAOJ,EAASI,EAAK,CAAC,CAClJ,CAGF,OAAIH,EAAO,OAASC,IAAW,UAAYC,EAAK,OAAS,GAAGd,EAAI,wBAAyBc,CAAI,EACtFA,CACT,CAGO,SAASI,KAAaC,EAAS,CACpC,IAAMC,EAAYC,GAAQA,GAAO,OAAOA,GAAQ,SAChD,OAAOF,EAAQ,OAAO,CAACG,EAAMD,KAC3B,OAAO,KAAKA,GAAO,CAAC,CAAC,EAAE,QAASN,GAAQ,CACtC,IAAMQ,EAAOD,EAAKP,GACZS,EAAOH,EAAIN,GACb,MAAM,QAAQQ,CAAI,GAAK,MAAM,QAAQC,CAAI,EAAGF,EAAKP,GAAOQ,EAAK,OAAO,GAAGC,CAAI,EACtEJ,EAASG,CAAI,GAAKH,EAASI,CAAI,EAAGF,EAAKP,GAAOG,EAAUK,EAAMC,CAAI,EACtEF,EAAKP,GAAOS,CACnB,CAAC,EACMF,GACN,CAAC,CAAC,CACP,CC6PA,IAAMG,GAAiB,CACrB,QAAS,GACT,cAAe,GACf,YAAa,GACb,SAAU,GACV,kBAAmB,GACnB,MAAO,GACP,MAAO,GACP,OAAQ,OACR,iBAAkB,GAClB,YAAa,GACb,WAAY,GACZ,OAAQ,CACN,QAAS,GACT,aAAc,GACd,MAAO,EACP,OAAQ,EACR,KAAM,GACN,OAAQ,GACR,WAAY,EACZ,SAAU,EACV,UAAW,EACX,KAAM,EACN,WAAY,EACZ,IAAK,EACL,SAAU,GACV,MAAO,GACP,QAAS,GACT,WAAY,GACZ,YAAa,GACb,SAAU,GACV,SAAU,CACZ,EACA,QAAS,CACP,QAAS,EACX,EACA,KAAM,CACJ,QAAS,GACT,SAAU,CACR,UAAW,iBACX,SAAU,GACV,YAAa,EACb,WAAY,GACZ,SAAU,KACV,cAAe,GACf,aAAc,GACd,KAAM,GACN,OAAQ,EACV,EACA,KAAM,CACJ,QAAS,GACT,UAAW,gBACX,YAAa,EACf,EACA,UAAW,CACT,QAAS,GACT,UAAW,yBACb,EACA,KAAM,CACJ,QAAS,GACT,UAAW,WACb,EACA,QAAS,CACP,QAAS,GACT,cAAe,GACf,WAAY,GACZ,SAAU,KACV,UAAW,cACb,EACA,YAAa,CACX,QAAS,GACT,UAAW,eACX,WAAY,GACZ,SAAU,IACV,cAAe,EACjB,EACA,UAAW,CACT,QAAS,GACT,WAAY,GACZ,SAAU,IACV,UAAW,gBACb,EACA,SAAU,CACR,QAAS,GACT,WAAY,GACZ,SAAU,IACV,UAAW,eACb,CACF,EACA,KAAM,CACJ,QAAS,GACT,UAAW,yBACX,YAAa,GACb,cAAe,GACf,WAAY,EACZ,SAAU,GACZ,EACA,KAAM,CACJ,QAAS,GACT,SAAU,GACV,WAAY,GACZ,SAAU,IACV,cAAe,GACf,aAAc,GACd,YAAa,GACb,UAAW,GACX,SAAU,CACR,UAAW,gBACb,EACA,SAAU,CACR,UAAW,wBACb,CACF,EACA,OAAQ,CACN,QAAS,GACT,UAAW,qBACX,cAAe,GACf,aAAc,GACd,YAAa,GACb,WAAY,GACZ,SAAU,GACZ,EACA,aAAc,CACZ,QAAS,GACT,UAAW,cACX,KAAM,CACR,CACF,ECvbA,IAAAC,EAAA,GAAAC,GAAAD,EAAA,gBAAAE,GAAA,WAAAC,GAAA,YAAAC,KAMAC,EAAAL,EAAAM,IAA4CD,EAAAL,EAAAM,IAA5C,UAAAA,OAAW,iCAAiC,UAAAA,OAAW,+CAAuP,OAAO,UAAUH,OAAM,iCAAiC,OAAO,cAAcD,OAAM,wCAA3R,IAAIK,GAAE,SAASC,GAAE,SAASC,GAAE,SAASC,GAAE,SAASC,GAAE,SAASC,GAAE,SAASC,GAAE,SAAST,GAAE,CAAC,KAAKG,GAAE,YAAYC,GAAE,YAAYC,GAAE,cAAcC,GAAE,iBAAiBC,GAAE,qBAAqBC,GAAE,oBAAoBC,EAAC,ECNrS,IAAMC,GAAiB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;EAqBvB,IAAMC,GAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAcvBC,GAA0B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAc1BC,GAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAeXC,GAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAyBPC,GAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;EChF3B,IAAMC,GAAU,CAACC,EAAQC,EAAQC,IAAe,CAC9C,IAAMC,EAAI,IAAI,OAAO,MAAQF,EAAS,eAAgB,IAAI,EAC1DD,EAAO,QAAQG,EAAG,CAACC,EAAOC,KACxBH,EAAWG,GAAQ,EACZD,EACR,CACH,EAEME,GAAN,KAAgB,CAMd,YAAYC,EAAIC,EAAcC,EAAgB,CAL9CC,EAAA,eAAU,CAAC,GACXA,EAAA,iBAAY,CAAC,GACbA,EAAA,WACAA,EAAA,WA2BAA,EAAA,eAAU,CAACV,EAAQW,IAA6B,CAC9C,IAAMC,EAAS,KAAK,GAAG,aAAaD,CAAI,EACxC,OAAKC,GAIL,KAAK,GAAG,aAAaA,EAAQZ,CAAM,EACnC,KAAK,GAAG,cAAcY,CAAM,EACvB,KAAK,GAAG,mBAAmBA,EAAQ,KAAK,GAAG,cAAc,EAIvDA,GAHLC,EAAI,8BAA8B,KAAK,GAAG,iBAAiBD,CAAM,GAAG,EAC7D,QAPPC,EAAI,iCAAiC,EAC9B,KASX,GArCE,KAAK,GAAKN,EACV,IAAMO,EAAe,KAAK,QAAQN,EAAc,KAAK,GAAG,aAAa,EAC/DO,EAAiB,KAAK,QAAQN,EAAgB,KAAK,GAAG,eAAe,EAE3E,GADA,KAAK,GAAK,KAAK,GAAG,cAAc,EAC5B,GAACK,GAAgB,CAACC,GACtB,IAAI,CAAC,KAAK,GAAI,CACZF,EAAI,wCAAwC,EAC5C,MACF,CAIA,GAHA,KAAK,GAAG,aAAa,KAAK,GAAIC,CAAY,EAC1C,KAAK,GAAG,aAAa,KAAK,GAAIC,CAAc,EAC5C,KAAK,GAAG,YAAY,KAAK,EAAE,EACvB,CAAC,KAAK,GAAG,oBAAoB,KAAK,GAAI,KAAK,GAAG,WAAW,EAAG,CAC9DF,EAAI,2BAA2B,KAAK,GAAG,kBAAkB,KAAK,EAAE,GAAG,EACnE,MACF,CACA,KAAK,GAAG,WAAW,KAAK,EAAE,EAC1Bd,GAAQS,EAAc,YAAa,KAAK,SAAS,EACjD,QAAW,KAAK,KAAK,UAAW,KAAK,UAAU,GAAK,KAAK,GAAG,kBAAkB,KAAK,GAAI,CAAC,EACxFT,GAAQS,EAAc,UAAW,KAAK,OAAO,EAC7CT,GAAQU,EAAgB,UAAW,KAAK,OAAO,EAC/C,QAAWO,KAAK,KAAK,QAAS,KAAK,QAAQA,GAAK,KAAK,GAAG,mBAAmB,KAAK,GAAIA,CAAC,EACvF,CAgBF,EAWO,SAASC,IAAgB,CAC9B,IAAIC,EAAY,EACZC,EAAqC,KACrCC,EAAc,GACdC,EAA0B,GAC1BC,EAAoG,CAAC,KAAM,IAAI,EAC/GC,EAAyC,CAAC,EAC1CC,EAAmC,KACnCC,EAAmC,KACjCC,EAAWC,GAAO,IAAK,GAAG,EAC1BC,EAAqB,CAAE,EACvBC,EAAO,CAAE,aAAc,CAAE,EACzBtB,EAAKmB,EAAS,WAAW,OAAO,EACtC,GAAI,CAACnB,EAAI,CACPM,EAAI,kCAAkC,EACtC,MACF,CAEA,KAAK,GAAKN,EAEV,SAASuB,EAAOC,EAAOC,EAAQ,CAC7B,GAAI,EAAAD,IAAUL,EAAS,OAASM,IAAWN,EAAS,QAGpD,IAFAA,EAAS,MAAQK,EACjBL,EAAS,OAASM,EACd,CAACR,EAAc,CACjB,IAAMS,EAAW,IAAI,aAAa,CAAC,GAAI,GAAI,EAAG,EAAG,EAAG,GAAI,EAAG,EAAG,GAAI,EAAG,EAAG,EAAG,GAAI,EAAG,EAAG,EAAG,EAAG,GAAI,EAAG,EAAG,EAAG,EAAG,EAAG,CAAC,CAAC,EAChHT,EAAejB,EAAG,aAAa,EAC/BA,EAAG,WAAWA,EAAG,aAAciB,CAAY,EAC3CjB,EAAG,WAAWA,EAAG,aAAc0B,EAAU1B,EAAG,WAAW,EACvDA,EAAG,YAAYA,EAAG,+BAAgC,EAAI,CACxD,CACAA,EAAG,SAAS,EAAG,EAAGmB,EAAS,MAAOA,EAAS,MAAM,EACjDJ,EAAmB,CAAC,KAAM,IAAI,EAChC,CAEA,SAASY,EAAyBH,EAAOC,EAAQ,CAC/C,IAAMG,EAAM5B,EAAG,kBAAkB,EACjCA,EAAG,gBAAgBA,EAAG,YAAa4B,CAAG,EACtC,IAAMC,EAAe7B,EAAG,mBAAmB,EAC3CA,EAAG,iBAAiBA,EAAG,aAAc6B,CAAY,EACjD,IAAMC,EAAU9B,EAAG,cAAc,EACjC,OAAAA,EAAG,YAAYA,EAAG,WAAY8B,CAAO,EACrC9B,EAAG,WAAWA,EAAG,WAAY,EAAGA,EAAG,KAAMwB,EAAOC,EAAQ,EAAGzB,EAAG,KAAMA,EAAG,cAAe,IAAI,EAC1FA,EAAG,cAAcA,EAAG,WAAYA,EAAG,mBAAoBA,EAAG,MAAM,EAChEA,EAAG,cAAcA,EAAG,WAAYA,EAAG,mBAAoBA,EAAG,MAAM,EAChEA,EAAG,cAAcA,EAAG,WAAYA,EAAG,eAAgBA,EAAG,aAAa,EACnEA,EAAG,cAAcA,EAAG,WAAYA,EAAG,eAAgBA,EAAG,aAAa,EACnEA,EAAG,qBAAqBA,EAAG,YAAaA,EAAG,kBAAmBA,EAAG,WAAY8B,EAAS,CAAC,EACvF9B,EAAG,YAAYA,EAAG,WAAY,IAAI,EAClCA,EAAG,gBAAgBA,EAAG,YAAa,IAAI,EAChC,CAAE,IAAA4B,EAAK,QAAAE,CAAQ,CACxB,CAEA,SAASC,EAAmBC,EAAuE,CACjG,OAAAjB,EAAiBiB,GAASjB,EAAiBiB,IAAUL,EAAyBR,EAAS,MAAOA,EAAS,MAAM,EACtGJ,EAAiBiB,EAC1B,CAEA,SAASC,EAAKC,EAAQ,EAAG,CACvB,GAAI,CAAChB,EAAgB,OACrB,IAAIzB,EAA8B,KAC9B0C,EAAkC,KAClCC,EAAQ,GACRzB,IAAc,EAAGlB,EAASmB,EACzBnB,EAASsC,EAAmBjB,CAAuB,EAAE,SAAW,KACrEH,IACIE,GAAe,EAAEqB,EAAQZ,EAAK,eAChCa,EAAS,KACTC,EAAQzB,EAAY,IAAM,IAE1BG,GAA2BA,EAA0B,GAAK,EAC1DqB,EAASJ,EAAmBjB,CAAuB,EAAE,KAAO,MAE9Dd,EAAG,YAAYA,EAAG,WAAYP,CAAM,EACpCO,EAAG,gBAAgBA,EAAG,YAAamC,CAAM,EACzCnC,EAAG,UAAUkB,EAAe,QAAQ,MAAWkB,EAAQ,GAAK,CAAE,EAC9DpC,EAAG,WAAWA,EAAG,UAAW,EAAG,CAAC,CAClC,CAEA,SAASqC,EAAcnC,EAAkC,CACvD,GAAImB,EAAmBnB,GACrB,OAAAgB,EAAiBG,EAAmBnB,GACpCF,EAAG,YAAYkB,EAAiBA,EAAe,GAAK,OAAS,IAAI,EAC1DA,EAGT,GADAA,EAAiB,IAAInB,GAAUC,EAAYsC,GAAgBpC,CAAc,EACrE,CAACgB,EACH,OAAAZ,EAAI,qCAAqC,EAClC,KAET,IAAMiC,EAAY,aAAa,kBACzBC,EAAW,EAAID,EACrB,OAAAvC,EAAG,wBAAwBkB,EAAe,UAAU,GAAM,EAC1DlB,EAAG,oBAAoBkB,EAAe,UAAU,IAAQ,EAAGlB,EAAG,MAAO,GAAOwC,EAAU,EAAID,CAAS,EACnGvC,EAAG,wBAAwBkB,EAAe,UAAU,EAAK,EACzDlB,EAAG,oBAAoBkB,EAAe,UAAU,GAAO,EAAGlB,EAAG,MAAO,GAAOwC,EAAU,EAAID,CAAS,EAClGlB,EAAmBnB,GAAkBgB,EAC9BA,CACT,CAEA,IAAMuB,EAAS,CACb,YAAcC,GAAW,CACvB,IAAMC,EAAI,IAAI,aAAaD,CAAM,EACjCC,EAAE,IAAM,IACRA,EAAE,IAAM,IACRA,EAAE,KAAO,IACTA,EAAE,KAAO,IACT,IAAMtC,EAAUsC,EAAE,MAAQ,GAAKA,EAAE,KAAO,GAAKA,EAAE,KAAO,GAAKA,EAAE,MAAQ,GAAKA,EAAE,MAAQ,GAAKA,EAAE,MAAQ,GAAKA,EAAE,MAAQ,GAAKA,EAAE,MAAQ,EACrHC,GACAC,GACNC,EAAUT,EAAchC,CAAM,EAChC,CAACyC,IACL9C,EAAG,WAAW8C,EAAQ,QAAQ,EAAMH,CAAC,EACrCV,EAAK,EACP,EAEA,WAAac,GAAe,CAC1B,IAAMC,GAAKD,GAAc,GAAK,EAC9BN,EAAO,YAAY,CACjBO,EAAG,EAAG,EAAG,EAAG,EACZ,EAAGA,EAAG,EAAG,EAAG,EACZ,EAAG,EAAGA,EAAG,EAAG,EACZ,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,WAAaC,GAAW,CACtB,IAAMC,GAAKD,GAAU,GAAK,EAAI,EAAI,EAC5BE,GAAMD,EAAI,GAAK,IACrBT,EAAO,YAAY,CACjBS,EAAGC,EAAGA,EAAG,EAAG,EACZA,EAAGD,EAAGC,EAAG,EAAG,EACZA,EAAGA,EAAGD,EAAG,EAAG,EACZ,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,WAAY,IAAM,CAChBT,EAAO,WAAW,EAAE,CACtB,EAEA,SAAWQ,GAAW,CACpB,IAAMG,GAAKH,GAAU,GAAK,EACpBI,EAAI,MAAQD,EAAI,GACtBX,EAAO,YAAY,CACjBW,EAAG,EAAG,EAAG,EAAGC,EACZ,EAAGD,EAAG,EAAG,EAAGC,EACZ,EAAG,EAAGD,EAAG,EAAGC,EACZ,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,SAAU,IAAM,CACdZ,EAAO,SAAS,EAAE,CACpB,EAEA,IAAMa,GAAa,CACjBA,GAAYA,GAAY,GAAK,IAAM,KAAK,GACxC,IAAMC,EAAM,KAAK,IAAID,CAAQ,EACvBE,EAAM,KAAK,IAAIF,CAAQ,EACvBG,EAAO,KACPC,EAAO,KACPC,EAAO,KACblB,EAAO,YAAY,CACjBgB,EAAOF,GAAO,EAAIE,GAAQD,EAAO,CAACC,EAAOC,EAAOH,EAAO,CAACG,EAAQF,EAAO,CAACE,EAAOC,EAAOJ,EAAO,CAACI,EAAQH,GAAO,EAAIG,GAAO,EAAG,EAC3HF,EAAOF,EAAO,CAACE,EAAQD,EAAO,KAAQE,EAAOH,GAAO,EAAIG,GAAQF,EAAO,IAAQG,EAAOJ,EAAO,CAACI,EAAQH,EAAO,MAAS,EAAG,EACzHC,EAAOF,EAAO,CAACE,EAAQD,EAAO,EAAE,EAAIC,GAAQC,EAAOH,EAAO,CAACG,EAAQF,EAAOE,EAAOC,EAAOJ,GAAO,EAAII,GAAQH,EAAOG,EAAO,EAAG,EAC5H,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,oBAAqB,IAAM,CACzBlB,EAAO,YAAY,CACjB,SAAW,QAAW,SAAW,EAAG,MACpC,SAAW,QAAW,SAAW,EAAG,MACpC,SAAW,QAAW,SAAW,EAAG,MACpC,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,MAAO,IAAM,CACXA,EAAO,YAAY,CACjB,KAAO,SAAW,UAAY,EAAG,EACjC,KAAO,SAAW,UAAY,EAAG,EACjC,KAAO,SAAW,UAAY,EAAG,EACjC,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,QAAS,IAAM,CACbA,EAAO,YAAY,CACjB,kBAAoB,mBAAqB,mBAAqB,EAAG,kBACjE,qBAAuB,kBAAoB,mBAAqB,EAAG,mBACnE,mBAAqB,oBAAsB,mBAAqB,EAAG,mBACnE,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,eAAgB,IAAM,CACpBA,EAAO,YAAY,CACjB,kBAAoB,kBAAoB,oBAAsB,EAAG,kBACjE,mBAAqB,kBAAoB,mBAAqB,EAAG,kBACjE,kBAAoB,mBAAqB,kBAAoB,EAAG,kBAChE,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,WAAY,IAAM,CAChBA,EAAO,YAAY,CACjB,mBAAoB,mBAAqB,oBAAsB,EAAG,kBAClE,oBAAsB,mBAAoB,oBAAsB,EAAG,mBACnE,oBAAsB,mBAAqB,mBAAoB,EAAG,kBAClE,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,YAAa,IAAM,CACjBA,EAAO,YAAY,CACjB,mBAAoB,mBAAqB,oBAAsB,EAAG,mBAClE,mBAAqB,mBAAoB,oBAAsB,EAAG,mBAClE,kBAAoB,mBAAqB,kBAAmB,EAAG,mBAC/D,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,SAAU,IAAM,CACdA,EAAO,YAAY,CACjB,MAAO,MAAQ,MAAQ,EAAG,EAC1B,MAAQ,MAAO,MAAQ,EAAG,EAC1B,MAAQ,MAAQ,MAAO,EAAG,EAC1B,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,WAAY,IAAM,CAChBA,EAAO,YAAY,CACjB,EAAG,EAAG,EAAG,EAAG,EACZ,EAAG,EAAG,EAAG,EAAG,EACZ,EAAG,EAAG,EAAG,EAAG,EACZ,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,YAAcC,GAAW,CACvB,IAAMC,EAAI,IAAI,aAAaD,CAAM,EAC3BkB,EAAa,EAAIzC,EAAS,MAC1B0C,EAAa,EAAI1C,EAAS,OAC1B2B,EAAUT,EAAsByB,EAAW,EAC7C,CAAChB,IACL9C,EAAG,WAAW8C,EAAQ,QAAQ,EAAMH,CAAC,EACrC3C,EAAG,UAAU8C,EAAQ,QAAQ,GAAOc,EAAYC,CAAU,EAC1D5B,EAAK,EACP,EAEA,YAAa,IAAM,CAEjBQ,EAAO,YAAY,KAAK,KAAM,CAC5B,EAAG,EAAG,EACN,EAAG,GAAI,EACP,EAAG,EAAG,CACR,CAAC,CACH,EAEA,OAAQ,IAAM,CAEZA,EAAO,YAAY,KAAK,KAAM,CAC5B,GAAI,EAAG,EACP,GAAI,EAAG,EACP,GAAI,EAAG,CACT,CAAC,CACH,EAEA,OAAQ,IAAM,CAEZA,EAAO,YAAY,KAAK,KAAM,CAC5B,GAAI,GAAI,GACR,EAAG,EAAG,EACN,EAAG,EAAG,CACR,CAAC,CACH,EAEA,QAAUQ,GAAW,CACnB,IAAMc,EAAId,GAAU,EAEpBR,EAAO,YAAY,KAAK,KAAM,CAC5B,EAAG,GAAKsB,EAAG,EACX,GAAKA,EAAG,EAAI,EAAIA,EAAG,GAAKA,EACxB,EAAG,GAAKA,EAAG,CACb,CAAC,CACH,EAEA,OAASC,GAAS,CAChB,IAAMC,EAAID,GAAQ,EAElBvB,EAAO,YAAY,KAAK,KAAM,CAC5B,GAAKwB,EAAG,GAAKA,EAAG,EAChB,GAAKA,EAAG,EAAG,EAAIA,EACf,EAAG,EAAIA,EAAG,EAAIA,CAChB,CAAC,CACH,EAEA,KAAOD,GAAS,CACd,IAAME,EAAaF,EAAO,EAAK7C,EAAS,MAClCgD,EAAaH,EAAO,EAAK7C,EAAS,OAClC2B,EAAUT,EAAsB+B,EAAI,EACtC,CAACtB,IAEL9C,EAAG,UAAU8C,EAAQ,QAAQ,GAAO,EAAGqB,CAAS,EAChDlC,EAAKX,EAAK,YAAY,EAEtBtB,EAAG,UAAU8C,EAAQ,QAAQ,GAAOoB,EAAW,CAAC,EAChDjC,EAAK,EACP,EAEA,SAAW+B,GAAS,CAClB,IAAME,EAAaF,EAAQ7C,EAAS,MAC9BgD,EAAaH,EAAQ7C,EAAS,OAC9B2B,EAAUT,EAAsBgC,EAAQ,EAC1C,CAACvB,IACL9C,EAAG,UAAU8C,EAAQ,QAAQ,KAASoB,EAAWC,CAAS,EAC1DlC,EAAK,EACP,CACF,EAGA,KAAK,IAAM,SAAUnC,EAAM,CAEzB,IAAMwE,EAAO,MAAM,UAAU,MAAM,KAAK,UAAW,CAAC,EAC9CC,EAAO9B,EAAO3C,GACpBkB,EAAY,KAAK,CAAE,KAAAuD,EAAM,KAAAD,CAAK,CAAC,CACjC,EAGA,KAAK,MAAQ,UAAY,CACvBtD,EAAc,CAAC,CACjB,EAGA,KAAK,IAAM,UAAY,CACrB,OAAOA,CACT,EAGA,KAAK,MAAQ,SAAUwD,EAAO,CAC5BjD,EAAOiD,EAAM,MAAOA,EAAM,MAAM,EAChC7D,EAAY,EACPC,IAAeA,EAAgBZ,EAAG,cAAc,GACrDA,EAAG,YAAYA,EAAG,WAAYY,CAAa,EAC3CZ,EAAG,cAAcA,EAAG,WAAYA,EAAG,eAAgBA,EAAG,aAAa,EACnEA,EAAG,cAAcA,EAAG,WAAYA,EAAG,eAAgBA,EAAG,aAAa,EACnEA,EAAG,cAAcA,EAAG,WAAYA,EAAG,mBAAoBA,EAAG,OAAO,EACjEA,EAAG,cAAcA,EAAG,WAAYA,EAAG,mBAAoBA,EAAG,OAAO,EACjEA,EAAG,WAAWA,EAAG,WAAY,EAAGA,EAAG,KAAMA,EAAG,KAAMA,EAAG,cAAewE,CAAK,EACzE,QAASC,EAAI,EAAGA,EAAIzD,EAAY,OAAQyD,IAAK,CAC3C5D,EAAe4D,IAAMzD,EAAY,OAAS,EAC1C,IAAM0D,EAAI1D,EAAYyD,GAEtBC,EAAE,KAAK,MAAM,KAAMA,EAAE,MAAQ,CAAC,CAAC,CACjC,CACA,OAAOvD,CACT,EAGA,KAAK,KAAO,SAAUqD,EAAO,CAC3B,YAAK,IAAI,aAAc,CAAC,EACjB,KAAK,MAAMA,CAAK,CACzB,CACF,CCjbA,eAAsBG,GAAsBC,EAAqC,CAE/E,IAAMC,EAAUD,EAAW,MAAM,SAAW,EAAO,UAAQA,CAAU,EAAIA,EACnEE,EAAc,QAAMD,EAAS,EAAG,CAAC,EACjCE,EAAgB,CAAI,MAAID,EAAS,EAAE,EAAM,MAAIA,EAAS,EAAE,EAAM,MAAIA,EAAS,EAAE,CAAC,EAC9EE,EAAgB,CAAI,MAAIF,EAAS,EAAE,EAAM,MAAIA,EAAS,EAAE,EAAM,MAAIA,EAAS,EAAE,CAAC,EAC9EG,EAAS,MAAM,QAAQ,IAAID,EAAI,IAAKE,GAAYA,EAAQ,KAAK,CAAC,CAAC,EAC/DC,EAAW,IAAO,KAAK,IAAIF,EAAO,GAAG,GAAIA,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,EACnEG,EAAM,CAAI,MAAIN,EAAS,GAAIC,EAAI,EAAE,EAAM,MAAID,EAAS,GAAIC,EAAI,EAAE,EAAM,MAAID,EAAS,GAAIC,EAAI,EAAE,CAAC,EAC5FM,EAAQ,CAAI,MAAIL,EAAI,GAAID,EAAI,EAAE,EAAM,MAAIC,EAAI,GAAID,EAAI,EAAE,EAAM,MAAIC,EAAI,GAAID,EAAI,EAAE,CAAC,EAC/EO,EAAO,CAAI,MAAIH,EAAUE,EAAM,EAAE,EAAM,MAAIF,EAAUE,EAAM,EAAE,EAAM,MAAIF,EAAUE,EAAM,EAAE,CAAC,EAC1FE,EAAM,CAAI,MAAIH,EAAI,GAAIE,EAAK,EAAE,EAAM,MAAIF,EAAI,GAAIE,EAAK,EAAE,EAAM,MAAIF,EAAI,GAAIE,EAAK,EAAE,CAAC,EAChFE,EAAS,QAAM,CAACD,EAAI,GAAIA,EAAI,GAAIA,EAAI,EAAE,EAAG,CAAC,EAC1CE,EAAa,UAAQD,EAAK,CAAC,EAAGX,EAAQ,MAAM,GAAIA,EAAQ,MAAM,GAAI,CAAC,CAAC,EAC1E,OAAG,UAAQ,CAAC,GAAGC,EAAU,GAAGC,EAAK,GAAGC,EAAK,GAAGI,EAAK,GAAGC,EAAO,GAAGC,EAAM,GAAGC,EAAKC,EAAKX,CAAO,CAAC,EAClFY,CACT,CCZA,IAAMC,GAAU,KAEZC,EAA6B,KAC7BC,EAA8B,KAC9BC,GAA8B,KAE9BC,EAEEC,GAAoG,CACxG,SAAU,EACV,UAAW,EACX,UAAW,EACX,YAAa,MACf,EAEO,SAASC,GAAOC,EAAeC,EAA2B,CAC/D,IAAIC,EACJ,GAAIC,EAAI,QACN,GAAIA,EAAI,OAAQ,CACd,GAAI,OAAO,iBAAoB,YAAa,MAAM,IAAI,MAAM,mFAAmF,EAC/ID,EAAI,IAAI,gBAAgBF,EAAOC,CAAM,CACvC,KAAO,CACL,GAAI,OAAO,UAAa,YAAa,MAAM,IAAI,MAAM,kEAAkE,EACvHC,EAAI,SAAS,cAAc,QAAQ,EACnCA,EAAE,MAAQF,EACVE,EAAE,OAASD,CACb,MAGI,OAAOE,EAAI,QAAW,YAAaD,EAAI,IAAIC,EAAI,OAAOH,EAAOC,CAAM,EAC9D,OAAO,WAAW,QAAW,cAAaC,EAAI,IAAI,WAAW,OAAOF,EAAOC,CAAM,GAG5F,OAAOC,CACT,CAGO,SAASE,GAAKC,EAAkBC,EAAoB,CACzD,IAAMC,EAAeD,GAAUP,GAAOM,EAAM,MAAOA,EAAM,MAAM,EAE/D,OADYE,EAAa,WAAW,IAAI,EACpC,UAAUF,EAAO,EAAG,CAAC,EAClBE,CACT,CAKA,eAAsBC,GAAQH,EAAcI,EAAgBC,EAAqB,GAAoE,CACnJ,GAAI,CAACL,EAEH,OAAII,EAAO,OAAOE,EAAI,+BAA+B,EAC9C,CAAE,OAAQ,KAAM,OAAQ,IAAK,EAGtC,GACE,EAAEN,aAAoBO,KACnB,EAAE,OAAO,OAAU,aAAeP,aAAiB,QACnD,EAAE,OAAOF,EAAI,QAAW,aAAeE,aAAiBF,EAAI,SAC5D,EAAE,OAAO,WAAW,QAAW,aAAeE,aAAiB,WAAW,SAC1E,EAAE,OAAO,WAAc,aAAeA,aAAiB,YACvD,EAAE,OAAO,aAAgB,aAAeA,aAAiB,cACzD,EAAE,OAAO,kBAAqB,aAAeA,aAAiB,mBAC9D,EAAE,OAAO,kBAAqB,aAAeA,aAAiB,mBAC9D,EAAE,OAAO,kBAAqB,aAAeA,aAAiB,mBAC9D,EAAE,OAAO,mBAAsB,aAAeA,aAAiB,oBAC/D,EAAE,OAAO,iBAAoB,aAAeA,aAAiB,iBAEhE,MAAM,IAAI,MAAM,qCAAqC,EAEvD,GAAIA,aAAoBO,GAAQ,CAC9B,IAAIC,EAAwB,KAC5B,GAAKR,EAAiB,mBAAuB,MAAM,IAAI,MAAM,yDAAyD,EACtH,GAAI,CAAEA,EAAiB,MAAU,MAAM,IAAI,MAAM,sDAAsD,EACvG,GAAKA,EAAiB,MAAM,SAAW,GACrC,GAAKA,EAAiB,MAAM,KAAO,EACjCQ,EAAY,aAAWR,EAAO,CAAC,UACrBA,EAAiB,MAAM,KAAO,EAAG,CAC3C,IAAMS,EAAS,UAAQT,EAAO,CAAC,EAAG,EAAG,CAAC,EAAG,CAAC,GAAI,GAAI,CAAC,CAAC,EACpDQ,EAAY,aAAWC,EAAK,CAAC,EAC1B,UAAQA,CAAG,CAChB,OACUT,EAAiB,MAAM,SAAW,IACvCA,EAAiB,MAAM,KAAO,EACjCQ,EAAY,QAAMR,CAAK,EACbA,EAAiB,MAAM,KAAO,IACxCQ,EAAY,UAAQR,EAAO,CAAC,EAAG,EAAG,EAAG,CAAC,EAAG,CAAC,GAAI,GAAI,GAAI,CAAC,CAAC,IAI5D,GAAIQ,GAAU,MAAQA,EAAO,MAAM,SAAW,GAAKA,EAAO,MAAM,KAAO,GAAKA,EAAO,MAAM,KAAO,EAAG,MAAM,IAAI,MAAM,iEAAiER,EAAM,OAAU,EACpM,GAAKQ,EAAkB,QAAU,QAAS,CACxC,IAAME,EAAU,OAAKF,EAAQ,SAAS,EACnC,UAAQA,CAAM,EACjBA,EAASE,CACX,CACA,MAAO,CAAE,OAAAF,EAAQ,OAASJ,EAAO,OAAO,OAASd,EAAY,IAAM,CACrE,KAAO,CAEL,GAAI,OAAOU,EAAM,YAAkB,aAAeA,EAAM,YAAiB,EACvE,OAAII,EAAO,OAAOE,EAAI,2BAA2B,EAC1C,CAAE,OAAQ,KAAM,OAAQjB,CAAS,EAE1C,IAAMsB,EAAgBX,EAAM,cAAmBA,EAAM,YAAiBA,EAAM,OAAaA,EAAM,OAAaA,EAAM,MAAS,GAAK,EAC1HY,EAAiBZ,EAAM,eAAoBA,EAAM,aAAkBA,EAAM,QAAcA,EAAM,OAAaA,EAAM,MAAS,GAAK,EACpI,GAAI,CAACW,GAAiB,CAACC,EACrB,OAAIR,EAAO,OAAOE,EAAI,mCAAmC,EAClD,CAAE,OAAQ,KAAM,OAAQjB,CAAS,EAE1C,IAAIwB,EAAcF,EACdG,EAAeF,EAenB,GAdIC,EAAczB,KAChByB,EAAczB,GACd0B,EAAe,KAAK,MAAMD,EAAcD,EAAiBD,CAAa,GAEpEG,EAAe1B,KACjB0B,EAAe1B,GACfyB,EAAc,KAAK,MAAMC,EAAeH,EAAgBC,CAAc,IAInER,EAAO,OAAO,OAAS,GAAK,EAAGS,EAAcT,EAAO,OAAO,OACtDA,EAAO,OAAO,QAAU,GAAK,IAAGS,EAAcF,IAAkBP,EAAO,OAAO,QAAU,GAAKQ,KAClGR,EAAO,OAAO,QAAU,GAAK,EAAGU,EAAeV,EAAO,OAAO,QACxDA,EAAO,OAAO,OAAS,GAAK,IAAGU,EAAeF,IAAmBR,EAAO,OAAO,OAAS,GAAKO,IACnG,CAACE,GAAe,CAACC,EAAc,MAAM,IAAI,MAAM,yCAAyC,GACxF,CAACzB,IAAaA,GAAA,YAAAA,EAAU,SAAUwB,IAAiBxB,GAAA,YAAAA,EAAU,UAAWyB,KAAezB,EAAWK,GAAOmB,EAAaC,CAAY,GAGtI,IAAMC,EAAQ1B,EAAS,WAAW,IAAI,EAmDtC,GAlDK,OAAO,WAAc,aAAiBW,aAAiB,UAC1De,EAAM,aAAaf,EAAO,EAAG,CAAC,EAE1BI,EAAO,OAAO,MAAQ,OAAOW,EAAM,WAAc,aACnDA,EAAM,UAAUJ,EAAe,CAAC,EAChCI,EAAM,MAAM,GAAI,CAAC,EACjBA,EAAM,UAAUf,EAAoB,EAAG,EAAGW,EAAeC,EAAgB,EAAG,EAAGvB,GAAA,YAAAA,EAAU,MAAOA,GAAA,YAAAA,EAAU,MAAM,EAChH0B,EAAM,aAAa,EAAG,EAAG,EAAG,EAAG,EAAG,CAAC,GAEnCA,EAAM,UAAUf,EAAoB,EAAG,EAAGW,EAAeC,EAAgB,EAAG,EAAGvB,GAAA,YAAAA,EAAU,MAAOA,GAAA,YAAAA,EAAU,MAAM,GAIhH,CAACC,GAAcD,EAAS,QAAUC,EAAU,QAAWD,GAAA,YAAAA,EAAU,WAAWC,GAAA,YAAAA,EAAW,WAASA,EAAYI,GAAOL,EAAS,MAAOA,EAAS,MAAM,GAGlJe,EAAO,OAAO,SAAWN,EAAI,MAAM,WAChCN,IAAIA,EAAKM,EAAI,QAAU,IAAYkB,GAAkB,MAC1DlB,EAAI,OAAS,CAAC,CAACN,EACX,CAACA,GAAM,CAACA,EAAG,KACTY,EAAO,OAAOE,EAAI,gDAAgD,EACtER,EAAI,MAAM,UAAY,GACtBM,EAAO,OAAO,QAAU,GACxBL,GAAKV,EAAUC,CAAS,IAGxBE,EAAG,MAAM,EACLY,EAAO,OAAO,aAAe,GAAGZ,EAAG,IAAI,aAAcY,EAAO,OAAO,UAAU,EAC7EA,EAAO,OAAO,WAAa,GAAGZ,EAAG,IAAI,WAAYY,EAAO,OAAO,QAAQ,EACvEA,EAAO,OAAO,YAAc,GAAGZ,EAAG,IAAI,UAAWY,EAAO,OAAO,SAAS,EACxEA,EAAO,OAAO,OAAS,GAAGZ,EAAG,IAAI,OAAQY,EAAO,OAAO,IAAI,EAC3DA,EAAO,OAAO,aAAe,GAAGZ,EAAG,IAAI,aAAcY,EAAO,OAAO,UAAU,EAC7EA,EAAO,OAAO,MAAQ,GAAGZ,EAAG,IAAI,MAAOY,EAAO,OAAO,GAAG,EACxDA,EAAO,OAAO,UAAUZ,EAAG,IAAI,UAAU,EACzCY,EAAO,OAAO,OAAOZ,EAAG,IAAI,OAAO,EACnCY,EAAO,OAAO,SAASZ,EAAG,IAAI,SAAS,EACvCY,EAAO,OAAO,OAAOZ,EAAG,IAAI,OAAO,EACnCY,EAAO,OAAO,YAAYZ,EAAG,IAAI,YAAY,EAC7CY,EAAO,OAAO,aAAaZ,EAAG,IAAI,aAAa,EAC/CY,EAAO,OAAO,UAAUZ,EAAG,IAAI,UAAU,EACzCY,EAAO,OAAO,WAAa,GAAGZ,EAAG,IAAI,WAAYY,EAAO,OAAO,QAAQ,EACvEZ,EAAG,IAAI,EAAI,EAAGF,EAAYE,EAAG,MAAMH,CAAQ,EAC1CC,EAAYE,EAAG,KAAKH,CAAQ,KAGnCU,GAAKV,EAAUC,CAAS,EACpBE,IAAIA,EAAK,MACbM,EAAI,OAAS,CAAC,CAACN,GAGb,CAACa,EAAW,MAAO,CAAE,OAAQ,KAAM,OAAQf,CAAU,EACzD,GAAI,CAACA,EAAW,MAAM,IAAI,MAAM,oCAAoC,EAGpE,IAAI2B,EACAC,EAAQ,EACZ,GAAK,OAAO,WAAc,aAAelB,aAAiB,WAAeA,EAAM,MAAWA,EAAM,OAAYA,EAAM,OAChH,GAAIF,EAAI,SAAc,UACpBmB,EAAY,UAAa,UAAQ,WAAWjB,CAAK,EAAI,SAChD,CACLkB,EAAQlB,EAAM,KAAQ,OAASA,EAAM,OAAYA,EAAM,MAEvD,IAAMmB,EAAM,IAAI,WAAWnB,EAAM,KAAQ,MAAS,EAClDiB,EAAY,SAAOE,EAAK,CAACnB,EAAM,OAAWA,EAAM,MAAUkB,CAAK,EAAG,OAAO,CAC3E,UAEI,CAAC3B,IAAcD,EAAU,QAAUC,GAAU,OAAWD,EAAU,SAAWC,GAAU,UAASA,GAAYG,GAAOJ,EAAU,MAAOA,EAAU,MAAM,GACjJ,WAAWQ,EAAI,QAChBM,EAAO,UAAY,SAAWA,EAAO,UAAY,WAAaA,EAAO,UAAY,SACnFa,EAAY,UAAQ,WAAW3B,CAAS,GAExCC,GAAYQ,GAAKT,CAAS,EAC1B2B,EAAY,UAAQ,WAAW1B,EAAS,OAErC,CAGL,IAAM6B,EAFarB,GAAKT,CAAS,EACN,WAAW,IAAI,EACjB,aAAa,EAAG,EAAGuB,EAAaC,CAAY,EACrEI,EAAQE,EAAS,KAAK,OAASP,EAAcC,EAC7C,IAAMK,EAAM,IAAI,WAAWC,EAAS,KAAK,MAAM,EAC/CH,EAAY,SAAOE,EAAK,CAACN,EAAaC,EAAcI,CAAK,CAAC,CAC5D,CAEF,GAAIA,IAAU,EAAG,CACf,IAAMT,EAAS,UAAQQ,EAAQ,CAAC,EAAG,EAAG,CAAC,EAAG,CAAC,GAAI,GAAI,CAAC,CAAC,EAClD,UAAQA,CAAM,EACjBA,EAASR,CACX,CACA,GAAI,CAACQ,EAAQ,MAAM,IAAI,MAAM,mCAAmC,EAChE,IAAMI,EAAY,OAAKJ,EAAQ,SAAS,EAClCT,EAASJ,EAAO,OAAO,aAAe,MAAckB,GAAsBD,CAAM,EAAO,aAAWA,EAAQ,CAAC,EACjH,OAAG,UAAQ,CAACJ,EAAQI,CAAM,CAAC,EACpB,CAAE,OAAAb,EAAQ,OAASJ,EAAO,OAAO,OAASd,EAAY,IAAM,CACrE,CACF,CAgCA,eAAsBiC,GAAKnB,EAAyBJ,EAAe,CACjE,IAAIwB,EAAY,GAChB,GAAIpB,EAAO,mBAAqB,GAAK,CAACJ,EAAM,OAASA,EAAM,MAAM,SAAW,GAAKA,EAAM,MAAM,GAAK,MAAQA,EAAM,MAAM,GAAK,KAAM,OAAOwB,EAcxI,GAAI,CAAC/B,GAAK,YACRA,GAAK,YAAiB,QAAMO,CAAK,UACxBP,GAAK,YAAY,MAAM,KAAOO,EAAM,MAAM,IAAMP,GAAK,YAAY,MAAM,KAAOO,EAAM,MAAM,GAChG,UAAQP,GAAK,WAAW,EAC3BA,GAAK,YAAiB,QAAMO,CAAK,MAC5B,CACL,IAAMyB,EAA4B,CAAC,EACnCA,EAAE,KAAU,MAAIzB,EAAOP,GAAK,WAAW,EACvCgC,EAAE,QAAa,MAAIA,EAAE,KAAMA,EAAE,IAAI,EACjCA,EAAE,IAAS,MAAIA,EAAE,OAAO,EAExB,IAAMC,GADU,MAAMD,EAAE,IAAI,KAAK,GACJ,IAAMzB,EAAM,MAAM,IAAM,IAAMA,EAAM,MAAM,IAAM,GAAK,IAAM,EACrF,UAAQ,CAACP,GAAK,YAAagC,EAAE,KAAMA,EAAE,QAASA,EAAE,GAAG,CAAC,EACvDhC,GAAK,YAAiB,QAAMO,CAAK,EACjCwB,EAAYE,IAAiBtB,EAAO,kBAAoB,EAC1D,CACA,OAAOoB,CACT,CAEA,eAAsBG,GAAQvB,EAAyBwB,EAAgBC,EAAiC,CACtG,IAAMJ,EAA4B,CAAC,EACnC,GAAI,CAACG,GAAU,CAACC,GAAUD,EAAO,MAAM,SAAW,GAAKA,EAAO,MAAM,SAAWC,EAAO,MAAM,OAC1F,OAAKzB,EAAO,OAAOE,EAAI,sDAAuDsB,EAAO,MAAOC,EAAO,KAAK,EACjG,EAET,GAAID,EAAO,MAAM,KAAO,GAAKC,EAAO,MAAM,KAAO,GAAKD,EAAO,MAAM,KAAO,GAAKC,EAAO,MAAM,KAAO,EACjG,OAAKzB,EAAO,OAAOE,EAAI,wDAAyDsB,EAAO,MAAOC,EAAO,KAAK,EACnG,EAETJ,EAAE,OAAY,QAAMG,CAAM,EAC1BH,EAAE,OAAUG,EAAO,MAAM,KAAOC,EAAO,MAAM,IAAMD,EAAO,MAAM,KAAOC,EAAO,MAAM,GAAS,QAAM,eAAeA,EAAQ,CAACD,EAAO,MAAM,GAAIA,EAAO,MAAM,EAAE,CAAC,EAAO,QAAMC,CAAM,EAC/KJ,EAAE,KAAU,MAAIA,EAAE,OAAQA,EAAE,MAAM,EAClCA,EAAE,QAAa,MAAIA,EAAE,KAAMA,EAAE,IAAI,EACjCA,EAAE,IAAS,MAAIA,EAAE,OAAO,EAExB,IAAMC,GADU,MAAMD,EAAE,IAAI,KAAK,GACJ,IAAMG,EAAO,MAAM,IAAM,IAAMA,EAAO,MAAM,IAAM,GAAK,IAAM,EAC1F,OAAG,UAAQ,CAACH,EAAE,OAAQA,EAAE,OAAQA,EAAE,KAAMA,EAAE,QAASA,EAAE,GAAG,CAAC,EAClDC,CACT,CC5TO,IAAMI,GAAN,KAAU,CA4Ef,aAAc,CA1EdC,EAAA,gBAEAA,EAAA,aAEAA,EAAA,eAEAA,EAAA,gBAAmB,IAEnBA,EAAA,aAAgB,IAEhBA,EAAA,gBAAqB,CAAC,GAEtBA,EAAA,gBAEAA,EAAA,eAEAA,EAAA,aAIAA,EAAA,kBAEAA,EAAA,eAAmB,IAEnBA,EAAA,YAKI,CACA,UAAW,OACX,QAAS,OACT,KAAM,OACN,YAAa,MACf,GAEFA,EAAA,aAKI,CACA,UAAW,OACX,QAAS,OACT,QAAS,OACT,SAAU,MACZ,GAEFA,EAAA,cAII,CACA,UAAW,OACX,QAAS,OACT,QAAS,MACX,GAEFA,EAAA,WAGI,CACA,MAAO,OACP,MAAO,CAAC,CACV,GAEFA,EAAA,eAAoB,CAAC,GAErBA,EAAA,eAEAA,EAAA,cAEAA,EAAA,kBAUE,GAPA,KAAK,QAAU,OAAO,WAAc,YACpC,KAAK,KAAQ,OAAO,SAAY,aAAiB,OAAO,QAAQ,UAAa,aAAiB,OAAO,QAAQ,SAAS,MAAS,YAC/H,KAAK,KAAO,CAAE,QAAYC,GAAQ,YAAa,EAC/C,KAAK,UAAY,OAAO,iBAAoB,YAC5C,KAAK,QAAU,GAEf,KAAK,OAAS,KAAK,SAAW,KAAK,UAAa,OAAO,mBAAsB,YAAe,OACxF,OAAO,WAAc,YAAa,CACpC,IAAMC,EAAM,UAAU,UAAU,MAAM,eAAe,EACrD,GAAIA,GAAOA,EAAI,GAAI,CACjB,IAAMC,EAAgBD,EAAI,GAAG,MAAM,eAAe,EAClD,KAAK,SAAYC,GAAiBA,EAAc,GAAMA,EAAc,GAAG,QAAQ,SAAU,EAAE,EAAI,GAC/F,KAAK,MAAQ,UAAU,UAAU,QAAQD,EAAI,GAAI,EAAE,EAC/C,KAAK,SAAS,KAAI,KAAK,MAAQ,KAAK,MAAM,QAAQA,EAAI,GAAI,EAAE,GAChE,KAAK,MAAQ,KAAK,MAAM,QAAQ,MAAO,GAAG,CAU5C,CACF,MAAW,OAAO,SAAY,cAC5B,KAAK,SAAW,GAAG,QAAQ,YAAY,QAAQ,OAC/C,KAAK,MAAQ,UAAU,QAAQ,UAEnC,CAGA,MAAM,eAAgB,CAEpB,KAAK,SAAW,OAAO,KAAQ,SAAO,EAAE,eAAe,EACvD,KAAK,KAAK,UAAY,OAAO,aAAgB,YAC7C,KAAK,KAAK,QAAU,KAAK,SAAS,SAAS,MAAM,EAC7C,KAAK,KAAK,WAAa,KAAK,KAAK,SAAc,aAAW,IAAM,SAClE,KAAK,KAAK,KAAO,MAAS,MAAI,EAAE,SAAS,uBAAuB,EAChE,KAAK,KAAK,YAAc,MAAS,MAAI,EAAE,SAAS,8BAA8B,GAEhF,IAAME,EAAUC,GAAO,IAAK,GAAG,EACzBC,EAAMF,EAAIA,EAAE,WAAW,QAAQ,EAAI,OAIzC,GAFA,KAAK,MAAM,UAAY,OAAOE,GAAQ,YACtC,KAAK,MAAM,QAAU,KAAK,SAAS,SAAS,OAAO,EAC/C,KAAK,MAAM,WAAa,KAAK,MAAM,UAAe,aAAW,IAAM,SAAc,aAAW,IAAM,WAAY,CAEhH,IAAMC,EAAQ,UAAQ,EAAE,QAAU,YAAc,MAAS,UAAQ,EAAE,gBAAgB,EAAE,GAAK,KACtFA,IACF,KAAK,MAAM,QAAUA,EAAG,aAAaA,EAAG,OAAO,EAC/C,KAAK,MAAM,SAAWA,EAAG,aAAaA,EAAG,QAAQ,EAErD,CAEA,KAAK,OAAO,UAAY,KAAK,SAAW,OAAO,UAAU,KAAW,YACpE,KAAK,OAAO,QAAU,KAAK,SAAS,SAAS,QAAQ,EACrD,GAAI,CAEE,KAAK,OAAO,YAAW,KAAK,OAAO,SAAW,MAAM,UAAU,IAAO,eAAe,GAAG,KAC7F,OAAQC,EAAN,CACA,KAAK,OAAO,UAAY,EAC1B,CACA,GAAI,CACF,KAAK,QAAa,uBAAwB,aAAW,CAAC,EAAE,IAAKC,GAAWA,EAAO,WAAW,YAAY,CAAC,CACzG,OAAQD,EAAN,CAAa,CACjB,CAGA,MAAM,WAAY,CAChB,IAAME,EAAM,CAAE,MAAO,GAAI,MAAO,CAAC,CAAE,EAC/B,KAAK,MAAQ,KAAK,SAAS,WAAW,OAAO,EAY5C,KAAK,IACL,KAAK,IAASA,EADD,OAAO,eAAe,KAAM,MAAO,CAAE,MAAOA,CAAI,CAAC,CAErE,CACF,EAEaC,EAAM,IAAIZ,mlECnKvB,IAAMa,GAAU,CACd,YAAa,GACb,eAAgB,GAChB,QAAS,GACT,MAAO,GACP,cAAe,EACjB,EAUaC,GAAwC,CAAC,EAEtD,eAAeC,GAAYC,EAAKC,EAAiC,CAC/D,OAAIJ,GAAQ,OAAOK,EAAI,oBAAqBF,EAAKC,CAAI,EAC9C,MAAMD,EAAKC,CAAI,CACxB,CAEO,SAASE,GAAoBC,EAAgB,CAClDP,GAAQ,YAAcO,EAAO,YAC7BP,GAAQ,QAAUO,EAAO,MACzBP,GAAQ,cAAgBO,EAAO,aACjC,CAEA,eAAsBC,EAAUC,EAAoD,CAnCpF,IAAAC,EAAAC,EAAAC,EAoCE,IAAIC,EAAWC,GAAKd,GAAQ,cAAeS,GAAa,EAAE,EACrDI,EAAS,YAAY,EAAE,SAAS,OAAO,IAAGA,GAAY,SAC3D,IAAME,EAAoBF,EAAS,SAAS,GAAG,EAAIA,EAAS,MAAM,GAAG,EAAIA,EAAS,MAAM,IAAI,EACtFG,EAAiBD,EAAkBA,EAAkB,OAAS,GAAG,QAAQ,QAAS,EAAE,EACpFE,EAAkB,eAAiBD,EACzCf,GAAWe,GAAkB,CAC3B,KAAMA,EACN,iBAAkB,EAClB,kBAAmB,EACnB,YAAaE,GAAWF,GACxB,QAAS,EACX,EACAhB,GAAQ,eAAkB,OAAO,QAAW,aAAiB,OAAO,OAAO,cAAiB,aAAiB,OAAO,OAAO,WAAc,YACzI,IAAImB,EAAe,CAAC,EACpB,GAAI,CACFA,EAAgBnB,GAAQ,gBAAkBA,GAAQ,YAAe,MAAS,KAAG,WAAW,EAAI,CAAC,CAC/F,OAAQoB,EAAN,CACApB,GAAQ,eAAiB,EAC3B,CACAC,GAAWe,GAAgB,QAAWhB,GAAQ,gBAAkBA,GAAQ,aAAgB,OAAO,KAAKmB,CAAY,EAAE,SAASF,CAAe,EAC1I,IAAMI,EAAgB,OAAO,OAAU,YAAc,CAAC,EAAI,CAAE,UAAW,CAAClB,EAAKC,IAAUF,GAAYC,EAAKC,CAAI,CAAE,EACxGkB,EAAoB,IAAOC,GAAWtB,GAAWe,GAAgB,QAAUC,EAAkBJ,EAAUQ,CAAa,EACtHG,EAAS,GACb,GAAI,CAEFF,EAAM,cAAc,EAChBtB,GAAQ,OAAOK,EAAI,sBAAuBiB,EAAM,OAAU,EAE9D,IAAMG,EAAY,MAAMH,EAAM,QAAQ,KAAK,EAC3CrB,GAAWe,GAAgB,mBAAmBN,EAAAe,GAAA,YAAAA,EAAW,aAAX,YAAAf,EAAuB,aAAc,EACnFY,EAAM,SAASG,CAAS,EAExBxB,GAAWe,GAAgB,oBAAoBJ,GAAAD,EAAAW,GAAA,YAAAA,EAAO,YAAP,YAAAX,EAAkB,aAAlB,YAAAC,EAA8B,aAAc,EACvFZ,GAAQ,SAASK,EAAI,cAAeiB,EAAM,SAAa,CAAE,MAAOrB,GAAWe,GAAgB,iBAAkB,EAAGhB,EAAO,EAC3HwB,EAAS,EACX,OAASE,EAAP,CACArB,EAAI,uBAAwBQ,EAAUa,CAAG,CAC3C,CACA,GAAIF,GAAUxB,GAAQ,aAAeA,GAAQ,gBAAkB,CAACC,GAAWe,GAAgB,QACzF,GAAI,CACF,IAAMW,EAAa,MAAML,EAAM,KAAKL,CAAe,EACnDZ,EAAI,eAAgBY,EAAiBU,CAAU,CACjD,OAASD,EAAP,CACArB,EAAI,sBAAuBQ,EAAUa,CAAG,CAC1C,CAEF,OAAOJ,CACT,gBCnFA,IAAAM,GAAA,GAAAC,GAAAD,GAAA,YAAAE,GAAA,kBAAAC,GAAA,SAAAC,GAAA,UAAAC,GAAA,aAAAC,KCeA,IAAIC,GACEC,GAAwB,CAAC,EACzBC,GAAY,CAAC,QAAS,QAAS,QAAS,SAAU,OAAO,EACzDC,GAAa,CAAC,GAAI,GAAI,GAAI,KAAM,KAAM,KAAM,EAAE,EAChDC,GAAY,EACZC,GAAW,EACXC,GAAU,OAAO,iBAGrB,eAAsBC,GAAKC,EAAgB,CAxB3C,IAAAC,EAyBE,OAAIC,EAAI,UAASV,GAAQ,MACpBA,GACIQ,EAAO,OAAOG,EAAI,gBAAiBX,GAAM,QAAW,EADjDA,GAAQ,MAAMY,GAAUH,EAAAD,EAAO,KAAK,OAAZ,YAAAC,EAAqB,SAAS,EAE3DT,EACT,CAGA,eAAsBa,GAAQC,EAAeN,EAAgBO,EAAaC,EAAkC,CAhC5G,IAAAP,EAAAQ,EAiCE,GAAI,CAACjB,GAAO,MAAO,CAAE,IAAK,EAAG,OAAQ,UAAW,YAAa,EAAG,KAAM,CAAC,CAAE,EACzE,IAAMkB,EAAYZ,MAAWG,EAAAD,EAAO,KAAK,OAAZ,YAAAC,EAAqB,aAAc,GAC1DU,KAAYF,EAAAT,EAAO,KAAK,OAAZ,YAAAS,EAAqB,WAAY,GAAMG,EAAI,EAAIf,GACjE,OAAIG,EAAO,aAAeW,GAAYD,GAAcd,KAAcY,GAAUf,GAAKc,IAC/ET,KACOL,GAAKc,KAEdT,GAAU,EACH,IAAI,QAAQ,MAAOe,GAAY,CAzCxC,IAAAZ,EAAAQ,EA0CI,GAAI,EAACjB,IAAA,MAAAA,GAAO,OAAO,GAAG,OAAO,OAC7B,IAAMsB,EAA4B,CAAC,EAE7BC,EAAM,CAAC,CAAC,EAAK,GAAM,GAAM,EAAI,CAAC,EACpCD,EAAE,OAAY,QAAM,cAAcR,EAAOS,EAAK,CAAC,CAAC,EAAG,CAACvB,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,CAAC,EACvG,IAAMwB,EAAgB,CAAE,IAAK,EAAG,OAAQ,UAAW,YAAa,EAAG,KAAM,CAAC,CAAE,GACxEf,EAAAD,EAAO,KAAK,OAAZ,MAAAC,EAAqB,UAAS,CAACa,EAAE,IAAKA,EAAE,OAAQA,EAAE,IAAI,EAAItB,GAAM,QAAQsB,EAAE,OAAQ,CAAC,aAAc,gBAAiB,aAAa,CAAC,GACpI,IAAMG,EAAS,MAAMH,EAAE,OAAO,KAAK,EACnCE,EAAI,OAASC,EAAO,GAAKA,EAAO,GAAK,OAAS,SAC9CD,EAAI,YAAc,KAAK,MAAM,KAAOC,EAAO,GAAKA,EAAO,GAAKA,EAAO,GAAKA,EAAO,GAAG,EAAI,IACtF,IAAMC,EAAO,MAAMJ,EAAE,KAAK,KAAK,EAC/B,QAASK,EAAI,EAAGA,EAAID,EAAK,OAAQC,IAC3BD,EAAKC,MAAMV,EAAAT,EAAO,KAAK,OAAZ,YAAAS,EAAqB,gBAAiB,KAAMO,EAAI,KAAK,KAAK,CAAE,MAAO,KAAK,MAAM,IAAME,EAAKC,EAAE,EAAI,IAAK,KAAMzB,GAAUyB,EAAW,CAAC,EAEjJH,EAAI,KAAK,KAAK,CAACI,EAAGC,IAAMA,EAAE,MAAQD,EAAE,KAAK,EAGzC,IAAME,EADkB,MAAM,KAAK,MAAMR,EAAE,IAAI,KAAK,CAAC,EACnB,IAAI,CAACM,EAAGD,IAAM,CAACxB,GAAWwB,GAAIC,CAAC,CAAC,EAAE,KAAK,CAACA,EAAGC,IAAMA,EAAE,GAAKD,EAAE,EAAE,EAC1FG,EAAMD,EAAU,GAAG,GACvB,QAASH,EAAI,EAAGA,EAAIG,EAAU,OAAQH,IAAKI,GAAOD,EAAUH,GAAG,IAAMG,EAAUH,GAAG,GAAKI,GACvFP,EAAI,IAAM,KAAK,MAAM,GAAKO,CAAG,EAAI,GACjC,OAAO,KAAKT,CAAC,EAAE,QAASU,GAAc,UAAQV,EAAEU,EAAO,CAAC,EACxD/B,GAAKc,GAAOS,EACZpB,GAAYY,EACZX,GAAWe,EAAI,EACfC,EAAQG,CAAG,CACb,CAAC,EACH,CClEO,IAAMS,EAAwD,CACnE,MAAO,IACP,IAAK,EACL,IAAK,EACL,KAAM,GACN,MAAO,MACP,IAAK,CAAC,MAAQ,KAAQ,IAAM,CAC9B,EAEO,SAASC,IAAO,CACrBD,EAAU,MAAW,SAAO,IAAK,SAAS,EAC1CA,EAAU,IAAS,SAAO,EAAG,SAAS,EACtCA,EAAU,IAAS,SAAO,EAAG,SAAS,EACtCA,EAAU,KAAU,SAAO,GAAK,SAAS,EACzCA,EAAU,MAAW,SAAO,MAAO,SAAS,EAC5CA,EAAU,IAAS,WAAS,CAAC,MAAQ,KAAQ,IAAM,EAAG,SAAS,CACjE,CCLA,IAAIE,GACEC,GAA+B,CAAC,EAClCC,GAAY,EACZC,GAAW,EACXC,GAAU,OAAO,iBAGrB,eAAsBC,GAAKC,EAAgB,CACzC,OAAIC,EAAI,UAASP,GAAQ,MACpBA,GACIM,EAAO,OAAOE,EAAI,gBAAiBR,GAAM,QAAW,EADjDA,GAAQ,MAAMS,EAAUH,EAAO,KAAK,OAAU,YAAY,EAE/DN,EACT,CAGA,eAAsBU,GAAQC,EAAeL,EAAgBM,EAAaC,EAAyC,CA7BnH,IAAAC,EAAAC,EAAAC,EAAAC,EA8BE,GAAI,CAACjB,GAAO,MAAO,CAAE,IAAK,CAAE,EAC5B,IAAMkB,EAAYd,MAAWU,EAAAR,EAAO,KAAK,SAAZ,YAAAQ,EAAuB,aAAc,GAC5DK,KAAYJ,EAAAT,EAAO,KAAK,SAAZ,YAAAS,EAAuB,WAAY,GAAMK,EAAI,EAAIjB,GACnE,OAAIG,EAAO,aAAeY,GAAaC,GAAajB,KAAcW,KAAUG,EAAAf,GAAKW,KAAL,YAAAI,EAAW,QAAQC,EAAAhB,GAAKW,KAAL,YAAAK,EAAW,KAAM,GAC9Gb,KACOH,GAAKW,KAEdR,GAAU,EACH,IAAI,QAAQ,MAAOiB,GAAY,CACpC,GAAI,EAACrB,IAAA,MAAAA,GAAO,SAAU,CAACA,GAAM,OAAO,IAAM,CAACA,GAAM,OAAO,GAAG,MAAO,OAClE,IAAMsB,EAA4B,CAAC,EACnCA,EAAE,OAAY,QAAM,eAAeX,EAAO,CAACX,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,EAAG,EAAK,EACrGsB,EAAE,QAAa,MAAIA,EAAE,OAAQC,EAAU,KAAK,EAC5C,IAAMC,EAAM,CAAE,IAAK,CAAE,EAErB,GADIlB,EAAO,KAAK,OAAU,UAASgB,EAAE,IAAMtB,GAAM,QAAQsB,EAAE,OAAO,GAC9DA,EAAE,IAAK,CACT,IAAMG,EAAO,MAAMH,EAAE,IAAI,KAAK,EAC9BE,EAAI,IAAM,KAAK,MAAM,GAAKC,EAAK,EAAE,EAAI,EACvC,CACA,OAAO,KAAKH,CAAC,EAAE,QAASI,GAAc,UAAQJ,EAAEI,EAAO,CAAC,EACxDzB,GAAKW,GAAOY,EACZtB,GAAYW,EACZV,GAAWiB,EAAI,EACfC,EAAQG,CAAG,CACb,CAAC,EACH,CCxCA,IAAIG,GACEC,GAAuD,CAAC,EAC1DC,GAAY,EACZC,GAAW,EACXC,GAAU,OAAO,iBAGfC,GAAM,CAAC,MAAQ,KAAQ,IAAM,EAGnC,eAAsBC,GAAKC,EAAsB,CAC/C,OAAIC,EAAI,UAASR,GAAQ,MACpBA,GACIO,EAAO,OAAOE,EAAI,gBAAiBT,GAAM,QAAW,EADjDA,GAAQ,MAAMU,EAAUH,EAAO,KAAK,OAAU,eAAe,EAElEP,EACT,CAGA,eAAsBW,GAAQC,EAAeL,EAAgBM,EAAKC,EAAyD,CAjC3H,IAAAC,EAAAC,EAAAC,EAAAC,EAkCE,GAAI,CAAClB,GAAO,MAAO,CAAE,OAAQ,UAAW,YAAa,CAAE,EACvD,IAAMmB,EAAYf,MAAWW,EAAAR,EAAO,KAAK,SAAZ,YAAAQ,EAAuB,aAAc,GAC5DK,KAAYJ,EAAAT,EAAO,KAAK,SAAZ,YAAAS,EAAuB,WAAY,GAAMK,EAAI,EAAIlB,GACnE,OAAII,EAAO,aAAeY,GAAaC,GAAalB,KAAcY,KAAUG,EAAAhB,GAAKY,KAAL,YAAAI,EAAW,WAAWC,EAAAjB,GAAKY,KAAL,YAAAK,EAAW,aAAc,GACzHd,KACOH,GAAKY,KAEdT,GAAU,EACH,IAAI,QAAQ,MAAOkB,GAAY,CACpC,GAAI,EAACtB,IAAA,MAAAA,GAAO,OAAO,GAAG,OAAO,OAC7B,IAAMuB,EAA4B,CAAC,EACnCA,EAAE,OAAY,QAAM,eAAeX,EAAO,CAACZ,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,EAAG,EAAK,EACrGuB,EAAE,QAAa,OAAK,IAAM,CACxB,GAAM,CAACC,EAAKC,EAAOC,CAAI,EAAO,QAAMH,EAAE,OAAQ,EAAG,CAAC,EAC5CI,EAAa,MAAIH,EAAKnB,GAAI,EAAE,EAC5BuB,EAAe,MAAIH,EAAOpB,GAAI,EAAE,EAChCwB,EAAc,MAAIH,EAAMrB,GAAI,EAAE,EAC9ByB,EAAe,OAAK,CAACH,EAASC,EAAWC,CAAQ,CAAC,EAExD,OADqB,MAAO,MAAIC,EAAWC,EAAU,IAAI,EAAG,CAAC,CAE/D,CAAC,EACD,IAAMC,EAA+C,CAAE,OAAQ,UAAW,YAAa,CAAE,EACrFzB,EAAO,KAAK,OAAU,UAASgB,EAAE,OAASvB,GAAM,QAAQuB,EAAE,OAAO,GACrE,IAAMU,EAAO,MAAMV,EAAE,OAAO,KAAK,EACjCS,EAAI,OAASC,EAAK,GAAKA,EAAK,GAAK,SAAW,OAC5CD,EAAI,YAAcC,EAAK,GAAKA,EAAK,GAAM,KAAK,MAAM,IAAMA,EAAK,EAAE,EAAI,IAAQ,KAAK,MAAM,IAAMA,EAAK,EAAE,EAAI,IACvG,OAAO,KAAKV,CAAC,EAAE,QAASW,GAAc,UAAQX,EAAEW,EAAO,CAAC,EACxDjC,GAAKY,GAAOmB,EACZ9B,GAAYY,EACZX,GAAWkB,EAAI,EACfC,EAAQU,CAAG,CACb,CAAC,EACH,CCvDA,IAAIG,GACEC,GAAwB,CAAC,EAC3BC,GAAU,OAAO,iBACjBC,GAAY,EACZC,GAAW,EAEf,eAAsBC,GAAKC,EAAqC,CAjBhE,IAAAC,EAkBE,OAAIC,EAAI,UAASR,GAAQ,MACpBA,GACIM,EAAO,OAAOG,EAAI,gBAAiBT,GAAM,QAAW,EADjDA,GAAQ,MAAMU,GAAUH,EAAAD,EAAO,KAAK,YAAZ,YAAAC,EAAuB,SAAS,EAE7DP,EACT,CAEA,eAAsBW,GAAQC,EAAeN,EAAgBO,EAAaC,EAAgC,CAxB1G,IAAAP,EAAAQ,EAyBE,GAAI,CAACf,GAAO,MAAO,GACnB,IAAMgB,KAAYT,EAAAD,EAAO,KAAK,YAAZ,YAAAC,EAAuB,WAAY,GAAMU,EAAI,EAAIb,GAC7Dc,EAAYhB,MAAWa,EAAAT,EAAO,KAAK,YAAZ,YAAAS,EAAuB,aAAc,GAClE,OAAIT,EAAO,aAAeU,GAAYE,GAAcf,KAAcW,GAAUb,GAAOY,IACjFX,KACOD,GAAOY,KAEhBX,GAAU,EACH,IAAI,QAAQ,MAAOiB,GAAY,CACpC,IAAMC,EAAY,QAAM,eAAeR,EAAO,CAACZ,IAAA,MAAAA,GAAO,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EAAGA,IAAA,MAAAA,GAAO,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,CAAC,EAAG,EAAK,EAC7JqB,EAAMrB,IAAA,YAAAA,GAAO,QAAQoB,GACrBE,GAAO,MAAMD,EAAI,KAAK,GAAG,GAC/BpB,GAAOY,GAAO,KAAK,MAAM,IAAMS,CAAG,EAAI,IACtCnB,GAAYW,EACZV,GAAWa,EAAI,EACZ,UAAQ,CAACG,EAAQC,CAAG,CAAC,EACxBF,EAAQlB,GAAOY,EAAI,CACrB,CAAC,EACH,CCtCO,IAAMU,GAA4C,CACvD,WAAY,CACV,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACtD,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACvD,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,GAAI,GACpD,EAKA,eAAgB,CAAC,IAAK,GAAI,GAAI,GAAI,EAAG,IAAK,IAAK,IAAK,GAAG,EACvD,eAAgB,CAAC,GAAI,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAG,EAClE,eAAgB,CAAC,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAG,EACxD,eAAgB,CAAC,GAAI,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAG,EACjE,mBAAoB,CAAC,GAAI,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAG,EACrE,mBAAoB,CAAC,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAG,EAC5D,mBAAoB,CAAC,GAAI,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAG,EACrE,mBAAoB,CAAC,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAG,EAC5D,eAAgB,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAClD,eAAgB,CAAC,GAAI,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EACzD,eAAgB,CAAC,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,GAAG,EAC7C,eAAgB,CAAC,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,GAAG,EACvD,eAAgB,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAClD,eAAgB,CAAC,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAC3D,eAAgB,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAC5D,kBAAmB,CAAC,IAAK,GAAI,GAAI,IAAK,GAAI,IAAK,GAAI,GAAG,EACtD,kBAAmB,CAAC,GAAI,IAAK,GAAI,GAAI,GAAI,EAAE,EAC3C,aAAc,CAAC,IAAK,IAAK,IAAK,IAAK,GAAG,EACtC,cAAe,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EACjD,cAAe,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAC3D,cAAe,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EACjD,cAAe,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAC3D,cAAe,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EACjD,cAAe,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAC3D,cAAe,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAC3D,iBAAkB,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EACzD,iBAAkB,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAC/C,YAAa,CAAC,IAAK,IAAK,IAAK,IAAK,GAAG,EACrC,kBAAmB,CAAC,GAAG,EACvB,QAAS,CAAC,CAAC,EACX,WAAY,CAAC,CAAC,EACd,gBAAiB,CAAC,EAAE,EACpB,eAAgB,CAAC,GAAG,EACpB,WAAY,CAAC,GAAG,EAChB,UAAW,CAAC,GAAG,CACjB,EAEaC,GAAmD,CAC9D,MAAO,IACP,MAAO,GACP,aAAc,CAAC,GAAID,GAAgB,kBAAqB,EAAE,CAC5D,EAEaE,GAAwD,CACnE,QAAS,EACT,SAAU,EACV,KAAM,EACN,MAAO,EACP,QAAS,EACT,SAAU,EACV,aAAc,CAAC,EAAG,CAAC,CACrB,EAEaC,GAAyD,CACpE,CAAE,IAAK,YAAa,QAAS,CAAC,EAAG,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,EACzD,CAAE,IAAK,YAAa,QAAS,CAAC,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,EAC1D,CAAE,IAAK,YAAa,QAAS,CAAC,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,EAC1D,CAAE,IAAK,YAAa,QAAS,CAAC,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,CAAC,CAAE,EACzD,CAAE,IAAK,YAAa,QAAS,CAAC,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,EAClE,CAAE,IAAK,YAAa,QAAS,CAAC,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,EAClE,CAAE,IAAK,YAAa,QAAS,CAAC,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,EAClE,CAAE,IAAK,eAAgB,QAAS,CAAC,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,EACjE,CAAE,IAAK,eAAgB,QAAS,CAAC,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,CAC3D,EAEaC,GAA4B,CACvC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,eAAgB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,eAAiB,eAAgB,EAClC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,cAAgB,gBAAiB,EAClC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,CACvC,EAEaC,GAAwB,CACnC,IAAK,GAAI,IAAK,GAAI,EAAG,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,EACtJ,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,GAAI,GAClJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,EAAG,IAAK,GAAI,GAAI,GAAI,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,GACrJ,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,EAAG,IAC7I,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAClJ,IAAK,IAAK,GAAI,GAAI,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,IAAK,GAAI,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,GACrJ,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,GACpJ,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,IAAK,GACjJ,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,EAAG,EAAG,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,EAAG,IAC/I,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,IAAK,EAAG,GAAI,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IACnJ,IAAK,GAAI,EAAG,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IACnJ,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,EAAG,IAAK,IAAK,GAAI,EAAG,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAC9I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,EAAG,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GACtJ,GAAI,GAAI,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,GAClJ,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,EAAG,EAAG,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GACnJ,IAAK,IAAK,IAAK,GAAI,GAAI,EAAG,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GACrJ,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IACpJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,EAAG,IAClJ,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,EAAG,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACnJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,GAAI,IAAK,IAAK,IAAK,IACnJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IACnJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAChJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,EAAG,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAChJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAC7I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAClJ,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAC7I,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,EAAG,IAAK,GAAI,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GACnJ,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,EAAG,GAAI,EAAG,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GACpJ,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,GAAI,IAAK,GAAI,IAAK,EAAG,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAClJ,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAClJ,GAAI,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,GAAI,GAAI,EAAG,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAChJ,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IACpJ,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,GACrJ,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,GAAI,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,GACpJ,IAAK,GAAI,IAAK,IAAK,EAAG,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,EAAG,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAC/I,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,EAAG,IAAK,GAAI,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAC9I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GACpJ,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GACrJ,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IACpJ,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,EAAG,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,EACpJ,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAC9I,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,EAAG,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,EAAG,GAAI,IAClJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAC9I,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAChJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAChJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAC9I,IAAK,GAAI,IAAK,EAAG,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAChJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAClJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,EAAG,IAAK,IAAK,IAAK,IAAK,IACpJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAwB1I,IAAMC,GAAuB,CACtB,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/E,GAAI,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAC1C,IAAK,EAAG,IAAK,EAAG,GAAI,GAAI,EAAG,IAAK,IAChC,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACtD,GAAI,GAAI,GAAI,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAChD,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAC7C,EAEaC,GAAuB,CAAC,GAAI,IAAK,IAAK,IAAK,EAAG,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,EAAG,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,GAAG,EAE5KC,GAAsB,CAAC,GAAI,IAAK,IAAK,IAAK,EAAG,GAAI,GAAG,EAEpDC,GAAOH,GAAM,IAAKI,GAAMC,GAAMD,EAAE,EAEhCE,GAAOL,GAAM,IAAKG,GAAMC,GAAMD,EAAE,EAEhCG,GAAML,GAAK,IAAKE,GAAMC,GAAMD,EAAE,EAO3C,SAASI,GAAqBC,EAAwB,CACpD,IAAMC,EAAUD,EAAY,IAAKE,GAAeA,EAAW,EAAE,EAC7D,OAAAD,EAAQ,KAAKD,EAAYA,EAAY,OAAS,GAAG,EAAE,EAC5CC,CACT,CAEO,IAAME,GAAuB,CACl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aC,GAA0B,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAEzNC,GAA8B,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAE7HC,GAA2B,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAE1EC,GAA2B,CAAC,CAAC,GAAI,CAAC,EAAG,CAAC,EAAG,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAEpNC,GAA+B,CAAC,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,CAAC,EAEjHC,GAA4B,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAE3EC,GAA8B,CACzC,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EACpE,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EACrE,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EACrE,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EACrE,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EACjE,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,CAChE,EAEaC,GAAmB,CAC9B,KAAMZ,GAAqBI,EAAS,EACpC,QAASJ,GAAqBK,EAAY,EAC1C,YAAaL,GAAqBM,EAAgB,EAClD,SAAUN,GAAqBO,EAAa,EAC5C,SAAUP,GAAqBQ,EAAa,EAC5C,aAAcR,GAAqBS,EAAiB,EACpD,UAAWT,GAAqBU,EAAc,EAC9C,SAAUV,GAAqBW,EAAgB,CACjD,ECrsBO,IAAME,GAAcC,GAA0B,CAAC,KAAK,IAAIA,EAAI,SAAS,GAAKA,EAAI,WAAW,EAAE,EAAG,KAAK,IAAIA,EAAI,SAAS,GAAKA,EAAI,WAAW,EAAE,CAAC,EAErIC,GAAgBD,GAAkC,CAACA,EAAI,WAAW,IAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAM,EAAGA,EAAI,WAAW,IAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAM,EAAG,CAAC,EAElLE,GAAW,CAACF,EAAKG,IAAgBH,EAAM,CAClD,KAAK,MAAM,KAAK,IAAI,EAAGA,EAAI,WAAW,EAAE,CAAC,EACzC,KAAK,MAAM,KAAK,IAAI,EAAGA,EAAI,WAAW,EAAE,CAAC,EACzC,KAAK,MAAM,KAAK,IAAKG,EAAM,MAAM,IAAM,EAAIH,EAAI,SAAS,EAAE,EAAI,KAAK,IAAI,EAAGA,EAAI,WAAW,EAAE,CAAC,EAC5F,KAAK,MAAM,KAAK,IAAKG,EAAM,MAAM,IAAM,EAAIH,EAAI,SAAS,EAAE,EAAI,KAAK,IAAI,EAAGA,EAAI,WAAW,EAAE,CAAC,CAC9F,EAAI,CAAC,EAAG,EAAG,EAAG,CAAC,EAEFI,GAAY,CAACJ,EAAKG,IAAgBH,EAAM,CACnDA,EAAI,WAAW,IAAMG,EAAM,MAAM,IAAM,GACvCH,EAAI,WAAW,IAAMG,EAAM,MAAM,IAAM,IACtCH,EAAI,SAAS,GAAKA,EAAI,WAAW,KAAOG,EAAM,MAAM,IAAM,IAC1DH,EAAI,SAAS,GAAKA,EAAI,WAAW,KAAOG,EAAM,MAAM,IAAM,EAC7D,EAAI,CAAC,EAAG,EAAG,EAAG,CAAC,EAEFE,GAAsB,CAACL,EAAKM,IAAW,CAClD,IAAMC,EAAoB,CAACP,EAAI,WAAW,GAAKM,EAAO,GAAIN,EAAI,WAAW,GAAKM,EAAO,EAAE,EACjFE,EAAkB,CAACR,EAAI,SAAS,GAAKM,EAAO,GAAIN,EAAI,SAAS,GAAKM,EAAO,EAAE,EACjF,MAAO,CAAE,WAAAC,EAAY,SAAAC,EAAU,UAAWR,EAAI,UAAW,WAAYA,EAAI,UAAW,CACtF,EAEaS,GAAe,CAACT,EAAKU,EAAOC,IAAa,CACpD,IAAMC,EAAIF,EAAM,MAAM,GAChBG,EAAIH,EAAM,MAAM,GAChBI,EAAS,CAACd,EAAI,WAAW,GAAKY,EAAGZ,EAAI,WAAW,GAAKa,EAAGb,EAAI,SAAS,GAAKY,EAAGZ,EAAI,SAAS,GAAKa,CAAC,EAChGE,EAAU,QAAM,cAAcL,EAAO,CAACI,CAAM,EAAG,CAAC,CAAC,EAAGH,CAAQ,EAC5DK,EAAU,MAAID,EAAME,EAAU,KAAK,EACzC,OAAG,UAAQF,CAAI,EACRC,CACT,EAEaE,GAAa,CAAClB,EAAKM,IAAW,CACzC,IAAMa,EAASlB,GAAaD,CAAG,EACzBoB,EAAOrB,GAAWC,CAAG,EACrBqB,EAA6B,CAACf,EAASc,EAAK,GAAK,EAAGd,EAASc,EAAK,GAAK,CAAC,EAC9E,MAAO,CAAE,WAAY,CAACD,EAAO,GAAKE,EAAS,GAAIF,EAAO,GAAKE,EAAS,EAAE,EAAY,SAAU,CAACF,EAAO,GAAKE,EAAS,GAAIF,EAAO,GAAKE,EAAS,EAAE,EAAY,UAAWrB,EAAI,UAAW,WAAYA,EAAI,UAAW,CAChN,EAEasB,GAAetB,GAAQ,CAClC,IAAMuB,EAAUtB,GAAaD,CAAG,EAC1BoB,EAAOrB,GAAWC,CAAG,EACrBqB,EAAW,KAAK,IAAI,GAAGD,CAAI,EAAI,EACrC,MAAO,CAAE,WAAY,CAAC,KAAK,MAAMG,EAAQ,GAAKF,CAAQ,EAAG,KAAK,MAAME,EAAQ,GAAKF,CAAQ,CAAC,EAAY,SAAU,CAAC,KAAK,MAAME,EAAQ,GAAKF,CAAQ,EAAG,KAAK,MAAME,EAAQ,GAAKF,CAAQ,CAAC,EAAY,UAAWrB,EAAI,UAAW,WAAYA,EAAI,UAAW,CACxP,EAEawB,GAAiCC,GAAc,CAC1D,IAAMC,EAAID,EAAU,IAAKE,GAAMA,EAAE,EAAE,EAC7BC,EAAIH,EAAU,IAAKE,GAAMA,EAAE,EAAE,EACnC,MAAO,CAAE,WAAY,CAAC,KAAK,IAAI,GAAGD,CAAC,EAAG,KAAK,IAAI,GAAGE,CAAC,CAAC,EAAY,SAAU,CAAC,KAAK,IAAI,GAAGF,CAAC,EAAG,KAAK,IAAI,GAAGE,CAAC,CAAC,EAAY,UAAAH,CAAU,CACjI,EAEaI,GAAsB,CAAC,CAAC,EAAG,EAAG,CAAC,EAAG,CAAC,EAAG,EAAG,CAAC,EAAG,CAAC,EAAG,EAAG,CAAC,CAAC,EAEtDC,GAAoBC,GAAUA,EAAQ,EAAI,KAAK,GAAK,KAAK,OAAOA,EAAQ,KAAK,KAAO,EAAI,KAAK,GAAG,EAEhGC,GAAkB,CAACC,EAAQC,IAAWJ,GAAiB,KAAK,GAAK,EAAI,KAAK,MAAM,EAAEI,EAAO,GAAKD,EAAO,IAAKC,EAAO,GAAKD,EAAO,EAAE,CAAC,EAItI,IAAME,GAAyB,CAACC,EAAGC,IAAM,CAAC,CAAC,EAAG,EAAGD,CAAC,EAAG,CAAC,EAAG,EAAGC,CAAC,EAAG,CAAC,EAAG,EAAG,CAAC,CAAC,EAEnEC,GAAM,CAACC,EAAcC,IAAiB,CACjD,IAAIC,EAAU,EACd,QAASC,EAAI,EAAGA,EAAIH,EAAG,OAAQG,IAAKD,GAAWF,EAAGG,GAAKF,EAAGE,GAC1D,OAAOD,CACT,EAEaE,GAAqB,CAACC,EAAKC,IAAgB,CACtD,IAAMC,EAAwB,CAAC,EAC/B,QAASJ,EAAI,EAAGA,EAAIE,EAAI,OAAQF,IAAKI,EAAO,KAAKF,EAAIF,GAAGG,EAAY,EACpE,OAAOC,CACT,EAEaC,GAA4B,CAACC,EAAMC,IAAS,CACvD,IAAMR,EAA2B,CAAC,EAC5BS,EAAOF,EAAK,OAClB,QAASG,EAAM,EAAGA,EAAMD,EAAMC,IAAO,CACnCV,EAAQ,KAAK,CAAC,CAAC,EACf,QAASW,EAAM,EAAGA,EAAMF,EAAME,IAAOX,EAAQU,GAAK,KAAKb,GAAIU,EAAKG,GAAMR,GAAmBM,EAAMG,CAAG,CAAC,CAAC,CACtG,CACA,OAAOX,CACT,EAEaY,GAAsB,CAACC,EAAUC,IAAW,CACvD,IAAMC,EAAO,KAAK,IAAIF,CAAQ,EACxBG,EAAO,KAAK,IAAIH,CAAQ,EACxBI,EAAiB,CAAC,CAACF,EAAM,CAACC,EAAM,CAAC,EAAG,CAACA,EAAMD,EAAM,CAAC,EAAG,CAAC,EAAG,EAAG,CAAC,CAAC,EAC9DG,EAAoBxB,GAAuBoB,EAAO,GAAIA,EAAO,EAAE,EAC/DK,EAA2Bb,GAA0BY,EAAmBD,CAAc,EACtFG,EAA4B1B,GAAuB,CAACoB,EAAO,GAAI,CAACA,EAAO,EAAE,EAC/E,OAAOR,GAA0Ba,EAA0BC,CAAyB,CACtF,EAEaC,GAAyBC,GAAW,CAC/C,IAAMC,EAAoB,CAAC,CAACD,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,EAAG,CAACA,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,CAAC,EAC/EE,EAAuB,CAACF,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,EAClDG,EAAsB,CAAC,CAAC5B,GAAI0B,EAAkB,GAAIC,CAAoB,EAAG,CAAC3B,GAAI0B,EAAkB,GAAIC,CAAoB,CAAC,EAC/H,MAAO,CAACD,EAAkB,GAAG,OAAOE,EAAoB,EAAE,EAAGF,EAAkB,GAAG,OAAOE,EAAoB,EAAE,EAAG,CAAC,EAAG,EAAG,CAAC,CAAC,CAC7H,EAEaC,GAAc,CAACC,EAAuBV,IAAmB,CAACpB,GAAI8B,EAAuBV,EAAe,EAAE,EAAGpB,GAAI8B,EAAuBV,EAAe,EAAE,CAAC,EAI5J,SAASW,GAAgBC,EAAW,CACzC,IAAMC,EAAOD,IAAc,IACvB,CAAE,QAAS,CAAC,CAAC,EAAG,QAAS,CAAC,CAAC,CAAE,EAC7B,CAAE,QAAS,CAACA,EAAY,GAAIA,EAAY,CAAC,EAAG,QAAS,CAAC,EAAG,CAAC,CAAE,EAC1DE,EAAmC,CAAC,EAC1C,QAASC,EAAI,EAAGA,EAAIF,EAAK,QAAQ,OAAQE,IAAK,CAC5C,IAAMC,EAASH,EAAK,QAAQE,GACtBE,EAAW,KAAK,OAAOL,EAAYI,EAAS,GAAKA,CAAM,EACvDE,EAAW,KAAK,OAAON,EAAYI,EAAS,GAAKA,CAAM,EACvDG,EAAaN,EAAK,QAAQE,GAChC,QAASK,EAAQ,EAAGA,EAAQH,EAAUG,IAAS,CAC7C,IAAMC,EAAUL,GAAUI,EAAQ,IAClC,QAASE,EAAQ,EAAGA,EAAQJ,EAAUI,IAAS,CAC7C,IAAMC,EAAUP,GAAUM,EAAQ,IAClC,QAASE,EAAI,EAAGA,EAAIL,EAAYK,IAAKV,EAAQ,KAAK,CAACS,EAASF,CAAO,CAAC,CACtE,CACF,CACF,CACA,OAAOP,CACT,CAEO,SAASW,GAAmBC,EAAWC,EAAKC,EAAOC,EAAgBjB,EAAW,CACnF,IAAMkB,EAAUC,GAAWJ,CAAG,EACxBK,EAAeN,EAAU,IAAKO,GAAW,CAC5CH,EAAQ,GAAKlB,GAAcqB,EAAM,GAAMrB,EAAY,GACnDkB,EAAQ,GAAKlB,GAAcqB,EAAM,GAAMrB,EAAY,GACnDqB,EAAM,IAAM,CACf,CAAE,EACIC,EAAaN,GAAUA,IAAU,GAAO,KAAK,IAAIA,CAAK,EAAI,GAC1DO,EAAuBD,EAAaE,GAAoBR,EAAO,CAAC,EAAG,CAAC,CAAC,EAAIS,GACzEC,EAAgBJ,EAAaF,EAAa,IAAKC,GAAW,CAAC,GAAGM,GAAYN,EAAOE,CAAoB,EAAGF,EAAM,EAAE,CAAE,EAAID,EACtHQ,EAAwBN,EAAaO,GAAsBZ,CAAc,EAAIQ,GAC7EK,EAAYC,GAAahB,CAAG,EAC5BiB,EAAU,CAACC,GAAIH,EAAWF,EAAsB,EAAE,EAAGK,GAAIH,EAAWF,EAAsB,EAAE,CAAC,EACnG,OAAOF,EAAc,IAAKL,GAAW,CACnC,KAAK,MAAMA,EAAM,GAAKW,EAAQ,EAAE,EAChC,KAAK,MAAMX,EAAM,GAAKW,EAAQ,EAAE,EAChC,KAAK,MAAMX,EAAM,IAAM,CAAC,CAC1B,CAAE,CACJ,CAEO,SAASa,GAAoBC,EAAQpB,EAAKqB,EAAOpC,EAAW,CACjE,IAAMqC,EAAgBtB,EAAI,UAAU,QAAiBuB,GAAc,MACxDA,GAAc,aACdC,GAAmB,aAC1BvB,EAAQ,EACRC,EAAiBQ,GACjBe,EAEJ,GAAIL,GAAUM,EAAI,QAAQ,SAAS,kBAAkB,EAGnD,GAFAzB,EAAQ0B,GAAgB3B,EAAI,UAAUsB,EAAa,IAAKtB,EAAI,UAAUsB,EAAa,GAAG,EACnErB,GAAUA,IAAU,GAAO,KAAK,IAAIA,CAAK,EAAI,GAChD,CACd,IAAM2B,EAAgBZ,GAAahB,CAAG,EAChC6B,EAAmB,CAACD,EAAO,GAAKP,EAAM,MAAM,GAAIO,EAAO,GAAKP,EAAM,MAAM,EAAE,EAC1ES,EAAa,QAAM,iBAAiBT,EAAOpB,EAAO,EAAG4B,CAAS,EACpE3B,EAAiBO,GAAoB,CAACR,EAAO2B,CAAM,EACnDH,EAAOM,GAAa/B,EAAK8B,EAAS,CAAC7C,EAAWA,CAAS,CAAC,EACrD,UAAQ6C,CAAO,CACpB,MACEL,EAAOM,GAAa/B,EAAKqB,EAAO,CAACpC,EAAWA,CAAS,CAAC,OAGxDwC,EAAOM,GAAa/B,EAAKqB,EAAO,CAACpC,EAAWA,CAAS,CAAC,EAExD,MAAO,CAACgB,EAAOC,EAAgBuB,CAAI,CACrC,CAEO,IAAMO,GAAkBC,GAAS,CACtC,IAAMC,EAAID,EAAK,IAAKE,GAAMA,EAAE,EAAE,EACxBC,EAAIH,EAAK,IAAKE,GAAMA,EAAE,EAAE,EAO9B,MAAO,CAAC,KAAK,IAAI,GAAGD,CAAC,GAAK,KAAK,IAAI,GAAGA,CAAC,EAAI,KAAK,IAAI,GAAGA,CAAC,GAAK,EAAG,KAAK,IAAI,GAAGE,CAAC,GAAK,KAAK,IAAI,GAAGA,CAAC,EAAI,KAAK,IAAI,GAAGA,CAAC,GAAK,CAAC,CACxH,EAEaC,GAAmB,CAACJ,EAAMK,IAAgB,CACrD,IAAMV,EAASI,GAAeC,CAAI,EAC5B9B,EAAUC,GAAWkC,CAAW,EAKtC,MAJsB,CACpB,WAAY,CAACV,EAAO,GAAKzB,EAAQ,GAAK,EAAGyB,EAAO,GAAKzB,EAAQ,GAAK,CAAC,EACnE,SAAU,CAACyB,EAAO,GAAKzB,EAAQ,GAAK,EAAGyB,EAAO,GAAKzB,EAAQ,GAAK,CAAC,CACnE,CAEF,ECnMA,IAAMoC,GAAiB,EACjBC,GAAqB,IACvBC,GACAC,GAAyB,KACzBC,GAAY,EACZC,GAA4B,KAInBC,GAAO,IAAMF,GAE1B,eAAsBG,GAAKC,EAAqC,CA1BhE,IAAAC,EA2BE,OAAIC,EAAI,UAASR,GAAQ,MACpBA,GACIM,EAAO,OAAOG,EAAI,gBAAiBT,GAAM,QAAW,EADjDA,GAAQ,MAAMU,GAAUH,EAAAD,EAAO,KAAK,WAAZ,YAAAC,EAAsB,SAAS,EAEnEL,GAAYF,GAAM,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EAC/DG,GAAgB,SAAOD,GAAW,OAAO,EACzCD,GAAa,WAAcU,GAAgBT,EAAS,CAAC,EAC9CF,EACT,CAEA,SAASY,GAAYC,EAAoB,CACvC,IAAM,EAA4B,CAAC,EACnC,EAAE,UAAe,QAAMA,EAAY,CAAC,EAAG,CAAC,EAAG,CAAC,GAAI,CAAC,CAAC,EAClD,EAAE,QAAa,MAAI,EAAE,UAAWZ,EAAO,EACvC,EAAE,SAAc,QAAMY,EAAY,CAAC,EAAG,CAAC,EAAG,CAAC,GAAI,CAAC,CAAC,EACjD,EAAE,mBAAwB,MAAI,EAAE,SAAUV,EAAU,EACpD,EAAE,kBAAuB,MAAI,EAAE,QAASA,EAAU,EAClD,EAAE,YAAiB,MAAI,EAAE,mBAAoBW,EAAU,GAAG,EAC1D,EAAE,OAAY,MAAI,EAAE,kBAAmB,EAAE,WAAW,EACpD,EAAE,KAAU,MAAI,EAAE,kBAAmB,EAAE,WAAW,EAClD,EAAE,gBAAqB,MAAI,EAAE,OAAQX,EAAU,EAC/C,EAAE,cAAmB,MAAI,EAAE,KAAMA,EAAU,EAC3C,IAAMY,EAAW,WAAS,CAAC,EAAE,gBAAiB,EAAE,aAAa,EAAG,CAAC,EACjE,cAAO,KAAK,CAAC,EAAE,QAASC,GAAc,UAAQ,EAAEA,EAAO,CAAC,EACjDD,CACT,CAEA,eAAsBE,GAASC,EAAoBZ,EAAgB,CArDnE,IAAAC,EAAAY,EAAAC,EAAAC,EAuDE,GAAK,CAACH,GAAgBA,EAAW,oBAA2BA,EAAW,MAAM,SAAW,GAAOA,EAAW,MAAM,GAAK,GAAOA,EAAW,MAAM,GAAK,EAAI,MAAO,CAAC,EAC9J,IAAMI,EAA4B,CAAC,EACnCA,EAAE,QAAa,QAAM,eAAeJ,EAAY,CAAChB,GAAWA,EAAS,CAAC,EACtEoB,EAAE,IAAS,MAAIA,EAAE,QAASR,EAAU,KAAK,EACzCQ,EAAE,WAAgB,MAAIA,EAAE,IAAKR,EAAU,IAAI,EAC3C,IAAMS,EAAMvB,IAAA,YAAAA,GAAO,QAAQsB,EAAE,YAC7B,GAAI,MAAM,QAAQC,CAAG,GAAKA,EAAI,OAAS,EAAG,CACxC,IAAMC,EAASD,EAAI,KAAK,CAACE,EAAGC,IAAMD,EAAE,KAAOC,EAAE,IAAI,EACjDJ,EAAE,UAAe,SAAO,CAACE,EAAO,GAAIA,EAAO,EAAE,EAAG,CAAC,EACjDF,EAAE,UAAe,SAAO,CAACE,EAAO,GAAIA,EAAO,EAAE,EAAG,CAAC,EACjDF,EAAE,OAAY,SAAO,CAACA,EAAE,UAAWA,EAAE,SAAS,EAAG,CAAC,EAClDA,EAAE,MAAW,UAAQA,EAAE,OAAQ,CAAC,CAClC,MAAW,MAAM,QAAQC,CAAG,EAC1BD,EAAE,MAAW,UAAQC,EAAI,EAAE,EAE3BD,EAAE,MAAW,UAAQC,CAAG,EAEvB,UAAQA,CAAG,EACdD,EAAE,MAAQV,GAAYU,EAAE,KAAK,EAC7BA,EAAE,OAAY,QAAMA,EAAE,MAAO,CAAC,EAAG,CAAC,EAAG,CAAC,GAAI,CAAC,CAAC,EAC5CA,EAAE,QAAa,UAAQA,EAAE,MAAM,EAC/BA,EAAE,OAAY,UAAQA,EAAE,OAAO,EAC/BA,EAAE,IAAM,MAAS,QAAM,uBAAuBA,EAAE,MAAOA,EAAE,SAASf,EAAAD,EAAO,KAAK,WAAZ,YAAAC,EAAsB,cAAe,IAAKY,EAAAb,EAAO,KAAK,WAAZ,YAAAa,EAAsB,eAAgB,IAAKC,EAAAd,EAAO,KAAK,WAAZ,YAAAc,EAAsB,gBAAiB,CAAE,EAChM,IAAMO,EAAM,MAAML,EAAE,IAAI,MAAM,EACxBP,EAA0B,CAAC,EAC3Ba,EAAS,MAAMN,EAAE,OAAO,KAAK,EACnC,QAASO,EAAI,EAAGA,EAAIF,EAAI,OAAQE,IAAK,CACnC,IAAMC,EAAaF,EAAOD,EAAIE,IAC9B,GAAIC,KAAcT,EAAAf,EAAO,KAAK,WAAZ,YAAAe,EAAsB,gBAAiB,GAAI,CAC3D,IAAMK,EAA4B,CAAC,EACnCA,EAAE,KAAU,QAAMJ,EAAE,MAAO,CAACK,EAAIE,GAAI,CAAC,EAAG,CAAC,EAAG,EAAE,CAAC,EAC/CH,EAAE,MAAW,QAAMJ,EAAE,MAAO,CAACK,EAAIE,GAAI/B,GAAiB,CAAC,EAAG,CAAC,EAAG,EAAE,CAAC,EACjE4B,EAAE,QAAa,UAAQA,EAAE,KAAK,EAC9BA,EAAE,UAAe,UAAQA,EAAE,QAAS,CAAC5B,GAAgB,EAAE,CAAC,EACxD,IAAMiC,EAAS,MAAML,EAAE,KAAK,KAAK,EAC3BM,EAAS,CACb,WAAY,CAACD,EAAO,GAAIA,EAAO,EAAE,EACjC,SAAU,CAACA,EAAO,GAAIA,EAAO,EAAE,EAC/B,UAAY,MAAML,EAAE,UAAU,MAAM,EACpC,WAAAI,CACF,EACMG,EAAiBC,GAAoBF,EAAQ,EAAEd,EAAW,MAAM,IAAM,GAAKhB,IAAYgB,EAAW,MAAM,IAAM,GAAKhB,EAAS,CAAC,EAC7HiC,EAAmBC,GAAWH,EAAW3B,EAAO,KAAK,OAAYP,EAAkB,EACnFsC,EAAkBC,GAAYH,CAAW,EAC/CpB,EAAM,KAAKsB,CAAU,EACrB,OAAO,KAAKX,CAAC,EAAE,QAASV,GAAc,UAAQU,EAAEV,EAAO,CAAC,CAC1D,CACF,CACA,cAAO,KAAKM,CAAC,EAAE,QAASN,GAAc,UAAQM,EAAEN,EAAO,CAAC,EACjDD,CACT,CCzGA,IAAAwB,GAAA,GAAAC,GAAAD,GAAA,eAAAE,GAAA,QAAAC,KAEO,IAAMA,GAAqB,CAChC,OACA,gBACA,UACA,iBACA,iBACA,WACA,kBACA,UACA,WACA,YACA,aACA,eACA,gBACA,YACA,aACA,YACA,aACA,YACA,aACA,YACA,aACA,YACA,aACA,UACA,WACA,WACA,YACA,YACA,aACA,WACA,YACA,WACA,YACA,aACA,UACA,WACA,WACA,YACA,WACF,EAEaD,GAAsC,CACjD,UAAW,CAAC,eAAgB,eAAe,EAC3C,KAAM,CAAC,WAAY,SAAS,EAC5B,MAAO,CAAC,YAAa,YAAY,EACjC,aAAc,CAAC,UAAW,UAAU,EACpC,aAAc,CAAC,WAAY,WAAW,EACtC,SAAU,CAAC,YAAa,WAAY,UAAU,EAC9C,UAAW,CAAC,eAAgB,SAAS,EACrC,aAAc,CAAC,eAAgB,WAAW,EAC1C,aAAc,CAAC,YAAa,WAAW,EACvC,SAAU,CAAC,YAAa,UAAU,EAClC,cAAe,CAAC,WAAY,WAAW,EACvC,cAAe,CAAC,WAAY,WAAW,EACvC,cAAe,CAAC,WAAY,WAAW,EACvC,eAAgB,CAAC,gBAAiB,gBAAgB,EAClD,cAAe,CAAC,WAAY,WAAW,EACvC,cAAe,CAAC,YAAa,YAAY,EACzC,UAAW,CAAC,aAAc,YAAa,WAAW,EAClD,WAAY,CAAC,gBAAiB,UAAU,EACxC,cAAe,CAAC,gBAAiB,YAAY,EAC7C,cAAe,CAAC,aAAc,YAAY,EAC1C,UAAW,CAAC,aAAc,WAAW,EACrC,eAAgB,CAAC,YAAa,YAAY,EAC1C,eAAgB,CAAC,YAAa,YAAY,EAC1C,eAAgB,CAAC,YAAa,YAAY,EAC1C,gBAAiB,CAAC,iBAAkB,iBAAiB,CACvD,EC/DA,IAAME,GAAY,IACdC,GACEC,GAAY,EACZC,GAAU,CAAC,EAAG,GAAI,GAAI,GAAI,EAAE,EAElC,eAAsBC,IAAgB,CACpC,IAAMC,EAA2C,CAAC,EAC9CC,EAAU,EACd,KAAOA,EAAUJ,IAAW,CAC1B,IAAIK,EAAc,EACdC,EAAsBF,EAC1B,KAAOE,EAAsBL,GAAQ,QAAUA,GAAQK,KAAyBL,GAAQG,IACtFC,GAAe,EACfC,IAEF,IAAMC,EAASN,GAAQG,GACjBI,EAAmB,KAAK,KAAKV,GAAYS,CAAM,EAC/CE,EAAkB,KAAK,KAAKX,GAAYS,CAAM,EACpD,QAASG,EAAI,EAAGA,EAAIF,EAAkB,EAAEE,EACtC,QAASC,EAAI,EAAGA,EAAIF,EAAiB,EAAEE,EACrC,QAASC,EAAW,EAAGA,EAAWP,EAAa,EAAEO,EAC/CT,EAAQ,KAAK,CAAE,GAAIQ,EAAI,IAAOF,EAAiB,GAAIC,EAAI,IAAOF,CAAiB,CAAC,EAItFJ,EAAUE,CACZ,CACAP,GAAe,CAAE,EAAM,WAASI,EAAQ,IAAKU,GAAMA,EAAE,CAAC,CAAC,EAAG,EAAM,WAASV,EAAQ,IAAKU,GAAMA,EAAE,CAAC,CAAC,CAAE,CACpG,CCjCO,SAASC,GAAKC,EAAyBC,EAA+B,CAAC,EAAG,CAAC,EAAG,CACnF,IAAMC,EAAS,CAACF,EAAU,IAAKG,GAAOA,EAAG,EAAE,EAAGH,EAAU,IAAKG,GAAOA,EAAG,EAAE,CAAC,EACpEC,EAAM,CAAC,KAAK,IAAI,GAAGF,EAAO,EAAE,EAAG,KAAK,IAAI,GAAGA,EAAO,EAAE,CAAC,EACrDG,EAAM,CAAC,KAAK,IAAI,GAAGH,EAAO,EAAE,EAAG,KAAK,IAAI,GAAGA,EAAO,EAAE,CAAC,EACrDI,EAAW,CAACF,EAAI,GAAIA,EAAI,GAAIC,EAAI,GAAKD,EAAI,GAAIC,EAAI,GAAKD,EAAI,EAAE,EAC5DG,EAAc,CAACD,EAAI,GAAKL,EAAW,GAAIK,EAAI,GAAKL,EAAW,GAAIK,EAAI,GAAKL,EAAW,GAAIK,EAAI,GAAKL,EAAW,EAAE,EACnH,MAAO,CAAE,IAAAK,EAAK,OAAAC,CAAO,CACvB,CAEO,SAASC,GAAOR,EAAyBC,EAA+B,CAAC,EAAG,CAAC,EAAG,CACrF,IAAMC,EAAS,CAACF,EAAU,IAAKG,GAAOA,EAAG,EAAE,EAAGH,EAAU,IAAKG,GAAOA,EAAG,EAAE,CAAC,EACpEC,EAAM,CAAC,KAAK,IAAI,GAAGF,EAAO,EAAE,EAAG,KAAK,IAAI,GAAGA,EAAO,EAAE,CAAC,EACrDG,EAAM,CAAC,KAAK,IAAI,GAAGH,EAAO,EAAE,EAAG,KAAK,IAAI,GAAGA,EAAO,EAAE,CAAC,EACrDO,EAAS,EAAEL,EAAI,GAAKC,EAAI,IAAM,GAAID,EAAI,GAAKC,EAAI,IAAM,CAAC,EACtDK,EAAO,KAAK,IAAID,EAAO,GAAKL,EAAI,GAAIK,EAAO,GAAKL,EAAI,GAAI,CAACK,EAAO,GAAKJ,EAAI,GAAI,CAACI,EAAO,GAAKJ,EAAI,EAAE,EAChGC,EAAW,CAAC,KAAK,MAAMG,EAAO,GAAKC,CAAI,EAAG,KAAK,MAAMD,EAAO,GAAKC,CAAI,EAAG,KAAK,MAAM,EAAIA,CAAI,EAAG,KAAK,MAAM,EAAIA,CAAI,CAAC,EAClHH,EAAc,CAACD,EAAI,GAAKL,EAAW,GAAIK,EAAI,GAAKL,EAAW,GAAIK,EAAI,GAAKL,EAAW,GAAIK,EAAI,GAAKL,EAAW,EAAE,EACnH,MAAO,CAAE,IAAAK,EAAK,OAAAC,CAAO,CACvB,CAEO,SAASI,GAAML,EAAUM,EAAmB,CACjD,IAAMF,EAAO,CAACJ,EAAI,GAAKM,EAAWN,EAAI,GAAKM,CAAS,EAOpD,MANoB,CAClBN,EAAI,IAAMI,EAAK,GAAKJ,EAAI,IAAM,EAC9BA,EAAI,IAAMI,EAAK,GAAKJ,EAAI,IAAM,EAC9BI,EAAK,GACLA,EAAK,EACP,CAEF,CChBA,IAAMG,GAAM,CAAE,QAAS,EAAK,EAEtBC,GAAwE,CAAE,SAAU,KAAM,UAAW,IAAK,EAC1GC,GAAyE,CAAE,SAAU,CAAC,IAAK,GAAG,EAAG,UAAW,CAAC,IAAK,GAAG,CAAE,EACzHC,GAAU,OAAO,iBACfC,GAA2D,CAC/D,UAAW,CAAC,QAAS,0BAA2B,qBAAsB,WAAY,iBAAiB,EACnG,SAAU,CAAC,CACb,EAEIC,GAA2B,KAC3BC,GACAC,GAA8B,CAAC,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,CAAC,EAC7DC,GAAW,EAETC,GAAWC,GAAO,EAAK,GAAK,EAAI,KAAK,IAAIA,CAAC,GAEhD,eAAsBC,GAAWC,EAAqC,CAEpE,GADIZ,GAAI,UAASC,GAAO,SAAW,MAC/B,CAACA,GAAO,UAAYW,EAAO,KAAK,UAAeA,EAAO,KAAK,SAAY,UAAoB,CAC7FX,GAAO,SAAW,MAAMY,EAAUD,EAAO,KAAK,SAAY,SAAY,EACtE,IAAME,EAAS,OAAO,OAAOb,GAAO,SAAS,eAAe,MAAS,EACrEC,GAAU,SAAS,GAAK,MAAM,QAAQY,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,EAC9FZ,GAAU,SAAS,GAAK,MAAM,QAAQY,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,CAChG,MAAWF,EAAO,OAASX,GAAO,UAAUc,EAAI,gBAAiBd,GAAO,SAAS,QAAW,EAC5F,aAAae,GAAc,EACpBf,GAAO,QAChB,CAEA,eAAsBgB,GAASL,EAAqC,CAElE,GADIZ,GAAI,UAASC,GAAO,UAAY,MAC/BA,GAAO,UAKDW,EAAO,OAAOG,EAAI,gBAAiBd,GAAO,UAAU,QAAW,MALnD,CACrBA,GAAO,UAAY,MAAMY,EAAUD,EAAO,KAAK,SAAS,EACxD,IAAME,EAAS,OAAO,OAAOb,GAAO,UAAU,eAAe,MAAS,EACtEC,GAAU,UAAU,GAAK,MAAM,QAAQY,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,EAC/FZ,GAAU,UAAU,GAAK,MAAM,QAAQY,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,CACjG,CACA,OAAOb,GAAO,SAChB,CAQA,eAAeiB,GAAaC,EAAeC,EAA+B,CACxE,IAAMC,EAA4B,CAAC,EACnC,GAAI,CAACF,EAAM,OAAS,CAACA,EAAM,MAAM,IAAM,CAACA,EAAM,MAAM,GAAI,OAAOA,EAC/D,IAAIG,EAIJ,GAHIC,KACFF,EAAE,QAAa,QAAM,cAAcF,EAAO,CAACI,EAAO,EAAG,CAAC,CAAC,EAAG,CAACJ,EAAM,MAAM,GAAIA,EAAM,MAAM,EAAE,CAAC,GAExFA,EAAM,MAAM,KAAOA,EAAM,MAAM,GAAI,CACrC,IAAMK,EAA2B,CAC/BL,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,EACtFA,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,CACxF,EACMM,EAA0B,CAC9BN,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,EACtFA,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,CACxF,EACAO,GAAU,CACR,CAAC,EAAG,CAAC,EACLF,EACAC,EACA,CAAC,EAAG,CAAC,CACP,EACAJ,EAAE,IAAS,MAAIA,EAAE,SAAWF,EAAOO,EAAO,EAC1CL,EAAE,OAAY,QAAM,eAAeA,EAAE,IAAK,CAACD,EAAMA,CAAI,CAAC,EACtDE,EAAW,MAAID,EAAE,OAAQM,EAAU,KAAK,CAC1C,MAAWR,EAAM,MAAM,KAAOC,GAC5BC,EAAE,OAAY,QAAM,eAAeA,EAAE,SAAWF,EAAO,CAACC,EAAMA,CAAI,CAAC,EACnEE,EAAW,MAAID,EAAE,OAAQM,EAAU,KAAK,GAExCL,EAAW,MAAID,EAAE,SAAWF,EAAOQ,EAAU,KAAK,EAEpD,cAAO,KAAKN,CAAC,EAAE,QAASO,GAAc,UAAQP,EAAEO,EAAO,CAAC,EACjDN,CACT,CAEA,SAASO,GAAiBC,EAAgCC,EAAmD,CAC3G,QAAWC,KAAOF,EAChBE,EAAI,SAAW,CACb,KAAK,MAAMA,EAAI,SAAS,IAAMD,EAAW,GAAKL,GAAQ,GAAG,GAAKA,GAAQ,GAAG,IAAMK,EAAW,GAAKL,GAAQ,GAAG,EAAE,EAC5G,KAAK,MAAMM,EAAI,SAAS,IAAMD,EAAW,GAAKL,GAAQ,GAAG,GAAKA,GAAQ,GAAG,IAAMK,EAAW,GAAKL,GAAQ,GAAG,EAAE,EAC5GM,EAAI,SAAS,EACf,EACAA,EAAI,YAAc,CAACA,EAAI,SAAS,GAAKD,EAAW,GAAIC,EAAI,SAAS,GAAKD,EAAW,GAAI,EAAKC,EAAI,SAAS,IAAiBD,EAAW,GAAKA,EAAW,GAAG,EAExJ,GAAIR,GACF,QAAWS,KAAOF,EAChBE,EAAI,YAAc,CAChBA,EAAI,YAAY,GAAKT,GAAQ,GAC7BS,EAAI,YAAY,GAAKT,GAAQ,GAC7BS,EAAI,YAAY,EAClB,EACAA,EAAI,SAAW,CACb,KAAK,MAAMA,EAAI,YAAY,GAAKD,EAAW,EAAE,EAC7C,KAAK,MAAMC,EAAI,YAAY,GAAKD,EAAW,EAAE,EAC7CC,EAAI,YAAY,EAClB,EAGJ,OAAOF,CACT,CAEA,eAAeG,GAAaH,EAAgC,CAE1D,IAAMI,EAAWJ,EAAU,KAAMK,GAAMA,EAAE,OAAS,UAAU,EACtDC,EAAYN,EAAU,KAAMK,GAAMA,EAAE,OAAS,WAAW,EACxDE,EAAYP,EAAU,KAAMK,GAAMA,EAAE,OAAS,WAAW,EAC9DD,EAAS,SAAS,KAAOE,EAAU,SAAS,IAAM,IAAMC,EAAU,SAAS,IAAM,IAAM,EACvF,IAAMC,EAAYR,EAAU,KAAMK,GAAMA,EAAE,OAAS,WAAW,EACxDI,EAAaT,EAAU,KAAMK,GAAMA,EAAE,OAAS,YAAY,EAC1DK,EAAaV,EAAU,KAAMK,GAAMA,EAAE,OAAS,YAAY,EAChEG,EAAU,SAAS,KAAOC,EAAW,SAAS,IAAM,IAAMC,EAAW,SAAS,IAAM,IAAM,CAC5F,CAEA,eAAeC,GAAgBtB,EAAeuB,EAAgBX,EAA0D,CAtIxH,IAAAY,EA8IE,IAAMtB,EAA4B,CAAC,EACnC,CAACA,EAAE,GAAqBA,EAAE,aAA+BA,EAAE,QAAyBA,EAAE,MAAwBA,EAAE,QAAiB,GAAIsB,EAAAC,GAAO,YAAP,YAAAD,EAAkB,QAAQxB,EAAO0B,GAAY,WAClL,IAAMC,GAAa,MAAMzB,EAAE,SAAS,KAAK,GAAG,GACtC0B,EAAS,MAAM1B,EAAE,GAAG,KAAK,EACzB2B,EAAY,MAAM3B,EAAE,MAAM,KAAK,EACrC,OAAO,KAAKA,CAAC,EAAE,QAASO,GAAc,UAAQP,EAAEO,EAAO,CAAC,EACxD,IAAMqB,EAAyC,CAAC,EAC1CC,EAAQ,EACd,QAASC,EAAI,EAAGA,EAAIJ,EAAO,OAASG,EAAOC,IAAK,CAC9C,IAAMC,EAAQC,GAAQN,EAAOG,EAAQC,EAAI,EAAE,EACrCG,EAAWD,GAAQN,EAAOG,EAAQC,EAAI,EAAE,EACxCI,EAAW,KAAK,MAAM,IAAMH,EAAQE,EAAWR,CAAS,EAAI,IAC5DU,EAAqB,CAACT,EAAOG,EAAQC,EAAI,GAAKM,GAAU,UAAU,GAAIV,EAAOG,EAAQC,EAAI,GAAKM,GAAU,UAAU,GAAIV,EAAOG,EAAQC,EAAI,GAAK,CAAC,EAC/IO,EAAkB,CAAC,KAAK,MAAM3B,EAAW,GAAKyB,EAAY,EAAE,EAAG,KAAK,MAAMzB,EAAW,GAAKyB,EAAY,EAAE,EAAGA,EAAY,EAAY,EACnIG,EAAkB,CAACX,EAAUE,EAAQC,EAAI,GAAIH,EAAUE,EAAQC,EAAI,GAAIH,EAAUE,EAAQC,EAAI,GAAK,CAAC,EACzGF,EAAkB,KAAK,CAAE,KAAajB,GAAImB,GAAoB,YAAAK,EAAa,SAAAE,EAAU,SAAAC,EAAU,MAAOJ,CAAS,CAAC,CAClH,CACA,GAAIT,GAAaJ,EAAO,KAAK,eAAiB,GAAI,OAAO,KACzDT,GAAagB,CAAiB,EAC9B,IAAMnB,EAAiCD,GAAiBoB,EAAmBlB,CAAU,EAC/E6B,EAAO9B,EAAU,IAAKK,GAAMA,EAAE,QAAQ,EACtC0B,EAAYC,GAAKF,EAAM,CAAC7B,EAAW,GAAIA,EAAW,EAAE,CAAC,EACrDgC,EAAiD,CAAC,EACxD,OAAW,CAACC,EAAMC,CAAO,IAAK,OAAO,QAAeC,EAAS,EAAG,CAC9D,IAAMC,EAAqB,CAAC,EAC5B,QAAShB,EAAI,EAAGA,EAAIc,EAAQ,OAAS,EAAGd,IAAK,CAC3C,IAAMiB,EAAMtC,EAAU,KAAME,GAAQA,EAAI,OAASiC,EAAQd,EAAE,EACrDkB,EAAMvC,EAAU,KAAME,GAAQA,EAAI,OAASiC,EAAQd,EAAI,EAAE,EAC3DiB,GAAOC,GAAKF,EAAG,KAAK,CAACC,EAAI,SAAUC,EAAI,QAAQ,CAAC,CACtD,CACAN,EAAYC,GAAQG,CACtB,CAEA,MADa,CAAE,GAAI,EAAG,MAAO,KAAK,MAAM,IAAMrB,CAAS,EAAI,IAAK,IAAKe,EAAM,IAAK,OAAQA,EAAM,OAAQ,UAAA/B,EAAW,YAAAiC,CAAY,CAE/H,CAgCA,eAAsBO,GAAQnD,EAAeuB,EAAuC,CAClF,IAAMX,EAA+B,CAACZ,EAAM,MAAM,IAAM,EAAGA,EAAM,MAAM,IAAM,CAAC,EACxEoD,GAAY7B,EAAO,KAAK,UAAY,GAAM8B,EAAI,EAAIC,GAClDC,EAAYC,IAAWjC,EAAO,KAAK,YAAc,GACvD,GAAIA,EAAO,aAAe6B,GAAYG,GAAaE,KAAU,KAC3DD,SACK,CACL,IAAMtD,EAA4B,CAAC,EAOnCA,EAAE,UAAY,MAAMH,GAAaC,EAAO,GAAG,EAC3CyD,GAAQ,MAAMnC,GAAgBpB,EAAE,UAAWqB,EAAQX,CAAU,EAe7D,OAAO,KAAKV,CAAC,EAAE,QAASO,GAAc,UAAQP,EAAEO,EAAO,CAAC,EACxD6C,GAAWD,EAAI,EACfG,GAAU,CACZ,CACA,OAAOC,GAAQ,CAACA,EAAK,EAAI,CAAC,CAC5B,CChPO,IAAMC,GAAS,CACpB,CAAE,MAAO,EAAG,MAAO,QAAS,EAC5B,CAAE,MAAO,EAAG,MAAO,SAAU,EAC7B,CAAE,MAAO,EAAG,MAAO,KAAM,EACzB,CAAE,MAAO,EAAG,MAAO,YAAa,EAChC,CAAE,MAAO,EAAG,MAAO,UAAW,EAC9B,CAAE,MAAO,EAAG,MAAO,KAAM,EACzB,CAAE,MAAO,EAAG,MAAO,OAAQ,EAC3B,CAAE,MAAO,EAAG,MAAO,OAAQ,EAC3B,CAAE,MAAO,EAAG,MAAO,MAAO,EAC1B,CAAE,MAAO,GAAI,MAAO,eAAgB,EACpC,CAAE,MAAO,GAAI,MAAO,cAAe,EACnC,CAAE,MAAO,GAAI,MAAO,WAAY,EAChC,CAAE,MAAO,GAAI,MAAO,eAAgB,EACpC,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,KAAM,EAC1B,CAAE,MAAO,GAAI,MAAO,KAAM,EAC1B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,KAAM,EAC1B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,SAAU,EAC9B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,SAAU,EAC9B,CAAE,MAAO,GAAI,MAAO,KAAM,EAC1B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,SAAU,EAC9B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,WAAY,EAChC,CAAE,MAAO,GAAI,MAAO,aAAc,EAClC,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,cAAe,EACnC,CAAE,MAAO,GAAI,MAAO,gBAAiB,EACrC,CAAE,MAAO,GAAI,MAAO,YAAa,EACjC,CAAE,MAAO,GAAI,MAAO,WAAY,EAChC,CAAE,MAAO,GAAI,MAAO,eAAgB,EACpC,CAAE,MAAO,GAAI,MAAO,QAAS,EAC7B,CAAE,MAAO,GAAI,MAAO,YAAa,EACjC,CAAE,MAAO,GAAI,MAAO,KAAM,EAC1B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,QAAS,EAC7B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,QAAS,EAC7B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,QAAS,EAC7B,CAAE,MAAO,GAAI,MAAO,SAAU,EAC9B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,cAAe,EACnC,CAAE,MAAO,GAAI,MAAO,KAAM,EAC1B,CAAE,MAAO,GAAI,MAAO,cAAe,EACnC,CAAE,MAAO,GAAI,MAAO,QAAS,EAC7B,CAAE,MAAO,GAAI,MAAO,IAAK,EACzB,CAAE,MAAO,GAAI,MAAO,QAAS,EAC7B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,QAAS,EAC7B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,YAAa,EACjC,CAAE,MAAO,GAAI,MAAO,WAAY,EAChC,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,SAAU,EAC9B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,cAAe,EACnC,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,YAAa,EACjC,CAAE,MAAO,GAAI,MAAO,YAAa,EACjC,CAAE,MAAO,GAAI,MAAO,YAAa,CACnC,ECrEA,IAAIC,GACAC,GAAY,EACZC,GAAuB,CAAC,EACxBC,GAAW,EACXC,GAAU,OAAO,iBAErB,eAAsBC,GAAKC,EAAqC,CAE9D,GADIC,EAAI,UAASP,GAAQ,MACpBA,GAKMM,EAAO,OAAOE,EAAI,gBAAiBR,GAAM,QAAW,MALnD,CAEVA,GAAQ,MAAMS,EAAUH,EAAO,OAAO,SAAS,EAC/C,IAAMI,EAAS,OAAO,OAAOV,GAAM,eAAe,MAAS,EAC3DC,GAAY,MAAM,QAAQS,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,CACpF,CACA,OAAOV,EACT,CAEA,eAAeW,GAAQC,EAAoBC,EAA+BP,EAAgB,CACxF,GAAI,CAACM,EAAK,MAAO,CAAC,EAClB,IAAME,EAA4B,CAAC,EAC7BC,EAA+B,CAAC,EAChCC,EAAa,MAAMJ,EAAI,MAAM,EACnCE,EAAE,QAAa,UAAQF,CAAG,EAC1B,IAAMK,EAAS,QAAMH,EAAE,QAAS,EAAG,CAAC,EACpCA,EAAE,MAAW,QAAM,CAACG,EAAI,GAAIA,EAAI,GAAIA,EAAI,GAAIA,EAAI,EAAE,EAAG,CAAC,EACtDH,EAAE,MAAW,UAAQA,EAAE,KAAK,EAC5BA,EAAE,OAAY,UAAQG,EAAI,EAAE,EAC5BH,EAAE,QAAa,UAAQG,EAAI,EAAE,EAC1B,UAAQ,CAACL,EAAK,GAAGK,CAAG,CAAC,EACxBH,EAAE,IAAM,MAAS,QAAM,uBAAuBA,EAAE,MAAOA,EAAE,OAAQR,EAAO,OAAO,YAAaA,EAAO,OAAO,aAAeA,EAAO,OAAO,eAAiB,CAAE,EAC1J,IAAMY,EAAM,MAAMJ,EAAE,IAAI,KAAK,EACzBK,EAAI,EACR,QAAWC,KAAM,MAAM,KAAKF,CAAG,EAAG,CAChC,IAAMG,EAAQ,KAAK,MAAM,IAAML,EAAW,GAAGI,GAAI,EAAE,EAAI,IACjDE,EAAWN,EAAW,GAAGI,GAAI,GAC7BG,EAAQC,GAAOF,GAAU,MACzB,CAACG,EAAGC,CAAC,EAAI,CACbV,EAAW,GAAGI,GAAI,GAAKnB,GACvBe,EAAW,GAAGI,GAAI,GAAKnB,EACzB,EACM0B,EAAc,CAClBF,EACAC,EACAV,EAAW,GAAGI,GAAI,GAAKnB,GAAYwB,EACnCT,EAAW,GAAGI,GAAI,GAAKnB,GAAYyB,CACrC,EACME,EAAW,CACf,KAAK,MAAMD,EAAO,GAAKd,EAAY,EAAE,EACrC,KAAK,MAAMc,EAAO,GAAKd,EAAY,EAAE,EACrC,KAAK,MAAMc,EAAO,GAAKd,EAAY,EAAE,EACrC,KAAK,MAAMc,EAAO,GAAKd,EAAY,EAAE,CACvC,EACAE,EAAQ,KAAK,CAAE,GAAII,IAAK,MAAAE,EAAO,MAAOC,EAAU,MAAAC,EAAO,IAAAK,EAAK,OAAAD,CAAO,CAAC,CACtE,CACA,cAAO,KAAKb,CAAC,EAAE,QAASe,GAAc,UAAQf,EAAEe,EAAO,CAAC,EACjDd,CACT,CAEA,eAAsBe,GAAQC,EAAezB,EAAyC,CACpF,IAAM0B,GAAY1B,EAAO,OAAO,UAAY,GAAM2B,EAAI,EAAI9B,GACpD+B,EAAY9B,IAAWE,EAAO,OAAO,YAAc,GACzD,OAAIA,EAAO,aAAe0B,GAAYE,GAAchC,GAAK,OAAS,GAChEE,KACOF,KAETE,GAAU,EACH,IAAI,QAAQ,MAAO+B,GAAY,CACpC,IAAMC,EAAa,CAACL,EAAM,MAAM,IAAM,EAAGA,EAAM,MAAM,IAAM,CAAC,EACtDM,EAAY,QAAM,eAAeN,EAAO,CAAC9B,GAAWA,EAAS,CAAC,EAC9DqC,EAAUhC,EAAO,OAAO,QAAUN,IAAA,YAAAA,GAAO,QAAQqC,EAAQ,CAAC,oBAAoB,GAAe,KACnGlC,GAAW8B,EAAI,EACZ,UAAQI,CAAM,EAEjB,IAAME,EAAM,MAAM5B,GAAQ2B,EAASF,EAAY9B,CAAM,EACrDJ,GAAOqC,EAEPJ,EAAQI,CAAG,CACb,CAAC,EACH,CC7FA,IAAAC,GAAA,GAAAC,GAAAD,GAAA,eAAAE,GAAA,QAAAC,KAAO,IAAMA,GAAqB,CAChC,OACA,OACA,gBACA,aACA,aACA,QACA,eACA,YACA,YACA,aACA,WACA,YACA,aACA,UACA,WACA,WACF,EAEaD,GAAsC,CACjD,QAAS,CAAC,UAAW,WAAY,WAAW,EAC5C,SAAU,CAAC,WAAY,YAAa,YAAY,EAChD,MAAO,CAAC,eAAgB,gBAAiB,WAAY,UAAW,cAAc,EAC9E,QAAS,CAAC,eAAgB,YAAa,WAAW,EAClD,SAAU,CAAC,gBAAiB,aAAc,YAAY,EACtD,KAAM,CAAC,CACT,ECVA,IAAIE,GACAC,GAAW,EACTC,GAAoB,CAAE,GAAI,EAAG,UAAW,CAAC,EAAG,IAAK,CAAC,EAAG,EAAG,EAAG,CAAC,EAAG,OAAQ,CAAC,EAAG,EAAG,EAAG,CAAC,EAAG,MAAO,EAAG,YAAa,CAAC,CAAuC,EAMtJC,GAAU,OAAO,iBAErB,eAAsBC,GAAKC,EAAqC,CAC9D,OAAIC,EAAI,UAASN,GAAQ,MACpBA,GACIK,EAAO,OAAOE,EAAI,gBAAiBP,GAAM,QAAW,EADjDA,GAAQ,MAAMQ,EAAUH,EAAO,KAAK,SAAS,EAElDL,EACT,CAGA,eAAeS,GAAMC,EAAQC,EAAU,CACrC,GAAM,CAACC,EAAOC,CAAM,EAAIH,EAAO,MACzBI,EAAc,UAAQJ,EAAQ,CAACG,EAASD,CAAK,CAAC,EAC9CG,EAAS,MAAID,EAAU,CAAC,EACxBE,GAAY,MAAMD,EAAI,KAAK,GAAG,GAEpC,GADG,UAAQ,CAACD,EAAUC,CAAG,CAAC,EACtBC,EAAWL,EAAU,CACvB,IAAMM,EAAiB,SAAOH,EAAU,CAAC,EACnCI,EAAS,MAAID,EAAaL,CAAK,EAC/BO,GAAK,MAAMD,EAAI,KAAK,GAAG,GACvBE,EAAS,MAAIH,EAAgB,SAAOL,EAAO,OAAO,CAAC,EACnD,GAAK,MAAMQ,EAAI,KAAK,GAAG,GAC7B,OAAG,UAAQ,CAACF,EAAKE,CAAG,CAAC,EACd,CAACD,EAAG,EAAGH,CAAQ,CACxB,CACA,MAAO,CAAC,EAAG,EAAGA,CAAQ,CACxB,CAEA,eAAsBK,GAAQC,EAAejB,EAAuC,CAClF,IAAMkB,GAAYlB,EAAO,KAAK,UAAY,GAAMmB,EAAI,EAAIvB,GAClDwB,EAAYtB,IAAWE,EAAO,KAAK,YAAc,GACvD,OAAIA,EAAO,aAAekB,GAAYE,GAAa,OAAO,KAAKvB,GAAM,SAAS,EAAE,OAAS,GACvFC,KACO,CAACD,EAAK,IAEfC,GAAU,EACH,IAAI,QAAQ,MAAOuB,GAAY,CA5DxC,IAAAC,EA6DI,IAAMC,EAAY,OAAK,IAAM,CAC3B,GAAI,EAAC5B,IAAA,MAAAA,GAAO,OAAO,GAAG,OAAO,OAAO,KACpC,IAAM6B,EAAY,QAAM,eAAeP,EAAO,CAACtB,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,EAAG,EAAK,EACnG8B,EAAa,MAAID,EAAQE,EAAU,GAAG,EAE5C,OADgB,MAAID,EAASC,EAAU,GAAG,CAE5C,CAAC,EAEGC,EAKJ,GAJI3B,EAAO,KAAK,UAAS2B,EAAOhC,IAAA,YAAAA,GAAO,QAAQ4B,IAC/C3B,GAAWuB,EAAI,EACZ,UAAQI,CAAM,EAEbI,EAAM,CACR9B,GAAM,UAAU,OAAS,EACzB,IAAM+B,EAAUD,EAAK,QAAQ,EAC1B,UAAQA,CAAI,EAEf,IAAME,EAAQD,EAAQ,QAAQ,CAAC,EAC5B,UAAQA,CAAO,EAElB,QAASE,EAAK,EAAGA,EAAKD,EAAM,OAAQC,IAAM,CAExC,GAAM,CAAChB,EAAGiB,EAAGC,CAAS,EAAI,MAAM5B,GAAMyB,EAAMC,GAAK9B,EAAO,KAAK,aAAa,EACtEgC,KAAaV,EAAAtB,EAAO,OAAP,YAAAsB,EAAa,gBAAiB,IAC7CzB,GAAM,UAAU,KAAK,CACnB,MAAO,KAAK,MAAM,IAAMmC,CAAS,EAAI,IACrC,KAAaC,GAAIH,GACjB,YAAa,CAEXhB,EAAInB,GAAM,OAAO,GAAG,MAAM,GAAIoC,EAAIpC,GAAM,OAAO,GAAG,MAAM,EAC1D,EACA,SAAU,CAER,KAAK,MAAMsB,EAAM,MAAM,GAAKH,EAAInB,GAAM,OAAO,GAAG,MAAM,EAAE,EAAG,KAAK,MAAMsB,EAAM,MAAM,GAAKc,EAAIpC,GAAM,OAAO,GAAG,MAAM,EAAE,CACrH,CACF,CAAC,CAEL,CACAkC,EAAM,QAASK,GAAS,UAAQA,CAAC,CAAC,CACpC,CACArC,GAAM,MAAQA,GAAM,UAAU,OAAO,CAACsC,EAAMC,IAAUA,EAAK,MAAQD,EAAOC,EAAK,MAAQD,EAAO,CAAC,EAC/F,IAAMrB,EAAIjB,GAAM,UAAU,IAAKwC,GAAMA,EAAE,SAAS,EAAE,EAC5CN,EAAIlC,GAAM,UAAU,IAAKwC,GAAMA,EAAE,SAAS,EAAE,EAClDxC,GAAM,IAAM,CACV,KAAK,IAAI,GAAGiB,CAAC,EACb,KAAK,IAAI,GAAGiB,CAAC,EACb,KAAK,IAAI,GAAGjB,CAAC,EAAI,KAAK,IAAI,GAAGA,CAAC,EAC9B,KAAK,IAAI,GAAGiB,CAAC,EAAI,KAAK,IAAI,GAAGA,CAAC,CAChC,EACA,IAAMO,EAAOzC,GAAM,UAAU,IAAKwC,GAAMA,EAAE,YAAY,EAAE,EAClDE,EAAO1C,GAAM,UAAU,IAAKwC,GAAMA,EAAE,YAAY,EAAE,EACxDxC,GAAM,OAAS,CACb,KAAK,IAAI,GAAGyC,CAAI,EAChB,KAAK,IAAI,GAAGC,CAAI,EAChB,KAAK,IAAI,GAAGD,CAAI,EAAI,KAAK,IAAI,GAAGA,CAAI,EACpC,KAAK,IAAI,GAAGC,CAAI,EAAI,KAAK,IAAI,GAAGA,CAAI,CACtC,EACA,OAAW,CAACC,EAAMC,CAAO,IAAK,OAAO,QAAeC,EAAS,EAAG,CAC9D,IAAMC,EAAqB,CAAC,EAC5B,QAASC,EAAI,EAAGA,EAAIH,EAAQ,OAAS,EAAGG,IAAK,CAC3C,IAAMC,EAAMhD,GAAM,UAAU,KAAMoC,GAAQA,EAAI,OAASQ,EAAQG,EAAE,EAC3DE,EAAMjD,GAAM,UAAU,KAAMoC,GAAQA,EAAI,OAASQ,EAAQG,EAAI,EAAE,EACjEC,GAAOC,GAAOD,EAAI,OAAS7C,EAAO,KAAK,eAAiB,IAAM8C,EAAI,OAAS9C,EAAO,KAAK,eAAiB,IAAI2C,EAAG,KAAK,CAACE,EAAI,SAAUC,EAAI,QAAQ,CAAC,CACtJ,CACAjD,GAAM,YAAY2C,GAAQG,CAC5B,CACAtB,EAAQ,CAACxB,EAAK,CAAC,CACjB,CAAC,EACH,CCnHA,IAAMkD,GAAc,CAAC,QAAS,UAAW,OAAQ,QAAS,MAAO,WAAY,SAAS,EAClFC,GACEC,GAA0D,CAAC,EAC7DC,GAAY,EACZC,GAAW,EACXC,GAAU,OAAO,iBAErB,eAAsBC,GAAKC,EAAqC,CAtBhE,IAAAC,EAuBE,OAAIC,EAAI,UAASR,GAAQ,MACpBA,GACIM,EAAO,OAAOG,EAAI,gBAAiBT,GAAM,QAAW,EADjDA,GAAQ,MAAMU,GAAUH,EAAAD,EAAO,KAAK,UAAZ,YAAAC,EAAqB,SAAS,EAE3DP,EACT,CAEA,eAAsBW,GAAQC,EAAeN,EAAgBO,EAAaC,EAAoE,CA7B9I,IAAAP,EAAAQ,EA8BE,GAAI,CAACf,GAAO,MAAO,CAAC,EACpB,IAAMgB,EAAYZ,MAAWG,EAAAD,EAAO,KAAK,UAAZ,YAAAC,EAAqB,aAAc,GAC1DU,KAAYF,EAAAT,EAAO,KAAK,UAAZ,YAAAS,EAAqB,WAAY,GAAMG,EAAI,EAAIf,GACjE,OAAIG,EAAO,aAAeW,GAAYD,GAAcd,KAAcY,GAAUb,GAAKY,IAASZ,GAAKY,GAAK,OAAS,GAC3GT,KACOH,GAAKY,KAEdT,GAAU,EACH,IAAI,QAAQ,MAAOe,GAAY,CAtCxC,IAAAZ,EAAAQ,EAuCI,IAAMK,EAAkD,CAAC,EACzD,IAAIb,EAAAD,EAAO,KAAK,UAAZ,MAAAC,EAAqB,QAAS,CAChC,IAAMc,EAA4B,CAAC,EAC7BC,EAAYtB,IAAA,MAAAA,GAAO,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EACtEqB,EAAE,OAAY,QAAM,eAAeT,EAAO,CAACU,EAAWA,CAAS,EAAG,EAAK,EASvED,EAAE,SAAc,MAAIA,EAAE,OAAQE,EAAU,GAAG,EAC3CF,EAAE,UAAe,MAAIA,EAAE,SAAU,EAAG,EAAI,EACxCA,EAAE,aAAkB,MAAIA,EAAE,UAAWE,EAAU,IAAI,EACnDF,EAAE,aAAkB,MAAIA,EAAE,aAAcE,EAAU,GAAG,EACrDF,EAAE,QAAUrB,IAAA,YAAAA,GAAO,QAAQqB,EAAE,cAC7BlB,GAAWe,EAAI,EACf,IAAMM,EAAO,MAAMH,EAAE,QAAQ,KAAK,EAClC,QAASI,EAAI,EAAGA,EAAID,EAAK,OAAQC,IAC3BD,EAAKC,MAAMV,EAAAT,EAAO,KAAK,UAAZ,YAAAS,EAAqB,gBAAiB,IAAIK,EAAI,KAAK,CAAE,MAAO,KAAK,IAAI,IAAM,KAAK,MAAM,IAAMI,EAAKC,EAAE,EAAI,GAAG,EAAG,QAAS1B,GAAY0B,EAAc,CAAC,EAElKL,EAAI,KAAK,CAACM,EAAGC,IAAMA,EAAE,MAAQD,EAAE,KAAK,EACpC,OAAO,KAAKL,CAAC,EAAE,QAASO,GAAc,UAAQP,EAAEO,EAAO,CAAC,CAC1D,CACA3B,GAAKY,GAAOO,EACZlB,GAAYY,EACZK,EAAQC,CAAG,CACb,CAAC,EACH,CCtDA,IAAIS,GACEC,GAAwB,CAAC,EAC3BC,GAAY,EACZC,GAAW,EACXC,GAAU,OAAO,iBAErB,eAAsBC,GAAKC,EAAqC,CAC9D,OAAIC,EAAI,UAASP,GAAQ,MACpBA,GACIM,EAAO,OAAOE,EAAI,gBAAiBR,GAAM,QAAW,EADjDA,GAAQ,MAAMS,EAAUH,EAAO,KAAK,cAAiB,SAAS,EAEnEN,EACT,CAoBA,eAAsBU,GAAQC,EAAeL,EAAgBM,EAAKC,EAA0B,CA9C5F,IAAAC,EAAAC,EA+CE,GAAI,CAACf,GAAO,MAAO,CAAC,EACpB,IAAMgB,EAAYZ,MAAWU,EAAAR,EAAO,KAAK,YAAZ,YAAAQ,EAA0B,aAAc,GAC/DG,KAAYF,EAAAT,EAAO,KAAK,YAAZ,YAAAS,EAA0B,WAAY,GAAMG,EAAI,EAAIf,GACtE,OAAIG,EAAO,aAAeW,GAAYD,GAAcd,KAAcW,GAAUZ,GAAKW,IAC/ER,KACOH,GAAKW,IAEP,IAAI,QAAQ,MAAOO,GAAY,CAtDxC,IAAAL,EAuDI,IAAIM,EAAsB,CAAC,EAC3B,KAAIN,EAAAR,EAAO,KAAK,YAAZ,YAAAQ,EAA0B,WAAWd,IAAA,YAAAA,GAAO,OAAO,GAAG,OAAO,CAC/D,IAAMqB,EAA4B,CAAC,EACnCA,EAAE,KAAU,QAAM,eAAeV,EAAO,CAACX,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,EAAG,EAAK,EAInGqB,EAAE,KAAOrB,IAAA,YAAAA,GAAO,QAAQqB,EAAE,MAa1B,IAAMC,EAAS,MAAMD,EAAE,KAAK,KAAK,EACjCD,EAAO,MAAM,KAAKE,CAAM,CAC1B,CACArB,GAAKW,GAAOQ,EACZlB,GAAYW,EACZV,GAAWe,EAAI,EACfC,EAAQC,CAAI,CACd,CAAC,CACH,CCzEA,IAAIG,GACAC,GAAY,EAEVC,GAAc,IAEdC,GAAqBC,GAAgB,cACrCC,GAAsBD,GAAgB,eAEtCE,GAAe,CACnB,WAAY,CAACH,GAAY,GAAIA,GAAYA,GAAY,OAAS,EAAE,EAChE,YAAa,CAACE,GAAa,GAAIA,GAAaA,GAAa,OAAS,EAAE,CACtE,EAEME,GAAgB,CACpB,YAAa,EACb,YAAa,EACb,MAAO,GACP,eAAgB,EAClB,EAEA,eAAsBC,GAAKC,EAAqC,CA9BhE,IAAAC,EA+BE,OAAIC,EAAI,UAASX,GAAQ,MACpBA,GACIS,EAAO,OAAOG,EAAI,gBAAiBZ,GAAM,QAAW,EADjDA,GAAQ,MAAMa,GAAUH,EAAAD,EAAO,KAAK,OAAZ,YAAAC,EAAkB,SAAS,EAE/DT,GAAYD,GAAM,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EAC3DC,KAAc,KAAIA,GAAY,IAC3BD,EACT,CAGO,SAASc,GAAkBC,EAAWC,EAAWC,EAAQC,EAAM,CACpE,QAASC,EAAI,EAAGA,EAAWC,GAAY,OAAQD,IAAK,CAClD,GAAM,CAAE,IAAAE,EAAK,QAAAC,CAAQ,EAAWF,GAAYD,GACtCI,EAAyBnB,GAAgB,GAAGa,IAASI,KAC3D,GAAI,CAACH,GAAQA,EAAK,SAASG,CAAG,EAC5B,QAASG,EAAI,EAAGA,EAAIF,EAAQ,OAAQE,IAAK,CACvC,IAAMC,EAAQH,EAAQE,GACtBT,EAAUQ,EAAgBC,IAAM,CAC9BR,EAAUS,GAAO,GACjBT,EAAUS,GAAO,IAChBT,EAAUS,GAAO,GAAKV,EAAUQ,EAAgBC,IAAI,IAAM,CAC7D,CACF,CAEJ,CACF,CAEO,IAAME,GAAoCX,GAAc,CAC7D,IAAMY,EAAWZ,EAAUT,GAAa,WAAW,IAAI,GACjDsB,EAAYb,EAAUT,GAAa,YAAY,IAAI,GACzD,OAAOqB,EAAWC,CACpB,EAGaC,GAAY,CAACd,EAAWe,EAAMC,EAAqBC,EAAqBC,EAAUC,EAAO,KAAU,CAC9G,IAAMC,EAAWC,GAAiBC,GAAgBC,GAA8B,CAACvB,EAAUgB,GAAsBhB,EAAUiB,EAAoB,CAAC,EAAG9B,EAAW,CAAC,EACzJqC,EAAeC,GAAWL,CAAG,EAC/BM,EAAU,QAAM,cAAcX,EAAM,CAAC,CACvCK,EAAI,WAAW,GAAKF,EACpBE,EAAI,WAAW,GAAKF,EAAUE,EAAI,SAAS,GAAKF,EAChDE,EAAI,SAAS,GAAKF,CACpB,CAAC,EAAG,CAAC,CAAC,EAAG,CAAChC,GAAWA,EAAS,CAAC,EAC/B,GAAIiC,GAAQvB,EAAI,QAAQ,SAAS,eAAe,EAAG,CACjD,IAAM+B,EAAa,QAAM,cAAcD,CAAI,EACxC,UAAQA,CAAI,EACfA,EAAOC,CACT,CACA,MAAO,CAAE,IAAAP,EAAK,QAAAI,EAAS,KAAAE,CAAK,CAC9B,EAGaE,GAAe,CAACC,EAASC,EAAQC,EAAYZ,EAAO,KAAU,CACzE,IAAMa,EAA6B,CAAC,EACpC,QAAS5B,EAAI,EAAGA,EAAIZ,GAAc,eAAgBY,IAAK,CACrD,IAAM6B,EAAIJ,EAAQzB,EAAI,GAChB8B,EAAIL,EAAQzB,EAAI,EAAI,GACpB+B,EAAIN,EAAQzB,EAAI,EAAI,GAC1B4B,EAAa,KAAK,EACfb,EAAQ,EAAKc,EAAI/C,GAAe+C,EAAI/C,IAAc6C,EAAW,GAAKD,EAAO,WAAW,GACpFI,EAAIhD,GAAa6C,EAAW,GAAKD,EAAO,WAAW,GAAIK,CAC1D,CAAC,CACH,CACA,MAAO,CAAE,UAAWH,EAAc,KAAMA,EAAa,MAAMxC,GAAc,KAAK,CAAE,CAClF,EAGa4C,GAAwB,CAACpC,EAAWqC,EAAYC,IAAc,CACzE,IAAMC,EAAevC,EAAiBX,GAAgB,GAAGiD,cAAsB9C,GAAc,cAAc,GACrGgD,EAAexC,EAAiBX,GAAgB,GAAGiD,cAAsB9C,GAAc,cAAc,GACrGiD,GAAYF,EAAeC,GAAgB,EAEjD,OAAOH,EAAW,IAAI,CAACK,EAAO,IAAM,CAClC,IAAIP,EAAIM,EACR,OAAI,IAAM,EACRN,EAAII,EACK,IAAM,IACfJ,EAAIK,GAEC,CAACE,EAAM,GAAIA,EAAM,GAAIP,CAAC,CAC/B,CAAC,CACH,EAEA,eAAsBQ,GAAY3C,EAAWe,EAAMrB,EAAQwB,EAAU,CACnE,GAAI,CAACjC,GACH,OAAIS,EAAO,OAAOG,EAAI,6DAA6D,EAC5EG,EAET,GAAM,CAAE,IAAK4C,EAAY,QAASC,EAAgB,KAAMC,CAAY,EAAIhC,GAAUd,EAAWe,EAAMxB,GAAa,WAAW,GAAIA,GAAa,WAAW,GAAI2B,EAAU,EAAI,EACnK,CAAE,IAAK6B,EAAa,QAASC,EAAiB,KAAMC,CAAa,EAAInC,GAAUd,EAAWe,EAAMxB,GAAa,YAAY,GAAIA,GAAa,YAAY,GAAI2B,EAAU,EAAI,EACxKgC,EAAc,SAAO,CAACJ,EAAaG,CAAY,CAAC,EACnD,UAAQH,CAAW,EACnB,UAAQG,CAAY,EACvB,IAAME,EAAiBlE,GAAM,QAAQiE,CAAQ,EAC1C,UAAQA,CAAQ,EACnB,IAAME,EAAqB,MAAMD,EAAe,KAAK,EAClD,UAAQA,CAAc,EACzB,IAAME,EAAcD,EAAmB,MAAM,EAAG5D,GAAc,eAAiB,CAAC,EAC1E,CAAE,UAAW8D,EAAkB,KAAMC,CAAkB,EAAI3B,GAAayB,EAAaT,EAAYC,EAAgB,EAAI,EACrHW,EAAeJ,EAAmB,MAAM5D,GAAc,eAAiB,CAAC,EACxE,CAAE,UAAWiE,EAAmB,KAAMC,CAAmB,EAAI9B,GAAa4B,EAAcT,EAAaC,EAAiB,EAAK,EAC3HW,EAAgChD,GAAiCX,CAAS,EAC5E,KAAK,IAAI2D,CAA6B,EAAI,IAC5C5D,GAAkBC,EAAWsD,EAAkB,OAAQ,IAAI,EAC3DvD,GAAkBC,EAAWyD,EAAmB,QAAS,IAAI,GAEpDE,EAAgC,EACzC5D,GAAkBC,EAAWsD,EAAkB,OAAQ,CAAC,YAAa,WAAW,CAAC,EAEjFvD,GAAkBC,EAAWyD,EAAmB,QAAS,CAAC,YAAa,WAAW,CAAC,EAErF,IAAMG,EAAyBxB,GAAsBpC,EAAWuD,EAAmB,MAAM,EACnFM,EAA0BzB,GAAsBpC,EAAW0D,EAAoB,OAAO,EAE5F,OADkB1D,EAAU,OAAO4D,CAAsB,EAAE,OAAOC,CAAuB,CAE3F,CC3IA,IAAMC,GAA8B,CACl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kC,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAEjOC,GAAsC,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAErIC,GAAmC,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAElFC,GAAmC,CAAC,CAAC,GAAI,CAAC,EAAG,CAAC,EAAG,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAE5NC,GAAuC,CAAC,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,CAAC,EAEzHC,GAAoC,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAEnFC,GAAmC,CACvC,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EACpN,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,CAC5M,EAmJA,SAASC,GAAqBC,EAAwB,CACpD,IAAMC,EAAUD,EAAY,IAAKE,GAAeA,EAAW,EAAE,EAC7D,OAAAD,EAAQ,KAAKD,EAAYA,EAAY,OAAS,GAAG,EAAE,EAC5CC,CACT,CAEO,IAAME,GAA2C,CACtD,KAAMJ,GAAqBK,EAAgB,EAC3C,QAASL,GAAqBM,EAAoB,EAClD,YAAaN,GAAqBO,EAAwB,EAC1D,SAAUP,GAAqBQ,EAAqB,EACpD,SAAUR,GAAqBS,EAAqB,EACpD,aAAcT,GAAqBU,EAAyB,EAC5D,UAAWV,GAAqBW,EAAsB,EACtD,SAAUX,GAAqBY,EAAqB,CACtD,EAEMC,GAA2C,OAAO,QAAQT,EAAwC,EACrG,IAAI,CAAC,CAACU,EAAOZ,CAAO,IAAMA,EAAQ,IAAKa,GAAU,CAACA,EAAOD,CAAK,CAAqB,CAAC,EACpF,KAAK,EAEKE,GAAgC,IAAI,IAAIH,EAAe,EAQvDI,GAAmC,CAC9C,GAAI,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAC9C,IAAK,GAAI,GAAI,GAAI,EAAG,IAAK,IAAK,IAAK,IACnC,GAAI,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAC7C,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IACpC,GAAI,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAC7C,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IACpC,GAAI,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAC7C,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GACtC,EAEaC,GAAuC,CAClD,GAAI,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACrC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC9B,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IACnC,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,IACzB,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACvC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC9B,GAAI,IAAK,GAAI,GAAI,GAAI,GACrB,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACxC,IAAK,GAAI,GAAI,IAAK,GAAI,IAAK,GAAI,GACjC,EAEaC,GAAwC,CACnD,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACxC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC9B,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACxC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC9B,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACxC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC9B,IAAK,IAAK,IAAK,IAAK,IAAK,IACzB,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACxC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GACrC,ECvOA,eAAsBC,GAAQC,EAAWC,EAAmB,CAC1D,IAAMC,EAAkC,CAGtC,KAAM,MAAMD,EAAQ,OAAQE,GAAMA,EAAE,OAAS,GAAG,EAAE,GAAG,KAAK,EAC1D,MAAO,MAAMF,EAAQ,OAAQE,GAAMA,EAAE,OAAS,EAAE,EAAE,GAAG,KAAK,EAC1D,KAAM,MAAMF,EAAQ,OAAQE,GAAMA,EAAE,OAAS,GAAG,EAAE,GAAG,KAAK,EAC1D,MAAO,MAAMF,EAAQ,OAAQE,GAAMA,EAAE,OAAS,EAAE,EAAE,GAAG,KAAK,EAC1D,KAAM,MAAMF,EAAQ,OAAQE,GAAMA,EAAE,OAAS,GAAG,EAAE,GAAG,KAAK,CAC5D,EAGMC,EAAuBC,GAAqC,OAAO,CAACC,EAAMC,IAASD,GAAQN,EAAUO,GAAM,GAAI,CAAC,EAAcF,GAAqC,OACzK,QAASG,EAAI,EAAGA,EAAIN,EAAE,MAAM,OAAS,EAAGM,IAAKR,EAAU,KAAK,CAACE,EAAE,MAAM,EAAIM,EAAI,GAAIN,EAAE,MAAM,EAAIM,EAAI,GAAIJ,CAAU,CAAC,EAChH,IAAMK,EAAuBC,GAAsC,OAAO,CAACJ,EAAMC,IAASD,GAAQN,EAAUO,GAAM,GAAI,CAAC,EAAcG,GAAsC,OAC3K,QAASF,EAAI,EAAGA,EAAIN,EAAE,MAAM,OAAS,EAAGM,IAAKR,EAAU,KAAK,CAACE,EAAE,MAAM,EAAIM,EAAI,GAAIN,EAAE,MAAM,EAAIM,EAAI,GAAIC,CAAU,CAAC,EAGhH,QAASD,EAAI,EAAGA,EAAIN,EAAE,KAAK,OAAS,EAAGM,IAAKR,EAAoBK,GAAqCG,IAAM,CAACN,EAAE,KAAK,EAAIM,EAAI,GAAIN,EAAE,KAAK,EAAIM,EAAI,GAAIR,EAAoBK,GAAqCG,IAAI,EAAE,EACjN,QAASA,EAAI,EAAGA,EAAIN,EAAE,KAAK,OAAS,EAAGM,IAAKR,EAAoBU,GAAsCF,IAAM,CAACN,EAAE,KAAK,EAAIM,EAAI,GAAIN,EAAE,KAAK,EAAIM,EAAI,GAAIR,EAAoBU,GAAsCF,IAAI,EAAE,EAGnN,QAASA,EAAI,EAAGA,EAAIN,EAAE,KAAK,OAAS,EAAGM,IAAKR,EAAoBW,GAAiCH,IAAM,CAACN,EAAE,KAAK,EAAIM,EAAI,GAAIN,EAAE,KAAK,EAAIM,EAAI,GAAIR,EAAoBW,GAAiCH,IAAI,EAAE,EAEzM,OAAOR,CACT,CCHA,IAAMY,GAAQ,CACZ,MAAO,CAAC,EACR,QAAS,OAAO,iBAChB,UAAW,CACb,EAEIC,GAA2B,KAC3BC,GAAY,EAEhB,eAAsBC,GAAQC,EAAeC,EAAuC,CAlCpF,IAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAoCE,IAAMC,KAAYX,EAAAD,EAAO,KAAK,WAAZ,YAAAC,EAAsB,WAAY,GAAMY,EAAI,EAAIlB,GAAM,UAClEmB,EAAYnB,GAAM,WAAWO,EAAAF,EAAO,KAAK,WAAZ,YAAAE,EAAsB,aAAc,GACnE,CAACF,EAAO,aAAe,CAACY,GAAY,CAACE,GAAanB,GAAM,MAAM,SAAW,GAC3EA,GAAM,MAAQ,MAAgBoB,GAAShB,EAAOC,CAAM,EACpDL,GAAM,UAAYkB,EAAI,EACtBlB,GAAM,QAAU,GAEhBA,GAAM,UAER,IAAMqB,EAA2B,CAAC,EAC5BC,EAA6B,CAAC,EAChCC,EAAK,EACT,QAASC,EAAI,EAAGA,EAAIxB,GAAM,MAAM,OAAQwB,IAAK,CAC3C,IAAMC,EAAMzB,GAAM,MAAMwB,GACpBE,EAAQ,EACRC,EACEC,EAAmB,CACvB,GAAIL,IACJ,KAAM,CAAC,EACP,QAAS,CAAC,EACV,IAAK,CAAC,EAAG,EAAG,EAAG,CAAC,EAChB,OAAQ,CAAC,EAAG,EAAG,EAAG,CAAC,EACnB,MAAO,EACP,SAAU,EACV,UAAW,EAGX,YAAa,CAAC,CAChB,EAIA,GADA,CAACG,EAAOC,EAAgBC,EAAK,MAAM,EAASC,IAAoBrB,EAAAH,EAAO,KAAK,WAAZ,YAAAG,EAAsB,SAAUiB,EAAKrB,GAAOK,EAAAJ,EAAO,KAAK,OAAZ,MAAAI,EAAkB,QAAUP,GAAsB4B,GAAK,CAAC,GAChKpB,EAAAL,GAAA,YAAAA,EAAQ,SAAR,MAAAK,EAAgB,aAAc,CAChC,IAAMqB,EAAY,MAAMC,GAAsBJ,EAAK,MAAgB,EAChE,UAAQA,EAAK,MAAM,EACtBA,EAAK,OAASG,CAChB,CAEA,GADAH,EAAK,SAAW,KAAK,MAAM,IAAMH,EAAI,UAAU,EAAI,KAC9Cd,EAAAN,EAAO,KAAK,OAAZ,MAAAM,EAAkB,QAYhB,GAAI,CAACV,GACNI,EAAO,OAAO4B,EAAI,wDAAwD,MACzE,CACL,IAAMC,EAAUjC,GAAM,QAAQ2B,EAAK,MAAgB,EAE7CO,EAAiB,MADHD,EAAQ,KAAME,GAAMA,EAAE,MAAMA,EAAE,MAAM,OAAS,KAAO,CAAC,EAChC,KAAK,EAG9C,GAFAR,EAAK,UAAY,KAAK,MAAM,IAAMO,EAAe,EAAE,EAAI,IAEnDP,EAAK,aAAahB,EAAAP,EAAO,KAAK,WAAZ,YAAAO,EAAsB,gBAAiB,IAE3D,GADAa,EAAI,WAAaG,EAAK,WAClBf,EAAAR,EAAO,KAAK,OAAZ,MAAAQ,EAAkB,YAAa,CACjCe,EAAK,IAAWS,GAASZ,EAAKrB,CAAK,EACnCwB,EAAK,OAAcU,GAAUb,EAAKrB,CAAK,EACvCwB,EAAK,MAAQA,EAAK,SAClBA,EAAK,KAAOH,EAAI,UAAU,IAAKc,GAAO,EAClCd,EAAI,WAAW,GAAKA,EAAI,SAAS,IAAO,GAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAMc,EAAG,GAAeT,GAAK,GAC5GL,EAAI,WAAW,GAAKA,EAAI,SAAS,IAAO,GAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAMc,EAAG,GAAeT,GAAK,CAChH,CAAC,EACDF,EAAK,QAAUA,EAAK,KAAK,IAAKW,GAAO,CAACA,EAAG,IAAMnC,EAAM,MAAM,IAAM,GAAImC,EAAG,IAAMnC,EAAM,MAAM,IAAM,IAAKmC,EAAG,IAAM,GAAKrC,EAAS,CAAC,EAC7H,QAAWsC,KAAO,OAAO,KAAYC,EAAkB,EACrDb,EAAK,YAAYY,GAAO,CAACZ,EAAK,KAAYa,GAAmBD,GAAe,CAEhF,MACK,CACL,IAAME,EAAQR,EAAQ,KAAME,GAAMA,EAAE,MAAMA,EAAE,MAAM,OAAS,KAAO,IAAI,EAChEO,EAAoB,UAAQD,EAAO,CAAC,GAAI,CAAC,CAAC,EAC5CE,EAAY,MAAMD,EAAe,MAAM,EACxC,UAAQA,CAAc,GACrB7B,EAAAT,EAAO,KAAK,YAAZ,MAAAS,EAAuB,QACzB8B,EAAY,MAAgBC,GAAQD,EAAWV,CAAO,GAC7CnB,EAAAV,EAAO,KAAK,OAAZ,MAAAU,EAAkB,UAC3B6B,EAAY,MAAWE,GAAYF,EAAWhB,EAAK,OAAQvB,EAAQH,EAAS,GAE9E0B,EAAK,KAAYmB,GAAmBH,EAAWnB,EAAKC,EAAOC,EAAgBzB,EAAS,EACpF0B,EAAK,QAAUA,EAAK,KAAK,IAAKW,GAAO,CAACA,EAAG,IAAMnC,EAAM,MAAM,IAAM,GAAImC,EAAG,IAAMnC,EAAM,MAAM,IAAM,IAAKmC,EAAG,IAAM,GAAKrC,EAAS,CAAC,EAC7H,QAAWsC,KAAO,OAAO,KAAYQ,EAAe,EAAGpB,EAAK,YAAYY,GAAcQ,GAAgBR,GAAK,IAAKS,IAAUrB,EAAK,KAAKqB,GAAM,EAC1IrB,EAAK,MAAQA,EAAK,UAClB,IAAMsB,GAAgB,CAAE,GAAQC,GAAiBvB,EAAK,KAAMH,CAAG,EAAG,WAAYA,EAAI,WAAY,UAAWA,EAAI,SAAU,EACvHG,EAAK,IAAWS,GAASa,GAAe9C,CAAK,EAC7CwB,EAAK,OAAcU,GAAUY,GAAe9C,CAAK,EAQjDkB,EAAS,KAAK4B,EAAa,CAC7B,CACG,UAAQhB,CAAO,CACpB,KA9DgC,CAC9BN,EAAK,IAAWS,GAASZ,EAAKrB,CAAK,EACnCwB,EAAK,OAAcU,GAAUb,EAAKrB,CAAK,EACvCwB,EAAK,MAAQA,EAAK,SAClBA,EAAK,KAAOH,EAAI,UAAU,IAAKc,GAAO,EAClCd,EAAI,WAAW,GAAKA,EAAI,SAAS,IAAO,GAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAMc,EAAG,GAAeT,GAAK,GAC5GL,EAAI,WAAW,GAAKA,EAAI,SAAS,IAAO,GAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAMc,EAAG,GAAeT,GAAK,CAChH,CAAC,EACDF,EAAK,QAAUA,EAAK,KAAK,IAAKW,GAAO,CAACA,EAAG,IAAMnC,EAAM,MAAM,IAAM,GAAImC,EAAG,IAAMnC,EAAM,MAAM,IAAM,IAAKmC,EAAG,IAAM,GAAKrC,EAAS,CAAC,EAC7H,QAAWsC,KAAO,OAAO,KAAYC,EAAkB,EACrDb,EAAK,YAAYY,GAAO,CAACZ,EAAK,KAAYa,GAAmBD,GAAe,CAEhF,CAmDIZ,EAAK,SAASZ,EAAAX,EAAO,KAAK,WAAZ,YAAAW,EAAsB,gBAAiB,GAAIK,EAAM,KAAKO,CAAI,EACpE,UAAQA,EAAK,MAAM,CAC7B,CACA,OAAA5B,GAAM,MAAQsB,EACPD,CACT,CAEA,eAAsB+B,GAAK/C,EAAqC,CAhJhE,IAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAiJE,OAAI0C,EAAI,UAASpD,GAAQ,QAErBM,GAAAD,EAAAD,GAAA,YAAAA,EAAQ,OAAR,YAAAC,EAAc,YAAd,YAAAC,EAAyB,WAAWN,IAAA,YAAAA,GAAO,YAEzC,OAAO,OAAKO,EAAAP,IAAA,YAAAA,GAAO,YAAP,YAAAO,EAAkB,UAAW,CAAC,CAAC,EAAE,OAAS,IAAGP,GAAQ,MAElEA,GAGMI,EAAO,OAChB4B,EAAI,gBAAiBhC,GAAM,QAAW,GAHlCQ,EAAAJ,EAAO,KAAK,YAAZ,MAAAI,EAAuB,QAASR,GAAQ,MAAMqD,GAAU5C,EAAAL,EAAO,KAAK,YAAZ,YAAAK,EAAuB,SAAS,EACvFT,GAAQ,MAAMqD,GAAU3C,EAAAN,EAAO,KAAK,OAAZ,YAAAM,EAAkB,SAAS,EAI1DT,GAAYD,GAAM,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EACxDA,EACT,CAEO,IAAMsD,GAAuBC,GACvBC,GAAeC,GC9I5B,IAAIC,GACEC,GAKD,CAAC,EAEFC,GAAW,EACXC,GAAY,EACZC,GAAU,OAAO,iBAErB,eAAsBC,GAAKC,EAAqC,CAhChE,IAAAC,EAiCE,OAAIC,EAAI,UAASR,GAAQ,MACpBA,GACIM,EAAO,OAAOG,EAAI,gBAAiBT,GAAM,QAAW,EADjDA,GAAQ,MAAMU,GAAUH,EAAAD,EAAO,KAAK,cAAZ,YAAAC,EAAyB,SAAS,EAE/DP,EACT,CAEO,SAASW,GAAQC,EAAe,CACrC,IAAMC,EAAUD,EAAM,OAASA,EAAM,QAAUA,EAC/C,GAAI,EAACZ,IAAA,MAAAA,GAAO,OAAO,GAAG,OAAO,OAAOa,EACpC,IAAMC,EAAU,QAAM,eAAeD,EAAQ,CAACb,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,EAAG,EAAK,EAClGe,EAAU,MAAID,EAAME,EAAU,KAAK,EACzC,OAAG,UAAQF,CAAI,EACRC,CAkBT,CAEA,eAAsBE,GAAQC,EAAeZ,EAAgBa,EAAaC,EAAiC,CAjE3G,IAAAb,EAAAc,EAAAC,EAAAC,EAkEE,GAAI,CAACvB,GAAO,MAAO,CAAE,IAAK,EAAG,OAAQ,UAAW,YAAa,EAAG,WAAY,CAAC,CAAE,EAC/E,IAAMwB,EAAYpB,MAAWG,EAAAD,EAAO,KAAK,cAAZ,YAAAC,EAAyB,aAAc,GAC9DkB,KAAYJ,EAAAf,EAAO,KAAK,cAAZ,YAAAe,EAAyB,WAAY,GAAMK,EAAI,EAAIxB,GACrE,OAAII,EAAO,aAAekB,GAAaC,GAAatB,KAAciB,KAAUE,EAAArB,GAAKkB,KAAL,YAAAG,EAAW,QAAQC,EAAAtB,GAAKkB,KAAL,YAAAI,EAAW,KAAM,GAC9GnB,KACOH,GAAKkB,KAEdf,GAAU,EACH,IAAI,QAAQ,MAAOuB,GAAY,CA1ExC,IAAApB,EAAAc,EA2EI,IAAMO,EAAM,CACV,IAAa,EACb,OAAgB,UAChB,YAAqB,EACrB,WAAsB,CAAC,CACzB,EAEA,IAAIrB,EAAAD,EAAO,KAAK,cAAZ,MAAAC,EAAyB,QAAS,CACpC,IAAMsB,EAAWlB,GAAQO,CAAK,EACxBY,EAAO9B,IAAA,YAAAA,GAAO,QAAQ6B,GAC5B3B,GAAWwB,EAAI,EACZ,UAAQG,CAAQ,EAEnB,IAAME,EAAS,MADC,MAAMD,EAAK,KAAME,GAAMA,EAAE,MAAM,KAAO,CAAC,GAC1B,KAAK,EAC5BC,EAAa,KAAK,MAAM,IAAM,KAAK,IAAKF,EAAO,GAAK,EAAI,CAAC,EAAI,IAC/DE,KAAcZ,EAAAf,EAAO,KAAK,cAAZ,YAAAe,EAAyB,gBAAiB,KAC1DO,EAAI,OAASG,EAAO,IAAM,GAAM,SAAW,OAC3CH,EAAI,YAAc,KAAK,IAAI,IAAMK,CAAU,GAE7C,IAAMC,EAAY,SAAOJ,EAAK,KAAME,GAAMA,EAAE,MAAM,KAAO,GAAG,EAAG,CAAC,EAC1DG,GAAO,MAAMD,EAAO,KAAK,GAAG,GAC/B,UAAQA,CAAM,EAEjB,IAAME,EAAM,MADCN,EAAK,KAAME,GAAMA,EAAE,MAAM,KAAO,GAAG,EACzB,KAAK,EAC5BJ,EAAI,IAAM,KAAK,MAAMQ,EAAID,EAAM,GAAKC,EAAID,EAAM,GAAK,GAAKA,EAAM,IAAMC,EAAID,EAAM,GAAK,GAAKA,EAAM,IAAMC,EAAID,EAAM,EAAE,EAAI,GAEpH,IAAME,EAAOP,EAAK,KAAME,GAAMA,EAAE,MAAM,KAAO,IAAI,EAG3CM,EAAaD,EAAO,MAAMA,EAAK,KAAK,EAAc,CAAC,EACzDT,EAAI,WAAa,MAAM,KAAKU,CAAU,EACtCR,EAAK,QAASE,GAAS,UAAQA,CAAC,CAAC,CACnC,CACA/B,GAAKkB,GAAOS,EACZzB,GAAYiB,EACZO,EAAQC,CAAG,CACb,CAAC,EACH,CC7GO,SAASW,GAAWC,EAAK,CAC9B,MAAO,CACL,KAAK,IAAIA,EAAI,SAAS,GAAKA,EAAI,WAAW,EAAE,EAC5C,KAAK,IAAIA,EAAI,SAAS,GAAKA,EAAI,WAAW,EAAE,CAC9C,CACF,CAEO,SAASC,GAAaD,EAAK,CAChC,MAAO,CACLA,EAAI,WAAW,IAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAM,EAC5DA,EAAI,WAAW,IAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAM,CAC9D,CACF,CAEO,SAASE,GAAyBF,EAAKG,EAAOC,EAAU,CAC7D,IAAMC,EAAIF,EAAM,MAAM,GAChBG,EAAIH,EAAM,MAAM,GAChBI,EAAQ,CAAC,CACbP,EAAI,WAAW,GAAKK,EACpBL,EAAI,WAAW,GAAKM,EACpBN,EAAI,SAAS,GAAKK,EAClBL,EAAI,SAAS,GAAKM,CACpB,CAAC,EACD,OAAU,QAAM,cAAcH,EAAOI,EAAO,CAAC,CAAC,EAAGH,CAAQ,CAC3D,CAEO,SAASI,GAAoBR,EAAKS,EAAQ,CAC/C,IAAMC,EAAa,CAACV,EAAI,WAAW,GAAKS,EAAO,GAAIT,EAAI,WAAW,GAAKS,EAAO,EAAE,EAC1EE,EAAW,CAACX,EAAI,SAAS,GAAKS,EAAO,GAAIT,EAAI,SAAS,GAAKS,EAAO,EAAE,EACpEG,EAAgBZ,EAAI,cAAc,IAAKa,GACvB,CAACA,EAAM,GAAKJ,EAAO,GAAII,EAAM,GAAKJ,EAAO,EAAE,CAEhE,EACD,MAAO,CAAE,WAAAC,EAAY,SAAAC,EAAU,cAAAC,EAAe,WAAYZ,EAAI,UAAW,CAC3E,CAEO,SAASc,GAAWd,EAAKS,EAAS,IAAK,CAC5C,IAAMM,EAASd,GAAaD,CAAG,EACzBgB,EAAOjB,GAAWC,CAAG,EACrBiB,EAAc,CAACR,EAASO,EAAK,GAAK,EAAGP,EAASO,EAAK,GAAK,CAAC,EACzDN,EAAa,CAACK,EAAO,GAAKE,EAAY,GAAIF,EAAO,GAAKE,EAAY,EAAE,EACpEN,EAAW,CAACI,EAAO,GAAKE,EAAY,GAAIF,EAAO,GAAKE,EAAY,EAAE,EACxE,MAAO,CAAE,WAAAP,EAAY,SAAAC,EAAU,cAAeX,EAAI,aAAc,CAClE,CAEO,SAASkB,GAAYlB,EAAK,CAC/B,IAAMmB,EAAUlB,GAAaD,CAAG,EAC1BgB,EAAOjB,GAAWC,CAAG,EAErBoB,EADU,KAAK,IAAI,GAAGJ,CAAI,EACL,EACrBN,EAAa,CAACS,EAAQ,GAAKC,EAAUD,EAAQ,GAAKC,CAAQ,EAC1DT,EAAW,CAACQ,EAAQ,GAAKC,EAAUD,EAAQ,GAAKC,CAAQ,EAC9D,MAAO,CAAE,WAAAV,EAAY,SAAAC,EAAU,cAAeX,EAAI,aAAc,CAClE,CAaO,SAASqB,GAAiBC,EAAO,CACtC,OAAOA,EAAQ,EAAI,KAAK,GAAK,KAAK,OAAOA,EAAQ,KAAK,KAAO,EAAI,KAAK,GAAG,CAC3E,CAEO,SAASC,GAAgBC,EAAQC,EAAQ,CAC9C,IAAMC,EAAU,KAAK,GAAK,EAAI,KAAK,MAAM,EAAED,EAAO,GAAKD,EAAO,IAAKC,EAAO,GAAKD,EAAO,EAAE,EACxF,OAAOH,GAAiBK,CAAO,CACjC,CAEO,IAAMC,GAAyB,CAACC,EAAGC,IAAM,CAAC,CAAC,EAAG,EAAGD,CAAC,EAAG,CAAC,EAAG,EAAGC,CAAC,EAAG,CAAC,EAAG,EAAG,CAAC,CAAC,EAEzE,SAASC,GAAIC,EAAIC,EAAI,CAC1B,IAAIC,EAAU,EACd,QAASC,EAAI,EAAGA,EAAIH,EAAG,OAAQG,IAC7BD,GAAWF,EAAGG,GAAKF,EAAGE,GAExB,OAAOD,CACT,CAEO,SAASE,GAAmBC,EAAKC,EAAa,CACnD,IAAMC,EAAwB,CAAC,EAC/B,QAASJ,EAAI,EAAGA,EAAIE,EAAI,OAAQF,IAC9BI,EAAO,KAAKF,EAAIF,GAAGG,EAAY,EAEjC,OAAOC,CACT,CAEO,SAASC,GAA0BC,EAAMC,EAAM,CACpD,IAAMR,EAA2B,CAAC,EAC5BS,EAAOF,EAAK,OAClB,QAASG,EAAM,EAAGA,EAAMD,EAAMC,IAAO,CACnCV,EAAQ,KAAK,CAAC,CAAC,EACf,QAASW,EAAM,EAAGA,EAAMF,EAAME,IAC5BX,EAAQU,GAAK,KAAKb,GAAIU,EAAKG,GAAMR,GAAmBM,EAAMG,CAAG,CAAC,CAAC,CAEnE,CACA,OAAOX,CACT,CAEO,SAASY,GAAoBC,EAAUC,EAAQ,CACpD,IAAMC,EAAO,KAAK,IAAIF,CAAQ,EACxBG,EAAO,KAAK,IAAIH,CAAQ,EACxBI,EAAiB,CAAC,CAACF,EAAM,CAACC,EAAM,CAAC,EAAG,CAACA,EAAMD,EAAM,CAAC,EAAG,CAAC,EAAG,EAAG,CAAC,CAAC,EAC9DG,EAAoBxB,GAAuBoB,EAAO,GAAIA,EAAO,EAAE,EAC/DK,EAA2Bb,GAA0BY,EAAmBD,CAAc,EACtFG,EAA4B1B,GAAuB,CAACoB,EAAO,GAAI,CAACA,EAAO,EAAE,EAC/E,OAAOR,GAA0Ba,EAA0BC,CAAyB,CACtF,CAEO,SAASC,GAAsBC,EAAQ,CAC5C,IAAMC,EAAoB,CAAC,CAACD,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,EAAG,CAACA,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,CAAC,EAC/EE,EAAuB,CAACF,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,EAClDG,EAAsB,CAC1B,CAAC5B,GAAI0B,EAAkB,GAAIC,CAAoB,EAC/C,CAAC3B,GAAI0B,EAAkB,GAAIC,CAAoB,CACjD,EACA,MAAO,CACLD,EAAkB,GAAG,OAAOE,EAAoB,EAAE,EAClDF,EAAkB,GAAG,OAAOE,EAAoB,EAAE,EAClD,CAAC,EAAG,EAAG,CAAC,CACV,CACF,CAEO,SAASC,GAAYC,EAAuBV,EAAgB,CACjE,MAAO,CACLpB,GAAI8B,EAAuBV,EAAe,EAAE,EAC5CpB,GAAI8B,EAAuBV,EAAe,EAAE,CAC9C,CACF,CCpIO,IAAMW,GAAU,CACrB,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,CACzB,EC13FO,IAAMC,GAAN,KAAmB,CAQxB,YAAYC,EAAO,CAPnBC,EAAA,cACAA,EAAA,gBACAA,EAAA,sBACAA,EAAA,kBACAA,EAAA,wBACAA,EAAA,8BAGE,KAAK,MAAQD,EACb,KAAK,QAAkBE,GAAQ,IAAKC,GAAW,CAACA,EAAO,EAAGA,EAAO,CAAC,CAAC,EACnE,KAAK,cAAmB,WAAS,KAAK,OAAO,EAC7C,KAAK,UAAa,KAAK,OAAS,KAAK,MAAM,QAAU,KAAK,MAAM,OAAO,GAAG,MAAS,KAAK,MAAM,OAAO,GAAG,MAAM,GAAK,EACnH,KAAK,gBAAqB,WAAS,CAAC,KAAK,UAAW,KAAK,SAAS,CAAC,EACnE,KAAK,sBAA2B,WAAS,CAAC,KAAK,UAAY,EAAG,KAAK,UAAY,CAAC,CAAC,CACnF,CAEA,eAAeC,EAAO,CACpB,IAAMC,EAA4B,CAAC,EACnCA,EAAE,WAAgB,QAAMD,EAAO,CAAC,EAAG,CAAC,EAAG,CAAC,GAAI,CAAC,CAAC,EAC9CC,EAAE,SAAc,QAAMD,EAAO,CAAC,EAAG,CAAC,EAAG,CAAC,GAAI,CAAC,CAAC,EAC5CC,EAAE,IAAS,MAAIA,EAAE,WAAY,KAAK,eAAe,EACjDA,EAAE,gBAAqB,MAAIA,EAAE,IAAK,KAAK,aAAa,EACpDA,EAAE,aAAkB,MAAIA,EAAE,SAAU,KAAK,qBAAqB,EAC9DA,EAAE,IAAS,MAAIA,EAAE,gBAAiBA,EAAE,YAAY,EAChDA,EAAE,YAAiB,MAAIA,EAAE,IAAK,KAAK,eAAe,EAClDA,EAAE,IAAS,MAAIA,EAAE,gBAAiBA,EAAE,YAAY,EAChDA,EAAE,UAAe,MAAIA,EAAE,IAAK,KAAK,eAAe,EAChD,IAAMC,EAAS,WAAS,CAACD,EAAE,YAAaA,EAAE,SAAS,EAAG,CAAC,EACvD,cAAO,KAAKA,CAAC,EAAE,QAASE,GAAc,UAAQF,EAAEE,EAAO,CAAC,EACjDD,CACT,CAEA,mBAAmBE,EAAkBC,EAAO,CAC1C,IAAMJ,EAA4B,CAAC,EACnCA,EAAE,QAAa,UAAQG,EAAkB,CAAC,GAAI,EAAG,CAAC,CAAC,EACnDH,EAAE,IAAS,MAAIA,EAAE,QAAS,KAAK,eAAe,EAC9CA,EAAE,UAAe,MAAIA,EAAE,IAAK,KAAK,QAAQI,EAAM,EAC/C,IAAMH,EAAS,MAAID,EAAE,UAAW,KAAK,eAAe,EACpD,cAAO,KAAKA,CAAC,EAAE,QAASE,GAAc,UAAQF,EAAEE,EAAO,CAAC,EACjDD,CACT,CAEA,MAAM,QAAQI,EAAOC,EAAuG,CAC1H,IAAMN,EAA4B,CAAC,EACnCA,EAAE,OAAY,QAAM,eAAeK,EAAO,CAAC,KAAK,UAAW,KAAK,SAAS,CAAC,EAC1EL,EAAE,IAAS,MAAIA,EAAE,OAAQO,EAAU,KAAK,EACxCP,EAAE,MAAW,MAAIA,EAAE,IAAKO,EAAU,GAAG,EACrCP,EAAE,QAAU,KAAK,MAAM,QAAQA,EAAE,KAAK,EACtCA,EAAE,YAAiB,UAAQA,EAAE,OAAO,EACpCA,EAAE,MAAW,QAAMA,EAAE,YAAa,CAAC,EAAG,CAAC,EAAG,CAAC,GAAI,CAAC,CAAC,EACjDA,EAAE,QAAa,UAAQA,EAAE,KAAK,EAC9BA,EAAE,OAAY,UAAQA,EAAE,OAAO,EAC/B,IAAMQ,EAAS,MAAMR,EAAE,OAAO,KAAK,EACnCA,EAAE,MAAW,QAAMA,EAAE,YAAa,CAAC,EAAG,CAAC,EAAG,CAAC,GAAI,CAAC,CAAC,EACjDA,EAAE,KAAO,KAAK,eAAeA,EAAE,KAAK,EAEpCA,EAAE,IAAM,MAAS,QAAM,uBAAuBA,EAAE,KAAMA,EAAE,OAAQ,EAAIM,EAAO,KAAK,YAAaA,EAAO,KAAK,aAAcA,EAAO,KAAK,aAAa,EAChJ,IAAMG,EAAM,MAAMT,EAAE,IAAI,MAAM,EACxBU,EAAmG,CAAC,EAC1G,QAAWN,KAASK,EAAK,CACvB,IAAME,EAA4B,CAAC,EACnCA,EAAE,IAAS,QAAMX,EAAE,KAAM,CAACI,EAAO,CAAC,EAAG,CAAC,EAAG,EAAE,CAAC,EAC5CO,EAAE,MAAW,QAAMX,EAAE,YAAa,CAACI,EAAO,CAAC,EAAG,CAAC,EAAG,EAAE,CAAC,EACrDO,EAAE,KAAO,KAAK,mBAAmBA,EAAE,MAAOP,CAAK,EAC/CO,EAAE,cAAmB,UAAQA,EAAE,KAAM,CAAC,GAAI,CAAC,CAAC,EAC5C,IAAMC,EAAM,MAAMD,EAAE,IAAI,KAAK,EACvBE,EAAaD,EAAI,MAAM,EAAG,CAAC,EAC3BE,EAAWF,EAAI,MAAM,EAAG,CAAC,EACzBG,EAAgB,MAAMJ,EAAE,cAAc,MAAM,EAC5CK,EAAO,CAAE,WAAAH,EAAY,SAAAC,EAAU,cAAAC,EAAe,WAAYP,EAAOJ,EAAO,EACxEa,EAAcC,GAAoBF,EAAM,CAACX,EAAM,MAAM,GAAK,KAAK,UAAWA,EAAM,MAAM,GAAK,KAAK,SAAS,CAAC,EAChHK,EAAM,KAAKO,CAAM,EACjB,OAAO,KAAKN,CAAC,EAAE,QAAST,GAAc,UAAQS,EAAET,EAAO,CAAC,CAC1D,CACA,cAAO,KAAKF,CAAC,EAAE,QAASE,GAAc,UAAQF,EAAEE,EAAO,CAAC,EACjDQ,CACT,CACF,EC5EA,IAAMS,GAAuB,EACvBC,GAAuB,KACvBC,GAAkB,CAAC,EAAG,EAAG,EAAG,GAAI,GAAI,EAAG,CAAC,EACxCC,GAAwB,EACxBC,GAAgC,EAClCC,GAAW,EAEFC,GAAN,KAAmB,CAQxB,YAAYC,EAAcC,EAAe,CAPzCC,EAAA,qBACAA,EAAA,sBACAA,EAAA,kBACAA,EAAA,oBACAA,EAAA,gBACAA,EAAA,sBAGE,KAAK,aAAeF,EACpB,KAAK,cAAgBC,EACrB,KAAK,UAAY,KAAK,eAAiB,KAAK,cAAc,OAAO,GAAG,MAAQ,KAAK,cAAc,OAAO,GAAG,MAAM,GAAK,EACpH,KAAK,YAAc,CAAC,EACpB,KAAK,QAAU,OAAO,iBACtB,KAAK,cAAgB,CACvB,CAGA,8BAA8BE,EAAW,CACvC,IAAMC,EAAKD,EAAU,IAAKE,GAAMA,EAAE,EAAE,EAC9BC,EAAKH,EAAU,IAAKE,GAAMA,EAAE,EAAE,EAC9BE,EAAa,CAAC,KAAK,IAAI,GAAGH,CAAE,EAAG,KAAK,IAAI,GAAGE,CAAE,CAAC,EAC9CE,EAAW,CAAC,KAAK,IAAI,GAAGJ,CAAE,EAAG,KAAK,IAAI,GAAGE,CAAE,CAAC,EAClD,MAAO,CAAE,WAAAC,EAAY,SAAAC,CAAS,CAChC,CAEA,uBAAuBC,EAAeC,EAAgB,CACpD,IAAMC,EAAuBF,EAAc,IAAKG,GAAeC,GAAY,CAAC,GAAGD,EAAO,CAAC,EAAGF,CAAc,CAAC,EACnGI,EAAgB,KAAK,8BAA8BH,CAAoB,EAC7E,OAAYI,GAAgBC,GAAYF,CAAa,EAAGrB,EAAoB,CAC9E,CAEA,uBAAuBU,EAAW,CAChC,IAAMc,EAAc,KAAK,8BAA8Bd,CAAS,EAC1De,EAAqBH,GAAgBC,GAAYC,CAAW,EAAGvB,EAAoB,EACzFwB,EAAc,cAAgB,CAAC,EAC/B,QAASC,EAAI,EAAGA,EAAIxB,GAAgB,OAAQwB,IAC1CD,EAAc,cAAc,KAAKf,EAAUR,GAAgBwB,IAAI,MAAM,EAAG,CAAC,CAAC,EAE5E,OAAOD,CACT,CAEA,mBAAmBE,EAAWC,EAAMC,EAAOZ,EAAgB,CACzD,IAAMa,EAAeC,GAAWH,CAAI,EAC9BI,EAAc,CAACF,EAAQ,GAAK,KAAK,UAAWA,EAAQ,GAAK,KAAK,WAAYA,EAAQ,GAAKA,EAAQ,IAAM,KAAK,UAAY,CAAC,EACvHG,EAAeN,EAAU,IAAKR,GAAU,CAC5Ca,EAAY,IAAMb,EAAM,GAAK,KAAK,UAAY,GAC9Ca,EAAY,IAAMb,EAAM,GAAK,KAAK,UAAY,GAC9Ca,EAAY,GAAKb,EAAM,EACzB,CAAC,EACKe,EAA4BC,GAAoBN,EAAO,CAAC,EAAG,CAAC,CAAC,EAC7DO,EAAgBH,EAAa,IAAKd,GAE/B,CAAC,GADaC,GAAYD,EAAOe,CAAoB,EACxCf,EAAM,EAAE,CAC7B,EACKkB,EAA6BC,GAAsBrB,CAAc,EACjEsB,EAAY,CAAC,GAAQC,GAAaZ,CAAI,EAAG,CAAC,EAC1Ca,EAAoB,CACnBC,GAAIH,EAAWF,EAAsB,EAAE,EACvCK,GAAIH,EAAWF,EAAsB,EAAE,CAC9C,EACA,OAAOD,EAAc,IAAKjB,GAAU,CAClC,KAAK,MAAMA,EAAM,GAAKsB,EAAkB,EAAE,EAC1C,KAAK,MAAMtB,EAAM,GAAKsB,EAAkB,EAAE,EAC1C,KAAK,MAAMtB,EAAM,EAAE,CACrB,CAAC,CACH,CAEA,MAAM,cAAcwB,EAAOC,EAAQ,CACjC,IAAIC,EAAc,GAGdC,EACEC,GAAYH,EAAO,KAAK,UAAY,GAAMI,EAAI,EAAI3C,GAClD4C,EAAY,KAAK,SAAWL,EAAO,KAAK,YAAc,GACxDA,EAAO,aAAeG,GAAYE,IACpCH,EAAQ,MAAM,KAAK,aAAa,QAAQH,EAAOC,CAAM,EACrD,KAAK,QAAU,GAEbA,EAAO,aAAa,KAAK,UAGzBE,GAAUA,EAAM,OAAS,IAAQA,EAAM,SAAW,KAAK,eAAmB,KAAK,gBAAkBF,EAAO,KAAK,aAAgB,CAACA,EAAO,KAAK,aAC5I,KAAK,cAAgB,EACrB,KAAK,YAAc,CAAC,GAAGE,CAAK,EAExB,KAAK,YAAY,OAAS,IAAGD,EAAc,KAEjD,IAAMK,EAAyJ,CAAC,EAGhK,QAASxB,EAAI,EAAGA,EAAI,KAAK,YAAY,OAAQA,IAAK,CAChD,IAAMyB,EAAa,KAAK,YAAYzB,GACpC,GAAI,EAACyB,EACL,GAAIP,EAAO,KAAK,UAAW,CACzB,IAAMf,EAAQe,EAAO,KAAK,SAAgBQ,GAAgBD,EAAW,cAAchD,IAAwBgD,EAAW,cAAc/C,GAA8B,EAAI,EAChKiD,EAAkBb,GAAaW,CAAU,EACzCG,EAAuB,CAACD,EAAW,GAAKV,EAAM,MAAM,GAAIU,EAAW,GAAKV,EAAM,MAAM,EAAE,EACtFY,EAAeX,EAAO,KAAK,UAAYY,EAAI,QAAQ,SAAS,kBAAkB,EAAO,QAAM,iBAAiBb,EAAOd,EAAO,EAAGyB,CAAoB,EAAIX,EAAM,MAAM,EACjK1B,EAAsBkB,GAAoB,CAACN,EAAOwB,CAAU,EAC5DI,EAASZ,EAAc,KAAK,uBAAuBM,EAAW,cAAelC,CAAc,EAAIkC,EAC/FO,EAAoBC,GAAyBF,EAAQF,EAAc,CAAC,KAAK,UAAW,KAAK,SAAS,CAAC,EACnGK,EAAe,MAAIF,EAAcG,EAAU,KAAK,EACnD,UAAQH,CAAY,EACpB,UAAQH,CAAY,EACvB,GAAM,CAACO,EAAaC,CAAS,EAAI,KAAK,cAAc,QAAQH,CAAS,EACrEvD,GAAW2C,EAAI,EACZ,UAAQY,CAAS,EACpB,IAAMI,GAAc,MAAMF,EAAY,KAAK,GAAG,GAE9C,GADG,UAAQA,CAAW,EAClBE,GAAcpB,EAAO,KAAK,cAAgB,EAAG,CAC/C,IAAMqB,EAAuB,UAAQF,EAAW,CAAC,GAAI,CAAC,CAAC,EACjDpC,EAAY,MAAMsC,EAAkB,MAAM,EAC7C,UAAQF,CAAS,EACjB,UAAQE,CAAiB,EAC5B,IAAMC,EAAS,KAAK,mBAAmBvC,EAAW8B,EAAQ5B,EAAOZ,CAAc,EACzEkD,EAAkB,KAAK,uBAAuBD,CAAM,EAC1D,KAAK,YAAYxC,GAAK,CAAE,GAAGyC,EAAiB,WAAAH,CAAW,EACvD,IAAMI,EAAS,CACb,UAAWF,EACX,WAAAF,EACA,cAAeb,EAAW,WAC1B,iBAAkBa,EAClB,IAAK,CAAE,QAASG,EAAgB,WAAY,YAAaA,EAAgB,QAAS,CACpF,EACAjB,EAAM,KAAKkB,CAAM,CACnB,MACE,KAAK,YAAY1C,GAAK,KAErB,UAAQqC,CAAS,CACtB,KAAO,CAEL,IAAMM,EAAgB/C,GAAgBC,GAAY4B,CAAU,EAAGlD,EAAoB,EAC7EmE,EAAS,CACb,WAAYjB,EAAW,WACvB,cAAeA,EAAW,WAC1B,iBAAkB,EAClB,IAAK,CAAE,QAASkB,EAAS,WAAY,YAAaA,EAAS,QAAS,EACpE,UAAW,CAAC,CACd,EACAnB,EAAM,KAAKkB,CAAM,CACnB,CACF,CACA,YAAK,YAAc,KAAK,YAAY,OAAQE,GAAMA,IAAM,IAAI,EAC5D,KAAK,cAAgBpB,EAAM,OACvBA,EAAM,OAASN,EAAO,KAAK,cAAaM,EAAM,OAASN,EAAO,KAAK,aAChEM,CACT,CACF,ECpKO,IAAMqB,GAAS,CACpB,MAAO,EACP,MAAO,EACP,OAAQ,EACR,KAAM,EACN,MAAO,EACP,IAAK,CAAC,EAAG,EAAG,EAAG,EAAG,CAAC,EACnB,YAAa,CAAE,EAAG,QAAS,EAAG,QAAS,EAAG,SAAU,EAAG,OAAQ,EAAG,OAAQ,EAQ1E,cAAe,CACb,EAAG,CAAC,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,CAAC,EAClC,EAAG,CAAC,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,CAAC,EAClC,EAAG,CAAC,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,CAAC,EACvC,EAAG,CAAC,CAAC,EAAG,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,CAAC,EACzC,EAAG,CAAC,CAAC,EAAG,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,CAAC,CAC3C,EACA,QAAUC,GAAUD,GAAO,YAAYC,GACvC,UAAYA,GAAUD,GAAO,cAAcC,EAC7C,EAEaC,GAAa,CACxB,KAAM,EACN,KAAM,EACN,KAAM,EACN,YAAa,CAAE,EAAG,OAAQ,EAAG,OAAQ,EAAG,MAAO,EAC/C,QAAUD,GAAUC,GAAW,YAAYD,EAC7C,EAEaE,EAAkB,CAC7B,WAAY,EACZ,aAAc,EACd,eAAgB,EAChB,gBAAiB,EACjB,gBAAiB,EACjB,eAAgB,EAChB,kBAAmB,EACnB,iBAAkB,EAClB,YAAa,CAAE,EAAG,aAAc,EAAG,eAAgB,EAAG,iBAAkB,EAAG,kBAAmB,EAAG,kBAAmB,EAAG,iBAAkB,EAAG,oBAAqB,EAAG,kBAAmB,EACvL,QAAUF,GAAUE,EAAgB,YAAYF,EAClD,EAEaG,GAAN,KAAoB,CAOzB,YAAYC,EAAM,CANlBC,EAAA,aACAA,EAAA,cACAA,EAAA,mBACAA,EAAA,gBACAA,EAAA,wBAIE,KAAK,KAAOD,EACZ,KAAK,MAAQ,CAAC,EACd,KAAK,WAAa,CAAC,EACnB,KAAK,QAAU,CAAC,EAAK,EAAK,EAAK,EAAK,CAAG,EACvC,KAAK,gBAAkB,CAAC,EAAK,EAAK,EAAK,EAAK,CAAG,CACjD,CAEA,KAAKE,EAAQC,EAAMC,EAAY,CACzB,OAAO,KAAK,MAAMF,IAAY,cAAa,KAAK,MAAMA,GAAU,CAAC,GACrE,KAAK,MAAMA,GAAQ,KAAK,CAACC,EAAMC,CAAU,CAAC,CAC5C,CAEA,UAAUF,EAAQG,EAAUD,EAAY,CACjC,KAAK,WAAWF,KAAS,KAAK,WAAWA,GAAU,CAAC,GACzD,KAAK,WAAWA,GAAQ,KAAK,CAACG,EAAUD,CAAU,CAAC,CACrD,CAEA,OAAOF,EAAQI,EAAQ,CACrB,KAAK,QAAQJ,GAAUI,EAEvB,IAAMC,EAAQ,KAAK,QAAQ,OAAO,CAACC,EAAGC,IAAMD,EAAIC,EAAG,CAAC,EACpD,KAAK,gBAAkB,KAAK,QAAQ,IAAKC,GAAOA,EAAK,EAAIH,CAAK,CAChE,CAEA,aAAaI,EAAeC,EAAoB,CAC9C,IAAIR,EAAa,EAGjB,QAAWS,KAAaF,EAAe,CACrC,IAAMG,EAAeH,EAAcE,GAC7BE,EAAgB,KAAK,MAAMF,GACjC,GAAI,OAAOE,GAAkB,YAAa,CAGxCX,GAAc,KAAK,gBAAgBS,GACnC,QACF,CAEA,OAAW,CAACG,EAAcC,CAAK,IAAKF,EAClC,GAAID,IAAiBE,EAAc,CACjCZ,GAAca,EAAQ,KAAK,gBAAgBJ,GAC3C,KACF,CAEJ,CAEA,QAAWA,KAAaD,EAAoB,CAC1C,IAAMM,EAAoBN,EAAmBC,GACvCM,EAAqB,KAAK,WAAWN,GAC3C,GAAI,OAAOM,GAAuB,YAAa,CAG7Cf,GAAc,KAAK,gBAAgBS,GACnC,QACF,CAEA,OAAW,CAACO,EAAmBH,CAAK,IAAKE,EACvC,GAAID,IAAsBE,EAAmB,CAC3ChB,GAAca,EAAQ,KAAK,gBAAgBJ,GAC3C,KACF,CAEJ,CACA,OAAOT,EAAa,EACtB,CACF,ECtHO,GAAM,CAAE,MAAAiB,GAAO,MAAAC,GAAO,OAAAC,GAAQ,KAAAC,GAAM,MAAAC,EAAM,EAAIC,GAExC,CAAE,KAAAC,GAAM,KAAAC,GAAM,KAAAC,EAAK,EAAIC,GAEvB,CAAE,WAAAC,GAAY,aAAAC,GAAc,eAAAC,GAAgB,gBAAAC,GAAiB,gBAAAC,GAAiB,eAAAC,GAAgB,kBAAAC,GAAmB,iBAAAC,EAAiB,EAAIC,EAG7IC,GAAW,IAAIC,GAAc,WAAW,EAC9CD,GAAS,KAAKnB,GAAOM,GAAM,CAAG,EAC9Ba,GAAS,UAAUnB,GAAOU,GAAY,CAAG,EACzCS,GAAS,UAAUnB,GAAOe,GAAgB,GAAI,EAC9CI,GAAS,UAAUnB,GAAOc,GAAiB,GAAI,EAC/C,QAAWO,IAAU,CAAChB,GAAO,MAAOA,GAAO,OAAQA,GAAO,KAAMA,GAAO,KAAK,EAC1Ec,GAAS,KAAKE,EAAQb,GAAM,CAAG,EAC/BW,GAAS,UAAUE,EAAQT,GAAgB,CAAG,EAC9CO,GAAS,UAAUE,EAAQR,GAAiB,CAAG,EAIjD,IAAMS,GAAU,IAAIF,GAAc,SAAS,EAC3CE,GAAQ,KAAKtB,GAAOO,GAAM,EAAG,EAC7Be,GAAQ,KAAKtB,GAAOM,GAAM,EAAG,EAC7BgB,GAAQ,UAAUtB,GAAOU,GAAY,CAAG,EACxCY,GAAQ,UAAUtB,GAAOe,GAAgB,CAAG,EAC5CO,GAAQ,KAAKrB,GAAOK,GAAM,CAAG,EAC7BgB,GAAQ,UAAUrB,GAAOS,GAAY,GAAI,EACzCY,GAAQ,UAAUrB,GAAOc,GAAgB,CAAG,EAC5CO,GAAQ,KAAKpB,GAAQI,GAAM,CAAG,EAC9BgB,GAAQ,UAAUpB,GAAQQ,GAAY,CAAG,EACzCY,GAAQ,UAAUpB,GAAQa,GAAgB,GAAI,EAC9CO,GAAQ,KAAKnB,GAAMK,GAAM,CAAG,EAC5Bc,GAAQ,UAAUnB,GAAMO,GAAY,EAAG,EACvCY,GAAQ,UAAUnB,GAAMY,GAAgB,CAAG,EAC3CO,GAAQ,UAAUnB,GAAMS,GAAgB,EAAG,EAC3CU,GAAQ,KAAKlB,GAAOI,GAAM,CAAG,EAC7Bc,GAAQ,UAAUlB,GAAOM,GAAY,EAAG,EACxCY,GAAQ,UAAUlB,GAAOW,GAAgB,CAAG,EAC5CO,GAAQ,UAAUlB,GAAOQ,GAAgB,EAAG,EAC5CU,GAAQ,OAAOrB,GAAO,CAAC,EACvBqB,GAAQ,OAAOpB,GAAQ,CAAC,EAGxB,IAAMqB,GAAQ,IAAIH,GAAc,OAAO,EACvCG,GAAM,KAAKvB,GAAOQ,GAAM,CAAG,EAC3Be,GAAM,KAAKtB,GAAOK,GAAM,EAAG,EAC3BiB,GAAM,KAAKrB,GAAQM,GAAM,EAAG,EAC5Be,GAAM,KAAKpB,GAAMK,GAAM,EAAG,EAC1Be,GAAM,KAAKnB,GAAOI,GAAM,EAAG,EAC3Be,GAAM,OAAOtB,GAAO,CAAC,EACrBsB,GAAM,OAAOrB,GAAQ,CAAC,EAGtB,IAAMsB,GAAe,IAAIJ,GAAc,eAAe,EACtDI,GAAa,KAAKxB,GAAOM,GAAM,CAAG,EAClCkB,GAAa,KAAKvB,GAAOO,GAAM,EAAG,EAClCgB,GAAa,KAAKtB,GAAQM,GAAM,EAAG,EACnCgB,GAAa,KAAKrB,GAAMK,GAAM,EAAG,EACjCgB,GAAa,KAAKpB,GAAOI,GAAM,EAAG,EAClCgB,GAAa,OAAOvB,GAAO,CAAC,EAC5BuB,GAAa,OAAOtB,GAAQ,CAAC,EAG7B,IAAMuB,GAAW,IAAIL,GAAc,WAAW,EAC9CK,GAAS,KAAKzB,GAAOM,GAAM,GAAI,EAC/BmB,GAAS,KAAKxB,GAAOK,GAAM,GAAI,EAC/BmB,GAAS,KAAKvB,GAAQI,GAAM,GAAI,EAChCmB,GAAS,KAAKtB,GAAMG,GAAM,GAAI,EAC9BmB,GAAS,KAAKrB,GAAOE,GAAM,GAAI,EAE/B,IAAOoB,GAAQ,CAACP,GAAUG,GAASC,GAAOC,GAAcC,EAAQ,ECpEhE,IAAME,GAAgB,GAChBC,GAAU,CAEd,sBAAuB,GACvB,oBAAqB,IAErB,oBAAqB,IACrB,wBAAyB,GACzB,uBAAwB,GAC1B,EAEA,SAASC,GAAeC,EAASC,EAASC,EAASC,EAAS,CAC1D,IAAMC,GAASH,EAAUE,IAAYH,EAAUE,GAC3CG,EAAQ,KAAK,KAAKD,CAAK,EAAI,IAAM,KAAK,GAC1C,OAAIC,GAAS,EAAGA,EAAQ,CAACA,EAChBA,EAAQ,IAAGA,EAAQ,IAAMA,GAC3BA,CACT,CAIA,SAASC,GAAUC,EAAQC,EAAQ,CACjC,GAAI,CAACD,GAAU,CAACC,EAAQ,MAAO,CAAC,EAAG,CAAC,EACpC,IAAMC,EAAUV,GAAeQ,EAAO,GAAIA,EAAO,GAAIC,EAAO,GAAIA,EAAO,EAAE,EACzE,GAAID,EAAO,SAAW,EAAG,OAAOE,EAChC,IAAMC,EAAUX,GAAeQ,EAAO,GAAIA,EAAO,GAAIC,EAAO,GAAIA,EAAO,EAAE,EACzE,MAAO,CAACC,EAASC,CAAO,CAC1B,CAEA,SAASC,GAAmBC,EAAOC,EAAc,EAAK,CACpD,IAAIC,EAAa,EACbC,EAAa,EACbC,EAAe,EACnB,OAAIJ,GAAS,IAAQA,GAAS,IAAOE,EAAa,EAAID,EAC7CD,GAAS,IAAQA,GAAS,IAAOG,EAAa,EAAIF,EACtDG,EAAe,EAAIH,EACjB,CAACC,EAAYC,EAAYC,CAAY,CAC9C,CAEA,SAASC,GAAmBC,EAAYC,EAAUC,EAAU,CAC1D,IAAMC,EAAmBH,EAAW,GAAKC,EAAS,GAC5CG,EAAmBJ,EAAW,GAAKE,EAAS,GAC5CG,EAAiBJ,EAAS,GAAKC,EAAS,GACxCI,EAAmBN,EAAW,GAAKC,EAAS,GAC5CM,EAAmBP,EAAW,GAAKE,EAAS,GAC5CM,EAAiBP,EAAS,GAAKC,EAAS,GACxCO,EAAmBT,EAAW,GAAKC,EAAS,GAC5CS,EAAmBV,EAAW,GAAKE,EAAS,GAC5CS,EAAiBV,EAAS,GAAKC,EAAS,GACxCU,EAAiB,KAAK,KAAKT,EAAmBA,EAAmBG,EAAmBA,EAAmBG,EAAmBA,CAAgB,EAC1II,EAAiB,KAAK,KAAKT,EAAmBA,EAAmBG,EAAmBA,EAAmBG,EAAmBA,CAAgB,EAC1II,EAAe,KAAK,KAAKT,EAAiBA,EAAiBG,EAAiBA,EAAiBG,EAAiBA,CAAc,EAC9HI,GAAUD,EAAeA,EAAeF,EAAiBA,EAAiBC,EAAiBA,IAAmB,EAAIC,EAAeF,GACjIG,EAAS,EAAKA,EAAS,EAClBA,EAAS,KAAMA,EAAS,IACjC,IAAIC,EAAe,KAAK,KAAKD,CAAM,EACnCC,EAAgB,QAAUA,EAAgB,IAC1C,IAAIC,EACJ,OAAID,EAAepC,GAAQ,oBAAqBqC,EAAaC,GAAW,KAC/DF,EAAepC,GAAQ,sBAAuBqC,EAAaC,GAAW,KAC1ED,EAAaC,GAAW,KACtBD,CACT,CAEA,SAASE,GAA4Bf,EAAkBD,EAAkBE,EAAgBe,EAAY,CACnG,IAAIC,EACJ,OAAID,IAAe,KAAK,IAAIhB,CAAgB,EACtCA,EAAmB,EAAGiB,EAAqBC,EAAgB,eAC1DD,EAAqBC,EAAgB,gBACjCF,IAAe,KAAK,IAAIjB,CAAgB,EAC7CA,EAAmB,EAAGkB,EAAqBC,EAAgB,eAC1DD,EAAqBC,EAAgB,gBAEtCjB,EAAiB,EAAGgB,EAAqBC,EAAgB,eACxDD,EAAqBC,EAAgB,gBAErCD,CACT,CAEA,SAASE,GAA0BhB,EAAkBD,EAAkBE,EAAgBgB,EAAY,CACjG,IAAIH,EACJ,OAAIG,IAAe,KAAK,IAAIjB,CAAgB,EACtCA,EAAmB,EAAGc,EAAqBC,EAAgB,aAC1DD,EAAqBC,EAAgB,WACjCE,IAAe,KAAK,IAAIlB,CAAgB,EAC7CA,EAAmB,EAAGe,EAAqBC,EAAgB,aAC1DD,EAAqBC,EAAgB,WAEtCd,EAAiB,EAAGa,EAAqBC,EAAgB,aACxDD,EAAqBC,EAAgB,WAErCD,CACT,CAEA,SAASI,GAA0BlB,EAAkBD,EAAkBE,EAAgBgB,EAAYpB,EAAkBD,EAAkBE,EAAgBe,EAAY,CACjK,IAAIC,EACEK,EAA0BH,GAA0BhB,EAAkBD,EAAkBE,EAAgBgB,CAAU,EAClHG,EAA4BR,GAA4Bf,EAAkBD,EAAkBE,EAAgBe,CAAU,EAC5H,OAAIM,IAA4BJ,EAAgB,WAC1CK,IAA8BL,EAAgB,eAAgBD,EAAqBC,EAAgB,eAClGD,EAAqBC,EAAgB,gBAEtCK,IAA8BL,EAAgB,eAAgBD,EAAqBC,EAAgB,iBAClGD,EAAqBC,EAAgB,kBAErCD,CACT,CAEA,SAASO,GAAyB5B,EAAYC,EAAUC,EAAU2B,EAAc,CAC9E,IAAM1B,EAAmBH,EAAW,GAAKC,EAAS,GAC5CG,EAAmBJ,EAAW,GAAKE,EAAS,GAC5CG,EAAiBJ,EAAS,GAAKC,EAAS,GACxCI,EAAmBN,EAAW,GAAKC,EAAS,GAC5CM,EAAmBP,EAAW,GAAKE,EAAS,GAC5CM,EAAiBP,EAAS,GAAKC,EAAS,GACxCkB,EAAa,KAAK,IAAI,KAAK,IAAIjB,CAAgB,EAAG,KAAK,IAAIC,CAAgB,EAAG,KAAK,IAAIC,CAAc,CAAC,EACtGmB,EAAa,KAAK,IAAI,KAAK,IAAIlB,CAAgB,EAAG,KAAK,IAAIC,CAAgB,EAAG,KAAK,IAAIC,CAAc,CAAC,EACxGsB,EAAe,EACfC,EAAe,EACfC,EAAiB,EACfC,EAA2BT,GAAcJ,EAAa,MACxDa,EAA2B,IAAKH,GAAgBlD,GAAQ,oBACnDqD,EAA2B,IAAMF,GAAgBnD,GAAQ,oBAC7DoD,GAAkBpD,GAAQ,oBAC/B,IAAMgC,EAAiB,KAAK,KAAKT,EAAmBA,EAAmBG,EAAmBA,CAAgB,EACpGO,EAAiB,KAAK,KAAKT,EAAmBA,EAAmBG,EAAmBA,CAAgB,EACpGO,EAAe,KAAK,KAAKT,EAAiBA,EAAiBG,EAAiBA,CAAc,EAC1F0B,EAAW,KAAK,IAAItB,EAAgBC,EAAgBC,CAAY,EAClEqB,EAAqBnC,EAAW,GAChCoC,EAAqBpC,EAAW,GAChCqC,EAAmBnC,EAAS,GAC5BoC,EAAmBpC,EAAS,GAC5BgC,IAAatB,GACfyB,EAAmBnC,EAAS,GAC5BoC,EAAmBpC,EAAS,IACnBgC,IAAapB,IACtBqB,EAAqBlC,EAAS,GAC9BmC,EAAqBnC,EAAS,IAIhC,IAAMsC,EAAanD,GAFI,CAAC+C,EAAoBC,CAAkB,EACzC,CAACC,EAAkBC,CAAgB,CACC,EACnDE,EAAQ/C,GAAmB8C,EAAY3D,GAAQ,sBAAsB,EAC3EkD,GAAgBU,EAAM,GACtBT,GAAgBS,EAAM,GACtBR,GAAkBQ,EAAM,GACxB,QAAWC,MAAeZ,EAAc,CACtC,IAAMa,EAAcjD,GAAmBgD,GAAa7D,GAAQ,uBAAuB,EACnFkD,GAAgBY,EAAY,GAC5BX,GAAgBW,EAAY,GAC5BV,GAAkBU,EAAY,EAChC,CAGA,IAAIrB,EACJ,OAAIS,IAAiB,KAAK,IAAIA,EAAcC,EAAcC,CAAc,EACtEX,EAAqBE,GAA0BhB,EAAkBD,EAAkBE,EAAgBgB,CAAU,EACpGQ,IAAmB,KAAK,IAAID,EAAcC,CAAc,EACjEX,EAAqBF,GAA4Bf,EAAkBD,EAAkBE,EAAgBe,CAAU,EAE/GC,EAAqBI,GAA0BlB,EAAkBD,EAAkBE,EAAgBgB,EAAYpB,EAAkBD,EAAkBE,EAAgBe,CAAU,EAExKC,CACT,CAEA,SAASsB,GAASC,EAAW,CAE3B,IAAMC,EAA4B,CAAC,EAC7BC,EAA4B,CAAC,EAC7BC,EAA6B,CAAC,EAC9BC,EAAkC,CAAC,EACzC,GAAI,CAACJ,EAAW,MAAO,CAAE,MAAOG,EAAa,WAAYC,CAAiB,EAG1E,QAAWC,KAAUC,GAAO,IAAK,CAC/B,IAAMC,EAASD,GAAO,UAAUD,CAAM,EAChCG,EAA2B,CAAC,EAC5BC,EAA2B,CAAC,EAClC,QAAWC,KAASH,EAAQ,CAC1B,IAAM9D,EAASuD,EAAUU,EAAM,IACzBhE,EAASsD,EAAUU,EAAM,IAEzBC,EAASnE,GAAUC,EAAQC,CAAM,EACjCC,EAAUgE,EAAO,GACjB/D,EAAU+D,EAAO,GACvBH,EAAU,KAAK7D,CAAO,EACtB8D,EAAU,KAAK7D,CAAO,CACxB,CACAqD,EAAS,KAAKO,CAAS,EACvBN,EAAS,KAAKO,CAAS,CACzB,CAGA,QAAWJ,KAAUC,GAAO,IAAK,CAE/B,IAAMM,EAAgBP,IAAWC,GAAO,MAAS,EAAI,EAC/CO,EAAiBP,GAAO,UAAUD,CAAM,EACxCjD,EAAa4C,EAAUa,EAAeD,GAAc,IACpDvD,EAAW2C,EAAUa,EAAeD,EAAe,GAAG,IACtDtD,EAAW0C,EAAUa,EAAe,GAAG,IAEvCC,EAAe3D,GAAmBC,EAAYC,EAAUC,CAAQ,EAChEyD,EAAiB/B,GAAyB5B,EAAYC,EAAUC,EAAU2C,EAASI,GAAQ,MAAMO,CAAY,CAAC,EACpHT,EAAYE,GAAUS,EACtBV,EAAiBC,GAAUU,CAC7B,CACA,MAAO,CAAE,MAAOZ,EAAa,WAAYC,CAAiB,CAC5D,CAEO,SAASY,GAAQC,EAAW,CACjC,GAAI,CAACA,GAAaA,EAAU,SAAW,EAAG,OAAO,KACjD,IAAMC,EAAenB,GAASkB,CAAS,EACjCjB,EAAY,CAAC,EACnB,QAAWmB,KAAab,GAAO,IAC7BN,EAAUM,GAAO,QAAQa,CAAS,GAAK,CACrC,KAAM7C,GAAW,QAAQ4C,EAAa,MAAMC,EAAU,EACtD,UAAWzC,EAAgB,QAAQwC,EAAa,WAAWC,EAAU,CACvE,EAEF,OAAOnB,CACT,CAEO,SAASoB,GAAMH,EAAW,CAC/B,IAAMI,EAAqD,CAAC,EAC5D,GAAI,CAACJ,GAAaA,EAAU,SAAW,EAAG,OAAOI,EACjD,IAAMH,EAAenB,GAASkB,CAAS,EACvC,QAAWK,KAAWC,GAAU,CAC9B,IAAMC,EAAaF,EAAQ,aAAaJ,EAAa,MAAOA,EAAa,UAAU,EAC/EM,GAAczF,IAAesF,EAAM,KAAK,CAAE,KAAMC,EAAQ,KAAM,WAAAE,CAAW,CAAC,CAChF,CACA,OAAOH,CACT,CChOA,IAAMI,GAAkB,CACtB,MAAO,CAAC,EAAG,EAAG,EAAG,CAAC,EAClB,MAAO,CAAC,EAAG,EAAG,EAAG,CAAC,EAClB,OAAQ,CAAC,EAAG,GAAI,GAAI,EAAE,EACtB,KAAM,CAAC,GAAI,GAAI,GAAI,EAAE,EACrB,MAAO,CAAC,GAAI,GAAI,GAAI,EAAE,EACtB,KAAM,CAAC,CAAC,CACV,EAEIC,GACAC,GACAC,GAEJ,eAAsBC,GAAQC,EAAeC,EAAuC,CAClF,IAAMC,EAAc,MAAMJ,GAAa,cAAcE,EAAOC,CAAM,EAClE,GAAI,CAACC,EAAa,MAAO,CAAC,EAC1B,IAAMC,EAA2B,CAAC,EAClC,QAASC,EAAI,EAAGA,EAAIF,EAAY,OAAQE,IAAK,CAC3C,IAAMC,EAAc,CAAC,EACrB,GAAIH,EAAYE,GAAG,UACjB,QAAWE,KAAO,OAAO,KAAKX,EAAe,EAC3CU,EAAYC,GAAOX,GAAgBW,GAAK,IAAKC,GAAUL,EAAYE,GAAG,UAAUG,EAAM,EAG1F,IAAMC,EAAYN,EAAYE,GAAG,UAC7BK,EAAW,CAAC,OAAO,iBAAkB,OAAO,iBAAkB,EAAG,CAAC,EAClEC,EAAc,CAAC,EAAG,EAAG,EAAG,CAAC,EAC7B,GAAIF,GAAaA,EAAU,OAAS,EAAG,CACrC,QAAWG,KAAMH,EACXG,EAAG,GAAKF,EAAI,KAAIA,EAAI,GAAKE,EAAG,IAC5BA,EAAG,GAAKF,EAAI,KAAIA,EAAI,GAAKE,EAAG,IAC5BA,EAAG,GAAKF,EAAI,KAAIA,EAAI,GAAKE,EAAG,IAC5BA,EAAG,GAAKF,EAAI,KAAIA,EAAI,GAAKE,EAAG,IAElCF,EAAI,IAAMA,EAAI,GACdA,EAAI,IAAMA,EAAI,GACdC,EAAS,CAACD,EAAI,IAAMT,EAAM,MAAM,IAAM,GAAIS,EAAI,IAAMT,EAAM,MAAM,IAAM,GAAIS,EAAI,IAAMT,EAAM,MAAM,IAAM,GAAIS,EAAI,IAAMT,EAAM,MAAM,IAAM,EAAE,CAC1I,MACES,EAAMP,EAAYE,GAAG,IAAM,CACzB,KAAK,MAAM,KAAK,IAAI,EAAGF,EAAYE,GAAG,IAAI,QAAQ,EAAE,CAAC,EACrD,KAAK,MAAM,KAAK,IAAI,EAAGF,EAAYE,GAAG,IAAI,QAAQ,EAAE,CAAC,EACrD,KAAK,MAAM,KAAK,IAAKJ,EAAM,MAAM,IAAM,EAAIE,EAAYE,GAAG,IAAI,YAAY,EAAE,EAAI,KAAK,IAAI,EAAGF,EAAYE,GAAG,IAAI,QAAQ,EAAE,CAAC,EAC1H,KAAK,MAAM,KAAK,IAAKJ,EAAM,MAAM,IAAM,EAAIE,EAAYE,GAAG,IAAI,YAAY,EAAE,EAAI,KAAK,IAAI,EAAGF,EAAYE,GAAG,IAAI,QAAQ,EAAE,CAAC,CAC5H,EAAI,CAAC,EAAG,EAAG,EAAG,CAAC,EACfM,EAAS,CACNR,EAAYE,GAAG,IAAI,QAAQ,IAAOJ,EAAM,MAAM,IAAM,GACpDE,EAAYE,GAAG,IAAI,QAAQ,IAAOJ,EAAM,MAAM,IAAM,IACpDE,EAAYE,GAAG,IAAI,YAAY,GAAKF,EAAYE,GAAG,IAAI,QAAQ,KAAOJ,EAAM,MAAM,IAAM,IACxFE,EAAYE,GAAG,IAAI,YAAY,GAAKF,EAAYE,GAAG,IAAI,QAAQ,KAAOJ,EAAM,MAAM,IAAM,EAC3F,EAEF,IAAMY,EAAuBC,GAAQL,CAAS,EAC9CL,EAAM,KAAK,CACT,GAAIC,EACJ,MAAO,KAAK,MAAM,IAAMF,EAAYE,GAAG,UAAU,EAAI,IACrD,SAAU,KAAK,MAAM,IAAMF,EAAYE,GAAG,aAAa,EAAI,IAC3D,YAAa,KAAK,MAAM,IAAMF,EAAYE,GAAG,gBAAgB,EAAI,IACjE,MAAO,OACP,IAAAK,EACA,OAAAC,EACA,UAAAF,EACA,YAAaH,EACb,UAAWO,CACb,CAAC,CACH,CACA,OAAOT,CACT,CAEA,eAAsBW,GAAKb,EAAiE,CApF5F,IAAAc,EAAAC,EAqFMC,EAAI,UACNrB,GAAoB,KACpBC,GAAgB,MAEd,CAACD,IAAqB,CAACC,GACzB,CAACD,GAAmBC,EAAa,EAAI,MAAM,QAAQ,IAAI,CACrDI,EAAO,KAAK,QAAUiB,GAAUH,EAAAd,EAAO,KAAK,WAAZ,YAAAc,EAAsB,SAAS,EAAI,KACnEd,EAAO,KAAK,UAAYiB,GAAUF,EAAAf,EAAO,KAAK,WAAZ,YAAAe,EAAsB,SAAS,EAAI,IACvE,CAAC,GAEGf,EAAO,OAAOkB,EAAI,gBAAiBvB,GAAkB,QAAW,EAChEK,EAAO,OAAOkB,EAAI,gBAAiBtB,GAAc,QAAW,GAElE,IAAMuB,EAAe,IAAiBC,GAAazB,EAAiB,EACpE,OAAAE,GAAe,IAAiBwB,GAAaF,EAAcvB,EAAa,EACjE,CAACD,GAAmBC,EAAa,CAC1C,CCjFA,IAAM0B,GAAiD,CAAC,KAAM,IAAI,EAC5DC,GAAmB,CAAC,8CAA+C,oDAAoD,EAEvHC,GAAY,CAAC,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,CAAC,EAE3BC,GAAU,CAAC,OAAQ,OAAQ,QAAS,QAAS,OAAQ,MAAO,UAAU,EACtEC,GAAY,EAEZC,GAAgB,IAChBC,GAAwB,IACxBC,GAAqB,IAEvBC,GAAU,OAAO,iBACjBC,GAAW,EACXC,GAA+B,CAAC,EAAG,CAAC,EAUlCC,EAGF,CACF,MAAO,CAAC,EACR,MAAO,CAAC,CACV,EAEMC,GAAY,CAShB,MAAO,CAAC,EAAG,EAAG,EAAG,CAAC,EAClB,MAAO,CAAC,EAAG,EAAG,EAAG,CAAC,EAClB,OAAQ,CAAC,EAAG,GAAI,GAAI,EAAE,EACtB,KAAM,CAAC,GAAI,GAAI,GAAI,EAAE,EACrB,MAAO,CAAC,GAAI,GAAI,GAAI,EAAE,EACtB,KAAM,CAAC,CAAC,EACR,KAAM,CAAC,EAAG,GAAI,GAAI,EAAG,EAAG,EAAG,CAAC,CAC9B,EAEA,eAAsBC,GAAWC,EAAqC,CAtEtE,IAAAC,EAyEE,GADIC,EAAI,UAAShB,GAAO,GAAK,MACxBA,GAAO,GAQDc,EAAO,OAAOG,EAAI,gBAAiBjB,GAAO,GAAG,QAAW,MARnD,CAGdkB,GAAQ,CAAC,oBAAqB,QAAS,uBAAwB,QAAS,WAAY,SAAU,OAAQ,kBAAmB,gBAAiB,oBAAqB,oBAAqB,aAAc,QAAS,QAAS,OAAO,EAAGJ,CAAM,EACpOd,GAAO,GAAK,MAAMmB,GAAUJ,EAAAD,EAAO,KAAK,WAAZ,YAAAC,EAAsB,SAAS,EAC3D,IAAMK,EAAS,OAAO,OAAOpB,GAAO,GAAG,eAAe,MAAS,EAC/DE,GAAU,GAAG,GAAK,MAAM,QAAQkB,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,EACxFlB,GAAU,GAAG,GAAK,MAAM,QAAQkB,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,CAC1F,CACA,OAAOpB,GAAO,EAChB,CAEA,eAAsBqB,GAAaP,EAAqC,CArFxE,IAAAC,EAuFE,GADIC,EAAI,UAAShB,GAAO,GAAK,MACxBA,GAAO,GAKDc,EAAO,OAAOG,EAAI,gBAAiBjB,GAAO,GAAG,QAAW,MALnD,CACdA,GAAO,GAAK,MAAMmB,GAAUJ,EAAAD,EAAO,KAAK,WAAZ,YAAAC,EAAsB,SAAS,EAC3D,IAAMK,EAAS,OAAO,OAAOpB,GAAO,GAAG,eAAe,MAAS,EAC/DE,GAAU,GAAG,GAAK,MAAM,QAAQkB,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,EACxFlB,GAAU,GAAG,GAAK,MAAM,QAAQkB,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,CAC1F,CACA,OAAOpB,GAAO,EAChB,CAQA,eAAesB,GAAYC,EAAeC,EAA6C,CACrF,IAAMC,EAA4B,CAAC,EACnC,GAAI,CAACF,GAAS,CAACG,GAAO,GAAI,OAAOD,EACjC,IAAME,EAA4B,CAAC,EAC7BC,GAASL,EAAM,MAAM,IAAM,IAAMA,EAAM,MAAM,IAAM,GACnDM,EAAS,KAAK,IAAI,KAAK,OAAON,EAAM,MAAM,IAAM,GAAK,CAAC,EAAI,EAAGO,EAAqB,EAClFC,EAAQ,KAAK,MAAMF,EAASD,EAAQ,CAAC,EAAI,EAC/CD,EAAE,OAAY,QAAM,eAAeJ,EAAO,CAACM,EAAQE,CAAK,CAAC,EACzDJ,EAAE,KAAU,OAAKA,EAAE,OAAQ,OAAO,EAClC,CAACA,EAAE,UAAWA,EAAE,QAAQ,EAAI,MAAMD,GAAO,GAAG,aAAaC,EAAE,KAAMK,EAAgB,EACjFL,EAAE,MAAW,UAAQA,EAAE,SAAU,CAAC,EAAG,CAAC,CAAC,EACvCA,EAAE,OAAY,UAAQA,EAAE,UAAW,CAAC,CAAC,CAAC,EACtC,IAAMM,EAAgC,UAAQN,EAAE,OAAQ,CAAC,EACtD,UAAQM,EAAYC,GAAU,EACjCD,EAAY,OAAOC,GAAW,CAAC,EAC/BP,EAAE,SAAc,QAAMM,EAAa,CAAC,EACjC,UAAQA,CAAW,EAEtBN,EAAE,IAAS,MAAIA,EAAE,SAAU,CAAC,EAC5BA,EAAE,OAAY,SAAOA,EAAE,SAAU,CAAC,EAClC,IAAIQ,EAAK,EACTR,EAAE,IAAM,MAAS,QAAM,uBAAuBA,EAAE,MAAOA,EAAE,KAAMH,EAAO,KAAK,aAAe,GAAK,EAAGA,EAAO,KAAK,cAAgB,EAAGA,EAAO,KAAK,eAAiB,CAAC,EAC/J,IAAMY,EAAM,MAAMT,EAAE,IAAI,KAAK,EACvBU,EAAS,MAAMV,EAAE,IAAI,KAAK,EAC1BW,EAAW,MAAMX,EAAE,OAAO,KAAK,EACrC,QAAWY,KAAY,MAAM,KAAKH,CAAG,EAAG,CACtC,IAAMI,EAAc,QAAMb,EAAE,MAAOY,EAAU,CAAC,EACxCE,EAAQ,MAAMD,EAAS,KAAK,EAC/B,UAAQA,CAAQ,EACnB,IAAME,EAAe,CAACD,EAAM,GAAIA,EAAM,GAAIA,EAAM,GAAKA,EAAM,GAAIA,EAAM,GAAKA,EAAM,EAAE,EAC5EE,EAAkBC,GAAMF,EAASG,EAAkB,EACnDC,EAAe,CAAC,KAAK,MAAMJ,EAAQ,GAAKK,GAAW,EAAE,EAAG,KAAK,MAAML,EAAQ,GAAKK,GAAW,EAAE,EAAG,KAAK,MAAML,EAAQ,GAAKK,GAAW,EAAE,EAAG,KAAK,MAAML,EAAQ,GAAKK,GAAW,EAAE,CAAC,EAC9KC,EAAQX,EAAOE,GACfU,EAAQC,GAAQZ,EAASC,IACzBY,EAAyB,CAAE,GAAIhB,IAAM,MAAAa,EAAO,IAAKF,EAAS,OAAAH,EAAQ,MAAAM,CAAM,EAC9ExB,EAAM,KAAK0B,CAAI,CACjB,CACA,cAAO,KAAKxB,CAAC,EAAE,QAASyB,GAAc,UAAQzB,EAAEyB,EAAO,CAAC,EACxD3B,EAAM,KAAK,CAAC4B,EAAGC,IAAMA,EAAE,MAAQD,EAAE,KAAK,EAClC5B,EAAM,QAAUD,EAAO,KAAK,aAAe,KAAIC,EAAM,OAAUD,EAAO,KAAK,aAAe,GACvFC,CACT,CAEA,eAAe8B,GAAchC,EAAeiC,EAAqBhC,EAAqC,CACpG,IAAM2B,EAAmB,CACvB,GAAIK,EAAE,GACN,MAAO,KAAK,MAAM,IAAMA,EAAE,KAAK,EAAI,IACnC,SAAU,KAAK,MAAM,IAAMA,EAAE,KAAK,EAAI,IACtC,YAAa,EACb,IAAKA,EAAE,IACP,OAAQA,EAAE,OACV,MAAOA,EAAE,MACT,UAAW,CAAC,EACZ,UAAW,CAAC,EACZ,YAAa,CAAC,CAChB,EACA,GAAIjC,GAASG,GAAO,IAAMF,EAAO,KAAK,WAAagC,EAAE,OAAShC,EAAO,KAAK,eAAiB,GAAI,CAC7F,IAAMG,EAA4B,CAAC,EAC7B8B,EAAU,CAACD,EAAE,OAAO,GAAIA,EAAE,OAAO,GAAIA,EAAE,OAAO,GAAKA,EAAE,OAAO,GAAIA,EAAE,OAAO,GAAKA,EAAE,OAAO,EAAE,EAC/F7B,EAAE,KAAU,QAAM,cAAcJ,EAAO,CAACkC,CAAO,EAAG,CAAC,CAAC,EAAG,CAACC,GAAU,GAAG,GAAIA,GAAU,GAAG,EAAE,EAAG,UAAU,EACrG/B,EAAE,IAAS,MAAIA,EAAE,KAAMgC,EAAU,KAAK,EACtC,CAAChC,EAAE,MAAOA,EAAE,SAAS,EAAID,GAAO,GAAG,QAAQC,EAAE,IAAK,CAAC,aAAc,UAAU,CAAC,EAC5E,IAAMiC,GAAY,MAAMjC,EAAE,MAAM,KAAK,GAAG,GAClCqB,GAAS,IAAM,KAAK,MAAM,KAAO,EAAI,KAAK,IAAIY,CAAQ,EAAE,GAAK,IACnE,GAAIZ,IAAUxB,EAAO,KAAK,eAAiB,GAAI,CAC7C2B,EAAK,YAAcH,EACnBrB,EAAE,SAAc,UAAQA,EAAE,UAAW,CAAC,GAAI,CAAC,CAAC,EAG5C,IAAMkC,GAFsB,MAAMlC,EAAE,SAAS,MAAM,GACb,IAAKmC,GAAQ,CAACA,EAAI,GAAKJ,GAAU,GAAG,GAAII,EAAI,GAAKJ,GAAU,GAAG,GAAKI,EAAI,IAAM,CAAE,CAAC,EAChF,IAAKA,GAAQ,CAACA,EAAI,GAAKN,EAAE,OAAO,GAAIM,EAAI,GAAKN,EAAE,OAAO,GAAKM,EAAI,IAAM,CAAE,CAAC,EAC9GX,EAAK,UAAaU,EAAY,IAAKC,GAAQ,CAACf,GAAW,IAAMe,EAAI,GAAKN,EAAE,OAAO,IAAKT,GAAW,IAAMe,EAAI,GAAKN,EAAE,OAAO,IAAMM,EAAI,IAAM,CAAE,CAAC,EAC1IX,EAAK,UAAuBY,GAAQZ,EAAK,SAAS,EAClD,QAAWa,KAAO,OAAO,KAAKC,EAAS,EACrCd,EAAK,YAAYa,GAAOC,GAAUD,GAAK,IAAKE,GAAmBf,EAAK,WAAaA,EAAK,UAAUe,GAASf,EAAK,UAAUe,GAAS,IAAK,CAE1I,CACA,OAAO,KAAKvC,CAAC,EAAE,QAASyB,GAAc,UAAQzB,EAAEyB,EAAO,CAAC,CAC1D,CACA,OAAOD,CACT,CAEA,eAAsBgB,GAAQ5C,EAAeC,EAAuC,CAvLpF,IAAA4C,EAAAC,EAwLE,GAAI,CAAC3C,GAAO,IAAM,CAACA,GAAO,IAAM,GAAC0C,EAAA1C,GAAO,KAAP,MAAA0C,EAAW,OAAO,GAAG,QAAS,GAACC,EAAA3C,GAAO,KAAP,MAAA2C,EAAW,OAAO,GAAG,OAAO,MAAO,CAAC,EACpGtB,GAAa,CAACxB,EAAM,MAAM,IAAM,EAAGA,EAAM,MAAM,IAAM,CAAC,EACtD+C,KACA,IAAMC,GAAY/C,EAAO,KAAK,UAAY,GAAMgD,EAAI,EAAIC,GAClDC,EAAYJ,IAAW9C,EAAO,KAAK,YAAc,GACvD,OAAIA,EAAO,aAAe+C,GAAYG,EAC7BC,EAAM,MAER,IAAI,QAAQ,MAAOC,GAAY,CACpC,IAAMC,EAAmB,GAAKrD,EAAO,KAAK,UAAY,GAAMgD,EAAI,EAAIC,GAC9DK,EAAoBR,GAAU,GAAK9C,EAAO,KAAK,YAAc,GAC/DA,EAAO,aAAemD,EAAM,MAAM,SAAWnD,EAAO,KAAK,YAC3DmD,EAAM,MAAQ,MAAM,QAAQ,IAAIA,EAAM,MAAM,IAAKI,GAAYxB,GAAchC,EAAOwD,EAASvD,CAAM,CAAC,CAAC,EAC1FA,EAAO,aAAeqD,GAAoBC,GAAqBH,EAAM,MAAM,OAAS,EAC7FA,EAAM,MAAQ,MAAM,QAAQ,IAAIA,EAAM,MAAM,IAAKI,GAAYxB,GAAchC,EAAOwD,EAASvD,CAAM,CAAC,CAAC,GAEnGmD,EAAM,MAAQ,MAAMrD,GAAYC,EAAOC,CAAM,EAC7CiD,GAAWD,EAAI,EACfG,EAAM,MAAQ,MAAM,QAAQ,IAAIA,EAAM,MAAM,IAAKI,GAAYxB,GAAchC,EAAOwD,EAASvD,CAAM,CAAC,CAAC,EACnG8C,GAAU,GAGZ,IAAMU,EAAW,CAAC,GAAGL,EAAM,KAAK,EAEhC,GADAA,EAAM,MAAM,OAAS,EACjBnD,EAAO,iBAAmB,EAC5B,QAASyD,EAAI,EAAGA,EAAIN,EAAM,MAAM,OAAQM,IAAK,CAC3C,IAAMC,EAAaC,GAAOR,EAAM,MAAMM,GAAG,UAAWlC,EAAU,EAC9D,GAAImC,EAAO,IAAI,IAAM3D,EAAM,MAAM,IAAM,GAAK,KAAQ2D,EAAO,IAAI,IAAM3D,EAAM,MAAM,IAAM,GAAK,KAAQoD,EAAM,MAAMM,GAAG,aAAeN,EAAM,MAAMM,GAAG,aAAezD,EAAO,KAAK,eAAiB,GAAI,CAC/L,IAAM4D,EAAexC,GAAMsC,EAAO,IAAKG,EAAa,EAC9CC,EAAkB1C,GAAMsC,EAAO,OAAQG,EAAa,EAE1DV,EAAM,MAAM,KAAK,CAAE,GAAGK,EAASC,GAAI,IAAKG,EAAU,OAAQE,CAAY,CAAC,CACzE,CACF,CAEF,QAASL,EAAI,EAAGA,EAAIN,EAAM,MAAM,OAAQM,IAAK,CAC3C,IAAMM,EAAWC,GAAKb,EAAM,MAAMM,GAAG,UAAWlC,EAAU,EAC1D4B,EAAM,MAAMM,GAAG,IAAMM,EAAK,IAC1BZ,EAAM,MAAMM,GAAG,OAASM,EAAK,MAC/B,CACAX,EAAQD,EAAM,KAAK,CACrB,CAAC,CACH,CCvNA,IAAIc,GACEC,GAAwB,CAAC,EAC3BC,GAAU,OAAO,iBACjBC,GAAY,EACZC,GAAW,EAEf,eAAsBC,GAAKC,EAAqC,CAjBhE,IAAAC,EAkBE,OAAIC,EAAI,UAASR,GAAQ,MACpBA,GACIM,EAAO,OAAOG,EAAI,gBAAiBT,GAAM,QAAW,EADjDA,GAAQ,MAAMU,GAAUH,EAAAD,EAAO,KAAK,WAAZ,YAAAC,EAAsB,SAAS,EAE5DP,EACT,CAEA,eAAsBW,GAAQC,EAAeN,EAAgBO,EAAaC,EAAgC,CAxB1G,IAAAP,EAAAQ,EAyBE,GAAI,CAACf,GAAO,MAAO,GACnB,IAAMgB,KAAYT,EAAAD,EAAO,KAAK,WAAZ,YAAAC,EAAsB,WAAY,GAAMU,EAAI,EAAIb,GAC5Dc,EAAYhB,MAAWa,EAAAT,EAAO,KAAK,WAAZ,YAAAS,EAAsB,aAAc,GACjE,OAAIT,EAAO,aAAeU,GAAYE,GAAcf,KAAcW,GAAUb,GAAOY,IACjFX,KACOD,GAAOY,KAEhBX,GAAU,EACH,IAAI,QAAQ,MAAOiB,GAAY,CACpC,IAAMC,EAAY,QAAM,eAAeR,EAAO,CAACZ,IAAA,MAAAA,GAAO,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EAAGA,IAAA,MAAAA,GAAO,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,CAAC,EAAG,EAAK,EAC7JqB,EAAMrB,IAAA,YAAAA,GAAO,QAAQoB,GACrBE,GAAO,MAAMD,EAAI,KAAK,GAAG,GAC/BpB,GAAOY,GAAO,KAAK,MAAM,IAAMS,CAAG,EAAI,IACtCnB,GAAYW,EACZV,GAAWa,EAAI,EACZ,UAAQ,CAACG,EAAQC,CAAG,CAAC,EACxBF,EAAQlB,GAAOY,EAAI,CACrB,CAAC,EACH,CC3CA,IAAAU,GAAA,GAAAC,GAAAD,GAAA,eAAAE,GAAA,eAAAC,GAAA,QAAAC,GAAA,aAAAC,GAAA,aAAAC,KAAO,IAAMF,GAAqB,CAChC,OACA,UACA,WACA,UACA,WACA,eACA,gBACA,YACA,aACA,YACA,aACA,UACA,WACA,WACA,YACA,YACA,YACF,EAEaD,GAA8B,CACzC,CAAC,UAAW,UAAU,EACtB,CAAC,UAAW,UAAU,EACtB,CAAC,eAAgB,eAAe,EAChC,CAAC,YAAa,YAAY,EAC1B,CAAC,YAAa,YAAY,EAC1B,CAAC,UAAW,UAAU,EACtB,CAAC,WAAY,WAAW,EACxB,CAAC,YAAa,YAAY,CAC5B,EAEaG,GAA4B,CACvC,CAAC,WAAY,cAAc,EAC3B,CAAC,YAAa,eAAe,EAC7B,CAAC,YAAa,UAAU,EACxB,CAAC,aAAc,WAAW,CAC5B,EAEaD,GAA8B,CACzC,CAAC,CAAC,UAAW,UAAU,EAAG,CAAC,eAAgB,eAAe,CAAC,EAC3D,CAAC,CAAC,YAAa,YAAY,EAAG,CAAC,eAAgB,eAAe,CAAC,CACjE,EAEaH,GAAsC,CACjD,QAAS,CAAC,UAAW,WAAY,WAAW,EAC5C,SAAU,CAAC,WAAY,YAAa,YAAY,EAChD,MAAO,CAAC,eAAgB,gBAAiB,WAAY,UAAW,cAAc,EAC9E,QAAS,CAAC,eAAgB,YAAa,WAAW,EAClD,SAAU,CAAC,gBAAiB,aAAc,YAAY,EACtD,KAAM,CAAC,CACT,EC5CA,IAAMK,GAAY,KAEZC,GAGF,CACF,UAAW,CAAC,EACZ,QAAS,CAAC,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,CAAC,CAC1C,EAEO,SAASC,GAAUC,EAAkB,CAC1C,QAAWC,KAAeC,GAAY,CACpC,IAAMC,EAAOH,EAAK,UAAU,UAAWI,GAAOA,EAAG,OAASH,EAAK,EAAE,EAC3DI,EAAQL,EAAK,UAAU,UAAWI,GAAOA,EAAG,OAASH,EAAK,EAAE,EAClE,GAAID,EAAK,UAAUG,IAASH,EAAK,UAAUK,IACrCL,EAAK,UAAUG,GAAM,SAAS,GAAKH,EAAK,UAAUK,GAAO,SAAS,GAAI,CACxE,IAAMC,EAAMN,EAAK,UAAUG,GAC3BH,EAAK,UAAUG,GAAQH,EAAK,UAAUK,GACtCL,EAAK,UAAUK,GAASC,CAC1B,CAEJ,CACA,QAAWL,KAAeM,GAAU,CAClC,IAAMC,EAAQR,EAAK,UAAU,UAAWI,GAAQA,GAAMA,EAAG,OAASH,EAAK,EAAG,EACpEQ,EAAST,EAAK,UAAU,UAAWI,GAAQA,GAAMA,EAAG,OAASH,EAAK,EAAG,EACvED,EAAK,UAAUQ,IAAUR,EAAK,UAAUS,IACtCT,EAAK,UAAUQ,GAAO,SAAS,GAAKR,EAAK,UAAUS,GAAQ,SAAS,IACtET,EAAK,UAAU,OAAOQ,EAAO,CAAC,CAGpC,CACA,OAAW,CAACP,EAAMS,CAAO,IAAYC,GAAU,CAC7C,IAAMR,EAAOH,EAAK,UAAU,UAAWI,GAAQA,GAAMA,EAAG,OAASH,EAAK,EAAG,EACnEI,EAAQL,EAAK,UAAU,UAAWI,GAAQA,GAAMA,EAAG,OAASH,EAAK,EAAG,EACpEW,EAASZ,EAAK,UAAU,UAAWI,GAAQA,GAAMA,EAAG,OAASM,EAAQ,EAAG,EACxEG,EAAUb,EAAK,UAAU,UAAWI,GAAQA,GAAMA,EAAG,OAASM,EAAQ,EAAG,EAC/E,GAAI,CAACV,EAAK,UAAUY,IAAW,CAACZ,EAAK,UAAUa,GAAU,SACzD,IAAMC,EAAed,EAAK,UAAUG,GAAQ,CAC1C,KAAK,IAAIH,EAAK,UAAUY,GAAQ,SAAS,GAAKZ,EAAK,UAAUG,GAAM,SAAS,EAAE,EAC9E,KAAK,IAAIH,EAAK,UAAUa,GAAS,SAAS,GAAKb,EAAK,UAAUG,GAAM,SAAS,EAAE,CACjF,EAAI,CAAC,EAAG,CAAC,EACHY,EAAgBf,EAAK,UAAUK,GAAS,CAC5C,KAAK,IAAIL,EAAK,UAAUa,GAAS,SAAS,GAAKb,EAAK,UAAUK,GAAO,SAAS,EAAE,EAChF,KAAK,IAAIL,EAAK,UAAUY,GAAQ,SAAS,GAAKZ,EAAK,UAAUK,GAAO,SAAS,EAAE,CACjF,EAAI,CAAC,EAAG,CAAC,EACT,GAAIS,EAAa,GAAKA,EAAa,IAAMC,EAAc,GAAKA,EAAc,GAAI,CAC5E,IAAMT,EAAMN,EAAK,UAAUG,GAC3BH,EAAK,UAAUG,GAAQH,EAAK,UAAUK,GACtCL,EAAK,UAAUK,GAASC,CAC1B,CACF,CACF,CAEO,SAASU,GAAOC,EAAqD,CAC1E,QAASC,EAAI,EAAGA,EAAID,EAAU,OAAQC,IACpC,GAAID,EAAUC,IAAMpB,GAAM,UAAUoB,GAAI,CACtC,IAAMC,EAAO,CAAC,KAAK,IAAIF,EAAUC,GAAG,YAAY,GAAKpB,GAAM,UAAUoB,GAAG,YAAY,EAAE,EAAG,KAAK,IAAID,EAAUC,GAAG,YAAY,GAAKpB,GAAM,UAAUoB,GAAG,YAAY,EAAE,CAAC,EAC9JC,EAAK,GAAKtB,IAAasB,EAAK,GAAKtB,GACnCoB,EAAUC,GAAKpB,GAAM,UAAUoB,GAE/BpB,GAAM,UAAUoB,GAAKD,EAAUC,EAEnC,MACEpB,GAAM,UAAUoB,GAAKD,EAAUC,GAGnC,OAAOD,CACT,CAEO,SAASG,GAASC,EAAeC,EAA2B,CACjE,IAAMC,EAA4B,CAAC,EACnC,GAAI,CAACF,EAAM,OAAS,CAACA,EAAM,MAAM,IAAM,CAACA,EAAM,MAAM,GAAI,OAAOA,EAC/DvB,GAAM,QAAU,CACd,CAAC,EAAG,CAAC,EACL,CAACuB,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,EAAGA,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,CAAC,EACjL,CAACA,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,EAAGA,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,CAAC,EACjL,CAAC,EAAG,CAAC,CACP,EACAE,EAAE,IAAS,MAAIF,EAAOvB,GAAM,OAAO,EACnCyB,EAAE,OAAY,QAAM,eAAeA,EAAE,IAAK,CAACD,EAAWA,CAAS,CAAC,EAChE,IAAME,EAAW,OAAKD,EAAE,OAAQ,OAAO,EACvC,cAAO,KAAKA,CAAC,EAAE,QAASE,GAAc,UAAQF,EAAEE,EAAO,CAAC,EACjDD,CACT,CAEO,SAASE,GAAY1B,EAAkB2B,EAA0C,CACtF3B,EAAK,UAAYA,EAAK,UAAU,OAAQ4B,GAAQA,GAAOA,EAAI,QAAQ,EACnE,QAAWA,KAAO5B,EAAK,UACrB4B,EAAI,SAAW,CACbA,EAAI,SAAS,IAAMD,EAAW,GAAK7B,GAAM,QAAQ,GAAG,GAAKA,GAAM,QAAQ,GAAG,IAAM6B,EAAW,GAAK7B,GAAM,QAAQ,GAAG,GACjH8B,EAAI,SAAS,IAAMD,EAAW,GAAK7B,GAAM,QAAQ,GAAG,GAAKA,GAAM,QAAQ,GAAG,IAAM6B,EAAW,GAAK7B,GAAM,QAAQ,GAAG,EACnH,EACA8B,EAAI,YAAc,CAChBA,EAAI,SAAS,GAAKD,EAAW,GAAIC,EAAI,SAAS,GAAKD,EAAW,EAChE,EAEF,IAAME,EAAoBC,GAAK9B,EAAK,UAAU,IAAK+B,GAAOA,EAAG,QAAQ,EAAGJ,CAAU,EAClF,OAAA3B,EAAK,IAAM6B,EAAc,IACzB7B,EAAK,OAAS6B,EAAc,OACrB7B,CACT,CCxFA,IAAIgC,GACAC,GAAY,EACZC,GAAU,OAAO,iBAGfC,GAIF,CACF,MAAO,CAAC,EACR,OAAQ,CAAC,EACT,KAAM,CACR,EAEA,eAAsBC,GAAKC,EAAqC,CAC9D,OAAIC,EAAI,UAASN,GAAQ,MACpBA,GAGMK,EAAO,OAAOE,EAAI,gBAAiBP,GAAM,QAAW,GAF7DQ,GAAQ,CAAC,MAAM,EAAGH,CAAM,EACxBL,GAAQ,MAAMS,EAAUJ,EAAO,KAAK,SAAS,GAE/CJ,GAAYD,GAAM,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EAC3DC,GAAY,KAAIA,GAAY,KACzBD,EACT,CAEA,eAAeU,GAAgBC,EAAKN,EAAQO,EAAO,CACjD,IAAMC,EAAMF,EAAI,GAAG,GACbG,EAAiC,CAAC,EACpCC,EAAQ,EACZ,QAASC,EAAK,EAAGA,EAAKH,EAAI,OAAQG,IAEhC,GADAD,EAAQF,EAAIG,GAAI,GACZD,EAAQV,EAAO,KAAK,cAAe,CACrC,IAAMY,EAAqB,CAACJ,EAAIG,GAAI,GAAIH,EAAIG,GAAI,EAAE,EAClDF,EAAU,KAAK,CACb,MAAO,KAAK,MAAM,IAAMC,CAAK,EAAI,IACjC,KAAaF,GAAIG,GACjB,YAAAC,EACA,SAAU,CACR,KAAK,OAAOL,EAAM,MAAM,IAAM,GAAKK,EAAY,EAAE,EACjD,KAAK,OAAOL,EAAM,MAAM,IAAM,GAAKK,EAAY,EAAE,CACnD,CACF,CAAC,CACH,CAEFF,EAAQD,EAAU,OAAO,CAACI,EAAMC,IAAUA,EAAK,MAAQD,EAAOC,EAAK,MAAQD,EAAO,CAAC,EACnF,IAAME,EAA4B,CAAC,EAC7BC,EAAaC,GAAKR,EAAU,IAAKS,GAAOA,EAAG,QAAQ,EAAG,CAACX,EAAM,MAAM,GAAIA,EAAM,MAAM,EAAE,CAAC,EACtFY,EAAyC,CAAC,EAChD,OAAW,CAACC,EAAMC,CAAO,IAAK,OAAO,QAAeC,EAAS,EAAG,CAC9D,IAAMJ,EAAqB,CAAC,EAC5B,QAASK,EAAI,EAAGA,EAAIF,EAAQ,OAAS,EAAGE,IAAK,CAC3C,IAAMC,EAAMf,EAAU,KAAMgB,GAAOA,EAAG,OAASJ,EAAQE,EAAE,EACnDG,EAAMjB,EAAU,KAAMgB,GAAOA,EAAG,OAASJ,EAAQE,EAAI,EAAE,EACzDC,GAAOE,GAAOF,EAAI,OAASxB,EAAO,KAAK,eAAiB,IAAM0B,EAAI,OAAS1B,EAAO,KAAK,eAAiB,IAAIkB,EAAG,KAAK,CAACM,EAAI,SAAUE,EAAI,QAAQ,CAAC,CACtJ,CACAP,EAAYC,GAAQF,CACtB,CACA,IAAMS,EAAmB,CAAE,GAAI,EAAG,MAAAjB,EAAO,IAAKM,EAAO,IAAK,OAAQA,EAAO,OAAQ,UAAAP,EAAW,YAAAU,CAAY,EACxG,OAAIS,GAAUD,CAAI,EAClBZ,EAAO,KAAKY,CAAI,EACTZ,CACT,CAEA,eAAec,GAAevB,EAAKN,EAAQO,EAAO,CAChD,IAAMQ,EAA4B,CAAC,EACnC,QAASJ,EAAK,EAAGA,EAAKL,EAAI,GAAG,OAAQK,IAAM,CACzC,IAAMH,EAAMF,EAAI,GAAGK,GACbmB,EAAa,KAAK,MAAM,IAAMtB,EAAI,GAAK,EAAE,EAAI,IACnD,GAAIsB,EAAa9B,EAAO,KAAK,cAAe,CAC1C,IAAMS,EAAiC,CAAC,EACxC,QAASc,EAAI,EAAGA,EAAI,GAAIA,IAAK,CAC3B,IAAMb,EAAQF,EAAI,EAAIe,EAAI,GAC1B,GAAIb,EAAQV,EAAO,KAAK,cAAe,CACrC,IAAMY,EAAqB,CAACJ,EAAI,EAAIe,EAAI,GAAIf,EAAI,EAAIe,EAAI,EAAE,EAC1Dd,EAAU,KAAK,CACb,KAAaD,GAAIe,GACjB,MAAO,KAAK,MAAM,IAAMb,CAAK,EAAI,IACjC,YAAAE,EACA,SAAU,CAAC,KAAK,OAAOL,EAAM,MAAM,IAAM,GAAKK,EAAY,EAAE,EAAG,KAAK,OAAOL,EAAM,MAAM,IAAM,GAAKK,EAAY,EAAE,CAAC,CACnH,CAAC,CACH,CACF,CACA,IAAMI,EAAaC,GAAKR,EAAU,IAAKS,GAAOA,EAAG,QAAQ,EAAG,CAACX,EAAM,MAAM,GAAIA,EAAM,MAAM,EAAE,CAAC,EAItFY,EAAiD,CAAC,EACxD,OAAW,CAACC,EAAMC,CAAO,IAAK,OAAO,QAAeC,EAAS,EAAG,CAC9D,IAAMJ,EAAqB,CAAC,EAC5B,QAASK,EAAI,EAAGA,EAAIF,EAAQ,OAAS,EAAGE,IAAK,CAC3C,IAAMC,EAAMf,EAAU,KAAMgB,GAAOA,EAAG,OAASJ,EAAQE,EAAE,EACnDG,EAAMjB,EAAU,KAAMgB,GAAOA,EAAG,OAASJ,EAAQE,EAAI,EAAE,EACzDC,GAAOE,GAAOF,EAAI,OAASxB,EAAO,KAAK,eAAiB,IAAM0B,EAAI,OAAS1B,EAAO,KAAK,eAAiB,IAAIkB,EAAG,KAAK,CAACM,EAAI,SAAUE,EAAI,QAAQ,CAAC,CACtJ,CACAP,EAAYC,GAAQF,CACtB,CACA,IAAMS,EAAmB,CAAE,GAAAhB,EAAI,MAAOmB,EAAY,IAAKd,EAAO,IAAK,OAAQA,EAAO,OAAQ,UAAW,CAAC,GAAGP,CAAS,EAAG,YAAAU,CAAY,EAC7HS,GAAUD,CAAI,EAClBZ,EAAO,KAAKY,CAAI,CAClB,CACF,CACA,OAAAZ,EAAO,KAAK,CAACgB,EAAGC,IAAMA,EAAE,MAAQD,EAAE,KAAK,EACnChB,EAAO,OAASf,EAAO,KAAK,cAAae,EAAO,OAASf,EAAO,KAAK,aAClEe,CACT,CAEA,eAAsBkB,GAAQC,EAAelC,EAAuC,CAClF,GAAI,CAACL,IAAS,EAACA,IAAA,MAAAA,GAAO,OAAO,GAAG,OAAO,MAAO,CAAC,EAC1CK,EAAO,cAAaF,GAAM,MAAM,OAAS,GAC9CD,KACA,IAAMsC,GAAYnC,EAAO,KAAK,UAAY,GAAMoC,EAAI,EAAItC,GAAM,KACxDuC,EAAYxC,IAAWG,EAAO,KAAK,YAAc,GACvD,OAAIA,EAAO,aAAemC,GAAYE,EAC7BvC,GAAM,OAER,IAAI,QAAQ,MAAOwC,GAAY,CACpC,IAAMC,EAA4B,CAAC,EACnC1C,GAAU,EAmCV0C,EAAE,MAAYC,GAASN,EAAOtC,EAAS,EACvC2C,EAAE,IAAM5C,IAAA,YAAAA,GAAO,QAAQ4C,EAAE,OACzBzC,GAAM,KAAOsC,EAAI,EACjB,IAAM9B,EAAM,MAAMiC,EAAE,IAAI,MAAM,EAC9BzC,GAAM,OAAUyC,EAAE,IAAI,MAAM,KAAO,GAC/B,MAAMlC,GAAgBC,EAAKN,EAAQkC,CAAK,EACxC,MAAML,GAAevB,EAAKN,EAAQkC,CAAK,EAC3C,QAAWP,KAAQ7B,GAAM,OACnB2C,GAAYd,EAAM,CAACO,EAAM,MAAM,IAAM,EAAGA,EAAM,MAAM,IAAM,CAAC,CAAC,EAC5DQ,GAAOf,EAAK,SAAS,EAE3B,OAAO,KAAKY,CAAC,EAAE,QAASI,GAAc,UAAQJ,EAAEI,EAAO,CAAC,EAExDL,EAAQxC,GAAM,MAAM,CACtB,CAAC,CACH,CC1KA,IAAI8C,GACAC,GAA4B,CAAC,EAC7BC,GAAW,EACXC,GAAU,OAAO,iBACjBC,GAAY,EAEVC,GAAW,IAEjB,eAAsBC,GAAKC,EAAqC,CAC9D,GAAI,CAACP,IAASQ,EAAI,QAAS,CACzBR,GAAQ,MAAMS,EAAUF,EAAO,OAAO,SAAS,EAC/C,IAAMG,EAAS,OAAO,OAAOV,GAAM,eAAe,MAAS,EAC3DI,GAAY,MAAM,QAAQM,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,CACpF,MAAWH,EAAO,OAAOI,EAAI,gBAAiBX,GAAM,QAAW,EAC/D,OAAOA,EACT,CAEA,eAAeY,GAAQC,EAAeC,EAA+BP,EAAgB,CACnF,IAAIQ,EAAK,EACLC,EAA+B,CAAC,EACpC,QAAWC,IAAc,CAAC,EAAG,EAAG,CAAC,EAE5B,OAAK,SAAY,CAClB,IAAMC,EAAWD,EAAa,GAExBE,EAAa,UAAQN,EAAI,KAAMO,GAAeA,EAAE,MAAM,KAAQF,GAAY,IAAOE,EAAE,MAAM,IAAM,KAAOC,GAAO,MAAO,CAAC,EACrHC,EAAe,UAAQT,EAAI,KAAMO,GAAeA,EAAE,MAAM,KAAQF,GAAY,IAAOE,EAAE,MAAM,IAAM,GAAKC,GAAO,MAAO,CAAC,EAErHE,EAAS,MADED,EAAU,QAAQ,CAAC,GAAI,EAAGA,EAAU,MAAM,GAAK,CAAC,CAAC,EACpC,OAAO,CAAC,EAAE,MAAM,EACxCE,EAAS,MAAML,EAAQ,MAAM,EACnC,QAASM,EAAI,EAAGA,EAAIN,EAAQ,MAAM,GAAIM,IACpC,QAASC,EAAI,EAAGA,EAAIP,EAAQ,MAAM,GAAIO,IAAK,CACzC,IAAMC,EAAQH,EAAOC,GAAGC,GACxB,GAAIC,GAASpB,EAAO,OAAO,eAAiB,IAAMmB,IAAM,GAAI,CAC1D,IAAME,GAAM,GAAM,KAAK,MAAMH,EAAIP,CAAQ,GAAKA,EACxCW,GAAM,GAAM,KAAK,MAAMJ,EAAIP,CAAQ,GAAKA,EACxCY,EAAYP,EAAOE,GAAG,IAAKL,GAAcA,GAAKF,EAAWD,EAAab,GAAU,EAChF,CAAC2B,EAAGC,CAAC,EAAI,CACbJ,EAAMvB,GAAWY,EAAaa,EAAU,GACxCD,EAAMxB,GAAWY,EAAaa,EAAU,EAC1C,EACM,CAACG,EAAGC,CAAC,EAAI,CACbN,EAAMvB,GAAWY,EAAaa,EAAU,GAAMC,EAC9CF,EAAMxB,GAAWY,EAAaa,EAAU,GAAME,CAChD,EACIG,EAAc,CAACJ,EAAGC,EAAGC,EAAGC,CAAC,EAC7BC,EAASA,EAAO,IAAKf,GAAM,KAAK,IAAI,EAAG,KAAK,IAAIA,EAAG,CAAC,CAAC,CAAC,EACtD,IAAMgB,EAAM,CACVD,EAAO,GAAKrB,EAAY,GACxBqB,EAAO,GAAKrB,EAAY,GACxBqB,EAAO,GAAKrB,EAAY,GACxBqB,EAAO,GAAKrB,EAAY,EAC1B,EACMuB,EAAS,CACb,GAAItB,IAEJ,MAAO,KAAK,MAAM,IAAMY,CAAK,EAAI,IACjC,MAAOD,EAAI,EACX,MAAOL,GAAOK,GAAG,MAGjB,IAAKU,EAAI,IAAKhB,GAAM,KAAK,MAAMA,CAAC,CAAC,EACjC,OAAAe,CACF,EACAnB,EAAQ,KAAKqB,CAAM,CACrB,CACF,CAEJ,CAAC,EAGHxB,EAAI,QAASyB,GAAS,UAAQA,CAAC,CAAC,EAIhC,IAAMC,EAAWvB,EAAQ,IAAKI,GAAM,CAACA,EAAE,OAAO,GAAIA,EAAE,OAAO,GAAIA,EAAE,OAAO,GAAIA,EAAE,OAAO,EAAE,CAAC,EAClFoB,EAAYxB,EAAQ,IAAKI,GAAMA,EAAE,KAAK,EACxCqB,EAAwB,CAAC,EAC7B,GAAIF,GAAYA,EAAS,OAAS,EAAG,CACnC,IAAMG,EAAM,MAAS,QAAM,uBAAuBH,EAAUC,EAAWjC,EAAO,OAAO,YAAaA,EAAO,OAAO,aAAcA,EAAO,OAAO,aAAa,EACzJkC,EAAS,MAAMC,EAAI,KAAK,EACrB,UAAQA,CAAG,CAChB,CAGA,OAAA1B,EAAUA,EACP,OAAO,CAAC2B,EAAMC,IAAQH,EAAO,SAASG,CAAG,CAAC,EAC1C,KAAK,CAACxB,EAAGyB,IAAOA,EAAE,MAAQzB,EAAE,KAAM,EAE9BJ,CACT,CAEA,eAAsB8B,GAAQC,EAAexC,EAAyC,CACpF,IAAMyC,GAAYzC,EAAO,OAAO,UAAY,GAAM0C,EAAI,EAAI/C,GACpDgD,EAAY/C,IAAWI,EAAO,OAAO,YAAc,GACzD,OAAIA,EAAO,aAAeyC,GAAYE,GAAcjD,GAAK,OAAS,GAChEE,KACOF,KAETE,GAAU,EACN,CAACK,EAAI,QAAQ,SAAS,KAAK,GAAK,CAACA,EAAI,QAAQ,SAAS,eAAe,EAAUP,GAC5E,IAAI,QAAQ,MAAOkD,GAAY,CACpC,IAAMC,EAAa,CAACL,EAAM,MAAM,IAAM,EAAGA,EAAM,MAAM,IAAM,CAAC,EACtDM,EAAY,QAAM,eAAeN,EAAO,CAAC3C,GAAWA,EAAS,EAAG,EAAK,EACrEkD,EAAU,MAAID,EAAQE,EAAU,KAAK,EACrCC,EAAYF,EAAK,UAAU,CAAC,EAAG,EAAG,EAAG,CAAC,CAAC,EAC1C,UAAQA,CAAI,EACZ,UAAQD,CAAM,EAEjB,IAAII,EACAlD,EAAO,OAAO,UAASkD,EAAUzD,GAAM,QAAQwD,CAAS,GAC5DtD,GAAW+C,EAAI,EACZ,UAAQO,CAAS,EAEpB,IAAME,EAAM,MAAM9C,GAAQ6C,EAAqBL,EAAgC7C,CAAM,EACrFN,GAAOyD,EACPP,EAAQO,CAAG,CACb,CAAC,EACH,CC/HO,IAAMC,GAAY,CACvB,OAAQ,UAAW,WAAY,UAAW,WAAY,eACtD,gBAAiB,YAAa,aAAc,YAAa,aACzD,UAAW,WAAY,WAAY,YAAa,YAAa,YAC/D,EAEaC,GAAQD,GAAU,OAElBE,GAAUF,GAAU,OAAO,CAACG,EAAQC,EAAWC,KAC1DF,EAAOC,GAAaC,EACbF,GACN,CAAC,CAAC,EAECG,GAAqB,CACzB,CAAC,UAAW,cAAc,EAAG,CAAC,YAAa,cAAc,EACzD,CAAC,YAAa,WAAW,EAAG,CAAC,UAAW,UAAU,EAClD,CAAC,WAAY,WAAW,EAAG,CAAC,WAAY,eAAe,EACvD,CAAC,aAAc,eAAe,EAAG,CAAC,aAAc,YAAY,EAC5D,CAAC,WAAY,WAAW,EAAG,CAAC,YAAa,YAAY,EACrD,CAAC,eAAgB,eAAe,EAAG,CAAC,UAAW,UAAU,CAC3D,EACaC,GAAuBD,GAAmB,IAAI,CAAC,CAACE,EAAYC,CAAU,IAAO,CAACP,GAAQM,GAAaN,GAAQO,EAAW,CAAE,EAExHC,GAAY,CACvB,CAAC,OAAQ,SAAS,EAAG,CAAC,UAAW,SAAS,EAAG,CAAC,OAAQ,UAAU,EAChE,CAAC,WAAY,UAAU,EAAG,CAAC,OAAQ,cAAc,EACjD,CAAC,eAAgB,WAAW,EAAG,CAAC,YAAa,WAAW,EACxD,CAAC,eAAgB,SAAS,EAAG,CAAC,UAAW,UAAU,EACnD,CAAC,WAAY,WAAW,EAAG,CAAC,OAAQ,eAAe,EACnD,CAAC,gBAAiB,YAAY,EAAG,CAAC,aAAc,YAAY,EAC5D,CAAC,gBAAiB,UAAU,EAAG,CAAC,WAAY,WAAW,EACvD,CAAC,YAAa,YAAY,CAC5B,EAgBO,SAASC,GAAeC,EAA6C,CAC1E,IAAMC,EAAQD,EAAU,OAAO,CAAC,CAAE,KAAAE,EAAM,KAAAC,EAAM,KAAAC,EAAM,KAAAC,CAAK,EAAG,CAAE,SAAU,CAAE,EAAAC,EAAG,EAAAC,CAAE,CAAE,KAAO,CACtF,KAAM,KAAK,IAAIL,EAAMI,CAAC,EACtB,KAAM,KAAK,IAAIH,EAAMI,CAAC,EACtB,KAAM,KAAK,IAAIH,EAAME,CAAC,EACtB,KAAM,KAAK,IAAID,EAAME,CAAC,CACxB,GAAI,CACF,KAAM,OAAO,kBACb,KAAM,OAAO,kBACb,KAAM,OAAO,kBACb,KAAM,OAAO,iBACf,CAAC,EACD,MAAO,CAACN,EAAM,KAAMA,EAAM,KAAMA,EAAM,KAAOA,EAAM,KAAMA,EAAM,KAAOA,EAAM,IAAI,CAClF,CAEO,SAASO,GAAWC,EAAO,CAACC,EAAQC,CAAK,EAAG,CAACC,EAAuBC,CAAoB,EAAsB,CACnH,IAAMC,EAASJ,EAASE,EAClBG,EAASJ,EAAQE,EACjBG,EAAY,CAACC,EAAMC,KAAmB,CAC1C,GAAIA,EACJ,MAAOD,EAAK,MACZ,OAAQ,CAACA,EAAK,IAAI,GAAKJ,EAAsBI,EAAK,IAAI,GAAKL,EAAuBK,EAAK,IAAI,GAAKJ,EAAsBI,EAAK,IAAI,GAAKL,CAAqB,EACzJ,IAAK,CAAC,KAAK,MAAMK,EAAK,IAAI,GAAKF,CAAM,EAAG,KAAK,MAAME,EAAK,IAAI,GAAKH,CAAM,EAAG,KAAK,MAAMG,EAAK,IAAI,GAAKF,CAAM,EAAG,KAAK,MAAME,EAAK,IAAI,GAAKH,CAAM,CAAC,EAC5I,UAAWG,EAAK,UAAU,IAAI,CAAC,CAAE,MAAAE,EAAO,KAAAC,EAAM,SAAAC,CAAS,KAAO,CAC5D,MAAOF,EACP,KAAMC,EACN,SAAU,CAAC,KAAK,MAAMC,EAAS,EAAIN,CAAM,EAAG,KAAK,MAAMM,EAAS,EAAIP,CAAM,CAAC,EAC3E,YAAa,CAACO,EAAS,EAAIT,EAAuBS,EAAS,EAAIT,CAAqB,CACtF,EAAE,EACF,YAAa,CAAC,CAChB,GAEA,OADoBH,EAAM,IAAI,CAACQ,EAAMC,IAAMF,EAAUC,EAAMC,CAAC,CAAC,CAE/D,CAGO,IAAMI,GAAN,KAAc,CAKnB,YAAYC,EAASC,EAAiB,CAJtCC,EAAA,sBACAA,EAAA,yBACAA,EAAA,wBAGE,KAAK,cAAgB,IAAI,MAAMF,CAAO,EACtC,KAAK,iBAAmB,GACxB,KAAK,gBAAkBC,CACzB,CAEA,QAAQlB,EAAG,CACT,KAAK,cAAc,EAAE,KAAK,kBAAoBA,EAC9C,KAAK,KAAK,KAAK,gBAAgB,CACjC,CAEA,SAAU,CACR,IAAMoB,EAAM,KAAK,cAAc,GAC/B,YAAK,SAAS,EAAG,KAAK,kBAAkB,EACxC,KAAK,KAAK,CAAC,EACX,KAAK,cAAc,KAAK,iBAAmB,GAAK,KACzCA,CACT,CAEA,OAAQ,CAAE,OAAO,KAAK,mBAAqB,EAAI,CAE/C,MAAO,CAAE,OAAO,KAAK,iBAAmB,CAAG,CAE3C,KAAM,CAAE,OAAO,KAAK,cAAc,MAAM,EAAG,KAAK,iBAAmB,CAAC,CAAG,CAEvE,KAAM,CAAE,OAAO,KAAK,cAAc,EAAI,CAEtC,KAAKC,EAAG,CACN,KAAOA,EAAI,GAAK,KAAK,KAAK,KAAK,MAAMA,EAAI,CAAC,EAAGA,CAAC,GAC5C,KAAK,SAASA,EAAG,KAAK,MAAMA,EAAI,CAAC,CAAC,EAClCA,EAAI,KAAK,MAAMA,EAAI,CAAC,CAExB,CAEA,KAAKA,EAAG,CACN,KAAO,EAAIA,GAAK,KAAK,kBAAkB,CACrC,IAAIC,EAAI,EAAID,EAEZ,GADIC,EAAI,KAAK,kBAAoB,KAAK,KAAKA,EAAGA,EAAI,CAAC,GAAGA,IAClD,CAAC,KAAK,KAAKD,EAAGC,CAAC,EAAG,MACtB,KAAK,SAASD,EAAGC,CAAC,EAClBD,EAAIC,CACN,CACF,CAEA,WAAWV,EAAG,CAEZ,OAAO,KAAK,gBAAgB,KAAK,cAAcA,EAAE,CACnD,CAEA,KAAKA,EAAGU,EAAG,CACT,OAAO,KAAK,WAAWV,CAAC,EAAI,KAAK,WAAWU,CAAC,CAC/C,CAEA,SAASV,EAAGU,EAAG,CACb,IAAMC,EAAI,KAAK,cAAcX,GAC7B,KAAK,cAAcA,GAAK,KAAK,cAAcU,GAC3C,KAAK,cAAcA,GAAKC,CAC1B,CACF,EAEO,SAASC,GAAevB,EAAGD,EAAGyB,EAAUC,EAAS,CACtD,MAAO,CACL,EAAGA,EAAQ,IAAIzB,EAAGD,EAAGyB,CAAQ,EAC7B,EAAGC,EAAQ,IAAIzB,EAAGD,EAAGyB,EAAWE,EAAK,CACvC,CACF,CAEO,SAASC,GAAed,EAAMe,EAAcH,EAAS,CAC1D,GAAM,CAAE,SAAAI,EAAU,SAAAC,EAAU,GAAIN,CAAS,EAAIX,EACvC,CAAE,EAAAb,EAAG,EAAAD,CAAE,EAAIwB,GAAeM,EAAUC,EAAUN,EAAUC,CAAO,EACrE,MAAO,CACL,EAAGZ,EAAK,SAAWe,EAAe7B,EAClC,EAAGc,EAAK,SAAWe,EAAe5B,CACpC,CACF,CAUO,SAAS+B,GAAMC,EAAGC,EAAKC,EAAK,CACjC,OAAIF,EAAIC,EAAYA,EAChBD,EAAIE,EAAYA,EACbF,CACT,CAEO,SAASG,GAAgBC,EAAIC,EAAIC,EAAIC,EAAI,CAC9C,IAAMC,EAAKF,EAAKF,EACVK,EAAKF,EAAKF,EAChB,OAAOG,EAAKA,EAAKC,EAAKA,CACxB,CAEO,SAASC,GAAWV,EAAGW,EAAG,CAC/B,MAAO,CAAE,EAAGX,EAAE,EAAIW,EAAE,EAAG,EAAGX,EAAE,EAAIW,EAAE,CAAE,CACtC,CCnLA,IAAIC,GACEC,GAAiB,CAAC,+BAA6C,gCAAoD,yCAA+D,wCAA6D,EAC/OC,GAAqB,EACrBC,GAAe,GACfC,GAAmB,IAAM,EAE/B,SAASC,GAASC,EAAQC,EAAgBC,EAAUC,EAAQC,EAASC,EAAeC,EAAmB,EAAG,CACxG,IAAMC,EAAmBC,IAAW,CAClC,EAAGH,EAAc,IAAIG,EAAM,EAAGA,EAAM,EAAGR,CAAM,EAC7C,EAAGK,EAAc,IAAIG,EAAM,EAAGA,EAAM,EAAIH,EAAc,MAAM,GAAK,EAAKL,CAAM,CAC9E,GACMS,EAA2B,CAACD,EAAOE,EAAQC,KAAW,CAC1D,EAASC,GAAM,KAAK,MAAMJ,EAAM,EAAIX,EAAY,EAAG,EAAGa,EAAS,CAAC,EAChE,EAASE,GAAM,KAAK,MAAMJ,EAAM,EAAIX,EAAY,EAAG,EAAGc,EAAQ,CAAC,CACjE,GAEM,CAACD,EAAQC,CAAK,EAAIR,EAAO,MAEzBU,EAAwBJ,EAAyBR,EAAe,SAAUS,EAAQC,CAAK,EACvFG,EAAeP,EAAgBM,CAAqB,EAEtDE,EADyBC,GAAWf,EAAe,SAAUa,CAAY,EAE7E,QAASG,EAAI,EAAGA,EAAIX,EAAkBW,IAAK,CACzC,IAAMC,EAAwBT,EAAyBM,EAAgBL,EAAQC,CAAK,EAC9EQ,EAAoBC,GAAeF,EAAsB,EAAGA,EAAsB,EAAGhB,EAAUE,CAAO,EAC5GW,EAAuBC,GACrB,CAAE,EAAGE,EAAsB,EAAIrB,GAAc,EAAGqB,EAAsB,EAAIrB,EAAa,EACvF,CAAE,EAAGsB,EAAY,EAAG,EAAGA,EAAY,CAAE,CACvC,CACF,CACA,IAAME,EAAwBZ,EAAyBM,EAAgBL,EAAQC,CAAK,EAC9EW,EAAQnB,EAAO,IAAIkB,EAAsB,EAAGA,EAAsB,EAAGnB,CAAQ,EACnF,MAAO,CAAE,SAAUa,EAAgB,KAAYQ,GAAUrB,GAAW,MAAAoB,CAAM,CAC5E,CAEO,SAASE,GAAWC,EAAMtB,EAAQC,EAASsB,EAAkBC,EAAkB,CACpF,IAAMC,EAAeC,GAAU,IAAI,CAAC,CAACC,EAAgBC,CAAa,IAAO,CAAOC,GAAQF,GAAuBE,GAAQD,EAAc,CAAE,EACjIE,EAAWL,EAAO,IAAI,CAAC,CAAC,CAAEM,CAAY,IAAMA,CAAY,EACxDC,EAAWP,EAAO,IAAI,CAAC,CAACQ,CAAa,IAAMA,CAAa,EACxDC,EAAWlC,EAAO,MAAM,GACxBmC,EAAWL,EAAS,OACpBM,EAAY,IAAI,MAAMF,CAAQ,EAE9BG,EAAkBC,GAAehB,EAAK,KAAM5B,GAAcO,CAAO,EACvEmC,EAAUd,EAAK,KAAK,IAAM,CACxB,MAAOA,EAAK,MACZ,KAAYF,GAAUE,EAAK,KAAK,IAChC,SAAUe,CACZ,EAEA,QAASE,EAAOJ,EAAW,EAAGI,GAAQ,EAAG,EAAEA,EAAM,CAC/C,IAAMC,EAAWV,EAASS,GACpBxC,EAAWiC,EAASO,GACtBH,EAAUI,IAAa,CAACJ,EAAUrC,KACpCqC,EAAUrC,GAAYH,GAAS2C,EAAMH,EAAUI,GAAWzC,EAAUC,EAAQC,EAASuB,CAAgB,EAEzG,CAEA,QAASe,EAAO,EAAGA,EAAOJ,EAAU,EAAEI,EAAM,CAC1C,IAAMC,EAAWR,EAASO,GACpBxC,EAAW+B,EAASS,GACtBH,EAAUI,IAAa,CAACJ,EAAUrC,KACpCqC,EAAUrC,GAAYH,GAAS2C,EAAMH,EAAUI,GAAWzC,EAAUC,EAAQC,EAASsB,CAAgB,EAEzG,CACA,OAAOa,CACT,CAEA,SAASK,GAA4BC,EAAYvB,EAAOwB,EAAUC,EAAU5C,EAAQ,CAClF,GAAM,CAACO,EAAQC,CAAK,EAAIR,EAAO,MAC3B6C,EAAe,GACbC,EAAS,KAAK,IAAIH,EAAWlD,GAAoB,CAAC,EAClDsD,EAAO,KAAK,IAAIJ,EAAWlD,GAAqB,EAAGc,CAAM,EAC/D,QAASyC,EAAWF,EAAQE,EAAWD,EAAM,EAAEC,EAAU,CACvD,IAAMC,EAAS,KAAK,IAAIL,EAAWnD,GAAoB,CAAC,EAClDyD,EAAO,KAAK,IAAIN,EAAWnD,GAAqB,EAAGe,CAAK,EAC9D,QAAS2C,EAAWF,EAAQE,EAAWD,EAAM,EAAEC,EAC7C,GAAInD,EAAO,IAAIgD,EAAUG,EAAUT,CAAU,EAAIvB,EAAO,CACtD0B,EAAe,GACf,KACF,CAEF,GAAI,CAACA,EAAc,KACrB,CACA,OAAOA,CACT,CAEO,SAASO,GAAwBC,EAAerD,EAAQ,CAC7D,GAAM,CAACO,EAAQC,EAAO8C,CAAY,EAAItD,EAAO,MACvCuD,EAAQ,IAAUC,GAAQjD,EAASC,EAAQ8C,EAAc,CAAC,CAAE,MAAAnC,CAAM,IAAMA,CAAK,EACnF,QAASwB,EAAW,EAAGA,EAAWpC,EAAQ,EAAEoC,EAC1C,QAASC,EAAW,EAAGA,EAAWpC,EAAO,EAAEoC,EACzC,QAASF,EAAa,EAAGA,EAAaY,EAAc,EAAEZ,EAAY,CAChE,IAAMvB,EAAQnB,EAAO,IAAI2C,EAAUC,EAAUF,CAAU,EAEnDvB,EAAQkC,GAERZ,GAA4BC,EAAYvB,EAAOwB,EAAUC,EAAU5C,CAAM,GAAGuD,EAAM,QAAQ,CAAE,MAAApC,EAAO,KAAM,CAAE,SAAAwB,EAAU,SAAAC,EAAU,GAAIF,CAAW,CAAE,CAAC,CACvJ,CAGJ,OAAOa,CACT,CAEA,SAASE,GAAaC,EAAO,CAAE,EAAAC,EAAG,EAAAC,CAAE,EAAGlB,EAAY,CACjD,OAAOgB,EAAM,KAAK,CAAC,CAAE,UAAAtB,CAAU,IAAM,CAxHvC,IAAAyB,EAyHI,IAAMC,GAAwBD,EAAAzB,EAAUM,KAAV,YAAAmB,EAAuB,SACrD,OAAKC,EACQC,GAAgBH,EAAGD,EAAGG,EAAsB,EAAGA,EAAsB,CAAC,GAAKnE,GADrD,EAErC,CAAC,CACH,CAEA,SAASqE,GAAiBC,EAAe7B,EAAW,CAKlD,OAJoCA,EAAU,OAAO,CAAC8B,EAAQ,CAAE,SAAAC,EAAU,MAAAhD,CAAM,EAAGuB,KAC5Ee,GAAaQ,EAAeE,EAAUzB,CAAU,IAAGwB,GAAU/C,GAC3D+C,GACN,CAAG,EAC+B9B,EAAU,MACjD,CAEO,SAASgC,GAAOnE,EAASD,EAAQuB,EAAkBC,EAAkB6C,EAAahB,EAAe,CACtG,IAAMK,EAAuD,CAAC,EACxDH,EAAQH,GAAwBC,EAAerD,CAAM,EAE3D,KAAO0D,EAAM,OAASW,GAAe,CAACd,EAAM,MAAM,GAAG,CAEnD,IAAMjC,EAAOiC,EAAM,QAAQ,EAGrBe,EAAwBhC,GAAehB,EAAK,KAAM5B,GAAcO,CAAO,EAE7E,GAAIwD,GAAaC,EAAOY,EAAiBhD,EAAK,KAAK,EAAE,EAAG,SAExD,IAAIc,EAAYf,GAAWC,EAAMtB,EAAQC,EAASsB,EAAkBC,CAAgB,EACpFY,EAAYA,EAAU,OAAQmC,GAAMA,EAAE,MAAQlB,CAAa,EAC3D,IAAMlC,EAAQ6C,GAAiBN,EAAOtB,CAAS,EACzCoC,EAAYC,GAAerC,CAAS,EACtCjB,EAAQkC,GAAeK,EAAM,KAAK,CAAE,UAAAtB,EAAW,IAAAoC,EAAK,MAAO,KAAK,MAAM,IAAMrD,CAAK,EAAI,GAAI,CAAC,CAChG,CACA,OAAOuC,CACT,CAEA,eAAsBgB,GAAQC,EAAeC,EAAuC,CAIlF,IAAMC,EAAS,OAAK,IAAM,CACxB,GAAI,CAACtF,GAAM,OAAO,GAAG,MAAO,MAAO,CAAC,EACpC,IAAMuF,EAAa,QAAM,eAAeH,EAAO,CAACpF,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,CAAC,EAC7FwF,EAAgB,MAAO,MAAO,OAAKD,EAAS,SAAS,EAAG,KAAK,EAAG,CAAG,EAEnEE,EADyBzF,GAAM,QAAQwF,EAAYvF,EAAc,EAC7C,IAAKoE,GAAS,UAAQA,EAAG,CAAC,CAAC,CAAC,CAAC,EACvD,OAAAoB,EAAU,GAAQ,UAAQA,EAAU,EAAE,EAC/BA,CACT,CAAC,EAEKC,EAAU,MAAM,QAAQ,IAAIJ,EAAI,IAAKK,GAAmBA,EAAO,OAAO,CAAC,CAAC,EAC9E,QAAWC,KAAKN,EAAQ,UAAQM,CAAC,EAEjC,IAAMC,EAAU,MAAMhB,GAAOa,EAAQ,GAAIA,EAAQ,GAAIA,EAAQ,GAAIA,EAAQ,GAAIL,EAAO,KAAK,YAAaA,EAAO,KAAK,aAAa,EAC/H,OAAKrF,GAAM,OAAO,GAAG,MACA8F,GAAWD,EAAS,CAACT,EAAM,MAAM,GAAIA,EAAM,MAAM,EAAE,EAAG,CAACpF,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,CAAC,EAD5F,CAAC,CAGtC,CAEA,eAAsB+F,GAAKV,EAAqC,CAC9D,MAAI,CAACrF,IAASgG,EAAI,QAAShG,GAAQ,MAAMiG,EAAUZ,EAAO,KAAK,SAAS,EAC/DA,EAAO,OAAOa,EAAI,gBAAiBlG,GAAM,QAAW,EACtDA,EACT,CCtKA,IAAImG,GACAC,GAAO,GAEX,eAAsBC,GAAKC,EAAqC,CAC9D,MAAI,CAACH,IAASI,EAAI,QAASJ,GAAQ,MAAMK,EAAUF,EAAO,aAAa,SAAS,EACvEA,EAAO,OAAOG,EAAI,gBAAiBN,GAAM,QAAW,EACtDA,EACT,CAEA,eAAsBO,GAAQC,EAAcC,EAA+BN,EACoB,CA5B/F,IAAAO,EAAAC,EA6BE,GAAIV,GAAM,MAAO,CAAE,KAAM,CAAC,EAAG,OAAQ,KAAM,MAAO,IAAK,EACvDA,GAAO,GACFD,IAAO,MAAME,GAAKC,CAAM,EAC7B,IAAMS,EAAa,MAAYL,GAAQC,EAAOL,CAAM,EAC9CU,IAAQH,EAAAE,EAAW,SAAX,YAAAF,EAAmB,MAAM,KAAM,EACvCI,IAASH,EAAAC,EAAW,SAAX,YAAAD,EAAmB,MAAM,KAAM,EAC9C,GAAI,CAACC,EAAW,OAAQ,MAAO,CAAE,KAAM,CAAC,EAAG,OAAQ,KAAM,MAAO,IAAK,EACrE,IAAMG,EAA4B,CAAC,EAEnCA,EAAE,OAAY,QAAM,eAAeH,EAAW,OAAQ,CAACZ,GAAM,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EAAGA,GAAM,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,CAAC,EAAG,EAAK,EACtK,UAAQY,EAAW,MAAM,EAC5BG,EAAE,KAAU,MAAIA,EAAE,OAAQC,EAAU,KAAK,EACzCD,EAAE,IAAMf,GAAM,QAAQe,EAAE,IAAI,EAE5BA,EAAE,QAAa,UAAQA,EAAE,IAAK,CAAC,EAC3BA,EAAE,QAAQ,MAAM,KAAO,GACzBA,EAAE,QAAa,UAAQA,EAAE,OAAO,EAChC,CAACA,EAAE,GAAIA,EAAE,EAAE,EAAO,UAAQA,EAAE,QAAS,CAAC,EACtCA,EAAE,OAAY,aAAWA,EAAE,GAAI,CAAC,EAChCA,EAAE,IAAS,aAAWA,EAAE,OAAQ,CAAC,EACjCA,EAAE,KAAU,QAAM,cAAcA,EAAE,IAAK,CAAC,CAAC,EAAG,EAAG,GAAK,EAAG,CAAC,EAAG,CAAC,CAAC,EAAG,CAACF,EAAOC,CAAM,CAAC,EAI/EC,EAAE,KAAU,UAAQA,EAAE,KAAM,CAAC,GAE7BA,EAAE,KAAU,QAAM,eAAeA,EAAE,QAAS,CAACD,EAAQD,CAAK,CAAC,EAE7D,IAAMI,EAAO,MAAM,KAAK,MAAMF,EAAE,KAAK,KAAK,CAAC,EAE3C,GAAIX,EAAI,MAAQ,CAACA,EAAI,QAAW,OAAO,WAAc,YACnD,OAAID,EAAO,OAAOG,EAAI,wBAAwB,EAC9C,OAAO,KAAKS,CAAC,EAAE,QAASG,GAAc,UAAQH,EAAEG,EAAO,CAAC,EACjD,CAAE,KAAAD,EAAM,OAAQ,KAAM,MAAO,IAAK,EAG3C,IAAME,EAAoBC,GAAOP,EAAOC,CAAM,EAEvC,WAAS,MAAS,UAAQ,SAASC,EAAE,KAAMI,CAAW,EAC7D,IAAME,EAAWF,EAAY,WAAW,IAAI,EACxChB,EAAO,aAAa,MAAQA,EAAO,aAAa,KAAO,IAAGkB,EAAS,OAAS,QAAQlB,EAAO,aAAa,WAC5G,IAAMmB,EAAYD,EAAS,aAAa,EAAG,EAAGR,EAAOC,CAAM,EAErDS,EAAwBH,GAAOP,EAAOC,CAAM,EAC5CU,EAAeD,EAAgB,WAAW,IAAI,EAChDX,EAAW,QAAQY,EAAa,UAAUZ,EAAW,OAAQ,EAAG,CAAC,EACrEY,EAAa,yBAA2B,SACpCrB,EAAO,aAAa,MAAQA,EAAO,aAAa,KAAO,IAAGqB,EAAa,OAAS,QAAQrB,EAAO,aAAa,WAChHqB,EAAa,UAAUL,EAAa,EAAG,CAAC,EACxCK,EAAa,yBAA2B,cACxCA,EAAa,OAAS,OACtB,IAAMC,EAAgBD,EAAa,aAAa,EAAG,EAAGX,EAAOC,CAAM,EACnE,QAASY,EAAI,EAAGA,EAAIb,EAAQC,EAAQY,IAAKD,EAAc,KAAK,EAAIC,EAAI,GAAKJ,EAAU,KAAK,EAAII,EAAI,GAChGF,EAAa,aAAaC,EAAe,EAAG,CAAC,EAE7C,IAAIE,EAAiC,KACrC,GAAIlB,GAAcc,EAAiB,CACjCI,EAAqBP,GAAOP,EAAOC,CAAM,EACzC,IAAMc,EAAU,MAAYrB,GAAQE,EAAYN,CAAM,EACnD,UAAQyB,EAAQ,MAAM,EACzB,IAAMC,EAAWF,EAAa,WAAW,IAAI,EAC7CE,EAAS,UAAUD,EAAQ,OAA6B,EAAG,EAAGD,EAAa,MAAOA,EAAa,MAAM,EACrGE,EAAS,UAAUN,EAAiB,EAAG,CAAC,CAC1C,CAEA,cAAO,KAAKR,CAAC,EAAE,QAASG,GAAc,UAAQH,EAAEG,EAAO,CAAC,EACxDjB,GAAO,GAEA,CAAE,KAAAgB,EAAM,OAAQM,EAAiB,MAAOJ,CAAY,CAC7D,CxC9DO,IAAMW,GAAN,KAAa,CAAb,cACLC,EAAA,iBAAqD,MACrDA,EAAA,YAAgD,MAChDA,EAAA,uBAA2D,MAC3DA,EAAA,iBAAqD,MACrDA,EAAA,iBAAqD,MACrDA,EAAA,qBAAyD,MACzDA,EAAA,qBAAyD,MACzDA,EAAA,eAAmD,MACnDA,EAAA,kBAAsD,MACtDA,EAAA,gBAAoD,MACpDA,EAAA,gBAAoD,MACpDA,EAAA,eAAmD,MACnDA,EAAA,oBAAwD,MACxDA,EAAA,gBAAoD,MACpDA,EAAA,oBAAwD,MACxDA,EAAA,iBAAqD,MACrDA,EAAA,gBAAoD,MACpDA,EAAA,eAAmD,MACnDA,EAAA,eAAmD,MACnDA,EAAA,eAAmD,MACnDA,EAAA,oBAAwD,MACxDA,EAAA,iBAAqD,MACvD,EAcaC,GAAiBC,GAAgC,CAC5D,IAAIC,EAAwB,EACxBC,EAAmB,EACnBC,EAAmB,EACvB,QAAWC,KAAK,OAAO,OAAOC,EAAU,EACtCJ,GAAyBG,EAAE,iBAC3BF,GAAoBE,EAAE,kBACtBD,GAAoBC,EAAE,YAExB,IAAME,EAAmBH,EAAmB,EAAID,EAAmBC,EAAmB,EACtF,MAAO,CACL,gBAAiB,OAAO,OAAOE,EAAU,EAAE,OAC3C,iBAAkB,OAClB,iBAAkB,OAAO,KAAKL,EAAS,MAAM,EAAE,OAC/C,iBAAAM,EACA,sBAAAL,EACA,iBAAAC,EACA,iBAAAC,EACA,iBAAkB,OAClB,WAAY,OAAO,OAAOE,EAAU,CACtC,CACF,EAEO,SAASE,GAAMP,EAAuB,CAE3C,QAAWQ,KAAS,OAAO,KAAKR,EAAS,MAAM,EAAGA,EAAS,OAAOQ,GAAyB,IAC7F,CAGA,eAAsBC,GAAKT,EAAgC,CAtG3D,IAAAU,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,GAAAC,EAAAC,GAuGMC,EAAI,SAASlC,GAAMP,CAAQ,EAC3BA,EAAS,OAAO,KAAK,UACnB,CAACA,EAAS,OAAO,YAAYW,GAAAD,EAAAV,EAAS,OAAO,KAAK,WAArB,YAAAU,EAA+B,YAA/B,YAAAC,EAA0C,SAAS,iBAClF,CAACX,EAAS,OAAO,SAAUA,EAAS,OAAO,YAAY,EAAI,MAAeS,GAAKT,EAAS,MAAM,GAE5F,CAACA,EAAS,OAAO,cAAgBA,EAAS,OAAO,KAAK,aAAaa,GAAAD,EAAAZ,EAAS,OAAO,KAAK,WAArB,YAAAY,EAA+B,YAA/B,YAAAC,EAA0C,SAAS,iBACxH,CAACb,EAAS,OAAO,SAAUA,EAAS,OAAO,YAAY,EAAI,MAAeS,GAAKT,EAAS,MAAM,IAG9FA,EAAS,OAAO,KAAK,SAAW,CAACA,EAAS,OAAO,aAAae,GAAAD,EAAAd,EAAS,OAAO,OAAhB,YAAAc,EAAsB,YAAtB,YAAAC,EAAiC,SAAS,gBAAcf,EAAS,OAAO,UAAsB0C,GAAS1C,EAAS,MAAM,GAEpLA,EAAS,OAAO,KAAK,SAAW,CAACA,EAAS,OAAO,iBAAmBA,EAAS,OAAO,KAAK,UAAeA,EAAS,OAAO,KAAK,SAAY,YAAcA,EAAS,OAAO,gBAA4B2C,GAAW3C,EAAS,MAAM,GAC7NA,EAAS,OAAO,KAAK,SAAW,CAACA,EAAS,OAAO,iBAAiBiB,GAAAD,EAAAhB,EAAS,OAAO,OAAhB,YAAAgB,EAAsB,YAAtB,YAAAC,EAAiC,SAAS,oBAAkBjB,EAAS,OAAO,cAA8BS,GAAKT,EAAS,MAAM,GAChMA,EAAS,OAAO,KAAK,SAAW,CAACA,EAAS,OAAO,WAAWmB,GAAAD,EAAAlB,EAAS,OAAO,OAAhB,YAAAkB,EAAsB,YAAtB,YAAAC,EAAiC,SAAS,cAAYnB,EAAS,OAAO,QAAkBS,GAAKT,EAAS,MAAM,GACxKA,EAAS,OAAO,KAAK,SAAW,CAACA,EAAS,OAAO,WAAWqB,GAAAD,EAAApB,EAAS,OAAO,OAAhB,YAAAoB,EAAsB,YAAtB,YAAAC,EAAiC,SAAS,cAAYrB,EAAS,OAAO,QAAkBS,GAAKT,EAAS,MAAM,GACxKA,EAAS,OAAO,KAAK,SAAW,CAACA,EAAS,OAAO,aAAYA,EAAS,OAAO,WAAuBS,GAAKT,EAAS,MAAM,GACxHA,EAAS,OAAO,KAAK,WAAWsB,EAAAtB,EAAS,OAAO,KAAK,YAArB,YAAAsB,EAAgC,UAAW,CAACtB,EAAS,OAAO,YAAWA,EAAS,OAAO,UAAsBS,GAAKT,EAAS,MAAM,GACjKA,EAAS,OAAO,KAAK,WAAWuB,EAAAvB,EAAS,OAAO,KAAK,WAArB,YAAAuB,EAA+B,UAAW,CAACvB,EAAS,OAAO,WAAUA,EAAS,OAAO,SAAoBS,GAAKT,EAAS,MAAM,GAC7JA,EAAS,OAAO,KAAK,WAAWwB,EAAAxB,EAAS,OAAO,KAAK,cAArB,YAAAwB,EAAkC,UAAW,CAACxB,EAAS,OAAO,UAASA,EAAS,OAAO,QAAkBS,GAAKT,EAAS,MAAM,GAC7JA,EAAS,OAAO,KAAK,WAAWyB,EAAAzB,EAAS,OAAO,KAAK,UAArB,YAAAyB,EAA8B,UAAW,CAACzB,EAAS,OAAO,UAASA,EAAS,OAAO,QAAkBS,GAAKT,EAAS,MAAM,GACzJA,EAAS,OAAO,KAAK,WAAW0B,EAAA1B,EAAS,OAAO,KAAK,OAArB,YAAA0B,EAA2B,UAAW,GAACC,EAAA3B,EAAS,OAAO,KAAK,YAArB,MAAA2B,EAAgC,UAAW,CAAC3B,EAAS,OAAO,WAAUA,EAAS,OAAO,SAAgBS,GAAKT,EAAS,MAAM,GACjMA,EAAS,OAAO,KAAK,WAAW4B,EAAA5B,EAAS,OAAO,KAAK,OAArB,YAAA4B,EAA2B,UAAW,CAAC5B,EAAS,OAAO,WAAUA,EAAS,OAAO,SAAoBS,GAAKT,EAAS,MAAM,GAEzJA,EAAS,OAAO,KAAK,WAAW6B,EAAA7B,EAAS,OAAO,KAAK,OAArB,YAAA6B,EAA8B,UAAW,CAAC7B,EAAS,OAAO,OAAMA,EAAS,OAAO,KAAYS,GAAKT,EAAS,MAAM,GAEhJA,EAAS,OAAO,KAAK,WAAW8B,EAAA9B,EAAS,OAAO,KAAK,SAArB,YAAA8B,EAAgC,UAAW,CAAC9B,EAAS,OAAO,YAAWA,EAAS,OAAO,UAAsBS,GAAKT,EAAS,MAAM,GAEjKA,EAAS,OAAO,KAAK,WAAW+B,EAAA/B,EAAS,OAAO,KAAK,SAArB,YAAA+B,EAAgC,UAAW,CAAC/B,EAAS,OAAO,eAAcA,EAAS,OAAO,aAA4BS,GAAKT,EAAS,MAAM,GAE1KA,EAAS,OAAO,KAAK,WAAWgC,EAAAhC,EAAS,OAAO,KAAK,gBAArB,YAAAgC,EAAuC,UAAW,CAAChC,EAAS,OAAO,gBAAeA,EAAS,OAAO,cAA8BS,GAAKT,EAAS,MAAM,GACpLA,EAAS,OAAO,KAAK,SAAW,CAACA,EAAS,OAAO,aAAakC,GAAAD,EAAAjC,EAAS,OAAO,KAAK,WAArB,YAAAiC,EAA+B,YAA/B,YAAAC,EAA0C,SAAS,gBAAclC,EAAS,OAAO,UAAsB2C,GAAW3C,EAAS,MAAM,GAC/LA,EAAS,OAAO,KAAK,SAAWA,EAAS,OAAO,KAAK,WAAa,CAACA,EAAS,OAAO,gBAAgBoC,GAAAD,EAAAnC,EAAS,OAAO,KAAK,WAArB,YAAAmC,EAA+B,YAA/B,YAAAC,EAA0C,SAAS,gBAAcpC,EAAS,OAAO,aAAyB4C,GAAa5C,EAAS,MAAM,GACzOA,EAAS,OAAO,OAAO,SAAW,CAACA,EAAS,OAAO,aAAasC,IAAAD,EAAArC,EAAS,OAAO,SAAhB,YAAAqC,EAAwB,YAAxB,YAAAC,GAAmC,SAAS,gBAActC,EAAS,OAAO,UAAsBS,GAAKT,EAAS,MAAM,GACpLA,EAAS,OAAO,OAAO,SAAW,CAACA,EAAS,OAAO,WAAWwC,IAAAD,EAAAvC,EAAS,OAAO,SAAhB,YAAAuC,EAAwB,YAAxB,YAAAC,GAAmC,SAAS,cAAYxC,EAAS,OAAO,QAAkBS,GAAKT,EAAS,MAAM,GAC5KA,EAAS,OAAO,aAAa,SAAW,CAACA,EAAS,OAAO,eAAcA,EAAS,OAAO,aAA4BS,GAAKT,EAAS,MAAM,GAG3I,cAAiBQ,MAAS,OAAO,KAAKR,EAAS,MAAM,EAC/CA,EAAS,OAAOQ,KAA0B,OAAOR,EAAS,OAAOQ,KAA2B,cAC9FR,EAAS,OAAOQ,IAAyB,MAAMR,EAAS,OAAOQ,IAGrE,CAEA,eAAsBqC,GAAS7C,EAAgC,CAE7D,IAAM8C,EAAY,CAAC,QAAS,cAAe,OAAQ,MAAO,UAAW,MAAO,MAAO,MAAO,KAAK,EAC/F,QAAWC,KAAW,OAAO,KAAK/C,EAAS,MAAM,EAAG,CAClD,IAAMQ,EAA2BR,EAAS,OAAO+C,GACjD,GAAI,CAACvC,EAAO,SACZ,IAAMwC,EAAgB,CAAC,EAEjBC,EAAWzC,GAAA,YAAAA,EAAO,SACxB,GAAIyC,GAAYA,EAAS,MAAM,MAC7B,QAAWC,KAAU,OAAO,OAAOD,EAAS,MAAM,KAAK,EAAG,CACxD,IAAME,EAAMD,EAAc,GAAG,YAAY,EACpCF,EAAI,SAASG,CAAE,GAAGH,EAAI,KAAKG,CAAE,CACpC,KAEI,CAACF,GAAYjD,EAAS,OAAO,OAAOoD,EAAI,kCAAmCL,CAAO,EAExF,IAAMM,EAAoB,CAAC,EAC3B,QAAWF,KAAMH,EACX,CAACF,EAAU,SAASK,CAAE,GACrB,CAACnD,EAAS,IAAI,QAAQ,SAASmD,CAAE,GACjC,CAACnD,EAAS,IAAI,QAAQ,SAASmD,EAAG,QAAQ,IAAK,EAAE,CAAC,GAClD,CAACnD,EAAS,IAAI,QAAQ,SAASmD,EAAG,QAAQ,SAAU,EAAE,CAAC,GACvD,CAACnD,EAAS,IAAI,QAAQ,SAASmD,EAAG,QAAQ,KAAM,EAAE,CAAC,GACtDE,EAAQ,KAAKF,CAAE,EAIfnD,EAAS,OAAO,OAASqD,EAAQ,OAAS,GAAGD,EAAI,2BAA4BL,EAASM,CAAO,CACnG,CACF,CyCvKO,IAAMC,EAAS,CACpB,KAAM,UACN,SAAU,IACV,OAA0B,KAC1B,GAAmC,KACnC,WAAuB,CAAC,EACxB,UAAW,CACT,MAAO,GACP,UAAW,GACX,mBAAoB,GACpB,sBAAuB,GACvB,MAAO,GACP,QAAS,GACT,6BAA8B,GAC9B,eAAgB,EAClB,CACF,EAEA,SAASC,IAAmB,CAK1B,IAAMC,EAAKF,EAAO,GACd,CAACE,IACLF,EAAO,WAAaE,EAAG,uBAAuB,EAEhD,CAOA,eAAsBC,GAASC,EAAgC,CA5C/D,IAAAC,EA8CE,GAAID,EAAS,OAAO,UAAY,YAC3BJ,EAAO,QAAW,SAAO,EAAE,WAAc,CAACA,EAAO,IAAM,CAACA,EAAO,GAAG,aAAaA,EAAO,GAAG,OAAO,KACnGM,EAAI,wCAAwC,EACrCC,GAAMH,CAAQ,GAOnB,CAAI,cAAYJ,EAAO,IAAI,GAAG,CAChC,GAAI,CACFA,EAAO,OAAS,MAAYQ,GAAO,IAAK,GAAG,CAC7C,OAASC,EAAP,CACAH,EAAI,+BAAgCG,CAAG,EACvC,MACF,CACA,GAAI,CAGF,GAFAT,EAAO,IAAKK,EAAAL,EAAO,SAAP,YAAAK,EAAe,WAAW,SAAUL,EAAO,WAEnD,CADSA,EAAO,GAAG,aAAaA,EAAO,GAAG,OAAO,EAAE,SAAS,KAAK,EAC1D,CACTM,EAAI,qEAAqE,EACzEF,EAAS,OAAO,QAAU,QAC1B,MACF,CACIJ,EAAO,SACTA,EAAO,OAAO,iBAAiB,mBAAoB,MAAOU,GAAM,CAC9D,MAAAJ,EAAI,kBAAmBI,EAAE,IAAI,EAC7BJ,EAAI,0FAA0F,EAC9FF,EAAS,KAAK,OAAO,EACf,IAAI,MAAM,mCAAmC,CAMrD,CAAC,EACDJ,EAAO,OAAO,iBAAiB,uBAAyBU,GAAM,CAC5DJ,EAAI,mCAAoCI,CAAC,CAC3C,CAAC,EACDV,EAAO,OAAO,iBAAiB,4BAA8BU,GAAM,CACjEJ,EAAI,iCAAkCI,CAAC,CACzC,CAAC,EAEL,OAASD,EAAP,CACAH,EAAI,mCAAoCG,CAAG,EAC3C,MACF,CACA,GAAI,CACC,kBAAgB,EAAGT,EAAO,EAAE,CACjC,OAASS,EAAP,CACAH,EAAI,mCAAoCG,CAAG,EAC3C,MACF,CACA,GAAI,CACF,IAAME,EAAM,IAAO,eAAaX,EAAO,EAAE,EACtC,kBAAgBA,EAAO,KAAM,IAAM,IAAO,mBAAiBW,CAAG,EAAGX,EAAO,QAAQ,CACrF,OAASS,EAAP,CACAH,EAAI,wCAAyCG,CAAG,EAChD,MACF,CACA,GAAI,CACiB,uBAAqB,OAAO,EACvC,QAASG,GAAiB,CAChC,IAAMC,EAAkB,CAAE,GAAGD,EAAc,YAAaZ,EAAO,IAAK,EACjE,iBAAea,CAAe,CACnC,CAAC,CACH,OAASJ,EAAP,CACAH,EAAI,mDAAoDG,CAAG,EAC3D,MACF,CACA,IAAMK,EAAa,UAAQ,EAAE,gBAAqB,UAAQ,EAAE,gBAAgB,EAAE,GAAK,KACnF,GAAIA,EACFR,EAAI,yBAAyBQ,EAAQ,aAAaA,EAAQ,OAAO,cAAcA,EAAQ,aAAaA,EAAQ,QAAQ,GAAG,MAClH,CACLR,EAAI,gCAAiCQ,EAASd,EAAO,EAAE,EACvD,MACF,CACA,GAAI,CACC,MAAI,IAAI,gBAAiB,CAAC,CAC/B,OAASS,EAAP,CACAH,EAAI,yCAA0CG,CAAG,EACjD,MACF,CACAR,GAAW,EACXK,EAAI,sBAAuBN,EAAO,IAAI,CACxC,CACF,CC5HA,SAASe,IAAoB,CAC3B,GAAI,CAACC,EAAI,QAAQ,SAAS,KAAK,EAAG,CAChC,IAAMC,EAAY,CAChB,WAAY,MACZ,YAAgB,aAAW,EAC3B,WAAaC,GAAU,OAAK,IAAS,MAAIA,EAAG,OAAO,EAAM,MAAO,MAAIA,EAAG,OAAO,EAAGA,EAAG,OAAO,CAAC,EAAGA,EAAG,OAAO,CAAC,CAAC,CAAC,CAC9G,EACG,iBAAeD,CAAS,EAC3BD,EAAI,QAAQ,KAAK,KAAK,CACxB,CACA,GAAI,CAACA,EAAI,QAAQ,SAAS,UAAU,EAAG,CACrC,IAAMC,EAAY,CAChB,WAAY,WACZ,YAAgB,aAAW,EAC3B,WAAaC,GAAU,OAAK,IAAS,WAASA,EAAG,OAAO,EAAIA,EAAG,OAAO,CAAC,EAAIA,EAAG,OAAO,EAAO,MAAIA,EAAG,OAAO,EAAGA,EAAG,OAAO,CAAC,CAAC,CAC3H,EACG,iBAAeD,CAAS,EAC3BD,EAAI,QAAQ,KAAK,UAAU,CAC7B,CACF,CAEA,eAAsBG,GAAMC,EAAiBC,EAAQ,GAAO,CAE1D,GADAD,EAAS,MAAQ,UACbC,GAASL,EAAI,SAAYI,EAAS,OAAO,SAAYA,EAAS,OAAO,QAAQ,OAAS,GAAU,aAAW,IAAMA,EAAS,OAAO,QAAW,CAC9I,IAAME,EAAYC,EAAI,EAEtB,GAAIH,EAAS,OAAO,SAAWA,EAAS,OAAO,QAAQ,OAAS,EAAG,CAkBjE,GAfI,OAAO,QAAW,aAAe,OAAO,mBAAsB,aAAeA,EAAS,OAAO,OAC3FA,EAAS,OAAO,OAAOI,EAAI,2BAA2B,EAIxDR,EAAI,SAAWI,EAAS,OAAO,UAAY,eACzCA,EAAS,OAAO,OAAOI,EAAI,8DAA8D,EAC7FJ,EAAS,OAAO,QAAU,WAExBJ,EAAI,OAASI,EAAS,OAAO,UAAY,SAAWA,EAAS,OAAO,UAAY,aAC9EA,EAAS,OAAO,OAAOI,EAAI,4BAA4BJ,EAAS,OAAO,iCAAiC,EAC5GA,EAAS,OAAO,QAAU,cAIxBJ,EAAI,SAAWI,EAAS,OAAO,UAAY,SAC7C,GAAI,OAAO,WAAc,aAAe,OAAO,UAAU,KAAW,YAClEI,EAAI,qEAAqE,EACzEJ,EAAS,OAAO,QAAU,cACrB,CACL,IAAMK,EAAU,MAAM,UAAU,IAAO,eAAe,EAEtD,GADIL,EAAS,OAAO,OAAOI,EAAI,6BAA8BC,CAAO,EAChE,CAACA,EACHD,EAAI,sEAAsE,EAC1EJ,EAAS,OAAO,QAAU,cACrB,CAGL,IAAMM,EAAc,uBAAwBD,EAAU,MAAOA,EAAuB,mBAAmB,EAAI,OAE3GD,EAAI,uBAAwBE,CAAW,CACzC,CACF,CAIEN,EAAS,OAAO,UAAY,WAAW,MAAcO,GAASP,CAAQ,EAC1E,IAAMQ,EAAY,OAAO,KAAQ,SAAO,EAAE,eAAe,EAYzD,GAXIR,EAAS,OAAO,OAAOI,EAAI,sBAAuBI,CAAS,EAE1DA,EAAU,SAASR,EAAS,OAAO,OAAO,IAC7CI,EAAI,kBAAkBJ,EAAS,OAAO,+BAA+B,EACrEA,EAAS,OAAO,QAAUJ,EAAI,KAAO,aAAe,QAChDI,EAAS,OAAO,OAAOI,EAAI,6BAA6BJ,EAAS,OAAO,SAAS,GAGnFA,EAAS,OAAO,OAAOI,EAAI,mBAAoBJ,EAAS,OAAO,OAAO,EAGtEA,EAAS,OAAO,UAAY,OAAQ,CACtC,GAAI,CACC,MAAI,EAAE,IAAI,gCAAiC,EAAI,CACpD,OAAQS,EAAN,CAAa,CAEf,GADIT,EAAS,OAAO,OAAOI,EAAI,aAAcJ,EAAS,OAAO,QAAQ,EACjE,OAAOU,GAAA,YAAAA,EAAI,eAAiB,YAAa,MAAS,eAAaV,EAAS,OAAO,SAAUA,EAAS,OAAO,iBAAiB,MACzH,OAAM,IAAI,MAAM,wEAAwE,EAC7F,IAAMW,EAAO,MAAS,MAAI,EAAE,SAAS,uBAAuB,EACtDC,EAAK,MAAS,MAAI,EAAE,SAAS,8BAA8B,EAC7DZ,EAAS,OAAO,OAAOI,EAAI,mBAAmBO,EAAO,OAAS,aAAaC,EAAK,gBAAkB,kBAAkB,EACpHZ,EAAS,OAAO,OAAS,CAACW,GAAMP,EAAI,2CAA2C,CACrF,CAEA,GAAI,CACF,MAAS,aAAWJ,EAAS,OAAO,OAAO,EAC3C,MAAS,QAAM,EACLa,GAAK,CACjB,OAASC,EAAP,CACA,OAAAV,EAAI,6BAA8BJ,EAAS,OAAO,QAASc,CAAG,EACvD,EACT,CACF,CAGA,GAAO,aAAW,IAAM,YACnB,MAAI,IAAI,+BAAgC,EAAK,EAC7C,MAAI,IAAI,oBAAqB,EAAI,EAEjC,MAAI,IAAI,4BAA6B,EAAI,EACzC,MAAI,IAAI,6BAA8B,GAAG,EAExC,OAAOd,EAAS,OAAO,YAAkB,aAAeA,EAAS,OAAO,aAC1EI,EAAI,kDAAmD,EAAI,EACxD,MAAI,IAAI,iCAAkC,CAAC,GAEzC,UAAQ,EAAE,iBAAiB,CAChC,IAAMW,EAAK,MAAS,UAAQ,EAAE,gBAAgB,EAAE,GAC5Cf,EAAS,OAAO,OAAOI,EAAI,cAAcW,EAAG,aAAaA,EAAG,OAAO,cAAcA,EAAG,aAAaA,EAAG,QAAQ,GAAG,CACrH,CAIK,aAAW,EAOf,iBAAe,EAClB,MAAS,QAAM,EAEff,EAAS,YAAY,YAAc,KAAK,MAAMG,EAAI,EAAID,CAAS,EAC/DF,EAAS,OAAO,QAAa,aAAW,EAExC,MAAMJ,EAAI,cAAc,EACxBD,GAAkB,CAEpB,CACA,MAAO,EACT,CAGO,SAASqB,GAAQC,EAA4BC,EAAQ,CAE1D,QAAWC,KAAcF,EAAa,CACpC,IAAMG,EAAe,CACnB,WAAAD,EACA,YAAaD,EAAO,QACpB,WAAY,IAAM,CAAMA,EAAO,OAAOd,EAAI,aAAce,EAAYD,EAAO,OAAO,CAAG,CAGvF,EACG,iBAAeE,CAAY,CAChC,CACAxB,EAAI,QAAa,uBAAwB,aAAW,CAAC,EAAE,IAAKyB,GAAWA,EAAO,WAAW,YAAY,CAAC,CACxG,CCnKA,IAAAC,GAAA,GAAAC,GAAAD,GAAA,SAAAE,GAAA,SAAAC,GAAA,WAAAC,GAAA,SAAAC,GAAA,YAAAC,GAAA,SAAAC,GAAA,WAAAC,GAAA,YAAAC,GAAA,WAAAC,KCKO,IAAMC,GAAoBC,GAAqB,CACpD,GAAI,CAACA,EAAOC,EAAI,4BAA4B,UACnC,CAACD,EAAM,WAAYC,EAAI,wCAAwC,MACnE,CACH,IAAMC,EAAMF,EAAM,WAAW,IAAI,EACjC,GAAI,CAACE,EAAKD,EAAI,uCAAuC,MAChD,QAAOC,CACd,CACA,OAAO,IACT,EAEaC,GAAWC,GAAkB,KAAK,MAAOA,EAAQ,IAAO,KAAK,EAAE,EAE/DC,GAAa,CAACC,EAAuBC,IAA6B,CAC7E,GAAI,CAACA,EAAI,UAAY,OAAOD,GAAM,YAAa,OAAOC,EAAI,MAC1D,IAAMC,EAAM,kBAAkB,KAAK,CAAC,IAAO,EAAIF,EAAI,IAAO,EAAIA,EAAI,GAAG,CAAC,EAEtE,MADc,QAAQE,EAAI,OAAOA,EAAI,OAAOA,EAAI,OAAOD,EAAI,QAE7D,EAEO,SAASE,GAAMP,EAAmEQ,EAAWC,EAAWL,EAAuBM,EAA2B,CAC/JV,EAAI,UAAYG,GAAWC,EAAGM,CAAY,EAC1CV,EAAI,UAAU,EACdA,EAAI,IAAIQ,EAAGC,EAAGC,EAAa,UAAW,EAAG,EAAI,KAAK,EAAE,EACpDV,EAAI,KAAK,CACX,CAEO,SAASW,GAAKX,EAAmEQ,EAAWC,EAAWG,EAAeC,EAAgBH,EAA2B,CAGtK,GAFAV,EAAI,UAAU,EACdA,EAAI,UAAYU,EAAa,UACzBA,EAAa,UAAW,CAC1B,IAAMI,GAAMN,EAAIA,EAAII,GAAS,EACvBG,GAAMN,EAAIA,EAAII,GAAU,EAC9Bb,EAAI,QAAQc,EAAIC,EAAIH,EAAQ,EAAGC,EAAS,EAAG,EAAG,EAAG,EAAI,KAAK,EAAE,CAC9D,MACEb,EAAI,OAAOQ,EAAIE,EAAa,UAAWD,CAAC,EACxCT,EAAI,OAAOQ,EAAII,EAAQF,EAAa,UAAWD,CAAC,EAChDT,EAAI,iBAAiBQ,EAAII,EAAOH,EAAGD,EAAII,EAAOH,EAAIC,EAAa,SAAS,EACxEV,EAAI,OAAOQ,EAAII,EAAOH,EAAII,EAASH,EAAa,SAAS,EACzDV,EAAI,iBAAiBQ,EAAII,EAAOH,EAAII,EAAQL,EAAII,EAAQF,EAAa,UAAWD,EAAII,CAAM,EAC1Fb,EAAI,OAAOQ,EAAIE,EAAa,UAAWD,EAAII,CAAM,EACjDb,EAAI,iBAAiBQ,EAAGC,EAAII,EAAQL,EAAGC,EAAII,EAASH,EAAa,SAAS,EAC1EV,EAAI,OAAOQ,EAAGC,EAAIC,EAAa,SAAS,EACxCV,EAAI,iBAAiBQ,EAAGC,EAAGD,EAAIE,EAAa,UAAWD,CAAC,EACxDT,EAAI,UAAU,EAEhBA,EAAI,OAAO,CACb,CAEO,SAASgB,GAAMhB,EAAmEiB,EAAiBP,EAA2B,CACnI,GAAI,EAAAO,EAAO,OAAS,GACpB,CAAAjB,EAAI,UAAU,EACdA,EAAI,OAAOiB,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,EACrC,QAAWC,KAAMD,EACfjB,EAAI,YAAcG,GAAWe,EAAG,IAAM,EAAGR,CAAY,EACrDV,EAAI,OAAO,KAAK,MAAMkB,EAAG,EAAE,EAAG,KAAK,MAAMA,EAAG,EAAE,CAAC,EAEjDlB,EAAI,OAAO,EACPU,EAAa,eACfV,EAAI,UAAU,EACdA,EAAI,KAAK,GAEb,CAEO,SAASmB,GAAOnB,EAAmEiB,EAAiBP,EAA2B,CACpI,GAAI,EAAAO,EAAO,OAAS,GAEpB,IADAjB,EAAI,UAAYU,EAAa,UACzB,CAACA,EAAa,WAAaO,EAAO,QAAU,EAAG,CACjDD,GAAMhB,EAAKiB,EAAQP,CAAY,EAC/B,MACF,CACAV,EAAI,OAAOiB,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,EACrC,QAASG,EAAI,EAAGA,EAAIH,EAAO,OAAS,EAAGG,IAAK,CAC1C,IAAMC,GAAMJ,EAAOG,GAAG,GAAKH,EAAOG,EAAI,GAAG,IAAM,EACzCE,GAAML,EAAOG,GAAG,GAAKH,EAAOG,EAAI,GAAG,IAAM,EAC/CpB,EAAI,iBAAiBiB,EAAOG,GAAG,GAAIH,EAAOG,GAAG,GAAIC,EAAIC,CAAE,CACzD,CACAtB,EAAI,iBAAiBiB,EAAOA,EAAO,OAAS,GAAG,GAAIA,EAAOA,EAAO,OAAS,GAAG,GAAIA,EAAOA,EAAO,OAAS,GAAG,GAAIA,EAAOA,EAAO,OAAS,GAAG,EAAE,EAC3IjB,EAAI,OAAO,EACPU,EAAa,eACfV,EAAI,UAAU,EACdA,EAAI,KAAK,GAEb,CAEO,SAASuB,GAAMvB,EAAmEwB,EAAaC,EAAWC,EAAS,EAAG,CAC3H,IAAIC,EACAnB,EACAC,EACJT,EAAI,UAAU,EACdA,EAAI,OAAOwB,EAAK,GAAIA,EAAK,EAAE,EAC3BxB,EAAI,OAAOyB,EAAG,GAAIA,EAAG,EAAE,EACvBE,EAAQ,KAAK,MAAMF,EAAG,GAAKD,EAAK,GAAIC,EAAG,GAAKD,EAAK,EAAE,EACnDhB,EAAIkB,EAAS,KAAK,IAAIC,CAAK,EAAIF,EAAG,GAClChB,EAAIiB,EAAS,KAAK,IAAIC,CAAK,EAAIF,EAAG,GAClCzB,EAAI,OAAOQ,EAAGC,CAAC,EACfkB,GAAU,EAAM,GAAQ,EAAI,KAAK,IACjCnB,EAAIkB,EAAS,KAAK,IAAIC,CAAK,EAAIF,EAAG,GAClChB,EAAIiB,EAAS,KAAK,IAAIC,CAAK,EAAIF,EAAG,GAClCzB,EAAI,OAAOQ,EAAGC,CAAC,EACfkB,GAAU,EAAM,GAAQ,EAAI,KAAK,IACjCnB,EAAIkB,EAAS,KAAK,IAAIC,CAAK,EAAIF,EAAG,GAClChB,EAAIiB,EAAS,KAAK,IAAIC,CAAK,EAAIF,EAAG,GAClCzB,EAAI,OAAOQ,EAAGC,CAAC,EACfT,EAAI,UAAU,EACdA,EAAI,OAAO,EACXA,EAAI,KAAK,CACX,CCnEO,IAAM4B,GAAuB,CAClC,MAAe,2BACf,WAAoB,yBACpB,YAAqB,QACrB,MAAO,GACP,KAAc,6BACd,WAAoB,GACpB,UAAmB,EACnB,UAAmB,EACnB,UAAmB,EACnB,WAAqB,GACrB,WAAqB,GACrB,UAAoB,GACpB,cAAwB,GACxB,aAAuB,GACvB,aAAuB,GACvB,SAAmB,GACnB,aAAuB,GACvB,SAAmB,GACnB,UAAoB,EACtB,ECzDA,IAAIC,EAEJ,SAASC,GAAWC,EAAeC,EAAmE,CACpG,GAAIH,EAAI,WAAY,CAElB,IAAMI,EAAkB,CAAC,EAOzB,GANAA,EAAO,KAAK,SAAS,KAAK,MAAM,IAAMF,EAAE,KAAK,IAAI,EAC7CA,EAAE,aAAaE,EAAO,KAAK,GAAGF,EAAE,QAAU,MAAM,KAAK,MAAM,IAAMA,EAAE,WAAW,IAAI,EAClFA,EAAE,KAAKE,EAAO,KAAK,QAAQF,EAAE,KAAO,IAAI,EACxCA,EAAE,MAAME,EAAO,KAAK,aAAaF,EAAE,MAAM,EACzCA,EAAE,MAAME,EAAO,KAAK,SAAS,KAAK,MAAM,IAAMF,EAAE,IAAI,IAAI,EACxDA,EAAE,MAAME,EAAO,KAAK,SAAS,KAAK,MAAM,IAAMF,EAAE,IAAI,IAAI,EACxDA,EAAE,SAAWA,EAAE,QAAQ,OAAS,EAAG,CACrC,IAAMG,EAAUH,EAAE,QAAQ,IAAKI,GAAM,GAAG,KAAK,MAAM,IAAMA,EAAE,KAAK,MAAMA,EAAE,SAAS,EAC7ED,EAAQ,OAAS,IAAGA,EAAQ,OAAS,GACzCD,EAAO,KAAKC,EAAQ,KAAK,GAAG,CAAC,CAC/B,CACIH,EAAE,UAAYA,EAAE,SAAS,OAASA,EAAE,SAAS,OAC3CA,EAAE,SAAS,MAAM,MAAME,EAAO,KAAK,SAASG,GAAQL,EAAE,SAAS,MAAM,IAAI,aAAUK,GAAQL,EAAE,SAAS,MAAM,GAAG,eAAYK,GAAQL,EAAE,SAAS,MAAM,KAAK,OAAI,EAC7JA,EAAE,SAAS,KAAK,SAASE,EAAO,KAAK,SAASG,GAAQL,EAAE,SAAS,KAAK,OAAO,OAAI,GAEnFE,EAAO,SAAW,GAAGA,EAAO,KAAK,MAAM,EAC3CD,EAAI,UAAYH,EAAI,MACpB,QAASQ,EAAIJ,EAAO,OAAS,EAAGI,GAAK,EAAGA,IAAK,CAC3C,IAAMC,EAAI,KAAK,IAAIP,EAAE,IAAI,GAAI,CAAC,EACxBQ,EAAIF,EAAIR,EAAI,WAAaE,EAAE,IAAI,GACjCF,EAAI,aAAeA,EAAI,cAAgB,KACzCG,EAAI,UAAYH,EAAI,YACpBG,EAAI,SAASC,EAAOI,GAAIC,EAAI,EAAGC,EAAI,EAAE,GAEvCP,EAAI,UAAYH,EAAI,WACpBG,EAAI,SAASC,EAAOI,GAAIC,EAAI,EAAGC,EAAI,EAAE,CACvC,CACF,CACF,CAEA,SAASC,GAAeT,EAAeC,EAAmE,CAExG,GAAID,EAAE,aAAeA,EAAE,YAAY,aAAkBA,EAAE,YAAY,YAAe,GAAI,CACpFC,EAAI,YAAcH,EAAI,SAAW,2BAA6BA,EAAI,MAClEG,EAAI,UAAU,EACd,IAAMS,EAAQ,KAAK,IAAIV,EAAE,YAAY,YAAe,GAAG,GAAKA,EAAE,YAAY,YAAe,GAAG,EAAE,EAAI,EAC5FW,EAAQ,KAAK,IAAIX,EAAE,YAAY,YAAe,GAAG,GAAKA,EAAE,YAAY,YAAe,GAAG,EAAE,EAAI,EAClGC,EAAI,QAAQD,EAAE,YAAY,YAAe,GAAG,GAAIA,EAAE,YAAY,YAAe,GAAG,GAAIU,EAAOC,EAAO,EAAG,EAAG,EAAI,KAAK,EAAE,EACnHV,EAAI,OAAO,EACPH,EAAI,eACNG,EAAI,UAAYH,EAAI,SAAW,2BAA6BA,EAAI,MAChEG,EAAI,KAAK,EAEb,CACA,GAAID,EAAE,aAAeA,EAAE,YAAY,cAAmBA,EAAE,YAAY,aAAgB,GAAI,CACtFC,EAAI,YAAcH,EAAI,SAAW,2BAA6BA,EAAI,MAClEG,EAAI,UAAU,EACd,IAAMS,EAAQ,KAAK,IAAIV,EAAE,YAAY,aAAgB,GAAG,GAAKA,EAAE,YAAY,aAAgB,GAAG,EAAE,EAAI,EAC9FW,EAAQ,KAAK,IAAIX,EAAE,YAAY,aAAgB,GAAG,GAAKA,EAAE,YAAY,aAAgB,GAAG,EAAE,EAAI,EACpGC,EAAI,QAAQD,EAAE,YAAY,aAAgB,GAAG,GAAIA,EAAE,YAAY,aAAgB,GAAG,GAAIU,EAAOC,EAAO,EAAG,EAAG,EAAI,KAAK,EAAE,EACrHV,EAAI,OAAO,EACPH,EAAI,eACNG,EAAI,UAAYH,EAAI,SAAW,2BAA6BA,EAAI,MAChEG,EAAI,KAAK,EAEb,CACF,CAEA,SAASW,GAAgBZ,EAAeC,EAAmE,CAxE3G,IAAAY,EAyEE,GAAIf,EAAI,YAAYe,EAAAb,EAAE,WAAF,YAAAa,EAAY,QAAS,OAAO,QAAW,YAAa,CACtEZ,EAAI,YAAc,OAClB,IAAMa,EAAQd,EAAE,IAAI,GAAKA,EAAE,IAAI,GAAK,EAAMA,EAAE,IAAI,GAAKK,GAAQL,EAAE,SAAS,MAAM,GAAG,EAAI,GAC/Ee,EAAQf,EAAE,IAAI,GAAKA,EAAE,IAAI,GAAK,EAAMA,EAAE,IAAI,GAAKK,GAAQL,EAAE,SAAS,MAAM,KAAK,EAAI,GACjFgB,EAAQ,IAAI,OAAO;AAAA,UACnBhB,EAAE,IAAI,GAAKA,EAAE,IAAI,GAAK,KAAKA,EAAE,IAAI;AAAA;AAAA,UAEjCc,KAAQd,EAAE,IAAI;AAAA,UACdc,KAAQd,EAAE,IAAI,GAAKA,EAAE,IAAI;AAAA,UACzBA,EAAE,IAAI,GAAKA,EAAE,IAAI,GAAK,KAAKA,EAAE,IAAI,GAAKA,EAAE,IAAI;AAAA,KACjD,EACKiB,EAAQ,IAAI,OAAO;AAAA,UACnBjB,EAAE,IAAI,MAAMA,EAAE,IAAI,GAAKA,EAAE,IAAI,GAAK;AAAA;AAAA,UAElCA,EAAE,IAAI,MAAMe;AAAA,UACZf,EAAE,IAAI,GAAKA,EAAE,IAAI,MAAMe;AAAA,UACvBf,EAAE,IAAI,GAAKA,EAAE,IAAI,MAAMA,EAAE,IAAI,GAAKA,EAAE,IAAI,GAAK;AAAA,KAClD,EACDC,EAAI,OAAOgB,CAAK,EAChBhB,EAAI,OAAOe,CAAK,CAClB,CACF,CAEA,SAASE,GAAelB,EAAeC,EAAmE,CAhG1G,IAAAY,EAAAM,EAAAC,EAAAC,EAiGE,GAAIvB,EAAI,YAAYqB,GAAAN,EAAAb,EAAE,WAAF,YAAAa,EAAY,OAAZ,YAAAM,EAAkB,aAAYE,GAAAD,EAAApB,EAAE,WAAF,YAAAoB,EAAY,OAAZ,YAAAC,EAAkB,UAAWrB,EAAE,YAAY,aAAkBA,EAAE,YAAY,cAAmBA,EAAE,YAAY,YAAe,IAAMA,EAAE,YAAY,aAAgB,GAAI,CACnNC,EAAI,YAAc,OAClBA,EAAI,UAAY,OAChB,IAAMqB,EAAW,CACftB,EAAE,YAAY,YAAe,GAAG,GAAM,KAAK,IAAIA,EAAE,SAAS,KAAK,OAAO,EAAIA,EAAE,SAAS,KAAK,SAAWA,EAAE,IAAI,GAC3GA,EAAE,YAAY,YAAe,GAAG,GAAM,KAAK,IAAIA,EAAE,SAAS,KAAK,OAAO,EAAIA,EAAE,SAAS,KAAK,SAAWA,EAAE,IAAI,EAC7G,EACAuB,GAAMtB,EAAK,CAACD,EAAE,YAAY,YAAe,GAAG,GAAIA,EAAE,YAAY,YAAe,GAAG,EAAE,EAAG,CAACsB,EAAS,GAAIA,EAAS,EAAE,EAAG,CAAC,EAClH,IAAME,EAAY,CAChBxB,EAAE,YAAY,aAAgB,GAAG,GAAM,KAAK,IAAIA,EAAE,SAAS,KAAK,OAAO,EAAIA,EAAE,SAAS,KAAK,SAAWA,EAAE,IAAI,GAC5GA,EAAE,YAAY,aAAgB,GAAG,GAAM,KAAK,IAAIA,EAAE,SAAS,KAAK,OAAO,EAAIA,EAAE,SAAS,KAAK,SAAWA,EAAE,IAAI,EAC9G,EACAuB,GAAMtB,EAAK,CAACD,EAAE,YAAY,aAAgB,GAAG,GAAIA,EAAE,YAAY,aAAgB,GAAG,EAAE,EAAG,CAACwB,EAAU,GAAIA,EAAU,EAAE,EAAG,CAAC,CACxH,CACF,CAEA,SAASC,GAAiBzB,EAAeC,EAAmE,CAC1G,GAAIH,EAAI,cAAgBE,EAAE,KAAK,QAAU,IAAK,CAC5CC,EAAI,UAAY,EAChB,QAASK,EAAI,EAAGA,EAAIoB,GAAc,OAAS,EAAGpB,IAAK,CACjD,IAAMqB,EAAS,CAACD,GAAcpB,EAAI,EAAI,GAAIoB,GAAcpB,EAAI,EAAI,GAAIoB,GAAcpB,EAAI,EAAI,EAAE,EAAE,IAAKsB,GAAU5B,EAAE,KAAK4B,EAAM,EAC1HC,GAAM5B,EAAK0B,EAAQ7B,CAAG,CACxB,CACAW,GAAeT,EAAGC,CAAG,CACvB,CAQF,CAEA,SAAS6B,GAAe9B,EAAeC,EAAmE,CACxG,GAAIH,EAAI,YAAcE,EAAE,KAAK,QAAU,IACrC,QAASM,EAAI,EAAGA,EAAIN,EAAE,KAAK,OAAQM,IACjCyB,GAAM9B,EAAKD,EAAE,KAAKM,GAAG,GAAIN,EAAE,KAAKM,GAAG,GAAIN,EAAE,KAAKM,GAAG,GAAIR,CAAG,EACpDA,EAAI,gBACgBkC,GAAiC,SAAS1B,CAAC,GAAGyB,GAAM9B,EAAKD,EAAE,KAAKM,GAAG,GAAIN,EAAE,KAAKM,GAAG,GAAKN,EAAE,KAAKM,GAAG,GAAgB,IAAKR,CAAG,EACxHmC,GAAqC,SAAS3B,CAAC,GAAGyB,GAAM9B,EAAKD,EAAE,KAAKM,GAAG,GAAIN,EAAE,KAAKM,GAAG,GAAKN,EAAE,KAAKM,GAAG,GAAgB,IAAKR,CAAG,EAC5HoC,GAAsC,SAAS5B,CAAC,GAAGyB,GAAM9B,EAAKD,EAAE,KAAKM,GAAG,GAAIN,EAAE,KAAKM,GAAG,GAAKN,EAAE,KAAKM,GAAG,GAAgB,IAAKR,CAAG,EAI3J,CAEA,SAASqC,GAAcnC,EAAeC,EAAK,CACrCH,EAAI,WACNsC,GAAKnC,EAAKD,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIF,CAAG,CAEzD,CAGA,eAAsBuC,GAAKC,EAAqBC,EAA2BC,EAAoC,CAE7G,GADA1C,EAAM2C,EAAUC,GAASF,CAAW,EAChC,CAACD,GAAU,CAACD,EAAU,OAC1B,IAAMrC,EAAM0C,GAAiBL,CAAQ,EACrC,GAAI,EAACrC,EACL,CAAAA,EAAI,KAAOH,EAAI,KACfG,EAAI,YAAcH,EAAI,MACtBG,EAAI,UAAYH,EAAI,MACpB,QAAWE,KAAKuC,EACdJ,GAAcnC,EAAGC,CAAG,EACpBF,GAAWC,EAAGC,CAAG,EACbD,EAAE,MAAQA,EAAE,KAAK,OAAS,IAC5B8B,GAAe9B,EAAGC,CAAG,EACrBwB,GAAiBzB,EAAGC,CAAG,EACvBW,GAAgBZ,EAAGC,CAAG,EACtBiB,GAAelB,EAAGC,CAAG,GAG3B,CClKA,eAAsB2C,GAAKC,EAAqBC,EAA2BC,EAAoC,CAP/G,IAAAC,EAQE,IAAMC,EAAeC,EAAUC,GAASJ,CAAW,EACnD,GAAI,CAACD,GAAU,CAACD,EAAU,OAC1B,IAAMO,EAAMC,GAAiBR,CAAQ,EACrC,GAAI,EAACO,EACL,CAAAA,EAAI,SAAW,QACf,QAASE,EAAI,EAAGA,EAAIR,EAAO,OAAQQ,IAAK,CAgBtC,GAfAF,EAAI,YAAcH,EAAa,MAC/BG,EAAI,UAAYH,EAAa,MAC7BG,EAAI,UAAYH,EAAa,UAC7BG,EAAI,KAAOH,EAAa,KACpBA,EAAa,WAAaH,EAAOQ,GAAG,OAAON,EAAAF,EAAOQ,GAAG,MAAV,YAAAN,EAAe,UAAW,IACvEO,GAAKH,EAAKN,EAAOQ,GAAG,IAAI,GAAIR,EAAOQ,GAAG,IAAI,GAAIR,EAAOQ,GAAG,IAAI,GAAIR,EAAOQ,GAAG,IAAI,GAAIL,CAAY,EAC1FA,EAAa,aACXA,EAAa,aAAeA,EAAa,cAAgB,KAC3DG,EAAI,UAAYH,EAAa,YAC7BG,EAAI,SAAS,QAAQ,IAAMN,EAAOQ,GAAG,SAAUR,EAAOQ,GAAG,IAAI,GAAK,EAAG,EAAIR,EAAOQ,GAAG,IAAI,GAAKL,EAAa,WAAYH,EAAOQ,GAAG,IAAI,EAAE,GAEvIF,EAAI,UAAYH,EAAa,WAC7BG,EAAI,SAAS,QAAQ,IAAMN,EAAOQ,GAAG,SAAUR,EAAOQ,GAAG,IAAI,GAAK,EAAG,EAAIR,EAAOQ,GAAG,IAAI,GAAKL,EAAa,WAAYH,EAAOQ,GAAG,IAAI,EAAE,IAGrIL,EAAa,YAAcH,EAAOQ,GAAG,UACvC,QAASE,EAAK,EAAGA,EAAKV,EAAOQ,GAAG,UAAU,OAAQE,IAC5C,CAACV,EAAOQ,GAAG,UAAUE,GAAI,OAAUV,EAAOQ,GAAG,UAAUE,GAAI,QAAU,IACzEJ,EAAI,UAAYK,GAAWX,EAAOQ,GAAG,UAAUE,GAAI,SAAS,GAAIP,CAAY,EAC5ES,GAAMN,EAAKN,EAAOQ,GAAG,UAAUE,GAAI,SAAS,GAAIV,EAAOQ,GAAG,UAAUE,GAAI,SAAS,GAAI,EAAGP,CAAY,GAGxG,GAAIA,EAAa,YAAcH,EAAOQ,GAAG,UAAW,CAClDF,EAAI,KAAOH,EAAa,KACxB,QAAWO,KAAMV,EAAOQ,GAAG,UACrB,CAACE,EAAG,OAAUA,EAAG,QAAU,IAC/BJ,EAAI,UAAYK,GAAWD,EAAG,SAAS,GAAIP,CAAY,EACvDG,EAAI,SAAS,GAAGI,EAAG,QAAQ,KAAK,MAAM,IAAMA,EAAG,KAAK,KAAMA,EAAG,SAAS,GAAK,EAAGA,EAAG,SAAS,GAAK,CAAC,EAEpG,CACA,GAAIP,EAAa,cAAgBH,EAAOQ,GAAG,WAAaR,EAAOQ,GAAG,YAChE,QAAWK,KAAQ,OAAO,OAAOb,EAAOQ,GAAG,WAAW,EACpD,QAAWM,KAAaD,EAAME,GAAOT,EAAKQ,EAAWX,CAAY,CAGvE,EACF,CC3CA,eAAsBa,GAAKC,EAAqBC,EAA2BC,EAAoC,CAC7G,IAAMC,EAAeC,EAAUC,GAASH,CAAW,EACnD,GAAI,CAACD,GAAU,CAACD,EAAU,OAC1B,IAAMM,EAAMC,GAAiBP,CAAQ,EACrC,GAAI,EAACM,EACL,CAAAA,EAAI,SAAW,QACfA,EAAI,KAAOH,EAAa,KACxB,QAAWK,KAAKP,EAAQ,CAetB,GAdIE,EAAa,YACfG,EAAI,YAAcH,EAAa,MAC/BG,EAAI,UAAYH,EAAa,MAC7BM,GAAKH,EAAKE,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIL,CAAY,EAC1DA,EAAa,aACXA,EAAa,aAAeA,EAAa,cAAgB,KAC3DG,EAAI,UAAYH,EAAa,YAC7BG,EAAI,SAAS,QAAQ,KAAK,MAAM,IAAME,EAAE,KAAK,KAAMA,EAAE,IAAI,GAAK,EAAG,EAAIA,EAAE,IAAI,GAAKL,EAAa,WAAYK,EAAE,IAAI,EAAE,GAEnHF,EAAI,UAAYH,EAAa,WAC7BG,EAAI,SAAS,QAAQ,KAAK,MAAM,IAAME,EAAE,KAAK,KAAMA,EAAE,IAAI,GAAK,EAAG,EAAIA,EAAE,IAAI,GAAKL,EAAa,WAAYK,EAAE,IAAI,EAAE,GAEnHF,EAAI,OAAO,GAETH,EAAa,YACXK,EAAE,WAAaA,EAAE,UAAU,OAAS,EACtC,QAAWE,KAAMF,EAAE,UACjBF,EAAI,UAAYK,GAAWD,EAAG,GAAIP,CAAY,EAC9CS,GAAMN,EAAKI,EAAG,GAAIA,EAAG,GAAI,EAAGP,CAAY,EAI9C,GAAIA,EAAa,YAAcK,EAAE,YAAa,CAC5C,IAAMK,EAAe,CAACC,EAAoBC,IAAkB,CAC1D,GAAI,CAACD,GAAQA,EAAK,SAAW,GAAK,CAACA,EAAK,GAAI,OAC5C,IAAME,EAAIF,EAAKA,EAAK,OAAS,GAAG,IAAM,KACtCR,EAAI,UAAYK,GAAWK,EAAGb,CAAY,EAC1CG,EAAI,SAASS,EAAOD,EAAKA,EAAK,OAAS,GAAG,GAAK,EAAGA,EAAKA,EAAK,OAAS,GAAG,GAAK,CAAC,CAChF,EACAR,EAAI,KAAOH,EAAa,KACxBU,EAAaL,EAAE,YAAY,MAAU,OAAO,EAC5CK,EAAaL,EAAE,YAAY,OAAW,QAAQ,EAC9CK,EAAaL,EAAE,YAAY,KAAS,MAAM,EAC1CK,EAAaL,EAAE,YAAY,MAAU,OAAO,EAC5CK,EAAaL,EAAE,YAAY,MAAU,OAAO,EAC5CK,EAAaL,EAAE,YAAY,KAAS,MAAM,CAC5C,CACA,GAAIL,EAAa,cAAgBK,EAAE,YAAa,CAC9C,IAAMS,EAAeH,GAAuB,CAC1C,GAAI,GAACA,GAAQA,EAAK,SAAW,GAAK,CAACA,EAAK,IACxC,QAASI,EAAI,EAAGA,EAAIJ,EAAK,OAAQI,IAAK,CACpCZ,EAAI,UAAU,EACd,IAAMU,EAAIF,EAAKI,GAAG,IAAM,EACxBZ,EAAI,YAAcK,GAAWO,EAAIF,EAAGb,CAAY,EAChDG,EAAI,OAAOQ,EAAKI,EAAI,EAAIA,EAAI,EAAI,GAAG,GAAIJ,EAAKI,EAAI,EAAIA,EAAI,EAAI,GAAG,EAAE,EACjEZ,EAAI,OAAOQ,EAAKI,GAAG,GAAIJ,EAAKI,GAAG,EAAE,EACjCZ,EAAI,OAAO,CACb,CACF,EACAA,EAAI,UAAYH,EAAa,UAC7Bc,EAAYT,EAAE,YAAY,KAAQ,EAClCS,EAAYT,EAAE,YAAY,MAAS,EACnCS,EAAYT,EAAE,YAAY,IAAO,EACjCS,EAAYT,EAAE,YAAY,KAAQ,EAClCS,EAAYT,EAAE,YAAY,KAAQ,CAEpC,CACF,EACF,CClEA,eAAsBW,GAAOC,EAAqBC,EAA6BC,EAAoC,CACjH,IAAMC,EAAeC,EAAUC,GAASH,CAAW,EACnD,GAAI,CAACD,GAAU,CAACD,EAAU,OAC1B,IAAMM,EAAMC,GAAiBP,CAAQ,EACrC,GAAI,EAACM,EACL,CAAAA,EAAI,SAAW,QACfA,EAAI,KAAOH,EAAa,KACxB,QAAWK,KAAKP,EACd,GAAIE,EAAa,UAAW,CAI1B,GAHAG,EAAI,YAAcH,EAAa,MAC/BG,EAAI,UAAYH,EAAa,MAC7BM,GAAKH,EAAKE,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIL,CAAY,EAC1DA,EAAa,WAAY,CAC3B,IAAMO,EAAQ,GAAGF,EAAE,SAAS,KAAK,MAAM,IAAMA,EAAE,KAAK,KAChDL,EAAa,aAAeA,EAAa,cAAgB,KAC3DG,EAAI,UAAYH,EAAa,YAC7BG,EAAI,SAASI,EAAOF,EAAE,IAAI,GAAK,EAAG,EAAIA,EAAE,IAAI,GAAKL,EAAa,WAAYK,EAAE,IAAI,EAAE,GAEpFF,EAAI,UAAYH,EAAa,WAC7BG,EAAI,SAASI,EAAOF,EAAE,IAAI,GAAK,EAAG,EAAIA,EAAE,IAAI,GAAKL,EAAa,WAAYK,EAAE,IAAI,EAAE,CACpF,CACAF,EAAI,OAAO,CACb,EAEJ,CCxBA,eAAsBK,GAAQC,EAAqBC,EAA8BC,EAAoC,CACnH,IAAMC,EAAeC,EAAUC,GAASH,CAAW,EACnD,GAAI,GAACD,GAAU,CAACD,IACZG,EAAa,aAAc,CAC7B,IAAMG,EAAMC,GAAiBP,CAAQ,EACrC,GAAI,CAACM,EAAK,OACVA,EAAI,KAAOH,EAAa,KACxBG,EAAI,UAAYH,EAAa,MAC7B,IAAIK,EAAI,EACR,QAASC,EAAI,EAAGA,EAAIR,EAAO,OAAQQ,IAAK,CACtC,IAAIC,EAAmB,CAAC,EACpBC,EAAkB,CAAC,EAEvB,GADA,CAACD,EAAOC,CAAI,EAAI,OAAO,QAAQV,EAAOQ,EAAE,EACnCE,EAAK,OAAS,GAAQA,EAAK,GAAc,OAAS,EAAI,CACzD,IAAMC,EAAMF,EAAM,GAAe,EAAI,IAAIA,EAAM,KAAO,GAChDG,EAAQ,GAAGH,EAAM,MAAME,MAAQD,EAAK,KACtCR,EAAa,aAAeA,EAAa,cAAgB,KAC3DG,EAAI,UAAYH,EAAa,YAC7BG,EAAI,SAASO,EAAO,EAAG,EAAKL,EAAIL,EAAa,UAAW,GAE1DG,EAAI,UAAYH,EAAa,WAC7BG,EAAI,SAASO,EAAO,EAAG,EAAKL,EAAIL,EAAa,UAAW,EACxDK,GAAK,CACP,CACF,CACF,CACF,CPjBA,IAAIM,GAAW,EAUf,eAAsBC,GAAOC,EAAqBC,EAA6BC,EAAoC,CACjH,IAAMC,EAAeC,EAAUC,GAASH,CAAW,EACnD,GAAI,CAACD,GAAU,CAACD,EAAU,OAC1B,IAAMM,EAAMC,GAAiBP,CAAQ,EACrC,GAAI,EAACM,EACL,CAAAA,EAAI,SAAW,QACfA,EAAI,KAAOH,EAAa,KAExB,QAASK,EAAI,EAAGA,EAAIP,EAAO,OAAQO,IACjC,GAAIL,EAAa,UAAW,CAI1B,GAHAG,EAAI,YAAcH,EAAa,MAC/BG,EAAI,UAAYH,EAAa,MAC7BM,GAAKH,EAAKL,EAAOO,GAAG,IAAI,GAAIP,EAAOO,GAAG,IAAI,GAAIP,EAAOO,GAAG,IAAI,GAAIP,EAAOO,GAAG,IAAI,GAAIL,CAAY,EAC1FA,EAAa,WAAY,CAC3B,IAAMO,EAAQ,WAAWF,IACrBL,EAAa,aAAeA,EAAa,cAAgB,KAC3DG,EAAI,UAAYH,EAAa,YAC7BG,EAAI,SAASI,EAAOT,EAAOO,GAAG,IAAI,GAAK,EAAG,EAAIP,EAAOO,GAAG,IAAI,GAAKL,EAAa,WAAYF,EAAOO,GAAG,IAAI,EAAE,GAE5GF,EAAI,UAAYH,EAAa,WAC7BG,EAAI,SAASI,EAAOT,EAAOO,GAAG,IAAI,GAAK,EAAG,EAAIP,EAAOO,GAAG,IAAI,GAAKL,EAAa,WAAYF,EAAOO,GAAG,IAAI,EAAE,CAC5G,CACAF,EAAI,OAAO,CACb,EAEJ,CAGA,eAAsBK,GAAOC,EAAwDC,EAAmB,CACtG,GAAI,CAACD,GAAS,CAACC,EAAQ,OACvB,IAAMP,EAAMC,GAAiBM,CAAM,EAC/B,CAACP,GACLA,EAAI,UAAUM,EAAO,EAAG,CAAC,CAC3B,CAGA,eAAsBE,GAAId,EAAqBC,EAAgBC,EAAoC,CACjG,GAAI,CAACD,GAAU,CAACA,EAAO,aAAe,CAACA,GAAU,CAACD,EAAU,OAAO,KACnE,IAAMe,EAAYC,EAAI,EAChBb,EAAeC,EAAUC,GAASH,CAAW,EAC7Ce,EAAU,QAAQ,IAAI,CAC1BC,GAAKlB,EAAUC,EAAO,KAAME,CAAY,EACxCgB,GAAKnB,EAAUC,EAAO,KAAME,CAAY,EACxCiB,GAAKpB,EAAUC,EAAO,KAAME,CAAY,EACxCkB,GAAOrB,EAAUC,EAAO,OAAQE,CAAY,EAC5CmB,GAAQtB,EAAUC,EAAO,QAASE,CAAY,CAEhD,CAAC,EACD,OAAAL,GAAWyB,EAAI,QAAUzB,GAAW,KAAK,MAAMkB,EAAI,EAAID,CAAS,EAAI,KAAK,MAAMC,EAAI,EAAID,CAAS,EAChGd,EAAO,YAAY,KAAOH,GACnBmB,CACT,CQxEA,IAAMO,GAAa,GACbC,GAAQ,GAGd,SAASC,GAAWC,EAAWC,EAAWC,EAAmD,CAC3F,IAAIC,EAAS,GACTC,EAAIF,EAAQ,OAAS,EACzB,QAASG,EAAI,EAAGA,EAAIH,EAAQ,OAAQE,EAAIC,IAChCH,EAAQG,GAAG,EAAIJ,GAAQC,EAAQE,GAAG,EAAIH,GAAQD,GAAKE,EAAQE,GAAG,EAAIF,EAAQG,GAAG,IAAMJ,EAAIC,EAAQG,GAAG,IAAMH,EAAQE,GAAG,EAAIF,EAAQG,GAAG,GAAKH,EAAQG,GAAG,IAAIF,EAAS,CAACA,GAExK,OAAOA,CACT,CAEA,eAAsBG,GAAKC,EAA+C,CAExE,GADI,CAACA,EAAK,QACN,CAACA,EAAK,MAAQA,EAAK,KAAK,OAAS,IAAK,OAAOA,EAAK,OACtD,IAAMC,EAAQD,EAAK,OAAO,MAAM,IAAM,EAChCE,EAASF,EAAK,OAAO,MAAM,IAAM,EACjCG,EAAS,MAAMH,EAAK,OAAO,OAAO,EACpCI,EAA8C,CAAC,EACnD,QAAWC,KAAMC,GAAgB,WAAYF,EAAW,KAAK,CAAE,GAAIJ,EAAK,KAAKK,GAAI,GAAKL,EAAK,IAAI,IAAMA,EAAK,IAAI,GAAI,GAAIA,EAAK,KAAKK,GAAI,GAAKL,EAAK,IAAI,IAAMA,EAAK,IAAI,EAAG,CAAC,EACjKV,IAAcA,GAAa,IAAGc,EAAaA,EAAW,IAAKC,IAAQ,CAAE,EAAGA,EAAG,EAAI,GAAMA,EAAG,EAAIf,GAAae,EAAG,EAAIf,GAAY,EAAGe,EAAG,EAAI,GAAMA,EAAG,EAAIf,GAAae,EAAG,EAAIf,EAAW,EAAE,GACxL,QAASG,EAAI,EAAGA,EAAIQ,EAAOR,IACzB,QAASC,EAAI,EAAGA,EAAIQ,EAAQR,IACXF,GAAWC,EAAIQ,EAAOP,EAAIO,EAAOG,CAAU,IAExDD,EAAO,IAAIZ,GAAQY,EAAO,IAAI,EAAGT,EAAGD,EAAG,CAAC,EAAG,EAAGC,EAAGD,EAAG,CAAC,EACrDU,EAAO,IAAIZ,GAAQY,EAAO,IAAI,EAAGT,EAAGD,EAAG,CAAC,EAAG,EAAGC,EAAGD,EAAG,CAAC,EACrDU,EAAO,IAAIZ,GAAQY,EAAO,IAAI,EAAGT,EAAGD,EAAG,CAAC,EAAG,EAAGC,EAAGD,EAAG,CAAC,GAI3D,IAAMc,EAASJ,EAAO,SAAS,EAC/B,OAAG,UAAQA,CAAM,EACVI,CACT,CCpCA,IAAMC,GAAiBC,GAA4D,CACjF,IAAMC,EAAU,CAACC,EAAYC,IAAe,KAAK,MAAMD,EAAI,GAAKC,EAAI,GAAID,EAAI,GAAKC,EAAI,EAAE,EACvF,GAAI,CAACH,EAAK,YAAY,cAAmB,CAACA,EAAK,YAAY,YAAgB,MAAO,CAAE,QAAS,EAAG,SAAU,CAAE,EAE5G,IAAMI,EAAa,CAAC,EAAG,GAAI,EACrBC,EAAW,EAEXC,GAAQN,EAAK,KAAK,IAAI,IAAM,IAAMA,EAAK,KAAK,KAAK,IAAM,GACvDO,EAAaD,EAAON,EAAK,KAAK,KAAOA,EAAK,KAAK,KAC/CQ,EAAYF,EACd,EAAEN,EAAK,KAAK,KAAK,GAAKA,EAAK,KAAK,IAAI,IAAM,GAAIA,EAAK,KAAK,KAAK,GAAKA,EAAK,KAAK,IAAI,IAAM,CAAC,EACvF,EAAEA,EAAK,KAAK,KAAK,GAAKA,EAAK,KAAK,KAAK,IAAM,GAAIA,EAAK,KAAK,KAAK,GAAKA,EAAK,KAAK,KAAK,IAAM,CAAC,EACvFS,EAAUH,EACZ,CAACN,EAAK,KAAK,KAAK,GAAKA,EAAK,KAAK,IAAI,GAAIA,EAAK,KAAK,IAAI,GAAKA,EAAK,KAAK,IAAI,EAAE,EAC1E,CAACA,EAAK,KAAK,KAAK,GAAKA,EAAK,KAAK,KAAK,GAAIA,EAAK,KAAK,KAAK,GAAKA,EAAK,KAAK,KAAK,EAAE,EAC3EU,EAAiB,EACpBF,EAAU,GAAKD,EAAW,IAAME,EAAQ,GAAKL,EAAW,GACzDC,GAAYE,EAAW,GAAKC,EAAU,IAAMC,EAAQ,GAAKL,EAAW,EACtE,EACIO,EAAW,KAAK,KAAMD,EAAQ,GAAKA,EAAQ,GAAOA,EAAQ,GAAKA,EAAQ,EAAG,EAC9E,OAAAC,EAAW,KAAK,IAAIA,EAAUX,EAAK,OAAO,GAAK,EAAGA,EAAK,OAAO,GAAK,CAAC,EAE7D,CAAE,SADQC,EAAQ,CAAC,EAAG,CAAC,EAAGS,CAAO,EAAK,KAAK,GAAK,GAAM,KAAK,GAChD,SAAAC,CAAS,CAC7B,EAEaC,GAAqB,CAACZ,EAAkBa,IAIhD,CAEH,IAAMC,EAAaC,GAAsB,CACvC,IAAMC,EAAS,KAAK,KAAKD,EAAE,GAAKA,EAAE,GAAKA,EAAE,GAAKA,EAAE,GAAKA,EAAE,GAAKA,EAAE,EAAE,EAChE,OAAAA,EAAE,IAAMC,EACRD,EAAE,IAAMC,EACRD,EAAE,IAAMC,EACDD,CACT,EACME,EAAa,CAACC,EAAWC,IAAsB,CACnD,IAAMC,EAAIF,EAAE,GAAKC,EAAE,GACbE,EAAIH,EAAE,GAAKC,EAAE,GACbG,EAAIJ,EAAE,GAAKC,EAAE,GACnB,MAAO,CAACC,EAAGC,EAAGC,CAAC,CACjB,EACMC,EAAe,CAACL,EAAWC,IAAsB,CACrD,IAAMC,EAAIF,EAAE,GAAKC,EAAE,GAAKD,EAAE,GAAKC,EAAE,GAC3BE,EAAIH,EAAE,GAAKC,EAAE,GAAKD,EAAE,GAAKC,EAAE,GAC3BG,EAAIJ,EAAE,GAAKC,EAAE,GAAKD,EAAE,GAAKC,EAAE,GACjC,MAAO,CAACC,EAAGC,EAAGC,CAAC,CACjB,EAEME,EAA8BC,GAA8D,CAEhG,GAAM,CAACC,EAAKC,EAAMC,EAAMC,EAAKC,EAAKC,EAAKC,EAAKC,EAAKC,CAAG,EAAIT,EACpDU,EACAC,EACAC,EACJ,OAAIR,EAAM,EACJA,EAAM,IACRQ,EAAS,KAAK,KAAKR,CAAG,EACtBO,EAAS,KAAK,MAAM,CAACJ,EAAKN,CAAG,EAC7BS,EAAS,KAAK,MAAM,CAACJ,EAAKD,CAAG,IAE7BO,EAAS,CAAC,KAAK,GAAK,EACpBD,EAAS,CAAC,KAAK,MAAMH,EAAKC,CAAG,EAC7BC,EAAS,IAGXE,EAAS,KAAK,GAAK,EACnBD,EAAS,KAAK,MAAMH,EAAKC,CAAG,EAC5BC,EAAS,GAEP,MAAMA,CAAM,IAAGA,EAAS,GACxB,MAAMC,CAAM,IAAGA,EAAS,GACxB,MAAMC,CAAM,IAAGA,EAAS,GACrB,CAAE,MAAO,EAAI,CAACF,EAAQ,IAAK,EAAI,CAACC,EAAQ,KAAM,EAAI,CAACC,CAAO,CACnE,EAcMC,EAAOtC,EAAK,QAClB,GAAI,CAACsC,GAAQA,EAAK,OAAS,IAAK,MAAO,CAAE,MAAO,CAAE,MAAO,EAAG,IAAK,EAAG,KAAM,CAAE,EAAG,OAAQ,CAAC,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,CAAC,EAAG,KAAM,CAAE,QAAS,EAAG,SAAU,CAAE,CAAE,EAEtJ,IAAMC,EAAO,KAAK,IAAIvC,EAAK,OAAO,GAAKa,EAAU,GAAIb,EAAK,OAAO,GAAKa,EAAU,EAAE,EAAI,IAEhF2B,EAAe,CAACF,EAAK,IAAKA,EAAK,KAAMA,EAAK,KAAMA,EAAK,IAAI,EAAE,IAAKG,GAAO,CAACA,EAAG,GAAK5B,EAAU,GAAK0B,EAAME,EAAG,GAAK5B,EAAU,GAAK0B,EAAME,EAAG,EAAE,CAAU,EAEjJC,EAAS5B,EAAUG,EAAWuB,EAAI,GAAcA,EAAI,EAAY,CAAC,EACnEG,EAAS7B,EAAUG,EAAWuB,EAAI,GAAcA,EAAI,EAAY,CAAC,EAC/DI,EAAS9B,EAAUS,EAAaoB,EAAQD,CAAM,CAAC,EAErDC,EAASpB,EAAamB,EAAQE,CAAM,EAIpC,IAAMC,EAAmF,CACvFF,EAAO,GAAIA,EAAO,GAAIA,EAAO,GAC7BD,EAAO,GAAIA,EAAO,GAAIA,EAAO,GAC7BE,EAAO,GAAIA,EAAO,GAAIA,EAAO,EAC/B,EACME,EAAQtB,EAA2BqB,CAAM,EAIzCE,EAAOT,EAAK,SAAW,IAAMvC,GAAcC,CAAI,EAAI,CAAE,QAAS,EAAG,SAAU,CAAE,EAEnF,MAAO,CAAE,MAAA8C,EAAO,OAAAD,EAAQ,KAAAE,CAAK,CAC/B,EChGO,IAAMC,GAAa,MAAOC,EAAyCC,IAAyC,CAzBnH,IAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,GAAAC,EAAAC,GAAAC,GAAAC,EAAAC,GA4BE,IAAIC,EAAoBC,EAAI,EACxBC,EACAC,EACAC,EACAC,EACAC,EACAC,EACAC,EACAC,EAEEC,EAA6B,CAAC,EACpClC,EAAS,MAAQ,WAEjB,IAAMmC,EAAQ,MAAeC,GAAQnC,EAAOD,EAAS,MAAM,EAE3D,GADAA,EAAS,YAAY,KAAOqC,EAAI,SAAWrC,EAAS,YAAY,MAAQ,GAAK,KAAK,MAAMyB,EAAI,EAAID,CAAS,EAAI,KAAK,MAAMC,EAAI,EAAID,CAAS,EACrI,CAACvB,EAAM,OAASA,EAAM,MAAM,SAAW,EAAG,MAAO,CAAC,EACtD,GAAI,CAACkC,EAAO,MAAO,CAAC,EAEpB,QAASG,EAAI,EAAGA,EAAIH,EAAM,OAAQG,IAAK,CAKrC,GAJAtC,EAAS,QAAQ,UAAU,EAIvB,CAACmC,EAAMG,GAAG,QAAUH,EAAMG,GAAG,OAAO,mBAAuB,CAC7DC,EAAI,2BAA4BJ,EAAMG,GAAG,MAAM,EAC/C,QACF,CAGA,IAAIpC,EAAAF,EAAS,OAAO,KAAK,WAArB,MAAAE,EAA+B,KAAM,CACvC,IAAMsC,EAAS,MAAWC,GAAKN,EAAMG,EAAE,EACpC,UAAQH,EAAMG,GAAG,MAAM,EAC1BH,EAAMG,GAAG,OAASE,CACpB,CAGA,IAAME,EAAWP,EAAMG,GAAG,MAASH,EAAMG,GAAG,KAAK,OAAS,IAAOK,GAAmBR,EAAMG,GAAI,CAACrC,EAAM,MAAM,GAAIA,EAAM,MAAM,EAAE,CAAC,EAAI,KAGlID,EAAS,QAAQ,gBAAgB,EAC7BA,EAAS,OAAO,MAClB6B,GAAa1B,EAAAH,EAAS,OAAO,KAAK,UAArB,MAAAG,EAA8B,QAAkBiC,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,CAAC,GAE5InC,EAAS,MAAQ,cACjBwB,EAAYC,EAAI,EAChBI,GAAazB,EAAAJ,EAAS,OAAO,KAAK,UAArB,MAAAI,EAA8B,QAAU,MAAcgC,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,CAAC,EAClJnC,EAAS,YAAY,QAAUqC,EAAI,SAAWrC,EAAS,YAAY,SAAW,GAAK,KAAK,MAAMyB,EAAI,EAAID,CAAS,EAAI,KAAK,MAAMC,EAAI,EAAID,CAAS,GAEjJxB,EAAS,QAAQ,cAAc,EAG/BA,EAAS,QAAQ,kBAAkB,EAC/BA,EAAS,OAAO,MAClB+B,GAAe1B,EAAAL,EAAS,OAAO,KAAK,YAArB,MAAAK,EAAgC,QAAoB+B,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,GAEjJnC,EAAS,MAAQ,gBACjBwB,EAAYC,EAAI,EAChBM,GAAezB,EAAAN,EAAS,OAAO,KAAK,YAArB,MAAAM,EAAgC,QAAU,MAAgB8B,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,EACvJnC,EAAS,YAAY,UAAYqC,EAAI,SAAWrC,EAAS,YAAY,WAAa,GAAK,KAAK,MAAMyB,EAAI,EAAID,CAAS,EAAI,KAAK,MAAMC,EAAI,EAAID,CAAS,GAErJxB,EAAS,QAAQ,gBAAgB,EAGjCA,EAAS,QAAQ,iBAAiB,EAC9BA,EAAS,OAAO,MAClBgC,GAAczB,EAAAP,EAAS,OAAO,KAAK,WAArB,MAAAO,EAA+B,QAAmB6B,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,GAE9InC,EAAS,MAAQ,eACjBwB,EAAYC,EAAI,EAChBO,GAAcxB,EAAAR,EAAS,OAAO,KAAK,WAArB,MAAAQ,EAA+B,QAAU,MAAe4B,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,EACpJnC,EAAS,YAAY,SAAWqC,EAAI,SAAWrC,EAAS,YAAY,WAAa,GAAK,KAAK,MAAMyB,EAAI,EAAID,CAAS,EAAI,KAAK,MAAMC,EAAI,EAAID,CAAS,GAEpJxB,EAAS,QAAQ,eAAe,EAGhCA,EAAS,QAAQ,aAAa,EAC1BA,EAAS,OAAO,MAClB2B,GAAUlB,EAAAT,EAAS,OAAO,KAAK,OAArB,MAAAS,EAA8B,QAAe2B,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,MAErInC,EAAS,MAAQ,WACjBwB,EAAYC,EAAI,EAChBE,GAAUjB,EAAAV,EAAS,OAAO,KAAK,OAArB,MAAAU,EAA8B,QAAU,MAAW0B,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,KAC3InC,EAAS,YAAY,KAAO,KAAK,MAAMyB,EAAI,EAAID,CAAS,GAE1DxB,EAAS,QAAQ,WAAW,EAG5BA,EAAS,QAAQ,eAAe,EAC5BA,EAAS,OAAO,OAClB0B,GAASf,EAAAX,EAAS,OAAO,KAAK,SAArB,MAAAW,EAAgC,QAAoByB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,KAC3IP,GAAYhB,EAAAZ,EAAS,OAAO,KAAK,SAArB,MAAAY,EAAgC,QAAuBwB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,OAEjJnC,EAAS,MAAQ,aACjBwB,EAAYC,EAAI,EAChBC,GAASb,EAAAb,EAAS,OAAO,KAAK,SAArB,MAAAa,EAAgC,QAAU,MAAgBuB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,KACjJP,GAAYd,EAAAd,EAAS,OAAO,KAAK,SAArB,MAAAc,EAAgC,QAAU,MAAmBsB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,KACvJnC,EAAS,YAAY,OAAS,KAAK,MAAMyB,EAAI,EAAID,CAAS,GAE5DxB,EAAS,QAAQ,aAAa,EAG9BA,EAAS,QAAQ,sBAAsB,EACnCA,EAAS,OAAO,MAClB8B,GAAmBf,EAAAf,EAAS,OAAO,KAAK,gBAArB,MAAAe,EAAuC,QAAwBqB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,MAEhKnC,EAAS,MAAQ,oBACjBwB,EAAYC,EAAI,EAChBK,GAAmBd,EAAAhB,EAAS,OAAO,KAAK,gBAArB,MAAAgB,EAAuC,QAAU,MAAoBoB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,KACtKnC,EAAS,YAAY,cAAgB,KAAK,MAAMyB,EAAI,EAAID,CAAS,GAEnExB,EAAS,QAAQ,oBAAoB,EAGrCA,EAAS,QAAQ,oBAAoB,EACjCA,EAAS,OAAO,MAClBiC,GAAUhB,EAAAjB,EAAS,OAAO,KAAK,cAArB,MAAAiB,EAAkC,QAAkBmB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,MAE5InC,EAAS,MAAQ,kBACjBwB,EAAYC,EAAI,EAChBQ,GAAUf,GAAAlB,EAAS,OAAO,KAAK,cAArB,MAAAkB,GAAkC,QAAU,MAAckB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,KAClJnC,EAAS,YAAY,YAAcqC,EAAI,SAAWrC,EAAS,YAAY,aAAe,GAAK,KAAK,MAAMyB,EAAI,EAAID,CAAS,EAAI,KAAK,MAAMC,EAAI,EAAID,CAAS,GAEzJxB,EAAS,QAAQ,kBAAkB,EAG/BA,EAAS,OAAO,QAClB,CAAC0B,EAAQE,EAAWC,EAAYC,EAAkBG,EAASN,EAASI,EAAcC,CAAW,EAAI,MAAM,QAAQ,IAAI,CAACN,EAAQE,EAAWC,EAAYC,EAAkBG,EAASN,EAASI,EAAcC,CAAW,CAAC,GAEnNhC,EAAS,QAAQ,cAAc,IAE3BmB,EAAAnB,EAAS,OAAO,KAAK,SAArB,YAAAmB,EAAgC,UAAWO,GAAUE,IACvDK,EAAU,CACR,GAAIA,EACJ,IAAMP,EAA0B,IAChC,OAASE,EAAsD,OAC/D,YAAcA,EAAsD,WACtE,KAEER,GAAApB,EAAS,OAAO,KAAK,OAArB,YAAAoB,GAA8B,UAAWO,IAC3CM,EAAU,CACR,GAAIA,EACJ,IAAMN,EAA0B,IAChC,OAASA,EAA0B,OACnC,YAAcA,EAA0B,YACxC,KAAOA,EAA0B,IACnC,KAEEN,GAAArB,EAAS,OAAO,KAAK,gBAArB,YAAAqB,GAAuC,UAAWS,IACnDG,EAAoB,WAAaH,IAK/BR,EAAAtB,EAAS,OAAO,KAAK,OAArB,MAAAsB,EAA2B,QAIhC,IAAMsB,EAAYT,EAAMG,GAAG,aAAeH,EAAMG,GAAG,YAAY,aAAeH,EAAMG,GAAG,YAAY,YAAY,IAAMH,EAAMG,GAAG,YAAY,cAAgBH,EAAMG,GAAG,YAAY,aAAa,IACtLH,EAAMG,GAAG,YAAY,YAAY,OAAS,GAAOH,EAAMG,GAAG,YAAY,aAAa,OAAS,GAC5FH,EAAMG,GAAG,YAAY,YAAY,KAAO,MAAUH,EAAMG,GAAG,YAAY,aAAa,KAAO,KAC7F,KAAK,IAAI,KAAK,IAAIH,EAAMG,GAAG,YAAY,YAAY,GAAG,GAAKH,EAAMG,GAAG,YAAY,YAAY,GAAG,EAAE,EAAG,KAAK,IAAIH,EAAMG,GAAG,YAAY,aAAa,GAAG,GAAKH,EAAMG,GAAG,YAAY,aAAa,GAAG,EAAE,CAAC,EAAIrC,EAAM,MAAM,GAC/M,EAGE4C,IAAStB,GAAAvB,EAAS,OAAO,KAAK,WAArB,MAAAuB,GAA+B,OAAY,UAAQY,EAAMG,GAAG,MAAM,EAAI,KAElF,UAAQH,EAAMG,GAAG,MAAM,EAEtBH,EAAMG,GAAG,QAAQ,OAAOH,EAAMG,GAAG,OAErC,IAAMQ,EAAkB,CACtB,GAAGX,EAAMG,GACT,GAAIA,CACN,EACKL,GAAA,MAAAA,EAAqB,MAAKa,EAAI,IAAOb,EAAoB,KACzDA,GAAA,MAAAA,EAAqB,SAAQa,EAAI,OAAUb,EAAoB,QAC/DA,GAAA,MAAAA,EAAqB,cAAaa,EAAI,YAAeb,GAAA,YAAAA,EAAqB,aAC1EA,GAAA,MAAAA,EAAqB,aAAYa,EAAI,UAAab,GAAA,YAAAA,EAAqB,YACvEA,GAAA,MAAAA,EAAqB,OAAMa,EAAI,KAAQb,GAAA,YAAAA,EAAqB,MAC7DJ,IAAYiB,EAAI,QAAUjB,GAC1BE,IAAce,EAAI,KAAOf,GACzBC,IAAac,EAAI,KAAOd,GACxBY,GAAYA,IAAa,IAAGE,EAAI,KAAO,KAAK,MAAM,IAAMF,EAAW,IAAI,EAAI,KAC3EF,IAAUI,EAAI,SAAWJ,GACzBG,KAAQC,EAAI,OAASD,IACzBX,EAAQ,KAAKY,CAAG,EAChB9C,EAAS,QAAQ,UAAU,CAC7B,CACA,OAAAA,EAAS,QAAQ,eAAe,EAC5BA,EAAS,OAAO,QACdA,EAAS,YAAY,MAAM,OAAOA,EAAS,YAAY,KACvDA,EAAS,YAAY,KAAK,OAAOA,EAAS,YAAY,IACtDA,EAAS,YAAY,QAAQ,OAAOA,EAAS,YAAY,OACzDA,EAAS,YAAY,SAAS,OAAOA,EAAS,YAAY,SAEzDkC,CACT,EC/LO,IAAMa,GAAQC,GAAuC,CAC1D,GAAI,CAACA,EAAK,MAAO,CAAC,EAClB,IAAMC,EAA0D,CAAC,EACjE,QAASC,EAAI,EAAGA,EAAIF,EAAI,OAAQE,IAAK,CAEnC,IAAMC,EAAYH,EAAIE,GAAG,UAAU,KAAME,GAAOA,EAAE,OAAS,WAAY,EACjEC,EAAaL,EAAIE,GAAG,UAAU,KAAME,GAAOA,EAAE,OAAS,YAAa,EACnEE,EAAON,EAAIE,GAAG,UAAU,KAAME,GAAOA,EAAE,OAAS,MAAO,EACzDE,GAAQH,GAAaE,GAAeF,EAAU,SAAS,GAAKG,EAAK,SAAS,IAAQD,EAAW,SAAS,GAAKC,EAAK,SAAS,GAAKL,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,WAAY,CAAC,EACxKI,GAAQH,GAAcA,EAAU,SAAS,GAAKG,EAAK,SAAS,GAAKL,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,iBAAkB,CAAC,EACtHI,GAAQD,GAAeA,EAAW,SAAS,GAAKC,EAAK,SAAS,IAAKL,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,kBAAmB,CAAC,EAGlI,IAAMK,EAAeP,EAAIE,GAAG,UAAU,KAAME,GAAOA,EAAE,OAAS,cAAe,EACvEI,EAAgBR,EAAIE,GAAG,UAAU,KAAME,GAAOA,EAAE,OAAS,eAAgB,EAC3EG,GAAgBC,GAAiB,KAAK,IAAID,EAAa,YAAY,GAAKC,EAAc,YAAY,EAAE,EAAI,IAC1GP,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,WAAYK,EAAa,SAAS,GAAKC,EAAc,SAAS,GAAM,OAAS,SAAU,CAAC,CAE9H,CACA,OAAOP,CACT,EAEaQ,GAAQT,GAAuC,CAC1D,GAAI,CAACA,EAAK,MAAO,CAAC,EAClB,IAAMC,EAA0D,CAAC,EACjE,QAASC,EAAI,EAAGA,EAAIF,EAAI,OAAQE,IAC9B,GAAIF,EAAIE,GAAG,MAAQF,EAAIE,GAAG,KAAK,OAAS,IAAK,CAC3C,IAAMQ,GAASV,EAAIE,GAAG,KAAK,IAAI,IAAM,IAAMF,EAAIE,GAAG,KAAK,KAAK,IAAM,GAC5DS,EAAQX,EAAIE,GAAG,KAAK,IAAI,GAAKF,EAAIE,GAAG,KAAK,KAAK,GAChD,KAAK,IAAIQ,EAAQC,CAAK,GAAK,IAAMV,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,eAAgB,CAAC,EACnFD,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,UAAUQ,EAAQ,EAAI,OAAS,SAAU,CAAC,EAChE,KAAK,IAAIV,EAAIE,GAAG,KAAK,KAAK,GAAKF,EAAIE,GAAG,KAAK,KAAK,EAAE,EAAI,KAAK,IAAIF,EAAIE,GAAG,KAAK,KAAK,GAAKF,EAAIE,GAAG,KAAK,KAAK,EAAE,EAC1G,IAAKD,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,gBAAiB,CAAC,EACtD,KAAK,IAAIF,EAAIE,GAAG,KAAK,KAAK,GAAKF,EAAIE,GAAG,KAAK,KAAK,EAAE,EAAI,KAAK,IAAIF,EAAIE,GAAG,KAAK,KAAK,GAAKF,EAAIE,GAAG,KAAK,KAAK,EAAE,EAC1G,IAAKD,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,iBAAkB,CAAC,EAC1E,IAAMU,EAAY,KAAK,IAAI,IAAK,IAAM,KAAK,IAAIZ,EAAIE,GAAG,KAAK,IAAI,GAAKF,EAAIE,GAAG,KAAK,IAAI,EAAE,EAAI,KAAK,IAAIF,EAAIE,GAAG,KAAK,IAAI,GAAKF,EAAIE,GAAG,KAAK,KAAK,EAAE,CAAC,EACxIU,EAAY,IAAIX,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,SAAS,KAAK,MAAMU,CAAS,SAAU,CAAC,EAC9F,IAAMC,EAAYb,EAAIE,GAAG,KAAK,KAAK,IAAM,EACrC,KAAK,IAAIW,CAAS,EAAI,IAAIZ,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,QAAQW,EAAY,EAAI,KAAO,QAAS,CAAC,CAC3G,CAEF,OAAOZ,CACT,EAEaa,GAAQd,GAAuC,CAC1D,GAAI,CAACA,EAAK,MAAO,CAAC,EAClB,IAAMC,EAA0D,CAAC,EACjE,QAASC,EAAI,EAAGA,EAAIF,EAAI,OAAQE,IAAK,CACnC,GAAI,CAACF,EAAIE,GAAG,aAAe,CAACF,EAAIE,GAAG,YAAY,aAAe,CAACF,EAAIE,GAAG,YAAY,YAAY,IAAM,CAACF,EAAIE,GAAG,YAAY,cAAgB,CAACF,EAAIE,GAAG,YAAY,aAAa,GAAI,SAC7K,IAAMa,EAAYf,EAAIE,GAAG,YAAY,YAAY,GAAG,GAAKF,EAAIE,GAAG,YAAY,YAAY,GAAG,GACrFc,EAAYhB,EAAIE,GAAG,YAAY,YAAY,GAAG,GAAKF,EAAIE,GAAG,YAAY,YAAY,GAAG,GACrFe,EAAW,KAAK,IAAIF,EAAYC,CAAS,EAEzCE,EAAalB,EAAIE,GAAG,YAAY,aAAa,GAAG,GAAKF,EAAIE,GAAG,YAAY,aAAa,GAAG,GACxFiB,EAAanB,EAAIE,GAAG,YAAY,aAAa,GAAG,GAAKF,EAAIE,GAAG,YAAY,aAAa,GAAG,GACxFkB,EAAY,KAAK,IAAIF,EAAaC,CAAU,EAE9CE,EAAS,GACM,KAAK,IAAIJ,EAAWG,CAAS,EAAI,KAAK,IAAIH,EAAUG,CAAS,EAC/D,MACfC,EAAS,GACTpB,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,eAAgB,CAAC,GAGrD,IAAMoB,EAAkB,KAAK,IAAItB,EAAIE,GAAG,KAAK,KAAK,GAAKF,EAAIE,GAAG,YAAY,YAAY,GAAG,EAAE,EAAIF,EAAIE,GAAG,IAAI,GACpGqB,EAAmB,KAAK,IAAIvB,EAAIE,GAAG,KAAK,IAAI,GAAKF,EAAIE,GAAG,YAAY,aAAa,GAAG,EAAE,EAAIF,EAAIE,GAAG,IAAI,IACvGoB,EAAkB,KAAQC,EAAmB,OAAMF,EAAS,IAC5DC,EAAkBC,EAChBD,EAAkB,KAAMrB,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,eAAgB,CAAC,EAE3EqB,EAAmB,KAAMtB,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,cAAe,CAAC,EAGjF,IAAMsB,EAAmB,KAAK,IAAIxB,EAAIE,GAAG,KAAK,KAAK,GAAKF,EAAIE,GAAG,YAAY,aAAa,GAAG,EAAE,EAAIF,EAAIE,GAAG,IAAI,GACtGuB,EAAkB,KAAK,IAAIzB,EAAIE,GAAG,KAAK,KAAK,GAAKF,EAAIE,GAAG,YAAY,YAAY,GAAG,EAAE,EAAIF,EAAIE,GAAG,IAAI,IACtGuB,EAAkB,KAAQD,EAAmB,KAAQC,EAAkB,MAASD,EAAmB,QAAOH,EAAS,KACnHI,EAAkB,KAAQD,EAAmB,MAAMvB,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,cAAe,CAAC,GACrGuB,EAAkB,MAASD,EAAmB,OAAOvB,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,YAAa,CAAC,EAGrGmB,GAAQpB,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,gBAAiB,CAAC,CAClE,CACA,OAAOD,CACT,EAEayB,GAAQ1B,GAAuC,CAC1D,GAAI,CAACA,EAAK,MAAO,CAAC,EAClB,IAAMC,EAA0D,CAAC,EACjE,QAASC,EAAI,EAAGA,EAAIF,EAAI,OAAQE,IAAK,CACnC,IAAMyB,EAAoD,CAAC,EAC3D,GAAI3B,EAAIE,GAAG,YACT,OAAW,CAAC0B,EAAQC,CAAG,IAAK,OAAO,QAAQ7B,EAAIE,GAAG,WAAc,EAC1D0B,IAAW,YAAc,MAAM,QAAQC,CAAG,GAAKA,EAAI,IAAIF,EAAQ,KAAK,CAAE,KAAMC,EAAO,YAAY,EAAG,SAAUC,EAAI,EAAG,CAAC,EAG5H,GAAIF,GAAWA,EAAQ,OAAS,EAAG,CACjC,IAAMG,EAAUH,EAAQ,OAAO,CAACI,EAAM3B,KAAQ2B,EAAK,SAAS,IAAM,IAAM3B,EAAE,SAAS,IAAM,GAAK2B,EAAO3B,CAAE,EACvGH,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,GAAG4B,EAAQ,cAA8B,CAAC,EAC5E,IAAME,EAAUL,EAAQ,OAAO,CAACI,EAAM3B,IAAO2B,EAAK,SAAS,GAAK3B,EAAE,SAAS,GAAK2B,EAAO3B,CAAE,EACzFH,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,GAAG8B,EAAQ,SAAyB,CAAC,CACzE,CACA,GAAIhC,EAAIE,GAAG,UAAc,CACvB,IAAM+B,EAAmBC,GAAMlC,EAAIE,GAAG,SAAY,EAClD,QAAWiC,KAAQF,EAAOhC,EAAS,KAAK,CAAE,KAAMC,EAAG,QAASiC,EAAK,IAAoB,CAAC,CACxF,CACF,CACA,OAAOlC,CACT,EC/HA,IAAMmC,EAAyB,CAAE,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,QAAS,CAAC,EAAG,OAAQ,CAAC,EAAG,QAAS,CAAC,EAAG,YAAa,CAAC,EAAG,UAAW,EAAG,MAAO,IAAK,EAC5IC,GAAkB,EAEf,SAASC,GAAKC,EAAmBC,EAAwB,CAhBhE,IAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,GAAAC,EAAAC,GAAAC,GAiBE,IAAMC,EAAKC,EAAI,EACf,GAAI,CAAC9B,EAAW,MAAO,CAAE,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,QAAS,CAAC,EAAG,OAAQ,CAAC,EAAG,QAAS,CAAC,EAAG,YAAa,CAAC,EAAG,UAAW,EAAG,MAAO,IAAK,EAKxI,IAAM+B,EAAU,KAAK,IAAI,EAAI/B,EAAU,UAQjCgC,EAAiBD,EAAU,IAAO,EAAI,KAAK,IAAIA,EAAU,CAAC,EAAI,EAMpE,GAJI/B,EAAU,SAAQH,EAAe,OAASG,EAAU,QACpDA,EAAU,QAAOH,EAAe,MAAQG,EAAU,OAGlD,CAACH,EAAe,MAASG,EAAU,KAAK,SAAWH,EAAe,KAAK,OACzEA,EAAe,KAAO,KAAK,MAAM,KAAK,UAAUG,EAAU,IAAoB,CAAC,MAE/E,SAASiC,EAAI,EAAGA,EAAIjC,EAAU,KAAK,OAAQiC,IAAK,CAC9C,IAAMC,GAAMlC,EAAU,KAAKiC,GAAG,IAC3B,IAAI,CAACE,EAAaC,MAAQJ,EAAiB,GAAKnC,EAAe,KAAKoC,GAAG,IAAIG,GAAKD,GAAeH,CAAc,EAC1GK,EAASrC,EAAU,KAAKiC,GAAG,OAC9B,IAAI,CAACE,EAAaC,MAAQJ,EAAiB,GAAKnC,EAAe,KAAKoC,GAAG,OAAOG,GAAKD,GAAeH,CAAc,EAC7GM,EAAatC,EAAU,KAAKiC,GAAG,UAClC,IAAI,CAACM,EAAQH,IAAG,CA9CzB,IAAAlC,GAAAC,GAAAC,GAAAC,GAAAC,GAAAC,GAAAC,GAAAC,GAAAC,GA8C6B,OACnB,MAAO6B,EAAO,MACd,KAAMA,EAAO,KACb,SAAU,CACR1C,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,IAAMnC,EAAe,KAAKoC,GAAG,UAAUG,GAAG,SAAS,IAAM,IAAMG,EAAO,SAAS,IAAM,IAAMP,EAAiBO,EAAO,SAAS,GACrL1C,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,IAAMnC,EAAe,KAAKoC,GAAG,UAAUG,GAAG,SAAS,IAAM,IAAMG,EAAO,SAAS,IAAM,IAAMP,EAAiBO,EAAO,SAAS,GACrL1C,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,IAAMnC,EAAe,KAAKoC,GAAG,UAAUG,GAAG,SAAS,IAAM,IAAMG,EAAO,SAAS,IAAM,IAAMP,EAAiBO,EAAO,SAAS,EACvL,EACA,YAAa,CACX1C,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,IAAMnC,EAAe,KAAKoC,GAAG,UAAUG,GAAG,YAAY,IAAM,IAAMG,EAAO,YAAY,IAAM,IAAMP,EAAiBO,EAAO,YAAY,GAC9L1C,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,IAAMnC,EAAe,KAAKoC,GAAG,UAAUG,GAAG,YAAY,IAAM,IAAMG,EAAO,YAAY,IAAM,IAAMP,EAAiBO,EAAO,YAAY,GAC9L1C,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,IAAMnC,EAAe,KAAKoC,GAAG,UAAUG,GAAG,YAAY,IAAM,IAAMG,EAAO,YAAY,IAAM,IAAMP,EAAiBO,EAAO,YAAY,EAChM,EACA,SAAU,CACR1C,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,MAAM9B,GAAAL,EAAe,KAAKoC,GAAG,UAAUG,GAAG,WAApC,YAAAlC,GAA+C,KAAM,MAAMC,GAAAoC,EAAO,WAAP,YAAApC,GAAkB,KAAM,IAAM6B,GAAiB5B,GAAAmC,EAAO,WAAP,YAAAnC,GAAkB,GAC3LP,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,MAAM3B,GAAAR,EAAe,KAAKoC,GAAG,UAAUG,GAAG,WAApC,YAAA/B,GAA+C,KAAM,MAAMC,GAAAiC,EAAO,WAAP,YAAAjC,GAAkB,KAAM,IAAM0B,GAAiBzB,GAAAgC,EAAO,WAAP,YAAAhC,GAAkB,GAC3LV,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,MAAMxB,GAAAX,EAAe,KAAKoC,GAAG,UAAUG,GAAG,WAApC,YAAA5B,GAA+C,KAAM,MAAMC,GAAA8B,EAAO,WAAP,YAAA9B,GAAkB,KAAM,IAAMuB,GAAiBtB,GAAA6B,EAAO,WAAP,YAAA7B,GAAkB,EAC7L,CACF,EAAE,EAEE8B,EAAiD,CAAC,EACpDC,GAAS,CAAE,UAAW,CAAC,CAAE,GACzBtC,GAAAD,EAAAD,EAAO,OAAP,YAAAC,EAAa,YAAb,MAAAC,EAAwB,SAAS,iBAAkBsC,GAASC,IACvDrC,GAAAD,EAAAH,EAAO,OAAP,YAAAG,EAAa,YAAb,MAAAC,EAAwB,SAAS,aAAcoC,GAASE,IACxDpC,GAAAD,EAAAL,EAAO,OAAP,YAAAK,EAAa,YAAb,MAAAC,EAAwB,SAAS,aAAYkC,GAASG,IAC/D,OAAW,CAACC,EAAMC,CAAO,IAAK,OAAO,QAAQL,GAAO,SAAqC,EAAG,CAC1F,IAAMM,GAAqB,CAAC,EAC5B,QAASX,GAAI,EAAGA,GAAIU,EAAQ,OAAS,EAAGV,KAAK,CAC3C,IAAMY,GAAMV,EAAU,KAAMW,IAAOA,GAAG,OAASH,EAAQV,GAAE,EACnDc,GAAMZ,EAAU,KAAMW,IAAOA,GAAG,OAASH,EAAQV,GAAI,EAAE,EAEzDY,IAAOE,IAAKH,GAAG,KAAK,CAACC,GAAI,SAAUE,GAAI,QAAQ,CAAC,CACtD,CACAV,EAAYK,GAAQE,EACtB,CACAlD,EAAe,KAAKoC,GAAK,CAAE,GAAGjC,EAAU,KAAKiC,GAAI,IAAAC,GAAK,OAAAG,EAAQ,UAAAC,EAAW,YAAaE,CAAyC,CACjI,CAIF,GAAI,CAAC3C,EAAe,MAASG,EAAU,KAAK,SAAWH,EAAe,KAAK,OACzEA,EAAe,KAAO,KAAK,MAAM,KAAK,UAAUG,EAAU,IAAoB,CAAC,MAE/E,SAASiC,EAAI,EAAGA,EAAIjC,EAAU,KAAK,OAAQiC,IAAK,CAC9C,IAAMC,GAAOlC,EAAU,KAAKiC,GAAG,IAC5B,IAAI,CAACkB,GAAGf,MAAQJ,EAAiB,GAAKnC,EAAe,KAAKoC,GAAG,IAAIG,GAAKe,IAAKnB,CAAc,EACtFK,EAAUrC,EAAU,KAAKiC,GAAG,OAC/B,IAAI,CAACkB,GAAGf,MAAQJ,EAAiB,GAAKnC,EAAe,KAAKoC,GAAG,OAAOG,GAAKe,IAAKnB,CAAc,EAC3FnC,EAAe,KAAKoC,GAAG,UAAU,SAAWjC,EAAU,KAAKiC,GAAG,UAAU,SAAQpC,EAAe,KAAKoC,GAAG,UAAYjC,EAAU,KAAKiC,GAAG,WACzI,IAAMK,EAAYtC,EAAU,KAAKiC,GAAG,WAAajC,EAAU,KAAKiC,GAAG,UAAU,OAAS,EAAIjC,EAAU,KAAKiC,GAAG,UACzG,IAAI,CAACmB,GAAUhB,IAAMgB,GACnB,IAAI,CAACC,EAAOC,OAAStB,EAAiB,IAAMnC,EAAe,KAAKoC,GAAG,UAAUG,GAAGkB,KAAM,IAAMD,GAAS,IAAMrB,CAAe,CAAU,EACrI,CAAC,EACDQ,EAAc,CAAC,EACnB,GAAI,OAAO,KAAK3C,EAAe,KAAKoC,GAAG,WAAW,EAAE,SAAW,OAAO,KAAKjC,EAAU,KAAKiC,GAAG,WAAW,EAAE,OACxGpC,EAAe,KAAKoC,GAAG,YAAcjC,EAAU,KAAKiC,GAAG,YACvDO,EAAc3C,EAAe,KAAKoC,GAAG,oBAC5BjC,EAAU,KAAKiC,GAAG,YAC3B,QAAWsB,MAAO,OAAO,KAAKvD,EAAU,KAAKiC,GAAG,WAAW,EACzDO,EAAYe,IAAOvD,EAAU,KAAKiC,GAAG,YAAYsB,KAAQvD,EAAU,KAAKiC,GAAG,YAAYsB,IAAK,GACxFvD,EAAU,KAAKiC,GAAG,YAAYsB,IAC7B,IAAI,CAACC,EAAKpB,IAAcoB,EACtB,IAAI,CAACH,GAAeC,OAAgBtB,EAAiB,GAAKnC,EAAe,KAAKoC,GAAG,YAAYsB,IAAKnB,GAAGkB,IAAKD,IAASrB,CAAc,CAAC,EACrI,KAGRnC,EAAe,KAAKoC,GAAK,CAAE,GAAGjC,EAAU,KAAKiC,GAAI,IAAAC,GAAK,OAAAG,EAAQ,UAAAC,EAAW,YAAaE,CAAyC,CACjI,CAIF,GAAI,CAAC3C,EAAe,MAASG,EAAU,KAAK,SAAWH,EAAe,KAAK,OACzEA,EAAe,KAAO,KAAK,MAAM,KAAK,UAAUG,EAAU,IAAoB,CAAC,MAE/E,SAASiC,EAAI,EAAGA,EAAIjC,EAAU,KAAK,OAAQiC,IAAK,CAC9C,IAAMC,GAAOlC,EAAU,KAAKiC,GAAG,IAC5B,IAAI,CAACkB,EAAGf,MAAQJ,EAAiB,GAAKnC,EAAe,KAAKoC,GAAG,IAAIG,GAAKe,GAAKnB,CAAc,EACtFK,EAAUrC,EAAU,KAAKiC,GAAG,OAC/B,IAAI,CAACkB,EAAGf,MAAQJ,EAAiB,GAAKnC,EAAe,KAAKoC,GAAG,OAAOG,GAAKe,GAAKnB,CAAc,EAC/F,GAAIhC,EAAU,KAAKiC,GAAG,SAAU,CAC9B,IAAMwB,EAIF,CAAE,OAAQ,CAAC,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,CAAC,EAAG,MAAO,CAAE,KAAM,EAAG,IAAK,EAAG,MAAO,CAAE,EAAG,KAAM,CAAE,QAAS,EAAG,SAAU,CAAE,CAAE,EACnHA,EAAS,QAASjD,EAAAR,EAAU,KAAKiC,GAAG,WAAlB,YAAAzB,EAA4B,OAC9CiD,EAAS,MAAQ,CACf,OAAQzB,EAAiB,MAAMtB,GAAAD,EAAAZ,EAAe,KAAKoC,GAAG,WAAvB,YAAAxB,EAAiC,QAAjC,YAAAC,EAAwC,OAAQ,MAAME,GAAAD,EAAAX,EAAU,KAAKiC,GAAG,WAAlB,YAAAtB,EAA4B,QAA5B,YAAAC,EAAmC,OAAQ,IAAMoB,EACtI,MAAOA,EAAiB,MAAMlB,GAAAD,EAAAhB,EAAe,KAAKoC,GAAG,WAAvB,YAAApB,EAAiC,QAAjC,YAAAC,EAAwC,MAAO,MAAME,GAAAD,EAAAf,EAAU,KAAKiC,GAAG,WAAlB,YAAAlB,EAA4B,QAA5B,YAAAC,EAAmC,MAAO,IAAMgB,EACnI,QAASA,EAAiB,MAAMd,GAAAD,EAAApB,EAAe,KAAKoC,GAAG,WAAvB,YAAAhB,EAAiC,QAAjC,YAAAC,EAAwC,QAAS,MAAME,GAAAD,EAAAnB,EAAU,KAAKiC,GAAG,WAAlB,YAAAd,EAA4B,QAA5B,YAAAC,EAAmC,QAAS,IAAMY,CAC3I,EACAyB,EAAS,KAAO,CAEd,UAAWzB,EAAiB,MAAMV,GAAAD,EAAAxB,EAAe,KAAKoC,GAAG,WAAvB,YAAAZ,EAAiC,OAAjC,YAAAC,EAAuC,UAAW,MAAME,GAAAD,EAAAvB,EAAU,KAAKiC,GAAG,WAAlB,YAAAV,EAA4B,OAA5B,YAAAC,EAAkC,UAAW,IAAMQ,EAC7I,WAAYA,EAAiB,MAAMN,GAAAD,GAAA5B,EAAe,KAAKoC,GAAG,WAAvB,YAAAR,GAAiC,OAAjC,YAAAC,EAAuC,WAAY,MAAME,IAAAD,GAAA3B,EAAU,KAAKiC,GAAG,WAAlB,YAAAN,GAA4B,OAA5B,YAAAC,GAAkC,WAAY,IAAMI,CAClJ,EACAnC,EAAe,KAAKoC,GAAK,CAAE,GAAGjC,EAAU,KAAKiC,GAAI,SAAAwB,EAAU,IAAAvB,GAAK,OAAAG,CAAO,CACzE,CACAxC,EAAe,KAAKoC,GAAK,CAAE,GAAGjC,EAAU,KAAKiC,GAAI,IAAAC,GAAK,OAAAG,CAAO,CAC/D,CAIF,GAAI,CAACxC,EAAe,QAAWG,EAAU,OAAO,SAAWH,EAAe,OAAO,OAC/EA,EAAe,OAAS,KAAK,MAAM,KAAK,UAAUG,EAAU,MAAwB,CAAC,MAErF,SAASiC,EAAI,EAAGA,EAAIjC,EAAU,OAAO,OAAQiC,IAAK,CAChD,IAAMC,GAAOlC,EAAU,OAAOiC,GAAG,IAC9B,IAAI,CAACkB,EAAGf,MAAQJ,EAAiB,GAAKnC,EAAe,OAAOoC,GAAG,IAAIG,GAAKe,GAAKnB,CAAc,EACxFK,EAAUrC,EAAU,OAAOiC,GAAG,OACjC,IAAI,CAACkB,EAAGf,MAAQJ,EAAiB,GAAKnC,EAAe,OAAOoC,GAAG,OAAOG,GAAKe,GAAKnB,CAAc,EACjGnC,EAAe,OAAOoC,GAAK,CAAE,GAAGjC,EAAU,OAAOiC,GAAI,IAAAC,GAAK,OAAAG,CAAO,CACnE,CAIF,GAAIrC,EAAU,QAAS,CACrB,IAAM0D,EAAa1D,EAAU,QAC7B,GAAI,CAACH,EAAe,SAAY6D,EAAW,SAAW7D,EAAe,QAAQ,OAC3EA,EAAe,QAAU,KAAK,MAAM,KAAK,UAAU6D,CAA4B,CAAC,MAEhF,SAASzB,GAAI,EAAGA,GAAIyB,EAAW,OAAQzB,KACrCpC,EAAe,QAAQoC,IAAG,IAAOyB,EAAWzB,IAAG,IAC5C,IAAI,CAACC,EAAKE,MAAQJ,EAAiB,GAAKnC,EAAe,QAAQoC,IAAG,IAAIG,GAAKF,GAAOF,CAAc,CAGzG,CAGIhC,EAAU,UAASH,EAAe,QAAUG,EAAU,SAG1D,IAAM2D,EAAK7B,EAAI,EACf,OAAAhC,GAAkB8D,EAAI,QAAU9D,GAAkB,KAAK,MAAM6D,EAAK9B,CAAE,EAAI,KAAK,MAAM8B,EAAK9B,CAAE,EACtF7B,EAAU,cAAaH,EAAe,YAAc,CAAE,GAAGG,EAAU,YAAa,YAAaF,EAAgB,GAE1GD,CACT,CCvLA,IAAAgE,GAAA,GAAAC,GAAAD,GAAA,cAAAE,GAAA,UAAAC,GAAA,eAAAC,KAWO,SAASF,GAASG,EAAyBC,EAAyBC,EAAwB,CAAE,MAAO,EAAG,WAAY,EAAG,EAAG,CAE/H,IAAIC,EAAM,EACV,QAASC,EAAI,EAAGA,EAAIJ,EAAY,OAAQI,IAAK,CAC3C,IAAMC,EAAQ,CAACH,EAAQ,OAASA,EAAQ,QAAU,EAAMF,EAAYI,GAAKH,EAAYG,GAAO,KAAK,IAAIJ,EAAYI,GAAKH,EAAYG,EAAE,EACpID,GAAQ,CAACD,EAAQ,OAASA,EAAQ,QAAU,EAAMG,EAAOA,EAASA,GAAQH,EAAQ,KACpF,CACA,OAAQA,EAAQ,YAAc,IAAMC,CACtC,CAGA,IAAMG,GAAoB,CAACC,EAAMC,EAAOC,EAAKC,IAAQ,CACnD,GAAIH,IAAS,EAAG,MAAO,GACvB,IAAMI,EAAOH,IAAU,EAAI,KAAK,KAAKD,CAAI,EAAIA,IAAS,EAAIC,GACpDI,GAAQ,EAAKD,EAAO,IAAOF,IAAQC,EAAMD,GAE/C,OADc,KAAK,IAAI,KAAK,IAAIG,EAAM,CAAC,EAAG,CAAC,CAE7C,EAaO,SAASb,GAAWC,EAAyBC,EAAyBC,EAAwB,CAAE,MAAO,EAAG,WAAY,GAAI,IAAK,GAAK,IAAK,EAAI,EAAG,CACrJ,IAAMK,EAAOV,GAASG,EAAaC,EAAaC,CAAO,EACvD,OAAOI,GAAkBC,EAAML,EAAQ,OAAS,EAAGA,EAAQ,KAAO,EAAGA,EAAQ,KAAO,CAAC,CACvF,CAWO,SAASJ,GAAMe,EAAwBC,EAAgCZ,EAAwB,CAAE,MAAO,EAAG,WAAY,GAAI,UAAW,EAAG,IAAK,GAAK,IAAK,EAAI,EAAG,CACpK,GAAI,CAAC,MAAM,QAAQW,CAAU,GAAK,CAAC,MAAM,QAAQC,CAAW,GAAKD,EAAW,OAAS,IAAMC,EAAY,SAAW,GAAKD,EAAW,SAAWC,EAAY,GAAG,OAC1J,MAAO,CAAE,MAAO,GAAI,SAAU,OAAO,kBAAmB,WAAY,CAAE,EAExE,IAAIC,EAAiB,OAAO,iBACxBC,EAAQ,GACZ,QAASZ,EAAI,EAAGA,EAAIU,EAAY,OAAQV,IAAK,CAC3C,IAAMa,EAAMpB,GAASgB,EAAYC,EAAYV,GAAIF,CAAO,EAKxD,GAJIe,EAAMF,IACRA,EAAiBE,EACjBD,EAAQZ,GAENW,GAAkBb,EAAQ,WAAa,GAAI,KACjD,CACA,IAAMgB,EAAuBZ,GAAkBS,EAAgBb,EAAQ,OAAS,EAAGA,EAAQ,KAAO,EAAGA,EAAQ,KAAO,CAAC,EACrH,MAAO,CAAE,MAAAc,EAAO,SAAUD,EAAgB,WAAYG,CAAqB,CAC7E,CCjEO,SAASC,GAAKC,EAA0BC,EAA2BC,EAA0BC,EAAgCC,EAAuD,CAN3L,IAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAOE,IAAIC,EAAK,EACHC,EAA+B,CAAC,EACtC,QAAWC,KAAQvB,EAAO,CACxB,IAAMwB,EAAuB,CAAE,GAAIH,IAAM,KAAAE,EAAM,KAAM,KAAM,MAAO,CAAE,KAAM,KAAM,MAAO,IAAK,EAAG,SAAU,CAAC,EAAG,IAAK,CAAC,EAAG,EAAG,EAAG,CAAC,CAAE,EAC/H,QAAWE,KAAQxB,EACbsB,EAAK,IAAI,GAAKE,EAAK,IAAI,IACtBF,EAAK,IAAI,GAAKE,EAAK,IAAI,GAAKA,EAAK,IAAI,IACrCF,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKE,EAAK,IAAI,IACrCF,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKE,EAAK,IAAI,GAAKA,EAAK,IAAI,KACtDD,EAAO,KAAOC,GAGlB,GAAID,EAAO,KACT,QAAWE,KAAQxB,EACbwB,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,IAC3CE,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,GAAKA,EAAO,KAAK,IAAI,IACjEE,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,IAC5CE,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,GAAKA,EAAO,KAAK,IAAI,IAChEA,EAAO,QAAOA,EAAO,MAAM,KAAOE,GAEpCA,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,GAAKA,EAAO,KAAK,IAAI,IAClDE,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,IAC9BE,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,IAC5CE,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,GAAKA,EAAO,KAAK,IAAI,IAChEA,EAAO,QAAOA,EAAO,MAAM,MAAQE,GAI7C,QAAWC,KAAWxB,EAChBwB,EAAQ,OAAY,QAAaA,EAAQ,OAAYJ,EAAK,IAAIlB,EAAAmB,EAAO,WAAP,MAAAnB,EAAiB,KAAKsB,GAC/EA,EAAQ,OAAY,QAAaA,EAAQ,OAAYJ,EAAK,IAAIjB,EAAAkB,EAAO,WAAP,MAAAlB,EAAiB,KAAKqB,GACpFA,EAAQ,OAAY,QAAaA,EAAQ,SAAYpB,EAAAiB,EAAO,OAAP,YAAAjB,EAAa,KAAIC,EAAAgB,EAAO,WAAP,MAAAhB,EAAiB,KAAKmB,GAC5FA,EAAQ,OAAY,QAAaA,EAAQ,SAAYjB,GAAAD,EAAAe,EAAO,QAAP,YAAAf,EAAc,OAAd,YAAAC,EAAoB,KAAIC,EAAAa,EAAO,WAAP,MAAAb,EAAiB,KAAKgB,GACnGA,EAAQ,OAAY,QAAaA,EAAQ,SAAYd,GAAAD,EAAAY,EAAO,QAAP,YAAAZ,EAAc,QAAd,YAAAC,EAAqB,OAAIC,EAAAU,EAAO,WAAP,MAAAV,EAAiB,KAAKa,IAI/G,IAAMC,EAAc,CAAC,EACfC,EAAc,CAAC,EACfC,EAAaC,GAAyB,CACtCA,GAAOA,EAAI,SAAW,IACxBH,EAAE,KAAKG,EAAI,GAAIA,EAAI,GAAKA,EAAI,EAAE,EAC9BF,EAAE,KAAKE,EAAI,GAAIA,EAAI,GAAKA,EAAI,EAAE,EAElC,EACAD,GAAUf,EAAAS,EAAO,OAAP,YAAAT,EAAa,GAAG,EAC1Be,GAAUd,EAAAQ,EAAO,OAAP,YAAAR,EAAa,GAAG,EAC1Bc,GAAUZ,GAAAD,EAAAO,EAAO,QAAP,YAAAP,EAAc,OAAd,YAAAC,EAAoB,GAAG,EACjCY,GAAUV,GAAAD,EAAAK,EAAO,QAAP,YAAAL,EAAc,QAAd,YAAAC,EAAqB,GAAG,EAClC,IAAMY,EAAO,KAAK,IAAI,GAAGJ,CAAC,EACpBK,GAAO,KAAK,IAAI,GAAGJ,CAAC,EAC1BL,EAAO,IAAM,CAACQ,EAAMC,GAAM,KAAK,IAAI,GAAGL,CAAC,EAAII,EAAM,KAAK,IAAI,GAAGH,CAAC,EAAII,EAAI,EAGlE7B,GAASA,EAAM,IAAMA,EAAM,KAAIoB,EAAO,OAAS,CAACA,EAAO,IAAI,GAAKpB,EAAM,GAAIoB,EAAO,IAAI,GAAKpB,EAAM,GAAIoB,EAAO,IAAI,GAAKpB,EAAM,GAAIoB,EAAO,IAAI,GAAKpB,EAAM,EAAE,GAE1JkB,EAAQ,KAAKE,CAAM,CACrB,CACA,OAAOF,CACT,CC7DO,IAAMY,GAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kEA0JPC,GAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;MCjJpB,eAAeC,GAAaC,EAA8C,CACxE,IAAMC,EAAY,CAACC,EAAgBC,EAAO,6BAA+B,MAAM,QAAQA,YAAeD,GAAQ,EAAE,KAAME,GAAQA,EAAI,KAAK,CAAC,EACpIC,EACAD,EACJ,OAAQJ,EAAS,OAAO,YACjB,OAAQK,EAAO,MAAMJ,EAAiBK,EAAI,EAAG,UAC7C,WACA,OAAQD,EAAO,MAAMJ,EAAiBM,EAAI,EAAG,cACzCF,EAAO,KAElB,GAAIA,EAAM,CACR,IAAMG,EAAS,MAAM,kBAAkBH,CAAI,EAC3CD,EAAM,MAAMJ,EAAS,OAAOQ,EAAQR,EAAS,MAAM,EACnDQ,EAAO,MAAM,CACf,CACA,OAAOJ,CACT,CAEA,eAAeK,GAAaT,EAA8C,CACxE,OAAO,IAAI,QAASU,GAAY,CAC9B,IAAIC,EAEJ,OAAQX,EAAS,OAAO,YACjB,OAEHW,EAAM,0BAAmCL,GACzC,UACG,WACA,OAEHK,EAAM,0BAAmCJ,GACzC,cAEAI,EAAM,KAGV,IAAIC,EACJ,GAAI,OAAO,OAAU,YAAaA,EAAM,IAAI,cAEnCC,EAAI,MAAOD,EAAM,IAAIC,EAAI,UAC7B,QACLD,EAAI,OAAS,SAAY,CACvB,IAAME,EAAeA,GAAOF,EAAI,aAAcA,EAAI,aAAa,EAC/D,GAAI,CAACE,EACHC,EAAI,0BAA0B,EAC9BL,EAAQ,MAAS,MACZ,CACL,IAAMM,EAAMF,EAAO,WAAW,IAAI,EAC9BE,GAAKA,EAAI,UAAUJ,EAAK,EAAG,CAAC,EAEhC,IAAMK,EAAS,MAAMjB,EAAS,MAAMc,CAAM,EACpCV,EAAM,MAAMJ,EAAS,OAAOiB,EAAO,OAAkBjB,EAAS,MAAM,EAC1EU,EAAQN,CAAG,CACb,CACF,EACIO,EAAKC,EAAI,IAAMD,EACdD,EAAQ,MAAS,CACxB,CAAC,CACH,CAEA,eAAeQ,GAAWlB,EAA8C,CACtE,IAAMmB,EAAQC,GAAgB,OAAO,KAAKA,EAAK,QAAQ,EACnDR,EACAZ,EAAS,OAAO,SAAW,OAAQY,EAAMO,EAAYb,EAAI,EACxDM,EAAMO,EAAYZ,EAAI,EAC3B,IAAIH,EACJ,GAAI,SAAUiB,EAAI,CAEhB,IAAMC,EAAU,OAAQ,WAAWV,CAAG,EAChCW,EAAWD,EAAK,WAAW,CAAC,EAClCtB,EAAS,GAAG,QAAQsB,CAAI,EAExBlB,EAAM,MAAMJ,EAAS,OAAOuB,EAAUvB,EAAS,MAAM,EACrDA,EAAS,GAAG,QAAQuB,CAAQ,CAC9B,MACMvB,EAAS,OAAO,OAAOe,EAAI,6BAA6B,EAS9D,OAAOX,CACT,CAEA,eAAeoB,GAAaxB,EAAiB,CAC3C,IAAII,EACJ,OAAI,OAAO,mBAAsB,WAAYA,EAAM,MAAML,GAAaC,CAAQ,EACrE,OAAO,OAAU,aAAea,EAAI,SAAW,OAAWT,EAAM,MAAMK,GAAaT,CAAQ,EAC/FI,EAAM,MAAMc,GAAWlB,CAAQ,EAC7BI,CACT,CAGA,eAAsBqB,GAAWC,EAAmB,CAClD,IAAMC,EAAiB,aAAW,EAC5BC,EAAkB,UAAQ,EAChC,GAAKD,IAAgB,SAAWA,IAAgB,WAAe,CAACC,GAAgB,CAACA,EAAa,uBAE5F,OAEC,MAAI,EAAE,IAAI,sBAAuB,EAAI,EACxC,IAAMC,EAAqB,SAAO,EAAE,MAAM,WACpCC,EAA2B,CAAC,EAClC,OAAW,CAACC,EAAWC,CAAK,IAAK,OAAO,QAAQN,CAAS,EAAE,OAAO,CAAC,CAACO,EAAKC,CAAG,IAAOD,IAAQ,MAAQC,IAAQ,IAAK,EAAG,CACjH,IAAMC,EAASH,EAAM,QAAUA,EAAM,OAAO,IAAMA,EAAM,OAAO,GAAG,MAAS,CAAC,GAAGA,EAAM,OAAO,GAAG,KAAK,EAAI,CAAC,EAAG,GAAI,GAAI,CAAC,EAC/GI,EAASJ,EAAM,QAAUA,EAAM,OAAO,IAAMA,EAAM,OAAO,GAAG,MAASA,EAAM,OAAO,GAAG,MAAQ,UACnG,QAASK,EAAM,EAAGA,EAAMF,EAAM,OAAQE,IAChCF,EAAME,KAAS,KAAIF,EAAME,GAAOA,IAAQ,EAAI,EAAI,IAEtD,IAAMpB,EAAY,QAAMkB,EAAOC,CAAK,EAEpC,GAAI,CACF,IAAMhC,EAAM4B,EAAM,QAAQf,CAAM,EAChCa,EAAe,KAAKC,CAAS,EACzB,MAAM,QAAQ3B,CAAG,EAAGA,EAAI,QAASkC,GAAS,UAAQA,CAAC,CAAC,EAChD,UAAQlC,CAAG,CACrB,OAAQmC,EAAN,CACAxB,EAAI,sBAAuBgB,CAAS,CACtC,CACG,UAAQd,CAAM,CACnB,CACA,IAAMuB,EAAU,MAAMZ,EAAa,4BAA4B,EAC/DA,EAAa,oBAAoB,EACjCb,EAAI,uBAAwBe,CAAc,EAC1Cf,EAAI,wBAAyByB,EAAQ,MAAM,EACxC,MAAI,EAAE,IAAI,sBAAuB,EAAK,EACzC,IAAMC,EAAmB,SAAO,EAAE,MAAM,WACnCA,EAAgBZ,EAAmB,GAAGd,EAAI,eAAgB0B,EAAgBZ,CAAe,CAChG,CAOA,eAAsBa,GAAO1C,EAAiB2C,EAA2D,CACvG,IAAMC,EAAKC,EAAI,EAGf,OAFA7C,EAAS,MAAQ,SACb2C,IAAY3C,EAAS,OAAS8C,EAAU9C,EAAS,OAAQ2C,CAAU,GACnE,CAAC3C,EAAS,OAAO,QAAUA,EAAS,OAAO,OAAO,SAAW,GAAKA,EAAS,OAAO,SAAW,OACxF,CAAE,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,QAAS,CAAC,EAAG,OAAQ,CAAC,EAAG,YAAaA,EAAS,YAAa,UAAW6C,EAAI,EAAG,QAAS,CAAC,EAAG,MAAO,IAAK,EAEzI,IAAI,QAAQ,MAAOnC,GAAY,CACpC,MAAMe,GAAWzB,EAAS,MAAM,EAChC,IAAMI,EAAM,MAAMoB,GAAaxB,CAAQ,EACjC+C,EAAKF,EAAI,EACX7C,EAAS,OAAO,OAAOe,EAAI,SAAUf,EAAS,OAAO,OAAQ,KAAK,MAAM+C,EAAKH,CAAE,EAAG,IAAI,EAC1F5C,EAAS,KAAK,QAAQ,EACtBU,EAAQN,CAAG,CACb,CAAC,CACH,CCvKA,IAAA4C,GAAAC,GAAAC,GAAAC,GAsDaC,GAAN,KAAY,CAuEjB,YAAYC,EAA8B,CArE1CC,EAAA,gBAKAA,EAAA,eAKAA,EAAA,eAMAA,EAAA,cAGAA,EAAA,gBAMAA,EAAA,WAGAA,EAAA,YAOAA,EAAA,aAMAA,EAAA,eAWAA,EAAA,eAEAA,EAAA,0BAEAA,EAAA,kBAEAA,EAAA,oBACAC,GAAA,KAAAP,GAAA,QACAO,GAAA,KAAAN,GAAA,QACAM,GAAA,KAAAL,GAAA,QAEAI,EAAA,WA2DAA,EAAA,eAAU,IAAIE,IAAkB,CAC9B,GAAI,CAACC,GAAA,KAAKR,IAAqB,OAC/B,IAAMS,EAAiB,KAAK,GAAG,OAAO,EAAE,MAAM,WACxCC,EAAkBF,GAAA,KAAKT,IAC7BY,GAAA,KAAKZ,GAAcU,GACnB,IAAMG,EAASH,EAAiBC,EAC5BE,IAAW,GAAGC,EAAI,GAAGN,EAAKK,CAAM,CACtC,GAGAN,GAAA,KAAAJ,GAAWY,GAAgC,CACzC,GAAI,CAACN,GAAA,KAAKP,IAAc,OAAO,KAC/B,GAAI,CAACa,EAAO,MAAO,uBACnB,GAAI,KAAK,IAAI,MAAQ,EAAEA,aAAoBC,IAAS,MAAO,yBAC3D,GAAI,CACF,KAAK,GAAG,WAAW,CACrB,OAAQC,EAAN,CACA,MAAO,oBACT,CACA,OAAO,IACT,GAeAX,EAAA,KAAO,aAAmBY,IAE1BZ,EAAA,KAAO,WAAiBa,IAExBb,EAAA,KAAO,QAAcc,IAoGrBd,EAAA,YAAQe,GAAkB,CA7T5B,IAAAC,EA8TQ,KAAK,QAAU,KAAK,OAAO,iBAAeA,EAAA,KAAK,SAAL,MAAAA,EAAa,cAAc,IAAI,MAAMD,CAAK,GAC1F,GA/TF,IAAAC,EA8HI,KAAK,IAAMC,EAMX,IAAMC,KAAaF,EAAGG,KAAH,YAAAH,EAAY,OAAW,gBAAc,QAAQ,QAAS,EAAE,EAC3EI,GAAS,SAAW,8DAA8DF,UAClFE,GAAS,cAAgBH,EAAI,QAAU,aAAe,iBACtDG,GAAS,QAAUH,EAAI,QAAU,UAAY,aAC7C,KAAK,QAAcI,GACnB,OAAO,eAAe,KAAM,UAAW,CAAE,MAAWA,EAAQ,CAAC,EAC7D,KAAK,OAAS,KAAK,MAAM,KAAK,UAAUD,EAAQ,CAAC,EACjD,OAAO,KAAK,KAAK,MAAM,EACvB,KAAK,OAAO,YAAc,OAAO,WAAc,YAC3CrB,IAAY,KAAK,OAASuB,EAAU,KAAK,OAAQvB,CAAU,GAC/DwB,GAAoB,KAAK,MAAM,EAC/B,KAAK,GAAKC,EACV,KAAK,MAAQ,OACblB,GAAA,KAAKZ,GAAc,GACnBY,GAAA,KAAKX,GAAsB,IAC3BW,GAAA,KAAKV,GAAe,IACpB,KAAK,YAAc,CAAC,EACpB,KAAK,OAAU,OAAO,aAAgB,YAAe,IAAI,YAAgB,OAEzE,KAAK,OAAS,IAAW6B,GAEzB,KAAK,KAAO,CACV,QAAcC,GACd,OAAQ,CAACjB,EAAwDkB,IAA2BC,GAAOnB,EAAOkB,CAAM,EAChH,KAAM,CAACA,EAAmBE,EAAsBH,IAAwCI,GAAKH,EAAQE,EAAQH,CAAO,EACpH,KAAM,CAACC,EAAmBE,EAAsBH,IAAwCK,GAAKJ,EAAQE,EAAQH,CAAO,EACpH,KAAM,CAACC,EAAmBE,EAAsBH,IAAwCM,GAAKL,EAAQE,EAAQH,CAAO,EACpH,QAAS,CAACC,EAAmBE,EAAyBH,IAAwCO,GAAQN,EAAQE,EAAQH,CAAO,EAC7H,OAAQ,CAACC,EAAmBE,EAAwBH,IAAwCQ,GAAOP,EAAQE,EAAQH,CAAO,EAC1H,OAAQ,CAACC,EAAmBE,EAAwBH,IAAwCS,GAAOR,EAAQE,EAAQH,CAAO,EAC1H,IAAK,CAACC,EAAmBE,EAAgBH,IAAwCU,GAAIT,EAAQE,EAAQH,CAAO,CAC9G,EACA,KAAK,OAAS,CAAE,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,QAAS,CAAC,EAAG,OAAQ,CAAC,EAAG,YAAa,CAAC,EAAG,UAAW,EAAG,QAAS,CAAC,EAAG,MAAO,IAAK,EAG/H,KAAK,QAAU,CAAE,OAAQ,KAAM,OAAQ,IAAK,EAE5C,KAAK,kBAA6BW,GAClC,KAAK,UAAqBC,GAE1B,KAAK,GAAalB,EAElB,KAAK,KAAK,QAAQ,CACpB,CA0BA,OAAc,CACZ,IAAMmB,EAAiB,KAAK,OAAO,QACnC,KAAK,OAAS,KAAK,MAAM,KAAK,UAAUnB,EAAQ,CAAC,EACjD,KAAK,OAAO,QAAUmB,CACxB,CAGA,SAASxC,EAA8B,CACrC,OAAOyC,GAASpB,GAAUrB,GAAc,KAAK,MAAM,CACrD,CAUA,KAAc,CACZ,OAAO0C,EAAI,CACb,CAQA,MAAMhC,EAAciC,EAAqB,GAAM,CAC7C,OAAaC,GAAQlC,EAAO,KAAK,OAAQiC,CAAS,CACpD,CAYA,MAAM,aAAajC,EAAcmC,EAA6G,CAC5I,OAAoBD,GAAQlC,EAAOmC,EAAY,KAAK,MAAM,CAC5D,CAQA,QAAQnC,EAA8B,CACpC,OAAeoC,GAAQpC,CAAK,CAC9B,CASA,QAAQqC,EAA0BC,EAA4C,CAC5E,OAAaC,GAAQ,KAAK,OAAQF,EAAkBC,CAAiB,CACvE,CAOA,MAAM,MAAsB,CAC1B,MAAcE,GAAM,KAAM,EAAI,EAC9B,MAAM,KAAK,GAAG,MAAM,CACtB,CAOA,MAAM,KAAKlD,EAA6C,CACtD,KAAK,MAAQ,OACb,IAAMmD,EAAYT,EAAI,EAChBU,EAAQ,OAAO,OAAO,KAAK,MAAM,EAAE,OAAQC,GAAUA,CAAK,EAAE,OAC9DrD,IAAY,KAAK,OAASuB,EAAU,KAAK,OAAQvB,CAAU,GAE3D,KAAK,IAAI,UACP,KAAK,OAAO,OAAOS,EAAI,YAAY,KAAK,SAAS,EACjD,KAAK,OAAO,OAAOA,EAAI,iBAAiB,KAAK,GAAG,QAAQ,cAAc,EACrE,MAAcyC,GAAM,IAAI,GAAGzC,EAAI,6BAA6B,EACjE,MAAS,QAAM,EACX,KAAK,IAAI,UACP,KAAK,OAAO,OAAOA,EAAI,iBAAkB,KAAK,MAAM,EACpD,KAAK,OAAO,OAAOA,EAAI,eAAgB,KAAK,GAAG,EAC/C,KAAK,OAAO,OAAOA,EAAI,YAAa,KAAK,GAAG,IAAI,KAAQ,IAIhE,MAAa6C,GAAK,IAAI,EAClB,KAAK,IAAI,SAAW,KAAK,OAAO,OAAO7C,EAAI,mBAAoB,KAAK,GAAG,OAAO,EAAE,MAAM,SAAU,QAAS,KAAK,GAAG,OAAO,EAAE,MAAM,WAAY,SAAS,EACzJ,KAAK,IAAI,QAAU,GAEJ,OAAO,OAAO,KAAK,MAAM,EAAE,OAAQ4C,GAAUA,CAAK,EAAE,SACpDD,IACb,MAAaX,GAAS,IAAI,EAC1B,KAAK,KAAK,MAAM,GAGlB,IAAMc,EAAU,KAAK,MAAMb,EAAI,EAAIS,CAAS,EACxCI,GAAW,KAAK,YAAY,YAAwB,KAAI,KAAK,YAAY,WAAa,KAAK,IAAI,SAAW,KAAK,YAAY,YAAc,GAAKA,EAAUA,EAC9J,CAaA,KAAKzB,EAAiB,KAAK,OAAgB,CACzC,OAAmB0B,GAAK1B,EAAQ,KAAK,MAAM,CAC7C,CAGA,eAA4B,CAAE,OAAc2B,GAAc,IAAI,CAAG,CAQjE,MAAM,OAAOzD,EAA8B,CACzC,IAAM0D,EAAKhB,EAAI,EACTiB,EAAM,MAAcC,GAAO,KAAM5D,CAAU,EAC3C6D,EAAKnB,EAAI,EACf,YAAK,YAAY,OAAS,KAAK,MAAMmB,EAAKH,CAAE,EACrCC,CACT,CAMA,MAAM,QAAQjD,EAAcV,EAA+D,CACzF,IAAM8D,EAAU,MAAM,KAAK,GAAG,QAAQ,IAAM,KAAK,OAAOpD,EAAOV,CAAU,CAAC,EACpE+D,EAAkC,CAAC,EACzC,QAAWC,KAAUF,EAAQ,QACvBC,EAAQC,EAAO,MAAOD,EAAQC,EAAO,OAASA,EAAO,aACpDD,EAAQC,EAAO,MAAQA,EAAO,aAErC,IAAMC,EAAiD,CAAC,EACxD,OAAO,QAAQF,CAAO,EAAE,QAASG,GAAQD,EAAU,KAAK,CAAE,KAAMC,EAAI,GAAI,GAAIA,EAAI,EAAwB,CAAC,CAAC,EAC1GD,EAAU,KAAK,CAACE,EAAGC,IAAMA,EAAE,GAAKD,EAAE,EAAE,EACpCF,EAAU,OAAS,GACnB,IAAMN,EAA8B,CAAC,EACrC,QAAWK,KAAUC,EAAWN,EAAIK,EAAO,MAAQA,EAAO,GAC1D,OAAOL,CACT,CAYA,MAAM,OAAOjD,EAAcV,EAA+C,CAExE,YAAK,MAAQ,SACN,IAAI,QAAQ,MAAOqE,GAAY,CA7X1C,IAAApD,EAAAqD,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,GAAAC,EAAAC,GAAAC,GAAAC,EAAAC,GAAAC,EAAAC,EAAAC,EA8XM,KAAK,MAAQ,SACb,IAAIvC,EAGJ,KAAK,OAAS5B,EAAU,KAAK,OAAQvB,CAAU,EAG/C,KAAK,MAAQ,QACb,IAAM2F,EAAQvF,GAAA,KAAKN,IAAL,UAAaY,GACvBiF,IACFlF,EAAIkF,EAAOjF,CAAK,EAChB,KAAK,KAAK,OAAO,EACjB2D,EAAQ,CAAE,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,QAAS,CAAC,EAAG,OAAQ,CAAC,EAAG,YAAa,KAAK,YAAa,UAAW3B,EAAI,EAAG,QAAS,CAAC,EAAG,MAAAiD,CAAM,CAAC,GAGxI,IAAMC,EAAYlD,EAAI,EAGtB,MAAcQ,GAAM,IAAI,EAGxB,MAAM,KAAK,KAAK,EAEhBC,EAAYT,EAAI,EAChB,KAAK,MAAQ,QACb,IAAMmD,EAAM,MAAYjD,GAAQlC,EAAO,KAAK,MAAM,EAKlD,GAJA,KAAK,QAAUmF,EACf,KAAK,YAAY,aAAe,KAAK,IAAI,SAAW,KAAK,YAAY,cAAgB,GAAK,KAAK,MAAMnD,EAAI,EAAIS,CAAS,EAAI,KAAK,MAAMT,EAAI,EAAIS,CAAS,EACtJ,KAAK,QAAQ,YAAY,EAErB,CAAC0C,EAAI,OAAQ,CACX,KAAK,OAAO,OAAOpF,EAAI,mCAAmC,EAC9D,KAAK,KAAK,OAAO,EACjB4D,EAAQ,CAAE,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,QAAS,CAAC,EAAG,OAAQ,CAAC,EAAG,YAAa,KAAK,YAAa,UAAW3B,EAAI,EAAG,QAAS,CAAC,EAAG,MAAO,mCAAoC,CAAC,EAC3K,MACF,CACA,KAAK,KAAK,OAAO,EAEjBS,EAAYT,EAAI,EAChB,KAAK,OAAO,YAAc,MAAYoD,GAAK,KAAK,OAAQD,EAAI,MAAM,EAC7D,KAAK,YAAY,cAAa,KAAK,YAAY,YAAc,GAC7D,KAAK,YAAY,eAAc,KAAK,YAAY,aAAe,GACnE,KAAK,YAAY,cACd,KAAK,OAAO,aAAa,KAAK,YAAY,eAC9C,KAAK,YAAY,WAAa,KAAK,IAAI,SAAW,KAAK,YAAY,YAAc,GAAK,KAAK,MAAMnD,EAAI,EAAIS,CAAS,EAAI,KAAK,MAAMT,EAAI,EAAIS,CAAS,EAClJ,KAAK,QAAQ,gBAAgB,EAI7B,IAAI4C,EAA0D,CAAC,EAC3DC,EAA0D,CAAC,EAC3DC,EAA0D,CAAC,EAC3DC,EAAgE,CAAC,EAGrE,KAAK,MAAQ,cACT,KAAK,OAAO,OACdH,EAAU,KAAK,OAAO,KAAK,QAAeI,GAAW,KAAMN,EAAI,MAAM,EAAI,CAAC,EACtE,KAAK,YAAY,MAAM,OAAO,KAAK,YAAY,OAEnD1C,EAAYT,EAAI,EAChBqD,EAAU,KAAK,OAAO,KAAK,QAAU,MAAWI,GAAW,KAAMN,EAAI,MAAM,EAAI,CAAC,EAChF,KAAK,YAAY,KAAO,KAAK,IAAI,SAAW,KAAK,YAAY,MAAQ,GAAK,KAAK,MAAMnD,EAAI,EAAIS,CAAS,EAAI,KAAK,MAAMT,EAAI,EAAIS,CAAS,GAGpI,KAAK,OAAO,QAAU,KAAK,OAAO,KAAK,cAAgB,IAAM,KAAK,OAAO,KAAK,cAAgB,MAAK4C,EAAU,MAAMA,GAGvH,KAAK,QAAQ,aAAa,EAC1B,KAAK,MAAQ,cACb,IAAMK,EAAa,KAAK,OAAO,KAAK,cAAgB,GAAK7E,EAAU,KAAK,OAAQ,CAAE,KAAM,CAAE,YAAa,KAAK,OAAO,KAAK,QAAU,EAAKwE,EAAyB,OAAS,CAAE,CAAE,CAAC,EAAI,KAAK,OACnL,KAAK,OAAO,QACV9E,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,WAAY+E,EAAU,KAAK,OAAO,KAAK,QAAkBK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GAC5H9B,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,aAAc0B,EAAU,KAAK,OAAO,KAAK,QAAoBK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GACrI7B,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,iBAAkByB,EAAU,KAAK,OAAO,KAAK,QAAwBK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GAC7I5B,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,aAAYwB,EAAU,KAAK,OAAO,KAAK,QAAkBK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GACtI,KAAK,YAAY,MAAM,OAAO,KAAK,YAAY,OAEnDjD,EAAYT,EAAI,GACZ+B,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,WAAYuB,EAAU,KAAK,OAAO,KAAK,QAAU,MAAcK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GAClI1B,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,aAAcsB,EAAU,KAAK,OAAO,KAAK,QAAU,MAAgBK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GAC3IzB,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,iBAAkBqB,EAAU,KAAK,OAAO,KAAK,QAAU,MAAoBK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GACnJxB,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,aAAYoB,EAAU,KAAK,OAAO,KAAK,QAAU,MAAcK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GAChJ,KAAK,YAAY,KAAO,KAAK,IAAI,SAAW,KAAK,YAAY,MAAQ,GAAK,KAAK,MAAM1D,EAAI,EAAIS,CAAS,EAAI,KAAK,MAAMT,EAAI,EAAIS,CAAS,GAExI,KAAK,QAAQ,WAAW,EAGxB,KAAK,QAAQ,aAAa,EAC1B,KAAK,MAAQ,cACb,IAAMmD,EAAa,KAAK,OAAO,KAAK,cAAgB,GAAK/E,EAAU,KAAK,OAAQ,CAAE,KAAM,CAAE,YAAa,KAAK,OAAO,KAAK,QAAU,EAAKwE,EAAyB,OAAS,CAAE,CAAE,CAAC,EAAI,KAAK,OACnL,KAAK,OAAO,QACVjB,GAAAD,EAAA,KAAK,OAAO,KAAK,WAAjB,YAAAA,EAA2B,YAA3B,MAAAC,EAAsC,SAAS,cAAemB,EAAU,KAAK,OAAO,KAAK,QAAmBI,GAAQR,EAAI,OAAQS,CAAU,EAAI,CAAC,GAC1ItB,GAAAD,EAAA,KAAK,OAAO,KAAK,WAAjB,YAAAA,EAA2B,YAA3B,MAAAC,EAAsC,SAAS,eAAciB,EAAU,KAAK,OAAO,KAAK,QAAoBI,GAAQR,EAAI,OAAQS,CAAU,EAAI,CAAC,GACpJ,KAAK,YAAY,MAAM,OAAO,KAAK,YAAY,OAEnDnD,EAAYT,EAAI,GACZwC,IAAAD,EAAA,KAAK,OAAO,KAAK,WAAjB,YAAAA,EAA2B,YAA3B,MAAAC,GAAsC,SAAS,cAAee,EAAU,KAAK,OAAO,KAAK,QAAU,MAAeI,GAAQR,EAAI,OAAQS,CAAU,EAAI,CAAC,GAChJlB,IAAAD,EAAA,KAAK,OAAO,KAAK,WAAjB,YAAAA,EAA2B,YAA3B,MAAAC,GAAsC,SAAS,eAAca,EAAU,KAAK,OAAO,KAAK,QAAU,MAAgBI,GAAQR,EAAI,OAAQS,CAAU,EAAI,CAAC,GAC9J,KAAK,YAAY,KAAO,KAAK,IAAI,SAAW,KAAK,YAAY,MAAQ,GAAK,KAAK,MAAM5D,EAAI,EAAIS,CAAS,EAAI,KAAK,MAAMT,EAAI,EAAIS,CAAS,GAExI,KAAK,QAAQ,WAAW,EAGxB,KAAK,QAAQ,eAAe,EAC5B,KAAK,MAAQ,gBACT,KAAK,OAAO,QACVkC,GAAA,KAAK,OAAO,OAAO,YAAnB,MAAAA,GAA8B,SAAS,WAAYa,EAAY,KAAK,OAAO,OAAO,QAAkBG,GAAQR,EAAI,OAAQ,KAAK,MAAM,EAAI,CAAC,GACnIP,EAAA,KAAK,OAAO,OAAO,YAAnB,MAAAA,EAA8B,SAAS,eAAcY,EAAY,KAAK,OAAO,OAAO,QAAoBG,GAAQR,EAAI,OAAQ,KAAK,MAAM,EAAI,CAAC,GACjJ,KAAK,YAAY,QAAQ,OAAO,KAAK,YAAY,SAErD1C,EAAYT,EAAI,GACZ6C,GAAA,KAAK,OAAO,OAAO,YAAnB,MAAAA,GAA8B,SAAS,WAAYW,EAAY,KAAK,OAAO,OAAO,QAAU,MAAcG,GAAQR,EAAI,OAAQ,KAAK,MAAM,EAAI,CAAC,GACzIL,EAAA,KAAK,OAAO,OAAO,YAAnB,MAAAA,EAA8B,SAAS,eAAcU,EAAY,KAAK,OAAO,OAAO,QAAU,MAAgBG,GAAQR,EAAI,OAAQ,KAAK,MAAM,EAAI,CAAC,GAC3J,KAAK,YAAY,OAAS,KAAK,IAAI,SAAW,KAAK,YAAY,QAAU,GAAK,KAAK,MAAMnD,EAAI,EAAIS,CAAS,EAAI,KAAK,MAAMT,EAAI,EAAIS,CAAS,GAE5I,KAAK,QAAQ,aAAa,EAG1B,KAAK,MAAQ,eACT,KAAK,OAAO,QAAO,CAAC4C,EAASC,EAASC,EAASC,CAAS,EAAI,MAAM,QAAQ,IAAI,CAACH,EAASC,EAASC,EAASC,CAAS,CAAC,GAGxH,KAAK,MAAQ,iBACb,IAAIK,EAA8B,CAAC,EAC/B,KAAK,OAAO,QAAQ,UACtBpD,EAAYT,EAAI,EAChB6D,EAAa,CAAC,GAAWxE,GAAKgE,CAAuB,EAAG,GAAW/D,GAAKgE,CAAuB,EAAG,GAAW/D,GAAKgE,CAAuB,EAAG,GAAWO,GAAKT,CAAuB,CAAC,EAC/K,KAAK,OAAO,MACR,KAAK,YAAY,SAAS,OAAO,KAAK,YAAY,QADnC,KAAK,YAAY,QAAU,KAAK,IAAI,SAAW,KAAK,YAAY,SAAW,GAAK,KAAK,MAAMrD,EAAI,EAAIS,CAAS,EAAI,KAAK,MAAMT,EAAI,EAAIS,CAAS,GAItK,KAAK,YAAY,MAAQ,KAAK,IAAI,SAAW,KAAK,YAAY,OAAS,GAAK,KAAK,MAAMT,EAAI,EAAIkD,CAAS,EAAI,KAAK,MAAMlD,EAAI,EAAIkD,CAAS,EACxI,IAAMa,IAAQf,GAAAD,EAAA,KAAK,UAAL,YAAAA,EAAc,SAAd,YAAAC,EAAsB,QAAS,CAAC,EAC9C,KAAK,OAAS,CACZ,KAAMK,EACN,KAAMC,EACN,KAAMC,EACN,QAASM,EACT,OAAQL,EACR,YAAa,KAAK,YAClB,OAAQ,KAAK,QAAQ,OACrB,UAAW,KAAK,IAAI,EACpB,MAAO,KACP,IAAI,SAAU,CAAE,OAAeQ,GAAKX,EAAyBC,EAAyBC,EAAyBM,EAAYE,CAAK,CAAG,CACrI,EAGG,UAAQZ,EAAI,MAAM,EAGrB,KAAK,KAAK,QAAQ,EAClB,KAAK,MAAQ,OACbxB,EAAQ,KAAK,MAAM,CACrB,CAAC,CACH,CACF,EAvaE1E,GAAA,YACAC,GAAA,YACAC,GAAA,YAuEAC,GAAA",
-  "names": ["log", "msg", "dt", "ts", "join", "folder", "file", "separator", "path", "now", "validate", "defaults", "config", "parent", "msgs", "key", "defined", "same", "mergeDeep", "objects", "isObject", "obj", "prev", "pVal", "oVal", "config", "tfjs_esm_exports", "__export", "b", "d", "v", "__reExport", "dist_star", "r", "e", "o", "a", "t", "s", "f", "vertexIdentity", "colorMatrixWithAlpha", "colorMatrixWithoutAlpha", "pixelate", "blur", "convolution", "collect", "source", "prefix", "collection", "r", "match", "name", "GLProgram", "gl", "vertexSource", "fragmentSource", "__publicField", "type", "shader", "log", "vertexShader", "fragmentShader", "u", "GLImageFilter", "drawCount", "sourceTexture", "lastInChain", "currentFramebufferIndex", "tempFramebuffers", "filterChain", "vertexBuffer", "currentProgram", "fxcanvas", "canvas", "shaderProgramCache", "DRAW", "resize", "width", "height", "vertices", "createFramebufferTexture", "fbo", "renderbuffer", "texture", "getTempFramebuffer", "index", "draw", "flags", "target", "flipY", "compileShader", "vertexIdentity", "floatSize", "vertSize", "filter", "matrix", "m", "colorMatrixWithoutAlpha", "colorMatrixWithAlpha", "program", "brightness", "b", "amount", "x", "y", "v", "o", "rotation", "cos", "sin", "lumR", "lumG", "lumB", "pixelSizeX", "pixelSizeY", "convolution", "a", "size", "s", "blurSizeX", "blurSizeY", "blur", "pixelate", "args", "func", "image", "i", "f", "histogramEqualization", "inputImage", "squeeze", "channels", "min", "max", "absMax", "channel", "maxValue", "sub", "range", "fact", "enh", "rgb", "reshape", "maxSize", "inCanvas", "outCanvas", "tmpCanvas", "fx", "last", "canvas", "width", "height", "c", "env", "copy", "input", "output", "outputCanvas", "process", "config", "getTensor", "log", "d", "tensor", "rgb", "cast", "originalWidth", "originalHeight", "targetWidth", "targetHeight", "inCtx", "GLImageFilter", "pixels", "depth", "arr", "tempData", "casted", "histogramEqualization", "skip", "skipFrame", "t", "diffRelative", "compare", "input1", "input2", "Env", "__publicField", "v", "raw", "platformMatch", "c", "canvas", "ctx", "gl", "e", "kernel", "cpu", "env", "options", "modelStats", "httpHandler", "url", "init", "log", "setModelLoadOptions", "config", "loadModel", "modelPath", "_a", "_b", "_c", "modelUrl", "join", "modelPathSegments", "shortModelName", "cachedModelName", "models_exports", "cachedModels", "e", "tfLoadOptions", "model", "b", "loaded", "artifacts", "err", "saveResult", "models_exports", "__export", "Models", "getModelStats", "load", "reset", "validate", "model", "last", "raceNames", "ageWeights", "lastCount", "lastTime", "skipped", "load", "config", "_a", "env", "log", "loadModel", "predict", "image", "idx", "count", "_b", "skipFrame", "skipTime", "now", "resolve", "t", "box", "obj", "gender", "race", "i", "a", "b", "ageSorted", "age", "tensor", "constants", "init", "model", "last", "lastCount", "lastTime", "skipped", "load", "config", "env", "log", "loadModel", "predict", "image", "idx", "count", "_a", "_b", "_c", "_d", "skipFrame", "skipTime", "now", "resolve", "t", "constants", "obj", "data", "tensor", "model", "last", "lastCount", "lastTime", "skipped", "rgb", "load", "config", "env", "log", "loadModel", "predict", "image", "idx", "count", "_a", "_b", "_c", "_d", "skipFrame", "skipTime", "now", "resolve", "t", "red", "green", "blue", "redNorm", "greenNorm", "blueNorm", "grayscale", "constants", "obj", "data", "tensor", "model", "cached", "skipped", "lastCount", "lastTime", "load", "config", "_a", "env", "log", "loadModel", "predict", "image", "idx", "count", "_b", "skipTime", "now", "skipFrame", "resolve", "resize", "res", "num", "meshAnnotations", "meshLandmarks", "blazeFaceLandmarks", "irisIndices", "UV468", "TRI468", "VTX68", "VTX33", "VTX7", "UV68", "x", "UV468", "UV33", "UV7", "connectionsToIndices", "connections", "indices", "connection", "pairsLips", "pairsLeftEye", "pairsLeftEyebrow", "pairsLeftIris", "pairsRightEye", "pairsRightEyebrow", "pairsRightIris", "pairsFaceContour", "contourKeypoints", "getBoxSize", "box", "getBoxCenter", "clampBox", "input", "getRawBox", "scaleBoxCoordinates", "factor", "startPoint", "endPoint", "cutAndResize", "image", "cropSize", "h", "w", "cutBox", "crop", "norm", "constants", "enlargeBox", "center", "size", "halfSize", "squarifyBox", "centers", "calculateLandmarksBoundingBox", "landmarks", "x", "d", "y", "fixedRotationMatrix", "normalizeRadians", "angle", "computeRotation", "point1", "point2", "buildTranslationMatrix", "x", "y", "dot", "v1", "v2", "product", "i", "getColumnFrom2DArr", "arr", "columnIndex", "column", "multiplyTransformMatrices", "mat1", "mat2", "size", "row", "col", "buildRotationMatrix", "rotation", "center", "cosA", "sinA", "rotationMatrix", "translationMatrix", "translationTimesRotation", "negativeTranslationMatrix", "invertTransformMatrix", "matrix", "rotationComponent", "translationComponent", "invertedTranslation", "rotatePoint", "homogeneousCoordinate", "generateAnchors", "inputSize", "spec", "anchors", "i", "stride", "gridRows", "gridCols", "anchorsNum", "gridY", "anchorY", "gridX", "anchorX", "n", "transformRawCoords", "coordsRaw", "box", "angle", "rotationMatrix", "boxSize", "getBoxSize", "coordsScaled", "coord", "largeAngle", "coordsRotationMatrix", "buildRotationMatrix", "fixedRotationMatrix", "coordsRotated", "rotatePoint", "inverseRotationMatrix", "invertTransformMatrix", "boxCenter", "getBoxCenter", "offsets", "dot", "correctFaceRotation", "rotate", "input", "symmetryLine", "meshLandmarks", "blazeFaceLandmarks", "face", "env", "computeRotation", "center", "centerRaw", "rotated", "cutAndResize", "findFaceCenter", "mesh", "x", "m", "y", "calculateFaceBox", "previousBox", "keypointsCount", "faceBoxScaleFactor", "model", "anchors", "inputSize", "inputSizeT", "size", "load", "config", "_a", "env", "log", "loadModel", "generateAnchors", "decodeBoxes", "boxOutputs", "constants", "boxes", "tensor", "getBoxes", "inputImage", "_b", "_c", "_d", "t", "res", "sorted", "a", "b", "nms", "scores", "i", "confidence", "points", "rawBox", "scaledBox", "scaleBoxCoordinates", "enlargedBox", "enlargeBox", "squaredBox", "squarifyBox", "blazeposecoords_exports", "__export", "connected", "kpt", "inputSize", "anchorTensor", "numLayers", "strides", "createAnchors", "anchors", "layerId", "anchorCount", "lastSameStrideLayer", "stride", "featureMapHeight", "featureMapWidth", "y", "x", "anchorId", "a", "calc", "keypoints", "outputSize", "coords", "pt", "min", "max", "box", "boxRaw", "square", "center", "dist", "scale", "scaleFact", "env", "models", "inputSize", "skipped", "outputNodes", "cache", "cropBox", "padding", "lastTime", "sigmoid", "x", "loadDetect", "config", "loadModel", "inputs", "log", "createAnchors", "loadPose", "prepareImage", "input", "size", "t", "final", "cropBox", "height", "width", "padding", "constants", "tensor", "rescaleKeypoints", "keypoints", "outputSize", "kpt", "fixKeypoints", "leftPalm", "k", "leftWrist", "leftIndex", "rightPalm", "rightWrist", "rightIndex", "detectLandmarks", "config", "_a", "models", "outputNodes", "poseScore", "points", "distances", "keypointsRelative", "depth", "i", "score", "sigmoid", "presence", "adjScore", "positionRaw", "inputSize", "position", "distance", "kpts", "boxes", "calc", "annotations", "name", "indexes", "connected", "pt", "pt0", "pt1", "predict", "skipTime", "now", "lastTime", "skipFrame", "skipped", "cache", "labels", "model", "inputSize", "last", "lastTime", "skipped", "load", "config", "env", "log", "loadModel", "inputs", "process", "res", "outputShape", "t", "results", "detections", "arr", "nms", "i", "id", "score", "classVal", "label", "labels", "x", "y", "boxRaw", "box", "tensor", "predict", "input", "skipTime", "now", "skipFrame", "resolve", "outputSize", "resize", "objectT", "obj", "efficientposecoords_exports", "__export", "connected", "kpt", "model", "lastTime", "cache", "skipped", "load", "config", "env", "log", "loadModel", "max2d", "inputs", "minScore", "width", "height", "reshaped", "max", "newScore", "coordinates", "mod", "x", "div", "predict", "image", "skipTime", "now", "skipFrame", "resolve", "_a", "tensor", "resize", "enhance", "constants", "resT", "squeeze", "stack", "id", "y", "partScore", "kpt", "s", "prev", "curr", "a", "xRaw", "yRaw", "name", "indexes", "connected", "pt", "i", "pt0", "pt1", "annotations", "model", "last", "lastCount", "lastTime", "skipped", "load", "config", "_a", "env", "log", "loadModel", "predict", "image", "idx", "count", "_b", "skipFrame", "skipTime", "now", "resolve", "obj", "t", "inputSize", "constants", "data", "i", "a", "b", "tensor", "model", "last", "lastCount", "lastTime", "skipped", "load", "config", "env", "log", "loadModel", "predict", "input", "idx", "count", "_a", "_b", "skipFrame", "skipTime", "now", "resolve", "data", "t", "output", "model", "inputSize", "irisEnlarge", "leftOutline", "meshAnnotations", "rightOutline", "eyeLandmarks", "irisLandmarks", "load", "config", "_a", "env", "log", "loadModel", "replaceIrisCoords", "rawCoords", "newCoords", "prefix", "keys", "i", "irisIndices", "key", "indices", "originalIndices", "j", "index", "getLeftToRightEyeDepthDifference", "leftEyeZ", "rightEyeZ", "getEyeBox", "face", "eyeInnerCornerIndex", "eyeOuterCornerIndex", "meshSize", "flip", "box", "squarifyBox", "enlargeBox", "calculateLandmarksBoundingBox", "boxSize", "getBoxSize", "crop", "flipped", "getEyeCoords", "eyeData", "eyeBox", "eyeBoxSize", "eyeRawCoords", "x", "y", "z", "getAdjustedIrisCoords", "irisCoords", "direction", "upperCenterZ", "lowerCenterZ", "averageZ", "coord", "augmentIris", "leftEyeBox", "leftEyeBoxSize", "leftEyeCrop", "rightEyeBox", "rightEyeBoxSize", "rightEyeCrop", "combined", "eyePredictions", "eyePredictionsData", "leftEyeData", "leftEyeRawCoords", "leftIrisRawCoords", "rightEyeData", "rightEyeRawCoords", "rightIrisRawCoords", "leftToRightEyeDepthDifference", "adjustedLeftIrisCoords", "adjustedRightIrisCoords", "LIPS_CONNECTIONS", "LEFT_EYE_CONNECTIONS", "LEFT_EYEBROW_CONNECTIONS", "LEFT_IRIS_CONNECTIONS", "RIGHT_EYE_CONNECTIONS", "RIGHT_EYEBROW_CONNECTIONS", "RIGHT_IRIS_CONNECTIONS", "FACE_OVAL_CONNECTIONS", "connectionsToIndices", "connections", "indices", "connection", "MEDIAPIPE_FACE_MESH_KEYPOINTS_BY_CONTOUR", "LIPS_CONNECTIONS", "LEFT_EYE_CONNECTIONS", "LEFT_EYEBROW_CONNECTIONS", "LEFT_IRIS_CONNECTIONS", "RIGHT_EYE_CONNECTIONS", "RIGHT_EYEBROW_CONNECTIONS", "RIGHT_IRIS_CONNECTIONS", "FACE_OVAL_CONNECTIONS", "indexLabelPairs", "label", "index", "MEDIAPIPE_FACE_MESH_KEYPOINTS", "LANDMARKS_REFINEMENT_LIPS_CONFIG", "LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG", "LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG", "augment", "rawCoords", "results", "t", "r", "irisLDepth", "LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG", "prev", "curr", "i", "irisRDepth", "LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG", "LANDMARKS_REFINEMENT_LIPS_CONFIG", "cache", "model", "inputSize", "predict", "input", "config", "_a", "_b", "_c", "_d", "_e", "_f", "_g", "_h", "_i", "_j", "_k", "skipTime", "now", "skipFrame", "getBoxes", "faces", "newCache", "id", "i", "box", "angle", "rotationMatrix", "face", "correctFaceRotation", "size", "equilized", "histogramEqualization", "log", "results", "faceConfidence", "t", "clampBox", "getRawBox", "pt", "key", "blazeFaceLandmarks", "meshT", "coordsReshaped", "rawCoords", "augment", "augmentIris", "transformRawCoords", "meshAnnotations", "index", "calculatedBox", "calculateFaceBox", "load", "env", "loadModel", "triangulation", "TRI468", "uvmap", "UV468", "model", "last", "lastTime", "lastCount", "skipped", "load", "config", "_a", "env", "log", "loadModel", "enhance", "input", "tensor", "crop", "norm", "constants", "predict", "image", "idx", "count", "_b", "_c", "_d", "skipFrame", "skipTime", "now", "resolve", "obj", "enhanced", "resT", "gender", "t", "confidence", "argmax", "age", "all", "desc", "descriptor", "getBoxSize", "box", "getBoxCenter", "cutBoxFromImageAndResize", "image", "cropSize", "h", "w", "boxes", "scaleBoxCoordinates", "factor", "startPoint", "endPoint", "palmLandmarks", "coord", "enlargeBox", "center", "size", "newHalfSize", "squarifyBox", "centers", "halfSize", "normalizeRadians", "angle", "computeRotation", "point1", "point2", "radians", "buildTranslationMatrix", "x", "y", "dot", "v1", "v2", "product", "i", "getColumnFrom2DArr", "arr", "columnIndex", "column", "multiplyTransformMatrices", "mat1", "mat2", "size", "row", "col", "buildRotationMatrix", "rotation", "center", "cosA", "sinA", "rotationMatrix", "translationMatrix", "translationTimesRotation", "negativeTranslationMatrix", "invertTransformMatrix", "matrix", "rotationComponent", "translationComponent", "invertedTranslation", "rotatePoint", "homogeneousCoordinate", "anchors", "HandDetector", "model", "__publicField", "anchors", "anchor", "boxes", "t", "res", "tensor", "rawPalmLandmarks", "index", "input", "config", "constants", "scores", "nms", "hands", "p", "box", "startPoint", "endPoint", "palmLandmarks", "hand", "scaled", "scaleBoxCoordinates", "palmBoxEnlargeFactor", "handBoxEnlargeFactor", "palmLandmarkIds", "palmLandmarksPalmBase", "palmLandmarksMiddleFingerBase", "lastTime", "HandPipeline", "handDetector", "handPoseModel", "__publicField", "landmarks", "xs", "d", "ys", "startPoint", "endPoint", "palmLandmarks", "rotationMatrix", "rotatedPalmLandmarks", "coord", "rotatePoint", "boxAroundPalm", "enlargeBox", "squarifyBox", "boundingBox", "boxAroundHand", "i", "rawCoords", "box2", "angle", "boxSize", "getBoxSize", "scaleFactor", "coordsScaled", "coordsRotationMatrix", "buildRotationMatrix", "coordsRotated", "inverseRotationMatrix", "invertTransformMatrix", "boxCenter", "getBoxCenter", "originalBoxCenter", "dot", "image", "config", "useFreshBox", "boxes", "skipTime", "now", "skipFrame", "hands", "currentBox", "computeRotation", "palmCenter", "palmCenterNormalized", "rotatedImage", "env", "newBox", "croppedInput", "cutBoxFromImageAndResize", "handImage", "constants", "confidenceT", "keypoints", "confidence", "keypointsReshaped", "coords", "nextBoundingBox", "result", "enlarged", "a", "Finger", "value", "FingerCurl", "FingerDirection", "FingerGesture", "name", "__publicField", "finger", "curl", "confidence", "position", "weight", "total", "a", "b", "el", "detectedCurls", "detectedDirections", "fingerIdx", "detectedCurl", "expectedCurls", "expectedCurl", "score", "detectedDirection", "expectedDirections", "expectedDirection", "thumb", "index", "middle", "ring", "pinky", "Finger", "none", "half", "full", "FingerCurl", "verticalUp", "verticalDown", "horizontalLeft", "horizontalRight", "diagonalUpRight", "diagonalUpLeft", "diagonalDownRight", "diagonalDownLeft", "FingerDirection", "ThumbsUp", "FingerGesture", "finger", "Victory", "Point", "MiddleFinger", "OpenPalm", "fingergesture_default", "minConfidence", "options", "calculateSlope", "point1x", "point1y", "point2x", "point2y", "value", "slope", "getSlopes", "point1", "point2", "slopeXY", "slopeYZ", "angleOrientationAt", "angle", "weightageAt", "isVertical", "isDiagonal", "isHorizontal", "estimateFingerCurl", "startPoint", "midPoint", "endPoint", "start_mid_x_dist", "start_end_x_dist", "mid_end_x_dist", "start_mid_y_dist", "start_end_y_dist", "mid_end_y_dist", "start_mid_z_dist", "start_end_z_dist", "mid_end_z_dist", "start_mid_dist", "start_end_dist", "mid_end_dist", "cos_in", "angleOfCurve", "fingerCurl", "FingerCurl", "estimateHorizontalDirection", "max_dist_x", "estimatedDirection", "FingerDirection", "estimateVerticalDirection", "max_dist_y", "estimateDiagonalDirection", "reqd_vertical_direction", "reqd_horizontal_direction", "calculateFingerDirection", "fingerSlopes", "voteVertical", "voteDiagonal", "voteHorizontal", "start_end_x_y_dist_ratio", "max_dist", "calc_start_point_x", "calc_start_point_y", "calc_end_point_x", "calc_end_point_y", "totalAngle", "votes", "fingerSlope", "fingerVotes", "estimate", "landmarks", "slopesXY", "slopesYZ", "fingerCurls", "fingerDirections", "finger", "Finger", "points", "slopeAtXY", "slopeAtYZ", "point", "slopes", "pointIndexAt", "fingerPointsAt", "fingerCurled", "fingerPosition", "analyze", "keypoints", "estimatorRes", "fingerIdx", "match", "poses", "gesture", "fingergesture_default", "confidence", "meshAnnotations", "handDetectorModel", "handPoseModel", "handPipeline", "predict", "input", "config", "predictions", "hands", "i", "annotations", "key", "index", "keypoints", "box", "boxRaw", "pt", "landmarks", "analyze", "load", "_a", "_b", "env", "loadModel", "log", "handDetector", "HandDetector", "HandPipeline", "models", "modelOutputNodes", "inputSize", "classes", "faceIndex", "boxExpandFact", "maxDetectorResolution", "detectorExpandFact", "skipped", "lastTime", "outputSize", "cache", "fingerMap", "loadDetect", "config", "_a", "env", "log", "fakeOps", "loadModel", "inputs", "loadSkeleton", "detectHands", "input", "config", "hands", "models", "t", "ratio", "height", "maxDetectorResolution", "width", "modelOutputNodes", "classScores", "faceIndex", "id", "nms", "scores", "classNum", "nmsIndex", "boxSlice", "boxYX", "boxData", "boxRaw", "scale", "detectorExpandFact", "boxFull", "outputSize", "score", "label", "classes", "hand", "tensor", "a", "b", "detectFingers", "h", "boxCrop", "inputSize", "constants", "rawScore", "coordsNorm", "kpt", "analyze", "key", "fingerMap", "index", "predict", "_a", "_b", "skipped", "skipTime", "now", "lastTime", "skipFrame", "cache", "resolve", "skipTimeExtended", "skipFrameExtended", "handBox", "oldCache", "i", "boxKpt", "square", "boxScale", "boxExpandFact", "boxScaleRaw", "bbox", "calc", "model", "cached", "skipped", "lastCount", "lastTime", "load", "config", "_a", "env", "log", "loadModel", "predict", "image", "idx", "count", "_b", "skipTime", "now", "skipFrame", "resolve", "resize", "res", "num", "movenetcoords_exports", "__export", "connected", "horizontal", "kpt", "relative", "vertical", "maxJitter", "cache", "bodyParts", "body", "pair", "horizontal", "left", "kp", "right", "tmp", "vertical", "lower", "higher", "compare", "relative", "leftTo", "rightTo", "distanceLeft", "distanceRight", "jitter", "keypoints", "i", "diff", "padInput", "input", "inputSize", "t", "final", "tensor", "rescaleBody", "outputSize", "kpt", "rescaledBoxes", "calc", "pt", "model", "inputSize", "skipped", "cache", "load", "config", "env", "log", "fakeOps", "loadModel", "parseSinglePose", "res", "image", "kpt", "keypoints", "score", "id", "positionRaw", "prev", "curr", "bodies", "newBox", "calc", "pt", "annotations", "name", "indexes", "connected", "i", "pt0", "kp", "pt1", "body", "bodyParts", "parseMultiPose", "totalScore", "a", "b", "predict", "input", "skipTime", "now", "skipFrame", "resolve", "t", "padInput", "rescaleBody", "jitter", "tensor", "model", "last", "lastTime", "skipped", "inputSize", "scaleBox", "load", "config", "env", "loadModel", "inputs", "log", "process", "res", "outputShape", "id", "results", "strideSize", "baseSize", "scoresT", "a", "labels", "featuresT", "boxIdx", "scores", "i", "j", "score", "cx", "cy", "boxOffset", "x", "y", "w", "h", "boxRaw", "box", "result", "t", "nmsBoxes", "nmsScores", "nmsIdx", "nms", "_val", "idx", "b", "predict", "image", "skipTime", "now", "skipFrame", "resolve", "outputSize", "resize", "norm", "constants", "transpose", "objectT", "obj", "partNames", "count", "partIds", "result", "jointName", "i", "connectedPartNames", "connectedPartIndices", "jointNameA", "jointNameB", "poseChain", "getBoundingBox", "keypoints", "coord", "maxX", "maxY", "minX", "minY", "x", "y", "scalePoses", "poses", "height", "width", "inputResolutionHeight", "inputResolutionWidth", "scaleY", "scaleX", "scalePose", "pose", "i", "score", "part", "position", "MaxHeap", "maxSize", "getElementValue", "__publicField", "max", "k", "j", "t", "getOffsetPoint", "keypoint", "offsets", "count", "getImageCoords", "outputStride", "heatmapY", "heatmapX", "clamp", "a", "min", "max", "squaredDistance", "y1", "x1", "y2", "x2", "dy", "dx", "addVectors", "b", "model", "poseNetOutputs", "localMaximumRadius", "outputStride", "squaredNmsRadius", "traverse", "edgeId", "sourceKeypoint", "targetId", "scores", "offsets", "displacements", "offsetRefineStep", "getDisplacement", "point", "getStridedIndexNearPoint", "height", "width", "clamp", "sourceKeypointIndices", "displacement", "targetKeypoint", "addVectors", "i", "targetKeypointIndices", "offsetPoint", "getOffsetPoint", "targetKeyPointIndices", "score", "partNames", "decodePose", "root", "displacementsFwd", "displacementsBwd", "tuples", "poseChain", "parentJoinName", "childJoinName", "partIds", "edgesFwd", "childJointId", "edgesBwd", "parentJointId", "numParts", "numEdges", "keypoints", "rootPoint", "getImageCoords", "edge", "sourceId", "scoreIsMaximumInLocalWindow", "keypointId", "heatmapY", "heatmapX", "localMaximum", "yStart", "yEnd", "yCurrent", "xStart", "xEnd", "xCurrent", "buildPartWithScoreQueue", "minConfidence", "numKeypoints", "queue", "MaxHeap", "withinRadius", "poses", "x", "y", "_a", "correspondingKeypoint", "squaredDistance", "getInstanceScore", "existingPoses", "result", "position", "decode", "maxDetected", "rootImageCoords", "a", "box", "getBoundingBox", "predict", "input", "config", "res", "resized", "normalized", "results3d", "buffers", "tensor", "t", "decoded", "scalePoses", "load", "env", "loadModel", "log", "model", "busy", "load", "config", "env", "loadModel", "log", "process", "input", "background", "_a", "_b", "inputImage", "width", "height", "t", "constants", "data", "tensor", "alphaCanvas", "canvas", "alphaCtx", "alphaData", "compositeCanvas", "compositeCtx", "compositeData", "i", "mergedCanvas", "bgImage", "ctxMerge", "Models", "__publicField", "getModelStats", "instance", "totalSizeFromManifest", "totalSizeWeights", "totalSizeLoading", "m", "modelStats", "percentageLoaded", "reset", "model", "load", "_a", "_b", "_c", "_d", "_e", "_f", "_g", "_h", "_i", "_j", "_k", "_l", "_m", "_n", "_o", "_p", "_q", "_r", "_s", "_t", "_u", "_v", "_w", "_x", "_y", "_z", "_A", "_B", "_C", "_D", "_E", "env", "loadPose", "loadDetect", "loadSkeleton", "validate", "simpleOps", "defined", "ops", "executor", "kernel", "op", "log", "missing", "config", "extensions", "gl", "register", "instance", "_a", "log", "reset", "canvas", "err", "e", "ctx", "kernelConfig", "newKernelConfig", "current", "registerCustomOps", "env", "kernelMod", "op", "check", "instance", "force", "timeStamp", "now", "log", "adapter", "adapterInfo", "register", "available", "e", "tfjs_esm_exports", "simd", "mt", "init", "err", "gl", "fakeOps", "kernelNames", "config", "kernelName", "kernelConfig", "kernel", "draw_exports", "__export", "all", "body", "canvas", "face", "gesture", "hand", "object", "options", "person", "getCanvasContext", "input", "log", "ctx", "rad2deg", "theta", "colorDepth", "z", "opt", "rgb", "point", "x", "y", "localOptions", "rect", "width", "height", "cx", "cy", "lines", "points", "pt", "curves", "i", "xc", "yc", "arrow", "from", "to", "radius", "angle", "options", "opt", "drawLabels", "f", "ctx", "labels", "emotion", "a", "rad2deg", "i", "x", "y", "drawIrisElipse", "sizeX", "sizeY", "drawGazeSpheres", "_a", "valX", "valY", "pathV", "pathH", "drawGazeArrows", "_b", "_c", "_d", "leftGaze", "arrow", "rightGaze", "drawFacePolygons", "TRI468", "points", "index", "lines", "drawFacePoints", "point", "LANDMARKS_REFINEMENT_LIPS_CONFIG", "LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG", "LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG", "drawFaceBoxes", "rect", "face", "inCanvas", "result", "drawOptions", "mergeDeep", "options", "getCanvasContext", "body", "inCanvas", "result", "drawOptions", "_a", "localOptions", "mergeDeep", "options", "ctx", "getCanvasContext", "i", "rect", "pt", "colorDepth", "point", "part", "connected", "curves", "hand", "inCanvas", "result", "drawOptions", "localOptions", "mergeDeep", "options", "ctx", "getCanvasContext", "h", "rect", "pt", "colorDepth", "point", "addHandLabel", "part", "title", "z", "addHandLine", "i", "object", "inCanvas", "result", "drawOptions", "localOptions", "mergeDeep", "options", "ctx", "getCanvasContext", "h", "rect", "label", "gesture", "inCanvas", "result", "drawOptions", "localOptions", "mergeDeep", "options", "ctx", "getCanvasContext", "i", "j", "where", "what", "who", "label", "drawTime", "person", "inCanvas", "result", "drawOptions", "localOptions", "mergeDeep", "options", "ctx", "getCanvasContext", "i", "rect", "label", "canvas", "input", "output", "all", "timeStamp", "now", "promise", "face", "body", "hand", "object", "gesture", "env", "expandFact", "alpha", "insidePoly", "x", "y", "polygon", "inside", "j", "i", "mask", "face", "width", "height", "buffer", "silhouette", "pt", "meshAnnotations", "output", "calculateGaze", "face", "radians", "pt1", "pt2", "offsetIris", "eyeRatio", "left", "irisCenter", "eyeCenter", "eyeSize", "eyeDiff", "strength", "calculateFaceAngle", "imageSize", "normalize", "v", "length", "subVectors", "a", "b", "x", "y", "z", "crossVectors", "rotationMatrixToEulerAngle", "r", "r00", "_r01", "_r02", "r10", "r11", "r12", "r20", "r21", "r22", "thetaX", "thetaY", "thetaZ", "mesh", "size", "pts", "pt", "y_axis", "x_axis", "z_axis", "matrix", "angle", "gaze", "detectFace", "instance", "input", "_a", "_b", "_c", "_d", "_e", "_f", "_g", "_h", "_i", "_j", "_k", "_l", "_m", "_n", "_o", "_p", "_q", "_r", "_s", "_t", "_u", "_v", "timeStamp", "now", "ageRes", "gearRes", "genderRes", "emotionRes", "mobilefacenetRes", "antispoofRes", "livenessRes", "descRes", "faceRes", "faces", "predict", "env", "i", "log", "masked", "mask", "rotation", "calculateFaceAngle", "irisSize", "tensor", "res", "body", "res", "gestures", "i", "leftWrist", "a", "rightWrist", "nose", "leftShoulder", "rightShoulder", "face", "zDiff", "xDiff", "mouthOpen", "chinDepth", "iris", "sizeXLeft", "sizeYLeft", "areaLeft", "sizeXRight", "sizeYRight", "areaRight", "center", "leftIrisCenterX", "rightIrisCenterX", "rightIrisCenterY", "leftIrisCenterY", "hand", "fingers", "finger", "pos", "closest", "best", "highest", "poses", "match", "pose", "bufferedResult", "interpolateTime", "calc", "newResult", "config", "_a", "_b", "_c", "_d", "_e", "_f", "_g", "_h", "_i", "_j", "_k", "_l", "_m", "_n", "_o", "_p", "_q", "_r", "_s", "_t", "_u", "_v", "_w", "_x", "_y", "_z", "_A", "t0", "now", "elapsed", "bufferedFactor", "i", "box", "newBoxCoord", "j", "boxRaw", "keypoints", "newKpt", "annotations", "coords", "efficientposecoords_exports", "blazeposecoords_exports", "movenetcoords_exports", "name", "indexes", "pt", "pt0", "kp", "pt1", "b", "landmark", "coord", "k", "key", "val", "rotation", "newPersons", "t1", "env", "match_exports", "__export", "distance", "match", "similarity", "descriptor1", "descriptor2", "options", "sum", "i", "diff", "normalizeDistance", "dist", "order", "min", "max", "root", "norm", "descriptor", "descriptors", "lowestDistance", "index", "res", "normalizedSimilarity", "join", "faces", "bodies", "hands", "gestures", "shape", "_a", "_b", "_c", "_d", "_e", "_f", "_g", "_h", "_i", "_j", "_k", "_l", "_m", "_n", "_o", "_p", "id", "persons", "face", "person", "body", "hand", "gesture", "x", "y", "extractXY", "box", "minX", "minY", "face", "body", "warmupBitmap", "instance", "b64toBlob", "base64", "type", "res", "blob", "face", "body", "bitmap", "warmupCanvas", "resolve", "src", "img", "env", "canvas", "log", "ctx", "tensor", "warmupNode", "atob", "str", "tfjs_esm_exports", "data", "expanded", "runInference", "runCompile", "allModels", "backendType", "webGLBackend", "numTensorsStart", "compiledModels", "modelName", "model", "key", "val", "shape", "dtype", "dim", "t", "e", "kernels", "numTensorsEnd", "warmup", "userConfig", "t0", "now", "mergeDeep", "t1", "_numTensors", "_analyzeMemoryLeaks", "_checkSanity", "_sanity", "Human", "userConfig", "__publicField", "__privateAdd", "msg", "__privateGet", "currentTensors", "previousTensors", "__privateSet", "leaked", "log", "input", "d", "e", "similarity", "distance", "match", "event", "_a", "env", "tfVersion", "v", "config", "version", "mergeDeep", "setModelLoadOptions", "tfjs_esm_exports", "Models", "options", "output", "canvas", "result", "face", "body", "hand", "gesture", "object", "person", "all", "triangulation", "uvmap", "currentBackend", "validate", "now", "getTensor", "process", "background", "enhance", "firstImageTensor", "secondImageTensor", "compare", "check", "timeStamp", "count", "model", "load", "current", "calc", "getModelStats", "t0", "res", "warmup", "t1", "profile", "kernels", "kernel", "kernelArr", "key", "a", "b", "resolve", "_b", "_c", "_d", "_e", "_f", "_g", "_h", "_i", "_j", "_k", "_l", "_m", "_n", "_o", "_p", "_q", "_r", "_s", "_t", "_u", "_v", "error", "timeStart", "img", "skip", "faceRes", "bodyRes", "handRes", "objectRes", "detectFace", "bodyConfig", "predict", "handConfig", "gestureRes", "iris", "shape", "join"]
+  "sourcesContent": ["import type { Config } from '../exports';\n\n/**\n * Simple helper functions used accross codebase\n */\n\n// helper function: wrapper around console output\nexport function log(...msg): void {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n\n// helper function: join two paths\nexport function join(folder: string, file: string): string {\n  const separator = folder.endsWith('/') ? '' : '/';\n  const skipJoin = file.startsWith('.') || file.startsWith('/') || file.startsWith('http:') || file.startsWith('https:') || file.startsWith('file:');\n  const path = skipJoin ? `${file}` : `${folder}${separator}${file}`;\n  if (!path.toLocaleLowerCase().includes('.json')) throw new Error(`modelpath error: expecting json file: ${path}`);\n  return path;\n}\n\n// helper function: gets elapsed time on both browser and nodejs\nexport const now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\n// helper function: checks current config validity\nexport function validate(defaults: Partial<Config>, config: Partial<Config>, parent = 'config', msgs: Array<{ reason: string, where: string, expected?: string }> = []) {\n  for (const key of Object.keys(config)) {\n    if (typeof config[key] === 'object') {\n      validate(defaults[key], config[key], key, msgs);\n    } else {\n      const defined = defaults && (typeof defaults[key] !== 'undefined');\n      if (!defined) msgs.push({ reason: 'unknown property', where: `${parent}.${key} = ${config[key]}` });\n      const same = defaults && typeof defaults[key] === typeof config[key];\n      if (defined && !same) msgs.push({ reason: 'property type mismatch', where: `${parent}.${key} = ${config[key]}`, expected: typeof defaults[key] });\n    }\n    // ok = ok && defined && same;\n  }\n  if (config.debug && parent === 'config' && msgs.length > 0) log('invalid configuration', msgs);\n  return msgs;\n}\n\n// helper function: perform deep merge of multiple objects so it allows full inheritance with overrides\nexport function mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\n// helper function: return min and max from input array\nexport const minmax = (data: Array<number>) => data.reduce((acc: Array<number>, val) => {\n  acc[0] = (acc[0] === undefined || val < acc[0]) ? val : acc[0];\n  acc[1] = (acc[1] === undefined || val > acc[1]) ? val : acc[1];\n  return acc;\n}, []);\n\n// helper function: async wait\nexport async function wait(time: number) {\n  const waiting = new Promise((resolve) => { setTimeout(() => resolve(true), time); });\n  await waiting;\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\n/** Generic config type inherited by all module types */\nexport interface GenericConfig {\n  /** is module enabled? */\n  enabled: boolean,\n  /** path to model json file (relative to `modelBasePath` */\n  modelPath: string,\n  /** how many max frames to go without re-running model if cached results are acceptable\n   * for two-phase models such as face and hand caching applies to bounding boxes detection only */\n  skipFrames: number,\n  /** how many max milliseconds to go without re-running model if cached results are acceptable\n  * for two-phase models such as face and hand caching applies to bounding boxes detection only */\n  skipTime: number,\n}\n\n/** Detector part of face configuration */\nexport interface FaceDetectorConfig extends GenericConfig {\n  /** is face rotation correction performed after detecting face?\n   * used to correctly analyze faces under high angles\n  */\n  rotation: boolean,\n  /** maximum number of detected faces */\n  maxDetected: number,\n  /** minimum confidence for a detected face before results are discarded */\n  minConfidence: number,\n  /** minimum overlap between two detected faces before one is discarded */\n  iouThreshold: number,\n  /** should child models perform on masked image of a face */\n  mask: boolean,\n  /** should face detection return processed and cropped face tensor that can with an external model for addtional processing?\n   * if enabled it must be manually deallocated to avoid memory leak */\n  return: boolean,\n}\n\n/** Mesh part of face configuration */\nexport interface FaceMeshConfig extends GenericConfig {\n  /** Keep detected faces that cannot be verified using facemesh */\n  keepInvalid: boolean\n}\n\n/** Iris part of face configuration */\nexport interface FaceIrisConfig extends GenericConfig {}\n\n/** Attention part of face configuration */\nexport interface FaceAttentionConfig extends GenericConfig {}\n\n/** Description or face embedding part of face configuration\n * - also used by age and gender detection\n */\nexport interface FaceDescriptionConfig extends GenericConfig {\n  /** minimum confidence for a detected face before results are discarded */\n  minConfidence: number,\n}\n\n/** Emotion part of face configuration */\nexport interface FaceEmotionConfig extends GenericConfig {\n  /** minimum confidence for a detected face before results are discarded */\n  minConfidence: number,\n}\n\n/** Anti-spoofing part of face configuration */\nexport interface FaceAntiSpoofConfig extends GenericConfig {}\n\n/** Liveness part of face configuration */\nexport interface FaceLivenessConfig extends GenericConfig {}\n\n/** Gear part of face configuration */\nexport interface FaceGearConfig extends GenericConfig {\n  /** minimum confidence for a detected race before results are discarded */\n  minConfidence: number,\n}\n\n/** Configures all face-specific options: face detection, mesh analysis, age, gender, emotion detection and face description */\nexport interface FaceConfig extends GenericConfig {\n  detector: Partial<FaceDetectorConfig>,\n  mesh: Partial<FaceMeshConfig>,\n  attention: Partial<FaceAttentionConfig>,\n  iris: Partial<FaceIrisConfig>,\n  description: Partial<FaceDescriptionConfig>,\n  emotion: Partial<FaceEmotionConfig>,\n  antispoof: Partial<FaceAntiSpoofConfig>,\n  liveness: Partial<FaceLivenessConfig>,\n  gear: Partial<FaceGearConfig>,\n}\n\n/** Configures all body detection specific options */\nexport interface BodyConfig extends GenericConfig {\n  /** maximum number of detected bodies */\n  maxDetected: number,\n  /** minimum confidence for a detected body before results are discarded */\n  minConfidence: number,\n  /* experimental\n  /** experimental: detector used for body model before actual analysis\n  detector?: {\n    /** experimental: enable body detector before body landmarks\n    enabled: boolean,\n    /** experimental: path to optional body detector model json file\n    modelPath: string,\n    /** experimental: minimum confidence for a detected body before results are discarded\n    minConfidence: number,\n    /** experimental: minimum overlap between two detected bodies before one is discarded\n    iouThreshold: number\n  },\n  */\n}\n\n/** Configures all hand detection specific options */\nexport interface HandConfig extends GenericConfig {\n  /** should hand rotation correction be performed after hand detection? */\n  rotation: boolean,\n  /** minimum confidence for a detected hand before results are discarded */\n  minConfidence: number,\n  /** minimum overlap between two detected hands before one is discarded */\n  iouThreshold: number,\n  /** maximum number of detected hands */\n  maxDetected: number,\n  /** should hand landmarks be detected or just return detected hand box */\n  landmarks: boolean,\n  detector: {\n    /** path to hand detector model json */\n    modelPath?: string,\n  },\n  skeleton: {\n    /** path to hand skeleton model json */\n    modelPath?: string,\n  },\n}\n\n/** Configures all object detection specific options */\nexport interface ObjectConfig extends GenericConfig {\n  /** minimum confidence for a detected objects before results are discarded */\n  minConfidence: number,\n  /** minimum overlap between two detected objects before one is discarded */\n  iouThreshold: number,\n  /** maximum number of detected objects */\n  maxDetected: number,\n}\n\n/** Configures all body segmentation module\n * removes background from input containing person\n * if segmentation is enabled it will run as preprocessing task before any other model\n * alternatively leave it disabled and use it on-demand using human.segmentation method which can\n * remove background or replace it with user-provided background\n*/\nexport interface SegmentationConfig extends GenericConfig {\n  /** blur segmentation output by <number> pixels for more realistic image */\n  blur: number,\n}\n\n/** Run input through image filters before inference\n * - available only in Browser environments\n * - image filters run with near-zero latency as they are executed on the GPU using WebGL\n*/\nexport interface FilterConfig {\n  /** are image filters enabled? */\n  enabled: boolean,\n  /** perform image histogram equalization\n   * - equalization is performed on input as a whole and detected face before its passed for further analysis\n  */\n  equalization: boolean,\n  /** resize input width\n  * - if both width and height are set to 0, there is no resizing\n  * - if just one is set, second one is scaled automatically\n  * - if both are set, values are used as-is\n  */\n  width: number,\n  /** resize input height\n  * - if both width and height are set to 0, there is no resizing\n  * - if just one is set, second one is scaled automatically\n  * - if both are set, values are used as-is\n  */\n  height: number,\n  /** return processed canvas imagedata in result */\n  return: boolean,\n  /** flip input as mirror image */\n  flip: boolean,\n  /** range: -1 (darken) to 1 (lighten) */\n  brightness: number,\n  /** range: -1 (reduce contrast) to 1 (increase contrast) */\n  contrast: number,\n  /** range: 0 (no sharpening) to 1 (maximum sharpening) */\n  sharpness: number,\n  /** range: 0 (no blur) to N (blur radius in pixels) */\n  blur: number\n  /** range: -1 (reduce saturation) to 1 (increase saturation) */\n  saturation: number,\n  /** range: 0 (no change) to 360 (hue rotation in degrees) */\n  hue: number,\n  /** image negative */\n  negative: boolean,\n  /** image sepia colors */\n  sepia: boolean,\n  /** image vintage colors */\n  vintage: boolean,\n  /** image kodachrome colors */\n  kodachrome: boolean,\n  /** image technicolor colors */\n  technicolor: boolean,\n  /** image polaroid camera effect */\n  polaroid: boolean,\n  /** range: 0 (no pixelate) to N (number of pixels to pixelate) */\n  pixelate: number,\n}\n\n/** Controlls gesture detection */\nexport interface GestureConfig {\n  /** is gesture detection enabled? */\n  enabled: boolean,\n}\n/** Possible TensorFlow backends */\nexport type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu'];\n\n/** Possible values for `human.warmup` */\nexport type WarmupType = ['' | 'none' | 'face' | 'full' | 'body'];\n\n/**\n * Configuration interface definition for **Human** library\n * Contains all configurable parameters\n * Defaults: [config](https://github.com/vladmandic/human/blob/main/src/config.ts#L262)\n */\nexport interface Config {\n  /** Backend used for TFJS operations\n   * valid build-in backends are:\n   * - Browser: `cpu`, `wasm`, `webgl`, `humangl`, `webgpu`\n   * - NodeJS: `cpu`, `wasm`, `tensorflow`\n   * default: `humangl` for browser and `tensorflow` for nodejs\n  */\n  backend: '' | 'cpu' | 'wasm' | 'webgl' | 'humangl' | 'tensorflow' | 'webgpu',\n\n  /** Path to *.wasm files if backend is set to `wasm`\n   *\n   * default: auto-detects to link to CDN `jsdelivr` when running in browser\n  */\n  wasmPath: string,\n\n  /** Force WASM loader to use platform fetch\n   *\n   * default: auto-detects to link to CDN `jsdelivr` when running in browser\n  */\n  wasmPlatformFetch: boolean,\n\n  /** Print debug statements to console\n   *\n   * default: `true`\n  */\n  debug: boolean,\n\n  /** Perform model loading and inference concurrently or sequentially\n   *\n   * default: `true`\n  */\n  async: boolean,\n\n  /** What to use for `human.warmup()`\n   * - warmup pre-initializes all models for faster inference but can take significant time on startup\n   * - used by `webgl`, `humangl` and `webgpu` backends\n   *\n   * default: `full`\n  */\n  warmup: '' | 'none' | 'face' | 'full' | 'body',\n\n  /** Base model path (typically starting with file://, http:// or https://) for all models\n   * - individual modelPath values are relative to this path\n   *\n   * default: `../models/` for browsers and `file://models/` for nodejs\n  */\n  modelBasePath: string,\n\n  /** Cache models in IndexDB on first sucessfull load\n   * default: true if indexdb is available (browsers), false if its not (nodejs)\n   */\n  cacheModels: boolean,\n\n  /** Cache sensitivity\n   * - values 0..1 where 0.01 means reset cache if input changed more than 1%\n   * - set to 0 to disable caching\n   *\n   * default: 0.7\n  */\n  cacheSensitivity: number;\n\n  /** Perform immediate garbage collection on deallocated tensors instead of caching them */\n  deallocate: boolean;\n\n  /** Internal Variable */\n  skipAllowed: boolean;\n\n  /** Filter config {@link FilterConfig} */\n  filter: Partial<FilterConfig>,\n\n  /** Gesture config {@link GestureConfig} */\n  gesture: Partial<GestureConfig>;\n\n  /** Face config {@link FaceConfig} */\n  face: Partial<FaceConfig>,\n\n  /** Body config {@link BodyConfig} */\n  body: Partial<BodyConfig>,\n\n  /** Hand config {@link HandConfig} */\n  hand: Partial<HandConfig>,\n\n  /** Object config {@link ObjectConfig} */\n  object: Partial<ObjectConfig>,\n\n  /** Segmentation config {@link SegmentationConfig} */\n  segmentation: Partial<SegmentationConfig>,\n}\n\n/** - [See all default Config values...](https://github.com/vladmandic/human/blob/main/src/config.ts#L262) */\nconst config: Config = {\n  backend: '',\n  modelBasePath: '',\n  cacheModels: true,\n  wasmPath: '',\n  wasmPlatformFetch: false,\n  debug: false,\n  async: true,\n  warmup: 'full',\n  cacheSensitivity: 0.70,\n  skipAllowed: false,\n  deallocate: false,\n  filter: {\n    enabled: true,\n    equalization: false,\n    width: 0,\n    height: 0,\n    flip: false,\n    return: true,\n    brightness: 0,\n    contrast: 0,\n    sharpness: 0,\n    blur: 0,\n    saturation: 0,\n    hue: 0,\n    negative: false,\n    sepia: false,\n    vintage: false,\n    kodachrome: false,\n    technicolor: false,\n    polaroid: false,\n    pixelate: 0,\n  },\n  gesture: {\n    enabled: true,\n  },\n  face: {\n    enabled: true,\n    detector: {\n      modelPath: 'blazeface.json',\n      rotation: true,\n      maxDetected: 1,\n      skipFrames: 99,\n      skipTime: 2500,\n      minConfidence: 0.2,\n      iouThreshold: 0.1,\n      mask: false,\n      return: false,\n    },\n    mesh: {\n      enabled: true,\n      modelPath: 'facemesh.json',\n      keepInvalid: false,\n    },\n    attention: {\n      enabled: false,\n      modelPath: 'facemesh-attention.json',\n    },\n    iris: {\n      enabled: true,\n      modelPath: 'iris.json',\n    },\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,\n      skipFrames: 99,\n      skipTime: 1500,\n      modelPath: 'emotion.json',\n    },\n    description: {\n      enabled: true,\n      modelPath: 'faceres.json',\n      skipFrames: 99,\n      skipTime: 3000,\n      minConfidence: 0.1,\n    },\n    antispoof: {\n      enabled: false,\n      skipFrames: 99,\n      skipTime: 4000,\n      modelPath: 'antispoof.json',\n    },\n    liveness: {\n      enabled: false,\n      skipFrames: 99,\n      skipTime: 4000,\n      modelPath: 'liveness.json',\n    },\n  },\n  body: {\n    enabled: true,\n    modelPath: 'movenet-lightning.json',\n    maxDetected: -1,\n    minConfidence: 0.3,\n    skipFrames: 1,\n    skipTime: 200,\n  },\n  hand: {\n    enabled: true,\n    rotation: true,\n    skipFrames: 99,\n    skipTime: 1000,\n    minConfidence: 0.50,\n    iouThreshold: 0.2,\n    maxDetected: -1,\n    landmarks: true,\n    detector: {\n      modelPath: 'handtrack.json',\n    },\n    skeleton: {\n      modelPath: 'handlandmark-full.json',\n    },\n  },\n  object: {\n    enabled: false,\n    modelPath: 'mb3-centernet.json',\n    minConfidence: 0.2,\n    iouThreshold: 0.4,\n    maxDetected: 10,\n    skipFrames: 99,\n    skipTime: 2000,\n  },\n  segmentation: {\n    enabled: false,\n    modelPath: 'selfie.json',\n    blur: 8,\n  },\n};\n\nexport { config as defaults };\n", "/*\n  Human\n  homepage: <https://github.com/vladmandic/human>\n  author: <https://github.com/vladmandic>'\n*/\n\nexport*from\"@tensorflow/tfjs/dist/index.js\";export*from\"@tensorflow/tfjs-backend-webgl/dist/index.js\";var r=\"3.19.0\",e=\"3.19.0\",o=\"3.19.0\",a=\"3.19.0\",t=\"3.19.0\",s=\"3.19.0\",f=\"3.19.0\",v={tfjs:r,\"tfjs-core\":e,\"tfjs-data\":o,\"tfjs-layers\":a,\"tfjs-converter\":t,\"tfjs-backend-webgl\":s,\"tfjs-backend-wasm\":f};import{Tensor as d}from\"@tensorflow/tfjs/dist/index.js\";import{GraphModel as b}from\"@tensorflow/tfjs-converter/dist/index\";export{b as GraphModel,d as Tensor,v as version};\n", "export const vertexIdentity = `\n  precision highp float;\n  attribute vec2 pos;\n  attribute vec2 uv;\n  varying vec2 vUv;\n  uniform float flipY;\n  void main(void) {\n    vUv = uv;\n    gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);\n  }\n`;\n\nexport const fragmentIdentity = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  void main(void) {\n    gl_FragColor = texture2D(texture, vUv);\n  }\n`;\n\nexport const colorMatrixWithAlpha = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform float m[20];\n  void main(void) {\n    vec4 c = texture2D(texture, vUv);\n    gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];\n    gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];\n    gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];\n    gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];\n  }\n`;\n\nexport const colorMatrixWithoutAlpha = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform float m[20];\n  void main(void) {\n    vec4 c = texture2D(texture, vUv);\n    gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];\n    gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];\n    gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];\n    gl_FragColor.a = c.a;\n  }\n`;\n\nexport const pixelate = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform vec2 size;\n  uniform sampler2D texture;\n  vec2 pixelate(vec2 coord, vec2 size) {\n    return floor( coord / size ) * size;\n  }\n  void main(void) {\n    gl_FragColor = vec4(0.0);\n    vec2 coord = pixelate(vUv, size);\n    gl_FragColor += texture2D(texture, coord);\n  }\n`;\n\nexport const blur = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform vec2 px;\n  void main(void) {\n    gl_FragColor = vec4(0.0);\n    gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;\n    gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;\n    gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;\n    gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;\n    gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;\n    gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;\n    gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;\n    gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;\n    gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;\n    gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;\n    gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;\n    gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;\n    gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;\n    gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;\n    gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;\n  }\n`;\n\nexport const convolution = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform vec2 px;\n  uniform float m[9];\n  void main(void) {\n    vec4 c11 = texture2D(texture, vUv - px); // top left\n    vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y)); // top center\n    vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y)); // top right\n    vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) ); // mid left\n    vec4 c22 = texture2D(texture, vUv); // mid center\n    vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) ); // mid right\n    vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) ); // bottom left\n    vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) ); // bottom center\n    vec4 c33 = texture2D(texture, vUv + px ); // bottom right\n    gl_FragColor = \n    c11 * m[0] + c12 * m[1] + c22 * m[2] +\n    c21 * m[3] + c22 * m[4] + c23 * m[5] +\n    c31 * m[6] + c32 * m[7] + c33 * m[8];\n    gl_FragColor.a = c22.a;\n  }\n`;\n", "/**\n * Image Filters in WebGL algoritm implementation\n * Based on: [WebGLImageFilter](https://github.com/phoboslab/WebGLImageFilter)\n */\n\nimport * as shaders from './imagefxshaders';\nimport { canvas } from './image';\nimport { log } from '../util/util';\n\nconst collect = (source, prefix, collection) => {\n  const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n  source.replace(r, (match, name) => {\n    collection[name] = 0;\n    return match;\n  });\n};\n\nclass GLProgram {\n  uniform = {};\n  attribute = {};\n  gl: WebGLRenderingContext;\n  id: WebGLProgram;\n\n  constructor(gl, vertexSource, fragmentSource) {\n    this.gl = gl;\n    const vertexShader = this.compile(vertexSource, this.gl.VERTEX_SHADER);\n    const fragmentShader = this.compile(fragmentSource, this.gl.FRAGMENT_SHADER);\n    this.id = this.gl.createProgram() as WebGLProgram;\n    if (!vertexShader || !fragmentShader) return;\n    if (!this.id) {\n      log('filter: could not create webgl program');\n      return;\n    }\n    this.gl.attachShader(this.id, vertexShader);\n    this.gl.attachShader(this.id, fragmentShader);\n    this.gl.linkProgram(this.id);\n    if (!this.gl.getProgramParameter(this.id, this.gl.LINK_STATUS)) {\n      log(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);\n      return;\n    }\n    this.gl.useProgram(this.id);\n    collect(vertexSource, 'attribute', this.attribute); // Collect attributes\n    for (const a in this.attribute) this.attribute[a] = this.gl.getAttribLocation(this.id, a);\n    collect(vertexSource, 'uniform', this.uniform); // Collect uniforms\n    collect(fragmentSource, 'uniform', this.uniform);\n    for (const u in this.uniform) this.uniform[u] = this.gl.getUniformLocation(this.id, u);\n  }\n\n  compile = (source, type): WebGLShader | null => {\n    const shader = this.gl.createShader(type) as WebGLShader;\n    if (!shader) {\n      log('filter: could not create shader');\n      return null;\n    }\n    this.gl.shaderSource(shader, source);\n    this.gl.compileShader(shader);\n    if (!this.gl.getShaderParameter(shader, this.gl.COMPILE_STATUS)) {\n      log(`filter: gl compile failed: ${this.gl.getShaderInfoLog(shader)}`);\n      return null;\n    }\n    return shader;\n  };\n}\n\n// function that is instantiated as class so it has private this members\n/**\n * @class GLImageFilter\n * @property {function} reset reset current filter chain\n * @property {function} add add specified filter to filter chain\n * @property {function} apply execute filter chain and draw result\n * @property {function} draw just draw input to result\n */\n\nexport function GLImageFilter() {\n  let drawCount = 0;\n  let sourceTexture: WebGLTexture | null = null;\n  let lastInChain = false;\n  let currentFramebufferIndex = -1;\n  let tempFramebuffers: [null, null] | [{ fbo: WebGLFramebuffer | null, texture: WebGLTexture | null }] = [null, null];\n  let filterChain: Record<string, unknown>[] = [];\n  let vertexBuffer: WebGLBuffer | null = null;\n  let currentProgram: GLProgram | null = null;\n  const fxcanvas = canvas(100, 100);\n  const shaderProgramCache = { }; // key is the shader program source, value is the compiled program\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = fxcanvas.getContext('webgl') as WebGLRenderingContext;\n  if (!gl) {\n    log('filter: cannot get webgl context');\n    return;\n  }\n  // @ts-ignore used for sanity checks outside of imagefx\n  this.gl = gl;\n\n  function resize(width, height) {\n    if (width === fxcanvas.width && height === fxcanvas.height) return; // Same width/height? Nothing to do here\n    fxcanvas.width = width;\n    fxcanvas.height = height;\n    if (!vertexBuffer) { // Create the context if we don't have it yet\n      const vertices = new Float32Array([-1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0]); // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      vertexBuffer = gl.createBuffer();\n      gl.bindBuffer(gl.ARRAY_BUFFER, vertexBuffer);\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, fxcanvas.width, fxcanvas.height);\n    tempFramebuffers = [null, null]; // Delete old temp framebuffers\n  }\n\n  function createFramebufferTexture(width, height) {\n    const fbo = gl.createFramebuffer() as WebGLFramebuffer;\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture() as WebGLTexture;\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  }\n\n  function getTempFramebuffer(index): { fbo: WebGLFramebuffer | null, texture: WebGLTexture | null } {\n    tempFramebuffers[index] = tempFramebuffers[index] || createFramebufferTexture(fxcanvas.width, fxcanvas.height);\n    return tempFramebuffers[index] as { fbo: WebGLFramebuffer, texture: WebGLTexture };\n  }\n\n  function draw(flags = 0) {\n    if (!currentProgram) return;\n    let source: WebGLTexture | null = null;\n    let target: WebGLFramebuffer | null = null;\n    let flipY = false;\n    if (drawCount === 0) source = sourceTexture; // First draw call - use the source texture\n    else source = getTempFramebuffer(currentFramebufferIndex).texture || null; // All following draw calls use the temp buffer last drawn to\n    drawCount++;\n    if (lastInChain && !(flags & DRAW.INTERMEDIATE)) { // Last filter in our chain - draw directly to the WebGL Canvas. We may also have to flip the image vertically now\n      target = null;\n      flipY = drawCount % 2 === 0;\n    } else {\n      currentFramebufferIndex = (currentFramebufferIndex + 1) % 2;\n      target = getTempFramebuffer(currentFramebufferIndex).fbo || null; // Intermediate draw call - get a temp buffer to draw to\n    }\n    gl.bindTexture(gl.TEXTURE_2D, source); // Bind the source and target and draw the two triangles\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(currentProgram.uniform['flipY'], (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  }\n\n  function compileShader(fragmentSource): GLProgram | null {\n    if (shaderProgramCache[fragmentSource]) {\n      currentProgram = shaderProgramCache[fragmentSource];\n      gl.useProgram((currentProgram ? currentProgram.id : null) || null);\n      return currentProgram as GLProgram;\n    }\n    currentProgram = new GLProgram(gl, shaders.vertexIdentity, fragmentSource);\n    if (!currentProgram) {\n      log('filter: could not get webgl program');\n      return null;\n    }\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(currentProgram.attribute['pos']);\n    gl.vertexAttribPointer(currentProgram.attribute['pos'], 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(currentProgram.attribute['uv']);\n    gl.vertexAttribPointer(currentProgram.attribute['uv'], 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    shaderProgramCache[fragmentSource] = currentProgram;\n    return currentProgram as GLProgram;\n  }\n\n  const filter = {\n    colorMatrix: (matrix) => { // general color matrix filter\n      const m = new Float32Array(matrix);\n      m[4] /= 255;\n      m[9] /= 255;\n      m[14] /= 255;\n      m[19] /= 255;\n      const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0) // Can we ignore the alpha value? Makes things a bit faster.\n        ? shaders.colorMatrixWithoutAlpha\n        : shaders.colorMatrixWithAlpha;\n      const program = compileShader(shader);\n      if (!program) return;\n      gl.uniform1fv(program.uniform['m'], m);\n      draw();\n    },\n\n    brightness: (brightness) => {\n      const b = (brightness || 0) + 1;\n      filter.colorMatrix([\n        b, 0, 0, 0, 0,\n        0, b, 0, 0, 0,\n        0, 0, b, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    saturation: (amount) => {\n      const x = (amount || 0) * 2 / 3 + 1;\n      const y = ((x - 1) * -0.5);\n      filter.colorMatrix([\n        x, y, y, 0, 0,\n        y, x, y, 0, 0,\n        y, y, x, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    desaturate: () => {\n      filter.saturation(-1);\n    },\n\n    contrast: (amount) => {\n      const v = (amount || 0) + 1;\n      const o = -128 * (v - 1);\n      filter.colorMatrix([\n        v, 0, 0, 0, o,\n        0, v, 0, 0, o,\n        0, 0, v, 0, o,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    negative: () => {\n      filter.contrast(-2);\n    },\n\n    hue: (rotation) => {\n      rotation = (rotation || 0) / 180 * Math.PI;\n      const cos = Math.cos(rotation);\n      const sin = Math.sin(rotation);\n      const lumR = 0.213;\n      const lumG = 0.715;\n      const lumB = 0.072;\n      filter.colorMatrix([\n        lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n        lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n        lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    desaturateLuminance: () => {\n      filter.colorMatrix([\n        0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n        0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n        0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    sepia: () => {\n      filter.colorMatrix([\n        0.393, 0.7689999, 0.18899999, 0, 0,\n        0.349, 0.6859999, 0.16799999, 0, 0,\n        0.272, 0.5339999, 0.13099999, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    brownie: () => {\n      filter.colorMatrix([\n        0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n        -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n        0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    vintagePinhole: () => {\n      filter.colorMatrix([\n        0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n        0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n        0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    kodachrome: () => {\n      filter.colorMatrix([\n        1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n        -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n        -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    technicolor: () => {\n      filter.colorMatrix([\n        1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n        -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n        -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    polaroid: () => {\n      filter.colorMatrix([\n        1.438, -0.062, -0.062, 0, 0,\n        -0.122, 1.378, -0.122, 0, 0,\n        -0.016, -0.016, 1.483, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    shiftToBGR: () => {\n      filter.colorMatrix([\n        0, 0, 1, 0, 0,\n        0, 1, 0, 0, 0,\n        1, 0, 0, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    convolution: (matrix) => { // general convolution Filter\n      const m = new Float32Array(matrix);\n      const pixelSizeX = 1 / fxcanvas.width;\n      const pixelSizeY = 1 / fxcanvas.height;\n      const program = compileShader(shaders.convolution);\n      if (!program) return;\n      gl.uniform1fv(program.uniform['m'], m);\n      gl.uniform2f(program.uniform['px'], pixelSizeX, pixelSizeY);\n      draw();\n    },\n\n    detectEdges: () => {\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        0, 1, 0,\n        1, -4, 1,\n        0, 1, 0,\n      ]);\n    },\n\n    sobelX: () => {\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        -1, 0, 1,\n        -2, 0, 2,\n        -1, 0, 1,\n      ]);\n    },\n\n    sobelY: () => {\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        -1, -2, -1,\n        0, 0, 0,\n        1, 2, 1,\n      ]);\n    },\n\n    sharpen: (amount) => {\n      const a = amount || 1;\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        0, -1 * a, 0,\n        -1 * a, 1 + 4 * a, -1 * a,\n        0, -1 * a, 0,\n      ]);\n    },\n\n    emboss: (size) => {\n      const s = size || 1;\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        -2 * s, -1 * s, 0,\n        -1 * s, 1, 1 * s,\n        0, 1 * s, 2 * s,\n      ]);\n    },\n\n    blur: (size) => {\n      const blurSizeX = (size / 7) / fxcanvas.width;\n      const blurSizeY = (size / 7) / fxcanvas.height;\n      const program = compileShader(shaders.blur);\n      if (!program) return;\n      // Vertical\n      gl.uniform2f(program.uniform['px'], 0, blurSizeY);\n      draw(DRAW.INTERMEDIATE);\n      // Horizontal\n      gl.uniform2f(program.uniform['px'], blurSizeX, 0);\n      draw();\n    },\n\n    pixelate: (size) => {\n      const blurSizeX = (size) / fxcanvas.width;\n      const blurSizeY = (size) / fxcanvas.height;\n      const program = compileShader(shaders.pixelate);\n      if (!program) return;\n      gl.uniform2f(program.uniform['size'], blurSizeX, blurSizeY);\n      draw();\n    },\n  };\n\n  // @ts-ignore this\n  this.add = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const func = filter[name];\n    filterChain.push({ func, args });\n  };\n\n  // @ts-ignore this\n  this.reset = function () {\n    filterChain = [];\n  };\n\n  // @ts-ignore this\n  this.get = function () {\n    return filterChain;\n  };\n\n  // @ts-ignore this\n  this.apply = function (image) {\n    resize(image.width, image.height);\n    drawCount = 0;\n    if (!sourceTexture) sourceTexture = gl.createTexture(); // Create the texture for the input image if we haven't yet\n    gl.bindTexture(gl.TEXTURE_2D, sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    for (let i = 0; i < filterChain.length; i++) {\n      lastInChain = (i === filterChain.length - 1);\n      const f = filterChain[i];\n      // @ts-ignore function assigment\n      f.func.apply(this, f.args || []);\n    }\n    return fxcanvas;\n  };\n\n  // @ts-ignore this\n  this.draw = function (image) {\n    this.add('brightness', 0);\n    return this.apply(image);\n  };\n}\n", "/**\n * Image enhancements\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from '../exports';\n\nexport async function histogramEqualization(inputImage: Tensor): Promise<Tensor> {\n  // const maxValue = 254; // using 255 results in values slightly larger than 1 due to math rounding errors\n  const squeeze = inputImage.shape.length === 4 ? tf.squeeze(inputImage) : inputImage;\n  const channels = tf.split(squeeze, 3, 2);\n  const min: Tensor[] = [tf.min(channels[0]), tf.min(channels[1]), tf.min(channels[2])];\n  const max: Tensor[] = [tf.max(channels[0]), tf.max(channels[1]), tf.max(channels[2])];\n  const absMax = await Promise.all(max.map((channel) => channel.data()));\n  const maxValue = 0.99 * Math.max(absMax[0][0], absMax[1][0], absMax[2][0]);\n  const sub = [tf.sub(channels[0], min[0]), tf.sub(channels[1], min[1]), tf.sub(channels[2], min[2])];\n  const range = [tf.sub(max[0], min[0]), tf.sub(max[1], min[1]), tf.sub(max[2], min[2])];\n  const fact = [tf.div(maxValue, range[0]), tf.div(maxValue, range[1]), tf.div(maxValue, range[2])];\n  const enh = [tf.mul(sub[0], fact[0]), tf.mul(sub[1], fact[1]), tf.mul(sub[2], fact[2])];\n  const rgb = tf.stack([enh[0], enh[1], enh[2]], 2);\n  const reshape = tf.reshape(rgb, [1, squeeze.shape[0], squeeze.shape[1], 3]);\n  tf.dispose([...channels, ...min, ...max, ...sub, ...range, ...fact, ...enh, rgb, squeeze]);\n  return reshape; // output shape is [1, height, width, 3]\n}\n", "/**\n * Image Processing algorithm implementation\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\nimport type { Input, AnyCanvas, Tensor, Config } from '../exports';\nimport { env } from '../util/env';\nimport { log } from '../util/util';\nimport * as enhance from './enhance';\n\nconst maxSize = 3840;\n// internal temp canvases\nlet inCanvas: AnyCanvas | null = null; // use global variable to avoid recreating canvas on each frame\nlet outCanvas: AnyCanvas | null = null; // use global variable to avoid recreating canvas on each frame\nlet tmpCanvas: AnyCanvas | null = null; // use global variable to avoid recreating canvas on each frame\n// @ts-ignore // imagefx is js module that should be converted to a class\nlet fx: fxImage.GLImageFilter | null; // instance of imagefx\n\nconst last: { inputSum: number, cacheDiff: number, sumMethod: number, inputTensor: undefined | Tensor } = {\n  inputSum: 0,\n  cacheDiff: 1,\n  sumMethod: 0,\n  inputTensor: undefined,\n};\n\nexport function canvas(width: number, height: number): AnyCanvas {\n  let c;\n  if (env.browser) { // browser defines canvas object\n    if (env.worker) { // if runing in web  worker use OffscreenCanvas\n      if (typeof OffscreenCanvas === 'undefined') throw new Error('canvas error: attempted to run in web worker but OffscreenCanvas is not supported');\n      c = new OffscreenCanvas(width, height);\n    } else { // otherwise use DOM canvas\n      if (typeof document === 'undefined') throw new Error('canvas error: attempted to run in browser but DOM is not defined');\n      c = document.createElement('canvas');\n      c.width = width;\n      c.height = height;\n    }\n  } else { // if not running in browser, there is no \"default\" canvas object, so we need monkey patch or fail\n    // @ts-ignore // env.canvas is an external monkey-patch\n    if (typeof env.Canvas !== 'undefined') c = new env.Canvas(width, height);\n    else if (typeof globalThis.Canvas !== 'undefined') c = new globalThis.Canvas(width, height);\n    // else throw new Error('canvas error: attempted to use canvas in nodejs without canvas support installed');\n  }\n  return c;\n}\n\n// helper function to copy canvas from input to output\nexport function copy(input: AnyCanvas, output?: AnyCanvas) {\n  const outputCanvas = output || canvas(input.width, input.height);\n  const ctx = outputCanvas.getContext('2d') as CanvasRenderingContext2D;\n  ctx.drawImage(input, 0, 0);\n  return outputCanvas;\n}\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport async function process(input: Input, config: Config, getTensor: boolean = true): Promise<{ tensor: Tensor | null, canvas: AnyCanvas | null }> {\n  if (!input) {\n    // throw new Error('input is missing');\n    if (config.debug) log('input error: input is missing');\n    return { tensor: null, canvas: null }; // video may become temporarily unavailable due to onresize\n  }\n  // sanity checks since different browsers do not implement all dom elements\n  if (\n    !(input instanceof tf.Tensor)\n    && !(typeof Image !== 'undefined' && input instanceof Image)\n    && !(typeof env.Canvas !== 'undefined' && input instanceof env.Canvas)\n    && !(typeof globalThis.Canvas !== 'undefined' && input instanceof globalThis.Canvas)\n    && !(typeof ImageData !== 'undefined' && input instanceof ImageData)\n    && !(typeof ImageBitmap !== 'undefined' && input instanceof ImageBitmap)\n    && !(typeof HTMLImageElement !== 'undefined' && input instanceof HTMLImageElement)\n    && !(typeof HTMLMediaElement !== 'undefined' && input instanceof HTMLMediaElement)\n    && !(typeof HTMLVideoElement !== 'undefined' && input instanceof HTMLVideoElement)\n    && !(typeof HTMLCanvasElement !== 'undefined' && input instanceof HTMLCanvasElement)\n    && !(typeof OffscreenCanvas !== 'undefined' && input instanceof OffscreenCanvas)\n  ) {\n    throw new Error('input error: type is not recognized');\n  }\n  if (input instanceof tf.Tensor) { // if input is tensor use as-is without filters but correct shape as needed\n    let tensor: Tensor | null = null;\n    if ((input as Tensor)['isDisposedInternal']) throw new Error('input error: attempted to use tensor but it is disposed');\n    if (!(input as Tensor)['shape']) throw new Error('input error: attempted to use tensor without a shape');\n    if ((input as Tensor).shape.length === 3) { // [height, width, 3 || 4]\n      if ((input as Tensor).shape[2] === 3) { // [height, width, 3] so add batch\n        tensor = tf.expandDims(input, 0);\n      } else if ((input as Tensor).shape[2] === 4) { // [height, width, 4] so strip alpha and add batch\n        const rgb = tf.slice3d(input, [0, 0, 0], [-1, -1, 3]);\n        tensor = tf.expandDims(rgb, 0);\n        tf.dispose(rgb);\n      }\n    } else if ((input as Tensor).shape.length === 4) { // [1, width, height, 3 || 4]\n      if ((input as Tensor).shape[3] === 3) { // [1, width, height, 3] just clone\n        tensor = tf.clone(input);\n      } else if ((input as Tensor).shape[3] === 4) { // [1, width, height, 4] so strip alpha\n        tensor = tf.slice4d(input, [0, 0, 0, 0], [-1, -1, -1, 3]);\n      }\n    }\n    // at the end shape must be [1, height, width, 3]\n    if (tensor == null || tensor.shape.length !== 4 || tensor.shape[0] !== 1 || tensor.shape[3] !== 3) throw new Error(`input error: attempted to use tensor with unrecognized shape: ${input['shape']}`);\n    if ((tensor as Tensor).dtype === 'int32') {\n      const cast = tf.cast(tensor, 'float32');\n      tf.dispose(tensor);\n      tensor = cast;\n    }\n    return { tensor, canvas: (config.filter.return ? outCanvas : null) };\n  } else {\n    // check if resizing will be needed\n    if (typeof input['readyState'] !== 'undefined' && input['readyState'] <= 2) {\n      if (config.debug) log('input stream is not ready');\n      return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize\n    }\n    const originalWidth = input['naturalWidth'] || input['videoWidth'] || input['width'] || (input['shape'] && (input['shape'][1] > 0));\n    const originalHeight = input['naturalHeight'] || input['videoHeight'] || input['height'] || (input['shape'] && (input['shape'][2] > 0));\n    if (!originalWidth || !originalHeight) {\n      if (config.debug) log('cannot determine input dimensions');\n      return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize\n    }\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = Math.trunc(targetWidth * originalHeight / originalWidth);\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = Math.trunc(targetHeight * originalWidth / originalHeight);\n    }\n\n    // create our canvas and resize it if needed\n    if ((config.filter.width || 0) > 0) targetWidth = config.filter.width;\n    else if ((config.filter.height || 0) > 0) targetWidth = originalWidth * ((config.filter.height || 0) / originalHeight);\n    if ((config.filter.height || 0) > 0) targetHeight = config.filter.height;\n    else if ((config.filter.width || 0) > 0) targetHeight = originalHeight * ((config.filter.width || 0) / originalWidth);\n    if (!targetWidth || !targetHeight) throw new Error('input error: cannot determine dimension');\n    if (!inCanvas || (inCanvas?.width !== targetWidth) || (inCanvas?.height !== targetHeight)) inCanvas = canvas(targetWidth, targetHeight);\n\n    // draw input to our canvas\n    const inCtx = inCanvas.getContext('2d') as CanvasRenderingContext2D;\n    if ((typeof ImageData !== 'undefined') && (input instanceof ImageData)) {\n      inCtx.putImageData(input, 0, 0);\n    } else {\n      if (config.filter.flip && typeof inCtx.translate !== 'undefined') {\n        inCtx.translate(originalWidth, 0);\n        inCtx.scale(-1, 1);\n        inCtx.drawImage(input as AnyCanvas, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas?.width, inCanvas?.height);\n        inCtx.setTransform(1, 0, 0, 1, 0, 0); // resets transforms to defaults\n      } else {\n        inCtx.drawImage(input as AnyCanvas, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas?.width, inCanvas?.height);\n      }\n    }\n\n    if (!outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas?.height !== outCanvas?.height)) outCanvas = canvas(inCanvas.width, inCanvas.height); // init output canvas\n\n    // imagefx transforms using gl from input canvas to output canvas\n    if (config.filter.enabled && env.webgl.supported) {\n      if (!fx) fx = env.browser ? new fxImage.GLImageFilter() : null; // && (typeof document !== 'undefined')\n      env.filter = !!fx;\n      if (!fx || !fx.add) {\n        if (config.debug) log('input process error: cannot initialize filters');\n        env.webgl.supported = false;\n        config.filter.enabled = false;\n        copy(inCanvas, outCanvas); // filter failed to initialize\n        // return { tensor: null, canvas: inCanvas };\n      } else {\n        fx.reset();\n        if (config.filter.brightness !== 0) fx.add('brightness', config.filter.brightness);\n        if (config.filter.contrast !== 0) fx.add('contrast', config.filter.contrast);\n        if (config.filter.sharpness !== 0) fx.add('sharpen', config.filter.sharpness);\n        if (config.filter.blur !== 0) fx.add('blur', config.filter.blur);\n        if (config.filter.saturation !== 0) fx.add('saturation', config.filter.saturation);\n        if (config.filter.hue !== 0) fx.add('hue', config.filter.hue);\n        if (config.filter.negative) fx.add('negative');\n        if (config.filter.sepia) fx.add('sepia');\n        if (config.filter.vintage) fx.add('brownie');\n        if (config.filter.sepia) fx.add('sepia');\n        if (config.filter.kodachrome) fx.add('kodachrome');\n        if (config.filter.technicolor) fx.add('technicolor');\n        if (config.filter.polaroid) fx.add('polaroid');\n        if (config.filter.pixelate !== 0) fx.add('pixelate', config.filter.pixelate);\n        if (fx.get() > 0) outCanvas = fx.apply(inCanvas);\n        else outCanvas = fx.draw(inCanvas);\n      }\n    } else {\n      copy(inCanvas, outCanvas); // if no filters applied, output canvas is input canvas\n      if (fx) fx = null;\n      env.filter = !!fx;\n    }\n\n    if (!getTensor) return { tensor: null, canvas: outCanvas }; // just canvas was requested\n    if (!outCanvas) throw new Error('canvas error: cannot create output');\n\n    // create tensor from image unless input was a tensor already\n    let pixels;\n    let depth = 3;\n    if ((typeof ImageData !== 'undefined' && input instanceof ImageData) || (input['data'] && input['width'] && input['height'])) { // if input is imagedata, just use it\n      if (env.browser && tf.browser) {\n        pixels = tf.browser ? tf.browser.fromPixels(input) : null;\n      } else {\n        depth = input['data'].length / input['height'] / input['width'];\n        // const arr = Uint8Array.from(input['data']);\n        const arr = new Uint8Array(input['data']['buffer']);\n        pixels = tf.tensor(arr, [input['height'], input['width'], depth], 'int32');\n      }\n    } else {\n      if (!tmpCanvas || (outCanvas.width !== tmpCanvas.width) || (outCanvas.height !== tmpCanvas.height)) tmpCanvas = canvas(outCanvas.width, outCanvas.height); // init output canvas\n      if (tf.browser && env.browser) {\n        if (config.backend === 'webgl' || config.backend === 'humangl' || config.backend === 'webgpu') {\n          pixels = tf.browser.fromPixels(outCanvas); // safe to reuse since both backend and context are gl based\n        } else {\n          tmpCanvas = copy(outCanvas); // cannot use output canvas as it already has gl context so we do a silly one more canvas\n          pixels = tf.browser.fromPixels(tmpCanvas);\n        }\n      } else {\n        const tempCanvas = copy(outCanvas); // cannot use output canvas as it already has gl context so we do a silly one more canvas\n        const tempCtx = tempCanvas.getContext('2d') as CanvasRenderingContext2D;\n        const tempData = tempCtx.getImageData(0, 0, targetWidth, targetHeight);\n        depth = tempData.data.length / targetWidth / targetHeight;\n        const arr = new Uint8Array(tempData.data.buffer);\n        pixels = tf.tensor(arr, [targetWidth, targetHeight, depth]);\n      }\n    }\n    if (depth === 4) { // rgba to rgb\n      const rgb = tf.slice3d(pixels, [0, 0, 0], [-1, -1, 3]); // strip alpha channel\n      tf.dispose(pixels);\n      pixels = rgb;\n    }\n    if (!pixels) throw new Error('input error: cannot create tensor');\n    const casted = tf.cast(pixels, 'float32');\n    const tensor = config.filter.equalization ? await enhance.histogramEqualization(casted) : tf.expandDims(casted, 0);\n    tf.dispose([pixels, casted]);\n    return { tensor, canvas: (config.filter.return ? outCanvas : null) };\n  }\n}\n\n/*\nconst checksum = async (input: Tensor): Promise<number> => { // use tf sum or js based sum loop depending on which is faster\n  const resizeFact = 48;\n  const reduced: Tensor = tf.image.resizeBilinear(input, [Math.trunc((input.shape[1] || 1) / resizeFact), Math.trunc((input.shape[2] || 1) / resizeFact)]);\n  const tfSum = async (): Promise<number> => {\n    const sumT = tf.sum(reduced);\n    const sum0 = await sumT.data();\n    tf.dispose(sumT);\n    return sum0[0];\n  };\n  const jsSum = async (): Promise<number> => {\n    const reducedData = await reduced.data(); // raw image rgb array\n    let sum0 = 0;\n    for (let i = 0; i < reducedData.length / 3; i++) sum0 += reducedData[3 * i + 2]; // look only at green value of each pixel\n    return sum0;\n  };\n  if (last.sumMethod === 0) {\n    const t0 = now();\n    await jsSum();\n    const t1 = now();\n    await tfSum();\n    const t2 = now();\n    last.sumMethod = t1 - t0 < t2 - t1 ? 1 : 2;\n  }\n  const res = last.sumMethod === 1 ? await jsSum() : await tfSum();\n  tf.dispose(reduced);\n  return res;\n};\n*/\n\nexport async function skip(config: Partial<Config>, input: Tensor) {\n  let skipFrame = false;\n  if (config.cacheSensitivity === 0 || !input.shape || input.shape.length !== 4 || input.shape[1] > 2048 || input.shape[2] > 2048) return skipFrame; // cache disabled or input is invalid or too large for cache analysis\n\n  /*\n  const checkSum = await checksum(input);\n  const diff = 100 * (Math.max(checkSum, last.inputSum) / Math.min(checkSum, last.inputSum) - 1);\n  last.inputSum = checkSum;\n  // if previous frame was skipped, skip this frame if changed more than cacheSensitivity\n  // if previous frame was not skipped, then look for cacheSensitivity or difference larger than one in previous frame to avoid resetting cache in subsequent frames unnecessarily\n  let skipFrame = diff < Math.max(config.cacheSensitivity, last.cacheDiff);\n  // if difference is above 10x threshold, don't use last value to force reset cache for significant change of scenes or images\n  last.cacheDiff = diff > 10 * config.cacheSensitivity ? 0 : diff;\n  skipFrame = skipFrame && (last.cacheDiff > 0); // if no cached diff value then force no skip\n  */\n\n  if (!last.inputTensor) {\n    last.inputTensor = tf.clone(input);\n  } else if (last.inputTensor.shape[1] !== input.shape[1] || last.inputTensor.shape[2] !== input.shape[2]) { // input resolution changed\n    tf.dispose(last.inputTensor);\n    last.inputTensor = tf.clone(input);\n  } else {\n    const t: Record<string, Tensor> = {};\n    t.diff = tf.sub(input, last.inputTensor);\n    t.squared = tf.mul(t.diff, t.diff);\n    t.sum = tf.sum(t.squared);\n    const diffSum = await t.sum.data();\n    const diffRelative = diffSum[0] / (input.shape[1] || 1) / (input.shape[2] || 1) / 255 / 3; // squared difference relative to input resolution and averaged per channel\n    tf.dispose([last.inputTensor, t.diff, t.squared, t.sum]);\n    last.inputTensor = tf.clone(input);\n    skipFrame = diffRelative <= (config.cacheSensitivity || 0);\n  }\n  return skipFrame;\n}\n\nexport async function compare(config: Partial<Config>, input1: Tensor, input2: Tensor): Promise<number> {\n  const t: Record<string, Tensor> = {};\n  if (!input1 || !input2 || input1.shape.length !== 4 || input1.shape.length !== input2.shape.length) {\n    if (!config.debug) log('invalid input tensor or tensor shapes do not match:', input1.shape, input2.shape);\n    return 0;\n  }\n  if (input1.shape[0] !== 1 || input2.shape[0] !== 1 || input1.shape[3] !== 3 || input2.shape[3] !== 3) {\n    if (!config.debug) log('input tensors must be of shape [1, height, width, 3]:', input1.shape, input2.shape);\n    return 0;\n  }\n  t.input1 = tf.clone(input1);\n  t.input2 = (input1.shape[1] !== input2.shape[1] || input1.shape[2] !== input2.shape[2]) ? tf.image.resizeBilinear(input2, [input1.shape[1], input1.shape[2]]) : tf.clone(input2);\n  t.diff = tf.sub(t.input1, t.input2);\n  t.squared = tf.mul(t.diff, t.diff);\n  t.sum = tf.sum(t.squared);\n  const diffSum = await t.sum.data();\n  const diffRelative = diffSum[0] / (input1.shape[1] || 1) / (input1.shape[2] || 1) / 255 / 3;\n  tf.dispose([t.input1, t.input2, t.diff, t.squared, t.sum]);\n  return diffRelative;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as image from '../image/image';\n\n/** Env class that holds detected capabilities */\nexport class Env {\n  /** Running in Browser */\n  browser: boolean;\n  /** Running in NodeJS */\n  node: boolean;\n  /** Running in WebWorker thread */\n  worker: boolean;\n  /** Detected platform */\n  platform: string = '';\n  /** Detected agent */\n  agent: string = '';\n  /** List of supported backends */\n  backends: string[] = [];\n  /** Has any work been performed so far */\n  initial: boolean;\n  /** Are image filters supported? */\n  filter: boolean | undefined;\n  /** TFJS instance details */\n  tfjs: {\n    version: undefined | string,\n  };\n  /** Is offscreenCanvas supported? */\n  offscreen: undefined | boolean;\n  /** Are performance counter instant values or additive */\n  perfadd: boolean = false;\n  /** WASM detected capabilities */\n  wasm: {\n    supported: undefined | boolean,\n    backend: undefined | boolean,\n    simd: undefined | boolean,\n    multithread: undefined | boolean,\n  } = {\n      supported: undefined,\n      backend: undefined,\n      simd: undefined,\n      multithread: undefined,\n    };\n  /** WebGL detected capabilities */\n  webgl: {\n    supported: undefined | boolean,\n    backend: undefined | boolean,\n    version: undefined | string,\n    renderer: undefined | string,\n  } = {\n      supported: undefined,\n      backend: undefined,\n      version: undefined,\n      renderer: undefined,\n    };\n  /** WebGPU detected capabilities */\n  webgpu: {\n    supported: undefined | boolean,\n    backend: undefined | boolean,\n    adapter: undefined | string,\n  } = {\n      supported: undefined,\n      backend: undefined,\n      adapter: undefined,\n    };\n  /** CPU info */\n  cpu: {\n    model: undefined | string,\n    flags: string[],\n  } = {\n      model: undefined,\n      flags: [],\n    };\n  /** List of supported kernels for current backend */\n  kernels: string[] = [];\n  /** MonkeyPatch for Canvas */\n  Canvas: undefined;\n  /** MonkeyPatch for Image */\n  Image: undefined;\n  /** MonkeyPatch for ImageData */\n  ImageData: undefined;\n\n  constructor() {\n    this.browser = typeof navigator !== 'undefined';\n    this.node = (typeof process !== 'undefined') && (typeof process.versions !== 'undefined') && (typeof process.versions.node !== 'undefined');\n    this.tfjs = { version: tf.version['tfjs-core'] };\n    this.offscreen = typeof OffscreenCanvas !== 'undefined';\n    this.initial = true;\n    // @ts-ignore WorkerGlobalScope evaluated in browser only\n    this.worker = this.browser && this.offscreen ? (typeof WorkerGlobalScope !== 'undefined') : undefined;\n    if (typeof navigator !== 'undefined') {\n      const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n      if (raw && raw[0]) {\n        const platformMatch = raw[0].match(/\\(([^()]+)\\)/g);\n        this.platform = (platformMatch && platformMatch[0]) ? platformMatch[0].replace(/\\(|\\)/g, '') : '';\n        this.agent = navigator.userAgent.replace(raw[0], '');\n        if (this.platform[1]) this.agent = this.agent.replace(raw[1], '');\n        this.agent = this.agent.replace(/  /g, ' ');\n        // chrome offscreencanvas gpu memory leak\n        /*\n        const isChrome = env.agent.match(/Chrome\\/.[0-9]/g);\n        const verChrome = isChrome && isChrome[0] ? isChrome[0].split('/')[1] : 0;\n        if (verChrome > 92 && verChrome < 96) {\n          log('disabling offscreenCanvas due to browser error:', isChrome ? isChrome[0] : 'unknown');\n          this.offscreen = false;\n        }\n        */\n      }\n    } else if (typeof process !== 'undefined') {\n      this.platform = `${process.platform} ${process.arch}`;\n      this.agent = `NodeJS ${process.version}`;\n    }\n  }\n\n  /** update backend information */\n  async updateBackend() {\n    // analyze backends\n    this.backends = Object.keys(tf.engine().registryFactory);\n    this.wasm.supported = typeof WebAssembly !== 'undefined';\n    this.wasm.backend = this.backends.includes('wasm');\n    if (this.wasm.supported && this.wasm.backend && tf.getBackend() === 'wasm') {\n      this.wasm.simd = await tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n      this.wasm.multithread = await tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n    }\n    const c = image.canvas(100, 100);\n    const ctx = c ? c.getContext('webgl2') : undefined; // causes too many gl contexts\n    // const ctx = typeof tf.backend().getGPGPUContext !== undefined ? tf.backend().getGPGPUContext : null;\n    this.webgl.supported = typeof ctx !== 'undefined';\n    this.webgl.backend = this.backends.includes('webgl');\n    if (this.webgl.supported && this.webgl.backend && (tf.getBackend() === 'webgl' || tf.getBackend() === 'humangl')) {\n      // @ts-ignore getGPGPUContext only exists on WebGL backend\n      const gl = tf.backend().gpgpu !== 'undefined' ? await tf.backend().getGPGPUContext().gl : null;\n      if (gl) {\n        this.webgl.version = gl.getParameter(gl.VERSION);\n        this.webgl.renderer = gl.getParameter(gl.RENDERER);\n      }\n    }\n    // @ts-ignore navigator.gpu is only defined when webgpu is available in browser\n    this.webgpu.supported = this.browser && typeof navigator['gpu'] !== 'undefined';\n    this.webgpu.backend = this.backends.includes('webgpu');\n    try {\n      // @ts-ignore navigator.gpu is only defined when webgpu is available in browser\n      if (this.webgpu.supported) this.webgpu.adapter = (await navigator['gpu'].requestAdapter()).name;\n    } catch {\n      this.webgpu.supported = false;\n    }\n    try {\n      this.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => kernel.kernelName.toLowerCase());\n    } catch { /**/ }\n  }\n\n  /** update cpu information */\n  async updateCPU() {\n    const cpu = { model: '', flags: [] };\n    if (this.node && this.platform.startsWith('linux')) {\n      /*\n      const fs = require('fs');\n      try {\n        const data = fs.readFileSync('/proc/cpuinfo').toString();\n        for (const line of data.split('\\n')) {\n          if (line.startsWith('model name')) cpu.model = line.match(/:(.*)/g)[0].replace(':', '').trim();\n          if (line.startsWith('flags')) cpu.flags = line.match(/:(.*)/g)[0].replace(':', '').trim().split(' ').sort();\n        }\n      } catch { }\n      */\n    }\n    if (!this['cpu']) Object.defineProperty(this, 'cpu', { value: cpu });\n    else this['cpu'] = cpu;\n  }\n}\n\nexport const env = new Env();\n", "import { log, join } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { GraphModel } from './types';\nimport type { Config } from '../config';\nimport * as modelsDefs from '../../models/models.json';\n\nconst options = {\n  cacheModels: true,\n  cacheSupported: true,\n  verbose: true,\n  debug: false,\n  modelBasePath: '',\n};\n\nexport type ModelInfo = {\n  name: string,\n  inCache: boolean,\n  sizeDesired: number,\n  sizeFromManifest: number,\n  sizeLoadedWeights: number,\n}\n\nexport const modelStats: Record<string, ModelInfo> = {};\n\nasync function httpHandler(url, init?): Promise<Response | null> {\n  if (options.debug) log('load model fetch:', url, init);\n  return fetch(url, init);\n}\n\nexport function setModelLoadOptions(config: Config) {\n  options.cacheModels = config.cacheModels;\n  options.verbose = config.debug;\n  options.modelBasePath = config.modelBasePath;\n}\n\nexport async function loadModel(modelPath: string | undefined): Promise<GraphModel> {\n  let modelUrl = join(options.modelBasePath, modelPath || '');\n  if (!modelUrl.toLowerCase().endsWith('.json')) modelUrl += '.json';\n  const modelPathSegments = modelUrl.includes('/') ? modelUrl.split('/') : modelUrl.split('\\\\');\n  const shortModelName = modelPathSegments[modelPathSegments.length - 1].replace('.json', '');\n  const cachedModelName = 'indexeddb://' + shortModelName; // generate short model name for cache\n  modelStats[shortModelName] = {\n    name: shortModelName,\n    sizeFromManifest: 0,\n    sizeLoadedWeights: 0,\n    sizeDesired: modelsDefs[shortModelName],\n    inCache: false,\n  };\n  options.cacheSupported = (typeof window !== 'undefined') && (typeof window.localStorage !== 'undefined') && (typeof window.indexedDB !== 'undefined'); // check if running in browser and if indexedb is available\n  let cachedModels = {};\n  try {\n    cachedModels = (options.cacheSupported && options.cacheModels) ? await tf.io.listModels() : {}; // list all models already in cache // this fails for webview although localStorage is defined\n  } catch {\n    options.cacheSupported = false;\n  }\n  modelStats[shortModelName].inCache = (options.cacheSupported && options.cacheModels) && Object.keys(cachedModels).includes(cachedModelName); // is model found in cache\n  const tfLoadOptions = typeof fetch === 'undefined' ? {} : { fetchFunc: (url, init?) => httpHandler(url, init) };\n  const model: GraphModel = new tf.GraphModel(modelStats[shortModelName].inCache ? cachedModelName : modelUrl, tfLoadOptions) as unknown as GraphModel; // create model prototype and decide if load from cache or from original modelurl\n  let loaded = false;\n  try {\n    // @ts-ignore private function\n    model.findIOHandler(); // decide how to actually load a model\n    if (options.debug) log('model load handler:', model['handler']);\n    // @ts-ignore private property\n    const artifacts = await model.handler.load(); // load manifest\n    modelStats[shortModelName].sizeFromManifest = artifacts?.weightData?.byteLength || 0;\n    model.loadSync(artifacts); // load weights\n    // @ts-ignore private property\n    modelStats[shortModelName].sizeLoadedWeights = model?.artifacts?.weightData?.byteLength || 0;\n    if (options.verbose) log('load model:', model['modelUrl'], { bytes: modelStats[shortModelName].sizeLoadedWeights }, options);\n    loaded = true;\n  } catch (err) {\n    log('error loading model:', modelUrl, err);\n  }\n  if (loaded && options.cacheModels && options.cacheSupported && !modelStats[shortModelName].inCache) { // save model to cache\n    try {\n      const saveResult = await model.save(cachedModelName);\n      log('model saved:', cachedModelName, saveResult);\n    } catch (err) {\n      log('error saving model:', modelUrl, err);\n    }\n  }\n  return model;\n}\n", "/**\n * Loader and Validator for all models used by Human\n */\n\nimport { env } from './util/env';\nimport { log } from './util/util';\nimport * as gear from './gear/gear';\nimport * as ssrnetAge from './gear/ssrnet-age';\nimport * as ssrnetGender from './gear/ssrnet-gender';\nimport * as antispoof from './face/antispoof';\nimport * as blazeface from './face/blazeface';\nimport * as blazepose from './body/blazepose';\nimport * as centernet from './object/centernet';\nimport * as efficientpose from './body/efficientpose';\nimport * as emotion from './gear/emotion';\nimport * as mobilefacenet from './face/mobilefacenet';\nimport * as facemesh from './face/facemesh';\nimport * as faceres from './face/faceres';\nimport * as handpose from './hand/handpose';\nimport * as handtrack from './hand/handtrack';\nimport * as iris from './face/iris';\nimport * as liveness from './face/liveness';\nimport * as movenet from './body/movenet';\nimport * as nanodet from './object/nanodet';\nimport * as posenet from './body/posenet';\nimport * as segmentation from './segmentation/segmentation';\nimport { modelStats, ModelInfo } from './tfjs/load';\nimport type { GraphModel } from './tfjs/types';\nimport type { Human } from './human';\n\n/** Instances of all possible TFJS Graph Models used by Human\n * - loaded as needed based on configuration\n * - initialized explictly with `human.load()` method\n * - initialized implicity on first call to `human.detect()`\n * - each model can be `null` if not loaded, instance of `GraphModel` if loaded or `Promise` if loading\n */\nexport class Models {\n  ssrnetage: null | GraphModel | Promise<GraphModel> = null;\n  gear: null | GraphModel | Promise<GraphModel> = null;\n  blazeposedetect: null | GraphModel | Promise<GraphModel> = null;\n  blazepose: null | GraphModel | Promise<GraphModel> = null;\n  centernet: null | GraphModel | Promise<GraphModel> = null;\n  efficientpose: null | GraphModel | Promise<GraphModel> = null;\n  mobilefacenet: null | GraphModel | Promise<GraphModel> = null;\n  emotion: null | GraphModel | Promise<GraphModel> = null;\n  facedetect: null | GraphModel | Promise<GraphModel> = null;\n  faceiris: null | GraphModel | Promise<GraphModel> = null;\n  facemesh: null | GraphModel | Promise<GraphModel> = null;\n  faceres: null | GraphModel | Promise<GraphModel> = null;\n  ssrnetgender: null | GraphModel | Promise<GraphModel> = null;\n  handpose: null | GraphModel | Promise<GraphModel> = null;\n  handskeleton: null | GraphModel | Promise<GraphModel> = null;\n  handtrack: null | GraphModel | Promise<GraphModel> = null;\n  liveness: null | GraphModel | Promise<GraphModel> = null;\n  movenet: null | GraphModel | Promise<GraphModel> = null;\n  nanodet: null | GraphModel | Promise<GraphModel> = null;\n  posenet: null | GraphModel | Promise<GraphModel> = null;\n  segmentation: null | GraphModel | Promise<GraphModel> = null;\n  antispoof: null | GraphModel | Promise<GraphModel> = null;\n}\n\nexport type ModelStats = {\n  numLoadedModels: number,\n  numEnabledModels: undefined,\n  numDefinedModels: number,\n  percentageLoaded: number,\n  totalSizeFromManifest: number,\n  totalSizeWeights: number,\n  totalSizeLoading: number,\n  totalSizeEnabled: undefined,\n  modelStats: ModelInfo[],\n}\n\nexport const getModelStats = (instance: Human): ModelStats => {\n  let totalSizeFromManifest = 0;\n  let totalSizeWeights = 0;\n  let totalSizeLoading = 0;\n  for (const m of Object.values(modelStats)) {\n    totalSizeFromManifest += m.sizeFromManifest;\n    totalSizeWeights += m.sizeLoadedWeights;\n    totalSizeLoading += m.sizeDesired;\n  }\n  const percentageLoaded = totalSizeLoading > 0 ? totalSizeWeights / totalSizeLoading : 0;\n  return {\n    numLoadedModels: Object.values(modelStats).length,\n    numEnabledModels: undefined,\n    numDefinedModels: Object.keys(instance.models).length,\n    percentageLoaded,\n    totalSizeFromManifest,\n    totalSizeWeights,\n    totalSizeLoading,\n    totalSizeEnabled: undefined,\n    modelStats: Object.values(modelStats),\n  };\n};\n\nexport function reset(instance: Human): void {\n  // if (instance.config.debug) log('resetting loaded models');\n  for (const model of Object.keys(instance.models)) instance.models[model as keyof Models] = null;\n}\n\n/** Load method preloads all instance.configured models on-demand */\nexport async function load(instance: Human): Promise<void> {\n  if (env.initial) reset(instance);\n  if (instance.config.hand.enabled) { // handpose model is a combo that must be loaded as a whole\n    if (!instance.models.handpose && instance.config.hand.detector?.modelPath?.includes('handdetect')) {\n      [instance.models.handpose, instance.models.handskeleton] = await handpose.load(instance.config);\n    }\n    if (!instance.models.handskeleton && instance.config.hand.landmarks && instance.config.hand.detector?.modelPath?.includes('handdetect')) {\n      [instance.models.handpose, instance.models.handskeleton] = await handpose.load(instance.config);\n    }\n  }\n  if (instance.config.body.enabled && !instance.models.blazepose && instance.config.body?.modelPath?.includes('blazepose')) instance.models.blazepose = blazepose.loadPose(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.body.enabled && !instance.models.blazeposedetect && instance.config.body['detector'] && instance.config.body['detector']['modelPath']) instance.models.blazeposedetect = blazepose.loadDetect(instance.config);\n  if (instance.config.body.enabled && !instance.models.efficientpose && instance.config.body?.modelPath?.includes('efficientpose')) instance.models.efficientpose = efficientpose.load(instance.config);\n  if (instance.config.body.enabled && !instance.models.movenet && instance.config.body?.modelPath?.includes('movenet')) instance.models.movenet = movenet.load(instance.config);\n  if (instance.config.body.enabled && !instance.models.posenet && instance.config.body?.modelPath?.includes('posenet')) instance.models.posenet = posenet.load(instance.config);\n  if (instance.config.face.enabled && !instance.models.facedetect) instance.models.facedetect = blazeface.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.antispoof?.enabled && !instance.models.antispoof) instance.models.antispoof = antispoof.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.liveness?.enabled && !instance.models.liveness) instance.models.liveness = liveness.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.description?.enabled && !instance.models.faceres) instance.models.faceres = faceres.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.emotion?.enabled && !instance.models.emotion) instance.models.emotion = emotion.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.iris?.enabled && !instance.config.face.attention?.enabled && !instance.models.faceiris) instance.models.faceiris = iris.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.mesh?.enabled && !instance.models.facemesh) instance.models.facemesh = facemesh.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['gear']?.enabled && !instance.models.gear) instance.models.gear = gear.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['ssrnet']?.enabled && !instance.models.ssrnetage) instance.models.ssrnetage = ssrnetAge.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['ssrnet']?.enabled && !instance.models.ssrnetgender) instance.models.ssrnetgender = ssrnetGender.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['mobilefacenet']?.enabled && !instance.models.mobilefacenet) instance.models.mobilefacenet = mobilefacenet.load(instance.config);\n  if (instance.config.hand.enabled && !instance.models.handtrack && instance.config.hand.detector?.modelPath?.includes('handtrack')) instance.models.handtrack = handtrack.loadDetect(instance.config);\n  if (instance.config.hand.enabled && instance.config.hand.landmarks && !instance.models.handskeleton && instance.config.hand.detector?.modelPath?.includes('handtrack')) instance.models.handskeleton = handtrack.loadSkeleton(instance.config);\n  if (instance.config.object.enabled && !instance.models.centernet && instance.config.object?.modelPath?.includes('centernet')) instance.models.centernet = centernet.load(instance.config);\n  if (instance.config.object.enabled && !instance.models.nanodet && instance.config.object?.modelPath?.includes('nanodet')) instance.models.nanodet = nanodet.load(instance.config);\n  if (instance.config.segmentation.enabled && !instance.models.segmentation) instance.models.segmentation = segmentation.load(instance.config);\n\n  // models are loaded in parallel asynchronously so lets wait until they are actually loaded\n  for await (const model of Object.keys(instance.models)) {\n    if (instance.models[model as keyof Models] && typeof instance.models[model as keyof Models] !== 'undefined') {\n      instance.models[model as keyof Models] = await instance.models[model as keyof Models];\n    }\n  }\n}\n\nexport async function validate(instance: Human): Promise<void> {\n  interface Op { name: string, category: string, op: string }\n  const simpleOps = ['const', 'placeholder', 'noop', 'pad', 'squeeze', 'add', 'sub', 'mul', 'div'];\n  for (const defined of Object.keys(instance.models)) {\n    const model: GraphModel | null = instance.models[defined as keyof Models] as GraphModel | null;\n    if (!model) continue;\n    const ops: string[] = [];\n    // @ts-ignore // executor is a private method\n    const executor = model?.executor;\n    if (executor && executor.graph.nodes) {\n      for (const kernel of Object.values(executor.graph.nodes)) {\n        const op = (kernel as Op).op.toLowerCase();\n        if (!ops.includes(op)) ops.push(op);\n      }\n    } else {\n      if (!executor && instance.config.debug) log('model signature not determined:', defined);\n    }\n    const missing: string[] = [];\n    for (const op of ops) {\n      if (!simpleOps.includes(op) // exclude simple ops\n        && !instance.env.kernels.includes(op) // check actual kernel ops\n        && !instance.env.kernels.includes(op.replace('_', '')) // check variation without _\n        && !instance.env.kernels.includes(op.replace('native', '')) // check standard variation\n        && !instance.env.kernels.includes(op.replace('v2', ''))) { // check non-versioned variation\n        missing.push(op);\n      }\n    }\n    // log('model validation ops:', defined, ops);\n    if (instance.config.debug && missing.length > 0) log('model validation failed:', defined, missing);\n  }\n}\n", "/**\n * GEAR [gender/emotion/age/race] model implementation\n *\n * Based on: [**GEAR Predictor**](https://github.com/Udolf15/GEAR-Predictor)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { Gender, Race } from '../result';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport { env } from '../util/env';\n\nexport type GearType = { age: number, gender: Gender, genderScore: number, race: Array<{ score: number, race: Race }> }\nlet model: GraphModel | null;\nconst last: Array<GearType> = [];\nconst raceNames = ['white', 'black', 'asian', 'indian', 'other'];\nconst ageWeights = [15, 23, 28, 35.5, 45.5, 55.5, 65];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function load(config: Config) {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['gear']?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<GearType> {\n  if (!model) return { age: 0, gender: 'unknown', genderScore: 0, race: [] };\n  const skipFrame = skipped < (config.face['gear']?.skipFrames || 0);\n  const skipTime = (config.face['gear']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && last[idx]) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    if (!model?.inputs[0].shape) return;\n    const t: Record<string, Tensor> = {};\n    // t.resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape[2], model?.inputs[0].shape[1]], false);\n    const box = [[0.0, 0.10, 0.90, 0.90]]; // empyrical values for top, left, bottom, right\n    t.resize = tf.image.cropAndResize(image, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n    const obj: GearType = { age: 0, gender: 'unknown', genderScore: 0, race: [] };\n    if (config.face['gear']?.enabled) [t.age, t.gender, t.race] = model.execute(t.resize, ['age_output', 'gender_output', 'race_output']) as Tensor[];\n    const gender = await t.gender.data();\n    obj.gender = gender[0] > gender[1] ? 'male' : 'female';\n    obj.genderScore = Math.round(100 * (gender[0] > gender[1] ? gender[0] : gender[1])) / 100;\n    const race = await t.race.data();\n    for (let i = 0; i < race.length; i++) {\n      if (race[i] > (config.face['gear']?.minConfidence || 0.2)) obj.race.push({ score: Math.round(100 * race[i]) / 100, race: raceNames[i] as Race });\n    }\n    obj.race.sort((a, b) => b.score - a.score);\n    // {0: 'Below20', 1: '21-25', 2: '26-30', 3: '31-40',4: '41-50', 5: '51-60', 6: 'Above60'}\n    const ageDistribution = Array.from(await t.age.data());\n    const ageSorted = ageDistribution.map((a, i) => [ageWeights[i], a]).sort((a, b) => b[1] - a[1]);\n    let age = ageSorted[0][0]; // pick best starting point\n    for (let i = 1; i < ageSorted.length; i++) age += ageSorted[i][1] * (ageSorted[i][0] - age); // adjust with each other choice by weight\n    obj.age = Math.round(10 * age) / 10;\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    last[idx] = obj;\n    lastCount = count;\n    lastTime = now();\n    resolve(obj);\n  });\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from './types';\n\nexport const constants: Record<string, Tensor | number | number[]> = {\n  tf255: 255,\n  tf1: 1,\n  tf2: 2,\n  tf05: 0.5,\n  tf127: 127.5,\n  rgb: [0.2989, 0.5870, 0.1140],\n};\n\nexport function init() {\n  constants.tf255 = tf.scalar(255, 'float32');\n  constants.tf1 = tf.scalar(1, 'float32');\n  constants.tf2 = tf.scalar(2, 'float32');\n  constants.tf05 = tf.scalar(0.5, 'float32');\n  constants.tf127 = tf.scalar(127.5, 'float32');\n  constants.rgb = tf.tensor1d([0.2989, 0.5870, 0.1140], 'float32'); // factors for red/green/blue colors when converting to grayscale\n}\n", "/**\n * Age model implementation\n *\n * Based on: [**SSR-Net**](https://github.com/shamangary/SSR-Net)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { env } from '../util/env';\nimport { constants } from '../tfjs/constants';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\n\nlet model: GraphModel | null;\nconst last: Array<{ age: number }> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function load(config: Config) {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['ssrnet'].modelPathAge);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<{ age: number }> {\n  if (!model) return { age: 0 };\n  const skipFrame = skipped < (config.face['ssrnet']?.skipFrames || 0);\n  const skipTime = (config.face['ssrnet']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipFrame && skipTime && (lastCount === count) && last[idx]?.age && (last[idx]?.age > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    if (!model?.inputs || !model.inputs[0] || !model.inputs[0].shape) return;\n    const t: Record<string, Tensor> = {};\n    t.resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    t.enhance = tf.mul(t.resize, constants.tf255);\n    const obj = { age: 0 };\n    if (config.face['ssrnet'].enabled) t.age = model.execute(t.enhance) as Tensor;\n    if (t.age) {\n      const data = await t.age.data();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    last[idx] = obj;\n    lastCount = count;\n    lastTime = now();\n    resolve(obj);\n  });\n}\n", "/**\n * Gender model implementation\n *\n * Based on: [**SSR-Net**](https://github.com/shamangary/SSR-Net)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport type { Gender } from '../result';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst last: Array<{ gender: Gender, genderScore: number }> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function load(config: Config | any) {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['ssrnet'].modelPathGender);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function predict(image: Tensor, config: Config, idx, count): Promise<{ gender: Gender, genderScore: number }> {\n  if (!model) return { gender: 'unknown', genderScore: 0 };\n  const skipFrame = skipped < (config.face['ssrnet']?.skipFrames || 0);\n  const skipTime = (config.face['ssrnet']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipFrame && skipTime && (lastCount === count) && last[idx]?.gender && (last[idx]?.genderScore > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    if (!model?.inputs[0].shape) return;\n    const t: Record<string, Tensor> = {};\n    t.resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    t.enhance = tf.tidy(() => {\n      const [red, green, blue] = tf.split(t.resize, 3, 3);\n      const redNorm = tf.mul(red, rgb[0]);\n      const greenNorm = tf.mul(green, rgb[1]);\n      const blueNorm = tf.mul(blue, rgb[2]);\n      const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n      const normalize = tf.mul(tf.sub(grayscale, constants.tf05), 2); // range grayscale:-1..1\n      return normalize;\n    });\n    const obj: { gender: Gender, genderScore: number } = { gender: 'unknown', genderScore: 0 };\n    if (config.face['ssrnet'].enabled) t.gender = model.execute(t.enhance) as Tensor;\n    const data = await t.gender.data();\n    obj.gender = data[0] > data[1] ? 'female' : 'male'; // returns two values 0..1, bigger one is prediction\n    obj.genderScore = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    last[idx] = obj;\n    lastCount = count;\n    lastTime = now();\n    resolve(obj);\n  });\n}\n", "/**\n * Anti-spoofing model implementation\n */\n\nimport { log, now } from '../util/util';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst cached: Array<number> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet lastCount = 0;\nlet lastTime = 0;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.antispoof?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<number> {\n  if (!model) return 0;\n  const skipTime = (config.face.antispoof?.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.face.antispoof?.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && cached[idx]) {\n    skipped++;\n    return cached[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape ? model.inputs[0].shape[2] : 0, model?.inputs[0].shape ? model.inputs[0].shape[1] : 0], false);\n    const res = model?.execute(resize) as Tensor;\n    const num = (await res.data())[0];\n    cached[idx] = Math.round(100 * num) / 100;\n    lastCount = count;\n    lastTime = now();\n    tf.dispose([resize, res]);\n    resolve(cached[idx]);\n  });\n}\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n * See `facemesh.ts` for entry point\n */\n\nexport const meshAnnotations: Record<string, number[]> = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  // lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291], // 11\n  // lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291], // 10\n  // lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308], // 11\n  // lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308], // 11\n  lipsUpperOuter: [185, 40, 39, 37, 0, 267, 269, 270, 409],\n  lipsLowerOuter: [61, 146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [191, 80, 81, 82, 13, 312, 311, 310, 415],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  lipsLowerSemiOuter: [76, 77, 90, 180, 85, 16, 315, 404, 320, 307, 306],\n  lipsUpperSemiOuter: [184, 74, 73, 72, 11, 302, 303, 304, 408],\n  lipsLowerSemiInner: [62, 96, 89, 179, 86, 15, 316, 403, 319, 325, 292],\n  lipsUpperSemiInner: [183, 42, 41, 38, 12, 268, 271, 272, 407],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173], // 7\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133], // 9\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190], // 7\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243], // 9\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189], // 7\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244], // 9\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245], // 9\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193], // 8\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65], // 6\n  rightEyeIris: [473, 474, 475, 476, 477], // 5\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const meshLandmarks: Record<string, number | number[]> = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, meshAnnotations['midwayBetweenEyes'][0]],\n};\n\nexport const blazeFaceLandmarks: Record<string, number | number[]> = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nexport const irisIndices: Array<{ key: string, indices: number[] }> = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] }, // 7 x 3d\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] }, // 7 x 3d\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] }, // 7 x 3d\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] }, // 7 x 3d\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] }, // 9 x 3d\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] }, // 9 x 3d\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] }, // 9 x 3d\n  { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] }, // 8 x 3d\n  { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] }, // 6 x 3d\n];\n\nexport const UV468: [number, number][] = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 0.547487020492554],\n  [0.499974012374878, 0.602371990680695],\n  [0.482113003730774, 0.471979022026062],\n  [0.500150978565216, 0.527155995368958],\n  [0.499909996986389, 0.498252987861633],\n  [0.499523013830185, 0.40106201171875],\n  [0.289712011814117, 0.380764007568359],\n  [0.499954998493195, 0.312398016452789],\n  [0.499987006187439, 0.269918978214264],\n  [0.500023007392883, 0.107050001621246],\n  [0.500023007392883, 0.666234016418457],\n  [0.5000159740448, 0.679224014282227],\n  [0.500023007392883, 0.692348003387451],\n  [0.499976992607117, 0.695277988910675],\n  [0.499976992607117, 0.70593398809433],\n  [0.499976992607117, 0.719385027885437],\n  [0.499976992607117, 0.737019002437592],\n  [0.499967992305756, 0.781370997428894],\n  [0.499816000461578, 0.562981009483337],\n  [0.473773002624512, 0.573909997940063],\n  [0.104906998574734, 0.254140973091125],\n  [0.365929991006851, 0.409575998783112],\n  [0.338757991790771, 0.41302502155304],\n  [0.311120003461838, 0.409460008144379],\n  [0.274657994508743, 0.389131009578705],\n  [0.393361985683441, 0.403706014156342],\n  [0.345234006643295, 0.344011008739471],\n  [0.370094001293182, 0.346076011657715],\n  [0.319321990013123, 0.347265005111694],\n  [0.297903001308441, 0.353591024875641],\n  [0.24779200553894, 0.410809993743896],\n  [0.396889001131058, 0.842755019664764],\n  [0.280097991228104, 0.375599980354309],\n  [0.106310002505779, 0.399955987930298],\n  [0.2099249958992, 0.391353011131287],\n  [0.355807989835739, 0.534406006336212],\n  [0.471751004457474, 0.65040397644043],\n  [0.474155008792877, 0.680191993713379],\n  [0.439785003662109, 0.657229006290436],\n  [0.414617002010345, 0.66654098033905],\n  [0.450374007225037, 0.680860996246338],\n  [0.428770989179611, 0.682690978050232],\n  [0.374971002340317, 0.727805018424988],\n  [0.486716985702515, 0.547628998756409],\n  [0.485300987958908, 0.527395009994507],\n  [0.257764995098114, 0.314490020275116],\n  [0.401223003864288, 0.455172002315521],\n  [0.429818987846375, 0.548614978790283],\n  [0.421351999044418, 0.533740997314453],\n  [0.276895999908447, 0.532056987285614],\n  [0.483370006084442, 0.499586999416351],\n  [0.33721199631691, 0.282882988452911],\n  [0.296391993761063, 0.293242990970612],\n  [0.169294998049736, 0.193813979625702],\n  [0.447580009698868, 0.302609980106354],\n  [0.392390012741089, 0.353887975215912],\n  [0.354490011930466, 0.696784019470215],\n  [0.067304998636246, 0.730105042457581],\n  [0.442739009857178, 0.572826027870178],\n  [0.457098007202148, 0.584792017936707],\n  [0.381974011659622, 0.694710969924927],\n  [0.392388999462128, 0.694203019142151],\n  [0.277076005935669, 0.271932005882263],\n  [0.422551989555359, 0.563233017921448],\n  [0.385919004678726, 0.281364023685455],\n  [0.383103013038635, 0.255840003490448],\n  [0.331431001424789, 0.119714021682739],\n  [0.229923993349075, 0.232002973556519],\n  [0.364500999450684, 0.189113974571228],\n  [0.229622006416321, 0.299540996551514],\n  [0.173287004232407, 0.278747975826263],\n  [0.472878992557526, 0.666198015213013],\n  [0.446828007698059, 0.668527007102966],\n  [0.422762006521225, 0.673889994621277],\n  [0.445307999849319, 0.580065965652466],\n  [0.388103008270264, 0.693961024284363],\n  [0.403039008378983, 0.706539988517761],\n  [0.403629004955292, 0.693953037261963],\n  [0.460041999816895, 0.557139039039612],\n  [0.431158006191254, 0.692366003990173],\n  [0.452181994915009, 0.692366003990173],\n  [0.475387006998062, 0.692366003990173],\n  [0.465828001499176, 0.779190003871918],\n  [0.472328990697861, 0.736225962638855],\n  [0.473087012767792, 0.717857003211975],\n  [0.473122000694275, 0.704625964164734],\n  [0.473033010959625, 0.695277988910675],\n  [0.427942007780075, 0.695277988910675],\n  [0.426479011774063, 0.703539967536926],\n  [0.423162013292313, 0.711845993995667],\n  [0.4183090031147, 0.720062971115112],\n  [0.390094995498657, 0.639572978019714],\n  [0.013953999616206, 0.560034036636353],\n  [0.499913990497589, 0.58014702796936],\n  [0.413199990987778, 0.69539999961853],\n  [0.409626007080078, 0.701822996139526],\n  [0.468080013990402, 0.601534962654114],\n  [0.422728985548019, 0.585985004901886],\n  [0.463079988956451, 0.593783974647522],\n  [0.37211999297142, 0.47341400384903],\n  [0.334562003612518, 0.496073007583618],\n  [0.411671012639999, 0.546965003013611],\n  [0.242175996303558, 0.14767599105835],\n  [0.290776997804642, 0.201445996761322],\n  [0.327338010072708, 0.256527006626129],\n  [0.399509996175766, 0.748921036720276],\n  [0.441727995872498, 0.261676013469696],\n  [0.429764986038208, 0.187834024429321],\n  [0.412198007106781, 0.108901023864746],\n  [0.288955003023148, 0.398952007293701],\n  [0.218936994671822, 0.435410976409912],\n  [0.41278201341629, 0.398970007896423],\n  [0.257135003805161, 0.355440020561218],\n  [0.427684992551804, 0.437960982322693],\n  [0.448339998722076, 0.536936044692993],\n  [0.178560003638268, 0.45755398273468],\n  [0.247308000922203, 0.457193970680237],\n  [0.286267012357712, 0.467674970626831],\n  [0.332827985286713, 0.460712015628815],\n  [0.368755996227264, 0.447206974029541],\n  [0.398963987827301, 0.432654976844788],\n  [0.476410001516342, 0.405806005001068],\n  [0.189241006970406, 0.523923993110657],\n  [0.228962004184723, 0.348950982093811],\n  [0.490725994110107, 0.562400996685028],\n  [0.404670000076294, 0.485132992267609],\n  [0.019469000399113, 0.401564002037048],\n  [0.426243007183075, 0.420431017875671],\n  [0.396993011236191, 0.548797011375427],\n  [0.266469985246658, 0.376977026462555],\n  [0.439121007919312, 0.51895797252655],\n  [0.032313998788595, 0.644356966018677],\n  [0.419054001569748, 0.387154996395111],\n  [0.462783008813858, 0.505746960639954],\n  [0.238978996872902, 0.779744982719421],\n  [0.198220998048782, 0.831938028335571],\n  [0.107550002634525, 0.540755033493042],\n  [0.183610007166862, 0.740257024765015],\n  [0.134409993886948, 0.333683013916016],\n  [0.385764002799988, 0.883153975009918],\n  [0.490967005491257, 0.579378008842468],\n  [0.382384985685349, 0.508572995662689],\n  [0.174399003386497, 0.397670984268188],\n  [0.318785011768341, 0.39623498916626],\n  [0.343364000320435, 0.400596976280212],\n  [0.396100014448166, 0.710216999053955],\n  [0.187885001301765, 0.588537991046906],\n  [0.430987000465393, 0.944064974784851],\n  [0.318993002176285, 0.898285031318665],\n  [0.266247987747192, 0.869701027870178],\n  [0.500023007392883, 0.190576016902924],\n  [0.499976992607117, 0.954452991485596],\n  [0.366169989109039, 0.398822009563446],\n  [0.393207013607025, 0.39553701877594],\n  [0.410373002290726, 0.391080021858215],\n  [0.194993004202843, 0.342101991176605],\n  [0.388664990663528, 0.362284004688263],\n  [0.365961998701096, 0.355970978736877],\n  [0.343364000320435, 0.355356991291046],\n  [0.318785011768341, 0.35834002494812],\n  [0.301414996385574, 0.363156020641327],\n  [0.058132998645306, 0.319076001644135],\n  [0.301414996385574, 0.387449026107788],\n  [0.499987989664078, 0.618434011936188],\n  [0.415838003158569, 0.624195992946625],\n  [0.445681989192963, 0.566076993942261],\n  [0.465844005346298, 0.620640993118286],\n  [0.49992299079895, 0.351523995399475],\n  [0.288718998432159, 0.819945991039276],\n  [0.335278987884521, 0.852819979190826],\n  [0.440512001514435, 0.902418971061707],\n  [0.128294005990028, 0.791940987110138],\n  [0.408771991729736, 0.373893976211548],\n  [0.455606997013092, 0.451801002025604],\n  [0.499877005815506, 0.908990025520325],\n  [0.375436991453171, 0.924192011356354],\n  [0.11421000212431, 0.615022003650665],\n  [0.448662012815475, 0.695277988910675],\n  [0.4480200111866, 0.704632043838501],\n  [0.447111994028091, 0.715808033943176],\n  [0.444831997156143, 0.730794012546539],\n  [0.430011987686157, 0.766808986663818],\n  [0.406787008047104, 0.685672998428345],\n  [0.400738000869751, 0.681069016456604],\n  [0.392399996519089, 0.677703022956848],\n  [0.367855995893478, 0.663918972015381],\n  [0.247923001646996, 0.601333022117615],\n  [0.452769994735718, 0.420849978923798],\n  [0.43639200925827, 0.359887003898621],\n  [0.416164010763168, 0.368713974952698],\n  [0.413385987281799, 0.692366003990173],\n  [0.228018000721931, 0.683571994304657],\n  [0.468268007040024, 0.352671027183533],\n  [0.411361992359161, 0.804327011108398],\n  [0.499989002943039, 0.469825029373169],\n  [0.479153990745544, 0.442654013633728],\n  [0.499974012374878, 0.439637005329132],\n  [0.432112008333206, 0.493588984012604],\n  [0.499886006116867, 0.866917014122009],\n  [0.49991300702095, 0.821729004383087],\n  [0.456548988819122, 0.819200992584229],\n  [0.344549000263214, 0.745438992977142],\n  [0.37890899181366, 0.574010014533997],\n  [0.374292999505997, 0.780184984207153],\n  [0.319687992334366, 0.570737957954407],\n  [0.357154995203018, 0.604269981384277],\n  [0.295284003019333, 0.621580958366394],\n  [0.447750002145767, 0.862477004528046],\n  [0.410986006259918, 0.508723020553589],\n  [0.31395098567009, 0.775308012962341],\n  [0.354128003120422, 0.812552988529205],\n  [0.324548006057739, 0.703992962837219],\n  [0.189096003770828, 0.646299958229065],\n  [0.279776990413666, 0.71465802192688],\n  [0.1338230073452, 0.682700991630554],\n  [0.336768001317978, 0.644733011722565],\n  [0.429883986711502, 0.466521978378296],\n  [0.455527991056442, 0.548622965812683],\n  [0.437114000320435, 0.558896005153656],\n  [0.467287987470627, 0.529924988746643],\n  [0.414712011814117, 0.335219979286194],\n  [0.37704598903656, 0.322777986526489],\n  [0.344107985496521, 0.320150971412659],\n  [0.312875986099243, 0.32233202457428],\n  [0.283526003360748, 0.333190023899078],\n  [0.241245999932289, 0.382785975933075],\n  [0.102986000478268, 0.468762993812561],\n  [0.267612010240555, 0.424560010433197],\n  [0.297879010438919, 0.433175981044769],\n  [0.333433985710144, 0.433878004550934],\n  [0.366427004337311, 0.426115989685059],\n  [0.396012008190155, 0.416696012020111],\n  [0.420121014118195, 0.41022801399231],\n  [0.007561000064015, 0.480777025222778],\n  [0.432949006557465, 0.569517970085144],\n  [0.458638995885849, 0.479089021682739],\n  [0.473466008901596, 0.545744001865387],\n  [0.476087987422943, 0.563830018043518],\n  [0.468472003936768, 0.555056989192963],\n  [0.433990985155106, 0.582361996173859],\n  [0.483518004417419, 0.562983989715576],\n  [0.482482999563217, 0.57784903049469],\n  [0.42645001411438, 0.389798998832703],\n  [0.438998997211456, 0.39649498462677],\n  [0.450067013502121, 0.400434017181396],\n  [0.289712011814117, 0.368252992630005],\n  [0.276670008897781, 0.363372981548309],\n  [0.517862021923065, 0.471948027610779],\n  [0.710287988185883, 0.380764007568359],\n  [0.526226997375488, 0.573909997940063],\n  [0.895093023777008, 0.254140973091125],\n  [0.634069979190826, 0.409575998783112],\n  [0.661242008209229, 0.41302502155304],\n  [0.688880026340485, 0.409460008144379],\n  [0.725341975688934, 0.389131009578705],\n  [0.606630027294159, 0.40370500087738],\n  [0.654766023159027, 0.344011008739471],\n  [0.629905998706818, 0.346076011657715],\n  [0.680678009986877, 0.347265005111694],\n  [0.702096998691559, 0.353591024875641],\n  [0.75221198797226, 0.410804986953735],\n  [0.602918028831482, 0.842862963676453],\n  [0.719901978969574, 0.375599980354309],\n  [0.893692970275879, 0.399959981441498],\n  [0.790081977844238, 0.391354024410248],\n  [0.643998026847839, 0.534487962722778],\n  [0.528249025344849, 0.65040397644043],\n  [0.525849997997284, 0.680191040039062],\n  [0.560214996337891, 0.657229006290436],\n  [0.585384011268616, 0.66654098033905],\n  [0.549625992774963, 0.680860996246338],\n  [0.57122802734375, 0.682691991329193],\n  [0.624852001667023, 0.72809898853302],\n  [0.513050019741058, 0.547281980514526],\n  [0.51509702205658, 0.527251958847046],\n  [0.742246985435486, 0.314507007598877],\n  [0.598631024360657, 0.454979002475739],\n  [0.570338010787964, 0.548575043678284],\n  [0.578631997108459, 0.533622980117798],\n  [0.723087012767792, 0.532054007053375],\n  [0.516445994377136, 0.499638974666595],\n  [0.662801027297974, 0.282917976379395],\n  [0.70362401008606, 0.293271005153656],\n  [0.830704987049103, 0.193813979625702],\n  [0.552385985851288, 0.302568018436432],\n  [0.607609987258911, 0.353887975215912],\n  [0.645429015159607, 0.696707010269165],\n  [0.932694971561432, 0.730105042457581],\n  [0.557260990142822, 0.572826027870178],\n  [0.542901992797852, 0.584792017936707],\n  [0.6180260181427, 0.694710969924927],\n  [0.607590973377228, 0.694203019142151],\n  [0.722943007946014, 0.271963000297546],\n  [0.577413976192474, 0.563166975975037],\n  [0.614082992076874, 0.281386971473694],\n  [0.616907000541687, 0.255886018276215],\n  [0.668509006500244, 0.119913995265961],\n  [0.770092010498047, 0.232020974159241],\n  [0.635536015033722, 0.189248979091644],\n  [0.77039098739624, 0.299556016921997],\n  [0.826722025871277, 0.278755009174347],\n  [0.527121007442474, 0.666198015213013],\n  [0.553171992301941, 0.668527007102966],\n  [0.577238023281097, 0.673889994621277],\n  [0.554691970348358, 0.580065965652466],\n  [0.611896991729736, 0.693961024284363],\n  [0.59696102142334, 0.706539988517761],\n  [0.596370995044708, 0.693953037261963],\n  [0.539958000183105, 0.557139039039612],\n  [0.568841993808746, 0.692366003990173],\n  [0.547818005084991, 0.692366003990173],\n  [0.52461302280426, 0.692366003990173],\n  [0.534089982509613, 0.779141008853912],\n  [0.527670979499817, 0.736225962638855],\n  [0.526912987232208, 0.717857003211975],\n  [0.526877999305725, 0.704625964164734],\n  [0.526966989040375, 0.695277988910675],\n  [0.572058022022247, 0.695277988910675],\n  [0.573521018028259, 0.703539967536926],\n  [0.57683801651001, 0.711845993995667],\n  [0.581691026687622, 0.720062971115112],\n  [0.609944999217987, 0.639909982681274],\n  [0.986046016216278, 0.560034036636353],\n  [0.5867999792099, 0.69539999961853],\n  [0.590372025966644, 0.701822996139526],\n  [0.531915009021759, 0.601536989212036],\n  [0.577268004417419, 0.585934996604919],\n  [0.536915004253387, 0.593786001205444],\n  [0.627542972564697, 0.473352015018463],\n  [0.665585994720459, 0.495950996875763],\n  [0.588353991508484, 0.546862006187439],\n  [0.757824003696442, 0.14767599105835],\n  [0.709249973297119, 0.201507985591888],\n  [0.672684013843536, 0.256581008434296],\n  [0.600408971309662, 0.74900496006012],\n  [0.55826598405838, 0.261672019958496],\n  [0.570303976535797, 0.187870979309082],\n  [0.588165998458862, 0.109044015407562],\n  [0.711045026779175, 0.398952007293701],\n  [0.781069993972778, 0.435405015945435],\n  [0.587247014045715, 0.398931980133057],\n  [0.742869973182678, 0.355445981025696],\n  [0.572156012058258, 0.437651991844177],\n  [0.55186802148819, 0.536570012569427],\n  [0.821442008018494, 0.457556009292603],\n  [0.752701997756958, 0.457181990146637],\n  [0.71375697851181, 0.467626988887787],\n  [0.66711300611496, 0.460672974586487],\n  [0.631101012229919, 0.447153985500336],\n  [0.6008620262146, 0.432473003864288],\n  [0.523481011390686, 0.405627012252808],\n  [0.810747981071472, 0.523926019668579],\n  [0.771045982837677, 0.348959028720856],\n  [0.509127020835876, 0.562718033790588],\n  [0.595292985439301, 0.485023975372314],\n  [0.980530977249146, 0.401564002037048],\n  [0.573499977588654, 0.420000016689301],\n  [0.602994978427887, 0.548687994480133],\n  [0.733529984951019, 0.376977026462555],\n  [0.560611009597778, 0.519016981124878],\n  [0.967685997486115, 0.644356966018677],\n  [0.580985009670258, 0.387160003185272],\n  [0.537728011608124, 0.505385041236877],\n  [0.760966002941132, 0.779752969741821],\n  [0.801778972148895, 0.831938028335571],\n  [0.892440974712372, 0.54076099395752],\n  [0.816350996494293, 0.740260004997253],\n  [0.865594983100891, 0.333687007427216],\n  [0.614073991775513, 0.883246004581451],\n  [0.508952975273132, 0.579437971115112],\n  [0.617941975593567, 0.508316040039062],\n  [0.825608015060425, 0.397674977779388],\n  [0.681214988231659, 0.39623498916626],\n  [0.656635999679565, 0.400596976280212],\n  [0.603900015354156, 0.710216999053955],\n  [0.81208598613739, 0.588539004325867],\n  [0.56801301240921, 0.944564998149872],\n  [0.681007981300354, 0.898285031318665],\n  [0.733752012252808, 0.869701027870178],\n  [0.633830010890961, 0.398822009563446],\n  [0.606792986392975, 0.39553701877594],\n  [0.589659988880157, 0.391062021255493],\n  [0.805015981197357, 0.342108011245728],\n  [0.611334979534149, 0.362284004688263],\n  [0.634037971496582, 0.355970978736877],\n  [0.656635999679565, 0.355356991291046],\n  [0.681214988231659, 0.35834002494812],\n  [0.698584973812103, 0.363156020641327],\n  [0.941866993904114, 0.319076001644135],\n  [0.698584973812103, 0.387449026107788],\n  [0.584177017211914, 0.624107003211975],\n  [0.554318010807037, 0.566076993942261],\n  [0.534153997898102, 0.62064003944397],\n  [0.711217999458313, 0.819975018501282],\n  [0.664629995822906, 0.852871000766754],\n  [0.559099972248077, 0.902631998062134],\n  [0.871706008911133, 0.791940987110138],\n  [0.591234028339386, 0.373893976211548],\n  [0.544341027736664, 0.451583981513977],\n  [0.624562978744507, 0.924192011356354],\n  [0.88577002286911, 0.615028977394104],\n  [0.551338016986847, 0.695277988910675],\n  [0.551980018615723, 0.704632043838501],\n  [0.552887976169586, 0.715808033943176],\n  [0.555167973041534, 0.730794012546539],\n  [0.569944024085999, 0.767035007476807],\n  [0.593203008174896, 0.685675978660583],\n  [0.599261999130249, 0.681069016456604],\n  [0.607599973678589, 0.677703022956848],\n  [0.631937980651855, 0.663500010967255],\n  [0.752032995223999, 0.601315021514893],\n  [0.547226011753082, 0.420395016670227],\n  [0.563543975353241, 0.359827995300293],\n  [0.583841025829315, 0.368713974952698],\n  [0.586614012718201, 0.692366003990173],\n  [0.771915018558502, 0.683578014373779],\n  [0.531597018241882, 0.352482974529266],\n  [0.588370978832245, 0.804440975189209],\n  [0.52079701423645, 0.442565023899078],\n  [0.567984998226166, 0.493479013442993],\n  [0.543282985687256, 0.819254994392395],\n  [0.655317008495331, 0.745514988899231],\n  [0.621008992195129, 0.574018001556396],\n  [0.625559985637665, 0.78031200170517],\n  [0.680198013782501, 0.570719003677368],\n  [0.64276397228241, 0.604337990283966],\n  [0.704662978649139, 0.621529996395111],\n  [0.552012026309967, 0.862591981887817],\n  [0.589071989059448, 0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468: Array<number> = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68: Array<number> = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33: Array<number> = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7: Array<number> = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68: Array<number> = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33: Array<number> = [33, 133, 362, 263, 1, 62, 308, 159, 145, 386, 374, 6, 102, 331, 2, 13, 14, 70, 105, 107, 336, 334, 300, 54, 10, 284, 50, 280, 234, 454, 58, 288, 152];\n\nexport const VTX7: Array<number> = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n\n// https://github.com/tensorflow/tfjs-models/blob/master/face-landmarks-detection/src/constants.ts\n// https://github.com/google/mediapipe/mediapipe/python/solutions/face_mesh_connections.py\n\ntype PairArray = Array<[number, number]>;\n\nfunction connectionsToIndices(connections: PairArray) {\n  const indices = connections.map((connection) => connection[0]);\n  indices.push(connections[connections.length - 1][1]);\n  return indices;\n}\n\nexport const pairsLips: PairArray = [\n  [61, 146], [146, 91], [91, 181], [181, 84], [84, 17], [17, 314], [314, 405], [405, 321], [321, 375], [375, 291], [61, 185], [185, 40], [40, 39], [39, 37], [37, 0], [0, 267], [267, 269], [269, 270], [270, 409], [409, 291],\n  [78, 95], [95, 88], [88, 178], [178, 87], [87, 14], [14, 317], [317, 402], [402, 318], [318, 324], [324, 308], [78, 191], [191, 80], [80, 81], [81, 82], [82, 13], [13, 312], [312, 311], [311, 310], [310, 415], [415, 308],\n];\n\nexport const pairsLeftEye: PairArray = [[263, 249], [249, 390], [390, 373], [373, 374], [374, 380], [380, 381], [381, 382], [382, 362], [263, 466], [466, 388], [388, 387], [387, 386], [386, 385], [385, 384], [384, 398], [398, 362]];\n\nexport const pairsLeftEyebrow: PairArray = [[276, 283], [283, 282], [282, 295], [295, 285], [300, 293], [293, 334], [334, 296], [296, 336]];\n\nexport const pairsLeftIris: PairArray = [[474, 475], [475, 476], [476, 477], [477, 474]];\n\nexport const pairsRightEye: PairArray = [[33, 7], [7, 163], [163, 144], [144, 145], [145, 153], [153, 154], [154, 155], [155, 133], [33, 246], [246, 161], [161, 160], [160, 159], [159, 158], [158, 157], [157, 173], [173, 133]];\n\nexport const pairsRightEyebrow: PairArray = [[46, 53], [53, 52], [52, 65], [65, 55], [70, 63], [63, 105], [105, 66], [66, 107]];\n\nexport const pairsRightIris: PairArray = [[469, 470], [470, 471], [471, 472], [472, 469]];\n\nexport const pairsFaceContour: PairArray = [\n  [10, 338], [338, 297], [297, 332], [332, 284], [284, 251], [251, 389],\n  [389, 356], [356, 454], [454, 323], [323, 361], [361, 288], [288, 397],\n  [397, 365], [365, 379], [379, 378], [378, 400], [400, 377], [377, 152],\n  [152, 148], [148, 176], [176, 149], [149, 150], [150, 136], [136, 172],\n  [172, 58], [58, 132], [132, 93], [93, 234], [234, 127], [127, 162],\n  [162, 21], [21, 54], [54, 103], [103, 67], [67, 109], [109, 10],\n];\n\nexport const contourKeypoints = {\n  lips: connectionsToIndices(pairsLips),\n  leftEye: connectionsToIndices(pairsLeftEye),\n  leftEyebrow: connectionsToIndices(pairsLeftEyebrow),\n  leftIris: connectionsToIndices(pairsLeftIris),\n  rightEye: connectionsToIndices(pairsRightEye),\n  rightEyebrow: connectionsToIndices(pairsRightEyebrow),\n  rightIris: connectionsToIndices(pairsRightIris),\n  faceOval: connectionsToIndices(pairsFaceContour),\n};\n\nexport const pairsFaceMesh: PairArray = [\n  [127, 34], [34, 139], [139, 127], [11, 0], [0, 37], [37, 11],\n  [232, 231], [231, 120], [120, 232], [72, 37], [37, 39], [39, 72],\n  [128, 121], [121, 47], [47, 128], [232, 121], [121, 128], [128, 232],\n  [104, 69], [69, 67], [67, 104], [175, 171], [171, 148], [148, 175],\n  [118, 50], [50, 101], [101, 118], [73, 39], [39, 40], [40, 73],\n  [9, 151], [151, 108], [108, 9], [48, 115], [115, 131], [131, 48],\n  [194, 204], [204, 211], [211, 194], [74, 40], [40, 185], [185, 74],\n  [80, 42], [42, 183], [183, 80], [40, 92], [92, 186], [186, 40],\n  [230, 229], [229, 118], [118, 230], [202, 212], [212, 214], [214, 202],\n  [83, 18], [18, 17], [17, 83], [76, 61], [61, 146], [146, 76],\n  [160, 29], [29, 30], [30, 160], [56, 157], [157, 173], [173, 56],\n  [106, 204], [204, 194], [194, 106], [135, 214], [214, 192], [192, 135],\n  [203, 165], [165, 98], [98, 203], [21, 71], [71, 68], [68, 21],\n  [51, 45], [45, 4], [4, 51], [144, 24], [24, 23], [23, 144],\n  [77, 146], [146, 91], [91, 77], [205, 50], [50, 187], [187, 205],\n  [201, 200], [200, 18], [18, 201], [91, 106], [106, 182], [182, 91],\n  [90, 91], [91, 181], [181, 90], [85, 84], [84, 17], [17, 85],\n  [206, 203], [203, 36], [36, 206], [148, 171], [171, 140], [140, 148],\n  [92, 40], [40, 39], [39, 92], [193, 189], [189, 244], [244, 193],\n  [159, 158], [158, 28], [28, 159], [247, 246], [246, 161], [161, 247],\n  [236, 3], [3, 196], [196, 236], [54, 68], [68, 104], [104, 54],\n  [193, 168], [168, 8], [8, 193], [117, 228], [228, 31], [31, 117],\n  [189, 193], [193, 55], [55, 189], [98, 97], [97, 99], [99, 98],\n  [126, 47], [47, 100], [100, 126], [166, 79], [79, 218], [218, 166],\n  [155, 154], [154, 26], [26, 155], [209, 49], [49, 131], [131, 209],\n  [135, 136], [136, 150], [150, 135], [47, 126], [126, 217], [217, 47],\n  [223, 52], [52, 53], [53, 223], [45, 51], [51, 134], [134, 45],\n  [211, 170], [170, 140], [140, 211], [67, 69], [69, 108], [108, 67],\n  [43, 106], [106, 91], [91, 43], [230, 119], [119, 120], [120, 230],\n  [226, 130], [130, 247], [247, 226], [63, 53], [53, 52], [52, 63],\n  [238, 20], [20, 242], [242, 238], [46, 70], [70, 156], [156, 46],\n  [78, 62], [62, 96], [96, 78], [46, 53], [53, 63], [63, 46],\n  [143, 34], [34, 227], [227, 143], [123, 117], [117, 111], [111, 123],\n  [44, 125], [125, 19], [19, 44], [236, 134], [134, 51], [51, 236],\n  [216, 206], [206, 205], [205, 216], [154, 153], [153, 22], [22, 154],\n  [39, 37], [37, 167], [167, 39], [200, 201], [201, 208], [208, 200],\n  [36, 142], [142, 100], [100, 36], [57, 212], [212, 202], [202, 57],\n  [20, 60], [60, 99], [99, 20], [28, 158], [158, 157], [157, 28],\n  [35, 226], [226, 113], [113, 35], [160, 159], [159, 27], [27, 160],\n  [204, 202], [202, 210], [210, 204], [113, 225], [225, 46], [46, 113],\n  [43, 202], [202, 204], [204, 43], [62, 76], [76, 77], [77, 62],\n  [137, 123], [123, 116], [116, 137], [41, 38], [38, 72], [72, 41],\n  [203, 129], [129, 142], [142, 203], [64, 98], [98, 240], [240, 64],\n  [49, 102], [102, 64], [64, 49], [41, 73], [73, 74], [74, 41],\n  [212, 216], [216, 207], [207, 212], [42, 74], [74, 184], [184, 42],\n  [169, 170], [170, 211], [211, 169], [170, 149], [149, 176], [176, 170],\n  [105, 66], [66, 69], [69, 105], [122, 6], [6, 168], [168, 122],\n  [123, 147], [147, 187], [187, 123], [96, 77], [77, 90], [90, 96],\n  [65, 55], [55, 107], [107, 65], [89, 90], [90, 180], [180, 89],\n  [101, 100], [100, 120], [120, 101], [63, 105], [105, 104], [104, 63],\n  [93, 137], [137, 227], [227, 93], [15, 86], [86, 85], [85, 15],\n  [129, 102], [102, 49], [49, 129], [14, 87], [87, 86], [86, 14],\n  [55, 8], [8, 9], [9, 55], [100, 47], [47, 121], [121, 100],\n  [145, 23], [23, 22], [22, 145], [88, 89], [89, 179], [179, 88],\n  [6, 122], [122, 196], [196, 6], [88, 95], [95, 96], [96, 88],\n  [138, 172], [172, 136], [136, 138], [215, 58], [58, 172], [172, 215],\n  [115, 48], [48, 219], [219, 115], [42, 80], [80, 81], [81, 42],\n  [195, 3], [3, 51], [51, 195], [43, 146], [146, 61], [61, 43],\n  [171, 175], [175, 199], [199, 171], [81, 82], [82, 38], [38, 81],\n  [53, 46], [46, 225], [225, 53], [144, 163], [163, 110], [110, 144],\n  [52, 65], [65, 66], [66, 52], [229, 228], [228, 117], [117, 229],\n  [34, 127], [127, 234], [234, 34], [107, 108], [108, 69], [69, 107],\n  [109, 108], [108, 151], [151, 109], [48, 64], [64, 235], [235, 48],\n  [62, 78], [78, 191], [191, 62], [129, 209], [209, 126], [126, 129],\n  [111, 35], [35, 143], [143, 111], [117, 123], [123, 50], [50, 117],\n  [222, 65], [65, 52], [52, 222], [19, 125], [125, 141], [141, 19],\n  [221, 55], [55, 65], [65, 221], [3, 195], [195, 197], [197, 3],\n  [25, 7], [7, 33], [33, 25], [220, 237], [237, 44], [44, 220],\n  [70, 71], [71, 139], [139, 70], [122, 193], [193, 245], [245, 122],\n  [247, 130], [130, 33], [33, 247], [71, 21], [21, 162], [162, 71],\n  [170, 169], [169, 150], [150, 170], [188, 174], [174, 196], [196, 188],\n  [216, 186], [186, 92], [92, 216], [2, 97], [97, 167], [167, 2],\n  [141, 125], [125, 241], [241, 141], [164, 167], [167, 37], [37, 164],\n  [72, 38], [38, 12], [12, 72], [38, 82], [82, 13], [13, 38],\n  [63, 68], [68, 71], [71, 63], [226, 35], [35, 111], [111, 226],\n  [101, 50], [50, 205], [205, 101], [206, 92], [92, 165], [165, 206],\n  [209, 198], [198, 217], [217, 209], [165, 167], [167, 97], [97, 165],\n  [220, 115], [115, 218], [218, 220], [133, 112], [112, 243], [243, 133],\n  [239, 238], [238, 241], [241, 239], [214, 135], [135, 169], [169, 214],\n  [190, 173], [173, 133], [133, 190], [171, 208], [208, 32], [32, 171],\n  [125, 44], [44, 237], [237, 125], [86, 87], [87, 178], [178, 86],\n  [85, 86], [86, 179], [179, 85], [84, 85], [85, 180], [180, 84],\n  [83, 84], [84, 181], [181, 83], [201, 83], [83, 182], [182, 201],\n  [137, 93], [93, 132], [132, 137], [76, 62], [62, 183], [183, 76],\n  [61, 76], [76, 184], [184, 61], [57, 61], [61, 185], [185, 57],\n  [212, 57], [57, 186], [186, 212], [214, 207], [207, 187], [187, 214],\n  [34, 143], [143, 156], [156, 34], [79, 239], [239, 237], [237, 79],\n  [123, 137], [137, 177], [177, 123], [44, 1], [1, 4], [4, 44],\n  [201, 194], [194, 32], [32, 201], [64, 102], [102, 129], [129, 64],\n  [213, 215], [215, 138], [138, 213], [59, 166], [166, 219], [219, 59],\n  [242, 99], [99, 97], [97, 242], [2, 94], [94, 141], [141, 2],\n  [75, 59], [59, 235], [235, 75], [24, 110], [110, 228], [228, 24],\n  [25, 130], [130, 226], [226, 25], [23, 24], [24, 229], [229, 23],\n  [22, 23], [23, 230], [230, 22], [26, 22], [22, 231], [231, 26],\n  [112, 26], [26, 232], [232, 112], [189, 190], [190, 243], [243, 189],\n  [221, 56], [56, 190], [190, 221], [28, 56], [56, 221], [221, 28],\n  [27, 28], [28, 222], [222, 27], [29, 27], [27, 223], [223, 29],\n  [30, 29], [29, 224], [224, 30], [247, 30], [30, 225], [225, 247],\n  [238, 79], [79, 20], [20, 238], [166, 59], [59, 75], [75, 166],\n  [60, 75], [75, 240], [240, 60], [147, 177], [177, 215], [215, 147],\n  [20, 79], [79, 166], [166, 20], [187, 147], [147, 213], [213, 187],\n  [112, 233], [233, 244], [244, 112], [233, 128], [128, 245], [245, 233],\n  [128, 114], [114, 188], [188, 128], [114, 217], [217, 174], [174, 114],\n  [131, 115], [115, 220], [220, 131], [217, 198], [198, 236], [236, 217],\n  [198, 131], [131, 134], [134, 198], [177, 132], [132, 58], [58, 177],\n  [143, 35], [35, 124], [124, 143], [110, 163], [163, 7], [7, 110],\n  [228, 110], [110, 25], [25, 228], [356, 389], [389, 368], [368, 356],\n  [11, 302], [302, 267], [267, 11], [452, 350], [350, 349], [349, 452],\n  [302, 303], [303, 269], [269, 302], [357, 343], [343, 277], [277, 357],\n  [452, 453], [453, 357], [357, 452], [333, 332], [332, 297], [297, 333],\n  [175, 152], [152, 377], [377, 175], [347, 348], [348, 330], [330, 347],\n  [303, 304], [304, 270], [270, 303], [9, 336], [336, 337], [337, 9],\n  [278, 279], [279, 360], [360, 278], [418, 262], [262, 431], [431, 418],\n  [304, 408], [408, 409], [409, 304], [310, 415], [415, 407], [407, 310],\n  [270, 409], [409, 410], [410, 270], [450, 348], [348, 347], [347, 450],\n  [422, 430], [430, 434], [434, 422], [313, 314], [314, 17], [17, 313],\n  [306, 307], [307, 375], [375, 306], [387, 388], [388, 260], [260, 387],\n  [286, 414], [414, 398], [398, 286], [335, 406], [406, 418], [418, 335],\n  [364, 367], [367, 416], [416, 364], [423, 358], [358, 327], [327, 423],\n  [251, 284], [284, 298], [298, 251], [281, 5], [5, 4], [4, 281],\n  [373, 374], [374, 253], [253, 373], [307, 320], [320, 321], [321, 307],\n  [425, 427], [427, 411], [411, 425], [421, 313], [313, 18], [18, 421],\n  [321, 405], [405, 406], [406, 321], [320, 404], [404, 405], [405, 320],\n  [315, 16], [16, 17], [17, 315], [426, 425], [425, 266], [266, 426],\n  [377, 400], [400, 369], [369, 377], [322, 391], [391, 269], [269, 322],\n  [417, 465], [465, 464], [464, 417], [386, 257], [257, 258], [258, 386],\n  [466, 260], [260, 388], [388, 466], [456, 399], [399, 419], [419, 456],\n  [284, 332], [332, 333], [333, 284], [417, 285], [285, 8], [8, 417],\n  [346, 340], [340, 261], [261, 346], [413, 441], [441, 285], [285, 413],\n  [327, 460], [460, 328], [328, 327], [355, 371], [371, 329], [329, 355],\n  [392, 439], [439, 438], [438, 392], [382, 341], [341, 256], [256, 382],\n  [429, 420], [420, 360], [360, 429], [364, 394], [394, 379], [379, 364],\n  [277, 343], [343, 437], [437, 277], [443, 444], [444, 283], [283, 443],\n  [275, 440], [440, 363], [363, 275], [431, 262], [262, 369], [369, 431],\n  [297, 338], [338, 337], [337, 297], [273, 375], [375, 321], [321, 273],\n  [450, 451], [451, 349], [349, 450], [446, 342], [342, 467], [467, 446],\n  [293, 334], [334, 282], [282, 293], [458, 461], [461, 462], [462, 458],\n  [276, 353], [353, 383], [383, 276], [308, 324], [324, 325], [325, 308],\n  [276, 300], [300, 293], [293, 276], [372, 345], [345, 447], [447, 372],\n  [352, 345], [345, 340], [340, 352], [274, 1], [1, 19], [19, 274],\n  [456, 248], [248, 281], [281, 456], [436, 427], [427, 425], [425, 436],\n  [381, 256], [256, 252], [252, 381], [269, 391], [391, 393], [393, 269],\n  [200, 199], [199, 428], [428, 200], [266, 330], [330, 329], [329, 266],\n  [287, 273], [273, 422], [422, 287], [250, 462], [462, 328], [328, 250],\n  [258, 286], [286, 384], [384, 258], [265, 353], [353, 342], [342, 265],\n  [387, 259], [259, 257], [257, 387], [424, 431], [431, 430], [430, 424],\n  [342, 353], [353, 276], [276, 342], [273, 335], [335, 424], [424, 273],\n  [292, 325], [325, 307], [307, 292], [366, 447], [447, 345], [345, 366],\n  [271, 303], [303, 302], [302, 271], [423, 266], [266, 371], [371, 423],\n  [294, 455], [455, 460], [460, 294], [279, 278], [278, 294], [294, 279],\n  [271, 272], [272, 304], [304, 271], [432, 434], [434, 427], [427, 432],\n  [272, 407], [407, 408], [408, 272], [394, 430], [430, 431], [431, 394],\n  [395, 369], [369, 400], [400, 395], [334, 333], [333, 299], [299, 334],\n  [351, 417], [417, 168], [168, 351], [352, 280], [280, 411], [411, 352],\n  [325, 319], [319, 320], [320, 325], [295, 296], [296, 336], [336, 295],\n  [319, 403], [403, 404], [404, 319], [330, 348], [348, 349], [349, 330],\n  [293, 298], [298, 333], [333, 293], [323, 454], [454, 447], [447, 323],\n  [15, 16], [16, 315], [315, 15], [358, 429], [429, 279], [279, 358],\n  [14, 15], [15, 316], [316, 14], [285, 336], [336, 9], [9, 285],\n  [329, 349], [349, 350], [350, 329], [374, 380], [380, 252], [252, 374],\n  [318, 402], [402, 403], [403, 318], [6, 197], [197, 419], [419, 6],\n  [318, 319], [319, 325], [325, 318], [367, 364], [364, 365], [365, 367],\n  [435, 367], [367, 397], [397, 435], [344, 438], [438, 439], [439, 344],\n  [272, 271], [271, 311], [311, 272], [195, 5], [5, 281], [281, 195],\n  [273, 287], [287, 291], [291, 273], [396, 428], [428, 199], [199, 396],\n  [311, 271], [271, 268], [268, 311], [283, 444], [444, 445], [445, 283],\n  [373, 254], [254, 339], [339, 373], [282, 334], [334, 296], [296, 282],\n  [449, 347], [347, 346], [346, 449], [264, 447], [447, 454], [454, 264],\n  [336, 296], [296, 299], [299, 336], [338, 10], [10, 151], [151, 338],\n  [278, 439], [439, 455], [455, 278], [292, 407], [407, 415], [415, 292],\n  [358, 371], [371, 355], [355, 358], [340, 345], [345, 372], [372, 340],\n  [346, 347], [347, 280], [280, 346], [442, 443], [443, 282], [282, 442],\n  [19, 94], [94, 370], [370, 19], [441, 442], [442, 295], [295, 441],\n  [248, 419], [419, 197], [197, 248], [263, 255], [255, 359], [359, 263],\n  [440, 275], [275, 274], [274, 440], [300, 383], [383, 368], [368, 300],\n  [351, 412], [412, 465], [465, 351], [263, 467], [467, 466], [466, 263],\n  [301, 368], [368, 389], [389, 301], [395, 378], [378, 379], [379, 395],\n  [412, 351], [351, 419], [419, 412], [436, 426], [426, 322], [322, 436],\n  [2, 164], [164, 393], [393, 2], [370, 462], [462, 461], [461, 370],\n  [164, 0], [0, 267], [267, 164], [302, 11], [11, 12], [12, 302],\n  [268, 12], [12, 13], [13, 268], [293, 300], [300, 301], [301, 293],\n  [446, 261], [261, 340], [340, 446], [330, 266], [266, 425], [425, 330],\n  [426, 423], [423, 391], [391, 426], [429, 355], [355, 437], [437, 429],\n  [391, 327], [327, 326], [326, 391], [440, 457], [457, 438], [438, 440],\n  [341, 382], [382, 362], [362, 341], [459, 457], [457, 461], [461, 459],\n  [434, 430], [430, 394], [394, 434], [414, 463], [463, 362], [362, 414],\n  [396, 369], [369, 262], [262, 396], [354, 461], [461, 457], [457, 354],\n  [316, 403], [403, 402], [402, 316], [315, 404], [404, 403], [403, 315],\n  [314, 405], [405, 404], [404, 314], [313, 406], [406, 405], [405, 313],\n  [421, 418], [418, 406], [406, 421], [366, 401], [401, 361], [361, 366],\n  [306, 408], [408, 407], [407, 306], [291, 409], [409, 408], [408, 291],\n  [287, 410], [410, 409], [409, 287], [432, 436], [436, 410], [410, 432],\n  [434, 416], [416, 411], [411, 434], [264, 368], [368, 383], [383, 264],\n  [309, 438], [438, 457], [457, 309], [352, 376], [376, 401], [401, 352],\n  [274, 275], [275, 4], [4, 274], [421, 428], [428, 262], [262, 421],\n  [294, 327], [327, 358], [358, 294], [433, 416], [416, 367], [367, 433],\n  [289, 455], [455, 439], [439, 289], [462, 370], [370, 326], [326, 462],\n  [2, 326], [326, 370], [370, 2], [305, 460], [460, 455], [455, 305],\n  [254, 449], [449, 448], [448, 254], [255, 261], [261, 446], [446, 255],\n  [253, 450], [450, 449], [449, 253], [252, 451], [451, 450], [450, 252],\n  [256, 452], [452, 451], [451, 256], [341, 453], [453, 452], [452, 341],\n  [413, 464], [464, 463], [463, 413], [441, 413], [413, 414], [414, 441],\n  [258, 442], [442, 441], [441, 258], [257, 443], [443, 442], [442, 257],\n  [259, 444], [444, 443], [443, 259], [260, 445], [445, 444], [444, 260],\n  [467, 342], [342, 445], [445, 467], [459, 458], [458, 250], [250, 459],\n  [289, 392], [392, 290], [290, 289], [290, 328], [328, 460], [460, 290],\n  [376, 433], [433, 435], [435, 376], [250, 290], [290, 392], [392, 250],\n  [411, 416], [416, 433], [433, 411], [341, 463], [463, 464], [464, 341],\n  [453, 464], [464, 465], [465, 453], [357, 465], [465, 412], [412, 357],\n  [343, 412], [412, 399], [399, 343], [360, 363], [363, 440], [440, 360],\n  [437, 399], [399, 456], [456, 437], [420, 456], [456, 363], [363, 420],\n  [401, 435], [435, 288], [288, 401], [372, 383], [383, 353], [353, 372],\n  [339, 255], [255, 249], [249, 339], [448, 261], [261, 255], [255, 448],\n  [133, 243], [243, 190], [190, 133], [133, 155], [155, 112], [112, 133],\n  [33, 246], [246, 247], [247, 33], [33, 130], [130, 25], [25, 33],\n  [398, 384], [384, 286], [286, 398], [362, 398], [398, 414], [414, 362],\n  [362, 463], [463, 341], [341, 362], [263, 359], [359, 467], [467, 263],\n  [263, 249], [249, 255], [255, 263], [466, 467], [467, 260], [260, 466],\n  [75, 60], [60, 166], [166, 75], [238, 239], [239, 79], [79, 238],\n  [162, 127], [127, 139], [139, 162], [72, 11], [11, 37], [37, 72],\n  [121, 232], [232, 120], [120, 121], [73, 72], [72, 39], [39, 73],\n  [114, 128], [128, 47], [47, 114], [233, 232], [232, 128], [128, 233],\n  [103, 104], [104, 67], [67, 103], [152, 175], [175, 148], [148, 152],\n  [119, 118], [118, 101], [101, 119], [74, 73], [73, 40], [40, 74],\n  [107, 9], [9, 108], [108, 107], [49, 48], [48, 131], [131, 49],\n  [32, 194], [194, 211], [211, 32], [184, 74], [74, 185], [185, 184],\n  [191, 80], [80, 183], [183, 191], [185, 40], [40, 186], [186, 185],\n  [119, 230], [230, 118], [118, 119], [210, 202], [202, 214], [214, 210],\n  [84, 83], [83, 17], [17, 84], [77, 76], [76, 146], [146, 77],\n  [161, 160], [160, 30], [30, 161], [190, 56], [56, 173], [173, 190],\n  [182, 106], [106, 194], [194, 182], [138, 135], [135, 192], [192, 138],\n  [129, 203], [203, 98], [98, 129], [54, 21], [21, 68], [68, 54],\n  [5, 51], [51, 4], [4, 5], [145, 144], [144, 23], [23, 145],\n  [90, 77], [77, 91], [91, 90], [207, 205], [205, 187], [187, 207],\n  [83, 201], [201, 18], [18, 83], [181, 91], [91, 182], [182, 181],\n  [180, 90], [90, 181], [181, 180], [16, 85], [85, 17], [17, 16],\n  [205, 206], [206, 36], [36, 205], [176, 148], [148, 140], [140, 176],\n  [165, 92], [92, 39], [39, 165], [245, 193], [193, 244], [244, 245],\n  [27, 159], [159, 28], [28, 27], [30, 247], [247, 161], [161, 30],\n  [174, 236], [236, 196], [196, 174], [103, 54], [54, 104], [104, 103],\n  [55, 193], [193, 8], [8, 55], [111, 117], [117, 31], [31, 111],\n  [221, 189], [189, 55], [55, 221], [240, 98], [98, 99], [99, 240],\n  [142, 126], [126, 100], [100, 142], [219, 166], [166, 218], [218, 219],\n  [112, 155], [155, 26], [26, 112], [198, 209], [209, 131], [131, 198],\n  [169, 135], [135, 150], [150, 169], [114, 47], [47, 217], [217, 114],\n  [224, 223], [223, 53], [53, 224], [220, 45], [45, 134], [134, 220],\n  [32, 211], [211, 140], [140, 32], [109, 67], [67, 108], [108, 109],\n  [146, 43], [43, 91], [91, 146], [231, 230], [230, 120], [120, 231],\n  [113, 226], [226, 247], [247, 113], [105, 63], [63, 52], [52, 105],\n  [241, 238], [238, 242], [242, 241], [124, 46], [46, 156], [156, 124],\n  [95, 78], [78, 96], [96, 95], [70, 46], [46, 63], [63, 70],\n  [116, 143], [143, 227], [227, 116], [116, 123], [123, 111], [111, 116],\n  [1, 44], [44, 19], [19, 1], [3, 236], [236, 51], [51, 3],\n  [207, 216], [216, 205], [205, 207], [26, 154], [154, 22], [22, 26],\n  [165, 39], [39, 167], [167, 165], [199, 200], [200, 208], [208, 199],\n  [101, 36], [36, 100], [100, 101], [43, 57], [57, 202], [202, 43],\n  [242, 20], [20, 99], [99, 242], [56, 28], [28, 157], [157, 56],\n  [124, 35], [35, 113], [113, 124], [29, 160], [160, 27], [27, 29],\n  [211, 204], [204, 210], [210, 211], [124, 113], [113, 46], [46, 124],\n  [106, 43], [43, 204], [204, 106], [96, 62], [62, 77], [77, 96],\n  [227, 137], [137, 116], [116, 227], [73, 41], [41, 72], [72, 73],\n  [36, 203], [203, 142], [142, 36], [235, 64], [64, 240], [240, 235],\n  [48, 49], [49, 64], [64, 48], [42, 41], [41, 74], [74, 42],\n  [214, 212], [212, 207], [207, 214], [183, 42], [42, 184], [184, 183],\n  [210, 169], [169, 211], [211, 210], [140, 170], [170, 176], [176, 140],\n  [104, 105], [105, 69], [69, 104], [193, 122], [122, 168], [168, 193],\n  [50, 123], [123, 187], [187, 50], [89, 96], [96, 90], [90, 89],\n  [66, 65], [65, 107], [107, 66], [179, 89], [89, 180], [180, 179],\n  [119, 101], [101, 120], [120, 119], [68, 63], [63, 104], [104, 68],\n  [234, 93], [93, 227], [227, 234], [16, 15], [15, 85], [85, 16],\n  [209, 129], [129, 49], [49, 209], [15, 14], [14, 86], [86, 15],\n  [107, 55], [55, 9], [9, 107], [120, 100], [100, 121], [121, 120],\n  [153, 145], [145, 22], [22, 153], [178, 88], [88, 179], [179, 178],\n  [197, 6], [6, 196], [196, 197], [89, 88], [88, 96], [96, 89],\n  [135, 138], [138, 136], [136, 135], [138, 215], [215, 172], [172, 138],\n  [218, 115], [115, 219], [219, 218], [41, 42], [42, 81], [81, 41],\n  [5, 195], [195, 51], [51, 5], [57, 43], [43, 61], [61, 57],\n  [208, 171], [171, 199], [199, 208], [41, 81], [81, 38], [38, 41],\n  [224, 53], [53, 225], [225, 224], [24, 144], [144, 110], [110, 24],\n  [105, 52], [52, 66], [66, 105], [118, 229], [229, 117], [117, 118],\n  [227, 34], [34, 234], [234, 227], [66, 107], [107, 69], [69, 66],\n  [10, 109], [109, 151], [151, 10], [219, 48], [48, 235], [235, 219],\n  [183, 62], [62, 191], [191, 183], [142, 129], [129, 126], [126, 142],\n  [116, 111], [111, 143], [143, 116], [118, 117], [117, 50], [50, 118],\n  [223, 222], [222, 52], [52, 223], [94, 19], [19, 141], [141, 94],\n  [222, 221], [221, 65], [65, 222], [196, 3], [3, 197], [197, 196],\n  [45, 220], [220, 44], [44, 45], [156, 70], [70, 139], [139, 156],\n  [188, 122], [122, 245], [245, 188], [139, 71], [71, 162], [162, 139],\n  [149, 170], [170, 150], [150, 149], [122, 188], [188, 196], [196, 122],\n  [206, 216], [216, 92], [92, 206], [164, 2], [2, 167], [167, 164],\n  [242, 141], [141, 241], [241, 242], [0, 164], [164, 37], [37, 0],\n  [11, 72], [72, 12], [12, 11], [12, 38], [38, 13], [13, 12],\n  [70, 63], [63, 71], [71, 70], [31, 226], [226, 111], [111, 31],\n  [36, 101], [101, 205], [205, 36], [203, 206], [206, 165], [165, 203],\n  [126, 209], [209, 217], [217, 126], [98, 165], [165, 97], [97, 98],\n  [237, 220], [220, 218], [218, 237], [237, 239], [239, 241], [241, 237],\n  [210, 214], [214, 169], [169, 210], [140, 171], [171, 32], [32, 140],\n  [241, 125], [125, 237], [237, 241], [179, 86], [86, 178], [178, 179],\n  [180, 85], [85, 179], [179, 180], [181, 84], [84, 180], [180, 181],\n  [182, 83], [83, 181], [181, 182], [194, 201], [201, 182], [182, 194],\n  [177, 137], [137, 132], [132, 177], [184, 76], [76, 183], [183, 184],\n  [185, 61], [61, 184], [184, 185], [186, 57], [57, 185], [185, 186],\n  [216, 212], [212, 186], [186, 216], [192, 214], [214, 187], [187, 192],\n  [139, 34], [34, 156], [156, 139], [218, 79], [79, 237], [237, 218],\n  [147, 123], [123, 177], [177, 147], [45, 44], [44, 4], [4, 45],\n  [208, 201], [201, 32], [32, 208], [98, 64], [64, 129], [129, 98],\n  [192, 213], [213, 138], [138, 192], [235, 59], [59, 219], [219, 235],\n  [141, 242], [242, 97], [97, 141], [97, 2], [2, 141], [141, 97],\n  [240, 75], [75, 235], [235, 240], [229, 24], [24, 228], [228, 229],\n  [31, 25], [25, 226], [226, 31], [230, 23], [23, 229], [229, 230],\n  [231, 22], [22, 230], [230, 231], [232, 26], [26, 231], [231, 232],\n  [233, 112], [112, 232], [232, 233], [244, 189], [189, 243], [243, 244],\n  [189, 221], [221, 190], [190, 189], [222, 28], [28, 221], [221, 222],\n  [223, 27], [27, 222], [222, 223], [224, 29], [29, 223], [223, 224],\n  [225, 30], [30, 224], [224, 225], [113, 247], [247, 225], [225, 113],\n  [99, 60], [60, 240], [240, 99], [213, 147], [147, 215], [215, 213],\n  [60, 20], [20, 166], [166, 60], [192, 187], [187, 213], [213, 192],\n  [243, 112], [112, 244], [244, 243], [244, 233], [233, 245], [245, 244],\n  [245, 128], [128, 188], [188, 245], [188, 114], [114, 174], [174, 188],\n  [134, 131], [131, 220], [220, 134], [174, 217], [217, 236], [236, 174],\n  [236, 198], [198, 134], [134, 236], [215, 177], [177, 58], [58, 215],\n  [156, 143], [143, 124], [124, 156], [25, 110], [110, 7], [7, 25],\n  [31, 228], [228, 25], [25, 31], [264, 356], [356, 368], [368, 264],\n  [0, 11], [11, 267], [267, 0], [451, 452], [452, 349], [349, 451],\n  [267, 302], [302, 269], [269, 267], [350, 357], [357, 277], [277, 350],\n  [350, 452], [452, 357], [357, 350], [299, 333], [333, 297], [297, 299],\n  [396, 175], [175, 377], [377, 396], [280, 347], [347, 330], [330, 280],\n  [269, 303], [303, 270], [270, 269], [151, 9], [9, 337], [337, 151],\n  [344, 278], [278, 360], [360, 344], [424, 418], [418, 431], [431, 424],\n  [270, 304], [304, 409], [409, 270], [272, 310], [310, 407], [407, 272],\n  [322, 270], [270, 410], [410, 322], [449, 450], [450, 347], [347, 449],\n  [432, 422], [422, 434], [434, 432], [18, 313], [313, 17], [17, 18],\n  [291, 306], [306, 375], [375, 291], [259, 387], [387, 260], [260, 259],\n  [424, 335], [335, 418], [418, 424], [434, 364], [364, 416], [416, 434],\n  [391, 423], [423, 327], [327, 391], [301, 251], [251, 298], [298, 301],\n  [275, 281], [281, 4], [4, 275], [254, 373], [373, 253], [253, 254],\n  [375, 307], [307, 321], [321, 375], [280, 425], [425, 411], [411, 280],\n  [200, 421], [421, 18], [18, 200], [335, 321], [321, 406], [406, 335],\n  [321, 320], [320, 405], [405, 321], [314, 315], [315, 17], [17, 314],\n  [423, 426], [426, 266], [266, 423], [396, 377], [377, 369], [369, 396],\n  [270, 322], [322, 269], [269, 270], [413, 417], [417, 464], [464, 413],\n  [385, 386], [386, 258], [258, 385], [248, 456], [456, 419], [419, 248],\n  [298, 284], [284, 333], [333, 298], [168, 417], [417, 8], [8, 168],\n  [448, 346], [346, 261], [261, 448], [417, 413], [413, 285], [285, 417],\n  [326, 327], [327, 328], [328, 326], [277, 355], [355, 329], [329, 277],\n  [309, 392], [392, 438], [438, 309], [381, 382], [382, 256], [256, 381],\n  [279, 429], [429, 360], [360, 279], [365, 364], [364, 379], [379, 365],\n  [355, 277], [277, 437], [437, 355], [282, 443], [443, 283], [283, 282],\n  [281, 275], [275, 363], [363, 281], [395, 431], [431, 369], [369, 395],\n  [299, 297], [297, 337], [337, 299], [335, 273], [273, 321], [321, 335],\n  [348, 450], [450, 349], [349, 348], [359, 446], [446, 467], [467, 359],\n  [283, 293], [293, 282], [282, 283], [250, 458], [458, 462], [462, 250],\n  [300, 276], [276, 383], [383, 300], [292, 308], [308, 325], [325, 292],\n  [283, 276], [276, 293], [293, 283], [264, 372], [372, 447], [447, 264],\n  [346, 352], [352, 340], [340, 346], [354, 274], [274, 19], [19, 354],\n  [363, 456], [456, 281], [281, 363], [426, 436], [436, 425], [425, 426],\n  [380, 381], [381, 252], [252, 380], [267, 269], [269, 393], [393, 267],\n  [421, 200], [200, 428], [428, 421], [371, 266], [266, 329], [329, 371],\n  [432, 287], [287, 422], [422, 432], [290, 250], [250, 328], [328, 290],\n  [385, 258], [258, 384], [384, 385], [446, 265], [265, 342], [342, 446],\n  [386, 387], [387, 257], [257, 386], [422, 424], [424, 430], [430, 422],\n  [445, 342], [342, 276], [276, 445], [422, 273], [273, 424], [424, 422],\n  [306, 292], [292, 307], [307, 306], [352, 366], [366, 345], [345, 352],\n  [268, 271], [271, 302], [302, 268], [358, 423], [423, 371], [371, 358],\n  [327, 294], [294, 460], [460, 327], [331, 279], [279, 294], [294, 331],\n  [303, 271], [271, 304], [304, 303], [436, 432], [432, 427], [427, 436],\n  [304, 272], [272, 408], [408, 304], [395, 394], [394, 431], [431, 395],\n  [378, 395], [395, 400], [400, 378], [296, 334], [334, 299], [299, 296],\n  [6, 351], [351, 168], [168, 6], [376, 352], [352, 411], [411, 376],\n  [307, 325], [325, 320], [320, 307], [285, 295], [295, 336], [336, 285],\n  [320, 319], [319, 404], [404, 320], [329, 330], [330, 349], [349, 329],\n  [334, 293], [293, 333], [333, 334], [366, 323], [323, 447], [447, 366],\n  [316, 15], [15, 315], [315, 316], [331, 358], [358, 279], [279, 331],\n  [317, 14], [14, 316], [316, 317], [8, 285], [285, 9], [9, 8],\n  [277, 329], [329, 350], [350, 277], [253, 374], [374, 252], [252, 253],\n  [319, 318], [318, 403], [403, 319], [351, 6], [6, 419], [419, 351],\n  [324, 318], [318, 325], [325, 324], [397, 367], [367, 365], [365, 397],\n  [288, 435], [435, 397], [397, 288], [278, 344], [344, 439], [439, 278],\n  [310, 272], [272, 311], [311, 310], [248, 195], [195, 281], [281, 248],\n  [375, 273], [273, 291], [291, 375], [175, 396], [396, 199], [199, 175],\n  [312, 311], [311, 268], [268, 312], [276, 283], [283, 445], [445, 276],\n  [390, 373], [373, 339], [339, 390], [295, 282], [282, 296], [296, 295],\n  [448, 449], [449, 346], [346, 448], [356, 264], [264, 454], [454, 356],\n  [337, 336], [336, 299], [299, 337], [337, 338], [338, 151], [151, 337],\n  [294, 278], [278, 455], [455, 294], [308, 292], [292, 415], [415, 308],\n  [429, 358], [358, 355], [355, 429], [265, 340], [340, 372], [372, 265],\n  [352, 346], [346, 280], [280, 352], [295, 442], [442, 282], [282, 295],\n  [354, 19], [19, 370], [370, 354], [285, 441], [441, 295], [295, 285],\n  [195, 248], [248, 197], [197, 195], [457, 440], [440, 274], [274, 457],\n  [301, 300], [300, 368], [368, 301], [417, 351], [351, 465], [465, 417],\n  [251, 301], [301, 389], [389, 251], [394, 395], [395, 379], [379, 394],\n  [399, 412], [412, 419], [419, 399], [410, 436], [436, 322], [322, 410],\n  [326, 2], [2, 393], [393, 326], [354, 370], [370, 461], [461, 354],\n  [393, 164], [164, 267], [267, 393], [268, 302], [302, 12], [12, 268],\n  [312, 268], [268, 13], [13, 312], [298, 293], [293, 301], [301, 298],\n  [265, 446], [446, 340], [340, 265], [280, 330], [330, 425], [425, 280],\n  [322, 426], [426, 391], [391, 322], [420, 429], [429, 437], [437, 420],\n  [393, 391], [391, 326], [326, 393], [344, 440], [440, 438], [438, 344],\n  [458, 459], [459, 461], [461, 458], [364, 434], [434, 394], [394, 364],\n  [428, 396], [396, 262], [262, 428], [274, 354], [354, 457], [457, 274],\n  [317, 316], [316, 402], [402, 317], [316, 315], [315, 403], [403, 316],\n  [315, 314], [314, 404], [404, 315], [314, 313], [313, 405], [405, 314],\n  [313, 421], [421, 406], [406, 313], [323, 366], [366, 361], [361, 323],\n  [292, 306], [306, 407], [407, 292], [306, 291], [291, 408], [408, 306],\n  [291, 287], [287, 409], [409, 291], [287, 432], [432, 410], [410, 287],\n  [427, 434], [434, 411], [411, 427], [372, 264], [264, 383], [383, 372],\n  [459, 309], [309, 457], [457, 459], [366, 352], [352, 401], [401, 366],\n  [1, 274], [274, 4], [4, 1], [418, 421], [421, 262], [262, 418],\n  [331, 294], [294, 358], [358, 331], [435, 433], [433, 367], [367, 435],\n  [392, 289], [289, 439], [439, 392], [328, 462], [462, 326], [326, 328],\n  [94, 2], [2, 370], [370, 94], [289, 305], [305, 455], [455, 289],\n  [339, 254], [254, 448], [448, 339], [359, 255], [255, 446], [446, 359],\n  [254, 253], [253, 449], [449, 254], [253, 252], [252, 450], [450, 253],\n  [252, 256], [256, 451], [451, 252], [256, 341], [341, 452], [452, 256],\n  [414, 413], [413, 463], [463, 414], [286, 441], [441, 414], [414, 286],\n  [286, 258], [258, 441], [441, 286], [258, 257], [257, 442], [442, 258],\n  [257, 259], [259, 443], [443, 257], [259, 260], [260, 444], [444, 259],\n  [260, 467], [467, 445], [445, 260], [309, 459], [459, 250], [250, 309],\n  [305, 289], [289, 290], [290, 305], [305, 290], [290, 460], [460, 305],\n  [401, 376], [376, 435], [435, 401], [309, 250], [250, 392], [392, 309],\n  [376, 411], [411, 433], [433, 376], [453, 341], [341, 464], [464, 453],\n  [357, 453], [453, 465], [465, 357], [343, 357], [357, 412], [412, 343],\n  [437, 343], [343, 399], [399, 437], [344, 360], [360, 440], [440, 344],\n  [420, 437], [437, 456], [456, 420], [360, 420], [420, 363], [363, 360],\n  [361, 401], [401, 288], [288, 361], [265, 372], [372, 353], [353, 265],\n  [390, 339], [339, 249], [249, 390], [339, 448], [448, 255], [255, 339],\n];\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n * See `facemesh.ts` for entry point\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as coords from './facemeshcoords';\nimport { constants } from '../tfjs/constants';\nimport type { Box, Point } from '../result';\nimport { env } from '../util/env';\n\nexport const createBox = (startEndTensor) => ({ startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]), endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]) });\n\nexport const disposeBox = (t) => tf.dispose([t.startPoint, t.endPoint]);\n\nexport const getBoxSize = (box): [number, number] => [Math.abs(box.endPoint[0] - box.startPoint[0]), Math.abs(box.endPoint[1] - box.startPoint[1])];\n\nexport const getBoxCenter = (box): [number, number, number] => [box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2, box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2, 1];\n\nexport const clampBox = (box, input): Box => (box ? [\n  Math.trunc(Math.max(0, box.startPoint[0])),\n  Math.trunc(Math.max(0, box.startPoint[1])),\n  Math.trunc(Math.min((input.shape[2] || 0), box.endPoint[0]) - Math.max(0, box.startPoint[0])),\n  Math.trunc(Math.min((input.shape[1] || 0), box.endPoint[1]) - Math.max(0, box.startPoint[1])),\n] : [0, 0, 0, 0]);\n\nexport const getRawBox = (box, input): Box => (box ? [\n  box.startPoint[0] / (input.shape[2] || 0),\n  box.startPoint[1] / (input.shape[1] || 0),\n  (box.endPoint[0] - box.startPoint[0]) / (input.shape[2] || 0),\n  (box.endPoint[1] - box.startPoint[1]) / (input.shape[1] || 0),\n] : [0, 0, 0, 0]);\n\nexport const scaleBoxCoordinates = (box, factor) => {\n  const startPoint: Point = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint: Point = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks, confidence: box.confidence };\n};\n\nexport const cutAndResize = (box, image, cropSize) => {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const cutBox = [box.startPoint[1] / h, box.startPoint[0] / w, box.endPoint[1] / h, box.endPoint[0] / w];\n  const crop = tf.image.cropAndResize(image, [cutBox], [0], cropSize);\n  const norm = tf.div(crop, constants.tf255);\n  tf.dispose(crop);\n  return norm;\n};\n\nexport const enlargeBox = (box, factor) => {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const halfSize: [number, number] = [factor * size[0] / 2, factor * size[1] / 2];\n  return { startPoint: [center[0] - halfSize[0], center[1] - halfSize[1]] as Point, endPoint: [center[0] + halfSize[0], center[1] + halfSize[1]] as Point, landmarks: box.landmarks, confidence: box.confidence };\n};\n\nexport const squarifyBox = (box) => {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const halfSize = Math.max(...size) / 2;\n  return { startPoint: [Math.round(centers[0] - halfSize), Math.round(centers[1] - halfSize)] as Point, endPoint: [Math.round(centers[0] + halfSize), Math.round(centers[1] + halfSize)] as Point, landmarks: box.landmarks, confidence: box.confidence };\n};\n\nexport const calculateLandmarksBoundingBox = (landmarks) => {\n  const x = landmarks.map((d) => d[0]);\n  const y = landmarks.map((d) => d[1]);\n  return { startPoint: [Math.min(...x), Math.min(...y)] as Point, endPoint: [Math.max(...x), Math.max(...y)] as Point, landmarks };\n};\n\nexport const fixedRotationMatrix = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n\nexport const normalizeRadians = (angle) => angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n\nexport const computeRotation = (point1, point2) => normalizeRadians(Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]));\n\nexport const radToDegrees = (rad) => rad * 180 / Math.PI;\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport const dot = (v1: number[], v2: number[]) => {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) product += v1[i] * v2[i];\n  return product;\n};\n\nexport const getColumnFrom2DArr = (arr, columnIndex) => {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) column.push(arr[i][columnIndex]);\n  return column;\n};\n\nexport const multiplyTransformMatrices = (mat1, mat2) => {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n  }\n  return product;\n};\n\nexport const buildRotationMatrix = (rotation, center) => {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n};\n\nexport const invertTransformMatrix = (matrix) => {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [-dot(rotationComponent[0], translationComponent), -dot(rotationComponent[1], translationComponent)];\n  return [rotationComponent[0].concat(invertedTranslation[0]), rotationComponent[1].concat(invertedTranslation[1]), [0, 0, 1]];\n};\n\nexport const rotatePoint = (homogeneousCoordinate, rotationMatrix) => [dot(homogeneousCoordinate, rotationMatrix[0]), dot(homogeneousCoordinate, rotationMatrix[1])];\n\nexport const xyDistanceBetweenPoints = (a, b) => Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n\nexport function generateAnchors(inputSize) {\n  const spec = inputSize === 192\n    ? { strides: [4], anchors: [1] } // facemesh-detector\n    : { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] }; // blazeface\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) anchors.push([anchorX, anchorY]);\n      }\n    }\n  }\n  return anchors;\n}\n\nexport function transformRawCoords(coordsRaw, box, angle, rotationMatrix, inputSize) {\n  const boxSize = getBoxSize(box);\n  const coordsScaled = coordsRaw.map((coord) => ([ // scaled around zero-point\n    (boxSize[0] / inputSize) * (coord[0] - (inputSize / 2)),\n    (boxSize[1] / inputSize) * (coord[1] - (inputSize / 2)),\n    (coord[2] || 0),\n  ]));\n  const largeAngle = angle && (angle !== 0) && (Math.abs(angle) > 0.2);\n  const coordsRotationMatrix = largeAngle ? buildRotationMatrix(angle, [0, 0]) : fixedRotationMatrix;\n  const coordsRotated = largeAngle ? coordsScaled.map((coord) => ([...rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n  const inverseRotationMatrix = largeAngle ? invertTransformMatrix(rotationMatrix) : fixedRotationMatrix;\n  const boxCenter = getBoxCenter(box);\n  const offsets = [dot(boxCenter, inverseRotationMatrix[0]), dot(boxCenter, inverseRotationMatrix[1])];\n  return coordsRotated.map((coord) => ([\n    Math.trunc(coord[0] + offsets[0]),\n    Math.trunc(coord[1] + offsets[1]),\n    Math.trunc(coord[2] || 0),\n  ]));\n}\n\nexport function correctFaceRotation(rotate, box, input, inputSize) {\n  const symmetryLine = (box.landmarks.length >= coords.meshLandmarks.count)\n    ? coords.meshLandmarks.symmetryLine\n    : coords.blazeFaceLandmarks.symmetryLine;\n  let angle = 0; // default\n  let rotationMatrix = fixedRotationMatrix; // default\n  let face; // default\n\n  if (rotate && env.kernels.includes('rotatewithoffset')) { // rotateWithOffset is not defined for tfjs-node\n    angle = computeRotation(box.landmarks[symmetryLine[0]], box.landmarks[symmetryLine[1]]);\n    const largeAngle = angle && (angle !== 0) && (Math.abs(angle) > 0.2);\n    if (largeAngle) { // perform rotation only if angle is sufficiently high\n      const center: Point = getBoxCenter(box);\n      const centerRaw: Point = [center[0] / input.shape[2], center[1] / input.shape[1]];\n      const rotated = tf.image.rotateWithOffset(input, angle, 0, centerRaw);\n      rotationMatrix = buildRotationMatrix(-angle, center);\n      face = cutAndResize(box, rotated, [inputSize, inputSize]);\n      tf.dispose(rotated);\n    } else {\n      face = cutAndResize(box, input, [inputSize, inputSize]);\n    }\n  } else {\n    face = cutAndResize(box, input, [inputSize, inputSize]);\n  }\n  return [angle, rotationMatrix, face];\n}\n\nexport const findFaceCenter = (mesh) => {\n  const x = mesh.map((m) => m[0]);\n  const y = mesh.map((m) => m[1]);\n  // weighted center\n  /*\n  const sum = (arr: number[]) => arr.reduce((prev, curr) => prev + curr, 0);\n  return [sum(x) / mesh.length, sum(y) / mesh.length];\n  */\n  // absolute center\n  return [Math.min(...x) + (Math.max(...x) - Math.min(...x)) / 2, Math.min(...y) + (Math.max(...y) - Math.min(...y)) / 2];\n};\n\nexport const calculateFaceBox = (mesh, previousBox) => {\n  const center = findFaceCenter(mesh);\n  const boxSize = getBoxSize(previousBox);\n  const calculatedBox = {\n    startPoint: [center[0] - boxSize[0] / 2, center[1] - boxSize[1] / 2] as Point,\n    endPoint: [center[0] + boxSize[0] / 2, center[1] + boxSize[1] / 2] as Point,\n  };\n  return calculatedBox;\n};\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n * See `facemesh.ts` for entry point\n */\n\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as util from './facemeshutil';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport type { Config } from '../config';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport { env } from '../util/env';\nimport type { Point } from '../result';\n\nconst keypointsCount = 6;\nconst faceBoxScaleFactor = 1.4;\nlet model: GraphModel | null;\nlet anchors: Tensor | null = null;\nlet inputSize = 0;\nlet inputSizeT: Tensor | null = null;\n\ntype DetectBox = { startPoint: Point, endPoint: Point, landmarks: Array<Point>, confidence: number };\n\nexport const size = () => inputSize;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.detector?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  inputSizeT = tf.scalar(inputSize, 'int32') as Tensor;\n  anchors = tf.tensor2d(util.generateAnchors(inputSize)) as Tensor;\n  return model;\n}\n\nfunction decodeBoxes(boxOutputs: Tensor) {\n  const t: Record<string, Tensor> = {};\n  t.boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  t.centers = tf.add(t.boxStarts, anchors);\n  t.boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  t.boxSizesNormalized = tf.div(t.boxSizes, inputSizeT);\n  t.centersNormalized = tf.div(t.centers, inputSizeT);\n  t.halfBoxSize = tf.div(t.boxSizesNormalized, constants.tf2);\n  t.starts = tf.sub(t.centersNormalized, t.halfBoxSize);\n  t.ends = tf.add(t.centersNormalized, t.halfBoxSize);\n  t.startNormalized = tf.mul(t.starts, inputSizeT);\n  t.endNormalized = tf.mul(t.ends, inputSizeT);\n  const boxes = tf.concat2d([t.startNormalized, t.endNormalized], 1);\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return boxes;\n}\n\nexport async function getBoxes(inputImage: Tensor, config: Config) {\n  // sanity check on input\n  if ((!inputImage) || (inputImage['isDisposedInternal']) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return [];\n  const t: Record<string, Tensor> = {};\n  t.resized = tf.image.resizeBilinear(inputImage, [inputSize, inputSize]);\n  t.div = tf.div(t.resized, constants.tf127);\n  t.normalized = tf.sub(t.div, constants.tf05);\n  const res = model?.execute(t.normalized) as Tensor[];\n  if (Array.isArray(res) && res.length > 2) { // pinto converted model?\n    const sorted = res.sort((a, b) => a.size - b.size);\n    t.concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n    t.concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n    t.concat = tf.concat([t.concat512, t.concat384], 1);\n    t.batch = tf.squeeze(t.concat, 0);\n  } else if (Array.isArray(res)) { // new facemesh-detection tfhub model\n    t.batch = tf.squeeze(res[0]);\n  } else { // original blazeface tfhub model\n    t.batch = tf.squeeze(res);\n  }\n  tf.dispose(res);\n  t.boxes = decodeBoxes(t.batch);\n  t.logits = tf.slice(t.batch, [0, 0], [-1, 1]);\n  t.sigmoid = tf.sigmoid(t.logits);\n  t.scores = tf.squeeze(t.sigmoid);\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.scores, (config.face.detector?.maxDetected || 0), (config.face.detector?.iouThreshold || 0), (config.face.detector?.minConfidence || 0));\n  const nms = await t.nms.array() as number[];\n  const boxes: Array<DetectBox> = [];\n  const scores = await t.scores.data();\n  for (let i = 0; i < nms.length; i++) {\n    const confidence = scores[nms[i]];\n    if (confidence > (config.face.detector?.minConfidence || 0)) {\n      const b: Record<string, Tensor> = {};\n      b.bbox = tf.slice(t.boxes, [nms[i], 0], [1, -1]);\n      b.slice = tf.slice(t.batch, [nms[i], keypointsCount - 1], [1, -1]);\n      b.squeeze = tf.squeeze(b.slice);\n      b.landmarks = tf.reshape(b.squeeze, [keypointsCount, -1]);\n      const points = await b.bbox.data();\n      const rawBox = {\n        startPoint: [points[0], points[1]] as Point,\n        endPoint: [points[2], points[3]] as Point,\n        landmarks: (await b.landmarks.array()) as Point[],\n        confidence,\n      };\n      const scaledBox = util.scaleBoxCoordinates(rawBox, [(inputImage.shape[2] || 0) / inputSize, (inputImage.shape[1] || 0) / inputSize]);\n      const enlargedBox = util.enlargeBox(scaledBox, config.face['scale'] || faceBoxScaleFactor);\n      const squaredBox = util.squarifyBox(enlargedBox);\n      boxes.push(squaredBox);\n      Object.keys(b).forEach((tensor) => tf.dispose(b[tensor]));\n    }\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return boxes;\n}\n", "/* eslint-disable no-multi-spaces */\n\nexport const kpt: Array<string> = [\n  'nose',            //  0\n  'leftEyeInside',   //  1\n  'leftEye',         //  2\n  'leftEyeOutside',  //  3\n  'rightEyeInside',  //  4\n  'rightEye',        //  5\n  'rightEyeOutside', //  6\n  'leftEar',         //  7\n  'rightEar',        //  8\n  'leftMouth',       //  9\n  'rightMouth',      // 10\n  'leftShoulder',    // 11\n  'rightShoulder',   // 12\n  'leftElbow',       // 13\n  'rightElbow',      // 14\n  'leftWrist',       // 15\n  'rightWrist',      // 16\n  'leftPinky',       // 17\n  'rightPinky',      // 18\n  'leftIndex',       // 19\n  'rightIndex',      // 20\n  'leftThumb',       // 21\n  'rightThumb',      // 22\n  'leftHip',         // 23\n  'rightHip',        // 24\n  'leftKnee',        // 25\n  'rightKnee',       // 26\n  'leftAnkle',       // 27\n  'rightAnkle',      // 28\n  'leftHeel',        // 29\n  'rightHeel',       // 30\n  'leftFoot',        // 31\n  'rightFoot',       // 32\n  'bodyCenter',      // 33\n  'bodyTop',         // 34\n  'leftPalm',        // 35 // z-coord not ok\n  'leftHand',        // 36 // similar to wrist but z-coord not ok\n  'rightPalm',       // 37 // z-coord not ok\n  'rightHand',       // 38 // similar to wrist but z-coord not ok\n];\n\nexport const connected: Record<string, string[]> = {\n  shoulders: ['leftShoulder', 'rightShoulder'],\n  hips: ['rightHip', 'leftHip'],\n  mouth: ['leftMouth', 'rightMouth'],\n  leftLegUpper: ['leftHip', 'leftKnee'],\n  leftLegLower: ['leftKnee', 'leftAnkle'],\n  leftFoot: ['leftAnkle', 'leftHeel', 'leftFoot'],\n  leftTorso: ['leftShoulder', 'leftHip'],\n  leftArmUpper: ['leftShoulder', 'leftElbow'],\n  leftArmLower: ['leftElbow', 'leftWrist'],\n  leftHand: ['leftWrist', 'leftPalm'],\n  leftHandPinky: ['leftPalm', 'leftPinky'],\n  leftHandIndex: ['leftPalm', 'leftIndex'],\n  leftHandThumb: ['leftPalm', 'leftThumb'],\n  leftEyeOutline: ['leftEyeInside', 'leftEyeOutside'],\n  rightLegUpper: ['rightHip', 'rightKnee'],\n  rightLegLower: ['rightKnee', 'rightAnkle'],\n  rightFoot: ['rightAnkle', 'rightHeel', 'rightFoot'],\n  rightTorso: ['rightShoulder', 'rightHip'],\n  rightArmUpper: ['rightShoulder', 'rightElbow'],\n  rightArmLower: ['rightElbow', 'rightWrist'],\n  rightHand: ['rightWrist', 'rightPalm'],\n  rightHandPinky: ['rightPalm', 'rightPinky'],\n  rightHandIndex: ['rightPalm', 'rightIndex'],\n  rightHandThumb: ['rightPalm', 'rightThumb'],\n  rightEyeOutline: ['rightEyeInside', 'rightEyeOutside'],\n};\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from '../tfjs/types';\nimport type { Box } from '../result';\nimport type { Config } from '../config';\n\ninterface DetectedBox { box: Box, boxRaw: Box, score: number }\n\nconst inputSize = 224;\nlet anchorTensor: { x, y };\nconst numLayers = 5;\nconst strides = [8, 16, 32, 32, 32];\n\nexport async function createAnchors() {\n  const anchors: Array<{ x: number, y: number }> = [];\n  let layerId = 0;\n  while (layerId < numLayers) {\n    let anchorCount = 0;\n    let lastSameStrideLayer = layerId;\n    while (lastSameStrideLayer < strides.length && strides[lastSameStrideLayer] === strides[layerId]) {\n      anchorCount += 2;\n      lastSameStrideLayer++;\n    }\n    const stride = strides[layerId];\n    const featureMapHeight = Math.ceil(inputSize / stride);\n    const featureMapWidth = Math.ceil(inputSize / stride);\n    for (let y = 0; y < featureMapHeight; ++y) {\n      for (let x = 0; x < featureMapWidth; ++x) {\n        for (let anchorId = 0; anchorId < anchorCount; ++anchorId) {\n          anchors.push({ x: (x + 0.5) / featureMapWidth, y: (y + 0.5) / featureMapHeight });\n        }\n      }\n    }\n    layerId = lastSameStrideLayer;\n  }\n  anchorTensor = { x: tf.tensor1d(anchors.map((a) => a.x)), y: tf.tensor1d(anchors.map((a) => a.y)) };\n}\n\nconst cropFactor = [5.0, 5.0];\nfunction decodeBoxes(boxesTensor, anchor): Tensor {\n  return tf.tidy(() => {\n    const split = tf.split(boxesTensor, 12, 1); // first 4 are box data [x,y,w,h] and 4 are keypoints data [x,y] for total of 12\n    let xCenter = tf.squeeze(split[0]);\n    let yCenter = tf.squeeze(split[1]);\n    let width = tf.squeeze(split[2]);\n    let height = tf.squeeze(split[3]);\n    xCenter = tf.add(tf.div(xCenter, inputSize), anchor.x);\n    yCenter = tf.add(tf.div(yCenter, inputSize), anchor.y);\n    width = tf.mul(tf.div(width, inputSize), cropFactor[0]);\n    height = tf.mul(tf.div(height, inputSize), cropFactor[1]);\n    const xMin = tf.sub(xCenter, tf.div(width, 2));\n    const yMin = tf.sub(yCenter, tf.div(height, 2));\n    const boxes = tf.stack([xMin, yMin, width, height], 1);\n    return boxes;\n  });\n}\n\nexport async function decode(boxesTensor: Tensor, logitsTensor: Tensor, config: Config, outputSize: [number, number]): Promise<DetectedBox[]> {\n  const t: Record<string, Tensor> = {};\n  t.boxes = decodeBoxes(boxesTensor, anchorTensor);\n  t.scores = tf.sigmoid(logitsTensor);\n  t.argmax = tf.argMax(t.scores);\n  const i = (await t.argmax.data())[0] as number;\n  const scores = await t.scores.data();\n  const detected: Array<{ box: Box, boxRaw: Box, score: number }> = [];\n  const minScore = (config.body['detector'] && config.body['detector']['minConfidence']) ? config.body['detector']['minConfidence'] : 0;\n  if (scores[i] >= minScore) {\n    const boxes = await t.boxes.array();\n    const boxRaw: Box = boxes[i];\n    const box: Box = [boxRaw[0] * outputSize[0], boxRaw[1] * outputSize[1], boxRaw[2] * outputSize[0], boxRaw[3] * outputSize[1]];\n    // console.log(box);\n    detected.push({ box, boxRaw, score: scores[i] });\n  }\n  /*\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.scores, 1, config.body.detector?.minConfidence || 0.1, config.body.detector?.iouThreshold || 0.1);\n  const boxes = t.boxes.arraySync();\n  const scores = t.scores.dataSync();\n  const nms = t.nms.dataSync();\n  const detected: Array<DetectedBox> = [];\n  for (const i of Array.from(nms)) {\n    const boxRaw: Box = boxes[i];\n    const box: Box = [boxRaw[0] * outputSize[0], boxRaw[0] * outputSize[1], boxRaw[3] * outputSize[0], boxRaw[2] * outputSize[1]];\n    detected.push({ box, boxRaw, score: scores[i] });\n  }\n  */\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return detected;\n}\n", "import type { Point, Box } from '../result';\n\nexport function calc(keypoints: Array<Point>, outputSize: [number, number] = [1, 1]) {\n  const coords = [keypoints.map((pt) => pt[0]), keypoints.map((pt) => pt[1])]; // all x/y coords\n  const min = [Math.min(...coords[0]), Math.min(...coords[1])];\n  const max = [Math.max(...coords[0]), Math.max(...coords[1])];\n  const box: Box = [min[0], min[1], max[0] - min[0], max[1] - min[1]];\n  const boxRaw: Box = [box[0] / outputSize[0], box[1] / outputSize[1], box[2] / outputSize[0], box[3] / outputSize[1]];\n  return { box, boxRaw };\n}\n\nexport function square(keypoints: Array<Point>, outputSize: [number, number] = [1, 1]) {\n  const coords = [keypoints.map((pt) => pt[0]), keypoints.map((pt) => pt[1])]; // all x/y coords\n  const min = [Math.min(...coords[0]), Math.min(...coords[1])];\n  const max = [Math.max(...coords[0]), Math.max(...coords[1])];\n  const center = [(min[0] + max[0]) / 2, (min[1] + max[1]) / 2]; // find center x and y coord of all fingers\n  const dist = Math.max(center[0] - min[0], center[1] - min[1], -center[0] + max[0], -center[1] + max[1]); // largest distance from center in any direction\n  const box: Box = [Math.trunc(center[0] - dist), Math.trunc(center[1] - dist), Math.trunc(2 * dist), Math.trunc(2 * dist)];\n  const boxRaw: Box = [box[0] / outputSize[0], box[1] / outputSize[1], box[2] / outputSize[0], box[3] / outputSize[1]];\n  return { box, boxRaw };\n}\n\nexport function scale(box: Box, scaleFact: number) {\n  const dist = [box[2] * scaleFact, box[3] * scaleFact];\n  const newBox: Box = [\n    box[0] - (dist[0] - box[2]) / 2,\n    box[1] - (dist[1] - box[3]) / 2,\n    dist[0],\n    dist[1],\n  ];\n  return newBox;\n}\n\nexport function crop(box: Box) { // [y1, x1, y2, x2] clamped to 0..1\n  const yxBox: Box = [Math.max(0, box[1]), Math.max(0, box[0]), Math.min(1, box[3] + box[1]), Math.min(1, box[2] + box[0])];\n  return yxBox;\n}\n", "/**\n * BlazePose model implementation\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport { log, now } from '../util/util';\nimport type { BodyKeypoint, BodyResult, BodyLandmark, Box, Point, BodyAnnotation } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport * as coords from './blazeposecoords';\nimport * as detect from './blazeposedetector';\nimport * as box from '../util/box';\n\nconst env = { initial: true };\n// const models: [GraphModel | null, GraphModel | null] = [null, null];\nconst models: { detector: GraphModel | null, landmarks: GraphModel | null } = { detector: null, landmarks: null };\nconst inputSize: { detector: [number, number], landmarks: [number, number] } = { detector: [224, 224], landmarks: [256, 256] };\nlet skipped = Number.MAX_SAFE_INTEGER;\nconst outputNodes: { detector: string[], landmarks: string[] } = {\n  landmarks: ['ld_3d', 'activation_segmentation', 'activation_heatmap', 'world_3d', 'output_poseflag'],\n  detector: [],\n};\n\nlet cache: BodyResult | null = null;\nlet cropBox: Box | undefined;\nlet padding: [number, number][] = [[0, 0], [0, 0], [0, 0], [0, 0]];\nlet lastTime = 0;\n\nconst sigmoid = (x) => (1 - (1 / (1 + Math.exp(x))));\n\nexport async function loadDetect(config: Config): Promise<GraphModel> {\n  if (env.initial) models.detector = null;\n  if (!models.detector && config.body['detector'] && config.body['detector']['modelPath'] || '') {\n    models.detector = await loadModel(config.body['detector']['modelPath']);\n    const inputs = Object.values(models.detector.modelSignature['inputs']);\n    inputSize.detector[0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize.detector[1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug && models.detector) log('cached model:', models.detector['modelUrl']);\n  await detect.createAnchors();\n  return models.detector as GraphModel;\n}\n\nexport async function loadPose(config: Config): Promise<GraphModel> {\n  if (env.initial) models.landmarks = null;\n  if (!models.landmarks) {\n    models.landmarks = await loadModel(config.body.modelPath);\n    const inputs = Object.values(models.landmarks.modelSignature['inputs']);\n    inputSize.landmarks[0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize.landmarks[1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', models.landmarks['modelUrl']);\n  return models.landmarks;\n}\n\nexport async function load(config: Config): Promise<[GraphModel | null, GraphModel | null]> {\n  if (!models.detector) await loadDetect(config);\n  if (!models.landmarks) await loadPose(config);\n  return [models.detector, models.landmarks];\n}\n\nasync function prepareImage(input: Tensor, size: number): Promise<Tensor> {\n  const t: Record<string, Tensor> = {};\n  if (!input.shape || !input.shape[1] || !input.shape[2]) return input;\n  let final: Tensor;\n  if (cropBox) {\n    t.cropped = tf.image.cropAndResize(input, [cropBox], [0], [input.shape[1], input.shape[2]]); // if we have cached box use it to crop input\n  }\n  if (input.shape[1] !== input.shape[2]) { // only pad if width different than height\n    const height: [number, number] = [\n      input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0,\n      input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0,\n    ];\n    const width: [number, number] = [\n      input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0,\n      input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0,\n    ];\n    padding = [\n      [0, 0], // dont touch batch\n      height, // height before&after\n      width, // width before&after\n      [0, 0], // dont touch rbg\n    ];\n    t.pad = tf.pad(t.cropped || input, padding); // use cropped box if it exists\n    t.resize = tf.image.resizeBilinear(t.pad, [size, size]);\n    final = tf.div(t.resize, constants.tf255);\n  } else if (input.shape[1] !== size) { // if input needs resizing\n    t.resize = tf.image.resizeBilinear(t.cropped || input, [size, size]);\n    final = tf.div(t.resize, constants.tf255);\n  } else { // if input is already in a correct resolution just normalize it\n    final = tf.div(t.cropped || input, constants.tf255);\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return final;\n}\n\nfunction rescaleKeypoints(keypoints: Array<BodyKeypoint>, outputSize: [number, number]): Array<BodyKeypoint> {\n  for (const kpt of keypoints) { // first rescale due to padding\n    kpt.position = [\n      Math.trunc(kpt.position[0] * (outputSize[0] + padding[2][0] + padding[2][1]) / outputSize[0] - padding[2][0]),\n      Math.trunc(kpt.position[1] * (outputSize[1] + padding[1][0] + padding[1][1]) / outputSize[1] - padding[1][0]),\n      kpt.position[2] as number,\n    ];\n    kpt.positionRaw = [kpt.position[0] / outputSize[0], kpt.position[1] / outputSize[1], 2 * (kpt.position[2] as number) / (outputSize[0] + outputSize[1])];\n  }\n  if (cropBox) { // second rescale due to cropping\n    for (const kpt of keypoints) {\n      kpt.positionRaw = [\n        kpt.positionRaw[0] + cropBox[1], // correct offset due to crop\n        kpt.positionRaw[1] + cropBox[0], // correct offset due to crop\n        kpt.positionRaw[2] as number,\n      ];\n      kpt.position = [\n        Math.trunc(kpt.positionRaw[0] * outputSize[0]),\n        Math.trunc(kpt.positionRaw[1] * outputSize[1]),\n        kpt.positionRaw[2] as number,\n      ];\n    }\n  }\n  return keypoints;\n}\n\nasync function fixKeypoints(keypoints: Array<BodyKeypoint>) {\n  // palm z-coord is incorrect around near-zero so we approximate it\n  const leftPalm = keypoints.find((k) => k.part === 'leftPalm') as BodyKeypoint;\n  const leftWrist = keypoints.find((k) => k.part === 'leftWrist') as BodyKeypoint;\n  const leftIndex = keypoints.find((k) => k.part === 'leftIndex') as BodyKeypoint;\n  leftPalm.position[2] = ((leftWrist.position[2] || 0) + (leftIndex.position[2] || 0)) / 2;\n  const rightPalm = keypoints.find((k) => k.part === 'rightPalm') as BodyKeypoint;\n  const rightWrist = keypoints.find((k) => k.part === 'rightWrist') as BodyKeypoint;\n  const rightIndex = keypoints.find((k) => k.part === 'rightIndex') as BodyKeypoint;\n  rightPalm.position[2] = ((rightWrist.position[2] || 0) + (rightIndex.position[2] || 0)) / 2;\n}\n\nasync function detectLandmarks(input: Tensor, config: Config, outputSize: [number, number]): Promise<BodyResult | null> {\n  /**\n   * t.ld: 39 keypoints [x,y,z,score,presence] normalized to input size\n   * t.segmentation:\n   * t.heatmap:\n   * t.world: 39 keypoints [x,y,z] normalized to -1..1\n   * t.poseflag: body score\n  */\n  const t: Record<string, Tensor> = {};\n  [t.ld/* 1,195(39*5) */, t.segmentation/* 1,256,256,1 */, t.heatmap/* 1,64,64,39 */, t.world/* 1,117(39*3) */, t.poseflag/* 1,1 */] = models.landmarks?.execute(input, outputNodes.landmarks) as Tensor[]; // run model\n  const poseScore = (await t.poseflag.data())[0];\n  const points = await t.ld.data();\n  const distances = await t.world.data();\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor])); // dont need tensors after this\n  const keypointsRelative: Array<BodyKeypoint> = [];\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    const score = sigmoid(points[depth * i + 3]);\n    const presence = sigmoid(points[depth * i + 4]);\n    const adjScore = Math.trunc(100 * score * presence * poseScore) / 100;\n    const positionRaw: Point = [points[depth * i + 0] / inputSize.landmarks[0], points[depth * i + 1] / inputSize.landmarks[1], points[depth * i + 2] + 0];\n    const position: Point = [Math.trunc(outputSize[0] * positionRaw[0]), Math.trunc(outputSize[1] * positionRaw[1]), positionRaw[2] as number];\n    const distance: Point = [distances[depth * i + 0], distances[depth * i + 1], distances[depth * i + 2] + 0];\n    keypointsRelative.push({ part: coords.kpt[i] as BodyLandmark, positionRaw, position, distance, score: adjScore });\n  }\n  if (poseScore < (config.body.minConfidence || 0)) return null;\n  fixKeypoints(keypointsRelative);\n  const keypoints: Array<BodyKeypoint> = rescaleKeypoints(keypointsRelative, outputSize); // keypoints were relative to input image which is padded\n  const kpts = keypoints.map((k) => k.position);\n  const boxes = box.calc(kpts, [outputSize[0], outputSize[1]]); // now find boxes based on rescaled keypoints\n  const annotations: Record<BodyAnnotation, Point[][]> = {} as Record<BodyAnnotation, Point[][]>;\n  for (const [name, indexes] of Object.entries(coords.connected)) {\n    const pt: Array<Point[]> = [];\n    for (let i = 0; i < indexes.length - 1; i++) {\n      const pt0 = keypoints.find((kpt) => kpt.part === indexes[i]);\n      const pt1 = keypoints.find((kpt) => kpt.part === indexes[i + 1]);\n      if (pt0 && pt1) pt.push([pt0.position, pt1.position]);\n    }\n    annotations[name] = pt;\n  }\n  const body = { id: 0, score: Math.trunc(100 * poseScore) / 100, box: boxes.box, boxRaw: boxes.boxRaw, keypoints, annotations };\n  return body;\n}\n\n/*\ninterface DetectedBox { box: Box, boxRaw: Box, score: number }\n\nfunction rescaleBoxes(boxes: Array<DetectedBox>, outputSize: [number, number]): Array<DetectedBox> {\n  for (const b of boxes) {\n    b.box = [\n      Math.trunc(b.box[0] * (outputSize[0] + padding[2][0] + padding[2][1]) / outputSize[0]),\n      Math.trunc(b.box[1] * (outputSize[1] + padding[1][0] + padding[1][1]) / outputSize[1]),\n      Math.trunc(b.box[2] * (outputSize[0] + padding[2][0] + padding[2][1]) / outputSize[0]),\n      Math.trunc(b.box[3] * (outputSize[1] + padding[1][0] + padding[1][1]) / outputSize[1]),\n    ];\n    b.boxRaw = [b.box[0] / outputSize[0], b.box[1] / outputSize[1], b.box[2] / outputSize[0], b.box[3] / outputSize[1]];\n  }\n  return boxes;\n}\n\nasync function detectBoxes(input: Tensor, config: Config, outputSize: [number, number]) {\n  const t: Record<string, Tensor> = {};\n  t.res = models.detector?.execute(input, ['Identity']) as Tensor; //\n  t.logitsRaw = tf.slice(t.res, [0, 0, 0], [1, -1, 1]);\n  t.boxesRaw = tf.slice(t.res, [0, 0, 1], [1, -1, -1]);\n  t.logits = tf.squeeze(t.logitsRaw);\n  t.boxes = tf.squeeze(t.boxesRaw);\n  const boxes = await detect.decode(t.boxes, t.logits, config, outputSize);\n  rescaleBoxes(boxes, outputSize);\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return boxes;\n}\n*/\n\nexport async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {\n  const outputSize: [number, number] = [input.shape[2] || 0, input.shape[1] || 0];\n  const skipTime = (config.body.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.body.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && cache !== null) {\n    skipped++;\n  } else {\n    const t: Record<string, Tensor> = {};\n    /*\n    if (config.body['detector'] && config.body['detector']['enabled']) {\n      t.detector = await prepareImage(input, 224);\n      const boxes = await detectBoxes(t.detector, config, outputSize);\n    }\n    */\n    t.landmarks = await prepareImage(input, 256); // padded and resized\n    cache = await detectLandmarks(t.landmarks, config, outputSize);\n    /*\n    cropBox = [0, 0, 1, 1]; // reset crop coordinates\n    if (cache?.boxRaw && config.skipAllowed) {\n      const cx = (2.0 * cache.boxRaw[0] + cache.boxRaw[2]) / 2;\n      const cy = (2.0 * cache.boxRaw[1] + cache.boxRaw[3]) / 2;\n      let size = cache.boxRaw[2] > cache.boxRaw[3] ? cache.boxRaw[2] : cache.boxRaw[3];\n      size = (size * 1.0) / 2; // enlarge and half it\n      if (cx > 0.1 && cx < 0.9 && cy > 0.1 && cy < 0.9 && size > 0.1) { // only update if box is sane\n        const y = 0; // cy - size;\n        const x = cx - size;\n        cropBox = [y, x, y + 1, x + 1]; // [y0,x0,y1,x1] used for cropping but width/height are not yet implemented so we only reposition image to center of body\n      }\n    }\n    */\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    lastTime = now();\n    skipped = 0;\n  }\n  return cache ? [cache] : [];\n}\n", "/**\n * CoCo Labels used by object detection implementations\n */\nexport const labels = [\n  { class: 1, label: 'person' },\n  { class: 2, label: 'bicycle' },\n  { class: 3, label: 'car' },\n  { class: 4, label: 'motorcycle' },\n  { class: 5, label: 'airplane' },\n  { class: 6, label: 'bus' },\n  { class: 7, label: 'train' },\n  { class: 8, label: 'truck' },\n  { class: 9, label: 'boat' },\n  { class: 10, label: 'traffic light' },\n  { class: 11, label: 'fire hydrant' },\n  { class: 12, label: 'stop sign' },\n  { class: 13, label: 'parking meter' },\n  { class: 14, label: 'bench' },\n  { class: 15, label: 'bird' },\n  { class: 16, label: 'cat' },\n  { class: 17, label: 'dog' },\n  { class: 18, label: 'horse' },\n  { class: 19, label: 'sheep' },\n  { class: 20, label: 'cow' },\n  { class: 21, label: 'elephant' },\n  { class: 22, label: 'bear' },\n  { class: 23, label: 'zebra' },\n  { class: 24, label: 'giraffe' },\n  { class: 25, label: 'backpack' },\n  { class: 26, label: 'umbrella' },\n  { class: 27, label: 'handbag' },\n  { class: 28, label: 'tie' },\n  { class: 29, label: 'suitcase' },\n  { class: 30, label: 'frisbee' },\n  { class: 31, label: 'skis' },\n  { class: 32, label: 'snowboard' },\n  { class: 33, label: 'sports ball' },\n  { class: 34, label: 'kite' },\n  { class: 35, label: 'baseball bat' },\n  { class: 36, label: 'baseball glove' },\n  { class: 37, label: 'skateboard' },\n  { class: 38, label: 'surfboard' },\n  { class: 39, label: 'tennis racket' },\n  { class: 40, label: 'bottle' },\n  { class: 41, label: 'wine glass' },\n  { class: 42, label: 'cup' },\n  { class: 43, label: 'fork' },\n  { class: 44, label: 'knife' },\n  { class: 45, label: 'spoon' },\n  { class: 46, label: 'bowl' },\n  { class: 47, label: 'banana' },\n  { class: 48, label: 'apple' },\n  { class: 49, label: 'sandwich' },\n  { class: 50, label: 'orange' },\n  { class: 51, label: 'broccoli' },\n  { class: 52, label: 'carrot' },\n  { class: 53, label: 'hot dog' },\n  { class: 54, label: 'pizza' },\n  { class: 55, label: 'donut' },\n  { class: 56, label: 'cake' },\n  { class: 57, label: 'chair' },\n  { class: 58, label: 'couch' },\n  { class: 59, label: 'potted plant' },\n  { class: 60, label: 'bed' },\n  { class: 61, label: 'dining table' },\n  { class: 62, label: 'toilet' },\n  { class: 63, label: 'tv' },\n  { class: 64, label: 'laptop' },\n  { class: 65, label: 'mouse' },\n  { class: 66, label: 'remote' },\n  { class: 67, label: 'keyboard' },\n  { class: 68, label: 'cell phone' },\n  { class: 69, label: 'microwave' },\n  { class: 70, label: 'oven' },\n  { class: 71, label: 'toaster' },\n  { class: 72, label: 'sink' },\n  { class: 73, label: 'refrigerator' },\n  { class: 74, label: 'book' },\n  { class: 75, label: 'clock' },\n  { class: 76, label: 'vase' },\n  { class: 77, label: 'scissors' },\n  { class: 78, label: 'teddy bear' },\n  { class: 79, label: 'hair drier' },\n  { class: 80, label: 'toothbrush' },\n];\n", "/**\n * CenterNet object detection model implementation\n *\n * Based on: [**NanoDet**](https://github.com/RangiLyu/nanodet)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { labels } from './labels';\nimport type { ObjectResult, ObjectType, Box } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nlet inputSize = 0;\nlet last: ObjectResult[] = [];\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) {\n    // fakeOps(['floormod'], config);\n    model = await loadModel(config.object.modelPath);\n    const inputs = Object.values(model.modelSignature['inputs']);\n    inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nasync function process(res: Tensor | null, outputShape: [number, number], config: Config) {\n  if (!res) return [];\n  const t: Record<string, Tensor> = {};\n  const results: Array<ObjectResult> = [];\n  const detections = await res.array() as number[][][];\n  t.squeeze = tf.squeeze(res);\n  const arr = tf.split(t.squeeze, 6, 1) as Tensor[]; // x1, y1, x2, y2, score, class\n  t.stack = tf.stack([arr[1], arr[0], arr[3], arr[2]], 1); // reorder dims as tf.nms expects y, x\n  t.boxes = tf.squeeze(t.stack);\n  t.scores = tf.squeeze(arr[4]);\n  t.classes = tf.squeeze(arr[5]);\n  tf.dispose([res, ...arr]);\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.scores, config.object.maxDetected, config.object.iouThreshold, (config.object.minConfidence || 0));\n  const nms = await t.nms.data();\n  let i = 0;\n  for (const id of Array.from(nms)) {\n    const score = Math.trunc(100 * detections[0][id][4]) / 100;\n    const classVal = detections[0][id][5];\n    const label = labels[classVal].label as ObjectType;\n    const [x, y] = [\n      detections[0][id][0] / inputSize,\n      detections[0][id][1] / inputSize,\n    ];\n    const boxRaw: Box = [\n      x,\n      y,\n      detections[0][id][2] / inputSize - x,\n      detections[0][id][3] / inputSize - y,\n    ];\n    const box: Box = [\n      Math.trunc(boxRaw[0] * outputShape[0]),\n      Math.trunc(boxRaw[1] * outputShape[1]),\n      Math.trunc(boxRaw[2] * outputShape[0]),\n      Math.trunc(boxRaw[3] * outputShape[1]),\n    ];\n    results.push({ id: i++, score, class: classVal, label, box, boxRaw });\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return results;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<ObjectResult[]> {\n  const skipTime = (config.object.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.object.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const outputSize = [input.shape[2] || 0, input.shape[1] || 0] as [number, number];\n    const resize = tf.image.resizeBilinear(input, [inputSize, inputSize]);\n    const objectT = config.object.enabled ? model?.execute(resize, ['tower_0/detections']) as Tensor : null;\n    lastTime = now();\n    tf.dispose(resize);\n\n    const obj = await process(objectT, outputSize, config);\n    last = obj;\n\n    resolve(obj);\n  });\n}\n", "export const kpt: Array<string> = [\n  'head',\n  'neck',\n  'rightShoulder',\n  'rightElbow',\n  'rightWrist',\n  'chest',\n  'leftShoulder',\n  'leftElbow',\n  'leftWrist',\n  'bodyCenter',\n  'rightHip',\n  'rightKnee',\n  'rightAnkle',\n  'leftHip',\n  'leftKnee',\n  'leftAnkle',\n];\n\nexport const connected: Record<string, string[]> = {\n  leftLeg: ['leftHip', 'leftKnee', 'leftAnkle'],\n  rightLeg: ['rightHip', 'rightKnee', 'rightAnkle'],\n  torso: ['leftShoulder', 'rightShoulder', 'rightHip', 'leftHip', 'leftShoulder'],\n  leftArm: ['leftShoulder', 'leftElbow', 'leftWrist'],\n  rightArm: ['rightShoulder', 'rightElbow', 'rightWrist'],\n  head: [],\n};\n", "/**\n * EfficientPose model implementation\n *\n * Based on: [**EfficientPose**](https://github.com/daniegr/EfficientPose)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport * as coords from './efficientposecoords';\nimport { constants } from '../tfjs/constants';\nimport type { BodyResult, Point, BodyLandmark, BodyAnnotation } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nlet lastTime = 0;\nconst cache: BodyResult = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} as Record<BodyAnnotation, Point[][]> };\n\n// const keypoints: Array<BodyKeypoint> = [];\n// let box: Box = [0, 0, 0, 0];\n// let boxRaw: Box = [0, 0, 0, 0];\n// let score = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.body.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// performs argmax and max functions on a 2d tensor\nasync function max2d(inputs, minScore) {\n  const [width, height] = inputs.shape;\n  const reshaped = tf.reshape(inputs, [height * width]); // combine all data\n  const max = tf.max(reshaped, 0);\n  const newScore = (await max.data())[0]; // get highest score\n  tf.dispose([reshaped, max]);\n  if (newScore > minScore) { // skip coordinate calculation is score is too low\n    const coordinates = tf.argMax(reshaped, 0);\n    const mod = tf.mod(coordinates, width);\n    const x = (await mod.data())[0];\n    const div = tf.div(coordinates, tf.scalar(width, 'int32'));\n    const y = (await div.data())[0];\n    tf.dispose([mod, div]);\n    return [x, y, newScore];\n  }\n  return [0, 0, newScore];\n}\n\nexport async function predict(image: Tensor, config: Config): Promise<BodyResult[]> {\n  const skipTime = (config.body.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.body.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && Object.keys(cache.keypoints).length > 0) {\n    skipped++;\n    return [cache];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const tensor = tf.tidy(() => {\n      if (!model?.inputs[0].shape) return null;\n      const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n      const enhance = tf.mul(resize, constants.tf2);\n      const norm = tf.sub(enhance, constants.tf1);\n      return norm;\n    });\n\n    let resT;\n    if (config.body.enabled) resT = model?.execute(tensor);\n    lastTime = now();\n    tf.dispose(tensor);\n\n    if (resT) {\n      cache.keypoints.length = 0;\n      const squeeze = resT.squeeze();\n      tf.dispose(resT);\n      // body parts are basically just a stack of 2d tensors\n      const stack = squeeze.unstack(2);\n      tf.dispose(squeeze);\n      // process each unstacked tensor as a separate body part\n      for (let id = 0; id < stack.length; id++) {\n        // actual processing to get coordinates and score\n        const [x, y, partScore] = await max2d(stack[id], config.body.minConfidence);\n        if (partScore > (config.body?.minConfidence || 0)) {\n          cache.keypoints.push({\n            score: Math.round(100 * partScore) / 100,\n            part: coords.kpt[id] as BodyLandmark,\n            positionRaw: [ // normalized to 0..1\n              // @ts-ignore model is not undefined here\n              x / model.inputs[0].shape[2], y / model.inputs[0].shape[1],\n            ],\n            position: [ // normalized to input image size\n              // @ts-ignore model is not undefined here\n              Math.round(image.shape[2] * x / model.inputs[0].shape[2]), Math.round(image.shape[1] * y / model.inputs[0].shape[1]),\n            ],\n          });\n        }\n      }\n      stack.forEach((s) => tf.dispose(s));\n    }\n    cache.score = cache.keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n    const x = cache.keypoints.map((a) => a.position[0]);\n    const y = cache.keypoints.map((a) => a.position[1]);\n    cache.box = [\n      Math.min(...x),\n      Math.min(...y),\n      Math.max(...x) - Math.min(...x),\n      Math.max(...y) - Math.min(...y),\n    ];\n    const xRaw = cache.keypoints.map((a) => a.positionRaw[0]);\n    const yRaw = cache.keypoints.map((a) => a.positionRaw[1]);\n    cache.boxRaw = [\n      Math.min(...xRaw),\n      Math.min(...yRaw),\n      Math.max(...xRaw) - Math.min(...xRaw),\n      Math.max(...yRaw) - Math.min(...yRaw),\n    ];\n    for (const [name, indexes] of Object.entries(coords.connected)) {\n      const pt: Array<Point[]> = [];\n      for (let i = 0; i < indexes.length - 1; i++) {\n        const pt0 = cache.keypoints.find((kpt) => kpt.part === indexes[i]);\n        const pt1 = cache.keypoints.find((kpt) => kpt.part === indexes[i + 1]);\n        if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n      }\n      cache.annotations[name] = pt;\n    }\n    resolve([cache]);\n  });\n}\n", "/**\n * Emotion model implementation\n *\n * [**Oarriaga**](https://github.com/oarriaga/face_classification)\n */\n\nimport type { Emotion } from '../result';\nimport { log, now } from '../util/util';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { env } from '../util/env';\nimport { constants } from '../tfjs/constants';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model: GraphModel | null;\nconst last: Array<Array<{ score: number, emotion: Emotion }>> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.emotion?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<Array<{ score: number, emotion: Emotion }>> {\n  if (!model) return [];\n  const skipFrame = skipped < (config.face.emotion?.skipFrames || 0);\n  const skipTime = (config.face.emotion?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && last[idx] && (last[idx].length > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const obj: Array<{ score: number, emotion: Emotion }> = [];\n    if (config.face.emotion?.enabled) {\n      const t: Record<string, Tensor> = {};\n      const inputSize = model?.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n      t.resize = tf.image.resizeBilinear(image, [inputSize, inputSize], false);\n      // const box = [[0.15, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n      // const resize = tf.image.cropAndResize(image, box, [0], [inputSize, inputSize]);\n      // [t.red, t.green, t.blue] = tf.split(t.resize, 3, 3);\n      // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n      // t.redNorm = tf.mul(t.red, rgb[0]);\n      // t.greenNorm = tf.mul(t.green, rgb[1]);\n      // t.blueNorm = tf.mul(t.blue, rgb[2]);\n      // t.grayscale = tf.addN([t.redNorm, t.greenNorm, t.blueNorm]);\n      t.channels = tf.mul(t.resize, constants.rgb);\n      t.grayscale = tf.sum(t.channels, 3, true);\n      t.grayscaleSub = tf.sub(t.grayscale, constants.tf05);\n      t.grayscaleMul = tf.mul(t.grayscaleSub, constants.tf2);\n      t.emotion = model?.execute(t.grayscaleMul) as Tensor; // result is already in range 0..1, no need for additional activation\n      lastTime = now();\n      const data = await t.emotion.data();\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > (config.face.emotion?.minConfidence || 0)) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] as Emotion });\n      }\n      obj.sort((a, b) => b.score - a.score);\n      Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    }\n    last[idx] = obj;\n    lastCount = count;\n    resolve(obj);\n  });\n}\n", "/**\n * EfficientPose model implementation\n *\n * Based on: [**BecauseofAI MobileFace**](https://github.com/becauseofAI/MobileFace)\n *\n * Obsolete and replaced by `faceres` that performs age/gender/descriptor analysis\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst last: Array<number[]> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['mobilefacenet'].modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n/*\n// convert to black&white to avoid colorization impact\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\nconst [red, green, blue] = tf.split(crop, 3, 3);\nconst redNorm = tf.mul(red, rgb[0]);\nconst greenNorm = tf.mul(green, rgb[1]);\nconst blueNorm = tf.mul(blue, rgb[2]);\nconst grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\nconst merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n// optional increase image contrast\n// or do it per-channel so mean is done on each channel\n// or do it based on histogram\nconst mean = merge.mean();\nconst factor = 5;\nconst contrast = merge.sub(mean).mul(factor).add(mean);\n*/\n\nexport async function predict(input: Tensor, config: Config, idx, count): Promise<number[]> {\n  if (!model) return [];\n  const skipFrame = skipped < (config.face['embedding']?.skipFrames || 0);\n  const skipTime = (config.face['embedding']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && last[idx]) {\n    skipped++;\n    return last[idx];\n  }\n  return new Promise(async (resolve) => {\n    let data: Array<number> = [];\n    if (config.face['embedding']?.enabled && model?.inputs[0].shape) {\n      const t: Record<string, Tensor> = {};\n      t.crop = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n      // do a tight crop of image and resize it to fit the model\n      // const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n      // t.crop = tf.image.cropAndResize(input, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n      t.data = model?.execute(t.crop) as Tensor;\n      /*\n      // optional normalize outputs with l2 normalization\n      const scaled = tf.tidy(() => {\n        const l2 = res.norm('euclidean');\n        const scale = res.div(l2);\n        return scale;\n      });\n\n      // optional reduce feature vector complexity\n      const reshape = tf.reshape(res, [128, 2]); // split 256 vectors into 128 x 2\n      const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n      */\n      const output = await t.data.data();\n      data = Array.from(output); // convert typed array to simple array\n    }\n    last[idx] = data;\n    lastCount = count;\n    lastTime = now();\n    resolve(data);\n  });\n}\n", "import * as coords from './facemeshcoords';\nimport * as util from './facemeshutil';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport { env } from '../util/env';\nimport { log } from '../util/util';\nimport { loadModel } from '../tfjs/load';\nimport type { Config } from '../config';\nimport type { Point } from '../result';\n\nlet model: GraphModel | null;\nlet inputSize = 0;\n\nconst irisEnlarge = 2.3;\n\nconst leftOutline = coords.meshAnnotations['leftEyeLower0'];\nconst rightOutline = coords.meshAnnotations['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.iris?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  if (inputSize === -1) inputSize = 64;\n  return model;\n}\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates and update the z coordinate to be an average of the original and the new.\nexport function replaceIrisCoords(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.irisIndices.length; i++) {\n    const { key, indices } = coords.irisIndices[i];\n    const originalIndices = coords.meshAnnotations[`${prefix}${key}`];\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0],\n          newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n\nexport const getLeftToRightEyeDepthDifference = (rawCoords) => {\n  const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n  const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n  return leftEyeZ - rightEyeZ;\n};\n\n// Returns a box describing a cropped region around the eye fit for passing to the iris model.\nexport const getEyeBox = (rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, meshSize, flip = false) => {\n  const box = util.squarifyBox(util.enlargeBox(util.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), irisEnlarge));\n  const boxSize = util.getBoxSize(box);\n  let crop = tf.image.cropAndResize(face, [[\n    box.startPoint[1] / meshSize,\n    box.startPoint[0] / meshSize, box.endPoint[1] / meshSize,\n    box.endPoint[0] / meshSize,\n  ]], [0], [inputSize, inputSize]);\n  if (flip && env.kernels.includes('flipleftright')) {\n    const flipped = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    tf.dispose(crop);\n    crop = flipped;\n  }\n  return { box, boxSize, crop };\n};\n\n// Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\nexport const getEyeCoords = (eyeData, eyeBox, eyeBoxSize, flip = false) => {\n  const eyeRawCoords: Array<Point> = [];\n  for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n    const x = eyeData[i * 3];\n    const y = eyeData[i * 3 + 1];\n    const z = eyeData[i * 3 + 2];\n    eyeRawCoords.push([\n      (flip ? (1 - (x / inputSize)) : (x / inputSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n      (y / inputSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n    ]);\n  }\n  return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n};\n\n// The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\nexport const getAdjustedIrisCoords = (rawCoords, irisCoords, direction) => {\n  const upperCenterZ = rawCoords[coords.meshAnnotations[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n  const lowerCenterZ = rawCoords[coords.meshAnnotations[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n  const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n  // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n  return irisCoords.map((coord, i) => {\n    let z = averageZ;\n    if (i === 2) {\n      z = upperCenterZ;\n    } else if (i === 4) {\n      z = lowerCenterZ;\n    }\n    return [coord[0], coord[1], z];\n  });\n};\n\nexport async function augmentIris(rawCoords, face, config, meshSize) {\n  if (!model) {\n    if (config.debug) log('face mesh iris detection requested, but model is not loaded');\n    return rawCoords;\n  }\n  const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], meshSize, true);\n  const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1], meshSize, true);\n  const combined = tf.concat([leftEyeCrop, rightEyeCrop]);\n  tf.dispose(leftEyeCrop);\n  tf.dispose(rightEyeCrop);\n  const eyePredictions = model.execute(combined) as Tensor;\n  tf.dispose(combined);\n  const eyePredictionsData = await eyePredictions.data();\n  tf.dispose(eyePredictions);\n  const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n  const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n  const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n  const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize, false);\n  const leftToRightEyeDepthDifference = getLeftToRightEyeDepthDifference(rawCoords);\n  if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n    replaceIrisCoords(rawCoords, leftEyeRawCoords, 'left', null);\n    replaceIrisCoords(rawCoords, rightEyeRawCoords, 'right', null);\n    // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged so we only update a single contour line above and below the eye.\n  } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n    replaceIrisCoords(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n  } else { // User is looking towards the left.\n    replaceIrisCoords(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n  }\n  const adjustedLeftIrisCoords = getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n  const adjustedRightIrisCoords = getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n  const newCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n  return newCoords;\n}\n", "// @tensorflow/tfjs-models/face-landmark-detection/src/constants.ts\n// https://github.com/google/mediapipe/mediapipe/python/solutions/face_mesh_connections.py\n\ntype PairArray = Array<[number, number]>;\n\nconst LIPS_CONNECTIONS: PairArray = [\n  [61, 146], [146, 91], [91, 181], [181, 84], [84, 17], [17, 314], [314, 405], [405, 321], [321, 375], [375, 291], [61, 185], [185, 40], [40, 39], [39, 37], [37, 0], [0, 267], [267, 269], [269, 270], [270, 409], [409, 291],\n  [78, 95], [95, 88], [88, 178], [178, 87], [87, 14], [14, 317], [317, 402], [402, 318], [318, 324], [324, 308], [78, 191], [191, 80], [80, 81], [81, 82], [82, 13], [13, 312], [312, 311], [311, 310], [310, 415], [415, 308],\n];\n\nconst LEFT_EYE_CONNECTIONS: PairArray = [[263, 249], [249, 390], [390, 373], [373, 374], [374, 380], [380, 381], [381, 382], [382, 362], [263, 466], [466, 388], [388, 387], [387, 386], [386, 385], [385, 384], [384, 398], [398, 362]];\n\nconst LEFT_EYEBROW_CONNECTIONS: PairArray = [[276, 283], [283, 282], [282, 295], [295, 285], [300, 293], [293, 334], [334, 296], [296, 336]];\n\nconst LEFT_IRIS_CONNECTIONS: PairArray = [[474, 475], [475, 476], [476, 477], [477, 474]];\n\nconst RIGHT_EYE_CONNECTIONS: PairArray = [[33, 7], [7, 163], [163, 144], [144, 145], [145, 153], [153, 154], [154, 155], [155, 133], [33, 246], [246, 161], [161, 160], [160, 159], [159, 158], [158, 157], [157, 173], [173, 133]];\n\nconst RIGHT_EYEBROW_CONNECTIONS: PairArray = [[46, 53], [53, 52], [52, 65], [65, 55], [70, 63], [63, 105], [105, 66], [66, 107]];\n\nconst RIGHT_IRIS_CONNECTIONS: PairArray = [[469, 470], [470, 471], [471, 472], [472, 469]];\n\nconst FACE_OVAL_CONNECTIONS: PairArray = [\n  [10, 338], [338, 297], [297, 332], [332, 284], [284, 251], [251, 389], [389, 356], [356, 454], [454, 323], [323, 361], [361, 288], [288, 397], [397, 365], [365, 379], [379, 378], [378, 400], [400, 377], [377, 152],\n  [152, 148], [148, 176], [176, 149], [149, 150], [150, 136], [136, 172], [172, 58], [58, 132], [132, 93], [93, 234], [234, 127], [127, 162], [162, 21], [21, 54], [54, 103], [103, 67], [67, 109], [109, 10],\n];\n\nexport const MEDIAPIPE_FACE_MESH_CONNECTED_KEYPOINTS_PAIRS: PairArray = [\n  [127, 34], [34, 139], [139, 127], [11, 0], [0, 37], [37, 11], [232, 231], [231, 120], [120, 232], [72, 37], [37, 39], [39, 72], [128, 121], [121, 47], [47, 128], [232, 121], [121, 128], [128, 232],\n  [104, 69], [69, 67], [67, 104], [175, 171], [171, 148], [148, 175], [118, 50], [50, 101], [101, 118], [73, 39], [39, 40], [40, 73], [9, 151], [151, 108], [108, 9], [48, 115], [115, 131], [131, 48],\n  [194, 204], [204, 211], [211, 194], [74, 40], [40, 185], [185, 74], [80, 42], [42, 183], [183, 80], [40, 92], [92, 186], [186, 40], [230, 229], [229, 118], [118, 230], [202, 212], [212, 214], [214, 202],\n  [83, 18], [18, 17], [17, 83], [76, 61], [61, 146], [146, 76], [160, 29], [29, 30], [30, 160], [56, 157], [157, 173], [173, 56], [106, 204], [204, 194], [194, 106], [135, 214], [214, 192], [192, 135],\n  [203, 165], [165, 98], [98, 203], [21, 71], [71, 68], [68, 21], [51, 45], [45, 4], [4, 51], [144, 24], [24, 23], [23, 144], [77, 146], [146, 91], [91, 77], [205, 50], [50, 187], [187, 205],\n  [201, 200], [200, 18], [18, 201], [91, 106], [106, 182], [182, 91], [90, 91], [91, 181], [181, 90], [85, 84], [84, 17], [17, 85], [206, 203], [203, 36], [36, 206], [148, 171], [171, 140], [140, 148],\n  [92, 40], [40, 39], [39, 92], [193, 189], [189, 244], [244, 193], [159, 158], [158, 28], [28, 159], [247, 246], [246, 161], [161, 247], [236, 3], [3, 196], [196, 236], [54, 68], [68, 104], [104, 54],\n  [193, 168], [168, 8], [8, 193], [117, 228], [228, 31], [31, 117], [189, 193], [193, 55], [55, 189], [98, 97], [97, 99], [99, 98], [126, 47], [47, 100], [100, 126], [166, 79], [79, 218], [218, 166],\n  [155, 154], [154, 26], [26, 155], [209, 49], [49, 131], [131, 209], [135, 136], [136, 150], [150, 135], [47, 126], [126, 217], [217, 47], [223, 52], [52, 53], [53, 223], [45, 51], [51, 134], [134, 45],\n  [211, 170], [170, 140], [140, 211], [67, 69], [69, 108], [108, 67], [43, 106], [106, 91], [91, 43], [230, 119], [119, 120], [120, 230], [226, 130], [130, 247], [247, 226], [63, 53], [53, 52], [52, 63],\n  [238, 20], [20, 242], [242, 238], [46, 70], [70, 156], [156, 46], [78, 62], [62, 96], [96, 78], [46, 53], [53, 63], [63, 46], [143, 34], [34, 227], [227, 143], [123, 117], [117, 111], [111, 123],\n  [44, 125], [125, 19], [19, 44], [236, 134], [134, 51], [51, 236], [216, 206], [206, 205], [205, 216], [154, 153], [153, 22], [22, 154], [39, 37], [37, 167], [167, 39], [200, 201], [201, 208], [208, 200],\n  [36, 142], [142, 100], [100, 36], [57, 212], [212, 202], [202, 57], [20, 60], [60, 99], [99, 20], [28, 158], [158, 157], [157, 28], [35, 226], [226, 113], [113, 35], [160, 159], [159, 27], [27, 160],\n  [204, 202], [202, 210], [210, 204], [113, 225], [225, 46], [46, 113], [43, 202], [202, 204], [204, 43], [62, 76], [76, 77], [77, 62], [137, 123], [123, 116], [116, 137], [41, 38], [38, 72], [72, 41],\n  [203, 129], [129, 142], [142, 203], [64, 98], [98, 240], [240, 64], [49, 102], [102, 64], [64, 49], [41, 73], [73, 74], [74, 41], [212, 216], [216, 207], [207, 212], [42, 74], [74, 184], [184, 42],\n  [169, 170], [170, 211], [211, 169], [170, 149], [149, 176], [176, 170], [105, 66], [66, 69], [69, 105], [122, 6], [6, 168], [168, 122], [123, 147], [147, 187], [187, 123], [96, 77], [77, 90], [90, 96],\n  [65, 55], [55, 107], [107, 65], [89, 90], [90, 180], [180, 89], [101, 100], [100, 120], [120, 101], [63, 105], [105, 104], [104, 63], [93, 137], [137, 227], [227, 93], [15, 86], [86, 85], [85, 15],\n  [129, 102], [102, 49], [49, 129], [14, 87], [87, 86], [86, 14], [55, 8], [8, 9], [9, 55], [100, 47], [47, 121], [121, 100], [145, 23], [23, 22], [22, 145], [88, 89], [89, 179], [179, 88],\n  [6, 122], [122, 196], [196, 6], [88, 95], [95, 96], [96, 88], [138, 172], [172, 136], [136, 138], [215, 58], [58, 172], [172, 215], [115, 48], [48, 219], [219, 115], [42, 80], [80, 81], [81, 42],\n  [195, 3], [3, 51], [51, 195], [43, 146], [146, 61], [61, 43], [171, 175], [175, 199], [199, 171], [81, 82], [82, 38], [38, 81], [53, 46], [46, 225], [225, 53], [144, 163], [163, 110], [110, 144],\n  [52, 65], [65, 66], [66, 52], [229, 228], [228, 117], [117, 229], [34, 127], [127, 234], [234, 34], [107, 108], [108, 69], [69, 107], [109, 108], [108, 151], [151, 109], [48, 64], [64, 235], [235, 48],\n  [62, 78], [78, 191], [191, 62], [129, 209], [209, 126], [126, 129], [111, 35], [35, 143], [143, 111], [117, 123], [123, 50], [50, 117], [222, 65], [65, 52], [52, 222], [19, 125], [125, 141], [141, 19],\n  [221, 55], [55, 65], [65, 221], [3, 195], [195, 197], [197, 3], [25, 7], [7, 33], [33, 25], [220, 237], [237, 44], [44, 220], [70, 71], [71, 139], [139, 70], [122, 193], [193, 245], [245, 122],\n  [247, 130], [130, 33], [33, 247], [71, 21], [21, 162], [162, 71], [170, 169], [169, 150], [150, 170], [188, 174], [174, 196], [196, 188], [216, 186], [186, 92], [92, 216], [2, 97], [97, 167], [167, 2],\n  [141, 125], [125, 241], [241, 141], [164, 167], [167, 37], [37, 164], [72, 38], [38, 12], [12, 72], [38, 82], [82, 13], [13, 38], [63, 68], [68, 71], [71, 63], [226, 35], [35, 111], [111, 226],\n  [101, 50], [50, 205], [205, 101], [206, 92], [92, 165], [165, 206], [209, 198], [198, 217], [217, 209], [165, 167], [167, 97], [97, 165], [220, 115], [115, 218], [218, 220], [133, 112], [112, 243], [243, 133],\n  [239, 238], [238, 241], [241, 239], [214, 135], [135, 169], [169, 214], [190, 173], [173, 133], [133, 190], [171, 208], [208, 32], [32, 171], [125, 44], [44, 237], [237, 125], [86, 87], [87, 178], [178, 86],\n  [85, 86], [86, 179], [179, 85], [84, 85], [85, 180], [180, 84], [83, 84], [84, 181], [181, 83], [201, 83], [83, 182], [182, 201], [137, 93], [93, 132], [132, 137], [76, 62], [62, 183], [183, 76],\n  [61, 76], [76, 184], [184, 61], [57, 61], [61, 185], [185, 57], [212, 57], [57, 186], [186, 212], [214, 207], [207, 187], [187, 214], [34, 143], [143, 156], [156, 34], [79, 239], [239, 237], [237, 79],\n  [123, 137], [137, 177], [177, 123], [44, 1], [1, 4], [4, 44], [201, 194], [194, 32], [32, 201], [64, 102], [102, 129], [129, 64], [213, 215], [215, 138], [138, 213], [59, 166], [166, 219], [219, 59],\n  [242, 99], [99, 97], [97, 242], [2, 94], [94, 141], [141, 2], [75, 59], [59, 235], [235, 75], [24, 110], [110, 228], [228, 24], [25, 130], [130, 226], [226, 25], [23, 24], [24, 229], [229, 23],\n  [22, 23], [23, 230], [230, 22], [26, 22], [22, 231], [231, 26], [112, 26], [26, 232], [232, 112], [189, 190], [190, 243], [243, 189], [221, 56], [56, 190], [190, 221], [28, 56], [56, 221], [221, 28],\n  [27, 28], [28, 222], [222, 27], [29, 27], [27, 223], [223, 29], [30, 29], [29, 224], [224, 30], [247, 30], [30, 225], [225, 247], [238, 79], [79, 20], [20, 238], [166, 59], [59, 75], [75, 166],\n  [60, 75], [75, 240], [240, 60], [147, 177], [177, 215], [215, 147], [20, 79], [79, 166], [166, 20], [187, 147], [147, 213], [213, 187], [112, 233], [233, 244], [244, 112], [233, 128], [128, 245], [245, 233],\n  [128, 114], [114, 188], [188, 128], [114, 217], [217, 174], [174, 114], [131, 115], [115, 220], [220, 131], [217, 198], [198, 236], [236, 217], [198, 131], [131, 134], [134, 198], [177, 132], [132, 58], [58, 177],\n  [143, 35], [35, 124], [124, 143], [110, 163], [163, 7], [7, 110], [228, 110], [110, 25], [25, 228], [356, 389], [389, 368], [368, 356], [11, 302], [302, 267], [267, 11], [452, 350], [350, 349], [349, 452],\n  [302, 303], [303, 269], [269, 302], [357, 343], [343, 277], [277, 357], [452, 453], [453, 357], [357, 452], [333, 332], [332, 297], [297, 333], [175, 152], [152, 377], [377, 175], [347, 348], [348, 330], [330, 347],\n  [303, 304], [304, 270], [270, 303], [9, 336], [336, 337], [337, 9], [278, 279], [279, 360], [360, 278], [418, 262], [262, 431], [431, 418], [304, 408], [408, 409], [409, 304], [310, 415], [415, 407], [407, 310],\n  [270, 409], [409, 410], [410, 270], [450, 348], [348, 347], [347, 450], [422, 430], [430, 434], [434, 422], [313, 314], [314, 17], [17, 313], [306, 307], [307, 375], [375, 306], [387, 388], [388, 260], [260, 387],\n  [286, 414], [414, 398], [398, 286], [335, 406], [406, 418], [418, 335], [364, 367], [367, 416], [416, 364], [423, 358], [358, 327], [327, 423], [251, 284], [284, 298], [298, 251], [281, 5], [5, 4], [4, 281],\n  [373, 374], [374, 253], [253, 373], [307, 320], [320, 321], [321, 307], [425, 427], [427, 411], [411, 425], [421, 313], [313, 18], [18, 421], [321, 405], [405, 406], [406, 321], [320, 404], [404, 405], [405, 320],\n  [315, 16], [16, 17], [17, 315], [426, 425], [425, 266], [266, 426], [377, 400], [400, 369], [369, 377], [322, 391], [391, 269], [269, 322], [417, 465], [465, 464], [464, 417], [386, 257], [257, 258], [258, 386],\n  [466, 260], [260, 388], [388, 466], [456, 399], [399, 419], [419, 456], [284, 332], [332, 333], [333, 284], [417, 285], [285, 8], [8, 417], [346, 340], [340, 261], [261, 346], [413, 441], [441, 285], [285, 413],\n  [327, 460], [460, 328], [328, 327], [355, 371], [371, 329], [329, 355], [392, 439], [439, 438], [438, 392], [382, 341], [341, 256], [256, 382], [429, 420], [420, 360], [360, 429], [364, 394], [394, 379], [379, 364],\n  [277, 343], [343, 437], [437, 277], [443, 444], [444, 283], [283, 443], [275, 440], [440, 363], [363, 275], [431, 262], [262, 369], [369, 431], [297, 338], [338, 337], [337, 297], [273, 375], [375, 321], [321, 273],\n  [450, 451], [451, 349], [349, 450], [446, 342], [342, 467], [467, 446], [293, 334], [334, 282], [282, 293], [458, 461], [461, 462], [462, 458], [276, 353], [353, 383], [383, 276], [308, 324], [324, 325], [325, 308],\n  [276, 300], [300, 293], [293, 276], [372, 345], [345, 447], [447, 372], [352, 345], [345, 340], [340, 352], [274, 1], [1, 19], [19, 274], [456, 248], [248, 281], [281, 456], [436, 427], [427, 425], [425, 436],\n  [381, 256], [256, 252], [252, 381], [269, 391], [391, 393], [393, 269], [200, 199], [199, 428], [428, 200], [266, 330], [330, 329], [329, 266], [287, 273], [273, 422], [422, 287], [250, 462], [462, 328], [328, 250],\n  [258, 286], [286, 384], [384, 258], [265, 353], [353, 342], [342, 265], [387, 259], [259, 257], [257, 387], [424, 431], [431, 430], [430, 424], [342, 353], [353, 276], [276, 342], [273, 335], [335, 424], [424, 273],\n  [292, 325], [325, 307], [307, 292], [366, 447], [447, 345], [345, 366], [271, 303], [303, 302], [302, 271], [423, 266], [266, 371], [371, 423], [294, 455], [455, 460], [460, 294], [279, 278], [278, 294], [294, 279],\n  [271, 272], [272, 304], [304, 271], [432, 434], [434, 427], [427, 432], [272, 407], [407, 408], [408, 272], [394, 430], [430, 431], [431, 394], [395, 369], [369, 400], [400, 395], [334, 333], [333, 299], [299, 334],\n  [351, 417], [417, 168], [168, 351], [352, 280], [280, 411], [411, 352], [325, 319], [319, 320], [320, 325], [295, 296], [296, 336], [336, 295], [319, 403], [403, 404], [404, 319], [330, 348], [348, 349], [349, 330],\n  [293, 298], [298, 333], [333, 293], [323, 454], [454, 447], [447, 323], [15, 16], [16, 315], [315, 15], [358, 429], [429, 279], [279, 358], [14, 15], [15, 316], [316, 14], [285, 336], [336, 9], [9, 285],\n  [329, 349], [349, 350], [350, 329], [374, 380], [380, 252], [252, 374], [318, 402], [402, 403], [403, 318], [6, 197], [197, 419], [419, 6], [318, 319], [319, 325], [325, 318], [367, 364], [364, 365], [365, 367],\n  [435, 367], [367, 397], [397, 435], [344, 438], [438, 439], [439, 344], [272, 271], [271, 311], [311, 272], [195, 5], [5, 281], [281, 195], [273, 287], [287, 291], [291, 273], [396, 428], [428, 199], [199, 396],\n  [311, 271], [271, 268], [268, 311], [283, 444], [444, 445], [445, 283], [373, 254], [254, 339], [339, 373], [282, 334], [334, 296], [296, 282], [449, 347], [347, 346], [346, 449], [264, 447], [447, 454], [454, 264],\n  [336, 296], [296, 299], [299, 336], [338, 10], [10, 151], [151, 338], [278, 439], [439, 455], [455, 278], [292, 407], [407, 415], [415, 292], [358, 371], [371, 355], [355, 358], [340, 345], [345, 372], [372, 340],\n  [346, 347], [347, 280], [280, 346], [442, 443], [443, 282], [282, 442], [19, 94], [94, 370], [370, 19], [441, 442], [442, 295], [295, 441], [248, 419], [419, 197], [197, 248], [263, 255], [255, 359], [359, 263],\n  [440, 275], [275, 274], [274, 440], [300, 383], [383, 368], [368, 300], [351, 412], [412, 465], [465, 351], [263, 467], [467, 466], [466, 263], [301, 368], [368, 389], [389, 301], [395, 378], [378, 379], [379, 395],\n  [412, 351], [351, 419], [419, 412], [436, 426], [426, 322], [322, 436], [2, 164], [164, 393], [393, 2], [370, 462], [462, 461], [461, 370], [164, 0], [0, 267], [267, 164], [302, 11], [11, 12], [12, 302],\n  [268, 12], [12, 13], [13, 268], [293, 300], [300, 301], [301, 293], [446, 261], [261, 340], [340, 446], [330, 266], [266, 425], [425, 330], [426, 423], [423, 391], [391, 426], [429, 355], [355, 437], [437, 429],\n  [391, 327], [327, 326], [326, 391], [440, 457], [457, 438], [438, 440], [341, 382], [382, 362], [362, 341], [459, 457], [457, 461], [461, 459], [434, 430], [430, 394], [394, 434], [414, 463], [463, 362], [362, 414],\n  [396, 369], [369, 262], [262, 396], [354, 461], [461, 457], [457, 354], [316, 403], [403, 402], [402, 316], [315, 404], [404, 403], [403, 315], [314, 405], [405, 404], [404, 314], [313, 406], [406, 405], [405, 313],\n  [421, 418], [418, 406], [406, 421], [366, 401], [401, 361], [361, 366], [306, 408], [408, 407], [407, 306], [291, 409], [409, 408], [408, 291], [287, 410], [410, 409], [409, 287], [432, 436], [436, 410], [410, 432],\n  [434, 416], [416, 411], [411, 434], [264, 368], [368, 383], [383, 264], [309, 438], [438, 457], [457, 309], [352, 376], [376, 401], [401, 352], [274, 275], [275, 4], [4, 274], [421, 428], [428, 262], [262, 421],\n  [294, 327], [327, 358], [358, 294], [433, 416], [416, 367], [367, 433], [289, 455], [455, 439], [439, 289], [462, 370], [370, 326], [326, 462], [2, 326], [326, 370], [370, 2], [305, 460], [460, 455], [455, 305],\n  [254, 449], [449, 448], [448, 254], [255, 261], [261, 446], [446, 255], [253, 450], [450, 449], [449, 253], [252, 451], [451, 450], [450, 252], [256, 452], [452, 451], [451, 256], [341, 453], [453, 452], [452, 341],\n  [413, 464], [464, 463], [463, 413], [441, 413], [413, 414], [414, 441], [258, 442], [442, 441], [441, 258], [257, 443], [443, 442], [442, 257], [259, 444], [444, 443], [443, 259], [260, 445], [445, 444], [444, 260],\n  [467, 342], [342, 445], [445, 467], [459, 458], [458, 250], [250, 459], [289, 392], [392, 290], [290, 289], [290, 328], [328, 460], [460, 290], [376, 433], [433, 435], [435, 376], [250, 290], [290, 392], [392, 250],\n  [411, 416], [416, 433], [433, 411], [341, 463], [463, 464], [464, 341], [453, 464], [464, 465], [465, 453], [357, 465], [465, 412], [412, 357], [343, 412], [412, 399], [399, 343], [360, 363], [363, 440], [440, 360],\n  [437, 399], [399, 456], [456, 437], [420, 456], [456, 363], [363, 420], [401, 435], [435, 288], [288, 401], [372, 383], [383, 353], [353, 372], [339, 255], [255, 249], [249, 339], [448, 261], [261, 255], [255, 448],\n  [133, 243], [243, 190], [190, 133], [133, 155], [155, 112], [112, 133], [33, 246], [246, 247], [247, 33], [33, 130], [130, 25], [25, 33], [398, 384], [384, 286], [286, 398], [362, 398], [398, 414], [414, 362],\n  [362, 463], [463, 341], [341, 362], [263, 359], [359, 467], [467, 263], [263, 249], [249, 255], [255, 263], [466, 467], [467, 260], [260, 466], [75, 60], [60, 166], [166, 75], [238, 239], [239, 79], [79, 238],\n  [162, 127], [127, 139], [139, 162], [72, 11], [11, 37], [37, 72], [121, 232], [232, 120], [120, 121], [73, 72], [72, 39], [39, 73], [114, 128], [128, 47], [47, 114], [233, 232], [232, 128], [128, 233],\n  [103, 104], [104, 67], [67, 103], [152, 175], [175, 148], [148, 152], [119, 118], [118, 101], [101, 119], [74, 73], [73, 40], [40, 74], [107, 9], [9, 108], [108, 107], [49, 48], [48, 131], [131, 49],\n  [32, 194], [194, 211], [211, 32], [184, 74], [74, 185], [185, 184], [191, 80], [80, 183], [183, 191], [185, 40], [40, 186], [186, 185], [119, 230], [230, 118], [118, 119], [210, 202], [202, 214], [214, 210],\n  [84, 83], [83, 17], [17, 84], [77, 76], [76, 146], [146, 77], [161, 160], [160, 30], [30, 161], [190, 56], [56, 173], [173, 190], [182, 106], [106, 194], [194, 182], [138, 135], [135, 192], [192, 138],\n  [129, 203], [203, 98], [98, 129], [54, 21], [21, 68], [68, 54], [5, 51], [51, 4], [4, 5], [145, 144], [144, 23], [23, 145], [90, 77], [77, 91], [91, 90], [207, 205], [205, 187], [187, 207],\n  [83, 201], [201, 18], [18, 83], [181, 91], [91, 182], [182, 181], [180, 90], [90, 181], [181, 180], [16, 85], [85, 17], [17, 16], [205, 206], [206, 36], [36, 205], [176, 148], [148, 140], [140, 176],\n  [165, 92], [92, 39], [39, 165], [245, 193], [193, 244], [244, 245], [27, 159], [159, 28], [28, 27], [30, 247], [247, 161], [161, 30], [174, 236], [236, 196], [196, 174], [103, 54], [54, 104], [104, 103],\n  [55, 193], [193, 8], [8, 55], [111, 117], [117, 31], [31, 111], [221, 189], [189, 55], [55, 221], [240, 98], [98, 99], [99, 240], [142, 126], [126, 100], [100, 142], [219, 166], [166, 218], [218, 219],\n  [112, 155], [155, 26], [26, 112], [198, 209], [209, 131], [131, 198], [169, 135], [135, 150], [150, 169], [114, 47], [47, 217], [217, 114], [224, 223], [223, 53], [53, 224], [220, 45], [45, 134], [134, 220],\n  [32, 211], [211, 140], [140, 32], [109, 67], [67, 108], [108, 109], [146, 43], [43, 91], [91, 146], [231, 230], [230, 120], [120, 231], [113, 226], [226, 247], [247, 113], [105, 63], [63, 52], [52, 105],\n  [241, 238], [238, 242], [242, 241], [124, 46], [46, 156], [156, 124], [95, 78], [78, 96], [96, 95], [70, 46], [46, 63], [63, 70], [116, 143], [143, 227], [227, 116], [116, 123], [123, 111], [111, 116],\n  [1, 44], [44, 19], [19, 1], [3, 236], [236, 51], [51, 3], [207, 216], [216, 205], [205, 207], [26, 154], [154, 22], [22, 26], [165, 39], [39, 167], [167, 165], [199, 200], [200, 208], [208, 199],\n  [101, 36], [36, 100], [100, 101], [43, 57], [57, 202], [202, 43], [242, 20], [20, 99], [99, 242], [56, 28], [28, 157], [157, 56], [124, 35], [35, 113], [113, 124], [29, 160], [160, 27], [27, 29],\n  [211, 204], [204, 210], [210, 211], [124, 113], [113, 46], [46, 124], [106, 43], [43, 204], [204, 106], [96, 62], [62, 77], [77, 96], [227, 137], [137, 116], [116, 227], [73, 41], [41, 72], [72, 73],\n  [36, 203], [203, 142], [142, 36], [235, 64], [64, 240], [240, 235], [48, 49], [49, 64], [64, 48], [42, 41], [41, 74], [74, 42], [214, 212], [212, 207], [207, 214], [183, 42], [42, 184], [184, 183],\n  [210, 169], [169, 211], [211, 210], [140, 170], [170, 176], [176, 140], [104, 105], [105, 69], [69, 104], [193, 122], [122, 168], [168, 193], [50, 123], [123, 187], [187, 50], [89, 96], [96, 90], [90, 89],\n  [66, 65], [65, 107], [107, 66], [179, 89], [89, 180], [180, 179], [119, 101], [101, 120], [120, 119], [68, 63], [63, 104], [104, 68], [234, 93], [93, 227], [227, 234], [16, 15], [15, 85], [85, 16],\n  [209, 129], [129, 49], [49, 209], [15, 14], [14, 86], [86, 15], [107, 55], [55, 9], [9, 107], [120, 100], [100, 121], [121, 120], [153, 145], [145, 22], [22, 153], [178, 88], [88, 179], [179, 178],\n  [197, 6], [6, 196], [196, 197], [89, 88], [88, 96], [96, 89], [135, 138], [138, 136], [136, 135], [138, 215], [215, 172], [172, 138], [218, 115], [115, 219], [219, 218], [41, 42], [42, 81], [81, 41],\n  [5, 195], [195, 51], [51, 5], [57, 43], [43, 61], [61, 57], [208, 171], [171, 199], [199, 208], [41, 81], [81, 38], [38, 41], [224, 53], [53, 225], [225, 224], [24, 144], [144, 110], [110, 24],\n  [105, 52], [52, 66], [66, 105], [118, 229], [229, 117], [117, 118], [227, 34], [34, 234], [234, 227], [66, 107], [107, 69], [69, 66], [10, 109], [109, 151], [151, 10], [219, 48], [48, 235], [235, 219],\n  [183, 62], [62, 191], [191, 183], [142, 129], [129, 126], [126, 142], [116, 111], [111, 143], [143, 116], [118, 117], [117, 50], [50, 118], [223, 222], [222, 52], [52, 223], [94, 19], [19, 141], [141, 94],\n  [222, 221], [221, 65], [65, 222], [196, 3], [3, 197], [197, 196], [45, 220], [220, 44], [44, 45], [156, 70], [70, 139], [139, 156], [188, 122], [122, 245], [245, 188], [139, 71], [71, 162], [162, 139],\n  [149, 170], [170, 150], [150, 149], [122, 188], [188, 196], [196, 122], [206, 216], [216, 92], [92, 206], [164, 2], [2, 167], [167, 164], [242, 141], [141, 241], [241, 242], [0, 164], [164, 37], [37, 0],\n  [11, 72], [72, 12], [12, 11], [12, 38], [38, 13], [13, 12], [70, 63], [63, 71], [71, 70], [31, 226], [226, 111], [111, 31], [36, 101], [101, 205], [205, 36], [203, 206], [206, 165], [165, 203],\n  [126, 209], [209, 217], [217, 126], [98, 165], [165, 97], [97, 98], [237, 220], [220, 218], [218, 237], [237, 239], [239, 241], [241, 237], [210, 214], [214, 169], [169, 210], [140, 171], [171, 32], [32, 140],\n  [241, 125], [125, 237], [237, 241], [179, 86], [86, 178], [178, 179], [180, 85], [85, 179], [179, 180], [181, 84], [84, 180], [180, 181], [182, 83], [83, 181], [181, 182], [194, 201], [201, 182], [182, 194],\n  [177, 137], [137, 132], [132, 177], [184, 76], [76, 183], [183, 184], [185, 61], [61, 184], [184, 185], [186, 57], [57, 185], [185, 186], [216, 212], [212, 186], [186, 216], [192, 214], [214, 187], [187, 192],\n  [139, 34], [34, 156], [156, 139], [218, 79], [79, 237], [237, 218], [147, 123], [123, 177], [177, 147], [45, 44], [44, 4], [4, 45], [208, 201], [201, 32], [32, 208], [98, 64], [64, 129], [129, 98],\n  [192, 213], [213, 138], [138, 192], [235, 59], [59, 219], [219, 235], [141, 242], [242, 97], [97, 141], [97, 2], [2, 141], [141, 97], [240, 75], [75, 235], [235, 240], [229, 24], [24, 228], [228, 229],\n  [31, 25], [25, 226], [226, 31], [230, 23], [23, 229], [229, 230], [231, 22], [22, 230], [230, 231], [232, 26], [26, 231], [231, 232], [233, 112], [112, 232], [232, 233], [244, 189], [189, 243], [243, 244],\n  [189, 221], [221, 190], [190, 189], [222, 28], [28, 221], [221, 222], [223, 27], [27, 222], [222, 223], [224, 29], [29, 223], [223, 224], [225, 30], [30, 224], [224, 225], [113, 247], [247, 225], [225, 113],\n  [99, 60], [60, 240], [240, 99], [213, 147], [147, 215], [215, 213], [60, 20], [20, 166], [166, 60], [192, 187], [187, 213], [213, 192], [243, 112], [112, 244], [244, 243], [244, 233], [233, 245], [245, 244],\n  [245, 128], [128, 188], [188, 245], [188, 114], [114, 174], [174, 188], [134, 131], [131, 220], [220, 134], [174, 217], [217, 236], [236, 174], [236, 198], [198, 134], [134, 236], [215, 177], [177, 58], [58, 215],\n  [156, 143], [143, 124], [124, 156], [25, 110], [110, 7], [7, 25], [31, 228], [228, 25], [25, 31], [264, 356], [356, 368], [368, 264], [0, 11], [11, 267], [267, 0], [451, 452], [452, 349], [349, 451],\n  [267, 302], [302, 269], [269, 267], [350, 357], [357, 277], [277, 350], [350, 452], [452, 357], [357, 350], [299, 333], [333, 297], [297, 299], [396, 175], [175, 377], [377, 396], [280, 347], [347, 330], [330, 280],\n  [269, 303], [303, 270], [270, 269], [151, 9], [9, 337], [337, 151], [344, 278], [278, 360], [360, 344], [424, 418], [418, 431], [431, 424], [270, 304], [304, 409], [409, 270], [272, 310], [310, 407], [407, 272],\n  [322, 270], [270, 410], [410, 322], [449, 450], [450, 347], [347, 449], [432, 422], [422, 434], [434, 432], [18, 313], [313, 17], [17, 18], [291, 306], [306, 375], [375, 291], [259, 387], [387, 260], [260, 259],\n  [424, 335], [335, 418], [418, 424], [434, 364], [364, 416], [416, 434], [391, 423], [423, 327], [327, 391], [301, 251], [251, 298], [298, 301], [275, 281], [281, 4], [4, 275], [254, 373], [373, 253], [253, 254],\n  [375, 307], [307, 321], [321, 375], [280, 425], [425, 411], [411, 280], [200, 421], [421, 18], [18, 200], [335, 321], [321, 406], [406, 335], [321, 320], [320, 405], [405, 321], [314, 315], [315, 17], [17, 314],\n  [423, 426], [426, 266], [266, 423], [396, 377], [377, 369], [369, 396], [270, 322], [322, 269], [269, 270], [413, 417], [417, 464], [464, 413], [385, 386], [386, 258], [258, 385], [248, 456], [456, 419], [419, 248],\n  [298, 284], [284, 333], [333, 298], [168, 417], [417, 8], [8, 168], [448, 346], [346, 261], [261, 448], [417, 413], [413, 285], [285, 417], [326, 327], [327, 328], [328, 326], [277, 355], [355, 329], [329, 277],\n  [309, 392], [392, 438], [438, 309], [381, 382], [382, 256], [256, 381], [279, 429], [429, 360], [360, 279], [365, 364], [364, 379], [379, 365], [355, 277], [277, 437], [437, 355], [282, 443], [443, 283], [283, 282],\n  [281, 275], [275, 363], [363, 281], [395, 431], [431, 369], [369, 395], [299, 297], [297, 337], [337, 299], [335, 273], [273, 321], [321, 335], [348, 450], [450, 349], [349, 348], [359, 446], [446, 467], [467, 359],\n  [283, 293], [293, 282], [282, 283], [250, 458], [458, 462], [462, 250], [300, 276], [276, 383], [383, 300], [292, 308], [308, 325], [325, 292], [283, 276], [276, 293], [293, 283], [264, 372], [372, 447], [447, 264],\n  [346, 352], [352, 340], [340, 346], [354, 274], [274, 19], [19, 354], [363, 456], [456, 281], [281, 363], [426, 436], [436, 425], [425, 426], [380, 381], [381, 252], [252, 380], [267, 269], [269, 393], [393, 267],\n  [421, 200], [200, 428], [428, 421], [371, 266], [266, 329], [329, 371], [432, 287], [287, 422], [422, 432], [290, 250], [250, 328], [328, 290], [385, 258], [258, 384], [384, 385], [446, 265], [265, 342], [342, 446],\n  [386, 387], [387, 257], [257, 386], [422, 424], [424, 430], [430, 422], [445, 342], [342, 276], [276, 445], [422, 273], [273, 424], [424, 422], [306, 292], [292, 307], [307, 306], [352, 366], [366, 345], [345, 352],\n  [268, 271], [271, 302], [302, 268], [358, 423], [423, 371], [371, 358], [327, 294], [294, 460], [460, 327], [331, 279], [279, 294], [294, 331], [303, 271], [271, 304], [304, 303], [436, 432], [432, 427], [427, 436],\n  [304, 272], [272, 408], [408, 304], [395, 394], [394, 431], [431, 395], [378, 395], [395, 400], [400, 378], [296, 334], [334, 299], [299, 296], [6, 351], [351, 168], [168, 6], [376, 352], [352, 411], [411, 376],\n  [307, 325], [325, 320], [320, 307], [285, 295], [295, 336], [336, 285], [320, 319], [319, 404], [404, 320], [329, 330], [330, 349], [349, 329], [334, 293], [293, 333], [333, 334], [366, 323], [323, 447], [447, 366],\n  [316, 15], [15, 315], [315, 316], [331, 358], [358, 279], [279, 331], [317, 14], [14, 316], [316, 317], [8, 285], [285, 9], [9, 8], [277, 329], [329, 350], [350, 277], [253, 374], [374, 252], [252, 253],\n  [319, 318], [318, 403], [403, 319], [351, 6], [6, 419], [419, 351], [324, 318], [318, 325], [325, 324], [397, 367], [367, 365], [365, 397], [288, 435], [435, 397], [397, 288], [278, 344], [344, 439], [439, 278],\n  [310, 272], [272, 311], [311, 310], [248, 195], [195, 281], [281, 248], [375, 273], [273, 291], [291, 375], [175, 396], [396, 199], [199, 175], [312, 311], [311, 268], [268, 312], [276, 283], [283, 445], [445, 276],\n  [390, 373], [373, 339], [339, 390], [295, 282], [282, 296], [296, 295], [448, 449], [449, 346], [346, 448], [356, 264], [264, 454], [454, 356], [337, 336], [336, 299], [299, 337], [337, 338], [338, 151], [151, 337],\n  [294, 278], [278, 455], [455, 294], [308, 292], [292, 415], [415, 308], [429, 358], [358, 355], [355, 429], [265, 340], [340, 372], [372, 265], [352, 346], [346, 280], [280, 352], [295, 442], [442, 282], [282, 295],\n  [354, 19], [19, 370], [370, 354], [285, 441], [441, 295], [295, 285], [195, 248], [248, 197], [197, 195], [457, 440], [440, 274], [274, 457], [301, 300], [300, 368], [368, 301], [417, 351], [351, 465], [465, 417],\n  [251, 301], [301, 389], [389, 251], [394, 395], [395, 379], [379, 394], [399, 412], [412, 419], [419, 399], [410, 436], [436, 322], [322, 410], [326, 2], [2, 393], [393, 326], [354, 370], [370, 461], [461, 354],\n  [393, 164], [164, 267], [267, 393], [268, 302], [302, 12], [12, 268], [312, 268], [268, 13], [13, 312], [298, 293], [293, 301], [301, 298], [265, 446], [446, 340], [340, 265], [280, 330], [330, 425], [425, 280],\n  [322, 426], [426, 391], [391, 322], [420, 429], [429, 437], [437, 420], [393, 391], [391, 326], [326, 393], [344, 440], [440, 438], [438, 344], [458, 459], [459, 461], [461, 458], [364, 434], [434, 394], [394, 364],\n  [428, 396], [396, 262], [262, 428], [274, 354], [354, 457], [457, 274], [317, 316], [316, 402], [402, 317], [316, 315], [315, 403], [403, 316], [315, 314], [314, 404], [404, 315], [314, 313], [313, 405], [405, 314],\n  [313, 421], [421, 406], [406, 313], [323, 366], [366, 361], [361, 323], [292, 306], [306, 407], [407, 292], [306, 291], [291, 408], [408, 306], [291, 287], [287, 409], [409, 291], [287, 432], [432, 410], [410, 287],\n  [427, 434], [434, 411], [411, 427], [372, 264], [264, 383], [383, 372], [459, 309], [309, 457], [457, 459], [366, 352], [352, 401], [401, 366], [1, 274], [274, 4], [4, 1], [418, 421], [421, 262], [262, 418],\n  [331, 294], [294, 358], [358, 331], [435, 433], [433, 367], [367, 435], [392, 289], [289, 439], [439, 392], [328, 462], [462, 326], [326, 328], [94, 2], [2, 370], [370, 94], [289, 305], [305, 455], [455, 289],\n  [339, 254], [254, 448], [448, 339], [359, 255], [255, 446], [446, 359], [254, 253], [253, 449], [449, 254], [253, 252], [252, 450], [450, 253], [252, 256], [256, 451], [451, 252], [256, 341], [341, 452], [452, 256],\n  [414, 413], [413, 463], [463, 414], [286, 441], [441, 414], [414, 286], [286, 258], [258, 441], [441, 286], [258, 257], [257, 442], [442, 258], [257, 259], [259, 443], [443, 257], [259, 260], [260, 444], [444, 259],\n  [260, 467], [467, 445], [445, 260], [309, 459], [459, 250], [250, 309], [305, 289], [289, 290], [290, 305], [305, 290], [290, 460], [460, 305], [401, 376], [376, 435], [435, 401], [309, 250], [250, 392], [392, 309],\n  [376, 411], [411, 433], [433, 376], [453, 341], [341, 464], [464, 453], [357, 453], [453, 465], [465, 357], [343, 357], [357, 412], [412, 343], [437, 343], [343, 399], [399, 437], [344, 360], [360, 440], [440, 344],\n  [420, 437], [437, 456], [456, 420], [360, 420], [420, 363], [363, 360], [361, 401], [401, 288], [288, 361], [265, 372], [372, 353], [353, 265], [390, 339], [339, 249], [249, 390], [339, 448], [448, 255], [255, 339],\n];\n\nfunction connectionsToIndices(connections: PairArray) {\n  const indices = connections.map((connection) => connection[0]);\n  indices.push(connections[connections.length - 1][1]);\n  return indices;\n}\n\nexport const MEDIAPIPE_FACE_MESH_KEYPOINTS_BY_CONTOUR = {\n  lips: connectionsToIndices(LIPS_CONNECTIONS),\n  leftEye: connectionsToIndices(LEFT_EYE_CONNECTIONS),\n  leftEyebrow: connectionsToIndices(LEFT_EYEBROW_CONNECTIONS),\n  leftIris: connectionsToIndices(LEFT_IRIS_CONNECTIONS),\n  rightEye: connectionsToIndices(RIGHT_EYE_CONNECTIONS),\n  rightEyebrow: connectionsToIndices(RIGHT_EYEBROW_CONNECTIONS),\n  rightIris: connectionsToIndices(RIGHT_IRIS_CONNECTIONS),\n  faceOval: connectionsToIndices(FACE_OVAL_CONNECTIONS),\n};\n\nconst indexLabelPairs: Array<[number, string]> = Object.entries(MEDIAPIPE_FACE_MESH_KEYPOINTS_BY_CONTOUR)\n  .map(([label, indices]) => indices.map((index) => [index, label] as [number, string]))\n  .flat();\n\nexport const MEDIAPIPE_FACE_MESH_KEYPOINTS = new Map(indexLabelPairs);\n\ntype AssignAverage = number[];\nexport interface LandmarksRefinementConfig {\n  indexesMapping: number[]; // Maps indexes of the given set of landmarks to indexes of the resulting set of landmarks. Should be non empty and contain the same amount of indexes as landmarks in the corresponding input\n  zRefinement: 'none'|'copy'|AssignAverage; // Z refinement instructions.\n}\n\nexport const LANDMARKS_REFINEMENT_LIPS_CONFIG = [\n  61, 146, 91, 181, 84, 17, 314, 405, 321, 375, 291, // Lower outer.\n  185, 40, 39, 37, 0, 267, 269, 270, 409, // Upper outer(excluding corners).\n  78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308, // Lower inner.\n  191, 80, 81, 82, 13, 312, 311, 310, 415, // Upper inner(excluding corners).\n  76, 77, 90, 180, 85, 16, 315, 404, 320, 307, 306, // Lower semi - outer.\n  184, 74, 73, 72, 11, 302, 303, 304, 408, // Upper semi - outer(excluding corners).\n  62, 96, 89, 179, 86, 15, 316, 403, 319, 325, 292, // Lower semi - inner.\n  183, 42, 41, 38, 12, 268, 271, 272, 407, // Upper semi - inner(excluding corners).\n];\n\nexport const LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG = [\n  33, 7, 163, 144, 145, 153, 154, 155, 133, // Lower contour.\n  246, 161, 160, 159, 158, 157, 173, // upper contour (excluding corners).\n  130, 25, 110, 24, 23, 22, 26, 112, 243, // Halo x2 lower contour.\n  247, 30, 29, 27, 28, 56, 190, // Halo x2 upper contour (excluding corners).\n  226, 31, 228, 229, 230, 231, 232, 233, 244, // Halo x3 lower contour.\n  113, 225, 224, 223, 222, 221, 189, // Halo x3 upper contour (excluding corners).\n  35, 124, 46, 53, 52, 65, // Halo x4 upper contour (no lower because of mesh structure) or eyebrow inner contour.\n  143, 111, 117, 118, 119, 120, 121, 128, 245, // Halo x5 lower contour.\n  156, 70, 63, 105, 66, 107, 55, 193, // Halo x5 upper contour (excluding corners) or eyebrow outer contour.\n];\n\nexport const LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG = [\n  263, 249, 390, 373, 374, 380, 381, 382, 362, // Lower contour.\n  466, 388, 387, 386, 385, 384, 398, // Upper contour (excluding corners).\n  359, 255, 339, 254, 253, 252, 256, 341, 463, // Halo x2 lower contour.\n  467, 260, 259, 257, 258, 286, 414, // Halo x2 upper contour (excluding corners).\n  446, 261, 448, 449, 450, 451, 452, 453, 464, // Halo x3 lower contour.\n  342, 445, 444, 443, 442, 441, 413, // Halo x3 upper contour (excluding corners).\n  265, 353, 276, 283, 282, 295, // Halo x4 upper contour (no lower because of mesh structure) or/ eyebrow inner contour.\n  372, 340, 346, 347, 348, 349, 350, 357, 465, // Halo x5 lower contour.\n  383, 300, 293, 334, 296, 336, 285, 417, // Halo x5 upper contour (excluding corners) or eyebrow outer contour.\n];\n\nexport const LANDMARKS_REFINEMENT_LEFT_IRIS_CONFIG = [\n  468, // Center.\n  469, // Iris right edge.\n  470, // Iris top edge.\n  471, // Iris left edge.\n  472, // Iris bottom edge.\n];\n/*\nzRefinement: [\n  33, 7, 163, 144, 145, 153, 154, 155, 133, // Lower contour.\n  246, 161, 160, 159, 158, 157, 173, // Upper contour (excluding corners).\n];\n*/\n\nexport const LANDMARKS_REFINEMENT_RIGHT_IRIS_CONFIG = [\n  473, // Center.\n  474, // Iris right edge.\n  475, // Iris top edge.\n  476, // Iris left edge.\n  477, // Iris bottom edge.\n];\n/*\nzRefinement: [\n  263, 249, 390, 373, 374, 380, 381, 382, 362, // Lower contour.\n  466, 388, 387, 386, 385, 384, 398, // Upper contour (excluding corners).\n];\n*/\n", "import * as constants from './constants';\nimport type { Tensor } from '../tfjs/types';\n\nexport async function augment(rawCoords, results: Tensor[]) {\n  const t: Record<string, Float32Array> = { // all attention models produce 2d results so it needs to be later augmented with correct z-coords\n    // mesh: results[0], // already have it in rawCoords // output_mesh_identity\n    // flag: results[1], // already processed in parent // conv_faceflag\n    lips: await results.filter((r) => r.size === 160)[0].data() as Float32Array, // 80 x 2d = 160 // output_lips\n    irisL: await results.filter((r) => r.size === 10)[0].data() as Float32Array, // 5 x 2d = 10 // output_right_iris\n    eyeL: await results.filter((r) => r.size === 142)[0].data() as Float32Array, // 71 x 2d = 142 // output_right_eye\n    irisR: await results.filter((r) => r.size === 10)[1].data() as Float32Array, // 5 x 2d = 10 // output_left_iris\n    eyeR: await results.filter((r) => r.size === 142)[1].data() as Float32Array, // 71 x 2d = 142// output_left_eye\n  };\n\n  // augment iris: adds additional 5 keypoints per eye\n  const irisLDepth = constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG.reduce((prev, curr) => prev += rawCoords[curr][2], 0) / constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG.length; // get average z-coord for iris\n  for (let i = 0; i < t.irisL.length / 2; i++) rawCoords.push([t.irisL[2 * i + 0], t.irisL[2 * i + 1], irisLDepth]);\n  const irisRDepth = constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG.reduce((prev, curr) => prev += rawCoords[curr][2], 0) / constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG.length; // get average z-coord for iris\n  for (let i = 0; i < t.irisR.length / 2; i++) rawCoords.push([t.irisR[2 * i + 0], t.irisR[2 * i + 1], irisRDepth]);\n\n  // augment eyes: replaces eye keypoints based on heuristic mapping\n  for (let i = 0; i < t.eyeL.length / 2; i++) rawCoords[constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG[i]] = [t.eyeL[2 * i + 0], t.eyeL[2 * i + 1], rawCoords[constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG[i]][2]];\n  for (let i = 0; i < t.eyeR.length / 2; i++) rawCoords[constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG[i]] = [t.eyeR[2 * i + 0], t.eyeR[2 * i + 1], rawCoords[constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG[i]][2]];\n\n  // augment lips: replaces eye keypoints based on heuristic mapping\n  for (let i = 0; i < t.lips.length / 2; i++) rawCoords[constants.LANDMARKS_REFINEMENT_LIPS_CONFIG[i]] = [t.lips[2 * i + 0], t.lips[2 * i + 1], rawCoords[constants.LANDMARKS_REFINEMENT_LIPS_CONFIG[i]][2]];\n\n  return rawCoords;\n}\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n *\n * Based on:\n * - [**MediaPipe BlazeFace**](https://drive.google.com/file/d/1f39lSzU5Oq-j_OXgS67KfN5wNsoeAZ4V/view)\n * - Facial Spacial Geometry: [**MediaPipe FaceMesh**](https://drive.google.com/file/d/1VFC_wIpw4O7xBOiTgUldl79d9LA-LsnA/view)\n * - Eye Iris Details: [**MediaPipe Iris**](https://drive.google.com/file/d/1bsWbokp9AklH2ANjCfmjqEzzxO1CNbMu/view)\n */\n\nimport { log, now } from '../util/util';\nimport { loadModel } from '../tfjs/load';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as util from './facemeshutil';\nimport * as coords from './facemeshcoords';\nimport * as iris from './iris';\nimport * as attention from './attention';\nimport { histogramEqualization } from '../image/enhance';\nimport { env } from '../util/env';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { FaceResult, FaceLandmark, Point } from '../result';\nimport type { Config } from '../config';\n\ntype DetectBox = { startPoint: Point, endPoint: Point, landmarks: Array<Point>, confidence: number };\n\nconst cache = {\n  boxes: [] as DetectBox[],\n  skipped: Number.MAX_SAFE_INTEGER,\n  timestamp: 0,\n};\n\nlet model: GraphModel | null = null;\nlet inputSize = 0;\n\nexport async function predict(input: Tensor, config: Config): Promise<FaceResult[]> {\n  // reset cached boxes\n  const skipTime = (config.face.detector?.skipTime || 0) > (now() - cache.timestamp);\n  const skipFrame = cache.skipped < (config.face.detector?.skipFrames || 0);\n  if (!config.skipAllowed || !skipTime || !skipFrame || cache.boxes.length === 0) {\n    cache.boxes = await blazeface.getBoxes(input, config); // get results from blazeface detector\n    cache.timestamp = now();\n    cache.skipped = 0;\n  } else {\n    cache.skipped++;\n  }\n  const faces: Array<FaceResult> = [];\n  const newCache: Array<DetectBox> = [];\n  let id = 0;\n  for (let i = 0; i < cache.boxes.length; i++) {\n    const box = cache.boxes[i];\n    let angle = 0;\n    let rotationMatrix;\n    const face: FaceResult = { // init face result\n      id: id++,\n      mesh: [],\n      meshRaw: [],\n      box: [0, 0, 0, 0],\n      boxRaw: [0, 0, 0, 0],\n      score: 0,\n      boxScore: 0,\n      faceScore: 0,\n      // contoursRaw: [],\n      // contours: [],\n      annotations: {} as Record<FaceLandmark, Point[]>,\n    };\n\n    // optional rotation correction based on detector data only if mesh is disabled otherwise perform it later when we have more accurate mesh data. if no rotation correction this function performs crop\n    [angle, rotationMatrix, face.tensor] = util.correctFaceRotation(config.face.detector?.rotation, box, input, config.face.mesh?.enabled ? inputSize : blazeface.size());\n    if (config?.filter?.equalization) {\n      const equilized = await histogramEqualization(face.tensor as Tensor);\n      tf.dispose(face.tensor);\n      face.tensor = equilized;\n    }\n    face.boxScore = Math.round(100 * box.confidence) / 100;\n    if (!config.face.mesh?.enabled) { // mesh not enabled, return resuts from detector only\n      face.box = util.clampBox(box, input);\n      face.boxRaw = util.getRawBox(box, input);\n      face.score = face.boxScore;\n      face.mesh = box.landmarks.map((pt) => [\n        ((box.startPoint[0] + box.endPoint[0])) / 2 + ((box.endPoint[0] + box.startPoint[0]) * pt[0] / blazeface.size()),\n        ((box.startPoint[1] + box.endPoint[1])) / 2 + ((box.endPoint[1] + box.startPoint[1]) * pt[1] / blazeface.size()),\n      ]);\n      face.meshRaw = face.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize]);\n      for (const key of Object.keys(coords.blazeFaceLandmarks)) {\n        face.annotations[key] = [face.mesh[coords.blazeFaceLandmarks[key] as number]]; // add annotations\n      }\n    } else if (!model) { // mesh enabled, but not loaded\n      if (config.debug) log('face mesh detection requested, but model is not loaded');\n    } else { // mesh enabled\n      const results = model.execute(face.tensor as Tensor) as Array<Tensor>;\n      const confidenceT = results.find((t) => t.shape[t.shape.length - 1] === 1) as Tensor;\n      const faceConfidence = await confidenceT.data();\n      face.faceScore = Math.round(100 * faceConfidence[0]) / 100;\n\n      if (face.faceScore < (config.face.detector?.minConfidence || 1)) { // low confidence in detected mesh\n        box.confidence = face.faceScore; // reset confidence of cached box\n        if (config.face.mesh?.keepInvalid) {\n          face.box = util.clampBox(box, input);\n          face.boxRaw = util.getRawBox(box, input);\n          face.score = face.boxScore;\n          face.mesh = box.landmarks.map((pt) => [\n            ((box.startPoint[0] + box.endPoint[0])) / 2 + ((box.endPoint[0] + box.startPoint[0]) * pt[0] / blazeface.size()),\n            ((box.startPoint[1] + box.endPoint[1])) / 2 + ((box.endPoint[1] + box.startPoint[1]) * pt[1] / blazeface.size()),\n          ]);\n          face.meshRaw = face.mesh.map((pt) => [pt[0] / (input.shape[2] || 1), pt[1] / (input.shape[1] || 1), (pt[2] || 0) / inputSize]);\n          for (const key of Object.keys(coords.blazeFaceLandmarks)) {\n            face.annotations[key] = [face.mesh[coords.blazeFaceLandmarks[key] as number]]; // add annotations\n          }\n        }\n      } else {\n        const meshT = results.find((t) => t.shape[t.shape.length - 1] === 1404) as Tensor;\n        const coordsReshaped = tf.reshape(meshT, [-1, 3]);\n        let rawCoords = await coordsReshaped.array();\n        tf.dispose(coordsReshaped);\n        if (config.face.attention?.enabled) {\n          rawCoords = await attention.augment(rawCoords, results); // augment iris results using attention model results\n        } else if (config.face.iris?.enabled) {\n          rawCoords = await iris.augmentIris(rawCoords, face.tensor, config, inputSize); // run iris model and augment results\n        }\n        face.mesh = util.transformRawCoords(rawCoords, box, angle, rotationMatrix, inputSize); // get processed mesh\n        face.meshRaw = face.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize]);\n        for (const key of Object.keys(coords.meshAnnotations)) face.annotations[key] = coords.meshAnnotations[key].map((index) => face.mesh[index]); // add annotations\n        face.score = face.faceScore;\n        const calculatedBox = { ...util.calculateFaceBox(face.mesh, box), confidence: box.confidence, landmarks: box.landmarks };\n        face.box = util.clampBox(calculatedBox, input);\n        face.boxRaw = util.getRawBox(calculatedBox, input);\n        /*\n        const contoursT = results.find((t) => t.shape[t.shape.length - 1] === 266) as Tensor;\n        const contoursData = contoursT && await contoursT.data(); // 133 x 2d points\n        face.contoursRaw = [];\n        for (let j = 0; j < contoursData.length / 2; j++) face.contoursRaw.push([contoursData[2 * j + 0] / inputSize, contoursData[2 * j + 1] / inputSize]);\n        face.contours = face.contoursRaw.map((c) => [Math.trunc((input.shape[2] || 1) * c[0]), Math.trunc((input.shape[1] || 1) * c[1])]);\n        */\n        newCache.push(calculatedBox);\n      }\n      tf.dispose(results);\n    }\n    if (face.score > (config.face.detector?.minConfidence || 1)) faces.push(face);\n    else tf.dispose(face.tensor);\n  }\n  cache.boxes = newCache; // reset cache\n  return faces;\n}\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  // @ts-ignore private property\n  if (config?.face?.attention?.enabled && model?.signature) {\n    // @ts-ignore private property\n    if (Object.keys(model?.signature?.outputs || {}).length < 6) model = null;\n  }\n  if (!model) {\n    if (config.face.attention?.enabled) model = await loadModel(config.face.attention?.modelPath);\n    else model = await loadModel(config.face.mesh?.modelPath);\n  } else if (config.debug) {\n    log('cached model:', model['modelUrl']);\n  }\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  return model;\n}\n\nexport const triangulation = coords.TRI468;\nexport const uvmap = coords.UV468;\n", "/**\n * FaceRes model implementation\n *\n * Returns Age, Gender, Descriptor\n * Implements Face simmilarity function\n *\n * Based on: [**HSE-FaceRes**](https://github.com/HSE-asavchenko/HSE_FaceRec_tf)\n */\n\nimport { log, now } from '../util/util';\nimport { env } from '../util/env';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport type { Gender, Race } from '../result';\n\nexport type FaceRes = { age: number, gender: Gender, genderScore: number, descriptor: number[], race?: { score: number, race: Race }[] };\n\nlet model: GraphModel | null;\nconst last: Array<{\n  age: number,\n  gender: Gender,\n  genderScore: number,\n  descriptor: number[],\n}> = [];\n\nlet lastTime = 0;\nlet lastCount = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.description?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport function enhance(input): Tensor {\n  const tensor = (input.image || input.tensor || input) as Tensor; // input received from detector is already normalized to 0..1, input is also assumed to be straightened\n  if (!model?.inputs[0].shape) return tensor; // model has no shape so no point continuing\n  const crop = tf.image.resizeBilinear(tensor, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n  const norm = tf.mul(crop, constants.tf255);\n  tf.dispose(crop);\n  return norm;\n  /*\n  // do a tight crop of image and resize it to fit the model\n  const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n  const crop = (tensor.shape.length === 3)\n    ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n    : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n  */\n  /*\n  // convert to black&white to avoid colorization impact\n  const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n  const [red, green, blue] = tf.split(crop, 3, 3);\n  const redNorm = tf.mul(red, rgb[0]);\n  const greenNorm = tf.mul(green, rgb[1]);\n  const blueNorm = tf.mul(blue, rgb[2]);\n  const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n  const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n  */\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<FaceRes> {\n  if (!model) return { age: 0, gender: 'unknown', genderScore: 0, descriptor: [] };\n  const skipFrame = skipped < (config.face.description?.skipFrames || 0);\n  const skipTime = (config.face.description?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipFrame && skipTime && (lastCount === count) && last[idx]?.age && (last[idx]?.age > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const obj = {\n      age: <number>0,\n      gender: <Gender>'unknown',\n      genderScore: <number>0,\n      descriptor: <number[]>[],\n    };\n\n    if (config.face.description?.enabled) {\n      const enhanced = enhance(image);\n      const resT = model?.execute(enhanced) as Tensor[];\n      lastTime = now();\n      tf.dispose(enhanced);\n      const genderT = await resT.find((t) => t.shape[1] === 1) as Tensor;\n      const gender = await genderT.data();\n      const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n      if (confidence > (config.face.description?.minConfidence || 0)) {\n        obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n        obj.genderScore = Math.min(0.99, confidence);\n      }\n      const argmax = tf.argMax(resT.find((t) => t.shape[1] === 100), 1);\n      const age = (await argmax.data())[0];\n      tf.dispose(argmax);\n      const ageT = resT.find((t) => t.shape[1] === 100) as Tensor;\n      const all = await ageT.data();\n      obj.age = Math.round(all[age - 1] > all[age + 1] ? 10 * age - 100 * all[age - 1] : 10 * age + 100 * all[age + 1]) / 10;\n\n      const desc = resT.find((t) => t.shape[1] === 1024);\n      // const reshape = desc.reshape([128, 8]); // reshape large 1024-element descriptor to 128 x 8\n      // const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it which leaves us with 128-element descriptor\n      const descriptor = desc ? await desc.data() : <number[]>[];\n      obj.descriptor = Array.from(descriptor);\n      resT.forEach((t) => tf.dispose(t));\n    }\n    last[idx] = obj;\n    lastCount = count;\n    resolve(obj);\n  });\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport type { Point } from '../result';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]] as Point;\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]] as Point;\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]] as Point;\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]] as Point;\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize] as Point;\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize] as Point;\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]] as Point;\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]] as Point;\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "/**\n * HandPose model implementation constants\n * See `handpose.ts` for entry point\n */\n\nexport const anchors = [\n  { x: 0.015625, y: 0.015625 },\n  { x: 0.015625, y: 0.015625 },\n  { x: 0.046875, y: 0.015625 },\n  { x: 0.046875, y: 0.015625 },\n  { x: 0.078125, y: 0.015625 },\n  { x: 0.078125, y: 0.015625 },\n  { x: 0.109375, y: 0.015625 },\n  { x: 0.109375, y: 0.015625 },\n  { x: 0.140625, y: 0.015625 },\n  { x: 0.140625, y: 0.015625 },\n  { x: 0.171875, y: 0.015625 },\n  { x: 0.171875, y: 0.015625 },\n  { x: 0.203125, y: 0.015625 },\n  { x: 0.203125, y: 0.015625 },\n  { x: 0.234375, y: 0.015625 },\n  { x: 0.234375, y: 0.015625 },\n  { x: 0.265625, y: 0.015625 },\n  { x: 0.265625, y: 0.015625 },\n  { x: 0.296875, y: 0.015625 },\n  { x: 0.296875, y: 0.015625 },\n  { x: 0.328125, y: 0.015625 },\n  { x: 0.328125, y: 0.015625 },\n  { x: 0.359375, y: 0.015625 },\n  { x: 0.359375, y: 0.015625 },\n  { x: 0.390625, y: 0.015625 },\n  { x: 0.390625, y: 0.015625 },\n  { x: 0.421875, y: 0.015625 },\n  { x: 0.421875, y: 0.015625 },\n  { x: 0.453125, y: 0.015625 },\n  { x: 0.453125, y: 0.015625 },\n  { x: 0.484375, y: 0.015625 },\n  { x: 0.484375, y: 0.015625 },\n  { x: 0.515625, y: 0.015625 },\n  { x: 0.515625, y: 0.015625 },\n  { x: 0.546875, y: 0.015625 },\n  { x: 0.546875, y: 0.015625 },\n  { x: 0.578125, y: 0.015625 },\n  { x: 0.578125, y: 0.015625 },\n  { x: 0.609375, y: 0.015625 },\n  { x: 0.609375, y: 0.015625 },\n  { x: 0.640625, y: 0.015625 },\n  { x: 0.640625, y: 0.015625 },\n  { x: 0.671875, y: 0.015625 },\n  { x: 0.671875, y: 0.015625 },\n  { x: 0.703125, y: 0.015625 },\n  { x: 0.703125, y: 0.015625 },\n  { x: 0.734375, y: 0.015625 },\n  { x: 0.734375, y: 0.015625 },\n  { x: 0.765625, y: 0.015625 },\n  { x: 0.765625, y: 0.015625 },\n  { x: 0.796875, y: 0.015625 },\n  { x: 0.796875, y: 0.015625 },\n  { x: 0.828125, y: 0.015625 },\n  { x: 0.828125, y: 0.015625 },\n  { x: 0.859375, y: 0.015625 },\n  { x: 0.859375, y: 0.015625 },\n  { x: 0.890625, y: 0.015625 },\n  { x: 0.890625, y: 0.015625 },\n  { x: 0.921875, y: 0.015625 },\n  { x: 0.921875, y: 0.015625 },\n  { x: 0.953125, y: 0.015625 },\n  { x: 0.953125, y: 0.015625 },\n  { x: 0.984375, y: 0.015625 },\n  { x: 0.984375, y: 0.015625 },\n  { x: 0.015625, y: 0.046875 },\n  { x: 0.015625, y: 0.046875 },\n  { x: 0.046875, y: 0.046875 },\n  { x: 0.046875, y: 0.046875 },\n  { x: 0.078125, y: 0.046875 },\n  { x: 0.078125, y: 0.046875 },\n  { x: 0.109375, y: 0.046875 },\n  { x: 0.109375, y: 0.046875 },\n  { x: 0.140625, y: 0.046875 },\n  { x: 0.140625, y: 0.046875 },\n  { x: 0.171875, y: 0.046875 },\n  { x: 0.171875, y: 0.046875 },\n  { x: 0.203125, y: 0.046875 },\n  { x: 0.203125, y: 0.046875 },\n  { x: 0.234375, y: 0.046875 },\n  { x: 0.234375, y: 0.046875 },\n  { x: 0.265625, y: 0.046875 },\n  { x: 0.265625, y: 0.046875 },\n  { x: 0.296875, y: 0.046875 },\n  { x: 0.296875, y: 0.046875 },\n  { x: 0.328125, y: 0.046875 },\n  { x: 0.328125, y: 0.046875 },\n  { x: 0.359375, y: 0.046875 },\n  { x: 0.359375, y: 0.046875 },\n  { x: 0.390625, y: 0.046875 },\n  { x: 0.390625, y: 0.046875 },\n  { x: 0.421875, y: 0.046875 },\n  { x: 0.421875, y: 0.046875 },\n  { x: 0.453125, y: 0.046875 },\n  { x: 0.453125, y: 0.046875 },\n  { x: 0.484375, y: 0.046875 },\n  { x: 0.484375, y: 0.046875 },\n  { x: 0.515625, y: 0.046875 },\n  { x: 0.515625, y: 0.046875 },\n  { x: 0.546875, y: 0.046875 },\n  { x: 0.546875, y: 0.046875 },\n  { x: 0.578125, y: 0.046875 },\n  { x: 0.578125, y: 0.046875 },\n  { x: 0.609375, y: 0.046875 },\n  { x: 0.609375, y: 0.046875 },\n  { x: 0.640625, y: 0.046875 },\n  { x: 0.640625, y: 0.046875 },\n  { x: 0.671875, y: 0.046875 },\n  { x: 0.671875, y: 0.046875 },\n  { x: 0.703125, y: 0.046875 },\n  { x: 0.703125, y: 0.046875 },\n  { x: 0.734375, y: 0.046875 },\n  { x: 0.734375, y: 0.046875 },\n  { x: 0.765625, y: 0.046875 },\n  { x: 0.765625, y: 0.046875 },\n  { x: 0.796875, y: 0.046875 },\n  { x: 0.796875, y: 0.046875 },\n  { x: 0.828125, y: 0.046875 },\n  { x: 0.828125, y: 0.046875 },\n  { x: 0.859375, y: 0.046875 },\n  { x: 0.859375, y: 0.046875 },\n  { x: 0.890625, y: 0.046875 },\n  { x: 0.890625, y: 0.046875 },\n  { x: 0.921875, y: 0.046875 },\n  { x: 0.921875, y: 0.046875 },\n  { x: 0.953125, y: 0.046875 },\n  { x: 0.953125, y: 0.046875 },\n  { x: 0.984375, y: 0.046875 },\n  { x: 0.984375, y: 0.046875 },\n  { x: 0.015625, y: 0.078125 },\n  { x: 0.015625, y: 0.078125 },\n  { x: 0.046875, y: 0.078125 },\n  { x: 0.046875, y: 0.078125 },\n  { x: 0.078125, y: 0.078125 },\n  { x: 0.078125, y: 0.078125 },\n  { x: 0.109375, y: 0.078125 },\n  { x: 0.109375, y: 0.078125 },\n  { x: 0.140625, y: 0.078125 },\n  { x: 0.140625, y: 0.078125 },\n  { x: 0.171875, y: 0.078125 },\n  { x: 0.171875, y: 0.078125 },\n  { x: 0.203125, y: 0.078125 },\n  { x: 0.203125, y: 0.078125 },\n  { x: 0.234375, y: 0.078125 },\n  { x: 0.234375, y: 0.078125 },\n  { x: 0.265625, y: 0.078125 },\n  { x: 0.265625, y: 0.078125 },\n  { x: 0.296875, y: 0.078125 },\n  { x: 0.296875, y: 0.078125 },\n  { x: 0.328125, y: 0.078125 },\n  { x: 0.328125, y: 0.078125 },\n  { x: 0.359375, y: 0.078125 },\n  { x: 0.359375, y: 0.078125 },\n  { x: 0.390625, y: 0.078125 },\n  { x: 0.390625, y: 0.078125 },\n  { x: 0.421875, y: 0.078125 },\n  { x: 0.421875, y: 0.078125 },\n  { x: 0.453125, y: 0.078125 },\n  { x: 0.453125, y: 0.078125 },\n  { x: 0.484375, y: 0.078125 },\n  { x: 0.484375, y: 0.078125 },\n  { x: 0.515625, y: 0.078125 },\n  { x: 0.515625, y: 0.078125 },\n  { x: 0.546875, y: 0.078125 },\n  { x: 0.546875, y: 0.078125 },\n  { x: 0.578125, y: 0.078125 },\n  { x: 0.578125, y: 0.078125 },\n  { x: 0.609375, y: 0.078125 },\n  { x: 0.609375, y: 0.078125 },\n  { x: 0.640625, y: 0.078125 },\n  { x: 0.640625, y: 0.078125 },\n  { x: 0.671875, y: 0.078125 },\n  { x: 0.671875, y: 0.078125 },\n  { x: 0.703125, y: 0.078125 },\n  { x: 0.703125, y: 0.078125 },\n  { x: 0.734375, y: 0.078125 },\n  { x: 0.734375, y: 0.078125 },\n  { x: 0.765625, y: 0.078125 },\n  { x: 0.765625, y: 0.078125 },\n  { x: 0.796875, y: 0.078125 },\n  { x: 0.796875, y: 0.078125 },\n  { x: 0.828125, y: 0.078125 },\n  { x: 0.828125, y: 0.078125 },\n  { x: 0.859375, y: 0.078125 },\n  { x: 0.859375, y: 0.078125 },\n  { x: 0.890625, y: 0.078125 },\n  { x: 0.890625, y: 0.078125 },\n  { x: 0.921875, y: 0.078125 },\n  { x: 0.921875, y: 0.078125 },\n  { x: 0.953125, y: 0.078125 },\n  { x: 0.953125, y: 0.078125 },\n  { x: 0.984375, y: 0.078125 },\n  { x: 0.984375, y: 0.078125 },\n  { x: 0.015625, y: 0.109375 },\n  { x: 0.015625, y: 0.109375 },\n  { x: 0.046875, y: 0.109375 },\n  { x: 0.046875, y: 0.109375 },\n  { x: 0.078125, y: 0.109375 },\n  { x: 0.078125, y: 0.109375 },\n  { x: 0.109375, y: 0.109375 },\n  { x: 0.109375, y: 0.109375 },\n  { x: 0.140625, y: 0.109375 },\n  { x: 0.140625, y: 0.109375 },\n  { x: 0.171875, y: 0.109375 },\n  { x: 0.171875, y: 0.109375 },\n  { x: 0.203125, y: 0.109375 },\n  { x: 0.203125, y: 0.109375 },\n  { x: 0.234375, y: 0.109375 },\n  { x: 0.234375, y: 0.109375 },\n  { x: 0.265625, y: 0.109375 },\n  { x: 0.265625, y: 0.109375 },\n  { x: 0.296875, y: 0.109375 },\n  { x: 0.296875, y: 0.109375 },\n  { x: 0.328125, y: 0.109375 },\n  { x: 0.328125, y: 0.109375 },\n  { x: 0.359375, y: 0.109375 },\n  { x: 0.359375, y: 0.109375 },\n  { x: 0.390625, y: 0.109375 },\n  { x: 0.390625, y: 0.109375 },\n  { x: 0.421875, y: 0.109375 },\n  { x: 0.421875, y: 0.109375 },\n  { x: 0.453125, y: 0.109375 },\n  { x: 0.453125, y: 0.109375 },\n  { x: 0.484375, y: 0.109375 },\n  { x: 0.484375, y: 0.109375 },\n  { x: 0.515625, y: 0.109375 },\n  { x: 0.515625, y: 0.109375 },\n  { x: 0.546875, y: 0.109375 },\n  { x: 0.546875, y: 0.109375 },\n  { x: 0.578125, y: 0.109375 },\n  { x: 0.578125, y: 0.109375 },\n  { x: 0.609375, y: 0.109375 },\n  { x: 0.609375, y: 0.109375 },\n  { x: 0.640625, y: 0.109375 },\n  { x: 0.640625, y: 0.109375 },\n  { x: 0.671875, y: 0.109375 },\n  { x: 0.671875, y: 0.109375 },\n  { x: 0.703125, y: 0.109375 },\n  { x: 0.703125, y: 0.109375 },\n  { x: 0.734375, y: 0.109375 },\n  { x: 0.734375, y: 0.109375 },\n  { x: 0.765625, y: 0.109375 },\n  { x: 0.765625, y: 0.109375 },\n  { x: 0.796875, y: 0.109375 },\n  { x: 0.796875, y: 0.109375 },\n  { x: 0.828125, y: 0.109375 },\n  { x: 0.828125, y: 0.109375 },\n  { x: 0.859375, y: 0.109375 },\n  { x: 0.859375, y: 0.109375 },\n  { x: 0.890625, y: 0.109375 },\n  { x: 0.890625, y: 0.109375 },\n  { x: 0.921875, y: 0.109375 },\n  { x: 0.921875, y: 0.109375 },\n  { x: 0.953125, y: 0.109375 },\n  { x: 0.953125, y: 0.109375 },\n  { x: 0.984375, y: 0.109375 },\n  { x: 0.984375, y: 0.109375 },\n  { x: 0.015625, y: 0.140625 },\n  { x: 0.015625, y: 0.140625 },\n  { x: 0.046875, y: 0.140625 },\n  { x: 0.046875, y: 0.140625 },\n  { x: 0.078125, y: 0.140625 },\n  { x: 0.078125, y: 0.140625 },\n  { x: 0.109375, y: 0.140625 },\n  { x: 0.109375, y: 0.140625 },\n  { x: 0.140625, y: 0.140625 },\n  { x: 0.140625, y: 0.140625 },\n  { x: 0.171875, y: 0.140625 },\n  { x: 0.171875, y: 0.140625 },\n  { x: 0.203125, y: 0.140625 },\n  { x: 0.203125, y: 0.140625 },\n  { x: 0.234375, y: 0.140625 },\n  { x: 0.234375, y: 0.140625 },\n  { x: 0.265625, y: 0.140625 },\n  { x: 0.265625, y: 0.140625 },\n  { x: 0.296875, y: 0.140625 },\n  { x: 0.296875, y: 0.140625 },\n  { x: 0.328125, y: 0.140625 },\n  { x: 0.328125, y: 0.140625 },\n  { x: 0.359375, y: 0.140625 },\n  { x: 0.359375, y: 0.140625 },\n  { x: 0.390625, y: 0.140625 },\n  { x: 0.390625, y: 0.140625 },\n  { x: 0.421875, y: 0.140625 },\n  { x: 0.421875, y: 0.140625 },\n  { x: 0.453125, y: 0.140625 },\n  { x: 0.453125, y: 0.140625 },\n  { x: 0.484375, y: 0.140625 },\n  { x: 0.484375, y: 0.140625 },\n  { x: 0.515625, y: 0.140625 },\n  { x: 0.515625, y: 0.140625 },\n  { x: 0.546875, y: 0.140625 },\n  { x: 0.546875, y: 0.140625 },\n  { x: 0.578125, y: 0.140625 },\n  { x: 0.578125, y: 0.140625 },\n  { x: 0.609375, y: 0.140625 },\n  { x: 0.609375, y: 0.140625 },\n  { x: 0.640625, y: 0.140625 },\n  { x: 0.640625, y: 0.140625 },\n  { x: 0.671875, y: 0.140625 },\n  { x: 0.671875, y: 0.140625 },\n  { x: 0.703125, y: 0.140625 },\n  { x: 0.703125, y: 0.140625 },\n  { x: 0.734375, y: 0.140625 },\n  { x: 0.734375, y: 0.140625 },\n  { x: 0.765625, y: 0.140625 },\n  { x: 0.765625, y: 0.140625 },\n  { x: 0.796875, y: 0.140625 },\n  { x: 0.796875, y: 0.140625 },\n  { x: 0.828125, y: 0.140625 },\n  { x: 0.828125, y: 0.140625 },\n  { x: 0.859375, y: 0.140625 },\n  { x: 0.859375, y: 0.140625 },\n  { x: 0.890625, y: 0.140625 },\n  { x: 0.890625, y: 0.140625 },\n  { x: 0.921875, y: 0.140625 },\n  { x: 0.921875, y: 0.140625 },\n  { x: 0.953125, y: 0.140625 },\n  { x: 0.953125, y: 0.140625 },\n  { x: 0.984375, y: 0.140625 },\n  { x: 0.984375, y: 0.140625 },\n  { x: 0.015625, y: 0.171875 },\n  { x: 0.015625, y: 0.171875 },\n  { x: 0.046875, y: 0.171875 },\n  { x: 0.046875, y: 0.171875 },\n  { x: 0.078125, y: 0.171875 },\n  { x: 0.078125, y: 0.171875 },\n  { x: 0.109375, y: 0.171875 },\n  { x: 0.109375, y: 0.171875 },\n  { x: 0.140625, y: 0.171875 },\n  { x: 0.140625, y: 0.171875 },\n  { x: 0.171875, y: 0.171875 },\n  { x: 0.171875, y: 0.171875 },\n  { x: 0.203125, y: 0.171875 },\n  { x: 0.203125, y: 0.171875 },\n  { x: 0.234375, y: 0.171875 },\n  { x: 0.234375, y: 0.171875 },\n  { x: 0.265625, y: 0.171875 },\n  { x: 0.265625, y: 0.171875 },\n  { x: 0.296875, y: 0.171875 },\n  { x: 0.296875, y: 0.171875 },\n  { x: 0.328125, y: 0.171875 },\n  { x: 0.328125, y: 0.171875 },\n  { x: 0.359375, y: 0.171875 },\n  { x: 0.359375, y: 0.171875 },\n  { x: 0.390625, y: 0.171875 },\n  { x: 0.390625, y: 0.171875 },\n  { x: 0.421875, y: 0.171875 },\n  { x: 0.421875, y: 0.171875 },\n  { x: 0.453125, y: 0.171875 },\n  { x: 0.453125, y: 0.171875 },\n  { x: 0.484375, y: 0.171875 },\n  { x: 0.484375, y: 0.171875 },\n  { x: 0.515625, y: 0.171875 },\n  { x: 0.515625, y: 0.171875 },\n  { x: 0.546875, y: 0.171875 },\n  { x: 0.546875, y: 0.171875 },\n  { x: 0.578125, y: 0.171875 },\n  { x: 0.578125, y: 0.171875 },\n  { x: 0.609375, y: 0.171875 },\n  { x: 0.609375, y: 0.171875 },\n  { x: 0.640625, y: 0.171875 },\n  { x: 0.640625, y: 0.171875 },\n  { x: 0.671875, y: 0.171875 },\n  { x: 0.671875, y: 0.171875 },\n  { x: 0.703125, y: 0.171875 },\n  { x: 0.703125, y: 0.171875 },\n  { x: 0.734375, y: 0.171875 },\n  { x: 0.734375, y: 0.171875 },\n  { x: 0.765625, y: 0.171875 },\n  { x: 0.765625, y: 0.171875 },\n  { x: 0.796875, y: 0.171875 },\n  { x: 0.796875, y: 0.171875 },\n  { x: 0.828125, y: 0.171875 },\n  { x: 0.828125, y: 0.171875 },\n  { x: 0.859375, y: 0.171875 },\n  { x: 0.859375, y: 0.171875 },\n  { x: 0.890625, y: 0.171875 },\n  { x: 0.890625, y: 0.171875 },\n  { x: 0.921875, y: 0.171875 },\n  { x: 0.921875, y: 0.171875 },\n  { x: 0.953125, y: 0.171875 },\n  { x: 0.953125, y: 0.171875 },\n  { x: 0.984375, y: 0.171875 },\n  { x: 0.984375, y: 0.171875 },\n  { x: 0.015625, y: 0.203125 },\n  { x: 0.015625, y: 0.203125 },\n  { x: 0.046875, y: 0.203125 },\n  { x: 0.046875, y: 0.203125 },\n  { x: 0.078125, y: 0.203125 },\n  { x: 0.078125, y: 0.203125 },\n  { x: 0.109375, y: 0.203125 },\n  { x: 0.109375, y: 0.203125 },\n  { x: 0.140625, y: 0.203125 },\n  { x: 0.140625, y: 0.203125 },\n  { x: 0.171875, y: 0.203125 },\n  { x: 0.171875, y: 0.203125 },\n  { x: 0.203125, y: 0.203125 },\n  { x: 0.203125, y: 0.203125 },\n  { x: 0.234375, y: 0.203125 },\n  { x: 0.234375, y: 0.203125 },\n  { x: 0.265625, y: 0.203125 },\n  { x: 0.265625, y: 0.203125 },\n  { x: 0.296875, y: 0.203125 },\n  { x: 0.296875, y: 0.203125 },\n  { x: 0.328125, y: 0.203125 },\n  { x: 0.328125, y: 0.203125 },\n  { x: 0.359375, y: 0.203125 },\n  { x: 0.359375, y: 0.203125 },\n  { x: 0.390625, y: 0.203125 },\n  { x: 0.390625, y: 0.203125 },\n  { x: 0.421875, y: 0.203125 },\n  { x: 0.421875, y: 0.203125 },\n  { x: 0.453125, y: 0.203125 },\n  { x: 0.453125, y: 0.203125 },\n  { x: 0.484375, y: 0.203125 },\n  { x: 0.484375, y: 0.203125 },\n  { x: 0.515625, y: 0.203125 },\n  { x: 0.515625, y: 0.203125 },\n  { x: 0.546875, y: 0.203125 },\n  { x: 0.546875, y: 0.203125 },\n  { x: 0.578125, y: 0.203125 },\n  { x: 0.578125, y: 0.203125 },\n  { x: 0.609375, y: 0.203125 },\n  { x: 0.609375, y: 0.203125 },\n  { x: 0.640625, y: 0.203125 },\n  { x: 0.640625, y: 0.203125 },\n  { x: 0.671875, y: 0.203125 },\n  { x: 0.671875, y: 0.203125 },\n  { x: 0.703125, y: 0.203125 },\n  { x: 0.703125, y: 0.203125 },\n  { x: 0.734375, y: 0.203125 },\n  { x: 0.734375, y: 0.203125 },\n  { x: 0.765625, y: 0.203125 },\n  { x: 0.765625, y: 0.203125 },\n  { x: 0.796875, y: 0.203125 },\n  { x: 0.796875, y: 0.203125 },\n  { x: 0.828125, y: 0.203125 },\n  { x: 0.828125, y: 0.203125 },\n  { x: 0.859375, y: 0.203125 },\n  { x: 0.859375, y: 0.203125 },\n  { x: 0.890625, y: 0.203125 },\n  { x: 0.890625, y: 0.203125 },\n  { x: 0.921875, y: 0.203125 },\n  { x: 0.921875, y: 0.203125 },\n  { x: 0.953125, y: 0.203125 },\n  { x: 0.953125, y: 0.203125 },\n  { x: 0.984375, y: 0.203125 },\n  { x: 0.984375, y: 0.203125 },\n  { x: 0.015625, y: 0.234375 },\n  { x: 0.015625, y: 0.234375 },\n  { x: 0.046875, y: 0.234375 },\n  { x: 0.046875, y: 0.234375 },\n  { x: 0.078125, y: 0.234375 },\n  { x: 0.078125, y: 0.234375 },\n  { x: 0.109375, y: 0.234375 },\n  { x: 0.109375, y: 0.234375 },\n  { x: 0.140625, y: 0.234375 },\n  { x: 0.140625, y: 0.234375 },\n  { x: 0.171875, y: 0.234375 },\n  { x: 0.171875, y: 0.234375 },\n  { x: 0.203125, y: 0.234375 },\n  { x: 0.203125, y: 0.234375 },\n  { x: 0.234375, y: 0.234375 },\n  { x: 0.234375, y: 0.234375 },\n  { x: 0.265625, y: 0.234375 },\n  { x: 0.265625, y: 0.234375 },\n  { x: 0.296875, y: 0.234375 },\n  { x: 0.296875, y: 0.234375 },\n  { x: 0.328125, y: 0.234375 },\n  { x: 0.328125, y: 0.234375 },\n  { x: 0.359375, y: 0.234375 },\n  { x: 0.359375, y: 0.234375 },\n  { x: 0.390625, y: 0.234375 },\n  { x: 0.390625, y: 0.234375 },\n  { x: 0.421875, y: 0.234375 },\n  { x: 0.421875, y: 0.234375 },\n  { x: 0.453125, y: 0.234375 },\n  { x: 0.453125, y: 0.234375 },\n  { x: 0.484375, y: 0.234375 },\n  { x: 0.484375, y: 0.234375 },\n  { x: 0.515625, y: 0.234375 },\n  { x: 0.515625, y: 0.234375 },\n  { x: 0.546875, y: 0.234375 },\n  { x: 0.546875, y: 0.234375 },\n  { x: 0.578125, y: 0.234375 },\n  { x: 0.578125, y: 0.234375 },\n  { x: 0.609375, y: 0.234375 },\n  { x: 0.609375, y: 0.234375 },\n  { x: 0.640625, y: 0.234375 },\n  { x: 0.640625, y: 0.234375 },\n  { x: 0.671875, y: 0.234375 },\n  { x: 0.671875, y: 0.234375 },\n  { x: 0.703125, y: 0.234375 },\n  { x: 0.703125, y: 0.234375 },\n  { x: 0.734375, y: 0.234375 },\n  { x: 0.734375, y: 0.234375 },\n  { x: 0.765625, y: 0.234375 },\n  { x: 0.765625, y: 0.234375 },\n  { x: 0.796875, y: 0.234375 },\n  { x: 0.796875, y: 0.234375 },\n  { x: 0.828125, y: 0.234375 },\n  { x: 0.828125, y: 0.234375 },\n  { x: 0.859375, y: 0.234375 },\n  { x: 0.859375, y: 0.234375 },\n  { x: 0.890625, y: 0.234375 },\n  { x: 0.890625, y: 0.234375 },\n  { x: 0.921875, y: 0.234375 },\n  { x: 0.921875, y: 0.234375 },\n  { x: 0.953125, y: 0.234375 },\n  { x: 0.953125, y: 0.234375 },\n  { x: 0.984375, y: 0.234375 },\n  { x: 0.984375, y: 0.234375 },\n  { x: 0.015625, y: 0.265625 },\n  { x: 0.015625, y: 0.265625 },\n  { x: 0.046875, y: 0.265625 },\n  { x: 0.046875, y: 0.265625 },\n  { x: 0.078125, y: 0.265625 },\n  { x: 0.078125, y: 0.265625 },\n  { x: 0.109375, y: 0.265625 },\n  { x: 0.109375, y: 0.265625 },\n  { x: 0.140625, y: 0.265625 },\n  { x: 0.140625, y: 0.265625 },\n  { x: 0.171875, y: 0.265625 },\n  { x: 0.171875, y: 0.265625 },\n  { x: 0.203125, y: 0.265625 },\n  { x: 0.203125, y: 0.265625 },\n  { x: 0.234375, y: 0.265625 },\n  { x: 0.234375, y: 0.265625 },\n  { x: 0.265625, y: 0.265625 },\n  { x: 0.265625, y: 0.265625 },\n  { x: 0.296875, y: 0.265625 },\n  { x: 0.296875, y: 0.265625 },\n  { x: 0.328125, y: 0.265625 },\n  { x: 0.328125, y: 0.265625 },\n  { x: 0.359375, y: 0.265625 },\n  { x: 0.359375, y: 0.265625 },\n  { x: 0.390625, y: 0.265625 },\n  { x: 0.390625, y: 0.265625 },\n  { x: 0.421875, y: 0.265625 },\n  { x: 0.421875, y: 0.265625 },\n  { x: 0.453125, y: 0.265625 },\n  { x: 0.453125, y: 0.265625 },\n  { x: 0.484375, y: 0.265625 },\n  { x: 0.484375, y: 0.265625 },\n  { x: 0.515625, y: 0.265625 },\n  { x: 0.515625, y: 0.265625 },\n  { x: 0.546875, y: 0.265625 },\n  { x: 0.546875, y: 0.265625 },\n  { x: 0.578125, y: 0.265625 },\n  { x: 0.578125, y: 0.265625 },\n  { x: 0.609375, y: 0.265625 },\n  { x: 0.609375, y: 0.265625 },\n  { x: 0.640625, y: 0.265625 },\n  { x: 0.640625, y: 0.265625 },\n  { x: 0.671875, y: 0.265625 },\n  { x: 0.671875, y: 0.265625 },\n  { x: 0.703125, y: 0.265625 },\n  { x: 0.703125, y: 0.265625 },\n  { x: 0.734375, y: 0.265625 },\n  { x: 0.734375, y: 0.265625 },\n  { x: 0.765625, y: 0.265625 },\n  { x: 0.765625, y: 0.265625 },\n  { x: 0.796875, y: 0.265625 },\n  { x: 0.796875, y: 0.265625 },\n  { x: 0.828125, y: 0.265625 },\n  { x: 0.828125, y: 0.265625 },\n  { x: 0.859375, y: 0.265625 },\n  { x: 0.859375, y: 0.265625 },\n  { x: 0.890625, y: 0.265625 },\n  { x: 0.890625, y: 0.265625 },\n  { x: 0.921875, y: 0.265625 },\n  { x: 0.921875, y: 0.265625 },\n  { x: 0.953125, y: 0.265625 },\n  { x: 0.953125, y: 0.265625 },\n  { x: 0.984375, y: 0.265625 },\n  { x: 0.984375, y: 0.265625 },\n  { x: 0.015625, y: 0.296875 },\n  { x: 0.015625, y: 0.296875 },\n  { x: 0.046875, y: 0.296875 },\n  { x: 0.046875, y: 0.296875 },\n  { x: 0.078125, y: 0.296875 },\n  { x: 0.078125, y: 0.296875 },\n  { x: 0.109375, y: 0.296875 },\n  { x: 0.109375, y: 0.296875 },\n  { x: 0.140625, y: 0.296875 },\n  { x: 0.140625, y: 0.296875 },\n  { x: 0.171875, y: 0.296875 },\n  { x: 0.171875, y: 0.296875 },\n  { x: 0.203125, y: 0.296875 },\n  { x: 0.203125, y: 0.296875 },\n  { x: 0.234375, y: 0.296875 },\n  { x: 0.234375, y: 0.296875 },\n  { x: 0.265625, y: 0.296875 },\n  { x: 0.265625, y: 0.296875 },\n  { x: 0.296875, y: 0.296875 },\n  { x: 0.296875, y: 0.296875 },\n  { x: 0.328125, y: 0.296875 },\n  { x: 0.328125, y: 0.296875 },\n  { x: 0.359375, y: 0.296875 },\n  { x: 0.359375, y: 0.296875 },\n  { x: 0.390625, y: 0.296875 },\n  { x: 0.390625, y: 0.296875 },\n  { x: 0.421875, y: 0.296875 },\n  { x: 0.421875, y: 0.296875 },\n  { x: 0.453125, y: 0.296875 },\n  { x: 0.453125, y: 0.296875 },\n  { x: 0.484375, y: 0.296875 },\n  { x: 0.484375, y: 0.296875 },\n  { x: 0.515625, y: 0.296875 },\n  { x: 0.515625, y: 0.296875 },\n  { x: 0.546875, y: 0.296875 },\n  { x: 0.546875, y: 0.296875 },\n  { x: 0.578125, y: 0.296875 },\n  { x: 0.578125, y: 0.296875 },\n  { x: 0.609375, y: 0.296875 },\n  { x: 0.609375, y: 0.296875 },\n  { x: 0.640625, y: 0.296875 },\n  { x: 0.640625, y: 0.296875 },\n  { x: 0.671875, y: 0.296875 },\n  { x: 0.671875, y: 0.296875 },\n  { x: 0.703125, y: 0.296875 },\n  { x: 0.703125, y: 0.296875 },\n  { x: 0.734375, y: 0.296875 },\n  { x: 0.734375, y: 0.296875 },\n  { x: 0.765625, y: 0.296875 },\n  { x: 0.765625, y: 0.296875 },\n  { x: 0.796875, y: 0.296875 },\n  { x: 0.796875, y: 0.296875 },\n  { x: 0.828125, y: 0.296875 },\n  { x: 0.828125, y: 0.296875 },\n  { x: 0.859375, y: 0.296875 },\n  { x: 0.859375, y: 0.296875 },\n  { x: 0.890625, y: 0.296875 },\n  { x: 0.890625, y: 0.296875 },\n  { x: 0.921875, y: 0.296875 },\n  { x: 0.921875, y: 0.296875 },\n  { x: 0.953125, y: 0.296875 },\n  { x: 0.953125, y: 0.296875 },\n  { x: 0.984375, y: 0.296875 },\n  { x: 0.984375, y: 0.296875 },\n  { x: 0.015625, y: 0.328125 },\n  { x: 0.015625, y: 0.328125 },\n  { x: 0.046875, y: 0.328125 },\n  { x: 0.046875, y: 0.328125 },\n  { x: 0.078125, y: 0.328125 },\n  { x: 0.078125, y: 0.328125 },\n  { x: 0.109375, y: 0.328125 },\n  { x: 0.109375, y: 0.328125 },\n  { x: 0.140625, y: 0.328125 },\n  { x: 0.140625, y: 0.328125 },\n  { x: 0.171875, y: 0.328125 },\n  { x: 0.171875, y: 0.328125 },\n  { x: 0.203125, y: 0.328125 },\n  { x: 0.203125, y: 0.328125 },\n  { x: 0.234375, y: 0.328125 },\n  { x: 0.234375, y: 0.328125 },\n  { x: 0.265625, y: 0.328125 },\n  { x: 0.265625, y: 0.328125 },\n  { x: 0.296875, y: 0.328125 },\n  { x: 0.296875, y: 0.328125 },\n  { x: 0.328125, y: 0.328125 },\n  { x: 0.328125, y: 0.328125 },\n  { x: 0.359375, y: 0.328125 },\n  { x: 0.359375, y: 0.328125 },\n  { x: 0.390625, y: 0.328125 },\n  { x: 0.390625, y: 0.328125 },\n  { x: 0.421875, y: 0.328125 },\n  { x: 0.421875, y: 0.328125 },\n  { x: 0.453125, y: 0.328125 },\n  { x: 0.453125, y: 0.328125 },\n  { x: 0.484375, y: 0.328125 },\n  { x: 0.484375, y: 0.328125 },\n  { x: 0.515625, y: 0.328125 },\n  { x: 0.515625, y: 0.328125 },\n  { x: 0.546875, y: 0.328125 },\n  { x: 0.546875, y: 0.328125 },\n  { x: 0.578125, y: 0.328125 },\n  { x: 0.578125, y: 0.328125 },\n  { x: 0.609375, y: 0.328125 },\n  { x: 0.609375, y: 0.328125 },\n  { x: 0.640625, y: 0.328125 },\n  { x: 0.640625, y: 0.328125 },\n  { x: 0.671875, y: 0.328125 },\n  { x: 0.671875, y: 0.328125 },\n  { x: 0.703125, y: 0.328125 },\n  { x: 0.703125, y: 0.328125 },\n  { x: 0.734375, y: 0.328125 },\n  { x: 0.734375, y: 0.328125 },\n  { x: 0.765625, y: 0.328125 },\n  { x: 0.765625, y: 0.328125 },\n  { x: 0.796875, y: 0.328125 },\n  { x: 0.796875, y: 0.328125 },\n  { x: 0.828125, y: 0.328125 },\n  { x: 0.828125, y: 0.328125 },\n  { x: 0.859375, y: 0.328125 },\n  { x: 0.859375, y: 0.328125 },\n  { x: 0.890625, y: 0.328125 },\n  { x: 0.890625, y: 0.328125 },\n  { x: 0.921875, y: 0.328125 },\n  { x: 0.921875, y: 0.328125 },\n  { x: 0.953125, y: 0.328125 },\n  { x: 0.953125, y: 0.328125 },\n  { x: 0.984375, y: 0.328125 },\n  { x: 0.984375, y: 0.328125 },\n  { x: 0.015625, y: 0.359375 },\n  { x: 0.015625, y: 0.359375 },\n  { x: 0.046875, y: 0.359375 },\n  { x: 0.046875, y: 0.359375 },\n  { x: 0.078125, y: 0.359375 },\n  { x: 0.078125, y: 0.359375 },\n  { x: 0.109375, y: 0.359375 },\n  { x: 0.109375, y: 0.359375 },\n  { x: 0.140625, y: 0.359375 },\n  { x: 0.140625, y: 0.359375 },\n  { x: 0.171875, y: 0.359375 },\n  { x: 0.171875, y: 0.359375 },\n  { x: 0.203125, y: 0.359375 },\n  { x: 0.203125, y: 0.359375 },\n  { x: 0.234375, y: 0.359375 },\n  { x: 0.234375, y: 0.359375 },\n  { x: 0.265625, y: 0.359375 },\n  { x: 0.265625, y: 0.359375 },\n  { x: 0.296875, y: 0.359375 },\n  { x: 0.296875, y: 0.359375 },\n  { x: 0.328125, y: 0.359375 },\n  { x: 0.328125, y: 0.359375 },\n  { x: 0.359375, y: 0.359375 },\n  { x: 0.359375, y: 0.359375 },\n  { x: 0.390625, y: 0.359375 },\n  { x: 0.390625, y: 0.359375 },\n  { x: 0.421875, y: 0.359375 },\n  { x: 0.421875, y: 0.359375 },\n  { x: 0.453125, y: 0.359375 },\n  { x: 0.453125, y: 0.359375 },\n  { x: 0.484375, y: 0.359375 },\n  { x: 0.484375, y: 0.359375 },\n  { x: 0.515625, y: 0.359375 },\n  { x: 0.515625, y: 0.359375 },\n  { x: 0.546875, y: 0.359375 },\n  { x: 0.546875, y: 0.359375 },\n  { x: 0.578125, y: 0.359375 },\n  { x: 0.578125, y: 0.359375 },\n  { x: 0.609375, y: 0.359375 },\n  { x: 0.609375, y: 0.359375 },\n  { x: 0.640625, y: 0.359375 },\n  { x: 0.640625, y: 0.359375 },\n  { x: 0.671875, y: 0.359375 },\n  { x: 0.671875, y: 0.359375 },\n  { x: 0.703125, y: 0.359375 },\n  { x: 0.703125, y: 0.359375 },\n  { x: 0.734375, y: 0.359375 },\n  { x: 0.734375, y: 0.359375 },\n  { x: 0.765625, y: 0.359375 },\n  { x: 0.765625, y: 0.359375 },\n  { x: 0.796875, y: 0.359375 },\n  { x: 0.796875, y: 0.359375 },\n  { x: 0.828125, y: 0.359375 },\n  { x: 0.828125, y: 0.359375 },\n  { x: 0.859375, y: 0.359375 },\n  { x: 0.859375, y: 0.359375 },\n  { x: 0.890625, y: 0.359375 },\n  { x: 0.890625, y: 0.359375 },\n  { x: 0.921875, y: 0.359375 },\n  { x: 0.921875, y: 0.359375 },\n  { x: 0.953125, y: 0.359375 },\n  { x: 0.953125, y: 0.359375 },\n  { x: 0.984375, y: 0.359375 },\n  { x: 0.984375, y: 0.359375 },\n  { x: 0.015625, y: 0.390625 },\n  { x: 0.015625, y: 0.390625 },\n  { x: 0.046875, y: 0.390625 },\n  { x: 0.046875, y: 0.390625 },\n  { x: 0.078125, y: 0.390625 },\n  { x: 0.078125, y: 0.390625 },\n  { x: 0.109375, y: 0.390625 },\n  { x: 0.109375, y: 0.390625 },\n  { x: 0.140625, y: 0.390625 },\n  { x: 0.140625, y: 0.390625 },\n  { x: 0.171875, y: 0.390625 },\n  { x: 0.171875, y: 0.390625 },\n  { x: 0.203125, y: 0.390625 },\n  { x: 0.203125, y: 0.390625 },\n  { x: 0.234375, y: 0.390625 },\n  { x: 0.234375, y: 0.390625 },\n  { x: 0.265625, y: 0.390625 },\n  { x: 0.265625, y: 0.390625 },\n  { x: 0.296875, y: 0.390625 },\n  { x: 0.296875, y: 0.390625 },\n  { x: 0.328125, y: 0.390625 },\n  { x: 0.328125, y: 0.390625 },\n  { x: 0.359375, y: 0.390625 },\n  { x: 0.359375, y: 0.390625 },\n  { x: 0.390625, y: 0.390625 },\n  { x: 0.390625, y: 0.390625 },\n  { x: 0.421875, y: 0.390625 },\n  { x: 0.421875, y: 0.390625 },\n  { x: 0.453125, y: 0.390625 },\n  { x: 0.453125, y: 0.390625 },\n  { x: 0.484375, y: 0.390625 },\n  { x: 0.484375, y: 0.390625 },\n  { x: 0.515625, y: 0.390625 },\n  { x: 0.515625, y: 0.390625 },\n  { x: 0.546875, y: 0.390625 },\n  { x: 0.546875, y: 0.390625 },\n  { x: 0.578125, y: 0.390625 },\n  { x: 0.578125, y: 0.390625 },\n  { x: 0.609375, y: 0.390625 },\n  { x: 0.609375, y: 0.390625 },\n  { x: 0.640625, y: 0.390625 },\n  { x: 0.640625, y: 0.390625 },\n  { x: 0.671875, y: 0.390625 },\n  { x: 0.671875, y: 0.390625 },\n  { x: 0.703125, y: 0.390625 },\n  { x: 0.703125, y: 0.390625 },\n  { x: 0.734375, y: 0.390625 },\n  { x: 0.734375, y: 0.390625 },\n  { x: 0.765625, y: 0.390625 },\n  { x: 0.765625, y: 0.390625 },\n  { x: 0.796875, y: 0.390625 },\n  { x: 0.796875, y: 0.390625 },\n  { x: 0.828125, y: 0.390625 },\n  { x: 0.828125, y: 0.390625 },\n  { x: 0.859375, y: 0.390625 },\n  { x: 0.859375, y: 0.390625 },\n  { x: 0.890625, y: 0.390625 },\n  { x: 0.890625, y: 0.390625 },\n  { x: 0.921875, y: 0.390625 },\n  { x: 0.921875, y: 0.390625 },\n  { x: 0.953125, y: 0.390625 },\n  { x: 0.953125, y: 0.390625 },\n  { x: 0.984375, y: 0.390625 },\n  { x: 0.984375, y: 0.390625 },\n  { x: 0.015625, y: 0.421875 },\n  { x: 0.015625, y: 0.421875 },\n  { x: 0.046875, y: 0.421875 },\n  { x: 0.046875, y: 0.421875 },\n  { x: 0.078125, y: 0.421875 },\n  { x: 0.078125, y: 0.421875 },\n  { x: 0.109375, y: 0.421875 },\n  { x: 0.109375, y: 0.421875 },\n  { x: 0.140625, y: 0.421875 },\n  { x: 0.140625, y: 0.421875 },\n  { x: 0.171875, y: 0.421875 },\n  { x: 0.171875, y: 0.421875 },\n  { x: 0.203125, y: 0.421875 },\n  { x: 0.203125, y: 0.421875 },\n  { x: 0.234375, y: 0.421875 },\n  { x: 0.234375, y: 0.421875 },\n  { x: 0.265625, y: 0.421875 },\n  { x: 0.265625, y: 0.421875 },\n  { x: 0.296875, y: 0.421875 },\n  { x: 0.296875, y: 0.421875 },\n  { x: 0.328125, y: 0.421875 },\n  { x: 0.328125, y: 0.421875 },\n  { x: 0.359375, y: 0.421875 },\n  { x: 0.359375, y: 0.421875 },\n  { x: 0.390625, y: 0.421875 },\n  { x: 0.390625, y: 0.421875 },\n  { x: 0.421875, y: 0.421875 },\n  { x: 0.421875, y: 0.421875 },\n  { x: 0.453125, y: 0.421875 },\n  { x: 0.453125, y: 0.421875 },\n  { x: 0.484375, y: 0.421875 },\n  { x: 0.484375, y: 0.421875 },\n  { x: 0.515625, y: 0.421875 },\n  { x: 0.515625, y: 0.421875 },\n  { x: 0.546875, y: 0.421875 },\n  { x: 0.546875, y: 0.421875 },\n  { x: 0.578125, y: 0.421875 },\n  { x: 0.578125, y: 0.421875 },\n  { x: 0.609375, y: 0.421875 },\n  { x: 0.609375, y: 0.421875 },\n  { x: 0.640625, y: 0.421875 },\n  { x: 0.640625, y: 0.421875 },\n  { x: 0.671875, y: 0.421875 },\n  { x: 0.671875, y: 0.421875 },\n  { x: 0.703125, y: 0.421875 },\n  { x: 0.703125, y: 0.421875 },\n  { x: 0.734375, y: 0.421875 },\n  { x: 0.734375, y: 0.421875 },\n  { x: 0.765625, y: 0.421875 },\n  { x: 0.765625, y: 0.421875 },\n  { x: 0.796875, y: 0.421875 },\n  { x: 0.796875, y: 0.421875 },\n  { x: 0.828125, y: 0.421875 },\n  { x: 0.828125, y: 0.421875 },\n  { x: 0.859375, y: 0.421875 },\n  { x: 0.859375, y: 0.421875 },\n  { x: 0.890625, y: 0.421875 },\n  { x: 0.890625, y: 0.421875 },\n  { x: 0.921875, y: 0.421875 },\n  { x: 0.921875, y: 0.421875 },\n  { x: 0.953125, y: 0.421875 },\n  { x: 0.953125, y: 0.421875 },\n  { x: 0.984375, y: 0.421875 },\n  { x: 0.984375, y: 0.421875 },\n  { x: 0.015625, y: 0.453125 },\n  { x: 0.015625, y: 0.453125 },\n  { x: 0.046875, y: 0.453125 },\n  { x: 0.046875, y: 0.453125 },\n  { x: 0.078125, y: 0.453125 },\n  { x: 0.078125, y: 0.453125 },\n  { x: 0.109375, y: 0.453125 },\n  { x: 0.109375, y: 0.453125 },\n  { x: 0.140625, y: 0.453125 },\n  { x: 0.140625, y: 0.453125 },\n  { x: 0.171875, y: 0.453125 },\n  { x: 0.171875, y: 0.453125 },\n  { x: 0.203125, y: 0.453125 },\n  { x: 0.203125, y: 0.453125 },\n  { x: 0.234375, y: 0.453125 },\n  { x: 0.234375, y: 0.453125 },\n  { x: 0.265625, y: 0.453125 },\n  { x: 0.265625, y: 0.453125 },\n  { x: 0.296875, y: 0.453125 },\n  { x: 0.296875, y: 0.453125 },\n  { x: 0.328125, y: 0.453125 },\n  { x: 0.328125, y: 0.453125 },\n  { x: 0.359375, y: 0.453125 },\n  { x: 0.359375, y: 0.453125 },\n  { x: 0.390625, y: 0.453125 },\n  { x: 0.390625, y: 0.453125 },\n  { x: 0.421875, y: 0.453125 },\n  { x: 0.421875, y: 0.453125 },\n  { x: 0.453125, y: 0.453125 },\n  { x: 0.453125, y: 0.453125 },\n  { x: 0.484375, y: 0.453125 },\n  { x: 0.484375, y: 0.453125 },\n  { x: 0.515625, y: 0.453125 },\n  { x: 0.515625, y: 0.453125 },\n  { x: 0.546875, y: 0.453125 },\n  { x: 0.546875, y: 0.453125 },\n  { x: 0.578125, y: 0.453125 },\n  { x: 0.578125, y: 0.453125 },\n  { x: 0.609375, y: 0.453125 },\n  { x: 0.609375, y: 0.453125 },\n  { x: 0.640625, y: 0.453125 },\n  { x: 0.640625, y: 0.453125 },\n  { x: 0.671875, y: 0.453125 },\n  { x: 0.671875, y: 0.453125 },\n  { x: 0.703125, y: 0.453125 },\n  { x: 0.703125, y: 0.453125 },\n  { x: 0.734375, y: 0.453125 },\n  { x: 0.734375, y: 0.453125 },\n  { x: 0.765625, y: 0.453125 },\n  { x: 0.765625, y: 0.453125 },\n  { x: 0.796875, y: 0.453125 },\n  { x: 0.796875, y: 0.453125 },\n  { x: 0.828125, y: 0.453125 },\n  { x: 0.828125, y: 0.453125 },\n  { x: 0.859375, y: 0.453125 },\n  { x: 0.859375, y: 0.453125 },\n  { x: 0.890625, y: 0.453125 },\n  { x: 0.890625, y: 0.453125 },\n  { x: 0.921875, y: 0.453125 },\n  { x: 0.921875, y: 0.453125 },\n  { x: 0.953125, y: 0.453125 },\n  { x: 0.953125, y: 0.453125 },\n  { x: 0.984375, y: 0.453125 },\n  { x: 0.984375, y: 0.453125 },\n  { x: 0.015625, y: 0.484375 },\n  { x: 0.015625, y: 0.484375 },\n  { x: 0.046875, y: 0.484375 },\n  { x: 0.046875, y: 0.484375 },\n  { x: 0.078125, y: 0.484375 },\n  { x: 0.078125, y: 0.484375 },\n  { x: 0.109375, y: 0.484375 },\n  { x: 0.109375, y: 0.484375 },\n  { x: 0.140625, y: 0.484375 },\n  { x: 0.140625, y: 0.484375 },\n  { x: 0.171875, y: 0.484375 },\n  { x: 0.171875, y: 0.484375 },\n  { x: 0.203125, y: 0.484375 },\n  { x: 0.203125, y: 0.484375 },\n  { x: 0.234375, y: 0.484375 },\n  { x: 0.234375, y: 0.484375 },\n  { x: 0.265625, y: 0.484375 },\n  { x: 0.265625, y: 0.484375 },\n  { x: 0.296875, y: 0.484375 },\n  { x: 0.296875, y: 0.484375 },\n  { x: 0.328125, y: 0.484375 },\n  { x: 0.328125, y: 0.484375 },\n  { x: 0.359375, y: 0.484375 },\n  { x: 0.359375, y: 0.484375 },\n  { x: 0.390625, y: 0.484375 },\n  { x: 0.390625, y: 0.484375 },\n  { x: 0.421875, y: 0.484375 },\n  { x: 0.421875, y: 0.484375 },\n  { x: 0.453125, y: 0.484375 },\n  { x: 0.453125, y: 0.484375 },\n  { x: 0.484375, y: 0.484375 },\n  { x: 0.484375, y: 0.484375 },\n  { x: 0.515625, y: 0.484375 },\n  { x: 0.515625, y: 0.484375 },\n  { x: 0.546875, y: 0.484375 },\n  { x: 0.546875, y: 0.484375 },\n  { x: 0.578125, y: 0.484375 },\n  { x: 0.578125, y: 0.484375 },\n  { x: 0.609375, y: 0.484375 },\n  { x: 0.609375, y: 0.484375 },\n  { x: 0.640625, y: 0.484375 },\n  { x: 0.640625, y: 0.484375 },\n  { x: 0.671875, y: 0.484375 },\n  { x: 0.671875, y: 0.484375 },\n  { x: 0.703125, y: 0.484375 },\n  { x: 0.703125, y: 0.484375 },\n  { x: 0.734375, y: 0.484375 },\n  { x: 0.734375, y: 0.484375 },\n  { x: 0.765625, y: 0.484375 },\n  { x: 0.765625, y: 0.484375 },\n  { x: 0.796875, y: 0.484375 },\n  { x: 0.796875, y: 0.484375 },\n  { x: 0.828125, y: 0.484375 },\n  { x: 0.828125, y: 0.484375 },\n  { x: 0.859375, y: 0.484375 },\n  { x: 0.859375, y: 0.484375 },\n  { x: 0.890625, y: 0.484375 },\n  { x: 0.890625, y: 0.484375 },\n  { x: 0.921875, y: 0.484375 },\n  { x: 0.921875, y: 0.484375 },\n  { x: 0.953125, y: 0.484375 },\n  { x: 0.953125, y: 0.484375 },\n  { x: 0.984375, y: 0.484375 },\n  { x: 0.984375, y: 0.484375 },\n  { x: 0.015625, y: 0.515625 },\n  { x: 0.015625, y: 0.515625 },\n  { x: 0.046875, y: 0.515625 },\n  { x: 0.046875, y: 0.515625 },\n  { x: 0.078125, y: 0.515625 },\n  { x: 0.078125, y: 0.515625 },\n  { x: 0.109375, y: 0.515625 },\n  { x: 0.109375, y: 0.515625 },\n  { x: 0.140625, y: 0.515625 },\n  { x: 0.140625, y: 0.515625 },\n  { x: 0.171875, y: 0.515625 },\n  { x: 0.171875, y: 0.515625 },\n  { x: 0.203125, y: 0.515625 },\n  { x: 0.203125, y: 0.515625 },\n  { x: 0.234375, y: 0.515625 },\n  { x: 0.234375, y: 0.515625 },\n  { x: 0.265625, y: 0.515625 },\n  { x: 0.265625, y: 0.515625 },\n  { x: 0.296875, y: 0.515625 },\n  { x: 0.296875, y: 0.515625 },\n  { x: 0.328125, y: 0.515625 },\n  { x: 0.328125, y: 0.515625 },\n  { x: 0.359375, y: 0.515625 },\n  { x: 0.359375, y: 0.515625 },\n  { x: 0.390625, y: 0.515625 },\n  { x: 0.390625, y: 0.515625 },\n  { x: 0.421875, y: 0.515625 },\n  { x: 0.421875, y: 0.515625 },\n  { x: 0.453125, y: 0.515625 },\n  { x: 0.453125, y: 0.515625 },\n  { x: 0.484375, y: 0.515625 },\n  { x: 0.484375, y: 0.515625 },\n  { x: 0.515625, y: 0.515625 },\n  { x: 0.515625, y: 0.515625 },\n  { x: 0.546875, y: 0.515625 },\n  { x: 0.546875, y: 0.515625 },\n  { x: 0.578125, y: 0.515625 },\n  { x: 0.578125, y: 0.515625 },\n  { x: 0.609375, y: 0.515625 },\n  { x: 0.609375, y: 0.515625 },\n  { x: 0.640625, y: 0.515625 },\n  { x: 0.640625, y: 0.515625 },\n  { x: 0.671875, y: 0.515625 },\n  { x: 0.671875, y: 0.515625 },\n  { x: 0.703125, y: 0.515625 },\n  { x: 0.703125, y: 0.515625 },\n  { x: 0.734375, y: 0.515625 },\n  { x: 0.734375, y: 0.515625 },\n  { x: 0.765625, y: 0.515625 },\n  { x: 0.765625, y: 0.515625 },\n  { x: 0.796875, y: 0.515625 },\n  { x: 0.796875, y: 0.515625 },\n  { x: 0.828125, y: 0.515625 },\n  { x: 0.828125, y: 0.515625 },\n  { x: 0.859375, y: 0.515625 },\n  { x: 0.859375, y: 0.515625 },\n  { x: 0.890625, y: 0.515625 },\n  { x: 0.890625, y: 0.515625 },\n  { x: 0.921875, y: 0.515625 },\n  { x: 0.921875, y: 0.515625 },\n  { x: 0.953125, y: 0.515625 },\n  { x: 0.953125, y: 0.515625 },\n  { x: 0.984375, y: 0.515625 },\n  { x: 0.984375, y: 0.515625 },\n  { x: 0.015625, y: 0.546875 },\n  { x: 0.015625, y: 0.546875 },\n  { x: 0.046875, y: 0.546875 },\n  { x: 0.046875, y: 0.546875 },\n  { x: 0.078125, y: 0.546875 },\n  { x: 0.078125, y: 0.546875 },\n  { x: 0.109375, y: 0.546875 },\n  { x: 0.109375, y: 0.546875 },\n  { x: 0.140625, y: 0.546875 },\n  { x: 0.140625, y: 0.546875 },\n  { x: 0.171875, y: 0.546875 },\n  { x: 0.171875, y: 0.546875 },\n  { x: 0.203125, y: 0.546875 },\n  { x: 0.203125, y: 0.546875 },\n  { x: 0.234375, y: 0.546875 },\n  { x: 0.234375, y: 0.546875 },\n  { x: 0.265625, y: 0.546875 },\n  { x: 0.265625, y: 0.546875 },\n  { x: 0.296875, y: 0.546875 },\n  { x: 0.296875, y: 0.546875 },\n  { x: 0.328125, y: 0.546875 },\n  { x: 0.328125, y: 0.546875 },\n  { x: 0.359375, y: 0.546875 },\n  { x: 0.359375, y: 0.546875 },\n  { x: 0.390625, y: 0.546875 },\n  { x: 0.390625, y: 0.546875 },\n  { x: 0.421875, y: 0.546875 },\n  { x: 0.421875, y: 0.546875 },\n  { x: 0.453125, y: 0.546875 },\n  { x: 0.453125, y: 0.546875 },\n  { x: 0.484375, y: 0.546875 },\n  { x: 0.484375, y: 0.546875 },\n  { x: 0.515625, y: 0.546875 },\n  { x: 0.515625, y: 0.546875 },\n  { x: 0.546875, y: 0.546875 },\n  { x: 0.546875, y: 0.546875 },\n  { x: 0.578125, y: 0.546875 },\n  { x: 0.578125, y: 0.546875 },\n  { x: 0.609375, y: 0.546875 },\n  { x: 0.609375, y: 0.546875 },\n  { x: 0.640625, y: 0.546875 },\n  { x: 0.640625, y: 0.546875 },\n  { x: 0.671875, y: 0.546875 },\n  { x: 0.671875, y: 0.546875 },\n  { x: 0.703125, y: 0.546875 },\n  { x: 0.703125, y: 0.546875 },\n  { x: 0.734375, y: 0.546875 },\n  { x: 0.734375, y: 0.546875 },\n  { x: 0.765625, y: 0.546875 },\n  { x: 0.765625, y: 0.546875 },\n  { x: 0.796875, y: 0.546875 },\n  { x: 0.796875, y: 0.546875 },\n  { x: 0.828125, y: 0.546875 },\n  { x: 0.828125, y: 0.546875 },\n  { x: 0.859375, y: 0.546875 },\n  { x: 0.859375, y: 0.546875 },\n  { x: 0.890625, y: 0.546875 },\n  { x: 0.890625, y: 0.546875 },\n  { x: 0.921875, y: 0.546875 },\n  { x: 0.921875, y: 0.546875 },\n  { x: 0.953125, y: 0.546875 },\n  { x: 0.953125, y: 0.546875 },\n  { x: 0.984375, y: 0.546875 },\n  { x: 0.984375, y: 0.546875 },\n  { x: 0.015625, y: 0.578125 },\n  { x: 0.015625, y: 0.578125 },\n  { x: 0.046875, y: 0.578125 },\n  { x: 0.046875, y: 0.578125 },\n  { x: 0.078125, y: 0.578125 },\n  { x: 0.078125, y: 0.578125 },\n  { x: 0.109375, y: 0.578125 },\n  { x: 0.109375, y: 0.578125 },\n  { x: 0.140625, y: 0.578125 },\n  { x: 0.140625, y: 0.578125 },\n  { x: 0.171875, y: 0.578125 },\n  { x: 0.171875, y: 0.578125 },\n  { x: 0.203125, y: 0.578125 },\n  { x: 0.203125, y: 0.578125 },\n  { x: 0.234375, y: 0.578125 },\n  { x: 0.234375, y: 0.578125 },\n  { x: 0.265625, y: 0.578125 },\n  { x: 0.265625, y: 0.578125 },\n  { x: 0.296875, y: 0.578125 },\n  { x: 0.296875, y: 0.578125 },\n  { x: 0.328125, y: 0.578125 },\n  { x: 0.328125, y: 0.578125 },\n  { x: 0.359375, y: 0.578125 },\n  { x: 0.359375, y: 0.578125 },\n  { x: 0.390625, y: 0.578125 },\n  { x: 0.390625, y: 0.578125 },\n  { x: 0.421875, y: 0.578125 },\n  { x: 0.421875, y: 0.578125 },\n  { x: 0.453125, y: 0.578125 },\n  { x: 0.453125, y: 0.578125 },\n  { x: 0.484375, y: 0.578125 },\n  { x: 0.484375, y: 0.578125 },\n  { x: 0.515625, y: 0.578125 },\n  { x: 0.515625, y: 0.578125 },\n  { x: 0.546875, y: 0.578125 },\n  { x: 0.546875, y: 0.578125 },\n  { x: 0.578125, y: 0.578125 },\n  { x: 0.578125, y: 0.578125 },\n  { x: 0.609375, y: 0.578125 },\n  { x: 0.609375, y: 0.578125 },\n  { x: 0.640625, y: 0.578125 },\n  { x: 0.640625, y: 0.578125 },\n  { x: 0.671875, y: 0.578125 },\n  { x: 0.671875, y: 0.578125 },\n  { x: 0.703125, y: 0.578125 },\n  { x: 0.703125, y: 0.578125 },\n  { x: 0.734375, y: 0.578125 },\n  { x: 0.734375, y: 0.578125 },\n  { x: 0.765625, y: 0.578125 },\n  { x: 0.765625, y: 0.578125 },\n  { x: 0.796875, y: 0.578125 },\n  { x: 0.796875, y: 0.578125 },\n  { x: 0.828125, y: 0.578125 },\n  { x: 0.828125, y: 0.578125 },\n  { x: 0.859375, y: 0.578125 },\n  { x: 0.859375, y: 0.578125 },\n  { x: 0.890625, y: 0.578125 },\n  { x: 0.890625, y: 0.578125 },\n  { x: 0.921875, y: 0.578125 },\n  { x: 0.921875, y: 0.578125 },\n  { x: 0.953125, y: 0.578125 },\n  { x: 0.953125, y: 0.578125 },\n  { x: 0.984375, y: 0.578125 },\n  { x: 0.984375, y: 0.578125 },\n  { x: 0.015625, y: 0.609375 },\n  { x: 0.015625, y: 0.609375 },\n  { x: 0.046875, y: 0.609375 },\n  { x: 0.046875, y: 0.609375 },\n  { x: 0.078125, y: 0.609375 },\n  { x: 0.078125, y: 0.609375 },\n  { x: 0.109375, y: 0.609375 },\n  { x: 0.109375, y: 0.609375 },\n  { x: 0.140625, y: 0.609375 },\n  { x: 0.140625, y: 0.609375 },\n  { x: 0.171875, y: 0.609375 },\n  { x: 0.171875, y: 0.609375 },\n  { x: 0.203125, y: 0.609375 },\n  { x: 0.203125, y: 0.609375 },\n  { x: 0.234375, y: 0.609375 },\n  { x: 0.234375, y: 0.609375 },\n  { x: 0.265625, y: 0.609375 },\n  { x: 0.265625, y: 0.609375 },\n  { x: 0.296875, y: 0.609375 },\n  { x: 0.296875, y: 0.609375 },\n  { x: 0.328125, y: 0.609375 },\n  { x: 0.328125, y: 0.609375 },\n  { x: 0.359375, y: 0.609375 },\n  { x: 0.359375, y: 0.609375 },\n  { x: 0.390625, y: 0.609375 },\n  { x: 0.390625, y: 0.609375 },\n  { x: 0.421875, y: 0.609375 },\n  { x: 0.421875, y: 0.609375 },\n  { x: 0.453125, y: 0.609375 },\n  { x: 0.453125, y: 0.609375 },\n  { x: 0.484375, y: 0.609375 },\n  { x: 0.484375, y: 0.609375 },\n  { x: 0.515625, y: 0.609375 },\n  { x: 0.515625, y: 0.609375 },\n  { x: 0.546875, y: 0.609375 },\n  { x: 0.546875, y: 0.609375 },\n  { x: 0.578125, y: 0.609375 },\n  { x: 0.578125, y: 0.609375 },\n  { x: 0.609375, y: 0.609375 },\n  { x: 0.609375, y: 0.609375 },\n  { x: 0.640625, y: 0.609375 },\n  { x: 0.640625, y: 0.609375 },\n  { x: 0.671875, y: 0.609375 },\n  { x: 0.671875, y: 0.609375 },\n  { x: 0.703125, y: 0.609375 },\n  { x: 0.703125, y: 0.609375 },\n  { x: 0.734375, y: 0.609375 },\n  { x: 0.734375, y: 0.609375 },\n  { x: 0.765625, y: 0.609375 },\n  { x: 0.765625, y: 0.609375 },\n  { x: 0.796875, y: 0.609375 },\n  { x: 0.796875, y: 0.609375 },\n  { x: 0.828125, y: 0.609375 },\n  { x: 0.828125, y: 0.609375 },\n  { x: 0.859375, y: 0.609375 },\n  { x: 0.859375, y: 0.609375 },\n  { x: 0.890625, y: 0.609375 },\n  { x: 0.890625, y: 0.609375 },\n  { x: 0.921875, y: 0.609375 },\n  { x: 0.921875, y: 0.609375 },\n  { x: 0.953125, y: 0.609375 },\n  { x: 0.953125, y: 0.609375 },\n  { x: 0.984375, y: 0.609375 },\n  { x: 0.984375, y: 0.609375 },\n  { x: 0.015625, y: 0.640625 },\n  { x: 0.015625, y: 0.640625 },\n  { x: 0.046875, y: 0.640625 },\n  { x: 0.046875, y: 0.640625 },\n  { x: 0.078125, y: 0.640625 },\n  { x: 0.078125, y: 0.640625 },\n  { x: 0.109375, y: 0.640625 },\n  { x: 0.109375, y: 0.640625 },\n  { x: 0.140625, y: 0.640625 },\n  { x: 0.140625, y: 0.640625 },\n  { x: 0.171875, y: 0.640625 },\n  { x: 0.171875, y: 0.640625 },\n  { x: 0.203125, y: 0.640625 },\n  { x: 0.203125, y: 0.640625 },\n  { x: 0.234375, y: 0.640625 },\n  { x: 0.234375, y: 0.640625 },\n  { x: 0.265625, y: 0.640625 },\n  { x: 0.265625, y: 0.640625 },\n  { x: 0.296875, y: 0.640625 },\n  { x: 0.296875, y: 0.640625 },\n  { x: 0.328125, y: 0.640625 },\n  { x: 0.328125, y: 0.640625 },\n  { x: 0.359375, y: 0.640625 },\n  { x: 0.359375, y: 0.640625 },\n  { x: 0.390625, y: 0.640625 },\n  { x: 0.390625, y: 0.640625 },\n  { x: 0.421875, y: 0.640625 },\n  { x: 0.421875, y: 0.640625 },\n  { x: 0.453125, y: 0.640625 },\n  { x: 0.453125, y: 0.640625 },\n  { x: 0.484375, y: 0.640625 },\n  { x: 0.484375, y: 0.640625 },\n  { x: 0.515625, y: 0.640625 },\n  { x: 0.515625, y: 0.640625 },\n  { x: 0.546875, y: 0.640625 },\n  { x: 0.546875, y: 0.640625 },\n  { x: 0.578125, y: 0.640625 },\n  { x: 0.578125, y: 0.640625 },\n  { x: 0.609375, y: 0.640625 },\n  { x: 0.609375, y: 0.640625 },\n  { x: 0.640625, y: 0.640625 },\n  { x: 0.640625, y: 0.640625 },\n  { x: 0.671875, y: 0.640625 },\n  { x: 0.671875, y: 0.640625 },\n  { x: 0.703125, y: 0.640625 },\n  { x: 0.703125, y: 0.640625 },\n  { x: 0.734375, y: 0.640625 },\n  { x: 0.734375, y: 0.640625 },\n  { x: 0.765625, y: 0.640625 },\n  { x: 0.765625, y: 0.640625 },\n  { x: 0.796875, y: 0.640625 },\n  { x: 0.796875, y: 0.640625 },\n  { x: 0.828125, y: 0.640625 },\n  { x: 0.828125, y: 0.640625 },\n  { x: 0.859375, y: 0.640625 },\n  { x: 0.859375, y: 0.640625 },\n  { x: 0.890625, y: 0.640625 },\n  { x: 0.890625, y: 0.640625 },\n  { x: 0.921875, y: 0.640625 },\n  { x: 0.921875, y: 0.640625 },\n  { x: 0.953125, y: 0.640625 },\n  { x: 0.953125, y: 0.640625 },\n  { x: 0.984375, y: 0.640625 },\n  { x: 0.984375, y: 0.640625 },\n  { x: 0.015625, y: 0.671875 },\n  { x: 0.015625, y: 0.671875 },\n  { x: 0.046875, y: 0.671875 },\n  { x: 0.046875, y: 0.671875 },\n  { x: 0.078125, y: 0.671875 },\n  { x: 0.078125, y: 0.671875 },\n  { x: 0.109375, y: 0.671875 },\n  { x: 0.109375, y: 0.671875 },\n  { x: 0.140625, y: 0.671875 },\n  { x: 0.140625, y: 0.671875 },\n  { x: 0.171875, y: 0.671875 },\n  { x: 0.171875, y: 0.671875 },\n  { x: 0.203125, y: 0.671875 },\n  { x: 0.203125, y: 0.671875 },\n  { x: 0.234375, y: 0.671875 },\n  { x: 0.234375, y: 0.671875 },\n  { x: 0.265625, y: 0.671875 },\n  { x: 0.265625, y: 0.671875 },\n  { x: 0.296875, y: 0.671875 },\n  { x: 0.296875, y: 0.671875 },\n  { x: 0.328125, y: 0.671875 },\n  { x: 0.328125, y: 0.671875 },\n  { x: 0.359375, y: 0.671875 },\n  { x: 0.359375, y: 0.671875 },\n  { x: 0.390625, y: 0.671875 },\n  { x: 0.390625, y: 0.671875 },\n  { x: 0.421875, y: 0.671875 },\n  { x: 0.421875, y: 0.671875 },\n  { x: 0.453125, y: 0.671875 },\n  { x: 0.453125, y: 0.671875 },\n  { x: 0.484375, y: 0.671875 },\n  { x: 0.484375, y: 0.671875 },\n  { x: 0.515625, y: 0.671875 },\n  { x: 0.515625, y: 0.671875 },\n  { x: 0.546875, y: 0.671875 },\n  { x: 0.546875, y: 0.671875 },\n  { x: 0.578125, y: 0.671875 },\n  { x: 0.578125, y: 0.671875 },\n  { x: 0.609375, y: 0.671875 },\n  { x: 0.609375, y: 0.671875 },\n  { x: 0.640625, y: 0.671875 },\n  { x: 0.640625, y: 0.671875 },\n  { x: 0.671875, y: 0.671875 },\n  { x: 0.671875, y: 0.671875 },\n  { x: 0.703125, y: 0.671875 },\n  { x: 0.703125, y: 0.671875 },\n  { x: 0.734375, y: 0.671875 },\n  { x: 0.734375, y: 0.671875 },\n  { x: 0.765625, y: 0.671875 },\n  { x: 0.765625, y: 0.671875 },\n  { x: 0.796875, y: 0.671875 },\n  { x: 0.796875, y: 0.671875 },\n  { x: 0.828125, y: 0.671875 },\n  { x: 0.828125, y: 0.671875 },\n  { x: 0.859375, y: 0.671875 },\n  { x: 0.859375, y: 0.671875 },\n  { x: 0.890625, y: 0.671875 },\n  { x: 0.890625, y: 0.671875 },\n  { x: 0.921875, y: 0.671875 },\n  { x: 0.921875, y: 0.671875 },\n  { x: 0.953125, y: 0.671875 },\n  { x: 0.953125, y: 0.671875 },\n  { x: 0.984375, y: 0.671875 },\n  { x: 0.984375, y: 0.671875 },\n  { x: 0.015625, y: 0.703125 },\n  { x: 0.015625, y: 0.703125 },\n  { x: 0.046875, y: 0.703125 },\n  { x: 0.046875, y: 0.703125 },\n  { x: 0.078125, y: 0.703125 },\n  { x: 0.078125, y: 0.703125 },\n  { x: 0.109375, y: 0.703125 },\n  { x: 0.109375, y: 0.703125 },\n  { x: 0.140625, y: 0.703125 },\n  { x: 0.140625, y: 0.703125 },\n  { x: 0.171875, y: 0.703125 },\n  { x: 0.171875, y: 0.703125 },\n  { x: 0.203125, y: 0.703125 },\n  { x: 0.203125, y: 0.703125 },\n  { x: 0.234375, y: 0.703125 },\n  { x: 0.234375, y: 0.703125 },\n  { x: 0.265625, y: 0.703125 },\n  { x: 0.265625, y: 0.703125 },\n  { x: 0.296875, y: 0.703125 },\n  { x: 0.296875, y: 0.703125 },\n  { x: 0.328125, y: 0.703125 },\n  { x: 0.328125, y: 0.703125 },\n  { x: 0.359375, y: 0.703125 },\n  { x: 0.359375, y: 0.703125 },\n  { x: 0.390625, y: 0.703125 },\n  { x: 0.390625, y: 0.703125 },\n  { x: 0.421875, y: 0.703125 },\n  { x: 0.421875, y: 0.703125 },\n  { x: 0.453125, y: 0.703125 },\n  { x: 0.453125, y: 0.703125 },\n  { x: 0.484375, y: 0.703125 },\n  { x: 0.484375, y: 0.703125 },\n  { x: 0.515625, y: 0.703125 },\n  { x: 0.515625, y: 0.703125 },\n  { x: 0.546875, y: 0.703125 },\n  { x: 0.546875, y: 0.703125 },\n  { x: 0.578125, y: 0.703125 },\n  { x: 0.578125, y: 0.703125 },\n  { x: 0.609375, y: 0.703125 },\n  { x: 0.609375, y: 0.703125 },\n  { x: 0.640625, y: 0.703125 },\n  { x: 0.640625, y: 0.703125 },\n  { x: 0.671875, y: 0.703125 },\n  { x: 0.671875, y: 0.703125 },\n  { x: 0.703125, y: 0.703125 },\n  { x: 0.703125, y: 0.703125 },\n  { x: 0.734375, y: 0.703125 },\n  { x: 0.734375, y: 0.703125 },\n  { x: 0.765625, y: 0.703125 },\n  { x: 0.765625, y: 0.703125 },\n  { x: 0.796875, y: 0.703125 },\n  { x: 0.796875, y: 0.703125 },\n  { x: 0.828125, y: 0.703125 },\n  { x: 0.828125, y: 0.703125 },\n  { x: 0.859375, y: 0.703125 },\n  { x: 0.859375, y: 0.703125 },\n  { x: 0.890625, y: 0.703125 },\n  { x: 0.890625, y: 0.703125 },\n  { x: 0.921875, y: 0.703125 },\n  { x: 0.921875, y: 0.703125 },\n  { x: 0.953125, y: 0.703125 },\n  { x: 0.953125, y: 0.703125 },\n  { x: 0.984375, y: 0.703125 },\n  { x: 0.984375, y: 0.703125 },\n  { x: 0.015625, y: 0.734375 },\n  { x: 0.015625, y: 0.734375 },\n  { x: 0.046875, y: 0.734375 },\n  { x: 0.046875, y: 0.734375 },\n  { x: 0.078125, y: 0.734375 },\n  { x: 0.078125, y: 0.734375 },\n  { x: 0.109375, y: 0.734375 },\n  { x: 0.109375, y: 0.734375 },\n  { x: 0.140625, y: 0.734375 },\n  { x: 0.140625, y: 0.734375 },\n  { x: 0.171875, y: 0.734375 },\n  { x: 0.171875, y: 0.734375 },\n  { x: 0.203125, y: 0.734375 },\n  { x: 0.203125, y: 0.734375 },\n  { x: 0.234375, y: 0.734375 },\n  { x: 0.234375, y: 0.734375 },\n  { x: 0.265625, y: 0.734375 },\n  { x: 0.265625, y: 0.734375 },\n  { x: 0.296875, y: 0.734375 },\n  { x: 0.296875, y: 0.734375 },\n  { x: 0.328125, y: 0.734375 },\n  { x: 0.328125, y: 0.734375 },\n  { x: 0.359375, y: 0.734375 },\n  { x: 0.359375, y: 0.734375 },\n  { x: 0.390625, y: 0.734375 },\n  { x: 0.390625, y: 0.734375 },\n  { x: 0.421875, y: 0.734375 },\n  { x: 0.421875, y: 0.734375 },\n  { x: 0.453125, y: 0.734375 },\n  { x: 0.453125, y: 0.734375 },\n  { x: 0.484375, y: 0.734375 },\n  { x: 0.484375, y: 0.734375 },\n  { x: 0.515625, y: 0.734375 },\n  { x: 0.515625, y: 0.734375 },\n  { x: 0.546875, y: 0.734375 },\n  { x: 0.546875, y: 0.734375 },\n  { x: 0.578125, y: 0.734375 },\n  { x: 0.578125, y: 0.734375 },\n  { x: 0.609375, y: 0.734375 },\n  { x: 0.609375, y: 0.734375 },\n  { x: 0.640625, y: 0.734375 },\n  { x: 0.640625, y: 0.734375 },\n  { x: 0.671875, y: 0.734375 },\n  { x: 0.671875, y: 0.734375 },\n  { x: 0.703125, y: 0.734375 },\n  { x: 0.703125, y: 0.734375 },\n  { x: 0.734375, y: 0.734375 },\n  { x: 0.734375, y: 0.734375 },\n  { x: 0.765625, y: 0.734375 },\n  { x: 0.765625, y: 0.734375 },\n  { x: 0.796875, y: 0.734375 },\n  { x: 0.796875, y: 0.734375 },\n  { x: 0.828125, y: 0.734375 },\n  { x: 0.828125, y: 0.734375 },\n  { x: 0.859375, y: 0.734375 },\n  { x: 0.859375, y: 0.734375 },\n  { x: 0.890625, y: 0.734375 },\n  { x: 0.890625, y: 0.734375 },\n  { x: 0.921875, y: 0.734375 },\n  { x: 0.921875, y: 0.734375 },\n  { x: 0.953125, y: 0.734375 },\n  { x: 0.953125, y: 0.734375 },\n  { x: 0.984375, y: 0.734375 },\n  { x: 0.984375, y: 0.734375 },\n  { x: 0.015625, y: 0.765625 },\n  { x: 0.015625, y: 0.765625 },\n  { x: 0.046875, y: 0.765625 },\n  { x: 0.046875, y: 0.765625 },\n  { x: 0.078125, y: 0.765625 },\n  { x: 0.078125, y: 0.765625 },\n  { x: 0.109375, y: 0.765625 },\n  { x: 0.109375, y: 0.765625 },\n  { x: 0.140625, y: 0.765625 },\n  { x: 0.140625, y: 0.765625 },\n  { x: 0.171875, y: 0.765625 },\n  { x: 0.171875, y: 0.765625 },\n  { x: 0.203125, y: 0.765625 },\n  { x: 0.203125, y: 0.765625 },\n  { x: 0.234375, y: 0.765625 },\n  { x: 0.234375, y: 0.765625 },\n  { x: 0.265625, y: 0.765625 },\n  { x: 0.265625, y: 0.765625 },\n  { x: 0.296875, y: 0.765625 },\n  { x: 0.296875, y: 0.765625 },\n  { x: 0.328125, y: 0.765625 },\n  { x: 0.328125, y: 0.765625 },\n  { x: 0.359375, y: 0.765625 },\n  { x: 0.359375, y: 0.765625 },\n  { x: 0.390625, y: 0.765625 },\n  { x: 0.390625, y: 0.765625 },\n  { x: 0.421875, y: 0.765625 },\n  { x: 0.421875, y: 0.765625 },\n  { x: 0.453125, y: 0.765625 },\n  { x: 0.453125, y: 0.765625 },\n  { x: 0.484375, y: 0.765625 },\n  { x: 0.484375, y: 0.765625 },\n  { x: 0.515625, y: 0.765625 },\n  { x: 0.515625, y: 0.765625 },\n  { x: 0.546875, y: 0.765625 },\n  { x: 0.546875, y: 0.765625 },\n  { x: 0.578125, y: 0.765625 },\n  { x: 0.578125, y: 0.765625 },\n  { x: 0.609375, y: 0.765625 },\n  { x: 0.609375, y: 0.765625 },\n  { x: 0.640625, y: 0.765625 },\n  { x: 0.640625, y: 0.765625 },\n  { x: 0.671875, y: 0.765625 },\n  { x: 0.671875, y: 0.765625 },\n  { x: 0.703125, y: 0.765625 },\n  { x: 0.703125, y: 0.765625 },\n  { x: 0.734375, y: 0.765625 },\n  { x: 0.734375, y: 0.765625 },\n  { x: 0.765625, y: 0.765625 },\n  { x: 0.765625, y: 0.765625 },\n  { x: 0.796875, y: 0.765625 },\n  { x: 0.796875, y: 0.765625 },\n  { x: 0.828125, y: 0.765625 },\n  { x: 0.828125, y: 0.765625 },\n  { x: 0.859375, y: 0.765625 },\n  { x: 0.859375, y: 0.765625 },\n  { x: 0.890625, y: 0.765625 },\n  { x: 0.890625, y: 0.765625 },\n  { x: 0.921875, y: 0.765625 },\n  { x: 0.921875, y: 0.765625 },\n  { x: 0.953125, y: 0.765625 },\n  { x: 0.953125, y: 0.765625 },\n  { x: 0.984375, y: 0.765625 },\n  { x: 0.984375, y: 0.765625 },\n  { x: 0.015625, y: 0.796875 },\n  { x: 0.015625, y: 0.796875 },\n  { x: 0.046875, y: 0.796875 },\n  { x: 0.046875, y: 0.796875 },\n  { x: 0.078125, y: 0.796875 },\n  { x: 0.078125, y: 0.796875 },\n  { x: 0.109375, y: 0.796875 },\n  { x: 0.109375, y: 0.796875 },\n  { x: 0.140625, y: 0.796875 },\n  { x: 0.140625, y: 0.796875 },\n  { x: 0.171875, y: 0.796875 },\n  { x: 0.171875, y: 0.796875 },\n  { x: 0.203125, y: 0.796875 },\n  { x: 0.203125, y: 0.796875 },\n  { x: 0.234375, y: 0.796875 },\n  { x: 0.234375, y: 0.796875 },\n  { x: 0.265625, y: 0.796875 },\n  { x: 0.265625, y: 0.796875 },\n  { x: 0.296875, y: 0.796875 },\n  { x: 0.296875, y: 0.796875 },\n  { x: 0.328125, y: 0.796875 },\n  { x: 0.328125, y: 0.796875 },\n  { x: 0.359375, y: 0.796875 },\n  { x: 0.359375, y: 0.796875 },\n  { x: 0.390625, y: 0.796875 },\n  { x: 0.390625, y: 0.796875 },\n  { x: 0.421875, y: 0.796875 },\n  { x: 0.421875, y: 0.796875 },\n  { x: 0.453125, y: 0.796875 },\n  { x: 0.453125, y: 0.796875 },\n  { x: 0.484375, y: 0.796875 },\n  { x: 0.484375, y: 0.796875 },\n  { x: 0.515625, y: 0.796875 },\n  { x: 0.515625, y: 0.796875 },\n  { x: 0.546875, y: 0.796875 },\n  { x: 0.546875, y: 0.796875 },\n  { x: 0.578125, y: 0.796875 },\n  { x: 0.578125, y: 0.796875 },\n  { x: 0.609375, y: 0.796875 },\n  { x: 0.609375, y: 0.796875 },\n  { x: 0.640625, y: 0.796875 },\n  { x: 0.640625, y: 0.796875 },\n  { x: 0.671875, y: 0.796875 },\n  { x: 0.671875, y: 0.796875 },\n  { x: 0.703125, y: 0.796875 },\n  { x: 0.703125, y: 0.796875 },\n  { x: 0.734375, y: 0.796875 },\n  { x: 0.734375, y: 0.796875 },\n  { x: 0.765625, y: 0.796875 },\n  { x: 0.765625, y: 0.796875 },\n  { x: 0.796875, y: 0.796875 },\n  { x: 0.796875, y: 0.796875 },\n  { x: 0.828125, y: 0.796875 },\n  { x: 0.828125, y: 0.796875 },\n  { x: 0.859375, y: 0.796875 },\n  { x: 0.859375, y: 0.796875 },\n  { x: 0.890625, y: 0.796875 },\n  { x: 0.890625, y: 0.796875 },\n  { x: 0.921875, y: 0.796875 },\n  { x: 0.921875, y: 0.796875 },\n  { x: 0.953125, y: 0.796875 },\n  { x: 0.953125, y: 0.796875 },\n  { x: 0.984375, y: 0.796875 },\n  { x: 0.984375, y: 0.796875 },\n  { x: 0.015625, y: 0.828125 },\n  { x: 0.015625, y: 0.828125 },\n  { x: 0.046875, y: 0.828125 },\n  { x: 0.046875, y: 0.828125 },\n  { x: 0.078125, y: 0.828125 },\n  { x: 0.078125, y: 0.828125 },\n  { x: 0.109375, y: 0.828125 },\n  { x: 0.109375, y: 0.828125 },\n  { x: 0.140625, y: 0.828125 },\n  { x: 0.140625, y: 0.828125 },\n  { x: 0.171875, y: 0.828125 },\n  { x: 0.171875, y: 0.828125 },\n  { x: 0.203125, y: 0.828125 },\n  { x: 0.203125, y: 0.828125 },\n  { x: 0.234375, y: 0.828125 },\n  { x: 0.234375, y: 0.828125 },\n  { x: 0.265625, y: 0.828125 },\n  { x: 0.265625, y: 0.828125 },\n  { x: 0.296875, y: 0.828125 },\n  { x: 0.296875, y: 0.828125 },\n  { x: 0.328125, y: 0.828125 },\n  { x: 0.328125, y: 0.828125 },\n  { x: 0.359375, y: 0.828125 },\n  { x: 0.359375, y: 0.828125 },\n  { x: 0.390625, y: 0.828125 },\n  { x: 0.390625, y: 0.828125 },\n  { x: 0.421875, y: 0.828125 },\n  { x: 0.421875, y: 0.828125 },\n  { x: 0.453125, y: 0.828125 },\n  { x: 0.453125, y: 0.828125 },\n  { x: 0.484375, y: 0.828125 },\n  { x: 0.484375, y: 0.828125 },\n  { x: 0.515625, y: 0.828125 },\n  { x: 0.515625, y: 0.828125 },\n  { x: 0.546875, y: 0.828125 },\n  { x: 0.546875, y: 0.828125 },\n  { x: 0.578125, y: 0.828125 },\n  { x: 0.578125, y: 0.828125 },\n  { x: 0.609375, y: 0.828125 },\n  { x: 0.609375, y: 0.828125 },\n  { x: 0.640625, y: 0.828125 },\n  { x: 0.640625, y: 0.828125 },\n  { x: 0.671875, y: 0.828125 },\n  { x: 0.671875, y: 0.828125 },\n  { x: 0.703125, y: 0.828125 },\n  { x: 0.703125, y: 0.828125 },\n  { x: 0.734375, y: 0.828125 },\n  { x: 0.734375, y: 0.828125 },\n  { x: 0.765625, y: 0.828125 },\n  { x: 0.765625, y: 0.828125 },\n  { x: 0.796875, y: 0.828125 },\n  { x: 0.796875, y: 0.828125 },\n  { x: 0.828125, y: 0.828125 },\n  { x: 0.828125, y: 0.828125 },\n  { x: 0.859375, y: 0.828125 },\n  { x: 0.859375, y: 0.828125 },\n  { x: 0.890625, y: 0.828125 },\n  { x: 0.890625, y: 0.828125 },\n  { x: 0.921875, y: 0.828125 },\n  { x: 0.921875, y: 0.828125 },\n  { x: 0.953125, y: 0.828125 },\n  { x: 0.953125, y: 0.828125 },\n  { x: 0.984375, y: 0.828125 },\n  { x: 0.984375, y: 0.828125 },\n  { x: 0.015625, y: 0.859375 },\n  { x: 0.015625, y: 0.859375 },\n  { x: 0.046875, y: 0.859375 },\n  { x: 0.046875, y: 0.859375 },\n  { x: 0.078125, y: 0.859375 },\n  { x: 0.078125, y: 0.859375 },\n  { x: 0.109375, y: 0.859375 },\n  { x: 0.109375, y: 0.859375 },\n  { x: 0.140625, y: 0.859375 },\n  { x: 0.140625, y: 0.859375 },\n  { x: 0.171875, y: 0.859375 },\n  { x: 0.171875, y: 0.859375 },\n  { x: 0.203125, y: 0.859375 },\n  { x: 0.203125, y: 0.859375 },\n  { x: 0.234375, y: 0.859375 },\n  { x: 0.234375, y: 0.859375 },\n  { x: 0.265625, y: 0.859375 },\n  { x: 0.265625, y: 0.859375 },\n  { x: 0.296875, y: 0.859375 },\n  { x: 0.296875, y: 0.859375 },\n  { x: 0.328125, y: 0.859375 },\n  { x: 0.328125, y: 0.859375 },\n  { x: 0.359375, y: 0.859375 },\n  { x: 0.359375, y: 0.859375 },\n  { x: 0.390625, y: 0.859375 },\n  { x: 0.390625, y: 0.859375 },\n  { x: 0.421875, y: 0.859375 },\n  { x: 0.421875, y: 0.859375 },\n  { x: 0.453125, y: 0.859375 },\n  { x: 0.453125, y: 0.859375 },\n  { x: 0.484375, y: 0.859375 },\n  { x: 0.484375, y: 0.859375 },\n  { x: 0.515625, y: 0.859375 },\n  { x: 0.515625, y: 0.859375 },\n  { x: 0.546875, y: 0.859375 },\n  { x: 0.546875, y: 0.859375 },\n  { x: 0.578125, y: 0.859375 },\n  { x: 0.578125, y: 0.859375 },\n  { x: 0.609375, y: 0.859375 },\n  { x: 0.609375, y: 0.859375 },\n  { x: 0.640625, y: 0.859375 },\n  { x: 0.640625, y: 0.859375 },\n  { x: 0.671875, y: 0.859375 },\n  { x: 0.671875, y: 0.859375 },\n  { x: 0.703125, y: 0.859375 },\n  { x: 0.703125, y: 0.859375 },\n  { x: 0.734375, y: 0.859375 },\n  { x: 0.734375, y: 0.859375 },\n  { x: 0.765625, y: 0.859375 },\n  { x: 0.765625, y: 0.859375 },\n  { x: 0.796875, y: 0.859375 },\n  { x: 0.796875, y: 0.859375 },\n  { x: 0.828125, y: 0.859375 },\n  { x: 0.828125, y: 0.859375 },\n  { x: 0.859375, y: 0.859375 },\n  { x: 0.859375, y: 0.859375 },\n  { x: 0.890625, y: 0.859375 },\n  { x: 0.890625, y: 0.859375 },\n  { x: 0.921875, y: 0.859375 },\n  { x: 0.921875, y: 0.859375 },\n  { x: 0.953125, y: 0.859375 },\n  { x: 0.953125, y: 0.859375 },\n  { x: 0.984375, y: 0.859375 },\n  { x: 0.984375, y: 0.859375 },\n  { x: 0.015625, y: 0.890625 },\n  { x: 0.015625, y: 0.890625 },\n  { x: 0.046875, y: 0.890625 },\n  { x: 0.046875, y: 0.890625 },\n  { x: 0.078125, y: 0.890625 },\n  { x: 0.078125, y: 0.890625 },\n  { x: 0.109375, y: 0.890625 },\n  { x: 0.109375, y: 0.890625 },\n  { x: 0.140625, y: 0.890625 },\n  { x: 0.140625, y: 0.890625 },\n  { x: 0.171875, y: 0.890625 },\n  { x: 0.171875, y: 0.890625 },\n  { x: 0.203125, y: 0.890625 },\n  { x: 0.203125, y: 0.890625 },\n  { x: 0.234375, y: 0.890625 },\n  { x: 0.234375, y: 0.890625 },\n  { x: 0.265625, y: 0.890625 },\n  { x: 0.265625, y: 0.890625 },\n  { x: 0.296875, y: 0.890625 },\n  { x: 0.296875, y: 0.890625 },\n  { x: 0.328125, y: 0.890625 },\n  { x: 0.328125, y: 0.890625 },\n  { x: 0.359375, y: 0.890625 },\n  { x: 0.359375, y: 0.890625 },\n  { x: 0.390625, y: 0.890625 },\n  { x: 0.390625, y: 0.890625 },\n  { x: 0.421875, y: 0.890625 },\n  { x: 0.421875, y: 0.890625 },\n  { x: 0.453125, y: 0.890625 },\n  { x: 0.453125, y: 0.890625 },\n  { x: 0.484375, y: 0.890625 },\n  { x: 0.484375, y: 0.890625 },\n  { x: 0.515625, y: 0.890625 },\n  { x: 0.515625, y: 0.890625 },\n  { x: 0.546875, y: 0.890625 },\n  { x: 0.546875, y: 0.890625 },\n  { x: 0.578125, y: 0.890625 },\n  { x: 0.578125, y: 0.890625 },\n  { x: 0.609375, y: 0.890625 },\n  { x: 0.609375, y: 0.890625 },\n  { x: 0.640625, y: 0.890625 },\n  { x: 0.640625, y: 0.890625 },\n  { x: 0.671875, y: 0.890625 },\n  { x: 0.671875, y: 0.890625 },\n  { x: 0.703125, y: 0.890625 },\n  { x: 0.703125, y: 0.890625 },\n  { x: 0.734375, y: 0.890625 },\n  { x: 0.734375, y: 0.890625 },\n  { x: 0.765625, y: 0.890625 },\n  { x: 0.765625, y: 0.890625 },\n  { x: 0.796875, y: 0.890625 },\n  { x: 0.796875, y: 0.890625 },\n  { x: 0.828125, y: 0.890625 },\n  { x: 0.828125, y: 0.890625 },\n  { x: 0.859375, y: 0.890625 },\n  { x: 0.859375, y: 0.890625 },\n  { x: 0.890625, y: 0.890625 },\n  { x: 0.890625, y: 0.890625 },\n  { x: 0.921875, y: 0.890625 },\n  { x: 0.921875, y: 0.890625 },\n  { x: 0.953125, y: 0.890625 },\n  { x: 0.953125, y: 0.890625 },\n  { x: 0.984375, y: 0.890625 },\n  { x: 0.984375, y: 0.890625 },\n  { x: 0.015625, y: 0.921875 },\n  { x: 0.015625, y: 0.921875 },\n  { x: 0.046875, y: 0.921875 },\n  { x: 0.046875, y: 0.921875 },\n  { x: 0.078125, y: 0.921875 },\n  { x: 0.078125, y: 0.921875 },\n  { x: 0.109375, y: 0.921875 },\n  { x: 0.109375, y: 0.921875 },\n  { x: 0.140625, y: 0.921875 },\n  { x: 0.140625, y: 0.921875 },\n  { x: 0.171875, y: 0.921875 },\n  { x: 0.171875, y: 0.921875 },\n  { x: 0.203125, y: 0.921875 },\n  { x: 0.203125, y: 0.921875 },\n  { x: 0.234375, y: 0.921875 },\n  { x: 0.234375, y: 0.921875 },\n  { x: 0.265625, y: 0.921875 },\n  { x: 0.265625, y: 0.921875 },\n  { x: 0.296875, y: 0.921875 },\n  { x: 0.296875, y: 0.921875 },\n  { x: 0.328125, y: 0.921875 },\n  { x: 0.328125, y: 0.921875 },\n  { x: 0.359375, y: 0.921875 },\n  { x: 0.359375, y: 0.921875 },\n  { x: 0.390625, y: 0.921875 },\n  { x: 0.390625, y: 0.921875 },\n  { x: 0.421875, y: 0.921875 },\n  { x: 0.421875, y: 0.921875 },\n  { x: 0.453125, y: 0.921875 },\n  { x: 0.453125, y: 0.921875 },\n  { x: 0.484375, y: 0.921875 },\n  { x: 0.484375, y: 0.921875 },\n  { x: 0.515625, y: 0.921875 },\n  { x: 0.515625, y: 0.921875 },\n  { x: 0.546875, y: 0.921875 },\n  { x: 0.546875, y: 0.921875 },\n  { x: 0.578125, y: 0.921875 },\n  { x: 0.578125, y: 0.921875 },\n  { x: 0.609375, y: 0.921875 },\n  { x: 0.609375, y: 0.921875 },\n  { x: 0.640625, y: 0.921875 },\n  { x: 0.640625, y: 0.921875 },\n  { x: 0.671875, y: 0.921875 },\n  { x: 0.671875, y: 0.921875 },\n  { x: 0.703125, y: 0.921875 },\n  { x: 0.703125, y: 0.921875 },\n  { x: 0.734375, y: 0.921875 },\n  { x: 0.734375, y: 0.921875 },\n  { x: 0.765625, y: 0.921875 },\n  { x: 0.765625, y: 0.921875 },\n  { x: 0.796875, y: 0.921875 },\n  { x: 0.796875, y: 0.921875 },\n  { x: 0.828125, y: 0.921875 },\n  { x: 0.828125, y: 0.921875 },\n  { x: 0.859375, y: 0.921875 },\n  { x: 0.859375, y: 0.921875 },\n  { x: 0.890625, y: 0.921875 },\n  { x: 0.890625, y: 0.921875 },\n  { x: 0.921875, y: 0.921875 },\n  { x: 0.921875, y: 0.921875 },\n  { x: 0.953125, y: 0.921875 },\n  { x: 0.953125, y: 0.921875 },\n  { x: 0.984375, y: 0.921875 },\n  { x: 0.984375, y: 0.921875 },\n  { x: 0.015625, y: 0.953125 },\n  { x: 0.015625, y: 0.953125 },\n  { x: 0.046875, y: 0.953125 },\n  { x: 0.046875, y: 0.953125 },\n  { x: 0.078125, y: 0.953125 },\n  { x: 0.078125, y: 0.953125 },\n  { x: 0.109375, y: 0.953125 },\n  { x: 0.109375, y: 0.953125 },\n  { x: 0.140625, y: 0.953125 },\n  { x: 0.140625, y: 0.953125 },\n  { x: 0.171875, y: 0.953125 },\n  { x: 0.171875, y: 0.953125 },\n  { x: 0.203125, y: 0.953125 },\n  { x: 0.203125, y: 0.953125 },\n  { x: 0.234375, y: 0.953125 },\n  { x: 0.234375, y: 0.953125 },\n  { x: 0.265625, y: 0.953125 },\n  { x: 0.265625, y: 0.953125 },\n  { x: 0.296875, y: 0.953125 },\n  { x: 0.296875, y: 0.953125 },\n  { x: 0.328125, y: 0.953125 },\n  { x: 0.328125, y: 0.953125 },\n  { x: 0.359375, y: 0.953125 },\n  { x: 0.359375, y: 0.953125 },\n  { x: 0.390625, y: 0.953125 },\n  { x: 0.390625, y: 0.953125 },\n  { x: 0.421875, y: 0.953125 },\n  { x: 0.421875, y: 0.953125 },\n  { x: 0.453125, y: 0.953125 },\n  { x: 0.453125, y: 0.953125 },\n  { x: 0.484375, y: 0.953125 },\n  { x: 0.484375, y: 0.953125 },\n  { x: 0.515625, y: 0.953125 },\n  { x: 0.515625, y: 0.953125 },\n  { x: 0.546875, y: 0.953125 },\n  { x: 0.546875, y: 0.953125 },\n  { x: 0.578125, y: 0.953125 },\n  { x: 0.578125, y: 0.953125 },\n  { x: 0.609375, y: 0.953125 },\n  { x: 0.609375, y: 0.953125 },\n  { x: 0.640625, y: 0.953125 },\n  { x: 0.640625, y: 0.953125 },\n  { x: 0.671875, y: 0.953125 },\n  { x: 0.671875, y: 0.953125 },\n  { x: 0.703125, y: 0.953125 },\n  { x: 0.703125, y: 0.953125 },\n  { x: 0.734375, y: 0.953125 },\n  { x: 0.734375, y: 0.953125 },\n  { x: 0.765625, y: 0.953125 },\n  { x: 0.765625, y: 0.953125 },\n  { x: 0.796875, y: 0.953125 },\n  { x: 0.796875, y: 0.953125 },\n  { x: 0.828125, y: 0.953125 },\n  { x: 0.828125, y: 0.953125 },\n  { x: 0.859375, y: 0.953125 },\n  { x: 0.859375, y: 0.953125 },\n  { x: 0.890625, y: 0.953125 },\n  { x: 0.890625, y: 0.953125 },\n  { x: 0.921875, y: 0.953125 },\n  { x: 0.921875, y: 0.953125 },\n  { x: 0.953125, y: 0.953125 },\n  { x: 0.953125, y: 0.953125 },\n  { x: 0.984375, y: 0.953125 },\n  { x: 0.984375, y: 0.953125 },\n  { x: 0.015625, y: 0.984375 },\n  { x: 0.015625, y: 0.984375 },\n  { x: 0.046875, y: 0.984375 },\n  { x: 0.046875, y: 0.984375 },\n  { x: 0.078125, y: 0.984375 },\n  { x: 0.078125, y: 0.984375 },\n  { x: 0.109375, y: 0.984375 },\n  { x: 0.109375, y: 0.984375 },\n  { x: 0.140625, y: 0.984375 },\n  { x: 0.140625, y: 0.984375 },\n  { x: 0.171875, y: 0.984375 },\n  { x: 0.171875, y: 0.984375 },\n  { x: 0.203125, y: 0.984375 },\n  { x: 0.203125, y: 0.984375 },\n  { x: 0.234375, y: 0.984375 },\n  { x: 0.234375, y: 0.984375 },\n  { x: 0.265625, y: 0.984375 },\n  { x: 0.265625, y: 0.984375 },\n  { x: 0.296875, y: 0.984375 },\n  { x: 0.296875, y: 0.984375 },\n  { x: 0.328125, y: 0.984375 },\n  { x: 0.328125, y: 0.984375 },\n  { x: 0.359375, y: 0.984375 },\n  { x: 0.359375, y: 0.984375 },\n  { x: 0.390625, y: 0.984375 },\n  { x: 0.390625, y: 0.984375 },\n  { x: 0.421875, y: 0.984375 },\n  { x: 0.421875, y: 0.984375 },\n  { x: 0.453125, y: 0.984375 },\n  { x: 0.453125, y: 0.984375 },\n  { x: 0.484375, y: 0.984375 },\n  { x: 0.484375, y: 0.984375 },\n  { x: 0.515625, y: 0.984375 },\n  { x: 0.515625, y: 0.984375 },\n  { x: 0.546875, y: 0.984375 },\n  { x: 0.546875, y: 0.984375 },\n  { x: 0.578125, y: 0.984375 },\n  { x: 0.578125, y: 0.984375 },\n  { x: 0.609375, y: 0.984375 },\n  { x: 0.609375, y: 0.984375 },\n  { x: 0.640625, y: 0.984375 },\n  { x: 0.640625, y: 0.984375 },\n  { x: 0.671875, y: 0.984375 },\n  { x: 0.671875, y: 0.984375 },\n  { x: 0.703125, y: 0.984375 },\n  { x: 0.703125, y: 0.984375 },\n  { x: 0.734375, y: 0.984375 },\n  { x: 0.734375, y: 0.984375 },\n  { x: 0.765625, y: 0.984375 },\n  { x: 0.765625, y: 0.984375 },\n  { x: 0.796875, y: 0.984375 },\n  { x: 0.796875, y: 0.984375 },\n  { x: 0.828125, y: 0.984375 },\n  { x: 0.828125, y: 0.984375 },\n  { x: 0.859375, y: 0.984375 },\n  { x: 0.859375, y: 0.984375 },\n  { x: 0.890625, y: 0.984375 },\n  { x: 0.890625, y: 0.984375 },\n  { x: 0.921875, y: 0.984375 },\n  { x: 0.921875, y: 0.984375 },\n  { x: 0.953125, y: 0.984375 },\n  { x: 0.953125, y: 0.984375 },\n  { x: 0.984375, y: 0.984375 },\n  { x: 0.984375, y: 0.984375 },\n  { x: 0.03125, y: 0.03125 },\n  { x: 0.03125, y: 0.03125 },\n  { x: 0.09375, y: 0.03125 },\n  { x: 0.09375, y: 0.03125 },\n  { x: 0.15625, y: 0.03125 },\n  { x: 0.15625, y: 0.03125 },\n  { x: 0.21875, y: 0.03125 },\n  { x: 0.21875, y: 0.03125 },\n  { x: 0.28125, y: 0.03125 },\n  { x: 0.28125, y: 0.03125 },\n  { x: 0.34375, y: 0.03125 },\n  { x: 0.34375, y: 0.03125 },\n  { x: 0.40625, y: 0.03125 },\n  { x: 0.40625, y: 0.03125 },\n  { x: 0.46875, y: 0.03125 },\n  { x: 0.46875, y: 0.03125 },\n  { x: 0.53125, y: 0.03125 },\n  { x: 0.53125, y: 0.03125 },\n  { x: 0.59375, y: 0.03125 },\n  { x: 0.59375, y: 0.03125 },\n  { x: 0.65625, y: 0.03125 },\n  { x: 0.65625, y: 0.03125 },\n  { x: 0.71875, y: 0.03125 },\n  { x: 0.71875, y: 0.03125 },\n  { x: 0.78125, y: 0.03125 },\n  { x: 0.78125, y: 0.03125 },\n  { x: 0.84375, y: 0.03125 },\n  { x: 0.84375, y: 0.03125 },\n  { x: 0.90625, y: 0.03125 },\n  { x: 0.90625, y: 0.03125 },\n  { x: 0.96875, y: 0.03125 },\n  { x: 0.96875, y: 0.03125 },\n  { x: 0.03125, y: 0.09375 },\n  { x: 0.03125, y: 0.09375 },\n  { x: 0.09375, y: 0.09375 },\n  { x: 0.09375, y: 0.09375 },\n  { x: 0.15625, y: 0.09375 },\n  { x: 0.15625, y: 0.09375 },\n  { x: 0.21875, y: 0.09375 },\n  { x: 0.21875, y: 0.09375 },\n  { x: 0.28125, y: 0.09375 },\n  { x: 0.28125, y: 0.09375 },\n  { x: 0.34375, y: 0.09375 },\n  { x: 0.34375, y: 0.09375 },\n  { x: 0.40625, y: 0.09375 },\n  { x: 0.40625, y: 0.09375 },\n  { x: 0.46875, y: 0.09375 },\n  { x: 0.46875, y: 0.09375 },\n  { x: 0.53125, y: 0.09375 },\n  { x: 0.53125, y: 0.09375 },\n  { x: 0.59375, y: 0.09375 },\n  { x: 0.59375, y: 0.09375 },\n  { x: 0.65625, y: 0.09375 },\n  { x: 0.65625, y: 0.09375 },\n  { x: 0.71875, y: 0.09375 },\n  { x: 0.71875, y: 0.09375 },\n  { x: 0.78125, y: 0.09375 },\n  { x: 0.78125, y: 0.09375 },\n  { x: 0.84375, y: 0.09375 },\n  { x: 0.84375, y: 0.09375 },\n  { x: 0.90625, y: 0.09375 },\n  { x: 0.90625, y: 0.09375 },\n  { x: 0.96875, y: 0.09375 },\n  { x: 0.96875, y: 0.09375 },\n  { x: 0.03125, y: 0.15625 },\n  { x: 0.03125, y: 0.15625 },\n  { x: 0.09375, y: 0.15625 },\n  { x: 0.09375, y: 0.15625 },\n  { x: 0.15625, y: 0.15625 },\n  { x: 0.15625, y: 0.15625 },\n  { x: 0.21875, y: 0.15625 },\n  { x: 0.21875, y: 0.15625 },\n  { x: 0.28125, y: 0.15625 },\n  { x: 0.28125, y: 0.15625 },\n  { x: 0.34375, y: 0.15625 },\n  { x: 0.34375, y: 0.15625 },\n  { x: 0.40625, y: 0.15625 },\n  { x: 0.40625, y: 0.15625 },\n  { x: 0.46875, y: 0.15625 },\n  { x: 0.46875, y: 0.15625 },\n  { x: 0.53125, y: 0.15625 },\n  { x: 0.53125, y: 0.15625 },\n  { x: 0.59375, y: 0.15625 },\n  { x: 0.59375, y: 0.15625 },\n  { x: 0.65625, y: 0.15625 },\n  { x: 0.65625, y: 0.15625 },\n  { x: 0.71875, y: 0.15625 },\n  { x: 0.71875, y: 0.15625 },\n  { x: 0.78125, y: 0.15625 },\n  { x: 0.78125, y: 0.15625 },\n  { x: 0.84375, y: 0.15625 },\n  { x: 0.84375, y: 0.15625 },\n  { x: 0.90625, y: 0.15625 },\n  { x: 0.90625, y: 0.15625 },\n  { x: 0.96875, y: 0.15625 },\n  { x: 0.96875, y: 0.15625 },\n  { x: 0.03125, y: 0.21875 },\n  { x: 0.03125, y: 0.21875 },\n  { x: 0.09375, y: 0.21875 },\n  { x: 0.09375, y: 0.21875 },\n  { x: 0.15625, y: 0.21875 },\n  { x: 0.15625, y: 0.21875 },\n  { x: 0.21875, y: 0.21875 },\n  { x: 0.21875, y: 0.21875 },\n  { x: 0.28125, y: 0.21875 },\n  { x: 0.28125, y: 0.21875 },\n  { x: 0.34375, y: 0.21875 },\n  { x: 0.34375, y: 0.21875 },\n  { x: 0.40625, y: 0.21875 },\n  { x: 0.40625, y: 0.21875 },\n  { x: 0.46875, y: 0.21875 },\n  { x: 0.46875, y: 0.21875 },\n  { x: 0.53125, y: 0.21875 },\n  { x: 0.53125, y: 0.21875 },\n  { x: 0.59375, y: 0.21875 },\n  { x: 0.59375, y: 0.21875 },\n  { x: 0.65625, y: 0.21875 },\n  { x: 0.65625, y: 0.21875 },\n  { x: 0.71875, y: 0.21875 },\n  { x: 0.71875, y: 0.21875 },\n  { x: 0.78125, y: 0.21875 },\n  { x: 0.78125, y: 0.21875 },\n  { x: 0.84375, y: 0.21875 },\n  { x: 0.84375, y: 0.21875 },\n  { x: 0.90625, y: 0.21875 },\n  { x: 0.90625, y: 0.21875 },\n  { x: 0.96875, y: 0.21875 },\n  { x: 0.96875, y: 0.21875 },\n  { x: 0.03125, y: 0.28125 },\n  { x: 0.03125, y: 0.28125 },\n  { x: 0.09375, y: 0.28125 },\n  { x: 0.09375, y: 0.28125 },\n  { x: 0.15625, y: 0.28125 },\n  { x: 0.15625, y: 0.28125 },\n  { x: 0.21875, y: 0.28125 },\n  { x: 0.21875, y: 0.28125 },\n  { x: 0.28125, y: 0.28125 },\n  { x: 0.28125, y: 0.28125 },\n  { x: 0.34375, y: 0.28125 },\n  { x: 0.34375, y: 0.28125 },\n  { x: 0.40625, y: 0.28125 },\n  { x: 0.40625, y: 0.28125 },\n  { x: 0.46875, y: 0.28125 },\n  { x: 0.46875, y: 0.28125 },\n  { x: 0.53125, y: 0.28125 },\n  { x: 0.53125, y: 0.28125 },\n  { x: 0.59375, y: 0.28125 },\n  { x: 0.59375, y: 0.28125 },\n  { x: 0.65625, y: 0.28125 },\n  { x: 0.65625, y: 0.28125 },\n  { x: 0.71875, y: 0.28125 },\n  { x: 0.71875, y: 0.28125 },\n  { x: 0.78125, y: 0.28125 },\n  { x: 0.78125, y: 0.28125 },\n  { x: 0.84375, y: 0.28125 },\n  { x: 0.84375, y: 0.28125 },\n  { x: 0.90625, y: 0.28125 },\n  { x: 0.90625, y: 0.28125 },\n  { x: 0.96875, y: 0.28125 },\n  { x: 0.96875, y: 0.28125 },\n  { x: 0.03125, y: 0.34375 },\n  { x: 0.03125, y: 0.34375 },\n  { x: 0.09375, y: 0.34375 },\n  { x: 0.09375, y: 0.34375 },\n  { x: 0.15625, y: 0.34375 },\n  { x: 0.15625, y: 0.34375 },\n  { x: 0.21875, y: 0.34375 },\n  { x: 0.21875, y: 0.34375 },\n  { x: 0.28125, y: 0.34375 },\n  { x: 0.28125, y: 0.34375 },\n  { x: 0.34375, y: 0.34375 },\n  { x: 0.34375, y: 0.34375 },\n  { x: 0.40625, y: 0.34375 },\n  { x: 0.40625, y: 0.34375 },\n  { x: 0.46875, y: 0.34375 },\n  { x: 0.46875, y: 0.34375 },\n  { x: 0.53125, y: 0.34375 },\n  { x: 0.53125, y: 0.34375 },\n  { x: 0.59375, y: 0.34375 },\n  { x: 0.59375, y: 0.34375 },\n  { x: 0.65625, y: 0.34375 },\n  { x: 0.65625, y: 0.34375 },\n  { x: 0.71875, y: 0.34375 },\n  { x: 0.71875, y: 0.34375 },\n  { x: 0.78125, y: 0.34375 },\n  { x: 0.78125, y: 0.34375 },\n  { x: 0.84375, y: 0.34375 },\n  { x: 0.84375, y: 0.34375 },\n  { x: 0.90625, y: 0.34375 },\n  { x: 0.90625, y: 0.34375 },\n  { x: 0.96875, y: 0.34375 },\n  { x: 0.96875, y: 0.34375 },\n  { x: 0.03125, y: 0.40625 },\n  { x: 0.03125, y: 0.40625 },\n  { x: 0.09375, y: 0.40625 },\n  { x: 0.09375, y: 0.40625 },\n  { x: 0.15625, y: 0.40625 },\n  { x: 0.15625, y: 0.40625 },\n  { x: 0.21875, y: 0.40625 },\n  { x: 0.21875, y: 0.40625 },\n  { x: 0.28125, y: 0.40625 },\n  { x: 0.28125, y: 0.40625 },\n  { x: 0.34375, y: 0.40625 },\n  { x: 0.34375, y: 0.40625 },\n  { x: 0.40625, y: 0.40625 },\n  { x: 0.40625, y: 0.40625 },\n  { x: 0.46875, y: 0.40625 },\n  { x: 0.46875, y: 0.40625 },\n  { x: 0.53125, y: 0.40625 },\n  { x: 0.53125, y: 0.40625 },\n  { x: 0.59375, y: 0.40625 },\n  { x: 0.59375, y: 0.40625 },\n  { x: 0.65625, y: 0.40625 },\n  { x: 0.65625, y: 0.40625 },\n  { x: 0.71875, y: 0.40625 },\n  { x: 0.71875, y: 0.40625 },\n  { x: 0.78125, y: 0.40625 },\n  { x: 0.78125, y: 0.40625 },\n  { x: 0.84375, y: 0.40625 },\n  { x: 0.84375, y: 0.40625 },\n  { x: 0.90625, y: 0.40625 },\n  { x: 0.90625, y: 0.40625 },\n  { x: 0.96875, y: 0.40625 },\n  { x: 0.96875, y: 0.40625 },\n  { x: 0.03125, y: 0.46875 },\n  { x: 0.03125, y: 0.46875 },\n  { x: 0.09375, y: 0.46875 },\n  { x: 0.09375, y: 0.46875 },\n  { x: 0.15625, y: 0.46875 },\n  { x: 0.15625, y: 0.46875 },\n  { x: 0.21875, y: 0.46875 },\n  { x: 0.21875, y: 0.46875 },\n  { x: 0.28125, y: 0.46875 },\n  { x: 0.28125, y: 0.46875 },\n  { x: 0.34375, y: 0.46875 },\n  { x: 0.34375, y: 0.46875 },\n  { x: 0.40625, y: 0.46875 },\n  { x: 0.40625, y: 0.46875 },\n  { x: 0.46875, y: 0.46875 },\n  { x: 0.46875, y: 0.46875 },\n  { x: 0.53125, y: 0.46875 },\n  { x: 0.53125, y: 0.46875 },\n  { x: 0.59375, y: 0.46875 },\n  { x: 0.59375, y: 0.46875 },\n  { x: 0.65625, y: 0.46875 },\n  { x: 0.65625, y: 0.46875 },\n  { x: 0.71875, y: 0.46875 },\n  { x: 0.71875, y: 0.46875 },\n  { x: 0.78125, y: 0.46875 },\n  { x: 0.78125, y: 0.46875 },\n  { x: 0.84375, y: 0.46875 },\n  { x: 0.84375, y: 0.46875 },\n  { x: 0.90625, y: 0.46875 },\n  { x: 0.90625, y: 0.46875 },\n  { x: 0.96875, y: 0.46875 },\n  { x: 0.96875, y: 0.46875 },\n  { x: 0.03125, y: 0.53125 },\n  { x: 0.03125, y: 0.53125 },\n  { x: 0.09375, y: 0.53125 },\n  { x: 0.09375, y: 0.53125 },\n  { x: 0.15625, y: 0.53125 },\n  { x: 0.15625, y: 0.53125 },\n  { x: 0.21875, y: 0.53125 },\n  { x: 0.21875, y: 0.53125 },\n  { x: 0.28125, y: 0.53125 },\n  { x: 0.28125, y: 0.53125 },\n  { x: 0.34375, y: 0.53125 },\n  { x: 0.34375, y: 0.53125 },\n  { x: 0.40625, y: 0.53125 },\n  { x: 0.40625, y: 0.53125 },\n  { x: 0.46875, y: 0.53125 },\n  { x: 0.46875, y: 0.53125 },\n  { x: 0.53125, y: 0.53125 },\n  { x: 0.53125, y: 0.53125 },\n  { x: 0.59375, y: 0.53125 },\n  { x: 0.59375, y: 0.53125 },\n  { x: 0.65625, y: 0.53125 },\n  { x: 0.65625, y: 0.53125 },\n  { x: 0.71875, y: 0.53125 },\n  { x: 0.71875, y: 0.53125 },\n  { x: 0.78125, y: 0.53125 },\n  { x: 0.78125, y: 0.53125 },\n  { x: 0.84375, y: 0.53125 },\n  { x: 0.84375, y: 0.53125 },\n  { x: 0.90625, y: 0.53125 },\n  { x: 0.90625, y: 0.53125 },\n  { x: 0.96875, y: 0.53125 },\n  { x: 0.96875, y: 0.53125 },\n  { x: 0.03125, y: 0.59375 },\n  { x: 0.03125, y: 0.59375 },\n  { x: 0.09375, y: 0.59375 },\n  { x: 0.09375, y: 0.59375 },\n  { x: 0.15625, y: 0.59375 },\n  { x: 0.15625, y: 0.59375 },\n  { x: 0.21875, y: 0.59375 },\n  { x: 0.21875, y: 0.59375 },\n  { x: 0.28125, y: 0.59375 },\n  { x: 0.28125, y: 0.59375 },\n  { x: 0.34375, y: 0.59375 },\n  { x: 0.34375, y: 0.59375 },\n  { x: 0.40625, y: 0.59375 },\n  { x: 0.40625, y: 0.59375 },\n  { x: 0.46875, y: 0.59375 },\n  { x: 0.46875, y: 0.59375 },\n  { x: 0.53125, y: 0.59375 },\n  { x: 0.53125, y: 0.59375 },\n  { x: 0.59375, y: 0.59375 },\n  { x: 0.59375, y: 0.59375 },\n  { x: 0.65625, y: 0.59375 },\n  { x: 0.65625, y: 0.59375 },\n  { x: 0.71875, y: 0.59375 },\n  { x: 0.71875, y: 0.59375 },\n  { x: 0.78125, y: 0.59375 },\n  { x: 0.78125, y: 0.59375 },\n  { x: 0.84375, y: 0.59375 },\n  { x: 0.84375, y: 0.59375 },\n  { x: 0.90625, y: 0.59375 },\n  { x: 0.90625, y: 0.59375 },\n  { x: 0.96875, y: 0.59375 },\n  { x: 0.96875, y: 0.59375 },\n  { x: 0.03125, y: 0.65625 },\n  { x: 0.03125, y: 0.65625 },\n  { x: 0.09375, y: 0.65625 },\n  { x: 0.09375, y: 0.65625 },\n  { x: 0.15625, y: 0.65625 },\n  { x: 0.15625, y: 0.65625 },\n  { x: 0.21875, y: 0.65625 },\n  { x: 0.21875, y: 0.65625 },\n  { x: 0.28125, y: 0.65625 },\n  { x: 0.28125, y: 0.65625 },\n  { x: 0.34375, y: 0.65625 },\n  { x: 0.34375, y: 0.65625 },\n  { x: 0.40625, y: 0.65625 },\n  { x: 0.40625, y: 0.65625 },\n  { x: 0.46875, y: 0.65625 },\n  { x: 0.46875, y: 0.65625 },\n  { x: 0.53125, y: 0.65625 },\n  { x: 0.53125, y: 0.65625 },\n  { x: 0.59375, y: 0.65625 },\n  { x: 0.59375, y: 0.65625 },\n  { x: 0.65625, y: 0.65625 },\n  { x: 0.65625, y: 0.65625 },\n  { x: 0.71875, y: 0.65625 },\n  { x: 0.71875, y: 0.65625 },\n  { x: 0.78125, y: 0.65625 },\n  { x: 0.78125, y: 0.65625 },\n  { x: 0.84375, y: 0.65625 },\n  { x: 0.84375, y: 0.65625 },\n  { x: 0.90625, y: 0.65625 },\n  { x: 0.90625, y: 0.65625 },\n  { x: 0.96875, y: 0.65625 },\n  { x: 0.96875, y: 0.65625 },\n  { x: 0.03125, y: 0.71875 },\n  { x: 0.03125, y: 0.71875 },\n  { x: 0.09375, y: 0.71875 },\n  { x: 0.09375, y: 0.71875 },\n  { x: 0.15625, y: 0.71875 },\n  { x: 0.15625, y: 0.71875 },\n  { x: 0.21875, y: 0.71875 },\n  { x: 0.21875, y: 0.71875 },\n  { x: 0.28125, y: 0.71875 },\n  { x: 0.28125, y: 0.71875 },\n  { x: 0.34375, y: 0.71875 },\n  { x: 0.34375, y: 0.71875 },\n  { x: 0.40625, y: 0.71875 },\n  { x: 0.40625, y: 0.71875 },\n  { x: 0.46875, y: 0.71875 },\n  { x: 0.46875, y: 0.71875 },\n  { x: 0.53125, y: 0.71875 },\n  { x: 0.53125, y: 0.71875 },\n  { x: 0.59375, y: 0.71875 },\n  { x: 0.59375, y: 0.71875 },\n  { x: 0.65625, y: 0.71875 },\n  { x: 0.65625, y: 0.71875 },\n  { x: 0.71875, y: 0.71875 },\n  { x: 0.71875, y: 0.71875 },\n  { x: 0.78125, y: 0.71875 },\n  { x: 0.78125, y: 0.71875 },\n  { x: 0.84375, y: 0.71875 },\n  { x: 0.84375, y: 0.71875 },\n  { x: 0.90625, y: 0.71875 },\n  { x: 0.90625, y: 0.71875 },\n  { x: 0.96875, y: 0.71875 },\n  { x: 0.96875, y: 0.71875 },\n  { x: 0.03125, y: 0.78125 },\n  { x: 0.03125, y: 0.78125 },\n  { x: 0.09375, y: 0.78125 },\n  { x: 0.09375, y: 0.78125 },\n  { x: 0.15625, y: 0.78125 },\n  { x: 0.15625, y: 0.78125 },\n  { x: 0.21875, y: 0.78125 },\n  { x: 0.21875, y: 0.78125 },\n  { x: 0.28125, y: 0.78125 },\n  { x: 0.28125, y: 0.78125 },\n  { x: 0.34375, y: 0.78125 },\n  { x: 0.34375, y: 0.78125 },\n  { x: 0.40625, y: 0.78125 },\n  { x: 0.40625, y: 0.78125 },\n  { x: 0.46875, y: 0.78125 },\n  { x: 0.46875, y: 0.78125 },\n  { x: 0.53125, y: 0.78125 },\n  { x: 0.53125, y: 0.78125 },\n  { x: 0.59375, y: 0.78125 },\n  { x: 0.59375, y: 0.78125 },\n  { x: 0.65625, y: 0.78125 },\n  { x: 0.65625, y: 0.78125 },\n  { x: 0.71875, y: 0.78125 },\n  { x: 0.71875, y: 0.78125 },\n  { x: 0.78125, y: 0.78125 },\n  { x: 0.78125, y: 0.78125 },\n  { x: 0.84375, y: 0.78125 },\n  { x: 0.84375, y: 0.78125 },\n  { x: 0.90625, y: 0.78125 },\n  { x: 0.90625, y: 0.78125 },\n  { x: 0.96875, y: 0.78125 },\n  { x: 0.96875, y: 0.78125 },\n  { x: 0.03125, y: 0.84375 },\n  { x: 0.03125, y: 0.84375 },\n  { x: 0.09375, y: 0.84375 },\n  { x: 0.09375, y: 0.84375 },\n  { x: 0.15625, y: 0.84375 },\n  { x: 0.15625, y: 0.84375 },\n  { x: 0.21875, y: 0.84375 },\n  { x: 0.21875, y: 0.84375 },\n  { x: 0.28125, y: 0.84375 },\n  { x: 0.28125, y: 0.84375 },\n  { x: 0.34375, y: 0.84375 },\n  { x: 0.34375, y: 0.84375 },\n  { x: 0.40625, y: 0.84375 },\n  { x: 0.40625, y: 0.84375 },\n  { x: 0.46875, y: 0.84375 },\n  { x: 0.46875, y: 0.84375 },\n  { x: 0.53125, y: 0.84375 },\n  { x: 0.53125, y: 0.84375 },\n  { x: 0.59375, y: 0.84375 },\n  { x: 0.59375, y: 0.84375 },\n  { x: 0.65625, y: 0.84375 },\n  { x: 0.65625, y: 0.84375 },\n  { x: 0.71875, y: 0.84375 },\n  { x: 0.71875, y: 0.84375 },\n  { x: 0.78125, y: 0.84375 },\n  { x: 0.78125, y: 0.84375 },\n  { x: 0.84375, y: 0.84375 },\n  { x: 0.84375, y: 0.84375 },\n  { x: 0.90625, y: 0.84375 },\n  { x: 0.90625, y: 0.84375 },\n  { x: 0.96875, y: 0.84375 },\n  { x: 0.96875, y: 0.84375 },\n  { x: 0.03125, y: 0.90625 },\n  { x: 0.03125, y: 0.90625 },\n  { x: 0.09375, y: 0.90625 },\n  { x: 0.09375, y: 0.90625 },\n  { x: 0.15625, y: 0.90625 },\n  { x: 0.15625, y: 0.90625 },\n  { x: 0.21875, y: 0.90625 },\n  { x: 0.21875, y: 0.90625 },\n  { x: 0.28125, y: 0.90625 },\n  { x: 0.28125, y: 0.90625 },\n  { x: 0.34375, y: 0.90625 },\n  { x: 0.34375, y: 0.90625 },\n  { x: 0.40625, y: 0.90625 },\n  { x: 0.40625, y: 0.90625 },\n  { x: 0.46875, y: 0.90625 },\n  { x: 0.46875, y: 0.90625 },\n  { x: 0.53125, y: 0.90625 },\n  { x: 0.53125, y: 0.90625 },\n  { x: 0.59375, y: 0.90625 },\n  { x: 0.59375, y: 0.90625 },\n  { x: 0.65625, y: 0.90625 },\n  { x: 0.65625, y: 0.90625 },\n  { x: 0.71875, y: 0.90625 },\n  { x: 0.71875, y: 0.90625 },\n  { x: 0.78125, y: 0.90625 },\n  { x: 0.78125, y: 0.90625 },\n  { x: 0.84375, y: 0.90625 },\n  { x: 0.84375, y: 0.90625 },\n  { x: 0.90625, y: 0.90625 },\n  { x: 0.90625, y: 0.90625 },\n  { x: 0.96875, y: 0.90625 },\n  { x: 0.96875, y: 0.90625 },\n  { x: 0.03125, y: 0.96875 },\n  { x: 0.03125, y: 0.96875 },\n  { x: 0.09375, y: 0.96875 },\n  { x: 0.09375, y: 0.96875 },\n  { x: 0.15625, y: 0.96875 },\n  { x: 0.15625, y: 0.96875 },\n  { x: 0.21875, y: 0.96875 },\n  { x: 0.21875, y: 0.96875 },\n  { x: 0.28125, y: 0.96875 },\n  { x: 0.28125, y: 0.96875 },\n  { x: 0.34375, y: 0.96875 },\n  { x: 0.34375, y: 0.96875 },\n  { x: 0.40625, y: 0.96875 },\n  { x: 0.40625, y: 0.96875 },\n  { x: 0.46875, y: 0.96875 },\n  { x: 0.46875, y: 0.96875 },\n  { x: 0.53125, y: 0.96875 },\n  { x: 0.53125, y: 0.96875 },\n  { x: 0.59375, y: 0.96875 },\n  { x: 0.59375, y: 0.96875 },\n  { x: 0.65625, y: 0.96875 },\n  { x: 0.65625, y: 0.96875 },\n  { x: 0.71875, y: 0.96875 },\n  { x: 0.71875, y: 0.96875 },\n  { x: 0.78125, y: 0.96875 },\n  { x: 0.78125, y: 0.96875 },\n  { x: 0.84375, y: 0.96875 },\n  { x: 0.84375, y: 0.96875 },\n  { x: 0.90625, y: 0.96875 },\n  { x: 0.90625, y: 0.96875 },\n  { x: 0.96875, y: 0.96875 },\n  { x: 0.96875, y: 0.96875 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n];\n", "/**\n * HandPose model implementation\n * See `handpose.ts` for entry point\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as util from './handposeutil';\nimport * as anchors from './handposeanchors';\nimport { constants } from '../tfjs/constants';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Point } from '../result';\n\nexport class HandDetector {\n  model: GraphModel;\n  anchors: number[][];\n  anchorsTensor: Tensor;\n  inputSize: number;\n  inputSizeTensor: Tensor;\n  doubleInputSizeTensor: Tensor;\n\n  constructor(model) {\n    this.model = model;\n    this.anchors = anchors.anchors.map((anchor) => [anchor.x, anchor.y]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = (this.model && this.model.inputs && this.model.inputs[0].shape) ? this.model.inputs[0].shape[2] : 0;\n    this.inputSizeTensor = tf.tensor1d([this.inputSize, this.inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([this.inputSize * 2, this.inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    const t: Record<string, Tensor> = {};\n    t.boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n    t.boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n    t.div = tf.div(t.boxOffsets, this.inputSizeTensor);\n    t.boxCenterPoints = tf.add(t.div, this.anchorsTensor);\n    t.halfBoxSizes = tf.div(t.boxSizes, this.doubleInputSizeTensor);\n    t.sub = tf.sub(t.boxCenterPoints, t.halfBoxSizes);\n    t.startPoints = tf.mul(t.sub, this.inputSizeTensor);\n    t.add = tf.add(t.boxCenterPoints, t.halfBoxSizes);\n    t.endPoints = tf.mul(t.add, this.inputSizeTensor);\n    const res = tf.concat2d([t.startPoints, t.endPoints], 1);\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return res;\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    const t: Record<string, Tensor> = {};\n    t.reshape = tf.reshape(rawPalmLandmarks, [-1, 7, 2]);\n    t.div = tf.div(t.reshape, this.inputSizeTensor);\n    t.landmarks = tf.add(t.div, this.anchors[index]);\n    const res = tf.mul(t.landmarks, this.inputSizeTensor);\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return res;\n  }\n\n  async predict(input, config): Promise<{ startPoint: Point; endPoint: Point, palmLandmarks: Point[]; confidence: number }[]> {\n    const t: Record<string, Tensor> = {};\n    t.resize = tf.image.resizeBilinear(input, [this.inputSize, this.inputSize]);\n    t.div = tf.div(t.resize, constants.tf127);\n    t.image = tf.sub(t.div, constants.tf1);\n    t.batched = this.model.execute(t.image) as Tensor;\n    t.predictions = tf.squeeze(t.batched);\n    t.slice = tf.slice(t.predictions, [0, 0], [-1, 1]);\n    t.sigmoid = tf.sigmoid(t.slice);\n    t.scores = tf.squeeze(t.sigmoid);\n    const scores = await t.scores.data();\n    t.boxes = tf.slice(t.predictions, [0, 1], [-1, 4]);\n    t.norm = this.normalizeBoxes(t.boxes);\n    // box detection is flaky so we look for 3x boxes than we need results\n    t.nms = await tf.image.nonMaxSuppressionAsync(t.norm, t.scores, 3 * config.hand.maxDetected, config.hand.iouThreshold, config.hand.minConfidence);\n    const nms = await t.nms.array() as Array<number>;\n    const hands: Array<{ startPoint: Point; endPoint: Point; palmLandmarks: Point[]; confidence: number }> = [];\n    for (const index of nms) {\n      const p: Record<string, Tensor> = {};\n      p.box = tf.slice(t.norm, [index, 0], [1, -1]);\n      p.slice = tf.slice(t.predictions, [index, 5], [1, 14]);\n      p.norm = this.normalizeLandmarks(p.slice, index);\n      p.palmLandmarks = tf.reshape(p.norm, [-1, 2]);\n      const box = await p.box.data();\n      const startPoint = box.slice(0, 2) as unknown as Point;\n      const endPoint = box.slice(2, 4) as unknown as Point;\n      const palmLandmarks = await p.palmLandmarks.array();\n      const hand = { startPoint, endPoint, palmLandmarks, confidence: scores[index] };\n      const scaled = util.scaleBoxCoordinates(hand, [input.shape[2] / this.inputSize, input.shape[1] / this.inputSize]);\n      hands.push(scaled);\n      Object.keys(p).forEach((tensor) => tf.dispose(p[tensor]));\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return hands;\n  }\n}\n", "/**\n * HandPose model implementation\n * See `handpose.ts` for entry point\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as util from './handposeutil';\nimport type * as detector from './handposedetector';\nimport { constants } from '../tfjs/constants';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport { env } from '../util/env';\nimport { now } from '../util/util';\nimport type { Point } from '../result';\n\nconst palmBoxEnlargeFactor = 5; // default 3\nconst handBoxEnlargeFactor = 1.65; // default 1.65\nconst palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];\nconst palmLandmarksPalmBase = 0;\nconst palmLandmarksMiddleFingerBase = 2;\nlet lastTime = 0;\n\nexport class HandPipeline {\n  handDetector: detector.HandDetector;\n  handPoseModel: GraphModel;\n  inputSize: number;\n  storedBoxes: Array<{ startPoint: Point; endPoint: Point; palmLandmarks: Point[]; confidence: number } | null>;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, handPoseModel) {\n    this.handDetector = handDetector;\n    this.handPoseModel = handPoseModel;\n    this.inputSize = this.handPoseModel && this.handPoseModel.inputs[0].shape ? this.handPoseModel.inputs[0].shape[2] : 0;\n    this.storedBoxes = [];\n    this.skipped = Number.MAX_SAFE_INTEGER;\n    this.detectedHands = 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    return util.enlargeBox(util.squarifyBox(boxAroundPalm), palmBoxEnlargeFactor);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    const boxAroundHand = util.enlargeBox(util.squarifyBox(boundingBox), handBoxEnlargeFactor);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < palmLandmarkIds.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[palmLandmarkIds[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = util.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...util.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      Math.trunc(coord[0] + originalBoxCenter[0]),\n      Math.trunc(coord[1] + originalBoxCenter[1]),\n      Math.trunc(coord[2]),\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames\n    let boxes;\n    const skipTime = (config.hand.skipTime || 0) > (now() - lastTime);\n    const skipFrame = this.skipped < (config.hand.skipFrames || 0);\n    if (config.skipAllowed && skipTime && skipFrame) {\n      boxes = await this.handDetector.predict(image, config);\n      this.skipped = 0;\n    }\n    if (config.skipAllowed) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxDetected) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{ landmarks: Point[], confidence: number, boxConfidence: number, fingerConfidence: number, box: { topLeft: Point, bottomRight: Point } }> = [];\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[palmLandmarksPalmBase], currentBox.palmLandmarks[palmLandmarksMiddleFingerBase]) : 0;\n        const palmCenter = util.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation && env.kernels.includes('rotatewithoffset') ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = util.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = tf.div(croppedInput, constants.tf255);\n        tf.dispose(croppedInput);\n        tf.dispose(rotatedImage);\n        const [confidenceT, keypoints] = this.handPoseModel.execute(handImage) as Array<Tensor>;\n        lastTime = now();\n        tf.dispose(handImage);\n        const confidence = (await confidenceT.data())[0];\n        tf.dispose(confidenceT);\n        if (confidence >= config.hand.minConfidence / 4) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = await keypointsReshaped.array();\n          tf.dispose(keypoints);\n          tf.dispose(keypointsReshaped);\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = { ...nextBoundingBox, confidence };\n          const result = {\n            landmarks: coords,\n            confidence,\n            boxConfidence: currentBox.confidence,\n            fingerConfidence: confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        tf.dispose(keypoints);\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), handBoxEnlargeFactor);\n        const enlarged = util.enlargeBox(util.squarifyBox(currentBox), handBoxEnlargeFactor);\n        const result = {\n          confidence: currentBox.confidence,\n          boxConfidence: currentBox.confidence,\n          fingerConfidence: 0,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n          landmarks: [],\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    if (hands.length > config.hand.maxDetected) hands.length = config.hand.maxDetected;\n    return hands;\n  }\n}\n", "/**\n * FingerPose algorithm implementation\n * See `fingerpose.ts` for entry point\n */\n\nexport const Finger = {\n  thumb: 0,\n  index: 1,\n  middle: 2,\n  ring: 3,\n  pinky: 4,\n  all: [0, 1, 2, 3, 4], // just for convenience\n  nameMapping: { 0: 'thumb', 1: 'index', 2: 'middle', 3: 'ring', 4: 'pinky' },\n  // Describes mapping of joints based on the 21 points returned by handpose.\n  // [0]     Palm\n  // [1-4]   Thumb\n  // [5-8]   Index\n  // [9-12]  Middle\n  // [13-16] Ring\n  // [17-20] Pinky\n  pointsMapping: {\n    0: [[0, 1], [1, 2], [2, 3], [3, 4]],\n    1: [[0, 5], [5, 6], [6, 7], [7, 8]],\n    2: [[0, 9], [9, 10], [10, 11], [11, 12]],\n    3: [[0, 13], [13, 14], [14, 15], [15, 16]],\n    4: [[0, 17], [17, 18], [18, 19], [19, 20]],\n  },\n  getName: (value) => Finger.nameMapping[value],\n  getPoints: (value) => Finger.pointsMapping[value],\n};\n\nexport const FingerCurl = {\n  none: 0,\n  half: 1,\n  full: 2,\n  nameMapping: { 0: 'none', 1: 'half', 2: 'full' },\n  getName: (value) => FingerCurl.nameMapping[value],\n};\n\nexport const FingerDirection = {\n  verticalUp: 0,\n  verticalDown: 1,\n  horizontalLeft: 2,\n  horizontalRight: 3,\n  diagonalUpRight: 4,\n  diagonalUpLeft: 5,\n  diagonalDownRight: 6,\n  diagonalDownLeft: 7,\n  nameMapping: { 0: 'verticalUp', 1: 'verticalDown', 2: 'horizontalLeft', 3: 'horizontalRight', 4: 'diagonalUpRight', 5: 'diagonalUpLeft', 6: 'diagonalDownRight', 7: 'diagonalDownLeft' },\n  getName: (value) => FingerDirection.nameMapping[value],\n};\n\nexport class FingerGesture {\n  name;\n  curls;\n  directions;\n  weights;\n  weightsRelative;\n\n  constructor(name) {\n    // name (should be unique)\n    this.name = name;\n    this.curls = {};\n    this.directions = {};\n    this.weights = [1.0, 1.0, 1.0, 1.0, 1.0];\n    this.weightsRelative = [1.0, 1.0, 1.0, 1.0, 1.0];\n  }\n\n  curl(finger, curl, confidence) {\n    if (typeof this.curls[finger] === 'undefined') this.curls[finger] = [];\n    this.curls[finger].push([curl, confidence]);\n  }\n\n  direction(finger, position, confidence) {\n    if (!this.directions[finger]) this.directions[finger] = [];\n    this.directions[finger].push([position, confidence]);\n  }\n\n  weight(finger, weight) {\n    this.weights[finger] = weight;\n    // recalculate relative weights\n    const total = this.weights.reduce((a, b) => a + b, 0);\n    this.weightsRelative = this.weights.map((el) => el * 5 / total);\n  }\n\n  matchAgainst(detectedCurls, detectedDirections) {\n    let confidence = 0.0;\n    // look at the detected curl of each finger and compare with\n    // the expected curl of this finger inside current gesture\n    for (const fingerIdx in detectedCurls) {\n      const detectedCurl = detectedCurls[fingerIdx];\n      const expectedCurls = this.curls[fingerIdx];\n      if (typeof expectedCurls === 'undefined') {\n        // no curl description available for this finger\n        // add default confidence of \"1\"\n        confidence += this.weightsRelative[fingerIdx];\n        continue;\n      }\n      // compare to each possible curl of this specific finger\n      for (const [expectedCurl, score] of expectedCurls) {\n        if (detectedCurl === expectedCurl) {\n          confidence += score * this.weightsRelative[fingerIdx];\n          break;\n        }\n      }\n    }\n    // same for detected direction of each finger\n    for (const fingerIdx in detectedDirections) {\n      const detectedDirection = detectedDirections[fingerIdx];\n      const expectedDirections = this.directions[fingerIdx];\n      if (typeof expectedDirections === 'undefined') {\n        // no direction description available for this finger\n        // add default confidence of \"1\"\n        confidence += this.weightsRelative[fingerIdx];\n        continue;\n      }\n      // compare to each possible direction of this specific finger\n      for (const [expectedDirection, score] of expectedDirections) {\n        if (detectedDirection === expectedDirection) {\n          confidence += score * this.weightsRelative[fingerIdx];\n          break;\n        }\n      }\n    }\n    return confidence / 10;\n  }\n}\n", "/**\n * FingerPose algorithm implementation\n * See `fingerpose.ts` for entry point\n */\n\nimport { Finger, FingerCurl, FingerDirection, FingerGesture } from './fingerdef';\n\n// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\nexport const { thumb, index, middle, ring, pinky } = Finger;\n// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\nexport const { none, half, full } = FingerCurl;\n// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\nexport const { verticalUp, verticalDown, horizontalLeft, horizontalRight, diagonalUpRight, diagonalUpLeft, diagonalDownRight, diagonalDownLeft } = FingerDirection;\n\n// describe thumbs up gesture \uD83D\uDC4D\nconst ThumbsUp = new FingerGesture('thumbs up');\nThumbsUp.curl(thumb, none, 1.0);\nThumbsUp.direction(thumb, verticalUp, 1.0);\nThumbsUp.direction(thumb, diagonalUpLeft, 0.25);\nThumbsUp.direction(thumb, diagonalUpRight, 0.25);\nfor (const finger of [Finger.index, Finger.middle, Finger.ring, Finger.pinky]) {\n  ThumbsUp.curl(finger, full, 1.0);\n  ThumbsUp.direction(finger, horizontalLeft, 1.0);\n  ThumbsUp.direction(finger, horizontalRight, 1.0);\n}\n\n// describe Victory gesture \u270C\uFE0F\nconst Victory = new FingerGesture('victory');\nVictory.curl(thumb, half, 0.5);\nVictory.curl(thumb, none, 0.5);\nVictory.direction(thumb, verticalUp, 1.0);\nVictory.direction(thumb, diagonalUpLeft, 1.0);\nVictory.curl(index, none, 1.0);\nVictory.direction(index, verticalUp, 0.75);\nVictory.direction(index, diagonalUpLeft, 1.0);\nVictory.curl(middle, none, 1.0);\nVictory.direction(middle, verticalUp, 1.0);\nVictory.direction(middle, diagonalUpLeft, 0.75);\nVictory.curl(ring, full, 1.0);\nVictory.direction(ring, verticalUp, 0.2);\nVictory.direction(ring, diagonalUpLeft, 1.0);\nVictory.direction(ring, horizontalLeft, 0.2);\nVictory.curl(pinky, full, 1.0);\nVictory.direction(pinky, verticalUp, 0.2);\nVictory.direction(pinky, diagonalUpLeft, 1.0);\nVictory.direction(pinky, horizontalLeft, 0.2);\nVictory.weight(index, 2);\nVictory.weight(middle, 2);\n\n// describe Point gesture \u270C\uFE0F\nconst Point = new FingerGesture('point');\nPoint.curl(thumb, full, 1.0);\nPoint.curl(index, none, 0.5);\nPoint.curl(middle, full, 0.5);\nPoint.curl(ring, full, 0.5);\nPoint.curl(pinky, full, 0.5);\nPoint.weight(index, 2);\nPoint.weight(middle, 2);\n\n// describe Point gesture \u270C\uFE0F\nconst MiddleFinger = new FingerGesture('middle finger');\nMiddleFinger.curl(thumb, none, 1.0);\nMiddleFinger.curl(index, full, 0.5);\nMiddleFinger.curl(middle, full, 0.5);\nMiddleFinger.curl(ring, full, 0.5);\nMiddleFinger.curl(pinky, full, 0.5);\nMiddleFinger.weight(index, 2);\nMiddleFinger.weight(middle, 2);\n\n// describe Open Palm gesture \u270C\uFE0F\nconst OpenPalm = new FingerGesture('open palm');\nOpenPalm.curl(thumb, none, 0.75);\nOpenPalm.curl(index, none, 0.75);\nOpenPalm.curl(middle, none, 0.75);\nOpenPalm.curl(ring, none, 0.75);\nOpenPalm.curl(pinky, none, 0.75);\n\nexport default [ThumbsUp, Victory, Point, MiddleFinger, OpenPalm];\n", "/**\n * FingerPose algorithm implementation constants\n *\n * Based on: [**FingerPose***](https://github.com/andypotato/fingerpose)\n */\n\nimport { Finger, FingerCurl, FingerDirection } from './fingerdef';\nimport Gestures from '../hand/fingergesture';\n\nconst minConfidence = 0.7;\nconst options = {\n  // curl estimation\n  HALF_CURL_START_LIMIT: 60.0,\n  NO_CURL_START_LIMIT: 130.0,\n  // direction estimation\n  DISTANCE_VOTE_POWER: 1.1,\n  SINGLE_ANGLE_VOTE_POWER: 0.9,\n  TOTAL_ANGLE_VOTE_POWER: 1.6,\n};\n\nfunction calculateSlope(point1x, point1y, point2x, point2y) {\n  const value = (point1y - point2y) / (point1x - point2x);\n  let slope = Math.atan(value) * 180 / Math.PI;\n  if (slope <= 0) slope = -slope;\n  else if (slope > 0) slope = 180 - slope;\n  return slope;\n}\n\n// point1, point2 are 2d or 3d point arrays (xy[z])\n// returns either a single scalar (2d) or array of two slopes (3d)\nfunction getSlopes(point1, point2) {\n  if (!point1 || !point2) return [0, 0];\n  const slopeXY = calculateSlope(point1[0], point1[1], point2[0], point2[1]);\n  if (point1.length === 2) return slopeXY;\n  const slopeYZ = calculateSlope(point1[1], point1[2], point2[1], point2[2]);\n  return [slopeXY, slopeYZ];\n}\n\nfunction angleOrientationAt(angle, weightageAt = 1.0) {\n  let isVertical = 0;\n  let isDiagonal = 0;\n  let isHorizontal = 0;\n  if (angle >= 75.0 && angle <= 105.0) isVertical = 1 * weightageAt;\n  else if (angle >= 25.0 && angle <= 155.0) isDiagonal = 1 * weightageAt;\n  else isHorizontal = 1 * weightageAt;\n  return [isVertical, isDiagonal, isHorizontal];\n}\n\nfunction estimateFingerCurl(startPoint, midPoint, endPoint) {\n  const start_mid_x_dist = startPoint[0] - midPoint[0];\n  const start_end_x_dist = startPoint[0] - endPoint[0];\n  const mid_end_x_dist = midPoint[0] - endPoint[0];\n  const start_mid_y_dist = startPoint[1] - midPoint[1];\n  const start_end_y_dist = startPoint[1] - endPoint[1];\n  const mid_end_y_dist = midPoint[1] - endPoint[1];\n  const start_mid_z_dist = startPoint[2] - midPoint[2];\n  const start_end_z_dist = startPoint[2] - endPoint[2];\n  const mid_end_z_dist = midPoint[2] - endPoint[2];\n  const start_mid_dist = Math.sqrt(start_mid_x_dist * start_mid_x_dist + start_mid_y_dist * start_mid_y_dist + start_mid_z_dist * start_mid_z_dist);\n  const start_end_dist = Math.sqrt(start_end_x_dist * start_end_x_dist + start_end_y_dist * start_end_y_dist + start_end_z_dist * start_end_z_dist);\n  const mid_end_dist = Math.sqrt(mid_end_x_dist * mid_end_x_dist + mid_end_y_dist * mid_end_y_dist + mid_end_z_dist * mid_end_z_dist);\n  let cos_in = (mid_end_dist * mid_end_dist + start_mid_dist * start_mid_dist - start_end_dist * start_end_dist) / (2 * mid_end_dist * start_mid_dist);\n  if (cos_in > 1.0) cos_in = 1.0;\n  else if (cos_in < -1.0) cos_in = -1.0;\n  let angleOfCurve = Math.acos(cos_in);\n  angleOfCurve = (57.2958 * angleOfCurve) % 180;\n  let fingerCurl;\n  if (angleOfCurve > options.NO_CURL_START_LIMIT) fingerCurl = FingerCurl.none;\n  else if (angleOfCurve > options.HALF_CURL_START_LIMIT) fingerCurl = FingerCurl.half;\n  else fingerCurl = FingerCurl.full;\n  return fingerCurl;\n}\n\nfunction estimateHorizontalDirection(start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x) {\n  let estimatedDirection;\n  if (max_dist_x === Math.abs(start_end_x_dist)) {\n    if (start_end_x_dist > 0) estimatedDirection = FingerDirection.horizontalLeft;\n    else estimatedDirection = FingerDirection.horizontalRight;\n  } else if (max_dist_x === Math.abs(start_mid_x_dist)) {\n    if (start_mid_x_dist > 0) estimatedDirection = FingerDirection.horizontalLeft;\n    else estimatedDirection = FingerDirection.horizontalRight;\n  } else {\n    if (mid_end_x_dist > 0) estimatedDirection = FingerDirection.horizontalLeft;\n    else estimatedDirection = FingerDirection.horizontalRight;\n  }\n  return estimatedDirection;\n}\n\nfunction estimateVerticalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y) {\n  let estimatedDirection;\n  if (max_dist_y === Math.abs(start_end_y_dist)) {\n    if (start_end_y_dist < 0) estimatedDirection = FingerDirection.verticalDown;\n    else estimatedDirection = FingerDirection.verticalUp;\n  } else if (max_dist_y === Math.abs(start_mid_y_dist)) {\n    if (start_mid_y_dist < 0) estimatedDirection = FingerDirection.verticalDown;\n    else estimatedDirection = FingerDirection.verticalUp;\n  } else {\n    if (mid_end_y_dist < 0) estimatedDirection = FingerDirection.verticalDown;\n    else estimatedDirection = FingerDirection.verticalUp;\n  }\n  return estimatedDirection;\n}\n\nfunction estimateDiagonalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y, start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x) {\n  let estimatedDirection;\n  const reqd_vertical_direction = estimateVerticalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y);\n  const reqd_horizontal_direction = estimateHorizontalDirection(start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x);\n  if (reqd_vertical_direction === FingerDirection.verticalUp) {\n    if (reqd_horizontal_direction === FingerDirection.horizontalLeft) estimatedDirection = FingerDirection.diagonalUpLeft;\n    else estimatedDirection = FingerDirection.diagonalUpRight;\n  } else {\n    if (reqd_horizontal_direction === FingerDirection.horizontalLeft) estimatedDirection = FingerDirection.diagonalDownLeft;\n    else estimatedDirection = FingerDirection.diagonalDownRight;\n  }\n  return estimatedDirection;\n}\n\nfunction calculateFingerDirection(startPoint, midPoint, endPoint, fingerSlopes) {\n  const start_mid_x_dist = startPoint[0] - midPoint[0];\n  const start_end_x_dist = startPoint[0] - endPoint[0];\n  const mid_end_x_dist = midPoint[0] - endPoint[0];\n  const start_mid_y_dist = startPoint[1] - midPoint[1];\n  const start_end_y_dist = startPoint[1] - endPoint[1];\n  const mid_end_y_dist = midPoint[1] - endPoint[1];\n  const max_dist_x = Math.max(Math.abs(start_mid_x_dist), Math.abs(start_end_x_dist), Math.abs(mid_end_x_dist));\n  const max_dist_y = Math.max(Math.abs(start_mid_y_dist), Math.abs(start_end_y_dist), Math.abs(mid_end_y_dist));\n  let voteVertical = 0.0;\n  let voteDiagonal = 0.0;\n  let voteHorizontal = 0.0;\n  const start_end_x_y_dist_ratio = max_dist_y / (max_dist_x + 0.00001);\n  if (start_end_x_y_dist_ratio > 1.5) voteVertical += options.DISTANCE_VOTE_POWER;\n  else if (start_end_x_y_dist_ratio > 0.66) voteDiagonal += options.DISTANCE_VOTE_POWER;\n  else voteHorizontal += options.DISTANCE_VOTE_POWER;\n  const start_mid_dist = Math.sqrt(start_mid_x_dist * start_mid_x_dist + start_mid_y_dist * start_mid_y_dist);\n  const start_end_dist = Math.sqrt(start_end_x_dist * start_end_x_dist + start_end_y_dist * start_end_y_dist);\n  const mid_end_dist = Math.sqrt(mid_end_x_dist * mid_end_x_dist + mid_end_y_dist * mid_end_y_dist);\n  const max_dist = Math.max(start_mid_dist, start_end_dist, mid_end_dist);\n  let calc_start_point_x = startPoint[0];\n  let calc_start_point_y = startPoint[1];\n  let calc_end_point_x = endPoint[0];\n  let calc_end_point_y = endPoint[1];\n  if (max_dist === start_mid_dist) {\n    calc_end_point_x = endPoint[0];\n    calc_end_point_y = endPoint[1];\n  } else if (max_dist === mid_end_dist) {\n    calc_start_point_x = midPoint[0];\n    calc_start_point_y = midPoint[1];\n  }\n  const calcStartPoint = [calc_start_point_x, calc_start_point_y];\n  const calcEndPoint = [calc_end_point_x, calc_end_point_y];\n  const totalAngle = getSlopes(calcStartPoint, calcEndPoint);\n  const votes = angleOrientationAt(totalAngle, options.TOTAL_ANGLE_VOTE_POWER);\n  voteVertical += votes[0];\n  voteDiagonal += votes[1];\n  voteHorizontal += votes[2];\n  for (const fingerSlope of fingerSlopes) {\n    const fingerVotes = angleOrientationAt(fingerSlope, options.SINGLE_ANGLE_VOTE_POWER);\n    voteVertical += fingerVotes[0];\n    voteDiagonal += fingerVotes[1];\n    voteHorizontal += fingerVotes[2];\n  }\n  // in case of tie, highest preference goes to Vertical,\n  // followed by horizontal and then diagonal\n  let estimatedDirection;\n  if (voteVertical === Math.max(voteVertical, voteDiagonal, voteHorizontal)) {\n    estimatedDirection = estimateVerticalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y);\n  } else if (voteHorizontal === Math.max(voteDiagonal, voteHorizontal)) {\n    estimatedDirection = estimateHorizontalDirection(start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x);\n  } else {\n    estimatedDirection = estimateDiagonalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y, start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x);\n  }\n  return estimatedDirection;\n}\n\nfunction estimate(landmarks) {\n  // step 1: calculate slopes\n  const slopesXY: Array<number[]> = [];\n  const slopesYZ: Array<number[]> = [];\n  const fingerCurls: Array<number> = [];\n  const fingerDirections: Array<number> = [];\n  if (!landmarks) return { curls: fingerCurls, directions: fingerDirections };\n\n  // step 1: calculate slopes\n  for (const finger of Finger.all) {\n    const points = Finger.getPoints(finger);\n    const slopeAtXY: Array<number> = [];\n    const slopeAtYZ: Array<number> = [];\n    for (const point of points) {\n      const point1 = landmarks[point[0]];\n      const point2 = landmarks[point[1]];\n      // calculate single slope\n      const slopes = getSlopes(point1, point2);\n      const slopeXY = slopes[0];\n      const slopeYZ = slopes[1];\n      slopeAtXY.push(slopeXY);\n      slopeAtYZ.push(slopeYZ);\n    }\n    slopesXY.push(slopeAtXY);\n    slopesYZ.push(slopeAtYZ);\n  }\n\n  // step 2: calculate orientations\n  for (const finger of Finger.all) {\n    // start finger predictions from palm - except for thumb\n    const pointIndexAt = (finger === Finger.thumb) ? 1 : 0;\n    const fingerPointsAt = Finger.getPoints(finger);\n    const startPoint = landmarks[fingerPointsAt[pointIndexAt][0]];\n    const midPoint = landmarks[fingerPointsAt[pointIndexAt + 1][1]];\n    const endPoint = landmarks[fingerPointsAt[3][1]];\n    // check if finger is curled\n    const fingerCurled = estimateFingerCurl(startPoint, midPoint, endPoint);\n    const fingerPosition = calculateFingerDirection(startPoint, midPoint, endPoint, slopesXY[finger].slice(pointIndexAt));\n    fingerCurls[finger] = fingerCurled;\n    fingerDirections[finger] = fingerPosition;\n  }\n  return { curls: fingerCurls, directions: fingerDirections };\n}\n\nexport function analyze(keypoints) { // get estimations of curl / direction for each finger\n  if (!keypoints || keypoints.length === 0) return null;\n  const estimatorRes = estimate(keypoints);\n  const landmarks = {};\n  for (const fingerIdx of Finger.all) {\n    landmarks[Finger.getName(fingerIdx)] = {\n      curl: FingerCurl.getName(estimatorRes.curls[fingerIdx]),\n      direction: FingerDirection.getName(estimatorRes.directions[fingerIdx]),\n    };\n  }\n  return landmarks;\n}\n\nexport function match(keypoints) { // compare gesture description to each known gesture\n  const poses: Array<{ name: string, confidence: number }> = [];\n  if (!keypoints || keypoints.length === 0) return poses;\n  const estimatorRes = estimate(keypoints);\n  for (const gesture of Gestures) {\n    const confidence = gesture.matchAgainst(estimatorRes.curls, estimatorRes.directions);\n    if (confidence >= minConfidence) poses.push({ name: gesture.name, confidence });\n  }\n  return poses;\n}\n", "/**\n * HandPose model implementation\n *\n * Based on: [**MediaPipe HandPose**](https://drive.google.com/file/d/1sv4sSb9BSNVZhLzxXJ0jBv9DqD-4jnAz/view)\n */\n\nimport { log } from '../util/util';\nimport * as handdetector from './handposedetector';\nimport * as handpipeline from './handposepipeline';\nimport * as fingerPose from './fingerpose';\nimport { loadModel } from '../tfjs/load';\nimport type { HandResult, Box, Point } from '../result';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nconst meshAnnotations = {\n  thumb: [1, 2, 3, 4],\n  index: [5, 6, 7, 8],\n  middle: [9, 10, 11, 12],\n  ring: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palm: [0],\n};\n\nlet handDetectorModel: GraphModel | null;\nlet handPoseModel: GraphModel | null;\nlet handPipeline: handpipeline.HandPipeline;\n\nexport async function predict(input: Tensor, config: Config): Promise<HandResult[]> {\n  const predictions = await handPipeline.estimateHands(input, config);\n  if (!predictions) return [];\n  const hands: Array<HandResult> = [];\n  for (let i = 0; i < predictions.length; i++) {\n    const annotations = {};\n    if (predictions[i].landmarks) {\n      for (const key of Object.keys(meshAnnotations)) {\n        annotations[key] = meshAnnotations[key].map((index) => predictions[i].landmarks[index]);\n      }\n    }\n    const keypoints = predictions[i].landmarks as unknown as Array<Point>;\n    let box: Box = [Number.MAX_SAFE_INTEGER, Number.MAX_SAFE_INTEGER, 0, 0]; // maximums so conditionals work\n    let boxRaw: Box = [0, 0, 0, 0];\n    if (keypoints && keypoints.length > 0) { // if we have landmarks, calculate box based on landmarks\n      for (const pt of keypoints) {\n        if (pt[0] < box[0]) box[0] = pt[0];\n        if (pt[1] < box[1]) box[1] = pt[1];\n        if (pt[0] > box[2]) box[2] = pt[0];\n        if (pt[1] > box[3]) box[3] = pt[1];\n      }\n      box[2] -= box[0];\n      box[3] -= box[1];\n      boxRaw = [box[0] / (input.shape[2] || 0), box[1] / (input.shape[1] || 0), box[2] / (input.shape[2] || 0), box[3] / (input.shape[1] || 0)];\n    } else { // otherwise use box from prediction\n      box = predictions[i].box ? [\n        Math.trunc(Math.max(0, predictions[i].box.topLeft[0])),\n        Math.trunc(Math.max(0, predictions[i].box.topLeft[1])),\n        Math.trunc(Math.min((input.shape[2] || 0), predictions[i].box.bottomRight[0]) - Math.max(0, predictions[i].box.topLeft[0])),\n        Math.trunc(Math.min((input.shape[1] || 0), predictions[i].box.bottomRight[1]) - Math.max(0, predictions[i].box.topLeft[1])),\n      ] : [0, 0, 0, 0];\n      boxRaw = [\n        (predictions[i].box.topLeft[0]) / (input.shape[2] || 0),\n        (predictions[i].box.topLeft[1]) / (input.shape[1] || 0),\n        (predictions[i].box.bottomRight[0] - predictions[i].box.topLeft[0]) / (input.shape[2] || 0),\n        (predictions[i].box.bottomRight[1] - predictions[i].box.topLeft[1]) / (input.shape[1] || 0),\n      ];\n    }\n    const landmarks = fingerPose.analyze(keypoints);\n    hands.push({\n      id: i,\n      score: Math.round(100 * predictions[i].confidence) / 100,\n      boxScore: Math.round(100 * predictions[i].boxConfidence) / 100,\n      fingerScore: Math.round(100 * predictions[i].fingerConfidence) / 100,\n      label: 'hand',\n      box,\n      boxRaw,\n      keypoints,\n      annotations: annotations as HandResult['annotations'],\n      landmarks: landmarks as HandResult['landmarks'],\n    });\n  }\n  return hands;\n}\n\nexport async function load(config: Config): Promise<[GraphModel | null, GraphModel | null]> {\n  if (env.initial) {\n    handDetectorModel = null;\n    handPoseModel = null;\n  }\n  if (!handDetectorModel || !handPoseModel) {\n    [handDetectorModel, handPoseModel] = await Promise.all([\n      config.hand.enabled ? loadModel(config.hand.detector?.modelPath) : null,\n      config.hand.landmarks ? loadModel(config.hand.skeleton?.modelPath) : null,\n    ]);\n  } else {\n    if (config.debug) log('cached model:', handDetectorModel['modelUrl']);\n    if (config.debug) log('cached model:', handPoseModel['modelUrl']);\n  }\n  const handDetector = new handdetector.HandDetector(handDetectorModel);\n  handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel);\n  return [handDetectorModel, handPoseModel];\n}\n", "/**\n * HandTrack model implementation\n *\n * Based on:\n * - Hand Detection & Skeleton: [**MediaPipe HandPose**](https://drive.google.com/file/d/1sv4sSb9BSNVZhLzxXJ0jBv9DqD-4jnAz/view)\n * - Hand Tracking: [**HandTracking**](https://github.com/victordibia/handtracking)\n */\n\nimport { log, now } from '../util/util';\nimport * as box from '../util/box';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { HandResult, HandType, Box, Point } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\nimport * as fingerPose from './fingerpose';\nimport { fakeOps } from '../tfjs/backend';\nimport { constants } from '../tfjs/constants';\n\nconst models: [GraphModel | null, GraphModel | null] = [null, null];\nconst modelOutputNodes = ['StatefulPartitionedCall/Postprocessor/Slice', 'StatefulPartitionedCall/Postprocessor/ExpandDims_1'];\n\nconst inputSize = [[0, 0], [0, 0]];\n\nconst classes = ['hand', 'fist', 'pinch', 'point', 'face', 'tip', 'pinchtip'];\nconst faceIndex = 4;\n\nconst boxExpandFact = 1.6;\nconst maxDetectorResolution = 512;\nconst detectorExpandFact = 1.4;\n\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet lastTime = 0;\nlet outputSize: [number, number] = [0, 0];\n\ntype HandDetectResult = {\n  id: number,\n  score: number,\n  box: Box,\n  boxRaw: Box,\n  label: HandType,\n}\n\nconst cache: {\n  boxes: Array<HandDetectResult>,\n  hands: Array<HandResult>;\n} = {\n  boxes: [],\n  hands: [],\n};\n\nconst fingerMap = {\n  /*\n  thumb: [0, 1, 2, 3, 4],\n  index: [0, 5, 6, 7, 8],\n  middle: [0, 9, 10, 11, 12],\n  ring: [0, 13, 14, 15, 16],\n  pinky: [0, 17, 18, 19, 20],\n  palm: [0],\n  */\n  thumb: [1, 2, 3, 4],\n  index: [5, 6, 7, 8],\n  middle: [9, 10, 11, 12],\n  ring: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  base: [0],\n  palm: [0, 17, 13, 9, 5, 1, 0],\n};\n\nexport async function loadDetect(config: Config): Promise<GraphModel> {\n  // HandTrack Model: Original: <https://github.com/victordibia/handtracking> TFJS Port: <https://github.com/victordibia/handtrack.js/>\n  if (env.initial) models[0] = null;\n  if (!models[0]) {\n    // handtrack model has some kernel ops defined in model but those are never referenced and non-existent in tfjs\n    // ideally need to prune the model itself\n    fakeOps(['tensorlistreserve', 'enter', 'tensorlistfromtensor', 'merge', 'loopcond', 'switch', 'exit', 'tensorliststack', 'nextiteration', 'tensorlistsetitem', 'tensorlistgetitem', 'reciprocal', 'shape', 'split', 'where'], config);\n    models[0] = await loadModel(config.hand.detector?.modelPath);\n    const inputs = Object.values(models[0].modelSignature['inputs']);\n    inputSize[0][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize[0][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', models[0]['modelUrl']);\n  return models[0];\n}\n\nexport async function loadSkeleton(config: Config): Promise<GraphModel> {\n  if (env.initial) models[1] = null;\n  if (!models[1]) {\n    models[1] = await loadModel(config.hand.skeleton?.modelPath);\n    const inputs = Object.values(models[1].modelSignature['inputs']);\n    inputSize[1][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize[1][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', models[1]['modelUrl']);\n  return models[1];\n}\n\nexport async function load(config: Config): Promise<[GraphModel | null, GraphModel | null]> {\n  if (!models[0]) await loadDetect(config);\n  if (!models[1]) await loadSkeleton(config);\n  return models;\n}\n\nasync function detectHands(input: Tensor, config: Config): Promise<HandDetectResult[]> {\n  const hands: HandDetectResult[] = [];\n  if (!input || !models[0]) return hands;\n  const t: Record<string, Tensor> = {};\n  const ratio = (input.shape[2] || 1) / (input.shape[1] || 1);\n  const height = Math.min(Math.round((input.shape[1] || 0) / 8) * 8, maxDetectorResolution); // use dynamic input size but cap at 512\n  const width = Math.round(height * ratio / 8) * 8;\n  t.resize = tf.image.resizeBilinear(input, [height, width]); // todo: resize with padding\n  t.cast = tf.cast(t.resize, 'int32');\n  [t.rawScores, t.rawBoxes] = await models[0].executeAsync(t.cast, modelOutputNodes) as Tensor[];\n  t.boxes = tf.squeeze(t.rawBoxes, [0, 2]);\n  t.scores = tf.squeeze(t.rawScores, [0]);\n  const classScores: Array<Tensor> = tf.unstack(t.scores, 1); // unstack scores based on classes\n  tf.dispose(classScores[faceIndex]);\n  classScores.splice(faceIndex, 1); // remove faces\n  t.filtered = tf.stack(classScores, 1); // restack\n  tf.dispose(classScores);\n  // t.filtered = t.scores;\n  t.max = tf.max(t.filtered, 1); // max overall score\n  t.argmax = tf.argMax(t.filtered, 1); // class index of max overall score\n  let id = 0;\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.max, (config.hand.maxDetected || 0) + 1, config.hand.iouThreshold || 0, config.hand.minConfidence || 1);\n  const nms = await t.nms.data();\n  const scores = await t.max.data();\n  const classNum = await t.argmax.data();\n  for (const nmsIndex of Array.from(nms)) { // generates results for each class\n    const boxSlice = tf.slice(t.boxes, nmsIndex, 1);\n    const boxYX = await boxSlice.data();\n    tf.dispose(boxSlice);\n    const boxData: Box = [boxYX[1], boxYX[0], boxYX[3] - boxYX[1], boxYX[2] - boxYX[0]]; // yx box reshaped to standard box\n    const boxRaw: Box = box.scale(boxData, detectorExpandFact);\n    const boxFull: Box = [Math.trunc(boxData[0] * outputSize[0]), Math.trunc(boxData[1] * outputSize[1]), Math.trunc(boxData[2] * outputSize[0]), Math.trunc(boxData[3] * outputSize[1])];\n    const score = scores[nmsIndex];\n    const label = classes[classNum[nmsIndex]] as HandType;\n    const hand: HandDetectResult = { id: id++, score, box: boxFull, boxRaw, label };\n    hands.push(hand);\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  hands.sort((a, b) => b.score - a.score);\n  if (hands.length > (config.hand.maxDetected || 1)) hands.length = (config.hand.maxDetected || 1);\n  return hands;\n}\n\nasync function detectFingers(input: Tensor, h: HandDetectResult, config: Config): Promise<HandResult> {\n  const hand: HandResult = { // initial values inherited from hand detect\n    id: h.id,\n    score: Math.round(100 * h.score) / 100,\n    boxScore: Math.round(100 * h.score) / 100,\n    fingerScore: 0,\n    box: h.box,\n    boxRaw: h.boxRaw,\n    label: h.label,\n    keypoints: [],\n    landmarks: {} as HandResult['landmarks'],\n    annotations: {} as HandResult['annotations'],\n  };\n  if (input && models[1] && config.hand.landmarks && h.score > (config.hand.minConfidence || 0)) {\n    const t: Record<string, Tensor> = {};\n    const boxCrop = [h.boxRaw[1], h.boxRaw[0], h.boxRaw[3] + h.boxRaw[1], h.boxRaw[2] + h.boxRaw[0]] as Box;\n    t.crop = tf.image.cropAndResize(input, [boxCrop], [0], [inputSize[1][0], inputSize[1][1]], 'bilinear');\n    t.div = tf.div(t.crop, constants.tf255);\n    [t.score, t.keypoints] = models[1].execute(t.div, ['Identity_1', 'Identity']) as Tensor[];\n    const rawScore = (await t.score.data())[0];\n    const score = (100 - Math.trunc(100 / (1 + Math.exp(rawScore)))) / 100; // reverse sigmoid value\n    if (score >= (config.hand.minConfidence || 0)) {\n      hand.fingerScore = score;\n      t.reshaped = tf.reshape(t.keypoints, [-1, 3]);\n      const coordsData: Point[] = await t.reshaped.array() as Point[];\n      const coordsRaw: Point[] = coordsData.map((kpt) => [kpt[0] / inputSize[1][1], kpt[1] / inputSize[1][0], (kpt[2] || 0)]);\n      const coordsNorm: Point[] = coordsRaw.map((kpt) => [kpt[0] * h.boxRaw[2], kpt[1] * h.boxRaw[3], (kpt[2] || 0)]);\n      hand.keypoints = (coordsNorm).map((kpt) => [outputSize[0] * (kpt[0] + h.boxRaw[0]), outputSize[1] * (kpt[1] + h.boxRaw[1]), (kpt[2] || 0)]);\n      hand.landmarks = fingerPose.analyze(hand.keypoints) as HandResult['landmarks']; // calculate finger gestures\n      for (const key of Object.keys(fingerMap)) { // map keypoints to per-finger annotations\n        hand.annotations[key] = fingerMap[key].map((index: number) => (hand.landmarks && hand.keypoints[index] ? hand.keypoints[index] : null));\n      }\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  }\n  return hand;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<HandResult[]> {\n  if (!models[0] || !models[1] || !models[0]?.inputs[0].shape || !models[1]?.inputs[0].shape) return []; // something is wrong with the model\n  outputSize = [input.shape[2] || 0, input.shape[1] || 0];\n  skipped++; // increment skip frames\n  const skipTime = (config.hand.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.hand.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame) {\n    return cache.hands; // return cached results without running anything\n  }\n  return new Promise(async (resolve) => {\n    const skipTimeExtended = 3 * (config.hand.skipTime || 0) > (now() - lastTime);\n    const skipFrameExtended = skipped < 3 * (config.hand.skipFrames || 0);\n    if (config.skipAllowed && cache.hands.length === config.hand.maxDetected) { // we have all detected hands so we're definitely skipping\n      cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));\n    } else if (config.skipAllowed && skipTimeExtended && skipFrameExtended && cache.hands.length > 0) { // we have some cached results: maybe not enough but anyhow continue for bit longer\n      cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));\n    } else { // finally rerun detector\n      cache.boxes = await detectHands(input, config);\n      lastTime = now();\n      cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));\n      skipped = 0;\n    }\n\n    const oldCache = [...cache.boxes];\n    cache.boxes.length = 0; // reset cache\n    if (config.cacheSensitivity > 0) {\n      for (let i = 0; i < cache.hands.length; i++) {\n        const boxKpt = box.square(cache.hands[i].keypoints, outputSize);\n        if (boxKpt.box[2] / (input.shape[2] || 1) > 0.05 && boxKpt.box[3] / (input.shape[1] || 1) > 0.05 && cache.hands[i].fingerScore && cache.hands[i].fingerScore > (config.hand.minConfidence || 0)) {\n          const boxScale = box.scale(boxKpt.box, boxExpandFact);\n          const boxScaleRaw = box.scale(boxKpt.boxRaw, boxExpandFact);\n          // const boxCrop = box.crop(boxScaleRaw);\n          cache.boxes.push({ ...oldCache[i], box: boxScale, boxRaw: boxScaleRaw });\n        }\n      }\n    }\n    for (let i = 0; i < cache.hands.length; i++) { // replace detected boxes with calculated boxes in final output\n      const bbox = box.calc(cache.hands[i].keypoints, outputSize);\n      cache.hands[i].box = bbox.box;\n      cache.hands[i].boxRaw = bbox.boxRaw;\n    }\n    resolve(cache.hands);\n  });\n}\n", "/**\n * Anti-spoofing model implementation\n */\n\nimport { log, now } from '../util/util';\nimport { loadModel } from '../tfjs/load';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst cached: Array<number> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet lastCount = 0;\nlet lastTime = 0;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.liveness?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<number> {\n  if (!model) return 0;\n  const skipTime = (config.face.liveness?.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.face.liveness?.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && cached[idx]) {\n    skipped++;\n    return cached[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape ? model.inputs[0].shape[2] : 0, model?.inputs[0].shape ? model.inputs[0].shape[1] : 0], false);\n    const res = model?.execute(resize) as Tensor;\n    const num = (await res.data())[0];\n    cached[idx] = Math.round(100 * num) / 100;\n    lastCount = count;\n    lastTime = now();\n    tf.dispose([resize, res]);\n    resolve(cached[idx]);\n  });\n}\n", "export const kpt: Array<string> = [ // used to create part labels\n  'nose',\n  'leftEye',\n  'rightEye',\n  'leftEar',\n  'rightEar',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n];\n\nexport const horizontal: Array<string[]> = [ // used to fix left vs right\n  ['leftEye', 'rightEye'],\n  ['leftEar', 'rightEar'],\n  ['leftShoulder', 'rightShoulder'],\n  ['leftElbow', 'rightElbow'],\n  ['leftWrist', 'rightWrist'],\n  ['leftHip', 'rightHip'],\n  ['leftKnee', 'rightKnee'],\n  ['leftAnkle', 'rightAnkle'],\n];\n\nexport const vertical: Array<string[]> = [ // used to remove unlikely keypoint positions\n  ['leftKnee', 'leftShoulder'],\n  ['rightKnee', 'rightShoulder'],\n  ['leftAnkle', 'leftKnee'],\n  ['rightAnkle', 'rightKnee'],\n];\n\nexport const relative: Array<string[][]> = [ // used to match relative body parts\n  [['leftHip', 'rightHip'], ['leftShoulder', 'rightShoulder']],\n  [['leftElbow', 'rightElbow'], ['leftShoulder', 'rightShoulder']],\n];\n\nexport const connected: Record<string, string[]> = { // used to create body outline in annotations\n  leftLeg: ['leftHip', 'leftKnee', 'leftAnkle'],\n  rightLeg: ['rightHip', 'rightKnee', 'rightAnkle'],\n  torso: ['leftShoulder', 'rightShoulder', 'rightHip', 'leftHip', 'leftShoulder'],\n  leftArm: ['leftShoulder', 'leftElbow', 'leftWrist'],\n  rightArm: ['rightShoulder', 'rightElbow', 'rightWrist'],\n  head: [],\n};\n", "import type { BodyKeypoint, BodyResult } from '../result';\nimport * as box from '../util/box';\nimport * as coords from './movenetcoords';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from '../tfjs/types';\n\nconst maxJitter = 0.005; // default allowed jitter is within 0.5%\n\nconst cache: {\n  keypoints: Array<BodyKeypoint>,\n  padding: [number, number][];\n} = {\n  keypoints: [],\n  padding: [[0, 0], [0, 0], [0, 0], [0, 0]],\n};\n\nexport function bodyParts(body: BodyResult) { // model sometimes mixes up left vs right keypoints so we fix them\n  for (const pair of coords.horizontal) { // fix body parts left vs right\n    const left = body.keypoints.findIndex((kp) => kp.part === pair[0]);\n    const right = body.keypoints.findIndex((kp) => kp.part === pair[1]);\n    if (body.keypoints[left] && body.keypoints[right]) {\n      if (body.keypoints[left].position[0] < body.keypoints[right].position[0]) {\n        const tmp = body.keypoints[left];\n        body.keypoints[left] = body.keypoints[right];\n        body.keypoints[right] = tmp;\n      }\n    }\n  }\n  for (const pair of coords.vertical) { // remove body parts with improbable vertical position\n    const lower = body.keypoints.findIndex((kp) => (kp && kp.part === pair[0]));\n    const higher = body.keypoints.findIndex((kp) => (kp && kp.part === pair[1]));\n    if (body.keypoints[lower] && body.keypoints[higher]) {\n      if (body.keypoints[lower].position[1] < body.keypoints[higher].position[1]) {\n        body.keypoints.splice(lower, 1);\n      }\n    }\n  }\n  for (const [pair, compare] of coords.relative) { // rearrange body parts according to their relative position\n    const left = body.keypoints.findIndex((kp) => (kp && kp.part === pair[0]));\n    const right = body.keypoints.findIndex((kp) => (kp && kp.part === pair[1]));\n    const leftTo = body.keypoints.findIndex((kp) => (kp && kp.part === compare[0]));\n    const rightTo = body.keypoints.findIndex((kp) => (kp && kp.part === compare[1]));\n    if (!body.keypoints[leftTo] || !body.keypoints[rightTo]) continue; // only if we have both compare points\n    const distanceLeft = body.keypoints[left] ? [\n      Math.abs(body.keypoints[leftTo].position[0] - body.keypoints[left].position[0]),\n      Math.abs(body.keypoints[rightTo].position[0] - body.keypoints[left].position[0]),\n    ] : [0, 0];\n    const distanceRight = body.keypoints[right] ? [\n      Math.abs(body.keypoints[rightTo].position[0] - body.keypoints[right].position[0]),\n      Math.abs(body.keypoints[leftTo].position[0] - body.keypoints[right].position[0]),\n    ] : [0, 0];\n    if (distanceLeft[0] > distanceLeft[1] || distanceRight[0] > distanceRight[1]) { // should flip keypoints\n      const tmp = body.keypoints[left];\n      body.keypoints[left] = body.keypoints[right];\n      body.keypoints[right] = tmp;\n    }\n  }\n}\n\nexport function jitter(keypoints: Array<BodyKeypoint>): Array<BodyKeypoint> {\n  for (let i = 0; i < keypoints.length; i++) {\n    if (keypoints[i] && cache.keypoints[i]) {\n      const diff = [Math.abs(keypoints[i].positionRaw[0] - cache.keypoints[i].positionRaw[0]), Math.abs(keypoints[i].positionRaw[1] - cache.keypoints[i].positionRaw[1])];\n      if (diff[0] < maxJitter && diff[1] < maxJitter) {\n        keypoints[i] = cache.keypoints[i]; // below jitter so replace keypoint\n      } else {\n        cache.keypoints[i] = keypoints[i]; // above jitter so update cache\n      }\n    } else {\n      cache.keypoints[i] = keypoints[i]; // cache for keypoint doesnt exist so create it here\n    }\n  }\n  return keypoints;\n}\n\nexport function padInput(input: Tensor, inputSize: number): Tensor {\n  const t: Record<string, Tensor> = {};\n  if (!input.shape || !input.shape[1] || !input.shape[2]) return input;\n  cache.padding = [\n    [0, 0], // dont touch batch\n    [input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0, input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0], // height before&after\n    [input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0, input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0], // width before&after\n    [0, 0], // dont touch rbg\n  ];\n  t.pad = tf.pad(input, cache.padding);\n  t.resize = tf.image.resizeBilinear(t.pad, [inputSize, inputSize]);\n  const final = tf.cast(t.resize, 'int32');\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return final;\n}\n\nexport function rescaleBody(body: BodyResult, outputSize: [number, number]): BodyResult {\n  body.keypoints = body.keypoints.filter((kpt) => kpt && kpt.position); // filter invalid keypoints\n  for (const kpt of body.keypoints) {\n    kpt.position = [\n      kpt.position[0] * (outputSize[0] + cache.padding[2][0] + cache.padding[2][1]) / outputSize[0] - cache.padding[2][0],\n      kpt.position[1] * (outputSize[1] + cache.padding[1][0] + cache.padding[1][1]) / outputSize[1] - cache.padding[1][0],\n    ];\n    kpt.positionRaw = [\n      kpt.position[0] / outputSize[0], kpt.position[1] / outputSize[1],\n    ];\n  }\n  const rescaledBoxes = box.calc(body.keypoints.map((pt) => pt.position), outputSize);\n  body.box = rescaledBoxes.box;\n  body.boxRaw = rescaledBoxes.boxRaw;\n  return body;\n}\n", "/**\n * MoveNet model implementation\n *\n * Based on: [**MoveNet**](https://blog.tensorflow.org/2021/05/next-generation-pose-detection-with-movenet-and-tensorflowjs.html)\n */\n\nimport { log, now } from '../util/util';\nimport * as box from '../util/box';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as coords from './movenetcoords';\nimport * as fix from './movenetfix';\nimport { loadModel } from '../tfjs/load';\nimport type { BodyKeypoint, BodyResult, BodyLandmark, BodyAnnotation, Box, Point } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { fakeOps } from '../tfjs/backend';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nlet inputSize = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n// const boxExpandFact = 1.5; // increase to 150%\n\nconst cache: {\n  boxes: Array<Box>, // unused\n  bodies: Array<BodyResult>;\n  last: number,\n} = {\n  boxes: [],\n  bodies: [],\n  last: 0,\n};\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) {\n    fakeOps(['size'], config);\n    model = await loadModel(config.body.modelPath);\n  } else if (config.debug) log('cached model:', model['modelUrl']);\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  if (inputSize < 64) inputSize = 256;\n  return model;\n}\n\nasync function parseSinglePose(res, config, image) {\n  const kpt = res[0][0];\n  const keypoints: Array<BodyKeypoint> = [];\n  let score = 0;\n  for (let id = 0; id < kpt.length; id++) {\n    score = kpt[id][2];\n    if (score > config.body.minConfidence) {\n      const positionRaw: Point = [kpt[id][1], kpt[id][0]];\n      keypoints.push({\n        score: Math.round(100 * score) / 100,\n        part: coords.kpt[id] as BodyLandmark,\n        positionRaw,\n        position: [ // normalized to input image size\n          Math.round((image.shape[2] || 0) * positionRaw[0]),\n          Math.round((image.shape[1] || 0) * positionRaw[1]),\n        ],\n      });\n    }\n  }\n  score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n  const bodies: Array<BodyResult> = [];\n  const newBox = box.calc(keypoints.map((pt) => pt.position), [image.shape[2], image.shape[1]]);\n  const annotations: Record<string, Point[][]> = {};\n  for (const [name, indexes] of Object.entries(coords.connected)) {\n    const pt: Array<Point[]> = [];\n    for (let i = 0; i < indexes.length - 1; i++) {\n      const pt0 = keypoints.find((kp) => kp.part === indexes[i]);\n      const pt1 = keypoints.find((kp) => kp.part === indexes[i + 1]);\n      if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n    }\n    annotations[name] = pt;\n  }\n  const body: BodyResult = { id: 0, score, box: newBox.box, boxRaw: newBox.boxRaw, keypoints, annotations };\n  fix.bodyParts(body);\n  bodies.push(body);\n  return bodies;\n}\n\nasync function parseMultiPose(res, config, image) {\n  const bodies: Array<BodyResult> = [];\n  for (let id = 0; id < res[0].length; id++) {\n    const kpt = res[0][id];\n    const totalScore = Math.round(100 * kpt[51 + 4]) / 100;\n    if (totalScore > config.body.minConfidence) {\n      const keypoints: Array<BodyKeypoint> = [];\n      for (let i = 0; i < 17; i++) {\n        const score = kpt[3 * i + 2];\n        if (score > config.body.minConfidence) {\n          const positionRaw: Point = [kpt[3 * i + 1], kpt[3 * i + 0]];\n          keypoints.push({\n            part: coords.kpt[i] as BodyLandmark,\n            score: Math.round(100 * score) / 100,\n            positionRaw,\n            position: [Math.round((image.shape[2] || 0) * positionRaw[0]), Math.round((image.shape[1] || 0) * positionRaw[1])],\n          });\n        }\n      }\n      const newBox = box.calc(keypoints.map((pt) => pt.position), [image.shape[2], image.shape[1]]);\n      // movenet-multipose has built-in box details\n      // const boxRaw: Box = [kpt[51 + 1], kpt[51 + 0], kpt[51 + 3] - kpt[51 + 1], kpt[51 + 2] - kpt[51 + 0]];\n      // const box: Box = [Math.trunc(boxRaw[0] * (image.shape[2] || 0)), Math.trunc(boxRaw[1] * (image.shape[1] || 0)), Math.trunc(boxRaw[2] * (image.shape[2] || 0)), Math.trunc(boxRaw[3] * (image.shape[1] || 0))];\n      const annotations: Record<BodyAnnotation, Point[][]> = {} as Record<BodyAnnotation, Point[][]>;\n      for (const [name, indexes] of Object.entries(coords.connected)) {\n        const pt: Array<Point[]> = [];\n        for (let i = 0; i < indexes.length - 1; i++) {\n          const pt0 = keypoints.find((kp) => kp.part === indexes[i]);\n          const pt1 = keypoints.find((kp) => kp.part === indexes[i + 1]);\n          if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n        }\n        annotations[name] = pt;\n      }\n      const body: BodyResult = { id, score: totalScore, box: newBox.box, boxRaw: newBox.boxRaw, keypoints: [...keypoints], annotations };\n      fix.bodyParts(body);\n      bodies.push(body);\n    }\n  }\n  bodies.sort((a, b) => b.score - a.score);\n  if (bodies.length > config.body.maxDetected) bodies.length = config.body.maxDetected;\n  return bodies;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {\n  if (!model || !model?.inputs[0].shape) return []; // something is wrong with the model\n  if (!config.skipAllowed) cache.boxes.length = 0; // allowed to use cache or not\n  skipped++; // increment skip frames\n  const skipTime = (config.body.skipTime || 0) > (now() - cache.last);\n  const skipFrame = skipped < (config.body.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame) {\n    return cache.bodies; // return cached results without running anything\n  }\n  return new Promise(async (resolve) => {\n    const t: Record<string, Tensor> = {};\n    skipped = 0;\n    // run detection on squared input and cached boxes\n    /*\n    cache.bodies = []; // reset bodies result\n    if (cache.boxes.length >= (config.body.maxDetected || 0)) { // if we have enough cached boxes run detection using cache\n      for (let i = 0; i < cache.boxes.length; i++) { // run detection based on cached boxes\n        t.crop = tf.image.cropAndResize(input, [cache.boxes[i]], [0], [inputSize, inputSize], 'bilinear');\n        t.cast = tf.cast(t.crop, 'int32');\n        // t.input = prepareImage(input);\n        t.res = model?.execute(t.cast) as Tensor;\n        const res = await t.res.array();\n        const newBodies = (t.res.shape[2] === 17) ? await parseSinglePose(res, config, input, cache.boxes[i]) : await parseMultiPose(res, config, input, cache.boxes[i]);\n        cache.bodies = cache.bodies.concat(newBodies);\n        Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n      }\n    }\n    if (cache.bodies.length !== config.body.maxDetected) { // did not find enough bodies based on cached boxes so run detection on full frame\n      t.input = prepareImage(input);\n      t.res = model?.execute(t.input) as Tensor;\n      const res = await t.res.array();\n      cache.bodies = (t.res.shape[2] === 17) ? await parseSinglePose(res, config, input, [0, 0, 1, 1]) : await parseMultiPose(res, config, input, [0, 0, 1, 1]);\n      for (const body of cache.bodies) rescaleBody(body, [input.shape[2] || 1, input.shape[1] || 1]);\n      Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    }\n    cache.boxes.length = 0; // reset cache\n    for (let i = 0; i < cache.bodies.length; i++) {\n      if (cache.bodies[i].keypoints.length > (coords.kpt.length / 2)) { // only update cache if we detected at least half keypoints\n        const scaledBox = box.scale(cache.bodies[i].boxRaw, boxExpandFact);\n        const cropBox = box.crop(scaledBox);\n        cache.boxes.push(cropBox);\n      }\n    }\n    */\n\n    // run detection on squared input and no cached boxes\n    t.input = fix.padInput(input, inputSize);\n    t.res = model?.execute(t.input) as Tensor;\n    cache.last = now();\n    const res = await t.res.array();\n    cache.bodies = (t.res.shape[2] === 17)\n      ? await parseSinglePose(res, config, input)\n      : await parseMultiPose(res, config, input);\n    for (const body of cache.bodies) {\n      fix.rescaleBody(body, [input.shape[2] || 1, input.shape[1] || 1]);\n      fix.jitter(body.keypoints);\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n\n    resolve(cache.bodies);\n  });\n}\n", "/**\n * NanoDet object detection model implementation\n *\n * Based on: [**MB3-CenterNet**](https://github.com/610265158/mobilenetv3_centernet)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport { labels } from './labels';\nimport type { ObjectResult, ObjectType, Box } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel;\nlet last: Array<ObjectResult> = [];\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet inputSize = 0;\n\nconst scaleBox = 2.5; // increase box size\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (!model || env.initial) {\n    model = await loadModel(config.object.modelPath);\n    const inputs = Object.values(model.modelSignature['inputs']);\n    inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nasync function process(res: Tensor[], outputShape: [number, number], config: Config) {\n  let id = 0;\n  let results: Array<ObjectResult> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(async () => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      const scoresT = tf.squeeze(res.find((a: Tensor) => (a.shape[1] === (baseSize ** 2) && (a.shape[2] || 0) === labels.length)));\n      const featuresT = tf.squeeze(res.find((a: Tensor) => (a.shape[1] === (baseSize ** 2) && (a.shape[2] || 0) < labels.length)));\n      const boxesMax = featuresT.reshape([-1, 4, featuresT.shape[1] / 4]); // reshape [output] to [4, output / 4] where number is number of different features inside each stride\n      const boxIdx = await boxesMax.argMax(2).array(); // what we need is indexes of features with highest scores, not values itself\n      const scores = await scoresT.array(); // optionally use exponential scores or just as-is\n      for (let i = 0; i < scoresT.shape[0]; i++) { // total strides (x * y matrix)\n        for (let j = 0; j < scoresT.shape[1]; j++) { // one score for each class\n          const score = scores[i][j]; // get score for current position\n          if (score > (config.object.minConfidence || 0) && j !== 61) {\n            const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n            const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n            const boxOffset = boxIdx[i].map((a: number) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n            const [x, y] = [\n              cx - (scaleBox / strideSize * boxOffset[0]),\n              cy - (scaleBox / strideSize * boxOffset[1]),\n            ];\n            const [w, h] = [\n              cx + (scaleBox / strideSize * boxOffset[2]) - x,\n              cy + (scaleBox / strideSize * boxOffset[3]) - y,\n            ];\n            let boxRaw: Box = [x, y, w, h]; // results normalized to range 0..1\n            boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))) as Box; // fix out-of-bounds coords\n            const box = [ // results normalized to input image pixels\n              boxRaw[0] * outputShape[0],\n              boxRaw[1] * outputShape[1],\n              boxRaw[2] * outputShape[0],\n              boxRaw[3] * outputShape[1],\n            ];\n            const result = {\n              id: id++,\n              // strideSize,\n              score: Math.round(100 * score) / 100,\n              class: j + 1,\n              label: labels[j].label as ObjectType,\n              // center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n              // centerRaw: [cx, cy],\n              box: box.map((a) => Math.trunc(a)) as Box,\n              boxRaw,\n            };\n            results.push(result);\n          }\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => [a.boxRaw[1], a.boxRaw[0], a.boxRaw[3], a.boxRaw[2]]); // switches coordinates from x,y to y,x as expected by tf.nms\n  const nmsScores = results.map((a) => a.score);\n  let nmsIdx: Array<number> = [];\n  if (nmsBoxes && nmsBoxes.length > 0) {\n    const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxDetected, config.object.iouThreshold, config.object.minConfidence);\n    nmsIdx = await nms.data();\n    tf.dispose(nms);\n  }\n\n  // filter & sort results\n  results = results\n    .filter((_val, idx) => nmsIdx.includes(idx))\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image: Tensor, config: Config): Promise<ObjectResult[]> {\n  const skipTime = (config.object.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.object.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  skipped = 0;\n  if (!env.kernels.includes('mod') || !env.kernels.includes('sparsetodense')) return last;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2] || 0, image.shape[1] || 0];\n    const resize = tf.image.resizeBilinear(image, [inputSize, inputSize], false);\n    const norm = tf.div(resize, constants.tf255);\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    tf.dispose(norm);\n    tf.dispose(resize);\n\n    let objectT;\n    if (config.object.enabled) objectT = model.execute(transpose);\n    lastTime = now();\n    tf.dispose(transpose);\n\n    const obj = await process(objectT as Tensor[], outputSize as [number, number], config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "/**\n * PoseNet body detection model implementation constants\n * See `posenet.ts` for entry point\n */\n\nimport type { Point, BodyResult, BodyAnnotation, BodyLandmark } from '../result';\n\nexport const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const count = partNames.length; // 17 keypoints\n\nexport const partIds = partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport function eitherPointDoesntMeetConfidence(a: number, b: number, minConfidence: number) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence: number) {\n  return connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nexport function getBoundingBox(keypoints): [number, number, number, number] {\n  const coord = keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: Number.NEGATIVE_INFINITY,\n    maxY: Number.NEGATIVE_INFINITY,\n    minX: Number.POSITIVE_INFINITY,\n    minY: Number.POSITIVE_INFINITY,\n  });\n  return [coord.minX, coord.minY, coord.maxX - coord.minX, coord.maxY - coord.minY];\n}\n\nexport function scalePoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]): Array<BodyResult> {\n  const scaleY = height / inputResolutionHeight;\n  const scaleX = width / inputResolutionWidth;\n  const scalePose = (pose, i): BodyResult => ({\n    id: i,\n    score: pose.score,\n    boxRaw: [pose.box[0] / inputResolutionWidth, pose.box[1] / inputResolutionHeight, pose.box[2] / inputResolutionWidth, pose.box[3] / inputResolutionHeight],\n    box: [Math.trunc(pose.box[0] * scaleX), Math.trunc(pose.box[1] * scaleY), Math.trunc(pose.box[2] * scaleX), Math.trunc(pose.box[3] * scaleY)],\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score: score as number,\n      part: part as BodyLandmark,\n      position: [Math.trunc(position.x * scaleX), Math.trunc(position.y * scaleY)] as Point,\n      positionRaw: [position.x / inputResolutionHeight, position.y / inputResolutionHeight] as Point,\n    })),\n    annotations: {} as Record<BodyAnnotation, Point[][]>,\n  });\n  const scaledPoses = poses.map((pose, i) => scalePose(pose, i));\n  return scaledPoses;\n}\n\n// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nexport class MaxHeap {\n  priorityQueue: Array<unknown>; // don't touch\n  numberOfElements: number;\n  getElementValue: unknown; // function call\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() { return this.numberOfElements === -1; }\n\n  size() { return this.numberOfElements + 1; }\n\n  all() { return this.priorityQueue.slice(0, this.numberOfElements + 1); }\n\n  max() { return this.priorityQueue[0]; }\n\n  swim(k) {\n    while (k > 0 && this.less(Math.floor(k / 2), k)) {\n      this.exchange(k, Math.floor(k / 2));\n      k = Math.floor(k / 2);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    // @ts-ignore getter is of unknown type\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + count),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "/**\n * PoseNet body detection model implementation\n *\n * Based on: [**PoseNet**](https://medium.com/tensorflow/real-time-human-pose-estimation-in-the-browser-with-tensorflow-js-7dd0bc881cd5)\n */\n\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { BodyResult, BodyLandmark, Box } from '../result';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\nimport * as utils from './posenetutils';\n\nlet model: GraphModel;\nconst poseNetOutputs = ['MobilenetV1/offset_2/BiasAdd'/* offsets */, 'MobilenetV1/heatmap_2/BiasAdd'/* heatmapScores */, 'MobilenetV1/displacement_fwd_2/BiasAdd'/* displacementFwd */, 'MobilenetV1/displacement_bwd_2/BiasAdd'/* displacementBwd */];\nconst localMaximumRadius = 1;\nconst outputStride = 16;\nconst squaredNmsRadius = 50 ** 2;\n\nfunction traverse(edgeId, sourceKeypoint, targetId, scores, offsets, displacements, offsetRefineStep = 2) {\n  const getDisplacement = (point) => ({\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, (displacements.shape[2] / 2) + edgeId),\n  });\n  const getStridedIndexNearPoint = (point, height, width) => ({\n    y: utils.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: utils.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  });\n\n  const [height, width] = scores.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, height, width);\n  const displacement = getDisplacement(sourceKeypointIndices);\n  const displacedPoint = utils.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, height, width);\n    const offsetPoint = utils.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetId, offsets);\n    targetKeypoint = utils.addVectors(\n      { x: targetKeypointIndices.x * outputStride, y: targetKeypointIndices.y * outputStride },\n      { x: offsetPoint.x, y: offsetPoint.y },\n    );\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, height, width);\n  const score = scores.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetId);\n  return { position: targetKeypoint, part: utils.partNames[targetId], score };\n}\n\nexport function decodePose(root, scores, offsets, displacementsFwd, displacementsBwd) {\n  const tuples = utils.poseChain.map(([parentJoinName, childJoinName]) => ([utils.partIds[parentJoinName], utils.partIds[childJoinName]]));\n  const edgesFwd = tuples.map(([, childJointId]) => childJointId);\n  const edgesBwd = tuples.map(([parentJointId]) => parentJointId);\n  const numParts = scores.shape[2]; // [21,21,17]\n  const numEdges = edgesFwd.length;\n  const keypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const rootPoint = utils.getImageCoords(root.part, outputStride, offsets);\n  keypoints[root.part.id] = {\n    score: root.score,\n    part: utils.partNames[root.part.id] as BodyLandmark,\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceId = edgesFwd[edge];\n    const targetId = edgesBwd[edge];\n    if (keypoints[sourceId] && !keypoints[targetId]) {\n      keypoints[targetId] = traverse(edge, keypoints[sourceId], targetId, scores, offsets, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceId = edgesBwd[edge];\n    const targetId = edgesFwd[edge];\n    if (keypoints[sourceId] && !keypoints[targetId]) {\n      keypoints[targetId] = traverse(edge, keypoints[sourceId], targetId, scores, offsets, displacementsFwd);\n    }\n  }\n  return keypoints;\n}\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(minConfidence, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new utils.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < minConfidence) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, scores)) queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n      }\n    }\n  }\n  return queue;\n}\n\nfunction withinRadius(poses, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId]?.position;\n    if (!correspondingKeypoint) return false;\n    return utils.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, keypoints) {\n  const notOverlappedKeypointScores = keypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinRadius(existingPoses, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / keypoints.length;\n}\n\nexport function decode(offsets, scores, displacementsFwd, displacementsBwd, maxDetected, minConfidence) {\n  const poses: Array<{ keypoints, box: Box, score: number }> = [];\n  const queue = buildPartWithScoreQueue(minConfidence, scores);\n  // Generate at most maxDetected object instances per image in decreasing root part score order.\n  while (poses.length < maxDetected && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    // @ts-ignore this one is tree walk\n    const rootImageCoords = utils.getImageCoords(root.part, outputStride, offsets);\n    // @ts-ignore this one is tree walk\n    if (withinRadius(poses, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    let keypoints = decodePose(root, scores, offsets, displacementsFwd, displacementsBwd);\n    keypoints = keypoints.filter((a) => a.score > minConfidence);\n    const score = getInstanceScore(poses, keypoints);\n    const box = utils.getBoundingBox(keypoints);\n    if (score > minConfidence) poses.push({ keypoints, box, score: Math.round(100 * score) / 100 });\n  }\n  return poses;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {\n  /** posenet is mostly obsolete\n   * caching is not implemented\n   */\n  const res = tf.tidy(() => {\n    if (!model.inputs[0].shape) return [];\n    const resized = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n    const normalized = tf.sub(tf.div(tf.cast(resized, 'float32'), 127.5), 1.0);\n    const results: Array<Tensor> = model.execute(normalized, poseNetOutputs) as Array<Tensor>;\n    const results3d = results.map((y) => tf.squeeze(y, [0]));\n    results3d[1] = tf.sigmoid(results3d[1]); // apply sigmoid on scores\n    return results3d;\n  });\n\n  const buffers = await Promise.all(res.map((tensor: Tensor) => tensor.buffer()));\n  for (const t of res) tf.dispose(t);\n\n  const decoded = await decode(buffers[0], buffers[1], buffers[2], buffers[3], config.body.maxDetected, config.body.minConfidence);\n  if (!model.inputs[0].shape) return [];\n  const scaled = utils.scalePoses(decoded, [input.shape[1], input.shape[2]], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) as BodyResult[];\n  return scaled;\n}\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (!model || env.initial) model = await loadModel(config.body.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n", "/**\n * Image segmentation for body detection model\n *\n * Based on:\n * - [**MediaPipe Meet**](https://drive.google.com/file/d/1lnP1bRi9CSqQQXUHa13159vLELYDgDu0/preview)\n * - [**MediaPipe Selfie**](https://drive.google.com/file/d/1dCfozqknMa068vVsO2j_1FgZkW_e3VWv/preview)\n */\n\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport * as image from '../image/image';\nimport { constants } from '../tfjs/constants';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\nimport type { Input, AnyCanvas } from '../exports';\n\nlet model: GraphModel;\nlet busy = false;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (!model || env.initial) model = await loadModel(config.segmentation.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function process(input: Input, background: Input | undefined, config: Config)\n: Promise<{ data: Array<number> | Tensor, canvas: AnyCanvas | null, alpha: AnyCanvas | null }> {\n  if (busy) return { data: [], canvas: null, alpha: null };\n  busy = true;\n  if (!model) await load(config);\n  const inputImage = await image.process(input, config);\n  const width = inputImage.tensor?.shape[2] || 0;\n  const height = inputImage.tensor?.shape[1] || 0;\n  if (!inputImage.tensor) return { data: [], canvas: null, alpha: null };\n  const t: Record<string, Tensor> = {};\n\n  t.resize = tf.image.resizeBilinear(inputImage.tensor, [model.inputs[0].shape ? model.inputs[0].shape[1] : 0, model.inputs[0].shape ? model.inputs[0].shape[2] : 0], false);\n  tf.dispose(inputImage.tensor);\n  t.norm = tf.div(t.resize, constants.tf255);\n  t.res = model.execute(t.norm) as Tensor;\n\n  t.squeeze = tf.squeeze(t.res, 0); // meet.shape:[1,256,256,1], selfie.shape:[1,144,256,2]\n  if (t.squeeze.shape[2] === 2) {\n    t.softmax = tf.softmax(t.squeeze); // model meet has two channels for fg and bg\n    [t.bg, t.fg] = tf.unstack(t.softmax, 2);\n    t.expand = tf.expandDims(t.fg, 2);\n    t.pad = tf.expandDims(t.expand, 0);\n    t.crop = tf.image.cropAndResize(t.pad, [[0, 0, 0.5, 0.5]], [0], [width, height]);\n    // running sofmax before unstack creates 2x2 matrix so we only take upper-left quadrant\n    // otherwise run softmax after unstack and use standard resize\n    // resizeOutput = tf.image.resizeBilinear(expand, [input.tensor?.shape[1], input.tensor?.shape[2]]);\n    t.data = tf.squeeze(t.crop, 0);\n  } else {\n    t.data = tf.image.resizeBilinear(t.squeeze, [height, width]); // model selfie has a single channel that we can use directly\n  }\n  const data = Array.from(await t.data.data()) as number[];\n\n  if (env.node && !env.Canvas && (typeof ImageData === 'undefined')) {\n    if (config.debug) log('canvas support missing');\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return { data, canvas: null, alpha: null }; // running in nodejs so return alpha array as-is\n  }\n\n  const alphaCanvas = image.canvas(width, height);\n  // @ts-ignore browser is not defined in tfjs-node\n  if (tf.browser) await tf.browser.toPixels(t.data, alphaCanvas);\n  const alphaCtx = alphaCanvas.getContext('2d') as CanvasRenderingContext2D;\n  if (config.segmentation.blur && config.segmentation.blur > 0) alphaCtx.filter = `blur(${config.segmentation.blur}px)`; // use css filter for bluring, can be done with gaussian blur manually instead\n  const alphaData = alphaCtx.getImageData(0, 0, width, height);\n\n  const compositeCanvas = image.canvas(width, height);\n  const compositeCtx = compositeCanvas.getContext('2d') as CanvasRenderingContext2D;\n  if (inputImage.canvas) compositeCtx.drawImage(inputImage.canvas, 0, 0);\n  compositeCtx.globalCompositeOperation = 'darken'; // https://developer.mozilla.org/en-US/docs/Web/API/CanvasRenderingContext2D/globalCompositeOperation // best options are: darken, color-burn, multiply\n  if (config.segmentation.blur && config.segmentation.blur > 0) compositeCtx.filter = `blur(${config.segmentation.blur}px)`; // use css filter for bluring, can be done with gaussian blur manually instead\n  compositeCtx.drawImage(alphaCanvas, 0, 0);\n  compositeCtx.globalCompositeOperation = 'source-over'; // reset composite operation\n  compositeCtx.filter = 'none'; // reset css filter\n  const compositeData = compositeCtx.getImageData(0, 0, width, height);\n  for (let i = 0; i < width * height; i++) compositeData.data[4 * i + 3] = alphaData.data[4 * i + 0]; // copy original alpha value to new composite canvas\n  compositeCtx.putImageData(compositeData, 0, 0);\n\n  let mergedCanvas: AnyCanvas | null = null;\n  if (background && compositeCanvas) { // draw background with segmentation as overlay if background is present\n    mergedCanvas = image.canvas(width, height);\n    const bgImage = await image.process(background, config);\n    tf.dispose(bgImage.tensor);\n    const ctxMerge = mergedCanvas.getContext('2d') as CanvasRenderingContext2D;\n    ctxMerge.drawImage(bgImage.canvas as HTMLCanvasElement, 0, 0, mergedCanvas.width, mergedCanvas.height);\n    ctxMerge.drawImage(compositeCanvas, 0, 0);\n  }\n\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  busy = false;\n  // return { data, canvas: mergedCanvas || compositeCanvas, alpha: alphaCanvas };\n  return { data, canvas: compositeCanvas, alpha: alphaCanvas };\n}\n", "/** TFJS custom backend registration */\n\nimport type { Human } from '../human';\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as image from '../image/image';\nimport * as models from '../models';\nimport type { AnyCanvas } from '../exports';\n// import { env } from '../env';\n\nexport const config = {\n  name: 'humangl',\n  priority: 999,\n  canvas: <null | AnyCanvas>null,\n  gl: <null | WebGL2RenderingContext>null,\n  extensions: <string[]> [],\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nfunction extensions(): void {\n  /*\n  https://www.khronos.org/registry/webgl/extensions/\n  https://webglreport.com/?v=2\n  */\n  const gl = config.gl;\n  if (!gl) return;\n  config.extensions = gl.getSupportedExtensions() as string[];\n  // gl.getExtension('KHR_parallel_shader_compile');\n}\n\n/**\n * Registers custom WebGL2 backend to be used by Human library\n *\n * @returns void\n */\nexport async function register(instance: Human): Promise<void> {\n  // force backend reload if gl context is not valid\n  if (instance.config.backend !== 'humangl') return;\n  if ((config.name in tf.engine().registry) && (!config.gl || !config.gl.getParameter(config.gl.VERSION))) {\n    log('error: humangl backend invalid context');\n    models.reset(instance);\n    /*\n    log('resetting humangl backend');\n    await tf.removeBackend(config.name);\n    await register(instance); // re-register\n    */\n  }\n  if (!tf.findBackend(config.name)) {\n    try {\n      config.canvas = await image.canvas(100, 100);\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      config.gl = config.canvas?.getContext('webgl2', config.webGLattr) as WebGL2RenderingContext;\n      const glv2 = config.gl.getParameter(config.gl.VERSION).includes('2.0');\n      if (!glv2) {\n        log('override: using fallback webgl backend as webgl 2.0 is not detected');\n        instance.config.backend = 'webgl';\n        return;\n      }\n      if (config.canvas) {\n        config.canvas.addEventListener('webglcontextlost', async (e) => {\n          log('error: humangl:', e.type);\n          log('possible browser memory leak using webgl or conflict with multiple backend registrations');\n          instance.emit('error');\n          throw new Error('backend error: webgl context lost');\n          // log('resetting humangl backend');\n          // env.initial = true;\n          // models.reset(instance);\n          // await tf.removeBackend(config.name);\n          // await register(instance); // re-register\n        });\n        config.canvas.addEventListener('webglcontextrestored', (e) => {\n          log('error: humangl context restored:', e);\n        });\n        config.canvas.addEventListener('webglcontextcreationerror', (e) => {\n          log('error: humangl context create:', e);\n        });\n      }\n    } catch (err) {\n      log('error: cannot get WebGL context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    const current = tf.backend().getGPGPUContext ? tf.backend().getGPGPUContext().gl : null;\n    if (current) {\n      log(`humangl webgl version:${current.getParameter(current.VERSION)} renderer:${current.getParameter(current.RENDERER)}`);\n    } else {\n      log('error: no current gl context:', current, config.gl);\n      return;\n    }\n    try {\n      if (tf.env().flagRegistry['WEBGL_VERSION']) tf.env().set('WEBGL_VERSION', 2);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    extensions();\n    log('backend registered:', config.name);\n  }\n}\n", "/** TFJS backend initialization and customization */\n\nimport type { Human } from '../human';\nimport { log, now } from '../util/util';\nimport { env } from '../util/env';\nimport * as humangl from './humangl';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as constants from './constants';\n\nfunction registerCustomOps() {\n  if (!env.kernels.includes('mod')) {\n    const kernelMod = {\n      kernelName: 'Mod',\n      backendName: tf.getBackend(),\n      kernelFunc: (op) => tf.tidy(() => tf.sub(op.inputs.a, tf.mul(tf.div(op.inputs.a, op.inputs.b), op.inputs.b))),\n    };\n    tf.registerKernel(kernelMod);\n    env.kernels.push('mod');\n  }\n  if (!env.kernels.includes('floormod')) {\n    const kernelMod = {\n      kernelName: 'FloorMod',\n      backendName: tf.getBackend(),\n      kernelFunc: (op) => tf.tidy(() => tf.floorDiv(op.inputs.a / op.inputs.b) * op.inputs.b + tf.mod(op.inputs.a, op.inputs.b)),\n    };\n    tf.registerKernel(kernelMod);\n    env.kernels.push('floormod');\n  }\n}\n\nexport async function check(instance: Human, force = false) {\n  instance.state = 'backend';\n  if (force || env.initial || (instance.config.backend && (instance.config.backend.length > 0) && (tf.getBackend() !== instance.config.backend))) {\n    const timeStamp = now();\n\n    if (instance.config.backend && instance.config.backend.length > 0) {\n      // detect web worker\n      // @ts-ignore ignore missing type for WorkerGlobalScope as that is the point\n      if (typeof window === 'undefined' && typeof WorkerGlobalScope !== 'undefined' && instance.config.debug) {\n        if (instance.config.debug) log('running inside web worker');\n      }\n\n      // force browser vs node backend\n      if (env.browser && instance.config.backend === 'tensorflow') {\n        if (instance.config.debug) log('override: backend set to tensorflow while running in browser');\n        instance.config.backend = 'humangl';\n      }\n      if (env.node && (instance.config.backend === 'webgl' || instance.config.backend === 'humangl')) {\n        if (instance.config.debug) log(`override: backend set to ${instance.config.backend} while running in nodejs`);\n        instance.config.backend = 'tensorflow';\n      }\n\n      // handle webgpu\n      if (env.browser && instance.config.backend === 'webgpu') {\n        if (typeof navigator === 'undefined' || typeof navigator['gpu'] === 'undefined') {\n          log('override: backend set to webgpu but browser does not support webgpu');\n          instance.config.backend = 'humangl';\n        } else {\n          const adapter = await navigator['gpu'].requestAdapter();\n          if (instance.config.debug) log('enumerated webgpu adapter:', adapter);\n          if (!adapter) {\n            log('override: backend set to webgpu but browser reports no available gpu');\n            instance.config.backend = 'humangl';\n          } else {\n            // @ts-ignore requestAdapterInfo is not in tslib\n            // eslint-disable-next-line no-undef\n            const adapterInfo = 'requestAdapterInfo' in adapter ? await (adapter as GPUAdapter).requestAdapterInfo() : undefined;\n            // if (adapter.features) adapter.features.forEach((feature) => log('webgpu features:', feature));\n            log('webgpu adapter info:', adapterInfo);\n          }\n        }\n      }\n\n      // check available backends\n      if (instance.config.backend === 'humangl') await humangl.register(instance);\n      const available = Object.keys(tf.engine().registryFactory);\n      if (instance.config.debug) log('available backends:', available);\n\n      if (!available.includes(instance.config.backend)) {\n        log(`error: backend ${instance.config.backend} not found in registry`);\n        instance.config.backend = env.node ? 'tensorflow' : 'webgl';\n        if (instance.config.debug) log(`override: setting backend ${instance.config.backend}`);\n      }\n\n      if (instance.config.debug) log('setting backend:', instance.config.backend);\n\n      // customize wasm\n      if (instance.config.backend === 'wasm') {\n        if (tf.env().flagRegistry['CANVAS2D_WILL_READ_FREQUENTLY']) tf.env().set('CANVAS2D_WILL_READ_FREQUENTLY', true);\n        if (instance.config.debug) log('wasm path:', instance.config.wasmPath);\n        if (typeof tf?.setWasmPaths !== 'undefined') await tf.setWasmPaths(instance.config.wasmPath, instance.config.wasmPlatformFetch);\n        else throw new Error('backend error: attempting to use wasm backend but wasm path is not set');\n        const simd = await tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n        const mt = await tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n        if (instance.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n        if (instance.config.debug && !simd) log('warning: wasm simd support is not enabled');\n      }\n\n      try {\n        await tf.setBackend(instance.config.backend);\n        await tf.ready();\n        constants.init();\n      } catch (err) {\n        log('error: cannot set backend:', instance.config.backend, err);\n        return false;\n      }\n    }\n\n    // customize humangl\n    if (tf.getBackend() === 'humangl') {\n      if (tf.env().flagRegistry['CHECK_COMPUTATION_FOR_ERRORS']) tf.env().set('CHECK_COMPUTATION_FOR_ERRORS', false);\n      if (tf.env().flagRegistry['WEBGL_CPU_FORWARD']) tf.env().set('WEBGL_CPU_FORWARD', true);\n      if (tf.env().flagRegistry['WEBGL_USE_SHAPES_UNIFORMS']) tf.env().set('WEBGL_USE_SHAPES_UNIFORMS', true);\n      if (tf.env().flagRegistry['CPU_HANDOFF_SIZE_THRESHOLD']) tf.env().set('CPU_HANDOFF_SIZE_THRESHOLD', 256);\n      if (tf.env().flagRegistry['WEBGL_EXP_CONV']) tf.env().set('WEBGL_EXP_CONV', true); // <https://github.com/tensorflow/tfjs/issues/6678>\n      if (tf.env().flagRegistry['USE_SETTIMEOUTWPM']) tf.env().set('USE_SETTIMEOUTWPM', true); // <https://github.com/tensorflow/tfjs/issues/6687>\n      // if (tf.env().flagRegistry['WEBGL_PACK_DEPTHWISECONV'])  tf.env().set('WEBGL_PACK_DEPTHWISECONV', false);\n      // if (if (tf.env().flagRegistry['WEBGL_FORCE_F16_TEXTURES']) && !instance.config.object.enabled) tf.env().set('WEBGL_FORCE_F16_TEXTURES', true); // safe to use 16bit precision\n      if (typeof instance.config['deallocate'] !== 'undefined' && instance.config['deallocate']) { // hidden param\n        log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', true);\n        tf.env().set('WEBGL_DELETE_TEXTURE_THRESHOLD', 0);\n      }\n      if (tf.backend().getGPGPUContext) {\n        const gl = await tf.backend().getGPGPUContext().gl;\n        if (instance.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n    }\n\n    // customize webgpu\n    if (tf.getBackend() === 'webgpu') {\n      // if (tf.env().flagRegistry['WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD']) tf.env().set('WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD', 512);\n      // if (tf.env().flagRegistry['WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE']) tf.env().set('WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE', 0);\n      // if (tf.env().flagRegistry['WEBGPU_CPU_FORWARD']) tf.env().set('WEBGPU_CPU_FORWARD', true);\n    }\n\n    // wait for ready\n    tf.enableProdMode();\n    await tf.ready();\n\n    instance.performance.initBackend = Math.trunc(now() - timeStamp);\n    instance.config.backend = tf.getBackend();\n\n    await env.updateBackend(); // update env on backend init\n    registerCustomOps();\n    // await env.updateBackend(); // update env on backend init\n  }\n  return true;\n}\n\n// register fake missing tfjs ops\nexport function fakeOps(kernelNames: Array<string>, config) {\n  // if (config.debug) log('registerKernel:', kernelNames);\n  for (const kernelName of kernelNames) {\n    const kernelConfig = {\n      kernelName,\n      backendName: config.backend,\n      kernelFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },\n      // setupFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },\n      // disposeFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },\n    };\n    tf.registerKernel(kernelConfig);\n  }\n  env.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => kernel.kernelName.toLowerCase()); // re-scan registered ops\n}\n", "/**\n * Module that implements helper draw functions, exposed as human.draw\n */\n\nimport { mergeDeep, now } from '../util/util';\nimport { env } from '../util/env';\nimport { getCanvasContext, rect } from './primitives';\nimport { options } from './options';\nimport { face } from './face';\nimport { body } from './body';\nimport { hand } from './hand';\nimport { object } from './object';\nimport { gesture } from './gesture';\nimport type { Result, PersonResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\nlet drawTime = 0;\n\nexport { options } from './options';\nexport { face } from './face';\nexport { body } from './body';\nexport { hand } from './hand';\nexport { object } from './object';\nexport { gesture } from './gesture';\n\n/** draw combined person results instead of individual detection result objects */\nexport async function person(inCanvas: AnyCanvas, result: Array<PersonResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = localOptions.font;\n\n  for (let i = 0; i < result.length; i++) {\n    if (localOptions.drawBoxes) {\n      ctx.strokeStyle = localOptions.color;\n      ctx.fillStyle = localOptions.color;\n      rect(ctx, result[i].box[0], result[i].box[1], result[i].box[2], result[i].box[3], localOptions);\n      if (localOptions.drawLabels) {\n        const label = `person #${i}`;\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(label, result[i].box[0] + 3, 1 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(label, result[i].box[0] + 2, 0 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\n/** draw processed canvas */\nexport async function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas) {\n  if (!input || !output) return;\n  const ctx = getCanvasContext(output);\n  if (!ctx) return;\n  ctx.drawImage(input, 0, 0);\n}\n\n/** meta-function that performs draw for: canvas, face, body, hand */\nexport async function all(inCanvas: AnyCanvas, result: Result, drawOptions?: Partial<DrawOptions>) {\n  if (!result || !result.performance || !result || !inCanvas) return null;\n  const timeStamp = now();\n  const localOptions = mergeDeep(options, drawOptions);\n  const promise = Promise.all([\n    face(inCanvas, result.face, localOptions),\n    body(inCanvas, result.body, localOptions),\n    hand(inCanvas, result.hand, localOptions),\n    object(inCanvas, result.object, localOptions),\n    gesture(inCanvas, result.gesture, localOptions), // gestures do not have buffering\n    // person(inCanvas, result.persons, localOptions); // already included above\n  ]);\n  drawTime = env.perfadd ? drawTime + Math.round(now() - timeStamp) : Math.round(now() - timeStamp);\n  result.performance.draw = drawTime;\n  return promise;\n}\n", "import { log } from '../util/util';\nimport type { AnyCanvas } from '../exports';\nimport type { Point } from '../result';\nimport type { DrawOptions } from './options';\n\nexport const getCanvasContext = (input: AnyCanvas) => {\n  if (!input) log('draw error: invalid canvas');\n  else if (!input.getContext) log('draw error: canvas context not defined');\n  else {\n    const ctx = input.getContext('2d');\n    if (!ctx) log('draw error: cannot get canvas context');\n    else return ctx;\n  }\n  return null;\n};\n\nexport const rad2deg = (theta: number) => Math.round((theta * 180) / Math.PI);\n\nexport const colorDepth = (z: number | undefined, opt: DrawOptions): string => {\n  if (!opt.useDepth || typeof z === 'undefined') return opt.color;\n  const rgb = Uint8ClampedArray.from([127 + (2 * z), 127 - (2 * z), 255]);\n  const color = `rgba(${rgb[0]}, ${rgb[1]}, ${rgb[2]}, ${opt.alpha})`;\n  return color;\n};\n\nexport function point(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, x: number, y: number, z: number | undefined, localOptions: DrawOptions) {\n  ctx.fillStyle = colorDepth(z, localOptions);\n  ctx.beginPath();\n  ctx.arc(x, y, localOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nexport function rect(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, x: number, y: number, width: number, height: number, localOptions: DrawOptions) {\n  ctx.beginPath();\n  ctx.lineWidth = localOptions.lineWidth;\n  if (localOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.moveTo(x + localOptions.roundRect, y);\n    ctx.lineTo(x + width - localOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + localOptions.roundRect);\n    ctx.lineTo(x + width, y + height - localOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - localOptions.roundRect, y + height);\n    ctx.lineTo(x + localOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - localOptions.roundRect);\n    ctx.lineTo(x, y + localOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + localOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nexport function lines(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, points: Point[], localOptions: DrawOptions) {\n  if (points.length < 2) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = colorDepth(pt[2] || 0, localOptions);\n    ctx.lineTo(Math.trunc(pt[0]), Math.trunc(pt[1]));\n  }\n  ctx.stroke();\n  if (localOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport function curves(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, points: Point[], localOptions: DrawOptions) {\n  if (points.length < 2) return;\n  ctx.lineWidth = localOptions.lineWidth;\n  if (!localOptions.useCurves || points.length <= 2) {\n    lines(ctx, points, localOptions);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (localOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport function arrow(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, from: Point, to: Point, radius = 5) {\n  let angle;\n  let x;\n  let y;\n  ctx.beginPath();\n  ctx.moveTo(from[0], from[1]);\n  ctx.lineTo(to[0], to[1]);\n  angle = Math.atan2(to[1] - from[1], to[0] - from[0]);\n  x = radius * Math.cos(angle) + to[0];\n  y = radius * Math.sin(angle) + to[1];\n  ctx.moveTo(x, y);\n  angle += (1.0 / 3.0) * (2 * Math.PI);\n  x = radius * Math.cos(angle) + to[0];\n  y = radius * Math.sin(angle) + to[1];\n  ctx.lineTo(x, y);\n  angle += (1.0 / 3.0) * (2 * Math.PI);\n  x = radius * Math.cos(angle) + to[0];\n  y = radius * Math.sin(angle) + to[1];\n  ctx.lineTo(x, y);\n  ctx.closePath();\n  ctx.stroke();\n  ctx.fill();\n}\n", "/** Draw Options\n * - Accessed via `human.draw.options` or provided per each draw method as the drawOptions optional parameter\n */\nexport type DrawOptions = {\n  /** draw line color */\n  color: string,\n  /** alpha value used for lines */\n  alpha: number,\n  /** label color */\n  labelColor: string,\n  /** label shadow color */\n  shadowColor: string,\n  /** label font */\n  font: string,\n  /** line spacing between labels */\n  lineHeight: number,\n  /** line width for drawn lines */\n  lineWidth: number,\n  /** size of drawn points */\n  pointSize: number,\n  /** draw rounded boxes by n pixels */\n  roundRect: number,\n  /** should points be drawn? */\n  drawPoints: boolean,\n  /** should labels be drawn? */\n  drawLabels: boolean,\n  /** should face attention keypoints be highlighted */\n  drawAttention: boolean;\n  /** should detected gestures be drawn? */\n  drawGestures: boolean,\n  /** should draw boxes around detection results? */\n  drawBoxes: boolean,\n  /** should draw polygons from detection points? */\n  drawPolygons: boolean,\n  /** should draw gaze arrows? */\n  drawGaze: boolean,\n  /** should fill polygons? */\n  fillPolygons: boolean,\n  /** use z-coordinate when available */\n  useDepth: boolean,\n  /** should lines be curved? */\n  useCurves: boolean,\n}\n\n/** currently set draw options {@link DrawOptions} */\nexport const options: DrawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.6)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  alpha: 0.5,\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>18,\n  lineWidth: <number>4,\n  pointSize: <number>2,\n  roundRect: <number>8,\n  drawPoints: <boolean>false,\n  drawLabels: <boolean>true,\n  drawBoxes: <boolean>true,\n  drawAttention: <boolean>true,\n  drawGestures: <boolean>true,\n  drawPolygons: <boolean>true,\n  drawGaze: <boolean>true,\n  fillPolygons: <boolean>false,\n  useDepth: <boolean>true,\n  useCurves: <boolean>false,\n};\n", "import { TRI468 as triangulation } from '../face/facemeshcoords';\nimport { mergeDeep } from '../util/util';\nimport { getCanvasContext, rad2deg, rect, point, lines, arrow } from './primitives';\nimport { options } from './options';\nimport * as facemeshConstants from '../face/constants';\nimport type { FaceResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\nlet opt: DrawOptions;\n\nfunction drawLabels(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawLabels) {\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face: ${Math.trunc(100 * f.score)}%`);\n    if (f.genderScore) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderScore)}%`);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`distance: ${f.iris}`);\n    if (f.real) labels.push(`real: ${Math.trunc(100 * f.real)}%`);\n    if (f.live) labels.push(`live: ${Math.trunc(100 * f.live)}%`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      if (emotion.length > 3) emotion.length = 3;\n      labels.push(emotion.join(' '));\n    }\n    if (f.rotation && f.rotation.angle && f.rotation.gaze) {\n      if (f.rotation.angle.roll) labels.push(`roll: ${rad2deg(f.rotation.angle.roll)}\u00B0 yaw:${rad2deg(f.rotation.angle.yaw)}\u00B0 pitch:${rad2deg(f.rotation.angle.pitch)}\u00B0`);\n      if (f.rotation.gaze.bearing) labels.push(`gaze: ${rad2deg(f.rotation.gaze.bearing)}\u00B0`);\n    }\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = opt.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * opt.lineHeight + f.box[1];\n      if (opt.shadowColor && opt.shadowColor !== '') {\n        ctx.fillStyle = opt.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = opt.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n  }\n}\n\nfunction drawIrisElipse(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  // iris: array[center, left, top, right, bottom]\n  if (f.annotations && f.annotations['leftEyeIris'] && f.annotations['leftEyeIris'][0]) {\n    ctx.strokeStyle = opt.useDepth ? 'rgba(255, 200, 255, 0.3)' : opt.color;\n    ctx.beginPath();\n    const sizeX = Math.abs(f.annotations['leftEyeIris'][3][0] - f.annotations['leftEyeIris'][1][0]) / 2;\n    const sizeY = Math.abs(f.annotations['leftEyeIris'][4][1] - f.annotations['leftEyeIris'][2][1]) / 2;\n    ctx.ellipse(f.annotations['leftEyeIris'][0][0], f.annotations['leftEyeIris'][0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n    ctx.stroke();\n    if (opt.fillPolygons) {\n      ctx.fillStyle = opt.useDepth ? 'rgba(255, 255, 200, 0.3)' : opt.color;\n      ctx.fill();\n    }\n  }\n  if (f.annotations && f.annotations['rightEyeIris'] && f.annotations['rightEyeIris'][0]) {\n    ctx.strokeStyle = opt.useDepth ? 'rgba(255, 200, 255, 0.3)' : opt.color;\n    ctx.beginPath();\n    const sizeX = Math.abs(f.annotations['rightEyeIris'][3][0] - f.annotations['rightEyeIris'][1][0]) / 2;\n    const sizeY = Math.abs(f.annotations['rightEyeIris'][4][1] - f.annotations['rightEyeIris'][2][1]) / 2;\n    ctx.ellipse(f.annotations['rightEyeIris'][0][0], f.annotations['rightEyeIris'][0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n    ctx.stroke();\n    if (opt.fillPolygons) {\n      ctx.fillStyle = opt.useDepth ? 'rgba(255, 255, 200, 0.3)' : opt.color;\n      ctx.fill();\n    }\n  }\n}\n\nfunction drawGazeSpheres(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawGaze && f.rotation?.angle && typeof Path2D !== 'undefined') {\n    ctx.strokeStyle = 'pink';\n    const valX = (f.box[0] + f.box[2] / 2) - (f.box[3] * rad2deg(f.rotation.angle.yaw) / 90);\n    const valY = (f.box[1] + f.box[3] / 2) + (f.box[2] * rad2deg(f.rotation.angle.pitch) / 90);\n    const pathV = new Path2D(`\n      M ${f.box[0] + f.box[2] / 2} ${f.box[1]}\n      C\n        ${valX} ${f.box[1]},\n        ${valX} ${f.box[1] + f.box[3]},\n        ${f.box[0] + f.box[2] / 2} ${f.box[1] + f.box[3]}\n    `);\n    const pathH = new Path2D(`\n      M ${f.box[0]} ${f.box[1] + f.box[3] / 2}\n      C \n        ${f.box[0]} ${valY},\n        ${f.box[0] + f.box[2]} ${valY},\n        ${f.box[0] + f.box[2]} ${f.box[1] + f.box[3] / 2}\n    `);\n    ctx.stroke(pathH);\n    ctx.stroke(pathV);\n  }\n}\n\nfunction drawGazeArrows(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawGaze && f.rotation?.gaze?.strength && f.rotation?.gaze?.bearing && f.annotations['leftEyeIris'] && f.annotations['rightEyeIris'] && f.annotations['leftEyeIris'][0] && f.annotations['rightEyeIris'][0]) {\n    ctx.strokeStyle = 'pink';\n    ctx.fillStyle = 'pink';\n    const leftGaze = [\n      f.annotations['leftEyeIris'][0][0] + (Math.sin(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[3]),\n      f.annotations['leftEyeIris'][0][1] + (Math.cos(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[2]),\n    ];\n    arrow(ctx, [f.annotations['leftEyeIris'][0][0], f.annotations['leftEyeIris'][0][1]], [leftGaze[0], leftGaze[1]], 4);\n    const rightGaze = [\n      f.annotations['rightEyeIris'][0][0] + (Math.sin(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[3]),\n      f.annotations['rightEyeIris'][0][1] + (Math.cos(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[2]),\n    ];\n    arrow(ctx, [f.annotations['rightEyeIris'][0][0], f.annotations['rightEyeIris'][0][1]], [rightGaze[0], rightGaze[1]], 4);\n  }\n}\n\nfunction drawFacePolygons(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawPolygons && f.mesh.length >= 468) {\n    ctx.lineWidth = 1;\n    for (let i = 0; i < triangulation.length / 3; i++) {\n      const points = [triangulation[i * 3 + 0], triangulation[i * 3 + 1], triangulation[i * 3 + 2]].map((index) => f.mesh[index]);\n      lines(ctx, points, opt);\n    }\n    drawIrisElipse(f, ctx);\n  }\n  /*\n  if (opt.drawPolygons && f.contours.length > 1) {\n    ctx.lineWidth = 5;\n    lines(ctx, f.contours, opt);\n  }\n  ctx.lineWidth = 1;\n  */\n}\n\nfunction drawFacePoints(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawPoints && f.mesh.length >= 468) {\n    for (let i = 0; i < f.mesh.length; i++) {\n      point(ctx, f.mesh[i][0], f.mesh[i][1], f.mesh[i][2], opt);\n      if (opt.drawAttention) {\n        if (facemeshConstants.LANDMARKS_REFINEMENT_LIPS_CONFIG.includes(i)) point(ctx, f.mesh[i][0], f.mesh[i][1], (f.mesh[i][2] as number) + 127, opt);\n        if (facemeshConstants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG.includes(i)) point(ctx, f.mesh[i][0], f.mesh[i][1], (f.mesh[i][2] as number) - 127, opt);\n        if (facemeshConstants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG.includes(i)) point(ctx, f.mesh[i][0], f.mesh[i][1], (f.mesh[i][2] as number) - 127, opt);\n      }\n    }\n  }\n}\n\nfunction drawFaceBoxes(f: FaceResult, ctx) {\n  if (opt.drawBoxes) {\n    rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3], opt);\n  }\n}\n\n/** draw detected faces */\nexport async function face(inCanvas: AnyCanvas, result: Array<FaceResult>, drawOptions?: Partial<DrawOptions>) {\n  opt = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.font = opt.font;\n  ctx.strokeStyle = opt.color;\n  ctx.fillStyle = opt.color;\n  for (const f of result) {\n    drawFaceBoxes(f, ctx);\n    drawLabels(f, ctx);\n    if (f.mesh && f.mesh.length > 0) {\n      drawFacePoints(f, ctx);\n      drawFacePolygons(f, ctx);\n      drawGazeSpheres(f, ctx);\n      drawGazeArrows(f, ctx);\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext, rect, point, curves, colorDepth } from './primitives';\nimport { options } from './options';\nimport type { BodyResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\n/** draw detected bodies */\nexport async function body(inCanvas: AnyCanvas, result: Array<BodyResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    ctx.strokeStyle = localOptions.color;\n    ctx.fillStyle = localOptions.color;\n    ctx.lineWidth = localOptions.lineWidth;\n    ctx.font = localOptions.font;\n    if (localOptions.drawBoxes && result[i].box && result[i].box?.length === 4) {\n      rect(ctx, result[i].box[0], result[i].box[1], result[i].box[2], result[i].box[3], localOptions);\n      if (localOptions.drawLabels) {\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(`body ${100 * result[i].score}%`, result[i].box[0] + 3, 1 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(`body ${100 * result[i].score}%`, result[i].box[0] + 2, 0 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n      }\n    }\n    if (localOptions.drawPoints && result[i].keypoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        if (!result[i].keypoints[pt].score || (result[i].keypoints[pt].score === 0)) continue;\n        ctx.fillStyle = colorDepth(result[i].keypoints[pt].position[2], localOptions);\n        point(ctx, result[i].keypoints[pt].position[0], result[i].keypoints[pt].position[1], 0, localOptions);\n      }\n    }\n    if (localOptions.drawLabels && result[i].keypoints) {\n      ctx.font = localOptions.font;\n      for (const pt of result[i].keypoints) {\n        if (!pt.score || (pt.score === 0)) continue;\n        ctx.fillStyle = colorDepth(pt.position[2], localOptions);\n        ctx.fillText(`${pt.part} ${Math.trunc(100 * pt.score)}%`, pt.position[0] + 4, pt.position[1] + 4);\n      }\n    }\n    if (localOptions.drawPolygons && result[i].keypoints && result[i].annotations) {\n      for (const part of Object.values(result[i].annotations)) {\n        for (const connected of part) curves(ctx, connected, localOptions);\n      }\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext, rect, point, colorDepth } from './primitives';\nimport { options } from './options';\nimport type { HandResult } from '../result';\nimport type { AnyCanvas, DrawOptions, Point } from '../exports';\n\n/** draw detected hands */\nexport async function hand(inCanvas: AnyCanvas, result: Array<HandResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = localOptions.font;\n  for (const h of result) {\n    if (localOptions.drawBoxes) {\n      ctx.strokeStyle = localOptions.color;\n      ctx.fillStyle = localOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3], localOptions);\n      if (localOptions.drawLabels) {\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(`hand:${Math.trunc(100 * h.score)}%`, h.box[0] + 3, 1 + h.box[1] + localOptions.lineHeight, h.box[2]); // can use h.label\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(`hand:${Math.trunc(100 * h.score)}%`, h.box[0] + 2, 0 + h.box[1] + localOptions.lineHeight, h.box[2]); // can use h.label\n      }\n      ctx.stroke();\n    }\n    if (localOptions.drawPoints) {\n      if (h.keypoints && h.keypoints.length > 0) {\n        for (const pt of h.keypoints) {\n          ctx.fillStyle = colorDepth(pt[2], localOptions);\n          point(ctx, pt[0], pt[1], 0, localOptions);\n        }\n      }\n    }\n    if (localOptions.drawLabels && h.annotations) {\n      const addHandLabel = (part: Array<Point>, title: string) => {\n        if (!part || part.length === 0 || !part[0]) return;\n        const z = part[part.length - 1][2] || -256;\n        ctx.fillStyle = colorDepth(z, localOptions);\n        ctx.fillText(title, part[part.length - 1][0] + 4, part[part.length - 1][1] + 4);\n      };\n      ctx.font = localOptions.font;\n      addHandLabel(h.annotations['index'], 'index');\n      addHandLabel(h.annotations['middle'], 'middle');\n      addHandLabel(h.annotations['ring'], 'ring');\n      addHandLabel(h.annotations['pinky'], 'pinky');\n      addHandLabel(h.annotations['thumb'], 'thumb');\n      addHandLabel(h.annotations['palm'], 'palm');\n    }\n    if (localOptions.drawPolygons && h.annotations) {\n      const addHandLine = (part: Array<Point>) => {\n        if (!part || part.length === 0 || !part[0]) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.beginPath();\n          const z = part[i][2] || 0;\n          ctx.strokeStyle = colorDepth(i * z, localOptions);\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      ctx.lineWidth = localOptions.lineWidth;\n      addHandLine(h.annotations['index']);\n      addHandLine(h.annotations['middle']);\n      addHandLine(h.annotations['ring']);\n      addHandLine(h.annotations['pinky']);\n      addHandLine(h.annotations['thumb']);\n      // addPart(h.annotations.palm);\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext, rect } from './primitives';\nimport { options } from './options';\nimport type { ObjectResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\n/** draw detected objects */\nexport async function object(inCanvas: AnyCanvas, result: Array<ObjectResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = localOptions.font;\n  for (const h of result) {\n    if (localOptions.drawBoxes) {\n      ctx.strokeStyle = localOptions.color;\n      ctx.fillStyle = localOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3], localOptions);\n      if (localOptions.drawLabels) {\n        const label = `${h.label} ${Math.round(100 * h.score)}%`;\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + localOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + localOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext } from './primitives';\nimport { options } from './options';\nimport type { GestureResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\n/** draw detected gestures */\nexport async function gesture(inCanvas: AnyCanvas, result: Array<GestureResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  if (localOptions.drawGestures) {\n    const ctx = getCanvasContext(inCanvas);\n    if (!ctx) return;\n    ctx.font = localOptions.font;\n    ctx.fillStyle = localOptions.color;\n    let i = 1;\n    for (let j = 0; j < result.length; j++) {\n      let where: unknown[] = []; // what&where is a record\n      let what: unknown[] = []; // what&where is a record\n      [where, what] = Object.entries(result[j]);\n      if ((what.length > 1) && ((what[1] as string).length > 0)) {\n        const who = where[1] as number > 0 ? `#${where[1]}` : '';\n        const label = `${where[0]} ${who}: ${what[1]}`;\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(label, 8, 2 + (i * localOptions.lineHeight));\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(label, 6, 0 + (i * localOptions.lineHeight));\n        i += 1;\n      }\n    }\n  }\n}\n", "import type { Tensor } from '../tfjs/types';\nimport type { FaceResult } from '../result';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { meshAnnotations } from './facemeshcoords';\n\nconst expandFact = 0.1;\nconst alpha = 0.5;\n\n// point inclusion in polygon based on https://wrf.ecse.rpi.edu/Research/Short_Notes/pnpoly.html\nfunction insidePoly(x: number, y: number, polygon: Array<{ x: number, y: number }>): boolean {\n  let inside = false;\n  let j = polygon.length - 1;\n  for (let i = 0; i < polygon.length; j = i++) {\n    if (((polygon[i].y > y) !== (polygon[j].y > y)) && (x < (polygon[j].x - polygon[i].x) * (y - polygon[i].y) / (polygon[j].y - polygon[i].y) + polygon[i].x)) inside = !inside;\n  }\n  return inside;\n}\n\nexport async function mask(face: FaceResult): Promise<Tensor | undefined> {\n  if (!face.tensor) return face.tensor;\n  if (!face.mesh || face.mesh.length < 100) return face.tensor;\n  const width = face.tensor.shape[2] || 0;\n  const height = face.tensor.shape[1] || 0;\n  const buffer = await face.tensor.buffer();\n  let silhouette: Array<{ x: number, y: number }> = [];\n  for (const pt of meshAnnotations.silhouette) silhouette.push({ x: (face.mesh[pt][0] - face.box[0]) / face.box[2], y: (face.mesh[pt][1] - face.box[1]) / face.box[3] }); // add all silhouette points scaled to local box\n  if (expandFact && expandFact > 0) silhouette = silhouette.map((pt) => ({ x: pt.x > 0.5 ? pt.x + expandFact : pt.x - expandFact, y: pt.y > 0.5 ? pt.y + expandFact : pt.y - expandFact })); // expand silhouette\n  for (let x = 0; x < width; x++) {\n    for (let y = 0; y < height; y++) {\n      const inside = insidePoly(x / width, y / width, silhouette);\n      if (!inside) {\n        buffer.set(alpha * buffer.get(0, y, x, 0), 0, y, x, 0);\n        buffer.set(alpha * buffer.get(0, y, x, 1), 0, y, x, 1);\n        buffer.set(alpha * buffer.get(0, y, x, 2), 0, y, x, 2);\n      }\n    }\n  }\n  const output = buffer.toTensor();\n  tf.dispose(buffer);\n  return output;\n}\n", "import type { Point, FaceResult } from '../result';\n\ntype Vector = [number, number, number];\n\nconst calculateGaze = (face: FaceResult): { bearing: number, strength: number } => {\n  const radians = (pt1: Point, pt2: Point) => Math.atan2(pt1[1] - pt2[1], pt1[0] - pt2[0]); // function to calculate angle between any two points\n  if (!face.annotations['rightEyeIris'] || !face.annotations['leftEyeIris']) return { bearing: 0, strength: 0 };\n\n  const offsetIris = [0, -0.1]; // iris center may not align with average of eye extremes\n  const eyeRatio = 1; // factor to normalize changes x vs y\n\n  const left = (face.mesh[33][2] || 0) > (face.mesh[263][2] || 0); // pick left or right eye depending which one is closer bazed on outsize point z axis\n  const irisCenter = left ? face.mesh[473] : face.mesh[468];\n  const eyeCenter = left // eye center is average of extreme points on x axis for both x and y, ignoring y extreme points as eyelids naturally open/close more when gazing up/down so relative point is less precise\n    ? [(face.mesh[133][0] + face.mesh[33][0]) / 2, (face.mesh[133][1] + face.mesh[33][1]) / 2]\n    : [(face.mesh[263][0] + face.mesh[362][0]) / 2, (face.mesh[263][1] + face.mesh[362][1]) / 2];\n  const eyeSize = left // eye size is difference between extreme points for both x and y, used to normalize & squarify eye dimensions\n    ? [face.mesh[133][0] - face.mesh[33][0], face.mesh[23][1] - face.mesh[27][1]]\n    : [face.mesh[263][0] - face.mesh[362][0], face.mesh[253][1] - face.mesh[257][1]];\n  const eyeDiff: Point = [ // x distance between extreme point and center point normalized with eye size\n    (eyeCenter[0] - irisCenter[0]) / eyeSize[0] - offsetIris[0],\n    eyeRatio * (irisCenter[1] - eyeCenter[1]) / eyeSize[1] - offsetIris[1],\n  ];\n  let strength = Math.sqrt((eyeDiff[0] * eyeDiff[0]) + (eyeDiff[1] * eyeDiff[1])); // vector length is a diagonal between two differences\n  strength = Math.min(strength, face.boxRaw[2] / 2, face.boxRaw[3] / 2); // limit strength to half of box size to avoid clipping due to low precision\n  const bearing = (radians([0, 0], eyeDiff) + (Math.PI / 2)) % Math.PI; // using eyeDiff instead eyeCenter/irisCenter combo due to manual adjustments and rotate clockwise 90degrees\n  return { bearing, strength };\n};\n\nexport const calculateFaceAngle = (face: FaceResult, imageSize: [number, number]): {\n  angle: { pitch: number, yaw: number, roll: number },\n  matrix: [number, number, number, number, number, number, number, number, number],\n  gaze: { bearing: number, strength: number },\n} => {\n  // const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n  const normalize = (v: Vector): Vector => { // normalize vector\n    const length = Math.sqrt(v[0] * v[0] + v[1] * v[1] + v[2] * v[2]);\n    v[0] /= length;\n    v[1] /= length;\n    v[2] /= length;\n    return v;\n  };\n  const subVectors = (a: Vector, b: Vector): Vector => { // vector subtraction (a - b)\n    const x = a[0] - b[0];\n    const y = a[1] - b[1];\n    const z = a[2] - b[2];\n    return [x, y, z];\n  };\n  const crossVectors = (a: Vector, b: Vector): Vector => { // vector cross product (a x b)\n    const x = a[1] * b[2] - a[2] * b[1];\n    const y = a[2] * b[0] - a[0] * b[2];\n    const z = a[0] * b[1] - a[1] * b[0];\n    return [x, y, z];\n  };\n  // 3x3 rotation matrix to Euler angles based on https://www.geometrictools.com/Documentation/EulerAngles.pdf\n  const rotationMatrixToEulerAngle = (r: number[]): { pitch: number, yaw: number, roll: number } => {\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const [r00, _r01, _r02, r10, r11, r12, r20, r21, r22] = r;\n    let thetaX: number;\n    let thetaY: number;\n    let thetaZ: number;\n    if (r10 < 1) { // YZX calculation\n      if (r10 > -1) {\n        thetaZ = Math.asin(r10);\n        thetaY = Math.atan2(-r20, r00);\n        thetaX = Math.atan2(-r12, r11);\n      } else {\n        thetaZ = -Math.PI / 2;\n        thetaY = -Math.atan2(r21, r22);\n        thetaX = 0;\n      }\n    } else {\n      thetaZ = Math.PI / 2;\n      thetaY = Math.atan2(r21, r22);\n      thetaX = 0;\n    }\n    if (isNaN(thetaX)) thetaX = 0;\n    if (isNaN(thetaY)) thetaY = 0;\n    if (isNaN(thetaZ)) thetaZ = 0;\n    return { pitch: 2 * -thetaX, yaw: 2 * -thetaY, roll: 2 * -thetaZ };\n  };\n\n  /*\n  const meshToEulerAngle = (mesh) => { // simple Euler angle calculation based existing 3D mesh\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    return { // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees, value of 0 means center\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face // pitch is face move up/down\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye // yaw is face turn left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye // roll is face lean left/right\n    };\n  };\n  */\n\n  // initialize gaze and mesh\n  const mesh = face.meshRaw;\n  if (!mesh || mesh.length < 300) return { angle: { pitch: 0, yaw: 0, roll: 0 }, matrix: [1, 0, 0, 0, 1, 0, 0, 0, 1], gaze: { bearing: 0, strength: 0 } };\n\n  const size = Math.max(face.boxRaw[2] * imageSize[0], face.boxRaw[3] * imageSize[1]) / 1.5;\n  // top, bottom, left, right\n  const pts: Point[] = [mesh[10], mesh[152], mesh[234], mesh[454]].map((pt) => [pt[0] * imageSize[0] / size, pt[1] * imageSize[1] / size, pt[2]] as Point); // make the xyz coordinates proportional, independent of the image/box size\n\n  const y_axis = normalize(subVectors(pts[1] as Vector, pts[0] as Vector));\n  let x_axis = normalize(subVectors(pts[3] as Vector, pts[2] as Vector));\n  const z_axis = normalize(crossVectors(x_axis, y_axis));\n  // adjust x_axis to make sure that all axes are perpendicular to each other\n  x_axis = crossVectors(y_axis, z_axis);\n\n  // Rotation Matrix from Axis Vectors - http://renderdan.blogspot.com/2006/05/rotation-matrix-from-axis-vectors.html\n  // 3x3 rotation matrix is flatten to array in row-major order. Note that the rotation represented by this matrix is inverted.\n  const matrix: [number, number, number, number, number, number, number, number, number] = [\n    x_axis[0], x_axis[1], x_axis[2],\n    y_axis[0], y_axis[1], y_axis[2],\n    z_axis[0], z_axis[1], z_axis[2],\n  ];\n  const angle = rotationMatrixToEulerAngle(matrix);\n  // const angle = meshToEulerAngle(mesh);\n\n  // we have iris keypoints so we can calculate gaze direction\n  const gaze = mesh.length === 478 ? calculateGaze(face) : { bearing: 0, strength: 0 };\n\n  return { angle, matrix, gaze };\n};\n", "/**\n * Face algorithm implementation\n * Uses FaceMesh, Emotion and FaceRes models to create a unified pipeline\n */\n\nimport { log, now } from '../util/util';\nimport { env } from '../util/env';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as facemesh from './facemesh';\nimport * as emotion from '../gear/emotion';\nimport * as faceres from './faceres';\nimport * as mask from './mask';\nimport * as antispoof from './antispoof';\nimport * as liveness from './liveness';\nimport * as gear from '../gear/gear';\nimport * as ssrnetAge from '../gear/ssrnet-age';\nimport * as ssrnetGender from '../gear/ssrnet-gender';\nimport * as mobilefacenet from './mobilefacenet';\nimport type { FaceResult, Emotion, Gender, Race } from '../result';\nimport type { Tensor } from '../tfjs/types';\nimport type { Human } from '../human';\nimport { calculateFaceAngle } from './angles';\n\ntype DescRes = { age: number, gender: Gender, genderScore: number, descriptor: number[], race?: { score: number, race: Race }[] };\n\nexport const detectFace = async (instance: Human /* instance of human */, input: Tensor): Promise<FaceResult[]> => {\n  // run facemesh, includes blazeface and iris\n  // eslint-disable-next-line no-async-promise-executor\n  let timeStamp: number = now();\n  let ageRes: { age: number } | Promise<{ age: number }> | null;\n  let gearRes: gear.GearType | Promise<gear.GearType> | null;\n  let genderRes: { gender: string, genderScore: number } | Promise<{ gender: string, genderScore: number }> | null;\n  let emotionRes: { score: number, emotion: Emotion }[] | Promise<{ score: number, emotion: Emotion }[]>;\n  let mobilefacenetRes: number[] | Promise<number[]> | null;\n  let antispoofRes: number | Promise<number> | null;\n  let livenessRes: number | Promise<number> | null;\n  let descRes: DescRes | Promise<DescRes> | null;\n\n  const faceRes: Array<FaceResult> = [];\n  instance.state = 'run:face';\n\n  const faces = await facemesh.predict(input, instance.config);\n  instance.performance.face = env.perfadd ? (instance.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n  if (!input.shape || input.shape.length !== 4) return [];\n  if (!faces) return [];\n  // for (const face of faces) {\n  for (let i = 0; i < faces.length; i++) {\n    instance.analyze('Get Face');\n\n    // is something went wrong, skip the face\n    // @ts-ignore possibly undefied\n    if (!faces[i].tensor || faces[i].tensor['isDisposedInternal']) {\n      log('Face object is disposed:', faces[i].tensor);\n      continue;\n    }\n\n    // optional face mask\n    if (instance.config.face.detector?.mask) {\n      const masked = await mask.mask(faces[i]);\n      tf.dispose(faces[i].tensor);\n      faces[i].tensor = masked as Tensor;\n    }\n\n    // calculate face angles\n    const rotation = faces[i].mesh && (faces[i].mesh.length > 200) ? calculateFaceAngle(faces[i], [input.shape[2], input.shape[1]]) : null;\n\n    // run emotion, inherits face from blazeface\n    instance.analyze('Start Emotion:');\n    if (instance.config.async) {\n      emotionRes = instance.config.face.emotion?.enabled ? emotion.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : [];\n    } else {\n      instance.state = 'run:emotion';\n      timeStamp = now();\n      emotionRes = instance.config.face.emotion?.enabled ? await emotion.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : [];\n      instance.performance.emotion = env.perfadd ? (instance.performance.emotion || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End Emotion:');\n\n    // run antispoof, inherits face from blazeface\n    instance.analyze('Start AntiSpoof:');\n    if (instance.config.async) {\n      antispoofRes = instance.config.face.antispoof?.enabled ? antispoof.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n    } else {\n      instance.state = 'run:antispoof';\n      timeStamp = now();\n      antispoofRes = instance.config.face.antispoof?.enabled ? await antispoof.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n      instance.performance.antispoof = env.perfadd ? (instance.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End AntiSpoof:');\n\n    // run liveness, inherits face from blazeface\n    instance.analyze('Start Liveness:');\n    if (instance.config.async) {\n      livenessRes = instance.config.face.liveness?.enabled ? liveness.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n    } else {\n      instance.state = 'run:liveness';\n      timeStamp = now();\n      livenessRes = instance.config.face.liveness?.enabled ? await liveness.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n      instance.performance.liveness = env.perfadd ? (instance.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End Liveness:');\n\n    // run gear, inherits face from blazeface\n    instance.analyze('Start GEAR:');\n    if (instance.config.async) {\n      gearRes = instance.config.face['gear']?.enabled ? gear.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:gear';\n      timeStamp = now();\n      gearRes = instance.config.face['gear']?.enabled ? await gear.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.gear = Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End GEAR:');\n\n    // run gear, inherits face from blazeface\n    instance.analyze('Start SSRNet:');\n    if (instance.config.async) {\n      ageRes = instance.config.face['ssrnet']?.enabled ? ssrnetAge.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      genderRes = instance.config.face['ssrnet']?.enabled ? ssrnetGender.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:ssrnet';\n      timeStamp = now();\n      ageRes = instance.config.face['ssrnet']?.enabled ? await ssrnetAge.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      genderRes = instance.config.face['ssrnet']?.enabled ? await ssrnetGender.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.ssrnet = Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End SSRNet:');\n\n    // run gear, inherits face from blazeface\n    instance.analyze('Start MobileFaceNet:');\n    if (instance.config.async) {\n      mobilefacenetRes = instance.config.face['mobilefacenet']?.enabled ? mobilefacenet.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:mobilefacenet';\n      timeStamp = now();\n      mobilefacenetRes = instance.config.face['mobilefacenet']?.enabled ? await mobilefacenet.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.mobilefacenet = Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End MobileFaceNet:');\n\n    // run emotion, inherits face from blazeface\n    instance.analyze('Start Description:');\n    if (instance.config.async) {\n      descRes = instance.config.face.description?.enabled ? faceres.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:description';\n      timeStamp = now();\n      descRes = instance.config.face.description?.enabled ? await faceres.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.description = env.perfadd ? (instance.performance.description || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End Description:');\n\n    // if async wait for results\n    if (instance.config.async) {\n      [ageRes, genderRes, emotionRes, mobilefacenetRes, descRes, gearRes, antispoofRes, livenessRes] = await Promise.all([ageRes, genderRes, emotionRes, mobilefacenetRes, descRes, gearRes, antispoofRes, livenessRes]);\n    }\n    instance.analyze('Finish Face:');\n\n    if (instance.config.face['ssrnet']?.enabled && ageRes && genderRes) { // override age/gender if ssrnet model is used\n      descRes = {\n        ...(descRes as DescRes),\n        age: (ageRes as { age: number}).age,\n        gender: (genderRes as { gender: Gender, genderScore: number }).gender,\n        genderScore: (genderRes as { gender: Gender, genderScore: number }).genderScore,\n      };\n    }\n    if (instance.config.face['gear']?.enabled && gearRes) { // override age/gender/race if gear model is used\n      descRes = {\n        ...(descRes as DescRes),\n        age: (gearRes as gear.GearType).age,\n        gender: (gearRes as gear.GearType).gender,\n        genderScore: (gearRes as gear.GearType).genderScore,\n        race: (gearRes as gear.GearType).race,\n      };\n    }\n    if (instance.config.face['mobilefacenet']?.enabled && mobilefacenetRes) { // override descriptor if embedding model is used\n      (descRes as DescRes).descriptor = mobilefacenetRes as number[];\n    }\n\n    // calculate iris distance\n    // iris: array[ center, left, top, right, bottom]\n    if (!instance.config.face.iris?.enabled) {\n      // if (faces[i]?.annotations?.leftEyeIris) delete faces[i].annotations.leftEyeIris;\n      // if (faces[i]?.annotations?.rightEyeIris) delete faces[i].annotations.rightEyeIris;\n    }\n    const irisSize = (faces[i].annotations && faces[i].annotations.leftEyeIris && faces[i].annotations.leftEyeIris[0] && faces[i].annotations.rightEyeIris && faces[i].annotations.rightEyeIris[0]\n      && (faces[i].annotations.leftEyeIris.length > 0) && (faces[i].annotations.rightEyeIris.length > 0)\n      && (faces[i].annotations.leftEyeIris[0] !== null) && (faces[i].annotations.rightEyeIris[0] !== null))\n      ? Math.max(Math.abs(faces[i].annotations.leftEyeIris[3][0] - faces[i].annotations.leftEyeIris[1][0]), Math.abs(faces[i].annotations.rightEyeIris[4][1] - faces[i].annotations.rightEyeIris[2][1])) / input.shape[2]\n      : 0; // note: average human iris size is 11.7mm\n\n    // optionally return tensor\n    const tensor = instance.config.face.detector?.return ? tf.squeeze(faces[i].tensor) : null;\n    // dispose original face tensor\n    tf.dispose(faces[i].tensor);\n    // delete temp face image\n    if (faces[i].tensor) delete faces[i].tensor;\n    // combine results\n    const res: FaceResult = {\n      ...faces[i],\n      id: i,\n    };\n    if ((descRes as DescRes)?.age) res.age = (descRes as DescRes).age as number;\n    if ((descRes as DescRes)?.gender) res.gender = (descRes as DescRes).gender as Gender;\n    if ((descRes as DescRes)?.genderScore) res.genderScore = (descRes as DescRes)?.genderScore as number;\n    if ((descRes as DescRes)?.descriptor) res.embedding = (descRes as DescRes)?.descriptor as Array<number>;\n    if ((descRes as DescRes)?.race) res.race = (descRes as DescRes)?.race as { score: number, race: Race }[];\n    if (emotionRes) res.emotion = emotionRes as Array<{ score: number, emotion: Emotion }>;\n    if (antispoofRes) res.real = antispoofRes as number;\n    if (livenessRes) res.live = livenessRes as number;\n    if (irisSize && irisSize !== 0) res.iris = Math.trunc(500 / irisSize / 11.7) / 100;\n    if (rotation) res.rotation = rotation;\n    if (tensor) res.tensor = tensor;\n    faceRes.push(res);\n    instance.analyze('End Face');\n  }\n  instance.analyze('End FaceMesh:');\n  if (instance.config.async) {\n    if (instance.performance.face) delete instance.performance.face;\n    if (instance.performance.age) delete instance.performance.age;\n    if (instance.performance.gender) delete instance.performance.gender;\n    if (instance.performance.emotion) delete instance.performance.emotion;\n  }\n  return faceRes;\n};\n", "/**\n * Gesture detection algorithm\n */\n\nimport type { GestureResult, BodyResult, FaceResult, HandResult, Point } from '../result';\nimport * as fingerPose from '../hand/fingerpose';\n\n/** face gesture type */\nexport type FaceGesture =\n  `facing ${'left' | 'center' | 'right'}`\n  | `blink ${'left' | 'right'} eye`\n  | `mouth ${number}% open`\n  | `head ${'up' | 'down'}`;\n\n/** iris gesture type */\nexport type IrisGesture =\n  'facing center'\n  | `looking ${'left' | 'right' | 'up' | 'down'}`\n  | 'looking center';\n\n/** body gesture type */\nexport type BodyGesture =\n  `leaning ${'left' | 'right'}`\n  | `raise ${'left' | 'right'} hand`\n  | 'i give up';\n\n/** hand gesture type */\nexport type HandGesture =\n  `${'thumb' | 'index' | 'middle' | 'ring' | 'pinky'} forward`\n  | `${'thumb' | 'index' | 'middle' | 'ring' | 'pinky'} up`\n  | 'victory'\n  | 'thumbs up';\n\nexport const body = (res: BodyResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: BodyGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position[1] < nose.position[1]) && (rightWrist.position[1] < nose.position[1])) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position[1] < nose.position[1])) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position[1] < nose.position[1])) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder && Math.abs(leftShoulder.positionRaw[1] - rightShoulder.positionRaw[1]) > 0.1) {\n      gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position[1] > rightShoulder.position[1]) ? 'left' : 'right'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const face = (res: FaceResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: FaceGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 450) {\n      const zDiff = (res[i].mesh[33][2] || 0) - (res[i].mesh[263][2] || 0);\n      const xDiff = res[i].mesh[33][0] - res[i].mesh[263][0];\n      if (Math.abs(zDiff / xDiff) <= 0.15) gestures.push({ face: i, gesture: 'facing center' });\n      else gestures.push({ face: i, gesture: `facing ${zDiff < 0 ? 'left' : 'right'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2] || 0;\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res: FaceResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: IrisGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.leftEyeIris[0] || !res[i].annotations.rightEyeIris || !res[i].annotations.rightEyeIris[0]) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    let center = false;\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) {\n      center = true;\n      gestures.push({ iris: i, gesture: 'facing center' });\n    }\n\n    const leftIrisCenterX = Math.abs(res[i].mesh[263][0] - res[i].annotations.leftEyeIris[0][0]) / res[i].box[2];\n    const rightIrisCenterX = Math.abs(res[i].mesh[33][0] - res[i].annotations.rightEyeIris[0][0]) / res[i].box[2];\n    if (leftIrisCenterX > 0.06 || rightIrisCenterX > 0.06) center = false;\n    if (leftIrisCenterX > rightIrisCenterX) { // check eye with bigger offset\n      if (leftIrisCenterX > 0.05) gestures.push({ iris: i, gesture: 'looking right' });\n    } else {\n      if (rightIrisCenterX > 0.05) gestures.push({ iris: i, gesture: 'looking left' });\n    }\n\n    const rightIrisCenterY = Math.abs(res[i].mesh[145][1] - res[i].annotations.rightEyeIris[0][1]) / res[i].box[3];\n    const leftIrisCenterY = Math.abs(res[i].mesh[374][1] - res[i].annotations.leftEyeIris[0][1]) / res[i].box[3];\n    if (leftIrisCenterY < 0.01 || rightIrisCenterY < 0.01 || leftIrisCenterY > 0.022 || rightIrisCenterY > 0.022) center = false;\n    if (leftIrisCenterY < 0.01 || rightIrisCenterY < 0.01) gestures.push({ iris: i, gesture: 'looking down' });\n    if (leftIrisCenterY > 0.022 || rightIrisCenterY > 0.022) gestures.push({ iris: i, gesture: 'looking up' });\n\n    // still center;\n    if (center) gestures.push({ iris: i, gesture: 'looking center' });\n  }\n  return gestures;\n};\n\nexport const hand = (res: HandResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: HandGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: Point }> = [];\n    if (res[i]['annotations']) {\n      for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n        if (finger !== 'palmBase' && Array.isArray(pos) && pos[0]) fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n      }\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => ((best.position[2] || 0) < (a.position[2] || 0) ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward` as HandGesture });\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${highest.name} up` as HandGesture });\n    }\n    if (res[i]['keypoints']) {\n      const poses = fingerPose.match(res[i]['keypoints']);\n      for (const pose of poses) gestures.push({ hand: i, gesture: pose.name as HandGesture });\n    }\n  }\n  return gestures;\n};\n", "/**\n * Results interpolation for smoothening of video detection results inbetween detected frames\n */\n\nimport type { Result, FaceResult, BodyResult, HandResult, ObjectResult, GestureResult, PersonResult, Box, Point, BodyLandmark, BodyAnnotation } from '../result';\nimport type { Config } from '../config';\n\nimport * as moveNetCoords from '../body/movenetcoords';\nimport * as blazePoseCoords from '../body/blazeposecoords';\nimport * as efficientPoseCoords from '../body/efficientposecoords';\nimport { now } from './util';\nimport { env } from './env';\n\nconst bufferedResult: Result = { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0, error: null };\nlet interpolateTime = 0;\n\nexport function calc(newResult: Result, config: Config): Result {\n  const t0 = now();\n  if (!newResult) return { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0, error: null };\n  // each record is only updated using deep clone when number of detected record changes, otherwise it will converge by itself\n  // otherwise bufferedResult is a shallow clone of result plus updated local calculated values\n  // thus mixing by-reference and by-value assignments to minimize memory operations\n\n  const elapsed = Date.now() - newResult.timestamp;\n  // curve fitted: buffer = 8 - ln(delay)\n  // interpolation formula: current = ((buffer - 1) * previous + live) / buffer\n  // - at  50ms delay buffer = ~4.1 => 28% towards live data\n  // - at 250ms delay buffer = ~2.5 => 40% towards live data\n  // - at 500ms delay buffer = ~1.8 => 55% towards live data\n  // - at 750ms delay buffer = ~1.4 => 71% towards live data\n  // - at  1sec delay buffer = 1 which means live data is used\n  const bufferedFactor = elapsed < 1000 ? 8 - Math.log(elapsed + 1) : 1;\n\n  if (newResult.canvas) bufferedResult.canvas = newResult.canvas;\n  if (newResult.error) bufferedResult.error = newResult.error;\n\n  // interpolate body results\n  if (!bufferedResult.body || (newResult.body.length !== bufferedResult.body.length)) {\n    bufferedResult.body = JSON.parse(JSON.stringify(newResult.body as BodyResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.body.length; i++) {\n      const box = newResult.body[i].box // update box\n        .map((newBoxCoord, j) => ((bufferedFactor - 1) * bufferedResult.body[i].box[j] + newBoxCoord) / bufferedFactor) as Box;\n      const boxRaw = newResult.body[i].boxRaw // update boxRaw\n        .map((newBoxCoord, j) => ((bufferedFactor - 1) * bufferedResult.body[i].boxRaw[j] + newBoxCoord) / bufferedFactor) as Box;\n      const keypoints = (newResult.body[i].keypoints // update keypoints\n        .map((newKpt, j) => ({\n          score: newKpt.score,\n          part: newKpt.part as BodyLandmark,\n          position: [\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].position[0] || 0) + (newKpt.position[0] || 0)) / bufferedFactor : newKpt.position[0],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].position[1] || 0) + (newKpt.position[1] || 0)) / bufferedFactor : newKpt.position[1],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].position[2] || 0) + (newKpt.position[2] || 0)) / bufferedFactor : newKpt.position[2],\n          ],\n          positionRaw: [\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].positionRaw[0] || 0) + (newKpt.positionRaw[0] || 0)) / bufferedFactor : newKpt.positionRaw[0],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].positionRaw[1] || 0) + (newKpt.positionRaw[1] || 0)) / bufferedFactor : newKpt.positionRaw[1],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].positionRaw[2] || 0) + (newKpt.positionRaw[2] || 0)) / bufferedFactor : newKpt.positionRaw[2],\n          ],\n          distance: [\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].distance?.[0] || 0) + (newKpt.distance?.[0] || 0)) / bufferedFactor : newKpt.distance?.[0],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].distance?.[1] || 0) + (newKpt.distance?.[1] || 0)) / bufferedFactor : newKpt.distance?.[1],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].distance?.[2] || 0) + (newKpt.distance?.[2] || 0)) / bufferedFactor : newKpt.distance?.[2],\n          ],\n        }))) as Array<{ score: number, part: BodyLandmark, position: [number, number, number?], positionRaw: [number, number, number?] }>;\n\n      const annotations: Record<BodyAnnotation, Point[][]> = {} as Record<BodyAnnotation, Point[][]>; // recreate annotations\n      let coords = { connected: {} };\n      if (config.body?.modelPath?.includes('efficientpose')) coords = efficientPoseCoords;\n      else if (config.body?.modelPath?.includes('blazepose')) coords = blazePoseCoords;\n      else if (config.body?.modelPath?.includes('movenet')) coords = moveNetCoords;\n      for (const [name, indexes] of Object.entries(coords.connected as Record<string, string[]>)) {\n        const pt: Array<Point[]> = [];\n        for (let j = 0; j < indexes.length - 1; j++) {\n          const pt0 = keypoints.find((kp) => kp.part === indexes[j]);\n          const pt1 = keypoints.find((kp) => kp.part === indexes[j + 1]);\n          // if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n          if (pt0 && pt1) pt.push([pt0.position, pt1.position]);\n        }\n        annotations[name] = pt;\n      }\n      bufferedResult.body[i] = { ...newResult.body[i], box, boxRaw, keypoints, annotations: annotations as BodyResult['annotations'] }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate hand results\n  if (!bufferedResult.hand || (newResult.hand.length !== bufferedResult.hand.length)) {\n    bufferedResult.hand = JSON.parse(JSON.stringify(newResult.hand as HandResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.hand.length; i++) {\n      const box = (newResult.hand[i].box// update box\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.hand[i].box[j] + b) / bufferedFactor)) as Box;\n      const boxRaw = (newResult.hand[i].boxRaw // update boxRaw\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.hand[i].boxRaw[j] + b) / bufferedFactor)) as Box;\n      if (bufferedResult.hand[i].keypoints.length !== newResult.hand[i].keypoints.length) bufferedResult.hand[i].keypoints = newResult.hand[i].keypoints; // reset keypoints as previous frame did not have them\n      const keypoints = newResult.hand[i].keypoints && newResult.hand[i].keypoints.length > 0 ? newResult.hand[i].keypoints // update landmarks\n        .map((landmark, j) => landmark\n          .map((coord, k) => (((bufferedFactor - 1) * (bufferedResult.hand[i].keypoints[j][k] || 1) + (coord || 0)) / bufferedFactor)) as Point)\n        : [];\n      let annotations = {};\n      if (Object.keys(bufferedResult.hand[i].annotations).length !== Object.keys(newResult.hand[i].annotations).length) {\n        bufferedResult.hand[i].annotations = newResult.hand[i].annotations; // reset annotations as previous frame did not have them\n        annotations = bufferedResult.hand[i].annotations;\n      } else if (newResult.hand[i].annotations) {\n        for (const key of Object.keys(newResult.hand[i].annotations)) { // update annotations\n          annotations[key] = newResult.hand[i].annotations[key] && newResult.hand[i].annotations[key][0]\n            ? newResult.hand[i].annotations[key]\n              .map((val, j: number) => val\n                .map((coord: number, k: number) => ((bufferedFactor - 1) * bufferedResult.hand[i].annotations[key][j][k] + coord) / bufferedFactor))\n            : null;\n        }\n      }\n      bufferedResult.hand[i] = { ...newResult.hand[i], box, boxRaw, keypoints, annotations: annotations as HandResult['annotations'] }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate face results\n  if (!bufferedResult.face || (newResult.face.length !== bufferedResult.face.length)) {\n    bufferedResult.face = JSON.parse(JSON.stringify(newResult.face as FaceResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.face.length; i++) {\n      const box = (newResult.face[i].box // update box\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i].box[j] + b) / bufferedFactor)) as Box;\n      const boxRaw = (newResult.face[i].boxRaw // update boxRaw\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i].boxRaw[j] + b) / bufferedFactor)) as Box;\n      if (newResult.face[i].rotation) {\n        const rotation: {\n          matrix: [number, number, number, number, number, number, number, number, number],\n          angle: { roll: number, yaw: number, pitch: number },\n          gaze: { bearing: number, strength: number }\n        } = { matrix: [0, 0, 0, 0, 0, 0, 0, 0, 0], angle: { roll: 0, yaw: 0, pitch: 0 }, gaze: { bearing: 0, strength: 0 } };\n        rotation.matrix = newResult.face[i].rotation?.matrix as [number, number, number, number, number, number, number, number, number];\n        rotation.angle = {\n          roll: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.roll || 0) + (newResult.face[i].rotation?.angle?.roll || 0)) / bufferedFactor,\n          yaw: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.yaw || 0) + (newResult.face[i].rotation?.angle?.yaw || 0)) / bufferedFactor,\n          pitch: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.pitch || 0) + (newResult.face[i].rotation?.angle?.pitch || 0)) / bufferedFactor,\n        };\n        rotation.gaze = {\n          // not fully correct due projection on circle, also causes wrap-around draw on jump from negative to positive\n          bearing: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.gaze?.bearing || 0) + (newResult.face[i].rotation?.gaze?.bearing || 0)) / bufferedFactor,\n          strength: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.gaze?.strength || 0) + (newResult.face[i].rotation?.gaze?.strength || 0)) / bufferedFactor,\n        };\n        bufferedResult.face[i] = { ...newResult.face[i], rotation, box, boxRaw }; // shallow clone plus updated values\n      }\n      bufferedResult.face[i] = { ...newResult.face[i], box, boxRaw }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate object detection results\n  if (!bufferedResult.object || (newResult.object.length !== bufferedResult.object.length)) {\n    bufferedResult.object = JSON.parse(JSON.stringify(newResult.object as ObjectResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.object.length; i++) {\n      const box = (newResult.object[i].box // update box\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.object[i].box[j] + b) / bufferedFactor)) as Box;\n      const boxRaw = (newResult.object[i].boxRaw // update boxRaw\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.object[i].boxRaw[j] + b) / bufferedFactor)) as Box;\n      bufferedResult.object[i] = { ...newResult.object[i], box, boxRaw }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate person results\n  if (newResult.persons) {\n    const newPersons = newResult.persons; // trigger getter function\n    if (!bufferedResult.persons || (newPersons.length !== bufferedResult.persons.length)) {\n      bufferedResult.persons = JSON.parse(JSON.stringify(newPersons as PersonResult[]));\n    } else {\n      for (let i = 0; i < newPersons.length; i++) { // update person box, we don't update the rest as it's updated as reference anyhow\n        bufferedResult.persons[i].box = (newPersons[i].box\n          .map((box, j) => ((bufferedFactor - 1) * bufferedResult.persons[i].box[j] + box) / bufferedFactor)) as Box;\n      }\n    }\n  }\n\n  // just copy latest gestures without interpolation\n  if (newResult.gesture) bufferedResult.gesture = newResult.gesture as GestureResult[];\n\n  // append interpolation performance data\n  const t1 = now();\n  interpolateTime = env.perfadd ? interpolateTime + Math.round(t1 - t0) : Math.round(t1 - t0);\n  if (newResult.performance) bufferedResult.performance = { ...newResult.performance, interpolate: interpolateTime };\n\n  return bufferedResult;\n}\n", "/** Face descriptor type as number array */\nexport type Descriptor = Array<number>\nexport type MatchOptions = { order?: number, threshold?: number, multiplier?: number, min?: number, max?: number } | undefined;\n\n/** Calculates distance between two descriptors\n * @param options - calculation options\n * - order - algorithm to use\n *   Euclidean distance if `order` is 2 (default), Minkowski distance algorithm of nth order if `order` is higher than 2\n * - multiplier - by how much to enhance difference analysis in range of 1..100\n *   default is 20 which normalizes results to similarity above 0.5 can be considered a match\n */\nexport function distance(descriptor1: Descriptor, descriptor2: Descriptor, options: MatchOptions = { order: 2, multiplier: 25 }) {\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  let sum = 0;\n  for (let i = 0; i < descriptor1.length; i++) {\n    const diff = (!options.order || options.order === 2) ? (descriptor1[i] - descriptor2[i]) : (Math.abs(descriptor1[i] - descriptor2[i]));\n    sum += (!options.order || options.order === 2) ? (diff * diff) : (diff ** options.order);\n  }\n  return (options.multiplier || 20) * sum;\n}\n\n// invert distance to similarity, normalize to given range and clamp\nconst normalizeDistance = (dist, order, min, max) => {\n  if (dist === 0) return 1; // short circuit for identical inputs\n  const root = order === 2 ? Math.sqrt(dist) : dist ** (1 / order); // take root of distance\n  const norm = (1 - (root / 100) - min) / (max - min); // normalize to range\n  const clamp = Math.max(Math.min(norm, 1), 0); // clamp to 0..1\n  return clamp;\n};\n\n/** Calculates normalized similarity between two face descriptors based on their `distance`\n * @param options - calculation options\n * - order - algorithm to use\n *   Euclidean distance if `order` is 2 (default), Minkowski distance algorithm of nth order if `order` is higher than 2\n * - multiplier - by how much to enhance difference analysis in range of 1..100\n *   default is 20 which normalizes results to similarity above 0.5 can be considered a match\n * - min - normalize similarity result to a given range\n * - max - normalzie similarity resutl to a given range\n *   default is 0.2...0.8\n * Returns similarity between two face descriptors normalized to 0..1 range where 0 is no similarity and 1 is perfect similarity\n */\nexport function similarity(descriptor1: Descriptor, descriptor2: Descriptor, options: MatchOptions = { order: 2, multiplier: 25, min: 0.2, max: 0.8 }) {\n  const dist = distance(descriptor1, descriptor2, options);\n  return normalizeDistance(dist, options.order || 2, options.min || 0, options.max || 1);\n}\n\n/** Matches given descriptor to a closest entry in array of descriptors\n * @param descriptor - face descriptor\n * @param descriptors - array of face descriptors to commpare given descriptor to\n * @param options - see `similarity` method for options description\n * Returns\n * - `index` index array index where best match was found or -1 if no matches\n * - `distance` calculated `distance` of given descriptor to the best match\n * - `similarity` calculated normalized `similarity` of given descriptor to the best match\n*/\nexport function match(descriptor: Descriptor, descriptors: Array<Descriptor>, options: MatchOptions = { order: 2, multiplier: 25, threshold: 0, min: 0.2, max: 0.8 }) {\n  if (!Array.isArray(descriptor) || !Array.isArray(descriptors) || descriptor.length < 64 || descriptors.length === 0 || descriptor.length !== descriptors[0].length) { // validate input\n    return { index: -1, distance: Number.POSITIVE_INFINITY, similarity: 0 };\n  }\n  let lowestDistance = Number.MAX_SAFE_INTEGER;\n  let index = -1;\n  for (let i = 0; i < descriptors.length; i++) {\n    const res = distance(descriptor, descriptors[i], options);\n    if (res < lowestDistance) {\n      lowestDistance = res;\n      index = i;\n    }\n    if (lowestDistance < (options.threshold || 0)) break;\n  }\n  const normalizedSimilarity = normalizeDistance(lowestDistance, options.order || 2, options.min || 0, options.max || 1);\n  return { index, distance: lowestDistance, similarity: normalizedSimilarity };\n}\n", "/**\n * Analyze detection Results and sort&combine them into per-person view\n */\n\nimport type { FaceResult, BodyResult, HandResult, GestureResult, PersonResult, Box } from '../result';\n\nexport function join(faces: Array<FaceResult>, bodies: Array<BodyResult>, hands: Array<HandResult>, gestures: Array<GestureResult>, shape: Array<number> | undefined): Array<PersonResult> {\n  let id = 0;\n  const persons: Array<PersonResult> = [];\n  for (const face of faces) { // person is defined primarily by face and then we append other objects as found\n    const person: PersonResult = { id: id++, face, body: null, hands: { left: null, right: null }, gestures: [], box: [0, 0, 0, 0] };\n    for (const body of bodies) {\n      if (face.box[0] > body.box[0] // x within body\n        && face.box[0] < body.box[0] + body.box[2]\n        && face.box[1] + face.box[3] > body.box[1] // y within body\n        && face.box[1] + face.box[3] < body.box[1] + body.box[3]) {\n        person.body = body;\n      }\n    }\n    if (person.body) { // only try to join hands if body is found\n      for (const hand of hands) {\n        if (hand.box[0] + hand.box[2] > person.body.box[0] // x within body for left hand\n          && hand.box[0] + hand.box[2] < person.body.box[0] + person.body.box[2]\n          && hand.box[1] + hand.box[3] > person.body.box[1] // x within body for left hand\n          && hand.box[1] + hand.box[3] < person.body.box[1] + person.body.box[3]) {\n          if (person.hands) person.hands.left = hand;\n        }\n        if (hand.box[0] < person.body.box[0] + person.body.box[2] // x within body for right hand\n          && hand.box[0] > person.body.box[0]\n          && hand.box[1] + hand.box[3] > person.body.box[1] // x within body for right hand\n          && hand.box[1] + hand.box[3] < person.body.box[1] + person.body.box[3]) {\n          if (person.hands) person.hands.right = hand;\n        }\n      }\n    }\n    for (const gesture of gestures) { // append all gestures according to ids\n      if (gesture['face'] !== undefined && gesture['face'] === face.id) person.gestures?.push(gesture);\n      else if (gesture['iris'] !== undefined && gesture['iris'] === face.id) person.gestures?.push(gesture);\n      else if (gesture['body'] !== undefined && gesture['body'] === person.body?.id) person.gestures?.push(gesture);\n      else if (gesture['hand'] !== undefined && gesture['hand'] === person.hands?.left?.id) person.gestures?.push(gesture);\n      else if (gesture['hand'] !== undefined && gesture['hand'] === person.hands?.right?.id) person.gestures?.push(gesture);\n    }\n\n    // create new overarching box from all boxes belonging to person\n    const x: number[] = [];\n    const y: number[] = [];\n    const extractXY = (box: Box | undefined) => { // extract all [x, y] coordinates from boxes [x, y, width, height]\n      if (box && box.length === 4) {\n        x.push(box[0], box[0] + box[2]);\n        y.push(box[1], box[1] + box[3]);\n      }\n    };\n    extractXY(person.face?.box);\n    extractXY(person.body?.box);\n    extractXY(person.hands?.left?.box);\n    extractXY(person.hands?.right?.box);\n    const minX = Math.min(...x);\n    const minY = Math.min(...y);\n    person.box = [minX, minY, Math.max(...x) - minX, Math.max(...y) - minY]; // create new overarching box\n\n    // shape is known so we calculate boxRaw as well\n    if (shape && shape[1] && shape[2]) person.boxRaw = [person.box[0] / shape[2], person.box[1] / shape[1], person.box[2] / shape[2], person.box[3] / shape[1]];\n\n    persons.push(person);\n  }\n  return persons;\n}\n", "/**\n * Embedded sample images used during warmup in dataURL format\n */\n\n// data:image/jpeg;base64,\nexport const face = `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`;\n\n// data:image/jpeg;base64,\nexport const body = `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\n2Q==`;\n", "/**\n * Warmup algorithm that uses embedded images to exercise loaded models for faster future inference\n */\n\nimport { log, now, mergeDeep } from './util/util';\nimport * as sample from './sample';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as image from './image/image';\nimport { env } from './util/env';\nimport type { Config } from './config';\nimport type { Result } from './result';\nimport type { Human, Models } from './human';\nimport type { Tensor } from './tfjs/types';\n\nasync function warmupBitmap(instance: Human): Promise<Result | undefined> {\n  const b64toBlob = (base64: string, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n  let blob;\n  let res;\n  switch (instance.config.warmup) {\n    case 'face': blob = await b64toBlob(sample.face); break;\n    case 'body':\n    case 'full': blob = await b64toBlob(sample.body); break;\n    default: blob = null;\n  }\n  if (blob) {\n    const bitmap = await createImageBitmap(blob);\n    res = await instance.detect(bitmap, instance.config);\n    bitmap.close();\n  }\n  return res;\n}\n\nasync function warmupCanvas(instance: Human): Promise<Result | undefined> {\n  return new Promise((resolve) => {\n    let src;\n    // let size = 0;\n    switch (instance.config.warmup) {\n      case 'face':\n        // size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        // size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    let img: HTMLImageElement;\n    if (typeof Image !== 'undefined') img = new Image();\n    // @ts-ignore env.image is an external monkey-patch\n    else if (env.Image) img = new env.Image();\n    else return;\n    img.onload = async () => {\n      const canvas = image.canvas(img.naturalWidth, img.naturalHeight);\n      if (!canvas) {\n        log('Warmup: Canvas not found');\n        resolve(undefined);\n      } else {\n        const ctx = canvas.getContext('2d');\n        if (ctx) ctx.drawImage(img, 0, 0);\n        // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n        const tensor = await instance.image(canvas);\n        const res = await instance.detect(tensor.tensor as Tensor, instance.config);\n        resolve(res);\n      }\n    };\n    if (src) img.src = src;\n    else resolve(undefined);\n  });\n}\n\nasync function warmupNode(instance: Human): Promise<Result | undefined> {\n  const atob = (str: string) => Buffer.from(str, 'base64');\n  let img;\n  if (instance.config.warmup === 'face') img = atob(sample.face);\n  else img = atob(sample.body);\n  let res;\n  if ('node' in tf) {\n    // @ts-ignore tf.node may be undefined\n    const data = tf['node'].decodeJpeg(img);\n    const expanded = data.expandDims(0);\n    instance.tf.dispose(data);\n    // log('Input:', expanded);\n    res = await instance.detect(expanded, instance.config);\n    instance.tf.dispose(expanded);\n  } else {\n    if (instance.config.debug) log('Warmup tfjs-node not loaded');\n    /*\n    const input = await canvasJS.loadImage(img);\n    const canvas = canvasJS.createCanvas(input.width, input.height);\n    const ctx = canvas.getContext('2d');\n    ctx.drawImage(img, 0, 0, input.width, input.height);\n    res = await instance.detect(input, instance.config);\n    */\n  }\n  return res;\n}\n\nasync function runInference(instance: Human) {\n  let res: Result | undefined;\n  if (typeof createImageBitmap === 'function') res = await warmupBitmap(instance);\n  else if (typeof Image !== 'undefined' || env.Canvas !== undefined) res = await warmupCanvas(instance);\n  else res = await warmupNode(instance);\n  return res;\n}\n\n/** Runs pre-compile on all loaded models */\nexport async function runCompile(allModels: Models) {\n  if (!tf.env().flagRegistry['ENGINE_COMPILE_ONLY']) return; // tfjs does not support compile-only inference\n  const backendType = tf.getBackend();\n  const webGLBackend = tf.backend();\n  if ((backendType !== 'webgl' && backendType !== 'humangl') || (!webGLBackend || !webGLBackend.checkCompileCompletion)) {\n    // log('compile pass: skip');\n    return;\n  }\n  tf.env().set('ENGINE_COMPILE_ONLY', true);\n  const numTensorsStart = tf.engine().state.numTensors;\n  const compiledModels: string[] = [];\n  for (const [modelName, model] of Object.entries(allModels).filter(([key, val]) => (key !== null && val !== null))) {\n    const shape = (model.inputs && model.inputs[0] && model.inputs[0].shape) ? [...model.inputs[0].shape] : [1, 64, 64, 3];\n    const dtype = (model.inputs && model.inputs[0] && model.inputs[0].dtype) ? model.inputs[0].dtype : 'float32';\n    for (let dim = 0; dim < shape.length; dim++) {\n      if (shape[dim] === -1) shape[dim] = dim === 0 ? 1 : 64; // override batch number and any dynamic dimensions\n    }\n    const tensor = tf.zeros(shape, dtype);\n    // const res = await model.executeAsync(tensor); // fails with current tfjs\n    try {\n      const res = model.execute(tensor);\n      compiledModels.push(modelName);\n      if (Array.isArray(res)) res.forEach((t) => tf.dispose(t));\n      else tf.dispose(res);\n    } catch {\n      log('compile fail model:', modelName);\n    }\n    tf.dispose(tensor);\n  }\n  const kernels = await webGLBackend.checkCompileCompletionAsync();\n  webGLBackend.getUniformLocations();\n  log('compile pass models:', compiledModels);\n  log('compile pass kernels:', kernels.length);\n  tf.env().set('ENGINE_COMPILE_ONLY', false);\n  const numTensorsEnd = tf.engine().state.numTensors;\n  if ((numTensorsEnd - numTensorsStart) > 0) log('tensor leak:', numTensorsEnd - numTensorsStart);\n}\n\n/** Warmup method pre-initializes all configured models for faster inference\n * - can take significant time on startup\n * - only used in browser environments for `webgl` and `humangl` backends\n * @param userConfig?: Config\n*/\nexport async function warmup(instance: Human, userConfig?: Partial<Config>): Promise<Result | undefined> {\n  const t0 = now();\n  instance.state = 'warmup';\n  if (userConfig) instance.config = mergeDeep(instance.config, userConfig) as Config;\n  if (!instance.config.warmup || instance.config.warmup.length === 0 || instance.config.warmup === 'none') {\n    return { face: [], body: [], hand: [], gesture: [], object: [], performance: instance.performance, timestamp: now(), persons: [], error: null };\n  }\n  return new Promise(async (resolve) => {\n    await runCompile(instance.models);\n    const res = await runInference(instance);\n    const t1 = now();\n    if (instance.config.debug) log('warmup', instance.config.warmup, Math.round(t1 - t0), 'ms');\n    instance.emit('warmup');\n    resolve(res);\n  });\n}\n", "/**\n * Human main module\n * @default Human Library\n * @summary <https://github.com/vladmandic/human>\n * @author <https://github.com/vladmandic>\n * @copyright <https://github.com/vladmandic>\n * @license MIT\n */\n\n// module imports\nimport { log, now, mergeDeep, validate } from './util/util';\nimport { defaults } from './config';\nimport { env, Env } from './util/env';\nimport { setModelLoadOptions } from './tfjs/load';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as app from '../package.json';\nimport * as backend from './tfjs/backend';\nimport * as blazepose from './body/blazepose';\nimport * as centernet from './object/centernet';\nimport * as draw from './draw/draw';\nimport * as efficientpose from './body/efficientpose';\nimport * as face from './face/face';\nimport * as facemesh from './face/facemesh';\nimport * as faceres from './face/faceres';\nimport * as gesture from './gesture/gesture';\nimport * as handpose from './hand/handpose';\nimport * as handtrack from './hand/handtrack';\nimport * as humangl from './tfjs/humangl';\nimport * as image from './image/image';\nimport * as interpolate from './util/interpolate';\nimport * as match from './face/match';\nimport * as models from './models';\nimport * as movenet from './body/movenet';\nimport * as nanodet from './object/nanodet';\nimport * as persons from './util/persons';\nimport * as posenet from './body/posenet';\nimport * as segmentation from './segmentation/segmentation';\nimport * as warmups from './warmup';\n// type definitions\nimport type { Input, Tensor, DrawOptions, Config, Result, FaceResult, HandResult, BodyResult, ObjectResult, GestureResult, PersonResult, AnyCanvas, ModelStats } from './exports';\n// type exports\nexport * from './exports';\n\n/** **Human** library main class\n *\n * All methods and properties are available only as members of Human class\n *\n * - Configuration object definition: {@link Config}\n * - Results object definition: {@link Result}\n * - Possible inputs: {@link Input}\n *\n * @param userConfig - {@link Config}\n * @returns instance of {@link Human}\n */\nexport class Human {\n  /** Current version of Human library in *semver* format */\n  version: string;\n\n  /** Current configuration\n   * - Defaults: [config](https://github.com/vladmandic/human/blob/main/src/config.ts#L262)\n   */\n  config: Config;\n\n  /** Last known result of detect run\n   * - Can be accessed anytime after initial detection\n  */\n  result: Result;\n\n  /** Current state of Human library\n   * - Can be polled to determine operations that are currently executed\n   * - Progresses through: 'config', 'check', 'backend', 'load', 'run:<model>', 'idle'\n   */\n  state: string;\n\n  /** currenty processed image tensor and canvas */\n  process: { tensor: Tensor | null, canvas: AnyCanvas | null };\n\n  /** Instance of TensorFlow/JS used by Human\n   *  - Can be embedded or externally provided\n   * [TFJS API](https://js.tensorflow.org/api/latest/)\n   */\n  tf;\n\n  /** Object containing environment information used for diagnostics */\n  env: Env;\n\n  /** Draw helper classes that can draw detected objects on canvas using specified draw\n   * - canvas: draws input to canvas\n   * - options: are global settings for all draw operations, can be overriden for each draw method {@link DrawOptions}\n   * - face, body, hand, gesture, object, person: draws detected results as overlays on canvas\n   */\n  draw: { canvas: typeof draw.canvas, face: typeof draw.face, body: typeof draw.body, hand: typeof draw.hand, gesture: typeof draw.gesture, object: typeof draw.object, person: typeof draw.person, all: typeof draw.all, options: DrawOptions };\n\n  /** Currently loaded models\n   * @internal\n   * {@link Models}\n  */\n  models: models.Models;\n\n  /** Container for events dispatched by Human\n   * Possible events:\n   * - `create`: triggered when Human object is instantiated\n   * - `load`: triggered when models are loaded (explicitly or on-demand)\n   * - `image`: triggered when input image is processed\n   * - `result`: triggered when detection is complete\n   * - `warmup`: triggered when warmup is complete\n   * - `error`: triggered on some errors\n   */\n  events: EventTarget | undefined;\n  /** Reference face triangualtion array of 468 points, used for triangle references between points */\n  faceTriangulation: number[];\n  /** Refernce UV map of 468 values, used for 3D mapping of the face mesh */\n  faceUVMap: [number, number][];\n  /** Performance object that contains values for all recently performed operations */\n  performance: Record<string, number>; // perf members are dynamically defined as needed\n  #numTensors: number;\n  #analyzeMemoryLeaks: boolean;\n  #checkSanity: boolean;\n  /** WebGL debug info */\n  gl: Record<string, unknown>;\n  // definition end\n\n  /** Constructor for **Human** library that is futher used for all operations\n   * @param userConfig - user configuration object {@link Config}\n   */\n  constructor(userConfig?: Partial<Config>) {\n    this.env = env;\n    /*\n    defaults.wasmPath = tf.version['tfjs-core'].includes('-') // custom build or official build\n      ? 'https://vladmandic.github.io/tfjs/dist/'\n      : `https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${tf.version_core}/dist/`;\n    */\n    const tfVersion = (tf.version?.tfjs || tf.version_core).replace(/-(.*)/, '');\n    defaults.wasmPath = `https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${tfVersion}/dist/`;\n    defaults.modelBasePath = env.browser ? '../models/' : 'file://models/';\n    defaults.backend = env.browser ? 'humangl' : 'tensorflow';\n    this.version = app.version; // expose version property on instance of class\n    Object.defineProperty(this, 'version', { value: app.version }); // expose version property directly on class itself\n    this.config = JSON.parse(JSON.stringify(defaults));\n    Object.seal(this.config);\n    this.config.cacheModels = typeof indexedDB !== 'undefined';\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    setModelLoadOptions(this.config);\n    this.tf = tf;\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.performance = {};\n    this.events = (typeof EventTarget !== 'undefined') ? new EventTarget() : undefined;\n    // object that contains all initialized models\n    this.models = new models.Models();\n    // reexport draw methods\n    this.draw = {\n      options: draw.options as DrawOptions,\n      canvas: (input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas) => draw.canvas(input, output),\n      face: (output: AnyCanvas, result: FaceResult[], options?: Partial<DrawOptions>) => draw.face(output, result, options),\n      body: (output: AnyCanvas, result: BodyResult[], options?: Partial<DrawOptions>) => draw.body(output, result, options),\n      hand: (output: AnyCanvas, result: HandResult[], options?: Partial<DrawOptions>) => draw.hand(output, result, options),\n      gesture: (output: AnyCanvas, result: GestureResult[], options?: Partial<DrawOptions>) => draw.gesture(output, result, options),\n      object: (output: AnyCanvas, result: ObjectResult[], options?: Partial<DrawOptions>) => draw.object(output, result, options),\n      person: (output: AnyCanvas, result: PersonResult[], options?: Partial<DrawOptions>) => draw.person(output, result, options),\n      all: (output: AnyCanvas, result: Result, options?: Partial<DrawOptions>) => draw.all(output, result, options),\n    };\n    this.result = { face: [], body: [], hand: [], gesture: [], object: [], performance: {}, timestamp: 0, persons: [], error: null };\n    // export access to image processing\n    // @ts-ignore eslint-typescript cannot correctly infer type in anonymous function\n    this.process = { tensor: null, canvas: null };\n    // export raw access to underlying models\n    this.faceTriangulation = facemesh.triangulation;\n    this.faceUVMap = facemesh.uvmap;\n    // set gl info\n    this.gl = humangl.config;\n    // include platform info\n    this.emit('create');\n  }\n\n  /** internal function to measure tensor leaks */\n  analyze = (...msg: string[]) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const currentTensors = this.tf.engine().state.numTensors;\n    const previousTensors = this.#numTensors;\n    this.#numTensors = currentTensors;\n    const leaked = currentTensors - previousTensors;\n    if (leaked !== 0) log(...msg, leaked);\n  };\n\n  /** internal function for quick sanity check on inputs @hidden */\n  #sanity = (input: Input): null | string => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.env.node && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  };\n\n  /** Reset configuration to default values */\n  reset(): void {\n    const currentBackend = this.config.backend; // save backend;\n    this.config = JSON.parse(JSON.stringify(defaults));\n    this.config.backend = currentBackend;\n  }\n\n  /** Validate current configuration schema */\n  validate(userConfig?: Partial<Config>) {\n    return validate(defaults, userConfig || this.config);\n  }\n\n  /** Exports face matching methods {@link match#similarity} */\n  public similarity = match.similarity;\n  /** Exports face matching methods {@link match#distance} */\n  public distance = match.distance;\n  /** Exports face matching methods {@link match#match} */\n  public match = match.match;\n\n  /** Utility wrapper for performance.now() */\n  now(): number {\n    return now();\n  }\n\n  /** Process input as return canvas and tensor\n   *\n   * @param input - any input {@link Input}\n   * @param getTensor - should image processing also return tensor or just canvas\n   * Returns object with `tensor` and `canvas`\n   */\n  image(input: Input, getTensor: boolean = true) {\n    return image.process(input, this.config, getTensor);\n  }\n\n  /** Segmentation method takes any input and returns processed canvas with body segmentation\n   *  - Segmentation is not triggered as part of detect process\n   * @param input - {@link Input}\n   * @param background - {@link Input}\n   *  - Optional parameter background is used to fill the background with specific input\n   *  Returns:\n   *  - `data` as raw data array with per-pixel segmentation values\n   *  - `canvas` as canvas which is input image filtered with segementation data and optionally merged with background image. canvas alpha values are set to segmentation values for easy merging\n   *  - `alpha` as grayscale canvas that represents segmentation alpha values\n   */\n  async segmentation(input: Input, background?: Input): Promise<{ data: number[] | Tensor, canvas: AnyCanvas | null, alpha: AnyCanvas | null }> {\n    return segmentation.process(input, background, this.config);\n  }\n\n  /** Enhance method performs additional enhacements to face image previously detected for futher processing\n   *\n   * @param input - Tensor as provided in human.result.face[n].tensor\n   * @returns Tensor\n   */\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return faceres.enhance(input);\n  }\n\n  /** Compare two input tensors for pixel simmilarity\n   * - use `human.image` to process any valid input and get a tensor that can be used for compare\n   * - when passing manually generated tensors:\n   *  - both input tensors must be in format [1, height, width, 3]\n   *  - if resolution of tensors does not match, second tensor will be resized to match resolution of the first tensor\n   * - return value is pixel similarity score normalized by input resolution and rgb channels\n  */\n  compare(firstImageTensor: Tensor, secondImageTensor: Tensor): Promise<number> {\n    return image.compare(this.config, firstImageTensor, secondImageTensor);\n  }\n\n  /** Explicit backend initialization\n   *  - Normally done implicitly during initial load phase\n   *  - Call to explictly register and initialize TFJS backend without any other operations\n   *  - Use when changing backend during runtime\n   */\n  async init(): Promise<void> {\n    await backend.check(this, true);\n    await this.tf.ready();\n  }\n\n  /** Load method preloads all configured models on-demand\n   * - Not explicitly required as any required model is load implicitly on it's first run\n   *\n   * @param userConfig - {@link Config}\n  */\n  async load(userConfig?: Partial<Config>): Promise<void> {\n    this.state = 'load';\n    const timeStamp = now();\n    const count = Object.values(this.models).filter((model) => model).length;\n    if (userConfig) this.config = mergeDeep(this.config, userConfig) as Config;\n\n    if (this.env.initial) { // print version info on first run and check for correct backend setup\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version['tfjs-core']}`);\n      if (!await backend.check(this)) log('error: backend check failed');\n      await tf.ready();\n      if (this.env.browser) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('environment:', this.env);\n        if (this.config.debug) log('tf flags:', this.tf.ENV['flags']);\n      }\n    }\n\n    await models.load(this); // actually loads models\n    if (this.env.initial && this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors'); // print memory stats on first run\n    this.env.initial = false;\n\n    const loaded = Object.values(this.models).filter((model) => model).length;\n    if (loaded !== count) { // number of loaded models changed\n      await models.validate(this); // validate kernel ops used by model against current backend\n      this.emit('load');\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.performance.loadModels as number || 0)) this.performance.loadModels = this.env.perfadd ? (this.performance.loadModels || 0) + current : current;\n  }\n\n  /** emit event */\n  emit = (event: string) => {\n    if (this.events && this.events.dispatchEvent) this.events?.dispatchEvent(new Event(event));\n  };\n\n  /** Runs interpolation using last known result and returns smoothened result\n   * Interpolation is based on time since last known result so can be called independently\n   *\n   * @param result - {@link Result} optional use specific result set to run interpolation on\n   * @returns result - {@link Result}\n   */\n  next(result: Result = this.result): Result {\n    return interpolate.calc(result, this.config) as Result;\n  }\n\n  /** get model loading/loaded stats */\n  getModelStats(): ModelStats { return models.getModelStats(this); }\n\n  /** Warmup method pre-initializes all configured models for faster inference\n   * - can take significant time on startup\n   * - only used for `webgl` and `humangl` backends\n   * @param userConfig - {@link Config}\n   * @returns result - {@link Result}\n  */\n  async warmup(userConfig?: Partial<Config>) {\n    const t0 = now();\n    const res = await warmups.warmup(this, userConfig);\n    const t1 = now();\n    this.performance.warmup = Math.trunc(t1 - t0);\n    return res;\n  }\n\n  /** Run detect with tensorflow profiling\n   * - result object will contain total exeuction time information for top-20 kernels\n   * - actual detection object can be accessed via `human.result`\n  */\n  async profile(input: Input, userConfig?: Partial<Config>): Promise<Array<{ kernel: string, time: number, perc: number }>> {\n    const profile = await this.tf.profile(() => this.detect(input, userConfig));\n    const kernels: Record<string, number> = {};\n    let total = 0;\n    for (const kernel of profile.kernels) { // sum kernel time values per kernel\n      if (kernels[kernel.name]) kernels[kernel.name] += kernel.kernelTimeMs;\n      else kernels[kernel.name] = kernel.kernelTimeMs;\n      total += kernel.kernelTimeMs;\n    }\n    const kernelArr: Array<{ kernel: string, time: number, perc: number }> = [];\n    Object.entries(kernels).forEach((key) => kernelArr.push({ kernel: key[0], time: key[1] as unknown as number, perc: 0 })); // convert to array\n    for (const kernel of kernelArr) {\n      kernel.perc = Math.round(1000 * kernel.time / total) / 1000;\n      kernel.time = Math.round(1000 * kernel.time) / 1000;\n    }\n    kernelArr.sort((a, b) => b.time - a.time); // sort\n    kernelArr.length = 20; // crop\n    // const res: Record<string, number> = {};\n    // for (const kernel of kernelArr) res[kernel.name] = kernel.ms; // create perf objects\n    return kernelArr;\n  }\n\n  /** Main detection method\n   * - Analyze configuration: {@link Config}\n   * - Pre-process input: {@link Input}\n   * - Run inference for all configured models\n   * - Process and return result: {@link Result}\n   *\n   * @param input - {@link Input}\n   * @param userConfig - {@link Config}\n   * @returns result - {@link Result}\n  */\n  async detect(input: Input, userConfig?: Partial<Config>): Promise<Result> {\n    // detection happens inside a promise\n    this.state = 'detect';\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig) as Config;\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        this.emit('error');\n        resolve({ face: [], body: [], hand: [], gesture: [], object: [], performance: this.performance, timestamp: now(), persons: [], error });\n      }\n\n      const timeStart = now();\n\n      // configure backend if needed\n      await backend.check(this);\n\n      // load models if enabled\n      await this.load();\n\n      timeStamp = now();\n      this.state = 'image';\n      const img = await image.process(input, this.config) as { canvas: AnyCanvas, tensor: Tensor };\n      this.process = img;\n      this.performance.inputProcess = this.env.perfadd ? (this.performance.inputProcess || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      this.analyze('Get Image:');\n\n      if (!img.tensor) {\n        if (this.config.debug) log('could not convert input to tensor');\n        this.emit('error');\n        resolve({ face: [], body: [], hand: [], gesture: [], object: [], performance: this.performance, timestamp: now(), persons: [], error: 'could not convert input to tensor' });\n        return;\n      }\n      this.emit('image');\n\n      timeStamp = now();\n      this.config.skipAllowed = await image.skip(this.config, img.tensor);\n      if (!this.performance.totalFrames) this.performance.totalFrames = 0;\n      if (!this.performance.cachedFrames) this.performance.cachedFrames = 0;\n      (this.performance.totalFrames as number)++;\n      if (this.config.skipAllowed) this.performance.cachedFrames++;\n      this.performance.cacheCheck = this.env.perfadd ? (this.performance.cacheCheck || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      this.analyze('Check Changed:');\n\n      // prepare where to store model results\n      // keep them with weak typing as it can be promise or not\n      let faceRes: FaceResult[] | Promise<FaceResult[]> | never[] = [];\n      let bodyRes: BodyResult[] | Promise<BodyResult[]> | never[] = [];\n      let handRes: HandResult[] | Promise<HandResult[]> | never[] = [];\n      let objectRes: ObjectResult[] | Promise<ObjectResult[]> | never[] = [];\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      this.state = 'detect:face';\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? face.detectFace(this, img.tensor) : [];\n        if (this.performance.face) delete this.performance.face;\n      } else {\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await face.detectFace(this, img.tensor) : [];\n        this.performance.face = this.env.perfadd ? (this.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n\n      if (this.config.async && (this.config.body.maxDetected === -1 || this.config.hand.maxDetected === -1)) faceRes = await faceRes; // need face result for auto-detect number of hands or bodies\n\n      // run body: can be posenet, blazepose, efficientpose, movenet\n      this.analyze('Start Body:');\n      this.state = 'detect:body';\n      const bodyConfig = this.config.body.maxDetected === -1 ? mergeDeep(this.config, { body: { maxDetected: this.config.face.enabled ? 1 * (faceRes as FaceResult[]).length : 1 } }) : this.config; // autodetect number of bodies\n      if (this.config.async) {\n        if (this.config.body.modelPath?.includes('posenet')) bodyRes = this.config.body.enabled ? posenet.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('blazepose')) bodyRes = this.config.body.enabled ? blazepose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('efficientpose')) bodyRes = this.config.body.enabled ? efficientpose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('movenet')) bodyRes = this.config.body.enabled ? movenet.predict(img.tensor, bodyConfig) : [];\n        if (this.performance.body) delete this.performance.body;\n      } else {\n        timeStamp = now();\n        if (this.config.body.modelPath?.includes('posenet')) bodyRes = this.config.body.enabled ? await posenet.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('blazepose')) bodyRes = this.config.body.enabled ? await blazepose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('efficientpose')) bodyRes = this.config.body.enabled ? await efficientpose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('movenet')) bodyRes = this.config.body.enabled ? await movenet.predict(img.tensor, bodyConfig) : [];\n        this.performance.body = this.env.perfadd ? (this.performance.body || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n      this.analyze('End Body:');\n\n      // run handpose\n      this.analyze('Start Hand:');\n      this.state = 'detect:hand';\n      const handConfig = this.config.hand.maxDetected === -1 ? mergeDeep(this.config, { hand: { maxDetected: this.config.face.enabled ? 2 * (faceRes as FaceResult[]).length : 1 } }) : this.config; // autodetect number of hands\n      if (this.config.async) {\n        if (this.config.hand.detector?.modelPath?.includes('handdetect')) handRes = this.config.hand.enabled ? handpose.predict(img.tensor, handConfig) : [];\n        else if (this.config.hand.detector?.modelPath?.includes('handtrack')) handRes = this.config.hand.enabled ? handtrack.predict(img.tensor, handConfig) : [];\n        if (this.performance.hand) delete this.performance.hand;\n      } else {\n        timeStamp = now();\n        if (this.config.hand.detector?.modelPath?.includes('handdetect')) handRes = this.config.hand.enabled ? await handpose.predict(img.tensor, handConfig) : [];\n        else if (this.config.hand.detector?.modelPath?.includes('handtrack')) handRes = this.config.hand.enabled ? await handtrack.predict(img.tensor, handConfig) : [];\n        this.performance.hand = this.env.perfadd ? (this.performance.hand || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n      this.analyze('End Hand:');\n\n      // run object detection\n      this.analyze('Start Object:');\n      this.state = 'detect:object';\n      if (this.config.async) {\n        if (this.config.object.modelPath?.includes('nanodet')) objectRes = this.config.object.enabled ? nanodet.predict(img.tensor, this.config) : [];\n        else if (this.config.object.modelPath?.includes('centernet')) objectRes = this.config.object.enabled ? centernet.predict(img.tensor, this.config) : [];\n        if (this.performance.object) delete this.performance.object;\n      } else {\n        timeStamp = now();\n        if (this.config.object.modelPath?.includes('nanodet')) objectRes = this.config.object.enabled ? await nanodet.predict(img.tensor, this.config) : [];\n        else if (this.config.object.modelPath?.includes('centernet')) objectRes = this.config.object.enabled ? await centernet.predict(img.tensor, this.config) : [];\n        this.performance.object = this.env.perfadd ? (this.performance.object || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n      this.analyze('End Object:');\n\n      // if async wait for results\n      this.state = 'detect:await';\n      if (this.config.async) [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n\n      // run gesture analysis last\n      this.state = 'detect:gesture';\n      let gestureRes: GestureResult[] = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        gestureRes = [...gesture.face(faceRes as FaceResult[]), ...gesture.body(bodyRes as BodyResult[]), ...gesture.hand(handRes as HandResult[]), ...gesture.iris(faceRes as FaceResult[])];\n        if (!this.config.async) this.performance.gesture = this.env.perfadd ? (this.performance.gesture || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n        else if (this.performance.gesture) delete this.performance.gesture;\n      }\n\n      this.performance.total = this.env.perfadd ? (this.performance.total || 0) + Math.trunc(now() - timeStart) : Math.trunc(now() - timeStart);\n      const shape = this.process?.tensor?.shape || [];\n      this.result = {\n        face: faceRes as FaceResult[],\n        body: bodyRes as BodyResult[],\n        hand: handRes as HandResult[],\n        gesture: gestureRes,\n        object: objectRes as ObjectResult[],\n        performance: this.performance,\n        canvas: this.process.canvas,\n        timestamp: Date.now(),\n        error: null,\n        get persons() { return persons.join(faceRes as FaceResult[], bodyRes as BodyResult[], handRes as HandResult[], gestureRes, shape); },\n      };\n\n      // finally dispose input tensor\n      tf.dispose(img.tensor);\n\n      // log('Result:', result);\n      this.emit('detect');\n      this.state = 'idle';\n      resolve(this.result);\n    });\n  }\n}\n\n/** Class Human as default export */\n/* eslint no-restricted-exports: [\"off\", { \"restrictedNamedExports\": [\"default\"] }] */\nexport { Human as default, match, draw, models };\n"],
+  "mappings": ";;;;;;m5BAOO,SAASA,KAAOC,EAAW,CAChC,IAAMC,EAAK,IAAI,KACTC,EAAK,GAAGD,EAAG,SAAS,EAAE,SAAS,EAAE,SAAS,EAAG,GAAG,KAAKA,EAAG,WAAW,EAAE,SAAS,EAAE,SAAS,EAAG,GAAG,KAAKA,EAAG,WAAW,EAAE,SAAS,EAAE,SAAS,EAAG,GAAG,KAAKA,EAAG,gBAAgB,EAAE,SAAS,EAAE,SAAS,EAAG,GAAG,IAEpMD,GAAK,QAAQ,IAAIE,EAAI,SAAU,GAAGF,CAAG,CAC3C,CAGO,SAASG,GAAKC,EAAgBC,EAAsB,CACzD,IAAMC,EAAYF,EAAO,SAAS,GAAG,EAAI,GAAK,IAExCG,EADWF,EAAK,WAAW,GAAG,GAAKA,EAAK,WAAW,GAAG,GAAKA,EAAK,WAAW,OAAO,GAAKA,EAAK,WAAW,QAAQ,GAAKA,EAAK,WAAW,OAAO,EACzH,GAAGA,IAAS,GAAGD,IAASE,IAAYD,IAC5D,GAAI,CAACE,EAAK,kBAAkB,EAAE,SAAS,OAAO,EAAG,MAAM,IAAI,MAAM,yCAAyCA,GAAM,EAChH,OAAOA,CACT,CAGO,IAAMC,EAAM,IACb,OAAO,aAAgB,YAAoB,YAAY,IAAI,EACxD,UAAU,OAAO,QAAQ,OAAO,OAAO,CAAC,EAAI,IAAO,KAAM,SAAS,CAAC,EAIrE,SAASC,GAASC,EAA2BC,EAAyBC,EAAS,SAAUC,EAAoE,CAAC,EAAG,CACtK,QAAWC,KAAO,OAAO,KAAKH,CAAM,EAClC,GAAI,OAAOA,EAAOG,IAAS,SACzBL,GAASC,EAASI,GAAMH,EAAOG,GAAMA,EAAKD,CAAI,MACzC,CACL,IAAME,EAAUL,GAAa,OAAOA,EAASI,IAAS,YACjDC,GAASF,EAAK,KAAK,CAAE,OAAQ,mBAAoB,MAAO,GAAGD,KAAUE,OAASH,EAAOG,IAAO,CAAC,EAClG,IAAME,EAAON,GAAY,OAAOA,EAASI,IAAS,OAAOH,EAAOG,GAC5DC,GAAW,CAACC,GAAMH,EAAK,KAAK,CAAE,OAAQ,yBAA0B,MAAO,GAAGD,KAAUE,OAASH,EAAOG,KAAQ,SAAU,OAAOJ,EAASI,EAAK,CAAC,CAClJ,CAGF,OAAIH,EAAO,OAASC,IAAW,UAAYC,EAAK,OAAS,GAAGd,EAAI,wBAAyBc,CAAI,EACtFA,CACT,CAGO,SAASI,KAAaC,EAAS,CACpC,IAAMC,EAAYC,GAAQA,GAAO,OAAOA,GAAQ,SAChD,OAAOF,EAAQ,OAAO,CAACG,EAAMD,KAC3B,OAAO,KAAKA,GAAO,CAAC,CAAC,EAAE,QAASN,GAAQ,CACtC,IAAMQ,EAAOD,EAAKP,GACZS,EAAOH,EAAIN,GACb,MAAM,QAAQQ,CAAI,GAAK,MAAM,QAAQC,CAAI,EAAGF,EAAKP,GAAOQ,EAAK,OAAO,GAAGC,CAAI,EACtEJ,EAASG,CAAI,GAAKH,EAASI,CAAI,EAAGF,EAAKP,GAAOG,EAAUK,EAAMC,CAAI,EACtEF,EAAKP,GAAOS,CACnB,CAAC,EACMF,GACN,CAAC,CAAC,CACP,CC6PA,IAAMG,GAAiB,CACrB,QAAS,GACT,cAAe,GACf,YAAa,GACb,SAAU,GACV,kBAAmB,GACnB,MAAO,GACP,MAAO,GACP,OAAQ,OACR,iBAAkB,GAClB,YAAa,GACb,WAAY,GACZ,OAAQ,CACN,QAAS,GACT,aAAc,GACd,MAAO,EACP,OAAQ,EACR,KAAM,GACN,OAAQ,GACR,WAAY,EACZ,SAAU,EACV,UAAW,EACX,KAAM,EACN,WAAY,EACZ,IAAK,EACL,SAAU,GACV,MAAO,GACP,QAAS,GACT,WAAY,GACZ,YAAa,GACb,SAAU,GACV,SAAU,CACZ,EACA,QAAS,CACP,QAAS,EACX,EACA,KAAM,CACJ,QAAS,GACT,SAAU,CACR,UAAW,iBACX,SAAU,GACV,YAAa,EACb,WAAY,GACZ,SAAU,KACV,cAAe,GACf,aAAc,GACd,KAAM,GACN,OAAQ,EACV,EACA,KAAM,CACJ,QAAS,GACT,UAAW,gBACX,YAAa,EACf,EACA,UAAW,CACT,QAAS,GACT,UAAW,yBACb,EACA,KAAM,CACJ,QAAS,GACT,UAAW,WACb,EACA,QAAS,CACP,QAAS,GACT,cAAe,GACf,WAAY,GACZ,SAAU,KACV,UAAW,cACb,EACA,YAAa,CACX,QAAS,GACT,UAAW,eACX,WAAY,GACZ,SAAU,IACV,cAAe,EACjB,EACA,UAAW,CACT,QAAS,GACT,WAAY,GACZ,SAAU,IACV,UAAW,gBACb,EACA,SAAU,CACR,QAAS,GACT,WAAY,GACZ,SAAU,IACV,UAAW,eACb,CACF,EACA,KAAM,CACJ,QAAS,GACT,UAAW,yBACX,YAAa,GACb,cAAe,GACf,WAAY,EACZ,SAAU,GACZ,EACA,KAAM,CACJ,QAAS,GACT,SAAU,GACV,WAAY,GACZ,SAAU,IACV,cAAe,GACf,aAAc,GACd,YAAa,GACb,UAAW,GACX,SAAU,CACR,UAAW,gBACb,EACA,SAAU,CACR,UAAW,wBACb,CACF,EACA,OAAQ,CACN,QAAS,GACT,UAAW,qBACX,cAAe,GACf,aAAc,GACd,YAAa,GACb,WAAY,GACZ,SAAU,GACZ,EACA,aAAc,CACZ,QAAS,GACT,UAAW,cACX,KAAM,CACR,CACF,ECvbA,IAAAC,EAAA,GAAAC,GAAAD,EAAA,gBAAAE,GAAA,WAAAC,GAAA,YAAAC,KAMAC,EAAAL,EAAAM,IAA4CD,EAAAL,EAAAM,IAA5C,UAAAA,OAAW,iCAAiC,UAAAA,OAAW,+CAAuP,OAAO,UAAUH,OAAM,iCAAiC,OAAO,cAAcD,OAAM,wCAA3R,IAAIK,GAAE,SAASC,GAAE,SAASC,GAAE,SAASC,GAAE,SAASC,GAAE,SAASC,GAAE,SAASC,GAAE,SAAST,GAAE,CAAC,KAAKG,GAAE,YAAYC,GAAE,YAAYC,GAAE,cAAcC,GAAE,iBAAiBC,GAAE,qBAAqBC,GAAE,oBAAoBC,EAAC,ECNrS,IAAMC,GAAiB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;EAqBvB,IAAMC,GAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAcvBC,GAA0B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAc1BC,GAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAeXC,GAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAyBPC,GAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;EChF3B,IAAMC,GAAU,CAACC,EAAQC,EAAQC,IAAe,CAC9C,IAAMC,EAAI,IAAI,OAAO,MAAQF,EAAS,eAAgB,IAAI,EAC1DD,EAAO,QAAQG,EAAG,CAACC,EAAOC,KACxBH,EAAWG,GAAQ,EACZD,EACR,CACH,EAEME,GAAN,KAAgB,CAMd,YAAYC,EAAIC,EAAcC,EAAgB,CAL9CC,EAAA,eAAU,CAAC,GACXA,EAAA,iBAAY,CAAC,GACbA,EAAA,WACAA,EAAA,WA2BAA,EAAA,eAAU,CAACV,EAAQW,IAA6B,CAC9C,IAAMC,EAAS,KAAK,GAAG,aAAaD,CAAI,EACxC,OAAKC,GAIL,KAAK,GAAG,aAAaA,EAAQZ,CAAM,EACnC,KAAK,GAAG,cAAcY,CAAM,EACvB,KAAK,GAAG,mBAAmBA,EAAQ,KAAK,GAAG,cAAc,EAIvDA,GAHLC,EAAI,8BAA8B,KAAK,GAAG,iBAAiBD,CAAM,GAAG,EAC7D,QAPPC,EAAI,iCAAiC,EAC9B,KASX,GArCE,KAAK,GAAKN,EACV,IAAMO,EAAe,KAAK,QAAQN,EAAc,KAAK,GAAG,aAAa,EAC/DO,EAAiB,KAAK,QAAQN,EAAgB,KAAK,GAAG,eAAe,EAE3E,GADA,KAAK,GAAK,KAAK,GAAG,cAAc,EAC5B,GAACK,GAAgB,CAACC,GACtB,IAAI,CAAC,KAAK,GAAI,CACZF,EAAI,wCAAwC,EAC5C,MACF,CAIA,GAHA,KAAK,GAAG,aAAa,KAAK,GAAIC,CAAY,EAC1C,KAAK,GAAG,aAAa,KAAK,GAAIC,CAAc,EAC5C,KAAK,GAAG,YAAY,KAAK,EAAE,EACvB,CAAC,KAAK,GAAG,oBAAoB,KAAK,GAAI,KAAK,GAAG,WAAW,EAAG,CAC9DF,EAAI,2BAA2B,KAAK,GAAG,kBAAkB,KAAK,EAAE,GAAG,EACnE,MACF,CACA,KAAK,GAAG,WAAW,KAAK,EAAE,EAC1Bd,GAAQS,EAAc,YAAa,KAAK,SAAS,EACjD,QAAW,KAAK,KAAK,UAAW,KAAK,UAAU,GAAK,KAAK,GAAG,kBAAkB,KAAK,GAAI,CAAC,EACxFT,GAAQS,EAAc,UAAW,KAAK,OAAO,EAC7CT,GAAQU,EAAgB,UAAW,KAAK,OAAO,EAC/C,QAAWO,KAAK,KAAK,QAAS,KAAK,QAAQA,GAAK,KAAK,GAAG,mBAAmB,KAAK,GAAIA,CAAC,EACvF,CAgBF,EAWO,SAASC,IAAgB,CAC9B,IAAIC,EAAY,EACZC,EAAqC,KACrCC,EAAc,GACdC,EAA0B,GAC1BC,EAAoG,CAAC,KAAM,IAAI,EAC/GC,EAAyC,CAAC,EAC1CC,EAAmC,KACnCC,EAAmC,KACjCC,EAAWC,GAAO,IAAK,GAAG,EAC1BC,EAAqB,CAAE,EACvBC,EAAO,CAAE,aAAc,CAAE,EACzBtB,EAAKmB,EAAS,WAAW,OAAO,EACtC,GAAI,CAACnB,EAAI,CACPM,EAAI,kCAAkC,EACtC,MACF,CAEA,KAAK,GAAKN,EAEV,SAASuB,EAAOC,EAAOC,EAAQ,CAC7B,GAAI,EAAAD,IAAUL,EAAS,OAASM,IAAWN,EAAS,QAGpD,IAFAA,EAAS,MAAQK,EACjBL,EAAS,OAASM,EACd,CAACR,EAAc,CACjB,IAAMS,EAAW,IAAI,aAAa,CAAC,GAAI,GAAI,EAAG,EAAG,EAAG,GAAI,EAAG,EAAG,GAAI,EAAG,EAAG,EAAG,GAAI,EAAG,EAAG,EAAG,EAAG,GAAI,EAAG,EAAG,EAAG,EAAG,EAAG,CAAC,CAAC,EAChHT,EAAejB,EAAG,aAAa,EAC/BA,EAAG,WAAWA,EAAG,aAAciB,CAAY,EAC3CjB,EAAG,WAAWA,EAAG,aAAc0B,EAAU1B,EAAG,WAAW,EACvDA,EAAG,YAAYA,EAAG,+BAAgC,EAAI,CACxD,CACAA,EAAG,SAAS,EAAG,EAAGmB,EAAS,MAAOA,EAAS,MAAM,EACjDJ,EAAmB,CAAC,KAAM,IAAI,EAChC,CAEA,SAASY,EAAyBH,EAAOC,EAAQ,CAC/C,IAAMG,EAAM5B,EAAG,kBAAkB,EACjCA,EAAG,gBAAgBA,EAAG,YAAa4B,CAAG,EACtC,IAAMC,EAAe7B,EAAG,mBAAmB,EAC3CA,EAAG,iBAAiBA,EAAG,aAAc6B,CAAY,EACjD,IAAMC,EAAU9B,EAAG,cAAc,EACjC,OAAAA,EAAG,YAAYA,EAAG,WAAY8B,CAAO,EACrC9B,EAAG,WAAWA,EAAG,WAAY,EAAGA,EAAG,KAAMwB,EAAOC,EAAQ,EAAGzB,EAAG,KAAMA,EAAG,cAAe,IAAI,EAC1FA,EAAG,cAAcA,EAAG,WAAYA,EAAG,mBAAoBA,EAAG,MAAM,EAChEA,EAAG,cAAcA,EAAG,WAAYA,EAAG,mBAAoBA,EAAG,MAAM,EAChEA,EAAG,cAAcA,EAAG,WAAYA,EAAG,eAAgBA,EAAG,aAAa,EACnEA,EAAG,cAAcA,EAAG,WAAYA,EAAG,eAAgBA,EAAG,aAAa,EACnEA,EAAG,qBAAqBA,EAAG,YAAaA,EAAG,kBAAmBA,EAAG,WAAY8B,EAAS,CAAC,EACvF9B,EAAG,YAAYA,EAAG,WAAY,IAAI,EAClCA,EAAG,gBAAgBA,EAAG,YAAa,IAAI,EAChC,CAAE,IAAA4B,EAAK,QAAAE,CAAQ,CACxB,CAEA,SAASC,EAAmBC,EAAuE,CACjG,OAAAjB,EAAiBiB,GAASjB,EAAiBiB,IAAUL,EAAyBR,EAAS,MAAOA,EAAS,MAAM,EACtGJ,EAAiBiB,EAC1B,CAEA,SAASC,EAAKC,EAAQ,EAAG,CACvB,GAAI,CAAChB,EAAgB,OACrB,IAAIzB,EAA8B,KAC9B0C,EAAkC,KAClCC,EAAQ,GACRzB,IAAc,EAAGlB,EAASmB,EACzBnB,EAASsC,EAAmBjB,CAAuB,EAAE,SAAW,KACrEH,IACIE,GAAe,EAAEqB,EAAQZ,EAAK,eAChCa,EAAS,KACTC,EAAQzB,EAAY,IAAM,IAE1BG,GAA2BA,EAA0B,GAAK,EAC1DqB,EAASJ,EAAmBjB,CAAuB,EAAE,KAAO,MAE9Dd,EAAG,YAAYA,EAAG,WAAYP,CAAM,EACpCO,EAAG,gBAAgBA,EAAG,YAAamC,CAAM,EACzCnC,EAAG,UAAUkB,EAAe,QAAQ,MAAWkB,EAAQ,GAAK,CAAE,EAC9DpC,EAAG,WAAWA,EAAG,UAAW,EAAG,CAAC,CAClC,CAEA,SAASqC,EAAcnC,EAAkC,CACvD,GAAImB,EAAmBnB,GACrB,OAAAgB,EAAiBG,EAAmBnB,GACpCF,EAAG,YAAYkB,EAAiBA,EAAe,GAAK,OAAS,IAAI,EAC1DA,EAGT,GADAA,EAAiB,IAAInB,GAAUC,EAAYsC,GAAgBpC,CAAc,EACrE,CAACgB,EACH,OAAAZ,EAAI,qCAAqC,EAClC,KAET,IAAMiC,EAAY,aAAa,kBACzBC,EAAW,EAAID,EACrB,OAAAvC,EAAG,wBAAwBkB,EAAe,UAAU,GAAM,EAC1DlB,EAAG,oBAAoBkB,EAAe,UAAU,IAAQ,EAAGlB,EAAG,MAAO,GAAOwC,EAAU,EAAID,CAAS,EACnGvC,EAAG,wBAAwBkB,EAAe,UAAU,EAAK,EACzDlB,EAAG,oBAAoBkB,EAAe,UAAU,GAAO,EAAGlB,EAAG,MAAO,GAAOwC,EAAU,EAAID,CAAS,EAClGlB,EAAmBnB,GAAkBgB,EAC9BA,CACT,CAEA,IAAMuB,EAAS,CACb,YAAcC,GAAW,CACvB,IAAMC,EAAI,IAAI,aAAaD,CAAM,EACjCC,EAAE,IAAM,IACRA,EAAE,IAAM,IACRA,EAAE,KAAO,IACTA,EAAE,KAAO,IACT,IAAMtC,EAAUsC,EAAE,MAAQ,GAAKA,EAAE,KAAO,GAAKA,EAAE,KAAO,GAAKA,EAAE,MAAQ,GAAKA,EAAE,MAAQ,GAAKA,EAAE,MAAQ,GAAKA,EAAE,MAAQ,GAAKA,EAAE,MAAQ,EACrHC,GACAC,GACNC,EAAUT,EAAchC,CAAM,EAChC,CAACyC,IACL9C,EAAG,WAAW8C,EAAQ,QAAQ,EAAMH,CAAC,EACrCV,EAAK,EACP,EAEA,WAAac,GAAe,CAC1B,IAAMC,GAAKD,GAAc,GAAK,EAC9BN,EAAO,YAAY,CACjBO,EAAG,EAAG,EAAG,EAAG,EACZ,EAAGA,EAAG,EAAG,EAAG,EACZ,EAAG,EAAGA,EAAG,EAAG,EACZ,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,WAAaC,GAAW,CACtB,IAAMC,GAAKD,GAAU,GAAK,EAAI,EAAI,EAC5BE,GAAMD,EAAI,GAAK,IACrBT,EAAO,YAAY,CACjBS,EAAGC,EAAGA,EAAG,EAAG,EACZA,EAAGD,EAAGC,EAAG,EAAG,EACZA,EAAGA,EAAGD,EAAG,EAAG,EACZ,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,WAAY,IAAM,CAChBT,EAAO,WAAW,EAAE,CACtB,EAEA,SAAWQ,GAAW,CACpB,IAAMG,GAAKH,GAAU,GAAK,EACpBI,EAAI,MAAQD,EAAI,GACtBX,EAAO,YAAY,CACjBW,EAAG,EAAG,EAAG,EAAGC,EACZ,EAAGD,EAAG,EAAG,EAAGC,EACZ,EAAG,EAAGD,EAAG,EAAGC,EACZ,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,SAAU,IAAM,CACdZ,EAAO,SAAS,EAAE,CACpB,EAEA,IAAMa,GAAa,CACjBA,GAAYA,GAAY,GAAK,IAAM,KAAK,GACxC,IAAMC,EAAM,KAAK,IAAID,CAAQ,EACvBE,EAAM,KAAK,IAAIF,CAAQ,EACvBG,EAAO,KACPC,EAAO,KACPC,EAAO,KACblB,EAAO,YAAY,CACjBgB,EAAOF,GAAO,EAAIE,GAAQD,EAAO,CAACC,EAAOC,EAAOH,EAAO,CAACG,EAAQF,EAAO,CAACE,EAAOC,EAAOJ,EAAO,CAACI,EAAQH,GAAO,EAAIG,GAAO,EAAG,EAC3HF,EAAOF,EAAO,CAACE,EAAQD,EAAO,KAAQE,EAAOH,GAAO,EAAIG,GAAQF,EAAO,IAAQG,EAAOJ,EAAO,CAACI,EAAQH,EAAO,MAAS,EAAG,EACzHC,EAAOF,EAAO,CAACE,EAAQD,EAAO,EAAE,EAAIC,GAAQC,EAAOH,EAAO,CAACG,EAAQF,EAAOE,EAAOC,EAAOJ,GAAO,EAAII,GAAQH,EAAOG,EAAO,EAAG,EAC5H,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,oBAAqB,IAAM,CACzBlB,EAAO,YAAY,CACjB,SAAW,QAAW,SAAW,EAAG,MACpC,SAAW,QAAW,SAAW,EAAG,MACpC,SAAW,QAAW,SAAW,EAAG,MACpC,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,MAAO,IAAM,CACXA,EAAO,YAAY,CACjB,KAAO,SAAW,UAAY,EAAG,EACjC,KAAO,SAAW,UAAY,EAAG,EACjC,KAAO,SAAW,UAAY,EAAG,EACjC,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,QAAS,IAAM,CACbA,EAAO,YAAY,CACjB,kBAAoB,mBAAqB,mBAAqB,EAAG,kBACjE,qBAAuB,kBAAoB,mBAAqB,EAAG,mBACnE,mBAAqB,oBAAsB,mBAAqB,EAAG,mBACnE,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,eAAgB,IAAM,CACpBA,EAAO,YAAY,CACjB,kBAAoB,kBAAoB,oBAAsB,EAAG,kBACjE,mBAAqB,kBAAoB,mBAAqB,EAAG,kBACjE,kBAAoB,mBAAqB,kBAAoB,EAAG,kBAChE,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,WAAY,IAAM,CAChBA,EAAO,YAAY,CACjB,mBAAoB,mBAAqB,oBAAsB,EAAG,kBAClE,oBAAsB,mBAAoB,oBAAsB,EAAG,mBACnE,oBAAsB,mBAAqB,mBAAoB,EAAG,kBAClE,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,YAAa,IAAM,CACjBA,EAAO,YAAY,CACjB,mBAAoB,mBAAqB,oBAAsB,EAAG,mBAClE,mBAAqB,mBAAoB,oBAAsB,EAAG,mBAClE,kBAAoB,mBAAqB,kBAAmB,EAAG,mBAC/D,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,SAAU,IAAM,CACdA,EAAO,YAAY,CACjB,MAAO,MAAQ,MAAQ,EAAG,EAC1B,MAAQ,MAAO,MAAQ,EAAG,EAC1B,MAAQ,MAAQ,MAAO,EAAG,EAC1B,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,WAAY,IAAM,CAChBA,EAAO,YAAY,CACjB,EAAG,EAAG,EAAG,EAAG,EACZ,EAAG,EAAG,EAAG,EAAG,EACZ,EAAG,EAAG,EAAG,EAAG,EACZ,EAAG,EAAG,EAAG,EAAG,CACd,CAAC,CACH,EAEA,YAAcC,GAAW,CACvB,IAAMC,EAAI,IAAI,aAAaD,CAAM,EAC3BkB,EAAa,EAAIzC,EAAS,MAC1B0C,EAAa,EAAI1C,EAAS,OAC1B2B,EAAUT,EAAsByB,EAAW,EAC7C,CAAChB,IACL9C,EAAG,WAAW8C,EAAQ,QAAQ,EAAMH,CAAC,EACrC3C,EAAG,UAAU8C,EAAQ,QAAQ,GAAOc,EAAYC,CAAU,EAC1D5B,EAAK,EACP,EAEA,YAAa,IAAM,CAEjBQ,EAAO,YAAY,KAAK,KAAM,CAC5B,EAAG,EAAG,EACN,EAAG,GAAI,EACP,EAAG,EAAG,CACR,CAAC,CACH,EAEA,OAAQ,IAAM,CAEZA,EAAO,YAAY,KAAK,KAAM,CAC5B,GAAI,EAAG,EACP,GAAI,EAAG,EACP,GAAI,EAAG,CACT,CAAC,CACH,EAEA,OAAQ,IAAM,CAEZA,EAAO,YAAY,KAAK,KAAM,CAC5B,GAAI,GAAI,GACR,EAAG,EAAG,EACN,EAAG,EAAG,CACR,CAAC,CACH,EAEA,QAAUQ,GAAW,CACnB,IAAMc,EAAId,GAAU,EAEpBR,EAAO,YAAY,KAAK,KAAM,CAC5B,EAAG,GAAKsB,EAAG,EACX,GAAKA,EAAG,EAAI,EAAIA,EAAG,GAAKA,EACxB,EAAG,GAAKA,EAAG,CACb,CAAC,CACH,EAEA,OAASC,GAAS,CAChB,IAAMC,EAAID,GAAQ,EAElBvB,EAAO,YAAY,KAAK,KAAM,CAC5B,GAAKwB,EAAG,GAAKA,EAAG,EAChB,GAAKA,EAAG,EAAG,EAAIA,EACf,EAAG,EAAIA,EAAG,EAAIA,CAChB,CAAC,CACH,EAEA,KAAOD,GAAS,CACd,IAAME,EAAaF,EAAO,EAAK7C,EAAS,MAClCgD,EAAaH,EAAO,EAAK7C,EAAS,OAClC2B,EAAUT,EAAsB+B,EAAI,EACtC,CAACtB,IAEL9C,EAAG,UAAU8C,EAAQ,QAAQ,GAAO,EAAGqB,CAAS,EAChDlC,EAAKX,EAAK,YAAY,EAEtBtB,EAAG,UAAU8C,EAAQ,QAAQ,GAAOoB,EAAW,CAAC,EAChDjC,EAAK,EACP,EAEA,SAAW+B,GAAS,CAClB,IAAME,EAAaF,EAAQ7C,EAAS,MAC9BgD,EAAaH,EAAQ7C,EAAS,OAC9B2B,EAAUT,EAAsBgC,EAAQ,EAC1C,CAACvB,IACL9C,EAAG,UAAU8C,EAAQ,QAAQ,KAASoB,EAAWC,CAAS,EAC1DlC,EAAK,EACP,CACF,EAGA,KAAK,IAAM,SAAUnC,EAAM,CAEzB,IAAMwE,EAAO,MAAM,UAAU,MAAM,KAAK,UAAW,CAAC,EAC9CC,EAAO9B,EAAO3C,GACpBkB,EAAY,KAAK,CAAE,KAAAuD,EAAM,KAAAD,CAAK,CAAC,CACjC,EAGA,KAAK,MAAQ,UAAY,CACvBtD,EAAc,CAAC,CACjB,EAGA,KAAK,IAAM,UAAY,CACrB,OAAOA,CACT,EAGA,KAAK,MAAQ,SAAUwD,EAAO,CAC5BjD,EAAOiD,EAAM,MAAOA,EAAM,MAAM,EAChC7D,EAAY,EACPC,IAAeA,EAAgBZ,EAAG,cAAc,GACrDA,EAAG,YAAYA,EAAG,WAAYY,CAAa,EAC3CZ,EAAG,cAAcA,EAAG,WAAYA,EAAG,eAAgBA,EAAG,aAAa,EACnEA,EAAG,cAAcA,EAAG,WAAYA,EAAG,eAAgBA,EAAG,aAAa,EACnEA,EAAG,cAAcA,EAAG,WAAYA,EAAG,mBAAoBA,EAAG,OAAO,EACjEA,EAAG,cAAcA,EAAG,WAAYA,EAAG,mBAAoBA,EAAG,OAAO,EACjEA,EAAG,WAAWA,EAAG,WAAY,EAAGA,EAAG,KAAMA,EAAG,KAAMA,EAAG,cAAewE,CAAK,EACzE,QAASC,EAAI,EAAGA,EAAIzD,EAAY,OAAQyD,IAAK,CAC3C5D,EAAe4D,IAAMzD,EAAY,OAAS,EAC1C,IAAM0D,EAAI1D,EAAYyD,GAEtBC,EAAE,KAAK,MAAM,KAAMA,EAAE,MAAQ,CAAC,CAAC,CACjC,CACA,OAAOvD,CACT,EAGA,KAAK,KAAO,SAAUqD,EAAO,CAC3B,YAAK,IAAI,aAAc,CAAC,EACjB,KAAK,MAAMA,CAAK,CACzB,CACF,CCjbA,eAAsBG,GAAsBC,EAAqC,CAE/E,IAAMC,EAAUD,EAAW,MAAM,SAAW,EAAO,UAAQA,CAAU,EAAIA,EACnEE,EAAc,QAAMD,EAAS,EAAG,CAAC,EACjCE,EAAgB,CAAI,MAAID,EAAS,EAAE,EAAM,MAAIA,EAAS,EAAE,EAAM,MAAIA,EAAS,EAAE,CAAC,EAC9EE,EAAgB,CAAI,MAAIF,EAAS,EAAE,EAAM,MAAIA,EAAS,EAAE,EAAM,MAAIA,EAAS,EAAE,CAAC,EAC9EG,EAAS,MAAM,QAAQ,IAAID,EAAI,IAAKE,GAAYA,EAAQ,KAAK,CAAC,CAAC,EAC/DC,EAAW,IAAO,KAAK,IAAIF,EAAO,GAAG,GAAIA,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,EACnEG,EAAM,CAAI,MAAIN,EAAS,GAAIC,EAAI,EAAE,EAAM,MAAID,EAAS,GAAIC,EAAI,EAAE,EAAM,MAAID,EAAS,GAAIC,EAAI,EAAE,CAAC,EAC5FM,EAAQ,CAAI,MAAIL,EAAI,GAAID,EAAI,EAAE,EAAM,MAAIC,EAAI,GAAID,EAAI,EAAE,EAAM,MAAIC,EAAI,GAAID,EAAI,EAAE,CAAC,EAC/EO,EAAO,CAAI,MAAIH,EAAUE,EAAM,EAAE,EAAM,MAAIF,EAAUE,EAAM,EAAE,EAAM,MAAIF,EAAUE,EAAM,EAAE,CAAC,EAC1FE,EAAM,CAAI,MAAIH,EAAI,GAAIE,EAAK,EAAE,EAAM,MAAIF,EAAI,GAAIE,EAAK,EAAE,EAAM,MAAIF,EAAI,GAAIE,EAAK,EAAE,CAAC,EAChFE,EAAS,QAAM,CAACD,EAAI,GAAIA,EAAI,GAAIA,EAAI,EAAE,EAAG,CAAC,EAC1CE,EAAa,UAAQD,EAAK,CAAC,EAAGX,EAAQ,MAAM,GAAIA,EAAQ,MAAM,GAAI,CAAC,CAAC,EAC1E,OAAG,UAAQ,CAAC,GAAGC,EAAU,GAAGC,EAAK,GAAGC,EAAK,GAAGI,EAAK,GAAGC,EAAO,GAAGC,EAAM,GAAGC,EAAKC,EAAKX,CAAO,CAAC,EAClFY,CACT,CCZA,IAAMC,GAAU,KAEZC,EAA6B,KAC7BC,EAA8B,KAC9BC,GAA8B,KAE9BC,EAEEC,GAAoG,CACxG,SAAU,EACV,UAAW,EACX,UAAW,EACX,YAAa,MACf,EAEO,SAASC,GAAOC,EAAeC,EAA2B,CAC/D,IAAIC,EACJ,GAAIC,EAAI,QACN,GAAIA,EAAI,OAAQ,CACd,GAAI,OAAO,iBAAoB,YAAa,MAAM,IAAI,MAAM,mFAAmF,EAC/ID,EAAI,IAAI,gBAAgBF,EAAOC,CAAM,CACvC,KAAO,CACL,GAAI,OAAO,UAAa,YAAa,MAAM,IAAI,MAAM,kEAAkE,EACvHC,EAAI,SAAS,cAAc,QAAQ,EACnCA,EAAE,MAAQF,EACVE,EAAE,OAASD,CACb,MAGI,OAAOE,EAAI,QAAW,YAAaD,EAAI,IAAIC,EAAI,OAAOH,EAAOC,CAAM,EAC9D,OAAO,WAAW,QAAW,cAAaC,EAAI,IAAI,WAAW,OAAOF,EAAOC,CAAM,GAG5F,OAAOC,CACT,CAGO,SAASE,GAAKC,EAAkBC,EAAoB,CACzD,IAAMC,EAAeD,GAAUP,GAAOM,EAAM,MAAOA,EAAM,MAAM,EAE/D,OADYE,EAAa,WAAW,IAAI,EACpC,UAAUF,EAAO,EAAG,CAAC,EAClBE,CACT,CAKA,eAAsBC,GAAQH,EAAcI,EAAgBC,EAAqB,GAAoE,CACnJ,GAAI,CAACL,EAEH,OAAII,EAAO,OAAOE,EAAI,+BAA+B,EAC9C,CAAE,OAAQ,KAAM,OAAQ,IAAK,EAGtC,GACE,EAAEN,aAAoBO,KACnB,EAAE,OAAO,OAAU,aAAeP,aAAiB,QACnD,EAAE,OAAOF,EAAI,QAAW,aAAeE,aAAiBF,EAAI,SAC5D,EAAE,OAAO,WAAW,QAAW,aAAeE,aAAiB,WAAW,SAC1E,EAAE,OAAO,WAAc,aAAeA,aAAiB,YACvD,EAAE,OAAO,aAAgB,aAAeA,aAAiB,cACzD,EAAE,OAAO,kBAAqB,aAAeA,aAAiB,mBAC9D,EAAE,OAAO,kBAAqB,aAAeA,aAAiB,mBAC9D,EAAE,OAAO,kBAAqB,aAAeA,aAAiB,mBAC9D,EAAE,OAAO,mBAAsB,aAAeA,aAAiB,oBAC/D,EAAE,OAAO,iBAAoB,aAAeA,aAAiB,iBAEhE,MAAM,IAAI,MAAM,qCAAqC,EAEvD,GAAIA,aAAoBO,GAAQ,CAC9B,IAAIC,EAAwB,KAC5B,GAAKR,EAAiB,mBAAuB,MAAM,IAAI,MAAM,yDAAyD,EACtH,GAAI,CAAEA,EAAiB,MAAU,MAAM,IAAI,MAAM,sDAAsD,EACvG,GAAKA,EAAiB,MAAM,SAAW,GACrC,GAAKA,EAAiB,MAAM,KAAO,EACjCQ,EAAY,aAAWR,EAAO,CAAC,UACrBA,EAAiB,MAAM,KAAO,EAAG,CAC3C,IAAMS,EAAS,UAAQT,EAAO,CAAC,EAAG,EAAG,CAAC,EAAG,CAAC,GAAI,GAAI,CAAC,CAAC,EACpDQ,EAAY,aAAWC,EAAK,CAAC,EAC1B,UAAQA,CAAG,CAChB,OACUT,EAAiB,MAAM,SAAW,IACvCA,EAAiB,MAAM,KAAO,EACjCQ,EAAY,QAAMR,CAAK,EACbA,EAAiB,MAAM,KAAO,IACxCQ,EAAY,UAAQR,EAAO,CAAC,EAAG,EAAG,EAAG,CAAC,EAAG,CAAC,GAAI,GAAI,GAAI,CAAC,CAAC,IAI5D,GAAIQ,GAAU,MAAQA,EAAO,MAAM,SAAW,GAAKA,EAAO,MAAM,KAAO,GAAKA,EAAO,MAAM,KAAO,EAAG,MAAM,IAAI,MAAM,iEAAiER,EAAM,OAAU,EACpM,GAAKQ,EAAkB,QAAU,QAAS,CACxC,IAAME,EAAU,OAAKF,EAAQ,SAAS,EACnC,UAAQA,CAAM,EACjBA,EAASE,CACX,CACA,MAAO,CAAE,OAAAF,EAAQ,OAASJ,EAAO,OAAO,OAASd,EAAY,IAAM,CACrE,KAAO,CAEL,GAAI,OAAOU,EAAM,YAAkB,aAAeA,EAAM,YAAiB,EACvE,OAAII,EAAO,OAAOE,EAAI,2BAA2B,EAC1C,CAAE,OAAQ,KAAM,OAAQjB,CAAS,EAE1C,IAAMsB,EAAgBX,EAAM,cAAmBA,EAAM,YAAiBA,EAAM,OAAaA,EAAM,OAAaA,EAAM,MAAS,GAAK,EAC1HY,EAAiBZ,EAAM,eAAoBA,EAAM,aAAkBA,EAAM,QAAcA,EAAM,OAAaA,EAAM,MAAS,GAAK,EACpI,GAAI,CAACW,GAAiB,CAACC,EACrB,OAAIR,EAAO,OAAOE,EAAI,mCAAmC,EAClD,CAAE,OAAQ,KAAM,OAAQjB,CAAS,EAE1C,IAAIwB,EAAcF,EACdG,EAAeF,EAenB,GAdIC,EAAczB,KAChByB,EAAczB,GACd0B,EAAe,KAAK,MAAMD,EAAcD,EAAiBD,CAAa,GAEpEG,EAAe1B,KACjB0B,EAAe1B,GACfyB,EAAc,KAAK,MAAMC,EAAeH,EAAgBC,CAAc,IAInER,EAAO,OAAO,OAAS,GAAK,EAAGS,EAAcT,EAAO,OAAO,OACtDA,EAAO,OAAO,QAAU,GAAK,IAAGS,EAAcF,IAAkBP,EAAO,OAAO,QAAU,GAAKQ,KAClGR,EAAO,OAAO,QAAU,GAAK,EAAGU,EAAeV,EAAO,OAAO,QACxDA,EAAO,OAAO,OAAS,GAAK,IAAGU,EAAeF,IAAmBR,EAAO,OAAO,OAAS,GAAKO,IACnG,CAACE,GAAe,CAACC,EAAc,MAAM,IAAI,MAAM,yCAAyC,GACxF,CAACzB,IAAaA,GAAA,YAAAA,EAAU,SAAUwB,IAAiBxB,GAAA,YAAAA,EAAU,UAAWyB,KAAezB,EAAWK,GAAOmB,EAAaC,CAAY,GAGtI,IAAMC,EAAQ1B,EAAS,WAAW,IAAI,EAmDtC,GAlDK,OAAO,WAAc,aAAiBW,aAAiB,UAC1De,EAAM,aAAaf,EAAO,EAAG,CAAC,EAE1BI,EAAO,OAAO,MAAQ,OAAOW,EAAM,WAAc,aACnDA,EAAM,UAAUJ,EAAe,CAAC,EAChCI,EAAM,MAAM,GAAI,CAAC,EACjBA,EAAM,UAAUf,EAAoB,EAAG,EAAGW,EAAeC,EAAgB,EAAG,EAAGvB,GAAA,YAAAA,EAAU,MAAOA,GAAA,YAAAA,EAAU,MAAM,EAChH0B,EAAM,aAAa,EAAG,EAAG,EAAG,EAAG,EAAG,CAAC,GAEnCA,EAAM,UAAUf,EAAoB,EAAG,EAAGW,EAAeC,EAAgB,EAAG,EAAGvB,GAAA,YAAAA,EAAU,MAAOA,GAAA,YAAAA,EAAU,MAAM,GAIhH,CAACC,GAAcD,EAAS,QAAUC,EAAU,QAAWD,GAAA,YAAAA,EAAU,WAAWC,GAAA,YAAAA,EAAW,WAASA,EAAYI,GAAOL,EAAS,MAAOA,EAAS,MAAM,GAGlJe,EAAO,OAAO,SAAWN,EAAI,MAAM,WAChCN,IAAIA,EAAKM,EAAI,QAAU,IAAYkB,GAAkB,MAC1DlB,EAAI,OAAS,CAAC,CAACN,EACX,CAACA,GAAM,CAACA,EAAG,KACTY,EAAO,OAAOE,EAAI,gDAAgD,EACtER,EAAI,MAAM,UAAY,GACtBM,EAAO,OAAO,QAAU,GACxBL,GAAKV,EAAUC,CAAS,IAGxBE,EAAG,MAAM,EACLY,EAAO,OAAO,aAAe,GAAGZ,EAAG,IAAI,aAAcY,EAAO,OAAO,UAAU,EAC7EA,EAAO,OAAO,WAAa,GAAGZ,EAAG,IAAI,WAAYY,EAAO,OAAO,QAAQ,EACvEA,EAAO,OAAO,YAAc,GAAGZ,EAAG,IAAI,UAAWY,EAAO,OAAO,SAAS,EACxEA,EAAO,OAAO,OAAS,GAAGZ,EAAG,IAAI,OAAQY,EAAO,OAAO,IAAI,EAC3DA,EAAO,OAAO,aAAe,GAAGZ,EAAG,IAAI,aAAcY,EAAO,OAAO,UAAU,EAC7EA,EAAO,OAAO,MAAQ,GAAGZ,EAAG,IAAI,MAAOY,EAAO,OAAO,GAAG,EACxDA,EAAO,OAAO,UAAUZ,EAAG,IAAI,UAAU,EACzCY,EAAO,OAAO,OAAOZ,EAAG,IAAI,OAAO,EACnCY,EAAO,OAAO,SAASZ,EAAG,IAAI,SAAS,EACvCY,EAAO,OAAO,OAAOZ,EAAG,IAAI,OAAO,EACnCY,EAAO,OAAO,YAAYZ,EAAG,IAAI,YAAY,EAC7CY,EAAO,OAAO,aAAaZ,EAAG,IAAI,aAAa,EAC/CY,EAAO,OAAO,UAAUZ,EAAG,IAAI,UAAU,EACzCY,EAAO,OAAO,WAAa,GAAGZ,EAAG,IAAI,WAAYY,EAAO,OAAO,QAAQ,EACvEZ,EAAG,IAAI,EAAI,EAAGF,EAAYE,EAAG,MAAMH,CAAQ,EAC1CC,EAAYE,EAAG,KAAKH,CAAQ,KAGnCU,GAAKV,EAAUC,CAAS,EACpBE,IAAIA,EAAK,MACbM,EAAI,OAAS,CAAC,CAACN,GAGb,CAACa,EAAW,MAAO,CAAE,OAAQ,KAAM,OAAQf,CAAU,EACzD,GAAI,CAACA,EAAW,MAAM,IAAI,MAAM,oCAAoC,EAGpE,IAAI2B,EACAC,EAAQ,EACZ,GAAK,OAAO,WAAc,aAAelB,aAAiB,WAAeA,EAAM,MAAWA,EAAM,OAAYA,EAAM,OAChH,GAAIF,EAAI,SAAc,UACpBmB,EAAY,UAAa,UAAQ,WAAWjB,CAAK,EAAI,SAChD,CACLkB,EAAQlB,EAAM,KAAQ,OAASA,EAAM,OAAYA,EAAM,MAEvD,IAAMmB,EAAM,IAAI,WAAWnB,EAAM,KAAQ,MAAS,EAClDiB,EAAY,SAAOE,EAAK,CAACnB,EAAM,OAAWA,EAAM,MAAUkB,CAAK,EAAG,OAAO,CAC3E,UAEI,CAAC3B,IAAcD,EAAU,QAAUC,GAAU,OAAWD,EAAU,SAAWC,GAAU,UAASA,GAAYG,GAAOJ,EAAU,MAAOA,EAAU,MAAM,GACjJ,WAAWQ,EAAI,QAChBM,EAAO,UAAY,SAAWA,EAAO,UAAY,WAAaA,EAAO,UAAY,SACnFa,EAAY,UAAQ,WAAW3B,CAAS,GAExCC,GAAYQ,GAAKT,CAAS,EAC1B2B,EAAY,UAAQ,WAAW1B,EAAS,OAErC,CAGL,IAAM6B,EAFarB,GAAKT,CAAS,EACN,WAAW,IAAI,EACjB,aAAa,EAAG,EAAGuB,EAAaC,CAAY,EACrEI,EAAQE,EAAS,KAAK,OAASP,EAAcC,EAC7C,IAAMK,EAAM,IAAI,WAAWC,EAAS,KAAK,MAAM,EAC/CH,EAAY,SAAOE,EAAK,CAACN,EAAaC,EAAcI,CAAK,CAAC,CAC5D,CAEF,GAAIA,IAAU,EAAG,CACf,IAAMT,EAAS,UAAQQ,EAAQ,CAAC,EAAG,EAAG,CAAC,EAAG,CAAC,GAAI,GAAI,CAAC,CAAC,EAClD,UAAQA,CAAM,EACjBA,EAASR,CACX,CACA,GAAI,CAACQ,EAAQ,MAAM,IAAI,MAAM,mCAAmC,EAChE,IAAMI,EAAY,OAAKJ,EAAQ,SAAS,EAClCT,EAASJ,EAAO,OAAO,aAAe,MAAckB,GAAsBD,CAAM,EAAO,aAAWA,EAAQ,CAAC,EACjH,OAAG,UAAQ,CAACJ,EAAQI,CAAM,CAAC,EACpB,CAAE,OAAAb,EAAQ,OAASJ,EAAO,OAAO,OAASd,EAAY,IAAM,CACrE,CACF,CAgCA,eAAsBiC,GAAKnB,EAAyBJ,EAAe,CACjE,IAAIwB,EAAY,GAChB,GAAIpB,EAAO,mBAAqB,GAAK,CAACJ,EAAM,OAASA,EAAM,MAAM,SAAW,GAAKA,EAAM,MAAM,GAAK,MAAQA,EAAM,MAAM,GAAK,KAAM,OAAOwB,EAcxI,GAAI,CAAC/B,GAAK,YACRA,GAAK,YAAiB,QAAMO,CAAK,UACxBP,GAAK,YAAY,MAAM,KAAOO,EAAM,MAAM,IAAMP,GAAK,YAAY,MAAM,KAAOO,EAAM,MAAM,GAChG,UAAQP,GAAK,WAAW,EAC3BA,GAAK,YAAiB,QAAMO,CAAK,MAC5B,CACL,IAAMyB,EAA4B,CAAC,EACnCA,EAAE,KAAU,MAAIzB,EAAOP,GAAK,WAAW,EACvCgC,EAAE,QAAa,MAAIA,EAAE,KAAMA,EAAE,IAAI,EACjCA,EAAE,IAAS,MAAIA,EAAE,OAAO,EAExB,IAAMC,GADU,MAAMD,EAAE,IAAI,KAAK,GACJ,IAAMzB,EAAM,MAAM,IAAM,IAAMA,EAAM,MAAM,IAAM,GAAK,IAAM,EACrF,UAAQ,CAACP,GAAK,YAAagC,EAAE,KAAMA,EAAE,QAASA,EAAE,GAAG,CAAC,EACvDhC,GAAK,YAAiB,QAAMO,CAAK,EACjCwB,EAAYE,IAAiBtB,EAAO,kBAAoB,EAC1D,CACA,OAAOoB,CACT,CAEA,eAAsBG,GAAQvB,EAAyBwB,EAAgBC,EAAiC,CACtG,IAAMJ,EAA4B,CAAC,EACnC,GAAI,CAACG,GAAU,CAACC,GAAUD,EAAO,MAAM,SAAW,GAAKA,EAAO,MAAM,SAAWC,EAAO,MAAM,OAC1F,OAAKzB,EAAO,OAAOE,EAAI,sDAAuDsB,EAAO,MAAOC,EAAO,KAAK,EACjG,EAET,GAAID,EAAO,MAAM,KAAO,GAAKC,EAAO,MAAM,KAAO,GAAKD,EAAO,MAAM,KAAO,GAAKC,EAAO,MAAM,KAAO,EACjG,OAAKzB,EAAO,OAAOE,EAAI,wDAAyDsB,EAAO,MAAOC,EAAO,KAAK,EACnG,EAETJ,EAAE,OAAY,QAAMG,CAAM,EAC1BH,EAAE,OAAUG,EAAO,MAAM,KAAOC,EAAO,MAAM,IAAMD,EAAO,MAAM,KAAOC,EAAO,MAAM,GAAS,QAAM,eAAeA,EAAQ,CAACD,EAAO,MAAM,GAAIA,EAAO,MAAM,EAAE,CAAC,EAAO,QAAMC,CAAM,EAC/KJ,EAAE,KAAU,MAAIA,EAAE,OAAQA,EAAE,MAAM,EAClCA,EAAE,QAAa,MAAIA,EAAE,KAAMA,EAAE,IAAI,EACjCA,EAAE,IAAS,MAAIA,EAAE,OAAO,EAExB,IAAMC,GADU,MAAMD,EAAE,IAAI,KAAK,GACJ,IAAMG,EAAO,MAAM,IAAM,IAAMA,EAAO,MAAM,IAAM,GAAK,IAAM,EAC1F,OAAG,UAAQ,CAACH,EAAE,OAAQA,EAAE,OAAQA,EAAE,KAAMA,EAAE,QAASA,EAAE,GAAG,CAAC,EAClDC,CACT,CC5TO,IAAMI,GAAN,KAAU,CA4Ef,aAAc,CA1EdC,EAAA,gBAEAA,EAAA,aAEAA,EAAA,eAEAA,EAAA,gBAAmB,IAEnBA,EAAA,aAAgB,IAEhBA,EAAA,gBAAqB,CAAC,GAEtBA,EAAA,gBAEAA,EAAA,eAEAA,EAAA,aAIAA,EAAA,kBAEAA,EAAA,eAAmB,IAEnBA,EAAA,YAKI,CACA,UAAW,OACX,QAAS,OACT,KAAM,OACN,YAAa,MACf,GAEFA,EAAA,aAKI,CACA,UAAW,OACX,QAAS,OACT,QAAS,OACT,SAAU,MACZ,GAEFA,EAAA,cAII,CACA,UAAW,OACX,QAAS,OACT,QAAS,MACX,GAEFA,EAAA,WAGI,CACA,MAAO,OACP,MAAO,CAAC,CACV,GAEFA,EAAA,eAAoB,CAAC,GAErBA,EAAA,eAEAA,EAAA,cAEAA,EAAA,kBAUE,GAPA,KAAK,QAAU,OAAO,WAAc,YACpC,KAAK,KAAQ,OAAO,SAAY,aAAiB,OAAO,QAAQ,UAAa,aAAiB,OAAO,QAAQ,SAAS,MAAS,YAC/H,KAAK,KAAO,CAAE,QAAYC,GAAQ,YAAa,EAC/C,KAAK,UAAY,OAAO,iBAAoB,YAC5C,KAAK,QAAU,GAEf,KAAK,OAAS,KAAK,SAAW,KAAK,UAAa,OAAO,mBAAsB,YAAe,OACxF,OAAO,WAAc,YAAa,CACpC,IAAMC,EAAM,UAAU,UAAU,MAAM,eAAe,EACrD,GAAIA,GAAOA,EAAI,GAAI,CACjB,IAAMC,EAAgBD,EAAI,GAAG,MAAM,eAAe,EAClD,KAAK,SAAYC,GAAiBA,EAAc,GAAMA,EAAc,GAAG,QAAQ,SAAU,EAAE,EAAI,GAC/F,KAAK,MAAQ,UAAU,UAAU,QAAQD,EAAI,GAAI,EAAE,EAC/C,KAAK,SAAS,KAAI,KAAK,MAAQ,KAAK,MAAM,QAAQA,EAAI,GAAI,EAAE,GAChE,KAAK,MAAQ,KAAK,MAAM,QAAQ,MAAO,GAAG,CAU5C,CACF,MAAW,OAAO,SAAY,cAC5B,KAAK,SAAW,GAAG,QAAQ,YAAY,QAAQ,OAC/C,KAAK,MAAQ,UAAU,QAAQ,UAEnC,CAGA,MAAM,eAAgB,CAEpB,KAAK,SAAW,OAAO,KAAQ,SAAO,EAAE,eAAe,EACvD,KAAK,KAAK,UAAY,OAAO,aAAgB,YAC7C,KAAK,KAAK,QAAU,KAAK,SAAS,SAAS,MAAM,EAC7C,KAAK,KAAK,WAAa,KAAK,KAAK,SAAc,aAAW,IAAM,SAClE,KAAK,KAAK,KAAO,MAAS,MAAI,EAAE,SAAS,uBAAuB,EAChE,KAAK,KAAK,YAAc,MAAS,MAAI,EAAE,SAAS,8BAA8B,GAEhF,IAAME,EAAUC,GAAO,IAAK,GAAG,EACzBC,EAAMF,EAAIA,EAAE,WAAW,QAAQ,EAAI,OAIzC,GAFA,KAAK,MAAM,UAAY,OAAOE,GAAQ,YACtC,KAAK,MAAM,QAAU,KAAK,SAAS,SAAS,OAAO,EAC/C,KAAK,MAAM,WAAa,KAAK,MAAM,UAAe,aAAW,IAAM,SAAc,aAAW,IAAM,WAAY,CAEhH,IAAMC,EAAQ,UAAQ,EAAE,QAAU,YAAc,MAAS,UAAQ,EAAE,gBAAgB,EAAE,GAAK,KACtFA,IACF,KAAK,MAAM,QAAUA,EAAG,aAAaA,EAAG,OAAO,EAC/C,KAAK,MAAM,SAAWA,EAAG,aAAaA,EAAG,QAAQ,EAErD,CAEA,KAAK,OAAO,UAAY,KAAK,SAAW,OAAO,UAAU,KAAW,YACpE,KAAK,OAAO,QAAU,KAAK,SAAS,SAAS,QAAQ,EACrD,GAAI,CAEE,KAAK,OAAO,YAAW,KAAK,OAAO,SAAW,MAAM,UAAU,IAAO,eAAe,GAAG,KAC7F,OAAQC,EAAN,CACA,KAAK,OAAO,UAAY,EAC1B,CACA,GAAI,CACF,KAAK,QAAa,uBAAwB,aAAW,CAAC,EAAE,IAAKC,GAAWA,EAAO,WAAW,YAAY,CAAC,CACzG,OAAQD,EAAN,CAAa,CACjB,CAGA,MAAM,WAAY,CAChB,IAAME,EAAM,CAAE,MAAO,GAAI,MAAO,CAAC,CAAE,EAC/B,KAAK,MAAQ,KAAK,SAAS,WAAW,OAAO,EAY5C,KAAK,IACL,KAAK,IAASA,EADD,OAAO,eAAe,KAAM,MAAO,CAAE,MAAOA,CAAI,CAAC,CAErE,CACF,EAEaC,EAAM,IAAIZ,mlECnKvB,IAAMa,GAAU,CACd,YAAa,GACb,eAAgB,GAChB,QAAS,GACT,MAAO,GACP,cAAe,EACjB,EAUaC,GAAwC,CAAC,EAEtD,eAAeC,GAAYC,EAAKC,EAAiC,CAC/D,OAAIJ,GAAQ,OAAOK,EAAI,oBAAqBF,EAAKC,CAAI,EAC9C,MAAMD,EAAKC,CAAI,CACxB,CAEO,SAASE,GAAoBC,EAAgB,CAClDP,GAAQ,YAAcO,EAAO,YAC7BP,GAAQ,QAAUO,EAAO,MACzBP,GAAQ,cAAgBO,EAAO,aACjC,CAEA,eAAsBC,EAAUC,EAAoD,CAnCpF,IAAAC,EAAAC,EAAAC,EAoCE,IAAIC,EAAWC,GAAKd,GAAQ,cAAeS,GAAa,EAAE,EACrDI,EAAS,YAAY,EAAE,SAAS,OAAO,IAAGA,GAAY,SAC3D,IAAME,EAAoBF,EAAS,SAAS,GAAG,EAAIA,EAAS,MAAM,GAAG,EAAIA,EAAS,MAAM,IAAI,EACtFG,EAAiBD,EAAkBA,EAAkB,OAAS,GAAG,QAAQ,QAAS,EAAE,EACpFE,EAAkB,eAAiBD,EACzCf,GAAWe,GAAkB,CAC3B,KAAMA,EACN,iBAAkB,EAClB,kBAAmB,EACnB,YAAaE,GAAWF,GACxB,QAAS,EACX,EACAhB,GAAQ,eAAkB,OAAO,QAAW,aAAiB,OAAO,OAAO,cAAiB,aAAiB,OAAO,OAAO,WAAc,YACzI,IAAImB,EAAe,CAAC,EACpB,GAAI,CACFA,EAAgBnB,GAAQ,gBAAkBA,GAAQ,YAAe,MAAS,KAAG,WAAW,EAAI,CAAC,CAC/F,OAAQoB,EAAN,CACApB,GAAQ,eAAiB,EAC3B,CACAC,GAAWe,GAAgB,QAAWhB,GAAQ,gBAAkBA,GAAQ,aAAgB,OAAO,KAAKmB,CAAY,EAAE,SAASF,CAAe,EAC1I,IAAMI,EAAgB,OAAO,OAAU,YAAc,CAAC,EAAI,CAAE,UAAW,CAAClB,EAAKC,IAAUF,GAAYC,EAAKC,CAAI,CAAE,EACxGkB,EAAoB,IAAOC,GAAWtB,GAAWe,GAAgB,QAAUC,EAAkBJ,EAAUQ,CAAa,EACtHG,EAAS,GACb,GAAI,CAEFF,EAAM,cAAc,EAChBtB,GAAQ,OAAOK,EAAI,sBAAuBiB,EAAM,OAAU,EAE9D,IAAMG,EAAY,MAAMH,EAAM,QAAQ,KAAK,EAC3CrB,GAAWe,GAAgB,mBAAmBN,EAAAe,GAAA,YAAAA,EAAW,aAAX,YAAAf,EAAuB,aAAc,EACnFY,EAAM,SAASG,CAAS,EAExBxB,GAAWe,GAAgB,oBAAoBJ,GAAAD,EAAAW,GAAA,YAAAA,EAAO,YAAP,YAAAX,EAAkB,aAAlB,YAAAC,EAA8B,aAAc,EACvFZ,GAAQ,SAASK,EAAI,cAAeiB,EAAM,SAAa,CAAE,MAAOrB,GAAWe,GAAgB,iBAAkB,EAAGhB,EAAO,EAC3HwB,EAAS,EACX,OAASE,EAAP,CACArB,EAAI,uBAAwBQ,EAAUa,CAAG,CAC3C,CACA,GAAIF,GAAUxB,GAAQ,aAAeA,GAAQ,gBAAkB,CAACC,GAAWe,GAAgB,QACzF,GAAI,CACF,IAAMW,EAAa,MAAML,EAAM,KAAKL,CAAe,EACnDZ,EAAI,eAAgBY,EAAiBU,CAAU,CACjD,OAASD,EAAP,CACArB,EAAI,sBAAuBQ,EAAUa,CAAG,CAC1C,CAEF,OAAOJ,CACT,gBCnFA,IAAAM,GAAA,GAAAC,GAAAD,GAAA,YAAAE,GAAA,kBAAAC,GAAA,SAAAC,GAAA,UAAAC,GAAA,aAAAC,KCeA,IAAIC,GACEC,GAAwB,CAAC,EACzBC,GAAY,CAAC,QAAS,QAAS,QAAS,SAAU,OAAO,EACzDC,GAAa,CAAC,GAAI,GAAI,GAAI,KAAM,KAAM,KAAM,EAAE,EAChDC,GAAY,EACZC,GAAW,EACXC,GAAU,OAAO,iBAGrB,eAAsBC,GAAKC,EAAgB,CAxB3C,IAAAC,EAyBE,OAAIC,EAAI,UAASV,GAAQ,MACpBA,GACIQ,EAAO,OAAOG,EAAI,gBAAiBX,GAAM,QAAW,EADjDA,GAAQ,MAAMY,GAAUH,EAAAD,EAAO,KAAK,OAAZ,YAAAC,EAAqB,SAAS,EAE3DT,EACT,CAGA,eAAsBa,GAAQC,EAAeN,EAAgBO,EAAaC,EAAkC,CAhC5G,IAAAP,EAAAQ,EAiCE,GAAI,CAACjB,GAAO,MAAO,CAAE,IAAK,EAAG,OAAQ,UAAW,YAAa,EAAG,KAAM,CAAC,CAAE,EACzE,IAAMkB,EAAYZ,MAAWG,EAAAD,EAAO,KAAK,OAAZ,YAAAC,EAAqB,aAAc,GAC1DU,KAAYF,EAAAT,EAAO,KAAK,OAAZ,YAAAS,EAAqB,WAAY,GAAMG,EAAI,EAAIf,GACjE,OAAIG,EAAO,aAAeW,GAAYD,GAAcd,KAAcY,GAAUf,GAAKc,IAC/ET,KACOL,GAAKc,KAEdT,GAAU,EACH,IAAI,QAAQ,MAAOe,GAAY,CAzCxC,IAAAZ,EAAAQ,EA0CI,GAAI,EAACjB,IAAA,MAAAA,GAAO,OAAO,GAAG,OAAO,OAC7B,IAAMsB,EAA4B,CAAC,EAE7BC,EAAM,CAAC,CAAC,EAAK,GAAM,GAAM,EAAI,CAAC,EACpCD,EAAE,OAAY,QAAM,cAAcR,EAAOS,EAAK,CAAC,CAAC,EAAG,CAACvB,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,CAAC,EACvG,IAAMwB,EAAgB,CAAE,IAAK,EAAG,OAAQ,UAAW,YAAa,EAAG,KAAM,CAAC,CAAE,GACxEf,EAAAD,EAAO,KAAK,OAAZ,MAAAC,EAAqB,UAAS,CAACa,EAAE,IAAKA,EAAE,OAAQA,EAAE,IAAI,EAAItB,GAAM,QAAQsB,EAAE,OAAQ,CAAC,aAAc,gBAAiB,aAAa,CAAC,GACpI,IAAMG,EAAS,MAAMH,EAAE,OAAO,KAAK,EACnCE,EAAI,OAASC,EAAO,GAAKA,EAAO,GAAK,OAAS,SAC9CD,EAAI,YAAc,KAAK,MAAM,KAAOC,EAAO,GAAKA,EAAO,GAAKA,EAAO,GAAKA,EAAO,GAAG,EAAI,IACtF,IAAMC,EAAO,MAAMJ,EAAE,KAAK,KAAK,EAC/B,QAASK,EAAI,EAAGA,EAAID,EAAK,OAAQC,IAC3BD,EAAKC,MAAMV,EAAAT,EAAO,KAAK,OAAZ,YAAAS,EAAqB,gBAAiB,KAAMO,EAAI,KAAK,KAAK,CAAE,MAAO,KAAK,MAAM,IAAME,EAAKC,EAAE,EAAI,IAAK,KAAMzB,GAAUyB,EAAW,CAAC,EAEjJH,EAAI,KAAK,KAAK,CAACI,EAAGC,IAAMA,EAAE,MAAQD,EAAE,KAAK,EAGzC,IAAME,EADkB,MAAM,KAAK,MAAMR,EAAE,IAAI,KAAK,CAAC,EACnB,IAAI,CAACM,EAAGD,IAAM,CAACxB,GAAWwB,GAAIC,CAAC,CAAC,EAAE,KAAK,CAACA,EAAGC,IAAMA,EAAE,GAAKD,EAAE,EAAE,EAC1FG,EAAMD,EAAU,GAAG,GACvB,QAASH,EAAI,EAAGA,EAAIG,EAAU,OAAQH,IAAKI,GAAOD,EAAUH,GAAG,IAAMG,EAAUH,GAAG,GAAKI,GACvFP,EAAI,IAAM,KAAK,MAAM,GAAKO,CAAG,EAAI,GACjC,OAAO,KAAKT,CAAC,EAAE,QAASU,GAAc,UAAQV,EAAEU,EAAO,CAAC,EACxD/B,GAAKc,GAAOS,EACZpB,GAAYY,EACZX,GAAWe,EAAI,EACfC,EAAQG,CAAG,CACb,CAAC,EACH,CClEO,IAAMS,EAAwD,CACnE,MAAO,IACP,IAAK,EACL,IAAK,EACL,KAAM,GACN,MAAO,MACP,IAAK,CAAC,MAAQ,KAAQ,IAAM,CAC9B,EAEO,SAASC,IAAO,CACrBD,EAAU,MAAW,SAAO,IAAK,SAAS,EAC1CA,EAAU,IAAS,SAAO,EAAG,SAAS,EACtCA,EAAU,IAAS,SAAO,EAAG,SAAS,EACtCA,EAAU,KAAU,SAAO,GAAK,SAAS,EACzCA,EAAU,MAAW,SAAO,MAAO,SAAS,EAC5CA,EAAU,IAAS,WAAS,CAAC,MAAQ,KAAQ,IAAM,EAAG,SAAS,CACjE,CCLA,IAAIE,GACEC,GAA+B,CAAC,EAClCC,GAAY,EACZC,GAAW,EACXC,GAAU,OAAO,iBAGrB,eAAsBC,GAAKC,EAAgB,CACzC,OAAIC,EAAI,UAASP,GAAQ,MACpBA,GACIM,EAAO,OAAOE,EAAI,gBAAiBR,GAAM,QAAW,EADjDA,GAAQ,MAAMS,EAAUH,EAAO,KAAK,OAAU,YAAY,EAE/DN,EACT,CAGA,eAAsBU,GAAQC,EAAeL,EAAgBM,EAAaC,EAAyC,CA7BnH,IAAAC,EAAAC,EAAAC,EAAAC,EA8BE,GAAI,CAACjB,GAAO,MAAO,CAAE,IAAK,CAAE,EAC5B,IAAMkB,EAAYd,MAAWU,EAAAR,EAAO,KAAK,SAAZ,YAAAQ,EAAuB,aAAc,GAC5DK,KAAYJ,EAAAT,EAAO,KAAK,SAAZ,YAAAS,EAAuB,WAAY,GAAMK,EAAI,EAAIjB,GACnE,OAAIG,EAAO,aAAeY,GAAaC,GAAajB,KAAcW,KAAUG,EAAAf,GAAKW,KAAL,YAAAI,EAAW,QAAQC,EAAAhB,GAAKW,KAAL,YAAAK,EAAW,KAAM,GAC9Gb,KACOH,GAAKW,KAEdR,GAAU,EACH,IAAI,QAAQ,MAAOiB,GAAY,CACpC,GAAI,EAACrB,IAAA,MAAAA,GAAO,SAAU,CAACA,GAAM,OAAO,IAAM,CAACA,GAAM,OAAO,GAAG,MAAO,OAClE,IAAMsB,EAA4B,CAAC,EACnCA,EAAE,OAAY,QAAM,eAAeX,EAAO,CAACX,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,EAAG,EAAK,EACrGsB,EAAE,QAAa,MAAIA,EAAE,OAAQC,EAAU,KAAK,EAC5C,IAAMC,EAAM,CAAE,IAAK,CAAE,EAErB,GADIlB,EAAO,KAAK,OAAU,UAASgB,EAAE,IAAMtB,GAAM,QAAQsB,EAAE,OAAO,GAC9DA,EAAE,IAAK,CACT,IAAMG,EAAO,MAAMH,EAAE,IAAI,KAAK,EAC9BE,EAAI,IAAM,KAAK,MAAM,GAAKC,EAAK,EAAE,EAAI,EACvC,CACA,OAAO,KAAKH,CAAC,EAAE,QAASI,GAAc,UAAQJ,EAAEI,EAAO,CAAC,EACxDzB,GAAKW,GAAOY,EACZtB,GAAYW,EACZV,GAAWiB,EAAI,EACfC,EAAQG,CAAG,CACb,CAAC,EACH,CCxCA,IAAIG,GACEC,GAAuD,CAAC,EAC1DC,GAAY,EACZC,GAAW,EACXC,GAAU,OAAO,iBAGfC,GAAM,CAAC,MAAQ,KAAQ,IAAM,EAGnC,eAAsBC,GAAKC,EAAsB,CAC/C,OAAIC,EAAI,UAASR,GAAQ,MACpBA,GACIO,EAAO,OAAOE,EAAI,gBAAiBT,GAAM,QAAW,EADjDA,GAAQ,MAAMU,EAAUH,EAAO,KAAK,OAAU,eAAe,EAElEP,EACT,CAGA,eAAsBW,GAAQC,EAAeL,EAAgBM,EAAKC,EAAyD,CAjC3H,IAAAC,EAAAC,EAAAC,EAAAC,EAkCE,GAAI,CAAClB,GAAO,MAAO,CAAE,OAAQ,UAAW,YAAa,CAAE,EACvD,IAAMmB,EAAYf,MAAWW,EAAAR,EAAO,KAAK,SAAZ,YAAAQ,EAAuB,aAAc,GAC5DK,KAAYJ,EAAAT,EAAO,KAAK,SAAZ,YAAAS,EAAuB,WAAY,GAAMK,EAAI,EAAIlB,GACnE,OAAII,EAAO,aAAeY,GAAaC,GAAalB,KAAcY,KAAUG,EAAAhB,GAAKY,KAAL,YAAAI,EAAW,WAAWC,EAAAjB,GAAKY,KAAL,YAAAK,EAAW,aAAc,GACzHd,KACOH,GAAKY,KAEdT,GAAU,EACH,IAAI,QAAQ,MAAOkB,GAAY,CACpC,GAAI,EAACtB,IAAA,MAAAA,GAAO,OAAO,GAAG,OAAO,OAC7B,IAAMuB,EAA4B,CAAC,EACnCA,EAAE,OAAY,QAAM,eAAeX,EAAO,CAACZ,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,EAAG,EAAK,EACrGuB,EAAE,QAAa,OAAK,IAAM,CACxB,GAAM,CAACC,EAAKC,EAAOC,CAAI,EAAO,QAAMH,EAAE,OAAQ,EAAG,CAAC,EAC5CI,EAAa,MAAIH,EAAKnB,GAAI,EAAE,EAC5BuB,EAAe,MAAIH,EAAOpB,GAAI,EAAE,EAChCwB,EAAc,MAAIH,EAAMrB,GAAI,EAAE,EAC9ByB,EAAe,OAAK,CAACH,EAASC,EAAWC,CAAQ,CAAC,EAExD,OADqB,MAAO,MAAIC,EAAWC,EAAU,IAAI,EAAG,CAAC,CAE/D,CAAC,EACD,IAAMC,EAA+C,CAAE,OAAQ,UAAW,YAAa,CAAE,EACrFzB,EAAO,KAAK,OAAU,UAASgB,EAAE,OAASvB,GAAM,QAAQuB,EAAE,OAAO,GACrE,IAAMU,EAAO,MAAMV,EAAE,OAAO,KAAK,EACjCS,EAAI,OAASC,EAAK,GAAKA,EAAK,GAAK,SAAW,OAC5CD,EAAI,YAAcC,EAAK,GAAKA,EAAK,GAAM,KAAK,MAAM,IAAMA,EAAK,EAAE,EAAI,IAAQ,KAAK,MAAM,IAAMA,EAAK,EAAE,EAAI,IACvG,OAAO,KAAKV,CAAC,EAAE,QAASW,GAAc,UAAQX,EAAEW,EAAO,CAAC,EACxDjC,GAAKY,GAAOmB,EACZ9B,GAAYY,EACZX,GAAWkB,EAAI,EACfC,EAAQU,CAAG,CACb,CAAC,EACH,CCvDA,IAAIG,GACEC,GAAwB,CAAC,EAC3BC,GAAU,OAAO,iBACjBC,GAAY,EACZC,GAAW,EAEf,eAAsBC,GAAKC,EAAqC,CAjBhE,IAAAC,EAkBE,OAAIC,EAAI,UAASR,GAAQ,MACpBA,GACIM,EAAO,OAAOG,EAAI,gBAAiBT,GAAM,QAAW,EADjDA,GAAQ,MAAMU,GAAUH,EAAAD,EAAO,KAAK,YAAZ,YAAAC,EAAuB,SAAS,EAE7DP,EACT,CAEA,eAAsBW,GAAQC,EAAeN,EAAgBO,EAAaC,EAAgC,CAxB1G,IAAAP,EAAAQ,EAyBE,GAAI,CAACf,GAAO,MAAO,GACnB,IAAMgB,KAAYT,EAAAD,EAAO,KAAK,YAAZ,YAAAC,EAAuB,WAAY,GAAMU,EAAI,EAAIb,GAC7Dc,EAAYhB,MAAWa,EAAAT,EAAO,KAAK,YAAZ,YAAAS,EAAuB,aAAc,GAClE,OAAIT,EAAO,aAAeU,GAAYE,GAAcf,KAAcW,GAAUb,GAAOY,IACjFX,KACOD,GAAOY,KAEhBX,GAAU,EACH,IAAI,QAAQ,MAAOiB,GAAY,CACpC,IAAMC,EAAY,QAAM,eAAeR,EAAO,CAACZ,IAAA,MAAAA,GAAO,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EAAGA,IAAA,MAAAA,GAAO,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,CAAC,EAAG,EAAK,EAC7JqB,EAAMrB,IAAA,YAAAA,GAAO,QAAQoB,GACrBE,GAAO,MAAMD,EAAI,KAAK,GAAG,GAC/BpB,GAAOY,GAAO,KAAK,MAAM,IAAMS,CAAG,EAAI,IACtCnB,GAAYW,EACZV,GAAWa,EAAI,EACZ,UAAQ,CAACG,EAAQC,CAAG,CAAC,EACxBF,EAAQlB,GAAOY,EAAI,CACrB,CAAC,EACH,CCtCO,IAAMU,GAA4C,CACvD,WAAY,CACV,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACtD,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACvD,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,GAAI,GACpD,EAKA,eAAgB,CAAC,IAAK,GAAI,GAAI,GAAI,EAAG,IAAK,IAAK,IAAK,GAAG,EACvD,eAAgB,CAAC,GAAI,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAG,EAClE,eAAgB,CAAC,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAG,EACxD,eAAgB,CAAC,GAAI,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAG,EACjE,mBAAoB,CAAC,GAAI,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAG,EACrE,mBAAoB,CAAC,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAG,EAC5D,mBAAoB,CAAC,GAAI,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAG,EACrE,mBAAoB,CAAC,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAG,EAC5D,eAAgB,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAClD,eAAgB,CAAC,GAAI,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EACzD,eAAgB,CAAC,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,GAAG,EAC7C,eAAgB,CAAC,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,GAAG,EACvD,eAAgB,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAClD,eAAgB,CAAC,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAC3D,eAAgB,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAC5D,kBAAmB,CAAC,IAAK,GAAI,GAAI,IAAK,GAAI,IAAK,GAAI,GAAG,EACtD,kBAAmB,CAAC,GAAI,IAAK,GAAI,GAAI,GAAI,EAAE,EAC3C,aAAc,CAAC,IAAK,IAAK,IAAK,IAAK,GAAG,EACtC,cAAe,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EACjD,cAAe,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAC3D,cAAe,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EACjD,cAAe,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAC3D,cAAe,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EACjD,cAAe,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAC3D,cAAe,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAC3D,iBAAkB,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EACzD,iBAAkB,CAAC,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAC/C,YAAa,CAAC,IAAK,IAAK,IAAK,IAAK,GAAG,EACrC,kBAAmB,CAAC,GAAG,EACvB,QAAS,CAAC,CAAC,EACX,WAAY,CAAC,CAAC,EACd,gBAAiB,CAAC,EAAE,EACpB,eAAgB,CAAC,GAAG,EACpB,WAAY,CAAC,GAAG,EAChB,UAAW,CAAC,GAAG,CACjB,EAEaC,GAAmD,CAC9D,MAAO,IACP,MAAO,GACP,aAAc,CAAC,GAAID,GAAgB,kBAAqB,EAAE,CAC5D,EAEaE,GAAwD,CACnE,QAAS,EACT,SAAU,EACV,KAAM,EACN,MAAO,EACP,QAAS,EACT,SAAU,EACV,aAAc,CAAC,EAAG,CAAC,CACrB,EAEaC,GAAyD,CACpE,CAAE,IAAK,YAAa,QAAS,CAAC,EAAG,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,EACzD,CAAE,IAAK,YAAa,QAAS,CAAC,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,EAC1D,CAAE,IAAK,YAAa,QAAS,CAAC,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,EAC1D,CAAE,IAAK,YAAa,QAAS,CAAC,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,CAAC,CAAE,EACzD,CAAE,IAAK,YAAa,QAAS,CAAC,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,EAClE,CAAE,IAAK,YAAa,QAAS,CAAC,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,EAClE,CAAE,IAAK,YAAa,QAAS,CAAC,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,EAClE,CAAE,IAAK,eAAgB,QAAS,CAAC,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,EACjE,CAAE,IAAK,eAAgB,QAAS,CAAC,GAAI,GAAI,GAAI,GAAI,GAAI,EAAE,CAAE,CAC3D,EAEaC,GAA4B,CACvC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,eAAgB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,eAAiB,eAAgB,EAClC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,eAAgB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,cAAgB,gBAAiB,EAClC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,gBAAkB,gBAAiB,EACpC,CAAC,eAAiB,gBAAiB,EACnC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,EACrC,CAAC,iBAAmB,gBAAiB,CACvC,EAEaC,GAAwB,CACnC,IAAK,GAAI,IAAK,GAAI,EAAG,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,EACtJ,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,GAAI,GAClJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,EAAG,IAAK,GAAI,GAAI,GAAI,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,GACrJ,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,EAAG,IAC7I,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAClJ,IAAK,IAAK,GAAI,GAAI,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,IAAK,GAAI,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,GACrJ,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,GACpJ,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,IAAK,GACjJ,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,EAAG,EAAG,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,EAAG,IAC/I,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,IAAK,EAAG,GAAI,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IACnJ,IAAK,GAAI,EAAG,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IACnJ,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,EAAG,IAAK,IAAK,GAAI,EAAG,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAC9I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,EAAG,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GACtJ,GAAI,GAAI,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,GAClJ,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,EAAG,EAAG,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GACnJ,IAAK,IAAK,IAAK,GAAI,GAAI,EAAG,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GACrJ,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IACpJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,EAAG,IAClJ,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,EAAG,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACnJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,GAAI,IAAK,IAAK,IAAK,IACnJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IACnJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAChJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,EAAG,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAChJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAC7I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAClJ,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAC7I,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,EAAG,IAAK,GAAI,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GACnJ,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,EAAG,GAAI,EAAG,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GACpJ,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,GAAI,IAAK,GAAI,IAAK,EAAG,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAClJ,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAClJ,GAAI,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,GAAI,GAAI,EAAG,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAChJ,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IACpJ,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,GACrJ,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,GAAI,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,GACpJ,IAAK,GAAI,IAAK,IAAK,EAAG,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,EAAG,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAC/I,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,EAAG,IAAK,GAAI,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAC9I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,GAAI,GACpJ,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GACrJ,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IACpJ,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,EAAG,IAAK,IAAK,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,GAAI,EACpJ,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAC9I,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,EAAG,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,EAAG,GAAI,IAClJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAC9I,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAChJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAChJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAC9I,IAAK,GAAI,IAAK,EAAG,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/I,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAChJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAClJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,EAAG,IAAK,IAAK,IAAK,IAAK,IACpJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACjJ,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GAAG,EAwB1I,IAAMC,GAAuB,CACtB,IAAK,IAAK,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC/E,GAAI,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAC1C,IAAK,EAAG,IAAK,EAAG,GAAI,GAAI,EAAG,IAAK,IAChC,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACtD,GAAI,GAAI,GAAI,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,GAChD,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GAAI,GAC7C,EAEaC,GAAuB,CAAC,GAAI,IAAK,IAAK,IAAK,EAAG,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,EAAG,IAAK,IAAK,EAAG,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,GAAI,GAAI,IAAK,GAAI,IAAK,IAAK,IAAK,GAAI,IAAK,GAAG,EAE5KC,GAAsB,CAAC,GAAI,IAAK,IAAK,IAAK,EAAG,GAAI,GAAG,EAEpDC,GAAOH,GAAM,IAAKI,GAAMC,GAAMD,EAAE,EAEhCE,GAAOL,GAAM,IAAKG,GAAMC,GAAMD,EAAE,EAEhCG,GAAML,GAAK,IAAKE,GAAMC,GAAMD,EAAE,EAO3C,SAASI,GAAqBC,EAAwB,CACpD,IAAMC,EAAUD,EAAY,IAAKE,GAAeA,EAAW,EAAE,EAC7D,OAAAD,EAAQ,KAAKD,EAAYA,EAAY,OAAS,GAAG,EAAE,EAC5CC,CACT,CAEO,IAAME,GAAuB,CACl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aC,GAA0B,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAEzNC,GAA8B,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAE7HC,GAA2B,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAE1EC,GAA2B,CAAC,CAAC,GAAI,CAAC,EAAG,CAAC,EAAG,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAEpNC,GAA+B,CAAC,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,CAAC,EAEjHC,GAA4B,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAE3EC,GAA8B,CACzC,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EACpE,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EACrE,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EACrE,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EACrE,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EACjE,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,CAChE,EAEaC,GAAmB,CAC9B,KAAMZ,GAAqBI,EAAS,EACpC,QAASJ,GAAqBK,EAAY,EAC1C,YAAaL,GAAqBM,EAAgB,EAClD,SAAUN,GAAqBO,EAAa,EAC5C,SAAUP,GAAqBQ,EAAa,EAC5C,aAAcR,GAAqBS,EAAiB,EACpD,UAAWT,GAAqBU,EAAc,EAC9C,SAAUV,GAAqBW,EAAgB,CACjD,ECrsBO,IAAME,GAAcC,GAA0B,CAAC,KAAK,IAAIA,EAAI,SAAS,GAAKA,EAAI,WAAW,EAAE,EAAG,KAAK,IAAIA,EAAI,SAAS,GAAKA,EAAI,WAAW,EAAE,CAAC,EAErIC,GAAgBD,GAAkC,CAACA,EAAI,WAAW,IAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAM,EAAGA,EAAI,WAAW,IAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAM,EAAG,CAAC,EAElLE,GAAW,CAACF,EAAKG,IAAgBH,EAAM,CAClD,KAAK,MAAM,KAAK,IAAI,EAAGA,EAAI,WAAW,EAAE,CAAC,EACzC,KAAK,MAAM,KAAK,IAAI,EAAGA,EAAI,WAAW,EAAE,CAAC,EACzC,KAAK,MAAM,KAAK,IAAKG,EAAM,MAAM,IAAM,EAAIH,EAAI,SAAS,EAAE,EAAI,KAAK,IAAI,EAAGA,EAAI,WAAW,EAAE,CAAC,EAC5F,KAAK,MAAM,KAAK,IAAKG,EAAM,MAAM,IAAM,EAAIH,EAAI,SAAS,EAAE,EAAI,KAAK,IAAI,EAAGA,EAAI,WAAW,EAAE,CAAC,CAC9F,EAAI,CAAC,EAAG,EAAG,EAAG,CAAC,EAEFI,GAAY,CAACJ,EAAKG,IAAgBH,EAAM,CACnDA,EAAI,WAAW,IAAMG,EAAM,MAAM,IAAM,GACvCH,EAAI,WAAW,IAAMG,EAAM,MAAM,IAAM,IACtCH,EAAI,SAAS,GAAKA,EAAI,WAAW,KAAOG,EAAM,MAAM,IAAM,IAC1DH,EAAI,SAAS,GAAKA,EAAI,WAAW,KAAOG,EAAM,MAAM,IAAM,EAC7D,EAAI,CAAC,EAAG,EAAG,EAAG,CAAC,EAEFE,GAAsB,CAACL,EAAKM,IAAW,CAClD,IAAMC,EAAoB,CAACP,EAAI,WAAW,GAAKM,EAAO,GAAIN,EAAI,WAAW,GAAKM,EAAO,EAAE,EACjFE,EAAkB,CAACR,EAAI,SAAS,GAAKM,EAAO,GAAIN,EAAI,SAAS,GAAKM,EAAO,EAAE,EACjF,MAAO,CAAE,WAAAC,EAAY,SAAAC,EAAU,UAAWR,EAAI,UAAW,WAAYA,EAAI,UAAW,CACtF,EAEaS,GAAe,CAACT,EAAKU,EAAOC,IAAa,CACpD,IAAMC,EAAIF,EAAM,MAAM,GAChBG,EAAIH,EAAM,MAAM,GAChBI,EAAS,CAACd,EAAI,WAAW,GAAKY,EAAGZ,EAAI,WAAW,GAAKa,EAAGb,EAAI,SAAS,GAAKY,EAAGZ,EAAI,SAAS,GAAKa,CAAC,EAChGE,EAAU,QAAM,cAAcL,EAAO,CAACI,CAAM,EAAG,CAAC,CAAC,EAAGH,CAAQ,EAC5DK,EAAU,MAAID,EAAME,EAAU,KAAK,EACzC,OAAG,UAAQF,CAAI,EACRC,CACT,EAEaE,GAAa,CAAClB,EAAKM,IAAW,CACzC,IAAMa,EAASlB,GAAaD,CAAG,EACzBoB,EAAOrB,GAAWC,CAAG,EACrBqB,EAA6B,CAACf,EAASc,EAAK,GAAK,EAAGd,EAASc,EAAK,GAAK,CAAC,EAC9E,MAAO,CAAE,WAAY,CAACD,EAAO,GAAKE,EAAS,GAAIF,EAAO,GAAKE,EAAS,EAAE,EAAY,SAAU,CAACF,EAAO,GAAKE,EAAS,GAAIF,EAAO,GAAKE,EAAS,EAAE,EAAY,UAAWrB,EAAI,UAAW,WAAYA,EAAI,UAAW,CAChN,EAEasB,GAAetB,GAAQ,CAClC,IAAMuB,EAAUtB,GAAaD,CAAG,EAC1BoB,EAAOrB,GAAWC,CAAG,EACrBqB,EAAW,KAAK,IAAI,GAAGD,CAAI,EAAI,EACrC,MAAO,CAAE,WAAY,CAAC,KAAK,MAAMG,EAAQ,GAAKF,CAAQ,EAAG,KAAK,MAAME,EAAQ,GAAKF,CAAQ,CAAC,EAAY,SAAU,CAAC,KAAK,MAAME,EAAQ,GAAKF,CAAQ,EAAG,KAAK,MAAME,EAAQ,GAAKF,CAAQ,CAAC,EAAY,UAAWrB,EAAI,UAAW,WAAYA,EAAI,UAAW,CACxP,EAEawB,GAAiCC,GAAc,CAC1D,IAAMC,EAAID,EAAU,IAAKE,GAAMA,EAAE,EAAE,EAC7BC,EAAIH,EAAU,IAAKE,GAAMA,EAAE,EAAE,EACnC,MAAO,CAAE,WAAY,CAAC,KAAK,IAAI,GAAGD,CAAC,EAAG,KAAK,IAAI,GAAGE,CAAC,CAAC,EAAY,SAAU,CAAC,KAAK,IAAI,GAAGF,CAAC,EAAG,KAAK,IAAI,GAAGE,CAAC,CAAC,EAAY,UAAAH,CAAU,CACjI,EAEaI,GAAsB,CAAC,CAAC,EAAG,EAAG,CAAC,EAAG,CAAC,EAAG,EAAG,CAAC,EAAG,CAAC,EAAG,EAAG,CAAC,CAAC,EAEtDC,GAAoBC,GAAUA,EAAQ,EAAI,KAAK,GAAK,KAAK,OAAOA,EAAQ,KAAK,KAAO,EAAI,KAAK,GAAG,EAEhGC,GAAkB,CAACC,EAAQC,IAAWJ,GAAiB,KAAK,GAAK,EAAI,KAAK,MAAM,EAAEI,EAAO,GAAKD,EAAO,IAAKC,EAAO,GAAKD,EAAO,EAAE,CAAC,EAItI,IAAME,GAAyB,CAACC,EAAGC,IAAM,CAAC,CAAC,EAAG,EAAGD,CAAC,EAAG,CAAC,EAAG,EAAGC,CAAC,EAAG,CAAC,EAAG,EAAG,CAAC,CAAC,EAEnEC,GAAM,CAACC,EAAcC,IAAiB,CACjD,IAAIC,EAAU,EACd,QAASC,EAAI,EAAGA,EAAIH,EAAG,OAAQG,IAAKD,GAAWF,EAAGG,GAAKF,EAAGE,GAC1D,OAAOD,CACT,EAEaE,GAAqB,CAACC,EAAKC,IAAgB,CACtD,IAAMC,EAAwB,CAAC,EAC/B,QAASJ,EAAI,EAAGA,EAAIE,EAAI,OAAQF,IAAKI,EAAO,KAAKF,EAAIF,GAAGG,EAAY,EACpE,OAAOC,CACT,EAEaC,GAA4B,CAACC,EAAMC,IAAS,CACvD,IAAMR,EAA2B,CAAC,EAC5BS,EAAOF,EAAK,OAClB,QAASG,EAAM,EAAGA,EAAMD,EAAMC,IAAO,CACnCV,EAAQ,KAAK,CAAC,CAAC,EACf,QAASW,EAAM,EAAGA,EAAMF,EAAME,IAAOX,EAAQU,GAAK,KAAKb,GAAIU,EAAKG,GAAMR,GAAmBM,EAAMG,CAAG,CAAC,CAAC,CACtG,CACA,OAAOX,CACT,EAEaY,GAAsB,CAACC,EAAUC,IAAW,CACvD,IAAMC,EAAO,KAAK,IAAIF,CAAQ,EACxBG,EAAO,KAAK,IAAIH,CAAQ,EACxBI,EAAiB,CAAC,CAACF,EAAM,CAACC,EAAM,CAAC,EAAG,CAACA,EAAMD,EAAM,CAAC,EAAG,CAAC,EAAG,EAAG,CAAC,CAAC,EAC9DG,EAAoBxB,GAAuBoB,EAAO,GAAIA,EAAO,EAAE,EAC/DK,EAA2Bb,GAA0BY,EAAmBD,CAAc,EACtFG,EAA4B1B,GAAuB,CAACoB,EAAO,GAAI,CAACA,EAAO,EAAE,EAC/E,OAAOR,GAA0Ba,EAA0BC,CAAyB,CACtF,EAEaC,GAAyBC,GAAW,CAC/C,IAAMC,EAAoB,CAAC,CAACD,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,EAAG,CAACA,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,CAAC,EAC/EE,EAAuB,CAACF,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,EAClDG,EAAsB,CAAC,CAAC5B,GAAI0B,EAAkB,GAAIC,CAAoB,EAAG,CAAC3B,GAAI0B,EAAkB,GAAIC,CAAoB,CAAC,EAC/H,MAAO,CAACD,EAAkB,GAAG,OAAOE,EAAoB,EAAE,EAAGF,EAAkB,GAAG,OAAOE,EAAoB,EAAE,EAAG,CAAC,EAAG,EAAG,CAAC,CAAC,CAC7H,EAEaC,GAAc,CAACC,EAAuBV,IAAmB,CAACpB,GAAI8B,EAAuBV,EAAe,EAAE,EAAGpB,GAAI8B,EAAuBV,EAAe,EAAE,CAAC,EAI5J,SAASW,GAAgBC,EAAW,CACzC,IAAMC,EAAOD,IAAc,IACvB,CAAE,QAAS,CAAC,CAAC,EAAG,QAAS,CAAC,CAAC,CAAE,EAC7B,CAAE,QAAS,CAACA,EAAY,GAAIA,EAAY,CAAC,EAAG,QAAS,CAAC,EAAG,CAAC,CAAE,EAC1DE,EAAmC,CAAC,EAC1C,QAASC,EAAI,EAAGA,EAAIF,EAAK,QAAQ,OAAQE,IAAK,CAC5C,IAAMC,EAASH,EAAK,QAAQE,GACtBE,EAAW,KAAK,OAAOL,EAAYI,EAAS,GAAKA,CAAM,EACvDE,EAAW,KAAK,OAAON,EAAYI,EAAS,GAAKA,CAAM,EACvDG,EAAaN,EAAK,QAAQE,GAChC,QAASK,EAAQ,EAAGA,EAAQH,EAAUG,IAAS,CAC7C,IAAMC,EAAUL,GAAUI,EAAQ,IAClC,QAASE,EAAQ,EAAGA,EAAQJ,EAAUI,IAAS,CAC7C,IAAMC,EAAUP,GAAUM,EAAQ,IAClC,QAASE,EAAI,EAAGA,EAAIL,EAAYK,IAAKV,EAAQ,KAAK,CAACS,EAASF,CAAO,CAAC,CACtE,CACF,CACF,CACA,OAAOP,CACT,CAEO,SAASW,GAAmBC,EAAWC,EAAKC,EAAOC,EAAgBjB,EAAW,CACnF,IAAMkB,EAAUC,GAAWJ,CAAG,EACxBK,EAAeN,EAAU,IAAKO,GAAW,CAC5CH,EAAQ,GAAKlB,GAAcqB,EAAM,GAAMrB,EAAY,GACnDkB,EAAQ,GAAKlB,GAAcqB,EAAM,GAAMrB,EAAY,GACnDqB,EAAM,IAAM,CACf,CAAE,EACIC,EAAaN,GAAUA,IAAU,GAAO,KAAK,IAAIA,CAAK,EAAI,GAC1DO,EAAuBD,EAAaE,GAAoBR,EAAO,CAAC,EAAG,CAAC,CAAC,EAAIS,GACzEC,EAAgBJ,EAAaF,EAAa,IAAKC,GAAW,CAAC,GAAGM,GAAYN,EAAOE,CAAoB,EAAGF,EAAM,EAAE,CAAE,EAAID,EACtHQ,EAAwBN,EAAaO,GAAsBZ,CAAc,EAAIQ,GAC7EK,EAAYC,GAAahB,CAAG,EAC5BiB,EAAU,CAACC,GAAIH,EAAWF,EAAsB,EAAE,EAAGK,GAAIH,EAAWF,EAAsB,EAAE,CAAC,EACnG,OAAOF,EAAc,IAAKL,GAAW,CACnC,KAAK,MAAMA,EAAM,GAAKW,EAAQ,EAAE,EAChC,KAAK,MAAMX,EAAM,GAAKW,EAAQ,EAAE,EAChC,KAAK,MAAMX,EAAM,IAAM,CAAC,CAC1B,CAAE,CACJ,CAEO,SAASa,GAAoBC,EAAQpB,EAAKqB,EAAOpC,EAAW,CACjE,IAAMqC,EAAgBtB,EAAI,UAAU,QAAiBuB,GAAc,MACxDA,GAAc,aACdC,GAAmB,aAC1BvB,EAAQ,EACRC,EAAiBQ,GACjBe,EAEJ,GAAIL,GAAUM,EAAI,QAAQ,SAAS,kBAAkB,EAGnD,GAFAzB,EAAQ0B,GAAgB3B,EAAI,UAAUsB,EAAa,IAAKtB,EAAI,UAAUsB,EAAa,GAAG,EACnErB,GAAUA,IAAU,GAAO,KAAK,IAAIA,CAAK,EAAI,GAChD,CACd,IAAM2B,EAAgBZ,GAAahB,CAAG,EAChC6B,EAAmB,CAACD,EAAO,GAAKP,EAAM,MAAM,GAAIO,EAAO,GAAKP,EAAM,MAAM,EAAE,EAC1ES,EAAa,QAAM,iBAAiBT,EAAOpB,EAAO,EAAG4B,CAAS,EACpE3B,EAAiBO,GAAoB,CAACR,EAAO2B,CAAM,EACnDH,EAAOM,GAAa/B,EAAK8B,EAAS,CAAC7C,EAAWA,CAAS,CAAC,EACrD,UAAQ6C,CAAO,CACpB,MACEL,EAAOM,GAAa/B,EAAKqB,EAAO,CAACpC,EAAWA,CAAS,CAAC,OAGxDwC,EAAOM,GAAa/B,EAAKqB,EAAO,CAACpC,EAAWA,CAAS,CAAC,EAExD,MAAO,CAACgB,EAAOC,EAAgBuB,CAAI,CACrC,CAEO,IAAMO,GAAkBC,GAAS,CACtC,IAAMC,EAAID,EAAK,IAAKE,GAAMA,EAAE,EAAE,EACxBC,EAAIH,EAAK,IAAKE,GAAMA,EAAE,EAAE,EAO9B,MAAO,CAAC,KAAK,IAAI,GAAGD,CAAC,GAAK,KAAK,IAAI,GAAGA,CAAC,EAAI,KAAK,IAAI,GAAGA,CAAC,GAAK,EAAG,KAAK,IAAI,GAAGE,CAAC,GAAK,KAAK,IAAI,GAAGA,CAAC,EAAI,KAAK,IAAI,GAAGA,CAAC,GAAK,CAAC,CACxH,EAEaC,GAAmB,CAACJ,EAAMK,IAAgB,CACrD,IAAMV,EAASI,GAAeC,CAAI,EAC5B9B,EAAUC,GAAWkC,CAAW,EAKtC,MAJsB,CACpB,WAAY,CAACV,EAAO,GAAKzB,EAAQ,GAAK,EAAGyB,EAAO,GAAKzB,EAAQ,GAAK,CAAC,EACnE,SAAU,CAACyB,EAAO,GAAKzB,EAAQ,GAAK,EAAGyB,EAAO,GAAKzB,EAAQ,GAAK,CAAC,CACnE,CAEF,ECnMA,IAAMoC,GAAiB,EACjBC,GAAqB,IACvBC,GACAC,GAAyB,KACzBC,GAAY,EACZC,GAA4B,KAInBC,GAAO,IAAMF,GAE1B,eAAsBG,GAAKC,EAAqC,CA1BhE,IAAAC,EA2BE,OAAIC,EAAI,UAASR,GAAQ,MACpBA,GACIM,EAAO,OAAOG,EAAI,gBAAiBT,GAAM,QAAW,EADjDA,GAAQ,MAAMU,GAAUH,EAAAD,EAAO,KAAK,WAAZ,YAAAC,EAAsB,SAAS,EAEnEL,GAAYF,GAAM,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EAC/DG,GAAgB,SAAOD,GAAW,OAAO,EACzCD,GAAa,WAAcU,GAAgBT,EAAS,CAAC,EAC9CF,EACT,CAEA,SAASY,GAAYC,EAAoB,CACvC,IAAM,EAA4B,CAAC,EACnC,EAAE,UAAe,QAAMA,EAAY,CAAC,EAAG,CAAC,EAAG,CAAC,GAAI,CAAC,CAAC,EAClD,EAAE,QAAa,MAAI,EAAE,UAAWZ,EAAO,EACvC,EAAE,SAAc,QAAMY,EAAY,CAAC,EAAG,CAAC,EAAG,CAAC,GAAI,CAAC,CAAC,EACjD,EAAE,mBAAwB,MAAI,EAAE,SAAUV,EAAU,EACpD,EAAE,kBAAuB,MAAI,EAAE,QAASA,EAAU,EAClD,EAAE,YAAiB,MAAI,EAAE,mBAAoBW,EAAU,GAAG,EAC1D,EAAE,OAAY,MAAI,EAAE,kBAAmB,EAAE,WAAW,EACpD,EAAE,KAAU,MAAI,EAAE,kBAAmB,EAAE,WAAW,EAClD,EAAE,gBAAqB,MAAI,EAAE,OAAQX,EAAU,EAC/C,EAAE,cAAmB,MAAI,EAAE,KAAMA,EAAU,EAC3C,IAAMY,EAAW,WAAS,CAAC,EAAE,gBAAiB,EAAE,aAAa,EAAG,CAAC,EACjE,cAAO,KAAK,CAAC,EAAE,QAASC,GAAc,UAAQ,EAAEA,EAAO,CAAC,EACjDD,CACT,CAEA,eAAsBE,GAASC,EAAoBZ,EAAgB,CArDnE,IAAAC,EAAAY,EAAAC,EAAAC,EAuDE,GAAK,CAACH,GAAgBA,EAAW,oBAA2BA,EAAW,MAAM,SAAW,GAAOA,EAAW,MAAM,GAAK,GAAOA,EAAW,MAAM,GAAK,EAAI,MAAO,CAAC,EAC9J,IAAMI,EAA4B,CAAC,EACnCA,EAAE,QAAa,QAAM,eAAeJ,EAAY,CAAChB,GAAWA,EAAS,CAAC,EACtEoB,EAAE,IAAS,MAAIA,EAAE,QAASR,EAAU,KAAK,EACzCQ,EAAE,WAAgB,MAAIA,EAAE,IAAKR,EAAU,IAAI,EAC3C,IAAMS,EAAMvB,IAAA,YAAAA,GAAO,QAAQsB,EAAE,YAC7B,GAAI,MAAM,QAAQC,CAAG,GAAKA,EAAI,OAAS,EAAG,CACxC,IAAMC,EAASD,EAAI,KAAK,CAACE,EAAGC,IAAMD,EAAE,KAAOC,EAAE,IAAI,EACjDJ,EAAE,UAAe,SAAO,CAACE,EAAO,GAAIA,EAAO,EAAE,EAAG,CAAC,EACjDF,EAAE,UAAe,SAAO,CAACE,EAAO,GAAIA,EAAO,EAAE,EAAG,CAAC,EACjDF,EAAE,OAAY,SAAO,CAACA,EAAE,UAAWA,EAAE,SAAS,EAAG,CAAC,EAClDA,EAAE,MAAW,UAAQA,EAAE,OAAQ,CAAC,CAClC,MAAW,MAAM,QAAQC,CAAG,EAC1BD,EAAE,MAAW,UAAQC,EAAI,EAAE,EAE3BD,EAAE,MAAW,UAAQC,CAAG,EAEvB,UAAQA,CAAG,EACdD,EAAE,MAAQV,GAAYU,EAAE,KAAK,EAC7BA,EAAE,OAAY,QAAMA,EAAE,MAAO,CAAC,EAAG,CAAC,EAAG,CAAC,GAAI,CAAC,CAAC,EAC5CA,EAAE,QAAa,UAAQA,EAAE,MAAM,EAC/BA,EAAE,OAAY,UAAQA,EAAE,OAAO,EAC/BA,EAAE,IAAM,MAAS,QAAM,uBAAuBA,EAAE,MAAOA,EAAE,SAASf,EAAAD,EAAO,KAAK,WAAZ,YAAAC,EAAsB,cAAe,IAAKY,EAAAb,EAAO,KAAK,WAAZ,YAAAa,EAAsB,eAAgB,IAAKC,EAAAd,EAAO,KAAK,WAAZ,YAAAc,EAAsB,gBAAiB,CAAE,EAChM,IAAMO,EAAM,MAAML,EAAE,IAAI,MAAM,EACxBP,EAA0B,CAAC,EAC3Ba,EAAS,MAAMN,EAAE,OAAO,KAAK,EACnC,QAASO,EAAI,EAAGA,EAAIF,EAAI,OAAQE,IAAK,CACnC,IAAMC,EAAaF,EAAOD,EAAIE,IAC9B,GAAIC,KAAcT,EAAAf,EAAO,KAAK,WAAZ,YAAAe,EAAsB,gBAAiB,GAAI,CAC3D,IAAMK,EAA4B,CAAC,EACnCA,EAAE,KAAU,QAAMJ,EAAE,MAAO,CAACK,EAAIE,GAAI,CAAC,EAAG,CAAC,EAAG,EAAE,CAAC,EAC/CH,EAAE,MAAW,QAAMJ,EAAE,MAAO,CAACK,EAAIE,GAAI/B,GAAiB,CAAC,EAAG,CAAC,EAAG,EAAE,CAAC,EACjE4B,EAAE,QAAa,UAAQA,EAAE,KAAK,EAC9BA,EAAE,UAAe,UAAQA,EAAE,QAAS,CAAC5B,GAAgB,EAAE,CAAC,EACxD,IAAMiC,EAAS,MAAML,EAAE,KAAK,KAAK,EAC3BM,EAAS,CACb,WAAY,CAACD,EAAO,GAAIA,EAAO,EAAE,EACjC,SAAU,CAACA,EAAO,GAAIA,EAAO,EAAE,EAC/B,UAAY,MAAML,EAAE,UAAU,MAAM,EACpC,WAAAI,CACF,EACMG,EAAiBC,GAAoBF,EAAQ,EAAEd,EAAW,MAAM,IAAM,GAAKhB,IAAYgB,EAAW,MAAM,IAAM,GAAKhB,EAAS,CAAC,EAC7HiC,EAAmBC,GAAWH,EAAW3B,EAAO,KAAK,OAAYP,EAAkB,EACnFsC,EAAkBC,GAAYH,CAAW,EAC/CpB,EAAM,KAAKsB,CAAU,EACrB,OAAO,KAAKX,CAAC,EAAE,QAASV,GAAc,UAAQU,EAAEV,EAAO,CAAC,CAC1D,CACF,CACA,cAAO,KAAKM,CAAC,EAAE,QAASN,GAAc,UAAQM,EAAEN,EAAO,CAAC,EACjDD,CACT,CCzGA,IAAAwB,GAAA,GAAAC,GAAAD,GAAA,eAAAE,GAAA,QAAAC,KAEO,IAAMA,GAAqB,CAChC,OACA,gBACA,UACA,iBACA,iBACA,WACA,kBACA,UACA,WACA,YACA,aACA,eACA,gBACA,YACA,aACA,YACA,aACA,YACA,aACA,YACA,aACA,YACA,aACA,UACA,WACA,WACA,YACA,YACA,aACA,WACA,YACA,WACA,YACA,aACA,UACA,WACA,WACA,YACA,WACF,EAEaD,GAAsC,CACjD,UAAW,CAAC,eAAgB,eAAe,EAC3C,KAAM,CAAC,WAAY,SAAS,EAC5B,MAAO,CAAC,YAAa,YAAY,EACjC,aAAc,CAAC,UAAW,UAAU,EACpC,aAAc,CAAC,WAAY,WAAW,EACtC,SAAU,CAAC,YAAa,WAAY,UAAU,EAC9C,UAAW,CAAC,eAAgB,SAAS,EACrC,aAAc,CAAC,eAAgB,WAAW,EAC1C,aAAc,CAAC,YAAa,WAAW,EACvC,SAAU,CAAC,YAAa,UAAU,EAClC,cAAe,CAAC,WAAY,WAAW,EACvC,cAAe,CAAC,WAAY,WAAW,EACvC,cAAe,CAAC,WAAY,WAAW,EACvC,eAAgB,CAAC,gBAAiB,gBAAgB,EAClD,cAAe,CAAC,WAAY,WAAW,EACvC,cAAe,CAAC,YAAa,YAAY,EACzC,UAAW,CAAC,aAAc,YAAa,WAAW,EAClD,WAAY,CAAC,gBAAiB,UAAU,EACxC,cAAe,CAAC,gBAAiB,YAAY,EAC7C,cAAe,CAAC,aAAc,YAAY,EAC1C,UAAW,CAAC,aAAc,WAAW,EACrC,eAAgB,CAAC,YAAa,YAAY,EAC1C,eAAgB,CAAC,YAAa,YAAY,EAC1C,eAAgB,CAAC,YAAa,YAAY,EAC1C,gBAAiB,CAAC,iBAAkB,iBAAiB,CACvD,EC/DA,IAAME,GAAY,IACdC,GACEC,GAAY,EACZC,GAAU,CAAC,EAAG,GAAI,GAAI,GAAI,EAAE,EAElC,eAAsBC,IAAgB,CACpC,IAAMC,EAA2C,CAAC,EAC9CC,EAAU,EACd,KAAOA,EAAUJ,IAAW,CAC1B,IAAIK,EAAc,EACdC,EAAsBF,EAC1B,KAAOE,EAAsBL,GAAQ,QAAUA,GAAQK,KAAyBL,GAAQG,IACtFC,GAAe,EACfC,IAEF,IAAMC,EAASN,GAAQG,GACjBI,EAAmB,KAAK,KAAKV,GAAYS,CAAM,EAC/CE,EAAkB,KAAK,KAAKX,GAAYS,CAAM,EACpD,QAASG,EAAI,EAAGA,EAAIF,EAAkB,EAAEE,EACtC,QAASC,EAAI,EAAGA,EAAIF,EAAiB,EAAEE,EACrC,QAASC,EAAW,EAAGA,EAAWP,EAAa,EAAEO,EAC/CT,EAAQ,KAAK,CAAE,GAAIQ,EAAI,IAAOF,EAAiB,GAAIC,EAAI,IAAOF,CAAiB,CAAC,EAItFJ,EAAUE,CACZ,CACAP,GAAe,CAAE,EAAM,WAASI,EAAQ,IAAKU,GAAMA,EAAE,CAAC,CAAC,EAAG,EAAM,WAASV,EAAQ,IAAKU,GAAMA,EAAE,CAAC,CAAC,CAAE,CACpG,CCjCO,SAASC,GAAKC,EAAyBC,EAA+B,CAAC,EAAG,CAAC,EAAG,CACnF,IAAMC,EAAS,CAACF,EAAU,IAAKG,GAAOA,EAAG,EAAE,EAAGH,EAAU,IAAKG,GAAOA,EAAG,EAAE,CAAC,EACpEC,EAAM,CAAC,KAAK,IAAI,GAAGF,EAAO,EAAE,EAAG,KAAK,IAAI,GAAGA,EAAO,EAAE,CAAC,EACrDG,EAAM,CAAC,KAAK,IAAI,GAAGH,EAAO,EAAE,EAAG,KAAK,IAAI,GAAGA,EAAO,EAAE,CAAC,EACrDI,EAAW,CAACF,EAAI,GAAIA,EAAI,GAAIC,EAAI,GAAKD,EAAI,GAAIC,EAAI,GAAKD,EAAI,EAAE,EAC5DG,EAAc,CAACD,EAAI,GAAKL,EAAW,GAAIK,EAAI,GAAKL,EAAW,GAAIK,EAAI,GAAKL,EAAW,GAAIK,EAAI,GAAKL,EAAW,EAAE,EACnH,MAAO,CAAE,IAAAK,EAAK,OAAAC,CAAO,CACvB,CAEO,SAASC,GAAOR,EAAyBC,EAA+B,CAAC,EAAG,CAAC,EAAG,CACrF,IAAMC,EAAS,CAACF,EAAU,IAAKG,GAAOA,EAAG,EAAE,EAAGH,EAAU,IAAKG,GAAOA,EAAG,EAAE,CAAC,EACpEC,EAAM,CAAC,KAAK,IAAI,GAAGF,EAAO,EAAE,EAAG,KAAK,IAAI,GAAGA,EAAO,EAAE,CAAC,EACrDG,EAAM,CAAC,KAAK,IAAI,GAAGH,EAAO,EAAE,EAAG,KAAK,IAAI,GAAGA,EAAO,EAAE,CAAC,EACrDO,EAAS,EAAEL,EAAI,GAAKC,EAAI,IAAM,GAAID,EAAI,GAAKC,EAAI,IAAM,CAAC,EACtDK,EAAO,KAAK,IAAID,EAAO,GAAKL,EAAI,GAAIK,EAAO,GAAKL,EAAI,GAAI,CAACK,EAAO,GAAKJ,EAAI,GAAI,CAACI,EAAO,GAAKJ,EAAI,EAAE,EAChGC,EAAW,CAAC,KAAK,MAAMG,EAAO,GAAKC,CAAI,EAAG,KAAK,MAAMD,EAAO,GAAKC,CAAI,EAAG,KAAK,MAAM,EAAIA,CAAI,EAAG,KAAK,MAAM,EAAIA,CAAI,CAAC,EAClHH,EAAc,CAACD,EAAI,GAAKL,EAAW,GAAIK,EAAI,GAAKL,EAAW,GAAIK,EAAI,GAAKL,EAAW,GAAIK,EAAI,GAAKL,EAAW,EAAE,EACnH,MAAO,CAAE,IAAAK,EAAK,OAAAC,CAAO,CACvB,CAEO,SAASI,GAAML,EAAUM,EAAmB,CACjD,IAAMF,EAAO,CAACJ,EAAI,GAAKM,EAAWN,EAAI,GAAKM,CAAS,EAOpD,MANoB,CAClBN,EAAI,IAAMI,EAAK,GAAKJ,EAAI,IAAM,EAC9BA,EAAI,IAAMI,EAAK,GAAKJ,EAAI,IAAM,EAC9BI,EAAK,GACLA,EAAK,EACP,CAEF,CChBA,IAAMG,GAAM,CAAE,QAAS,EAAK,EAEtBC,GAAwE,CAAE,SAAU,KAAM,UAAW,IAAK,EAC1GC,GAAyE,CAAE,SAAU,CAAC,IAAK,GAAG,EAAG,UAAW,CAAC,IAAK,GAAG,CAAE,EACzHC,GAAU,OAAO,iBACfC,GAA2D,CAC/D,UAAW,CAAC,QAAS,0BAA2B,qBAAsB,WAAY,iBAAiB,EACnG,SAAU,CAAC,CACb,EAEIC,GAA2B,KAC3BC,GACAC,GAA8B,CAAC,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,CAAC,EAC7DC,GAAW,EAETC,GAAWC,GAAO,EAAK,GAAK,EAAI,KAAK,IAAIA,CAAC,GAEhD,eAAsBC,GAAWC,EAAqC,CAEpE,GADIZ,GAAI,UAASC,GAAO,SAAW,MAC/B,CAACA,GAAO,UAAYW,EAAO,KAAK,UAAeA,EAAO,KAAK,SAAY,UAAoB,CAC7FX,GAAO,SAAW,MAAMY,EAAUD,EAAO,KAAK,SAAY,SAAY,EACtE,IAAME,EAAS,OAAO,OAAOb,GAAO,SAAS,eAAe,MAAS,EACrEC,GAAU,SAAS,GAAK,MAAM,QAAQY,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,EAC9FZ,GAAU,SAAS,GAAK,MAAM,QAAQY,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,CAChG,MAAWF,EAAO,OAASX,GAAO,UAAUc,EAAI,gBAAiBd,GAAO,SAAS,QAAW,EAC5F,aAAae,GAAc,EACpBf,GAAO,QAChB,CAEA,eAAsBgB,GAASL,EAAqC,CAElE,GADIZ,GAAI,UAASC,GAAO,UAAY,MAC/BA,GAAO,UAKDW,EAAO,OAAOG,EAAI,gBAAiBd,GAAO,UAAU,QAAW,MALnD,CACrBA,GAAO,UAAY,MAAMY,EAAUD,EAAO,KAAK,SAAS,EACxD,IAAME,EAAS,OAAO,OAAOb,GAAO,UAAU,eAAe,MAAS,EACtEC,GAAU,UAAU,GAAK,MAAM,QAAQY,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,EAC/FZ,GAAU,UAAU,GAAK,MAAM,QAAQY,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,CACjG,CACA,OAAOb,GAAO,SAChB,CAQA,eAAeiB,GAAaC,EAAeC,EAA+B,CACxE,IAAMC,EAA4B,CAAC,EACnC,GAAI,CAACF,EAAM,OAAS,CAACA,EAAM,MAAM,IAAM,CAACA,EAAM,MAAM,GAAI,OAAOA,EAC/D,IAAIG,EAIJ,GAHIC,KACFF,EAAE,QAAa,QAAM,cAAcF,EAAO,CAACI,EAAO,EAAG,CAAC,CAAC,EAAG,CAACJ,EAAM,MAAM,GAAIA,EAAM,MAAM,EAAE,CAAC,GAExFA,EAAM,MAAM,KAAOA,EAAM,MAAM,GAAI,CACrC,IAAMK,EAA2B,CAC/BL,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,EACtFA,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,CACxF,EACMM,EAA0B,CAC9BN,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,EACtFA,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,CACxF,EACAO,GAAU,CACR,CAAC,EAAG,CAAC,EACLF,EACAC,EACA,CAAC,EAAG,CAAC,CACP,EACAJ,EAAE,IAAS,MAAIA,EAAE,SAAWF,EAAOO,EAAO,EAC1CL,EAAE,OAAY,QAAM,eAAeA,EAAE,IAAK,CAACD,EAAMA,CAAI,CAAC,EACtDE,EAAW,MAAID,EAAE,OAAQM,EAAU,KAAK,CAC1C,MAAWR,EAAM,MAAM,KAAOC,GAC5BC,EAAE,OAAY,QAAM,eAAeA,EAAE,SAAWF,EAAO,CAACC,EAAMA,CAAI,CAAC,EACnEE,EAAW,MAAID,EAAE,OAAQM,EAAU,KAAK,GAExCL,EAAW,MAAID,EAAE,SAAWF,EAAOQ,EAAU,KAAK,EAEpD,cAAO,KAAKN,CAAC,EAAE,QAASO,GAAc,UAAQP,EAAEO,EAAO,CAAC,EACjDN,CACT,CAEA,SAASO,GAAiBC,EAAgCC,EAAmD,CAC3G,QAAWC,KAAOF,EAChBE,EAAI,SAAW,CACb,KAAK,MAAMA,EAAI,SAAS,IAAMD,EAAW,GAAKL,GAAQ,GAAG,GAAKA,GAAQ,GAAG,IAAMK,EAAW,GAAKL,GAAQ,GAAG,EAAE,EAC5G,KAAK,MAAMM,EAAI,SAAS,IAAMD,EAAW,GAAKL,GAAQ,GAAG,GAAKA,GAAQ,GAAG,IAAMK,EAAW,GAAKL,GAAQ,GAAG,EAAE,EAC5GM,EAAI,SAAS,EACf,EACAA,EAAI,YAAc,CAACA,EAAI,SAAS,GAAKD,EAAW,GAAIC,EAAI,SAAS,GAAKD,EAAW,GAAI,EAAKC,EAAI,SAAS,IAAiBD,EAAW,GAAKA,EAAW,GAAG,EAExJ,GAAIR,GACF,QAAWS,KAAOF,EAChBE,EAAI,YAAc,CAChBA,EAAI,YAAY,GAAKT,GAAQ,GAC7BS,EAAI,YAAY,GAAKT,GAAQ,GAC7BS,EAAI,YAAY,EAClB,EACAA,EAAI,SAAW,CACb,KAAK,MAAMA,EAAI,YAAY,GAAKD,EAAW,EAAE,EAC7C,KAAK,MAAMC,EAAI,YAAY,GAAKD,EAAW,EAAE,EAC7CC,EAAI,YAAY,EAClB,EAGJ,OAAOF,CACT,CAEA,eAAeG,GAAaH,EAAgC,CAE1D,IAAMI,EAAWJ,EAAU,KAAMK,GAAMA,EAAE,OAAS,UAAU,EACtDC,EAAYN,EAAU,KAAMK,GAAMA,EAAE,OAAS,WAAW,EACxDE,EAAYP,EAAU,KAAMK,GAAMA,EAAE,OAAS,WAAW,EAC9DD,EAAS,SAAS,KAAOE,EAAU,SAAS,IAAM,IAAMC,EAAU,SAAS,IAAM,IAAM,EACvF,IAAMC,EAAYR,EAAU,KAAMK,GAAMA,EAAE,OAAS,WAAW,EACxDI,EAAaT,EAAU,KAAMK,GAAMA,EAAE,OAAS,YAAY,EAC1DK,EAAaV,EAAU,KAAMK,GAAMA,EAAE,OAAS,YAAY,EAChEG,EAAU,SAAS,KAAOC,EAAW,SAAS,IAAM,IAAMC,EAAW,SAAS,IAAM,IAAM,CAC5F,CAEA,eAAeC,GAAgBtB,EAAeuB,EAAgBX,EAA0D,CAtIxH,IAAAY,EA8IE,IAAMtB,EAA4B,CAAC,EACnC,CAACA,EAAE,GAAqBA,EAAE,aAA+BA,EAAE,QAAyBA,EAAE,MAAwBA,EAAE,QAAiB,GAAIsB,EAAAC,GAAO,YAAP,YAAAD,EAAkB,QAAQxB,EAAO0B,GAAY,WAClL,IAAMC,GAAa,MAAMzB,EAAE,SAAS,KAAK,GAAG,GACtC0B,EAAS,MAAM1B,EAAE,GAAG,KAAK,EACzB2B,EAAY,MAAM3B,EAAE,MAAM,KAAK,EACrC,OAAO,KAAKA,CAAC,EAAE,QAASO,GAAc,UAAQP,EAAEO,EAAO,CAAC,EACxD,IAAMqB,EAAyC,CAAC,EAC1CC,EAAQ,EACd,QAASC,EAAI,EAAGA,EAAIJ,EAAO,OAASG,EAAOC,IAAK,CAC9C,IAAMC,EAAQC,GAAQN,EAAOG,EAAQC,EAAI,EAAE,EACrCG,EAAWD,GAAQN,EAAOG,EAAQC,EAAI,EAAE,EACxCI,EAAW,KAAK,MAAM,IAAMH,EAAQE,EAAWR,CAAS,EAAI,IAC5DU,EAAqB,CAACT,EAAOG,EAAQC,EAAI,GAAKM,GAAU,UAAU,GAAIV,EAAOG,EAAQC,EAAI,GAAKM,GAAU,UAAU,GAAIV,EAAOG,EAAQC,EAAI,GAAK,CAAC,EAC/IO,EAAkB,CAAC,KAAK,MAAM3B,EAAW,GAAKyB,EAAY,EAAE,EAAG,KAAK,MAAMzB,EAAW,GAAKyB,EAAY,EAAE,EAAGA,EAAY,EAAY,EACnIG,EAAkB,CAACX,EAAUE,EAAQC,EAAI,GAAIH,EAAUE,EAAQC,EAAI,GAAIH,EAAUE,EAAQC,EAAI,GAAK,CAAC,EACzGF,EAAkB,KAAK,CAAE,KAAajB,GAAImB,GAAoB,YAAAK,EAAa,SAAAE,EAAU,SAAAC,EAAU,MAAOJ,CAAS,CAAC,CAClH,CACA,GAAIT,GAAaJ,EAAO,KAAK,eAAiB,GAAI,OAAO,KACzDT,GAAagB,CAAiB,EAC9B,IAAMnB,EAAiCD,GAAiBoB,EAAmBlB,CAAU,EAC/E6B,EAAO9B,EAAU,IAAKK,GAAMA,EAAE,QAAQ,EACtC0B,EAAYC,GAAKF,EAAM,CAAC7B,EAAW,GAAIA,EAAW,EAAE,CAAC,EACrDgC,EAAiD,CAAC,EACxD,OAAW,CAACC,EAAMC,CAAO,IAAK,OAAO,QAAeC,EAAS,EAAG,CAC9D,IAAMC,EAAqB,CAAC,EAC5B,QAAShB,EAAI,EAAGA,EAAIc,EAAQ,OAAS,EAAGd,IAAK,CAC3C,IAAMiB,EAAMtC,EAAU,KAAME,GAAQA,EAAI,OAASiC,EAAQd,EAAE,EACrDkB,EAAMvC,EAAU,KAAME,GAAQA,EAAI,OAASiC,EAAQd,EAAI,EAAE,EAC3DiB,GAAOC,GAAKF,EAAG,KAAK,CAACC,EAAI,SAAUC,EAAI,QAAQ,CAAC,CACtD,CACAN,EAAYC,GAAQG,CACtB,CAEA,MADa,CAAE,GAAI,EAAG,MAAO,KAAK,MAAM,IAAMrB,CAAS,EAAI,IAAK,IAAKe,EAAM,IAAK,OAAQA,EAAM,OAAQ,UAAA/B,EAAW,YAAAiC,CAAY,CAE/H,CAgCA,eAAsBO,GAAQnD,EAAeuB,EAAuC,CAClF,IAAMX,EAA+B,CAACZ,EAAM,MAAM,IAAM,EAAGA,EAAM,MAAM,IAAM,CAAC,EACxEoD,GAAY7B,EAAO,KAAK,UAAY,GAAM8B,EAAI,EAAIC,GAClDC,EAAYC,IAAWjC,EAAO,KAAK,YAAc,GACvD,GAAIA,EAAO,aAAe6B,GAAYG,GAAaE,KAAU,KAC3DD,SACK,CACL,IAAMtD,EAA4B,CAAC,EAOnCA,EAAE,UAAY,MAAMH,GAAaC,EAAO,GAAG,EAC3CyD,GAAQ,MAAMnC,GAAgBpB,EAAE,UAAWqB,EAAQX,CAAU,EAe7D,OAAO,KAAKV,CAAC,EAAE,QAASO,GAAc,UAAQP,EAAEO,EAAO,CAAC,EACxD6C,GAAWD,EAAI,EACfG,GAAU,CACZ,CACA,OAAOC,GAAQ,CAACA,EAAK,EAAI,CAAC,CAC5B,CChPO,IAAMC,GAAS,CACpB,CAAE,MAAO,EAAG,MAAO,QAAS,EAC5B,CAAE,MAAO,EAAG,MAAO,SAAU,EAC7B,CAAE,MAAO,EAAG,MAAO,KAAM,EACzB,CAAE,MAAO,EAAG,MAAO,YAAa,EAChC,CAAE,MAAO,EAAG,MAAO,UAAW,EAC9B,CAAE,MAAO,EAAG,MAAO,KAAM,EACzB,CAAE,MAAO,EAAG,MAAO,OAAQ,EAC3B,CAAE,MAAO,EAAG,MAAO,OAAQ,EAC3B,CAAE,MAAO,EAAG,MAAO,MAAO,EAC1B,CAAE,MAAO,GAAI,MAAO,eAAgB,EACpC,CAAE,MAAO,GAAI,MAAO,cAAe,EACnC,CAAE,MAAO,GAAI,MAAO,WAAY,EAChC,CAAE,MAAO,GAAI,MAAO,eAAgB,EACpC,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,KAAM,EAC1B,CAAE,MAAO,GAAI,MAAO,KAAM,EAC1B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,KAAM,EAC1B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,SAAU,EAC9B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,SAAU,EAC9B,CAAE,MAAO,GAAI,MAAO,KAAM,EAC1B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,SAAU,EAC9B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,WAAY,EAChC,CAAE,MAAO,GAAI,MAAO,aAAc,EAClC,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,cAAe,EACnC,CAAE,MAAO,GAAI,MAAO,gBAAiB,EACrC,CAAE,MAAO,GAAI,MAAO,YAAa,EACjC,CAAE,MAAO,GAAI,MAAO,WAAY,EAChC,CAAE,MAAO,GAAI,MAAO,eAAgB,EACpC,CAAE,MAAO,GAAI,MAAO,QAAS,EAC7B,CAAE,MAAO,GAAI,MAAO,YAAa,EACjC,CAAE,MAAO,GAAI,MAAO,KAAM,EAC1B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,QAAS,EAC7B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,QAAS,EAC7B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,QAAS,EAC7B,CAAE,MAAO,GAAI,MAAO,SAAU,EAC9B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,cAAe,EACnC,CAAE,MAAO,GAAI,MAAO,KAAM,EAC1B,CAAE,MAAO,GAAI,MAAO,cAAe,EACnC,CAAE,MAAO,GAAI,MAAO,QAAS,EAC7B,CAAE,MAAO,GAAI,MAAO,IAAK,EACzB,CAAE,MAAO,GAAI,MAAO,QAAS,EAC7B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,QAAS,EAC7B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,YAAa,EACjC,CAAE,MAAO,GAAI,MAAO,WAAY,EAChC,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,SAAU,EAC9B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,cAAe,EACnC,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,OAAQ,EAC5B,CAAE,MAAO,GAAI,MAAO,MAAO,EAC3B,CAAE,MAAO,GAAI,MAAO,UAAW,EAC/B,CAAE,MAAO,GAAI,MAAO,YAAa,EACjC,CAAE,MAAO,GAAI,MAAO,YAAa,EACjC,CAAE,MAAO,GAAI,MAAO,YAAa,CACnC,ECrEA,IAAIC,GACAC,GAAY,EACZC,GAAuB,CAAC,EACxBC,GAAW,EACXC,GAAU,OAAO,iBAErB,eAAsBC,GAAKC,EAAqC,CAE9D,GADIC,EAAI,UAASP,GAAQ,MACpBA,GAKMM,EAAO,OAAOE,EAAI,gBAAiBR,GAAM,QAAW,MALnD,CAEVA,GAAQ,MAAMS,EAAUH,EAAO,OAAO,SAAS,EAC/C,IAAMI,EAAS,OAAO,OAAOV,GAAM,eAAe,MAAS,EAC3DC,GAAY,MAAM,QAAQS,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,CACpF,CACA,OAAOV,EACT,CAEA,eAAeW,GAAQC,EAAoBC,EAA+BP,EAAgB,CACxF,GAAI,CAACM,EAAK,MAAO,CAAC,EAClB,IAAME,EAA4B,CAAC,EAC7BC,EAA+B,CAAC,EAChCC,EAAa,MAAMJ,EAAI,MAAM,EACnCE,EAAE,QAAa,UAAQF,CAAG,EAC1B,IAAMK,EAAS,QAAMH,EAAE,QAAS,EAAG,CAAC,EACpCA,EAAE,MAAW,QAAM,CAACG,EAAI,GAAIA,EAAI,GAAIA,EAAI,GAAIA,EAAI,EAAE,EAAG,CAAC,EACtDH,EAAE,MAAW,UAAQA,EAAE,KAAK,EAC5BA,EAAE,OAAY,UAAQG,EAAI,EAAE,EAC5BH,EAAE,QAAa,UAAQG,EAAI,EAAE,EAC1B,UAAQ,CAACL,EAAK,GAAGK,CAAG,CAAC,EACxBH,EAAE,IAAM,MAAS,QAAM,uBAAuBA,EAAE,MAAOA,EAAE,OAAQR,EAAO,OAAO,YAAaA,EAAO,OAAO,aAAeA,EAAO,OAAO,eAAiB,CAAE,EAC1J,IAAMY,EAAM,MAAMJ,EAAE,IAAI,KAAK,EACzBK,EAAI,EACR,QAAWC,KAAM,MAAM,KAAKF,CAAG,EAAG,CAChC,IAAMG,EAAQ,KAAK,MAAM,IAAML,EAAW,GAAGI,GAAI,EAAE,EAAI,IACjDE,EAAWN,EAAW,GAAGI,GAAI,GAC7BG,EAAQC,GAAOF,GAAU,MACzB,CAACG,EAAGC,CAAC,EAAI,CACbV,EAAW,GAAGI,GAAI,GAAKnB,GACvBe,EAAW,GAAGI,GAAI,GAAKnB,EACzB,EACM0B,EAAc,CAClBF,EACAC,EACAV,EAAW,GAAGI,GAAI,GAAKnB,GAAYwB,EACnCT,EAAW,GAAGI,GAAI,GAAKnB,GAAYyB,CACrC,EACME,EAAW,CACf,KAAK,MAAMD,EAAO,GAAKd,EAAY,EAAE,EACrC,KAAK,MAAMc,EAAO,GAAKd,EAAY,EAAE,EACrC,KAAK,MAAMc,EAAO,GAAKd,EAAY,EAAE,EACrC,KAAK,MAAMc,EAAO,GAAKd,EAAY,EAAE,CACvC,EACAE,EAAQ,KAAK,CAAE,GAAII,IAAK,MAAAE,EAAO,MAAOC,EAAU,MAAAC,EAAO,IAAAK,EAAK,OAAAD,CAAO,CAAC,CACtE,CACA,cAAO,KAAKb,CAAC,EAAE,QAASe,GAAc,UAAQf,EAAEe,EAAO,CAAC,EACjDd,CACT,CAEA,eAAsBe,GAAQC,EAAezB,EAAyC,CACpF,IAAM0B,GAAY1B,EAAO,OAAO,UAAY,GAAM2B,EAAI,EAAI9B,GACpD+B,EAAY9B,IAAWE,EAAO,OAAO,YAAc,GACzD,OAAIA,EAAO,aAAe0B,GAAYE,GAAchC,GAAK,OAAS,GAChEE,KACOF,KAETE,GAAU,EACH,IAAI,QAAQ,MAAO+B,GAAY,CACpC,IAAMC,EAAa,CAACL,EAAM,MAAM,IAAM,EAAGA,EAAM,MAAM,IAAM,CAAC,EACtDM,EAAY,QAAM,eAAeN,EAAO,CAAC9B,GAAWA,EAAS,CAAC,EAC9DqC,EAAUhC,EAAO,OAAO,QAAUN,IAAA,YAAAA,GAAO,QAAQqC,EAAQ,CAAC,oBAAoB,GAAe,KACnGlC,GAAW8B,EAAI,EACZ,UAAQI,CAAM,EAEjB,IAAME,EAAM,MAAM5B,GAAQ2B,EAASF,EAAY9B,CAAM,EACrDJ,GAAOqC,EAEPJ,EAAQI,CAAG,CACb,CAAC,EACH,CC7FA,IAAAC,GAAA,GAAAC,GAAAD,GAAA,eAAAE,GAAA,QAAAC,KAAO,IAAMA,GAAqB,CAChC,OACA,OACA,gBACA,aACA,aACA,QACA,eACA,YACA,YACA,aACA,WACA,YACA,aACA,UACA,WACA,WACF,EAEaD,GAAsC,CACjD,QAAS,CAAC,UAAW,WAAY,WAAW,EAC5C,SAAU,CAAC,WAAY,YAAa,YAAY,EAChD,MAAO,CAAC,eAAgB,gBAAiB,WAAY,UAAW,cAAc,EAC9E,QAAS,CAAC,eAAgB,YAAa,WAAW,EAClD,SAAU,CAAC,gBAAiB,aAAc,YAAY,EACtD,KAAM,CAAC,CACT,ECVA,IAAIE,GACAC,GAAW,EACTC,GAAoB,CAAE,GAAI,EAAG,UAAW,CAAC,EAAG,IAAK,CAAC,EAAG,EAAG,EAAG,CAAC,EAAG,OAAQ,CAAC,EAAG,EAAG,EAAG,CAAC,EAAG,MAAO,EAAG,YAAa,CAAC,CAAuC,EAMtJC,GAAU,OAAO,iBAErB,eAAsBC,GAAKC,EAAqC,CAC9D,OAAIC,EAAI,UAASN,GAAQ,MACpBA,GACIK,EAAO,OAAOE,EAAI,gBAAiBP,GAAM,QAAW,EADjDA,GAAQ,MAAMQ,EAAUH,EAAO,KAAK,SAAS,EAElDL,EACT,CAGA,eAAeS,GAAMC,EAAQC,EAAU,CACrC,GAAM,CAACC,EAAOC,CAAM,EAAIH,EAAO,MACzBI,EAAc,UAAQJ,EAAQ,CAACG,EAASD,CAAK,CAAC,EAC9CG,EAAS,MAAID,EAAU,CAAC,EACxBE,GAAY,MAAMD,EAAI,KAAK,GAAG,GAEpC,GADG,UAAQ,CAACD,EAAUC,CAAG,CAAC,EACtBC,EAAWL,EAAU,CACvB,IAAMM,EAAiB,SAAOH,EAAU,CAAC,EACnCI,EAAS,MAAID,EAAaL,CAAK,EAC/BO,GAAK,MAAMD,EAAI,KAAK,GAAG,GACvBE,EAAS,MAAIH,EAAgB,SAAOL,EAAO,OAAO,CAAC,EACnD,GAAK,MAAMQ,EAAI,KAAK,GAAG,GAC7B,OAAG,UAAQ,CAACF,EAAKE,CAAG,CAAC,EACd,CAACD,EAAG,EAAGH,CAAQ,CACxB,CACA,MAAO,CAAC,EAAG,EAAGA,CAAQ,CACxB,CAEA,eAAsBK,GAAQC,EAAejB,EAAuC,CAClF,IAAMkB,GAAYlB,EAAO,KAAK,UAAY,GAAMmB,EAAI,EAAIvB,GAClDwB,EAAYtB,IAAWE,EAAO,KAAK,YAAc,GACvD,OAAIA,EAAO,aAAekB,GAAYE,GAAa,OAAO,KAAKvB,GAAM,SAAS,EAAE,OAAS,GACvFC,KACO,CAACD,EAAK,IAEfC,GAAU,EACH,IAAI,QAAQ,MAAOuB,GAAY,CA5DxC,IAAAC,EA6DI,IAAMC,EAAY,OAAK,IAAM,CAC3B,GAAI,EAAC5B,IAAA,MAAAA,GAAO,OAAO,GAAG,OAAO,OAAO,KACpC,IAAM6B,EAAY,QAAM,eAAeP,EAAO,CAACtB,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,EAAG,EAAK,EACnG8B,EAAa,MAAID,EAAQE,EAAU,GAAG,EAE5C,OADgB,MAAID,EAASC,EAAU,GAAG,CAE5C,CAAC,EAEGC,EAKJ,GAJI3B,EAAO,KAAK,UAAS2B,EAAOhC,IAAA,YAAAA,GAAO,QAAQ4B,IAC/C3B,GAAWuB,EAAI,EACZ,UAAQI,CAAM,EAEbI,EAAM,CACR9B,GAAM,UAAU,OAAS,EACzB,IAAM+B,EAAUD,EAAK,QAAQ,EAC1B,UAAQA,CAAI,EAEf,IAAME,EAAQD,EAAQ,QAAQ,CAAC,EAC5B,UAAQA,CAAO,EAElB,QAASE,EAAK,EAAGA,EAAKD,EAAM,OAAQC,IAAM,CAExC,GAAM,CAAChB,EAAGiB,EAAGC,CAAS,EAAI,MAAM5B,GAAMyB,EAAMC,GAAK9B,EAAO,KAAK,aAAa,EACtEgC,KAAaV,EAAAtB,EAAO,OAAP,YAAAsB,EAAa,gBAAiB,IAC7CzB,GAAM,UAAU,KAAK,CACnB,MAAO,KAAK,MAAM,IAAMmC,CAAS,EAAI,IACrC,KAAaC,GAAIH,GACjB,YAAa,CAEXhB,EAAInB,GAAM,OAAO,GAAG,MAAM,GAAIoC,EAAIpC,GAAM,OAAO,GAAG,MAAM,EAC1D,EACA,SAAU,CAER,KAAK,MAAMsB,EAAM,MAAM,GAAKH,EAAInB,GAAM,OAAO,GAAG,MAAM,EAAE,EAAG,KAAK,MAAMsB,EAAM,MAAM,GAAKc,EAAIpC,GAAM,OAAO,GAAG,MAAM,EAAE,CACrH,CACF,CAAC,CAEL,CACAkC,EAAM,QAASK,GAAS,UAAQA,CAAC,CAAC,CACpC,CACArC,GAAM,MAAQA,GAAM,UAAU,OAAO,CAACsC,EAAMC,IAAUA,EAAK,MAAQD,EAAOC,EAAK,MAAQD,EAAO,CAAC,EAC/F,IAAMrB,EAAIjB,GAAM,UAAU,IAAKwC,GAAMA,EAAE,SAAS,EAAE,EAC5CN,EAAIlC,GAAM,UAAU,IAAKwC,GAAMA,EAAE,SAAS,EAAE,EAClDxC,GAAM,IAAM,CACV,KAAK,IAAI,GAAGiB,CAAC,EACb,KAAK,IAAI,GAAGiB,CAAC,EACb,KAAK,IAAI,GAAGjB,CAAC,EAAI,KAAK,IAAI,GAAGA,CAAC,EAC9B,KAAK,IAAI,GAAGiB,CAAC,EAAI,KAAK,IAAI,GAAGA,CAAC,CAChC,EACA,IAAMO,EAAOzC,GAAM,UAAU,IAAKwC,GAAMA,EAAE,YAAY,EAAE,EAClDE,EAAO1C,GAAM,UAAU,IAAKwC,GAAMA,EAAE,YAAY,EAAE,EACxDxC,GAAM,OAAS,CACb,KAAK,IAAI,GAAGyC,CAAI,EAChB,KAAK,IAAI,GAAGC,CAAI,EAChB,KAAK,IAAI,GAAGD,CAAI,EAAI,KAAK,IAAI,GAAGA,CAAI,EACpC,KAAK,IAAI,GAAGC,CAAI,EAAI,KAAK,IAAI,GAAGA,CAAI,CACtC,EACA,OAAW,CAACC,EAAMC,CAAO,IAAK,OAAO,QAAeC,EAAS,EAAG,CAC9D,IAAMC,EAAqB,CAAC,EAC5B,QAASC,EAAI,EAAGA,EAAIH,EAAQ,OAAS,EAAGG,IAAK,CAC3C,IAAMC,EAAMhD,GAAM,UAAU,KAAMoC,GAAQA,EAAI,OAASQ,EAAQG,EAAE,EAC3DE,EAAMjD,GAAM,UAAU,KAAMoC,GAAQA,EAAI,OAASQ,EAAQG,EAAI,EAAE,EACjEC,GAAOC,GAAOD,EAAI,OAAS7C,EAAO,KAAK,eAAiB,IAAM8C,EAAI,OAAS9C,EAAO,KAAK,eAAiB,IAAI2C,EAAG,KAAK,CAACE,EAAI,SAAUC,EAAI,QAAQ,CAAC,CACtJ,CACAjD,GAAM,YAAY2C,GAAQG,CAC5B,CACAtB,EAAQ,CAACxB,EAAK,CAAC,CACjB,CAAC,EACH,CCnHA,IAAMkD,GAAc,CAAC,QAAS,UAAW,OAAQ,QAAS,MAAO,WAAY,SAAS,EAClFC,GACEC,GAA0D,CAAC,EAC7DC,GAAY,EACZC,GAAW,EACXC,GAAU,OAAO,iBAErB,eAAsBC,GAAKC,EAAqC,CAtBhE,IAAAC,EAuBE,OAAIC,EAAI,UAASR,GAAQ,MACpBA,GACIM,EAAO,OAAOG,EAAI,gBAAiBT,GAAM,QAAW,EADjDA,GAAQ,MAAMU,GAAUH,EAAAD,EAAO,KAAK,UAAZ,YAAAC,EAAqB,SAAS,EAE3DP,EACT,CAEA,eAAsBW,GAAQC,EAAeN,EAAgBO,EAAaC,EAAoE,CA7B9I,IAAAP,EAAAQ,EA8BE,GAAI,CAACf,GAAO,MAAO,CAAC,EACpB,IAAMgB,EAAYZ,MAAWG,EAAAD,EAAO,KAAK,UAAZ,YAAAC,EAAqB,aAAc,GAC1DU,KAAYF,EAAAT,EAAO,KAAK,UAAZ,YAAAS,EAAqB,WAAY,GAAMG,EAAI,EAAIf,GACjE,OAAIG,EAAO,aAAeW,GAAYD,GAAcd,KAAcY,GAAUb,GAAKY,IAASZ,GAAKY,GAAK,OAAS,GAC3GT,KACOH,GAAKY,KAEdT,GAAU,EACH,IAAI,QAAQ,MAAOe,GAAY,CAtCxC,IAAAZ,EAAAQ,EAuCI,IAAMK,EAAkD,CAAC,EACzD,IAAIb,EAAAD,EAAO,KAAK,UAAZ,MAAAC,EAAqB,QAAS,CAChC,IAAMc,EAA4B,CAAC,EAC7BC,EAAYtB,IAAA,MAAAA,GAAO,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EACtEqB,EAAE,OAAY,QAAM,eAAeT,EAAO,CAACU,EAAWA,CAAS,EAAG,EAAK,EASvED,EAAE,SAAc,MAAIA,EAAE,OAAQE,EAAU,GAAG,EAC3CF,EAAE,UAAe,MAAIA,EAAE,SAAU,EAAG,EAAI,EACxCA,EAAE,aAAkB,MAAIA,EAAE,UAAWE,EAAU,IAAI,EACnDF,EAAE,aAAkB,MAAIA,EAAE,aAAcE,EAAU,GAAG,EACrDF,EAAE,QAAUrB,IAAA,YAAAA,GAAO,QAAQqB,EAAE,cAC7BlB,GAAWe,EAAI,EACf,IAAMM,EAAO,MAAMH,EAAE,QAAQ,KAAK,EAClC,QAASI,EAAI,EAAGA,EAAID,EAAK,OAAQC,IAC3BD,EAAKC,MAAMV,EAAAT,EAAO,KAAK,UAAZ,YAAAS,EAAqB,gBAAiB,IAAIK,EAAI,KAAK,CAAE,MAAO,KAAK,IAAI,IAAM,KAAK,MAAM,IAAMI,EAAKC,EAAE,EAAI,GAAG,EAAG,QAAS1B,GAAY0B,EAAc,CAAC,EAElKL,EAAI,KAAK,CAACM,EAAGC,IAAMA,EAAE,MAAQD,EAAE,KAAK,EACpC,OAAO,KAAKL,CAAC,EAAE,QAASO,GAAc,UAAQP,EAAEO,EAAO,CAAC,CAC1D,CACA3B,GAAKY,GAAOO,EACZlB,GAAYY,EACZK,EAAQC,CAAG,CACb,CAAC,EACH,CCtDA,IAAIS,GACEC,GAAwB,CAAC,EAC3BC,GAAY,EACZC,GAAW,EACXC,GAAU,OAAO,iBAErB,eAAsBC,GAAKC,EAAqC,CAC9D,OAAIC,EAAI,UAASP,GAAQ,MACpBA,GACIM,EAAO,OAAOE,EAAI,gBAAiBR,GAAM,QAAW,EADjDA,GAAQ,MAAMS,EAAUH,EAAO,KAAK,cAAiB,SAAS,EAEnEN,EACT,CAoBA,eAAsBU,GAAQC,EAAeL,EAAgBM,EAAKC,EAA0B,CA9C5F,IAAAC,EAAAC,EA+CE,GAAI,CAACf,GAAO,MAAO,CAAC,EACpB,IAAMgB,EAAYZ,MAAWU,EAAAR,EAAO,KAAK,YAAZ,YAAAQ,EAA0B,aAAc,GAC/DG,KAAYF,EAAAT,EAAO,KAAK,YAAZ,YAAAS,EAA0B,WAAY,GAAMG,EAAI,EAAIf,GACtE,OAAIG,EAAO,aAAeW,GAAYD,GAAcd,KAAcW,GAAUZ,GAAKW,IAC/ER,KACOH,GAAKW,IAEP,IAAI,QAAQ,MAAOO,GAAY,CAtDxC,IAAAL,EAuDI,IAAIM,EAAsB,CAAC,EAC3B,KAAIN,EAAAR,EAAO,KAAK,YAAZ,YAAAQ,EAA0B,WAAWd,IAAA,YAAAA,GAAO,OAAO,GAAG,OAAO,CAC/D,IAAMqB,EAA4B,CAAC,EACnCA,EAAE,KAAU,QAAM,eAAeV,EAAO,CAACX,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,EAAG,EAAK,EAInGqB,EAAE,KAAOrB,IAAA,YAAAA,GAAO,QAAQqB,EAAE,MAa1B,IAAMC,EAAS,MAAMD,EAAE,KAAK,KAAK,EACjCD,EAAO,MAAM,KAAKE,CAAM,CAC1B,CACArB,GAAKW,GAAOQ,EACZlB,GAAYW,EACZV,GAAWe,EAAI,EACfC,EAAQC,CAAI,CACd,CAAC,CACH,CCzEA,IAAIG,GACAC,GAAY,EAEVC,GAAc,IAEdC,GAAqBC,GAAgB,cACrCC,GAAsBD,GAAgB,eAEtCE,GAAe,CACnB,WAAY,CAACH,GAAY,GAAIA,GAAYA,GAAY,OAAS,EAAE,EAChE,YAAa,CAACE,GAAa,GAAIA,GAAaA,GAAa,OAAS,EAAE,CACtE,EAEME,GAAgB,CACpB,YAAa,EACb,YAAa,EACb,MAAO,GACP,eAAgB,EAClB,EAEA,eAAsBC,GAAKC,EAAqC,CA9BhE,IAAAC,EA+BE,OAAIC,EAAI,UAASX,GAAQ,MACpBA,GACIS,EAAO,OAAOG,EAAI,gBAAiBZ,GAAM,QAAW,EADjDA,GAAQ,MAAMa,GAAUH,EAAAD,EAAO,KAAK,OAAZ,YAAAC,EAAkB,SAAS,EAE/DT,GAAYD,GAAM,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EAC3DC,KAAc,KAAIA,GAAY,IAC3BD,EACT,CAGO,SAASc,GAAkBC,EAAWC,EAAWC,EAAQC,EAAM,CACpE,QAASC,EAAI,EAAGA,EAAWC,GAAY,OAAQD,IAAK,CAClD,GAAM,CAAE,IAAAE,EAAK,QAAAC,CAAQ,EAAWF,GAAYD,GACtCI,EAAyBnB,GAAgB,GAAGa,IAASI,KAC3D,GAAI,CAACH,GAAQA,EAAK,SAASG,CAAG,EAC5B,QAASG,EAAI,EAAGA,EAAIF,EAAQ,OAAQE,IAAK,CACvC,IAAMC,EAAQH,EAAQE,GACtBT,EAAUQ,EAAgBC,IAAM,CAC9BR,EAAUS,GAAO,GACjBT,EAAUS,GAAO,IAChBT,EAAUS,GAAO,GAAKV,EAAUQ,EAAgBC,IAAI,IAAM,CAC7D,CACF,CAEJ,CACF,CAEO,IAAME,GAAoCX,GAAc,CAC7D,IAAMY,EAAWZ,EAAUT,GAAa,WAAW,IAAI,GACjDsB,EAAYb,EAAUT,GAAa,YAAY,IAAI,GACzD,OAAOqB,EAAWC,CACpB,EAGaC,GAAY,CAACd,EAAWe,EAAMC,EAAqBC,EAAqBC,EAAUC,EAAO,KAAU,CAC9G,IAAMC,EAAWC,GAAiBC,GAAgBC,GAA8B,CAACvB,EAAUgB,GAAsBhB,EAAUiB,EAAoB,CAAC,EAAG9B,EAAW,CAAC,EACzJqC,EAAeC,GAAWL,CAAG,EAC/BM,EAAU,QAAM,cAAcX,EAAM,CAAC,CACvCK,EAAI,WAAW,GAAKF,EACpBE,EAAI,WAAW,GAAKF,EAAUE,EAAI,SAAS,GAAKF,EAChDE,EAAI,SAAS,GAAKF,CACpB,CAAC,EAAG,CAAC,CAAC,EAAG,CAAChC,GAAWA,EAAS,CAAC,EAC/B,GAAIiC,GAAQvB,EAAI,QAAQ,SAAS,eAAe,EAAG,CACjD,IAAM+B,EAAa,QAAM,cAAcD,CAAI,EACxC,UAAQA,CAAI,EACfA,EAAOC,CACT,CACA,MAAO,CAAE,IAAAP,EAAK,QAAAI,EAAS,KAAAE,CAAK,CAC9B,EAGaE,GAAe,CAACC,EAASC,EAAQC,EAAYZ,EAAO,KAAU,CACzE,IAAMa,EAA6B,CAAC,EACpC,QAAS5B,EAAI,EAAGA,EAAIZ,GAAc,eAAgBY,IAAK,CACrD,IAAM6B,EAAIJ,EAAQzB,EAAI,GAChB8B,EAAIL,EAAQzB,EAAI,EAAI,GACpB+B,EAAIN,EAAQzB,EAAI,EAAI,GAC1B4B,EAAa,KAAK,EACfb,EAAQ,EAAKc,EAAI/C,GAAe+C,EAAI/C,IAAc6C,EAAW,GAAKD,EAAO,WAAW,GACpFI,EAAIhD,GAAa6C,EAAW,GAAKD,EAAO,WAAW,GAAIK,CAC1D,CAAC,CACH,CACA,MAAO,CAAE,UAAWH,EAAc,KAAMA,EAAa,MAAMxC,GAAc,KAAK,CAAE,CAClF,EAGa4C,GAAwB,CAACpC,EAAWqC,EAAYC,IAAc,CACzE,IAAMC,EAAevC,EAAiBX,GAAgB,GAAGiD,cAAsB9C,GAAc,cAAc,GACrGgD,EAAexC,EAAiBX,GAAgB,GAAGiD,cAAsB9C,GAAc,cAAc,GACrGiD,GAAYF,EAAeC,GAAgB,EAEjD,OAAOH,EAAW,IAAI,CAACK,EAAO,IAAM,CAClC,IAAIP,EAAIM,EACR,OAAI,IAAM,EACRN,EAAII,EACK,IAAM,IACfJ,EAAIK,GAEC,CAACE,EAAM,GAAIA,EAAM,GAAIP,CAAC,CAC/B,CAAC,CACH,EAEA,eAAsBQ,GAAY3C,EAAWe,EAAMrB,EAAQwB,EAAU,CACnE,GAAI,CAACjC,GACH,OAAIS,EAAO,OAAOG,EAAI,6DAA6D,EAC5EG,EAET,GAAM,CAAE,IAAK4C,EAAY,QAASC,EAAgB,KAAMC,CAAY,EAAIhC,GAAUd,EAAWe,EAAMxB,GAAa,WAAW,GAAIA,GAAa,WAAW,GAAI2B,EAAU,EAAI,EACnK,CAAE,IAAK6B,EAAa,QAASC,EAAiB,KAAMC,CAAa,EAAInC,GAAUd,EAAWe,EAAMxB,GAAa,YAAY,GAAIA,GAAa,YAAY,GAAI2B,EAAU,EAAI,EACxKgC,EAAc,SAAO,CAACJ,EAAaG,CAAY,CAAC,EACnD,UAAQH,CAAW,EACnB,UAAQG,CAAY,EACvB,IAAME,EAAiBlE,GAAM,QAAQiE,CAAQ,EAC1C,UAAQA,CAAQ,EACnB,IAAME,EAAqB,MAAMD,EAAe,KAAK,EAClD,UAAQA,CAAc,EACzB,IAAME,EAAcD,EAAmB,MAAM,EAAG5D,GAAc,eAAiB,CAAC,EAC1E,CAAE,UAAW8D,EAAkB,KAAMC,CAAkB,EAAI3B,GAAayB,EAAaT,EAAYC,EAAgB,EAAI,EACrHW,EAAeJ,EAAmB,MAAM5D,GAAc,eAAiB,CAAC,EACxE,CAAE,UAAWiE,EAAmB,KAAMC,CAAmB,EAAI9B,GAAa4B,EAAcT,EAAaC,EAAiB,EAAK,EAC3HW,EAAgChD,GAAiCX,CAAS,EAC5E,KAAK,IAAI2D,CAA6B,EAAI,IAC5C5D,GAAkBC,EAAWsD,EAAkB,OAAQ,IAAI,EAC3DvD,GAAkBC,EAAWyD,EAAmB,QAAS,IAAI,GAEpDE,EAAgC,EACzC5D,GAAkBC,EAAWsD,EAAkB,OAAQ,CAAC,YAAa,WAAW,CAAC,EAEjFvD,GAAkBC,EAAWyD,EAAmB,QAAS,CAAC,YAAa,WAAW,CAAC,EAErF,IAAMG,EAAyBxB,GAAsBpC,EAAWuD,EAAmB,MAAM,EACnFM,EAA0BzB,GAAsBpC,EAAW0D,EAAoB,OAAO,EAE5F,OADkB1D,EAAU,OAAO4D,CAAsB,EAAE,OAAOC,CAAuB,CAE3F,CC3IA,IAAMC,GAA8B,CACl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kC,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAEjOC,GAAsC,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAErIC,GAAmC,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAElFC,GAAmC,CAAC,CAAC,GAAI,CAAC,EAAG,CAAC,EAAG,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAE5NC,GAAuC,CAAC,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,CAAC,EAEzHC,GAAoC,CAAC,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,CAAC,EAEnFC,GAAmC,CACvC,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EACpN,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,EAAG,CAAC,GAAI,GAAG,EAAG,CAAC,IAAK,EAAE,CAC5M,EAmJA,SAASC,GAAqBC,EAAwB,CACpD,IAAMC,EAAUD,EAAY,IAAKE,GAAeA,EAAW,EAAE,EAC7D,OAAAD,EAAQ,KAAKD,EAAYA,EAAY,OAAS,GAAG,EAAE,EAC5CC,CACT,CAEO,IAAME,GAA2C,CACtD,KAAMJ,GAAqBK,EAAgB,EAC3C,QAASL,GAAqBM,EAAoB,EAClD,YAAaN,GAAqBO,EAAwB,EAC1D,SAAUP,GAAqBQ,EAAqB,EACpD,SAAUR,GAAqBS,EAAqB,EACpD,aAAcT,GAAqBU,EAAyB,EAC5D,UAAWV,GAAqBW,EAAsB,EACtD,SAAUX,GAAqBY,EAAqB,CACtD,EAEMC,GAA2C,OAAO,QAAQT,EAAwC,EACrG,IAAI,CAAC,CAACU,EAAOZ,CAAO,IAAMA,EAAQ,IAAKa,GAAU,CAACA,EAAOD,CAAK,CAAqB,CAAC,EACpF,KAAK,EAEKE,GAAgC,IAAI,IAAIH,EAAe,EAQvDI,GAAmC,CAC9C,GAAI,IAAK,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAC9C,IAAK,GAAI,GAAI,GAAI,EAAG,IAAK,IAAK,IAAK,IACnC,GAAI,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAC7C,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IACpC,GAAI,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAC7C,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,IACpC,GAAI,GAAI,GAAI,IAAK,GAAI,GAAI,IAAK,IAAK,IAAK,IAAK,IAC7C,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IAAK,IAAK,GACtC,EAEaC,GAAuC,CAClD,GAAI,EAAG,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACrC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC9B,IAAK,GAAI,IAAK,GAAI,GAAI,GAAI,GAAI,IAAK,IACnC,IAAK,GAAI,GAAI,GAAI,GAAI,GAAI,IACzB,IAAK,GAAI,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACvC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC9B,GAAI,IAAK,GAAI,GAAI,GAAI,GACrB,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACxC,IAAK,GAAI,GAAI,IAAK,GAAI,IAAK,GAAI,GACjC,EAEaC,GAAwC,CACnD,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACxC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC9B,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACxC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC9B,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACxC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAC9B,IAAK,IAAK,IAAK,IAAK,IAAK,IACzB,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IACxC,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,IAAK,GACrC,ECvOA,eAAsBC,GAAQC,EAAWC,EAAmB,CAC1D,IAAMC,EAAkC,CAGtC,KAAM,MAAMD,EAAQ,OAAQE,GAAMA,EAAE,OAAS,GAAG,EAAE,GAAG,KAAK,EAC1D,MAAO,MAAMF,EAAQ,OAAQE,GAAMA,EAAE,OAAS,EAAE,EAAE,GAAG,KAAK,EAC1D,KAAM,MAAMF,EAAQ,OAAQE,GAAMA,EAAE,OAAS,GAAG,EAAE,GAAG,KAAK,EAC1D,MAAO,MAAMF,EAAQ,OAAQE,GAAMA,EAAE,OAAS,EAAE,EAAE,GAAG,KAAK,EAC1D,KAAM,MAAMF,EAAQ,OAAQE,GAAMA,EAAE,OAAS,GAAG,EAAE,GAAG,KAAK,CAC5D,EAGMC,EAAuBC,GAAqC,OAAO,CAACC,EAAMC,IAASD,GAAQN,EAAUO,GAAM,GAAI,CAAC,EAAcF,GAAqC,OACzK,QAASG,EAAI,EAAGA,EAAIN,EAAE,MAAM,OAAS,EAAGM,IAAKR,EAAU,KAAK,CAACE,EAAE,MAAM,EAAIM,EAAI,GAAIN,EAAE,MAAM,EAAIM,EAAI,GAAIJ,CAAU,CAAC,EAChH,IAAMK,EAAuBC,GAAsC,OAAO,CAACJ,EAAMC,IAASD,GAAQN,EAAUO,GAAM,GAAI,CAAC,EAAcG,GAAsC,OAC3K,QAASF,EAAI,EAAGA,EAAIN,EAAE,MAAM,OAAS,EAAGM,IAAKR,EAAU,KAAK,CAACE,EAAE,MAAM,EAAIM,EAAI,GAAIN,EAAE,MAAM,EAAIM,EAAI,GAAIC,CAAU,CAAC,EAGhH,QAASD,EAAI,EAAGA,EAAIN,EAAE,KAAK,OAAS,EAAGM,IAAKR,EAAoBK,GAAqCG,IAAM,CAACN,EAAE,KAAK,EAAIM,EAAI,GAAIN,EAAE,KAAK,EAAIM,EAAI,GAAIR,EAAoBK,GAAqCG,IAAI,EAAE,EACjN,QAASA,EAAI,EAAGA,EAAIN,EAAE,KAAK,OAAS,EAAGM,IAAKR,EAAoBU,GAAsCF,IAAM,CAACN,EAAE,KAAK,EAAIM,EAAI,GAAIN,EAAE,KAAK,EAAIM,EAAI,GAAIR,EAAoBU,GAAsCF,IAAI,EAAE,EAGnN,QAASA,EAAI,EAAGA,EAAIN,EAAE,KAAK,OAAS,EAAGM,IAAKR,EAAoBW,GAAiCH,IAAM,CAACN,EAAE,KAAK,EAAIM,EAAI,GAAIN,EAAE,KAAK,EAAIM,EAAI,GAAIR,EAAoBW,GAAiCH,IAAI,EAAE,EAEzM,OAAOR,CACT,CCHA,IAAMY,GAAQ,CACZ,MAAO,CAAC,EACR,QAAS,OAAO,iBAChB,UAAW,CACb,EAEIC,GAA2B,KAC3BC,GAAY,EAEhB,eAAsBC,GAAQC,EAAeC,EAAuC,CAlCpF,IAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAoCE,IAAMC,KAAYX,EAAAD,EAAO,KAAK,WAAZ,YAAAC,EAAsB,WAAY,GAAMY,EAAI,EAAIlB,GAAM,UAClEmB,EAAYnB,GAAM,WAAWO,EAAAF,EAAO,KAAK,WAAZ,YAAAE,EAAsB,aAAc,GACnE,CAACF,EAAO,aAAe,CAACY,GAAY,CAACE,GAAanB,GAAM,MAAM,SAAW,GAC3EA,GAAM,MAAQ,MAAgBoB,GAAShB,EAAOC,CAAM,EACpDL,GAAM,UAAYkB,EAAI,EACtBlB,GAAM,QAAU,GAEhBA,GAAM,UAER,IAAMqB,EAA2B,CAAC,EAC5BC,EAA6B,CAAC,EAChCC,EAAK,EACT,QAASC,EAAI,EAAGA,EAAIxB,GAAM,MAAM,OAAQwB,IAAK,CAC3C,IAAMC,EAAMzB,GAAM,MAAMwB,GACpBE,EAAQ,EACRC,EACEC,EAAmB,CACvB,GAAIL,IACJ,KAAM,CAAC,EACP,QAAS,CAAC,EACV,IAAK,CAAC,EAAG,EAAG,EAAG,CAAC,EAChB,OAAQ,CAAC,EAAG,EAAG,EAAG,CAAC,EACnB,MAAO,EACP,SAAU,EACV,UAAW,EAGX,YAAa,CAAC,CAChB,EAIA,GADA,CAACG,EAAOC,EAAgBC,EAAK,MAAM,EAASC,IAAoBrB,EAAAH,EAAO,KAAK,WAAZ,YAAAG,EAAsB,SAAUiB,EAAKrB,GAAOK,EAAAJ,EAAO,KAAK,OAAZ,MAAAI,EAAkB,QAAUP,GAAsB4B,GAAK,CAAC,GAChKpB,EAAAL,GAAA,YAAAA,EAAQ,SAAR,MAAAK,EAAgB,aAAc,CAChC,IAAMqB,EAAY,MAAMC,GAAsBJ,EAAK,MAAgB,EAChE,UAAQA,EAAK,MAAM,EACtBA,EAAK,OAASG,CAChB,CAEA,GADAH,EAAK,SAAW,KAAK,MAAM,IAAMH,EAAI,UAAU,EAAI,KAC9Cd,EAAAN,EAAO,KAAK,OAAZ,MAAAM,EAAkB,QAYhB,GAAI,CAACV,GACNI,EAAO,OAAO4B,EAAI,wDAAwD,MACzE,CACL,IAAMC,EAAUjC,GAAM,QAAQ2B,EAAK,MAAgB,EAE7CO,EAAiB,MADHD,EAAQ,KAAME,GAAMA,EAAE,MAAMA,EAAE,MAAM,OAAS,KAAO,CAAC,EAChC,KAAK,EAG9C,GAFAR,EAAK,UAAY,KAAK,MAAM,IAAMO,EAAe,EAAE,EAAI,IAEnDP,EAAK,aAAahB,EAAAP,EAAO,KAAK,WAAZ,YAAAO,EAAsB,gBAAiB,IAE3D,GADAa,EAAI,WAAaG,EAAK,WAClBf,EAAAR,EAAO,KAAK,OAAZ,MAAAQ,EAAkB,YAAa,CACjCe,EAAK,IAAWS,GAASZ,EAAKrB,CAAK,EACnCwB,EAAK,OAAcU,GAAUb,EAAKrB,CAAK,EACvCwB,EAAK,MAAQA,EAAK,SAClBA,EAAK,KAAOH,EAAI,UAAU,IAAKc,GAAO,EAClCd,EAAI,WAAW,GAAKA,EAAI,SAAS,IAAO,GAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAMc,EAAG,GAAeT,GAAK,GAC5GL,EAAI,WAAW,GAAKA,EAAI,SAAS,IAAO,GAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAMc,EAAG,GAAeT,GAAK,CAChH,CAAC,EACDF,EAAK,QAAUA,EAAK,KAAK,IAAKW,GAAO,CAACA,EAAG,IAAMnC,EAAM,MAAM,IAAM,GAAImC,EAAG,IAAMnC,EAAM,MAAM,IAAM,IAAKmC,EAAG,IAAM,GAAKrC,EAAS,CAAC,EAC7H,QAAWsC,KAAO,OAAO,KAAYC,EAAkB,EACrDb,EAAK,YAAYY,GAAO,CAACZ,EAAK,KAAYa,GAAmBD,GAAe,CAEhF,MACK,CACL,IAAME,EAAQR,EAAQ,KAAME,GAAMA,EAAE,MAAMA,EAAE,MAAM,OAAS,KAAO,IAAI,EAChEO,EAAoB,UAAQD,EAAO,CAAC,GAAI,CAAC,CAAC,EAC5CE,EAAY,MAAMD,EAAe,MAAM,EACxC,UAAQA,CAAc,GACrB7B,EAAAT,EAAO,KAAK,YAAZ,MAAAS,EAAuB,QACzB8B,EAAY,MAAgBC,GAAQD,EAAWV,CAAO,GAC7CnB,EAAAV,EAAO,KAAK,OAAZ,MAAAU,EAAkB,UAC3B6B,EAAY,MAAWE,GAAYF,EAAWhB,EAAK,OAAQvB,EAAQH,EAAS,GAE9E0B,EAAK,KAAYmB,GAAmBH,EAAWnB,EAAKC,EAAOC,EAAgBzB,EAAS,EACpF0B,EAAK,QAAUA,EAAK,KAAK,IAAKW,GAAO,CAACA,EAAG,IAAMnC,EAAM,MAAM,IAAM,GAAImC,EAAG,IAAMnC,EAAM,MAAM,IAAM,IAAKmC,EAAG,IAAM,GAAKrC,EAAS,CAAC,EAC7H,QAAWsC,KAAO,OAAO,KAAYQ,EAAe,EAAGpB,EAAK,YAAYY,GAAcQ,GAAgBR,GAAK,IAAKS,IAAUrB,EAAK,KAAKqB,GAAM,EAC1IrB,EAAK,MAAQA,EAAK,UAClB,IAAMsB,GAAgB,CAAE,GAAQC,GAAiBvB,EAAK,KAAMH,CAAG,EAAG,WAAYA,EAAI,WAAY,UAAWA,EAAI,SAAU,EACvHG,EAAK,IAAWS,GAASa,GAAe9C,CAAK,EAC7CwB,EAAK,OAAcU,GAAUY,GAAe9C,CAAK,EAQjDkB,EAAS,KAAK4B,EAAa,CAC7B,CACG,UAAQhB,CAAO,CACpB,KA9DgC,CAC9BN,EAAK,IAAWS,GAASZ,EAAKrB,CAAK,EACnCwB,EAAK,OAAcU,GAAUb,EAAKrB,CAAK,EACvCwB,EAAK,MAAQA,EAAK,SAClBA,EAAK,KAAOH,EAAI,UAAU,IAAKc,GAAO,EAClCd,EAAI,WAAW,GAAKA,EAAI,SAAS,IAAO,GAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAMc,EAAG,GAAeT,GAAK,GAC5GL,EAAI,WAAW,GAAKA,EAAI,SAAS,IAAO,GAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAMc,EAAG,GAAeT,GAAK,CAChH,CAAC,EACDF,EAAK,QAAUA,EAAK,KAAK,IAAKW,GAAO,CAACA,EAAG,IAAMnC,EAAM,MAAM,IAAM,GAAImC,EAAG,IAAMnC,EAAM,MAAM,IAAM,IAAKmC,EAAG,IAAM,GAAKrC,EAAS,CAAC,EAC7H,QAAWsC,KAAO,OAAO,KAAYC,EAAkB,EACrDb,EAAK,YAAYY,GAAO,CAACZ,EAAK,KAAYa,GAAmBD,GAAe,CAEhF,CAmDIZ,EAAK,SAASZ,EAAAX,EAAO,KAAK,WAAZ,YAAAW,EAAsB,gBAAiB,GAAIK,EAAM,KAAKO,CAAI,EACpE,UAAQA,EAAK,MAAM,CAC7B,CACA,OAAA5B,GAAM,MAAQsB,EACPD,CACT,CAEA,eAAsB+B,GAAK/C,EAAqC,CAhJhE,IAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAiJE,OAAI0C,EAAI,UAASpD,GAAQ,QAErBM,GAAAD,EAAAD,GAAA,YAAAA,EAAQ,OAAR,YAAAC,EAAc,YAAd,YAAAC,EAAyB,WAAWN,IAAA,YAAAA,GAAO,YAEzC,OAAO,OAAKO,EAAAP,IAAA,YAAAA,GAAO,YAAP,YAAAO,EAAkB,UAAW,CAAC,CAAC,EAAE,OAAS,IAAGP,GAAQ,MAElEA,GAGMI,EAAO,OAChB4B,EAAI,gBAAiBhC,GAAM,QAAW,GAHlCQ,EAAAJ,EAAO,KAAK,YAAZ,MAAAI,EAAuB,QAASR,GAAQ,MAAMqD,GAAU5C,EAAAL,EAAO,KAAK,YAAZ,YAAAK,EAAuB,SAAS,EACvFT,GAAQ,MAAMqD,GAAU3C,EAAAN,EAAO,KAAK,OAAZ,YAAAM,EAAkB,SAAS,EAI1DT,GAAYD,GAAM,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EACxDA,EACT,CAEO,IAAMsD,GAAuBC,GACvBC,GAAeC,GC9I5B,IAAIC,GACEC,GAKD,CAAC,EAEFC,GAAW,EACXC,GAAY,EACZC,GAAU,OAAO,iBAErB,eAAsBC,GAAKC,EAAqC,CAhChE,IAAAC,EAiCE,OAAIC,EAAI,UAASR,GAAQ,MACpBA,GACIM,EAAO,OAAOG,EAAI,gBAAiBT,GAAM,QAAW,EADjDA,GAAQ,MAAMU,GAAUH,EAAAD,EAAO,KAAK,cAAZ,YAAAC,EAAyB,SAAS,EAE/DP,EACT,CAEO,SAASW,GAAQC,EAAe,CACrC,IAAMC,EAAUD,EAAM,OAASA,EAAM,QAAUA,EAC/C,GAAI,EAACZ,IAAA,MAAAA,GAAO,OAAO,GAAG,OAAO,OAAOa,EACpC,IAAMC,EAAU,QAAM,eAAeD,EAAQ,CAACb,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,EAAG,EAAK,EAClGe,EAAU,MAAID,EAAME,EAAU,KAAK,EACzC,OAAG,UAAQF,CAAI,EACRC,CAkBT,CAEA,eAAsBE,GAAQC,EAAeZ,EAAgBa,EAAaC,EAAiC,CAjE3G,IAAAb,EAAAc,EAAAC,EAAAC,EAkEE,GAAI,CAACvB,GAAO,MAAO,CAAE,IAAK,EAAG,OAAQ,UAAW,YAAa,EAAG,WAAY,CAAC,CAAE,EAC/E,IAAMwB,EAAYpB,MAAWG,EAAAD,EAAO,KAAK,cAAZ,YAAAC,EAAyB,aAAc,GAC9DkB,KAAYJ,EAAAf,EAAO,KAAK,cAAZ,YAAAe,EAAyB,WAAY,GAAMK,EAAI,EAAIxB,GACrE,OAAII,EAAO,aAAekB,GAAaC,GAAatB,KAAciB,KAAUE,EAAArB,GAAKkB,KAAL,YAAAG,EAAW,QAAQC,EAAAtB,GAAKkB,KAAL,YAAAI,EAAW,KAAM,GAC9GnB,KACOH,GAAKkB,KAEdf,GAAU,EACH,IAAI,QAAQ,MAAOuB,GAAY,CA1ExC,IAAApB,EAAAc,EA2EI,IAAMO,EAAM,CACV,IAAa,EACb,OAAgB,UAChB,YAAqB,EACrB,WAAsB,CAAC,CACzB,EAEA,IAAIrB,EAAAD,EAAO,KAAK,cAAZ,MAAAC,EAAyB,QAAS,CACpC,IAAMsB,EAAWlB,GAAQO,CAAK,EACxBY,EAAO9B,IAAA,YAAAA,GAAO,QAAQ6B,GAC5B3B,GAAWwB,EAAI,EACZ,UAAQG,CAAQ,EAEnB,IAAME,EAAS,MADC,MAAMD,EAAK,KAAME,GAAMA,EAAE,MAAM,KAAO,CAAC,GAC1B,KAAK,EAC5BC,EAAa,KAAK,MAAM,IAAM,KAAK,IAAKF,EAAO,GAAK,EAAI,CAAC,EAAI,IAC/DE,KAAcZ,EAAAf,EAAO,KAAK,cAAZ,YAAAe,EAAyB,gBAAiB,KAC1DO,EAAI,OAASG,EAAO,IAAM,GAAM,SAAW,OAC3CH,EAAI,YAAc,KAAK,IAAI,IAAMK,CAAU,GAE7C,IAAMC,EAAY,SAAOJ,EAAK,KAAME,GAAMA,EAAE,MAAM,KAAO,GAAG,EAAG,CAAC,EAC1DG,GAAO,MAAMD,EAAO,KAAK,GAAG,GAC/B,UAAQA,CAAM,EAEjB,IAAME,EAAM,MADCN,EAAK,KAAME,GAAMA,EAAE,MAAM,KAAO,GAAG,EACzB,KAAK,EAC5BJ,EAAI,IAAM,KAAK,MAAMQ,EAAID,EAAM,GAAKC,EAAID,EAAM,GAAK,GAAKA,EAAM,IAAMC,EAAID,EAAM,GAAK,GAAKA,EAAM,IAAMC,EAAID,EAAM,EAAE,EAAI,GAEpH,IAAME,EAAOP,EAAK,KAAME,GAAMA,EAAE,MAAM,KAAO,IAAI,EAG3CM,EAAaD,EAAO,MAAMA,EAAK,KAAK,EAAc,CAAC,EACzDT,EAAI,WAAa,MAAM,KAAKU,CAAU,EACtCR,EAAK,QAASE,GAAS,UAAQA,CAAC,CAAC,CACnC,CACA/B,GAAKkB,GAAOS,EACZzB,GAAYiB,EACZO,EAAQC,CAAG,CACb,CAAC,EACH,CC7GO,SAASW,GAAWC,EAAK,CAC9B,MAAO,CACL,KAAK,IAAIA,EAAI,SAAS,GAAKA,EAAI,WAAW,EAAE,EAC5C,KAAK,IAAIA,EAAI,SAAS,GAAKA,EAAI,WAAW,EAAE,CAC9C,CACF,CAEO,SAASC,GAAaD,EAAK,CAChC,MAAO,CACLA,EAAI,WAAW,IAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAM,EAC5DA,EAAI,WAAW,IAAMA,EAAI,SAAS,GAAKA,EAAI,WAAW,IAAM,CAC9D,CACF,CAEO,SAASE,GAAyBF,EAAKG,EAAOC,EAAU,CAC7D,IAAMC,EAAIF,EAAM,MAAM,GAChBG,EAAIH,EAAM,MAAM,GAChBI,EAAQ,CAAC,CACbP,EAAI,WAAW,GAAKK,EACpBL,EAAI,WAAW,GAAKM,EACpBN,EAAI,SAAS,GAAKK,EAClBL,EAAI,SAAS,GAAKM,CACpB,CAAC,EACD,OAAU,QAAM,cAAcH,EAAOI,EAAO,CAAC,CAAC,EAAGH,CAAQ,CAC3D,CAEO,SAASI,GAAoBR,EAAKS,EAAQ,CAC/C,IAAMC,EAAa,CAACV,EAAI,WAAW,GAAKS,EAAO,GAAIT,EAAI,WAAW,GAAKS,EAAO,EAAE,EAC1EE,EAAW,CAACX,EAAI,SAAS,GAAKS,EAAO,GAAIT,EAAI,SAAS,GAAKS,EAAO,EAAE,EACpEG,EAAgBZ,EAAI,cAAc,IAAKa,GACvB,CAACA,EAAM,GAAKJ,EAAO,GAAII,EAAM,GAAKJ,EAAO,EAAE,CAEhE,EACD,MAAO,CAAE,WAAAC,EAAY,SAAAC,EAAU,cAAAC,EAAe,WAAYZ,EAAI,UAAW,CAC3E,CAEO,SAASc,GAAWd,EAAKS,EAAS,IAAK,CAC5C,IAAMM,EAASd,GAAaD,CAAG,EACzBgB,EAAOjB,GAAWC,CAAG,EACrBiB,EAAc,CAACR,EAASO,EAAK,GAAK,EAAGP,EAASO,EAAK,GAAK,CAAC,EACzDN,EAAa,CAACK,EAAO,GAAKE,EAAY,GAAIF,EAAO,GAAKE,EAAY,EAAE,EACpEN,EAAW,CAACI,EAAO,GAAKE,EAAY,GAAIF,EAAO,GAAKE,EAAY,EAAE,EACxE,MAAO,CAAE,WAAAP,EAAY,SAAAC,EAAU,cAAeX,EAAI,aAAc,CAClE,CAEO,SAASkB,GAAYlB,EAAK,CAC/B,IAAMmB,EAAUlB,GAAaD,CAAG,EAC1BgB,EAAOjB,GAAWC,CAAG,EAErBoB,EADU,KAAK,IAAI,GAAGJ,CAAI,EACL,EACrBN,EAAa,CAACS,EAAQ,GAAKC,EAAUD,EAAQ,GAAKC,CAAQ,EAC1DT,EAAW,CAACQ,EAAQ,GAAKC,EAAUD,EAAQ,GAAKC,CAAQ,EAC9D,MAAO,CAAE,WAAAV,EAAY,SAAAC,EAAU,cAAeX,EAAI,aAAc,CAClE,CAaO,SAASqB,GAAiBC,EAAO,CACtC,OAAOA,EAAQ,EAAI,KAAK,GAAK,KAAK,OAAOA,EAAQ,KAAK,KAAO,EAAI,KAAK,GAAG,CAC3E,CAEO,SAASC,GAAgBC,EAAQC,EAAQ,CAC9C,IAAMC,EAAU,KAAK,GAAK,EAAI,KAAK,MAAM,EAAED,EAAO,GAAKD,EAAO,IAAKC,EAAO,GAAKD,EAAO,EAAE,EACxF,OAAOH,GAAiBK,CAAO,CACjC,CAEO,IAAMC,GAAyB,CAACC,EAAGC,IAAM,CAAC,CAAC,EAAG,EAAGD,CAAC,EAAG,CAAC,EAAG,EAAGC,CAAC,EAAG,CAAC,EAAG,EAAG,CAAC,CAAC,EAEzE,SAASC,GAAIC,EAAIC,EAAI,CAC1B,IAAIC,EAAU,EACd,QAASC,EAAI,EAAGA,EAAIH,EAAG,OAAQG,IAC7BD,GAAWF,EAAGG,GAAKF,EAAGE,GAExB,OAAOD,CACT,CAEO,SAASE,GAAmBC,EAAKC,EAAa,CACnD,IAAMC,EAAwB,CAAC,EAC/B,QAASJ,EAAI,EAAGA,EAAIE,EAAI,OAAQF,IAC9BI,EAAO,KAAKF,EAAIF,GAAGG,EAAY,EAEjC,OAAOC,CACT,CAEO,SAASC,GAA0BC,EAAMC,EAAM,CACpD,IAAMR,EAA2B,CAAC,EAC5BS,EAAOF,EAAK,OAClB,QAASG,EAAM,EAAGA,EAAMD,EAAMC,IAAO,CACnCV,EAAQ,KAAK,CAAC,CAAC,EACf,QAASW,EAAM,EAAGA,EAAMF,EAAME,IAC5BX,EAAQU,GAAK,KAAKb,GAAIU,EAAKG,GAAMR,GAAmBM,EAAMG,CAAG,CAAC,CAAC,CAEnE,CACA,OAAOX,CACT,CAEO,SAASY,GAAoBC,EAAUC,EAAQ,CACpD,IAAMC,EAAO,KAAK,IAAIF,CAAQ,EACxBG,EAAO,KAAK,IAAIH,CAAQ,EACxBI,EAAiB,CAAC,CAACF,EAAM,CAACC,EAAM,CAAC,EAAG,CAACA,EAAMD,EAAM,CAAC,EAAG,CAAC,EAAG,EAAG,CAAC,CAAC,EAC9DG,EAAoBxB,GAAuBoB,EAAO,GAAIA,EAAO,EAAE,EAC/DK,EAA2Bb,GAA0BY,EAAmBD,CAAc,EACtFG,EAA4B1B,GAAuB,CAACoB,EAAO,GAAI,CAACA,EAAO,EAAE,EAC/E,OAAOR,GAA0Ba,EAA0BC,CAAyB,CACtF,CAEO,SAASC,GAAsBC,EAAQ,CAC5C,IAAMC,EAAoB,CAAC,CAACD,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,EAAG,CAACA,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,CAAC,EAC/EE,EAAuB,CAACF,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,EAClDG,EAAsB,CAC1B,CAAC5B,GAAI0B,EAAkB,GAAIC,CAAoB,EAC/C,CAAC3B,GAAI0B,EAAkB,GAAIC,CAAoB,CACjD,EACA,MAAO,CACLD,EAAkB,GAAG,OAAOE,EAAoB,EAAE,EAClDF,EAAkB,GAAG,OAAOE,EAAoB,EAAE,EAClD,CAAC,EAAG,EAAG,CAAC,CACV,CACF,CAEO,SAASC,GAAYC,EAAuBV,EAAgB,CACjE,MAAO,CACLpB,GAAI8B,EAAuBV,EAAe,EAAE,EAC5CpB,GAAI8B,EAAuBV,EAAe,EAAE,CAC9C,CACF,CCpIO,IAAMW,GAAU,CACrB,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,QAAU,EAAG,OAAS,EAC3B,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,OAAS,EAAG,MAAQ,EACzB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,EACvB,CAAE,EAAG,MAAQ,EAAG,KAAO,CACzB,EC13FO,IAAMC,GAAN,KAAmB,CAQxB,YAAYC,EAAO,CAPnBC,EAAA,cACAA,EAAA,gBACAA,EAAA,sBACAA,EAAA,kBACAA,EAAA,wBACAA,EAAA,8BAGE,KAAK,MAAQD,EACb,KAAK,QAAkBE,GAAQ,IAAKC,GAAW,CAACA,EAAO,EAAGA,EAAO,CAAC,CAAC,EACnE,KAAK,cAAmB,WAAS,KAAK,OAAO,EAC7C,KAAK,UAAa,KAAK,OAAS,KAAK,MAAM,QAAU,KAAK,MAAM,OAAO,GAAG,MAAS,KAAK,MAAM,OAAO,GAAG,MAAM,GAAK,EACnH,KAAK,gBAAqB,WAAS,CAAC,KAAK,UAAW,KAAK,SAAS,CAAC,EACnE,KAAK,sBAA2B,WAAS,CAAC,KAAK,UAAY,EAAG,KAAK,UAAY,CAAC,CAAC,CACnF,CAEA,eAAeC,EAAO,CACpB,IAAMC,EAA4B,CAAC,EACnCA,EAAE,WAAgB,QAAMD,EAAO,CAAC,EAAG,CAAC,EAAG,CAAC,GAAI,CAAC,CAAC,EAC9CC,EAAE,SAAc,QAAMD,EAAO,CAAC,EAAG,CAAC,EAAG,CAAC,GAAI,CAAC,CAAC,EAC5CC,EAAE,IAAS,MAAIA,EAAE,WAAY,KAAK,eAAe,EACjDA,EAAE,gBAAqB,MAAIA,EAAE,IAAK,KAAK,aAAa,EACpDA,EAAE,aAAkB,MAAIA,EAAE,SAAU,KAAK,qBAAqB,EAC9DA,EAAE,IAAS,MAAIA,EAAE,gBAAiBA,EAAE,YAAY,EAChDA,EAAE,YAAiB,MAAIA,EAAE,IAAK,KAAK,eAAe,EAClDA,EAAE,IAAS,MAAIA,EAAE,gBAAiBA,EAAE,YAAY,EAChDA,EAAE,UAAe,MAAIA,EAAE,IAAK,KAAK,eAAe,EAChD,IAAMC,EAAS,WAAS,CAACD,EAAE,YAAaA,EAAE,SAAS,EAAG,CAAC,EACvD,cAAO,KAAKA,CAAC,EAAE,QAASE,GAAc,UAAQF,EAAEE,EAAO,CAAC,EACjDD,CACT,CAEA,mBAAmBE,EAAkBC,EAAO,CAC1C,IAAMJ,EAA4B,CAAC,EACnCA,EAAE,QAAa,UAAQG,EAAkB,CAAC,GAAI,EAAG,CAAC,CAAC,EACnDH,EAAE,IAAS,MAAIA,EAAE,QAAS,KAAK,eAAe,EAC9CA,EAAE,UAAe,MAAIA,EAAE,IAAK,KAAK,QAAQI,EAAM,EAC/C,IAAMH,EAAS,MAAID,EAAE,UAAW,KAAK,eAAe,EACpD,cAAO,KAAKA,CAAC,EAAE,QAASE,GAAc,UAAQF,EAAEE,EAAO,CAAC,EACjDD,CACT,CAEA,MAAM,QAAQI,EAAOC,EAAuG,CAC1H,IAAMN,EAA4B,CAAC,EACnCA,EAAE,OAAY,QAAM,eAAeK,EAAO,CAAC,KAAK,UAAW,KAAK,SAAS,CAAC,EAC1EL,EAAE,IAAS,MAAIA,EAAE,OAAQO,EAAU,KAAK,EACxCP,EAAE,MAAW,MAAIA,EAAE,IAAKO,EAAU,GAAG,EACrCP,EAAE,QAAU,KAAK,MAAM,QAAQA,EAAE,KAAK,EACtCA,EAAE,YAAiB,UAAQA,EAAE,OAAO,EACpCA,EAAE,MAAW,QAAMA,EAAE,YAAa,CAAC,EAAG,CAAC,EAAG,CAAC,GAAI,CAAC,CAAC,EACjDA,EAAE,QAAa,UAAQA,EAAE,KAAK,EAC9BA,EAAE,OAAY,UAAQA,EAAE,OAAO,EAC/B,IAAMQ,EAAS,MAAMR,EAAE,OAAO,KAAK,EACnCA,EAAE,MAAW,QAAMA,EAAE,YAAa,CAAC,EAAG,CAAC,EAAG,CAAC,GAAI,CAAC,CAAC,EACjDA,EAAE,KAAO,KAAK,eAAeA,EAAE,KAAK,EAEpCA,EAAE,IAAM,MAAS,QAAM,uBAAuBA,EAAE,KAAMA,EAAE,OAAQ,EAAIM,EAAO,KAAK,YAAaA,EAAO,KAAK,aAAcA,EAAO,KAAK,aAAa,EAChJ,IAAMG,EAAM,MAAMT,EAAE,IAAI,MAAM,EACxBU,EAAmG,CAAC,EAC1G,QAAWN,KAASK,EAAK,CACvB,IAAME,EAA4B,CAAC,EACnCA,EAAE,IAAS,QAAMX,EAAE,KAAM,CAACI,EAAO,CAAC,EAAG,CAAC,EAAG,EAAE,CAAC,EAC5CO,EAAE,MAAW,QAAMX,EAAE,YAAa,CAACI,EAAO,CAAC,EAAG,CAAC,EAAG,EAAE,CAAC,EACrDO,EAAE,KAAO,KAAK,mBAAmBA,EAAE,MAAOP,CAAK,EAC/CO,EAAE,cAAmB,UAAQA,EAAE,KAAM,CAAC,GAAI,CAAC,CAAC,EAC5C,IAAMC,EAAM,MAAMD,EAAE,IAAI,KAAK,EACvBE,EAAaD,EAAI,MAAM,EAAG,CAAC,EAC3BE,EAAWF,EAAI,MAAM,EAAG,CAAC,EACzBG,EAAgB,MAAMJ,EAAE,cAAc,MAAM,EAC5CK,EAAO,CAAE,WAAAH,EAAY,SAAAC,EAAU,cAAAC,EAAe,WAAYP,EAAOJ,EAAO,EACxEa,EAAcC,GAAoBF,EAAM,CAACX,EAAM,MAAM,GAAK,KAAK,UAAWA,EAAM,MAAM,GAAK,KAAK,SAAS,CAAC,EAChHK,EAAM,KAAKO,CAAM,EACjB,OAAO,KAAKN,CAAC,EAAE,QAAST,GAAc,UAAQS,EAAET,EAAO,CAAC,CAC1D,CACA,cAAO,KAAKF,CAAC,EAAE,QAASE,GAAc,UAAQF,EAAEE,EAAO,CAAC,EACjDQ,CACT,CACF,EC5EA,IAAMS,GAAuB,EACvBC,GAAuB,KACvBC,GAAkB,CAAC,EAAG,EAAG,EAAG,GAAI,GAAI,EAAG,CAAC,EACxCC,GAAwB,EACxBC,GAAgC,EAClCC,GAAW,EAEFC,GAAN,KAAmB,CAQxB,YAAYC,EAAcC,EAAe,CAPzCC,EAAA,qBACAA,EAAA,sBACAA,EAAA,kBACAA,EAAA,oBACAA,EAAA,gBACAA,EAAA,sBAGE,KAAK,aAAeF,EACpB,KAAK,cAAgBC,EACrB,KAAK,UAAY,KAAK,eAAiB,KAAK,cAAc,OAAO,GAAG,MAAQ,KAAK,cAAc,OAAO,GAAG,MAAM,GAAK,EACpH,KAAK,YAAc,CAAC,EACpB,KAAK,QAAU,OAAO,iBACtB,KAAK,cAAgB,CACvB,CAGA,8BAA8BE,EAAW,CACvC,IAAMC,EAAKD,EAAU,IAAKE,GAAMA,EAAE,EAAE,EAC9BC,EAAKH,EAAU,IAAKE,GAAMA,EAAE,EAAE,EAC9BE,EAAa,CAAC,KAAK,IAAI,GAAGH,CAAE,EAAG,KAAK,IAAI,GAAGE,CAAE,CAAC,EAC9CE,EAAW,CAAC,KAAK,IAAI,GAAGJ,CAAE,EAAG,KAAK,IAAI,GAAGE,CAAE,CAAC,EAClD,MAAO,CAAE,WAAAC,EAAY,SAAAC,CAAS,CAChC,CAEA,uBAAuBC,EAAeC,EAAgB,CACpD,IAAMC,EAAuBF,EAAc,IAAKG,GAAeC,GAAY,CAAC,GAAGD,EAAO,CAAC,EAAGF,CAAc,CAAC,EACnGI,EAAgB,KAAK,8BAA8BH,CAAoB,EAC7E,OAAYI,GAAgBC,GAAYF,CAAa,EAAGrB,EAAoB,CAC9E,CAEA,uBAAuBU,EAAW,CAChC,IAAMc,EAAc,KAAK,8BAA8Bd,CAAS,EAC1De,EAAqBH,GAAgBC,GAAYC,CAAW,EAAGvB,EAAoB,EACzFwB,EAAc,cAAgB,CAAC,EAC/B,QAASC,EAAI,EAAGA,EAAIxB,GAAgB,OAAQwB,IAC1CD,EAAc,cAAc,KAAKf,EAAUR,GAAgBwB,IAAI,MAAM,EAAG,CAAC,CAAC,EAE5E,OAAOD,CACT,CAEA,mBAAmBE,EAAWC,EAAMC,EAAOZ,EAAgB,CACzD,IAAMa,EAAeC,GAAWH,CAAI,EAC9BI,EAAc,CAACF,EAAQ,GAAK,KAAK,UAAWA,EAAQ,GAAK,KAAK,WAAYA,EAAQ,GAAKA,EAAQ,IAAM,KAAK,UAAY,CAAC,EACvHG,EAAeN,EAAU,IAAKR,GAAU,CAC5Ca,EAAY,IAAMb,EAAM,GAAK,KAAK,UAAY,GAC9Ca,EAAY,IAAMb,EAAM,GAAK,KAAK,UAAY,GAC9Ca,EAAY,GAAKb,EAAM,EACzB,CAAC,EACKe,EAA4BC,GAAoBN,EAAO,CAAC,EAAG,CAAC,CAAC,EAC7DO,EAAgBH,EAAa,IAAKd,GAE/B,CAAC,GADaC,GAAYD,EAAOe,CAAoB,EACxCf,EAAM,EAAE,CAC7B,EACKkB,EAA6BC,GAAsBrB,CAAc,EACjEsB,EAAY,CAAC,GAAQC,GAAaZ,CAAI,EAAG,CAAC,EAC1Ca,EAAoB,CACnBC,GAAIH,EAAWF,EAAsB,EAAE,EACvCK,GAAIH,EAAWF,EAAsB,EAAE,CAC9C,EACA,OAAOD,EAAc,IAAKjB,GAAU,CAClC,KAAK,MAAMA,EAAM,GAAKsB,EAAkB,EAAE,EAC1C,KAAK,MAAMtB,EAAM,GAAKsB,EAAkB,EAAE,EAC1C,KAAK,MAAMtB,EAAM,EAAE,CACrB,CAAC,CACH,CAEA,MAAM,cAAcwB,EAAOC,EAAQ,CACjC,IAAIC,EAAc,GAGdC,EACEC,GAAYH,EAAO,KAAK,UAAY,GAAMI,EAAI,EAAI3C,GAClD4C,EAAY,KAAK,SAAWL,EAAO,KAAK,YAAc,GACxDA,EAAO,aAAeG,GAAYE,IACpCH,EAAQ,MAAM,KAAK,aAAa,QAAQH,EAAOC,CAAM,EACrD,KAAK,QAAU,GAEbA,EAAO,aAAa,KAAK,UAGzBE,GAAUA,EAAM,OAAS,IAAQA,EAAM,SAAW,KAAK,eAAmB,KAAK,gBAAkBF,EAAO,KAAK,aAAgB,CAACA,EAAO,KAAK,aAC5I,KAAK,cAAgB,EACrB,KAAK,YAAc,CAAC,GAAGE,CAAK,EAExB,KAAK,YAAY,OAAS,IAAGD,EAAc,KAEjD,IAAMK,EAAyJ,CAAC,EAGhK,QAASxB,EAAI,EAAGA,EAAI,KAAK,YAAY,OAAQA,IAAK,CAChD,IAAMyB,EAAa,KAAK,YAAYzB,GACpC,GAAI,EAACyB,EACL,GAAIP,EAAO,KAAK,UAAW,CACzB,IAAMf,EAAQe,EAAO,KAAK,SAAgBQ,GAAgBD,EAAW,cAAchD,IAAwBgD,EAAW,cAAc/C,GAA8B,EAAI,EAChKiD,EAAkBb,GAAaW,CAAU,EACzCG,EAAuB,CAACD,EAAW,GAAKV,EAAM,MAAM,GAAIU,EAAW,GAAKV,EAAM,MAAM,EAAE,EACtFY,EAAeX,EAAO,KAAK,UAAYY,EAAI,QAAQ,SAAS,kBAAkB,EAAO,QAAM,iBAAiBb,EAAOd,EAAO,EAAGyB,CAAoB,EAAIX,EAAM,MAAM,EACjK1B,EAAsBkB,GAAoB,CAACN,EAAOwB,CAAU,EAC5DI,EAASZ,EAAc,KAAK,uBAAuBM,EAAW,cAAelC,CAAc,EAAIkC,EAC/FO,EAAoBC,GAAyBF,EAAQF,EAAc,CAAC,KAAK,UAAW,KAAK,SAAS,CAAC,EACnGK,EAAe,MAAIF,EAAcG,EAAU,KAAK,EACnD,UAAQH,CAAY,EACpB,UAAQH,CAAY,EACvB,GAAM,CAACO,EAAaC,CAAS,EAAI,KAAK,cAAc,QAAQH,CAAS,EACrEvD,GAAW2C,EAAI,EACZ,UAAQY,CAAS,EACpB,IAAMI,GAAc,MAAMF,EAAY,KAAK,GAAG,GAE9C,GADG,UAAQA,CAAW,EAClBE,GAAcpB,EAAO,KAAK,cAAgB,EAAG,CAC/C,IAAMqB,EAAuB,UAAQF,EAAW,CAAC,GAAI,CAAC,CAAC,EACjDpC,EAAY,MAAMsC,EAAkB,MAAM,EAC7C,UAAQF,CAAS,EACjB,UAAQE,CAAiB,EAC5B,IAAMC,EAAS,KAAK,mBAAmBvC,EAAW8B,EAAQ5B,EAAOZ,CAAc,EACzEkD,EAAkB,KAAK,uBAAuBD,CAAM,EAC1D,KAAK,YAAYxC,GAAK,CAAE,GAAGyC,EAAiB,WAAAH,CAAW,EACvD,IAAMI,EAAS,CACb,UAAWF,EACX,WAAAF,EACA,cAAeb,EAAW,WAC1B,iBAAkBa,EAClB,IAAK,CAAE,QAASG,EAAgB,WAAY,YAAaA,EAAgB,QAAS,CACpF,EACAjB,EAAM,KAAKkB,CAAM,CACnB,MACE,KAAK,YAAY1C,GAAK,KAErB,UAAQqC,CAAS,CACtB,KAAO,CAEL,IAAMM,EAAgB/C,GAAgBC,GAAY4B,CAAU,EAAGlD,EAAoB,EAC7EmE,EAAS,CACb,WAAYjB,EAAW,WACvB,cAAeA,EAAW,WAC1B,iBAAkB,EAClB,IAAK,CAAE,QAASkB,EAAS,WAAY,YAAaA,EAAS,QAAS,EACpE,UAAW,CAAC,CACd,EACAnB,EAAM,KAAKkB,CAAM,CACnB,CACF,CACA,YAAK,YAAc,KAAK,YAAY,OAAQE,GAAMA,IAAM,IAAI,EAC5D,KAAK,cAAgBpB,EAAM,OACvBA,EAAM,OAASN,EAAO,KAAK,cAAaM,EAAM,OAASN,EAAO,KAAK,aAChEM,CACT,CACF,ECpKO,IAAMqB,GAAS,CACpB,MAAO,EACP,MAAO,EACP,OAAQ,EACR,KAAM,EACN,MAAO,EACP,IAAK,CAAC,EAAG,EAAG,EAAG,EAAG,CAAC,EACnB,YAAa,CAAE,EAAG,QAAS,EAAG,QAAS,EAAG,SAAU,EAAG,OAAQ,EAAG,OAAQ,EAQ1E,cAAe,CACb,EAAG,CAAC,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,CAAC,EAClC,EAAG,CAAC,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,CAAC,EAClC,EAAG,CAAC,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,CAAC,EACvC,EAAG,CAAC,CAAC,EAAG,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,CAAC,EACzC,EAAG,CAAC,CAAC,EAAG,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,EAAG,CAAC,GAAI,EAAE,CAAC,CAC3C,EACA,QAAUC,GAAUD,GAAO,YAAYC,GACvC,UAAYA,GAAUD,GAAO,cAAcC,EAC7C,EAEaC,GAAa,CACxB,KAAM,EACN,KAAM,EACN,KAAM,EACN,YAAa,CAAE,EAAG,OAAQ,EAAG,OAAQ,EAAG,MAAO,EAC/C,QAAUD,GAAUC,GAAW,YAAYD,EAC7C,EAEaE,EAAkB,CAC7B,WAAY,EACZ,aAAc,EACd,eAAgB,EAChB,gBAAiB,EACjB,gBAAiB,EACjB,eAAgB,EAChB,kBAAmB,EACnB,iBAAkB,EAClB,YAAa,CAAE,EAAG,aAAc,EAAG,eAAgB,EAAG,iBAAkB,EAAG,kBAAmB,EAAG,kBAAmB,EAAG,iBAAkB,EAAG,oBAAqB,EAAG,kBAAmB,EACvL,QAAUF,GAAUE,EAAgB,YAAYF,EAClD,EAEaG,GAAN,KAAoB,CAOzB,YAAYC,EAAM,CANlBC,EAAA,aACAA,EAAA,cACAA,EAAA,mBACAA,EAAA,gBACAA,EAAA,wBAIE,KAAK,KAAOD,EACZ,KAAK,MAAQ,CAAC,EACd,KAAK,WAAa,CAAC,EACnB,KAAK,QAAU,CAAC,EAAK,EAAK,EAAK,EAAK,CAAG,EACvC,KAAK,gBAAkB,CAAC,EAAK,EAAK,EAAK,EAAK,CAAG,CACjD,CAEA,KAAKE,EAAQC,EAAMC,EAAY,CACzB,OAAO,KAAK,MAAMF,IAAY,cAAa,KAAK,MAAMA,GAAU,CAAC,GACrE,KAAK,MAAMA,GAAQ,KAAK,CAACC,EAAMC,CAAU,CAAC,CAC5C,CAEA,UAAUF,EAAQG,EAAUD,EAAY,CACjC,KAAK,WAAWF,KAAS,KAAK,WAAWA,GAAU,CAAC,GACzD,KAAK,WAAWA,GAAQ,KAAK,CAACG,EAAUD,CAAU,CAAC,CACrD,CAEA,OAAOF,EAAQI,EAAQ,CACrB,KAAK,QAAQJ,GAAUI,EAEvB,IAAMC,EAAQ,KAAK,QAAQ,OAAO,CAACC,EAAGC,IAAMD,EAAIC,EAAG,CAAC,EACpD,KAAK,gBAAkB,KAAK,QAAQ,IAAKC,GAAOA,EAAK,EAAIH,CAAK,CAChE,CAEA,aAAaI,EAAeC,EAAoB,CAC9C,IAAIR,EAAa,EAGjB,QAAWS,KAAaF,EAAe,CACrC,IAAMG,EAAeH,EAAcE,GAC7BE,EAAgB,KAAK,MAAMF,GACjC,GAAI,OAAOE,GAAkB,YAAa,CAGxCX,GAAc,KAAK,gBAAgBS,GACnC,QACF,CAEA,OAAW,CAACG,EAAcC,CAAK,IAAKF,EAClC,GAAID,IAAiBE,EAAc,CACjCZ,GAAca,EAAQ,KAAK,gBAAgBJ,GAC3C,KACF,CAEJ,CAEA,QAAWA,KAAaD,EAAoB,CAC1C,IAAMM,EAAoBN,EAAmBC,GACvCM,EAAqB,KAAK,WAAWN,GAC3C,GAAI,OAAOM,GAAuB,YAAa,CAG7Cf,GAAc,KAAK,gBAAgBS,GACnC,QACF,CAEA,OAAW,CAACO,EAAmBH,CAAK,IAAKE,EACvC,GAAID,IAAsBE,EAAmB,CAC3ChB,GAAca,EAAQ,KAAK,gBAAgBJ,GAC3C,KACF,CAEJ,CACA,OAAOT,EAAa,EACtB,CACF,ECtHO,GAAM,CAAE,MAAAiB,GAAO,MAAAC,GAAO,OAAAC,GAAQ,KAAAC,GAAM,MAAAC,EAAM,EAAIC,GAExC,CAAE,KAAAC,GAAM,KAAAC,GAAM,KAAAC,EAAK,EAAIC,GAEvB,CAAE,WAAAC,GAAY,aAAAC,GAAc,eAAAC,GAAgB,gBAAAC,GAAiB,gBAAAC,GAAiB,eAAAC,GAAgB,kBAAAC,GAAmB,iBAAAC,EAAiB,EAAIC,EAG7IC,GAAW,IAAIC,GAAc,WAAW,EAC9CD,GAAS,KAAKnB,GAAOM,GAAM,CAAG,EAC9Ba,GAAS,UAAUnB,GAAOU,GAAY,CAAG,EACzCS,GAAS,UAAUnB,GAAOe,GAAgB,GAAI,EAC9CI,GAAS,UAAUnB,GAAOc,GAAiB,GAAI,EAC/C,QAAWO,IAAU,CAAChB,GAAO,MAAOA,GAAO,OAAQA,GAAO,KAAMA,GAAO,KAAK,EAC1Ec,GAAS,KAAKE,EAAQb,GAAM,CAAG,EAC/BW,GAAS,UAAUE,EAAQT,GAAgB,CAAG,EAC9CO,GAAS,UAAUE,EAAQR,GAAiB,CAAG,EAIjD,IAAMS,GAAU,IAAIF,GAAc,SAAS,EAC3CE,GAAQ,KAAKtB,GAAOO,GAAM,EAAG,EAC7Be,GAAQ,KAAKtB,GAAOM,GAAM,EAAG,EAC7BgB,GAAQ,UAAUtB,GAAOU,GAAY,CAAG,EACxCY,GAAQ,UAAUtB,GAAOe,GAAgB,CAAG,EAC5CO,GAAQ,KAAKrB,GAAOK,GAAM,CAAG,EAC7BgB,GAAQ,UAAUrB,GAAOS,GAAY,GAAI,EACzCY,GAAQ,UAAUrB,GAAOc,GAAgB,CAAG,EAC5CO,GAAQ,KAAKpB,GAAQI,GAAM,CAAG,EAC9BgB,GAAQ,UAAUpB,GAAQQ,GAAY,CAAG,EACzCY,GAAQ,UAAUpB,GAAQa,GAAgB,GAAI,EAC9CO,GAAQ,KAAKnB,GAAMK,GAAM,CAAG,EAC5Bc,GAAQ,UAAUnB,GAAMO,GAAY,EAAG,EACvCY,GAAQ,UAAUnB,GAAMY,GAAgB,CAAG,EAC3CO,GAAQ,UAAUnB,GAAMS,GAAgB,EAAG,EAC3CU,GAAQ,KAAKlB,GAAOI,GAAM,CAAG,EAC7Bc,GAAQ,UAAUlB,GAAOM,GAAY,EAAG,EACxCY,GAAQ,UAAUlB,GAAOW,GAAgB,CAAG,EAC5CO,GAAQ,UAAUlB,GAAOQ,GAAgB,EAAG,EAC5CU,GAAQ,OAAOrB,GAAO,CAAC,EACvBqB,GAAQ,OAAOpB,GAAQ,CAAC,EAGxB,IAAMqB,GAAQ,IAAIH,GAAc,OAAO,EACvCG,GAAM,KAAKvB,GAAOQ,GAAM,CAAG,EAC3Be,GAAM,KAAKtB,GAAOK,GAAM,EAAG,EAC3BiB,GAAM,KAAKrB,GAAQM,GAAM,EAAG,EAC5Be,GAAM,KAAKpB,GAAMK,GAAM,EAAG,EAC1Be,GAAM,KAAKnB,GAAOI,GAAM,EAAG,EAC3Be,GAAM,OAAOtB,GAAO,CAAC,EACrBsB,GAAM,OAAOrB,GAAQ,CAAC,EAGtB,IAAMsB,GAAe,IAAIJ,GAAc,eAAe,EACtDI,GAAa,KAAKxB,GAAOM,GAAM,CAAG,EAClCkB,GAAa,KAAKvB,GAAOO,GAAM,EAAG,EAClCgB,GAAa,KAAKtB,GAAQM,GAAM,EAAG,EACnCgB,GAAa,KAAKrB,GAAMK,GAAM,EAAG,EACjCgB,GAAa,KAAKpB,GAAOI,GAAM,EAAG,EAClCgB,GAAa,OAAOvB,GAAO,CAAC,EAC5BuB,GAAa,OAAOtB,GAAQ,CAAC,EAG7B,IAAMuB,GAAW,IAAIL,GAAc,WAAW,EAC9CK,GAAS,KAAKzB,GAAOM,GAAM,GAAI,EAC/BmB,GAAS,KAAKxB,GAAOK,GAAM,GAAI,EAC/BmB,GAAS,KAAKvB,GAAQI,GAAM,GAAI,EAChCmB,GAAS,KAAKtB,GAAMG,GAAM,GAAI,EAC9BmB,GAAS,KAAKrB,GAAOE,GAAM,GAAI,EAE/B,IAAOoB,GAAQ,CAACP,GAAUG,GAASC,GAAOC,GAAcC,EAAQ,ECpEhE,IAAME,GAAgB,GAChBC,GAAU,CAEd,sBAAuB,GACvB,oBAAqB,IAErB,oBAAqB,IACrB,wBAAyB,GACzB,uBAAwB,GAC1B,EAEA,SAASC,GAAeC,EAASC,EAASC,EAASC,EAAS,CAC1D,IAAMC,GAASH,EAAUE,IAAYH,EAAUE,GAC3CG,EAAQ,KAAK,KAAKD,CAAK,EAAI,IAAM,KAAK,GAC1C,OAAIC,GAAS,EAAGA,EAAQ,CAACA,EAChBA,EAAQ,IAAGA,EAAQ,IAAMA,GAC3BA,CACT,CAIA,SAASC,GAAUC,EAAQC,EAAQ,CACjC,GAAI,CAACD,GAAU,CAACC,EAAQ,MAAO,CAAC,EAAG,CAAC,EACpC,IAAMC,EAAUV,GAAeQ,EAAO,GAAIA,EAAO,GAAIC,EAAO,GAAIA,EAAO,EAAE,EACzE,GAAID,EAAO,SAAW,EAAG,OAAOE,EAChC,IAAMC,EAAUX,GAAeQ,EAAO,GAAIA,EAAO,GAAIC,EAAO,GAAIA,EAAO,EAAE,EACzE,MAAO,CAACC,EAASC,CAAO,CAC1B,CAEA,SAASC,GAAmBC,EAAOC,EAAc,EAAK,CACpD,IAAIC,EAAa,EACbC,EAAa,EACbC,EAAe,EACnB,OAAIJ,GAAS,IAAQA,GAAS,IAAOE,EAAa,EAAID,EAC7CD,GAAS,IAAQA,GAAS,IAAOG,EAAa,EAAIF,EACtDG,EAAe,EAAIH,EACjB,CAACC,EAAYC,EAAYC,CAAY,CAC9C,CAEA,SAASC,GAAmBC,EAAYC,EAAUC,EAAU,CAC1D,IAAMC,EAAmBH,EAAW,GAAKC,EAAS,GAC5CG,EAAmBJ,EAAW,GAAKE,EAAS,GAC5CG,EAAiBJ,EAAS,GAAKC,EAAS,GACxCI,EAAmBN,EAAW,GAAKC,EAAS,GAC5CM,EAAmBP,EAAW,GAAKE,EAAS,GAC5CM,EAAiBP,EAAS,GAAKC,EAAS,GACxCO,EAAmBT,EAAW,GAAKC,EAAS,GAC5CS,EAAmBV,EAAW,GAAKE,EAAS,GAC5CS,EAAiBV,EAAS,GAAKC,EAAS,GACxCU,EAAiB,KAAK,KAAKT,EAAmBA,EAAmBG,EAAmBA,EAAmBG,EAAmBA,CAAgB,EAC1II,EAAiB,KAAK,KAAKT,EAAmBA,EAAmBG,EAAmBA,EAAmBG,EAAmBA,CAAgB,EAC1II,EAAe,KAAK,KAAKT,EAAiBA,EAAiBG,EAAiBA,EAAiBG,EAAiBA,CAAc,EAC9HI,GAAUD,EAAeA,EAAeF,EAAiBA,EAAiBC,EAAiBA,IAAmB,EAAIC,EAAeF,GACjIG,EAAS,EAAKA,EAAS,EAClBA,EAAS,KAAMA,EAAS,IACjC,IAAIC,EAAe,KAAK,KAAKD,CAAM,EACnCC,EAAgB,QAAUA,EAAgB,IAC1C,IAAIC,EACJ,OAAID,EAAepC,GAAQ,oBAAqBqC,EAAaC,GAAW,KAC/DF,EAAepC,GAAQ,sBAAuBqC,EAAaC,GAAW,KAC1ED,EAAaC,GAAW,KACtBD,CACT,CAEA,SAASE,GAA4Bf,EAAkBD,EAAkBE,EAAgBe,EAAY,CACnG,IAAIC,EACJ,OAAID,IAAe,KAAK,IAAIhB,CAAgB,EACtCA,EAAmB,EAAGiB,EAAqBC,EAAgB,eAC1DD,EAAqBC,EAAgB,gBACjCF,IAAe,KAAK,IAAIjB,CAAgB,EAC7CA,EAAmB,EAAGkB,EAAqBC,EAAgB,eAC1DD,EAAqBC,EAAgB,gBAEtCjB,EAAiB,EAAGgB,EAAqBC,EAAgB,eACxDD,EAAqBC,EAAgB,gBAErCD,CACT,CAEA,SAASE,GAA0BhB,EAAkBD,EAAkBE,EAAgBgB,EAAY,CACjG,IAAIH,EACJ,OAAIG,IAAe,KAAK,IAAIjB,CAAgB,EACtCA,EAAmB,EAAGc,EAAqBC,EAAgB,aAC1DD,EAAqBC,EAAgB,WACjCE,IAAe,KAAK,IAAIlB,CAAgB,EAC7CA,EAAmB,EAAGe,EAAqBC,EAAgB,aAC1DD,EAAqBC,EAAgB,WAEtCd,EAAiB,EAAGa,EAAqBC,EAAgB,aACxDD,EAAqBC,EAAgB,WAErCD,CACT,CAEA,SAASI,GAA0BlB,EAAkBD,EAAkBE,EAAgBgB,EAAYpB,EAAkBD,EAAkBE,EAAgBe,EAAY,CACjK,IAAIC,EACEK,EAA0BH,GAA0BhB,EAAkBD,EAAkBE,EAAgBgB,CAAU,EAClHG,EAA4BR,GAA4Bf,EAAkBD,EAAkBE,EAAgBe,CAAU,EAC5H,OAAIM,IAA4BJ,EAAgB,WAC1CK,IAA8BL,EAAgB,eAAgBD,EAAqBC,EAAgB,eAClGD,EAAqBC,EAAgB,gBAEtCK,IAA8BL,EAAgB,eAAgBD,EAAqBC,EAAgB,iBAClGD,EAAqBC,EAAgB,kBAErCD,CACT,CAEA,SAASO,GAAyB5B,EAAYC,EAAUC,EAAU2B,EAAc,CAC9E,IAAM1B,EAAmBH,EAAW,GAAKC,EAAS,GAC5CG,EAAmBJ,EAAW,GAAKE,EAAS,GAC5CG,EAAiBJ,EAAS,GAAKC,EAAS,GACxCI,EAAmBN,EAAW,GAAKC,EAAS,GAC5CM,EAAmBP,EAAW,GAAKE,EAAS,GAC5CM,EAAiBP,EAAS,GAAKC,EAAS,GACxCkB,EAAa,KAAK,IAAI,KAAK,IAAIjB,CAAgB,EAAG,KAAK,IAAIC,CAAgB,EAAG,KAAK,IAAIC,CAAc,CAAC,EACtGmB,EAAa,KAAK,IAAI,KAAK,IAAIlB,CAAgB,EAAG,KAAK,IAAIC,CAAgB,EAAG,KAAK,IAAIC,CAAc,CAAC,EACxGsB,EAAe,EACfC,EAAe,EACfC,EAAiB,EACfC,EAA2BT,GAAcJ,EAAa,MACxDa,EAA2B,IAAKH,GAAgBlD,GAAQ,oBACnDqD,EAA2B,IAAMF,GAAgBnD,GAAQ,oBAC7DoD,GAAkBpD,GAAQ,oBAC/B,IAAMgC,EAAiB,KAAK,KAAKT,EAAmBA,EAAmBG,EAAmBA,CAAgB,EACpGO,EAAiB,KAAK,KAAKT,EAAmBA,EAAmBG,EAAmBA,CAAgB,EACpGO,EAAe,KAAK,KAAKT,EAAiBA,EAAiBG,EAAiBA,CAAc,EAC1F0B,EAAW,KAAK,IAAItB,EAAgBC,EAAgBC,CAAY,EAClEqB,EAAqBnC,EAAW,GAChCoC,EAAqBpC,EAAW,GAChCqC,EAAmBnC,EAAS,GAC5BoC,EAAmBpC,EAAS,GAC5BgC,IAAatB,GACfyB,EAAmBnC,EAAS,GAC5BoC,EAAmBpC,EAAS,IACnBgC,IAAapB,IACtBqB,EAAqBlC,EAAS,GAC9BmC,EAAqBnC,EAAS,IAIhC,IAAMsC,EAAanD,GAFI,CAAC+C,EAAoBC,CAAkB,EACzC,CAACC,EAAkBC,CAAgB,CACC,EACnDE,EAAQ/C,GAAmB8C,EAAY3D,GAAQ,sBAAsB,EAC3EkD,GAAgBU,EAAM,GACtBT,GAAgBS,EAAM,GACtBR,GAAkBQ,EAAM,GACxB,QAAWC,MAAeZ,EAAc,CACtC,IAAMa,EAAcjD,GAAmBgD,GAAa7D,GAAQ,uBAAuB,EACnFkD,GAAgBY,EAAY,GAC5BX,GAAgBW,EAAY,GAC5BV,GAAkBU,EAAY,EAChC,CAGA,IAAIrB,EACJ,OAAIS,IAAiB,KAAK,IAAIA,EAAcC,EAAcC,CAAc,EACtEX,EAAqBE,GAA0BhB,EAAkBD,EAAkBE,EAAgBgB,CAAU,EACpGQ,IAAmB,KAAK,IAAID,EAAcC,CAAc,EACjEX,EAAqBF,GAA4Bf,EAAkBD,EAAkBE,EAAgBe,CAAU,EAE/GC,EAAqBI,GAA0BlB,EAAkBD,EAAkBE,EAAgBgB,EAAYpB,EAAkBD,EAAkBE,EAAgBe,CAAU,EAExKC,CACT,CAEA,SAASsB,GAASC,EAAW,CAE3B,IAAMC,EAA4B,CAAC,EAC7BC,EAA4B,CAAC,EAC7BC,EAA6B,CAAC,EAC9BC,EAAkC,CAAC,EACzC,GAAI,CAACJ,EAAW,MAAO,CAAE,MAAOG,EAAa,WAAYC,CAAiB,EAG1E,QAAWC,KAAUC,GAAO,IAAK,CAC/B,IAAMC,EAASD,GAAO,UAAUD,CAAM,EAChCG,EAA2B,CAAC,EAC5BC,EAA2B,CAAC,EAClC,QAAWC,KAASH,EAAQ,CAC1B,IAAM9D,EAASuD,EAAUU,EAAM,IACzBhE,EAASsD,EAAUU,EAAM,IAEzBC,EAASnE,GAAUC,EAAQC,CAAM,EACjCC,EAAUgE,EAAO,GACjB/D,EAAU+D,EAAO,GACvBH,EAAU,KAAK7D,CAAO,EACtB8D,EAAU,KAAK7D,CAAO,CACxB,CACAqD,EAAS,KAAKO,CAAS,EACvBN,EAAS,KAAKO,CAAS,CACzB,CAGA,QAAWJ,KAAUC,GAAO,IAAK,CAE/B,IAAMM,EAAgBP,IAAWC,GAAO,MAAS,EAAI,EAC/CO,EAAiBP,GAAO,UAAUD,CAAM,EACxCjD,EAAa4C,EAAUa,EAAeD,GAAc,IACpDvD,EAAW2C,EAAUa,EAAeD,EAAe,GAAG,IACtDtD,EAAW0C,EAAUa,EAAe,GAAG,IAEvCC,EAAe3D,GAAmBC,EAAYC,EAAUC,CAAQ,EAChEyD,EAAiB/B,GAAyB5B,EAAYC,EAAUC,EAAU2C,EAASI,GAAQ,MAAMO,CAAY,CAAC,EACpHT,EAAYE,GAAUS,EACtBV,EAAiBC,GAAUU,CAC7B,CACA,MAAO,CAAE,MAAOZ,EAAa,WAAYC,CAAiB,CAC5D,CAEO,SAASY,GAAQC,EAAW,CACjC,GAAI,CAACA,GAAaA,EAAU,SAAW,EAAG,OAAO,KACjD,IAAMC,EAAenB,GAASkB,CAAS,EACjCjB,EAAY,CAAC,EACnB,QAAWmB,KAAab,GAAO,IAC7BN,EAAUM,GAAO,QAAQa,CAAS,GAAK,CACrC,KAAM7C,GAAW,QAAQ4C,EAAa,MAAMC,EAAU,EACtD,UAAWzC,EAAgB,QAAQwC,EAAa,WAAWC,EAAU,CACvE,EAEF,OAAOnB,CACT,CAEO,SAASoB,GAAMH,EAAW,CAC/B,IAAMI,EAAqD,CAAC,EAC5D,GAAI,CAACJ,GAAaA,EAAU,SAAW,EAAG,OAAOI,EACjD,IAAMH,EAAenB,GAASkB,CAAS,EACvC,QAAWK,KAAWC,GAAU,CAC9B,IAAMC,EAAaF,EAAQ,aAAaJ,EAAa,MAAOA,EAAa,UAAU,EAC/EM,GAAczF,IAAesF,EAAM,KAAK,CAAE,KAAMC,EAAQ,KAAM,WAAAE,CAAW,CAAC,CAChF,CACA,OAAOH,CACT,CChOA,IAAMI,GAAkB,CACtB,MAAO,CAAC,EAAG,EAAG,EAAG,CAAC,EAClB,MAAO,CAAC,EAAG,EAAG,EAAG,CAAC,EAClB,OAAQ,CAAC,EAAG,GAAI,GAAI,EAAE,EACtB,KAAM,CAAC,GAAI,GAAI,GAAI,EAAE,EACrB,MAAO,CAAC,GAAI,GAAI,GAAI,EAAE,EACtB,KAAM,CAAC,CAAC,CACV,EAEIC,GACAC,GACAC,GAEJ,eAAsBC,GAAQC,EAAeC,EAAuC,CAClF,IAAMC,EAAc,MAAMJ,GAAa,cAAcE,EAAOC,CAAM,EAClE,GAAI,CAACC,EAAa,MAAO,CAAC,EAC1B,IAAMC,EAA2B,CAAC,EAClC,QAASC,EAAI,EAAGA,EAAIF,EAAY,OAAQE,IAAK,CAC3C,IAAMC,EAAc,CAAC,EACrB,GAAIH,EAAYE,GAAG,UACjB,QAAWE,KAAO,OAAO,KAAKX,EAAe,EAC3CU,EAAYC,GAAOX,GAAgBW,GAAK,IAAKC,GAAUL,EAAYE,GAAG,UAAUG,EAAM,EAG1F,IAAMC,EAAYN,EAAYE,GAAG,UAC7BK,EAAW,CAAC,OAAO,iBAAkB,OAAO,iBAAkB,EAAG,CAAC,EAClEC,EAAc,CAAC,EAAG,EAAG,EAAG,CAAC,EAC7B,GAAIF,GAAaA,EAAU,OAAS,EAAG,CACrC,QAAWG,KAAMH,EACXG,EAAG,GAAKF,EAAI,KAAIA,EAAI,GAAKE,EAAG,IAC5BA,EAAG,GAAKF,EAAI,KAAIA,EAAI,GAAKE,EAAG,IAC5BA,EAAG,GAAKF,EAAI,KAAIA,EAAI,GAAKE,EAAG,IAC5BA,EAAG,GAAKF,EAAI,KAAIA,EAAI,GAAKE,EAAG,IAElCF,EAAI,IAAMA,EAAI,GACdA,EAAI,IAAMA,EAAI,GACdC,EAAS,CAACD,EAAI,IAAMT,EAAM,MAAM,IAAM,GAAIS,EAAI,IAAMT,EAAM,MAAM,IAAM,GAAIS,EAAI,IAAMT,EAAM,MAAM,IAAM,GAAIS,EAAI,IAAMT,EAAM,MAAM,IAAM,EAAE,CAC1I,MACES,EAAMP,EAAYE,GAAG,IAAM,CACzB,KAAK,MAAM,KAAK,IAAI,EAAGF,EAAYE,GAAG,IAAI,QAAQ,EAAE,CAAC,EACrD,KAAK,MAAM,KAAK,IAAI,EAAGF,EAAYE,GAAG,IAAI,QAAQ,EAAE,CAAC,EACrD,KAAK,MAAM,KAAK,IAAKJ,EAAM,MAAM,IAAM,EAAIE,EAAYE,GAAG,IAAI,YAAY,EAAE,EAAI,KAAK,IAAI,EAAGF,EAAYE,GAAG,IAAI,QAAQ,EAAE,CAAC,EAC1H,KAAK,MAAM,KAAK,IAAKJ,EAAM,MAAM,IAAM,EAAIE,EAAYE,GAAG,IAAI,YAAY,EAAE,EAAI,KAAK,IAAI,EAAGF,EAAYE,GAAG,IAAI,QAAQ,EAAE,CAAC,CAC5H,EAAI,CAAC,EAAG,EAAG,EAAG,CAAC,EACfM,EAAS,CACNR,EAAYE,GAAG,IAAI,QAAQ,IAAOJ,EAAM,MAAM,IAAM,GACpDE,EAAYE,GAAG,IAAI,QAAQ,IAAOJ,EAAM,MAAM,IAAM,IACpDE,EAAYE,GAAG,IAAI,YAAY,GAAKF,EAAYE,GAAG,IAAI,QAAQ,KAAOJ,EAAM,MAAM,IAAM,IACxFE,EAAYE,GAAG,IAAI,YAAY,GAAKF,EAAYE,GAAG,IAAI,QAAQ,KAAOJ,EAAM,MAAM,IAAM,EAC3F,EAEF,IAAMY,EAAuBC,GAAQL,CAAS,EAC9CL,EAAM,KAAK,CACT,GAAIC,EACJ,MAAO,KAAK,MAAM,IAAMF,EAAYE,GAAG,UAAU,EAAI,IACrD,SAAU,KAAK,MAAM,IAAMF,EAAYE,GAAG,aAAa,EAAI,IAC3D,YAAa,KAAK,MAAM,IAAMF,EAAYE,GAAG,gBAAgB,EAAI,IACjE,MAAO,OACP,IAAAK,EACA,OAAAC,EACA,UAAAF,EACA,YAAaH,EACb,UAAWO,CACb,CAAC,CACH,CACA,OAAOT,CACT,CAEA,eAAsBW,GAAKb,EAAiE,CApF5F,IAAAc,EAAAC,EAqFMC,EAAI,UACNrB,GAAoB,KACpBC,GAAgB,MAEd,CAACD,IAAqB,CAACC,GACzB,CAACD,GAAmBC,EAAa,EAAI,MAAM,QAAQ,IAAI,CACrDI,EAAO,KAAK,QAAUiB,GAAUH,EAAAd,EAAO,KAAK,WAAZ,YAAAc,EAAsB,SAAS,EAAI,KACnEd,EAAO,KAAK,UAAYiB,GAAUF,EAAAf,EAAO,KAAK,WAAZ,YAAAe,EAAsB,SAAS,EAAI,IACvE,CAAC,GAEGf,EAAO,OAAOkB,EAAI,gBAAiBvB,GAAkB,QAAW,EAChEK,EAAO,OAAOkB,EAAI,gBAAiBtB,GAAc,QAAW,GAElE,IAAMuB,EAAe,IAAiBC,GAAazB,EAAiB,EACpE,OAAAE,GAAe,IAAiBwB,GAAaF,EAAcvB,EAAa,EACjE,CAACD,GAAmBC,EAAa,CAC1C,CCjFA,IAAM0B,GAAiD,CAAC,KAAM,IAAI,EAC5DC,GAAmB,CAAC,8CAA+C,oDAAoD,EAEvHC,GAAY,CAAC,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,CAAC,EAE3BC,GAAU,CAAC,OAAQ,OAAQ,QAAS,QAAS,OAAQ,MAAO,UAAU,EACtEC,GAAY,EAEZC,GAAgB,IAChBC,GAAwB,IACxBC,GAAqB,IAEvBC,GAAU,OAAO,iBACjBC,GAAW,EACXC,GAA+B,CAAC,EAAG,CAAC,EAUlCC,EAGF,CACF,MAAO,CAAC,EACR,MAAO,CAAC,CACV,EAEMC,GAAY,CAShB,MAAO,CAAC,EAAG,EAAG,EAAG,CAAC,EAClB,MAAO,CAAC,EAAG,EAAG,EAAG,CAAC,EAClB,OAAQ,CAAC,EAAG,GAAI,GAAI,EAAE,EACtB,KAAM,CAAC,GAAI,GAAI,GAAI,EAAE,EACrB,MAAO,CAAC,GAAI,GAAI,GAAI,EAAE,EACtB,KAAM,CAAC,CAAC,EACR,KAAM,CAAC,EAAG,GAAI,GAAI,EAAG,EAAG,EAAG,CAAC,CAC9B,EAEA,eAAsBC,GAAWC,EAAqC,CAtEtE,IAAAC,EAyEE,GADIC,EAAI,UAAShB,GAAO,GAAK,MACxBA,GAAO,GAQDc,EAAO,OAAOG,EAAI,gBAAiBjB,GAAO,GAAG,QAAW,MARnD,CAGdkB,GAAQ,CAAC,oBAAqB,QAAS,uBAAwB,QAAS,WAAY,SAAU,OAAQ,kBAAmB,gBAAiB,oBAAqB,oBAAqB,aAAc,QAAS,QAAS,OAAO,EAAGJ,CAAM,EACpOd,GAAO,GAAK,MAAMmB,GAAUJ,EAAAD,EAAO,KAAK,WAAZ,YAAAC,EAAsB,SAAS,EAC3D,IAAMK,EAAS,OAAO,OAAOpB,GAAO,GAAG,eAAe,MAAS,EAC/DE,GAAU,GAAG,GAAK,MAAM,QAAQkB,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,EACxFlB,GAAU,GAAG,GAAK,MAAM,QAAQkB,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,CAC1F,CACA,OAAOpB,GAAO,EAChB,CAEA,eAAsBqB,GAAaP,EAAqC,CArFxE,IAAAC,EAuFE,GADIC,EAAI,UAAShB,GAAO,GAAK,MACxBA,GAAO,GAKDc,EAAO,OAAOG,EAAI,gBAAiBjB,GAAO,GAAG,QAAW,MALnD,CACdA,GAAO,GAAK,MAAMmB,GAAUJ,EAAAD,EAAO,KAAK,WAAZ,YAAAC,EAAsB,SAAS,EAC3D,IAAMK,EAAS,OAAO,OAAOpB,GAAO,GAAG,eAAe,MAAS,EAC/DE,GAAU,GAAG,GAAK,MAAM,QAAQkB,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,EACxFlB,GAAU,GAAG,GAAK,MAAM,QAAQkB,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,CAC1F,CACA,OAAOpB,GAAO,EAChB,CAQA,eAAesB,GAAYC,EAAeC,EAA6C,CACrF,IAAMC,EAA4B,CAAC,EACnC,GAAI,CAACF,GAAS,CAACG,GAAO,GAAI,OAAOD,EACjC,IAAME,EAA4B,CAAC,EAC7BC,GAASL,EAAM,MAAM,IAAM,IAAMA,EAAM,MAAM,IAAM,GACnDM,EAAS,KAAK,IAAI,KAAK,OAAON,EAAM,MAAM,IAAM,GAAK,CAAC,EAAI,EAAGO,EAAqB,EAClFC,EAAQ,KAAK,MAAMF,EAASD,EAAQ,CAAC,EAAI,EAC/CD,EAAE,OAAY,QAAM,eAAeJ,EAAO,CAACM,EAAQE,CAAK,CAAC,EACzDJ,EAAE,KAAU,OAAKA,EAAE,OAAQ,OAAO,EAClC,CAACA,EAAE,UAAWA,EAAE,QAAQ,EAAI,MAAMD,GAAO,GAAG,aAAaC,EAAE,KAAMK,EAAgB,EACjFL,EAAE,MAAW,UAAQA,EAAE,SAAU,CAAC,EAAG,CAAC,CAAC,EACvCA,EAAE,OAAY,UAAQA,EAAE,UAAW,CAAC,CAAC,CAAC,EACtC,IAAMM,EAAgC,UAAQN,EAAE,OAAQ,CAAC,EACtD,UAAQM,EAAYC,GAAU,EACjCD,EAAY,OAAOC,GAAW,CAAC,EAC/BP,EAAE,SAAc,QAAMM,EAAa,CAAC,EACjC,UAAQA,CAAW,EAEtBN,EAAE,IAAS,MAAIA,EAAE,SAAU,CAAC,EAC5BA,EAAE,OAAY,SAAOA,EAAE,SAAU,CAAC,EAClC,IAAIQ,EAAK,EACTR,EAAE,IAAM,MAAS,QAAM,uBAAuBA,EAAE,MAAOA,EAAE,KAAMH,EAAO,KAAK,aAAe,GAAK,EAAGA,EAAO,KAAK,cAAgB,EAAGA,EAAO,KAAK,eAAiB,CAAC,EAC/J,IAAMY,EAAM,MAAMT,EAAE,IAAI,KAAK,EACvBU,EAAS,MAAMV,EAAE,IAAI,KAAK,EAC1BW,EAAW,MAAMX,EAAE,OAAO,KAAK,EACrC,QAAWY,KAAY,MAAM,KAAKH,CAAG,EAAG,CACtC,IAAMI,EAAc,QAAMb,EAAE,MAAOY,EAAU,CAAC,EACxCE,EAAQ,MAAMD,EAAS,KAAK,EAC/B,UAAQA,CAAQ,EACnB,IAAME,EAAe,CAACD,EAAM,GAAIA,EAAM,GAAIA,EAAM,GAAKA,EAAM,GAAIA,EAAM,GAAKA,EAAM,EAAE,EAC5EE,EAAkBC,GAAMF,EAASG,EAAkB,EACnDC,EAAe,CAAC,KAAK,MAAMJ,EAAQ,GAAKK,GAAW,EAAE,EAAG,KAAK,MAAML,EAAQ,GAAKK,GAAW,EAAE,EAAG,KAAK,MAAML,EAAQ,GAAKK,GAAW,EAAE,EAAG,KAAK,MAAML,EAAQ,GAAKK,GAAW,EAAE,CAAC,EAC9KC,EAAQX,EAAOE,GACfU,EAAQC,GAAQZ,EAASC,IACzBY,EAAyB,CAAE,GAAIhB,IAAM,MAAAa,EAAO,IAAKF,EAAS,OAAAH,EAAQ,MAAAM,CAAM,EAC9ExB,EAAM,KAAK0B,CAAI,CACjB,CACA,cAAO,KAAKxB,CAAC,EAAE,QAASyB,GAAc,UAAQzB,EAAEyB,EAAO,CAAC,EACxD3B,EAAM,KAAK,CAAC4B,EAAGC,IAAMA,EAAE,MAAQD,EAAE,KAAK,EAClC5B,EAAM,QAAUD,EAAO,KAAK,aAAe,KAAIC,EAAM,OAAUD,EAAO,KAAK,aAAe,GACvFC,CACT,CAEA,eAAe8B,GAAchC,EAAeiC,EAAqBhC,EAAqC,CACpG,IAAM2B,EAAmB,CACvB,GAAIK,EAAE,GACN,MAAO,KAAK,MAAM,IAAMA,EAAE,KAAK,EAAI,IACnC,SAAU,KAAK,MAAM,IAAMA,EAAE,KAAK,EAAI,IACtC,YAAa,EACb,IAAKA,EAAE,IACP,OAAQA,EAAE,OACV,MAAOA,EAAE,MACT,UAAW,CAAC,EACZ,UAAW,CAAC,EACZ,YAAa,CAAC,CAChB,EACA,GAAIjC,GAASG,GAAO,IAAMF,EAAO,KAAK,WAAagC,EAAE,OAAShC,EAAO,KAAK,eAAiB,GAAI,CAC7F,IAAMG,EAA4B,CAAC,EAC7B8B,EAAU,CAACD,EAAE,OAAO,GAAIA,EAAE,OAAO,GAAIA,EAAE,OAAO,GAAKA,EAAE,OAAO,GAAIA,EAAE,OAAO,GAAKA,EAAE,OAAO,EAAE,EAC/F7B,EAAE,KAAU,QAAM,cAAcJ,EAAO,CAACkC,CAAO,EAAG,CAAC,CAAC,EAAG,CAACC,GAAU,GAAG,GAAIA,GAAU,GAAG,EAAE,EAAG,UAAU,EACrG/B,EAAE,IAAS,MAAIA,EAAE,KAAMgC,EAAU,KAAK,EACtC,CAAChC,EAAE,MAAOA,EAAE,SAAS,EAAID,GAAO,GAAG,QAAQC,EAAE,IAAK,CAAC,aAAc,UAAU,CAAC,EAC5E,IAAMiC,GAAY,MAAMjC,EAAE,MAAM,KAAK,GAAG,GAClCqB,GAAS,IAAM,KAAK,MAAM,KAAO,EAAI,KAAK,IAAIY,CAAQ,EAAE,GAAK,IACnE,GAAIZ,IAAUxB,EAAO,KAAK,eAAiB,GAAI,CAC7C2B,EAAK,YAAcH,EACnBrB,EAAE,SAAc,UAAQA,EAAE,UAAW,CAAC,GAAI,CAAC,CAAC,EAG5C,IAAMkC,GAFsB,MAAMlC,EAAE,SAAS,MAAM,GACb,IAAKmC,GAAQ,CAACA,EAAI,GAAKJ,GAAU,GAAG,GAAII,EAAI,GAAKJ,GAAU,GAAG,GAAKI,EAAI,IAAM,CAAE,CAAC,EAChF,IAAKA,GAAQ,CAACA,EAAI,GAAKN,EAAE,OAAO,GAAIM,EAAI,GAAKN,EAAE,OAAO,GAAKM,EAAI,IAAM,CAAE,CAAC,EAC9GX,EAAK,UAAaU,EAAY,IAAKC,GAAQ,CAACf,GAAW,IAAMe,EAAI,GAAKN,EAAE,OAAO,IAAKT,GAAW,IAAMe,EAAI,GAAKN,EAAE,OAAO,IAAMM,EAAI,IAAM,CAAE,CAAC,EAC1IX,EAAK,UAAuBY,GAAQZ,EAAK,SAAS,EAClD,QAAWa,KAAO,OAAO,KAAKC,EAAS,EACrCd,EAAK,YAAYa,GAAOC,GAAUD,GAAK,IAAKE,GAAmBf,EAAK,WAAaA,EAAK,UAAUe,GAASf,EAAK,UAAUe,GAAS,IAAK,CAE1I,CACA,OAAO,KAAKvC,CAAC,EAAE,QAASyB,GAAc,UAAQzB,EAAEyB,EAAO,CAAC,CAC1D,CACA,OAAOD,CACT,CAEA,eAAsBgB,GAAQ5C,EAAeC,EAAuC,CAvLpF,IAAA4C,EAAAC,EAwLE,GAAI,CAAC3C,GAAO,IAAM,CAACA,GAAO,IAAM,GAAC0C,EAAA1C,GAAO,KAAP,MAAA0C,EAAW,OAAO,GAAG,QAAS,GAACC,EAAA3C,GAAO,KAAP,MAAA2C,EAAW,OAAO,GAAG,OAAO,MAAO,CAAC,EACpGtB,GAAa,CAACxB,EAAM,MAAM,IAAM,EAAGA,EAAM,MAAM,IAAM,CAAC,EACtD+C,KACA,IAAMC,GAAY/C,EAAO,KAAK,UAAY,GAAMgD,EAAI,EAAIC,GAClDC,EAAYJ,IAAW9C,EAAO,KAAK,YAAc,GACvD,OAAIA,EAAO,aAAe+C,GAAYG,EAC7BC,EAAM,MAER,IAAI,QAAQ,MAAOC,GAAY,CACpC,IAAMC,EAAmB,GAAKrD,EAAO,KAAK,UAAY,GAAMgD,EAAI,EAAIC,GAC9DK,EAAoBR,GAAU,GAAK9C,EAAO,KAAK,YAAc,GAC/DA,EAAO,aAAemD,EAAM,MAAM,SAAWnD,EAAO,KAAK,YAC3DmD,EAAM,MAAQ,MAAM,QAAQ,IAAIA,EAAM,MAAM,IAAKI,GAAYxB,GAAchC,EAAOwD,EAASvD,CAAM,CAAC,CAAC,EAC1FA,EAAO,aAAeqD,GAAoBC,GAAqBH,EAAM,MAAM,OAAS,EAC7FA,EAAM,MAAQ,MAAM,QAAQ,IAAIA,EAAM,MAAM,IAAKI,GAAYxB,GAAchC,EAAOwD,EAASvD,CAAM,CAAC,CAAC,GAEnGmD,EAAM,MAAQ,MAAMrD,GAAYC,EAAOC,CAAM,EAC7CiD,GAAWD,EAAI,EACfG,EAAM,MAAQ,MAAM,QAAQ,IAAIA,EAAM,MAAM,IAAKI,GAAYxB,GAAchC,EAAOwD,EAASvD,CAAM,CAAC,CAAC,EACnG8C,GAAU,GAGZ,IAAMU,EAAW,CAAC,GAAGL,EAAM,KAAK,EAEhC,GADAA,EAAM,MAAM,OAAS,EACjBnD,EAAO,iBAAmB,EAC5B,QAASyD,EAAI,EAAGA,EAAIN,EAAM,MAAM,OAAQM,IAAK,CAC3C,IAAMC,EAAaC,GAAOR,EAAM,MAAMM,GAAG,UAAWlC,EAAU,EAC9D,GAAImC,EAAO,IAAI,IAAM3D,EAAM,MAAM,IAAM,GAAK,KAAQ2D,EAAO,IAAI,IAAM3D,EAAM,MAAM,IAAM,GAAK,KAAQoD,EAAM,MAAMM,GAAG,aAAeN,EAAM,MAAMM,GAAG,aAAezD,EAAO,KAAK,eAAiB,GAAI,CAC/L,IAAM4D,EAAexC,GAAMsC,EAAO,IAAKG,EAAa,EAC9CC,EAAkB1C,GAAMsC,EAAO,OAAQG,EAAa,EAE1DV,EAAM,MAAM,KAAK,CAAE,GAAGK,EAASC,GAAI,IAAKG,EAAU,OAAQE,CAAY,CAAC,CACzE,CACF,CAEF,QAASL,EAAI,EAAGA,EAAIN,EAAM,MAAM,OAAQM,IAAK,CAC3C,IAAMM,EAAWC,GAAKb,EAAM,MAAMM,GAAG,UAAWlC,EAAU,EAC1D4B,EAAM,MAAMM,GAAG,IAAMM,EAAK,IAC1BZ,EAAM,MAAMM,GAAG,OAASM,EAAK,MAC/B,CACAX,EAAQD,EAAM,KAAK,CACrB,CAAC,CACH,CCvNA,IAAIc,GACEC,GAAwB,CAAC,EAC3BC,GAAU,OAAO,iBACjBC,GAAY,EACZC,GAAW,EAEf,eAAsBC,GAAKC,EAAqC,CAjBhE,IAAAC,EAkBE,OAAIC,EAAI,UAASR,GAAQ,MACpBA,GACIM,EAAO,OAAOG,EAAI,gBAAiBT,GAAM,QAAW,EADjDA,GAAQ,MAAMU,GAAUH,EAAAD,EAAO,KAAK,WAAZ,YAAAC,EAAsB,SAAS,EAE5DP,EACT,CAEA,eAAsBW,GAAQC,EAAeN,EAAgBO,EAAaC,EAAgC,CAxB1G,IAAAP,EAAAQ,EAyBE,GAAI,CAACf,GAAO,MAAO,GACnB,IAAMgB,KAAYT,EAAAD,EAAO,KAAK,WAAZ,YAAAC,EAAsB,WAAY,GAAMU,EAAI,EAAIb,GAC5Dc,EAAYhB,MAAWa,EAAAT,EAAO,KAAK,WAAZ,YAAAS,EAAsB,aAAc,GACjE,OAAIT,EAAO,aAAeU,GAAYE,GAAcf,KAAcW,GAAUb,GAAOY,IACjFX,KACOD,GAAOY,KAEhBX,GAAU,EACH,IAAI,QAAQ,MAAOiB,GAAY,CACpC,IAAMC,EAAY,QAAM,eAAeR,EAAO,CAACZ,IAAA,MAAAA,GAAO,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EAAGA,IAAA,MAAAA,GAAO,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,CAAC,EAAG,EAAK,EAC7JqB,EAAMrB,IAAA,YAAAA,GAAO,QAAQoB,GACrBE,GAAO,MAAMD,EAAI,KAAK,GAAG,GAC/BpB,GAAOY,GAAO,KAAK,MAAM,IAAMS,CAAG,EAAI,IACtCnB,GAAYW,EACZV,GAAWa,EAAI,EACZ,UAAQ,CAACG,EAAQC,CAAG,CAAC,EACxBF,EAAQlB,GAAOY,EAAI,CACrB,CAAC,EACH,CC3CA,IAAAU,GAAA,GAAAC,GAAAD,GAAA,eAAAE,GAAA,eAAAC,GAAA,QAAAC,GAAA,aAAAC,GAAA,aAAAC,KAAO,IAAMF,GAAqB,CAChC,OACA,UACA,WACA,UACA,WACA,eACA,gBACA,YACA,aACA,YACA,aACA,UACA,WACA,WACA,YACA,YACA,YACF,EAEaD,GAA8B,CACzC,CAAC,UAAW,UAAU,EACtB,CAAC,UAAW,UAAU,EACtB,CAAC,eAAgB,eAAe,EAChC,CAAC,YAAa,YAAY,EAC1B,CAAC,YAAa,YAAY,EAC1B,CAAC,UAAW,UAAU,EACtB,CAAC,WAAY,WAAW,EACxB,CAAC,YAAa,YAAY,CAC5B,EAEaG,GAA4B,CACvC,CAAC,WAAY,cAAc,EAC3B,CAAC,YAAa,eAAe,EAC7B,CAAC,YAAa,UAAU,EACxB,CAAC,aAAc,WAAW,CAC5B,EAEaD,GAA8B,CACzC,CAAC,CAAC,UAAW,UAAU,EAAG,CAAC,eAAgB,eAAe,CAAC,EAC3D,CAAC,CAAC,YAAa,YAAY,EAAG,CAAC,eAAgB,eAAe,CAAC,CACjE,EAEaH,GAAsC,CACjD,QAAS,CAAC,UAAW,WAAY,WAAW,EAC5C,SAAU,CAAC,WAAY,YAAa,YAAY,EAChD,MAAO,CAAC,eAAgB,gBAAiB,WAAY,UAAW,cAAc,EAC9E,QAAS,CAAC,eAAgB,YAAa,WAAW,EAClD,SAAU,CAAC,gBAAiB,aAAc,YAAY,EACtD,KAAM,CAAC,CACT,EC5CA,IAAMK,GAAY,KAEZC,GAGF,CACF,UAAW,CAAC,EACZ,QAAS,CAAC,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,EAAG,CAAC,CAAC,CAC1C,EAEO,SAASC,GAAUC,EAAkB,CAC1C,QAAWC,KAAeC,GAAY,CACpC,IAAMC,EAAOH,EAAK,UAAU,UAAWI,GAAOA,EAAG,OAASH,EAAK,EAAE,EAC3DI,EAAQL,EAAK,UAAU,UAAWI,GAAOA,EAAG,OAASH,EAAK,EAAE,EAClE,GAAID,EAAK,UAAUG,IAASH,EAAK,UAAUK,IACrCL,EAAK,UAAUG,GAAM,SAAS,GAAKH,EAAK,UAAUK,GAAO,SAAS,GAAI,CACxE,IAAMC,EAAMN,EAAK,UAAUG,GAC3BH,EAAK,UAAUG,GAAQH,EAAK,UAAUK,GACtCL,EAAK,UAAUK,GAASC,CAC1B,CAEJ,CACA,QAAWL,KAAeM,GAAU,CAClC,IAAMC,EAAQR,EAAK,UAAU,UAAWI,GAAQA,GAAMA,EAAG,OAASH,EAAK,EAAG,EACpEQ,EAAST,EAAK,UAAU,UAAWI,GAAQA,GAAMA,EAAG,OAASH,EAAK,EAAG,EACvED,EAAK,UAAUQ,IAAUR,EAAK,UAAUS,IACtCT,EAAK,UAAUQ,GAAO,SAAS,GAAKR,EAAK,UAAUS,GAAQ,SAAS,IACtET,EAAK,UAAU,OAAOQ,EAAO,CAAC,CAGpC,CACA,OAAW,CAACP,EAAMS,CAAO,IAAYC,GAAU,CAC7C,IAAMR,EAAOH,EAAK,UAAU,UAAWI,GAAQA,GAAMA,EAAG,OAASH,EAAK,EAAG,EACnEI,EAAQL,EAAK,UAAU,UAAWI,GAAQA,GAAMA,EAAG,OAASH,EAAK,EAAG,EACpEW,EAASZ,EAAK,UAAU,UAAWI,GAAQA,GAAMA,EAAG,OAASM,EAAQ,EAAG,EACxEG,EAAUb,EAAK,UAAU,UAAWI,GAAQA,GAAMA,EAAG,OAASM,EAAQ,EAAG,EAC/E,GAAI,CAACV,EAAK,UAAUY,IAAW,CAACZ,EAAK,UAAUa,GAAU,SACzD,IAAMC,EAAed,EAAK,UAAUG,GAAQ,CAC1C,KAAK,IAAIH,EAAK,UAAUY,GAAQ,SAAS,GAAKZ,EAAK,UAAUG,GAAM,SAAS,EAAE,EAC9E,KAAK,IAAIH,EAAK,UAAUa,GAAS,SAAS,GAAKb,EAAK,UAAUG,GAAM,SAAS,EAAE,CACjF,EAAI,CAAC,EAAG,CAAC,EACHY,EAAgBf,EAAK,UAAUK,GAAS,CAC5C,KAAK,IAAIL,EAAK,UAAUa,GAAS,SAAS,GAAKb,EAAK,UAAUK,GAAO,SAAS,EAAE,EAChF,KAAK,IAAIL,EAAK,UAAUY,GAAQ,SAAS,GAAKZ,EAAK,UAAUK,GAAO,SAAS,EAAE,CACjF,EAAI,CAAC,EAAG,CAAC,EACT,GAAIS,EAAa,GAAKA,EAAa,IAAMC,EAAc,GAAKA,EAAc,GAAI,CAC5E,IAAMT,EAAMN,EAAK,UAAUG,GAC3BH,EAAK,UAAUG,GAAQH,EAAK,UAAUK,GACtCL,EAAK,UAAUK,GAASC,CAC1B,CACF,CACF,CAEO,SAASU,GAAOC,EAAqD,CAC1E,QAASC,EAAI,EAAGA,EAAID,EAAU,OAAQC,IACpC,GAAID,EAAUC,IAAMpB,GAAM,UAAUoB,GAAI,CACtC,IAAMC,EAAO,CAAC,KAAK,IAAIF,EAAUC,GAAG,YAAY,GAAKpB,GAAM,UAAUoB,GAAG,YAAY,EAAE,EAAG,KAAK,IAAID,EAAUC,GAAG,YAAY,GAAKpB,GAAM,UAAUoB,GAAG,YAAY,EAAE,CAAC,EAC9JC,EAAK,GAAKtB,IAAasB,EAAK,GAAKtB,GACnCoB,EAAUC,GAAKpB,GAAM,UAAUoB,GAE/BpB,GAAM,UAAUoB,GAAKD,EAAUC,EAEnC,MACEpB,GAAM,UAAUoB,GAAKD,EAAUC,GAGnC,OAAOD,CACT,CAEO,SAASG,GAASC,EAAeC,EAA2B,CACjE,IAAMC,EAA4B,CAAC,EACnC,GAAI,CAACF,EAAM,OAAS,CAACA,EAAM,MAAM,IAAM,CAACA,EAAM,MAAM,GAAI,OAAOA,EAC/DvB,GAAM,QAAU,CACd,CAAC,EAAG,CAAC,EACL,CAACuB,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,EAAGA,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,CAAC,EACjL,CAACA,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,EAAGA,EAAM,MAAM,GAAKA,EAAM,MAAM,GAAK,KAAK,OAAOA,EAAM,MAAM,GAAKA,EAAM,MAAM,IAAM,CAAC,EAAI,CAAC,EACjL,CAAC,EAAG,CAAC,CACP,EACAE,EAAE,IAAS,MAAIF,EAAOvB,GAAM,OAAO,EACnCyB,EAAE,OAAY,QAAM,eAAeA,EAAE,IAAK,CAACD,EAAWA,CAAS,CAAC,EAChE,IAAME,EAAW,OAAKD,EAAE,OAAQ,OAAO,EACvC,cAAO,KAAKA,CAAC,EAAE,QAASE,GAAc,UAAQF,EAAEE,EAAO,CAAC,EACjDD,CACT,CAEO,SAASE,GAAY1B,EAAkB2B,EAA0C,CACtF3B,EAAK,UAAYA,EAAK,UAAU,OAAQ4B,GAAQA,GAAOA,EAAI,QAAQ,EACnE,QAAWA,KAAO5B,EAAK,UACrB4B,EAAI,SAAW,CACbA,EAAI,SAAS,IAAMD,EAAW,GAAK7B,GAAM,QAAQ,GAAG,GAAKA,GAAM,QAAQ,GAAG,IAAM6B,EAAW,GAAK7B,GAAM,QAAQ,GAAG,GACjH8B,EAAI,SAAS,IAAMD,EAAW,GAAK7B,GAAM,QAAQ,GAAG,GAAKA,GAAM,QAAQ,GAAG,IAAM6B,EAAW,GAAK7B,GAAM,QAAQ,GAAG,EACnH,EACA8B,EAAI,YAAc,CAChBA,EAAI,SAAS,GAAKD,EAAW,GAAIC,EAAI,SAAS,GAAKD,EAAW,EAChE,EAEF,IAAME,EAAoBC,GAAK9B,EAAK,UAAU,IAAK+B,GAAOA,EAAG,QAAQ,EAAGJ,CAAU,EAClF,OAAA3B,EAAK,IAAM6B,EAAc,IACzB7B,EAAK,OAAS6B,EAAc,OACrB7B,CACT,CCxFA,IAAIgC,GACAC,GAAY,EACZC,GAAU,OAAO,iBAGfC,GAIF,CACF,MAAO,CAAC,EACR,OAAQ,CAAC,EACT,KAAM,CACR,EAEA,eAAsBC,GAAKC,EAAqC,CAC9D,OAAIC,EAAI,UAASN,GAAQ,MACpBA,GAGMK,EAAO,OAAOE,EAAI,gBAAiBP,GAAM,QAAW,GAF7DQ,GAAQ,CAAC,MAAM,EAAGH,CAAM,EACxBL,GAAQ,MAAMS,EAAUJ,EAAO,KAAK,SAAS,GAE/CJ,GAAYD,GAAM,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EAC3DC,GAAY,KAAIA,GAAY,KACzBD,EACT,CAEA,eAAeU,GAAgBC,EAAKN,EAAQO,EAAO,CACjD,IAAMC,EAAMF,EAAI,GAAG,GACbG,EAAiC,CAAC,EACpCC,EAAQ,EACZ,QAASC,EAAK,EAAGA,EAAKH,EAAI,OAAQG,IAEhC,GADAD,EAAQF,EAAIG,GAAI,GACZD,EAAQV,EAAO,KAAK,cAAe,CACrC,IAAMY,EAAqB,CAACJ,EAAIG,GAAI,GAAIH,EAAIG,GAAI,EAAE,EAClDF,EAAU,KAAK,CACb,MAAO,KAAK,MAAM,IAAMC,CAAK,EAAI,IACjC,KAAaF,GAAIG,GACjB,YAAAC,EACA,SAAU,CACR,KAAK,OAAOL,EAAM,MAAM,IAAM,GAAKK,EAAY,EAAE,EACjD,KAAK,OAAOL,EAAM,MAAM,IAAM,GAAKK,EAAY,EAAE,CACnD,CACF,CAAC,CACH,CAEFF,EAAQD,EAAU,OAAO,CAACI,EAAMC,IAAUA,EAAK,MAAQD,EAAOC,EAAK,MAAQD,EAAO,CAAC,EACnF,IAAME,EAA4B,CAAC,EAC7BC,EAAaC,GAAKR,EAAU,IAAKS,GAAOA,EAAG,QAAQ,EAAG,CAACX,EAAM,MAAM,GAAIA,EAAM,MAAM,EAAE,CAAC,EACtFY,EAAyC,CAAC,EAChD,OAAW,CAACC,EAAMC,CAAO,IAAK,OAAO,QAAeC,EAAS,EAAG,CAC9D,IAAMJ,EAAqB,CAAC,EAC5B,QAASK,EAAI,EAAGA,EAAIF,EAAQ,OAAS,EAAGE,IAAK,CAC3C,IAAMC,EAAMf,EAAU,KAAMgB,GAAOA,EAAG,OAASJ,EAAQE,EAAE,EACnDG,EAAMjB,EAAU,KAAMgB,GAAOA,EAAG,OAASJ,EAAQE,EAAI,EAAE,EACzDC,GAAOE,GAAOF,EAAI,OAASxB,EAAO,KAAK,eAAiB,IAAM0B,EAAI,OAAS1B,EAAO,KAAK,eAAiB,IAAIkB,EAAG,KAAK,CAACM,EAAI,SAAUE,EAAI,QAAQ,CAAC,CACtJ,CACAP,EAAYC,GAAQF,CACtB,CACA,IAAMS,EAAmB,CAAE,GAAI,EAAG,MAAAjB,EAAO,IAAKM,EAAO,IAAK,OAAQA,EAAO,OAAQ,UAAAP,EAAW,YAAAU,CAAY,EACxG,OAAIS,GAAUD,CAAI,EAClBZ,EAAO,KAAKY,CAAI,EACTZ,CACT,CAEA,eAAec,GAAevB,EAAKN,EAAQO,EAAO,CAChD,IAAMQ,EAA4B,CAAC,EACnC,QAASJ,EAAK,EAAGA,EAAKL,EAAI,GAAG,OAAQK,IAAM,CACzC,IAAMH,EAAMF,EAAI,GAAGK,GACbmB,EAAa,KAAK,MAAM,IAAMtB,EAAI,GAAK,EAAE,EAAI,IACnD,GAAIsB,EAAa9B,EAAO,KAAK,cAAe,CAC1C,IAAMS,EAAiC,CAAC,EACxC,QAASc,EAAI,EAAGA,EAAI,GAAIA,IAAK,CAC3B,IAAMb,EAAQF,EAAI,EAAIe,EAAI,GAC1B,GAAIb,EAAQV,EAAO,KAAK,cAAe,CACrC,IAAMY,EAAqB,CAACJ,EAAI,EAAIe,EAAI,GAAIf,EAAI,EAAIe,EAAI,EAAE,EAC1Dd,EAAU,KAAK,CACb,KAAaD,GAAIe,GACjB,MAAO,KAAK,MAAM,IAAMb,CAAK,EAAI,IACjC,YAAAE,EACA,SAAU,CAAC,KAAK,OAAOL,EAAM,MAAM,IAAM,GAAKK,EAAY,EAAE,EAAG,KAAK,OAAOL,EAAM,MAAM,IAAM,GAAKK,EAAY,EAAE,CAAC,CACnH,CAAC,CACH,CACF,CACA,IAAMI,EAAaC,GAAKR,EAAU,IAAKS,GAAOA,EAAG,QAAQ,EAAG,CAACX,EAAM,MAAM,GAAIA,EAAM,MAAM,EAAE,CAAC,EAItFY,EAAiD,CAAC,EACxD,OAAW,CAACC,EAAMC,CAAO,IAAK,OAAO,QAAeC,EAAS,EAAG,CAC9D,IAAMJ,EAAqB,CAAC,EAC5B,QAASK,EAAI,EAAGA,EAAIF,EAAQ,OAAS,EAAGE,IAAK,CAC3C,IAAMC,EAAMf,EAAU,KAAMgB,GAAOA,EAAG,OAASJ,EAAQE,EAAE,EACnDG,EAAMjB,EAAU,KAAMgB,GAAOA,EAAG,OAASJ,EAAQE,EAAI,EAAE,EACzDC,GAAOE,GAAOF,EAAI,OAASxB,EAAO,KAAK,eAAiB,IAAM0B,EAAI,OAAS1B,EAAO,KAAK,eAAiB,IAAIkB,EAAG,KAAK,CAACM,EAAI,SAAUE,EAAI,QAAQ,CAAC,CACtJ,CACAP,EAAYC,GAAQF,CACtB,CACA,IAAMS,EAAmB,CAAE,GAAAhB,EAAI,MAAOmB,EAAY,IAAKd,EAAO,IAAK,OAAQA,EAAO,OAAQ,UAAW,CAAC,GAAGP,CAAS,EAAG,YAAAU,CAAY,EAC7HS,GAAUD,CAAI,EAClBZ,EAAO,KAAKY,CAAI,CAClB,CACF,CACA,OAAAZ,EAAO,KAAK,CAACgB,EAAGC,IAAMA,EAAE,MAAQD,EAAE,KAAK,EACnChB,EAAO,OAASf,EAAO,KAAK,cAAae,EAAO,OAASf,EAAO,KAAK,aAClEe,CACT,CAEA,eAAsBkB,GAAQC,EAAelC,EAAuC,CAClF,GAAI,CAACL,IAAS,EAACA,IAAA,MAAAA,GAAO,OAAO,GAAG,OAAO,MAAO,CAAC,EAC1CK,EAAO,cAAaF,GAAM,MAAM,OAAS,GAC9CD,KACA,IAAMsC,GAAYnC,EAAO,KAAK,UAAY,GAAMoC,EAAI,EAAItC,GAAM,KACxDuC,EAAYxC,IAAWG,EAAO,KAAK,YAAc,GACvD,OAAIA,EAAO,aAAemC,GAAYE,EAC7BvC,GAAM,OAER,IAAI,QAAQ,MAAOwC,GAAY,CACpC,IAAMC,EAA4B,CAAC,EACnC1C,GAAU,EAmCV0C,EAAE,MAAYC,GAASN,EAAOtC,EAAS,EACvC2C,EAAE,IAAM5C,IAAA,YAAAA,GAAO,QAAQ4C,EAAE,OACzBzC,GAAM,KAAOsC,EAAI,EACjB,IAAM9B,EAAM,MAAMiC,EAAE,IAAI,MAAM,EAC9BzC,GAAM,OAAUyC,EAAE,IAAI,MAAM,KAAO,GAC/B,MAAMlC,GAAgBC,EAAKN,EAAQkC,CAAK,EACxC,MAAML,GAAevB,EAAKN,EAAQkC,CAAK,EAC3C,QAAWP,KAAQ7B,GAAM,OACnB2C,GAAYd,EAAM,CAACO,EAAM,MAAM,IAAM,EAAGA,EAAM,MAAM,IAAM,CAAC,CAAC,EAC5DQ,GAAOf,EAAK,SAAS,EAE3B,OAAO,KAAKY,CAAC,EAAE,QAASI,GAAc,UAAQJ,EAAEI,EAAO,CAAC,EAExDL,EAAQxC,GAAM,MAAM,CACtB,CAAC,CACH,CC1KA,IAAI8C,GACAC,GAA4B,CAAC,EAC7BC,GAAW,EACXC,GAAU,OAAO,iBACjBC,GAAY,EAEVC,GAAW,IAEjB,eAAsBC,GAAKC,EAAqC,CAC9D,GAAI,CAACP,IAASQ,EAAI,QAAS,CACzBR,GAAQ,MAAMS,EAAUF,EAAO,OAAO,SAAS,EAC/C,IAAMG,EAAS,OAAO,OAAOV,GAAM,eAAe,MAAS,EAC3DI,GAAY,MAAM,QAAQM,CAAM,EAAI,SAASA,EAAO,GAAG,YAAY,IAAI,GAAG,IAAI,EAAI,CACpF,MAAWH,EAAO,OAAOI,EAAI,gBAAiBX,GAAM,QAAW,EAC/D,OAAOA,EACT,CAEA,eAAeY,GAAQC,EAAeC,EAA+BP,EAAgB,CACnF,IAAIQ,EAAK,EACLC,EAA+B,CAAC,EACpC,QAAWC,IAAc,CAAC,EAAG,EAAG,CAAC,EAE5B,OAAK,SAAY,CAClB,IAAMC,EAAWD,EAAa,GAExBE,EAAa,UAAQN,EAAI,KAAMO,GAAeA,EAAE,MAAM,KAAQF,GAAY,IAAOE,EAAE,MAAM,IAAM,KAAOC,GAAO,MAAO,CAAC,EACrHC,EAAe,UAAQT,EAAI,KAAMO,GAAeA,EAAE,MAAM,KAAQF,GAAY,IAAOE,EAAE,MAAM,IAAM,GAAKC,GAAO,MAAO,CAAC,EAErHE,EAAS,MADED,EAAU,QAAQ,CAAC,GAAI,EAAGA,EAAU,MAAM,GAAK,CAAC,CAAC,EACpC,OAAO,CAAC,EAAE,MAAM,EACxCE,EAAS,MAAML,EAAQ,MAAM,EACnC,QAASM,EAAI,EAAGA,EAAIN,EAAQ,MAAM,GAAIM,IACpC,QAASC,EAAI,EAAGA,EAAIP,EAAQ,MAAM,GAAIO,IAAK,CACzC,IAAMC,EAAQH,EAAOC,GAAGC,GACxB,GAAIC,GAASpB,EAAO,OAAO,eAAiB,IAAMmB,IAAM,GAAI,CAC1D,IAAME,GAAM,GAAM,KAAK,MAAMH,EAAIP,CAAQ,GAAKA,EACxCW,GAAM,GAAM,KAAK,MAAMJ,EAAIP,CAAQ,GAAKA,EACxCY,EAAYP,EAAOE,GAAG,IAAKL,GAAcA,GAAKF,EAAWD,EAAab,GAAU,EAChF,CAAC2B,EAAGC,CAAC,EAAI,CACbJ,EAAMvB,GAAWY,EAAaa,EAAU,GACxCD,EAAMxB,GAAWY,EAAaa,EAAU,EAC1C,EACM,CAACG,EAAGC,CAAC,EAAI,CACbN,EAAMvB,GAAWY,EAAaa,EAAU,GAAMC,EAC9CF,EAAMxB,GAAWY,EAAaa,EAAU,GAAME,CAChD,EACIG,EAAc,CAACJ,EAAGC,EAAGC,EAAGC,CAAC,EAC7BC,EAASA,EAAO,IAAKf,GAAM,KAAK,IAAI,EAAG,KAAK,IAAIA,EAAG,CAAC,CAAC,CAAC,EACtD,IAAMgB,EAAM,CACVD,EAAO,GAAKrB,EAAY,GACxBqB,EAAO,GAAKrB,EAAY,GACxBqB,EAAO,GAAKrB,EAAY,GACxBqB,EAAO,GAAKrB,EAAY,EAC1B,EACMuB,EAAS,CACb,GAAItB,IAEJ,MAAO,KAAK,MAAM,IAAMY,CAAK,EAAI,IACjC,MAAOD,EAAI,EACX,MAAOL,GAAOK,GAAG,MAGjB,IAAKU,EAAI,IAAKhB,GAAM,KAAK,MAAMA,CAAC,CAAC,EACjC,OAAAe,CACF,EACAnB,EAAQ,KAAKqB,CAAM,CACrB,CACF,CAEJ,CAAC,EAGHxB,EAAI,QAASyB,GAAS,UAAQA,CAAC,CAAC,EAIhC,IAAMC,EAAWvB,EAAQ,IAAKI,GAAM,CAACA,EAAE,OAAO,GAAIA,EAAE,OAAO,GAAIA,EAAE,OAAO,GAAIA,EAAE,OAAO,EAAE,CAAC,EAClFoB,EAAYxB,EAAQ,IAAKI,GAAMA,EAAE,KAAK,EACxCqB,EAAwB,CAAC,EAC7B,GAAIF,GAAYA,EAAS,OAAS,EAAG,CACnC,IAAMG,EAAM,MAAS,QAAM,uBAAuBH,EAAUC,EAAWjC,EAAO,OAAO,YAAaA,EAAO,OAAO,aAAcA,EAAO,OAAO,aAAa,EACzJkC,EAAS,MAAMC,EAAI,KAAK,EACrB,UAAQA,CAAG,CAChB,CAGA,OAAA1B,EAAUA,EACP,OAAO,CAAC2B,EAAMC,IAAQH,EAAO,SAASG,CAAG,CAAC,EAC1C,KAAK,CAACxB,EAAGyB,IAAOA,EAAE,MAAQzB,EAAE,KAAM,EAE9BJ,CACT,CAEA,eAAsB8B,GAAQC,EAAexC,EAAyC,CACpF,IAAMyC,GAAYzC,EAAO,OAAO,UAAY,GAAM0C,EAAI,EAAI/C,GACpDgD,EAAY/C,IAAWI,EAAO,OAAO,YAAc,GACzD,OAAIA,EAAO,aAAeyC,GAAYE,GAAcjD,GAAK,OAAS,GAChEE,KACOF,KAETE,GAAU,EACN,CAACK,EAAI,QAAQ,SAAS,KAAK,GAAK,CAACA,EAAI,QAAQ,SAAS,eAAe,EAAUP,GAC5E,IAAI,QAAQ,MAAOkD,GAAY,CACpC,IAAMC,EAAa,CAACL,EAAM,MAAM,IAAM,EAAGA,EAAM,MAAM,IAAM,CAAC,EACtDM,EAAY,QAAM,eAAeN,EAAO,CAAC3C,GAAWA,EAAS,EAAG,EAAK,EACrEkD,EAAU,MAAID,EAAQE,EAAU,KAAK,EACrCC,EAAYF,EAAK,UAAU,CAAC,EAAG,EAAG,EAAG,CAAC,CAAC,EAC1C,UAAQA,CAAI,EACZ,UAAQD,CAAM,EAEjB,IAAII,EACAlD,EAAO,OAAO,UAASkD,EAAUzD,GAAM,QAAQwD,CAAS,GAC5DtD,GAAW+C,EAAI,EACZ,UAAQO,CAAS,EAEpB,IAAME,EAAM,MAAM9C,GAAQ6C,EAAqBL,EAAgC7C,CAAM,EACrFN,GAAOyD,EACPP,EAAQO,CAAG,CACb,CAAC,EACH,CC/HO,IAAMC,GAAY,CACvB,OAAQ,UAAW,WAAY,UAAW,WAAY,eACtD,gBAAiB,YAAa,aAAc,YAAa,aACzD,UAAW,WAAY,WAAY,YAAa,YAAa,YAC/D,EAEaC,GAAQD,GAAU,OAElBE,GAAUF,GAAU,OAAO,CAACG,EAAQC,EAAWC,KAC1DF,EAAOC,GAAaC,EACbF,GACN,CAAC,CAAC,EAECG,GAAqB,CACzB,CAAC,UAAW,cAAc,EAAG,CAAC,YAAa,cAAc,EACzD,CAAC,YAAa,WAAW,EAAG,CAAC,UAAW,UAAU,EAClD,CAAC,WAAY,WAAW,EAAG,CAAC,WAAY,eAAe,EACvD,CAAC,aAAc,eAAe,EAAG,CAAC,aAAc,YAAY,EAC5D,CAAC,WAAY,WAAW,EAAG,CAAC,YAAa,YAAY,EACrD,CAAC,eAAgB,eAAe,EAAG,CAAC,UAAW,UAAU,CAC3D,EACaC,GAAuBD,GAAmB,IAAI,CAAC,CAACE,EAAYC,CAAU,IAAO,CAACP,GAAQM,GAAaN,GAAQO,EAAW,CAAE,EAExHC,GAAY,CACvB,CAAC,OAAQ,SAAS,EAAG,CAAC,UAAW,SAAS,EAAG,CAAC,OAAQ,UAAU,EAChE,CAAC,WAAY,UAAU,EAAG,CAAC,OAAQ,cAAc,EACjD,CAAC,eAAgB,WAAW,EAAG,CAAC,YAAa,WAAW,EACxD,CAAC,eAAgB,SAAS,EAAG,CAAC,UAAW,UAAU,EACnD,CAAC,WAAY,WAAW,EAAG,CAAC,OAAQ,eAAe,EACnD,CAAC,gBAAiB,YAAY,EAAG,CAAC,aAAc,YAAY,EAC5D,CAAC,gBAAiB,UAAU,EAAG,CAAC,WAAY,WAAW,EACvD,CAAC,YAAa,YAAY,CAC5B,EAgBO,SAASC,GAAeC,EAA6C,CAC1E,IAAMC,EAAQD,EAAU,OAAO,CAAC,CAAE,KAAAE,EAAM,KAAAC,EAAM,KAAAC,EAAM,KAAAC,CAAK,EAAG,CAAE,SAAU,CAAE,EAAAC,EAAG,EAAAC,CAAE,CAAE,KAAO,CACtF,KAAM,KAAK,IAAIL,EAAMI,CAAC,EACtB,KAAM,KAAK,IAAIH,EAAMI,CAAC,EACtB,KAAM,KAAK,IAAIH,EAAME,CAAC,EACtB,KAAM,KAAK,IAAID,EAAME,CAAC,CACxB,GAAI,CACF,KAAM,OAAO,kBACb,KAAM,OAAO,kBACb,KAAM,OAAO,kBACb,KAAM,OAAO,iBACf,CAAC,EACD,MAAO,CAACN,EAAM,KAAMA,EAAM,KAAMA,EAAM,KAAOA,EAAM,KAAMA,EAAM,KAAOA,EAAM,IAAI,CAClF,CAEO,SAASO,GAAWC,EAAO,CAACC,EAAQC,CAAK,EAAG,CAACC,EAAuBC,CAAoB,EAAsB,CACnH,IAAMC,EAASJ,EAASE,EAClBG,EAASJ,EAAQE,EACjBG,EAAY,CAACC,EAAMC,KAAmB,CAC1C,GAAIA,EACJ,MAAOD,EAAK,MACZ,OAAQ,CAACA,EAAK,IAAI,GAAKJ,EAAsBI,EAAK,IAAI,GAAKL,EAAuBK,EAAK,IAAI,GAAKJ,EAAsBI,EAAK,IAAI,GAAKL,CAAqB,EACzJ,IAAK,CAAC,KAAK,MAAMK,EAAK,IAAI,GAAKF,CAAM,EAAG,KAAK,MAAME,EAAK,IAAI,GAAKH,CAAM,EAAG,KAAK,MAAMG,EAAK,IAAI,GAAKF,CAAM,EAAG,KAAK,MAAME,EAAK,IAAI,GAAKH,CAAM,CAAC,EAC5I,UAAWG,EAAK,UAAU,IAAI,CAAC,CAAE,MAAAE,EAAO,KAAAC,EAAM,SAAAC,CAAS,KAAO,CAC5D,MAAOF,EACP,KAAMC,EACN,SAAU,CAAC,KAAK,MAAMC,EAAS,EAAIN,CAAM,EAAG,KAAK,MAAMM,EAAS,EAAIP,CAAM,CAAC,EAC3E,YAAa,CAACO,EAAS,EAAIT,EAAuBS,EAAS,EAAIT,CAAqB,CACtF,EAAE,EACF,YAAa,CAAC,CAChB,GAEA,OADoBH,EAAM,IAAI,CAACQ,EAAMC,IAAMF,EAAUC,EAAMC,CAAC,CAAC,CAE/D,CAGO,IAAMI,GAAN,KAAc,CAKnB,YAAYC,EAASC,EAAiB,CAJtCC,EAAA,sBACAA,EAAA,yBACAA,EAAA,wBAGE,KAAK,cAAgB,IAAI,MAAMF,CAAO,EACtC,KAAK,iBAAmB,GACxB,KAAK,gBAAkBC,CACzB,CAEA,QAAQlB,EAAG,CACT,KAAK,cAAc,EAAE,KAAK,kBAAoBA,EAC9C,KAAK,KAAK,KAAK,gBAAgB,CACjC,CAEA,SAAU,CACR,IAAMoB,EAAM,KAAK,cAAc,GAC/B,YAAK,SAAS,EAAG,KAAK,kBAAkB,EACxC,KAAK,KAAK,CAAC,EACX,KAAK,cAAc,KAAK,iBAAmB,GAAK,KACzCA,CACT,CAEA,OAAQ,CAAE,OAAO,KAAK,mBAAqB,EAAI,CAE/C,MAAO,CAAE,OAAO,KAAK,iBAAmB,CAAG,CAE3C,KAAM,CAAE,OAAO,KAAK,cAAc,MAAM,EAAG,KAAK,iBAAmB,CAAC,CAAG,CAEvE,KAAM,CAAE,OAAO,KAAK,cAAc,EAAI,CAEtC,KAAKC,EAAG,CACN,KAAOA,EAAI,GAAK,KAAK,KAAK,KAAK,MAAMA,EAAI,CAAC,EAAGA,CAAC,GAC5C,KAAK,SAASA,EAAG,KAAK,MAAMA,EAAI,CAAC,CAAC,EAClCA,EAAI,KAAK,MAAMA,EAAI,CAAC,CAExB,CAEA,KAAKA,EAAG,CACN,KAAO,EAAIA,GAAK,KAAK,kBAAkB,CACrC,IAAIC,EAAI,EAAID,EAEZ,GADIC,EAAI,KAAK,kBAAoB,KAAK,KAAKA,EAAGA,EAAI,CAAC,GAAGA,IAClD,CAAC,KAAK,KAAKD,EAAGC,CAAC,EAAG,MACtB,KAAK,SAASD,EAAGC,CAAC,EAClBD,EAAIC,CACN,CACF,CAEA,WAAWV,EAAG,CAEZ,OAAO,KAAK,gBAAgB,KAAK,cAAcA,EAAE,CACnD,CAEA,KAAKA,EAAGU,EAAG,CACT,OAAO,KAAK,WAAWV,CAAC,EAAI,KAAK,WAAWU,CAAC,CAC/C,CAEA,SAASV,EAAGU,EAAG,CACb,IAAMC,EAAI,KAAK,cAAcX,GAC7B,KAAK,cAAcA,GAAK,KAAK,cAAcU,GAC3C,KAAK,cAAcA,GAAKC,CAC1B,CACF,EAEO,SAASC,GAAevB,EAAGD,EAAGyB,EAAUC,EAAS,CACtD,MAAO,CACL,EAAGA,EAAQ,IAAIzB,EAAGD,EAAGyB,CAAQ,EAC7B,EAAGC,EAAQ,IAAIzB,EAAGD,EAAGyB,EAAWE,EAAK,CACvC,CACF,CAEO,SAASC,GAAed,EAAMe,EAAcH,EAAS,CAC1D,GAAM,CAAE,SAAAI,EAAU,SAAAC,EAAU,GAAIN,CAAS,EAAIX,EACvC,CAAE,EAAAb,EAAG,EAAAD,CAAE,EAAIwB,GAAeM,EAAUC,EAAUN,EAAUC,CAAO,EACrE,MAAO,CACL,EAAGZ,EAAK,SAAWe,EAAe7B,EAClC,EAAGc,EAAK,SAAWe,EAAe5B,CACpC,CACF,CAUO,SAAS+B,GAAMC,EAAGC,EAAKC,EAAK,CACjC,OAAIF,EAAIC,EAAYA,EAChBD,EAAIE,EAAYA,EACbF,CACT,CAEO,SAASG,GAAgBC,EAAIC,EAAIC,EAAIC,EAAI,CAC9C,IAAMC,EAAKF,EAAKF,EACVK,EAAKF,EAAKF,EAChB,OAAOG,EAAKA,EAAKC,EAAKA,CACxB,CAEO,SAASC,GAAWV,EAAGW,EAAG,CAC/B,MAAO,CAAE,EAAGX,EAAE,EAAIW,EAAE,EAAG,EAAGX,EAAE,EAAIW,EAAE,CAAE,CACtC,CCnLA,IAAIC,GACEC,GAAiB,CAAC,+BAA6C,gCAAoD,yCAA+D,wCAA6D,EAC/OC,GAAqB,EACrBC,GAAe,GACfC,GAAmB,IAAM,EAE/B,SAASC,GAASC,EAAQC,EAAgBC,EAAUC,EAAQC,EAASC,EAAeC,EAAmB,EAAG,CACxG,IAAMC,EAAmBC,IAAW,CAClC,EAAGH,EAAc,IAAIG,EAAM,EAAGA,EAAM,EAAGR,CAAM,EAC7C,EAAGK,EAAc,IAAIG,EAAM,EAAGA,EAAM,EAAIH,EAAc,MAAM,GAAK,EAAKL,CAAM,CAC9E,GACMS,EAA2B,CAACD,EAAOE,EAAQC,KAAW,CAC1D,EAASC,GAAM,KAAK,MAAMJ,EAAM,EAAIX,EAAY,EAAG,EAAGa,EAAS,CAAC,EAChE,EAASE,GAAM,KAAK,MAAMJ,EAAM,EAAIX,EAAY,EAAG,EAAGc,EAAQ,CAAC,CACjE,GAEM,CAACD,EAAQC,CAAK,EAAIR,EAAO,MAEzBU,EAAwBJ,EAAyBR,EAAe,SAAUS,EAAQC,CAAK,EACvFG,EAAeP,EAAgBM,CAAqB,EAEtDE,EADyBC,GAAWf,EAAe,SAAUa,CAAY,EAE7E,QAASG,EAAI,EAAGA,EAAIX,EAAkBW,IAAK,CACzC,IAAMC,EAAwBT,EAAyBM,EAAgBL,EAAQC,CAAK,EAC9EQ,EAAoBC,GAAeF,EAAsB,EAAGA,EAAsB,EAAGhB,EAAUE,CAAO,EAC5GW,EAAuBC,GACrB,CAAE,EAAGE,EAAsB,EAAIrB,GAAc,EAAGqB,EAAsB,EAAIrB,EAAa,EACvF,CAAE,EAAGsB,EAAY,EAAG,EAAGA,EAAY,CAAE,CACvC,CACF,CACA,IAAME,EAAwBZ,EAAyBM,EAAgBL,EAAQC,CAAK,EAC9EW,EAAQnB,EAAO,IAAIkB,EAAsB,EAAGA,EAAsB,EAAGnB,CAAQ,EACnF,MAAO,CAAE,SAAUa,EAAgB,KAAYQ,GAAUrB,GAAW,MAAAoB,CAAM,CAC5E,CAEO,SAASE,GAAWC,EAAMtB,EAAQC,EAASsB,EAAkBC,EAAkB,CACpF,IAAMC,EAAeC,GAAU,IAAI,CAAC,CAACC,EAAgBC,CAAa,IAAO,CAAOC,GAAQF,GAAuBE,GAAQD,EAAc,CAAE,EACjIE,EAAWL,EAAO,IAAI,CAAC,CAAC,CAAEM,CAAY,IAAMA,CAAY,EACxDC,EAAWP,EAAO,IAAI,CAAC,CAACQ,CAAa,IAAMA,CAAa,EACxDC,EAAWlC,EAAO,MAAM,GACxBmC,EAAWL,EAAS,OACpBM,EAAY,IAAI,MAAMF,CAAQ,EAE9BG,EAAkBC,GAAehB,EAAK,KAAM5B,GAAcO,CAAO,EACvEmC,EAAUd,EAAK,KAAK,IAAM,CACxB,MAAOA,EAAK,MACZ,KAAYF,GAAUE,EAAK,KAAK,IAChC,SAAUe,CACZ,EAEA,QAASE,EAAOJ,EAAW,EAAGI,GAAQ,EAAG,EAAEA,EAAM,CAC/C,IAAMC,EAAWV,EAASS,GACpBxC,EAAWiC,EAASO,GACtBH,EAAUI,IAAa,CAACJ,EAAUrC,KACpCqC,EAAUrC,GAAYH,GAAS2C,EAAMH,EAAUI,GAAWzC,EAAUC,EAAQC,EAASuB,CAAgB,EAEzG,CAEA,QAASe,EAAO,EAAGA,EAAOJ,EAAU,EAAEI,EAAM,CAC1C,IAAMC,EAAWR,EAASO,GACpBxC,EAAW+B,EAASS,GACtBH,EAAUI,IAAa,CAACJ,EAAUrC,KACpCqC,EAAUrC,GAAYH,GAAS2C,EAAMH,EAAUI,GAAWzC,EAAUC,EAAQC,EAASsB,CAAgB,EAEzG,CACA,OAAOa,CACT,CAEA,SAASK,GAA4BC,EAAYvB,EAAOwB,EAAUC,EAAU5C,EAAQ,CAClF,GAAM,CAACO,EAAQC,CAAK,EAAIR,EAAO,MAC3B6C,EAAe,GACbC,EAAS,KAAK,IAAIH,EAAWlD,GAAoB,CAAC,EAClDsD,EAAO,KAAK,IAAIJ,EAAWlD,GAAqB,EAAGc,CAAM,EAC/D,QAASyC,EAAWF,EAAQE,EAAWD,EAAM,EAAEC,EAAU,CACvD,IAAMC,EAAS,KAAK,IAAIL,EAAWnD,GAAoB,CAAC,EAClDyD,EAAO,KAAK,IAAIN,EAAWnD,GAAqB,EAAGe,CAAK,EAC9D,QAAS2C,EAAWF,EAAQE,EAAWD,EAAM,EAAEC,EAC7C,GAAInD,EAAO,IAAIgD,EAAUG,EAAUT,CAAU,EAAIvB,EAAO,CACtD0B,EAAe,GACf,KACF,CAEF,GAAI,CAACA,EAAc,KACrB,CACA,OAAOA,CACT,CAEO,SAASO,GAAwBC,EAAerD,EAAQ,CAC7D,GAAM,CAACO,EAAQC,EAAO8C,CAAY,EAAItD,EAAO,MACvCuD,EAAQ,IAAUC,GAAQjD,EAASC,EAAQ8C,EAAc,CAAC,CAAE,MAAAnC,CAAM,IAAMA,CAAK,EACnF,QAASwB,EAAW,EAAGA,EAAWpC,EAAQ,EAAEoC,EAC1C,QAASC,EAAW,EAAGA,EAAWpC,EAAO,EAAEoC,EACzC,QAASF,EAAa,EAAGA,EAAaY,EAAc,EAAEZ,EAAY,CAChE,IAAMvB,EAAQnB,EAAO,IAAI2C,EAAUC,EAAUF,CAAU,EAEnDvB,EAAQkC,GAERZ,GAA4BC,EAAYvB,EAAOwB,EAAUC,EAAU5C,CAAM,GAAGuD,EAAM,QAAQ,CAAE,MAAApC,EAAO,KAAM,CAAE,SAAAwB,EAAU,SAAAC,EAAU,GAAIF,CAAW,CAAE,CAAC,CACvJ,CAGJ,OAAOa,CACT,CAEA,SAASE,GAAaC,EAAO,CAAE,EAAAC,EAAG,EAAAC,CAAE,EAAGlB,EAAY,CACjD,OAAOgB,EAAM,KAAK,CAAC,CAAE,UAAAtB,CAAU,IAAM,CAxHvC,IAAAyB,EAyHI,IAAMC,GAAwBD,EAAAzB,EAAUM,KAAV,YAAAmB,EAAuB,SACrD,OAAKC,EACQC,GAAgBH,EAAGD,EAAGG,EAAsB,EAAGA,EAAsB,CAAC,GAAKnE,GADrD,EAErC,CAAC,CACH,CAEA,SAASqE,GAAiBC,EAAe7B,EAAW,CAKlD,OAJoCA,EAAU,OAAO,CAAC8B,EAAQ,CAAE,SAAAC,EAAU,MAAAhD,CAAM,EAAGuB,KAC5Ee,GAAaQ,EAAeE,EAAUzB,CAAU,IAAGwB,GAAU/C,GAC3D+C,GACN,CAAG,EAC+B9B,EAAU,MACjD,CAEO,SAASgC,GAAOnE,EAASD,EAAQuB,EAAkBC,EAAkB6C,EAAahB,EAAe,CACtG,IAAMK,EAAuD,CAAC,EACxDH,EAAQH,GAAwBC,EAAerD,CAAM,EAE3D,KAAO0D,EAAM,OAASW,GAAe,CAACd,EAAM,MAAM,GAAG,CAEnD,IAAMjC,EAAOiC,EAAM,QAAQ,EAGrBe,EAAwBhC,GAAehB,EAAK,KAAM5B,GAAcO,CAAO,EAE7E,GAAIwD,GAAaC,EAAOY,EAAiBhD,EAAK,KAAK,EAAE,EAAG,SAExD,IAAIc,EAAYf,GAAWC,EAAMtB,EAAQC,EAASsB,EAAkBC,CAAgB,EACpFY,EAAYA,EAAU,OAAQmC,GAAMA,EAAE,MAAQlB,CAAa,EAC3D,IAAMlC,EAAQ6C,GAAiBN,EAAOtB,CAAS,EACzCoC,EAAYC,GAAerC,CAAS,EACtCjB,EAAQkC,GAAeK,EAAM,KAAK,CAAE,UAAAtB,EAAW,IAAAoC,EAAK,MAAO,KAAK,MAAM,IAAMrD,CAAK,EAAI,GAAI,CAAC,CAChG,CACA,OAAOuC,CACT,CAEA,eAAsBgB,GAAQC,EAAeC,EAAuC,CAIlF,IAAMC,EAAS,OAAK,IAAM,CACxB,GAAI,CAACtF,GAAM,OAAO,GAAG,MAAO,MAAO,CAAC,EACpC,IAAMuF,EAAa,QAAM,eAAeH,EAAO,CAACpF,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,CAAC,EAC7FwF,EAAgB,MAAO,MAAO,OAAKD,EAAS,SAAS,EAAG,KAAK,EAAG,CAAG,EAEnEE,EADyBzF,GAAM,QAAQwF,EAAYvF,EAAc,EAC7C,IAAKoE,GAAS,UAAQA,EAAG,CAAC,CAAC,CAAC,CAAC,EACvD,OAAAoB,EAAU,GAAQ,UAAQA,EAAU,EAAE,EAC/BA,CACT,CAAC,EAEKC,EAAU,MAAM,QAAQ,IAAIJ,EAAI,IAAKK,GAAmBA,EAAO,OAAO,CAAC,CAAC,EAC9E,QAAWC,KAAKN,EAAQ,UAAQM,CAAC,EAEjC,IAAMC,EAAU,MAAMhB,GAAOa,EAAQ,GAAIA,EAAQ,GAAIA,EAAQ,GAAIA,EAAQ,GAAIL,EAAO,KAAK,YAAaA,EAAO,KAAK,aAAa,EAC/H,OAAKrF,GAAM,OAAO,GAAG,MACA8F,GAAWD,EAAS,CAACT,EAAM,MAAM,GAAIA,EAAM,MAAM,EAAE,EAAG,CAACpF,GAAM,OAAO,GAAG,MAAM,GAAIA,GAAM,OAAO,GAAG,MAAM,EAAE,CAAC,EAD5F,CAAC,CAGtC,CAEA,eAAsB+F,GAAKV,EAAqC,CAC9D,MAAI,CAACrF,IAASgG,EAAI,QAAShG,GAAQ,MAAMiG,EAAUZ,EAAO,KAAK,SAAS,EAC/DA,EAAO,OAAOa,EAAI,gBAAiBlG,GAAM,QAAW,EACtDA,EACT,CCtKA,IAAImG,GACAC,GAAO,GAEX,eAAsBC,GAAKC,EAAqC,CAC9D,MAAI,CAACH,IAASI,EAAI,QAASJ,GAAQ,MAAMK,EAAUF,EAAO,aAAa,SAAS,EACvEA,EAAO,OAAOG,EAAI,gBAAiBN,GAAM,QAAW,EACtDA,EACT,CAEA,eAAsBO,GAAQC,EAAcC,EAA+BN,EACoB,CA5B/F,IAAAO,EAAAC,EA6BE,GAAIV,GAAM,MAAO,CAAE,KAAM,CAAC,EAAG,OAAQ,KAAM,MAAO,IAAK,EACvDA,GAAO,GACFD,IAAO,MAAME,GAAKC,CAAM,EAC7B,IAAMS,EAAa,MAAYL,GAAQC,EAAOL,CAAM,EAC9CU,IAAQH,EAAAE,EAAW,SAAX,YAAAF,EAAmB,MAAM,KAAM,EACvCI,IAASH,EAAAC,EAAW,SAAX,YAAAD,EAAmB,MAAM,KAAM,EAC9C,GAAI,CAACC,EAAW,OAAQ,MAAO,CAAE,KAAM,CAAC,EAAG,OAAQ,KAAM,MAAO,IAAK,EACrE,IAAMG,EAA4B,CAAC,EAEnCA,EAAE,OAAY,QAAM,eAAeH,EAAW,OAAQ,CAACZ,GAAM,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,EAAGA,GAAM,OAAO,GAAG,MAAQA,GAAM,OAAO,GAAG,MAAM,GAAK,CAAC,EAAG,EAAK,EACtK,UAAQY,EAAW,MAAM,EAC5BG,EAAE,KAAU,MAAIA,EAAE,OAAQC,EAAU,KAAK,EACzCD,EAAE,IAAMf,GAAM,QAAQe,EAAE,IAAI,EAE5BA,EAAE,QAAa,UAAQA,EAAE,IAAK,CAAC,EAC3BA,EAAE,QAAQ,MAAM,KAAO,GACzBA,EAAE,QAAa,UAAQA,EAAE,OAAO,EAChC,CAACA,EAAE,GAAIA,EAAE,EAAE,EAAO,UAAQA,EAAE,QAAS,CAAC,EACtCA,EAAE,OAAY,aAAWA,EAAE,GAAI,CAAC,EAChCA,EAAE,IAAS,aAAWA,EAAE,OAAQ,CAAC,EACjCA,EAAE,KAAU,QAAM,cAAcA,EAAE,IAAK,CAAC,CAAC,EAAG,EAAG,GAAK,EAAG,CAAC,EAAG,CAAC,CAAC,EAAG,CAACF,EAAOC,CAAM,CAAC,EAI/EC,EAAE,KAAU,UAAQA,EAAE,KAAM,CAAC,GAE7BA,EAAE,KAAU,QAAM,eAAeA,EAAE,QAAS,CAACD,EAAQD,CAAK,CAAC,EAE7D,IAAMI,EAAO,MAAM,KAAK,MAAMF,EAAE,KAAK,KAAK,CAAC,EAE3C,GAAIX,EAAI,MAAQ,CAACA,EAAI,QAAW,OAAO,WAAc,YACnD,OAAID,EAAO,OAAOG,EAAI,wBAAwB,EAC9C,OAAO,KAAKS,CAAC,EAAE,QAASG,GAAc,UAAQH,EAAEG,EAAO,CAAC,EACjD,CAAE,KAAAD,EAAM,OAAQ,KAAM,MAAO,IAAK,EAG3C,IAAME,EAAoBC,GAAOP,EAAOC,CAAM,EAEvC,WAAS,MAAS,UAAQ,SAASC,EAAE,KAAMI,CAAW,EAC7D,IAAME,EAAWF,EAAY,WAAW,IAAI,EACxChB,EAAO,aAAa,MAAQA,EAAO,aAAa,KAAO,IAAGkB,EAAS,OAAS,QAAQlB,EAAO,aAAa,WAC5G,IAAMmB,EAAYD,EAAS,aAAa,EAAG,EAAGR,EAAOC,CAAM,EAErDS,EAAwBH,GAAOP,EAAOC,CAAM,EAC5CU,EAAeD,EAAgB,WAAW,IAAI,EAChDX,EAAW,QAAQY,EAAa,UAAUZ,EAAW,OAAQ,EAAG,CAAC,EACrEY,EAAa,yBAA2B,SACpCrB,EAAO,aAAa,MAAQA,EAAO,aAAa,KAAO,IAAGqB,EAAa,OAAS,QAAQrB,EAAO,aAAa,WAChHqB,EAAa,UAAUL,EAAa,EAAG,CAAC,EACxCK,EAAa,yBAA2B,cACxCA,EAAa,OAAS,OACtB,IAAMC,EAAgBD,EAAa,aAAa,EAAG,EAAGX,EAAOC,CAAM,EACnE,QAASY,EAAI,EAAGA,EAAIb,EAAQC,EAAQY,IAAKD,EAAc,KAAK,EAAIC,EAAI,GAAKJ,EAAU,KAAK,EAAII,EAAI,GAChGF,EAAa,aAAaC,EAAe,EAAG,CAAC,EAE7C,IAAIE,EAAiC,KACrC,GAAIlB,GAAcc,EAAiB,CACjCI,EAAqBP,GAAOP,EAAOC,CAAM,EACzC,IAAMc,EAAU,MAAYrB,GAAQE,EAAYN,CAAM,EACnD,UAAQyB,EAAQ,MAAM,EACzB,IAAMC,EAAWF,EAAa,WAAW,IAAI,EAC7CE,EAAS,UAAUD,EAAQ,OAA6B,EAAG,EAAGD,EAAa,MAAOA,EAAa,MAAM,EACrGE,EAAS,UAAUN,EAAiB,EAAG,CAAC,CAC1C,CAEA,cAAO,KAAKR,CAAC,EAAE,QAASG,GAAc,UAAQH,EAAEG,EAAO,CAAC,EACxDjB,GAAO,GAEA,CAAE,KAAAgB,EAAM,OAAQM,EAAiB,MAAOJ,CAAY,CAC7D,CxC9DO,IAAMW,GAAN,KAAa,CAAb,cACLC,EAAA,iBAAqD,MACrDA,EAAA,YAAgD,MAChDA,EAAA,uBAA2D,MAC3DA,EAAA,iBAAqD,MACrDA,EAAA,iBAAqD,MACrDA,EAAA,qBAAyD,MACzDA,EAAA,qBAAyD,MACzDA,EAAA,eAAmD,MACnDA,EAAA,kBAAsD,MACtDA,EAAA,gBAAoD,MACpDA,EAAA,gBAAoD,MACpDA,EAAA,eAAmD,MACnDA,EAAA,oBAAwD,MACxDA,EAAA,gBAAoD,MACpDA,EAAA,oBAAwD,MACxDA,EAAA,iBAAqD,MACrDA,EAAA,gBAAoD,MACpDA,EAAA,eAAmD,MACnDA,EAAA,eAAmD,MACnDA,EAAA,eAAmD,MACnDA,EAAA,oBAAwD,MACxDA,EAAA,iBAAqD,MACvD,EAcaC,GAAiBC,GAAgC,CAC5D,IAAIC,EAAwB,EACxBC,EAAmB,EACnBC,EAAmB,EACvB,QAAWC,KAAK,OAAO,OAAOC,EAAU,EACtCJ,GAAyBG,EAAE,iBAC3BF,GAAoBE,EAAE,kBACtBD,GAAoBC,EAAE,YAExB,IAAME,EAAmBH,EAAmB,EAAID,EAAmBC,EAAmB,EACtF,MAAO,CACL,gBAAiB,OAAO,OAAOE,EAAU,EAAE,OAC3C,iBAAkB,OAClB,iBAAkB,OAAO,KAAKL,EAAS,MAAM,EAAE,OAC/C,iBAAAM,EACA,sBAAAL,EACA,iBAAAC,EACA,iBAAAC,EACA,iBAAkB,OAClB,WAAY,OAAO,OAAOE,EAAU,CACtC,CACF,EAEO,SAASE,GAAMP,EAAuB,CAE3C,QAAWQ,KAAS,OAAO,KAAKR,EAAS,MAAM,EAAGA,EAAS,OAAOQ,GAAyB,IAC7F,CAGA,eAAsBC,GAAKT,EAAgC,CAtG3D,IAAAU,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,GAAAC,EAAAC,GAuGMC,EAAI,SAASlC,GAAMP,CAAQ,EAC3BA,EAAS,OAAO,KAAK,UACnB,CAACA,EAAS,OAAO,YAAYW,GAAAD,EAAAV,EAAS,OAAO,KAAK,WAArB,YAAAU,EAA+B,YAA/B,YAAAC,EAA0C,SAAS,iBAClF,CAACX,EAAS,OAAO,SAAUA,EAAS,OAAO,YAAY,EAAI,MAAeS,GAAKT,EAAS,MAAM,GAE5F,CAACA,EAAS,OAAO,cAAgBA,EAAS,OAAO,KAAK,aAAaa,GAAAD,EAAAZ,EAAS,OAAO,KAAK,WAArB,YAAAY,EAA+B,YAA/B,YAAAC,EAA0C,SAAS,iBACxH,CAACb,EAAS,OAAO,SAAUA,EAAS,OAAO,YAAY,EAAI,MAAeS,GAAKT,EAAS,MAAM,IAG9FA,EAAS,OAAO,KAAK,SAAW,CAACA,EAAS,OAAO,aAAae,GAAAD,EAAAd,EAAS,OAAO,OAAhB,YAAAc,EAAsB,YAAtB,YAAAC,EAAiC,SAAS,gBAAcf,EAAS,OAAO,UAAsB0C,GAAS1C,EAAS,MAAM,GAEpLA,EAAS,OAAO,KAAK,SAAW,CAACA,EAAS,OAAO,iBAAmBA,EAAS,OAAO,KAAK,UAAeA,EAAS,OAAO,KAAK,SAAY,YAAcA,EAAS,OAAO,gBAA4B2C,GAAW3C,EAAS,MAAM,GAC7NA,EAAS,OAAO,KAAK,SAAW,CAACA,EAAS,OAAO,iBAAiBiB,GAAAD,EAAAhB,EAAS,OAAO,OAAhB,YAAAgB,EAAsB,YAAtB,YAAAC,EAAiC,SAAS,oBAAkBjB,EAAS,OAAO,cAA8BS,GAAKT,EAAS,MAAM,GAChMA,EAAS,OAAO,KAAK,SAAW,CAACA,EAAS,OAAO,WAAWmB,GAAAD,EAAAlB,EAAS,OAAO,OAAhB,YAAAkB,EAAsB,YAAtB,YAAAC,EAAiC,SAAS,cAAYnB,EAAS,OAAO,QAAkBS,GAAKT,EAAS,MAAM,GACxKA,EAAS,OAAO,KAAK,SAAW,CAACA,EAAS,OAAO,WAAWqB,GAAAD,EAAApB,EAAS,OAAO,OAAhB,YAAAoB,EAAsB,YAAtB,YAAAC,EAAiC,SAAS,cAAYrB,EAAS,OAAO,QAAkBS,GAAKT,EAAS,MAAM,GACxKA,EAAS,OAAO,KAAK,SAAW,CAACA,EAAS,OAAO,aAAYA,EAAS,OAAO,WAAuBS,GAAKT,EAAS,MAAM,GACxHA,EAAS,OAAO,KAAK,WAAWsB,EAAAtB,EAAS,OAAO,KAAK,YAArB,YAAAsB,EAAgC,UAAW,CAACtB,EAAS,OAAO,YAAWA,EAAS,OAAO,UAAsBS,GAAKT,EAAS,MAAM,GACjKA,EAAS,OAAO,KAAK,WAAWuB,EAAAvB,EAAS,OAAO,KAAK,WAArB,YAAAuB,EAA+B,UAAW,CAACvB,EAAS,OAAO,WAAUA,EAAS,OAAO,SAAoBS,GAAKT,EAAS,MAAM,GAC7JA,EAAS,OAAO,KAAK,WAAWwB,EAAAxB,EAAS,OAAO,KAAK,cAArB,YAAAwB,EAAkC,UAAW,CAACxB,EAAS,OAAO,UAASA,EAAS,OAAO,QAAkBS,GAAKT,EAAS,MAAM,GAC7JA,EAAS,OAAO,KAAK,WAAWyB,EAAAzB,EAAS,OAAO,KAAK,UAArB,YAAAyB,EAA8B,UAAW,CAACzB,EAAS,OAAO,UAASA,EAAS,OAAO,QAAkBS,GAAKT,EAAS,MAAM,GACzJA,EAAS,OAAO,KAAK,WAAW0B,EAAA1B,EAAS,OAAO,KAAK,OAArB,YAAA0B,EAA2B,UAAW,GAACC,EAAA3B,EAAS,OAAO,KAAK,YAArB,MAAA2B,EAAgC,UAAW,CAAC3B,EAAS,OAAO,WAAUA,EAAS,OAAO,SAAgBS,GAAKT,EAAS,MAAM,GACjMA,EAAS,OAAO,KAAK,WAAW4B,EAAA5B,EAAS,OAAO,KAAK,OAArB,YAAA4B,EAA2B,UAAW,CAAC5B,EAAS,OAAO,WAAUA,EAAS,OAAO,SAAoBS,GAAKT,EAAS,MAAM,GAEzJA,EAAS,OAAO,KAAK,WAAW6B,EAAA7B,EAAS,OAAO,KAAK,OAArB,YAAA6B,EAA8B,UAAW,CAAC7B,EAAS,OAAO,OAAMA,EAAS,OAAO,KAAYS,GAAKT,EAAS,MAAM,GAEhJA,EAAS,OAAO,KAAK,WAAW8B,EAAA9B,EAAS,OAAO,KAAK,SAArB,YAAA8B,EAAgC,UAAW,CAAC9B,EAAS,OAAO,YAAWA,EAAS,OAAO,UAAsBS,GAAKT,EAAS,MAAM,GAEjKA,EAAS,OAAO,KAAK,WAAW+B,EAAA/B,EAAS,OAAO,KAAK,SAArB,YAAA+B,EAAgC,UAAW,CAAC/B,EAAS,OAAO,eAAcA,EAAS,OAAO,aAA4BS,GAAKT,EAAS,MAAM,GAE1KA,EAAS,OAAO,KAAK,WAAWgC,EAAAhC,EAAS,OAAO,KAAK,gBAArB,YAAAgC,EAAuC,UAAW,CAAChC,EAAS,OAAO,gBAAeA,EAAS,OAAO,cAA8BS,GAAKT,EAAS,MAAM,GACpLA,EAAS,OAAO,KAAK,SAAW,CAACA,EAAS,OAAO,aAAakC,GAAAD,EAAAjC,EAAS,OAAO,KAAK,WAArB,YAAAiC,EAA+B,YAA/B,YAAAC,EAA0C,SAAS,gBAAclC,EAAS,OAAO,UAAsB2C,GAAW3C,EAAS,MAAM,GAC/LA,EAAS,OAAO,KAAK,SAAWA,EAAS,OAAO,KAAK,WAAa,CAACA,EAAS,OAAO,gBAAgBoC,GAAAD,EAAAnC,EAAS,OAAO,KAAK,WAArB,YAAAmC,EAA+B,YAA/B,YAAAC,EAA0C,SAAS,gBAAcpC,EAAS,OAAO,aAAyB4C,GAAa5C,EAAS,MAAM,GACzOA,EAAS,OAAO,OAAO,SAAW,CAACA,EAAS,OAAO,aAAasC,IAAAD,EAAArC,EAAS,OAAO,SAAhB,YAAAqC,EAAwB,YAAxB,YAAAC,GAAmC,SAAS,gBAActC,EAAS,OAAO,UAAsBS,GAAKT,EAAS,MAAM,GACpLA,EAAS,OAAO,OAAO,SAAW,CAACA,EAAS,OAAO,WAAWwC,IAAAD,EAAAvC,EAAS,OAAO,SAAhB,YAAAuC,EAAwB,YAAxB,YAAAC,GAAmC,SAAS,cAAYxC,EAAS,OAAO,QAAkBS,GAAKT,EAAS,MAAM,GAC5KA,EAAS,OAAO,aAAa,SAAW,CAACA,EAAS,OAAO,eAAcA,EAAS,OAAO,aAA4BS,GAAKT,EAAS,MAAM,GAG3I,cAAiBQ,MAAS,OAAO,KAAKR,EAAS,MAAM,EAC/CA,EAAS,OAAOQ,KAA0B,OAAOR,EAAS,OAAOQ,KAA2B,cAC9FR,EAAS,OAAOQ,IAAyB,MAAMR,EAAS,OAAOQ,IAGrE,CAEA,eAAsBqC,GAAS7C,EAAgC,CAE7D,IAAM8C,EAAY,CAAC,QAAS,cAAe,OAAQ,MAAO,UAAW,MAAO,MAAO,MAAO,KAAK,EAC/F,QAAWC,KAAW,OAAO,KAAK/C,EAAS,MAAM,EAAG,CAClD,IAAMQ,EAA2BR,EAAS,OAAO+C,GACjD,GAAI,CAACvC,EAAO,SACZ,IAAMwC,EAAgB,CAAC,EAEjBC,EAAWzC,GAAA,YAAAA,EAAO,SACxB,GAAIyC,GAAYA,EAAS,MAAM,MAC7B,QAAWC,KAAU,OAAO,OAAOD,EAAS,MAAM,KAAK,EAAG,CACxD,IAAME,EAAMD,EAAc,GAAG,YAAY,EACpCF,EAAI,SAASG,CAAE,GAAGH,EAAI,KAAKG,CAAE,CACpC,KAEI,CAACF,GAAYjD,EAAS,OAAO,OAAOoD,EAAI,kCAAmCL,CAAO,EAExF,IAAMM,EAAoB,CAAC,EAC3B,QAAWF,KAAMH,EACX,CAACF,EAAU,SAASK,CAAE,GACrB,CAACnD,EAAS,IAAI,QAAQ,SAASmD,CAAE,GACjC,CAACnD,EAAS,IAAI,QAAQ,SAASmD,EAAG,QAAQ,IAAK,EAAE,CAAC,GAClD,CAACnD,EAAS,IAAI,QAAQ,SAASmD,EAAG,QAAQ,SAAU,EAAE,CAAC,GACvD,CAACnD,EAAS,IAAI,QAAQ,SAASmD,EAAG,QAAQ,KAAM,EAAE,CAAC,GACtDE,EAAQ,KAAKF,CAAE,EAIfnD,EAAS,OAAO,OAASqD,EAAQ,OAAS,GAAGD,EAAI,2BAA4BL,EAASM,CAAO,CACnG,CACF,CyCvKO,IAAMC,EAAS,CACpB,KAAM,UACN,SAAU,IACV,OAA0B,KAC1B,GAAmC,KACnC,WAAuB,CAAC,EACxB,UAAW,CACT,MAAO,GACP,UAAW,GACX,mBAAoB,GACpB,sBAAuB,GACvB,MAAO,GACP,QAAS,GACT,6BAA8B,GAC9B,eAAgB,EAClB,CACF,EAEA,SAASC,IAAmB,CAK1B,IAAMC,EAAKF,EAAO,GACd,CAACE,IACLF,EAAO,WAAaE,EAAG,uBAAuB,EAEhD,CAOA,eAAsBC,GAASC,EAAgC,CA5C/D,IAAAC,EA8CE,GAAID,EAAS,OAAO,UAAY,YAC3BJ,EAAO,QAAW,SAAO,EAAE,WAAc,CAACA,EAAO,IAAM,CAACA,EAAO,GAAG,aAAaA,EAAO,GAAG,OAAO,KACnGM,EAAI,wCAAwC,EACrCC,GAAMH,CAAQ,GAOnB,CAAI,cAAYJ,EAAO,IAAI,GAAG,CAChC,GAAI,CACFA,EAAO,OAAS,MAAYQ,GAAO,IAAK,GAAG,CAC7C,OAASC,EAAP,CACAH,EAAI,+BAAgCG,CAAG,EACvC,MACF,CACA,GAAI,CAGF,GAFAT,EAAO,IAAKK,EAAAL,EAAO,SAAP,YAAAK,EAAe,WAAW,SAAUL,EAAO,WAEnD,CADSA,EAAO,GAAG,aAAaA,EAAO,GAAG,OAAO,EAAE,SAAS,KAAK,EAC1D,CACTM,EAAI,qEAAqE,EACzEF,EAAS,OAAO,QAAU,QAC1B,MACF,CACIJ,EAAO,SACTA,EAAO,OAAO,iBAAiB,mBAAoB,MAAOU,GAAM,CAC9D,MAAAJ,EAAI,kBAAmBI,EAAE,IAAI,EAC7BJ,EAAI,0FAA0F,EAC9FF,EAAS,KAAK,OAAO,EACf,IAAI,MAAM,mCAAmC,CAMrD,CAAC,EACDJ,EAAO,OAAO,iBAAiB,uBAAyBU,GAAM,CAC5DJ,EAAI,mCAAoCI,CAAC,CAC3C,CAAC,EACDV,EAAO,OAAO,iBAAiB,4BAA8BU,GAAM,CACjEJ,EAAI,iCAAkCI,CAAC,CACzC,CAAC,EAEL,OAASD,EAAP,CACAH,EAAI,mCAAoCG,CAAG,EAC3C,MACF,CACA,GAAI,CACC,kBAAgB,EAAGT,EAAO,EAAE,CACjC,OAASS,EAAP,CACAH,EAAI,mCAAoCG,CAAG,EAC3C,MACF,CACA,GAAI,CACF,IAAME,EAAM,IAAO,eAAaX,EAAO,EAAE,EACtC,kBAAgBA,EAAO,KAAM,IAAM,IAAO,mBAAiBW,CAAG,EAAGX,EAAO,QAAQ,CACrF,OAASS,EAAP,CACAH,EAAI,wCAAyCG,CAAG,EAChD,MACF,CACA,GAAI,CACiB,uBAAqB,OAAO,EACvC,QAASG,GAAiB,CAChC,IAAMC,EAAkB,CAAE,GAAGD,EAAc,YAAaZ,EAAO,IAAK,EACjE,iBAAea,CAAe,CACnC,CAAC,CACH,OAASJ,EAAP,CACAH,EAAI,mDAAoDG,CAAG,EAC3D,MACF,CACA,IAAMK,EAAa,UAAQ,EAAE,gBAAqB,UAAQ,EAAE,gBAAgB,EAAE,GAAK,KACnF,GAAIA,EACFR,EAAI,yBAAyBQ,EAAQ,aAAaA,EAAQ,OAAO,cAAcA,EAAQ,aAAaA,EAAQ,QAAQ,GAAG,MAClH,CACLR,EAAI,gCAAiCQ,EAASd,EAAO,EAAE,EACvD,MACF,CACA,GAAI,CACK,MAAI,EAAE,aAAa,eAAqB,MAAI,EAAE,IAAI,gBAAiB,CAAC,CAC7E,OAASS,EAAP,CACAH,EAAI,yCAA0CG,CAAG,EACjD,MACF,CACAR,GAAW,EACXK,EAAI,sBAAuBN,EAAO,IAAI,CACxC,CACF,CC5HA,SAASe,IAAoB,CAC3B,GAAI,CAACC,EAAI,QAAQ,SAAS,KAAK,EAAG,CAChC,IAAMC,EAAY,CAChB,WAAY,MACZ,YAAgB,aAAW,EAC3B,WAAaC,GAAU,OAAK,IAAS,MAAIA,EAAG,OAAO,EAAM,MAAO,MAAIA,EAAG,OAAO,EAAGA,EAAG,OAAO,CAAC,EAAGA,EAAG,OAAO,CAAC,CAAC,CAAC,CAC9G,EACG,iBAAeD,CAAS,EAC3BD,EAAI,QAAQ,KAAK,KAAK,CACxB,CACA,GAAI,CAACA,EAAI,QAAQ,SAAS,UAAU,EAAG,CACrC,IAAMC,EAAY,CAChB,WAAY,WACZ,YAAgB,aAAW,EAC3B,WAAaC,GAAU,OAAK,IAAS,WAASA,EAAG,OAAO,EAAIA,EAAG,OAAO,CAAC,EAAIA,EAAG,OAAO,EAAO,MAAIA,EAAG,OAAO,EAAGA,EAAG,OAAO,CAAC,CAAC,CAC3H,EACG,iBAAeD,CAAS,EAC3BD,EAAI,QAAQ,KAAK,UAAU,CAC7B,CACF,CAEA,eAAsBG,GAAMC,EAAiBC,EAAQ,GAAO,CAE1D,GADAD,EAAS,MAAQ,UACbC,GAASL,EAAI,SAAYI,EAAS,OAAO,SAAYA,EAAS,OAAO,QAAQ,OAAS,GAAU,aAAW,IAAMA,EAAS,OAAO,QAAW,CAC9I,IAAME,EAAYC,EAAI,EAEtB,GAAIH,EAAS,OAAO,SAAWA,EAAS,OAAO,QAAQ,OAAS,EAAG,CAkBjE,GAfI,OAAO,QAAW,aAAe,OAAO,mBAAsB,aAAeA,EAAS,OAAO,OAC3FA,EAAS,OAAO,OAAOI,EAAI,2BAA2B,EAIxDR,EAAI,SAAWI,EAAS,OAAO,UAAY,eACzCA,EAAS,OAAO,OAAOI,EAAI,8DAA8D,EAC7FJ,EAAS,OAAO,QAAU,WAExBJ,EAAI,OAASI,EAAS,OAAO,UAAY,SAAWA,EAAS,OAAO,UAAY,aAC9EA,EAAS,OAAO,OAAOI,EAAI,4BAA4BJ,EAAS,OAAO,iCAAiC,EAC5GA,EAAS,OAAO,QAAU,cAIxBJ,EAAI,SAAWI,EAAS,OAAO,UAAY,SAC7C,GAAI,OAAO,WAAc,aAAe,OAAO,UAAU,KAAW,YAClEI,EAAI,qEAAqE,EACzEJ,EAAS,OAAO,QAAU,cACrB,CACL,IAAMK,EAAU,MAAM,UAAU,IAAO,eAAe,EAEtD,GADIL,EAAS,OAAO,OAAOI,EAAI,6BAA8BC,CAAO,EAChE,CAACA,EACHD,EAAI,sEAAsE,EAC1EJ,EAAS,OAAO,QAAU,cACrB,CAGL,IAAMM,EAAc,uBAAwBD,EAAU,MAAOA,EAAuB,mBAAmB,EAAI,OAE3GD,EAAI,uBAAwBE,CAAW,CACzC,CACF,CAIEN,EAAS,OAAO,UAAY,WAAW,MAAcO,GAASP,CAAQ,EAC1E,IAAMQ,EAAY,OAAO,KAAQ,SAAO,EAAE,eAAe,EAYzD,GAXIR,EAAS,OAAO,OAAOI,EAAI,sBAAuBI,CAAS,EAE1DA,EAAU,SAASR,EAAS,OAAO,OAAO,IAC7CI,EAAI,kBAAkBJ,EAAS,OAAO,+BAA+B,EACrEA,EAAS,OAAO,QAAUJ,EAAI,KAAO,aAAe,QAChDI,EAAS,OAAO,OAAOI,EAAI,6BAA6BJ,EAAS,OAAO,SAAS,GAGnFA,EAAS,OAAO,OAAOI,EAAI,mBAAoBJ,EAAS,OAAO,OAAO,EAGtEA,EAAS,OAAO,UAAY,OAAQ,CAGtC,GAFO,MAAI,EAAE,aAAa,+BAAqC,MAAI,EAAE,IAAI,gCAAiC,EAAI,EAC1GA,EAAS,OAAO,OAAOI,EAAI,aAAcJ,EAAS,OAAO,QAAQ,EACjE,OAAOS,GAAA,YAAAA,EAAI,eAAiB,YAAa,MAAS,eAAaT,EAAS,OAAO,SAAUA,EAAS,OAAO,iBAAiB,MACzH,OAAM,IAAI,MAAM,wEAAwE,EAC7F,IAAMU,EAAO,MAAS,MAAI,EAAE,SAAS,uBAAuB,EACtDC,EAAK,MAAS,MAAI,EAAE,SAAS,8BAA8B,EAC7DX,EAAS,OAAO,OAAOI,EAAI,mBAAmBM,EAAO,OAAS,aAAaC,EAAK,gBAAkB,kBAAkB,EACpHX,EAAS,OAAO,OAAS,CAACU,GAAMN,EAAI,2CAA2C,CACrF,CAEA,GAAI,CACF,MAAS,aAAWJ,EAAS,OAAO,OAAO,EAC3C,MAAS,QAAM,EACLY,GAAK,CACjB,OAASC,EAAP,CACA,OAAAT,EAAI,6BAA8BJ,EAAS,OAAO,QAASa,CAAG,EACvD,EACT,CACF,CAGA,GAAO,aAAW,IAAM,YACf,MAAI,EAAE,aAAa,8BAAoC,MAAI,EAAE,IAAI,+BAAgC,EAAK,EACtG,MAAI,EAAE,aAAa,mBAAyB,MAAI,EAAE,IAAI,oBAAqB,EAAI,EAC/E,MAAI,EAAE,aAAa,2BAAiC,MAAI,EAAE,IAAI,4BAA6B,EAAI,EAC/F,MAAI,EAAE,aAAa,4BAAkC,MAAI,EAAE,IAAI,6BAA8B,GAAG,EAChG,MAAI,EAAE,aAAa,gBAAsB,MAAI,EAAE,IAAI,iBAAkB,EAAI,EACzE,MAAI,EAAE,aAAa,mBAAyB,MAAI,EAAE,IAAI,oBAAqB,EAAI,EAGlF,OAAOb,EAAS,OAAO,YAAkB,aAAeA,EAAS,OAAO,aAC1EI,EAAI,kDAAmD,EAAI,EACxD,MAAI,EAAE,IAAI,iCAAkC,CAAC,GAE3C,UAAQ,EAAE,iBAAiB,CAChC,IAAMU,EAAK,MAAS,UAAQ,EAAE,gBAAgB,EAAE,GAC5Cd,EAAS,OAAO,OAAOI,EAAI,cAAcU,EAAG,aAAaA,EAAG,OAAO,cAAcA,EAAG,aAAaA,EAAG,QAAQ,GAAG,CACrH,CAIK,aAAW,EAOf,iBAAe,EAClB,MAAS,QAAM,EAEfd,EAAS,YAAY,YAAc,KAAK,MAAMG,EAAI,EAAID,CAAS,EAC/DF,EAAS,OAAO,QAAa,aAAW,EAExC,MAAMJ,EAAI,cAAc,EACxBD,GAAkB,CAEpB,CACA,MAAO,EACT,CAGO,SAASoB,GAAQC,EAA4BC,EAAQ,CAE1D,QAAWC,KAAcF,EAAa,CACpC,IAAMG,EAAe,CACnB,WAAAD,EACA,YAAaD,EAAO,QACpB,WAAY,IAAM,CAAMA,EAAO,OAAOb,EAAI,aAAcc,EAAYD,EAAO,OAAO,CAAG,CAGvF,EACG,iBAAeE,CAAY,CAChC,CACAvB,EAAI,QAAa,uBAAwB,aAAW,CAAC,EAAE,IAAKwB,GAAWA,EAAO,WAAW,YAAY,CAAC,CACxG,CCnKA,IAAAC,GAAA,GAAAC,GAAAD,GAAA,SAAAE,GAAA,SAAAC,GAAA,WAAAC,GAAA,SAAAC,GAAA,YAAAC,GAAA,SAAAC,GAAA,WAAAC,GAAA,YAAAC,GAAA,WAAAC,KCKO,IAAMC,GAAoBC,GAAqB,CACpD,GAAI,CAACA,EAAOC,EAAI,4BAA4B,UACnC,CAACD,EAAM,WAAYC,EAAI,wCAAwC,MACnE,CACH,IAAMC,EAAMF,EAAM,WAAW,IAAI,EACjC,GAAI,CAACE,EAAKD,EAAI,uCAAuC,MAChD,QAAOC,CACd,CACA,OAAO,IACT,EAEaC,GAAWC,GAAkB,KAAK,MAAOA,EAAQ,IAAO,KAAK,EAAE,EAE/DC,GAAa,CAACC,EAAuBC,IAA6B,CAC7E,GAAI,CAACA,EAAI,UAAY,OAAOD,GAAM,YAAa,OAAOC,EAAI,MAC1D,IAAMC,EAAM,kBAAkB,KAAK,CAAC,IAAO,EAAIF,EAAI,IAAO,EAAIA,EAAI,GAAG,CAAC,EAEtE,MADc,QAAQE,EAAI,OAAOA,EAAI,OAAOA,EAAI,OAAOD,EAAI,QAE7D,EAEO,SAASE,GAAMP,EAAmEQ,EAAWC,EAAWL,EAAuBM,EAA2B,CAC/JV,EAAI,UAAYG,GAAWC,EAAGM,CAAY,EAC1CV,EAAI,UAAU,EACdA,EAAI,IAAIQ,EAAGC,EAAGC,EAAa,UAAW,EAAG,EAAI,KAAK,EAAE,EACpDV,EAAI,KAAK,CACX,CAEO,SAASW,GAAKX,EAAmEQ,EAAWC,EAAWG,EAAeC,EAAgBH,EAA2B,CAGtK,GAFAV,EAAI,UAAU,EACdA,EAAI,UAAYU,EAAa,UACzBA,EAAa,UAAW,CAC1B,IAAMI,GAAMN,EAAIA,EAAII,GAAS,EACvBG,GAAMN,EAAIA,EAAII,GAAU,EAC9Bb,EAAI,QAAQc,EAAIC,EAAIH,EAAQ,EAAGC,EAAS,EAAG,EAAG,EAAG,EAAI,KAAK,EAAE,CAC9D,MACEb,EAAI,OAAOQ,EAAIE,EAAa,UAAWD,CAAC,EACxCT,EAAI,OAAOQ,EAAII,EAAQF,EAAa,UAAWD,CAAC,EAChDT,EAAI,iBAAiBQ,EAAII,EAAOH,EAAGD,EAAII,EAAOH,EAAIC,EAAa,SAAS,EACxEV,EAAI,OAAOQ,EAAII,EAAOH,EAAII,EAASH,EAAa,SAAS,EACzDV,EAAI,iBAAiBQ,EAAII,EAAOH,EAAII,EAAQL,EAAII,EAAQF,EAAa,UAAWD,EAAII,CAAM,EAC1Fb,EAAI,OAAOQ,EAAIE,EAAa,UAAWD,EAAII,CAAM,EACjDb,EAAI,iBAAiBQ,EAAGC,EAAII,EAAQL,EAAGC,EAAII,EAASH,EAAa,SAAS,EAC1EV,EAAI,OAAOQ,EAAGC,EAAIC,EAAa,SAAS,EACxCV,EAAI,iBAAiBQ,EAAGC,EAAGD,EAAIE,EAAa,UAAWD,CAAC,EACxDT,EAAI,UAAU,EAEhBA,EAAI,OAAO,CACb,CAEO,SAASgB,GAAMhB,EAAmEiB,EAAiBP,EAA2B,CACnI,GAAI,EAAAO,EAAO,OAAS,GACpB,CAAAjB,EAAI,UAAU,EACdA,EAAI,OAAOiB,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,EACrC,QAAWC,KAAMD,EACfjB,EAAI,YAAcG,GAAWe,EAAG,IAAM,EAAGR,CAAY,EACrDV,EAAI,OAAO,KAAK,MAAMkB,EAAG,EAAE,EAAG,KAAK,MAAMA,EAAG,EAAE,CAAC,EAEjDlB,EAAI,OAAO,EACPU,EAAa,eACfV,EAAI,UAAU,EACdA,EAAI,KAAK,GAEb,CAEO,SAASmB,GAAOnB,EAAmEiB,EAAiBP,EAA2B,CACpI,GAAI,EAAAO,EAAO,OAAS,GAEpB,IADAjB,EAAI,UAAYU,EAAa,UACzB,CAACA,EAAa,WAAaO,EAAO,QAAU,EAAG,CACjDD,GAAMhB,EAAKiB,EAAQP,CAAY,EAC/B,MACF,CACAV,EAAI,OAAOiB,EAAO,GAAG,GAAIA,EAAO,GAAG,EAAE,EACrC,QAASG,EAAI,EAAGA,EAAIH,EAAO,OAAS,EAAGG,IAAK,CAC1C,IAAMC,GAAMJ,EAAOG,GAAG,GAAKH,EAAOG,EAAI,GAAG,IAAM,EACzCE,GAAML,EAAOG,GAAG,GAAKH,EAAOG,EAAI,GAAG,IAAM,EAC/CpB,EAAI,iBAAiBiB,EAAOG,GAAG,GAAIH,EAAOG,GAAG,GAAIC,EAAIC,CAAE,CACzD,CACAtB,EAAI,iBAAiBiB,EAAOA,EAAO,OAAS,GAAG,GAAIA,EAAOA,EAAO,OAAS,GAAG,GAAIA,EAAOA,EAAO,OAAS,GAAG,GAAIA,EAAOA,EAAO,OAAS,GAAG,EAAE,EAC3IjB,EAAI,OAAO,EACPU,EAAa,eACfV,EAAI,UAAU,EACdA,EAAI,KAAK,GAEb,CAEO,SAASuB,GAAMvB,EAAmEwB,EAAaC,EAAWC,EAAS,EAAG,CAC3H,IAAIC,EACAnB,EACAC,EACJT,EAAI,UAAU,EACdA,EAAI,OAAOwB,EAAK,GAAIA,EAAK,EAAE,EAC3BxB,EAAI,OAAOyB,EAAG,GAAIA,EAAG,EAAE,EACvBE,EAAQ,KAAK,MAAMF,EAAG,GAAKD,EAAK,GAAIC,EAAG,GAAKD,EAAK,EAAE,EACnDhB,EAAIkB,EAAS,KAAK,IAAIC,CAAK,EAAIF,EAAG,GAClChB,EAAIiB,EAAS,KAAK,IAAIC,CAAK,EAAIF,EAAG,GAClCzB,EAAI,OAAOQ,EAAGC,CAAC,EACfkB,GAAU,EAAM,GAAQ,EAAI,KAAK,IACjCnB,EAAIkB,EAAS,KAAK,IAAIC,CAAK,EAAIF,EAAG,GAClChB,EAAIiB,EAAS,KAAK,IAAIC,CAAK,EAAIF,EAAG,GAClCzB,EAAI,OAAOQ,EAAGC,CAAC,EACfkB,GAAU,EAAM,GAAQ,EAAI,KAAK,IACjCnB,EAAIkB,EAAS,KAAK,IAAIC,CAAK,EAAIF,EAAG,GAClChB,EAAIiB,EAAS,KAAK,IAAIC,CAAK,EAAIF,EAAG,GAClCzB,EAAI,OAAOQ,EAAGC,CAAC,EACfT,EAAI,UAAU,EACdA,EAAI,OAAO,EACXA,EAAI,KAAK,CACX,CCnEO,IAAM4B,GAAuB,CAClC,MAAe,2BACf,WAAoB,yBACpB,YAAqB,QACrB,MAAO,GACP,KAAc,6BACd,WAAoB,GACpB,UAAmB,EACnB,UAAmB,EACnB,UAAmB,EACnB,WAAqB,GACrB,WAAqB,GACrB,UAAoB,GACpB,cAAwB,GACxB,aAAuB,GACvB,aAAuB,GACvB,SAAmB,GACnB,aAAuB,GACvB,SAAmB,GACnB,UAAoB,EACtB,ECzDA,IAAIC,EAEJ,SAASC,GAAWC,EAAeC,EAAmE,CACpG,GAAIH,EAAI,WAAY,CAElB,IAAMI,EAAkB,CAAC,EAOzB,GANAA,EAAO,KAAK,SAAS,KAAK,MAAM,IAAMF,EAAE,KAAK,IAAI,EAC7CA,EAAE,aAAaE,EAAO,KAAK,GAAGF,EAAE,QAAU,MAAM,KAAK,MAAM,IAAMA,EAAE,WAAW,IAAI,EAClFA,EAAE,KAAKE,EAAO,KAAK,QAAQF,EAAE,KAAO,IAAI,EACxCA,EAAE,MAAME,EAAO,KAAK,aAAaF,EAAE,MAAM,EACzCA,EAAE,MAAME,EAAO,KAAK,SAAS,KAAK,MAAM,IAAMF,EAAE,IAAI,IAAI,EACxDA,EAAE,MAAME,EAAO,KAAK,SAAS,KAAK,MAAM,IAAMF,EAAE,IAAI,IAAI,EACxDA,EAAE,SAAWA,EAAE,QAAQ,OAAS,EAAG,CACrC,IAAMG,EAAUH,EAAE,QAAQ,IAAKI,GAAM,GAAG,KAAK,MAAM,IAAMA,EAAE,KAAK,MAAMA,EAAE,SAAS,EAC7ED,EAAQ,OAAS,IAAGA,EAAQ,OAAS,GACzCD,EAAO,KAAKC,EAAQ,KAAK,GAAG,CAAC,CAC/B,CACIH,EAAE,UAAYA,EAAE,SAAS,OAASA,EAAE,SAAS,OAC3CA,EAAE,SAAS,MAAM,MAAME,EAAO,KAAK,SAASG,GAAQL,EAAE,SAAS,MAAM,IAAI,aAAUK,GAAQL,EAAE,SAAS,MAAM,GAAG,eAAYK,GAAQL,EAAE,SAAS,MAAM,KAAK,OAAI,EAC7JA,EAAE,SAAS,KAAK,SAASE,EAAO,KAAK,SAASG,GAAQL,EAAE,SAAS,KAAK,OAAO,OAAI,GAEnFE,EAAO,SAAW,GAAGA,EAAO,KAAK,MAAM,EAC3CD,EAAI,UAAYH,EAAI,MACpB,QAASQ,EAAIJ,EAAO,OAAS,EAAGI,GAAK,EAAGA,IAAK,CAC3C,IAAMC,EAAI,KAAK,IAAIP,EAAE,IAAI,GAAI,CAAC,EACxBQ,EAAIF,EAAIR,EAAI,WAAaE,EAAE,IAAI,GACjCF,EAAI,aAAeA,EAAI,cAAgB,KACzCG,EAAI,UAAYH,EAAI,YACpBG,EAAI,SAASC,EAAOI,GAAIC,EAAI,EAAGC,EAAI,EAAE,GAEvCP,EAAI,UAAYH,EAAI,WACpBG,EAAI,SAASC,EAAOI,GAAIC,EAAI,EAAGC,EAAI,EAAE,CACvC,CACF,CACF,CAEA,SAASC,GAAeT,EAAeC,EAAmE,CAExG,GAAID,EAAE,aAAeA,EAAE,YAAY,aAAkBA,EAAE,YAAY,YAAe,GAAI,CACpFC,EAAI,YAAcH,EAAI,SAAW,2BAA6BA,EAAI,MAClEG,EAAI,UAAU,EACd,IAAMS,EAAQ,KAAK,IAAIV,EAAE,YAAY,YAAe,GAAG,GAAKA,EAAE,YAAY,YAAe,GAAG,EAAE,EAAI,EAC5FW,EAAQ,KAAK,IAAIX,EAAE,YAAY,YAAe,GAAG,GAAKA,EAAE,YAAY,YAAe,GAAG,EAAE,EAAI,EAClGC,EAAI,QAAQD,EAAE,YAAY,YAAe,GAAG,GAAIA,EAAE,YAAY,YAAe,GAAG,GAAIU,EAAOC,EAAO,EAAG,EAAG,EAAI,KAAK,EAAE,EACnHV,EAAI,OAAO,EACPH,EAAI,eACNG,EAAI,UAAYH,EAAI,SAAW,2BAA6BA,EAAI,MAChEG,EAAI,KAAK,EAEb,CACA,GAAID,EAAE,aAAeA,EAAE,YAAY,cAAmBA,EAAE,YAAY,aAAgB,GAAI,CACtFC,EAAI,YAAcH,EAAI,SAAW,2BAA6BA,EAAI,MAClEG,EAAI,UAAU,EACd,IAAMS,EAAQ,KAAK,IAAIV,EAAE,YAAY,aAAgB,GAAG,GAAKA,EAAE,YAAY,aAAgB,GAAG,EAAE,EAAI,EAC9FW,EAAQ,KAAK,IAAIX,EAAE,YAAY,aAAgB,GAAG,GAAKA,EAAE,YAAY,aAAgB,GAAG,EAAE,EAAI,EACpGC,EAAI,QAAQD,EAAE,YAAY,aAAgB,GAAG,GAAIA,EAAE,YAAY,aAAgB,GAAG,GAAIU,EAAOC,EAAO,EAAG,EAAG,EAAI,KAAK,EAAE,EACrHV,EAAI,OAAO,EACPH,EAAI,eACNG,EAAI,UAAYH,EAAI,SAAW,2BAA6BA,EAAI,MAChEG,EAAI,KAAK,EAEb,CACF,CAEA,SAASW,GAAgBZ,EAAeC,EAAmE,CAxE3G,IAAAY,EAyEE,GAAIf,EAAI,YAAYe,EAAAb,EAAE,WAAF,YAAAa,EAAY,QAAS,OAAO,QAAW,YAAa,CACtEZ,EAAI,YAAc,OAClB,IAAMa,EAAQd,EAAE,IAAI,GAAKA,EAAE,IAAI,GAAK,EAAMA,EAAE,IAAI,GAAKK,GAAQL,EAAE,SAAS,MAAM,GAAG,EAAI,GAC/Ee,EAAQf,EAAE,IAAI,GAAKA,EAAE,IAAI,GAAK,EAAMA,EAAE,IAAI,GAAKK,GAAQL,EAAE,SAAS,MAAM,KAAK,EAAI,GACjFgB,EAAQ,IAAI,OAAO;AAAA,UACnBhB,EAAE,IAAI,GAAKA,EAAE,IAAI,GAAK,KAAKA,EAAE,IAAI;AAAA;AAAA,UAEjCc,KAAQd,EAAE,IAAI;AAAA,UACdc,KAAQd,EAAE,IAAI,GAAKA,EAAE,IAAI;AAAA,UACzBA,EAAE,IAAI,GAAKA,EAAE,IAAI,GAAK,KAAKA,EAAE,IAAI,GAAKA,EAAE,IAAI;AAAA,KACjD,EACKiB,EAAQ,IAAI,OAAO;AAAA,UACnBjB,EAAE,IAAI,MAAMA,EAAE,IAAI,GAAKA,EAAE,IAAI,GAAK;AAAA;AAAA,UAElCA,EAAE,IAAI,MAAMe;AAAA,UACZf,EAAE,IAAI,GAAKA,EAAE,IAAI,MAAMe;AAAA,UACvBf,EAAE,IAAI,GAAKA,EAAE,IAAI,MAAMA,EAAE,IAAI,GAAKA,EAAE,IAAI,GAAK;AAAA,KAClD,EACDC,EAAI,OAAOgB,CAAK,EAChBhB,EAAI,OAAOe,CAAK,CAClB,CACF,CAEA,SAASE,GAAelB,EAAeC,EAAmE,CAhG1G,IAAAY,EAAAM,EAAAC,EAAAC,EAiGE,GAAIvB,EAAI,YAAYqB,GAAAN,EAAAb,EAAE,WAAF,YAAAa,EAAY,OAAZ,YAAAM,EAAkB,aAAYE,GAAAD,EAAApB,EAAE,WAAF,YAAAoB,EAAY,OAAZ,YAAAC,EAAkB,UAAWrB,EAAE,YAAY,aAAkBA,EAAE,YAAY,cAAmBA,EAAE,YAAY,YAAe,IAAMA,EAAE,YAAY,aAAgB,GAAI,CACnNC,EAAI,YAAc,OAClBA,EAAI,UAAY,OAChB,IAAMqB,EAAW,CACftB,EAAE,YAAY,YAAe,GAAG,GAAM,KAAK,IAAIA,EAAE,SAAS,KAAK,OAAO,EAAIA,EAAE,SAAS,KAAK,SAAWA,EAAE,IAAI,GAC3GA,EAAE,YAAY,YAAe,GAAG,GAAM,KAAK,IAAIA,EAAE,SAAS,KAAK,OAAO,EAAIA,EAAE,SAAS,KAAK,SAAWA,EAAE,IAAI,EAC7G,EACAuB,GAAMtB,EAAK,CAACD,EAAE,YAAY,YAAe,GAAG,GAAIA,EAAE,YAAY,YAAe,GAAG,EAAE,EAAG,CAACsB,EAAS,GAAIA,EAAS,EAAE,EAAG,CAAC,EAClH,IAAME,EAAY,CAChBxB,EAAE,YAAY,aAAgB,GAAG,GAAM,KAAK,IAAIA,EAAE,SAAS,KAAK,OAAO,EAAIA,EAAE,SAAS,KAAK,SAAWA,EAAE,IAAI,GAC5GA,EAAE,YAAY,aAAgB,GAAG,GAAM,KAAK,IAAIA,EAAE,SAAS,KAAK,OAAO,EAAIA,EAAE,SAAS,KAAK,SAAWA,EAAE,IAAI,EAC9G,EACAuB,GAAMtB,EAAK,CAACD,EAAE,YAAY,aAAgB,GAAG,GAAIA,EAAE,YAAY,aAAgB,GAAG,EAAE,EAAG,CAACwB,EAAU,GAAIA,EAAU,EAAE,EAAG,CAAC,CACxH,CACF,CAEA,SAASC,GAAiBzB,EAAeC,EAAmE,CAC1G,GAAIH,EAAI,cAAgBE,EAAE,KAAK,QAAU,IAAK,CAC5CC,EAAI,UAAY,EAChB,QAASK,EAAI,EAAGA,EAAIoB,GAAc,OAAS,EAAGpB,IAAK,CACjD,IAAMqB,EAAS,CAACD,GAAcpB,EAAI,EAAI,GAAIoB,GAAcpB,EAAI,EAAI,GAAIoB,GAAcpB,EAAI,EAAI,EAAE,EAAE,IAAKsB,GAAU5B,EAAE,KAAK4B,EAAM,EAC1HC,GAAM5B,EAAK0B,EAAQ7B,CAAG,CACxB,CACAW,GAAeT,EAAGC,CAAG,CACvB,CAQF,CAEA,SAAS6B,GAAe9B,EAAeC,EAAmE,CACxG,GAAIH,EAAI,YAAcE,EAAE,KAAK,QAAU,IACrC,QAASM,EAAI,EAAGA,EAAIN,EAAE,KAAK,OAAQM,IACjCyB,GAAM9B,EAAKD,EAAE,KAAKM,GAAG,GAAIN,EAAE,KAAKM,GAAG,GAAIN,EAAE,KAAKM,GAAG,GAAIR,CAAG,EACpDA,EAAI,gBACgBkC,GAAiC,SAAS1B,CAAC,GAAGyB,GAAM9B,EAAKD,EAAE,KAAKM,GAAG,GAAIN,EAAE,KAAKM,GAAG,GAAKN,EAAE,KAAKM,GAAG,GAAgB,IAAKR,CAAG,EACxHmC,GAAqC,SAAS3B,CAAC,GAAGyB,GAAM9B,EAAKD,EAAE,KAAKM,GAAG,GAAIN,EAAE,KAAKM,GAAG,GAAKN,EAAE,KAAKM,GAAG,GAAgB,IAAKR,CAAG,EAC5HoC,GAAsC,SAAS5B,CAAC,GAAGyB,GAAM9B,EAAKD,EAAE,KAAKM,GAAG,GAAIN,EAAE,KAAKM,GAAG,GAAKN,EAAE,KAAKM,GAAG,GAAgB,IAAKR,CAAG,EAI3J,CAEA,SAASqC,GAAcnC,EAAeC,EAAK,CACrCH,EAAI,WACNsC,GAAKnC,EAAKD,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIF,CAAG,CAEzD,CAGA,eAAsBuC,GAAKC,EAAqBC,EAA2BC,EAAoC,CAE7G,GADA1C,EAAM2C,EAAUC,GAASF,CAAW,EAChC,CAACD,GAAU,CAACD,EAAU,OAC1B,IAAMrC,EAAM0C,GAAiBL,CAAQ,EACrC,GAAI,EAACrC,EACL,CAAAA,EAAI,KAAOH,EAAI,KACfG,EAAI,YAAcH,EAAI,MACtBG,EAAI,UAAYH,EAAI,MACpB,QAAWE,KAAKuC,EACdJ,GAAcnC,EAAGC,CAAG,EACpBF,GAAWC,EAAGC,CAAG,EACbD,EAAE,MAAQA,EAAE,KAAK,OAAS,IAC5B8B,GAAe9B,EAAGC,CAAG,EACrBwB,GAAiBzB,EAAGC,CAAG,EACvBW,GAAgBZ,EAAGC,CAAG,EACtBiB,GAAelB,EAAGC,CAAG,GAG3B,CClKA,eAAsB2C,GAAKC,EAAqBC,EAA2BC,EAAoC,CAP/G,IAAAC,EAQE,IAAMC,EAAeC,EAAUC,GAASJ,CAAW,EACnD,GAAI,CAACD,GAAU,CAACD,EAAU,OAC1B,IAAMO,EAAMC,GAAiBR,CAAQ,EACrC,GAAI,EAACO,EACL,CAAAA,EAAI,SAAW,QACf,QAASE,EAAI,EAAGA,EAAIR,EAAO,OAAQQ,IAAK,CAgBtC,GAfAF,EAAI,YAAcH,EAAa,MAC/BG,EAAI,UAAYH,EAAa,MAC7BG,EAAI,UAAYH,EAAa,UAC7BG,EAAI,KAAOH,EAAa,KACpBA,EAAa,WAAaH,EAAOQ,GAAG,OAAON,EAAAF,EAAOQ,GAAG,MAAV,YAAAN,EAAe,UAAW,IACvEO,GAAKH,EAAKN,EAAOQ,GAAG,IAAI,GAAIR,EAAOQ,GAAG,IAAI,GAAIR,EAAOQ,GAAG,IAAI,GAAIR,EAAOQ,GAAG,IAAI,GAAIL,CAAY,EAC1FA,EAAa,aACXA,EAAa,aAAeA,EAAa,cAAgB,KAC3DG,EAAI,UAAYH,EAAa,YAC7BG,EAAI,SAAS,QAAQ,IAAMN,EAAOQ,GAAG,SAAUR,EAAOQ,GAAG,IAAI,GAAK,EAAG,EAAIR,EAAOQ,GAAG,IAAI,GAAKL,EAAa,WAAYH,EAAOQ,GAAG,IAAI,EAAE,GAEvIF,EAAI,UAAYH,EAAa,WAC7BG,EAAI,SAAS,QAAQ,IAAMN,EAAOQ,GAAG,SAAUR,EAAOQ,GAAG,IAAI,GAAK,EAAG,EAAIR,EAAOQ,GAAG,IAAI,GAAKL,EAAa,WAAYH,EAAOQ,GAAG,IAAI,EAAE,IAGrIL,EAAa,YAAcH,EAAOQ,GAAG,UACvC,QAASE,EAAK,EAAGA,EAAKV,EAAOQ,GAAG,UAAU,OAAQE,IAC5C,CAACV,EAAOQ,GAAG,UAAUE,GAAI,OAAUV,EAAOQ,GAAG,UAAUE,GAAI,QAAU,IACzEJ,EAAI,UAAYK,GAAWX,EAAOQ,GAAG,UAAUE,GAAI,SAAS,GAAIP,CAAY,EAC5ES,GAAMN,EAAKN,EAAOQ,GAAG,UAAUE,GAAI,SAAS,GAAIV,EAAOQ,GAAG,UAAUE,GAAI,SAAS,GAAI,EAAGP,CAAY,GAGxG,GAAIA,EAAa,YAAcH,EAAOQ,GAAG,UAAW,CAClDF,EAAI,KAAOH,EAAa,KACxB,QAAWO,KAAMV,EAAOQ,GAAG,UACrB,CAACE,EAAG,OAAUA,EAAG,QAAU,IAC/BJ,EAAI,UAAYK,GAAWD,EAAG,SAAS,GAAIP,CAAY,EACvDG,EAAI,SAAS,GAAGI,EAAG,QAAQ,KAAK,MAAM,IAAMA,EAAG,KAAK,KAAMA,EAAG,SAAS,GAAK,EAAGA,EAAG,SAAS,GAAK,CAAC,EAEpG,CACA,GAAIP,EAAa,cAAgBH,EAAOQ,GAAG,WAAaR,EAAOQ,GAAG,YAChE,QAAWK,KAAQ,OAAO,OAAOb,EAAOQ,GAAG,WAAW,EACpD,QAAWM,KAAaD,EAAME,GAAOT,EAAKQ,EAAWX,CAAY,CAGvE,EACF,CC3CA,eAAsBa,GAAKC,EAAqBC,EAA2BC,EAAoC,CAC7G,IAAMC,EAAeC,EAAUC,GAASH,CAAW,EACnD,GAAI,CAACD,GAAU,CAACD,EAAU,OAC1B,IAAMM,EAAMC,GAAiBP,CAAQ,EACrC,GAAI,EAACM,EACL,CAAAA,EAAI,SAAW,QACfA,EAAI,KAAOH,EAAa,KACxB,QAAWK,KAAKP,EAAQ,CAetB,GAdIE,EAAa,YACfG,EAAI,YAAcH,EAAa,MAC/BG,EAAI,UAAYH,EAAa,MAC7BM,GAAKH,EAAKE,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIL,CAAY,EAC1DA,EAAa,aACXA,EAAa,aAAeA,EAAa,cAAgB,KAC3DG,EAAI,UAAYH,EAAa,YAC7BG,EAAI,SAAS,QAAQ,KAAK,MAAM,IAAME,EAAE,KAAK,KAAMA,EAAE,IAAI,GAAK,EAAG,EAAIA,EAAE,IAAI,GAAKL,EAAa,WAAYK,EAAE,IAAI,EAAE,GAEnHF,EAAI,UAAYH,EAAa,WAC7BG,EAAI,SAAS,QAAQ,KAAK,MAAM,IAAME,EAAE,KAAK,KAAMA,EAAE,IAAI,GAAK,EAAG,EAAIA,EAAE,IAAI,GAAKL,EAAa,WAAYK,EAAE,IAAI,EAAE,GAEnHF,EAAI,OAAO,GAETH,EAAa,YACXK,EAAE,WAAaA,EAAE,UAAU,OAAS,EACtC,QAAWE,KAAMF,EAAE,UACjBF,EAAI,UAAYK,GAAWD,EAAG,GAAIP,CAAY,EAC9CS,GAAMN,EAAKI,EAAG,GAAIA,EAAG,GAAI,EAAGP,CAAY,EAI9C,GAAIA,EAAa,YAAcK,EAAE,YAAa,CAC5C,IAAMK,EAAe,CAACC,EAAoBC,IAAkB,CAC1D,GAAI,CAACD,GAAQA,EAAK,SAAW,GAAK,CAACA,EAAK,GAAI,OAC5C,IAAME,EAAIF,EAAKA,EAAK,OAAS,GAAG,IAAM,KACtCR,EAAI,UAAYK,GAAWK,EAAGb,CAAY,EAC1CG,EAAI,SAASS,EAAOD,EAAKA,EAAK,OAAS,GAAG,GAAK,EAAGA,EAAKA,EAAK,OAAS,GAAG,GAAK,CAAC,CAChF,EACAR,EAAI,KAAOH,EAAa,KACxBU,EAAaL,EAAE,YAAY,MAAU,OAAO,EAC5CK,EAAaL,EAAE,YAAY,OAAW,QAAQ,EAC9CK,EAAaL,EAAE,YAAY,KAAS,MAAM,EAC1CK,EAAaL,EAAE,YAAY,MAAU,OAAO,EAC5CK,EAAaL,EAAE,YAAY,MAAU,OAAO,EAC5CK,EAAaL,EAAE,YAAY,KAAS,MAAM,CAC5C,CACA,GAAIL,EAAa,cAAgBK,EAAE,YAAa,CAC9C,IAAMS,EAAeH,GAAuB,CAC1C,GAAI,GAACA,GAAQA,EAAK,SAAW,GAAK,CAACA,EAAK,IACxC,QAASI,EAAI,EAAGA,EAAIJ,EAAK,OAAQI,IAAK,CACpCZ,EAAI,UAAU,EACd,IAAMU,EAAIF,EAAKI,GAAG,IAAM,EACxBZ,EAAI,YAAcK,GAAWO,EAAIF,EAAGb,CAAY,EAChDG,EAAI,OAAOQ,EAAKI,EAAI,EAAIA,EAAI,EAAI,GAAG,GAAIJ,EAAKI,EAAI,EAAIA,EAAI,EAAI,GAAG,EAAE,EACjEZ,EAAI,OAAOQ,EAAKI,GAAG,GAAIJ,EAAKI,GAAG,EAAE,EACjCZ,EAAI,OAAO,CACb,CACF,EACAA,EAAI,UAAYH,EAAa,UAC7Bc,EAAYT,EAAE,YAAY,KAAQ,EAClCS,EAAYT,EAAE,YAAY,MAAS,EACnCS,EAAYT,EAAE,YAAY,IAAO,EACjCS,EAAYT,EAAE,YAAY,KAAQ,EAClCS,EAAYT,EAAE,YAAY,KAAQ,CAEpC,CACF,EACF,CClEA,eAAsBW,GAAOC,EAAqBC,EAA6BC,EAAoC,CACjH,IAAMC,EAAeC,EAAUC,GAASH,CAAW,EACnD,GAAI,CAACD,GAAU,CAACD,EAAU,OAC1B,IAAMM,EAAMC,GAAiBP,CAAQ,EACrC,GAAI,EAACM,EACL,CAAAA,EAAI,SAAW,QACfA,EAAI,KAAOH,EAAa,KACxB,QAAWK,KAAKP,EACd,GAAIE,EAAa,UAAW,CAI1B,GAHAG,EAAI,YAAcH,EAAa,MAC/BG,EAAI,UAAYH,EAAa,MAC7BM,GAAKH,EAAKE,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIA,EAAE,IAAI,GAAIL,CAAY,EAC1DA,EAAa,WAAY,CAC3B,IAAMO,EAAQ,GAAGF,EAAE,SAAS,KAAK,MAAM,IAAMA,EAAE,KAAK,KAChDL,EAAa,aAAeA,EAAa,cAAgB,KAC3DG,EAAI,UAAYH,EAAa,YAC7BG,EAAI,SAASI,EAAOF,EAAE,IAAI,GAAK,EAAG,EAAIA,EAAE,IAAI,GAAKL,EAAa,WAAYK,EAAE,IAAI,EAAE,GAEpFF,EAAI,UAAYH,EAAa,WAC7BG,EAAI,SAASI,EAAOF,EAAE,IAAI,GAAK,EAAG,EAAIA,EAAE,IAAI,GAAKL,EAAa,WAAYK,EAAE,IAAI,EAAE,CACpF,CACAF,EAAI,OAAO,CACb,EAEJ,CCxBA,eAAsBK,GAAQC,EAAqBC,EAA8BC,EAAoC,CACnH,IAAMC,EAAeC,EAAUC,GAASH,CAAW,EACnD,GAAI,GAACD,GAAU,CAACD,IACZG,EAAa,aAAc,CAC7B,IAAMG,EAAMC,GAAiBP,CAAQ,EACrC,GAAI,CAACM,EAAK,OACVA,EAAI,KAAOH,EAAa,KACxBG,EAAI,UAAYH,EAAa,MAC7B,IAAIK,EAAI,EACR,QAASC,EAAI,EAAGA,EAAIR,EAAO,OAAQQ,IAAK,CACtC,IAAIC,EAAmB,CAAC,EACpBC,EAAkB,CAAC,EAEvB,GADA,CAACD,EAAOC,CAAI,EAAI,OAAO,QAAQV,EAAOQ,EAAE,EACnCE,EAAK,OAAS,GAAQA,EAAK,GAAc,OAAS,EAAI,CACzD,IAAMC,EAAMF,EAAM,GAAe,EAAI,IAAIA,EAAM,KAAO,GAChDG,EAAQ,GAAGH,EAAM,MAAME,MAAQD,EAAK,KACtCR,EAAa,aAAeA,EAAa,cAAgB,KAC3DG,EAAI,UAAYH,EAAa,YAC7BG,EAAI,SAASO,EAAO,EAAG,EAAKL,EAAIL,EAAa,UAAW,GAE1DG,EAAI,UAAYH,EAAa,WAC7BG,EAAI,SAASO,EAAO,EAAG,EAAKL,EAAIL,EAAa,UAAW,EACxDK,GAAK,CACP,CACF,CACF,CACF,CPjBA,IAAIM,GAAW,EAUf,eAAsBC,GAAOC,EAAqBC,EAA6BC,EAAoC,CACjH,IAAMC,EAAeC,EAAUC,GAASH,CAAW,EACnD,GAAI,CAACD,GAAU,CAACD,EAAU,OAC1B,IAAMM,EAAMC,GAAiBP,CAAQ,EACrC,GAAI,EAACM,EACL,CAAAA,EAAI,SAAW,QACfA,EAAI,KAAOH,EAAa,KAExB,QAASK,EAAI,EAAGA,EAAIP,EAAO,OAAQO,IACjC,GAAIL,EAAa,UAAW,CAI1B,GAHAG,EAAI,YAAcH,EAAa,MAC/BG,EAAI,UAAYH,EAAa,MAC7BM,GAAKH,EAAKL,EAAOO,GAAG,IAAI,GAAIP,EAAOO,GAAG,IAAI,GAAIP,EAAOO,GAAG,IAAI,GAAIP,EAAOO,GAAG,IAAI,GAAIL,CAAY,EAC1FA,EAAa,WAAY,CAC3B,IAAMO,EAAQ,WAAWF,IACrBL,EAAa,aAAeA,EAAa,cAAgB,KAC3DG,EAAI,UAAYH,EAAa,YAC7BG,EAAI,SAASI,EAAOT,EAAOO,GAAG,IAAI,GAAK,EAAG,EAAIP,EAAOO,GAAG,IAAI,GAAKL,EAAa,WAAYF,EAAOO,GAAG,IAAI,EAAE,GAE5GF,EAAI,UAAYH,EAAa,WAC7BG,EAAI,SAASI,EAAOT,EAAOO,GAAG,IAAI,GAAK,EAAG,EAAIP,EAAOO,GAAG,IAAI,GAAKL,EAAa,WAAYF,EAAOO,GAAG,IAAI,EAAE,CAC5G,CACAF,EAAI,OAAO,CACb,EAEJ,CAGA,eAAsBK,GAAOC,EAAwDC,EAAmB,CACtG,GAAI,CAACD,GAAS,CAACC,EAAQ,OACvB,IAAMP,EAAMC,GAAiBM,CAAM,EAC/B,CAACP,GACLA,EAAI,UAAUM,EAAO,EAAG,CAAC,CAC3B,CAGA,eAAsBE,GAAId,EAAqBC,EAAgBC,EAAoC,CACjG,GAAI,CAACD,GAAU,CAACA,EAAO,aAAe,CAACA,GAAU,CAACD,EAAU,OAAO,KACnE,IAAMe,EAAYC,EAAI,EAChBb,EAAeC,EAAUC,GAASH,CAAW,EAC7Ce,EAAU,QAAQ,IAAI,CAC1BC,GAAKlB,EAAUC,EAAO,KAAME,CAAY,EACxCgB,GAAKnB,EAAUC,EAAO,KAAME,CAAY,EACxCiB,GAAKpB,EAAUC,EAAO,KAAME,CAAY,EACxCkB,GAAOrB,EAAUC,EAAO,OAAQE,CAAY,EAC5CmB,GAAQtB,EAAUC,EAAO,QAASE,CAAY,CAEhD,CAAC,EACD,OAAAL,GAAWyB,EAAI,QAAUzB,GAAW,KAAK,MAAMkB,EAAI,EAAID,CAAS,EAAI,KAAK,MAAMC,EAAI,EAAID,CAAS,EAChGd,EAAO,YAAY,KAAOH,GACnBmB,CACT,CQxEA,IAAMO,GAAa,GACbC,GAAQ,GAGd,SAASC,GAAWC,EAAWC,EAAWC,EAAmD,CAC3F,IAAIC,EAAS,GACTC,EAAIF,EAAQ,OAAS,EACzB,QAASG,EAAI,EAAGA,EAAIH,EAAQ,OAAQE,EAAIC,IAChCH,EAAQG,GAAG,EAAIJ,GAAQC,EAAQE,GAAG,EAAIH,GAAQD,GAAKE,EAAQE,GAAG,EAAIF,EAAQG,GAAG,IAAMJ,EAAIC,EAAQG,GAAG,IAAMH,EAAQE,GAAG,EAAIF,EAAQG,GAAG,GAAKH,EAAQG,GAAG,IAAIF,EAAS,CAACA,GAExK,OAAOA,CACT,CAEA,eAAsBG,GAAKC,EAA+C,CAExE,GADI,CAACA,EAAK,QACN,CAACA,EAAK,MAAQA,EAAK,KAAK,OAAS,IAAK,OAAOA,EAAK,OACtD,IAAMC,EAAQD,EAAK,OAAO,MAAM,IAAM,EAChCE,EAASF,EAAK,OAAO,MAAM,IAAM,EACjCG,EAAS,MAAMH,EAAK,OAAO,OAAO,EACpCI,EAA8C,CAAC,EACnD,QAAWC,KAAMC,GAAgB,WAAYF,EAAW,KAAK,CAAE,GAAIJ,EAAK,KAAKK,GAAI,GAAKL,EAAK,IAAI,IAAMA,EAAK,IAAI,GAAI,GAAIA,EAAK,KAAKK,GAAI,GAAKL,EAAK,IAAI,IAAMA,EAAK,IAAI,EAAG,CAAC,EACjKV,IAAcA,GAAa,IAAGc,EAAaA,EAAW,IAAKC,IAAQ,CAAE,EAAGA,EAAG,EAAI,GAAMA,EAAG,EAAIf,GAAae,EAAG,EAAIf,GAAY,EAAGe,EAAG,EAAI,GAAMA,EAAG,EAAIf,GAAae,EAAG,EAAIf,EAAW,EAAE,GACxL,QAASG,EAAI,EAAGA,EAAIQ,EAAOR,IACzB,QAASC,EAAI,EAAGA,EAAIQ,EAAQR,IACXF,GAAWC,EAAIQ,EAAOP,EAAIO,EAAOG,CAAU,IAExDD,EAAO,IAAIZ,GAAQY,EAAO,IAAI,EAAGT,EAAGD,EAAG,CAAC,EAAG,EAAGC,EAAGD,EAAG,CAAC,EACrDU,EAAO,IAAIZ,GAAQY,EAAO,IAAI,EAAGT,EAAGD,EAAG,CAAC,EAAG,EAAGC,EAAGD,EAAG,CAAC,EACrDU,EAAO,IAAIZ,GAAQY,EAAO,IAAI,EAAGT,EAAGD,EAAG,CAAC,EAAG,EAAGC,EAAGD,EAAG,CAAC,GAI3D,IAAMc,EAASJ,EAAO,SAAS,EAC/B,OAAG,UAAQA,CAAM,EACVI,CACT,CCpCA,IAAMC,GAAiBC,GAA4D,CACjF,IAAMC,EAAU,CAACC,EAAYC,IAAe,KAAK,MAAMD,EAAI,GAAKC,EAAI,GAAID,EAAI,GAAKC,EAAI,EAAE,EACvF,GAAI,CAACH,EAAK,YAAY,cAAmB,CAACA,EAAK,YAAY,YAAgB,MAAO,CAAE,QAAS,EAAG,SAAU,CAAE,EAE5G,IAAMI,EAAa,CAAC,EAAG,GAAI,EACrBC,EAAW,EAEXC,GAAQN,EAAK,KAAK,IAAI,IAAM,IAAMA,EAAK,KAAK,KAAK,IAAM,GACvDO,EAAaD,EAAON,EAAK,KAAK,KAAOA,EAAK,KAAK,KAC/CQ,EAAYF,EACd,EAAEN,EAAK,KAAK,KAAK,GAAKA,EAAK,KAAK,IAAI,IAAM,GAAIA,EAAK,KAAK,KAAK,GAAKA,EAAK,KAAK,IAAI,IAAM,CAAC,EACvF,EAAEA,EAAK,KAAK,KAAK,GAAKA,EAAK,KAAK,KAAK,IAAM,GAAIA,EAAK,KAAK,KAAK,GAAKA,EAAK,KAAK,KAAK,IAAM,CAAC,EACvFS,EAAUH,EACZ,CAACN,EAAK,KAAK,KAAK,GAAKA,EAAK,KAAK,IAAI,GAAIA,EAAK,KAAK,IAAI,GAAKA,EAAK,KAAK,IAAI,EAAE,EAC1E,CAACA,EAAK,KAAK,KAAK,GAAKA,EAAK,KAAK,KAAK,GAAIA,EAAK,KAAK,KAAK,GAAKA,EAAK,KAAK,KAAK,EAAE,EAC3EU,EAAiB,EACpBF,EAAU,GAAKD,EAAW,IAAME,EAAQ,GAAKL,EAAW,GACzDC,GAAYE,EAAW,GAAKC,EAAU,IAAMC,EAAQ,GAAKL,EAAW,EACtE,EACIO,EAAW,KAAK,KAAMD,EAAQ,GAAKA,EAAQ,GAAOA,EAAQ,GAAKA,EAAQ,EAAG,EAC9E,OAAAC,EAAW,KAAK,IAAIA,EAAUX,EAAK,OAAO,GAAK,EAAGA,EAAK,OAAO,GAAK,CAAC,EAE7D,CAAE,SADQC,EAAQ,CAAC,EAAG,CAAC,EAAGS,CAAO,EAAK,KAAK,GAAK,GAAM,KAAK,GAChD,SAAAC,CAAS,CAC7B,EAEaC,GAAqB,CAACZ,EAAkBa,IAIhD,CAEH,IAAMC,EAAaC,GAAsB,CACvC,IAAMC,EAAS,KAAK,KAAKD,EAAE,GAAKA,EAAE,GAAKA,EAAE,GAAKA,EAAE,GAAKA,EAAE,GAAKA,EAAE,EAAE,EAChE,OAAAA,EAAE,IAAMC,EACRD,EAAE,IAAMC,EACRD,EAAE,IAAMC,EACDD,CACT,EACME,EAAa,CAACC,EAAWC,IAAsB,CACnD,IAAMC,EAAIF,EAAE,GAAKC,EAAE,GACbE,EAAIH,EAAE,GAAKC,EAAE,GACbG,EAAIJ,EAAE,GAAKC,EAAE,GACnB,MAAO,CAACC,EAAGC,EAAGC,CAAC,CACjB,EACMC,EAAe,CAACL,EAAWC,IAAsB,CACrD,IAAMC,EAAIF,EAAE,GAAKC,EAAE,GAAKD,EAAE,GAAKC,EAAE,GAC3BE,EAAIH,EAAE,GAAKC,EAAE,GAAKD,EAAE,GAAKC,EAAE,GAC3BG,EAAIJ,EAAE,GAAKC,EAAE,GAAKD,EAAE,GAAKC,EAAE,GACjC,MAAO,CAACC,EAAGC,EAAGC,CAAC,CACjB,EAEME,EAA8BC,GAA8D,CAEhG,GAAM,CAACC,EAAKC,EAAMC,EAAMC,EAAKC,EAAKC,EAAKC,EAAKC,EAAKC,CAAG,EAAIT,EACpDU,EACAC,EACAC,EACJ,OAAIR,EAAM,EACJA,EAAM,IACRQ,EAAS,KAAK,KAAKR,CAAG,EACtBO,EAAS,KAAK,MAAM,CAACJ,EAAKN,CAAG,EAC7BS,EAAS,KAAK,MAAM,CAACJ,EAAKD,CAAG,IAE7BO,EAAS,CAAC,KAAK,GAAK,EACpBD,EAAS,CAAC,KAAK,MAAMH,EAAKC,CAAG,EAC7BC,EAAS,IAGXE,EAAS,KAAK,GAAK,EACnBD,EAAS,KAAK,MAAMH,EAAKC,CAAG,EAC5BC,EAAS,GAEP,MAAMA,CAAM,IAAGA,EAAS,GACxB,MAAMC,CAAM,IAAGA,EAAS,GACxB,MAAMC,CAAM,IAAGA,EAAS,GACrB,CAAE,MAAO,EAAI,CAACF,EAAQ,IAAK,EAAI,CAACC,EAAQ,KAAM,EAAI,CAACC,CAAO,CACnE,EAcMC,EAAOtC,EAAK,QAClB,GAAI,CAACsC,GAAQA,EAAK,OAAS,IAAK,MAAO,CAAE,MAAO,CAAE,MAAO,EAAG,IAAK,EAAG,KAAM,CAAE,EAAG,OAAQ,CAAC,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,CAAC,EAAG,KAAM,CAAE,QAAS,EAAG,SAAU,CAAE,CAAE,EAEtJ,IAAMC,EAAO,KAAK,IAAIvC,EAAK,OAAO,GAAKa,EAAU,GAAIb,EAAK,OAAO,GAAKa,EAAU,EAAE,EAAI,IAEhF2B,EAAe,CAACF,EAAK,IAAKA,EAAK,KAAMA,EAAK,KAAMA,EAAK,IAAI,EAAE,IAAKG,GAAO,CAACA,EAAG,GAAK5B,EAAU,GAAK0B,EAAME,EAAG,GAAK5B,EAAU,GAAK0B,EAAME,EAAG,EAAE,CAAU,EAEjJC,EAAS5B,EAAUG,EAAWuB,EAAI,GAAcA,EAAI,EAAY,CAAC,EACnEG,EAAS7B,EAAUG,EAAWuB,EAAI,GAAcA,EAAI,EAAY,CAAC,EAC/DI,EAAS9B,EAAUS,EAAaoB,EAAQD,CAAM,CAAC,EAErDC,EAASpB,EAAamB,EAAQE,CAAM,EAIpC,IAAMC,EAAmF,CACvFF,EAAO,GAAIA,EAAO,GAAIA,EAAO,GAC7BD,EAAO,GAAIA,EAAO,GAAIA,EAAO,GAC7BE,EAAO,GAAIA,EAAO,GAAIA,EAAO,EAC/B,EACME,EAAQtB,EAA2BqB,CAAM,EAIzCE,EAAOT,EAAK,SAAW,IAAMvC,GAAcC,CAAI,EAAI,CAAE,QAAS,EAAG,SAAU,CAAE,EAEnF,MAAO,CAAE,MAAA8C,EAAO,OAAAD,EAAQ,KAAAE,CAAK,CAC/B,EChGO,IAAMC,GAAa,MAAOC,EAAyCC,IAAyC,CAzBnH,IAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,GAAAC,EAAAC,GAAAC,GAAAC,EAAAC,GA4BE,IAAIC,EAAoBC,EAAI,EACxBC,EACAC,EACAC,EACAC,EACAC,EACAC,EACAC,EACAC,EAEEC,EAA6B,CAAC,EACpClC,EAAS,MAAQ,WAEjB,IAAMmC,EAAQ,MAAeC,GAAQnC,EAAOD,EAAS,MAAM,EAE3D,GADAA,EAAS,YAAY,KAAOqC,EAAI,SAAWrC,EAAS,YAAY,MAAQ,GAAK,KAAK,MAAMyB,EAAI,EAAID,CAAS,EAAI,KAAK,MAAMC,EAAI,EAAID,CAAS,EACrI,CAACvB,EAAM,OAASA,EAAM,MAAM,SAAW,EAAG,MAAO,CAAC,EACtD,GAAI,CAACkC,EAAO,MAAO,CAAC,EAEpB,QAASG,EAAI,EAAGA,EAAIH,EAAM,OAAQG,IAAK,CAKrC,GAJAtC,EAAS,QAAQ,UAAU,EAIvB,CAACmC,EAAMG,GAAG,QAAUH,EAAMG,GAAG,OAAO,mBAAuB,CAC7DC,EAAI,2BAA4BJ,EAAMG,GAAG,MAAM,EAC/C,QACF,CAGA,IAAIpC,EAAAF,EAAS,OAAO,KAAK,WAArB,MAAAE,EAA+B,KAAM,CACvC,IAAMsC,EAAS,MAAWC,GAAKN,EAAMG,EAAE,EACpC,UAAQH,EAAMG,GAAG,MAAM,EAC1BH,EAAMG,GAAG,OAASE,CACpB,CAGA,IAAME,EAAWP,EAAMG,GAAG,MAASH,EAAMG,GAAG,KAAK,OAAS,IAAOK,GAAmBR,EAAMG,GAAI,CAACrC,EAAM,MAAM,GAAIA,EAAM,MAAM,EAAE,CAAC,EAAI,KAGlID,EAAS,QAAQ,gBAAgB,EAC7BA,EAAS,OAAO,MAClB6B,GAAa1B,EAAAH,EAAS,OAAO,KAAK,UAArB,MAAAG,EAA8B,QAAkBiC,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,CAAC,GAE5InC,EAAS,MAAQ,cACjBwB,EAAYC,EAAI,EAChBI,GAAazB,EAAAJ,EAAS,OAAO,KAAK,UAArB,MAAAI,EAA8B,QAAU,MAAcgC,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,CAAC,EAClJnC,EAAS,YAAY,QAAUqC,EAAI,SAAWrC,EAAS,YAAY,SAAW,GAAK,KAAK,MAAMyB,EAAI,EAAID,CAAS,EAAI,KAAK,MAAMC,EAAI,EAAID,CAAS,GAEjJxB,EAAS,QAAQ,cAAc,EAG/BA,EAAS,QAAQ,kBAAkB,EAC/BA,EAAS,OAAO,MAClB+B,GAAe1B,EAAAL,EAAS,OAAO,KAAK,YAArB,MAAAK,EAAgC,QAAoB+B,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,GAEjJnC,EAAS,MAAQ,gBACjBwB,EAAYC,EAAI,EAChBM,GAAezB,EAAAN,EAAS,OAAO,KAAK,YAArB,MAAAM,EAAgC,QAAU,MAAgB8B,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,EACvJnC,EAAS,YAAY,UAAYqC,EAAI,SAAWrC,EAAS,YAAY,WAAa,GAAK,KAAK,MAAMyB,EAAI,EAAID,CAAS,EAAI,KAAK,MAAMC,EAAI,EAAID,CAAS,GAErJxB,EAAS,QAAQ,gBAAgB,EAGjCA,EAAS,QAAQ,iBAAiB,EAC9BA,EAAS,OAAO,MAClBgC,GAAczB,EAAAP,EAAS,OAAO,KAAK,WAArB,MAAAO,EAA+B,QAAmB6B,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,GAE9InC,EAAS,MAAQ,eACjBwB,EAAYC,EAAI,EAChBO,GAAcxB,EAAAR,EAAS,OAAO,KAAK,WAArB,MAAAQ,EAA+B,QAAU,MAAe4B,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,EACpJnC,EAAS,YAAY,SAAWqC,EAAI,SAAWrC,EAAS,YAAY,WAAa,GAAK,KAAK,MAAMyB,EAAI,EAAID,CAAS,EAAI,KAAK,MAAMC,EAAI,EAAID,CAAS,GAEpJxB,EAAS,QAAQ,eAAe,EAGhCA,EAAS,QAAQ,aAAa,EAC1BA,EAAS,OAAO,MAClB2B,GAAUlB,EAAAT,EAAS,OAAO,KAAK,OAArB,MAAAS,EAA8B,QAAe2B,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,MAErInC,EAAS,MAAQ,WACjBwB,EAAYC,EAAI,EAChBE,GAAUjB,EAAAV,EAAS,OAAO,KAAK,OAArB,MAAAU,EAA8B,QAAU,MAAW0B,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,KAC3InC,EAAS,YAAY,KAAO,KAAK,MAAMyB,EAAI,EAAID,CAAS,GAE1DxB,EAAS,QAAQ,WAAW,EAG5BA,EAAS,QAAQ,eAAe,EAC5BA,EAAS,OAAO,OAClB0B,GAASf,EAAAX,EAAS,OAAO,KAAK,SAArB,MAAAW,EAAgC,QAAoByB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,KAC3IP,GAAYhB,EAAAZ,EAAS,OAAO,KAAK,SAArB,MAAAY,EAAgC,QAAuBwB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,OAEjJnC,EAAS,MAAQ,aACjBwB,EAAYC,EAAI,EAChBC,GAASb,EAAAb,EAAS,OAAO,KAAK,SAArB,MAAAa,EAAgC,QAAU,MAAgBuB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,KACjJP,GAAYd,EAAAd,EAAS,OAAO,KAAK,SAArB,MAAAc,EAAgC,QAAU,MAAmBsB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,KACvJnC,EAAS,YAAY,OAAS,KAAK,MAAMyB,EAAI,EAAID,CAAS,GAE5DxB,EAAS,QAAQ,aAAa,EAG9BA,EAAS,QAAQ,sBAAsB,EACnCA,EAAS,OAAO,MAClB8B,GAAmBf,EAAAf,EAAS,OAAO,KAAK,gBAArB,MAAAe,EAAuC,QAAwBqB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,MAEhKnC,EAAS,MAAQ,oBACjBwB,EAAYC,EAAI,EAChBK,GAAmBd,EAAAhB,EAAS,OAAO,KAAK,gBAArB,MAAAgB,EAAuC,QAAU,MAAoBoB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,KACtKnC,EAAS,YAAY,cAAgB,KAAK,MAAMyB,EAAI,EAAID,CAAS,GAEnExB,EAAS,QAAQ,oBAAoB,EAGrCA,EAAS,QAAQ,oBAAoB,EACjCA,EAAS,OAAO,MAClBiC,GAAUhB,EAAAjB,EAAS,OAAO,KAAK,cAArB,MAAAiB,EAAkC,QAAkBmB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,MAE5InC,EAAS,MAAQ,kBACjBwB,EAAYC,EAAI,EAChBQ,GAAUf,GAAAlB,EAAS,OAAO,KAAK,cAArB,MAAAkB,GAAkC,QAAU,MAAckB,GAAQD,EAAMG,GAAG,QAAa,SAAO,CAAC,CAAC,EAAGtC,EAAS,OAAQsC,EAAGH,EAAM,MAAM,EAAI,KAClJnC,EAAS,YAAY,YAAcqC,EAAI,SAAWrC,EAAS,YAAY,aAAe,GAAK,KAAK,MAAMyB,EAAI,EAAID,CAAS,EAAI,KAAK,MAAMC,EAAI,EAAID,CAAS,GAEzJxB,EAAS,QAAQ,kBAAkB,EAG/BA,EAAS,OAAO,QAClB,CAAC0B,EAAQE,EAAWC,EAAYC,EAAkBG,EAASN,EAASI,EAAcC,CAAW,EAAI,MAAM,QAAQ,IAAI,CAACN,EAAQE,EAAWC,EAAYC,EAAkBG,EAASN,EAASI,EAAcC,CAAW,CAAC,GAEnNhC,EAAS,QAAQ,cAAc,IAE3BmB,EAAAnB,EAAS,OAAO,KAAK,SAArB,YAAAmB,EAAgC,UAAWO,GAAUE,IACvDK,EAAU,CACR,GAAIA,EACJ,IAAMP,EAA0B,IAChC,OAASE,EAAsD,OAC/D,YAAcA,EAAsD,WACtE,KAEER,GAAApB,EAAS,OAAO,KAAK,OAArB,YAAAoB,GAA8B,UAAWO,IAC3CM,EAAU,CACR,GAAIA,EACJ,IAAMN,EAA0B,IAChC,OAASA,EAA0B,OACnC,YAAcA,EAA0B,YACxC,KAAOA,EAA0B,IACnC,KAEEN,GAAArB,EAAS,OAAO,KAAK,gBAArB,YAAAqB,GAAuC,UAAWS,IACnDG,EAAoB,WAAaH,IAK/BR,EAAAtB,EAAS,OAAO,KAAK,OAArB,MAAAsB,EAA2B,QAIhC,IAAMsB,EAAYT,EAAMG,GAAG,aAAeH,EAAMG,GAAG,YAAY,aAAeH,EAAMG,GAAG,YAAY,YAAY,IAAMH,EAAMG,GAAG,YAAY,cAAgBH,EAAMG,GAAG,YAAY,aAAa,IACtLH,EAAMG,GAAG,YAAY,YAAY,OAAS,GAAOH,EAAMG,GAAG,YAAY,aAAa,OAAS,GAC5FH,EAAMG,GAAG,YAAY,YAAY,KAAO,MAAUH,EAAMG,GAAG,YAAY,aAAa,KAAO,KAC7F,KAAK,IAAI,KAAK,IAAIH,EAAMG,GAAG,YAAY,YAAY,GAAG,GAAKH,EAAMG,GAAG,YAAY,YAAY,GAAG,EAAE,EAAG,KAAK,IAAIH,EAAMG,GAAG,YAAY,aAAa,GAAG,GAAKH,EAAMG,GAAG,YAAY,aAAa,GAAG,EAAE,CAAC,EAAIrC,EAAM,MAAM,GAC/M,EAGE4C,IAAStB,GAAAvB,EAAS,OAAO,KAAK,WAArB,MAAAuB,GAA+B,OAAY,UAAQY,EAAMG,GAAG,MAAM,EAAI,KAElF,UAAQH,EAAMG,GAAG,MAAM,EAEtBH,EAAMG,GAAG,QAAQ,OAAOH,EAAMG,GAAG,OAErC,IAAMQ,EAAkB,CACtB,GAAGX,EAAMG,GACT,GAAIA,CACN,EACKL,GAAA,MAAAA,EAAqB,MAAKa,EAAI,IAAOb,EAAoB,KACzDA,GAAA,MAAAA,EAAqB,SAAQa,EAAI,OAAUb,EAAoB,QAC/DA,GAAA,MAAAA,EAAqB,cAAaa,EAAI,YAAeb,GAAA,YAAAA,EAAqB,aAC1EA,GAAA,MAAAA,EAAqB,aAAYa,EAAI,UAAab,GAAA,YAAAA,EAAqB,YACvEA,GAAA,MAAAA,EAAqB,OAAMa,EAAI,KAAQb,GAAA,YAAAA,EAAqB,MAC7DJ,IAAYiB,EAAI,QAAUjB,GAC1BE,IAAce,EAAI,KAAOf,GACzBC,IAAac,EAAI,KAAOd,GACxBY,GAAYA,IAAa,IAAGE,EAAI,KAAO,KAAK,MAAM,IAAMF,EAAW,IAAI,EAAI,KAC3EF,IAAUI,EAAI,SAAWJ,GACzBG,KAAQC,EAAI,OAASD,IACzBX,EAAQ,KAAKY,CAAG,EAChB9C,EAAS,QAAQ,UAAU,CAC7B,CACA,OAAAA,EAAS,QAAQ,eAAe,EAC5BA,EAAS,OAAO,QACdA,EAAS,YAAY,MAAM,OAAOA,EAAS,YAAY,KACvDA,EAAS,YAAY,KAAK,OAAOA,EAAS,YAAY,IACtDA,EAAS,YAAY,QAAQ,OAAOA,EAAS,YAAY,OACzDA,EAAS,YAAY,SAAS,OAAOA,EAAS,YAAY,SAEzDkC,CACT,EC/LO,IAAMa,GAAQC,GAAuC,CAC1D,GAAI,CAACA,EAAK,MAAO,CAAC,EAClB,IAAMC,EAA0D,CAAC,EACjE,QAASC,EAAI,EAAGA,EAAIF,EAAI,OAAQE,IAAK,CAEnC,IAAMC,EAAYH,EAAIE,GAAG,UAAU,KAAME,GAAOA,EAAE,OAAS,WAAY,EACjEC,EAAaL,EAAIE,GAAG,UAAU,KAAME,GAAOA,EAAE,OAAS,YAAa,EACnEE,EAAON,EAAIE,GAAG,UAAU,KAAME,GAAOA,EAAE,OAAS,MAAO,EACzDE,GAAQH,GAAaE,GAAeF,EAAU,SAAS,GAAKG,EAAK,SAAS,IAAQD,EAAW,SAAS,GAAKC,EAAK,SAAS,GAAKL,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,WAAY,CAAC,EACxKI,GAAQH,GAAcA,EAAU,SAAS,GAAKG,EAAK,SAAS,GAAKL,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,iBAAkB,CAAC,EACtHI,GAAQD,GAAeA,EAAW,SAAS,GAAKC,EAAK,SAAS,IAAKL,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,kBAAmB,CAAC,EAGlI,IAAMK,EAAeP,EAAIE,GAAG,UAAU,KAAME,GAAOA,EAAE,OAAS,cAAe,EACvEI,EAAgBR,EAAIE,GAAG,UAAU,KAAME,GAAOA,EAAE,OAAS,eAAgB,EAC3EG,GAAgBC,GAAiB,KAAK,IAAID,EAAa,YAAY,GAAKC,EAAc,YAAY,EAAE,EAAI,IAC1GP,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,WAAYK,EAAa,SAAS,GAAKC,EAAc,SAAS,GAAM,OAAS,SAAU,CAAC,CAE9H,CACA,OAAOP,CACT,EAEaQ,GAAQT,GAAuC,CAC1D,GAAI,CAACA,EAAK,MAAO,CAAC,EAClB,IAAMC,EAA0D,CAAC,EACjE,QAASC,EAAI,EAAGA,EAAIF,EAAI,OAAQE,IAC9B,GAAIF,EAAIE,GAAG,MAAQF,EAAIE,GAAG,KAAK,OAAS,IAAK,CAC3C,IAAMQ,GAASV,EAAIE,GAAG,KAAK,IAAI,IAAM,IAAMF,EAAIE,GAAG,KAAK,KAAK,IAAM,GAC5DS,EAAQX,EAAIE,GAAG,KAAK,IAAI,GAAKF,EAAIE,GAAG,KAAK,KAAK,GAChD,KAAK,IAAIQ,EAAQC,CAAK,GAAK,IAAMV,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,eAAgB,CAAC,EACnFD,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,UAAUQ,EAAQ,EAAI,OAAS,SAAU,CAAC,EAChE,KAAK,IAAIV,EAAIE,GAAG,KAAK,KAAK,GAAKF,EAAIE,GAAG,KAAK,KAAK,EAAE,EAAI,KAAK,IAAIF,EAAIE,GAAG,KAAK,KAAK,GAAKF,EAAIE,GAAG,KAAK,KAAK,EAAE,EAC1G,IAAKD,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,gBAAiB,CAAC,EACtD,KAAK,IAAIF,EAAIE,GAAG,KAAK,KAAK,GAAKF,EAAIE,GAAG,KAAK,KAAK,EAAE,EAAI,KAAK,IAAIF,EAAIE,GAAG,KAAK,KAAK,GAAKF,EAAIE,GAAG,KAAK,KAAK,EAAE,EAC1G,IAAKD,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,iBAAkB,CAAC,EAC1E,IAAMU,EAAY,KAAK,IAAI,IAAK,IAAM,KAAK,IAAIZ,EAAIE,GAAG,KAAK,IAAI,GAAKF,EAAIE,GAAG,KAAK,IAAI,EAAE,EAAI,KAAK,IAAIF,EAAIE,GAAG,KAAK,IAAI,GAAKF,EAAIE,GAAG,KAAK,KAAK,EAAE,CAAC,EACxIU,EAAY,IAAIX,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,SAAS,KAAK,MAAMU,CAAS,SAAU,CAAC,EAC9F,IAAMC,EAAYb,EAAIE,GAAG,KAAK,KAAK,IAAM,EACrC,KAAK,IAAIW,CAAS,EAAI,IAAIZ,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,QAAQW,EAAY,EAAI,KAAO,QAAS,CAAC,CAC3G,CAEF,OAAOZ,CACT,EAEaa,GAAQd,GAAuC,CAC1D,GAAI,CAACA,EAAK,MAAO,CAAC,EAClB,IAAMC,EAA0D,CAAC,EACjE,QAASC,EAAI,EAAGA,EAAIF,EAAI,OAAQE,IAAK,CACnC,GAAI,CAACF,EAAIE,GAAG,aAAe,CAACF,EAAIE,GAAG,YAAY,aAAe,CAACF,EAAIE,GAAG,YAAY,YAAY,IAAM,CAACF,EAAIE,GAAG,YAAY,cAAgB,CAACF,EAAIE,GAAG,YAAY,aAAa,GAAI,SAC7K,IAAMa,EAAYf,EAAIE,GAAG,YAAY,YAAY,GAAG,GAAKF,EAAIE,GAAG,YAAY,YAAY,GAAG,GACrFc,EAAYhB,EAAIE,GAAG,YAAY,YAAY,GAAG,GAAKF,EAAIE,GAAG,YAAY,YAAY,GAAG,GACrFe,EAAW,KAAK,IAAIF,EAAYC,CAAS,EAEzCE,EAAalB,EAAIE,GAAG,YAAY,aAAa,GAAG,GAAKF,EAAIE,GAAG,YAAY,aAAa,GAAG,GACxFiB,EAAanB,EAAIE,GAAG,YAAY,aAAa,GAAG,GAAKF,EAAIE,GAAG,YAAY,aAAa,GAAG,GACxFkB,EAAY,KAAK,IAAIF,EAAaC,CAAU,EAE9CE,EAAS,GACM,KAAK,IAAIJ,EAAWG,CAAS,EAAI,KAAK,IAAIH,EAAUG,CAAS,EAC/D,MACfC,EAAS,GACTpB,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,eAAgB,CAAC,GAGrD,IAAMoB,EAAkB,KAAK,IAAItB,EAAIE,GAAG,KAAK,KAAK,GAAKF,EAAIE,GAAG,YAAY,YAAY,GAAG,EAAE,EAAIF,EAAIE,GAAG,IAAI,GACpGqB,EAAmB,KAAK,IAAIvB,EAAIE,GAAG,KAAK,IAAI,GAAKF,EAAIE,GAAG,YAAY,aAAa,GAAG,EAAE,EAAIF,EAAIE,GAAG,IAAI,IACvGoB,EAAkB,KAAQC,EAAmB,OAAMF,EAAS,IAC5DC,EAAkBC,EAChBD,EAAkB,KAAMrB,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,eAAgB,CAAC,EAE3EqB,EAAmB,KAAMtB,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,cAAe,CAAC,EAGjF,IAAMsB,EAAmB,KAAK,IAAIxB,EAAIE,GAAG,KAAK,KAAK,GAAKF,EAAIE,GAAG,YAAY,aAAa,GAAG,EAAE,EAAIF,EAAIE,GAAG,IAAI,GACtGuB,EAAkB,KAAK,IAAIzB,EAAIE,GAAG,KAAK,KAAK,GAAKF,EAAIE,GAAG,YAAY,YAAY,GAAG,EAAE,EAAIF,EAAIE,GAAG,IAAI,IACtGuB,EAAkB,KAAQD,EAAmB,KAAQC,EAAkB,MAASD,EAAmB,QAAOH,EAAS,KACnHI,EAAkB,KAAQD,EAAmB,MAAMvB,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,cAAe,CAAC,GACrGuB,EAAkB,MAASD,EAAmB,OAAOvB,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,YAAa,CAAC,EAGrGmB,GAAQpB,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,gBAAiB,CAAC,CAClE,CACA,OAAOD,CACT,EAEayB,GAAQ1B,GAAuC,CAC1D,GAAI,CAACA,EAAK,MAAO,CAAC,EAClB,IAAMC,EAA0D,CAAC,EACjE,QAASC,EAAI,EAAGA,EAAIF,EAAI,OAAQE,IAAK,CACnC,IAAMyB,EAAoD,CAAC,EAC3D,GAAI3B,EAAIE,GAAG,YACT,OAAW,CAAC0B,EAAQC,CAAG,IAAK,OAAO,QAAQ7B,EAAIE,GAAG,WAAc,EAC1D0B,IAAW,YAAc,MAAM,QAAQC,CAAG,GAAKA,EAAI,IAAIF,EAAQ,KAAK,CAAE,KAAMC,EAAO,YAAY,EAAG,SAAUC,EAAI,EAAG,CAAC,EAG5H,GAAIF,GAAWA,EAAQ,OAAS,EAAG,CACjC,IAAMG,EAAUH,EAAQ,OAAO,CAACI,EAAM3B,KAAQ2B,EAAK,SAAS,IAAM,IAAM3B,EAAE,SAAS,IAAM,GAAK2B,EAAO3B,CAAE,EACvGH,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,GAAG4B,EAAQ,cAA8B,CAAC,EAC5E,IAAME,EAAUL,EAAQ,OAAO,CAACI,EAAM3B,IAAO2B,EAAK,SAAS,GAAK3B,EAAE,SAAS,GAAK2B,EAAO3B,CAAE,EACzFH,EAAS,KAAK,CAAE,KAAMC,EAAG,QAAS,GAAG8B,EAAQ,SAAyB,CAAC,CACzE,CACA,GAAIhC,EAAIE,GAAG,UAAc,CACvB,IAAM+B,EAAmBC,GAAMlC,EAAIE,GAAG,SAAY,EAClD,QAAWiC,KAAQF,EAAOhC,EAAS,KAAK,CAAE,KAAMC,EAAG,QAASiC,EAAK,IAAoB,CAAC,CACxF,CACF,CACA,OAAOlC,CACT,EC/HA,IAAMmC,EAAyB,CAAE,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,QAAS,CAAC,EAAG,OAAQ,CAAC,EAAG,QAAS,CAAC,EAAG,YAAa,CAAC,EAAG,UAAW,EAAG,MAAO,IAAK,EAC5IC,GAAkB,EAEf,SAASC,GAAKC,EAAmBC,EAAwB,CAhBhE,IAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,GAAAC,EAAAC,GAAAC,GAiBE,IAAMC,EAAKC,EAAI,EACf,GAAI,CAAC9B,EAAW,MAAO,CAAE,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,QAAS,CAAC,EAAG,OAAQ,CAAC,EAAG,QAAS,CAAC,EAAG,YAAa,CAAC,EAAG,UAAW,EAAG,MAAO,IAAK,EAKxI,IAAM+B,EAAU,KAAK,IAAI,EAAI/B,EAAU,UAQjCgC,EAAiBD,EAAU,IAAO,EAAI,KAAK,IAAIA,EAAU,CAAC,EAAI,EAMpE,GAJI/B,EAAU,SAAQH,EAAe,OAASG,EAAU,QACpDA,EAAU,QAAOH,EAAe,MAAQG,EAAU,OAGlD,CAACH,EAAe,MAASG,EAAU,KAAK,SAAWH,EAAe,KAAK,OACzEA,EAAe,KAAO,KAAK,MAAM,KAAK,UAAUG,EAAU,IAAoB,CAAC,MAE/E,SAASiC,EAAI,EAAGA,EAAIjC,EAAU,KAAK,OAAQiC,IAAK,CAC9C,IAAMC,GAAMlC,EAAU,KAAKiC,GAAG,IAC3B,IAAI,CAACE,EAAaC,MAAQJ,EAAiB,GAAKnC,EAAe,KAAKoC,GAAG,IAAIG,GAAKD,GAAeH,CAAc,EAC1GK,EAASrC,EAAU,KAAKiC,GAAG,OAC9B,IAAI,CAACE,EAAaC,MAAQJ,EAAiB,GAAKnC,EAAe,KAAKoC,GAAG,OAAOG,GAAKD,GAAeH,CAAc,EAC7GM,EAAatC,EAAU,KAAKiC,GAAG,UAClC,IAAI,CAACM,EAAQH,IAAG,CA9CzB,IAAAlC,GAAAC,GAAAC,GAAAC,GAAAC,GAAAC,GAAAC,GAAAC,GAAAC,GA8C6B,OACnB,MAAO6B,EAAO,MACd,KAAMA,EAAO,KACb,SAAU,CACR1C,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,IAAMnC,EAAe,KAAKoC,GAAG,UAAUG,GAAG,SAAS,IAAM,IAAMG,EAAO,SAAS,IAAM,IAAMP,EAAiBO,EAAO,SAAS,GACrL1C,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,IAAMnC,EAAe,KAAKoC,GAAG,UAAUG,GAAG,SAAS,IAAM,IAAMG,EAAO,SAAS,IAAM,IAAMP,EAAiBO,EAAO,SAAS,GACrL1C,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,IAAMnC,EAAe,KAAKoC,GAAG,UAAUG,GAAG,SAAS,IAAM,IAAMG,EAAO,SAAS,IAAM,IAAMP,EAAiBO,EAAO,SAAS,EACvL,EACA,YAAa,CACX1C,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,IAAMnC,EAAe,KAAKoC,GAAG,UAAUG,GAAG,YAAY,IAAM,IAAMG,EAAO,YAAY,IAAM,IAAMP,EAAiBO,EAAO,YAAY,GAC9L1C,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,IAAMnC,EAAe,KAAKoC,GAAG,UAAUG,GAAG,YAAY,IAAM,IAAMG,EAAO,YAAY,IAAM,IAAMP,EAAiBO,EAAO,YAAY,GAC9L1C,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,IAAMnC,EAAe,KAAKoC,GAAG,UAAUG,GAAG,YAAY,IAAM,IAAMG,EAAO,YAAY,IAAM,IAAMP,EAAiBO,EAAO,YAAY,EAChM,EACA,SAAU,CACR1C,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,MAAM9B,GAAAL,EAAe,KAAKoC,GAAG,UAAUG,GAAG,WAApC,YAAAlC,GAA+C,KAAM,MAAMC,GAAAoC,EAAO,WAAP,YAAApC,GAAkB,KAAM,IAAM6B,GAAiB5B,GAAAmC,EAAO,WAAP,YAAAnC,GAAkB,GAC3LP,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,MAAM3B,GAAAR,EAAe,KAAKoC,GAAG,UAAUG,GAAG,WAApC,YAAA/B,GAA+C,KAAM,MAAMC,GAAAiC,EAAO,WAAP,YAAAjC,GAAkB,KAAM,IAAM0B,GAAiBzB,GAAAgC,EAAO,WAAP,YAAAhC,GAAkB,GAC3LV,EAAe,KAAKoC,GAAG,UAAUG,KAAOJ,EAAiB,MAAMxB,GAAAX,EAAe,KAAKoC,GAAG,UAAUG,GAAG,WAApC,YAAA5B,GAA+C,KAAM,MAAMC,GAAA8B,EAAO,WAAP,YAAA9B,GAAkB,KAAM,IAAMuB,GAAiBtB,GAAA6B,EAAO,WAAP,YAAA7B,GAAkB,EAC7L,CACF,EAAE,EAEE8B,EAAiD,CAAC,EACpDC,GAAS,CAAE,UAAW,CAAC,CAAE,GACzBtC,GAAAD,EAAAD,EAAO,OAAP,YAAAC,EAAa,YAAb,MAAAC,EAAwB,SAAS,iBAAkBsC,GAASC,IACvDrC,GAAAD,EAAAH,EAAO,OAAP,YAAAG,EAAa,YAAb,MAAAC,EAAwB,SAAS,aAAcoC,GAASE,IACxDpC,GAAAD,EAAAL,EAAO,OAAP,YAAAK,EAAa,YAAb,MAAAC,EAAwB,SAAS,aAAYkC,GAASG,IAC/D,OAAW,CAACC,EAAMC,CAAO,IAAK,OAAO,QAAQL,GAAO,SAAqC,EAAG,CAC1F,IAAMM,GAAqB,CAAC,EAC5B,QAASX,GAAI,EAAGA,GAAIU,EAAQ,OAAS,EAAGV,KAAK,CAC3C,IAAMY,GAAMV,EAAU,KAAMW,IAAOA,GAAG,OAASH,EAAQV,GAAE,EACnDc,GAAMZ,EAAU,KAAMW,IAAOA,GAAG,OAASH,EAAQV,GAAI,EAAE,EAEzDY,IAAOE,IAAKH,GAAG,KAAK,CAACC,GAAI,SAAUE,GAAI,QAAQ,CAAC,CACtD,CACAV,EAAYK,GAAQE,EACtB,CACAlD,EAAe,KAAKoC,GAAK,CAAE,GAAGjC,EAAU,KAAKiC,GAAI,IAAAC,GAAK,OAAAG,EAAQ,UAAAC,EAAW,YAAaE,CAAyC,CACjI,CAIF,GAAI,CAAC3C,EAAe,MAASG,EAAU,KAAK,SAAWH,EAAe,KAAK,OACzEA,EAAe,KAAO,KAAK,MAAM,KAAK,UAAUG,EAAU,IAAoB,CAAC,MAE/E,SAASiC,EAAI,EAAGA,EAAIjC,EAAU,KAAK,OAAQiC,IAAK,CAC9C,IAAMC,GAAOlC,EAAU,KAAKiC,GAAG,IAC5B,IAAI,CAACkB,GAAGf,MAAQJ,EAAiB,GAAKnC,EAAe,KAAKoC,GAAG,IAAIG,GAAKe,IAAKnB,CAAc,EACtFK,EAAUrC,EAAU,KAAKiC,GAAG,OAC/B,IAAI,CAACkB,GAAGf,MAAQJ,EAAiB,GAAKnC,EAAe,KAAKoC,GAAG,OAAOG,GAAKe,IAAKnB,CAAc,EAC3FnC,EAAe,KAAKoC,GAAG,UAAU,SAAWjC,EAAU,KAAKiC,GAAG,UAAU,SAAQpC,EAAe,KAAKoC,GAAG,UAAYjC,EAAU,KAAKiC,GAAG,WACzI,IAAMK,EAAYtC,EAAU,KAAKiC,GAAG,WAAajC,EAAU,KAAKiC,GAAG,UAAU,OAAS,EAAIjC,EAAU,KAAKiC,GAAG,UACzG,IAAI,CAACmB,GAAUhB,IAAMgB,GACnB,IAAI,CAACC,EAAOC,OAAStB,EAAiB,IAAMnC,EAAe,KAAKoC,GAAG,UAAUG,GAAGkB,KAAM,IAAMD,GAAS,IAAMrB,CAAe,CAAU,EACrI,CAAC,EACDQ,EAAc,CAAC,EACnB,GAAI,OAAO,KAAK3C,EAAe,KAAKoC,GAAG,WAAW,EAAE,SAAW,OAAO,KAAKjC,EAAU,KAAKiC,GAAG,WAAW,EAAE,OACxGpC,EAAe,KAAKoC,GAAG,YAAcjC,EAAU,KAAKiC,GAAG,YACvDO,EAAc3C,EAAe,KAAKoC,GAAG,oBAC5BjC,EAAU,KAAKiC,GAAG,YAC3B,QAAWsB,MAAO,OAAO,KAAKvD,EAAU,KAAKiC,GAAG,WAAW,EACzDO,EAAYe,IAAOvD,EAAU,KAAKiC,GAAG,YAAYsB,KAAQvD,EAAU,KAAKiC,GAAG,YAAYsB,IAAK,GACxFvD,EAAU,KAAKiC,GAAG,YAAYsB,IAC7B,IAAI,CAACC,EAAKpB,IAAcoB,EACtB,IAAI,CAACH,GAAeC,OAAgBtB,EAAiB,GAAKnC,EAAe,KAAKoC,GAAG,YAAYsB,IAAKnB,GAAGkB,IAAKD,IAASrB,CAAc,CAAC,EACrI,KAGRnC,EAAe,KAAKoC,GAAK,CAAE,GAAGjC,EAAU,KAAKiC,GAAI,IAAAC,GAAK,OAAAG,EAAQ,UAAAC,EAAW,YAAaE,CAAyC,CACjI,CAIF,GAAI,CAAC3C,EAAe,MAASG,EAAU,KAAK,SAAWH,EAAe,KAAK,OACzEA,EAAe,KAAO,KAAK,MAAM,KAAK,UAAUG,EAAU,IAAoB,CAAC,MAE/E,SAASiC,EAAI,EAAGA,EAAIjC,EAAU,KAAK,OAAQiC,IAAK,CAC9C,IAAMC,GAAOlC,EAAU,KAAKiC,GAAG,IAC5B,IAAI,CAACkB,EAAGf,MAAQJ,EAAiB,GAAKnC,EAAe,KAAKoC,GAAG,IAAIG,GAAKe,GAAKnB,CAAc,EACtFK,EAAUrC,EAAU,KAAKiC,GAAG,OAC/B,IAAI,CAACkB,EAAGf,MAAQJ,EAAiB,GAAKnC,EAAe,KAAKoC,GAAG,OAAOG,GAAKe,GAAKnB,CAAc,EAC/F,GAAIhC,EAAU,KAAKiC,GAAG,SAAU,CAC9B,IAAMwB,EAIF,CAAE,OAAQ,CAAC,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,EAAG,CAAC,EAAG,MAAO,CAAE,KAAM,EAAG,IAAK,EAAG,MAAO,CAAE,EAAG,KAAM,CAAE,QAAS,EAAG,SAAU,CAAE,CAAE,EACnHA,EAAS,QAASjD,EAAAR,EAAU,KAAKiC,GAAG,WAAlB,YAAAzB,EAA4B,OAC9CiD,EAAS,MAAQ,CACf,OAAQzB,EAAiB,MAAMtB,GAAAD,EAAAZ,EAAe,KAAKoC,GAAG,WAAvB,YAAAxB,EAAiC,QAAjC,YAAAC,EAAwC,OAAQ,MAAME,GAAAD,EAAAX,EAAU,KAAKiC,GAAG,WAAlB,YAAAtB,EAA4B,QAA5B,YAAAC,EAAmC,OAAQ,IAAMoB,EACtI,MAAOA,EAAiB,MAAMlB,GAAAD,EAAAhB,EAAe,KAAKoC,GAAG,WAAvB,YAAApB,EAAiC,QAAjC,YAAAC,EAAwC,MAAO,MAAME,GAAAD,EAAAf,EAAU,KAAKiC,GAAG,WAAlB,YAAAlB,EAA4B,QAA5B,YAAAC,EAAmC,MAAO,IAAMgB,EACnI,QAASA,EAAiB,MAAMd,GAAAD,EAAApB,EAAe,KAAKoC,GAAG,WAAvB,YAAAhB,EAAiC,QAAjC,YAAAC,EAAwC,QAAS,MAAME,GAAAD,EAAAnB,EAAU,KAAKiC,GAAG,WAAlB,YAAAd,EAA4B,QAA5B,YAAAC,EAAmC,QAAS,IAAMY,CAC3I,EACAyB,EAAS,KAAO,CAEd,UAAWzB,EAAiB,MAAMV,GAAAD,EAAAxB,EAAe,KAAKoC,GAAG,WAAvB,YAAAZ,EAAiC,OAAjC,YAAAC,EAAuC,UAAW,MAAME,GAAAD,EAAAvB,EAAU,KAAKiC,GAAG,WAAlB,YAAAV,EAA4B,OAA5B,YAAAC,EAAkC,UAAW,IAAMQ,EAC7I,WAAYA,EAAiB,MAAMN,GAAAD,GAAA5B,EAAe,KAAKoC,GAAG,WAAvB,YAAAR,GAAiC,OAAjC,YAAAC,EAAuC,WAAY,MAAME,IAAAD,GAAA3B,EAAU,KAAKiC,GAAG,WAAlB,YAAAN,GAA4B,OAA5B,YAAAC,GAAkC,WAAY,IAAMI,CAClJ,EACAnC,EAAe,KAAKoC,GAAK,CAAE,GAAGjC,EAAU,KAAKiC,GAAI,SAAAwB,EAAU,IAAAvB,GAAK,OAAAG,CAAO,CACzE,CACAxC,EAAe,KAAKoC,GAAK,CAAE,GAAGjC,EAAU,KAAKiC,GAAI,IAAAC,GAAK,OAAAG,CAAO,CAC/D,CAIF,GAAI,CAACxC,EAAe,QAAWG,EAAU,OAAO,SAAWH,EAAe,OAAO,OAC/EA,EAAe,OAAS,KAAK,MAAM,KAAK,UAAUG,EAAU,MAAwB,CAAC,MAErF,SAASiC,EAAI,EAAGA,EAAIjC,EAAU,OAAO,OAAQiC,IAAK,CAChD,IAAMC,GAAOlC,EAAU,OAAOiC,GAAG,IAC9B,IAAI,CAACkB,EAAGf,MAAQJ,EAAiB,GAAKnC,EAAe,OAAOoC,GAAG,IAAIG,GAAKe,GAAKnB,CAAc,EACxFK,EAAUrC,EAAU,OAAOiC,GAAG,OACjC,IAAI,CAACkB,EAAGf,MAAQJ,EAAiB,GAAKnC,EAAe,OAAOoC,GAAG,OAAOG,GAAKe,GAAKnB,CAAc,EACjGnC,EAAe,OAAOoC,GAAK,CAAE,GAAGjC,EAAU,OAAOiC,GAAI,IAAAC,GAAK,OAAAG,CAAO,CACnE,CAIF,GAAIrC,EAAU,QAAS,CACrB,IAAM0D,EAAa1D,EAAU,QAC7B,GAAI,CAACH,EAAe,SAAY6D,EAAW,SAAW7D,EAAe,QAAQ,OAC3EA,EAAe,QAAU,KAAK,MAAM,KAAK,UAAU6D,CAA4B,CAAC,MAEhF,SAASzB,GAAI,EAAGA,GAAIyB,EAAW,OAAQzB,KACrCpC,EAAe,QAAQoC,IAAG,IAAOyB,EAAWzB,IAAG,IAC5C,IAAI,CAACC,EAAKE,MAAQJ,EAAiB,GAAKnC,EAAe,QAAQoC,IAAG,IAAIG,GAAKF,GAAOF,CAAc,CAGzG,CAGIhC,EAAU,UAASH,EAAe,QAAUG,EAAU,SAG1D,IAAM2D,EAAK7B,EAAI,EACf,OAAAhC,GAAkB8D,EAAI,QAAU9D,GAAkB,KAAK,MAAM6D,EAAK9B,CAAE,EAAI,KAAK,MAAM8B,EAAK9B,CAAE,EACtF7B,EAAU,cAAaH,EAAe,YAAc,CAAE,GAAGG,EAAU,YAAa,YAAaF,EAAgB,GAE1GD,CACT,CCvLA,IAAAgE,GAAA,GAAAC,GAAAD,GAAA,cAAAE,GAAA,UAAAC,GAAA,eAAAC,KAWO,SAASF,GAASG,EAAyBC,EAAyBC,EAAwB,CAAE,MAAO,EAAG,WAAY,EAAG,EAAG,CAE/H,IAAIC,EAAM,EACV,QAASC,EAAI,EAAGA,EAAIJ,EAAY,OAAQI,IAAK,CAC3C,IAAMC,EAAQ,CAACH,EAAQ,OAASA,EAAQ,QAAU,EAAMF,EAAYI,GAAKH,EAAYG,GAAO,KAAK,IAAIJ,EAAYI,GAAKH,EAAYG,EAAE,EACpID,GAAQ,CAACD,EAAQ,OAASA,EAAQ,QAAU,EAAMG,EAAOA,EAASA,GAAQH,EAAQ,KACpF,CACA,OAAQA,EAAQ,YAAc,IAAMC,CACtC,CAGA,IAAMG,GAAoB,CAACC,EAAMC,EAAOC,EAAKC,IAAQ,CACnD,GAAIH,IAAS,EAAG,MAAO,GACvB,IAAMI,EAAOH,IAAU,EAAI,KAAK,KAAKD,CAAI,EAAIA,IAAS,EAAIC,GACpDI,GAAQ,EAAKD,EAAO,IAAOF,IAAQC,EAAMD,GAE/C,OADc,KAAK,IAAI,KAAK,IAAIG,EAAM,CAAC,EAAG,CAAC,CAE7C,EAaO,SAASb,GAAWC,EAAyBC,EAAyBC,EAAwB,CAAE,MAAO,EAAG,WAAY,GAAI,IAAK,GAAK,IAAK,EAAI,EAAG,CACrJ,IAAMK,EAAOV,GAASG,EAAaC,EAAaC,CAAO,EACvD,OAAOI,GAAkBC,EAAML,EAAQ,OAAS,EAAGA,EAAQ,KAAO,EAAGA,EAAQ,KAAO,CAAC,CACvF,CAWO,SAASJ,GAAMe,EAAwBC,EAAgCZ,EAAwB,CAAE,MAAO,EAAG,WAAY,GAAI,UAAW,EAAG,IAAK,GAAK,IAAK,EAAI,EAAG,CACpK,GAAI,CAAC,MAAM,QAAQW,CAAU,GAAK,CAAC,MAAM,QAAQC,CAAW,GAAKD,EAAW,OAAS,IAAMC,EAAY,SAAW,GAAKD,EAAW,SAAWC,EAAY,GAAG,OAC1J,MAAO,CAAE,MAAO,GAAI,SAAU,OAAO,kBAAmB,WAAY,CAAE,EAExE,IAAIC,EAAiB,OAAO,iBACxBC,EAAQ,GACZ,QAASZ,EAAI,EAAGA,EAAIU,EAAY,OAAQV,IAAK,CAC3C,IAAMa,EAAMpB,GAASgB,EAAYC,EAAYV,GAAIF,CAAO,EAKxD,GAJIe,EAAMF,IACRA,EAAiBE,EACjBD,EAAQZ,GAENW,GAAkBb,EAAQ,WAAa,GAAI,KACjD,CACA,IAAMgB,EAAuBZ,GAAkBS,EAAgBb,EAAQ,OAAS,EAAGA,EAAQ,KAAO,EAAGA,EAAQ,KAAO,CAAC,EACrH,MAAO,CAAE,MAAAc,EAAO,SAAUD,EAAgB,WAAYG,CAAqB,CAC7E,CCjEO,SAASC,GAAKC,EAA0BC,EAA2BC,EAA0BC,EAAgCC,EAAuD,CAN3L,IAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAOE,IAAIC,EAAK,EACHC,EAA+B,CAAC,EACtC,QAAWC,KAAQvB,EAAO,CACxB,IAAMwB,EAAuB,CAAE,GAAIH,IAAM,KAAAE,EAAM,KAAM,KAAM,MAAO,CAAE,KAAM,KAAM,MAAO,IAAK,EAAG,SAAU,CAAC,EAAG,IAAK,CAAC,EAAG,EAAG,EAAG,CAAC,CAAE,EAC/H,QAAWE,KAAQxB,EACbsB,EAAK,IAAI,GAAKE,EAAK,IAAI,IACtBF,EAAK,IAAI,GAAKE,EAAK,IAAI,GAAKA,EAAK,IAAI,IACrCF,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKE,EAAK,IAAI,IACrCF,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKE,EAAK,IAAI,GAAKA,EAAK,IAAI,KACtDD,EAAO,KAAOC,GAGlB,GAAID,EAAO,KACT,QAAWE,KAAQxB,EACbwB,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,IAC3CE,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,GAAKA,EAAO,KAAK,IAAI,IACjEE,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,IAC5CE,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,GAAKA,EAAO,KAAK,IAAI,IAChEA,EAAO,QAAOA,EAAO,MAAM,KAAOE,GAEpCA,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,GAAKA,EAAO,KAAK,IAAI,IAClDE,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,IAC9BE,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,IAC5CE,EAAK,IAAI,GAAKA,EAAK,IAAI,GAAKF,EAAO,KAAK,IAAI,GAAKA,EAAO,KAAK,IAAI,IAChEA,EAAO,QAAOA,EAAO,MAAM,MAAQE,GAI7C,QAAWC,KAAWxB,EAChBwB,EAAQ,OAAY,QAAaA,EAAQ,OAAYJ,EAAK,IAAIlB,EAAAmB,EAAO,WAAP,MAAAnB,EAAiB,KAAKsB,GAC/EA,EAAQ,OAAY,QAAaA,EAAQ,OAAYJ,EAAK,IAAIjB,EAAAkB,EAAO,WAAP,MAAAlB,EAAiB,KAAKqB,GACpFA,EAAQ,OAAY,QAAaA,EAAQ,SAAYpB,EAAAiB,EAAO,OAAP,YAAAjB,EAAa,KAAIC,EAAAgB,EAAO,WAAP,MAAAhB,EAAiB,KAAKmB,GAC5FA,EAAQ,OAAY,QAAaA,EAAQ,SAAYjB,GAAAD,EAAAe,EAAO,QAAP,YAAAf,EAAc,OAAd,YAAAC,EAAoB,KAAIC,EAAAa,EAAO,WAAP,MAAAb,EAAiB,KAAKgB,GACnGA,EAAQ,OAAY,QAAaA,EAAQ,SAAYd,GAAAD,EAAAY,EAAO,QAAP,YAAAZ,EAAc,QAAd,YAAAC,EAAqB,OAAIC,EAAAU,EAAO,WAAP,MAAAV,EAAiB,KAAKa,IAI/G,IAAMC,EAAc,CAAC,EACfC,EAAc,CAAC,EACfC,EAAaC,GAAyB,CACtCA,GAAOA,EAAI,SAAW,IACxBH,EAAE,KAAKG,EAAI,GAAIA,EAAI,GAAKA,EAAI,EAAE,EAC9BF,EAAE,KAAKE,EAAI,GAAIA,EAAI,GAAKA,EAAI,EAAE,EAElC,EACAD,GAAUf,EAAAS,EAAO,OAAP,YAAAT,EAAa,GAAG,EAC1Be,GAAUd,EAAAQ,EAAO,OAAP,YAAAR,EAAa,GAAG,EAC1Bc,GAAUZ,GAAAD,EAAAO,EAAO,QAAP,YAAAP,EAAc,OAAd,YAAAC,EAAoB,GAAG,EACjCY,GAAUV,GAAAD,EAAAK,EAAO,QAAP,YAAAL,EAAc,QAAd,YAAAC,EAAqB,GAAG,EAClC,IAAMY,EAAO,KAAK,IAAI,GAAGJ,CAAC,EACpBK,GAAO,KAAK,IAAI,GAAGJ,CAAC,EAC1BL,EAAO,IAAM,CAACQ,EAAMC,GAAM,KAAK,IAAI,GAAGL,CAAC,EAAII,EAAM,KAAK,IAAI,GAAGH,CAAC,EAAII,EAAI,EAGlE7B,GAASA,EAAM,IAAMA,EAAM,KAAIoB,EAAO,OAAS,CAACA,EAAO,IAAI,GAAKpB,EAAM,GAAIoB,EAAO,IAAI,GAAKpB,EAAM,GAAIoB,EAAO,IAAI,GAAKpB,EAAM,GAAIoB,EAAO,IAAI,GAAKpB,EAAM,EAAE,GAE1JkB,EAAQ,KAAKE,CAAM,CACrB,CACA,OAAOF,CACT,CC7DO,IAAMY,GAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kEA0JPC,GAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;MCjJpB,eAAeC,GAAaC,EAA8C,CACxE,IAAMC,EAAY,CAACC,EAAgBC,EAAO,6BAA+B,MAAM,QAAQA,YAAeD,GAAQ,EAAE,KAAME,GAAQA,EAAI,KAAK,CAAC,EACpIC,EACAD,EACJ,OAAQJ,EAAS,OAAO,YACjB,OAAQK,EAAO,MAAMJ,EAAiBK,EAAI,EAAG,UAC7C,WACA,OAAQD,EAAO,MAAMJ,EAAiBM,EAAI,EAAG,cACzCF,EAAO,KAElB,GAAIA,EAAM,CACR,IAAMG,EAAS,MAAM,kBAAkBH,CAAI,EAC3CD,EAAM,MAAMJ,EAAS,OAAOQ,EAAQR,EAAS,MAAM,EACnDQ,EAAO,MAAM,CACf,CACA,OAAOJ,CACT,CAEA,eAAeK,GAAaT,EAA8C,CACxE,OAAO,IAAI,QAASU,GAAY,CAC9B,IAAIC,EAEJ,OAAQX,EAAS,OAAO,YACjB,OAEHW,EAAM,0BAAmCL,GACzC,UACG,WACA,OAEHK,EAAM,0BAAmCJ,GACzC,cAEAI,EAAM,KAGV,IAAIC,EACJ,GAAI,OAAO,OAAU,YAAaA,EAAM,IAAI,cAEnCC,EAAI,MAAOD,EAAM,IAAIC,EAAI,UAC7B,QACLD,EAAI,OAAS,SAAY,CACvB,IAAME,EAAeA,GAAOF,EAAI,aAAcA,EAAI,aAAa,EAC/D,GAAI,CAACE,EACHC,EAAI,0BAA0B,EAC9BL,EAAQ,MAAS,MACZ,CACL,IAAMM,EAAMF,EAAO,WAAW,IAAI,EAC9BE,GAAKA,EAAI,UAAUJ,EAAK,EAAG,CAAC,EAEhC,IAAMK,EAAS,MAAMjB,EAAS,MAAMc,CAAM,EACpCV,EAAM,MAAMJ,EAAS,OAAOiB,EAAO,OAAkBjB,EAAS,MAAM,EAC1EU,EAAQN,CAAG,CACb,CACF,EACIO,EAAKC,EAAI,IAAMD,EACdD,EAAQ,MAAS,CACxB,CAAC,CACH,CAEA,eAAeQ,GAAWlB,EAA8C,CACtE,IAAMmB,EAAQC,GAAgB,OAAO,KAAKA,EAAK,QAAQ,EACnDR,EACAZ,EAAS,OAAO,SAAW,OAAQY,EAAMO,EAAYb,EAAI,EACxDM,EAAMO,EAAYZ,EAAI,EAC3B,IAAIH,EACJ,GAAI,SAAUiB,EAAI,CAEhB,IAAMC,EAAU,OAAQ,WAAWV,CAAG,EAChCW,EAAWD,EAAK,WAAW,CAAC,EAClCtB,EAAS,GAAG,QAAQsB,CAAI,EAExBlB,EAAM,MAAMJ,EAAS,OAAOuB,EAAUvB,EAAS,MAAM,EACrDA,EAAS,GAAG,QAAQuB,CAAQ,CAC9B,MACMvB,EAAS,OAAO,OAAOe,EAAI,6BAA6B,EAS9D,OAAOX,CACT,CAEA,eAAeoB,GAAaxB,EAAiB,CAC3C,IAAII,EACJ,OAAI,OAAO,mBAAsB,WAAYA,EAAM,MAAML,GAAaC,CAAQ,EACrE,OAAO,OAAU,aAAea,EAAI,SAAW,OAAWT,EAAM,MAAMK,GAAaT,CAAQ,EAC/FI,EAAM,MAAMc,GAAWlB,CAAQ,EAC7BI,CACT,CAGA,eAAsBqB,GAAWC,EAAmB,CAClD,GAAI,CAAI,MAAI,EAAE,aAAa,oBAAwB,OACnD,IAAMC,EAAiB,aAAW,EAC5BC,EAAkB,UAAQ,EAChC,GAAKD,IAAgB,SAAWA,IAAgB,WAAe,CAACC,GAAgB,CAACA,EAAa,uBAE5F,OAEC,MAAI,EAAE,IAAI,sBAAuB,EAAI,EACxC,IAAMC,EAAqB,SAAO,EAAE,MAAM,WACpCC,EAA2B,CAAC,EAClC,OAAW,CAACC,EAAWC,CAAK,IAAK,OAAO,QAAQN,CAAS,EAAE,OAAO,CAAC,CAACO,EAAKC,CAAG,IAAOD,IAAQ,MAAQC,IAAQ,IAAK,EAAG,CACjH,IAAMC,EAASH,EAAM,QAAUA,EAAM,OAAO,IAAMA,EAAM,OAAO,GAAG,MAAS,CAAC,GAAGA,EAAM,OAAO,GAAG,KAAK,EAAI,CAAC,EAAG,GAAI,GAAI,CAAC,EAC/GI,EAASJ,EAAM,QAAUA,EAAM,OAAO,IAAMA,EAAM,OAAO,GAAG,MAASA,EAAM,OAAO,GAAG,MAAQ,UACnG,QAASK,EAAM,EAAGA,EAAMF,EAAM,OAAQE,IAChCF,EAAME,KAAS,KAAIF,EAAME,GAAOA,IAAQ,EAAI,EAAI,IAEtD,IAAMpB,EAAY,QAAMkB,EAAOC,CAAK,EAEpC,GAAI,CACF,IAAMhC,EAAM4B,EAAM,QAAQf,CAAM,EAChCa,EAAe,KAAKC,CAAS,EACzB,MAAM,QAAQ3B,CAAG,EAAGA,EAAI,QAASkC,GAAS,UAAQA,CAAC,CAAC,EAChD,UAAQlC,CAAG,CACrB,OAAQmC,EAAN,CACAxB,EAAI,sBAAuBgB,CAAS,CACtC,CACG,UAAQd,CAAM,CACnB,CACA,IAAMuB,EAAU,MAAMZ,EAAa,4BAA4B,EAC/DA,EAAa,oBAAoB,EACjCb,EAAI,uBAAwBe,CAAc,EAC1Cf,EAAI,wBAAyByB,EAAQ,MAAM,EACxC,MAAI,EAAE,IAAI,sBAAuB,EAAK,EACzC,IAAMC,EAAmB,SAAO,EAAE,MAAM,WACnCA,EAAgBZ,EAAmB,GAAGd,EAAI,eAAgB0B,EAAgBZ,CAAe,CAChG,CAOA,eAAsBa,GAAO1C,EAAiB2C,EAA2D,CACvG,IAAMC,EAAKC,EAAI,EAGf,OAFA7C,EAAS,MAAQ,SACb2C,IAAY3C,EAAS,OAAS8C,EAAU9C,EAAS,OAAQ2C,CAAU,GACnE,CAAC3C,EAAS,OAAO,QAAUA,EAAS,OAAO,OAAO,SAAW,GAAKA,EAAS,OAAO,SAAW,OACxF,CAAE,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,QAAS,CAAC,EAAG,OAAQ,CAAC,EAAG,YAAaA,EAAS,YAAa,UAAW6C,EAAI,EAAG,QAAS,CAAC,EAAG,MAAO,IAAK,EAEzI,IAAI,QAAQ,MAAOnC,GAAY,CACpC,MAAMe,GAAWzB,EAAS,MAAM,EAChC,IAAMI,EAAM,MAAMoB,GAAaxB,CAAQ,EACjC+C,EAAKF,EAAI,EACX7C,EAAS,OAAO,OAAOe,EAAI,SAAUf,EAAS,OAAO,OAAQ,KAAK,MAAM+C,EAAKH,CAAE,EAAG,IAAI,EAC1F5C,EAAS,KAAK,QAAQ,EACtBU,EAAQN,CAAG,CACb,CAAC,CACH,CCxKA,IAAA4C,GAAAC,GAAAC,GAAAC,GAsDaC,GAAN,KAAY,CAuEjB,YAAYC,EAA8B,CArE1CC,EAAA,gBAKAA,EAAA,eAKAA,EAAA,eAMAA,EAAA,cAGAA,EAAA,gBAMAA,EAAA,WAGAA,EAAA,YAOAA,EAAA,aAMAA,EAAA,eAWAA,EAAA,eAEAA,EAAA,0BAEAA,EAAA,kBAEAA,EAAA,oBACAC,GAAA,KAAAP,GAAA,QACAO,GAAA,KAAAN,GAAA,QACAM,GAAA,KAAAL,GAAA,QAEAI,EAAA,WA2DAA,EAAA,eAAU,IAAIE,IAAkB,CAC9B,GAAI,CAACC,GAAA,KAAKR,IAAqB,OAC/B,IAAMS,EAAiB,KAAK,GAAG,OAAO,EAAE,MAAM,WACxCC,EAAkBF,GAAA,KAAKT,IAC7BY,GAAA,KAAKZ,GAAcU,GACnB,IAAMG,EAASH,EAAiBC,EAC5BE,IAAW,GAAGC,EAAI,GAAGN,EAAKK,CAAM,CACtC,GAGAN,GAAA,KAAAJ,GAAWY,GAAgC,CACzC,GAAI,CAACN,GAAA,KAAKP,IAAc,OAAO,KAC/B,GAAI,CAACa,EAAO,MAAO,uBACnB,GAAI,KAAK,IAAI,MAAQ,EAAEA,aAAoBC,IAAS,MAAO,yBAC3D,GAAI,CACF,KAAK,GAAG,WAAW,CACrB,OAAQC,EAAN,CACA,MAAO,oBACT,CACA,OAAO,IACT,GAeAX,EAAA,KAAO,aAAmBY,IAE1BZ,EAAA,KAAO,WAAiBa,IAExBb,EAAA,KAAO,QAAcc,IAoGrBd,EAAA,YAAQe,GAAkB,CA7T5B,IAAAC,EA8TQ,KAAK,QAAU,KAAK,OAAO,iBAAeA,EAAA,KAAK,SAAL,MAAAA,EAAa,cAAc,IAAI,MAAMD,CAAK,GAC1F,GA/TF,IAAAC,EA8HI,KAAK,IAAMC,EAMX,IAAMC,KAAaF,EAAGG,KAAH,YAAAH,EAAY,OAAW,gBAAc,QAAQ,QAAS,EAAE,EAC3EI,GAAS,SAAW,8DAA8DF,UAClFE,GAAS,cAAgBH,EAAI,QAAU,aAAe,iBACtDG,GAAS,QAAUH,EAAI,QAAU,UAAY,aAC7C,KAAK,QAAcI,GACnB,OAAO,eAAe,KAAM,UAAW,CAAE,MAAWA,EAAQ,CAAC,EAC7D,KAAK,OAAS,KAAK,MAAM,KAAK,UAAUD,EAAQ,CAAC,EACjD,OAAO,KAAK,KAAK,MAAM,EACvB,KAAK,OAAO,YAAc,OAAO,WAAc,YAC3CrB,IAAY,KAAK,OAASuB,EAAU,KAAK,OAAQvB,CAAU,GAC/DwB,GAAoB,KAAK,MAAM,EAC/B,KAAK,GAAKC,EACV,KAAK,MAAQ,OACblB,GAAA,KAAKZ,GAAc,GACnBY,GAAA,KAAKX,GAAsB,IAC3BW,GAAA,KAAKV,GAAe,IACpB,KAAK,YAAc,CAAC,EACpB,KAAK,OAAU,OAAO,aAAgB,YAAe,IAAI,YAAgB,OAEzE,KAAK,OAAS,IAAW6B,GAEzB,KAAK,KAAO,CACV,QAAcC,GACd,OAAQ,CAACjB,EAAwDkB,IAA2BC,GAAOnB,EAAOkB,CAAM,EAChH,KAAM,CAACA,EAAmBE,EAAsBH,IAAwCI,GAAKH,EAAQE,EAAQH,CAAO,EACpH,KAAM,CAACC,EAAmBE,EAAsBH,IAAwCK,GAAKJ,EAAQE,EAAQH,CAAO,EACpH,KAAM,CAACC,EAAmBE,EAAsBH,IAAwCM,GAAKL,EAAQE,EAAQH,CAAO,EACpH,QAAS,CAACC,EAAmBE,EAAyBH,IAAwCO,GAAQN,EAAQE,EAAQH,CAAO,EAC7H,OAAQ,CAACC,EAAmBE,EAAwBH,IAAwCQ,GAAOP,EAAQE,EAAQH,CAAO,EAC1H,OAAQ,CAACC,EAAmBE,EAAwBH,IAAwCS,GAAOR,EAAQE,EAAQH,CAAO,EAC1H,IAAK,CAACC,EAAmBE,EAAgBH,IAAwCU,GAAIT,EAAQE,EAAQH,CAAO,CAC9G,EACA,KAAK,OAAS,CAAE,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,QAAS,CAAC,EAAG,OAAQ,CAAC,EAAG,YAAa,CAAC,EAAG,UAAW,EAAG,QAAS,CAAC,EAAG,MAAO,IAAK,EAG/H,KAAK,QAAU,CAAE,OAAQ,KAAM,OAAQ,IAAK,EAE5C,KAAK,kBAA6BW,GAClC,KAAK,UAAqBC,GAE1B,KAAK,GAAalB,EAElB,KAAK,KAAK,QAAQ,CACpB,CA0BA,OAAc,CACZ,IAAMmB,EAAiB,KAAK,OAAO,QACnC,KAAK,OAAS,KAAK,MAAM,KAAK,UAAUnB,EAAQ,CAAC,EACjD,KAAK,OAAO,QAAUmB,CACxB,CAGA,SAASxC,EAA8B,CACrC,OAAOyC,GAASpB,GAAUrB,GAAc,KAAK,MAAM,CACrD,CAUA,KAAc,CACZ,OAAO0C,EAAI,CACb,CAQA,MAAMhC,EAAciC,EAAqB,GAAM,CAC7C,OAAaC,GAAQlC,EAAO,KAAK,OAAQiC,CAAS,CACpD,CAYA,MAAM,aAAajC,EAAcmC,EAA6G,CAC5I,OAAoBD,GAAQlC,EAAOmC,EAAY,KAAK,MAAM,CAC5D,CAQA,QAAQnC,EAA8B,CACpC,OAAeoC,GAAQpC,CAAK,CAC9B,CASA,QAAQqC,EAA0BC,EAA4C,CAC5E,OAAaC,GAAQ,KAAK,OAAQF,EAAkBC,CAAiB,CACvE,CAOA,MAAM,MAAsB,CAC1B,MAAcE,GAAM,KAAM,EAAI,EAC9B,MAAM,KAAK,GAAG,MAAM,CACtB,CAOA,MAAM,KAAKlD,EAA6C,CACtD,KAAK,MAAQ,OACb,IAAMmD,EAAYT,EAAI,EAChBU,EAAQ,OAAO,OAAO,KAAK,MAAM,EAAE,OAAQC,GAAUA,CAAK,EAAE,OAC9DrD,IAAY,KAAK,OAASuB,EAAU,KAAK,OAAQvB,CAAU,GAE3D,KAAK,IAAI,UACP,KAAK,OAAO,OAAOS,EAAI,YAAY,KAAK,SAAS,EACjD,KAAK,OAAO,OAAOA,EAAI,iBAAiB,KAAK,GAAG,QAAQ,cAAc,EACrE,MAAcyC,GAAM,IAAI,GAAGzC,EAAI,6BAA6B,EACjE,MAAS,QAAM,EACX,KAAK,IAAI,UACP,KAAK,OAAO,OAAOA,EAAI,iBAAkB,KAAK,MAAM,EACpD,KAAK,OAAO,OAAOA,EAAI,eAAgB,KAAK,GAAG,EAC/C,KAAK,OAAO,OAAOA,EAAI,YAAa,KAAK,GAAG,IAAI,KAAQ,IAIhE,MAAa6C,GAAK,IAAI,EAClB,KAAK,IAAI,SAAW,KAAK,OAAO,OAAO7C,EAAI,mBAAoB,KAAK,GAAG,OAAO,EAAE,MAAM,SAAU,QAAS,KAAK,GAAG,OAAO,EAAE,MAAM,WAAY,SAAS,EACzJ,KAAK,IAAI,QAAU,GAEJ,OAAO,OAAO,KAAK,MAAM,EAAE,OAAQ4C,GAAUA,CAAK,EAAE,SACpDD,IACb,MAAaX,GAAS,IAAI,EAC1B,KAAK,KAAK,MAAM,GAGlB,IAAMc,EAAU,KAAK,MAAMb,EAAI,EAAIS,CAAS,EACxCI,GAAW,KAAK,YAAY,YAAwB,KAAI,KAAK,YAAY,WAAa,KAAK,IAAI,SAAW,KAAK,YAAY,YAAc,GAAKA,EAAUA,EAC9J,CAaA,KAAKzB,EAAiB,KAAK,OAAgB,CACzC,OAAmB0B,GAAK1B,EAAQ,KAAK,MAAM,CAC7C,CAGA,eAA4B,CAAE,OAAc2B,GAAc,IAAI,CAAG,CAQjE,MAAM,OAAOzD,EAA8B,CACzC,IAAM0D,EAAKhB,EAAI,EACTiB,EAAM,MAAcC,GAAO,KAAM5D,CAAU,EAC3C6D,EAAKnB,EAAI,EACf,YAAK,YAAY,OAAS,KAAK,MAAMmB,EAAKH,CAAE,EACrCC,CACT,CAMA,MAAM,QAAQjD,EAAcV,EAA8F,CACxH,IAAM8D,EAAU,MAAM,KAAK,GAAG,QAAQ,IAAM,KAAK,OAAOpD,EAAOV,CAAU,CAAC,EACpE+D,EAAkC,CAAC,EACrCC,EAAQ,EACZ,QAAWC,KAAUH,EAAQ,QACvBC,EAAQE,EAAO,MAAOF,EAAQE,EAAO,OAASA,EAAO,aACpDF,EAAQE,EAAO,MAAQA,EAAO,aACnCD,GAASC,EAAO,aAElB,IAAMC,EAAmE,CAAC,EAC1E,OAAO,QAAQH,CAAO,EAAE,QAASI,GAAQD,EAAU,KAAK,CAAE,OAAQC,EAAI,GAAI,KAAMA,EAAI,GAAyB,KAAM,CAAE,CAAC,CAAC,EACvH,QAAWF,KAAUC,EACnBD,EAAO,KAAO,KAAK,MAAM,IAAOA,EAAO,KAAOD,CAAK,EAAI,IACvDC,EAAO,KAAO,KAAK,MAAM,IAAOA,EAAO,IAAI,EAAI,IAEjD,OAAAC,EAAU,KAAK,CAACE,EAAGC,IAAMA,EAAE,KAAOD,EAAE,IAAI,EACxCF,EAAU,OAAS,GAGZA,CACT,CAYA,MAAM,OAAOxD,EAAcV,EAA+C,CAExE,YAAK,MAAQ,SACN,IAAI,QAAQ,MAAOsE,GAAY,CAnY1C,IAAArD,EAAAsD,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,EAAAC,GAAAC,EAAAC,GAAAC,GAAAC,EAAAC,GAAAC,EAAAC,EAAAC,EAoYM,KAAK,MAAQ,SACb,IAAIxC,EAGJ,KAAK,OAAS5B,EAAU,KAAK,OAAQvB,CAAU,EAG/C,KAAK,MAAQ,QACb,IAAM4F,EAAQxF,GAAA,KAAKN,IAAL,UAAaY,GACvBkF,IACFnF,EAAImF,EAAOlF,CAAK,EAChB,KAAK,KAAK,OAAO,EACjB4D,EAAQ,CAAE,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,QAAS,CAAC,EAAG,OAAQ,CAAC,EAAG,YAAa,KAAK,YAAa,UAAW5B,EAAI,EAAG,QAAS,CAAC,EAAG,MAAAkD,CAAM,CAAC,GAGxI,IAAMC,EAAYnD,EAAI,EAGtB,MAAcQ,GAAM,IAAI,EAGxB,MAAM,KAAK,KAAK,EAEhBC,EAAYT,EAAI,EAChB,KAAK,MAAQ,QACb,IAAMoD,EAAM,MAAYlD,GAAQlC,EAAO,KAAK,MAAM,EAKlD,GAJA,KAAK,QAAUoF,EACf,KAAK,YAAY,aAAe,KAAK,IAAI,SAAW,KAAK,YAAY,cAAgB,GAAK,KAAK,MAAMpD,EAAI,EAAIS,CAAS,EAAI,KAAK,MAAMT,EAAI,EAAIS,CAAS,EACtJ,KAAK,QAAQ,YAAY,EAErB,CAAC2C,EAAI,OAAQ,CACX,KAAK,OAAO,OAAOrF,EAAI,mCAAmC,EAC9D,KAAK,KAAK,OAAO,EACjB6D,EAAQ,CAAE,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,KAAM,CAAC,EAAG,QAAS,CAAC,EAAG,OAAQ,CAAC,EAAG,YAAa,KAAK,YAAa,UAAW5B,EAAI,EAAG,QAAS,CAAC,EAAG,MAAO,mCAAoC,CAAC,EAC3K,MACF,CACA,KAAK,KAAK,OAAO,EAEjBS,EAAYT,EAAI,EAChB,KAAK,OAAO,YAAc,MAAYqD,GAAK,KAAK,OAAQD,EAAI,MAAM,EAC7D,KAAK,YAAY,cAAa,KAAK,YAAY,YAAc,GAC7D,KAAK,YAAY,eAAc,KAAK,YAAY,aAAe,GACnE,KAAK,YAAY,cACd,KAAK,OAAO,aAAa,KAAK,YAAY,eAC9C,KAAK,YAAY,WAAa,KAAK,IAAI,SAAW,KAAK,YAAY,YAAc,GAAK,KAAK,MAAMpD,EAAI,EAAIS,CAAS,EAAI,KAAK,MAAMT,EAAI,EAAIS,CAAS,EAClJ,KAAK,QAAQ,gBAAgB,EAI7B,IAAI6C,EAA0D,CAAC,EAC3DC,EAA0D,CAAC,EAC3DC,EAA0D,CAAC,EAC3DC,EAAgE,CAAC,EAGrE,KAAK,MAAQ,cACT,KAAK,OAAO,OACdH,EAAU,KAAK,OAAO,KAAK,QAAeI,GAAW,KAAMN,EAAI,MAAM,EAAI,CAAC,EACtE,KAAK,YAAY,MAAM,OAAO,KAAK,YAAY,OAEnD3C,EAAYT,EAAI,EAChBsD,EAAU,KAAK,OAAO,KAAK,QAAU,MAAWI,GAAW,KAAMN,EAAI,MAAM,EAAI,CAAC,EAChF,KAAK,YAAY,KAAO,KAAK,IAAI,SAAW,KAAK,YAAY,MAAQ,GAAK,KAAK,MAAMpD,EAAI,EAAIS,CAAS,EAAI,KAAK,MAAMT,EAAI,EAAIS,CAAS,GAGpI,KAAK,OAAO,QAAU,KAAK,OAAO,KAAK,cAAgB,IAAM,KAAK,OAAO,KAAK,cAAgB,MAAK6C,EAAU,MAAMA,GAGvH,KAAK,QAAQ,aAAa,EAC1B,KAAK,MAAQ,cACb,IAAMK,EAAa,KAAK,OAAO,KAAK,cAAgB,GAAK9E,EAAU,KAAK,OAAQ,CAAE,KAAM,CAAE,YAAa,KAAK,OAAO,KAAK,QAAU,EAAKyE,EAAyB,OAAS,CAAE,CAAE,CAAC,EAAI,KAAK,OACnL,KAAK,OAAO,QACV/E,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,WAAYgF,EAAU,KAAK,OAAO,KAAK,QAAkBK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GAC5H9B,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,aAAc0B,EAAU,KAAK,OAAO,KAAK,QAAoBK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GACrI7B,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,iBAAkByB,EAAU,KAAK,OAAO,KAAK,QAAwBK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GAC7I5B,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,aAAYwB,EAAU,KAAK,OAAO,KAAK,QAAkBK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GACtI,KAAK,YAAY,MAAM,OAAO,KAAK,YAAY,OAEnDlD,EAAYT,EAAI,GACZgC,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,WAAYuB,EAAU,KAAK,OAAO,KAAK,QAAU,MAAcK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GAClI1B,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,aAAcsB,EAAU,KAAK,OAAO,KAAK,QAAU,MAAgBK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GAC3IzB,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,iBAAkBqB,EAAU,KAAK,OAAO,KAAK,QAAU,MAAoBK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GACnJxB,EAAA,KAAK,OAAO,KAAK,YAAjB,MAAAA,EAA4B,SAAS,aAAYoB,EAAU,KAAK,OAAO,KAAK,QAAU,MAAcK,GAAQR,EAAI,OAAQO,CAAU,EAAI,CAAC,GAChJ,KAAK,YAAY,KAAO,KAAK,IAAI,SAAW,KAAK,YAAY,MAAQ,GAAK,KAAK,MAAM3D,EAAI,EAAIS,CAAS,EAAI,KAAK,MAAMT,EAAI,EAAIS,CAAS,GAExI,KAAK,QAAQ,WAAW,EAGxB,KAAK,QAAQ,aAAa,EAC1B,KAAK,MAAQ,cACb,IAAMoD,EAAa,KAAK,OAAO,KAAK,cAAgB,GAAKhF,EAAU,KAAK,OAAQ,CAAE,KAAM,CAAE,YAAa,KAAK,OAAO,KAAK,QAAU,EAAKyE,EAAyB,OAAS,CAAE,CAAE,CAAC,EAAI,KAAK,OACnL,KAAK,OAAO,QACVjB,GAAAD,EAAA,KAAK,OAAO,KAAK,WAAjB,YAAAA,EAA2B,YAA3B,MAAAC,EAAsC,SAAS,cAAemB,EAAU,KAAK,OAAO,KAAK,QAAmBI,GAAQR,EAAI,OAAQS,CAAU,EAAI,CAAC,GAC1ItB,GAAAD,EAAA,KAAK,OAAO,KAAK,WAAjB,YAAAA,EAA2B,YAA3B,MAAAC,EAAsC,SAAS,eAAciB,EAAU,KAAK,OAAO,KAAK,QAAoBI,GAAQR,EAAI,OAAQS,CAAU,EAAI,CAAC,GACpJ,KAAK,YAAY,MAAM,OAAO,KAAK,YAAY,OAEnDpD,EAAYT,EAAI,GACZyC,IAAAD,EAAA,KAAK,OAAO,KAAK,WAAjB,YAAAA,EAA2B,YAA3B,MAAAC,GAAsC,SAAS,cAAee,EAAU,KAAK,OAAO,KAAK,QAAU,MAAeI,GAAQR,EAAI,OAAQS,CAAU,EAAI,CAAC,GAChJlB,IAAAD,EAAA,KAAK,OAAO,KAAK,WAAjB,YAAAA,EAA2B,YAA3B,MAAAC,GAAsC,SAAS,eAAca,EAAU,KAAK,OAAO,KAAK,QAAU,MAAgBI,GAAQR,EAAI,OAAQS,CAAU,EAAI,CAAC,GAC9J,KAAK,YAAY,KAAO,KAAK,IAAI,SAAW,KAAK,YAAY,MAAQ,GAAK,KAAK,MAAM7D,EAAI,EAAIS,CAAS,EAAI,KAAK,MAAMT,EAAI,EAAIS,CAAS,GAExI,KAAK,QAAQ,WAAW,EAGxB,KAAK,QAAQ,eAAe,EAC5B,KAAK,MAAQ,gBACT,KAAK,OAAO,QACVmC,GAAA,KAAK,OAAO,OAAO,YAAnB,MAAAA,GAA8B,SAAS,WAAYa,EAAY,KAAK,OAAO,OAAO,QAAkBG,GAAQR,EAAI,OAAQ,KAAK,MAAM,EAAI,CAAC,GACnIP,EAAA,KAAK,OAAO,OAAO,YAAnB,MAAAA,EAA8B,SAAS,eAAcY,EAAY,KAAK,OAAO,OAAO,QAAoBG,GAAQR,EAAI,OAAQ,KAAK,MAAM,EAAI,CAAC,GACjJ,KAAK,YAAY,QAAQ,OAAO,KAAK,YAAY,SAErD3C,EAAYT,EAAI,GACZ8C,GAAA,KAAK,OAAO,OAAO,YAAnB,MAAAA,GAA8B,SAAS,WAAYW,EAAY,KAAK,OAAO,OAAO,QAAU,MAAcG,GAAQR,EAAI,OAAQ,KAAK,MAAM,EAAI,CAAC,GACzIL,EAAA,KAAK,OAAO,OAAO,YAAnB,MAAAA,EAA8B,SAAS,eAAcU,EAAY,KAAK,OAAO,OAAO,QAAU,MAAgBG,GAAQR,EAAI,OAAQ,KAAK,MAAM,EAAI,CAAC,GAC3J,KAAK,YAAY,OAAS,KAAK,IAAI,SAAW,KAAK,YAAY,QAAU,GAAK,KAAK,MAAMpD,EAAI,EAAIS,CAAS,EAAI,KAAK,MAAMT,EAAI,EAAIS,CAAS,GAE5I,KAAK,QAAQ,aAAa,EAG1B,KAAK,MAAQ,eACT,KAAK,OAAO,QAAO,CAAC6C,EAASC,EAASC,EAASC,CAAS,EAAI,MAAM,QAAQ,IAAI,CAACH,EAASC,EAASC,EAASC,CAAS,CAAC,GAGxH,KAAK,MAAQ,iBACb,IAAIK,EAA8B,CAAC,EAC/B,KAAK,OAAO,QAAQ,UACtBrD,EAAYT,EAAI,EAChB8D,EAAa,CAAC,GAAWzE,GAAKiE,CAAuB,EAAG,GAAWhE,GAAKiE,CAAuB,EAAG,GAAWhE,GAAKiE,CAAuB,EAAG,GAAWO,GAAKT,CAAuB,CAAC,EAC/K,KAAK,OAAO,MACR,KAAK,YAAY,SAAS,OAAO,KAAK,YAAY,QADnC,KAAK,YAAY,QAAU,KAAK,IAAI,SAAW,KAAK,YAAY,SAAW,GAAK,KAAK,MAAMtD,EAAI,EAAIS,CAAS,EAAI,KAAK,MAAMT,EAAI,EAAIS,CAAS,GAItK,KAAK,YAAY,MAAQ,KAAK,IAAI,SAAW,KAAK,YAAY,OAAS,GAAK,KAAK,MAAMT,EAAI,EAAImD,CAAS,EAAI,KAAK,MAAMnD,EAAI,EAAImD,CAAS,EACxI,IAAMa,IAAQf,GAAAD,EAAA,KAAK,UAAL,YAAAA,EAAc,SAAd,YAAAC,EAAsB,QAAS,CAAC,EAC9C,KAAK,OAAS,CACZ,KAAMK,EACN,KAAMC,EACN,KAAMC,EACN,QAASM,EACT,OAAQL,EACR,YAAa,KAAK,YAClB,OAAQ,KAAK,QAAQ,OACrB,UAAW,KAAK,IAAI,EACpB,MAAO,KACP,IAAI,SAAU,CAAE,OAAeQ,GAAKX,EAAyBC,EAAyBC,EAAyBM,EAAYE,CAAK,CAAG,CACrI,EAGG,UAAQZ,EAAI,MAAM,EAGrB,KAAK,KAAK,QAAQ,EAClB,KAAK,MAAQ,OACbxB,EAAQ,KAAK,MAAM,CACrB,CAAC,CACH,CACF,EA7aE3E,GAAA,YACAC,GAAA,YACAC,GAAA,YAuEAC,GAAA",
+  "names": ["log", "msg", "dt", "ts", "join", "folder", "file", "separator", "path", "now", "validate", "defaults", "config", "parent", "msgs", "key", "defined", "same", "mergeDeep", "objects", "isObject", "obj", "prev", "pVal", "oVal", "config", "tfjs_esm_exports", "__export", "b", "d", "v", "__reExport", "dist_star", "r", "e", "o", "a", "t", "s", "f", "vertexIdentity", "colorMatrixWithAlpha", "colorMatrixWithoutAlpha", "pixelate", "blur", "convolution", "collect", "source", "prefix", "collection", "r", "match", "name", "GLProgram", "gl", "vertexSource", "fragmentSource", "__publicField", "type", "shader", "log", "vertexShader", "fragmentShader", "u", "GLImageFilter", "drawCount", "sourceTexture", "lastInChain", "currentFramebufferIndex", "tempFramebuffers", "filterChain", "vertexBuffer", "currentProgram", "fxcanvas", "canvas", "shaderProgramCache", "DRAW", "resize", "width", "height", "vertices", "createFramebufferTexture", "fbo", "renderbuffer", "texture", "getTempFramebuffer", "index", "draw", "flags", "target", "flipY", "compileShader", "vertexIdentity", "floatSize", "vertSize", "filter", "matrix", "m", "colorMatrixWithoutAlpha", "colorMatrixWithAlpha", "program", "brightness", "b", "amount", "x", "y", "v", "o", "rotation", "cos", "sin", "lumR", "lumG", "lumB", "pixelSizeX", "pixelSizeY", "convolution", "a", "size", "s", "blurSizeX", "blurSizeY", "blur", "pixelate", "args", "func", "image", "i", "f", "histogramEqualization", "inputImage", "squeeze", "channels", "min", "max", "absMax", "channel", "maxValue", "sub", "range", "fact", "enh", "rgb", "reshape", "maxSize", "inCanvas", "outCanvas", "tmpCanvas", "fx", "last", "canvas", "width", "height", "c", "env", "copy", "input", "output", "outputCanvas", "process", "config", "getTensor", "log", "d", "tensor", "rgb", "cast", "originalWidth", "originalHeight", "targetWidth", "targetHeight", "inCtx", "GLImageFilter", "pixels", "depth", "arr", "tempData", "casted", "histogramEqualization", "skip", "skipFrame", "t", "diffRelative", "compare", "input1", "input2", "Env", "__publicField", "v", "raw", "platformMatch", "c", "canvas", "ctx", "gl", "e", "kernel", "cpu", "env", "options", "modelStats", "httpHandler", "url", "init", "log", "setModelLoadOptions", "config", "loadModel", "modelPath", "_a", "_b", "_c", "modelUrl", "join", "modelPathSegments", "shortModelName", "cachedModelName", "models_exports", "cachedModels", "e", "tfLoadOptions", "model", "b", "loaded", "artifacts", "err", "saveResult", "models_exports", "__export", "Models", "getModelStats", "load", "reset", "validate", "model", "last", "raceNames", "ageWeights", "lastCount", "lastTime", "skipped", "load", "config", "_a", "env", "log", "loadModel", "predict", "image", "idx", "count", "_b", "skipFrame", "skipTime", "now", "resolve", "t", "box", "obj", "gender", "race", "i", "a", "b", "ageSorted", "age", "tensor", "constants", "init", "model", "last", "lastCount", "lastTime", "skipped", "load", "config", "env", "log", "loadModel", "predict", "image", "idx", "count", "_a", "_b", "_c", "_d", "skipFrame", "skipTime", "now", "resolve", "t", "constants", "obj", "data", "tensor", "model", "last", "lastCount", "lastTime", "skipped", "rgb", "load", "config", "env", "log", "loadModel", "predict", "image", "idx", "count", "_a", "_b", "_c", "_d", "skipFrame", "skipTime", "now", "resolve", "t", "red", "green", "blue", "redNorm", "greenNorm", "blueNorm", "grayscale", "constants", "obj", "data", "tensor", "model", "cached", "skipped", "lastCount", "lastTime", "load", "config", "_a", "env", "log", "loadModel", "predict", "image", "idx", "count", "_b", "skipTime", "now", "skipFrame", "resolve", "resize", "res", "num", "meshAnnotations", "meshLandmarks", "blazeFaceLandmarks", "irisIndices", "UV468", "TRI468", "VTX68", "VTX33", "VTX7", "UV68", "x", "UV468", "UV33", "UV7", "connectionsToIndices", "connections", "indices", "connection", "pairsLips", "pairsLeftEye", "pairsLeftEyebrow", "pairsLeftIris", "pairsRightEye", "pairsRightEyebrow", "pairsRightIris", "pairsFaceContour", "contourKeypoints", "getBoxSize", "box", "getBoxCenter", "clampBox", "input", "getRawBox", "scaleBoxCoordinates", "factor", "startPoint", "endPoint", "cutAndResize", "image", "cropSize", "h", "w", "cutBox", "crop", "norm", "constants", "enlargeBox", "center", "size", "halfSize", "squarifyBox", "centers", "calculateLandmarksBoundingBox", "landmarks", "x", "d", "y", "fixedRotationMatrix", "normalizeRadians", "angle", "computeRotation", "point1", "point2", "buildTranslationMatrix", "x", "y", "dot", "v1", "v2", "product", "i", "getColumnFrom2DArr", "arr", "columnIndex", "column", "multiplyTransformMatrices", "mat1", "mat2", "size", "row", "col", "buildRotationMatrix", "rotation", "center", "cosA", "sinA", "rotationMatrix", "translationMatrix", "translationTimesRotation", "negativeTranslationMatrix", "invertTransformMatrix", "matrix", "rotationComponent", "translationComponent", "invertedTranslation", "rotatePoint", "homogeneousCoordinate", "generateAnchors", "inputSize", "spec", "anchors", "i", "stride", "gridRows", "gridCols", "anchorsNum", "gridY", "anchorY", "gridX", "anchorX", "n", "transformRawCoords", "coordsRaw", "box", "angle", "rotationMatrix", "boxSize", "getBoxSize", "coordsScaled", "coord", "largeAngle", "coordsRotationMatrix", "buildRotationMatrix", "fixedRotationMatrix", "coordsRotated", "rotatePoint", "inverseRotationMatrix", "invertTransformMatrix", "boxCenter", "getBoxCenter", "offsets", "dot", "correctFaceRotation", "rotate", "input", "symmetryLine", "meshLandmarks", "blazeFaceLandmarks", "face", "env", "computeRotation", "center", "centerRaw", "rotated", "cutAndResize", "findFaceCenter", "mesh", "x", "m", "y", "calculateFaceBox", "previousBox", "keypointsCount", "faceBoxScaleFactor", "model", "anchors", "inputSize", "inputSizeT", "size", "load", "config", "_a", "env", "log", "loadModel", "generateAnchors", "decodeBoxes", "boxOutputs", "constants", "boxes", "tensor", "getBoxes", "inputImage", "_b", "_c", "_d", "t", "res", "sorted", "a", "b", "nms", "scores", "i", "confidence", "points", "rawBox", "scaledBox", "scaleBoxCoordinates", "enlargedBox", "enlargeBox", "squaredBox", "squarifyBox", "blazeposecoords_exports", "__export", "connected", "kpt", "inputSize", "anchorTensor", "numLayers", "strides", "createAnchors", "anchors", "layerId", "anchorCount", "lastSameStrideLayer", "stride", "featureMapHeight", "featureMapWidth", "y", "x", "anchorId", "a", "calc", "keypoints", "outputSize", "coords", "pt", "min", "max", "box", "boxRaw", "square", "center", "dist", "scale", "scaleFact", "env", "models", "inputSize", "skipped", "outputNodes", "cache", "cropBox", "padding", "lastTime", "sigmoid", "x", "loadDetect", "config", "loadModel", "inputs", "log", "createAnchors", "loadPose", "prepareImage", "input", "size", "t", "final", "cropBox", "height", "width", "padding", "constants", "tensor", "rescaleKeypoints", "keypoints", "outputSize", "kpt", "fixKeypoints", "leftPalm", "k", "leftWrist", "leftIndex", "rightPalm", "rightWrist", "rightIndex", "detectLandmarks", "config", "_a", "models", "outputNodes", "poseScore", "points", "distances", "keypointsRelative", "depth", "i", "score", "sigmoid", "presence", "adjScore", "positionRaw", "inputSize", "position", "distance", "kpts", "boxes", "calc", "annotations", "name", "indexes", "connected", "pt", "pt0", "pt1", "predict", "skipTime", "now", "lastTime", "skipFrame", "skipped", "cache", "labels", "model", "inputSize", "last", "lastTime", "skipped", "load", "config", "env", "log", "loadModel", "inputs", "process", "res", "outputShape", "t", "results", "detections", "arr", "nms", "i", "id", "score", "classVal", "label", "labels", "x", "y", "boxRaw", "box", "tensor", "predict", "input", "skipTime", "now", "skipFrame", "resolve", "outputSize", "resize", "objectT", "obj", "efficientposecoords_exports", "__export", "connected", "kpt", "model", "lastTime", "cache", "skipped", "load", "config", "env", "log", "loadModel", "max2d", "inputs", "minScore", "width", "height", "reshaped", "max", "newScore", "coordinates", "mod", "x", "div", "predict", "image", "skipTime", "now", "skipFrame", "resolve", "_a", "tensor", "resize", "enhance", "constants", "resT", "squeeze", "stack", "id", "y", "partScore", "kpt", "s", "prev", "curr", "a", "xRaw", "yRaw", "name", "indexes", "connected", "pt", "i", "pt0", "pt1", "annotations", "model", "last", "lastCount", "lastTime", "skipped", "load", "config", "_a", "env", "log", "loadModel", "predict", "image", "idx", "count", "_b", "skipFrame", "skipTime", "now", "resolve", "obj", "t", "inputSize", "constants", "data", "i", "a", "b", "tensor", "model", "last", "lastCount", "lastTime", "skipped", "load", "config", "env", "log", "loadModel", "predict", "input", "idx", "count", "_a", "_b", "skipFrame", "skipTime", "now", "resolve", "data", "t", "output", "model", "inputSize", "irisEnlarge", "leftOutline", "meshAnnotations", "rightOutline", "eyeLandmarks", "irisLandmarks", "load", "config", "_a", "env", "log", "loadModel", "replaceIrisCoords", "rawCoords", "newCoords", "prefix", "keys", "i", "irisIndices", "key", "indices", "originalIndices", "j", "index", "getLeftToRightEyeDepthDifference", "leftEyeZ", "rightEyeZ", "getEyeBox", "face", "eyeInnerCornerIndex", "eyeOuterCornerIndex", "meshSize", "flip", "box", "squarifyBox", "enlargeBox", "calculateLandmarksBoundingBox", "boxSize", "getBoxSize", "crop", "flipped", "getEyeCoords", "eyeData", "eyeBox", "eyeBoxSize", "eyeRawCoords", "x", "y", "z", "getAdjustedIrisCoords", "irisCoords", "direction", "upperCenterZ", "lowerCenterZ", "averageZ", "coord", "augmentIris", "leftEyeBox", "leftEyeBoxSize", "leftEyeCrop", "rightEyeBox", "rightEyeBoxSize", "rightEyeCrop", "combined", "eyePredictions", "eyePredictionsData", "leftEyeData", "leftEyeRawCoords", "leftIrisRawCoords", "rightEyeData", "rightEyeRawCoords", "rightIrisRawCoords", "leftToRightEyeDepthDifference", "adjustedLeftIrisCoords", "adjustedRightIrisCoords", "LIPS_CONNECTIONS", "LEFT_EYE_CONNECTIONS", "LEFT_EYEBROW_CONNECTIONS", "LEFT_IRIS_CONNECTIONS", "RIGHT_EYE_CONNECTIONS", "RIGHT_EYEBROW_CONNECTIONS", "RIGHT_IRIS_CONNECTIONS", "FACE_OVAL_CONNECTIONS", "connectionsToIndices", "connections", "indices", "connection", "MEDIAPIPE_FACE_MESH_KEYPOINTS_BY_CONTOUR", "LIPS_CONNECTIONS", "LEFT_EYE_CONNECTIONS", "LEFT_EYEBROW_CONNECTIONS", "LEFT_IRIS_CONNECTIONS", "RIGHT_EYE_CONNECTIONS", "RIGHT_EYEBROW_CONNECTIONS", "RIGHT_IRIS_CONNECTIONS", "FACE_OVAL_CONNECTIONS", "indexLabelPairs", "label", "index", "MEDIAPIPE_FACE_MESH_KEYPOINTS", "LANDMARKS_REFINEMENT_LIPS_CONFIG", "LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG", "LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG", "augment", "rawCoords", "results", "t", "r", "irisLDepth", "LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG", "prev", "curr", "i", "irisRDepth", "LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG", "LANDMARKS_REFINEMENT_LIPS_CONFIG", "cache", "model", "inputSize", "predict", "input", "config", "_a", "_b", "_c", "_d", "_e", "_f", "_g", "_h", "_i", "_j", "_k", "skipTime", "now", "skipFrame", "getBoxes", "faces", "newCache", "id", "i", "box", "angle", "rotationMatrix", "face", "correctFaceRotation", "size", "equilized", "histogramEqualization", "log", "results", "faceConfidence", "t", "clampBox", "getRawBox", "pt", "key", "blazeFaceLandmarks", "meshT", "coordsReshaped", "rawCoords", "augment", "augmentIris", "transformRawCoords", "meshAnnotations", "index", "calculatedBox", "calculateFaceBox", "load", "env", "loadModel", "triangulation", "TRI468", "uvmap", "UV468", "model", "last", "lastTime", "lastCount", "skipped", "load", "config", "_a", "env", "log", "loadModel", "enhance", "input", "tensor", "crop", "norm", "constants", "predict", "image", "idx", "count", "_b", "_c", "_d", "skipFrame", "skipTime", "now", "resolve", "obj", "enhanced", "resT", "gender", "t", "confidence", "argmax", "age", "all", "desc", "descriptor", "getBoxSize", "box", "getBoxCenter", "cutBoxFromImageAndResize", "image", "cropSize", "h", "w", "boxes", "scaleBoxCoordinates", "factor", "startPoint", "endPoint", "palmLandmarks", "coord", "enlargeBox", "center", "size", "newHalfSize", "squarifyBox", "centers", "halfSize", "normalizeRadians", "angle", "computeRotation", "point1", "point2", "radians", "buildTranslationMatrix", "x", "y", "dot", "v1", "v2", "product", "i", "getColumnFrom2DArr", "arr", "columnIndex", "column", "multiplyTransformMatrices", "mat1", "mat2", "size", "row", "col", "buildRotationMatrix", "rotation", "center", "cosA", "sinA", "rotationMatrix", "translationMatrix", "translationTimesRotation", "negativeTranslationMatrix", "invertTransformMatrix", "matrix", "rotationComponent", "translationComponent", "invertedTranslation", "rotatePoint", "homogeneousCoordinate", "anchors", "HandDetector", "model", "__publicField", "anchors", "anchor", "boxes", "t", "res", "tensor", "rawPalmLandmarks", "index", "input", "config", "constants", "scores", "nms", "hands", "p", "box", "startPoint", "endPoint", "palmLandmarks", "hand", "scaled", "scaleBoxCoordinates", "palmBoxEnlargeFactor", "handBoxEnlargeFactor", "palmLandmarkIds", "palmLandmarksPalmBase", "palmLandmarksMiddleFingerBase", "lastTime", "HandPipeline", "handDetector", "handPoseModel", "__publicField", "landmarks", "xs", "d", "ys", "startPoint", "endPoint", "palmLandmarks", "rotationMatrix", "rotatedPalmLandmarks", "coord", "rotatePoint", "boxAroundPalm", "enlargeBox", "squarifyBox", "boundingBox", "boxAroundHand", "i", "rawCoords", "box2", "angle", "boxSize", "getBoxSize", "scaleFactor", "coordsScaled", "coordsRotationMatrix", "buildRotationMatrix", "coordsRotated", "inverseRotationMatrix", "invertTransformMatrix", "boxCenter", "getBoxCenter", "originalBoxCenter", "dot", "image", "config", "useFreshBox", "boxes", "skipTime", "now", "skipFrame", "hands", "currentBox", "computeRotation", "palmCenter", "palmCenterNormalized", "rotatedImage", "env", "newBox", "croppedInput", "cutBoxFromImageAndResize", "handImage", "constants", "confidenceT", "keypoints", "confidence", "keypointsReshaped", "coords", "nextBoundingBox", "result", "enlarged", "a", "Finger", "value", "FingerCurl", "FingerDirection", "FingerGesture", "name", "__publicField", "finger", "curl", "confidence", "position", "weight", "total", "a", "b", "el", "detectedCurls", "detectedDirections", "fingerIdx", "detectedCurl", "expectedCurls", "expectedCurl", "score", "detectedDirection", "expectedDirections", "expectedDirection", "thumb", "index", "middle", "ring", "pinky", "Finger", "none", "half", "full", "FingerCurl", "verticalUp", "verticalDown", "horizontalLeft", "horizontalRight", "diagonalUpRight", "diagonalUpLeft", "diagonalDownRight", "diagonalDownLeft", "FingerDirection", "ThumbsUp", "FingerGesture", "finger", "Victory", "Point", "MiddleFinger", "OpenPalm", "fingergesture_default", "minConfidence", "options", "calculateSlope", "point1x", "point1y", "point2x", "point2y", "value", "slope", "getSlopes", "point1", "point2", "slopeXY", "slopeYZ", "angleOrientationAt", "angle", "weightageAt", "isVertical", "isDiagonal", "isHorizontal", "estimateFingerCurl", "startPoint", "midPoint", "endPoint", "start_mid_x_dist", "start_end_x_dist", "mid_end_x_dist", "start_mid_y_dist", "start_end_y_dist", "mid_end_y_dist", "start_mid_z_dist", "start_end_z_dist", "mid_end_z_dist", "start_mid_dist", "start_end_dist", "mid_end_dist", "cos_in", "angleOfCurve", "fingerCurl", "FingerCurl", "estimateHorizontalDirection", "max_dist_x", "estimatedDirection", "FingerDirection", "estimateVerticalDirection", "max_dist_y", "estimateDiagonalDirection", "reqd_vertical_direction", "reqd_horizontal_direction", "calculateFingerDirection", "fingerSlopes", "voteVertical", "voteDiagonal", "voteHorizontal", "start_end_x_y_dist_ratio", "max_dist", "calc_start_point_x", "calc_start_point_y", "calc_end_point_x", "calc_end_point_y", "totalAngle", "votes", "fingerSlope", "fingerVotes", "estimate", "landmarks", "slopesXY", "slopesYZ", "fingerCurls", "fingerDirections", "finger", "Finger", "points", "slopeAtXY", "slopeAtYZ", "point", "slopes", "pointIndexAt", "fingerPointsAt", "fingerCurled", "fingerPosition", "analyze", "keypoints", "estimatorRes", "fingerIdx", "match", "poses", "gesture", "fingergesture_default", "confidence", "meshAnnotations", "handDetectorModel", "handPoseModel", "handPipeline", "predict", "input", "config", "predictions", "hands", "i", "annotations", "key", "index", "keypoints", "box", "boxRaw", "pt", "landmarks", "analyze", "load", "_a", "_b", "env", "loadModel", "log", "handDetector", "HandDetector", "HandPipeline", "models", "modelOutputNodes", "inputSize", "classes", "faceIndex", "boxExpandFact", "maxDetectorResolution", "detectorExpandFact", "skipped", "lastTime", "outputSize", "cache", "fingerMap", "loadDetect", "config", "_a", "env", "log", "fakeOps", "loadModel", "inputs", "loadSkeleton", "detectHands", "input", "config", "hands", "models", "t", "ratio", "height", "maxDetectorResolution", "width", "modelOutputNodes", "classScores", "faceIndex", "id", "nms", "scores", "classNum", "nmsIndex", "boxSlice", "boxYX", "boxData", "boxRaw", "scale", "detectorExpandFact", "boxFull", "outputSize", "score", "label", "classes", "hand", "tensor", "a", "b", "detectFingers", "h", "boxCrop", "inputSize", "constants", "rawScore", "coordsNorm", "kpt", "analyze", "key", "fingerMap", "index", "predict", "_a", "_b", "skipped", "skipTime", "now", "lastTime", "skipFrame", "cache", "resolve", "skipTimeExtended", "skipFrameExtended", "handBox", "oldCache", "i", "boxKpt", "square", "boxScale", "boxExpandFact", "boxScaleRaw", "bbox", "calc", "model", "cached", "skipped", "lastCount", "lastTime", "load", "config", "_a", "env", "log", "loadModel", "predict", "image", "idx", "count", "_b", "skipTime", "now", "skipFrame", "resolve", "resize", "res", "num", "movenetcoords_exports", "__export", "connected", "horizontal", "kpt", "relative", "vertical", "maxJitter", "cache", "bodyParts", "body", "pair", "horizontal", "left", "kp", "right", "tmp", "vertical", "lower", "higher", "compare", "relative", "leftTo", "rightTo", "distanceLeft", "distanceRight", "jitter", "keypoints", "i", "diff", "padInput", "input", "inputSize", "t", "final", "tensor", "rescaleBody", "outputSize", "kpt", "rescaledBoxes", "calc", "pt", "model", "inputSize", "skipped", "cache", "load", "config", "env", "log", "fakeOps", "loadModel", "parseSinglePose", "res", "image", "kpt", "keypoints", "score", "id", "positionRaw", "prev", "curr", "bodies", "newBox", "calc", "pt", "annotations", "name", "indexes", "connected", "i", "pt0", "kp", "pt1", "body", "bodyParts", "parseMultiPose", "totalScore", "a", "b", "predict", "input", "skipTime", "now", "skipFrame", "resolve", "t", "padInput", "rescaleBody", "jitter", "tensor", "model", "last", "lastTime", "skipped", "inputSize", "scaleBox", "load", "config", "env", "loadModel", "inputs", "log", "process", "res", "outputShape", "id", "results", "strideSize", "baseSize", "scoresT", "a", "labels", "featuresT", "boxIdx", "scores", "i", "j", "score", "cx", "cy", "boxOffset", "x", "y", "w", "h", "boxRaw", "box", "result", "t", "nmsBoxes", "nmsScores", "nmsIdx", "nms", "_val", "idx", "b", "predict", "image", "skipTime", "now", "skipFrame", "resolve", "outputSize", "resize", "norm", "constants", "transpose", "objectT", "obj", "partNames", "count", "partIds", "result", "jointName", "i", "connectedPartNames", "connectedPartIndices", "jointNameA", "jointNameB", "poseChain", "getBoundingBox", "keypoints", "coord", "maxX", "maxY", "minX", "minY", "x", "y", "scalePoses", "poses", "height", "width", "inputResolutionHeight", "inputResolutionWidth", "scaleY", "scaleX", "scalePose", "pose", "i", "score", "part", "position", "MaxHeap", "maxSize", "getElementValue", "__publicField", "max", "k", "j", "t", "getOffsetPoint", "keypoint", "offsets", "count", "getImageCoords", "outputStride", "heatmapY", "heatmapX", "clamp", "a", "min", "max", "squaredDistance", "y1", "x1", "y2", "x2", "dy", "dx", "addVectors", "b", "model", "poseNetOutputs", "localMaximumRadius", "outputStride", "squaredNmsRadius", "traverse", "edgeId", "sourceKeypoint", "targetId", "scores", "offsets", "displacements", "offsetRefineStep", "getDisplacement", "point", "getStridedIndexNearPoint", "height", "width", "clamp", "sourceKeypointIndices", "displacement", "targetKeypoint", "addVectors", "i", "targetKeypointIndices", "offsetPoint", "getOffsetPoint", "targetKeyPointIndices", "score", "partNames", "decodePose", "root", "displacementsFwd", "displacementsBwd", "tuples", "poseChain", "parentJoinName", "childJoinName", "partIds", "edgesFwd", "childJointId", "edgesBwd", "parentJointId", "numParts", "numEdges", "keypoints", "rootPoint", "getImageCoords", "edge", "sourceId", "scoreIsMaximumInLocalWindow", "keypointId", "heatmapY", "heatmapX", "localMaximum", "yStart", "yEnd", "yCurrent", "xStart", "xEnd", "xCurrent", "buildPartWithScoreQueue", "minConfidence", "numKeypoints", "queue", "MaxHeap", "withinRadius", "poses", "x", "y", "_a", "correspondingKeypoint", "squaredDistance", "getInstanceScore", "existingPoses", "result", "position", "decode", "maxDetected", "rootImageCoords", "a", "box", "getBoundingBox", "predict", "input", "config", "res", "resized", "normalized", "results3d", "buffers", "tensor", "t", "decoded", "scalePoses", "load", "env", "loadModel", "log", "model", "busy", "load", "config", "env", "loadModel", "log", "process", "input", "background", "_a", "_b", "inputImage", "width", "height", "t", "constants", "data", "tensor", "alphaCanvas", "canvas", "alphaCtx", "alphaData", "compositeCanvas", "compositeCtx", "compositeData", "i", "mergedCanvas", "bgImage", "ctxMerge", "Models", "__publicField", "getModelStats", "instance", "totalSizeFromManifest", "totalSizeWeights", "totalSizeLoading", "m", "modelStats", "percentageLoaded", "reset", "model", "load", "_a", "_b", "_c", "_d", "_e", "_f", "_g", "_h", "_i", "_j", "_k", "_l", "_m", "_n", "_o", "_p", "_q", "_r", "_s", "_t", "_u", "_v", "_w", "_x", "_y", "_z", "_A", "_B", "_C", "_D", "_E", "env", "loadPose", "loadDetect", "loadSkeleton", "validate", "simpleOps", "defined", "ops", "executor", "kernel", "op", "log", "missing", "config", "extensions", "gl", "register", "instance", "_a", "log", "reset", "canvas", "err", "e", "ctx", "kernelConfig", "newKernelConfig", "current", "registerCustomOps", "env", "kernelMod", "op", "check", "instance", "force", "timeStamp", "now", "log", "adapter", "adapterInfo", "register", "available", "tfjs_esm_exports", "simd", "mt", "init", "err", "gl", "fakeOps", "kernelNames", "config", "kernelName", "kernelConfig", "kernel", "draw_exports", "__export", "all", "body", "canvas", "face", "gesture", "hand", "object", "options", "person", "getCanvasContext", "input", "log", "ctx", "rad2deg", "theta", "colorDepth", "z", "opt", "rgb", "point", "x", "y", "localOptions", "rect", "width", "height", "cx", "cy", "lines", "points", "pt", "curves", "i", "xc", "yc", "arrow", "from", "to", "radius", "angle", "options", "opt", "drawLabels", "f", "ctx", "labels", "emotion", "a", "rad2deg", "i", "x", "y", "drawIrisElipse", "sizeX", "sizeY", "drawGazeSpheres", "_a", "valX", "valY", "pathV", "pathH", "drawGazeArrows", "_b", "_c", "_d", "leftGaze", "arrow", "rightGaze", "drawFacePolygons", "TRI468", "points", "index", "lines", "drawFacePoints", "point", "LANDMARKS_REFINEMENT_LIPS_CONFIG", "LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG", "LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG", "drawFaceBoxes", "rect", "face", "inCanvas", "result", "drawOptions", "mergeDeep", "options", "getCanvasContext", "body", "inCanvas", "result", "drawOptions", "_a", "localOptions", "mergeDeep", "options", "ctx", "getCanvasContext", "i", "rect", "pt", "colorDepth", "point", "part", "connected", "curves", "hand", "inCanvas", "result", "drawOptions", "localOptions", "mergeDeep", "options", "ctx", "getCanvasContext", "h", "rect", "pt", "colorDepth", "point", "addHandLabel", "part", "title", "z", "addHandLine", "i", "object", "inCanvas", "result", "drawOptions", "localOptions", "mergeDeep", "options", "ctx", "getCanvasContext", "h", "rect", "label", "gesture", "inCanvas", "result", "drawOptions", "localOptions", "mergeDeep", "options", "ctx", "getCanvasContext", "i", "j", "where", "what", "who", "label", "drawTime", "person", "inCanvas", "result", "drawOptions", "localOptions", "mergeDeep", "options", "ctx", "getCanvasContext", "i", "rect", "label", "canvas", "input", "output", "all", "timeStamp", "now", "promise", "face", "body", "hand", "object", "gesture", "env", "expandFact", "alpha", "insidePoly", "x", "y", "polygon", "inside", "j", "i", "mask", "face", "width", "height", "buffer", "silhouette", "pt", "meshAnnotations", "output", "calculateGaze", "face", "radians", "pt1", "pt2", "offsetIris", "eyeRatio", "left", "irisCenter", "eyeCenter", "eyeSize", "eyeDiff", "strength", "calculateFaceAngle", "imageSize", "normalize", "v", "length", "subVectors", "a", "b", "x", "y", "z", "crossVectors", "rotationMatrixToEulerAngle", "r", "r00", "_r01", "_r02", "r10", "r11", "r12", "r20", "r21", "r22", "thetaX", "thetaY", "thetaZ", "mesh", "size", "pts", "pt", "y_axis", "x_axis", "z_axis", "matrix", "angle", "gaze", "detectFace", "instance", "input", "_a", "_b", "_c", "_d", "_e", "_f", "_g", "_h", "_i", "_j", "_k", "_l", "_m", "_n", "_o", "_p", "_q", "_r", "_s", "_t", "_u", "_v", "timeStamp", "now", "ageRes", "gearRes", "genderRes", "emotionRes", "mobilefacenetRes", "antispoofRes", "livenessRes", "descRes", "faceRes", "faces", "predict", "env", "i", "log", "masked", "mask", "rotation", "calculateFaceAngle", "irisSize", "tensor", "res", "body", "res", "gestures", "i", "leftWrist", "a", "rightWrist", "nose", "leftShoulder", "rightShoulder", "face", "zDiff", "xDiff", "mouthOpen", "chinDepth", "iris", "sizeXLeft", "sizeYLeft", "areaLeft", "sizeXRight", "sizeYRight", "areaRight", "center", "leftIrisCenterX", "rightIrisCenterX", "rightIrisCenterY", "leftIrisCenterY", "hand", "fingers", "finger", "pos", "closest", "best", "highest", "poses", "match", "pose", "bufferedResult", "interpolateTime", "calc", "newResult", "config", "_a", "_b", "_c", "_d", "_e", "_f", "_g", "_h", "_i", "_j", "_k", "_l", "_m", "_n", "_o", "_p", "_q", "_r", "_s", "_t", "_u", "_v", "_w", "_x", "_y", "_z", "_A", "t0", "now", "elapsed", "bufferedFactor", "i", "box", "newBoxCoord", "j", "boxRaw", "keypoints", "newKpt", "annotations", "coords", "efficientposecoords_exports", "blazeposecoords_exports", "movenetcoords_exports", "name", "indexes", "pt", "pt0", "kp", "pt1", "b", "landmark", "coord", "k", "key", "val", "rotation", "newPersons", "t1", "env", "match_exports", "__export", "distance", "match", "similarity", "descriptor1", "descriptor2", "options", "sum", "i", "diff", "normalizeDistance", "dist", "order", "min", "max", "root", "norm", "descriptor", "descriptors", "lowestDistance", "index", "res", "normalizedSimilarity", "join", "faces", "bodies", "hands", "gestures", "shape", "_a", "_b", "_c", "_d", "_e", "_f", "_g", "_h", "_i", "_j", "_k", "_l", "_m", "_n", "_o", "_p", "id", "persons", "face", "person", "body", "hand", "gesture", "x", "y", "extractXY", "box", "minX", "minY", "face", "body", "warmupBitmap", "instance", "b64toBlob", "base64", "type", "res", "blob", "face", "body", "bitmap", "warmupCanvas", "resolve", "src", "img", "env", "canvas", "log", "ctx", "tensor", "warmupNode", "atob", "str", "tfjs_esm_exports", "data", "expanded", "runInference", "runCompile", "allModels", "backendType", "webGLBackend", "numTensorsStart", "compiledModels", "modelName", "model", "key", "val", "shape", "dtype", "dim", "t", "e", "kernels", "numTensorsEnd", "warmup", "userConfig", "t0", "now", "mergeDeep", "t1", "_numTensors", "_analyzeMemoryLeaks", "_checkSanity", "_sanity", "Human", "userConfig", "__publicField", "__privateAdd", "msg", "__privateGet", "currentTensors", "previousTensors", "__privateSet", "leaked", "log", "input", "d", "e", "similarity", "distance", "match", "event", "_a", "env", "tfVersion", "v", "config", "version", "mergeDeep", "setModelLoadOptions", "tfjs_esm_exports", "Models", "options", "output", "canvas", "result", "face", "body", "hand", "gesture", "object", "person", "all", "triangulation", "uvmap", "currentBackend", "validate", "now", "getTensor", "process", "background", "enhance", "firstImageTensor", "secondImageTensor", "compare", "check", "timeStamp", "count", "model", "load", "current", "calc", "getModelStats", "t0", "res", "warmup", "t1", "profile", "kernels", "total", "kernel", "kernelArr", "key", "a", "b", "resolve", "_b", "_c", "_d", "_e", "_f", "_g", "_h", "_i", "_j", "_k", "_l", "_m", "_n", "_o", "_p", "_q", "_r", "_s", "_t", "_u", "_v", "error", "timeStart", "img", "skip", "faceRes", "bodyRes", "handRes", "objectRes", "detectFace", "bodyConfig", "predict", "handConfig", "gestureRes", "iris", "shape", "join"]
 }
diff --git a/dist/human.esm.d.ts b/dist/human.esm.d.ts
index 4f1e9723..925302ef 100644
--- a/dist/human.esm.d.ts
+++ b/dist/human.esm.d.ts
@@ -1330,7 +1330,11 @@ declare class Human {
      * - result object will contain total exeuction time information for top-20 kernels
      * - actual detection object can be accessed via `human.result`
      */
-    profile(input: Input, userConfig?: Partial<Config>): Promise<Record<string, number>>;
+    profile(input: Input, userConfig?: Partial<Config>): Promise<Array<{
+        kernel: string;
+        time: number;
+        perc: number;
+    }>>;
     /** Main detection method
      * - Analyze configuration: {@link Config}
      * - Pre-process input: {@link Input}
diff --git a/dist/human.esm.js b/dist/human.esm.js
index 8dcca3cd..7d43195b 100644
--- a/dist/human.esm.js
+++ b/dist/human.esm.js
@@ -84034,7 +84034,8 @@ async function register(instance) {
       return;
     }
     try {
-      ENV.set("WEBGL_VERSION", 2);
+      if (env().flagRegistry["WEBGL_VERSION"])
+        env().set("WEBGL_VERSION", 2);
     } catch (err) {
       log("error: cannot set WebGL backend flags:", err);
       return;
@@ -84115,10 +84116,8 @@ async function check(instance, force = false) {
       if (instance.config.debug)
         log("setting backend:", instance.config.backend);
       if (instance.config.backend === "wasm") {
-        try {
+        if (env().flagRegistry["CANVAS2D_WILL_READ_FREQUENTLY"])
           env().set("CANVAS2D_WILL_READ_FREQUENTLY", true);
-        } catch (e2) {
-        }
         if (instance.config.debug)
           log("wasm path:", instance.config.wasmPath);
         if (typeof (tfjs_esm_exports == null ? void 0 : tfjs_esm_exports.setWasmPaths) !== "undefined")
@@ -84142,13 +84141,21 @@ async function check(instance, force = false) {
       }
     }
     if (getBackend() === "humangl") {
-      ENV.set("CHECK_COMPUTATION_FOR_ERRORS", false);
-      ENV.set("WEBGL_CPU_FORWARD", true);
-      ENV.set("WEBGL_USE_SHAPES_UNIFORMS", true);
-      ENV.set("CPU_HANDOFF_SIZE_THRESHOLD", 256);
+      if (env().flagRegistry["CHECK_COMPUTATION_FOR_ERRORS"])
+        env().set("CHECK_COMPUTATION_FOR_ERRORS", false);
+      if (env().flagRegistry["WEBGL_CPU_FORWARD"])
+        env().set("WEBGL_CPU_FORWARD", true);
+      if (env().flagRegistry["WEBGL_USE_SHAPES_UNIFORMS"])
+        env().set("WEBGL_USE_SHAPES_UNIFORMS", true);
+      if (env().flagRegistry["CPU_HANDOFF_SIZE_THRESHOLD"])
+        env().set("CPU_HANDOFF_SIZE_THRESHOLD", 256);
+      if (env().flagRegistry["WEBGL_EXP_CONV"])
+        env().set("WEBGL_EXP_CONV", true);
+      if (env().flagRegistry["USE_SETTIMEOUTWPM"])
+        env().set("USE_SETTIMEOUTWPM", true);
       if (typeof instance.config["deallocate"] !== "undefined" && instance.config["deallocate"]) {
         log("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:", true);
-        ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD", 0);
+        env().set("WEBGL_DELETE_TEXTURE_THRESHOLD", 0);
       }
       if (backend().getGPGPUContext) {
         const gl = await backend().getGPGPUContext().gl;
@@ -86218,6 +86225,8 @@ async function runInference(instance) {
   return res;
 }
 async function runCompile(allModels) {
+  if (!env().flagRegistry["ENGINE_COMPILE_ONLY"])
+    return;
   const backendType = getBackend();
   const webGLBackend = backend();
   if (backendType !== "webgl" && backendType !== "humangl" || (!webGLBackend || !webGLBackend.checkCompileCompletion)) {
@@ -86446,20 +86455,23 @@ var Human = class {
   async profile(input2, userConfig) {
     const profile2 = await this.tf.profile(() => this.detect(input2, userConfig));
     const kernels = {};
+    let total = 0;
     for (const kernel of profile2.kernels) {
       if (kernels[kernel.name])
         kernels[kernel.name] += kernel.kernelTimeMs;
       else
         kernels[kernel.name] = kernel.kernelTimeMs;
+      total += kernel.kernelTimeMs;
     }
     const kernelArr = [];
-    Object.entries(kernels).forEach((key) => kernelArr.push({ name: key[0], ms: key[1] }));
-    kernelArr.sort((a, b) => b.ms - a.ms);
+    Object.entries(kernels).forEach((key) => kernelArr.push({ kernel: key[0], time: key[1], perc: 0 }));
+    for (const kernel of kernelArr) {
+      kernel.perc = Math.round(1e3 * kernel.time / total) / 1e3;
+      kernel.time = Math.round(1e3 * kernel.time) / 1e3;
+    }
+    kernelArr.sort((a, b) => b.time - a.time);
     kernelArr.length = 20;
-    const res = {};
-    for (const kernel of kernelArr)
-      res[kernel.name] = kernel.ms;
-    return res;
+    return kernelArr;
   }
   async detect(input2, userConfig) {
     this.state = "detect";
diff --git a/dist/human.esm.js.map b/dist/human.esm.js.map
index 251d326b..af061ade 100644
--- a/dist/human.esm.js.map
+++ b/dist/human.esm.js.map
@@ -1,7 +1,7 @@
 {
   "version": 3,
   "sources": ["../src/util/util.ts", "../src/config.ts", "tfjs.esm.js", "../src/image/imagefxshaders.ts", "../src/image/imagefx.ts", "../src/image/enhance.ts", "../src/image/image.ts", "../src/util/env.ts", "../src/tfjs/load.ts", "../src/models.ts", "../src/gear/gear.ts", "../src/tfjs/constants.ts", "../src/gear/ssrnet-age.ts", "../src/gear/ssrnet-gender.ts", "../src/face/antispoof.ts", "../src/face/facemeshcoords.ts", "../src/face/facemeshutil.ts", "../src/face/blazeface.ts", "../src/body/blazeposecoords.ts", "../src/body/blazeposedetector.ts", "../src/util/box.ts", "../src/body/blazepose.ts", "../src/object/labels.ts", "../src/object/centernet.ts", "../src/body/efficientposecoords.ts", "../src/body/efficientpose.ts", "../src/gear/emotion.ts", "../src/face/mobilefacenet.ts", "../src/face/iris.ts", "../src/face/constants.ts", "../src/face/attention.ts", "../src/face/facemesh.ts", "../src/face/faceres.ts", "../src/hand/handposeutil.ts", "../src/hand/handposeanchors.ts", "../src/hand/handposedetector.ts", "../src/hand/handposepipeline.ts", "../src/hand/fingerdef.ts", "../src/hand/fingergesture.ts", "../src/hand/fingerpose.ts", "../src/hand/handpose.ts", "../src/hand/handtrack.ts", "../src/face/liveness.ts", "../src/body/movenetcoords.ts", "../src/body/movenetfix.ts", "../src/body/movenet.ts", "../src/object/nanodet.ts", "../src/body/posenetutils.ts", "../src/body/posenet.ts", "../src/segmentation/segmentation.ts", "../src/tfjs/humangl.ts", "../src/tfjs/backend.ts", "../src/draw/draw.ts", "../src/draw/primitives.ts", "../src/draw/options.ts", "../src/draw/face.ts", "../src/draw/body.ts", "../src/draw/hand.ts", "../src/draw/object.ts", "../src/draw/gesture.ts", "../src/face/mask.ts", "../src/face/angles.ts", "../src/face/face.ts", "../src/gesture/gesture.ts", "../src/util/interpolate.ts", "../src/face/match.ts", "../src/util/persons.ts", "../src/sample.ts", "../src/warmup.ts", "../src/human.ts"],
-  "sourcesContent": ["import type { Config } from '../exports';\n\n/**\n * Simple helper functions used accross codebase\n */\n\n// helper function: wrapper around console output\nexport function log(...msg): void {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n\n// helper function: join two paths\nexport function join(folder: string, file: string): string {\n  const separator = folder.endsWith('/') ? '' : '/';\n  const skipJoin = file.startsWith('.') || file.startsWith('/') || file.startsWith('http:') || file.startsWith('https:') || file.startsWith('file:');\n  const path = skipJoin ? `${file}` : `${folder}${separator}${file}`;\n  if (!path.toLocaleLowerCase().includes('.json')) throw new Error(`modelpath error: expecting json file: ${path}`);\n  return path;\n}\n\n// helper function: gets elapsed time on both browser and nodejs\nexport const now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\n// helper function: checks current config validity\nexport function validate(defaults: Partial<Config>, config: Partial<Config>, parent = 'config', msgs: Array<{ reason: string, where: string, expected?: string }> = []) {\n  for (const key of Object.keys(config)) {\n    if (typeof config[key] === 'object') {\n      validate(defaults[key], config[key], key, msgs);\n    } else {\n      const defined = defaults && (typeof defaults[key] !== 'undefined');\n      if (!defined) msgs.push({ reason: 'unknown property', where: `${parent}.${key} = ${config[key]}` });\n      const same = defaults && typeof defaults[key] === typeof config[key];\n      if (defined && !same) msgs.push({ reason: 'property type mismatch', where: `${parent}.${key} = ${config[key]}`, expected: typeof defaults[key] });\n    }\n    // ok = ok && defined && same;\n  }\n  if (config.debug && parent === 'config' && msgs.length > 0) log('invalid configuration', msgs);\n  return msgs;\n}\n\n// helper function: perform deep merge of multiple objects so it allows full inheritance with overrides\nexport function mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\n// helper function: return min and max from input array\nexport const minmax = (data: Array<number>) => data.reduce((acc: Array<number>, val) => {\n  acc[0] = (acc[0] === undefined || val < acc[0]) ? val : acc[0];\n  acc[1] = (acc[1] === undefined || val > acc[1]) ? val : acc[1];\n  return acc;\n}, []);\n\n// helper function: async wait\nexport async function wait(time: number) {\n  const waiting = new Promise((resolve) => { setTimeout(() => resolve(true), time); });\n  await waiting;\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\n/** Generic config type inherited by all module types */\nexport interface GenericConfig {\n  /** is module enabled? */\n  enabled: boolean,\n  /** path to model json file (relative to `modelBasePath` */\n  modelPath: string,\n  /** how many max frames to go without re-running model if cached results are acceptable\n   * for two-phase models such as face and hand caching applies to bounding boxes detection only */\n  skipFrames: number,\n  /** how many max milliseconds to go without re-running model if cached results are acceptable\n  * for two-phase models such as face and hand caching applies to bounding boxes detection only */\n  skipTime: number,\n}\n\n/** Detector part of face configuration */\nexport interface FaceDetectorConfig extends GenericConfig {\n  /** is face rotation correction performed after detecting face?\n   * used to correctly analyze faces under high angles\n  */\n  rotation: boolean,\n  /** maximum number of detected faces */\n  maxDetected: number,\n  /** minimum confidence for a detected face before results are discarded */\n  minConfidence: number,\n  /** minimum overlap between two detected faces before one is discarded */\n  iouThreshold: number,\n  /** should child models perform on masked image of a face */\n  mask: boolean,\n  /** should face detection return processed and cropped face tensor that can with an external model for addtional processing?\n   * if enabled it must be manually deallocated to avoid memory leak */\n  return: boolean,\n}\n\n/** Mesh part of face configuration */\nexport interface FaceMeshConfig extends GenericConfig {\n  /** Keep detected faces that cannot be verified using facemesh */\n  keepInvalid: boolean\n}\n\n/** Iris part of face configuration */\nexport interface FaceIrisConfig extends GenericConfig {}\n\n/** Attention part of face configuration */\nexport interface FaceAttentionConfig extends GenericConfig {}\n\n/** Description or face embedding part of face configuration\n * - also used by age and gender detection\n */\nexport interface FaceDescriptionConfig extends GenericConfig {\n  /** minimum confidence for a detected face before results are discarded */\n  minConfidence: number,\n}\n\n/** Emotion part of face configuration */\nexport interface FaceEmotionConfig extends GenericConfig {\n  /** minimum confidence for a detected face before results are discarded */\n  minConfidence: number,\n}\n\n/** Anti-spoofing part of face configuration */\nexport interface FaceAntiSpoofConfig extends GenericConfig {}\n\n/** Liveness part of face configuration */\nexport interface FaceLivenessConfig extends GenericConfig {}\n\n/** Gear part of face configuration */\nexport interface FaceGearConfig extends GenericConfig {\n  /** minimum confidence for a detected race before results are discarded */\n  minConfidence: number,\n}\n\n/** Configures all face-specific options: face detection, mesh analysis, age, gender, emotion detection and face description */\nexport interface FaceConfig extends GenericConfig {\n  detector: Partial<FaceDetectorConfig>,\n  mesh: Partial<FaceMeshConfig>,\n  attention: Partial<FaceAttentionConfig>,\n  iris: Partial<FaceIrisConfig>,\n  description: Partial<FaceDescriptionConfig>,\n  emotion: Partial<FaceEmotionConfig>,\n  antispoof: Partial<FaceAntiSpoofConfig>,\n  liveness: Partial<FaceLivenessConfig>,\n  gear: Partial<FaceGearConfig>,\n}\n\n/** Configures all body detection specific options */\nexport interface BodyConfig extends GenericConfig {\n  /** maximum number of detected bodies */\n  maxDetected: number,\n  /** minimum confidence for a detected body before results are discarded */\n  minConfidence: number,\n  /* experimental\n  /** experimental: detector used for body model before actual analysis\n  detector?: {\n    /** experimental: enable body detector before body landmarks\n    enabled: boolean,\n    /** experimental: path to optional body detector model json file\n    modelPath: string,\n    /** experimental: minimum confidence for a detected body before results are discarded\n    minConfidence: number,\n    /** experimental: minimum overlap between two detected bodies before one is discarded\n    iouThreshold: number\n  },\n  */\n}\n\n/** Configures all hand detection specific options */\nexport interface HandConfig extends GenericConfig {\n  /** should hand rotation correction be performed after hand detection? */\n  rotation: boolean,\n  /** minimum confidence for a detected hand before results are discarded */\n  minConfidence: number,\n  /** minimum overlap between two detected hands before one is discarded */\n  iouThreshold: number,\n  /** maximum number of detected hands */\n  maxDetected: number,\n  /** should hand landmarks be detected or just return detected hand box */\n  landmarks: boolean,\n  detector: {\n    /** path to hand detector model json */\n    modelPath?: string,\n  },\n  skeleton: {\n    /** path to hand skeleton model json */\n    modelPath?: string,\n  },\n}\n\n/** Configures all object detection specific options */\nexport interface ObjectConfig extends GenericConfig {\n  /** minimum confidence for a detected objects before results are discarded */\n  minConfidence: number,\n  /** minimum overlap between two detected objects before one is discarded */\n  iouThreshold: number,\n  /** maximum number of detected objects */\n  maxDetected: number,\n}\n\n/** Configures all body segmentation module\n * removes background from input containing person\n * if segmentation is enabled it will run as preprocessing task before any other model\n * alternatively leave it disabled and use it on-demand using human.segmentation method which can\n * remove background or replace it with user-provided background\n*/\nexport interface SegmentationConfig extends GenericConfig {\n  /** blur segmentation output by <number> pixels for more realistic image */\n  blur: number,\n}\n\n/** Run input through image filters before inference\n * - available only in Browser environments\n * - image filters run with near-zero latency as they are executed on the GPU using WebGL\n*/\nexport interface FilterConfig {\n  /** are image filters enabled? */\n  enabled: boolean,\n  /** perform image histogram equalization\n   * - equalization is performed on input as a whole and detected face before its passed for further analysis\n  */\n  equalization: boolean,\n  /** resize input width\n  * - if both width and height are set to 0, there is no resizing\n  * - if just one is set, second one is scaled automatically\n  * - if both are set, values are used as-is\n  */\n  width: number,\n  /** resize input height\n  * - if both width and height are set to 0, there is no resizing\n  * - if just one is set, second one is scaled automatically\n  * - if both are set, values are used as-is\n  */\n  height: number,\n  /** return processed canvas imagedata in result */\n  return: boolean,\n  /** flip input as mirror image */\n  flip: boolean,\n  /** range: -1 (darken) to 1 (lighten) */\n  brightness: number,\n  /** range: -1 (reduce contrast) to 1 (increase contrast) */\n  contrast: number,\n  /** range: 0 (no sharpening) to 1 (maximum sharpening) */\n  sharpness: number,\n  /** range: 0 (no blur) to N (blur radius in pixels) */\n  blur: number\n  /** range: -1 (reduce saturation) to 1 (increase saturation) */\n  saturation: number,\n  /** range: 0 (no change) to 360 (hue rotation in degrees) */\n  hue: number,\n  /** image negative */\n  negative: boolean,\n  /** image sepia colors */\n  sepia: boolean,\n  /** image vintage colors */\n  vintage: boolean,\n  /** image kodachrome colors */\n  kodachrome: boolean,\n  /** image technicolor colors */\n  technicolor: boolean,\n  /** image polaroid camera effect */\n  polaroid: boolean,\n  /** range: 0 (no pixelate) to N (number of pixels to pixelate) */\n  pixelate: number,\n}\n\n/** Controlls gesture detection */\nexport interface GestureConfig {\n  /** is gesture detection enabled? */\n  enabled: boolean,\n}\n/** Possible TensorFlow backends */\nexport type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu'];\n\n/** Possible values for `human.warmup` */\nexport type WarmupType = ['' | 'none' | 'face' | 'full' | 'body'];\n\n/**\n * Configuration interface definition for **Human** library\n * Contains all configurable parameters\n * Defaults: [config](https://github.com/vladmandic/human/blob/main/src/config.ts#L262)\n */\nexport interface Config {\n  /** Backend used for TFJS operations\n   * valid build-in backends are:\n   * - Browser: `cpu`, `wasm`, `webgl`, `humangl`, `webgpu`\n   * - NodeJS: `cpu`, `wasm`, `tensorflow`\n   * default: `humangl` for browser and `tensorflow` for nodejs\n  */\n  backend: '' | 'cpu' | 'wasm' | 'webgl' | 'humangl' | 'tensorflow' | 'webgpu',\n\n  /** Path to *.wasm files if backend is set to `wasm`\n   *\n   * default: auto-detects to link to CDN `jsdelivr` when running in browser\n  */\n  wasmPath: string,\n\n  /** Force WASM loader to use platform fetch\n   *\n   * default: auto-detects to link to CDN `jsdelivr` when running in browser\n  */\n  wasmPlatformFetch: boolean,\n\n  /** Print debug statements to console\n   *\n   * default: `true`\n  */\n  debug: boolean,\n\n  /** Perform model loading and inference concurrently or sequentially\n   *\n   * default: `true`\n  */\n  async: boolean,\n\n  /** What to use for `human.warmup()`\n   * - warmup pre-initializes all models for faster inference but can take significant time on startup\n   * - used by `webgl`, `humangl` and `webgpu` backends\n   *\n   * default: `full`\n  */\n  warmup: '' | 'none' | 'face' | 'full' | 'body',\n\n  /** Base model path (typically starting with file://, http:// or https://) for all models\n   * - individual modelPath values are relative to this path\n   *\n   * default: `../models/` for browsers and `file://models/` for nodejs\n  */\n  modelBasePath: string,\n\n  /** Cache models in IndexDB on first sucessfull load\n   * default: true if indexdb is available (browsers), false if its not (nodejs)\n   */\n  cacheModels: boolean,\n\n  /** Cache sensitivity\n   * - values 0..1 where 0.01 means reset cache if input changed more than 1%\n   * - set to 0 to disable caching\n   *\n   * default: 0.7\n  */\n  cacheSensitivity: number;\n\n  /** Perform immediate garbage collection on deallocated tensors instead of caching them */\n  deallocate: boolean;\n\n  /** Internal Variable */\n  skipAllowed: boolean;\n\n  /** Filter config {@link FilterConfig} */\n  filter: Partial<FilterConfig>,\n\n  /** Gesture config {@link GestureConfig} */\n  gesture: Partial<GestureConfig>;\n\n  /** Face config {@link FaceConfig} */\n  face: Partial<FaceConfig>,\n\n  /** Body config {@link BodyConfig} */\n  body: Partial<BodyConfig>,\n\n  /** Hand config {@link HandConfig} */\n  hand: Partial<HandConfig>,\n\n  /** Object config {@link ObjectConfig} */\n  object: Partial<ObjectConfig>,\n\n  /** Segmentation config {@link SegmentationConfig} */\n  segmentation: Partial<SegmentationConfig>,\n}\n\n/** - [See all default Config values...](https://github.com/vladmandic/human/blob/main/src/config.ts#L262) */\nconst config: Config = {\n  backend: '',\n  modelBasePath: '',\n  cacheModels: true,\n  wasmPath: '',\n  wasmPlatformFetch: false,\n  debug: false,\n  async: true,\n  warmup: 'full',\n  cacheSensitivity: 0.70,\n  skipAllowed: false,\n  deallocate: false,\n  filter: {\n    enabled: true,\n    equalization: false,\n    width: 0,\n    height: 0,\n    flip: false,\n    return: true,\n    brightness: 0,\n    contrast: 0,\n    sharpness: 0,\n    blur: 0,\n    saturation: 0,\n    hue: 0,\n    negative: false,\n    sepia: false,\n    vintage: false,\n    kodachrome: false,\n    technicolor: false,\n    polaroid: false,\n    pixelate: 0,\n  },\n  gesture: {\n    enabled: true,\n  },\n  face: {\n    enabled: true,\n    detector: {\n      modelPath: 'blazeface.json',\n      rotation: true,\n      maxDetected: 1,\n      skipFrames: 99,\n      skipTime: 2500,\n      minConfidence: 0.2,\n      iouThreshold: 0.1,\n      mask: false,\n      return: false,\n    },\n    mesh: {\n      enabled: true,\n      modelPath: 'facemesh.json',\n      keepInvalid: false,\n    },\n    attention: {\n      enabled: false,\n      modelPath: 'facemesh-attention.json',\n    },\n    iris: {\n      enabled: true,\n      modelPath: 'iris.json',\n    },\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,\n      skipFrames: 99,\n      skipTime: 1500,\n      modelPath: 'emotion.json',\n    },\n    description: {\n      enabled: true,\n      modelPath: 'faceres.json',\n      skipFrames: 99,\n      skipTime: 3000,\n      minConfidence: 0.1,\n    },\n    antispoof: {\n      enabled: false,\n      skipFrames: 99,\n      skipTime: 4000,\n      modelPath: 'antispoof.json',\n    },\n    liveness: {\n      enabled: false,\n      skipFrames: 99,\n      skipTime: 4000,\n      modelPath: 'liveness.json',\n    },\n  },\n  body: {\n    enabled: true,\n    modelPath: 'movenet-lightning.json',\n    maxDetected: -1,\n    minConfidence: 0.3,\n    skipFrames: 1,\n    skipTime: 200,\n  },\n  hand: {\n    enabled: true,\n    rotation: true,\n    skipFrames: 99,\n    skipTime: 1000,\n    minConfidence: 0.50,\n    iouThreshold: 0.2,\n    maxDetected: -1,\n    landmarks: true,\n    detector: {\n      modelPath: 'handtrack.json',\n    },\n    skeleton: {\n      modelPath: 'handlandmark-full.json',\n    },\n  },\n  object: {\n    enabled: false,\n    modelPath: 'mb3-centernet.json',\n    minConfidence: 0.2,\n    iouThreshold: 0.4,\n    maxDetected: 10,\n    skipFrames: 99,\n    skipTime: 2000,\n  },\n  segmentation: {\n    enabled: false,\n    modelPath: 'selfie.json',\n    blur: 8,\n  },\n};\n\nexport { config as defaults };\n", "/*\n  Human\n  homepage: <https://github.com/vladmandic/human>\n  author: <https://github.com/vladmandic>'\n*/\n\nvar __create = Object.create;\nvar __defProp = Object.defineProperty;\nvar __getOwnPropDesc = Object.getOwnPropertyDescriptor;\nvar __getOwnPropNames = Object.getOwnPropertyNames;\nvar __getProtoOf = Object.getPrototypeOf;\nvar __hasOwnProp = Object.prototype.hasOwnProperty;\nvar __commonJS = (cb, mod4) => function __require() {\n  return mod4 || (0, cb[__getOwnPropNames(cb)[0]])((mod4 = { exports: {} }).exports, mod4), mod4.exports;\n};\nvar __export = (target, all5) => {\n  for (var name in all5)\n    __defProp(target, name, { get: all5[name], enumerable: true });\n};\nvar __copyProps = (to, from, except, desc) => {\n  if (from && typeof from === \"object\" || typeof from === \"function\") {\n    for (let key of __getOwnPropNames(from))\n      if (!__hasOwnProp.call(to, key) && key !== except)\n        __defProp(to, key, { get: () => from[key], enumerable: !(desc = __getOwnPropDesc(from, key)) || desc.enumerable });\n  }\n  return to;\n};\nvar __toESM = (mod4, isNodeMode, target) => (target = mod4 != null ? __create(__getProtoOf(mod4)) : {}, __copyProps(\n  isNodeMode || !mod4 || !mod4.__esModule ? __defProp(target, \"default\", { value: mod4, enumerable: true }) : target,\n  mod4\n));\n\n// node_modules/.pnpm/long@4.0.0/node_modules/long/src/long.js\nvar require_long = __commonJS({\n  \"node_modules/.pnpm/long@4.0.0/node_modules/long/src/long.js\"(exports, module) {\n    module.exports = Long2;\n    var wasm = null;\n    try {\n      wasm = new WebAssembly.Instance(new WebAssembly.Module(new Uint8Array([\n        0,\n        97,\n        115,\n        109,\n        1,\n        0,\n        0,\n        0,\n        1,\n        13,\n        2,\n        96,\n        0,\n        1,\n        127,\n        96,\n        4,\n        127,\n        127,\n        127,\n        127,\n        1,\n        127,\n        3,\n        7,\n        6,\n        0,\n        1,\n        1,\n        1,\n        1,\n        1,\n        6,\n        6,\n        1,\n        127,\n        1,\n        65,\n        0,\n        11,\n        7,\n        50,\n        6,\n        3,\n        109,\n        117,\n        108,\n        0,\n        1,\n        5,\n        100,\n        105,\n        118,\n        95,\n        115,\n        0,\n        2,\n        5,\n        100,\n        105,\n        118,\n        95,\n        117,\n        0,\n        3,\n        5,\n        114,\n        101,\n        109,\n        95,\n        115,\n        0,\n        4,\n        5,\n        114,\n        101,\n        109,\n        95,\n        117,\n        0,\n        5,\n        8,\n        103,\n        101,\n        116,\n        95,\n        104,\n        105,\n        103,\n        104,\n        0,\n        0,\n        10,\n        191,\n        1,\n        6,\n        4,\n        0,\n        35,\n        0,\n        11,\n        36,\n        1,\n        1,\n        126,\n        32,\n        0,\n        173,\n        32,\n        1,\n        173,\n        66,\n        32,\n        134,\n        132,\n        32,\n        2,\n        173,\n        32,\n        3,\n        173,\n        66,\n        32,\n        134,\n        132,\n        126,\n        34,\n        4,\n        66,\n        32,\n        135,\n        167,\n        36,\n        0,\n        32,\n        4,\n        167,\n        11,\n        36,\n        1,\n        1,\n        126,\n        32,\n        0,\n        173,\n        32,\n        1,\n        173,\n        66,\n        32,\n        134,\n        132,\n        32,\n        2,\n        173,\n        32,\n        3,\n        173,\n        66,\n        32,\n        134,\n        132,\n        127,\n        34,\n        4,\n        66,\n        32,\n        135,\n        167,\n        36,\n        0,\n        32,\n        4,\n        167,\n        11,\n        36,\n        1,\n        1,\n        126,\n        32,\n        0,\n        173,\n        32,\n        1,\n        173,\n        66,\n        32,\n        134,\n        132,\n        32,\n        2,\n        173,\n        32,\n        3,\n        173,\n        66,\n        32,\n        134,\n        132,\n        128,\n        34,\n        4,\n        66,\n        32,\n        135,\n        167,\n        36,\n        0,\n        32,\n        4,\n        167,\n        11,\n        36,\n        1,\n        1,\n        126,\n        32,\n        0,\n        173,\n        32,\n        1,\n        173,\n        66,\n        32,\n        134,\n        132,\n        32,\n        2,\n        173,\n        32,\n        3,\n        173,\n        66,\n        32,\n        134,\n        132,\n        129,\n        34,\n        4,\n        66,\n        32,\n        135,\n        167,\n        36,\n        0,\n        32,\n        4,\n        167,\n        11,\n        36,\n        1,\n        1,\n        126,\n        32,\n        0,\n        173,\n        32,\n        1,\n        173,\n        66,\n        32,\n        134,\n        132,\n        32,\n        2,\n        173,\n        32,\n        3,\n        173,\n        66,\n        32,\n        134,\n        132,\n        130,\n        34,\n        4,\n        66,\n        32,\n        135,\n        167,\n        36,\n        0,\n        32,\n        4,\n        167,\n        11\n      ])), {}).exports;\n    } catch (e2) {\n    }\n    function Long2(low, high, unsigned) {\n      this.low = low | 0;\n      this.high = high | 0;\n      this.unsigned = !!unsigned;\n    }\n    Long2.prototype.__isLong__;\n    Object.defineProperty(Long2.prototype, \"__isLong__\", { value: true });\n    function isLong(obj) {\n      return (obj && obj[\"__isLong__\"]) === true;\n    }\n    Long2.isLong = isLong;\n    var INT_CACHE = {};\n    var UINT_CACHE = {};\n    function fromInt(value, unsigned) {\n      var obj, cachedObj, cache;\n      if (unsigned) {\n        value >>>= 0;\n        if (cache = 0 <= value && value < 256) {\n          cachedObj = UINT_CACHE[value];\n          if (cachedObj)\n            return cachedObj;\n        }\n        obj = fromBits(value, (value | 0) < 0 ? -1 : 0, true);\n        if (cache)\n          UINT_CACHE[value] = obj;\n        return obj;\n      } else {\n        value |= 0;\n        if (cache = -128 <= value && value < 128) {\n          cachedObj = INT_CACHE[value];\n          if (cachedObj)\n            return cachedObj;\n        }\n        obj = fromBits(value, value < 0 ? -1 : 0, false);\n        if (cache)\n          INT_CACHE[value] = obj;\n        return obj;\n      }\n    }\n    Long2.fromInt = fromInt;\n    function fromNumber(value, unsigned) {\n      if (isNaN(value))\n        return unsigned ? UZERO : ZERO;\n      if (unsigned) {\n        if (value < 0)\n          return UZERO;\n        if (value >= TWO_PWR_64_DBL)\n          return MAX_UNSIGNED_VALUE;\n      } else {\n        if (value <= -TWO_PWR_63_DBL)\n          return MIN_VALUE;\n        if (value + 1 >= TWO_PWR_63_DBL)\n          return MAX_VALUE;\n      }\n      if (value < 0)\n        return fromNumber(-value, unsigned).neg();\n      return fromBits(value % TWO_PWR_32_DBL | 0, value / TWO_PWR_32_DBL | 0, unsigned);\n    }\n    Long2.fromNumber = fromNumber;\n    function fromBits(lowBits, highBits, unsigned) {\n      return new Long2(lowBits, highBits, unsigned);\n    }\n    Long2.fromBits = fromBits;\n    var pow_dbl = Math.pow;\n    function fromString(str, unsigned, radix) {\n      if (str.length === 0)\n        throw Error(\"empty string\");\n      if (str === \"NaN\" || str === \"Infinity\" || str === \"+Infinity\" || str === \"-Infinity\")\n        return ZERO;\n      if (typeof unsigned === \"number\") {\n        radix = unsigned, unsigned = false;\n      } else {\n        unsigned = !!unsigned;\n      }\n      radix = radix || 10;\n      if (radix < 2 || 36 < radix)\n        throw RangeError(\"radix\");\n      var p2;\n      if ((p2 = str.indexOf(\"-\")) > 0)\n        throw Error(\"interior hyphen\");\n      else if (p2 === 0) {\n        return fromString(str.substring(1), unsigned, radix).neg();\n      }\n      var radixToPower = fromNumber(pow_dbl(radix, 8));\n      var result = ZERO;\n      for (var i2 = 0; i2 < str.length; i2 += 8) {\n        var size = Math.min(8, str.length - i2), value = parseInt(str.substring(i2, i2 + size), radix);\n        if (size < 8) {\n          var power = fromNumber(pow_dbl(radix, size));\n          result = result.mul(power).add(fromNumber(value));\n        } else {\n          result = result.mul(radixToPower);\n          result = result.add(fromNumber(value));\n        }\n      }\n      result.unsigned = unsigned;\n      return result;\n    }\n    Long2.fromString = fromString;\n    function fromValue(val, unsigned) {\n      if (typeof val === \"number\")\n        return fromNumber(val, unsigned);\n      if (typeof val === \"string\")\n        return fromString(val, unsigned);\n      return fromBits(val.low, val.high, typeof unsigned === \"boolean\" ? unsigned : val.unsigned);\n    }\n    Long2.fromValue = fromValue;\n    var TWO_PWR_16_DBL = 1 << 16;\n    var TWO_PWR_24_DBL = 1 << 24;\n    var TWO_PWR_32_DBL = TWO_PWR_16_DBL * TWO_PWR_16_DBL;\n    var TWO_PWR_64_DBL = TWO_PWR_32_DBL * TWO_PWR_32_DBL;\n    var TWO_PWR_63_DBL = TWO_PWR_64_DBL / 2;\n    var TWO_PWR_24 = fromInt(TWO_PWR_24_DBL);\n    var ZERO = fromInt(0);\n    Long2.ZERO = ZERO;\n    var UZERO = fromInt(0, true);\n    Long2.UZERO = UZERO;\n    var ONE = fromInt(1);\n    Long2.ONE = ONE;\n    var UONE = fromInt(1, true);\n    Long2.UONE = UONE;\n    var NEG_ONE = fromInt(-1);\n    Long2.NEG_ONE = NEG_ONE;\n    var MAX_VALUE = fromBits(4294967295 | 0, 2147483647 | 0, false);\n    Long2.MAX_VALUE = MAX_VALUE;\n    var MAX_UNSIGNED_VALUE = fromBits(4294967295 | 0, 4294967295 | 0, true);\n    Long2.MAX_UNSIGNED_VALUE = MAX_UNSIGNED_VALUE;\n    var MIN_VALUE = fromBits(0, 2147483648 | 0, false);\n    Long2.MIN_VALUE = MIN_VALUE;\n    var LongPrototype = Long2.prototype;\n    LongPrototype.toInt = function toInt() {\n      return this.unsigned ? this.low >>> 0 : this.low;\n    };\n    LongPrototype.toNumber = function toNumber() {\n      if (this.unsigned)\n        return (this.high >>> 0) * TWO_PWR_32_DBL + (this.low >>> 0);\n      return this.high * TWO_PWR_32_DBL + (this.low >>> 0);\n    };\n    LongPrototype.toString = function toString(radix) {\n      radix = radix || 10;\n      if (radix < 2 || 36 < radix)\n        throw RangeError(\"radix\");\n      if (this.isZero())\n        return \"0\";\n      if (this.isNegative()) {\n        if (this.eq(MIN_VALUE)) {\n          var radixLong = fromNumber(radix), div3 = this.div(radixLong), rem1 = div3.mul(radixLong).sub(this);\n          return div3.toString(radix) + rem1.toInt().toString(radix);\n        } else\n          return \"-\" + this.neg().toString(radix);\n      }\n      var radixToPower = fromNumber(pow_dbl(radix, 6), this.unsigned), rem = this;\n      var result = \"\";\n      while (true) {\n        var remDiv = rem.div(radixToPower), intval = rem.sub(remDiv.mul(radixToPower)).toInt() >>> 0, digits = intval.toString(radix);\n        rem = remDiv;\n        if (rem.isZero())\n          return digits + result;\n        else {\n          while (digits.length < 6)\n            digits = \"0\" + digits;\n          result = \"\" + digits + result;\n        }\n      }\n    };\n    LongPrototype.getHighBits = function getHighBits() {\n      return this.high;\n    };\n    LongPrototype.getHighBitsUnsigned = function getHighBitsUnsigned() {\n      return this.high >>> 0;\n    };\n    LongPrototype.getLowBits = function getLowBits() {\n      return this.low;\n    };\n    LongPrototype.getLowBitsUnsigned = function getLowBitsUnsigned() {\n      return this.low >>> 0;\n    };\n    LongPrototype.getNumBitsAbs = function getNumBitsAbs() {\n      if (this.isNegative())\n        return this.eq(MIN_VALUE) ? 64 : this.neg().getNumBitsAbs();\n      var val = this.high != 0 ? this.high : this.low;\n      for (var bit = 31; bit > 0; bit--)\n        if ((val & 1 << bit) != 0)\n          break;\n      return this.high != 0 ? bit + 33 : bit + 1;\n    };\n    LongPrototype.isZero = function isZero() {\n      return this.high === 0 && this.low === 0;\n    };\n    LongPrototype.eqz = LongPrototype.isZero;\n    LongPrototype.isNegative = function isNegative() {\n      return !this.unsigned && this.high < 0;\n    };\n    LongPrototype.isPositive = function isPositive() {\n      return this.unsigned || this.high >= 0;\n    };\n    LongPrototype.isOdd = function isOdd() {\n      return (this.low & 1) === 1;\n    };\n    LongPrototype.isEven = function isEven2() {\n      return (this.low & 1) === 0;\n    };\n    LongPrototype.equals = function equals(other) {\n      if (!isLong(other))\n        other = fromValue(other);\n      if (this.unsigned !== other.unsigned && this.high >>> 31 === 1 && other.high >>> 31 === 1)\n        return false;\n      return this.high === other.high && this.low === other.low;\n    };\n    LongPrototype.eq = LongPrototype.equals;\n    LongPrototype.notEquals = function notEquals(other) {\n      return !this.eq(other);\n    };\n    LongPrototype.neq = LongPrototype.notEquals;\n    LongPrototype.ne = LongPrototype.notEquals;\n    LongPrototype.lessThan = function lessThan(other) {\n      return this.comp(other) < 0;\n    };\n    LongPrototype.lt = LongPrototype.lessThan;\n    LongPrototype.lessThanOrEqual = function lessThanOrEqual(other) {\n      return this.comp(other) <= 0;\n    };\n    LongPrototype.lte = LongPrototype.lessThanOrEqual;\n    LongPrototype.le = LongPrototype.lessThanOrEqual;\n    LongPrototype.greaterThan = function greaterThan(other) {\n      return this.comp(other) > 0;\n    };\n    LongPrototype.gt = LongPrototype.greaterThan;\n    LongPrototype.greaterThanOrEqual = function greaterThanOrEqual(other) {\n      return this.comp(other) >= 0;\n    };\n    LongPrototype.gte = LongPrototype.greaterThanOrEqual;\n    LongPrototype.ge = LongPrototype.greaterThanOrEqual;\n    LongPrototype.compare = function compare(other) {\n      if (!isLong(other))\n        other = fromValue(other);\n      if (this.eq(other))\n        return 0;\n      var thisNeg = this.isNegative(), otherNeg = other.isNegative();\n      if (thisNeg && !otherNeg)\n        return -1;\n      if (!thisNeg && otherNeg)\n        return 1;\n      if (!this.unsigned)\n        return this.sub(other).isNegative() ? -1 : 1;\n      return other.high >>> 0 > this.high >>> 0 || other.high === this.high && other.low >>> 0 > this.low >>> 0 ? -1 : 1;\n    };\n    LongPrototype.comp = LongPrototype.compare;\n    LongPrototype.negate = function negate() {\n      if (!this.unsigned && this.eq(MIN_VALUE))\n        return MIN_VALUE;\n      return this.not().add(ONE);\n    };\n    LongPrototype.neg = LongPrototype.negate;\n    LongPrototype.add = function add5(addend) {\n      if (!isLong(addend))\n        addend = fromValue(addend);\n      var a48 = this.high >>> 16;\n      var a32 = this.high & 65535;\n      var a16 = this.low >>> 16;\n      var a00 = this.low & 65535;\n      var b48 = addend.high >>> 16;\n      var b32 = addend.high & 65535;\n      var b16 = addend.low >>> 16;\n      var b00 = addend.low & 65535;\n      var c48 = 0, c32 = 0, c16 = 0, c00 = 0;\n      c00 += a00 + b00;\n      c16 += c00 >>> 16;\n      c00 &= 65535;\n      c16 += a16 + b16;\n      c32 += c16 >>> 16;\n      c16 &= 65535;\n      c32 += a32 + b32;\n      c48 += c32 >>> 16;\n      c32 &= 65535;\n      c48 += a48 + b48;\n      c48 &= 65535;\n      return fromBits(c16 << 16 | c00, c48 << 16 | c32, this.unsigned);\n    };\n    LongPrototype.subtract = function subtract(subtrahend) {\n      if (!isLong(subtrahend))\n        subtrahend = fromValue(subtrahend);\n      return this.add(subtrahend.neg());\n    };\n    LongPrototype.sub = LongPrototype.subtract;\n    LongPrototype.multiply = function multiply4(multiplier) {\n      if (this.isZero())\n        return ZERO;\n      if (!isLong(multiplier))\n        multiplier = fromValue(multiplier);\n      if (wasm) {\n        var low = wasm.mul(\n          this.low,\n          this.high,\n          multiplier.low,\n          multiplier.high\n        );\n        return fromBits(low, wasm.get_high(), this.unsigned);\n      }\n      if (multiplier.isZero())\n        return ZERO;\n      if (this.eq(MIN_VALUE))\n        return multiplier.isOdd() ? MIN_VALUE : ZERO;\n      if (multiplier.eq(MIN_VALUE))\n        return this.isOdd() ? MIN_VALUE : ZERO;\n      if (this.isNegative()) {\n        if (multiplier.isNegative())\n          return this.neg().mul(multiplier.neg());\n        else\n          return this.neg().mul(multiplier).neg();\n      } else if (multiplier.isNegative())\n        return this.mul(multiplier.neg()).neg();\n      if (this.lt(TWO_PWR_24) && multiplier.lt(TWO_PWR_24))\n        return fromNumber(this.toNumber() * multiplier.toNumber(), this.unsigned);\n      var a48 = this.high >>> 16;\n      var a32 = this.high & 65535;\n      var a16 = this.low >>> 16;\n      var a00 = this.low & 65535;\n      var b48 = multiplier.high >>> 16;\n      var b32 = multiplier.high & 65535;\n      var b16 = multiplier.low >>> 16;\n      var b00 = multiplier.low & 65535;\n      var c48 = 0, c32 = 0, c16 = 0, c00 = 0;\n      c00 += a00 * b00;\n      c16 += c00 >>> 16;\n      c00 &= 65535;\n      c16 += a16 * b00;\n      c32 += c16 >>> 16;\n      c16 &= 65535;\n      c16 += a00 * b16;\n      c32 += c16 >>> 16;\n      c16 &= 65535;\n      c32 += a32 * b00;\n      c48 += c32 >>> 16;\n      c32 &= 65535;\n      c32 += a16 * b16;\n      c48 += c32 >>> 16;\n      c32 &= 65535;\n      c32 += a00 * b32;\n      c48 += c32 >>> 16;\n      c32 &= 65535;\n      c48 += a48 * b00 + a32 * b16 + a16 * b32 + a00 * b48;\n      c48 &= 65535;\n      return fromBits(c16 << 16 | c00, c48 << 16 | c32, this.unsigned);\n    };\n    LongPrototype.mul = LongPrototype.multiply;\n    LongPrototype.divide = function divide(divisor) {\n      if (!isLong(divisor))\n        divisor = fromValue(divisor);\n      if (divisor.isZero())\n        throw Error(\"division by zero\");\n      if (wasm) {\n        if (!this.unsigned && this.high === -2147483648 && divisor.low === -1 && divisor.high === -1) {\n          return this;\n        }\n        var low = (this.unsigned ? wasm.div_u : wasm.div_s)(\n          this.low,\n          this.high,\n          divisor.low,\n          divisor.high\n        );\n        return fromBits(low, wasm.get_high(), this.unsigned);\n      }\n      if (this.isZero())\n        return this.unsigned ? UZERO : ZERO;\n      var approx, rem, res;\n      if (!this.unsigned) {\n        if (this.eq(MIN_VALUE)) {\n          if (divisor.eq(ONE) || divisor.eq(NEG_ONE))\n            return MIN_VALUE;\n          else if (divisor.eq(MIN_VALUE))\n            return ONE;\n          else {\n            var halfThis = this.shr(1);\n            approx = halfThis.div(divisor).shl(1);\n            if (approx.eq(ZERO)) {\n              return divisor.isNegative() ? ONE : NEG_ONE;\n            } else {\n              rem = this.sub(divisor.mul(approx));\n              res = approx.add(rem.div(divisor));\n              return res;\n            }\n          }\n        } else if (divisor.eq(MIN_VALUE))\n          return this.unsigned ? UZERO : ZERO;\n        if (this.isNegative()) {\n          if (divisor.isNegative())\n            return this.neg().div(divisor.neg());\n          return this.neg().div(divisor).neg();\n        } else if (divisor.isNegative())\n          return this.div(divisor.neg()).neg();\n        res = ZERO;\n      } else {\n        if (!divisor.unsigned)\n          divisor = divisor.toUnsigned();\n        if (divisor.gt(this))\n          return UZERO;\n        if (divisor.gt(this.shru(1)))\n          return UONE;\n        res = UZERO;\n      }\n      rem = this;\n      while (rem.gte(divisor)) {\n        approx = Math.max(1, Math.floor(rem.toNumber() / divisor.toNumber()));\n        var log22 = Math.ceil(Math.log(approx) / Math.LN2), delta = log22 <= 48 ? 1 : pow_dbl(2, log22 - 48), approxRes = fromNumber(approx), approxRem = approxRes.mul(divisor);\n        while (approxRem.isNegative() || approxRem.gt(rem)) {\n          approx -= delta;\n          approxRes = fromNumber(approx, this.unsigned);\n          approxRem = approxRes.mul(divisor);\n        }\n        if (approxRes.isZero())\n          approxRes = ONE;\n        res = res.add(approxRes);\n        rem = rem.sub(approxRem);\n      }\n      return res;\n    };\n    LongPrototype.div = LongPrototype.divide;\n    LongPrototype.modulo = function modulo(divisor) {\n      if (!isLong(divisor))\n        divisor = fromValue(divisor);\n      if (wasm) {\n        var low = (this.unsigned ? wasm.rem_u : wasm.rem_s)(\n          this.low,\n          this.high,\n          divisor.low,\n          divisor.high\n        );\n        return fromBits(low, wasm.get_high(), this.unsigned);\n      }\n      return this.sub(this.div(divisor).mul(divisor));\n    };\n    LongPrototype.mod = LongPrototype.modulo;\n    LongPrototype.rem = LongPrototype.modulo;\n    LongPrototype.not = function not() {\n      return fromBits(~this.low, ~this.high, this.unsigned);\n    };\n    LongPrototype.and = function and(other) {\n      if (!isLong(other))\n        other = fromValue(other);\n      return fromBits(this.low & other.low, this.high & other.high, this.unsigned);\n    };\n    LongPrototype.or = function or(other) {\n      if (!isLong(other))\n        other = fromValue(other);\n      return fromBits(this.low | other.low, this.high | other.high, this.unsigned);\n    };\n    LongPrototype.xor = function xor(other) {\n      if (!isLong(other))\n        other = fromValue(other);\n      return fromBits(this.low ^ other.low, this.high ^ other.high, this.unsigned);\n    };\n    LongPrototype.shiftLeft = function shiftLeft(numBits) {\n      if (isLong(numBits))\n        numBits = numBits.toInt();\n      if ((numBits &= 63) === 0)\n        return this;\n      else if (numBits < 32)\n        return fromBits(this.low << numBits, this.high << numBits | this.low >>> 32 - numBits, this.unsigned);\n      else\n        return fromBits(0, this.low << numBits - 32, this.unsigned);\n    };\n    LongPrototype.shl = LongPrototype.shiftLeft;\n    LongPrototype.shiftRight = function shiftRight(numBits) {\n      if (isLong(numBits))\n        numBits = numBits.toInt();\n      if ((numBits &= 63) === 0)\n        return this;\n      else if (numBits < 32)\n        return fromBits(this.low >>> numBits | this.high << 32 - numBits, this.high >> numBits, this.unsigned);\n      else\n        return fromBits(this.high >> numBits - 32, this.high >= 0 ? 0 : -1, this.unsigned);\n    };\n    LongPrototype.shr = LongPrototype.shiftRight;\n    LongPrototype.shiftRightUnsigned = function shiftRightUnsigned(numBits) {\n      if (isLong(numBits))\n        numBits = numBits.toInt();\n      numBits &= 63;\n      if (numBits === 0)\n        return this;\n      else {\n        var high = this.high;\n        if (numBits < 32) {\n          var low = this.low;\n          return fromBits(low >>> numBits | high << 32 - numBits, high >>> numBits, this.unsigned);\n        } else if (numBits === 32)\n          return fromBits(high, 0, this.unsigned);\n        else\n          return fromBits(high >>> numBits - 32, 0, this.unsigned);\n      }\n    };\n    LongPrototype.shru = LongPrototype.shiftRightUnsigned;\n    LongPrototype.shr_u = LongPrototype.shiftRightUnsigned;\n    LongPrototype.toSigned = function toSigned() {\n      if (!this.unsigned)\n        return this;\n      return fromBits(this.low, this.high, false);\n    };\n    LongPrototype.toUnsigned = function toUnsigned() {\n      if (this.unsigned)\n        return this;\n      return fromBits(this.low, this.high, true);\n    };\n    LongPrototype.toBytes = function toBytes(le) {\n      return le ? this.toBytesLE() : this.toBytesBE();\n    };\n    LongPrototype.toBytesLE = function toBytesLE() {\n      var hi = this.high, lo = this.low;\n      return [\n        lo & 255,\n        lo >>> 8 & 255,\n        lo >>> 16 & 255,\n        lo >>> 24,\n        hi & 255,\n        hi >>> 8 & 255,\n        hi >>> 16 & 255,\n        hi >>> 24\n      ];\n    };\n    LongPrototype.toBytesBE = function toBytesBE() {\n      var hi = this.high, lo = this.low;\n      return [\n        hi >>> 24,\n        hi >>> 16 & 255,\n        hi >>> 8 & 255,\n        hi & 255,\n        lo >>> 24,\n        lo >>> 16 & 255,\n        lo >>> 8 & 255,\n        lo & 255\n      ];\n    };\n    Long2.fromBytes = function fromBytes(bytes, unsigned, le) {\n      return le ? Long2.fromBytesLE(bytes, unsigned) : Long2.fromBytesBE(bytes, unsigned);\n    };\n    Long2.fromBytesLE = function fromBytesLE(bytes, unsigned) {\n      return new Long2(\n        bytes[0] | bytes[1] << 8 | bytes[2] << 16 | bytes[3] << 24,\n        bytes[4] | bytes[5] << 8 | bytes[6] << 16 | bytes[7] << 24,\n        unsigned\n      );\n    };\n    Long2.fromBytesBE = function fromBytesBE(bytes, unsigned) {\n      return new Long2(\n        bytes[4] << 24 | bytes[5] << 16 | bytes[6] << 8 | bytes[7],\n        bytes[0] << 24 | bytes[1] << 16 | bytes[2] << 8 | bytes[3],\n        unsigned\n      );\n    };\n  }\n});\n\n// (disabled):node_modules/.pnpm/node-fetch@2.6.7/node_modules/node-fetch/browser.js\nvar require_browser = __commonJS({\n  \"(disabled):node_modules/.pnpm/node-fetch@2.6.7/node_modules/node-fetch/browser.js\"() {\n  }\n});\n\n// (disabled):util\nvar require_util = __commonJS({\n  \"(disabled):util\"() {\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/alea.js\nvar require_alea = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/alea.js\"(exports, module) {\n    (function(global2, module2, define2) {\n      function Alea(seed) {\n        var me = this, mash = Mash();\n        me.next = function() {\n          var t2 = 2091639 * me.s0 + me.c * 23283064365386963e-26;\n          me.s0 = me.s1;\n          me.s1 = me.s2;\n          return me.s2 = t2 - (me.c = t2 | 0);\n        };\n        me.c = 1;\n        me.s0 = mash(\" \");\n        me.s1 = mash(\" \");\n        me.s2 = mash(\" \");\n        me.s0 -= mash(seed);\n        if (me.s0 < 0) {\n          me.s0 += 1;\n        }\n        me.s1 -= mash(seed);\n        if (me.s1 < 0) {\n          me.s1 += 1;\n        }\n        me.s2 -= mash(seed);\n        if (me.s2 < 0) {\n          me.s2 += 1;\n        }\n        mash = null;\n      }\n      function copy(f, t2) {\n        t2.c = f.c;\n        t2.s0 = f.s0;\n        t2.s1 = f.s1;\n        t2.s2 = f.s2;\n        return t2;\n      }\n      function impl(seed, opts) {\n        var xg = new Alea(seed), state = opts && opts.state, prng = xg.next;\n        prng.int32 = function() {\n          return xg.next() * 4294967296 | 0;\n        };\n        prng.double = function() {\n          return prng() + (prng() * 2097152 | 0) * 11102230246251565e-32;\n        };\n        prng.quick = prng;\n        if (state) {\n          if (typeof state == \"object\")\n            copy(state, xg);\n          prng.state = function() {\n            return copy(xg, {});\n          };\n        }\n        return prng;\n      }\n      function Mash() {\n        var n2 = 4022871197;\n        var mash = function(data) {\n          data = String(data);\n          for (var i2 = 0; i2 < data.length; i2++) {\n            n2 += data.charCodeAt(i2);\n            var h = 0.02519603282416938 * n2;\n            n2 = h >>> 0;\n            h -= n2;\n            h *= n2;\n            n2 = h >>> 0;\n            h -= n2;\n            n2 += h * 4294967296;\n          }\n          return (n2 >>> 0) * 23283064365386963e-26;\n        };\n        return mash;\n      }\n      if (module2 && module2.exports) {\n        module2.exports = impl;\n      } else if (define2 && define2.amd) {\n        define2(function() {\n          return impl;\n        });\n      } else {\n        this.alea = impl;\n      }\n    })(\n      exports,\n      typeof module == \"object\" && module,\n      typeof define == \"function\" && define\n    );\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xor128.js\nvar require_xor128 = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xor128.js\"(exports, module) {\n    (function(global2, module2, define2) {\n      function XorGen(seed) {\n        var me = this, strseed = \"\";\n        me.x = 0;\n        me.y = 0;\n        me.z = 0;\n        me.w = 0;\n        me.next = function() {\n          var t2 = me.x ^ me.x << 11;\n          me.x = me.y;\n          me.y = me.z;\n          me.z = me.w;\n          return me.w ^= me.w >>> 19 ^ t2 ^ t2 >>> 8;\n        };\n        if (seed === (seed | 0)) {\n          me.x = seed;\n        } else {\n          strseed += seed;\n        }\n        for (var k = 0; k < strseed.length + 64; k++) {\n          me.x ^= strseed.charCodeAt(k) | 0;\n          me.next();\n        }\n      }\n      function copy(f, t2) {\n        t2.x = f.x;\n        t2.y = f.y;\n        t2.z = f.z;\n        t2.w = f.w;\n        return t2;\n      }\n      function impl(seed, opts) {\n        var xg = new XorGen(seed), state = opts && opts.state, prng = function() {\n          return (xg.next() >>> 0) / 4294967296;\n        };\n        prng.double = function() {\n          do {\n            var top = xg.next() >>> 11, bot = (xg.next() >>> 0) / 4294967296, result = (top + bot) / (1 << 21);\n          } while (result === 0);\n          return result;\n        };\n        prng.int32 = xg.next;\n        prng.quick = prng;\n        if (state) {\n          if (typeof state == \"object\")\n            copy(state, xg);\n          prng.state = function() {\n            return copy(xg, {});\n          };\n        }\n        return prng;\n      }\n      if (module2 && module2.exports) {\n        module2.exports = impl;\n      } else if (define2 && define2.amd) {\n        define2(function() {\n          return impl;\n        });\n      } else {\n        this.xor128 = impl;\n      }\n    })(\n      exports,\n      typeof module == \"object\" && module,\n      typeof define == \"function\" && define\n    );\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xorwow.js\nvar require_xorwow = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xorwow.js\"(exports, module) {\n    (function(global2, module2, define2) {\n      function XorGen(seed) {\n        var me = this, strseed = \"\";\n        me.next = function() {\n          var t2 = me.x ^ me.x >>> 2;\n          me.x = me.y;\n          me.y = me.z;\n          me.z = me.w;\n          me.w = me.v;\n          return (me.d = me.d + 362437 | 0) + (me.v = me.v ^ me.v << 4 ^ (t2 ^ t2 << 1)) | 0;\n        };\n        me.x = 0;\n        me.y = 0;\n        me.z = 0;\n        me.w = 0;\n        me.v = 0;\n        if (seed === (seed | 0)) {\n          me.x = seed;\n        } else {\n          strseed += seed;\n        }\n        for (var k = 0; k < strseed.length + 64; k++) {\n          me.x ^= strseed.charCodeAt(k) | 0;\n          if (k == strseed.length) {\n            me.d = me.x << 10 ^ me.x >>> 4;\n          }\n          me.next();\n        }\n      }\n      function copy(f, t2) {\n        t2.x = f.x;\n        t2.y = f.y;\n        t2.z = f.z;\n        t2.w = f.w;\n        t2.v = f.v;\n        t2.d = f.d;\n        return t2;\n      }\n      function impl(seed, opts) {\n        var xg = new XorGen(seed), state = opts && opts.state, prng = function() {\n          return (xg.next() >>> 0) / 4294967296;\n        };\n        prng.double = function() {\n          do {\n            var top = xg.next() >>> 11, bot = (xg.next() >>> 0) / 4294967296, result = (top + bot) / (1 << 21);\n          } while (result === 0);\n          return result;\n        };\n        prng.int32 = xg.next;\n        prng.quick = prng;\n        if (state) {\n          if (typeof state == \"object\")\n            copy(state, xg);\n          prng.state = function() {\n            return copy(xg, {});\n          };\n        }\n        return prng;\n      }\n      if (module2 && module2.exports) {\n        module2.exports = impl;\n      } else if (define2 && define2.amd) {\n        define2(function() {\n          return impl;\n        });\n      } else {\n        this.xorwow = impl;\n      }\n    })(\n      exports,\n      typeof module == \"object\" && module,\n      typeof define == \"function\" && define\n    );\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xorshift7.js\nvar require_xorshift7 = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xorshift7.js\"(exports, module) {\n    (function(global2, module2, define2) {\n      function XorGen(seed) {\n        var me = this;\n        me.next = function() {\n          var X = me.x, i2 = me.i, t2, v, w;\n          t2 = X[i2];\n          t2 ^= t2 >>> 7;\n          v = t2 ^ t2 << 24;\n          t2 = X[i2 + 1 & 7];\n          v ^= t2 ^ t2 >>> 10;\n          t2 = X[i2 + 3 & 7];\n          v ^= t2 ^ t2 >>> 3;\n          t2 = X[i2 + 4 & 7];\n          v ^= t2 ^ t2 << 7;\n          t2 = X[i2 + 7 & 7];\n          t2 = t2 ^ t2 << 13;\n          v ^= t2 ^ t2 << 9;\n          X[i2] = v;\n          me.i = i2 + 1 & 7;\n          return v;\n        };\n        function init2(me2, seed2) {\n          var j, w, X = [];\n          if (seed2 === (seed2 | 0)) {\n            w = X[0] = seed2;\n          } else {\n            seed2 = \"\" + seed2;\n            for (j = 0; j < seed2.length; ++j) {\n              X[j & 7] = X[j & 7] << 15 ^ seed2.charCodeAt(j) + X[j + 1 & 7] << 13;\n            }\n          }\n          while (X.length < 8)\n            X.push(0);\n          for (j = 0; j < 8 && X[j] === 0; ++j)\n            ;\n          if (j == 8)\n            w = X[7] = -1;\n          else\n            w = X[j];\n          me2.x = X;\n          me2.i = 0;\n          for (j = 256; j > 0; --j) {\n            me2.next();\n          }\n        }\n        init2(me, seed);\n      }\n      function copy(f, t2) {\n        t2.x = f.x.slice();\n        t2.i = f.i;\n        return t2;\n      }\n      function impl(seed, opts) {\n        if (seed == null)\n          seed = +new Date();\n        var xg = new XorGen(seed), state = opts && opts.state, prng = function() {\n          return (xg.next() >>> 0) / 4294967296;\n        };\n        prng.double = function() {\n          do {\n            var top = xg.next() >>> 11, bot = (xg.next() >>> 0) / 4294967296, result = (top + bot) / (1 << 21);\n          } while (result === 0);\n          return result;\n        };\n        prng.int32 = xg.next;\n        prng.quick = prng;\n        if (state) {\n          if (state.x)\n            copy(state, xg);\n          prng.state = function() {\n            return copy(xg, {});\n          };\n        }\n        return prng;\n      }\n      if (module2 && module2.exports) {\n        module2.exports = impl;\n      } else if (define2 && define2.amd) {\n        define2(function() {\n          return impl;\n        });\n      } else {\n        this.xorshift7 = impl;\n      }\n    })(\n      exports,\n      typeof module == \"object\" && module,\n      typeof define == \"function\" && define\n    );\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xor4096.js\nvar require_xor4096 = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xor4096.js\"(exports, module) {\n    (function(global2, module2, define2) {\n      function XorGen(seed) {\n        var me = this;\n        me.next = function() {\n          var w = me.w, X = me.X, i2 = me.i, t2, v;\n          me.w = w = w + 1640531527 | 0;\n          v = X[i2 + 34 & 127];\n          t2 = X[i2 = i2 + 1 & 127];\n          v ^= v << 13;\n          t2 ^= t2 << 17;\n          v ^= v >>> 15;\n          t2 ^= t2 >>> 12;\n          v = X[i2] = v ^ t2;\n          me.i = i2;\n          return v + (w ^ w >>> 16) | 0;\n        };\n        function init2(me2, seed2) {\n          var t2, v, i2, j, w, X = [], limit = 128;\n          if (seed2 === (seed2 | 0)) {\n            v = seed2;\n            seed2 = null;\n          } else {\n            seed2 = seed2 + \"\\0\";\n            v = 0;\n            limit = Math.max(limit, seed2.length);\n          }\n          for (i2 = 0, j = -32; j < limit; ++j) {\n            if (seed2)\n              v ^= seed2.charCodeAt((j + 32) % seed2.length);\n            if (j === 0)\n              w = v;\n            v ^= v << 10;\n            v ^= v >>> 15;\n            v ^= v << 4;\n            v ^= v >>> 13;\n            if (j >= 0) {\n              w = w + 1640531527 | 0;\n              t2 = X[j & 127] ^= v + w;\n              i2 = 0 == t2 ? i2 + 1 : 0;\n            }\n          }\n          if (i2 >= 128) {\n            X[(seed2 && seed2.length || 0) & 127] = -1;\n          }\n          i2 = 127;\n          for (j = 4 * 128; j > 0; --j) {\n            v = X[i2 + 34 & 127];\n            t2 = X[i2 = i2 + 1 & 127];\n            v ^= v << 13;\n            t2 ^= t2 << 17;\n            v ^= v >>> 15;\n            t2 ^= t2 >>> 12;\n            X[i2] = v ^ t2;\n          }\n          me2.w = w;\n          me2.X = X;\n          me2.i = i2;\n        }\n        init2(me, seed);\n      }\n      function copy(f, t2) {\n        t2.i = f.i;\n        t2.w = f.w;\n        t2.X = f.X.slice();\n        return t2;\n      }\n      ;\n      function impl(seed, opts) {\n        if (seed == null)\n          seed = +new Date();\n        var xg = new XorGen(seed), state = opts && opts.state, prng = function() {\n          return (xg.next() >>> 0) / 4294967296;\n        };\n        prng.double = function() {\n          do {\n            var top = xg.next() >>> 11, bot = (xg.next() >>> 0) / 4294967296, result = (top + bot) / (1 << 21);\n          } while (result === 0);\n          return result;\n        };\n        prng.int32 = xg.next;\n        prng.quick = prng;\n        if (state) {\n          if (state.X)\n            copy(state, xg);\n          prng.state = function() {\n            return copy(xg, {});\n          };\n        }\n        return prng;\n      }\n      if (module2 && module2.exports) {\n        module2.exports = impl;\n      } else if (define2 && define2.amd) {\n        define2(function() {\n          return impl;\n        });\n      } else {\n        this.xor4096 = impl;\n      }\n    })(\n      exports,\n      typeof module == \"object\" && module,\n      typeof define == \"function\" && define\n    );\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/tychei.js\nvar require_tychei = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/tychei.js\"(exports, module) {\n    (function(global2, module2, define2) {\n      function XorGen(seed) {\n        var me = this, strseed = \"\";\n        me.next = function() {\n          var b = me.b, c = me.c, d = me.d, a = me.a;\n          b = b << 25 ^ b >>> 7 ^ c;\n          c = c - d | 0;\n          d = d << 24 ^ d >>> 8 ^ a;\n          a = a - b | 0;\n          me.b = b = b << 20 ^ b >>> 12 ^ c;\n          me.c = c = c - d | 0;\n          me.d = d << 16 ^ c >>> 16 ^ a;\n          return me.a = a - b | 0;\n        };\n        me.a = 0;\n        me.b = 0;\n        me.c = 2654435769 | 0;\n        me.d = 1367130551;\n        if (seed === Math.floor(seed)) {\n          me.a = seed / 4294967296 | 0;\n          me.b = seed | 0;\n        } else {\n          strseed += seed;\n        }\n        for (var k = 0; k < strseed.length + 20; k++) {\n          me.b ^= strseed.charCodeAt(k) | 0;\n          me.next();\n        }\n      }\n      function copy(f, t2) {\n        t2.a = f.a;\n        t2.b = f.b;\n        t2.c = f.c;\n        t2.d = f.d;\n        return t2;\n      }\n      ;\n      function impl(seed, opts) {\n        var xg = new XorGen(seed), state = opts && opts.state, prng = function() {\n          return (xg.next() >>> 0) / 4294967296;\n        };\n        prng.double = function() {\n          do {\n            var top = xg.next() >>> 11, bot = (xg.next() >>> 0) / 4294967296, result = (top + bot) / (1 << 21);\n          } while (result === 0);\n          return result;\n        };\n        prng.int32 = xg.next;\n        prng.quick = prng;\n        if (state) {\n          if (typeof state == \"object\")\n            copy(state, xg);\n          prng.state = function() {\n            return copy(xg, {});\n          };\n        }\n        return prng;\n      }\n      if (module2 && module2.exports) {\n        module2.exports = impl;\n      } else if (define2 && define2.amd) {\n        define2(function() {\n          return impl;\n        });\n      } else {\n        this.tychei = impl;\n      }\n    })(\n      exports,\n      typeof module == \"object\" && module,\n      typeof define == \"function\" && define\n    );\n  }\n});\n\n// (disabled):crypto\nvar require_crypto = __commonJS({\n  \"(disabled):crypto\"() {\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/seedrandom.js\nvar require_seedrandom = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/seedrandom.js\"(exports, module) {\n    (function(global2, pool3, math) {\n      var width = 256, chunks = 6, digits = 52, rngname = \"random\", startdenom = math.pow(width, chunks), significance = math.pow(2, digits), overflow = significance * 2, mask = width - 1, nodecrypto;\n      function seedrandom5(seed, options, callback) {\n        var key = [];\n        options = options == true ? { entropy: true } : options || {};\n        var shortseed = mixkey(flatten4(\n          options.entropy ? [seed, tostring(pool3)] : seed == null ? autoseed() : seed,\n          3\n        ), key);\n        var arc4 = new ARC4(key);\n        var prng = function() {\n          var n2 = arc4.g(chunks), d = startdenom, x = 0;\n          while (n2 < significance) {\n            n2 = (n2 + x) * width;\n            d *= width;\n            x = arc4.g(1);\n          }\n          while (n2 >= overflow) {\n            n2 /= 2;\n            d /= 2;\n            x >>>= 1;\n          }\n          return (n2 + x) / d;\n        };\n        prng.int32 = function() {\n          return arc4.g(4) | 0;\n        };\n        prng.quick = function() {\n          return arc4.g(4) / 4294967296;\n        };\n        prng.double = prng;\n        mixkey(tostring(arc4.S), pool3);\n        return (options.pass || callback || function(prng2, seed2, is_math_call, state) {\n          if (state) {\n            if (state.S) {\n              copy(state, arc4);\n            }\n            prng2.state = function() {\n              return copy(arc4, {});\n            };\n          }\n          if (is_math_call) {\n            math[rngname] = prng2;\n            return seed2;\n          } else\n            return prng2;\n        })(\n          prng,\n          shortseed,\n          \"global\" in options ? options.global : this == math,\n          options.state\n        );\n      }\n      function ARC4(key) {\n        var t2, keylen = key.length, me = this, i2 = 0, j = me.i = me.j = 0, s2 = me.S = [];\n        if (!keylen) {\n          key = [keylen++];\n        }\n        while (i2 < width) {\n          s2[i2] = i2++;\n        }\n        for (i2 = 0; i2 < width; i2++) {\n          s2[i2] = s2[j = mask & j + key[i2 % keylen] + (t2 = s2[i2])];\n          s2[j] = t2;\n        }\n        (me.g = function(count2) {\n          var t3, r2 = 0, i3 = me.i, j2 = me.j, s3 = me.S;\n          while (count2--) {\n            t3 = s3[i3 = mask & i3 + 1];\n            r2 = r2 * width + s3[mask & (s3[i3] = s3[j2 = mask & j2 + t3]) + (s3[j2] = t3)];\n          }\n          me.i = i3;\n          me.j = j2;\n          return r2;\n        })(width);\n      }\n      function copy(f, t2) {\n        t2.i = f.i;\n        t2.j = f.j;\n        t2.S = f.S.slice();\n        return t2;\n      }\n      ;\n      function flatten4(obj, depth) {\n        var result = [], typ = typeof obj, prop;\n        if (depth && typ == \"object\") {\n          for (prop in obj) {\n            try {\n              result.push(flatten4(obj[prop], depth - 1));\n            } catch (e2) {\n            }\n          }\n        }\n        return result.length ? result : typ == \"string\" ? obj : obj + \"\\0\";\n      }\n      function mixkey(seed, key) {\n        var stringseed = seed + \"\", smear, j = 0;\n        while (j < stringseed.length) {\n          key[mask & j] = mask & (smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++);\n        }\n        return tostring(key);\n      }\n      function autoseed() {\n        try {\n          var out;\n          if (nodecrypto && (out = nodecrypto.randomBytes)) {\n            out = out(width);\n          } else {\n            out = new Uint8Array(width);\n            (global2.crypto || global2.msCrypto).getRandomValues(out);\n          }\n          return tostring(out);\n        } catch (e2) {\n          var browser = global2.navigator, plugins = browser && browser.plugins;\n          return [+new Date(), global2, plugins, global2.screen, tostring(pool3)];\n        }\n      }\n      function tostring(a) {\n        return String.fromCharCode.apply(0, a);\n      }\n      mixkey(math.random(), pool3);\n      if (typeof module == \"object\" && module.exports) {\n        module.exports = seedrandom5;\n        try {\n          nodecrypto = require_crypto();\n        } catch (ex) {\n        }\n      } else if (typeof define == \"function\" && define.amd) {\n        define(function() {\n          return seedrandom5;\n        });\n      } else {\n        math[\"seed\" + rngname] = seedrandom5;\n      }\n    })(\n      typeof self !== \"undefined\" ? self : exports,\n      [],\n      Math\n    );\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/index.js\nvar require_seedrandom2 = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/index.js\"(exports, module) {\n    var alea5 = require_alea();\n    var xor128 = require_xor128();\n    var xorwow = require_xorwow();\n    var xorshift7 = require_xorshift7();\n    var xor4096 = require_xor4096();\n    var tychei = require_tychei();\n    var sr = require_seedrandom();\n    sr.alea = alea5;\n    sr.xor128 = xor128;\n    sr.xorwow = xorwow;\n    sr.xorshift7 = xorshift7;\n    sr.xor4096 = xor4096;\n    sr.tychei = tychei;\n    module.exports = sr;\n  }\n});\n\n// (disabled):node_modules/.pnpm/string_decoder@1.3.0/node_modules/string_decoder/lib/string_decoder.js\nvar require_string_decoder = __commonJS({\n  \"(disabled):node_modules/.pnpm/string_decoder@1.3.0/node_modules/string_decoder/lib/string_decoder.js\"() {\n  }\n});\n\n// (disabled):fs\nvar require_fs = __commonJS({\n  \"(disabled):fs\"() {\n  }\n});\n\n// (disabled):path\nvar require_path = __commonJS({\n  \"(disabled):path\"() {\n  }\n});\n\n// (disabled):worker_threads\nvar require_worker_threads = __commonJS({\n  \"(disabled):worker_threads\"() {\n  }\n});\n\n// (disabled):perf_hooks\nvar require_perf_hooks = __commonJS({\n  \"(disabled):perf_hooks\"() {\n  }\n});\n\n// (disabled):os\nvar require_os = __commonJS({\n  \"(disabled):os\"() {\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.js\nvar require_tfjs_backend_wasm_threaded_simd = __commonJS({\n  \"node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.js\"(exports, module) {\n    var WasmBackendModuleThreadedSimd2 = (() => {\n      var _scriptDir = typeof document !== \"undefined\" && document.currentScript ? document.currentScript.src : void 0;\n      if (typeof __filename !== \"undefined\")\n        _scriptDir = _scriptDir || __filename;\n      return function(WasmBackendModuleThreadedSimd3) {\n        WasmBackendModuleThreadedSimd3 = WasmBackendModuleThreadedSimd3 || {};\n        function GROWABLE_HEAP_I8() {\n          if (wasmMemory.buffer != buffer2) {\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n          }\n          return HEAP8;\n        }\n        function GROWABLE_HEAP_U8() {\n          if (wasmMemory.buffer != buffer2) {\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n          }\n          return HEAPU8;\n        }\n        function GROWABLE_HEAP_I16() {\n          if (wasmMemory.buffer != buffer2) {\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n          }\n          return HEAP16;\n        }\n        function GROWABLE_HEAP_U16() {\n          if (wasmMemory.buffer != buffer2) {\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n          }\n          return HEAPU16;\n        }\n        function GROWABLE_HEAP_I32() {\n          if (wasmMemory.buffer != buffer2) {\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n          }\n          return HEAP32;\n        }\n        function GROWABLE_HEAP_F32() {\n          if (wasmMemory.buffer != buffer2) {\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n          }\n          return HEAPF32;\n        }\n        function GROWABLE_HEAP_F64() {\n          if (wasmMemory.buffer != buffer2) {\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n          }\n          return HEAPF64;\n        }\n        var Module = typeof WasmBackendModuleThreadedSimd3 !== \"undefined\" ? WasmBackendModuleThreadedSimd3 : {};\n        var readyPromiseResolve, readyPromiseReject;\n        Module[\"ready\"] = new Promise(function(resolve, reject) {\n          readyPromiseResolve = resolve;\n          readyPromiseReject = reject;\n        });\n        var beforeListeners;\n        if (typeof process !== \"undefined\" && process.listeners) {\n          beforeListeners = { uncaughtException: process.listeners(\"uncaughtException\"), unhandledRejection: process.listeners(\"unhandledRejection\") };\n        }\n        var moduleOverrides = Object.assign({}, Module);\n        var arguments_ = [];\n        var thisProgram = \"./this.program\";\n        var quit_ = (status, toThrow) => {\n          throw toThrow;\n        };\n        var ENVIRONMENT_IS_WEB = typeof window === \"object\";\n        var ENVIRONMENT_IS_WORKER = typeof importScripts === \"function\";\n        var ENVIRONMENT_IS_NODE = typeof process === \"object\" && typeof process.versions === \"object\" && typeof process.versions.node === \"string\";\n        var ENVIRONMENT_IS_PTHREAD = Module[\"ENVIRONMENT_IS_PTHREAD\"] || false;\n        var scriptDirectory = \"\";\n        function locateFile(path) {\n          if (Module[\"locateFile\"]) {\n            return Module[\"locateFile\"](path, scriptDirectory);\n          }\n          return scriptDirectory + path;\n        }\n        var read_, readAsync, readBinary, setWindowTitle;\n        function logExceptionOnExit(e2) {\n          if (e2 instanceof ExitStatus)\n            return;\n          let toLog = e2;\n          err(\"exiting due to exception: \" + toLog);\n        }\n        var fs;\n        var nodePath;\n        var requireNodeFS;\n        if (ENVIRONMENT_IS_NODE) {\n          if (ENVIRONMENT_IS_WORKER) {\n            scriptDirectory = require_path().dirname(scriptDirectory) + \"/\";\n          } else {\n            scriptDirectory = __dirname + \"/\";\n          }\n          requireNodeFS = () => {\n            if (!nodePath) {\n              fs = require_fs();\n              nodePath = require_path();\n            }\n          };\n          read_ = function shell_read(filename, binary) {\n            requireNodeFS();\n            filename = nodePath[\"normalize\"](filename);\n            return fs.readFileSync(filename, binary ? void 0 : \"utf8\");\n          };\n          readBinary = (filename) => {\n            var ret = read_(filename, true);\n            if (!ret.buffer) {\n              ret = new Uint8Array(ret);\n            }\n            return ret;\n          };\n          readAsync = (filename, onload, onerror) => {\n            requireNodeFS();\n            filename = nodePath[\"normalize\"](filename);\n            fs.readFile(filename, function(err2, data) {\n              if (err2)\n                onerror(err2);\n              else\n                onload(data.buffer);\n            });\n          };\n          if (process[\"argv\"].length > 1) {\n            thisProgram = process[\"argv\"][1].replace(/\\\\/g, \"/\");\n          }\n          arguments_ = process[\"argv\"].slice(2);\n          process[\"on\"](\"uncaughtException\", function(ex) {\n            if (!(ex instanceof ExitStatus)) {\n              throw ex;\n            }\n          });\n          process[\"on\"](\"unhandledRejection\", function(reason) {\n            throw reason;\n          });\n          quit_ = (status, toThrow) => {\n            if (keepRuntimeAlive()) {\n              process[\"exitCode\"] = status;\n              throw toThrow;\n            }\n            logExceptionOnExit(toThrow);\n            process[\"exit\"](status);\n          };\n          Module[\"inspect\"] = function() {\n            return \"[Emscripten Module object]\";\n          };\n          let nodeWorkerThreads;\n          try {\n            nodeWorkerThreads = require_worker_threads();\n          } catch (e2) {\n            console.error('The \"worker_threads\" module is not supported in this node.js build - perhaps a newer version is needed?');\n            throw e2;\n          }\n          global.Worker = nodeWorkerThreads.Worker;\n        } else if (ENVIRONMENT_IS_WEB || ENVIRONMENT_IS_WORKER) {\n          if (ENVIRONMENT_IS_WORKER) {\n            scriptDirectory = self.location.href;\n          } else if (typeof document !== \"undefined\" && document.currentScript) {\n            scriptDirectory = document.currentScript.src;\n          }\n          if (typeof _scriptDir !== \"undefined\" && _scriptDir) {\n            scriptDirectory = _scriptDir;\n          }\n          if (scriptDirectory.indexOf(\"blob:\") !== 0) {\n            scriptDirectory = scriptDirectory.substr(0, scriptDirectory.replace(/[?#].*/, \"\").lastIndexOf(\"/\") + 1);\n          } else {\n            scriptDirectory = \"\";\n          }\n          if (!ENVIRONMENT_IS_NODE) {\n            read_ = (url) => {\n              var xhr = new XMLHttpRequest();\n              xhr.open(\"GET\", url, false);\n              xhr.send(null);\n              return xhr.responseText;\n            };\n            if (ENVIRONMENT_IS_WORKER) {\n              readBinary = (url) => {\n                var xhr = new XMLHttpRequest();\n                xhr.open(\"GET\", url, false);\n                xhr.responseType = \"arraybuffer\";\n                xhr.send(null);\n                return new Uint8Array(xhr.response);\n              };\n            }\n            readAsync = (url, onload, onerror) => {\n              var xhr = new XMLHttpRequest();\n              xhr.open(\"GET\", url, true);\n              xhr.responseType = \"arraybuffer\";\n              xhr.onload = () => {\n                if (xhr.status == 200 || xhr.status == 0 && xhr.response) {\n                  onload(xhr.response);\n                  return;\n                }\n                onerror();\n              };\n              xhr.onerror = onerror;\n              xhr.send(null);\n            };\n          }\n          setWindowTitle = (title) => document.title = title;\n        } else {\n        }\n        if (ENVIRONMENT_IS_NODE) {\n          if (typeof performance === \"undefined\") {\n            global.performance = require_perf_hooks().performance;\n          }\n        }\n        var defaultPrint = console.log.bind(console);\n        var defaultPrintErr = console.warn.bind(console);\n        if (ENVIRONMENT_IS_NODE) {\n          requireNodeFS();\n          defaultPrint = (str) => fs.writeSync(1, str + \"\\n\");\n          defaultPrintErr = (str) => fs.writeSync(2, str + \"\\n\");\n        }\n        var out = Module[\"print\"] || defaultPrint;\n        var err = Module[\"printErr\"] || defaultPrintErr;\n        Object.assign(Module, moduleOverrides);\n        moduleOverrides = null;\n        if (Module[\"arguments\"])\n          arguments_ = Module[\"arguments\"];\n        if (Module[\"thisProgram\"])\n          thisProgram = Module[\"thisProgram\"];\n        if (Module[\"quit\"])\n          quit_ = Module[\"quit\"];\n        var POINTER_SIZE = 4;\n        function warnOnce(text) {\n          if (!warnOnce.shown)\n            warnOnce.shown = {};\n          if (!warnOnce.shown[text]) {\n            warnOnce.shown[text] = 1;\n            err(text);\n          }\n        }\n        function convertJsFunctionToWasm(func2, sig) {\n          if (typeof WebAssembly.Function === \"function\") {\n            var typeNames = { \"i\": \"i32\", \"j\": \"i64\", \"f\": \"f32\", \"d\": \"f64\" };\n            var type = { parameters: [], results: sig[0] == \"v\" ? [] : [typeNames[sig[0]]] };\n            for (var i2 = 1; i2 < sig.length; ++i2) {\n              type.parameters.push(typeNames[sig[i2]]);\n            }\n            return new WebAssembly.Function(type, func2);\n          }\n          var typeSection = [1, 0, 1, 96];\n          var sigRet = sig.slice(0, 1);\n          var sigParam = sig.slice(1);\n          var typeCodes = { \"i\": 127, \"j\": 126, \"f\": 125, \"d\": 124 };\n          typeSection.push(sigParam.length);\n          for (var i2 = 0; i2 < sigParam.length; ++i2) {\n            typeSection.push(typeCodes[sigParam[i2]]);\n          }\n          if (sigRet == \"v\") {\n            typeSection.push(0);\n          } else {\n            typeSection = typeSection.concat([1, typeCodes[sigRet]]);\n          }\n          typeSection[1] = typeSection.length - 2;\n          var bytes = new Uint8Array([0, 97, 115, 109, 1, 0, 0, 0].concat(typeSection, [2, 7, 1, 1, 101, 1, 102, 0, 0, 7, 5, 1, 1, 102, 0, 0]));\n          var module2 = new WebAssembly.Module(bytes);\n          var instance = new WebAssembly.Instance(module2, { \"e\": { \"f\": func2 } });\n          var wrappedFunc = instance.exports[\"f\"];\n          return wrappedFunc;\n        }\n        var freeTableIndexes = [];\n        var functionsInTableMap;\n        function getEmptyTableSlot() {\n          if (freeTableIndexes.length) {\n            return freeTableIndexes.pop();\n          }\n          try {\n            wasmTable.grow(1);\n          } catch (err2) {\n            if (!(err2 instanceof RangeError)) {\n              throw err2;\n            }\n            throw \"Unable to grow wasm table. Set ALLOW_TABLE_GROWTH.\";\n          }\n          return wasmTable.length - 1;\n        }\n        function updateTableMap(offset, count2) {\n          for (var i2 = offset; i2 < offset + count2; i2++) {\n            var item = getWasmTableEntry(i2);\n            if (item) {\n              functionsInTableMap.set(item, i2);\n            }\n          }\n        }\n        var tempRet0 = 0;\n        var setTempRet0 = (value) => {\n          tempRet0 = value;\n        };\n        var Atomics_load = Atomics.load;\n        var Atomics_store = Atomics.store;\n        var Atomics_compareExchange = Atomics.compareExchange;\n        var wasmBinary;\n        if (Module[\"wasmBinary\"])\n          wasmBinary = Module[\"wasmBinary\"];\n        var noExitRuntime = Module[\"noExitRuntime\"] || true;\n        if (typeof WebAssembly !== \"object\") {\n          abort(\"no native wasm support detected\");\n        }\n        var wasmMemory;\n        var wasmModule;\n        var ABORT = false;\n        var EXITSTATUS;\n        function assert3(condition, text) {\n          if (!condition) {\n            abort(text);\n          }\n        }\n        function getCFunc(ident) {\n          var func2 = Module[\"_\" + ident];\n          return func2;\n        }\n        function ccall(ident, returnType, argTypes, args, opts) {\n          var toC = { \"string\": function(str) {\n            var ret2 = 0;\n            if (str !== null && str !== void 0 && str !== 0) {\n              var len = (str.length << 2) + 1;\n              ret2 = stackAlloc(len);\n              stringToUTF8(str, ret2, len);\n            }\n            return ret2;\n          }, \"array\": function(arr) {\n            var ret2 = stackAlloc(arr.length);\n            writeArrayToMemory(arr, ret2);\n            return ret2;\n          } };\n          function convertReturnValue(ret2) {\n            if (returnType === \"string\")\n              return UTF8ToString(ret2);\n            if (returnType === \"boolean\")\n              return Boolean(ret2);\n            return ret2;\n          }\n          var func2 = getCFunc(ident);\n          var cArgs = [];\n          var stack2 = 0;\n          if (args) {\n            for (var i2 = 0; i2 < args.length; i2++) {\n              var converter = toC[argTypes[i2]];\n              if (converter) {\n                if (stack2 === 0)\n                  stack2 = stackSave();\n                cArgs[i2] = converter(args[i2]);\n              } else {\n                cArgs[i2] = args[i2];\n              }\n            }\n          }\n          var ret = func2.apply(null, cArgs);\n          function onDone(ret2) {\n            if (stack2 !== 0)\n              stackRestore(stack2);\n            return convertReturnValue(ret2);\n          }\n          ret = onDone(ret);\n          return ret;\n        }\n        function cwrap(ident, returnType, argTypes, opts) {\n          argTypes = argTypes || [];\n          var numericArgs = argTypes.every(function(type) {\n            return type === \"number\";\n          });\n          var numericRet = returnType !== \"string\";\n          if (numericRet && numericArgs && !opts) {\n            return getCFunc(ident);\n          }\n          return function() {\n            return ccall(ident, returnType, argTypes, arguments, opts);\n          };\n        }\n        var ALLOC_STACK = 1;\n        function TextDecoderWrapper(encoding) {\n          var textDecoder = new TextDecoder(encoding);\n          this.decode = (data) => {\n            if (data.buffer instanceof SharedArrayBuffer) {\n              data = new Uint8Array(data);\n            }\n            return textDecoder.decode.call(textDecoder, data);\n          };\n        }\n        var UTF8Decoder = typeof TextDecoder !== \"undefined\" ? new TextDecoderWrapper(\"utf8\") : void 0;\n        function UTF8ArrayToString(heap, idx, maxBytesToRead) {\n          var endIdx = idx + maxBytesToRead;\n          var endPtr = idx;\n          while (heap[endPtr] && !(endPtr >= endIdx))\n            ++endPtr;\n          if (endPtr - idx > 16 && heap.subarray && UTF8Decoder) {\n            return UTF8Decoder.decode(heap.subarray(idx, endPtr));\n          } else {\n            var str = \"\";\n            while (idx < endPtr) {\n              var u0 = heap[idx++];\n              if (!(u0 & 128)) {\n                str += String.fromCharCode(u0);\n                continue;\n              }\n              var u1 = heap[idx++] & 63;\n              if ((u0 & 224) == 192) {\n                str += String.fromCharCode((u0 & 31) << 6 | u1);\n                continue;\n              }\n              var u2 = heap[idx++] & 63;\n              if ((u0 & 240) == 224) {\n                u0 = (u0 & 15) << 12 | u1 << 6 | u2;\n              } else {\n                u0 = (u0 & 7) << 18 | u1 << 12 | u2 << 6 | heap[idx++] & 63;\n              }\n              if (u0 < 65536) {\n                str += String.fromCharCode(u0);\n              } else {\n                var ch = u0 - 65536;\n                str += String.fromCharCode(55296 | ch >> 10, 56320 | ch & 1023);\n              }\n            }\n          }\n          return str;\n        }\n        function UTF8ToString(ptr, maxBytesToRead) {\n          return ptr ? UTF8ArrayToString(GROWABLE_HEAP_U8(), ptr, maxBytesToRead) : \"\";\n        }\n        function stringToUTF8Array(str, heap, outIdx, maxBytesToWrite) {\n          if (!(maxBytesToWrite > 0))\n            return 0;\n          var startIdx = outIdx;\n          var endIdx = outIdx + maxBytesToWrite - 1;\n          for (var i2 = 0; i2 < str.length; ++i2) {\n            var u = str.charCodeAt(i2);\n            if (u >= 55296 && u <= 57343) {\n              var u1 = str.charCodeAt(++i2);\n              u = 65536 + ((u & 1023) << 10) | u1 & 1023;\n            }\n            if (u <= 127) {\n              if (outIdx >= endIdx)\n                break;\n              heap[outIdx++] = u;\n            } else if (u <= 2047) {\n              if (outIdx + 1 >= endIdx)\n                break;\n              heap[outIdx++] = 192 | u >> 6;\n              heap[outIdx++] = 128 | u & 63;\n            } else if (u <= 65535) {\n              if (outIdx + 2 >= endIdx)\n                break;\n              heap[outIdx++] = 224 | u >> 12;\n              heap[outIdx++] = 128 | u >> 6 & 63;\n              heap[outIdx++] = 128 | u & 63;\n            } else {\n              if (outIdx + 3 >= endIdx)\n                break;\n              heap[outIdx++] = 240 | u >> 18;\n              heap[outIdx++] = 128 | u >> 12 & 63;\n              heap[outIdx++] = 128 | u >> 6 & 63;\n              heap[outIdx++] = 128 | u & 63;\n            }\n          }\n          heap[outIdx] = 0;\n          return outIdx - startIdx;\n        }\n        function stringToUTF8(str, outPtr, maxBytesToWrite) {\n          return stringToUTF8Array(str, GROWABLE_HEAP_U8(), outPtr, maxBytesToWrite);\n        }\n        function lengthBytesUTF8(str) {\n          var len = 0;\n          for (var i2 = 0; i2 < str.length; ++i2) {\n            var u = str.charCodeAt(i2);\n            if (u >= 55296 && u <= 57343)\n              u = 65536 + ((u & 1023) << 10) | str.charCodeAt(++i2) & 1023;\n            if (u <= 127)\n              ++len;\n            else if (u <= 2047)\n              len += 2;\n            else if (u <= 65535)\n              len += 3;\n            else\n              len += 4;\n          }\n          return len;\n        }\n        var UTF16Decoder = typeof TextDecoder !== \"undefined\" ? new TextDecoderWrapper(\"utf-16le\") : void 0;\n        function writeArrayToMemory(array2, buffer3) {\n          GROWABLE_HEAP_I8().set(array2, buffer3);\n        }\n        function writeAsciiToMemory(str, buffer3, dontAddNull) {\n          for (var i2 = 0; i2 < str.length; ++i2) {\n            GROWABLE_HEAP_I8()[buffer3++ >> 0] = str.charCodeAt(i2);\n          }\n          if (!dontAddNull)\n            GROWABLE_HEAP_I8()[buffer3 >> 0] = 0;\n        }\n        function alignUp(x, multiple) {\n          if (x % multiple > 0) {\n            x += multiple - x % multiple;\n          }\n          return x;\n        }\n        var buffer2, HEAP8, HEAPU8, HEAP16, HEAPU16, HEAP32, HEAPU32, HEAPF32, HEAPF64;\n        if (ENVIRONMENT_IS_PTHREAD) {\n          buffer2 = Module[\"buffer\"];\n        }\n        function updateGlobalBufferAndViews(buf) {\n          buffer2 = buf;\n          Module[\"HEAP8\"] = HEAP8 = new Int8Array(buf);\n          Module[\"HEAP16\"] = HEAP16 = new Int16Array(buf);\n          Module[\"HEAP32\"] = HEAP32 = new Int32Array(buf);\n          Module[\"HEAPU8\"] = HEAPU8 = new Uint8Array(buf);\n          Module[\"HEAPU16\"] = HEAPU16 = new Uint16Array(buf);\n          Module[\"HEAPU32\"] = HEAPU32 = new Uint32Array(buf);\n          Module[\"HEAPF32\"] = HEAPF32 = new Float32Array(buf);\n          Module[\"HEAPF64\"] = HEAPF64 = new Float64Array(buf);\n        }\n        var INITIAL_MEMORY = Module[\"INITIAL_MEMORY\"] || 16777216;\n        if (ENVIRONMENT_IS_PTHREAD) {\n          wasmMemory = Module[\"wasmMemory\"];\n          buffer2 = Module[\"buffer\"];\n        } else {\n          if (Module[\"wasmMemory\"]) {\n            wasmMemory = Module[\"wasmMemory\"];\n          } else {\n            wasmMemory = new WebAssembly.Memory({ \"initial\": INITIAL_MEMORY / 65536, \"maximum\": 2147483648 / 65536, \"shared\": true });\n            if (!(wasmMemory.buffer instanceof SharedArrayBuffer)) {\n              err(\"requested a shared WebAssembly.Memory but the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag\");\n              if (ENVIRONMENT_IS_NODE) {\n                console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\");\n              }\n              throw Error(\"bad memory\");\n            }\n          }\n        }\n        if (wasmMemory) {\n          buffer2 = wasmMemory.buffer;\n        }\n        INITIAL_MEMORY = buffer2.byteLength;\n        updateGlobalBufferAndViews(buffer2);\n        var wasmTable;\n        var __ATPRERUN__ = [];\n        var __ATINIT__ = [];\n        var __ATEXIT__ = [];\n        var __ATPOSTRUN__ = [];\n        var runtimeInitialized = false;\n        var runtimeExited = false;\n        var runtimeKeepaliveCounter = 0;\n        function keepRuntimeAlive() {\n          return noExitRuntime || runtimeKeepaliveCounter > 0;\n        }\n        function preRun() {\n          if (Module[\"preRun\"]) {\n            if (typeof Module[\"preRun\"] == \"function\")\n              Module[\"preRun\"] = [Module[\"preRun\"]];\n            while (Module[\"preRun\"].length) {\n              addOnPreRun(Module[\"preRun\"].shift());\n            }\n          }\n          callRuntimeCallbacks(__ATPRERUN__);\n        }\n        function initRuntime() {\n          runtimeInitialized = true;\n          if (ENVIRONMENT_IS_PTHREAD)\n            return;\n          callRuntimeCallbacks(__ATINIT__);\n        }\n        function exitRuntime() {\n          if (ENVIRONMENT_IS_PTHREAD)\n            return;\n          PThread.terminateAllThreads();\n          runtimeExited = true;\n        }\n        function postRun() {\n          if (ENVIRONMENT_IS_PTHREAD)\n            return;\n          if (Module[\"postRun\"]) {\n            if (typeof Module[\"postRun\"] == \"function\")\n              Module[\"postRun\"] = [Module[\"postRun\"]];\n            while (Module[\"postRun\"].length) {\n              addOnPostRun(Module[\"postRun\"].shift());\n            }\n          }\n          callRuntimeCallbacks(__ATPOSTRUN__);\n        }\n        function addOnPreRun(cb) {\n          __ATPRERUN__.unshift(cb);\n        }\n        function addOnInit(cb) {\n          __ATINIT__.unshift(cb);\n        }\n        function addOnPostRun(cb) {\n          __ATPOSTRUN__.unshift(cb);\n        }\n        var runDependencies = 0;\n        var runDependencyWatcher = null;\n        var dependenciesFulfilled = null;\n        function addRunDependency(id) {\n          runDependencies++;\n          if (Module[\"monitorRunDependencies\"]) {\n            Module[\"monitorRunDependencies\"](runDependencies);\n          }\n        }\n        function removeRunDependency(id) {\n          runDependencies--;\n          if (Module[\"monitorRunDependencies\"]) {\n            Module[\"monitorRunDependencies\"](runDependencies);\n          }\n          if (runDependencies == 0) {\n            if (runDependencyWatcher !== null) {\n              clearInterval(runDependencyWatcher);\n              runDependencyWatcher = null;\n            }\n            if (dependenciesFulfilled) {\n              var callback = dependenciesFulfilled;\n              dependenciesFulfilled = null;\n              callback();\n            }\n          }\n        }\n        Module[\"preloadedImages\"] = {};\n        Module[\"preloadedAudios\"] = {};\n        function abort(what) {\n          if (ENVIRONMENT_IS_PTHREAD) {\n            postMessage({ \"cmd\": \"onAbort\", \"arg\": what });\n          } else {\n            if (Module[\"onAbort\"]) {\n              Module[\"onAbort\"](what);\n            }\n          }\n          what = \"Aborted(\" + what + \")\";\n          err(what);\n          ABORT = true;\n          EXITSTATUS = 1;\n          what += \". Build with -s ASSERTIONS=1 for more info.\";\n          var e2 = new WebAssembly.RuntimeError(what);\n          readyPromiseReject(e2);\n          throw e2;\n        }\n        var dataURIPrefix = \"data:application/octet-stream;base64,\";\n        function isDataURI(filename) {\n          return filename.startsWith(dataURIPrefix);\n        }\n        function isFileURI(filename) {\n          return filename.startsWith(\"file://\");\n        }\n        var wasmBinaryFile;\n        wasmBinaryFile = \"tfjs-backend-wasm-threaded-simd.wasm\";\n        if (!isDataURI(wasmBinaryFile)) {\n          wasmBinaryFile = locateFile(wasmBinaryFile);\n        }\n        function getBinary(file) {\n          try {\n            if (file == wasmBinaryFile && wasmBinary) {\n              return new Uint8Array(wasmBinary);\n            }\n            if (readBinary) {\n              return readBinary(file);\n            } else {\n              throw \"both async and sync fetching of the wasm failed\";\n            }\n          } catch (err2) {\n            abort(err2);\n          }\n        }\n        function getBinaryPromise() {\n          if (!wasmBinary && (ENVIRONMENT_IS_WEB || ENVIRONMENT_IS_WORKER)) {\n            if (typeof fetch === \"function\" && !isFileURI(wasmBinaryFile)) {\n              return fetch(wasmBinaryFile, { credentials: \"same-origin\" }).then(function(response) {\n                if (!response[\"ok\"]) {\n                  throw \"failed to load wasm binary file at '\" + wasmBinaryFile + \"'\";\n                }\n                return response[\"arrayBuffer\"]();\n              }).catch(function() {\n                return getBinary(wasmBinaryFile);\n              });\n            } else {\n              if (readAsync) {\n                return new Promise(function(resolve, reject) {\n                  readAsync(wasmBinaryFile, function(response) {\n                    resolve(new Uint8Array(response));\n                  }, reject);\n                });\n              }\n            }\n          }\n          return Promise.resolve().then(function() {\n            return getBinary(wasmBinaryFile);\n          });\n        }\n        function createWasm() {\n          var info = { \"env\": asmLibraryArg, \"wasi_snapshot_preview1\": asmLibraryArg };\n          function receiveInstance(instance, module2) {\n            var exports3 = instance.exports;\n            Module[\"asm\"] = exports3;\n            registerTlsInit(Module[\"asm\"][\"emscripten_tls_init\"]);\n            wasmTable = Module[\"asm\"][\"__indirect_function_table\"];\n            addOnInit(Module[\"asm\"][\"__wasm_call_ctors\"]);\n            wasmModule = module2;\n            if (!ENVIRONMENT_IS_PTHREAD) {\n              var numWorkersToLoad = PThread.unusedWorkers.length;\n              PThread.unusedWorkers.forEach(function(w) {\n                PThread.loadWasmModuleToWorker(w, function() {\n                  if (!--numWorkersToLoad)\n                    removeRunDependency(\"wasm-instantiate\");\n                });\n              });\n            }\n          }\n          if (!ENVIRONMENT_IS_PTHREAD) {\n            addRunDependency(\"wasm-instantiate\");\n          }\n          function receiveInstantiationResult(result) {\n            receiveInstance(result[\"instance\"], result[\"module\"]);\n          }\n          function instantiateArrayBuffer(receiver) {\n            return getBinaryPromise().then(function(binary) {\n              return WebAssembly.instantiate(binary, info);\n            }).then(function(instance) {\n              return instance;\n            }).then(receiver, function(reason) {\n              err(\"failed to asynchronously prepare wasm: \" + reason);\n              abort(reason);\n            });\n          }\n          function instantiateAsync() {\n            if (!wasmBinary && typeof WebAssembly.instantiateStreaming === \"function\" && !isDataURI(wasmBinaryFile) && !isFileURI(wasmBinaryFile) && typeof fetch === \"function\") {\n              return fetch(wasmBinaryFile, { credentials: \"same-origin\" }).then(function(response) {\n                var result = WebAssembly.instantiateStreaming(response, info);\n                return result.then(receiveInstantiationResult, function(reason) {\n                  err(\"wasm streaming compile failed: \" + reason);\n                  err(\"falling back to ArrayBuffer instantiation\");\n                  return instantiateArrayBuffer(receiveInstantiationResult);\n                });\n              });\n            } else {\n              return instantiateArrayBuffer(receiveInstantiationResult);\n            }\n          }\n          if (Module[\"instantiateWasm\"]) {\n            try {\n              var exports2 = Module[\"instantiateWasm\"](info, receiveInstance);\n              return exports2;\n            } catch (e2) {\n              err(\"Module.instantiateWasm callback failed with error: \" + e2);\n              return false;\n            }\n          }\n          instantiateAsync().catch(readyPromiseReject);\n          return {};\n        }\n        var tempDouble;\n        var tempI64;\n        var ASM_CONSTS = {};\n        function callRuntimeCallbacks(callbacks2) {\n          while (callbacks2.length > 0) {\n            var callback = callbacks2.shift();\n            if (typeof callback == \"function\") {\n              callback(Module);\n              continue;\n            }\n            var func2 = callback.func;\n            if (typeof func2 === \"number\") {\n              if (callback.arg === void 0) {\n                getWasmTableEntry(func2)();\n              } else {\n                getWasmTableEntry(func2)(callback.arg);\n              }\n            } else {\n              func2(callback.arg === void 0 ? null : callback.arg);\n            }\n          }\n        }\n        function withStackSave(f) {\n          var stack2 = stackSave();\n          var ret = f();\n          stackRestore(stack2);\n          return ret;\n        }\n        function demangle(func2) {\n          return func2;\n        }\n        function demangleAll(text) {\n          var regex = /\\b_Z[\\w\\d_]+/g;\n          return text.replace(regex, function(x) {\n            var y = demangle(x);\n            return x === y ? x : y + \" [\" + x + \"]\";\n          });\n        }\n        function killThread(pthread_ptr) {\n          GROWABLE_HEAP_I32()[pthread_ptr >> 2] = 0;\n          var pthread = PThread.pthreads[pthread_ptr];\n          delete PThread.pthreads[pthread_ptr];\n          pthread.worker.terminate();\n          __emscripten_thread_free_data(pthread_ptr);\n          PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker), 1);\n          pthread.worker.pthread = void 0;\n        }\n        function cancelThread(pthread_ptr) {\n          var pthread = PThread.pthreads[pthread_ptr];\n          pthread.worker.postMessage({ \"cmd\": \"cancel\" });\n        }\n        function cleanupThread(pthread_ptr) {\n          var pthread = PThread.pthreads[pthread_ptr];\n          if (pthread) {\n            GROWABLE_HEAP_I32()[pthread_ptr >> 2] = 0;\n            var worker = pthread.worker;\n            PThread.returnWorkerToPool(worker);\n          }\n        }\n        function _exit(status) {\n          exit(status);\n        }\n        function handleException(e2) {\n          if (e2 instanceof ExitStatus || e2 == \"unwind\") {\n            return EXITSTATUS;\n          }\n          quit_(1, e2);\n        }\n        var PThread = { unusedWorkers: [], runningWorkers: [], tlsInitFunctions: [], init: function() {\n          if (ENVIRONMENT_IS_PTHREAD) {\n            PThread.initWorker();\n          } else {\n            PThread.initMainThread();\n          }\n        }, initMainThread: function() {\n          var pthreadPoolSize = 8;\n          for (var i2 = 0; i2 < pthreadPoolSize; ++i2) {\n            PThread.allocateUnusedWorker();\n          }\n        }, initWorker: function() {\n          noExitRuntime = false;\n        }, pthreads: {}, setExitStatus: function(status) {\n          EXITSTATUS = status;\n        }, terminateAllThreads: function() {\n          for (var t2 in PThread.pthreads) {\n            var pthread = PThread.pthreads[t2];\n            if (pthread && pthread.worker) {\n              PThread.returnWorkerToPool(pthread.worker);\n            }\n          }\n          for (var i2 = 0; i2 < PThread.unusedWorkers.length; ++i2) {\n            var worker = PThread.unusedWorkers[i2];\n            worker.terminate();\n          }\n          PThread.unusedWorkers = [];\n        }, returnWorkerToPool: function(worker) {\n          PThread.runWithoutMainThreadQueuedCalls(function() {\n            delete PThread.pthreads[worker.pthread.threadInfoStruct];\n            PThread.unusedWorkers.push(worker);\n            PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker), 1);\n            __emscripten_thread_free_data(worker.pthread.threadInfoStruct);\n            worker.pthread = void 0;\n          });\n        }, runWithoutMainThreadQueuedCalls: function(func2) {\n          GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls >> 2] = 0;\n          try {\n            func2();\n          } finally {\n            GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls >> 2] = 1;\n          }\n        }, receiveObjectTransfer: function(data) {\n        }, threadInit: function() {\n          for (var i2 in PThread.tlsInitFunctions) {\n            PThread.tlsInitFunctions[i2]();\n          }\n        }, loadWasmModuleToWorker: function(worker, onFinishedLoading) {\n          worker.onmessage = (e2) => {\n            var d = e2[\"data\"];\n            var cmd = d[\"cmd\"];\n            if (worker.pthread)\n              PThread.currentProxiedOperationCallerThread = worker.pthread.threadInfoStruct;\n            if (d[\"targetThread\"] && d[\"targetThread\"] != _pthread_self()) {\n              var thread = PThread.pthreads[d.targetThread];\n              if (thread) {\n                thread.worker.postMessage(d, d[\"transferList\"]);\n              } else {\n                err('Internal error! Worker sent a message \"' + cmd + '\" to target pthread ' + d[\"targetThread\"] + \", but that thread no longer exists!\");\n              }\n              PThread.currentProxiedOperationCallerThread = void 0;\n              return;\n            }\n            if (cmd === \"processQueuedMainThreadWork\") {\n              _emscripten_main_thread_process_queued_calls();\n            } else if (cmd === \"spawnThread\") {\n              spawnThread(d);\n            } else if (cmd === \"cleanupThread\") {\n              cleanupThread(d[\"thread\"]);\n            } else if (cmd === \"killThread\") {\n              killThread(d[\"thread\"]);\n            } else if (cmd === \"cancelThread\") {\n              cancelThread(d[\"thread\"]);\n            } else if (cmd === \"loaded\") {\n              worker.loaded = true;\n              if (onFinishedLoading)\n                onFinishedLoading(worker);\n              if (worker.runPthread) {\n                worker.runPthread();\n                delete worker.runPthread;\n              }\n            } else if (cmd === \"print\") {\n              out(\"Thread \" + d[\"threadId\"] + \": \" + d[\"text\"]);\n            } else if (cmd === \"printErr\") {\n              err(\"Thread \" + d[\"threadId\"] + \": \" + d[\"text\"]);\n            } else if (cmd === \"alert\") {\n              alert(\"Thread \" + d[\"threadId\"] + \": \" + d[\"text\"]);\n            } else if (d.target === \"setimmediate\") {\n              worker.postMessage(d);\n            } else if (cmd === \"onAbort\") {\n              if (Module[\"onAbort\"]) {\n                Module[\"onAbort\"](d[\"arg\"]);\n              }\n            } else {\n              err(\"worker sent an unknown command \" + cmd);\n            }\n            PThread.currentProxiedOperationCallerThread = void 0;\n          };\n          worker.onerror = (e2) => {\n            var message = \"worker sent an error!\";\n            err(message + \" \" + e2.filename + \":\" + e2.lineno + \": \" + e2.message);\n            throw e2;\n          };\n          if (ENVIRONMENT_IS_NODE) {\n            worker.on(\"message\", function(data) {\n              worker.onmessage({ data });\n            });\n            worker.on(\"error\", function(e2) {\n              worker.onerror(e2);\n            });\n            worker.on(\"detachedExit\", function() {\n            });\n          }\n          worker.postMessage({ \"cmd\": \"load\", \"urlOrBlob\": Module[\"mainScriptUrlOrBlob\"] || _scriptDir, \"wasmMemory\": wasmMemory, \"wasmModule\": wasmModule });\n        }, allocateUnusedWorker: function() {\n          var pthreadMainJs = locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");\n          PThread.unusedWorkers.push(new Worker(pthreadMainJs));\n        }, getNewWorker: function() {\n          if (PThread.unusedWorkers.length == 0) {\n            PThread.allocateUnusedWorker();\n            PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0]);\n          }\n          return PThread.unusedWorkers.pop();\n        } };\n        function establishStackSpace() {\n          var pthread_ptr = _pthread_self();\n          var stackTop = GROWABLE_HEAP_I32()[pthread_ptr + 44 >> 2];\n          var stackSize = GROWABLE_HEAP_I32()[pthread_ptr + 48 >> 2];\n          var stackMax = stackTop - stackSize;\n          _emscripten_stack_set_limits(stackTop, stackMax);\n          stackRestore(stackTop);\n        }\n        Module[\"establishStackSpace\"] = establishStackSpace;\n        function exitOnMainThread(returnCode) {\n          if (ENVIRONMENT_IS_PTHREAD)\n            return _emscripten_proxy_to_main_thread_js(1, 0, returnCode);\n          try {\n            _exit(returnCode);\n          } catch (e2) {\n            handleException(e2);\n          }\n        }\n        var wasmTableMirror = [];\n        function getWasmTableEntry(funcPtr) {\n          var func2 = wasmTableMirror[funcPtr];\n          if (!func2) {\n            if (funcPtr >= wasmTableMirror.length)\n              wasmTableMirror.length = funcPtr + 1;\n            wasmTableMirror[funcPtr] = func2 = wasmTable.get(funcPtr);\n          }\n          return func2;\n        }\n        function invokeEntryPoint(ptr, arg) {\n          return getWasmTableEntry(ptr)(arg);\n        }\n        Module[\"invokeEntryPoint\"] = invokeEntryPoint;\n        function jsStackTrace() {\n          var error = new Error();\n          if (!error.stack) {\n            try {\n              throw new Error();\n            } catch (e2) {\n              error = e2;\n            }\n            if (!error.stack) {\n              return \"(no stack trace available)\";\n            }\n          }\n          return error.stack.toString();\n        }\n        function registerTlsInit(tlsInitFunc, moduleExports, metadata) {\n          PThread.tlsInitFunctions.push(tlsInitFunc);\n        }\n        function setWasmTableEntry(idx, func2) {\n          wasmTable.set(idx, func2);\n          wasmTableMirror[idx] = func2;\n        }\n        var _emscripten_get_now;\n        if (ENVIRONMENT_IS_NODE) {\n          _emscripten_get_now = () => {\n            var t2 = process[\"hrtime\"]();\n            return t2[0] * 1e3 + t2[1] / 1e6;\n          };\n        } else if (ENVIRONMENT_IS_PTHREAD) {\n          _emscripten_get_now = () => performance.now() - Module[\"__performance_now_clock_drift\"];\n        } else\n          _emscripten_get_now = () => performance.now();\n        var _emscripten_get_now_is_monotonic = true;\n        function setErrNo(value) {\n          GROWABLE_HEAP_I32()[___errno_location() >> 2] = value;\n          return value;\n        }\n        function _clock_gettime(clk_id, tp) {\n          var now2;\n          if (clk_id === 0) {\n            now2 = Date.now();\n          } else if ((clk_id === 1 || clk_id === 4) && _emscripten_get_now_is_monotonic) {\n            now2 = _emscripten_get_now();\n          } else {\n            setErrNo(28);\n            return -1;\n          }\n          GROWABLE_HEAP_I32()[tp >> 2] = now2 / 1e3 | 0;\n          GROWABLE_HEAP_I32()[tp + 4 >> 2] = now2 % 1e3 * 1e3 * 1e3 | 0;\n          return 0;\n        }\n        function ___clock_gettime(a0, a12) {\n          return _clock_gettime(a0, a12);\n        }\n        function ___emscripten_init_main_thread_js(tb) {\n          __emscripten_thread_init(tb, !ENVIRONMENT_IS_WORKER, 1, !ENVIRONMENT_IS_WEB);\n          PThread.threadInit();\n        }\n        function ___emscripten_thread_cleanup(thread) {\n          if (!ENVIRONMENT_IS_PTHREAD)\n            cleanupThread(thread);\n          else\n            postMessage({ \"cmd\": \"cleanupThread\", \"thread\": thread });\n        }\n        function spawnThread(threadParams) {\n          var worker = PThread.getNewWorker();\n          if (!worker) {\n            return 6;\n          }\n          PThread.runningWorkers.push(worker);\n          var pthread = PThread.pthreads[threadParams.pthread_ptr] = { worker, threadInfoStruct: threadParams.pthread_ptr };\n          worker.pthread = pthread;\n          var msg = { \"cmd\": \"run\", \"start_routine\": threadParams.startRoutine, \"arg\": threadParams.arg, \"threadInfoStruct\": threadParams.pthread_ptr };\n          worker.runPthread = () => {\n            msg.time = performance.now();\n            worker.postMessage(msg, threadParams.transferList);\n          };\n          if (worker.loaded) {\n            worker.runPthread();\n            delete worker.runPthread;\n          }\n          return 0;\n        }\n        function ___pthread_create_js(pthread_ptr, attr, start_routine, arg) {\n          if (typeof SharedArrayBuffer === \"undefined\") {\n            err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");\n            return 6;\n          }\n          var transferList = [];\n          var error = 0;\n          if (ENVIRONMENT_IS_PTHREAD && (transferList.length === 0 || error)) {\n            return _emscripten_sync_run_in_main_thread_4(687865856, pthread_ptr, attr, start_routine, arg);\n          }\n          if (error)\n            return error;\n          var threadParams = { startRoutine: start_routine, pthread_ptr, arg, transferList };\n          if (ENVIRONMENT_IS_PTHREAD) {\n            threadParams.cmd = \"spawnThread\";\n            postMessage(threadParams, transferList);\n            return 0;\n          }\n          return spawnThread(threadParams);\n        }\n        function __emscripten_default_pthread_stack_size() {\n          return 2097152;\n        }\n        function __emscripten_notify_thread_queue(targetThreadId, mainThreadId) {\n          if (targetThreadId == mainThreadId) {\n            postMessage({ \"cmd\": \"processQueuedMainThreadWork\" });\n          } else if (ENVIRONMENT_IS_PTHREAD) {\n            postMessage({ \"targetThread\": targetThreadId, \"cmd\": \"processThreadQueue\" });\n          } else {\n            var pthread = PThread.pthreads[targetThreadId];\n            var worker = pthread && pthread.worker;\n            if (!worker) {\n              return;\n            }\n            worker.postMessage({ \"cmd\": \"processThreadQueue\" });\n          }\n          return 1;\n        }\n        function _abort() {\n          abort(\"\");\n        }\n        function _emscripten_check_blocking_allowed() {\n          if (ENVIRONMENT_IS_NODE)\n            return;\n          if (ENVIRONMENT_IS_WORKER)\n            return;\n          warnOnce(\"Blocking on the main thread is very dangerous, see https://emscripten.org/docs/porting/pthreads.html#blocking-on-the-main-browser-thread\");\n        }\n        function _emscripten_get_heap_max() {\n          return 2147483648;\n        }\n        function _emscripten_memcpy_big(dest, src, num) {\n          GROWABLE_HEAP_U8().copyWithin(dest, src, src + num);\n        }\n        function _emscripten_num_logical_cores() {\n          if (ENVIRONMENT_IS_NODE)\n            return require_os().cpus().length;\n          return navigator[\"hardwareConcurrency\"];\n        }\n        function _emscripten_proxy_to_main_thread_js(index, sync) {\n          var numCallArgs = arguments.length - 2;\n          var outerArgs = arguments;\n          return withStackSave(function() {\n            var serializedNumCallArgs = numCallArgs;\n            var args = stackAlloc(serializedNumCallArgs * 8);\n            var b = args >> 3;\n            for (var i2 = 0; i2 < numCallArgs; i2++) {\n              var arg = outerArgs[2 + i2];\n              GROWABLE_HEAP_F64()[b + i2] = arg;\n            }\n            return _emscripten_run_in_main_runtime_thread_js(index, serializedNumCallArgs, args, sync);\n          });\n        }\n        var _emscripten_receive_on_main_thread_js_callArgs = [];\n        function _emscripten_receive_on_main_thread_js(index, numCallArgs, args) {\n          _emscripten_receive_on_main_thread_js_callArgs.length = numCallArgs;\n          var b = args >> 3;\n          for (var i2 = 0; i2 < numCallArgs; i2++) {\n            _emscripten_receive_on_main_thread_js_callArgs[i2] = GROWABLE_HEAP_F64()[b + i2];\n          }\n          var isEmAsmConst = index < 0;\n          var func2 = !isEmAsmConst ? proxiedFunctionTable[index] : ASM_CONSTS[-index - 1];\n          return func2.apply(null, _emscripten_receive_on_main_thread_js_callArgs);\n        }\n        function emscripten_realloc_buffer(size) {\n          try {\n            wasmMemory.grow(size - buffer2.byteLength + 65535 >>> 16);\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n            return 1;\n          } catch (e2) {\n          }\n        }\n        function _emscripten_resize_heap(requestedSize) {\n          var oldSize = GROWABLE_HEAP_U8().length;\n          requestedSize = requestedSize >>> 0;\n          if (requestedSize <= oldSize) {\n            return false;\n          }\n          var maxHeapSize = _emscripten_get_heap_max();\n          if (requestedSize > maxHeapSize) {\n            return false;\n          }\n          for (var cutDown = 1; cutDown <= 4; cutDown *= 2) {\n            var overGrownHeapSize = oldSize * (1 + 0.2 / cutDown);\n            overGrownHeapSize = Math.min(overGrownHeapSize, requestedSize + 100663296);\n            var newSize = Math.min(maxHeapSize, alignUp(Math.max(requestedSize, overGrownHeapSize), 65536));\n            var replacement = emscripten_realloc_buffer(newSize);\n            if (replacement) {\n              return true;\n            }\n          }\n          return false;\n        }\n        var JSEvents = { inEventHandler: 0, removeAllEventListeners: function() {\n          for (var i2 = JSEvents.eventHandlers.length - 1; i2 >= 0; --i2) {\n            JSEvents._removeHandler(i2);\n          }\n          JSEvents.eventHandlers = [];\n          JSEvents.deferredCalls = [];\n        }, registerRemoveEventListeners: function() {\n          if (!JSEvents.removeEventListenersRegistered) {\n            __ATEXIT__.push(JSEvents.removeAllEventListeners);\n            JSEvents.removeEventListenersRegistered = true;\n          }\n        }, deferredCalls: [], deferCall: function(targetFunction, precedence, argsList) {\n          function arraysHaveEqualContent(arrA, arrB) {\n            if (arrA.length != arrB.length)\n              return false;\n            for (var i3 in arrA) {\n              if (arrA[i3] != arrB[i3])\n                return false;\n            }\n            return true;\n          }\n          for (var i2 in JSEvents.deferredCalls) {\n            var call = JSEvents.deferredCalls[i2];\n            if (call.targetFunction == targetFunction && arraysHaveEqualContent(call.argsList, argsList)) {\n              return;\n            }\n          }\n          JSEvents.deferredCalls.push({ targetFunction, precedence, argsList });\n          JSEvents.deferredCalls.sort(function(x, y) {\n            return x.precedence < y.precedence;\n          });\n        }, removeDeferredCalls: function(targetFunction) {\n          for (var i2 = 0; i2 < JSEvents.deferredCalls.length; ++i2) {\n            if (JSEvents.deferredCalls[i2].targetFunction == targetFunction) {\n              JSEvents.deferredCalls.splice(i2, 1);\n              --i2;\n            }\n          }\n        }, canPerformEventHandlerRequests: function() {\n          return JSEvents.inEventHandler && JSEvents.currentEventHandler.allowsDeferredCalls;\n        }, runDeferredCalls: function() {\n          if (!JSEvents.canPerformEventHandlerRequests()) {\n            return;\n          }\n          for (var i2 = 0; i2 < JSEvents.deferredCalls.length; ++i2) {\n            var call = JSEvents.deferredCalls[i2];\n            JSEvents.deferredCalls.splice(i2, 1);\n            --i2;\n            call.targetFunction.apply(null, call.argsList);\n          }\n        }, eventHandlers: [], removeAllHandlersOnTarget: function(target, eventTypeString) {\n          for (var i2 = 0; i2 < JSEvents.eventHandlers.length; ++i2) {\n            if (JSEvents.eventHandlers[i2].target == target && (!eventTypeString || eventTypeString == JSEvents.eventHandlers[i2].eventTypeString)) {\n              JSEvents._removeHandler(i2--);\n            }\n          }\n        }, _removeHandler: function(i2) {\n          var h = JSEvents.eventHandlers[i2];\n          h.target.removeEventListener(h.eventTypeString, h.eventListenerFunc, h.useCapture);\n          JSEvents.eventHandlers.splice(i2, 1);\n        }, registerOrRemoveHandler: function(eventHandler) {\n          var jsEventHandler = function jsEventHandler2(event) {\n            ++JSEvents.inEventHandler;\n            JSEvents.currentEventHandler = eventHandler;\n            JSEvents.runDeferredCalls();\n            eventHandler.handlerFunc(event);\n            JSEvents.runDeferredCalls();\n            --JSEvents.inEventHandler;\n          };\n          if (eventHandler.callbackfunc) {\n            eventHandler.eventListenerFunc = jsEventHandler;\n            eventHandler.target.addEventListener(eventHandler.eventTypeString, jsEventHandler, eventHandler.useCapture);\n            JSEvents.eventHandlers.push(eventHandler);\n            JSEvents.registerRemoveEventListeners();\n          } else {\n            for (var i2 = 0; i2 < JSEvents.eventHandlers.length; ++i2) {\n              if (JSEvents.eventHandlers[i2].target == eventHandler.target && JSEvents.eventHandlers[i2].eventTypeString == eventHandler.eventTypeString) {\n                JSEvents._removeHandler(i2--);\n              }\n            }\n          }\n        }, queueEventHandlerOnThread_iiii: function(targetThread, eventHandlerFunc, eventTypeId, eventData, userData) {\n          withStackSave(function() {\n            var varargs = stackAlloc(12);\n            GROWABLE_HEAP_I32()[varargs >> 2] = eventTypeId;\n            GROWABLE_HEAP_I32()[varargs + 4 >> 2] = eventData;\n            GROWABLE_HEAP_I32()[varargs + 8 >> 2] = userData;\n            _emscripten_dispatch_to_thread_(targetThread, 637534208, eventHandlerFunc, eventData, varargs);\n          });\n        }, getTargetThreadForEventCallback: function(targetThread) {\n          switch (targetThread) {\n            case 1:\n              return 0;\n            case 2:\n              return PThread.currentProxiedOperationCallerThread;\n            default:\n              return targetThread;\n          }\n        }, getNodeNameForTarget: function(target) {\n          if (!target)\n            return \"\";\n          if (target == window)\n            return \"#window\";\n          if (target == screen)\n            return \"#screen\";\n          return target && target.nodeName ? target.nodeName : \"\";\n        }, fullscreenEnabled: function() {\n          return document.fullscreenEnabled || document.webkitFullscreenEnabled;\n        } };\n        function stringToNewUTF8(jsString) {\n          var length = lengthBytesUTF8(jsString) + 1;\n          var cString = _malloc(length);\n          stringToUTF8(jsString, cString, length);\n          return cString;\n        }\n        function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread, targetCanvas, width, height) {\n          withStackSave(function() {\n            var varargs = stackAlloc(12);\n            var targetCanvasPtr = 0;\n            if (targetCanvas) {\n              targetCanvasPtr = stringToNewUTF8(targetCanvas);\n            }\n            GROWABLE_HEAP_I32()[varargs >> 2] = targetCanvasPtr;\n            GROWABLE_HEAP_I32()[varargs + 4 >> 2] = width;\n            GROWABLE_HEAP_I32()[varargs + 8 >> 2] = height;\n            _emscripten_dispatch_to_thread_(targetThread, 657457152, 0, targetCanvasPtr, varargs);\n          });\n        }\n        function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread, targetCanvas, width, height) {\n          targetCanvas = targetCanvas ? UTF8ToString(targetCanvas) : \"\";\n          _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread, targetCanvas, width, height);\n        }\n        function maybeCStringToJsString(cString) {\n          return cString > 2 ? UTF8ToString(cString) : cString;\n        }\n        var specialHTMLTargets = [0, typeof document !== \"undefined\" ? document : 0, typeof window !== \"undefined\" ? window : 0];\n        function findEventTarget(target) {\n          target = maybeCStringToJsString(target);\n          var domElement = specialHTMLTargets[target] || (typeof document !== \"undefined\" ? document.querySelector(target) : void 0);\n          return domElement;\n        }\n        function findCanvasEventTarget(target) {\n          return findEventTarget(target);\n        }\n        function _emscripten_set_canvas_element_size_calling_thread(target, width, height) {\n          var canvas = findCanvasEventTarget(target);\n          if (!canvas)\n            return -4;\n          if (canvas.canvasSharedPtr) {\n            GROWABLE_HEAP_I32()[canvas.canvasSharedPtr >> 2] = width;\n            GROWABLE_HEAP_I32()[canvas.canvasSharedPtr + 4 >> 2] = height;\n          }\n          if (canvas.offscreenCanvas || !canvas.controlTransferredOffscreen) {\n            if (canvas.offscreenCanvas)\n              canvas = canvas.offscreenCanvas;\n            var autoResizeViewport = false;\n            if (canvas.GLctxObject && canvas.GLctxObject.GLctx) {\n              var prevViewport = canvas.GLctxObject.GLctx.getParameter(2978);\n              autoResizeViewport = prevViewport[0] === 0 && prevViewport[1] === 0 && prevViewport[2] === canvas.width && prevViewport[3] === canvas.height;\n            }\n            canvas.width = width;\n            canvas.height = height;\n            if (autoResizeViewport) {\n              canvas.GLctxObject.GLctx.viewport(0, 0, width, height);\n            }\n          } else if (canvas.canvasSharedPtr) {\n            var targetThread = GROWABLE_HEAP_I32()[canvas.canvasSharedPtr + 8 >> 2];\n            _emscripten_set_offscreencanvas_size_on_target_thread(targetThread, target, width, height);\n            return 1;\n          } else {\n            return -4;\n          }\n          return 0;\n        }\n        function _emscripten_set_canvas_element_size_main_thread(target, width, height) {\n          if (ENVIRONMENT_IS_PTHREAD)\n            return _emscripten_proxy_to_main_thread_js(2, 1, target, width, height);\n          return _emscripten_set_canvas_element_size_calling_thread(target, width, height);\n        }\n        function _emscripten_set_canvas_element_size(target, width, height) {\n          var canvas = findCanvasEventTarget(target);\n          if (canvas) {\n            return _emscripten_set_canvas_element_size_calling_thread(target, width, height);\n          } else {\n            return _emscripten_set_canvas_element_size_main_thread(target, width, height);\n          }\n        }\n        function _emscripten_unwind_to_js_event_loop() {\n          throw \"unwind\";\n        }\n        function __webgl_enable_ANGLE_instanced_arrays(ctx) {\n          var ext = ctx.getExtension(\"ANGLE_instanced_arrays\");\n          if (ext) {\n            ctx[\"vertexAttribDivisor\"] = function(index, divisor) {\n              ext[\"vertexAttribDivisorANGLE\"](index, divisor);\n            };\n            ctx[\"drawArraysInstanced\"] = function(mode, first, count2, primcount) {\n              ext[\"drawArraysInstancedANGLE\"](mode, first, count2, primcount);\n            };\n            ctx[\"drawElementsInstanced\"] = function(mode, count2, type, indices, primcount) {\n              ext[\"drawElementsInstancedANGLE\"](mode, count2, type, indices, primcount);\n            };\n            return 1;\n          }\n        }\n        function __webgl_enable_OES_vertex_array_object(ctx) {\n          var ext = ctx.getExtension(\"OES_vertex_array_object\");\n          if (ext) {\n            ctx[\"createVertexArray\"] = function() {\n              return ext[\"createVertexArrayOES\"]();\n            };\n            ctx[\"deleteVertexArray\"] = function(vao) {\n              ext[\"deleteVertexArrayOES\"](vao);\n            };\n            ctx[\"bindVertexArray\"] = function(vao) {\n              ext[\"bindVertexArrayOES\"](vao);\n            };\n            ctx[\"isVertexArray\"] = function(vao) {\n              return ext[\"isVertexArrayOES\"](vao);\n            };\n            return 1;\n          }\n        }\n        function __webgl_enable_WEBGL_draw_buffers(ctx) {\n          var ext = ctx.getExtension(\"WEBGL_draw_buffers\");\n          if (ext) {\n            ctx[\"drawBuffers\"] = function(n2, bufs) {\n              ext[\"drawBuffersWEBGL\"](n2, bufs);\n            };\n            return 1;\n          }\n        }\n        function __webgl_enable_WEBGL_multi_draw(ctx) {\n          return !!(ctx.multiDrawWebgl = ctx.getExtension(\"WEBGL_multi_draw\"));\n        }\n        var GL = { counter: 1, buffers: [], programs: [], framebuffers: [], renderbuffers: [], textures: [], shaders: [], vaos: [], contexts: {}, offscreenCanvases: {}, queries: [], stringCache: {}, unpackAlignment: 4, recordError: function recordError(errorCode) {\n          if (!GL.lastError) {\n            GL.lastError = errorCode;\n          }\n        }, getNewId: function(table) {\n          var ret = GL.counter++;\n          for (var i2 = table.length; i2 < ret; i2++) {\n            table[i2] = null;\n          }\n          return ret;\n        }, getSource: function(shader, count2, string2, length) {\n          var source = \"\";\n          for (var i2 = 0; i2 < count2; ++i2) {\n            var len = length ? GROWABLE_HEAP_I32()[length + i2 * 4 >> 2] : -1;\n            source += UTF8ToString(GROWABLE_HEAP_I32()[string2 + i2 * 4 >> 2], len < 0 ? void 0 : len);\n          }\n          return source;\n        }, createContext: function(canvas, webGLContextAttributes) {\n          if (!canvas.getContextSafariWebGL2Fixed) {\n            canvas.getContextSafariWebGL2Fixed = canvas.getContext;\n            canvas.getContext = function(ver, attrs) {\n              var gl = canvas.getContextSafariWebGL2Fixed(ver, attrs);\n              return ver == \"webgl\" == gl instanceof WebGLRenderingContext ? gl : null;\n            };\n          }\n          var ctx = canvas.getContext(\"webgl\", webGLContextAttributes);\n          if (!ctx)\n            return 0;\n          var handle = GL.registerContext(ctx, webGLContextAttributes);\n          return handle;\n        }, registerContext: function(ctx, webGLContextAttributes) {\n          var handle = _malloc(8);\n          GROWABLE_HEAP_I32()[handle + 4 >> 2] = _pthread_self();\n          var context = { handle, attributes: webGLContextAttributes, version: webGLContextAttributes.majorVersion, GLctx: ctx };\n          if (ctx.canvas)\n            ctx.canvas.GLctxObject = context;\n          GL.contexts[handle] = context;\n          if (typeof webGLContextAttributes.enableExtensionsByDefault === \"undefined\" || webGLContextAttributes.enableExtensionsByDefault) {\n            GL.initExtensions(context);\n          }\n          return handle;\n        }, makeContextCurrent: function(contextHandle) {\n          GL.currentContext = GL.contexts[contextHandle];\n          Module.ctx = GLctx = GL.currentContext && GL.currentContext.GLctx;\n          return !(contextHandle && !GLctx);\n        }, getContext: function(contextHandle) {\n          return GL.contexts[contextHandle];\n        }, deleteContext: function(contextHandle) {\n          if (GL.currentContext === GL.contexts[contextHandle])\n            GL.currentContext = null;\n          if (typeof JSEvents === \"object\")\n            JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);\n          if (GL.contexts[contextHandle] && GL.contexts[contextHandle].GLctx.canvas)\n            GL.contexts[contextHandle].GLctx.canvas.GLctxObject = void 0;\n          _free(GL.contexts[contextHandle].handle);\n          GL.contexts[contextHandle] = null;\n        }, initExtensions: function(context) {\n          if (!context)\n            context = GL.currentContext;\n          if (context.initExtensionsDone)\n            return;\n          context.initExtensionsDone = true;\n          var GLctx2 = context.GLctx;\n          __webgl_enable_ANGLE_instanced_arrays(GLctx2);\n          __webgl_enable_OES_vertex_array_object(GLctx2);\n          __webgl_enable_WEBGL_draw_buffers(GLctx2);\n          {\n            GLctx2.disjointTimerQueryExt = GLctx2.getExtension(\"EXT_disjoint_timer_query\");\n          }\n          __webgl_enable_WEBGL_multi_draw(GLctx2);\n          var exts = GLctx2.getSupportedExtensions() || [];\n          exts.forEach(function(ext) {\n            if (!ext.includes(\"lose_context\") && !ext.includes(\"debug\")) {\n              GLctx2.getExtension(ext);\n            }\n          });\n        } };\n        var __emscripten_webgl_power_preferences = [\"default\", \"low-power\", \"high-performance\"];\n        function _emscripten_webgl_do_create_context(target, attributes) {\n          var a = attributes >> 2;\n          var powerPreference = GROWABLE_HEAP_I32()[a + (24 >> 2)];\n          var contextAttributes = { \"alpha\": !!GROWABLE_HEAP_I32()[a + (0 >> 2)], \"depth\": !!GROWABLE_HEAP_I32()[a + (4 >> 2)], \"stencil\": !!GROWABLE_HEAP_I32()[a + (8 >> 2)], \"antialias\": !!GROWABLE_HEAP_I32()[a + (12 >> 2)], \"premultipliedAlpha\": !!GROWABLE_HEAP_I32()[a + (16 >> 2)], \"preserveDrawingBuffer\": !!GROWABLE_HEAP_I32()[a + (20 >> 2)], \"powerPreference\": __emscripten_webgl_power_preferences[powerPreference], \"failIfMajorPerformanceCaveat\": !!GROWABLE_HEAP_I32()[a + (28 >> 2)], majorVersion: GROWABLE_HEAP_I32()[a + (32 >> 2)], minorVersion: GROWABLE_HEAP_I32()[a + (36 >> 2)], enableExtensionsByDefault: GROWABLE_HEAP_I32()[a + (40 >> 2)], explicitSwapControl: GROWABLE_HEAP_I32()[a + (44 >> 2)], proxyContextToMainThread: GROWABLE_HEAP_I32()[a + (48 >> 2)], renderViaOffscreenBackBuffer: GROWABLE_HEAP_I32()[a + (52 >> 2)] };\n          var canvas = findCanvasEventTarget(target);\n          if (!canvas) {\n            return 0;\n          }\n          if (contextAttributes.explicitSwapControl) {\n            return 0;\n          }\n          var contextHandle = GL.createContext(canvas, contextAttributes);\n          return contextHandle;\n        }\n        function _emscripten_webgl_create_context(a0, a12) {\n          return _emscripten_webgl_do_create_context(a0, a12);\n        }\n        var SYSCALLS = { mappings: {}, buffers: [null, [], []], printChar: function(stream, curr) {\n          var buffer3 = SYSCALLS.buffers[stream];\n          if (curr === 0 || curr === 10) {\n            (stream === 1 ? out : err)(UTF8ArrayToString(buffer3, 0));\n            buffer3.length = 0;\n          } else {\n            buffer3.push(curr);\n          }\n        }, varargs: void 0, get: function() {\n          SYSCALLS.varargs += 4;\n          var ret = GROWABLE_HEAP_I32()[SYSCALLS.varargs - 4 >> 2];\n          return ret;\n        }, getStr: function(ptr) {\n          var ret = UTF8ToString(ptr);\n          return ret;\n        }, get64: function(low, high) {\n          return low;\n        } };\n        function _fd_close(fd) {\n          if (ENVIRONMENT_IS_PTHREAD)\n            return _emscripten_proxy_to_main_thread_js(3, 1, fd);\n          return 0;\n        }\n        function _fd_seek(fd, offset_low, offset_high, whence, newOffset) {\n          if (ENVIRONMENT_IS_PTHREAD)\n            return _emscripten_proxy_to_main_thread_js(4, 1, fd, offset_low, offset_high, whence, newOffset);\n        }\n        function _fd_write(fd, iov, iovcnt, pnum) {\n          if (ENVIRONMENT_IS_PTHREAD)\n            return _emscripten_proxy_to_main_thread_js(5, 1, fd, iov, iovcnt, pnum);\n          var num = 0;\n          for (var i2 = 0; i2 < iovcnt; i2++) {\n            var ptr = GROWABLE_HEAP_I32()[iov >> 2];\n            var len = GROWABLE_HEAP_I32()[iov + 4 >> 2];\n            iov += 8;\n            for (var j = 0; j < len; j++) {\n              SYSCALLS.printChar(fd, GROWABLE_HEAP_U8()[ptr + j]);\n            }\n            num += len;\n          }\n          GROWABLE_HEAP_I32()[pnum >> 2] = num;\n          return 0;\n        }\n        function _setTempRet0(val) {\n          setTempRet0(val);\n        }\n        PThread.init();\n        var GLctx;\n        var proxiedFunctionTable = [null, exitOnMainThread, _emscripten_set_canvas_element_size_main_thread, _fd_close, _fd_seek, _fd_write];\n        var ASSERTIONS = false;\n        var asmLibraryArg = { \"__clock_gettime\": ___clock_gettime, \"__emscripten_init_main_thread_js\": ___emscripten_init_main_thread_js, \"__emscripten_thread_cleanup\": ___emscripten_thread_cleanup, \"__pthread_create_js\": ___pthread_create_js, \"_emscripten_default_pthread_stack_size\": __emscripten_default_pthread_stack_size, \"_emscripten_notify_thread_queue\": __emscripten_notify_thread_queue, \"abort\": _abort, \"emscripten_check_blocking_allowed\": _emscripten_check_blocking_allowed, \"emscripten_get_heap_max\": _emscripten_get_heap_max, \"emscripten_get_now\": _emscripten_get_now, \"emscripten_memcpy_big\": _emscripten_memcpy_big, \"emscripten_num_logical_cores\": _emscripten_num_logical_cores, \"emscripten_receive_on_main_thread_js\": _emscripten_receive_on_main_thread_js, \"emscripten_resize_heap\": _emscripten_resize_heap, \"emscripten_set_canvas_element_size\": _emscripten_set_canvas_element_size, \"emscripten_unwind_to_js_event_loop\": _emscripten_unwind_to_js_event_loop, \"emscripten_webgl_create_context\": _emscripten_webgl_create_context, \"exit\": _exit, \"fd_close\": _fd_close, \"fd_seek\": _fd_seek, \"fd_write\": _fd_write, \"memory\": wasmMemory || Module[\"wasmMemory\"], \"setTempRet0\": _setTempRet0 };\n        var asm = createWasm();\n        var ___wasm_call_ctors = Module[\"___wasm_call_ctors\"] = function() {\n          return (___wasm_call_ctors = Module[\"___wasm_call_ctors\"] = Module[\"asm\"][\"__wasm_call_ctors\"]).apply(null, arguments);\n        };\n        var _init = Module[\"_init\"] = function() {\n          return (_init = Module[\"_init\"] = Module[\"asm\"][\"init\"]).apply(null, arguments);\n        };\n        var _init_with_threads_count = Module[\"_init_with_threads_count\"] = function() {\n          return (_init_with_threads_count = Module[\"_init_with_threads_count\"] = Module[\"asm\"][\"init_with_threads_count\"]).apply(null, arguments);\n        };\n        var _get_threads_count = Module[\"_get_threads_count\"] = function() {\n          return (_get_threads_count = Module[\"_get_threads_count\"] = Module[\"asm\"][\"get_threads_count\"]).apply(null, arguments);\n        };\n        var _register_tensor = Module[\"_register_tensor\"] = function() {\n          return (_register_tensor = Module[\"_register_tensor\"] = Module[\"asm\"][\"register_tensor\"]).apply(null, arguments);\n        };\n        var _dispose_data = Module[\"_dispose_data\"] = function() {\n          return (_dispose_data = Module[\"_dispose_data\"] = Module[\"asm\"][\"dispose_data\"]).apply(null, arguments);\n        };\n        var _dispose = Module[\"_dispose\"] = function() {\n          return (_dispose = Module[\"_dispose\"] = Module[\"asm\"][\"dispose\"]).apply(null, arguments);\n        };\n        var _Abs = Module[\"_Abs\"] = function() {\n          return (_Abs = Module[\"_Abs\"] = Module[\"asm\"][\"Abs\"]).apply(null, arguments);\n        };\n        var _Add = Module[\"_Add\"] = function() {\n          return (_Add = Module[\"_Add\"] = Module[\"asm\"][\"Add\"]).apply(null, arguments);\n        };\n        var _AddN = Module[\"_AddN\"] = function() {\n          return (_AddN = Module[\"_AddN\"] = Module[\"asm\"][\"AddN\"]).apply(null, arguments);\n        };\n        var _All = Module[\"_All\"] = function() {\n          return (_All = Module[\"_All\"] = Module[\"asm\"][\"All\"]).apply(null, arguments);\n        };\n        var _Any = Module[\"_Any\"] = function() {\n          return (_Any = Module[\"_Any\"] = Module[\"asm\"][\"Any\"]).apply(null, arguments);\n        };\n        var _ArgMax = Module[\"_ArgMax\"] = function() {\n          return (_ArgMax = Module[\"_ArgMax\"] = Module[\"asm\"][\"ArgMax\"]).apply(null, arguments);\n        };\n        var _AvgPool = Module[\"_AvgPool\"] = function() {\n          return (_AvgPool = Module[\"_AvgPool\"] = Module[\"asm\"][\"AvgPool\"]).apply(null, arguments);\n        };\n        var _BatchMatMul = Module[\"_BatchMatMul\"] = function() {\n          return (_BatchMatMul = Module[\"_BatchMatMul\"] = Module[\"asm\"][\"BatchMatMul\"]).apply(null, arguments);\n        };\n        var _Ceil = Module[\"_Ceil\"] = function() {\n          return (_Ceil = Module[\"_Ceil\"] = Module[\"asm\"][\"Ceil\"]).apply(null, arguments);\n        };\n        var _ClipByValue = Module[\"_ClipByValue\"] = function() {\n          return (_ClipByValue = Module[\"_ClipByValue\"] = Module[\"asm\"][\"ClipByValue\"]).apply(null, arguments);\n        };\n        var _Conv2D = Module[\"_Conv2D\"] = function() {\n          return (_Conv2D = Module[\"_Conv2D\"] = Module[\"asm\"][\"Conv2D\"]).apply(null, arguments);\n        };\n        var _Conv2DBackpropInput = Module[\"_Conv2DBackpropInput\"] = function() {\n          return (_Conv2DBackpropInput = Module[\"_Conv2DBackpropInput\"] = Module[\"asm\"][\"Conv2DBackpropInput\"]).apply(null, arguments);\n        };\n        var _Cos = Module[\"_Cos\"] = function() {\n          return (_Cos = Module[\"_Cos\"] = Module[\"asm\"][\"Cos\"]).apply(null, arguments);\n        };\n        var _Cosh = Module[\"_Cosh\"] = function() {\n          return (_Cosh = Module[\"_Cosh\"] = Module[\"asm\"][\"Cosh\"]).apply(null, arguments);\n        };\n        var _CropAndResize = Module[\"_CropAndResize\"] = function() {\n          return (_CropAndResize = Module[\"_CropAndResize\"] = Module[\"asm\"][\"CropAndResize\"]).apply(null, arguments);\n        };\n        var _Cumprod = Module[\"_Cumprod\"] = function() {\n          return (_Cumprod = Module[\"_Cumprod\"] = Module[\"asm\"][\"Cumprod\"]).apply(null, arguments);\n        };\n        var _Cumsum = Module[\"_Cumsum\"] = function() {\n          return (_Cumsum = Module[\"_Cumsum\"] = Module[\"asm\"][\"Cumsum\"]).apply(null, arguments);\n        };\n        var _DepthToSpace = Module[\"_DepthToSpace\"] = function() {\n          return (_DepthToSpace = Module[\"_DepthToSpace\"] = Module[\"asm\"][\"DepthToSpace\"]).apply(null, arguments);\n        };\n        var _DepthwiseConv2dNative = Module[\"_DepthwiseConv2dNative\"] = function() {\n          return (_DepthwiseConv2dNative = Module[\"_DepthwiseConv2dNative\"] = Module[\"asm\"][\"DepthwiseConv2dNative\"]).apply(null, arguments);\n        };\n        var _Elu = Module[\"_Elu\"] = function() {\n          return (_Elu = Module[\"_Elu\"] = Module[\"asm\"][\"Elu\"]).apply(null, arguments);\n        };\n        var _Equal = Module[\"_Equal\"] = function() {\n          return (_Equal = Module[\"_Equal\"] = Module[\"asm\"][\"Equal\"]).apply(null, arguments);\n        };\n        var _Exp = Module[\"_Exp\"] = function() {\n          return (_Exp = Module[\"_Exp\"] = Module[\"asm\"][\"Exp\"]).apply(null, arguments);\n        };\n        var _FlipLeftRight = Module[\"_FlipLeftRight\"] = function() {\n          return (_FlipLeftRight = Module[\"_FlipLeftRight\"] = Module[\"asm\"][\"FlipLeftRight\"]).apply(null, arguments);\n        };\n        var _Floor = Module[\"_Floor\"] = function() {\n          return (_Floor = Module[\"_Floor\"] = Module[\"asm\"][\"Floor\"]).apply(null, arguments);\n        };\n        var _FloorDiv = Module[\"_FloorDiv\"] = function() {\n          return (_FloorDiv = Module[\"_FloorDiv\"] = Module[\"asm\"][\"FloorDiv\"]).apply(null, arguments);\n        };\n        var _FusedBatchNorm = Module[\"_FusedBatchNorm\"] = function() {\n          return (_FusedBatchNorm = Module[\"_FusedBatchNorm\"] = Module[\"asm\"][\"FusedBatchNorm\"]).apply(null, arguments);\n        };\n        var _FusedConv2D = Module[\"_FusedConv2D\"] = function() {\n          return (_FusedConv2D = Module[\"_FusedConv2D\"] = Module[\"asm\"][\"FusedConv2D\"]).apply(null, arguments);\n        };\n        var _FusedDepthwiseConv2D = Module[\"_FusedDepthwiseConv2D\"] = function() {\n          return (_FusedDepthwiseConv2D = Module[\"_FusedDepthwiseConv2D\"] = Module[\"asm\"][\"FusedDepthwiseConv2D\"]).apply(null, arguments);\n        };\n        var _Gather = Module[\"_Gather\"] = function() {\n          return (_Gather = Module[\"_Gather\"] = Module[\"asm\"][\"Gather\"]).apply(null, arguments);\n        };\n        var _GatherNd = Module[\"_GatherNd\"] = function() {\n          return (_GatherNd = Module[\"_GatherNd\"] = Module[\"asm\"][\"GatherNd\"]).apply(null, arguments);\n        };\n        var _Greater = Module[\"_Greater\"] = function() {\n          return (_Greater = Module[\"_Greater\"] = Module[\"asm\"][\"Greater\"]).apply(null, arguments);\n        };\n        var _GreaterEqual = Module[\"_GreaterEqual\"] = function() {\n          return (_GreaterEqual = Module[\"_GreaterEqual\"] = Module[\"asm\"][\"GreaterEqual\"]).apply(null, arguments);\n        };\n        var _LeakyRelu = Module[\"_LeakyRelu\"] = function() {\n          return (_LeakyRelu = Module[\"_LeakyRelu\"] = Module[\"asm\"][\"LeakyRelu\"]).apply(null, arguments);\n        };\n        var _Less = Module[\"_Less\"] = function() {\n          return (_Less = Module[\"_Less\"] = Module[\"asm\"][\"Less\"]).apply(null, arguments);\n        };\n        var _LessEqual = Module[\"_LessEqual\"] = function() {\n          return (_LessEqual = Module[\"_LessEqual\"] = Module[\"asm\"][\"LessEqual\"]).apply(null, arguments);\n        };\n        var _Log = Module[\"_Log\"] = function() {\n          return (_Log = Module[\"_Log\"] = Module[\"asm\"][\"Log\"]).apply(null, arguments);\n        };\n        var _LogicalAnd = Module[\"_LogicalAnd\"] = function() {\n          return (_LogicalAnd = Module[\"_LogicalAnd\"] = Module[\"asm\"][\"LogicalAnd\"]).apply(null, arguments);\n        };\n        var _LogicalNot = Module[\"_LogicalNot\"] = function() {\n          return (_LogicalNot = Module[\"_LogicalNot\"] = Module[\"asm\"][\"LogicalNot\"]).apply(null, arguments);\n        };\n        var _LogicalOr = Module[\"_LogicalOr\"] = function() {\n          return (_LogicalOr = Module[\"_LogicalOr\"] = Module[\"asm\"][\"LogicalOr\"]).apply(null, arguments);\n        };\n        var _LogicalXor = Module[\"_LogicalXor\"] = function() {\n          return (_LogicalXor = Module[\"_LogicalXor\"] = Module[\"asm\"][\"LogicalXor\"]).apply(null, arguments);\n        };\n        var _Max = Module[\"_Max\"] = function() {\n          return (_Max = Module[\"_Max\"] = Module[\"asm\"][\"Max\"]).apply(null, arguments);\n        };\n        var _MaxPool = Module[\"_MaxPool\"] = function() {\n          return (_MaxPool = Module[\"_MaxPool\"] = Module[\"asm\"][\"MaxPool\"]).apply(null, arguments);\n        };\n        var _Maximum = Module[\"_Maximum\"] = function() {\n          return (_Maximum = Module[\"_Maximum\"] = Module[\"asm\"][\"Maximum\"]).apply(null, arguments);\n        };\n        var _Mean = Module[\"_Mean\"] = function() {\n          return (_Mean = Module[\"_Mean\"] = Module[\"asm\"][\"Mean\"]).apply(null, arguments);\n        };\n        var _Min = Module[\"_Min\"] = function() {\n          return (_Min = Module[\"_Min\"] = Module[\"asm\"][\"Min\"]).apply(null, arguments);\n        };\n        var _Minimum = Module[\"_Minimum\"] = function() {\n          return (_Minimum = Module[\"_Minimum\"] = Module[\"asm\"][\"Minimum\"]).apply(null, arguments);\n        };\n        var _MirrorPad = Module[\"_MirrorPad\"] = function() {\n          return (_MirrorPad = Module[\"_MirrorPad\"] = Module[\"asm\"][\"MirrorPad\"]).apply(null, arguments);\n        };\n        var _Multiply = Module[\"_Multiply\"] = function() {\n          return (_Multiply = Module[\"_Multiply\"] = Module[\"asm\"][\"Multiply\"]).apply(null, arguments);\n        };\n        var _Neg = Module[\"_Neg\"] = function() {\n          return (_Neg = Module[\"_Neg\"] = Module[\"asm\"][\"Neg\"]).apply(null, arguments);\n        };\n        var _NonMaxSuppressionV3 = Module[\"_NonMaxSuppressionV3\"] = function() {\n          return (_NonMaxSuppressionV3 = Module[\"_NonMaxSuppressionV3\"] = Module[\"asm\"][\"NonMaxSuppressionV3\"]).apply(null, arguments);\n        };\n        var _NonMaxSuppressionV4 = Module[\"_NonMaxSuppressionV4\"] = function() {\n          return (_NonMaxSuppressionV4 = Module[\"_NonMaxSuppressionV4\"] = Module[\"asm\"][\"NonMaxSuppressionV4\"]).apply(null, arguments);\n        };\n        var _NonMaxSuppressionV5 = Module[\"_NonMaxSuppressionV5\"] = function() {\n          return (_NonMaxSuppressionV5 = Module[\"_NonMaxSuppressionV5\"] = Module[\"asm\"][\"NonMaxSuppressionV5\"]).apply(null, arguments);\n        };\n        var _NotEqual = Module[\"_NotEqual\"] = function() {\n          return (_NotEqual = Module[\"_NotEqual\"] = Module[\"asm\"][\"NotEqual\"]).apply(null, arguments);\n        };\n        var _OneHot = Module[\"_OneHot\"] = function() {\n          return (_OneHot = Module[\"_OneHot\"] = Module[\"asm\"][\"OneHot\"]).apply(null, arguments);\n        };\n        var _PadV2 = Module[\"_PadV2\"] = function() {\n          return (_PadV2 = Module[\"_PadV2\"] = Module[\"asm\"][\"PadV2\"]).apply(null, arguments);\n        };\n        var _Pow = Module[\"_Pow\"] = function() {\n          return (_Pow = Module[\"_Pow\"] = Module[\"asm\"][\"Pow\"]).apply(null, arguments);\n        };\n        var _Prelu = Module[\"_Prelu\"] = function() {\n          return (_Prelu = Module[\"_Prelu\"] = Module[\"asm\"][\"Prelu\"]).apply(null, arguments);\n        };\n        var _Prod = Module[\"_Prod\"] = function() {\n          return (_Prod = Module[\"_Prod\"] = Module[\"asm\"][\"Prod\"]).apply(null, arguments);\n        };\n        var _RealDiv = Module[\"_RealDiv\"] = function() {\n          return (_RealDiv = Module[\"_RealDiv\"] = Module[\"asm\"][\"RealDiv\"]).apply(null, arguments);\n        };\n        var _Relu = Module[\"_Relu\"] = function() {\n          return (_Relu = Module[\"_Relu\"] = Module[\"asm\"][\"Relu\"]).apply(null, arguments);\n        };\n        var _Relu6 = Module[\"_Relu6\"] = function() {\n          return (_Relu6 = Module[\"_Relu6\"] = Module[\"asm\"][\"Relu6\"]).apply(null, arguments);\n        };\n        var _ResizeBilinear = Module[\"_ResizeBilinear\"] = function() {\n          return (_ResizeBilinear = Module[\"_ResizeBilinear\"] = Module[\"asm\"][\"ResizeBilinear\"]).apply(null, arguments);\n        };\n        var _ResizeNearestNeighbor = Module[\"_ResizeNearestNeighbor\"] = function() {\n          return (_ResizeNearestNeighbor = Module[\"_ResizeNearestNeighbor\"] = Module[\"asm\"][\"ResizeNearestNeighbor\"]).apply(null, arguments);\n        };\n        var _Reverse = Module[\"_Reverse\"] = function() {\n          return (_Reverse = Module[\"_Reverse\"] = Module[\"asm\"][\"Reverse\"]).apply(null, arguments);\n        };\n        var _RotateWithOffset = Module[\"_RotateWithOffset\"] = function() {\n          return (_RotateWithOffset = Module[\"_RotateWithOffset\"] = Module[\"asm\"][\"RotateWithOffset\"]).apply(null, arguments);\n        };\n        var _Round = Module[\"_Round\"] = function() {\n          return (_Round = Module[\"_Round\"] = Module[\"asm\"][\"Round\"]).apply(null, arguments);\n        };\n        var _Rsqrt = Module[\"_Rsqrt\"] = function() {\n          return (_Rsqrt = Module[\"_Rsqrt\"] = Module[\"asm\"][\"Rsqrt\"]).apply(null, arguments);\n        };\n        var _ScatterNd = Module[\"_ScatterNd\"] = function() {\n          return (_ScatterNd = Module[\"_ScatterNd\"] = Module[\"asm\"][\"ScatterNd\"]).apply(null, arguments);\n        };\n        var _SelectV2 = Module[\"_SelectV2\"] = function() {\n          return (_SelectV2 = Module[\"_SelectV2\"] = Module[\"asm\"][\"SelectV2\"]).apply(null, arguments);\n        };\n        var _Sigmoid = Module[\"_Sigmoid\"] = function() {\n          return (_Sigmoid = Module[\"_Sigmoid\"] = Module[\"asm\"][\"Sigmoid\"]).apply(null, arguments);\n        };\n        var _Sin = Module[\"_Sin\"] = function() {\n          return (_Sin = Module[\"_Sin\"] = Module[\"asm\"][\"Sin\"]).apply(null, arguments);\n        };\n        var _Softmax = Module[\"_Softmax\"] = function() {\n          return (_Softmax = Module[\"_Softmax\"] = Module[\"asm\"][\"Softmax\"]).apply(null, arguments);\n        };\n        var _SparseFillEmptyRows = Module[\"_SparseFillEmptyRows\"] = function() {\n          return (_SparseFillEmptyRows = Module[\"_SparseFillEmptyRows\"] = Module[\"asm\"][\"SparseFillEmptyRows\"]).apply(null, arguments);\n        };\n        var _SparseReshape = Module[\"_SparseReshape\"] = function() {\n          return (_SparseReshape = Module[\"_SparseReshape\"] = Module[\"asm\"][\"SparseReshape\"]).apply(null, arguments);\n        };\n        var _SparseSegmentReduction = Module[\"_SparseSegmentReduction\"] = function() {\n          return (_SparseSegmentReduction = Module[\"_SparseSegmentReduction\"] = Module[\"asm\"][\"SparseSegmentReduction\"]).apply(null, arguments);\n        };\n        var _Sqrt = Module[\"_Sqrt\"] = function() {\n          return (_Sqrt = Module[\"_Sqrt\"] = Module[\"asm\"][\"Sqrt\"]).apply(null, arguments);\n        };\n        var _Square = Module[\"_Square\"] = function() {\n          return (_Square = Module[\"_Square\"] = Module[\"asm\"][\"Square\"]).apply(null, arguments);\n        };\n        var _SquaredDifference = Module[\"_SquaredDifference\"] = function() {\n          return (_SquaredDifference = Module[\"_SquaredDifference\"] = Module[\"asm\"][\"SquaredDifference\"]).apply(null, arguments);\n        };\n        var _Step = Module[\"_Step\"] = function() {\n          return (_Step = Module[\"_Step\"] = Module[\"asm\"][\"Step\"]).apply(null, arguments);\n        };\n        var _StridedSlice = Module[\"_StridedSlice\"] = function() {\n          return (_StridedSlice = Module[\"_StridedSlice\"] = Module[\"asm\"][\"StridedSlice\"]).apply(null, arguments);\n        };\n        var _Sub = Module[\"_Sub\"] = function() {\n          return (_Sub = Module[\"_Sub\"] = Module[\"asm\"][\"Sub\"]).apply(null, arguments);\n        };\n        var _Sum = Module[\"_Sum\"] = function() {\n          return (_Sum = Module[\"_Sum\"] = Module[\"asm\"][\"Sum\"]).apply(null, arguments);\n        };\n        var _Tan = Module[\"_Tan\"] = function() {\n          return (_Tan = Module[\"_Tan\"] = Module[\"asm\"][\"Tan\"]).apply(null, arguments);\n        };\n        var _Tanh = Module[\"_Tanh\"] = function() {\n          return (_Tanh = Module[\"_Tanh\"] = Module[\"asm\"][\"Tanh\"]).apply(null, arguments);\n        };\n        var _Tile = Module[\"_Tile\"] = function() {\n          return (_Tile = Module[\"_Tile\"] = Module[\"asm\"][\"Tile\"]).apply(null, arguments);\n        };\n        var _TopK = Module[\"_TopK\"] = function() {\n          return (_TopK = Module[\"_TopK\"] = Module[\"asm\"][\"TopK\"]).apply(null, arguments);\n        };\n        var _Transform = Module[\"_Transform\"] = function() {\n          return (_Transform = Module[\"_Transform\"] = Module[\"asm\"][\"Transform\"]).apply(null, arguments);\n        };\n        var _Transpose = Module[\"_Transpose\"] = function() {\n          return (_Transpose = Module[\"_Transpose\"] = Module[\"asm\"][\"Transpose\"]).apply(null, arguments);\n        };\n        var __FusedMatMul = Module[\"__FusedMatMul\"] = function() {\n          return (__FusedMatMul = Module[\"__FusedMatMul\"] = Module[\"asm\"][\"_FusedMatMul\"]).apply(null, arguments);\n        };\n        var _malloc = Module[\"_malloc\"] = function() {\n          return (_malloc = Module[\"_malloc\"] = Module[\"asm\"][\"malloc\"]).apply(null, arguments);\n        };\n        var _free = Module[\"_free\"] = function() {\n          return (_free = Module[\"_free\"] = Module[\"asm\"][\"free\"]).apply(null, arguments);\n        };\n        var _emscripten_tls_init = Module[\"_emscripten_tls_init\"] = function() {\n          return (_emscripten_tls_init = Module[\"_emscripten_tls_init\"] = Module[\"asm\"][\"emscripten_tls_init\"]).apply(null, arguments);\n        };\n        var ___errno_location = Module[\"___errno_location\"] = function() {\n          return (___errno_location = Module[\"___errno_location\"] = Module[\"asm\"][\"__errno_location\"]).apply(null, arguments);\n        };\n        var _pthread_self = Module[\"_pthread_self\"] = function() {\n          return (_pthread_self = Module[\"_pthread_self\"] = Module[\"asm\"][\"pthread_self\"]).apply(null, arguments);\n        };\n        var _emscripten_main_thread_process_queued_calls = Module[\"_emscripten_main_thread_process_queued_calls\"] = function() {\n          return (_emscripten_main_thread_process_queued_calls = Module[\"_emscripten_main_thread_process_queued_calls\"] = Module[\"asm\"][\"emscripten_main_thread_process_queued_calls\"]).apply(null, arguments);\n        };\n        var __emscripten_thread_crashed = Module[\"__emscripten_thread_crashed\"] = function() {\n          return (__emscripten_thread_crashed = Module[\"__emscripten_thread_crashed\"] = Module[\"asm\"][\"_emscripten_thread_crashed\"]).apply(null, arguments);\n        };\n        var __emscripten_thread_init = Module[\"__emscripten_thread_init\"] = function() {\n          return (__emscripten_thread_init = Module[\"__emscripten_thread_init\"] = Module[\"asm\"][\"_emscripten_thread_init\"]).apply(null, arguments);\n        };\n        var _emscripten_current_thread_process_queued_calls = Module[\"_emscripten_current_thread_process_queued_calls\"] = function() {\n          return (_emscripten_current_thread_process_queued_calls = Module[\"_emscripten_current_thread_process_queued_calls\"] = Module[\"asm\"][\"emscripten_current_thread_process_queued_calls\"]).apply(null, arguments);\n        };\n        var _emscripten_main_browser_thread_id = Module[\"_emscripten_main_browser_thread_id\"] = function() {\n          return (_emscripten_main_browser_thread_id = Module[\"_emscripten_main_browser_thread_id\"] = Module[\"asm\"][\"emscripten_main_browser_thread_id\"]).apply(null, arguments);\n        };\n        var _emscripten_sync_run_in_main_thread_2 = Module[\"_emscripten_sync_run_in_main_thread_2\"] = function() {\n          return (_emscripten_sync_run_in_main_thread_2 = Module[\"_emscripten_sync_run_in_main_thread_2\"] = Module[\"asm\"][\"emscripten_sync_run_in_main_thread_2\"]).apply(null, arguments);\n        };\n        var _emscripten_sync_run_in_main_thread_4 = Module[\"_emscripten_sync_run_in_main_thread_4\"] = function() {\n          return (_emscripten_sync_run_in_main_thread_4 = Module[\"_emscripten_sync_run_in_main_thread_4\"] = Module[\"asm\"][\"emscripten_sync_run_in_main_thread_4\"]).apply(null, arguments);\n        };\n        var _emscripten_run_in_main_runtime_thread_js = Module[\"_emscripten_run_in_main_runtime_thread_js\"] = function() {\n          return (_emscripten_run_in_main_runtime_thread_js = Module[\"_emscripten_run_in_main_runtime_thread_js\"] = Module[\"asm\"][\"emscripten_run_in_main_runtime_thread_js\"]).apply(null, arguments);\n        };\n        var _emscripten_dispatch_to_thread_ = Module[\"_emscripten_dispatch_to_thread_\"] = function() {\n          return (_emscripten_dispatch_to_thread_ = Module[\"_emscripten_dispatch_to_thread_\"] = Module[\"asm\"][\"emscripten_dispatch_to_thread_\"]).apply(null, arguments);\n        };\n        var __emscripten_thread_free_data = Module[\"__emscripten_thread_free_data\"] = function() {\n          return (__emscripten_thread_free_data = Module[\"__emscripten_thread_free_data\"] = Module[\"asm\"][\"_emscripten_thread_free_data\"]).apply(null, arguments);\n        };\n        var __emscripten_thread_exit = Module[\"__emscripten_thread_exit\"] = function() {\n          return (__emscripten_thread_exit = Module[\"__emscripten_thread_exit\"] = Module[\"asm\"][\"_emscripten_thread_exit\"]).apply(null, arguments);\n        };\n        var _memalign = Module[\"_memalign\"] = function() {\n          return (_memalign = Module[\"_memalign\"] = Module[\"asm\"][\"memalign\"]).apply(null, arguments);\n        };\n        var _emscripten_stack_set_limits = Module[\"_emscripten_stack_set_limits\"] = function() {\n          return (_emscripten_stack_set_limits = Module[\"_emscripten_stack_set_limits\"] = Module[\"asm\"][\"emscripten_stack_set_limits\"]).apply(null, arguments);\n        };\n        var stackSave = Module[\"stackSave\"] = function() {\n          return (stackSave = Module[\"stackSave\"] = Module[\"asm\"][\"stackSave\"]).apply(null, arguments);\n        };\n        var stackRestore = Module[\"stackRestore\"] = function() {\n          return (stackRestore = Module[\"stackRestore\"] = Module[\"asm\"][\"stackRestore\"]).apply(null, arguments);\n        };\n        var stackAlloc = Module[\"stackAlloc\"] = function() {\n          return (stackAlloc = Module[\"stackAlloc\"] = Module[\"asm\"][\"stackAlloc\"]).apply(null, arguments);\n        };\n        var dynCall_iijjiiii = Module[\"dynCall_iijjiiii\"] = function() {\n          return (dynCall_iijjiiii = Module[\"dynCall_iijjiiii\"] = Module[\"asm\"][\"dynCall_iijjiiii\"]).apply(null, arguments);\n        };\n        var dynCall_jiji = Module[\"dynCall_jiji\"] = function() {\n          return (dynCall_jiji = Module[\"dynCall_jiji\"] = Module[\"asm\"][\"dynCall_jiji\"]).apply(null, arguments);\n        };\n        var __emscripten_allow_main_runtime_queued_calls = Module[\"__emscripten_allow_main_runtime_queued_calls\"] = 21672;\n        Module[\"cwrap\"] = cwrap;\n        Module[\"keepRuntimeAlive\"] = keepRuntimeAlive;\n        Module[\"PThread\"] = PThread;\n        Module[\"PThread\"] = PThread;\n        Module[\"wasmMemory\"] = wasmMemory;\n        Module[\"ExitStatus\"] = ExitStatus;\n        var calledRun;\n        function ExitStatus(status) {\n          this.name = \"ExitStatus\";\n          this.message = \"Program terminated with exit(\" + status + \")\";\n          this.status = status;\n        }\n        dependenciesFulfilled = function runCaller() {\n          if (!calledRun)\n            run();\n          if (!calledRun)\n            dependenciesFulfilled = runCaller;\n        };\n        function run(args) {\n          args = args || arguments_;\n          if (runDependencies > 0) {\n            return;\n          }\n          if (ENVIRONMENT_IS_PTHREAD) {\n            readyPromiseResolve(Module);\n            initRuntime();\n            postMessage({ \"cmd\": \"loaded\" });\n            return;\n          }\n          preRun();\n          if (runDependencies > 0) {\n            return;\n          }\n          function doRun() {\n            if (calledRun)\n              return;\n            calledRun = true;\n            Module[\"calledRun\"] = true;\n            if (ABORT)\n              return;\n            initRuntime();\n            readyPromiseResolve(Module);\n            if (Module[\"onRuntimeInitialized\"])\n              Module[\"onRuntimeInitialized\"]();\n            postRun();\n          }\n          if (Module[\"setStatus\"]) {\n            Module[\"setStatus\"](\"Running...\");\n            setTimeout(function() {\n              setTimeout(function() {\n                Module[\"setStatus\"](\"\");\n              }, 1);\n              doRun();\n            }, 1);\n          } else {\n            doRun();\n          }\n        }\n        Module[\"run\"] = run;\n        function exit(status, implicit) {\n          EXITSTATUS = status;\n          if (!implicit) {\n            if (ENVIRONMENT_IS_PTHREAD) {\n              exitOnMainThread(status);\n              throw \"unwind\";\n            } else {\n            }\n          }\n          if (keepRuntimeAlive()) {\n          } else {\n            exitRuntime();\n          }\n          procExit(status);\n        }\n        function procExit(code) {\n          EXITSTATUS = code;\n          if (!keepRuntimeAlive()) {\n            PThread.terminateAllThreads();\n            if (Module[\"onExit\"])\n              Module[\"onExit\"](code);\n            ABORT = true;\n          }\n          quit_(code, new ExitStatus(code));\n        }\n        if (Module[\"preInit\"]) {\n          if (typeof Module[\"preInit\"] == \"function\")\n            Module[\"preInit\"] = [Module[\"preInit\"]];\n          while (Module[\"preInit\"].length > 0) {\n            Module[\"preInit\"].pop()();\n          }\n        }\n        run();\n        var listenersAdded;\n        if (beforeListeners) {\n          listenersAdded = { uncaughtException: process.listeners(\"uncaughtException\").filter(function(listener) {\n            return !beforeListeners.uncaughtException.indexOf(listener) > -1;\n          }), unhandledRejection: process.listeners(\"unhandledRejection\").filter(function(listener) {\n            return !beforeListeners.unhandledRejection.indexOf(listener) > -1;\n          }) };\n        }\n        var actualModule;\n        if (typeof WasmBackendModule !== \"undefined\") {\n          actualModule = WasmBackendModule;\n        } else if (typeof WasmBackendModuleThreadedSimd3 !== \"undefined\") {\n          actualModule = WasmBackendModuleThreadedSimd3;\n        } else {\n          throw new Error(\"Could not find wasm module in post.js\");\n        }\n        if (listenersAdded) {\n          var tmpDispose = actualModule[\"_dispose\"];\n          actualModule[\"_dispose\"] = function() {\n            tmpDispose();\n            listenersAdded.uncaughtException.forEach(function(listener) {\n              process.removeListener(\"uncaughtException\", listener);\n            });\n            listenersAdded.unhandledRejection.forEach(function(listener) {\n              process.removeListener(\"unhandledRejection\", listener);\n            });\n          };\n        }\n        return WasmBackendModuleThreadedSimd3.ready;\n      };\n    })();\n    if (typeof exports === \"object\" && typeof module === \"object\")\n      module.exports = WasmBackendModuleThreadedSimd2;\n    else if (typeof define === \"function\" && define[\"amd\"])\n      define([], function() {\n        return WasmBackendModuleThreadedSimd2;\n      });\n    else if (typeof exports === \"object\")\n      exports[\"WasmBackendModuleThreadedSimd\"] = WasmBackendModuleThreadedSimd2;\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.worker.js\nvar require_tfjs_backend_wasm_threaded_simd_worker = __commonJS({\n  \"node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.worker.js\"(exports, module) {\n    module.exports.wasmWorkerContents = `\"use strict\";var Module={};var ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";if(ENVIRONMENT_IS_NODE){var nodeWorkerThreads=require(\"worker_threads\");var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var fs=require(\"fs\");Object.assign(global,{self:global,require:require,Module:Module,location:{href:__filename},Worker:nodeWorkerThreads.Worker,importScripts:function(f){(0,eval)(fs.readFileSync(f,\"utf8\"))},postMessage:function(msg){parentPort.postMessage(msg)},performance:global.performance||{now:function(){return Date.now()}}})}function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");if(ENVIRONMENT_IS_NODE){fs.writeSync(2,text+\"\n\");return}console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(\" \");postMessage({cmd:\"alert\",text:text,threadId:Module[\"_pthread_self\"]()})}var err=threadPrintErr;self.alert=threadAlert;Module[\"instantiateWasm\"]=((info,receiveInstance)=>{var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);receiveInstance(instance);Module[\"wasmModule\"]=null;return instance.exports});self.onmessage=(e=>{try{if(e.data.cmd===\"load\"){Module[\"wasmModule\"]=e.data.wasmModule;Module[\"wasmMemory\"]=e.data.wasmMemory;Module[\"buffer\"]=Module[\"wasmMemory\"].buffer;Module[\"ENVIRONMENT_IS_PTHREAD\"]=true;if(typeof e.data.urlOrBlob===\"string\"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module).then(function(instance){Module=instance})}else if(e.data.cmd===\"run\"){Module[\"__performance_now_clock_drift\"]=performance.now()-e.data.time;Module[\"__emscripten_thread_init\"](e.data.threadInfoStruct,0,0,1);Module[\"establishStackSpace\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].threadInit();try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(Module[\"keepRuntimeAlive\"]()){Module[\"PThread\"].setExitStatus(result)}else{Module[\"__emscripten_thread_exit\"](result)}}catch(ex){if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"keepRuntimeAlive\"]()){}else{Module[\"__emscripten_thread_exit\"](ex.status)}}else{throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"__emscripten_thread_exit\"](-1)}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}else if(e.data.cmd===\"processProxyingQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_proxy_execute_queue\"](e.data.queue)}}else{err(\"worker.js received unknown command \"+e.data.cmd);err(e.data)}}catch(ex){err(\"worker.js onmessage() captured an uncaught exception: \"+ex);if(ex&&ex.stack)err(ex.stack);if(Module[\"__emscripten_thread_crashed\"]){Module[\"__emscripten_thread_crashed\"]()}throw ex}});`;\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm.js\nvar require_tfjs_backend_wasm = __commonJS({\n  \"node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm.js\"(exports, module) {\n    var WasmBackendModule2 = (() => {\n      var _scriptDir = typeof document !== \"undefined\" && document.currentScript ? document.currentScript.src : void 0;\n      if (typeof __filename !== \"undefined\")\n        _scriptDir = _scriptDir || __filename;\n      return function(WasmBackendModule3) {\n        WasmBackendModule3 = WasmBackendModule3 || {};\n        var Module = typeof WasmBackendModule3 !== \"undefined\" ? WasmBackendModule3 : {};\n        var readyPromiseResolve, readyPromiseReject;\n        Module[\"ready\"] = new Promise(function(resolve, reject) {\n          readyPromiseResolve = resolve;\n          readyPromiseReject = reject;\n        });\n        var beforeListeners;\n        if (typeof process !== \"undefined\" && process.listeners) {\n          beforeListeners = { uncaughtException: process.listeners(\"uncaughtException\"), unhandledRejection: process.listeners(\"unhandledRejection\") };\n        }\n        var moduleOverrides = Object.assign({}, Module);\n        var arguments_ = [];\n        var thisProgram = \"./this.program\";\n        var quit_ = (status, toThrow) => {\n          throw toThrow;\n        };\n        var ENVIRONMENT_IS_WEB = typeof window === \"object\";\n        var ENVIRONMENT_IS_WORKER = typeof importScripts === \"function\";\n        var ENVIRONMENT_IS_NODE = typeof process === \"object\" && typeof process.versions === \"object\" && typeof process.versions.node === \"string\";\n        var scriptDirectory = \"\";\n        function locateFile(path) {\n          if (Module[\"locateFile\"]) {\n            return Module[\"locateFile\"](path, scriptDirectory);\n          }\n          return scriptDirectory + path;\n        }\n        var read_, readAsync, readBinary, setWindowTitle;\n        function logExceptionOnExit(e2) {\n          if (e2 instanceof ExitStatus)\n            return;\n          let toLog = e2;\n          err(\"exiting due to exception: \" + toLog);\n        }\n        var fs;\n        var nodePath;\n        var requireNodeFS;\n        if (ENVIRONMENT_IS_NODE) {\n          if (ENVIRONMENT_IS_WORKER) {\n            scriptDirectory = require_path().dirname(scriptDirectory) + \"/\";\n          } else {\n            scriptDirectory = __dirname + \"/\";\n          }\n          requireNodeFS = () => {\n            if (!nodePath) {\n              fs = require_fs();\n              nodePath = require_path();\n            }\n          };\n          read_ = function shell_read(filename, binary) {\n            requireNodeFS();\n            filename = nodePath[\"normalize\"](filename);\n            return fs.readFileSync(filename, binary ? void 0 : \"utf8\");\n          };\n          readBinary = (filename) => {\n            var ret = read_(filename, true);\n            if (!ret.buffer) {\n              ret = new Uint8Array(ret);\n            }\n            return ret;\n          };\n          readAsync = (filename, onload, onerror) => {\n            requireNodeFS();\n            filename = nodePath[\"normalize\"](filename);\n            fs.readFile(filename, function(err2, data) {\n              if (err2)\n                onerror(err2);\n              else\n                onload(data.buffer);\n            });\n          };\n          if (process[\"argv\"].length > 1) {\n            thisProgram = process[\"argv\"][1].replace(/\\\\/g, \"/\");\n          }\n          arguments_ = process[\"argv\"].slice(2);\n          process[\"on\"](\"uncaughtException\", function(ex) {\n            if (!(ex instanceof ExitStatus)) {\n              throw ex;\n            }\n          });\n          process[\"on\"](\"unhandledRejection\", function(reason) {\n            throw reason;\n          });\n          quit_ = (status, toThrow) => {\n            if (keepRuntimeAlive()) {\n              process[\"exitCode\"] = status;\n              throw toThrow;\n            }\n            logExceptionOnExit(toThrow);\n            process[\"exit\"](status);\n          };\n          Module[\"inspect\"] = function() {\n            return \"[Emscripten Module object]\";\n          };\n        } else if (ENVIRONMENT_IS_WEB || ENVIRONMENT_IS_WORKER) {\n          if (ENVIRONMENT_IS_WORKER) {\n            scriptDirectory = self.location.href;\n          } else if (typeof document !== \"undefined\" && document.currentScript) {\n            scriptDirectory = document.currentScript.src;\n          }\n          if (_scriptDir) {\n            scriptDirectory = _scriptDir;\n          }\n          if (scriptDirectory.indexOf(\"blob:\") !== 0) {\n            scriptDirectory = scriptDirectory.substr(0, scriptDirectory.replace(/[?#].*/, \"\").lastIndexOf(\"/\") + 1);\n          } else {\n            scriptDirectory = \"\";\n          }\n          {\n            read_ = (url) => {\n              var xhr = new XMLHttpRequest();\n              xhr.open(\"GET\", url, false);\n              xhr.send(null);\n              return xhr.responseText;\n            };\n            if (ENVIRONMENT_IS_WORKER) {\n              readBinary = (url) => {\n                var xhr = new XMLHttpRequest();\n                xhr.open(\"GET\", url, false);\n                xhr.responseType = \"arraybuffer\";\n                xhr.send(null);\n                return new Uint8Array(xhr.response);\n              };\n            }\n            readAsync = (url, onload, onerror) => {\n              var xhr = new XMLHttpRequest();\n              xhr.open(\"GET\", url, true);\n              xhr.responseType = \"arraybuffer\";\n              xhr.onload = () => {\n                if (xhr.status == 200 || xhr.status == 0 && xhr.response) {\n                  onload(xhr.response);\n                  return;\n                }\n                onerror();\n              };\n              xhr.onerror = onerror;\n              xhr.send(null);\n            };\n          }\n          setWindowTitle = (title) => document.title = title;\n        } else {\n        }\n        var out = Module[\"print\"] || console.log.bind(console);\n        var err = Module[\"printErr\"] || console.warn.bind(console);\n        Object.assign(Module, moduleOverrides);\n        moduleOverrides = null;\n        if (Module[\"arguments\"])\n          arguments_ = Module[\"arguments\"];\n        if (Module[\"thisProgram\"])\n          thisProgram = Module[\"thisProgram\"];\n        if (Module[\"quit\"])\n          quit_ = Module[\"quit\"];\n        var POINTER_SIZE = 4;\n        function warnOnce(text) {\n          if (!warnOnce.shown)\n            warnOnce.shown = {};\n          if (!warnOnce.shown[text]) {\n            warnOnce.shown[text] = 1;\n            err(text);\n          }\n        }\n        function convertJsFunctionToWasm(func2, sig) {\n          if (typeof WebAssembly.Function === \"function\") {\n            var typeNames = { \"i\": \"i32\", \"j\": \"i64\", \"f\": \"f32\", \"d\": \"f64\" };\n            var type = { parameters: [], results: sig[0] == \"v\" ? [] : [typeNames[sig[0]]] };\n            for (var i2 = 1; i2 < sig.length; ++i2) {\n              type.parameters.push(typeNames[sig[i2]]);\n            }\n            return new WebAssembly.Function(type, func2);\n          }\n          var typeSection = [1, 0, 1, 96];\n          var sigRet = sig.slice(0, 1);\n          var sigParam = sig.slice(1);\n          var typeCodes = { \"i\": 127, \"j\": 126, \"f\": 125, \"d\": 124 };\n          typeSection.push(sigParam.length);\n          for (var i2 = 0; i2 < sigParam.length; ++i2) {\n            typeSection.push(typeCodes[sigParam[i2]]);\n          }\n          if (sigRet == \"v\") {\n            typeSection.push(0);\n          } else {\n            typeSection = typeSection.concat([1, typeCodes[sigRet]]);\n          }\n          typeSection[1] = typeSection.length - 2;\n          var bytes = new Uint8Array([0, 97, 115, 109, 1, 0, 0, 0].concat(typeSection, [2, 7, 1, 1, 101, 1, 102, 0, 0, 7, 5, 1, 1, 102, 0, 0]));\n          var module2 = new WebAssembly.Module(bytes);\n          var instance = new WebAssembly.Instance(module2, { \"e\": { \"f\": func2 } });\n          var wrappedFunc = instance.exports[\"f\"];\n          return wrappedFunc;\n        }\n        var freeTableIndexes = [];\n        var functionsInTableMap;\n        function getEmptyTableSlot() {\n          if (freeTableIndexes.length) {\n            return freeTableIndexes.pop();\n          }\n          try {\n            wasmTable.grow(1);\n          } catch (err2) {\n            if (!(err2 instanceof RangeError)) {\n              throw err2;\n            }\n            throw \"Unable to grow wasm table. Set ALLOW_TABLE_GROWTH.\";\n          }\n          return wasmTable.length - 1;\n        }\n        function updateTableMap(offset, count2) {\n          for (var i2 = offset; i2 < offset + count2; i2++) {\n            var item = getWasmTableEntry(i2);\n            if (item) {\n              functionsInTableMap.set(item, i2);\n            }\n          }\n        }\n        var tempRet0 = 0;\n        var setTempRet0 = (value) => {\n          tempRet0 = value;\n        };\n        var wasmBinary;\n        if (Module[\"wasmBinary\"])\n          wasmBinary = Module[\"wasmBinary\"];\n        var noExitRuntime = Module[\"noExitRuntime\"] || true;\n        if (typeof WebAssembly !== \"object\") {\n          abort(\"no native wasm support detected\");\n        }\n        var wasmMemory;\n        var ABORT = false;\n        var EXITSTATUS;\n        function assert3(condition, text) {\n          if (!condition) {\n            abort(text);\n          }\n        }\n        function getCFunc(ident) {\n          var func2 = Module[\"_\" + ident];\n          return func2;\n        }\n        function ccall(ident, returnType, argTypes, args, opts) {\n          var toC = { \"string\": function(str) {\n            var ret2 = 0;\n            if (str !== null && str !== void 0 && str !== 0) {\n              var len = (str.length << 2) + 1;\n              ret2 = stackAlloc(len);\n              stringToUTF8(str, ret2, len);\n            }\n            return ret2;\n          }, \"array\": function(arr) {\n            var ret2 = stackAlloc(arr.length);\n            writeArrayToMemory(arr, ret2);\n            return ret2;\n          } };\n          function convertReturnValue(ret2) {\n            if (returnType === \"string\")\n              return UTF8ToString(ret2);\n            if (returnType === \"boolean\")\n              return Boolean(ret2);\n            return ret2;\n          }\n          var func2 = getCFunc(ident);\n          var cArgs = [];\n          var stack2 = 0;\n          if (args) {\n            for (var i2 = 0; i2 < args.length; i2++) {\n              var converter = toC[argTypes[i2]];\n              if (converter) {\n                if (stack2 === 0)\n                  stack2 = stackSave();\n                cArgs[i2] = converter(args[i2]);\n              } else {\n                cArgs[i2] = args[i2];\n              }\n            }\n          }\n          var ret = func2.apply(null, cArgs);\n          function onDone(ret2) {\n            if (stack2 !== 0)\n              stackRestore(stack2);\n            return convertReturnValue(ret2);\n          }\n          ret = onDone(ret);\n          return ret;\n        }\n        function cwrap(ident, returnType, argTypes, opts) {\n          argTypes = argTypes || [];\n          var numericArgs = argTypes.every(function(type) {\n            return type === \"number\";\n          });\n          var numericRet = returnType !== \"string\";\n          if (numericRet && numericArgs && !opts) {\n            return getCFunc(ident);\n          }\n          return function() {\n            return ccall(ident, returnType, argTypes, arguments, opts);\n          };\n        }\n        var ALLOC_STACK = 1;\n        var UTF8Decoder = typeof TextDecoder !== \"undefined\" ? new TextDecoder(\"utf8\") : void 0;\n        function UTF8ArrayToString(heap, idx, maxBytesToRead) {\n          var endIdx = idx + maxBytesToRead;\n          var endPtr = idx;\n          while (heap[endPtr] && !(endPtr >= endIdx))\n            ++endPtr;\n          if (endPtr - idx > 16 && heap.subarray && UTF8Decoder) {\n            return UTF8Decoder.decode(heap.subarray(idx, endPtr));\n          } else {\n            var str = \"\";\n            while (idx < endPtr) {\n              var u0 = heap[idx++];\n              if (!(u0 & 128)) {\n                str += String.fromCharCode(u0);\n                continue;\n              }\n              var u1 = heap[idx++] & 63;\n              if ((u0 & 224) == 192) {\n                str += String.fromCharCode((u0 & 31) << 6 | u1);\n                continue;\n              }\n              var u2 = heap[idx++] & 63;\n              if ((u0 & 240) == 224) {\n                u0 = (u0 & 15) << 12 | u1 << 6 | u2;\n              } else {\n                u0 = (u0 & 7) << 18 | u1 << 12 | u2 << 6 | heap[idx++] & 63;\n              }\n              if (u0 < 65536) {\n                str += String.fromCharCode(u0);\n              } else {\n                var ch = u0 - 65536;\n                str += String.fromCharCode(55296 | ch >> 10, 56320 | ch & 1023);\n              }\n            }\n          }\n          return str;\n        }\n        function UTF8ToString(ptr, maxBytesToRead) {\n          return ptr ? UTF8ArrayToString(HEAPU8, ptr, maxBytesToRead) : \"\";\n        }\n        function stringToUTF8Array(str, heap, outIdx, maxBytesToWrite) {\n          if (!(maxBytesToWrite > 0))\n            return 0;\n          var startIdx = outIdx;\n          var endIdx = outIdx + maxBytesToWrite - 1;\n          for (var i2 = 0; i2 < str.length; ++i2) {\n            var u = str.charCodeAt(i2);\n            if (u >= 55296 && u <= 57343) {\n              var u1 = str.charCodeAt(++i2);\n              u = 65536 + ((u & 1023) << 10) | u1 & 1023;\n            }\n            if (u <= 127) {\n              if (outIdx >= endIdx)\n                break;\n              heap[outIdx++] = u;\n            } else if (u <= 2047) {\n              if (outIdx + 1 >= endIdx)\n                break;\n              heap[outIdx++] = 192 | u >> 6;\n              heap[outIdx++] = 128 | u & 63;\n            } else if (u <= 65535) {\n              if (outIdx + 2 >= endIdx)\n                break;\n              heap[outIdx++] = 224 | u >> 12;\n              heap[outIdx++] = 128 | u >> 6 & 63;\n              heap[outIdx++] = 128 | u & 63;\n            } else {\n              if (outIdx + 3 >= endIdx)\n                break;\n              heap[outIdx++] = 240 | u >> 18;\n              heap[outIdx++] = 128 | u >> 12 & 63;\n              heap[outIdx++] = 128 | u >> 6 & 63;\n              heap[outIdx++] = 128 | u & 63;\n            }\n          }\n          heap[outIdx] = 0;\n          return outIdx - startIdx;\n        }\n        function stringToUTF8(str, outPtr, maxBytesToWrite) {\n          return stringToUTF8Array(str, HEAPU8, outPtr, maxBytesToWrite);\n        }\n        function lengthBytesUTF8(str) {\n          var len = 0;\n          for (var i2 = 0; i2 < str.length; ++i2) {\n            var u = str.charCodeAt(i2);\n            if (u >= 55296 && u <= 57343)\n              u = 65536 + ((u & 1023) << 10) | str.charCodeAt(++i2) & 1023;\n            if (u <= 127)\n              ++len;\n            else if (u <= 2047)\n              len += 2;\n            else if (u <= 65535)\n              len += 3;\n            else\n              len += 4;\n          }\n          return len;\n        }\n        var UTF16Decoder = typeof TextDecoder !== \"undefined\" ? new TextDecoder(\"utf-16le\") : void 0;\n        function writeArrayToMemory(array2, buffer3) {\n          HEAP8.set(array2, buffer3);\n        }\n        function writeAsciiToMemory(str, buffer3, dontAddNull) {\n          for (var i2 = 0; i2 < str.length; ++i2) {\n            HEAP8[buffer3++ >> 0] = str.charCodeAt(i2);\n          }\n          if (!dontAddNull)\n            HEAP8[buffer3 >> 0] = 0;\n        }\n        function alignUp(x, multiple) {\n          if (x % multiple > 0) {\n            x += multiple - x % multiple;\n          }\n          return x;\n        }\n        var buffer2, HEAP8, HEAPU8, HEAP16, HEAPU16, HEAP32, HEAPU32, HEAPF32, HEAPF64;\n        function updateGlobalBufferAndViews(buf) {\n          buffer2 = buf;\n          Module[\"HEAP8\"] = HEAP8 = new Int8Array(buf);\n          Module[\"HEAP16\"] = HEAP16 = new Int16Array(buf);\n          Module[\"HEAP32\"] = HEAP32 = new Int32Array(buf);\n          Module[\"HEAPU8\"] = HEAPU8 = new Uint8Array(buf);\n          Module[\"HEAPU16\"] = HEAPU16 = new Uint16Array(buf);\n          Module[\"HEAPU32\"] = HEAPU32 = new Uint32Array(buf);\n          Module[\"HEAPF32\"] = HEAPF32 = new Float32Array(buf);\n          Module[\"HEAPF64\"] = HEAPF64 = new Float64Array(buf);\n        }\n        var INITIAL_MEMORY = Module[\"INITIAL_MEMORY\"] || 16777216;\n        var wasmTable;\n        var __ATPRERUN__ = [];\n        var __ATINIT__ = [];\n        var __ATPOSTRUN__ = [];\n        var runtimeInitialized = false;\n        var runtimeExited = false;\n        var runtimeKeepaliveCounter = 0;\n        function keepRuntimeAlive() {\n          return noExitRuntime || runtimeKeepaliveCounter > 0;\n        }\n        function preRun() {\n          if (Module[\"preRun\"]) {\n            if (typeof Module[\"preRun\"] == \"function\")\n              Module[\"preRun\"] = [Module[\"preRun\"]];\n            while (Module[\"preRun\"].length) {\n              addOnPreRun(Module[\"preRun\"].shift());\n            }\n          }\n          callRuntimeCallbacks(__ATPRERUN__);\n        }\n        function initRuntime() {\n          runtimeInitialized = true;\n          callRuntimeCallbacks(__ATINIT__);\n        }\n        function exitRuntime() {\n          runtimeExited = true;\n        }\n        function postRun() {\n          if (Module[\"postRun\"]) {\n            if (typeof Module[\"postRun\"] == \"function\")\n              Module[\"postRun\"] = [Module[\"postRun\"]];\n            while (Module[\"postRun\"].length) {\n              addOnPostRun(Module[\"postRun\"].shift());\n            }\n          }\n          callRuntimeCallbacks(__ATPOSTRUN__);\n        }\n        function addOnPreRun(cb) {\n          __ATPRERUN__.unshift(cb);\n        }\n        function addOnInit(cb) {\n          __ATINIT__.unshift(cb);\n        }\n        function addOnPostRun(cb) {\n          __ATPOSTRUN__.unshift(cb);\n        }\n        var runDependencies = 0;\n        var runDependencyWatcher = null;\n        var dependenciesFulfilled = null;\n        function addRunDependency(id) {\n          runDependencies++;\n          if (Module[\"monitorRunDependencies\"]) {\n            Module[\"monitorRunDependencies\"](runDependencies);\n          }\n        }\n        function removeRunDependency(id) {\n          runDependencies--;\n          if (Module[\"monitorRunDependencies\"]) {\n            Module[\"monitorRunDependencies\"](runDependencies);\n          }\n          if (runDependencies == 0) {\n            if (runDependencyWatcher !== null) {\n              clearInterval(runDependencyWatcher);\n              runDependencyWatcher = null;\n            }\n            if (dependenciesFulfilled) {\n              var callback = dependenciesFulfilled;\n              dependenciesFulfilled = null;\n              callback();\n            }\n          }\n        }\n        Module[\"preloadedImages\"] = {};\n        Module[\"preloadedAudios\"] = {};\n        function abort(what) {\n          {\n            if (Module[\"onAbort\"]) {\n              Module[\"onAbort\"](what);\n            }\n          }\n          what = \"Aborted(\" + what + \")\";\n          err(what);\n          ABORT = true;\n          EXITSTATUS = 1;\n          what += \". Build with -s ASSERTIONS=1 for more info.\";\n          var e2 = new WebAssembly.RuntimeError(what);\n          readyPromiseReject(e2);\n          throw e2;\n        }\n        var dataURIPrefix = \"data:application/octet-stream;base64,\";\n        function isDataURI(filename) {\n          return filename.startsWith(dataURIPrefix);\n        }\n        function isFileURI(filename) {\n          return filename.startsWith(\"file://\");\n        }\n        var wasmBinaryFile;\n        wasmBinaryFile = \"tfjs-backend-wasm.wasm\";\n        if (!isDataURI(wasmBinaryFile)) {\n          wasmBinaryFile = locateFile(wasmBinaryFile);\n        }\n        function getBinary(file) {\n          try {\n            if (file == wasmBinaryFile && wasmBinary) {\n              return new Uint8Array(wasmBinary);\n            }\n            if (readBinary) {\n              return readBinary(file);\n            } else {\n              throw \"both async and sync fetching of the wasm failed\";\n            }\n          } catch (err2) {\n            abort(err2);\n          }\n        }\n        function getBinaryPromise() {\n          if (!wasmBinary && (ENVIRONMENT_IS_WEB || ENVIRONMENT_IS_WORKER)) {\n            if (typeof fetch === \"function\" && !isFileURI(wasmBinaryFile)) {\n              return fetch(wasmBinaryFile, { credentials: \"same-origin\" }).then(function(response) {\n                if (!response[\"ok\"]) {\n                  throw \"failed to load wasm binary file at '\" + wasmBinaryFile + \"'\";\n                }\n                return response[\"arrayBuffer\"]();\n              }).catch(function() {\n                return getBinary(wasmBinaryFile);\n              });\n            } else {\n              if (readAsync) {\n                return new Promise(function(resolve, reject) {\n                  readAsync(wasmBinaryFile, function(response) {\n                    resolve(new Uint8Array(response));\n                  }, reject);\n                });\n              }\n            }\n          }\n          return Promise.resolve().then(function() {\n            return getBinary(wasmBinaryFile);\n          });\n        }\n        function createWasm() {\n          var info = { \"env\": asmLibraryArg, \"wasi_snapshot_preview1\": asmLibraryArg };\n          function receiveInstance(instance, module2) {\n            var exports3 = instance.exports;\n            Module[\"asm\"] = exports3;\n            wasmMemory = Module[\"asm\"][\"memory\"];\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n            wasmTable = Module[\"asm\"][\"__indirect_function_table\"];\n            addOnInit(Module[\"asm\"][\"__wasm_call_ctors\"]);\n            removeRunDependency(\"wasm-instantiate\");\n          }\n          addRunDependency(\"wasm-instantiate\");\n          function receiveInstantiationResult(result) {\n            receiveInstance(result[\"instance\"]);\n          }\n          function instantiateArrayBuffer(receiver) {\n            return getBinaryPromise().then(function(binary) {\n              return WebAssembly.instantiate(binary, info);\n            }).then(function(instance) {\n              return instance;\n            }).then(receiver, function(reason) {\n              err(\"failed to asynchronously prepare wasm: \" + reason);\n              abort(reason);\n            });\n          }\n          function instantiateAsync() {\n            if (!wasmBinary && typeof WebAssembly.instantiateStreaming === \"function\" && !isDataURI(wasmBinaryFile) && !isFileURI(wasmBinaryFile) && typeof fetch === \"function\") {\n              return fetch(wasmBinaryFile, { credentials: \"same-origin\" }).then(function(response) {\n                var result = WebAssembly.instantiateStreaming(response, info);\n                return result.then(receiveInstantiationResult, function(reason) {\n                  err(\"wasm streaming compile failed: \" + reason);\n                  err(\"falling back to ArrayBuffer instantiation\");\n                  return instantiateArrayBuffer(receiveInstantiationResult);\n                });\n              });\n            } else {\n              return instantiateArrayBuffer(receiveInstantiationResult);\n            }\n          }\n          if (Module[\"instantiateWasm\"]) {\n            try {\n              var exports2 = Module[\"instantiateWasm\"](info, receiveInstance);\n              return exports2;\n            } catch (e2) {\n              err(\"Module.instantiateWasm callback failed with error: \" + e2);\n              return false;\n            }\n          }\n          instantiateAsync().catch(readyPromiseReject);\n          return {};\n        }\n        var tempDouble;\n        var tempI64;\n        function callRuntimeCallbacks(callbacks2) {\n          while (callbacks2.length > 0) {\n            var callback = callbacks2.shift();\n            if (typeof callback == \"function\") {\n              callback(Module);\n              continue;\n            }\n            var func2 = callback.func;\n            if (typeof func2 === \"number\") {\n              if (callback.arg === void 0) {\n                getWasmTableEntry(func2)();\n              } else {\n                getWasmTableEntry(func2)(callback.arg);\n              }\n            } else {\n              func2(callback.arg === void 0 ? null : callback.arg);\n            }\n          }\n        }\n        function demangle(func2) {\n          return func2;\n        }\n        function demangleAll(text) {\n          var regex = /\\b_Z[\\w\\d_]+/g;\n          return text.replace(regex, function(x) {\n            var y = demangle(x);\n            return x === y ? x : y + \" [\" + x + \"]\";\n          });\n        }\n        var wasmTableMirror = [];\n        function getWasmTableEntry(funcPtr) {\n          var func2 = wasmTableMirror[funcPtr];\n          if (!func2) {\n            if (funcPtr >= wasmTableMirror.length)\n              wasmTableMirror.length = funcPtr + 1;\n            wasmTableMirror[funcPtr] = func2 = wasmTable.get(funcPtr);\n          }\n          return func2;\n        }\n        function jsStackTrace() {\n          var error = new Error();\n          if (!error.stack) {\n            try {\n              throw new Error();\n            } catch (e2) {\n              error = e2;\n            }\n            if (!error.stack) {\n              return \"(no stack trace available)\";\n            }\n          }\n          return error.stack.toString();\n        }\n        function setWasmTableEntry(idx, func2) {\n          wasmTable.set(idx, func2);\n          wasmTableMirror[idx] = func2;\n        }\n        function _abort() {\n          abort(\"\");\n        }\n        function _emscripten_get_heap_max() {\n          return 2147483648;\n        }\n        function _emscripten_memcpy_big(dest, src, num) {\n          HEAPU8.copyWithin(dest, src, src + num);\n        }\n        function emscripten_realloc_buffer(size) {\n          try {\n            wasmMemory.grow(size - buffer2.byteLength + 65535 >>> 16);\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n            return 1;\n          } catch (e2) {\n          }\n        }\n        function _emscripten_resize_heap(requestedSize) {\n          var oldSize = HEAPU8.length;\n          requestedSize = requestedSize >>> 0;\n          var maxHeapSize = _emscripten_get_heap_max();\n          if (requestedSize > maxHeapSize) {\n            return false;\n          }\n          for (var cutDown = 1; cutDown <= 4; cutDown *= 2) {\n            var overGrownHeapSize = oldSize * (1 + 0.2 / cutDown);\n            overGrownHeapSize = Math.min(overGrownHeapSize, requestedSize + 100663296);\n            var newSize = Math.min(maxHeapSize, alignUp(Math.max(requestedSize, overGrownHeapSize), 65536));\n            var replacement = emscripten_realloc_buffer(newSize);\n            if (replacement) {\n              return true;\n            }\n          }\n          return false;\n        }\n        var SYSCALLS = { mappings: {}, buffers: [null, [], []], printChar: function(stream, curr) {\n          var buffer3 = SYSCALLS.buffers[stream];\n          if (curr === 0 || curr === 10) {\n            (stream === 1 ? out : err)(UTF8ArrayToString(buffer3, 0));\n            buffer3.length = 0;\n          } else {\n            buffer3.push(curr);\n          }\n        }, varargs: void 0, get: function() {\n          SYSCALLS.varargs += 4;\n          var ret = HEAP32[SYSCALLS.varargs - 4 >> 2];\n          return ret;\n        }, getStr: function(ptr) {\n          var ret = UTF8ToString(ptr);\n          return ret;\n        }, get64: function(low, high) {\n          return low;\n        } };\n        function _fd_close(fd) {\n          return 0;\n        }\n        function _fd_seek(fd, offset_low, offset_high, whence, newOffset) {\n        }\n        function _fd_write(fd, iov, iovcnt, pnum) {\n          var num = 0;\n          for (var i2 = 0; i2 < iovcnt; i2++) {\n            var ptr = HEAP32[iov >> 2];\n            var len = HEAP32[iov + 4 >> 2];\n            iov += 8;\n            for (var j = 0; j < len; j++) {\n              SYSCALLS.printChar(fd, HEAPU8[ptr + j]);\n            }\n            num += len;\n          }\n          HEAP32[pnum >> 2] = num;\n          return 0;\n        }\n        function _setTempRet0(val) {\n          setTempRet0(val);\n        }\n        var ASSERTIONS = false;\n        var asmLibraryArg = { \"abort\": _abort, \"emscripten_get_heap_max\": _emscripten_get_heap_max, \"emscripten_memcpy_big\": _emscripten_memcpy_big, \"emscripten_resize_heap\": _emscripten_resize_heap, \"fd_close\": _fd_close, \"fd_seek\": _fd_seek, \"fd_write\": _fd_write, \"setTempRet0\": _setTempRet0 };\n        var asm = createWasm();\n        var ___wasm_call_ctors = Module[\"___wasm_call_ctors\"] = function() {\n          return (___wasm_call_ctors = Module[\"___wasm_call_ctors\"] = Module[\"asm\"][\"__wasm_call_ctors\"]).apply(null, arguments);\n        };\n        var _init = Module[\"_init\"] = function() {\n          return (_init = Module[\"_init\"] = Module[\"asm\"][\"init\"]).apply(null, arguments);\n        };\n        var _init_with_threads_count = Module[\"_init_with_threads_count\"] = function() {\n          return (_init_with_threads_count = Module[\"_init_with_threads_count\"] = Module[\"asm\"][\"init_with_threads_count\"]).apply(null, arguments);\n        };\n        var _get_threads_count = Module[\"_get_threads_count\"] = function() {\n          return (_get_threads_count = Module[\"_get_threads_count\"] = Module[\"asm\"][\"get_threads_count\"]).apply(null, arguments);\n        };\n        var _register_tensor = Module[\"_register_tensor\"] = function() {\n          return (_register_tensor = Module[\"_register_tensor\"] = Module[\"asm\"][\"register_tensor\"]).apply(null, arguments);\n        };\n        var _dispose_data = Module[\"_dispose_data\"] = function() {\n          return (_dispose_data = Module[\"_dispose_data\"] = Module[\"asm\"][\"dispose_data\"]).apply(null, arguments);\n        };\n        var _dispose = Module[\"_dispose\"] = function() {\n          return (_dispose = Module[\"_dispose\"] = Module[\"asm\"][\"dispose\"]).apply(null, arguments);\n        };\n        var _Abs = Module[\"_Abs\"] = function() {\n          return (_Abs = Module[\"_Abs\"] = Module[\"asm\"][\"Abs\"]).apply(null, arguments);\n        };\n        var _Add = Module[\"_Add\"] = function() {\n          return (_Add = Module[\"_Add\"] = Module[\"asm\"][\"Add\"]).apply(null, arguments);\n        };\n        var _AddN = Module[\"_AddN\"] = function() {\n          return (_AddN = Module[\"_AddN\"] = Module[\"asm\"][\"AddN\"]).apply(null, arguments);\n        };\n        var _All = Module[\"_All\"] = function() {\n          return (_All = Module[\"_All\"] = Module[\"asm\"][\"All\"]).apply(null, arguments);\n        };\n        var _Any = Module[\"_Any\"] = function() {\n          return (_Any = Module[\"_Any\"] = Module[\"asm\"][\"Any\"]).apply(null, arguments);\n        };\n        var _ArgMax = Module[\"_ArgMax\"] = function() {\n          return (_ArgMax = Module[\"_ArgMax\"] = Module[\"asm\"][\"ArgMax\"]).apply(null, arguments);\n        };\n        var _AvgPool = Module[\"_AvgPool\"] = function() {\n          return (_AvgPool = Module[\"_AvgPool\"] = Module[\"asm\"][\"AvgPool\"]).apply(null, arguments);\n        };\n        var _BatchMatMul = Module[\"_BatchMatMul\"] = function() {\n          return (_BatchMatMul = Module[\"_BatchMatMul\"] = Module[\"asm\"][\"BatchMatMul\"]).apply(null, arguments);\n        };\n        var _Ceil = Module[\"_Ceil\"] = function() {\n          return (_Ceil = Module[\"_Ceil\"] = Module[\"asm\"][\"Ceil\"]).apply(null, arguments);\n        };\n        var _ClipByValue = Module[\"_ClipByValue\"] = function() {\n          return (_ClipByValue = Module[\"_ClipByValue\"] = Module[\"asm\"][\"ClipByValue\"]).apply(null, arguments);\n        };\n        var _Conv2D = Module[\"_Conv2D\"] = function() {\n          return (_Conv2D = Module[\"_Conv2D\"] = Module[\"asm\"][\"Conv2D\"]).apply(null, arguments);\n        };\n        var _Conv2DBackpropInput = Module[\"_Conv2DBackpropInput\"] = function() {\n          return (_Conv2DBackpropInput = Module[\"_Conv2DBackpropInput\"] = Module[\"asm\"][\"Conv2DBackpropInput\"]).apply(null, arguments);\n        };\n        var _Cos = Module[\"_Cos\"] = function() {\n          return (_Cos = Module[\"_Cos\"] = Module[\"asm\"][\"Cos\"]).apply(null, arguments);\n        };\n        var _Cosh = Module[\"_Cosh\"] = function() {\n          return (_Cosh = Module[\"_Cosh\"] = Module[\"asm\"][\"Cosh\"]).apply(null, arguments);\n        };\n        var _CropAndResize = Module[\"_CropAndResize\"] = function() {\n          return (_CropAndResize = Module[\"_CropAndResize\"] = Module[\"asm\"][\"CropAndResize\"]).apply(null, arguments);\n        };\n        var _Cumprod = Module[\"_Cumprod\"] = function() {\n          return (_Cumprod = Module[\"_Cumprod\"] = Module[\"asm\"][\"Cumprod\"]).apply(null, arguments);\n        };\n        var _Cumsum = Module[\"_Cumsum\"] = function() {\n          return (_Cumsum = Module[\"_Cumsum\"] = Module[\"asm\"][\"Cumsum\"]).apply(null, arguments);\n        };\n        var _DepthToSpace = Module[\"_DepthToSpace\"] = function() {\n          return (_DepthToSpace = Module[\"_DepthToSpace\"] = Module[\"asm\"][\"DepthToSpace\"]).apply(null, arguments);\n        };\n        var _DepthwiseConv2dNative = Module[\"_DepthwiseConv2dNative\"] = function() {\n          return (_DepthwiseConv2dNative = Module[\"_DepthwiseConv2dNative\"] = Module[\"asm\"][\"DepthwiseConv2dNative\"]).apply(null, arguments);\n        };\n        var _Elu = Module[\"_Elu\"] = function() {\n          return (_Elu = Module[\"_Elu\"] = Module[\"asm\"][\"Elu\"]).apply(null, arguments);\n        };\n        var _Equal = Module[\"_Equal\"] = function() {\n          return (_Equal = Module[\"_Equal\"] = Module[\"asm\"][\"Equal\"]).apply(null, arguments);\n        };\n        var _Exp = Module[\"_Exp\"] = function() {\n          return (_Exp = Module[\"_Exp\"] = Module[\"asm\"][\"Exp\"]).apply(null, arguments);\n        };\n        var _FlipLeftRight = Module[\"_FlipLeftRight\"] = function() {\n          return (_FlipLeftRight = Module[\"_FlipLeftRight\"] = Module[\"asm\"][\"FlipLeftRight\"]).apply(null, arguments);\n        };\n        var _Floor = Module[\"_Floor\"] = function() {\n          return (_Floor = Module[\"_Floor\"] = Module[\"asm\"][\"Floor\"]).apply(null, arguments);\n        };\n        var _FloorDiv = Module[\"_FloorDiv\"] = function() {\n          return (_FloorDiv = Module[\"_FloorDiv\"] = Module[\"asm\"][\"FloorDiv\"]).apply(null, arguments);\n        };\n        var _FusedBatchNorm = Module[\"_FusedBatchNorm\"] = function() {\n          return (_FusedBatchNorm = Module[\"_FusedBatchNorm\"] = Module[\"asm\"][\"FusedBatchNorm\"]).apply(null, arguments);\n        };\n        var _FusedConv2D = Module[\"_FusedConv2D\"] = function() {\n          return (_FusedConv2D = Module[\"_FusedConv2D\"] = Module[\"asm\"][\"FusedConv2D\"]).apply(null, arguments);\n        };\n        var _FusedDepthwiseConv2D = Module[\"_FusedDepthwiseConv2D\"] = function() {\n          return (_FusedDepthwiseConv2D = Module[\"_FusedDepthwiseConv2D\"] = Module[\"asm\"][\"FusedDepthwiseConv2D\"]).apply(null, arguments);\n        };\n        var _Gather = Module[\"_Gather\"] = function() {\n          return (_Gather = Module[\"_Gather\"] = Module[\"asm\"][\"Gather\"]).apply(null, arguments);\n        };\n        var _GatherNd = Module[\"_GatherNd\"] = function() {\n          return (_GatherNd = Module[\"_GatherNd\"] = Module[\"asm\"][\"GatherNd\"]).apply(null, arguments);\n        };\n        var _Greater = Module[\"_Greater\"] = function() {\n          return (_Greater = Module[\"_Greater\"] = Module[\"asm\"][\"Greater\"]).apply(null, arguments);\n        };\n        var _GreaterEqual = Module[\"_GreaterEqual\"] = function() {\n          return (_GreaterEqual = Module[\"_GreaterEqual\"] = Module[\"asm\"][\"GreaterEqual\"]).apply(null, arguments);\n        };\n        var _LeakyRelu = Module[\"_LeakyRelu\"] = function() {\n          return (_LeakyRelu = Module[\"_LeakyRelu\"] = Module[\"asm\"][\"LeakyRelu\"]).apply(null, arguments);\n        };\n        var _Less = Module[\"_Less\"] = function() {\n          return (_Less = Module[\"_Less\"] = Module[\"asm\"][\"Less\"]).apply(null, arguments);\n        };\n        var _LessEqual = Module[\"_LessEqual\"] = function() {\n          return (_LessEqual = Module[\"_LessEqual\"] = Module[\"asm\"][\"LessEqual\"]).apply(null, arguments);\n        };\n        var _Log = Module[\"_Log\"] = function() {\n          return (_Log = Module[\"_Log\"] = Module[\"asm\"][\"Log\"]).apply(null, arguments);\n        };\n        var _LogicalAnd = Module[\"_LogicalAnd\"] = function() {\n          return (_LogicalAnd = Module[\"_LogicalAnd\"] = Module[\"asm\"][\"LogicalAnd\"]).apply(null, arguments);\n        };\n        var _LogicalNot = Module[\"_LogicalNot\"] = function() {\n          return (_LogicalNot = Module[\"_LogicalNot\"] = Module[\"asm\"][\"LogicalNot\"]).apply(null, arguments);\n        };\n        var _LogicalOr = Module[\"_LogicalOr\"] = function() {\n          return (_LogicalOr = Module[\"_LogicalOr\"] = Module[\"asm\"][\"LogicalOr\"]).apply(null, arguments);\n        };\n        var _LogicalXor = Module[\"_LogicalXor\"] = function() {\n          return (_LogicalXor = Module[\"_LogicalXor\"] = Module[\"asm\"][\"LogicalXor\"]).apply(null, arguments);\n        };\n        var _Max = Module[\"_Max\"] = function() {\n          return (_Max = Module[\"_Max\"] = Module[\"asm\"][\"Max\"]).apply(null, arguments);\n        };\n        var _MaxPool = Module[\"_MaxPool\"] = function() {\n          return (_MaxPool = Module[\"_MaxPool\"] = Module[\"asm\"][\"MaxPool\"]).apply(null, arguments);\n        };\n        var _Maximum = Module[\"_Maximum\"] = function() {\n          return (_Maximum = Module[\"_Maximum\"] = Module[\"asm\"][\"Maximum\"]).apply(null, arguments);\n        };\n        var _Mean = Module[\"_Mean\"] = function() {\n          return (_Mean = Module[\"_Mean\"] = Module[\"asm\"][\"Mean\"]).apply(null, arguments);\n        };\n        var _Min = Module[\"_Min\"] = function() {\n          return (_Min = Module[\"_Min\"] = Module[\"asm\"][\"Min\"]).apply(null, arguments);\n        };\n        var _Minimum = Module[\"_Minimum\"] = function() {\n          return (_Minimum = Module[\"_Minimum\"] = Module[\"asm\"][\"Minimum\"]).apply(null, arguments);\n        };\n        var _MirrorPad = Module[\"_MirrorPad\"] = function() {\n          return (_MirrorPad = Module[\"_MirrorPad\"] = Module[\"asm\"][\"MirrorPad\"]).apply(null, arguments);\n        };\n        var _Multiply = Module[\"_Multiply\"] = function() {\n          return (_Multiply = Module[\"_Multiply\"] = Module[\"asm\"][\"Multiply\"]).apply(null, arguments);\n        };\n        var _Neg = Module[\"_Neg\"] = function() {\n          return (_Neg = Module[\"_Neg\"] = Module[\"asm\"][\"Neg\"]).apply(null, arguments);\n        };\n        var _NonMaxSuppressionV3 = Module[\"_NonMaxSuppressionV3\"] = function() {\n          return (_NonMaxSuppressionV3 = Module[\"_NonMaxSuppressionV3\"] = Module[\"asm\"][\"NonMaxSuppressionV3\"]).apply(null, arguments);\n        };\n        var _NonMaxSuppressionV4 = Module[\"_NonMaxSuppressionV4\"] = function() {\n          return (_NonMaxSuppressionV4 = Module[\"_NonMaxSuppressionV4\"] = Module[\"asm\"][\"NonMaxSuppressionV4\"]).apply(null, arguments);\n        };\n        var _NonMaxSuppressionV5 = Module[\"_NonMaxSuppressionV5\"] = function() {\n          return (_NonMaxSuppressionV5 = Module[\"_NonMaxSuppressionV5\"] = Module[\"asm\"][\"NonMaxSuppressionV5\"]).apply(null, arguments);\n        };\n        var _NotEqual = Module[\"_NotEqual\"] = function() {\n          return (_NotEqual = Module[\"_NotEqual\"] = Module[\"asm\"][\"NotEqual\"]).apply(null, arguments);\n        };\n        var _OneHot = Module[\"_OneHot\"] = function() {\n          return (_OneHot = Module[\"_OneHot\"] = Module[\"asm\"][\"OneHot\"]).apply(null, arguments);\n        };\n        var _PadV2 = Module[\"_PadV2\"] = function() {\n          return (_PadV2 = Module[\"_PadV2\"] = Module[\"asm\"][\"PadV2\"]).apply(null, arguments);\n        };\n        var _Pow = Module[\"_Pow\"] = function() {\n          return (_Pow = Module[\"_Pow\"] = Module[\"asm\"][\"Pow\"]).apply(null, arguments);\n        };\n        var _Prelu = Module[\"_Prelu\"] = function() {\n          return (_Prelu = Module[\"_Prelu\"] = Module[\"asm\"][\"Prelu\"]).apply(null, arguments);\n        };\n        var _Prod = Module[\"_Prod\"] = function() {\n          return (_Prod = Module[\"_Prod\"] = Module[\"asm\"][\"Prod\"]).apply(null, arguments);\n        };\n        var _RealDiv = Module[\"_RealDiv\"] = function() {\n          return (_RealDiv = Module[\"_RealDiv\"] = Module[\"asm\"][\"RealDiv\"]).apply(null, arguments);\n        };\n        var _Relu = Module[\"_Relu\"] = function() {\n          return (_Relu = Module[\"_Relu\"] = Module[\"asm\"][\"Relu\"]).apply(null, arguments);\n        };\n        var _Relu6 = Module[\"_Relu6\"] = function() {\n          return (_Relu6 = Module[\"_Relu6\"] = Module[\"asm\"][\"Relu6\"]).apply(null, arguments);\n        };\n        var _ResizeBilinear = Module[\"_ResizeBilinear\"] = function() {\n          return (_ResizeBilinear = Module[\"_ResizeBilinear\"] = Module[\"asm\"][\"ResizeBilinear\"]).apply(null, arguments);\n        };\n        var _ResizeNearestNeighbor = Module[\"_ResizeNearestNeighbor\"] = function() {\n          return (_ResizeNearestNeighbor = Module[\"_ResizeNearestNeighbor\"] = Module[\"asm\"][\"ResizeNearestNeighbor\"]).apply(null, arguments);\n        };\n        var _Reverse = Module[\"_Reverse\"] = function() {\n          return (_Reverse = Module[\"_Reverse\"] = Module[\"asm\"][\"Reverse\"]).apply(null, arguments);\n        };\n        var _RotateWithOffset = Module[\"_RotateWithOffset\"] = function() {\n          return (_RotateWithOffset = Module[\"_RotateWithOffset\"] = Module[\"asm\"][\"RotateWithOffset\"]).apply(null, arguments);\n        };\n        var _Round = Module[\"_Round\"] = function() {\n          return (_Round = Module[\"_Round\"] = Module[\"asm\"][\"Round\"]).apply(null, arguments);\n        };\n        var _Rsqrt = Module[\"_Rsqrt\"] = function() {\n          return (_Rsqrt = Module[\"_Rsqrt\"] = Module[\"asm\"][\"Rsqrt\"]).apply(null, arguments);\n        };\n        var _ScatterNd = Module[\"_ScatterNd\"] = function() {\n          return (_ScatterNd = Module[\"_ScatterNd\"] = Module[\"asm\"][\"ScatterNd\"]).apply(null, arguments);\n        };\n        var _SelectV2 = Module[\"_SelectV2\"] = function() {\n          return (_SelectV2 = Module[\"_SelectV2\"] = Module[\"asm\"][\"SelectV2\"]).apply(null, arguments);\n        };\n        var _Sigmoid = Module[\"_Sigmoid\"] = function() {\n          return (_Sigmoid = Module[\"_Sigmoid\"] = Module[\"asm\"][\"Sigmoid\"]).apply(null, arguments);\n        };\n        var _Sin = Module[\"_Sin\"] = function() {\n          return (_Sin = Module[\"_Sin\"] = Module[\"asm\"][\"Sin\"]).apply(null, arguments);\n        };\n        var _Softmax = Module[\"_Softmax\"] = function() {\n          return (_Softmax = Module[\"_Softmax\"] = Module[\"asm\"][\"Softmax\"]).apply(null, arguments);\n        };\n        var _SparseFillEmptyRows = Module[\"_SparseFillEmptyRows\"] = function() {\n          return (_SparseFillEmptyRows = Module[\"_SparseFillEmptyRows\"] = Module[\"asm\"][\"SparseFillEmptyRows\"]).apply(null, arguments);\n        };\n        var _SparseReshape = Module[\"_SparseReshape\"] = function() {\n          return (_SparseReshape = Module[\"_SparseReshape\"] = Module[\"asm\"][\"SparseReshape\"]).apply(null, arguments);\n        };\n        var _SparseSegmentReduction = Module[\"_SparseSegmentReduction\"] = function() {\n          return (_SparseSegmentReduction = Module[\"_SparseSegmentReduction\"] = Module[\"asm\"][\"SparseSegmentReduction\"]).apply(null, arguments);\n        };\n        var _Sqrt = Module[\"_Sqrt\"] = function() {\n          return (_Sqrt = Module[\"_Sqrt\"] = Module[\"asm\"][\"Sqrt\"]).apply(null, arguments);\n        };\n        var _Square = Module[\"_Square\"] = function() {\n          return (_Square = Module[\"_Square\"] = Module[\"asm\"][\"Square\"]).apply(null, arguments);\n        };\n        var _SquaredDifference = Module[\"_SquaredDifference\"] = function() {\n          return (_SquaredDifference = Module[\"_SquaredDifference\"] = Module[\"asm\"][\"SquaredDifference\"]).apply(null, arguments);\n        };\n        var _Step = Module[\"_Step\"] = function() {\n          return (_Step = Module[\"_Step\"] = Module[\"asm\"][\"Step\"]).apply(null, arguments);\n        };\n        var _StridedSlice = Module[\"_StridedSlice\"] = function() {\n          return (_StridedSlice = Module[\"_StridedSlice\"] = Module[\"asm\"][\"StridedSlice\"]).apply(null, arguments);\n        };\n        var _Sub = Module[\"_Sub\"] = function() {\n          return (_Sub = Module[\"_Sub\"] = Module[\"asm\"][\"Sub\"]).apply(null, arguments);\n        };\n        var _Sum = Module[\"_Sum\"] = function() {\n          return (_Sum = Module[\"_Sum\"] = Module[\"asm\"][\"Sum\"]).apply(null, arguments);\n        };\n        var _Tan = Module[\"_Tan\"] = function() {\n          return (_Tan = Module[\"_Tan\"] = Module[\"asm\"][\"Tan\"]).apply(null, arguments);\n        };\n        var _Tanh = Module[\"_Tanh\"] = function() {\n          return (_Tanh = Module[\"_Tanh\"] = Module[\"asm\"][\"Tanh\"]).apply(null, arguments);\n        };\n        var _Tile = Module[\"_Tile\"] = function() {\n          return (_Tile = Module[\"_Tile\"] = Module[\"asm\"][\"Tile\"]).apply(null, arguments);\n        };\n        var _TopK = Module[\"_TopK\"] = function() {\n          return (_TopK = Module[\"_TopK\"] = Module[\"asm\"][\"TopK\"]).apply(null, arguments);\n        };\n        var _Transform = Module[\"_Transform\"] = function() {\n          return (_Transform = Module[\"_Transform\"] = Module[\"asm\"][\"Transform\"]).apply(null, arguments);\n        };\n        var _Transpose = Module[\"_Transpose\"] = function() {\n          return (_Transpose = Module[\"_Transpose\"] = Module[\"asm\"][\"Transpose\"]).apply(null, arguments);\n        };\n        var __FusedMatMul = Module[\"__FusedMatMul\"] = function() {\n          return (__FusedMatMul = Module[\"__FusedMatMul\"] = Module[\"asm\"][\"_FusedMatMul\"]).apply(null, arguments);\n        };\n        var _malloc = Module[\"_malloc\"] = function() {\n          return (_malloc = Module[\"_malloc\"] = Module[\"asm\"][\"malloc\"]).apply(null, arguments);\n        };\n        var _free = Module[\"_free\"] = function() {\n          return (_free = Module[\"_free\"] = Module[\"asm\"][\"free\"]).apply(null, arguments);\n        };\n        var ___errno_location = Module[\"___errno_location\"] = function() {\n          return (___errno_location = Module[\"___errno_location\"] = Module[\"asm\"][\"__errno_location\"]).apply(null, arguments);\n        };\n        var _emscripten_main_thread_process_queued_calls = Module[\"_emscripten_main_thread_process_queued_calls\"] = function() {\n          return (_emscripten_main_thread_process_queued_calls = Module[\"_emscripten_main_thread_process_queued_calls\"] = Module[\"asm\"][\"emscripten_main_thread_process_queued_calls\"]).apply(null, arguments);\n        };\n        var stackSave = Module[\"stackSave\"] = function() {\n          return (stackSave = Module[\"stackSave\"] = Module[\"asm\"][\"stackSave\"]).apply(null, arguments);\n        };\n        var stackRestore = Module[\"stackRestore\"] = function() {\n          return (stackRestore = Module[\"stackRestore\"] = Module[\"asm\"][\"stackRestore\"]).apply(null, arguments);\n        };\n        var stackAlloc = Module[\"stackAlloc\"] = function() {\n          return (stackAlloc = Module[\"stackAlloc\"] = Module[\"asm\"][\"stackAlloc\"]).apply(null, arguments);\n        };\n        var dynCall_iijjiiii = Module[\"dynCall_iijjiiii\"] = function() {\n          return (dynCall_iijjiiii = Module[\"dynCall_iijjiiii\"] = Module[\"asm\"][\"dynCall_iijjiiii\"]).apply(null, arguments);\n        };\n        var dynCall_jiji = Module[\"dynCall_jiji\"] = function() {\n          return (dynCall_jiji = Module[\"dynCall_jiji\"] = Module[\"asm\"][\"dynCall_jiji\"]).apply(null, arguments);\n        };\n        Module[\"cwrap\"] = cwrap;\n        var calledRun;\n        function ExitStatus(status) {\n          this.name = \"ExitStatus\";\n          this.message = \"Program terminated with exit(\" + status + \")\";\n          this.status = status;\n        }\n        dependenciesFulfilled = function runCaller() {\n          if (!calledRun)\n            run();\n          if (!calledRun)\n            dependenciesFulfilled = runCaller;\n        };\n        function run(args) {\n          args = args || arguments_;\n          if (runDependencies > 0) {\n            return;\n          }\n          preRun();\n          if (runDependencies > 0) {\n            return;\n          }\n          function doRun() {\n            if (calledRun)\n              return;\n            calledRun = true;\n            Module[\"calledRun\"] = true;\n            if (ABORT)\n              return;\n            initRuntime();\n            readyPromiseResolve(Module);\n            if (Module[\"onRuntimeInitialized\"])\n              Module[\"onRuntimeInitialized\"]();\n            postRun();\n          }\n          if (Module[\"setStatus\"]) {\n            Module[\"setStatus\"](\"Running...\");\n            setTimeout(function() {\n              setTimeout(function() {\n                Module[\"setStatus\"](\"\");\n              }, 1);\n              doRun();\n            }, 1);\n          } else {\n            doRun();\n          }\n        }\n        Module[\"run\"] = run;\n        function procExit(code) {\n          EXITSTATUS = code;\n          if (!keepRuntimeAlive()) {\n            if (Module[\"onExit\"])\n              Module[\"onExit\"](code);\n            ABORT = true;\n          }\n          quit_(code, new ExitStatus(code));\n        }\n        if (Module[\"preInit\"]) {\n          if (typeof Module[\"preInit\"] == \"function\")\n            Module[\"preInit\"] = [Module[\"preInit\"]];\n          while (Module[\"preInit\"].length > 0) {\n            Module[\"preInit\"].pop()();\n          }\n        }\n        run();\n        var listenersAdded;\n        if (beforeListeners) {\n          listenersAdded = { uncaughtException: process.listeners(\"uncaughtException\").filter(function(listener) {\n            return !beforeListeners.uncaughtException.indexOf(listener) > -1;\n          }), unhandledRejection: process.listeners(\"unhandledRejection\").filter(function(listener) {\n            return !beforeListeners.unhandledRejection.indexOf(listener) > -1;\n          }) };\n        }\n        var actualModule;\n        if (typeof WasmBackendModule3 !== \"undefined\") {\n          actualModule = WasmBackendModule3;\n        } else if (typeof WasmBackendModuleThreadedSimd !== \"undefined\") {\n          actualModule = WasmBackendModuleThreadedSimd;\n        } else {\n          throw new Error(\"Could not find wasm module in post.js\");\n        }\n        if (listenersAdded) {\n          var tmpDispose = actualModule[\"_dispose\"];\n          actualModule[\"_dispose\"] = function() {\n            tmpDispose();\n            listenersAdded.uncaughtException.forEach(function(listener) {\n              process.removeListener(\"uncaughtException\", listener);\n            });\n            listenersAdded.unhandledRejection.forEach(function(listener) {\n              process.removeListener(\"unhandledRejection\", listener);\n            });\n          };\n        }\n        return WasmBackendModule3.ready;\n      };\n    })();\n    if (typeof exports === \"object\" && typeof module === \"object\")\n      module.exports = WasmBackendModule2;\n    else if (typeof define === \"function\" && define[\"amd\"])\n      define([], function() {\n        return WasmBackendModule2;\n      });\n    else if (typeof exports === \"object\")\n      exports[\"WasmBackendModule\"] = WasmBackendModule2;\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/backend.js\nvar EPSILON_FLOAT32 = 1e-7;\nvar EPSILON_FLOAT16 = 1e-4;\nvar DataStorage = class {\n  constructor(backend2, dataMover) {\n    this.backend = backend2;\n    this.dataMover = dataMover;\n    this.data = /* @__PURE__ */ new WeakMap();\n    this.dataIdsCount = 0;\n  }\n  get(dataId) {\n    if (!this.data.has(dataId)) {\n      this.dataMover.moveData(this.backend, dataId);\n    }\n    return this.data.get(dataId);\n  }\n  set(dataId, value) {\n    this.dataIdsCount++;\n    this.data.set(dataId, value);\n  }\n  has(dataId) {\n    return this.data.has(dataId);\n  }\n  delete(dataId) {\n    this.dataIdsCount--;\n    return this.data.delete(dataId);\n  }\n  numDataIds() {\n    return this.dataIdsCount;\n  }\n};\nvar KernelBackend = class {\n  refCount(dataId) {\n    return notYetImplemented(\"refCount\");\n  }\n  incRef(dataId) {\n    return notYetImplemented(\"incRef\");\n  }\n  timerAvailable() {\n    return true;\n  }\n  time(f) {\n    return notYetImplemented(\"time\");\n  }\n  read(dataId) {\n    return notYetImplemented(\"read\");\n  }\n  readSync(dataId) {\n    return notYetImplemented(\"readSync\");\n  }\n  readToGPU(dataId, options) {\n    return notYetImplemented(\"readToGPU\");\n  }\n  numDataIds() {\n    return notYetImplemented(\"numDataIds\");\n  }\n  disposeData(dataId, force) {\n    return notYetImplemented(\"disposeData\");\n  }\n  write(values, shape, dtype) {\n    return notYetImplemented(\"write\");\n  }\n  move(dataId, values, shape, dtype, refCount) {\n    return notYetImplemented(\"move\");\n  }\n  memory() {\n    return notYetImplemented(\"memory\");\n  }\n  floatPrecision() {\n    return notYetImplemented(\"floatPrecision\");\n  }\n  epsilon() {\n    return this.floatPrecision() === 32 ? EPSILON_FLOAT32 : EPSILON_FLOAT16;\n  }\n  dispose() {\n    return notYetImplemented(\"dispose\");\n  }\n};\nfunction notYetImplemented(kernelName) {\n  throw new Error(`'${kernelName}' not yet implemented or not found in the registry. This kernel may not be supported by the tfjs backend you have chosen`);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/util_base.js\nfunction shuffle(array2) {\n  let counter = array2.length;\n  let index = 0;\n  while (counter > 0) {\n    index = Math.random() * counter | 0;\n    counter--;\n    swap(array2, counter, index);\n  }\n}\nfunction shuffleCombo(array2, array22) {\n  if (array2.length !== array22.length) {\n    throw new Error(`Array sizes must match to be shuffled together First array length was ${array2.length}Second array length was ${array22.length}`);\n  }\n  let counter = array2.length;\n  let index = 0;\n  while (counter > 0) {\n    index = Math.random() * counter | 0;\n    counter--;\n    swap(array2, counter, index);\n    swap(array22, counter, index);\n  }\n}\nfunction clamp(min7, x, max7) {\n  return Math.max(min7, Math.min(x, max7));\n}\nfunction nearestLargerEven(val) {\n  return val % 2 === 0 ? val : val + 1;\n}\nfunction swap(object, left, right) {\n  const temp = object[left];\n  object[left] = object[right];\n  object[right] = temp;\n}\nfunction sum(arr) {\n  let sum7 = 0;\n  for (let i2 = 0; i2 < arr.length; i2++) {\n    sum7 += arr[i2];\n  }\n  return sum7;\n}\nfunction randUniform(a, b) {\n  const r2 = Math.random();\n  return b * r2 + (1 - r2) * a;\n}\nfunction distSquared(a, b) {\n  let result = 0;\n  for (let i2 = 0; i2 < a.length; i2++) {\n    const diff = Number(a[i2]) - Number(b[i2]);\n    result += diff * diff;\n  }\n  return result;\n}\nfunction assert(expr, msg) {\n  if (!expr) {\n    throw new Error(typeof msg === \"string\" ? msg : msg());\n  }\n}\nfunction assertShapesMatch(shapeA, shapeB, errorMessagePrefix = \"\") {\n  assert(arraysEqual(shapeA, shapeB), () => errorMessagePrefix + ` Shapes ${shapeA} and ${shapeB} must match`);\n}\nfunction assertNonNull(a) {\n  assert(a != null, () => `The input to the tensor constructor must be a non-null value.`);\n}\nfunction flatten(arr, result = [], skipTypedArray = false) {\n  if (result == null) {\n    result = [];\n  }\n  if (Array.isArray(arr) || isTypedArray(arr) && !skipTypedArray) {\n    for (let i2 = 0; i2 < arr.length; ++i2) {\n      flatten(arr[i2], result, skipTypedArray);\n    }\n  } else {\n    result.push(arr);\n  }\n  return result;\n}\nfunction sizeFromShape(shape) {\n  if (shape.length === 0) {\n    return 1;\n  }\n  let size = shape[0];\n  for (let i2 = 1; i2 < shape.length; i2++) {\n    size *= shape[i2];\n  }\n  return size;\n}\nfunction isScalarShape(shape) {\n  return shape.length === 0;\n}\nfunction arraysEqual(n1, n2) {\n  if (n1 === n2) {\n    return true;\n  }\n  if (n1 == null || n2 == null) {\n    return false;\n  }\n  if (n1.length !== n2.length) {\n    return false;\n  }\n  for (let i2 = 0; i2 < n1.length; i2++) {\n    if (n1[i2] !== n2[i2]) {\n      return false;\n    }\n  }\n  return true;\n}\nfunction isInt(a) {\n  return a % 1 === 0;\n}\nfunction tanh(x) {\n  if (Math.tanh != null) {\n    return Math.tanh(x);\n  }\n  if (x === Infinity) {\n    return 1;\n  } else if (x === -Infinity) {\n    return -1;\n  } else {\n    const e2x = Math.exp(2 * x);\n    return (e2x - 1) / (e2x + 1);\n  }\n}\nfunction sizeToSquarishShape(size) {\n  const width = Math.ceil(Math.sqrt(size));\n  return [width, Math.ceil(size / width)];\n}\nfunction createShuffledIndices(n2) {\n  const shuffledIndices = new Uint32Array(n2);\n  for (let i2 = 0; i2 < n2; ++i2) {\n    shuffledIndices[i2] = i2;\n  }\n  shuffle(shuffledIndices);\n  return shuffledIndices;\n}\nfunction rightPad(a, size) {\n  if (size <= a.length) {\n    return a;\n  }\n  return a + \" \".repeat(size - a.length);\n}\nfunction repeatedTry(checkFn, delayFn = (counter) => 0, maxCounter) {\n  return new Promise((resolve, reject) => {\n    let tryCount = 0;\n    const tryFn = () => {\n      if (checkFn()) {\n        resolve();\n        return;\n      }\n      tryCount++;\n      const nextBackoff = delayFn(tryCount);\n      if (maxCounter != null && tryCount >= maxCounter) {\n        reject();\n        return;\n      }\n      setTimeout(tryFn, nextBackoff);\n    };\n    tryFn();\n  });\n}\nfunction inferFromImplicitShape(shape, size) {\n  let shapeProd = 1;\n  let implicitIdx = -1;\n  for (let i2 = 0; i2 < shape.length; ++i2) {\n    if (shape[i2] >= 0) {\n      shapeProd *= shape[i2];\n    } else if (shape[i2] === -1) {\n      if (implicitIdx !== -1) {\n        throw Error(`Shapes can only have 1 implicit size. Found -1 at dim ${implicitIdx} and dim ${i2}`);\n      }\n      implicitIdx = i2;\n    } else if (shape[i2] < 0) {\n      throw Error(`Shapes can not be < 0. Found ${shape[i2]} at dim ${i2}`);\n    }\n  }\n  if (implicitIdx === -1) {\n    if (size > 0 && size !== shapeProd) {\n      throw Error(`Size(${size}) must match the product of shape ${shape}`);\n    }\n    return shape;\n  }\n  if (shapeProd === 0) {\n    throw Error(`Cannot infer the missing size in [${shape}] when there are 0 elements`);\n  }\n  if (size % shapeProd !== 0) {\n    throw Error(`The implicit shape can't be a fractional number. Got ${size} / ${shapeProd}`);\n  }\n  const newShape = shape.slice();\n  newShape[implicitIdx] = size / shapeProd;\n  return newShape;\n}\nfunction parseAxisParam(axis, shape) {\n  const rank = shape.length;\n  axis = axis == null ? shape.map((s2, i2) => i2) : [].concat(axis);\n  assert(axis.every((ax) => ax >= -rank && ax < rank), () => `All values in axis param must be in range [-${rank}, ${rank}) but got axis ${axis}`);\n  assert(axis.every((ax) => isInt(ax)), () => `All values in axis param must be integers but got axis ${axis}`);\n  return axis.map((a) => a < 0 ? rank + a : a);\n}\nfunction squeezeShape(shape, axis) {\n  const newShape = [];\n  const keptDims = [];\n  const isEmptyArray = axis != null && Array.isArray(axis) && axis.length === 0;\n  const axes = axis == null || isEmptyArray ? null : parseAxisParam(axis, shape).sort();\n  let j = 0;\n  for (let i2 = 0; i2 < shape.length; ++i2) {\n    if (axes != null) {\n      if (axes[j] === i2 && shape[i2] !== 1) {\n        throw new Error(`Can't squeeze axis ${i2} since its dim '${shape[i2]}' is not 1`);\n      }\n      if ((axes[j] == null || axes[j] > i2) && shape[i2] === 1) {\n        newShape.push(shape[i2]);\n        keptDims.push(i2);\n      }\n      if (axes[j] <= i2) {\n        j++;\n      }\n    }\n    if (shape[i2] !== 1) {\n      newShape.push(shape[i2]);\n      keptDims.push(i2);\n    }\n  }\n  return { newShape, keptDims };\n}\nfunction getTypedArrayFromDType(dtype, size) {\n  let values = null;\n  if (dtype == null || dtype === \"float32\") {\n    values = new Float32Array(size);\n  } else if (dtype === \"int32\") {\n    values = new Int32Array(size);\n  } else if (dtype === \"bool\") {\n    values = new Uint8Array(size);\n  } else {\n    throw new Error(`Unknown data type ${dtype}`);\n  }\n  return values;\n}\nfunction getArrayFromDType(dtype, size) {\n  let values = null;\n  if (dtype == null || dtype === \"float32\") {\n    values = new Float32Array(size);\n  } else if (dtype === \"int32\") {\n    values = new Int32Array(size);\n  } else if (dtype === \"bool\") {\n    values = new Uint8Array(size);\n  } else if (dtype === \"string\") {\n    values = new Array(size);\n  } else {\n    throw new Error(`Unknown data type ${dtype}`);\n  }\n  return values;\n}\nfunction checkConversionForErrors(vals, dtype) {\n  for (let i2 = 0; i2 < vals.length; i2++) {\n    const num = vals[i2];\n    if (isNaN(num) || !isFinite(num)) {\n      throw Error(`A tensor of type ${dtype} being uploaded contains ${num}.`);\n    }\n  }\n}\nfunction isValidDtype(dtype) {\n  return dtype === \"bool\" || dtype === \"complex64\" || dtype === \"float32\" || dtype === \"int32\" || dtype === \"string\";\n}\nfunction hasEncodingLoss(oldType, newType) {\n  if (newType === \"complex64\") {\n    return false;\n  }\n  if (newType === \"float32\" && oldType !== \"complex64\") {\n    return false;\n  }\n  if (newType === \"int32\" && oldType !== \"float32\" && oldType !== \"complex64\") {\n    return false;\n  }\n  if (newType === \"bool\" && oldType === \"bool\") {\n    return false;\n  }\n  return true;\n}\nfunction isTypedArray(a) {\n  return a instanceof Float32Array || a instanceof Int32Array || a instanceof Uint8Array || a instanceof Uint8ClampedArray;\n}\nfunction bytesPerElement(dtype) {\n  if (dtype === \"float32\" || dtype === \"int32\") {\n    return 4;\n  } else if (dtype === \"complex64\") {\n    return 8;\n  } else if (dtype === \"bool\") {\n    return 1;\n  } else {\n    throw new Error(`Unknown dtype ${dtype}`);\n  }\n}\nfunction bytesFromStringArray(arr) {\n  if (arr == null) {\n    return 0;\n  }\n  let bytes = 0;\n  arr.forEach((x) => bytes += x.length);\n  return bytes;\n}\nfunction isString(value) {\n  return typeof value === \"string\" || value instanceof String;\n}\nfunction isBoolean(value) {\n  return typeof value === \"boolean\";\n}\nfunction isNumber(value) {\n  return typeof value === \"number\";\n}\nfunction inferDtype(values) {\n  if (Array.isArray(values)) {\n    return inferDtype(values[0]);\n  }\n  if (values instanceof Float32Array) {\n    return \"float32\";\n  } else if (values instanceof Int32Array || values instanceof Uint8Array || values instanceof Uint8ClampedArray) {\n    return \"int32\";\n  } else if (isNumber(values)) {\n    return \"float32\";\n  } else if (isString(values)) {\n    return \"string\";\n  } else if (isBoolean(values)) {\n    return \"bool\";\n  }\n  return \"float32\";\n}\nfunction isFunction(f) {\n  return !!(f && f.constructor && f.call && f.apply);\n}\nfunction nearestDivisor(size, start) {\n  for (let i2 = start; i2 < size; ++i2) {\n    if (size % i2 === 0) {\n      return i2;\n    }\n  }\n  return size;\n}\nfunction computeStrides(shape) {\n  const rank = shape.length;\n  if (rank < 2) {\n    return [];\n  }\n  const strides = new Array(rank - 1);\n  strides[rank - 2] = shape[rank - 1];\n  for (let i2 = rank - 3; i2 >= 0; --i2) {\n    strides[i2] = strides[i2 + 1] * shape[i2 + 1];\n  }\n  return strides;\n}\nfunction createNestedArray(offset, shape, a, isComplex = false) {\n  const ret = new Array();\n  if (shape.length === 1) {\n    const d = shape[0] * (isComplex ? 2 : 1);\n    for (let i2 = 0; i2 < d; i2++) {\n      ret[i2] = a[offset + i2];\n    }\n  } else {\n    const d = shape[0];\n    const rest = shape.slice(1);\n    const len = rest.reduce((acc, c) => acc * c) * (isComplex ? 2 : 1);\n    for (let i2 = 0; i2 < d; i2++) {\n      ret[i2] = createNestedArray(offset + i2 * len, rest, a, isComplex);\n    }\n  }\n  return ret;\n}\nfunction toNestedArray(shape, a, isComplex = false) {\n  if (shape.length === 0) {\n    return a[0];\n  }\n  const size = shape.reduce((acc, c) => acc * c) * (isComplex ? 2 : 1);\n  if (size === 0) {\n    return [];\n  }\n  if (size !== a.length) {\n    throw new Error(`[${shape}] does not match the input size ${a.length}${isComplex ? \" for a complex tensor\" : \"\"}.`);\n  }\n  return createNestedArray(0, shape, a, isComplex);\n}\nfunction makeOnesTypedArray(size, dtype) {\n  const array2 = makeZerosTypedArray(size, dtype);\n  for (let i2 = 0; i2 < array2.length; i2++) {\n    array2[i2] = 1;\n  }\n  return array2;\n}\nfunction makeZerosTypedArray(size, dtype) {\n  if (dtype == null || dtype === \"float32\" || dtype === \"complex64\") {\n    return new Float32Array(size);\n  } else if (dtype === \"int32\") {\n    return new Int32Array(size);\n  } else if (dtype === \"bool\") {\n    return new Uint8Array(size);\n  } else {\n    throw new Error(`Unknown data type ${dtype}`);\n  }\n}\nfunction makeZerosNestedTypedArray(shape, dtype) {\n  const size = shape.reduce((prev, curr) => prev * curr, 1);\n  if (dtype == null || dtype === \"float32\") {\n    return toNestedArray(shape, new Float32Array(size));\n  } else if (dtype === \"int32\") {\n    return toNestedArray(shape, new Int32Array(size));\n  } else if (dtype === \"bool\") {\n    return toNestedArray(shape, new Uint8Array(size));\n  } else {\n    throw new Error(`Unknown data type ${dtype}`);\n  }\n}\nfunction assertNonNegativeIntegerDimensions(shape) {\n  shape.forEach((dimSize) => {\n    assert(Number.isInteger(dimSize) && dimSize >= 0, () => `Tensor must have a shape comprised of positive integers but got shape [${shape}].`);\n  });\n}\nfunction locToIndex(locs, rank, strides) {\n  if (rank === 0) {\n    return 0;\n  } else if (rank === 1) {\n    return locs[0];\n  }\n  let index = locs[locs.length - 1];\n  for (let i2 = 0; i2 < locs.length - 1; ++i2) {\n    index += strides[i2] * locs[i2];\n  }\n  return index;\n}\nfunction indexToLoc(index, rank, strides) {\n  if (rank === 0) {\n    return [];\n  } else if (rank === 1) {\n    return [index];\n  }\n  const locs = new Array(rank);\n  for (let i2 = 0; i2 < locs.length - 1; ++i2) {\n    locs[i2] = Math.floor(index / strides[i2]);\n    index -= locs[i2] * strides[i2];\n  }\n  locs[locs.length - 1] = index;\n  return locs;\n}\nfunction isPromise(object) {\n  return object && object.then && typeof object.then === \"function\";\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/environment.js\nvar TENSORFLOWJS_FLAGS_PREFIX = \"tfjsflags\";\nvar Environment = class {\n  constructor(global2) {\n    this.global = global2;\n    this.flags = {};\n    this.flagRegistry = {};\n    this.urlFlags = {};\n    this.getQueryParams = getQueryParams;\n    this.populateURLFlags();\n  }\n  setPlatform(platformName, platform) {\n    if (this.platform != null) {\n      if (!(env().getBool(\"IS_TEST\") || env().getBool(\"PROD\"))) {\n        console.warn(`Platform ${this.platformName} has already been set. Overwriting the platform with ${platformName}.`);\n      }\n    }\n    this.platformName = platformName;\n    this.platform = platform;\n  }\n  registerFlag(flagName, evaluationFn, setHook) {\n    this.flagRegistry[flagName] = { evaluationFn, setHook };\n    if (this.urlFlags[flagName] != null) {\n      const flagValue = this.urlFlags[flagName];\n      if (!(env().getBool(\"IS_TEST\") || env().getBool(\"PROD\"))) {\n        console.warn(`Setting feature override from URL ${flagName}: ${flagValue}.`);\n      }\n      this.set(flagName, flagValue);\n    }\n  }\n  async getAsync(flagName) {\n    if (flagName in this.flags) {\n      return this.flags[flagName];\n    }\n    this.flags[flagName] = await this.evaluateFlag(flagName);\n    return this.flags[flagName];\n  }\n  get(flagName) {\n    if (flagName in this.flags) {\n      return this.flags[flagName];\n    }\n    const flagValue = this.evaluateFlag(flagName);\n    if (isPromise(flagValue)) {\n      throw new Error(`Flag ${flagName} cannot be synchronously evaluated. Please use getAsync() instead.`);\n    }\n    this.flags[flagName] = flagValue;\n    return this.flags[flagName];\n  }\n  getNumber(flagName) {\n    return this.get(flagName);\n  }\n  getBool(flagName) {\n    return this.get(flagName);\n  }\n  getFlags() {\n    return this.flags;\n  }\n  get features() {\n    return this.flags;\n  }\n  set(flagName, value) {\n    if (this.flagRegistry[flagName] == null) {\n      throw new Error(`Cannot set flag ${flagName} as it has not been registered.`);\n    }\n    this.flags[flagName] = value;\n    if (this.flagRegistry[flagName].setHook != null) {\n      this.flagRegistry[flagName].setHook(value);\n    }\n  }\n  evaluateFlag(flagName) {\n    if (this.flagRegistry[flagName] == null) {\n      throw new Error(`Cannot evaluate flag '${flagName}': no evaluation function found.`);\n    }\n    return this.flagRegistry[flagName].evaluationFn();\n  }\n  setFlags(flags) {\n    this.flags = Object.assign({}, flags);\n  }\n  reset() {\n    this.flags = {};\n    this.urlFlags = {};\n    this.populateURLFlags();\n  }\n  populateURLFlags() {\n    if (typeof this.global === \"undefined\" || typeof this.global.location === \"undefined\" || typeof this.global.location.search === \"undefined\") {\n      return;\n    }\n    const urlParams = this.getQueryParams(this.global.location.search);\n    if (TENSORFLOWJS_FLAGS_PREFIX in urlParams) {\n      const keyValues = urlParams[TENSORFLOWJS_FLAGS_PREFIX].split(\",\");\n      keyValues.forEach((keyValue) => {\n        const [key, value] = keyValue.split(\":\");\n        this.urlFlags[key] = parseValue(key, value);\n      });\n    }\n  }\n};\nfunction getQueryParams(queryString) {\n  const params = {};\n  queryString.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g, (s2, ...t2) => {\n    decodeParam(params, t2[0], t2[1]);\n    return t2.join(\"=\");\n  });\n  return params;\n}\nfunction decodeParam(params, name, value) {\n  params[decodeURIComponent(name)] = decodeURIComponent(value || \"\");\n}\nfunction parseValue(flagName, value) {\n  value = value.toLowerCase();\n  if (value === \"true\" || value === \"false\") {\n    return value === \"true\";\n  } else if (`${+value}` === value) {\n    return +value;\n  }\n  throw new Error(`Could not parse value flag value ${value} for flag ${flagName}.`);\n}\nfunction env() {\n  return ENV;\n}\nvar ENV = null;\nfunction setEnvironmentGlobal(environment) {\n  ENV = environment;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/global_util.js\nvar globalNameSpace;\nfunction getGlobalNamespace() {\n  if (globalNameSpace == null) {\n    let ns;\n    if (typeof window !== \"undefined\") {\n      ns = window;\n    } else if (typeof global !== \"undefined\") {\n      ns = global;\n    } else if (typeof process !== \"undefined\") {\n      ns = process;\n    } else if (typeof self !== \"undefined\") {\n      ns = self;\n    } else {\n      throw new Error(\"Could not find a global object\");\n    }\n    globalNameSpace = ns;\n  }\n  return globalNameSpace;\n}\nfunction getGlobalMap() {\n  const ns = getGlobalNamespace();\n  if (ns._tfGlobals == null) {\n    ns._tfGlobals = /* @__PURE__ */ new Map();\n  }\n  return ns._tfGlobals;\n}\nfunction getGlobal(key, init2) {\n  const globalMap = getGlobalMap();\n  if (globalMap.has(key)) {\n    return globalMap.get(key);\n  } else {\n    const singleton = init2();\n    globalMap.set(key, singleton);\n    return globalMap.get(key);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/kernel_names.js\nvar Abs = \"Abs\";\nvar Acos = \"Acos\";\nvar Acosh = \"Acosh\";\nvar Add = \"Add\";\nvar AddN = \"AddN\";\nvar All = \"All\";\nvar Any = \"Any\";\nvar ArgMax = \"ArgMax\";\nvar ArgMin = \"ArgMin\";\nvar Asin = \"Asin\";\nvar Asinh = \"Asinh\";\nvar Atan = \"Atan\";\nvar Atanh = \"Atanh\";\nvar Atan2 = \"Atan2\";\nvar AvgPool = \"AvgPool\";\nvar AvgPoolGrad = \"AvgPoolGrad\";\nvar AvgPool3D = \"AvgPool3D\";\nvar AvgPool3DGrad = \"AvgPool3DGrad\";\nvar BatchMatMul = \"BatchMatMul\";\nvar BatchToSpaceND = \"BatchToSpaceND\";\nvar Bincount = \"Bincount\";\nvar BroadcastTo = \"BroadcastTo\";\nvar BroadcastArgs = \"BroadcastArgs\";\nvar Cast = \"Cast\";\nvar Ceil = \"Ceil\";\nvar ClipByValue = \"ClipByValue\";\nvar Complex = \"Complex\";\nvar ComplexAbs = \"ComplexAbs\";\nvar Concat = \"Concat\";\nvar Conv2D = \"Conv2D\";\nvar Conv2DBackpropFilter = \"Conv2DBackpropFilter\";\nvar Conv2DBackpropInput = \"Conv2DBackpropInput\";\nvar Conv3D = \"Conv3D\";\nvar Conv3DBackpropFilterV2 = \"Conv3DBackpropFilterV2\";\nvar Conv3DBackpropInputV2 = \"Conv3DBackpropInputV2\";\nvar Cos = \"Cos\";\nvar Cosh = \"Cosh\";\nvar Cumprod = \"Cumprod\";\nvar Cumsum = \"Cumsum\";\nvar CropAndResize = \"CropAndResize\";\nvar DenseBincount = \"DenseBincount\";\nvar DepthToSpace = \"DepthToSpace\";\nvar DepthwiseConv2dNative = \"DepthwiseConv2dNative\";\nvar DepthwiseConv2dNativeBackpropFilter = \"DepthwiseConv2dNativeBackpropFilter\";\nvar DepthwiseConv2dNativeBackpropInput = \"DepthwiseConv2dNativeBackpropInput\";\nvar Diag = \"Diag\";\nvar Dilation2D = \"Dilation2D\";\nvar Dilation2DBackpropInput = \"Dilation2DBackpropInput\";\nvar Dilation2DBackpropFilter = \"Dilation2DBackpropFilter\";\nvar RealDiv = \"RealDiv\";\nvar Einsum = \"Einsum\";\nvar Elu = \"Elu\";\nvar EluGrad = \"EluGrad\";\nvar Erf = \"Erf\";\nvar Equal = \"Equal\";\nvar Exp = \"Exp\";\nvar ExpandDims = \"ExpandDims\";\nvar Expm1 = \"Expm1\";\nvar FFT = \"FFT\";\nvar Fill = \"Fill\";\nvar FlipLeftRight = \"FlipLeftRight\";\nvar Floor = \"Floor\";\nvar FloorDiv = \"FloorDiv\";\nvar FusedBatchNorm = \"FusedBatchNorm\";\nvar GatherV2 = \"GatherV2\";\nvar GatherNd = \"GatherNd\";\nvar Greater = \"Greater\";\nvar GreaterEqual = \"GreaterEqual\";\nvar Identity = \"Identity\";\nvar IFFT = \"IFFT\";\nvar Imag = \"Imag\";\nvar IsFinite = \"IsFinite\";\nvar IsInf = \"IsInf\";\nvar IsNan = \"IsNan\";\nvar LeakyRelu = \"LeakyRelu\";\nvar Less = \"Less\";\nvar LessEqual = \"LessEqual\";\nvar LinSpace = \"LinSpace\";\nvar Log = \"Log\";\nvar Log1p = \"Log1p\";\nvar LogicalAnd = \"LogicalAnd\";\nvar LogicalNot = \"LogicalNot\";\nvar LogicalOr = \"LogicalOr\";\nvar LogicalXor = \"LogicalXor\";\nvar LogSoftmax = \"LogSoftmax\";\nvar LowerBound = \"LowerBound\";\nvar LRN = \"LRN\";\nvar LRNGrad = \"LRNGrad\";\nvar Max = \"Max\";\nvar Maximum = \"Maximum\";\nvar MaxPool = \"MaxPool\";\nvar MaxPoolGrad = \"MaxPoolGrad\";\nvar MaxPool3D = \"MaxPool3D\";\nvar MaxPool3DGrad = \"MaxPool3DGrad\";\nvar MaxPoolWithArgmax = \"MaxPoolWithArgmax\";\nvar Mean = \"Mean\";\nvar Min = \"Min\";\nvar Minimum = \"Minimum\";\nvar MirrorPad = \"MirrorPad\";\nvar Mod = \"Mod\";\nvar Multinomial = \"Multinomial\";\nvar Multiply = \"Multiply\";\nvar Neg = \"Neg\";\nvar NotEqual = \"NotEqual\";\nvar NonMaxSuppressionV3 = \"NonMaxSuppressionV3\";\nvar NonMaxSuppressionV4 = \"NonMaxSuppressionV4\";\nvar NonMaxSuppressionV5 = \"NonMaxSuppressionV5\";\nvar OnesLike = \"OnesLike\";\nvar OneHot = \"OneHot\";\nvar Pack = \"Pack\";\nvar PadV2 = \"PadV2\";\nvar Pool = \"Pool\";\nvar Pow = \"Pow\";\nvar Prelu = \"Prelu\";\nvar Prod = \"Prod\";\nvar Range = \"Range\";\nvar Real = \"Real\";\nvar Reciprocal = \"Reciprocal\";\nvar Relu = \"Relu\";\nvar Reshape = \"Reshape\";\nvar ResizeNearestNeighbor = \"ResizeNearestNeighbor\";\nvar ResizeNearestNeighborGrad = \"ResizeNearestNeighborGrad\";\nvar ResizeBilinear = \"ResizeBilinear\";\nvar ResizeBilinearGrad = \"ResizeBilinearGrad\";\nvar Relu6 = \"Relu6\";\nvar Reverse = \"Reverse\";\nvar Round = \"Round\";\nvar Rsqrt = \"Rsqrt\";\nvar ScatterNd = \"ScatterNd\";\nvar SearchSorted = \"SearchSorted\";\nvar Select = \"Select\";\nvar Selu = \"Selu\";\nvar Slice = \"Slice\";\nvar Sin = \"Sin\";\nvar Sinh = \"Sinh\";\nvar Sign = \"Sign\";\nvar Sigmoid = \"Sigmoid\";\nvar Softplus = \"Softplus\";\nvar Sqrt = \"Sqrt\";\nvar Sum = \"Sum\";\nvar SpaceToBatchND = \"SpaceToBatchND\";\nvar SplitV = \"SplitV\";\nvar Softmax = \"Softmax\";\nvar SparseFillEmptyRows = \"SparseFillEmptyRows\";\nvar SparseReshape = \"SparseReshape\";\nvar SparseSegmentMean = \"SparseSegmentMean\";\nvar SparseSegmentSum = \"SparseSegmentSum\";\nvar SparseToDense = \"SparseToDense\";\nvar SquaredDifference = \"SquaredDifference\";\nvar Square = \"Square\";\nvar StridedSlice = \"StridedSlice\";\nvar StringNGrams = \"StringNGrams\";\nvar StringSplit = \"StringSplit\";\nvar StringToHashBucketFast = \"StringToHashBucketFast\";\nvar Sub = \"Sub\";\nvar Tan = \"Tan\";\nvar Tanh = \"Tanh\";\nvar Tile = \"Tile\";\nvar TopK = \"TopK\";\nvar Transform = \"Transform\";\nvar Transpose = \"Transpose\";\nvar Unique = \"Unique\";\nvar Unpack = \"Unpack\";\nvar UnsortedSegmentSum = \"UnsortedSegmentSum\";\nvar UpperBound = \"UpperBound\";\nvar ZerosLike = \"ZerosLike\";\nvar Step = \"Step\";\nvar FromPixels = \"FromPixels\";\nvar RotateWithOffset = \"RotateWithOffset\";\nvar _FusedMatMul = \"_FusedMatMul\";\nvar FusedConv2D = \"FusedConv2D\";\nvar FusedDepthwiseConv2D = \"FusedDepthwiseConv2D\";\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/log.js\nfunction warn(...msg) {\n  if (!(env().getBool(\"IS_TEST\") || env().getBool(\"PROD\"))) {\n    console.warn(...msg);\n  }\n}\nfunction log(...msg) {\n  if (!(env().getBool(\"IS_TEST\") || env().getBool(\"PROD\"))) {\n    console.log(...msg);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/kernel_registry.js\nvar kernelRegistry = getGlobal(\"kernelRegistry\", () => /* @__PURE__ */ new Map());\nvar gradRegistry = getGlobal(\"gradRegistry\", () => /* @__PURE__ */ new Map());\nfunction getKernel(kernelName, backendName) {\n  const key = makeKey(kernelName, backendName);\n  return kernelRegistry.get(key);\n}\nfunction getGradient(kernelName) {\n  return gradRegistry.get(kernelName);\n}\nfunction getKernelsForBackend(backendName) {\n  const it = kernelRegistry.entries();\n  const result = [];\n  while (true) {\n    const { done, value } = it.next();\n    if (done) {\n      break;\n    }\n    const [key, config] = value;\n    const [backend2] = key.split(\"_\");\n    if (backend2 === backendName) {\n      result.push(config);\n    }\n  }\n  return result;\n}\nfunction registerKernel(config) {\n  const { kernelName, backendName } = config;\n  const key = makeKey(kernelName, backendName);\n  if (kernelRegistry.has(key)) {\n    warn(`The kernel '${kernelName}' for backend '${backendName}' is already registered`);\n  }\n  kernelRegistry.set(key, config);\n}\nfunction registerGradient(config) {\n  const { kernelName } = config;\n  if (gradRegistry.has(kernelName)) {\n    if (env().getBool(\"DEBUG\")) {\n      warn(`Overriding the gradient for '${kernelName}'`);\n    }\n  }\n  gradRegistry.set(kernelName, config);\n}\nfunction unregisterKernel(kernelName, backendName) {\n  const key = makeKey(kernelName, backendName);\n  if (!kernelRegistry.has(key)) {\n    throw new Error(`The kernel '${kernelName}' for backend '${backendName}' is not registered`);\n  }\n  kernelRegistry.delete(key);\n}\nfunction unregisterGradient(kernelName) {\n  if (!gradRegistry.has(kernelName)) {\n    throw new Error(`The gradient '${kernelName}' for backend is not registered`);\n  }\n  gradRegistry.delete(kernelName);\n}\nfunction copyRegisteredKernels(registeredBackendName, newBackendName) {\n  const kernels = getKernelsForBackend(registeredBackendName);\n  kernels.forEach((kernelConfig) => {\n    const newKernelConfig = Object.assign({}, kernelConfig, { backendName: newBackendName });\n    registerKernel(newKernelConfig);\n  });\n}\nfunction makeKey(kernelName, backendName) {\n  return `${backendName}_${kernelName}`;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/util.js\nvar util_exports = {};\n__export(util_exports, {\n  arraysEqual: () => arraysEqual,\n  assert: () => assert,\n  assertNonNegativeIntegerDimensions: () => assertNonNegativeIntegerDimensions,\n  assertNonNull: () => assertNonNull,\n  assertShapesMatch: () => assertShapesMatch,\n  bytesFromStringArray: () => bytesFromStringArray,\n  bytesPerElement: () => bytesPerElement,\n  checkConversionForErrors: () => checkConversionForErrors,\n  clamp: () => clamp,\n  computeStrides: () => computeStrides,\n  createScalarValue: () => createScalarValue,\n  createShuffledIndices: () => createShuffledIndices,\n  decodeString: () => decodeString,\n  distSquared: () => distSquared,\n  encodeString: () => encodeString,\n  fetch: () => fetch3,\n  fingerPrint64: () => fingerPrint64,\n  flatten: () => flatten,\n  getArrayFromDType: () => getArrayFromDType,\n  getTypedArrayFromDType: () => getTypedArrayFromDType,\n  hasEncodingLoss: () => hasEncodingLoss,\n  hexToLong: () => hexToLong,\n  indexToLoc: () => indexToLoc,\n  inferDtype: () => inferDtype,\n  inferFromImplicitShape: () => inferFromImplicitShape,\n  isBoolean: () => isBoolean,\n  isFunction: () => isFunction,\n  isInt: () => isInt,\n  isNumber: () => isNumber,\n  isPromise: () => isPromise,\n  isScalarShape: () => isScalarShape,\n  isString: () => isString,\n  isTypedArray: () => isTypedArray,\n  isValidDtype: () => isValidDtype,\n  locToIndex: () => locToIndex,\n  makeOnesTypedArray: () => makeOnesTypedArray,\n  makeZerosNestedTypedArray: () => makeZerosNestedTypedArray,\n  makeZerosTypedArray: () => makeZerosTypedArray,\n  nearestDivisor: () => nearestDivisor,\n  nearestLargerEven: () => nearestLargerEven,\n  now: () => now,\n  parseAxisParam: () => parseAxisParam,\n  randUniform: () => randUniform,\n  repeatedTry: () => repeatedTry,\n  rightPad: () => rightPad,\n  shuffle: () => shuffle,\n  shuffleCombo: () => shuffleCombo,\n  sizeFromShape: () => sizeFromShape,\n  sizeToSquarishShape: () => sizeToSquarishShape,\n  squeezeShape: () => squeezeShape,\n  sum: () => sum,\n  swap: () => swap,\n  tanh: () => tanh,\n  toNestedArray: () => toNestedArray,\n  toTypedArray: () => toTypedArray\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/hash_util.js\nvar LongExports = __toESM(require_long());\nvar Long = LongExports.default || LongExports;\nfunction hexToLong(hex) {\n  return Long.fromString(hex, true, 16);\n}\nvar k0 = hexToLong(\"c3a5c85c97cb3127\");\nvar k1 = hexToLong(\"b492b66fbe98f273\");\nvar k2 = hexToLong(\"9ae16a3b2f90404f\");\nfunction shiftMix(val) {\n  return val.xor(val.shru(47));\n}\nfunction fetch2(s2, offset, numBytes) {\n  const bytes = s2.slice(offset, offset + numBytes);\n  return Long.fromBytes(Array.from(bytes), true, true);\n}\nfunction fetch64(s2, offset) {\n  return fetch2(s2, offset, 8);\n}\nfunction fetch32(s2, offset) {\n  return fetch2(s2, offset, 4);\n}\nfunction rotate64(val, shift) {\n  return shift === 0 ? val : val.shru(shift).or(val.shl(64 - shift));\n}\nfunction hashLen16(u, v, mul2 = hexToLong(\"9ddfea08eb382d69\")) {\n  let a = u.xor(v).mul(mul2);\n  a = a.xor(a.shru(47));\n  let b = v.xor(a).mul(mul2);\n  b = b.xor(b.shru(47));\n  b = b.mul(mul2);\n  return b;\n}\nfunction weakHashLen32WithSeeds(w, x, y, z, a, b) {\n  a = a.add(w);\n  b = rotate64(b.add(a).add(z), 21);\n  const c = a;\n  a = a.add(x);\n  a = a.add(y);\n  b = b.add(rotate64(a, 44));\n  return [a.add(z), b.add(c)];\n}\nfunction weakHashLen32WithSeedsStr(s2, offset, a, b) {\n  return weakHashLen32WithSeeds(fetch64(s2, offset), fetch64(s2, offset + 8), fetch64(s2, offset + 16), fetch64(s2, offset + 24), a, b);\n}\nfunction hashLen0to16(s2, len = s2.length) {\n  if (len >= 8) {\n    const mul2 = k2.add(len * 2);\n    const a = fetch64(s2, 0).add(k2);\n    const b = fetch64(s2, len - 8);\n    const c = rotate64(b, 37).mul(mul2).add(a);\n    const d = rotate64(a, 25).add(b).mul(mul2);\n    return hashLen16(c, d, mul2);\n  }\n  if (len >= 4) {\n    const mul2 = k2.add(len * 2);\n    const a = fetch32(s2, 0);\n    return hashLen16(a.shl(3).add(len), fetch32(s2, len - 4), mul2);\n  }\n  if (len > 0) {\n    const a = s2[0];\n    const b = s2[len >> 1];\n    const c = s2[len - 1];\n    const y = a + (b << 8);\n    const z = len + (c << 2);\n    return shiftMix(k2.mul(y).xor(k0.mul(z))).mul(k2);\n  }\n  return k2;\n}\nfunction hashLen17to32(s2, len = s2.length) {\n  const mul2 = k2.add(len * 2);\n  const a = fetch64(s2, 0).mul(k1);\n  const b = fetch64(s2, 8);\n  const c = fetch64(s2, len - 8).mul(mul2);\n  const d = fetch64(s2, len - 16).mul(k2);\n  return hashLen16(rotate64(a.add(b), 43).add(rotate64(c, 30)).add(d), a.add(rotate64(b.add(k2), 18)).add(c), mul2);\n}\nfunction hashLen33to64(s2, len = s2.length) {\n  const mul2 = k2.add(len * 2);\n  const a = fetch64(s2, 0).mul(k2);\n  const b = fetch64(s2, 8);\n  const c = fetch64(s2, len - 8).mul(mul2);\n  const d = fetch64(s2, len - 16).mul(k2);\n  const y = rotate64(a.add(b), 43).add(rotate64(c, 30)).add(d);\n  const z = hashLen16(y, a.add(rotate64(b.add(k2), 18)).add(c), mul2);\n  const e2 = fetch64(s2, 16).mul(mul2);\n  const f = fetch64(s2, 24);\n  const g = y.add(fetch64(s2, len - 32)).mul(mul2);\n  const h = z.add(fetch64(s2, len - 24)).mul(mul2);\n  return hashLen16(rotate64(e2.add(f), 43).add(rotate64(g, 30)).add(h), e2.add(rotate64(f.add(a), 18)).add(g), mul2);\n}\nfunction fingerPrint64(s2, len = s2.length) {\n  const seed = Long.fromNumber(81, true);\n  if (len <= 32) {\n    if (len <= 16) {\n      return hashLen0to16(s2, len);\n    } else {\n      return hashLen17to32(s2, len);\n    }\n  } else if (len <= 64) {\n    return hashLen33to64(s2, len);\n  }\n  let x = seed;\n  let y = seed.mul(k1).add(113);\n  let z = shiftMix(y.mul(k2).add(113)).mul(k2);\n  let v = [Long.UZERO, Long.UZERO];\n  let w = [Long.UZERO, Long.UZERO];\n  x = x.mul(k2).add(fetch64(s2, 0));\n  let offset = 0;\n  const end = (len - 1 >> 6) * 64;\n  const last64 = end + (len - 1 & 63) - 63;\n  do {\n    x = rotate64(x.add(y).add(v[0]).add(fetch64(s2, offset + 8)), 37).mul(k1);\n    y = rotate64(y.add(v[1]).add(fetch64(s2, offset + 48)), 42).mul(k1);\n    x = x.xor(w[1]);\n    y = y.add(v[0]).add(fetch64(s2, offset + 40));\n    z = rotate64(z.add(w[0]), 33).mul(k1);\n    v = weakHashLen32WithSeedsStr(s2, offset, v[1].mul(k1), x.add(w[0]));\n    w = weakHashLen32WithSeedsStr(s2, offset + 32, z.add(w[1]), y.add(fetch64(s2, offset + 16)));\n    [z, x] = [x, z];\n    offset += 64;\n  } while (offset !== end);\n  const mul2 = k1.add(z.and(255).shl(1));\n  offset = last64;\n  w[0] = w[0].add(len - 1 & 63);\n  v[0] = v[0].add(w[0]);\n  w[0] = w[0].add(v[0]);\n  x = rotate64(x.add(y).add(v[0]).add(fetch64(s2, offset + 8)), 37).mul(mul2);\n  y = rotate64(y.add(v[1]).add(fetch64(s2, offset + 48)), 42).mul(mul2);\n  x = x.xor(w[1].mul(9));\n  y = y.add(v[0].mul(9).add(fetch64(s2, offset + 40)));\n  z = rotate64(z.add(w[0]), 33).mul(mul2);\n  v = weakHashLen32WithSeedsStr(s2, offset, v[1].mul(mul2), x.add(w[0]));\n  w = weakHashLen32WithSeedsStr(s2, offset + 32, z.add(w[1]), y.add(fetch64(s2, offset + 16)));\n  [z, x] = [x, z];\n  return hashLen16(hashLen16(v[0], w[0], mul2).add(shiftMix(y).mul(k0)).add(z), hashLen16(v[1], w[1], mul2).add(x), mul2);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/util.js\nfunction createScalarValue(value, dtype) {\n  if (dtype === \"string\") {\n    return encodeString(value);\n  }\n  return toTypedArray([value], dtype);\n}\nfunction noConversionNeeded(a, dtype) {\n  return a instanceof Float32Array && dtype === \"float32\" || a instanceof Int32Array && dtype === \"int32\" || a instanceof Uint8Array && dtype === \"bool\";\n}\nfunction toTypedArray(a, dtype) {\n  if (dtype === \"string\") {\n    throw new Error(\"Cannot convert a string[] to a TypedArray\");\n  }\n  if (Array.isArray(a)) {\n    a = flatten(a);\n  }\n  if (env().getBool(\"DEBUG\")) {\n    checkConversionForErrors(a, dtype);\n  }\n  if (noConversionNeeded(a, dtype)) {\n    return a;\n  }\n  if (dtype == null || dtype === \"float32\" || dtype === \"complex64\") {\n    return new Float32Array(a);\n  } else if (dtype === \"int32\") {\n    return new Int32Array(a);\n  } else if (dtype === \"bool\") {\n    const bool = new Uint8Array(a.length);\n    for (let i2 = 0; i2 < bool.length; ++i2) {\n      if (Math.round(a[i2]) !== 0) {\n        bool[i2] = 1;\n      }\n    }\n    return bool;\n  } else {\n    throw new Error(`Unknown data type ${dtype}`);\n  }\n}\nfunction now() {\n  return env().platform.now();\n}\nfunction fetch3(path, requestInits) {\n  return env().platform.fetch(path, requestInits);\n}\nfunction encodeString(s2, encoding = \"utf-8\") {\n  encoding = encoding || \"utf-8\";\n  return env().platform.encode(s2, encoding);\n}\nfunction decodeString(bytes, encoding = \"utf-8\") {\n  encoding = encoding || \"utf-8\";\n  return env().platform.decode(bytes, encoding);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/profiler.js\nvar Profiler = class {\n  constructor(backendTimer, logger) {\n    this.backendTimer = backendTimer;\n    this.logger = logger;\n    if (logger == null) {\n      this.logger = new Logger();\n    }\n  }\n  profileKernel(kernelName, inputs, f) {\n    let outputs;\n    const holdResultWrapperFn = () => {\n      outputs = f();\n    };\n    let timer;\n    const start = now();\n    if (this.backendTimer.timerAvailable()) {\n      timer = this.backendTimer.time(holdResultWrapperFn);\n    } else {\n      holdResultWrapperFn();\n      for (const output of outputs) {\n        output.dataSync();\n      }\n      timer = Promise.resolve({ kernelMs: now() - start });\n    }\n    if (env().getBool(\"CHECK_COMPUTATION_FOR_ERRORS\")) {\n      for (let i2 = 0; i2 < outputs.length; i2++) {\n        const output = outputs[i2];\n        output.data().then((tensorVals) => {\n          checkComputationForErrors(tensorVals, output.dtype, kernelName);\n        });\n      }\n    }\n    const kernelProfile = {\n      kernelName,\n      outputs,\n      inputs,\n      timeMs: timer.then((timing) => timing.kernelMs),\n      extraInfo: timer.then((timing) => timing.getExtraProfileInfo != null ? timing.getExtraProfileInfo() : \"\")\n    };\n    return kernelProfile;\n  }\n  logKernelProfile(kernelProfile) {\n    const { kernelName, outputs, timeMs, inputs, extraInfo } = kernelProfile;\n    outputs.forEach((result) => {\n      Promise.all([result.data(), timeMs, extraInfo]).then((valueContainer) => {\n        this.logger.logKernelProfile(kernelName, result, valueContainer[0], valueContainer[1], inputs, valueContainer[2]);\n      });\n    });\n  }\n};\nfunction checkComputationForErrors(vals, dtype, kernelName) {\n  if (dtype !== \"float32\") {\n    return false;\n  }\n  for (let i2 = 0; i2 < vals.length; i2++) {\n    const num = vals[i2];\n    if (isNaN(num) || !isFinite(num)) {\n      console.warn(`Found ${num} in the result of '${kernelName}'`);\n      return true;\n    }\n  }\n  return false;\n}\nvar Logger = class {\n  logKernelProfile(name, result, vals, timeMs, inputs, extraInfo) {\n    const time2 = typeof timeMs === \"number\" ? rightPad(`${timeMs}ms`, 9) : timeMs[\"error\"];\n    const paddedName = rightPad(name, 25);\n    const rank = result.rank;\n    const size = result.size;\n    const shape = rightPad(result.shape.toString(), 14);\n    let inputShapesDescription = \"\";\n    for (const name2 in inputs) {\n      const input2 = inputs[name2];\n      if (input2 != null) {\n        const inputShape = input2.shape || result.shape;\n        const inputRank = inputShape.length;\n        inputShapesDescription += `${name2}: ${inputRank}D ${inputRank > 0 ? inputShape : \"\"} `;\n      }\n    }\n    console.log(`%c${paddedName}\t%c${time2}\t%c${rank}D ${shape}\t%c${size}\t%c${inputShapesDescription}\t%c${extraInfo}`, \"font-weight:bold\", \"color:red\", \"color:blue\", \"color: orange\", \"color: green\", \"color: steelblue\");\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/tape.js\nfunction getFilteredNodesXToY(tape, xs, y) {\n  const tensorsFromX = {};\n  const nodesFromX = {};\n  for (let i2 = 0; i2 < xs.length; i2++) {\n    tensorsFromX[xs[i2].id] = true;\n  }\n  for (let i2 = 0; i2 < tape.length; i2++) {\n    const node = tape[i2];\n    const nodeInputs = node.inputs;\n    for (const inputName in nodeInputs) {\n      const input2 = nodeInputs[inputName];\n      let anyInputFromX = false;\n      for (let j = 0; j < xs.length; j++) {\n        if (tensorsFromX[input2.id]) {\n          node.outputs.forEach((output) => tensorsFromX[output.id] = true);\n          anyInputFromX = true;\n          nodesFromX[node.id] = true;\n          break;\n        }\n      }\n      if (anyInputFromX) {\n        break;\n      }\n    }\n  }\n  const tensorsLeadToY = {};\n  tensorsLeadToY[y.id] = true;\n  const nodesToY = {};\n  for (let i2 = tape.length - 1; i2 >= 0; i2--) {\n    const node = tape[i2];\n    const nodeInputs = node.inputs;\n    for (let j = 0; j < node.outputs.length; j++) {\n      if (tensorsLeadToY[node.outputs[j].id]) {\n        for (const inputName in nodeInputs) {\n          tensorsLeadToY[nodeInputs[inputName].id] = true;\n          nodesToY[node.id] = true;\n        }\n        break;\n      }\n    }\n  }\n  const filteredTape = [];\n  for (let i2 = 0; i2 < tape.length; i2++) {\n    const node = tape[i2];\n    if (nodesFromX[node.id] && nodesToY[node.id]) {\n      const prunedInputs = {};\n      for (const inputName in node.inputs) {\n        const nodeInput = node.inputs[inputName];\n        if (tensorsFromX[nodeInput.id]) {\n          prunedInputs[inputName] = nodeInput;\n        }\n      }\n      const prunedNode = Object.assign({}, node);\n      prunedNode.inputs = prunedInputs;\n      prunedNode.outputs = node.outputs;\n      filteredTape.push(prunedNode);\n    }\n  }\n  return filteredTape;\n}\nfunction backpropagateGradients(tensorAccumulatedGradientMap, filteredTape, tidy2, add5) {\n  for (let i2 = filteredTape.length - 1; i2 >= 0; i2--) {\n    const node = filteredTape[i2];\n    const dys = [];\n    node.outputs.forEach((o) => {\n      const gradTensor = tensorAccumulatedGradientMap[o.id];\n      if (gradTensor != null) {\n        dys.push(gradTensor);\n      } else {\n        dys.push(null);\n      }\n    });\n    if (node.gradient == null) {\n      throw new Error(`Cannot compute gradient: gradient function not found for ${node.kernelName}.`);\n    }\n    const inputGradients = node.gradient(dys);\n    for (const inputName in node.inputs) {\n      if (!(inputName in inputGradients)) {\n        throw new Error(`Cannot backprop through input ${inputName}. Available gradients found: ${Object.keys(inputGradients)}.`);\n      }\n      const dx = tidy2(() => inputGradients[inputName]());\n      if (dx.dtype !== \"float32\") {\n        throw new Error(`Error in gradient for op ${node.kernelName}. The gradient of input ${inputName} must have 'float32' dtype, but has '${dx.dtype}'`);\n      }\n      const x = node.inputs[inputName];\n      if (!arraysEqual(dx.shape, x.shape)) {\n        throw new Error(`Error in gradient for op ${node.kernelName}. The gradient of input '${inputName}' has shape '${dx.shape}', which does not match the shape of the input '${x.shape}'`);\n      }\n      if (tensorAccumulatedGradientMap[x.id] == null) {\n        tensorAccumulatedGradientMap[x.id] = dx;\n      } else {\n        const curGradient = tensorAccumulatedGradientMap[x.id];\n        tensorAccumulatedGradientMap[x.id] = add5(curGradient, dx);\n        curGradient.dispose();\n      }\n    }\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/tensor_format.js\nvar FORMAT_LIMIT_NUM_VALS = 20;\nvar FORMAT_NUM_FIRST_LAST_VALS = 3;\nvar FORMAT_NUM_SIG_DIGITS = 7;\nfunction tensorToString(vals, shape, dtype, verbose) {\n  const strides = computeStrides(shape);\n  const padPerCol = computeMaxSizePerColumn(vals, shape, dtype, strides);\n  const rank = shape.length;\n  const valsLines = subTensorToString(vals, shape, dtype, strides, padPerCol);\n  const lines = [\"Tensor\"];\n  if (verbose) {\n    lines.push(`  dtype: ${dtype}`);\n    lines.push(`  rank: ${rank}`);\n    lines.push(`  shape: [${shape}]`);\n    lines.push(`  values:`);\n  }\n  lines.push(valsLines.map((l3) => \"    \" + l3).join(\"\\n\"));\n  return lines.join(\"\\n\");\n}\nfunction computeMaxSizePerColumn(vals, shape, dtype, strides) {\n  const n2 = sizeFromShape(shape);\n  const numCols = strides[strides.length - 1];\n  const padPerCol = new Array(numCols).fill(0);\n  const rank = shape.length;\n  const valuesOrTuples = dtype === \"complex64\" ? createComplexTuples(vals) : vals;\n  if (rank > 1) {\n    for (let row = 0; row < n2 / numCols; row++) {\n      const offset = row * numCols;\n      for (let j = 0; j < numCols; j++) {\n        padPerCol[j] = Math.max(padPerCol[j], valToString(valuesOrTuples[offset + j], 0, dtype).length);\n      }\n    }\n  }\n  return padPerCol;\n}\nfunction valToString(val, pad3, dtype) {\n  let valStr;\n  if (Array.isArray(val)) {\n    valStr = `${parseFloat(val[0].toFixed(FORMAT_NUM_SIG_DIGITS))} + ${parseFloat(val[1].toFixed(FORMAT_NUM_SIG_DIGITS))}j`;\n  } else if (isString(val)) {\n    valStr = `'${val}'`;\n  } else if (dtype === \"bool\") {\n    valStr = boolNumToString(val);\n  } else {\n    valStr = parseFloat(val.toFixed(FORMAT_NUM_SIG_DIGITS)).toString();\n  }\n  return rightPad(valStr, pad3);\n}\nfunction boolNumToString(v) {\n  return v === 0 ? \"false\" : \"true\";\n}\nfunction subTensorToString(vals, shape, dtype, strides, padPerCol, isLast = true) {\n  const storagePerElement = dtype === \"complex64\" ? 2 : 1;\n  const size = shape[0];\n  const rank = shape.length;\n  if (rank === 0) {\n    if (dtype === \"complex64\") {\n      const complexTuple = createComplexTuples(vals);\n      return [valToString(complexTuple[0], 0, dtype)];\n    }\n    if (dtype === \"bool\") {\n      return [boolNumToString(vals[0])];\n    }\n    return [vals[0].toString()];\n  }\n  if (rank === 1) {\n    if (size > FORMAT_LIMIT_NUM_VALS) {\n      const firstValsSize = FORMAT_NUM_FIRST_LAST_VALS * storagePerElement;\n      let firstVals = Array.from(vals.slice(0, firstValsSize));\n      let lastVals = Array.from(vals.slice((size - FORMAT_NUM_FIRST_LAST_VALS) * storagePerElement, size * storagePerElement));\n      if (dtype === \"complex64\") {\n        firstVals = createComplexTuples(firstVals);\n        lastVals = createComplexTuples(lastVals);\n      }\n      return [\n        \"[\" + firstVals.map((x, i2) => valToString(x, padPerCol[i2], dtype)).join(\", \") + \", ..., \" + lastVals.map((x, i2) => valToString(x, padPerCol[size - FORMAT_NUM_FIRST_LAST_VALS + i2], dtype)).join(\", \") + \"]\"\n      ];\n    }\n    const displayVals = dtype === \"complex64\" ? createComplexTuples(vals) : Array.from(vals);\n    return [\n      \"[\" + displayVals.map((x, i2) => valToString(x, padPerCol[i2], dtype)).join(\", \") + \"]\"\n    ];\n  }\n  const subshape = shape.slice(1);\n  const substrides = strides.slice(1);\n  const stride = strides[0] * storagePerElement;\n  const lines = [];\n  if (size > FORMAT_LIMIT_NUM_VALS) {\n    for (let i2 = 0; i2 < FORMAT_NUM_FIRST_LAST_VALS; i2++) {\n      const start = i2 * stride;\n      const end = start + stride;\n      lines.push(...subTensorToString(vals.slice(start, end), subshape, dtype, substrides, padPerCol, false));\n    }\n    lines.push(\"...\");\n    for (let i2 = size - FORMAT_NUM_FIRST_LAST_VALS; i2 < size; i2++) {\n      const start = i2 * stride;\n      const end = start + stride;\n      lines.push(...subTensorToString(vals.slice(start, end), subshape, dtype, substrides, padPerCol, i2 === size - 1));\n    }\n  } else {\n    for (let i2 = 0; i2 < size; i2++) {\n      const start = i2 * stride;\n      const end = start + stride;\n      lines.push(...subTensorToString(vals.slice(start, end), subshape, dtype, substrides, padPerCol, i2 === size - 1));\n    }\n  }\n  const sep = rank === 2 ? \",\" : \"\";\n  lines[0] = \"[\" + lines[0] + sep;\n  for (let i2 = 1; i2 < lines.length - 1; i2++) {\n    lines[i2] = \" \" + lines[i2] + sep;\n  }\n  let newLineSep = \",\\n\";\n  for (let i2 = 2; i2 < rank; i2++) {\n    newLineSep += \"\\n\";\n  }\n  lines[lines.length - 1] = \" \" + lines[lines.length - 1] + \"]\" + (isLast ? \"\" : newLineSep);\n  return lines;\n}\nfunction createComplexTuples(vals) {\n  const complexTuples = [];\n  for (let i2 = 0; i2 < vals.length; i2 += 2) {\n    complexTuples.push([vals[i2], vals[i2 + 1]]);\n  }\n  return complexTuples;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/tensor.js\nvar TensorBuffer = class {\n  constructor(shape, dtype, values) {\n    this.dtype = dtype;\n    this.shape = shape.slice();\n    this.size = sizeFromShape(shape);\n    if (values != null) {\n      const n2 = values.length;\n      assert(n2 === this.size, () => `Length of values '${n2}' does not match the size inferred by the shape '${this.size}'.`);\n    }\n    if (dtype === \"complex64\") {\n      throw new Error(`complex64 dtype TensorBuffers are not supported. Please create a TensorBuffer for the real and imaginary parts separately and call tf.complex(real, imag).`);\n    }\n    this.values = values || getArrayFromDType(dtype, this.size);\n    this.strides = computeStrides(shape);\n  }\n  set(value, ...locs) {\n    if (locs.length === 0) {\n      locs = [0];\n    }\n    assert(locs.length === this.rank, () => `The number of provided coordinates (${locs.length}) must match the rank (${this.rank})`);\n    const index = this.locToIndex(locs);\n    this.values[index] = value;\n  }\n  get(...locs) {\n    if (locs.length === 0) {\n      locs = [0];\n    }\n    let i2 = 0;\n    for (const loc of locs) {\n      if (loc < 0 || loc >= this.shape[i2]) {\n        const msg = `Requested out of range element at ${locs}.   Buffer shape=${this.shape}`;\n        throw new Error(msg);\n      }\n      i2++;\n    }\n    let index = locs[locs.length - 1];\n    for (let i3 = 0; i3 < locs.length - 1; ++i3) {\n      index += this.strides[i3] * locs[i3];\n    }\n    return this.values[index];\n  }\n  locToIndex(locs) {\n    if (this.rank === 0) {\n      return 0;\n    } else if (this.rank === 1) {\n      return locs[0];\n    }\n    let index = locs[locs.length - 1];\n    for (let i2 = 0; i2 < locs.length - 1; ++i2) {\n      index += this.strides[i2] * locs[i2];\n    }\n    return index;\n  }\n  indexToLoc(index) {\n    if (this.rank === 0) {\n      return [];\n    } else if (this.rank === 1) {\n      return [index];\n    }\n    const locs = new Array(this.shape.length);\n    for (let i2 = 0; i2 < locs.length - 1; ++i2) {\n      locs[i2] = Math.floor(index / this.strides[i2]);\n      index -= locs[i2] * this.strides[i2];\n    }\n    locs[locs.length - 1] = index;\n    return locs;\n  }\n  get rank() {\n    return this.shape.length;\n  }\n  toTensor() {\n    return trackerFn().makeTensor(this.values, this.shape, this.dtype);\n  }\n};\nvar trackerFn = null;\nvar opHandler = null;\nvar deprecationWarningFn = null;\nfunction setTensorTracker(fn) {\n  trackerFn = fn;\n}\nfunction setOpHandler(handler) {\n  opHandler = handler;\n}\nfunction setDeprecationWarningFn(fn) {\n  deprecationWarningFn = fn;\n}\nvar Tensor = class {\n  constructor(shape, dtype, dataId, id) {\n    this.kept = false;\n    this.isDisposedInternal = false;\n    this.shape = shape.slice();\n    this.dtype = dtype || \"float32\";\n    this.size = sizeFromShape(shape);\n    this.strides = computeStrides(shape);\n    this.dataId = dataId;\n    this.id = id;\n    this.rankType = this.rank < 5 ? this.rank.toString() : \"higher\";\n  }\n  get rank() {\n    return this.shape.length;\n  }\n  async buffer() {\n    const vals = await this.data();\n    return opHandler.buffer(this.shape, this.dtype, vals);\n  }\n  bufferSync() {\n    return opHandler.buffer(this.shape, this.dtype, this.dataSync());\n  }\n  async array() {\n    const vals = await this.data();\n    return toNestedArray(this.shape, vals, this.dtype === \"complex64\");\n  }\n  arraySync() {\n    return toNestedArray(this.shape, this.dataSync(), this.dtype === \"complex64\");\n  }\n  async data() {\n    this.throwIfDisposed();\n    const data = trackerFn().read(this.dataId);\n    if (this.dtype === \"string\") {\n      const bytes = await data;\n      try {\n        return bytes.map((b) => decodeString(b));\n      } catch (_a) {\n        throw new Error(\"Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().\");\n      }\n    }\n    return data;\n  }\n  dataToGPU(options) {\n    this.throwIfDisposed();\n    return trackerFn().readToGPU(this.dataId, options);\n  }\n  dataSync() {\n    this.throwIfDisposed();\n    const data = trackerFn().readSync(this.dataId);\n    if (this.dtype === \"string\") {\n      try {\n        return data.map((b) => decodeString(b));\n      } catch (_a) {\n        throw new Error(\"Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().\");\n      }\n    }\n    return data;\n  }\n  async bytes() {\n    this.throwIfDisposed();\n    const data = await trackerFn().read(this.dataId);\n    if (this.dtype === \"string\") {\n      return data;\n    } else {\n      return new Uint8Array(data.buffer);\n    }\n  }\n  dispose() {\n    if (this.isDisposed) {\n      return;\n    }\n    trackerFn().disposeTensor(this);\n    this.isDisposedInternal = true;\n  }\n  get isDisposed() {\n    return this.isDisposedInternal;\n  }\n  throwIfDisposed() {\n    if (this.isDisposed) {\n      throw new Error(`Tensor is disposed.`);\n    }\n  }\n  print(verbose = false) {\n    return opHandler.print(this, verbose);\n  }\n  clone() {\n    this.throwIfDisposed();\n    return opHandler.clone(this);\n  }\n  toString(verbose = false) {\n    const vals = this.dataSync();\n    return tensorToString(vals, this.shape, this.dtype, verbose);\n  }\n  cast(dtype) {\n    this.throwIfDisposed();\n    return opHandler.cast(this, dtype);\n  }\n  variable(trainable = true, name, dtype) {\n    this.throwIfDisposed();\n    return trackerFn().makeVariable(this, trainable, name, dtype);\n  }\n};\nObject.defineProperty(Tensor, Symbol.hasInstance, {\n  value: (instance) => {\n    return !!instance && instance.data != null && instance.dataSync != null && instance.throwIfDisposed != null;\n  }\n});\nfunction getGlobalTensorClass() {\n  return getGlobal(\"Tensor\", () => {\n    return Tensor;\n  });\n}\ngetGlobalTensorClass();\nvar Variable = class extends Tensor {\n  constructor(initialValue, trainable, name, tensorId) {\n    super(initialValue.shape, initialValue.dtype, initialValue.dataId, tensorId);\n    this.trainable = trainable;\n    this.name = name;\n  }\n  assign(newValue) {\n    if (newValue.dtype !== this.dtype) {\n      throw new Error(`dtype of the new value (${newValue.dtype}) and previous value (${this.dtype}) must match`);\n    }\n    if (!arraysEqual(newValue.shape, this.shape)) {\n      throw new Error(`shape of the new value (${newValue.shape}) and previous value (${this.shape}) must match`);\n    }\n    trackerFn().disposeTensor(this);\n    this.dataId = newValue.dataId;\n    trackerFn().incRef(this, null);\n  }\n  dispose() {\n    trackerFn().disposeVariable(this);\n    this.isDisposedInternal = true;\n  }\n};\nObject.defineProperty(Variable, Symbol.hasInstance, {\n  value: (instance) => {\n    return instance instanceof Tensor && instance.assign != null && instance.assign instanceof Function;\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/tensor_util.js\nvar tensor_util_exports = {};\n__export(tensor_util_exports, {\n  assertTypesMatch: () => assertTypesMatch,\n  getTensorsInContainer: () => getTensorsInContainer,\n  isTensorInList: () => isTensorInList,\n  makeTypesMatch: () => makeTypesMatch\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/types.js\nvar Rank;\n(function(Rank2) {\n  Rank2[\"R0\"] = \"R0\";\n  Rank2[\"R1\"] = \"R1\";\n  Rank2[\"R2\"] = \"R2\";\n  Rank2[\"R3\"] = \"R3\";\n  Rank2[\"R4\"] = \"R4\";\n  Rank2[\"R5\"] = \"R5\";\n  Rank2[\"R6\"] = \"R6\";\n})(Rank || (Rank = {}));\nvar UpcastInt32AndMap;\n(function(UpcastInt32AndMap2) {\n  UpcastInt32AndMap2[\"float32\"] = \"float32\";\n  UpcastInt32AndMap2[\"int32\"] = \"int32\";\n  UpcastInt32AndMap2[\"bool\"] = \"int32\";\n  UpcastInt32AndMap2[\"complex64\"] = \"complex64\";\n})(UpcastInt32AndMap || (UpcastInt32AndMap = {}));\nvar UpcastBoolAndMap;\n(function(UpcastBoolAndMap2) {\n  UpcastBoolAndMap2[\"float32\"] = \"float32\";\n  UpcastBoolAndMap2[\"int32\"] = \"int32\";\n  UpcastBoolAndMap2[\"bool\"] = \"bool\";\n  UpcastBoolAndMap2[\"complex64\"] = \"complex64\";\n})(UpcastBoolAndMap || (UpcastBoolAndMap = {}));\nvar UpcastFloat32AndMap;\n(function(UpcastFloat32AndMap2) {\n  UpcastFloat32AndMap2[\"float32\"] = \"float32\";\n  UpcastFloat32AndMap2[\"int32\"] = \"float32\";\n  UpcastFloat32AndMap2[\"bool\"] = \"float32\";\n  UpcastFloat32AndMap2[\"complex64\"] = \"complex64\";\n})(UpcastFloat32AndMap || (UpcastFloat32AndMap = {}));\nvar UpcastComplex64AndMap;\n(function(UpcastComplex64AndMap2) {\n  UpcastComplex64AndMap2[\"float32\"] = \"complex64\";\n  UpcastComplex64AndMap2[\"int32\"] = \"complex64\";\n  UpcastComplex64AndMap2[\"bool\"] = \"complex64\";\n  UpcastComplex64AndMap2[\"complex64\"] = \"complex64\";\n})(UpcastComplex64AndMap || (UpcastComplex64AndMap = {}));\nvar upcastTypeMap = {\n  \"float32\": UpcastFloat32AndMap,\n  \"int32\": UpcastInt32AndMap,\n  \"bool\": UpcastBoolAndMap,\n  \"complex64\": UpcastComplex64AndMap\n};\nfunction upcastType(typeA, typeB) {\n  if (typeA === \"string\" || typeB === \"string\") {\n    if (typeA === \"string\" && typeB === \"string\") {\n      return \"string\";\n    }\n    throw new Error(`Can not upcast ${typeA} with ${typeB}`);\n  }\n  return upcastTypeMap[typeA][typeB];\n}\nfunction sumOutType(type) {\n  return upcastType(type, \"int32\");\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/tensor_util.js\nfunction makeTypesMatch(a, b) {\n  if (a.dtype === b.dtype) {\n    return [a, b];\n  }\n  const dtype = upcastType(a.dtype, b.dtype);\n  return [a.cast(dtype), b.cast(dtype)];\n}\nfunction assertTypesMatch(a, b) {\n  assert(a.dtype === b.dtype, () => `The dtypes of the first(${a.dtype}) and second(${b.dtype}) input must match`);\n}\nfunction isTensorInList(tensor2, tensorList) {\n  return tensorList.some((x) => x.id === tensor2.id);\n}\nfunction getTensorsInContainer(result) {\n  const list = [];\n  const seen = /* @__PURE__ */ new Set();\n  walkTensorContainer(result, list, seen);\n  return list;\n}\nfunction walkTensorContainer(container, list, seen) {\n  if (container == null) {\n    return;\n  }\n  if (container instanceof Tensor) {\n    list.push(container);\n    return;\n  }\n  if (!isIterable(container)) {\n    return;\n  }\n  const iterable = container;\n  for (const k in iterable) {\n    const val = iterable[k];\n    if (!seen.has(val)) {\n      seen.add(val);\n      walkTensorContainer(val, list, seen);\n    }\n  }\n}\nfunction isIterable(obj) {\n  return Array.isArray(obj) || typeof obj === \"object\";\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/engine.js\nfunction isRegisteredKernelInvocation(kernelInvocation) {\n  return kernelInvocation.kernelName != null;\n}\nvar EngineState = class {\n  constructor() {\n    this.registeredVariables = {};\n    this.nextTapeNodeId = 0;\n    this.numBytes = 0;\n    this.numTensors = 0;\n    this.numStringTensors = 0;\n    this.numDataBuffers = 0;\n    this.gradientDepth = 0;\n    this.kernelDepth = 0;\n    this.scopeStack = [];\n    this.numDataMovesStack = [];\n    this.nextScopeId = 0;\n    this.tensorInfo = /* @__PURE__ */ new WeakMap();\n    this.profiling = false;\n    this.activeProfile = {\n      newBytes: 0,\n      newTensors: 0,\n      peakBytes: 0,\n      kernels: [],\n      result: null,\n      get kernelNames() {\n        return Array.from(new Set(this.kernels.map((k) => k.name)));\n      }\n    };\n  }\n  dispose() {\n    for (const variableName in this.registeredVariables) {\n      this.registeredVariables[variableName].dispose();\n    }\n  }\n};\nvar Engine = class {\n  constructor(ENV8) {\n    this.ENV = ENV8;\n    this.registry = {};\n    this.registryFactory = {};\n    this.pendingBackendInitId = 0;\n    this.state = new EngineState();\n  }\n  async ready() {\n    if (this.pendingBackendInit != null) {\n      return this.pendingBackendInit.then(() => {\n      });\n    }\n    if (this.backendInstance != null) {\n      return;\n    }\n    const sortedBackends = this.getSortedBackends();\n    for (let i2 = 0; i2 < sortedBackends.length; i2++) {\n      const backendName = sortedBackends[i2];\n      const success = await this.initializeBackend(backendName).success;\n      if (success) {\n        await this.setBackend(backendName);\n        return;\n      }\n    }\n    throw new Error(`Could not initialize any backends, all backend initializations failed.`);\n  }\n  get backend() {\n    if (this.pendingBackendInit != null) {\n      throw new Error(`Backend '${this.backendName}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);\n    }\n    if (this.backendInstance == null) {\n      const { name, asyncInit } = this.initializeBackendsAndReturnBest();\n      if (asyncInit) {\n        throw new Error(`The highest priority backend '${name}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);\n      }\n      this.setBackend(name);\n    }\n    return this.backendInstance;\n  }\n  backendNames() {\n    return Object.keys(this.registryFactory);\n  }\n  findBackend(backendName) {\n    if (!(backendName in this.registry)) {\n      if (backendName in this.registryFactory) {\n        const { asyncInit } = this.initializeBackend(backendName);\n        if (asyncInit) {\n          return null;\n        }\n      } else {\n        return null;\n      }\n    }\n    return this.registry[backendName];\n  }\n  findBackendFactory(backendName) {\n    if (!(backendName in this.registryFactory)) {\n      return null;\n    }\n    return this.registryFactory[backendName].factory;\n  }\n  registerBackend(backendName, factory, priority = 1) {\n    if (backendName in this.registryFactory) {\n      warn(`${backendName} backend was already registered. Reusing existing backend factory.`);\n      return false;\n    }\n    this.registryFactory[backendName] = { factory, priority };\n    return true;\n  }\n  async setBackend(backendName) {\n    if (this.registryFactory[backendName] == null) {\n      throw new Error(`Backend name '${backendName}' not found in registry`);\n    }\n    this.backendName = backendName;\n    if (this.registry[backendName] == null) {\n      this.backendInstance = null;\n      const { success, asyncInit } = this.initializeBackend(backendName);\n      const result = asyncInit ? await success : success;\n      if (!result) {\n        return false;\n      }\n    }\n    this.backendInstance = this.registry[backendName];\n    this.setupRegisteredKernels();\n    this.profiler = new Profiler(this.backendInstance);\n    return true;\n  }\n  setupRegisteredKernels() {\n    const kernels = getKernelsForBackend(this.backendName);\n    kernels.forEach((kernel) => {\n      if (kernel.setupFunc != null) {\n        kernel.setupFunc(this.backendInstance);\n      }\n    });\n  }\n  disposeRegisteredKernels(backendName) {\n    const kernels = getKernelsForBackend(backendName);\n    kernels.forEach((kernel) => {\n      if (kernel.disposeFunc != null) {\n        kernel.disposeFunc(this.registry[backendName]);\n      }\n    });\n  }\n  initializeBackend(backendName) {\n    const registryFactoryEntry = this.registryFactory[backendName];\n    if (registryFactoryEntry == null) {\n      throw new Error(`Cannot initialize backend ${backendName}, no registration found.`);\n    }\n    try {\n      const backend2 = registryFactoryEntry.factory();\n      if (backend2 && !(backend2 instanceof KernelBackend) && typeof backend2.then === \"function\") {\n        const promiseId = ++this.pendingBackendInitId;\n        const success = backend2.then((backendInstance) => {\n          if (promiseId < this.pendingBackendInitId) {\n            return false;\n          }\n          this.registry[backendName] = backendInstance;\n          this.pendingBackendInit = null;\n          return true;\n        }).catch((err) => {\n          if (promiseId < this.pendingBackendInitId) {\n            return false;\n          }\n          this.pendingBackendInit = null;\n          warn(`Initialization of backend ${backendName} failed`);\n          warn(err.stack || err.message);\n          return false;\n        });\n        this.pendingBackendInit = success;\n        return { success, asyncInit: true };\n      } else {\n        this.registry[backendName] = backend2;\n        return { success: true, asyncInit: false };\n      }\n    } catch (err) {\n      warn(`Initialization of backend ${backendName} failed`);\n      warn(err.stack || err.message);\n      return { success: false, asyncInit: false };\n    }\n  }\n  removeBackend(backendName) {\n    if (!(backendName in this.registryFactory)) {\n      throw new Error(`${backendName} backend not found in registry`);\n    }\n    if (this.backendName === backendName && this.pendingBackendInit != null) {\n      this.pendingBackendInitId++;\n    }\n    if (backendName in this.registry) {\n      this.disposeRegisteredKernels(backendName);\n      this.registry[backendName].dispose();\n      delete this.registry[backendName];\n    }\n    delete this.registryFactory[backendName];\n    if (this.backendName === backendName) {\n      this.pendingBackendInit = null;\n      this.backendName = null;\n      this.backendInstance = null;\n    }\n  }\n  getSortedBackends() {\n    if (Object.keys(this.registryFactory).length === 0) {\n      throw new Error(\"No backend found in registry.\");\n    }\n    return Object.keys(this.registryFactory).sort((a, b) => {\n      return this.registryFactory[b].priority - this.registryFactory[a].priority;\n    });\n  }\n  initializeBackendsAndReturnBest() {\n    const sortedBackends = this.getSortedBackends();\n    for (let i2 = 0; i2 < sortedBackends.length; i2++) {\n      const backendName = sortedBackends[i2];\n      const { success, asyncInit } = this.initializeBackend(backendName);\n      if (asyncInit || success) {\n        return { name: backendName, asyncInit };\n      }\n    }\n    throw new Error(`Could not initialize any backends, all backend initializations failed.`);\n  }\n  moveData(backend2, dataId) {\n    const info = this.state.tensorInfo.get(dataId);\n    const srcBackend = info.backend;\n    const values = this.readSync(dataId);\n    const refCount = srcBackend.refCount(dataId);\n    srcBackend.disposeData(dataId, true);\n    info.backend = backend2;\n    backend2.move(dataId, values, info.shape, info.dtype, refCount);\n    if (this.shouldCheckForMemLeaks()) {\n      this.state.numDataMovesStack[this.state.numDataMovesStack.length - 1]++;\n    }\n  }\n  tidy(nameOrFn, fn) {\n    let name = null;\n    if (fn == null) {\n      if (typeof nameOrFn !== \"function\") {\n        throw new Error(\"Please provide a function to tidy()\");\n      }\n      fn = nameOrFn;\n    } else {\n      if (typeof nameOrFn !== \"string\" && !(nameOrFn instanceof String)) {\n        throw new Error(\"When calling with two arguments, the first argument to tidy() must be a string\");\n      }\n      if (typeof fn !== \"function\") {\n        throw new Error(\"When calling with two arguments, the 2nd argument to tidy() must be a function\");\n      }\n      name = nameOrFn;\n    }\n    let result;\n    return this.scopedRun(() => this.startScope(name), () => this.endScope(result), () => {\n      result = fn();\n      if (result instanceof Promise) {\n        console.error(\"Cannot return a Promise inside of tidy.\");\n      }\n      return result;\n    });\n  }\n  scopedRun(start, end, f) {\n    start();\n    try {\n      const res = f();\n      end();\n      return res;\n    } catch (ex) {\n      end();\n      throw ex;\n    }\n  }\n  nextTensorId() {\n    return Engine.nextTensorId++;\n  }\n  nextVariableId() {\n    return Engine.nextVariableId++;\n  }\n  clone(x) {\n    const y = ENGINE.runKernel(Identity, { x });\n    const inputs = { x };\n    const grad2 = (dy) => ({\n      x: () => {\n        const dtype = \"float32\";\n        const gradInputs = { x: dy };\n        const attrs = { dtype };\n        return ENGINE.runKernel(\n          Cast,\n          gradInputs,\n          attrs\n        );\n      }\n    });\n    const saved = [];\n    this.addTapeNode(this.state.activeScope.name, inputs, [y], grad2, saved, {});\n    return y;\n  }\n  runKernel(kernelName, inputs, attrs) {\n    if (this.backendName == null) {\n      this.backend;\n    }\n    const hasKernel = getKernel(kernelName, this.backendName) != null;\n    if (!hasKernel) {\n      throw new Error(`Kernel '${kernelName}' not registered for backend '${this.backendName}'`);\n    }\n    return this.runKernelFunc({ kernelName, inputs, attrs });\n  }\n  shouldCheckForMemLeaks() {\n    return this.ENV.getBool(\"IS_TEST\");\n  }\n  checkKernelForMemLeak(kernelName, numDataIdsBefore, outInfos) {\n    const numDataIdsAfter = this.backend.numDataIds();\n    let numOutputDataIds = 0;\n    outInfos.forEach((info) => {\n      numOutputDataIds += info.dtype === \"complex64\" ? 3 : 1;\n    });\n    const numMoves = this.state.numDataMovesStack[this.state.numDataMovesStack.length - 1];\n    const dataIdsLeaked = numDataIdsAfter - numDataIdsBefore - numOutputDataIds - numMoves;\n    if (dataIdsLeaked > 0) {\n      throw new Error(`Backend '${this.backendName}' has an internal memory leak (${dataIdsLeaked} data ids) after running '${kernelName}'`);\n    }\n  }\n  runKernelFunc(kernelParams) {\n    let outputs;\n    let saved = [];\n    const isTapeOn = this.isTapeOn();\n    const startingBytecount = this.state.numBytes;\n    const startingNumTensors = this.state.numTensors;\n    if (this.shouldCheckForMemLeaks()) {\n      this.state.numDataMovesStack.push(0);\n    }\n    let kernelFunc3;\n    if (this.backendName == null) {\n      this.backend;\n    }\n    let out;\n    const kernelOrScopeName = isRegisteredKernelInvocation(kernelParams) ? kernelParams.kernelName : this.state.activeScope != null ? this.state.activeScope.name : \"\";\n    if (isRegisteredKernelInvocation(kernelParams)) {\n      const { kernelName, inputs: inputs2, attrs: attrs2 } = kernelParams;\n      if (this.backendName == null) {\n        this.backend;\n      }\n      const kernel = getKernel(kernelName, this.backendName);\n      assert(kernel != null, () => `Cannot find registered kernel '${kernelName}' for backend '${this.backendName}'`);\n      kernelFunc3 = () => {\n        const numDataIdsBefore = this.backend.numDataIds();\n        out = kernel.kernelFunc({ inputs: inputs2, attrs: attrs2, backend: this.backend });\n        const outInfos = Array.isArray(out) ? out : [out];\n        if (this.shouldCheckForMemLeaks()) {\n          this.checkKernelForMemLeak(kernelName, numDataIdsBefore, outInfos);\n        }\n        const outTensors = outInfos.map((outInfo) => {\n          if (outInfo.rank != null) {\n            return outInfo;\n          }\n          return this.makeTensorFromTensorInfo(outInfo);\n        });\n        if (isTapeOn) {\n          const tensorsToSave = this.getTensorsForGradient(kernelName, inputs2, outTensors);\n          saved = this.saveTensorsForBackwardMode(tensorsToSave);\n        }\n        return outTensors;\n      };\n    } else {\n      const { forwardFunc } = kernelParams;\n      const saveFunc = (tensors) => {\n        if (!isTapeOn) {\n          return;\n        }\n        saved = tensors.map((tensor2) => this.keep(this.clone(tensor2)));\n      };\n      kernelFunc3 = () => {\n        const numDataIdsBefore = this.backend.numDataIds();\n        out = this.tidy(() => forwardFunc(this.backend, saveFunc));\n        const outs = Array.isArray(out) ? out : [out];\n        if (this.shouldCheckForMemLeaks()) {\n          this.checkKernelForMemLeak(kernelOrScopeName, numDataIdsBefore, outs);\n        }\n        return outs;\n      };\n    }\n    const { inputs, attrs } = kernelParams;\n    const backwardsFunc = isRegisteredKernelInvocation(kernelParams) ? null : kernelParams.backwardsFunc;\n    let kernelProfile;\n    this.scopedRun(\n      () => this.state.kernelDepth++,\n      () => this.state.kernelDepth--,\n      () => {\n        if (!this.ENV.getBool(\"DEBUG\") && !this.state.profiling) {\n          outputs = kernelFunc3();\n        } else {\n          kernelProfile = this.profiler.profileKernel(kernelOrScopeName, inputs, () => kernelFunc3());\n          if (this.ENV.getBool(\"DEBUG\")) {\n            this.profiler.logKernelProfile(kernelProfile);\n          }\n          outputs = kernelProfile.outputs;\n        }\n      }\n    );\n    if (isTapeOn) {\n      this.addTapeNode(kernelOrScopeName, inputs, outputs, backwardsFunc, saved, attrs);\n    }\n    if (this.state.profiling) {\n      this.state.activeProfile.kernels.push({\n        name: kernelOrScopeName,\n        bytesAdded: this.state.numBytes - startingBytecount,\n        totalBytesSnapshot: this.state.numBytes,\n        tensorsAdded: this.state.numTensors - startingNumTensors,\n        totalTensorsSnapshot: this.state.numTensors,\n        inputShapes: Object.keys(inputs).map((key) => inputs[key] != null ? inputs[key].shape : null),\n        outputShapes: outputs.map((item) => item.shape),\n        kernelTimeMs: kernelProfile.timeMs,\n        extraInfo: kernelProfile.extraInfo\n      });\n    }\n    return Array.isArray(out) ? outputs : outputs[0];\n  }\n  saveTensorsForBackwardMode(tensors) {\n    const saved = tensors.map((tensor2) => this.keep(this.clone(tensor2)));\n    return saved;\n  }\n  getTensorsForGradient(kernelName, inputs, outputs) {\n    const gradConfig = getGradient(kernelName);\n    if (gradConfig != null) {\n      const inputsToSave = gradConfig.inputsToSave || [];\n      const outputsToSave = gradConfig.outputsToSave || [];\n      let inputTensorsToSave;\n      if (gradConfig.saveAllInputs) {\n        assert(Array.isArray(inputs), () => \"saveAllInputs is true, expected inputs to be an array.\");\n        inputTensorsToSave = Object.keys(inputs).map((key) => inputs[key]);\n      } else {\n        inputTensorsToSave = inputsToSave.map((inputName) => inputs[inputName]);\n      }\n      const outputTensorsToSave = outputs.filter((_, i2) => outputsToSave[i2]);\n      return inputTensorsToSave.concat(outputTensorsToSave);\n    }\n    return [];\n  }\n  makeTensor(values, shape, dtype, backend2) {\n    if (values == null) {\n      throw new Error(\"Values passed to engine.makeTensor() are null\");\n    }\n    dtype = dtype || \"float32\";\n    backend2 = backend2 || this.backend;\n    let backendVals = values;\n    if (dtype === \"string\" && isString(values[0])) {\n      backendVals = values.map((d) => encodeString(d));\n    }\n    const dataId = backend2.write(backendVals, shape, dtype);\n    const t2 = new Tensor(shape, dtype, dataId, this.nextTensorId());\n    this.trackTensor(t2, backend2);\n    if (dtype === \"string\") {\n      const info = this.state.tensorInfo.get(dataId);\n      const newBytes = bytesFromStringArray(backendVals);\n      this.state.numBytes += newBytes - info.bytes;\n      info.bytes = newBytes;\n    }\n    return t2;\n  }\n  makeTensorFromDataId(dataId, shape, dtype, backend2) {\n    dtype = dtype || \"float32\";\n    const tensorInfo = { dataId, shape, dtype };\n    return this.makeTensorFromTensorInfo(tensorInfo, backend2);\n  }\n  makeTensorFromTensorInfo(tensorInfo, backend2) {\n    const { dataId, shape, dtype } = tensorInfo;\n    const t2 = new Tensor(shape, dtype, dataId, this.nextTensorId());\n    this.trackTensor(t2, backend2);\n    return t2;\n  }\n  makeVariable(initialValue, trainable = true, name, dtype) {\n    name = name || this.nextVariableId().toString();\n    if (dtype != null && dtype !== initialValue.dtype) {\n      initialValue = initialValue.cast(dtype);\n    }\n    const v = new Variable(initialValue, trainable, name, this.nextTensorId());\n    if (this.state.registeredVariables[v.name] != null) {\n      throw new Error(`Variable with name ${v.name} was already registered`);\n    }\n    this.state.registeredVariables[v.name] = v;\n    this.incRef(v, this.backend);\n    return v;\n  }\n  trackTensor(a, backend2) {\n    this.state.numTensors++;\n    if (a.dtype === \"string\") {\n      this.state.numStringTensors++;\n    }\n    let bytes = 0;\n    if (a.dtype !== \"complex64\" && a.dtype !== \"string\") {\n      bytes = a.size * bytesPerElement(a.dtype);\n    }\n    this.state.numBytes += bytes;\n    if (!this.state.tensorInfo.has(a.dataId)) {\n      this.state.numDataBuffers++;\n      this.state.tensorInfo.set(a.dataId, {\n        backend: backend2 || this.backend,\n        dtype: a.dtype,\n        shape: a.shape,\n        bytes\n      });\n    }\n    if (!(a instanceof Variable)) {\n      this.track(a);\n    }\n  }\n  incRef(a, backend2) {\n    this.trackTensor(a, backend2);\n    this.backend.incRef(a.dataId);\n  }\n  removeDataId(dataId, backend2) {\n    if (this.state.tensorInfo.has(dataId) && this.state.tensorInfo.get(dataId).backend === backend2) {\n      this.state.tensorInfo.delete(dataId);\n      this.state.numDataBuffers--;\n    }\n  }\n  disposeTensor(a) {\n    if (!this.state.tensorInfo.has(a.dataId)) {\n      return;\n    }\n    const info = this.state.tensorInfo.get(a.dataId);\n    this.state.numTensors--;\n    if (a.dtype === \"string\") {\n      this.state.numStringTensors--;\n      this.state.numBytes -= info.bytes;\n    }\n    if (a.dtype !== \"complex64\" && a.dtype !== \"string\") {\n      const bytes = a.size * bytesPerElement(a.dtype);\n      this.state.numBytes -= bytes;\n    }\n    if (info.backend.disposeData(a.dataId)) {\n      this.removeDataId(a.dataId, info.backend);\n    }\n  }\n  disposeVariables() {\n    for (const varName in this.state.registeredVariables) {\n      const v = this.state.registeredVariables[varName];\n      this.disposeVariable(v);\n    }\n  }\n  disposeVariable(v) {\n    this.disposeTensor(v);\n    if (this.state.registeredVariables[v.name] != null) {\n      delete this.state.registeredVariables[v.name];\n    }\n  }\n  memory() {\n    const info = this.backend.memory();\n    info.numTensors = this.state.numTensors;\n    info.numDataBuffers = this.state.numDataBuffers;\n    info.numBytes = this.state.numBytes;\n    if (this.state.numStringTensors > 0) {\n      info.unreliable = true;\n      if (info.reasons == null) {\n        info.reasons = [];\n      }\n      info.reasons.push(\"Memory usage by string tensors is approximate (2 bytes per character)\");\n    }\n    return info;\n  }\n  async profile(query) {\n    this.state.profiling = true;\n    const startBytes = this.state.numBytes;\n    const startNumTensors = this.state.numTensors;\n    this.state.activeProfile.kernels = [];\n    this.state.activeProfile.result = await query();\n    this.state.profiling = false;\n    this.state.activeProfile.peakBytes = Math.max(...this.state.activeProfile.kernels.map((d) => d.totalBytesSnapshot));\n    this.state.activeProfile.newBytes = this.state.numBytes - startBytes;\n    this.state.activeProfile.newTensors = this.state.numTensors - startNumTensors;\n    for (const kernel of this.state.activeProfile.kernels) {\n      kernel.kernelTimeMs = await kernel.kernelTimeMs;\n      kernel.extraInfo = await kernel.extraInfo;\n    }\n    return this.state.activeProfile;\n  }\n  isTapeOn() {\n    return this.state.gradientDepth > 0 && this.state.kernelDepth === 0;\n  }\n  addTapeNode(kernelName, inputs, outputs, gradientsFunc, saved, attrs) {\n    const tapeNode = { id: this.state.nextTapeNodeId++, kernelName, inputs, outputs, saved };\n    const gradConfig = getGradient(kernelName);\n    if (gradConfig != null) {\n      gradientsFunc = gradConfig.gradFunc;\n    }\n    if (gradientsFunc != null) {\n      tapeNode.gradient = (dys) => {\n        dys = dys.map((dy, i2) => {\n          if (dy == null) {\n            const output = outputs[i2];\n            const vals = makeZerosTypedArray(output.size, output.dtype);\n            return this.makeTensor(vals, output.shape, output.dtype);\n          }\n          return dy;\n        });\n        return gradientsFunc(dys.length > 1 ? dys : dys[0], saved, attrs);\n      };\n    }\n    this.state.activeTape.push(tapeNode);\n  }\n  keep(result) {\n    result.kept = true;\n    return result;\n  }\n  startTape() {\n    if (this.state.gradientDepth === 0) {\n      this.state.activeTape = [];\n    }\n    this.state.gradientDepth++;\n  }\n  endTape() {\n    this.state.gradientDepth--;\n  }\n  startScope(name) {\n    const scopeInfo = {\n      track: [],\n      name: \"unnamed scope\",\n      id: this.state.nextScopeId++\n    };\n    if (name) {\n      scopeInfo.name = name;\n    }\n    this.state.scopeStack.push(scopeInfo);\n    this.state.activeScope = scopeInfo;\n  }\n  endScope(result) {\n    const tensorsToTrackInParent = getTensorsInContainer(result);\n    const tensorsToTrackInParentSet = new Set(tensorsToTrackInParent.map((t2) => t2.id));\n    for (let i2 = 0; i2 < this.state.activeScope.track.length; i2++) {\n      const tensor2 = this.state.activeScope.track[i2];\n      if (!tensor2.kept && !tensorsToTrackInParentSet.has(tensor2.id)) {\n        tensor2.dispose();\n      }\n    }\n    const oldScope = this.state.scopeStack.pop();\n    this.state.activeScope = this.state.scopeStack.length === 0 ? null : this.state.scopeStack[this.state.scopeStack.length - 1];\n    tensorsToTrackInParent.forEach((tensor2) => {\n      if (!tensor2.kept && tensor2.scopeId === oldScope.id) {\n        this.track(tensor2);\n      }\n    });\n  }\n  gradients(f, xs, dy, allowNoGradients = false) {\n    assert(xs.length > 0, () => \"gradients() received an empty list of xs.\");\n    if (dy != null && dy.dtype !== \"float32\") {\n      throw new Error(`dy must have 'float32' dtype, but has '${dy.dtype}'`);\n    }\n    const y = this.scopedRun(() => this.startTape(), () => this.endTape(), () => this.tidy(\"forward\", f));\n    assert(y instanceof Tensor, () => \"The result y returned by f() must be a tensor.\");\n    const filteredTape = getFilteredNodesXToY(this.state.activeTape, xs, y);\n    if (!allowNoGradients && filteredTape.length === 0 && xs.length > 0) {\n      throw new Error(\"Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.\");\n    }\n    return this.tidy(\"backward\", () => {\n      const accumulatedGradientMap = {};\n      accumulatedGradientMap[y.id] = dy == null ? ones(y.shape) : dy;\n      backpropagateGradients(\n        accumulatedGradientMap,\n        filteredTape,\n        (f2) => this.tidy(f2),\n        add\n      );\n      const grads2 = xs.map((x) => accumulatedGradientMap[x.id]);\n      if (this.state.gradientDepth === 0) {\n        this.state.activeTape.forEach((node) => {\n          for (const tensor2 of node.saved) {\n            tensor2.dispose();\n          }\n        });\n        this.state.activeTape = null;\n      }\n      return { value: y, grads: grads2 };\n    });\n  }\n  customGrad(f) {\n    assert(isFunction(f), () => \"The f passed in customGrad(f) must be a function.\");\n    return (...inputs) => {\n      assert(inputs.every((t2) => t2 instanceof Tensor), () => \"The args passed in customGrad(f)(x1, x2,...) must all be tensors\");\n      let res;\n      const inputMap = {};\n      inputs.forEach((input2, i2) => {\n        inputMap[i2] = input2;\n      });\n      const forwardFunc = (_, save) => {\n        res = f(...[...inputs, save]);\n        assert(res.value instanceof Tensor, () => \"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor\");\n        assert(isFunction(res.gradFunc), () => \"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function.\");\n        return res.value;\n      };\n      const backwardsFunc = (dy, saved) => {\n        const gradRes = res.gradFunc(dy, saved);\n        const grads2 = Array.isArray(gradRes) ? gradRes : [gradRes];\n        assert(grads2.length === inputs.length, () => \"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...).\");\n        assert(grads2.every((t2) => t2 instanceof Tensor), () => \"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors.\");\n        const gradMap = {};\n        grads2.forEach((grad2, i2) => {\n          gradMap[i2] = () => grad2;\n        });\n        return gradMap;\n      };\n      return this.runKernelFunc({\n        forwardFunc,\n        backwardsFunc,\n        inputs: inputMap\n      });\n    };\n  }\n  readSync(dataId) {\n    const info = this.state.tensorInfo.get(dataId);\n    return info.backend.readSync(dataId);\n  }\n  read(dataId) {\n    const info = this.state.tensorInfo.get(dataId);\n    return info.backend.read(dataId);\n  }\n  readToGPU(dataId, options) {\n    const info = this.state.tensorInfo.get(dataId);\n    return info.backend.readToGPU(dataId, options);\n  }\n  async time(query) {\n    const start = now();\n    const timingInfo = await this.backend.time(query);\n    timingInfo.wallMs = now() - start;\n    return timingInfo;\n  }\n  track(result) {\n    if (this.state.activeScope != null) {\n      result.scopeId = this.state.activeScope.id;\n      this.state.activeScope.track.push(result);\n    }\n    return result;\n  }\n  get registeredVariables() {\n    return this.state.registeredVariables;\n  }\n  reset() {\n    this.pendingBackendInitId++;\n    this.state.dispose();\n    this.ENV.reset();\n    this.state = new EngineState();\n    for (const backendName in this.registry) {\n      this.disposeRegisteredKernels(backendName);\n      this.registry[backendName].dispose();\n      delete this.registry[backendName];\n    }\n    this.backendName = null;\n    this.backendInstance = null;\n    this.pendingBackendInit = null;\n  }\n};\nEngine.nextTensorId = 0;\nEngine.nextVariableId = 0;\nfunction ones(shape) {\n  const values = makeOnesTypedArray(sizeFromShape(shape), \"float32\");\n  return ENGINE.makeTensor(values, shape, \"float32\");\n}\nfunction getOrMakeEngine() {\n  const ns = getGlobalNamespace();\n  if (ns._tfengine == null) {\n    const environment = new Environment(ns);\n    ns._tfengine = new Engine(environment);\n  }\n  setEnvironmentGlobal(ns._tfengine.ENV);\n  setTensorTracker(() => ns._tfengine);\n  return ns._tfengine;\n}\nvar ENGINE = getOrMakeEngine();\nfunction add(a, b) {\n  const inputs = { a, b };\n  return ENGINE.runKernel(Add, inputs);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/device_util.js\nvar device_util_exports = {};\n__export(device_util_exports, {\n  isBrowser: () => isBrowser,\n  isMobile: () => isMobile,\n  mockIsMobile: () => mockIsMobile\n});\nfunction _isNavigatorDefined() {\n  return typeof navigator !== \"undefined\" && navigator != null;\n}\nvar isMobileMockValue;\nfunction mockIsMobile(value) {\n  isMobileMockValue = value;\n}\nfunction isMobile(nav) {\n  if (isMobileMockValue !== void 0) {\n    return isMobileMockValue;\n  }\n  if (nav || _isNavigatorDefined()) {\n    if (!nav) {\n      nav = navigator;\n    }\n    if (nav.product === \"ReactNative\") {\n      return true;\n    }\n    const a = nav.userAgent || nav.vendor || (typeof window !== \"undefined\" ? window.opera : \"\");\n    if (!a) {\n      const navAny = nav;\n      return navAny.userAgentData && navAny.userAgentData.mobile;\n    }\n    return /(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i.test(a) || /1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\\-(n|u)|c55\\/|capi|ccwa|cdm\\-|cell|chtm|cldc|cmd\\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\\-s|devi|dica|dmob|do(c|p)o|ds(12|\\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\\-|_)|g1 u|g560|gene|gf\\-5|g\\-mo|go(\\.w|od)|gr(ad|un)|haie|hcit|hd\\-(m|p|t)|hei\\-|hi(pt|ta)|hp( i|ip)|hs\\-c|ht(c(\\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\\-(20|go|ma)|i230|iac( |\\-|\\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\\/)|klon|kpt |kwc\\-|kyo(c|k)|le(no|xi)|lg( g|\\/(k|l|u)|50|54|\\-[a-w])|libw|lynx|m1\\-w|m3ga|m50\\/|ma(te|ui|xo)|mc(01|21|ca)|m\\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\\-2|po(ck|rt|se)|prox|psio|pt\\-g|qa\\-a|qc(07|12|21|32|60|\\-[2-7]|i\\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\\-|oo|p\\-)|sdk\\/|se(c(\\-|0|1)|47|mc|nd|ri)|sgh\\-|shar|sie(\\-|m)|sk\\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\\-|v\\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\\-|tdg\\-|tel(i|m)|tim\\-|t\\-mo|to(pl|sh)|ts(70|m\\-|m3|m5)|tx\\-9|up(\\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\\-|your|zeto|zte\\-/i.test(a.substr(0, 4));\n  }\n  return false;\n}\nfunction isBrowser() {\n  return typeof window !== \"undefined\" && window.document != null || typeof WorkerGlobalScope !== \"undefined\";\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/flags.js\nvar ENV2 = env();\nENV2.registerFlag(\"DEBUG\", () => false, (debugValue) => {\n  if (debugValue) {\n    console.warn(\"Debugging mode is ON. The output of every math call will be downloaded to CPU and checked for NaNs. This significantly impacts performance.\");\n  }\n});\nENV2.registerFlag(\"IS_BROWSER\", () => isBrowser());\nENV2.registerFlag(\"IS_NODE\", () => typeof process !== \"undefined\" && typeof process.versions !== \"undefined\" && typeof process.versions.node !== \"undefined\");\nENV2.registerFlag(\"IS_CHROME\", () => typeof navigator !== \"undefined\" && navigator != null && navigator.userAgent != null && /Chrome/.test(navigator.userAgent) && /Google Inc/.test(navigator.vendor));\nENV2.registerFlag(\"PROD\", () => false);\nENV2.registerFlag(\"TENSORLIKE_CHECK_SHAPE_CONSISTENCY\", () => ENV2.getBool(\"DEBUG\"));\nENV2.registerFlag(\"DEPRECATION_WARNINGS_ENABLED\", () => true);\nENV2.registerFlag(\"IS_TEST\", () => false);\nENV2.registerFlag(\"CHECK_COMPUTATION_FOR_ERRORS\", () => true);\nENV2.registerFlag(\"WRAP_TO_IMAGEBITMAP\", () => false);\nENV2.registerFlag(\"ENGINE_COMPILE_ONLY\", () => false);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/tensor_util_env.js\nfunction inferShape(val, dtype) {\n  let firstElem = val;\n  if (isTypedArray(val)) {\n    return dtype === \"string\" ? [] : [val.length];\n  }\n  if (!Array.isArray(val)) {\n    return [];\n  }\n  const shape = [];\n  while (Array.isArray(firstElem) || isTypedArray(firstElem) && dtype !== \"string\") {\n    shape.push(firstElem.length);\n    firstElem = firstElem[0];\n  }\n  if (Array.isArray(val) && env().getBool(\"TENSORLIKE_CHECK_SHAPE_CONSISTENCY\")) {\n    deepAssertShapeConsistency(val, shape, []);\n  }\n  return shape;\n}\nfunction deepAssertShapeConsistency(val, shape, indices) {\n  indices = indices || [];\n  if (!Array.isArray(val) && !isTypedArray(val)) {\n    assert(shape.length === 0, () => `Element arr[${indices.join(\"][\")}] is a primitive, but should be an array/TypedArray of ${shape[0]} elements`);\n    return;\n  }\n  assert(shape.length > 0, () => `Element arr[${indices.join(\"][\")}] should be a primitive, but is an array of ${val.length} elements`);\n  assert(val.length === shape[0], () => `Element arr[${indices.join(\"][\")}] should have ${shape[0]} elements, but has ${val.length} elements`);\n  const subShape = shape.slice(1);\n  for (let i2 = 0; i2 < val.length; ++i2) {\n    deepAssertShapeConsistency(val[i2], subShape, indices.concat(i2));\n  }\n}\nfunction assertDtype(expectedDtype, actualDType, argName, functionName) {\n  if (expectedDtype === \"string_or_numeric\") {\n    return;\n  }\n  if (expectedDtype == null) {\n    throw new Error(`Expected dtype cannot be null.`);\n  }\n  if (expectedDtype !== \"numeric\" && expectedDtype !== actualDType || expectedDtype === \"numeric\" && actualDType === \"string\") {\n    throw new Error(`Argument '${argName}' passed to '${functionName}' must be ${expectedDtype} tensor, but got ${actualDType} tensor`);\n  }\n}\nfunction convertToTensor(x, argName, functionName, parseAsDtype = \"numeric\") {\n  if (x instanceof Tensor) {\n    assertDtype(parseAsDtype, x.dtype, argName, functionName);\n    return x;\n  }\n  let inferredDtype = inferDtype(x);\n  if (inferredDtype !== \"string\" && [\"bool\", \"int32\", \"float32\"].indexOf(parseAsDtype) >= 0) {\n    inferredDtype = parseAsDtype;\n  }\n  assertDtype(parseAsDtype, inferredDtype, argName, functionName);\n  if (x == null || !isTypedArray(x) && !Array.isArray(x) && typeof x !== \"number\" && typeof x !== \"boolean\" && typeof x !== \"string\") {\n    const type = x == null ? \"null\" : x.constructor.name;\n    throw new Error(`Argument '${argName}' passed to '${functionName}' must be a Tensor or TensorLike, but got '${type}'`);\n  }\n  const inferredShape = inferShape(x, inferredDtype);\n  if (!isTypedArray(x) && !Array.isArray(x)) {\n    x = [x];\n  }\n  const skipTypedArray = true;\n  const values = inferredDtype !== \"string\" ? toTypedArray(x, inferredDtype) : flatten(x, [], skipTypedArray);\n  return ENGINE.makeTensor(values, inferredShape, inferredDtype);\n}\nfunction convertToTensorArray(arg, argName, functionName, parseAsDtype = \"numeric\") {\n  if (!Array.isArray(arg)) {\n    throw new Error(`Argument ${argName} passed to ${functionName} must be a \\`Tensor[]\\` or \\`TensorLike[]\\``);\n  }\n  const tensors = arg;\n  return tensors.map((t2, i2) => convertToTensor(t2, `${argName}[${i2}]`, functionName, parseAsDtype));\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/operation.js\nvar OP_SCOPE_SUFFIX = \"__op\";\nfunction op(f) {\n  const keys = Object.keys(f);\n  if (keys.length !== 1) {\n    throw new Error(`Please provide an object with a single key (operation name) mapping to a function. Got an object with ${keys.length} keys.`);\n  }\n  let opName = keys[0];\n  const fn = f[opName];\n  if (opName.endsWith(\"_\")) {\n    opName = opName.substring(0, opName.length - 1);\n  }\n  opName = opName + OP_SCOPE_SUFFIX;\n  const f2 = (...args) => {\n    ENGINE.startScope(opName);\n    try {\n      const result = fn(...args);\n      if (isPromise(result)) {\n        console.error(\"Cannot return a Promise inside of tidy.\");\n      }\n      ENGINE.endScope(result);\n      return result;\n    } catch (ex) {\n      ENGINE.endScope(null);\n      throw ex;\n    }\n  };\n  Object.defineProperty(f2, \"name\", { value: opName, configurable: true });\n  return f2;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/complex.js\nfunction complex_(real5, imag5) {\n  const $real = convertToTensor(real5, \"real\", \"complex\");\n  const $imag = convertToTensor(imag5, \"imag\", \"complex\");\n  assertShapesMatch($real.shape, $imag.shape, `real and imag shapes, ${$real.shape} and ${$imag.shape}, must match in call to tf.complex().`);\n  const inputs = { real: $real, imag: $imag };\n  return ENGINE.runKernel(Complex, inputs);\n}\nvar complex = op({ complex_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor_ops_util.js\nfunction makeTensor(values, shape, inferredShape, dtype) {\n  if (dtype == null) {\n    dtype = inferDtype(values);\n  }\n  if (dtype === \"complex64\") {\n    throw new Error(`Cannot construct a complex64 tensor directly. Please use tf.complex(real, imag).`);\n  }\n  if (!isTypedArray(values) && !Array.isArray(values) && typeof values !== \"number\" && typeof values !== \"boolean\" && typeof values !== \"string\") {\n    throw new Error(\"values passed to tensor(values) must be a number/boolean/string or an array of numbers/booleans/strings, or a TypedArray\");\n  }\n  if (shape != null) {\n    assertNonNegativeIntegerDimensions(shape);\n    const providedSize = sizeFromShape(shape);\n    const inferredSize = sizeFromShape(inferredShape);\n    assert(providedSize === inferredSize, () => `Based on the provided shape, [${shape}], the tensor should have ${providedSize} values but has ${inferredSize}`);\n    for (let i2 = 0; i2 < inferredShape.length; ++i2) {\n      const inferred = inferredShape[i2];\n      const flatDimsDontMatch = i2 === inferredShape.length - 1 ? inferred !== sizeFromShape(shape.slice(i2)) : true;\n      assert(inferredShape[i2] === shape[i2] || !flatDimsDontMatch, () => `Error creating a new Tensor. Inferred shape (${inferredShape}) does not match the provided shape (${shape}). `);\n    }\n  }\n  if (!isTypedArray(values) && !Array.isArray(values)) {\n    values = [values];\n  }\n  shape = shape || inferredShape;\n  values = dtype !== \"string\" ? toTypedArray(values, dtype) : flatten(values, [], true);\n  return ENGINE.makeTensor(values, shape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor.js\nfunction tensor(values, shape, dtype) {\n  const inferredShape = inferShape(values, dtype);\n  return makeTensor(values, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/types.js\nvar DTYPE_VALUE_SIZE_MAP = {\n  \"float32\": 4,\n  \"float16\": 2,\n  \"int32\": 4,\n  \"uint16\": 2,\n  \"uint8\": 1,\n  \"bool\": 1,\n  \"complex64\": 8\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/io_utils.js\nvar NUM_BYTES_STRING_LENGTH = 4;\nasync function encodeWeights(tensors, group) {\n  const specs = [];\n  const dataPromises = [];\n  const names = Array.isArray(tensors) ? tensors.map((tensor2) => tensor2.name) : Object.keys(tensors);\n  for (let i2 = 0; i2 < names.length; ++i2) {\n    const name = names[i2];\n    const t2 = Array.isArray(tensors) ? tensors[i2].tensor : tensors[name];\n    if (t2.dtype !== \"float32\" && t2.dtype !== \"int32\" && t2.dtype !== \"bool\" && t2.dtype !== \"string\" && t2.dtype !== \"complex64\") {\n      throw new Error(`Unsupported dtype in weight '${name}': ${t2.dtype}`);\n    }\n    const spec = { name, shape: t2.shape, dtype: t2.dtype };\n    if (t2.dtype === \"string\") {\n      const utf8bytes = new Promise(async (resolve) => {\n        const vals = await t2.bytes();\n        const totalNumBytes = vals.reduce((p2, c) => p2 + c.length, 0) + NUM_BYTES_STRING_LENGTH * vals.length;\n        const bytes = new Uint8Array(totalNumBytes);\n        let offset = 0;\n        for (let i3 = 0; i3 < vals.length; i3++) {\n          const val = vals[i3];\n          const bytesOfLength = new Uint8Array(new Uint32Array([val.length]).buffer);\n          bytes.set(bytesOfLength, offset);\n          offset += NUM_BYTES_STRING_LENGTH;\n          bytes.set(val, offset);\n          offset += val.length;\n        }\n        resolve(bytes);\n      });\n      dataPromises.push(utf8bytes);\n    } else {\n      dataPromises.push(t2.data());\n    }\n    if (group != null) {\n      spec.group = group;\n    }\n    specs.push(spec);\n  }\n  const tensorValues = await Promise.all(dataPromises);\n  return { data: concatenateTypedArrays(tensorValues), specs };\n}\nfunction decodeWeights(buffer2, specs) {\n  const out = {};\n  let float16Decode;\n  let offset = 0;\n  for (const spec of specs) {\n    const name = spec.name;\n    const dtype = spec.dtype;\n    const shape = spec.shape;\n    const size = sizeFromShape(shape);\n    let values;\n    if (\"quantization\" in spec) {\n      const quantization = spec.quantization;\n      if (quantization.dtype === \"uint8\" || quantization.dtype === \"uint16\") {\n        if (!(\"min\" in quantization && \"scale\" in quantization)) {\n          throw new Error(`Weight ${spec.name} with quantization ${quantization.dtype} doesn't have corresponding metadata min and scale.`);\n        }\n      } else if (quantization.dtype === \"float16\") {\n        if (dtype !== \"float32\") {\n          throw new Error(`Weight ${spec.name} is quantized with ${quantization.dtype} which only supports weights of type float32 not ${dtype}.`);\n        }\n      } else {\n        throw new Error(`Weight ${spec.name} has unknown quantization dtype ${quantization.dtype}. Supported quantization dtypes are: 'uint8', 'uint16', and 'float16'.`);\n      }\n      const quantizationSizeFactor = DTYPE_VALUE_SIZE_MAP[quantization.dtype];\n      const byteBuffer = buffer2.slice(offset, offset + size * quantizationSizeFactor);\n      const quantizedArray = quantization.dtype === \"uint8\" ? new Uint8Array(byteBuffer) : new Uint16Array(byteBuffer);\n      if (dtype === \"float32\") {\n        if (quantization.dtype === \"uint8\" || quantization.dtype === \"uint16\") {\n          values = new Float32Array(quantizedArray.length);\n          for (let i2 = 0; i2 < quantizedArray.length; i2++) {\n            const v = quantizedArray[i2];\n            values[i2] = v * quantization.scale + quantization.min;\n          }\n        } else if (quantization.dtype === \"float16\") {\n          if (float16Decode === void 0) {\n            float16Decode = getFloat16Decoder();\n          }\n          values = float16Decode(quantizedArray);\n        } else {\n          throw new Error(`Unsupported quantization type ${quantization.dtype} for weight type float32.`);\n        }\n      } else if (dtype === \"int32\") {\n        if (quantization.dtype !== \"uint8\" && quantization.dtype !== \"uint16\") {\n          throw new Error(`Unsupported quantization type ${quantization.dtype} for weight type int32.`);\n        }\n        values = new Int32Array(quantizedArray.length);\n        for (let i2 = 0; i2 < quantizedArray.length; i2++) {\n          const v = quantizedArray[i2];\n          values[i2] = Math.round(v * quantization.scale + quantization.min);\n        }\n      } else {\n        throw new Error(`Unsupported dtype in weight '${name}': ${dtype}`);\n      }\n      offset += size * quantizationSizeFactor;\n    } else if (dtype === \"string\") {\n      const size2 = sizeFromShape(spec.shape);\n      values = [];\n      for (let i2 = 0; i2 < size2; i2++) {\n        const byteLength = new Uint32Array(buffer2.slice(offset, offset + NUM_BYTES_STRING_LENGTH))[0];\n        offset += NUM_BYTES_STRING_LENGTH;\n        const bytes = new Uint8Array(buffer2.slice(offset, offset + byteLength));\n        values.push(bytes);\n        offset += byteLength;\n      }\n    } else {\n      const dtypeFactor = DTYPE_VALUE_SIZE_MAP[dtype];\n      const byteBuffer = buffer2.slice(offset, offset + size * dtypeFactor);\n      if (dtype === \"float32\") {\n        values = new Float32Array(byteBuffer);\n      } else if (dtype === \"int32\") {\n        values = new Int32Array(byteBuffer);\n      } else if (dtype === \"bool\") {\n        values = new Uint8Array(byteBuffer);\n      } else if (dtype === \"complex64\") {\n        values = new Float32Array(byteBuffer);\n        const real5 = new Float32Array(values.length / 2);\n        const image2 = new Float32Array(values.length / 2);\n        for (let i2 = 0; i2 < real5.length; i2++) {\n          real5[i2] = values[i2 * 2];\n          image2[i2] = values[i2 * 2 + 1];\n        }\n        const realTensor = tensor(real5, shape, \"float32\");\n        const imageTensor = tensor(image2, shape, \"float32\");\n        out[name] = complex(realTensor, imageTensor);\n        realTensor.dispose();\n        imageTensor.dispose();\n      } else {\n        throw new Error(`Unsupported dtype in weight '${name}': ${dtype}`);\n      }\n      offset += size * dtypeFactor;\n    }\n    if (dtype !== \"complex64\") {\n      out[name] = tensor(values, shape, dtype);\n    }\n  }\n  return out;\n}\nfunction concatenateTypedArrays(xs) {\n  if (xs === null) {\n    throw new Error(`Invalid input value: ${JSON.stringify(xs)}`);\n  }\n  let totalByteLength = 0;\n  const normalizedXs = [];\n  xs.forEach((x) => {\n    totalByteLength += x.byteLength;\n    normalizedXs.push(x.byteLength === x.buffer.byteLength ? x : new x.constructor(x));\n    if (!(x instanceof Float32Array || x instanceof Int32Array || x instanceof Uint8Array)) {\n      throw new Error(`Unsupported TypedArray subtype: ${x.constructor.name}`);\n    }\n  });\n  const y = new Uint8Array(totalByteLength);\n  let offset = 0;\n  normalizedXs.forEach((x) => {\n    y.set(new Uint8Array(x.buffer), offset);\n    offset += x.byteLength;\n  });\n  return y.buffer;\n}\nvar useNodeBuffer = typeof Buffer !== \"undefined\" && (typeof Blob === \"undefined\" || typeof atob === \"undefined\" || typeof btoa === \"undefined\");\nfunction stringByteLength(str) {\n  if (useNodeBuffer) {\n    return Buffer.byteLength(str);\n  }\n  return new Blob([str]).size;\n}\nfunction arrayBufferToBase64String(buffer2) {\n  if (useNodeBuffer) {\n    return Buffer.from(buffer2).toString(\"base64\");\n  }\n  const buf = new Uint8Array(buffer2);\n  let s2 = \"\";\n  for (let i2 = 0, l3 = buf.length; i2 < l3; i2++) {\n    s2 += String.fromCharCode(buf[i2]);\n  }\n  return btoa(s2);\n}\nfunction base64StringToArrayBuffer(str) {\n  if (useNodeBuffer) {\n    const buf = Buffer.from(str, \"base64\");\n    return buf.buffer.slice(buf.byteOffset, buf.byteOffset + buf.byteLength);\n  }\n  const s2 = atob(str);\n  const buffer2 = new Uint8Array(s2.length);\n  for (let i2 = 0; i2 < s2.length; ++i2) {\n    buffer2.set([s2.charCodeAt(i2)], i2);\n  }\n  return buffer2.buffer;\n}\nfunction concatenateArrayBuffers(buffers) {\n  if (buffers.length === 1) {\n    return buffers[0];\n  }\n  let totalByteLength = 0;\n  buffers.forEach((buffer2) => {\n    totalByteLength += buffer2.byteLength;\n  });\n  const temp = new Uint8Array(totalByteLength);\n  let offset = 0;\n  buffers.forEach((buffer2) => {\n    temp.set(new Uint8Array(buffer2), offset);\n    offset += buffer2.byteLength;\n  });\n  return temp.buffer;\n}\nfunction basename(path) {\n  const SEPARATOR = \"/\";\n  path = path.trim();\n  while (path.endsWith(SEPARATOR)) {\n    path = path.slice(0, path.length - 1);\n  }\n  const items = path.split(SEPARATOR);\n  return items[items.length - 1];\n}\nfunction getModelJSONForModelArtifacts(artifacts, manifest) {\n  const result = {\n    modelTopology: artifacts.modelTopology,\n    format: artifacts.format,\n    generatedBy: artifacts.generatedBy,\n    convertedBy: artifacts.convertedBy,\n    weightsManifest: manifest\n  };\n  if (artifacts.signature != null) {\n    result.signature = artifacts.signature;\n  }\n  if (artifacts.userDefinedMetadata != null) {\n    result.userDefinedMetadata = artifacts.userDefinedMetadata;\n  }\n  if (artifacts.modelInitializer != null) {\n    result.modelInitializer = artifacts.modelInitializer;\n  }\n  if (artifacts.trainingConfig != null) {\n    result.trainingConfig = artifacts.trainingConfig;\n  }\n  return result;\n}\nasync function getModelArtifactsForJSON(modelJSON, loadWeights2) {\n  const modelArtifacts = {\n    modelTopology: modelJSON.modelTopology,\n    format: modelJSON.format,\n    generatedBy: modelJSON.generatedBy,\n    convertedBy: modelJSON.convertedBy\n  };\n  if (modelJSON.trainingConfig != null) {\n    modelArtifacts.trainingConfig = modelJSON.trainingConfig;\n  }\n  if (modelJSON.weightsManifest != null) {\n    const [weightSpecs, weightData] = await loadWeights2(modelJSON.weightsManifest);\n    modelArtifacts.weightSpecs = weightSpecs;\n    modelArtifacts.weightData = weightData;\n  }\n  if (modelJSON.signature != null) {\n    modelArtifacts.signature = modelJSON.signature;\n  }\n  if (modelJSON.userDefinedMetadata != null) {\n    modelArtifacts.userDefinedMetadata = modelJSON.userDefinedMetadata;\n  }\n  if (modelJSON.modelInitializer != null) {\n    modelArtifacts.modelInitializer = modelJSON.modelInitializer;\n  }\n  return modelArtifacts;\n}\nfunction getModelArtifactsInfoForJSON(modelArtifacts) {\n  if (modelArtifacts.modelTopology instanceof ArrayBuffer) {\n    throw new Error(\"Expected JSON model topology, received ArrayBuffer.\");\n  }\n  return {\n    dateSaved: new Date(),\n    modelTopologyType: \"JSON\",\n    modelTopologyBytes: modelArtifacts.modelTopology == null ? 0 : stringByteLength(JSON.stringify(modelArtifacts.modelTopology)),\n    weightSpecsBytes: modelArtifacts.weightSpecs == null ? 0 : stringByteLength(JSON.stringify(modelArtifacts.weightSpecs)),\n    weightDataBytes: modelArtifacts.weightData == null ? 0 : modelArtifacts.weightData.byteLength\n  };\n}\nfunction computeFloat16MantisaTable() {\n  const convertMantissa = (i2) => {\n    let m = i2 << 13;\n    let e2 = 0;\n    while ((m & 8388608) === 0) {\n      e2 -= 8388608;\n      m <<= 1;\n    }\n    m &= ~8388608;\n    e2 += 947912704;\n    return m | e2;\n  };\n  const mantisaTable = new Uint32Array(2048);\n  mantisaTable[0] = 0;\n  for (let i2 = 1; i2 < 1024; i2++) {\n    mantisaTable[i2] = convertMantissa(i2);\n  }\n  for (let i2 = 1024; i2 < 2048; i2++) {\n    mantisaTable[i2] = 939524096 + (i2 - 1024 << 13);\n  }\n  return mantisaTable;\n}\nfunction computeFloat16ExponentTable() {\n  const exponentTable = new Uint32Array(64);\n  exponentTable[0] = 0;\n  exponentTable[31] = 1199570944;\n  exponentTable[32] = 2147483648;\n  exponentTable[63] = 3347054592;\n  for (let i2 = 1; i2 < 31; i2++) {\n    exponentTable[i2] = i2 << 23;\n  }\n  for (let i2 = 33; i2 < 63; i2++) {\n    exponentTable[i2] = 2147483648 + (i2 - 32 << 23);\n  }\n  return exponentTable;\n}\nfunction computeFloat16OffsetTable() {\n  const offsetTable = new Uint32Array(64);\n  for (let i2 = 0; i2 < 64; i2++) {\n    offsetTable[i2] = 1024;\n  }\n  offsetTable[0] = offsetTable[32] = 0;\n  return offsetTable;\n}\nfunction getFloat16Decoder() {\n  const mantisaTable = computeFloat16MantisaTable();\n  const exponentTable = computeFloat16ExponentTable();\n  const offsetTable = computeFloat16OffsetTable();\n  return (quantizedArray) => {\n    const buffer2 = new ArrayBuffer(4 * quantizedArray.length);\n    const bufferUint32View = new Uint32Array(buffer2);\n    for (let index = 0; index < quantizedArray.length; index++) {\n      const float16Bits = quantizedArray[index];\n      const float32Bits = mantisaTable[offsetTable[float16Bits >> 10] + (float16Bits & 1023)] + exponentTable[float16Bits >> 10];\n      bufferUint32View[index] = float32Bits;\n    }\n    return new Float32Array(buffer2);\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/router_registry.js\nvar IORouterRegistry = class {\n  constructor() {\n    this.saveRouters = [];\n    this.loadRouters = [];\n  }\n  static getInstance() {\n    if (IORouterRegistry.instance == null) {\n      IORouterRegistry.instance = new IORouterRegistry();\n    }\n    return IORouterRegistry.instance;\n  }\n  static registerSaveRouter(saveRouter) {\n    IORouterRegistry.getInstance().saveRouters.push(saveRouter);\n  }\n  static registerLoadRouter(loadRouter) {\n    IORouterRegistry.getInstance().loadRouters.push(loadRouter);\n  }\n  static getSaveHandlers(url) {\n    return IORouterRegistry.getHandlers(url, \"save\");\n  }\n  static getLoadHandlers(url, loadOptions) {\n    return IORouterRegistry.getHandlers(url, \"load\", loadOptions);\n  }\n  static getHandlers(url, handlerType, loadOptions) {\n    const validHandlers = [];\n    const routers = handlerType === \"load\" ? IORouterRegistry.getInstance().loadRouters : IORouterRegistry.getInstance().saveRouters;\n    routers.forEach((router) => {\n      const handler = router(url, loadOptions);\n      if (handler !== null) {\n        validHandlers.push(handler);\n      }\n    });\n    return validHandlers;\n  }\n};\nvar registerSaveRouter = (loudRouter) => IORouterRegistry.registerSaveRouter(loudRouter);\nvar registerLoadRouter = (loudRouter) => IORouterRegistry.registerLoadRouter(loudRouter);\nvar getSaveHandlers = (url) => IORouterRegistry.getSaveHandlers(url);\nvar getLoadHandlers = (url, loadOptions) => IORouterRegistry.getLoadHandlers(url, loadOptions);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/indexed_db.js\nvar DATABASE_NAME = \"tensorflowjs\";\nvar DATABASE_VERSION = 1;\nvar MODEL_STORE_NAME = \"models_store\";\nvar INFO_STORE_NAME = \"model_info_store\";\nfunction getIndexedDBFactory() {\n  if (!env().getBool(\"IS_BROWSER\")) {\n    throw new Error(\"Failed to obtain IndexedDB factory because the current environmentis not a web browser.\");\n  }\n  const theWindow = typeof window === \"undefined\" ? self : window;\n  const factory = theWindow.indexedDB || theWindow.mozIndexedDB || theWindow.webkitIndexedDB || theWindow.msIndexedDB || theWindow.shimIndexedDB;\n  if (factory == null) {\n    throw new Error(\"The current browser does not appear to support IndexedDB.\");\n  }\n  return factory;\n}\nfunction setUpDatabase(openRequest) {\n  const db = openRequest.result;\n  db.createObjectStore(MODEL_STORE_NAME, { keyPath: \"modelPath\" });\n  db.createObjectStore(INFO_STORE_NAME, { keyPath: \"modelPath\" });\n}\nvar BrowserIndexedDB = class {\n  constructor(modelPath) {\n    this.indexedDB = getIndexedDBFactory();\n    if (modelPath == null || !modelPath) {\n      throw new Error(\"For IndexedDB, modelPath must not be null, undefined or empty.\");\n    }\n    this.modelPath = modelPath;\n  }\n  async save(modelArtifacts) {\n    if (modelArtifacts.modelTopology instanceof ArrayBuffer) {\n      throw new Error(\"BrowserLocalStorage.save() does not support saving model topology in binary formats yet.\");\n    }\n    return this.databaseAction(this.modelPath, modelArtifacts);\n  }\n  async load() {\n    return this.databaseAction(this.modelPath);\n  }\n  databaseAction(modelPath, modelArtifacts) {\n    return new Promise((resolve, reject) => {\n      const openRequest = this.indexedDB.open(DATABASE_NAME, DATABASE_VERSION);\n      openRequest.onupgradeneeded = () => setUpDatabase(openRequest);\n      openRequest.onsuccess = () => {\n        const db = openRequest.result;\n        if (modelArtifacts == null) {\n          const modelTx = db.transaction(MODEL_STORE_NAME, \"readonly\");\n          const modelStore = modelTx.objectStore(MODEL_STORE_NAME);\n          const getRequest = modelStore.get(this.modelPath);\n          getRequest.onsuccess = () => {\n            if (getRequest.result == null) {\n              db.close();\n              return reject(new Error(`Cannot find model with path '${this.modelPath}' in IndexedDB.`));\n            } else {\n              resolve(getRequest.result.modelArtifacts);\n            }\n          };\n          getRequest.onerror = (error) => {\n            db.close();\n            return reject(getRequest.error);\n          };\n          modelTx.oncomplete = () => db.close();\n        } else {\n          const modelArtifactsInfo = getModelArtifactsInfoForJSON(modelArtifacts);\n          const infoTx = db.transaction(INFO_STORE_NAME, \"readwrite\");\n          let infoStore = infoTx.objectStore(INFO_STORE_NAME);\n          const putInfoRequest = infoStore.put({ modelPath: this.modelPath, modelArtifactsInfo });\n          let modelTx;\n          putInfoRequest.onsuccess = () => {\n            modelTx = db.transaction(MODEL_STORE_NAME, \"readwrite\");\n            const modelStore = modelTx.objectStore(MODEL_STORE_NAME);\n            const putModelRequest = modelStore.put({\n              modelPath: this.modelPath,\n              modelArtifacts,\n              modelArtifactsInfo\n            });\n            putModelRequest.onsuccess = () => resolve({ modelArtifactsInfo });\n            putModelRequest.onerror = (error) => {\n              infoStore = infoTx.objectStore(INFO_STORE_NAME);\n              const deleteInfoRequest = infoStore.delete(this.modelPath);\n              deleteInfoRequest.onsuccess = () => {\n                db.close();\n                return reject(putModelRequest.error);\n              };\n              deleteInfoRequest.onerror = (error2) => {\n                db.close();\n                return reject(putModelRequest.error);\n              };\n            };\n          };\n          putInfoRequest.onerror = (error) => {\n            db.close();\n            return reject(putInfoRequest.error);\n          };\n          infoTx.oncomplete = () => {\n            if (modelTx == null) {\n              db.close();\n            } else {\n              modelTx.oncomplete = () => db.close();\n            }\n          };\n        }\n      };\n      openRequest.onerror = (error) => reject(openRequest.error);\n    });\n  }\n};\nBrowserIndexedDB.URL_SCHEME = \"indexeddb://\";\nvar indexedDBRouter = (url) => {\n  if (!env().getBool(\"IS_BROWSER\")) {\n    return null;\n  } else {\n    if (!Array.isArray(url) && url.startsWith(BrowserIndexedDB.URL_SCHEME)) {\n      return browserIndexedDB(url.slice(BrowserIndexedDB.URL_SCHEME.length));\n    } else {\n      return null;\n    }\n  }\n};\nIORouterRegistry.registerSaveRouter(indexedDBRouter);\nIORouterRegistry.registerLoadRouter(indexedDBRouter);\nfunction browserIndexedDB(modelPath) {\n  return new BrowserIndexedDB(modelPath);\n}\nfunction maybeStripScheme(key) {\n  return key.startsWith(BrowserIndexedDB.URL_SCHEME) ? key.slice(BrowserIndexedDB.URL_SCHEME.length) : key;\n}\nvar BrowserIndexedDBManager = class {\n  constructor() {\n    this.indexedDB = getIndexedDBFactory();\n  }\n  async listModels() {\n    return new Promise((resolve, reject) => {\n      const openRequest = this.indexedDB.open(DATABASE_NAME, DATABASE_VERSION);\n      openRequest.onupgradeneeded = () => setUpDatabase(openRequest);\n      openRequest.onsuccess = () => {\n        const db = openRequest.result;\n        const tx = db.transaction(INFO_STORE_NAME, \"readonly\");\n        const store = tx.objectStore(INFO_STORE_NAME);\n        const getAllInfoRequest = store.getAll();\n        getAllInfoRequest.onsuccess = () => {\n          const out = {};\n          for (const item of getAllInfoRequest.result) {\n            out[item.modelPath] = item.modelArtifactsInfo;\n          }\n          resolve(out);\n        };\n        getAllInfoRequest.onerror = (error) => {\n          db.close();\n          return reject(getAllInfoRequest.error);\n        };\n        tx.oncomplete = () => db.close();\n      };\n      openRequest.onerror = (error) => reject(openRequest.error);\n    });\n  }\n  async removeModel(path) {\n    path = maybeStripScheme(path);\n    return new Promise((resolve, reject) => {\n      const openRequest = this.indexedDB.open(DATABASE_NAME, DATABASE_VERSION);\n      openRequest.onupgradeneeded = () => setUpDatabase(openRequest);\n      openRequest.onsuccess = () => {\n        const db = openRequest.result;\n        const infoTx = db.transaction(INFO_STORE_NAME, \"readwrite\");\n        const infoStore = infoTx.objectStore(INFO_STORE_NAME);\n        const getInfoRequest = infoStore.get(path);\n        let modelTx;\n        getInfoRequest.onsuccess = () => {\n          if (getInfoRequest.result == null) {\n            db.close();\n            return reject(new Error(`Cannot find model with path '${path}' in IndexedDB.`));\n          } else {\n            const deleteInfoRequest = infoStore.delete(path);\n            const deleteModelData = () => {\n              modelTx = db.transaction(MODEL_STORE_NAME, \"readwrite\");\n              const modelStore = modelTx.objectStore(MODEL_STORE_NAME);\n              const deleteModelRequest = modelStore.delete(path);\n              deleteModelRequest.onsuccess = () => resolve(getInfoRequest.result.modelArtifactsInfo);\n              deleteModelRequest.onerror = (error) => reject(getInfoRequest.error);\n            };\n            deleteInfoRequest.onsuccess = deleteModelData;\n            deleteInfoRequest.onerror = (error) => {\n              deleteModelData();\n              db.close();\n              return reject(getInfoRequest.error);\n            };\n          }\n        };\n        getInfoRequest.onerror = (error) => {\n          db.close();\n          return reject(getInfoRequest.error);\n        };\n        infoTx.oncomplete = () => {\n          if (modelTx == null) {\n            db.close();\n          } else {\n            modelTx.oncomplete = () => db.close();\n          }\n        };\n      };\n      openRequest.onerror = (error) => reject(openRequest.error);\n    });\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/local_storage.js\nvar PATH_SEPARATOR = \"/\";\nvar PATH_PREFIX = \"tensorflowjs_models\";\nvar INFO_SUFFIX = \"info\";\nvar MODEL_TOPOLOGY_SUFFIX = \"model_topology\";\nvar WEIGHT_SPECS_SUFFIX = \"weight_specs\";\nvar WEIGHT_DATA_SUFFIX = \"weight_data\";\nvar MODEL_METADATA_SUFFIX = \"model_metadata\";\nfunction getModelKeys(path) {\n  return {\n    info: [PATH_PREFIX, path, INFO_SUFFIX].join(PATH_SEPARATOR),\n    topology: [PATH_PREFIX, path, MODEL_TOPOLOGY_SUFFIX].join(PATH_SEPARATOR),\n    weightSpecs: [PATH_PREFIX, path, WEIGHT_SPECS_SUFFIX].join(PATH_SEPARATOR),\n    weightData: [PATH_PREFIX, path, WEIGHT_DATA_SUFFIX].join(PATH_SEPARATOR),\n    modelMetadata: [PATH_PREFIX, path, MODEL_METADATA_SUFFIX].join(PATH_SEPARATOR)\n  };\n}\nfunction removeItems(keys) {\n  for (const key of Object.values(keys)) {\n    window.localStorage.removeItem(key);\n  }\n}\nfunction getModelPathFromKey(key) {\n  const items = key.split(PATH_SEPARATOR);\n  if (items.length < 3) {\n    throw new Error(`Invalid key format: ${key}`);\n  }\n  return items.slice(1, items.length - 1).join(PATH_SEPARATOR);\n}\nfunction maybeStripScheme2(key) {\n  return key.startsWith(BrowserLocalStorage.URL_SCHEME) ? key.slice(BrowserLocalStorage.URL_SCHEME.length) : key;\n}\nvar BrowserLocalStorage = class {\n  constructor(modelPath) {\n    if (!env().getBool(\"IS_BROWSER\") || typeof window === \"undefined\" || typeof window.localStorage === \"undefined\") {\n      throw new Error(\"The current environment does not support local storage.\");\n    }\n    this.LS = window.localStorage;\n    if (modelPath == null || !modelPath) {\n      throw new Error(\"For local storage, modelPath must not be null, undefined or empty.\");\n    }\n    this.modelPath = modelPath;\n    this.keys = getModelKeys(this.modelPath);\n  }\n  async save(modelArtifacts) {\n    if (modelArtifacts.modelTopology instanceof ArrayBuffer) {\n      throw new Error(\"BrowserLocalStorage.save() does not support saving model topology in binary formats yet.\");\n    } else {\n      const topology = JSON.stringify(modelArtifacts.modelTopology);\n      const weightSpecs = JSON.stringify(modelArtifacts.weightSpecs);\n      const modelArtifactsInfo = getModelArtifactsInfoForJSON(modelArtifacts);\n      try {\n        this.LS.setItem(this.keys.info, JSON.stringify(modelArtifactsInfo));\n        this.LS.setItem(this.keys.topology, topology);\n        this.LS.setItem(this.keys.weightSpecs, weightSpecs);\n        this.LS.setItem(this.keys.weightData, arrayBufferToBase64String(modelArtifacts.weightData));\n        const metadata = {\n          format: modelArtifacts.format,\n          generatedBy: modelArtifacts.generatedBy,\n          convertedBy: modelArtifacts.convertedBy,\n          signature: modelArtifacts.signature != null ? modelArtifacts.signature : void 0,\n          userDefinedMetadata: modelArtifacts.userDefinedMetadata != null ? modelArtifacts.userDefinedMetadata : void 0,\n          modelInitializer: modelArtifacts.modelInitializer != null ? modelArtifacts.modelInitializer : void 0,\n          trainingConfig: modelArtifacts.trainingConfig != null ? modelArtifacts.trainingConfig : void 0\n        };\n        this.LS.setItem(this.keys.modelMetadata, JSON.stringify(metadata));\n        return { modelArtifactsInfo };\n      } catch (err) {\n        removeItems(this.keys);\n        throw new Error(`Failed to save model '${this.modelPath}' to local storage: size quota being exceeded is a possible cause of this failure: modelTopologyBytes=${modelArtifactsInfo.modelTopologyBytes}, weightSpecsBytes=${modelArtifactsInfo.weightSpecsBytes}, weightDataBytes=${modelArtifactsInfo.weightDataBytes}.`);\n      }\n    }\n  }\n  async load() {\n    const info = JSON.parse(this.LS.getItem(this.keys.info));\n    if (info == null) {\n      throw new Error(`In local storage, there is no model with name '${this.modelPath}'`);\n    }\n    if (info.modelTopologyType !== \"JSON\") {\n      throw new Error(\"BrowserLocalStorage does not support loading non-JSON model topology yet.\");\n    }\n    const out = {};\n    const topology = JSON.parse(this.LS.getItem(this.keys.topology));\n    if (topology == null) {\n      throw new Error(`In local storage, the topology of model '${this.modelPath}' is missing.`);\n    }\n    out.modelTopology = topology;\n    const weightSpecs = JSON.parse(this.LS.getItem(this.keys.weightSpecs));\n    if (weightSpecs == null) {\n      throw new Error(`In local storage, the weight specs of model '${this.modelPath}' are missing.`);\n    }\n    out.weightSpecs = weightSpecs;\n    const metadataString = this.LS.getItem(this.keys.modelMetadata);\n    if (metadataString != null) {\n      const metadata = JSON.parse(metadataString);\n      out.format = metadata.format;\n      out.generatedBy = metadata.generatedBy;\n      out.convertedBy = metadata.convertedBy;\n      if (metadata.signature != null) {\n        out.signature = metadata.signature;\n      }\n      if (metadata.userDefinedMetadata != null) {\n        out.userDefinedMetadata = metadata.userDefinedMetadata;\n      }\n      if (metadata.modelInitializer != null) {\n        out.modelInitializer = metadata.modelInitializer;\n      }\n      if (metadata.trainingConfig != null) {\n        out.trainingConfig = metadata.trainingConfig;\n      }\n    }\n    const weightDataBase64 = this.LS.getItem(this.keys.weightData);\n    if (weightDataBase64 == null) {\n      throw new Error(`In local storage, the binary weight values of model '${this.modelPath}' are missing.`);\n    }\n    out.weightData = base64StringToArrayBuffer(weightDataBase64);\n    return out;\n  }\n};\nBrowserLocalStorage.URL_SCHEME = \"localstorage://\";\nvar localStorageRouter = (url) => {\n  if (!env().getBool(\"IS_BROWSER\")) {\n    return null;\n  } else {\n    if (!Array.isArray(url) && url.startsWith(BrowserLocalStorage.URL_SCHEME)) {\n      return browserLocalStorage(url.slice(BrowserLocalStorage.URL_SCHEME.length));\n    } else {\n      return null;\n    }\n  }\n};\nIORouterRegistry.registerSaveRouter(localStorageRouter);\nIORouterRegistry.registerLoadRouter(localStorageRouter);\nfunction browserLocalStorage(modelPath) {\n  return new BrowserLocalStorage(modelPath);\n}\nvar BrowserLocalStorageManager = class {\n  constructor() {\n    assert(env().getBool(\"IS_BROWSER\"), () => \"Current environment is not a web browser\");\n    assert(typeof window === \"undefined\" || typeof window.localStorage !== \"undefined\", () => \"Current browser does not appear to support localStorage\");\n    this.LS = window.localStorage;\n  }\n  async listModels() {\n    const out = {};\n    const prefix = PATH_PREFIX + PATH_SEPARATOR;\n    const suffix = PATH_SEPARATOR + INFO_SUFFIX;\n    for (let i2 = 0; i2 < this.LS.length; ++i2) {\n      const key = this.LS.key(i2);\n      if (key.startsWith(prefix) && key.endsWith(suffix)) {\n        const modelPath = getModelPathFromKey(key);\n        out[modelPath] = JSON.parse(this.LS.getItem(key));\n      }\n    }\n    return out;\n  }\n  async removeModel(path) {\n    path = maybeStripScheme2(path);\n    const keys = getModelKeys(path);\n    if (this.LS.getItem(keys.info) == null) {\n      throw new Error(`Cannot find model at path '${path}'`);\n    }\n    const info = JSON.parse(this.LS.getItem(keys.info));\n    removeItems(keys);\n    return info;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/model_management.js\nvar URL_SCHEME_SUFFIX = \"://\";\nvar ModelStoreManagerRegistry = class {\n  constructor() {\n    this.managers = {};\n  }\n  static getInstance() {\n    if (ModelStoreManagerRegistry.instance == null) {\n      ModelStoreManagerRegistry.instance = new ModelStoreManagerRegistry();\n    }\n    return ModelStoreManagerRegistry.instance;\n  }\n  static registerManager(scheme, manager) {\n    assert(scheme != null, () => \"scheme must not be undefined or null.\");\n    if (scheme.endsWith(URL_SCHEME_SUFFIX)) {\n      scheme = scheme.slice(0, scheme.indexOf(URL_SCHEME_SUFFIX));\n    }\n    assert(scheme.length > 0, () => \"scheme must not be an empty string.\");\n    const registry = ModelStoreManagerRegistry.getInstance();\n    assert(registry.managers[scheme] == null, () => `A model store manager is already registered for scheme '${scheme}'.`);\n    registry.managers[scheme] = manager;\n  }\n  static getManager(scheme) {\n    const manager = ModelStoreManagerRegistry.getInstance().managers[scheme];\n    if (manager == null) {\n      throw new Error(`Cannot find model manager for scheme '${scheme}'`);\n    }\n    return manager;\n  }\n  static getSchemes() {\n    return Object.keys(ModelStoreManagerRegistry.getInstance().managers);\n  }\n};\nfunction parseURL(url) {\n  if (url.indexOf(URL_SCHEME_SUFFIX) === -1) {\n    throw new Error(`The url string provided does not contain a scheme. Supported schemes are: ${ModelStoreManagerRegistry.getSchemes().join(\",\")}`);\n  }\n  return {\n    scheme: url.split(URL_SCHEME_SUFFIX)[0],\n    path: url.split(URL_SCHEME_SUFFIX)[1]\n  };\n}\nasync function cloneModelInternal(sourceURL, destURL, deleteSource = false) {\n  assert(sourceURL !== destURL, () => `Old path and new path are the same: '${sourceURL}'`);\n  const loadHandlers = IORouterRegistry.getLoadHandlers(sourceURL);\n  assert(loadHandlers.length > 0, () => `Copying failed because no load handler is found for source URL ${sourceURL}.`);\n  assert(loadHandlers.length < 2, () => `Copying failed because more than one (${loadHandlers.length}) load handlers for source URL ${sourceURL}.`);\n  const loadHandler = loadHandlers[0];\n  const saveHandlers = IORouterRegistry.getSaveHandlers(destURL);\n  assert(saveHandlers.length > 0, () => `Copying failed because no save handler is found for destination URL ${destURL}.`);\n  assert(saveHandlers.length < 2, () => `Copying failed because more than one (${loadHandlers.length}) save handlers for destination URL ${destURL}.`);\n  const saveHandler = saveHandlers[0];\n  const sourceScheme = parseURL(sourceURL).scheme;\n  const sourcePath = parseURL(sourceURL).path;\n  const sameMedium = sourceScheme === parseURL(sourceURL).scheme;\n  const modelArtifacts = await loadHandler.load();\n  if (deleteSource && sameMedium) {\n    await ModelStoreManagerRegistry.getManager(sourceScheme).removeModel(sourcePath);\n  }\n  const saveResult = await saveHandler.save(modelArtifacts);\n  if (deleteSource && !sameMedium) {\n    await ModelStoreManagerRegistry.getManager(sourceScheme).removeModel(sourcePath);\n  }\n  return saveResult.modelArtifactsInfo;\n}\nasync function listModels() {\n  const schemes = ModelStoreManagerRegistry.getSchemes();\n  const out = {};\n  for (const scheme of schemes) {\n    const schemeOut = await ModelStoreManagerRegistry.getManager(scheme).listModels();\n    for (const path in schemeOut) {\n      const url = scheme + URL_SCHEME_SUFFIX + path;\n      out[url] = schemeOut[path];\n    }\n  }\n  return out;\n}\nasync function removeModel(url) {\n  const schemeAndPath = parseURL(url);\n  const manager = ModelStoreManagerRegistry.getManager(schemeAndPath.scheme);\n  return manager.removeModel(schemeAndPath.path);\n}\nasync function copyModel(sourceURL, destURL) {\n  const deleteSource = false;\n  return cloneModelInternal(sourceURL, destURL, deleteSource);\n}\nasync function moveModel(sourceURL, destURL) {\n  const deleteSource = true;\n  return cloneModelInternal(sourceURL, destURL, deleteSource);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/platforms/platform_browser.js\nvar PlatformBrowser = class {\n  fetch(path, init2) {\n    return fetch(path, init2);\n  }\n  now() {\n    return performance.now();\n  }\n  encode(text, encoding) {\n    if (encoding !== \"utf-8\" && encoding !== \"utf8\") {\n      throw new Error(`Browser's encoder only supports utf-8, but got ${encoding}`);\n    }\n    if (this.textEncoder == null) {\n      this.textEncoder = new TextEncoder();\n    }\n    return this.textEncoder.encode(text);\n  }\n  decode(bytes, encoding) {\n    return new TextDecoder(encoding).decode(bytes);\n  }\n};\nif (env().get(\"IS_BROWSER\")) {\n  env().setPlatform(\"browser\", new PlatformBrowser());\n  try {\n    ModelStoreManagerRegistry.registerManager(BrowserLocalStorage.URL_SCHEME, new BrowserLocalStorageManager());\n  } catch (err) {\n  }\n  try {\n    ModelStoreManagerRegistry.registerManager(BrowserIndexedDB.URL_SCHEME, new BrowserIndexedDBManager());\n  } catch (err) {\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/platforms/platform_node.js\nvar getNodeFetch = {\n  importFetch: () => require_browser()\n};\nvar systemFetch;\nvar PlatformNode = class {\n  constructor() {\n    this.util = require_util();\n    this.textEncoder = new this.util.TextEncoder();\n  }\n  fetch(path, requestInits) {\n    if (env().global.fetch != null) {\n      return env().global.fetch(path, requestInits);\n    }\n    if (systemFetch == null) {\n      systemFetch = getNodeFetch.importFetch();\n    }\n    return systemFetch(path, requestInits);\n  }\n  now() {\n    const time2 = process.hrtime();\n    return time2[0] * 1e3 + time2[1] / 1e6;\n  }\n  encode(text, encoding) {\n    if (encoding !== \"utf-8\" && encoding !== \"utf8\") {\n      throw new Error(`Node built-in encoder only supports utf-8, but got ${encoding}`);\n    }\n    return this.textEncoder.encode(text);\n  }\n  decode(bytes, encoding) {\n    if (bytes.length === 0) {\n      return \"\";\n    }\n    return new this.util.TextDecoder(encoding).decode(bytes);\n  }\n};\nif (env().get(\"IS_NODE\") && !env().get(\"IS_BROWSER\")) {\n  env().setPlatform(\"node\", new PlatformNode());\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/buffer.js\nfunction buffer(shape, dtype = \"float32\", values) {\n  dtype = dtype || \"float32\";\n  assertNonNegativeIntegerDimensions(shape);\n  return new TensorBuffer(shape, dtype, values);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/cast.js\nfunction cast_(x, dtype) {\n  const $x = convertToTensor(x, \"x\", \"cast\");\n  if (!isValidDtype(dtype)) {\n    throw new Error(`Failed to cast to unknown dtype ${dtype}`);\n  }\n  if (dtype === \"string\" && $x.dtype !== \"string\" || dtype !== \"string\" && $x.dtype === \"string\") {\n    throw new Error(\"Only strings can be casted to strings\");\n  }\n  const inputs = { x: $x };\n  const attrs = { dtype };\n  return ENGINE.runKernel(Cast, inputs, attrs);\n}\nvar cast = op({ cast_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/clone.js\nfunction clone_(x) {\n  const $x = convertToTensor(x, \"x\", \"clone\", \"string_or_numeric\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Identity, inputs);\n}\nvar clone = op({ clone_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/print.js\nfunction print(x, verbose = false) {\n  console.log(x.toString(verbose));\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/base_side_effects.js\ngetOrMakeEngine();\nvar opHandler2 = {\n  buffer,\n  cast,\n  clone,\n  print\n};\nsetOpHandler(opHandler2);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/io.js\nvar io_exports = {};\n__export(io_exports, {\n  browserFiles: () => browserFiles,\n  browserHTTPRequest: () => browserHTTPRequest,\n  concatenateArrayBuffers: () => concatenateArrayBuffers,\n  copyModel: () => copyModel,\n  decodeWeights: () => decodeWeights,\n  encodeWeights: () => encodeWeights,\n  fromMemory: () => fromMemory,\n  fromMemorySync: () => fromMemorySync,\n  getLoadHandlers: () => getLoadHandlers,\n  getModelArtifactsForJSON: () => getModelArtifactsForJSON,\n  getModelArtifactsInfoForJSON: () => getModelArtifactsInfoForJSON,\n  getSaveHandlers: () => getSaveHandlers,\n  http: () => http,\n  isHTTPScheme: () => isHTTPScheme,\n  listModels: () => listModels,\n  loadWeights: () => loadWeights,\n  moveModel: () => moveModel,\n  registerLoadRouter: () => registerLoadRouter,\n  registerSaveRouter: () => registerSaveRouter,\n  removeModel: () => removeModel,\n  weightsLoaderFactory: () => weightsLoaderFactory,\n  withSaveHandler: () => withSaveHandler,\n  withSaveHandlerSync: () => withSaveHandlerSync\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/browser_files.js\nvar DEFAULT_FILE_NAME_PREFIX = \"model\";\nvar DEFAULT_JSON_EXTENSION_NAME = \".json\";\nvar DEFAULT_WEIGHT_DATA_EXTENSION_NAME = \".weights.bin\";\nfunction defer(f) {\n  return new Promise((resolve) => setTimeout(resolve)).then(f);\n}\nvar BrowserDownloads = class {\n  constructor(fileNamePrefix) {\n    if (!env().getBool(\"IS_BROWSER\")) {\n      throw new Error(\"browserDownloads() cannot proceed because the current environment is not a browser.\");\n    }\n    if (fileNamePrefix.startsWith(BrowserDownloads.URL_SCHEME)) {\n      fileNamePrefix = fileNamePrefix.slice(BrowserDownloads.URL_SCHEME.length);\n    }\n    if (fileNamePrefix == null || fileNamePrefix.length === 0) {\n      fileNamePrefix = DEFAULT_FILE_NAME_PREFIX;\n    }\n    this.modelJsonFileName = fileNamePrefix + DEFAULT_JSON_EXTENSION_NAME;\n    this.weightDataFileName = fileNamePrefix + DEFAULT_WEIGHT_DATA_EXTENSION_NAME;\n  }\n  async save(modelArtifacts) {\n    if (typeof document === \"undefined\") {\n      throw new Error(\"Browser downloads are not supported in this environment since `document` is not present\");\n    }\n    const weightsURL = window.URL.createObjectURL(new Blob([modelArtifacts.weightData], { type: \"application/octet-stream\" }));\n    if (modelArtifacts.modelTopology instanceof ArrayBuffer) {\n      throw new Error(\"BrowserDownloads.save() does not support saving model topology in binary formats yet.\");\n    } else {\n      const weightsManifest = [{\n        paths: [\"./\" + this.weightDataFileName],\n        weights: modelArtifacts.weightSpecs\n      }];\n      const modelJSON = getModelJSONForModelArtifacts(modelArtifacts, weightsManifest);\n      const modelJsonURL = window.URL.createObjectURL(new Blob([JSON.stringify(modelJSON)], { type: \"application/json\" }));\n      const jsonAnchor = this.modelJsonAnchor == null ? document.createElement(\"a\") : this.modelJsonAnchor;\n      jsonAnchor.download = this.modelJsonFileName;\n      jsonAnchor.href = modelJsonURL;\n      await defer(() => jsonAnchor.dispatchEvent(new MouseEvent(\"click\")));\n      if (modelArtifacts.weightData != null) {\n        const weightDataAnchor = this.weightDataAnchor == null ? document.createElement(\"a\") : this.weightDataAnchor;\n        weightDataAnchor.download = this.weightDataFileName;\n        weightDataAnchor.href = weightsURL;\n        await defer(() => weightDataAnchor.dispatchEvent(new MouseEvent(\"click\")));\n      }\n      return { modelArtifactsInfo: getModelArtifactsInfoForJSON(modelArtifacts) };\n    }\n  }\n};\nBrowserDownloads.URL_SCHEME = \"downloads://\";\nvar BrowserFiles = class {\n  constructor(files) {\n    if (files == null || files.length < 1) {\n      throw new Error(`When calling browserFiles, at least 1 file is required, but received ${files}`);\n    }\n    this.jsonFile = files[0];\n    this.weightsFiles = files.slice(1);\n  }\n  async load() {\n    return new Promise((resolve, reject) => {\n      const jsonReader = new FileReader();\n      jsonReader.onload = (event) => {\n        const modelJSON = JSON.parse(event.target.result);\n        const modelTopology = modelJSON.modelTopology;\n        if (modelTopology == null) {\n          reject(new Error(`modelTopology field is missing from file ${this.jsonFile.name}`));\n          return;\n        }\n        const weightsManifest = modelJSON.weightsManifest;\n        if (weightsManifest == null) {\n          reject(new Error(`weightManifest field is missing from file ${this.jsonFile.name}`));\n          return;\n        }\n        if (this.weightsFiles.length === 0) {\n          resolve({ modelTopology });\n          return;\n        }\n        const modelArtifactsPromise = getModelArtifactsForJSON(modelJSON, (weightsManifest2) => this.loadWeights(weightsManifest2));\n        resolve(modelArtifactsPromise);\n      };\n      jsonReader.onerror = (error) => reject(`Failed to read model topology and weights manifest JSON from file '${this.jsonFile.name}'. BrowserFiles supports loading Keras-style tf.Model artifacts only.`);\n      jsonReader.readAsText(this.jsonFile);\n    });\n  }\n  loadWeights(weightsManifest) {\n    const weightSpecs = [];\n    const paths = [];\n    for (const entry of weightsManifest) {\n      weightSpecs.push(...entry.weights);\n      paths.push(...entry.paths);\n    }\n    const pathToFile = this.checkManifestAndWeightFiles(weightsManifest);\n    const promises = paths.map((path) => this.loadWeightsFile(path, pathToFile[path]));\n    return Promise.all(promises).then((buffers) => [weightSpecs, concatenateArrayBuffers(buffers)]);\n  }\n  loadWeightsFile(path, file) {\n    return new Promise((resolve, reject) => {\n      const weightFileReader = new FileReader();\n      weightFileReader.onload = (event) => {\n        const weightData = event.target.result;\n        resolve(weightData);\n      };\n      weightFileReader.onerror = (error) => reject(`Failed to weights data from file of path '${path}'.`);\n      weightFileReader.readAsArrayBuffer(file);\n    });\n  }\n  checkManifestAndWeightFiles(manifest) {\n    const basenames = [];\n    const fileNames = this.weightsFiles.map((file) => basename(file.name));\n    const pathToFile = {};\n    for (const group of manifest) {\n      group.paths.forEach((path) => {\n        const pathBasename = basename(path);\n        if (basenames.indexOf(pathBasename) !== -1) {\n          throw new Error(`Duplicate file basename found in weights manifest: '${pathBasename}'`);\n        }\n        basenames.push(pathBasename);\n        if (fileNames.indexOf(pathBasename) === -1) {\n          throw new Error(`Weight file with basename '${pathBasename}' is not provided.`);\n        } else {\n          pathToFile[path] = this.weightsFiles[fileNames.indexOf(pathBasename)];\n        }\n      });\n    }\n    if (basenames.length !== this.weightsFiles.length) {\n      throw new Error(`Mismatch in the number of files in weights manifest (${basenames.length}) and the number of weight files provided (${this.weightsFiles.length}).`);\n    }\n    return pathToFile;\n  }\n};\nvar browserDownloadsRouter = (url) => {\n  if (!env().getBool(\"IS_BROWSER\")) {\n    return null;\n  } else {\n    if (!Array.isArray(url) && url.startsWith(BrowserDownloads.URL_SCHEME)) {\n      return browserDownloads(url.slice(BrowserDownloads.URL_SCHEME.length));\n    } else {\n      return null;\n    }\n  }\n};\nIORouterRegistry.registerSaveRouter(browserDownloadsRouter);\nfunction browserDownloads(fileNamePrefix = \"model\") {\n  return new BrowserDownloads(fileNamePrefix);\n}\nfunction browserFiles(files) {\n  return new BrowserFiles(files);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/progress.js\nfunction monitorPromisesProgress(promises, onProgress, startFraction, endFraction) {\n  checkPromises(promises);\n  startFraction = startFraction == null ? 0 : startFraction;\n  endFraction = endFraction == null ? 1 : endFraction;\n  checkFraction(startFraction, endFraction);\n  let resolvedPromise = 0;\n  const registerMonitor = (promise) => {\n    promise.then((value) => {\n      const fraction = startFraction + ++resolvedPromise / promises.length * (endFraction - startFraction);\n      onProgress(fraction);\n      return value;\n    });\n    return promise;\n  };\n  function checkPromises(promises2) {\n    assert(promises2 != null && Array.isArray(promises2) && promises2.length > 0, () => \"promises must be a none empty array\");\n  }\n  function checkFraction(startFraction2, endFraction2) {\n    assert(startFraction2 >= 0 && startFraction2 <= 1, () => `Progress fraction must be in range [0, 1], but got startFraction ${startFraction2}`);\n    assert(endFraction2 >= 0 && endFraction2 <= 1, () => `Progress fraction must be in range [0, 1], but got endFraction ${endFraction2}`);\n    assert(endFraction2 >= startFraction2, () => `startFraction must be no more than endFraction, but got startFraction ${startFraction2} and endFraction ${endFraction2}`);\n  }\n  return Promise.all(promises.map(registerMonitor));\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/weights_loader.js\nasync function loadWeightsAsArrayBuffer(fetchURLs, loadOptions) {\n  if (loadOptions == null) {\n    loadOptions = {};\n  }\n  const fetchFunc = loadOptions.fetchFunc == null ? env().platform.fetch : loadOptions.fetchFunc;\n  const requests = fetchURLs.map((fetchURL) => fetchFunc(fetchURL, loadOptions.requestInit, { isBinary: true }));\n  const fetchStartFraction = 0;\n  const fetchEndFraction = 0.5;\n  const responses = loadOptions.onProgress == null ? await Promise.all(requests) : await monitorPromisesProgress(requests, loadOptions.onProgress, fetchStartFraction, fetchEndFraction);\n  const bufferPromises = responses.map((response) => response.arrayBuffer());\n  const bufferStartFraction = 0.5;\n  const bufferEndFraction = 1;\n  const buffers = loadOptions.onProgress == null ? await Promise.all(bufferPromises) : await monitorPromisesProgress(bufferPromises, loadOptions.onProgress, bufferStartFraction, bufferEndFraction);\n  return buffers;\n}\nasync function loadWeights(manifest, filePathPrefix = \"\", weightNames, requestInit) {\n  const fetchWeights = (fetchUrls) => loadWeightsAsArrayBuffer(fetchUrls, { requestInit });\n  const loadWeights2 = weightsLoaderFactory(fetchWeights);\n  return loadWeights2(manifest, filePathPrefix, weightNames);\n}\nfunction weightsLoaderFactory(fetchWeightsFunction) {\n  return async (manifest, filePathPrefix = \"\", weightNames) => {\n    const groupIndicesToFetchMap = manifest.map(() => false);\n    const groupWeightsToFetch = {};\n    const weightsFound = weightNames != null ? weightNames.map(() => false) : [];\n    const allManifestWeightNames = [];\n    manifest.forEach((manifestGroupConfig, groupIndex) => {\n      let groupOffset = 0;\n      manifestGroupConfig.weights.forEach((weightsEntry) => {\n        const rawDtype = \"quantization\" in weightsEntry ? weightsEntry.quantization.dtype : weightsEntry.dtype;\n        const weightsBytes = DTYPE_VALUE_SIZE_MAP[rawDtype] * sizeFromShape(weightsEntry.shape);\n        const enqueueWeightsForFetchingFn = () => {\n          groupIndicesToFetchMap[groupIndex] = true;\n          if (groupWeightsToFetch[groupIndex] == null) {\n            groupWeightsToFetch[groupIndex] = [];\n          }\n          groupWeightsToFetch[groupIndex].push({\n            manifestEntry: weightsEntry,\n            groupOffset,\n            sizeBytes: weightsBytes\n          });\n        };\n        if (weightNames != null) {\n          weightNames.forEach((weightName, weightIndex) => {\n            if (weightName === weightsEntry.name) {\n              enqueueWeightsForFetchingFn();\n              weightsFound[weightIndex] = true;\n            }\n          });\n        } else {\n          enqueueWeightsForFetchingFn();\n        }\n        allManifestWeightNames.push(weightsEntry.name);\n        groupOffset += weightsBytes;\n      });\n    });\n    if (!weightsFound.every((found) => found)) {\n      const weightsNotFound = weightNames.filter((_, i2) => !weightsFound[i2]);\n      throw new Error(`Could not find weights in manifest with names: ${weightsNotFound.join(\", \")}. \nManifest JSON has weights with names: ${allManifestWeightNames.join(\", \")}.`);\n    }\n    const groupIndicesToFetch = groupIndicesToFetchMap.reduce((accumulator, shouldFetch, i2) => {\n      if (shouldFetch) {\n        accumulator.push(i2);\n      }\n      return accumulator;\n    }, []);\n    const fetchUrls = [];\n    groupIndicesToFetch.forEach((i2) => {\n      manifest[i2].paths.forEach((filepath) => {\n        const fetchUrl = filePathPrefix + (!filePathPrefix.endsWith(\"/\") ? \"/\" : \"\") + filepath;\n        fetchUrls.push(fetchUrl);\n      });\n    });\n    const buffers = await fetchWeightsFunction(fetchUrls);\n    const weightsTensorMap = {};\n    let bufferIndexOffset = 0;\n    groupIndicesToFetch.forEach((i2) => {\n      const numBuffers = manifest[i2].paths.length;\n      let groupBytes = 0;\n      for (let i3 = 0; i3 < numBuffers; i3++) {\n        groupBytes += buffers[bufferIndexOffset + i3].byteLength;\n      }\n      const groupBuffer = new ArrayBuffer(groupBytes);\n      const groupByteBuffer = new Uint8Array(groupBuffer);\n      let groupBufferOffset = 0;\n      for (let i3 = 0; i3 < numBuffers; i3++) {\n        const buffer2 = new Uint8Array(buffers[bufferIndexOffset + i3]);\n        groupByteBuffer.set(buffer2, groupBufferOffset);\n        groupBufferOffset += buffer2.byteLength;\n      }\n      const weightsEntries = groupWeightsToFetch[i2];\n      weightsEntries.forEach((weightsEntry) => {\n        const byteBuffer = groupBuffer.slice(weightsEntry.groupOffset, weightsEntry.groupOffset + weightsEntry.sizeBytes);\n        const nameToTensorMap = decodeWeights(byteBuffer, [weightsEntry.manifestEntry]);\n        for (const name in nameToTensorMap) {\n          weightsTensorMap[name] = nameToTensorMap[name];\n        }\n      });\n      bufferIndexOffset += numBuffers;\n    });\n    return weightsTensorMap;\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/http.js\nvar OCTET_STREAM_MIME_TYPE = \"application/octet-stream\";\nvar JSON_TYPE = \"application/json\";\nvar HTTPRequest = class {\n  constructor(path, loadOptions) {\n    this.DEFAULT_METHOD = \"POST\";\n    if (loadOptions == null) {\n      loadOptions = {};\n    }\n    this.weightPathPrefix = loadOptions.weightPathPrefix;\n    this.onProgress = loadOptions.onProgress;\n    this.weightUrlConverter = loadOptions.weightUrlConverter;\n    if (loadOptions.fetchFunc != null) {\n      assert(typeof loadOptions.fetchFunc === \"function\", () => \"Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)\");\n      this.fetch = loadOptions.fetchFunc;\n    } else {\n      this.fetch = env().platform.fetch;\n    }\n    assert(path != null && path.length > 0, () => \"URL path for http must not be null, undefined or empty.\");\n    if (Array.isArray(path)) {\n      assert(path.length === 2, () => `URL paths for http must have a length of 2, (actual length is ${path.length}).`);\n    }\n    this.path = path;\n    if (loadOptions.requestInit != null && loadOptions.requestInit.body != null) {\n      throw new Error(\"requestInit is expected to have no pre-existing body, but has one.\");\n    }\n    this.requestInit = loadOptions.requestInit || {};\n  }\n  async save(modelArtifacts) {\n    if (modelArtifacts.modelTopology instanceof ArrayBuffer) {\n      throw new Error(\"BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.\");\n    }\n    const init2 = Object.assign({ method: this.DEFAULT_METHOD }, this.requestInit);\n    init2.body = new FormData();\n    const weightsManifest = [{\n      paths: [\"./model.weights.bin\"],\n      weights: modelArtifacts.weightSpecs\n    }];\n    const modelTopologyAndWeightManifest = getModelJSONForModelArtifacts(modelArtifacts, weightsManifest);\n    init2.body.append(\"model.json\", new Blob([JSON.stringify(modelTopologyAndWeightManifest)], { type: JSON_TYPE }), \"model.json\");\n    if (modelArtifacts.weightData != null) {\n      init2.body.append(\"model.weights.bin\", new Blob([modelArtifacts.weightData], { type: OCTET_STREAM_MIME_TYPE }), \"model.weights.bin\");\n    }\n    const response = await this.fetch(this.path, init2);\n    if (response.ok) {\n      return {\n        modelArtifactsInfo: getModelArtifactsInfoForJSON(modelArtifacts),\n        responses: [response]\n      };\n    } else {\n      throw new Error(`BrowserHTTPRequest.save() failed due to HTTP response status ${response.status}.`);\n    }\n  }\n  async load() {\n    const modelConfigRequest = await this.fetch(this.path, this.requestInit);\n    if (!modelConfigRequest.ok) {\n      throw new Error(`Request to ${this.path} failed with status code ${modelConfigRequest.status}. Please verify this URL points to the model JSON of the model to load.`);\n    }\n    let modelJSON;\n    try {\n      modelJSON = await modelConfigRequest.json();\n    } catch (e2) {\n      let message = `Failed to parse model JSON of response from ${this.path}.`;\n      if (this.path.endsWith(\".pb\")) {\n        message += \" Your path contains a .pb file extension. Support for .pb models have been removed in TensorFlow.js 1.0 in favor of .json models. You can re-convert your Python TensorFlow model using the TensorFlow.js 1.0 conversion scripts or you can convert your.pb models with the 'pb2json'NPM script in the tensorflow/tfjs-converter repository.\";\n      } else {\n        message += \" Please make sure the server is serving valid JSON for this request.\";\n      }\n      throw new Error(message);\n    }\n    const modelTopology = modelJSON.modelTopology;\n    const weightsManifest = modelJSON.weightsManifest;\n    if (modelTopology == null && weightsManifest == null) {\n      throw new Error(`The JSON from HTTP path ${this.path} contains neither model topology or manifest for weights.`);\n    }\n    return getModelArtifactsForJSON(modelJSON, (weightsManifest2) => this.loadWeights(weightsManifest2));\n  }\n  async loadWeights(weightsManifest) {\n    const weightPath = Array.isArray(this.path) ? this.path[1] : this.path;\n    const [prefix, suffix] = parseUrl(weightPath);\n    const pathPrefix = this.weightPathPrefix || prefix;\n    const weightSpecs = [];\n    for (const entry of weightsManifest) {\n      weightSpecs.push(...entry.weights);\n    }\n    const fetchURLs = [];\n    const urlPromises = [];\n    for (const weightsGroup of weightsManifest) {\n      for (const path of weightsGroup.paths) {\n        if (this.weightUrlConverter != null) {\n          urlPromises.push(this.weightUrlConverter(path));\n        } else {\n          fetchURLs.push(pathPrefix + path + suffix);\n        }\n      }\n    }\n    if (this.weightUrlConverter) {\n      fetchURLs.push(...await Promise.all(urlPromises));\n    }\n    const buffers = await loadWeightsAsArrayBuffer(fetchURLs, {\n      requestInit: this.requestInit,\n      fetchFunc: this.fetch,\n      onProgress: this.onProgress\n    });\n    return [weightSpecs, concatenateArrayBuffers(buffers)];\n  }\n};\nHTTPRequest.URL_SCHEME_REGEX = /^https?:\\/\\//;\nfunction parseUrl(url) {\n  const lastSlash = url.lastIndexOf(\"/\");\n  const lastSearchParam = url.lastIndexOf(\"?\");\n  const prefix = url.substring(0, lastSlash);\n  const suffix = lastSearchParam > lastSlash ? url.substring(lastSearchParam) : \"\";\n  return [prefix + \"/\", suffix];\n}\nfunction isHTTPScheme(url) {\n  return url.match(HTTPRequest.URL_SCHEME_REGEX) != null;\n}\nvar httpRouter = (url, loadOptions) => {\n  if (typeof fetch === \"undefined\" && (loadOptions == null || loadOptions.fetchFunc == null)) {\n    return null;\n  } else {\n    let isHTTP = true;\n    if (Array.isArray(url)) {\n      isHTTP = url.every((urlItem) => isHTTPScheme(urlItem));\n    } else {\n      isHTTP = isHTTPScheme(url);\n    }\n    if (isHTTP) {\n      return http(url, loadOptions);\n    }\n  }\n  return null;\n};\nIORouterRegistry.registerSaveRouter(httpRouter);\nIORouterRegistry.registerLoadRouter(httpRouter);\nfunction http(path, loadOptions) {\n  return new HTTPRequest(path, loadOptions);\n}\nfunction browserHTTPRequest(path, loadOptions) {\n  return http(path, loadOptions);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/passthrough.js\nvar PassthroughLoader = class {\n  constructor(modelArtifacts) {\n    this.modelArtifacts = modelArtifacts;\n  }\n  load() {\n    return this.modelArtifacts;\n  }\n};\nvar PassthroughSaver = class {\n  constructor(saveHandler) {\n    this.saveHandler = saveHandler;\n  }\n  save(modelArtifacts) {\n    return this.saveHandler(modelArtifacts);\n  }\n};\nvar PassthroughAsync = class {\n  constructor(handler) {\n    if (handler.load) {\n      this.load = () => Promise.resolve(handler.load());\n    }\n    if (handler.save) {\n      this.save = (modelArtifacts) => Promise.resolve(handler.save(modelArtifacts));\n    }\n  }\n};\nfunction fromMemory(modelArtifacts, weightSpecs, weightData, trainingConfig) {\n  const args = arguments;\n  return new PassthroughAsync(fromMemorySync(...args));\n}\nfunction fromMemorySync(modelArtifacts, weightSpecs, weightData, trainingConfig) {\n  if (arguments.length === 1) {\n    const isModelArtifacts = modelArtifacts.modelTopology != null || modelArtifacts.weightSpecs != null;\n    if (isModelArtifacts) {\n      return new PassthroughLoader(modelArtifacts);\n    } else {\n      console.warn(\"Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release.\");\n      return new PassthroughLoader({ modelTopology: modelArtifacts });\n    }\n  } else {\n    console.warn(\"Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release.\");\n    return new PassthroughLoader({\n      modelTopology: modelArtifacts,\n      weightSpecs,\n      weightData,\n      trainingConfig\n    });\n  }\n}\nfunction withSaveHandler(saveHandler) {\n  return new PassthroughSaver(saveHandler);\n}\nfunction withSaveHandlerSync(saveHandler) {\n  return new PassthroughSaver(saveHandler);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/math.js\nvar math_exports = {};\n__export(math_exports, {\n  confusionMatrix: () => confusionMatrix\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/mat_mul.js\nfunction matMul_(a, b, transposeA = false, transposeB = false) {\n  let $a = convertToTensor(a, \"a\", \"matMul\");\n  let $b = convertToTensor(b, \"b\", \"matMul\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const inputs = { a: $a, b: $b };\n  const attrs = { transposeA, transposeB };\n  return ENGINE.runKernel(BatchMatMul, inputs, attrs);\n}\nvar matMul = op({ matMul_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/one_hot.js\nfunction oneHot_(indices, depth, onValue = 1, offValue = 0) {\n  if (depth < 2) {\n    throw new Error(`Error in oneHot: depth must be >=2, but it is ${depth}`);\n  }\n  const $indices = convertToTensor(indices, \"indices\", \"oneHot\", \"int32\");\n  const inputs = { indices: $indices };\n  const attrs = { depth, onValue, offValue };\n  return ENGINE.runKernel(OneHot, inputs, attrs);\n}\nvar oneHot = op({ oneHot_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/globals.js\nfunction enableProdMode() {\n  env().set(\"PROD\", true);\n}\nfunction enableDebugMode() {\n  env().set(\"DEBUG\", true);\n}\nfunction disableDeprecationWarnings() {\n  env().set(\"DEPRECATION_WARNINGS_ENABLED\", false);\n  console.warn(`TensorFlow.js deprecation warnings have been disabled.`);\n}\nfunction deprecationWarn(msg) {\n  if (env().getBool(\"DEPRECATION_WARNINGS_ENABLED\")) {\n    console.warn(msg + \" You can disable deprecation warnings with tf.disableDeprecationWarnings().\");\n  }\n}\nsetDeprecationWarningFn(deprecationWarn);\nfunction disposeVariables() {\n  ENGINE.disposeVariables();\n}\nfunction engine() {\n  return ENGINE;\n}\nfunction memory() {\n  return ENGINE.memory();\n}\nfunction profile(f) {\n  return ENGINE.profile(f);\n}\nfunction tidy(nameOrFn, fn) {\n  return ENGINE.tidy(nameOrFn, fn);\n}\nfunction dispose(container) {\n  const tensors = getTensorsInContainer(container);\n  tensors.forEach((tensor2) => tensor2.dispose());\n}\nfunction keep(result) {\n  return ENGINE.keep(result);\n}\nfunction time(f) {\n  return ENGINE.time(f);\n}\nfunction setBackend(backendName) {\n  return ENGINE.setBackend(backendName);\n}\nfunction ready() {\n  return ENGINE.ready();\n}\nfunction getBackend() {\n  return ENGINE.backendName;\n}\nfunction removeBackend(name) {\n  ENGINE.removeBackend(name);\n}\nfunction findBackend(name) {\n  return ENGINE.findBackend(name);\n}\nfunction findBackendFactory(name) {\n  return ENGINE.findBackendFactory(name);\n}\nfunction registerBackend(name, factory, priority = 1) {\n  return ENGINE.registerBackend(name, factory, priority);\n}\nfunction backend() {\n  return ENGINE.backend;\n}\nfunction setPlatform(platformName, platform) {\n  env().setPlatform(platformName, platform);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/imag.js\nfunction imag_(input2) {\n  const $input = convertToTensor(input2, \"input\", \"imag\");\n  const inputs = { input: $input };\n  return ENGINE.runKernel(Imag, inputs);\n}\nvar imag = op({ imag_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/neg.js\nfunction neg_(x) {\n  const $x = convertToTensor(x, \"x\", \"neg\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Neg, inputs);\n}\nvar neg = op({ neg_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/real.js\nfunction real_(input2) {\n  const $input = convertToTensor(input2, \"input\", \"real\");\n  const inputs = { input: $input };\n  return ENGINE.runKernel(Real, inputs);\n}\nvar real = op({ real_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/transpose.js\nfunction transpose_(x, perm, conjugate) {\n  const $x = convertToTensor(x, \"x\", \"transpose\");\n  if (perm == null) {\n    perm = $x.shape.map((s2, i2) => i2).reverse();\n  }\n  assert($x.rank === perm.length, () => `Error in transpose: rank of input ${$x.rank} must match length of perm ${perm}.`);\n  perm.forEach((axis) => {\n    assert(axis >= 0 && axis < $x.rank, () => `All entries in 'perm' must be between 0 and ${$x.rank - 1} but got ${perm}`);\n  });\n  if ($x.rank <= 1) {\n    return $x.clone();\n  }\n  const inputs = { x: $x };\n  const attrs = { perm };\n  if ($x.dtype === \"complex64\") {\n    return tidy(() => {\n      let $real = real($x);\n      let $imag = imag($x);\n      $real = ENGINE.runKernel(Transpose, { x: $real }, attrs);\n      $imag = ENGINE.runKernel(Transpose, { x: $imag }, attrs);\n      if (conjugate) {\n        $imag = neg($imag);\n      }\n      return complex($real, $imag);\n    });\n  }\n  return ENGINE.runKernel(Transpose, inputs, attrs);\n}\nvar transpose = op({ transpose_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/confusion_matrix.js\nfunction confusionMatrix_(labels, predictions, numClasses) {\n  const $labels = convertToTensor(labels, \"labels\", \"confusionMatrix\");\n  const $predictions = convertToTensor(predictions, \"predictions\", \"confusionMatrix\");\n  assert(numClasses == null || numClasses > 0 && Number.isInteger(numClasses), () => `If provided, numClasses must be a positive integer, but got ${numClasses}`);\n  assert($labels.rank === 1, () => `Expected the rank of labels to be 1, but got ${$labels.rank}`);\n  assert($predictions.rank === 1, () => `Expected the rank of predictions to be 1, but got ${$predictions.rank}`);\n  assert($labels.shape[0] === $predictions.shape[0], () => `Mismatch in the number of examples: ${$labels.shape[0]} vs. ${$predictions.shape[0]}. Labels and predictions should have the same number of elements.`);\n  assert(numClasses > 0 && Number.isInteger(numClasses), () => `numClasses is required to be a positive integer, but got ${numClasses}`);\n  const oneHotLabels = oneHot(cast($labels, \"int32\"), numClasses);\n  const oneHotPredictions = oneHot(cast($predictions, \"int32\"), numClasses);\n  const oneHotLabelsT = transpose(oneHotLabels);\n  const product = matMul(oneHotLabelsT, oneHotPredictions);\n  return cast(product, \"int32\");\n}\nvar confusionMatrix = op({ confusionMatrix_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/broadcast_util.js\nvar broadcast_util_exports = {};\n__export(broadcast_util_exports, {\n  assertAndGetBroadcastShape: () => assertAndGetBroadcastShape,\n  getBroadcastDims: () => getBroadcastDims,\n  getReductionAxes: () => getReductionAxes\n});\nfunction getBroadcastDims(inShape, outShape) {\n  const inRank = inShape.length;\n  const dims = [];\n  for (let i2 = 0; i2 < inRank; i2++) {\n    const dim = inRank - 1 - i2;\n    const a = inShape[dim] || 1;\n    const b = outShape[outShape.length - 1 - i2] || 1;\n    if (b > 1 && a === 1) {\n      dims.unshift(dim);\n    }\n  }\n  return dims;\n}\nfunction getReductionAxes(inShape, outShape) {\n  const result = [];\n  for (let i2 = 0; i2 < outShape.length; i2++) {\n    const inDim = inShape[inShape.length - i2 - 1];\n    const outAxis = outShape.length - i2 - 1;\n    const outDim = outShape[outAxis];\n    if (inDim == null || inDim === 1 && outDim > 1) {\n      result.unshift(outAxis);\n    }\n  }\n  return result;\n}\nfunction assertAndGetBroadcastShape(shapeA, shapeB) {\n  const result = [];\n  const l3 = Math.max(shapeA.length, shapeB.length);\n  for (let i2 = 0; i2 < l3; i2++) {\n    let a = shapeA[shapeA.length - i2 - 1];\n    if (a == null) {\n      a = 1;\n    }\n    let b = shapeB[shapeB.length - i2 - 1];\n    if (b == null) {\n      b = 1;\n    }\n    if (a === 1) {\n      result.unshift(b);\n    } else if (b === 1) {\n      result.unshift(a);\n    } else if (a !== b) {\n      const errMsg = `Operands could not be broadcast together with shapes ${shapeA} and ${shapeB}.`;\n      throw Error(errMsg);\n    } else {\n      result.unshift(a);\n    }\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/browser.js\nvar browser_exports = {};\n__export(browser_exports, {\n  fromPixels: () => fromPixels,\n  fromPixelsAsync: () => fromPixelsAsync,\n  toPixels: () => toPixels\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor3d.js\nfunction tensor3d(values, shape, dtype) {\n  assertNonNull(values);\n  if (shape != null && shape.length !== 3) {\n    throw new Error(\"tensor3d() requires shape to have three numbers\");\n  }\n  const inferredShape = inferShape(values, dtype);\n  if (inferredShape.length !== 3 && inferredShape.length !== 1) {\n    throw new Error(\"tensor3d() requires values to be number[][][] or flat/TypedArray\");\n  }\n  if (inferredShape.length === 1 && shape == null) {\n    throw new Error(\"tensor3d() requires shape to be provided when `values` are a flat array\");\n  }\n  return makeTensor(values, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/browser.js\nvar fromPixels2DContext;\nfunction fromPixels_(pixels, numChannels = 3) {\n  if (numChannels > 4) {\n    throw new Error(\"Cannot construct Tensor with more than 4 channels from pixels.\");\n  }\n  if (pixels == null) {\n    throw new Error(\"pixels passed to tf.browser.fromPixels() can not be null\");\n  }\n  let isPixelData2 = false;\n  let isImageData = false;\n  let isVideo = false;\n  let isImage = false;\n  let isCanvasLike = false;\n  let isImageBitmap = false;\n  if (pixels.data instanceof Uint8Array) {\n    isPixelData2 = true;\n  } else if (typeof ImageData !== \"undefined\" && pixels instanceof ImageData) {\n    isImageData = true;\n  } else if (typeof HTMLVideoElement !== \"undefined\" && pixels instanceof HTMLVideoElement) {\n    isVideo = true;\n  } else if (typeof HTMLImageElement !== \"undefined\" && pixels instanceof HTMLImageElement) {\n    isImage = true;\n  } else if (pixels.getContext != null) {\n    isCanvasLike = true;\n  } else if (typeof ImageBitmap !== \"undefined\" && pixels instanceof ImageBitmap) {\n    isImageBitmap = true;\n  } else {\n    throw new Error(`pixels passed to tf.browser.fromPixels() must be either an HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData in browser, or OffscreenCanvas, ImageData in webworker or {data: Uint32Array, width: number, height: number}, but was ${pixels.constructor.name}`);\n  }\n  if (isVideo) {\n    const HAVE_CURRENT_DATA_READY_STATE = 2;\n    if (isVideo && pixels.readyState < HAVE_CURRENT_DATA_READY_STATE) {\n      throw new Error(\"The video element has not loaded data yet. Please wait for `loadeddata` event on the <video> element.\");\n    }\n  }\n  const kernel = getKernel(FromPixels, ENGINE.backendName);\n  if (kernel != null) {\n    const inputs = { pixels };\n    const attrs = { numChannels };\n    return ENGINE.runKernel(FromPixels, inputs, attrs);\n  }\n  const [width, height] = isVideo ? [\n    pixels.videoWidth,\n    pixels.videoHeight\n  ] : [pixels.width, pixels.height];\n  let vals;\n  if (isCanvasLike) {\n    vals = pixels.getContext(\"2d\").getImageData(0, 0, width, height).data;\n  } else if (isImageData || isPixelData2) {\n    vals = pixels.data;\n  } else if (isImage || isVideo || isImageBitmap) {\n    if (fromPixels2DContext == null) {\n      if (typeof document === \"undefined\") {\n        if (typeof OffscreenCanvas !== \"undefined\" && typeof OffscreenCanvasRenderingContext2D !== \"undefined\") {\n          fromPixels2DContext = new OffscreenCanvas(1, 1).getContext(\"2d\");\n        } else {\n          throw new Error(\"Cannot parse input in current context. Reason: OffscreenCanvas Context2D rendering is not supported.\");\n        }\n      } else {\n        fromPixels2DContext = document.createElement(\"canvas\").getContext(\"2d\", { willReadFrequently: true });\n      }\n    }\n    fromPixels2DContext.canvas.width = width;\n    fromPixels2DContext.canvas.height = height;\n    fromPixels2DContext.drawImage(pixels, 0, 0, width, height);\n    vals = fromPixels2DContext.getImageData(0, 0, width, height).data;\n  }\n  let values;\n  if (numChannels === 4) {\n    values = new Int32Array(vals);\n  } else {\n    const numPixels = width * height;\n    values = new Int32Array(numPixels * numChannels);\n    for (let i2 = 0; i2 < numPixels; i2++) {\n      for (let channel = 0; channel < numChannels; ++channel) {\n        values[i2 * numChannels + channel] = vals[i2 * 4 + channel];\n      }\n    }\n  }\n  const outShape = [height, width, numChannels];\n  return tensor3d(values, outShape, \"int32\");\n}\nfunction isPixelData(pixels) {\n  return pixels != null && pixels.data instanceof Uint8Array;\n}\nfunction isImageBitmapFullySupported() {\n  return typeof window !== \"undefined\" && typeof ImageBitmap !== \"undefined\" && window.hasOwnProperty(\"createImageBitmap\");\n}\nfunction isNonEmptyPixels(pixels) {\n  return pixels != null && pixels.width !== 0 && pixels.height !== 0;\n}\nfunction canWrapPixelsToImageBitmap(pixels) {\n  return isImageBitmapFullySupported() && !(pixels instanceof ImageBitmap) && isNonEmptyPixels(pixels) && !isPixelData(pixels);\n}\nasync function fromPixelsAsync(pixels, numChannels = 3) {\n  let inputs = null;\n  if (env().getBool(\"WRAP_TO_IMAGEBITMAP\") && canWrapPixelsToImageBitmap(pixels)) {\n    let imageBitmap;\n    try {\n      imageBitmap = await createImageBitmap(pixels, { premultiplyAlpha: \"none\" });\n    } catch (e2) {\n      imageBitmap = null;\n    }\n    if (imageBitmap != null && imageBitmap.width === pixels.width && imageBitmap.height === pixels.height) {\n      inputs = imageBitmap;\n    } else {\n      inputs = pixels;\n    }\n  } else {\n    inputs = pixels;\n  }\n  return fromPixels_(inputs, numChannels);\n}\nasync function toPixels(img, canvas) {\n  let $img = convertToTensor(img, \"img\", \"toPixels\");\n  if (!(img instanceof Tensor)) {\n    const originalImgTensor = $img;\n    $img = cast(originalImgTensor, \"int32\");\n    originalImgTensor.dispose();\n  }\n  if ($img.rank !== 2 && $img.rank !== 3) {\n    throw new Error(`toPixels only supports rank 2 or 3 tensors, got rank ${$img.rank}.`);\n  }\n  const [height, width] = $img.shape.slice(0, 2);\n  const depth = $img.rank === 2 ? 1 : $img.shape[2];\n  if (depth > 4 || depth === 2) {\n    throw new Error(`toPixels only supports depth of size 1, 3 or 4 but got ${depth}`);\n  }\n  if ($img.dtype !== \"float32\" && $img.dtype !== \"int32\") {\n    throw new Error(`Unsupported type for toPixels: ${$img.dtype}. Please use float32 or int32 tensors.`);\n  }\n  const data = await $img.data();\n  const multiplier = $img.dtype === \"float32\" ? 255 : 1;\n  const bytes = new Uint8ClampedArray(width * height * 4);\n  for (let i2 = 0; i2 < height * width; ++i2) {\n    const rgba = [0, 0, 0, 255];\n    for (let d = 0; d < depth; d++) {\n      const value = data[i2 * depth + d];\n      if ($img.dtype === \"float32\") {\n        if (value < 0 || value > 1) {\n          throw new Error(`Tensor values for a float32 Tensor must be in the range [0 - 1] but encountered ${value}.`);\n        }\n      } else if ($img.dtype === \"int32\") {\n        if (value < 0 || value > 255) {\n          throw new Error(`Tensor values for a int32 Tensor must be in the range [0 - 255] but encountered ${value}.`);\n        }\n      }\n      if (depth === 1) {\n        rgba[0] = value * multiplier;\n        rgba[1] = value * multiplier;\n        rgba[2] = value * multiplier;\n      } else {\n        rgba[d] = value * multiplier;\n      }\n    }\n    const j = i2 * 4;\n    bytes[j + 0] = Math.round(rgba[0]);\n    bytes[j + 1] = Math.round(rgba[1]);\n    bytes[j + 2] = Math.round(rgba[2]);\n    bytes[j + 3] = Math.round(rgba[3]);\n  }\n  if (canvas != null) {\n    canvas.width = width;\n    canvas.height = height;\n    const ctx = canvas.getContext(\"2d\");\n    const imageData = new ImageData(bytes, width, height);\n    ctx.putImageData(imageData, 0, 0);\n  }\n  if ($img !== img) {\n    $img.dispose();\n  }\n  return bytes;\n}\nvar fromPixels = op({ fromPixels_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/gather_nd_util.js\nvar gather_nd_util_exports = {};\n__export(gather_nd_util_exports, {\n  prepareAndValidate: () => prepareAndValidate\n});\nfunction prepareAndValidate(tensor2, indices) {\n  const tensorRank = tensor2.shape.length;\n  const indicesRank = indices.shape.length;\n  if (tensorRank < 1) {\n    throw new Error(`tf.gatherND() expects the input to be rank 1 or higher, but the rank was ${tensorRank}.`);\n  }\n  if (indicesRank < 1) {\n    throw new Error(`tf.gatherND() expects the indices to be rank 1 or higher, but the rank was ${indicesRank}.`);\n  }\n  if (indices.dtype !== \"int32\") {\n    throw new Error(`tf.gatherND() expects the indices to be int32 type, but the dtype was ${indices.dtype}.`);\n  }\n  if (indices.shape[indicesRank - 1] > tensorRank) {\n    throw new Error(`index innermost dimension length must be <= tensor rank; saw: ${indices.shape[indicesRank - 1]} vs. ${tensorRank}`);\n  }\n  if (sizeFromShape(tensor2.shape) === 0) {\n    throw new Error(`Requested more than 0 entries, but input is empty. Input shape: ${tensor2.shape}.`);\n  }\n  const indicesShape = indices.shape;\n  const sliceRank = indicesShape[indicesShape.length - 1];\n  let nResult = 1;\n  for (let i2 = 0; i2 < indicesShape.length - 1; ++i2) {\n    nResult *= indicesShape[i2];\n  }\n  const inputShape = tensor2.shape;\n  const resultShape = indicesShape.slice();\n  resultShape.pop();\n  let sliceSize = 1;\n  for (let i2 = sliceRank; i2 < tensorRank; ++i2) {\n    sliceSize *= inputShape[i2];\n    resultShape.push(inputShape[i2]);\n  }\n  const strides = [\n    ...computeStrides(tensor2.shape).map((stride) => stride / sliceSize),\n    1\n  ].slice(0, sliceRank);\n  return [resultShape, nResult, sliceSize, strides];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/scatter_nd_util.js\nvar scatter_nd_util_exports = {};\n__export(scatter_nd_util_exports, {\n  calculateShapes: () => calculateShapes,\n  validateInput: () => validateInput,\n  validateUpdateShape: () => validateUpdateShape\n});\nfunction validateUpdateShape(shape, indices, updates) {\n  const sliceDim = indices.rank > 1 ? indices.shape[indices.rank - 1] : 1;\n  const batchDim = indices.rank > 1 ? indices.rank - 1 : 1;\n  const shapeError = `Must have updates.shape = indices.shape[:batchDim] + shape[sliceDim:], got updates.shape: ${updates.shape}, indices.shape: ${indices.shape}, shape: ${shape}, sliceDim: ${sliceDim}, and batchDim: ${batchDim}.`;\n  if (updates.rank < batchDim) {\n    throw new Error(shapeError + ` update.rank < ${batchDim}. `);\n  }\n  if (shape.length < sliceDim + (updates.rank - batchDim)) {\n    throw new Error(shapeError + ` Output shape length < ${sliceDim + (updates.rank - batchDim)}`);\n  }\n  if (updates.rank !== batchDim + shape.length - sliceDim) {\n    throw new Error(shapeError + ` update.rank != ${batchDim + shape.length - sliceDim}`);\n  }\n  for (let d = 0; d < batchDim; ++d) {\n    if (updates.shape[d] !== indices.shape[d]) {\n      throw new Error(shapeError + ` updates.shape[${d}] (${updates.shape[d]}) != indices.shape[${d}] (${indices.shape[d]}).`);\n    }\n  }\n  for (let d = 0; d < updates.rank - batchDim; ++d) {\n    if (updates.shape[d + batchDim] !== shape[d + sliceDim]) {\n      throw new Error(shapeError + ` updates.shape[${d + batchDim}] (${updates.shape[d + batchDim]}) != shape[${d + batchDim}] (${shape[d + batchDim]})`);\n    }\n  }\n}\nfunction validateInput(updates, indices, shape) {\n  if (indices.rank < 1) {\n    throw new Error(`tf.scatterND() expects the indices to be rank 1 or higher, but the rank was ${indices.rank}.`);\n  }\n  if (updates.rank < 1) {\n    throw new Error(`tf.scatterND() expects the updates to be rank 1 or higher, but the rank was ${updates.rank}.`);\n  }\n  if (indices.dtype !== \"int32\") {\n    throw new Error(`The dtype of 'indices' should be int32, but got dtype: ${indices.dtype}`);\n  }\n  if (shape.length < 1) {\n    throw new Error(`Output rank must be greater or equal to 1, but got shape: ${shape}`);\n  }\n  if (shape.length === 0) {\n    if (indices.size === 0) {\n      throw new Error(`Indices specified for empty output. indices shape: ${indices.shape}`);\n    }\n    if (updates.size === 0) {\n      throw new Error(`Updates specified for empty output. updates shape: ${updates.shape}`);\n    }\n  }\n  validateUpdateShape(shape, indices, updates);\n}\nfunction calculateShapes(updates, indices, shape) {\n  const indicesRank = indices.shape.length;\n  const sliceRank = indicesRank > 1 ? indices.shape[indicesRank - 1] : 1;\n  const totalNd = shape.length;\n  let sliceSize = 1;\n  for (let i2 = sliceRank; i2 < totalNd; ++i2) {\n    sliceSize *= shape[i2];\n  }\n  const safeSliceDim = sliceRank < 1 ? 1 : sliceRank;\n  const numUpdates = sizeFromShape(indices.shape) / safeSliceDim;\n  const strides = [...computeStrides(shape.slice(0, sliceRank)), 1];\n  const outputSize = sizeFromShape(shape);\n  return { sliceRank, numUpdates, sliceSize, strides, outputSize };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/slice_util.js\nvar slice_util_exports = {};\n__export(slice_util_exports, {\n  assertParamsValid: () => assertParamsValid,\n  computeFlatOffset: () => computeFlatOffset,\n  computeOutShape: () => computeOutShape,\n  getNormalizedAxes: () => getNormalizedAxes,\n  isSliceContinous: () => isSliceContinous,\n  maskToAxes: () => maskToAxes,\n  parseSliceParams: () => parseSliceParams,\n  sliceInfo: () => sliceInfo,\n  startForAxis: () => startForAxis,\n  startIndicesWithElidedDims: () => startIndicesWithElidedDims,\n  stopForAxis: () => stopForAxis,\n  stopIndicesWithElidedDims: () => stopIndicesWithElidedDims,\n  stridesForAxis: () => stridesForAxis,\n  stridesWithElidedDims: () => stridesWithElidedDims\n});\nvar NEW_AXIS = -2;\nvar SHRINK_AXIS = -1;\nfunction assertParamsValid(input2, begin, size) {\n  const inputRank = input2.shape.length;\n  assert(inputRank === begin.length, () => `Error in slice${inputRank}D: Length of begin ${begin} must match the rank of the array (${inputRank}).`);\n  assert(inputRank === size.length, () => `Error in slice${inputRank}D: Length of size ${size} must match the rank of the array (${inputRank}).`);\n  for (let i2 = 0; i2 < inputRank; ++i2) {\n    assert(begin[i2] + size[i2] <= input2.shape[i2], () => `Error in slice${inputRank}D: begin[${i2}] + size[${i2}] (${begin[i2] + size[i2]}) would overflow input.shape[${i2}] (${input2.shape[i2]})`);\n  }\n}\nfunction maskToAxes(mask) {\n  const axes = [];\n  let axis = 0;\n  while (mask > 0) {\n    if (mask & 1) {\n      axes.push(axis);\n    }\n    mask /= 2;\n    axis++;\n  }\n  return axes;\n}\nfunction computeOutShape(begin, end, strides) {\n  const size = [];\n  for (let axis = 0; axis < begin.length; axis++) {\n    size[axis] = Math.ceil((end[axis] - begin[axis]) / strides[axis]);\n  }\n  return size;\n}\nfunction stridesWithElidedDims(strides, ellipsisInsertionIndex, numElidedAxes, inputShape) {\n  const newStrides = [...strides];\n  for (let i2 = newStrides.length; i2 < inputShape.length; i2++) {\n    newStrides.push(1);\n  }\n  for (let i2 = 0; i2 < numElidedAxes; i2++) {\n    if (i2 === 0) {\n      newStrides[ellipsisInsertionIndex] = 1;\n    } else {\n      newStrides.splice(ellipsisInsertionIndex, 0, 1);\n      newStrides.pop();\n    }\n  }\n  return newStrides;\n}\nfunction unnormalizeAxis(ellipsisInsertionIndex, numElidedAxes, normalizedAxis) {\n  if (normalizedAxis <= ellipsisInsertionIndex) {\n    return normalizedAxis;\n  }\n  return normalizedAxis - (numElidedAxes - 1);\n}\nfunction getElidedAxes(numElidedAxes, ellipsisInsertionIndex) {\n  const elidedAxes = [];\n  for (let i2 = 0; i2 < numElidedAxes; i2++) {\n    elidedAxes.push(ellipsisInsertionIndex + i2);\n  }\n  return elidedAxes;\n}\nfunction getNormalizedAxes(inputShape, ellipsisAxes, numInterpolatedAxes, begin, end, strides, beginMask, endMask, ellipsisMask) {\n  const inputRank = inputShape.length;\n  let normalizedBegin = new Array(inputRank), normalizedEnd = new Array(inputRank), normalizedStrides = new Array(inputRank);\n  if (ellipsisAxes.length && numInterpolatedAxes > 0) {\n    const fullIndex = ellipsisAxes[0];\n    const numElidedAxes = numInterpolatedAxes + 1;\n    normalizedBegin = startIndicesWithElidedDims(beginMask, fullIndex, numElidedAxes, begin, inputShape);\n    normalizedEnd = stopIndicesWithElidedDims(endMask, fullIndex, numElidedAxes, end, inputShape);\n    normalizedStrides = stridesWithElidedDims(strides, fullIndex, numElidedAxes, inputShape);\n  } else {\n    for (let axis = 0; axis < inputRank; axis++) {\n      normalizedBegin[axis] = startForAxis(beginMask, begin, strides, inputShape, axis, ellipsisMask);\n      normalizedEnd[axis] = stopForAxis(endMask, end, strides, inputShape, axis, ellipsisMask);\n      normalizedStrides[axis] = stridesForAxis(strides, axis, ellipsisMask);\n    }\n  }\n  return {\n    begin: normalizedBegin,\n    end: normalizedEnd,\n    strides: normalizedStrides\n  };\n}\nfunction startIndicesWithElidedDims(beginMask, ellipsisInsertionIndex, numElidedAxes, originalBegin, inputShape) {\n  const newIndices = [...inputShape];\n  const elidedAxes = getElidedAxes(numElidedAxes, ellipsisInsertionIndex);\n  for (let axis = 0; axis < newIndices.length; axis++) {\n    if (elidedAxes.indexOf(axis) > -1) {\n      newIndices[axis] = 0;\n    } else {\n      const originalAxis = unnormalizeAxis(ellipsisInsertionIndex, numElidedAxes, axis);\n      let originalValue = originalBegin[originalAxis];\n      if (beginMask & 1 << originalAxis) {\n        originalValue = 0;\n      }\n      newIndices[axis] = originalValue;\n    }\n  }\n  return newIndices;\n}\nfunction stopIndicesWithElidedDims(endMask, ellipsisInsertionIndex, numElidedAxes, originalEnd, inputShape) {\n  const newIndices = [...inputShape];\n  const elidedAxes = getElidedAxes(numElidedAxes, ellipsisInsertionIndex);\n  for (let axis = 0; axis < newIndices.length; axis++) {\n    if (elidedAxes.indexOf(axis) > -1) {\n      newIndices[axis] = Number.MAX_SAFE_INTEGER;\n    } else {\n      const originalAxis = unnormalizeAxis(ellipsisInsertionIndex, numElidedAxes, axis);\n      let originalValue = originalEnd[originalAxis];\n      if (endMask & 1 << originalAxis) {\n        originalValue = Number.MAX_SAFE_INTEGER;\n      }\n      newIndices[axis] = originalValue;\n    }\n  }\n  for (let i2 = 0; i2 < newIndices.length; i2++) {\n    const axisSize = inputShape[i2];\n    if (newIndices[i2] < 0) {\n      newIndices[i2] += axisSize;\n    }\n    newIndices[i2] = clamp(0, newIndices[i2], inputShape[i2]);\n  }\n  return newIndices;\n}\nfunction stridesForAxis(strides, axis, ellipsisMask) {\n  let stride = strides[axis];\n  if (ellipsisMask & 1 << axis || stride == null) {\n    stride = 1;\n  }\n  return stride;\n}\nfunction startForAxis(beginMask, startIndices, strides, inputShape, axis, ellipsisMask) {\n  let start = startIndices[axis];\n  const stride = strides[axis] || 1;\n  if (beginMask & 1 << axis || ellipsisMask & 1 << axis || start == null) {\n    if (stride > 0) {\n      start = Number.MIN_SAFE_INTEGER;\n    } else {\n      start = Number.MAX_SAFE_INTEGER;\n    }\n  }\n  const axisSize = inputShape[axis];\n  if (start < 0) {\n    start += axisSize;\n  }\n  start = clamp(0, start, axisSize - 1);\n  return start;\n}\nfunction stopForAxis(endMask, stopIndices, strides, inputShape, axis, ellipsisMask) {\n  let stop = stopIndices[axis];\n  const stride = strides[axis] || 1;\n  if (endMask & 1 << axis || ellipsisMask & 1 << axis || stop == null) {\n    if (stride > 0) {\n      stop = Number.MAX_SAFE_INTEGER;\n    } else {\n      stop = Number.MIN_SAFE_INTEGER;\n    }\n  }\n  const axisSize = inputShape[axis];\n  if (stop < 0) {\n    stop += axisSize;\n  }\n  if (stride > 0) {\n    stop = clamp(0, stop, axisSize);\n  } else {\n    stop = clamp(-1, stop, axisSize - 1);\n  }\n  return stop;\n}\nfunction isSliceContinous(shape, begin, size) {\n  let firstNonOneAxis = size.length;\n  for (let i2 = 0; i2 < size.length; i2++) {\n    if (size[i2] > 1) {\n      firstNonOneAxis = i2;\n      break;\n    }\n  }\n  for (let i2 = firstNonOneAxis + 1; i2 < size.length; i2++) {\n    if (begin[i2] > 0 || size[i2] !== shape[i2]) {\n      return false;\n    }\n  }\n  return true;\n}\nfunction computeFlatOffset(begin, strides) {\n  let flatOffset = begin.length > 0 ? begin[begin.length - 1] : 1;\n  for (let i2 = 0; i2 < begin.length - 1; i2++) {\n    flatOffset += begin[i2] * strides[i2];\n  }\n  return flatOffset;\n}\nfunction parseSliceParams(x, begin, size) {\n  let begin_;\n  const xRank = x.shape.length;\n  if (typeof begin === \"number\") {\n    begin_ = [begin, ...new Array(xRank - 1).fill(0)];\n  } else if (begin.length < xRank) {\n    begin_ = begin.concat(new Array(xRank - begin.length).fill(0));\n  } else {\n    begin_ = begin.slice();\n  }\n  begin_.forEach((d) => {\n    assert(d !== -1, () => \"slice() does not support negative begin indexing.\");\n  });\n  let size_;\n  if (size == null) {\n    size_ = new Array(xRank).fill(-1);\n  } else if (typeof size === \"number\") {\n    size_ = [size, ...new Array(xRank - 1).fill(-1)];\n  } else if (size.length < xRank) {\n    size_ = size.concat(new Array(xRank - size.length).fill(-1));\n  } else {\n    size_ = size;\n  }\n  size_ = size_.map((d, i2) => {\n    if (d >= 0) {\n      return d;\n    } else {\n      assert(d === -1, () => `Negative size values should be exactly -1 but got ${d} for the slice() size at index ${i2}.`);\n      return x.shape[i2] - begin_[i2];\n    }\n  });\n  return [begin_, size_];\n}\nfunction sliceInfo(xShape, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask) {\n  let stridesNonNull;\n  if (strides == null) {\n    stridesNonNull = new Array(begin.length);\n    stridesNonNull.fill(1);\n  } else {\n    stridesNonNull = strides;\n  }\n  if (ellipsisMask != null && (ellipsisMask & ellipsisMask - 1) !== 0) {\n    throw new Error(\"Multiple ellipses in slice is not allowed.\");\n  }\n  let ellipsisSeen = false;\n  const sparseSpec = {\n    dims: stridesNonNull.length,\n    numAddAxisAfterEllipsis: 0,\n    begin: begin.slice(),\n    end: end.slice(),\n    strides: stridesNonNull.slice(),\n    beginMask,\n    endMask,\n    ellipsisMask,\n    newAxisMask,\n    shrinkAxisMask\n  };\n  for (let i2 = 0; i2 < sparseSpec.dims; i2++) {\n    if (ellipsisSeen && (1 << i2 & newAxisMask) !== 0) {\n      sparseSpec.numAddAxisAfterEllipsis++;\n    }\n    if (1 << i2 & ellipsisMask) {\n      ellipsisSeen = true;\n    }\n  }\n  if (!ellipsisSeen) {\n    sparseSpec.ellipsisMask |= 1 << sparseSpec.dims;\n    sparseSpec.dims++;\n  }\n  const denseSpec = {\n    dims: xShape.length,\n    beginMask: 0,\n    endMask: 0,\n    beginValid: false,\n    endValid: false\n  };\n  buildDenseSpec(sparseSpec, denseSpec);\n  let isIdentity = true;\n  let sliceDim0 = true;\n  let isSimpleSlice = true;\n  const processingShape = [];\n  const finalShape = [];\n  for (let i2 = 0; i2 < xShape.length; ++i2) {\n    if (denseSpec.strides[i2] === 0) {\n      throw Error(`strides[${i2}] must be non-zero`);\n    }\n    const shrinkI = !!(denseSpec.shrinkAxisMask & 1 << i2);\n    const dimI = xShape[i2];\n    if (dimI === -1) {\n      processingShape.push(shrinkI ? 1 : -1);\n      continue;\n    }\n    const masks = [denseSpec.beginMask & 1 << i2, denseSpec.endMask & 1 << i2];\n    const validRange = [\n      denseSpec.strides[i2] > 0 ? 0 : -1,\n      denseSpec.strides[i2] > 0 ? dimI : dimI - 1\n    ];\n    if (shrinkI && denseSpec.strides[i2] <= 0) {\n      throw Error(\"only stride 1 allowed on non-range indexing.\");\n    }\n    isSimpleSlice = isSimpleSlice && denseSpec.strides[i2] === 1;\n    const beginAndEndMasked = !!(denseSpec.beginMask & 1 << i2 && denseSpec.endMask & 1 << i2);\n    if (denseSpec.beginValid && denseSpec.endValid) {\n      if (shrinkI) {\n        const xFwd = denseSpec.begin[i2] < 0 ? dimI + denseSpec.begin[i2] : denseSpec.begin[i2];\n        denseSpec.begin[i2] = xFwd;\n        denseSpec.end[i2] = denseSpec.begin[i2] + 1;\n        if (xFwd < 0 || xFwd >= dimI) {\n          throw Error(`slice index ${denseSpec.begin[i2]} of dimension ${i2} out of bounds.`);\n        }\n      } else {\n        denseSpec.begin[i2] = canonical(denseSpec.begin[i2], 0, denseSpec.strides[i2], dimI, masks, validRange);\n        denseSpec.end[i2] = canonical(denseSpec.end[i2], 1, denseSpec.strides[i2], dimI, masks, validRange);\n      }\n      const takeAllInDimension = denseSpec.strides[i2] === 1 && denseSpec.begin[i2] === 0 && denseSpec.end[i2] === dimI;\n      isIdentity = isIdentity && takeAllInDimension;\n      sliceDim0 = sliceDim0 && (i2 === 0 && denseSpec.strides[i2] === 1 || takeAllInDimension);\n    } else {\n      isIdentity = isIdentity && (denseSpec.strides[i2] === 1 && beginAndEndMasked);\n      sliceDim0 = sliceDim0 && (i2 === 0 && denseSpec.strides[i2] === 1 || beginAndEndMasked);\n    }\n    let intervalLength;\n    let knownInterval = false;\n    if (denseSpec.beginValid && denseSpec.endValid) {\n      intervalLength = denseSpec.end[i2] - denseSpec.begin[i2];\n      knownInterval = true;\n    } else if (shrinkI) {\n      intervalLength = 1;\n      knownInterval = true;\n    } else if (beginAndEndMasked) {\n      if (dimI >= 0) {\n        if (denseSpec.strides[i2] < 0) {\n          intervalLength = -dimI;\n        } else {\n          intervalLength = dimI;\n        }\n        knownInterval = true;\n      }\n    }\n    if (knownInterval) {\n      let sizeI;\n      if (intervalLength === 0 || intervalLength < 0 !== denseSpec.strides[i2] < 0) {\n        sizeI = 0;\n      } else {\n        sizeI = Math.trunc(intervalLength / denseSpec.strides[i2]) + (intervalLength % denseSpec.strides[i2] !== 0 ? 1 : 0);\n      }\n      processingShape.push(sizeI);\n    } else {\n      processingShape.push(-1);\n    }\n  }\n  for (let denseDim = 0; denseDim < denseSpec.finalShapeGatherIndices.length; ++denseDim) {\n    const gatherIndex = denseSpec.finalShapeGatherIndices[denseDim];\n    if (gatherIndex >= 0) {\n      finalShape.push(processingShape[gatherIndex]);\n    } else if (gatherIndex === NEW_AXIS) {\n      finalShape.push(1);\n    }\n  }\n  const finalShapeSparse = finalShape.filter((dim, i2) => denseSpec.finalShapeGatherIndices[i2] !== NEW_AXIS);\n  return {\n    finalShapeSparse,\n    finalShape,\n    isIdentity,\n    sliceDim0,\n    isSimpleSlice,\n    begin: denseSpec.begin,\n    end: denseSpec.end,\n    strides: denseSpec.strides\n  };\n}\nfunction buildDenseSpec(sparse2, dense2) {\n  dense2.beginMask = 0;\n  dense2.endMask = 0;\n  dense2.shrinkAxisMask = 0;\n  let fullIndex = 0;\n  dense2.beginValid = sparse2.begin != null;\n  dense2.endValid = sparse2.end != null;\n  dense2.begin = new Array(dense2.dims);\n  dense2.end = new Array(dense2.dims);\n  dense2.strides = new Array(dense2.dims);\n  dense2.finalShapeGatherIndices = [];\n  dense2.finalShapeGatherIndicesSparse = [];\n  dense2.inputShapeGatherIndicesSparse = new Array(dense2.dims);\n  for (let i2 = 0; i2 < sparse2.dims; i2++) {\n    if (1 << i2 & sparse2.ellipsisMask) {\n      const nextIndex = Math.min(dense2.dims - (sparse2.dims - i2) + 1 + sparse2.numAddAxisAfterEllipsis, dense2.dims);\n      for (; fullIndex < nextIndex; fullIndex++) {\n        dense2.begin[fullIndex] = 0;\n        dense2.end[fullIndex] = 0;\n        dense2.strides[fullIndex] = 1;\n        dense2.beginMask |= 1 << fullIndex;\n        dense2.endMask |= 1 << fullIndex;\n        dense2.finalShapeGatherIndices.push(fullIndex);\n        dense2.finalShapeGatherIndicesSparse.push(-1);\n        dense2.inputShapeGatherIndicesSparse[fullIndex] = i2;\n      }\n    } else if (1 << i2 & sparse2.newAxisMask) {\n      dense2.finalShapeGatherIndices.push(NEW_AXIS);\n      dense2.finalShapeGatherIndicesSparse.push(-1);\n    } else {\n      if (fullIndex === dense2.begin.length) {\n        throw Error(`Index out of range using input dim ${fullIndex}; input has only ${dense2.dims} dims, ${dense2.begin.length}.`);\n      }\n      if (sparse2.begin != null) {\n        dense2.begin[fullIndex] = sparse2.begin[i2];\n      }\n      if (sparse2.end != null) {\n        dense2.end[fullIndex] = sparse2.end[i2];\n      }\n      dense2.strides[fullIndex] = sparse2.strides[i2];\n      if (sparse2.beginMask & 1 << i2) {\n        dense2.beginMask |= 1 << fullIndex;\n      }\n      if (sparse2.endMask & 1 << i2) {\n        dense2.endMask |= 1 << fullIndex;\n      }\n      if (sparse2.shrinkAxisMask & 1 << i2) {\n        dense2.finalShapeGatherIndices.push(SHRINK_AXIS);\n        dense2.finalShapeGatherIndicesSparse.push(-1);\n        dense2.shrinkAxisMask |= 1 << fullIndex;\n      } else {\n        dense2.finalShapeGatherIndices.push(fullIndex);\n        dense2.finalShapeGatherIndicesSparse.push(i2);\n      }\n      dense2.inputShapeGatherIndicesSparse[fullIndex] = i2;\n      fullIndex++;\n    }\n  }\n}\nfunction canonical(x, c, strideI, dimI, masks, validRange) {\n  if (masks[c]) {\n    return strideI > 0 ? validRange[c] : validRange[c + 1 & 1];\n  } else {\n    const xFwd = x < 0 ? dimI + x : x;\n    return xFwd < validRange[0] ? validRange[0] : xFwd > validRange[1] ? validRange[1] : xFwd;\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/serialization.js\nvar serialization_exports = {};\n__export(serialization_exports, {\n  Serializable: () => Serializable,\n  SerializationMap: () => SerializationMap,\n  registerClass: () => registerClass\n});\nvar Serializable = class {\n  getClassName() {\n    return this.constructor.className;\n  }\n  static fromConfig(cls, config) {\n    return new cls(config);\n  }\n};\nvar SerializationMap = class {\n  constructor() {\n    this.classNameMap = {};\n  }\n  static getMap() {\n    if (SerializationMap.instance == null) {\n      SerializationMap.instance = new SerializationMap();\n    }\n    return SerializationMap.instance;\n  }\n  static register(cls) {\n    SerializationMap.getMap().classNameMap[cls.className] = [cls, cls.fromConfig];\n  }\n};\nfunction registerClass(cls) {\n  assert(cls.className != null, () => `Class being registered does not have the static className property defined.`);\n  assert(typeof cls.className === \"string\", () => `className is required to be a string, but got type ` + typeof cls.className);\n  assert(cls.className.length > 0, () => `Class being registered has an empty-string as its className, which is disallowed.`);\n  SerializationMap.register(cls);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/test_util.js\nvar test_util_exports = {};\n__export(test_util_exports, {\n  TEST_EPSILON_FLOAT16: () => TEST_EPSILON_FLOAT16,\n  encodeStrings: () => encodeStrings,\n  expectArrayBuffersEqual: () => expectArrayBuffersEqual,\n  expectArraysClose: () => expectArraysClose,\n  expectArraysEqual: () => expectArraysEqual,\n  expectNumbersClose: () => expectNumbersClose,\n  expectPromiseToFail: () => expectPromiseToFail,\n  expectValuesInRange: () => expectValuesInRange,\n  testEpsilon: () => testEpsilon\n});\nvar TEST_EPSILON_FLOAT32 = 1e-3;\nvar TEST_EPSILON_FLOAT16 = 0.1;\nfunction expectArraysClose(actual, expected, epsilon3) {\n  if (epsilon3 == null) {\n    epsilon3 = testEpsilon();\n  }\n  return expectArraysPredicate(actual, expected, (a, b) => areClose(a, b, epsilon3));\n}\nfunction testEpsilon() {\n  return ENGINE.backend.floatPrecision() === 32 ? TEST_EPSILON_FLOAT32 : TEST_EPSILON_FLOAT16;\n}\nfunction expectArraysPredicate(actual, expected, predicate) {\n  let checkClassType = true;\n  if (isTypedArray(actual) || isTypedArray(expected)) {\n    checkClassType = false;\n  }\n  if (isTypedArray(actual) && isTypedArray(expected)) {\n    checkClassType = true;\n  }\n  if (checkClassType) {\n    const aType = actual.constructor.name;\n    const bType = expected.constructor.name;\n    if (aType !== bType) {\n      throw new Error(`Arrays are of different type. Actual: ${aType}. Expected: ${bType}`);\n    }\n  }\n  if (Array.isArray(actual) && Array.isArray(expected)) {\n    const actualShape = inferShape(actual);\n    const expectedShape = inferShape(expected);\n    if (!arraysEqual(actualShape, expectedShape)) {\n      throw new Error(`Arrays have different shapes. Actual: [${actualShape}]. Expected: [${expectedShape}]`);\n    }\n  }\n  const actualFlat = isTypedArray(actual) ? actual : flatten(actual);\n  const expectedFlat = isTypedArray(expected) ? expected : flatten(expected);\n  if (actualFlat.length !== expectedFlat.length) {\n    throw new Error(`Arrays have different lengths actual: ${actualFlat.length} vs expected: ${expectedFlat.length}.\nActual:   ${actualFlat}.\nExpected: ${expectedFlat}.`);\n  }\n  for (let i2 = 0; i2 < expectedFlat.length; ++i2) {\n    const a = actualFlat[i2];\n    const e2 = expectedFlat[i2];\n    if (!predicate(a, e2)) {\n      throw new Error(`Arrays differ: actual[${i2}] = ${a}, expected[${i2}] = ${e2}.\nActual:   ${actualFlat}.\nExpected: ${expectedFlat}.`);\n    }\n  }\n}\nfunction expectPromiseToFail(fn, done) {\n  fn().then(() => done.fail(), () => done());\n}\nfunction expectArraysEqual(actual, expected) {\n  const exp5 = typeof expected === \"string\" || typeof expected === \"number\" || typeof expected === \"boolean\" ? [expected] : expected;\n  if (isString(actual) || isString(actual[0]) || isString(expected) || isString(expected[0])) {\n    return expectArraysPredicate(actual, exp5, (a, b) => a == b);\n  }\n  return expectArraysPredicate(actual, expected, (a, b) => areClose(a, b, 0));\n}\nfunction expectNumbersClose(a, e2, epsilon3) {\n  if (epsilon3 == null) {\n    epsilon3 = testEpsilon();\n  }\n  if (!areClose(a, e2, epsilon3)) {\n    throw new Error(`Numbers differ: actual === ${a}, expected === ${e2}`);\n  }\n}\nfunction areClose(a, e2, epsilon3) {\n  if (!isFinite(a) && !isFinite(e2)) {\n    return true;\n  }\n  if (isNaN(a) || isNaN(e2) || Math.abs(a - e2) > epsilon3) {\n    return false;\n  }\n  return true;\n}\nfunction expectValuesInRange(actual, low, high) {\n  for (let i2 = 0; i2 < actual.length; i2++) {\n    if (actual[i2] < low || actual[i2] > high) {\n      throw new Error(`Value out of range:${actual[i2]} low: ${low}, high: ${high}`);\n    }\n  }\n}\nfunction expectArrayBuffersEqual(actual, expected) {\n  const actualArray = new Float32Array(actual);\n  const expectedArray = new Float32Array(expected);\n  if (actualArray.length !== expectedArray.length) {\n    throw new Error(`Expected ArrayBuffer to be of length ${expectedArray.length}, but it was ${actualArray.length}`);\n  }\n  for (let i2 = 0; i2 < expectedArray.length; i2++) {\n    if (actualArray[i2] !== expectedArray[i2]) {\n      throw new Error(`Expected ArrayBuffer value at ${i2} to be ${expectedArray[i2]} but got ${actualArray[i2]} instead`);\n    }\n  }\n}\nfunction encodeStrings(a) {\n  for (let i2 = 0; i2 < a.length; i2++) {\n    const val = a[i2];\n    if (Array.isArray(val)) {\n      encodeStrings(val);\n    } else {\n      a[i2] = encodeString(val);\n    }\n  }\n  return a;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/version.js\nvar version = \"3.19.0\";\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/add.js\nfunction add_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"add\");\n  let $b = convertToTensor(b, \"b\", \"add\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Add, inputs);\n}\nvar add2 = op({ add_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/floorDiv.js\nfunction floorDiv_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"floorDiv\");\n  let $b = convertToTensor(b, \"b\", \"floorDiv\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(FloorDiv, inputs);\n}\nvar floorDiv = op({ floorDiv_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/div.js\nfunction div_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"div\");\n  let $b = convertToTensor(b, \"b\", \"div\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  if ($a.dtype === \"int32\" && $b.dtype === \"int32\") {\n    return floorDiv($a, $b);\n  }\n  const inputs = { a: $a, b: $b };\n  const attrs = {};\n  return ENGINE.runKernel(RealDiv, inputs, attrs);\n}\nvar div = op({ div_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/mul.js\nfunction mul_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"mul\");\n  let $b = convertToTensor(b, \"b\", \"mul\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Multiply, inputs);\n}\nvar mul = op({ mul_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/abs.js\nfunction abs_(x) {\n  const $x = convertToTensor(x, \"x\", \"abs\");\n  if ($x.dtype === \"complex64\") {\n    const inputs = { x: $x };\n    return ENGINE.runKernel(ComplexAbs, inputs);\n  } else {\n    const inputs = { x: $x };\n    return ENGINE.runKernel(Abs, inputs);\n  }\n}\nvar abs = op({ abs_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/acos.js\nfunction acos_(x) {\n  const $x = convertToTensor(x, \"x\", \"acos\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Acos, inputs);\n}\nvar acos = op({ acos_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/acosh.js\nfunction acosh_(x) {\n  const $x = convertToTensor(x, \"x\", \"acosh\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Acosh, inputs);\n}\nvar acosh = op({ acosh_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/add_n.js\nfunction addN_(tensors) {\n  assert(Array.isArray(tensors), () => \"The argument passed to tf.addN() must be a list of tensors\");\n  assert(tensors.length >= 1, () => `Must pass at least one tensor to tf.addN(), but got ${tensors.length}`);\n  const $tensors = tensors.map((t2, i2) => convertToTensor(t2, `tensors${i2}`, \"addN\"));\n  const firstTensor = $tensors[0];\n  $tensors.forEach((t2) => {\n    if (t2.dtype !== firstTensor.dtype) {\n      throw new Error(\"All tensors passed to tf.addN() must have the same dtype\");\n    }\n  });\n  $tensors.forEach((t2) => {\n    if (!arraysEqual(t2.shape, firstTensor.shape)) {\n      throw new Error(\"All tensors passed to tf.addN() must have the same shape\");\n    }\n  });\n  const inputs = $tensors;\n  return ENGINE.runKernel(AddN, inputs);\n}\nvar addN = op({ addN_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/all.js\nfunction all_(x, axis = null, keepDims = false) {\n  const $x = convertToTensor(x, \"x\", \"all\", \"bool\");\n  const inputs = { x: $x };\n  const attrs = { axis, keepDims };\n  return ENGINE.runKernel(All, inputs, attrs);\n}\nvar all = op({ all_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/any.js\nfunction any_(x, axis = null, keepDims = false) {\n  const $x = convertToTensor(x, \"x\", \"any\", \"bool\");\n  const inputs = { x: $x };\n  const attrs = { axis, keepDims };\n  return ENGINE.runKernel(Any, inputs, attrs);\n}\nvar any = op({ any_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/arg_max.js\nfunction argMax_(x, axis = 0) {\n  const $x = convertToTensor(x, \"x\", \"argMax\");\n  const inputs = { x: $x };\n  const attrs = { axis };\n  return ENGINE.runKernel(ArgMax, inputs, attrs);\n}\nvar argMax = op({ argMax_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/arg_min.js\nfunction argMin_(x, axis = 0) {\n  const $x = convertToTensor(x, \"x\", \"argMin\");\n  const inputs = { x: $x };\n  const attrs = { axis };\n  return ENGINE.runKernel(ArgMin, inputs, attrs);\n}\nvar argMin = op({ argMin_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/asin.js\nfunction asin_(x) {\n  const $x = convertToTensor(x, \"x\", \"asin\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Asin, inputs);\n}\nvar asin = op({ asin_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/asinh.js\nfunction asinh_(x) {\n  const $x = convertToTensor(x, \"x\", \"asinh\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Asinh, inputs);\n}\nvar asinh = op({ asinh_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/atan.js\nfunction atan_(x) {\n  const $x = convertToTensor(x, \"x\", \"atan\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Atan, inputs);\n}\nvar atan = op({ atan_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/atan2.js\nfunction atan2_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"atan2\");\n  let $b = convertToTensor(b, \"b\", \"atan2\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Atan2, inputs);\n}\nvar atan2 = op({ atan2_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/atanh.js\nfunction atanh_(x) {\n  const $x = convertToTensor(x, \"x\", \"atanh\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Atanh, inputs);\n}\nvar atanh = op({ atanh_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv_util.js\nfunction computeDilation2DInfo(inputShape, filterShape, strides, pad3, dataFormat = \"NHWC\", dilations) {\n  const inputChannels = inputShape[3];\n  const $filterShape = [...filterShape, inputChannels];\n  const $dataFormat = convertConv2DDataFormat(dataFormat);\n  return computeConv2DInfo(inputShape, $filterShape, strides, dilations, pad3, null, null, $dataFormat);\n}\nfunction computePool2DInfo(inShape, filterSize, strides, dilations, pad3, roundingMode, dataFormat = \"channelsLast\") {\n  const [filterHeight, filterWidth] = parseTupleParam(filterSize);\n  let filterShape;\n  if (dataFormat === \"channelsLast\") {\n    filterShape = [filterHeight, filterWidth, inShape[3], inShape[3]];\n  } else if (dataFormat === \"channelsFirst\") {\n    filterShape = [filterHeight, filterWidth, inShape[1], inShape[1]];\n  } else {\n    throw new Error(`Unknown dataFormat ${dataFormat}`);\n  }\n  return computeConv2DInfo(inShape, filterShape, strides, dilations, pad3, roundingMode, false, dataFormat);\n}\nfunction computePool3DInfo(inShape, filterSize, strides, dilations, pad3, roundingMode, dataFormat = \"NDHWC\") {\n  const [filterDepth, filterHeight, filterWidth] = parse3TupleParam(filterSize);\n  let filterShape;\n  let $dataFormat;\n  if (dataFormat === \"NDHWC\") {\n    $dataFormat = \"channelsLast\";\n    filterShape = [filterDepth, filterHeight, filterWidth, inShape[4], inShape[4]];\n  } else if (dataFormat === \"NCDHW\") {\n    $dataFormat = \"channelsFirst\";\n    filterShape = [filterDepth, filterHeight, filterWidth, inShape[1], inShape[1]];\n  } else {\n    throw new Error(`Unknown dataFormat ${dataFormat}`);\n  }\n  return computeConv3DInfo(inShape, filterShape, strides, dilations, pad3, false, $dataFormat, roundingMode);\n}\nfunction computeConv2DInfo(inShape, filterShape, strides, dilations, pad3, roundingMode, depthwise = false, dataFormat = \"channelsLast\") {\n  let [batchSize, inHeight, inWidth, inChannels] = [-1, -1, -1, -1];\n  if (dataFormat === \"channelsLast\") {\n    [batchSize, inHeight, inWidth, inChannels] = inShape;\n  } else if (dataFormat === \"channelsFirst\") {\n    [batchSize, inChannels, inHeight, inWidth] = inShape;\n  } else {\n    throw new Error(`Unknown dataFormat ${dataFormat}`);\n  }\n  const [filterHeight, filterWidth, , filterChannels] = filterShape;\n  const [strideHeight, strideWidth] = parseTupleParam(strides);\n  const [dilationHeight, dilationWidth] = parseTupleParam(dilations);\n  const effectiveFilterHeight = getEffectiveFilterSize(filterHeight, dilationHeight);\n  const effectiveFilterWidth = getEffectiveFilterSize(filterWidth, dilationWidth);\n  const { padInfo, outHeight, outWidth } = getPadAndOutInfo(pad3, inHeight, inWidth, strideHeight, strideWidth, effectiveFilterHeight, effectiveFilterWidth, roundingMode, dataFormat);\n  const outChannels = depthwise ? filterChannels * inChannels : filterChannels;\n  let outShape;\n  if (dataFormat === \"channelsFirst\") {\n    outShape = [batchSize, outChannels, outHeight, outWidth];\n  } else if (dataFormat === \"channelsLast\") {\n    outShape = [batchSize, outHeight, outWidth, outChannels];\n  }\n  return {\n    batchSize,\n    dataFormat,\n    inHeight,\n    inWidth,\n    inChannels,\n    outHeight,\n    outWidth,\n    outChannels,\n    padInfo,\n    strideHeight,\n    strideWidth,\n    filterHeight,\n    filterWidth,\n    effectiveFilterHeight,\n    effectiveFilterWidth,\n    dilationHeight,\n    dilationWidth,\n    inShape,\n    outShape,\n    filterShape\n  };\n}\nfunction computeConv3DInfo(inShape, filterShape, strides, dilations, pad3, depthwise = false, dataFormat = \"channelsLast\", roundingMode) {\n  let [batchSize, inDepth, inHeight, inWidth, inChannels] = [-1, -1, -1, -1, -1];\n  if (dataFormat === \"channelsLast\") {\n    [batchSize, inDepth, inHeight, inWidth, inChannels] = inShape;\n  } else if (dataFormat === \"channelsFirst\") {\n    [batchSize, inChannels, inDepth, inHeight, inWidth] = inShape;\n  } else {\n    throw new Error(`Unknown dataFormat ${dataFormat}`);\n  }\n  const [filterDepth, filterHeight, filterWidth, , filterChannels] = filterShape;\n  const [strideDepth, strideHeight, strideWidth] = parse3TupleParam(strides);\n  const [dilationDepth, dilationHeight, dilationWidth] = parse3TupleParam(dilations);\n  const effectiveFilterDepth = getEffectiveFilterSize(filterDepth, dilationDepth);\n  const effectiveFilterHeight = getEffectiveFilterSize(filterHeight, dilationHeight);\n  const effectiveFilterWidth = getEffectiveFilterSize(filterWidth, dilationWidth);\n  const { padInfo, outDepth, outHeight, outWidth } = get3DPadAndOutInfo(pad3, inDepth, inHeight, inWidth, strideDepth, strideHeight, strideWidth, effectiveFilterDepth, effectiveFilterHeight, effectiveFilterWidth, roundingMode);\n  const outChannels = depthwise ? filterChannels * inChannels : filterChannels;\n  let outShape;\n  if (dataFormat === \"channelsFirst\") {\n    outShape = [batchSize, outChannels, outDepth, outHeight, outWidth];\n  } else if (dataFormat === \"channelsLast\") {\n    outShape = [batchSize, outDepth, outHeight, outWidth, outChannels];\n  }\n  return {\n    batchSize,\n    dataFormat,\n    inDepth,\n    inHeight,\n    inWidth,\n    inChannels,\n    outDepth,\n    outHeight,\n    outWidth,\n    outChannels,\n    padInfo,\n    strideDepth,\n    strideHeight,\n    strideWidth,\n    filterDepth,\n    filterHeight,\n    filterWidth,\n    effectiveFilterDepth,\n    effectiveFilterHeight,\n    effectiveFilterWidth,\n    dilationDepth,\n    dilationHeight,\n    dilationWidth,\n    inShape,\n    outShape,\n    filterShape\n  };\n}\nfunction computeOutputShape2D(inShape, fieldSize, stride, zeroPad, roundingMode) {\n  if (zeroPad == null) {\n    zeroPad = computeDefaultPad(inShape, fieldSize, stride);\n  }\n  const inputRows = inShape[0];\n  const inputCols = inShape[1];\n  const outputRows = round((inputRows - fieldSize + 2 * zeroPad) / stride + 1, roundingMode);\n  const outputCols = round((inputCols - fieldSize + 2 * zeroPad) / stride + 1, roundingMode);\n  return [outputRows, outputCols];\n}\nfunction computeOutputShape4D(inShape, fieldSize, outChannels, stride, zeroPad, roundingMode) {\n  if (zeroPad == null) {\n    zeroPad = computeDefaultPad(inShape, fieldSize, stride);\n  }\n  const inputDepth = inShape[0];\n  const inputRows = inShape[1];\n  const inputCols = inShape[2];\n  const outputDepths = round((inputDepth - fieldSize + 2 * zeroPad) / stride + 1, roundingMode);\n  const outputRows = round((inputRows - fieldSize + 2 * zeroPad) / stride + 1, roundingMode);\n  const outputCols = round((inputCols - fieldSize + 2 * zeroPad) / stride + 1, roundingMode);\n  return [outputDepths, outputRows, outputCols, outChannels];\n}\nfunction computeDefaultPad(inputShape, fieldSize, stride, dilation = 1) {\n  const effectiveFieldSize = getEffectiveFilterSize(fieldSize, dilation);\n  return Math.floor((inputShape[0] * (stride - 1) - stride + effectiveFieldSize) / 2);\n}\nfunction parseTupleParam(param) {\n  if (typeof param === \"number\") {\n    return [param, param, param];\n  }\n  if (param.length === 2) {\n    return [param[0], param[1], 1];\n  }\n  return param;\n}\nfunction parse3TupleParam(param) {\n  return typeof param === \"number\" ? [param, param, param] : param;\n}\nfunction getEffectiveFilterSize(filterSize, dilation) {\n  if (dilation <= 1) {\n    return filterSize;\n  }\n  return filterSize + (filterSize - 1) * (dilation - 1);\n}\nfunction getPadAndOutInfo(pad3, inHeight, inWidth, strideHeight, strideWidth, filterHeight, filterWidth, roundingMode, dataFormat) {\n  let padInfo;\n  let outHeight;\n  let outWidth;\n  if (typeof pad3 === \"number\") {\n    const padType = pad3 === 0 ? \"VALID\" : \"NUMBER\";\n    padInfo = { top: pad3, bottom: pad3, left: pad3, right: pad3, type: padType };\n    const outShape = computeOutputShape2D([inHeight, inWidth], filterHeight, strideHeight, pad3, roundingMode);\n    outHeight = outShape[0];\n    outWidth = outShape[1];\n  } else if (pad3 === \"same\") {\n    outHeight = Math.ceil(inHeight / strideHeight);\n    outWidth = Math.ceil(inWidth / strideWidth);\n    const padAlongHeight = Math.max(0, (outHeight - 1) * strideHeight + filterHeight - inHeight);\n    const padAlongWidth = Math.max(0, (outWidth - 1) * strideWidth + filterWidth - inWidth);\n    const top = Math.floor(padAlongHeight / 2);\n    const bottom = padAlongHeight - top;\n    const left = Math.floor(padAlongWidth / 2);\n    const right = padAlongWidth - left;\n    padInfo = { top, bottom, left, right, type: \"SAME\" };\n  } else if (pad3 === \"valid\") {\n    padInfo = { top: 0, bottom: 0, left: 0, right: 0, type: \"VALID\" };\n    outHeight = Math.ceil((inHeight - filterHeight + 1) / strideHeight);\n    outWidth = Math.ceil((inWidth - filterWidth + 1) / strideWidth);\n  } else if (typeof pad3 === \"object\") {\n    const top = dataFormat === \"channelsLast\" ? pad3[1][0] : pad3[2][0];\n    const bottom = dataFormat === \"channelsLast\" ? pad3[1][1] : pad3[2][1];\n    const left = dataFormat === \"channelsLast\" ? pad3[2][0] : pad3[3][0];\n    const right = dataFormat === \"channelsLast\" ? pad3[2][1] : pad3[3][1];\n    const padType = top === 0 && bottom === 0 && left === 0 && right === 0 ? \"VALID\" : \"EXPLICIT\";\n    padInfo = { top, bottom, left, right, type: padType };\n    outHeight = round((inHeight - filterHeight + top + bottom) / strideHeight + 1, roundingMode);\n    outWidth = round((inWidth - filterWidth + left + right) / strideWidth + 1, roundingMode);\n  } else {\n    throw Error(`Unknown padding parameter: ${pad3}`);\n  }\n  return { padInfo, outHeight, outWidth };\n}\nfunction get3DPadAndOutInfo(pad3, inDepth, inHeight, inWidth, strideDepth, strideHeight, strideWidth, filterDepth, filterHeight, filterWidth, roundingMode) {\n  let padInfo;\n  let outDepth;\n  let outHeight;\n  let outWidth;\n  if (typeof pad3 === \"number\") {\n    const padType = pad3 === 0 ? \"VALID\" : \"NUMBER\";\n    padInfo = {\n      top: pad3,\n      bottom: pad3,\n      left: pad3,\n      right: pad3,\n      front: pad3,\n      back: pad3,\n      type: padType\n    };\n    const outShape = computeOutputShape4D([inDepth, inHeight, inWidth, 1], filterDepth, 1, strideDepth, pad3, roundingMode);\n    outDepth = outShape[0];\n    outHeight = outShape[1];\n    outWidth = outShape[2];\n  } else if (pad3 === \"same\") {\n    outDepth = Math.ceil(inDepth / strideDepth);\n    outHeight = Math.ceil(inHeight / strideHeight);\n    outWidth = Math.ceil(inWidth / strideWidth);\n    const padAlongDepth = (outDepth - 1) * strideDepth + filterDepth - inDepth;\n    const padAlongHeight = (outHeight - 1) * strideHeight + filterHeight - inHeight;\n    const padAlongWidth = (outWidth - 1) * strideWidth + filterWidth - inWidth;\n    const front = Math.floor(padAlongDepth / 2);\n    const back = padAlongDepth - front;\n    const top = Math.floor(padAlongHeight / 2);\n    const bottom = padAlongHeight - top;\n    const left = Math.floor(padAlongWidth / 2);\n    const right = padAlongWidth - left;\n    padInfo = { top, bottom, left, right, front, back, type: \"SAME\" };\n  } else if (pad3 === \"valid\") {\n    padInfo = {\n      top: 0,\n      bottom: 0,\n      left: 0,\n      right: 0,\n      front: 0,\n      back: 0,\n      type: \"VALID\"\n    };\n    outDepth = Math.ceil((inDepth - filterDepth + 1) / strideDepth);\n    outHeight = Math.ceil((inHeight - filterHeight + 1) / strideHeight);\n    outWidth = Math.ceil((inWidth - filterWidth + 1) / strideWidth);\n  } else {\n    throw Error(`Unknown padding parameter: ${pad3}`);\n  }\n  return { padInfo, outDepth, outHeight, outWidth };\n}\nfunction round(value, roundingMode) {\n  if (!roundingMode) {\n    return Math.trunc(value);\n  }\n  switch (roundingMode) {\n    case \"round\":\n      return Math.round(value);\n    case \"ceil\":\n      return Math.ceil(value);\n    case \"floor\":\n      return Math.floor(value);\n    default:\n      throw new Error(`Unknown roundingMode ${roundingMode}`);\n  }\n}\nfunction tupleValuesAreOne(param) {\n  const [dimA, dimB, dimC] = parseTupleParam(param);\n  return dimA === 1 && dimB === 1 && dimC === 1;\n}\nfunction eitherStridesOrDilationsAreOne(strides, dilations) {\n  return tupleValuesAreOne(strides) || tupleValuesAreOne(dilations);\n}\nfunction convertConv2DDataFormat(dataFormat) {\n  if (dataFormat === \"NHWC\") {\n    return \"channelsLast\";\n  } else if (dataFormat === \"NCHW\") {\n    return \"channelsFirst\";\n  } else {\n    throw new Error(`Unknown dataFormat ${dataFormat}`);\n  }\n}\nfunction checkPadOnDimRoundingMode(opDesc, pad3, dimRoundingMode) {\n  if (dimRoundingMode != null) {\n    if (typeof pad3 === \"string\") {\n      throw Error(`Error in ${opDesc}: pad must be an integer when using dimRoundingMode ${dimRoundingMode} but got pad ${pad3}.`);\n    } else if (typeof pad3 === \"number\") {\n      assert(isInt(pad3), () => `Error in ${opDesc}: pad must be an integer when using dimRoundingMode ${dimRoundingMode} but got pad ${pad3}.`);\n    } else if (typeof pad3 === \"object\") {\n      pad3.forEach((p2) => {\n        p2.forEach((v) => {\n          assert(isInt(v), () => `Error in ${opDesc}: pad must be an integer when using dimRoundingMode ${dimRoundingMode} but got pad ${v}.`);\n        });\n      });\n    } else {\n      throw Error(`Error in ${opDesc}: Unknown padding parameter: ${pad3}`);\n    }\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reshape.js\nfunction reshape_(x, shape) {\n  const $x = convertToTensor(x, \"x\", \"reshape\", \"string_or_numeric\");\n  const inputs = { x: $x };\n  const attrs = { shape };\n  return ENGINE.runKernel(Reshape, inputs, attrs);\n}\nvar reshape = op({ reshape_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool.js\nfunction avgPool_(x, filterSize, strides, pad3, dimRoundingMode) {\n  const $x = convertToTensor(x, \"x\", \"avgPool\", \"float32\");\n  const dilations = 1;\n  assert(eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in avgPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  assert(x4D.rank === 4, () => `Error in avgPool: x must be rank 4 but got rank ${x4D.rank}.`);\n  checkPadOnDimRoundingMode(\"avgPool\", pad3, dimRoundingMode);\n  const inputs = { x: x4D };\n  const attrs = { filterSize, strides, pad: pad3, dimRoundingMode };\n  let res = ENGINE.runKernel(AvgPool, inputs, attrs);\n  res = cast(res, $x.dtype);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar avgPool = op({ avgPool_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool_3d.js\nfunction avgPool3d_(x, filterSize, strides, pad3, dimRoundingMode, dataFormat = \"NDHWC\") {\n  const $x = convertToTensor(x, \"x\", \"avgPool3d\", \"float32\");\n  let x5D = $x;\n  let reshapedTo5D = false;\n  if ($x.rank === 4) {\n    reshapedTo5D = true;\n    x5D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]]);\n  }\n  assert(x5D.rank === 5, () => `Error in avgPool3d: x must be rank 5 but got rank ${x5D.rank}.`);\n  assert(dataFormat === \"NDHWC\", () => `Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of ${dataFormat}`);\n  checkPadOnDimRoundingMode(\"avgPool3d\", pad3, dimRoundingMode);\n  const inputs = { x: x5D };\n  const attrs = { filterSize, strides, pad: pad3, dimRoundingMode, dataFormat };\n  let res = ENGINE.runKernel(AvgPool3D, inputs, attrs);\n  res = cast(res, x5D.dtype);\n  if (reshapedTo5D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);\n  }\n  return res;\n}\nvar avgPool3d = op({ avgPool3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/concat.js\nfunction concat_(tensors, axis = 0) {\n  assert(tensors.length >= 1, () => \"Pass at least one tensor to concat\");\n  const $tensors = convertToTensorArray(tensors, \"tensors\", \"concat\", \"string_or_numeric\");\n  if ($tensors[0].dtype === \"complex64\") {\n    $tensors.forEach((tensor2) => {\n      if (tensor2.dtype !== \"complex64\") {\n        throw new Error(`Cannot concatenate complex64 tensors with a tensor\n          with dtype ${tensor2.dtype}. `);\n      }\n    });\n  }\n  if ($tensors.length === 1) {\n    return clone($tensors[0]);\n  }\n  const inputs = $tensors;\n  const attr = { axis };\n  return ENGINE.runKernel(Concat, inputs, attr);\n}\nvar concat = op({ concat_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sigmoid.js\nfunction sigmoid_(x) {\n  const $x = convertToTensor(x, \"x\", \"sigmoid\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Sigmoid, inputs);\n}\nvar sigmoid = op({ sigmoid_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/slice.js\nfunction slice_(x, begin, size) {\n  const $x = convertToTensor(x, \"x\", \"slice\", \"string_or_numeric\");\n  if ($x.rank === 0) {\n    throw new Error(\"Slicing scalar is not possible\");\n  }\n  const inputs = { x: $x };\n  const attrs = { begin, size };\n  return ENGINE.runKernel(Slice, inputs, attrs);\n}\nvar slice = op({ slice_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tanh.js\nfunction tanh_(x) {\n  const $x = convertToTensor(x, \"x\", \"tanh\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Tanh, inputs);\n}\nvar tanh2 = op({ tanh_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/basic_lstm_cell.js\nfunction basicLSTMCell_(forgetBias, lstmKernel, lstmBias, data, c, h) {\n  const $forgetBias = convertToTensor(forgetBias, \"forgetBias\", \"basicLSTMCell\");\n  const $lstmKernel = convertToTensor(lstmKernel, \"lstmKernel\", \"basicLSTMCell\");\n  const $lstmBias = convertToTensor(lstmBias, \"lstmBias\", \"basicLSTMCell\");\n  const $data = convertToTensor(data, \"data\", \"basicLSTMCell\");\n  const $c = convertToTensor(c, \"c\", \"basicLSTMCell\");\n  const $h = convertToTensor(h, \"h\", \"basicLSTMCell\");\n  const combined = concat([$data, $h], 1);\n  const weighted = matMul(combined, $lstmKernel);\n  const res = add2(weighted, $lstmBias);\n  const batchSize = res.shape[0];\n  const sliceCols = res.shape[1] / 4;\n  const sliceSize = [batchSize, sliceCols];\n  const i2 = slice(res, [0, 0], sliceSize);\n  const j = slice(res, [0, sliceCols], sliceSize);\n  const f = slice(res, [0, sliceCols * 2], sliceSize);\n  const o = slice(res, [0, sliceCols * 3], sliceSize);\n  const newC = add2(mul(sigmoid(i2), tanh2(j)), mul($c, sigmoid(add2($forgetBias, f))));\n  const newH = mul(tanh2(newC), sigmoid(o));\n  return [newC, newH];\n}\nvar basicLSTMCell = op({ basicLSTMCell_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/batch_to_space_nd.js\nfunction batchToSpaceND_(x, blockShape, crops) {\n  const $x = convertToTensor(x, \"x\", \"batchToSpaceND\");\n  const prod6 = blockShape.reduce((a, b) => a * b);\n  assert($x.rank >= 1 + blockShape.length, () => `input rank is ${$x.rank} but should be > than blockShape.length ${blockShape.length}`);\n  assert(crops.length === blockShape.length, () => `crops.length is ${crops.length} but should be equal to blockShape.length  ${blockShape.length}`);\n  assert($x.shape[0] % prod6 === 0, () => `input tensor batch is ${$x.shape[0]} but is not divisible by the product of the elements of blockShape ${blockShape.join(\" * \")} === ${prod6}`);\n  const inputs = { x: $x };\n  const attrs = { blockShape, crops };\n  return ENGINE.runKernel(BatchToSpaceND, inputs, attrs);\n}\nvar batchToSpaceND = op({ batchToSpaceND_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm_util.js\nfunction xAs4D(x) {\n  let x4D;\n  if (x.rank === 0 || x.rank === 1) {\n    x4D = reshape(x, [1, 1, 1, x.size]);\n  } else if (x.rank === 2) {\n    x4D = reshape(x, [1, 1, x.shape[0], x.shape[1]]);\n  } else if (x.rank === 3) {\n    x4D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2]]);\n  } else {\n    x4D = x;\n  }\n  return x4D;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm.js\nfunction batchNorm_(x, mean5, variance, offset, scale2, varianceEpsilon) {\n  if (varianceEpsilon == null) {\n    varianceEpsilon = 1e-3;\n  }\n  const $x = convertToTensor(x, \"x\", \"batchNorm\");\n  const $mean = convertToTensor(mean5, \"mean\", \"batchNorm\");\n  const $variance = convertToTensor(variance, \"variance\", \"batchNorm\");\n  let $scale;\n  if (scale2 != null) {\n    $scale = convertToTensor(scale2, \"scale\", \"batchNorm\");\n  }\n  let $offset;\n  if (offset != null) {\n    $offset = convertToTensor(offset, \"offset\", \"batchNorm\");\n  }\n  assert($mean.rank === $variance.rank, () => \"Batch normalization gradient requires mean and variance to have equal ranks.\");\n  assert($offset == null || $mean.rank === $offset.rank, () => \"Batch normalization gradient requires mean and offset to have equal ranks.\");\n  assert($scale == null || $mean.rank === $scale.rank, () => \"Batch normalization gradient requires mean and scale to have equal ranks.\");\n  const x4D = xAs4D($x);\n  const inputs = {\n    x: x4D,\n    scale: $scale,\n    offset: $offset,\n    mean: $mean,\n    variance: $variance\n  };\n  const attrs = { varianceEpsilon };\n  const res = ENGINE.runKernel(FusedBatchNorm, inputs, attrs);\n  return reshape(res, $x.shape);\n}\nvar batchNorm = op({ batchNorm_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm2d.js\nfunction batchNorm2d_(x, mean5, variance, offset, scale2, varianceEpsilon) {\n  const $x = convertToTensor(x, \"x\", \"batchNorm\");\n  const $mean = convertToTensor(mean5, \"mean\", \"batchNorm\");\n  const $variance = convertToTensor(variance, \"variance\", \"batchNorm\");\n  let $scale;\n  if (scale2 != null) {\n    $scale = convertToTensor(scale2, \"scale\", \"batchNorm\");\n  }\n  let $offset;\n  if (offset != null) {\n    $offset = convertToTensor(offset, \"offset\", \"batchNorm\");\n  }\n  assert($x.rank === 2, () => `Error in batchNorm2D: x must be rank 2 but got rank ${$x.rank}.`);\n  assert($mean.rank === 2 || $mean.rank === 1, () => `Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank ${$mean.rank}.`);\n  assert($variance.rank === 2 || $variance.rank === 1, () => `Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank ${$variance.rank}.`);\n  if ($scale != null) {\n    assert($scale.rank === 2 || $scale.rank === 1, () => `Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank ${$scale.rank}.`);\n  }\n  if ($offset != null) {\n    assert($offset.rank === 2 || $offset.rank === 1, () => `Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${$offset.rank}.`);\n  }\n  return batchNorm($x, $mean, $variance, $offset, $scale, varianceEpsilon);\n}\nvar batchNorm2d = op({ batchNorm2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm3d.js\nfunction batchNorm3d_(x, mean5, variance, offset, scale2, varianceEpsilon) {\n  const $x = convertToTensor(x, \"x\", \"batchNorm\");\n  const $mean = convertToTensor(mean5, \"mean\", \"batchNorm\");\n  const $variance = convertToTensor(variance, \"variance\", \"batchNorm\");\n  let $scale;\n  if (scale2 != null) {\n    $scale = convertToTensor(scale2, \"scale\", \"batchNorm\");\n  }\n  let $offset;\n  if (offset != null) {\n    $offset = convertToTensor(offset, \"offset\", \"batchNorm\");\n  }\n  assert($x.rank === 3, () => `Error in batchNorm3D: x must be rank 3 but got rank ${$x.rank}.`);\n  assert($mean.rank === 3 || $mean.rank === 1, () => `Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${$mean.rank}.`);\n  assert($variance.rank === 3 || $variance.rank === 1, () => `Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${$variance.rank}.`);\n  if ($scale != null) {\n    assert($scale.rank === 3 || $scale.rank === 1, () => `Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${$scale.rank}.`);\n  }\n  if ($offset != null) {\n    assert($offset.rank === 3 || $offset.rank === 1, () => `Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${$offset.rank}.`);\n  }\n  return batchNorm($x, $mean, $variance, $offset, $scale, varianceEpsilon);\n}\nvar batchNorm3d = op({ batchNorm3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm4d.js\nfunction batchNorm4d_(x, mean5, variance, offset, scale2, varianceEpsilon) {\n  const $x = convertToTensor(x, \"x\", \"batchNorm\");\n  const $mean = convertToTensor(mean5, \"mean\", \"batchNorm\");\n  const $variance = convertToTensor(variance, \"variance\", \"batchNorm\");\n  let $scale;\n  if (scale2 != null) {\n    $scale = convertToTensor(scale2, \"scale\", \"batchNorm\");\n  }\n  let $offset;\n  if (offset != null) {\n    $offset = convertToTensor(offset, \"offset\", \"batchNorm\");\n  }\n  assert($x.rank === 4, () => `Error in batchNorm4D: x must be rank 4 but got rank ${$x.rank}.`);\n  assert($mean.rank === 4 || $mean.rank === 1, () => `Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${$mean.rank}.`);\n  assert($variance.rank === 4 || $variance.rank === 1, () => `Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${$variance.rank}.`);\n  if ($scale != null) {\n    assert($scale.rank === 4 || $scale.rank === 1, () => `Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${$scale.rank}.`);\n  }\n  if ($offset != null) {\n    assert($offset.rank === 4 || $offset.rank === 1, () => `Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${$offset.rank}.`);\n  }\n  return batchNorm($x, $mean, $variance, $offset, $scale, varianceEpsilon);\n}\nvar batchNorm4d = op({ batchNorm4d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/bincount.js\nfunction bincount_(x, weights, size) {\n  const $x = convertToTensor(x, \"x\", \"bincount\");\n  const $weights = convertToTensor(weights, \"weights\", \"bincount\");\n  assert($x.dtype === \"int32\", () => `Error in bincount: input dtype must be int32, but got ${$x.dtype}`);\n  assert(size >= 0, () => `size must be non-negative, but got ${size}.`);\n  assert($weights.size === $x.size || $weights.size === 0, () => `Error in bincount: weights must have the same size as input or0-length, but got input shape: ${$x.shape}, weights shape: ${$weights.shape}.`);\n  const inputs = { x: $x, weights: $weights };\n  const attrs = { size };\n  return ENGINE.runKernel(Bincount, inputs, attrs);\n}\nvar bincount = op({ bincount_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/broadcast_args.js\nfunction broadcastArgs_(s0, s1) {\n  const shape1Input = convertToTensor(s0, \"s0\", \"broadcastArgs\", \"int32\");\n  const shape2Input = convertToTensor(s1, \"s1\", \"broadcastArgs\", \"int32\");\n  if (shape1Input.rank !== 1) {\n    throw new Error(`broadcastArgs(): first input must be a vector (rank=1). Has rank ${shape1Input.rank}`);\n  }\n  if (shape2Input.rank !== 1) {\n    throw new Error(`broadcastArgs(): second input must be a vector (rank=1). Has rank ${shape2Input.rank}`);\n  }\n  const inputs = { s0: shape1Input, s1: shape2Input };\n  return ENGINE.runKernel(BroadcastArgs, inputs);\n}\nvar broadcastArgs = op({ broadcastArgs_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/broadcast_to.js\nfunction broadcastTo_(x, shape) {\n  let input2 = convertToTensor(x, \"broadcastTo\", \"x\");\n  const xShape = input2.shape;\n  if (shape.some((d) => !(d > 0) || d % 1 !== 0)) {\n    throw new Error(`broadcastTo(): Invalid broadcast shape [${shape}].`);\n  }\n  if (shape.length < input2.rank) {\n    throw new Error(`broadcastTo(): shape.length=${shape.length} < input.rank=${input2.rank}.`);\n  }\n  if (shape.length > input2.rank) {\n    const newShape = input2.shape.slice();\n    while (newShape.length < shape.length) {\n      newShape.unshift(1);\n    }\n    input2 = reshape(input2, newShape);\n  }\n  const inputShape = input2.shape;\n  const reps = Array.from(shape);\n  for (let i2 = shape.length - 1; i2 >= 0; i2--) {\n    if (inputShape[i2] === shape[i2]) {\n      reps[i2] = 1;\n    } else if (input2.shape[i2] !== 1) {\n      throw new Error(`broadcastTo(): [${xShape}] cannot be broadcast to [${shape}].`);\n    }\n  }\n  const axes = reps.map((n2, i2) => n2 > 1 ? i2 : -1).filter((i2) => i2 >= 0);\n  if (axes.length === 0) {\n    return clone(input2);\n  }\n  const inputs = { x: input2 };\n  const attrs = { reps };\n  return ENGINE.runKernel(Tile, inputs, attrs);\n}\nvar broadcastTo = op({ broadcastTo_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/ceil.js\nfunction ceil_(x) {\n  const $x = convertToTensor(x, \"x\", \"ceil\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Ceil, inputs);\n}\nvar ceil = op({ ceil_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/clip_by_value.js\nfunction clipByValue_(x, clipValueMin, clipValueMax) {\n  const $x = convertToTensor(x, \"x\", \"clipByValue\");\n  assert(clipValueMin <= clipValueMax, () => `Error in clip: min (${clipValueMin}) must be less than or equal to max (${clipValueMax}).`);\n  const inputs = { x: $x };\n  const attrs = { clipValueMin, clipValueMax };\n  return ENGINE.runKernel(ClipByValue, inputs, attrs);\n}\nvar clipByValue = op({ clipByValue_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/concat_1d.js\nfunction concat1d_(tensors) {\n  return concat(tensors, 0);\n}\nvar concat1d = op({ concat1d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/concat_2d.js\nfunction concat2d_(tensors, axis) {\n  return concat(tensors, axis);\n}\nvar concat2d = op({ concat2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/concat_3d.js\nfunction concat3d_(tensors, axis) {\n  return concat(tensors, axis);\n}\nvar concat3d = op({ concat3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/concat_4d.js\nfunction concat4d_(tensors, axis) {\n  return concat(tensors, axis);\n}\nvar concat4d = op({ concat4d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv2d.js\nfunction conv2d_(x, filter, strides, pad3, dataFormat = \"NHWC\", dilations = [1, 1], dimRoundingMode) {\n  const $x = convertToTensor(x, \"x\", \"conv2d\", \"float32\");\n  const $filter = convertToTensor(filter, \"filter\", \"conv2d\", \"float32\");\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  assert(x4D.rank === 4, () => `Error in conv2d: input must be rank 4, but got rank ${x4D.rank}.`);\n  assert($filter.rank === 4, () => `Error in conv2d: filter must be rank 4, but got rank ${$filter.rank}.`);\n  checkPadOnDimRoundingMode(\"conv2d\", pad3, dimRoundingMode);\n  const inDepth = dataFormat === \"NHWC\" ? x4D.shape[3] : x4D.shape[1];\n  assert(inDepth === $filter.shape[2], () => `Error in conv2d: depth of input (${inDepth}) must match input depth for filter ${$filter.shape[2]}.`);\n  assert(eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in conv2D: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  const inputs = { x: x4D, filter: $filter };\n  const attrs = { strides, pad: pad3, dataFormat, dilations, dimRoundingMode };\n  const res = ENGINE.runKernel(Conv2D, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar conv2d = op({ conv2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv1d.js\nfunction conv1d_(x, filter, stride, pad3, dataFormat = \"NWC\", dilation = 1, dimRoundingMode) {\n  const $x = convertToTensor(x, \"x\", \"conv1d\");\n  const $filter = convertToTensor(filter, \"filter\", \"conv1d\");\n  let x3D = $x;\n  let reshapedTo3D = false;\n  if ($x.rank === 2) {\n    reshapedTo3D = true;\n    x3D = reshape($x, [1, $x.shape[0], $x.shape[1]]);\n  }\n  assert(x3D.rank === 3, () => `Error in conv1d: input must be rank 3, but got rank ${x3D.rank}.`);\n  assert($filter.rank === 3, () => `Error in conv1d: filter must be rank 3, but got rank ${$filter.rank}.`);\n  checkPadOnDimRoundingMode(\"conv1d\", pad3, dimRoundingMode);\n  assert(x3D.shape[2] === $filter.shape[1], () => `Error in conv1d: depth of input (${x3D.shape[2]}) must match input depth for filter ${$filter.shape[1]}.`);\n  assert(eitherStridesOrDilationsAreOne(stride, dilation), () => `Error in conv1D: Either stride or dilation must be 1. Got stride ${stride} and dilation '${dilation}'`);\n  assert(dataFormat === \"NWC\", () => `Error in conv1d: got dataFormat of ${dataFormat} but only NWC is currently supported.`);\n  const filter4D = reshape($filter, [1, $filter.shape[0], $filter.shape[1], $filter.shape[2]]);\n  const input4D = reshape(x3D, [x3D.shape[0], 1, x3D.shape[1], x3D.shape[2]]);\n  const strides = [1, stride];\n  const dilations = [1, dilation];\n  const conv2dDataFormat = \"NHWC\";\n  const res = conv2d(input4D, filter4D, strides, pad3, conv2dDataFormat, dilations, dimRoundingMode);\n  if (reshapedTo3D) {\n    return reshape(res, [res.shape[2], res.shape[3]]);\n  }\n  return reshape(res, [res.shape[0], res.shape[2], res.shape[3]]);\n}\nvar conv1d = op({ conv1d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv2d_backprop_input.js\nfunction conv2DBackpropInput_(xShape, dy, filter, strides, pad3, dataFormat = \"NHWC\", dimRoundingMode) {\n  assert(xShape.length === dy.rank, () => `Length of inShape (${xShape.length}) and rank of dy (${dy.rank}) must match`);\n  let xShape4D = xShape;\n  let dy4D = dy;\n  let reshapedTo4D = false;\n  if (dy.rank === 3) {\n    reshapedTo4D = true;\n    dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);\n    xShape4D = [1, xShape[0], xShape[1], xShape[2]];\n  }\n  assert(xShape4D.length === 4, () => `Error in conv2dDerInput: inShape must be length 4, but got length ${xShape4D.length}.`);\n  assert(dy4D.rank === 4, () => `Error in conv2dDerInput: dy must be rank 4, but got rank ${dy4D.rank}`);\n  assert(filter.rank === 4, () => `Error in conv2dDerInput: filter must be rank 4, but got rank ${filter.rank}`);\n  const inDepth = dataFormat === \"NHWC\" ? xShape4D[3] : xShape4D[1];\n  const outDepth = dataFormat === \"NHWC\" ? dy4D.shape[3] : dy4D.shape[1];\n  assert(inDepth === filter.shape[2], () => `Error in conv2dDerInput: depth of input (${inDepth}) must match input depth for filter ${filter.shape[2]}.`);\n  assert(outDepth === filter.shape[3], () => `Error in conv2dDerInput: depth of output (${outDepth}) must match output depth for filter ${filter.shape[3]}.`);\n  checkPadOnDimRoundingMode(\"conv2dDerInput\", pad3, dimRoundingMode);\n  const inputs = { dy: dy4D, filter };\n  const attrs = { strides, pad: pad3, dataFormat, dimRoundingMode, inputShape: xShape4D };\n  const res = ENGINE.runKernel(Conv2DBackpropInput, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar conv2DBackpropInput = op({ conv2DBackpropInput_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv2d_transpose.js\nfunction conv2dTranspose_(x, filter, outputShape, strides, pad3, dimRoundingMode) {\n  const $x = convertToTensor(x, \"x\", \"conv2dTranspose\");\n  const $filter = convertToTensor(filter, \"filter\", \"conv2dTranspose\");\n  return conv2DBackpropInput(outputShape, $x, $filter, strides, pad3, \"NHWC\", dimRoundingMode);\n}\nvar conv2dTranspose = op({ conv2dTranspose_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv3d.js\nfunction conv3d_(x, filter, strides, pad3, dataFormat = \"NDHWC\", dilations = [1, 1, 1]) {\n  const $x = convertToTensor(x, \"x\", \"conv3d\");\n  const $filter = convertToTensor(filter, \"filter\", \"conv3d\");\n  let x5D = $x;\n  let reshapedTo5D = false;\n  if ($x.rank === 4) {\n    reshapedTo5D = true;\n    x5D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]]);\n  }\n  assert(x5D.rank === 5, () => `Error in conv3d: input must be rank 5, but got rank ${x5D.rank}.`);\n  assert($filter.rank === 5, () => `Error in conv3d: filter must be rank 5, but got rank ${$filter.rank}.`);\n  assert(x5D.shape[4] === $filter.shape[3], () => `Error in conv3d: depth of input (${x5D.shape[4]}) must match input depth for filter ${$filter.shape[3]}.`);\n  assert(eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in conv3D: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  assert(dataFormat === \"NDHWC\", () => `Error in conv3d: got dataFormat of ${dataFormat} but only NDHWC is currently supported.`);\n  const inputs = { x: x5D, filter: $filter };\n  const attrs = { strides, pad: pad3, dataFormat, dilations };\n  const res = ENGINE.runKernel(Conv3D, inputs, attrs);\n  if (reshapedTo5D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);\n  }\n  return res;\n}\nvar conv3d = op({ conv3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv3d_backprop_input.js\nfunction conv3DBackpropInput_(xShape, dy, filter, strides, pad3) {\n  assert(xShape.length === dy.rank, () => `Length of inShape (${xShape.length}) and rank of dy (${dy.rank}) must match`);\n  let xShape5D = xShape;\n  let dy5D = dy;\n  let reshapedTo5D = false;\n  if (dy.rank === 4) {\n    reshapedTo5D = true;\n    dy5D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2], dy.shape[3]]);\n    xShape5D = [1, xShape[0], xShape[1], xShape[2], xShape[3]];\n  }\n  const inDepth = xShape5D[4];\n  const outDepth = dy5D.shape[4];\n  assert(xShape5D.length === 5, () => `Error in conv3dDerInput: inShape must be length 5, but got length ${xShape5D.length}.`);\n  assert(dy5D.rank === 5, () => `Error in conv3dDerInput: dy must be rank 5, but got rank ${dy5D.rank}`);\n  assert(filter.rank === 5, () => `Error in conv3dDerInput: filter must be rank 5, but got rank ${filter.rank}`);\n  assert(inDepth === filter.shape[3], () => `Error in conv3dDerInput: depth of input (${inDepth}) must match input depth for filter ${filter.shape[3]}.`);\n  assert(outDepth === filter.shape[4], () => `Error in conv3dDerInput: depth of output (${outDepth}) must match output depth for filter ${filter.shape[4]}.`);\n  const inputs = { dy: dy5D, filter };\n  const attrs = { pad: pad3, strides, inputShape: xShape5D };\n  const res = ENGINE.runKernel(Conv3DBackpropInputV2, inputs, attrs);\n  if (reshapedTo5D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);\n  }\n  return res;\n}\nvar conv3DBackpropInput = op({ conv3DBackpropInput_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv3d_transpose.js\nfunction conv3dTranspose_(x, filter, outputShape, strides, pad3) {\n  const $x = convertToTensor(x, \"x\", \"conv3dTranspose\");\n  const $filter = convertToTensor(filter, \"filter\", \"conv3dTranspose\");\n  return conv3DBackpropInput(outputShape, $x, $filter, strides, pad3);\n}\nvar conv3dTranspose = op({ conv3dTranspose_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/cos.js\nfunction cos_(x) {\n  const $x = convertToTensor(x, \"x\", \"cos\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Cos, inputs);\n}\nvar cos = op({ cos_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/cosh.js\nfunction cosh_(x) {\n  const $x = convertToTensor(x, \"x\", \"cosh\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Cosh, inputs);\n}\nvar cosh = op({ cosh_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/cumprod.js\nfunction cumprod_(x, axis = 0, exclusive = false, reverse5 = false) {\n  const $x = convertToTensor(x, \"x\", \"cumprod\");\n  const inputs = { x: $x };\n  const attrs = { axis, exclusive, reverse: reverse5 };\n  return ENGINE.runKernel(Cumprod, inputs, attrs);\n}\nvar cumprod = op({ cumprod_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/cumsum.js\nfunction cumsum_(x, axis = 0, exclusive = false, reverse5 = false) {\n  const $x = convertToTensor(x, \"x\", \"cumsum\");\n  const inputs = { x: $x };\n  const attrs = { axis, exclusive, reverse: reverse5 };\n  return ENGINE.runKernel(Cumsum, inputs, attrs);\n}\nvar cumsum = op({ cumsum_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/dense_bincount.js\nfunction denseBincount_(x, weights, size, binaryOutput = false) {\n  const $x = convertToTensor(x, \"x\", \"denseBincount\");\n  const $weights = convertToTensor(weights, \"weights\", \"denseBincount\");\n  assert($x.dtype === \"int32\", () => `Error in denseBincount: input dtype must be int32, but got ${$x.dtype}`);\n  assert($x.rank <= 2, () => `Error in denseBincount: input must be at most rank 2, but got rank ${$x.rank}.`);\n  assert(size >= 0, () => `size must be non-negative, but got ${size}.`);\n  assert($weights.size === $x.size || $weights.size === 0, () => `Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${$x.shape}, weights shape: ${$weights.shape}.`);\n  const inputs = { x: $x, weights: $weights };\n  const attrs = { size, binaryOutput };\n  return ENGINE.runKernel(DenseBincount, inputs, attrs);\n}\nvar denseBincount = op({ denseBincount_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/depth_to_space.js\nfunction depthToSpace_(x, blockSize, dataFormat = \"NHWC\") {\n  const $x = convertToTensor(x, \"x\", \"depthToSpace\", \"float32\");\n  const inputHeight = dataFormat === \"NHWC\" ? $x.shape[1] : $x.shape[2];\n  const inputWidth = dataFormat === \"NHWC\" ? $x.shape[2] : $x.shape[3];\n  const inputDepth = dataFormat === \"NHWC\" ? $x.shape[3] : $x.shape[1];\n  assert(blockSize > 1, () => `blockSize should be > 1 for depthToSpace, but was: ${blockSize}`);\n  assert(inputHeight * blockSize >= 0, () => `Negative dimension size caused by overflow when multiplying\n    ${inputHeight} and ${blockSize}  for depthToSpace with input shape\n    ${$x.shape}`);\n  assert(inputWidth * blockSize >= 0, () => `Negative dimension size caused by overflow when multiplying\n    ${inputWidth} and ${blockSize} for depthToSpace with input shape\n        ${$x.shape}`);\n  assert(inputDepth % (blockSize * blockSize) === 0, () => `Dimension size must be evenly divisible by ${blockSize * blockSize} but is ${inputDepth} for depthToSpace with input shape ${$x.shape}`);\n  const inputs = { x: $x };\n  const attrs = { blockSize, dataFormat };\n  return ENGINE.runKernel(DepthToSpace, inputs, attrs);\n}\nvar depthToSpace = op({ depthToSpace_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/depthwise_conv2d.js\nfunction depthwiseConv2d_(x, filter, strides, pad3, dataFormat = \"NHWC\", dilations = [1, 1], dimRoundingMode) {\n  const $x = convertToTensor(x, \"x\", \"depthwiseConv2d\", \"float32\");\n  const $filter = convertToTensor(filter, \"filter\", \"depthwiseConv2d\", \"float32\");\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  assert(x4D.rank === 4, () => `Error in depthwiseConv2d: input must be rank 4, but got rank ${x4D.rank}.`);\n  assert($filter.rank === 4, () => `Error in depthwiseConv2d: filter must be rank 4, but got rank ${$filter.rank}.`);\n  const inChannels = dataFormat === \"NHWC\" ? x4D.shape[3] : x4D.shape[1];\n  assert(inChannels === $filter.shape[2], () => `Error in depthwiseConv2d: number of input channels (${inChannels}) must match the inChannels dimension in filter ${$filter.shape[2]}.`);\n  checkPadOnDimRoundingMode(\"depthwiseConv2d\", pad3, dimRoundingMode);\n  const inputs = { x: x4D, filter: $filter };\n  const attrs = { strides, pad: pad3, dataFormat, dilations, dimRoundingMode };\n  const res = ENGINE.runKernel(DepthwiseConv2dNative, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar depthwiseConv2d = op({ depthwiseConv2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/diag.js\nfunction diag_(x) {\n  const $x = convertToTensor(x, \"x\", \"diag\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Diag, inputs);\n}\nvar diag = op({ diag_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/dilation2d.js\nfunction dilation2d_(x, filter, strides, pad3, dilations = [1, 1], dataFormat = \"NHWC\") {\n  const $x = convertToTensor(x, \"x\", \"dilation2d\");\n  const $filter = convertToTensor(filter, \"filter\", \"dilation2d\");\n  assert($x.rank === 3 || $x.rank === 4, () => `Error in dilation2d: input must be rank 3 or 4, but got rank ${$x.rank}.`);\n  assert($filter.rank === 3, () => `Error in dilation2d: filter must be rank 3, but got rank ${$filter.rank}.`);\n  assert(dataFormat === \"NHWC\", () => `Error in dilation2d: Only NHWC is currently supported, but got dataFormat of ${dataFormat}`);\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n    reshapedTo4D = true;\n  }\n  const inputs = { x: x4D, filter: $filter };\n  const attrs = { strides, pad: pad3, dilations };\n  const res = ENGINE.runKernel(Dilation2D, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar dilation2d = op({ dilation2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/equal.js\nfunction equal_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"equal\", \"string_or_numeric\");\n  let $b = convertToTensor(b, \"b\", \"equal\", \"string_or_numeric\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Equal, inputs);\n}\nvar equal = op({ equal_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/where.js\nfunction where_(condition, a, b) {\n  const $a = convertToTensor(a, \"a\", \"where\");\n  const $b = convertToTensor(b, \"b\", \"where\");\n  const $condition = convertToTensor(condition, \"condition\", \"where\", \"bool\");\n  const broadcastShape = assertAndGetBroadcastShape(assertAndGetBroadcastShape($condition.shape, $a.shape), $b.shape);\n  const $broadcastedCondition = broadcastTo($condition, broadcastShape);\n  const $broadcastedA = broadcastTo($a, broadcastShape);\n  const $broadcastedB = broadcastTo($b, broadcastShape);\n  const inputs = {\n    condition: $broadcastedCondition,\n    t: $broadcastedA,\n    e: $broadcastedB\n  };\n  return ENGINE.runKernel(Select, inputs);\n}\nvar where = op({ where_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/zeros_like.js\nfunction zerosLike_(x) {\n  const $x = convertToTensor(x, \"x\", \"zerosLike\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(ZerosLike, inputs);\n}\nvar zerosLike = op({ zerosLike_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/div_no_nan.js\nfunction divNoNan_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"div\");\n  let $b = convertToTensor(b, \"b\", \"div\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const divResult = div($a, $b);\n  const zeros4 = zerosLike(divResult);\n  const bEqualsZero = equal($b, zeros4);\n  return where(bEqualsZero, zeros4, divResult);\n}\nvar divNoNan = op({ divNoNan_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/dot.js\nfunction dot_(t1, t2) {\n  const $t1 = convertToTensor(t1, \"t1\", \"dot\");\n  const $t2 = convertToTensor(t2, \"t2\", \"dot\");\n  assert(($t1.rank === 1 || $t1.rank === 2) && ($t2.rank === 1 || $t2.rank === 2), () => `Error in dot: inputs must all be rank 1 or 2, but got ranks ${$t1.rank} and ${$t2.rank}.`);\n  const t1Inner = $t1.rank === 1 ? $t1.size : $t1.shape[1];\n  const t2Inner = $t2.rank === 1 ? $t2.size : $t2.shape[0];\n  assert(t1Inner === t2Inner, () => `Error in dot: inner dimensions of inputs must match, but got ${t1Inner} and ${t2Inner}.`);\n  if ($t1.rank === 1 && $t2.rank === 1) {\n    const t12D = reshape($t1, [1, -1]);\n    const t22D = reshape($t2, [-1, 1]);\n    const t1t2 = matMul(t12D, t22D);\n    return reshape(t1t2, []);\n  } else if ($t1.rank === 1 && $t2.rank === 2) {\n    const t12D = reshape($t1, [1, -1]);\n    const t22D = reshape($t2, [$t2.shape[0], $t2.shape[1]]);\n    const t1t2 = matMul(t12D, t22D);\n    return reshape(t1t2, [t1t2.size]);\n  } else if ($t1.rank === 2 && $t2.rank === 1) {\n    const t22D = reshape($t2, [-1, 1]);\n    const t1t2 = matMul($t1, t22D);\n    return reshape(t1t2, [t1t2.size]);\n  } else {\n    const t22D = reshape($t2, [$t2.shape[0], $t2.shape[1]]);\n    const t1t2 = matMul($t1, t22D);\n    return t1t2;\n  }\n}\nvar dot = op({ dot_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/einsum.js\nfunction einsum_(equation, ...tensors) {\n  const $tensors = tensors.map((t2, i2) => convertToTensor(t2, `tensors${i2}`, \"einsum\"));\n  const attrs = { equation };\n  return ENGINE.runKernel(Einsum, $tensors, attrs);\n}\nvar einsum = op({ einsum_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/elu.js\nfunction elu_(x) {\n  const $x = convertToTensor(x, \"x\", \"elu\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Elu, inputs);\n}\nvar elu = op({ elu_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/erf.js\nfunction erf_(x) {\n  let $x = convertToTensor(x, \"x\", \"erf\");\n  assert($x.dtype === \"int32\" || $x.dtype === \"float32\", () => \"Input dtype must be `int32` or `float32`.\");\n  if ($x.dtype === \"int32\") {\n    $x = cast($x, \"float32\");\n  }\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Erf, inputs);\n}\nvar erf = op({ erf_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/axis_util.js\nfunction axesAreInnerMostDims(axes, rank) {\n  for (let i2 = 0; i2 < axes.length; ++i2) {\n    if (axes[axes.length - i2 - 1] !== rank - 1 - i2) {\n      return false;\n    }\n  }\n  return true;\n}\nfunction combineLocations(outputLoc, reduceLoc, axes) {\n  const rank = outputLoc.length + reduceLoc.length;\n  const loc = [];\n  let outIdx = 0;\n  let reduceIdx = 0;\n  for (let dim = 0; dim < rank; dim++) {\n    if (axes.indexOf(dim) === -1) {\n      loc.push(outputLoc[outIdx++]);\n    } else {\n      loc.push(reduceLoc[reduceIdx++]);\n    }\n  }\n  return loc;\n}\nfunction computeOutAndReduceShapes(aShape, axes) {\n  const outShape = [];\n  const rank = aShape.length;\n  for (let dim = 0; dim < rank; dim++) {\n    if (axes.indexOf(dim) === -1) {\n      outShape.push(aShape[dim]);\n    }\n  }\n  const reduceShape = axes.map((dim) => aShape[dim]);\n  return [outShape, reduceShape];\n}\nfunction expandShapeToKeepDim(shape, axes) {\n  const reduceSubShape = axes.map((x) => 1);\n  return combineLocations(shape, reduceSubShape, axes);\n}\nfunction assertAxesAreInnerMostDims(msg, axes, rank) {\n  assert(axesAreInnerMostDims(axes, rank), () => `${msg} supports only inner-most axes for now. Got axes ${axes} and rank-${rank} input.`);\n}\nfunction getAxesPermutation(axes, rank) {\n  if (axesAreInnerMostDims(axes, rank)) {\n    return null;\n  }\n  const result = [];\n  for (let i2 = 0; i2 < rank; ++i2) {\n    if (axes.indexOf(i2) === -1) {\n      result.push(i2);\n    }\n  }\n  axes.forEach((axis) => result.push(axis));\n  return result;\n}\nfunction getUndoAxesPermutation(axes) {\n  return axes.map((axis, i2) => [i2, axis]).sort((a, b) => a[1] - b[1]).map((x) => x[0]);\n}\nfunction getInnerMostAxes(numAxes, rank) {\n  const res = [];\n  for (let i2 = rank - numAxes; i2 < rank; ++i2) {\n    res.push(i2);\n  }\n  return res;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/max.js\nfunction max_(x, axis = null, keepDims = false) {\n  const $x = convertToTensor(x, \"x\", \"max\");\n  const inputs = { x: $x };\n  const attrs = { reductionIndices: axis, keepDims };\n  return ENGINE.runKernel(Max, inputs, attrs);\n}\nvar max = op({ max_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/min.js\nfunction min_(x, axis = null, keepDims = false) {\n  const $x = convertToTensor(x, \"x\", \"min\");\n  const inputs = { x: $x };\n  const attrs = { axis, keepDims };\n  return ENGINE.runKernel(Min, inputs, attrs);\n}\nvar min = op({ min_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/pow.js\nfunction pow_(base, exp5) {\n  let $base = convertToTensor(base, \"base\", \"pow\");\n  let $exp = convertToTensor(exp5, \"exp\", \"pow\");\n  [$base, $exp] = makeTypesMatch($base, $exp);\n  const inputs = { a: $base, b: $exp };\n  return ENGINE.runKernel(Pow, inputs);\n}\nvar pow = op({ pow_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/scalar.js\nfunction scalar(value, dtype) {\n  if ((isTypedArray(value) && dtype !== \"string\" || Array.isArray(value)) && dtype !== \"complex64\") {\n    throw new Error(\"Error creating a new Scalar: value must be a primitive (number|boolean|string)\");\n  }\n  if (dtype === \"string\" && isTypedArray(value) && !(value instanceof Uint8Array)) {\n    throw new Error(\"When making a scalar from encoded string, the value must be `Uint8Array`.\");\n  }\n  const shape = [];\n  const inferredShape = [];\n  return makeTensor(value, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sqrt.js\nfunction sqrt_(x) {\n  const $x = convertToTensor(x, \"x\", \"sqrt\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Sqrt, inputs);\n}\nvar sqrt = op({ sqrt_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/square.js\nfunction square_(x) {\n  const $x = convertToTensor(x, \"x\", \"square\");\n  const attrs = {};\n  return ENGINE.runKernel(\"Square\", { x: $x }, attrs);\n}\nvar square = op({ square_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sum.js\nfunction sum_(x, axis = null, keepDims = false) {\n  let $x = convertToTensor(x, \"x\", \"sum\");\n  if ($x.dtype === \"bool\") {\n    $x = cast($x, \"int32\");\n  }\n  const inputs = { x: $x };\n  const attrs = { axis, keepDims };\n  return ENGINE.runKernel(Sum, inputs, attrs);\n}\nvar sum2 = op({ sum_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/norm.js\nfunction norm_(x, ord = \"euclidean\", axis = null, keepDims = false) {\n  x = convertToTensor(x, \"x\", \"norm\");\n  const norm2 = normImpl(x, ord, axis);\n  let keepDimsShape = norm2.shape;\n  if (keepDims) {\n    const axes = parseAxisParam(axis, x.shape);\n    keepDimsShape = expandShapeToKeepDim(norm2.shape, axes);\n  }\n  return reshape(norm2, keepDimsShape);\n}\nfunction normImpl(x, p2, axis = null) {\n  if (x.rank === 0) {\n    return abs(x);\n  }\n  if (x.rank !== 1 && axis === null) {\n    return normImpl(reshape(x, [-1]), p2, axis);\n  }\n  if (x.rank === 1 || typeof axis === \"number\" || Array.isArray(axis) && axis.length === 1) {\n    if (p2 === 1) {\n      return sum2(abs(x), axis);\n    }\n    if (p2 === Infinity) {\n      return max(abs(x), axis);\n    }\n    if (p2 === -Infinity) {\n      return min(abs(x), axis);\n    }\n    if (p2 === \"euclidean\" || p2 === 2) {\n      return sqrt(sum2(pow(abs(x), scalar(2, \"int32\")), axis));\n    }\n    throw new Error(`Error in norm: invalid ord value: ${p2}`);\n  }\n  if (Array.isArray(axis) && axis.length === 2) {\n    if (p2 === 1) {\n      return max(sum2(abs(x), axis[0]), axis[1] - 1);\n    }\n    if (p2 === Infinity) {\n      return max(sum2(abs(x), axis[1]), axis[0]);\n    }\n    if (p2 === -Infinity) {\n      return min(sum2(abs(x), axis[1]), axis[0]);\n    }\n    if (p2 === \"fro\" || p2 === \"euclidean\") {\n      return sqrt(sum2(square(x), axis));\n    }\n    throw new Error(`Error in norm: invalid ord value: ${p2}`);\n  }\n  throw new Error(`Error in norm: invalid axis: ${axis}`);\n}\nvar norm = op({ norm_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/euclidean_norm.js\nfunction euclideanNorm_(x, axis = null, keepDims = false) {\n  return norm(x, \"euclidean\", axis, keepDims);\n}\nvar euclideanNorm = op({ euclideanNorm_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/exp.js\nfunction exp_(x) {\n  const $x = convertToTensor(x, \"x\", \"exp\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Exp, inputs);\n}\nvar exp = op({ exp_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/expand_dims.js\nfunction expandDims_(x, axis = 0) {\n  const $x = convertToTensor(x, \"x\", \"expandDims\", \"string_or_numeric\");\n  assert(axis <= $x.rank, () => \"Axis must be <= rank of the tensor\");\n  const inputs = { input: $x };\n  const attrs = { dim: axis };\n  return ENGINE.runKernel(ExpandDims, inputs, attrs);\n}\nvar expandDims = op({ expandDims_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/expm1.js\nfunction expm1_(x) {\n  const $x = convertToTensor(x, \"x\", \"expm1\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Expm1, inputs);\n}\nvar expm1 = op({ expm1_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tile.js\nfunction tile_(x, reps) {\n  const $x = convertToTensor(x, \"x\", \"tile\", \"string_or_numeric\");\n  assert($x.rank === reps.length, () => `Error in transpose: rank of input ${$x.rank} must match length of reps ${reps}.`);\n  const inputs = { x: $x };\n  const attrs = { reps };\n  return ENGINE.runKernel(Tile, inputs, attrs);\n}\nvar tile = op({ tile_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/eye.js\nfunction eye_(numRows, numColumns, batchShape, dtype = \"float32\") {\n  if (numColumns == null) {\n    numColumns = numRows;\n  }\n  const buff = buffer([numRows, numColumns], dtype);\n  const n2 = numRows <= numColumns ? numRows : numColumns;\n  for (let i2 = 0; i2 < n2; ++i2) {\n    buff.set(1, i2, i2);\n  }\n  const out = reshape(buff.toTensor(), [numRows, numColumns]);\n  if (batchShape == null) {\n    return out;\n  } else {\n    if (batchShape.length === 1) {\n      return tile(expandDims(out, 0), [batchShape[0], 1, 1]);\n    } else if (batchShape.length === 2) {\n      return tile(expandDims(expandDims(out, 0), 0), [batchShape[0], batchShape[1], 1, 1]);\n    } else if (batchShape.length === 3) {\n      return tile(expandDims(expandDims(expandDims(out, 0), 0), 0), [\n        batchShape[0],\n        batchShape[1],\n        batchShape[2],\n        1,\n        1\n      ]);\n    } else {\n      throw new Error(`eye() currently supports only 1D and 2D batchShapes, but received ${batchShape.length}D.`);\n    }\n  }\n}\nvar eye = op({ eye_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/fill.js\nfunction fill(shape, value, dtype) {\n  const attrs = { shape, value, dtype };\n  return ENGINE.runKernel(Fill, {}, attrs);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/floor.js\nfunction floor_(x) {\n  const $x = convertToTensor(x, \"x\", \"floor\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Floor, inputs);\n}\nvar floor = op({ floor_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/gather.js\nfunction gather_(x, indices, axis = 0, batchDims = 0) {\n  const $x = convertToTensor(x, \"x\", \"gather\");\n  const $indices = convertToTensor(indices, \"indices\", \"gather\", \"int32\");\n  const inputs = { x: $x, indices: $indices };\n  const attrs = { axis, batchDims };\n  return ENGINE.runKernel(GatherV2, inputs, attrs);\n}\nvar gather = op({ gather_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/greater.js\nfunction greater_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"greater\", \"string_or_numeric\");\n  let $b = convertToTensor(b, \"b\", \"greater\", \"string_or_numeric\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Greater, inputs);\n}\nvar greater = op({ greater_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/greater_equal.js\nfunction greaterEqual_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"greaterEqual\", \"string_or_numeric\");\n  let $b = convertToTensor(b, \"b\", \"greaterEqual\", \"string_or_numeric\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(GreaterEqual, inputs);\n}\nvar greaterEqual = op({ greaterEqual_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/is_finite.js\nfunction isFinite_(x) {\n  const $x = convertToTensor(x, \"x\", \"isFinite\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(IsFinite, inputs);\n}\nvar isFinite2 = op({ isFinite_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/is_inf.js\nfunction isInf_(x) {\n  const $x = convertToTensor(x, \"x\", \"isInf\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(IsInf, inputs);\n}\nvar isInf = op({ isInf_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/is_nan.js\nfunction isNaN_(x) {\n  const $x = convertToTensor(x, \"x\", \"isNaN\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(IsNan, inputs);\n}\nvar isNaN2 = op({ isNaN_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/leaky_relu.js\nfunction leakyRelu_(x, alpha = 0.2) {\n  const $x = convertToTensor(x, \"x\", \"leakyRelu\");\n  const inputs = { x: $x };\n  const attrs = { alpha };\n  return ENGINE.runKernel(LeakyRelu, inputs, attrs);\n}\nvar leakyRelu = op({ leakyRelu_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/less.js\nfunction less_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"less\", \"string_or_numeric\");\n  let $b = convertToTensor(b, \"b\", \"less\", \"string_or_numeric\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Less, inputs);\n}\nvar less = op({ less_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/less_equal.js\nfunction lessEqual_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"lessEqual\", \"string_or_numeric\");\n  let $b = convertToTensor(b, \"b\", \"lessEqual\", \"string_or_numeric\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(LessEqual, inputs);\n}\nvar lessEqual = op({ lessEqual_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/linspace.js\nfunction linspace(start, stop, num) {\n  if (num <= 0) {\n    throw new Error(\"The number of values should be positive.\");\n  }\n  const attrs = { start, stop, num };\n  return ENGINE.runKernel(LinSpace, {}, attrs);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/local_response_normalization.js\nfunction localResponseNormalization_(x, depthRadius = 5, bias = 1, alpha = 1, beta = 0.5) {\n  const $x = convertToTensor(x, \"x\", \"localResponseNormalization\");\n  assert($x.rank === 4 || $x.rank === 3, () => `Error in localResponseNormalization: x must be rank 3 or 4 but got\n               rank ${$x.rank}.`);\n  assert(isInt(depthRadius), () => `Error in localResponseNormalization: depthRadius must be an integer but got depthRadius ${depthRadius}.`);\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  const inputs = { x: x4D };\n  const attrs = { depthRadius, bias, alpha, beta };\n  const res = ENGINE.runKernel(LRN, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  } else {\n    return res;\n  }\n}\nvar localResponseNormalization = op({ localResponseNormalization_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/log.js\nfunction log_(x) {\n  const $x = convertToTensor(x, \"x\", \"log\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Log, inputs);\n}\nvar log2 = op({ log_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/log1p.js\nfunction log1p_(x) {\n  const $x = convertToTensor(x, \"x\", \"log1p\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Log1p, inputs);\n}\nvar log1p = op({ log1p_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients.js\nfunction grad(f) {\n  assert(isFunction(f), () => \"The f passed in grad(f) must be a function\");\n  return (x, dy) => {\n    const $x = convertToTensor(x, \"x\", \"tf.grad\", \"string_or_numeric\");\n    const $dy = dy != null ? convertToTensor(dy, \"dy\", \"tf.grad\") : null;\n    return ENGINE.tidy(() => {\n      const { value, grads: grads2 } = ENGINE.gradients(() => f($x), [$x], $dy);\n      if ($dy != null) {\n        assertShapesMatch(value.shape, $dy.shape, \"The shape of dy passed in grad(f)(x, dy) must match the shape returned by f(x)\");\n      }\n      checkGrads(grads2);\n      return grads2[0];\n    });\n  };\n}\nfunction grads(f) {\n  assert(isFunction(f), () => \"The f passed in grads(f) must be a function\");\n  return (args, dy) => {\n    assert(Array.isArray(args), () => \"The args passed in grads(f)(args) must be an array of `Tensor`s or `TensorLike`s\");\n    const $args = convertToTensorArray(args, \"args\", \"tf.grads\", \"string_or_numeric\");\n    const $dy = dy != null ? convertToTensor(dy, \"dy\", \"tf.grads\") : null;\n    return ENGINE.tidy(() => {\n      const { value, grads: grads2 } = ENGINE.gradients(() => f(...$args), $args, $dy);\n      if ($dy != null) {\n        assertShapesMatch(value.shape, $dy.shape, \"The shape of dy passed in grads(f)([x1,...], dy) must match the shape returned by f([x1,...])\");\n      }\n      checkGrads(grads2);\n      return grads2;\n    });\n  };\n}\nfunction valueAndGrad(f) {\n  assert(isFunction(f), () => \"The f passed in valueAndGrad(f) must be a function\");\n  return (x, dy) => {\n    assert(x instanceof Tensor, () => \"The x passed in valueAndGrad(f)(x) must be a tensor\");\n    assert(dy == null || dy instanceof Tensor, () => \"The dy passed in valueAndGrad(f)(x, dy) must be a tensor\");\n    const { grads: grads2, value } = ENGINE.gradients(() => f(x), [x], dy);\n    checkGrads(grads2);\n    return { grad: grads2[0], value };\n  };\n}\nfunction valueAndGrads(f) {\n  assert(isFunction(f), () => \"The f passed in valueAndGrads(f) must be a function\");\n  return (args, dy) => {\n    assert(Array.isArray(args) && args.every((arg) => arg instanceof Tensor), () => \"The args passed in valueAndGrads(f)(args) must be array of tensors\");\n    assert(dy == null || dy instanceof Tensor, () => \"The dy passed in valueAndGrads(f)(args, dy) must be a tensor\");\n    const res = ENGINE.gradients(() => f(...args), args, dy);\n    if (dy != null) {\n      assertShapesMatch(res.value.shape, dy.shape, \"The shape of dy passed in valueAndGrads(f)([x1,...], dy) must match the shape returned by f([x1,...])\");\n    }\n    checkGrads(res.grads);\n    return res;\n  };\n}\nfunction variableGrads(f, varList) {\n  assert(isFunction(f), () => \"The f passed in variableGrads(f) must be a function\");\n  assert(varList == null || Array.isArray(varList) && varList.every((v) => v instanceof Variable), () => \"The varList passed in variableGrads(f, varList) must be an array of variables\");\n  const specifiedVarList = varList != null;\n  if (!specifiedVarList) {\n    varList = [];\n    for (const varName in ENGINE.registeredVariables) {\n      varList.push(ENGINE.registeredVariables[varName]);\n    }\n  }\n  const specifiedNonTrainable = specifiedVarList ? varList.filter((variable2) => !variable2.trainable) : null;\n  const originalVarCount = varList.length;\n  varList = varList.filter((variable2) => variable2.trainable);\n  assert(varList.length > 0, () => `variableGrads() expects at least one of the input variables to be trainable, but none of the ${originalVarCount} variables is trainable.`);\n  const allowNoGradients = true;\n  const { value, grads: grads2 } = ENGINE.gradients(f, varList, null, allowNoGradients);\n  assert(grads2.some((g) => g != null), () => \"Cannot find a connection between any variable and the result of the loss function y=f(x). Please make sure the operations that use variables are inside the function f passed to minimize().\");\n  assert(value.rank === 0, () => `The f passed in variableGrads(f) must return a scalar, but it returned a rank-${value.rank} tensor`);\n  const namedGrads = {};\n  varList.forEach((v, i2) => {\n    if (grads2[i2] != null) {\n      namedGrads[v.name] = grads2[i2];\n    }\n  });\n  if (specifiedNonTrainable != null) {\n    specifiedNonTrainable.forEach((v) => namedGrads[v.name] = null);\n  }\n  return { value, grads: namedGrads };\n}\nfunction customGrad(f) {\n  return ENGINE.customGrad(f);\n}\nfunction checkGrads(grads2) {\n  const numNullGradients = grads2.filter((g) => g == null).length;\n  if (numNullGradients > 0) {\n    throw new Error(`Cannot compute gradient of y=f(x) with respect to x. Make sure that\n    the f you passed encloses all operations that lead from x to y.`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/softplus.js\nfunction softplus_(x) {\n  const $x = convertToTensor(x, \"x\", \"softplus\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Softplus, inputs);\n}\nvar softplus = op({ softplus_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/log_sigmoid.js\nfunction logSigmoid_(x) {\n  const $x = convertToTensor(x, \"x\", \"logSigmoid\");\n  const customOp = customGrad((x2) => {\n    const value = neg(softplus(neg(x2)));\n    const gradFunc = (dy) => {\n      const derX = mul(dy, sigmoid(neg(x2)));\n      return derX;\n    };\n    return { value, gradFunc };\n  });\n  return customOp($x);\n}\nvar logSigmoid = op({ logSigmoid_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sub.js\nfunction sub_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"sub\");\n  let $b = convertToTensor(b, \"b\", \"sub\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Sub, inputs);\n}\nvar sub = op({ sub_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/log_softmax.js\nfunction logSoftmax_(logits, axis = -1) {\n  const $logits = convertToTensor(logits, \"logits\", \"logSoftmax\");\n  if (axis === -1) {\n    axis = $logits.rank - 1;\n  }\n  if (axis !== $logits.rank - 1) {\n    throw Error(`Log Softmax along a non-last dimension is not yet supported. Logits was rank ${$logits.rank} and axis was ${axis}`);\n  }\n  const customOp = customGrad((logits2, save) => {\n    const keepDims = true;\n    const xMax = max(logits2, axis, true);\n    const shifted = sub(logits2, xMax);\n    const value = sub(cast(shifted, \"float32\"), log2(sum2(exp(shifted), axis, keepDims)));\n    save([value]);\n    const gradFunc = (dy, saved) => {\n      const [value2] = saved;\n      const keepDims2 = true;\n      const softmax7 = exp(value2);\n      return sub(dy, mul(sum2(dy, axis, keepDims2), softmax7));\n    };\n    return { value, gradFunc };\n  });\n  return customOp($logits);\n}\nvar logSoftmax = op({ logSoftmax_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/log_sum_exp.js\nfunction logSumExp_(x, axis = null, keepDims = false) {\n  const $x = convertToTensor(x, \"x\", \"logSumExp\");\n  const axes = parseAxisParam(axis, $x.shape);\n  const xMax = max($x, axes, true);\n  const a = sub($x, xMax);\n  const b = exp(a);\n  const c = sum2(b, axes);\n  const d = log2(c);\n  const res = add2(reshape(xMax, d.shape), d);\n  if (keepDims) {\n    const newShape = expandShapeToKeepDim(res.shape, axes);\n    return reshape(res, newShape);\n  }\n  return res;\n}\nvar logSumExp = op({ logSumExp_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/logical_and.js\nfunction logicalAnd_(a, b) {\n  const $a = convertToTensor(a, \"a\", \"logicalAnd\", \"bool\");\n  const $b = convertToTensor(b, \"b\", \"logicalAnd\", \"bool\");\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(LogicalAnd, inputs);\n}\nvar logicalAnd = op({ logicalAnd_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/logical_not.js\nfunction logicalNot_(x) {\n  const $x = convertToTensor(x, \"x\", \"logicalNot\", \"bool\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(LogicalNot, inputs);\n}\nvar logicalNot = op({ logicalNot_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/logical_or.js\nfunction logicalOr_(a, b) {\n  const $a = convertToTensor(a, \"a\", \"logicalOr\", \"bool\");\n  const $b = convertToTensor(b, \"b\", \"logicalOr\", \"bool\");\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(LogicalOr, inputs);\n}\nvar logicalOr = op({ logicalOr_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/logical_xor.js\nfunction logicalXor_(a, b) {\n  const $a = convertToTensor(a, \"a\", \"logicalXor\", \"bool\");\n  const $b = convertToTensor(b, \"b\", \"logicalXor\", \"bool\");\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  return logicalAnd(logicalOr(a, b), logicalNot(logicalAnd(a, b)));\n}\nvar logicalXor = op({ logicalXor_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/search_sorted.js\nvar INT32_MAX = 2147483648;\nfunction searchSorted_(sortedSequence, values, side = \"left\") {\n  const $sortedSequence = convertToTensor(sortedSequence, \"sortedSequence\", \"searchSorted\");\n  const $values = convertToTensor(values, \"values\", \"searchSorted\");\n  const sequenceSize = $sortedSequence.shape[$sortedSequence.shape.length - 1];\n  const valuesSize = $values.shape[$values.shape.length - 1];\n  const $sortedSequence2D = reshape($sortedSequence, [-1, sequenceSize]);\n  const $values2D = reshape($values, [-1, valuesSize]);\n  if ($sortedSequence2D.rank < 2) {\n    throw new Error(`Sorted input argument must be at least 2-dimensional`);\n  }\n  if ($sortedSequence2D.shape[0] !== $values2D.shape[0]) {\n    throw new Error(`Leading dimension of 'sortedSequence' and 'values' must match.`);\n  }\n  if (sizeFromShape($values2D.shape) >= INT32_MAX) {\n    throw new Error(`values tensor size must less than ${INT32_MAX}`);\n  }\n  if ($sortedSequence2D.shape[1] >= INT32_MAX) {\n    throw new Error(`trailing dim_size must less than ${INT32_MAX} for int32 output type, was ${$sortedSequence2D.shape[1]}`);\n  }\n  const inputs = {\n    sortedSequence: $sortedSequence2D,\n    values: $values2D\n  };\n  const attrs = { side };\n  return ENGINE.runKernel(SearchSorted, inputs, attrs);\n}\nvar searchSorted = op({ searchSorted_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/lower_bound.js\nfunction lowerBound(sortedSequence, values) {\n  return searchSorted(sortedSequence, values, \"left\");\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/max_pool.js\nfunction maxPool_(x, filterSize, strides, pad3, dimRoundingMode) {\n  const $x = convertToTensor(x, \"x\", \"maxPool\");\n  const dilations = 1;\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  assert(x4D.rank === 4, () => `Error in maxPool: input must be rank 4 but got rank ${x4D.rank}.`);\n  assert(eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in maxPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  checkPadOnDimRoundingMode(\"maxPool\", pad3, dimRoundingMode);\n  const inputs = { x: x4D };\n  const attrs = { filterSize, strides, pad: pad3, dimRoundingMode };\n  const res = ENGINE.runKernel(MaxPool, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar maxPool = op({ maxPool_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_3d.js\nfunction maxPool3d_(x, filterSize = [1, 1, 1], strides, pad3, dimRoundingMode, dataFormat = \"NDHWC\") {\n  const $x = convertToTensor(x, \"x\", \"maxPool3d\");\n  let x5D = $x;\n  let reshapedTo5D = false;\n  if ($x.rank === 4) {\n    reshapedTo5D = true;\n    x5D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]]);\n  }\n  assert(x5D.rank === 5, () => `Error in maxPool3d: x must be rank 5 but got rank ${x5D.rank}.`);\n  assert(dataFormat === \"NDHWC\", () => `Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of ${dataFormat}`);\n  checkPadOnDimRoundingMode(\"maxPool3d\", pad3, dimRoundingMode);\n  const inputs = { x: x5D };\n  const attrs = { filterSize, strides, pad: pad3, dimRoundingMode, dataFormat };\n  const res = ENGINE.runKernel(MaxPool3D, inputs, attrs);\n  if (reshapedTo5D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);\n  }\n  return res;\n}\nvar maxPool3d = op({ maxPool3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_with_argmax.js\nfunction maxPoolWithArgmax_(x, filterSize, strides, pad3, includeBatchInIndex = false) {\n  const $x = convertToTensor(x, \"x\", \"maxPoolWithArgmax\");\n  const inputs = { x: $x };\n  const attrs = { filterSize, strides, pad: pad3, includeBatchInIndex };\n  const result = ENGINE.runKernel(MaxPoolWithArgmax, inputs, attrs);\n  return { result: result[0], indexes: result[1] };\n}\nvar maxPoolWithArgmax = op({ maxPoolWithArgmax_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/maximum.js\nfunction maximum_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"maximum\");\n  let $b = convertToTensor(b, \"b\", \"maximum\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  if ($a.dtype === \"bool\") {\n    $a = cast($a, \"int32\");\n    $b = cast($b, \"int32\");\n  }\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Maximum, inputs);\n}\nvar maximum = op({ maximum_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/mean.js\nfunction mean_(x, axis = null, keepDims = false) {\n  const $x = convertToTensor(x, \"x\", \"mean\");\n  const inputs = { x: $x };\n  const attrs = { axis, keepDims };\n  return ENGINE.runKernel(Mean, inputs, attrs);\n}\nvar mean = op({ mean_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/zeros.js\nfunction zeros(shape, dtype = \"float32\") {\n  if (dtype === \"complex64\") {\n    const real5 = zeros(shape, \"float32\");\n    const imag5 = zeros(shape, \"float32\");\n    return complex(real5, imag5);\n  }\n  const values = makeZerosTypedArray(sizeFromShape(shape), dtype);\n  return ENGINE.makeTensor(values, shape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/ones.js\nfunction ones2(shape, dtype = \"float32\") {\n  if (dtype === \"complex64\") {\n    const real5 = ones2(shape, \"float32\");\n    const imag5 = zeros(shape, \"float32\");\n    return complex(real5, imag5);\n  }\n  const values = makeOnesTypedArray(sizeFromShape(shape), dtype);\n  return ENGINE.makeTensor(values, shape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/meshgrid.js\nfunction meshgrid(x, y, { indexing = \"xy\" } = {}) {\n  if (indexing !== \"xy\" && indexing !== \"ij\") {\n    throw new TypeError(`${indexing} is not a valid third argument to meshgrid`);\n  }\n  if (x === void 0) {\n    return [];\n  }\n  let $x = convertToTensor(x, \"x\", \"meshgrid\", x instanceof Tensor ? x.dtype : \"float32\");\n  if (y === void 0) {\n    return [$x];\n  }\n  let $y = convertToTensor(y, \"y\", \"meshgrid\", y instanceof Tensor ? y.dtype : \"float32\");\n  const w = sizeFromShape($x.shape);\n  const h = sizeFromShape($y.shape);\n  if (indexing === \"xy\") {\n    $x = reshape($x, [1, -1]);\n    $y = reshape($y, [-1, 1]);\n    return [\n      matMul(ones2([h, 1], $x.dtype), $x),\n      matMul($y, ones2([1, w], $y.dtype))\n    ];\n  }\n  $x = reshape($x, [-1, 1]);\n  $y = reshape($y, [1, -1]);\n  return [\n    matMul($x, ones2([1, h], $x.dtype)),\n    matMul(ones2([w, 1], $y.dtype), $y)\n  ];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/minimum.js\nfunction minimum_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"minimum\");\n  let $b = convertToTensor(b, \"b\", \"minimum\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  if ($a.dtype === \"bool\") {\n    $a = cast($a, \"int32\");\n    $b = cast($b, \"int32\");\n  }\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Minimum, inputs);\n}\nvar minimum = op({ minimum_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/mirror_pad.js\nfunction mirrorPad_(x, paddings, mode) {\n  assert(mode === \"reflect\" || mode === \"symmetric\", () => `Invalid mode. Mode must be either reflect or symmetric. Got ${mode}.`);\n  const $x = convertToTensor(x, \"x\", \"mirrorPad\");\n  if ($x.rank === 0) {\n    throw new Error(\"mirrorPad(scalar) is not defined. Pass non-scalar to mirrorPad\");\n  }\n  assert(paddings.length === $x.rank, () => `Padding doesn't match input. Must be ${$x.rank}. Got ${paddings.length}.`);\n  const shapeOffset = mode === \"reflect\" ? 1 : 0;\n  for (let i2 = 0; i2 < $x.rank; i2++) {\n    assert(paddings[i2].length === 2, () => `Invalid number of paddings. Must be length of 2 each.`);\n    assert(paddings[i2][0] >= 0 && paddings[i2][0] <= $x.shape[i2] - shapeOffset && paddings[i2][1] >= 0 && paddings[i2][1] <= $x.shape[i2] - shapeOffset, () => `Padding in dimension ${i2} cannot be greater than or equal to ${$x.shape[i2] - shapeOffset} or less than 0 for input of shape ${$x.shape}`);\n  }\n  const attrs = { paddings, mode };\n  const inputs = { x: $x };\n  return ENGINE.runKernel(MirrorPad, inputs, attrs);\n}\nvar mirrorPad = op({ mirrorPad_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/mod.js\nfunction mod_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"mod\");\n  let $b = convertToTensor(b, \"b\", \"mod\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Mod, inputs);\n}\nvar mod = op({ mod_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/moments.js\nfunction moments_(x, axis = null, keepDims = false) {\n  x = convertToTensor(x, \"x\", \"moments\");\n  const axes = parseAxisParam(axis, x.shape);\n  const xMean = mean(x, axes, keepDims);\n  let keepDimsShape = xMean.shape;\n  if (!keepDims) {\n    keepDimsShape = expandShapeToKeepDim(xMean.shape, axes);\n  }\n  const devSquared = square(sub(cast(x, \"float32\"), reshape(xMean, keepDimsShape)));\n  const variance = mean(devSquared, axes, keepDims);\n  return { mean: xMean, variance };\n}\nvar moments = op({ moments_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/multi_rnn_cell.js\nfunction multiRNNCell_(lstmCells, data, c, h) {\n  const $data = convertToTensor(data, \"data\", \"multiRNNCell\");\n  const $c = convertToTensorArray(c, \"c\", \"multiRNNCell\");\n  const $h = convertToTensorArray(h, \"h\", \"multiRNNCell\");\n  let input2 = $data;\n  const newStates = [];\n  for (let i2 = 0; i2 < lstmCells.length; i2++) {\n    const output = lstmCells[i2](input2, $c[i2], $h[i2]);\n    newStates.push(output[0]);\n    newStates.push(output[1]);\n    input2 = output[1];\n  }\n  const newC = [];\n  const newH = [];\n  for (let i2 = 0; i2 < newStates.length; i2 += 2) {\n    newC.push(newStates[i2]);\n    newH.push(newStates[i2 + 1]);\n  }\n  return [newC, newH];\n}\nvar multiRNNCell = op({ multiRNNCell_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/multinomial.js\nfunction multinomial_(logits, numSamples, seed, normalized = false) {\n  const $logits = convertToTensor(logits, \"logits\", \"multinomial\");\n  const numOutcomes = $logits.size;\n  const origRank = $logits.rank;\n  if (numOutcomes < 2) {\n    throw new Error(`Error in multinomial: you need at least 2 outcomes, but got ${numOutcomes}.`);\n  }\n  if (origRank > 2) {\n    throw new Error(`Rank of probabilities must be 1 or 2, but is ${origRank}`);\n  }\n  seed = seed || Math.random();\n  const logits2D = origRank === 1 ? reshape($logits, [1, -1]) : $logits;\n  const inputs = { logits: logits2D };\n  const attrs = { numSamples, seed, normalized };\n  const res = ENGINE.runKernel(Multinomial, inputs, attrs);\n  return origRank === 1 ? reshape(res, [res.size]) : res;\n}\nvar multinomial = op({ multinomial_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/not_equal.js\nfunction notEqual_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"notEqual\", \"string_or_numeric\");\n  let $b = convertToTensor(b, \"b\", \"notEqual\", \"string_or_numeric\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(NotEqual, inputs);\n}\nvar notEqual = op({ notEqual_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/ones_like.js\nfunction onesLike_(x) {\n  const $x = convertToTensor(x, \"x\", \"onesLike\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(OnesLike, inputs);\n}\nvar onesLike = op({ onesLike_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/outer_product.js\nfunction outerProduct_(v1, v2) {\n  const $v1 = convertToTensor(v1, \"v1\", \"outerProduct\");\n  const $v2 = convertToTensor(v2, \"v2\", \"outerProduct\");\n  assert($v1.rank === 1 && $v2.rank === 1, () => `Error in outerProduct: inputs must be rank 1, but got ranks ${$v1.rank} and ${$v2.rank}.`);\n  const v12D = reshape($v1, [-1, 1]);\n  const v22D = reshape($v2, [1, -1]);\n  return matMul(v12D, v22D);\n}\nvar outerProduct = op({ outerProduct_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/pad.js\nfunction pad_(x, paddings, constantValue = 0) {\n  const $x = convertToTensor(x, \"x\", \"pad\");\n  if ($x.rank === 0) {\n    throw new Error(\"pad(scalar) is not defined. Pass non-scalar to pad\");\n  }\n  const attrs = { paddings, constantValue };\n  const inputs = { x: $x };\n  return ENGINE.runKernel(PadV2, inputs, attrs);\n}\nvar pad = op({ pad_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/pad1d.js\nfunction pad1d_(x, paddings, constantValue = 0) {\n  assert(paddings.length === 2, () => \"Invalid number of paddings. Must be length of 2.\");\n  return pad(x, [paddings], constantValue);\n}\nvar pad1d = op({ pad1d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/pad2d.js\nfunction pad2d_(x, paddings, constantValue = 0) {\n  assert(paddings.length === 2 && paddings[0].length === 2 && paddings[1].length === 2, () => \"Invalid number of paddings. Must be length of 2 each.\");\n  return pad(x, paddings, constantValue);\n}\nvar pad2d = op({ pad2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/pad3d.js\nfunction pad3d_(x, paddings, constantValue = 0) {\n  assert(paddings.length === 3 && paddings[0].length === 2 && paddings[1].length === 2 && paddings[2].length === 2, () => \"Invalid number of paddings. Must be length of 2 each.\");\n  return pad(x, paddings, constantValue);\n}\nvar pad3d = op({ pad3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/pad4d.js\nfunction pad4d_(x, paddings, constantValue = 0) {\n  assert(paddings.length === 4 && paddings[0].length === 2 && paddings[1].length === 2 && paddings[2].length === 2 && paddings[3].length === 2, () => \"Invalid number of paddings. Must be length of 2 each.\");\n  return pad(x, paddings, constantValue);\n}\nvar pad4d = op({ pad4d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/space_to_batch_nd.js\nfunction spaceToBatchND_(x, blockShape, paddings) {\n  const $x = convertToTensor(x, \"x\", \"spaceToBatchND\");\n  assert($x.rank >= 1 + blockShape.length, () => `input rank ${$x.rank} should be > than [blockShape] ${blockShape.length}`);\n  assert(paddings.length === blockShape.length, () => `paddings.shape[0] ${paddings.length} must be equal to [blockShape] ${blockShape.length}`);\n  assert($x.shape.reduce((a, b, i2) => {\n    if (i2 > 0 && i2 <= blockShape.length) {\n      return a && (b + paddings[i2 - 1][0] + paddings[i2 - 1][1]) % blockShape[i2 - 1] === 0;\n    }\n    return a;\n  }, true), () => `input spatial dimensions ${$x.shape.slice(1)} with paddings ${paddings.toString()} must be divisible by blockShapes ${blockShape.toString()}`);\n  const inputs = { x: $x };\n  const attrs = { blockShape, paddings };\n  return ENGINE.runKernel(SpaceToBatchND, inputs, attrs);\n}\nvar spaceToBatchND = op({ spaceToBatchND_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/pool.js\nfunction pool_(input2, windowShape, poolingType, pad3, dilations, strides, dimRoundingMode) {\n  if (dilations == null) {\n    dilations = [1, 1];\n  }\n  if (strides == null) {\n    strides = 1;\n  }\n  if (pad3 === 0) {\n    pad3 = \"valid\";\n  }\n  const $x = convertToTensor(input2, \"x\", \"maxPool\");\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  assert(eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in pool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  const convInfo = computePool2DInfo(x4D.shape, windowShape, strides, dilations, pad3);\n  const dilation = [convInfo.dilationHeight, convInfo.dilationWidth];\n  let basePadding;\n  if (pad3 === \"same\") {\n    basePadding = withSpaceToBatchBasePaddings([convInfo.filterHeight, convInfo.filterWidth], dilation);\n  } else {\n    basePadding = [[0, 0], [0, 0]];\n  }\n  const isDilationOne = dilation[0] === 1 && dilation[1] === 1;\n  const [adjustedPadding, adjustedCrops] = requiredSpaceToBatchPaddings([convInfo.inHeight, convInfo.inWidth], dilation, basePadding);\n  const convertedPad = isDilationOne ? pad3 : \"valid\";\n  const convertedX = isDilationOne ? x4D : spaceToBatchND(x4D, dilation, adjustedPadding);\n  const forwardOp = poolingType === \"avg\" ? () => avgPool(convertedX, windowShape, strides, convertedPad, dimRoundingMode) : () => maxPool(convertedX, windowShape, strides, convertedPad, dimRoundingMode);\n  const y = forwardOp();\n  const res = isDilationOne ? y : batchToSpaceND(y, dilation, adjustedCrops);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nfunction requiredSpaceToBatchPaddings(inputShape, blockShape, basePadding) {\n  const padStart = basePadding.map((b) => b[0]);\n  const origPadEnd = basePadding.map((b) => b[1]);\n  const fullInputShape = inputShape.concat(padStart, origPadEnd);\n  const padEndExtra = blockShape.map((b, i2) => (b - fullInputShape[i2] % b) % b);\n  const padEnd = origPadEnd.map((s2, i2) => s2 + padEndExtra[i2]);\n  const paddings = blockShape.map((_, i2) => [padStart[i2], padEnd[i2]]);\n  const crops = blockShape.map((_, i2) => [0, padEndExtra[i2]]);\n  return [paddings, crops];\n}\nfunction withSpaceToBatchBasePaddings(filterShape, dilation) {\n  const dilatedFilterShape = filterShape.map((s2, i2) => {\n    return s2 + (s2 - 1) * (dilation[i2] - 1);\n  });\n  const padExtraShape = dilatedFilterShape.map((s2) => s2 - 1);\n  const padExtraStart = padExtraShape.map((s2) => Math.floor(s2 / 2));\n  const padExtraEnd = padExtraShape.map((s2, i2) => s2 - padExtraStart[i2]);\n  return padExtraShape.map((_, i2) => {\n    return [padExtraStart[i2], padExtraEnd[i2]];\n  });\n}\nvar pool = op({ pool_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/prelu.js\nfunction prelu_(x, alpha) {\n  const $x = convertToTensor(x, \"x\", \"prelu\");\n  const $alpha = convertToTensor(alpha, \"alpha\", \"prelu\");\n  const inputs = { x: $x, alpha: $alpha };\n  return ENGINE.runKernel(Prelu, inputs);\n}\nvar prelu = op({ prelu_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/prod.js\nfunction prod_(x, axis = null, keepDims = false) {\n  let $x = convertToTensor(x, \"x\", \"prod\");\n  if ($x.dtype === \"bool\") {\n    $x = cast($x, \"int32\");\n  }\n  const inputs = { x: $x };\n  const attrs = { axis, keepDims };\n  return ENGINE.runKernel(Prod, inputs, attrs);\n}\nvar prod = op({ prod_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/rand.js\nfunction rand_(shape, randFunction, dtype) {\n  const size = sizeFromShape(shape);\n  let values = null;\n  if (dtype == null || dtype === \"float32\") {\n    values = new Float32Array(size);\n  } else if (dtype === \"int32\") {\n    values = new Int32Array(size);\n  } else if (dtype === \"bool\") {\n    values = new Uint8Array(size);\n  } else {\n    throw new Error(`Unknown data type ${dtype}`);\n  }\n  for (let i2 = 0; i2 < size; i2++) {\n    values[i2] = randFunction();\n  }\n  return ENGINE.makeTensor(values, shape, dtype);\n}\nvar rand = op({ rand_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/rand_util.js\nvar seedrandom = __toESM(require_seedrandom2());\nvar MPRandGauss = class {\n  constructor(mean5, stdDeviation, dtype, truncated, seed) {\n    this.mean = mean5;\n    this.stdDev = stdDeviation;\n    this.dtype = dtype;\n    this.nextVal = NaN;\n    this.truncated = truncated;\n    if (this.truncated) {\n      this.upper = this.mean + this.stdDev * 2;\n      this.lower = this.mean - this.stdDev * 2;\n    }\n    const seedValue = seed ? seed : Math.random();\n    this.random = seedrandom.alea(seedValue.toString());\n  }\n  nextValue() {\n    if (!isNaN(this.nextVal)) {\n      const value = this.nextVal;\n      this.nextVal = NaN;\n      return value;\n    }\n    let resultX, resultY;\n    let isValid = false;\n    while (!isValid) {\n      let v1, v2, s2;\n      do {\n        v1 = 2 * this.random() - 1;\n        v2 = 2 * this.random() - 1;\n        s2 = v1 * v1 + v2 * v2;\n      } while (s2 >= 1 || s2 === 0);\n      const mul2 = Math.sqrt(-2 * Math.log(s2) / s2);\n      resultX = this.mean + this.stdDev * v1 * mul2;\n      resultY = this.mean + this.stdDev * v2 * mul2;\n      if (!this.truncated || this.isValidTruncated(resultX)) {\n        isValid = true;\n      }\n    }\n    if (!this.truncated || this.isValidTruncated(resultY)) {\n      this.nextVal = this.convertValue(resultY);\n    }\n    return this.convertValue(resultX);\n  }\n  convertValue(value) {\n    if (this.dtype == null || this.dtype === \"float32\") {\n      return value;\n    }\n    return Math.round(value);\n  }\n  isValidTruncated(value) {\n    return value <= this.upper && value >= this.lower;\n  }\n};\nvar RandGamma = class {\n  constructor(alpha, beta, dtype, seed) {\n    this.alpha = alpha;\n    this.beta = 1 / beta;\n    this.dtype = dtype;\n    const seedValue = seed ? seed : Math.random();\n    this.randu = seedrandom.alea(seedValue.toString());\n    this.randn = new MPRandGauss(0, 1, dtype, false, this.randu());\n    if (alpha < 1) {\n      this.d = alpha + 2 / 3;\n    } else {\n      this.d = alpha - 1 / 3;\n    }\n    this.c = 1 / Math.sqrt(9 * this.d);\n  }\n  nextValue() {\n    let x2, v0, v1, x, u, v;\n    while (true) {\n      do {\n        x = this.randn.nextValue();\n        v = 1 + this.c * x;\n      } while (v <= 0);\n      v *= v * v;\n      x2 = x * x;\n      v0 = 1 - 0.331 * x2 * x2;\n      v1 = 0.5 * x2 + this.d * (1 - v + Math.log(v));\n      u = this.randu();\n      if (u < v0 || Math.log(u) < v1) {\n        break;\n      }\n    }\n    v = 1 / this.beta * this.d * v;\n    if (this.alpha < 1) {\n      v *= Math.pow(this.randu(), 1 / this.alpha);\n    }\n    return this.convertValue(v);\n  }\n  convertValue(value) {\n    if (this.dtype === \"float32\") {\n      return value;\n    }\n    return Math.round(value);\n  }\n};\nvar UniformRandom = class {\n  constructor(min7 = 0, max7 = 1, dtype, seed) {\n    this.canReturnFloat = () => this.dtype == null || this.dtype === \"float32\";\n    this.min = min7;\n    this.range = max7 - min7;\n    this.dtype = dtype;\n    if (seed == null) {\n      seed = Math.random();\n    }\n    if (typeof seed === \"number\") {\n      seed = seed.toString();\n    }\n    if (!this.canReturnFloat() && this.range <= 1) {\n      throw new Error(`The difference between ${min7} - ${max7} <= 1 and dtype is not float`);\n    }\n    this.random = seedrandom.alea(seed);\n  }\n  convertValue(value) {\n    if (this.canReturnFloat()) {\n      return value;\n    }\n    return Math.round(value);\n  }\n  nextValue() {\n    return this.convertValue(this.min + this.range * this.random());\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/random_gamma.js\nfunction randomGamma_(shape, alpha, beta = 1, dtype = \"float32\", seed) {\n  if (beta == null) {\n    beta = 1;\n  }\n  if (dtype == null) {\n    dtype = \"float32\";\n  }\n  if (dtype !== \"float32\" && dtype !== \"int32\") {\n    throw new Error(`Unsupported data type ${dtype}`);\n  }\n  const rgamma = new RandGamma(alpha, beta, dtype, seed);\n  const res = buffer(shape, dtype);\n  for (let i2 = 0; i2 < res.values.length; i2++) {\n    res.values[i2] = rgamma.nextValue();\n  }\n  return res.toTensor();\n}\nvar randomGamma = op({ randomGamma_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/random_normal.js\nfunction randomNormal_(shape, mean5 = 0, stdDev = 1, dtype, seed) {\n  if (dtype != null && dtype === \"bool\") {\n    throw new Error(`Unsupported data type ${dtype}`);\n  }\n  const randGauss = new MPRandGauss(mean5, stdDev, dtype, false, seed);\n  const res = buffer(shape, dtype);\n  for (let i2 = 0; i2 < res.values.length; i2++) {\n    res.values[i2] = randGauss.nextValue();\n  }\n  return res.toTensor();\n}\nvar randomNormal = op({ randomNormal_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/random_standard_normal.js\nfunction randomStandardNormal_(shape, dtype, seed) {\n  if (dtype != null && dtype === \"bool\") {\n    throw new Error(`Unsupported data type ${dtype}`);\n  }\n  return randomNormal(shape, 0, 1, dtype, seed);\n}\nvar randomStandardNormal = op({ randomStandardNormal_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/random_uniform.js\nfunction randomUniform_(shape, minval = 0, maxval = 1, dtype = \"float32\", seed) {\n  const res = buffer(shape, dtype);\n  const random = new UniformRandom(minval, maxval, null, seed);\n  for (let i2 = 0; i2 < res.values.length; i2++) {\n    res.values[i2] = random.nextValue();\n  }\n  return res.toTensor();\n}\nvar randomUniform = op({ randomUniform_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/range.js\nfunction range(start, stop, step5 = 1, dtype = \"float32\") {\n  if (step5 === 0) {\n    throw new Error(\"Cannot have a step of zero\");\n  }\n  const attrs = { start, stop, step: step5, dtype };\n  return ENGINE.runKernel(Range, {}, attrs);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reciprocal.js\nfunction reciprocal_(x) {\n  const $x = convertToTensor(x, \"x\", \"reciprocal\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Reciprocal, inputs);\n}\nvar reciprocal = op({ reciprocal_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/relu.js\nfunction relu_(x) {\n  const $x = convertToTensor(x, \"x\", \"relu\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Relu, inputs);\n}\nvar relu = op({ relu_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/relu6.js\nfunction relu6_(x) {\n  const $x = convertToTensor(x, \"x\", \"relu6\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Relu6, inputs);\n}\nvar relu6 = op({ relu6_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reverse.js\nfunction reverse_(x, axis) {\n  const $x = convertToTensor(x, \"x\", \"reverse\");\n  const inputs = { x: $x };\n  const attrs = { dims: axis };\n  return ENGINE.runKernel(Reverse, inputs, attrs);\n}\nvar reverse = op({ reverse_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reverse_1d.js\nfunction reverse1d_(x) {\n  const $x = convertToTensor(x, \"x\", \"reverse\");\n  assert($x.rank === 1, () => `Error in reverse1D: x must be rank 1 but got rank ${$x.rank}.`);\n  return reverse($x, 0);\n}\nvar reverse1d = op({ reverse1d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reverse_2d.js\nfunction reverse2d_(x, axis) {\n  const $x = convertToTensor(x, \"x\", \"reverse\");\n  assert($x.rank === 2, () => `Error in reverse2D: x must be rank 2 but got rank ${$x.rank}.`);\n  return reverse($x, axis);\n}\nvar reverse2d = op({ reverse2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reverse_3d.js\nfunction reverse3d_(x, axis) {\n  const $x = convertToTensor(x, \"x\", \"reverse\");\n  assert($x.rank === 3, () => `Error in reverse3D: x must be rank 3 but got rank ${$x.rank}.`);\n  return reverse($x, axis);\n}\nvar reverse3d = op({ reverse3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reverse_4d.js\nfunction reverse4d_(x, axis) {\n  const $x = convertToTensor(x, \"x\", \"reverse\");\n  assert($x.rank === 4, () => `Error in reverse4D: x must be rank 4 but got rank ${$x.rank}.`);\n  return reverse($x, axis);\n}\nvar reverse4d = op({ reverse4d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/round.js\nfunction round_(x) {\n  const $x = convertToTensor(x, \"x\", \"round\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Round, inputs);\n}\nvar round2 = op({ round_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/rsqrt.js\nfunction rsqrt_(x) {\n  const $x = convertToTensor(x, \"x\", \"rsqrt\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Rsqrt, inputs);\n}\nvar rsqrt = op({ rsqrt_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/selu.js\nfunction selu_(x) {\n  const $x = convertToTensor(x, \"x\", \"selu\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Selu, inputs);\n}\nvar selu = op({ selu_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/separable_conv2d.js\nfunction separableConv2d_(x, depthwiseFilter, pointwiseFilter, strides, pad3, dilation = [1, 1], dataFormat = \"NHWC\") {\n  const $x = convertToTensor(x, \"x\", \"separableConv2d\");\n  const $depthwiseFilter = convertToTensor(depthwiseFilter, \"depthwiseFilter\", \"separableConv2d\");\n  const $pointwiseFilter = convertToTensor(pointwiseFilter, \"pointwiseFilter\", \"separableConv2d\");\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  if (dataFormat === \"NCHW\") {\n    throw new Error(\"separableConv2d currently does not support dataFormat NCHW; only NHWC is supported\");\n  }\n  assert(x4D.rank === 4, () => `Error in separableConv2d: input must be rank 4, but got rank ${x4D.rank}.`);\n  assert($depthwiseFilter.rank === 4, () => `Error in separableConv2d: depthwise filter must be rank 4, but got rank ${$depthwiseFilter.rank}.`);\n  assert($pointwiseFilter.rank === 4, () => `Error in separableConv2d: pointwise filter must be rank 4, but got rank ${$depthwiseFilter.rank}.`);\n  assert($pointwiseFilter.shape[0] === 1, () => `Error in separableConv2d: the first dimension of pointwise filter  must be 1, but got ${$pointwiseFilter.shape[0]}.`);\n  assert($pointwiseFilter.shape[1] === 1, () => `Error in separableConv2d: the second dimension of pointwise filter must be 1, but got ${$pointwiseFilter.shape[1]}.`);\n  const inChannels = $depthwiseFilter.shape[2];\n  const channelMultiplier = $depthwiseFilter.shape[3];\n  assert($pointwiseFilter.shape[2] === inChannels * channelMultiplier, () => `Error in separableConv2d: the third dimension of pointwise filter must be ${inChannels * channelMultiplier}, but got ${$pointwiseFilter.shape[2]}.`);\n  const depthwise = depthwiseConv2d(x4D, $depthwiseFilter, strides, pad3, dataFormat, dilation);\n  const pointwiseStride = 1;\n  const res = conv2d(depthwise, $pointwiseFilter, pointwiseStride, \"valid\", dataFormat);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar separableConv2d = op({ separableConv2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/setdiff1d_async.js\nasync function setdiff1dAsync_(x, y) {\n  const $x = convertToTensor(x, \"x\", \"setdiff1d\");\n  const $y = convertToTensor(y, \"y\", \"setdiff1d\");\n  assert($x.dtype === $y.dtype, () => `x and y should have the same dtype, but got x (${$x.dtype}) and y (${$y.dtype}).`);\n  assert($x.rank === 1, () => `x should be 1D tensor, but got x (${$x.shape}).`);\n  assert($y.rank === 1, () => `y should be 1D tensor, but got y (${$y.shape}).`);\n  const xVals = await $x.data();\n  const yVals = await $y.data();\n  const ySet = new Set(yVals);\n  let outputSize = 0;\n  for (let i2 = 0; i2 < xVals.length; i2++) {\n    if (!ySet.has(xVals[i2])) {\n      outputSize++;\n    }\n  }\n  const buffer2 = new TensorBuffer([outputSize], $x.dtype);\n  const indices = new TensorBuffer([outputSize], \"int32\");\n  for (let i2 = 0, p2 = 0; i2 < xVals.length; i2++) {\n    if (!ySet.has(xVals[i2])) {\n      buffer2.values[p2] = xVals[i2];\n      indices.values[p2] = i2;\n      p2++;\n    }\n  }\n  return [buffer2.toTensor(), indices.toTensor()];\n}\nvar setdiff1dAsync = setdiff1dAsync_;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sign.js\nfunction sign_(x) {\n  const $x = convertToTensor(x, \"x\", \"sign\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Sign, inputs);\n}\nvar sign = op({ sign_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sin.js\nfunction sin_(x) {\n  const $x = convertToTensor(x, \"x\", \"sin\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Sin, inputs);\n}\nvar sin = op({ sin_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sinh.js\nfunction sinh_(x) {\n  const $x = convertToTensor(x, \"x\", \"sinh\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Sinh, inputs);\n}\nvar sinh = op({ sinh_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/slice1d.js\nfunction slice1d_(x, begin, size) {\n  const $x = convertToTensor(x, \"x\", \"slice1d\");\n  assert($x.rank === 1, () => `slice1d expects a rank-1 tensor, but got a rank-${$x.rank} tensor`);\n  return slice($x, [begin], [size]);\n}\nvar slice1d = op({ slice1d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/slice2d.js\nfunction slice2d_(x, begin, size) {\n  const $x = convertToTensor(x, \"x\", \"slice2d\");\n  assert($x.rank === 2, () => `slice2d expects a rank-2 tensor, but got a rank-${$x.rank} tensor`);\n  return slice($x, begin, size);\n}\nvar slice2d = op({ slice2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/slice3d.js\nfunction slice3d_(x, begin, size) {\n  const $x = convertToTensor(x, \"x\", \"slice3d\");\n  assert($x.rank === 3, () => `slice3d expects a rank-3 tensor, but got a rank-${$x.rank} tensor`);\n  return slice($x, begin, size);\n}\nvar slice3d = op({ slice3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/slice4d.js\nfunction slice4d_(x, begin, size) {\n  const $x = convertToTensor(x, \"x\", \"slice4d\");\n  assert($x.rank === 4, () => `slice4d expects a rank-4 tensor, but got a rank-${$x.rank} tensor`);\n  return slice($x, begin, size);\n}\nvar slice4d = op({ slice4d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/softmax.js\nfunction softmax_(logits, dim = -1) {\n  const $logits = convertToTensor(logits, \"logits\", \"softmax\", \"float32\");\n  if (dim === -1) {\n    dim = $logits.rank - 1;\n  }\n  if (dim !== $logits.rank - 1) {\n    throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${$logits.rank} and dim was ${dim}`);\n  }\n  const inputs = { logits: $logits };\n  const attrs = { dim };\n  return ENGINE.runKernel(Softmax, inputs, attrs);\n}\nvar softmax = op({ softmax_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/spectral/fft.js\nfunction fft_(input2) {\n  assert(input2.dtype === \"complex64\", () => `The dtype for tf.spectral.fft() must be complex64 but got ${input2.dtype}.`);\n  const inputs = { input: input2 };\n  return ENGINE.runKernel(FFT, inputs);\n}\nvar fft = op({ fft_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/spectral/ifft.js\nfunction ifft_(input2) {\n  assert(input2.dtype === \"complex64\", () => `The dtype for tf.spectral.ifft() must be complex64 but got ${input2.dtype}.`);\n  const inputs = { input: input2 };\n  return ENGINE.runKernel(IFFT, inputs);\n}\nvar ifft = op({ ifft_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/spectral/irfft.js\nfunction irfft_(input2) {\n  const innerDimensionSize = input2.shape[input2.shape.length - 1];\n  const batch = input2.size / innerDimensionSize;\n  let ret;\n  if (innerDimensionSize <= 2) {\n    const complexInput = reshape(input2, [batch, innerDimensionSize]);\n    ret = ifft(complexInput);\n  } else {\n    const outputShape = [batch, 2 * (innerDimensionSize - 1)];\n    const realInput = reshape(real(input2), [batch, innerDimensionSize]);\n    const imagInput = reshape(imag(input2), [batch, innerDimensionSize]);\n    const realConjugate = reverse(slice(realInput, [0, 1], [batch, innerDimensionSize - 2]), 1);\n    const imagConjugate = mul(reverse(slice(imagInput, [0, 1], [batch, innerDimensionSize - 2]), 1), scalar(-1));\n    const r2 = concat([realInput, realConjugate], 1);\n    const i2 = concat([imagInput, imagConjugate], 1);\n    const complexInput = reshape(complex(r2, i2), [outputShape[0], outputShape[1]]);\n    ret = ifft(complexInput);\n  }\n  ret = real(ret);\n  if (input2.rank === 3 && input2.shape[0] !== 0) {\n    const temp = ret;\n    const batch2 = input2.shape[0];\n    ret = reshape(ret, [batch2, ret.shape[0] / batch2, ret.shape[1]]);\n    temp.dispose();\n  }\n  return ret;\n}\nvar irfft = op({ irfft_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/split.js\nfunction split_(x, numOrSizeSplits, axis = 0) {\n  const $x = convertToTensor(x, \"x\", \"split\");\n  const inputs = { x: $x };\n  const attr = { numOrSizeSplits, axis };\n  return ENGINE.runKernel(SplitV, inputs, attr);\n}\nvar split = op({ split_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/spectral/rfft.js\nfunction rfft_(input2, fftLength) {\n  assert(input2.dtype === \"float32\", () => `The dtype for rfft() must be real value but got ${input2.dtype}`);\n  let innerDimensionSize = input2.shape[input2.shape.length - 1];\n  const batch = input2.size / innerDimensionSize;\n  let adjustedInput;\n  if (fftLength != null && fftLength < innerDimensionSize) {\n    const begin = input2.shape.map((v) => 0);\n    const size = input2.shape.map((v) => v);\n    size[input2.shape.length - 1] = fftLength;\n    adjustedInput = slice(input2, begin, size);\n    innerDimensionSize = fftLength;\n  } else if (fftLength != null && fftLength > innerDimensionSize) {\n    const zerosShape = input2.shape.map((v) => v);\n    zerosShape[input2.shape.length - 1] = fftLength - innerDimensionSize;\n    adjustedInput = concat([input2, zeros(zerosShape)], input2.shape.length - 1);\n    innerDimensionSize = fftLength;\n  } else {\n    adjustedInput = input2;\n  }\n  const zerosInput = zerosLike(adjustedInput);\n  const complexInput = reshape(complex(adjustedInput, zerosInput), [batch, innerDimensionSize]);\n  const ret = fft(complexInput);\n  const half = Math.floor(innerDimensionSize / 2) + 1;\n  const realValues = real(ret);\n  const imagValues = imag(ret);\n  const realComplexConjugate = split(realValues, [half, innerDimensionSize - half], realValues.shape.length - 1);\n  const imagComplexConjugate = split(imagValues, [half, innerDimensionSize - half], imagValues.shape.length - 1);\n  const outputShape = adjustedInput.shape.slice();\n  outputShape[adjustedInput.shape.length - 1] = half;\n  return reshape(complex(realComplexConjugate[0], imagComplexConjugate[0]), outputShape);\n}\nvar rfft = op({ rfft_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/squared_difference.js\nfunction squaredDifference_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"squaredDifference\");\n  let $b = convertToTensor(b, \"b\", \"squaredDifference\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  const attrs = {};\n  return ENGINE.runKernel(SquaredDifference, inputs, attrs);\n}\nvar squaredDifference = op({ squaredDifference_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/squeeze.js\nfunction squeeze_(x, axis) {\n  const $x = convertToTensor(x, \"x\", \"squeeze\", \"string_or_numeric\");\n  return reshape($x, squeezeShape($x.shape, axis).newShape);\n}\nvar squeeze = op({ squeeze_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/stack.js\nfunction stack_(tensors, axis = 0) {\n  const $tensors = convertToTensorArray(tensors, \"tensors\", \"stack\", \"string_or_numeric\");\n  assert($tensors.length >= 1, () => \"Pass at least one tensor to tf.stack\");\n  if ($tensors.length > 0) {\n    assert(axis <= $tensors[0].rank, () => \"Axis must be <= rank of the tensor\");\n  }\n  const inputs = $tensors;\n  const attrs = { axis };\n  return ENGINE.runKernel(Pack, inputs, attrs);\n}\nvar stack = op({ stack_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/step.js\nfunction step_(x, alpha = 0) {\n  const $x = convertToTensor(x, \"x\", \"step\");\n  const inputs = { x: $x };\n  const attrs = { alpha };\n  return ENGINE.runKernel(Step, inputs, attrs);\n}\nvar step = op({ step_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/strided_slice.js\nfunction stridedSlice_(x, begin, end, strides, beginMask = 0, endMask = 0, ellipsisMask = 0, newAxisMask = 0, shrinkAxisMask = 0) {\n  const $x = convertToTensor(x, \"x\", \"stridedSlice\", \"string_or_numeric\");\n  const inputs = { x: $x };\n  const attrs = {\n    begin,\n    end,\n    strides,\n    beginMask,\n    endMask,\n    ellipsisMask,\n    newAxisMask,\n    shrinkAxisMask\n  };\n  return ENGINE.runKernel(StridedSlice, inputs, attrs);\n}\nvar stridedSlice = op({ stridedSlice_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tan.js\nfunction tan_(x) {\n  const $x = convertToTensor(x, \"x\", \"tan\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Tan, inputs);\n}\nvar tan = op({ tan_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor1d.js\nfunction tensor1d(values, dtype) {\n  assertNonNull(values);\n  const inferredShape = inferShape(values, dtype);\n  if (inferredShape.length !== 1) {\n    throw new Error(\"tensor1d() requires values to be a flat/TypedArray\");\n  }\n  const shape = null;\n  return makeTensor(values, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor2d.js\nfunction tensor2d(values, shape, dtype) {\n  assertNonNull(values);\n  if (shape != null && shape.length !== 2) {\n    throw new Error(\"tensor2d() requires shape to have two numbers\");\n  }\n  const inferredShape = inferShape(values, dtype);\n  if (inferredShape.length !== 2 && inferredShape.length !== 1) {\n    throw new Error(\"tensor2d() requires values to be number[][] or flat/TypedArray\");\n  }\n  if (inferredShape.length === 1 && shape == null) {\n    throw new Error(\"tensor2d() requires shape to be provided when `values` are a flat/TypedArray\");\n  }\n  return makeTensor(values, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor4d.js\nfunction tensor4d(values, shape, dtype) {\n  assertNonNull(values);\n  if (shape != null && shape.length !== 4) {\n    throw new Error(\"tensor4d() requires shape to have four numbers\");\n  }\n  const inferredShape = inferShape(values, dtype);\n  if (inferredShape.length !== 4 && inferredShape.length !== 1) {\n    throw new Error(\"tensor4d() requires values to be number[][][][] or flat/TypedArray\");\n  }\n  if (inferredShape.length === 1 && shape == null) {\n    throw new Error(\"tensor4d() requires shape to be provided when `values` are a flat array\");\n  }\n  return makeTensor(values, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor5d.js\nfunction tensor5d(values, shape, dtype) {\n  assertNonNull(values);\n  if (shape != null && shape.length !== 5) {\n    throw new Error(\"tensor5d() requires shape to have five numbers\");\n  }\n  const inferredShape = inferShape(values, dtype);\n  if (inferredShape.length !== 5 && inferredShape.length !== 1) {\n    throw new Error(\"tensor5d() requires values to be number[][][][][] or flat/TypedArray\");\n  }\n  if (inferredShape.length === 1 && shape == null) {\n    throw new Error(\"tensor5d() requires shape to be provided when `values` are a flat array\");\n  }\n  return makeTensor(values, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor6d.js\nfunction tensor6d(values, shape, dtype) {\n  assertNonNull(values);\n  if (shape != null && shape.length !== 6) {\n    throw new Error(\"tensor6d() requires shape to have six numbers\");\n  }\n  const inferredShape = inferShape(values, dtype);\n  if (inferredShape.length !== 6 && inferredShape.length !== 1) {\n    throw new Error(\"tensor6d() requires values to be number[][][][][][] or flat/TypedArray\");\n  }\n  if (inferredShape.length === 1 && shape == null) {\n    throw new Error(\"tensor6d() requires shape to be provided when `values` are a flat array\");\n  }\n  shape = shape || inferredShape;\n  return makeTensor(values, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/topk.js\nfunction topk_(x, k = 1, sorted = true) {\n  const $x = convertToTensor(x, \"x\", \"topk\");\n  if ($x.rank === 0) {\n    throw new Error(\"topk() expects the input to be of rank 1 or higher\");\n  }\n  const lastDim = $x.shape[$x.shape.length - 1];\n  if (k < 0) {\n    throw new Error(`'k' passed to topk() must be >= 0 but got ${k}`);\n  }\n  if (k > lastDim) {\n    throw new Error(`'k' passed to topk() must be <= the last dimension (${lastDim}) but got ${k}`);\n  }\n  const inputs = { x: $x };\n  const attrs = { k, sorted };\n  const [values, indices] = ENGINE.runKernel(TopK, inputs, attrs);\n  return { values, indices };\n}\nvar topk = op({ topk_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/truncated_normal.js\nfunction truncatedNormal_(shape, mean5 = 0, stdDev = 1, dtype, seed) {\n  if (dtype != null && dtype === \"bool\") {\n    throw new Error(`Unsupported data type $ { dtype }`);\n  }\n  const randGauss = new MPRandGauss(mean5, stdDev, dtype, true, seed);\n  const res = buffer(shape, dtype);\n  for (let i2 = 0; i2 < res.values.length; i2++) {\n    res.values[i2] = randGauss.nextValue();\n  }\n  return res.toTensor();\n}\nvar truncatedNormal = op({ truncatedNormal_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/unique.js\nfunction unique_(x, axis = 0) {\n  const $x = convertToTensor(x, \"x\", \"unique\", \"string_or_numeric\");\n  assert($x.rank > 0, () => \"The input tensor must be at least 1D\");\n  const inputs = { x: $x };\n  const attrs = { axis };\n  const [values, indices] = ENGINE.runKernel(Unique, inputs, attrs);\n  return { values, indices };\n}\nvar unique = op({ unique_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/unsorted_segment_sum.js\nfunction unsortedSegmentSum_(x, segmentIds, numSegments) {\n  const $x = convertToTensor(x, \"x\", \"unsortedSegmentSum\");\n  const $segmentIds = convertToTensor(segmentIds, \"segmentIds\", \"unsortedSegmentSum\", \"int32\");\n  assert(isInt(numSegments), () => \"numSegments must be of dtype int\");\n  const inputs = { x: $x, segmentIds: $segmentIds };\n  const attrs = { numSegments };\n  return ENGINE.runKernel(UnsortedSegmentSum, inputs, attrs);\n}\nvar unsortedSegmentSum = op({ unsortedSegmentSum_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/unstack.js\nfunction unstack_(x, axis = 0) {\n  const $x = convertToTensor(x, \"x\", \"unstack\", \"string_or_numeric\");\n  assert(axis >= -$x.shape.length && axis < $x.shape.length, () => `Axis = ${axis} is not in [-${$x.shape.length}, ${$x.shape.length})`);\n  const inputs = { value: $x };\n  const attrs = { axis };\n  return ENGINE.runKernel(Unpack, inputs, attrs);\n}\nvar unstack = op({ unstack_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/upper_bound.js\nfunction upperBound(sortedSequence, values) {\n  return searchSorted(sortedSequence, values, \"right\");\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/variable.js\nfunction variable(initialValue, trainable = true, name, dtype) {\n  return ENGINE.makeVariable(initialValue, trainable, name, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/where_impl.js\nfunction whereImpl(condShape, condVals) {\n  const indices = [];\n  for (let i2 = 0; i2 < condVals.length; i2++) {\n    if (condVals[i2]) {\n      indices.push(i2);\n    }\n  }\n  const inBuffer = buffer(condShape, \"int32\");\n  const out = buffer([indices.length, condShape.length], \"int32\");\n  for (let i2 = 0; i2 < indices.length; i2++) {\n    const loc = inBuffer.indexToLoc(indices[i2]);\n    const offset = i2 * condShape.length;\n    out.values.set(loc, offset);\n  }\n  return out.toTensor();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/where_async.js\nasync function whereAsync_(condition) {\n  const $condition = convertToTensor(condition, \"condition\", \"whereAsync\", \"bool\");\n  const vals = await $condition.data();\n  const res = whereImpl($condition.shape, vals);\n  if (condition !== $condition) {\n    $condition.dispose();\n  }\n  return res;\n}\nvar whereAsync = whereAsync_;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/boolean_mask.js\nasync function booleanMaskAsync_(tensor2, mask, axis) {\n  const $tensor = convertToTensor(tensor2, \"tensor\", \"boolMask\");\n  const $mask = convertToTensor(mask, \"mask\", \"boolMask\", \"bool\");\n  const axisFrom = axis == null ? 0 : axis;\n  const maskDim = $mask.rank;\n  const tensorShape = $tensor.shape;\n  assert(maskDim > 0, () => \"mask cannot be scalar\");\n  assertShapesMatch(tensorShape.slice(axisFrom, axisFrom + maskDim), $mask.shape, `mask's shape must match the first K dimensions of tensor's shape,`);\n  let leadingSize = 1;\n  for (let i2 = axisFrom; i2 < axisFrom + maskDim; i2++) {\n    leadingSize *= tensorShape[i2];\n  }\n  const targetTensorShape = tensorShape.slice(0, axisFrom).concat([leadingSize], tensorShape.slice(axisFrom + maskDim));\n  const reshapedTensor = reshape($tensor, targetTensorShape);\n  const reshapedMask = reshape($mask, [-1]);\n  const positivePositions = await whereAsync(reshapedMask);\n  const indices = squeeze(positivePositions, [1]);\n  const res = gather(reshapedTensor, indices, axisFrom);\n  if (tensor2 !== $tensor) {\n    $tensor.dispose();\n  }\n  if (mask !== $mask) {\n    $mask.dispose();\n  }\n  indices.dispose();\n  reshapedTensor.dispose();\n  reshapedMask.dispose();\n  positivePositions.dispose();\n  return res;\n}\nvar booleanMaskAsync = booleanMaskAsync_;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/moving_average.js\nfunction movingAverage_(v, x, decay, step5, zeroDebias = true) {\n  const $v = convertToTensor(v, \"v\", \"movingAverage\");\n  const $x = convertToTensor(x, \"x\", \"movingAverage\");\n  const $decay = convertToTensor(decay, \"decay\", \"movingAverage\");\n  assertTypesMatch($v, $x);\n  assert(arraysEqual($v.shape, $x.shape), () => \"Shape mismatch in v and x\");\n  const one = scalar(1);\n  const oneMinusDecay = sub(one, $decay);\n  let update = mul(sub($x, $v), oneMinusDecay);\n  if (zeroDebias) {\n    assert(step5 != null, () => \"When using zeroDebias: true, step is required.\");\n    const $step = convertToTensor(step5, \"step\", \"movingAverage\");\n    update = div(update, sub(one, pow($decay, $step)));\n  }\n  return add2($v, update);\n}\nvar movingAverage = op({ movingAverage_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/scatter_nd.js\nfunction scatterND_(indices, updates, shape) {\n  const $indices = convertToTensor(indices, \"indices\", \"scatterND\", \"int32\");\n  const $updates = convertToTensor(updates, \"updates\", \"scatterND\");\n  validateInput($updates, $indices, shape);\n  const inputs = { indices: $indices, updates: $updates };\n  const attrs = { shape };\n  return ENGINE.runKernel(ScatterNd, inputs, attrs);\n}\nvar scatterND = op({ scatterND_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse_to_dense_util.js\nfunction validateInput2(sparseIndices, sparseValues, outputShape, defaultValues) {\n  if (sparseIndices.dtype !== \"int32\") {\n    throw new Error(`tf.sparseToDense() expects the indices to be int32 type, but the dtype was ${sparseIndices.dtype}.`);\n  }\n  if (sparseIndices.rank > 2) {\n    throw new Error(`sparseIndices should be a scalar, vector, or matrix, but got shape ${sparseIndices.shape}.`);\n  }\n  const numElems = sparseIndices.rank > 0 ? sparseIndices.shape[0] : 1;\n  const numDims = sparseIndices.rank > 1 ? sparseIndices.shape[1] : 1;\n  if (outputShape.length !== numDims) {\n    throw new Error(`outputShape has incorrect number of elements:, ${outputShape.length}, should be: ${numDims}.`);\n  }\n  const numValues = sparseValues.size;\n  if (!(sparseValues.rank === 0 || sparseValues.rank === 1 && numValues === numElems)) {\n    throw new Error(`sparseValues has incorrect shape ${sparseValues.shape}, should be [] or [${numElems}]`);\n  }\n  if (sparseValues.dtype !== defaultValues.dtype) {\n    throw new Error(\"sparseValues.dtype must match defaultValues.dtype\");\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse_to_dense.js\nfunction sparseToDense_(sparseIndices, sparseValues, outputShape, defaultValue = 0) {\n  const $sparseIndices = convertToTensor(sparseIndices, \"sparseIndices\", \"sparseToDense\", \"int32\");\n  const $sparseValues = convertToTensor(sparseValues, \"sparseValues\", \"sparseToDense\", \"string_or_numeric\");\n  const $defaultValue = convertToTensor(defaultValue, \"defaultValue\", \"sparseToDense\", $sparseValues.dtype);\n  validateInput2($sparseIndices, $sparseValues, outputShape, $defaultValue);\n  const inputs = {\n    sparseIndices: $sparseIndices,\n    sparseValues: $sparseValues,\n    defaultValue: $defaultValue\n  };\n  const attrs = { outputShape };\n  return ENGINE.runKernel(SparseToDense, inputs, attrs);\n}\nvar sparseToDense = op({ sparseToDense_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/gather_nd.js\nfunction gatherND_(x, indices) {\n  const $indices = convertToTensor(indices, \"indices\", \"gatherND\", \"int32\");\n  const $x = convertToTensor(x, \"x\", \"gatherND\", \"string_or_numeric\");\n  const inputs = { params: $x, indices: $indices };\n  return ENGINE.runKernel(GatherNd, inputs);\n}\nvar gatherND = op({ gatherND_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/dropout_util.js\nfunction getNoiseShape(x, noiseShape) {\n  if (noiseShape == null) {\n    return x.shape.slice();\n  }\n  if (arraysEqual(x.shape, noiseShape)) {\n    return noiseShape;\n  }\n  if (x.shape.length === noiseShape.length) {\n    const newDimension = [];\n    for (let i2 = 0; i2 < x.shape.length; i2++) {\n      if (noiseShape[i2] == null && x.shape[i2] != null) {\n        newDimension.push(x.shape[i2]);\n      } else {\n        newDimension.push(noiseShape[i2]);\n      }\n    }\n    return newDimension;\n  }\n  return noiseShape;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/dropout.js\nfunction dropout_(x, rate, noiseShape, seed) {\n  const $x = convertToTensor(x, \"x\", \"dropout\");\n  assert($x.dtype === \"float32\", () => `x has to be a floating point tensor since it's going to be scaled, but got a ${$x.dtype} tensor instead.`);\n  assert(rate >= 0 && rate < 1, () => `rate must be a float in the range [0, 1), but got ${rate}.`);\n  if (rate === 0) {\n    return x instanceof Tensor ? $x.clone() : $x;\n  }\n  const $noiseShape = getNoiseShape($x, noiseShape);\n  const keepProb = 1 - rate;\n  const multiplier = div(floor(add2(randomUniform($noiseShape, 0, 1, \"float32\", seed), keepProb)), keepProb);\n  return mul($x, multiplier);\n}\nvar dropout = op({ dropout_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/signal_ops_util.js\nfunction enclosingPowerOfTwo(value) {\n  return Math.floor(Math.pow(2, Math.ceil(Math.log(value) / Math.log(2))));\n}\nfunction cosineWindow(windowLength, a, b) {\n  const even = 1 - windowLength % 2;\n  const newValues = new Float32Array(windowLength);\n  for (let i2 = 0; i2 < windowLength; ++i2) {\n    const cosArg = 2 * Math.PI * i2 / (windowLength + even - 1);\n    newValues[i2] = a - b * Math.cos(cosArg);\n  }\n  return tensor1d(newValues, \"float32\");\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/in_top_k.js\nasync function inTopKAsync_(predictions, targets, k = 1) {\n  const $predictions = convertToTensor(predictions, \"predictions\", \"inTopK\");\n  const $targets = convertToTensor(targets, \"targets\", \"inTopK\");\n  assert($predictions.rank > 1, () => `inTopK() expects the predictions to be of rank 2 or higher, but got ${$predictions.rank}`);\n  assert($predictions.rank - 1 === $targets.rank, () => `predictions rank should be 1 larger than targets rank, but got predictions rank ${$predictions.rank} and targets rank ${$targets.rank}`);\n  assertShapesMatch($predictions.shape.slice(0, $predictions.shape.length - 1), $targets.shape, `predictions's shape should be align with the targets' shape, except the last dimension.`);\n  const lastDim = $predictions.shape[$predictions.shape.length - 1];\n  assert(k > 0 && k <= lastDim, () => `'k' passed to inTopK() must be > 0 && <= the predictions last dimension (${lastDim}), but got ${k}`);\n  const predictionsVals = await $predictions.data();\n  const targetsVals = await $targets.data();\n  const [batch, size] = [predictionsVals.length / lastDim, lastDim];\n  const precision3 = getTypedArrayFromDType(\"bool\", batch);\n  for (let b = 0; b < batch; b++) {\n    const offset = b * size;\n    const vals = predictionsVals.subarray(offset, offset + size);\n    const valAndInd = [];\n    for (let i2 = 0; i2 < vals.length; i2++) {\n      valAndInd.push({ value: vals[i2], index: i2 });\n    }\n    valAndInd.sort((a, b2) => b2.value - a.value);\n    precision3[b] = 0;\n    for (let i2 = 0; i2 < k; i2++) {\n      if (valAndInd[i2].index === targetsVals[b]) {\n        precision3[b] = 1;\n        break;\n      }\n    }\n  }\n  if (predictions !== $predictions) {\n    $predictions.dispose();\n  }\n  if (targets !== $targets) {\n    $targets.dispose();\n  }\n  return tensor(precision3, $targets.shape, \"bool\");\n}\nvar inTopKAsync = inTopKAsync_;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/fused_ops.js\nvar fused_ops_exports = {};\n__export(fused_ops_exports, {\n  conv2d: () => conv2d2,\n  depthwiseConv2d: () => depthwiseConv2d2,\n  matMul: () => matMul2\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv2d_backprop_filter.js\nfunction conv2DBackpropFilter_(x, dy, filterShape, strides, pad3, dataFormat = \"NHWC\", dimRoundingMode) {\n  let x4D = x;\n  if (x.rank === 3) {\n    x4D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2]]);\n  }\n  let dy4D = dy;\n  if (dy4D.rank === 3) {\n    dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);\n  }\n  assert(x4D.rank === 4, () => `Error in conv2dDerFilter: input must be rank 4, but got shape ${x4D.shape}.`);\n  assert(dy4D.rank === 4, () => `Error in conv2dDerFilter: dy must be rank 4, but got shape ${dy4D.shape}.`);\n  assert(filterShape.length === 4, () => `Error in conv2dDerFilter: filterShape must be length 4, but got ${filterShape}.`);\n  const inDepth = dataFormat === \"NHWC\" ? x4D.shape[3] : x4D.shape[1];\n  const outDepth = dataFormat === \"NHWC\" ? dy4D.shape[3] : dy4D.shape[1];\n  assert(inDepth === filterShape[2], () => `Error in conv2dDerFilter: depth of input ${inDepth}) must match input depth in filter (${filterShape[2]}.`);\n  assert(outDepth === filterShape[3], () => `Error in conv2dDerFilter: depth of dy (${outDepth}) must match output depth for filter (${filterShape[3]}).`);\n  checkPadOnDimRoundingMode(\"conv2dDerFilter\", pad3, dimRoundingMode);\n  const inputs = { x: x4D, dy: dy4D };\n  const attrs = { strides, pad: pad3, dataFormat, dimRoundingMode, filterShape };\n  return ENGINE.runKernel(Conv2DBackpropFilter, inputs, attrs);\n}\nvar conv2DBackpropFilter = op({ conv2DBackpropFilter_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/fused_util.js\nfunction getFusedDyActivation(dy, y, activation2) {\n  if (activation2 == null || activation2 === \"linear\") {\n    return dy;\n  }\n  if (activation2 === \"relu\") {\n    return mul(dy, step(y));\n  }\n  throw new Error(`Cannot compute gradient for fused activation ${activation2}.`);\n}\nfunction getFusedBiasGradient(bias, dyActivation) {\n  let res = dyActivation;\n  const reduceAxes = getReductionAxes(bias.shape, dyActivation.shape);\n  if (reduceAxes.length > 0) {\n    res = sum2(res, reduceAxes);\n  }\n  return reshape(res, bias.shape);\n}\nfunction applyActivation(x, activation2, preluActivationWeights, leakyreluAlpha) {\n  if (activation2 === \"linear\") {\n    return x;\n  } else if (activation2 === \"relu\") {\n    return relu(x);\n  } else if (activation2 === \"elu\") {\n    return elu(x);\n  } else if (activation2 === \"relu6\") {\n    return relu6(x);\n  } else if (activation2 === \"prelu\") {\n    return prelu(x, preluActivationWeights);\n  } else if (activation2 === \"leakyrelu\") {\n    return leakyRelu(x, leakyreluAlpha);\n  } else if (activation2 === \"sigmoid\") {\n    return sigmoid(x);\n  }\n  throw new Error(`Unknown fused activation ${activation2}.`);\n}\nvar shouldFuse = (gradientDepth, activation2) => {\n  const gradientMode = gradientDepth > 0;\n  return !gradientMode || activation2 === \"linear\";\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/fused/conv2d.js\nfunction fusedConv2d_({ x, filter, strides, pad: pad3, dataFormat = \"NHWC\", dilations = [1, 1], dimRoundingMode, bias, activation: activation2 = \"linear\", preluActivationWeights, leakyreluAlpha }) {\n  activation2 = activation2 || \"linear\";\n  if (shouldFuse(ENGINE.state.gradientDepth, activation2) === false) {\n    assert(dataFormat === \"NHWC\", () => `Error in fused conv2d: got dataFormat of ${dataFormat} but only NHWC is currently supported for the case of gradient depth is 0 and the activation is not linear.`);\n    let result = conv2d(x, filter, strides, pad3, dataFormat, dilations, dimRoundingMode);\n    if (bias != null) {\n      result = add2(result, bias);\n    }\n    return applyActivation(result, activation2, preluActivationWeights, leakyreluAlpha);\n  }\n  const $x = convertToTensor(x, \"x\", \"conv2d\", \"float32\");\n  const $filter = convertToTensor(filter, \"filter\", \"conv2d\", \"float32\");\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  assert(x4D.rank === 4, () => `Error in fused conv2d: input must be rank 4, but got rank ${x4D.rank}.`);\n  assert($filter.rank === 4, () => `Error in fused conv2d: filter must be rank 4, but got rank ${$filter.rank}.`);\n  checkPadOnDimRoundingMode(\"fused conv2d\", pad3, dimRoundingMode);\n  const inputChannels = dataFormat === \"NHWC\" ? x4D.shape[3] : x4D.shape[1];\n  assert($filter.shape[2] === inputChannels, () => `Error in conv2d: depth of input (${inputChannels}) must match input depth for filter ${$filter.shape[2]}.`);\n  assert(eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in conv2D: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  const convInfo = computeConv2DInfo(x4D.shape, $filter.shape, strides, dilations, pad3, dimRoundingMode);\n  let $bias;\n  if (bias != null) {\n    $bias = convertToTensor(bias, \"bias\", \"fused conv2d\");\n    [$bias] = makeTypesMatch($bias, $x);\n    if (dataFormat === \"NHWC\") {\n      assertAndGetBroadcastShape(convInfo.outShape, $bias.shape);\n    } else {\n      assert($bias.shape.length <= 1, () => `Error in fused conv2d: only supports scalar or 1-D Tensor bias for NCHW format but got the bias of rank-${$bias.shape.length}.`);\n      assert($bias.shape.length === 0 || $bias.shape[0] === convInfo.outChannels || $bias.shape[0] === 1, () => `Error in fused conv2d: bias shape (${$bias.shape}) is not compatible with the number of output channels (${convInfo.outChannels})`);\n    }\n  }\n  let $preluActivationWeights;\n  if (preluActivationWeights != null) {\n    const alphaShape = preluActivationWeights.shape;\n    assert(alphaShape.length <= 1 || alphaShape.length === 3, () => `Error in fused conv2d: only supports scalar, 1-D Tensor or 3-D Tensor PReLU activation weights but got a tensor of rank-${alphaShape.length}.`);\n    if (alphaShape.length === 1) {\n      assert(alphaShape[0] === 1 || alphaShape[0] === convInfo.outChannels, () => `Error in fused conv2d: PReLU activation weights (${alphaShape}) is not compatible with the number of output channels (${convInfo.outChannels}).`);\n    } else if (alphaShape.length === 3) {\n      try {\n        assertAndGetBroadcastShape(alphaShape, convInfo.outShape);\n      } catch (e2) {\n        const errMsg = `Error in fused conv2d: PReLU activation weights (${alphaShape}) is not compatible with the output shape of the conv2d (${convInfo.outShape}).`;\n        throw Error(errMsg);\n      }\n    }\n    $preluActivationWeights = convertToTensor(preluActivationWeights, \"prelu weights\", \"fused conv2d\");\n  }\n  const grad2 = (dy, saved) => {\n    assert(dataFormat === \"NHWC\", () => `Error in gradient of fused conv2D: got dataFormat of ${dataFormat} but only NHWC is currently supported.`);\n    const [$filter2, x4D2, y, $bias2] = saved;\n    const dyActivation = getFusedDyActivation(dy, y, activation2);\n    assert(tupleValuesAreOne(dilations), () => `Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${dilations}'`);\n    const xDer = conv2DBackpropInput(x4D2.shape, dyActivation, $filter2, strides, pad3);\n    const filterDer = conv2DBackpropFilter(x4D2, dyActivation, $filter2.shape, strides, pad3);\n    const der = [xDer, filterDer];\n    if ($bias2 != null) {\n      const biasDer = getFusedBiasGradient($bias2, dyActivation);\n      der.push(biasDer);\n    }\n    return der;\n  };\n  const inputs = {\n    x: x4D,\n    filter: $filter,\n    bias: $bias,\n    preluActivationWeights: $preluActivationWeights\n  };\n  const attrs = {\n    strides,\n    pad: pad3,\n    dataFormat,\n    dilations,\n    dimRoundingMode,\n    activation: activation2,\n    leakyreluAlpha\n  };\n  if (bias == null) {\n    const customOp = customGrad((x4D2, filter2, save) => {\n      let res = ENGINE.runKernel(FusedConv2D, inputs, attrs);\n      save([filter2, x4D2, res]);\n      if (reshapedTo4D) {\n        res = reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n      }\n      return { value: res, gradFunc: grad2 };\n    });\n    return customOp(x4D, $filter);\n  } else {\n    const customOpWithBias = customGrad((x4D2, filter2, bias2, save) => {\n      let res = ENGINE.runKernel(FusedConv2D, inputs, attrs);\n      save([filter2, x4D2, res, bias2]);\n      if (reshapedTo4D) {\n        res = reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n      }\n      return { value: res, gradFunc: grad2 };\n    });\n    return customOpWithBias(x4D, $filter, $bias);\n  }\n}\nvar conv2d2 = op({ fusedConv2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/depthwise_conv2d_native_backprop_filter.js\nfunction depthwiseConv2dNativeBackpropFilter_(x, dy, filterShape, strides, pad3, dilations = [1, 1], dimRoundingMode) {\n  let x4D = x;\n  if (x.rank === 3) {\n    x4D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2]]);\n  }\n  let dy4D = dy;\n  if (dy4D.rank === 3) {\n    dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);\n  }\n  const inputs = { x: x4D, dy: dy4D };\n  const attrs = { strides, pad: pad3, dimRoundingMode, dilations, filterShape };\n  return ENGINE.runKernel(DepthwiseConv2dNativeBackpropFilter, inputs, attrs);\n}\nvar depthwiseConv2dNativeBackpropFilter = op({ depthwiseConv2dNativeBackpropFilter_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/depthwise_conv2d_native_backprop_input.js\nfunction depthwiseConv2dNativeBackpropInput_(xShape, dy, filter, strides, pad3, dilations = [1, 1], dimRoundingMode) {\n  let dy4D = dy;\n  let reshapedTo4D = false;\n  if (dy.rank === 3) {\n    reshapedTo4D = true;\n    dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);\n  }\n  const inputs = { dy: dy4D, filter };\n  const attrs = { strides, pad: pad3, dimRoundingMode, dilations, inputShape: xShape };\n  const res = ENGINE.runKernel(DepthwiseConv2dNativeBackpropInput, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar depthwiseConv2dNativeBackpropInput = op({ depthwiseConv2dNativeBackpropInput_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/fused/depthwise_conv2d.js\nfunction fusedDepthwiseConv2d_({ x, filter, strides, pad: pad3, dataFormat = \"NHWC\", dilations = [1, 1], dimRoundingMode, bias, activation: activation2 = \"linear\", preluActivationWeights, leakyreluAlpha }) {\n  if (shouldFuse(ENGINE.state.gradientDepth, activation2) === false) {\n    let result = depthwiseConv2d(x, filter, strides, pad3, dataFormat, dilations, dimRoundingMode);\n    if (bias != null) {\n      result = add2(result, bias);\n    }\n    return applyActivation(result, activation2, preluActivationWeights, leakyreluAlpha);\n  }\n  const $x = convertToTensor(x, \"x\", \"depthwiseConv2d\", \"float32\");\n  const $filter = convertToTensor(filter, \"filter\", \"depthwiseConv2d\", \"float32\");\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  assert(x4D.rank === 4, () => `Error in fused depthwiseConv2d: input must be rank 4, but got rank ${x4D.rank}.`);\n  assert($filter.rank === 4, () => `Error in fused depthwiseConv2d: filter must be rank 4, but got rank ${$filter.rank}.`);\n  assert(x4D.shape[3] === $filter.shape[2], () => `Error in fused depthwiseConv2d: number of input channels (${x4D.shape[3]}) must match the inChannels dimension in filter ${$filter.shape[2]}.`);\n  if (dilations == null) {\n    dilations = [1, 1];\n  }\n  assert(eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in fused depthwiseConv2d: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  checkPadOnDimRoundingMode(\"fused depthwiseConv2d\", pad3, dimRoundingMode);\n  const convInfo = computeConv2DInfo(x4D.shape, $filter.shape, strides, dilations, pad3, dimRoundingMode, true);\n  let $bias;\n  if (bias != null) {\n    $bias = convertToTensor(bias, \"bias\", \"fused conv2d\");\n    [$bias] = makeTypesMatch($bias, $x);\n    assertAndGetBroadcastShape(convInfo.outShape, $bias.shape);\n  }\n  let $preluActivationWeights;\n  if (preluActivationWeights != null) {\n    $preluActivationWeights = convertToTensor(preluActivationWeights, \"prelu weights\", \"fused depthwiseConv2d\");\n  }\n  const grad2 = (dy, saved) => {\n    assert(tupleValuesAreOne(dilations), () => `Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '${dilations}'`);\n    const [$filter2, x4D2, y, bias2] = saved;\n    const dyActivation = getFusedDyActivation(dy, y, activation2);\n    const xDer = depthwiseConv2dNativeBackpropInput(x4D2.shape, dyActivation, $filter2, strides, pad3, dilations, dimRoundingMode);\n    const filterDer = depthwiseConv2dNativeBackpropFilter(x4D2, dyActivation, $filter2.shape, strides, pad3, dilations, dimRoundingMode);\n    if (bias2 != null) {\n      const biasDer = getFusedBiasGradient($bias, dyActivation);\n      return [xDer, filterDer, biasDer];\n    }\n    return [xDer, filterDer];\n  };\n  const inputs = {\n    x: x4D,\n    filter: $filter,\n    bias: $bias,\n    preluActivationWeights: $preluActivationWeights\n  };\n  const attrs = {\n    strides,\n    pad: pad3,\n    dataFormat,\n    dilations,\n    dimRoundingMode,\n    activation: activation2,\n    leakyreluAlpha\n  };\n  if (bias == null) {\n    const customOp = customGrad((x4D2, filter2, save) => {\n      let res = ENGINE.runKernel(FusedDepthwiseConv2D, inputs, attrs);\n      save([filter2, x4D2, res]);\n      if (reshapedTo4D) {\n        res = reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n      }\n      return { value: res, gradFunc: grad2 };\n    });\n    return customOp(x4D, $filter);\n  } else {\n    const customOpWithBias = customGrad((x4D2, filter2, bias2, save) => {\n      let res = ENGINE.runKernel(FusedDepthwiseConv2D, inputs, attrs);\n      save([filter2, x4D2, res, bias2]);\n      if (reshapedTo4D) {\n        res = reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n      }\n      return { value: res, gradFunc: grad2 };\n    });\n    return customOpWithBias(x4D, $filter, $bias);\n  }\n}\nvar depthwiseConv2d2 = op({ fusedDepthwiseConv2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/fused/mat_mul.js\nfunction fusedMatMul_({ a, b, transposeA = false, transposeB = false, bias, activation: activation2 = \"linear\", preluActivationWeights, leakyreluAlpha = 0.2 }) {\n  if (shouldFuse(ENGINE.state.gradientDepth, activation2) === false) {\n    let result = matMul(a, b, transposeA, transposeB);\n    if (bias != null) {\n      result = add2(result, bias);\n    }\n    return applyActivation(result, activation2, preluActivationWeights, leakyreluAlpha);\n  }\n  let $a = convertToTensor(a, \"a\", \"fused matMul\");\n  let $b = convertToTensor(b, \"b\", \"fused matMul\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const innerShapeA = transposeA ? $a.shape[$a.rank - 2] : $a.shape[$a.rank - 1];\n  const innerShapeB = transposeB ? $b.shape[$b.rank - 1] : $b.shape[$b.rank - 2];\n  const outerShapeA = transposeA ? $a.shape[$a.rank - 1] : $a.shape[$a.rank - 2];\n  const outerShapeB = transposeB ? $b.shape[$b.rank - 2] : $b.shape[$b.rank - 1];\n  const outerDimsA = $a.shape.slice(0, -2);\n  const outerDimsB = $b.shape.slice(0, -2);\n  const batchDimA = sizeFromShape(outerDimsA);\n  const batchDimB = sizeFromShape(outerDimsB);\n  assert(innerShapeA === innerShapeB, () => `Error in fused matMul: inner shapes (${innerShapeA}) and (${innerShapeB}) of Tensors with shapes ${$a.shape} and ${$b.shape} and transposeA=${transposeA} and transposeB=${transposeB} must match.`);\n  const outShapeOuterDims = assertAndGetBroadcastShape($a.shape.slice(0, -2), $b.shape.slice(0, -2));\n  const outShape = outShapeOuterDims.concat([outerShapeA, outerShapeB]);\n  const a3D = transposeA ? reshape($a, [batchDimA, innerShapeA, outerShapeA]) : reshape($a, [batchDimA, outerShapeA, innerShapeA]);\n  const b3D = transposeB ? reshape($b, [batchDimB, outerShapeB, innerShapeB]) : reshape($b, [batchDimB, innerShapeB, outerShapeB]);\n  let $bias;\n  if (bias != null) {\n    $bias = convertToTensor(bias, \"bias\", \"fused matMul\");\n    [$bias] = makeTypesMatch($bias, $a);\n    assertAndGetBroadcastShape(outShape, $bias.shape);\n  }\n  let $preluActivationWeights;\n  if (preluActivationWeights != null) {\n    $preluActivationWeights = convertToTensor(preluActivationWeights, \"prelu weights\", \"fused matMul\");\n  }\n  const grad2 = (dy, saved) => {\n    const [a3D2, b3D2, y, $bias2] = saved;\n    const dyActivation = getFusedDyActivation(reshape(dy, y.shape), y, activation2);\n    let aDer;\n    let bDer;\n    if (!transposeA && !transposeB) {\n      aDer = matMul(dyActivation, b3D2, false, true);\n      bDer = matMul(a3D2, dyActivation, true, false);\n    } else if (!transposeA && transposeB) {\n      aDer = matMul(dyActivation, b3D2, false, false);\n      bDer = matMul(dyActivation, a3D2, true, false);\n    } else if (transposeA && !transposeB) {\n      aDer = matMul(b3D2, dyActivation, false, true);\n      bDer = matMul(a3D2, dyActivation, false, false);\n    } else {\n      aDer = matMul(b3D2, dyActivation, true, true);\n      bDer = matMul(dyActivation, a3D2, true, true);\n    }\n    if (bias != null) {\n      const biasDer = getFusedBiasGradient($bias2, dyActivation);\n      return [aDer, bDer, biasDer];\n    } else {\n      return [aDer, bDer];\n    }\n  };\n  const inputs = {\n    a: a3D,\n    b: b3D,\n    bias: $bias,\n    preluActivationWeights: $preluActivationWeights\n  };\n  const attrs = { transposeA, transposeB, activation: activation2, leakyreluAlpha };\n  if (bias == null) {\n    const customOp = customGrad((a3D2, b3D2, save) => {\n      const res = ENGINE.runKernel(_FusedMatMul, inputs, attrs);\n      save([a3D2, b3D2, res]);\n      return { value: reshape(res, outShape), gradFunc: grad2 };\n    });\n    return customOp(a3D, b3D);\n  } else {\n    const customOpWithBias = customGrad((a3D2, b3D2, $bias2, save) => {\n      const res = ENGINE.runKernel(_FusedMatMul, inputs, attrs);\n      save([a3D2, b3D2, res, $bias2]);\n      return { value: reshape(res, outShape), gradFunc: grad2 };\n    });\n    return customOpWithBias(a3D, b3D, $bias);\n  }\n}\nvar matMul2 = op({ fusedMatMul_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/signal/hamming_window.js\nfunction hammingWindow_(windowLength) {\n  return cosineWindow(windowLength, 0.54, 0.46);\n}\nvar hammingWindow = op({ hammingWindow_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/signal/hann_window.js\nfunction hannWindow_(windowLength) {\n  return cosineWindow(windowLength, 0.5, 0.5);\n}\nvar hannWindow = op({ hannWindow_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/signal/frame.js\nfunction frame_(signal2, frameLength, frameStep, padEnd = false, padValue = 0) {\n  let start = 0;\n  const output = [];\n  while (start + frameLength <= signal2.size) {\n    output.push(slice(signal2, start, frameLength));\n    start += frameStep;\n  }\n  if (padEnd) {\n    while (start < signal2.size) {\n      const padLen = start + frameLength - signal2.size;\n      const pad3 = concat([\n        slice(signal2, start, frameLength - padLen),\n        fill([padLen], padValue)\n      ]);\n      output.push(pad3);\n      start += frameStep;\n    }\n  }\n  if (output.length === 0) {\n    return tensor2d([], [0, frameLength]);\n  }\n  return reshape(concat(output), [output.length, frameLength]);\n}\nvar frame = op({ frame_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/signal/stft.js\nfunction stft_(signal2, frameLength, frameStep, fftLength, windowFn = hannWindow) {\n  if (fftLength == null) {\n    fftLength = enclosingPowerOfTwo(frameLength);\n  }\n  const framedSignal = frame(signal2, frameLength, frameStep);\n  const windowedSignal = mul(framedSignal, windowFn(frameLength));\n  return rfft(windowedSignal, fftLength);\n}\nvar stft = op({ stft_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/crop_and_resize.js\nfunction cropAndResize_(image2, boxes, boxInd, cropSize, method = \"bilinear\", extrapolationValue = 0) {\n  const $image = convertToTensor(image2, \"image\", \"cropAndResize\");\n  const $boxes = convertToTensor(boxes, \"boxes\", \"cropAndResize\", \"float32\");\n  const $boxInd = convertToTensor(boxInd, \"boxInd\", \"cropAndResize\", \"int32\");\n  const numBoxes = $boxes.shape[0];\n  assert($image.rank === 4, () => `Error in cropAndResize: image must be rank 4,but got rank ${$image.rank}.`);\n  assert($boxes.rank === 2 && $boxes.shape[1] === 4, () => `Error in cropAndResize: boxes must be have size [${numBoxes},4] but had shape ${$boxes.shape}.`);\n  assert($boxInd.rank === 1 && $boxInd.shape[0] === numBoxes, () => `Error in cropAndResize: boxInd must be have size [${numBoxes}] but had shape ${$boxes.shape}.`);\n  assert(cropSize.length === 2, () => `Error in cropAndResize: cropSize must be of length 2, but got length ${cropSize.length}.`);\n  assert(cropSize[0] >= 1 && cropSize[1] >= 1, () => `cropSize must be atleast [1,1], but was ${cropSize}`);\n  assert(method === \"bilinear\" || method === \"nearest\", () => `method must be bilinear or nearest, but was ${method}`);\n  const inputs = { image: $image, boxes: $boxes, boxInd: $boxInd };\n  const attrs = { method, extrapolationValue, cropSize };\n  const res = ENGINE.runKernel(CropAndResize, inputs, attrs);\n  return res;\n}\nvar cropAndResize = op({ cropAndResize_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/flip_left_right.js\nfunction flipLeftRight_(image2) {\n  const $image = convertToTensor(image2, \"image\", \"flipLeftRight\", \"float32\");\n  assert($image.rank === 4, () => `Error in flipLeftRight: image must be rank 4,but got rank ${$image.rank}.`);\n  const inputs = { image: $image };\n  const res = ENGINE.runKernel(FlipLeftRight, inputs, {});\n  return res;\n}\nvar flipLeftRight = op({ flipLeftRight_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/grayscale_to_rgb.js\nfunction grayscaleToRGB_(image2) {\n  const $image = convertToTensor(image2, \"image\", \"grayscaleToRGB\");\n  const lastDimsIdx = $image.rank - 1;\n  const lastDims = $image.shape[lastDimsIdx];\n  assert($image.rank >= 2, () => `Error in grayscaleToRGB: images must be at least rank 2, but got rank ${$image.rank}.`);\n  assert(lastDims === 1, () => `Error in grayscaleToRGB: last dimension of a grayscale image should be size 1, but got size ${lastDims}.`);\n  const reps = new Array($image.rank);\n  reps.fill(1, 0, lastDimsIdx);\n  reps[lastDimsIdx] = 3;\n  return tile($image, reps);\n}\nvar grayscaleToRGB = op({ grayscaleToRGB_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/rotate_with_offset.js\nfunction rotateWithOffset_(image2, radians, fillValue = 0, center = 0.5) {\n  const $image = convertToTensor(image2, \"image\", \"rotateWithOffset\", \"float32\");\n  assert($image.rank === 4, () => `Error in rotateWithOffset: image must be rank 4,but got rank ${$image.rank}.`);\n  const inputs = { image: $image };\n  const attrs = { radians, fillValue, center };\n  const res = ENGINE.runKernel(RotateWithOffset, inputs, attrs);\n  return res;\n}\nvar rotateWithOffset = op({ rotateWithOffset_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/nonmax_util.js\nfunction nonMaxSuppSanityCheck(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma) {\n  if (iouThreshold == null) {\n    iouThreshold = 0.5;\n  }\n  if (scoreThreshold == null) {\n    scoreThreshold = Number.NEGATIVE_INFINITY;\n  }\n  if (softNmsSigma == null) {\n    softNmsSigma = 0;\n  }\n  const numBoxes = boxes.shape[0];\n  maxOutputSize = Math.min(maxOutputSize, numBoxes);\n  assert(0 <= iouThreshold && iouThreshold <= 1, () => `iouThreshold must be in [0, 1], but was '${iouThreshold}'`);\n  assert(boxes.rank === 2, () => `boxes must be a 2D tensor, but was of rank '${boxes.rank}'`);\n  assert(boxes.shape[1] === 4, () => `boxes must have 4 columns, but 2nd dimension was ${boxes.shape[1]}`);\n  assert(scores.rank === 1, () => \"scores must be a 1D tensor\");\n  assert(scores.shape[0] === numBoxes, () => `scores has incompatible shape with boxes. Expected ${numBoxes}, but was ${scores.shape[0]}`);\n  assert(0 <= softNmsSigma && softNmsSigma <= 1, () => `softNmsSigma must be in [0, 1], but was '${softNmsSigma}'`);\n  return { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/non_max_suppression.js\nfunction nonMaxSuppression_(boxes, scores, maxOutputSize, iouThreshold = 0.5, scoreThreshold = Number.NEGATIVE_INFINITY) {\n  const $boxes = convertToTensor(boxes, \"boxes\", \"nonMaxSuppression\", \"float32\");\n  const $scores = convertToTensor(scores, \"scores\", \"nonMaxSuppression\", \"float32\");\n  const inputs = nonMaxSuppSanityCheck($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold);\n  maxOutputSize = inputs.maxOutputSize;\n  iouThreshold = inputs.iouThreshold;\n  scoreThreshold = inputs.scoreThreshold;\n  const attrs = { maxOutputSize, iouThreshold, scoreThreshold };\n  return ENGINE.runKernel(NonMaxSuppressionV3, { boxes: $boxes, scores: $scores }, attrs);\n}\nvar nonMaxSuppression = op({ nonMaxSuppression_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/non_max_suppression_util.js\nfunction binaryInsert(arr, element, comparator) {\n  const index = binarySearch(arr, element, comparator);\n  const insertionPoint = index < 0 ? -(index + 1) : index;\n  arr.splice(insertionPoint, 0, element);\n}\nfunction binarySearch(arr, target, comparator) {\n  return binarySearch_(arr, target, comparator || defaultComparator);\n}\nfunction defaultComparator(a, b) {\n  return a > b ? 1 : a < b ? -1 : 0;\n}\nfunction binarySearch_(arr, target, comparator) {\n  let left = 0;\n  let right = arr.length;\n  let middle = 0;\n  let found = false;\n  while (left < right) {\n    middle = left + (right - left >>> 1);\n    const compareResult = comparator(target, arr[middle]);\n    if (compareResult > 0) {\n      left = middle + 1;\n    } else {\n      right = middle;\n      found = !compareResult;\n    }\n  }\n  return found ? left : -left - 1;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/non_max_suppression_impl.js\nfunction nonMaxSuppressionV3Impl(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold) {\n  return nonMaxSuppressionImpl_(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, 0);\n}\nfunction nonMaxSuppressionV4Impl(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize) {\n  return nonMaxSuppressionImpl_(\n    boxes,\n    scores,\n    maxOutputSize,\n    iouThreshold,\n    scoreThreshold,\n    0,\n    false,\n    padToMaxOutputSize,\n    true\n  );\n}\nfunction nonMaxSuppressionV5Impl(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma) {\n  return nonMaxSuppressionImpl_(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma, true);\n}\nfunction nonMaxSuppressionImpl_(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma, returnScoresTensor = false, padToMaxOutputSize = false, returnValidOutputs = false) {\n  const candidates = [];\n  for (let i2 = 0; i2 < scores.length; i2++) {\n    if (scores[i2] > scoreThreshold) {\n      candidates.push({ score: scores[i2], boxIndex: i2, suppressBeginIndex: 0 });\n    }\n  }\n  candidates.sort(ascendingComparator);\n  const scale2 = softNmsSigma > 0 ? -0.5 / softNmsSigma : 0;\n  const selectedIndices = [];\n  const selectedScores = [];\n  while (selectedIndices.length < maxOutputSize && candidates.length > 0) {\n    const candidate = candidates.pop();\n    const { score: originalScore, boxIndex, suppressBeginIndex } = candidate;\n    if (originalScore < scoreThreshold) {\n      break;\n    }\n    let ignoreCandidate = false;\n    for (let j = selectedIndices.length - 1; j >= suppressBeginIndex; --j) {\n      const iou = intersectionOverUnion(boxes, boxIndex, selectedIndices[j]);\n      if (iou >= iouThreshold) {\n        ignoreCandidate = true;\n        break;\n      }\n      candidate.score = candidate.score * suppressWeight(iouThreshold, scale2, iou);\n      if (candidate.score <= scoreThreshold) {\n        break;\n      }\n    }\n    candidate.suppressBeginIndex = selectedIndices.length;\n    if (!ignoreCandidate) {\n      if (candidate.score === originalScore) {\n        selectedIndices.push(boxIndex);\n        selectedScores.push(candidate.score);\n      } else if (candidate.score > scoreThreshold) {\n        binaryInsert(candidates, candidate, ascendingComparator);\n      }\n    }\n  }\n  const validOutputs = selectedIndices.length;\n  const elemsToPad = maxOutputSize - validOutputs;\n  if (padToMaxOutputSize && elemsToPad > 0) {\n    selectedIndices.push(...new Array(elemsToPad).fill(0));\n    selectedScores.push(...new Array(elemsToPad).fill(0));\n  }\n  const result = { selectedIndices };\n  if (returnScoresTensor) {\n    result[\"selectedScores\"] = selectedScores;\n  }\n  if (returnValidOutputs) {\n    result[\"validOutputs\"] = validOutputs;\n  }\n  return result;\n}\nfunction intersectionOverUnion(boxes, i2, j) {\n  const iCoord = boxes.subarray(i2 * 4, i2 * 4 + 4);\n  const jCoord = boxes.subarray(j * 4, j * 4 + 4);\n  const yminI = Math.min(iCoord[0], iCoord[2]);\n  const xminI = Math.min(iCoord[1], iCoord[3]);\n  const ymaxI = Math.max(iCoord[0], iCoord[2]);\n  const xmaxI = Math.max(iCoord[1], iCoord[3]);\n  const yminJ = Math.min(jCoord[0], jCoord[2]);\n  const xminJ = Math.min(jCoord[1], jCoord[3]);\n  const ymaxJ = Math.max(jCoord[0], jCoord[2]);\n  const xmaxJ = Math.max(jCoord[1], jCoord[3]);\n  const areaI = (ymaxI - yminI) * (xmaxI - xminI);\n  const areaJ = (ymaxJ - yminJ) * (xmaxJ - xminJ);\n  if (areaI <= 0 || areaJ <= 0) {\n    return 0;\n  }\n  const intersectionYmin = Math.max(yminI, yminJ);\n  const intersectionXmin = Math.max(xminI, xminJ);\n  const intersectionYmax = Math.min(ymaxI, ymaxJ);\n  const intersectionXmax = Math.min(xmaxI, xmaxJ);\n  const intersectionArea = Math.max(intersectionYmax - intersectionYmin, 0) * Math.max(intersectionXmax - intersectionXmin, 0);\n  return intersectionArea / (areaI + areaJ - intersectionArea);\n}\nfunction suppressWeight(iouThreshold, scale2, iou) {\n  const weight = Math.exp(scale2 * iou * iou);\n  return iou <= iouThreshold ? weight : 0;\n}\nfunction ascendingComparator(c1, c2) {\n  return c1.score - c2.score || c1.score === c2.score && c2.boxIndex - c1.boxIndex;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/non_max_suppression_async.js\nasync function nonMaxSuppressionAsync_(boxes, scores, maxOutputSize, iouThreshold = 0.5, scoreThreshold = Number.NEGATIVE_INFINITY) {\n  const $boxes = convertToTensor(boxes, \"boxes\", \"nonMaxSuppressionAsync\");\n  const $scores = convertToTensor(scores, \"scores\", \"nonMaxSuppressionAsync\");\n  const inputs = nonMaxSuppSanityCheck($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold);\n  maxOutputSize = inputs.maxOutputSize;\n  iouThreshold = inputs.iouThreshold;\n  scoreThreshold = inputs.scoreThreshold;\n  const boxesAndScores = await Promise.all([$boxes.data(), $scores.data()]);\n  const boxesVals = boxesAndScores[0];\n  const scoresVals = boxesAndScores[1];\n  const { selectedIndices } = nonMaxSuppressionV3Impl(boxesVals, scoresVals, maxOutputSize, iouThreshold, scoreThreshold);\n  if ($boxes !== boxes) {\n    $boxes.dispose();\n  }\n  if ($scores !== scores) {\n    $scores.dispose();\n  }\n  return tensor1d(selectedIndices, \"int32\");\n}\nvar nonMaxSuppressionAsync = nonMaxSuppressionAsync_;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/non_max_suppression_with_score.js\nfunction nonMaxSuppressionWithScore_(boxes, scores, maxOutputSize, iouThreshold = 0.5, scoreThreshold = Number.NEGATIVE_INFINITY, softNmsSigma = 0) {\n  const $boxes = convertToTensor(boxes, \"boxes\", \"nonMaxSuppression\");\n  const $scores = convertToTensor(scores, \"scores\", \"nonMaxSuppression\");\n  const params = nonMaxSuppSanityCheck($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma);\n  maxOutputSize = params.maxOutputSize;\n  iouThreshold = params.iouThreshold;\n  scoreThreshold = params.scoreThreshold;\n  softNmsSigma = params.softNmsSigma;\n  const inputs = { boxes: $boxes, scores: $scores };\n  const attrs = { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma };\n  const result = ENGINE.runKernel(NonMaxSuppressionV5, inputs, attrs);\n  return { selectedIndices: result[0], selectedScores: result[1] };\n}\nvar nonMaxSuppressionWithScore = op({ nonMaxSuppressionWithScore_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/non_max_suppression_with_score_async.js\nasync function nonMaxSuppressionWithScoreAsync_(boxes, scores, maxOutputSize, iouThreshold = 0.5, scoreThreshold = Number.NEGATIVE_INFINITY, softNmsSigma = 0) {\n  const $boxes = convertToTensor(boxes, \"boxes\", \"nonMaxSuppressionAsync\");\n  const $scores = convertToTensor(scores, \"scores\", \"nonMaxSuppressionAsync\");\n  const params = nonMaxSuppSanityCheck($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma);\n  maxOutputSize = params.maxOutputSize;\n  iouThreshold = params.iouThreshold;\n  scoreThreshold = params.scoreThreshold;\n  softNmsSigma = params.softNmsSigma;\n  const boxesAndScores = await Promise.all([$boxes.data(), $scores.data()]);\n  const boxesVals = boxesAndScores[0];\n  const scoresVals = boxesAndScores[1];\n  const { selectedIndices, selectedScores } = nonMaxSuppressionV5Impl(boxesVals, scoresVals, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma);\n  if ($boxes !== boxes) {\n    $boxes.dispose();\n  }\n  if ($scores !== scores) {\n    $scores.dispose();\n  }\n  return {\n    selectedIndices: tensor1d(selectedIndices, \"int32\"),\n    selectedScores: tensor1d(selectedScores)\n  };\n}\nvar nonMaxSuppressionWithScoreAsync = nonMaxSuppressionWithScoreAsync_;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/non_max_suppression_padded.js\nfunction nonMaxSuppressionPadded_(boxes, scores, maxOutputSize, iouThreshold = 0.5, scoreThreshold = Number.NEGATIVE_INFINITY, padToMaxOutputSize = false) {\n  const $boxes = convertToTensor(boxes, \"boxes\", \"nonMaxSuppression\");\n  const $scores = convertToTensor(scores, \"scores\", \"nonMaxSuppression\");\n  const params = nonMaxSuppSanityCheck($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold, null);\n  const $maxOutputSize = params.maxOutputSize;\n  const $iouThreshold = params.iouThreshold;\n  const $scoreThreshold = params.scoreThreshold;\n  const inputs = { boxes: $boxes, scores: $scores };\n  const attrs = {\n    maxOutputSize: $maxOutputSize,\n    iouThreshold: $iouThreshold,\n    scoreThreshold: $scoreThreshold,\n    padToMaxOutputSize\n  };\n  const result = ENGINE.runKernel(NonMaxSuppressionV4, inputs, attrs);\n  return { selectedIndices: result[0], validOutputs: result[1] };\n}\nvar nonMaxSuppressionPadded = op({ nonMaxSuppressionPadded_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/non_max_suppression_padded_async.js\nasync function nonMaxSuppressionPaddedAsync_(boxes, scores, maxOutputSize, iouThreshold = 0.5, scoreThreshold = Number.NEGATIVE_INFINITY, padToMaxOutputSize = false) {\n  const $boxes = convertToTensor(boxes, \"boxes\", \"nonMaxSuppressionAsync\");\n  const $scores = convertToTensor(scores, \"scores\", \"nonMaxSuppressionAsync\");\n  const params = nonMaxSuppSanityCheck($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold, null);\n  const $maxOutputSize = params.maxOutputSize;\n  const $iouThreshold = params.iouThreshold;\n  const $scoreThreshold = params.scoreThreshold;\n  const [boxesVals, scoresVals] = await Promise.all([$boxes.data(), $scores.data()]);\n  const { selectedIndices, validOutputs } = nonMaxSuppressionV4Impl(boxesVals, scoresVals, $maxOutputSize, $iouThreshold, $scoreThreshold, padToMaxOutputSize);\n  if ($boxes !== boxes) {\n    $boxes.dispose();\n  }\n  if ($scores !== scores) {\n    $scores.dispose();\n  }\n  return {\n    selectedIndices: tensor1d(selectedIndices, \"int32\"),\n    validOutputs: scalar(validOutputs, \"int32\")\n  };\n}\nvar nonMaxSuppressionPaddedAsync = nonMaxSuppressionPaddedAsync_;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/resize_bilinear.js\nfunction resizeBilinear_(images, size, alignCorners = false, halfPixelCenters = false) {\n  const $images = convertToTensor(images, \"images\", \"resizeBilinear\");\n  assert($images.rank === 3 || $images.rank === 4, () => `Error in resizeBilinear: x must be rank 3 or 4, but got rank ${$images.rank}.`);\n  assert(size.length === 2, () => `Error in resizeBilinear: new shape must 2D, but got shape ${size}.`);\n  assert(halfPixelCenters === false || alignCorners === false, () => `Error in resizeBilinear: If halfPixelCenters is true, alignCorners must be false.`);\n  let batchImages = $images;\n  let reshapedTo4D = false;\n  if ($images.rank === 3) {\n    reshapedTo4D = true;\n    batchImages = reshape($images, [1, $images.shape[0], $images.shape[1], $images.shape[2]]);\n  }\n  const [] = size;\n  const inputs = { images: batchImages };\n  const attrs = { alignCorners, halfPixelCenters, size };\n  const res = ENGINE.runKernel(ResizeBilinear, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar resizeBilinear = op({ resizeBilinear_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/resize_nearest_neighbor.js\nfunction resizeNearestNeighbor_(images, size, alignCorners = false, halfPixelCenters = false) {\n  const $images = convertToTensor(images, \"images\", \"resizeNearestNeighbor\");\n  assert($images.rank === 3 || $images.rank === 4, () => `Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank ${$images.rank}.`);\n  assert(size.length === 2, () => `Error in resizeNearestNeighbor: new shape must 2D, but got shape ${size}.`);\n  assert($images.dtype === \"float32\" || $images.dtype === \"int32\", () => \"`images` must have `int32` or `float32` as dtype\");\n  assert(halfPixelCenters === false || alignCorners === false, () => `Error in resizeNearestNeighbor: If halfPixelCenters is true, alignCorners must be false.`);\n  let batchImages = $images;\n  let reshapedTo4D = false;\n  if ($images.rank === 3) {\n    reshapedTo4D = true;\n    batchImages = reshape($images, [1, $images.shape[0], $images.shape[1], $images.shape[2]]);\n  }\n  const [] = size;\n  const inputs = { images: batchImages };\n  const attrs = { alignCorners, halfPixelCenters, size };\n  const res = ENGINE.runKernel(ResizeNearestNeighbor, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar resizeNearestNeighbor = op({ resizeNearestNeighbor_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/threshold.js\nfunction threshold_(image2, method = \"binary\", inverted = false, threshValue = 0.5) {\n  const $image = convertToTensor(image2, \"image\", \"threshold\");\n  const RED_INTENCITY_COEF = 0.2989;\n  const GREEN_INTENCITY_COEF = 0.587;\n  const BLUE_INTENCITY_COEF = 0.114;\n  const totalPixelsInImage = $image.shape[0] * $image.shape[1];\n  let $threshold = mul(tensor1d([threshValue]), 255);\n  let r2, g, b, grayscale;\n  assert($image.rank === 3, () => `Error in threshold: image must be rank 3,but got rank ${$image.rank}.`);\n  assert($image.shape[2] === 3 || $image.shape[2] === 1, () => `Error in threshold: image color channel must be equal to 3 or 1but got ${$image.shape[2]}.`);\n  assert($image.dtype === \"int32\" || $image.dtype === \"float32\", () => `Error in dtype: image dtype must be int32 or float32,but got dtype ${$image.dtype}.`);\n  assert(method === \"otsu\" || method === \"binary\", () => `Method must be binary or otsu, but was ${method}`);\n  if ($image.shape[2] === 3) {\n    [r2, g, b] = split($image, [1, 1, 1], -1);\n    const $r = mul(r2, RED_INTENCITY_COEF);\n    const $g = mul(g, GREEN_INTENCITY_COEF);\n    const $b = mul(b, BLUE_INTENCITY_COEF);\n    grayscale = add2(add2($r, $g), $b);\n  } else {\n    grayscale = image2;\n  }\n  if (method === \"otsu\") {\n    const $histogram = bincount(cast(round2(grayscale), \"int32\"), tensor([]), 256);\n    $threshold = otsu($histogram, totalPixelsInImage);\n  }\n  const invCondition = inverted ? lessEqual(grayscale, $threshold) : greater(grayscale, $threshold);\n  const result = cast(mul(invCondition, 255), \"int32\");\n  return result;\n}\nfunction otsu(histogram, total) {\n  let bestThresh = tensor1d([-1]);\n  let bestInBetVar = tensor1d([0]);\n  let cInBetVar = tensor1d([0]);\n  let classFirst, classSecond, meanFirst, meanSec, weightForeground, weightBack;\n  for (let index = 0; index < histogram.size - 1; index++) {\n    classFirst = slice(histogram, 0, index + 1);\n    classSecond = slice(histogram, index + 1);\n    weightForeground = div(sum2(classFirst), total);\n    weightBack = div(sum2(classSecond), total);\n    const meanFirstDivA = sum2(mul(classFirst, range(0, classFirst.size)));\n    meanFirst = div(meanFirstDivA, sum2(classFirst));\n    const meanSecFill = fill(classSecond.shape, classFirst.size);\n    const meanSecAdd = add2(range(0, classSecond.size), meanSecFill);\n    const meanSecMul = mul(classSecond, meanSecAdd);\n    meanSec = div(sum2(meanSecMul), sum2(classSecond));\n    const cInBetVarSubA = sub(meanFirst, meanSec);\n    const cInBetVarSubB = sub(meanFirst, meanSec);\n    const cInBetVarMul = mul(weightForeground, weightBack);\n    cInBetVar = mul(mul(cInBetVarMul, cInBetVarSubA), cInBetVarSubB);\n    const condition = greater(cInBetVar, bestInBetVar);\n    bestInBetVar = where(condition, cInBetVar, bestInBetVar);\n    bestThresh = where(condition, tensor1d([index]), bestThresh);\n  }\n  return bestThresh;\n}\nvar threshold = op({ threshold_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/transform.js\nfunction transform_(image2, transforms, interpolation = \"nearest\", fillMode = \"constant\", fillValue = 0, outputShape) {\n  const $image = convertToTensor(image2, \"image\", \"transform\", \"float32\");\n  const $transforms = convertToTensor(transforms, \"transforms\", \"transform\", \"float32\");\n  assert($image.rank === 4, () => `Error in transform: image must be rank 4,but got rank ${$image.rank}.`);\n  assert($transforms.rank === 2 && ($transforms.shape[0] === $image.shape[0] || $transforms.shape[0] === 1) && $transforms.shape[1] === 8, () => `Error in transform: Input transform should be batch x 8 or 1 x 8`);\n  assert(outputShape == null || outputShape.length === 2, () => `Error in transform: outputShape must be [height, width] or null, but got ${outputShape}.`);\n  const inputs = { image: $image, transforms: $transforms };\n  const attrs = { interpolation, fillMode, fillValue, outputShape };\n  return ENGINE.runKernel(Transform, inputs, attrs);\n}\nvar transform = op({ transform_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/linalg/band_part.js\nfunction bandPart_(a, numLower, numUpper) {\n  assert(numLower % 1 === 0, () => `bandPart(): numLower must be an integer, got ${numLower}.`);\n  assert(numUpper % 1 === 0, () => `bandPart(): numUpper must be an integer, got ${numUpper}.`);\n  const $a = convertToTensor(a, \"a\", \"bandPart\");\n  assert($a.rank >= 2, () => `bandPart(): Rank must be at least 2, got ${$a.rank}.`);\n  const shape = $a.shape;\n  const [M, N] = $a.shape.slice(-2);\n  if (!(numLower <= M)) {\n    throw new Error(`bandPart(): numLower (${numLower}) must not be greater than the number of rows (${M}).`);\n  }\n  if (!(numUpper <= N)) {\n    throw new Error(`bandPart(): numUpper (${numUpper}) must not be greater than the number of columns (${N}).`);\n  }\n  if (numLower < 0) {\n    numLower = M;\n  }\n  if (numUpper < 0) {\n    numUpper = N;\n  }\n  const i2 = reshape(range(0, M, 1, \"int32\"), [-1, 1]);\n  const j = range(0, N, 1, \"int32\");\n  const ij = sub(i2, j);\n  const inBand = logicalAnd(lessEqual(ij, scalar(+numLower, \"int32\")), greaterEqual(ij, scalar(-numUpper, \"int32\")));\n  const zero = zeros([M, N], $a.dtype);\n  return reshape(stack(unstack(reshape($a, [-1, M, N])).map((mat) => where(inBand, mat, zero))), shape);\n}\nvar bandPart = op({ bandPart_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/linalg/gram_schmidt.js\nfunction gramSchmidt_(xs) {\n  let inputIsTensor2D;\n  if (Array.isArray(xs)) {\n    inputIsTensor2D = false;\n    assert(xs != null && xs.length > 0, () => \"Gram-Schmidt process: input must not be null, undefined, or empty\");\n    const dim = xs[0].shape[0];\n    for (let i2 = 1; i2 < xs.length; ++i2) {\n      assert(xs[i2].shape[0] === dim, () => `Gram-Schmidt: Non-unique lengths found in the input vectors: (${xs[i2].shape[0]} vs. ${dim})`);\n    }\n  } else {\n    inputIsTensor2D = true;\n    xs = split(xs, xs.shape[0], 0).map((x) => squeeze(x, [0]));\n  }\n  assert(xs.length <= xs[0].shape[0], () => `Gram-Schmidt: Number of vectors (${xs.length}) exceeds number of dimensions (${xs[0].shape[0]}).`);\n  const ys = [];\n  const xs1d = xs;\n  for (let i2 = 0; i2 < xs.length; ++i2) {\n    ys.push(ENGINE.tidy(() => {\n      let x = xs1d[i2];\n      if (i2 > 0) {\n        for (let j = 0; j < i2; ++j) {\n          const proj = mul(sum2(mul(ys[j], x)), ys[j]);\n          x = sub(x, proj);\n        }\n      }\n      return div(x, norm(x, \"euclidean\"));\n    }));\n  }\n  if (inputIsTensor2D) {\n    return stack(ys, 0);\n  } else {\n    return ys;\n  }\n}\nvar gramSchmidt = op({ gramSchmidt_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/linalg/qr.js\nfunction qr_(x, fullMatrices = false) {\n  assert(x.rank >= 2, () => `qr() requires input tensor to have a rank >= 2, but got rank ${x.rank}`);\n  if (x.rank === 2) {\n    return qr2d(x, fullMatrices);\n  } else {\n    const outerDimsProd = x.shape.slice(0, x.shape.length - 2).reduce((value, prev) => value * prev);\n    const x2ds = unstack(reshape(x, [\n      outerDimsProd,\n      x.shape[x.shape.length - 2],\n      x.shape[x.shape.length - 1]\n    ]), 0);\n    const q2ds = [];\n    const r2ds = [];\n    x2ds.forEach((x2d) => {\n      const [q2d, r2d] = qr2d(x2d, fullMatrices);\n      q2ds.push(q2d);\n      r2ds.push(r2d);\n    });\n    const q = reshape(stack(q2ds, 0), x.shape);\n    const r2 = reshape(stack(r2ds, 0), x.shape);\n    return [q, r2];\n  }\n}\nfunction qr2d(x, fullMatrices = false) {\n  return ENGINE.tidy(() => {\n    assert(x.shape.length === 2, () => `qr2d() requires a 2D Tensor, but got a ${x.shape.length}D Tensor.`);\n    const m = x.shape[0];\n    const n2 = x.shape[1];\n    let q = eye(m);\n    let r2 = clone(x);\n    const one2D = tensor2d([[1]], [1, 1]);\n    let w = clone(one2D);\n    const iters = m >= n2 ? n2 : m;\n    for (let j = 0; j < iters; ++j) {\n      const rTemp = r2;\n      const wTemp = w;\n      const qTemp = q;\n      [w, r2, q] = ENGINE.tidy(() => {\n        const rjEnd1 = slice(r2, [j, j], [m - j, 1]);\n        const normX = norm(rjEnd1);\n        const rjj = slice(r2, [j, j], [1, 1]);\n        const s2 = where(greater(rjj, 0), tensor2d([[-1]]), tensor2d([[1]]));\n        const u1 = sub(rjj, mul(s2, normX));\n        const wPre = div(rjEnd1, u1);\n        if (wPre.shape[0] === 1) {\n          w = clone(one2D);\n        } else {\n          w = concat([\n            one2D,\n            slice(wPre, [1, 0], [wPre.shape[0] - 1, wPre.shape[1]])\n          ], 0);\n        }\n        const tau = neg(div(matMul(s2, u1), normX));\n        const rjEndAll = slice(r2, [j, 0], [m - j, n2]);\n        const tauTimesW = mul(tau, w);\n        const wT = transpose(w);\n        if (j === 0) {\n          r2 = sub(rjEndAll, matMul(tauTimesW, matMul(wT, rjEndAll)));\n        } else {\n          const rTimesTau = sub(rjEndAll, matMul(tauTimesW, matMul(wT, rjEndAll)));\n          r2 = concat([slice(r2, [0, 0], [j, n2]), rTimesTau], 0);\n        }\n        const tawTimesWT = transpose(tauTimesW);\n        const qAllJEnd = slice(q, [0, j], [m, q.shape[1] - j]);\n        if (j === 0) {\n          q = sub(qAllJEnd, matMul(matMul(qAllJEnd, w), tawTimesWT));\n        } else {\n          const qTimesTau = sub(qAllJEnd, matMul(matMul(qAllJEnd, w), tawTimesWT));\n          q = concat([slice(q, [0, 0], [m, j]), qTimesTau], 1);\n        }\n        return [w, r2, q];\n      });\n      dispose([rTemp, wTemp, qTemp]);\n    }\n    if (!fullMatrices && m > n2) {\n      q = slice(q, [0, 0], [m, n2]);\n      r2 = slice(r2, [0, 0], [n2, n2]);\n    }\n    return [q, r2];\n  });\n}\nvar qr = op({ qr_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/loss_ops_utils.js\nvar Reduction;\n(function(Reduction2) {\n  Reduction2[Reduction2[\"NONE\"] = 0] = \"NONE\";\n  Reduction2[Reduction2[\"MEAN\"] = 1] = \"MEAN\";\n  Reduction2[Reduction2[\"SUM\"] = 2] = \"SUM\";\n  Reduction2[Reduction2[\"SUM_BY_NONZERO_WEIGHTS\"] = 3] = \"SUM_BY_NONZERO_WEIGHTS\";\n})(Reduction || (Reduction = {}));\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/compute_weighted_loss.js\nfunction computeWeightedLoss_(losses2, weights, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  const $losses = convertToTensor(losses2, \"losses\", \"computeWeightedLoss\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"computeWeightedLoss\");\n  }\n  const weightedLoss = $weights == null ? $losses : mul($losses, $weights);\n  if (reduction === Reduction.NONE) {\n    return weightedLoss;\n  }\n  if (reduction === Reduction.SUM) {\n    return sum2(weightedLoss);\n  }\n  if (reduction === Reduction.MEAN) {\n    if ($weights == null) {\n      return mean(weightedLoss);\n    } else {\n      const broadcastFactor = $losses.size / $weights.size;\n      const result = div(sum2(weightedLoss), sum2($weights));\n      return broadcastFactor > 1 ? div(result, scalar(broadcastFactor)) : result;\n    }\n  }\n  if (reduction === Reduction.SUM_BY_NONZERO_WEIGHTS) {\n    if ($weights == null) {\n      return div(sum2(weightedLoss), scalar($losses.size));\n    } else {\n      const broadcastedWeights = mul($weights, ones2($losses.shape));\n      const numNonZeros = cast(sum2(notEqual(broadcastedWeights, scalar(0))), \"float32\");\n      return div(sum2(weightedLoss), numNonZeros);\n    }\n  }\n  throw Error(`Unknown reduction: ${reduction}`);\n}\nvar computeWeightedLoss = op({ computeWeightedLoss_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/absolute_difference.js\nfunction absoluteDifference_(labels, predictions, weights, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  const $labels = convertToTensor(labels, \"labels\", \"absoluteDifference\");\n  const $predictions = convertToTensor(predictions, \"predictions\", \"absoluteDifference\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"absoluteDifference\");\n  }\n  assertShapesMatch($labels.shape, $predictions.shape, \"Error in absoluteDifference: \");\n  const losses2 = abs(sub($labels, $predictions));\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar absoluteDifference = op({ absoluteDifference_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/cosine_distance.js\nfunction cosineDistance_(labels, predictions, axis, weights, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  const $labels = convertToTensor(labels, \"labels\", \"cosineDistance\");\n  const $predictions = convertToTensor(predictions, \"predictions\", \"cosineDistance\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"cosineDistance\");\n  }\n  assertShapesMatch($labels.shape, $predictions.shape, \"Error in cosineDistance: \");\n  const one = scalar(1);\n  const losses2 = sub(one, sum2(mul($labels, $predictions), axis, true));\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar cosineDistance = op({ cosineDistance_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/hinge_loss.js\nfunction hingeLoss_(labels, predictions, weights, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  let $labels = convertToTensor(labels, \"labels\", \"hingeLoss\");\n  const $predictions = convertToTensor(predictions, \"predictions\", \"hingeLoss\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"hingeLoss\");\n  }\n  assertShapesMatch($labels.shape, $predictions.shape, \"Error in hingeLoss: \");\n  const one = scalar(1);\n  $labels = sub(mul(scalar(2), $labels), one);\n  const losses2 = relu(sub(one, mul($labels, $predictions)));\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar hingeLoss = op({ hingeLoss_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/huber_loss.js\nfunction huberLoss_(labels, predictions, weights, delta = 1, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  const $labels = convertToTensor(labels, \"labels\", \"huberLoss\");\n  const $predictions = convertToTensor(predictions, \"predictions\", \"huberLoss\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"huberLoss\");\n  }\n  assertShapesMatch($labels.shape, $predictions.shape, \"Error in huberLoss: \");\n  const deltaScalar = scalar(delta);\n  const error = abs(sub($predictions, $labels));\n  const quadratic = minimum(error, deltaScalar);\n  const linear = sub(error, quadratic);\n  const losses2 = add2(mul(scalar(0.5), square(quadratic)), mul(deltaScalar, linear));\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar huberLoss = op({ huberLoss_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/log_loss.js\nfunction logLoss_(labels, predictions, weights, epsilon3 = 1e-7, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  const $labels = convertToTensor(labels, \"labels\", \"logLoss\");\n  const $predictions = convertToTensor(predictions, \"predictions\", \"logLoss\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"logLoss\");\n  }\n  assertShapesMatch($labels.shape, $predictions.shape, \"Error in logLoss: \");\n  const one = scalar(1);\n  const epsilonScalar = scalar(epsilon3);\n  const l13 = neg(mul($labels, log2(add2($predictions, epsilonScalar))));\n  const l23 = mul(sub(one, $labels), log2(add2(sub(one, $predictions), epsilonScalar)));\n  const losses2 = sub(l13, l23);\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar logLoss = op({ logLoss_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/mean_squared_error.js\nfunction meanSquaredError_(labels, predictions, weights, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  const $labels = convertToTensor(labels, \"labels\", \"meanSquaredError\");\n  const $predictions = convertToTensor(predictions, \"predictions\", \"meanSquaredError\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"meanSquaredError\");\n  }\n  assertShapesMatch($labels.shape, $predictions.shape, \"Error in meanSquaredError: \");\n  const losses2 = squaredDifference($labels, $predictions);\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar meanSquaredError = op({ meanSquaredError_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/sigmoid_cross_entropy.js\nfunction sigmoidCrossEntropyWithLogits_(labels, logits) {\n  const $labels = convertToTensor(labels, \"labels\", \"sigmoidCrossEntropyWithLogits\");\n  const $logits = convertToTensor(logits, \"logits\", \"sigmoidCrossEntropyWithLogits\");\n  assertShapesMatch($labels.shape, $logits.shape, \"Error in sigmoidCrossEntropyWithLogits: \");\n  const maxOutput = relu($logits);\n  const outputXTarget = mul($logits, $labels);\n  const sigmoidOutput = log1p(exp(neg(abs($logits))));\n  return add2(sub(maxOutput, outputXTarget), sigmoidOutput);\n}\nfunction sigmoidCrossEntropy_(multiClassLabels, logits, weights, labelSmoothing = 0, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  let $multiClassLabels = convertToTensor(multiClassLabels, \"multiClassLabels\", \"sigmoidCrossEntropy\");\n  const $logits = convertToTensor(logits, \"logits\", \"sigmoidCrossEntropy\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"sigmoidCrossEntropy\");\n  }\n  assertShapesMatch($multiClassLabels.shape, $logits.shape, \"Error in sigmoidCrossEntropy: \");\n  if (labelSmoothing > 0) {\n    const labelSmoothingScalar = scalar(labelSmoothing);\n    const one = scalar(1);\n    const half = scalar(0.5);\n    $multiClassLabels = add2(mul($multiClassLabels, sub(one, labelSmoothingScalar)), mul(half, labelSmoothingScalar));\n  }\n  const losses2 = sigmoidCrossEntropyWithLogits_($multiClassLabels, $logits);\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar sigmoidCrossEntropy = op({ sigmoidCrossEntropy_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/softmax_cross_entropy.js\nfunction softmaxCrossEntropyWithLogits_(labels, logits, dim = -1) {\n  if (dim === -1) {\n    dim = logits.rank - 1;\n  }\n  if (dim !== logits.rank - 1) {\n    throw Error(`Softmax cross entropy along a non-last dimension is not yet supported. Labels / logits was rank ${logits.rank} and dim was ${dim}`);\n  }\n  const customOp = customGrad((labels2, logits2, save) => {\n    const keepDims = true;\n    const lse = logSumExp(logits2, [dim], keepDims);\n    const logResult = sub(cast(logits2, \"float32\"), lse);\n    save([labels2, logResult]);\n    const costVector = neg(mul(logResult, labels2));\n    const value = sum2(costVector, [dim]);\n    const gradFunc = (dy, saved) => {\n      const [labels3, logResult2] = saved;\n      const dyShape = expandShapeToKeepDim(dy.shape, [dim]);\n      return [\n        mul(reshape(dy, dyShape), sub(cast(labels3, \"float32\"), exp(logResult2))),\n        mul(reshape(dy, dyShape), sub(exp(logResult2), cast(labels3, \"float32\")))\n      ];\n    };\n    return { value, gradFunc };\n  });\n  return customOp(labels, logits);\n}\nfunction softmaxCrossEntropy_(onehotLabels, logits, weights, labelSmoothing = 0, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  let $onehotLabels = convertToTensor(onehotLabels, \"onehotLabels\", \"softmaxCrossEntropy\");\n  const $logits = convertToTensor(logits, \"logits\", \"softmaxCrossEntropy\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"softmaxCrossEntropy\");\n  }\n  assertShapesMatch($onehotLabels.shape, $logits.shape, \"Error in softmaxCrossEntropy: \");\n  if (labelSmoothing > 0) {\n    const labelSmoothingScalar = scalar(labelSmoothing);\n    const one = scalar(1);\n    const numClasses = scalar($onehotLabels.shape[1]);\n    $onehotLabels = add2(mul($onehotLabels, sub(one, labelSmoothingScalar)), div(labelSmoothingScalar, numClasses));\n  }\n  const losses2 = softmaxCrossEntropyWithLogits_($onehotLabels, $logits);\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar softmaxCrossEntropy = op({ softmaxCrossEntropy_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse/sparse_fill_empty_rows.js\nfunction sparseFillEmptyRows_(indices, values, denseShape, defaultValue) {\n  const $indices = convertToTensor(indices, \"indices\", \"sparseFillEmptyRows\", \"int32\");\n  const $values = convertToTensor(values, \"values\", \"sparseFillEmptyRows\");\n  const $denseShape = convertToTensor(denseShape, \"denseShape\", \"sparseFillEmptyRows\", \"int32\");\n  const $defaultValue = convertToTensor(defaultValue, \"defaultValue\", \"sparseFillEmptyRows\", $values.dtype);\n  if ($indices.rank !== 2) {\n    throw new Error(`Indices should be Tensor2D but received shape\n        ${$indices.shape}`);\n  }\n  if ($values.rank !== 1) {\n    throw new Error(`Values should be Tensor1D but received shape ${$values.shape}`);\n  }\n  if ($denseShape.rank !== 1) {\n    throw new Error(`Dense shape should be Tensor1D but received shape ${$denseShape.shape}`);\n  }\n  if ($defaultValue.rank !== 0) {\n    throw new Error(`Default value should be a scalar but received shape ${$defaultValue.shape}`);\n  }\n  const inputs = {\n    indices: $indices,\n    values: $values,\n    denseShape: $denseShape,\n    defaultValue: $defaultValue\n  };\n  const result = ENGINE.runKernel(SparseFillEmptyRows, inputs);\n  return {\n    outputIndices: result[0],\n    outputValues: result[1],\n    emptyRowIndicator: result[2],\n    reverseIndexMap: result[3]\n  };\n}\nvar sparseFillEmptyRows = op({ sparseFillEmptyRows_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse/sparse_reshape.js\nfunction sparseReshape_(inputIndices, inputShape, newShape) {\n  const $inputIndices = convertToTensor(inputIndices, \"inputIndices\", \"sparseReshape\", \"int32\");\n  const $inputShape = convertToTensor(inputShape, \"inputShape\", \"sparseReshape\", \"int32\");\n  const $newShape = convertToTensor(newShape, \"newShape\", \"sparseReshape\", \"int32\");\n  if ($inputIndices.rank !== 2) {\n    throw new Error(`Input indices should be Tensor2D but received shape\n        ${$inputIndices.shape}`);\n  }\n  if ($inputShape.rank !== 1) {\n    throw new Error(`Input shape should be Tensor1D but received shape ${$inputShape.shape}`);\n  }\n  if ($newShape.rank !== 1) {\n    throw new Error(`New shape should be Tensor1D but received shape ${$newShape.shape}`);\n  }\n  const inputs = {\n    inputIndices: $inputIndices,\n    inputShape: $inputShape,\n    newShape: $newShape\n  };\n  const result = ENGINE.runKernel(SparseReshape, inputs);\n  return { outputIndices: result[0], outputShape: result[1] };\n}\nvar sparseReshape = op({ sparseReshape_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse/sparse_segment_mean.js\nfunction sparseSegmentMean_(data, indices, segmentIds) {\n  const $data = convertToTensor(data, \"data\", \"sparseSegmentMean\");\n  const $indices = convertToTensor(indices, \"indices\", \"sparseSegmentMean\", \"int32\");\n  const $segmentIds = convertToTensor(segmentIds, \"segmentIds\", \"sparseSegmentMean\", \"int32\");\n  if ($data.rank < 1) {\n    throw new Error(`Data should be at least 1 dimensional but received scalar`);\n  }\n  if ($indices.rank !== 1) {\n    throw new Error(`Indices should be Tensor1D but received shape\n          ${$indices.shape}`);\n  }\n  if ($segmentIds.rank !== 1) {\n    throw new Error(`Segment ids should be Tensor1D but received shape\n          ${$segmentIds.shape}`);\n  }\n  const inputs = {\n    data: $data,\n    indices: $indices,\n    segmentIds: $segmentIds\n  };\n  return ENGINE.runKernel(SparseSegmentMean, inputs);\n}\nvar sparseSegmentMean = op({ sparseSegmentMean_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse/sparse_segment_sum.js\nfunction sparseSegmentSum_(data, indices, segmentIds) {\n  const $data = convertToTensor(data, \"data\", \"sparseSegmentSum\");\n  const $indices = convertToTensor(indices, \"indices\", \"sparseSegmentSum\", \"int32\");\n  const $segmentIds = convertToTensor(segmentIds, \"segmentIds\", \"sparseSegmentSum\", \"int32\");\n  if ($data.rank < 1) {\n    throw new Error(`Data should be at least 1 dimensional but received scalar`);\n  }\n  if ($indices.rank !== 1) {\n    throw new Error(`Indices should be Tensor1D but received shape\n         ${$indices.shape}`);\n  }\n  if ($segmentIds.rank !== 1) {\n    throw new Error(`Segment ids should be Tensor1D but received shape\n         ${$segmentIds.shape}`);\n  }\n  const inputs = {\n    data: $data,\n    indices: $indices,\n    segmentIds: $segmentIds\n  };\n  return ENGINE.runKernel(SparseSegmentSum, inputs);\n}\nvar sparseSegmentSum = op({ sparseSegmentSum_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/string/string_n_grams.js\nfunction stringNGrams_(data, dataSplits, separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences) {\n  const $data = convertToTensor(data, \"data\", \"stringNGrams\", \"string\");\n  if ($data.dtype !== \"string\") {\n    throw new Error(\"Data must be of datatype string\");\n  }\n  if ($data.shape.length !== 1) {\n    throw new Error(`Data must be a vector, saw: ${$data.shape}`);\n  }\n  const $dataSplits = convertToTensor(dataSplits, \"dataSplits\", \"stringNGrams\");\n  if ($dataSplits.dtype !== \"int32\") {\n    throw new Error(\"Data splits must be of datatype int32\");\n  }\n  const attrs = {\n    separator,\n    nGramWidths,\n    leftPad,\n    rightPad: rightPad2,\n    padWidth,\n    preserveShortSequences\n  };\n  const inputs = { data: $data, dataSplits: $dataSplits };\n  const result = ENGINE.runKernel(StringNGrams, inputs, attrs);\n  return { nGrams: result[0], nGramsSplits: result[1] };\n}\nvar stringNGrams = op({ stringNGrams_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/string/string_split.js\nfunction stringSplit_(input2, delimiter, skipEmpty = true) {\n  const $input = convertToTensor(input2, \"input\", \"stringSplit\", \"string\");\n  const $delimiter = convertToTensor(delimiter, \"delimiter\", \"stringSplit\", \"string\");\n  if ($input.rank !== 1) {\n    throw new Error(`Input should be Tensor1D but received shape ${$input.shape}`);\n  }\n  if ($delimiter.rank !== 0) {\n    throw new Error(`Delimiter should be a scalar but received shape ${$delimiter.shape}`);\n  }\n  const attrs = { skipEmpty };\n  const inputs = { input: $input, delimiter: $delimiter };\n  const result = ENGINE.runKernel(StringSplit, inputs, attrs);\n  return { indices: result[0], values: result[1], shape: result[2] };\n}\nvar stringSplit = op({ stringSplit_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/string/string_to_hash_bucket_fast.js\nfunction stringToHashBucketFast_(input2, numBuckets) {\n  const $input = convertToTensor(input2, \"input\", \"stringToHashBucketFast\", \"string\");\n  const attrs = { numBuckets };\n  if (numBuckets <= 0) {\n    throw new Error(`Number of buckets must be at least 1`);\n  }\n  const inputs = { input: $input };\n  return ENGINE.runKernel(StringToHashBucketFast, inputs, attrs);\n}\nvar stringToHashBucketFast = op({ stringToHashBucketFast_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/ops.js\nvar spectral = {\n  fft,\n  ifft,\n  rfft,\n  irfft\n};\nvar signal = {\n  hammingWindow,\n  hannWindow,\n  frame,\n  stft\n};\nvar image = {\n  flipLeftRight,\n  grayscaleToRGB,\n  resizeNearestNeighbor,\n  resizeBilinear,\n  rotateWithOffset,\n  cropAndResize,\n  nonMaxSuppression,\n  nonMaxSuppressionAsync,\n  nonMaxSuppressionWithScore,\n  nonMaxSuppressionWithScoreAsync,\n  nonMaxSuppressionPadded,\n  nonMaxSuppressionPaddedAsync,\n  threshold,\n  transform\n};\nvar linalg = {\n  bandPart,\n  gramSchmidt,\n  qr\n};\nvar losses = {\n  absoluteDifference,\n  computeWeightedLoss,\n  cosineDistance,\n  hingeLoss,\n  huberLoss,\n  logLoss,\n  meanSquaredError,\n  sigmoidCrossEntropy,\n  softmaxCrossEntropy\n};\nvar sparse = {\n  sparseFillEmptyRows,\n  sparseReshape,\n  sparseSegmentMean,\n  sparseSegmentSum\n};\nvar string = {\n  stringNGrams,\n  stringSplit,\n  stringToHashBucketFast\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/optimizer.js\nvar Optimizer = class extends Serializable {\n  minimize(f, returnCost = false, varList) {\n    const { value, grads: grads2 } = this.computeGradients(f, varList);\n    if (varList != null) {\n      const gradArray = varList.map((v) => ({ name: v.name, tensor: grads2[v.name] }));\n      this.applyGradients(gradArray);\n    } else {\n      this.applyGradients(grads2);\n    }\n    dispose(grads2);\n    if (returnCost) {\n      return value;\n    } else {\n      value.dispose();\n      return null;\n    }\n  }\n  get iterations() {\n    if (this.iterations_ == null) {\n      this.iterations_ = 0;\n    }\n    return this.iterations_;\n  }\n  incrementIterations() {\n    this.iterations_ = this.iterations + 1;\n  }\n  computeGradients(f, varList) {\n    return variableGrads(f, varList);\n  }\n  dispose() {\n    if (this.iterations_ != null) {\n      dispose(this.iterations_);\n    }\n  }\n  async saveIterations() {\n    if (this.iterations_ == null) {\n      this.iterations_ = 0;\n    }\n    return {\n      name: \"iter\",\n      tensor: scalar(this.iterations_, \"int32\")\n    };\n  }\n  async getWeights() {\n    throw new Error(\"getWeights() is not implemented for this optimizer yet.\");\n  }\n  async setWeights(weightValues) {\n    throw new Error(`setWeights() is not implemented for this optimizer class ${this.getClassName()}`);\n  }\n  async extractIterations(weightValues) {\n    this.iterations_ = (await weightValues[0].tensor.data())[0];\n    return weightValues.slice(1);\n  }\n};\nObject.defineProperty(Optimizer, Symbol.hasInstance, {\n  value: (instance) => {\n    return instance.minimize != null && instance.computeGradients != null && instance.applyGradients != null;\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/adadelta_optimizer.js\nvar AdadeltaOptimizer = class extends Optimizer {\n  constructor(learningRate, rho, epsilon3 = null) {\n    super();\n    this.learningRate = learningRate;\n    this.rho = rho;\n    this.epsilon = epsilon3;\n    this.accumulatedGrads = [];\n    this.accumulatedUpdates = [];\n    if (epsilon3 == null) {\n      this.epsilon = ENGINE.backend.epsilon();\n    }\n  }\n  applyGradients(variableGradients) {\n    const variableNames = Array.isArray(variableGradients) ? variableGradients.map((item) => item.name) : Object.keys(variableGradients);\n    variableNames.forEach((name, i2) => {\n      const value = ENGINE.registeredVariables[name];\n      const trainable = false;\n      if (this.accumulatedGrads[i2] == null) {\n        this.accumulatedGrads[i2] = {\n          originalName: `${name}/accum_grad`,\n          variable: tidy(() => zerosLike(value).variable(trainable))\n        };\n      }\n      if (this.accumulatedUpdates[i2] == null) {\n        this.accumulatedUpdates[i2] = {\n          originalName: `${name}/accum_var`,\n          variable: tidy(() => zerosLike(value).variable(trainable))\n        };\n      }\n      const gradient = Array.isArray(variableGradients) ? variableGradients[i2].tensor : variableGradients[name];\n      if (gradient == null) {\n        return;\n      }\n      const accumulatedGrad = this.accumulatedGrads[i2].variable;\n      const accumulatedUpdate = this.accumulatedUpdates[i2].variable;\n      tidy(() => {\n        const newAccumulatedGrad = add2(mul(accumulatedGrad, this.rho), mul(square(gradient), 1 - this.rho));\n        const updates = mul(div(sqrt(add2(accumulatedUpdate, this.epsilon)), sqrt(add2(accumulatedGrad, this.epsilon))), gradient);\n        const newAccumulatedUpdate = add2(mul(accumulatedUpdate, this.rho), mul(square(updates), 1 - this.rho));\n        accumulatedGrad.assign(newAccumulatedGrad);\n        accumulatedUpdate.assign(newAccumulatedUpdate);\n        const newValue = add2(mul(updates, -this.learningRate), value);\n        value.assign(newValue);\n      });\n    });\n    this.incrementIterations();\n  }\n  dispose() {\n    if (this.accumulatedUpdates != null) {\n      dispose(this.accumulatedGrads.map((v) => v.variable));\n      dispose(this.accumulatedUpdates.map((v) => v.variable));\n    }\n  }\n  async getWeights() {\n    const variables = [...this.accumulatedGrads, ...this.accumulatedUpdates];\n    return [await this.saveIterations()].concat(variables.map((v) => ({ name: v.originalName, tensor: v.variable })));\n  }\n  async setWeights(weightValues) {\n    weightValues = await this.extractIterations(weightValues);\n    const variableCount = weightValues.length / 2;\n    const trainable = false;\n    this.accumulatedGrads = weightValues.slice(0, variableCount).map((v) => ({\n      originalName: v.name,\n      variable: v.tensor.variable(trainable)\n    }));\n    this.accumulatedUpdates = weightValues.slice(variableCount, variableCount * 2).map((v) => ({\n      originalName: v.name,\n      variable: v.tensor.variable(trainable)\n    }));\n  }\n  getConfig() {\n    return {\n      \"learningRate\": this.learningRate,\n      \"rho\": this.rho,\n      \"epsilon\": this.epsilon\n    };\n  }\n  static fromConfig(cls, config) {\n    return new cls(config[\"learningRate\"], config[\"rho\"], config[\"epsilon\"]);\n  }\n};\nAdadeltaOptimizer.className = \"Adadelta\";\nregisterClass(AdadeltaOptimizer);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/adagrad_optimizer.js\nvar AdagradOptimizer = class extends Optimizer {\n  constructor(learningRate, initialAccumulatorValue = 0.1) {\n    super();\n    this.learningRate = learningRate;\n    this.initialAccumulatorValue = initialAccumulatorValue;\n    this.accumulatedGrads = [];\n  }\n  applyGradients(variableGradients) {\n    const variableNames = Array.isArray(variableGradients) ? variableGradients.map((item) => item.name) : Object.keys(variableGradients);\n    variableNames.forEach((name, i2) => {\n      const value = ENGINE.registeredVariables[name];\n      if (this.accumulatedGrads[i2] == null) {\n        const trainable = false;\n        this.accumulatedGrads[i2] = {\n          originalName: `${name}/accumulator`,\n          variable: tidy(() => fill(value.shape, this.initialAccumulatorValue).variable(trainable))\n        };\n      }\n      const gradient = Array.isArray(variableGradients) ? variableGradients[i2].tensor : variableGradients[name];\n      if (gradient == null) {\n        return;\n      }\n      const accumulatedGrad = this.accumulatedGrads[i2].variable;\n      tidy(() => {\n        const newAccumulatedGrad = add2(accumulatedGrad, square(gradient));\n        accumulatedGrad.assign(newAccumulatedGrad);\n        const newValue = add2(mul(div(gradient, sqrt(add2(newAccumulatedGrad, ENGINE.backend.epsilon()))), -this.learningRate), value);\n        value.assign(newValue);\n      });\n    });\n    this.incrementIterations();\n  }\n  dispose() {\n    if (this.accumulatedGrads != null) {\n      dispose(this.accumulatedGrads.map((v) => v.variable));\n    }\n  }\n  async getWeights() {\n    return [await this.saveIterations()].concat(this.accumulatedGrads.map((v) => ({ name: v.originalName, tensor: v.variable })));\n  }\n  async setWeights(weightValues) {\n    weightValues = await this.extractIterations(weightValues);\n    const trainable = false;\n    this.accumulatedGrads = weightValues.map((v) => ({ originalName: v.name, variable: v.tensor.variable(trainable) }));\n  }\n  getConfig() {\n    return {\n      \"learningRate\": this.learningRate,\n      \"initialAccumulatorValue\": this.initialAccumulatorValue\n    };\n  }\n  static fromConfig(cls, config) {\n    return new cls(config[\"learningRate\"], config[\"initialAccumulatorValue\"]);\n  }\n};\nAdagradOptimizer.className = \"Adagrad\";\nregisterClass(AdagradOptimizer);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/adam_optimizer.js\nvar AdamOptimizer = class extends Optimizer {\n  constructor(learningRate, beta1, beta2, epsilon3 = null) {\n    super();\n    this.learningRate = learningRate;\n    this.beta1 = beta1;\n    this.beta2 = beta2;\n    this.epsilon = epsilon3;\n    this.accumulatedFirstMoment = [];\n    this.accumulatedSecondMoment = [];\n    tidy(() => {\n      this.accBeta1 = scalar(beta1).variable();\n      this.accBeta2 = scalar(beta2).variable();\n    });\n    if (epsilon3 == null) {\n      this.epsilon = ENGINE.backend.epsilon();\n    }\n  }\n  applyGradients(variableGradients) {\n    const varNames = Array.isArray(variableGradients) ? variableGradients.map((v) => v.name) : Object.keys(variableGradients);\n    tidy(() => {\n      const oneMinusAccBeta1 = sub(1, this.accBeta1);\n      const oneMinusAccBeta2 = sub(1, this.accBeta2);\n      varNames.forEach((name, i2) => {\n        const value = ENGINE.registeredVariables[name];\n        const trainable = false;\n        if (this.accumulatedFirstMoment[i2] == null) {\n          this.accumulatedFirstMoment[i2] = {\n            originalName: `${name}/m`,\n            variable: tidy(() => zerosLike(value).variable(trainable))\n          };\n        }\n        if (this.accumulatedSecondMoment[i2] == null) {\n          this.accumulatedSecondMoment[i2] = {\n            originalName: `${name}/v`,\n            variable: tidy(() => zerosLike(value).variable(trainable))\n          };\n        }\n        const gradient = Array.isArray(variableGradients) ? variableGradients[i2].tensor : variableGradients[name];\n        if (gradient == null) {\n          return;\n        }\n        const firstMoment = this.accumulatedFirstMoment[i2].variable;\n        const secondMoment = this.accumulatedSecondMoment[i2].variable;\n        const newFirstMoment = add2(mul(firstMoment, this.beta1), mul(gradient, 1 - this.beta1));\n        const newSecondMoment = add2(mul(secondMoment, this.beta2), mul(square(gradient), 1 - this.beta2));\n        const biasCorrectedFirstMoment = div(newFirstMoment, oneMinusAccBeta1);\n        const biasCorrectedSecondMoment = div(newSecondMoment, oneMinusAccBeta2);\n        firstMoment.assign(newFirstMoment);\n        secondMoment.assign(newSecondMoment);\n        const newValue = add2(mul(div(biasCorrectedFirstMoment, add2(sqrt(biasCorrectedSecondMoment), this.epsilon)), -this.learningRate), value);\n        value.assign(newValue);\n      });\n      this.accBeta1.assign(mul(this.accBeta1, this.beta1));\n      this.accBeta2.assign(mul(this.accBeta2, this.beta2));\n    });\n    this.incrementIterations();\n  }\n  dispose() {\n    this.accBeta1.dispose();\n    this.accBeta2.dispose();\n    if (this.accumulatedFirstMoment != null) {\n      dispose(this.accumulatedFirstMoment.map((v) => v.variable));\n    }\n    if (this.accumulatedSecondMoment != null) {\n      dispose(this.accumulatedSecondMoment.map((v) => v.variable));\n    }\n  }\n  async getWeights() {\n    const variables = [...this.accumulatedFirstMoment, ...this.accumulatedSecondMoment];\n    return [await this.saveIterations()].concat(variables.map((v) => ({ name: v.originalName, tensor: v.variable })));\n  }\n  async setWeights(weightValues) {\n    weightValues = await this.extractIterations(weightValues);\n    tidy(() => {\n      this.accBeta1.assign(pow(this.beta1, this.iterations_ + 1));\n      this.accBeta2.assign(pow(this.beta2, this.iterations_ + 1));\n    });\n    const variableCount = weightValues.length / 2;\n    const trainable = false;\n    this.accumulatedFirstMoment = weightValues.slice(0, variableCount).map((v) => ({\n      originalName: v.name,\n      variable: v.tensor.variable(trainable)\n    }));\n    this.accumulatedSecondMoment = weightValues.slice(variableCount, variableCount * 2).map((v) => ({\n      originalName: v.name,\n      variable: v.tensor.variable(trainable)\n    }));\n  }\n  getConfig() {\n    return {\n      \"learningRate\": this.learningRate,\n      \"beta1\": this.beta1,\n      \"beta2\": this.beta2,\n      \"epsilon\": this.epsilon\n    };\n  }\n  static fromConfig(cls, config) {\n    return new cls(config[\"learningRate\"], config[\"beta1\"], config[\"beta2\"], config[\"epsilon\"]);\n  }\n};\nAdamOptimizer.className = \"Adam\";\nregisterClass(AdamOptimizer);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/adamax_optimizer.js\nvar AdamaxOptimizer = class extends Optimizer {\n  constructor(learningRate, beta1, beta2, epsilon3 = null, decay = 0) {\n    super();\n    this.learningRate = learningRate;\n    this.beta1 = beta1;\n    this.beta2 = beta2;\n    this.epsilon = epsilon3;\n    this.decay = decay;\n    this.accumulatedFirstMoment = [];\n    this.accumulatedWeightedInfNorm = [];\n    tidy(() => {\n      this.iteration = scalar(0).variable();\n      this.accBeta1 = scalar(beta1).variable();\n    });\n    if (epsilon3 == null) {\n      this.epsilon = ENGINE.backend.epsilon();\n    }\n  }\n  applyGradients(variableGradients) {\n    const variableNames = Array.isArray(variableGradients) ? variableGradients.map((item) => item.name) : Object.keys(variableGradients);\n    tidy(() => {\n      const oneMinusAccBeta1 = sub(1, this.accBeta1);\n      const lr = div(-this.learningRate, add2(mul(this.iteration, this.decay), 1));\n      variableNames.forEach((name, i2) => {\n        const value = ENGINE.registeredVariables[name];\n        const trainable = false;\n        if (this.accumulatedFirstMoment[i2] == null) {\n          this.accumulatedFirstMoment[i2] = {\n            originalName: `${name}/m`,\n            variable: zerosLike(value).variable(trainable)\n          };\n        }\n        if (this.accumulatedWeightedInfNorm[i2] == null) {\n          this.accumulatedWeightedInfNorm[i2] = {\n            originalName: `${name}/v`,\n            variable: zerosLike(value).variable(trainable)\n          };\n        }\n        const gradient = Array.isArray(variableGradients) ? variableGradients[i2].tensor : variableGradients[name];\n        if (gradient == null) {\n          return;\n        }\n        const firstMoment = this.accumulatedFirstMoment[i2].variable;\n        const weightedInfNorm = this.accumulatedWeightedInfNorm[i2].variable;\n        const newFirstMoment = add2(mul(firstMoment, this.beta1), mul(gradient, 1 - this.beta1));\n        const ut0 = mul(weightedInfNorm, this.beta2);\n        const ut1 = abs(gradient);\n        const newWeightedInfNorm = maximum(ut0, ut1);\n        firstMoment.assign(newFirstMoment);\n        weightedInfNorm.assign(newWeightedInfNorm);\n        const newValue = add2(mul(div(lr, oneMinusAccBeta1), div(newFirstMoment, add2(newWeightedInfNorm, this.epsilon))), value);\n        value.assign(newValue);\n      });\n      this.iteration.assign(add2(this.iteration, 1));\n      this.accBeta1.assign(mul(this.accBeta1, this.beta1));\n    });\n    this.incrementIterations();\n  }\n  dispose() {\n    this.accBeta1.dispose();\n    this.iteration.dispose();\n    if (this.accumulatedFirstMoment != null) {\n      dispose(this.accumulatedFirstMoment.map((v) => v.variable));\n    }\n    if (this.accumulatedWeightedInfNorm != null) {\n      dispose(this.accumulatedWeightedInfNorm.map((v) => v.variable));\n    }\n  }\n  async getWeights() {\n    throw new Error(\"getWeights() is not implemented for Adamax yet.\");\n  }\n  async setWeights(weightValues) {\n    throw new Error(\"setWeights() is not implemented for Adamax yet.\");\n  }\n  getConfig() {\n    return {\n      \"learningRate\": this.learningRate,\n      \"beta1\": this.beta1,\n      \"beta2\": this.beta2,\n      \"epsilon\": this.epsilon,\n      \"decay\": this.decay\n    };\n  }\n  static fromConfig(cls, config) {\n    return new cls(config[\"learningRate\"], config[\"beta1\"], config[\"beta2\"], config[\"epsilon\"], config[\"decay\"]);\n  }\n};\nAdamaxOptimizer.className = \"Adamax\";\nregisterClass(AdamaxOptimizer);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/sgd_optimizer.js\nvar SGDOptimizer = class extends Optimizer {\n  constructor(learningRate) {\n    super();\n    this.learningRate = learningRate;\n    this.setLearningRate(learningRate);\n  }\n  applyGradients(variableGradients) {\n    const varNames = Array.isArray(variableGradients) ? variableGradients.map((v) => v.name) : Object.keys(variableGradients);\n    varNames.forEach((name, i2) => {\n      const gradient = Array.isArray(variableGradients) ? variableGradients[i2].tensor : variableGradients[name];\n      if (gradient == null) {\n        return;\n      }\n      const value = ENGINE.registeredVariables[name];\n      tidy(() => {\n        const newValue = add2(mul(this.c, gradient), value);\n        value.assign(newValue);\n      });\n    });\n    this.incrementIterations();\n  }\n  setLearningRate(learningRate) {\n    this.learningRate = learningRate;\n    if (this.c != null) {\n      this.c.dispose();\n    }\n    this.c = keep(scalar(-learningRate));\n  }\n  dispose() {\n    this.c.dispose();\n  }\n  async getWeights() {\n    return [await this.saveIterations()];\n  }\n  async setWeights(weightValues) {\n    weightValues = await this.extractIterations(weightValues);\n    if (weightValues.length !== 0) {\n      throw new Error(\"SGD optimizer does not have settable weights.\");\n    }\n  }\n  getConfig() {\n    return { \"learningRate\": this.learningRate };\n  }\n  static fromConfig(cls, config) {\n    return new cls(config[\"learningRate\"]);\n  }\n};\nSGDOptimizer.className = \"SGD\";\nregisterClass(SGDOptimizer);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/momentum_optimizer.js\nvar MomentumOptimizer = class extends SGDOptimizer {\n  constructor(learningRate, momentum, useNesterov = false) {\n    super(learningRate);\n    this.learningRate = learningRate;\n    this.momentum = momentum;\n    this.useNesterov = useNesterov;\n    this.accumulations = [];\n    this.m = scalar(this.momentum);\n  }\n  applyGradients(variableGradients) {\n    const variableNames = Array.isArray(variableGradients) ? variableGradients.map((item) => item.name) : Object.keys(variableGradients);\n    variableNames.forEach((name, i2) => {\n      const value = ENGINE.registeredVariables[name];\n      if (this.accumulations[i2] == null) {\n        const trainable = false;\n        this.accumulations[i2] = {\n          originalName: `${name}/momentum`,\n          variable: tidy(() => zerosLike(value).variable(trainable))\n        };\n      }\n      const accumulation = this.accumulations[i2].variable;\n      const gradient = Array.isArray(variableGradients) ? variableGradients[i2].tensor : variableGradients[name];\n      if (gradient == null) {\n        return;\n      }\n      tidy(() => {\n        let newValue;\n        const newAccumulation = add2(mul(this.m, accumulation), gradient);\n        if (this.useNesterov) {\n          newValue = add2(mul(this.c, add2(gradient, mul(newAccumulation, this.m))), value);\n        } else {\n          newValue = add2(mul(this.c, newAccumulation), value);\n        }\n        accumulation.assign(newAccumulation);\n        value.assign(newValue);\n      });\n    });\n    this.incrementIterations();\n  }\n  dispose() {\n    this.m.dispose();\n    if (this.accumulations != null) {\n      dispose(this.accumulations.map((v) => v.variable));\n    }\n  }\n  setMomentum(momentum) {\n    this.momentum = momentum;\n  }\n  async getWeights() {\n    return [await this.saveIterations()].concat(this.accumulations.map((v) => ({ name: v.originalName, tensor: v.variable })));\n  }\n  async setWeights(weightValues) {\n    weightValues = await this.extractIterations(weightValues);\n    const trainable = false;\n    this.accumulations = weightValues.map((v) => ({ originalName: v.name, variable: v.tensor.variable(trainable) }));\n  }\n  getConfig() {\n    return {\n      \"learningRate\": this.learningRate,\n      \"momentum\": this.momentum,\n      \"useNesterov\": this.useNesterov\n    };\n  }\n  static fromConfig(cls, config) {\n    return new cls(config[\"learningRate\"], config[\"momentum\"], config[\"useNesterov\"]);\n  }\n};\nMomentumOptimizer.className = \"Momentum\";\nregisterClass(MomentumOptimizer);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/rmsprop_optimizer.js\nvar RMSPropOptimizer = class extends Optimizer {\n  constructor(learningRate, decay = 0.9, momentum = 0, epsilon3 = null, centered = false) {\n    super();\n    this.learningRate = learningRate;\n    this.decay = decay;\n    this.momentum = momentum;\n    this.epsilon = epsilon3;\n    this.accumulatedMeanSquares = [];\n    this.accumulatedMoments = [];\n    this.accumulatedMeanGrads = [];\n    this.centered = centered;\n    if (epsilon3 == null) {\n      this.epsilon = ENGINE.backend.epsilon();\n    }\n    if (learningRate == null) {\n      throw new Error(`learningRate for RMSPropOptimizer must be defined.`);\n    }\n  }\n  applyGradients(variableGradients) {\n    const variableNames = Array.isArray(variableGradients) ? variableGradients.map((item) => item.name) : Object.keys(variableGradients);\n    variableNames.forEach((name, i2) => {\n      const value = ENGINE.registeredVariables[name];\n      const trainable = false;\n      if (this.accumulatedMeanSquares[i2] == null) {\n        this.accumulatedMeanSquares[i2] = {\n          originalName: `${name}/rms`,\n          variable: tidy(() => zerosLike(value).variable(trainable))\n        };\n      }\n      if (this.accumulatedMoments[i2] == null) {\n        this.accumulatedMoments[i2] = {\n          originalName: `${name}/momentum`,\n          variable: tidy(() => zerosLike(value).variable(trainable))\n        };\n      }\n      if (this.accumulatedMeanGrads[i2] == null && this.centered) {\n        this.accumulatedMeanGrads[i2] = {\n          originalName: `${name}/mg`,\n          variable: tidy(() => zerosLike(value).variable(trainable))\n        };\n      }\n      const gradient = Array.isArray(variableGradients) ? variableGradients[i2].tensor : variableGradients[name];\n      if (gradient == null) {\n        return;\n      }\n      const accumulatedMeanSquare = this.accumulatedMeanSquares[i2].variable;\n      const accumulatedMoments = this.accumulatedMoments[i2].variable;\n      tidy(() => {\n        const newAccumulatedMeanSquare = add2(mul(accumulatedMeanSquare, this.decay), mul(square(gradient), 1 - this.decay));\n        if (this.centered) {\n          const accumulatedMeanGrad = this.accumulatedMeanGrads[i2].variable;\n          const newAccumulatedMeanGrad = add2(mul(accumulatedMeanGrad, this.decay), mul(gradient, 1 - this.decay));\n          const gradContribution = div(mul(gradient, this.learningRate), sqrt(sub(newAccumulatedMeanSquare, add2(square(newAccumulatedMeanGrad), this.epsilon))));\n          const newAccumulatedMoments = add2(mul(accumulatedMoments, this.momentum), gradContribution);\n          accumulatedMeanSquare.assign(newAccumulatedMeanSquare);\n          accumulatedMeanGrad.assign(newAccumulatedMeanGrad);\n          accumulatedMoments.assign(newAccumulatedMoments);\n          const newValue = sub(value, newAccumulatedMoments);\n          value.assign(newValue);\n        } else {\n          const newAccumulatedMeanSquare2 = add2(mul(accumulatedMeanSquare, this.decay), mul(square(gradient), 1 - this.decay));\n          const newAccumulatedMoments = add2(mul(accumulatedMoments, this.momentum), div(mul(gradient, this.learningRate), sqrt(add2(newAccumulatedMeanSquare2, this.epsilon))));\n          accumulatedMeanSquare.assign(newAccumulatedMeanSquare2);\n          accumulatedMoments.assign(newAccumulatedMoments);\n          const newValue = sub(value, newAccumulatedMoments);\n          value.assign(newValue);\n        }\n      });\n    });\n    this.incrementIterations();\n  }\n  dispose() {\n    if (this.accumulatedMeanSquares != null) {\n      dispose(this.accumulatedMeanSquares.map((v) => v.variable));\n    }\n    if (this.accumulatedMeanGrads != null && this.centered) {\n      dispose(this.accumulatedMeanGrads.map((v) => v.variable));\n    }\n    if (this.accumulatedMoments != null) {\n      dispose(this.accumulatedMoments.map((v) => v.variable));\n    }\n  }\n  async getWeights() {\n    const variables = [...this.accumulatedMeanSquares, ...this.accumulatedMoments];\n    if (this.centered) {\n      variables.push(...this.accumulatedMeanGrads);\n    }\n    return [await this.saveIterations()].concat(variables.map((v) => ({ name: v.originalName, tensor: v.variable })));\n  }\n  async setWeights(weightValues) {\n    weightValues = await this.extractIterations(weightValues);\n    const variableCount = this.centered ? weightValues.length / 3 : weightValues.length / 2;\n    const trainable = false;\n    this.accumulatedMeanSquares = weightValues.slice(0, variableCount).map((v) => ({\n      originalName: v.name,\n      variable: v.tensor.variable(trainable)\n    }));\n    this.accumulatedMoments = weightValues.slice(variableCount, variableCount * 2).map((v) => ({\n      originalName: v.name,\n      variable: v.tensor.variable(trainable)\n    }));\n    if (this.centered) {\n      this.accumulatedMeanGrads = weightValues.slice(variableCount * 2, variableCount * 3).map((v) => ({\n        originalName: v.name,\n        variable: v.tensor.variable(trainable)\n      }));\n    }\n  }\n  getConfig() {\n    return {\n      \"learningRate\": this.learningRate,\n      \"decay\": this.decay,\n      \"momentum\": this.momentum,\n      \"epsilon\": this.epsilon,\n      \"centered\": this.centered\n    };\n  }\n  static fromConfig(cls, config) {\n    return new cls(config[\"learningRate\"], config[\"decay\"], config[\"momentum\"], config[\"epsilon\"], config[\"centered\"]);\n  }\n};\nRMSPropOptimizer.className = \"RMSProp\";\nregisterClass(RMSPropOptimizer);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/optimizer_constructors.js\nvar OptimizerConstructors = class {\n  static sgd(learningRate) {\n    return new SGDOptimizer(learningRate);\n  }\n  static momentum(learningRate, momentum, useNesterov = false) {\n    return new MomentumOptimizer(learningRate, momentum, useNesterov);\n  }\n  static rmsprop(learningRate, decay = 0.9, momentum = 0, epsilon3 = null, centered = false) {\n    return new RMSPropOptimizer(learningRate, decay, momentum, epsilon3, centered);\n  }\n  static adam(learningRate = 1e-3, beta1 = 0.9, beta2 = 0.999, epsilon3 = null) {\n    return new AdamOptimizer(learningRate, beta1, beta2, epsilon3);\n  }\n  static adadelta(learningRate = 1e-3, rho = 0.95, epsilon3 = null) {\n    return new AdadeltaOptimizer(learningRate, rho, epsilon3);\n  }\n  static adamax(learningRate = 2e-3, beta1 = 0.9, beta2 = 0.999, epsilon3 = null, decay = 0) {\n    return new AdamaxOptimizer(learningRate, beta1, beta2, epsilon3, decay);\n  }\n  static adagrad(learningRate, initialAccumulatorValue = 0.1) {\n    return new AdagradOptimizer(learningRate, initialAccumulatorValue);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/train.js\nvar train = {\n  sgd: OptimizerConstructors.sgd,\n  momentum: OptimizerConstructors.momentum,\n  adadelta: OptimizerConstructors.adadelta,\n  adagrad: OptimizerConstructors.adagrad,\n  rmsprop: OptimizerConstructors.rmsprop,\n  adamax: OptimizerConstructors.adamax,\n  adam: OptimizerConstructors.adam\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/browser_util.js\nvar delayCallback = (() => {\n  if (typeof requestAnimationFrame !== \"undefined\") {\n    return requestAnimationFrame;\n  } else if (typeof setImmediate !== \"undefined\") {\n    return setImmediate;\n  }\n  return (f) => f();\n})();\nfunction nextFrame() {\n  return new Promise((resolve) => delayCallback(() => resolve()));\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/backend_util.js\nvar backend_util_exports = {};\n__export(backend_util_exports, {\n  ERF_A1: () => ERF_A1,\n  ERF_A2: () => ERF_A2,\n  ERF_A3: () => ERF_A3,\n  ERF_A4: () => ERF_A4,\n  ERF_A5: () => ERF_A5,\n  ERF_P: () => ERF_P,\n  PARALLELIZE_THRESHOLD: () => PARALLELIZE_THRESHOLD,\n  SELU_SCALE: () => SELU_SCALE,\n  SELU_SCALEALPHA: () => SELU_SCALEALPHA,\n  applyActivation: () => applyActivation,\n  assertAndGetBroadcastShape: () => assertAndGetBroadcastShape,\n  assertAxesAreInnerMostDims: () => assertAxesAreInnerMostDims,\n  assertParamsConsistent: () => assertParamsConsistent,\n  assignToTypedArray: () => assignToTypedArray,\n  axesAreInnerMostDims: () => axesAreInnerMostDims,\n  calculateShapes: () => calculateShapes,\n  checkEinsumDimSizes: () => checkEinsumDimSizes,\n  checkPadOnDimRoundingMode: () => checkPadOnDimRoundingMode,\n  combineLocations: () => combineLocations,\n  complexWithEvenIndex: () => complexWithEvenIndex,\n  complexWithOddIndex: () => complexWithOddIndex,\n  computeConv2DInfo: () => computeConv2DInfo,\n  computeConv3DInfo: () => computeConv3DInfo,\n  computeDefaultPad: () => computeDefaultPad,\n  computeDilation2DInfo: () => computeDilation2DInfo,\n  computeOptimalWindowSize: () => computeOptimalWindowSize,\n  computeOutAndReduceShapes: () => computeOutAndReduceShapes,\n  computeOutShape: () => computeOutShape2,\n  computePool2DInfo: () => computePool2DInfo,\n  computePool3DInfo: () => computePool3DInfo,\n  convertConv2DDataFormat: () => convertConv2DDataFormat,\n  decodeEinsumEquation: () => decodeEinsumEquation,\n  eitherStridesOrDilationsAreOne: () => eitherStridesOrDilationsAreOne,\n  expandShapeToKeepDim: () => expandShapeToKeepDim,\n  exponent: () => exponent,\n  exponents: () => exponents,\n  fromStringArrayToUint8: () => fromStringArrayToUint8,\n  fromUint8ToStringArray: () => fromUint8ToStringArray,\n  getAxesPermutation: () => getAxesPermutation,\n  getBroadcastDims: () => getBroadcastDims,\n  getComplexWithIndex: () => getComplexWithIndex,\n  getEinsumComputePath: () => getEinsumComputePath,\n  getEinsumPermutation: () => getEinsumPermutation,\n  getFusedBiasGradient: () => getFusedBiasGradient,\n  getFusedDyActivation: () => getFusedDyActivation,\n  getImageCenter: () => getImageCenter,\n  getInnerMostAxes: () => getInnerMostAxes,\n  getPermuted: () => getPermuted,\n  getReductionAxes: () => getReductionAxes,\n  getReshaped: () => getReshaped,\n  getReshapedPermuted: () => getReshapedPermuted,\n  getSliceBeginCoords: () => getSliceBeginCoords,\n  getSliceSize: () => getSliceSize,\n  getSparseFillEmptyRowsIndicesDenseShapeMismatch: () => getSparseFillEmptyRowsIndicesDenseShapeMismatch,\n  getSparseFillEmptyRowsNegativeIndexErrorMessage: () => getSparseFillEmptyRowsNegativeIndexErrorMessage,\n  getSparseFillEmptyRowsOutOfRangeIndexErrorMessage: () => getSparseFillEmptyRowsOutOfRangeIndexErrorMessage,\n  getSparseReshapeEmptyTensorZeroOutputDimErrorMessage: () => getSparseReshapeEmptyTensorZeroOutputDimErrorMessage,\n  getSparseReshapeInputOutputMismatchErrorMessage: () => getSparseReshapeInputOutputMismatchErrorMessage,\n  getSparseReshapeInputOutputMultipleErrorMessage: () => getSparseReshapeInputOutputMultipleErrorMessage,\n  getSparseReshapeMultipleNegativeOneOutputDimErrorMessage: () => getSparseReshapeMultipleNegativeOneOutputDimErrorMessage,\n  getSparseReshapeNegativeOutputDimErrorMessage: () => getSparseReshapeNegativeOutputDimErrorMessage,\n  getSparseSegmentReductionIndicesOutOfRangeErrorMessage: () => getSparseSegmentReductionIndicesOutOfRangeErrorMessage,\n  getSparseSegmentReductionNegativeSegmentIdsErrorMessage: () => getSparseSegmentReductionNegativeSegmentIdsErrorMessage,\n  getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage: () => getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage,\n  getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage: () => getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage,\n  getUndoAxesPermutation: () => getUndoAxesPermutation,\n  isIdentityPermutation: () => isIdentityPermutation,\n  log: () => log,\n  mergeRealAndImagArrays: () => mergeRealAndImagArrays,\n  prepareAndValidate: () => prepareAndValidate,\n  prepareSplitSize: () => prepareSplitSize,\n  segment_util: () => segment_util_exports,\n  shouldFuse: () => shouldFuse,\n  slice_util: () => slice_util_exports,\n  splitRealAndImagArrays: () => splitRealAndImagArrays,\n  tupleValuesAreOne: () => tupleValuesAreOne,\n  upcastType: () => upcastType,\n  validateInput: () => validateInput,\n  validateUpdateShape: () => validateUpdateShape,\n  warn: () => warn\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/concat_util.js\nfunction assertParamsConsistent(shapes, axis) {\n  const rank = shapes[0].length;\n  shapes.forEach((shape, i2) => {\n    assert(shape.length === rank, () => `Error in concat${rank}D: rank of tensors[${i2}] must be the same as the rank of the rest (${rank})`);\n  });\n  assert(axis >= 0 && axis < rank, () => `Error in concat${rank}D: axis must be between 0 and ${rank - 1}.`);\n  const firstShape = shapes[0];\n  shapes.forEach((shape, i2) => {\n    for (let r2 = 0; r2 < rank; r2++) {\n      assert(r2 === axis || shape[r2] === firstShape[r2], () => `Error in concat${rank}D: Shape of tensors[${i2}] (${shape}) does not match the shape of the rest (${firstShape}) along the non-concatenated axis ${i2}.`);\n    }\n  });\n}\nfunction computeOutShape2(shapes, axis) {\n  const outputShape = shapes[0].slice();\n  for (let i2 = 1; i2 < shapes.length; i2++) {\n    outputShape[axis] += shapes[i2][axis];\n  }\n  return outputShape;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reduce_util.js\nvar PARALLELIZE_THRESHOLD = 30;\nfunction computeOptimalWindowSize(inSize) {\n  if (inSize <= PARALLELIZE_THRESHOLD) {\n    return inSize;\n  }\n  return nearestDivisor(inSize, Math.floor(Math.sqrt(inSize)));\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/rotate_util.js\nfunction getImageCenter(center, imageHeight, imageWidth) {\n  const centerX = imageWidth * (typeof center === \"number\" ? center : center[0]);\n  const centerY = imageHeight * (typeof center === \"number\" ? center : center[1]);\n  return [centerX, centerY];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/array_ops_util.js\nfunction getReshaped(inputShape, blockShape, prod6, batchToSpace = true) {\n  let reshaped = [];\n  if (batchToSpace) {\n    reshaped = reshaped.concat(blockShape.slice(0));\n    reshaped.push(inputShape[0] / prod6);\n    reshaped = reshaped.concat(inputShape.slice(1));\n  } else {\n    reshaped = reshaped.concat(inputShape[0]);\n    const spatialLength = blockShape.length;\n    for (let i2 = 0; i2 < spatialLength; ++i2) {\n      reshaped = reshaped.concat([inputShape[i2 + 1] / blockShape[i2], blockShape[i2]]);\n    }\n    reshaped = reshaped.concat(inputShape.slice(spatialLength + 1));\n  }\n  return reshaped;\n}\nfunction getPermuted(reshapedRank, blockShapeRank, batchToSpace = true) {\n  const permuted = [];\n  if (batchToSpace) {\n    permuted.push(blockShapeRank);\n    for (let i2 = blockShapeRank + 1; i2 < reshapedRank; ++i2) {\n      if (i2 <= 2 * blockShapeRank) {\n        permuted.push(i2);\n        permuted.push(i2 - (blockShapeRank + 1));\n      } else {\n        permuted.push(i2);\n      }\n    }\n  } else {\n    const permutedBeforeBatch = [];\n    const permutedAfterBatch = [];\n    for (let i2 = 1; i2 < reshapedRank; ++i2) {\n      if (i2 >= blockShapeRank * 2 + 1 || i2 % 2 === 1) {\n        permutedAfterBatch.push(i2);\n      } else {\n        permutedBeforeBatch.push(i2);\n      }\n    }\n    permuted.push(...permutedBeforeBatch);\n    permuted.push(0);\n    permuted.push(...permutedAfterBatch);\n  }\n  return permuted;\n}\nfunction getReshapedPermuted(inputShape, blockShape, prod6, batchToSpace = true) {\n  const reshapedPermuted = [];\n  if (batchToSpace) {\n    reshapedPermuted.push(inputShape[0] / prod6);\n  } else {\n    reshapedPermuted.push(inputShape[0] * prod6);\n  }\n  for (let i2 = 1; i2 < inputShape.length; ++i2) {\n    if (i2 <= blockShape.length) {\n      if (batchToSpace) {\n        reshapedPermuted.push(blockShape[i2 - 1] * inputShape[i2]);\n      } else {\n        reshapedPermuted.push(inputShape[i2] / blockShape[i2 - 1]);\n      }\n    } else {\n      reshapedPermuted.push(inputShape[i2]);\n    }\n  }\n  return reshapedPermuted;\n}\nfunction getSliceBeginCoords(crops, blockShape) {\n  const sliceBeginCoords = [0];\n  for (let i2 = 0; i2 < blockShape; ++i2) {\n    sliceBeginCoords.push(crops[i2][0]);\n  }\n  return sliceBeginCoords;\n}\nfunction getSliceSize(uncroppedShape, crops, blockShape) {\n  const sliceSize = uncroppedShape.slice(0, 1);\n  for (let i2 = 0; i2 < blockShape; ++i2) {\n    sliceSize.push(uncroppedShape[i2 + 1] - crops[i2][0] - crops[i2][1]);\n  }\n  return sliceSize;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/selu_util.js\nvar SELU_SCALEALPHA = 1.7580993408473768;\nvar SELU_SCALE = 1.0507009873554805;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/erf_util.js\nvar ERF_P = 0.3275911;\nvar ERF_A1 = 0.254829592;\nvar ERF_A2 = -0.284496736;\nvar ERF_A3 = 1.421413741;\nvar ERF_A4 = -1.453152027;\nvar ERF_A5 = 1.061405429;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/complex_util.js\nfunction mergeRealAndImagArrays(real5, imag5) {\n  if (real5.length !== imag5.length) {\n    throw new Error(`Cannot merge real and imag arrays of different lengths. real:${real5.length}, imag: ${imag5.length}.`);\n  }\n  const result = new Float32Array(real5.length * 2);\n  for (let i2 = 0; i2 < result.length; i2 += 2) {\n    result[i2] = real5[i2 / 2];\n    result[i2 + 1] = imag5[i2 / 2];\n  }\n  return result;\n}\nfunction splitRealAndImagArrays(complex5) {\n  const real5 = new Float32Array(complex5.length / 2);\n  const imag5 = new Float32Array(complex5.length / 2);\n  for (let i2 = 0; i2 < complex5.length; i2 += 2) {\n    real5[i2 / 2] = complex5[i2];\n    imag5[i2 / 2] = complex5[i2 + 1];\n  }\n  return { real: real5, imag: imag5 };\n}\nfunction complexWithEvenIndex(complex5) {\n  const len = Math.ceil(complex5.length / 4);\n  const real5 = new Float32Array(len);\n  const imag5 = new Float32Array(len);\n  for (let i2 = 0; i2 < complex5.length; i2 += 4) {\n    real5[Math.floor(i2 / 4)] = complex5[i2];\n    imag5[Math.floor(i2 / 4)] = complex5[i2 + 1];\n  }\n  return { real: real5, imag: imag5 };\n}\nfunction complexWithOddIndex(complex5) {\n  const len = Math.floor(complex5.length / 4);\n  const real5 = new Float32Array(len);\n  const imag5 = new Float32Array(len);\n  for (let i2 = 2; i2 < complex5.length; i2 += 4) {\n    real5[Math.floor(i2 / 4)] = complex5[i2];\n    imag5[Math.floor(i2 / 4)] = complex5[i2 + 1];\n  }\n  return { real: real5, imag: imag5 };\n}\nfunction getComplexWithIndex(complex5, index) {\n  const real5 = complex5[index * 2];\n  const imag5 = complex5[index * 2 + 1];\n  return { real: real5, imag: imag5 };\n}\nfunction assignToTypedArray(data, real5, imag5, index) {\n  data[index * 2] = real5;\n  data[index * 2 + 1] = imag5;\n}\nfunction exponents(n2, inverse) {\n  const real5 = new Float32Array(n2 / 2);\n  const imag5 = new Float32Array(n2 / 2);\n  for (let i2 = 0; i2 < Math.ceil(n2 / 2); i2++) {\n    const x = (inverse ? 2 : -2) * Math.PI * (i2 / n2);\n    real5[i2] = Math.cos(x);\n    imag5[i2] = Math.sin(x);\n  }\n  return { real: real5, imag: imag5 };\n}\nfunction exponent(k, n2, inverse) {\n  const x = (inverse ? 2 : -2) * Math.PI * (k / n2);\n  const real5 = Math.cos(x);\n  const imag5 = Math.sin(x);\n  return { real: real5, imag: imag5 };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/einsum_util.js\nvar ARROW = \"->\";\nvar ARROW_REGEX = /->/g;\nvar COMMA = \",\";\nvar ELLIPSIS = \"...\";\nfunction decodeEinsumEquation(equation, numTensors) {\n  equation = equation.replace(/\\s/g, \"\");\n  const numArrows = (equation.length - equation.replace(ARROW_REGEX, \"\").length) / ARROW.length;\n  if (numArrows < 1) {\n    throw new Error(\"Equations without an arrow are not supported.\");\n  } else if (numArrows > 1) {\n    throw new Error(`Equation must contain exactly one arrow (\"${ARROW}\").`);\n  }\n  const [inputString, outputString] = equation.split(ARROW);\n  assert(inputString.indexOf(ELLIPSIS) === -1, () => `The ellipsis notation (\"${ELLIPSIS}\") is not supported yet.`);\n  const inputTerms = inputString.split(COMMA);\n  const numInputs = inputTerms.length;\n  if (numTensors !== numInputs) {\n    throw new Error(`Expected ${numInputs} input tensors, received ${numTensors}`);\n  }\n  if (numInputs > 2) {\n    throw new Error(\"Support for more than 2 input tensors is not implemented yet.\");\n  }\n  const allDims = [];\n  for (let i2 = 0; i2 < outputString.length; ++i2) {\n    const dimName = outputString[i2];\n    if (!inputTerms.some((inputTerm) => inputTerm.indexOf(dimName) !== -1)) {\n      throw new Error(`Output subscripts contain the label ${dimName} not present in the input subscripts.`);\n    }\n    if (allDims.indexOf(dimName) === -1) {\n      allDims.push(dimName);\n    }\n  }\n  for (let i2 = 0; i2 < inputString.length; ++i2) {\n    const dimName = inputString[i2];\n    if (allDims.indexOf(dimName) === -1 && dimName !== COMMA) {\n      allDims.push(dimName);\n    }\n  }\n  const idDims = new Array(inputTerms.length);\n  for (let i2 = 0; i2 < numInputs; ++i2) {\n    if (new Set(inputTerms[i2].split(\"\")).size !== inputTerms[i2].length) {\n      throw new Error(`Found duplicate axes in input component ${inputTerms[i2]}. Support for duplicate axes in input is not implemented yet.`);\n    }\n    idDims[i2] = [];\n    for (let j = 0; j < inputTerms[i2].length; ++j) {\n      idDims[i2].push(allDims.indexOf(inputTerms[i2][j]));\n    }\n  }\n  const numDims = allDims.length;\n  const numOutDims = outputString.length;\n  const summedDims = [];\n  for (let i2 = numOutDims; i2 < numDims; ++i2) {\n    summedDims.push(i2);\n  }\n  return { allDims, summedDims, idDims };\n}\nfunction getEinsumPermutation(nDims, idDims) {\n  let permutationIndices = new Array(nDims);\n  permutationIndices.fill(-1);\n  for (let i2 = 0; i2 < idDims.length; ++i2) {\n    permutationIndices[idDims[i2]] = i2;\n  }\n  const expandDims7 = [];\n  for (let i2 = 0; i2 < nDims; ++i2) {\n    if (permutationIndices[i2] === -1) {\n      expandDims7.push(i2);\n    }\n  }\n  permutationIndices = permutationIndices.filter((d) => d !== -1);\n  return { permutationIndices, expandDims: expandDims7 };\n}\nfunction checkEinsumDimSizes(nDims, idDims, tensors) {\n  const dimSizes = new Array(nDims);\n  for (let i2 = 0; i2 < tensors.length; ++i2) {\n    const shape = tensors[i2].shape;\n    for (let j = 0; j < idDims[i2].length; ++j) {\n      if (dimSizes[idDims[i2][j]] === void 0) {\n        dimSizes[idDims[i2][j]] = shape[j];\n      } else {\n        assert(dimSizes[idDims[i2][j]] === shape[j], () => `Expected dimension ${dimSizes[idDims[i2][j]]} at axis ${j} of input shaped ${JSON.stringify(shape)}, but got dimension ${shape[j]}`);\n      }\n    }\n  }\n}\nfunction getEinsumComputePath(summedDims, idDims) {\n  const path = summedDims;\n  const steps = [];\n  let nSteps = 0;\n  if (summedDims.length === 0) {\n    path.push(-1);\n  }\n  nSteps = summedDims.length + 1;\n  for (let i2 = 0; i2 < nSteps; ++i2) {\n    steps.push([]);\n  }\n  const computedTermIndices = [];\n  for (let i2 = 0; i2 < path.length; ++i2) {\n    const summedDim = path[i2];\n    const termIndices = findTermsWithDim(idDims, summedDim);\n    for (const termIndex of termIndices) {\n      if (computedTermIndices.indexOf(termIndex) === -1) {\n        steps[i2].push(termIndex);\n        computedTermIndices.push(termIndex);\n      }\n    }\n  }\n  return { path, steps };\n}\nfunction isIdentityPermutation(perm) {\n  return perm.every((dim, index) => dim === index);\n}\nfunction findTermsWithDim(idDims, dim) {\n  const termIndices = [];\n  for (let i2 = 0; i2 < idDims.length; ++i2) {\n    if (idDims[i2].length === 0 || idDims[i2].indexOf(dim) !== -1 || dim === -1) {\n      termIndices.push(i2);\n    }\n  }\n  return termIndices;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/split_util.js\nfunction prepareSplitSize(x, numOrSizeSplits, axis = 0) {\n  let splitSizes = [];\n  if (typeof numOrSizeSplits === \"number\") {\n    assert(x.shape[axis] % numOrSizeSplits === 0, () => \"Number of splits must evenly divide the axis.\");\n    splitSizes = new Array(numOrSizeSplits).fill(x.shape[axis] / numOrSizeSplits);\n  } else {\n    const numOfNegs = numOrSizeSplits.reduce((count2, value) => {\n      if (value === -1) {\n        count2 += 1;\n      }\n      return count2;\n    }, 0);\n    assert(numOfNegs <= 1, () => \"There should be only one negative value in split array.\");\n    const negIndex = numOrSizeSplits.indexOf(-1);\n    if (negIndex !== -1) {\n      const total = numOrSizeSplits.reduce((a, b) => b > 0 ? a + b : a);\n      numOrSizeSplits[negIndex] = x.shape[axis] - total;\n    }\n    assert(x.shape[axis] === numOrSizeSplits.reduce((a, b) => a + b), () => \"The sum of sizes must match the size of the axis dimension.\");\n    splitSizes = numOrSizeSplits;\n  }\n  return splitSizes;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse/sparse_fill_empty_rows_util.js\nfunction getSparseFillEmptyRowsIndicesDenseShapeMismatch(indicesLength) {\n  return `Received SparseTensor with denseShape[0] = 0 but\n  indices.shape[0] = ${indicesLength}`;\n}\nfunction getSparseFillEmptyRowsNegativeIndexErrorMessage(index, value) {\n  return `indices(${index}, 0) is invalid: ${value} < 0`;\n}\nfunction getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(index, value, limit) {\n  return `indices(${index}, 0) is invalid: ${value} >= ${limit}`;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse/sparse_reshape_util.js\nfunction getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(dim1, dim2) {\n  return `only one output dimension may be -1, not both ${dim1} and ${dim2}`;\n}\nfunction getSparseReshapeNegativeOutputDimErrorMessage(dim, value) {\n  return `size ${dim} must be non-negative, not ${value}`;\n}\nfunction getSparseReshapeEmptyTensorZeroOutputDimErrorMessage() {\n  return \"reshape cannot infer the missing input size for an empty tensor unless all specified input sizes are non-zero\";\n}\nfunction getSparseReshapeInputOutputMultipleErrorMessage(inputShape, outputShape) {\n  const inputSize = sizeFromShape(inputShape);\n  const outputSize = sizeFromShape(outputShape);\n  return `Input to reshape is a SparseTensor with ${inputSize}\n  dense values, but the requested shape requires a multiple of ${outputSize}. inputShape=${inputShape} outputShape= ${outputShape}`;\n}\nfunction getSparseReshapeInputOutputMismatchErrorMessage(inputShape, outputShape) {\n  const inputSize = sizeFromShape(inputShape);\n  const outputSize = sizeFromShape(outputShape);\n  return `Input to reshape is a tensor with ${inputSize} dense values, but the requested shape has ${outputSize}. inputShape=${inputShape} outputShape=${outputShape}`;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse/sparse_segment_reduction_util.js\nfunction getSparseSegmentReductionNegativeSegmentIdsErrorMessage() {\n  return `segment ids must be >= 0`;\n}\nfunction getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage() {\n  return `segment ids are not increasing`;\n}\nfunction getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(segmentId, outputRows) {\n  return `Segment id ${segmentId} out of range [0, ${outputRows}), possibly because segmentIds input is not sorted.`;\n}\nfunction getSparseSegmentReductionIndicesOutOfRangeErrorMessage(index, indexValue, inputRows) {\n  return `Bad: indices[${index}] == ${indexValue} out of range [0, ${inputRows})`;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/segment_util.js\nvar segment_util_exports = {};\n__export(segment_util_exports, {\n  collectGatherOpShapeInfo: () => collectGatherOpShapeInfo,\n  computeOutShape: () => computeOutShape3,\n  segOpComputeOptimalWindowSize: () => segOpComputeOptimalWindowSize\n});\nfunction segOpComputeOptimalWindowSize(inSize, numSegments) {\n  let done = false;\n  let res;\n  if (inSize <= PARALLELIZE_THRESHOLD) {\n    res = inSize;\n    done = true;\n  } else {\n    res = nearestDivisor(inSize, Math.floor(Math.sqrt(inSize)));\n  }\n  while (!done) {\n    if (res > numSegments || res === inSize) {\n      done = true;\n    } else {\n      res = nearestDivisor(inSize, res + 1);\n    }\n  }\n  return res;\n}\nfunction computeOutShape3(aShape, axis, numSegments) {\n  const outShape = [];\n  const rank = aShape.length;\n  for (let dim = 0; dim < rank; dim++) {\n    if (dim !== axis) {\n      outShape.push(aShape[dim]);\n    } else {\n      outShape.push(numSegments);\n    }\n  }\n  return outShape;\n}\nfunction collectGatherOpShapeInfo(x, indices, axis, batchDims) {\n  const indicesRank = indices.shape.length;\n  const xRank = x.shape.length;\n  if (batchDims !== 0) {\n    if (batchDims < -indicesRank || batchDims > indicesRank) {\n      throw new Error(`Expect batchDims in the range of [-${indicesRank}, ${indicesRank}], but got ${batchDims}`);\n    }\n  }\n  if (batchDims < 0) {\n    batchDims += indicesRank;\n  }\n  if (batchDims > xRank) {\n    throw new Error(`batchDims (${batchDims}) must be less than rank(x) (\n    ${xRank}).`);\n  }\n  if (axis < batchDims) {\n    throw new Error(`batchDims (${batchDims}) must be less than or equal to axis (${axis}).`);\n  }\n  for (let i2 = 0; i2 < batchDims; ++i2) {\n    if (x.shape[i2] !== indices.shape[i2]) {\n      throw new Error(`x.shape[${i2}]: ${x.shape[i2]} should be equal to indices.shape[${i2}]: ${indices.shape[i2]}.`);\n    }\n  }\n  const dimSize = x.shape[axis];\n  const outputShape = [];\n  let batchSize = 1;\n  let outerSize = 1;\n  let sliceSize = 1;\n  for (let i2 = 0; i2 < batchDims; ++i2) {\n    outputShape.push(x.shape[i2]);\n    batchSize *= x.shape[i2];\n  }\n  for (let i2 = batchDims; i2 < axis; i2++) {\n    outputShape.push(x.shape[i2]);\n    outerSize *= x.shape[i2];\n  }\n  for (let i2 = batchDims; i2 < indicesRank; i2++) {\n    outputShape.push(indices.shape[i2]);\n  }\n  for (let i2 = axis + 1; i2 < xRank; i2++) {\n    outputShape.push(x.shape[i2]);\n    sliceSize *= x.shape[i2];\n  }\n  return { batchSize, sliceSize, outerSize, dimSize, outputShape };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/backend_util.js\nfunction fromUint8ToStringArray(vals) {\n  try {\n    return vals.map((val) => decodeString(val));\n  } catch (err) {\n    throw new Error(`Failed to decode encoded string bytes into utf-8, error: ${err}`);\n  }\n}\nfunction fromStringArrayToUint8(strings) {\n  return strings.map((s2) => encodeString(s2));\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/kernel_impls.js\nvar kernel_impls_exports = {};\n__export(kernel_impls_exports, {\n  nonMaxSuppressionV3Impl: () => nonMaxSuppressionV3Impl,\n  nonMaxSuppressionV4Impl: () => nonMaxSuppressionV4Impl,\n  nonMaxSuppressionV5Impl: () => nonMaxSuppressionV5Impl,\n  whereImpl: () => whereImpl\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Abs_grad.js\nvar absGradConfig = {\n  kernelName: Abs,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(dy, step(cast(x, \"float32\"), -1)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Acos_grad.js\nvar acosGradConfig = {\n  kernelName: Acos,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return {\n      x: () => {\n        const a = square(cast(x, \"float32\"));\n        const b = sqrt(sub(scalar(1), a));\n        return neg(div(dy, b));\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Acosh_grad.js\nvar acoshGradConfig = {\n  kernelName: Acosh,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return {\n      x: () => {\n        const a = sqrt(sub(square(cast(x, \"float32\")), 1));\n        return div(dy, a);\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Add_grad.js\nvar addGradConfig = {\n  kernelName: Add,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const outShape = assertAndGetBroadcastShape(a.shape, b.shape);\n    const derA = () => {\n      let res = dy;\n      const reduceAxes = getReductionAxes(a.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(res, a.shape);\n    };\n    const derB = () => {\n      let res = dy;\n      const reduceAxes = getReductionAxes(b.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(res, b.shape);\n    };\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/AddN_grad.js\nvar addNGradConfig = {\n  kernelName: AddN,\n  saveAllInputs: true,\n  gradFunc: (dy, saved) => {\n    const ders = {};\n    saved.forEach((_, i2) => {\n      ders[i2] = () => dy.clone();\n    });\n    return ders;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ArgMax_grad.js\nvar argMaxGradConfig = {\n  kernelName: ArgMax,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => zerosLike(x) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ArgMin_grad.js\nvar argMinGradConfig = {\n  kernelName: ArgMin,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => zerosLike(x) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Asin_grad.js\nvar asinGradConfig = {\n  kernelName: Asin,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, sqrt(sub(scalar(1), square(cast(x, \"float32\"))))) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Asinh_grad.js\nvar asinhGradConfig = {\n  kernelName: Asinh,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return {\n      x: () => {\n        const a = sqrt(add2(scalar(1), square(cast(x, \"float32\"))));\n        return div(dy, a);\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Atan2_grad.js\nvar atan2GradConfig = {\n  kernelName: Atan2,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const outShape = assertAndGetBroadcastShape(a.shape, b.shape);\n    const derA = () => {\n      const d = add2(square(a), square(b));\n      let res = mul(dy, div(b, d));\n      const reduceAxes = getReductionAxes(a.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(res, a.shape);\n    };\n    const derB = () => {\n      const d = add2(square(a), square(b));\n      let res = neg(mul(dy, div(a, d)));\n      const reduceAxes = getReductionAxes(b.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(res, b.shape);\n    };\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Atan_grad.js\nvar atanGradConfig = {\n  kernelName: Atan,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, add2(square(cast(x, \"float32\")), 1)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Atanh_grad.js\nvar atanhGradConfig = {\n  kernelName: Atanh,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, sub(scalar(1), square(cast(x, \"float32\")))) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool_3d_grad.js\nfunction avgPool3dGrad_(dy, input2, filterSize, strides, pad3, dimRoundingMode) {\n  const $dy = convertToTensor(dy, \"dy\", \"avgPool3dGrad\");\n  const $input = convertToTensor(input2, \"input\", \"avgPool3dGrad\");\n  let dy5D = $dy;\n  let input5D = $input;\n  let reshapedTo5D = false;\n  if ($input.rank === 4) {\n    reshapedTo5D = true;\n    dy5D = reshape($dy, [1, $dy.shape[0], $dy.shape[1], $dy.shape[2], $dy.shape[3]]);\n    input5D = reshape($input, [\n      1,\n      $input.shape[0],\n      $input.shape[1],\n      $input.shape[2],\n      $input.shape[3]\n    ]);\n  }\n  assert(dy5D.rank === 5, () => `Error in avgPool3dGrad: dy must be rank 5 but got rank ${dy5D.rank}.`);\n  assert(input5D.rank === 5, () => `Error in avgPool3dGrad: input must be rank 5 but got rank ${input5D.rank}.`);\n  checkPadOnDimRoundingMode(\"avgPool3dGrad\", pad3, dimRoundingMode);\n  const inputs = { dy: dy5D, input: input5D };\n  const attrs = { filterSize, strides, pad: pad3, dimRoundingMode };\n  const res = ENGINE.runKernel(AvgPool3DGrad, inputs, attrs);\n  if (reshapedTo5D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);\n  }\n  return res;\n}\nvar avgPool3dGrad = op({ avgPool3dGrad_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/AvgPool3D_grad.js\nvar avgPool3DGradConfig = {\n  kernelName: AvgPool3D,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n    return {\n      x: () => avgPool3dGrad(dy, x, filterSize, strides, pad3, dimRoundingMode)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool_grad.js\nfunction avgPoolGrad_(dy, input2, filterSize, strides, pad3) {\n  const $dy = convertToTensor(dy, \"dy\", \"avgPoolGrad\");\n  const $input = convertToTensor(input2, \"input\", \"avgPoolGrad\");\n  assert($input.rank === $dy.rank, () => `Rank of input (${$input.rank}) does not match rank of dy (${$dy.rank})`);\n  let input4D = $input;\n  let dy4D = $dy;\n  let reshapedTo4D = false;\n  if ($input.rank === 3) {\n    reshapedTo4D = true;\n    input4D = reshape($input, [1, $input.shape[0], $input.shape[1], $input.shape[2]]);\n    dy4D = reshape($dy, [1, $dy.shape[0], $dy.shape[1], $dy.shape[2]]);\n  }\n  assert(dy4D.rank === 4, () => `Error in avgPoolGrad: dy must be rank 4 but got rank ${dy4D.rank}.`);\n  assert(input4D.rank === 4, () => `Error in avgPoolGrad: input must be rank 4 but got rank ${input4D.rank}.`);\n  const inputs = { dy: dy4D, input: input4D };\n  const attrs = { filterSize, strides, pad: pad3 };\n  const res = ENGINE.runKernel(AvgPoolGrad, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar avgPoolGrad = op({ avgPoolGrad_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/AvgPool_grad.js\nvar avgPoolGradConfig = {\n  kernelName: AvgPool,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { filterSize, strides, pad: pad3 } = attrs;\n    return { x: () => avgPoolGrad(dy, x, filterSize, strides, pad3) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/BatchMatMul_grad.js\nvar batchMatMulGradConfig = {\n  kernelName: BatchMatMul,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [a, b] = saved;\n    const { transposeA, transposeB } = attrs;\n    if (!transposeA && !transposeB) {\n      return {\n        a: () => matMul(dy, b, false, true),\n        b: () => matMul(a, dy, true, false)\n      };\n    } else if (!transposeA && transposeB) {\n      return {\n        a: () => matMul(dy, b, false, false),\n        b: () => matMul(dy, a, true, false)\n      };\n    } else if (transposeA && !transposeB) {\n      return {\n        a: () => matMul(b, dy, false, true),\n        b: () => matMul(a, dy, false, false)\n      };\n    } else {\n      return {\n        a: () => matMul(b, dy, true, true),\n        b: () => matMul(dy, a, true, true)\n      };\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/BatchToSpaceND_grad.js\nvar batchToSpaceNDGradConfig = {\n  kernelName: BatchToSpaceND,\n  gradFunc: (dy, saved, attrs) => {\n    const { blockShape, crops } = attrs;\n    return { x: () => spaceToBatchND(dy, blockShape, crops) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/BroadcastTo_grad.js\nvar broadcastToGradConfig = {\n  kernelName: BroadcastTo,\n  gradFunc: (dy, saved, attrs) => {\n    const broadCastToAttrs = attrs;\n    const inputShape = broadCastToAttrs.inputShape;\n    const outputShape = broadCastToAttrs.shape;\n    const reps = Array.from(outputShape);\n    for (let i2 = inputShape.length - 1; i2 >= 0; i2--) {\n      if (inputShape[i2] === outputShape[i2]) {\n        reps[i2] = 1;\n      } else if (inputShape[i2] !== 1) {\n        throw new Error(`broadcastTo(): [${inputShape}] cannot be broadcast to [${outputShape}].`);\n      }\n    }\n    const axes = [];\n    for (let i2 = 0; i2 < reps.length; i2++) {\n      if (reps[i2] > 1) {\n        axes.push(i2);\n      }\n    }\n    return { x: () => sum2(dy, axes, true) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Cast_grad.js\nvar castGradConfig = {\n  kernelName: Cast,\n  gradFunc: (dy) => {\n    return { x: () => dy.clone() };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Ceil_grad.js\nvar ceilGradConfig = {\n  kernelName: Ceil,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ClipByValue_grad.js\nvar clipByValueGradConfig = {\n  kernelName: ClipByValue,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { clipValueMin, clipValueMax } = attrs;\n    return {\n      x: () => where(logicalAnd(greaterEqual(x, clipValueMin), lessEqual(x, clipValueMax)), dy, zerosLike(dy))\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ComplexAbs_grad.js\nvar complexAbsGradConfig = {\n  kernelName: ComplexAbs,\n  inputsToSave: [\"x\"],\n  gradFunc: absGradConfig.gradFunc\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Concat_grad.js\nvar concatGradConfig = {\n  kernelName: Concat,\n  saveAllInputs: true,\n  gradFunc: (dy, saved, attrs) => {\n    const shapes = saved.map((t2) => t2.shape);\n    const { axis } = attrs;\n    const $axis = parseAxisParam(axis, saved[0].shape)[0];\n    const sizeSplits = shapes.map((s2) => s2[$axis]);\n    const derTensors = split(dy, sizeSplits, $axis);\n    return derTensors.map((t2) => () => t2);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Conv2D_grad.js\nvar conv2DGradConfig = {\n  kernelName: Conv2D,\n  inputsToSave: [\"x\", \"filter\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x4D, $filter] = saved;\n    const { dilations, strides, pad: pad3, dataFormat } = attrs;\n    assert(tupleValuesAreOne(dilations), () => `Error in gradient of conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${dilations}'`);\n    return {\n      x: () => conv2DBackpropInput(x4D.shape, dy, $filter, strides, pad3, dataFormat),\n      filter: () => conv2DBackpropFilter(x4D, dy, $filter.shape, strides, pad3, dataFormat)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Conv2DBackpropInput_grad.js\nvar conv2DBackpropInputGradConfig = {\n  kernelName: Conv2DBackpropInput,\n  inputsToSave: [\"dy\", \"filter\"],\n  gradFunc: (ddx, saved, attrs) => {\n    const [dy, filter] = saved;\n    const { strides, pad: pad3, dataFormat, dimRoundingMode } = attrs;\n    return {\n      dy: () => conv2d(ddx, filter, strides, pad3, dataFormat, 1, dimRoundingMode),\n      filter: () => conv2DBackpropFilter(ddx, dy, filter.shape, strides, pad3, dataFormat, dimRoundingMode)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv3d_backprop_filter.js\nfunction conv3DBackpropFilter_(x, dy, filterShape, strides, pad3) {\n  let x5D = x;\n  if (x.rank === 4) {\n    x5D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2], x.shape[3]]);\n  }\n  let dy5D = dy;\n  if (dy5D.rank === 4) {\n    dy5D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2], dy.shape[3]]);\n  }\n  assert(x5D.rank === 5, () => `Error in conv3dDerFilter: input must be rank 5, but got shape ${x5D.shape}.`);\n  assert(dy5D.rank === 5, () => `Error in conv3dDerFilter: dy must be rank 5, but got shape ${dy5D.shape}.`);\n  assert(filterShape.length === 5, () => `Error in conv3dDerFilter: filterShape must be length 5, but got ${filterShape}.`);\n  assert(x5D.shape[4] === filterShape[3], () => `Error in conv3dDerFilter: depth of input ${x5D.shape[4]}) must match input depth in filter (${filterShape[3]}.`);\n  assert(dy5D.shape[4] === filterShape[4], () => `Error in conv3dDerFilter: depth of dy (${dy5D.shape[4]}) must match output depth for filter (${filterShape[4]}).`);\n  const inputs = { x: x5D, dy: dy5D };\n  const attrs = { strides, pad: pad3, filterShape };\n  return ENGINE.runKernel(Conv3DBackpropFilterV2, inputs, attrs);\n}\nvar conv3DBackpropFilter = op({ conv3DBackpropFilter_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Conv3D_grad.js\nvar conv3DGradConfig = {\n  kernelName: Conv3D,\n  inputsToSave: [\"x\", \"filter\"],\n  gradFunc: (dy, saved, attrs) => {\n    const { dilations, strides, pad: pad3 } = attrs;\n    assert(tupleValuesAreOne(dilations), () => `Error in gradient of conv3D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${dilations}'`);\n    const [x5D, $filter] = saved;\n    return {\n      x: () => conv3DBackpropInput(x5D.shape, dy, $filter, strides, pad3),\n      filter: () => conv3DBackpropFilter(x5D, dy, $filter.shape, strides, pad3)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Cos_grad.js\nvar cosGradConfig = {\n  kernelName: Cos,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(neg(sin(cast(x, \"float32\"))), dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Cosh_grad.js\nvar coshGradConfig = {\n  kernelName: Cosh,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(sinh(cast(x, \"float32\")), dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Cumsum_grad.js\nvar cumsumGradConfig = {\n  kernelName: Cumsum,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { axis, exclusive, reverse: reverse5 } = attrs;\n    return {\n      x: () => {\n        const permutation = getAxesPermutation([axis], x.rank);\n        let out = cumsum(dy, axis, exclusive, !reverse5);\n        if (permutation != null) {\n          out = transpose(out, permutation);\n        }\n        return out;\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/DepthwiseConv2dNative_grad.js\nvar depthwiseConv2dNativeGradConfig = {\n  kernelName: DepthwiseConv2dNative,\n  inputsToSave: [\"x\", \"filter\"],\n  gradFunc: (dy, saved, attrs) => {\n    const { dilations, strides, pad: pad3, dimRoundingMode } = attrs;\n    const $dilations = dilations == null ? [1, 1] : dilations;\n    assert(tupleValuesAreOne($dilations), () => `Error in gradient of depthwiseConv2dNative: dilation rates greater than 1 are not yet supported. Got dilations '${$dilations}'`);\n    const [x, filter] = saved;\n    assert(x.rank === 4, () => `Error in gradient of depthwiseConv2dNative: input must be rank 4, but got rank ${x.rank}.`);\n    assert(filter.rank === 4, () => `Error in gradient of depthwiseConv2dNative: filter must be rank 4, but got rank ${filter.rank}.`);\n    assert(x.shape[3] === filter.shape[2], () => `Error in gradient of depthwiseConv2d: number of input channels (${x.shape[3]}) must match the inChannels dimension in filter ${filter.shape[2]}.`);\n    assert(eitherStridesOrDilationsAreOne(strides, $dilations), () => `Error in gradient of depthwiseConv2d: Either strides or dilations must be  1. Got strides ${strides} and dilations '${$dilations}'.`);\n    checkPadOnDimRoundingMode(\"depthwiseConv2d\", pad3, dimRoundingMode);\n    return {\n      x: () => depthwiseConv2dNativeBackpropInput(x.shape, dy, filter, strides, pad3, $dilations, dimRoundingMode),\n      filter: () => depthwiseConv2dNativeBackpropFilter(x, dy, filter.shape, strides, pad3, $dilations, dimRoundingMode)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Dilation2D_grad.js\nvar dilation2dGradConfig = {\n  kernelName: Dilation2D,\n  inputsToSave: [\"x\", \"filter\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x, filter] = saved;\n    const inputInputs = { x, filter, dy };\n    const filterInputs = { x, filter, dy };\n    return {\n      x: () => ENGINE.runKernel(Dilation2DBackpropInput, inputInputs, attrs),\n      filter: () => ENGINE.runKernel(Dilation2DBackpropFilter, filterInputs, attrs)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Elu_grad.js\nvar eluGradConfig = {\n  kernelName: Elu,\n  outputsToSave: [true],\n  gradFunc: (dy, saved) => {\n    const [y] = saved;\n    const inputs = { dy, y };\n    return { x: () => ENGINE.runKernel(EluGrad, inputs) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Erf_grad.js\nvar erfGradConfig = {\n  kernelName: Erf,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    const a = mul(exp(neg(square(x))), 2 / Math.sqrt(Math.PI));\n    return { x: () => mul(dy, a) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Exp_grad.js\nvar expGradConfig = {\n  kernelName: Exp,\n  outputsToSave: [true],\n  gradFunc: (dy, saved) => {\n    const [y] = saved;\n    return { x: () => mul(dy, y) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ExpandDims_grad.js\nvar expandDimsGradConfig = {\n  kernelName: ExpandDims,\n  inputsToSave: [\"input\"],\n  gradFunc: (dy, saved) => {\n    const [input2] = saved;\n    return { input: () => reshape(dy, input2.shape) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Expm1_grad.js\nvar expm1GradConfig = {\n  kernelName: Expm1,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(dy, exp(x)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Floor_grad.js\nvar floorGradConfig = {\n  kernelName: Floor,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/FloorDiv_grad.js\nvar floorDivGradConfig = {\n  kernelName: FloorDiv,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const outShape = assertAndGetBroadcastShape(a.shape, b.shape);\n    const derA = () => {\n      const res = div(dy, cast(b, \"float32\"));\n      const reduceAxes = getReductionAxes(a.shape, outShape);\n      if (reduceAxes.length > 0) {\n        return reshape(sum2(res, reduceAxes), a.shape);\n      }\n      return res;\n    };\n    const derB = () => {\n      let res = mul(dy, cast(a, \"float32\"));\n      const reduceAxes = getReductionAxes(b.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = reshape(sum2(res, reduceAxes), b.shape);\n      }\n      const tmp = square(b);\n      return neg(div(res, cast(tmp, \"float32\")));\n    };\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/FusedBatchNorm_grad.js\nvar fusedBatchNormGradConfig = {\n  kernelName: FusedBatchNorm,\n  inputsToSave: [\"x\", \"mean\", \"variance\", \"scale\"],\n  gradFunc: (dy, saved, attrs) => {\n    const { varianceEpsilon } = attrs;\n    const [x, mean5, variance, scale2] = saved;\n    const scaleValue = scale2 == null ? scalar(1) : scale2;\n    const reductionAxes = getReductionAxes(mean5.shape, x.shape);\n    const tileShape = [];\n    if (mean5.rank === 1) {\n      for (let i2 = 0; i2 < x.shape.length - 1; ++i2) {\n        tileShape.push(x.shape[i2]);\n      }\n      tileShape.push(1);\n    }\n    const xMinusMean = sub(x, mean5);\n    const dyTimesScaleValue = mul(dy, scaleValue);\n    const oneOverSqrtVariance = rsqrt(add2(variance, scalar(varianceEpsilon)));\n    const minusHalfRCube = mul(mul(mul(oneOverSqrtVariance, oneOverSqrtVariance), oneOverSqrtVariance), scalar(-0.5));\n    const derX = () => {\n      if (mean5.rank === 1) {\n        return reshape(mul(mul(dy, tile(reshape(oneOverSqrtVariance, [1, 1, 1, mean5.shape[0]]), tileShape)), scaleValue), x.shape);\n      } else {\n        return reshape(mul(mul(dy, oneOverSqrtVariance), scaleValue), x.shape);\n      }\n    };\n    const derMean = () => {\n      let meanDer = mul(mul(oneOverSqrtVariance, scalar(-1)), dyTimesScaleValue);\n      if (mean5.rank === 1) {\n        meanDer = sum2(meanDer, reductionAxes);\n      }\n      return reshape(meanDer, mean5.shape);\n    };\n    const derVariance = () => {\n      let varianceDer = mul(mul(minusHalfRCube, xMinusMean), dyTimesScaleValue);\n      if (mean5.rank === 1) {\n        varianceDer = sum2(varianceDer, reductionAxes);\n      }\n      return reshape(varianceDer, mean5.shape);\n    };\n    const derScale = () => {\n      const xMinusMean2TimesRsqrt = mul(xMinusMean, oneOverSqrtVariance);\n      let scaleDer = mul(dy, xMinusMean2TimesRsqrt);\n      if (mean5.rank === 1) {\n        scaleDer = sum2(scaleDer, reductionAxes);\n      }\n      return reshape(scaleDer, mean5.shape);\n    };\n    const derOffset = () => {\n      let offsetDer = dy;\n      if (mean5.rank === 1) {\n        offsetDer = sum2(offsetDer, reductionAxes);\n      }\n      return reshape(offsetDer, mean5.shape);\n    };\n    return {\n      x: derX,\n      mean: derMean,\n      variance: derVariance,\n      scale: derScale,\n      offset: derOffset\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/GatherV2_grad.js\nvar gatherGradConfig = {\n  kernelName: GatherV2,\n  inputsToSave: [\"x\", \"indices\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x, indices] = saved;\n    const { axis } = attrs;\n    const parsedAxis = parseAxisParam(axis, x.shape)[0];\n    const derX = () => {\n      const paramsShape = x.shape;\n      const indicesSize = indices.size;\n      const outerShape = paramsShape.slice(0, parsedAxis);\n      const outerDims = outerShape.length;\n      const innerShape = paramsShape.slice(axis, paramsShape.length).slice(1);\n      const innerDims = innerShape.length;\n      const outerAxesIndices = arrayRange(0, outerDims);\n      const innerAxesIndices = arrayRange(outerDims + 1, outerDims + 1 + innerDims);\n      const valuesShape = arrayConcat([outerShape, [indicesSize], innerShape]);\n      const values = reshape(dy, valuesShape);\n      const reshapedIndices = reshape(indices, [indicesSize]);\n      const transposeDims = arrayConcat([[outerDims], outerAxesIndices, innerAxesIndices]);\n      const valuesTranspose = transpose(values, transposeDims);\n      let paramsGrad = unsortedSegmentSum(valuesTranspose, reshapedIndices, x.shape[parsedAxis]);\n      const invertTransposeDims = getUndoAxesPermutation(transposeDims);\n      paramsGrad = transpose(paramsGrad, invertTransposeDims);\n      return paramsGrad;\n    };\n    return { x: derX, indices: () => indices };\n  }\n};\nfunction arrayRange(start, stop) {\n  const result = [];\n  for (let i2 = start; i2 < stop; ++i2) {\n    result.push(i2);\n  }\n  return result;\n}\nfunction arrayConcat(arrays) {\n  const result = [];\n  for (let i2 = 0; i2 < arrays.length; ++i2) {\n    for (let j = 0; j < arrays[i2].length; ++j) {\n      result.push(arrays[i2][j]);\n    }\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/GreaterEqual_grad.js\nvar greaterEqualGradConfig = {\n  kernelName: GreaterEqual,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    return { a: () => zerosLike(a), b: () => zerosLike(b) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Identity_grad.js\nvar identityGradConfig = {\n  kernelName: Identity,\n  gradFunc: (dy) => {\n    return { x: () => cast(dy, \"float32\") };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/IsFinite_grad.js\nvar isFiniteGradConfig = {\n  kernelName: IsFinite,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/IsInf_grad.js\nvar isInfGradConfig = {\n  kernelName: IsInf,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/IsNan_grad.js\nvar isNanGradConfig = {\n  kernelName: IsNan,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/LeakyRelu_grad.js\nvar leakyReluGradConfig = {\n  kernelName: LeakyRelu,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { alpha } = attrs;\n    const mask = greater(x, 0);\n    return { x: () => where(mask, dy, mul(dy, alpha)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Log1p_grad.js\nvar log1pGradConfig = {\n  kernelName: Log1p,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, add2(x, 1)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Log_grad.js\nvar logGradConfig = {\n  kernelName: Log,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, cast(x, \"float32\")) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/LogSoftmax_grad.js\nvar logSoftmaxGradConfig = {\n  kernelName: LogSoftmax,\n  inputsToSave: [],\n  outputsToSave: [true],\n  gradFunc: (dy, saved, attrs) => {\n    const [value] = saved;\n    const { axis } = attrs;\n    return {\n      logits: () => {\n        const keepDims = true;\n        const softmax7 = exp(value);\n        return sub(dy, mul(sum2(dy, axis, keepDims), softmax7));\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/local_response_normalization_backprop.js\nfunction localResponseNormalizationBackprop_(x, y, dy, depthRadius = 5, bias = 1, alpha = 1, beta = 0.5) {\n  const inputs = { x, y, dy };\n  const attrs = { depthRadius, bias, alpha, beta };\n  return ENGINE.runKernel(LRNGrad, inputs, attrs);\n}\nvar localResponseNormalizationBackprop = op({ localResponseNormalizationBackprop_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/LRN_grad.js\nvar lrnGradConfig = {\n  kernelName: LRN,\n  inputsToSave: [\"x\"],\n  outputsToSave: [true],\n  gradFunc: (dy, saved, attrs) => {\n    const [x, y] = saved;\n    const { depthRadius, bias, alpha, beta } = attrs;\n    return {\n      x: () => localResponseNormalizationBackprop(x, y, dy, depthRadius, bias, alpha, beta)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/min_max_grad_util.js\nfunction gradForMinAndMax(dy, y, xOrig, origAxes) {\n  if (y.rank < xOrig.rank) {\n    y = reshape(y, expandShapeToKeepDim(y.shape, origAxes));\n  }\n  if (dy.rank < xOrig.rank) {\n    dy = reshape(dy, expandShapeToKeepDim(dy.shape, origAxes));\n  }\n  return {\n    x: () => {\n      const dx = mul(dy, cast(equal(xOrig, y), dy.dtype));\n      return dx;\n    }\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Max_grad.js\nvar maxGradConfig = {\n  kernelName: Max,\n  inputsToSave: [\"x\"],\n  outputsToSave: [true],\n  gradFunc: (dy, saved, attrs) => {\n    const maxAttrs = attrs;\n    const { reductionIndices } = maxAttrs;\n    const x = saved[0];\n    const y = saved[1];\n    const origAxes = parseAxisParam(reductionIndices, x.shape);\n    const maxGrad = gradForMinAndMax(dy, y, x, origAxes);\n    return {\n      x: () => {\n        return maxGrad[\"x\"]();\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Maximum_grad.js\nvar maximumGradConfig = {\n  kernelName: Maximum,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const derA = () => mul(dy, cast(greaterEqual(a, b), \"float32\"));\n    const derB = () => mul(dy, cast(less(a, b), \"float32\"));\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_3d_grad.js\nfunction maxPool3dGrad_(dy, input2, output, filterSize, strides, pad3, dimRoundingMode) {\n  const $dy = convertToTensor(dy, \"dy\", \"maxPool3dGrad\");\n  const $input = convertToTensor(input2, \"input\", \"maxPool3dGrad\");\n  const $output = convertToTensor(output, \"output\", \"maxPool3dGrad\");\n  let dy5D = $dy;\n  let input5D = $input;\n  let output5D = $output;\n  let reshapedTo5D = false;\n  if ($input.rank === 4) {\n    reshapedTo5D = true;\n    dy5D = reshape($dy, [1, $dy.shape[0], $dy.shape[1], $dy.shape[2], $dy.shape[3]]);\n    input5D = reshape($input, [\n      1,\n      $input.shape[0],\n      $input.shape[1],\n      $input.shape[2],\n      $input.shape[3]\n    ]);\n    output5D = reshape($output, [\n      1,\n      $output.shape[0],\n      $output.shape[1],\n      $output.shape[2],\n      $output.shape[3]\n    ]);\n  }\n  assert(dy5D.rank === 5, () => `Error in maxPool3dGrad: dy must be rank 5 but got rank ${dy5D.rank}.`);\n  assert(input5D.rank === 5, () => `Error in maxPool3dGrad: input must be rank 5 but got rank ${input5D.rank}.`);\n  assert(output5D.rank === 5, () => `Error in maxPool3dGrad: output must be rank 5 but got rank ${output5D.rank}.`);\n  checkPadOnDimRoundingMode(\"maxPool3dGrad\", pad3, dimRoundingMode);\n  const inputs = { dy: dy5D, input: input5D, output: output5D };\n  const attrs = { filterSize, strides, pad: pad3, dimRoundingMode };\n  const res = ENGINE.runKernel(MaxPool3DGrad, inputs, attrs);\n  if (reshapedTo5D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);\n  }\n  return res;\n}\nvar maxPool3dGrad = op({ maxPool3dGrad_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/MaxPool3D_grad.js\nvar maxPool3DGradConfig = {\n  kernelName: MaxPool3D,\n  inputsToSave: [\"x\"],\n  outputsToSave: [true],\n  gradFunc: (dy, saved, attrs) => {\n    const [x, y] = saved;\n    const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n    return {\n      x: () => maxPool3dGrad(dy, x, y, filterSize, strides, pad3, dimRoundingMode)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_grad.js\nfunction maxPoolGrad_(dy, input2, output, filterSize, strides, pad3, dimRoundingMode) {\n  const $dy = convertToTensor(dy, \"dy\", \"maxPoolGrad\");\n  const $input = convertToTensor(input2, \"input\", \"maxPoolGrad\");\n  const $output = convertToTensor(output, \"output\", \"maxPoolGrad\");\n  assert($input.rank === $dy.rank, () => `Rank of input (${$input.rank}) does not match rank of dy (${$dy.rank})`);\n  assert($dy.rank === 4, () => `Error in maxPoolGrad: dy must be rank 4 but got rank ${$dy.rank}.`);\n  assert($input.rank === 4, () => `Error in maxPoolGrad: input must be rank 4 but got rank ${$input.rank}.`);\n  checkPadOnDimRoundingMode(\"maxPoolGrad\", pad3, dimRoundingMode);\n  const inputs = { dy: $dy, input: $input, output: $output };\n  const attrs = { filterSize, strides, pad: pad3, dimRoundingMode };\n  return ENGINE.runKernel(MaxPoolGrad, inputs, attrs);\n}\nvar maxPoolGrad = op({ maxPoolGrad_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/MaxPool_grad.js\nvar maxPoolGradConfig = {\n  kernelName: MaxPool,\n  inputsToSave: [\"x\"],\n  outputsToSave: [true],\n  gradFunc: (dy, saved, attrs) => {\n    const [x, y] = saved;\n    const { filterSize, strides, pad: pad3 } = attrs;\n    return {\n      x: () => maxPoolGrad(dy, x, y, filterSize, strides, pad3)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Mean_grad.js\nvar meanGradConfig = {\n  kernelName: Mean,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { axis } = attrs;\n    const axes = parseAxisParam(axis, x.shape);\n    const shapes = computeOutAndReduceShapes(x.shape, axes);\n    const reduceShape = shapes[1];\n    const reduceSize = sizeFromShape(reduceShape);\n    const derX = () => {\n      const expandedDyShape = x.shape.slice();\n      axes.forEach((axis2) => {\n        expandedDyShape[axis2] = 1;\n      });\n      const expandedDy = reshape(dy, expandedDyShape);\n      const res = div(mul(expandedDy, ones2(x.shape, \"float32\")), reduceSize);\n      return res;\n    };\n    return { x: derX };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Min_grad.js\nvar minGradConfig = {\n  kernelName: Min,\n  inputsToSave: [\"x\"],\n  outputsToSave: [true],\n  gradFunc: (dy, saved, attrs) => {\n    const minAttrs = attrs;\n    const { axis } = minAttrs;\n    const [x, y] = saved;\n    const origAxes = parseAxisParam(axis, x.shape);\n    const minGrad = gradForMinAndMax(dy, y, x, origAxes);\n    return {\n      x: () => {\n        return minGrad[\"x\"]();\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Minimum_grad.js\nvar minimumGradConfig = {\n  kernelName: Minimum,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const derA = () => mul(dy, cast(lessEqual(a, b), \"float32\"));\n    const derB = () => mul(dy, cast(greater(a, b), \"float32\"));\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/MirrorPad_grad.js\nvar mirrorPadGradConfig = {\n  kernelName: MirrorPad,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const x = saved[0];\n    const { paddings } = attrs;\n    const begin = paddings.map((p2) => p2[0]);\n    return { x: () => slice(dy, begin, x.shape) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Mod_grad.js\nvar modGradConfig = {\n  kernelName: Mod,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const outShape = assertAndGetBroadcastShape(a.shape, b.shape);\n    const derA = () => {\n      const reduceAxes = getReductionAxes(a.shape, outShape);\n      if (reduceAxes.length > 0) {\n        return reshape(sum2(dy, reduceAxes), a.shape);\n      }\n      return dy;\n    };\n    const derB = () => {\n      const res = mul(dy, neg(floor(div(a, b))));\n      const reduceAxes = getReductionAxes(b.shape, outShape);\n      if (reduceAxes.length > 0) {\n        return reshape(sum2(res, reduceAxes), b.shape);\n      }\n      return res;\n    };\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Multiply_grad.js\nvar multiplyGradConfig = {\n  kernelName: Multiply,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const outShape = assertAndGetBroadcastShape(a.shape, b.shape);\n    const derA = () => {\n      const res = mul(dy, cast(b, \"float32\"));\n      const reduceAxes = getReductionAxes(a.shape, outShape);\n      if (reduceAxes.length > 0) {\n        return reshape(sum2(res, reduceAxes), a.shape);\n      }\n      return res;\n    };\n    const derB = () => {\n      const res = mul(dy, cast(a, \"float32\"));\n      const reduceAxes = getReductionAxes(b.shape, outShape);\n      if (reduceAxes.length > 0) {\n        return reshape(sum2(res, reduceAxes), b.shape);\n      }\n      return res;\n    };\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Neg_grad.js\nvar negGradConfig = {\n  kernelName: Neg,\n  gradFunc: (dy) => {\n    return { x: () => neg(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/OneHot_grad.js\nvar oneHotGradConfig = {\n  kernelName: OneHot,\n  inputsToSave: [\"indices\"],\n  gradFunc: (dy, saved) => {\n    const indices = saved[0];\n    return { indices: () => zeros(indices.shape, \"float32\") };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/OnesLike_grad.js\nvar onesLikeGradConfig = {\n  kernelName: OnesLike,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Pack_grad.js\nvar packGradConfig = {\n  kernelName: Pack,\n  saveAllInputs: true,\n  gradFunc: (dy, saved, attrs) => {\n    const { axis } = attrs;\n    const derTensors = unstack(dy, axis);\n    return derTensors.map((t2) => () => t2);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/PadV2_grad.js\nvar padV2GradConfig = {\n  kernelName: PadV2,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const x = saved[0];\n    const { paddings } = attrs;\n    const begin = paddings.map((p2) => p2[0]);\n    return { x: () => slice(dy, begin, x.shape) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Pow_grad.js\nvar powGradConfig = {\n  kernelName: Pow,\n  inputsToSave: [\"a\", \"b\"],\n  outputsToSave: [true],\n  gradFunc: (dy, saved) => {\n    const [a, b, y] = saved;\n    const base = a;\n    const exp5 = b;\n    const outShape = assertAndGetBroadcastShape(base.shape, exp5.shape);\n    const derBase = () => {\n      const expFloat = cast(exp5, \"float32\");\n      let res = mul(dy, mul(expFloat, pow(base, sub(expFloat, scalar(1)))));\n      const reduceAxes = getReductionAxes(base.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(res, base.shape);\n    };\n    const derExp = () => {\n      const condition = greater(base, 0);\n      const logBase = where(condition, log2(base), zerosLike(base));\n      let res = mul(dy, mul(y, logBase));\n      const reduceAxes = getReductionAxes(exp5.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(res, exp5.shape);\n    };\n    return { a: derBase, b: derExp };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Prelu_grad.js\nvar preluGradConfig = {\n  kernelName: Prelu,\n  inputsToSave: [\"x\", \"alpha\"],\n  gradFunc: (dy, saved) => {\n    const [x, alpha] = saved;\n    const mask = greater(x, 0);\n    return {\n      x: () => where(mask, dy, mul(dy, alpha)),\n      alpha: () => {\n        let res = where(mask, zerosLike(dy), mul(dy, x));\n        const reduceAxes = getReductionAxes(alpha.shape, dy.shape);\n        if (reduceAxes.length > 0) {\n          res = sum2(res, reduceAxes);\n        }\n        return reshape(res, alpha.shape);\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Prod_grad.js\nfunction prodGradFn_(x, dy, axis) {\n  const expandedYShape = x.shape.slice();\n  expandedYShape[axis] = 1;\n  const expandedDy = reshape(dy, expandedYShape);\n  const xCumProd = cumprod(x, axis, true, false);\n  const xCumRevProd = cumprod(x, axis, true, true);\n  const dx = mul(xCumProd, xCumRevProd);\n  return mul(expandedDy, dx);\n}\nfunction prodsGradFn_(x, dy, axis) {\n  const xRank = x.shape.length;\n  const finalProdAxis = xRank - axis.length;\n  const xPermutation = backend_util_exports.getAxesPermutation(axis, xRank);\n  let permutedX = x;\n  if (xPermutation != null) {\n    permutedX = transpose(x, xPermutation);\n  }\n  const newShape = permutedX.shape.slice();\n  const removedShape = newShape.splice(xRank - axis.length, axis.length);\n  const endPartShape = removedShape.reduce((p2, c) => p2 * c, 1);\n  newShape.push(endPartShape);\n  const reshapedPermutedX = permutedX.reshape(newShape);\n  let prodGrad = prodGradFn_(reshapedPermutedX, dy, finalProdAxis);\n  prodGrad = prodGrad.reshape(permutedX.shape);\n  if (xPermutation != null) {\n    const undoPermutation = backend_util_exports.getUndoAxesPermutation(xPermutation);\n    prodGrad = transpose(prodGrad, undoPermutation);\n  }\n  return prodGrad;\n}\nvar prodGradConfig = {\n  kernelName: Prod,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { axis } = attrs;\n    let axisArr = [];\n    if (axis === void 0 || axis === null) {\n      axisArr = x.shape.map((_, i2) => i2);\n    } else if (typeof axis === \"number\") {\n      axisArr = [axis];\n    } else {\n      axisArr = axis;\n    }\n    return { x: () => prodsGradFn_(x, dy, axisArr) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/RealDiv_grad.js\nvar divGradConfig = {\n  kernelName: RealDiv,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const outShape = assertAndGetBroadcastShape(a.shape, b.shape);\n    const derA = () => {\n      const res = div(dy, cast(b, \"float32\"));\n      const reduceAxes = getReductionAxes(a.shape, outShape);\n      if (reduceAxes.length > 0) {\n        return reshape(sum2(res, reduceAxes), a.shape);\n      }\n      return res;\n    };\n    const derB = () => {\n      let res = mul(dy, cast(a, \"float32\"));\n      const reduceAxes = getReductionAxes(b.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = reshape(sum2(res, reduceAxes), b.shape);\n      }\n      const tmp = square(b);\n      return neg(div(res, cast(tmp, \"float32\")));\n    };\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Reciprocal_grad.js\nvar reciprocalGradConfig = {\n  kernelName: Reciprocal,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, neg(square(x))) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Relu6_grad.js\nvar relu6GradConfig = {\n  kernelName: Relu6,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    const mask = mul(lessEqual(x, 6), step(x));\n    return { x: () => mul(dy, cast(mask, \"float32\")) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Relu_grad.js\nvar reluGradConfig = {\n  kernelName: Relu,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(dy, cast(step(x), \"float32\")) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Reshape_grad.js\nvar reshapeGradConfig = {\n  kernelName: Reshape,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => reshape(dy, x.shape) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ResizeBilinear_grad.js\nvar resizeBilinearGradConfig = {\n  kernelName: ResizeBilinear,\n  inputsToSave: [\"images\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [images] = saved;\n    const inputs = { dy, images };\n    const imagesDer = () => ENGINE.runKernel(ResizeBilinearGrad, inputs, attrs);\n    return { images: imagesDer };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ResizeNearestNeighbor_grad.js\nvar resizeNearestNeighborGradConfig = {\n  kernelName: ResizeNearestNeighbor,\n  inputsToSave: [\"images\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [images] = saved;\n    const inputs = { dy, images };\n    const imagesDer = () => ENGINE.runKernel(ResizeNearestNeighborGrad, inputs, attrs);\n    return { images: imagesDer };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Reverse_grad.js\nvar reverseGradConfig = {\n  kernelName: Reverse,\n  gradFunc: (dy, saved, attrs) => {\n    const { dims } = attrs;\n    const axes = parseAxisParam(dims, dy.shape);\n    return { x: () => reverse(dy, axes) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Round_grad.js\nvar roundGradConfig = {\n  kernelName: Round,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Rsqrt_grad.js\nvar rsqrtGradConfig = {\n  kernelName: Rsqrt,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => neg(div(dy, mul(pow(x, 1.5), 2))) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Select_grad.js\nvar selectGradConfig = {\n  kernelName: Select,\n  inputsToSave: [\"condition\"],\n  gradFunc: (dy, saved) => {\n    const [condition] = saved;\n    return {\n      condition: () => cast(zerosLike(condition), \"float32\"),\n      t: () => mul(dy, cast(condition, dy.dtype)),\n      e: () => mul(dy, cast(logicalNot(condition), dy.dtype))\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Selu_grad.js\nvar seluGradConfig = {\n  kernelName: Selu,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return {\n      x: () => {\n        const mask = greater(x, scalar(0));\n        const scaleAlpha2 = scalar(SELU_SCALEALPHA);\n        const scale2 = scalar(SELU_SCALE);\n        const greaterThanZeroDer = mul(dy, scale2);\n        const lessEqualZeroDer = mul(mul(dy, scaleAlpha2), exp(cast(x, \"float32\")));\n        return where(mask, greaterThanZeroDer, lessEqualZeroDer);\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Sigmoid_grad.js\nvar sigmoidGradConfig = {\n  kernelName: Sigmoid,\n  outputsToSave: [true],\n  gradFunc: (dy, saved) => {\n    const [y] = saved;\n    return { x: () => mul(dy, mul(y, sub(scalar(1), y))) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Sign_grad.js\nvar signGradConfig = {\n  kernelName: Sign,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Sin_grad.js\nvar sinGradConfig = {\n  kernelName: Sin,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(cos(cast(x, \"float32\")), dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Sinh_grad.js\nvar sinhGradConfig = {\n  kernelName: Sinh,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(cosh(cast(x, \"float32\")), dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Slice_grad.js\nvar sliceGradConfig = {\n  kernelName: Slice,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { begin, size } = attrs;\n    const inputShape = x.shape;\n    const [begin_, size_] = parseSliceParams(x, begin, size);\n    const paddings = [];\n    for (let i2 = 0; i2 < dy.rank; i2++) {\n      paddings.push([begin_[i2], inputShape[i2] - begin_[i2] - size_[i2]]);\n    }\n    return { x: () => pad(dy, paddings) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Softmax_grad.js\nvar softmaxGradConfig = {\n  kernelName: Softmax,\n  outputsToSave: [true],\n  gradFunc: (dy, saved, attrs) => {\n    const [y] = saved;\n    const { dim } = attrs;\n    const keepDims = true;\n    const dyTimesY = mul(dy, y);\n    return {\n      logits: () => sub(dyTimesY, mul(sum2(dyTimesY, [dim], keepDims), y))\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Softplus_grad.js\nvar softplusGradConfig = {\n  kernelName: Softplus,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(dy, sigmoid(x)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/SpaceToBatchND_grad.js\nvar spaceToBatchNDGradConfig = {\n  kernelName: SpaceToBatchND,\n  gradFunc: (dy, saved, attrs) => {\n    const { blockShape, paddings } = attrs;\n    return { x: () => batchToSpaceND(dy, blockShape, paddings) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/SplitV_grad.js\nvar splitVGradConfig = {\n  kernelName: SplitV,\n  gradFunc: (dy, saved, attrs) => {\n    const { axis } = attrs;\n    return { x: () => concat(dy, axis) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Sqrt_grad.js\nvar sqrtGradConfig = {\n  kernelName: Sqrt,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, mul(sqrt(cast(x, \"float32\")), 2)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Square_grad.js\nvar squareGradConfig = {\n  kernelName: Square,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(dy, mul(cast(x, \"float32\"), 2)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/SquaredDifference_grad.js\nvar squaredDifferenceGradConfig = {\n  kernelName: SquaredDifference,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const two = scalar(2);\n    const derA = () => mul(dy, mul(two, sub(a, b)));\n    const derB = () => mul(dy, mul(two, sub(b, a)));\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Step_grad.js\nvar stepGradConfig = {\n  kernelName: Step,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Sub_grad.js\nvar subGradConfig = {\n  kernelName: Sub,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const outShape = assertAndGetBroadcastShape(a.shape, b.shape);\n    const derA = () => {\n      let res = dy;\n      const reduceAxes = getReductionAxes(a.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(res, a.shape);\n    };\n    const derB = () => {\n      let res = dy;\n      const reduceAxes = getReductionAxes(b.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(neg(res), b.shape);\n    };\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Sum_grad.js\nvar sumGradConfig = {\n  kernelName: Sum,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const expandedDyShape = x.shape.slice();\n    const { axis } = attrs;\n    const axes = parseAxisParam(axis, x.shape);\n    axes.forEach((axis2) => {\n      expandedDyShape[axis2] = 1;\n    });\n    const expandedDy = reshape(dy, expandedDyShape);\n    const derX = mul(expandedDy, ones2(x.shape, \"float32\"));\n    return { x: () => derX };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Tan_grad.js\nvar tanGradConfig = {\n  kernelName: Tan,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, square(cos(x))) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Tanh_grad.js\nvar tanhGradConfig = {\n  kernelName: Tanh,\n  outputsToSave: [true],\n  gradFunc: (dy, saved) => {\n    const [y] = saved;\n    return { x: () => mul(sub(scalar(1), square(y)), dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Tile_grad.js\nvar tileGradConfig = {\n  kernelName: Tile,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { reps } = attrs;\n    const derX = () => {\n      let xGrad = zerosLike(x);\n      if (x.rank === 1) {\n        for (let i2 = 0; i2 < reps[0]; ++i2) {\n          xGrad = add2(xGrad, slice(dy, [i2 * x.shape[0]], [x.shape[0]]));\n        }\n      } else if (x.rank === 2) {\n        for (let i2 = 0; i2 < reps[0]; ++i2) {\n          for (let j = 0; j < reps[1]; ++j) {\n            xGrad = add2(xGrad, slice(dy, [i2 * x.shape[0], j * x.shape[1]], [\n              x.shape[0],\n              x.shape[1]\n            ]));\n          }\n        }\n      } else if (x.rank === 3) {\n        for (let i2 = 0; i2 < reps[0]; ++i2) {\n          for (let j = 0; j < reps[1]; ++j) {\n            for (let k = 0; k < reps[2]; ++k) {\n              xGrad = add2(xGrad, slice(dy, [i2 * x.shape[0], j * x.shape[1], k * x.shape[2]], [x.shape[0], x.shape[1], x.shape[2]]));\n            }\n          }\n        }\n      } else if (x.rank === 4) {\n        for (let i2 = 0; i2 < reps[0]; ++i2) {\n          for (let j = 0; j < reps[1]; ++j) {\n            for (let k = 0; k < reps[2]; ++k) {\n              for (let l3 = 0; l3 < reps[3]; ++l3) {\n                xGrad = add2(xGrad, slice(dy, [\n                  i2 * x.shape[0],\n                  j * x.shape[1],\n                  k * x.shape[2],\n                  l3 * x.shape[3]\n                ], [x.shape[0], x.shape[1], x.shape[2], x.shape[3]]));\n              }\n            }\n          }\n        }\n      } else {\n        throw new Error(`Gradient for tile operation is not implemented for rank-${x.rank} tensors yet.`);\n      }\n      return xGrad;\n    };\n    return { x: derX };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Transpose_grad.js\nvar transposeGradConfig = {\n  kernelName: Transpose,\n  gradFunc: (dy, saved, attrs) => {\n    const transposeAttrs = attrs;\n    const { perm } = transposeAttrs;\n    const undoPerm = getUndoAxesPermutation(perm);\n    return { x: () => transpose(dy, undoPerm) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Unpack_grad.js\nvar unpackGradConfig = {\n  kernelName: Unpack,\n  gradFunc: (dy, saved, attrs) => {\n    const unpackAttrs = attrs;\n    const { axis } = unpackAttrs;\n    return { value: () => stack(dy, axis) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/UnsortedSegmentSum_grad.js\nvar unsortedSegmentSumGradConfig = {\n  kernelName: UnsortedSegmentSum,\n  inputsToSave: [\"segmentIds\"],\n  gradFunc: (dy, saved) => {\n    const [segmentIds] = saved;\n    const derX = () => {\n      return gatherDropNegatives(dy, segmentIds);\n    };\n    return { x: derX };\n  }\n};\nfunction gatherDropNegatives(x, indices) {\n  const zeroClippedIndices = maximum(indices, zerosLike(indices));\n  const gathered = gather(x, zeroClippedIndices);\n  let isPositive = greaterEqual(indices, scalar(0, \"int32\"));\n  const numIters = gathered.rank - isPositive.rank;\n  for (let i2 = 0; i2 < numIters; ++i2) {\n    isPositive = expandDims(isPositive, i2 + 1);\n  }\n  isPositive = logicalAnd(isPositive, ones2(gathered.shape, \"bool\"));\n  const zeroSlice = zerosLike(gathered);\n  return where(isPositive, gathered, zeroSlice);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ZerosLike_grad.js\nvar zerosLikeGradConfig = {\n  kernelName: ZerosLike,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/register_all_gradients.js\nvar gradConfigs = [\n  absGradConfig,\n  acosGradConfig,\n  acoshGradConfig,\n  addGradConfig,\n  addNGradConfig,\n  argMaxGradConfig,\n  argMinGradConfig,\n  asinGradConfig,\n  asinhGradConfig,\n  atan2GradConfig,\n  atanGradConfig,\n  atanhGradConfig,\n  avgPool3DGradConfig,\n  avgPoolGradConfig,\n  batchMatMulGradConfig,\n  batchToSpaceNDGradConfig,\n  broadcastToGradConfig,\n  castGradConfig,\n  ceilGradConfig,\n  clipByValueGradConfig,\n  complexAbsGradConfig,\n  concatGradConfig,\n  conv2DBackpropInputGradConfig,\n  conv2DGradConfig,\n  conv3DGradConfig,\n  cosGradConfig,\n  coshGradConfig,\n  cumsumGradConfig,\n  depthwiseConv2dNativeGradConfig,\n  dilation2dGradConfig,\n  divGradConfig,\n  eluGradConfig,\n  erfGradConfig,\n  expGradConfig,\n  expandDimsGradConfig,\n  expm1GradConfig,\n  floorDivGradConfig,\n  floorGradConfig,\n  fusedBatchNormGradConfig,\n  gatherGradConfig,\n  greaterEqualGradConfig,\n  identityGradConfig,\n  isFiniteGradConfig,\n  isInfGradConfig,\n  isNanGradConfig,\n  leakyReluGradConfig,\n  log1pGradConfig,\n  logGradConfig,\n  logSoftmaxGradConfig,\n  lrnGradConfig,\n  maxGradConfig,\n  maxGradConfig,\n  maximumGradConfig,\n  maxPool3DGradConfig,\n  maxPoolGradConfig,\n  meanGradConfig,\n  minGradConfig,\n  minimumGradConfig,\n  mirrorPadGradConfig,\n  modGradConfig,\n  multiplyGradConfig,\n  negGradConfig,\n  oneHotGradConfig,\n  onesLikeGradConfig,\n  packGradConfig,\n  padV2GradConfig,\n  padV2GradConfig,\n  powGradConfig,\n  preluGradConfig,\n  prodGradConfig,\n  reciprocalGradConfig,\n  relu6GradConfig,\n  reluGradConfig,\n  reshapeGradConfig,\n  resizeBilinearGradConfig,\n  resizeNearestNeighborGradConfig,\n  reverseGradConfig,\n  roundGradConfig,\n  rsqrtGradConfig,\n  selectGradConfig,\n  seluGradConfig,\n  sigmoidGradConfig,\n  signGradConfig,\n  sinGradConfig,\n  sinhGradConfig,\n  sliceGradConfig,\n  softmaxGradConfig,\n  softplusGradConfig,\n  spaceToBatchNDGradConfig,\n  spaceToBatchNDGradConfig,\n  splitVGradConfig,\n  splitVGradConfig,\n  sqrtGradConfig,\n  squaredDifferenceGradConfig,\n  squareGradConfig,\n  stepGradConfig,\n  subGradConfig,\n  sumGradConfig,\n  tanGradConfig,\n  tanhGradConfig,\n  tileGradConfig,\n  transposeGradConfig,\n  unpackGradConfig,\n  unsortedSegmentSumGradConfig,\n  zerosLikeGradConfig\n];\nfor (const gradientConfig of gradConfigs) {\n  registerGradient(gradientConfig);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/abs.js\ngetGlobalTensorClass().prototype.abs = function() {\n  this.throwIfDisposed();\n  return abs(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/acos.js\ngetGlobalTensorClass().prototype.acos = function() {\n  this.throwIfDisposed();\n  return acos(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/acosh.js\ngetGlobalTensorClass().prototype.acosh = function() {\n  this.throwIfDisposed();\n  return acosh(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/add.js\ngetGlobalTensorClass().prototype.add = function(b) {\n  this.throwIfDisposed();\n  return add2(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/all.js\ngetGlobalTensorClass().prototype.all = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return all(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/any.js\ngetGlobalTensorClass().prototype.any = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return any(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/arg_max.js\ngetGlobalTensorClass().prototype.argMax = function(axis) {\n  this.throwIfDisposed();\n  return argMax(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/arg_min.js\ngetGlobalTensorClass().prototype.argMin = function(axis) {\n  this.throwIfDisposed();\n  return argMin(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/as_scalar.js\ngetGlobalTensorClass().prototype.asScalar = function() {\n  this.throwIfDisposed();\n  assert(this.size === 1, () => \"The array must have only 1 element.\");\n  return reshape(this, []);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/as_type.js\ngetGlobalTensorClass().prototype.asType = function(dtype) {\n  this.throwIfDisposed();\n  return cast(this, dtype);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/as1d.js\ngetGlobalTensorClass().prototype.as1D = function() {\n  this.throwIfDisposed();\n  return reshape(this, [this.size]);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/as2d.js\ngetGlobalTensorClass().prototype.as2D = function(rows, columns) {\n  this.throwIfDisposed();\n  return reshape(this, [rows, columns]);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/as3d.js\ngetGlobalTensorClass().prototype.as3D = function(rows, columns, depth) {\n  this.throwIfDisposed();\n  return reshape(this, [rows, columns, depth]);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/as4d.js\ngetGlobalTensorClass().prototype.as4D = function(rows, columns, depth, depth2) {\n  this.throwIfDisposed();\n  return reshape(this, [rows, columns, depth, depth2]);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/as5d.js\ngetGlobalTensorClass().prototype.as5D = function(rows, columns, depth, depth2, depth3) {\n  this.throwIfDisposed();\n  return reshape(this, [rows, columns, depth, depth2, depth3]);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/asin.js\ngetGlobalTensorClass().prototype.asin = function() {\n  this.throwIfDisposed();\n  return asin(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/asinh.js\ngetGlobalTensorClass().prototype.asinh = function() {\n  this.throwIfDisposed();\n  return asinh(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/atan.js\ngetGlobalTensorClass().prototype.atan = function() {\n  this.throwIfDisposed();\n  return atan(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/atan2.js\ngetGlobalTensorClass().prototype.atan2 = function(b) {\n  this.throwIfDisposed();\n  return atan2(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/atanh.js\ngetGlobalTensorClass().prototype.atanh = function() {\n  this.throwIfDisposed();\n  return atanh(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/avg_pool.js\ngetGlobalTensorClass().prototype.avgPool = function(filterSize, strides, pad3, dimRoundingMode) {\n  this.throwIfDisposed();\n  return avgPool(this, filterSize, strides, pad3, dimRoundingMode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/batch_to_space_nd.js\ngetGlobalTensorClass().prototype.batchToSpaceND = function(blockShape, crops) {\n  this.throwIfDisposed();\n  return batchToSpaceND(this, blockShape, crops);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/batchnorm.js\ngetGlobalTensorClass().prototype.batchNorm = function(mean5, variance, offset, scale2, varianceEpsilon) {\n  this.throwIfDisposed();\n  return batchNorm(this, mean5, variance, offset, scale2, varianceEpsilon);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/broadcast_to.js\ngetGlobalTensorClass().prototype.broadcastTo = function(shape) {\n  this.throwIfDisposed();\n  return broadcastTo(this, shape);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/cast.js\ngetGlobalTensorClass().prototype.cast = function(dtype) {\n  this.throwIfDisposed();\n  return cast(this, dtype);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/ceil.js\ngetGlobalTensorClass().prototype.ceil = function() {\n  this.throwIfDisposed();\n  return ceil(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/clip_by_value.js\ngetGlobalTensorClass().prototype.clipByValue = function(min7, max7) {\n  this.throwIfDisposed();\n  return clipByValue(this, min7, max7);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/concat.js\ngetGlobalTensorClass().prototype.concat = function(x, axis) {\n  this.throwIfDisposed();\n  if (x instanceof Tensor) {\n    x = [x];\n  }\n  return concat([this, ...x], axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/conv1d.js\ngetGlobalTensorClass().prototype.conv1d = function(filter, stride, pad3, dataFormat, dilation, dimRoundingMode) {\n  this.throwIfDisposed();\n  return conv1d(this, filter, stride, pad3, dataFormat, dilation, dimRoundingMode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/conv2d_transpose.js\ngetGlobalTensorClass().prototype.conv2dTranspose = function(filter, outputShape, strides, pad3, dimRoundingMode) {\n  this.throwIfDisposed();\n  return conv2dTranspose(this, filter, outputShape, strides, pad3, dimRoundingMode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/conv2d.js\ngetGlobalTensorClass().prototype.conv2d = function(filter, strides, pad3, dataFormat, dilations, dimRoundingMode) {\n  this.throwIfDisposed();\n  return conv2d(this, filter, strides, pad3, dataFormat, dilations, dimRoundingMode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/cos.js\ngetGlobalTensorClass().prototype.cos = function() {\n  this.throwIfDisposed();\n  return cos(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/cosh.js\ngetGlobalTensorClass().prototype.cosh = function() {\n  this.throwIfDisposed();\n  return cosh(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/cumprod.js\ngetGlobalTensorClass().prototype.cumprod = function(axis, exclusive, reverse5) {\n  this.throwIfDisposed();\n  return cumprod(this, axis, exclusive, reverse5);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/cumsum.js\ngetGlobalTensorClass().prototype.cumsum = function(axis, exclusive, reverse5) {\n  this.throwIfDisposed();\n  return cumsum(this, axis, exclusive, reverse5);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/depth_to_space.js\ngetGlobalTensorClass().prototype.depthToSpace = function(blockSize, dataFormat) {\n  this.throwIfDisposed();\n  return depthToSpace(this, blockSize, dataFormat);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/depthwise_conv2d.js\ngetGlobalTensorClass().prototype.depthwiseConv2d = function(filter, strides, pad3, dataFormat, dilations, dimRoundingMode) {\n  this.throwIfDisposed();\n  return depthwiseConv2d(this, filter, strides, pad3, dataFormat, dilations, dimRoundingMode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/dilation2d.js\ngetGlobalTensorClass().prototype.dilation2d = function(filter, strides, pad3, dilations, dataFormat) {\n  this.throwIfDisposed();\n  return dilation2d(this, filter, strides, pad3, dilations, dataFormat);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/div_no_nan.js\ngetGlobalTensorClass().prototype.divNoNan = function(b) {\n  this.throwIfDisposed();\n  return divNoNan(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/div.js\ngetGlobalTensorClass().prototype.div = function(b) {\n  this.throwIfDisposed();\n  return div(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/dot.js\ngetGlobalTensorClass().prototype.dot = function(b) {\n  this.throwIfDisposed();\n  return dot(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/elu.js\ngetGlobalTensorClass().prototype.elu = function() {\n  this.throwIfDisposed();\n  return elu(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/equal.js\ngetGlobalTensorClass().prototype.equal = function(b) {\n  this.throwIfDisposed();\n  return equal(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/erf.js\ngetGlobalTensorClass().prototype.erf = function() {\n  this.throwIfDisposed();\n  return erf(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/euclidean_norm.js\ngetGlobalTensorClass().prototype.euclideanNorm = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return euclideanNorm(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/exp.js\ngetGlobalTensorClass().prototype.exp = function() {\n  this.throwIfDisposed();\n  return exp(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/expand_dims.js\ngetGlobalTensorClass().prototype.expandDims = function(axis) {\n  this.throwIfDisposed();\n  return expandDims(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/expm1.js\ngetGlobalTensorClass().prototype.expm1 = function() {\n  this.throwIfDisposed();\n  return expm1(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/fft.js\ngetGlobalTensorClass().prototype.fft = function() {\n  this.throwIfDisposed();\n  return fft(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/flatten.js\ngetGlobalTensorClass().prototype.flatten = function() {\n  this.throwIfDisposed();\n  return reshape(this, [this.size]);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/floor.js\ngetGlobalTensorClass().prototype.floor = function() {\n  this.throwIfDisposed();\n  return floor(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/floorDiv.js\ngetGlobalTensorClass().prototype.floorDiv = function(b) {\n  this.throwIfDisposed();\n  return floorDiv(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/gather.js\ngetGlobalTensorClass().prototype.gather = function(indices, axis) {\n  this.throwIfDisposed();\n  return gather(this, indices, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/greater_equal.js\ngetGlobalTensorClass().prototype.greaterEqual = function(b) {\n  this.throwIfDisposed();\n  return greaterEqual(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/greater.js\ngetGlobalTensorClass().prototype.greater = function(b) {\n  this.throwIfDisposed();\n  return greater(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/ifft.js\ngetGlobalTensorClass().prototype.ifft = function() {\n  this.throwIfDisposed();\n  return ifft(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/irfft.js\ngetGlobalTensorClass().prototype.irfft = function() {\n  this.throwIfDisposed();\n  return irfft(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/is_finite.js\ngetGlobalTensorClass().prototype.isFinite = function() {\n  this.throwIfDisposed();\n  return isFinite2(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/is_inf.js\ngetGlobalTensorClass().prototype.isInf = function() {\n  this.throwIfDisposed();\n  return isInf(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/is_nan.js\ngetGlobalTensorClass().prototype.isNaN = function() {\n  this.throwIfDisposed();\n  return isNaN2(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/leaky_relu.js\ngetGlobalTensorClass().prototype.leakyRelu = function(alpha) {\n  this.throwIfDisposed();\n  return leakyRelu(this, alpha);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/less_equal.js\ngetGlobalTensorClass().prototype.lessEqual = function(b) {\n  this.throwIfDisposed();\n  return lessEqual(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/less.js\ngetGlobalTensorClass().prototype.less = function(b) {\n  this.throwIfDisposed();\n  return less(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/local_response_normalization.js\ngetGlobalTensorClass().prototype.localResponseNormalization = function(depthRadius, bias, alpha, beta) {\n  this.throwIfDisposed();\n  return localResponseNormalization(this, depthRadius, bias, alpha, beta);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/log_sigmoid.js\ngetGlobalTensorClass().prototype.logSigmoid = function() {\n  this.throwIfDisposed();\n  return logSigmoid(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/log_softmax.js\ngetGlobalTensorClass().prototype.logSoftmax = function(axis) {\n  this.throwIfDisposed();\n  return logSoftmax(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/log_sum_exp.js\ngetGlobalTensorClass().prototype.logSumExp = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return logSumExp(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/log.js\ngetGlobalTensorClass().prototype.log = function() {\n  this.throwIfDisposed();\n  return log2(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/log1p.js\ngetGlobalTensorClass().prototype.log1p = function() {\n  this.throwIfDisposed();\n  return log1p(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/logical_and.js\ngetGlobalTensorClass().prototype.logicalAnd = function(b) {\n  this.throwIfDisposed();\n  return logicalAnd(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/logical_not.js\ngetGlobalTensorClass().prototype.logicalNot = function() {\n  this.throwIfDisposed();\n  return logicalNot(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/logical_or.js\ngetGlobalTensorClass().prototype.logicalOr = function(b) {\n  this.throwIfDisposed();\n  return logicalOr(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/logical_xor.js\ngetGlobalTensorClass().prototype.logicalXor = function(b) {\n  this.throwIfDisposed();\n  return logicalXor(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mat_mul.js\ngetGlobalTensorClass().prototype.matMul = function(b, transposeA, transposeB) {\n  this.throwIfDisposed();\n  return matMul(this, b, transposeA, transposeB);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/max_pool.js\ngetGlobalTensorClass().prototype.maxPool = function(filterSize, strides, pad3, dimRoundingMode) {\n  this.throwIfDisposed();\n  return maxPool(this, filterSize, strides, pad3, dimRoundingMode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/max.js\ngetGlobalTensorClass().prototype.max = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return max(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/maximum.js\ngetGlobalTensorClass().prototype.maximum = function(b) {\n  this.throwIfDisposed();\n  return maximum(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mean.js\ngetGlobalTensorClass().prototype.mean = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return mean(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/min.js\ngetGlobalTensorClass().prototype.min = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return min(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/minimum.js\ngetGlobalTensorClass().prototype.minimum = function(b) {\n  this.throwIfDisposed();\n  return minimum(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mirror_pad.js\ngetGlobalTensorClass().prototype.mirrorPad = function(paddings, mode) {\n  this.throwIfDisposed();\n  return mirrorPad(this, paddings, mode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mod.js\ngetGlobalTensorClass().prototype.mod = function(b) {\n  this.throwIfDisposed();\n  return mod(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mul.js\ngetGlobalTensorClass().prototype.mul = function(b) {\n  this.throwIfDisposed();\n  return mul(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/neg.js\ngetGlobalTensorClass().prototype.neg = function() {\n  this.throwIfDisposed();\n  return neg(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/norm.js\ngetGlobalTensorClass().prototype.norm = function(ord, axis, keepDims) {\n  this.throwIfDisposed();\n  return norm(this, ord, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/not_equal.js\ngetGlobalTensorClass().prototype.notEqual = function(b) {\n  this.throwIfDisposed();\n  return notEqual(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/one_hot.js\ngetGlobalTensorClass().prototype.oneHot = function(depth, onValue = 1, offValue = 0) {\n  this.throwIfDisposed();\n  return oneHot(this, depth, onValue, offValue);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/ones_like.js\ngetGlobalTensorClass().prototype.onesLike = function() {\n  this.throwIfDisposed();\n  return onesLike(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/pad.js\ngetGlobalTensorClass().prototype.pad = function(paddings, constantValue) {\n  this.throwIfDisposed();\n  return pad(this, paddings, constantValue);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/pool.js\ngetGlobalTensorClass().prototype.pool = function(windowShape, poolingType, padding, dilationRate, strides, dimRoundingMode) {\n  this.throwIfDisposed();\n  return pool(this, windowShape, poolingType, padding, dilationRate, strides, dimRoundingMode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/pow.js\ngetGlobalTensorClass().prototype.pow = function(exp5) {\n  this.throwIfDisposed();\n  return pow(this, exp5);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/prelu.js\ngetGlobalTensorClass().prototype.prelu = function(alpha) {\n  this.throwIfDisposed();\n  return prelu(this, alpha);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/prod.js\ngetGlobalTensorClass().prototype.prod = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return prod(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/reciprocal.js\ngetGlobalTensorClass().prototype.reciprocal = function() {\n  this.throwIfDisposed();\n  return reciprocal(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/relu.js\ngetGlobalTensorClass().prototype.relu = function() {\n  this.throwIfDisposed();\n  return relu(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/relu6.js\ngetGlobalTensorClass().prototype.relu6 = function() {\n  this.throwIfDisposed();\n  return relu6(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/reshape_as.js\ngetGlobalTensorClass().prototype.reshapeAs = function(x) {\n  this.throwIfDisposed();\n  return reshape(this, x.shape);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/reshape.js\ngetGlobalTensorClass().prototype.reshape = function(shape) {\n  this.throwIfDisposed();\n  return reshape(this, shape);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/resize_bilinear.js\ngetGlobalTensorClass().prototype.resizeBilinear = function(newShape2D, alignCorners, halfPixelCenters) {\n  this.throwIfDisposed();\n  return resizeBilinear(this, newShape2D, alignCorners, halfPixelCenters);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/resize_nearest_neighbor.js\ngetGlobalTensorClass().prototype.resizeNearestNeighbor = function(newShape2D, alignCorners, halfFloatCenters) {\n  this.throwIfDisposed();\n  return resizeNearestNeighbor(this, newShape2D, alignCorners, halfFloatCenters);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/reverse.js\ngetGlobalTensorClass().prototype.reverse = function(axis) {\n  this.throwIfDisposed();\n  return reverse(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/rfft.js\ngetGlobalTensorClass().prototype.rfft = function() {\n  this.throwIfDisposed();\n  return rfft(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/round.js\ngetGlobalTensorClass().prototype.round = function() {\n  this.throwIfDisposed();\n  return round2(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/rsqrt.js\ngetGlobalTensorClass().prototype.rsqrt = function() {\n  this.throwIfDisposed();\n  return rsqrt(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/selu.js\ngetGlobalTensorClass().prototype.selu = function() {\n  this.throwIfDisposed();\n  return selu(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/separable_conv2d.js\ngetGlobalTensorClass().prototype.separableConv2d = function(depthwiseFilter, pointwiseFilter, strides, pad3, dilation, dataFormat) {\n  this.throwIfDisposed();\n  return separableConv2d(this, depthwiseFilter, pointwiseFilter, strides, pad3, dilation, dataFormat);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sigmoid.js\ngetGlobalTensorClass().prototype.sigmoid = function() {\n  this.throwIfDisposed();\n  return sigmoid(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sign.js\ngetGlobalTensorClass().prototype.sign = function() {\n  this.throwIfDisposed();\n  return sign(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sin.js\ngetGlobalTensorClass().prototype.sin = function() {\n  this.throwIfDisposed();\n  return sin(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sinh.js\ngetGlobalTensorClass().prototype.sinh = function() {\n  this.throwIfDisposed();\n  return sinh(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/slice.js\ngetGlobalTensorClass().prototype.slice = function(begin, size) {\n  this.throwIfDisposed();\n  return slice(this, begin, size);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/softmax.js\ngetGlobalTensorClass().prototype.softmax = function(dim) {\n  this.throwIfDisposed();\n  return softmax(this, dim);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/softplus.js\ngetGlobalTensorClass().prototype.softplus = function() {\n  this.throwIfDisposed();\n  return softplus(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/space_to_batch_nd.js\ngetGlobalTensorClass().prototype.spaceToBatchND = function(blockShape, paddings) {\n  this.throwIfDisposed();\n  return spaceToBatchND(this, blockShape, paddings);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/split.js\ngetGlobalTensorClass().prototype.split = function(numOrSizeSplits, axis) {\n  this.throwIfDisposed();\n  return split(this, numOrSizeSplits, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sqrt.js\ngetGlobalTensorClass().prototype.sqrt = function() {\n  this.throwIfDisposed();\n  return sqrt(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/square.js\ngetGlobalTensorClass().prototype.square = function() {\n  this.throwIfDisposed();\n  return square(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/squared_difference.js\ngetGlobalTensorClass().prototype.squaredDifference = function(b) {\n  this.throwIfDisposed();\n  return squaredDifference(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/squeeze.js\ngetGlobalTensorClass().prototype.squeeze = function(axis) {\n  this.throwIfDisposed();\n  return squeeze(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/stack.js\ngetGlobalTensorClass().prototype.stack = function(x, axis) {\n  this.throwIfDisposed();\n  const tensorsToBeStacked = x instanceof Tensor ? [this, x] : [this, ...x];\n  return stack(tensorsToBeStacked, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/step.js\ngetGlobalTensorClass().prototype.step = function(alpha) {\n  this.throwIfDisposed();\n  return step(this, alpha);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/strided_slice.js\ngetGlobalTensorClass().prototype.stridedSlice = function(begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask) {\n  this.throwIfDisposed();\n  return stridedSlice(this, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sub.js\ngetGlobalTensorClass().prototype.sub = function(b) {\n  this.throwIfDisposed();\n  return sub(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sum.js\ngetGlobalTensorClass().prototype.sum = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return sum2(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/tan.js\ngetGlobalTensorClass().prototype.tan = function() {\n  this.throwIfDisposed();\n  return tan(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/tanh.js\ngetGlobalTensorClass().prototype.tanh = function() {\n  this.throwIfDisposed();\n  return tanh2(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/tile.js\ngetGlobalTensorClass().prototype.tile = function(reps) {\n  this.throwIfDisposed();\n  return tile(this, reps);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/to_bool.js\ngetGlobalTensorClass().prototype.toBool = function() {\n  this.throwIfDisposed();\n  return cast(this, \"bool\");\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/to_float.js\ngetGlobalTensorClass().prototype.toFloat = function() {\n  this.throwIfDisposed();\n  return cast(this, \"float32\");\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/to_int.js\ngetGlobalTensorClass().prototype.toInt = function() {\n  this.throwIfDisposed();\n  return cast(this, \"int32\");\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/topk.js\ngetGlobalTensorClass().prototype.topk = function(k, sorted) {\n  this.throwIfDisposed();\n  return topk(this, k, sorted);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/transpose.js\ngetGlobalTensorClass().prototype.transpose = function(perm) {\n  this.throwIfDisposed();\n  return transpose(this, perm);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/unique.js\ngetGlobalTensorClass().prototype.unique = function(axis) {\n  this.throwIfDisposed();\n  return unique(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/unsorted_segment_sum.js\ngetGlobalTensorClass().prototype.unsortedSegmentSum = function(segmentIds, numSegments) {\n  this.throwIfDisposed();\n  return unsortedSegmentSum(this, segmentIds, numSegments);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/unstack.js\ngetGlobalTensorClass().prototype.unstack = function(axis) {\n  this.throwIfDisposed();\n  return unstack(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/where.js\ngetGlobalTensorClass().prototype.where = function(condition, x) {\n  this.throwIfDisposed();\n  return where(condition, this, x);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/zeros_like.js\ngetGlobalTensorClass().prototype.zerosLike = function() {\n  this.throwIfDisposed();\n  return zerosLike(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/errors.js\nvar AttributeError = class extends Error {\n  constructor(message) {\n    super(message);\n    Object.setPrototypeOf(this, AttributeError.prototype);\n  }\n};\nvar RuntimeError = class extends Error {\n  constructor(message) {\n    super(message);\n    Object.setPrototypeOf(this, RuntimeError.prototype);\n  }\n};\nvar ValueError = class extends Error {\n  constructor(message) {\n    super(message);\n    Object.setPrototypeOf(this, ValueError.prototype);\n  }\n};\nvar NotImplementedError = class extends Error {\n  constructor(message) {\n    super(message);\n    Object.setPrototypeOf(this, NotImplementedError.prototype);\n  }\n};\nvar AssertionError = class extends Error {\n  constructor(message) {\n    super(message);\n    Object.setPrototypeOf(this, AssertionError.prototype);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/executor_utils.js\nvar LruCache = class {\n  constructor(maxEntries) {\n    this.maxEntries = maxEntries || 100;\n    this.cache = /* @__PURE__ */ new Map();\n  }\n  get(key) {\n    let entry;\n    if (this.cache.has(key)) {\n      entry = this.cache.get(key);\n      this.cache.delete(key);\n      this.cache.set(key, entry);\n    }\n    return entry;\n  }\n  put(key, value) {\n    if (this.cache.has(key)) {\n      this.cache.delete(key);\n    } else if (this.cache.size >= this.maxEntries) {\n      const keyToDelete = this.cache.keys().next().value;\n      this.cache.delete(keyToDelete);\n    }\n    this.cache.set(key, value);\n  }\n  getMaxEntries() {\n    return this.maxEntries;\n  }\n  setMaxEntries(maxEntries) {\n    if (maxEntries < 0) {\n      throw new Error(`The maxEntries of LRU caches must be at least 0, but got ${maxEntries}.`);\n    }\n    if (this.maxEntries > maxEntries) {\n      for (let i2 = 0; i2 < this.maxEntries - maxEntries; i2++) {\n        const keyToDelete = this.cache.keys().next().value;\n        this.cache.delete(keyToDelete);\n      }\n    }\n    this.maxEntries = maxEntries;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/generic_utils.js\nfunction pyListRepeat(value, numValues) {\n  if (Array.isArray(value)) {\n    let newArray = [];\n    for (let i2 = 0; i2 < numValues; i2++) {\n      newArray = newArray.concat(value);\n    }\n    return newArray;\n  } else {\n    const newArray = new Array(numValues);\n    newArray.fill(value);\n    return newArray;\n  }\n}\nfunction assert2(val, message) {\n  if (!val) {\n    throw new AssertionError(message);\n  }\n}\nfunction count(array2, refernce) {\n  let counter = 0;\n  for (const item of array2) {\n    if (item === refernce) {\n      counter++;\n    }\n  }\n  return counter;\n}\nfunction singletonOrArray(xs) {\n  if (xs.length === 1) {\n    return xs[0];\n  }\n  return xs;\n}\nfunction toList(x) {\n  if (Array.isArray(x)) {\n    return x;\n  }\n  return [x];\n}\nfunction toSnakeCase(name) {\n  const intermediate = name.replace(/(.)([A-Z][a-z0-9]+)/g, \"$1_$2\");\n  const insecure = intermediate.replace(/([a-z])([A-Z])/g, \"$1_$2\").toLowerCase();\n  if (insecure[0] !== \"_\") {\n    return insecure;\n  }\n  return \"private\" + insecure;\n}\nfunction toCamelCase(identifier) {\n  if (identifier.length <= 1) {\n    return identifier;\n  }\n  if (identifier.indexOf(\"_\") === -1) {\n    return identifier;\n  }\n  return identifier.replace(/[_]+(\\w|$)/g, (m, p1) => p1.toUpperCase());\n}\nvar _GLOBAL_CUSTOM_OBJECTS = {};\nfunction serializeKerasObject(instance) {\n  if (instance === null || instance === void 0) {\n    return null;\n  }\n  const dict = {};\n  dict[\"className\"] = instance.getClassName();\n  dict[\"config\"] = instance.getConfig();\n  return dict;\n}\nfunction convertNDArrayScalarsInConfig(config) {\n  if (config == null || typeof config !== \"object\") {\n    return;\n  } else if (Array.isArray(config)) {\n    config.forEach((configItem) => convertNDArrayScalarsInConfig(configItem));\n  } else {\n    const fields = Object.keys(config);\n    for (const field of fields) {\n      const value = config[field];\n      if (value != null && typeof value === \"object\") {\n        if (!Array.isArray(value) && value[\"type\"] === \"ndarray\" && typeof value[\"value\"] === \"number\") {\n          config[field] = value[\"value\"];\n        } else {\n          convertNDArrayScalarsInConfig(value);\n        }\n      }\n    }\n  }\n}\nfunction deserializeKerasObject(identifier, moduleObjects = {}, customObjects = {}, printableModuleName = \"object\", fastWeightInit = false) {\n  if (typeof identifier === \"string\") {\n    const functionName = identifier;\n    let fn;\n    if (functionName in customObjects) {\n      fn = customObjects[functionName];\n    } else if (functionName in _GLOBAL_CUSTOM_OBJECTS) {\n      fn = _GLOBAL_CUSTOM_OBJECTS[functionName];\n    } else {\n      fn = moduleObjects[functionName];\n      if (fn == null) {\n        throw new ValueError(`Unknown ${printableModuleName}: ${identifier}. This may be due to one of the following reasons:\n1. The ${printableModuleName} is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.\n2. The custom ${printableModuleName} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);\n      }\n    }\n    return fn;\n  } else {\n    const config = identifier;\n    if (config[\"className\"] == null || config[\"config\"] == null) {\n      throw new ValueError(`${printableModuleName}: Improper config format: ${JSON.stringify(config)}.\n'className' and 'config' must set.`);\n    }\n    const className = config[\"className\"];\n    let cls, fromConfig;\n    if (className in customObjects) {\n      [cls, fromConfig] = customObjects[className];\n    } else if (className in _GLOBAL_CUSTOM_OBJECTS) {\n      [cls, fromConfig] = _GLOBAL_CUSTOM_OBJECTS[\"className\"];\n    } else if (className in moduleObjects) {\n      [cls, fromConfig] = moduleObjects[className];\n    }\n    if (cls == null) {\n      throw new ValueError(`Unknown ${printableModuleName}: ${className}. This may be due to one of the following reasons:\n1. The ${printableModuleName} is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.\n2. The custom ${printableModuleName} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);\n    }\n    if (fromConfig != null) {\n      const customObjectsCombined = {};\n      for (const key of Object.keys(_GLOBAL_CUSTOM_OBJECTS)) {\n        customObjectsCombined[key] = _GLOBAL_CUSTOM_OBJECTS[key];\n      }\n      for (const key of Object.keys(customObjects)) {\n        customObjectsCombined[key] = customObjects[key];\n      }\n      const nestedConfig = config[\"config\"];\n      nestedConfig[\"customObjects\"] = customObjectsCombined;\n      const backupCustomObjects = Object.assign({}, _GLOBAL_CUSTOM_OBJECTS);\n      for (const key of Object.keys(customObjects)) {\n        _GLOBAL_CUSTOM_OBJECTS[key] = customObjects[key];\n      }\n      convertNDArrayScalarsInConfig(config[\"config\"]);\n      const returnObj = fromConfig(cls, config[\"config\"], customObjects, fastWeightInit);\n      _GLOBAL_CUSTOM_OBJECTS = Object.assign({}, backupCustomObjects);\n      return returnObj;\n    } else {\n      const backupCustomObjects = Object.assign({}, _GLOBAL_CUSTOM_OBJECTS);\n      for (const key of Object.keys(customObjects)) {\n        _GLOBAL_CUSTOM_OBJECTS[key] = customObjects[key];\n      }\n      const returnObj = new cls(config[\"config\"]);\n      _GLOBAL_CUSTOM_OBJECTS = Object.assign({}, backupCustomObjects);\n      return returnObj;\n    }\n  }\n}\nfunction numberCompare(a, b) {\n  return a < b ? -1 : a > b ? 1 : 0;\n}\nfunction reverseNumberCompare(a, b) {\n  return -1 * numberCompare(a, b);\n}\nfunction unique2(xs) {\n  if (xs == null) {\n    return xs;\n  }\n  const out = [];\n  for (const x of xs) {\n    if (out.indexOf(x) === -1) {\n      out.push(x);\n    }\n  }\n  return out;\n}\nfunction isObjectEmpty(obj) {\n  if (obj == null) {\n    throw new ValueError(`Invalid value in obj: ${JSON.stringify(obj)}`);\n  }\n  for (const key in obj) {\n    if (obj.hasOwnProperty(key)) {\n      return false;\n    }\n  }\n  return true;\n}\nfunction checkStringTypeUnionValue(values, label, value) {\n  if (value == null) {\n    return;\n  }\n  if (values.indexOf(value) < 0) {\n    throw new ValueError(`${value} is not a valid ${label}.  Valid values are ${values} or null/undefined.`);\n  }\n}\nfunction checkArrayTypeAndLength(x, expectedType, minLength = 0, maxLength = Infinity) {\n  assert2(minLength >= 0);\n  assert2(maxLength >= minLength);\n  return Array.isArray(x) && x.length >= minLength && x.length <= maxLength && x.every((e2) => typeof e2 === expectedType);\n}\nfunction assertPositiveInteger(value, name) {\n  if (Array.isArray(value)) {\n    util_exports.assert(value.length > 0, () => `${name} is unexpectedly an empty array.`);\n    value.forEach((v, i2) => assertPositiveInteger(v, `element ${i2 + 1} of ${name}`));\n  } else {\n    util_exports.assert(Number.isInteger(value) && value > 0, () => `Expected ${name} to be a positive integer, but got ${formatAsFriendlyString(value)}.`);\n  }\n}\nfunction formatAsFriendlyString(value) {\n  if (value === null) {\n    return \"null\";\n  } else if (Array.isArray(value)) {\n    return \"[\" + value.map((v) => formatAsFriendlyString(v)).join(\",\") + \"]\";\n  } else if (typeof value === \"string\") {\n    return `\"${value}\"`;\n  } else {\n    return `${value}`;\n  }\n}\nfunction debounce(f, waitMs, nowFunc) {\n  let lastTime = nowFunc != null ? nowFunc() : util_exports.now();\n  let lastResult;\n  const f2 = (...args) => {\n    const now2 = nowFunc != null ? nowFunc() : util_exports.now();\n    if (now2 - lastTime < waitMs) {\n      return lastResult;\n    }\n    lastTime = now2;\n    lastResult = f(...args);\n    return lastResult;\n  };\n  return f2;\n}\nfunction mapActivationToFusedKernel(activationName) {\n  if (activationName === \"relu\") {\n    return \"relu\";\n  }\n  if (activationName === \"linear\") {\n    return \"linear\";\n  }\n  if (activationName === \"elu\") {\n    return \"elu\";\n  }\n  return null;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/backend/state.js\nvar _nextUniqueTensorId = 0;\nfunction getNextUniqueTensorId() {\n  return _nextUniqueTensorId++;\n}\nvar _uidPrefixes = {};\nfunction getUid(prefix = \"\") {\n  if (!(prefix in _uidPrefixes)) {\n    _uidPrefixes[prefix] = 0;\n  }\n  _uidPrefixes[prefix] += 1;\n  return prefix + _uidPrefixes[prefix].toString();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/keras_format/common.js\nvar VALID_DATA_FORMAT_VALUES = [\"channelsFirst\", \"channelsLast\"];\nvar VALID_INTERPOLATION_FORMAT_VALUES = [\"nearest\", \"bilinear\"];\nvar VALID_PADDING_MODE_VALUES = [\"valid\", \"same\", \"causal\"];\nvar VALID_POOL_MODE_VALUES = [\"max\", \"avg\"];\nvar VALID_BIDIRECTIONAL_MERGE_MODES = [\"sum\", \"mul\", \"concat\", \"ave\"];\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/common.js\nvar nameMap = /* @__PURE__ */ new Map();\nfunction checkDataFormat(value) {\n  checkStringTypeUnionValue(VALID_DATA_FORMAT_VALUES, \"DataFormat\", value);\n}\nfunction checkInterpolationFormat(value) {\n  checkStringTypeUnionValue(VALID_INTERPOLATION_FORMAT_VALUES, \"InterpolationFormat\", value);\n}\nfunction checkPaddingMode(value) {\n  checkStringTypeUnionValue(VALID_PADDING_MODE_VALUES, \"PaddingMode\", value);\n}\nfunction checkPoolMode(value) {\n  checkStringTypeUnionValue(VALID_POOL_MODE_VALUES, \"PoolMode\", value);\n}\nvar _nameScopeStack = [];\nvar _nameScopeDivider = \"/\";\nfunction nameScope(name, fn) {\n  _nameScopeStack.push(name);\n  try {\n    const val = fn();\n    _nameScopeStack.pop();\n    return val;\n  } catch (e2) {\n    _nameScopeStack.pop();\n    throw e2;\n  }\n}\nfunction currentNameScopePrefix() {\n  if (_nameScopeStack.length === 0) {\n    return \"\";\n  } else {\n    return _nameScopeStack.join(_nameScopeDivider) + _nameScopeDivider;\n  }\n}\nfunction getScopedTensorName(tensorName) {\n  if (!isValidTensorName(tensorName)) {\n    throw new Error(\"Not a valid tensor name: '\" + tensorName + \"'\");\n  }\n  return currentNameScopePrefix() + tensorName;\n}\nfunction getUniqueTensorName(scopedName) {\n  if (!isValidTensorName(scopedName)) {\n    throw new Error(\"Not a valid tensor name: '\" + scopedName + \"'\");\n  }\n  if (!nameMap.has(scopedName)) {\n    nameMap.set(scopedName, 0);\n  }\n  const index = nameMap.get(scopedName);\n  nameMap.set(scopedName, nameMap.get(scopedName) + 1);\n  if (index > 0) {\n    const result = `${scopedName}_${index}`;\n    nameMap.set(result, 1);\n    return result;\n  } else {\n    return scopedName;\n  }\n}\nvar tensorNameRegex = new RegExp(/^[A-Za-z0-9][-A-Za-z0-9\\._\\/]*$/);\nfunction isValidTensorName(name) {\n  return !!name.match(tensorNameRegex);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/math_utils.js\nfunction isInteger(x) {\n  return x === parseInt(x.toString(), 10);\n}\nfunction arrayProd(array2, begin, end) {\n  if (begin == null) {\n    begin = 0;\n  }\n  if (end == null) {\n    end = array2.length;\n  }\n  let prod6 = 1;\n  for (let i2 = begin; i2 < end; ++i2) {\n    prod6 *= array2[i2];\n  }\n  return prod6;\n}\nfunction min2(array2) {\n  if (array2.length === 0) {\n    return Number.NaN;\n  }\n  let min7 = Number.POSITIVE_INFINITY;\n  for (let i2 = 0; i2 < array2.length; i2++) {\n    const value = array2[i2];\n    if (value < min7) {\n      min7 = value;\n    }\n  }\n  return min7;\n}\nfunction max2(array2) {\n  if (array2.length === 0) {\n    return Number.NaN;\n  }\n  let max7 = Number.NEGATIVE_INFINITY;\n  for (let i2 = 0; i2 < array2.length; i2++) {\n    const value = array2[i2];\n    if (value > max7) {\n      max7 = value;\n    }\n  }\n  return max7;\n}\nfunction range2(begin, end) {\n  if (end < begin) {\n    throw new ValueError(`end (${end}) < begin (${begin}) is forbidden.`);\n  }\n  const out = [];\n  for (let i2 = begin; i2 < end; ++i2) {\n    out.push(i2);\n  }\n  return out;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/backend/common.js\nvar _epsilon;\nfunction epsilon() {\n  if (_epsilon == null) {\n    _epsilon = backend().epsilon();\n  }\n  return _epsilon;\n}\nfunction imageDataFormat() {\n  return \"channelsLast\";\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/backend/tfjs_backend.js\nfunction cast2(x, dtype) {\n  return cast(x, dtype);\n}\nfunction expandDims2(x, axis = -1) {\n  const outShape = x.shape.slice();\n  if (axis < 0) {\n    axis = outShape.length + axis + 1;\n  }\n  outShape.splice(axis, 0, 1);\n  return reshape(x, outShape);\n}\nfunction repeat(x, n2) {\n  return tidy(() => {\n    if (x.shape.length !== 2) {\n      throw new ValueError(`repeat() expects a rank-2 tensor, but received a rank-${x.shape.length} tensor.`);\n    }\n    const y = expandDims2(x, 1);\n    return tile2(y, [1, n2, 1]);\n  });\n}\nfunction flatten2(x) {\n  const newShape = [arrayProd(x.shape)];\n  return reshape(x, newShape);\n}\nfunction batchFlatten(x) {\n  if (x.rank <= 1) {\n    throw new ValueError(`batchFlatten requires a minimum rank of 2. Got rank: ${x.rank}.`);\n  }\n  const newShape = [x.shape[0], arrayProd(x.shape, 1)];\n  return reshape(x, newShape);\n}\nfunction sliceAlongFirstAxis(array2, start, size) {\n  return tidy(() => {\n    switch (array2.rank) {\n      case 1:\n        return slice1d(array2, start, size);\n      case 2:\n        return slice2d(array2, [start, 0], [size, array2.shape[1]]);\n      case 3:\n        return slice3d(array2, [start, 0, 0], [size, array2.shape[1], array2.shape[2]]);\n      case 4:\n        return slice4d(array2, [start, 0, 0, 0], [size, array2.shape[1], array2.shape[2], array2.shape[3]]);\n      case 5:\n        return slice(array2, [start, 0, 0, 0, 0], [\n          size,\n          array2.shape[1],\n          array2.shape[2],\n          array2.shape[3],\n          array2.shape[4]\n        ]);\n      case 6:\n        return slice(array2, [start, 0, 0, 0, 0, 0], [\n          size,\n          array2.shape[1],\n          array2.shape[2],\n          array2.shape[3],\n          array2.shape[4],\n          array2.shape[5]\n        ]);\n      default:\n        throw new ValueError(`sliceAlongFirstAxis() received an unsupported tensor rank: ${array2.rank}`);\n    }\n  });\n}\nfunction sliceAlongLastAxis(array2, start, size) {\n  return tidy(() => {\n    switch (array2.rank) {\n      case 1:\n        return slice1d(array2, start, size);\n      case 2:\n        return slice2d(array2, [0, start], [array2.shape[0], size]);\n      case 3:\n        return slice3d(array2, [0, 0, start], [array2.shape[0], array2.shape[1], size]);\n      case 4:\n        return slice4d(array2, [0, 0, 0, start], [array2.shape[0], array2.shape[1], array2.shape[2], size]);\n      default:\n        throw new ValueError(`sliceAlongLastAxis() received an unsupported tensor rank: ${array2.rank}`);\n    }\n  });\n}\nfunction sliceAlongAxis(array2, start, size, axis) {\n  return tidy(() => {\n    switch (array2.rank) {\n      case 1:\n        return slice1d(array2, start, size);\n      case 2:\n        switch (axis) {\n          case 1:\n            return sliceAlongFirstAxis(array2, start, size);\n          case 2:\n            return sliceAlongLastAxis(array2, start, size);\n          default:\n            throw new ValueError(`The axis is not within the rank of the tensor ${axis}`);\n        }\n      case 3:\n        switch (axis) {\n          case 1:\n            return sliceAlongFirstAxis(array2, start, size);\n          case 2:\n            return slice3d(array2, [0, start, 0], [array2.shape[0], size, array2.shape[2]]);\n          case 3:\n            return sliceAlongLastAxis(array2, start, size);\n          default:\n            throw new ValueError(`The axis is not within the rank of the tensor ${axis}`);\n        }\n      case 4:\n        switch (axis) {\n          case 1:\n            return sliceAlongFirstAxis(array2, start, size);\n          case 2:\n            return slice4d(array2, [0, start, 0, 0], [array2.shape[0], size, array2.shape[2], array2.shape[3]]);\n          case 3:\n            return slice4d(array2, [0, 0, start, 0], [array2.shape[0], array2.shape[1], size, array2.shape[3]]);\n          case 4:\n            return sliceAlongLastAxis(array2, start, size);\n          default:\n            throw new ValueError(`The axis is not within the rank of the tensor ${axis}`);\n        }\n      default:\n        throw new ValueError(`sliceAlongLastAxis() received an unsupported tensor rank: ${array2.rank}`);\n    }\n  });\n}\nfunction concatenate(tensors, axis = -1) {\n  let rank;\n  if (axis < 0) {\n    rank = tensors[0].rank;\n    if (rank !== 0) {\n      axis = rank;\n    } else {\n      axis = 0;\n    }\n  }\n  if (axis === tensors[0].rank) {\n    axis = -1;\n  }\n  return concat(tensors, axis);\n}\nfunction concatAlongFirstAxis(a, b) {\n  switch (a.rank) {\n    case 1:\n      return concat1d([a, b]);\n    case 2:\n      return concat2d([a, b], 0);\n    case 3:\n      return concat3d([a, b], 0);\n    case 4:\n      return concat4d([a, b], 0);\n    default:\n      throw new ValueError(`concatAlongFirstAxis() received an unsupported tensor rank: ${a.rank}`);\n  }\n}\nfunction tile2(x, n2) {\n  if (!Array.isArray(n2)) {\n    n2 = [n2];\n  }\n  if (x.rank !== n2.length) {\n    throw new ValueError(`The length of input n (${n2.length}) does not match the number of dimensions in input x (${x.rank})`);\n  }\n  return tile(x, n2);\n}\nfunction randomNormal2(shape, mean5 = 0, stddev = 1, dtype, seed) {\n  return randomNormal(shape, mean5, stddev, dtype, seed);\n}\nfunction dot2(a, b, activation2, bias) {\n  if (a.rank < 2 || b.rank < 2) {\n    throw new NotImplementedError(`dot requires both inputs to be rank >= 2 but got x shape = ${a.shape} and y shape = ${b.shape}`);\n  }\n  if (b.rank >= 3) {\n    const xLastDim = a.shape.slice(-1)[0];\n    const ySecondLastDim = b.shape.slice(-2)[0];\n    if (xLastDim !== ySecondLastDim) {\n      throw new NotImplementedError(`If rank y >= 3, then the second last dim of y must equal the last dim of x but got x shape = ${a.shape} and  y shape = ${b.shape}`);\n    }\n  }\n  if (a.rank === 2 && b.rank === 2) {\n    const transposeA = false;\n    const transposeB = false;\n    return fused_ops_exports.matMul({\n      a,\n      b,\n      transposeA,\n      transposeB,\n      bias: bias ? reshapeBias(a.rank, bias, imageDataFormat()) : null,\n      activation: activation2\n    });\n  } else {\n    const aFirstDims = a.shape.slice();\n    const aLastDim = aFirstDims.pop();\n    a = reshape(a, [-1, aLastDim]);\n    const bShape = b.shape.slice();\n    const bLastDim = bShape.pop();\n    const ySecondLastDim = bShape.pop();\n    const yOtherDims = [...bShape, bLastDim];\n    const perm = Array.from({ length: b.rank }, (_, i2) => {\n      if (i2 === 0) {\n        return b.rank - 2;\n      } else if (i2 <= b.rank - 2) {\n        return i2 - 1;\n      }\n      return i2;\n    });\n    b = reshape(transpose(b, perm), [ySecondLastDim, -1]);\n    const outputShape = [...aFirstDims, ...yOtherDims];\n    const transposeA = false;\n    const transposeB = false;\n    return reshape(fused_ops_exports.matMul({\n      a,\n      b,\n      transposeA,\n      transposeB,\n      bias: bias ? reshapeBias(a.rank, bias, imageDataFormat()) : null,\n      activation: activation2\n    }), outputShape);\n  }\n}\nfunction gather2(reference, indices, axis) {\n  return tidy(() => {\n    if (Array.isArray(indices)) {\n      indices = tensor1d(indices, \"int32\");\n    } else {\n      indices = cast(indices, \"int32\");\n    }\n    return gather(reference, indices, axis);\n  });\n}\nfunction square2(x) {\n  return mul(x, x);\n}\nfunction reshapeBias(xRank, bias, dataFormat) {\n  const biasShape = bias.shape;\n  if (bias.rank !== 1 && bias.rank !== xRank) {\n    throw new ValueError(`Unexpected bias dimensions: ${bias.rank}; expected it to be 1 or ${xRank}`);\n  }\n  if (xRank === 5) {\n    if (dataFormat === \"channelsFirst\") {\n      if (biasShape.length === 1) {\n        return reshape(bias, [1, biasShape[0], 1, 1, 1]);\n      } else {\n        return reshape(bias, [1, biasShape[3], biasShape[0], biasShape[1], biasShape[2]]);\n      }\n    } else if (dataFormat === \"channelsLast\") {\n      if (biasShape.length === 1) {\n        return reshape(bias, [1, 1, 1, 1, biasShape[0]]);\n      } else {\n        return reshape(bias, [1].concat(biasShape));\n      }\n    }\n  } else if (xRank === 4) {\n    if (dataFormat === \"channelsFirst\") {\n      if (biasShape.length === 1) {\n        return reshape(bias, [1, biasShape[0], 1, 1]);\n      } else {\n        return reshape(bias, [1, biasShape[2], biasShape[0], biasShape[1]]);\n      }\n    } else if (dataFormat === \"channelsLast\") {\n      if (biasShape.length === 1) {\n        return reshape(bias, [1, 1, 1, biasShape[0]]);\n      } else {\n        return reshape(bias, [1].concat(biasShape));\n      }\n    }\n  } else if (xRank === 3) {\n    if (dataFormat === \"channelsFirst\") {\n      if (biasShape.length === 1) {\n        return reshape(bias, [1, biasShape[0], 1]);\n      } else {\n        return reshape(bias, [1, biasShape[1], biasShape[0]]);\n      }\n    } else if (dataFormat === \"channelsLast\") {\n      if (biasShape.length === 1) {\n        return reshape(bias, [1, 1, biasShape[0]]);\n      } else {\n        return reshape(bias, [1].concat(biasShape));\n      }\n    }\n  } else if (xRank < 3) {\n    return bias;\n  }\n  throw new ValueError(`Unsupported input rank by biasAdd: ${bias.rank}`);\n}\nfunction biasAdd(x, bias, dataFormat) {\n  return tidy(() => {\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    checkDataFormat(dataFormat);\n    return add2(x, reshapeBias(x.rank, bias, dataFormat));\n  });\n}\nfunction elu2(x, alpha = 1) {\n  if (alpha !== 1) {\n    throw new NotImplementedError(`Support for alpha values other than 1 (${alpha}) is not implemented yet.`);\n  }\n  return elu(x);\n}\nfunction softsign(x) {\n  return tidy(() => div(x, add2(abs(x), 1)));\n}\nfunction dropout2(x, level, noiseShape, seed) {\n  return tidy(() => dropout(x, level, noiseShape, seed));\n}\nfunction hardSigmoid(x) {\n  return tidy(() => {\n    const y = add2(0.5, mul(0.2, x));\n    return clipByValue(y, 0, 1);\n  });\n}\nfunction inTrainPhase(x, alt, training = false) {\n  return training ? x() : alt();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/keras_format/initializer_config.js\nvar VALID_FAN_MODE_VALUES = [\"fanIn\", \"fanOut\", \"fanAvg\"];\nvar VALID_DISTRIBUTION_VALUES = [\"normal\", \"uniform\", \"truncatedNormal\"];\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/initializers.js\nfunction checkFanMode(value) {\n  checkStringTypeUnionValue(VALID_FAN_MODE_VALUES, \"FanMode\", value);\n}\nfunction checkDistribution(value) {\n  checkStringTypeUnionValue(VALID_DISTRIBUTION_VALUES, \"Distribution\", value);\n}\nvar Initializer = class extends serialization_exports.Serializable {\n  fromConfigUsesCustomObjects() {\n    return false;\n  }\n  getConfig() {\n    return {};\n  }\n};\nvar Zeros = class extends Initializer {\n  apply(shape, dtype) {\n    return zeros(shape, dtype);\n  }\n};\nZeros.className = \"Zeros\";\nserialization_exports.registerClass(Zeros);\nvar Ones = class extends Initializer {\n  apply(shape, dtype) {\n    return ones2(shape, dtype);\n  }\n};\nOnes.className = \"Ones\";\nserialization_exports.registerClass(Ones);\nvar Constant = class extends Initializer {\n  constructor(args) {\n    super();\n    if (typeof args !== \"object\") {\n      throw new ValueError(`Expected argument of type ConstantConfig but got ${args}`);\n    }\n    if (args.value === void 0) {\n      throw new ValueError(`config must have value set but got ${args}`);\n    }\n    this.value = args.value;\n  }\n  apply(shape, dtype) {\n    return tidy(() => mul(scalar(this.value), ones2(shape, dtype)));\n  }\n  getConfig() {\n    return {\n      value: this.value\n    };\n  }\n};\nConstant.className = \"Constant\";\nserialization_exports.registerClass(Constant);\nvar RandomUniform = class extends Initializer {\n  constructor(args) {\n    super();\n    this.DEFAULT_MINVAL = -0.05;\n    this.DEFAULT_MAXVAL = 0.05;\n    this.minval = args.minval || this.DEFAULT_MINVAL;\n    this.maxval = args.maxval || this.DEFAULT_MAXVAL;\n    this.seed = args.seed;\n  }\n  apply(shape, dtype) {\n    return randomUniform(shape, this.minval, this.maxval, dtype);\n  }\n  getConfig() {\n    return { minval: this.minval, maxval: this.maxval, seed: this.seed };\n  }\n};\nRandomUniform.className = \"RandomUniform\";\nserialization_exports.registerClass(RandomUniform);\nvar RandomNormal = class extends Initializer {\n  constructor(args) {\n    super();\n    this.DEFAULT_MEAN = 0;\n    this.DEFAULT_STDDEV = 0.05;\n    this.mean = args.mean || this.DEFAULT_MEAN;\n    this.stddev = args.stddev || this.DEFAULT_STDDEV;\n    this.seed = args.seed;\n  }\n  apply(shape, dtype) {\n    dtype = dtype || \"float32\";\n    if (dtype !== \"float32\" && dtype !== \"int32\") {\n      throw new NotImplementedError(`randomNormal does not support dType ${dtype}.`);\n    }\n    return randomNormal2(shape, this.mean, this.stddev, dtype, this.seed);\n  }\n  getConfig() {\n    return { mean: this.mean, stddev: this.stddev, seed: this.seed };\n  }\n};\nRandomNormal.className = \"RandomNormal\";\nserialization_exports.registerClass(RandomNormal);\nvar TruncatedNormal = class extends Initializer {\n  constructor(args) {\n    super();\n    this.DEFAULT_MEAN = 0;\n    this.DEFAULT_STDDEV = 0.05;\n    this.mean = args.mean || this.DEFAULT_MEAN;\n    this.stddev = args.stddev || this.DEFAULT_STDDEV;\n    this.seed = args.seed;\n  }\n  apply(shape, dtype) {\n    dtype = dtype || \"float32\";\n    if (dtype !== \"float32\" && dtype !== \"int32\") {\n      throw new NotImplementedError(`truncatedNormal does not support dType ${dtype}.`);\n    }\n    return truncatedNormal(shape, this.mean, this.stddev, dtype, this.seed);\n  }\n  getConfig() {\n    return { mean: this.mean, stddev: this.stddev, seed: this.seed };\n  }\n};\nTruncatedNormal.className = \"TruncatedNormal\";\nserialization_exports.registerClass(TruncatedNormal);\nvar Identity2 = class extends Initializer {\n  constructor(args) {\n    super();\n    this.gain = args.gain != null ? args.gain : 1;\n  }\n  apply(shape, dtype) {\n    return tidy(() => {\n      if (shape.length !== 2 || shape[0] !== shape[1]) {\n        throw new ValueError(\"Identity matrix initializer can only be used for 2D square matrices.\");\n      } else {\n        return mul(this.gain, eye(shape[0]));\n      }\n    });\n  }\n  getConfig() {\n    return { gain: this.gain };\n  }\n};\nIdentity2.className = \"Identity\";\nserialization_exports.registerClass(Identity2);\nfunction computeFans(shape, dataFormat = \"channelsLast\") {\n  let fanIn;\n  let fanOut;\n  checkDataFormat(dataFormat);\n  if (shape.length === 2) {\n    fanIn = shape[0];\n    fanOut = shape[1];\n  } else if ([3, 4, 5].indexOf(shape.length) !== -1) {\n    if (dataFormat === \"channelsFirst\") {\n      const receptiveFieldSize = arrayProd(shape, 2);\n      fanIn = shape[1] * receptiveFieldSize;\n      fanOut = shape[0] * receptiveFieldSize;\n    } else if (dataFormat === \"channelsLast\") {\n      const receptiveFieldSize = arrayProd(shape, 0, shape.length - 2);\n      fanIn = shape[shape.length - 2] * receptiveFieldSize;\n      fanOut = shape[shape.length - 1] * receptiveFieldSize;\n    }\n  } else {\n    const shapeProd = arrayProd(shape);\n    fanIn = Math.sqrt(shapeProd);\n    fanOut = Math.sqrt(shapeProd);\n  }\n  return [fanIn, fanOut];\n}\nvar VarianceScaling = class extends Initializer {\n  constructor(args) {\n    super();\n    if (args.scale < 0) {\n      throw new ValueError(`scale must be a positive float. Got: ${args.scale}`);\n    }\n    this.scale = args.scale == null ? 1 : args.scale;\n    this.mode = args.mode == null ? \"fanIn\" : args.mode;\n    checkFanMode(this.mode);\n    this.distribution = args.distribution == null ? \"normal\" : args.distribution;\n    checkDistribution(this.distribution);\n    this.seed = args.seed;\n  }\n  apply(shape, dtype) {\n    const fans = computeFans(shape);\n    const fanIn = fans[0];\n    const fanOut = fans[1];\n    let scale2 = this.scale;\n    if (this.mode === \"fanIn\") {\n      scale2 /= Math.max(1, fanIn);\n    } else if (this.mode === \"fanOut\") {\n      scale2 /= Math.max(1, fanOut);\n    } else {\n      scale2 /= Math.max(1, (fanIn + fanOut) / 2);\n    }\n    if (this.distribution === \"normal\") {\n      const stddev = Math.sqrt(scale2);\n      dtype = dtype || \"float32\";\n      if (dtype !== \"float32\" && dtype !== \"int32\") {\n        throw new NotImplementedError(`${this.getClassName()} does not support dType ${dtype}.`);\n      }\n      return truncatedNormal(shape, 0, stddev, dtype, this.seed);\n    } else {\n      const limit = Math.sqrt(3 * scale2);\n      return randomUniform(shape, -limit, limit, dtype);\n    }\n  }\n  getConfig() {\n    return {\n      scale: this.scale,\n      mode: this.mode,\n      distribution: this.distribution,\n      seed: this.seed\n    };\n  }\n};\nVarianceScaling.className = \"VarianceScaling\";\nserialization_exports.registerClass(VarianceScaling);\nvar GlorotUniform = class extends VarianceScaling {\n  constructor(args) {\n    super({\n      scale: 1,\n      mode: \"fanAvg\",\n      distribution: \"uniform\",\n      seed: args == null ? null : args.seed\n    });\n  }\n  getClassName() {\n    return VarianceScaling.className;\n  }\n};\nGlorotUniform.className = \"GlorotUniform\";\nserialization_exports.registerClass(GlorotUniform);\nvar GlorotNormal = class extends VarianceScaling {\n  constructor(args) {\n    super({\n      scale: 1,\n      mode: \"fanAvg\",\n      distribution: \"normal\",\n      seed: args == null ? null : args.seed\n    });\n  }\n  getClassName() {\n    return VarianceScaling.className;\n  }\n};\nGlorotNormal.className = \"GlorotNormal\";\nserialization_exports.registerClass(GlorotNormal);\nvar HeNormal = class extends VarianceScaling {\n  constructor(args) {\n    super({\n      scale: 2,\n      mode: \"fanIn\",\n      distribution: \"normal\",\n      seed: args == null ? null : args.seed\n    });\n  }\n  getClassName() {\n    return VarianceScaling.className;\n  }\n};\nHeNormal.className = \"HeNormal\";\nserialization_exports.registerClass(HeNormal);\nvar HeUniform = class extends VarianceScaling {\n  constructor(args) {\n    super({\n      scale: 2,\n      mode: \"fanIn\",\n      distribution: \"uniform\",\n      seed: args == null ? null : args.seed\n    });\n  }\n  getClassName() {\n    return VarianceScaling.className;\n  }\n};\nHeUniform.className = \"HeUniform\";\nserialization_exports.registerClass(HeUniform);\nvar LeCunNormal = class extends VarianceScaling {\n  constructor(args) {\n    super({\n      scale: 1,\n      mode: \"fanIn\",\n      distribution: \"normal\",\n      seed: args == null ? null : args.seed\n    });\n  }\n  getClassName() {\n    return VarianceScaling.className;\n  }\n};\nLeCunNormal.className = \"LeCunNormal\";\nserialization_exports.registerClass(LeCunNormal);\nvar LeCunUniform = class extends VarianceScaling {\n  constructor(args) {\n    super({\n      scale: 1,\n      mode: \"fanIn\",\n      distribution: \"uniform\",\n      seed: args == null ? null : args.seed\n    });\n  }\n  getClassName() {\n    return VarianceScaling.className;\n  }\n};\nLeCunUniform.className = \"LeCunNormal\";\nserialization_exports.registerClass(LeCunUniform);\nvar Orthogonal = class extends Initializer {\n  constructor(args) {\n    super();\n    this.DEFAULT_GAIN = 1;\n    this.gain = args.gain == null ? this.DEFAULT_GAIN : args.gain;\n    this.seed = args.seed;\n    if (this.seed != null) {\n      throw new NotImplementedError(\"Random seed is not implemented for Orthogonal Initializer yet.\");\n    }\n  }\n  apply(shape, dtype) {\n    return tidy(() => {\n      if (shape.length < 2) {\n        throw new NotImplementedError(\"Shape must be at least 2D.\");\n      }\n      if (shape[0] * shape[1] > 2e3) {\n        console.warn(`Orthogonal initializer is being called on a matrix with more than 2000 (${shape[0] * shape[1]}) elements: Slowness may result.`);\n      }\n      const normalizedShape = shape[0] > shape[1] ? [shape[1], shape[0]] : shape;\n      const a = randomNormal2(normalizedShape, 0, 1, \"float32\");\n      let q = linalg.gramSchmidt(a);\n      if (shape[0] > shape[1]) {\n        q = transpose(q);\n      }\n      return mul(this.gain, q);\n    });\n  }\n  getConfig() {\n    return {\n      gain: this.gain,\n      seed: this.seed\n    };\n  }\n};\nOrthogonal.className = \"Orthogonal\";\nserialization_exports.registerClass(Orthogonal);\nvar INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP = {\n  \"constant\": \"Constant\",\n  \"glorotNormal\": \"GlorotNormal\",\n  \"glorotUniform\": \"GlorotUniform\",\n  \"heNormal\": \"HeNormal\",\n  \"heUniform\": \"HeUniform\",\n  \"identity\": \"Identity\",\n  \"leCunNormal\": \"LeCunNormal\",\n  \"leCunUniform\": \"LeCunUniform\",\n  \"ones\": \"Ones\",\n  \"orthogonal\": \"Orthogonal\",\n  \"randomNormal\": \"RandomNormal\",\n  \"randomUniform\": \"RandomUniform\",\n  \"truncatedNormal\": \"TruncatedNormal\",\n  \"varianceScaling\": \"VarianceScaling\",\n  \"zeros\": \"Zeros\"\n};\nfunction deserializeInitializer(config, customObjects = {}) {\n  return deserializeKerasObject(config, serialization_exports.SerializationMap.getMap().classNameMap, customObjects, \"initializer\");\n}\nfunction serializeInitializer(initializer) {\n  return serializeKerasObject(initializer);\n}\nfunction getInitializer(identifier) {\n  if (typeof identifier === \"string\") {\n    const className = identifier in INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP ? INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP[identifier] : identifier;\n    if (className === \"GlorotNormal\") {\n      return new GlorotNormal();\n    } else if (className === \"GlorotUniform\") {\n      return new GlorotUniform();\n    } else if (className === \"HeNormal\") {\n      return new HeNormal();\n    } else if (className === \"HeUniform\") {\n      return new HeUniform();\n    } else if (className === \"LeCunNormal\") {\n      return new LeCunNormal();\n    } else if (className === \"LeCunUniform\") {\n      return new LeCunUniform();\n    } else {\n      const config = {};\n      config[\"className\"] = className;\n      config[\"config\"] = {};\n      return deserializeInitializer(config);\n    }\n  } else if (identifier instanceof Initializer) {\n    return identifier;\n  } else {\n    return deserializeInitializer(identifier);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/types_utils.js\nfunction isArrayOfShapes(x) {\n  return Array.isArray(x) && Array.isArray(x[0]);\n}\nfunction normalizeShapeList(x) {\n  if (x.length === 0) {\n    return [];\n  }\n  if (!Array.isArray(x[0])) {\n    return [x];\n  }\n  return x;\n}\nfunction getExactlyOneTensor(xs) {\n  let x;\n  if (Array.isArray(xs)) {\n    if (xs.length !== 1) {\n      throw new ValueError(`Expected Tensor length to be 1; got ${xs.length}`);\n    }\n    x = xs[0];\n  } else {\n    x = xs;\n  }\n  return x;\n}\nfunction getExactlyOneShape(shapes) {\n  if (Array.isArray(shapes) && Array.isArray(shapes[0])) {\n    if (shapes.length === 1) {\n      shapes = shapes;\n      return shapes[0];\n    } else {\n      throw new ValueError(`Expected exactly 1 Shape; got ${shapes.length}`);\n    }\n  } else {\n    return shapes;\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/variable_utils.js\nfunction countParamsInWeights(weights) {\n  let count2 = 0;\n  for (const weight of weights) {\n    if (weight.shape.length === 0) {\n      count2 += 1;\n    } else {\n      count2 += weight.shape.reduce((a, b) => a * b);\n    }\n  }\n  return count2;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/variables.js\nvar DEFAULT_VARIABLE_NAME_PREFIX = \"Variable\";\nvar LayerVariable = class {\n  constructor(val, dtype = \"float32\", name = DEFAULT_VARIABLE_NAME_PREFIX, trainable = true, constraint = null) {\n    this.dtype = dtype == null ? \"float32\" : dtype;\n    this.shape = val.shape;\n    this.id = getNextUniqueTensorId();\n    name = name == null ? DEFAULT_VARIABLE_NAME_PREFIX : name;\n    this.originalName = getScopedTensorName(name);\n    this.name = getUniqueTensorName(this.originalName);\n    this.trainable_ = trainable;\n    this.constraint = constraint;\n    this.val = variable(val, this.trainable_, this.name, this.dtype);\n  }\n  read() {\n    this.assertNotDisposed();\n    return this.val;\n  }\n  write(newVal) {\n    this.assertNotDisposed();\n    checkShapesMatch(this.val, newVal);\n    if (this.val.id !== newVal.id) {\n      this.val.assign(newVal);\n      if (this.constraint != null) {\n        this.val.assign(this.constraint.apply(this.val));\n      }\n    }\n    return this;\n  }\n  dispose() {\n    this.assertNotDisposed();\n    this.val.dispose();\n  }\n  assertNotDisposed() {\n    if (this.val.isDisposed) {\n      throw new Error(`LayersVariable ${this.name} is already disposed.`);\n    }\n  }\n  get trainable() {\n    return this.trainable_;\n  }\n  set trainable(trainable) {\n    this.trainable_ = trainable;\n    this.val.trainable = trainable;\n  }\n};\nfunction checkShapesMatch(x, y) {\n  if (x.shape.toString() !== y.shape.toString()) {\n    throw new Error(\"Shape mismatch: \" + JSON.stringify(x.shape) + \" vs. \" + JSON.stringify(y.shape));\n  }\n}\nfunction batchGetValue(xs) {\n  return xs.map((x) => x.read());\n}\nfunction batchSetValue(variablesAndValues) {\n  variablesAndValues.forEach((variableAndValue) => {\n    const variable2 = variableAndValue[0];\n    variable2.write(variableAndValue[1]);\n  });\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/topology.js\nvar InputSpec = class {\n  constructor(args) {\n    this.dtype = args.dtype;\n    this.shape = args.shape;\n    if (args.shape != null) {\n      this.ndim = args.shape.length;\n    } else {\n      this.ndim = args.ndim;\n    }\n    this.maxNDim = args.maxNDim;\n    this.minNDim = args.minNDim;\n    this.axes = args.axes || {};\n  }\n};\nvar SymbolicTensor = class {\n  constructor(dtype, shape, sourceLayer, inputs, callArgs, name, outputTensorIndex) {\n    this.dtype = dtype;\n    this.shape = shape;\n    this.sourceLayer = sourceLayer;\n    this.inputs = inputs;\n    this.callArgs = callArgs;\n    this.outputTensorIndex = outputTensorIndex;\n    this.id = getNextUniqueTensorId();\n    if (name != null) {\n      this.originalName = getScopedTensorName(name);\n      this.name = getUniqueTensorName(this.originalName);\n    }\n    this.rank = shape.length;\n  }\n};\nvar _nextNodeID = 0;\nvar Node = class {\n  constructor(args, callArgs) {\n    this.callArgs = callArgs;\n    this.id = _nextNodeID++;\n    this.outboundLayer = args.outboundLayer;\n    this.inboundLayers = args.inboundLayers;\n    this.nodeIndices = args.nodeIndices;\n    this.tensorIndices = args.tensorIndices;\n    this.inputTensors = args.inputTensors;\n    this.outputTensors = args.outputTensors;\n    this.inputMasks = args.inputMasks;\n    this.outputMasks = args.outputMasks;\n    this.inputShapes = args.inputShapes;\n    this.outputShapes = args.outputShapes;\n    for (const layer of args.inboundLayers) {\n      if (layer != null) {\n        layer.outboundNodes.push(this);\n      }\n    }\n    args.outboundLayer.inboundNodes.push(this);\n  }\n  getConfig() {\n    const inboundNames = [];\n    for (const layer of this.inboundLayers) {\n      if (layer != null) {\n        inboundNames.push(layer.name);\n      } else {\n        inboundNames.push(null);\n      }\n    }\n    return {\n      outboundLayer: this.outboundLayer ? this.outboundLayer.name : null,\n      inboundLayers: inboundNames,\n      nodeIndices: this.nodeIndices,\n      tensorIndices: this.tensorIndices\n    };\n  }\n};\nvar _nextLayerID = 0;\nvar Layer = class extends serialization_exports.Serializable {\n  constructor(args = {}) {\n    super();\n    this._callHook = null;\n    this._addedWeightNames = [];\n    this._stateful = false;\n    this.id = _nextLayerID++;\n    this.activityRegularizer = null;\n    this.inputSpec = null;\n    this.supportsMasking = false;\n    this._trainableWeights = [];\n    this._nonTrainableWeights = [];\n    this._losses = [];\n    this._updates = [];\n    this._built = false;\n    this.inboundNodes = [];\n    this.outboundNodes = [];\n    let name = args.name;\n    if (!name) {\n      const prefix = this.getClassName();\n      name = toSnakeCase(prefix) + \"_\" + getUid(prefix);\n    }\n    this.name = name;\n    this.trainable_ = args.trainable == null ? true : args.trainable;\n    if (args.inputShape != null || args.batchInputShape != null) {\n      let batchInputShape;\n      if (args.batchInputShape != null) {\n        batchInputShape = args.batchInputShape;\n      } else if (args.inputShape != null) {\n        let batchSize = null;\n        if (args.batchSize != null) {\n          batchSize = args.batchSize;\n        }\n        batchInputShape = [batchSize].concat(args.inputShape);\n      }\n      this.batchInputShape = batchInputShape;\n      let dtype = args.dtype;\n      if (dtype == null) {\n        dtype = args.inputDType;\n      }\n      if (dtype == null) {\n        dtype = \"float32\";\n      }\n      this.dtype = dtype;\n    }\n    if (args.weights != null) {\n      this.initialWeights = args.weights;\n    } else {\n      this.initialWeights = null;\n    }\n    this._refCount = null;\n    this.fastWeightInitDuringBuild = false;\n  }\n  static nodeKey(layer, nodeIndex) {\n    return layer.name + \"_ib-\" + nodeIndex.toString();\n  }\n  getNodeAtIndex(nodeIndex, attrName) {\n    if (this.inboundNodes.length === 0) {\n      throw new RuntimeError(`The layer has never been called and thus has no defined ${attrName}.`);\n    }\n    if (this.inboundNodes.length <= nodeIndex) {\n      throw new ValueError(`Asked to get ${attrName} at node ${nodeIndex}, but the layer has only ${this.inboundNodes.length} inbound nodes.`);\n    }\n    return this.inboundNodes[nodeIndex];\n  }\n  getInputAt(nodeIndex) {\n    return singletonOrArray(this.getNodeAtIndex(nodeIndex, \"input\").inputTensors);\n  }\n  getOutputAt(nodeIndex) {\n    return singletonOrArray(this.getNodeAtIndex(nodeIndex, \"output\").outputTensors);\n  }\n  get input() {\n    if (this.inboundNodes.length > 1) {\n      throw new AttributeError(`Layer ${this.name} has multiple inbound nodes, hence the notion of \"layer input\" is ill-defined. Use \\`getInputAt(nodeIndex)\\` instead.`);\n    } else if (this.inboundNodes.length === 0) {\n      throw new AttributeError(`Layer ${this.name} is not connected, no input to return.`);\n    }\n    return singletonOrArray(this.getNodeAtIndex(0, \"input\").inputTensors);\n  }\n  get output() {\n    if (this.inboundNodes.length === 0) {\n      throw new AttributeError(`Layer ${this.name} has no inbound nodes.`);\n    }\n    if (this.inboundNodes.length > 1) {\n      throw new AttributeError(`Layer ${this.name} has multiple inbound nodes, hence the notion of \"layer output\" is ill-defined. Use \\`getOutputAt(nodeIndex)\\` instead.`);\n    }\n    return singletonOrArray(this.getNodeAtIndex(0, \"output\").outputTensors);\n  }\n  get losses() {\n    return this._losses;\n  }\n  calculateLosses() {\n    return this.losses.map((lossFn) => lossFn());\n  }\n  get updates() {\n    return this._updates;\n  }\n  get built() {\n    return this._built;\n  }\n  set built(built) {\n    this._built = built;\n  }\n  get trainable() {\n    return this.trainable_;\n  }\n  set trainable(trainable) {\n    this._trainableWeights.forEach((w) => w.trainable = trainable);\n    this.trainable_ = trainable;\n  }\n  get trainableWeights() {\n    if (this.trainable_) {\n      return this._trainableWeights.filter((w) => w.trainable);\n    } else {\n      return [];\n    }\n  }\n  set trainableWeights(weights) {\n    this._trainableWeights = weights;\n  }\n  get nonTrainableWeights() {\n    if (this.trainable) {\n      return this._trainableWeights.filter((w) => !w.trainable).concat(this._nonTrainableWeights);\n    } else {\n      return this._trainableWeights.concat(this._nonTrainableWeights);\n    }\n  }\n  set nonTrainableWeights(weights) {\n    this._nonTrainableWeights = weights;\n  }\n  get weights() {\n    return this.trainableWeights.concat(this.nonTrainableWeights);\n  }\n  get stateful() {\n    return this._stateful;\n  }\n  resetStates() {\n    if (!this.stateful) {\n      throw new Error(\"Cannot call the resetStates() method of a non-stateful Layer object.\");\n    }\n  }\n  assertInputCompatibility(inputs) {\n    inputs = toList(inputs);\n    if (this.inputSpec == null || this.inputSpec.length === 0) {\n      return;\n    }\n    const inputSpec = toList(this.inputSpec);\n    if (inputs.length !== inputSpec.length) {\n      throw new ValueError(`Layer ${this.name} expects ${inputSpec.length} inputs, but it received ${inputs.length} input tensors. Input received: ${inputs}`);\n    }\n    for (let inputIndex = 0; inputIndex < inputs.length; inputIndex++) {\n      const x = inputs[inputIndex];\n      const spec = inputSpec[inputIndex];\n      if (spec == null) {\n        continue;\n      }\n      const ndim = x.rank;\n      if (spec.ndim != null) {\n        if (ndim !== spec.ndim) {\n          throw new ValueError(`Input ${inputIndex} is incompatible with layer ${this.name}: expected ndim=${spec.ndim}, found ndim=${ndim}`);\n        }\n      }\n      if (spec.maxNDim != null) {\n        if (ndim > spec.maxNDim) {\n          throw new ValueError(`Input ${inputIndex} is incompatible with layer ${this.name}: expected max_ndim=${spec.maxNDim}, found ndim=${ndim}`);\n        }\n      }\n      if (spec.minNDim != null) {\n        if (ndim < spec.minNDim) {\n          throw new ValueError(`Input ${inputIndex} is incompatible with layer ${this.name}: expected min_ndim=${spec.minNDim}, found ndim=${ndim}.`);\n        }\n      }\n      if (spec.dtype != null) {\n        if (x.dtype !== spec.dtype) {\n          throw new ValueError(`Input ${inputIndex} is incompatible with layer ${this.name} : expected dtype=${spec.dtype}, found dtype=${x.dtype}.`);\n        }\n      }\n      if (spec.axes) {\n        const xShape = x.shape;\n        for (const key in spec.axes) {\n          const axis = Number(key);\n          const value = spec.axes[key];\n          const xShapeAtAxis = axis >= 0 ? xShape[axis] : xShape[xShape.length + axis];\n          if (value != null && [value, null].indexOf(xShapeAtAxis) === -1) {\n            throw new ValueError(`Input ${inputIndex} is incompatible with layer ${this.name}: expected axis ${axis} of input shape to have value ${value} but got shape ${xShape}.`);\n          }\n        }\n      }\n      if (spec.shape != null) {\n        for (let i2 = 0; i2 < spec.shape.length; ++i2) {\n          const specDim = spec.shape[i2];\n          const dim = x.shape[i2];\n          if (specDim != null && dim != null) {\n            if (specDim !== dim) {\n              throw new ValueError(`Input ${inputIndex} is incompatible with layer ${this.name}: expected shape=${spec.shape}, found shape=${x.shape}.`);\n            }\n          }\n        }\n      }\n    }\n  }\n  call(inputs, kwargs) {\n    return inputs;\n  }\n  invokeCallHook(inputs, kwargs) {\n    if (this._callHook != null) {\n      this._callHook(inputs, kwargs);\n    }\n  }\n  setCallHook(callHook) {\n    this._callHook = callHook;\n  }\n  clearCallHook() {\n    this._callHook = null;\n  }\n  apply(inputs, kwargs) {\n    kwargs = kwargs || {};\n    this.assertNotDisposed();\n    const inputsList = toList(inputs);\n    let allAreSymbolic = true;\n    for (const input2 of inputsList) {\n      if (!(input2 instanceof SymbolicTensor)) {\n        allAreSymbolic = false;\n        break;\n      }\n    }\n    let noneAreSymbolic = true;\n    for (const input2 of inputsList) {\n      if (input2 instanceof SymbolicTensor) {\n        noneAreSymbolic = false;\n        break;\n      }\n    }\n    if (allAreSymbolic === noneAreSymbolic) {\n      throw new ValueError(\"Arguments to apply() must be all SymbolicTensors or all Tensors\");\n    }\n    return nameScope(this.name, () => {\n      if (!this.built) {\n        this.assertInputCompatibility(inputs);\n        const inputShapes = [];\n        for (const xElem of toList(inputs)) {\n          inputShapes.push(xElem.shape);\n        }\n        this.build(singletonOrArray(inputShapes));\n        this.built = true;\n        if (this.initialWeights) {\n          this.setWeights(this.initialWeights);\n        }\n        if (this._refCount === null && noneAreSymbolic) {\n          this._refCount = 1;\n        }\n      }\n      this.assertInputCompatibility(inputs);\n      if (noneAreSymbolic) {\n        let output = this.call(inputs, kwargs);\n        const outputList = toList(output);\n        const outputListCopy = [];\n        for (let x of outputList) {\n          if (inputsList.indexOf(x) !== -1) {\n            x = x.clone();\n          }\n          outputListCopy.push(x);\n        }\n        output = singletonOrArray(outputListCopy);\n        if (this.activityRegularizer != null) {\n          throw new NotImplementedError(\"Layer invocation in the presence of activity regularizer(s) is not supported yet.\");\n        }\n        return output;\n      } else {\n        const inputShape = collectInputShape(inputs);\n        const outputShape = this.computeOutputShape(inputShape);\n        let output;\n        const outputDType = guessOutputDType(inputs);\n        this.warnOnIncompatibleInputShape(Array.isArray(inputs) ? inputShape[0] : inputShape);\n        if (outputShape != null && outputShape.length > 0 && Array.isArray(outputShape[0])) {\n          output = outputShape.map((shape, index) => new SymbolicTensor(outputDType, shape, this, toList(inputs), kwargs, this.name, index));\n        } else {\n          output = new SymbolicTensor(outputDType, outputShape, this, toList(inputs), kwargs, this.name);\n        }\n        this.addInboundNode(inputs, output, null, null, inputShape, outputShape, kwargs);\n        this._refCount++;\n        if (this.activityRegularizer != null) {\n          throw new NotImplementedError(\"Layer invocation in the presence of activity regularizer(s) is not supported yet.\");\n        }\n        return output;\n      }\n    });\n  }\n  warnOnIncompatibleInputShape(inputShape) {\n    if (this.batchInputShape == null) {\n      return;\n    } else if (inputShape.length !== this.batchInputShape.length) {\n      console.warn(`The rank of the input tensor provided (shape: ${JSON.stringify(inputShape)}) does not match that of the batchInputShape (${JSON.stringify(this.batchInputShape)}) of the layer ${this.name}`);\n    } else {\n      let dimMismatch = false;\n      this.batchInputShape.forEach((dimension, i2) => {\n        if (dimension != null && inputShape[i2] != null && inputShape[i2] !== dimension) {\n          dimMismatch = true;\n        }\n      });\n      if (dimMismatch) {\n        console.warn(`The shape of the input tensor (${JSON.stringify(inputShape)}) does not match the expectation of layer ${this.name}: ${JSON.stringify(this.batchInputShape)}`);\n      }\n    }\n  }\n  get outputShape() {\n    if (this.inboundNodes == null || this.inboundNodes.length === 0) {\n      throw new AttributeError(`The layer ${this.name} has never been called and thus has no defined output shape.`);\n    }\n    const allOutputShapes = [];\n    for (const node of this.inboundNodes) {\n      const shapeString = JSON.stringify(node.outputShapes);\n      if (allOutputShapes.indexOf(shapeString) === -1) {\n        allOutputShapes.push(shapeString);\n      }\n    }\n    if (allOutputShapes.length === 1) {\n      const outputShapes = this.inboundNodes[0].outputShapes;\n      if (Array.isArray(outputShapes) && Array.isArray(outputShapes[0]) && outputShapes.length === 1) {\n        return outputShapes[0];\n      } else {\n        return outputShapes;\n      }\n    } else {\n      throw new AttributeError(`The layer ${this.name} has multiple inbound nodes with different output shapes. Hence the notion of \"output shape\" is ill-defined for the layer.`);\n    }\n  }\n  countParams() {\n    if (!this.built) {\n      throw new RuntimeError(`You tried to call countParams() on ${this.name}, but the layer is not built yet. Build it first by calling build(batchInputShape).`);\n    }\n    return countParamsInWeights(this.weights);\n  }\n  build(inputShape) {\n    this.built = true;\n  }\n  getWeights(trainableOnly = false) {\n    return batchGetValue(trainableOnly ? this.trainableWeights : this.weights);\n  }\n  setWeights(weights) {\n    tidy(() => {\n      const params = this.weights;\n      if (params.length !== weights.length) {\n        throw new ValueError(`You called setWeights(weights) on layer \"${this.name}\" with a weight list of length ${weights.length}, but the layer was expecting ${params.length} weights. Provided weights: ${weights}...`);\n      }\n      if (params.length === 0) {\n        return;\n      }\n      const weightValueTuples = [];\n      const paramValues = batchGetValue(params);\n      for (let i2 = 0; i2 < paramValues.length; ++i2) {\n        const pv = paramValues[i2];\n        const p2 = params[i2];\n        const w = weights[i2];\n        if (!util_exports.arraysEqual(pv.shape, w.shape)) {\n          throw new ValueError(`Layer weight shape ${pv.shape} not compatible with provided weight shape ${w.shape}`);\n        }\n        weightValueTuples.push([p2, w]);\n      }\n      batchSetValue(weightValueTuples);\n    });\n  }\n  addWeight(name, shape, dtype, initializer, regularizer, trainable, constraint, getInitializerFunc) {\n    if (this._addedWeightNames.indexOf(name) !== -1) {\n      throw new ValueError(`Duplicate weight name ${name} for layer ${this.name}`);\n    }\n    this._addedWeightNames.push(name);\n    if (dtype == null) {\n      dtype = \"float32\";\n    }\n    if (this.fastWeightInitDuringBuild) {\n      initializer = getInitializerFunc != null ? getInitializerFunc() : getInitializer(\"zeros\");\n    }\n    const initValue = initializer.apply(shape, dtype);\n    const weight = new LayerVariable(initValue, dtype, name, trainable, constraint);\n    initValue.dispose();\n    if (regularizer != null) {\n      this.addLoss(() => regularizer.apply(weight.read()));\n    }\n    if (trainable == null) {\n      trainable = true;\n    }\n    if (trainable) {\n      this._trainableWeights.push(weight);\n    } else {\n      this._nonTrainableWeights.push(weight);\n    }\n    return weight;\n  }\n  setFastWeightInitDuringBuild(value) {\n    this.fastWeightInitDuringBuild = value;\n  }\n  addLoss(losses2) {\n    if (losses2 == null || Array.isArray(losses2) && losses2.length === 0) {\n      return;\n    }\n    losses2 = toList(losses2);\n    if (this._losses !== void 0 && this._losses !== null) {\n      this.losses.push(...losses2);\n    }\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  computeMask(inputs, mask) {\n    if (!this.supportsMasking) {\n      if (mask != null) {\n        if (Array.isArray(mask)) {\n          mask.forEach((maskElement) => {\n            if (maskElement != null) {\n              throw new TypeError(`Layer ${this.name} does not support masking, but was passed an inputMask.`);\n            }\n          });\n        } else {\n          throw new TypeError(`Layer ${this.name} does not support masking, but was passed an inputMask.`);\n        }\n      }\n      return null;\n    }\n    return mask;\n  }\n  addInboundNode(inputTensors, outputTensors, inputMasks, outputMasks, inputShapes, outputShapes, kwargs = null) {\n    const inputTensorList = toList(inputTensors);\n    outputTensors = toList(outputTensors);\n    inputMasks = toList(inputMasks);\n    outputMasks = toList(outputMasks);\n    inputShapes = normalizeShapeList(inputShapes);\n    outputShapes = normalizeShapeList(outputShapes);\n    const inboundLayers = [];\n    const nodeIndices = [];\n    const tensorIndices = [];\n    for (const x of inputTensorList) {\n      inboundLayers.push(x.sourceLayer);\n      nodeIndices.push(x.nodeIndex);\n      tensorIndices.push(x.tensorIndex);\n    }\n    new Node({\n      outboundLayer: this,\n      inboundLayers,\n      nodeIndices,\n      tensorIndices,\n      inputTensors: inputTensorList,\n      outputTensors,\n      inputMasks,\n      outputMasks,\n      inputShapes,\n      outputShapes\n    }, kwargs);\n    for (let i2 = 0; i2 < outputTensors.length; i2++) {\n      outputTensors[i2].sourceLayer = this;\n      outputTensors[i2].nodeIndex = this.inboundNodes.length - 1;\n      outputTensors[i2].tensorIndex = i2;\n    }\n  }\n  getConfig() {\n    const config = { name: this.name, trainable: this.trainable };\n    if (this.batchInputShape != null) {\n      config[\"batchInputShape\"] = this.batchInputShape;\n    }\n    if (this.dtype != null) {\n      config[\"dtype\"] = this.dtype;\n    }\n    return config;\n  }\n  disposeWeights() {\n    this.weights.forEach((weight) => weight.dispose());\n    return this.weights.length;\n  }\n  assertNotDisposed() {\n    if (this._refCount === 0) {\n      throw new Error(`Layer '${this.name}' is already disposed.`);\n    }\n  }\n  dispose() {\n    if (!this.built) {\n      throw new Error(`Cannot dispose Layer ${this.name} because it has not been built yet.`);\n    }\n    if (this._refCount === null) {\n      throw new Error(`Cannot dispose Layer ${this.name} because it has not been used yet.`);\n    }\n    this.assertNotDisposed();\n    let numDisposedVariables = 0;\n    if (--this._refCount === 0) {\n      numDisposedVariables = this.disposeWeights();\n    }\n    return { refCountAfterDispose: this._refCount, numDisposedVariables };\n  }\n};\nfunction collectInputShape(inputTensors) {\n  inputTensors = toList(inputTensors);\n  const shapes = [];\n  for (const x of inputTensors) {\n    shapes.push(x.shape);\n  }\n  return singletonOrArray(shapes);\n}\nfunction guessOutputDType(inputTensors) {\n  return \"float32\";\n}\nfunction getSourceInputs(tensor2, layer, nodeIndex) {\n  if (layer == null || nodeIndex != null && nodeIndex > 0) {\n    layer = tensor2.sourceLayer;\n    nodeIndex = tensor2.nodeIndex;\n  }\n  if (layer.inboundNodes.length === 0) {\n    return [tensor2];\n  } else {\n    const node = layer.inboundNodes[nodeIndex];\n    if (node.inboundLayers.length === 0) {\n      return node.inputTensors;\n    } else {\n      const sourceTensors = [];\n      for (let i2 = 0; i2 < node.inboundLayers.length; i2++) {\n        const x = node.inputTensors[i2];\n        const layer2 = node.inboundLayers[i2];\n        const nodeIndex2 = node.nodeIndices[i2];\n        const previousSources = getSourceInputs(x, layer2, nodeIndex2);\n        for (const x2 of previousSources) {\n          if (sourceTensors.indexOf(x2) === -1) {\n            sourceTensors.push(x2);\n          }\n        }\n      }\n      return sourceTensors;\n    }\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/input_layer.js\nvar InputLayer = class extends Layer {\n  constructor(args) {\n    super({\n      dtype: args.dtype,\n      name: args.name != null ? args.name : getUid(\"input\").toString()\n    });\n    if (args.batchSize == null) {\n      args.batchSize = null;\n    }\n    if (args.sparse == null) {\n      args.sparse = false;\n    }\n    this.trainable = false;\n    this.built = true;\n    this.sparse = args.sparse;\n    if (args.inputShape != null && args.batchInputShape != null) {\n      throw new ValueError(\"Only provide the inputShape OR batchInputShape argument to inputLayer, not both at the same time.\");\n    }\n    let batchInputShape = args.batchInputShape;\n    if (batchInputShape == null) {\n      if (args.inputShape == null) {\n        throw new ValueError(\"An InputLayer should be passed either a `batchInputShape` or an `inputShape`.\");\n      } else {\n        batchInputShape = [args.batchSize].concat(args.inputShape);\n      }\n    } else {\n      if (args.batchSize != null) {\n        throw new ValueError(\"Cannot specify batchSize if batchInputShape is specified when creating an InputLayer.\");\n      }\n    }\n    const dtype = args.dtype || \"float32\";\n    this.batchInputShape = batchInputShape;\n    this.dtype = dtype;\n    this.inputSpec = [{ shape: batchInputShape }];\n    const inputTensor = new SymbolicTensor(this.dtype, this.batchInputShape, this, [], {}, this.name);\n    inputTensor.nodeIndex = 0;\n    inputTensor.tensorIndex = 0;\n    new Node({\n      outboundLayer: this,\n      inboundLayers: [],\n      nodeIndices: [],\n      tensorIndices: [],\n      inputTensors: [inputTensor],\n      outputTensors: [inputTensor],\n      inputMasks: [null],\n      outputMasks: [null],\n      inputShapes: [batchInputShape],\n      outputShapes: [batchInputShape]\n    });\n  }\n  apply(inputs, kwargs) {\n    throw new ValueError(`Cannot pass any input to an InputLayer's apply() method. InputLayer name: ${this.name}`);\n  }\n  dispose() {\n    return { refCountAfterDispose: this._refCount, numDisposedVariables: 0 };\n  }\n  getConfig() {\n    return {\n      batchInputShape: this.batchInputShape,\n      dtype: this.dtype,\n      sparse: this.sparse,\n      name: this.name\n    };\n  }\n};\nInputLayer.className = \"InputLayer\";\nserialization_exports.registerClass(InputLayer);\nfunction Input(config) {\n  if (config.batchShape == null && config.shape == null) {\n    throw new Error(\"Please provide to Input either a `shape` or a `batchShape` argument. Note that `shape` does not include the batch dimension.\");\n  }\n  if (config.batchShape != null && config.shape != null) {\n    throw new ValueError(\"Please provide either a `shape` or `batchShape` argument to Input, but not both.\");\n  }\n  let batchShape = config.batchShape;\n  if (config.shape != null && batchShape == null) {\n    batchShape = [null].concat(config.shape);\n  }\n  let dtype = config.dtype;\n  if (dtype == null) {\n    dtype = \"float32\";\n  }\n  const inputLayer2 = new InputLayer({\n    batchInputShape: batchShape,\n    name: config.name,\n    dtype,\n    sparse: config.sparse\n  });\n  const outputs = inputLayer2.inboundNodes[0].outputTensors;\n  return outputs[0];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/executor.js\nfunction assertFeedCompatibility(key, val) {\n  if (key.dtype == null || key.dtype === val.dtype) {\n    return val;\n  }\n  try {\n    return cast(val, key.dtype);\n  } catch (err) {\n    throw new ValueError(`The dtype of the feed (${val.dtype}) can not be cast to the dtype of the key '${key.name}' (${key.dtype}).`);\n  }\n}\nvar FeedDict = class {\n  constructor(feeds) {\n    this.id2Value = {};\n    this.id2Mask = {};\n    this.name2Id = {};\n    if (feeds instanceof FeedDict) {\n      for (const id in feeds.id2Value) {\n        this.id2Value[id] = feeds.id2Value[id];\n        if (id in feeds.id2Mask) {\n          this.id2Mask[id] = feeds.id2Mask[id];\n        }\n      }\n    } else {\n      if (feeds == null) {\n        return;\n      }\n      for (const feed of feeds) {\n        this.add(feed.key, feed.value);\n      }\n    }\n  }\n  add(key, value, mask) {\n    if (this.id2Value[key.id] == null) {\n      this.id2Value[key.id] = assertFeedCompatibility(key, value);\n      this.name2Id[key.name] = key.id;\n      if (mask != null) {\n        this.id2Mask[key.id] = mask;\n      }\n    } else {\n      throw new ValueError(`Duplicate key: name=${key.name}, id=${key.id}`);\n    }\n    return this;\n  }\n  addFeed(feed) {\n    this.add(feed.key, feed.value);\n  }\n  hasKey(key) {\n    return this.id2Value[key.id] != null;\n  }\n  names() {\n    return Object.keys(this.name2Id);\n  }\n  getValue(key) {\n    if (key instanceof SymbolicTensor) {\n      if (this.id2Value[key.id] == null) {\n        throw new ValueError(`Nonexistent key: ${key.name}`);\n      } else {\n        return this.id2Value[key.id];\n      }\n    } else {\n      const id = this.name2Id[key];\n      if (id == null) {\n        throw new ValueError(`Feed dict has no SymbolicTensor name: ${key}`);\n      }\n      return this.id2Value[id];\n    }\n  }\n  getMask(key) {\n    if (key instanceof SymbolicTensor) {\n      if (this.id2Value[key.id] == null) {\n        throw new ValueError(`Nonexistent key: ${key.name}`);\n      } else {\n        return this.id2Mask[key.id];\n      }\n    } else {\n      const id = this.name2Id[key];\n      if (id == null) {\n        throw new ValueError(`Feed dict has no SymbolicTensor name: ${key}`);\n      }\n      return this.id2Mask[id];\n    }\n  }\n  disposeMasks() {\n    if (this.id2Mask != null) {\n      dispose(this.id2Mask);\n    }\n  }\n};\nvar cachedSorted = new LruCache();\nvar cachedRecipientCounts = new LruCache();\nfunction updateCacheMaxEntries(maxEntries) {\n  if (cachedSorted != null) {\n    cachedSorted.setMaxEntries(maxEntries);\n  }\n  if (cachedRecipientCounts != null) {\n    cachedRecipientCounts.setMaxEntries(maxEntries);\n  }\n}\nfunction execute(fetches, feedDict, kwargs, probe) {\n  const training = kwargs == null ? false : kwargs[\"training\"];\n  const arrayFetches = Array.isArray(fetches);\n  const fetchArray = arrayFetches ? fetches : [fetches];\n  const outputNames = fetchArray.map((t2) => t2.name);\n  const finalOutputs = [];\n  const feedNames = feedDict.names();\n  for (const outputName of outputNames) {\n    if (feedNames.indexOf(outputName) !== -1) {\n      finalOutputs.push(feedDict.getValue(outputName));\n    } else {\n      finalOutputs.push(null);\n    }\n  }\n  if (probe != null) {\n    probe.maxNumTensors = -Infinity;\n    probe.minNumTensors = Infinity;\n  }\n  const fetchAndFeedKey = outputNames.join(\",\") + \"|\" + feedDict.names().sort().join(\",\");\n  let sorted = cachedSorted.get(fetchAndFeedKey);\n  let recipientCounts;\n  if (sorted == null) {\n    const out = getTopologicalSortAndRecipientCounts(fetchArray, feedDict);\n    sorted = out.sorted;\n    recipientCounts = out.recipientCounts;\n    cachedSorted.put(fetchAndFeedKey, sorted);\n    cachedRecipientCounts.put(fetchAndFeedKey, recipientCounts);\n  }\n  recipientCounts = {};\n  if (!training) {\n    Object.assign(recipientCounts, cachedRecipientCounts.get(fetchAndFeedKey));\n  }\n  const internalFeedDict = new FeedDict(feedDict);\n  for (let i2 = 0; i2 < sorted.length; ++i2) {\n    if (probe != null) {\n      const numTensors = memory().numTensors;\n      if (numTensors > probe.maxNumTensors) {\n        probe.maxNumTensors = numTensors;\n      }\n      if (numTensors < probe.minNumTensors) {\n        probe.minNumTensors = numTensors;\n      }\n    }\n    const symbolic = sorted[i2];\n    const srcLayer = symbolic.sourceLayer;\n    if (srcLayer instanceof InputLayer) {\n      continue;\n    }\n    const inputValues = [];\n    const inputMasks = [];\n    const tensorsToDispose = [];\n    let maskExists = false;\n    for (const input2 of symbolic.inputs) {\n      const value = internalFeedDict.getValue(input2);\n      const mask = internalFeedDict.getMask(input2);\n      inputValues.push(value);\n      inputMasks.push(mask);\n      if (mask != null) {\n        maskExists = true;\n      }\n      if (!training) {\n        recipientCounts[input2.name]--;\n        if (recipientCounts[input2.name] === 0 && !feedDict.hasKey(input2) && outputNames.indexOf(input2.name) === -1 && !value.isDisposed && input2.sourceLayer.stateful !== true) {\n          tensorsToDispose.push(value);\n        }\n      }\n    }\n    if (maskExists) {\n      kwargs = kwargs || {};\n      kwargs[\"mask\"] = inputMasks[0];\n    }\n    const outputTensors = toList(srcLayer.apply(inputValues, kwargs));\n    let outputMask = null;\n    if (srcLayer.supportsMasking) {\n      outputMask = srcLayer.computeMask(inputValues, inputMasks);\n    }\n    const layerOutputs = getNodeOutputs(symbolic);\n    const outputSymbolicTensors = Array.isArray(layerOutputs) ? layerOutputs : [layerOutputs];\n    for (let i3 = 0; i3 < outputSymbolicTensors.length; ++i3) {\n      if (!internalFeedDict.hasKey(outputSymbolicTensors[i3])) {\n        internalFeedDict.add(outputSymbolicTensors[i3], outputTensors[i3], Array.isArray(outputMask) ? outputMask[0] : outputMask);\n      }\n      const index = outputNames.indexOf(outputSymbolicTensors[i3].name);\n      if (index !== -1) {\n        finalOutputs[index] = outputTensors[i3];\n      }\n    }\n    if (!training) {\n      dispose(tensorsToDispose);\n    }\n  }\n  internalFeedDict.disposeMasks();\n  return arrayFetches ? finalOutputs : finalOutputs[0];\n}\nfunction getTopologicalSortAndRecipientCounts(fetches, feedDict) {\n  util_exports.assert(fetches != null && fetches.length > 0, () => `Expected at least one fetch, got none`);\n  let finalSorted = [];\n  let finalRecipientMap = {};\n  if (fetches.length === 1) {\n    const out = getTopologicalSortAndRecipientCountsForOneFetch(fetches[0], feedDict);\n    finalSorted = out.sorted;\n    finalRecipientMap = out.recipientMap;\n  } else {\n    const visited = /* @__PURE__ */ new Set();\n    for (const fetch4 of fetches) {\n      const { sorted, recipientMap } = getTopologicalSortAndRecipientCountsForOneFetch(fetch4, feedDict);\n      for (const symbolicTensor of sorted) {\n        if (!visited.has(symbolicTensor.name)) {\n          finalSorted.push(symbolicTensor);\n          visited.add(symbolicTensor.name);\n        }\n      }\n      for (const name in recipientMap) {\n        if (finalRecipientMap[name] == null) {\n          finalRecipientMap[name] = /* @__PURE__ */ new Set();\n        }\n        recipientMap[name].forEach((recipient) => finalRecipientMap[name].add(recipient));\n      }\n    }\n  }\n  return {\n    sorted: finalSorted,\n    recipientCounts: recipientMap2Counts(finalRecipientMap)\n  };\n}\nfunction recipientMap2Counts(recipientMap) {\n  const recipientCounts = {};\n  for (const name in recipientMap) {\n    recipientCounts[name] = recipientMap[name].size;\n  }\n  return recipientCounts;\n}\nfunction getTopologicalSortAndRecipientCountsForOneFetch(fetch4, feedDict) {\n  const visited = /* @__PURE__ */ new Set();\n  const sorted = [];\n  const recipientMap = {};\n  for (const key of feedDict.names()) {\n    visited.add(key);\n  }\n  const stack2 = [];\n  const marks = [];\n  stack2.push(fetch4);\n  while (stack2.length > 0) {\n    const top = stack2[stack2.length - 1];\n    if (visited.has(top.name)) {\n      stack2.pop();\n      continue;\n    }\n    const topIsMarked = marks[marks.length - 1] === stack2.length - 1;\n    if (top.inputs.length === 0 || topIsMarked) {\n      stack2.pop();\n      sorted.push(top);\n      visited.add(top.name);\n      if (topIsMarked) {\n        marks.pop();\n      }\n    } else {\n      marks.push(stack2.length - 1);\n      for (const input2 of top.inputs) {\n        if (recipientMap[input2.name] == null) {\n          recipientMap[input2.name] = /* @__PURE__ */ new Set();\n        }\n        recipientMap[input2.name].add(top.name);\n        if (visited.has(input2.name)) {\n          continue;\n        }\n        stack2.push(input2);\n      }\n    }\n  }\n  return { sorted, recipientMap };\n}\nfunction getNodeOutputs(fetch4) {\n  let layerOutputs;\n  if (fetch4.sourceLayer.inboundNodes.length === 1) {\n    layerOutputs = fetch4.sourceLayer.output;\n  } else {\n    let nodeIndex = null;\n    for (let i2 = 0; i2 < fetch4.sourceLayer.inboundNodes.length; ++i2) {\n      for (const outputTensor of fetch4.sourceLayer.inboundNodes[i2].outputTensors) {\n        if (outputTensor.id === fetch4.id) {\n          nodeIndex = i2;\n          break;\n        }\n      }\n    }\n    layerOutputs = fetch4.sourceLayer.getOutputAt(nodeIndex);\n  }\n  return layerOutputs;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/flags_layers.js\nvar ENV3 = env();\nENV3.registerFlag(\"TOPOLOGICAL_SORT_CACHE_MAX_ENTRIES\", () => 100, updateCacheMaxEntries);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_constraints.js\nvar exports_constraints_exports = {};\n__export(exports_constraints_exports, {\n  maxNorm: () => maxNorm,\n  minMaxNorm: () => minMaxNorm,\n  nonNeg: () => nonNeg,\n  unitNorm: () => unitNorm\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/constraints.js\nfunction calcL2Norms(w, axis) {\n  return tidy(() => sqrt(sum2(mul(w, w), axis, true)));\n}\nvar Constraint = class extends serialization_exports.Serializable {\n  getConfig() {\n    return {};\n  }\n};\nvar MaxNorm = class extends Constraint {\n  constructor(args) {\n    super();\n    this.defaultMaxValue = 2;\n    this.defaultAxis = 0;\n    this.maxValue = args.maxValue != null ? args.maxValue : this.defaultMaxValue;\n    this.axis = args.axis != null ? args.axis : this.defaultAxis;\n  }\n  apply(w) {\n    return tidy(() => {\n      const norms = calcL2Norms(w, this.axis);\n      const desired = clipByValue(norms, 0, this.maxValue);\n      return mul(w, div(desired, add2(epsilon(), norms)));\n    });\n  }\n  getConfig() {\n    return { maxValue: this.maxValue, axis: this.axis };\n  }\n};\nMaxNorm.className = \"MaxNorm\";\nserialization_exports.registerClass(MaxNorm);\nvar UnitNorm = class extends Constraint {\n  constructor(args) {\n    super();\n    this.defaultAxis = 0;\n    this.axis = args.axis != null ? args.axis : this.defaultAxis;\n  }\n  apply(w) {\n    return tidy(() => div(w, add2(epsilon(), calcL2Norms(w, this.axis))));\n  }\n  getConfig() {\n    return { axis: this.axis };\n  }\n};\nUnitNorm.className = \"UnitNorm\";\nserialization_exports.registerClass(UnitNorm);\nvar NonNeg = class extends Constraint {\n  apply(w) {\n    return relu(w);\n  }\n};\nNonNeg.className = \"NonNeg\";\nserialization_exports.registerClass(NonNeg);\nvar MinMaxNorm = class extends Constraint {\n  constructor(args) {\n    super();\n    this.defaultMinValue = 0;\n    this.defaultMaxValue = 1;\n    this.defaultRate = 1;\n    this.defaultAxis = 0;\n    this.minValue = args.minValue != null ? args.minValue : this.defaultMinValue;\n    this.maxValue = args.maxValue != null ? args.maxValue : this.defaultMaxValue;\n    this.rate = args.rate != null ? args.rate : this.defaultRate;\n    this.axis = args.axis != null ? args.axis : this.defaultAxis;\n  }\n  apply(w) {\n    return tidy(() => {\n      const norms = calcL2Norms(w, this.axis);\n      const desired = add2(mul(this.rate, clipByValue(norms, this.minValue, this.maxValue)), mul(1 - this.rate, norms));\n      return mul(w, div(desired, add2(epsilon(), norms)));\n    });\n  }\n  getConfig() {\n    return {\n      minValue: this.minValue,\n      maxValue: this.maxValue,\n      rate: this.rate,\n      axis: this.axis\n    };\n  }\n};\nMinMaxNorm.className = \"MinMaxNorm\";\nserialization_exports.registerClass(MinMaxNorm);\nvar CONSTRAINT_IDENTIFIER_REGISTRY_SYMBOL_MAP = {\n  \"maxNorm\": \"MaxNorm\",\n  \"minMaxNorm\": \"MinMaxNorm\",\n  \"nonNeg\": \"NonNeg\",\n  \"unitNorm\": \"UnitNorm\"\n};\nfunction serializeConstraint(constraint) {\n  return serializeKerasObject(constraint);\n}\nfunction deserializeConstraint(config, customObjects = {}) {\n  return deserializeKerasObject(config, serialization_exports.SerializationMap.getMap().classNameMap, customObjects, \"constraint\");\n}\nfunction getConstraint(identifier) {\n  if (identifier == null) {\n    return null;\n  }\n  if (typeof identifier === \"string\") {\n    const className = identifier in CONSTRAINT_IDENTIFIER_REGISTRY_SYMBOL_MAP ? CONSTRAINT_IDENTIFIER_REGISTRY_SYMBOL_MAP[identifier] : identifier;\n    const config = { className, config: {} };\n    return deserializeConstraint(config);\n  } else if (identifier instanceof Constraint) {\n    return identifier;\n  } else {\n    return deserializeConstraint(identifier);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_constraints.js\nfunction maxNorm(args) {\n  return new MaxNorm(args);\n}\nfunction unitNorm(args) {\n  return new UnitNorm(args);\n}\nfunction nonNeg() {\n  return new NonNeg();\n}\nfunction minMaxNorm(config) {\n  return new MinMaxNorm(config);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_initializers.js\nvar exports_initializers_exports = {};\n__export(exports_initializers_exports, {\n  constant: () => constant,\n  glorotNormal: () => glorotNormal,\n  glorotUniform: () => glorotUniform,\n  heNormal: () => heNormal,\n  heUniform: () => heUniform,\n  identity: () => identity,\n  leCunNormal: () => leCunNormal,\n  leCunUniform: () => leCunUniform,\n  ones: () => ones3,\n  orthogonal: () => orthogonal,\n  randomNormal: () => randomNormal3,\n  randomUniform: () => randomUniform2,\n  truncatedNormal: () => truncatedNormal2,\n  varianceScaling: () => varianceScaling,\n  zeros: () => zeros2\n});\nfunction zeros2() {\n  return new Zeros();\n}\nfunction ones3() {\n  return new Ones();\n}\nfunction constant(args) {\n  return new Constant(args);\n}\nfunction randomUniform2(args) {\n  return new RandomUniform(args);\n}\nfunction randomNormal3(args) {\n  return new RandomNormal(args);\n}\nfunction truncatedNormal2(args) {\n  return new TruncatedNormal(args);\n}\nfunction identity(args) {\n  return new Identity2(args);\n}\nfunction varianceScaling(config) {\n  return new VarianceScaling(config);\n}\nfunction glorotUniform(args) {\n  return new GlorotUniform(args);\n}\nfunction glorotNormal(args) {\n  return new GlorotNormal(args);\n}\nfunction heNormal(args) {\n  return new HeNormal(args);\n}\nfunction heUniform(args) {\n  return new HeUniform(args);\n}\nfunction leCunNormal(args) {\n  return new LeCunNormal(args);\n}\nfunction leCunUniform(args) {\n  return new LeCunUniform(args);\n}\nfunction orthogonal(args) {\n  return new Orthogonal(args);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_layers.js\nvar exports_layers_exports = {};\n__export(exports_layers_exports, {\n  Layer: () => Layer,\n  RNN: () => RNN,\n  RNNCell: () => RNNCell,\n  activation: () => activation,\n  add: () => add3,\n  alphaDropout: () => alphaDropout,\n  average: () => average,\n  averagePooling1d: () => averagePooling1d,\n  averagePooling2d: () => averagePooling2d,\n  averagePooling3d: () => averagePooling3d,\n  avgPool1d: () => avgPool1d,\n  avgPool2d: () => avgPool2d,\n  avgPool3d: () => avgPool3d2,\n  avgPooling1d: () => avgPooling1d,\n  avgPooling2d: () => avgPooling2d,\n  avgPooling3d: () => avgPooling3d,\n  batchNormalization: () => batchNormalization2,\n  bidirectional: () => bidirectional,\n  concatenate: () => concatenate2,\n  conv1d: () => conv1d2,\n  conv2d: () => conv2d3,\n  conv2dTranspose: () => conv2dTranspose2,\n  conv3d: () => conv3d2,\n  conv3dTranspose: () => conv3dTranspose2,\n  convLstm2d: () => convLstm2d,\n  convLstm2dCell: () => convLstm2dCell,\n  cropping2D: () => cropping2D,\n  dense: () => dense,\n  depthwiseConv2d: () => depthwiseConv2d4,\n  dot: () => dot3,\n  dropout: () => dropout3,\n  elu: () => elu3,\n  embedding: () => embedding,\n  flatten: () => flatten3,\n  gaussianDropout: () => gaussianDropout,\n  gaussianNoise: () => gaussianNoise,\n  globalAveragePooling1d: () => globalAveragePooling1d,\n  globalAveragePooling2d: () => globalAveragePooling2d,\n  globalMaxPool1d: () => globalMaxPool1d,\n  globalMaxPool2d: () => globalMaxPool2d,\n  globalMaxPooling1d: () => globalMaxPooling1d,\n  globalMaxPooling2d: () => globalMaxPooling2d,\n  gru: () => gru,\n  gruCell: () => gruCell,\n  input: () => input,\n  inputLayer: () => inputLayer,\n  layerNormalization: () => layerNormalization,\n  leakyReLU: () => leakyReLU,\n  lstm: () => lstm,\n  lstmCell: () => lstmCell,\n  masking: () => masking,\n  maxPool1d: () => maxPool1d,\n  maxPool2d: () => maxPool2d,\n  maxPooling1d: () => maxPooling1d,\n  maxPooling2d: () => maxPooling2d,\n  maxPooling3d: () => maxPooling3d,\n  maximum: () => maximum2,\n  minimum: () => minimum2,\n  multiply: () => multiply,\n  permute: () => permute,\n  prelu: () => prelu2,\n  reLU: () => reLU,\n  repeatVector: () => repeatVector,\n  reshape: () => reshape2,\n  rnn: () => rnn2,\n  separableConv2d: () => separableConv2d2,\n  simpleRNN: () => simpleRNN,\n  simpleRNNCell: () => simpleRNNCell,\n  softmax: () => softmax2,\n  spatialDropout1d: () => spatialDropout1d,\n  stackedRNNCells: () => stackedRNNCells,\n  thresholdedReLU: () => thresholdedReLU,\n  timeDistributed: () => timeDistributed,\n  upSampling2d: () => upSampling2d,\n  zeroPadding2d: () => zeroPadding2d\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/logs.js\nasync function resolveScalarsInLogs(logs) {\n  if (logs == null) {\n    return;\n  }\n  const promises = [];\n  const keys = [];\n  const scalarsToDispose = [];\n  for (const key in logs) {\n    const value = logs[key];\n    if (typeof value !== \"number\") {\n      const valueScalar = value;\n      promises.push(valueScalar.data());\n      keys.push(key);\n      scalarsToDispose.push(valueScalar);\n    }\n  }\n  if (promises.length > 0) {\n    const values = await Promise.all(promises);\n    for (let i2 = 0; i2 < values.length; ++i2) {\n      logs[keys[i2]] = values[i2][0];\n    }\n    dispose(scalarsToDispose);\n  }\n}\nfunction disposeTensorsInLogs(logs) {\n  if (logs == null) {\n    return;\n  }\n  for (const key in logs) {\n    const value = logs[key];\n    if (typeof value !== \"number\") {\n      value.dispose();\n    }\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/base_callbacks.js\nvar ModelLoggingVerbosity;\n(function(ModelLoggingVerbosity2) {\n  ModelLoggingVerbosity2[ModelLoggingVerbosity2[\"SILENT\"] = 0] = \"SILENT\";\n  ModelLoggingVerbosity2[ModelLoggingVerbosity2[\"VERBOSE\"] = 1] = \"VERBOSE\";\n})(ModelLoggingVerbosity || (ModelLoggingVerbosity = {}));\nvar DEFAULT_YIELD_EVERY_MS = 125;\nvar BaseCallback = class {\n  constructor() {\n    this.validationData = null;\n  }\n  setParams(params) {\n    this.params = params;\n  }\n  async onEpochBegin(epoch, logs) {\n  }\n  async onEpochEnd(epoch, logs) {\n  }\n  async onBatchBegin(batch, logs) {\n  }\n  async onBatchEnd(batch, logs) {\n  }\n  async onTrainBegin(logs) {\n  }\n  async onTrainEnd(logs) {\n  }\n  setModel(model2) {\n  }\n};\nvar CallbackList = class {\n  constructor(callbacks2, queueLength = 10) {\n    if (callbacks2 == null) {\n      callbacks2 = [];\n    }\n    this.callbacks = callbacks2;\n    this.queueLength = queueLength;\n  }\n  append(callback) {\n    this.callbacks.push(callback);\n  }\n  setParams(params) {\n    for (const callback of this.callbacks) {\n      callback.setParams(params);\n    }\n  }\n  setModel(model2) {\n    for (const callback of this.callbacks) {\n      callback.setModel(model2);\n    }\n  }\n  async onEpochBegin(epoch, logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    for (const callback of this.callbacks) {\n      await callback.onEpochBegin(epoch, logs);\n    }\n  }\n  async onEpochEnd(epoch, logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    for (const callback of this.callbacks) {\n      await callback.onEpochEnd(epoch, logs);\n    }\n  }\n  async onBatchBegin(batch, logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    for (const callback of this.callbacks) {\n      await callback.onBatchBegin(batch, logs);\n    }\n  }\n  async onBatchEnd(batch, logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    for (const callback of this.callbacks) {\n      await callback.onBatchEnd(batch, logs);\n    }\n  }\n  async onTrainBegin(logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    for (const callback of this.callbacks) {\n      await callback.onTrainBegin(logs);\n    }\n  }\n  async onTrainEnd(logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    for (const callback of this.callbacks) {\n      await callback.onTrainEnd(logs);\n    }\n  }\n};\nvar BaseLogger = class extends BaseCallback {\n  constructor() {\n    super();\n  }\n  async onEpochBegin(epoch) {\n    this.seen = 0;\n    this.totals = {};\n  }\n  async onBatchEnd(batch, logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    const batchSize = logs[\"size\"] == null ? 0 : logs[\"size\"];\n    this.seen += batchSize;\n    for (const key in logs) {\n      const value = logs[key];\n      if (typeof value === \"number\") {\n        if (!this.totals.hasOwnProperty(key)) {\n          this.totals[key] = 0;\n        }\n        this.totals[key] = this.totals[key] + value * batchSize;\n      } else {\n        let oldTotalsToDispose;\n        if (key in this.totals) {\n          oldTotalsToDispose = this.totals[key];\n        } else {\n          this.totals[key] = 0;\n        }\n        const total = tidy(() => add2(this.totals[key], mul(value, batchSize)));\n        this.totals[key] = total;\n        if (oldTotalsToDispose != null) {\n          oldTotalsToDispose.dispose();\n        }\n      }\n    }\n  }\n  async onEpochEnd(epoch, logs) {\n    if (logs != null) {\n      for (const key of this.params[\"metrics\"]) {\n        if (this.totals[key] == null) {\n          continue;\n        }\n        if (typeof this.totals[key] === \"number\") {\n          logs[key] = this.totals[key] / this.seen;\n        } else {\n          tidy(() => {\n            const log6 = mul(div(1, this.seen), this.totals[key]);\n            logs[key] = log6;\n            this.totals[key].dispose();\n            keep(logs[key]);\n          });\n        }\n      }\n    }\n  }\n};\nvar History = class extends BaseCallback {\n  async onTrainBegin(logs) {\n    this.epoch = [];\n    this.history = {};\n  }\n  async onEpochEnd(epoch, logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    this.epoch.push(epoch);\n    for (const key in logs) {\n      if (this.history[key] == null) {\n        this.history[key] = [];\n      }\n      this.history[key].push(logs[key]);\n    }\n  }\n  async syncData() {\n    const promises = [];\n    const keys = [];\n    const indices = [];\n    for (const key in this.history) {\n      const valueArray = this.history[key];\n      for (let i2 = 0; i2 < valueArray.length; ++i2) {\n        if (typeof valueArray[i2] !== \"number\") {\n          const valueScalar = valueArray[i2];\n          promises.push(valueScalar.data());\n          keys.push(key);\n          indices.push(i2);\n        }\n      }\n    }\n    const values = await Promise.all(promises);\n    for (let n2 = 0; n2 < values.length; ++n2) {\n      const tensorToDispose = this.history[keys[n2]][indices[n2]];\n      tensorToDispose.dispose();\n      this.history[keys[n2]][indices[n2]] = values[n2][0];\n    }\n  }\n};\nvar CustomCallback = class extends BaseCallback {\n  constructor(args, yieldEvery) {\n    super();\n    this.currentEpoch = 0;\n    this.nowFunc = args.nowFunc;\n    this.nextFrameFunc = args.nextFrameFunc || nextFrame;\n    this.yieldEvery = yieldEvery || \"auto\";\n    if (this.yieldEvery === \"auto\") {\n      this.yieldEvery = DEFAULT_YIELD_EVERY_MS;\n    }\n    if (this.yieldEvery === \"never\" && args.onYield != null) {\n      throw new Error(\"yieldEvery is `never` but you provided an `onYield` callback. Either change `yieldEvery` or remove the callback\");\n    }\n    if (util_exports.isNumber(this.yieldEvery)) {\n      this.maybeWait = debounce(this.maybeWait.bind(this), this.yieldEvery, this.nowFunc);\n    }\n    this.trainBegin = args.onTrainBegin;\n    this.trainEnd = args.onTrainEnd;\n    this.epochBegin = args.onEpochBegin;\n    this.epochEnd = args.onEpochEnd;\n    this.batchBegin = args.onBatchBegin;\n    this.batchEnd = args.onBatchEnd;\n    this.yield = args.onYield;\n  }\n  async maybeWait(epoch, batch, logs) {\n    const ps = [];\n    if (this.yield != null) {\n      await resolveScalarsInLogs(logs);\n      ps.push(this.yield(epoch, batch, logs));\n    }\n    ps.push(this.nextFrameFunc());\n    await Promise.all(ps);\n  }\n  async onEpochBegin(epoch, logs) {\n    this.currentEpoch = epoch;\n    if (this.epochBegin != null) {\n      await resolveScalarsInLogs(logs);\n      await this.epochBegin(epoch, logs);\n    }\n  }\n  async onEpochEnd(epoch, logs) {\n    const ps = [];\n    if (this.epochEnd != null) {\n      await resolveScalarsInLogs(logs);\n      ps.push(this.epochEnd(epoch, logs));\n    }\n    if (this.yieldEvery === \"epoch\") {\n      ps.push(this.nextFrameFunc());\n    }\n    await Promise.all(ps);\n  }\n  async onBatchBegin(batch, logs) {\n    if (this.batchBegin != null) {\n      await resolveScalarsInLogs(logs);\n      await this.batchBegin(batch, logs);\n    }\n  }\n  async onBatchEnd(batch, logs) {\n    const ps = [];\n    if (this.batchEnd != null) {\n      await resolveScalarsInLogs(logs);\n      ps.push(this.batchEnd(batch, logs));\n    }\n    if (this.yieldEvery === \"batch\") {\n      ps.push(this.nextFrameFunc());\n    } else if (util_exports.isNumber(this.yieldEvery)) {\n      ps.push(this.maybeWait(this.currentEpoch, batch, logs));\n    }\n    await Promise.all(ps);\n  }\n  async onTrainBegin(logs) {\n    if (this.trainBegin != null) {\n      await resolveScalarsInLogs(logs);\n      await this.trainBegin(logs);\n    }\n  }\n  async onTrainEnd(logs) {\n    if (this.trainEnd != null) {\n      await resolveScalarsInLogs(logs);\n      await this.trainEnd(logs);\n    }\n  }\n};\nfunction standardizeCallbacks(callbacks2, yieldEvery) {\n  if (callbacks2 == null) {\n    callbacks2 = {};\n  }\n  if (callbacks2 instanceof BaseCallback) {\n    return [callbacks2];\n  }\n  if (Array.isArray(callbacks2) && callbacks2[0] instanceof BaseCallback) {\n    return callbacks2;\n  }\n  const callbackConfigs = toList(callbacks2);\n  return callbackConfigs.map((callbackConfig) => new CustomCallback(callbackConfig, yieldEvery));\n}\nvar CallbackConstructorRegistry = class {\n  constructor() {\n  }\n  static registerCallbackConstructor(verbosityLevel, callbackConstructor) {\n    util_exports.assert(verbosityLevel >= 0 && Number.isInteger(verbosityLevel), () => `Verbosity level is expected to be an integer >= 0, but got ${verbosityLevel}`);\n    CallbackConstructorRegistry.checkForDuplicate(callbackConstructor);\n    if (CallbackConstructorRegistry.constructors[verbosityLevel] == null) {\n      CallbackConstructorRegistry.constructors[verbosityLevel] = [];\n    }\n    CallbackConstructorRegistry.constructors[verbosityLevel].push(callbackConstructor);\n  }\n  static checkForDuplicate(callbackConstructor) {\n    for (const levelName in CallbackConstructorRegistry.constructors) {\n      const constructors = CallbackConstructorRegistry.constructors[+levelName];\n      constructors.forEach((ctor) => {\n        if (ctor === callbackConstructor) {\n          throw new ValueError(\"Duplicate callback constructor.\");\n        }\n      });\n    }\n  }\n  static clear() {\n    CallbackConstructorRegistry.constructors = {};\n  }\n  static createCallbacks(verbosityLevel) {\n    const constructors = [];\n    for (const levelName in CallbackConstructorRegistry.constructors) {\n      const level = +levelName;\n      if (verbosityLevel >= level) {\n        constructors.push(...CallbackConstructorRegistry.constructors[level]);\n      }\n    }\n    return constructors.map((ctor) => new ctor());\n  }\n};\nCallbackConstructorRegistry.constructors = {};\nfunction configureCallbacks(callbacks2, verbose, epochs, initialEpoch, numTrainSamples, stepsPerEpoch, batchSize, doValidation, callbackMetrics) {\n  const history = new History();\n  const actualCallbacks = [\n    new BaseLogger(),\n    ...CallbackConstructorRegistry.createCallbacks(verbose)\n  ];\n  if (callbacks2 != null) {\n    actualCallbacks.push(...callbacks2);\n  }\n  actualCallbacks.push(history);\n  const callbackList = new CallbackList(actualCallbacks);\n  callbackList.setParams({\n    epochs,\n    initialEpoch,\n    samples: numTrainSamples,\n    steps: stepsPerEpoch,\n    batchSize,\n    verbose,\n    doValidation,\n    metrics: callbackMetrics\n  });\n  return { callbackList, history };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/serialization.js\nfunction deserialize(config, customObjects = {}, fastWeightInit = false) {\n  return deserializeKerasObject(config, serialization_exports.SerializationMap.getMap().classNameMap, customObjects, \"layer\", fastWeightInit);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/losses.js\nfunction l2Normalize(x, axis) {\n  return tidy(() => {\n    if (x.dtype !== \"float32\") {\n      x = cast(x, \"float32\");\n    }\n    const squareSum = sum2(square2(x), axis, true);\n    const epsilonTensor = fill(squareSum.shape, epsilon());\n    const norm2 = sqrt(maximum(squareSum, epsilonTensor));\n    return div(x, norm2);\n  });\n}\nfunction meanSquaredError2(yTrue, yPred) {\n  return tidy(() => mean(square2(sub(yPred, yTrue)), -1));\n}\nfunction meanAbsoluteError(yTrue, yPred) {\n  return tidy(() => mean(abs(sub(yPred, yTrue)), -1));\n}\nfunction meanAbsolutePercentageError(yTrue, yPred) {\n  return tidy(() => {\n    const diff = sub(yTrue, yPred);\n    const clippedTrue = clipByValue(abs(yTrue), epsilon(), Number.MAX_VALUE);\n    const absResult = abs(div(diff, clippedTrue));\n    return mul(100, mean(absResult, -1));\n  });\n}\nfunction meanSquaredLogarithmicError(yTrue, yPred) {\n  return tidy(() => {\n    const clippedPred = clipByValue(yPred, epsilon(), Number.MAX_VALUE);\n    const firstLog = log2(add2(1, clippedPred));\n    const clippedTrue = clipByValue(yTrue, epsilon(), Number.MAX_VALUE);\n    const secondLog = log2(add2(1, clippedTrue));\n    return mean(square2(sub(firstLog, secondLog)), -1);\n  });\n}\nfunction squaredHinge(yTrue, yPred) {\n  return tidy(() => {\n    const maxResult = maximum(0, sub(1, mul(yTrue, yPred)));\n    return mean(square2(maxResult), -1);\n  });\n}\nfunction hinge(yTrue, yPred) {\n  return tidy(() => {\n    const maxResult = maximum(0, sub(1, mul(yTrue, yPred)));\n    return mean(maxResult, -1);\n  });\n}\nfunction categoricalHinge(yTrue, yPred) {\n  return tidy(() => {\n    const pos = sum2(mul(yTrue, yPred), -1);\n    const neg5 = max(mul(sub(1, yTrue), yPred), -1);\n    return maximum(0, add2(1, sub(neg5, pos)));\n  });\n}\nfunction logcosh(yTrue, yPred) {\n  return tidy(() => {\n    const log22 = Math.log(2);\n    const predictionDiff = sub(yPred, yTrue);\n    const logcoshResult = sub(add2(predictionDiff, softplus(mul(-2, predictionDiff))), log22);\n    return mean(logcoshResult, -1);\n  });\n}\nfunction categoricalCrossentropy(target, output, fromLogits = false) {\n  return tidy(() => {\n    if (fromLogits) {\n      output = softmax(output);\n    } else {\n      const outputSum = sum2(output, output.shape.length - 1, true);\n      output = div(output, outputSum);\n    }\n    output = clipByValue(output, epsilon(), 1 - epsilon());\n    return neg(sum2(mul(cast(target, \"float32\"), log2(output)), output.shape.length - 1));\n  });\n}\nfunction sparseCategoricalCrossentropy(target, output, fromLogits = false) {\n  return tidy(() => {\n    const flatTarget = cast(floor(flatten2(target)), \"int32\");\n    output = clipByValue(output, epsilon(), 1 - epsilon());\n    const outputShape = output.shape;\n    const oneHotTarget = reshape(oneHot(flatTarget, outputShape[outputShape.length - 1]), outputShape);\n    return categoricalCrossentropy(oneHotTarget, output, fromLogits);\n  });\n}\nfunction sigmoidCrossEntropyWithLogits(labels, logits) {\n  if (!util_exports.arraysEqual(labels.shape, logits.shape)) {\n    throw new ValueError(`logits and labels must have the same shape, but got shapes ${JSON.stringify(labels.shape)} and ${JSON.stringify(logits.shape)}`);\n  }\n  return tidy(() => {\n    const reluLogits = relu(logits);\n    const negAbsLogits = neg(abs(logits));\n    return add2(sub(reluLogits, mul(logits, labels)), log1p(exp(negAbsLogits)));\n  });\n}\nfunction binaryCrossentropy(yTrue, yPred) {\n  return tidy(() => {\n    let y;\n    y = clipByValue(yPred, epsilon(), 1 - epsilon());\n    y = log2(div(y, sub(1, y)));\n    return mean(sigmoidCrossEntropyWithLogits(yTrue, y), -1);\n  });\n}\nfunction kullbackLeiblerDivergence(yTrue, yPred) {\n  return tidy(() => {\n    const clippedTrue = clipByValue(yTrue, epsilon(), 1);\n    const clippedPred = clipByValue(yPred, epsilon(), 1);\n    return sum2(mul(yTrue, log2(div(clippedTrue, clippedPred))), -1);\n  });\n}\nfunction poisson(yTrue, yPred) {\n  return tidy(() => {\n    const logPred = log2(add2(epsilon(), yPred));\n    return mean(sub(yPred, mul(yTrue, logPred)), -1);\n  });\n}\nfunction cosineProximity(yTrue, yPred) {\n  return tidy(() => {\n    const trueNormalized = l2Normalize(yTrue, -1);\n    const predNormalized = l2Normalize(yPred, -1);\n    const trueXPred = mul(trueNormalized, predNormalized);\n    return neg(sum2(trueXPred, -1));\n  });\n}\nvar lossesMap = {\n  meanSquaredError: meanSquaredError2,\n  meanAbsoluteError,\n  meanAbsolutePercentageError,\n  meanSquaredLogarithmicError,\n  squaredHinge,\n  hinge,\n  categoricalHinge,\n  logcosh,\n  categoricalCrossentropy,\n  sparseCategoricalCrossentropy,\n  binaryCrossentropy,\n  kullbackLeiblerDivergence,\n  poisson,\n  cosineProximity\n};\nfunction get(identifierOrFn) {\n  if (typeof identifierOrFn === \"string\") {\n    if (identifierOrFn in lossesMap) {\n      return lossesMap[identifierOrFn];\n    }\n    let errMsg = `Unknown loss ${identifierOrFn}`;\n    if (identifierOrFn.toLowerCase().includes(\"softmaxcrossentropy\")) {\n      errMsg = `Unknown loss ${identifierOrFn}. Use \"categoricalCrossentropy\" as the string name for tf.losses.softmaxCrossEntropy`;\n    }\n    throw new ValueError(errMsg);\n  } else {\n    return identifierOrFn;\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/metrics.js\nfunction binaryAccuracy(yTrue, yPred) {\n  return tidy(() => {\n    const threshold3 = mul(0.5, onesLike(yPred));\n    const yPredThresholded = cast2(greater(yPred, threshold3), yTrue.dtype);\n    return mean(equal(yTrue, yPredThresholded), -1);\n  });\n}\nfunction categoricalAccuracy(yTrue, yPred) {\n  return tidy(() => cast2(equal(argMax(yTrue, -1), argMax(yPred, -1)), \"float32\"));\n}\nfunction truePositives(yTrue, yPred) {\n  return tidy(() => {\n    return cast(sum2(logicalAnd(equal(yTrue, 1), equal(yPred, 1))), \"float32\");\n  });\n}\nfunction falseNegatives(yTrue, yPred) {\n  return tidy(() => {\n    return cast(sum2(logicalAnd(equal(yTrue, 1), equal(yPred, 0))), \"float32\");\n  });\n}\nfunction falsePositives(yTrue, yPred) {\n  return tidy(() => {\n    return cast(sum2(logicalAnd(equal(yTrue, 0), equal(yPred, 1))), \"float32\");\n  });\n}\nfunction precision(yTrue, yPred) {\n  return tidy(() => {\n    const tp = truePositives(yTrue, yPred);\n    const fp = falsePositives(yTrue, yPred);\n    const denominator = add2(tp, fp);\n    return cast(where(greater(denominator, 0), div(tp, denominator), 0), \"float32\");\n  });\n}\nfunction recall(yTrue, yPred) {\n  return tidy(() => {\n    const tp = truePositives(yTrue, yPred);\n    const fn = falseNegatives(yTrue, yPred);\n    const denominator = add2(tp, fn);\n    return cast(where(greater(denominator, 0), div(tp, denominator), 0), \"float32\");\n  });\n}\nfunction binaryCrossentropy2(yTrue, yPred) {\n  return binaryCrossentropy(yTrue, yPred);\n}\nfunction sparseCategoricalAccuracy(yTrue, yPred) {\n  if (yTrue.rank === yPred.rank) {\n    yTrue = squeeze(yTrue, [yTrue.rank - 1]);\n  }\n  yPred = argMax(yPred, -1);\n  if (yPred.dtype !== yTrue.dtype) {\n    yPred = cast(yPred, yTrue.dtype);\n  }\n  return cast(equal(yTrue, yPred), \"float32\");\n}\nvar mse = meanSquaredError2;\nvar MSE = meanSquaredError2;\nvar mae = meanAbsoluteError;\nvar MAE = meanAbsoluteError;\nvar mape = meanAbsolutePercentageError;\nvar MAPE = meanAbsolutePercentageError;\nvar categoricalCrossentropy2 = categoricalCrossentropy;\nvar cosine = cosineProximity;\nvar sparseCategoricalCrossentropy2 = sparseCategoricalCrossentropy;\nvar metricsMap = {\n  binaryAccuracy,\n  categoricalAccuracy,\n  precision,\n  categoricalCrossentropy: categoricalCrossentropy2,\n  sparseCategoricalCrossentropy: sparseCategoricalCrossentropy2,\n  mse,\n  MSE,\n  mae,\n  MAE,\n  mape,\n  MAPE,\n  cosine\n};\nfunction get2(identifier) {\n  if (typeof identifier === \"string\" && identifier in metricsMap) {\n    return metricsMap[identifier];\n  } else if (typeof identifier !== \"string\" && identifier != null) {\n    return identifier;\n  } else {\n    throw new ValueError(`Unknown metric ${identifier}`);\n  }\n}\nfunction getLossOrMetricName(fn) {\n  assert2(fn !== null, `Unknown LossOrMetricFn ${fn}`);\n  if (typeof fn === \"string\") {\n    return fn;\n  } else {\n    let fnName;\n    for (const key of Object.keys(lossesMap)) {\n      if (lossesMap[key] === fn) {\n        fnName = key;\n        break;\n      }\n    }\n    if (fnName !== void 0) {\n      return fnName;\n    }\n    for (const key of Object.keys(metricsMap)) {\n      if (metricsMap[key] === fn) {\n        fnName = key;\n        break;\n      }\n    }\n    if (fnName !== void 0) {\n      return fnName;\n    }\n    return fn.name;\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/optimizers.js\nfunction getOptimizer(identifier) {\n  const optimizerMap = {\n    \"Adagrad\": () => train.adagrad(0.01),\n    \"Adadelta\": () => train.adadelta(1, 0.95, epsilon()),\n    \"Adam\": () => train.adam(1e-3, 0.9, 0.999, epsilon()),\n    \"Adamax\": () => train.adamax(2e-3, 0.9, 0.999, epsilon(), 0),\n    \"RMSProp\": () => train.rmsprop(1e-3, 0.9, 0, epsilon()),\n    \"SGD\": () => train.sgd(0.01)\n  };\n  optimizerMap[\"adagrad\"] = optimizerMap[\"Adagrad\"];\n  optimizerMap[\"adadelta\"] = optimizerMap[\"Adadelta\"];\n  optimizerMap[\"adam\"] = optimizerMap[\"Adam\"];\n  optimizerMap[\"adamax\"] = optimizerMap[\"Adamax\"];\n  optimizerMap[\"rmsprop\"] = optimizerMap[\"RMSProp\"];\n  optimizerMap[\"sgd\"] = optimizerMap[\"SGD\"];\n  if (identifier in optimizerMap) {\n    return optimizerMap[identifier]();\n  }\n  throw new ValueError(`Unknown Optimizer ${identifier}`);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/user_defined_metadata.js\nvar MAX_USER_DEFINED_METADATA_SERIALIZED_LENGTH = 1 * 1024 * 1024;\nfunction checkUserDefinedMetadata(userDefinedMetadata, modelName, checkSize = false) {\n  if (userDefinedMetadata == null || typeof userDefinedMetadata !== \"object\" || Object.getPrototypeOf(userDefinedMetadata) !== Object.prototype || !plainObjectCheck(userDefinedMetadata)) {\n    throw new Error(\"User-defined metadata is expected to be a JSON object, but is not.\");\n  }\n  if (checkSize) {\n    const out = JSON.stringify(userDefinedMetadata);\n    if (out.length > MAX_USER_DEFINED_METADATA_SERIALIZED_LENGTH) {\n      console.warn(`User-defined metadata of model \"${modelName}\" is too large in size (length=${out.length} when serialized). It is not recommended to store such large objects in user-defined metadata. Please make sure its serialized length is <= ${MAX_USER_DEFINED_METADATA_SERIALIZED_LENGTH}.`);\n    }\n  }\n}\nfunction plainObjectCheck(x) {\n  if (x === null) {\n    return true;\n  } else if (typeof x === \"object\") {\n    if (Object.getPrototypeOf(x) === Object.prototype) {\n      const keys = Object.keys(x);\n      for (const key of keys) {\n        if (typeof key !== \"string\") {\n          return false;\n        }\n        if (!plainObjectCheck(x[key])) {\n          return false;\n        }\n      }\n      return true;\n    } else {\n      if (Array.isArray(x)) {\n        for (const item of x) {\n          if (!plainObjectCheck(item)) {\n            return false;\n          }\n        }\n        return true;\n      } else {\n        return false;\n      }\n    }\n  } else {\n    const xType = typeof x;\n    return xType === \"string\" || xType === \"number\" || xType === \"boolean\";\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/layer_utils.js\nfunction printSummary(model2, lineLength, positions, printFn = console.log) {\n  const sequentialLike = isModelSequentialLike(model2);\n  const toDisplay = [\"Layer (type)\", \"Input Shape\", \"Output shape\", \"Param #\"];\n  if (sequentialLike) {\n    lineLength = lineLength || 90;\n    positions = positions || [0.32, 0.61, 0.89, 1];\n  } else {\n    lineLength = lineLength || 115;\n    positions = positions || [0.24, 0.48, 0.7, 0.8, 1];\n  }\n  if (positions[positions.length - 1] <= 1) {\n    positions = positions.map((p2) => Math.floor(lineLength * p2));\n  }\n  let relevantNodes;\n  if (!sequentialLike) {\n    toDisplay.push(\"Receives inputs\");\n    relevantNodes = [];\n    for (const depth in model2.nodesByDepth) {\n      relevantNodes.push(...model2.nodesByDepth[depth]);\n    }\n  }\n  printFn(\"_\".repeat(lineLength));\n  printRow(toDisplay, positions, printFn);\n  printFn(\"=\".repeat(lineLength));\n  const layers = model2.layers;\n  for (let i2 = 0; i2 < layers.length; ++i2) {\n    if (sequentialLike) {\n      printLayerSummary(layers[i2], positions, printFn);\n    } else {\n      printLayerSummaryWithConnections(layers[i2], positions, relevantNodes, printFn);\n    }\n    printFn((i2 === layers.length - 1 ? \"=\" : \"_\").repeat(lineLength));\n  }\n  model2.checkTrainableWeightsConsistency();\n  const trainableCount = countTrainableParams(model2);\n  const nonTrainableCount = countParamsInWeights(model2.nonTrainableWeights);\n  printFn(`Total params: ${trainableCount + nonTrainableCount}`);\n  printFn(`Trainable params: ${trainableCount}`);\n  printFn(`Non-trainable params: ${nonTrainableCount}`);\n  printFn(\"_\".repeat(lineLength));\n}\nfunction countTrainableParams(model2) {\n  let trainableCount;\n  if (model2.collectedTrainableWeights != null) {\n    trainableCount = countParamsInWeights(model2.collectedTrainableWeights);\n  } else {\n    trainableCount = countParamsInWeights(model2.trainableWeights);\n  }\n  return trainableCount;\n}\nfunction isModelSequentialLike(model2) {\n  let sequentialLike = true;\n  const nodesByDepth = [];\n  const nodes = [];\n  for (const depth in model2.nodesByDepth) {\n    nodesByDepth.push(model2.nodesByDepth[depth]);\n  }\n  for (const depthNodes of nodesByDepth) {\n    if (depthNodes.length > 1 || depthNodes.length === 1 && depthNodes[0].inboundLayers.length > 1) {\n      sequentialLike = false;\n      break;\n    }\n    nodes.push(...depthNodes);\n  }\n  if (sequentialLike) {\n    for (const layer of model2.layers) {\n      let flag = false;\n      for (const node of layer.inboundNodes) {\n        if (nodes.indexOf(node) !== -1) {\n          if (flag) {\n            sequentialLike = false;\n            break;\n          } else {\n            flag = true;\n          }\n        }\n      }\n      if (!sequentialLike) {\n        break;\n      }\n    }\n  }\n  return sequentialLike;\n}\nfunction printRow(fields, positions, printFn = console.log) {\n  let line = \"\";\n  for (let i2 = 0; i2 < fields.length; ++i2) {\n    if (i2 > 0) {\n      line = line.slice(0, line.length - 1) + \" \";\n    }\n    line += fields[i2];\n    line = line.slice(0, positions[i2]);\n    line += \" \".repeat(positions[i2] - line.length);\n  }\n  printFn(line);\n}\nfunction printLayerSummary(layer, positions, printFn) {\n  let outputShape;\n  let inputShape;\n  try {\n    inputShape = layer.inboundNodes.map((x) => JSON.stringify(x.inputShapes)).join(\",\");\n  } catch (err) {\n    inputShape = \"multiple\";\n  }\n  try {\n    outputShape = JSON.stringify(layer.outputShape);\n  } catch (err) {\n    outputShape = \"multiple\";\n  }\n  const name = layer.name;\n  const className = layer.getClassName();\n  const fields = [\n    `${name} (${className})`,\n    inputShape,\n    outputShape,\n    layer.countParams().toString()\n  ];\n  printRow(fields, positions, printFn);\n}\nfunction printLayerSummaryWithConnections(layer, positions, relevantNodes, printFn) {\n  let outputShape;\n  let inputShape;\n  try {\n    inputShape = layer.inboundNodes.map((x) => JSON.stringify(x.inputShapes)).join(\",\");\n  } catch (err) {\n    inputShape = \"multiple\";\n  }\n  try {\n    outputShape = JSON.stringify(layer.outputShape);\n  } catch (err) {\n    outputShape = \"multiple\";\n  }\n  const connections = [];\n  for (const node of layer.inboundNodes) {\n    if (relevantNodes != null && relevantNodes.length > 0 && relevantNodes.indexOf(node) === -1) {\n      continue;\n    }\n    for (let i2 = 0; i2 < node.inboundLayers.length; ++i2) {\n      const inboundLayer = node.inboundLayers[i2].name;\n      const inboundLayerIndex = node.nodeIndices[i2];\n      const inboundTensorIndex = node.tensorIndices[i2];\n      connections.push(`${inboundLayer}[${inboundLayerIndex}][${inboundTensorIndex}]`);\n    }\n  }\n  const name = layer.name;\n  const className = layer.getClassName();\n  const firstConnection = connections.length === 0 ? \"\" : connections[0];\n  const fields = [\n    `${name} (${className})`,\n    inputShape,\n    outputShape,\n    layer.countParams().toString(),\n    firstConnection\n  ];\n  printRow(fields, positions, printFn);\n  for (let i2 = 1; i2 < connections.length; ++i2) {\n    printRow([\"\", \"\", \"\", \"\", connections[i2]], positions, printFn);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/serialization_utils.js\nfunction isArrayItemInputOrOutputName(key, index, value) {\n  return (key === \"inboundNodes\" || key === \"outputLayers\" || key === \"inputLayers\") && index === 0 && typeof value === \"string\";\n}\nfunction convertPythonicToTs(pythonicConfig, key) {\n  if (pythonicConfig === null) {\n    return null;\n  } else if (typeof pythonicConfig === \"string\") {\n    return toCamelCase(pythonicConfig);\n  } else if (typeof pythonicConfig === \"number\" || typeof pythonicConfig === \"boolean\") {\n    return pythonicConfig;\n  } else if (pythonicConfig instanceof Array) {\n    const tsArray = [];\n    const arrayLength = pythonicConfig.length;\n    for (let i2 = 0; i2 < arrayLength; ++i2) {\n      const item = pythonicConfig[i2];\n      if (isArrayItemInputOrOutputName(key, i2, item)) {\n        tsArray.push(item);\n      } else {\n        tsArray.push(convertPythonicToTs(item, key));\n      }\n    }\n    return tsArray;\n  } else {\n    const tsDict = {};\n    for (const pythonicKey of Object.keys(pythonicConfig)) {\n      const pythonicValue = pythonicConfig[pythonicKey];\n      if (pythonicKey === \"name\" && typeof pythonicValue === \"string\") {\n        tsDict[pythonicKey] = pythonicValue;\n      } else {\n        const tsKey = toCamelCase(pythonicKey);\n        tsDict[tsKey] = convertPythonicToTs(pythonicValue, tsKey);\n      }\n    }\n    return tsDict;\n  }\n}\nfunction convertTsToPythonic(tsConfig, key) {\n  if (tsConfig === null || tsConfig === void 0) {\n    return null;\n  } else if (typeof tsConfig === \"string\") {\n    return toSnakeCase(tsConfig);\n  } else if (typeof tsConfig === \"number\" || typeof tsConfig === \"boolean\") {\n    return tsConfig;\n  } else if (tsConfig instanceof Array) {\n    const pyArray = [];\n    const arrayLength = tsConfig.length;\n    for (let i2 = 0; i2 < arrayLength; ++i2) {\n      const item = tsConfig[i2];\n      if (isArrayItemInputOrOutputName(key, i2, item)) {\n        pyArray.push(item);\n      } else {\n        pyArray.push(convertTsToPythonic(item, key));\n      }\n    }\n    return pyArray;\n  } else {\n    const pyDict = {};\n    for (const tsKey of Object.keys(tsConfig)) {\n      const tsValue = tsConfig[tsKey];\n      const pyKey = toSnakeCase(tsKey);\n      if ((tsKey === \"name\" || tsKey === \"className\") && typeof tsValue === \"string\") {\n        pyDict[pyKey] = tsValue;\n      } else {\n        pyDict[pyKey] = convertTsToPythonic(tsValue, tsKey);\n      }\n    }\n    return pyDict;\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/version.js\nvar version2 = \"3.19.0\";\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/container.js\nvar Container = class extends Layer {\n  constructor(args) {\n    super({});\n    this.containerNodes = /* @__PURE__ */ new Set();\n    this.name = args.name;\n    if (this.name == null) {\n      const prefix = this.getClassName().toLowerCase();\n      this.name = getUid(prefix);\n    }\n    this.supportsMasking = false;\n    this.trainable_ = true;\n    if (Array.isArray(args.inputs)) {\n      this.inputs = args.inputs.slice();\n    } else {\n      this.inputs = [args.inputs];\n    }\n    if (Array.isArray(args.outputs)) {\n      this.outputs = args.outputs.slice();\n    } else {\n      this.outputs = [args.outputs];\n    }\n    if (unique2(this.inputs).length !== this.inputs.length) {\n      throw new ValueError(`The list of inputs passed to the model is redundant. All inputs should only appear once. Found: ${this.inputs.map((x) => x.name)}`);\n    }\n    if (unique2(this.outputs).length !== this.outputs.length) {\n      console.warn(`The list of outputs passed to the model is redundant. All outputs should only appear once. Found: ${this.outputs.map((x) => x.name)}`);\n    }\n    this.inputLayers = [];\n    this.inputLayersNodeIndices = [];\n    this.inputLayersTensorIndices = [];\n    this.outputLayers = [];\n    this.outputLayersNodeIndices = [];\n    this.outputLayersTensorIndices = [];\n    this.layers = [];\n    this.internalContainerRefs = [];\n    for (const x of this.outputs) {\n      const layer = x.sourceLayer;\n      const nodeIndex = x.nodeIndex;\n      const tensorIndex = x.tensorIndex;\n      this.outputLayers.push(layer);\n      this.outputLayersNodeIndices.push(nodeIndex);\n      this.outputLayersTensorIndices.push(tensorIndex);\n    }\n    for (const x of this.inputs) {\n      const layer = x.sourceLayer;\n      const nodeIndex = x.nodeIndex;\n      const tensorIndex = x.tensorIndex;\n      assert2(nodeIndex === 0, \"input layer has >1 nodes\");\n      assert2(tensorIndex === 0, \"input layer has >1 tensors\");\n      this.inputLayers.push(layer);\n      this.inputLayersNodeIndices.push(nodeIndex);\n      this.inputLayersTensorIndices.push(tensorIndex);\n    }\n    this.inputNames = [];\n    this.outputNames = [];\n    this.feedInputShapes = [];\n    this.feedInputNames = [];\n    this.feedOutputNames = [];\n    for (let i2 = 0; i2 < this.inputLayers.length; i2++) {\n      const layer = this.inputLayers[i2];\n      if (!(layer instanceof InputLayer)) {\n        throw new TypeError(`Input layers to a LayersModel must be InputLayer objects. Received inputs: ${args.inputs}. Input ${i2} (0-based) originates from layer type ${layer.getClassName()}.`);\n      }\n      this.inputNames.push(layer.name);\n      this.feedInputShapes.push(layer.batchInputShape);\n      this.feedInputNames.push(layer.name);\n    }\n    for (const layer of this.outputLayers) {\n      this.outputNames.push(layer.name);\n    }\n    this.internalInputShapes = this.inputs.map((x) => x.shape);\n    this.internalOutputShapes = this.outputs.map((x) => x.shape);\n    const nodesDepths = {};\n    const nodeIDToNode = {};\n    const layersDepths = {};\n    const layerIDToLayer = {};\n    const layerIndices = {};\n    const nodesInDecreasingDepth = [];\n    const buildMapOfGraph = (tensor2, finishedNodes2, nodesInProgress2, layer, nodeIndex, tensorIndex) => {\n      if (layer == null || nodeIndex == null || tensorIndex == null) {\n        layer = tensor2.sourceLayer;\n        nodeIndex = tensor2.nodeIndex;\n        tensorIndex = tensor2.tensorIndex;\n      }\n      const node = layer.inboundNodes[nodeIndex];\n      if (nodesInProgress2.indexOf(node) !== -1) {\n        throw new RuntimeError(`The tensor ${tensor2.name} at layer \"${layer.name}\" is part of a cycle.`);\n      }\n      if (finishedNodes2.indexOf(node) !== -1) {\n        return;\n      }\n      this.containerNodes.add(Container.nodeKey(layer, nodeIndex));\n      if (!(layer.id in layerIndices)) {\n        layerIndices[layer.id] = Object.keys(layerIndices).length;\n      }\n      if (nodesInProgress2.indexOf(node) === -1) {\n        nodesInProgress2.push(node);\n      }\n      const numInboundLayers = node.inboundLayers.length;\n      for (let i2 = 0; i2 < numInboundLayers; i2++) {\n        const x = node.inputTensors[i2];\n        const layer2 = node.inboundLayers[i2];\n        const nodeIndex2 = node.nodeIndices[i2];\n        const tensorIndex2 = node.tensorIndices[i2];\n        buildMapOfGraph(x, finishedNodes2, nodesInProgress2, layer2, nodeIndex2, tensorIndex2);\n      }\n      finishedNodes2.push(node);\n      while (nodesInProgress2.indexOf(node) >= 0) {\n        nodesInProgress2.splice(nodesInProgress2.indexOf(node), 1);\n      }\n      nodesInDecreasingDepth.push(node);\n    };\n    const finishedNodes = [];\n    const nodesInProgress = [];\n    for (const x of this.outputs) {\n      buildMapOfGraph(x, finishedNodes, nodesInProgress);\n    }\n    const reversedNodesInDecreasingDepth = nodesInDecreasingDepth.slice().reverse();\n    for (const node of reversedNodesInDecreasingDepth) {\n      nodeIDToNode[node.id] = node;\n      if (!(node.id in nodesDepths)) {\n        nodesDepths[node.id] = 0;\n      }\n      let depth = nodesDepths[node.id];\n      const previousDepth = layersDepths[node.outboundLayer.id] == null ? 0 : layersDepths[node.outboundLayer.id];\n      depth = Math.max(depth, previousDepth);\n      layersDepths[node.outboundLayer.id] = depth;\n      layerIDToLayer[node.outboundLayer.id] = node.outboundLayer;\n      nodesDepths[node.id] = depth;\n      for (let i2 = 0; i2 < node.inboundLayers.length; i2++) {\n        const inboundLayer = node.inboundLayers[i2];\n        const nodeIndex = node.nodeIndices[i2];\n        const inboundNode = inboundLayer.inboundNodes[nodeIndex];\n        const previousDepth2 = nodesDepths[inboundNode.id] == null ? 0 : nodesDepths[inboundNode.id];\n        nodesDepths[inboundNode.id] = Math.max(depth + 1, previousDepth2);\n        nodeIDToNode[inboundNode.id] = inboundNode;\n      }\n    }\n    const nodesByDepth = {};\n    for (const nodeID in nodesDepths) {\n      const depth = nodesDepths[nodeID];\n      if (!(depth in nodesByDepth)) {\n        nodesByDepth[depth] = [];\n      }\n      nodesByDepth[depth].push(nodeIDToNode[nodeID]);\n    }\n    const layersByDepth = {};\n    for (const layerID in layersDepths) {\n      const depth = layersDepths[layerID];\n      if (!(depth in layersByDepth)) {\n        layersByDepth[depth] = [];\n      }\n      layersByDepth[depth].push(layerIDToLayer[layerID]);\n    }\n    let depthKeys = Object.keys(layersByDepth).map((x) => parseInt(x, 10)).sort(reverseNumberCompare);\n    this.layers = [];\n    for (const depth of depthKeys) {\n      const layersForDepth = layersByDepth[depth];\n      layersForDepth.sort((a, b) => {\n        const aIndex = layerIndices[a.id];\n        const bIndex = layerIndices[b.id];\n        if (aIndex < bIndex) {\n          return -1;\n        }\n        if (aIndex > bIndex) {\n          return 1;\n        }\n        return 0;\n      });\n      for (const layer of layersForDepth) {\n        if (layer instanceof Container) {\n          this.internalContainerRefs.push(layer);\n        }\n        this.layers.push(layer);\n      }\n    }\n    this.layersByDepth = layersByDepth;\n    depthKeys = Object.keys(nodesByDepth).map((x) => parseInt(x, 10)).sort(reverseNumberCompare);\n    const computableTensors = this.inputs.slice();\n    const layersWithCompleteInput = [];\n    for (const depth of depthKeys) {\n      for (const node of nodesByDepth[depth]) {\n        const layer = node.outboundLayer;\n        if (layer != null) {\n          for (const x of node.inputTensors) {\n            if (computableTensors.indexOf(x) === -1) {\n              throw new RuntimeError(`Graph disconnected: cannot obtain value for tensor ${x} at layer \"${layer.name}\". The following previous layers were accessed without issue: ${layersWithCompleteInput}`);\n            }\n          }\n          for (const x of node.outputTensors) {\n            computableTensors.push(x);\n          }\n          layersWithCompleteInput.push(layer.name);\n        }\n      }\n    }\n    this.nodesByDepth = nodesByDepth;\n    const allNames = this.layers.map((x) => x.name);\n    for (const name of allNames) {\n      const numOccurrences = allNames.filter((x) => x === name).length;\n      if (numOccurrences !== 1) {\n        throw new RuntimeError(`The name \"${name}\" is used ${numOccurrences} times in the model. All layer names should be unique. Layer names: ` + JSON.stringify(allNames));\n      }\n    }\n    this.outboundNodes = [];\n    this.inboundNodes = [];\n    new Node({\n      outboundLayer: this,\n      inboundLayers: [],\n      nodeIndices: [],\n      tensorIndices: [],\n      inputTensors: this.inputs,\n      outputTensors: this.outputs,\n      inputMasks: this.inputs.map((x) => null),\n      outputMasks: this.outputs.map((x) => null),\n      inputShapes: this.inputs.map((x) => x.shape),\n      outputShapes: this.outputs.map((x) => x.shape)\n    });\n    this.built = true;\n    this._refCount = 1;\n  }\n  assertNotDisposed() {\n    if (this._refCount === 0) {\n      throw new Error(`Container '${this.name}' is already disposed.`);\n    }\n  }\n  dispose() {\n    this.assertNotDisposed();\n    const result = { refCountAfterDispose: null, numDisposedVariables: 0 };\n    if (--this._refCount === 0) {\n      for (const layer of this.layers) {\n        result.numDisposedVariables += layer.dispose().numDisposedVariables;\n      }\n      for (const container of this.internalContainerRefs) {\n        result.numDisposedVariables += container.dispose().numDisposedVariables;\n      }\n    }\n    result.refCountAfterDispose = this._refCount;\n    return result;\n  }\n  get trainable() {\n    return this.trainable_;\n  }\n  set trainable(trainable) {\n    this.layers.forEach((layer) => {\n      layer._trainableWeights.forEach((w) => w.trainable = trainable);\n    });\n    this.trainable_ = trainable;\n  }\n  get trainableWeights() {\n    if (this._trainableWeights.length > 0) {\n      throw new ValueError(\"Container instance unexpectedly contains _trainableWeights.The trainable weights of a Container are a union of the trainable weights of its consituent Layers. Its own _trainableWeights must remain an empty Array.\");\n    }\n    if (!this.trainable) {\n      return [];\n    }\n    let weights = [];\n    for (const layer of this.layers) {\n      weights = weights.concat(layer.trainableWeights);\n    }\n    return weights;\n  }\n  get nonTrainableWeights() {\n    const weights = [];\n    for (const layer of this.layers) {\n      weights.push(...layer.nonTrainableWeights);\n    }\n    if (!this.trainable) {\n      const trainableWeights = [];\n      for (const layer of this.layers) {\n        trainableWeights.push(...layer.trainableWeights);\n      }\n      return trainableWeights.concat(weights);\n    }\n    return weights;\n  }\n  get weights() {\n    return this.trainableWeights.concat(this.nonTrainableWeights);\n  }\n  loadWeights(weights, strict = true) {\n    const nameToWeight = {};\n    let totalWeightsCount = 0;\n    for (const layer of this.layers) {\n      for (const weight of layer.weights) {\n        if (nameToWeight[weight.originalName] != null) {\n          throw new ValueError(`Duplicate weight name: ${weight.originalName}`);\n        }\n        nameToWeight[weight.originalName] = weight;\n        totalWeightsCount++;\n      }\n    }\n    const weightValueTuples = [];\n    for (const name in weights) {\n      let validatedName = name;\n      if (nameToWeight[name] == null) {\n        const tokens = name.split(\"/\");\n        const shortenNameArray = tokens.slice(0, -2).concat([tokens[tokens.length - 1]]);\n        validatedName = shortenNameArray.join(\"/\");\n      }\n      if (nameToWeight[validatedName] != null) {\n        weightValueTuples.push([nameToWeight[validatedName], weights[name]]);\n      } else if (strict) {\n        throw new ValueError(`Provided weight data has no target variable: ${name}`);\n      }\n      delete nameToWeight[validatedName];\n    }\n    if (strict) {\n      const unsetNames = [];\n      for (const name in nameToWeight) {\n        unsetNames.push(name);\n      }\n      if (unsetNames.length > 0) {\n        throw new ValueError(`${unsetNames.length} of ${totalWeightsCount} weights are not set: ${unsetNames}`);\n      }\n    }\n    batchSetValue(weightValueTuples);\n  }\n  updatedConfig() {\n    const theConfig = this.getConfig();\n    const modelConfig = {};\n    modelConfig[\"className\"] = this.getClassName();\n    modelConfig[\"config\"] = theConfig;\n    modelConfig[\"kerasVersion\"] = `tfjs-layers ${version2}`;\n    modelConfig[\"backend\"] = \"TensorFlow.js\";\n    return modelConfig;\n  }\n  toJSON(unused, returnString = true) {\n    const modelConfig = convertTsToPythonic(this.updatedConfig());\n    return returnString ? JSON.stringify(modelConfig) : modelConfig;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = toList(inputs);\n      const feedDict = new FeedDict();\n      for (let i2 = 0; i2 < this.inputs.length; ++i2) {\n        feedDict.add(this.inputs[i2], inputs[i2]);\n      }\n      return execute(this.outputs, feedDict, kwargs);\n    });\n  }\n  computeMask(inputs, mask) {\n    return tidy(() => {\n      inputs = toList(inputs);\n      let masks;\n      if (mask == null) {\n        masks = pyListRepeat(null, inputs.length);\n      } else {\n        masks = toList(mask);\n      }\n      return this.runInternalGraph(inputs, masks)[1];\n    });\n  }\n  computeOutputShape(inputShape) {\n    const inputShapes = normalizeShapeList(inputShape);\n    if (inputShapes.length !== this.inputLayers.length) {\n      throw new ValueError(`Invalid inputShape argument ${inputShape}: model has ${this.inputLayers.length} tensor inputs.`);\n    }\n    const layersToOutputShapes = {};\n    for (let i2 = 0; i2 < inputShapes.length; i2++) {\n      const layer = this.inputLayers[i2];\n      const inputShape2 = inputShapes[i2];\n      const shapeKey = layer.name + \"_0_0\";\n      layersToOutputShapes[shapeKey] = inputShape2;\n    }\n    const depthKeys = Object.keys(this.nodesByDepth).map((x) => parseInt(x, 10)).sort(reverseNumberCompare);\n    if (depthKeys.length > 1) {\n      for (const depth of depthKeys) {\n        const nodes = this.nodesByDepth[depth];\n        for (const node of nodes) {\n          const layer = node.outboundLayer;\n          if (this.inputLayers.map((x) => x.id).indexOf(layer.id) !== -1) {\n            continue;\n          }\n          const inputShapes2 = [];\n          for (let j = 0; j < node.inboundLayers.length; j++) {\n            const inboundLayer = node.inboundLayers[j];\n            const nodeIndex2 = node.nodeIndices[j];\n            const tensorIndex = node.tensorIndices[j];\n            const shapeKey = `${inboundLayer.name}_${nodeIndex2}_${tensorIndex}`;\n            const inputShape2 = layersToOutputShapes[shapeKey];\n            inputShapes2.push(inputShape2);\n          }\n          const outputShape = layer.computeOutputShape(singletonOrArray(inputShapes2));\n          const outputShapes2 = normalizeShapeList(outputShape);\n          const nodeIndex = layer.inboundNodes.indexOf(node);\n          for (let j = 0; j < outputShapes2.length; j++) {\n            const shapeKey = `${layer.name}_${nodeIndex}_${j}`;\n            layersToOutputShapes[shapeKey] = outputShapes2[j];\n          }\n        }\n      }\n    }\n    const outputShapes = [];\n    const outputShapeKeys = [];\n    for (let i2 = 0; i2 < this.outputLayers.length; i2++) {\n      const layer = this.outputLayers[i2];\n      const nodeIndex = this.outputLayersNodeIndices[i2];\n      const tensorIndex = this.outputLayersTensorIndices[i2];\n      const shapeKey = `${layer.name}_${nodeIndex}_${tensorIndex}`;\n      outputShapeKeys.push(shapeKey);\n    }\n    for (let i2 = 0; i2 < outputShapeKeys.length; i2++) {\n      const key = outputShapeKeys[i2];\n      assert2(key in layersToOutputShapes);\n      outputShapes.push(layersToOutputShapes[key]);\n    }\n    return singletonOrArray(outputShapes);\n  }\n  runInternalGraph(inputs, masks) {\n    if (masks == null) {\n      masks = pyListRepeat(null, inputs.length);\n    }\n    const tensorMap = {};\n    for (let i2 = 0; i2 < this.inputs.length; ++i2) {\n      const x = this.inputs[i2];\n      const y = inputs[i2];\n      const mask = masks[i2];\n      tensorMap[x.id] = [y, mask];\n    }\n    const depthKeys = Object.keys(this.nodesByDepth).map((x) => parseInt(x, 10)).sort(reverseNumberCompare);\n    for (const depth of depthKeys) {\n      const nodes = this.nodesByDepth[depth];\n      for (const node of nodes) {\n        const layer = node.outboundLayer;\n        const referenceInputTensors = node.inputTensors;\n        const referenceOutputTensors = node.outputTensors;\n        const computedData = new Array();\n        for (const x of referenceInputTensors) {\n          if (x.id in tensorMap) {\n            computedData.push(tensorMap[x.id]);\n          }\n        }\n        if (computedData.length === referenceInputTensors.length) {\n          let kwargs = {};\n          let computedTensors;\n          let computedMasks;\n          let outputTensors2;\n          let outputMasks2;\n          if (node.callArgs != null) {\n            kwargs = node.callArgs;\n          }\n          if (computedData.length === 1) {\n            const [computedTensor, computedMask] = computedData[0];\n            if (kwargs[\"mask\"] == null) {\n              kwargs[\"mask\"] = computedMask;\n            }\n            outputTensors2 = toList(layer.call(computedTensor, kwargs));\n            outputMasks2 = toList(layer.computeMask(computedTensor, computedMask));\n            computedTensors = [computedTensor];\n            computedMasks = [computedMask];\n          } else {\n            computedTensors = computedData.map((x) => x[0]);\n            computedMasks = computedData.map((x) => x[1]);\n            if (kwargs[\"mask\"] == null) {\n              kwargs[\"mask\"] = computedMasks;\n            }\n            outputTensors2 = toList(layer.call(computedTensors, kwargs));\n            outputMasks2 = toList(layer.computeMask(computedTensors, computedMasks));\n          }\n          if (layer.activityRegularizer) {\n            throw new NotImplementedError(\"LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.\");\n          }\n          for (let i2 = 0; i2 < referenceOutputTensors.length; ++i2) {\n            const x = referenceOutputTensors[i2];\n            const y = outputTensors2[i2];\n            const mask = outputMasks2[i2];\n            tensorMap[x.id] = [y, mask];\n          }\n        }\n      }\n    }\n    const outputTensors = [];\n    const outputMasks = [];\n    const outputShapes = [];\n    for (const x of this.outputs) {\n      assert2(x.id in tensorMap, `Could not compute output ${x.name} : ${x.id}`);\n      const [tensor2, mask] = tensorMap[x.id];\n      outputShapes.push(tensor2.shape);\n      outputTensors.push(tensor2);\n      outputMasks.push(mask);\n    }\n    return [outputTensors, outputMasks, outputShapes];\n  }\n  buildNodeConversionMap(layers) {\n    const nodeConversionMap = {};\n    let keptNodes;\n    for (const layer of this.layers) {\n      keptNodes = layer instanceof Container ? 1 : 0;\n      for (let originalNodeIndex = 0; originalNodeIndex < layer.inboundNodes.length; originalNodeIndex++) {\n        const nodeKey = Container.nodeKey(layer, originalNodeIndex);\n        if (this.containerNodes.has(nodeKey)) {\n          nodeConversionMap[nodeKey] = keptNodes;\n          keptNodes += 1;\n        }\n      }\n    }\n    return nodeConversionMap;\n  }\n  getLayer(name, index) {\n    if (index != null) {\n      if (this.layers.length <= index) {\n        throw new ValueError(`Was asked to retrieve layer at index ${index}, but model only has ${this.layers.length} layer(s).`);\n      } else {\n        return this.layers[index];\n      }\n    } else {\n      if (name == null) {\n        throw new ValueError(\"Provide either a layer name or layer index\");\n      }\n    }\n    for (const layer of this.layers) {\n      if (layer.name === name) {\n        return layer;\n      }\n    }\n    throw new ValueError(`No such layer: ${name}`);\n  }\n  calculateLosses() {\n    return tidy(() => {\n      const losses2 = [];\n      for (const layer of this.layers) {\n        for (let nodeIndex = 0; nodeIndex < layer.inboundNodes.length; ++nodeIndex) {\n          const nodeKey = Container.nodeKey(layer, nodeIndex);\n          if (this.containerNodes.has(nodeKey)) {\n            losses2.push(...layer.calculateLosses());\n          }\n        }\n      }\n      return losses2;\n    });\n  }\n  getConfig() {\n    const config = { name: this.name };\n    const nodeConversionMap = this.buildNodeConversionMap(this.layers);\n    const layerConfigs = [];\n    for (const layer of this.layers) {\n      const layerClassName = layer.getClassName();\n      const layerConfig = layer.getConfig();\n      const filteredInboundNodes = [];\n      for (let originalNodeIndex = 0; originalNodeIndex < layer.inboundNodes.length; originalNodeIndex++) {\n        const node = layer.inboundNodes[originalNodeIndex];\n        const nodeKey = Container.nodeKey(layer, originalNodeIndex);\n        let kwargs = {};\n        if (this.containerNodes.has(nodeKey)) {\n          if (node.callArgs) {\n            try {\n              JSON.stringify(node.callArgs);\n              kwargs = node.callArgs;\n            } catch (err) {\n              console.warn(`Layer ${layer.name} was passed non-serializable keyword arguments: ${node.callArgs}. They will not be included in the serialized model (and thus will be missing at deserialization time).`);\n              kwargs = {};\n            }\n          }\n          if (node.inboundLayers.length > 0) {\n            const nodeData = [];\n            for (let i2 = 0; i2 < node.inboundLayers.length; i2++) {\n              const inboundLayer = node.inboundLayers[i2];\n              const nodeIndex = node.nodeIndices[i2];\n              const tensorIndex = node.tensorIndices[i2];\n              const nodeKey2 = Container.nodeKey(inboundLayer, nodeIndex);\n              let newNodeIndex = nodeConversionMap[nodeKey2];\n              if (newNodeIndex == null) {\n                newNodeIndex = 0;\n              }\n              nodeData.push([inboundLayer.name, newNodeIndex, tensorIndex, kwargs]);\n            }\n            filteredInboundNodes.push(nodeData);\n          }\n        }\n      }\n      const dict = {};\n      dict[\"name\"] = layer.name;\n      dict[\"className\"] = layerClassName;\n      dict[\"config\"] = layerConfig;\n      dict[\"inboundNodes\"] = filteredInboundNodes;\n      layerConfigs.push(dict);\n    }\n    config[\"layers\"] = layerConfigs;\n    const modelInputs = [];\n    for (let i2 = 0; i2 < this.inputLayers.length; i2++) {\n      const layer = this.inputLayers[i2];\n      const nodeIndex = this.inputLayersNodeIndices[i2];\n      const nodeKey = Container.nodeKey(layer, nodeIndex);\n      if (!this.containerNodes.has(nodeKey)) {\n        continue;\n      }\n      let newNodeIndex = nodeConversionMap[nodeKey];\n      if (newNodeIndex === null || newNodeIndex === void 0) {\n        newNodeIndex = 0;\n      }\n      const tensorIndex = this.inputLayersTensorIndices[i2];\n      modelInputs.push([layer.name, newNodeIndex, tensorIndex]);\n    }\n    config[\"inputLayers\"] = modelInputs;\n    const modelOutputs = [];\n    for (let i2 = 0; i2 < this.outputLayers.length; i2++) {\n      const layer = this.outputLayers[i2];\n      const nodeIndex = this.outputLayersNodeIndices[i2];\n      const nodeKey = Container.nodeKey(layer, nodeIndex);\n      if (!this.containerNodes.has(nodeKey)) {\n        continue;\n      }\n      let newNodeIndex = nodeConversionMap[nodeKey];\n      if (newNodeIndex === null || newNodeIndex === void 0) {\n        newNodeIndex = 0;\n      }\n      const tensorIndex = this.outputLayersTensorIndices[i2];\n      modelOutputs.push([layer.name, newNodeIndex, tensorIndex]);\n    }\n    config[\"outputLayers\"] = modelOutputs;\n    return config;\n  }\n  static fromConfig(cls, config, customObjects = {}, fastWeightInit = false) {\n    const createdLayers = {};\n    const unprocessedNodes = {};\n    function addUnprocessedNode(layer, nodeData) {\n      if (!(layer.name in unprocessedNodes)) {\n        unprocessedNodes[layer.name] = [nodeData];\n      } else {\n        unprocessedNodes[layer.name].push(nodeData);\n      }\n    }\n    function processNode(layer, nodeData) {\n      const inputTensors2 = [];\n      let kwargs;\n      for (const inputData of nodeData) {\n        const inboundLayerName = inputData[0];\n        const inboundNodeIndex = inputData[1];\n        const inboundTensorIndex = inputData[2];\n        kwargs = inputData[3] == null ? {} : inputData[3];\n        if (!(inboundLayerName in createdLayers)) {\n          addUnprocessedNode(layer, nodeData);\n          return;\n        }\n        const inboundLayer = createdLayers[inboundLayerName];\n        if (inboundLayer.inboundNodes.length <= inboundNodeIndex) {\n          addUnprocessedNode(layer, nodeData);\n          return;\n        }\n        const inboundNode = inboundLayer.inboundNodes[inboundNodeIndex];\n        inputTensors2.push(inboundNode.outputTensors[inboundTensorIndex]);\n      }\n      if (inputTensors2.length > 0) {\n        layer.apply(singletonOrArray(inputTensors2), kwargs);\n      }\n    }\n    function processLayer(layerData) {\n      const layerName = layerData[\"name\"];\n      const layer = deserialize(layerData, config[\"customObjects\"] != null ? config[\"customObjects\"] : {});\n      layer.setFastWeightInitDuringBuild(fastWeightInit);\n      createdLayers[layerName] = layer;\n      const inboundNodesData = layerData[\"inboundNodes\"];\n      inboundNodesData.forEach((nodeData) => {\n        if (!(nodeData instanceof Array)) {\n          throw new ValueError(`Corrupted configuration, expected array for nodeData: ${nodeData}`);\n        }\n        addUnprocessedNode(layer, nodeData);\n      });\n    }\n    const name = config[\"name\"];\n    const layersFromConfig = config[\"layers\"];\n    for (const layerData of layersFromConfig) {\n      processLayer(layerData);\n    }\n    while (!isObjectEmpty(unprocessedNodes)) {\n      for (const layerData of layersFromConfig) {\n        const layer = createdLayers[layerData[\"name\"]];\n        if (layer.name in unprocessedNodes) {\n          const currentUnprocessedNodesForLayer = unprocessedNodes[layer.name];\n          delete unprocessedNodes[layer.name];\n          for (const nodeData of currentUnprocessedNodesForLayer) {\n            processNode(layer, nodeData);\n          }\n        }\n      }\n    }\n    const inputTensors = [];\n    const outputTensors = [];\n    const inputLayersFromConfig = config[\"inputLayers\"];\n    for (const layerData of inputLayersFromConfig) {\n      const layerName = layerData[0];\n      const nodeIndex = layerData[1];\n      const tensorIndex = layerData[2];\n      assert2(layerName in createdLayers);\n      const layer = createdLayers[layerName];\n      const layerOutputTensors = layer.inboundNodes[nodeIndex].outputTensors;\n      inputTensors.push(layerOutputTensors[tensorIndex]);\n    }\n    const outputLayersFromConfig = config[\"outputLayers\"];\n    for (const layerData of outputLayersFromConfig) {\n      const layerName = layerData[0];\n      const nodeIndex = layerData[1];\n      const tensorIndex = layerData[2];\n      assert2(layerName in createdLayers);\n      const layer = createdLayers[layerName];\n      const layerOutputTensors = layer.inboundNodes[nodeIndex].outputTensors;\n      outputTensors.push(layerOutputTensors[tensorIndex]);\n    }\n    return new cls({ inputs: inputTensors, outputs: outputTensors, name });\n  }\n  get stateful() {\n    if (this._stateful) {\n      throw new ValueError(\"Container instance unexpectedly has _stateful = true. The statefulness of a Container is determined by the Layers it contains. Its _stateful property must remain the default false.\");\n    }\n    for (const layer of this.layers) {\n      if (layer.stateful) {\n        return true;\n      }\n    }\n    return false;\n  }\n  resetStates() {\n    tidy(() => {\n      this.layers.forEach((layer) => {\n        if (layer.stateful) {\n          layer.resetStates();\n        }\n      });\n    });\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/training_utils.js\nfunction standardizeSampleOrClassWeights(xWeight, outputNames, weightType) {\n  const numOutputs = outputNames.length;\n  if (xWeight == null || Array.isArray(xWeight) && xWeight.length === 0) {\n    return outputNames.map((name) => null);\n  }\n  if (numOutputs === 1) {\n    if (Array.isArray(xWeight) && xWeight.length === 1) {\n      return xWeight;\n    } else if (typeof xWeight === \"object\" && outputNames[0] in xWeight) {\n      return [xWeight[outputNames[0]]];\n    } else {\n      return [xWeight];\n    }\n  }\n  if (Array.isArray(xWeight)) {\n    if (xWeight.length !== numOutputs) {\n      throw new Error(`Provided ${weightType} is an array of ${xWeight.length} element(s), but the model has ${numOutputs} outputs. Make sure a set of weights is provided for each model output.`);\n    }\n    return xWeight;\n  } else if (typeof xWeight === \"object\" && Object.keys(xWeight).length > 0 && typeof xWeight[Object.keys(xWeight)[0]] === \"object\") {\n    const output = [];\n    outputNames.forEach((outputName) => {\n      if (outputName in xWeight) {\n        output.push(xWeight[outputName]);\n      } else {\n        output.push(null);\n      }\n    });\n    return output;\n  } else {\n    throw new Error(`The model has multiple (${numOutputs}) outputs, so ${weightType} must be either an array with ${numOutputs} elements or an object with ${outputNames} keys. Provided ${weightType} not understood: ${JSON.stringify(xWeight)}`);\n  }\n}\nfunction standardizeClassWeights(classWeight, outputNames) {\n  return standardizeSampleOrClassWeights(classWeight, outputNames, \"classWeight\");\n}\nasync function standardizeWeights(y, sampleWeight, classWeight, sampleWeightMode) {\n  if (sampleWeight != null || sampleWeightMode != null) {\n    throw new Error(\"Support sampleWeight is not implemented yet\");\n  }\n  if (classWeight != null) {\n    const yClasses = tidy(() => {\n      if (y.shape.length === 1) {\n        return clone(y);\n      } else if (y.shape.length === 2) {\n        if (y.shape[1] > 1) {\n          const axis = 1;\n          return argMax(y, axis);\n        } else if (y.shape[1] === 1) {\n          return reshape(y, [y.shape[0]]);\n        } else {\n          throw new Error(`Encountered unexpected last-dimension size (${y.shape[1]}) during handling of class weights. The size is expected to be >= 1.`);\n        }\n      } else {\n        throw new Error(`Unexpected rank of target (y) tensor (${y.rank}) during handling of class weights. The rank is expected to be 1 or 2.`);\n      }\n    });\n    const yClassIndices = Array.from(await yClasses.data());\n    dispose(yClasses);\n    const classSampleWeight = [];\n    yClassIndices.forEach((classIndex) => {\n      if (classWeight[classIndex] == null) {\n        throw new Error(`classWeight must contain all classes in the training data. The class ${classIndex} exists in the data but not in classWeight`);\n      } else {\n        classSampleWeight.push(classWeight[classIndex]);\n      }\n    });\n    return tensor1d(classSampleWeight, \"float32\");\n  } else {\n    return null;\n  }\n}\nfunction computeWeightedLoss2(losses2, sampleWeights) {\n  return mul(losses2, sampleWeights);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/training_dataset.js\nvar DEFAULT_VALIDATION_BATCH_SIZE = 32;\nfunction standardizeDataIteratorOutput(model2, iteratorOut) {\n  let xs;\n  let ys;\n  const iteratorOutObj = iteratorOut;\n  xs = iteratorOutObj[\"xs\"];\n  ys = iteratorOutObj[\"ys\"];\n  util_exports.assert(xs != null && ys != null, () => `A Dataset iterator for fitDataset() is expected to generate objects of the form \\`{xs: xVal, ys: yVal}\\`, where the two values may be \\`tf.Tensor\\`, an array of Tensors, or a map of string to Tensor.  The provided Dataset instead generates ${iteratorOut}`);\n  const flattenedXs = flattenTensorOrArrayOrMap(\"input\", model2.inputNames, xs);\n  const flattenedYs = flattenTensorOrArrayOrMap(\"output\", model2.outputNames, ys);\n  const batchSize = flattenedXs[0].shape[0];\n  util_exports.assert(flattenedXs.length === model2.inputs.length, () => `LayersModel has ${model2.inputs.length} inputs, but the dataset provides ${flattenedXs.length} inputs.  (Expected input keys: ${JSON.stringify(model2.inputNames)})`);\n  util_exports.assert(flattenedYs.length === model2.outputs.length, () => `LayersModel has ${model2.outputs.length} outputs, but the dataset provides ${flattenedYs.length} outputs.  (Expected output keys: ${JSON.stringify(model2.outputNames)})`);\n  for (let xIndex = 0; xIndex < flattenedXs.length; xIndex++) {\n    util_exports.assert(flattenedXs[xIndex].shape[0] === batchSize, () => `Batch size mismatch: input ${model2.inputNames[xIndex]} has ${flattenedXs[xIndex].shape[0]}; expected  ${batchSize} based on input ${model2.inputNames[0]}.`);\n  }\n  for (let yIndex = 0; yIndex < flattenedYs.length; yIndex++) {\n    util_exports.assert(flattenedYs[yIndex].shape[0] === batchSize, () => `Batch size mismatch: output ${model2.outputNames[yIndex]} has ${flattenedYs[yIndex].shape[0]}; expected  ${batchSize} based on input ${model2.inputNames[0]}.`);\n  }\n  return { xs: flattenedXs, ys: flattenedYs };\n}\nfunction flattenTensorOrArrayOrMap(inputOrOutput, names, values) {\n  if (values instanceof Tensor) {\n    return [values];\n  } else if (Array.isArray(values)) {\n    util_exports.assert(values.length === names.length, () => `Received an array of ${values.length} Tensors, but expected ${names.length} to match the ${inputOrOutput} keys ${names}.`);\n    return values;\n  } else {\n    const result = [];\n    for (const name of names) {\n      if (values[name] == null) {\n        throw new ValueError(`The feature data generated by the dataset lacks the required ${inputOrOutput} key '${name}'.`);\n      }\n      result.push(values[name]);\n    }\n    return result;\n  }\n}\nfunction standardizeTensorValidationData(data) {\n  if (data.length === 3) {\n    throw new NotImplementedError(\"Validation with sample weights is not implemented yet.\");\n  }\n  return { xs: data[0], ys: data[1] };\n}\nasync function fitDataset(model2, dataset, args) {\n  const hasBatchesPerEpoch = args.batchesPerEpoch != null;\n  util_exports.assert(model2.optimizer != null, () => \"You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig).\");\n  util_exports.assert(args != null, () => `For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call.`);\n  util_exports.assert(args.epochs != null && args.epochs > 0 && Number.isInteger(args.epochs), () => `For fitDataset(), config.epochs is expected to be a positive integer, but got ${args.epochs}`);\n  util_exports.assert(!hasBatchesPerEpoch || args.batchesPerEpoch > 0 && Number.isInteger(args.batchesPerEpoch), () => `For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${args.batchesPerEpoch}`);\n  util_exports.assert(\n    args[\"validationSplit\"] == null,\n    () => \"`validationSplit` is not supported by `fitDataset()`. Use validationData instead.\"\n  );\n  if (model2.isTraining) {\n    throw new Error(\"Cannot start training because another fit() call is ongoing.\");\n  }\n  model2.isTraining = true;\n  try {\n    const doValidation = args.validationData != null;\n    let valXs;\n    let valYs;\n    if (doValidation) {\n      if (isDatasetObject(args.validationData)) {\n        util_exports.assert(args.validationBatches == null || args.validationBatches > 0 && Number.isInteger(args.validationBatches), () => `For fitDataset() with dataset-based validation, config.validationBatches is expected not to be provided, or to be a positive integer, but got ${args.validationBatches}`);\n      } else {\n        const validationData = standardizeTensorValidationData(args.validationData);\n        valXs = validationData.xs;\n        valYs = validationData.ys;\n      }\n    }\n    const trainFunction = model2.makeTrainFunction();\n    const outLabels = model2.getDedupedMetricsNames();\n    let callbackMetrics;\n    if (doValidation) {\n      callbackMetrics = outLabels.slice().concat(outLabels.map((n2) => \"val_\" + n2));\n    } else {\n      callbackMetrics = outLabels.slice();\n    }\n    const callbacks2 = standardizeCallbacks(args.callbacks, args.yieldEvery);\n    const verbose = args.verbose == null ? 1 : args.verbose;\n    const { callbackList, history } = configureCallbacks(\n      callbacks2,\n      verbose,\n      args.epochs,\n      null,\n      null,\n      getStepsPerEpoch(dataset, args),\n      null,\n      doValidation,\n      callbackMetrics\n    );\n    callbackList.setModel(model2);\n    model2.history = history;\n    await callbackList.onTrainBegin();\n    model2.stopTraining_ = false;\n    let epoch = args.initialEpoch == null ? 0 : args.initialEpoch;\n    let dataIterator = await dataset.iterator();\n    while (epoch < args.epochs) {\n      const epochLogs = {};\n      await callbackList.onEpochBegin(epoch);\n      let stepsDone = 0;\n      let batchIndex = 0;\n      if (!hasBatchesPerEpoch) {\n        dataIterator = await dataset.iterator();\n      }\n      while (hasBatchesPerEpoch ? stepsDone < args.batchesPerEpoch : true) {\n        const iteratorOut = await dataIterator.next();\n        if (hasBatchesPerEpoch && iteratorOut.done) {\n          console.warn(`You provided \\`batchesPerEpoch\\` as ${args.batchesPerEpoch}, but your dataset iterator ran out of data after ${stepsDone} batches; interrupting training. Make sure that your dataset can generate at least \\`batchesPerEpoch * epochs\\` batches (in this case, ${args.batchesPerEpoch * args.epochs} batches). You may need to use the repeat() function when building your dataset.`);\n          break;\n        }\n        if (iteratorOut.value != null) {\n          const { xs, ys } = standardizeDataIteratorOutput(model2, iteratorOut.value);\n          const batchLogs = {};\n          batchLogs[\"batch\"] = batchIndex;\n          batchLogs[\"size\"] = xs[0].shape[0];\n          await callbackList.onBatchBegin(batchIndex, batchLogs);\n          const sampleWeights = [];\n          if (args.classWeight != null) {\n            const standardClassWeights = standardizeClassWeights(args.classWeight, model2.outputNames);\n            for (let i2 = 0; i2 < standardClassWeights.length; ++i2) {\n              sampleWeights.push(await standardizeWeights(ys[i2], null, standardClassWeights[i2]));\n            }\n          }\n          const ins = xs.concat(ys).concat(sampleWeights);\n          const outs = trainFunction(ins);\n          dispose(ins);\n          for (let i2 = 0; i2 < outLabels.length; ++i2) {\n            const label = outLabels[i2];\n            const out = outs[i2];\n            batchLogs[label] = out;\n            keep(out);\n          }\n          await callbackList.onBatchEnd(batchIndex, batchLogs);\n          disposeTensorsInLogs(batchLogs);\n          batchIndex++;\n          stepsDone++;\n        }\n        if (hasBatchesPerEpoch ? stepsDone >= args.batchesPerEpoch : iteratorOut.done) {\n          if (doValidation) {\n            let valOuts;\n            if (isDatasetObject(args.validationData)) {\n              valOuts = toList(await model2.evaluateDataset(args.validationData, { batches: args.validationBatches }));\n            } else {\n              valOuts = toList(model2.evaluate(valXs, valYs, {\n                batchSize: args.validationBatchSize == null ? DEFAULT_VALIDATION_BATCH_SIZE : args.validationBatchSize,\n                verbose: 0\n              }));\n            }\n            for (let i2 = 0; i2 < model2.metricsNames.length; ++i2) {\n              epochLogs[`val_${model2.metricsNames[i2]}`] = valOuts[i2];\n            }\n          }\n          break;\n        }\n        if (model2.stopTraining_) {\n          break;\n        }\n      }\n      await callbackList.onEpochEnd(epoch, epochLogs);\n      epoch++;\n      if (model2.stopTraining_) {\n        break;\n      }\n    }\n    await callbackList.onTrainEnd();\n    await model2.history.syncData();\n    return model2.history;\n  } finally {\n    model2.isTraining = false;\n  }\n}\nfunction getStepsPerEpoch(dataset, args) {\n  let stepsPerEpoch = null;\n  if (args.batchesPerEpoch != null) {\n    stepsPerEpoch = args.batchesPerEpoch;\n  } else if (Number.isFinite(dataset.size)) {\n    stepsPerEpoch = dataset.size;\n  }\n  return stepsPerEpoch;\n}\nfunction isDatasetObject(dataset) {\n  return typeof dataset.iterator === \"function\";\n}\nfunction isLazyIteratorObject(iterator) {\n  return typeof iterator.next === \"function\";\n}\nasync function evaluateDataset(model2, dataset, args) {\n  args = args || {};\n  const hasBatches = args.batches != null;\n  const f = model2.testFunction;\n  let outs = [];\n  if (args.verbose > 0) {\n    throw new NotImplementedError(\"Verbose mode is not implemented yet.\");\n  }\n  util_exports.assert(!hasBatches || args.batches > 0 && Number.isInteger(args.batches), () => `Test loop expects \\`batches\\` to be a positive integer, but received ${JSON.stringify(args.batches)}`);\n  const dataIterator = isLazyIteratorObject(dataset) ? dataset : await dataset.iterator();\n  let numExamples = 0;\n  let batch = 0;\n  while (hasBatches ? batch < args.batches : true) {\n    const iteratorOut = await dataIterator.next();\n    outs = tidy(() => {\n      if (iteratorOut.value) {\n        const { xs, ys } = standardizeDataIteratorOutput(model2, iteratorOut.value);\n        const xsAndYs = xs.concat(ys);\n        const batchOuts = tidy(() => f(xsAndYs));\n        dispose(xsAndYs);\n        if (batch === 0) {\n          for (let i2 = 0; i2 < batchOuts.length; ++i2) {\n            outs.push(scalar(0));\n          }\n        }\n        const batchSize = xsAndYs[0].shape[0];\n        for (let i2 = 0; i2 < batchOuts.length; ++i2) {\n          const batchOut = batchOuts[i2];\n          const oldScalar = outs[i2];\n          outs[i2] = tidy(() => add2(outs[i2], mul(batchSize, batchOut)));\n          if (batch > 0) {\n            dispose(oldScalar);\n          }\n        }\n        dispose(batchOuts);\n        numExamples += batchSize;\n        ++batch;\n      }\n      return outs;\n    });\n    if (iteratorOut.done) {\n      if (hasBatches) {\n        console.warn(`Your dataset iterator ran out of data during evaluateDataset(). Interrupting evalution. Make sure that your dataset can generate at least \\`batches\\` batches (in this case, ${args.batches} batches). You may need to use the repeat() function when building your dataset.`);\n      }\n      break;\n    }\n  }\n  for (let i2 = 0; i2 < outs.length; ++i2) {\n    const oldScalar = outs[i2];\n    outs[i2] = div(outs[i2], numExamples);\n    dispose(oldScalar);\n  }\n  return singletonOrArray(outs);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/training_tensors.js\nfunction checkBatchSize(batchSize) {\n  util_exports.assert(batchSize > 0 && Number.isInteger(batchSize), () => `batchSize is required to be a positive integer, but got ${batchSize}`);\n}\nfunction sliceArrays(arrays, start, stop) {\n  if (arrays == null) {\n    return [null];\n  } else if (Array.isArray(arrays)) {\n    return arrays.map((array2) => sliceAlongFirstAxis(array2, start, stop - start));\n  } else {\n    return sliceAlongFirstAxis(arrays, start, stop - start);\n  }\n}\nfunction sliceArraysByIndices(arrays, indices) {\n  return tidy(() => {\n    if (arrays == null) {\n      return null;\n    } else if (Array.isArray(arrays)) {\n      return arrays.map((array2) => sliceArraysByIndices(array2, indices));\n    } else {\n      return gather2(arrays, indices.dtype === \"int32\" ? indices : cast(indices, \"int32\"));\n    }\n  });\n}\nfunction makeBatches(size, batchSize) {\n  const output = [];\n  let batchStart = 0;\n  let batchEnd = null;\n  while (batchStart < size) {\n    batchEnd = batchStart + batchSize;\n    if (batchEnd >= size) {\n      batchEnd = size;\n    }\n    output.push([batchStart, batchEnd]);\n    batchStart = batchEnd;\n  }\n  return output;\n}\nasync function fitLoop(model2, f, ins, outLabels, batchSize, epochs, verbose, callbacks2, valF, valIns, shuffle2, callbackMetrics, initialEpoch, stepsPerEpoch, validationSteps) {\n  if (batchSize == null) {\n    batchSize = 32;\n  }\n  if (epochs == null) {\n    epochs = 1;\n  }\n  if (shuffle2 == null) {\n    shuffle2 = true;\n  }\n  if (initialEpoch == null) {\n    initialEpoch = 0;\n  }\n  let doValidation = false;\n  if (valF != null && valIns != null) {\n    doValidation = true;\n  }\n  if (validationSteps != null) {\n    doValidation = true;\n    if (stepsPerEpoch == null) {\n      throw new ValueError(\"Can only use `validationSteps` when doing step-wise training, i.e., `stepsPerEpoch` must be set.\");\n    }\n  }\n  const numTrainSamples = model2.checkNumSamples(ins, batchSize, stepsPerEpoch, \"steps_per_epoch\");\n  let indexArray;\n  if (numTrainSamples != null) {\n    indexArray = range2(0, numTrainSamples);\n  }\n  if (verbose == null) {\n    verbose = 1;\n  }\n  const { callbackList, history } = configureCallbacks(callbacks2, verbose, epochs, initialEpoch, numTrainSamples, stepsPerEpoch, batchSize, doValidation, callbackMetrics);\n  callbackList.setModel(model2);\n  model2.history = history;\n  await callbackList.onTrainBegin();\n  model2.stopTraining_ = false;\n  for (let epoch = initialEpoch; epoch < epochs; ++epoch) {\n    await callbackList.onEpochBegin(epoch);\n    const epochLogs = {};\n    if (stepsPerEpoch != null) {\n      throw new NotImplementedError(\"stepsPerEpoch mode is not implemented yet.\");\n    } else {\n      if (shuffle2 === \"batch\") {\n        throw new NotImplementedError(\"batch shuffling is not implemneted yet\");\n      } else if (shuffle2) {\n        util_exports.shuffle(indexArray);\n      }\n      const epochIndexArray1D = tensor1d(indexArray);\n      const batches = makeBatches(numTrainSamples, batchSize);\n      for (let batchIndex = 0; batchIndex < batches.length; ++batchIndex) {\n        const batchLogs = {};\n        await callbackList.onBatchBegin(batchIndex, batchLogs);\n        tidy(() => {\n          const batchStart = batches[batchIndex][0];\n          const batchEnd = batches[batchIndex][1];\n          const batchIds = sliceAlongFirstAxis(epochIndexArray1D, batchStart, batchEnd - batchStart);\n          batchLogs[\"batch\"] = batchIndex;\n          batchLogs[\"size\"] = batchEnd - batchStart;\n          const insBatch = sliceArraysByIndices(ins, batchIds);\n          const outs = f(insBatch);\n          for (let i2 = 0; i2 < outLabels.length; ++i2) {\n            const label = outLabels[i2];\n            const out = outs[i2];\n            batchLogs[label] = out;\n            keep(out);\n          }\n          if (batchIndex === batches.length - 1) {\n            if (doValidation) {\n              const valOuts = model2.testLoop(valF, valIns, batchSize);\n              for (let i2 = 0; i2 < outLabels.length; ++i2) {\n                const label = outLabels[i2];\n                const out = valOuts[i2];\n                keep(out);\n                epochLogs[\"val_\" + label] = out;\n              }\n            }\n          }\n        });\n        await callbackList.onBatchEnd(batchIndex, batchLogs);\n        disposeTensorsInLogs(batchLogs);\n        if (model2.stopTraining_) {\n          break;\n        }\n      }\n      epochIndexArray1D.dispose();\n    }\n    await callbackList.onEpochEnd(epoch, epochLogs);\n    if (model2.stopTraining_) {\n      break;\n    }\n  }\n  await callbackList.onTrainEnd();\n  await model2.history.syncData();\n  return model2.history;\n}\nasync function fitTensors(model2, x, y, args = {}) {\n  if (model2.isTraining) {\n    throw new Error(\"Cannot start training because another fit() call is ongoing.\");\n  }\n  model2.isTraining = true;\n  let inputs;\n  let targets;\n  let originalInputs;\n  let originalTargets;\n  let inputValX;\n  let inputValY;\n  let valX;\n  let valY;\n  let sampleWeights;\n  try {\n    const batchSize = args.batchSize == null ? 32 : args.batchSize;\n    checkBatchSize(batchSize);\n    const checkBatchAxis = false;\n    const standardizedOuts = await model2.standardizeUserData(x, y, args.sampleWeight, args.classWeight, checkBatchAxis, batchSize);\n    inputs = standardizedOuts[0];\n    targets = standardizedOuts[1];\n    sampleWeights = standardizedOuts[2];\n    let doValidation = false;\n    let valIns;\n    if (args.validationData != null && args.validationData.length > 0) {\n      doValidation = true;\n      if (args.validationData.length === 2) {\n        inputValX = args.validationData[0];\n        inputValY = args.validationData[1];\n      } else if (args.validationData.length === 3) {\n        throw new NotImplementedError(\"validationData including sample weights is not supported yet.\");\n      } else {\n        throw new ValueError(`When passing validation data, it must contain 2 (valX, valY) or 3 (valX, valY, valSampleWeight) items; ${args.validationData} is invalid.`);\n      }\n      const checkBatchAxis2 = true;\n      const valStandardized = await model2.standardizeUserData(inputValX, inputValY, null, null, checkBatchAxis2, batchSize);\n      valX = valStandardized[0];\n      valY = valStandardized[1];\n      valIns = valX.concat(valY);\n    } else if (args.validationSplit != null && args.validationSplit > 0 && args.validationSplit < 1) {\n      doValidation = true;\n      const splitAt = Math.floor(inputs[0].shape[0] * (1 - args.validationSplit));\n      const originalBatchSize = inputs[0].shape[0];\n      valX = sliceArrays(inputs, splitAt, originalBatchSize);\n      originalInputs = inputs;\n      inputs = sliceArrays(inputs, 0, splitAt);\n      valY = sliceArrays(targets, splitAt, originalBatchSize);\n      originalTargets = targets;\n      targets = sliceArrays(targets, 0, splitAt);\n      valIns = valX.concat(valY);\n    } else if (args.validationSteps != null) {\n      doValidation = true;\n    }\n    const ins = inputs.concat(targets).concat(sampleWeights);\n    model2.checkTrainableWeightsConsistency();\n    const trainFunction = model2.makeTrainFunction();\n    const outLabels = model2.getDedupedMetricsNames();\n    let valFunction;\n    let callbackMetrics;\n    if (doValidation) {\n      model2.makeTestFunction();\n      valFunction = model2.testFunction;\n      callbackMetrics = outLabels.slice().concat(outLabels.map((n2) => \"val_\" + n2));\n    } else {\n      valFunction = null;\n      valIns = [];\n      callbackMetrics = outLabels.slice();\n    }\n    const callbacks2 = standardizeCallbacks(args.callbacks, args.yieldEvery);\n    const out = await fitLoop(model2, trainFunction, ins, outLabels, batchSize, args.epochs, args.verbose, callbacks2, valFunction, valIns, args.shuffle, callbackMetrics, args.initialEpoch, null, null);\n    return out;\n  } finally {\n    model2.isTraining = false;\n    disposeNewTensors(inputs, x);\n    disposeNewTensors(targets, y);\n    disposeNewTensors(originalInputs, x);\n    disposeNewTensors(originalTargets, y);\n    disposeNewTensors(valX, inputValX);\n    disposeNewTensors(valY, inputValY);\n    if (sampleWeights != null) {\n      dispose(sampleWeights);\n    }\n  }\n}\nfunction ensureTensorsRank2OrHigher(tensors) {\n  const outs = [];\n  if (tensors instanceof Tensor) {\n    tensors = [tensors];\n  }\n  for (let i2 = 0; i2 < tensors.length; ++i2) {\n    const tensor2 = tensors[i2];\n    if (tensor2.rank === 1) {\n      outs.push(expandDims2(tensor2, 1));\n    } else if (tensor2.rank === 0) {\n      throw new Error(\"Expected tensor to be at least 1D, but received a 0D tensor (scalar).\");\n    } else {\n      outs.push(tensor2);\n    }\n  }\n  return outs;\n}\nfunction disposeNewTensors(tensors, refTensors) {\n  if (tensors == null) {\n    return;\n  }\n  const oldTensorIds = [];\n  if (refTensors instanceof Tensor) {\n    oldTensorIds.push(refTensors.id);\n  } else if (Array.isArray(refTensors)) {\n    refTensors.forEach((t2) => oldTensorIds.push(t2.id));\n  } else if (refTensors != null) {\n    for (const name in refTensors) {\n      const oldTensor = refTensors[name];\n      oldTensorIds.push(oldTensor.id);\n    }\n  }\n  const tensorsToDispose = [];\n  if (tensors instanceof Tensor) {\n    if (oldTensorIds.indexOf(tensors.id) === -1) {\n      tensorsToDispose.push(tensors);\n    }\n  } else if (Array.isArray(tensors)) {\n    tensors.forEach((t2) => {\n      if (oldTensorIds.indexOf(t2.id) === -1) {\n        tensorsToDispose.push(t2);\n      }\n    });\n  } else if (tensors != null) {\n    for (const name in tensors) {\n      const tensor2 = tensors[name];\n      if (oldTensorIds.indexOf(tensor2.id) === -1) {\n        tensorsToDispose.push(tensor2);\n      }\n    }\n  }\n  tensorsToDispose.forEach((t2) => {\n    if (!t2.isDisposed) {\n      t2.dispose();\n    }\n  });\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/training.js\nfunction isDataTensor(x) {\n  return x instanceof Tensor;\n}\nfunction isDataArray(x) {\n  return Array.isArray(x);\n}\nfunction isDataDict(x) {\n  return !isDataTensor(x) && !isDataArray(x);\n}\nfunction standardizeInputData(data, names, shapes, checkBatchAxis = true, exceptionPrefix = \"\") {\n  if (names == null || names.length === 0) {\n    if (data != null) {\n      let gotUnexpectedData = false;\n      if (isDataArray(data) && data.length > 0) {\n        gotUnexpectedData = true;\n      } else if (isDataDict(data)) {\n        for (const key in data) {\n          if (data.hasOwnProperty(key)) {\n            gotUnexpectedData = true;\n            break;\n          }\n        }\n      } else {\n        gotUnexpectedData = true;\n      }\n      if (gotUnexpectedData) {\n        throw new ValueError(`Error when checking model ${exceptionPrefix} expected no data, but got ${data}`);\n      }\n    }\n    return [];\n  }\n  if (data == null) {\n    return names.map((name) => null);\n  }\n  let arrays;\n  if (isDataDict(data)) {\n    data = data;\n    arrays = [];\n    for (const name of names) {\n      if (data[name] == null) {\n        throw new ValueError(`No data provided for \"${name}\". Need data for each key in: ${names}`);\n      }\n      arrays.push(data[name]);\n    }\n  } else if (isDataArray(data)) {\n    data = data;\n    if (data.length !== names.length) {\n      throw new ValueError(`Error when checking model ${exceptionPrefix}: the Array of Tensors that you are passing to your model is not the size the model expected. Expected to see ${names.length} Tensor(s), but instead got the following list of Tensor(s): ${data}`);\n    }\n    arrays = data;\n  } else {\n    data = data;\n    if (names.length > 1) {\n      throw new ValueError(`The model ${exceptionPrefix} expects ${names.length} Tensor(s), but only received one Tensor. Found: Tensor with shape ${data.shape}`);\n    }\n    arrays = [data];\n  }\n  arrays = ensureTensorsRank2OrHigher(arrays);\n  if (shapes != null) {\n    for (let i2 = 0; i2 < names.length; ++i2) {\n      if (shapes[i2] == null) {\n        continue;\n      }\n      const array2 = arrays[i2];\n      if (array2.shape.length !== shapes[i2].length) {\n        throw new ValueError(`Error when checking ${exceptionPrefix}: expected ${names[i2]} to have ${shapes[i2].length} dimension(s). but got array with shape ${array2.shape}`);\n      }\n      for (let j = 0; j < shapes[i2].length; ++j) {\n        if (j === 0 && !checkBatchAxis) {\n          continue;\n        }\n        const dim = array2.shape[j];\n        const refDim = shapes[i2][j];\n        if (refDim != null && refDim >= 0 && dim !== refDim) {\n          throw new ValueError(`${exceptionPrefix} expected a batch of elements where each example has shape [${shapes[i2].slice(1, shapes[i2].length)}] (i.e.,tensor shape [*,${shapes[i2].slice(1, shapes[i2].length)}]) but the ${exceptionPrefix} received an input with ${array2.shape[0]} examples, each with shape [${array2.shape.slice(1, array2.shape.length)}] (tensor shape [${array2.shape}])`);\n        }\n      }\n    }\n  }\n  return arrays;\n}\nfunction checkArrayLengths(inputs, targets, weights) {\n  const setX = unique2(inputs.map((input2) => input2.shape[0]));\n  setX.sort();\n  const setY = unique2(targets.map((target) => target.shape[0]));\n  setY.sort();\n  if (setX.length > 1) {\n    throw new ValueError(`All input Tensors (x) should have the same number of samples. Got array shapes: ${JSON.stringify(inputs.map((input2) => input2.shape))}`);\n  }\n  if (setY.length > 1) {\n    throw new ValueError(`All target Tensors (y) should have the same number of samples. Got array shapes: ${JSON.stringify(targets.map((target) => target.shape))}`);\n  }\n  if (setX.length > 0 && setY.length > 0 && !util_exports.arraysEqual(setX, setY)) {\n    throw new ValueError(`Input Tensors should have the same number of samples as target Tensors. Found ${setX[0]} input sample(s) and ${setY[0]} target sample(s).`);\n  }\n}\nfunction checkLossAndTargetCompatibility(targets, lossFns, outputShapes) {\n  const keyLosses = [\n    meanSquaredError2,\n    binaryCrossentropy,\n    categoricalCrossentropy\n  ];\n  for (let i2 = 0; i2 < targets.length; ++i2) {\n    const y = targets[i2];\n    const loss = lossFns[i2];\n    const shape = outputShapes[i2];\n    if (loss == null) {\n      continue;\n    }\n    if (loss === categoricalCrossentropy) {\n      if (y.shape[y.shape.length - 1] === 1) {\n        throw new ValueError(`You are passing a target array of shape ${y.shape} while using a loss 'categorical_crossentropy'. 'categorical_crossentropy'expects targets to be binary matrices (1s and 0s) of shape [samples, classes].`);\n      }\n    }\n    if (keyLosses.indexOf(loss) !== -1) {\n      const slicedYShape = y.shape.slice(1);\n      const slicedShape = shape.slice(1);\n      for (let j = 0; j < slicedYShape.length; ++j) {\n        const targetDim = slicedYShape[j];\n        const outDim = slicedShape[j];\n        if (outDim != null && targetDim !== outDim) {\n          throw new ValueError(`A target Tensor with shape ${y.shape} was passed for an output of shape ${shape}, while using a loss function that expects targets to have the same shape as the output.`);\n        }\n      }\n    }\n  }\n}\nfunction checkInputData(data, names, shapes, checkBatchAxis = true, exceptionPrefix = \"\") {\n  let arrays;\n  if (Array.isArray(data)) {\n    if (data.length !== names.length) {\n      throw new ValueError(`Error when checking model ${exceptionPrefix}: the Array of Tensors that you are passing to your model is not the size the the model expected. Expected to see ${names.length} Tensor(s), but instead got ${data.length} Tensors(s).`);\n    }\n    arrays = data;\n  } else {\n    if (names.length > 1) {\n      throw new ValueError(`The model expects ${names.length} ${exceptionPrefix} Tensors, but only received one Tensor. Found: array with shape ${JSON.stringify(data.shape)}.`);\n    }\n    arrays = [data];\n  }\n  if (shapes != null) {\n    for (let i2 = 0; i2 < names.length; ++i2) {\n      if (shapes[i2] == null) {\n        continue;\n      }\n      const array2 = arrays[i2];\n      if (array2.shape.length !== shapes[i2].length) {\n        throw new ValueError(`Error when checking ${exceptionPrefix}: expected ${names[i2]} to have ${shapes[i2].length} dimension(s), but got array with shape ${JSON.stringify(array2.shape)}`);\n      }\n      for (let j = 0; j < shapes[i2].length; ++j) {\n        if (j === 0 && !checkBatchAxis) {\n          continue;\n        }\n        const dim = array2.shape[j];\n        const refDim = shapes[i2][j];\n        if (refDim != null) {\n          if (refDim !== dim) {\n            throw new ValueError(`Error when checking ${exceptionPrefix}: expected ${names[i2]} to have shape ${JSON.stringify(shapes[i2])} but got array with shape ${JSON.stringify(array2.shape)}.`);\n          }\n        }\n      }\n    }\n  }\n}\nfunction collectMetrics(metrics, outputNames) {\n  if (metrics == null || Array.isArray(metrics) && metrics.length === 0) {\n    return outputNames.map((name) => []);\n  }\n  let wrappedMetrics;\n  if (typeof metrics === \"string\" || typeof metrics === \"function\") {\n    wrappedMetrics = [metrics];\n  } else if (Array.isArray(metrics) || typeof metrics === \"object\") {\n    wrappedMetrics = metrics;\n  } else {\n    throw new TypeError(`Type of metrics argument not understood. Expected an string,function, Array, or Object, found: ${metrics}`);\n  }\n  if (Array.isArray(wrappedMetrics)) {\n    return outputNames.map((name) => wrappedMetrics);\n  } else {\n    const nestedMetrics = [];\n    for (const name of outputNames) {\n      let outputMetrics = wrappedMetrics.hasOwnProperty(name) ? wrappedMetrics[name] : [];\n      if (!Array.isArray(outputMetrics)) {\n        outputMetrics = [outputMetrics];\n      }\n      nestedMetrics.push(outputMetrics);\n    }\n    return nestedMetrics;\n  }\n}\nvar LAYERS_MODEL_FORMAT_NAME = \"layers-model\";\nvar LayersModel = class extends Container {\n  constructor(args) {\n    super(args);\n    this.isTraining = false;\n  }\n  summary(lineLength, positions, printFn = console.log) {\n    if (!this.built) {\n      throw new ValueError(`This model has never been called, thus its weights have not been created yet. So no summary can be displayed. Build the model first (e.g., by calling it on some test data).`);\n    }\n    printSummary(this, lineLength, positions, printFn);\n  }\n  compile(args) {\n    if (args.loss == null) {\n      args.loss = [];\n    }\n    this.loss = args.loss;\n    if (typeof args.optimizer === \"string\") {\n      this.optimizer_ = getOptimizer(args.optimizer);\n      this.isOptimizerOwned = true;\n    } else {\n      if (!(args.optimizer instanceof Optimizer)) {\n        throw new ValueError(`User-defined optimizer must be an instance of tf.Optimizer.`);\n      }\n      this.optimizer_ = args.optimizer;\n      this.isOptimizerOwned = false;\n    }\n    let lossFunctions = [];\n    if (!Array.isArray(args.loss) && typeof args.loss !== \"string\" && typeof args.loss !== \"function\") {\n      args.loss = args.loss;\n      for (const name in args.loss) {\n        if (this.outputNames.indexOf(name) === -1) {\n          throw new ValueError(`Unknown entry in loss dictionary: \"${name}\". Only expected the following keys: ${this.outputNames}`);\n        }\n      }\n      for (const name of this.outputNames) {\n        if (args.loss[name] == null) {\n          console.warn(`Output \"${name}\" is missing from loss dictionary. We assume this was done on purpose, and we will not be expecting data to be passed to ${name} during training`);\n        }\n        lossFunctions.push(get(args.loss[name]));\n      }\n    } else if (Array.isArray(args.loss)) {\n      if (args.loss.length !== this.outputs.length) {\n        throw new ValueError(`When passing an Array as loss, it should have one entry per model output. The model has ${this.outputs.length} output(s), but you passed loss=${args.loss}.`);\n      }\n      const theLosses = args.loss;\n      lossFunctions = theLosses.map((l3) => get(l3));\n    } else {\n      const lossFunction = get(args.loss);\n      this.outputs.forEach((_) => {\n        lossFunctions.push(lossFunction);\n      });\n    }\n    this.lossFunctions = lossFunctions;\n    this.feedOutputNames = [];\n    this.feedOutputShapes = [];\n    this.feedLossFns = [];\n    for (let i2 = 0; i2 < this.outputs.length; ++i2) {\n      const shape = this.internalOutputShapes[i2];\n      const name = this.outputNames[i2];\n      this.feedOutputNames.push(name);\n      this.feedOutputShapes.push(shape);\n      this.feedLossFns.push(this.lossFunctions[i2]);\n    }\n    const skipTargetIndices = [];\n    this.metrics = args.metrics;\n    this.metricsNames = [\"loss\"];\n    this.metricsTensors = [];\n    nameScope(\"loss\", () => {\n      for (let i2 = 0; i2 < this.outputs.length; ++i2) {\n        if (skipTargetIndices.indexOf(i2) !== -1) {\n          continue;\n        }\n        const weightedLoss = this.lossFunctions[i2];\n        if (this.outputs.length > 1) {\n          this.metricsTensors.push([weightedLoss, i2]);\n          this.metricsNames.push(this.outputNames[i2] + \"_loss\");\n        }\n      }\n    });\n    const nestedMetrics = collectMetrics(args.metrics, this.outputNames);\n    const appendMetric = (outputIndex, metricName, metricTensor) => {\n      if (this.outputNames.length > 1) {\n        metricName = this.outputNames[outputIndex] + \"_\" + metricName;\n      }\n      this.metricsNames.push(metricName);\n      this.metricsTensors.push([metricTensor, outputIndex]);\n    };\n    nameScope(\"metric\", () => {\n      for (let i2 = 0; i2 < this.outputs.length; ++i2) {\n        if (skipTargetIndices.indexOf(i2) !== -1) {\n          continue;\n        }\n        const outputMetrics = nestedMetrics[i2];\n        const handleMetrics = (metrics) => {\n          const metricNamePrefix = \"\";\n          let metricName;\n          let accFn;\n          let weightedMetricFn;\n          for (const metric of metrics) {\n            if (typeof metric === \"string\" && [\"accuracy\", \"acc\", \"crossentropy\", \"ce\"].indexOf(metric) !== -1) {\n              const outputShape = this.internalOutputShapes[i2];\n              if (outputShape[outputShape.length - 1] === 1 || this.lossFunctions[i2] === binaryCrossentropy) {\n                if ([\"accuracy\", \"acc\"].indexOf(metric) !== -1) {\n                  accFn = binaryAccuracy;\n                } else if ([\"crossentropy\", \"ce\"].indexOf(metric) !== -1) {\n                  accFn = binaryCrossentropy2;\n                }\n              } else if (this.lossFunctions[i2] === sparseCategoricalCrossentropy) {\n                if ([\"accuracy\", \"acc\"].indexOf(metric) !== -1) {\n                  accFn = sparseCategoricalAccuracy;\n                } else if ([\"crossentropy\", \"ce\"].indexOf(metric) !== -1) {\n                  accFn = sparseCategoricalCrossentropy2;\n                }\n              } else {\n                if ([\"accuracy\", \"acc\"].indexOf(metric) !== -1) {\n                  accFn = categoricalAccuracy;\n                } else if ([\"crossentropy\", \"ce\"].indexOf(metric) !== -1) {\n                  accFn = categoricalCrossentropy2;\n                }\n              }\n              let suffix;\n              if ([\"accuracy\", \"acc\"].indexOf(metric) !== -1) {\n                suffix = \"acc\";\n              } else if ([\"crossentropy\", \"ce\"].indexOf(metric) !== -1) {\n                suffix = \"ce\";\n              }\n              weightedMetricFn = accFn;\n              metricName = metricNamePrefix + suffix;\n            } else {\n              const metricFn = get2(metric);\n              weightedMetricFn = metricFn;\n              metricName = metricNamePrefix + getLossOrMetricName(metric);\n            }\n            let metricResult;\n            nameScope(metricName, () => {\n              metricResult = weightedMetricFn;\n            });\n            appendMetric(i2, metricName, metricResult);\n          }\n        };\n        handleMetrics(outputMetrics);\n      }\n    });\n    this.collectedTrainableWeights = this.trainableWeights;\n  }\n  checkTrainableWeightsConsistency() {\n    if (this.collectedTrainableWeights == null) {\n      return;\n    }\n    if (this.trainableWeights.length !== this.collectedTrainableWeights.length) {\n      console.warn(\"Discrepancy between trainableweights and collected trainable weights. Did you set `model.trainable` without calling `model.compile()` afterwards?\");\n    }\n  }\n  evaluate(x, y, args = {}) {\n    const batchSize = args.batchSize == null ? 32 : args.batchSize;\n    checkBatchSize(batchSize);\n    const checkBatchAxis = true;\n    const standardizedOuts = this.standardizeUserDataXY(x, y, checkBatchAxis, batchSize);\n    try {\n      const ins = standardizedOuts[0].concat(standardizedOuts[1]);\n      this.makeTestFunction();\n      const f = this.testFunction;\n      const testOuts = this.testLoop(f, ins, batchSize, args.verbose, args.steps);\n      return singletonOrArray(testOuts);\n    } finally {\n      disposeNewTensors(standardizedOuts[0], x);\n      disposeNewTensors(standardizedOuts[1], y);\n    }\n  }\n  async evaluateDataset(dataset, args) {\n    this.makeTestFunction();\n    return evaluateDataset(this, dataset, args);\n  }\n  checkNumSamples(ins, batchSize, steps, stepsName = \"steps\") {\n    let numSamples;\n    if (steps != null) {\n      numSamples = null;\n      if (batchSize != null) {\n        throw new ValueError(`If ${stepsName} is set, batchSize must be null or undefined.Got batchSize = ${batchSize}`);\n      }\n    } else if (ins != null) {\n      if (Array.isArray(ins)) {\n        numSamples = ins[0].shape[0];\n      } else {\n        numSamples = ins.shape[0];\n      }\n    } else {\n      throw new ValueError(`Either the input data should have a defined shape, or ${stepsName} shoud be specified.`);\n    }\n    return numSamples;\n  }\n  execute(inputs, outputs) {\n    if (Array.isArray(outputs) && outputs.length === 0) {\n      throw new ValueError(\"`outputs` is an empty Array, which is not allowed.\");\n    }\n    const outputsIsArray = Array.isArray(outputs);\n    const outputNames = outputsIsArray ? outputs : [outputs];\n    const outputSymbolicTensors = this.retrieveSymbolicTensors(outputNames);\n    const feedDict = new FeedDict();\n    if (inputs instanceof Tensor) {\n      inputs = [inputs];\n    }\n    if (Array.isArray(inputs)) {\n      if (inputs.length !== this.inputs.length) {\n        throw new ValueError(`The number of inputs provided (${inputs.length}) does not match the number of inputs of this model (${this.inputs.length}).`);\n      }\n      for (let i2 = 0; i2 < this.inputs.length; ++i2) {\n        feedDict.add(this.inputs[i2], inputs[i2]);\n      }\n    } else {\n      for (const input2 of this.inputs) {\n        const tensorValue = inputs[input2.name];\n        if (tensorValue == null) {\n          throw new ValueError(`No value is provided for the model's input ${input2.name}`);\n        }\n        feedDict.add(input2, tensorValue);\n      }\n    }\n    const executeOutputs = execute(outputSymbolicTensors, feedDict);\n    return outputsIsArray ? executeOutputs : executeOutputs[0];\n  }\n  retrieveSymbolicTensors(symbolicTensorNames) {\n    const outputSymbolicTensors = pyListRepeat(null, symbolicTensorNames.length);\n    let outputsRemaining = symbolicTensorNames.length;\n    for (const layer of this.layers) {\n      const layerOutputs = Array.isArray(layer.output) ? layer.output : [layer.output];\n      const layerOutputNames = layerOutputs.map((output) => output.name);\n      for (let i2 = 0; i2 < symbolicTensorNames.length; ++i2) {\n        const index = layerOutputNames.indexOf(symbolicTensorNames[i2]);\n        if (index !== -1) {\n          outputSymbolicTensors[i2] = layerOutputs[index];\n          outputsRemaining--;\n        }\n        if (outputsRemaining === 0) {\n          break;\n        }\n      }\n      if (outputsRemaining === 0) {\n        break;\n      }\n    }\n    if (outputsRemaining > 0) {\n      const remainingNames = [];\n      outputSymbolicTensors.forEach((tensor2, i2) => {\n        if (tensor2 == null) {\n          remainingNames.push(symbolicTensorNames[i2]);\n        }\n      });\n      throw new ValueError(`Cannot find SymbolicTensors for output name(s): ${JSON.stringify(remainingNames)}`);\n    }\n    return outputSymbolicTensors;\n  }\n  predictLoop(ins, batchSize = 32, verbose = false) {\n    return tidy(() => {\n      const numSamples = this.checkNumSamples(ins);\n      if (verbose) {\n        throw new NotImplementedError(\"Verbose predictLoop() is not implemented yet.\");\n      }\n      const batches = makeBatches(numSamples, batchSize);\n      const outsBatches = this.outputs.map((output) => []);\n      for (let batchIndex = 0; batchIndex < batches.length; ++batchIndex) {\n        const batchOuts = tidy(() => {\n          const batchStart = batches[batchIndex][0];\n          const batchEnd = batches[batchIndex][1];\n          const insBatch = sliceArrays(ins, batchStart, batchEnd);\n          const feeds = [];\n          if (Array.isArray(insBatch)) {\n            for (let i2 = 0; i2 < insBatch.length; ++i2) {\n              feeds.push({ key: this.inputs[i2], value: insBatch[i2] });\n            }\n          } else {\n            feeds.push({ key: this.inputs[0], value: insBatch });\n          }\n          const feedDict = new FeedDict(feeds);\n          return execute(this.outputs, feedDict);\n        });\n        batchOuts.forEach((batchOut, i2) => outsBatches[i2].push(batchOut));\n      }\n      return singletonOrArray(outsBatches.map((batches2) => concat(batches2, 0)));\n    });\n  }\n  predict(x, args = {}) {\n    const xsRank2OrHigher = ensureTensorsRank2OrHigher(x);\n    checkInputData(xsRank2OrHigher, this.inputNames, this.feedInputShapes, false);\n    try {\n      const batchSize = args.batchSize == null ? 32 : args.batchSize;\n      checkBatchSize(batchSize);\n      return this.predictLoop(xsRank2OrHigher, batchSize);\n    } finally {\n      disposeNewTensors(xsRank2OrHigher, x);\n    }\n  }\n  predictOnBatch(x) {\n    checkInputData(x, this.inputNames, this.feedInputShapes, true);\n    const batchSize = (Array.isArray(x) ? x[0] : x).shape[0];\n    return this.predictLoop(x, batchSize);\n  }\n  standardizeUserDataXY(x, y, checkBatchAxis = true, batchSize) {\n    if (this.optimizer_ == null) {\n      throw new RuntimeError(\"You must compile a model before training/testing. Use LayersModel.compile(modelCompileArgs).\");\n    }\n    const outputShapes = [];\n    for (let i2 = 0; i2 < this.feedOutputShapes.length; ++i2) {\n      const outputShape = this.feedOutputShapes[i2];\n      const lossFn = this.feedLossFns[i2];\n      if (lossFn === sparseCategoricalCrossentropy) {\n        outputShapes.push(outputShape.slice(0, outputShape.length - 1).concat([1]));\n      } else {\n        outputShapes.push(outputShape);\n      }\n    }\n    x = standardizeInputData(x, this.feedInputNames, this.feedInputShapes, false, \"input\");\n    y = standardizeInputData(y, this.feedOutputNames, outputShapes, false, \"target\");\n    checkArrayLengths(x, y, null);\n    checkLossAndTargetCompatibility(y, this.feedLossFns, this.feedOutputShapes);\n    if (this.stateful && batchSize != null && batchSize > 0) {\n      if (x[0].shape[0] % batchSize !== 0) {\n        throw new ValueError(`In a stateful network, you should only pass inputs with a number of samples that is divisible by the batch size ${batchSize}. Found: ${x[0].shape[0]} sample(s).`);\n      }\n    }\n    return [x, y];\n  }\n  async standardizeUserData(x, y, sampleWeight, classWeight, checkBatchAxis = true, batchSize) {\n    const [standardXs, standardYs] = this.standardizeUserDataXY(x, y, checkBatchAxis, batchSize);\n    if (sampleWeight != null) {\n      throw new Error(\"sample weight is not supported yet.\");\n    }\n    let standardSampleWeights = null;\n    if (classWeight != null) {\n      const classWeights = standardizeClassWeights(classWeight, this.outputNames);\n      standardSampleWeights = [];\n      for (let i2 = 0; i2 < classWeights.length; ++i2) {\n        standardSampleWeights.push(await standardizeWeights(standardYs[i2], null, classWeights[i2]));\n      }\n    }\n    return [standardXs, standardYs, standardSampleWeights];\n  }\n  testLoop(f, ins, batchSize, verbose = 0, steps) {\n    return tidy(() => {\n      const numSamples = this.checkNumSamples(ins, batchSize, steps, \"steps\");\n      const outs = [];\n      if (verbose > 0) {\n        throw new NotImplementedError(\"Verbose mode is not implemented yet.\");\n      }\n      if (steps != null) {\n        throw new NotImplementedError(\"steps mode in testLoop() is not implemented yet\");\n      } else {\n        const batches = makeBatches(numSamples, batchSize);\n        const indexArray = tensor1d(range2(0, numSamples));\n        for (let batchIndex = 0; batchIndex < batches.length; ++batchIndex) {\n          const batchStart = batches[batchIndex][0];\n          const batchEnd = batches[batchIndex][1];\n          const batchIds = sliceAlongFirstAxis(indexArray, batchStart, batchEnd - batchStart);\n          const insBatch = sliceArraysByIndices(ins, batchIds);\n          const batchOuts = f(insBatch);\n          if (batchIndex === 0) {\n            for (let i2 = 0; i2 < batchOuts.length; ++i2) {\n              outs.push(scalar(0));\n            }\n          }\n          for (let i2 = 0; i2 < batchOuts.length; ++i2) {\n            const batchOut = batchOuts[i2];\n            outs[i2] = add2(outs[i2], mul(batchEnd - batchStart, batchOut));\n          }\n        }\n        for (let i2 = 0; i2 < outs.length; ++i2) {\n          outs[i2] = div(outs[i2], numSamples);\n        }\n      }\n      return outs;\n    });\n  }\n  getDedupedMetricsNames() {\n    const outLabels = this.metricsNames;\n    const dedupedOutLabels = [];\n    for (let i2 = 0; i2 < outLabels.length; ++i2) {\n      const label = outLabels[i2];\n      let newLabel = label;\n      if (count(outLabels, label) > 1) {\n        const dupIndex = count(outLabels.slice(0, i2), label);\n        newLabel += `_${dupIndex}`;\n      }\n      dedupedOutLabels.push(newLabel);\n    }\n    return dedupedOutLabels;\n  }\n  makeTrainFunction() {\n    return (data) => {\n      const lossValues = [];\n      const inputs = data.slice(0, this.inputs.length);\n      const targets = data.slice(this.inputs.length, this.inputs.length + this.outputs.length);\n      const sampleWeights = data.slice(this.inputs.length + this.outputs.length, this.inputs.length + this.outputs.length * 2);\n      const metricsValues = [];\n      const totalLossFunction = () => {\n        const feeds = [];\n        for (let i2 = 0; i2 < this.inputs.length; ++i2) {\n          feeds.push({ key: this.inputs[i2], value: inputs[i2] });\n        }\n        const feedDict = new FeedDict(feeds);\n        const outputs = execute(this.outputs, feedDict, { \"training\": true });\n        let totalLoss;\n        for (let i2 = 0; i2 < this.lossFunctions.length; ++i2) {\n          const lossFunction = this.lossFunctions[i2];\n          let loss = lossFunction(targets[i2], outputs[i2]);\n          if (sampleWeights[i2] != null) {\n            loss = computeWeightedLoss2(loss, sampleWeights[i2]);\n          }\n          const meanLoss = mean(loss);\n          lossValues.push(meanLoss);\n          if (i2 === 0) {\n            totalLoss = loss;\n          } else {\n            totalLoss = add2(totalLoss, loss);\n          }\n        }\n        for (let i2 = 0; i2 < this.metricsTensors.length; ++i2) {\n          let weightedMetric;\n          if (this.outputs.length > 1 && i2 < this.outputs.length) {\n            weightedMetric = lossValues[i2];\n          } else {\n            const metric = this.metricsTensors[i2][0];\n            const outputIndex = this.metricsTensors[i2][1];\n            weightedMetric = mean(metric(targets[outputIndex], outputs[outputIndex]));\n          }\n          keep(weightedMetric);\n          metricsValues.push(weightedMetric);\n        }\n        totalLoss = mean(totalLoss);\n        this.calculateLosses().forEach((regularizerLoss) => {\n          totalLoss = add2(totalLoss, regularizerLoss);\n        });\n        return totalLoss;\n      };\n      const variables = this.collectedTrainableWeights.map((param) => param.read());\n      const returnCost = true;\n      const totalLossValue = this.optimizer_.minimize(totalLossFunction, returnCost, variables);\n      return [totalLossValue].concat(metricsValues);\n    };\n  }\n  makeTestFunction() {\n    this.testFunction = (data) => {\n      return tidy(() => {\n        const valOutputs = [];\n        let totalLoss;\n        const inputs = data.slice(0, this.inputs.length);\n        const targets = data.slice(this.inputs.length, this.inputs.length + this.outputs.length);\n        const feeds = [];\n        for (let i2 = 0; i2 < this.inputs.length; ++i2) {\n          feeds.push({ key: this.inputs[i2], value: inputs[i2] });\n        }\n        const feedDict = new FeedDict(feeds);\n        const outputs = execute(this.outputs, feedDict);\n        for (let i2 = 0; i2 < this.lossFunctions.length; ++i2) {\n          const lossFunction = this.lossFunctions[i2];\n          const loss = mean(lossFunction(targets[i2], outputs[i2]));\n          if (i2 === 0) {\n            totalLoss = loss;\n          } else {\n            totalLoss = add2(totalLoss, loss);\n          }\n          valOutputs.push(totalLoss);\n        }\n        for (let i2 = 0; i2 < this.metricsTensors.length; ++i2) {\n          const metric = this.metricsTensors[i2][0];\n          const outputIndex = this.metricsTensors[i2][1];\n          const meanMetric = mean(metric(targets[outputIndex], outputs[outputIndex]));\n          valOutputs.push(meanMetric);\n        }\n        return valOutputs;\n      });\n    };\n  }\n  async fit(x, y, args = {}) {\n    return fitTensors(this, x, y, args);\n  }\n  async fitDataset(dataset, args) {\n    return fitDataset(this, dataset, args);\n  }\n  async trainOnBatch(x, y) {\n    const standardizeOut = await this.standardizeUserData(x, y);\n    const inputs = standardizeOut[0];\n    const targets = standardizeOut[1];\n    const trainFunction = this.makeTrainFunction();\n    const losses2 = trainFunction(inputs.concat(targets));\n    const lossValues = [];\n    for (const loss of losses2) {\n      const v = await loss.data();\n      lossValues.push(v[0]);\n    }\n    dispose(losses2);\n    disposeNewTensors(standardizeOut[0], x);\n    disposeNewTensors(standardizeOut[1], y);\n    return singletonOrArray(lossValues);\n  }\n  getNamedWeights(config) {\n    const namedWeights = [];\n    const trainableOnly = config != null && config.trainableOnly;\n    const weights = trainableOnly ? this.trainableWeights : this.weights;\n    const weightValues = this.getWeights(trainableOnly);\n    for (let i2 = 0; i2 < weights.length; ++i2) {\n      if (trainableOnly && !weights[i2].trainable) {\n        continue;\n      }\n      namedWeights.push({ name: weights[i2].originalName, tensor: weightValues[i2] });\n    }\n    return namedWeights;\n  }\n  set stopTraining(stop) {\n    this.stopTraining_ = stop;\n  }\n  get stopTraining() {\n    return this.stopTraining_;\n  }\n  get optimizer() {\n    return this.optimizer_;\n  }\n  set optimizer(optimizer) {\n    if (this.optimizer_ !== optimizer) {\n      this.optimizer_ = optimizer;\n      this.isOptimizerOwned = false;\n    }\n  }\n  dispose() {\n    const result = super.dispose();\n    if (result.refCountAfterDispose === 0 && this.optimizer != null && this.isOptimizerOwned) {\n      const numTensorsBeforeOptmizerDisposal = memory().numTensors;\n      this.optimizer_.dispose();\n      result.numDisposedVariables += numTensorsBeforeOptmizerDisposal - memory().numTensors;\n    }\n    return result;\n  }\n  getLossIdentifiers() {\n    let lossNames;\n    if (typeof this.loss === \"string\") {\n      lossNames = toSnakeCase(this.loss);\n    } else if (Array.isArray(this.loss)) {\n      for (const loss of this.loss) {\n        if (typeof loss !== \"string\") {\n          throw new Error(\"Serialization of non-string loss is not supported.\");\n        }\n      }\n      lossNames = this.loss.map((name) => toSnakeCase(name));\n    } else {\n      const outputNames = Object.keys(this.loss);\n      lossNames = {};\n      const losses2 = this.loss;\n      for (const outputName of outputNames) {\n        if (typeof losses2[outputName] === \"string\") {\n          lossNames[outputName] = toSnakeCase(losses2[outputName]);\n        } else {\n          throw new Error(\"Serialization of non-string loss is not supported.\");\n        }\n      }\n    }\n    return lossNames;\n  }\n  getMetricIdentifiers() {\n    if (typeof this.metrics === \"string\" || typeof this.metrics === \"function\") {\n      return [toSnakeCase(getLossOrMetricName(this.metrics))];\n    } else if (Array.isArray(this.metrics)) {\n      return this.metrics.map((metric) => toSnakeCase(getLossOrMetricName(metric)));\n    } else {\n      const metricsIdentifiers = {};\n      for (const key in this.metrics) {\n        metricsIdentifiers[key] = toSnakeCase(getLossOrMetricName(this.metrics[key]));\n      }\n      return metricsIdentifiers;\n    }\n  }\n  getTrainingConfig() {\n    return {\n      loss: this.getLossIdentifiers(),\n      metrics: this.getMetricIdentifiers(),\n      optimizer_config: {\n        class_name: this.optimizer.getClassName(),\n        config: this.optimizer.getConfig()\n      }\n    };\n  }\n  loadTrainingConfig(trainingConfig) {\n    if (trainingConfig.weighted_metrics != null) {\n      throw new Error(\"Loading weight_metrics is not supported yet.\");\n    }\n    if (trainingConfig.loss_weights != null) {\n      throw new Error(\"Loading loss_weights is not supported yet.\");\n    }\n    if (trainingConfig.sample_weight_mode != null) {\n      throw new Error(\"Loading sample_weight_mode is not supported yet.\");\n    }\n    const tsConfig = convertPythonicToTs(trainingConfig.optimizer_config);\n    const optimizer = deserialize(tsConfig);\n    let loss;\n    if (typeof trainingConfig.loss === \"string\") {\n      loss = toCamelCase(trainingConfig.loss);\n    } else if (Array.isArray(trainingConfig.loss)) {\n      loss = trainingConfig.loss.map((lossEntry) => toCamelCase(lossEntry));\n    } else if (trainingConfig.loss != null) {\n      loss = {};\n      for (const key in trainingConfig.loss) {\n        loss[key] = toCamelCase(trainingConfig.loss[key]);\n      }\n    }\n    let metrics;\n    if (Array.isArray(trainingConfig.metrics)) {\n      metrics = trainingConfig.metrics.map((metric) => toCamelCase(metric));\n    } else if (trainingConfig.metrics != null) {\n      metrics = {};\n      for (const key in trainingConfig.metrics) {\n        metrics[key] = toCamelCase(trainingConfig.metrics[key]);\n      }\n    }\n    this.compile({ loss, metrics, optimizer });\n  }\n  async save(handlerOrURL, config) {\n    if (typeof handlerOrURL === \"string\") {\n      const handlers = io_exports.getSaveHandlers(handlerOrURL);\n      if (handlers.length === 0) {\n        throw new ValueError(`Cannot find any save handlers for URL '${handlerOrURL}'`);\n      } else if (handlers.length > 1) {\n        throw new ValueError(`Found more than one (${handlers.length}) save handlers for URL '${handlerOrURL}'`);\n      }\n      handlerOrURL = handlers[0];\n    }\n    if (handlerOrURL.save == null) {\n      throw new ValueError(\"LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.\");\n    }\n    const weightDataAndSpecs = await io_exports.encodeWeights(this.getNamedWeights(config));\n    const returnString = false;\n    const unusedArg = null;\n    const modelConfig = this.toJSON(unusedArg, returnString);\n    const modelArtifacts = {\n      modelTopology: modelConfig,\n      format: LAYERS_MODEL_FORMAT_NAME,\n      generatedBy: `TensorFlow.js tfjs-layers v${version2}`,\n      convertedBy: null\n    };\n    const includeOptimizer = config == null ? false : config.includeOptimizer;\n    if (includeOptimizer && this.optimizer != null) {\n      modelArtifacts.trainingConfig = this.getTrainingConfig();\n      const weightType = \"optimizer\";\n      const { data: optimizerWeightData, specs: optimizerWeightSpecs } = await io_exports.encodeWeights(await this.optimizer.getWeights(), weightType);\n      weightDataAndSpecs.specs.push(...optimizerWeightSpecs);\n      weightDataAndSpecs.data = io_exports.concatenateArrayBuffers([weightDataAndSpecs.data, optimizerWeightData]);\n    }\n    if (this.userDefinedMetadata != null) {\n      const checkSize = true;\n      checkUserDefinedMetadata(this.userDefinedMetadata, this.name, checkSize);\n      modelArtifacts.userDefinedMetadata = this.userDefinedMetadata;\n    }\n    modelArtifacts.weightData = weightDataAndSpecs.data;\n    modelArtifacts.weightSpecs = weightDataAndSpecs.specs;\n    return handlerOrURL.save(modelArtifacts);\n  }\n  setUserDefinedMetadata(userDefinedMetadata) {\n    checkUserDefinedMetadata(userDefinedMetadata, this.name);\n    this.userDefinedMetadata = userDefinedMetadata;\n  }\n  getUserDefinedMetadata() {\n    return this.userDefinedMetadata;\n  }\n};\nLayersModel.className = \"Model\";\nserialization_exports.registerClass(LayersModel);\nvar Functional = class extends LayersModel {\n};\nFunctional.className = \"Functional\";\nserialization_exports.registerClass(Functional);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/models.js\nasync function modelFromJSON(modelAndWeightsConfig, customObjects) {\n  if (!(\"modelTopology\" in modelAndWeightsConfig)) {\n    modelAndWeightsConfig = { modelTopology: modelAndWeightsConfig };\n  }\n  modelAndWeightsConfig = modelAndWeightsConfig;\n  let modelTopology = modelAndWeightsConfig.modelTopology;\n  if (modelTopology[\"model_config\"] != null) {\n    modelTopology = modelTopology[\"model_config\"];\n  }\n  const tsConfig = convertPythonicToTs(modelTopology);\n  const model2 = deserialize(tsConfig, customObjects);\n  if (modelAndWeightsConfig.weightsManifest != null) {\n    const weightValues = await io_exports.loadWeights(modelAndWeightsConfig.weightsManifest, modelAndWeightsConfig.pathPrefix, model2.weights.map((weight) => weight.originalName));\n    const uniqueWeightValues = {};\n    for (const weight of model2.weights) {\n      uniqueWeightValues[weight.originalName] = weightValues[weight.originalName];\n    }\n    model2.loadWeights(uniqueWeightValues);\n    dispose(weightValues);\n  }\n  return model2;\n}\nasync function loadLayersModelInternal(pathOrIOHandler, options) {\n  if (options == null) {\n    options = {};\n  }\n  if (typeof pathOrIOHandler === \"string\") {\n    const handlers = io_exports.getLoadHandlers(pathOrIOHandler, options);\n    if (handlers.length === 0) {\n      handlers.push(io_exports.browserHTTPRequest(pathOrIOHandler, options));\n    } else if (handlers.length > 1) {\n      throw new ValueError(`Found more than one (${handlers.length}) load handlers for URL '${pathOrIOHandler}'`);\n    }\n    pathOrIOHandler = handlers[0];\n  }\n  return loadLayersModelFromIOHandler(pathOrIOHandler, void 0, options);\n}\nasync function loadLayersModelFromIOHandler(handler, customObjects, options) {\n  if (options == null) {\n    options = {};\n  }\n  if (handler.load == null) {\n    throw new ValueError(\"Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.\");\n  }\n  const artifacts = await handler.load();\n  let modelTopology = artifacts.modelTopology;\n  if (modelTopology[\"model_config\"] != null) {\n    modelTopology = modelTopology[\"model_config\"];\n  }\n  const strict = options.strict == null ? true : options.strict;\n  const fastWeightInit = artifacts.weightData != null && artifacts.weightSpecs != null && strict;\n  const model2 = deserialize(convertPythonicToTs(modelTopology), customObjects, fastWeightInit);\n  const trainingConfig = artifacts.trainingConfig;\n  if (trainingConfig != null) {\n    model2.loadTrainingConfig(trainingConfig);\n  }\n  if (artifacts.userDefinedMetadata != null) {\n    model2.setUserDefinedMetadata(artifacts.userDefinedMetadata);\n  }\n  if (artifacts.weightData != null) {\n    if (artifacts.weightSpecs == null) {\n      throw new ValueError(\"LayersModel artifacts contains weight data, but not weight specs. Therefore loading of weights cannot proceed.\");\n    }\n    const { modelWeights, optimizerWeights } = decodeModelAndOptimizerWeights(artifacts.weightData, artifacts.weightSpecs);\n    model2.loadWeights(modelWeights, strict);\n    if (model2.optimizer != null && optimizerWeights.length > 0) {\n      await model2.optimizer.setWeights(optimizerWeights);\n    }\n    dispose(modelWeights);\n    dispose(optimizerWeights.map((w) => w.tensor));\n  }\n  return model2;\n}\nfunction decodeModelAndOptimizerWeights(buffer2, specs) {\n  const name2Tensor = io_exports.decodeWeights(buffer2, specs);\n  const modelWeights = {};\n  const optimizerWeights = [];\n  specs.forEach((spec) => {\n    if (spec.group === \"optimizer\") {\n      optimizerWeights.push({ name: spec.name, tensor: name2Tensor[spec.name] });\n    } else {\n      modelWeights[spec.name] = name2Tensor[spec.name];\n    }\n  });\n  return { modelWeights, optimizerWeights };\n}\nvar Sequential = class extends LayersModel {\n  constructor(args) {\n    super({ inputs: [], outputs: [] });\n    args = args || {};\n    this.trainable = true;\n    this.built = false;\n    this.name = args.name != null ? args.name : getUid(\"sequential_\");\n    if (args.layers != null) {\n      for (const layer of args.layers) {\n        this.add(layer);\n      }\n    }\n  }\n  checkShape(layer) {\n    const shape = layer.inboundNodes[0].outputTensors[0].shape;\n    if (shape.some((x) => x < 0)) {\n      throw new ValueError(`Negative dimension size caused by adding layer ${layer.name} with input shape [${layer.inboundNodes[0].inputTensors[0].shape}]`);\n    }\n  }\n  add(layer) {\n    const isLayerModelInstance = layer instanceof Sequential || layer instanceof LayersModel;\n    let modelLayer;\n    if (isLayerModelInstance) {\n      modelLayer = layer;\n      if (modelLayer.outputs.length !== 1) {\n        throw new ValueError(\"All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.\");\n      }\n      if (modelLayer.inputs.length !== 1) {\n        throw new ValueError(\"All layers in a Sequential model should have a single input tensor. For multi-input layers, use the functional API.\");\n      }\n    }\n    if (this.outputs.length === 0) {\n      if (layer.inboundNodes.length === 0) {\n        if (layer.batchInputShape == null) {\n          throw new ValueError(\"The first layer in a Sequential model must get an `inputShape` or `batchInputShape` argument.\");\n        }\n        const x = Input({\n          batchShape: layer.batchInputShape,\n          dtype: layer.dtype,\n          name: layer.name + \"_input\"\n        });\n        layer.apply(x);\n      }\n      if (isLayerModelInstance) {\n        this.outputs = modelLayer.outputs;\n        this.inputs = modelLayer.inputs;\n      } else {\n        if (layer.inboundNodes.length !== 1) {\n          throw new ValueError(`A layer added to a Sequential model must not already be connected somewhere else. LayersModel received layer ${layer.name} which has ${layer.inboundNodes.length} pre-existing inbound connections.`);\n        }\n        if (layer.inboundNodes[0].outputTensors.length !== 1) {\n          throw new ValueError(\"All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.\");\n        }\n        this.checkShape(layer);\n        this.outputs = [layer.inboundNodes[0].outputTensors[0]];\n        this.inputs = getSourceInputs(this.outputs[0]);\n      }\n      this.inboundNodes = [];\n      new Node({\n        outboundLayer: this,\n        inboundLayers: [],\n        nodeIndices: [],\n        tensorIndices: [],\n        inputTensors: this.inputs,\n        outputTensors: this.outputs,\n        inputMasks: pyListRepeat(null, this.inputs.length),\n        outputMasks: [null],\n        inputShapes: this.inputs.map((x) => x.shape),\n        outputShapes: this.outputs[0].shape\n      });\n    } else {\n      const outputTensor = layer.apply(this.outputs[0]);\n      if (Array.isArray(outputTensor)) {\n        throw new TypeError(\"All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.\");\n      }\n      this.checkShape(layer);\n      this.outputs = [outputTensor];\n      this.inboundNodes[0].outputTensors = this.outputs;\n      this.inboundNodes[0].outputShapes = [this.outputs[0].shape];\n    }\n    this.layers.push(layer);\n    this.built = false;\n  }\n  pop() {\n    if (this.layers.length === 0) {\n      throw new TypeError(\"There are no layers in the model.\");\n    }\n    this.layers.pop();\n    if (this.layers.length === 0) {\n      this.outputs = [];\n      this.inboundNodes = [];\n      this.outboundNodes = [];\n    } else {\n      const lastLayerIndex = this.layers.length - 1;\n      this.layers[lastLayerIndex].outboundNodes = [];\n      this.outputs = [this.layers[lastLayerIndex].output];\n      this.inboundNodes[0].outputTensors = this.outputs;\n      this.inboundNodes[0].outputShapes = [this.outputs[0].shape];\n    }\n  }\n  call(inputs, kwargs) {\n    if (this.model == null) {\n      this.build();\n    }\n    return this.model.call(inputs, kwargs);\n  }\n  build(inputShape) {\n    getExactlyOneShape(inputShape);\n    if (this.inputs.length === 0 || this.outputs.length === 0) {\n      throw new TypeError(\"Sequential model cannot be built: model is empty. Add some layers first.\");\n    }\n    this.model = new LayersModel({\n      inputs: this.inputs,\n      outputs: this.outputs[0],\n      name: this.name + \"_model\"\n    });\n    this.model.trainable = this.trainable;\n    this.supportsMasking = this.model.supportsMasking;\n    this.inputLayers = this.model.inputLayers;\n    this.inputLayersNodeIndices = this.model.inputLayersNodeIndices;\n    this.inputLayersTensorIndices = this.model.inputLayersTensorIndices;\n    this.outputLayers = this.model.outputLayers;\n    this.outputLayersNodeIndices = this.model.outputLayersNodeIndices;\n    this.outputLayersTensorIndices = this.model.outputLayersTensorIndices;\n    this.nodesByDepth = this.model.nodesByDepth;\n    this.containerNodes = this.model.containerNodes;\n    this.outputNames = this.model.outputNames;\n    this.inputNames = this.model.inputNames;\n    this.built = true;\n  }\n  countParams() {\n    if (!this.built) {\n      this.build();\n    }\n    return super.countParams();\n  }\n  summary(lineLength, positions, printFn = console.log) {\n    if (!this.built) {\n      this.build();\n    }\n    super.summary(lineLength, positions, printFn);\n  }\n  setWeights(weights) {\n    if (this.model == null) {\n      this.build();\n    }\n    this.model.setWeights(weights);\n  }\n  evaluate(x, y, args = {}) {\n    if (!this.built) {\n      throw new RuntimeError(\"The model needs to be compiled before being used.\");\n    }\n    return this.model.evaluate(x, y, args);\n  }\n  async evaluateDataset(dataset, args) {\n    if (!this.built) {\n      throw new RuntimeError(\"The model needs to be compiled before being used.\");\n    }\n    return this.model.evaluateDataset(dataset, args);\n  }\n  predict(x, args = {}) {\n    if (this.model == null) {\n      this.build();\n    }\n    return this.model.predict(x, args);\n  }\n  predictOnBatch(x) {\n    if (this.model == null) {\n      this.build();\n    }\n    return this.model.predictOnBatch(x);\n  }\n  compile(args) {\n    this.build();\n    this.model.compile(args);\n    this.optimizer_ = this.model.optimizer;\n    this.isOptimizerOwned = this.model.isOptimizerOwned;\n    this.loss = this.model.loss;\n    this.metrics = this.model.metrics;\n    this.metricsTensors = this.model.metricsTensors;\n    this.metricsNames = this.model.metricsNames;\n  }\n  get optimizer() {\n    return this.model == null ? void 0 : this.model.optimizer;\n  }\n  set optimizer(optimizer) {\n    this.model.optimizer = optimizer;\n  }\n  async fit(x, y, args = {}) {\n    if (!this.built) {\n      throw new RuntimeError(\"The model needs to be compiled before being used.\");\n    }\n    return this.model.fit(x, y, args);\n  }\n  async fitDataset(dataset, args) {\n    if (!this.built) {\n      throw new RuntimeError(\"The model needs to be compiled before being used.\");\n    }\n    return this.model.fitDataset(dataset, args);\n  }\n  async trainOnBatch(x, y) {\n    return this.model.trainOnBatch(x, y);\n  }\n  static fromConfig(cls, config, customObjects = {}, fastWeightInit = false) {\n    let configArray;\n    let extraModelConfig = {};\n    if (config instanceof Array) {\n      if (!(config[0].className != null) || config[0][\"className\"] === \"Merge\") {\n        throw new ValueError(\"Legacy serialization format not supported yet.\");\n      }\n      configArray = config;\n    } else {\n      util_exports.assert(config[\"layers\"] != null, () => `When the config data for a Sequential model is not an Array, it must be an Object that contains the 'layers' field.`);\n      configArray = config[\"layers\"];\n      delete config[\"layers\"];\n      extraModelConfig = config;\n    }\n    const model2 = new cls(extraModelConfig);\n    if (!(model2 instanceof Sequential)) {\n      throw new NotImplementedError(`Sequential.fromConfig called on non-Sequential input: ${model2}`);\n    }\n    for (const conf of configArray) {\n      const customObjects2 = void 0;\n      const layer = deserialize(conf, customObjects2, fastWeightInit);\n      if (fastWeightInit) {\n        layer.setFastWeightInitDuringBuild(true);\n      }\n      model2.add(layer);\n    }\n    return model2;\n  }\n  set stopTraining(stop) {\n    if (this.model == null) {\n      throw new ValueError(\"Cannot set the stopTraining property of a sequential model before it is compiled.\");\n    }\n    this.model.stopTraining = stop;\n  }\n  get stopTraining() {\n    if (this.model == null) {\n      throw new ValueError(\"Cannot get the stopTraining property of a sequential model before it is compiled.\");\n    }\n    return this.model.stopTraining;\n  }\n  getConfig() {\n    const layers = [];\n    for (const layer of this.layers) {\n      const dict = {};\n      dict[\"className\"] = layer.getClassName();\n      dict[\"config\"] = layer.getConfig();\n      layers.push(dict);\n    }\n    return { name: this.name, layers };\n  }\n};\nSequential.className = \"Sequential\";\nserialization_exports.registerClass(Sequential);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports.js\nfunction model(args) {\n  return new LayersModel(args);\n}\nfunction sequential(config) {\n  return new Sequential(config);\n}\nfunction loadLayersModel(pathOrIOHandler, options) {\n  if (options == null) {\n    options = {};\n  }\n  return loadLayersModelInternal(pathOrIOHandler, options);\n}\nfunction input(config) {\n  return Input(config);\n}\nfunction registerCallbackConstructor(verbosityLevel, callbackConstructor) {\n  CallbackConstructorRegistry.registerCallbackConstructor(verbosityLevel, callbackConstructor);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/activations.js\nvar Activation = class extends serialization_exports.Serializable {\n  getConfig() {\n    return {};\n  }\n};\nvar Elu2 = class extends Activation {\n  apply(x, alpha = 1) {\n    return elu2(x, alpha);\n  }\n};\nElu2.className = \"elu\";\nserialization_exports.registerClass(Elu2);\nvar Selu2 = class extends Activation {\n  apply(x) {\n    return selu(x);\n  }\n};\nSelu2.className = \"selu\";\nserialization_exports.registerClass(Selu2);\nvar Relu2 = class extends Activation {\n  apply(x) {\n    return relu(x);\n  }\n};\nRelu2.className = \"relu\";\nserialization_exports.registerClass(Relu2);\nvar Relu62 = class extends Activation {\n  apply(x) {\n    return tidy(() => minimum(6, relu(x)));\n  }\n};\nRelu62.className = \"relu6\";\nserialization_exports.registerClass(Relu62);\nvar Linear = class extends Activation {\n  apply(x) {\n    return x;\n  }\n};\nLinear.className = \"linear\";\nserialization_exports.registerClass(Linear);\nvar Sigmoid2 = class extends Activation {\n  apply(x) {\n    return sigmoid(x);\n  }\n};\nSigmoid2.className = \"sigmoid\";\nserialization_exports.registerClass(Sigmoid2);\nvar HardSigmoid = class extends Activation {\n  apply(x) {\n    return hardSigmoid(x);\n  }\n};\nHardSigmoid.className = \"hardSigmoid\";\nserialization_exports.registerClass(HardSigmoid);\nvar Softplus2 = class extends Activation {\n  apply(x) {\n    return softplus(x);\n  }\n};\nSoftplus2.className = \"softplus\";\nserialization_exports.registerClass(Softplus2);\nvar Softsign = class extends Activation {\n  apply(x) {\n    return softsign(x);\n  }\n};\nSoftsign.className = \"softsign\";\nserialization_exports.registerClass(Softsign);\nvar Tanh2 = class extends Activation {\n  apply(x) {\n    return tanh2(x);\n  }\n};\nTanh2.className = \"tanh\";\nserialization_exports.registerClass(Tanh2);\nvar Softmax2 = class extends Activation {\n  apply(x, axis = -1) {\n    return softmax(x, axis);\n  }\n};\nSoftmax2.className = \"softmax\";\nserialization_exports.registerClass(Softmax2);\nvar LogSoftmax2 = class extends Activation {\n  apply(x, axis = -1) {\n    return logSoftmax(x, axis);\n  }\n};\nLogSoftmax2.className = \"logSoftmax\";\nserialization_exports.registerClass(LogSoftmax2);\nvar Swish = class extends Activation {\n  apply(x, alpha = 1) {\n    return tidy(() => mul(sigmoid(mul(x, alpha)), x));\n  }\n};\nSwish.className = \"swish\";\nserialization_exports.registerClass(Swish);\nvar Mish = class extends Activation {\n  apply(x) {\n    return tidy(() => mul(x, tanh2(softplus(x))));\n  }\n};\nMish.className = \"mish\";\nserialization_exports.registerClass(Mish);\nfunction serializeActivation(activation2) {\n  return activation2.getClassName();\n}\nfunction deserializeActivation(config, customObjects = {}) {\n  return deserializeKerasObject(config, serialization_exports.SerializationMap.getMap().classNameMap, customObjects, \"activation\");\n}\nfunction getActivation(identifier) {\n  if (identifier == null) {\n    const config = {};\n    config[\"className\"] = \"linear\";\n    config[\"config\"] = {};\n    return deserializeActivation(config);\n  }\n  if (typeof identifier === \"string\") {\n    const config = {};\n    config[\"className\"] = identifier;\n    config[\"config\"] = {};\n    return deserializeActivation(config);\n  } else if (identifier instanceof Activation) {\n    return identifier;\n  } else {\n    return deserializeActivation(identifier);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/regularizers.js\nfunction assertObjectArgs(args) {\n  if (args != null && typeof args !== \"object\") {\n    throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${args}`);\n  }\n}\nvar Regularizer = class extends serialization_exports.Serializable {\n};\nvar L1L2 = class extends Regularizer {\n  constructor(args) {\n    super();\n    assertObjectArgs(args);\n    this.l1 = args == null || args.l1 == null ? 0.01 : args.l1;\n    this.l2 = args == null || args.l2 == null ? 0.01 : args.l2;\n    this.hasL1 = this.l1 !== 0;\n    this.hasL2 = this.l2 !== 0;\n  }\n  apply(x) {\n    return tidy(() => {\n      let regularization = zeros([1]);\n      if (this.hasL1) {\n        regularization = add2(regularization, sum2(mul(this.l1, abs(x))));\n      }\n      if (this.hasL2) {\n        regularization = add2(regularization, sum2(mul(this.l2, square2(x))));\n      }\n      return reshape(regularization, []);\n    });\n  }\n  getConfig() {\n    return { \"l1\": this.l1, \"l2\": this.l2 };\n  }\n  static fromConfig(cls, config) {\n    return new cls({ l1: config[\"l1\"], l2: config[\"l2\"] });\n  }\n};\nL1L2.className = \"L1L2\";\nserialization_exports.registerClass(L1L2);\nfunction l1(args) {\n  assertObjectArgs(args);\n  return new L1L2({ l1: args != null ? args.l1 : null, l2: 0 });\n}\nfunction l2(args) {\n  assertObjectArgs(args);\n  return new L1L2({ l2: args != null ? args.l2 : null, l1: 0 });\n}\nvar REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP = {\n  \"l1l2\": \"L1L2\"\n};\nfunction serializeRegularizer(constraint) {\n  return serializeKerasObject(constraint);\n}\nfunction deserializeRegularizer(config, customObjects = {}) {\n  return deserializeKerasObject(config, serialization_exports.SerializationMap.getMap().classNameMap, customObjects, \"regularizer\");\n}\nfunction getRegularizer(identifier) {\n  if (identifier == null) {\n    return null;\n  }\n  if (typeof identifier === \"string\") {\n    const className = identifier in REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP ? REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP[identifier] : identifier;\n    const config = { className, config: {} };\n    return deserializeRegularizer(config);\n  } else if (identifier instanceof Regularizer) {\n    return identifier;\n  } else {\n    return deserializeRegularizer(identifier);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/advanced_activations.js\nvar ReLU = class extends Layer {\n  constructor(args) {\n    super(args == null ? {} : args);\n    this.supportsMasking = true;\n    if (args != null) {\n      this.maxValue = args.maxValue;\n    }\n  }\n  call(inputs, kwargs) {\n    inputs = getExactlyOneTensor(inputs);\n    let output = relu(inputs);\n    if (this.maxValue != null) {\n      output = clipByValue(output, 0, this.maxValue);\n    }\n    return output;\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const config = { maxValue: this.maxValue };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nReLU.className = \"ReLU\";\nserialization_exports.registerClass(ReLU);\nvar LeakyReLU = class extends Layer {\n  constructor(args) {\n    super(args == null ? {} : args);\n    this.DEFAULT_ALPHA = 0.3;\n    if (args == null) {\n      args = {};\n    }\n    this.alpha = args.alpha == null ? this.DEFAULT_ALPHA : args.alpha;\n  }\n  call(inputs, kwargs) {\n    const x = getExactlyOneTensor(inputs);\n    return leakyRelu(x, this.alpha);\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const config = { alpha: this.alpha };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nLeakyReLU.className = \"LeakyReLU\";\nserialization_exports.registerClass(LeakyReLU);\nvar PReLU = class extends Layer {\n  constructor(args) {\n    super(args == null ? {} : args);\n    this.DEFAULT_ALPHA_INITIALIZER = \"zeros\";\n    if (args == null) {\n      args = {};\n    }\n    this.supportsMasking = true;\n    this.alphaInitializer = getInitializer(args.alphaInitializer || this.DEFAULT_ALPHA_INITIALIZER);\n    this.alphaRegularizer = getRegularizer(args.alphaRegularizer);\n    this.alphaConstraint = getConstraint(args.alphaConstraint);\n    if (args.sharedAxes == null) {\n      this.sharedAxes = null;\n    } else if (Array.isArray(args.sharedAxes)) {\n      this.sharedAxes = args.sharedAxes;\n    } else if (typeof args.sharedAxes === \"number\") {\n      this.sharedAxes = [args.sharedAxes];\n    } else {\n      throw new ValueError(`Expected sharedAxes to be a number or an array of numbers, but got ${args.sharedAxes}`);\n    }\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const paramShape = inputShape.slice(1);\n    if (this.sharedAxes != null) {\n      for (const i2 of this.sharedAxes) {\n        paramShape[i2 - 1] = 1;\n      }\n    }\n    this.alpha = this.addWeight(\"alpha\", paramShape, \"float32\", this.alphaInitializer, this.alphaRegularizer, true, this.alphaConstraint);\n    const axes = {};\n    if (this.sharedAxes != null) {\n      for (let i2 = 1; i2 < inputShape.length; ++i2) {\n        axes[i2] = inputShape[i2];\n      }\n    }\n    this.inputSpec = [new InputSpec({\n      ndim: inputShape.length,\n      axes\n    })];\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    inputs = getExactlyOneTensor(inputs);\n    return prelu(inputs, this.alpha.read());\n  }\n  getConfig() {\n    const config = {\n      alphaInitializer: serializeInitializer(this.alphaInitializer),\n      alphaRegularizer: serializeRegularizer(this.alphaRegularizer),\n      alphaConstraint: serializeConstraint(this.alphaConstraint),\n      sharedAxes: this.sharedAxes\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nPReLU.className = \"PReLU\";\nserialization_exports.registerClass(PReLU);\nvar ELU = class extends Layer {\n  constructor(args) {\n    super(args == null ? {} : args);\n    this.DEFAULT_ALPHA = 1;\n    if (args == null) {\n      args = {};\n    }\n    if (args.alpha != null && args.alpha !== this.DEFAULT_ALPHA) {\n      throw new NotImplementedError(`Non-default alpha value (${args.alpha}) is not supported by the ELU layer yet.`);\n    }\n    this.alpha = args.alpha == null ? this.DEFAULT_ALPHA : args.alpha;\n  }\n  call(inputs, kwargs) {\n    const x = getExactlyOneTensor(inputs);\n    return elu(x);\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const config = { alpha: this.alpha };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nELU.className = \"ELU\";\nserialization_exports.registerClass(ELU);\nvar ThresholdedReLU = class extends Layer {\n  constructor(args) {\n    super(args == null ? {} : args);\n    this.DEFAULT_THETA = 1;\n    if (args == null) {\n      args = {};\n    }\n    this.theta = args.theta == null ? this.DEFAULT_THETA : args.theta;\n  }\n  call(inputs, kwargs) {\n    const x = getExactlyOneTensor(inputs);\n    return mul(x, cast(greater(x, this.theta), \"float32\"));\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const config = { theta: this.theta };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nThresholdedReLU.className = \"ThresholdedReLU\";\nserialization_exports.registerClass(ThresholdedReLU);\nvar Softmax3 = class extends Layer {\n  constructor(args) {\n    super(args == null ? {} : args);\n    this.DEFAULT_AXIS = 1;\n    if (args == null) {\n      args = {};\n    }\n    this.softmax = new Softmax2().apply;\n    this.axis = args.axis == null ? this.DEFAULT_AXIS : args.axis;\n  }\n  call(inputs, kwargs) {\n    const x = getExactlyOneTensor(inputs);\n    return this.softmax(x, this.axis);\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const config = { axis: this.axis };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nSoftmax3.className = \"Softmax\";\nserialization_exports.registerClass(Softmax3);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/conv_utils.js\nfunction normalizeArray(value, n2, name) {\n  if (typeof value === \"number\") {\n    return pyListRepeat(value, n2);\n  } else {\n    if (value.length !== n2) {\n      throw new ValueError(`The ${name} argument must be an integer or tuple of ${n2} integers. Received: ${value.length} elements.`);\n    }\n    for (let i2 = 0; i2 < n2; ++i2) {\n      const singleValue = value[i2];\n      if (!isInteger(singleValue)) {\n        throw new ValueError(`The ${name} argument must be an integer or tuple of ${n2} integers. Received: ${JSON.stringify(value)} including a non-integer number ${singleValue}`);\n      }\n    }\n    return value;\n  }\n}\nfunction convOutputLength(inputLength, filterSize, padding, stride, dilation = 1) {\n  if (inputLength == null) {\n    return inputLength;\n  }\n  const dilatedFilterSize = filterSize + (filterSize - 1) * (dilation - 1);\n  let outputLength;\n  if (padding === \"same\") {\n    outputLength = inputLength;\n  } else {\n    outputLength = inputLength - dilatedFilterSize + 1;\n  }\n  return Math.floor((outputLength + stride - 1) / stride);\n}\nfunction deconvLength(dimSize, strideSize, kernelSize, padding) {\n  if (dimSize == null) {\n    return null;\n  }\n  if (padding === \"valid\") {\n    dimSize = dimSize * strideSize + max2([kernelSize - strideSize, 0]);\n  } else if (padding === \"same\") {\n    dimSize = dimSize * strideSize;\n  } else {\n    throw new ValueError(`Unsupport padding mode: ${padding}.`);\n  }\n  return dimSize;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/convolutional.js\nfunction preprocessConv2DInput(x, dataFormat) {\n  return tidy(() => {\n    checkDataFormat(dataFormat);\n    if (dataFormat === \"channelsFirst\") {\n      return transpose(x, [0, 2, 3, 1]);\n    } else {\n      return x;\n    }\n  });\n}\nfunction preprocessConv3DInput(x, dataFormat) {\n  return tidy(() => {\n    checkDataFormat(dataFormat);\n    if (dataFormat === \"channelsFirst\") {\n      return transpose(x, [0, 2, 3, 4, 1]);\n    } else {\n      return x;\n    }\n  });\n}\nfunction conv1dWithBias(x, kernel, bias, strides = 1, padding = \"valid\", dataFormat, dilationRate = 1) {\n  return tidy(() => {\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    checkDataFormat(dataFormat);\n    if (x.shape.length !== 3) {\n      throw new ValueError(`The input of a conv1dWithBias operation should be 3, but is ${x.shape.length} instead.`);\n    }\n    if (kernel.shape.length !== 3) {\n      throw new ValueError(`The kernel for a conv1dWithBias operation should be 3, but is ${kernel.shape.length} instead`);\n    }\n    if (bias != null && bias.shape.length !== 1) {\n      throw new ValueError(`The bias for a conv1dWithBias operation should be 1, but is ${kernel.shape.length} instead`);\n    }\n    if (dataFormat === \"channelsFirst\") {\n      x = transpose(x, [0, 2, 1]);\n    }\n    if (padding === \"causal\") {\n      throw new NotImplementedError(\"The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.\");\n    }\n    let y = conv1d(x, kernel, strides, padding === \"same\" ? \"same\" : \"valid\", \"NWC\", dilationRate);\n    if (bias != null) {\n      y = biasAdd(y, bias);\n    }\n    return y;\n  });\n}\nfunction conv2dWithBiasActivation(x, kernel, bias, strides = [1, 1], padding = \"valid\", dataFormat, dilationRate, activation2 = null) {\n  return tidy(() => {\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    checkDataFormat(dataFormat);\n    if (x.rank !== 3 && x.rank !== 4) {\n      throw new ValueError(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${x.rank}.`);\n    }\n    if (kernel.rank !== 3 && kernel.rank !== 4) {\n      throw new ValueError(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${x.rank}.`);\n    }\n    let y = preprocessConv2DInput(x, dataFormat);\n    if (padding === \"causal\") {\n      throw new NotImplementedError(\"The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.\");\n    }\n    y = fused_ops_exports.conv2d({\n      x: y,\n      filter: kernel,\n      strides,\n      pad: padding === \"same\" ? \"same\" : \"valid\",\n      dilations: dilationRate,\n      dataFormat: \"NHWC\",\n      bias,\n      activation: activation2\n    });\n    if (dataFormat === \"channelsFirst\") {\n      y = transpose(y, [0, 3, 1, 2]);\n    }\n    return y;\n  });\n}\nfunction conv3dWithBias(x, kernel, bias, strides = [1, 1, 1], padding = \"valid\", dataFormat, dilationRate) {\n  return tidy(() => {\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    checkDataFormat(dataFormat);\n    if (x.rank !== 4 && x.rank !== 5) {\n      throw new ValueError(`conv3dWithBias expects input to be of rank 4 or 5, but received ${x.rank}.`);\n    }\n    if (kernel.rank !== 4 && kernel.rank !== 5) {\n      throw new ValueError(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${x.rank}.`);\n    }\n    let y = preprocessConv3DInput(x, dataFormat);\n    if (padding === \"causal\") {\n      throw new NotImplementedError(\"The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.\");\n    }\n    y = conv3d(y, kernel, strides, padding === \"same\" ? \"same\" : \"valid\", \"NDHWC\", dilationRate);\n    if (bias != null) {\n      y = biasAdd(y, bias);\n    }\n    if (dataFormat === \"channelsFirst\") {\n      y = transpose(y, [0, 4, 1, 2, 3]);\n    }\n    return y;\n  });\n}\nvar BaseConv = class extends Layer {\n  constructor(rank, args) {\n    super(args);\n    this.bias = null;\n    this.DEFAULT_KERNEL_INITIALIZER = \"glorotNormal\";\n    this.DEFAULT_BIAS_INITIALIZER = \"zeros\";\n    BaseConv.verifyArgs(args);\n    this.rank = rank;\n    assertPositiveInteger(this.rank, \"rank\");\n    if (this.rank !== 1 && this.rank !== 2 && this.rank !== 3) {\n      throw new NotImplementedError(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);\n    }\n    this.kernelSize = normalizeArray(args.kernelSize, rank, \"kernelSize\");\n    this.strides = normalizeArray(args.strides == null ? 1 : args.strides, rank, \"strides\");\n    this.padding = args.padding == null ? \"valid\" : args.padding;\n    checkPaddingMode(this.padding);\n    this.dataFormat = args.dataFormat == null ? \"channelsLast\" : args.dataFormat;\n    checkDataFormat(this.dataFormat);\n    this.activation = getActivation(args.activation);\n    this.useBias = args.useBias == null ? true : args.useBias;\n    this.biasInitializer = getInitializer(args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER);\n    this.biasConstraint = getConstraint(args.biasConstraint);\n    this.biasRegularizer = getRegularizer(args.biasRegularizer);\n    this.activityRegularizer = getRegularizer(args.activityRegularizer);\n    this.dilationRate = normalizeArray(args.dilationRate == null ? 1 : args.dilationRate, rank, \"dilationRate\");\n    if (this.rank === 1 && (Array.isArray(this.dilationRate) && this.dilationRate.length !== 1)) {\n      throw new ValueError(`dilationRate must be a number or an array of a single number for 1D convolution, but received ${JSON.stringify(this.dilationRate)}`);\n    } else if (this.rank === 2) {\n      if (typeof this.dilationRate === \"number\") {\n        this.dilationRate = [this.dilationRate, this.dilationRate];\n      } else if (this.dilationRate.length !== 2) {\n        throw new ValueError(`dilationRate must be a number or array of two numbers for 2D convolution, but received ${JSON.stringify(this.dilationRate)}`);\n      }\n    } else if (this.rank === 3) {\n      if (typeof this.dilationRate === \"number\") {\n        this.dilationRate = [this.dilationRate, this.dilationRate, this.dilationRate];\n      } else if (this.dilationRate.length !== 3) {\n        throw new ValueError(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`);\n      }\n    }\n  }\n  static verifyArgs(args) {\n    assert2(\"kernelSize\" in args, `required key 'kernelSize' not in config`);\n    if (typeof args.kernelSize !== \"number\" && !checkArrayTypeAndLength(args.kernelSize, \"number\", 1, 3)) {\n      throw new ValueError(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(args.kernelSize)}.`);\n    }\n  }\n  getConfig() {\n    const config = {\n      kernelSize: this.kernelSize,\n      strides: this.strides,\n      padding: this.padding,\n      dataFormat: this.dataFormat,\n      dilationRate: this.dilationRate,\n      activation: serializeActivation(this.activation),\n      useBias: this.useBias,\n      biasInitializer: serializeInitializer(this.biasInitializer),\n      biasRegularizer: serializeRegularizer(this.biasRegularizer),\n      activityRegularizer: serializeRegularizer(this.activityRegularizer),\n      biasConstraint: serializeConstraint(this.biasConstraint)\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nvar Conv = class extends BaseConv {\n  constructor(rank, args) {\n    super(rank, args);\n    this.kernel = null;\n    Conv.verifyArgs(args);\n    this.filters = args.filters;\n    assertPositiveInteger(this.filters, \"filters\");\n    this.kernelInitializer = getInitializer(args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER);\n    this.kernelConstraint = getConstraint(args.kernelConstraint);\n    this.kernelRegularizer = getRegularizer(args.kernelRegularizer);\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const channelAxis = this.dataFormat === \"channelsFirst\" ? 1 : inputShape.length - 1;\n    if (inputShape[channelAxis] == null) {\n      throw new ValueError(`The channel dimension of the input should be defined. Found ${inputShape[channelAxis]}`);\n    }\n    const inputDim = inputShape[channelAxis];\n    const kernelShape = this.kernelSize.concat([inputDim, this.filters]);\n    this.kernel = this.addWeight(\"kernel\", kernelShape, null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n    if (this.useBias) {\n      this.bias = this.addWeight(\"bias\", [this.filters], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    }\n    this.inputSpec = [{ ndim: this.rank + 2, axes: { [channelAxis]: inputDim } }];\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = getExactlyOneTensor(inputs);\n      let outputs;\n      const biasValue = this.bias == null ? null : this.bias.read();\n      const fusedActivationName = mapActivationToFusedKernel(this.activation.getClassName());\n      if (fusedActivationName != null && this.rank === 2) {\n        outputs = conv2dWithBiasActivation(inputs, this.kernel.read(), biasValue, this.strides, this.padding, this.dataFormat, this.dilationRate, fusedActivationName);\n      } else {\n        if (this.rank === 1) {\n          outputs = conv1dWithBias(inputs, this.kernel.read(), biasValue, this.strides[0], this.padding, this.dataFormat, this.dilationRate[0]);\n        } else if (this.rank === 2) {\n          outputs = conv2dWithBiasActivation(inputs, this.kernel.read(), biasValue, this.strides, this.padding, this.dataFormat, this.dilationRate);\n        } else if (this.rank === 3) {\n          outputs = conv3dWithBias(inputs, this.kernel.read(), biasValue, this.strides, this.padding, this.dataFormat, this.dilationRate);\n        } else {\n          throw new NotImplementedError(\"convolutions greater than 3D are not implemented yet.\");\n        }\n        if (this.activation != null) {\n          outputs = this.activation.apply(outputs);\n        }\n      }\n      return outputs;\n    });\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const newSpace = [];\n    const space = this.dataFormat === \"channelsLast\" ? inputShape.slice(1, inputShape.length - 1) : inputShape.slice(2);\n    for (let i2 = 0; i2 < space.length; ++i2) {\n      const newDim = convOutputLength(space[i2], this.kernelSize[i2], this.padding, this.strides[i2], typeof this.dilationRate === \"number\" ? this.dilationRate : this.dilationRate[i2]);\n      newSpace.push(newDim);\n    }\n    let outputShape = [inputShape[0]];\n    if (this.dataFormat === \"channelsLast\") {\n      outputShape = outputShape.concat(newSpace);\n      outputShape.push(this.filters);\n    } else {\n      outputShape.push(this.filters);\n      outputShape = outputShape.concat(newSpace);\n    }\n    return outputShape;\n  }\n  getConfig() {\n    const config = {\n      filters: this.filters,\n      kernelInitializer: serializeInitializer(this.kernelInitializer),\n      kernelRegularizer: serializeRegularizer(this.kernelRegularizer),\n      kernelConstraint: serializeConstraint(this.kernelConstraint)\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  static verifyArgs(args) {\n    if (!(\"filters\" in args) || typeof args.filters !== \"number\" || args.filters < 1) {\n      throw new ValueError(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(args.filters)}`);\n    }\n  }\n};\nvar Conv2D2 = class extends Conv {\n  constructor(args) {\n    super(2, args);\n    Conv2D2.verifyArgs(args);\n  }\n  getConfig() {\n    const config = super.getConfig();\n    delete config[\"rank\"];\n    return config;\n  }\n  static verifyArgs(args) {\n    if (typeof args.kernelSize !== \"number\" && !checkArrayTypeAndLength(args.kernelSize, \"number\", 1, 2)) {\n      throw new ValueError(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(args.kernelSize)}.`);\n    }\n  }\n};\nConv2D2.className = \"Conv2D\";\nserialization_exports.registerClass(Conv2D2);\nvar Conv3D2 = class extends Conv {\n  constructor(args) {\n    super(3, args);\n    Conv3D2.verifyArgs(args);\n  }\n  getConfig() {\n    const config = super.getConfig();\n    delete config[\"rank\"];\n    return config;\n  }\n  static verifyArgs(args) {\n    if (typeof args.kernelSize !== \"number\") {\n      if (!(Array.isArray(args.kernelSize) && (args.kernelSize.length === 1 || args.kernelSize.length === 3))) {\n        throw new ValueError(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(args.kernelSize)}.`);\n      }\n    }\n  }\n};\nConv3D2.className = \"Conv3D\";\nserialization_exports.registerClass(Conv3D2);\nvar Conv2DTranspose = class extends Conv2D2 {\n  constructor(args) {\n    super(args);\n    this.inputSpec = [new InputSpec({ ndim: 4 })];\n    if (this.padding !== \"same\" && this.padding !== \"valid\") {\n      throw new ValueError(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`);\n    }\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    if (inputShape.length !== 4) {\n      throw new ValueError(\"Input should have rank 4; Received input shape: \" + JSON.stringify(inputShape));\n    }\n    const channelAxis = this.dataFormat === \"channelsFirst\" ? 1 : inputShape.length - 1;\n    if (inputShape[channelAxis] == null) {\n      throw new ValueError(\"The channel dimension of the inputs should be defined. Found `None`.\");\n    }\n    const inputDim = inputShape[channelAxis];\n    const kernelShape = this.kernelSize.concat([this.filters, inputDim]);\n    this.kernel = this.addWeight(\"kernel\", kernelShape, \"float32\", this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n    if (this.useBias) {\n      this.bias = this.addWeight(\"bias\", [this.filters], \"float32\", this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    }\n    this.inputSpec = [new InputSpec({ ndim: 4, axes: { [channelAxis]: inputDim } })];\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      let input2 = getExactlyOneTensor(inputs);\n      if (input2.shape.length !== 4) {\n        throw new ValueError(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${input2.shape.length}`);\n      }\n      const inputShape = input2.shape;\n      const batchSize = inputShape[0];\n      let hAxis;\n      let wAxis;\n      if (this.dataFormat === \"channelsFirst\") {\n        hAxis = 2;\n        wAxis = 3;\n      } else {\n        hAxis = 1;\n        wAxis = 2;\n      }\n      const height = inputShape[hAxis];\n      const width = inputShape[wAxis];\n      const kernelH = this.kernelSize[0];\n      const kernelW = this.kernelSize[1];\n      const strideH = this.strides[0];\n      const strideW = this.strides[1];\n      const outHeight = deconvLength(height, strideH, kernelH, this.padding);\n      const outWidth = deconvLength(width, strideW, kernelW, this.padding);\n      const outputShape = [batchSize, outHeight, outWidth, this.filters];\n      if (this.dataFormat !== \"channelsLast\") {\n        input2 = transpose(input2, [0, 2, 3, 1]);\n      }\n      let outputs = conv2dTranspose(input2, this.kernel.read(), outputShape, this.strides, this.padding);\n      if (this.dataFormat !== \"channelsLast\") {\n        outputs = transpose(outputs, [0, 3, 1, 2]);\n      }\n      if (this.bias != null) {\n        outputs = biasAdd(outputs, this.bias.read(), this.dataFormat);\n      }\n      if (this.activation != null) {\n        outputs = this.activation.apply(outputs);\n      }\n      return outputs;\n    });\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const outputShape = inputShape.slice();\n    let channelAxis;\n    let heightAxis;\n    let widthAxis;\n    if (this.dataFormat === \"channelsFirst\") {\n      channelAxis = 1;\n      heightAxis = 2;\n      widthAxis = 3;\n    } else {\n      channelAxis = 3;\n      heightAxis = 1;\n      widthAxis = 2;\n    }\n    const kernelH = this.kernelSize[0];\n    const kernelW = this.kernelSize[1];\n    const strideH = this.strides[0];\n    const strideW = this.strides[1];\n    outputShape[channelAxis] = this.filters;\n    outputShape[heightAxis] = deconvLength(outputShape[heightAxis], strideH, kernelH, this.padding);\n    outputShape[widthAxis] = deconvLength(outputShape[widthAxis], strideW, kernelW, this.padding);\n    return outputShape;\n  }\n  getConfig() {\n    const config = super.getConfig();\n    delete config[\"dilationRate\"];\n    return config;\n  }\n};\nConv2DTranspose.className = \"Conv2DTranspose\";\nserialization_exports.registerClass(Conv2DTranspose);\nvar Conv3DTranspose = class extends Conv3D2 {\n  constructor(args) {\n    super(args);\n    this.inputSpec = [new InputSpec({ ndim: 5 })];\n    if (this.padding !== \"same\" && this.padding !== \"valid\") {\n      throw new ValueError(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`);\n    }\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    if (inputShape.length !== 5) {\n      throw new ValueError(\"Input should have rank 5; Received input shape: \" + JSON.stringify(inputShape));\n    }\n    const channelAxis = this.dataFormat === \"channelsFirst\" ? 1 : inputShape.length - 1;\n    if (inputShape[channelAxis] == null) {\n      throw new ValueError(\"The channel dimension of the inputs should be defined. Found `None`.\");\n    }\n    const inputDim = inputShape[channelAxis];\n    const kernelShape = this.kernelSize.concat([this.filters, inputDim]);\n    this.kernel = this.addWeight(\"kernel\", kernelShape, \"float32\", this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n    if (this.useBias) {\n      this.bias = this.addWeight(\"bias\", [this.filters], \"float32\", this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    }\n    this.inputSpec = [new InputSpec({ ndim: 5, axes: { [channelAxis]: inputDim } })];\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      let input2 = getExactlyOneTensor(inputs);\n      if (input2.shape.length !== 5) {\n        throw new ValueError(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${input2.shape.length}`);\n      }\n      const inputShape = input2.shape;\n      const batchSize = inputShape[0];\n      let hAxis;\n      let wAxis;\n      let dAxis;\n      if (this.dataFormat === \"channelsFirst\") {\n        dAxis = 2;\n        hAxis = 3;\n        wAxis = 4;\n      } else {\n        dAxis = 1;\n        hAxis = 2;\n        wAxis = 3;\n      }\n      const depth = inputShape[dAxis];\n      const height = inputShape[hAxis];\n      const width = inputShape[wAxis];\n      const kernelD = this.kernelSize[0];\n      const kernelH = this.kernelSize[1];\n      const kernelW = this.kernelSize[2];\n      const strideD = this.strides[0];\n      const strideH = this.strides[1];\n      const strideW = this.strides[2];\n      const outDepth = deconvLength(depth, strideD, kernelD, this.padding);\n      const outHeight = deconvLength(height, strideH, kernelH, this.padding);\n      const outWidth = deconvLength(width, strideW, kernelW, this.padding);\n      const outputShape = [batchSize, outDepth, outHeight, outWidth, this.filters];\n      if (this.dataFormat !== \"channelsLast\") {\n        input2 = transpose(input2, [0, 2, 3, 4, 1]);\n      }\n      let outputs = conv3dTranspose(input2, this.kernel.read(), outputShape, this.strides, this.padding);\n      if (this.dataFormat !== \"channelsLast\") {\n        outputs = transpose(outputs, [0, 4, 1, 2, 3]);\n      }\n      if (this.bias !== null) {\n        outputs = biasAdd(outputs, this.bias.read(), this.dataFormat);\n      }\n      if (this.activation !== null) {\n        outputs = this.activation.apply(outputs);\n      }\n      return outputs;\n    });\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const outputShape = inputShape.slice();\n    let channelAxis;\n    let depthAxis;\n    let heightAxis;\n    let widthAxis;\n    if (this.dataFormat === \"channelsFirst\") {\n      channelAxis = 1;\n      depthAxis = 2;\n      heightAxis = 3;\n      widthAxis = 4;\n    } else {\n      channelAxis = 4;\n      depthAxis = 1;\n      heightAxis = 2;\n      widthAxis = 3;\n    }\n    const kernelD = this.kernelSize[0];\n    const kernelH = this.kernelSize[1];\n    const kernelW = this.kernelSize[2];\n    const strideD = this.strides[0];\n    const strideH = this.strides[1];\n    const strideW = this.strides[2];\n    outputShape[channelAxis] = this.filters;\n    outputShape[depthAxis] = deconvLength(outputShape[depthAxis], strideD, kernelD, this.padding);\n    outputShape[heightAxis] = deconvLength(outputShape[heightAxis], strideH, kernelH, this.padding);\n    outputShape[widthAxis] = deconvLength(outputShape[widthAxis], strideW, kernelW, this.padding);\n    return outputShape;\n  }\n  getConfig() {\n    const config = super.getConfig();\n    delete config[\"dilationRate\"];\n    return config;\n  }\n};\nConv3DTranspose.className = \"Conv3DTranspose\";\nserialization_exports.registerClass(Conv3DTranspose);\nvar SeparableConv = class extends Conv {\n  constructor(rank, config) {\n    super(rank, config);\n    this.DEFAULT_DEPTHWISE_INITIALIZER = \"glorotUniform\";\n    this.DEFAULT_POINTWISE_INITIALIZER = \"glorotUniform\";\n    this.depthwiseKernel = null;\n    this.pointwiseKernel = null;\n    if (config.filters == null) {\n      throw new ValueError(\"The `filters` configuration field is required by SeparableConv, but is unspecified.\");\n    }\n    if (config.kernelInitializer != null || config.kernelRegularizer != null || config.kernelConstraint != null) {\n      throw new ValueError(\"Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.\");\n    }\n    if (config.padding != null && config.padding !== \"same\" && config.padding !== \"valid\") {\n      throw new ValueError(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(config.padding)}`);\n    }\n    this.depthMultiplier = config.depthMultiplier == null ? 1 : config.depthMultiplier;\n    this.depthwiseInitializer = getInitializer(config.depthwiseInitializer || this.DEFAULT_DEPTHWISE_INITIALIZER);\n    this.depthwiseRegularizer = getRegularizer(config.depthwiseRegularizer);\n    this.depthwiseConstraint = getConstraint(config.depthwiseConstraint);\n    this.pointwiseInitializer = getInitializer(config.depthwiseInitializer || this.DEFAULT_POINTWISE_INITIALIZER);\n    this.pointwiseRegularizer = getRegularizer(config.pointwiseRegularizer);\n    this.pointwiseConstraint = getConstraint(config.pointwiseConstraint);\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    if (inputShape.length < this.rank + 2) {\n      throw new ValueError(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank + 2}, but received input shape: ${JSON.stringify(inputShape)}`);\n    }\n    const channelAxis = this.dataFormat === \"channelsFirst\" ? 1 : inputShape.length - 1;\n    if (inputShape[channelAxis] == null || inputShape[channelAxis] < 0) {\n      throw new ValueError(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(inputShape[channelAxis])}`);\n    }\n    const inputDim = inputShape[channelAxis];\n    const depthwiseKernelShape = this.kernelSize.concat([inputDim, this.depthMultiplier]);\n    const pointwiseKernelShape = [];\n    for (let i2 = 0; i2 < this.rank; ++i2) {\n      pointwiseKernelShape.push(1);\n    }\n    pointwiseKernelShape.push(inputDim * this.depthMultiplier, this.filters);\n    const trainable = true;\n    this.depthwiseKernel = this.addWeight(\"depthwise_kernel\", depthwiseKernelShape, \"float32\", this.depthwiseInitializer, this.depthwiseRegularizer, trainable, this.depthwiseConstraint);\n    this.pointwiseKernel = this.addWeight(\"pointwise_kernel\", pointwiseKernelShape, \"float32\", this.pointwiseInitializer, this.pointwiseRegularizer, trainable, this.pointwiseConstraint);\n    if (this.useBias) {\n      this.bias = this.addWeight(\"bias\", [this.filters], \"float32\", this.biasInitializer, this.biasRegularizer, trainable, this.biasConstraint);\n    } else {\n      this.bias = null;\n    }\n    this.inputSpec = [new InputSpec({ ndim: this.rank + 2, axes: { [channelAxis]: inputDim } })];\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = getExactlyOneTensor(inputs);\n      let output;\n      if (this.rank === 1) {\n        throw new NotImplementedError(\"1D separable convolution is not implemented yet.\");\n      } else if (this.rank === 2) {\n        if (this.dataFormat === \"channelsFirst\") {\n          inputs = transpose(inputs, [0, 2, 3, 1]);\n        }\n        output = separableConv2d(inputs, this.depthwiseKernel.read(), this.pointwiseKernel.read(), this.strides, this.padding, this.dilationRate, \"NHWC\");\n      }\n      if (this.useBias) {\n        output = biasAdd(output, this.bias.read(), this.dataFormat);\n      }\n      if (this.activation != null) {\n        output = this.activation.apply(output);\n      }\n      if (this.dataFormat === \"channelsFirst\") {\n        output = transpose(output, [0, 3, 1, 2]);\n      }\n      return output;\n    });\n  }\n  getConfig() {\n    const config = super.getConfig();\n    delete config[\"rank\"];\n    delete config[\"kernelInitializer\"];\n    delete config[\"kernelRegularizer\"];\n    delete config[\"kernelConstraint\"];\n    config[\"depthwiseInitializer\"] = serializeInitializer(this.depthwiseInitializer);\n    config[\"pointwiseInitializer\"] = serializeInitializer(this.pointwiseInitializer);\n    config[\"depthwiseRegularizer\"] = serializeRegularizer(this.depthwiseRegularizer);\n    config[\"pointwiseRegularizer\"] = serializeRegularizer(this.pointwiseRegularizer);\n    config[\"depthwiseConstraint\"] = serializeConstraint(this.depthwiseConstraint);\n    config[\"pointwiseConstraint\"] = serializeConstraint(this.pointwiseConstraint);\n    return config;\n  }\n};\nSeparableConv.className = \"SeparableConv\";\nvar SeparableConv2D = class extends SeparableConv {\n  constructor(args) {\n    super(2, args);\n  }\n};\nSeparableConv2D.className = \"SeparableConv2D\";\nserialization_exports.registerClass(SeparableConv2D);\nvar Conv1D = class extends Conv {\n  constructor(args) {\n    super(1, args);\n    Conv1D.verifyArgs(args);\n    this.inputSpec = [{ ndim: 3 }];\n  }\n  getConfig() {\n    const config = super.getConfig();\n    delete config[\"rank\"];\n    delete config[\"dataFormat\"];\n    return config;\n  }\n  static verifyArgs(args) {\n    if (typeof args.kernelSize !== \"number\" && !checkArrayTypeAndLength(args.kernelSize, \"number\", 1, 1)) {\n      throw new ValueError(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(args.kernelSize)}.`);\n    }\n  }\n};\nConv1D.className = \"Conv1D\";\nserialization_exports.registerClass(Conv1D);\nvar Cropping2D = class extends Layer {\n  constructor(args) {\n    super(args);\n    if (typeof args.cropping === \"number\") {\n      this.cropping = [[args.cropping, args.cropping], [args.cropping, args.cropping]];\n    } else if (typeof args.cropping[0] === \"number\") {\n      this.cropping = [\n        [args.cropping[0], args.cropping[0]],\n        [args.cropping[1], args.cropping[1]]\n      ];\n    } else {\n      this.cropping = args.cropping;\n    }\n    this.dataFormat = args.dataFormat === void 0 ? \"channelsLast\" : args.dataFormat;\n    this.inputSpec = [{ ndim: 4 }];\n  }\n  computeOutputShape(inputShape) {\n    if (this.dataFormat === \"channelsFirst\") {\n      return [\n        inputShape[0],\n        inputShape[1],\n        inputShape[2] - this.cropping[0][0] - this.cropping[0][1],\n        inputShape[3] - this.cropping[1][0] - this.cropping[1][1]\n      ];\n    } else {\n      return [\n        inputShape[0],\n        inputShape[1] - this.cropping[0][0] - this.cropping[0][1],\n        inputShape[2] - this.cropping[1][0] - this.cropping[1][1],\n        inputShape[3]\n      ];\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = getExactlyOneTensor(inputs);\n      if (this.dataFormat === \"channelsLast\") {\n        const hSliced = sliceAlongAxis(inputs, this.cropping[0][0], inputs.shape[1] - this.cropping[0][0] - this.cropping[0][1], 2);\n        return sliceAlongAxis(hSliced, this.cropping[1][0], inputs.shape[2] - this.cropping[1][1] - this.cropping[1][0], 3);\n      } else {\n        const hSliced = sliceAlongAxis(inputs, this.cropping[0][0], inputs.shape[2] - this.cropping[0][0] - this.cropping[0][1], 3);\n        return sliceAlongAxis(hSliced, this.cropping[1][0], inputs.shape[3] - this.cropping[1][1] - this.cropping[1][0], 4);\n      }\n    });\n  }\n  getConfig() {\n    const config = { cropping: this.cropping, dataFormat: this.dataFormat };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nCropping2D.className = \"Cropping2D\";\nserialization_exports.registerClass(Cropping2D);\nvar UpSampling2D = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.DEFAULT_SIZE = [2, 2];\n    this.inputSpec = [{ ndim: 4 }];\n    this.size = args.size == null ? this.DEFAULT_SIZE : args.size;\n    this.dataFormat = args.dataFormat == null ? \"channelsLast\" : args.dataFormat;\n    checkDataFormat(this.dataFormat);\n    this.interpolation = args.interpolation == null ? \"nearest\" : args.interpolation;\n    checkInterpolationFormat(this.interpolation);\n  }\n  computeOutputShape(inputShape) {\n    if (this.dataFormat === \"channelsFirst\") {\n      const height = inputShape[2] == null ? null : this.size[0] * inputShape[2];\n      const width = inputShape[3] == null ? null : this.size[1] * inputShape[3];\n      return [inputShape[0], inputShape[1], height, width];\n    } else {\n      const height = inputShape[1] == null ? null : this.size[0] * inputShape[1];\n      const width = inputShape[2] == null ? null : this.size[1] * inputShape[2];\n      return [inputShape[0], height, width, inputShape[3]];\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      let input2 = getExactlyOneTensor(inputs);\n      const inputShape = input2.shape;\n      if (this.dataFormat === \"channelsFirst\") {\n        input2 = transpose(input2, [0, 2, 3, 1]);\n        const height = this.size[0] * inputShape[2];\n        const width = this.size[1] * inputShape[3];\n        const resized = this.interpolation === \"nearest\" ? image.resizeNearestNeighbor(input2, [height, width]) : image.resizeBilinear(input2, [height, width]);\n        return transpose(resized, [0, 3, 1, 2]);\n      } else {\n        const height = this.size[0] * inputShape[1];\n        const width = this.size[1] * inputShape[2];\n        return this.interpolation === \"nearest\" ? image.resizeNearestNeighbor(input2, [height, width]) : image.resizeBilinear(input2, [height, width]);\n      }\n    });\n  }\n  getConfig() {\n    const config = {\n      size: this.size,\n      dataFormat: this.dataFormat,\n      interpolation: this.interpolation\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nUpSampling2D.className = \"UpSampling2D\";\nserialization_exports.registerClass(UpSampling2D);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/convolutional_depthwise.js\nfunction depthwiseConv2d3(x, depthwiseKernel, strides = [1, 1], padding = \"valid\", dataFormat, dilationRate) {\n  return tidy(() => {\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    checkDataFormat(dataFormat);\n    let y = preprocessConv2DInput(x, dataFormat);\n    if (x.rank !== 4) {\n      throw new ValueError(`Input for depthwiseConv2d is required to be 4-D, but is instead ${x.rank}-D`);\n    }\n    if (depthwiseKernel.rank !== 4) {\n      throw new ValueError(`depthwiseKernel is required to be 4-D, but is instead ${depthwiseKernel.rank}-D`);\n    }\n    y = depthwiseConv2d(y, depthwiseKernel, strides, padding === \"same\" ? \"same\" : \"valid\", \"NHWC\", dilationRate);\n    if (dataFormat === \"channelsFirst\") {\n      y = transpose(y, [0, 3, 1, 2]);\n    }\n    return y;\n  });\n}\nvar DepthwiseConv2D = class extends BaseConv {\n  constructor(args) {\n    super(2, args);\n    this.depthwiseKernel = null;\n    this.depthMultiplier = args.depthMultiplier == null ? 1 : args.depthMultiplier;\n    this.depthwiseInitializer = getInitializer(args.depthwiseInitializer || this.DEFAULT_KERNEL_INITIALIZER);\n    this.depthwiseConstraint = getConstraint(args.depthwiseConstraint);\n    this.depthwiseRegularizer = getRegularizer(args.depthwiseRegularizer);\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    if (inputShape.length < 4) {\n      throw new ValueError(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(inputShape)}.`);\n    }\n    const channelAxis = this.dataFormat === \"channelsFirst\" ? 1 : 3;\n    if (inputShape[channelAxis] == null || inputShape[channelAxis] < 0) {\n      throw new ValueError(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${inputShape[channelAxis]}).`);\n    }\n    const inputDim = inputShape[channelAxis];\n    const depthwiseKernelShape = [\n      this.kernelSize[0],\n      this.kernelSize[1],\n      inputDim,\n      this.depthMultiplier\n    ];\n    this.depthwiseKernel = this.addWeight(\"depthwise_kernel\", depthwiseKernelShape, null, this.depthwiseInitializer, this.depthwiseRegularizer, true, this.depthwiseConstraint);\n    if (this.useBias) {\n      this.bias = this.addWeight(\"bias\", [inputDim * this.depthMultiplier], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    } else {\n      this.bias = null;\n    }\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = getExactlyOneTensor(inputs);\n      let outputs = depthwiseConv2d3(inputs, this.depthwiseKernel.read(), this.strides, this.padding, this.dataFormat, null);\n      if (this.useBias) {\n        outputs = biasAdd(outputs, this.bias.read(), this.dataFormat);\n      }\n      if (this.activation != null) {\n        outputs = this.activation.apply(outputs);\n      }\n      return outputs;\n    });\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const rows = this.dataFormat === \"channelsFirst\" ? inputShape[2] : inputShape[1];\n    const cols = this.dataFormat === \"channelsFirst\" ? inputShape[3] : inputShape[2];\n    const outFilters = this.dataFormat === \"channelsFirst\" ? inputShape[1] * this.depthMultiplier : inputShape[3] * this.depthMultiplier;\n    const outRows = convOutputLength(rows, this.kernelSize[0], this.padding, this.strides[0]);\n    const outCols = convOutputLength(cols, this.kernelSize[1], this.padding, this.strides[1]);\n    if (this.dataFormat === \"channelsFirst\") {\n      return [inputShape[0], outFilters, outRows, outCols];\n    } else {\n      return [inputShape[0], outRows, outCols, outFilters];\n    }\n  }\n  getConfig() {\n    const config = super.getConfig();\n    config[\"depthMultiplier\"] = this.depthMultiplier;\n    config[\"depthwiseInitializer\"] = serializeInitializer(this.depthwiseInitializer);\n    config[\"depthwiseRegularizer\"] = serializeRegularizer(this.depthwiseRegularizer);\n    config[\"depthwiseConstraint\"] = serializeConstraint(this.depthwiseRegularizer);\n    return config;\n  }\n};\nDepthwiseConv2D.className = \"DepthwiseConv2D\";\nserialization_exports.registerClass(DepthwiseConv2D);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/recurrent.js\nfunction standardizeArgs(inputs, initialState, constants, numConstants) {\n  if (Array.isArray(inputs)) {\n    if (initialState != null || constants != null) {\n      throw new ValueError(\"When inputs is an array, neither initialState or constants should be provided\");\n    }\n    if (numConstants != null) {\n      constants = inputs.slice(inputs.length - numConstants, inputs.length);\n      inputs = inputs.slice(0, inputs.length - numConstants);\n    }\n    if (inputs.length > 1) {\n      initialState = inputs.slice(1, inputs.length);\n    }\n    inputs = inputs[0];\n  }\n  function toListOrNull(x) {\n    if (x == null || Array.isArray(x)) {\n      return x;\n    } else {\n      return [x];\n    }\n  }\n  initialState = toListOrNull(initialState);\n  constants = toListOrNull(constants);\n  return { inputs, initialState, constants };\n}\nfunction rnn(stepFunction, inputs, initialStates, goBackwards = false, mask, constants, unroll = false, needPerStepOutputs = false) {\n  return tidy(() => {\n    const ndim = inputs.shape.length;\n    if (ndim < 3) {\n      throw new ValueError(`Input should be at least 3D, but is ${ndim}D.`);\n    }\n    const axes = [1, 0].concat(range2(2, ndim));\n    inputs = transpose(inputs, axes);\n    if (constants != null) {\n      throw new NotImplementedError(\"The rnn() functoin of the deeplearn.js backend does not support constants yet.\");\n    }\n    if (unroll) {\n      console.warn(\"Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend.\");\n    }\n    if (mask != null) {\n      mask = cast(cast(mask, \"bool\"), \"float32\");\n      if (mask.rank === ndim - 1) {\n        mask = expandDims(mask, -1);\n      }\n      mask = transpose(mask, axes);\n    }\n    if (goBackwards) {\n      inputs = reverse(inputs, 0);\n      if (mask != null) {\n        mask = reverse(mask, 0);\n      }\n    }\n    const perStepOutputs = [];\n    let lastOutput;\n    let states = initialStates;\n    const timeSteps = inputs.shape[0];\n    const perStepInputs = unstack(inputs);\n    let perStepMasks;\n    if (mask != null) {\n      perStepMasks = unstack(mask);\n    }\n    for (let t2 = 0; t2 < timeSteps; ++t2) {\n      const currentInput = perStepInputs[t2];\n      const stepOutputs = tidy(() => stepFunction(currentInput, states));\n      if (mask == null) {\n        lastOutput = stepOutputs[0];\n        states = stepOutputs[1];\n      } else {\n        const maskedOutputs = tidy(() => {\n          const stepMask = perStepMasks[t2];\n          const negStepMask = sub(onesLike(stepMask), stepMask);\n          const output = add2(mul(stepOutputs[0], stepMask), mul(states[0], negStepMask));\n          const newStates = states.map((state, i2) => {\n            return add2(mul(stepOutputs[1][i2], stepMask), mul(state, negStepMask));\n          });\n          return { output, newStates };\n        });\n        lastOutput = maskedOutputs.output;\n        states = maskedOutputs.newStates;\n      }\n      if (needPerStepOutputs) {\n        perStepOutputs.push(lastOutput);\n      }\n    }\n    let outputs;\n    if (needPerStepOutputs) {\n      const axis = 1;\n      outputs = stack(perStepOutputs, axis);\n    }\n    return [lastOutput, outputs, states];\n  });\n}\nvar RNN = class extends Layer {\n  constructor(args) {\n    super(args);\n    let cell;\n    if (args.cell == null) {\n      throw new ValueError(\"cell property is missing for the constructor of RNN.\");\n    } else if (Array.isArray(args.cell)) {\n      cell = new StackedRNNCells({ cells: args.cell });\n    } else {\n      cell = args.cell;\n    }\n    if (cell.stateSize == null) {\n      throw new ValueError(\"The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).\");\n    }\n    this.cell = cell;\n    this.returnSequences = args.returnSequences == null ? false : args.returnSequences;\n    this.returnState = args.returnState == null ? false : args.returnState;\n    this.goBackwards = args.goBackwards == null ? false : args.goBackwards;\n    this._stateful = args.stateful == null ? false : args.stateful;\n    this.unroll = args.unroll == null ? false : args.unroll;\n    this.supportsMasking = true;\n    this.inputSpec = [new InputSpec({ ndim: 3 })];\n    this.stateSpec = null;\n    this.states_ = null;\n    this.numConstants = null;\n    this.keptStates = [];\n  }\n  getStates() {\n    if (this.states_ == null) {\n      const numStates = Array.isArray(this.cell.stateSize) ? this.cell.stateSize.length : 1;\n      return range2(0, numStates).map((x) => null);\n    } else {\n      return this.states_;\n    }\n  }\n  setStates(states) {\n    this.states_ = states;\n  }\n  computeOutputShape(inputShape) {\n    if (isArrayOfShapes(inputShape)) {\n      inputShape = inputShape[0];\n    }\n    inputShape = inputShape;\n    let stateSize = this.cell.stateSize;\n    if (!Array.isArray(stateSize)) {\n      stateSize = [stateSize];\n    }\n    const outputDim = stateSize[0];\n    let outputShape;\n    if (this.returnSequences) {\n      outputShape = [inputShape[0], inputShape[1], outputDim];\n    } else {\n      outputShape = [inputShape[0], outputDim];\n    }\n    if (this.returnState) {\n      const stateShape = [];\n      for (const dim of stateSize) {\n        stateShape.push([inputShape[0], dim]);\n      }\n      return [outputShape].concat(stateShape);\n    } else {\n      return outputShape;\n    }\n  }\n  computeMask(inputs, mask) {\n    return tidy(() => {\n      if (Array.isArray(mask)) {\n        mask = mask[0];\n      }\n      const outputMask = this.returnSequences ? mask : null;\n      if (this.returnState) {\n        const stateMask = this.states.map((s2) => null);\n        return [outputMask].concat(stateMask);\n      } else {\n        return outputMask;\n      }\n    });\n  }\n  get states() {\n    if (this.states_ == null) {\n      const numStates = Array.isArray(this.cell.stateSize) ? this.cell.stateSize.length : 1;\n      const output = [];\n      for (let i2 = 0; i2 < numStates; ++i2) {\n        output.push(null);\n      }\n      return output;\n    } else {\n      return this.states_;\n    }\n  }\n  set states(s2) {\n    this.states_ = s2;\n  }\n  build(inputShape) {\n    const constantShape = null;\n    if (this.numConstants != null) {\n      throw new NotImplementedError(\"Constants support is not implemented in RNN yet.\");\n    }\n    if (isArrayOfShapes(inputShape)) {\n      inputShape = inputShape[0];\n    }\n    inputShape = inputShape;\n    const batchSize = this.stateful ? inputShape[0] : null;\n    const inputDim = inputShape.slice(2);\n    this.inputSpec[0] = new InputSpec({ shape: [batchSize, null, ...inputDim] });\n    const stepInputShape = [inputShape[0]].concat(inputShape.slice(2));\n    if (constantShape != null) {\n      throw new NotImplementedError(\"Constants support is not implemented in RNN yet.\");\n    } else {\n      this.cell.build(stepInputShape);\n    }\n    let stateSize;\n    if (Array.isArray(this.cell.stateSize)) {\n      stateSize = this.cell.stateSize;\n    } else {\n      stateSize = [this.cell.stateSize];\n    }\n    if (this.stateSpec != null) {\n      if (!util_exports.arraysEqual(this.stateSpec.map((spec) => spec.shape[spec.shape.length - 1]), stateSize)) {\n        throw new ValueError(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`);\n      }\n    } else {\n      this.stateSpec = stateSize.map((dim) => new InputSpec({ shape: [null, dim] }));\n    }\n    if (this.stateful) {\n      this.resetStates();\n    }\n  }\n  resetStates(states, training = false) {\n    tidy(() => {\n      if (!this.stateful) {\n        throw new AttributeError(\"Cannot call resetStates() on an RNN Layer that is not stateful.\");\n      }\n      const batchSize = this.inputSpec[0].shape[0];\n      if (batchSize == null) {\n        throw new ValueError(\"If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \\n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.\");\n      }\n      if (this.states_ == null) {\n        if (Array.isArray(this.cell.stateSize)) {\n          this.states_ = this.cell.stateSize.map((dim) => zeros([batchSize, dim]));\n        } else {\n          this.states_ = [zeros([batchSize, this.cell.stateSize])];\n        }\n      } else if (states == null) {\n        dispose(this.states_);\n        if (this.keptStates != null) {\n          dispose(this.keptStates);\n          this.keptStates = [];\n        }\n        if (Array.isArray(this.cell.stateSize)) {\n          this.states_ = this.cell.stateSize.map((dim) => zeros([batchSize, dim]));\n        } else {\n          this.states_[0] = zeros([batchSize, this.cell.stateSize]);\n        }\n      } else {\n        if (!Array.isArray(states)) {\n          states = [states];\n        }\n        if (states.length !== this.states_.length) {\n          throw new ValueError(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${states.length} state value(s). Input received: ${states}`);\n        }\n        if (training === true) {\n          this.keptStates.push(this.states_.slice());\n        } else {\n          dispose(this.states_);\n        }\n        for (let index = 0; index < this.states_.length; ++index) {\n          const value = states[index];\n          const dim = Array.isArray(this.cell.stateSize) ? this.cell.stateSize[index] : this.cell.stateSize;\n          const expectedShape = [batchSize, dim];\n          if (!util_exports.arraysEqual(value.shape, expectedShape)) {\n            throw new ValueError(`State ${index} is incompatible with layer ${this.name}: expected shape=${expectedShape}, received shape=${value.shape}`);\n          }\n          this.states_[index] = value;\n        }\n      }\n      this.states_ = this.states_.map((state) => keep(state.clone()));\n    });\n  }\n  apply(inputs, kwargs) {\n    let initialState = kwargs == null ? null : kwargs[\"initialState\"];\n    let constants = kwargs == null ? null : kwargs[\"constants\"];\n    if (kwargs == null) {\n      kwargs = {};\n    }\n    const standardized = standardizeArgs(inputs, initialState, constants, this.numConstants);\n    inputs = standardized.inputs;\n    initialState = standardized.initialState;\n    constants = standardized.constants;\n    let additionalInputs = [];\n    let additionalSpecs = [];\n    if (initialState != null) {\n      kwargs[\"initialState\"] = initialState;\n      additionalInputs = additionalInputs.concat(initialState);\n      this.stateSpec = [];\n      for (const state of initialState) {\n        this.stateSpec.push(new InputSpec({ shape: state.shape }));\n      }\n      additionalSpecs = additionalSpecs.concat(this.stateSpec);\n    }\n    if (constants != null) {\n      kwargs[\"constants\"] = constants;\n      additionalInputs = additionalInputs.concat(constants);\n      this.numConstants = constants.length;\n    }\n    const isTensor = additionalInputs[0] instanceof SymbolicTensor;\n    if (isTensor) {\n      const fullInput = [inputs].concat(additionalInputs);\n      const fullInputSpec = this.inputSpec.concat(additionalSpecs);\n      const originalInputSpec = this.inputSpec;\n      this.inputSpec = fullInputSpec;\n      const output = super.apply(fullInput, kwargs);\n      this.inputSpec = originalInputSpec;\n      return output;\n    } else {\n      return super.apply(inputs, kwargs);\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const mask = kwargs == null ? null : kwargs[\"mask\"];\n      const training = kwargs == null ? null : kwargs[\"training\"];\n      let initialState = kwargs == null ? null : kwargs[\"initialState\"];\n      inputs = getExactlyOneTensor(inputs);\n      if (initialState == null) {\n        if (this.stateful) {\n          initialState = this.states_;\n        } else {\n          initialState = this.getInitialState(inputs);\n        }\n      }\n      const numStates = Array.isArray(this.cell.stateSize) ? this.cell.stateSize.length : 1;\n      if (initialState.length !== numStates) {\n        throw new ValueError(`RNN Layer has ${numStates} state(s) but was passed ${initialState.length} initial state(s).`);\n      }\n      if (this.unroll) {\n        console.warn(\"Ignoring unroll = true for RNN layer, due to imperative backend.\");\n      }\n      const cellCallKwargs = { training };\n      const step5 = (inputs2, states2) => {\n        const outputs2 = this.cell.call([inputs2].concat(states2), cellCallKwargs);\n        return [outputs2[0], outputs2.slice(1)];\n      };\n      const rnnOutputs = rnn(step5, inputs, initialState, this.goBackwards, mask, null, this.unroll, this.returnSequences);\n      const lastOutput = rnnOutputs[0];\n      const outputs = rnnOutputs[1];\n      const states = rnnOutputs[2];\n      if (this.stateful) {\n        this.resetStates(states, training);\n      }\n      const output = this.returnSequences ? outputs : lastOutput;\n      if (this.returnState) {\n        return [output].concat(states);\n      } else {\n        return output;\n      }\n    });\n  }\n  getInitialState(inputs) {\n    return tidy(() => {\n      let initialState = zeros(inputs.shape);\n      initialState = sum2(initialState, [1, 2]);\n      initialState = expandDims2(initialState);\n      if (Array.isArray(this.cell.stateSize)) {\n        return this.cell.stateSize.map((dim) => dim > 1 ? tile2(initialState, [1, dim]) : initialState);\n      } else {\n        return this.cell.stateSize > 1 ? [tile2(initialState, [1, this.cell.stateSize])] : [initialState];\n      }\n    });\n  }\n  get trainableWeights() {\n    if (!this.trainable) {\n      return [];\n    }\n    return this.cell.trainableWeights;\n  }\n  get nonTrainableWeights() {\n    if (!this.trainable) {\n      return this.cell.weights;\n    }\n    return this.cell.nonTrainableWeights;\n  }\n  setFastWeightInitDuringBuild(value) {\n    super.setFastWeightInitDuringBuild(value);\n    if (this.cell != null) {\n      this.cell.setFastWeightInitDuringBuild(value);\n    }\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = {\n      returnSequences: this.returnSequences,\n      returnState: this.returnState,\n      goBackwards: this.goBackwards,\n      stateful: this.stateful,\n      unroll: this.unroll\n    };\n    if (this.numConstants != null) {\n      config[\"numConstants\"] = this.numConstants;\n    }\n    const cellConfig = this.cell.getConfig();\n    if (this.getClassName() === RNN.className) {\n      config[\"cell\"] = {\n        \"className\": this.cell.getClassName(),\n        \"config\": cellConfig\n      };\n    }\n    return Object.assign({}, cellConfig, baseConfig, config);\n  }\n  static fromConfig(cls, config, customObjects = {}) {\n    const cellConfig = config[\"cell\"];\n    const cell = deserialize(cellConfig, customObjects);\n    return new cls(Object.assign(config, { cell }));\n  }\n};\nRNN.className = \"RNN\";\nserialization_exports.registerClass(RNN);\nvar RNNCell = class extends Layer {\n};\nvar SimpleRNNCell = class extends RNNCell {\n  constructor(args) {\n    super(args);\n    this.DEFAULT_ACTIVATION = \"tanh\";\n    this.DEFAULT_KERNEL_INITIALIZER = \"glorotNormal\";\n    this.DEFAULT_RECURRENT_INITIALIZER = \"orthogonal\";\n    this.DEFAULT_BIAS_INITIALIZER = \"zeros\";\n    this.units = args.units;\n    assertPositiveInteger(this.units, `units`);\n    this.activation = getActivation(args.activation == null ? this.DEFAULT_ACTIVATION : args.activation);\n    this.useBias = args.useBias == null ? true : args.useBias;\n    this.kernelInitializer = getInitializer(args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER);\n    this.recurrentInitializer = getInitializer(args.recurrentInitializer || this.DEFAULT_RECURRENT_INITIALIZER);\n    this.biasInitializer = getInitializer(args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER);\n    this.kernelRegularizer = getRegularizer(args.kernelRegularizer);\n    this.recurrentRegularizer = getRegularizer(args.recurrentRegularizer);\n    this.biasRegularizer = getRegularizer(args.biasRegularizer);\n    this.kernelConstraint = getConstraint(args.kernelConstraint);\n    this.recurrentConstraint = getConstraint(args.recurrentConstraint);\n    this.biasConstraint = getConstraint(args.biasConstraint);\n    this.dropout = min2([1, max2([0, args.dropout == null ? 0 : args.dropout])]);\n    this.recurrentDropout = min2([\n      1,\n      max2([0, args.recurrentDropout == null ? 0 : args.recurrentDropout])\n    ]);\n    this.dropoutFunc = args.dropoutFunc;\n    this.stateSize = this.units;\n    this.dropoutMask = null;\n    this.recurrentDropoutMask = null;\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    this.kernel = this.addWeight(\"kernel\", [inputShape[inputShape.length - 1], this.units], null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n    this.recurrentKernel = this.addWeight(\"recurrent_kernel\", [this.units, this.units], null, this.recurrentInitializer, this.recurrentRegularizer, true, this.recurrentConstraint);\n    if (this.useBias) {\n      this.bias = this.addWeight(\"bias\", [this.units], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    } else {\n      this.bias = null;\n    }\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = inputs;\n      if (inputs.length !== 2) {\n        throw new ValueError(`SimpleRNNCell expects 2 input Tensors, got ${inputs.length}.`);\n      }\n      let prevOutput = inputs[1];\n      inputs = inputs[0];\n      const training = kwargs[\"training\"] == null ? false : kwargs[\"training\"];\n      if (0 < this.dropout && this.dropout < 1 && this.dropoutMask == null) {\n        this.dropoutMask = generateDropoutMask({\n          ones: () => onesLike(inputs),\n          rate: this.dropout,\n          training,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      if (0 < this.recurrentDropout && this.recurrentDropout < 1 && this.recurrentDropoutMask == null) {\n        this.recurrentDropoutMask = generateDropoutMask({\n          ones: () => onesLike(prevOutput),\n          rate: this.recurrentDropout,\n          training,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      let h;\n      const dpMask = this.dropoutMask;\n      const recDpMask = this.recurrentDropoutMask;\n      if (dpMask != null) {\n        h = dot2(mul(inputs, dpMask), this.kernel.read());\n      } else {\n        h = dot2(inputs, this.kernel.read());\n      }\n      if (this.bias != null) {\n        h = biasAdd(h, this.bias.read());\n      }\n      if (recDpMask != null) {\n        prevOutput = mul(prevOutput, recDpMask);\n      }\n      let output = add2(h, dot2(prevOutput, this.recurrentKernel.read()));\n      if (this.activation != null) {\n        output = this.activation.apply(output);\n      }\n      return [output, output];\n    });\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = {\n      units: this.units,\n      activation: serializeActivation(this.activation),\n      useBias: this.useBias,\n      kernelInitializer: serializeInitializer(this.kernelInitializer),\n      recurrentInitializer: serializeInitializer(this.recurrentInitializer),\n      biasInitializer: serializeInitializer(this.biasInitializer),\n      kernelRegularizer: serializeRegularizer(this.kernelRegularizer),\n      recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),\n      biasRegularizer: serializeRegularizer(this.biasRegularizer),\n      activityRegularizer: serializeRegularizer(this.activityRegularizer),\n      kernelConstraint: serializeConstraint(this.kernelConstraint),\n      recurrentConstraint: serializeConstraint(this.recurrentConstraint),\n      biasConstraint: serializeConstraint(this.biasConstraint),\n      dropout: this.dropout,\n      recurrentDropout: this.recurrentDropout\n    };\n    return Object.assign({}, baseConfig, config);\n  }\n};\nSimpleRNNCell.className = \"SimpleRNNCell\";\nserialization_exports.registerClass(SimpleRNNCell);\nvar SimpleRNN = class extends RNN {\n  constructor(args) {\n    args.cell = new SimpleRNNCell(args);\n    super(args);\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      if (this.cell.dropoutMask != null) {\n        dispose(this.cell.dropoutMask);\n        this.cell.dropoutMask = null;\n      }\n      if (this.cell.recurrentDropoutMask != null) {\n        dispose(this.cell.recurrentDropoutMask);\n        this.cell.recurrentDropoutMask = null;\n      }\n      const mask = kwargs == null ? null : kwargs[\"mask\"];\n      const training = kwargs == null ? null : kwargs[\"training\"];\n      const initialState = kwargs == null ? null : kwargs[\"initialState\"];\n      return super.call(inputs, { mask, training, initialState });\n    });\n  }\n  static fromConfig(cls, config) {\n    return new cls(config);\n  }\n};\nSimpleRNN.className = \"SimpleRNN\";\nserialization_exports.registerClass(SimpleRNN);\nvar GRUCell = class extends RNNCell {\n  constructor(args) {\n    super(args);\n    this.DEFAULT_ACTIVATION = \"tanh\";\n    this.DEFAULT_RECURRENT_ACTIVATION = \"hardSigmoid\";\n    this.DEFAULT_KERNEL_INITIALIZER = \"glorotNormal\";\n    this.DEFAULT_RECURRENT_INITIALIZER = \"orthogonal\";\n    this.DEFAULT_BIAS_INITIALIZER = \"zeros\";\n    if (args.resetAfter) {\n      throw new ValueError(`GRUCell does not support reset_after parameter set to true.`);\n    }\n    this.units = args.units;\n    assertPositiveInteger(this.units, \"units\");\n    this.activation = getActivation(args.activation === void 0 ? this.DEFAULT_ACTIVATION : args.activation);\n    this.recurrentActivation = getActivation(args.recurrentActivation === void 0 ? this.DEFAULT_RECURRENT_ACTIVATION : args.recurrentActivation);\n    this.useBias = args.useBias == null ? true : args.useBias;\n    this.kernelInitializer = getInitializer(args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER);\n    this.recurrentInitializer = getInitializer(args.recurrentInitializer || this.DEFAULT_RECURRENT_INITIALIZER);\n    this.biasInitializer = getInitializer(args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER);\n    this.kernelRegularizer = getRegularizer(args.kernelRegularizer);\n    this.recurrentRegularizer = getRegularizer(args.recurrentRegularizer);\n    this.biasRegularizer = getRegularizer(args.biasRegularizer);\n    this.kernelConstraint = getConstraint(args.kernelConstraint);\n    this.recurrentConstraint = getConstraint(args.recurrentConstraint);\n    this.biasConstraint = getConstraint(args.biasConstraint);\n    this.dropout = min2([1, max2([0, args.dropout == null ? 0 : args.dropout])]);\n    this.recurrentDropout = min2([\n      1,\n      max2([0, args.recurrentDropout == null ? 0 : args.recurrentDropout])\n    ]);\n    this.dropoutFunc = args.dropoutFunc;\n    this.implementation = args.implementation;\n    this.stateSize = this.units;\n    this.dropoutMask = null;\n    this.recurrentDropoutMask = null;\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const inputDim = inputShape[inputShape.length - 1];\n    this.kernel = this.addWeight(\"kernel\", [inputDim, this.units * 3], null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n    this.recurrentKernel = this.addWeight(\"recurrent_kernel\", [this.units, this.units * 3], null, this.recurrentInitializer, this.recurrentRegularizer, true, this.recurrentConstraint);\n    if (this.useBias) {\n      this.bias = this.addWeight(\"bias\", [this.units * 3], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    } else {\n      this.bias = null;\n    }\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = inputs;\n      if (inputs.length !== 2) {\n        throw new ValueError(`GRUCell expects 2 input Tensors (inputs, h, c), got ${inputs.length}.`);\n      }\n      const training = kwargs[\"training\"] == null ? false : kwargs[\"training\"];\n      let hTMinus1 = inputs[1];\n      inputs = inputs[0];\n      if (0 < this.dropout && this.dropout < 1 && this.dropoutMask == null) {\n        this.dropoutMask = generateDropoutMask({\n          ones: () => onesLike(inputs),\n          rate: this.dropout,\n          training,\n          count: 3,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      if (0 < this.recurrentDropout && this.recurrentDropout < 1 && this.recurrentDropoutMask == null) {\n        this.recurrentDropoutMask = generateDropoutMask({\n          ones: () => onesLike(hTMinus1),\n          rate: this.recurrentDropout,\n          training,\n          count: 3,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      const dpMask = this.dropoutMask;\n      const recDpMask = this.recurrentDropoutMask;\n      let z;\n      let r2;\n      let hh;\n      if (0 < this.dropout && this.dropout < 1) {\n        inputs = mul(inputs, dpMask[0]);\n      }\n      let matrixX = dot2(inputs, this.kernel.read());\n      if (this.useBias) {\n        matrixX = biasAdd(matrixX, this.bias.read());\n      }\n      if (0 < this.recurrentDropout && this.recurrentDropout < 1) {\n        hTMinus1 = mul(hTMinus1, recDpMask[0]);\n      }\n      const recurrentKernelValue = this.recurrentKernel.read();\n      const [rk1, rk2] = split(recurrentKernelValue, [2 * this.units, this.units], recurrentKernelValue.rank - 1);\n      const matrixInner = dot2(hTMinus1, rk1);\n      const [xZ, xR, xH] = split(matrixX, 3, matrixX.rank - 1);\n      const [recurrentZ, recurrentR] = split(matrixInner, 2, matrixInner.rank - 1);\n      z = this.recurrentActivation.apply(add2(xZ, recurrentZ));\n      r2 = this.recurrentActivation.apply(add2(xR, recurrentR));\n      const recurrentH = dot2(mul(r2, hTMinus1), rk2);\n      hh = this.activation.apply(add2(xH, recurrentH));\n      const h = add2(mul(z, hTMinus1), mul(add2(1, neg(z)), hh));\n      return [h, h];\n    });\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = {\n      units: this.units,\n      activation: serializeActivation(this.activation),\n      recurrentActivation: serializeActivation(this.recurrentActivation),\n      useBias: this.useBias,\n      kernelInitializer: serializeInitializer(this.kernelInitializer),\n      recurrentInitializer: serializeInitializer(this.recurrentInitializer),\n      biasInitializer: serializeInitializer(this.biasInitializer),\n      kernelRegularizer: serializeRegularizer(this.kernelRegularizer),\n      recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),\n      biasRegularizer: serializeRegularizer(this.biasRegularizer),\n      activityRegularizer: serializeRegularizer(this.activityRegularizer),\n      kernelConstraint: serializeConstraint(this.kernelConstraint),\n      recurrentConstraint: serializeConstraint(this.recurrentConstraint),\n      biasConstraint: serializeConstraint(this.biasConstraint),\n      dropout: this.dropout,\n      recurrentDropout: this.recurrentDropout,\n      implementation: this.implementation,\n      resetAfter: false\n    };\n    return Object.assign({}, baseConfig, config);\n  }\n};\nGRUCell.className = \"GRUCell\";\nserialization_exports.registerClass(GRUCell);\nvar GRU = class extends RNN {\n  constructor(args) {\n    if (args.implementation === 0) {\n      console.warn(\"`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call.\");\n    }\n    args.cell = new GRUCell(args);\n    super(args);\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      if (this.cell.dropoutMask != null) {\n        dispose(this.cell.dropoutMask);\n        this.cell.dropoutMask = null;\n      }\n      if (this.cell.recurrentDropoutMask != null) {\n        dispose(this.cell.recurrentDropoutMask);\n        this.cell.recurrentDropoutMask = null;\n      }\n      const mask = kwargs == null ? null : kwargs[\"mask\"];\n      const training = kwargs == null ? null : kwargs[\"training\"];\n      const initialState = kwargs == null ? null : kwargs[\"initialState\"];\n      return super.call(inputs, { mask, training, initialState });\n    });\n  }\n  static fromConfig(cls, config) {\n    if (config[\"implmentation\"] === 0) {\n      config[\"implementation\"] = 1;\n    }\n    return new cls(config);\n  }\n};\nGRU.className = \"GRU\";\nserialization_exports.registerClass(GRU);\nvar LSTMCell = class extends RNNCell {\n  constructor(args) {\n    super(args);\n    this.DEFAULT_ACTIVATION = \"tanh\";\n    this.DEFAULT_RECURRENT_ACTIVATION = \"hardSigmoid\";\n    this.DEFAULT_KERNEL_INITIALIZER = \"glorotNormal\";\n    this.DEFAULT_RECURRENT_INITIALIZER = \"orthogonal\";\n    this.DEFAULT_BIAS_INITIALIZER = \"zeros\";\n    this.units = args.units;\n    assertPositiveInteger(this.units, \"units\");\n    this.activation = getActivation(args.activation === void 0 ? this.DEFAULT_ACTIVATION : args.activation);\n    this.recurrentActivation = getActivation(args.recurrentActivation === void 0 ? this.DEFAULT_RECURRENT_ACTIVATION : args.recurrentActivation);\n    this.useBias = args.useBias == null ? true : args.useBias;\n    this.kernelInitializer = getInitializer(args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER);\n    this.recurrentInitializer = getInitializer(args.recurrentInitializer || this.DEFAULT_RECURRENT_INITIALIZER);\n    this.biasInitializer = getInitializer(args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER);\n    this.unitForgetBias = args.unitForgetBias;\n    this.kernelRegularizer = getRegularizer(args.kernelRegularizer);\n    this.recurrentRegularizer = getRegularizer(args.recurrentRegularizer);\n    this.biasRegularizer = getRegularizer(args.biasRegularizer);\n    this.kernelConstraint = getConstraint(args.kernelConstraint);\n    this.recurrentConstraint = getConstraint(args.recurrentConstraint);\n    this.biasConstraint = getConstraint(args.biasConstraint);\n    this.dropout = min2([1, max2([0, args.dropout == null ? 0 : args.dropout])]);\n    this.recurrentDropout = min2([\n      1,\n      max2([0, args.recurrentDropout == null ? 0 : args.recurrentDropout])\n    ]);\n    this.dropoutFunc = args.dropoutFunc;\n    this.implementation = args.implementation;\n    this.stateSize = [this.units, this.units];\n    this.dropoutMask = null;\n    this.recurrentDropoutMask = null;\n  }\n  build(inputShape) {\n    var _a;\n    inputShape = getExactlyOneShape(inputShape);\n    const inputDim = inputShape[inputShape.length - 1];\n    this.kernel = this.addWeight(\"kernel\", [inputDim, this.units * 4], null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n    this.recurrentKernel = this.addWeight(\"recurrent_kernel\", [this.units, this.units * 4], null, this.recurrentInitializer, this.recurrentRegularizer, true, this.recurrentConstraint);\n    let biasInitializer;\n    if (this.useBias) {\n      if (this.unitForgetBias) {\n        const capturedBiasInit = this.biasInitializer;\n        const capturedUnits = this.units;\n        biasInitializer = new (_a = class CustomInit extends Initializer {\n          apply(shape, dtype) {\n            const bI = capturedBiasInit.apply([capturedUnits]);\n            const bF = new Ones().apply([capturedUnits]);\n            const bCAndH = capturedBiasInit.apply([capturedUnits * 2]);\n            return concatAlongFirstAxis(concatAlongFirstAxis(bI, bF), bCAndH);\n          }\n        }, _a.className = \"CustomInit\", _a)();\n      } else {\n        biasInitializer = this.biasInitializer;\n      }\n      this.bias = this.addWeight(\"bias\", [this.units * 4], null, biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    } else {\n      this.bias = null;\n    }\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const training = kwargs[\"training\"] == null ? false : kwargs[\"training\"];\n      inputs = inputs;\n      if (inputs.length !== 3) {\n        throw new ValueError(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${inputs.length}.`);\n      }\n      let hTMinus1 = inputs[1];\n      const cTMinus1 = inputs[2];\n      inputs = inputs[0];\n      if (0 < this.dropout && this.dropout < 1 && this.dropoutMask == null) {\n        this.dropoutMask = generateDropoutMask({\n          ones: () => onesLike(inputs),\n          rate: this.dropout,\n          training,\n          count: 4,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      if (0 < this.recurrentDropout && this.recurrentDropout < 1 && this.recurrentDropoutMask == null) {\n        this.recurrentDropoutMask = generateDropoutMask({\n          ones: () => onesLike(hTMinus1),\n          rate: this.recurrentDropout,\n          training,\n          count: 4,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      const dpMask = this.dropoutMask;\n      const recDpMask = this.recurrentDropoutMask;\n      let i2;\n      let f;\n      let c;\n      let o;\n      if (0 < this.dropout && this.dropout < 1) {\n        inputs = mul(inputs, dpMask[0]);\n      }\n      let z = dot2(inputs, this.kernel.read());\n      if (0 < this.recurrentDropout && this.recurrentDropout < 1) {\n        hTMinus1 = mul(hTMinus1, recDpMask[0]);\n      }\n      z = add2(z, dot2(hTMinus1, this.recurrentKernel.read()));\n      if (this.useBias) {\n        z = biasAdd(z, this.bias.read());\n      }\n      const [z0, z1, z2, z3] = split(z, 4, z.rank - 1);\n      i2 = this.recurrentActivation.apply(z0);\n      f = this.recurrentActivation.apply(z1);\n      c = add2(mul(f, cTMinus1), mul(i2, this.activation.apply(z2)));\n      o = this.recurrentActivation.apply(z3);\n      const h = mul(o, this.activation.apply(c));\n      return [h, h, c];\n    });\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = {\n      units: this.units,\n      activation: serializeActivation(this.activation),\n      recurrentActivation: serializeActivation(this.recurrentActivation),\n      useBias: this.useBias,\n      kernelInitializer: serializeInitializer(this.kernelInitializer),\n      recurrentInitializer: serializeInitializer(this.recurrentInitializer),\n      biasInitializer: serializeInitializer(this.biasInitializer),\n      unitForgetBias: this.unitForgetBias,\n      kernelRegularizer: serializeRegularizer(this.kernelRegularizer),\n      recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),\n      biasRegularizer: serializeRegularizer(this.biasRegularizer),\n      activityRegularizer: serializeRegularizer(this.activityRegularizer),\n      kernelConstraint: serializeConstraint(this.kernelConstraint),\n      recurrentConstraint: serializeConstraint(this.recurrentConstraint),\n      biasConstraint: serializeConstraint(this.biasConstraint),\n      dropout: this.dropout,\n      recurrentDropout: this.recurrentDropout,\n      implementation: this.implementation\n    };\n    return Object.assign({}, baseConfig, config);\n  }\n};\nLSTMCell.className = \"LSTMCell\";\nserialization_exports.registerClass(LSTMCell);\nvar LSTM = class extends RNN {\n  constructor(args) {\n    if (args.implementation === 0) {\n      console.warn(\"`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call.\");\n    }\n    args.cell = new LSTMCell(args);\n    super(args);\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      if (this.cell.dropoutMask != null) {\n        dispose(this.cell.dropoutMask);\n        this.cell.dropoutMask = null;\n      }\n      if (this.cell.recurrentDropoutMask != null) {\n        dispose(this.cell.recurrentDropoutMask);\n        this.cell.recurrentDropoutMask = null;\n      }\n      const mask = kwargs == null ? null : kwargs[\"mask\"];\n      const training = kwargs == null ? null : kwargs[\"training\"];\n      const initialState = kwargs == null ? null : kwargs[\"initialState\"];\n      return super.call(inputs, { mask, training, initialState });\n    });\n  }\n  static fromConfig(cls, config) {\n    if (config[\"implmentation\"] === 0) {\n      config[\"implementation\"] = 1;\n    }\n    return new cls(config);\n  }\n};\nLSTM.className = \"LSTM\";\nserialization_exports.registerClass(LSTM);\nvar StackedRNNCells = class extends RNNCell {\n  constructor(args) {\n    super(args);\n    this.cells = args.cells;\n  }\n  get stateSize() {\n    const stateSize = [];\n    for (const cell of this.cells.slice().reverse()) {\n      if (Array.isArray(cell.stateSize)) {\n        stateSize.push(...cell.stateSize);\n      } else {\n        stateSize.push(cell.stateSize);\n      }\n    }\n    return stateSize;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = inputs;\n      let states = inputs.slice(1);\n      const nestedStates = [];\n      for (const cell of this.cells.slice().reverse()) {\n        if (Array.isArray(cell.stateSize)) {\n          nestedStates.push(states.splice(0, cell.stateSize.length));\n        } else {\n          nestedStates.push(states.splice(0, 1));\n        }\n      }\n      nestedStates.reverse();\n      const newNestedStates = [];\n      let callInputs;\n      for (let i2 = 0; i2 < this.cells.length; ++i2) {\n        const cell = this.cells[i2];\n        states = nestedStates[i2];\n        if (i2 === 0) {\n          callInputs = [inputs[0]].concat(states);\n        } else {\n          callInputs = [callInputs[0]].concat(states);\n        }\n        callInputs = cell.call(callInputs, kwargs);\n        newNestedStates.push(callInputs.slice(1));\n      }\n      states = [];\n      for (const cellStates of newNestedStates.slice().reverse()) {\n        states.push(...cellStates);\n      }\n      return [callInputs[0]].concat(states);\n    });\n  }\n  build(inputShape) {\n    if (isArrayOfShapes(inputShape)) {\n      inputShape = inputShape[0];\n    }\n    inputShape = inputShape;\n    let outputDim;\n    this.cells.forEach((cell, i2) => {\n      nameScope(`RNNCell_${i2}`, () => {\n        cell.build(inputShape);\n        if (Array.isArray(cell.stateSize)) {\n          outputDim = cell.stateSize[0];\n        } else {\n          outputDim = cell.stateSize;\n        }\n        inputShape = [inputShape[0], outputDim];\n      });\n    });\n    this.built = true;\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const getCellConfig = (cell) => {\n      return {\n        \"className\": cell.getClassName(),\n        \"config\": cell.getConfig()\n      };\n    };\n    const cellConfigs = this.cells.map(getCellConfig);\n    const config = { \"cells\": cellConfigs };\n    return Object.assign({}, baseConfig, config);\n  }\n  static fromConfig(cls, config, customObjects = {}) {\n    const cells = [];\n    for (const cellConfig of config[\"cells\"]) {\n      cells.push(deserialize(cellConfig, customObjects));\n    }\n    return new cls({ cells });\n  }\n  get trainableWeights() {\n    if (!this.trainable) {\n      return [];\n    }\n    const weights = [];\n    for (const cell of this.cells) {\n      weights.push(...cell.trainableWeights);\n    }\n    return weights;\n  }\n  get nonTrainableWeights() {\n    const weights = [];\n    for (const cell of this.cells) {\n      weights.push(...cell.nonTrainableWeights);\n    }\n    if (!this.trainable) {\n      const trainableWeights = [];\n      for (const cell of this.cells) {\n        trainableWeights.push(...cell.trainableWeights);\n      }\n      return trainableWeights.concat(weights);\n    }\n    return weights;\n  }\n  getWeights() {\n    const weights = [];\n    for (const cell of this.cells) {\n      weights.push(...cell.weights);\n    }\n    return batchGetValue(weights);\n  }\n  setWeights(weights) {\n    const tuples = [];\n    for (const cell of this.cells) {\n      const numParams = cell.weights.length;\n      const inputWeights = weights.splice(numParams);\n      for (let i2 = 0; i2 < cell.weights.length; ++i2) {\n        tuples.push([cell.weights[i2], inputWeights[i2]]);\n      }\n    }\n    batchSetValue(tuples);\n  }\n};\nStackedRNNCells.className = \"StackedRNNCells\";\nserialization_exports.registerClass(StackedRNNCells);\nfunction generateDropoutMask(args) {\n  const { ones: ones4, rate, training = false, count: count2 = 1, dropoutFunc } = args;\n  const droppedInputs = () => dropoutFunc != null ? dropoutFunc(ones4(), rate) : dropout2(ones4(), rate);\n  const createMask = () => inTrainPhase(droppedInputs, ones4, training);\n  if (!count2 || count2 <= 1) {\n    return keep(createMask().clone());\n  }\n  const masks = Array(count2).fill(void 0).map(createMask);\n  return masks.map((m) => keep(m.clone()));\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/convolutional_recurrent.js\nvar __rest = function(s2, e2) {\n  var t2 = {};\n  for (var p2 in s2)\n    if (Object.prototype.hasOwnProperty.call(s2, p2) && e2.indexOf(p2) < 0)\n      t2[p2] = s2[p2];\n  if (s2 != null && typeof Object.getOwnPropertySymbols === \"function\")\n    for (var i2 = 0, p2 = Object.getOwnPropertySymbols(s2); i2 < p2.length; i2++) {\n      if (e2.indexOf(p2[i2]) < 0 && Object.prototype.propertyIsEnumerable.call(s2, p2[i2]))\n        t2[p2[i2]] = s2[p2[i2]];\n    }\n  return t2;\n};\nvar ConvRNN2D = class extends RNN {\n  constructor(args) {\n    if (args.unroll) {\n      throw new NotImplementedError(\"Unrolling is not possible with convolutional RNNs.\");\n    }\n    if (Array.isArray(args.cell)) {\n      throw new NotImplementedError(\"It is not possible at the moment to stack convolutional cells.\");\n    }\n    super(args);\n    this.inputSpec = [new InputSpec({ ndim: 5 })];\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      if (this.cell.dropoutMask != null) {\n        dispose(this.cell.dropoutMask);\n        this.cell.dropoutMask = null;\n      }\n      if (this.cell.recurrentDropoutMask != null) {\n        dispose(this.cell.recurrentDropoutMask);\n        this.cell.recurrentDropoutMask = null;\n      }\n      if (kwargs && kwargs[\"constants\"]) {\n        throw new ValueError(\"ConvRNN2D cell does not support constants\");\n      }\n      const mask = kwargs == null ? null : kwargs[\"mask\"];\n      const training = kwargs == null ? null : kwargs[\"training\"];\n      const initialState = kwargs == null ? null : kwargs[\"initialState\"];\n      return super.call(inputs, { mask, training, initialState });\n    });\n  }\n  computeOutputShape(inputShape) {\n    let outShape = this.computeSingleOutputShape(inputShape);\n    if (!this.returnSequences) {\n      outShape = [outShape[0], ...outShape.slice(2)];\n    }\n    if (this.returnState) {\n      outShape = [outShape, ...Array(2).fill([inputShape[0], ...outShape.slice(-3)])];\n    }\n    return outShape;\n  }\n  getInitialState(inputs) {\n    return tidy(() => {\n      const { stateSize } = this.cell;\n      const inputShape = inputs.shape;\n      const outputShape = this.computeSingleOutputShape(inputShape);\n      const stateShape = [outputShape[0], ...outputShape.slice(2)];\n      const initialState = zeros(stateShape);\n      if (Array.isArray(stateSize)) {\n        return Array(stateSize.length).fill(initialState);\n      }\n      return [initialState];\n    });\n  }\n  resetStates(states, training = false) {\n    tidy(() => {\n      if (!this.stateful) {\n        throw new AttributeError(\"Cannot call resetStates() on an RNN Layer that is not stateful.\");\n      }\n      const inputShape = this.inputSpec[0].shape;\n      const outputShape = this.computeSingleOutputShape(inputShape);\n      const stateShape = [outputShape[0], ...outputShape.slice(2)];\n      const batchSize = inputShape[0];\n      if (batchSize == null) {\n        throw new ValueError(\"If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \\n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.\");\n      }\n      if (this.getStates() == null) {\n        if (Array.isArray(this.cell.stateSize)) {\n          this.states_ = this.cell.stateSize.map(() => zeros(stateShape));\n        } else {\n          this.states_ = [zeros(stateShape)];\n        }\n      } else if (states == null) {\n        dispose(this.states_);\n        if (this.keptStates != null) {\n          dispose(this.keptStates);\n          this.keptStates = [];\n        }\n        if (Array.isArray(this.cell.stateSize)) {\n          this.states_ = this.cell.stateSize.map(() => zeros(stateShape));\n        } else {\n          this.states_[0] = zeros(stateShape);\n        }\n      } else {\n        if (!Array.isArray(states)) {\n          states = [states];\n        }\n        if (states.length !== this.states_.length) {\n          throw new ValueError(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${states.length} state value(s). Input received: ${states}`);\n        }\n        if (training) {\n          this.keptStates.push(this.states_.slice());\n        } else {\n          dispose(this.states_);\n        }\n        for (let index = 0; index < this.states_.length; ++index) {\n          const value = states[index];\n          const expectedShape = stateShape;\n          if (!util_exports.arraysEqual(value.shape, expectedShape)) {\n            throw new ValueError(`State ${index} is incompatible with layer ${this.name}: expected shape=${expectedShape}, received shape=${value.shape}`);\n          }\n          this.states_[index] = value;\n        }\n      }\n      this.states_ = this.states_.map((state) => keep(state.clone()));\n    });\n  }\n  computeSingleOutputShape(inputShape) {\n    const { dataFormat, filters, kernelSize, padding, strides, dilationRate } = this.cell;\n    const isChannelsFirst = dataFormat === \"channelsFirst\";\n    const h = inputShape[isChannelsFirst ? 3 : 2];\n    const w = inputShape[isChannelsFirst ? 4 : 3];\n    const hOut = convOutputLength(h, kernelSize[0], padding, strides[0], dilationRate[0]);\n    const wOut = convOutputLength(w, kernelSize[1], padding, strides[1], dilationRate[1]);\n    const outShape = [\n      ...inputShape.slice(0, 2),\n      ...isChannelsFirst ? [filters, hOut, wOut] : [hOut, wOut, filters]\n    ];\n    return outShape;\n  }\n};\nConvRNN2D.className = \"ConvRNN2D\";\nvar ConvLSTM2DCell = class extends LSTMCell {\n  constructor(args) {\n    const { filters, kernelSize, strides, padding, dataFormat, dilationRate } = args;\n    super(Object.assign({}, args, { units: filters }));\n    this.filters = filters;\n    assertPositiveInteger(this.filters, \"filters\");\n    this.kernelSize = normalizeArray(kernelSize, 2, \"kernelSize\");\n    this.kernelSize.forEach((size) => assertPositiveInteger(size, \"kernelSize\"));\n    this.strides = normalizeArray(strides || 1, 2, \"strides\");\n    this.strides.forEach((stride) => assertPositiveInteger(stride, \"strides\"));\n    this.padding = padding || \"valid\";\n    checkPaddingMode(this.padding);\n    this.dataFormat = dataFormat || \"channelsLast\";\n    checkDataFormat(this.dataFormat);\n    this.dilationRate = normalizeArray(dilationRate || 1, 2, \"dilationRate\");\n    this.dilationRate.forEach((rate) => assertPositiveInteger(rate, \"dilationRate\"));\n  }\n  build(inputShape) {\n    var _a;\n    inputShape = getExactlyOneShape(inputShape);\n    const channelAxis = this.dataFormat === \"channelsFirst\" ? 1 : inputShape.length - 1;\n    if (inputShape[channelAxis] == null) {\n      throw new ValueError(`The channel dimension of the input should be defined. Found ${inputShape[channelAxis]}`);\n    }\n    const inputDim = inputShape[channelAxis];\n    const numOfKernels = 4;\n    const kernelShape = this.kernelSize.concat([inputDim, this.filters * numOfKernels]);\n    this.kernel = this.addWeight(\"kernel\", kernelShape, null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n    const recurrentKernelShape = this.kernelSize.concat([this.filters, this.filters * numOfKernels]);\n    this.recurrentKernel = this.addWeight(\"recurrent_kernel\", recurrentKernelShape, null, this.recurrentInitializer, this.recurrentRegularizer, true, this.recurrentConstraint);\n    if (this.useBias) {\n      let biasInitializer;\n      if (this.unitForgetBias) {\n        const init2 = this.biasInitializer;\n        const filters = this.filters;\n        biasInitializer = new (_a = class CustomInit extends Initializer {\n          apply(shape, dtype) {\n            const biasI = init2.apply([filters]);\n            const biasF = ones2([filters]);\n            const biasCAndO = init2.apply([filters * 2]);\n            return concatenate([biasI, biasF, biasCAndO]);\n          }\n        }, _a.className = \"CustomInit\", _a)();\n      } else {\n        biasInitializer = this.biasInitializer;\n      }\n      this.bias = this.addWeight(\"bias\", [this.filters * numOfKernels], null, biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    }\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      if (inputs.length !== 3) {\n        throw new ValueError(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${inputs.length}.`);\n      }\n      const training = kwargs[\"training\"] || false;\n      const x = inputs[0];\n      const hTMinus1 = inputs[1];\n      const cTMinus1 = inputs[2];\n      const numOfKernels = 4;\n      if (0 < this.dropout && this.dropout < 1 && this.dropoutMask == null) {\n        this.dropoutMask = generateDropoutMask({\n          ones: () => onesLike(x),\n          rate: this.dropout,\n          training,\n          count: numOfKernels,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      const dropoutMask = this.dropoutMask;\n      const applyDropout = (x2, mask, index) => {\n        if (!mask || !mask[index]) {\n          return x2;\n        }\n        return mul(mask[index], x2);\n      };\n      let xI = applyDropout(x, dropoutMask, 0);\n      let xF = applyDropout(x, dropoutMask, 1);\n      let xC = applyDropout(x, dropoutMask, 2);\n      let xO = applyDropout(x, dropoutMask, 3);\n      if (0 < this.recurrentDropout && this.recurrentDropout < 1 && this.recurrentDropoutMask == null) {\n        this.recurrentDropoutMask = generateDropoutMask({\n          ones: () => onesLike(hTMinus1),\n          rate: this.recurrentDropout,\n          training,\n          count: numOfKernels,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      const recDropoutMask = this.recurrentDropoutMask;\n      let hI = applyDropout(hTMinus1, recDropoutMask, 0);\n      let hF = applyDropout(hTMinus1, recDropoutMask, 1);\n      let hC = applyDropout(hTMinus1, recDropoutMask, 2);\n      let hO = applyDropout(hTMinus1, recDropoutMask, 3);\n      const kernelChannelAxis = 3;\n      const [kernelI, kernelF, kernelC, kernelO] = split(this.kernel.read(), numOfKernels, kernelChannelAxis);\n      const [biasI, biasF, biasC, biasO] = this.useBias ? split(this.bias.read(), numOfKernels) : [null, null, null, null];\n      xI = this.inputConv(xI, kernelI, biasI, this.padding);\n      xF = this.inputConv(xF, kernelF, biasF, this.padding);\n      xC = this.inputConv(xC, kernelC, biasC, this.padding);\n      xO = this.inputConv(xO, kernelO, biasO, this.padding);\n      const [recKernelI, recKernelF, recKernelC, recKernelO] = split(this.recurrentKernel.read(), numOfKernels, kernelChannelAxis);\n      hI = this.recurrentConv(hI, recKernelI);\n      hF = this.recurrentConv(hF, recKernelF);\n      hC = this.recurrentConv(hC, recKernelC);\n      hO = this.recurrentConv(hO, recKernelO);\n      const i2 = this.recurrentActivation.apply(add2(xI, hI));\n      const f = this.recurrentActivation.apply(add2(xF, hF));\n      const c = add2(mul(f, cTMinus1), mul(i2, this.activation.apply(add2(xC, hC))));\n      const h = mul(this.recurrentActivation.apply(add2(xO, hO)), this.activation.apply(c));\n      return [h, h, c];\n    });\n  }\n  getConfig() {\n    const _a = super.getConfig(), { \"units\": _ } = _a, baseConfig = __rest(_a, [\"units\"]);\n    const config = {\n      filters: this.filters,\n      kernelSize: this.kernelSize,\n      padding: this.padding,\n      dataFormat: this.dataFormat,\n      dilationRate: this.dilationRate,\n      strides: this.strides\n    };\n    return Object.assign({}, baseConfig, config);\n  }\n  inputConv(x, w, b, padding) {\n    const out = conv2d(x, w, this.strides, padding || \"valid\", this.dataFormat === \"channelsFirst\" ? \"NCHW\" : \"NHWC\", this.dilationRate);\n    if (b) {\n      return biasAdd(out, b, this.dataFormat);\n    }\n    return out;\n  }\n  recurrentConv(x, w) {\n    const strides = 1;\n    return conv2d(x, w, strides, \"same\", this.dataFormat === \"channelsFirst\" ? \"NCHW\" : \"NHWC\");\n  }\n};\nConvLSTM2DCell.className = \"ConvLSTM2DCell\";\nserialization_exports.registerClass(ConvLSTM2DCell);\nvar ConvLSTM2D = class extends ConvRNN2D {\n  constructor(args) {\n    const cell = new ConvLSTM2DCell(args);\n    super(Object.assign({}, args, { cell }));\n  }\n  static fromConfig(cls, config) {\n    return new cls(config);\n  }\n};\nConvLSTM2D.className = \"ConvLSTM2D\";\nserialization_exports.registerClass(ConvLSTM2D);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/core.js\nvar Dropout = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.rate = Math.max(Math.min(args.rate, 1), 0);\n    this.noiseShape = args.noiseShape;\n    this.seed = args.seed;\n    this.supportsMasking = true;\n  }\n  getNoiseShape(input2) {\n    if (this.noiseShape == null) {\n      return this.noiseShape;\n    }\n    const inputShape = input2.shape;\n    const noiseShape = [];\n    for (let i2 = 0; i2 < this.noiseShape.length; ++i2) {\n      noiseShape.push(this.noiseShape[i2] == null ? inputShape[i2] : this.noiseShape[i2]);\n    }\n    return noiseShape;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      const input2 = getExactlyOneTensor(inputs);\n      if (0 < this.rate && this.rate < 1) {\n        const training = kwargs[\"training\"] == null ? false : kwargs[\"training\"];\n        const noiseShape = this.getNoiseShape(input2);\n        const output = inTrainPhase(() => dropout2(input2, this.rate, noiseShape, this.seed), () => input2, training);\n        return output;\n      }\n      return inputs;\n    });\n  }\n  getConfig() {\n    const config = {\n      rate: this.rate,\n      noiseShape: this.noiseShape,\n      seed: this.seed\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  dispose() {\n    return super.dispose();\n  }\n};\nDropout.className = \"Dropout\";\nserialization_exports.registerClass(Dropout);\nvar SpatialDropout1D = class extends Dropout {\n  constructor(args) {\n    super(args);\n    this.inputSpec = [{ ndim: 3 }];\n  }\n  getNoiseShape(input2) {\n    const inputShape = input2.shape;\n    return [inputShape[0], 1, inputShape[2]];\n  }\n};\nSpatialDropout1D.className = \"SpatialDropout1D\";\nserialization_exports.registerClass(SpatialDropout1D);\nvar Dense = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.activation = null;\n    this.useBias = true;\n    this.kernel = null;\n    this.bias = null;\n    this.DEFAULT_KERNEL_INITIALIZER = \"glorotNormal\";\n    this.DEFAULT_BIAS_INITIALIZER = \"zeros\";\n    if (args.batchInputShape == null && args.inputShape == null && args.inputDim != null) {\n      let batchSize = null;\n      if (args.batchSize != null) {\n        batchSize = args.batchSize;\n      }\n      this.batchInputShape = [batchSize, args.inputDim];\n    }\n    this.units = args.units;\n    assertPositiveInteger(this.units, \"units\");\n    this.activation = getActivation(args.activation);\n    if (args.useBias != null) {\n      this.useBias = args.useBias;\n    }\n    this.kernelInitializer = getInitializer(args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER);\n    this.biasInitializer = getInitializer(args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER);\n    this.kernelConstraint = getConstraint(args.kernelConstraint);\n    this.biasConstraint = getConstraint(args.biasConstraint);\n    this.kernelRegularizer = getRegularizer(args.kernelRegularizer);\n    this.biasRegularizer = getRegularizer(args.biasRegularizer);\n    this.activityRegularizer = getRegularizer(args.activityRegularizer);\n    this.supportsMasking = true;\n    this.inputSpec = [{ minNDim: 2 }];\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const inputLastDim = inputShape[inputShape.length - 1];\n    if (this.kernel == null) {\n      this.kernel = this.addWeight(\"kernel\", [inputLastDim, this.units], null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n      if (this.useBias) {\n        this.bias = this.addWeight(\"bias\", [this.units], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n      }\n    }\n    this.inputSpec = [{ minNDim: 2, axes: { [-1]: inputLastDim } }];\n    this.built = true;\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const outputShape = inputShape.slice();\n    outputShape[outputShape.length - 1] = this.units;\n    return outputShape;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      const input2 = getExactlyOneTensor(inputs);\n      const fusedActivationName = mapActivationToFusedKernel(this.activation.getClassName());\n      let output;\n      if (fusedActivationName != null) {\n        output = dot2(input2, this.kernel.read(), fusedActivationName, this.bias ? this.bias.read() : null);\n      } else {\n        output = dot2(input2, this.kernel.read());\n        if (this.bias != null) {\n          output = biasAdd(output, this.bias.read());\n        }\n        if (this.activation != null) {\n          output = this.activation.apply(output);\n        }\n      }\n      return output;\n    });\n  }\n  getConfig() {\n    const config = {\n      units: this.units,\n      activation: serializeActivation(this.activation),\n      useBias: this.useBias,\n      kernelInitializer: serializeInitializer(this.kernelInitializer),\n      biasInitializer: serializeInitializer(this.biasInitializer),\n      kernelRegularizer: serializeRegularizer(this.kernelRegularizer),\n      biasRegularizer: serializeRegularizer(this.biasRegularizer),\n      activityRegularizer: serializeRegularizer(this.activityRegularizer),\n      kernelConstraint: serializeConstraint(this.kernelConstraint),\n      biasConstraint: serializeConstraint(this.biasConstraint)\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nDense.className = \"Dense\";\nserialization_exports.registerClass(Dense);\nvar Flatten = class extends Layer {\n  constructor(args) {\n    args = args || {};\n    super(args);\n    this.inputSpec = [{ minNDim: 3 }];\n    this.dataFormat = args.dataFormat;\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    for (const dim of inputShape.slice(1)) {\n      if (dim == null) {\n        throw new ValueError(`The shape of the input to \"Flatten\" is not fully defined (got ${inputShape.slice(1)}). Make sure to pass a complete \"input_shape\" or \"batch_input_shape\" argument to the first layer in your model.`);\n      }\n    }\n    return [inputShape[0], arrayProd(inputShape, 1)];\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      let input2 = getExactlyOneTensor(inputs);\n      if (this.dataFormat === \"channelsFirst\" && input2.rank > 1) {\n        const permutation = [0];\n        for (let i2 = 2; i2 < input2.rank; ++i2) {\n          permutation.push(i2);\n        }\n        permutation.push(1);\n        input2 = transpose(input2, permutation);\n      }\n      return batchFlatten(input2);\n    });\n  }\n  getConfig() {\n    const config = {};\n    if (this.dataFormat != null) {\n      config[\"dataFormat\"] = this.dataFormat;\n    }\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nFlatten.className = \"Flatten\";\nserialization_exports.registerClass(Flatten);\nvar Activation2 = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.supportsMasking = true;\n    this.activation = getActivation(args.activation);\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      const input2 = getExactlyOneTensor(inputs);\n      return this.activation.apply(input2);\n    });\n  }\n  getConfig() {\n    const config = { activation: serializeActivation(this.activation) };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nActivation2.className = \"Activation\";\nserialization_exports.registerClass(Activation2);\nvar RepeatVector = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.n = args.n;\n    this.inputSpec = [{ ndim: 2 }];\n  }\n  computeOutputShape(inputShape) {\n    return [inputShape[0], this.n, inputShape[1]];\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = getExactlyOneTensor(inputs);\n      return repeat(inputs, this.n);\n    });\n  }\n  getConfig() {\n    const config = {\n      n: this.n\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nRepeatVector.className = \"RepeatVector\";\nserialization_exports.registerClass(RepeatVector);\nvar Reshape2 = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.targetShape = args.targetShape;\n    for (let i2 = 0; i2 < this.targetShape.length; ++i2) {\n      if (this.isUnknown(this.targetShape[i2])) {\n        this.targetShape[i2] = null;\n      }\n    }\n  }\n  isUnknown(dim) {\n    return dim < 0 || dim == null;\n  }\n  fixUnknownDimension(inputShape, outputShape) {\n    const errorMsg = \"Total size of new array must be unchanged.\";\n    const finalShape = outputShape.slice();\n    let known = 1;\n    let unknown = null;\n    for (let i2 = 0; i2 < finalShape.length; ++i2) {\n      const dim = finalShape[i2];\n      if (this.isUnknown(dim)) {\n        if (unknown === null) {\n          unknown = i2;\n        } else {\n          throw new ValueError(\"Can only specifiy one unknown dimension.\");\n        }\n      } else {\n        known *= dim;\n      }\n    }\n    const originalSize = arrayProd(inputShape);\n    if (unknown !== null) {\n      if (known === 0 || originalSize % known !== 0) {\n        throw new ValueError(errorMsg);\n      }\n      finalShape[unknown] = originalSize / known;\n    } else if (originalSize !== known) {\n      throw new ValueError(errorMsg);\n    }\n    return finalShape;\n  }\n  computeOutputShape(inputShape) {\n    let anyUnknownDims = false;\n    for (let i2 = 0; i2 < inputShape.length; ++i2) {\n      if (this.isUnknown(inputShape[i2])) {\n        anyUnknownDims = true;\n        break;\n      }\n    }\n    if (anyUnknownDims) {\n      return inputShape.slice(0, 1).concat(this.targetShape);\n    } else {\n      return inputShape.slice(0, 1).concat(this.fixUnknownDimension(inputShape.slice(1), this.targetShape));\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      const input2 = getExactlyOneTensor(inputs);\n      const inputShape = input2.shape;\n      const outputShape = inputShape.slice(0, 1).concat(this.fixUnknownDimension(inputShape.slice(1), this.targetShape));\n      return reshape(input2, outputShape);\n    });\n  }\n  getConfig() {\n    const config = {\n      targetShape: this.targetShape\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nReshape2.className = \"Reshape\";\nserialization_exports.registerClass(Reshape2);\nvar Permute = class extends Layer {\n  constructor(args) {\n    super(args);\n    if (args.dims == null) {\n      throw new Error(\"Required configuration field `dims` is missing during Permute constructor call.\");\n    }\n    if (!Array.isArray(args.dims)) {\n      throw new Error(`Permute constructor requires \\`dims\\` to be an Array, but received ${args.dims} instead.`);\n    }\n    const expectedSortedIndices = range2(1, args.dims.length + 1);\n    if (!util_exports.arraysEqual(args.dims.slice().sort(), expectedSortedIndices)) {\n      throw new Error(\"Invalid permutation `dims`: \" + JSON.stringify(args.dims) + \" `dims` must contain consecutive integers starting from 1.\");\n    }\n    this.dims = args.dims;\n    this.dimsIncludingBatch = [0].concat(this.dims);\n    this.inputSpec = [new InputSpec({ ndim: this.dims.length + 1 })];\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const outputShape = inputShape.slice();\n    this.dims.forEach((dim, i2) => {\n      outputShape[i2 + 1] = inputShape[dim];\n    });\n    return outputShape;\n  }\n  call(inputs, kwargs) {\n    return transpose(getExactlyOneTensor(inputs), this.dimsIncludingBatch);\n  }\n  getConfig() {\n    const config = {\n      dims: this.dims\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nPermute.className = \"Permute\";\nserialization_exports.registerClass(Permute);\nvar Masking = class extends Layer {\n  constructor(args) {\n    super(args == null ? {} : args);\n    this.supportsMasking = true;\n    if (args != null) {\n      this.maskValue = args.maskValue == null ? 0 : args.maskValue;\n    } else {\n      this.maskValue = 0;\n    }\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = { maskValue: this.maskValue };\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  computeMask(inputs, mask) {\n    const input2 = getExactlyOneTensor(inputs);\n    const axis = -1;\n    return any(notEqual(input2, this.maskValue), axis);\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      const input2 = getExactlyOneTensor(inputs);\n      const axis = -1;\n      const keepDims = true;\n      const booleanMask = any(notEqual(input2, this.maskValue), axis, keepDims);\n      const output = mul(input2, cast(booleanMask, input2.dtype));\n      return output;\n    });\n  }\n};\nMasking.className = \"Masking\";\nserialization_exports.registerClass(Masking);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/embeddings.js\nvar Embedding = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.embeddings = null;\n    this.DEFAULT_EMBEDDINGS_INITIALIZER = \"randomUniform\";\n    if (args.batchInputShape == null && args.inputShape == null) {\n      let batchSize = null;\n      if (args.batchSize != null) {\n        batchSize = args.batchSize;\n      }\n      if (args.inputLength == null) {\n        this.batchInputShape = [batchSize, null];\n      } else {\n        this.batchInputShape = [batchSize].concat(toList(args.inputLength));\n      }\n    }\n    this.inputDim = args.inputDim;\n    assertPositiveInteger(this.inputDim, \"inputDim\");\n    this.outputDim = args.outputDim;\n    assertPositiveInteger(this.outputDim, \"outputDim\");\n    this.embeddingsInitializer = getInitializer(args.embeddingsInitializer || this.DEFAULT_EMBEDDINGS_INITIALIZER);\n    this.embeddingsRegularizer = getRegularizer(args.embeddingsRegularizer);\n    this.activityRegularizer = getRegularizer(args.activityRegularizer);\n    this.embeddingsConstraint = getConstraint(args.embeddingsConstraint);\n    this.maskZero = args.maskZero;\n    this.supportsMasking = args.maskZero;\n    this.inputLength = args.inputLength;\n  }\n  build(inputShape) {\n    this.embeddings = this.addWeight(\"embeddings\", [this.inputDim, this.outputDim], this.dtype, this.embeddingsInitializer, this.embeddingsRegularizer, true, this.embeddingsConstraint);\n    this.built = true;\n  }\n  warnOnIncompatibleInputShape(inputShape) {\n  }\n  computeMask(inputs, mask) {\n    return tidy(() => {\n      if (!this.maskZero) {\n        return null;\n      } else {\n        inputs = getExactlyOneTensor(inputs);\n        return notEqual(inputs, zerosLike(inputs));\n      }\n    });\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    if (this.inputLength == null) {\n      return [...inputShape, this.outputDim];\n    }\n    const inLens = toList(this.inputLength);\n    if (inLens.length !== inputShape.length - 1) {\n      throw new ValueError(`\"inputLength\" is ${this.inputLength}, but received input shape has shape ${inputShape}`);\n    } else {\n      let i2 = 0;\n      for (let k = 0; k < inLens.length; ++k) {\n        const s1 = inLens[k];\n        const s2 = inputShape[k + 1];\n        if (s1 != null && s2 != null && s1 !== s2) {\n          throw new ValueError(`\"inputLength\" is ${this.inputLength}, but received input shape has shape ${inputShape}`);\n        } else if (s1 == null) {\n          inLens[i2] = s2;\n        }\n        i2++;\n      }\n    }\n    return [inputShape[0], ...inLens, this.outputDim];\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      let input2 = getExactlyOneTensor(inputs);\n      if (input2.dtype !== \"int32\") {\n        input2 = cast2(input2, \"int32\");\n      }\n      const output = gather2(this.embeddings.read(), reshape(input2, [input2.size]));\n      return reshape(output, getExactlyOneShape(this.computeOutputShape(input2.shape)));\n    });\n  }\n  getConfig() {\n    const config = {\n      inputDim: this.inputDim,\n      outputDim: this.outputDim,\n      embeddingsInitializer: serializeInitializer(this.embeddingsInitializer),\n      embeddingsRegularizer: serializeRegularizer(this.embeddingsRegularizer),\n      activityRegularizer: serializeRegularizer(this.activityRegularizer),\n      embeddingsConstraint: serializeConstraint(this.embeddingsConstraint),\n      maskZero: this.maskZero,\n      inputLength: this.inputLength\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nEmbedding.className = \"Embedding\";\nserialization_exports.registerClass(Embedding);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/merge.js\nvar Merge = class extends Layer {\n  constructor(args) {\n    super(args || {});\n    this.supportsMasking = true;\n  }\n  mergeFunction(inputs) {\n    throw new NotImplementedError();\n  }\n  computeElementwiseOpOutputShape(shape1, shape2) {\n    if (shape1 == null || shape2 == null) {\n      return null;\n    } else if (shape1.length < shape2.length) {\n      return this.computeElementwiseOpOutputShape(shape2, shape1);\n    } else if (shape2.length === 0) {\n      return shape1;\n    }\n    const outputShape = shape1.slice(0, shape1.length - shape2.length);\n    for (let k = 0; k < shape2.length; ++k) {\n      const i2 = shape1[shape1.length - shape2.length + k];\n      const j = shape2[k];\n      if (i2 == null || j == null || i2 < 0 || j < 0) {\n        outputShape.push(null);\n      } else if (i2 === 1) {\n        outputShape.push(j);\n      } else if (j === 1) {\n        outputShape.push(i2);\n      } else {\n        if (i2 !== j) {\n          throw new ValueError(\"Operands could not be broadcast together with shapes \" + JSON.stringify(shape1) + \" \" + JSON.stringify(shape2));\n        }\n        outputShape.push(i2);\n      }\n    }\n    return outputShape;\n  }\n  build(inputShape) {\n    if (Array.isArray(inputShape) && !Array.isArray(inputShape[0])) {\n      inputShape = [getExactlyOneShape(inputShape)];\n    }\n    inputShape = inputShape;\n    if (inputShape.length < 2) {\n      throw new ValueError(`A merge layer should be called on an Array of at least 2 inputs. Got ${inputShape.length} input(s).`);\n    }\n    let batchSizes = [];\n    for (const shape of inputShape) {\n      if (shape != null && shape[0] !== null) {\n        batchSizes.push(shape[0]);\n      }\n    }\n    batchSizes = unique2(batchSizes);\n    if (batchSizes.length > 1) {\n      throw new ValueError(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(inputShape)}.`);\n    }\n    let outputShape = inputShape[0] == null ? null : inputShape[0].slice(1);\n    for (let i2 = 1; i2 < inputShape.length; ++i2) {\n      const shape = inputShape[i2] == null ? null : inputShape[i2].slice(1);\n      outputShape = this.computeElementwiseOpOutputShape(outputShape, shape);\n    }\n    const allRanks = inputShape.map((shape) => shape.length);\n    if (inputShape.indexOf(null) === -1 && unique2(allRanks).length === 1) {\n      this.reshapeRequired = false;\n    } else {\n      this.reshapeRequired = true;\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = inputs;\n      if (this.reshapeRequired) {\n        const reshapedInputs = [];\n        const inputDims = inputs.map((input2) => input2.rank);\n        if (inputDims.indexOf(null) === -1) {\n          const maxNDim = max2(inputDims);\n          for (let x of inputs) {\n            const xNDim = x.rank;\n            for (let k = 0; k < maxNDim - xNDim; ++k) {\n              x = expandDims2(x, 1);\n            }\n            reshapedInputs.push(x);\n          }\n          return this.mergeFunction(reshapedInputs);\n        } else {\n          let transposed = false;\n          for (const x of inputs) {\n            const xNDim = x.rank;\n            if (xNDim == null) {\n              const xShape = x.shape;\n              const batchSize = xShape[0];\n              const newShape = xShape.slice(1).concat([batchSize]);\n              let xTransposed = reshape(x, [batchSize].concat(arrayProd(xShape.slice(1))));\n              xTransposed = transpose(xTransposed, [1, 0]);\n              xTransposed = reshape(xTransposed, newShape);\n              reshapedInputs.push(xTransposed);\n              transposed = true;\n            } else if (xNDim > 1) {\n              const dims = range2(1, xNDim).concat([0]);\n              reshapedInputs.push(transpose(x, dims));\n              transposed = true;\n            } else {\n              reshapedInputs.push(x);\n            }\n          }\n          let y = this.mergeFunction(reshapedInputs);\n          const yNDim = y.rank;\n          if (transposed) {\n            if (yNDim == null) {\n              const yShape = y.shape;\n              const yNDim2 = yShape.length;\n              const batchSize = yShape[yNDim2 - 1];\n              const newShape = [batchSize].concat(yShape.slice(0, yShape.length - 1));\n              y = reshape(transpose(reshape(y, [-1, batchSize]), [1, 0]), newShape);\n            } else if (yNDim > 1) {\n              const dims = [yNDim - 1].concat(range2(0, yNDim - 1));\n              y = transpose(y, dims);\n            }\n          }\n          return y;\n        }\n      } else {\n        return this.mergeFunction(inputs);\n      }\n    });\n  }\n  computeOutputShape(inputShape) {\n    inputShape = inputShape;\n    let outputShape;\n    if (inputShape[0] == null) {\n      outputShape = null;\n    } else {\n      outputShape = inputShape[0].slice(1);\n    }\n    for (let i2 = 1; i2 < inputShape.length; ++i2) {\n      const shape = inputShape[i2] == null ? null : inputShape[i2].slice(1);\n      outputShape = this.computeElementwiseOpOutputShape(outputShape, shape);\n    }\n    let batchSizes = [];\n    for (const shape of inputShape) {\n      if (shape != null && shape[0] !== null) {\n        batchSizes.push(shape[0]);\n      }\n    }\n    batchSizes = unique2(batchSizes);\n    if (batchSizes.length === 1) {\n      outputShape = batchSizes.concat(outputShape);\n    } else {\n      outputShape = [null].concat(outputShape);\n    }\n    return outputShape;\n  }\n  computeMask(inputs, mask) {\n    return tidy(() => {\n      if (mask == null) {\n        return null;\n      }\n      if (!Array.isArray(mask)) {\n        throw new ValueError(\"`mask` should be an Array\");\n      }\n      if (!Array.isArray(inputs)) {\n        throw new ValueError(\"`inputs` should be an Array\");\n      }\n      if (mask.length !== inputs.length) {\n        throw new ValueError(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${inputs.length} vs ${mask.length})`);\n      }\n      if (mask.every((m) => m == null)) {\n        return null;\n      }\n      mask = mask.map((m) => m == null ? m : expandDims(m, 0));\n      let output = mask[0];\n      for (let i2 = 1; i2 < mask.length - 1; ++i2) {\n        output = logicalAnd(output, mask[i2]);\n      }\n      return output;\n    });\n  }\n};\nvar Add2 = class extends Merge {\n  constructor(args) {\n    super(args);\n  }\n  mergeFunction(inputs) {\n    return tidy(() => {\n      let output = inputs[0].clone();\n      for (let i2 = 1; i2 < inputs.length; ++i2) {\n        output = add2(output, inputs[i2]);\n      }\n      return output;\n    });\n  }\n};\nAdd2.className = \"Add\";\nserialization_exports.registerClass(Add2);\nvar Multiply2 = class extends Merge {\n  constructor(args) {\n    super(args);\n  }\n  mergeFunction(inputs) {\n    return tidy(() => {\n      let output = inputs[0].clone();\n      for (let i2 = 1; i2 < inputs.length; ++i2) {\n        output = mul(output, inputs[i2]);\n      }\n      return output;\n    });\n  }\n};\nMultiply2.className = \"Multiply\";\nserialization_exports.registerClass(Multiply2);\nvar Average = class extends Merge {\n  constructor(args) {\n    super(args);\n  }\n  mergeFunction(inputs) {\n    return tidy(() => {\n      let output = inputs[0].clone();\n      for (let i2 = 1; i2 < inputs.length; ++i2) {\n        output = add2(output, inputs[i2]);\n      }\n      return mul(1 / inputs.length, output);\n    });\n  }\n};\nAverage.className = \"Average\";\nserialization_exports.registerClass(Average);\nvar Maximum2 = class extends Merge {\n  constructor(args) {\n    super(args);\n  }\n  mergeFunction(inputs) {\n    return tidy(() => {\n      let output = inputs[0];\n      for (let i2 = 1; i2 < inputs.length; ++i2) {\n        output = maximum(output, inputs[i2]);\n      }\n      return output;\n    });\n  }\n};\nMaximum2.className = \"Maximum\";\nserialization_exports.registerClass(Maximum2);\nvar Minimum2 = class extends Merge {\n  constructor(args) {\n    super(args);\n  }\n  mergeFunction(inputs) {\n    return tidy(() => {\n      let output = inputs[0];\n      for (let i2 = 1; i2 < inputs.length; ++i2) {\n        output = minimum(output, inputs[i2]);\n      }\n      return output;\n    });\n  }\n};\nMinimum2.className = \"Minimum\";\nserialization_exports.registerClass(Minimum2);\nvar Concatenate = class extends Merge {\n  constructor(args) {\n    super(args);\n    this.DEFAULT_AXIS = -1;\n    if (args == null) {\n      args = {};\n    }\n    this.axis = args.axis == null ? this.DEFAULT_AXIS : args.axis;\n    this.supportsMasking = true;\n    this.reshapeRequired = false;\n  }\n  build(inputShape) {\n    if (!(Array.isArray(inputShape) && Array.isArray(inputShape[0])) || inputShape.length === 1) {\n      throw new ValueError(\"A `Concatenate` layer should be called on a list of at least 2 inputs\");\n    }\n    inputShape = inputShape;\n    let allNoneShape = true;\n    for (const shape of inputShape) {\n      if (shape != null) {\n        allNoneShape = false;\n        break;\n      }\n    }\n    if (allNoneShape) {\n      return;\n    }\n    const shapeSet = [];\n    for (let i2 = 0; i2 < inputShape.length; ++i2) {\n      const shapeWithoutConcatAxis = inputShape[i2].slice();\n      shapeWithoutConcatAxis.splice(this.axis, 1);\n      let exists = false;\n      for (const shape of shapeSet) {\n        if (util_exports.arraysEqual(shape, shapeWithoutConcatAxis)) {\n          exists = true;\n          break;\n        }\n      }\n      if (!exists) {\n        shapeSet.push(shapeWithoutConcatAxis);\n      }\n    }\n    if (shapeSet.length > 1) {\n      throw new ValueError(\"A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: \" + JSON.stringify(inputShape));\n    }\n  }\n  mergeFunction(inputs) {\n    return tidy(() => {\n      return concatenate(inputs, this.axis);\n    });\n  }\n  computeOutputShape(inputShape) {\n    if (!(Array.isArray(inputShape) && Array.isArray(inputShape[0]))) {\n      throw new ValueError(\"A `Concatenate` layer should be called on a list of inputs.\");\n    }\n    const inputShapes = inputShape;\n    const outputShape = inputShapes[0].slice();\n    const axis = this.axis < 0 ? outputShape.length + this.axis : this.axis;\n    for (const shape of inputShapes.slice(1)) {\n      if (outputShape[axis] == null || shape[axis] == null) {\n        outputShape[axis] = null;\n        break;\n      }\n      outputShape[axis] += shape[axis];\n    }\n    return outputShape;\n  }\n  computeMask(inputs, mask) {\n    if (mask == null) {\n      return null;\n    }\n    if (!Array.isArray(mask)) {\n      throw new ValueError(\"`mask` should be an array for Concatenate\");\n    }\n    if (!Array.isArray(inputs)) {\n      throw new ValueError(\"`inputs` should be an array for Concatenate\");\n    }\n    if (mask.length !== inputs.length) {\n      throw new ValueError(`Mismatch in the length of mask (${mask.length}) and the legnth of inputs (${inputs.length})`);\n    }\n    return tidy(() => {\n      let allNullMasks = true;\n      mask.forEach((m) => {\n        if (m != null) {\n          allNullMasks = false;\n          return;\n        }\n      });\n      if (allNullMasks) {\n        return null;\n      }\n      const outputMasks = [];\n      for (let i2 = 0; i2 < inputs.length; ++i2) {\n        if (mask[i2] == null) {\n          outputMasks.push(cast(onesLike(inputs[i2]), \"bool\"));\n        } else if (mask[i2].rank < inputs[i2].rank) {\n          outputMasks.push(expandDims(mask[i2], -1));\n        } else {\n          outputMasks.push(mask[i2]);\n        }\n      }\n      const concatenatedMasks = concat(outputMasks, this.axis);\n      return all(concatenatedMasks, -1, false);\n    });\n  }\n  getConfig() {\n    const config = {\n      \"axis\": this.axis\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nConcatenate.className = \"Concatenate\";\nserialization_exports.registerClass(Concatenate);\nfunction interpretAxis(axis, dim) {\n  while (axis < 0) {\n    axis += dim;\n  }\n  return axis;\n}\nfunction batchDot(x, y, axes) {\n  if (x.shape.length > 3 || y.shape.length > 3) {\n    throw new NotImplementedError(\"batchDot is not implemented for tensors of 4D or higher rank yet\");\n  }\n  util_exports.assert(x.shape.length >= 2, () => `batchDot requires the rank of x to be >= 2, but got ${x.shape.length}`);\n  util_exports.assert(x.shape.length >= 2, () => `batchDot requires the rank of y to be >= 2, but got ${y.shape.length}`);\n  if (typeof axes === \"number\") {\n    axes = [axes, axes];\n  }\n  if (x.dtype === \"complex64\" || y.dtype === \"complex64\") {\n    throw new NotImplementedError(\"batchDot is not implemented for complex64-type Tensors yet.\");\n  }\n  const xNDim = x.shape.length;\n  const yNDim = y.shape.length;\n  if (axes == null) {\n    axes = [xNDim - 1, yNDim - 2];\n  }\n  const axesArray = axes;\n  return tidy(() => {\n    let diff;\n    if (xNDim > yNDim) {\n      diff = xNDim - yNDim;\n      const diffShape = [];\n      for (let i2 = 0; i2 < diff; ++i2) {\n        diffShape.push(1);\n      }\n      y = reshape(y, y.shape.concat(diffShape));\n    } else if (yNDim > xNDim) {\n      diff = yNDim - xNDim;\n      const diffShape = [];\n      for (let i2 = 0; i2 < diff; ++i2) {\n        diffShape.push(1);\n      }\n      x = reshape(x, x.shape.concat(diffShape));\n    } else {\n      diff = 0;\n    }\n    let out;\n    if (x.shape.length === 2 && y.shape.length === 2) {\n      if (axesArray[0] === axesArray[1]) {\n        out = sum2(mul(x, y), axesArray[0]);\n      } else {\n        out = sum2(mul(transpose(x, [1, 0]), y), axesArray[1]);\n      }\n    } else {\n      const adjX = axesArray[0] !== x.shape.length - 1;\n      const adjY = axesArray[1] === y.shape.length - 1;\n      out = matMul(x, y, adjX, adjY);\n    }\n    if (diff > 0) {\n      let idx;\n      if (xNDim > yNDim) {\n        idx = xNDim + yNDim - 3;\n      } else {\n        idx = xNDim - 1;\n      }\n      const squeezeAxes = [];\n      for (let i2 = idx; i2 < idx + diff; ++i2) {\n        squeezeAxes.push(i2);\n      }\n      out = squeeze(out, squeezeAxes);\n    }\n    if (out.shape.length === 1) {\n      out = expandDims(out, 1);\n    }\n    return out;\n  });\n}\nvar Dot = class extends Merge {\n  constructor(args) {\n    super(args);\n    this.axes = args.axes;\n    this.normalize = args.normalize == null ? false : args.normalize;\n    this.supportsMasking = true;\n    this.reshapeRequired = false;\n  }\n  build(inputShape) {\n    util_exports.assert(Array.isArray(inputShape) && inputShape.length === 2 && Array.isArray(inputShape[0]) && Array.isArray(inputShape[1]), () => \"A `Dot` layer should be called on a list of exactly 2 inputs.\");\n    const shape1 = inputShape[0];\n    const shape2 = inputShape[1];\n    if (shape1.length > 3 || shape2.length > 3) {\n      throw new NotImplementedError(\"Dot layer does not support tensors of 4D or higher rank yet.\");\n    }\n    const axes = this.interpretAxes(shape1, shape2);\n    if (shape1[axes[0]] !== shape2[axes[1]]) {\n      throw new ValueError(`Dimension incompatibility: ${shape1[axes[0]]} !== ${shape2[axes[1]]}`);\n    }\n  }\n  mergeFunction(inputs) {\n    if (inputs.length !== 2) {\n      throw new ValueError(`A \\`Dot\\` layer must be called on exactly 2 inputs, but received ${inputs.length} input(s).`);\n    }\n    let x1 = inputs[0];\n    let x2 = inputs[1];\n    let axes;\n    if (!Array.isArray(this.axes)) {\n      axes = [\n        interpretAxis(this.axes, x1.shape.length),\n        interpretAxis(this.axes, x2.shape.length)\n      ];\n    } else {\n      axes = this.axes.map((axis, i2) => interpretAxis(axis, inputs[i2].shape.length));\n    }\n    if (this.normalize) {\n      x1 = l2Normalize(x1, axes[0]);\n      x2 = l2Normalize(x2, axes[1]);\n    }\n    return batchDot(x1, x2, axes);\n  }\n  interpretAxes(shape1, shape2) {\n    let axes;\n    if (!Array.isArray(this.axes)) {\n      axes = [\n        interpretAxis(this.axes, shape1.length),\n        interpretAxis(this.axes, shape2.length)\n      ];\n    } else {\n      axes = this.axes;\n    }\n    return axes;\n  }\n  computeOutputShape(inputShape) {\n    util_exports.assert(Array.isArray(inputShape) && inputShape.length === 2 && Array.isArray(inputShape[0]) && Array.isArray(inputShape[1]), () => \"A `Dot` layer should be called on a list of exactly 2 inputs.\");\n    const shape1 = inputShape[0].slice();\n    const shape2 = inputShape[1].slice();\n    if (shape1.length > 3 || shape2.length > 3) {\n      throw new NotImplementedError(\"Dot layer does not support tensors of 4D or higher rank yet.\");\n    }\n    const axes = this.interpretAxes(shape1, shape2);\n    shape1.splice(axes[0], 1);\n    shape2.splice(axes[1], 1);\n    shape2.splice(0, 1);\n    const outputShape = shape1.concat(shape2);\n    if (outputShape.length === 1) {\n      outputShape.push(1);\n    }\n    return outputShape;\n  }\n  computeMask(inputs, mask) {\n    return null;\n  }\n  getConfig() {\n    const config = {\n      \"axes\": this.axes,\n      \"normalize\": this.normalize\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nDot.className = \"Dot\";\nserialization_exports.registerClass(Dot);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/noise.js\nvar GaussianNoise = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.supportsMasking = true;\n    this.stddev = args.stddev;\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = { stddev: this.stddev };\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      const input2 = getExactlyOneTensor(inputs);\n      const noised = () => add2(randomNormal2(input2.shape, 0, this.stddev), input2);\n      const output = inTrainPhase(noised, () => input2, kwargs[\"training\"] || false);\n      return output;\n    });\n  }\n};\nGaussianNoise.className = \"GaussianNoise\";\nserialization_exports.registerClass(GaussianNoise);\nvar GaussianDropout = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.supportsMasking = true;\n    this.rate = args.rate;\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = { rate: this.rate };\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      const input2 = getExactlyOneTensor(inputs);\n      if (this.rate > 0 && this.rate < 1) {\n        const noised = () => {\n          const stddev = Math.sqrt(this.rate / (1 - this.rate));\n          return mul(input2, randomNormal2(input2.shape, 1, stddev));\n        };\n        return inTrainPhase(noised, () => input2, kwargs[\"training\"] || false);\n      }\n      return input2;\n    });\n  }\n};\nGaussianDropout.className = \"GaussianDropout\";\nserialization_exports.registerClass(GaussianDropout);\nvar AlphaDropout = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.supportsMasking = true;\n    this.rate = args.rate;\n    this.noiseShape = args.noiseShape;\n  }\n  _getNoiseShape(inputs) {\n    return this.noiseShape || getExactlyOneTensor(inputs).shape;\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = { rate: this.rate };\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      if (this.rate < 1 && this.rate > 0) {\n        const noiseShape = this._getNoiseShape(inputs);\n        const droppedInputs = () => {\n          const input2 = getExactlyOneTensor(inputs);\n          const alpha = 1.6732632423543772;\n          const scale2 = 1.0507009873554805;\n          const alphaP = -alpha * scale2;\n          let keptIdx = greaterEqual(randomUniform(noiseShape), this.rate);\n          keptIdx = cast2(keptIdx, \"float32\");\n          const a = ((1 - this.rate) * (1 + this.rate * alphaP ** 2)) ** -0.5;\n          const b = -a * alphaP * this.rate;\n          const x = add2(mul(input2, keptIdx), mul(add2(keptIdx, -1), alphaP));\n          return add2(mul(x, a), b);\n        };\n        return inTrainPhase(droppedInputs, () => getExactlyOneTensor(inputs), kwargs[\"training\"] || false);\n      }\n      return inputs;\n    });\n  }\n};\nAlphaDropout.className = \"AlphaDropout\";\nserialization_exports.registerClass(AlphaDropout);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/normalization.js\nfunction batchNormalization(x, mean5, variance, beta, gamma, epsilon3 = 1e-3) {\n  let out;\n  if (x.rank === 2) {\n    out = batchNorm2d(x, mean5, variance, beta, gamma, epsilon3);\n  } else if (x.rank === 3) {\n    out = batchNorm3d(x, mean5, variance, beta, gamma, epsilon3);\n  } else if (x.rank === 4) {\n    out = batchNorm4d(x, mean5, variance, beta, gamma, epsilon3);\n  } else {\n    throw new NotImplementedError(`batchNormalization is not implemented for array of rank ${x.rank} yet`);\n  }\n  return out;\n}\nfunction regularNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon3 = 1e-3) {\n  return tidy(() => {\n    const meanAndVariance = moments(x, reductionAxes);\n    const mean5 = meanAndVariance.mean;\n    const variance = meanAndVariance.variance;\n    const normed = batchNormalization(x, mean5, variance, beta, gamma, epsilon3);\n    return [normed, mean5, variance];\n  });\n}\nfunction broadcastNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon3 = 1e-3) {\n  return tidy(() => {\n    const meanAndVariance = moments(x, reductionAxes);\n    const mean5 = meanAndVariance.mean;\n    const variance = meanAndVariance.variance;\n    const targetShape = [];\n    for (const axis of range2(0, x.rank)) {\n      if (reductionAxes.indexOf(axis) !== -1) {\n        targetShape.push(1);\n      } else {\n        targetShape.push(x.shape[axis]);\n      }\n    }\n    const broadcastMean = reshape(mean5, targetShape);\n    const broadcastVariance = reshape(variance, targetShape);\n    const broadcastGamma = gamma == null ? null : reshape(gamma, targetShape);\n    const broadcastBeta = beta == null ? null : reshape(beta, targetShape);\n    const normed = batchNormalization(x, broadcastMean, broadcastVariance, broadcastBeta, broadcastGamma, epsilon3);\n    return [normed, mean5, variance];\n  });\n}\nfunction normalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon3 = 1e-3) {\n  if (util_exports.arraysEqual(reductionAxes.slice().sort(), range2(0, x.rank - 1))) {\n    return regularNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon3);\n  } else {\n    return broadcastNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon3);\n  }\n}\nvar BatchNormalization = class extends Layer {\n  constructor(args) {\n    if (args == null) {\n      args = {};\n    }\n    super(args);\n    this.supportsMasking = true;\n    this.axis = args.axis == null ? -1 : args.axis;\n    this.momentum = args.momentum == null ? 0.99 : args.momentum;\n    this.epsilon = args.epsilon == null ? 1e-3 : args.epsilon;\n    this.center = args.center == null ? true : args.center;\n    this.scale = args.scale == null ? true : args.scale;\n    this.betaInitializer = getInitializer(args.betaInitializer || \"zeros\");\n    this.gammaInitializer = getInitializer(args.gammaInitializer || \"ones\");\n    this.movingMeanInitializer = getInitializer(args.movingMeanInitializer || \"zeros\");\n    this.movingVarianceInitializer = getInitializer(args.movingVarianceInitializer || \"ones\");\n    this.betaConstraint = getConstraint(args.betaConstraint);\n    this.gammaConstraint = getConstraint(args.gammaConstraint);\n    this.betaRegularizer = getRegularizer(args.betaRegularizer);\n    this.gammaRegularizer = getRegularizer(args.gammaRegularizer);\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const axis = this.axis >= 0 ? this.axis : this.axis + inputShape.length;\n    const dim = inputShape[axis];\n    if (dim == null) {\n      throw new ValueError(`Axis ${axis} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(inputShape)}.`);\n    }\n    this.inputSpec = [new InputSpec({ ndim: inputShape.length, axes: { [axis]: dim } })];\n    const shape = [dim];\n    if (this.scale) {\n      this.gamma = this.addWeight(\"gamma\", shape, null, this.gammaInitializer, this.gammaRegularizer, true, this.gammaConstraint);\n    }\n    if (this.center) {\n      this.beta = this.addWeight(\"beta\", shape, null, this.betaInitializer, this.betaRegularizer, true, this.betaConstraint);\n    }\n    this.movingMean = this.addWeight(\"moving_mean\", shape, null, this.movingMeanInitializer, null, false);\n    this.movingVariance = this.addWeight(\"moving_variance\", shape, null, this.movingVarianceInitializer, null, false);\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const training = kwargs[\"training\"] == null ? false : kwargs[\"training\"];\n      const input2 = getExactlyOneTensor(inputs);\n      const inputShape = input2.shape;\n      const ndim = inputShape.length;\n      const reductionAxes = range2(0, ndim);\n      const axis = this.axis >= 0 ? this.axis : this.axis + ndim;\n      reductionAxes.splice(axis, 1);\n      const broadcastShape = pyListRepeat(1, ndim);\n      broadcastShape[axis] = inputShape[axis];\n      const sortedReductionAxes = reductionAxes.slice();\n      sortedReductionAxes.sort();\n      const needsBroadcasting = !util_exports.arraysEqual(sortedReductionAxes, range2(0, ndim).slice(0, ndim - 1));\n      const normalizeInference = () => {\n        if (needsBroadcasting) {\n          const broadcastMovingMean = reshape(this.movingMean.read(), broadcastShape);\n          const broadcastMovingVariance = reshape(this.movingVariance.read(), broadcastShape);\n          const broadcastBeta = this.center ? reshape(this.beta.read(), broadcastShape) : null;\n          const broadcastGamma = this.scale ? reshape(this.gamma.read(), broadcastShape) : null;\n          return batchNormalization(input2, broadcastMovingMean, broadcastMovingVariance, broadcastBeta, broadcastGamma, this.epsilon);\n        } else {\n          return batchNormalization(input2, this.movingMean.read(), this.movingVariance.read(), this.beta == null ? null : this.beta.read(), this.gamma == null ? null : this.gamma.read(), this.epsilon);\n        }\n      };\n      if (!training) {\n        return normalizeInference();\n      }\n      const [normedTraining, mean5, variance] = normalizeBatchInTraining(input2, this.gamma.read(), this.beta.read(), reductionAxes, this.epsilon);\n      const doMovingAverage = (variable2, value, momentum) => {\n        tidy(() => {\n          const decay = 1 - momentum;\n          const origValue = variable2.read();\n          const updateDelta = mul(sub(origValue, value), decay);\n          variable2.write(sub(origValue, updateDelta));\n        });\n      };\n      const updateMovingMeanAndVariance = () => {\n        doMovingAverage(this.movingMean, mean5, this.momentum);\n        doMovingAverage(this.movingVariance, variance, this.momentum);\n      };\n      updateMovingMeanAndVariance();\n      return normedTraining;\n    });\n  }\n  getConfig() {\n    const config = {\n      axis: this.axis,\n      momentum: this.momentum,\n      epsilon: this.epsilon,\n      center: this.center,\n      scale: this.scale,\n      betaInitializer: serializeInitializer(this.betaInitializer),\n      gammaInitializer: serializeInitializer(this.gammaInitializer),\n      movingMeanInitializer: serializeInitializer(this.movingMeanInitializer),\n      movingVarianceInitializer: serializeInitializer(this.movingVarianceInitializer),\n      betaRegularizer: serializeRegularizer(this.betaRegularizer),\n      gammaRegularizer: serializeRegularizer(this.gammaRegularizer),\n      betaConstraint: serializeConstraint(this.betaConstraint),\n      gammaConstraint: serializeConstraint(this.gammaConstraint)\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nBatchNormalization.className = \"BatchNormalization\";\nserialization_exports.registerClass(BatchNormalization);\nvar LayerNormalization = class extends Layer {\n  constructor(args) {\n    if (args == null) {\n      args = {};\n    }\n    super(args);\n    this.axis = args.axis == null ? -1 : args.axis;\n    if (typeof this.axis === \"number\") {\n      if (!Number.isInteger(this.axis)) {\n        throw new Error(`Expected axis to be an integer, but received ${this.axis}`);\n      }\n    } else if (Array.isArray(this.axis)) {\n      for (const axis of this.axis) {\n        if (!Number.isInteger(axis)) {\n          throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`);\n        }\n      }\n    } else {\n      throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);\n    }\n    this.epsilon = args.epsilon == null ? 1e-3 : args.epsilon;\n    this.center = args.center == null ? true : args.center;\n    this.scale = args.scale == null ? true : args.scale;\n    this.betaInitializer = getInitializer(args.betaInitializer || \"zeros\");\n    this.gammaInitializer = getInitializer(args.gammaInitializer || \"ones\");\n    this.betaRegularizer = getRegularizer(args.betaRegularizer);\n    this.gammaRegularizer = getRegularizer(args.gammaRegularizer);\n    this.supportsMasking = true;\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const nDims = inputShape.length;\n    if (typeof this.axis === \"number\") {\n      this.axis = [this.axis];\n    }\n    for (let i2 = 0; i2 < this.axis.length; ++i2) {\n      if (this.axis[i2] < 0) {\n        this.axis[i2] += nDims;\n      }\n    }\n    for (const axis of this.axis) {\n      if (axis < 0 || axis >= nDims) {\n        throw new Error(`Invalid axis: ${axis}`);\n      }\n    }\n    if (this.axis.length !== unique2(this.axis).length) {\n      throw new Error(`Found duplicate axes in: ${this.axis}`);\n    }\n    const paramShape = this.axis.map((axis) => inputShape[axis]);\n    const trainable = true;\n    if (this.scale) {\n      this.gamma = this.addWeight(\"gamma\", paramShape, \"float32\", this.gammaInitializer, this.gammaRegularizer, trainable);\n    } else {\n      this.gamma = null;\n    }\n    if (this.center) {\n      this.beta = this.addWeight(\"beta\", paramShape, \"float32\", this.betaInitializer, this.betaRegularizer, trainable);\n    } else {\n      this.beta = null;\n    }\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    const input2 = getExactlyOneTensor(inputs);\n    const inputShape = input2.shape;\n    const nDims = inputShape.length;\n    return tidy(() => {\n      const keepDims = true;\n      let { mean: mean5, variance } = moments(input2, this.axis, keepDims);\n      const broadcastShape = pyListRepeat(1, nDims);\n      for (const dim of this.axis) {\n        broadcastShape[dim] = inputShape[dim];\n      }\n      const broadcast = (v) => {\n        if (v != null && v.shape.length !== nDims) {\n          return reshape(v, broadcastShape);\n        } else {\n          return v;\n        }\n      };\n      let scale2 = this.scale ? broadcast(this.gamma.read()) : null;\n      let offset = this.center ? broadcast(this.beta.read()) : null;\n      const momentsTiling = [];\n      const scaleOffsetTiling = [];\n      for (let i2 = 0; i2 < nDims; ++i2) {\n        if (this.axis.indexOf(i2) !== -1) {\n          momentsTiling.push(inputShape[i2]);\n          scaleOffsetTiling.push(1);\n        } else {\n          momentsTiling.push(1);\n          scaleOffsetTiling.push(inputShape[i2]);\n        }\n      }\n      mean5 = tile(mean5, momentsTiling);\n      variance = tile(variance, momentsTiling);\n      if (scale2 != null) {\n        scale2 = tile(scale2, scaleOffsetTiling);\n      }\n      if (offset != null) {\n        offset = tile(offset, scaleOffsetTiling);\n      }\n      return batchNormalization(input2, mean5, variance, offset, scale2, this.epsilon);\n    });\n  }\n  getConfig() {\n    const config = {\n      axis: this.axis,\n      epsilon: this.epsilon,\n      center: this.center,\n      scale: this.scale,\n      betaInitializer: serializeInitializer(this.betaInitializer),\n      gammaInitializer: serializeInitializer(this.gammaInitializer),\n      betaRegularizer: serializeRegularizer(this.betaRegularizer),\n      gammaRegularizer: serializeRegularizer(this.gammaRegularizer)\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nLayerNormalization.className = \"LayerNormalization\";\nserialization_exports.registerClass(LayerNormalization);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/padding.js\nfunction spatial2dPadding(x, padding, dataFormat) {\n  return tidy(() => {\n    if (x.rank !== 4) {\n      throw new ValueError(`temporalPadding expects input tensor to be 4-D, but received a ${x.rank}-D tensor.`);\n    }\n    if (padding == null) {\n      padding = [[1, 1], [1, 1]];\n    }\n    if (padding.length !== 2 || padding[0].length !== 2 || padding[1].length !== 2) {\n      throw new ValueError(\"spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.\");\n    }\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    if (dataFormat !== \"channelsLast\" && dataFormat !== \"channelsFirst\") {\n      throw new ValueError(`Unknown data format: ${dataFormat}. Supported data formats are 'channelsLast' and 'channelsFirst.`);\n    }\n    let pattern;\n    if (dataFormat === \"channelsFirst\") {\n      pattern = [[0, 0], [0, 0], padding[0], padding[1]];\n    } else {\n      pattern = [[0, 0], padding[0], padding[1], [0, 0]];\n    }\n    return pad(x, pattern);\n  });\n}\nvar ZeroPadding2D = class extends Layer {\n  constructor(args) {\n    if (args == null) {\n      args = {};\n    }\n    super(args);\n    this.dataFormat = args.dataFormat == null ? imageDataFormat() : args.dataFormat;\n    if (args.padding == null) {\n      this.padding = [[1, 1], [1, 1]];\n    } else if (typeof args.padding === \"number\") {\n      this.padding = [[args.padding, args.padding], [args.padding, args.padding]];\n    } else {\n      args.padding = args.padding;\n      if (args.padding.length !== 2) {\n        throw new ValueError(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${args.padding.length} array.`);\n      }\n      let heightPadding;\n      let widthPadding;\n      if (typeof args.padding[0] === \"number\") {\n        heightPadding = [args.padding[0], args.padding[0]];\n        widthPadding = [args.padding[1], args.padding[1]];\n      } else {\n        args.padding = args.padding;\n        if (args.padding[0].length !== 2) {\n          throw new ValueError(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${args.padding[0].length} array.`);\n        }\n        heightPadding = args.padding[0];\n        if (args.padding[1].length !== 2) {\n          throw new ValueError(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${args.padding[1].length} array.`);\n        }\n        widthPadding = args.padding[1];\n      }\n      this.padding = [heightPadding, widthPadding];\n    }\n    this.inputSpec = [new InputSpec({ ndim: 4 })];\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    let rows;\n    let cols;\n    if (this.dataFormat === \"channelsFirst\") {\n      if (inputShape[2] != null && inputShape[2] >= 0) {\n        rows = inputShape[2] + this.padding[0][0] + this.padding[0][1];\n      } else {\n        rows = null;\n      }\n      if (inputShape[3] != null && inputShape[3] >= 0) {\n        cols = inputShape[3] + this.padding[1][0] + this.padding[1][1];\n      } else {\n        cols = null;\n      }\n      return [inputShape[0], inputShape[1], rows, cols];\n    } else {\n      if (inputShape[1] != null && inputShape[1] >= 0) {\n        rows = inputShape[1] + this.padding[0][0] + this.padding[0][1];\n      } else {\n        rows = null;\n      }\n      if (inputShape[2] != null && inputShape[2] >= 0) {\n        cols = inputShape[2] + this.padding[1][0] + this.padding[1][1];\n      } else {\n        cols = null;\n      }\n      return [inputShape[0], rows, cols, inputShape[3]];\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => spatial2dPadding(getExactlyOneTensor(inputs), this.padding, this.dataFormat));\n  }\n  getConfig() {\n    const config = {\n      padding: this.padding,\n      dataFormat: this.dataFormat\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nZeroPadding2D.className = \"ZeroPadding2D\";\nserialization_exports.registerClass(ZeroPadding2D);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/pooling.js\nfunction pool2d(x, poolSize, strides, padding, dataFormat, poolMode) {\n  return tidy(() => {\n    checkDataFormat(dataFormat);\n    checkPoolMode(poolMode);\n    checkPaddingMode(padding);\n    if (strides == null) {\n      strides = [1, 1];\n    }\n    if (padding == null) {\n      padding = \"valid\";\n    }\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    if (poolMode == null) {\n      poolMode = \"max\";\n    }\n    x = preprocessConv2DInput(x, dataFormat);\n    let y;\n    const paddingString = padding === \"same\" ? \"same\" : \"valid\";\n    if (poolMode === \"max\") {\n      y = maxPool(x, poolSize, strides, paddingString);\n    } else {\n      y = avgPool(\n        x,\n        poolSize,\n        strides,\n        paddingString\n      );\n    }\n    if (dataFormat === \"channelsFirst\") {\n      y = transpose(y, [0, 3, 1, 2]);\n    }\n    return y;\n  });\n}\nfunction pool3d(x, poolSize, strides, padding, dataFormat, poolMode) {\n  return tidy(() => {\n    checkDataFormat(dataFormat);\n    checkPoolMode(poolMode);\n    checkPaddingMode(padding);\n    if (strides == null) {\n      strides = [1, 1, 1];\n    }\n    if (padding == null) {\n      padding = \"valid\";\n    }\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    if (poolMode == null) {\n      poolMode = \"max\";\n    }\n    x = preprocessConv3DInput(x, dataFormat);\n    let y;\n    const paddingString = padding === \"same\" ? \"same\" : \"valid\";\n    if (poolMode === \"max\") {\n      y = maxPool3d(x, poolSize, strides, paddingString);\n    } else {\n      y = avgPool3d(x, poolSize, strides, paddingString);\n    }\n    if (dataFormat === \"channelsFirst\") {\n      y = transpose(y, [0, 4, 1, 2, 3]);\n    }\n    return y;\n  });\n}\nvar Pooling1D = class extends Layer {\n  constructor(args) {\n    if (args.poolSize == null) {\n      args.poolSize = 2;\n    }\n    super(args);\n    if (typeof args.poolSize === \"number\") {\n      this.poolSize = [args.poolSize];\n    } else if (Array.isArray(args.poolSize) && args.poolSize.length === 1 && typeof args.poolSize[0] === \"number\") {\n      this.poolSize = args.poolSize;\n    } else {\n      throw new ValueError(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(args.poolSize)}`);\n    }\n    assertPositiveInteger(this.poolSize, \"poolSize\");\n    if (args.strides == null) {\n      this.strides = this.poolSize;\n    } else {\n      if (typeof args.strides === \"number\") {\n        this.strides = [args.strides];\n      } else if (Array.isArray(args.strides) && args.strides.length === 1 && typeof args.strides[0] === \"number\") {\n        this.strides = args.strides;\n      } else {\n        throw new ValueError(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(args.strides)}`);\n      }\n    }\n    assertPositiveInteger(this.strides, \"strides\");\n    this.padding = args.padding == null ? \"valid\" : args.padding;\n    checkPaddingMode(this.padding);\n    this.inputSpec = [new InputSpec({ ndim: 3 })];\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const length = convOutputLength(inputShape[1], this.poolSize[0], this.padding, this.strides[0]);\n    return [inputShape[0], length, inputShape[2]];\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      inputs = expandDims2(getExactlyOneTensor(inputs), 2);\n      const output = this.poolingFunction(getExactlyOneTensor(inputs), [this.poolSize[0], 1], [this.strides[0], 1], this.padding, \"channelsLast\");\n      return squeeze(output, [2]);\n    });\n  }\n  getConfig() {\n    const config = {\n      poolSize: this.poolSize,\n      padding: this.padding,\n      strides: this.strides\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nvar MaxPooling1D = class extends Pooling1D {\n  constructor(args) {\n    super(args);\n  }\n  poolingFunction(inputs, poolSize, strides, padding, dataFormat) {\n    checkDataFormat(dataFormat);\n    checkPaddingMode(padding);\n    return pool2d(inputs, poolSize, strides, padding, dataFormat, \"max\");\n  }\n};\nMaxPooling1D.className = \"MaxPooling1D\";\nserialization_exports.registerClass(MaxPooling1D);\nvar AveragePooling1D = class extends Pooling1D {\n  constructor(args) {\n    super(args);\n  }\n  poolingFunction(inputs, poolSize, strides, padding, dataFormat) {\n    checkDataFormat(dataFormat);\n    checkPaddingMode(padding);\n    return pool2d(inputs, poolSize, strides, padding, dataFormat, \"avg\");\n  }\n};\nAveragePooling1D.className = \"AveragePooling1D\";\nserialization_exports.registerClass(AveragePooling1D);\nvar Pooling2D = class extends Layer {\n  constructor(args) {\n    if (args.poolSize == null) {\n      args.poolSize = [2, 2];\n    }\n    super(args);\n    this.poolSize = Array.isArray(args.poolSize) ? args.poolSize : [args.poolSize, args.poolSize];\n    if (args.strides == null) {\n      this.strides = this.poolSize;\n    } else if (Array.isArray(args.strides)) {\n      if (args.strides.length !== 2) {\n        throw new ValueError(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${args.strides.length}.`);\n      }\n      this.strides = args.strides;\n    } else {\n      this.strides = [args.strides, args.strides];\n    }\n    assertPositiveInteger(this.poolSize, \"poolSize\");\n    assertPositiveInteger(this.strides, \"strides\");\n    this.padding = args.padding == null ? \"valid\" : args.padding;\n    this.dataFormat = args.dataFormat == null ? \"channelsLast\" : args.dataFormat;\n    checkDataFormat(this.dataFormat);\n    checkPaddingMode(this.padding);\n    this.inputSpec = [new InputSpec({ ndim: 4 })];\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    let rows = this.dataFormat === \"channelsFirst\" ? inputShape[2] : inputShape[1];\n    let cols = this.dataFormat === \"channelsFirst\" ? inputShape[3] : inputShape[2];\n    rows = convOutputLength(rows, this.poolSize[0], this.padding, this.strides[0]);\n    cols = convOutputLength(cols, this.poolSize[1], this.padding, this.strides[1]);\n    if (this.dataFormat === \"channelsFirst\") {\n      return [inputShape[0], inputShape[1], rows, cols];\n    } else {\n      return [inputShape[0], rows, cols, inputShape[3]];\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      return this.poolingFunction(getExactlyOneTensor(inputs), this.poolSize, this.strides, this.padding, this.dataFormat);\n    });\n  }\n  getConfig() {\n    const config = {\n      poolSize: this.poolSize,\n      padding: this.padding,\n      strides: this.strides,\n      dataFormat: this.dataFormat\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nvar MaxPooling2D = class extends Pooling2D {\n  constructor(args) {\n    super(args);\n  }\n  poolingFunction(inputs, poolSize, strides, padding, dataFormat) {\n    checkDataFormat(dataFormat);\n    checkPaddingMode(padding);\n    return pool2d(inputs, poolSize, strides, padding, dataFormat, \"max\");\n  }\n};\nMaxPooling2D.className = \"MaxPooling2D\";\nserialization_exports.registerClass(MaxPooling2D);\nvar AveragePooling2D = class extends Pooling2D {\n  constructor(args) {\n    super(args);\n  }\n  poolingFunction(inputs, poolSize, strides, padding, dataFormat) {\n    checkDataFormat(dataFormat);\n    checkPaddingMode(padding);\n    return pool2d(inputs, poolSize, strides, padding, dataFormat, \"avg\");\n  }\n};\nAveragePooling2D.className = \"AveragePooling2D\";\nserialization_exports.registerClass(AveragePooling2D);\nvar Pooling3D = class extends Layer {\n  constructor(args) {\n    if (args.poolSize == null) {\n      args.poolSize = [2, 2, 2];\n    }\n    super(args);\n    this.poolSize = Array.isArray(args.poolSize) ? args.poolSize : [args.poolSize, args.poolSize, args.poolSize];\n    if (args.strides == null) {\n      this.strides = this.poolSize;\n    } else if (Array.isArray(args.strides)) {\n      if (args.strides.length !== 3) {\n        throw new ValueError(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${args.strides.length}.`);\n      }\n      this.strides = args.strides;\n    } else {\n      this.strides = [args.strides, args.strides, args.strides];\n    }\n    assertPositiveInteger(this.poolSize, \"poolSize\");\n    assertPositiveInteger(this.strides, \"strides\");\n    this.padding = args.padding == null ? \"valid\" : args.padding;\n    this.dataFormat = args.dataFormat == null ? \"channelsLast\" : args.dataFormat;\n    checkDataFormat(this.dataFormat);\n    checkPaddingMode(this.padding);\n    this.inputSpec = [new InputSpec({ ndim: 5 })];\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    let depths = this.dataFormat === \"channelsFirst\" ? inputShape[2] : inputShape[1];\n    let rows = this.dataFormat === \"channelsFirst\" ? inputShape[3] : inputShape[2];\n    let cols = this.dataFormat === \"channelsFirst\" ? inputShape[4] : inputShape[3];\n    depths = convOutputLength(depths, this.poolSize[0], this.padding, this.strides[0]);\n    rows = convOutputLength(rows, this.poolSize[1], this.padding, this.strides[1]);\n    cols = convOutputLength(cols, this.poolSize[2], this.padding, this.strides[2]);\n    if (this.dataFormat === \"channelsFirst\") {\n      return [inputShape[0], inputShape[1], depths, rows, cols];\n    } else {\n      return [inputShape[0], depths, rows, cols, inputShape[4]];\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      return this.poolingFunction(getExactlyOneTensor(inputs), this.poolSize, this.strides, this.padding, this.dataFormat);\n    });\n  }\n  getConfig() {\n    const config = {\n      poolSize: this.poolSize,\n      padding: this.padding,\n      strides: this.strides,\n      dataFormat: this.dataFormat\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nvar MaxPooling3D = class extends Pooling3D {\n  constructor(args) {\n    super(args);\n  }\n  poolingFunction(inputs, poolSize, strides, padding, dataFormat) {\n    checkDataFormat(dataFormat);\n    checkPaddingMode(padding);\n    return pool3d(inputs, poolSize, strides, padding, dataFormat, \"max\");\n  }\n};\nMaxPooling3D.className = \"MaxPooling3D\";\nserialization_exports.registerClass(MaxPooling3D);\nvar AveragePooling3D = class extends Pooling3D {\n  constructor(args) {\n    super(args);\n  }\n  poolingFunction(inputs, poolSize, strides, padding, dataFormat) {\n    checkDataFormat(dataFormat);\n    checkPaddingMode(padding);\n    return pool3d(inputs, poolSize, strides, padding, dataFormat, \"avg\");\n  }\n};\nAveragePooling3D.className = \"AveragePooling3D\";\nserialization_exports.registerClass(AveragePooling3D);\nvar GlobalPooling1D = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.inputSpec = [new InputSpec({ ndim: 3 })];\n  }\n  computeOutputShape(inputShape) {\n    return [inputShape[0], inputShape[2]];\n  }\n  call(inputs, kwargs) {\n    throw new NotImplementedError();\n  }\n};\nvar GlobalAveragePooling1D = class extends GlobalPooling1D {\n  constructor(args) {\n    super(args || {});\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const input2 = getExactlyOneTensor(inputs);\n      return mean(input2, 1);\n    });\n  }\n};\nGlobalAveragePooling1D.className = \"GlobalAveragePooling1D\";\nserialization_exports.registerClass(GlobalAveragePooling1D);\nvar GlobalMaxPooling1D = class extends GlobalPooling1D {\n  constructor(args) {\n    super(args || {});\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const input2 = getExactlyOneTensor(inputs);\n      return max(input2, 1);\n    });\n  }\n};\nGlobalMaxPooling1D.className = \"GlobalMaxPooling1D\";\nserialization_exports.registerClass(GlobalMaxPooling1D);\nvar GlobalPooling2D = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.dataFormat = args.dataFormat == null ? \"channelsLast\" : args.dataFormat;\n    checkDataFormat(this.dataFormat);\n    this.inputSpec = [new InputSpec({ ndim: 4 })];\n  }\n  computeOutputShape(inputShape) {\n    inputShape = inputShape;\n    if (this.dataFormat === \"channelsLast\") {\n      return [inputShape[0], inputShape[3]];\n    } else {\n      return [inputShape[0], inputShape[1]];\n    }\n  }\n  call(inputs, kwargs) {\n    throw new NotImplementedError();\n  }\n  getConfig() {\n    const config = { dataFormat: this.dataFormat };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nvar GlobalAveragePooling2D = class extends GlobalPooling2D {\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const input2 = getExactlyOneTensor(inputs);\n      if (this.dataFormat === \"channelsLast\") {\n        return mean(input2, [1, 2]);\n      } else {\n        return mean(input2, [2, 3]);\n      }\n    });\n  }\n};\nGlobalAveragePooling2D.className = \"GlobalAveragePooling2D\";\nserialization_exports.registerClass(GlobalAveragePooling2D);\nvar GlobalMaxPooling2D = class extends GlobalPooling2D {\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const input2 = getExactlyOneTensor(inputs);\n      if (this.dataFormat === \"channelsLast\") {\n        return max(input2, [1, 2]);\n      } else {\n        return max(input2, [2, 3]);\n      }\n    });\n  }\n};\nGlobalMaxPooling2D.className = \"GlobalMaxPooling2D\";\nserialization_exports.registerClass(GlobalMaxPooling2D);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/wrappers.js\nvar Wrapper = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.layer = args.layer;\n  }\n  build(inputShape) {\n    this.built = true;\n  }\n  get trainable() {\n    if (this.layer != null) {\n      return this.layer.trainable;\n    } else {\n      return false;\n    }\n  }\n  set trainable(value) {\n    if (this.layer != null) {\n      this.layer.trainable = value;\n    }\n  }\n  get trainableWeights() {\n    return this.layer.trainableWeights;\n  }\n  get nonTrainableWeights() {\n    return this.layer.nonTrainableWeights;\n  }\n  get updates() {\n    return this.layer._updates;\n  }\n  get losses() {\n    return this.layer.losses;\n  }\n  getWeights() {\n    return this.layer.getWeights();\n  }\n  setWeights(weights) {\n    this.layer.setWeights(weights);\n  }\n  getConfig() {\n    const config = {\n      \"layer\": {\n        \"className\": this.layer.getClassName(),\n        \"config\": this.layer.getConfig()\n      }\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  setFastWeightInitDuringBuild(value) {\n    super.setFastWeightInitDuringBuild(value);\n    if (this.layer != null) {\n      this.layer.setFastWeightInitDuringBuild(value);\n    }\n  }\n  static fromConfig(cls, config, customObjects = {}) {\n    const layerConfig = config[\"layer\"];\n    const layer = deserialize(layerConfig, customObjects);\n    delete config[\"layer\"];\n    const newConfig = { layer };\n    Object.assign(newConfig, config);\n    return new cls(newConfig);\n  }\n};\nvar TimeDistributed = class extends Wrapper {\n  constructor(args) {\n    super(args);\n    this.supportsMasking = true;\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    if (inputShape.length < 3) {\n      throw new ValueError(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(inputShape)}`);\n    }\n    this.inputSpec = [{ shape: inputShape }];\n    const childInputShape = [inputShape[0]].concat(inputShape.slice(2));\n    if (!this.layer.built) {\n      this.layer.build(childInputShape);\n      this.layer.built = true;\n    }\n    super.build(inputShape);\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const childInputShape = [inputShape[0]].concat(inputShape.slice(2));\n    const childOutputShape = this.layer.computeOutputShape(childInputShape);\n    const timesteps = inputShape[1];\n    return [childOutputShape[0], timesteps].concat(childOutputShape.slice(1));\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = getExactlyOneTensor(inputs);\n      const step5 = (inputs2, states) => {\n        const output = getExactlyOneTensor(this.layer.call(inputs2, kwargs));\n        return [output, []];\n      };\n      const rnnOutputs = rnn(step5, inputs, [], false, null, null, false, true);\n      const y = rnnOutputs[1];\n      return y;\n    });\n  }\n};\nTimeDistributed.className = \"TimeDistributed\";\nserialization_exports.registerClass(TimeDistributed);\nfunction checkBidirectionalMergeMode(value) {\n  checkStringTypeUnionValue(VALID_BIDIRECTIONAL_MERGE_MODES, \"BidirectionalMergeMode\", value);\n}\nvar DEFAULT_BIDIRECTIONAL_MERGE_MODE = \"concat\";\nvar Bidirectional = class extends Wrapper {\n  constructor(args) {\n    super(args);\n    const layerConfig = args.layer.getConfig();\n    const forwDict = {};\n    forwDict[\"className\"] = args.layer.getClassName();\n    forwDict[\"config\"] = layerConfig;\n    this.forwardLayer = deserialize(forwDict);\n    layerConfig[\"goBackwards\"] = layerConfig[\"goBackwards\"] === true ? false : true;\n    const backDict = {};\n    backDict[\"className\"] = args.layer.getClassName();\n    backDict[\"config\"] = layerConfig;\n    this.backwardLayer = deserialize(backDict);\n    this.forwardLayer.name = \"forward_\" + this.forwardLayer.name;\n    this.backwardLayer.name = \"backward_\" + this.backwardLayer.name;\n    this.mergeMode = args.mergeMode === void 0 ? DEFAULT_BIDIRECTIONAL_MERGE_MODE : args.mergeMode;\n    checkBidirectionalMergeMode(this.mergeMode);\n    if (args.weights) {\n      throw new NotImplementedError(\"weights support is not implemented for Bidirectional layer yet.\");\n    }\n    this._stateful = args.layer.stateful;\n    this.returnSequences = args.layer.returnSequences;\n    this.returnState = args.layer.returnState;\n    this.supportsMasking = true;\n    this._trainable = true;\n    this.inputSpec = args.layer.inputSpec;\n    this.numConstants = null;\n  }\n  get trainable() {\n    return this._trainable;\n  }\n  set trainable(value) {\n    this._trainable = value;\n    if (this.forwardLayer != null) {\n      this.forwardLayer.trainable = value;\n    }\n    if (this.backwardLayer != null) {\n      this.backwardLayer.trainable = value;\n    }\n  }\n  getWeights() {\n    return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights());\n  }\n  setWeights(weights) {\n    const numWeights = weights.length;\n    const numeightsOver2 = Math.floor(numWeights / 2);\n    this.forwardLayer.setWeights(weights.slice(0, numeightsOver2));\n    this.backwardLayer.setWeights(weights.slice(numeightsOver2));\n  }\n  computeOutputShape(inputShape) {\n    let layerShapes = this.forwardLayer.computeOutputShape(inputShape);\n    if (!(Array.isArray(layerShapes) && Array.isArray(layerShapes[0]))) {\n      layerShapes = [layerShapes];\n    }\n    layerShapes = layerShapes;\n    let outputShape;\n    let outputShapes;\n    let stateShape;\n    if (this.returnState) {\n      stateShape = layerShapes.slice(1);\n      outputShape = layerShapes[0];\n    } else {\n      outputShape = layerShapes[0];\n    }\n    outputShape = outputShape;\n    if (this.mergeMode === \"concat\") {\n      outputShape[outputShape.length - 1] *= 2;\n      outputShapes = [outputShape];\n    } else if (this.mergeMode == null) {\n      outputShapes = [outputShape, outputShape.slice()];\n    } else {\n      outputShapes = [outputShape];\n    }\n    if (this.returnState) {\n      if (this.mergeMode == null) {\n        return outputShapes.concat(stateShape).concat(stateShape.slice());\n      }\n      return [outputShape].concat(stateShape).concat(stateShape.slice());\n    }\n    return singletonOrArray(outputShapes);\n  }\n  apply(inputs, kwargs) {\n    let initialState = kwargs == null ? null : kwargs[\"initialState\"];\n    let constants = kwargs == null ? null : kwargs[\"constants\"];\n    if (kwargs == null) {\n      kwargs = {};\n    }\n    const standardized = standardizeArgs(inputs, initialState, constants, this.numConstants);\n    inputs = standardized.inputs;\n    initialState = standardized.initialState;\n    constants = standardized.constants;\n    if (Array.isArray(inputs)) {\n      initialState = inputs.slice(1);\n      inputs = inputs[0];\n    }\n    if ((initialState == null || initialState.length === 0) && constants == null) {\n      return super.apply(inputs, kwargs);\n    }\n    const additionalInputs = [];\n    const additionalSpecs = [];\n    if (initialState != null) {\n      const numStates = initialState.length;\n      if (numStates % 2 > 0) {\n        throw new ValueError(\"When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.\");\n      }\n      kwargs[\"initialState\"] = initialState;\n      additionalInputs.push(...initialState);\n      const stateSpecs = initialState.map((state) => new InputSpec({ shape: state.shape }));\n      this.forwardLayer.stateSpec = stateSpecs.slice(0, numStates / 2);\n      this.backwardLayer.stateSpec = stateSpecs.slice(numStates / 2);\n      additionalSpecs.push(...stateSpecs);\n    }\n    if (constants != null) {\n      throw new NotImplementedError(\"Support for constants in Bidirectional layers is not implemented yet.\");\n    }\n    const isSymbolicTensor = additionalInputs[0] instanceof SymbolicTensor;\n    for (const tensor2 of additionalInputs) {\n      if (tensor2 instanceof SymbolicTensor !== isSymbolicTensor) {\n        throw new ValueError(\"The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors\");\n      }\n    }\n    if (isSymbolicTensor) {\n      const fullInput = [inputs].concat(additionalInputs);\n      const fullInputSpec = this.inputSpec.concat(additionalSpecs);\n      const originalInputSpec = this.inputSpec;\n      this.inputSpec = fullInputSpec;\n      const output = super.apply(fullInput, kwargs);\n      this.inputSpec = originalInputSpec;\n      return output;\n    } else {\n      return super.apply(inputs, kwargs);\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const initialState = kwargs[\"initialState\"];\n      let y;\n      let yRev;\n      if (initialState == null) {\n        y = this.forwardLayer.call(inputs, kwargs);\n        yRev = this.backwardLayer.call(inputs, kwargs);\n      } else {\n        const forwardState = initialState.slice(0, initialState.length / 2);\n        const backwardState = initialState.slice(initialState.length / 2);\n        y = this.forwardLayer.call(inputs, Object.assign(kwargs, { initialState: forwardState }));\n        yRev = this.backwardLayer.call(inputs, Object.assign(kwargs, { initialState: backwardState }));\n      }\n      let states;\n      if (this.returnState) {\n        if (Array.isArray(y)) {\n          states = y.slice(1).concat(yRev.slice(1));\n        } else {\n        }\n        y = y[0];\n        yRev = yRev[0];\n      }\n      if (this.returnSequences) {\n        yRev = reverse(yRev, 1);\n      }\n      let output;\n      if (this.mergeMode === \"concat\") {\n        output = concatenate([y, yRev]);\n      } else if (this.mergeMode === \"sum\") {\n        output = add2(y, yRev);\n      } else if (this.mergeMode === \"ave\") {\n        output = mul(0.5, add2(y, yRev));\n      } else if (this.mergeMode === \"mul\") {\n        output = mul(y, yRev);\n      } else if (this.mergeMode == null) {\n        output = [y, yRev];\n      }\n      if (this.returnState) {\n        if (this.mergeMode == null) {\n          return output.concat(states);\n        }\n        return [output].concat(states);\n      }\n      return output;\n    });\n  }\n  resetStates(states) {\n    this.forwardLayer.resetStates();\n    this.backwardLayer.resetStates();\n  }\n  build(inputShape) {\n    nameScope(this.forwardLayer.name, () => {\n      this.forwardLayer.build(inputShape);\n    });\n    nameScope(this.backwardLayer.name, () => {\n      this.backwardLayer.build(inputShape);\n    });\n    this.built = true;\n  }\n  computeMask(inputs, mask) {\n    if (Array.isArray(mask)) {\n      mask = mask[0];\n    }\n    let outputMask;\n    if (this.returnSequences) {\n      if (this.mergeMode == null) {\n        outputMask = [mask, mask];\n      } else {\n        outputMask = mask;\n      }\n    } else {\n      if (this.mergeMode == null) {\n        outputMask = [null, null];\n      } else {\n        outputMask = null;\n      }\n    }\n    if (this.returnState) {\n      const states = this.forwardLayer.states;\n      const stateMask = states.map((state) => null);\n      if (Array.isArray(outputMask)) {\n        return outputMask.concat(stateMask).concat(stateMask);\n      } else {\n        return [outputMask].concat(stateMask).concat(stateMask);\n      }\n    } else {\n      return outputMask;\n    }\n  }\n  get trainableWeights() {\n    return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights);\n  }\n  get nonTrainableWeights() {\n    return this.forwardLayer.nonTrainableWeights.concat(this.backwardLayer.nonTrainableWeights);\n  }\n  setFastWeightInitDuringBuild(value) {\n    super.setFastWeightInitDuringBuild(value);\n    if (this.forwardLayer != null) {\n      this.forwardLayer.setFastWeightInitDuringBuild(value);\n    }\n    if (this.backwardLayer != null) {\n      this.backwardLayer.setFastWeightInitDuringBuild(value);\n    }\n  }\n  getConfig() {\n    const config = {\n      \"mergeMode\": this.mergeMode\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  static fromConfig(cls, config) {\n    const rnnLayer = deserialize(config[\"layer\"]);\n    delete config[\"layer\"];\n    if (config[\"numConstants\"] != null) {\n      throw new NotImplementedError(`Deserialization of a Bidirectional layer with numConstants present is not supported yet.`);\n    }\n    const newConfig = config;\n    newConfig[\"layer\"] = rnnLayer;\n    return new cls(newConfig);\n  }\n};\nBidirectional.className = \"Bidirectional\";\nserialization_exports.registerClass(Bidirectional);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_layers.js\nfunction inputLayer(args) {\n  return new InputLayer(args);\n}\nfunction elu3(args) {\n  return new ELU(args);\n}\nfunction reLU(args) {\n  return new ReLU(args);\n}\nfunction leakyReLU(args) {\n  return new LeakyReLU(args);\n}\nfunction prelu2(args) {\n  return new PReLU(args);\n}\nfunction softmax2(args) {\n  return new Softmax3(args);\n}\nfunction thresholdedReLU(args) {\n  return new ThresholdedReLU(args);\n}\nfunction conv1d2(args) {\n  return new Conv1D(args);\n}\nfunction conv2d3(args) {\n  return new Conv2D2(args);\n}\nfunction conv2dTranspose2(args) {\n  return new Conv2DTranspose(args);\n}\nfunction conv3d2(args) {\n  return new Conv3D2(args);\n}\nfunction conv3dTranspose2(args) {\n  return new Conv3DTranspose(args);\n}\nfunction separableConv2d2(args) {\n  return new SeparableConv2D(args);\n}\nfunction cropping2D(args) {\n  return new Cropping2D(args);\n}\nfunction upSampling2d(args) {\n  return new UpSampling2D(args);\n}\nfunction depthwiseConv2d4(args) {\n  return new DepthwiseConv2D(args);\n}\nfunction activation(args) {\n  return new Activation2(args);\n}\nfunction dense(args) {\n  return new Dense(args);\n}\nfunction dropout3(args) {\n  return new Dropout(args);\n}\nfunction spatialDropout1d(args) {\n  return new SpatialDropout1D(args);\n}\nfunction flatten3(args) {\n  return new Flatten(args);\n}\nfunction repeatVector(args) {\n  return new RepeatVector(args);\n}\nfunction reshape2(args) {\n  return new Reshape2(args);\n}\nfunction permute(args) {\n  return new Permute(args);\n}\nfunction embedding(args) {\n  return new Embedding(args);\n}\nfunction add3(args) {\n  return new Add2(args);\n}\nfunction average(args) {\n  return new Average(args);\n}\nfunction concatenate2(args) {\n  return new Concatenate(args);\n}\nfunction maximum2(args) {\n  return new Maximum2(args);\n}\nfunction minimum2(args) {\n  return new Minimum2(args);\n}\nfunction multiply(args) {\n  return new Multiply2(args);\n}\nfunction dot3(args) {\n  return new Dot(args);\n}\nfunction batchNormalization2(args) {\n  return new BatchNormalization(args);\n}\nfunction layerNormalization(args) {\n  return new LayerNormalization(args);\n}\nfunction zeroPadding2d(args) {\n  return new ZeroPadding2D(args);\n}\nfunction averagePooling1d(args) {\n  return new AveragePooling1D(args);\n}\nfunction avgPool1d(args) {\n  return averagePooling1d(args);\n}\nfunction avgPooling1d(args) {\n  return averagePooling1d(args);\n}\nfunction averagePooling2d(args) {\n  return new AveragePooling2D(args);\n}\nfunction avgPool2d(args) {\n  return averagePooling2d(args);\n}\nfunction avgPooling2d(args) {\n  return averagePooling2d(args);\n}\nfunction averagePooling3d(args) {\n  return new AveragePooling3D(args);\n}\nfunction avgPool3d2(args) {\n  return averagePooling3d(args);\n}\nfunction avgPooling3d(args) {\n  return averagePooling3d(args);\n}\nfunction globalAveragePooling1d(args) {\n  return new GlobalAveragePooling1D(args);\n}\nfunction globalAveragePooling2d(args) {\n  return new GlobalAveragePooling2D(args);\n}\nfunction globalMaxPooling1d(args) {\n  return new GlobalMaxPooling1D(args);\n}\nfunction globalMaxPooling2d(args) {\n  return new GlobalMaxPooling2D(args);\n}\nfunction maxPooling1d(args) {\n  return new MaxPooling1D(args);\n}\nfunction maxPooling2d(args) {\n  return new MaxPooling2D(args);\n}\nfunction maxPooling3d(args) {\n  return new MaxPooling3D(args);\n}\nfunction gru(args) {\n  return new GRU(args);\n}\nfunction gruCell(args) {\n  return new GRUCell(args);\n}\nfunction lstm(args) {\n  return new LSTM(args);\n}\nfunction lstmCell(args) {\n  return new LSTMCell(args);\n}\nfunction simpleRNN(args) {\n  return new SimpleRNN(args);\n}\nfunction simpleRNNCell(args) {\n  return new SimpleRNNCell(args);\n}\nfunction convLstm2d(args) {\n  return new ConvLSTM2D(args);\n}\nfunction convLstm2dCell(args) {\n  return new ConvLSTM2DCell(args);\n}\nfunction rnn2(args) {\n  return new RNN(args);\n}\nfunction stackedRNNCells(args) {\n  return new StackedRNNCells(args);\n}\nfunction bidirectional(args) {\n  return new Bidirectional(args);\n}\nfunction timeDistributed(args) {\n  return new TimeDistributed(args);\n}\nvar globalMaxPool1d = globalMaxPooling1d;\nvar globalMaxPool2d = globalMaxPooling2d;\nvar maxPool1d = maxPooling1d;\nvar maxPool2d = maxPooling2d;\nfunction gaussianNoise(args) {\n  return new GaussianNoise(args);\n}\nfunction gaussianDropout(args) {\n  return new GaussianDropout(args);\n}\nfunction alphaDropout(args) {\n  return new AlphaDropout(args);\n}\nfunction masking(args) {\n  return new Masking(args);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_metrics.js\nvar exports_metrics_exports = {};\n__export(exports_metrics_exports, {\n  MAPE: () => MAPE2,\n  MSE: () => MSE2,\n  binaryAccuracy: () => binaryAccuracy2,\n  binaryCrossentropy: () => binaryCrossentropy3,\n  categoricalAccuracy: () => categoricalAccuracy2,\n  categoricalCrossentropy: () => categoricalCrossentropy3,\n  cosineProximity: () => cosineProximity2,\n  mape: () => mape2,\n  meanAbsoluteError: () => meanAbsoluteError2,\n  meanAbsolutePercentageError: () => meanAbsolutePercentageError2,\n  meanSquaredError: () => meanSquaredError3,\n  mse: () => mse2,\n  precision: () => precision2,\n  recall: () => recall2,\n  sparseCategoricalAccuracy: () => sparseCategoricalAccuracy2\n});\nfunction binaryAccuracy2(yTrue, yPred) {\n  return binaryAccuracy(yTrue, yPred);\n}\nfunction binaryCrossentropy3(yTrue, yPred) {\n  return binaryCrossentropy2(yTrue, yPred);\n}\nfunction sparseCategoricalAccuracy2(yTrue, yPred) {\n  return sparseCategoricalAccuracy(yTrue, yPred);\n}\nfunction categoricalAccuracy2(yTrue, yPred) {\n  return categoricalAccuracy(yTrue, yPred);\n}\nfunction categoricalCrossentropy3(yTrue, yPred) {\n  return categoricalCrossentropy2(yTrue, yPred);\n}\nfunction precision2(yTrue, yPred) {\n  return precision(yTrue, yPred);\n}\nfunction recall2(yTrue, yPred) {\n  return recall(yTrue, yPred);\n}\nfunction cosineProximity2(yTrue, yPred) {\n  return cosineProximity(yTrue, yPred);\n}\nfunction meanAbsoluteError2(yTrue, yPred) {\n  return meanAbsoluteError(yTrue, yPred);\n}\nfunction meanAbsolutePercentageError2(yTrue, yPred) {\n  return meanAbsolutePercentageError(yTrue, yPred);\n}\nfunction MAPE2(yTrue, yPred) {\n  return meanAbsolutePercentageError(yTrue, yPred);\n}\nfunction mape2(yTrue, yPred) {\n  return meanAbsolutePercentageError(yTrue, yPred);\n}\nfunction meanSquaredError3(yTrue, yPred) {\n  return meanSquaredError2(yTrue, yPred);\n}\nfunction MSE2(yTrue, yPred) {\n  return meanSquaredError2(yTrue, yPred);\n}\nfunction mse2(yTrue, yPred) {\n  return meanSquaredError2(yTrue, yPred);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_models.js\nvar exports_models_exports = {};\n__export(exports_models_exports, {\n  modelFromJSON: () => modelFromJSON\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_regularizers.js\nvar exports_regularizers_exports = {};\n__export(exports_regularizers_exports, {\n  l1: () => l12,\n  l1l2: () => l1l2,\n  l2: () => l22\n});\nfunction l1l2(config) {\n  return new L1L2(config);\n}\nfunction l12(config) {\n  return l1(config);\n}\nfunction l22(config) {\n  return l2(config);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/callbacks.js\nvar Callback = class extends BaseCallback {\n  constructor() {\n    super(...arguments);\n    this.model = null;\n  }\n  setModel(model2) {\n    if (!(model2 instanceof LayersModel)) {\n      throw new Error(\"model must be a LayersModel, not some other Container\");\n    }\n    this.model = model2;\n  }\n};\nfunction less2(currVal, prevVal) {\n  return currVal < prevVal;\n}\nfunction greater2(currVal, prevVal) {\n  return currVal > prevVal;\n}\nvar EarlyStopping = class extends Callback {\n  constructor(args) {\n    super();\n    if (args == null) {\n      args = {};\n    }\n    if (args.restoreBestWeights) {\n      throw new NotImplementedError(\"restoreBestWeights = True is not implemented in EarlyStopping yet.\");\n    }\n    this.monitor = args.monitor || \"val_loss\";\n    this.minDelta = Math.abs(args.minDelta || 0);\n    this.patience = args.patience || 0;\n    this.verbose = args.verbose || 0;\n    this.mode = args.mode || \"auto\";\n    this.baseline = args.baseline;\n    if ([\"auto\", \"min\", \"max\"].indexOf(this.mode) === -1) {\n      console.warn(`EarlyStopping mode '${this.mode}' is invalid. Falling back to mode 'auto'.`);\n      this.mode = \"auto\";\n    }\n    if (this.mode === \"min\") {\n      this.monitorFunc = less2;\n    } else if (this.mode === \"max\") {\n      this.monitorFunc = greater2;\n    } else {\n      if (this.monitor.indexOf(\"acc\") !== -1) {\n        this.monitorFunc = greater2;\n      } else {\n        this.monitorFunc = less2;\n      }\n    }\n    if (this.monitorFunc === less2) {\n      this.minDelta *= -1;\n    }\n  }\n  async onTrainBegin(logs) {\n    this.wait = 0;\n    this.stoppedEpoch = 0;\n    if (this.baseline != null) {\n      this.best = this.baseline;\n    } else {\n      this.best = this.monitorFunc === less2 ? Infinity : -Infinity;\n    }\n  }\n  async onEpochEnd(epoch, logs) {\n    await resolveScalarsInLogs(logs);\n    const current = this.getMonitorValue(logs);\n    if (current == null) {\n      return;\n    }\n    if (this.monitorFunc(current - this.minDelta, this.best)) {\n      this.best = current;\n      this.wait = 0;\n    } else {\n      this.wait++;\n      if (this.wait >= this.patience) {\n        this.stoppedEpoch = epoch;\n        this.model.stopTraining = true;\n      }\n    }\n  }\n  async onTrainEnd(logs) {\n    if (this.stoppedEpoch > 0 && this.verbose) {\n      console.log(`Epoch ${this.stoppedEpoch}: early stopping.`);\n    }\n  }\n  getMonitorValue(logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    const monitorValue = logs[this.monitor];\n    if (monitorValue == null) {\n      console.warn(`Metric for EarlyStopping ${this.monitor} is not available. Available metrics are: ${Object.keys(logs)}`);\n    }\n    return monitorValue;\n  }\n};\nfunction earlyStopping(args) {\n  return new EarlyStopping(args);\n}\nvar callbacks = { earlyStopping };\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/flags.js\nvar ENV4 = env();\nENV4.registerFlag(\"KEEP_INTERMEDIATE_TENSORS\", () => false, (debugValue) => {\n  if (debugValue) {\n    console.warn(\"Keep intermediate tensors is ON. This will print the values of all intermediate tensors during model inference. Not all models support this mode. For details, check e2e/benchmarks/ model_config.js. This significantly impacts performance.\");\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/data/compiled_api.js\nvar DataType;\n(function(DataType2) {\n  DataType2[DataType2[\"DT_INVALID\"] = 0] = \"DT_INVALID\";\n  DataType2[DataType2[\"DT_FLOAT\"] = 1] = \"DT_FLOAT\";\n  DataType2[DataType2[\"DT_DOUBLE\"] = 2] = \"DT_DOUBLE\";\n  DataType2[DataType2[\"DT_INT32\"] = 3] = \"DT_INT32\";\n  DataType2[DataType2[\"DT_UINT8\"] = 4] = \"DT_UINT8\";\n  DataType2[DataType2[\"DT_INT16\"] = 5] = \"DT_INT16\";\n  DataType2[DataType2[\"DT_INT8\"] = 6] = \"DT_INT8\";\n  DataType2[DataType2[\"DT_STRING\"] = 7] = \"DT_STRING\";\n  DataType2[DataType2[\"DT_COMPLEX64\"] = 8] = \"DT_COMPLEX64\";\n  DataType2[DataType2[\"DT_INT64\"] = 9] = \"DT_INT64\";\n  DataType2[DataType2[\"DT_BOOL\"] = 10] = \"DT_BOOL\";\n  DataType2[DataType2[\"DT_QINT8\"] = 11] = \"DT_QINT8\";\n  DataType2[DataType2[\"DT_QUINT8\"] = 12] = \"DT_QUINT8\";\n  DataType2[DataType2[\"DT_QINT32\"] = 13] = \"DT_QINT32\";\n  DataType2[DataType2[\"DT_BFLOAT16\"] = 14] = \"DT_BFLOAT16\";\n  DataType2[DataType2[\"DT_QINT16\"] = 15] = \"DT_QINT16\";\n  DataType2[DataType2[\"DT_QUINT16\"] = 16] = \"DT_QUINT16\";\n  DataType2[DataType2[\"DT_UINT16\"] = 17] = \"DT_UINT16\";\n  DataType2[DataType2[\"DT_COMPLEX128\"] = 18] = \"DT_COMPLEX128\";\n  DataType2[DataType2[\"DT_HALF\"] = 19] = \"DT_HALF\";\n  DataType2[DataType2[\"DT_RESOURCE\"] = 20] = \"DT_RESOURCE\";\n  DataType2[DataType2[\"DT_VARIANT\"] = 21] = \"DT_VARIANT\";\n  DataType2[DataType2[\"DT_UINT32\"] = 22] = \"DT_UINT32\";\n  DataType2[DataType2[\"DT_UINT64\"] = 23] = \"DT_UINT64\";\n  DataType2[DataType2[\"DT_FLOAT_REF\"] = 101] = \"DT_FLOAT_REF\";\n  DataType2[DataType2[\"DT_DOUBLE_REF\"] = 102] = \"DT_DOUBLE_REF\";\n  DataType2[DataType2[\"DT_INT32_REF\"] = 103] = \"DT_INT32_REF\";\n  DataType2[DataType2[\"DT_UINT8_REF\"] = 104] = \"DT_UINT8_REF\";\n  DataType2[DataType2[\"DT_INT16_REF\"] = 105] = \"DT_INT16_REF\";\n  DataType2[DataType2[\"DT_INT8_REF\"] = 106] = \"DT_INT8_REF\";\n  DataType2[DataType2[\"DT_STRING_REF\"] = 107] = \"DT_STRING_REF\";\n  DataType2[DataType2[\"DT_COMPLEX64_REF\"] = 108] = \"DT_COMPLEX64_REF\";\n  DataType2[DataType2[\"DT_INT64_REF\"] = 109] = \"DT_INT64_REF\";\n  DataType2[DataType2[\"DT_BOOL_REF\"] = 110] = \"DT_BOOL_REF\";\n  DataType2[DataType2[\"DT_QINT8_REF\"] = 111] = \"DT_QINT8_REF\";\n  DataType2[DataType2[\"DT_QUINT8_REF\"] = 112] = \"DT_QUINT8_REF\";\n  DataType2[DataType2[\"DT_QINT32_REF\"] = 113] = \"DT_QINT32_REF\";\n  DataType2[DataType2[\"DT_BFLOAT16_REF\"] = 114] = \"DT_BFLOAT16_REF\";\n  DataType2[DataType2[\"DT_QINT16_REF\"] = 115] = \"DT_QINT16_REF\";\n  DataType2[DataType2[\"DT_QUINT16_REF\"] = 116] = \"DT_QUINT16_REF\";\n  DataType2[DataType2[\"DT_UINT16_REF\"] = 117] = \"DT_UINT16_REF\";\n  DataType2[DataType2[\"DT_COMPLEX128_REF\"] = 118] = \"DT_COMPLEX128_REF\";\n  DataType2[DataType2[\"DT_HALF_REF\"] = 119] = \"DT_HALF_REF\";\n  DataType2[DataType2[\"DT_RESOURCE_REF\"] = 120] = \"DT_RESOURCE_REF\";\n  DataType2[DataType2[\"DT_VARIANT_REF\"] = 121] = \"DT_VARIANT_REF\";\n  DataType2[DataType2[\"DT_UINT32_REF\"] = 122] = \"DT_UINT32_REF\";\n  DataType2[DataType2[\"DT_UINT64_REF\"] = 123] = \"DT_UINT64_REF\";\n})(DataType || (DataType = {}));\nvar SaverDef;\n(function(SaverDef2) {\n  let CheckpointFormatVersion;\n  (function(CheckpointFormatVersion2) {\n    CheckpointFormatVersion2[CheckpointFormatVersion2[\"LEGACY\"] = 0] = \"LEGACY\";\n    CheckpointFormatVersion2[CheckpointFormatVersion2[\"V1\"] = 1] = \"V1\";\n    CheckpointFormatVersion2[CheckpointFormatVersion2[\"V2\"] = 2] = \"V2\";\n  })(CheckpointFormatVersion = SaverDef2.CheckpointFormatVersion || (SaverDef2.CheckpointFormatVersion = {}));\n})(SaverDef || (SaverDef = {}));\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/custom_op/register.js\nvar CUSTOM_OPS = {};\nfunction registerOp(name, opFunc) {\n  const opMapper = {\n    tfOpName: name,\n    category: \"custom\",\n    inputs: [],\n    attrs: [],\n    customExecutor: opFunc\n  };\n  CUSTOM_OPS[name] = opMapper;\n}\nfunction getRegisteredOp(name) {\n  return CUSTOM_OPS[name];\n}\nfunction deregisterOp(name) {\n  delete CUSTOM_OPS[name];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/utils.js\nfunction getParamValue(paramName, node, tensorMap, context, resourceManager) {\n  const inputParam = node.inputParams[paramName];\n  if (inputParam && inputParam.inputIndexStart !== void 0) {\n    const start = inputParam.inputIndexStart;\n    const end = inputParam.inputIndexEnd === 0 ? void 0 : inputParam.inputIndexEnd === void 0 ? start + 1 : inputParam.inputIndexEnd;\n    if (inputParam.type === \"tensor\") {\n      return getTensor(node.inputNames[inputParam.inputIndexStart], tensorMap, context, resourceManager);\n    }\n    if (inputParam.type === \"tensors\") {\n      const inputs = node.inputNames.slice(start, end);\n      return inputs.map((name) => getTensor(name, tensorMap, context, resourceManager));\n    }\n    const tensor2 = getTensor(node.inputNames.slice(start)[0], tensorMap, context, resourceManager);\n    const data = tensor2.dataSync();\n    return inputParam.type === \"number\" ? data[0] : util_exports.toNestedArray(tensor2.shape, data);\n  }\n  const attrParam = node.attrParams[paramName];\n  return attrParam && attrParam.value;\n}\nfunction getTensor(name, tensorsMap, context, resourceManager) {\n  const [nodeName, index] = parseNodeName(name);\n  if (resourceManager != null) {\n    const tensor2 = resourceManager.getHashTableHandleByName(nodeName);\n    if (tensor2 != null) {\n      return tensor2;\n    }\n  }\n  const contextId = context.currentContextIds.find((contextId2) => {\n    return !!tensorsMap[getNodeNameWithContextId(nodeName, contextId2)];\n  });\n  return contextId !== void 0 ? tensorsMap[getNodeNameWithContextId(nodeName, contextId)][index] : void 0;\n}\nfunction getTensorsForCurrentContenxt(name, tensorsMap, context) {\n  return tensorsMap[getNodeNameWithContextId(name, context.currentContextId)];\n}\nfunction getNodeNameAndIndex(inputName, context) {\n  const [nodeName, index, outputName] = parseNodeName(inputName);\n  return [\n    getNodeNameWithContextId(nodeName, context && context.currentContextId),\n    index,\n    outputName\n  ];\n}\nfunction getNodeNameWithContextId(name, contextId) {\n  return !!contextId ? `${name}-${contextId}` : name;\n}\nfunction parseNodeName(name) {\n  const parts = name.split(\":\");\n  if (parts.length === 1) {\n    return [name, 0, void 0];\n  }\n  const nodeName = parts[0];\n  const outputName = parts.length === 3 ? parts[1] : void 0;\n  const index = Number(parts[parts.length - 1]);\n  return [nodeName, index, outputName];\n}\nfunction getPadding(node, tensorMap, context) {\n  let pad3 = getParamValue(\"pad\", node, tensorMap, context);\n  if (pad3 === \"explicit\") {\n    pad3 = getParamValue(\"explicitPaddings\", node, tensorMap, context);\n    const explicitPadding = [[0, 0], [0, 0], [0, 0], [0, 0]];\n    for (let i2 = 0; i2 < 4; i2++) {\n      explicitPadding[i2][0] = pad3[i2 * 2];\n      explicitPadding[i2][1] = pad3[i2 * 2 + 1];\n    }\n    return explicitPadding;\n  }\n  return pad3;\n}\nfunction cloneTensor(tensor2) {\n  return tensor2.kept ? tensor2 : clone(tensor2);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/arithmetic.js\nvar arithmetic_exports = {};\n__export(arithmetic_exports, {\n  json: () => json\n});\nvar json = [\n  {\n    \"tfOpName\": \"Add\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"AddV2\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"AddN\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"tensors\",\n        \"type\": \"tensors\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"BiasAdd\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Sub\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"RealDiv\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Div\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"DivNoNan\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"FloorDiv\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Mul\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Maximum\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Minimum\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Pow\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SquaredDifference\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Mod\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"FloorMod\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/basic_math.js\nvar basic_math_exports = {};\n__export(basic_math_exports, {\n  json: () => json2\n});\nvar json2 = [\n  {\n    \"tfOpName\": \"Abs\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Acos\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Asin\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Atan\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Atan2\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"y\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Ceil\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ClipByValue\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"clipValueMin\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"clipValueMax\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Complex\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"real\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"imag\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ComplexAbs\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Cos\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Cosh\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Elu\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Exp\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Floor\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Log\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Imag\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"Tout\",\n        \"name\": \"outputType\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Neg\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Real\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"Tout\",\n        \"name\": \"outputType\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Prelu\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"alpha\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Relu\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Relu6\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Selu\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Sigmoid\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Sin\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Sinh\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Sqrt\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Rsqrt\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Square\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Tan\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Tanh\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Sign\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Round\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Expm1\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Log1p\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Reciprocal\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Softplus\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Asinh\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Acosh\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Atanh\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Erf\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Prod\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axes\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LeakyRelu\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"alpha\",\n        \"name\": \"alpha\",\n        \"type\": \"number\",\n        \"defaultValue\": 0.2\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"IsNan\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/control.js\nvar control_exports = {};\n__export(control_exports, {\n  json: () => json3\n});\nvar json3 = [\n  {\n    \"tfOpName\": \"EmptyTensorList\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"maxNumElements\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LoopCond\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"pred\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Switch\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"data\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"pred\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Merge\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"tensors\",\n        \"type\": \"tensors\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Enter\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"frame_name\",\n        \"name\": \"frameName\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"is_constant\",\n        \"name\": \"isConstant\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Exit\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"NextIteration\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArrayV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"size\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"element_shape\",\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"tfName\": \"dynamic_size\",\n        \"name\": \"dynamicSize\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"clear_after_read\",\n        \"name\": \"clearAfterRead\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"identical_element_shapes\",\n        \"name\": \"identicalElementShapes\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"tensor_array_name\",\n        \"name\": \"name\",\n        \"type\": \"string\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArrayWriteV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"index\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"flowIn\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArrayReadV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"index\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"flowIn\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArrayGatherV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"flowIn\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"element_shape\",\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArrayScatterV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"flowIn\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArrayConcatV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"flowIn\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"element_shape_except0\",\n        \"name\": \"elementShapeExcept0\",\n        \"type\": \"shape\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArraySplitV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"lengths\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"flowIn\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArraySizeV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"flowIn\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArrayCloseV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"StatelessIf\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"cond\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"end\": 0,\n        \"name\": \"args\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"then_branch\",\n        \"name\": \"thenBranch\",\n        \"type\": \"func\"\n      },\n      {\n        \"tfName\": \"else_branch\",\n        \"name\": \"elseBranch\",\n        \"type\": \"func\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"If\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"cond\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"end\": 0,\n        \"name\": \"args\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"then_branch\",\n        \"name\": \"thenBranch\",\n        \"type\": \"func\"\n      },\n      {\n        \"tfName\": \"else_branch\",\n        \"name\": \"elseBranch\",\n        \"type\": \"func\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"StatelessWhile\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"args\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"cond\",\n        \"name\": \"cond\",\n        \"type\": \"func\"\n      },\n      {\n        \"tfName\": \"body\",\n        \"name\": \"body\",\n        \"type\": \"func\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"While\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"args\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"cond\",\n        \"name\": \"cond\",\n        \"type\": \"func\"\n      },\n      {\n        \"tfName\": \"body\",\n        \"name\": \"body\",\n        \"type\": \"func\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListScatter\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListScatterV2\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"numElements\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListGather\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListGetItem\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"index\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListSetItem\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"index\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListReserve\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"numElements\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListFromTensor\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListStack\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"num_elements\",\n        \"name\": \"numElements\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListSplit\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"lengths\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListConcat\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_shape\",\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListConcatV2\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_shape\",\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListPopBack\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListPushBack\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListLength\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListResize\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"size\",\n        \"type\": \"number\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/convolution.js\nvar convolution_exports = {};\n__export(convolution_exports, {\n  json: () => json4\n});\nvar json4 = [\n  {\n    \"tfOpName\": \"AvgPool\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"ksize\",\n        \"name\": \"kernelSize\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"MaxPool\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"ksize\",\n        \"name\": \"kernelSize\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"explicit_paddings\",\n        \"name\": \"explicitPaddings\",\n        \"type\": \"number[]\",\n        \"defaultValue\": [],\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"MaxPoolWithArgmax\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"ksize\",\n        \"name\": \"kernelSize\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"include_batch_in_index\",\n        \"name\": \"includeBatchInIndex\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"AvgPool3D\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"ksize\",\n        \"name\": \"kernelSize\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"MaxPool3D\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"ksize\",\n        \"name\": \"kernelSize\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Conv1D\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"stride\",\n        \"name\": \"stride\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"defaultValue\": \"NWC\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"dilation\",\n        \"name\": \"dilation\",\n        \"type\": \"number\",\n        \"defaultValue\": 1\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Conv2D\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"useCudnnOnGpu\",\n        \"name\": \"useCudnnOnGpu\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"defaultValue\": \"NHWC\"\n      },\n      {\n        \"tfName\": \"explicit_paddings\",\n        \"name\": \"explicitPaddings\",\n        \"type\": \"number[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"dilations\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"_FusedConv2D\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"end\": 0,\n        \"name\": \"args\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"num_args\",\n        \"name\": \"numArgs\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"explicit_paddings\",\n        \"name\": \"explicitPaddings\",\n        \"type\": \"number[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"use_cudnn_on_gpu\",\n        \"name\": \"useCudnnOnGpu\",\n        \"type\": \"bool\",\n        \"defaultValue\": true\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"defaultValue\": \"NHWC\"\n      },\n      {\n        \"tfName\": \"dilations\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\",\n        \"defaultValue\": [\n          1,\n          1,\n          1,\n          1\n        ]\n      },\n      {\n        \"tfName\": \"fused_ops\",\n        \"name\": \"fusedOps\",\n        \"type\": \"string[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"epsilon\",\n        \"name\": \"epsilon\",\n        \"type\": \"number\",\n        \"defaultValue\": 1e-4\n      },\n      {\n        \"tfName\": \"leakyrelu_alpha\",\n        \"name\": \"leakyreluAlpha\",\n        \"type\": \"number\",\n        \"defaultValue\": 0.2\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Conv2DBackpropInput\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 2,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 0,\n        \"name\": \"outputShape\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"explicit_paddings\",\n        \"name\": \"explicitPaddings\",\n        \"type\": \"number[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"dilations\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"DepthwiseConv2d\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"input\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"defaultValue\": \"NHWC\"\n      },\n      {\n        \"tfName\": \"explicit_paddings\",\n        \"name\": \"explicitPaddings\",\n        \"type\": \"number[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"dilations\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"DepthwiseConv2dNative\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"input\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"defaultValue\": \"NHWC\"\n      },\n      {\n        \"tfName\": \"explicit_paddings\",\n        \"name\": \"explicitPaddings\",\n        \"type\": \"number[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"dilations\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"FusedDepthwiseConv2dNative\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"end\": 0,\n        \"name\": \"args\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"num_args\",\n        \"name\": \"numArgs\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"defaultValue\": \"NHWC\"\n      },\n      {\n        \"tfName\": \"dilations\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\",\n        \"defaultValue\": [\n          1,\n          1,\n          1,\n          1\n        ]\n      },\n      {\n        \"tfName\": \"fused_ops\",\n        \"name\": \"fusedOps\",\n        \"type\": \"string[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"explicit_paddings\",\n        \"name\": \"explicitPaddings\",\n        \"type\": \"number[]\",\n        \"defaultValue\": []\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Conv3D\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"defaultValue\": \"NHWC\"\n      },\n      {\n        \"tfName\": \"dilations\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Dilation2D\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"rates\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/creation.js\nvar creation_exports = {};\n__export(creation_exports, {\n  json: () => json5\n});\nvar json5 = [\n  {\n    \"tfOpName\": \"Fill\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"value\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LinSpace\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"start\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"stop\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"num\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"OneHot\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"depth\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"onValue\",\n        \"type\": \"number\",\n        \"defaultValue\": 1\n      },\n      {\n        \"start\": 3,\n        \"name\": \"offValue\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"axis\",\n        \"name\": \"axis\",\n        \"type\": \"number\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Ones\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"OnesLike\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"RandomStandardNormal\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"seed\",\n        \"name\": \"seed\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"seed2\",\n        \"name\": \"seed2\",\n        \"type\": \"number\",\n        \"defaultValue\": 0,\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"T\",\n        \"type\": \"number\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"RandomUniform\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"minval\",\n        \"name\": \"minval\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"maxval\",\n        \"name\": \"maxval\",\n        \"type\": \"number\",\n        \"defaultValue\": 1\n      },\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"seed\",\n        \"name\": \"seed\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"seed2\",\n        \"name\": \"seed2\",\n        \"type\": \"number\",\n        \"defaultValue\": 0,\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"T\",\n        \"type\": \"number\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Range\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"start\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"stop\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"step\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"Tidx\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TruncatedNormal\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"means\",\n        \"name\": \"mean\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"stddev\",\n        \"name\": \"stdDev\",\n        \"type\": \"number\",\n        \"defaultValue\": 1\n      },\n      {\n        \"tfName\": \"seed\",\n        \"name\": \"seed\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"seed2\",\n        \"name\": \"seed2\",\n        \"type\": \"number\",\n        \"defaultValue\": 0,\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"T\",\n        \"type\": \"number\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Zeros\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ZerosLike\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Multinomial\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"logits\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"numSamples\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"seed\",\n        \"name\": \"seed\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"seed2\",\n        \"name\": \"seed2\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"output_dtype\",\n        \"name\": \"output_dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/dynamic.js\nvar dynamic_exports = {};\n__export(dynamic_exports, {\n  json: () => json6\n});\nvar json6 = [\n  {\n    \"tfOpName\": \"NonMaxSuppressionV2\",\n    \"category\": \"dynamic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"boxes\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"scores\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"maxOutputSize\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"iouThreshold\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"NonMaxSuppressionV3\",\n    \"category\": \"dynamic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"boxes\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"scores\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"maxOutputSize\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"iouThreshold\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 4,\n        \"name\": \"scoreThreshold\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"NonMaxSuppressionV4\",\n    \"category\": \"dynamic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"boxes\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"scores\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"maxOutputSize\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"iouThreshold\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 4,\n        \"name\": \"scoreThreshold\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"T_threshold\",\n        \"name\": \"threshold\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"pad_to_max_output_size\",\n        \"name\": \"padToMaxOutputSize\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"NonMaxSuppressionV5\",\n    \"category\": \"dynamic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"boxes\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"scores\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"maxOutputSize\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"iouThreshold\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 4,\n        \"name\": \"scoreThreshold\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 5,\n        \"name\": \"softNmsSigma\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Where\",\n    \"category\": \"dynamic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"condition\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ListDiff\",\n    \"category\": \"dynamic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"y\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/evaluation.js\nvar evaluation_exports = {};\n__export(evaluation_exports, {\n  json: () => json7\n});\nvar json7 = [\n  {\n    \"tfOpName\": \"LowerBound\",\n    \"category\": \"evaluation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"sortedSequence\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"values\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TopKV2\",\n    \"category\": \"evaluation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"k\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"sorted\",\n        \"name\": \"sorted\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"UpperBound\",\n    \"category\": \"evaluation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"sortedSequence\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"values\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Unique\",\n    \"category\": \"evaluation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"UniqueV2\",\n    \"category\": \"evaluation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/graph.js\nvar graph_exports = {};\n__export(graph_exports, {\n  json: () => json8\n});\nvar json8 = [\n  {\n    \"tfOpName\": \"PlaceholderWithDefault\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"default\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"shape\",\n        \"name\": \"shape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Placeholder\",\n    \"category\": \"graph\",\n    \"attrs\": [\n      {\n        \"tfName\": \"shape\",\n        \"name\": \"shape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Const\",\n    \"category\": \"graph\"\n  },\n  {\n    \"tfOpName\": \"Identity\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"IdentityN\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensors\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Snapshot\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Rank\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Size\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Shape\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ShapeN\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensors\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Print\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"data\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"message\",\n        \"name\": \"message\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"first_n\",\n        \"name\": \"firstN\",\n        \"type\": \"number\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"summarize\",\n        \"name\": \"summarize\",\n        \"type\": \"number\",\n        \"defaultValue\": 3\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"NoOp\",\n    \"category\": \"graph\",\n    \"inputs\": []\n  },\n  {\n    \"tfOpName\": \"StopGradient\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"FakeQuantWithMinMaxVars\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"min\",\n        \"name\": \"min\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"max\",\n        \"name\": \"max\",\n        \"type\": \"number\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/hash_table.js\nvar hash_table_exports = {};\n__export(hash_table_exports, {\n  json: () => json9\n});\nvar json9 = [\n  {\n    \"tfOpName\": \"HashTable\",\n    \"category\": \"hash_table\",\n    \"inputs\": [],\n    \"attrs\": [\n      {\n        \"tfName\": \"shared_name\",\n        \"name\": \"sharedName\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"use_node_name_sharing\",\n        \"name\": \"useNodeNameSharing\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"key_dtype\",\n        \"name\": \"keyDType\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"value_dtype\",\n        \"name\": \"valueDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"HashTableV2\",\n    \"category\": \"hash_table\",\n    \"inputs\": [],\n    \"attrs\": [\n      {\n        \"tfName\": \"shared_name\",\n        \"name\": \"sharedName\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"use_node_name_sharing\",\n        \"name\": \"useNodeNameSharing\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"key_dtype\",\n        \"name\": \"keyDType\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"value_dtype\",\n        \"name\": \"valueDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LookupTableImport\",\n    \"category\": \"hash_table\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tableHandle\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"keys\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"values\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"Tin\",\n        \"name\": \"tIn\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"Tout\",\n        \"name\": \"tOut\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LookupTableImportV2\",\n    \"category\": \"hash_table\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tableHandle\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"keys\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"values\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"Tin\",\n        \"name\": \"tIn\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"Tout\",\n        \"name\": \"tOut\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LookupTableFind\",\n    \"category\": \"hash_table\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tableHandle\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"keys\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"defaultValue\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"Tin\",\n        \"name\": \"tIn\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"Tout\",\n        \"name\": \"tOut\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LookupTableFindV2\",\n    \"category\": \"hash_table\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tableHandle\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"keys\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"defaultValue\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"Tin\",\n        \"name\": \"tIn\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"Tout\",\n        \"name\": \"tOut\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LookupTableSize\",\n    \"category\": \"hash_table\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tableHandle\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LookupTableSizeV2\",\n    \"category\": \"hash_table\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tableHandle\",\n        \"type\": \"tensor\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/image.js\nvar image_exports = {};\n__export(image_exports, {\n  json: () => json10\n});\nvar json10 = [\n  {\n    \"tfOpName\": \"ResizeBilinear\",\n    \"category\": \"image\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"images\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"size\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"align_corners\",\n        \"name\": \"alignCorners\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"half_pixel_centers\",\n        \"name\": \"halfPixelCenters\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ResizeNearestNeighbor\",\n    \"category\": \"image\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"images\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"size\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"align_corners\",\n        \"name\": \"alignCorners\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"half_pixel_centers\",\n        \"name\": \"halfPixelCenters\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"CropAndResize\",\n    \"category\": \"image\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"image\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"boxes\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"boxInd\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"cropSize\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"method\",\n        \"name\": \"method\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"extrapolation_value\",\n        \"name\": \"extrapolationValue\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ImageProjectiveTransformV3\",\n    \"category\": \"image\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"images\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"transforms\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"outputShape\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"fillValue\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"interpolation\",\n        \"name\": \"interpolation\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"fill_mode\",\n        \"name\": \"fillMode\",\n        \"type\": \"string\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/logical.js\nvar logical_exports = {};\n__export(logical_exports, {\n  json: () => json11\n});\nvar json11 = [\n  {\n    \"tfOpName\": \"Equal\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"NotEqual\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Greater\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"GreaterEqual\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Less\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LessEqual\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LogicalAnd\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LogicalNot\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LogicalOr\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Select\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"condition\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SelectV2\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"condition\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/matrices.js\nvar matrices_exports = {};\n__export(matrices_exports, {\n  json: () => json12\n});\nvar json12 = [\n  {\n    \"tfOpName\": \"_FusedMatMul\",\n    \"category\": \"matrices\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"end\": 0,\n        \"name\": \"args\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"num_args\",\n        \"name\": \"numArgs\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"fused_ops\",\n        \"name\": \"fusedOps\",\n        \"type\": \"string[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"epsilon\",\n        \"name\": \"epsilon\",\n        \"type\": \"number\",\n        \"defaultValue\": 1e-4\n      },\n      {\n        \"tfName\": \"transpose_a\",\n        \"name\": \"transposeA\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"transpose_b\",\n        \"name\": \"transposeB\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"leakyrelu_alpha\",\n        \"name\": \"leakyreluAlpha\",\n        \"type\": \"number\",\n        \"defaultValue\": 0.2\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"MatMul\",\n    \"category\": \"matrices\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"transpose_a\",\n        \"name\": \"transposeA\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"transpose_b\",\n        \"name\": \"transposeB\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"BatchMatMul\",\n    \"category\": \"matrices\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"adj_x\",\n        \"name\": \"transposeA\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"adj_y\",\n        \"name\": \"transposeB\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"BatchMatMulV2\",\n    \"category\": \"matrices\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"adj_x\",\n        \"name\": \"transposeA\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"adj_y\",\n        \"name\": \"transposeB\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Transpose\",\n    \"category\": \"matrices\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"perm\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Einsum\",\n    \"category\": \"matrices\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"tensors\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"equation\",\n        \"name\": \"equation\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"N\",\n        \"name\": \"n\",\n        \"type\": \"number\",\n        \"defaultValue\": 2\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/normalization.js\nvar normalization_exports = {};\n__export(normalization_exports, {\n  json: () => json13\n});\nvar json13 = [\n  {\n    \"tfOpName\": \"EuclideanNorm\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"FusedBatchNorm\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"scale\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"offset\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"mean\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 4,\n        \"name\": \"variance\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"epsilon\",\n        \"name\": \"epsilon\",\n        \"type\": \"number\",\n        \"defaultValue\": 1e-3\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"FusedBatchNormV2\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"scale\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"offset\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"mean\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 4,\n        \"name\": \"variance\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"epsilon\",\n        \"name\": \"epsilon\",\n        \"type\": \"number\",\n        \"defaultValue\": 1e-3\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"FusedBatchNormV3\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"scale\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"offset\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"mean\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 4,\n        \"name\": \"variance\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"epsilon\",\n        \"name\": \"epsilon\",\n        \"type\": \"number\",\n        \"defaultValue\": 1e-3\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LRN\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"depth_radius\",\n        \"name\": \"radius\",\n        \"type\": \"number\",\n        \"defaultValue\": 5\n      },\n      {\n        \"tfName\": \"bias\",\n        \"name\": \"bias\",\n        \"type\": \"number\",\n        \"defaultValue\": 1\n      },\n      {\n        \"tfName\": \"alpha\",\n        \"name\": \"alpha\",\n        \"type\": \"number\",\n        \"defaultValue\": 1\n      },\n      {\n        \"tfName\": \"beta\",\n        \"name\": \"beta\",\n        \"type\": \"number\",\n        \"defaultValue\": 0.5\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Softmax\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LogSoftmax\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SparseToDense\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"sparseIndices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"outputShape\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"sparseValues\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"defaultValue\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"validate_indices\",\n        \"name\": \"validateIndices\",\n        \"type\": \"bool\",\n        \"defaultValue\": true,\n        \"notSupported\": true\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/reduction.js\nvar reduction_exports = {};\n__export(reduction_exports, {\n  json: () => json14\n});\nvar json14 = [\n  {\n    \"tfOpName\": \"Bincount\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"size\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"weights\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"DenseBincount\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"size\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"weights\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"binary_output\",\n        \"name\": \"binaryOutput\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Max\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Mean\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Min\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Sum\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"All\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Any\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ArgMax\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ArgMin\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Prod\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Cumprod\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"exclusive\",\n        \"name\": \"exclusive\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"reverse\",\n        \"name\": \"reverse\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Cumsum\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"exclusive\",\n        \"name\": \"exclusive\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"reverse\",\n        \"name\": \"reverse\",\n        \"type\": \"bool\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/slice_join.js\nvar slice_join_exports = {};\n__export(slice_join_exports, {\n  json: () => json15\n});\nvar json15 = [\n  {\n    \"tfOpName\": \"ConcatV2\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": -1,\n        \"name\": \"tensors\",\n        \"type\": \"tensors\"\n      },\n      {\n        \"start\": -1,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"N\",\n        \"name\": \"n\",\n        \"type\": \"number\",\n        \"defaultValue\": 2\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Concat\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 1,\n        \"end\": 0,\n        \"name\": \"tensors\",\n        \"type\": \"tensors\"\n      },\n      {\n        \"start\": 0,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"N\",\n        \"name\": \"n\",\n        \"type\": \"number\",\n        \"defaultValue\": 2\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"GatherV2\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"axis\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"batch_dims\",\n        \"name\": \"batchDims\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Gather\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"validate_indices\",\n        \"name\": \"validateIndices\",\n        \"type\": \"bool\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Reverse\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"dims\",\n        \"type\": \"bool[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ReverseV2\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Slice\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"begin\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"size\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"StridedSlice\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"begin\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"end\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"begin_mask\",\n        \"name\": \"beginMask\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"end_mask\",\n        \"name\": \"endMask\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"new_axis_mask\",\n        \"name\": \"newAxisMask\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"ellipsis_mask\",\n        \"name\": \"ellipsisMask\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"shrink_axis_mask\",\n        \"name\": \"shrinkAxisMask\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Pack\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"tensors\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"axis\",\n        \"name\": \"axis\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Unpack\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"axis\",\n        \"name\": \"axis\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"num\",\n        \"name\": \"num\",\n        \"type\": \"number\",\n        \"defaultValue\": 0,\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Tile\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"reps\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Split\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"axis\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"start\": 1,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"num_split\",\n        \"name\": \"numOrSizeSplits\",\n        \"type\": \"number\",\n        \"defaultValue\": 1\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SplitV\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"numOrSizeSplits\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"axis\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ScatterNd\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"values\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"GatherNd\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SparseToDense\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"sparseIndices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"outputShape\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"sparseValues\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"defaultValue\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"validate_indices\",\n        \"name\": \"validateIndices\",\n        \"type\": \"bool\",\n        \"defaultValue\": false,\n        \"notSupported\": true\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/sparse.js\nvar sparse_exports = {};\n__export(sparse_exports, {\n  json: () => json16\n});\nvar json16 = [\n  {\n    \"tfOpName\": \"SparseFillEmptyRows\",\n    \"category\": \"sparse\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"values\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"denseShape\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"defaultValue\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SparseReshape\",\n    \"category\": \"sparse\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"inputIndices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"inputShape\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"newShape\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SparseSegmentMean\",\n    \"category\": \"sparse\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"data\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"segmentIds\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SparseSegmentSum\",\n    \"category\": \"sparse\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"data\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"segmentIds\",\n        \"type\": \"tensor\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/spectral.js\nvar spectral_exports = {};\n__export(spectral_exports, {\n  json: () => json17\n});\nvar json17 = [\n  {\n    \"tfOpName\": \"FFT\",\n    \"category\": \"spectral\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"IFFT\",\n    \"category\": \"spectral\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"RFFT\",\n    \"category\": \"spectral\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"fft_length\",\n        \"type\": \"number\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"IRFFT\",\n    \"category\": \"spectral\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"fft_length\",\n        \"type\": \"number\",\n        \"notSupported\": true\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/string.js\nvar string_exports = {};\n__export(string_exports, {\n  json: () => json18\n});\nvar json18 = [\n  {\n    \"tfOpName\": \"StringNGrams\",\n    \"category\": \"string\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"data\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"dataSplits\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"separator\",\n        \"name\": \"separator\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"ngram_widths\",\n        \"name\": \"nGramWidths\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"left_pad\",\n        \"name\": \"leftPad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"right_pad\",\n        \"name\": \"rightPad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"pad_width\",\n        \"name\": \"padWidth\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"preserve_short_sequences\",\n        \"name\": \"preserveShortSequences\",\n        \"type\": \"bool\"\n      }\n    ],\n    \"outputs\": [\n      \"ngrams\",\n      \"ngrams_splits\"\n    ]\n  },\n  {\n    \"tfOpName\": \"StringSplit\",\n    \"category\": \"string\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"input\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"delimiter\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"skip_empty\",\n        \"name\": \"skipEmpty\",\n        \"type\": \"bool\"\n      }\n    ],\n    \"outputs\": [\n      \"indices\",\n      \"values\",\n      \"shape\"\n    ]\n  },\n  {\n    \"tfOpName\": \"StringToHashBucketFast\",\n    \"category\": \"string\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"input\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"num_buckets\",\n        \"name\": \"numBuckets\",\n        \"type\": \"number\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/transformation.js\nvar transformation_exports = {};\n__export(transformation_exports, {\n  json: () => json19\n});\nvar json19 = [\n  {\n    \"tfOpName\": \"Cast\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"SrcT\",\n        \"name\": \"sdtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"DstT\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ExpandDims\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"MirrorPad\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"padding\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"mode\",\n        \"name\": \"mode\",\n        \"type\": \"string\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Pad\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"padding\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"constant_value\",\n        \"name\": \"constantValue\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"PadV2\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"padding\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"constantValue\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Reshape\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Squeeze\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"axis\",\n        \"tfDeprecatedName\": \"squeeze_dims\",\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SpaceToBatchND\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"blockShape\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"paddings\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"BatchToSpaceND\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"blockShape\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"crops\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"DepthToSpace\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"block_size\",\n        \"name\": \"blockSize\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"BroadcastTo\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": []\n  },\n  {\n    \"tfOpName\": \"BroadcastArgs\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"s0\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"s1\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": []\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/operation_mapper.js\nvar OperationMapper = class {\n  static get Instance() {\n    return this._instance || (this._instance = new this());\n  }\n  constructor() {\n    const ops = [\n      arithmetic_exports,\n      basic_math_exports,\n      control_exports,\n      convolution_exports,\n      creation_exports,\n      dynamic_exports,\n      evaluation_exports,\n      graph_exports,\n      hash_table_exports,\n      image_exports,\n      logical_exports,\n      matrices_exports,\n      normalization_exports,\n      reduction_exports,\n      slice_join_exports,\n      sparse_exports,\n      spectral_exports,\n      string_exports,\n      transformation_exports\n    ];\n    const mappersJson = [].concat(...ops.map((op2) => op2.json));\n    this.opMappers = mappersJson.reduce((map, mapper) => {\n      map[mapper.tfOpName] = mapper;\n      return map;\n    }, {});\n  }\n  transformGraph(graph, signature = {}) {\n    const tfNodes = graph.node;\n    const placeholders = [];\n    const weights = [];\n    const initNodes = [];\n    const nodes = tfNodes.reduce((map, node) => {\n      map[node.name] = this.mapNode(node);\n      if (node.op.startsWith(\"Placeholder\")) {\n        placeholders.push(map[node.name]);\n      } else if (node.op === \"Const\") {\n        weights.push(map[node.name]);\n      } else if (node.input == null || node.input.length === 0) {\n        initNodes.push(map[node.name]);\n      }\n      return map;\n    }, {});\n    let inputs = [];\n    const outputs = [];\n    let inputNodeNameToKey = {};\n    let outputNodeNameToKey = {};\n    if (signature != null) {\n      inputNodeNameToKey = this.mapSignatureEntries(signature.inputs);\n      outputNodeNameToKey = this.mapSignatureEntries(signature.outputs);\n    }\n    const allNodes = Object.keys(nodes);\n    allNodes.forEach((key) => {\n      const node = nodes[key];\n      node.inputNames.forEach((name, index) => {\n        const [nodeName, , outputName] = getNodeNameAndIndex(name);\n        const inputNode = nodes[nodeName];\n        if (inputNode.outputs != null) {\n          const outputIndex = inputNode.outputs.indexOf(outputName);\n          if (outputIndex !== -1) {\n            const inputName = `${nodeName}:${outputIndex}`;\n            node.inputNames[index] = inputName;\n          }\n        }\n        node.inputs.push(inputNode);\n        inputNode.children.push(node);\n      });\n    });\n    if (Object.keys(outputNodeNameToKey).length === 0) {\n      allNodes.forEach((key) => {\n        const node = nodes[key];\n        if (node.children.length === 0) {\n          outputs.push(node);\n        }\n      });\n    } else {\n      Object.keys(outputNodeNameToKey).forEach((name) => {\n        const [nodeName] = getNodeNameAndIndex(name);\n        const node = nodes[nodeName];\n        if (node != null) {\n          node.signatureKey = outputNodeNameToKey[name];\n          outputs.push(node);\n        }\n      });\n    }\n    if (Object.keys(inputNodeNameToKey).length > 0) {\n      Object.keys(inputNodeNameToKey).forEach((name) => {\n        const [nodeName] = getNodeNameAndIndex(name);\n        const node = nodes[nodeName];\n        if (node) {\n          node.signatureKey = inputNodeNameToKey[name];\n          inputs.push(node);\n        }\n      });\n    } else {\n      inputs = placeholders;\n    }\n    let functions = {};\n    if (graph.library != null && graph.library.function != null) {\n      functions = graph.library.function.reduce((functions2, func2) => {\n        functions2[func2.signature.name] = this.mapFunction(func2);\n        return functions2;\n      }, {});\n    }\n    const result = { nodes, inputs, outputs, weights, placeholders, signature, functions };\n    if (initNodes.length > 0) {\n      result.initNodes = initNodes;\n    }\n    return result;\n  }\n  mapSignatureEntries(entries) {\n    return Object.keys(entries || {}).reduce((prev, curr) => {\n      prev[entries[curr].name] = curr;\n      return prev;\n    }, {});\n  }\n  mapNode(node) {\n    const mapper = getRegisteredOp(node.op) || this.opMappers[node.op] || {};\n    if (node.attr == null) {\n      node.attr = {};\n    }\n    const newNode = {\n      name: node.name,\n      op: node.op,\n      category: mapper.category,\n      inputNames: (node.input || []).map((input2) => input2.startsWith(\"^\") ? input2.slice(1) : input2),\n      inputs: [],\n      children: [],\n      inputParams: {},\n      attrParams: {},\n      rawAttrs: node.attr,\n      outputs: mapper.outputs\n    };\n    if (mapper.inputs != null) {\n      newNode.inputParams = mapper.inputs.reduce((map, param) => {\n        map[param.name] = {\n          type: param.type,\n          inputIndexStart: param.start,\n          inputIndexEnd: param.end\n        };\n        return map;\n      }, {});\n    }\n    if (mapper.attrs != null) {\n      newNode.attrParams = mapper.attrs.reduce((map, param) => {\n        const type = param.type;\n        let value = void 0;\n        switch (param.type) {\n          case \"string\":\n            value = getStringParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getStringParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"string[]\":\n            value = getStringArrayParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getStringArrayParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"number\":\n            value = getNumberParam(node.attr, param.tfName, param.defaultValue || 0);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getNumberParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"number[]\":\n            value = getNumericArrayParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getNumericArrayParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"bool\":\n            value = getBoolParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getBoolParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"bool[]\":\n            value = getBoolArrayParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getBoolArrayParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"shape\":\n            value = getTensorShapeParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getTensorShapeParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"shape[]\":\n            value = getTensorShapeArrayParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getTensorShapeArrayParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"dtype\":\n            value = getDtypeParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getDtypeParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"dtype[]\":\n            value = getDtypeArrayParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getDtypeArrayParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"func\":\n            value = getFuncParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getFuncParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"tensor\":\n          case \"tensors\":\n            break;\n          default:\n            throw new Error(`Unsupported param type: ${param.type} for op: ${node.op}`);\n        }\n        map[param.name] = { value, type };\n        return map;\n      }, {});\n    }\n    return newNode;\n  }\n  mapFunction(functionDef) {\n    const tfNodes = functionDef.nodeDef;\n    const placeholders = [];\n    const weights = [];\n    let nodes = {};\n    if (tfNodes != null) {\n      nodes = tfNodes.reduce((map, node) => {\n        map[node.name] = this.mapNode(node);\n        if (node.op === \"Const\") {\n          weights.push(map[node.name]);\n        }\n        return map;\n      }, {});\n    }\n    const inputs = [];\n    const outputs = [];\n    functionDef.signature.inputArg.forEach((arg) => {\n      const [nodeName] = getNodeNameAndIndex(arg.name);\n      const node = {\n        name: nodeName,\n        op: \"Placeholder\",\n        inputs: [],\n        inputNames: [],\n        category: \"graph\",\n        inputParams: {},\n        attrParams: { dtype: { value: parseDtypeParam(arg.type), type: \"dtype\" } },\n        children: []\n      };\n      node.signatureKey = arg.name;\n      inputs.push(node);\n      nodes[nodeName] = node;\n    });\n    const allNodes = Object.keys(nodes);\n    allNodes.forEach((key) => {\n      const node = nodes[key];\n      node.inputNames.forEach((name, index) => {\n        const [nodeName, , outputName] = getNodeNameAndIndex(name);\n        const inputNode = nodes[nodeName];\n        if (inputNode.outputs != null) {\n          const outputIndex = inputNode.outputs.indexOf(outputName);\n          if (outputIndex !== -1) {\n            const inputName = `${nodeName}:${outputIndex}`;\n            node.inputNames[index] = inputName;\n          }\n        }\n        node.inputs.push(inputNode);\n        inputNode.children.push(node);\n      });\n    });\n    const returnNodeMap = functionDef.ret;\n    functionDef.signature.outputArg.forEach((output) => {\n      const [nodeName, index] = getNodeNameAndIndex(returnNodeMap[output.name]);\n      const node = nodes[nodeName];\n      if (node != null) {\n        node.defaultOutput = index;\n        outputs.push(node);\n      }\n    });\n    const signature = this.mapArgsToSignature(functionDef);\n    return { nodes, inputs, outputs, weights, placeholders, signature };\n  }\n  mapArgsToSignature(functionDef) {\n    return {\n      methodName: functionDef.signature.name,\n      inputs: functionDef.signature.inputArg.reduce((map, arg) => {\n        map[arg.name] = this.mapArgToTensorInfo(arg);\n        return map;\n      }, {}),\n      outputs: functionDef.signature.outputArg.reduce((map, arg) => {\n        map[arg.name] = this.mapArgToTensorInfo(arg, functionDef.ret);\n        return map;\n      }, {})\n    };\n  }\n  mapArgToTensorInfo(arg, nameMap2) {\n    let name = arg.name;\n    if (nameMap2 != null) {\n      name = nameMap2[name];\n    }\n    return { name, dtype: arg.type };\n  }\n};\nfunction decodeBase64(text) {\n  const global2 = env().global;\n  if (typeof global2.atob !== \"undefined\") {\n    return global2.atob(text);\n  } else if (typeof Buffer !== \"undefined\") {\n    return new Buffer(text, \"base64\").toString();\n  } else {\n    throw new Error(\"Unable to decode base64 in this environment. Missing built-in atob() or Buffer()\");\n  }\n}\nfunction parseStringParam(s2, keepCase) {\n  const value = Array.isArray(s2) ? String.fromCharCode.apply(null, s2) : decodeBase64(s2);\n  return keepCase ? value : value.toLowerCase();\n}\nfunction getStringParam(attrs, name, def, keepCase = false) {\n  const param = attrs[name];\n  if (param != null) {\n    return parseStringParam(param.s, keepCase);\n  }\n  return def;\n}\nfunction getBoolParam(attrs, name, def) {\n  const param = attrs[name];\n  return param ? param.b : def;\n}\nfunction getNumberParam(attrs, name, def) {\n  const param = attrs[name] || {};\n  const value = param[\"i\"] != null ? param[\"i\"] : param[\"f\"] != null ? param[\"f\"] : def;\n  return typeof value === \"number\" ? value : parseInt(value, 10);\n}\nfunction parseDtypeParam(value) {\n  if (typeof value === \"string\") {\n    value = DataType[value];\n  }\n  switch (value) {\n    case DataType.DT_FLOAT:\n    case DataType.DT_HALF:\n      return \"float32\";\n    case DataType.DT_INT32:\n    case DataType.DT_INT64:\n    case DataType.DT_INT8:\n    case DataType.DT_UINT8:\n      return \"int32\";\n    case DataType.DT_BOOL:\n      return \"bool\";\n    case DataType.DT_DOUBLE:\n      return \"float32\";\n    case DataType.DT_STRING:\n      return \"string\";\n    default:\n      return null;\n  }\n}\nfunction getFuncParam(attrs, name, def) {\n  const param = attrs[name];\n  if (param && param.func) {\n    return param.func.name;\n  }\n  return def;\n}\nfunction getDtypeParam(attrs, name, def) {\n  const param = attrs[name];\n  if (param && param.type) {\n    return parseDtypeParam(param.type);\n  }\n  return def;\n}\nfunction getDtypeArrayParam(attrs, name, def) {\n  const param = attrs[name];\n  if (param && param.list && param.list.type) {\n    return param.list.type.map((v) => parseDtypeParam(v));\n  }\n  return def;\n}\nfunction parseTensorShapeParam(shape) {\n  if (shape.unknownRank) {\n    return void 0;\n  }\n  if (shape.dim != null) {\n    return shape.dim.map((dim) => typeof dim.size === \"number\" ? dim.size : parseInt(dim.size, 10));\n  }\n  return [];\n}\nfunction getTensorShapeParam(attrs, name, def) {\n  const param = attrs[name];\n  if (param && param.shape) {\n    return parseTensorShapeParam(param.shape);\n  }\n  return def;\n}\nfunction getNumericArrayParam(attrs, name, def) {\n  const param = attrs[name];\n  if (param) {\n    return ((param.list.f && param.list.f.length ? param.list.f : param.list.i) || []).map((v) => typeof v === \"number\" ? v : parseInt(v, 10));\n  }\n  return def;\n}\nfunction getStringArrayParam(attrs, name, def, keepCase = false) {\n  const param = attrs[name];\n  if (param && param.list && param.list.s) {\n    return param.list.s.map((v) => {\n      return parseStringParam(v, keepCase);\n    });\n  }\n  return def;\n}\nfunction getTensorShapeArrayParam(attrs, name, def) {\n  const param = attrs[name];\n  if (param && param.list && param.list.shape) {\n    return param.list.shape.map((v) => {\n      return parseTensorShapeParam(v);\n    });\n  }\n  return def;\n}\nfunction getBoolArrayParam(attrs, name, def) {\n  const param = attrs[name];\n  if (param && param.list && param.list.b) {\n    return param.list.b;\n  }\n  return def;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/custom_op/node_value_impl.js\nvar NodeValueImpl = class {\n  constructor(node, tensorMap, context) {\n    this.node = node;\n    this.tensorMap = tensorMap;\n    this.context = context;\n    this.inputs = [];\n    this.attrs = {};\n    this.inputs = node.inputNames.map((name) => this.getInput(name));\n    if (node.rawAttrs != null) {\n      this.attrs = Object.keys(node.rawAttrs).reduce((attrs, key) => {\n        attrs[key] = this.getAttr(key);\n        return attrs;\n      }, {});\n    }\n  }\n  getInput(name) {\n    return getTensor(name, this.tensorMap, this.context);\n  }\n  getAttr(name, defaultValue) {\n    const value = this.node.rawAttrs[name];\n    if (value.tensor != null) {\n      return getTensor(name, this.tensorMap, this.context);\n    }\n    if (value.i != null || value.f != null) {\n      return getNumberParam(this.node.rawAttrs, name, defaultValue);\n    }\n    if (value.s != null) {\n      return getStringParam(this.node.rawAttrs, name, defaultValue);\n    }\n    if (value.b != null) {\n      return getBoolParam(this.node.rawAttrs, name, defaultValue);\n    }\n    if (value.shape != null) {\n      return getTensorShapeParam(this.node.rawAttrs, name, defaultValue);\n    }\n    if (value.type != null) {\n      return getDtypeParam(this.node.rawAttrs, name, defaultValue);\n    }\n    if (value.list != null) {\n      if (value.list.i != null || value.list.f != null) {\n        return getNumericArrayParam(this.node.rawAttrs, name, defaultValue);\n      }\n      if (value.list.s != null) {\n        return getStringArrayParam(this.node.rawAttrs, name, defaultValue);\n      }\n      if (value.list.shape != null) {\n        return getTensorShapeArrayParam(this.node.rawAttrs, name, defaultValue);\n      }\n      if (value.list.b != null) {\n        return getBoolArrayParam(this.node.rawAttrs, name, defaultValue);\n      }\n      if (value.list.type != null) {\n        return getDtypeArrayParam(this.node.rawAttrs, name, defaultValue);\n      }\n    }\n    return defaultValue;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/ops_for_converter.js\nvar ops_for_converter_exports = {};\n__export(ops_for_converter_exports, {\n  OP_SCOPE_SUFFIX: () => OP_SCOPE_SUFFIX,\n  abs: () => abs,\n  acos: () => acos,\n  acosh: () => acosh,\n  add: () => add2,\n  addN: () => addN,\n  all: () => all,\n  any: () => any,\n  argMax: () => argMax,\n  argMin: () => argMin,\n  asin: () => asin,\n  asinh: () => asinh,\n  atan: () => atan,\n  atan2: () => atan2,\n  atanh: () => atanh,\n  avgPool: () => avgPool,\n  avgPool3d: () => avgPool3d,\n  basicLSTMCell: () => basicLSTMCell,\n  batchNorm: () => batchNorm,\n  batchNorm2d: () => batchNorm2d,\n  batchNorm3d: () => batchNorm3d,\n  batchNorm4d: () => batchNorm4d,\n  batchToSpaceND: () => batchToSpaceND,\n  bincount: () => bincount,\n  booleanMaskAsync: () => booleanMaskAsync,\n  broadcastArgs: () => broadcastArgs,\n  broadcastTo: () => broadcastTo,\n  buffer: () => buffer,\n  cast: () => cast,\n  ceil: () => ceil,\n  clipByValue: () => clipByValue,\n  clone: () => clone,\n  complex: () => complex,\n  concat: () => concat,\n  concat1d: () => concat1d,\n  concat2d: () => concat2d,\n  concat3d: () => concat3d,\n  concat4d: () => concat4d,\n  conv1d: () => conv1d,\n  conv2d: () => conv2d,\n  conv2dTranspose: () => conv2dTranspose,\n  conv3d: () => conv3d,\n  conv3dTranspose: () => conv3dTranspose,\n  cos: () => cos,\n  cosh: () => cosh,\n  cosineWindow: () => cosineWindow,\n  cumprod: () => cumprod,\n  cumsum: () => cumsum,\n  denseBincount: () => denseBincount,\n  depthToSpace: () => depthToSpace,\n  depthwiseConv2d: () => depthwiseConv2d,\n  diag: () => diag,\n  dilation2d: () => dilation2d,\n  div: () => div,\n  divNoNan: () => divNoNan,\n  dot: () => dot,\n  dropout: () => dropout,\n  einsum: () => einsum,\n  elu: () => elu,\n  enclosingPowerOfTwo: () => enclosingPowerOfTwo,\n  equal: () => equal,\n  erf: () => erf,\n  euclideanNorm: () => euclideanNorm,\n  exp: () => exp,\n  expandDims: () => expandDims,\n  expm1: () => expm1,\n  eye: () => eye,\n  fft: () => fft,\n  fill: () => fill,\n  floor: () => floor,\n  floorDiv: () => floorDiv,\n  fused: () => fused_ops_exports,\n  gather: () => gather,\n  gatherND: () => gatherND,\n  greater: () => greater,\n  greaterEqual: () => greaterEqual,\n  ifft: () => ifft,\n  imag: () => imag,\n  image: () => image,\n  inTopKAsync: () => inTopKAsync,\n  irfft: () => irfft,\n  isFinite: () => isFinite2,\n  isInf: () => isInf,\n  isNaN: () => isNaN2,\n  leakyRelu: () => leakyRelu,\n  less: () => less,\n  lessEqual: () => lessEqual,\n  linalg: () => linalg,\n  linspace: () => linspace,\n  localResponseNormalization: () => localResponseNormalization,\n  log: () => log2,\n  log1p: () => log1p,\n  logSigmoid: () => logSigmoid,\n  logSoftmax: () => logSoftmax,\n  logSumExp: () => logSumExp,\n  logicalAnd: () => logicalAnd,\n  logicalNot: () => logicalNot,\n  logicalOr: () => logicalOr,\n  logicalXor: () => logicalXor,\n  losses: () => losses,\n  lowerBound: () => lowerBound,\n  matMul: () => matMul,\n  max: () => max,\n  maxPool: () => maxPool,\n  maxPool3d: () => maxPool3d,\n  maxPoolWithArgmax: () => maxPoolWithArgmax,\n  maximum: () => maximum,\n  mean: () => mean,\n  meshgrid: () => meshgrid,\n  min: () => min,\n  minimum: () => minimum,\n  mirrorPad: () => mirrorPad,\n  mod: () => mod,\n  moments: () => moments,\n  movingAverage: () => movingAverage,\n  mul: () => mul,\n  multiRNNCell: () => multiRNNCell,\n  multinomial: () => multinomial,\n  neg: () => neg,\n  norm: () => norm,\n  notEqual: () => notEqual,\n  oneHot: () => oneHot,\n  ones: () => ones2,\n  onesLike: () => onesLike,\n  op: () => op,\n  outerProduct: () => outerProduct,\n  pad: () => pad,\n  pad1d: () => pad1d,\n  pad2d: () => pad2d,\n  pad3d: () => pad3d,\n  pad4d: () => pad4d,\n  pool: () => pool,\n  pow: () => pow,\n  prelu: () => prelu,\n  print: () => print,\n  prod: () => prod,\n  rand: () => rand,\n  randomGamma: () => randomGamma,\n  randomNormal: () => randomNormal,\n  randomStandardNormal: () => randomStandardNormal,\n  randomUniform: () => randomUniform,\n  range: () => range,\n  real: () => real,\n  reciprocal: () => reciprocal,\n  relu: () => relu,\n  relu6: () => relu6,\n  reshape: () => reshape,\n  reverse: () => reverse,\n  reverse1d: () => reverse1d,\n  reverse2d: () => reverse2d,\n  reverse3d: () => reverse3d,\n  reverse4d: () => reverse4d,\n  rfft: () => rfft,\n  round: () => round2,\n  rsqrt: () => rsqrt,\n  scalar: () => scalar,\n  scatterND: () => scatterND,\n  searchSorted: () => searchSorted,\n  selu: () => selu,\n  separableConv2d: () => separableConv2d,\n  setdiff1dAsync: () => setdiff1dAsync,\n  sigmoid: () => sigmoid,\n  sign: () => sign,\n  signal: () => signal,\n  sin: () => sin,\n  sinh: () => sinh,\n  slice: () => slice,\n  slice1d: () => slice1d,\n  slice2d: () => slice2d,\n  slice3d: () => slice3d,\n  slice4d: () => slice4d,\n  softmax: () => softmax,\n  softplus: () => softplus,\n  spaceToBatchND: () => spaceToBatchND,\n  sparse: () => sparse,\n  sparseToDense: () => sparseToDense,\n  spectral: () => spectral,\n  split: () => split,\n  sqrt: () => sqrt,\n  square: () => square,\n  squaredDifference: () => squaredDifference,\n  squeeze: () => squeeze,\n  stack: () => stack,\n  step: () => step,\n  stridedSlice: () => stridedSlice,\n  string: () => string,\n  sub: () => sub,\n  sum: () => sum2,\n  tan: () => tan,\n  tanh: () => tanh2,\n  tensor: () => tensor,\n  tensor1d: () => tensor1d,\n  tensor2d: () => tensor2d,\n  tensor3d: () => tensor3d,\n  tensor4d: () => tensor4d,\n  tensor5d: () => tensor5d,\n  tensor6d: () => tensor6d,\n  tile: () => tile,\n  topk: () => topk,\n  transpose: () => transpose,\n  truncatedNormal: () => truncatedNormal,\n  unique: () => unique,\n  unsortedSegmentSum: () => unsortedSegmentSum,\n  unstack: () => unstack,\n  upperBound: () => upperBound,\n  variable: () => variable,\n  where: () => where,\n  whereAsync: () => whereAsync,\n  zeros: () => zeros,\n  zerosLike: () => zerosLike\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/arithmetic_executor.js\nvar executeOp = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"BiasAdd\":\n    case \"AddV2\":\n    case \"Add\": {\n      return [ops.add(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"AddN\": {\n      return [ops.addN(getParamValue(\"tensors\", node, tensorMap, context))];\n    }\n    case \"FloorMod\":\n    case \"Mod\":\n      return [ops.mod(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    case \"Mul\":\n      return [ops.mul(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    case \"RealDiv\":\n    case \"Div\": {\n      return [ops.div(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"DivNoNan\": {\n      return [ops.divNoNan(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"FloorDiv\": {\n      return [ops.floorDiv(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"Sub\": {\n      return [ops.sub(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"Minimum\": {\n      return [ops.minimum(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"Maximum\": {\n      return [ops.maximum(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"Pow\": {\n      return [ops.pow(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"SquaredDifference\": {\n      return [ops.squaredDifference(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/basic_math_executor.js\nvar executeOp2 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"Abs\":\n    case \"ComplexAbs\":\n      return [ops.abs(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Acos\":\n      return [ops.acos(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Acosh\":\n      return [ops.acosh(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Asin\":\n      return [ops.asin(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Asinh\":\n      return [ops.asinh(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Atan\":\n      return [ops.atan(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Atan2\":\n      return [ops.atan2(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"y\", node, tensorMap, context))];\n    case \"Atanh\":\n      return [ops.atanh(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Ceil\":\n      return [ops.ceil(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Complex\":\n      return [ops.complex(getParamValue(\"real\", node, tensorMap, context), getParamValue(\"imag\", node, tensorMap, context))];\n    case \"Cos\":\n      return [ops.cos(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Cosh\":\n      return [ops.cosh(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Elu\":\n      return [ops.elu(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Erf\":\n      return [ops.erf(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Exp\":\n      return [ops.exp(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Expm1\": {\n      return [ops.expm1(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Floor\":\n      return [ops.floor(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Log\":\n      return [ops.log(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Log1p\": {\n      return [ops.log1p(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Imag\":\n      return [ops.imag(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Neg\":\n      return [ops.neg(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Reciprocal\": {\n      return [ops.reciprocal(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Real\":\n      return [ops.real(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Relu\":\n      return [ops.relu(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Round\": {\n      return [ops.round(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Selu\":\n      return [ops.selu(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Sigmoid\":\n      return [ops.sigmoid(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Sin\":\n      return [ops.sin(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Sign\": {\n      return [ops.sign(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Sinh\": {\n      return [ops.sinh(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Softplus\": {\n      return [ops.softplus(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Sqrt\": {\n      return [ops.sqrt(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Square\": {\n      return [ops.square(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Tanh\": {\n      return [ops.tanh(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Tan\":\n      return [ops.tan(getParamValue(\"x\", node, tensorMap, context))];\n    case \"ClipByValue\":\n      return [ops.clipByValue(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"clipValueMin\", node, tensorMap, context), getParamValue(\"clipValueMax\", node, tensorMap, context))];\n    case \"Relu6\":\n      return [ops.relu6(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Rsqrt\":\n      return [ops.rsqrt(getTensor(node.inputNames[0], tensorMap, context))];\n    case \"Prod\":\n      return [ops.prod(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"axes\", node, tensorMap, context))];\n    case \"LeakyRelu\":\n      return [ops.leakyRelu(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"alpha\", node, tensorMap, context))];\n    case \"Prelu\":\n      return [ops.prelu(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"alpha\", node, tensorMap, context))];\n    case \"IsNan\":\n      return [ops.isNaN(getTensor(node.inputNames[0], tensorMap, context))];\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/tensor_utils.js\nfunction assertShapesMatchAllowUndefinedSize(shapeA, shapeB, errorMessagePrefix = \"\") {\n  if (typeof shapeA === \"number\" || typeof shapeB === \"number\") {\n    return;\n  }\n  util_exports.assert(shapeA.length === shapeB.length, () => errorMessagePrefix + ` Shapes ${shapeA} and ${shapeB} must match`);\n  for (let i2 = 0; i2 < shapeA.length; i2++) {\n    const dim0 = shapeA[i2];\n    const dim1 = shapeB[i2];\n    util_exports.assert(dim0 < 0 || dim1 < 0 || dim0 === dim1, () => errorMessagePrefix + ` Shapes ${shapeA} and ${shapeB} must match`);\n  }\n}\nfunction fullDefinedShape(elementShape) {\n  if (typeof elementShape === \"number\" || elementShape.some((dim) => dim < 0)) {\n    return false;\n  }\n  return true;\n}\nfunction inferElementShape(listElementShape, tensors, elementShape) {\n  let partialShape = mergeElementShape(listElementShape, elementShape);\n  const notfullDefinedShape = !fullDefinedShape(partialShape);\n  if (notfullDefinedShape && tensors.length === 0) {\n    throw new Error(`Tried to calculate elements of an empty list with non-fully-defined elementShape: ${partialShape}`);\n  }\n  if (notfullDefinedShape) {\n    tensors.forEach((tensor2) => {\n      partialShape = mergeElementShape(tensor2.shape, partialShape);\n    });\n  }\n  if (!fullDefinedShape(partialShape)) {\n    throw new Error(`Non-fully-defined elementShape: ${partialShape}`);\n  }\n  return partialShape;\n}\nfunction mergeElementShape(elementShapeA, elementShapeB) {\n  if (typeof elementShapeA === \"number\") {\n    return elementShapeB;\n  }\n  if (typeof elementShapeB === \"number\") {\n    return elementShapeA;\n  }\n  if (elementShapeA.length !== elementShapeB.length) {\n    throw new Error(`Incompatible ranks during merge: ${elementShapeA} vs. ${elementShapeB}`);\n  }\n  const result = [];\n  for (let i2 = 0; i2 < elementShapeA.length; ++i2) {\n    const dim0 = elementShapeA[i2];\n    const dim1 = elementShapeB[i2];\n    if (dim0 >= 0 && dim1 >= 0 && dim0 !== dim1) {\n      throw new Error(`Incompatible shape during merge: ${elementShapeA} vs. ${elementShapeB}`);\n    }\n    result[i2] = dim0 >= 0 ? dim0 : dim1;\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/tensor_array.js\nvar TensorArray = class {\n  constructor(name, dtype, maxSize, elementShape, identicalElementShapes, dynamicSize, clearAfterRead) {\n    this.name = name;\n    this.dtype = dtype;\n    this.maxSize = maxSize;\n    this.elementShape = elementShape;\n    this.identicalElementShapes = identicalElementShapes;\n    this.dynamicSize = dynamicSize;\n    this.clearAfterRead = clearAfterRead;\n    this.tensors = [];\n    this.closed_ = false;\n    this.idTensor = scalar(0);\n    keep(this.idTensor);\n  }\n  get id() {\n    return this.idTensor.id;\n  }\n  get closed() {\n    return this.closed_;\n  }\n  clearAndClose(keepIds) {\n    this.tensors.forEach((tensor2) => {\n      if (keepIds == null || !keepIds.has(tensor2.tensor.id)) {\n        tensor2.tensor.dispose();\n      }\n    });\n    this.tensors = [];\n    this.closed_ = true;\n    this.idTensor.dispose();\n  }\n  size() {\n    return this.tensors.length;\n  }\n  read(index) {\n    if (this.closed_) {\n      throw new Error(`TensorArray ${this.name} has already been closed.`);\n    }\n    if (index < 0 || index >= this.size()) {\n      throw new Error(`Tried to read from index ${index}, but array size is: ${this.size()}`);\n    }\n    const tensorWithState = this.tensors[index];\n    if (tensorWithState.cleared) {\n      throw new Error(`TensorArray ${this.name}: Could not read index ${index} twice because it was cleared after a previous read (perhaps try setting clear_after_read = false?).`);\n    }\n    if (this.clearAfterRead) {\n      tensorWithState.cleared = true;\n    }\n    tensorWithState.read = true;\n    return tensorWithState.tensor;\n  }\n  readMany(indices) {\n    return indices.map((index) => this.read(index));\n  }\n  write(index, tensor2) {\n    if (this.closed_) {\n      throw new Error(`TensorArray ${this.name} has already been closed.`);\n    }\n    if (index < 0 || !this.dynamicSize && index >= this.maxSize) {\n      throw new Error(`Tried to write to index ${index}, but array is not resizeable and size is: ${this.maxSize}`);\n    }\n    const t2 = this.tensors[index] || {};\n    if (tensor2.dtype !== this.dtype) {\n      throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${index},\n          because the value dtype is ${tensor2.dtype}, but TensorArray dtype is ${this.dtype}.`);\n    }\n    if (this.size() === 0 && (this.elementShape == null || this.elementShape.length === 0)) {\n      this.elementShape = tensor2.shape;\n    }\n    assertShapesMatchAllowUndefinedSize(this.elementShape, tensor2.shape, `TensorArray ${this.name}: Could not write to TensorArray index ${index}.`);\n    if (t2.read) {\n      throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${index}, because it has already been read.`);\n    }\n    if (t2.written) {\n      throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${index}, because it has already been written.`);\n    }\n    t2.tensor = tensor2;\n    keep(tensor2);\n    t2.written = true;\n    this.tensors[index] = t2;\n  }\n  writeMany(indices, tensors) {\n    if (indices.length !== tensors.length) {\n      throw new Error(`TensorArray ${this.name}: could not write multiple tensors,because the index size: ${indices.length} is not the same as tensors size: ${tensors.length}.`);\n    }\n    indices.forEach((i2, index) => this.write(i2, tensors[index]));\n  }\n  gather(indices, dtype) {\n    if (!!dtype && dtype !== this.dtype) {\n      throw new Error(`TensorArray dtype is ${this.dtype} but gather requested dtype ${dtype}`);\n    }\n    if (!indices) {\n      indices = [];\n      for (let i2 = 0; i2 < this.size(); i2++) {\n        indices.push(i2);\n      }\n    } else {\n      indices = indices.slice(0, this.size());\n    }\n    if (indices.length === 0) {\n      return tensor([], [0].concat(this.elementShape));\n    }\n    const tensors = this.readMany(indices);\n    assertShapesMatchAllowUndefinedSize(this.elementShape, tensors[0].shape, \"TensorArray shape mismatch: \");\n    return stack(tensors, 0);\n  }\n  concat(dtype) {\n    if (!!dtype && dtype !== this.dtype) {\n      throw new Error(`TensorArray dtype is ${this.dtype} but concat requested dtype ${dtype}`);\n    }\n    if (this.size() === 0) {\n      return tensor([], [0].concat(this.elementShape));\n    }\n    const indices = [];\n    for (let i2 = 0; i2 < this.size(); i2++) {\n      indices.push(i2);\n    }\n    const tensors = this.readMany(indices);\n    assertShapesMatchAllowUndefinedSize(this.elementShape, tensors[0].shape, `TensorArray shape mismatch: tensor array shape (${this.elementShape}) vs first tensor shape (${tensors[0].shape})`);\n    return concat(tensors, 0);\n  }\n  scatter(indices, tensor2) {\n    if (tensor2.dtype !== this.dtype) {\n      throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${tensor2.dtype}`);\n    }\n    if (indices.length !== tensor2.shape[0]) {\n      throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${indices.length} vs. ${tensor2.shape[0]}`);\n    }\n    const maxIndex = Math.max(...indices);\n    if (!this.dynamicSize && maxIndex >= this.maxSize) {\n      throw new Error(`Max index must be < array size (${maxIndex}  vs. ${this.maxSize})`);\n    }\n    this.writeMany(indices, unstack(tensor2, 0));\n  }\n  split(length, tensor2) {\n    if (tensor2.dtype !== this.dtype) {\n      throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${tensor2.dtype}`);\n    }\n    let totalLength = 0;\n    const cumulativeLengths = length.map((len) => {\n      totalLength += len;\n      return totalLength;\n    });\n    if (totalLength !== tensor2.shape[0]) {\n      throw new Error(`Expected sum of lengths to be equal to\n          tensor.shape[0], but sum of lengths is\n        ${totalLength}, and tensor's shape is: ${tensor2.shape}`);\n    }\n    if (!this.dynamicSize && length.length !== this.maxSize) {\n      throw new Error(`TensorArray's size is not equal to the size of lengths (${this.maxSize} vs. ${length.length}), and the TensorArray is not marked as dynamically resizeable`);\n    }\n    const elementPerRow = totalLength === 0 ? 0 : tensor2.size / totalLength;\n    const tensors = [];\n    tidy(() => {\n      tensor2 = reshape(tensor2, [1, totalLength, elementPerRow]);\n      for (let i2 = 0; i2 < length.length; ++i2) {\n        const previousLength = i2 === 0 ? 0 : cumulativeLengths[i2 - 1];\n        const indices2 = [0, previousLength, 0];\n        const sizes = [1, length[i2], elementPerRow];\n        tensors[i2] = reshape(slice(tensor2, indices2, sizes), this.elementShape);\n      }\n      return tensors;\n    });\n    const indices = [];\n    for (let i2 = 0; i2 < length.length; i2++) {\n      indices[i2] = i2;\n    }\n    this.writeMany(indices, tensors);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/tensor_list.js\nvar TensorList = class {\n  constructor(tensors, elementShape, elementDtype, maxNumElements = -1) {\n    this.tensors = tensors;\n    this.elementShape = elementShape;\n    this.elementDtype = elementDtype;\n    if (tensors != null) {\n      tensors.forEach((tensor2) => {\n        if (elementDtype !== tensor2.dtype) {\n          throw new Error(`Invalid data types; op elements ${elementDtype}, but list elements ${tensor2.dtype}`);\n        }\n        assertShapesMatchAllowUndefinedSize(elementShape, tensor2.shape, \"TensorList shape mismatch: \");\n        keep(tensor2);\n      });\n    }\n    this.idTensor = scalar(0);\n    this.maxNumElements = maxNumElements;\n    keep(this.idTensor);\n  }\n  get id() {\n    return this.idTensor.id;\n  }\n  copy() {\n    return new TensorList([...this.tensors], this.elementShape, this.elementDtype);\n  }\n  clearAndClose(keepIds) {\n    this.tensors.forEach((tensor2) => {\n      if (keepIds == null || !keepIds.has(tensor2.id)) {\n        tensor2.dispose();\n      }\n    });\n    this.tensors.length = 0;\n    this.idTensor.dispose();\n  }\n  size() {\n    return this.tensors.length;\n  }\n  stack(elementShape, elementDtype, numElements = -1) {\n    if (elementDtype !== this.elementDtype) {\n      throw new Error(`Invalid data types; op elements ${elementDtype}, but list elements ${this.elementDtype}`);\n    }\n    if (numElements !== -1 && this.tensors.length !== numElements) {\n      throw new Error(`Operation expected a list with ${numElements} elements but got a list with ${this.tensors.length} elements.`);\n    }\n    assertShapesMatchAllowUndefinedSize(elementShape, this.elementShape, \"TensorList shape mismatch: \");\n    const outputElementShape = inferElementShape(this.elementShape, this.tensors, elementShape);\n    return tidy(() => {\n      const reshapedTensors = this.tensors.map((tensor2) => reshape(tensor2, outputElementShape));\n      return stack(reshapedTensors, 0);\n    });\n  }\n  popBack(elementShape, elementDtype) {\n    if (elementDtype !== this.elementDtype) {\n      throw new Error(`Invalid data types; op elements ${elementDtype}, but list elements ${this.elementDtype}`);\n    }\n    if (this.size() === 0) {\n      throw new Error(\"Trying to pop from an empty list.\");\n    }\n    const outputElementShape = inferElementShape(this.elementShape, this.tensors, elementShape);\n    const tensor2 = this.tensors.pop();\n    assertShapesMatchAllowUndefinedSize(tensor2.shape, elementShape, \"TensorList shape mismatch: \");\n    return reshape(tensor2, outputElementShape);\n  }\n  pushBack(tensor2) {\n    if (tensor2.dtype !== this.elementDtype) {\n      throw new Error(`Invalid data types; op elements ${tensor2.dtype}, but list elements ${this.elementDtype}`);\n    }\n    assertShapesMatchAllowUndefinedSize(tensor2.shape, this.elementShape, \"TensorList shape mismatch: \");\n    if (this.maxNumElements === this.size()) {\n      throw new Error(`Trying to push element into a full list.`);\n    }\n    keep(tensor2);\n    this.tensors.push(tensor2);\n  }\n  resize(size) {\n    if (size < 0) {\n      throw new Error(`TensorListResize expects size to be non-negative. Got: ${size}`);\n    }\n    if (this.maxNumElements !== -1 && size > this.maxNumElements) {\n      throw new Error(`TensorListResize input size ${size} is greater maxNumElement ${this.maxNumElements}.`);\n    }\n    const destTensorList = new TensorList([], this.elementShape, this.elementDtype, this.maxNumElements);\n    destTensorList.tensors.length = size;\n    for (let i2 = 0; i2 < Math.min(this.tensors.length, size); ++i2) {\n      destTensorList.tensors[i2] = this.tensors[i2];\n    }\n    return destTensorList;\n  }\n  getItem(elementIndex, elementShape, elementDtype) {\n    if (elementDtype !== this.elementDtype) {\n      throw new Error(`Invalid data types; op elements ${elementDtype}, but list elements ${this.elementDtype}`);\n    }\n    if (elementIndex < 0 || elementIndex > this.tensors.length) {\n      throw new Error(`Trying to access element ${elementIndex} in a list with ${this.tensors.length} elements.`);\n    }\n    if (this.tensors[elementIndex] == null) {\n      throw new Error(`element at index ${elementIndex} is null.`);\n    }\n    assertShapesMatchAllowUndefinedSize(this.tensors[elementIndex].shape, elementShape, \"TensorList shape mismatch: \");\n    const outputElementShape = inferElementShape(this.elementShape, this.tensors, elementShape);\n    return reshape(this.tensors[elementIndex], outputElementShape);\n  }\n  setItem(elementIndex, tensor2) {\n    if (tensor2.dtype !== this.elementDtype) {\n      throw new Error(`Invalid data types; op elements ${tensor2.dtype}, but list elements ${this.elementDtype}`);\n    }\n    if (elementIndex < 0 || this.maxNumElements !== -1 && elementIndex >= this.maxNumElements) {\n      throw new Error(`Trying to set element ${elementIndex} in a list with max ${this.maxNumElements} elements.`);\n    }\n    assertShapesMatchAllowUndefinedSize(this.elementShape, tensor2.shape, \"TensorList shape mismatch: \");\n    keep(tensor2);\n    this.tensors[elementIndex] = tensor2;\n  }\n  gather(indices, elementDtype, elementShape) {\n    if (elementDtype !== this.elementDtype) {\n      throw new Error(`Invalid data types; op elements ${elementDtype}, but list elements ${this.elementDtype}`);\n    }\n    assertShapesMatchAllowUndefinedSize(this.elementShape, elementShape, \"TensorList shape mismatch: \");\n    indices = indices.slice(0, this.size());\n    const outputElementShape = inferElementShape(this.elementShape, this.tensors, elementShape);\n    if (indices.length === 0) {\n      return tensor([], [0].concat(outputElementShape));\n    }\n    return tidy(() => {\n      const tensors = indices.map((i2) => reshape(this.tensors[i2], outputElementShape));\n      return stack(tensors, 0);\n    });\n  }\n  concat(elementDtype, elementShape) {\n    if (!!elementDtype && elementDtype !== this.elementDtype) {\n      throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${elementDtype}`);\n    }\n    assertShapesMatchAllowUndefinedSize(this.elementShape, elementShape, \"TensorList shape mismatch: \");\n    const outputElementShape = inferElementShape(this.elementShape, this.tensors, elementShape);\n    if (this.size() === 0) {\n      return tensor([], [0].concat(outputElementShape));\n    }\n    return tidy(() => {\n      const tensors = this.tensors.map((t2) => reshape(t2, outputElementShape));\n      return concat(tensors, 0);\n    });\n  }\n};\nfunction fromTensor(tensor2, elementShape, elementDtype) {\n  const dtype = tensor2.dtype;\n  if (tensor2.shape.length < 1) {\n    throw new Error(`Tensor must be at least a vector, but saw shape: ${tensor2.shape}`);\n  }\n  if (tensor2.dtype !== elementDtype) {\n    throw new Error(`Invalid data types; op elements ${tensor2.dtype}, but list elements ${elementDtype}`);\n  }\n  const tensorElementShape = tensor2.shape.slice(1);\n  assertShapesMatchAllowUndefinedSize(tensorElementShape, elementShape, \"TensorList shape mismatch: \");\n  const tensorList = unstack(tensor2);\n  return new TensorList(tensorList, elementShape, dtype);\n}\nfunction reserve(elementShape, elementDtype, numElements, maxNumElements) {\n  return new TensorList([], elementShape, elementDtype, maxNumElements);\n}\nfunction scatter(tensor2, indices, elementShape, numElements) {\n  if (indices.length !== tensor2.shape[0]) {\n    throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${indices.length} vs. ${tensor2.shape[0]}`);\n  }\n  const maxIndex = Math.max(...indices);\n  if (numElements != null && numElements !== -1 && maxIndex >= numElements) {\n    throw new Error(`Max index must be < array size (${maxIndex}  vs. ${numElements})`);\n  }\n  const list = new TensorList([], elementShape, tensor2.dtype, numElements);\n  const tensors = unstack(tensor2, 0);\n  indices.forEach((value, index) => {\n    list.setItem(value, tensors[index]);\n  });\n  return list;\n}\nfunction split2(tensor2, length, elementShape) {\n  let totalLength = 0;\n  const cumulativeLengths = length.map((len) => {\n    totalLength += len;\n    return totalLength;\n  });\n  if (totalLength !== tensor2.shape[0]) {\n    throw new Error(`Expected sum of lengths to be equal to\n          tensor.shape[0], but sum of lengths is\n        ${totalLength}, and tensor's shape is: ${tensor2.shape}`);\n  }\n  const shapeWithoutFirstDim = tensor2.shape.slice(1);\n  const outputElementShape = mergeElementShape(shapeWithoutFirstDim, elementShape);\n  const elementPerRow = totalLength === 0 ? 0 : tensor2.size / totalLength;\n  const tensors = tidy(() => {\n    const tensors2 = [];\n    tensor2 = reshape(tensor2, [1, totalLength, elementPerRow]);\n    for (let i2 = 0; i2 < length.length; ++i2) {\n      const previousLength = i2 === 0 ? 0 : cumulativeLengths[i2 - 1];\n      const indices = [0, previousLength, 0];\n      const sizes = [1, length[i2], elementPerRow];\n      tensors2[i2] = reshape(slice(tensor2, indices, sizes), outputElementShape);\n    }\n    tensor2.dispose();\n    return tensors2;\n  });\n  const list = new TensorList([], elementShape, tensor2.dtype, length.length);\n  for (let i2 = 0; i2 < tensors.length; i2++) {\n    list.setItem(i2, tensors[i2]);\n  }\n  return list;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/control_executor.js\nvar executeOp3 = async (node, tensorMap, context) => {\n  switch (node.op) {\n    case \"If\":\n    case \"StatelessIf\": {\n      const thenFunc = getParamValue(\"thenBranch\", node, tensorMap, context);\n      const elseFunc = getParamValue(\"elseBranch\", node, tensorMap, context);\n      const cond = getParamValue(\"cond\", node, tensorMap, context);\n      const args = getParamValue(\"args\", node, tensorMap, context);\n      const condValue = await cond.data();\n      if (condValue[0]) {\n        return context.functionMap[thenFunc].executeFunctionAsync(args, context.tensorArrayMap, context.tensorListMap);\n      } else {\n        return context.functionMap[elseFunc].executeFunctionAsync(args, context.tensorArrayMap, context.tensorListMap);\n      }\n    }\n    case \"While\":\n    case \"StatelessWhile\": {\n      const bodyFunc = getParamValue(\"body\", node, tensorMap, context);\n      const condFunc = getParamValue(\"cond\", node, tensorMap, context);\n      const args = getParamValue(\"args\", node, tensorMap, context);\n      const condResult = await context.functionMap[condFunc].executeFunctionAsync(args, context.tensorArrayMap, context.tensorListMap);\n      const argIds = args.map((tensor2) => tensor2.id);\n      let condValue = await condResult[0].data();\n      condResult.forEach((tensor2) => {\n        if (!tensor2.kept && argIds.indexOf(tensor2.id) === -1) {\n          tensor2.dispose();\n        }\n      });\n      let result = args;\n      while (condValue[0]) {\n        const origResult = result;\n        result = await context.functionMap[bodyFunc].executeFunctionAsync(result, context.tensorArrayMap, context.tensorListMap);\n        const resultIds = result.map((tensor2) => tensor2.id);\n        origResult.forEach((tensor2) => {\n          if (!tensor2.kept && argIds.indexOf(tensor2.id) === -1 && resultIds.indexOf(tensor2.id) === -1) {\n            tensor2.dispose();\n          }\n        });\n        const condResult2 = await context.functionMap[condFunc].executeFunctionAsync(result, context.tensorArrayMap, context.tensorListMap);\n        condValue = await condResult2[0].data();\n        condResult2.forEach((tensor2) => {\n          if (!tensor2.kept && argIds.indexOf(tensor2.id) === -1 && resultIds.indexOf(tensor2.id) === -1) {\n            tensor2.dispose();\n          }\n        });\n      }\n      return result;\n    }\n    case \"LoopCond\": {\n      const pred = getParamValue(\"pred\", node, tensorMap, context);\n      return [cloneTensor(pred)];\n    }\n    case \"Switch\": {\n      const pred = getParamValue(\"pred\", node, tensorMap, context);\n      let data = getParamValue(\"data\", node, tensorMap, context);\n      if (!data.kept) {\n        data = cloneTensor(data);\n      }\n      return (await pred.data())[0] ? [void 0, data] : [data, void 0];\n    }\n    case \"Merge\": {\n      const inputName = node.inputNames.find((name) => getTensor(name, tensorMap, context) !== void 0);\n      if (inputName) {\n        const data = getTensor(inputName, tensorMap, context);\n        return [cloneTensor(data)];\n      }\n      return void 0;\n    }\n    case \"Enter\": {\n      const frameId = getParamValue(\"frameName\", node, tensorMap, context);\n      const data = getParamValue(\"tensor\", node, tensorMap, context);\n      context.enterFrame(frameId);\n      return [cloneTensor(data)];\n    }\n    case \"Exit\": {\n      const data = getParamValue(\"tensor\", node, tensorMap, context);\n      context.exitFrame();\n      return [cloneTensor(data)];\n    }\n    case \"NextIteration\": {\n      const data = getParamValue(\"tensor\", node, tensorMap, context);\n      context.nextIteration();\n      return [cloneTensor(data)];\n    }\n    case \"TensorArrayV3\": {\n      const size = getParamValue(\"size\", node, tensorMap, context);\n      const dtype = getParamValue(\"dtype\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const dynamicSize = getParamValue(\"dynamicSize\", node, tensorMap, context);\n      const clearAfterRead = getParamValue(\"clearAfterRead\", node, tensorMap, context);\n      const identicalElementShapes = getParamValue(\"identicalElementShapes\", node, tensorMap, context);\n      const name = getParamValue(\"name\", node, tensorMap, context);\n      const tensorArray = new TensorArray(name, dtype, size, elementShape, identicalElementShapes, dynamicSize, clearAfterRead);\n      context.addTensorArray(tensorArray);\n      return [tensorArray.idTensor, scalar(1)];\n    }\n    case \"TensorArrayWriteV3\": {\n      const id = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const index = getParamValue(\"index\", node, tensorMap, context);\n      const writeTensor = getParamValue(\"tensor\", node, tensorMap, context);\n      const writeTensorArray = context.getTensorArray(id.id);\n      writeTensorArray.write(index, writeTensor);\n      return [writeTensorArray.idTensor];\n    }\n    case \"TensorArrayReadV3\": {\n      const readId = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const readIndex = getParamValue(\"index\", node, tensorMap, context);\n      const readTensorArray = context.getTensorArray(readId.id);\n      return [readTensorArray.read(readIndex)];\n    }\n    case \"TensorArrayGatherV3\": {\n      const gatherId = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const gatherIndices = getParamValue(\"indices\", node, tensorMap, context);\n      const gatherDtype = getParamValue(\"dtype\", node, tensorMap, context);\n      const gatherTensorArray = context.getTensorArray(gatherId.id);\n      return [gatherTensorArray.gather(gatherIndices, gatherDtype)];\n    }\n    case \"TensorArrayScatterV3\": {\n      const scatterId = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const scatterIndices = getParamValue(\"indices\", node, tensorMap, context);\n      const scatterTensor = getParamValue(\"tensor\", node, tensorMap, context);\n      const scatterTensorArray = context.getTensorArray(scatterId.id);\n      scatterTensorArray.scatter(scatterIndices, scatterTensor);\n      return [scatterTensorArray.idTensor];\n    }\n    case \"TensorArrayConcatV3\": {\n      const concatId = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const concatTensorArray = context.getTensorArray(concatId.id);\n      const concatDtype = getParamValue(\"dtype\", node, tensorMap, context);\n      return [concatTensorArray.concat(concatDtype)];\n    }\n    case \"TensorArraySplitV3\": {\n      const splitId = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const splitTensor = getParamValue(\"tensor\", node, tensorMap, context);\n      const lengths = getParamValue(\"lengths\", node, tensorMap, context);\n      const splitTensorArray = context.getTensorArray(splitId.id);\n      splitTensorArray.split(lengths, splitTensor);\n      return [splitTensorArray.idTensor];\n    }\n    case \"TensorArraySizeV3\": {\n      const sizeId = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const sizeTensorArray = context.getTensorArray(sizeId.id);\n      return [scalar(sizeTensorArray.size(), \"int32\")];\n    }\n    case \"TensorArrayCloseV3\": {\n      const closeId = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const closeTensorArray = context.getTensorArray(closeId.id);\n      closeTensorArray.clearAndClose();\n      return [closeTensorArray.idTensor];\n    }\n    case \"TensorListSetItem\": {\n      const idTensor = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const index = getParamValue(\"index\", node, tensorMap, context);\n      const writeTensor = getParamValue(\"tensor\", node, tensorMap, context);\n      const tensorList = context.getTensorList(idTensor.id);\n      tensorList.setItem(index, writeTensor);\n      return [tensorList.idTensor];\n    }\n    case \"TensorListGetItem\": {\n      const idTensor = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const readIndex = getParamValue(\"index\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const elementDType = getParamValue(\"elementDType\", node, tensorMap, context);\n      const tensorList = context.getTensorList(idTensor.id);\n      return [tensorList.getItem(readIndex, elementShape, elementDType)];\n    }\n    case \"TensorListScatterV2\":\n    case \"TensorListScatter\": {\n      const scatterIndices = getParamValue(\"indices\", node, tensorMap, context);\n      const scatterTensor = getParamValue(\"tensor\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const numElements = getParamValue(\"numElements\", node, tensorMap, context);\n      const tensorList = scatter(scatterTensor, scatterIndices, elementShape, numElements);\n      context.addTensorList(tensorList);\n      return [tensorList.idTensor];\n    }\n    case \"TensorListReserve\":\n    case \"EmptyTensorList\": {\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const elementDtype = getParamValue(\"elementDType\", node, tensorMap, context);\n      let numElementsParam;\n      if (node.op === \"TensorListReserve\") {\n        numElementsParam = \"numElements\";\n      } else {\n        numElementsParam = \"maxNumElements\";\n      }\n      const numElements = getParamValue(numElementsParam, node, tensorMap, context);\n      const maxNumElements = node.op === \"TensorListReserve\" ? -1 : numElements;\n      const tensorList = reserve(elementShape, elementDtype, numElements, maxNumElements);\n      context.addTensorList(tensorList);\n      return [tensorList.idTensor];\n    }\n    case \"TensorListGather\": {\n      const gatherId = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const gatherIndices = getParamValue(\"indices\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const elementDtype = getParamValue(\"elementDType\", node, tensorMap, context);\n      const tensorList = context.getTensorList(gatherId.id);\n      return [tensorList.gather(gatherIndices, elementDtype, elementShape)];\n    }\n    case \"TensorListStack\": {\n      const idTensor = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const elementDtype = getParamValue(\"elementDType\", node, tensorMap, context);\n      const numElements = getParamValue(\"numElements\", node, tensorMap, context);\n      const tensorList = context.getTensorList(idTensor.id);\n      return [tensorList.stack(elementShape, elementDtype, numElements)];\n    }\n    case \"TensorListFromTensor\": {\n      const tensor2 = getParamValue(\"tensor\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const elementDtype = getParamValue(\"elementDType\", node, tensorMap, context);\n      const tensorList = fromTensor(tensor2, elementShape, elementDtype);\n      context.addTensorList(tensorList);\n      return [tensorList.idTensor];\n    }\n    case \"TensorListConcat\":\n    case \"TensorListConcatV2\": {\n      const concatId = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const tensorList = context.getTensorList(concatId.id);\n      const concatDtype = getParamValue(\"dtype\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      return [tensorList.concat(concatDtype, elementShape)];\n    }\n    case \"TensorListPushBack\": {\n      const idTensor = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const writeTensor = getParamValue(\"tensor\", node, tensorMap, context);\n      const tensorList = context.getTensorList(idTensor.id);\n      tensorList.pushBack(writeTensor);\n      return [tensorList.idTensor];\n    }\n    case \"TensorListPopBack\": {\n      const idTensor = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const elementDType = getParamValue(\"elementDType\", node, tensorMap, context);\n      const tensorList = context.getTensorList(idTensor.id);\n      return [tensorList.popBack(elementShape, elementDType)];\n    }\n    case \"TensorListSplit\": {\n      const splitTensor = getParamValue(\"tensor\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const lengths = getParamValue(\"lengths\", node, tensorMap, context);\n      const tensorList = split2(splitTensor, lengths, elementShape);\n      context.addTensorList(tensorList);\n      return [tensorList.idTensor];\n    }\n    case \"TensorListLength\": {\n      const idTensor = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const tensorList = context.getTensorList(idTensor.id);\n      return [scalar(tensorList.size(), \"int32\")];\n    }\n    case \"TensorListResize\": {\n      const idTensor = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const size = getParamValue(\"size\", node, tensorMap, context);\n      const srcTensorList = context.getTensorList(idTensor.id);\n      const destTensorList = srcTensorList.resize(size);\n      context.addTensorList(destTensorList);\n      return [destTensorList.idTensor];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/convolution_executor.js\nfunction fusedConvAndDepthWiseParams(node, tensorMap, context) {\n  const [extraOp, activationFunc] = getParamValue(\"fusedOps\", node, tensorMap, context);\n  const isBiasAdd = extraOp === \"biasadd\";\n  const noBiasAdd = !isBiasAdd;\n  const isPrelu = activationFunc === \"prelu\";\n  const isBatchNorm = extraOp === \"fusedbatchnorm\";\n  const numArgs = getParamValue(\"numArgs\", node, tensorMap, context);\n  if (isBiasAdd) {\n    if (isPrelu && numArgs !== 2) {\n      throw new Error(\"FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.\");\n    }\n    if (!isPrelu && isBiasAdd && numArgs !== 1) {\n      throw new Error(\"FusedConv2d and DepthwiseConv2d with BiasAdd must have one extra argument: bias.\");\n    }\n  }\n  if (isBatchNorm) {\n    throw new Error(\"FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported\");\n  }\n  const stride = getParamValue(\"strides\", node, tensorMap, context);\n  const pad3 = getPadding(node, tensorMap, context);\n  const dataFormat = getParamValue(\"dataFormat\", node, tensorMap, context).toUpperCase();\n  const dilations = getParamValue(\"dilations\", node, tensorMap, context);\n  let [biasArg, preluArg] = getParamValue(\"args\", node, tensorMap, context);\n  if (noBiasAdd) {\n    preluArg = biasArg;\n    biasArg = void 0;\n  }\n  const leakyreluAlpha = getParamValue(\"leakyreluAlpha\", node, tensorMap, context);\n  return {\n    stride,\n    pad: pad3,\n    dataFormat,\n    dilations,\n    biasArg,\n    preluArg,\n    activationFunc,\n    leakyreluAlpha\n  };\n}\nvar executeOp4 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"Conv1D\": {\n      const stride = getParamValue(\"stride\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const dataFormat = getParamValue(\"dataFormat\", node, tensorMap, context).toUpperCase();\n      const dilation = getParamValue(\"dilation\", node, tensorMap, context);\n      return [ops.conv1d(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"filter\", node, tensorMap, context), stride, pad3, dataFormat, dilation)];\n    }\n    case \"Conv2D\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getPadding(node, tensorMap, context);\n      const dataFormat = getParamValue(\"dataFormat\", node, tensorMap, context).toUpperCase();\n      const dilations = getParamValue(\"dilations\", node, tensorMap, context);\n      return [ops.conv2d(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"filter\", node, tensorMap, context), [stride[1], stride[2]], pad3, dataFormat, [dilations[1], dilations[2]])];\n    }\n    case \"_FusedConv2D\": {\n      const { stride, pad: pad3, dataFormat, dilations, biasArg, preluArg, activationFunc, leakyreluAlpha } = fusedConvAndDepthWiseParams(node, tensorMap, context);\n      return [ops.fused.conv2d({\n        x: getParamValue(\"x\", node, tensorMap, context),\n        filter: getParamValue(\"filter\", node, tensorMap, context),\n        strides: [stride[1], stride[2]],\n        pad: pad3,\n        dataFormat,\n        dilations: [dilations[1], dilations[2]],\n        bias: biasArg,\n        activation: activationFunc,\n        preluActivationWeights: preluArg,\n        leakyreluAlpha\n      })];\n    }\n    case \"FusedDepthwiseConv2dNative\": {\n      const { stride, pad: pad3, dataFormat, dilations, biasArg, preluArg, activationFunc, leakyreluAlpha } = fusedConvAndDepthWiseParams(node, tensorMap, context);\n      return [ops.fused.depthwiseConv2d({\n        x: getParamValue(\"x\", node, tensorMap, context),\n        filter: getParamValue(\"filter\", node, tensorMap, context),\n        strides: [stride[1], stride[2]],\n        pad: pad3,\n        dataFormat,\n        dilations: [dilations[1], dilations[2]],\n        bias: biasArg,\n        activation: activationFunc,\n        preluActivationWeights: preluArg,\n        leakyreluAlpha\n      })];\n    }\n    case \"Conv2DBackpropInput\":\n    case \"Conv2dTranspose\": {\n      const shape = getParamValue(\"outputShape\", node, tensorMap, context);\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getPadding(node, tensorMap, context);\n      return [ops.conv2dTranspose(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"filter\", node, tensorMap, context), shape, [stride[1], stride[2]], pad3)];\n    }\n    case \"DepthwiseConv2dNative\":\n    case \"DepthwiseConv2d\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getPadding(node, tensorMap, context);\n      const dilations = getParamValue(\"dilations\", node, tensorMap, context);\n      const dataFormat = getParamValue(\"dataFormat\", node, tensorMap, context).toUpperCase();\n      return [ops.depthwiseConv2d(getParamValue(\"input\", node, tensorMap, context), getParamValue(\"filter\", node, tensorMap, context), [stride[1], stride[2]], pad3, dataFormat, [dilations[1], dilations[2]])];\n    }\n    case \"Conv3D\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const dataFormat = getParamValue(\"dataFormat\", node, tensorMap, context).toUpperCase();\n      const dilations = getParamValue(\"dilations\", node, tensorMap, context);\n      return [ops.conv3d(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"filter\", node, tensorMap, context), [stride[1], stride[2], stride[3]], pad3, dataFormat, [dilations[1], dilations[2], dilations[3]])];\n    }\n    case \"AvgPool\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const kernelSize = getParamValue(\"kernelSize\", node, tensorMap, context);\n      return [ops.avgPool(getParamValue(\"x\", node, tensorMap, context), [kernelSize[1], kernelSize[2]], [stride[1], stride[2]], pad3)];\n    }\n    case \"MaxPool\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const kernelSize = getParamValue(\"kernelSize\", node, tensorMap, context);\n      return [ops.maxPool(getParamValue(\"x\", node, tensorMap, context), [kernelSize[1], kernelSize[2]], [stride[1], stride[2]], pad3)];\n    }\n    case \"MaxPoolWithArgmax\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const kernelSize = getParamValue(\"kernelSize\", node, tensorMap, context);\n      const includeBatchInIndex = getParamValue(\"includeBatchInIndex\", node, tensorMap, context);\n      const { result, indexes } = ops.maxPoolWithArgmax(getParamValue(\"x\", node, tensorMap, context), [kernelSize[1], kernelSize[2]], [stride[1], stride[2]], pad3, includeBatchInIndex);\n      return [result, indexes];\n    }\n    case \"AvgPool3D\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const kernelSize = getParamValue(\"kernelSize\", node, tensorMap, context);\n      return [ops.avgPool3d(getParamValue(\"x\", node, tensorMap, context), [kernelSize[1], kernelSize[2], kernelSize[3]], [stride[1], stride[2], stride[3]], pad3)];\n    }\n    case \"MaxPool3D\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const kernelSize = getParamValue(\"kernelSize\", node, tensorMap, context);\n      return [ops.maxPool3d(getParamValue(\"x\", node, tensorMap, context), [kernelSize[1], kernelSize[2], kernelSize[3]], [stride[1], stride[2], stride[3]], pad3)];\n    }\n    case \"Dilation2D\": {\n      const strides = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const dilations = getParamValue(\"dilations\", node, tensorMap, context);\n      const strideHeight = strides[1];\n      const strideWidth = strides[2];\n      const dilationHeight = dilations[1];\n      const dilationWidth = dilations[2];\n      return [ops.dilation2d(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"filter\", node, tensorMap, context), [strideHeight, strideWidth], pad3, [dilationHeight, dilationWidth], \"NHWC\")];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/creation_executor.js\nvar executeOp5 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"Fill\": {\n      const shape = getParamValue(\"shape\", node, tensorMap, context);\n      const dtype = getParamValue(\"dtype\", node, tensorMap, context);\n      const value = getParamValue(\"value\", node, tensorMap, context);\n      return [ops.fill(shape, value, dtype)];\n    }\n    case \"LinSpace\": {\n      const start = getParamValue(\"start\", node, tensorMap, context);\n      const stop = getParamValue(\"stop\", node, tensorMap, context);\n      const num = getParamValue(\"num\", node, tensorMap, context);\n      return [ops.linspace(start, stop, num)];\n    }\n    case \"Multinomial\": {\n      const logits = getParamValue(\"logits\", node, tensorMap, context);\n      const numSamples = getParamValue(\"numSamples\", node, tensorMap, context);\n      const seed = getParamValue(\"seed\", node, tensorMap, context);\n      return [ops.multinomial(logits, numSamples, seed)];\n    }\n    case \"OneHot\": {\n      const indices = getParamValue(\"indices\", node, tensorMap, context);\n      const depth = getParamValue(\"depth\", node, tensorMap, context);\n      const onValue = getParamValue(\"onValue\", node, tensorMap, context);\n      const offValue = getParamValue(\"offValue\", node, tensorMap, context);\n      return [ops.oneHot(indices, depth, onValue, offValue)];\n    }\n    case \"Ones\": {\n      return [ops.ones(getParamValue(\"shape\", node, tensorMap, context), getParamValue(\"dtype\", node, tensorMap, context))];\n    }\n    case \"OnesLike\": {\n      return [ops.onesLike(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"RandomStandardNormal\": {\n      return [ops.randomStandardNormal(getParamValue(\"shape\", node, tensorMap, context), getParamValue(\"dtype\", node, tensorMap, context), getParamValue(\"seed\", node, tensorMap, context))];\n    }\n    case \"RandomUniform\": {\n      return [ops.randomUniform(\n        getParamValue(\"shape\", node, tensorMap, context),\n        getParamValue(\"minval\", node, tensorMap, context),\n        getParamValue(\"maxval\", node, tensorMap, context),\n        getParamValue(\"dtype\", node, tensorMap, context)\n      )];\n    }\n    case \"Range\": {\n      const start = getParamValue(\"start\", node, tensorMap, context);\n      const stop = getParamValue(\"stop\", node, tensorMap, context);\n      const step5 = getParamValue(\"step\", node, tensorMap, context);\n      return [ops.range(start, stop, step5, getParamValue(\"dtype\", node, tensorMap, context))];\n    }\n    case \"TruncatedNormal\": {\n      const shape = getParamValue(\"shape\", node, tensorMap, context);\n      const mean5 = getParamValue(\"mean\", node, tensorMap, context);\n      const stdDev = getParamValue(\"stdDev\", node, tensorMap, context);\n      const seed = getParamValue(\"seed\", node, tensorMap, context);\n      return [ops.truncatedNormal(shape, mean5, stdDev, getParamValue(\"dtype\", node, tensorMap, context), seed)];\n    }\n    case \"Zeros\": {\n      return [ops.zeros(getParamValue(\"shape\", node, tensorMap, context), getParamValue(\"dtype\", node, tensorMap, context))];\n    }\n    case \"ZerosLike\": {\n      return [ops.zerosLike(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/dynamic_executor.js\nfunction nmsParams(node, tensorMap, context) {\n  const boxes = getParamValue(\"boxes\", node, tensorMap, context);\n  const scores = getParamValue(\"scores\", node, tensorMap, context);\n  const maxOutputSize = getParamValue(\"maxOutputSize\", node, tensorMap, context);\n  const iouThreshold = getParamValue(\"iouThreshold\", node, tensorMap, context);\n  const scoreThreshold = getParamValue(\"scoreThreshold\", node, tensorMap, context);\n  const softNmsSigma = getParamValue(\"softNmsSigma\", node, tensorMap, context);\n  return {\n    boxes,\n    scores,\n    maxOutputSize,\n    iouThreshold,\n    scoreThreshold,\n    softNmsSigma\n  };\n}\nvar executeOp6 = async (node, tensorMap, context, resourceManager, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"NonMaxSuppressionV5\": {\n      const { boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma } = nmsParams(node, tensorMap, context);\n      const result = await ops.image.nonMaxSuppressionWithScoreAsync(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma);\n      return [result.selectedIndices, result.selectedScores];\n    }\n    case \"NonMaxSuppressionV4\": {\n      const { boxes, scores, maxOutputSize, iouThreshold, scoreThreshold } = nmsParams(node, tensorMap, context);\n      const padToMaxOutputSize = getParamValue(\"padToMaxOutputSize\", node, tensorMap, context);\n      const result = await ops.image.nonMaxSuppressionPaddedAsync(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize);\n      return [result.selectedIndices, result.validOutputs];\n    }\n    case \"NonMaxSuppressionV3\":\n    case \"NonMaxSuppressionV2\": {\n      const { boxes, scores, maxOutputSize, iouThreshold, scoreThreshold } = nmsParams(node, tensorMap, context);\n      return [await ops.image.nonMaxSuppressionAsync(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold)];\n    }\n    case \"Where\": {\n      const condition = ops.cast(getParamValue(\"condition\", node, tensorMap, context), \"bool\");\n      const result = [await ops.whereAsync(condition)];\n      condition.dispose();\n      return result;\n    }\n    case \"ListDiff\": {\n      return ops.setdiff1dAsync(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"y\", node, tensorMap, context));\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/evaluation_executor.js\nvar executeOp7 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"LowerBound\": {\n      const sortedSequence = getParamValue(\"sortedSequence\", node, tensorMap, context);\n      const values = getParamValue(\"values\", node, tensorMap, context);\n      return [ops.lowerBound(sortedSequence, values)];\n    }\n    case \"TopKV2\": {\n      const x = getParamValue(\"x\", node, tensorMap, context);\n      const k = getParamValue(\"k\", node, tensorMap, context);\n      const sorted = getParamValue(\"sorted\", node, tensorMap, context);\n      const result = ops.topk(x, k, sorted);\n      return [result.values, result.indices];\n    }\n    case \"UpperBound\": {\n      const sortedSequence = getParamValue(\"sortedSequence\", node, tensorMap, context);\n      const values = getParamValue(\"values\", node, tensorMap, context);\n      return [ops.upperBound(sortedSequence, values)];\n    }\n    case \"Unique\": {\n      const x = getParamValue(\"x\", node, tensorMap, context);\n      const result = ops.unique(x);\n      return [result.values, result.indices];\n    }\n    case \"UniqueV2\": {\n      const x = getParamValue(\"x\", node, tensorMap, context);\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const result = ops.unique(x, axis);\n      return [result.values, result.indices];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/graph_executor.js\nvar executeOp8 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"Const\": {\n      return tensorMap[node.name];\n    }\n    case \"PlaceholderWithDefault\":\n      const def = getParamValue(\"default\", node, tensorMap, context);\n      return [getTensor(node.name, tensorMap, context) || def];\n    case \"Placeholder\":\n      return [getTensor(node.name, tensorMap, context)];\n    case \"Identity\":\n    case \"StopGradient\":\n    case \"FakeQuantWithMinMaxVars\": {\n      const data2 = getParamValue(\"x\", node, tensorMap, context);\n      return [cloneTensor(data2)];\n    }\n    case \"IdentityN\":\n      return getParamValue(\"x\", node, tensorMap, context).map((t2) => cloneTensor(t2));\n    case \"Snapshot\":\n      const snapshot = getParamValue(\"x\", node, tensorMap, context);\n      return [cloneTensor(snapshot)];\n    case \"Shape\":\n      return [ops.tensor1d(getParamValue(\"x\", node, tensorMap, context).shape, \"int32\")];\n    case \"ShapeN\":\n      return getParamValue(\"x\", node, tensorMap, context).map((t2) => ops.tensor1d(t2.shape));\n    case \"Size\":\n      return [ops.scalar(getParamValue(\"x\", node, tensorMap, context).size, \"int32\")];\n    case \"Rank\":\n      return [ops.scalar(getParamValue(\"x\", node, tensorMap, context).rank, \"int32\")];\n    case \"NoOp\":\n      return [ops.scalar(1)];\n    case \"Print\":\n      const input2 = getParamValue(\"x\", node, tensorMap, context);\n      const data = getParamValue(\"data\", node, tensorMap, context);\n      const message = getParamValue(\"message\", node, tensorMap, context);\n      const summarize = getParamValue(\"summarize\", node, tensorMap, context);\n      console.warn(\"The graph has a tf.print() operation,usually used for debugging, which slows down performance.\");\n      console.log(message);\n      for (let i2 = 0; i2 < data.length; i2++) {\n        console.log(Array.prototype.slice.call(data[i2].dataSync()).slice(0, summarize));\n      }\n      return [input2];\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/hash_table.js\nvar HashTable = class {\n  constructor(keyDType, valueDType) {\n    this.keyDType = keyDType;\n    this.valueDType = valueDType;\n    this.handle = scalar(0);\n    this.tensorMap = /* @__PURE__ */ new Map();\n    keep(this.handle);\n  }\n  get id() {\n    return this.handle.id;\n  }\n  clearAndClose() {\n    this.tensorMap.forEach((value) => value.dispose());\n    this.tensorMap.clear();\n    this.handle.dispose();\n  }\n  size() {\n    return this.tensorMap.size;\n  }\n  tensorSize() {\n    return scalar(this.size(), \"int32\");\n  }\n  async import(keys, values) {\n    this.checkKeyAndValueTensor(keys, values);\n    const $keys = await keys.data();\n    this.tensorMap.forEach((value) => value.dispose());\n    this.tensorMap.clear();\n    return tidy(() => {\n      const $values = unstack(values);\n      const keysLength = $keys.length;\n      const valuesLength = $values.length;\n      util_exports.assert(keysLength === valuesLength, () => `The number of elements doesn't match, keys has ${keysLength} elements, the values has ${valuesLength} elements.`);\n      for (let i2 = 0; i2 < keysLength; i2++) {\n        const key = $keys[i2];\n        const value = $values[i2];\n        keep(value);\n        this.tensorMap.set(key, value);\n      }\n      return this.handle;\n    });\n  }\n  async find(keys, defaultValue) {\n    this.checkKeyAndValueTensor(keys, defaultValue);\n    const $keys = await keys.data();\n    return tidy(() => {\n      const result = [];\n      for (let i2 = 0; i2 < $keys.length; i2++) {\n        const key = $keys[i2];\n        const value = this.findWithDefault(key, defaultValue);\n        result.push(value);\n      }\n      return stack(result);\n    });\n  }\n  findWithDefault(key, defaultValue) {\n    const result = this.tensorMap.get(key);\n    return result != null ? result : defaultValue;\n  }\n  checkKeyAndValueTensor(key, value) {\n    if (key.dtype !== this.keyDType) {\n      throw new Error(`Expect key dtype ${this.keyDType}, but got ${key.dtype}`);\n    }\n    if (value.dtype !== this.valueDType) {\n      throw new Error(`Expect value dtype ${this.valueDType}, but got ${value.dtype}`);\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/hash_table_executor.js\nvar executeOp9 = async (node, tensorMap, context, resourceManager) => {\n  switch (node.op) {\n    case \"HashTable\":\n    case \"HashTableV2\": {\n      const keyDType = getParamValue(\"keyDType\", node, tensorMap, context);\n      const valueDType = getParamValue(\"valueDType\", node, tensorMap, context);\n      const hashTable = new HashTable(keyDType, valueDType);\n      resourceManager.addHashTable(node.name, hashTable);\n      return [hashTable.handle];\n    }\n    case \"LookupTableImport\":\n    case \"LookupTableImportV2\": {\n      const handle = getParamValue(\"tableHandle\", node, tensorMap, context, resourceManager);\n      const keys = getParamValue(\"keys\", node, tensorMap, context);\n      const values = getParamValue(\"values\", node, tensorMap, context);\n      const hashTable = resourceManager.getHashTableById(handle.id);\n      return [await hashTable.import(keys, values)];\n    }\n    case \"LookupTableFind\":\n    case \"LookupTableFindV2\": {\n      const handle = getParamValue(\"tableHandle\", node, tensorMap, context, resourceManager);\n      const keys = getParamValue(\"keys\", node, tensorMap, context);\n      const defaultValue = getParamValue(\"defaultValue\", node, tensorMap, context);\n      const hashTable = resourceManager.getHashTableById(handle.id);\n      return [await hashTable.find(keys, defaultValue)];\n    }\n    case \"LookupTableSize\":\n    case \"LookupTableSizeV2\": {\n      const handle = getParamValue(\"tableHandle\", node, tensorMap, context, resourceManager);\n      const hashTable = resourceManager.getHashTableById(handle.id);\n      return [hashTable.tensorSize()];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/image_executor.js\nvar executeOp10 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"ResizeBilinear\": {\n      const images = getParamValue(\"images\", node, tensorMap, context);\n      const size = getParamValue(\"size\", node, tensorMap, context);\n      const alignCorners = getParamValue(\"alignCorners\", node, tensorMap, context);\n      const halfPixelCenters = getParamValue(\"halfPixelCenters\", node, tensorMap, context);\n      return [ops.image.resizeBilinear(images, [size[0], size[1]], alignCorners, halfPixelCenters)];\n    }\n    case \"ResizeNearestNeighbor\": {\n      const images = getParamValue(\"images\", node, tensorMap, context);\n      const size = getParamValue(\"size\", node, tensorMap, context);\n      const alignCorners = getParamValue(\"alignCorners\", node, tensorMap, context);\n      const halfPixelCenters = getParamValue(\"halfPixelCenters\", node, tensorMap, context);\n      return [ops.image.resizeNearestNeighbor(images, [size[0], size[1]], alignCorners, halfPixelCenters)];\n    }\n    case \"CropAndResize\": {\n      const image2 = getParamValue(\"image\", node, tensorMap, context);\n      const boxes = getParamValue(\"boxes\", node, tensorMap, context);\n      const boxInd = getParamValue(\"boxInd\", node, tensorMap, context);\n      const cropSize = getParamValue(\"cropSize\", node, tensorMap, context);\n      const method = getParamValue(\"method\", node, tensorMap, context);\n      const extrapolationValue = getParamValue(\"extrapolationValue\", node, tensorMap, context);\n      return [ops.image.cropAndResize(image2, boxes, boxInd, cropSize, method, extrapolationValue)];\n    }\n    case \"ImageProjectiveTransformV3\": {\n      const images = getParamValue(\"images\", node, tensorMap, context);\n      const transforms = getParamValue(\"transforms\", node, tensorMap, context);\n      const outputShape = getParamValue(\"outputShape\", node, tensorMap, context);\n      const fillValue = getParamValue(\"fillValue\", node, tensorMap, context);\n      const interpolation = getParamValue(\"interpolation\", node, tensorMap, context);\n      const fillMode = getParamValue(\"fillMode\", node, tensorMap, context);\n      return [ops.image.transform(images, transforms, interpolation.toLowerCase(), fillMode.toLowerCase(), fillValue, outputShape)];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/logical_executor.js\nvar executeOp11 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"Equal\": {\n      return [ops.equal(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"NotEqual\": {\n      return [ops.notEqual(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"Greater\": {\n      return [ops.greater(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"GreaterEqual\": {\n      return [ops.greaterEqual(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"Less\": {\n      return [ops.less(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"LessEqual\": {\n      return [ops.lessEqual(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"LogicalAnd\": {\n      return [ops.logicalAnd(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"LogicalNot\": {\n      return [ops.logicalNot(getParamValue(\"a\", node, tensorMap, context))];\n    }\n    case \"LogicalOr\": {\n      return [ops.logicalOr(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"Select\":\n    case \"SelectV2\": {\n      return [ops.where(getParamValue(\"condition\", node, tensorMap, context), getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/matrices_executor.js\nvar executeOp12 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"BatchMatMul\":\n    case \"BatchMatMulV2\":\n    case \"MatMul\":\n      return [ops.matMul(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context), getParamValue(\"transposeA\", node, tensorMap, context), getParamValue(\"transposeB\", node, tensorMap, context))];\n    case \"Einsum\":\n      return [ops.einsum(getParamValue(\"equation\", node, tensorMap, context), ...getParamValue(\"tensors\", node, tensorMap, context))];\n    case \"Transpose\":\n      return [ops.transpose(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"perm\", node, tensorMap, context))];\n    case \"_FusedMatMul\":\n      const [extraOp, activationFunc] = getParamValue(\"fusedOps\", node, tensorMap, context);\n      const isBiasAdd = extraOp === \"biasadd\";\n      const isPrelu = activationFunc === \"prelu\";\n      const numArgs = getParamValue(\"numArgs\", node, tensorMap, context);\n      const leakyreluAlpha = getParamValue(\"leakyreluAlpha\", node, tensorMap, context);\n      if (isBiasAdd) {\n        if (isPrelu && numArgs !== 2) {\n          throw new Error(\"Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.\");\n        }\n        if (!isPrelu && numArgs !== 1) {\n          throw new Error(\"Fused MatMul with BiasAdd must have one extra argument: bias.\");\n        }\n      }\n      const [biasArg, preluArg] = getParamValue(\"args\", node, tensorMap, context);\n      return [ops.fused.matMul({\n        a: getParamValue(\"a\", node, tensorMap, context),\n        b: getParamValue(\"b\", node, tensorMap, context),\n        transposeA: getParamValue(\"transposeA\", node, tensorMap, context),\n        transposeB: getParamValue(\"transposeB\", node, tensorMap, context),\n        bias: biasArg,\n        activation: activationFunc,\n        preluActivationWeights: preluArg,\n        leakyreluAlpha\n      })];\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/normalization_executor.js\nvar executeOp13 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"EuclideanNorm\":\n      return [ops.euclideanNorm(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"axis\", node, tensorMap, context), getParamValue(\"keepDims\", node, tensorMap, context))];\n    case \"FusedBatchNorm\":\n    case \"FusedBatchNormV2\": {\n      return [ops.batchNorm(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"mean\", node, tensorMap, context), getParamValue(\"variance\", node, tensorMap, context), getParamValue(\"offset\", node, tensorMap, context), getParamValue(\"scale\", node, tensorMap, context), getParamValue(\"epsilon\", node, tensorMap, context))];\n    }\n    case \"FusedBatchNormV3\": {\n      return [ops.batchNorm(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"mean\", node, tensorMap, context), getParamValue(\"variance\", node, tensorMap, context), getParamValue(\"offset\", node, tensorMap, context), getParamValue(\"scale\", node, tensorMap, context), getParamValue(\"epsilon\", node, tensorMap, context))];\n    }\n    case \"LRN\": {\n      return [ops.localResponseNormalization(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"radius\", node, tensorMap, context), getParamValue(\"bias\", node, tensorMap, context), getParamValue(\"alpha\", node, tensorMap, context), getParamValue(\"beta\", node, tensorMap, context))];\n    }\n    case \"Softmax\": {\n      return [ops.softmax(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"LogSoftmax\": {\n      return [ops.logSoftmax(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"SparseToDense\": {\n      return [ops.sparseToDense(getParamValue(\"sparseIndices\", node, tensorMap, context), getParamValue(\"outputShape\", node, tensorMap, context), getParamValue(\"sparseValues\", node, tensorMap, context), getParamValue(\"defaultValue\", node, tensorMap, context))];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/reduction_executor.js\nvar executeOp14 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"Max\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const keepDims = getParamValue(\"keepDims\", node, tensorMap, context);\n      return [ops.max(getParamValue(\"x\", node, tensorMap, context), axis, keepDims)];\n    }\n    case \"Mean\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const keepDims = getParamValue(\"keepDims\", node, tensorMap, context);\n      return [ops.mean(getParamValue(\"x\", node, tensorMap, context), axis, keepDims)];\n    }\n    case \"Min\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const keepDims = getParamValue(\"keepDims\", node, tensorMap, context);\n      return [ops.min(getParamValue(\"x\", node, tensorMap, context), axis, keepDims)];\n    }\n    case \"Sum\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const keepDims = getParamValue(\"keepDims\", node, tensorMap, context);\n      return [ops.sum(getParamValue(\"x\", node, tensorMap, context), axis, keepDims)];\n    }\n    case \"All\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const keepDims = getParamValue(\"keepDims\", node, tensorMap, context);\n      return [ops.all(getParamValue(\"x\", node, tensorMap, context), axis, keepDims)];\n    }\n    case \"Any\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const keepDims = getParamValue(\"keepDims\", node, tensorMap, context);\n      return [ops.any(getParamValue(\"x\", node, tensorMap, context), axis, keepDims)];\n    }\n    case \"ArgMax\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      return [ops.argMax(getParamValue(\"x\", node, tensorMap, context), axis)];\n    }\n    case \"ArgMin\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      return [ops.argMin(getParamValue(\"x\", node, tensorMap, context), axis)];\n    }\n    case \"Prod\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const keepDims = getParamValue(\"keepDims\", node, tensorMap, context);\n      return [ops.prod(getParamValue(\"x\", node, tensorMap, context), axis, keepDims)];\n    }\n    case \"Cumprod\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const exclusive = getParamValue(\"exclusive\", node, tensorMap, context);\n      const reverse5 = getParamValue(\"reverse\", node, tensorMap, context);\n      return [ops.cumprod(getParamValue(\"x\", node, tensorMap, context), axis, exclusive, reverse5)];\n    }\n    case \"Cumsum\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const exclusive = getParamValue(\"exclusive\", node, tensorMap, context);\n      const reverse5 = getParamValue(\"reverse\", node, tensorMap, context);\n      return [ops.cumsum(getParamValue(\"x\", node, tensorMap, context), axis, exclusive, reverse5)];\n    }\n    case \"Bincount\":\n      const x = getParamValue(\"x\", node, tensorMap, context);\n      const weights = getParamValue(\"weights\", node, tensorMap, context);\n      const size = getParamValue(\"size\", node, tensorMap, context);\n      return [ops.bincount(x, weights, size)];\n    case \"DenseBincount\": {\n      const x2 = getParamValue(\"x\", node, tensorMap, context);\n      const weights2 = getParamValue(\"weights\", node, tensorMap, context);\n      const size2 = getParamValue(\"size\", node, tensorMap, context);\n      const binaryOutput = getParamValue(\"binaryOutput\", node, tensorMap, context);\n      return [ops.denseBincount(x2, weights2, size2, binaryOutput)];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/slice_join_executor.js\nvar executeOp15 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"ConcatV2\":\n    case \"Concat\": {\n      const n2 = getParamValue(\"n\", node, tensorMap, context);\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      let inputs = getParamValue(\"tensors\", node, tensorMap, context);\n      inputs = inputs.slice(0, n2);\n      return [ops.concat(inputs, axis)];\n    }\n    case \"Gather\": {\n      const input2 = getParamValue(\"x\", node, tensorMap, context);\n      const indices = getParamValue(\"indices\", node, tensorMap, context);\n      return [ops.gather(input2, ops.cast(indices, \"int32\"), 0)];\n    }\n    case \"GatherV2\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const batchDims = getParamValue(\"batchDims\", node, tensorMap, context);\n      const input2 = getParamValue(\"x\", node, tensorMap, context);\n      const indices = getParamValue(\"indices\", node, tensorMap, context);\n      return [ops.gather(input2, ops.cast(indices, \"int32\"), axis, batchDims)];\n    }\n    case \"Reverse\": {\n      const dims = getParamValue(\"dims\", node, tensorMap, context);\n      const axis = [];\n      for (let i2 = 0; i2 < dims.length; i2++) {\n        if (dims[i2]) {\n          axis.push(i2);\n        }\n      }\n      const input2 = getParamValue(\"x\", node, tensorMap, context);\n      return [ops.reverse(input2, axis)];\n    }\n    case \"ReverseV2\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const input2 = getParamValue(\"x\", node, tensorMap, context);\n      return [ops.reverse(input2, axis)];\n    }\n    case \"Slice\": {\n      const begin = getParamValue(\"begin\", node, tensorMap, context);\n      const size = getParamValue(\"size\", node, tensorMap, context);\n      return [ops.slice(getParamValue(\"x\", node, tensorMap, context), begin, size)];\n    }\n    case \"StridedSlice\": {\n      const begin = getParamValue(\"begin\", node, tensorMap, context);\n      const end = getParamValue(\"end\", node, tensorMap, context);\n      const strides = getParamValue(\"strides\", node, tensorMap, context);\n      const beginMask = getParamValue(\"beginMask\", node, tensorMap, context);\n      const endMask = getParamValue(\"endMask\", node, tensorMap, context);\n      const ellipsisMask = getParamValue(\"ellipsisMask\", node, tensorMap, context);\n      const newAxisMask = getParamValue(\"newAxisMask\", node, tensorMap, context);\n      const shrinkAxisMask = getParamValue(\"shrinkAxisMask\", node, tensorMap, context);\n      const tensor2 = getParamValue(\"x\", node, tensorMap, context);\n      return [ops.stridedSlice(tensor2, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask)];\n    }\n    case \"Pack\": {\n      return tidy(() => {\n        const axis = getParamValue(\"axis\", node, tensorMap, context);\n        const tensors = getParamValue(\"tensors\", node, tensorMap, context);\n        const shape = tensors[0].shape;\n        const squeezedShape = ops.squeeze(tensors[0]).shape;\n        const mapped = tensors.map((tensor2) => {\n          const sameShape = util_exports.arraysEqual(tensor2.shape, shape);\n          if (!sameShape && !util_exports.arraysEqual(ops.squeeze(tensor2).shape, squeezedShape)) {\n            throw new Error(\"the input tensors shape does not match\");\n          }\n          return sameShape ? tensor2 : ops.reshape(tensor2, shape);\n        });\n        return [ops.stack(mapped, axis)];\n      });\n    }\n    case \"Unpack\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const tensor2 = getParamValue(\"tensor\", node, tensorMap, context);\n      return ops.unstack(tensor2, axis);\n    }\n    case \"Tile\": {\n      const reps = getParamValue(\"reps\", node, tensorMap, context);\n      return [ops.tile(getParamValue(\"x\", node, tensorMap, context), reps)];\n    }\n    case \"Split\":\n    case \"SplitV\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const numOrSizeSplits = getParamValue(\"numOrSizeSplits\", node, tensorMap, context);\n      const tensor2 = getParamValue(\"x\", node, tensorMap, context);\n      return ops.split(tensor2, numOrSizeSplits, axis);\n    }\n    case \"ScatterNd\": {\n      const indices = getParamValue(\"indices\", node, tensorMap, context);\n      const values = getParamValue(\"values\", node, tensorMap, context);\n      const shape = getParamValue(\"shape\", node, tensorMap, context);\n      return [ops.scatterND(indices, values, shape)];\n    }\n    case \"GatherNd\": {\n      const x = getParamValue(\"x\", node, tensorMap, context);\n      const indices = getParamValue(\"indices\", node, tensorMap, context);\n      return [ops.gatherND(x, indices)];\n    }\n    case \"SparseToDense\": {\n      const indices = getParamValue(\"sparseIndices\", node, tensorMap, context);\n      const shape = getParamValue(\"outputShape\", node, tensorMap, context);\n      const sparseValues = getParamValue(\"sparseValues\", node, tensorMap, context);\n      const defaultValue = getParamValue(\"defaultValue\", node, tensorMap, context);\n      return [ops.sparseToDense(indices, sparseValues, shape, sparseValues.dtype === defaultValue.dtype ? defaultValue : ops.cast(defaultValue, sparseValues.dtype))];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/sparse_executor.js\nvar executeOp16 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"SparseFillEmptyRows\": {\n      const { outputIndices, outputValues, emptyRowIndicator, reverseIndexMap } = ops.sparse.sparseFillEmptyRows(getParamValue(\"indices\", node, tensorMap, context), getParamValue(\"values\", node, tensorMap, context), getParamValue(\"denseShape\", node, tensorMap, context), getParamValue(\"defaultValue\", node, tensorMap, context));\n      return [\n        outputIndices,\n        outputValues,\n        emptyRowIndicator,\n        reverseIndexMap\n      ];\n    }\n    case \"SparseReshape\": {\n      const { outputIndices, outputShape } = ops.sparse.sparseReshape(getParamValue(\"inputIndices\", node, tensorMap, context), getParamValue(\"inputShape\", node, tensorMap, context), getParamValue(\"newShape\", node, tensorMap, context));\n      return [outputIndices, outputShape];\n    }\n    case \"SparseSegmentMean\": {\n      const outputData = ops.sparse.sparseSegmentMean(getParamValue(\"data\", node, tensorMap, context), getParamValue(\"indices\", node, tensorMap, context), getParamValue(\"segmentIds\", node, tensorMap, context));\n      return [outputData];\n    }\n    case \"SparseSegmentSum\": {\n      const outputData = ops.sparse.sparseSegmentSum(getParamValue(\"data\", node, tensorMap, context), getParamValue(\"indices\", node, tensorMap, context), getParamValue(\"segmentIds\", node, tensorMap, context));\n      return [outputData];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/spectral_executor.js\nvar executeOp17 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"FFT\": {\n      return [ops.fft(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"IFFT\": {\n      return [ops.ifft(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"RFFT\": {\n      return [ops.rfft(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"IRFFT\": {\n      return [ops.irfft(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/string_executor.js\nvar executeOp18 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"StringNGrams\": {\n      const { nGrams, nGramsSplits } = ops.string.stringNGrams(getParamValue(\"data\", node, tensorMap, context), getParamValue(\"dataSplits\", node, tensorMap, context), getParamValue(\"separator\", node, tensorMap, context), getParamValue(\"nGramWidths\", node, tensorMap, context), getParamValue(\"leftPad\", node, tensorMap, context), getParamValue(\"rightPad\", node, tensorMap, context), getParamValue(\"padWidth\", node, tensorMap, context), getParamValue(\"preserveShortSequences\", node, tensorMap, context));\n      return [nGrams, nGramsSplits];\n    }\n    case \"StringSplit\": {\n      const { indices, values, shape } = ops.string.stringSplit(getParamValue(\"input\", node, tensorMap, context), getParamValue(\"delimiter\", node, tensorMap, context), getParamValue(\"skipEmpty\", node, tensorMap, context));\n      return [indices, values, shape];\n    }\n    case \"StringToHashBucketFast\": {\n      const output = ops.string.stringToHashBucketFast(getParamValue(\"input\", node, tensorMap, context), getParamValue(\"numBuckets\", node, tensorMap, context));\n      return [output];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/transformation_executor.js\nvar executeOp19 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"Cast\": {\n      return [ops.cast(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"dtype\", node, tensorMap, context))];\n    }\n    case \"ExpandDims\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      return [ops.expandDims(getParamValue(\"x\", node, tensorMap, context), axis)];\n    }\n    case \"Squeeze\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      return [ops.squeeze(getParamValue(\"x\", node, tensorMap, context), axis)];\n    }\n    case \"Reshape\": {\n      return [ops.reshape(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"shape\", node, tensorMap, context))];\n    }\n    case \"MirrorPad\": {\n      return [ops.mirrorPad(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"padding\", node, tensorMap, context), getParamValue(\"mode\", node, tensorMap, context))];\n    }\n    case \"PadV2\":\n    case \"Pad\": {\n      return [ops.pad(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"padding\", node, tensorMap, context), getParamValue(\"constantValue\", node, tensorMap, context))];\n    }\n    case \"SpaceToBatchND\": {\n      const blockShape = getParamValue(\"blockShape\", node, tensorMap, context);\n      const paddings = getParamValue(\"paddings\", node, tensorMap, context);\n      return [ops.spaceToBatchND(getParamValue(\"x\", node, tensorMap, context), blockShape, paddings)];\n    }\n    case \"BatchToSpaceND\": {\n      const blockShape = getParamValue(\"blockShape\", node, tensorMap, context);\n      const crops = getParamValue(\"crops\", node, tensorMap, context);\n      return [ops.batchToSpaceND(getParamValue(\"x\", node, tensorMap, context), blockShape, crops)];\n    }\n    case \"DepthToSpace\": {\n      const blockSize = getParamValue(\"blockSize\", node, tensorMap, context);\n      const dataFormat = getParamValue(\"dataFormat\", node, tensorMap, context).toUpperCase();\n      return [ops.depthToSpace(getParamValue(\"x\", node, tensorMap, context), blockSize, dataFormat)];\n    }\n    case \"BroadcastTo\": {\n      return [ops.broadcastTo(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"shape\", node, tensorMap, context))];\n    }\n    case \"BroadcastArgs\": {\n      return [ops.broadcastArgs(getParamValue(\"s0\", node, tensorMap, context), getParamValue(\"s1\", node, tensorMap, context))];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/operation_executor.js\nfunction executeOp20(node, tensorMap, context, resourceManager, tidy2 = tidy) {\n  const value = ((node2, tensorMap2, context2) => {\n    switch (node2.category) {\n      case \"arithmetic\":\n        return tidy2(() => executeOp(node2, tensorMap2, context2));\n      case \"basic_math\":\n        return tidy2(() => executeOp2(node2, tensorMap2, context2));\n      case \"control\":\n        return executeOp3(node2, tensorMap2, context2);\n      case \"convolution\":\n        return tidy2(() => executeOp4(node2, tensorMap2, context2));\n      case \"creation\":\n        return tidy2(() => executeOp5(node2, tensorMap2, context2));\n      case \"dynamic\":\n        return executeOp6(node2, tensorMap2, context2);\n      case \"evaluation\":\n        return tidy2(() => executeOp7(node2, tensorMap2, context2));\n      case \"image\":\n        return tidy2(() => executeOp10(node2, tensorMap2, context2));\n      case \"graph\":\n        return tidy2(() => executeOp8(node2, tensorMap2, context2));\n      case \"logical\":\n        return tidy2(() => executeOp11(node2, tensorMap2, context2));\n      case \"matrices\":\n        return tidy2(() => executeOp12(node2, tensorMap2, context2));\n      case \"normalization\":\n        return tidy2(() => executeOp13(node2, tensorMap2, context2));\n      case \"reduction\":\n        return tidy2(() => executeOp14(node2, tensorMap2, context2));\n      case \"slice_join\":\n        return tidy2(() => executeOp15(node2, tensorMap2, context2));\n      case \"sparse\":\n        return tidy2(() => executeOp16(node2, tensorMap2, context2));\n      case \"spectral\":\n        return tidy2(() => executeOp17(node2, tensorMap2, context2));\n      case \"string\":\n        return tidy2(() => executeOp18(node2, tensorMap2, context2));\n      case \"transformation\":\n        return tidy2(() => executeOp19(node2, tensorMap2, context2));\n      case \"hash_table\":\n        return executeOp9(node2, tensorMap2, context2, resourceManager);\n      case \"custom\":\n        const opMapper = getRegisteredOp(node2.op);\n        if (opMapper && opMapper.customExecutor) {\n          return opMapper.customExecutor(new NodeValueImpl(node2, tensorMap2, context2));\n        } else {\n          throw TypeError(`Custom op ${node2.op} is not registered.`);\n        }\n      default:\n        throw TypeError(`Unknown op '${node2.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`);\n    }\n  })(node, tensorMap, context);\n  if (util_exports.isPromise(value)) {\n    return value.then((data) => [].concat(data));\n  }\n  return [].concat(value);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/execution_context.js\nvar ExecutionContext = class {\n  constructor(weightMap = {}, tensorArrayMap = {}, tensorListMap = {}, functionMap = {}) {\n    this.weightMap = weightMap;\n    this.tensorArrayMap = tensorArrayMap;\n    this.tensorListMap = tensorListMap;\n    this.functionMap = functionMap;\n    this.rootContext = { id: 0, frameName: \"\", iterationId: 0 };\n    this.contexts = [this.rootContext];\n    this.lastId = 0;\n    this.generateCurrentContextIds();\n  }\n  newFrame(id, frameName) {\n    return { id, frameName, iterationId: 0 };\n  }\n  set currentContext(contexts2) {\n    if (this.contexts !== contexts2) {\n      this.contexts = contexts2;\n      this.generateCurrentContextIds();\n    }\n  }\n  get currentContext() {\n    return this.contexts;\n  }\n  get currentContextId() {\n    return this._currentContextIds[0];\n  }\n  get currentContextIds() {\n    return this._currentContextIds;\n  }\n  generateCurrentContextIds() {\n    const names = [];\n    for (let i2 = 0; i2 < this.contexts.length - 1; i2++) {\n      const contexts2 = this.contexts.slice(0, this.contexts.length - i2);\n      names.push(this.contextIdforContexts(contexts2));\n    }\n    names.push(\"\");\n    this._currentContextIds = names;\n  }\n  contextIdforContexts(contexts2) {\n    return contexts2 ? contexts2.map((context) => context.id === 0 && context.iterationId === 0 ? \"\" : `${context.frameName}-${context.iterationId}`).join(\"/\") : \"\";\n  }\n  enterFrame(frameId) {\n    if (this.contexts) {\n      this.lastId++;\n      this.contexts = this.contexts.slice();\n      this.contexts.push(this.newFrame(this.lastId, frameId));\n      this._currentContextIds.unshift(this.contextIdforContexts(this.contexts));\n    }\n  }\n  exitFrame() {\n    if (this.contexts && this.contexts.length > 1) {\n      this.contexts = this.contexts.slice();\n      this.contexts.splice(-1);\n      this.currentContextIds.shift();\n    } else {\n      throw new Error(\"Cannot exit frame, the context is empty\");\n    }\n  }\n  nextIteration() {\n    if (this.contexts && this.contexts.length > 0) {\n      this.contexts = this.contexts.slice();\n      this.lastId++;\n      const context = Object.assign({}, this.contexts[this.contexts.length - 1]);\n      context.iterationId += 1;\n      context.id = this.lastId;\n      this.contexts.splice(-1, 1, context);\n      this._currentContextIds.splice(0, 1, this.contextIdforContexts(this.contexts));\n    } else {\n      throw new Error(\"Cannot increase frame iteration, the context is empty\");\n    }\n  }\n  getWeight(name) {\n    return this.weightMap[name];\n  }\n  addTensorArray(tensorArray) {\n    this.tensorArrayMap[tensorArray.id] = tensorArray;\n  }\n  getTensorArray(id) {\n    return this.tensorArrayMap[id];\n  }\n  addTensorList(tensorList) {\n    this.tensorListMap[tensorList.id] = tensorList;\n  }\n  getTensorList(id) {\n    return this.tensorListMap[id];\n  }\n  dispose(keepIds) {\n    for (const key in this.tensorArrayMap) {\n      this.tensorArrayMap[key].clearAndClose(keepIds);\n    }\n    for (const key in this.tensorListMap) {\n      this.tensorListMap[key].clearAndClose(keepIds);\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/model_analysis.js\nfunction getExecutionSubgraph(inputs, outputs, weightMap, initNodes) {\n  const usedNodes = /* @__PURE__ */ new Set();\n  const missingInputs = [];\n  let dynamicNode = null;\n  let syncInputs = null;\n  const seen = /* @__PURE__ */ new Set();\n  const inputNodeNames = Object.keys(inputs).map((name) => parseNodeName(name)[0]);\n  let initNodeNames = [];\n  if (initNodes != null) {\n    initNodeNames = initNodes.map((node) => parseNodeName(node.name)[0]);\n  }\n  const frontier = [...outputs];\n  while (frontier.length > 0) {\n    const node = frontier.pop();\n    if (isControlFlow(node) || isDynamicShape(node) || isHashTable(node)) {\n      if (dynamicNode == null) {\n        dynamicNode = node;\n        syncInputs = dynamicNode.children.map((child) => child.name).filter((name) => usedNodes.has(name));\n      }\n    }\n    usedNodes.add(node.name);\n    if (weightMap[node.name] != null) {\n      continue;\n    }\n    if (inputNodeNames.indexOf(node.name) !== -1) {\n      continue;\n    }\n    if (initNodeNames.indexOf(node.name) !== -1) {\n      continue;\n    }\n    if (node.inputs.length === 0) {\n      missingInputs.push(node.name);\n      continue;\n    }\n    node.inputs.forEach((input2) => {\n      if (seen.has(input2.name)) {\n        return;\n      }\n      seen.add(input2.name);\n      frontier.push(input2);\n    });\n  }\n  return { inputs, outputs, usedNodes, missingInputs, dynamicNode, syncInputs };\n}\nfunction getNodesInTopologicalOrder(graph, weightMap, executionInfo) {\n  const { usedNodes, inputs } = executionInfo;\n  const frontier = [];\n  const inputNodes = Object.keys(inputs).map((name) => parseNodeName(name)[0]).map((name) => graph.nodes[name]);\n  const initNodes = graph.initNodes;\n  inputNodes.forEach((input2) => {\n    if (usedNodes.has(input2.name)) {\n      frontier.push(input2);\n    }\n  });\n  graph.weights.forEach((weight) => {\n    if (usedNodes.has(weight.name)) {\n      frontier.push(weight);\n    }\n  });\n  if (initNodes != null) {\n    initNodes.forEach((node) => {\n      if (usedNodes.has(node.name)) {\n        frontier.push(node);\n      }\n    });\n  }\n  const seen = /* @__PURE__ */ new Set();\n  const orderedNodes = [];\n  while (frontier.length > 0) {\n    const node = frontier.pop();\n    seen.add(node.name);\n    if (!weightMap[node.name]) {\n      orderedNodes.push(node);\n    }\n    node.children.forEach((child) => {\n      if (!seen.has(child.name) && usedNodes.has(child.name) && child.inputs.every((input2) => seen.has(input2.name))) {\n        frontier.push(child);\n      }\n    });\n  }\n  return orderedNodes;\n}\nvar CONTROL_FLOW_OPS = [\n  \"Switch\",\n  \"Merge\",\n  \"Enter\",\n  \"Exit\",\n  \"NextIteration\",\n  \"StatelessIf\",\n  \"StatelessWhile\",\n  \"if\",\n  \"While\"\n];\nvar DYNAMIC_SHAPE_OPS = [\n  \"NonMaxSuppressionV2\",\n  \"NonMaxSuppressionV3\",\n  \"NonMaxSuppressionV5\",\n  \"Where\"\n];\nvar HASH_TABLE_OPS = [\n  \"HashTable\",\n  \"HashTableV2\",\n  \"LookupTableImport\",\n  \"LookupTableImportV2\",\n  \"LookupTableFind\",\n  \"LookupTableFindV2\",\n  \"LookupTableSize\",\n  \"LookupTableSizeV2\"\n];\nfunction isControlFlow(node) {\n  return CONTROL_FLOW_OPS.indexOf(node.op) >= 0;\n}\nfunction isDynamicShape(node) {\n  return DYNAMIC_SHAPE_OPS.indexOf(node.op) >= 0;\n}\nfunction isHashTable(node) {\n  return HASH_TABLE_OPS.indexOf(node.op) >= 0;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/graph_executor.js\nvar GraphExecutor = class {\n  constructor(graph, parent) {\n    this.graph = graph;\n    this.parent = parent;\n    this.compiledMap = /* @__PURE__ */ new Map();\n    this._weightMap = {};\n    this.SEPERATOR = \",\";\n    this._functions = {};\n    this._functionExecutorMap = {};\n    this.intermediateTensors = {};\n    this.keepTensorForDebug = false;\n    this._outputs = graph.outputs;\n    this._inputs = graph.inputs;\n    this._initNodes = graph.initNodes;\n    this._signature = graph.signature;\n    this._functions = graph.functions;\n    if (graph.functions != null) {\n      Object.keys(graph.functions).forEach((name) => {\n        this._functionExecutorMap[name] = new GraphExecutor(graph.functions[name], this);\n      });\n    }\n  }\n  get weightIds() {\n    return this.parent ? this.parent.weightIds : this._weightIds;\n  }\n  get functionExecutorMap() {\n    return this.parent ? this.parent.functionExecutorMap : this._functionExecutorMap;\n  }\n  get weightMap() {\n    return this.parent ? this.parent.weightMap : this._weightMap;\n  }\n  set weightMap(weightMap) {\n    const weightIds = Object.keys(weightMap).map((key) => weightMap[key].map((tensor2) => tensor2.id));\n    this._weightIds = [].concat(...weightIds);\n    this._weightMap = weightMap;\n  }\n  set resourceManager(resourceManager) {\n    this._resourceManager = resourceManager;\n  }\n  get inputs() {\n    return this._inputs.map((node) => {\n      return {\n        name: node.name,\n        shape: node.attrParams[\"shape\"] ? node.attrParams[\"shape\"].value : void 0,\n        dtype: node.attrParams[\"dtype\"] ? node.attrParams[\"dtype\"].value : void 0\n      };\n    });\n  }\n  get outputs() {\n    return this._outputs.map((node) => {\n      return {\n        name: node.name,\n        shape: node.attrParams[\"shape\"] ? node.attrParams[\"shape\"].value : void 0,\n        dtype: node.attrParams[\"dtype\"] ? node.attrParams[\"dtype\"].value : void 0\n      };\n    });\n  }\n  get inputNodes() {\n    return this._inputs.map((node) => node.signatureKey || node.name);\n  }\n  get outputNodes() {\n    return this._outputs.map((node) => {\n      const name = node.signatureKey || node.name;\n      return node.defaultOutput ? `${name}:${node.defaultOutput}` : name;\n    });\n  }\n  get functions() {\n    return Object.keys(this._functions).reduce((map, key) => {\n      map[key] = this._functions[key].signature;\n      return map;\n    }, {});\n  }\n  getCompilationKey(inputs, outputs) {\n    const sortedInputs = inputs.map((node) => node.name).sort();\n    const sortedOutputs = outputs.map((node) => node.name).sort();\n    return sortedInputs.join(this.SEPERATOR) + \"--\" + sortedOutputs.join(this.SEPERATOR);\n  }\n  compile(inputs, outputs) {\n    const executionInfo = getExecutionSubgraph(inputs, outputs, this.weightMap, this._initNodes);\n    const { missingInputs, dynamicNode, syncInputs } = executionInfo;\n    if (dynamicNode != null) {\n      throw new Error(`This execution contains the node '${dynamicNode.name}', which has the dynamic op '${dynamicNode.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${syncInputs}]`);\n    }\n    if (missingInputs.length > 0) {\n      const outNames = outputs.map((n2) => n2.name);\n      const inNames = Object.keys(inputs);\n      throw new Error(`Cannot compute the outputs [${outNames}] from the provided inputs [${inNames}]. Missing the following inputs: [${missingInputs}]`);\n    }\n    return getNodesInTopologicalOrder(this.graph, this.weightMap, executionInfo);\n  }\n  execute(inputs, outputs) {\n    inputs = this.mapInputs(inputs);\n    const names = Object.keys(inputs).sort();\n    this.checkInputs(inputs);\n    this.checkInputShapeAndType(inputs);\n    outputs = this.mapOutputs(outputs);\n    this.checkOutputs(outputs);\n    const inputNodes = names.map((name) => this.graph.nodes[parseNodeName(name)[0]]);\n    const outputNodeNames = outputs.map((name) => parseNodeName(name)[0]);\n    let outputNodes = outputNodeNames.map((name) => this.graph.nodes[name]);\n    this.resetIntermediateTensors();\n    if (outputNodes.length === 0) {\n      outputNodes = this._outputs;\n    }\n    const compilationKey = this.getCompilationKey(inputNodes, outputNodes);\n    let orderedNodes = this.compiledMap.get(compilationKey);\n    if (orderedNodes == null) {\n      orderedNodes = this.compile(inputs, outputNodes);\n      this.compiledMap.set(compilationKey, orderedNodes);\n    }\n    const tensorArrayMap = {};\n    const tensorListMap = {};\n    return tidy(() => {\n      const context = new ExecutionContext(this.weightMap, tensorArrayMap, tensorListMap, this.functionExecutorMap);\n      const tensorsMap = Object.assign({}, this.weightMap);\n      Object.keys(inputs).forEach((name) => {\n        const [nodeName, index] = parseNodeName(name);\n        const tensors = [];\n        tensors[index] = inputs[name];\n        tensorsMap[nodeName] = tensors;\n      });\n      const tensorsToKeep = this.getFrozenTensorIds(tensorsMap);\n      const intermediateTensorConsumerCount = {};\n      for (let i2 = 0; i2 < orderedNodes.length; i2++) {\n        const node = orderedNodes[i2];\n        if (!tensorsMap[node.name]) {\n          const tensors = executeOp20(node, tensorsMap, context, this._resourceManager);\n          if (util_exports.isPromise(tensors)) {\n            throw new Error(`The execution of the op '${node.op}' returned a promise. Please use model.executeAsync() instead.`);\n          }\n          tensorsMap[node.name] = tensors;\n          this.checkTensorForDisposal(node.name, node, tensorsMap, context, tensorsToKeep, outputNodeNames, intermediateTensorConsumerCount);\n        }\n      }\n      if (this.parent == null) {\n        context.dispose(tensorsToKeep);\n      }\n      return outputs.map((name) => getTensor(name, tensorsMap, context));\n    });\n  }\n  getFrozenTensorIds(tensorMap) {\n    const ids = [].concat.apply([], Object.keys(tensorMap).map((key) => tensorMap[key]).map((tensors) => tensors.map((tensor2) => tensor2.id)));\n    return new Set(ids);\n  }\n  checkTensorForDisposal(nodeName, node, tensorMap, context, tensorsToKeep, outputNames, intermediateTensorConsumerCount) {\n    if (node.category === \"control\" || outputNames.indexOf(nodeName) !== -1) {\n      return;\n    }\n    tensorMap[nodeName].forEach((tensor2) => {\n      if (tensor2 != null) {\n        intermediateTensorConsumerCount[tensor2.id] = (intermediateTensorConsumerCount[tensor2.id] || 0) + node.children.length;\n      }\n    });\n    node.inputs.forEach((input2) => {\n      if (input2.category !== \"control\") {\n        const tensors = getTensorsForCurrentContenxt(input2.name, tensorMap, context);\n        if (tensors != null) {\n          tensors.forEach((tensor2) => {\n            if (tensor2 && !tensor2.kept && !tensorsToKeep.has(tensor2.id)) {\n              const count2 = intermediateTensorConsumerCount[tensor2.id];\n              if (count2 === 1) {\n                if (!this.keepTensorForDebug) {\n                  tensor2.dispose();\n                } else {\n                  const [nodeName2, index] = getNodeNameAndIndex(node.name, context);\n                  if (this.intermediateTensors[nodeName2]) {\n                    this.intermediateTensors[nodeName2][index] = tensor2;\n                  } else {\n                    this.intermediateTensors[nodeName2] = [];\n                    this.intermediateTensors[nodeName2][index] = tensor2;\n                  }\n                }\n                delete intermediateTensorConsumerCount[tensor2.id];\n              } else if (count2 != null) {\n                intermediateTensorConsumerCount[tensor2.id]--;\n              }\n            }\n          });\n        }\n      }\n    });\n  }\n  async executeAsync(inputs, outputs) {\n    return this._executeAsync(inputs, outputs);\n  }\n  disposeIntermediateTensors() {\n    if (!this.intermediateTensors) {\n      return;\n    }\n    Object.keys(this.intermediateTensors).forEach((key) => this.intermediateTensors[key].forEach((tensor2) => tensor2.dispose()));\n    this.disposeTensorsMap();\n  }\n  disposeTensorsMap() {\n    if (!this.tensorsMap) {\n      return;\n    }\n    Object.keys(this.tensorsMap).forEach((key) => {\n      const tensorArray = this.tensorsMap[key];\n      tensorArray.forEach((tensor2) => {\n        if (tensor2 && !tensor2.kept && !tensor2.isDisposed && !this.keepIds.has(tensor2.id)) {\n          tensor2.dispose();\n        }\n      });\n    });\n  }\n  getIntermediateTensors() {\n    return this.tensorsMap;\n  }\n  resetIntermediateTensors() {\n    for (const key in this.intermediateTensors) {\n      this.intermediateTensors[key].forEach((tensor2) => tensor2.dispose());\n      delete this.intermediateTensors[key];\n    }\n  }\n  async _executeAsync(inputs, outputs, isFunctionExecution = false, tensorArrayMap = {}, tensorListMap = {}) {\n    if (!isFunctionExecution) {\n      inputs = this.mapInputs(inputs);\n      this.checkInputs(inputs);\n      this.checkInputShapeAndType(inputs);\n      outputs = this.mapOutputs(outputs);\n      this.checkOutputs(outputs);\n    }\n    try {\n      this.keepTensorForDebug = env().getBool(\"KEEP_INTERMEDIATE_TENSORS\");\n    } catch (e2) {\n      console.warn(e2.message);\n    }\n    this.resetIntermediateTensors();\n    const context = new ExecutionContext(this.weightMap, tensorArrayMap, tensorListMap, this.functionExecutorMap);\n    this.tensorsMap = await this.executeWithControlFlow(inputs, context, outputs, isFunctionExecution);\n    const results = outputs.map((name) => getTensor(name, this.tensorsMap, context));\n    const outputIds = results.map((t2) => t2.id);\n    const inputIds = Object.keys(inputs).map((name) => inputs[name].id);\n    this.keepIds = /* @__PURE__ */ new Set([...outputIds, ...inputIds, ...this.weightIds]);\n    if (!this.keepTensorForDebug) {\n      this.disposeTensorsMap();\n    }\n    if (this.parent == null) {\n      context.dispose(this.keepIds);\n    }\n    return results;\n  }\n  async executeFunctionAsync(inputs, tensorArrayMap, tensorListMap) {\n    const mappedInputs = inputs.reduce((map, tensor2, index) => {\n      map[this.inputs[index].name] = tensor2;\n      return map;\n    }, {});\n    return this._executeAsync(mappedInputs, this.outputNodes, true, tensorArrayMap, tensorListMap);\n  }\n  async executeWithControlFlow(inputs, context, outputNames, isFunctionExecution) {\n    const names = Object.keys(inputs);\n    const inputNodes = names.map((name) => this.graph.nodes[parseNodeName(name)[0]]);\n    const outputNodeNames = outputNames.map((name) => parseNodeName(name)[0]);\n    let outputNodes = outputNodeNames.map((name) => this.graph.nodes[name]);\n    if (outputNodes.length === 0) {\n      outputNodes = this._outputs;\n    }\n    const { usedNodes, missingInputs, dynamicNode, syncInputs } = getExecutionSubgraph(inputs, outputNodes, this.weightMap, this._initNodes);\n    const stack2 = [\n      ...inputNodes,\n      ...this.graph.weights,\n      ...this._initNodes || []\n    ].map((node) => {\n      return { node, contexts: context.currentContext };\n    });\n    const tensorsMap = Object.assign({}, this.weightMap);\n    Object.keys(inputs).forEach((name) => {\n      const [nodeName, index] = parseNodeName(name);\n      const tensors = [];\n      tensors[index] = inputs[name];\n      tensorsMap[nodeName] = tensors;\n    });\n    const intermediateTensorConsumerCount = {};\n    const tensorsToKeep = this.getFrozenTensorIds(tensorsMap);\n    const added = {};\n    while (stack2.length > 0) {\n      const promises = this.processStack(inputNodes, stack2, context, tensorsMap, added, tensorsToKeep, outputNodeNames, intermediateTensorConsumerCount, usedNodes);\n      await Promise.all(promises);\n    }\n    if (dynamicNode == null && !isFunctionExecution) {\n      console.warn(`This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.`);\n    }\n    const missingOutputs = outputNodes.filter((node) => !isControlFlow(node) && !getTensor(node.name, tensorsMap, context)).map((node) => node.name);\n    if (missingOutputs.length > 0) {\n      let alternativeMsg = \"\";\n      if (dynamicNode != null) {\n        alternativeMsg = `Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${syncInputs}]`;\n      }\n      throw new Error(`Cannot compute the outputs [${missingOutputs}] from the provided inputs [${names}]. Consider providing the following inputs: [${missingInputs}]. ${alternativeMsg}`);\n    }\n    return tensorsMap;\n  }\n  processStack(inputNodes, stack2, context, tensorMap, added, tensorsToKeep, outputNames, intermediateTensorConsumerCount, usedNodes) {\n    const promises = [];\n    while (stack2.length > 0) {\n      const item = stack2.pop();\n      context.currentContext = item.contexts;\n      let nodeName = \"\";\n      if (item.node.op === \"Enter\" && getParamValue(\"isConstant\", item.node, tensorMap, context)) {\n        [nodeName] = getNodeNameAndIndex(item.node.name, context);\n      }\n      if (tensorMap[item.node.name] == null) {\n        const tensors = executeOp20(item.node, tensorMap, context, this._resourceManager);\n        if (!nodeName) {\n          [nodeName] = getNodeNameAndIndex(item.node.name, context);\n        }\n        const currentContext = context.currentContext;\n        if (util_exports.isPromise(tensors)) {\n          promises.push(tensors.then((t2) => {\n            tensorMap[nodeName] = t2;\n            context.currentContext = currentContext;\n            this.checkTensorForDisposal(nodeName, item.node, tensorMap, context, tensorsToKeep, outputNames, intermediateTensorConsumerCount);\n            this.processChildNodes(item.node, stack2, context, tensorMap, added, usedNodes);\n            return t2;\n          }));\n        } else {\n          tensorMap[nodeName] = tensors;\n          this.checkTensorForDisposal(nodeName, item.node, tensorMap, context, tensorsToKeep, outputNames, intermediateTensorConsumerCount);\n          this.processChildNodes(item.node, stack2, context, tensorMap, added, usedNodes);\n        }\n      } else {\n        this.processChildNodes(item.node, stack2, context, tensorMap, added, usedNodes);\n      }\n    }\n    return promises;\n  }\n  processChildNodes(node, stack2, context, tensorMap, added, usedNodes) {\n    node.children.forEach((childNode) => {\n      const [nodeName] = getNodeNameAndIndex(childNode.name, context);\n      if (added[nodeName] || !usedNodes.has(childNode.name)) {\n        return;\n      }\n      if (childNode.op === \"Merge\") {\n        if (childNode.inputNames.some((name) => {\n          return !!getTensor(name, tensorMap, context);\n        })) {\n          added[nodeName] = true;\n          stack2.push({ contexts: context.currentContext, node: childNode });\n        }\n      } else if (childNode.inputNames.every((name) => {\n        return !!getTensor(name, tensorMap, context);\n      })) {\n        added[nodeName] = true;\n        stack2.push({ contexts: context.currentContext, node: childNode });\n      }\n    });\n  }\n  dispose() {\n    Object.keys(this.weightMap).forEach((key) => this.weightMap[key].forEach((tensor2) => tensor2.dispose()));\n  }\n  checkInputShapeAndType(inputs) {\n    Object.keys(inputs).forEach((name) => {\n      const input2 = inputs[name];\n      const [nodeName] = parseNodeName(name);\n      const node = this.graph.nodes[nodeName];\n      if (node.attrParams[\"shape\"] && node.attrParams[\"shape\"].value) {\n        const shape = node.attrParams[\"shape\"].value;\n        const match = shape.length === input2.shape.length && input2.shape.every((dim, index) => shape[index] === -1 || shape[index] === dim);\n        util_exports.assert(match, () => `The shape of dict['${node.name}'] provided in model.execute(dict) must be [${shape}], but was [${input2.shape}]`);\n      }\n      if (node.attrParams[\"dtype\"] && node.attrParams[\"dtype\"].value) {\n        util_exports.assert(input2.dtype === node.attrParams[\"dtype\"].value, () => `The dtype of dict['${node.name}'] provided in model.execute(dict) must be ${node.attrParams[\"dtype\"].value}, but was ${input2.dtype}`);\n      }\n    });\n  }\n  mapInputs(inputs) {\n    const result = {};\n    for (const inputName in inputs) {\n      if (this._signature != null && this._signature.inputs != null && this._signature.inputs[inputName] != null) {\n        const tensor2 = this._signature.inputs[inputName];\n        result[tensor2.name] = inputs[inputName];\n      } else {\n        result[inputName] = inputs[inputName];\n      }\n    }\n    return result;\n  }\n  checkInputs(inputs) {\n    const notInGraph = Object.keys(inputs).filter((name) => {\n      const [nodeName] = parseNodeName(name);\n      return this.graph.nodes[nodeName] == null;\n    });\n    if (notInGraph.length > 0) {\n      throw new Error(`The dict provided in model.execute(dict) has keys: [${notInGraph}] that are not part of graph`);\n    }\n  }\n  mapOutputs(outputs) {\n    return outputs.map((name) => {\n      if (this._signature != null && this._signature.outputs != null && this._signature.outputs[name] != null) {\n        const tensor2 = this._signature.outputs[name];\n        return tensor2.name;\n      }\n      return name;\n    }, {});\n  }\n  checkOutputs(outputs) {\n    outputs.forEach((name) => {\n      const [normalizedName] = parseNodeName(name);\n      if (!this.graph.nodes[normalizedName]) {\n        throw new Error(`The output '${name}' is not found in the graph`);\n      }\n    });\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/resource_manager.js\nvar ResourceManager = class {\n  constructor(hashTableNameToHandle = {}, hashTableMap = {}) {\n    this.hashTableNameToHandle = hashTableNameToHandle;\n    this.hashTableMap = hashTableMap;\n  }\n  addHashTable(name, hashTable) {\n    this.hashTableNameToHandle[name] = hashTable.handle;\n    this.hashTableMap[hashTable.id] = hashTable;\n  }\n  getHashTableHandleByName(name) {\n    return this.hashTableNameToHandle[name];\n  }\n  getHashTableById(id) {\n    return this.hashTableMap[id];\n  }\n  dispose() {\n    for (const key in this.hashTableMap) {\n      this.hashTableMap[key].clearAndClose();\n      delete this.hashTableMap[key];\n    }\n    for (const name in this.hashTableNameToHandle) {\n      this.hashTableNameToHandle[name].dispose();\n      delete this.hashTableNameToHandle[name];\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/graph_model.js\nvar TFHUB_SEARCH_PARAM = \"?tfjs-format=file\";\nvar DEFAULT_MODEL_NAME = \"model.json\";\nvar GraphModel = class {\n  constructor(modelUrl, loadOptions = {}, tfio = io_exports) {\n    this.modelUrl = modelUrl;\n    this.loadOptions = loadOptions;\n    this.version = \"n/a\";\n    this.io = tfio;\n    if (loadOptions == null) {\n      this.loadOptions = {};\n    }\n    this.resourceManager = new ResourceManager();\n  }\n  get modelVersion() {\n    return this.version;\n  }\n  get inputNodes() {\n    return this.executor.inputNodes;\n  }\n  get outputNodes() {\n    return this.executor.outputNodes;\n  }\n  get inputs() {\n    return this.executor.inputs;\n  }\n  get outputs() {\n    return this.executor.outputs;\n  }\n  get weights() {\n    return this.executor.weightMap;\n  }\n  get metadata() {\n    return this.artifacts.userDefinedMetadata;\n  }\n  get modelSignature() {\n    return this.signature;\n  }\n  get modelStructuredOutputKeys() {\n    return this.structuredOutputKeys;\n  }\n  findIOHandler() {\n    const path = this.modelUrl;\n    if (path.load != null) {\n      this.handler = path;\n    } else if (this.loadOptions.requestInit != null) {\n      this.handler = this.io.browserHTTPRequest(path, this.loadOptions);\n    } else {\n      const handlers = this.io.getLoadHandlers(path, this.loadOptions);\n      if (handlers.length === 0) {\n        handlers.push(this.io.browserHTTPRequest(path, this.loadOptions));\n      } else if (handlers.length > 1) {\n        throw new Error(`Found more than one (${handlers.length}) load handlers for URL '${[path]}'`);\n      }\n      this.handler = handlers[0];\n    }\n  }\n  load() {\n    this.findIOHandler();\n    if (this.handler.load == null) {\n      throw new Error(\"Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.\");\n    }\n    const loadResult = this.handler.load();\n    if (util_exports.isPromise(loadResult)) {\n      return loadResult.then((artifacts) => this.loadSync(artifacts));\n    }\n    return this.loadSync(loadResult);\n  }\n  loadSync(artifacts) {\n    this.artifacts = artifacts;\n    const graph = this.artifacts.modelTopology;\n    let signature = this.artifacts.signature;\n    if (this.artifacts.userDefinedMetadata != null) {\n      const metadata = this.artifacts.userDefinedMetadata;\n      if (metadata.signature != null) {\n        signature = metadata.signature;\n      }\n      if (metadata.structuredOutputKeys != null) {\n        this.structuredOutputKeys = metadata.structuredOutputKeys;\n      }\n    }\n    this.signature = signature;\n    this.version = `${graph.versions.producer}.${graph.versions.minConsumer}`;\n    const weightMap = this.io.decodeWeights(this.artifacts.weightData, this.artifacts.weightSpecs);\n    this.executor = new GraphExecutor(OperationMapper.Instance.transformGraph(graph, this.signature));\n    this.executor.weightMap = this.convertTensorMapToTensorsMap(weightMap);\n    this.executor.resourceManager = this.resourceManager;\n    if (artifacts.modelInitializer != null && artifacts.modelInitializer.node != null) {\n      const initializer = OperationMapper.Instance.transformGraph(artifacts.modelInitializer);\n      this.initializer = new GraphExecutor(initializer);\n      this.initializer.weightMap = this.executor.weightMap;\n      this.initializer.resourceManager = this.resourceManager;\n      this.initializer.executeAsync({}, []);\n    }\n    return true;\n  }\n  async save(handlerOrURL, config) {\n    if (typeof handlerOrURL === \"string\") {\n      const handlers = this.io.getSaveHandlers(handlerOrURL);\n      if (handlers.length === 0) {\n        throw new Error(`Cannot find any save handlers for URL '${handlerOrURL}'`);\n      } else if (handlers.length > 1) {\n        throw new Error(`Found more than one (${handlers.length}) save handlers for URL '${handlerOrURL}'`);\n      }\n      handlerOrURL = handlers[0];\n    }\n    if (handlerOrURL.save == null) {\n      throw new Error(\"GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.\");\n    }\n    return handlerOrURL.save(this.artifacts);\n  }\n  predict(inputs, config) {\n    const outputTensors = this.execute(inputs, this.outputNodes);\n    if (this.structuredOutputKeys) {\n      const outputTensorsArray = outputTensors instanceof Tensor ? [outputTensors] : outputTensors;\n      const outputTensorMap = {};\n      outputTensorsArray.forEach((outputTensor, i2) => outputTensorMap[this.structuredOutputKeys[i2]] = outputTensor);\n      return outputTensorMap;\n    }\n    return outputTensors;\n  }\n  normalizeInputs(inputs) {\n    if (!(inputs instanceof Tensor) && !Array.isArray(inputs)) {\n      return inputs;\n    }\n    inputs = Array.isArray(inputs) ? inputs : [inputs];\n    if (inputs.length !== this.inputNodes.length) {\n      throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${inputs.length} input tensors.`);\n    }\n    return this.inputNodes.reduce((map, inputName, i2) => {\n      map[inputName] = inputs[i2];\n      return map;\n    }, {});\n  }\n  normalizeOutputs(outputs) {\n    outputs = outputs || this.outputNodes;\n    return !Array.isArray(outputs) ? [outputs] : outputs;\n  }\n  execute(inputs, outputs) {\n    inputs = this.normalizeInputs(inputs);\n    outputs = this.normalizeOutputs(outputs);\n    const result = this.executor.execute(inputs, outputs);\n    return result.length > 1 ? result : result[0];\n  }\n  async executeAsync(inputs, outputs) {\n    inputs = this.normalizeInputs(inputs);\n    outputs = this.normalizeOutputs(outputs);\n    const result = await this.executor.executeAsync(inputs, outputs);\n    return result.length > 1 ? result : result[0];\n  }\n  getIntermediateTensors() {\n    return this.executor.getIntermediateTensors();\n  }\n  disposeIntermediateTensors() {\n    this.executor.disposeIntermediateTensors();\n  }\n  convertTensorMapToTensorsMap(map) {\n    return Object.keys(map).reduce((newMap, key) => {\n      newMap[key] = [map[key]];\n      return newMap;\n    }, {});\n  }\n  dispose() {\n    this.executor.dispose();\n    if (this.initializer) {\n      this.initializer.dispose();\n    }\n    this.resourceManager.dispose();\n  }\n};\nasync function loadGraphModel(modelUrl, options = {}, tfio = io_exports) {\n  if (modelUrl == null) {\n    throw new Error(\"modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model\");\n  }\n  if (options == null) {\n    options = {};\n  }\n  if (options.fromTFHub && typeof modelUrl === \"string\") {\n    modelUrl = getTFHubUrl(modelUrl);\n  }\n  const model2 = new GraphModel(modelUrl, options, tfio);\n  await model2.load();\n  return model2;\n}\nfunction loadGraphModelSync(modelSource) {\n  if (modelSource == null) {\n    throw new Error(\"modelUrl in loadGraphModelSync() cannot be null. Please provide a url or an IOHandler that loads the model\");\n  }\n  if (!modelSource.load) {\n    throw new Error(`modelUrl IO Handler ${modelSource} has no load function`);\n  }\n  const model2 = new GraphModel(modelSource);\n  model2.load();\n  return model2;\n}\nfunction getTFHubUrl(modelUrl) {\n  if (!modelUrl.endsWith(\"/\")) {\n    modelUrl = modelUrl + \"/\";\n  }\n  return `${modelUrl}${DEFAULT_MODEL_NAME}${TFHUB_SEARCH_PARAM}`;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/version.js\nvar version3 = \"3.19.0\";\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/index.js\nvar dist_exports2 = {};\n__export(dist_exports2, {\n  CSVDataset: () => CSVDataset,\n  Dataset: () => Dataset,\n  FileDataSource: () => FileDataSource,\n  TextLineDataset: () => TextLineDataset,\n  URLDataSource: () => URLDataSource,\n  array: () => array,\n  csv: () => csv,\n  func: () => func,\n  generator: () => generator,\n  microphone: () => microphone,\n  version_data: () => version4,\n  webcam: () => webcam,\n  zip: () => zip\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/dataset.js\nvar seedrandom3 = __toESM(require_seedrandom2());\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/lazy_iterator.js\nvar seedrandom2 = __toESM(require_seedrandom2());\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/util/deep_map.js\nfunction deepMap(input2, mapFn) {\n  return deepMapInternal(input2, mapFn);\n}\nfunction deepMapInternal(input2, mapFn, seen = /* @__PURE__ */ new Map(), containedIn = /* @__PURE__ */ new Set()) {\n  if (input2 == null) {\n    return null;\n  }\n  if (typeof Blob === \"function\" && input2 instanceof Blob) {\n    return input2.slice();\n  }\n  if (containedIn.has(input2)) {\n    throw new Error(\"Circular references are not supported.\");\n  }\n  if (seen.has(input2)) {\n    return seen.get(input2);\n  }\n  const result = mapFn(input2);\n  if (result.recurse && result.value !== null) {\n    throw new Error(\"A deep map function may not return both a value and recurse=true.\");\n  }\n  if (!result.recurse) {\n    seen.set(input2, result.value);\n    return result.value;\n  } else if (isIterable2(input2)) {\n    const mappedIterable = Array.isArray(input2) ? [] : {};\n    containedIn.add(input2);\n    for (const k in input2) {\n      const child = input2[k];\n      const childResult = deepMapInternal(child, mapFn, seen, containedIn);\n      mappedIterable[k] = childResult;\n    }\n    containedIn.delete(input2);\n    if (input2.__proto__) {\n      mappedIterable.__proto__ = input2.__proto__;\n    }\n    return mappedIterable;\n  } else {\n    throw new Error(`Can't recurse into non-iterable type: ${input2}`);\n  }\n}\nfunction deepZip(inputs, zipFn = zipToList) {\n  return deepZipInternal(inputs, zipFn);\n}\nfunction deepZipInternal(inputs, zipFn, containedIn = /* @__PURE__ */ new Set()) {\n  const input2 = inputs[0];\n  if (containedIn.has(input2)) {\n    throw new Error(\"Circular references are not supported.\");\n  }\n  const result = zipFn(inputs);\n  if (result.recurse && result.value !== null) {\n    throw new Error(\"A deep zip function may not return both a value and recurse=true.\");\n  }\n  if (!result.recurse) {\n    return result.value;\n  } else if (isIterable2(input2)) {\n    const mappedIterable = Array.isArray(input2) ? [] : {};\n    containedIn.add(input2);\n    for (const k in input2) {\n      const children = inputs.map((x) => x[k]);\n      const childResult = deepZipInternal(children, zipFn, containedIn);\n      mappedIterable[k] = childResult;\n    }\n    containedIn.delete(input2);\n    return mappedIterable;\n  } else {\n    throw new Error(`Can't recurse into non-iterable type: ${input2}`);\n  }\n}\nfunction zipToList(x) {\n  if (x === null) {\n    return null;\n  }\n  if (isIterable2(x[0])) {\n    return { value: null, recurse: true };\n  } else {\n    return { value: x, recurse: false };\n  }\n}\nasync function deepMapAndAwaitAll(input2, mapFn) {\n  const seen = /* @__PURE__ */ new Map();\n  deepMapInternal(input2, mapFn, seen);\n  for (const key of Array.from(seen.keys())) {\n    const value = seen.get(key);\n    if (util_exports.isPromise(value)) {\n      const mappedValue = await value;\n      seen.set(key, mappedValue);\n    }\n  }\n  const result = deepMapInternal(input2, mapFn, seen);\n  return result;\n}\nfunction isIterable2(obj) {\n  let isTextDecoder = false;\n  if (env().get(\"IS_BROWSER\")) {\n    isTextDecoder = obj instanceof TextDecoder;\n  } else {\n    const { StringDecoder } = require_string_decoder();\n    isTextDecoder = obj instanceof StringDecoder;\n  }\n  return obj != null && !ArrayBuffer.isView(obj) && (Array.isArray(obj) || typeof obj === \"object\" && !(obj instanceof Tensor) && !(obj instanceof Promise) && !isTextDecoder);\n}\nfunction canTensorify(obj) {\n  return obj == null || isPrimitive(obj) || Array.isArray(obj) || typeof obj === \"object\" && obj instanceof Tensor || util_exports.isTypedArray(obj);\n}\nfunction isPrimitive(value) {\n  return value === null || typeof value !== \"object\" && typeof value !== \"function\";\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/util/deep_clone.js\nfunction deepClone(container) {\n  return deepMap(container, cloneIfTensor);\n}\nfunction cloneIfTensor(item) {\n  if (item instanceof Tensor) {\n    return { value: item.clone(), recurse: false };\n  } else if (isIterable2(item)) {\n    return { value: null, recurse: true };\n  } else {\n    return { value: item, recurse: false };\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/util/ring_buffer.js\nvar RingBuffer = class {\n  constructor(capacity) {\n    this.capacity = capacity;\n    this.begin = 0;\n    this.end = 0;\n    if (capacity == null) {\n      throw new RangeError(\"Can't create a ring buffer of unknown capacity.\");\n    }\n    if (capacity < 1) {\n      throw new RangeError(\"Can't create ring buffer of capacity < 1.\");\n    }\n    this.data = new Array(capacity);\n    this.doubledCapacity = 2 * capacity;\n  }\n  wrap(index) {\n    while (index < 0) {\n      index += this.doubledCapacity;\n    }\n    return index % this.doubledCapacity;\n  }\n  get(index) {\n    if (index < 0) {\n      throw new RangeError(\"Can't get item at a negative index.\");\n    }\n    return this.data[index % this.capacity];\n  }\n  set(index, value) {\n    if (index < 0) {\n      throw new RangeError(\"Can't set item at a negative index.\");\n    }\n    this.data[index % this.capacity] = value;\n  }\n  length() {\n    let length = this.end - this.begin;\n    if (length < 0) {\n      length = this.doubledCapacity + length;\n    }\n    return length;\n  }\n  isFull() {\n    return this.length() === this.capacity;\n  }\n  isEmpty() {\n    return this.length() === 0;\n  }\n  push(value) {\n    if (this.isFull()) {\n      throw new RangeError(\"Ring buffer is full.\");\n    }\n    this.set(this.end, value);\n    this.end = this.wrap(this.end + 1);\n  }\n  pushAll(values) {\n    for (const value of values) {\n      this.push(value);\n    }\n  }\n  pop() {\n    if (this.isEmpty()) {\n      throw new RangeError(\"Ring buffer is empty.\");\n    }\n    this.end = this.wrap(this.end - 1);\n    const result = this.get(this.end);\n    this.set(this.end, void 0);\n    return result;\n  }\n  unshift(value) {\n    if (this.isFull()) {\n      throw new RangeError(\"Ring buffer is full.\");\n    }\n    this.begin = this.wrap(this.begin - 1);\n    this.set(this.begin, value);\n  }\n  shift() {\n    if (this.isEmpty()) {\n      throw new RangeError(\"Ring buffer is empty.\");\n    }\n    const result = this.get(this.begin);\n    this.set(this.begin, void 0);\n    this.begin = this.wrap(this.begin + 1);\n    return result;\n  }\n  shuffleExcise(relativeIndex) {\n    if (this.isEmpty()) {\n      throw new RangeError(\"Ring buffer is empty.\");\n    }\n    const index = this.wrap(this.begin + relativeIndex);\n    const result = this.get(index);\n    this.set(index, this.pop());\n    return result;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/util/growing_ring_buffer.js\nvar GrowingRingBuffer = class extends RingBuffer {\n  constructor() {\n    super(GrowingRingBuffer.INITIAL_CAPACITY);\n  }\n  isFull() {\n    return false;\n  }\n  push(value) {\n    if (super.isFull()) {\n      this.expand();\n    }\n    super.push(value);\n  }\n  unshift(value) {\n    if (super.isFull()) {\n      this.expand();\n    }\n    super.unshift(value);\n  }\n  expand() {\n    const newCapacity = this.capacity * 2;\n    const newData = new Array(newCapacity);\n    const len = this.length();\n    for (let i2 = 0; i2 < len; i2++) {\n      newData[i2] = this.get(this.wrap(this.begin + i2));\n    }\n    this.data = newData;\n    this.capacity = newCapacity;\n    this.doubledCapacity = 2 * this.capacity;\n    this.begin = 0;\n    this.end = len;\n  }\n};\nGrowingRingBuffer.INITIAL_CAPACITY = 32;\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/lazy_iterator.js\nfunction iteratorFromItems(items) {\n  return new ArrayIterator(items);\n}\nfunction iteratorFromFunction(func2) {\n  return new FunctionCallIterator(func2);\n}\nfunction iteratorFromConcatenated(baseIterators, baseErrorHandler) {\n  return new ChainedIterator(baseIterators, baseErrorHandler);\n}\nfunction iteratorFromZipped(iterators, mismatchMode = ZipMismatchMode.FAIL) {\n  return new ZipIterator(iterators, mismatchMode);\n}\nvar LazyIterator = class {\n  async toArray() {\n    const result = [];\n    let x = await this.next();\n    while (!x.done) {\n      result.push(x.value);\n      x = await this.next();\n    }\n    return result;\n  }\n  async toArrayForTest() {\n    const stream = this.prefetch(100);\n    const result = [];\n    let x = await stream.next();\n    while (!x.done) {\n      result.push(x.value);\n      x = await stream.next();\n    }\n    return result;\n  }\n  async resolveFully() {\n    let x = await this.next();\n    while (!x.done) {\n      x = await this.next();\n    }\n  }\n  async resolveWhile(predicate) {\n    let x = await this.next();\n    let shouldContinue = predicate(x.value);\n    while (!x.done && shouldContinue) {\n      x = await this.next();\n      shouldContinue = predicate(x.value);\n    }\n  }\n  handleErrors(handler) {\n    return new ErrorHandlingLazyIterator(this, handler);\n  }\n  filter(predicate) {\n    return new FilterIterator(this, predicate);\n  }\n  map(transform6) {\n    return new MapIterator(this, transform6);\n  }\n  mapAsync(transform6) {\n    return new AsyncMapIterator(this, transform6);\n  }\n  serialMapAsync(transform6) {\n    return new AsyncMapIterator(this, transform6).serial();\n  }\n  flatmap(transform6) {\n    return new FlatmapIterator(this, transform6);\n  }\n  async forEachAsync(f) {\n    return this.map(f).resolveFully();\n  }\n  async serialForEach(f) {\n    return this.serialMapAsync(f).resolveWhile((x) => x === true);\n  }\n  rowMajorBatch(batchSize, smallLastBatch = true) {\n    return new RowMajorBatchIterator(this, batchSize, smallLastBatch);\n  }\n  columnMajorBatch(batchSize, smallLastBatch = true, zipFn = zipToList) {\n    const rowBatches = this.rowMajorBatch(batchSize, smallLastBatch);\n    return rowBatches.map((x) => deepZip(x, zipFn));\n  }\n  concatenate(iterator, baseErrorHandler) {\n    return new ChainedIterator(iteratorFromItems([this, iterator]), baseErrorHandler);\n  }\n  take(count2) {\n    if (count2 < 0 || count2 == null) {\n      return this;\n    }\n    return new TakeIterator(this, count2);\n  }\n  skip(count2) {\n    if (count2 < 0 || count2 == null) {\n      return this;\n    }\n    return new SkipIterator(this, count2);\n  }\n  prefetch(bufferSize) {\n    return new PrefetchIterator(this, bufferSize);\n  }\n  shuffle(windowSize, seed) {\n    return new ShuffleIterator(this, windowSize, seed);\n  }\n  serial() {\n    return new SerialIterator(this);\n  }\n};\nvar ArrayIterator = class extends LazyIterator {\n  constructor(items) {\n    super();\n    this.items = items;\n    this.trav = 0;\n  }\n  summary() {\n    return `Array of ${this.items.length} items`;\n  }\n  async next() {\n    if (this.trav >= this.items.length) {\n      return { value: null, done: true };\n    }\n    const item = this.items[this.trav];\n    this.trav++;\n    return { value: deepClone(item), done: false };\n  }\n};\nvar FunctionCallIterator = class extends LazyIterator {\n  constructor(nextFn) {\n    super();\n    this.nextFn = nextFn;\n  }\n  summary() {\n    return `Function call`;\n  }\n  async next() {\n    try {\n      return this.nextFn();\n    } catch (e2) {\n      e2.message = `Error thrown while iterating through a dataset: ${e2.message}`;\n      throw e2;\n    }\n  }\n};\nvar SerialIterator = class extends LazyIterator {\n  constructor(upstream) {\n    super();\n    this.upstream = upstream;\n    this.lastRead = Promise.resolve({ value: null, done: false });\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Serial`;\n  }\n  async next() {\n    this.lastRead = this.lastRead.then(() => this.serialNext());\n    return this.lastRead;\n  }\n  async serialNext() {\n    return this.upstream.next();\n  }\n};\nvar SkipIterator = class extends LazyIterator {\n  constructor(upstream, maxCount) {\n    super();\n    this.upstream = upstream;\n    this.maxCount = maxCount;\n    this.count = 0;\n    this.lastRead = Promise.resolve({ value: null, done: false });\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Skip`;\n  }\n  async next() {\n    this.lastRead = this.lastRead.then(() => this.serialNext());\n    return this.lastRead;\n  }\n  async serialNext() {\n    while (this.count++ < this.maxCount) {\n      const skipped = await this.upstream.next();\n      if (skipped.done) {\n        return skipped;\n      }\n      dispose(skipped.value);\n    }\n    return this.upstream.next();\n  }\n};\nvar TakeIterator = class extends LazyIterator {\n  constructor(upstream, maxCount) {\n    super();\n    this.upstream = upstream;\n    this.maxCount = maxCount;\n    this.count = 0;\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Take`;\n  }\n  async next() {\n    if (this.count++ >= this.maxCount) {\n      return { value: null, done: true };\n    }\n    return this.upstream.next();\n  }\n};\nvar RowMajorBatchIterator = class extends LazyIterator {\n  constructor(upstream, batchSize, enableSmallLastBatch = true) {\n    super();\n    this.upstream = upstream;\n    this.batchSize = batchSize;\n    this.enableSmallLastBatch = enableSmallLastBatch;\n    this.lastRead = Promise.resolve({ value: null, done: false });\n  }\n  summary() {\n    return `${this.upstream.summary()} -> RowMajorBatch`;\n  }\n  async next() {\n    this.lastRead = this.lastRead.then(() => this.serialNext());\n    return this.lastRead;\n  }\n  async serialNext() {\n    const batch = [];\n    while (batch.length < this.batchSize) {\n      const item = await this.upstream.next();\n      if (item.done) {\n        if (this.enableSmallLastBatch && batch.length > 0) {\n          return { value: batch, done: false };\n        }\n        return { value: null, done: true };\n      }\n      batch.push(item.value);\n    }\n    return { value: batch, done: false };\n  }\n};\nvar FilterIterator = class extends LazyIterator {\n  constructor(upstream, predicate) {\n    super();\n    this.upstream = upstream;\n    this.predicate = predicate;\n    this.lastRead = Promise.resolve({ value: null, done: false });\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Filter`;\n  }\n  async next() {\n    this.lastRead = this.lastRead.then(() => this.serialNext());\n    return this.lastRead;\n  }\n  async serialNext() {\n    while (true) {\n      const item = await this.upstream.next();\n      if (item.done || this.predicate(item.value)) {\n        return item;\n      }\n      dispose(item.value);\n    }\n  }\n};\nvar MapIterator = class extends LazyIterator {\n  constructor(upstream, transform6) {\n    super();\n    this.upstream = upstream;\n    this.transform = transform6;\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Map`;\n  }\n  async next() {\n    const item = await this.upstream.next();\n    if (item.done) {\n      return { value: null, done: true };\n    }\n    const inputTensors = tensor_util_exports.getTensorsInContainer(item.value);\n    const mapped = this.transform(item.value);\n    const outputTensors = tensor_util_exports.getTensorsInContainer(mapped);\n    for (const t2 of inputTensors) {\n      if (!tensor_util_exports.isTensorInList(t2, outputTensors)) {\n        t2.dispose();\n      }\n    }\n    return { value: mapped, done: false };\n  }\n};\nvar ErrorHandlingLazyIterator = class extends LazyIterator {\n  constructor(upstream, handler) {\n    super();\n    this.upstream = upstream;\n    this.handler = handler;\n    this.count = 0;\n    this.lastRead = Promise.resolve({ value: null, done: false });\n  }\n  summary() {\n    return `${this.upstream.summary()} -> handleErrors`;\n  }\n  async next() {\n    this.lastRead = this.lastRead.then(() => this.serialNext());\n    return this.lastRead;\n  }\n  async serialNext() {\n    while (true) {\n      try {\n        return await this.upstream.next();\n      } catch (e2) {\n        if (!this.handler(e2)) {\n          return { value: null, done: true };\n        }\n      }\n    }\n  }\n};\nvar AsyncMapIterator = class extends LazyIterator {\n  constructor(upstream, transform6) {\n    super();\n    this.upstream = upstream;\n    this.transform = transform6;\n  }\n  summary() {\n    return `${this.upstream.summary()} -> AsyncMap`;\n  }\n  async next() {\n    const item = await this.upstream.next();\n    if (item.done) {\n      return { value: null, done: true };\n    }\n    const inputTensors = tensor_util_exports.getTensorsInContainer(item.value);\n    const mapped = await this.transform(item.value);\n    const outputTensors = tensor_util_exports.getTensorsInContainer(mapped);\n    for (const t2 of inputTensors) {\n      if (!tensor_util_exports.isTensorInList(t2, outputTensors)) {\n        t2.dispose();\n      }\n    }\n    return { value: mapped, done: false };\n  }\n};\nvar OneToManyIterator = class extends LazyIterator {\n  constructor() {\n    super();\n    this.outputQueue = new GrowingRingBuffer();\n    this.lastRead = Promise.resolve({ value: null, done: false });\n  }\n  async next() {\n    this.lastRead = this.lastRead.then(() => this.serialNext());\n    return this.lastRead;\n  }\n  async serialNext() {\n    while (this.outputQueue.length() === 0) {\n      if (!await this.pump()) {\n        return { value: null, done: true };\n      }\n    }\n    return { value: this.outputQueue.shift(), done: false };\n  }\n};\nvar FlatmapIterator = class extends OneToManyIterator {\n  constructor(upstream, transform6) {\n    super();\n    this.upstream = upstream;\n    this.transform = transform6;\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Flatmap`;\n  }\n  async pump() {\n    const item = await this.upstream.next();\n    if (item.done) {\n      return false;\n    }\n    const inputTensors = tensor_util_exports.getTensorsInContainer(item.value);\n    const mappedArray = this.transform(item.value);\n    const outputTensors = tensor_util_exports.getTensorsInContainer(mappedArray);\n    this.outputQueue.pushAll(mappedArray);\n    for (const t2 of inputTensors) {\n      if (!tensor_util_exports.isTensorInList(t2, outputTensors)) {\n        t2.dispose();\n      }\n    }\n    return true;\n  }\n};\nvar ChainedIterator = class extends LazyIterator {\n  constructor(iterators, baseErrorHandler) {\n    super();\n    this.baseErrorHandler = baseErrorHandler;\n    this.lastRead = null;\n    this.iterator = null;\n    this.moreIterators = iterators;\n  }\n  summary() {\n    const upstreamSummaries = \"TODO: fill in upstream of chained summaries\";\n    return `${upstreamSummaries} -> Chained`;\n  }\n  async next() {\n    this.lastRead = this.readFromChain(this.lastRead);\n    return this.lastRead;\n  }\n  async readFromChain(lastRead) {\n    await lastRead;\n    if (this.iterator == null) {\n      const iteratorResult = await this.moreIterators.next();\n      if (iteratorResult.done) {\n        return { value: null, done: true };\n      }\n      this.iterator = iteratorResult.value;\n      if (this.baseErrorHandler != null) {\n        this.iterator = this.iterator.handleErrors(this.baseErrorHandler);\n      }\n    }\n    const itemResult = await this.iterator.next();\n    if (itemResult.done) {\n      this.iterator = null;\n      return this.readFromChain(lastRead);\n    }\n    return itemResult;\n  }\n};\nvar ZipMismatchMode;\n(function(ZipMismatchMode2) {\n  ZipMismatchMode2[ZipMismatchMode2[\"FAIL\"] = 0] = \"FAIL\";\n  ZipMismatchMode2[ZipMismatchMode2[\"SHORTEST\"] = 1] = \"SHORTEST\";\n  ZipMismatchMode2[ZipMismatchMode2[\"LONGEST\"] = 2] = \"LONGEST\";\n})(ZipMismatchMode || (ZipMismatchMode = {}));\nvar ZipIterator = class extends LazyIterator {\n  constructor(iterators, mismatchMode = ZipMismatchMode.FAIL) {\n    super();\n    this.iterators = iterators;\n    this.mismatchMode = mismatchMode;\n    this.count = 0;\n    this.currentPromise = null;\n  }\n  summary() {\n    const upstreamSummaries = \"TODO: fill in upstream of zip summaries\";\n    return `{${upstreamSummaries}} -> Zip`;\n  }\n  async nextState(afterState) {\n    await afterState;\n    let numIterators = 0;\n    let iteratorsDone = 0;\n    function getNext(container) {\n      if (container instanceof LazyIterator) {\n        const result = container.next();\n        return {\n          value: result.then((x) => {\n            numIterators++;\n            if (x.done) {\n              iteratorsDone++;\n            }\n            return x.value;\n          }),\n          recurse: false\n        };\n      } else {\n        return { value: null, recurse: true };\n      }\n    }\n    const mapped = await deepMapAndAwaitAll(this.iterators, getNext);\n    if (numIterators === iteratorsDone) {\n      return { value: null, done: true };\n    }\n    if (iteratorsDone > 0) {\n      switch (this.mismatchMode) {\n        case ZipMismatchMode.FAIL:\n          throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);\n        case ZipMismatchMode.SHORTEST:\n          return { value: null, done: true };\n        case ZipMismatchMode.LONGEST:\n        default:\n      }\n    }\n    this.count++;\n    return { value: mapped, done: false };\n  }\n  async next() {\n    this.currentPromise = this.nextState(this.currentPromise);\n    return this.currentPromise;\n  }\n};\nvar PrefetchIterator = class extends LazyIterator {\n  constructor(upstream, bufferSize) {\n    super();\n    this.upstream = upstream;\n    this.bufferSize = bufferSize;\n    this.buffer = new RingBuffer(bufferSize);\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Prefetch`;\n  }\n  refill() {\n    while (!this.buffer.isFull()) {\n      const v = this.upstream.next();\n      this.buffer.push(v);\n    }\n  }\n  next() {\n    this.refill();\n    return this.buffer.shift();\n  }\n};\nvar ShuffleIterator = class extends PrefetchIterator {\n  constructor(upstream, windowSize, seed) {\n    super(upstream, windowSize);\n    this.upstream = upstream;\n    this.windowSize = windowSize;\n    this.upstreamExhausted = false;\n    this.random = seedrandom2.alea(seed || util_exports.now().toString());\n    this.lastRead = Promise.resolve({ value: null, done: false });\n  }\n  async next() {\n    this.lastRead = this.lastRead.then(() => this.serialNext());\n    return this.lastRead;\n  }\n  randomInt(max7) {\n    return Math.floor(this.random() * max7);\n  }\n  chooseIndex() {\n    return this.randomInt(this.buffer.length());\n  }\n  async serialNext() {\n    if (!this.upstreamExhausted) {\n      this.refill();\n    }\n    while (!this.buffer.isEmpty()) {\n      const chosenIndex = this.chooseIndex();\n      const result = await this.buffer.shuffleExcise(chosenIndex);\n      if (result.done) {\n        this.upstreamExhausted = true;\n      } else {\n        this.refill();\n        return result;\n      }\n    }\n    return { value: null, done: true };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/dataset.js\nvar Dataset = class {\n  constructor() {\n    this.size = null;\n  }\n  batch(batchSize, smallLastBatch = true) {\n    const base = this;\n    util_exports.assert(batchSize > 0, () => `batchSize needs to be positive, but it is\n      ${batchSize}`);\n    let size;\n    if (this.size === Infinity || this.size == null) {\n      size = this.size;\n    } else if (smallLastBatch) {\n      size = Math.ceil(this.size / batchSize);\n    } else {\n      size = Math.floor(this.size / batchSize);\n    }\n    return datasetFromIteratorFn(async () => {\n      return (await base.iterator()).columnMajorBatch(batchSize, smallLastBatch, deepBatchConcat);\n    }, size);\n  }\n  concatenate(dataset) {\n    const base = this;\n    let size;\n    if (this.size === Infinity || dataset.size === Infinity) {\n      size = Infinity;\n    } else if (this.size != null && dataset.size != null) {\n      size = this.size + dataset.size;\n    } else {\n      size = null;\n    }\n    return datasetFromIteratorFn(async () => (await base.iterator()).concatenate(await dataset.iterator()), size);\n  }\n  filter(predicate) {\n    const base = this;\n    let size;\n    if (this.size === Infinity) {\n      size = Infinity;\n    } else {\n      size = null;\n    }\n    return datasetFromIteratorFn(async () => {\n      return (await base.iterator()).filter((x) => tidy(() => predicate(x)));\n    }, size);\n  }\n  async forEachAsync(f) {\n    return (await this.iterator()).forEachAsync(f);\n  }\n  map(transform6) {\n    const base = this;\n    return datasetFromIteratorFn(async () => {\n      return (await base.iterator()).map((x) => tidy(() => transform6(x)));\n    }, this.size);\n  }\n  mapAsync(transform6) {\n    const base = this;\n    return datasetFromIteratorFn(async () => {\n      return (await base.iterator()).mapAsync(transform6);\n    }, this.size);\n  }\n  prefetch(bufferSize) {\n    if (bufferSize == null) {\n      throw new RangeError(\"`Dataset.prefetch()` requires bufferSize to be specified.\");\n    }\n    const base = this;\n    return datasetFromIteratorFn(async () => (await base.iterator()).prefetch(bufferSize), this.size);\n  }\n  repeat(count2) {\n    const base = this;\n    let size;\n    if (this.size != null && count2 > 0) {\n      size = this.size * count2;\n    } else if (count2 === 0) {\n      size = 0;\n    } else if (this.size != null && (count2 === void 0 || count2 < 0)) {\n      size = Infinity;\n    } else {\n      size = null;\n    }\n    return datasetFromIteratorFn(async () => {\n      const iteratorIterator = iteratorFromFunction(async () => ({ value: await base.iterator(), done: false }));\n      return iteratorFromConcatenated(iteratorIterator.take(count2));\n    }, size);\n  }\n  skip(count2) {\n    const base = this;\n    let size;\n    if (this.size != null && count2 >= 0 && this.size >= count2) {\n      size = this.size - count2;\n    } else if (this.size != null && (this.size < count2 || count2 === void 0 || count2 < 0)) {\n      size = 0;\n    } else {\n      size = null;\n    }\n    return datasetFromIteratorFn(async () => (await base.iterator()).skip(count2), size);\n  }\n  shuffle(bufferSize, seed, reshuffleEachIteration = true) {\n    if (bufferSize == null || bufferSize < 0) {\n      if (this.size == null) {\n        throw new RangeError(\"`Dataset.shuffle()` requires bufferSize to be specified.\");\n      } else {\n        throw new RangeError(`\\`Dataset.shuffle()\\` requires bufferSize to be specified.  If your data fits in main memory (for regular JS objects), and/or GPU memory (for \\`tf.Tensor\\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);\n      }\n    }\n    const base = this;\n    const random = seedrandom3.alea(seed || util_exports.now().toString());\n    return datasetFromIteratorFn(async () => {\n      let seed2 = random.int32();\n      if (reshuffleEachIteration) {\n        seed2 += random.int32();\n      }\n      return (await base.iterator()).shuffle(bufferSize, seed2.toString());\n    }, this.size);\n  }\n  take(count2) {\n    const base = this;\n    let size;\n    if (this.size != null && this.size > count2) {\n      size = count2;\n    } else if (this.size != null && this.size <= count2) {\n      size = this.size;\n    } else {\n      size = null;\n    }\n    return datasetFromIteratorFn(async () => (await base.iterator()).take(count2), size);\n  }\n  async toArray() {\n    if (this.size === Infinity) {\n      throw new Error(\"Can not convert infinite data stream to array.\");\n    }\n    return (await this.iterator()).toArray();\n  }\n  async toArrayForTest() {\n    if (this.size === Infinity) {\n      throw new Error(\"Can not convert infinite data stream to array.\");\n    }\n    return (await this.iterator()).toArrayForTest();\n  }\n};\nDataset.MAX_BUFFER_SIZE = 1e4;\nfunction datasetFromIteratorFn(iteratorFn, size = null) {\n  return new class extends Dataset {\n    constructor() {\n      super(...arguments);\n      this.size = size;\n    }\n    async iterator() {\n      return iteratorFn();\n    }\n  }();\n}\nfunction array(items) {\n  return datasetFromIteratorFn(async () => iteratorFromItems(items), items.length);\n}\nfunction zip(datasets) {\n  if (!isIterable2(datasets)) {\n    throw new Error(\"The argument to zip() must be an object or array.\");\n  }\n  let size;\n  if (Array.isArray(datasets)) {\n    for (let i2 = 0; i2 < datasets.length; i2++) {\n      size = size == null ? datasets[i2].size : Math.min(size, datasets[i2].size);\n    }\n  } else if (datasets instanceof Object) {\n    for (const ds in datasets) {\n      size = size == null ? datasets[ds].size : Math.min(size, datasets[ds].size);\n    }\n  }\n  return datasetFromIteratorFn(async () => {\n    const streams = await deepMapAndAwaitAll(datasets, (d) => {\n      if (d instanceof Dataset) {\n        return { value: d.iterator(), recurse: false };\n      } else if (isIterable2(d)) {\n        return { value: null, recurse: true };\n      } else {\n        throw new Error(\"Leaves of the structure passed to zip() must be Datasets, not primitives.\");\n      }\n    });\n    return iteratorFromZipped(streams, ZipMismatchMode.SHORTEST);\n  }, size);\n}\nfunction deepBatchConcat(rows) {\n  if (rows === null) {\n    return null;\n  }\n  const exampleRow = rows[0];\n  if (canTensorify(exampleRow)) {\n    const value = batchConcat(rows);\n    return { value, recurse: false };\n  }\n  return { value: null, recurse: true };\n}\nfunction batchConcat(arrays) {\n  if (arrays.length === 0) {\n    throw new Error(\"Can't make a batch of zero elements.\");\n  }\n  if (arrays[0] instanceof Tensor) {\n    return stack(arrays);\n  } else {\n    return tensor(arrays);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/datasets/text_line_dataset.js\nvar TextLineDataset = class extends Dataset {\n  constructor(input2) {\n    super();\n    this.input = input2;\n  }\n  async iterator() {\n    const inputIterator = await this.input.iterator();\n    const utf8Iterator = inputIterator.decodeUTF8();\n    const lineIterator = utf8Iterator.split(\"\\n\").map((line) => {\n      if (line.endsWith(\"\\r\")) {\n        line = line.slice(0, -1);\n      }\n      return line;\n    });\n    return lineIterator;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/datasets/csv_dataset.js\nvar CODE_QUOTE = '\"';\nvar STATE_OUT = Symbol(\"out\");\nvar STATE_FIELD = Symbol(\"field\");\nvar STATE_QUOTE = Symbol(\"quote\");\nvar STATE_QUOTE_AFTER_QUOTE = Symbol(\"quoteafterquote\");\nvar STATE_WITHIN_QUOTE_IN_QUOTE = Symbol(\"quoteinquote\");\nvar CSVDataset = class extends Dataset {\n  constructor(input2, csvConfig) {\n    super();\n    this.input = input2;\n    this.hasHeader = true;\n    this.fullColumnNames = null;\n    this.columnNamesValidated = false;\n    this.columnConfigs = null;\n    this.configuredColumnsOnly = false;\n    this.delimiter = \",\";\n    this.delimWhitespace = false;\n    this.base = new TextLineDataset(input2);\n    if (!csvConfig) {\n      csvConfig = {};\n    }\n    this.hasHeader = csvConfig.hasHeader === false ? false : true;\n    this.fullColumnNames = csvConfig.columnNames;\n    this.columnConfigs = csvConfig.columnConfigs;\n    this.configuredColumnsOnly = csvConfig.configuredColumnsOnly;\n    if (csvConfig.delimWhitespace) {\n      util_exports.assert(csvConfig.delimiter == null, () => \"Delimiter should not be provided when delimWhitespace is true.\");\n      this.delimWhitespace = true;\n      this.delimiter = \" \";\n    } else {\n      this.delimiter = csvConfig.delimiter ? csvConfig.delimiter : \",\";\n    }\n  }\n  async columnNames() {\n    if (!this.columnNamesValidated) {\n      await this.setColumnNames();\n    }\n    return this.configuredColumnsOnly ? Object.keys(this.columnConfigs) : this.fullColumnNames;\n  }\n  async setColumnNames() {\n    const columnNamesFromFile = await this.maybeReadHeaderLine();\n    if (!this.fullColumnNames && !columnNamesFromFile) {\n      throw new Error(\"Column names must be provided if there is no header line.\");\n    } else if (this.fullColumnNames && columnNamesFromFile) {\n      util_exports.assert(columnNamesFromFile.length === this.fullColumnNames.length, () => \"The length of provided columnNames (\" + this.fullColumnNames.length.toString() + \") does not match the length of the header line read from file (\" + columnNamesFromFile.length.toString() + \").\");\n    }\n    if (!this.fullColumnNames) {\n      this.fullColumnNames = columnNamesFromFile;\n    }\n    const counts = this.fullColumnNames.reduce((countAcc, name) => {\n      countAcc[name] = countAcc[name] + 1 || 1;\n      return countAcc;\n    }, {});\n    const duplicateNames = Object.keys(counts).filter((name) => counts[name] > 1);\n    util_exports.assert(duplicateNames.length === 0, () => \"Duplicate column names found: \" + duplicateNames.toString());\n    if (this.columnConfigs) {\n      for (const key of Object.keys(this.columnConfigs)) {\n        const index = this.fullColumnNames.indexOf(key);\n        if (index === -1) {\n          throw new Error('The key \"' + key + '\" provided in columnConfigs does not match any of the column names (' + this.fullColumnNames.toString() + \").\");\n        }\n      }\n    }\n    this.columnNamesValidated = true;\n  }\n  async maybeReadHeaderLine() {\n    if (this.hasHeader) {\n      const iter = await this.base.iterator();\n      const firstElement = await iter.next();\n      if (firstElement.done) {\n        throw new Error(\"No data was found for CSV parsing.\");\n      }\n      const firstLine = firstElement.value;\n      const headers = this.parseRow(firstLine, false);\n      return headers;\n    } else {\n      return null;\n    }\n  }\n  async iterator() {\n    if (!this.columnNamesValidated) {\n      await this.setColumnNames();\n    }\n    let lines = await this.base.iterator();\n    if (this.hasHeader) {\n      lines = lines.skip(1);\n    }\n    return lines.map((x) => this.makeDataElement(x));\n  }\n  makeDataElement(line) {\n    const values = this.parseRow(line);\n    const features = {};\n    const labels = {};\n    for (let i2 = 0; i2 < this.fullColumnNames.length; i2++) {\n      const key = this.fullColumnNames[i2];\n      const config = this.columnConfigs ? this.columnConfigs[key] : null;\n      if (this.configuredColumnsOnly && !config) {\n        continue;\n      } else {\n        const value = values[i2];\n        let parsedValue = null;\n        if (value === \"\") {\n          if (config && config.default !== void 0) {\n            parsedValue = config.default;\n          } else if (config && (config.required || config.isLabel)) {\n            throw new Error(`Required column ${key} is empty in this line: ${line}`);\n          } else {\n            parsedValue = void 0;\n          }\n        } else {\n          const valueAsNum = Number(value);\n          if (isNaN(valueAsNum)) {\n            if (config && config.dtype === \"bool\") {\n              parsedValue = this.getBoolean(value);\n            } else {\n              parsedValue = value;\n            }\n          } else if (!config || !config.dtype) {\n            parsedValue = valueAsNum;\n          } else {\n            switch (config.dtype) {\n              case \"float32\":\n                parsedValue = valueAsNum;\n                break;\n              case \"int32\":\n                parsedValue = Math.floor(valueAsNum);\n                break;\n              case \"bool\":\n                parsedValue = this.getBoolean(value);\n                break;\n              default:\n                parsedValue = valueAsNum;\n            }\n          }\n        }\n        config && config.isLabel ? labels[key] = parsedValue : features[key] = parsedValue;\n      }\n    }\n    if (Object.keys(labels).length === 0) {\n      return features;\n    } else {\n      return { xs: features, ys: labels };\n    }\n  }\n  getBoolean(value) {\n    if (value === \"1\" || value.toLowerCase() === \"true\") {\n      return 1;\n    } else {\n      return 0;\n    }\n  }\n  parseRow(line, validateElementCount = true) {\n    const result = [];\n    let readOffset = 0;\n    const readLength = line.length;\n    let currentState = STATE_OUT;\n    for (let i2 = 0; i2 < readLength; i2++) {\n      switch (currentState) {\n        case STATE_OUT:\n          switch (line.charAt(i2)) {\n            case CODE_QUOTE:\n              readOffset = i2 + 1;\n              currentState = STATE_QUOTE;\n              break;\n            case this.delimiter:\n              readOffset = i2 + 1;\n              if (this.delimiter === \" \" && this.delimWhitespace) {\n                break;\n              }\n              result.push(\"\");\n              currentState = STATE_OUT;\n              break;\n            default:\n              currentState = STATE_FIELD;\n              readOffset = i2;\n              break;\n          }\n          break;\n        case STATE_FIELD:\n          switch (line.charAt(i2)) {\n            case this.delimiter:\n              result.push(line.substring(readOffset, i2));\n              currentState = STATE_OUT;\n              readOffset = i2 + 1;\n              break;\n            default:\n          }\n          break;\n        case STATE_QUOTE:\n          switch (line.charAt(i2)) {\n            case CODE_QUOTE:\n              currentState = STATE_QUOTE_AFTER_QUOTE;\n              break;\n            default:\n          }\n          break;\n        case STATE_QUOTE_AFTER_QUOTE:\n          switch (line.charAt(i2)) {\n            case this.delimiter:\n              result.push(line.substring(readOffset, i2 - 1));\n              currentState = STATE_OUT;\n              readOffset = i2 + 1;\n              break;\n            case CODE_QUOTE:\n              currentState = STATE_QUOTE;\n              break;\n            default:\n              currentState = STATE_WITHIN_QUOTE_IN_QUOTE;\n              break;\n          }\n          break;\n        case STATE_WITHIN_QUOTE_IN_QUOTE:\n          switch (line.charAt(i2)) {\n            case CODE_QUOTE:\n              currentState = STATE_QUOTE;\n              break;\n            default:\n          }\n          break;\n        default:\n      }\n    }\n    if (currentState === STATE_QUOTE_AFTER_QUOTE) {\n      result.push(line.substring(readOffset, readLength - 1));\n    } else {\n      result.push(line.substring(readOffset));\n    }\n    if (validateElementCount && result.length !== this.fullColumnNames.length) {\n      throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${result}`);\n    }\n    return result;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/microphone_iterator.js\nvar MicrophoneIterator = class extends LazyIterator {\n  constructor(microphoneConfig) {\n    super();\n    this.microphoneConfig = microphoneConfig;\n    this.isClosed = false;\n    this.fftSize = microphoneConfig.fftSize || 1024;\n    const fftSizeLog2 = Math.log2(this.fftSize);\n    if (this.fftSize < 0 || fftSizeLog2 < 4 || fftSizeLog2 > 14 || !Number.isInteger(fftSizeLog2)) {\n      throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);\n    }\n    this.numFrames = microphoneConfig.numFramesPerSpectrogram || 43;\n    this.sampleRateHz = microphoneConfig.sampleRateHz;\n    this.columnTruncateLength = microphoneConfig.columnTruncateLength || this.fftSize;\n    this.audioTrackConstraints = microphoneConfig.audioTrackConstraints;\n    this.smoothingTimeConstant = microphoneConfig.smoothingTimeConstant || 0;\n    this.includeSpectrogram = microphoneConfig.includeSpectrogram === false ? false : true;\n    this.includeWaveform = microphoneConfig.includeWaveform === true ? true : false;\n    if (!this.includeSpectrogram && !this.includeWaveform) {\n      throw new Error(\"Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.\");\n    }\n  }\n  summary() {\n    return `microphone`;\n  }\n  static async create(microphoneConfig = {}) {\n    if (!env().get(\"IS_BROWSER\")) {\n      throw new Error(\"microphone API is only supported in browser environment.\");\n    }\n    const microphoneIterator = new MicrophoneIterator(microphoneConfig);\n    await microphoneIterator.start();\n    return microphoneIterator;\n  }\n  async start() {\n    try {\n      this.stream = await navigator.mediaDevices.getUserMedia({\n        audio: this.audioTrackConstraints == null ? true : this.audioTrackConstraints,\n        video: false\n      });\n    } catch (e2) {\n      throw new Error(`Error thrown while initializing video stream: ${e2.message}`);\n    }\n    if (!this.stream) {\n      throw new Error(\"Could not obtain audio from microphone.\");\n    }\n    const ctxConstructor = window.AudioContext || window.webkitAudioContext;\n    this.audioContext = new ctxConstructor();\n    if (!this.sampleRateHz) {\n      this.sampleRateHz = this.audioContext.sampleRate;\n    } else if (this.audioContext.sampleRate !== this.sampleRateHz) {\n      throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);\n    }\n    const streamSource = this.audioContext.createMediaStreamSource(this.stream);\n    this.analyser = this.audioContext.createAnalyser();\n    this.analyser.fftSize = this.fftSize * 2;\n    this.analyser.smoothingTimeConstant = this.smoothingTimeConstant;\n    streamSource.connect(this.analyser);\n    this.freqData = new Float32Array(this.fftSize);\n    this.timeData = new Float32Array(this.fftSize);\n    return;\n  }\n  async next() {\n    if (this.isClosed) {\n      return { value: null, done: true };\n    }\n    let spectrogramTensor;\n    let waveformTensor;\n    const audioDataQueue = await this.getAudioData();\n    if (this.includeSpectrogram) {\n      const freqData = this.flattenQueue(audioDataQueue.freqDataQueue);\n      spectrogramTensor = this.getTensorFromAudioDataArray(freqData, [this.numFrames, this.columnTruncateLength, 1]);\n    }\n    if (this.includeWaveform) {\n      const timeData = this.flattenQueue(audioDataQueue.timeDataQueue);\n      waveformTensor = this.getTensorFromAudioDataArray(timeData, [this.numFrames * this.fftSize, 1]);\n    }\n    return {\n      value: { \"spectrogram\": spectrogramTensor, \"waveform\": waveformTensor },\n      done: false\n    };\n  }\n  async capture() {\n    return (await this.next()).value;\n  }\n  async getAudioData() {\n    const freqDataQueue = [];\n    const timeDataQueue = [];\n    let currentFrames = 0;\n    return new Promise((resolve) => {\n      const intervalID = setInterval(() => {\n        if (this.includeSpectrogram) {\n          this.analyser.getFloatFrequencyData(this.freqData);\n          if (this.freqData[0] === -Infinity) {\n            resolve({ freqDataQueue, timeDataQueue });\n          }\n          freqDataQueue.push(this.freqData.slice(0, this.columnTruncateLength));\n        }\n        if (this.includeWaveform) {\n          this.analyser.getFloatTimeDomainData(this.timeData);\n          timeDataQueue.push(this.timeData.slice());\n        }\n        if (++currentFrames === this.numFrames) {\n          clearInterval(intervalID);\n          resolve({ freqDataQueue, timeDataQueue });\n        }\n      }, this.fftSize / this.sampleRateHz * 1e3);\n    });\n  }\n  stop() {\n    if (!this.isClosed) {\n      this.isClosed = true;\n      this.analyser.disconnect();\n      this.audioContext.close();\n      if (this.stream != null && this.stream.getTracks().length > 0) {\n        this.stream.getTracks()[0].stop();\n      }\n    }\n  }\n  toArray() {\n    throw new Error(\"Can not convert infinite audio stream to array.\");\n  }\n  getSampleRate() {\n    return this.sampleRateHz;\n  }\n  flattenQueue(queue) {\n    const frameSize = queue[0].length;\n    const freqData = new Float32Array(queue.length * frameSize);\n    queue.forEach((data, i2) => freqData.set(data, i2 * frameSize));\n    return freqData;\n  }\n  getTensorFromAudioDataArray(freqData, shape) {\n    const vals = new Float32Array(util_exports.sizeFromShape(shape));\n    vals.set(freqData, vals.length - freqData.length);\n    return tensor(vals, shape);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/webcam_iterator.js\nvar WebcamIterator = class extends LazyIterator {\n  constructor(webcamVideoElement, webcamConfig) {\n    super();\n    this.webcamVideoElement = webcamVideoElement;\n    this.webcamConfig = webcamConfig;\n    this.isClosed = true;\n    this.resize = false;\n    if (this.needToResize()) {\n      this.resize = true;\n      this.cropSize = [this.webcamConfig.resizeHeight, this.webcamConfig.resizeWidth];\n      this.cropBoxInd = tensor1d([0], \"int32\");\n      if (this.webcamConfig.centerCrop) {\n        const widthCroppingRatio = this.webcamConfig.resizeWidth * 1 / this.webcamVideoElement.width;\n        const heightCroppingRatio = this.webcamConfig.resizeHeight * 1 / this.webcamVideoElement.height;\n        const widthCropStart = (1 - widthCroppingRatio) / 2;\n        const heightCropStart = (1 - heightCroppingRatio) / 2;\n        const widthCropEnd = widthCropStart + widthCroppingRatio;\n        const heightCropEnd = heightCroppingRatio + heightCropStart;\n        this.cropBox = tensor2d([heightCropStart, widthCropStart, heightCropEnd, widthCropEnd], [1, 4]);\n      } else {\n        this.cropBox = tensor2d([0, 0, 1, 1], [1, 4]);\n      }\n    }\n  }\n  summary() {\n    return `webcam`;\n  }\n  static async create(webcamVideoElement, webcamConfig = {}) {\n    if (!env().get(\"IS_BROWSER\")) {\n      throw new Error(\"tf.data.webcam is only supported in browser environment.\");\n    }\n    if (!webcamVideoElement) {\n      webcamVideoElement = document.createElement(\"video\");\n      if (!webcamConfig.resizeWidth || !webcamConfig.resizeHeight) {\n        throw new Error(\"Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.\");\n      }\n      webcamVideoElement.width = webcamConfig.resizeWidth;\n      webcamVideoElement.height = webcamConfig.resizeHeight;\n    }\n    const webcamIterator = new WebcamIterator(webcamVideoElement, webcamConfig);\n    await webcamIterator.start();\n    return webcamIterator;\n  }\n  async start() {\n    if (this.webcamConfig.facingMode) {\n      util_exports.assert(this.webcamConfig.facingMode === \"user\" || this.webcamConfig.facingMode === \"environment\", () => `Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);\n    }\n    try {\n      this.stream = await navigator.mediaDevices.getUserMedia({\n        video: {\n          deviceId: this.webcamConfig.deviceId,\n          facingMode: this.webcamConfig.facingMode ? this.webcamConfig.facingMode : \"user\",\n          width: this.webcamVideoElement.width,\n          height: this.webcamVideoElement.height\n        }\n      });\n    } catch (e2) {\n      e2.message = `Error thrown while initializing video stream: ${e2.message}`;\n      throw e2;\n    }\n    if (!this.stream) {\n      throw new Error(\"Could not obtain video from webcam.\");\n    }\n    try {\n      this.webcamVideoElement.srcObject = this.stream;\n    } catch (error) {\n      console.log(error);\n      this.webcamVideoElement.src = window.URL.createObjectURL(this.stream);\n    }\n    this.webcamVideoElement.play();\n    this.isClosed = false;\n    return new Promise((resolve) => {\n      this.webcamVideoElement.onloadedmetadata = () => {\n        resolve();\n      };\n    });\n  }\n  async next() {\n    if (this.isClosed) {\n      return { value: null, done: true };\n    }\n    let img;\n    try {\n      img = browser_exports.fromPixels(this.webcamVideoElement);\n    } catch (e2) {\n      throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(e2)}`);\n    }\n    if (this.resize) {\n      try {\n        return { value: this.cropAndResizeFrame(img), done: false };\n      } catch (e2) {\n        throw new Error(`Error thrown cropping the video: ${e2.message}`);\n      } finally {\n        img.dispose();\n      }\n    } else {\n      return { value: img, done: false };\n    }\n  }\n  needToResize() {\n    if (this.webcamConfig.resizeWidth && this.webcamConfig.resizeHeight && (this.webcamVideoElement.width !== this.webcamConfig.resizeWidth || this.webcamVideoElement.height !== this.webcamConfig.resizeHeight)) {\n      return true;\n    }\n    return false;\n  }\n  cropAndResizeFrame(img) {\n    return tidy(() => {\n      const expandedImage = expandDims(cast(img, \"float32\"), 0);\n      let resizedImage;\n      resizedImage = image.cropAndResize(expandedImage, this.cropBox, this.cropBoxInd, this.cropSize, \"bilinear\");\n      const shape = resizedImage.shape;\n      return reshape(resizedImage, shape.slice(1));\n    });\n  }\n  async capture() {\n    return (await this.next()).value;\n  }\n  stop() {\n    const tracks = this.stream.getTracks();\n    tracks.forEach((track) => track.stop());\n    try {\n      this.webcamVideoElement.srcObject = null;\n    } catch (error) {\n      console.log(error);\n      this.webcamVideoElement.src = null;\n    }\n    this.isClosed = true;\n  }\n  toArray() {\n    throw new Error(\"Can not convert infinite video stream to array.\");\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/datasource.js\nvar DataSource = class {\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/string_iterator.js\nvar StringIterator = class extends LazyIterator {\n  split(separator) {\n    return new SplitIterator(this, separator);\n  }\n};\nvar SplitIterator = class extends StringIterator {\n  constructor(upstream, separator) {\n    super();\n    this.upstream = upstream;\n    this.impl = new SplitIteratorImpl(upstream, separator);\n  }\n  summary() {\n    return this.impl.summary();\n  }\n  async next() {\n    return this.impl.next();\n  }\n};\nvar SplitIteratorImpl = class extends OneToManyIterator {\n  constructor(upstream, separator) {\n    super();\n    this.upstream = upstream;\n    this.separator = separator;\n    this.carryover = \"\";\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Split('${this.separator}')`;\n  }\n  async pump() {\n    const chunkResult = await this.upstream.next();\n    if (chunkResult.done) {\n      if (this.carryover === \"\") {\n        return false;\n      }\n      this.outputQueue.push(this.carryover);\n      this.carryover = \"\";\n      return true;\n    }\n    const lines = chunkResult.value.split(this.separator);\n    lines[0] = this.carryover + lines[0];\n    for (const line of lines.slice(0, -1)) {\n      this.outputQueue.push(line);\n    }\n    this.carryover = lines[lines.length - 1];\n    return true;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/byte_chunk_iterator.js\nvar ByteChunkIterator = class extends LazyIterator {\n  decodeUTF8() {\n    return new Utf8Iterator(this);\n  }\n};\nvar Utf8Iterator = class extends StringIterator {\n  constructor(upstream) {\n    super();\n    this.upstream = upstream;\n    this.impl = new Utf8IteratorImpl(upstream);\n  }\n  summary() {\n    return this.impl.summary();\n  }\n  async next() {\n    return this.impl.next();\n  }\n};\nvar Utf8IteratorImpl = class extends OneToManyIterator {\n  constructor(upstream) {\n    super();\n    this.upstream = upstream;\n    if (env().get(\"IS_BROWSER\")) {\n      this.decoder = new TextDecoder(\"utf-8\");\n    } else {\n      const { StringDecoder } = require_string_decoder();\n      this.decoder = new StringDecoder(\"utf8\");\n    }\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Utf8`;\n  }\n  async pump() {\n    const chunkResult = await this.upstream.next();\n    let chunk;\n    if (chunkResult.done) {\n      return false;\n    } else {\n      chunk = chunkResult.value;\n    }\n    let text;\n    if (env().get(\"IS_BROWSER\")) {\n      text = this.decoder.decode(chunk, { stream: true });\n    } else {\n      text = this.decoder.write(Buffer.from(chunk.buffer));\n    }\n    this.outputQueue.push(text);\n    return true;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/file_chunk_iterator.js\nvar FileChunkIterator = class extends ByteChunkIterator {\n  constructor(file, options = {}) {\n    super();\n    this.file = file;\n    this.options = options;\n    util_exports.assert(file instanceof Uint8Array || (env().get(\"IS_BROWSER\") ? file instanceof File || file instanceof Blob : false), () => \"FileChunkIterator only supports File, Blob and Uint8Array right now.\");\n    this.offset = options.offset || 0;\n    this.chunkSize = options.chunkSize || 1024 * 1024;\n  }\n  summary() {\n    return `FileChunks ${this.file}`;\n  }\n  async next() {\n    if (this.offset >= (this.file instanceof Uint8Array ? this.file.byteLength : this.file.size)) {\n      return { value: null, done: true };\n    }\n    const chunk = new Promise((resolve, reject) => {\n      const end = this.offset + this.chunkSize;\n      if (this.file instanceof Uint8Array) {\n        resolve(new Uint8Array(this.file.slice(this.offset, end)));\n      } else {\n        const fileReader = new FileReader();\n        fileReader.onload = (event) => {\n          let data = fileReader.result;\n          if (data instanceof ArrayBuffer) {\n            data = new Uint8Array(data);\n          }\n          if (!(data instanceof Uint8Array)) {\n            return reject(new TypeError(\"FileReader returned unknown type.\"));\n          }\n          resolve(data);\n        };\n        fileReader.onabort = (event) => {\n          return reject(new Error(\"Aborted\"));\n        };\n        fileReader.onerror = (event) => {\n          return reject(new Error(event.type));\n        };\n        const slice6 = this.file.slice(this.offset, end);\n        fileReader.readAsArrayBuffer(slice6);\n      }\n      this.offset = end;\n    });\n    return { value: await chunk, done: false };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/url_chunk_iterator.js\nasync function urlChunkIterator(url, options = {}, fetchFunc) {\n  let urlString;\n  let requestInit;\n  if (typeof url === \"string\") {\n    urlString = url;\n  } else {\n    urlString = url.url;\n    requestInit = getRequestInitFromRequest(url);\n  }\n  const response = await (fetchFunc || util_exports.fetch)(urlString, requestInit);\n  if (response.ok) {\n    const uint8Array = new Uint8Array(await response.arrayBuffer());\n    return new FileChunkIterator(uint8Array, options);\n  } else {\n    throw new Error(response.statusText);\n  }\n}\nvar getRequestInitFromRequest = (request) => {\n  const init2 = {\n    method: request.method,\n    headers: request.headers,\n    body: request.body,\n    mode: request.mode,\n    credentials: request.credentials,\n    cache: request.cache,\n    redirect: request.redirect,\n    referrer: request.referrer,\n    integrity: request.integrity\n  };\n  return init2;\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/util/source_util.js\nfunction isLocalPath(source) {\n  return typeof source === \"string\" && source.slice(0, 7) === \"file://\";\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/sources/file_data_source.js\nvar FileDataSource = class extends DataSource {\n  constructor(input2, options = {}) {\n    super();\n    this.input = input2;\n    this.options = options;\n  }\n  async iterator() {\n    if (isLocalPath(this.input) && env().get(\"IS_NODE\")) {\n      const fs = require_fs();\n      this.input = fs.readFileSync(this.input.slice(7));\n    }\n    return new FileChunkIterator(this.input, this.options);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/sources/url_data_source.js\nvar URLDataSource = class extends DataSource {\n  constructor(url, fileOptions = {}) {\n    super();\n    this.url = url;\n    this.fileOptions = fileOptions;\n  }\n  async iterator() {\n    if (isLocalPath(this.url)) {\n      return new FileDataSource(this.url, this.fileOptions).iterator();\n    } else {\n      return urlChunkIterator(this.url, this.fileOptions);\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/readers.js\nfunction csv(source, csvConfig = {}) {\n  return new CSVDataset(new URLDataSource(source), csvConfig);\n}\nfunction func(f) {\n  const iter = iteratorFromFunction(f);\n  return datasetFromIteratorFn(async () => iter);\n}\nfunction generator(generator2) {\n  return datasetFromIteratorFn(async () => {\n    const gen = await generator2();\n    return iteratorFromFunction(() => gen.next());\n  });\n}\nasync function webcam(webcamVideoElement, webcamConfig) {\n  return WebcamIterator.create(webcamVideoElement, webcamConfig);\n}\nasync function microphone(microphoneConfig) {\n  return MicrophoneIterator.create(microphoneConfig);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/version.js\nvar version4 = \"3.19.0\";\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/cpu_util.js\nfunction assertNotComplex(tensor2, opName) {\n  if (!Array.isArray(tensor2)) {\n    tensor2 = [tensor2];\n  }\n  tensor2.forEach((t2) => {\n    if (t2 != null) {\n      util_exports.assert(t2.dtype !== \"complex64\", () => `${opName} does not support complex64 tensors in the CPU backend.`);\n    }\n  });\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/backend_cpu.js\nvar whereImpl2 = kernel_impls_exports.whereImpl;\nvar MathBackendCPU = class extends KernelBackend {\n  constructor() {\n    super();\n    this.blockSize = 48;\n    this.firstUse = true;\n    this.data = new DataStorage(this, engine());\n  }\n  nextDataId() {\n    return MathBackendCPU.nextDataId++;\n  }\n  write(values, shape, dtype) {\n    if (this.firstUse) {\n      this.firstUse = false;\n      if (env().get(\"IS_NODE\")) {\n        backend_util_exports.warn(\"\\n============================\\nHi, looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, visit https://github.com/tensorflow/tfjs-node for more details. \\n============================\");\n      }\n    }\n    const dataId = { id: this.nextDataId() };\n    this.data.set(dataId, { values, dtype, refCount: 1 });\n    return dataId;\n  }\n  makeTensorInfo(shape, dtype, values) {\n    let outId;\n    if (dtype === \"string\" && values != null && values.length > 0 && util_exports.isString(values[0])) {\n      const encodedValues = values.map((d) => util_exports.encodeString(d));\n      outId = this.write(encodedValues, shape, dtype);\n    } else {\n      outId = this.write(values, shape, dtype);\n    }\n    return { dataId: outId, shape, dtype };\n  }\n  refCount(dataId) {\n    if (this.data.has(dataId)) {\n      const tensorData = this.data.get(dataId);\n      return tensorData.refCount;\n    }\n    return 0;\n  }\n  incRef(dataId) {\n    const tensorData = this.data.get(dataId);\n    tensorData.refCount++;\n  }\n  decRef(dataId) {\n    if (this.data.has(dataId)) {\n      const tensorData = this.data.get(dataId);\n      tensorData.refCount--;\n    }\n  }\n  move(dataId, values, shape, dtype, refCount) {\n    this.data.set(dataId, { values, dtype, refCount });\n  }\n  numDataIds() {\n    return this.data.numDataIds();\n  }\n  async read(dataId) {\n    return this.readSync(dataId);\n  }\n  readSync(dataId) {\n    const { dtype, complexTensorInfos } = this.data.get(dataId);\n    if (dtype === \"complex64\") {\n      const realValues = this.readSync(complexTensorInfos.real.dataId);\n      const imagValues = this.readSync(complexTensorInfos.imag.dataId);\n      return backend_util_exports.mergeRealAndImagArrays(realValues, imagValues);\n    }\n    return this.data.get(dataId).values;\n  }\n  bufferSync(t2) {\n    const data = this.readSync(t2.dataId);\n    if (t2.dtype === \"string\") {\n      try {\n        const strings = data.map((d) => util_exports.decodeString(d));\n        return buffer(t2.shape, t2.dtype, strings);\n      } catch (_a) {\n        throw new Error(\"Failed to decode encoded string bytes into utf-8\");\n      }\n    }\n    return buffer(t2.shape, t2.dtype, data);\n  }\n  makeOutput(values, shape, dtype) {\n    return engine().makeTensorFromTensorInfo(this.makeTensorInfo(shape, dtype, values), this);\n  }\n  disposeData(dataId, force = false) {\n    if (this.data.has(dataId)) {\n      this.data.get(dataId).refCount--;\n      if (!force && this.data.get(dataId).refCount > 0) {\n        return false;\n      }\n      const { complexTensorInfos } = this.data.get(dataId);\n      if (complexTensorInfos != null) {\n        this.disposeData(complexTensorInfos.real.dataId, true);\n        this.disposeData(complexTensorInfos.imag.dataId, true);\n      }\n      this.data.delete(dataId);\n    }\n    return true;\n  }\n  disposeIntermediateTensorInfo(tensorInfo) {\n    this.disposeData(tensorInfo.dataId);\n  }\n  async time(f) {\n    const start = util_exports.now();\n    f();\n    const kernelMs = util_exports.now() - start;\n    return { kernelMs };\n  }\n  memory() {\n    return {\n      unreliable: true,\n      reasons: [\"The reported memory is an upper bound. Due to automatic garbage collection, the true allocated memory may be less.\"]\n    };\n  }\n  where(condition) {\n    assertNotComplex([condition], \"where\");\n    const condVals = this.readSync(condition.dataId);\n    return whereImpl2(condition.shape, condVals);\n  }\n  dispose() {\n  }\n  floatPrecision() {\n    return 32;\n  }\n  epsilon() {\n    return super.epsilon();\n  }\n};\nMathBackendCPU.nextDataId = 0;\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/shared.js\nvar shared_exports = {};\n__export(shared_exports, {\n  addImpl: () => addImpl,\n  bincountImpl: () => bincountImpl,\n  bincountReduceImpl: () => bincountReduceImpl,\n  ceilImpl: () => ceilImpl,\n  concatImpl: () => concatImpl,\n  equalImpl: () => equalImpl,\n  expImpl: () => expImpl,\n  expm1Impl: () => expm1Impl,\n  floorImpl: () => floorImpl,\n  gatherNdImpl: () => gatherNdImpl,\n  gatherV2Impl: () => gatherV2Impl,\n  greaterEqualImpl: () => greaterEqualImpl,\n  greaterImpl: () => greaterImpl,\n  lessEqualImpl: () => lessEqualImpl,\n  lessImpl: () => lessImpl,\n  linSpaceImpl: () => linSpaceImpl,\n  logImpl: () => logImpl,\n  maxImpl: () => maxImpl,\n  maximumImpl: () => maximumImpl,\n  minimumImpl: () => minimumImpl,\n  multiplyImpl: () => multiplyImpl,\n  negImpl: () => negImpl,\n  notEqualImpl: () => notEqualImpl,\n  prodImpl: () => prodImpl,\n  rangeImpl: () => rangeImpl,\n  rsqrtImpl: () => rsqrtImpl,\n  scatterImpl: () => scatterImpl,\n  sigmoidImpl: () => sigmoidImpl,\n  simpleAbsImpl: () => simpleAbsImpl,\n  sliceImpl: () => sliceImpl,\n  sparseFillEmptyRowsImpl: () => sparseFillEmptyRowsImpl,\n  sparseReshapeImpl: () => sparseReshapeImpl,\n  sparseSegmentReductionImpl: () => sparseSegmentReductionImpl,\n  sqrtImpl: () => sqrtImpl,\n  squaredDifferenceImpl: () => squaredDifferenceImpl,\n  stridedSliceImpl: () => stridedSliceImpl,\n  stringNGramsImpl: () => stringNGramsImpl,\n  stringSplitImpl: () => stringSplitImpl,\n  stringToHashBucketFastImpl: () => stringToHashBucketFastImpl,\n  subImpl: () => subImpl,\n  tileImpl: () => tileImpl,\n  topKImpl: () => topKImpl,\n  transposeImpl: () => transposeImpl,\n  uniqueImpl: () => uniqueImpl\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Abs.js\nfunction simpleAbsImpl(vals) {\n  const resultValues = new Float32Array(vals.length);\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    resultValues[i2] = Math.abs(vals[i2]);\n  }\n  return resultValues;\n}\nvar abs2 = (args) => {\n  const { x } = args.inputs;\n  const cpuBackend = args.backend;\n  assertNotComplex(x, \"abs\");\n  let resultValues = new Float32Array(util_exports.sizeFromShape(x.shape));\n  const values = cpuBackend.data.get(x.dataId).values;\n  resultValues = simpleAbsImpl(values);\n  return cpuBackend.makeOutput(resultValues, x.shape, x.dtype);\n};\nvar absConfig = {\n  kernelName: Abs,\n  backendName: \"cpu\",\n  kernelFunc: abs2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/binary_impl.js\nfunction createSimpleBinaryKernelImpl(op2) {\n  return (aShape, bShape, aVals, bVals, dtype) => {\n    const newShape = backend_util_exports.assertAndGetBroadcastShape(aShape, bShape);\n    const resultRank = newShape.length;\n    const resultStrides = util_exports.computeStrides(newShape);\n    const resultSize = util_exports.sizeFromShape(newShape);\n    const result = util_exports.getTypedArrayFromDType(dtype, resultSize);\n    const aRank = aShape.length;\n    const bRank = bShape.length;\n    const aStrides = util_exports.computeStrides(aShape);\n    const bStrides = util_exports.computeStrides(bShape);\n    const aBroadcastDims = backend_util_exports.getBroadcastDims(aShape, newShape);\n    const bBroadcastDims = backend_util_exports.getBroadcastDims(bShape, newShape);\n    if (aBroadcastDims.length + bBroadcastDims.length === 0) {\n      for (let i2 = 0; i2 < result.length; ++i2) {\n        result[i2] = op2(aVals[i2 % aVals.length], bVals[i2 % bVals.length]);\n      }\n    } else {\n      for (let i2 = 0; i2 < result.length; ++i2) {\n        const loc = util_exports.indexToLoc(i2, resultRank, resultStrides);\n        const aLoc = loc.slice(-aRank);\n        aBroadcastDims.forEach((d) => aLoc[d] = 0);\n        const aIndex = util_exports.locToIndex(aLoc, aRank, aStrides);\n        const bLoc = loc.slice(-bRank);\n        bBroadcastDims.forEach((d) => bLoc[d] = 0);\n        const bIndex = util_exports.locToIndex(bLoc, bRank, bStrides);\n        result[i2] = op2(aVals[aIndex], bVals[bIndex]);\n      }\n    }\n    return [result, newShape];\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Complex.js\nfunction complex2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { real: real5, imag: imag5 } = inputs;\n  const realVals = backend2.data.get(real5.dataId).values;\n  const imagVals = backend2.data.get(imag5.dataId).values;\n  const complexInfo = backend2.makeTensorInfo(real5.shape, \"complex64\");\n  const complex5 = backend2.data.get(complexInfo.dataId);\n  complex5.complexTensorInfos = {\n    real: backend2.makeTensorInfo(real5.shape, \"float32\", realVals),\n    imag: backend2.makeTensorInfo(imag5.shape, \"float32\", imagVals)\n  };\n  return complexInfo;\n}\nvar complexConfig = {\n  kernelName: Complex,\n  backendName: \"cpu\",\n  kernelFunc: complex2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/zeros_impl.js\nfunction zeros3(backend2, shape, dtype = \"float32\") {\n  if (dtype === \"complex64\") {\n    const real5 = zeros3(backend2, shape, \"float32\");\n    const imag5 = zeros3(backend2, shape, \"float32\");\n    return complex2({ inputs: { real: real5, imag: imag5 }, backend: backend2 });\n  }\n  const values = util_exports.makeZerosTypedArray(util_exports.sizeFromShape(shape), dtype);\n  return backend2.makeTensorInfo(shape, dtype, values);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Identity.js\nfunction identity2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  backend2.incRef(x.dataId);\n  return { dataId: x.dataId, shape: x.shape, dtype: x.dtype };\n}\nvar identityConfig = {\n  kernelName: Identity,\n  backendName: \"cpu\",\n  kernelFunc: identity2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Real.js\nfunction real2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const real5 = backend2.data.get(input2.dataId).complexTensorInfos.real;\n  const realVal = backend2.data.get(real5.dataId).values;\n  return backend2.makeTensorInfo(real5.shape, real5.dtype, realVal);\n}\nvar realConfig = {\n  kernelName: Real,\n  backendName: \"cpu\",\n  kernelFunc: real2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Cast.js\nfunction cast3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { dtype } = attrs;\n  if (dtype === \"complex64\") {\n    if (x.dtype === \"complex64\") {\n      return identity2({ inputs: { x }, backend: backend2 });\n    }\n    const zerosTensorInfo = zeros3(backend2, x.shape, x.dtype);\n    const floatX = cast3({ inputs: { x }, backend: backend2, attrs: { dtype: \"float32\" } });\n    const result = complex2({ inputs: { real: floatX, imag: zerosTensorInfo }, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(zerosTensorInfo);\n    backend2.disposeIntermediateTensorInfo(floatX);\n    return result;\n  }\n  if (x.dtype === \"complex64\") {\n    const realPart = real2({ inputs: { input: x }, backend: backend2 });\n    const result = cast3({ inputs: { x: realPart }, backend: backend2, attrs: { dtype } });\n    backend2.disposeIntermediateTensorInfo(realPart);\n    return result;\n  }\n  if (!util_exports.hasEncodingLoss(x.dtype, dtype)) {\n    const result = identity2({ inputs: { x }, backend: backend2 });\n    return { dataId: result.dataId, shape: result.shape, dtype };\n  }\n  if (dtype === \"int32\") {\n    const values = backend2.data.get(x.dataId).values;\n    const resultValues = Int32Array.from(values);\n    return backend2.makeTensorInfo(x.shape, \"int32\", resultValues);\n  }\n  if (dtype === \"bool\") {\n    const xVals = backend2.data.get(x.dataId).values;\n    const zero = util_exports.toTypedArray([0], x.dtype);\n    const [resultData, resultShape] = createSimpleBinaryKernelImpl((a, b) => a !== b ? 1 : 0)(x.shape, [], xVals, zero, \"bool\");\n    return backend2.makeTensorInfo(resultShape, \"bool\", resultData);\n  }\n  throw new Error(`Error in Cast: failed to cast ${x.dtype} to ${dtype}`);\n}\nvar castConfig = {\n  kernelName: Cast,\n  backendName: \"cpu\",\n  kernelFunc: cast3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/binary_utils.js\nfunction binaryKernelFunc(name, simpleImpl, complexImpl, dtype) {\n  if (complexImpl == null) {\n    return ({ inputs, backend: backend2 }) => {\n      const { a, b } = inputs;\n      const cpuBackend = backend2;\n      assertNotComplex([a, b], name);\n      const aVals = cpuBackend.data.get(a.dataId).values;\n      const bVals = cpuBackend.data.get(b.dataId).values;\n      const decodedAVals = a.dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(aVals) : aVals;\n      const decodedBVals = a.dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(bVals) : bVals;\n      const $dtype = dtype || a.dtype;\n      const [resultData, resultShape] = simpleImpl(a.shape, b.shape, decodedAVals, decodedBVals, $dtype);\n      return cpuBackend.makeTensorInfo(resultShape, $dtype, resultData);\n    };\n  }\n  return ({ inputs, backend: backend2 }) => {\n    const { a, b } = inputs;\n    const cpuBackend = backend2;\n    if (a.dtype === \"complex64\" || b.dtype === \"complex64\") {\n      const $aComplex = cast3({ inputs: { x: a }, backend: cpuBackend, attrs: { dtype: \"complex64\" } });\n      const $aComplexVals = cpuBackend.data.get($aComplex.dataId);\n      const aReal = $aComplexVals.complexTensorInfos.real;\n      const aImag = $aComplexVals.complexTensorInfos.imag;\n      const aRealVals = cpuBackend.data.get(aReal.dataId).values;\n      const aImagVals = cpuBackend.data.get(aImag.dataId).values;\n      const $bComplex = cast3({ inputs: { x: b }, backend: cpuBackend, attrs: { dtype: \"complex64\" } });\n      const $bComplexVals = cpuBackend.data.get($bComplex.dataId);\n      const bReal = $bComplexVals.complexTensorInfos.real;\n      const bImag = $bComplexVals.complexTensorInfos.imag;\n      const bRealVals = cpuBackend.data.get(bReal.dataId).values;\n      const bImagVals = cpuBackend.data.get(bImag.dataId).values;\n      const [resultRealData, resultImagData, resultShape] = complexImpl(a.shape, b.shape, aRealVals, aImagVals, bRealVals, bImagVals);\n      const resultReal = cpuBackend.makeTensorInfo(resultShape, \"float32\", resultRealData);\n      const resultImag = cpuBackend.makeTensorInfo(resultShape, \"float32\", resultImagData);\n      const result = complex2({ inputs: { real: resultReal, imag: resultImag }, backend: cpuBackend });\n      cpuBackend.disposeIntermediateTensorInfo($aComplex);\n      cpuBackend.disposeIntermediateTensorInfo($bComplex);\n      cpuBackend.disposeIntermediateTensorInfo(resultReal);\n      cpuBackend.disposeIntermediateTensorInfo(resultImag);\n      return result;\n    } else {\n      const aVals = cpuBackend.data.get(a.dataId).values;\n      const bVals = cpuBackend.data.get(b.dataId).values;\n      const $dtype = dtype || a.dtype;\n      const [resultData, resultShape] = simpleImpl(a.shape, b.shape, aVals, bVals, $dtype);\n      return cpuBackend.makeTensorInfo(resultShape, $dtype, resultData);\n    }\n  };\n}\nfunction createComplexBinaryKernelImpl(op2) {\n  return (aShape, bShape, aRealVals, aImagVals, bRealVals, bImagVals) => {\n    const resultShape = backend_util_exports.assertAndGetBroadcastShape(aShape, bShape);\n    const resultSize = util_exports.sizeFromShape(resultShape);\n    const resultRank = resultShape.length;\n    const resultStrides = util_exports.computeStrides(resultShape);\n    const resultRealVals = util_exports.getTypedArrayFromDType(\"float32\", resultSize);\n    const resultImagVals = util_exports.getTypedArrayFromDType(\"float32\", resultSize);\n    const aBroadcastDims = backend_util_exports.getBroadcastDims(aShape, resultShape);\n    const bBroadcastDims = backend_util_exports.getBroadcastDims(bShape, resultShape);\n    const aVals = backend_util_exports.mergeRealAndImagArrays(aRealVals, aImagVals);\n    const bVals = backend_util_exports.mergeRealAndImagArrays(bRealVals, bImagVals);\n    const aRank = aShape.length;\n    const aStrides = util_exports.computeStrides(aShape);\n    const bRank = bShape.length;\n    const bStrides = util_exports.computeStrides(bShape);\n    if (aBroadcastDims.length + bBroadcastDims.length === 0) {\n      for (let i2 = 0; i2 < resultRealVals.length; i2++) {\n        const aIdx = i2 % aVals.length;\n        const bIdx = i2 % bVals.length;\n        const result = op2(aVals[aIdx * 2], aVals[aIdx * 2 + 1], bVals[bIdx * 2], bVals[bIdx * 2 + 1]);\n        resultRealVals[i2] = result.real;\n        resultImagVals[i2] = result.imag;\n      }\n    } else {\n      for (let i2 = 0; i2 < resultRealVals.length; i2++) {\n        const loc = util_exports.indexToLoc(i2, resultRank, resultStrides);\n        const aLoc = loc.slice(-aRank);\n        aBroadcastDims.forEach((d) => aLoc[d] = 0);\n        const aIndex = util_exports.locToIndex(aLoc, aRank, aStrides);\n        const bLoc = loc.slice(-bRank);\n        bBroadcastDims.forEach((d) => bLoc[d] = 0);\n        const bIndex = util_exports.locToIndex(bLoc, bRank, bStrides);\n        const opResult = op2(aVals[aIndex * 2], aVals[aIndex * 2 + 1], bVals[bIndex * 2], bVals[bIndex * 2 + 1]);\n        resultRealVals[i2] = opResult.real;\n        resultImagVals[i2] = opResult.imag;\n      }\n    }\n    return [resultRealVals, resultImagVals, resultShape];\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Add.js\nvar addImpl = createSimpleBinaryKernelImpl((a, b) => a + b);\nvar addComplexImpl = createComplexBinaryKernelImpl((aReal, aImag, bReal, bImag) => {\n  return { real: aReal + bReal, imag: aImag + bImag };\n});\nvar add4 = binaryKernelFunc(Add, addImpl, addComplexImpl);\nvar addConfig = {\n  kernelName: Add,\n  backendName: \"cpu\",\n  kernelFunc: add4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Bincount_impl.js\nfunction bincountImpl(xVals, weightsVals, weightsDtype, weightsShape, size) {\n  const weightsSize = util_exports.sizeFromShape(weightsShape);\n  const outVals = util_exports.makeZerosTypedArray(size, weightsDtype);\n  for (let i2 = 0; i2 < xVals.length; i2++) {\n    const value = xVals[i2];\n    if (value < 0) {\n      throw new Error(\"Input x must be non-negative!\");\n    }\n    if (value >= size) {\n      continue;\n    }\n    if (weightsSize > 0) {\n      outVals[value] += weightsVals[i2];\n    } else {\n      outVals[value] += 1;\n    }\n  }\n  return outVals;\n}\nfunction bincountReduceImpl(xBuf, weightsBuf, size, binaryOutput = false) {\n  const numRows = xBuf.shape[0];\n  const numCols = xBuf.shape[1];\n  const outBuf = buffer([numRows, size], weightsBuf.dtype);\n  for (let i2 = 0; i2 < numRows; i2++) {\n    for (let j = 0; j < numCols; j++) {\n      const value = xBuf.get(i2, j);\n      if (value < 0) {\n        throw new Error(\"Input x must be non-negative!\");\n      }\n      if (value >= size) {\n        continue;\n      }\n      if (binaryOutput) {\n        outBuf.set(1, i2, value);\n      } else {\n        if (weightsBuf.size > 0) {\n          outBuf.set(outBuf.get(i2, value) + weightsBuf.get(i2, j), i2, value);\n        } else {\n          outBuf.set(outBuf.get(i2, value) + 1, i2, value);\n        }\n      }\n    }\n  }\n  return outBuf;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/unary_impl.js\nfunction createSimpleUnaryImpl(op2) {\n  return (values, dtype, attrs) => {\n    const newValues = util_exports.getTypedArrayFromDType(dtype, values.length);\n    for (let i2 = 0; i2 < values.length; ++i2) {\n      newValues[i2] = op2(values[i2], attrs);\n    }\n    return newValues;\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/unary_utils.js\nfunction unaryKernelFunc(name, op2, dtype) {\n  return ({ inputs, attrs, backend: backend2 }) => {\n    const { x } = inputs;\n    assertNotComplex(x, name);\n    if (x.dtype === \"string\" || dtype === \"string\") {\n      throw new Error(\"unaryKernelFunc does not support string input/output\");\n    }\n    const cpuBackend = backend2;\n    const values = cpuBackend.data.get(x.dataId).values;\n    const xSize = util_exports.sizeFromShape(x.shape);\n    const $dtype = dtype || x.dtype;\n    const newValues = util_exports.getArrayFromDType($dtype, xSize);\n    for (let i2 = 0; i2 < xSize; ++i2) {\n      newValues[i2] = op2(values[i2], attrs);\n    }\n    return cpuBackend.makeTensorInfo(x.shape, $dtype, newValues);\n  };\n}\nfunction unaryKernelFuncFromImpl(name, unaryImpl, dtype) {\n  return ({ inputs, attrs, backend: backend2 }) => {\n    const { x } = inputs;\n    assertNotComplex(x, name);\n    if (x.dtype === \"string\" || dtype === \"string\") {\n      throw new Error(\"unaryKernelFunc does not support string input/output\");\n    }\n    const cpuBackend = backend2;\n    const values = cpuBackend.data.get(x.dataId).values;\n    const $dtype = dtype || x.dtype;\n    const newValues = unaryImpl(values, $dtype, attrs);\n    return cpuBackend.makeTensorInfo(x.shape, $dtype, newValues);\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Ceil.js\nvar ceilImpl = createSimpleUnaryImpl((xi) => Math.ceil(xi));\nvar ceil2 = unaryKernelFuncFromImpl(Ceil, ceilImpl);\nvar ceilConfig = {\n  kernelName: Ceil,\n  backendName: \"cpu\",\n  kernelFunc: ceil2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Concat_impl.js\nfunction concatImpl(inputs, outShape, dtype, simplyConcat) {\n  const outVals = util_exports.getArrayFromDType(dtype, util_exports.sizeFromShape(outShape));\n  if (simplyConcat && dtype !== \"string\") {\n    let offset = 0;\n    inputs.forEach((input2) => {\n      const size = util_exports.sizeFromShape(input2.shape);\n      outVals.set(input2.vals, offset);\n      offset += size;\n    });\n  } else {\n    let colOffset = 0;\n    inputs.forEach((input2) => {\n      const decodedData = dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(input2.vals) : input2.vals;\n      let tIdx = 0;\n      for (let row = 0; row < input2.shape[0]; ++row) {\n        const resIdx = row * outShape[1] + colOffset;\n        for (let col = 0; col < input2.shape[1]; ++col) {\n          outVals[resIdx + col] = decodedData[tIdx++];\n        }\n      }\n      colOffset += input2.shape[1];\n    });\n  }\n  return outVals;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Equal.js\nvar equalImpl = createSimpleBinaryKernelImpl((a, b) => a === b ? 1 : 0);\nvar equal2 = binaryKernelFunc(Equal, equalImpl, null, \"bool\");\nvar equalConfig = {\n  kernelName: Equal,\n  backendName: \"cpu\",\n  kernelFunc: equal2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Exp.js\nvar expImpl = createSimpleUnaryImpl((xi) => Math.exp(xi));\nvar exp2 = unaryKernelFuncFromImpl(Exp, expImpl, \"float32\");\nvar expConfig = {\n  kernelName: Exp,\n  backendName: \"cpu\",\n  kernelFunc: exp2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Expm1.js\nvar expm1Impl = createSimpleUnaryImpl((xi) => Math.expm1(xi));\nvar expm12 = unaryKernelFuncFromImpl(Expm1, expm1Impl);\nvar expm1Config = {\n  kernelName: Expm1,\n  backendName: \"cpu\",\n  kernelFunc: expm12\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Floor.js\nvar floorImpl = createSimpleUnaryImpl((xi) => Math.floor(xi));\nvar floor2 = unaryKernelFuncFromImpl(Floor, floorImpl);\nvar floorConfig = {\n  kernelName: Floor,\n  backendName: \"cpu\",\n  kernelFunc: floor2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/GatherNd_Impl.js\nfunction gatherNdImpl(indicesData, paramsBuf, dtype, numSlices, sliceRank, sliceSize, strides, paramsShape, paramsSize) {\n  const outBuf = buffer([numSlices, sliceSize], dtype);\n  for (let i2 = 0; i2 < numSlices; i2++) {\n    const index = [];\n    let flattenIndex = 0;\n    for (let j = 0; j < sliceRank; j++) {\n      const dim = indicesData[i2 * sliceRank + j];\n      flattenIndex += dim * strides[j];\n      index.push(dim);\n    }\n    if (flattenIndex < 0 || flattenIndex >= paramsSize / sliceSize) {\n      throw new Error(`Invalid indices: ${index} does not index into ${paramsShape}`);\n    }\n    for (let k = 0; k < sliceSize; k++) {\n      outBuf.values[i2 * sliceSize + k] = paramsBuf.get(...paramsBuf.indexToLoc(flattenIndex * sliceSize + k));\n    }\n  }\n  return outBuf;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/GatherV2_impl.js\nfunction gatherV2Impl(xBuf, indicesBuf, flattenOutputShape) {\n  const outBuf = buffer(flattenOutputShape, xBuf.dtype);\n  for (let i2 = 0; i2 < outBuf.size; ++i2) {\n    const newLoc = outBuf.indexToLoc(i2);\n    const originalLoc = newLoc.slice();\n    const batchIdx = originalLoc[0];\n    const indicesIdx = originalLoc[2];\n    const indicesIndex = indicesBuf.locToIndex([batchIdx, indicesIdx]);\n    originalLoc[2] = indicesBuf.values[indicesIndex];\n    const originalIndex = xBuf.locToIndex(originalLoc);\n    if (0 <= originalIndex && originalIndex < xBuf.values.length) {\n      outBuf.values[i2] = xBuf.values[originalIndex];\n    }\n  }\n  return outBuf;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Greater.js\nvar greaterImpl = createSimpleBinaryKernelImpl((a, b) => a > b ? 1 : 0);\nvar greater3 = binaryKernelFunc(Greater, greaterImpl, null, \"bool\");\nvar greaterConfig = {\n  kernelName: Greater,\n  backendName: \"cpu\",\n  kernelFunc: greater3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/GreaterEqual.js\nvar greaterEqualImpl = createSimpleBinaryKernelImpl((a, b) => a >= b ? 1 : 0);\nvar greaterEqual2 = binaryKernelFunc(GreaterEqual, greaterEqualImpl, null, \"bool\");\nvar greaterEqualConfig = {\n  kernelName: GreaterEqual,\n  backendName: \"cpu\",\n  kernelFunc: greaterEqual2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Less.js\nvar lessImpl = createSimpleBinaryKernelImpl((a, b) => a < b ? 1 : 0);\nvar less3 = binaryKernelFunc(Less, lessImpl, null, \"bool\");\nvar lessConfig = {\n  kernelName: Less,\n  backendName: \"cpu\",\n  kernelFunc: less3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LessEqual.js\nvar lessEqualImpl = createSimpleBinaryKernelImpl((a, b) => a <= b ? 1 : 0);\nvar lessEqual2 = binaryKernelFunc(LessEqual, lessEqualImpl, null, \"bool\");\nvar lessEqualConfig = {\n  kernelName: LessEqual,\n  backendName: \"cpu\",\n  kernelFunc: lessEqual2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LinSpace_impl.js\nfunction linSpaceImpl(start, stop, num) {\n  const step5 = (stop - start) / (num - 1);\n  const values = util_exports.makeZerosTypedArray(num, \"float32\");\n  values[0] = start;\n  for (let i2 = 1; i2 < values.length; i2++) {\n    values[i2] = values[i2 - 1] + step5;\n  }\n  return values;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Log.js\nvar logImpl = createSimpleUnaryImpl((xi) => Math.log(xi));\nvar log3 = unaryKernelFuncFromImpl(Log, logImpl);\nvar logConfig = {\n  kernelName: Log,\n  backendName: \"cpu\",\n  kernelFunc: log3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Max_impl.js\nfunction maxImpl(aVals, reduceSize, outShape, dtype) {\n  const vals = util_exports.getTypedArrayFromDType(dtype, util_exports.sizeFromShape(outShape));\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let max7 = aVals[offset];\n    for (let j = 0; j < reduceSize; ++j) {\n      const value = aVals[offset + j];\n      if (Number.isNaN(value) || value > max7) {\n        max7 = value;\n      }\n    }\n    vals[i2] = max7;\n  }\n  return vals;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Maximum.js\nvar maximumImpl = createSimpleBinaryKernelImpl((aValue, bValue) => Math.max(aValue, bValue));\nvar maximum3 = binaryKernelFunc(Maximum, maximumImpl);\nvar maximumConfig = {\n  kernelName: Maximum,\n  backendName: \"cpu\",\n  kernelFunc: maximum3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Minimum.js\nvar minimumImpl = createSimpleBinaryKernelImpl((aValue, bValue) => Math.min(aValue, bValue));\nvar minimum3 = binaryKernelFunc(Minimum, minimumImpl);\nvar minimumConfig = {\n  kernelName: Minimum,\n  backendName: \"cpu\",\n  kernelFunc: minimum3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Multiply.js\nvar multiplyImpl = createSimpleBinaryKernelImpl((aValue, bValue) => aValue * bValue);\nvar multiplyComplexImpl = createComplexBinaryKernelImpl((aReal, aImag, bReal, bImag) => {\n  return {\n    real: aReal * bReal - aImag * bImag,\n    imag: aReal * bImag + aImag * bReal\n  };\n});\nvar multiply2 = binaryKernelFunc(Multiply, multiplyImpl, multiplyComplexImpl);\nvar multiplyConfig = {\n  kernelName: Multiply,\n  backendName: \"cpu\",\n  kernelFunc: multiply2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Neg.js\nfunction negImpl(xVals, xShape, xDtype) {\n  const minusOne = util_exports.createScalarValue(-1, xDtype);\n  return multiplyImpl([], xShape, minusOne, xVals, xDtype);\n}\nfunction neg2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  assertNotComplex(x, \"neg\");\n  const xVals = backend2.data.get(x.dataId).values;\n  const [res, newShape] = negImpl(xVals, x.shape, x.dtype);\n  return backend2.makeTensorInfo(newShape, x.dtype, res);\n}\nvar negConfig = {\n  kernelName: Neg,\n  backendName: \"cpu\",\n  kernelFunc: neg2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/NotEqual.js\nvar notEqualImpl = createSimpleBinaryKernelImpl((a, b) => a !== b ? 1 : 0);\nvar notEqual2 = binaryKernelFunc(NotEqual, notEqualImpl, null, \"bool\");\nvar notEqualConfig = {\n  kernelName: NotEqual,\n  backendName: \"cpu\",\n  kernelFunc: notEqual2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Transpose_impl.js\nfunction transposeImpl(xVals, xShape, dtype, perm, newShape) {\n  const xRank = xShape.length;\n  const xSize = util_exports.sizeFromShape(xShape);\n  const xStrides = util_exports.computeStrides(xShape);\n  const newStrides = util_exports.computeStrides(newShape);\n  const result = util_exports.getTypedArrayFromDType(dtype, util_exports.sizeFromShape(newShape));\n  for (let i2 = 0; i2 < xSize; ++i2) {\n    const loc = util_exports.indexToLoc(i2, xRank, xStrides);\n    const newLoc = new Array(loc.length);\n    for (let i3 = 0; i3 < newLoc.length; i3++) {\n      newLoc[i3] = loc[perm[i3]];\n    }\n    const newIndex = util_exports.locToIndex(newLoc, xRank, newStrides);\n    result[newIndex] = xVals[i2];\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Transpose.js\nfunction transpose2(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { x } = inputs;\n  const { perm } = attrs;\n  assertNotComplex(x, \"transpose\");\n  const xRank = x.shape.length;\n  const newShape = new Array(xRank);\n  for (let i2 = 0; i2 < newShape.length; i2++) {\n    newShape[i2] = x.shape[perm[i2]];\n  }\n  const values = backend2.data.get(x.dataId).values;\n  const result = transposeImpl(values, x.shape, x.dtype, perm, newShape);\n  const dataId = backend2.write(result, newShape, x.dtype);\n  return { dataId, shape: newShape, dtype: x.dtype };\n}\nvar transposeConfig = {\n  kernelName: Transpose,\n  backendName: \"cpu\",\n  kernelFunc: transpose2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Prod.js\nfunction prodImpl(xShape, xDtype, xVals, reductionAxes) {\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(xShape, reductionAxes);\n  const outDtype = upcastType(xDtype, \"int32\");\n  const outVals = util_exports.makeZerosTypedArray(util_exports.sizeFromShape(outShape), outDtype);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  for (let i2 = 0; i2 < outVals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let prod6 = 1;\n    for (let j = 0; j < reduceSize; ++j) {\n      prod6 *= xVals[offset + j];\n    }\n    outVals[i2] = prod6;\n  }\n  return { outVals, outShape, outDtype };\n}\nfunction prod2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  assertNotComplex(x, \"prod\");\n  const xRank = x.shape.length;\n  const axes = util_exports.parseAxisParam(axis, x.shape);\n  const permutation = backend_util_exports.getAxesPermutation(axes, xRank);\n  let reductionAxes = axes;\n  let permutedX = x;\n  const intermediateTensorInfos = [];\n  if (permutation != null) {\n    permutedX = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutation } });\n    intermediateTensorInfos.push(permutedX);\n    reductionAxes = backend_util_exports.getInnerMostAxes(reductionAxes.length, xRank);\n  }\n  const xVals = backend2.data.get(permutedX.dataId).values;\n  const { outVals, outShape, outDtype } = prodImpl(permutedX.shape, permutedX.dtype, xVals, reductionAxes);\n  let resultShape = outShape;\n  if (keepDims) {\n    resultShape = backend_util_exports.expandShapeToKeepDim(outShape, axes);\n  }\n  intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return backend2.makeTensorInfo(resultShape, outDtype, outVals);\n}\nvar prodConfig = {\n  kernelName: Prod,\n  backendName: \"cpu\",\n  kernelFunc: prod2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Range_impl.js\nfunction rangeImpl(start, stop, step5, dtype) {\n  const sameStartStop = start === stop;\n  const increasingRangeNegativeStep = start < stop && step5 < 0;\n  const decreasingRangePositiveStep = stop < start && step5 > 1;\n  if (sameStartStop || increasingRangeNegativeStep || decreasingRangePositiveStep) {\n    return util_exports.makeZerosTypedArray(0, dtype);\n  }\n  const numElements = Math.abs(Math.ceil((stop - start) / step5));\n  const values = util_exports.makeZerosTypedArray(numElements, dtype);\n  if (stop < start && step5 === 1) {\n    step5 = -1;\n  }\n  values[0] = start;\n  for (let i2 = 1; i2 < values.length; i2++) {\n    values[i2] = values[i2 - 1] + step5;\n  }\n  return values;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Rsqrt.js\nvar rsqrtImpl = createSimpleUnaryImpl((xi) => 1 / Math.sqrt(xi));\nvar rsqrt2 = unaryKernelFuncFromImpl(Rsqrt, rsqrtImpl);\nvar rsqrtConfig = {\n  kernelName: Rsqrt,\n  backendName: \"cpu\",\n  kernelFunc: rsqrt2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Scatter_impl.js\nfunction scatterImpl(indices, updates, shape, outputSize, sliceSize, numUpdates, sliceRank, strides, defaultValue, sumDupeIndices) {\n  const flattenShape = [outputSize / sliceSize, sliceSize];\n  const indicesData = indices.values;\n  const updatesData = updates.values;\n  if (outputSize === 0) {\n    return buffer(shape, updates.dtype);\n  }\n  const outBuf = buffer(flattenShape, updates.dtype);\n  if (typeof defaultValue === \"string\") {\n    outBuf.values.fill(defaultValue);\n  } else if (typeof defaultValue === \"number\") {\n    outBuf.values.fill(defaultValue);\n  } else if (typeof defaultValue === \"boolean\") {\n    outBuf.values.fill(+defaultValue);\n  }\n  for (let i2 = 0; i2 < numUpdates; i2++) {\n    const index = [];\n    let flattenIndex = 0;\n    for (let j = 0; j < sliceRank; j++) {\n      const dim = indicesData[i2 * sliceRank + j];\n      index.push(dim);\n      flattenIndex += dim * strides[j];\n    }\n    if (flattenIndex < 0 || flattenIndex >= outputSize / sliceSize) {\n      throw new Error(`Invalid indices: ${index} does not index into ${shape}`);\n    }\n    for (let k = 0; k < sliceSize; k++) {\n      if (sumDupeIndices) {\n        outBuf.values[flattenIndex * sliceSize + k] += updatesData[i2 * sliceSize + k];\n      } else {\n        outBuf.values[flattenIndex * sliceSize + k] = updates.rank === 0 ? updatesData[0] : updatesData[i2 * sliceSize + k];\n      }\n    }\n  }\n  return outBuf;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Sigmoid.js\nvar sigmoidImpl = createSimpleUnaryImpl((xi) => 1 / (1 + Math.exp(-xi)));\nvar sigmoid2 = unaryKernelFunc(Sigmoid, (xi) => 1 / (1 + Math.exp(-xi)));\nvar sigmoidConfig = {\n  kernelName: Sigmoid,\n  backendName: \"cpu\",\n  kernelFunc: sigmoid2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Slice.js\nfunction sliceImpl(vals, begin, size, shape, dtype) {\n  const isContinous = slice_util_exports.isSliceContinous(shape, begin, size);\n  const length = util_exports.sizeFromShape(size);\n  const xStrides = util_exports.computeStrides(shape);\n  if (isContinous) {\n    const flatOffset = slice_util_exports.computeFlatOffset(begin, xStrides);\n    if (dtype === \"string\") {\n      return vals.slice(flatOffset, flatOffset + length);\n    }\n    return vals.subarray(flatOffset, flatOffset + length);\n  }\n  const decodedData = dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(vals) : vals;\n  const inBuf = buffer(shape, dtype, decodedData);\n  const outBuf = buffer(size, dtype);\n  for (let i2 = 0; i2 < outBuf.size; ++i2) {\n    const outLoc = outBuf.indexToLoc(i2);\n    const inLoc = outLoc.map((idx, j) => idx + begin[j]);\n    outBuf.set(inBuf.get(...inLoc), ...outLoc);\n  }\n  if (dtype === \"string\") {\n    return backend_util_exports.fromStringArrayToUint8(outBuf.values);\n  }\n  return outBuf.values;\n}\nfunction slice2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { begin, size } = attrs;\n  assertNotComplex(x, \"slice\");\n  const [$begin, $size] = slice_util_exports.parseSliceParams(x, begin, size);\n  slice_util_exports.assertParamsValid(x, $begin, $size);\n  const vals = backend2.data.get(x.dataId).values;\n  const outVals = sliceImpl(vals, $begin, $size, x.shape, x.dtype);\n  return backend2.makeTensorInfo($size, x.dtype, outVals);\n}\nvar sliceConfig = {\n  kernelName: Slice,\n  backendName: \"cpu\",\n  kernelFunc: slice2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseFillEmptyRows_impl.js\nfunction sparseFillEmptyRowsImpl(indices, indicesShape, indicesDType, values, valuesDType, denseShape, defaultValue) {\n  const indicesCount = indicesShape[0];\n  const denseRows = denseShape[0];\n  const emptyRowIndicator = new Array(denseRows);\n  const reverseIndexMap = new Array(indicesCount);\n  const rank = indicesShape[1];\n  if (denseRows === 0) {\n    if (indicesCount !== 0) {\n      throw new Error(backend_util_exports.getSparseFillEmptyRowsIndicesDenseShapeMismatch(indicesCount));\n    }\n    const outputIndices = util_exports.getArrayFromDType(indicesDType, 0);\n    const outputValues = util_exports.getArrayFromDType(valuesDType, 0);\n    return [\n      outputIndices,\n      [0, rank],\n      outputValues,\n      emptyRowIndicator,\n      reverseIndexMap\n    ];\n  }\n  let rowsAreOrdered = true;\n  let lastIndicesRow = 0;\n  const csrOffset = new Array(denseRows).fill(0);\n  for (let i2 = 0; i2 < indicesCount; ++i2) {\n    const row = indices[i2 * rank];\n    if (row < 0) {\n      throw new Error(backend_util_exports.getSparseFillEmptyRowsNegativeIndexErrorMessage(i2, row));\n    }\n    if (row >= denseRows) {\n      throw new Error(backend_util_exports.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(i2, row, denseRows));\n    }\n    ++csrOffset[row];\n    rowsAreOrdered = rowsAreOrdered && row >= lastIndicesRow;\n    lastIndicesRow = row;\n  }\n  let allRowsFull = true;\n  for (let row = 0; row < denseRows; ++row) {\n    const rowEmpty = csrOffset[row] === 0;\n    emptyRowIndicator[row] = rowEmpty;\n    allRowsFull = allRowsFull && !rowEmpty;\n    csrOffset[row] = Math.max(csrOffset[row], 1);\n    if (row > 0) {\n      csrOffset[row] += csrOffset[row - 1];\n    }\n  }\n  if (allRowsFull && rowsAreOrdered) {\n    const outputIndices = indices;\n    const outputValues = values;\n    for (let i2 = 0; i2 < indicesCount; ++i2) {\n      reverseIndexMap[i2] = i2;\n    }\n    return [\n      outputIndices,\n      [indicesCount, rank],\n      outputValues,\n      emptyRowIndicator,\n      reverseIndexMap\n    ];\n  } else {\n    const fullIndicesCount = csrOffset[denseRows - 1];\n    const outputIndices = util_exports.getArrayFromDType(indicesDType, fullIndicesCount * rank);\n    const outputValues = util_exports.getArrayFromDType(valuesDType, fullIndicesCount);\n    const filledCount = new Array(denseRows).fill(0);\n    for (let i2 = 0; i2 < indicesCount; ++i2) {\n      const row = indices[i2 * rank];\n      const offset = filledCount[row];\n      const outputI = (row === 0 ? 0 : csrOffset[row - 1]) + offset;\n      filledCount[row]++;\n      for (let j = 0; j < rank; ++j) {\n        outputIndices[outputI * rank + j] = indices[i2 * rank + j];\n      }\n      outputValues[outputI] = values[i2];\n      reverseIndexMap[i2] = outputI;\n    }\n    for (let row = 0; row < denseRows; ++row) {\n      const rowCount = filledCount[row];\n      if (rowCount === 0) {\n        const startingIndex = row === 0 ? 0 : csrOffset[row - 1];\n        outputIndices[startingIndex * rank + 0] = row;\n        for (let col = 1; col < rank; ++col) {\n          outputIndices[startingIndex * rank + col] = 0;\n        }\n        outputValues[startingIndex] = defaultValue;\n      }\n    }\n    return [\n      outputIndices,\n      [fullIndicesCount, rank],\n      outputValues,\n      emptyRowIndicator,\n      reverseIndexMap\n    ];\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseReshape_impl.js\nfunction sparseReshapeImpl(inputIndices, inputIndicesShape, inputDType, inputShape, targetShape) {\n  const denseSize = util_exports.sizeFromShape(inputShape);\n  const nnz = inputIndicesShape[0];\n  const outputRank = targetShape.length;\n  const outputShape = [];\n  let product = 1;\n  let unknownIndex = -1;\n  for (let d = 0; d < outputRank; ++d) {\n    const size = targetShape[d];\n    if (size === -1) {\n      if (unknownIndex !== -1) {\n        throw new Error(backend_util_exports.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(unknownIndex, d));\n      }\n      unknownIndex = d;\n      outputShape.push(1);\n    } else {\n      if (size < 0) {\n        throw new Error(backend_util_exports.getSparseReshapeNegativeOutputDimErrorMessage(d, size));\n      }\n      product *= size;\n      outputShape.push(size);\n    }\n  }\n  if (unknownIndex !== -1) {\n    if (product <= 0) {\n      throw new Error(backend_util_exports.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage());\n    }\n    const missing = Math.trunc(denseSize / product);\n    if (product * missing !== denseSize) {\n      throw new Error(backend_util_exports.getSparseReshapeInputOutputMultipleErrorMessage(inputShape, outputShape));\n    }\n    outputShape[unknownIndex] = missing;\n  }\n  const outputSize = util_exports.sizeFromShape(outputShape);\n  if (outputSize !== denseSize) {\n    throw new Error(backend_util_exports.getSparseReshapeInputOutputMismatchErrorMessage(inputShape, outputShape));\n  }\n  const inputRank = inputShape.length;\n  const inputStrides = [];\n  if (inputRank > 0) {\n    inputStrides[inputRank - 1] = 1;\n    for (let d = inputRank - 2; d >= 0; --d) {\n      inputStrides[d] = inputStrides[d + 1] * inputShape[d + 1];\n    }\n  }\n  const outputStrides = [];\n  if (outputRank > 0) {\n    outputStrides[outputRank - 1] = 1;\n    for (let d = outputRank - 2; d >= 0; --d) {\n      outputStrides[d] = outputStrides[d + 1] * outputShape[d + 1];\n    }\n  }\n  const newIndices = util_exports.getArrayFromDType(inputDType, nnz * outputRank);\n  for (let i2 = 0; i2 < nnz; ++i2) {\n    let id = 0;\n    for (let j = 0; j < inputRank; ++j) {\n      id += inputIndices[i2 * inputRank + j] * inputStrides[j];\n    }\n    for (let j = 0; j < outputRank; ++j) {\n      newIndices[i2 * outputRank + j] = Math.trunc(id / outputStrides[j]);\n      id %= outputStrides[j];\n    }\n  }\n  return [newIndices, [nnz, outputRank], outputShape];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseSegmentReduction_impl.js\nfunction sparseSegmentReductionImpl(input2, inputShape, inputDType, indices, segmentIds, isMean = false, defaultValue = 0) {\n  const numIndices = indices.length;\n  const inputFlat = [inputShape[0], input2.length / inputShape[0]];\n  const numCol = inputFlat[1];\n  const lastSegmentIdPlusOne = numIndices > 0 ? segmentIds[numIndices - 1] + 1 : 0;\n  const outputRows = lastSegmentIdPlusOne;\n  if (outputRows < 0) {\n    throw new Error(backend_util_exports.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());\n  }\n  const outputShape = inputShape.slice();\n  outputShape[0] = outputRows;\n  const outputLength = outputShape.reduce((product, value) => product * value, 1);\n  const output = util_exports.getArrayFromDType(inputDType, outputLength);\n  if (numIndices === 0) {\n    if (outputRows > 0) {\n      output.fill(defaultValue);\n    }\n    return [output, outputShape];\n  }\n  if (outputRows <= 0) {\n    throw new Error(backend_util_exports.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());\n  }\n  let start = 0, end = 1;\n  let uninitializedIndex = 0;\n  let outIndex = segmentIds[start];\n  while (true) {\n    let nextIndex = 0;\n    if (end < numIndices) {\n      nextIndex = segmentIds[end];\n      if (outIndex === nextIndex) {\n        ++end;\n        continue;\n      }\n      if (outIndex >= nextIndex) {\n        throw new Error(backend_util_exports.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage());\n      }\n    }\n    if (outIndex < 0 || outIndex >= outputRows) {\n      throw new Error(backend_util_exports.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(outIndex, outputRows));\n    }\n    if (outIndex > uninitializedIndex) {\n      output.fill(defaultValue, uninitializedIndex * numCol, outIndex * numCol);\n    }\n    for (let i2 = start; i2 < end; ++i2) {\n      const index = indices[i2];\n      if (index < 0 || index >= inputFlat[0]) {\n        throw new Error(backend_util_exports.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(i2, indices[i2], inputFlat[0]));\n      }\n      for (let j = 0; j < numCol; j++) {\n        output[outIndex * numCol + j] += input2[index * numCol + j];\n      }\n    }\n    if (isMean) {\n      for (let j = 0; j < numCol; j++) {\n        output[outIndex * numCol + j] /= end - start;\n      }\n    }\n    start = end;\n    ++end;\n    uninitializedIndex = outIndex + 1;\n    outIndex = nextIndex;\n    if (end > numIndices) {\n      break;\n    }\n  }\n  if (uninitializedIndex < outputRows) {\n    output.fill(defaultValue, uninitializedIndex * numCol, outputRows * numCol);\n  }\n  return [output, outputShape];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Sqrt.js\nvar sqrtImpl = createSimpleUnaryImpl((xi) => Math.sqrt(xi));\nvar sqrt2 = unaryKernelFunc(Sqrt, (xi) => Math.sqrt(xi));\nvar sqrtConfig = {\n  kernelName: Sqrt,\n  backendName: \"cpu\",\n  kernelFunc: sqrt2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SquaredDifference.js\nvar squaredDifferenceImpl = createSimpleBinaryKernelImpl((a, b) => {\n  const diff = a - b;\n  return diff * diff;\n});\nvar squaredDifference2 = binaryKernelFunc(SquaredDifference, squaredDifferenceImpl);\nvar squaredDifferenceConfig = {\n  kernelName: SquaredDifference,\n  backendName: \"cpu\",\n  kernelFunc: squaredDifference2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StridedSlice_impl.js\nfunction stridedSliceImpl(outShape, xBuf, strides, begin) {\n  const outBuf = buffer(outShape, xBuf.dtype);\n  for (let i2 = 0; i2 < outBuf.size; i2++) {\n    const loc = outBuf.indexToLoc(i2);\n    const newLoc = new Array(loc.length);\n    for (let j = 0; j < newLoc.length; j++) {\n      newLoc[j] = loc[j] * strides[j] + begin[j];\n    }\n    outBuf.set(xBuf.get(...newLoc), ...loc);\n  }\n  return outBuf;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StringNGrams_impl.js\nvar StringNGramsOp = class {\n  constructor(separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences) {\n    this.separator = util_exports.encodeString(separator);\n    this.nGramWidths = nGramWidths;\n    this.leftPad = util_exports.encodeString(leftPad);\n    this.rightPad = util_exports.encodeString(rightPad2);\n    this.padWidth = padWidth;\n    this.preserveShort = preserveShortSequences;\n  }\n  getPadWidth(nGramWidth) {\n    return Math.min(this.padWidth < 0 ? nGramWidth - 1 : this.padWidth, nGramWidth - 1);\n  }\n  getNumNGrams(length, nGramWidth) {\n    const padWidth = this.getPadWidth(nGramWidth);\n    return Math.max(0, length + 2 * padWidth - nGramWidth + 1);\n  }\n  createNGrams(data, splitIndex, output, outputStartIndex, numNGrams, nGramWidth) {\n    for (let nGramIndex = 0; nGramIndex < numNGrams; ++nGramIndex) {\n      const padWidth = this.getPadWidth(nGramWidth);\n      const leftPadding = Math.max(0, padWidth - nGramIndex);\n      const rightPadding = Math.max(0, padWidth - (numNGrams - (nGramIndex + 1)));\n      const numTokens = nGramWidth - (leftPadding + rightPadding);\n      const dataStartIndex = splitIndex + (leftPadding > 0 ? 0 : nGramIndex - padWidth);\n      let nGramSize = 0;\n      nGramSize += leftPadding * this.leftPad.length;\n      for (let n2 = 0; n2 < numTokens; ++n2) {\n        nGramSize += data[dataStartIndex + n2].length;\n      }\n      nGramSize += rightPadding * this.rightPad.length;\n      const numSeparators = leftPadding + rightPadding + numTokens - 1;\n      nGramSize += numSeparators * this.separator.length;\n      output[outputStartIndex + nGramIndex] = new Uint8Array(nGramSize);\n      const nGram = output[outputStartIndex + nGramIndex];\n      let nextNGramIndex = 0;\n      const appendToNGram = (str) => str.forEach((value) => nGram[nextNGramIndex++] = value);\n      for (let n2 = 0; n2 < leftPadding; ++n2) {\n        appendToNGram(this.leftPad);\n        appendToNGram(this.separator);\n      }\n      for (let n2 = 0; n2 < numTokens - 1; ++n2) {\n        appendToNGram(data[dataStartIndex + n2]);\n        appendToNGram(this.separator);\n      }\n      if (numTokens > 0) {\n        appendToNGram(data[dataStartIndex + numTokens - 1]);\n        for (let n2 = 0; n2 < rightPadding; ++n2) {\n          appendToNGram(this.separator);\n          appendToNGram(this.rightPad);\n        }\n      } else {\n        for (let n2 = 0; n2 < rightPadding - 1; ++n2) {\n          appendToNGram(this.rightPad);\n          appendToNGram(this.separator);\n        }\n        appendToNGram(this.rightPad);\n      }\n    }\n  }\n  compute(data, splits) {\n    const inputDataSize = data.length;\n    const splitsSize = splits.length;\n    if (splitsSize > 0) {\n      let prevSplit = splits[0];\n      if (prevSplit !== 0) {\n        throw new Error(`First split value must be 0, got ${prevSplit}`);\n      }\n      for (let i2 = 1; i2 < splitsSize; ++i2) {\n        let validSplits = splits[i2] >= prevSplit;\n        validSplits = validSplits && splits[i2] <= inputDataSize;\n        if (!validSplits) {\n          throw new Error(`Invalid split value ${splits[i2]}, must be in [${prevSplit}, ${inputDataSize}]`);\n        }\n        prevSplit = splits[i2];\n      }\n      if (prevSplit !== inputDataSize) {\n        throw new Error(`Last split value must be data size. Expected ${inputDataSize}, got ${prevSplit}`);\n      }\n    }\n    const numBatchItems = splitsSize - 1;\n    const nGramsSplits = util_exports.getArrayFromDType(\"int32\", splitsSize);\n    if (inputDataSize === 0 || splitsSize === 0) {\n      const empty = new Array(inputDataSize);\n      for (let i2 = 0; i2 <= numBatchItems; ++i2) {\n        nGramsSplits[i2] = 0;\n      }\n      return [empty, nGramsSplits];\n    }\n    nGramsSplits[0] = 0;\n    for (let i2 = 1; i2 <= numBatchItems; ++i2) {\n      const length = splits[i2] - splits[i2 - 1];\n      let numNGrams = 0;\n      this.nGramWidths.forEach((nGramWidth) => {\n        numNGrams += this.getNumNGrams(length, nGramWidth);\n      });\n      if (this.preserveShort && length > 0 && numNGrams === 0) {\n        numNGrams = 1;\n      }\n      nGramsSplits[i2] = nGramsSplits[i2 - 1] + numNGrams;\n    }\n    const nGrams = new Array(nGramsSplits[numBatchItems]);\n    for (let i2 = 0; i2 < numBatchItems; ++i2) {\n      const splitIndex = splits[i2];\n      let outputStartIdx = nGramsSplits[i2];\n      this.nGramWidths.forEach((nGramWidth) => {\n        const length = splits[i2 + 1] - splits[i2];\n        const numNGrams = this.getNumNGrams(length, nGramWidth);\n        this.createNGrams(data, splitIndex, nGrams, outputStartIdx, numNGrams, nGramWidth);\n        outputStartIdx += numNGrams;\n      });\n      if (this.preserveShort && outputStartIdx === nGramsSplits[i2]) {\n        const dataLength = splits[i2 + 1] - splits[i2];\n        if (dataLength === 0) {\n          continue;\n        }\n        const nGramWidth = dataLength + 2 * this.padWidth;\n        const numNGrams = 1;\n        this.createNGrams(data, splitIndex, nGrams, outputStartIdx, numNGrams, nGramWidth);\n      }\n    }\n    return [nGrams, nGramsSplits];\n  }\n};\nfunction stringNGramsImpl(data, dataSplits, separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences) {\n  return new StringNGramsOp(separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences).compute(data, dataSplits);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StringSplit_impl.js\nfunction split3(str, delimiters, skipEmpty, result) {\n  if (!str.length) {\n    return;\n  }\n  if (delimiters.length === 0) {\n    for (let i2 = 0; i2 < str.length; ++i2) {\n      result.push(str.subarray(i2, i2 + 1));\n    }\n    return;\n  }\n  if (delimiters.length === 1) {\n    const delimiter = delimiters[0];\n    let f = str.indexOf(delimiter);\n    while (f !== -1) {\n      const token = str.subarray(0, f);\n      if (!skipEmpty || token.length !== 0) {\n        result.push(token);\n      }\n      str = str.subarray(f + 1);\n      f = str.indexOf(delimiter);\n    }\n    if (!skipEmpty || str.length !== 0) {\n      result.push(str);\n    }\n    return;\n  }\n  let tokenStart = 0;\n  for (let i2 = 0; i2 < str.length + 1; i2++) {\n    if (i2 === str.length || delimiters.indexOf(str[i2]) !== -1) {\n      const token = str.subarray(tokenStart, i2);\n      if (!skipEmpty || token.length !== 0) {\n        result.push(token);\n      }\n      tokenStart = i2 + 1;\n    }\n  }\n}\nfunction stringSplitImpl(input2, delimiter, skipEmpty) {\n  const batchSize = input2.length;\n  const tokens = [];\n  let outputSize = 0;\n  let maxNumEntries = 0;\n  const numIndices = new Array(batchSize);\n  for (let i2 = 0; i2 < batchSize; ++i2) {\n    const prevTokensLength = tokens.length;\n    split3(input2[i2], delimiter, skipEmpty, tokens);\n    const nEntries = tokens.length - prevTokensLength;\n    numIndices[i2] = nEntries;\n    outputSize += nEntries;\n    maxNumEntries = Math.max(maxNumEntries, nEntries);\n  }\n  const indices = util_exports.getArrayFromDType(\"int32\", outputSize * 2);\n  const values = new Array(outputSize);\n  const shape = [batchSize, maxNumEntries];\n  let c = 0;\n  for (let i2 = 0; i2 < batchSize; ++i2) {\n    for (let j = 0; j < numIndices[i2]; ++j) {\n      indices[c * 2] = i2;\n      indices[c * 2 + 1] = j;\n      values[c] = tokens[c];\n      ++c;\n    }\n  }\n  return [indices, values, shape];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StringToHashBucketFast_impl.js\nfunction stringToHashBucketFastImpl(input2, numBuckets) {\n  const output = util_exports.getArrayFromDType(\"int32\", input2.length);\n  for (let i2 = 0; i2 < input2.length; ++i2) {\n    output[i2] = util_exports.fingerPrint64(input2[i2]).modulo(numBuckets).getLowBitsUnsigned();\n  }\n  return output;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Sub.js\nvar subImpl = createSimpleBinaryKernelImpl((aValue, bValue) => aValue - bValue);\nvar subComplexImpl = createComplexBinaryKernelImpl((aReal, aImag, bReal, bImag) => {\n  return { real: aReal - bReal, imag: aImag - bImag };\n});\nvar sub2 = binaryKernelFunc(Sub, subImpl, subComplexImpl);\nvar subConfig = {\n  kernelName: Sub,\n  backendName: \"cpu\",\n  kernelFunc: sub2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Tile_impl.js\nfunction tileImpl(xBuf, reps) {\n  const newShape = new Array(xBuf.rank);\n  for (let i2 = 0; i2 < newShape.length; i2++) {\n    newShape[i2] = xBuf.shape[i2] * reps[i2];\n  }\n  const result = buffer(newShape, xBuf.dtype);\n  for (let i2 = 0; i2 < result.values.length; ++i2) {\n    const newLoc = result.indexToLoc(i2);\n    const originalLoc = new Array(xBuf.rank);\n    for (let j = 0; j < originalLoc.length; j++) {\n      originalLoc[j] = newLoc[j] % xBuf.shape[j];\n    }\n    const originalIndex = xBuf.locToIndex(originalLoc);\n    result.values[i2] = xBuf.values[originalIndex];\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/TopK_impl.js\nvar comparePair = (a, b) => {\n  const valueDiff = b.value - a.value;\n  return valueDiff === 0 ? a.index - b.index : valueDiff;\n};\nfunction select(array2, k, left = 0, right = array2.length - 1) {\n  while (right > left) {\n    if (right - left > 600) {\n      const n2 = right - left + 1;\n      const i3 = k - left + 1;\n      const z = Math.log(n2);\n      const s2 = 0.5 * Math.exp(2 * z / 3);\n      const sd = 0.5 * Math.sqrt(z * s2 * (n2 - s2) / n2) * Math.sign(i3 - n2 / 2);\n      const newLeft = Math.max(left, Math.floor(k - i3 * s2 / n2 + sd));\n      const newRight = Math.min(right, Math.floor(k + (n2 - i3) * s2 / n2 + sd));\n      select(array2, k, newLeft, newRight);\n    }\n    const t2 = array2[k];\n    let i2 = left;\n    let j = right;\n    util_exports.swap(array2, left, k);\n    if (comparePair(array2[right], t2) > 0) {\n      util_exports.swap(array2, left, right);\n    }\n    while (i2 < j) {\n      util_exports.swap(array2, i2, j);\n      i2++;\n      j--;\n      while (comparePair(array2[i2], t2) < 0) {\n        i2 = i2 + 1;\n      }\n      while (comparePair(array2[j], t2) > 0) {\n        j = j - 1;\n      }\n    }\n    if (comparePair(array2[left], t2) === 0) {\n      util_exports.swap(array2, left, j);\n    } else {\n      j = j + 1;\n      util_exports.swap(array2, j, right);\n    }\n    if (j <= k) {\n      left = j + 1;\n    }\n    if (k <= j) {\n      right = j - 1;\n    }\n  }\n}\nfunction topKImpl(x, xShape, xDtype, k, sorted) {\n  const lastDim = xShape[xShape.length - 1];\n  const [batch, size] = [x.length / lastDim, lastDim];\n  const allTopKVals = util_exports.getTypedArrayFromDType(xDtype, batch * k);\n  const allTopKIndices = util_exports.getTypedArrayFromDType(\"int32\", batch * k);\n  for (let b = 0; b < batch; b++) {\n    const offset = b * size;\n    const vals = x.subarray(offset, offset + size);\n    let valAndInd = new Array(vals.length);\n    vals.forEach((value, index) => valAndInd[index] = { value, index });\n    if (k < valAndInd.length) {\n      select(valAndInd, k);\n      valAndInd = valAndInd.slice(0, k);\n    }\n    if (sorted) {\n      valAndInd.sort(comparePair);\n    }\n    const outOffset = b * k;\n    const topKVals = allTopKVals.subarray(outOffset, outOffset + k);\n    const topKIndices = allTopKIndices.subarray(outOffset, outOffset + k);\n    for (let i2 = 0; i2 < k; i2++) {\n      topKVals[i2] = valAndInd[i2].value;\n      topKIndices[i2] = valAndInd[i2].index;\n    }\n  }\n  const outputShape = xShape.slice();\n  outputShape[outputShape.length - 1] = k;\n  return [\n    buffer(outputShape, xDtype, allTopKVals),\n    buffer(outputShape, \"int32\", allTopKIndices)\n  ];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Unique_impl.js\nfunction uniqueImpl(values, axis, shape, dtype) {\n  const $axis = util_exports.parseAxisParam(axis, shape)[0];\n  const newShape = [1, shape[0], 1];\n  for (let i2 = 0; i2 < $axis; i2++) {\n    newShape[0] *= shape[i2];\n  }\n  newShape[1] = shape[$axis];\n  for (let i2 = $axis + 1; i2 < shape.length; i2++) {\n    newShape[2] *= shape[i2];\n  }\n  const uniqueElements = {};\n  const indices = new Int32Array(shape[$axis]);\n  const inputBuffer = new TensorBuffer(newShape, dtype, values);\n  const uniqueIndices = [];\n  const is1DTensor = newShape[0] === 1 && newShape[2] === 1;\n  for (let i2 = 0; i2 < shape[$axis]; i2++) {\n    let element;\n    if (is1DTensor) {\n      element = values[i2].toString();\n    } else {\n      const axisValues = [];\n      for (let m = 0; m < newShape[0]; m++) {\n        for (let n2 = 0; n2 < newShape[2]; n2++) {\n          axisValues.push(inputBuffer.get(m, i2, n2));\n        }\n      }\n      element = axisValues.join(\",\");\n    }\n    if (uniqueElements[element] !== void 0) {\n      indices[i2] = uniqueElements[element];\n    } else {\n      const uniqueIndex = Object.keys(uniqueElements).length;\n      uniqueElements[element] = uniqueIndex;\n      indices[i2] = uniqueIndex;\n      uniqueIndices.push(i2);\n    }\n  }\n  const outputTmpShape = newShape.slice();\n  outputTmpShape[1] = Object.keys(uniqueElements).length;\n  const outputBuffer = new TensorBuffer(outputTmpShape, dtype);\n  uniqueIndices.forEach((uniqueElementIndex, i2) => {\n    for (let m = 0; m < newShape[0]; m++) {\n      for (let n2 = 0; n2 < newShape[2]; n2++) {\n        outputBuffer.set(inputBuffer.get(m, uniqueElementIndex, n2), m, i2, n2);\n      }\n    }\n  });\n  const outputShape = shape.slice();\n  outputShape[$axis] = outputTmpShape[1];\n  return {\n    outputValues: outputBuffer.values,\n    outputShape,\n    indices\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/base.js\nregisterBackend(\"cpu\", () => new MathBackendCPU(), 1);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Elu.js\nvar elu4 = unaryKernelFunc(Elu, (xi) => xi >= 0 ? xi : Math.exp(xi) - 1);\nvar eluConfig = {\n  kernelName: Elu,\n  backendName: \"cpu\",\n  kernelFunc: elu4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LeakyRelu.js\nfunction leakyRelu2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { alpha } = attrs;\n  assertNotComplex([x], \"leakyRelu\");\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const xVals = backend2.data.get(x.dataId).values;\n  const outVals = util_exports.getTypedArrayFromDType(\"float32\", xSize);\n  for (let i2 = 0; i2 < xVals.length; i2++) {\n    outVals[i2] = xVals[i2] < 0 ? alpha * xVals[i2] : xVals[i2];\n  }\n  return backend2.makeTensorInfo(x.shape, \"float32\", outVals);\n}\nvar leakyReluConfig = {\n  kernelName: LeakyRelu,\n  backendName: \"cpu\",\n  kernelFunc: leakyRelu2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Prelu.js\nvar preluImpl = createSimpleBinaryKernelImpl((xValue, aValue) => xValue < 0 ? aValue * xValue : xValue);\nfunction prelu3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x, alpha } = inputs;\n  assertNotComplex([x, alpha], \"prelu\");\n  const aVals = backend2.data.get(x.dataId).values;\n  const bVals = backend2.data.get(alpha.dataId).values;\n  const [resultData, resultShape] = preluImpl(x.shape, alpha.shape, aVals, bVals, \"float32\");\n  return backend2.makeTensorInfo(resultShape, \"float32\", resultData);\n}\nvar preluConfig = {\n  kernelName: Prelu,\n  backendName: \"cpu\",\n  kernelFunc: prelu3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Relu.js\nvar relu2 = unaryKernelFunc(Relu, (xi) => Math.max(0, xi));\nvar reluConfig = {\n  kernelName: Relu,\n  backendName: \"cpu\",\n  kernelFunc: relu2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Relu6.js\nvar relu62 = unaryKernelFunc(Relu6, (xi) => Math.min(Math.max(0, xi), 6));\nvar relu6Config = {\n  kernelName: Relu6,\n  backendName: \"cpu\",\n  kernelFunc: relu62\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/fused_utils.js\nfunction applyActivation2(backend2, x, activation2, preluActivationWeights, leakyreluAlpha) {\n  if (activation2 === \"linear\") {\n    return identity2({ inputs: { x }, backend: backend2 });\n  } else if (activation2 === \"relu\") {\n    return relu2({ inputs: { x }, backend: backend2 });\n  } else if (activation2 === \"elu\") {\n    return elu4({ inputs: { x }, backend: backend2 });\n  } else if (activation2 === \"relu6\") {\n    return relu62({ inputs: { x }, backend: backend2 });\n  } else if (activation2 === \"prelu\") {\n    return prelu3({ inputs: { x, alpha: preluActivationWeights }, backend: backend2 });\n  } else if (activation2 === \"leakyrelu\") {\n    return leakyRelu2({ inputs: { x }, backend: backend2, attrs: { alpha: leakyreluAlpha } });\n  } else if (activation2 === \"sigmoid\") {\n    return sigmoid2({ inputs: { x }, backend: backend2 });\n  }\n  throw new Error(`Activation ${activation2} has not been implemented for the CPU backend.`);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Reshape.js\nfunction reshape3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { shape } = attrs;\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const $shape = util_exports.inferFromImplicitShape(shape, xSize);\n  const $xSize = util_exports.sizeFromShape($shape);\n  util_exports.assert(xSize === $xSize, () => `The new shape (${$shape}) has ${$xSize} elements and the old shape (${x.shape}) has ${xSize} elements. The new shape and old shape must have the same number of elements.`);\n  backend2.incRef(x.dataId);\n  const xData = backend2.data.get(x.dataId);\n  if (xData.complexTensorInfos != null) {\n    const real5 = xData.complexTensorInfos.real;\n    const imag5 = xData.complexTensorInfos.imag;\n    real5.shape = $shape;\n    imag5.shape = $shape;\n  }\n  return { dataId: x.dataId, shape: $shape, dtype: x.dtype };\n}\nvar reshapeConfig = {\n  kernelName: Reshape,\n  backendName: \"cpu\",\n  kernelFunc: reshape3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/BatchMatMul.js\nfunction batchMatMul(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b } = inputs;\n  const { transposeA, transposeB } = attrs;\n  assertNotComplex([a, b], \"matMul\");\n  const aRank = a.shape.length;\n  const bRank = b.shape.length;\n  const innerShapeA = transposeA ? a.shape[aRank - 2] : a.shape[aRank - 1];\n  const innerShapeB = transposeB ? b.shape[bRank - 1] : b.shape[bRank - 2];\n  const outerShapeA = transposeA ? a.shape[aRank - 1] : a.shape[aRank - 2];\n  const outerShapeB = transposeB ? b.shape[bRank - 2] : b.shape[bRank - 1];\n  const outerDimsA = a.shape.slice(0, -2);\n  const outerDimsB = b.shape.slice(0, -2);\n  const batchDimA = util_exports.sizeFromShape(outerDimsA);\n  const batchDimB = util_exports.sizeFromShape(outerDimsB);\n  const outShapeOuterDims = broadcast_util_exports.assertAndGetBroadcastShape(a.shape.slice(0, -2), b.shape.slice(0, -2));\n  const outShape = outShapeOuterDims.concat([outerShapeA, outerShapeB]);\n  util_exports.assert(innerShapeA === innerShapeB, () => `Error in matMul: inner shapes (${innerShapeA}) and (${innerShapeB}) of Tensors with shapes ${a.shape} and ${b.shape} and transposeA=${transposeA} and transposeB=${transposeB} must match.`);\n  const a3dShape = transposeA ? [batchDimA, innerShapeA, outerShapeA] : [batchDimA, outerShapeA, innerShapeA];\n  const b3dShape = transposeB ? [batchDimB, outerShapeB, innerShapeB] : [batchDimB, innerShapeB, outerShapeB];\n  const a3d = reshape3({ inputs: { x: a }, backend: backend2, attrs: { shape: a3dShape } });\n  const b3d = reshape3({ inputs: { x: b }, backend: backend2, attrs: { shape: b3dShape } });\n  const sharedDim = transposeA ? a3d.shape[1] : a3d.shape[2];\n  const leftDim = transposeA ? a3d.shape[2] : a3d.shape[1];\n  const rightDim = transposeB ? b3d.shape[1] : b3d.shape[2];\n  const batchDim = Math.max(batchDimA, batchDimB);\n  const a3dValues = backend2.data.get(a3d.dataId).values;\n  const b3dValues = backend2.data.get(b3d.dataId).values;\n  const a3dStrides = util_exports.computeStrides(a3d.shape);\n  const b3dStrides = util_exports.computeStrides(b3d.shape);\n  const [aBatch, aOuterStep, aInnerStep] = transposeA ? [a3dStrides[0], 1, a3dStrides[1]] : [a3dStrides[0], a3dStrides[1], 1];\n  const [bInnerStep, bOuterStep, bBatch] = transposeB ? [1, b3dStrides[1], b3dStrides[0]] : [b3dStrides[1], 1, b3dStrides[0]];\n  const size = leftDim * rightDim;\n  const result = buffer([batchDim, leftDim, rightDim], a3d.dtype);\n  const resVals = result.values;\n  const blockSize = backend2.blockSize;\n  for (let bi = 0; bi < batchDim; bi++) {\n    for (let i0 = 0; i0 < leftDim; i0 += blockSize) {\n      for (let j0 = 0; j0 < rightDim; j0 += blockSize) {\n        for (let k02 = 0; k02 < sharedDim; k02 += blockSize) {\n          const iBlock = Math.min(i0 + blockSize, leftDim);\n          const jBlock = Math.min(j0 + blockSize, rightDim);\n          const kBlock = Math.min(k02 + blockSize, sharedDim);\n          for (let i2 = i0; i2 < iBlock; i2++) {\n            for (let j = j0; j < jBlock; j++) {\n              let sum7 = 0;\n              for (let k = k02; k < kBlock; k++) {\n                const batchOffsetA = Math.min(bi, batchDimA - 1) * aBatch;\n                const batchOffsetB = Math.min(bi, batchDimB - 1) * bBatch;\n                const aVal = a3dValues[batchOffsetA + i2 * aOuterStep + k * aInnerStep];\n                const bVal = b3dValues[k * bInnerStep + j * bOuterStep + batchOffsetB];\n                sum7 += aVal * bVal;\n              }\n              resVals[bi * size + (i2 * rightDim + j)] += sum7;\n            }\n          }\n        }\n      }\n    }\n  }\n  backend2.disposeIntermediateTensorInfo(a3d);\n  backend2.disposeIntermediateTensorInfo(b3d);\n  return backend2.makeTensorInfo(outShape, result.dtype, result.values);\n}\nvar batchMatMulConfig = {\n  kernelName: BatchMatMul,\n  backendName: \"cpu\",\n  kernelFunc: batchMatMul\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/_FusedMatMul.js\nfunction _fusedMatMul(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b, bias, preluActivationWeights } = inputs;\n  const { transposeA, transposeB, activation: activation2, leakyreluAlpha } = attrs;\n  let current;\n  let addRes;\n  let activationRes;\n  const intermediates = [];\n  const matMulRes = batchMatMul({ inputs: { a, b }, attrs: { transposeA, transposeB }, backend: backend2 });\n  current = matMulRes;\n  if (bias) {\n    addRes = add4({ inputs: { a: current, b: bias }, backend: backend2 });\n    intermediates.push(current);\n    current = addRes;\n  }\n  if (activation2) {\n    activationRes = applyActivation2(backend2, current, activation2, preluActivationWeights, leakyreluAlpha);\n    intermediates.push(current);\n    current = activationRes;\n  }\n  for (const i2 of intermediates) {\n    backend2.disposeIntermediateTensorInfo(i2);\n  }\n  return current;\n}\nvar _fusedMatMulConfig = {\n  kernelName: _FusedMatMul,\n  backendName: \"cpu\",\n  kernelFunc: _fusedMatMul\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Acos.js\nvar acos2 = unaryKernelFunc(Acos, (xi) => Math.acos(xi));\nvar acosConfig = {\n  kernelName: Acos,\n  backendName: \"cpu\",\n  kernelFunc: acos2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Acosh.js\nvar acosh2 = unaryKernelFunc(Acosh, (xi) => Math.acosh(xi));\nvar acoshConfig = {\n  kernelName: Acosh,\n  backendName: \"cpu\",\n  kernelFunc: acosh2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/AddN.js\nfunction addN2(args) {\n  const { inputs, backend: backend2 } = args;\n  const tensors = inputs;\n  assertNotComplex(inputs, \"addN\");\n  const vals = tensors.map((t2) => backend2.data.get(t2.dataId).values);\n  const outBuf = buffer(tensors[0].shape, tensors[0].dtype);\n  const outVals = outBuf.values;\n  for (let i2 = 0; i2 < tensors.length; i2++) {\n    const currVals = vals[i2];\n    for (let j = 0; j < outVals.length; j++) {\n      outVals[j] += currVals[j];\n    }\n  }\n  return backend2.makeTensorInfo(outBuf.shape, outBuf.dtype, outBuf.values);\n}\nvar addNConfig = {\n  kernelName: AddN,\n  backendName: \"cpu\",\n  kernelFunc: addN2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/All.js\nfunction all2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  assertNotComplex(x, \"all\");\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  if (permutedAxes != null) {\n    $x = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"all\", axes, $x.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes($x.shape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const vals = util_exports.makeZerosTypedArray(util_exports.sizeFromShape(outShape), $x.dtype);\n  const aVals = backend2.data.get($x.dataId).values;\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let all5 = aVals[offset];\n    for (let j = 0; j < reduceSize; ++j) {\n      const value = aVals[offset + j];\n      all5 = all5 && value;\n    }\n    vals[i2] = all5;\n  }\n  if (permutedAxes != null) {\n    backend2.disposeIntermediateTensorInfo($x);\n  }\n  const result = backend2.makeTensorInfo(outShape, $x.dtype, vals);\n  if (keepDims) {\n    const expandedShape = backend_util_exports.expandShapeToKeepDim(outShape, origAxes);\n    const reshapedResult = reshape3({ inputs: { x: result }, backend: backend2, attrs: { shape: expandedShape } });\n    backend2.disposeIntermediateTensorInfo(result);\n    return reshapedResult;\n  }\n  return result;\n}\nvar allConfig = {\n  kernelName: All,\n  backendName: \"cpu\",\n  kernelFunc: all2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Any.js\nfunction any2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  assertNotComplex(x, \"any\");\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  if (permutedAxes != null) {\n    $x = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"any\", axes, $x.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes($x.shape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const vals = util_exports.makeZerosTypedArray(util_exports.sizeFromShape(outShape), $x.dtype);\n  const aVals = backend2.data.get($x.dataId).values;\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let anyVal = aVals[offset];\n    for (let j = 0; j < reduceSize; ++j) {\n      const value = aVals[offset + j];\n      anyVal = anyVal || value;\n    }\n    vals[i2] = anyVal;\n  }\n  if (permutedAxes != null) {\n    backend2.disposeIntermediateTensorInfo($x);\n  }\n  const result = backend2.makeTensorInfo(outShape, $x.dtype, vals);\n  if (keepDims) {\n    const expandedShape = backend_util_exports.expandShapeToKeepDim(outShape, origAxes);\n    const reshapedResult = reshape3({ inputs: { x: result }, backend: backend2, attrs: { shape: expandedShape } });\n    backend2.disposeIntermediateTensorInfo(result);\n    return reshapedResult;\n  }\n  return result;\n}\nvar anyConfig = {\n  kernelName: Any,\n  backendName: \"cpu\",\n  kernelFunc: any2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ArgMax.js\nfunction argMax2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis } = attrs;\n  assertNotComplex(x, \"argMax\");\n  let axes = util_exports.parseAxisParam(axis, x.shape);\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  const intermediateTensorInfos = [];\n  if (permutedAxes != null) {\n    $x = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    intermediateTensorInfos.push($x);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, $x.shape.length);\n  }\n  axes = [axes[0]];\n  backend_util_exports.assertAxesAreInnerMostDims(\"argMax\", axes, $x.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes($x.shape, axes);\n  const outSize = util_exports.sizeFromShape(outShape);\n  const vals = util_exports.makeZerosTypedArray(outSize, \"int32\");\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const aVals = backend2.data.get($x.dataId).values;\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let max7 = aVals[offset];\n    let maxIndex = 0;\n    for (let j = 0; j < reduceSize; ++j) {\n      const value = aVals[offset + j];\n      if (value > max7) {\n        max7 = value;\n        maxIndex = j;\n      }\n    }\n    vals[i2] = maxIndex;\n  }\n  intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return backend2.makeTensorInfo(outShape, \"int32\", vals);\n}\nvar argMaxConfig = {\n  kernelName: ArgMax,\n  backendName: \"cpu\",\n  kernelFunc: argMax2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ArgMin.js\nfunction argMin2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis } = attrs;\n  assertNotComplex(x, \"argMin\");\n  let axes = util_exports.parseAxisParam(axis, x.shape);\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  const intermediateTensorInfos = [];\n  if (permutedAxes != null) {\n    $x = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    intermediateTensorInfos.push($x);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, $x.shape.length);\n  }\n  axes = [axes[0]];\n  backend_util_exports.assertAxesAreInnerMostDims(\"argMin\", axes, $x.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes($x.shape, axes);\n  const outSize = util_exports.sizeFromShape(outShape);\n  const vals = util_exports.makeZerosTypedArray(outSize, \"int32\");\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const aVals = backend2.data.get($x.dataId).values;\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let min7 = aVals[offset];\n    let minIndex = 0;\n    for (let j = 0; j < reduceSize; ++j) {\n      const value = aVals[offset + j];\n      if (value < min7) {\n        min7 = value;\n        minIndex = j;\n      }\n    }\n    vals[i2] = minIndex;\n  }\n  intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return backend2.makeTensorInfo(outShape, \"int32\", vals);\n}\nvar argMinConfig = {\n  kernelName: ArgMin,\n  backendName: \"cpu\",\n  kernelFunc: argMin2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Asin.js\nvar asin2 = unaryKernelFunc(Asin, (xi) => Math.asin(xi));\nvar asinConfig = {\n  kernelName: Asin,\n  backendName: \"cpu\",\n  kernelFunc: asin2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Asinh.js\nvar asinh2 = unaryKernelFunc(Asinh, (xi) => Math.asinh(xi));\nvar asinhConfig = {\n  kernelName: Asinh,\n  backendName: \"cpu\",\n  kernelFunc: asinh2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Atan.js\nvar atan3 = unaryKernelFunc(Atan, (xi) => Math.atan(xi));\nvar atanConfig = {\n  kernelName: Atan,\n  backendName: \"cpu\",\n  kernelFunc: atan3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Atan2.js\nvar atan2Impl = createSimpleBinaryKernelImpl((aValue, bValue) => Math.atan2(aValue, bValue));\nvar atan22 = binaryKernelFunc(Atan2, atan2Impl);\nvar atan2Config = {\n  kernelName: Atan2,\n  backendName: \"cpu\",\n  kernelFunc: atan22\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Atanh.js\nvar atanh2 = unaryKernelFunc(Atanh, (xi) => Math.atanh(xi));\nvar atanhConfig = {\n  kernelName: Atanh,\n  backendName: \"cpu\",\n  kernelFunc: atanh2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/pool_utils.js\nfunction pool2(xValues, xShape, dtype, strides, convInfo, poolType) {\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padLeft = convInfo.padInfo.left;\n  const initialValue = poolType === \"max\" ? Number.NEGATIVE_INFINITY : Number.POSITIVE_INFINITY;\n  const output = buffer(convInfo.outShape, dtype);\n  const outputVals = output.values;\n  const outputBatchStrides = convInfo.outShape[1] * convInfo.outShape[2] * convInfo.outShape[3];\n  const outputRowStrides = convInfo.outShape[2] * convInfo.outShape[3];\n  const outputColStrides = convInfo.outShape[3];\n  for (let b = 0; b < convInfo.batchSize; ++b) {\n    const outputBatchOffset = b * outputBatchStrides;\n    const inputBatchOffset = b * strides[0];\n    for (let d = 0; d < convInfo.inChannels; ++d) {\n      for (let yR = 0; yR < convInfo.outHeight; ++yR) {\n        const xRCorner = yR * strideHeight - padTop;\n        const xRMin = Math.max(0, xRCorner);\n        const xRMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRCorner);\n        const outputRowOffset = outputBatchOffset + yR * outputRowStrides;\n        for (let yC = 0; yC < convInfo.outWidth; ++yC) {\n          const xCCorner = yC * strideWidth - padLeft;\n          const xCMin = Math.max(0, xCCorner);\n          const xCMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xCCorner);\n          let minMaxValue = initialValue;\n          let avgValue = 0;\n          let count2 = 0;\n          for (let xR = xRMin; xR < xRMax; xR += dilationHeight) {\n            const xROffset = inputBatchOffset + xR * strides[1];\n            for (let xC = xCMin; xC < xCMax; xC += dilationWidth) {\n              const xCOffset = xROffset + xC * strides[2];\n              const pixel = xValues[xCOffset + d];\n              if (poolType === \"max\" && pixel > minMaxValue) {\n                minMaxValue = pixel;\n              } else if (poolType === \"avg\") {\n                avgValue += pixel;\n                count2++;\n              }\n            }\n            if (isNaN(minMaxValue)) {\n              break;\n            }\n          }\n          const outputOffset = outputRowOffset + yC * outputColStrides + d;\n          outputVals[outputOffset] = poolType === \"avg\" ? avgValue / count2 : minMaxValue;\n        }\n      }\n    }\n  }\n  return output;\n}\nfunction maxPoolPositions(xValues, xShape, dtype, convInfo, flattenPositions = false, includeBatchInIndex = false) {\n  const maxPositions = buffer(convInfo.outShape, \"int32\");\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padLeft = convInfo.padInfo.left;\n  const xBuf = buffer(xShape, dtype, xValues);\n  for (let b = 0; b < convInfo.batchSize; ++b) {\n    for (let d = 0; d < convInfo.inChannels; ++d) {\n      for (let yR = 0; yR < convInfo.outHeight; ++yR) {\n        const xRCorner = yR * strideHeight - padTop;\n        let xRMin = xRCorner;\n        while (xRMin < 0) {\n          xRMin += dilationHeight;\n        }\n        const xRMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRCorner);\n        for (let yC = 0; yC < convInfo.outWidth; ++yC) {\n          const xCCorner = yC * strideWidth - padLeft;\n          let xCMin = xCCorner;\n          while (xCMin < 0) {\n            xCMin += dilationWidth;\n          }\n          const xCMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xCCorner);\n          let maxValue = Number.NEGATIVE_INFINITY;\n          let maxPosition = -1;\n          for (let xR = xRMin; xR < xRMax; xR += dilationHeight) {\n            const wR = xR - xRCorner;\n            for (let xC = xCMin; xC < xCMax; xC += dilationWidth) {\n              const wC = xC - xCCorner;\n              const pixel = xBuf.get(b, xR, xC, d);\n              if (pixel > maxValue) {\n                maxValue = pixel;\n                if (flattenPositions) {\n                  maxPosition = includeBatchInIndex ? ((b * convInfo.inHeight + xR) * convInfo.inWidth + xC) * convInfo.inChannels + d : (xR * convInfo.inWidth + xC) * convInfo.inChannels + d;\n                } else {\n                  maxPosition = wR * effectiveFilterWidth + wC;\n                }\n              }\n            }\n          }\n          maxPositions.set(maxPosition, b, yR, yC, d);\n        }\n      }\n    }\n  }\n  return maxPositions;\n}\nfunction pool3d2(xValues, xShape, dtype, strides, convInfo, poolType) {\n  const strideDepth = convInfo.strideDepth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const dilationDepth = convInfo.dilationDepth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterDepth = convInfo.effectiveFilterDepth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padFront = convInfo.padInfo.front;\n  const padTop = convInfo.padInfo.top;\n  const padLeft = convInfo.padInfo.left;\n  const initialValue = poolType === \"max\" ? Number.NEGATIVE_INFINITY : Number.POSITIVE_INFINITY;\n  const output = buffer(convInfo.outShape, dtype);\n  const outputVals = output.values;\n  const outputBatchStrides = convInfo.outShape[1] * convInfo.outShape[2] * convInfo.outShape[3] * convInfo.outShape[4];\n  const outputDepthStrides = convInfo.outShape[2] * convInfo.outShape[3] * convInfo.outShape[4];\n  const outputRowStrides = convInfo.outShape[3] * convInfo.outShape[4];\n  const outputColStrides = convInfo.outShape[4];\n  for (let batch = 0; batch < convInfo.batchSize; ++batch) {\n    const outputBatchOffset = batch * outputBatchStrides;\n    const inputBatchOffset = batch * strides[0];\n    for (let channel = 0; channel < convInfo.inChannels; ++channel) {\n      for (let yDepth = 0; yDepth < convInfo.outDepth; ++yDepth) {\n        const xDepthCorner = yDepth * strideDepth - padFront;\n        let xDepthMin = xDepthCorner;\n        while (xDepthMin < 0) {\n          xDepthMin += dilationDepth;\n        }\n        const xDepthMax = Math.min(convInfo.inDepth, effectiveFilterDepth + xDepthCorner);\n        const outputDepthOffset = outputBatchOffset + yDepth * outputDepthStrides;\n        for (let yRow = 0; yRow < convInfo.outHeight; ++yRow) {\n          const xRowCorner = yRow * strideHeight - padTop;\n          let xRowMin = xRowCorner;\n          while (xRowMin < 0) {\n            xRowMin += dilationHeight;\n          }\n          const xRowMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRowCorner);\n          const outputRowOffset = outputDepthOffset + yRow * outputRowStrides;\n          for (let yCol = 0; yCol < convInfo.outWidth; ++yCol) {\n            const xColCorner = yCol * strideWidth - padLeft;\n            let xColMin = xColCorner;\n            while (xColMin < 0) {\n              xColMin += dilationWidth;\n            }\n            const xColMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xColCorner);\n            const outputColOffset = outputRowOffset + yCol * outputColStrides;\n            let minMaxValue = initialValue;\n            let avgValue = 0;\n            let count2 = 0;\n            for (let xDepth = xDepthMin; xDepth < xDepthMax; xDepth += dilationDepth) {\n              const xDepthOffset = inputBatchOffset + xDepth * strides[1];\n              for (let xRow = xRowMin; xRow < xRowMax; xRow += dilationHeight) {\n                const xRowOffset = xDepthOffset + xRow * strides[2];\n                for (let xCol = xColMin; xCol < xColMax; xCol += dilationWidth) {\n                  const xColOffset = xRowOffset + xCol * strides[3];\n                  const pixel = xValues[xColOffset + channel];\n                  if (poolType === \"max\" && pixel > minMaxValue) {\n                    minMaxValue = pixel;\n                  } else if (poolType === \"avg\") {\n                    avgValue += pixel;\n                    count2++;\n                  }\n                  if (isNaN(minMaxValue)) {\n                    break;\n                  }\n                }\n                if (isNaN(minMaxValue)) {\n                  break;\n                }\n              }\n              if (isNaN(minMaxValue)) {\n                break;\n              }\n            }\n            const outputOffset = outputColOffset + channel;\n            outputVals[outputOffset] = poolType === \"avg\" ? avgValue / count2 : minMaxValue;\n          }\n        }\n      }\n    }\n  }\n  return output;\n}\nfunction maxPool3dPositions(xBuf, convInfo) {\n  const maxPositions = buffer(convInfo.outShape, \"int32\");\n  const strideDepth = convInfo.strideDepth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const dilationDepth = convInfo.dilationDepth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterDepth = convInfo.effectiveFilterDepth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padFront = convInfo.padInfo.front;\n  const padTop = convInfo.padInfo.top;\n  const padLeft = convInfo.padInfo.left;\n  for (let batch = 0; batch < convInfo.batchSize; ++batch) {\n    for (let channel = 0; channel < convInfo.inChannels; ++channel) {\n      for (let yDepth = 0; yDepth < convInfo.outDepth; ++yDepth) {\n        const xDepthCorner = yDepth * strideDepth - padFront;\n        let xDepthMin = xDepthCorner;\n        while (xDepthMin < 0) {\n          xDepthMin += dilationDepth;\n        }\n        const xDepthMax = Math.min(convInfo.inDepth, effectiveFilterDepth + xDepthCorner);\n        for (let yRow = 0; yRow < convInfo.outHeight; ++yRow) {\n          const xRowCorner = yRow * strideHeight - padTop;\n          let xRowMin = xRowCorner;\n          while (xRowMin < 0) {\n            xRowMin += dilationHeight;\n          }\n          const xRowMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRowCorner);\n          for (let yCol = 0; yCol < convInfo.outWidth; ++yCol) {\n            const xColCorner = yCol * strideWidth - padLeft;\n            let xColMin = xColCorner;\n            while (xColMin < 0) {\n              xColMin += dilationWidth;\n            }\n            const xColMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xColCorner);\n            let maxValue = Number.NEGATIVE_INFINITY;\n            let maxPosition = -1;\n            for (let xDepth = xDepthMin; xDepth < xDepthMax; xDepth += dilationDepth) {\n              const wDepth = xDepth - xDepthCorner;\n              for (let xRow = xRowMin; xRow < xRowMax; xRow += dilationHeight) {\n                const wRow = xRow - xRowCorner;\n                for (let xCol = xColMin; xCol < xColMax; xCol += dilationWidth) {\n                  const wCol = xCol - xColCorner;\n                  const pixel = xBuf.get(batch, xDepth, xRow, xCol, channel);\n                  if (pixel >= maxValue) {\n                    maxValue = pixel;\n                    maxPosition = wDepth * effectiveFilterHeight * effectiveFilterWidth + wRow * effectiveFilterHeight + wCol;\n                  }\n                }\n              }\n            }\n            maxPositions.set(maxPosition, batch, yDepth, yRow, yCol, channel);\n          }\n        }\n      }\n    }\n  }\n  return maxPositions;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/AvgPool.js\nfunction avgPool2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  assertNotComplex(x, \"avgPool\");\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = 1;\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in avgPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  let res;\n  if (convInfo.filterWidth === 1 && convInfo.filterHeight === 1 && util_exports.arraysEqual(convInfo.inShape, convInfo.outShape)) {\n    res = identity2({ inputs: { x }, backend: backend2 });\n  } else {\n    const xValues = backend2.data.get(x.dataId).values;\n    const strides2 = util_exports.computeStrides(x.shape);\n    const buffer2 = pool2(xValues, x.shape, x.dtype, strides2, convInfo, \"avg\");\n    res = backend2.makeTensorInfo(convInfo.outShape, x.dtype, buffer2.values);\n  }\n  return res;\n}\nvar avgPoolConfig = {\n  kernelName: AvgPool,\n  backendName: \"cpu\",\n  kernelFunc: avgPool2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/AvgPool3D.js\nfunction avgPool3D(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { filterSize, strides, pad: pad3, dimRoundingMode, dataFormat } = attrs;\n  assertNotComplex(x, \"avgPool3d\");\n  const convInfo = backend_util_exports.computePool3DInfo(x.shape, filterSize, strides, 1, pad3, dimRoundingMode, dataFormat);\n  const xValues = backend2.data.get(x.dataId).values;\n  const outBuf = pool3d2(xValues, x.shape, x.dtype, util_exports.computeStrides(x.shape), convInfo, \"avg\");\n  return backend2.makeTensorInfo(outBuf.shape, \"float32\", outBuf.values);\n}\nvar avgPool3DConfig = {\n  kernelName: AvgPool3D,\n  backendName: \"cpu\",\n  kernelFunc: avgPool3D\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/AvgPool3DGrad.js\nfunction avgPool3DGrad(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2 } = inputs;\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  assertNotComplex([dy, input2], \"avgPool3DGrad\");\n  const convInfo = backend_util_exports.computePool3DInfo(input2.shape, filterSize, strides, 1, pad3, dimRoundingMode);\n  const strideDepth = convInfo.strideDepth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const filterDepth = convInfo.filterDepth;\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const dilationDepth = convInfo.dilationDepth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterDepth = convInfo.effectiveFilterDepth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;\n  const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n  const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n  const dx = buffer(input2.shape, \"float32\");\n  const avgMultiplier = 1 / (filterDepth * filterHeight * filterWidth);\n  const dyBuf = backend2.bufferSync(dy);\n  for (let batch = 0; batch < convInfo.batchSize; ++batch) {\n    for (let channel = 0; channel < convInfo.inChannels; ++channel) {\n      for (let dxDepth = 0; dxDepth < convInfo.inDepth; ++dxDepth) {\n        for (let dxRow = 0; dxRow < convInfo.inHeight; ++dxRow) {\n          for (let dxCol = 0; dxCol < convInfo.inWidth; ++dxCol) {\n            const dyDepthCorner = dxDepth - padFront;\n            const dyRowCorner = dxRow - padTop;\n            const dyColCorner = dxCol - padLeft;\n            let dotProd = 0;\n            for (let wDepth = 0; wDepth < effectiveFilterDepth; wDepth += dilationDepth) {\n              const dyDepth = (dyDepthCorner + wDepth) / strideDepth;\n              if (dyDepth < 0 || dyDepth >= convInfo.outDepth || Math.floor(dyDepth) !== dyDepth) {\n                continue;\n              }\n              for (let wRow = 0; wRow < effectiveFilterHeight; wRow += dilationHeight) {\n                const dyRow = (dyRowCorner + wRow) / strideHeight;\n                if (dyRow < 0 || dyRow >= convInfo.outHeight || Math.floor(dyRow) !== dyRow) {\n                  continue;\n                }\n                for (let wCol = 0; wCol < effectiveFilterWidth; wCol += dilationWidth) {\n                  const dyCol = (dyColCorner + wCol) / strideWidth;\n                  if (dyCol < 0 || dyCol >= convInfo.outWidth || Math.floor(dyCol) !== dyCol) {\n                    continue;\n                  }\n                  const pixel = dyBuf.get(batch, dyDepth, dyRow, dyCol, channel);\n                  dotProd += pixel;\n                }\n              }\n            }\n            dx.set(dotProd * avgMultiplier, batch, dxDepth, dxRow, dxCol, channel);\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dx.shape, dx.dtype, dx.values);\n}\nvar avgPool3DGradConfig2 = {\n  kernelName: AvgPool3DGrad,\n  backendName: \"cpu\",\n  kernelFunc: avgPool3DGrad\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/AvgPoolGrad.js\nfunction avgPoolGrad2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2 } = inputs;\n  const x = input2;\n  assertNotComplex([dy, input2], \"avgPoolGrad\");\n  const { filterSize, strides, pad: pad3 } = attrs;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, 1, pad3);\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n  const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n  const dx = buffer(x.shape, \"float32\");\n  const avgMultiplier = 1 / (filterHeight * filterWidth);\n  const dyData = backend2.data.get(dy.dataId).values;\n  const dyBuf = buffer(dy.shape, \"float32\", dyData);\n  for (let b = 0; b < convInfo.batchSize; ++b) {\n    for (let d = 0; d < convInfo.inChannels; ++d) {\n      for (let dxR = 0; dxR < convInfo.inHeight; ++dxR) {\n        for (let dxC = 0; dxC < convInfo.inWidth; ++dxC) {\n          const dyRCorner = dxR - padTop;\n          const dyCCorner = dxC - padLeft;\n          let dotProd = 0;\n          for (let wR = 0; wR < effectiveFilterHeight; wR += dilationHeight) {\n            const dyR = (dyRCorner + wR) / strideHeight;\n            if (dyR < 0 || dyR >= convInfo.outHeight || Math.floor(dyR) !== dyR) {\n              continue;\n            }\n            for (let wC = 0; wC < effectiveFilterWidth; wC += dilationWidth) {\n              const dyC = (dyCCorner + wC) / strideWidth;\n              if (dyC < 0 || dyC >= convInfo.outWidth || Math.floor(dyC) !== dyC) {\n                continue;\n              }\n              const pixel = dyBuf.get(b, dyR, dyC, d);\n              dotProd += pixel;\n            }\n          }\n          dx.set(dotProd * avgMultiplier, b, dxR, dxC, d);\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dx.shape, dx.dtype, dx.values);\n}\nvar avgPoolGradConfig2 = {\n  kernelName: AvgPoolGrad,\n  backendName: \"cpu\",\n  kernelFunc: avgPoolGrad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/BatchNorm.js\nfunction batchNorm2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, scale: scale2, offset, mean: mean5, variance } = inputs;\n  util_exports.assert(mean5.shape.length === variance.shape.length, () => \"Batch normalization gradient requires mean and variance to have equal ranks.\");\n  util_exports.assert(offset == null || mean5.shape.length === offset.shape.length, () => \"Batch normalization gradient requires mean and offset to have equal ranks.\");\n  util_exports.assert(scale2 == null || mean5.shape.length === scale2.shape.length, () => \"Batch normalization gradient requires mean and scale to have equal ranks.\");\n  assertNotComplex([x, mean5, variance, scale2, offset], \"batchNorm\");\n  let { varianceEpsilon } = attrs;\n  if (varianceEpsilon == null) {\n    varianceEpsilon = 1e-3;\n  }\n  const xVals = backend2.data.get(x.dataId).values;\n  const mVals = backend2.data.get(mean5.dataId).values;\n  const varVals = backend2.data.get(variance.dataId).values;\n  const sVals = scale2 ? backend2.data.get(scale2.dataId).values : new Float32Array([1]);\n  const offVals = offset ? backend2.data.get(offset.dataId).values : new Float32Array([0]);\n  const outVals = new Float32Array(xVals.length);\n  const offValsLength = offVals.length;\n  const sValsLength = sVals.length;\n  const varValsLength = varVals.length;\n  const mValsLength = mVals.length;\n  let offi = 0;\n  let mi = 0;\n  let si = 0;\n  let vi = 0;\n  for (let i2 = 0; i2 < xVals.length; ++i2) {\n    outVals[i2] = offVals[offi++] + (xVals[i2] - mVals[mi++]) * sVals[si++] / Math.sqrt(varVals[vi++] + varianceEpsilon);\n    if (offi >= offValsLength) {\n      offi = 0;\n    }\n    if (mi >= mValsLength) {\n      mi = 0;\n    }\n    if (si >= sValsLength) {\n      si = 0;\n    }\n    if (vi >= varValsLength) {\n      vi = 0;\n    }\n  }\n  return backend2.makeTensorInfo(x.shape, x.dtype, outVals);\n}\nvar batchNormConfig = {\n  kernelName: FusedBatchNorm,\n  backendName: \"cpu\",\n  kernelFunc: batchNorm2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/BatchToSpaceND.js\nfunction batchToSpaceND2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, crops } = attrs;\n  assertNotComplex([x], \"batchToSpaceND\");\n  const prod6 = blockShape.reduce((a, b) => a * b);\n  const reshaped = backend_util_exports.getReshaped(x.shape, blockShape, prod6);\n  const permuted = backend_util_exports.getPermuted(reshaped.length, blockShape.length);\n  const reshapedPermuted = backend_util_exports.getReshapedPermuted(x.shape, blockShape, prod6);\n  const sliceBeginCoords = backend_util_exports.getSliceBeginCoords(crops, blockShape.length);\n  const sliceSize = backend_util_exports.getSliceSize(reshapedPermuted, crops, blockShape.length);\n  const xReshaped = reshape3({ inputs: { x }, backend: backend2, attrs: { shape: reshaped } });\n  const xTransposed = transpose2({ inputs: { x: xReshaped }, backend: backend2, attrs: { perm: permuted } });\n  const xTransposedReshaped = reshape3({ inputs: { x: xTransposed }, backend: backend2, attrs: { shape: reshapedPermuted } });\n  const result = slice2({\n    inputs: { x: xTransposedReshaped },\n    backend: backend2,\n    attrs: { begin: sliceBeginCoords, size: sliceSize }\n  });\n  backend2.disposeIntermediateTensorInfo(xReshaped);\n  backend2.disposeIntermediateTensorInfo(xTransposed);\n  backend2.disposeIntermediateTensorInfo(xTransposedReshaped);\n  return result;\n}\nvar batchToSpaceNDConfig = {\n  kernelName: BatchToSpaceND,\n  backendName: \"cpu\",\n  kernelFunc: batchToSpaceND2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Bincount.js\nfunction bincount2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, weights } = inputs;\n  const { size } = attrs;\n  const xVals = backend2.data.get(x.dataId).values;\n  const weightsVals = backend2.data.get(weights.dataId).values;\n  const outVals = bincountImpl(xVals, weightsVals, weights.dtype, weights.shape, size);\n  return backend2.makeTensorInfo([size], weights.dtype, outVals);\n}\nvar bincountConfig = {\n  kernelName: Bincount,\n  backendName: \"cpu\",\n  kernelFunc: bincount2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/BroadcastArgs.js\nfunction broadcastArgs2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { s0, s1 } = inputs;\n  const s0Vals = backend2.data.get(s0.dataId).values;\n  const s1Vals = backend2.data.get(s1.dataId).values;\n  const broadcastShape = backend_util_exports.assertAndGetBroadcastShape(Array.from(s0Vals), Array.from(s1Vals));\n  return backend2.makeTensorInfo([broadcastShape.length], \"int32\", Int32Array.from(broadcastShape));\n}\nvar broadcastArgsConfig = {\n  kernelName: BroadcastArgs,\n  backendName: \"cpu\",\n  kernelFunc: broadcastArgs2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ClipByValue.js\nvar clipByValue2 = unaryKernelFunc(ClipByValue, (xi, attrs) => {\n  const clipAttrs = attrs;\n  if (xi > clipAttrs.clipValueMax) {\n    return clipAttrs.clipValueMax;\n  }\n  return xi < clipAttrs.clipValueMin ? clipAttrs.clipValueMin : xi;\n});\nvar clipByValueConfig = {\n  kernelName: ClipByValue,\n  backendName: \"cpu\",\n  kernelFunc: clipByValue2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ComplexAbs.js\nvar complexAbs = (args) => {\n  const { x } = args.inputs;\n  const cpuBackend = args.backend;\n  const resultValues = new Float32Array(util_exports.sizeFromShape(x.shape));\n  const complexVals = cpuBackend.data.get(x.dataId);\n  const real5 = complexVals.complexTensorInfos.real;\n  const imag5 = complexVals.complexTensorInfos.imag;\n  const realVals = cpuBackend.data.get(real5.dataId).values;\n  const imagVals = cpuBackend.data.get(imag5.dataId).values;\n  for (let i2 = 0; i2 < realVals.length; i2++) {\n    const real6 = realVals[i2];\n    const imag6 = imagVals[i2];\n    resultValues[i2] = Math.hypot(real6, imag6);\n  }\n  return cpuBackend.makeOutput(resultValues, x.shape, \"float32\");\n};\nvar complexAbsConfig = {\n  kernelName: ComplexAbs,\n  backendName: \"cpu\",\n  kernelFunc: complexAbs\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Imag.js\nfunction imag2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const imag5 = backend2.data.get(input2.dataId).complexTensorInfos.imag;\n  const imagVal = backend2.data.get(imag5.dataId).values;\n  return backend2.makeTensorInfo(imag5.shape, imag5.dtype, imagVal);\n}\nvar imagConfig = {\n  kernelName: Imag,\n  backendName: \"cpu\",\n  kernelFunc: imag2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Concat.js\nfunction concat2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { axis } = attrs;\n  const $axis = util_exports.parseAxisParam(axis, inputs[0].shape)[0];\n  let outShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), $axis);\n  if (util_exports.sizeFromShape(outShape) === 0) {\n    return backend2.makeTensorInfo(outShape, inputs[0].dtype, []);\n  }\n  const $inputs = inputs.filter((t2) => util_exports.sizeFromShape(t2.shape) > 0);\n  if ($inputs.length === 1) {\n    return identity2({ inputs: { x: $inputs[0] }, backend: backend2 });\n  }\n  const shapes = $inputs.map((t2) => t2.shape);\n  backend_util_exports.assertParamsConsistent(shapes, $axis);\n  if ($inputs[0].dtype === \"complex64\") {\n    const reals = $inputs.map((t2) => real2({ inputs: { input: t2 }, backend: backend2 }));\n    const imags = $inputs.map((t2) => imag2({ inputs: { input: t2 }, backend: backend2 }));\n    const realConcated = concat2({ inputs: reals, backend: backend2, attrs: { axis: $axis } });\n    const imagConcated = concat2({ inputs: imags, backend: backend2, attrs: { axis: $axis } });\n    const result = complex2({ inputs: { real: realConcated, imag: imagConcated }, backend: backend2 });\n    reals.forEach((r2) => backend2.disposeIntermediateTensorInfo(r2));\n    imags.forEach((i2) => backend2.disposeIntermediateTensorInfo(i2));\n    backend2.disposeIntermediateTensorInfo(realConcated);\n    backend2.disposeIntermediateTensorInfo(imagConcated);\n    return result;\n  }\n  const inputs2D = $inputs.map((t2) => {\n    const innerSize = util_exports.sizeFromShape(t2.shape.slice($axis));\n    const shape = [-1, innerSize];\n    return reshape3({ inputs: { x: t2 }, backend: backend2, attrs: { shape } });\n  });\n  const inputsValShapes = inputs2D.map((t2) => {\n    return { vals: backend2.data.get(t2.dataId).values, shape: t2.shape };\n  });\n  outShape = backend_util_exports.computeOutShape(inputs2D.map((t2) => t2.shape), 1);\n  const simplyConcat = inputs2D[0].shape[0] === 1;\n  const outVals = concatImpl(inputsValShapes, outShape, inputs[0].dtype, simplyConcat);\n  const finalOutShape = backend_util_exports.computeOutShape($inputs.map((t2) => t2.shape), $axis);\n  const outInfo = backend2.makeTensorInfo(finalOutShape, inputs[0].dtype, outVals);\n  inputs2D.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return outInfo;\n}\nvar concatConfig = {\n  kernelName: Concat,\n  backendName: \"cpu\",\n  kernelFunc: concat2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Conv2D.js\nfunction conv2D(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode } = attrs;\n  assertNotComplex([x, filter], \"conv2d\");\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode, false, $dataFormat);\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const padLeft = convInfo.padInfo.left;\n  const padTop = convInfo.padInfo.top;\n  const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n  const y = new TensorBuffer(convInfo.outShape, x.dtype);\n  const xStrides = util_exports.computeStrides(x.shape);\n  const filterStrides = util_exports.computeStrides(filter.shape);\n  const xBatchStride = xStrides[0];\n  const xRowStride = isChannelsLast ? xStrides[1] : xStrides[2];\n  const xColStride = isChannelsLast ? xStrides[2] : 1;\n  const xChannelStride = isChannelsLast ? 1 : xStrides[1];\n  const yBatchStride = y.strides[0];\n  const yRowStride = isChannelsLast ? y.strides[1] : y.strides[2];\n  const yColStride = isChannelsLast ? y.strides[2] : 1;\n  const yChannelStride = isChannelsLast ? 1 : y.strides[1];\n  const xVals = backend2.data.get(x.dataId).values;\n  const wVals = backend2.data.get(filter.dataId).values;\n  const yVals = y.values;\n  for (let b = 0; b < convInfo.batchSize; ++b) {\n    const xOffset1 = b * xBatchStride;\n    const yOffset1 = b * yBatchStride;\n    for (let yR = 0; yR < convInfo.outHeight; ++yR) {\n      const yOffset2 = yOffset1 + yR * yRowStride;\n      const xRCorner = yR * convInfo.strideHeight - padTop;\n      for (let wR = 0; wR < filterHeight; ++wR) {\n        const xR = xRCorner + wR * dilationHeight;\n        if (xR < 0 || xR >= convInfo.inHeight) {\n          continue;\n        }\n        const wOffset1 = wR * filterStrides[0];\n        const xOffset2 = xOffset1 + xR * xRowStride;\n        for (let yC = 0; yC < convInfo.outWidth; ++yC) {\n          const yOffset3 = yOffset2 + yC * yColStride;\n          const xCCorner = yC * convInfo.strideWidth - padLeft;\n          for (let wC = 0; wC < filterWidth; ++wC) {\n            const xC = xCCorner + wC * dilationWidth;\n            if (xC < 0 || xC >= convInfo.inWidth) {\n              continue;\n            }\n            const wOffset2 = wOffset1 + wC * filterStrides[1];\n            const xOffset3 = xOffset2 + xC * xColStride;\n            let wOffset3 = wOffset2;\n            for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {\n              const xVal = xVals[xOffset3 + d1 * xChannelStride];\n              for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {\n                yVals[yOffset3 + d2 * yChannelStride] += xVal * wVals[wOffset3 + d2];\n              }\n              wOffset3 += convInfo.outChannels;\n            }\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(y.shape, y.dtype, yVals);\n}\nvar conv2DConfig = {\n  kernelName: Conv2D,\n  backendName: \"cpu\",\n  kernelFunc: conv2D\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Conv2DBackpropFilter.js\nfunction conv2DBackpropFilter2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, dy } = inputs;\n  const { strides, pad: pad3, dataFormat, dimRoundingMode, filterShape } = attrs;\n  assertNotComplex([x, dy], \"conv2dBackpropFilter\");\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filterShape, strides, 1, pad3, dimRoundingMode, false, $dataFormat);\n  const { strideHeight, strideWidth, filterHeight, filterWidth } = convInfo;\n  const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n  const dW = new TensorBuffer(convInfo.filterShape, \"float32\");\n  const leftPad = convInfo.padInfo.left;\n  const topPad = convInfo.padInfo.top;\n  const xVals = backend2.data.get(x.dataId).values;\n  const dyVals = backend2.data.get(dy.dataId).values;\n  const xBuf = new TensorBuffer(x.shape, x.dtype, xVals);\n  const dyBuf = new TensorBuffer(dy.shape, dy.dtype, dyVals);\n  for (let wR = 0; wR < filterHeight; ++wR) {\n    const yRMin = Math.max(0, Math.ceil((topPad - wR) / strideHeight));\n    const yRMax = Math.min(convInfo.outHeight, (convInfo.inHeight + topPad - wR) / strideHeight);\n    for (let wC = 0; wC < filterWidth; ++wC) {\n      const yCMin = Math.max(0, Math.ceil((leftPad - wC) / strideWidth));\n      const yCMax = Math.min(convInfo.outWidth, (convInfo.inWidth + leftPad - wC) / strideWidth);\n      for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {\n        for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {\n          let dotProd = 0;\n          for (let b = 0; b < convInfo.batchSize; ++b) {\n            for (let yR = yRMin; yR < yRMax; ++yR) {\n              const xR = wR + yR * strideHeight - topPad;\n              for (let yC = yCMin; yC < yCMax; ++yC) {\n                const xC = wC + yC * strideWidth - leftPad;\n                if (isChannelsLast) {\n                  dotProd += xBuf.get(b, xR, xC, d1) * dyBuf.get(b, yR, yC, d2);\n                } else {\n                  dotProd += xBuf.get(b, d1, xR, xC) * dyBuf.get(b, d2, yR, yC);\n                }\n              }\n            }\n          }\n          dW.set(dotProd, wR, wC, d1, d2);\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dW.shape, dW.dtype, dW.values);\n}\nvar conv2DBackpropFilterConfig = {\n  kernelName: Conv2DBackpropFilter,\n  backendName: \"cpu\",\n  kernelFunc: conv2DBackpropFilter2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Conv2DBackpropInput.js\nfunction conv2DBackpropInput2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, filter } = inputs;\n  const { inputShape, strides, pad: pad3, dataFormat, dimRoundingMode } = attrs;\n  assertNotComplex([dy, filter], \"conv2dBackpropInput\");\n  const filterStrides = util_exports.computeStrides(filter.shape);\n  const dyStrides = util_exports.computeStrides(dy.shape);\n  let $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(inputShape, filter.shape, strides, 1, pad3, dimRoundingMode, false, $dataFormat);\n  const dx = new TensorBuffer(convInfo.inShape, \"float32\");\n  const dxValues = dx.values;\n  const dyValues = backend2.data.get(dy.dataId).values;\n  const fltValues = backend2.data.get(filter.dataId).values;\n  const [fltS0, fltS1, fltS2] = filterStrides;\n  const { batchSize, filterHeight, filterWidth, inChannels, inHeight, inWidth, outChannels, outHeight, outWidth, strideHeight, strideWidth } = convInfo;\n  $dataFormat = convInfo.dataFormat;\n  const topPad = filterHeight - 1 - convInfo.padInfo.top;\n  const leftPad = filterWidth - 1 - convInfo.padInfo.left;\n  const isChannelsLast = $dataFormat === \"channelsLast\";\n  const xBatchStride = dx.strides[0];\n  const xRowStride = isChannelsLast ? dx.strides[1] : dx.strides[2];\n  const xColStride = isChannelsLast ? dx.strides[2] : 1;\n  const xChannelStride = isChannelsLast ? 1 : dx.strides[1];\n  const yBatchStride = dyStrides[0];\n  const yRowStride = isChannelsLast ? dyStrides[1] : dyStrides[2];\n  const yColStride = isChannelsLast ? dyStrides[2] : 1;\n  const yChannelStride = isChannelsLast ? 1 : dyStrides[1];\n  for (let b = 0; b < batchSize; ++b) {\n    for (let d1 = 0; d1 < inChannels; ++d1) {\n      for (let xR = 0; xR < inHeight; ++xR) {\n        const xRCorner = xR - topPad;\n        const xRMin = Math.max(0, Math.ceil(xRCorner / strideHeight));\n        const yRMax = Math.min(outHeight, (filterHeight + xRCorner) / strideHeight);\n        for (let xC = 0; xC < inWidth; ++xC) {\n          const xCCorner = xC - leftPad;\n          const xCMin = Math.max(0, Math.ceil(xCCorner / strideWidth));\n          const yCMax = Math.min(outWidth, (filterWidth + xCCorner) / strideWidth);\n          let dotProd = 0;\n          for (let yR = xRMin; yR < yRMax; ++yR) {\n            const wR = yR * strideHeight - xRCorner;\n            for (let yC = xCMin; yC < yCMax; ++yC) {\n              const wC = yC * strideWidth - xCCorner;\n              const dyOffset = yBatchStride * b + yRowStride * yR + yColStride * yC;\n              const fltOffset = fltS0 * (filterHeight - 1 - wR) + fltS1 * (filterWidth - 1 - wC) + fltS2 * d1;\n              for (let d2 = 0; d2 < outChannels; ++d2) {\n                const pixel = dyValues[dyOffset + yChannelStride * d2];\n                const weight = fltValues[fltOffset + d2];\n                dotProd += pixel * weight;\n              }\n            }\n          }\n          const dxOffset = xBatchStride * b + xRowStride * xR + xColStride * xC + xChannelStride * d1;\n          dxValues[dxOffset] = dotProd;\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dx.shape, dx.dtype, dx.values);\n}\nvar conv2DBackpropInputConfig = {\n  kernelName: Conv2DBackpropInput,\n  backendName: \"cpu\",\n  kernelFunc: conv2DBackpropInput2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Conv3D.js\nfunction conv3D(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dilations } = attrs;\n  assertNotComplex([x, filter], \"conv3d\");\n  const convInfo = backend_util_exports.computeConv3DInfo(x.shape, filter.shape, strides, dilations, pad3);\n  const { filterDepth, filterHeight, filterWidth, dilationDepth, dilationHeight, dilationWidth, padInfo } = convInfo;\n  const padFront = padInfo.front;\n  const padLeft = padInfo.left;\n  const padTop = padInfo.top;\n  const y = new TensorBuffer(convInfo.outShape, x.dtype);\n  const xVals = backend2.data.get(x.dataId).values;\n  const wVals = backend2.data.get(filter.dataId).values;\n  const yVals = y.values;\n  const xStrides = util_exports.computeStrides(x.shape);\n  const filterStrides = util_exports.computeStrides(filter.shape);\n  for (let b = 0; b < convInfo.batchSize; ++b) {\n    const xOffset1 = b * xStrides[0];\n    const yOffset1 = b * y.strides[0];\n    for (let yF = 0; yF < convInfo.outDepth; ++yF) {\n      const yOffset2 = yOffset1 + yF * y.strides[1];\n      const xFCorner = yF * convInfo.strideDepth - padFront;\n      for (let wF = 0; wF < filterDepth; ++wF) {\n        const xF = xFCorner + wF * dilationDepth;\n        if (xF < 0 || xF >= convInfo.inDepth) {\n          continue;\n        }\n        const wOffset1 = wF * filterStrides[0];\n        const xOffset2 = xOffset1 + xF * xStrides[1];\n        for (let yR = 0; yR < convInfo.outHeight; ++yR) {\n          const yOffset3 = yOffset2 + yR * y.strides[2];\n          const xRCorner = yR * convInfo.strideHeight - padTop;\n          for (let wR = 0; wR < filterHeight; ++wR) {\n            const xR = xRCorner + wR * dilationHeight;\n            if (xR < 0 || xR >= convInfo.inHeight) {\n              continue;\n            }\n            const wOffset2 = wOffset1 + wR * filterStrides[1];\n            const xOffset3 = xOffset2 + xR * xStrides[2];\n            for (let yC = 0; yC < convInfo.outWidth; ++yC) {\n              const yOffset4 = yOffset3 + yC * convInfo.outChannels;\n              const xCCorner = yC * convInfo.strideWidth - padLeft;\n              for (let wC = 0; wC < filterWidth; ++wC) {\n                const xC = xCCorner + wC * dilationWidth;\n                if (xC < 0 || xC >= convInfo.inWidth) {\n                  continue;\n                }\n                const wOffset3 = wOffset2 + wC * filterStrides[2];\n                const xOffset4 = xOffset3 + xC * convInfo.inChannels;\n                let wOffset4 = wOffset3;\n                for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {\n                  const xVal = xVals[xOffset4 + d1];\n                  for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {\n                    yVals[yOffset4 + d2] += xVal * wVals[wOffset4 + d2];\n                  }\n                  wOffset4 += convInfo.outChannels;\n                }\n              }\n            }\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(y.shape, y.dtype, y.values);\n}\nvar conv3DConfig = {\n  kernelName: Conv3D,\n  backendName: \"cpu\",\n  kernelFunc: conv3D\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Conv3DBackpropFilterV2.js\nfunction conv3DBackpropFilterV2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, dy } = inputs;\n  const { strides, pad: pad3, filterShape } = attrs;\n  assertNotComplex([x, dy], \"conv3dBackpropFilterV2\");\n  const xStrides = util_exports.computeStrides(x.shape);\n  const dyStrides = util_exports.computeStrides(dy.shape);\n  const convInfo = backend_util_exports.computeConv3DInfo(x.shape, filterShape, strides, 1, pad3);\n  const strideDepth = convInfo.strideDepth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const filterDepth = convInfo.filterDepth;\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const dw = new TensorBuffer(convInfo.filterShape, \"float32\");\n  const dwValues = dw.values;\n  const [dwS0, dwS1, dwS2, dwS3] = dw.strides;\n  const dyValues = backend2.data.get(dy.dataId).values;\n  const [dyS0, dyS1, dyS2, dyS3] = dyStrides;\n  const xValues = backend2.data.get(x.dataId).values;\n  const [xS0, xS1, xS2, xS3] = xStrides;\n  const frontPad = convInfo.padInfo.front;\n  const leftPad = convInfo.padInfo.left;\n  const topPad = convInfo.padInfo.top;\n  for (let wF = 0; wF < filterDepth; ++wF) {\n    const yFMin = Math.max(0, Math.ceil((frontPad - wF) / strideDepth));\n    const yFMax = Math.min(convInfo.outDepth, (convInfo.inDepth + frontPad - wF) / strideDepth);\n    const wOffset1 = wF * dwS0;\n    for (let wR = 0; wR < filterHeight; ++wR) {\n      const yRMin = Math.max(0, Math.ceil((topPad - wR) / strideHeight));\n      const yRMax = Math.min(convInfo.outHeight, (convInfo.inHeight + topPad - wR) / strideHeight);\n      const wOffset2 = wR * dwS1 + wOffset1;\n      for (let wC = 0; wC < filterWidth; ++wC) {\n        const yCMin = Math.max(0, Math.ceil((leftPad - wC) / strideWidth));\n        const yCMax = Math.min(convInfo.outWidth, (convInfo.inWidth + leftPad - wC) / strideWidth);\n        const wOffset3 = wC * dwS2 + wOffset2;\n        for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {\n          const wOffset4 = d1 * dwS3 + wOffset3;\n          for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {\n            let dotProd = 0;\n            for (let b = 0; b < convInfo.batchSize; ++b) {\n              const xOffset1 = b * xS0;\n              const yOffset1 = b * dyS0;\n              for (let yF = yFMin; yF < yFMax; ++yF) {\n                const xF = wF + yF * strideDepth - frontPad;\n                const xOffset2 = xF * xS1 + xOffset1;\n                const yOffset2 = yF * dyS1 + yOffset1;\n                for (let yR = yRMin; yR < yRMax; ++yR) {\n                  const xR = wR + yR * strideHeight - topPad;\n                  const xOffset3 = xR * xS2 + xOffset2;\n                  const yOffset3 = yR * dyS2 + yOffset2;\n                  for (let yC = yCMin; yC < yCMax; ++yC) {\n                    const xC = wC + yC * strideWidth - leftPad;\n                    const xOffset4 = xC * xS3 + xOffset3;\n                    const yOffset4 = yC * dyS3 + yOffset3;\n                    dotProd += xValues[xOffset4 + d1] * dyValues[yOffset4 + d2];\n                  }\n                }\n              }\n            }\n            dwValues[wOffset4 + d2] = dotProd;\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dw.shape, dw.dtype, dw.values);\n}\nvar conv3DBackpropFilterV2Config = {\n  kernelName: Conv3DBackpropFilterV2,\n  backendName: \"cpu\",\n  kernelFunc: conv3DBackpropFilterV2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Conv3DBackpropInputV2.js\nfunction conv3DBackpropInputV2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, filter } = inputs;\n  const { pad: pad3, strides, inputShape } = attrs;\n  assertNotComplex([dy], \"conv3dBackpropInputV2\");\n  const dyStrides = util_exports.computeStrides(dy.shape);\n  const filterStrides = util_exports.computeStrides(filter.shape);\n  const convInfo = backend_util_exports.computeConv3DInfo(inputShape, filter.shape, strides, 1, pad3);\n  const dx = new TensorBuffer(convInfo.inShape, \"float32\");\n  const dxValues = dx.values;\n  const [dxS0, dxS1, dxS2, dxS3] = dx.strides;\n  const dyValues = backend2.data.get(dy.dataId).values;\n  const [dyS0, dyS1, dyS2, dyS3] = dyStrides;\n  const fltValues = backend2.data.get(filter.dataId).values;\n  const [fltS0, fltS1, fltS2, fltS3] = filterStrides;\n  const { batchSize, filterDepth, filterHeight, filterWidth, inChannels, inDepth, inHeight, inWidth, outChannels, outDepth, outHeight, outWidth, strideDepth, strideHeight, strideWidth } = convInfo;\n  const frontPad = filterDepth - 1 - convInfo.padInfo.front;\n  const topPad = filterHeight - 1 - convInfo.padInfo.top;\n  const leftPad = filterWidth - 1 - convInfo.padInfo.left;\n  for (let b = 0; b < batchSize; ++b) {\n    for (let d1 = 0; d1 < inChannels; ++d1) {\n      for (let xF = 0; xF < inDepth; ++xF) {\n        const xFCorner = xF - frontPad;\n        const xFMin = Math.max(0, Math.ceil(xFCorner / strideDepth));\n        const yFMax = Math.min(outDepth, (filterDepth + xFCorner) / strideDepth);\n        for (let xR = 0; xR < inHeight; ++xR) {\n          const xRCorner = xR - topPad;\n          const xRMin = Math.max(0, Math.ceil(xRCorner / strideHeight));\n          const yRMax = Math.min(outHeight, (filterHeight + xRCorner) / strideHeight);\n          for (let xC = 0; xC < inWidth; ++xC) {\n            const xCCorner = xC - leftPad;\n            const xCMin = Math.max(0, Math.ceil(xCCorner / strideWidth));\n            const yCMax = Math.min(outWidth, (filterWidth + xCCorner) / strideWidth);\n            let dotProd = 0;\n            for (let yF = xFMin; yF < yFMax; ++yF) {\n              const wF = yF * strideDepth - xFCorner;\n              for (let yR = xRMin; yR < yRMax; ++yR) {\n                const wR = yR * strideHeight - xRCorner;\n                for (let yC = xCMin; yC < yCMax; ++yC) {\n                  const wC = yC * strideWidth - xCCorner;\n                  const dyOffset = dyS0 * b + dyS1 * yF + dyS2 * yR + dyS3 * yC;\n                  const fltOffset = fltS0 * (filterDepth - 1 - wF) + fltS1 * (filterHeight - 1 - wR) + fltS2 * (filterWidth - 1 - wC) + fltS3 * d1;\n                  for (let d2 = 0; d2 < outChannels; ++d2) {\n                    const pixel = dyValues[dyOffset + d2];\n                    const weight = fltValues[fltOffset + d2];\n                    dotProd += pixel * weight;\n                  }\n                }\n              }\n            }\n            dxValues[dxS0 * b + dxS1 * xF + dxS2 * xR + dxS3 * xC + d1] = dotProd;\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dx.shape, dx.dtype, dx.values);\n}\nvar conv3DBackpropInputV2Config = {\n  kernelName: Conv3DBackpropInputV2,\n  backendName: \"cpu\",\n  kernelFunc: conv3DBackpropInputV2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Cos.js\nvar cos2 = unaryKernelFunc(Cos, (xi) => Math.cos(xi));\nvar cosConfig = {\n  kernelName: Cos,\n  backendName: \"cpu\",\n  kernelFunc: cos2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Cosh.js\nvar cosh2 = unaryKernelFunc(Cosh, (xi) => Math.cosh(xi));\nvar coshConfig = {\n  kernelName: Cosh,\n  backendName: \"cpu\",\n  kernelFunc: cosh2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/CropAndResize.js\nfunction cropAndResize2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { image: image2, boxes, boxInd } = inputs;\n  const { cropSize, method, extrapolationValue } = attrs;\n  const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n  const numBoxes = boxes.shape[0];\n  const [cropHeight, cropWidth] = cropSize;\n  const output = buffer([numBoxes, cropHeight, cropWidth, numChannels], \"float32\");\n  const boxVals = backend2.data.get(boxes.dataId).values;\n  const boxIndVals = backend2.data.get(boxInd.dataId).values;\n  const imageVals = backend2.data.get(image2.dataId).values;\n  const inStride = util_exports.computeStrides(image2.shape);\n  const outStride = util_exports.computeStrides(output.shape);\n  for (let b = 0; b < numBoxes; b++) {\n    const startInd = b * 4;\n    const y1 = boxVals[startInd];\n    const x1 = boxVals[startInd + 1];\n    const y2 = boxVals[startInd + 2];\n    const x2 = boxVals[startInd + 3];\n    const bInd = boxIndVals[b];\n    if (bInd >= batch) {\n      continue;\n    }\n    const heightScale = cropHeight > 1 ? (y2 - y1) * (imageHeight - 1) / (cropHeight - 1) : 0;\n    const widthScale = cropWidth > 1 ? (x2 - x1) * (imageWidth - 1) / (cropWidth - 1) : 0;\n    for (let y = 0; y < cropHeight; y++) {\n      const yInd = cropHeight > 1 ? y1 * (imageHeight - 1) + y * heightScale : 0.5 * (y1 + y2) * (imageHeight - 1);\n      if (yInd < 0 || yInd > imageHeight - 1) {\n        for (let x = 0; x < cropWidth; x++) {\n          for (let c = 0; c < numChannels; c++) {\n            const ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];\n            output.values[ind] = extrapolationValue;\n          }\n        }\n        continue;\n      }\n      if (method === \"bilinear\") {\n        const topInd = Math.floor(yInd);\n        const bottomInd = Math.ceil(yInd);\n        const yLerp = yInd - topInd;\n        for (let x = 0; x < cropWidth; x++) {\n          const xInd = cropWidth > 1 ? x1 * (imageWidth - 1) + x * widthScale : 0.5 * (x1 + x2) * (imageWidth - 1);\n          if (xInd < 0 || xInd > imageWidth - 1) {\n            for (let c = 0; c < numChannels; c++) {\n              const ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];\n              output.values[ind] = extrapolationValue;\n            }\n            continue;\n          }\n          const leftInd = Math.floor(xInd);\n          const rightInd = Math.ceil(xInd);\n          const xLerp = xInd - leftInd;\n          for (let c = 0; c < numChannels; c++) {\n            let ind = c + leftInd * inStride[2] + topInd * inStride[1] + bInd * inStride[0];\n            const topLeft = imageVals[ind];\n            ind = c + rightInd * inStride[2] + topInd * inStride[1] + bInd * inStride[0];\n            const topRight = imageVals[ind];\n            ind = c + leftInd * inStride[2] + bottomInd * inStride[1] + bInd * inStride[0];\n            const bottomLeft = imageVals[ind];\n            ind = c + rightInd * inStride[2] + bottomInd * inStride[1] + bInd * inStride[0];\n            const bottomRight = imageVals[ind];\n            const top = topLeft + (topRight - topLeft) * xLerp;\n            const bottom = bottomLeft + (bottomRight - bottomLeft) * xLerp;\n            ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];\n            output.values[ind] = top + (bottom - top) * yLerp;\n          }\n        }\n      } else {\n        for (let x = 0; x < cropWidth; ++x) {\n          const xInd = cropWidth > 1 ? x1 * (imageWidth - 1) + x * widthScale : 0.5 * (x1 + x2) * (imageWidth - 1);\n          if (xInd < 0 || xInd > imageWidth - 1) {\n            for (let c = 0; c < numChannels; c++) {\n              const ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];\n              output.values[ind] = extrapolationValue;\n            }\n            continue;\n          }\n          const closestX = Math.round(xInd);\n          const closestY = Math.round(yInd);\n          for (let c = 0; c < numChannels; c++) {\n            const inInd = c + closestX * inStride[2] + closestY * inStride[1] + bInd * inStride[0];\n            const outInd = c + x * outStride[2] + y * outStride[1] + b * outStride[0];\n            output.values[outInd] = imageVals[inInd];\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(output.shape, output.dtype, output.values);\n}\nvar cropAndResizeConfig = {\n  kernelName: CropAndResize,\n  backendName: \"cpu\",\n  kernelFunc: cropAndResize2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Cumprod.js\nfunction cumprod2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  assertNotComplex(x, \"cumprod\");\n  const permutation = backend_util_exports.getAxesPermutation([axis], x.shape.length);\n  let $x = x;\n  if (permutation != null) {\n    $x = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutation } });\n  }\n  const permutedAxis = backend_util_exports.getInnerMostAxes(1, x.shape.length)[0];\n  if (permutedAxis !== $x.shape.length - 1) {\n    throw new Error(`backend.cumprod in CPU expects an inner-most axis=${$x.shape.length - 1} but got axis=${permutedAxis}`);\n  }\n  const resultDtype = upcastType($x.dtype, \"int32\");\n  const vals = util_exports.makeOnesTypedArray(util_exports.sizeFromShape($x.shape), resultDtype);\n  const aVals = backend2.data.get($x.dataId).values;\n  const finalDim = $x.shape[$x.shape.length - 1];\n  const indexAdjuster = reverse5 ? (i2, j) => i2 + finalDim - j - 1 : (i2, j) => i2 + j;\n  for (let i2 = 0; i2 < aVals.length; i2 += finalDim) {\n    for (let j = 0; j < finalDim; j++) {\n      const idx = indexAdjuster(i2, j);\n      if (j === 0) {\n        vals[idx] = exclusive ? 1 : aVals[idx];\n      } else {\n        const prevIdx = indexAdjuster(i2, j - 1);\n        vals[idx] = exclusive ? aVals[prevIdx] * vals[prevIdx] : aVals[idx] * vals[prevIdx];\n      }\n    }\n  }\n  const result = backend2.makeTensorInfo($x.shape, resultDtype, vals);\n  if (permutation != null) {\n    const reversePermutation = backend_util_exports.getUndoAxesPermutation(permutation);\n    const reverseTransposedResult = transpose2({ inputs: { x: result }, backend: backend2, attrs: { perm: reversePermutation } });\n    backend2.disposeIntermediateTensorInfo(result);\n    backend2.disposeIntermediateTensorInfo($x);\n    return reverseTransposedResult;\n  }\n  return result;\n}\nvar cumprodConfig = {\n  kernelName: Cumprod,\n  backendName: \"cpu\",\n  kernelFunc: cumprod2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Cumsum.js\nfunction cumsum2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  assertNotComplex(x, \"cumsum\");\n  const permutation = backend_util_exports.getAxesPermutation([axis], x.shape.length);\n  let $x = x;\n  if (permutation != null) {\n    $x = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutation } });\n  }\n  const permutedAxis = backend_util_exports.getInnerMostAxes(1, x.shape.length)[0];\n  if (permutedAxis !== $x.shape.length - 1) {\n    throw new Error(`backend.cumsum in CPU expects an inner-most axis=${$x.shape.length - 1} but got axis=${permutedAxis}`);\n  }\n  const resultDtype = upcastType($x.dtype, \"int32\");\n  const vals = util_exports.makeZerosTypedArray(util_exports.sizeFromShape($x.shape), resultDtype);\n  const aVals = backend2.data.get($x.dataId).values;\n  const finalDim = $x.shape[$x.shape.length - 1];\n  const indexAdjuster = reverse5 ? (i2, j) => i2 + finalDim - j - 1 : (i2, j) => i2 + j;\n  for (let i2 = 0; i2 < aVals.length; i2 += finalDim) {\n    for (let j = 0; j < finalDim; j++) {\n      const idx = indexAdjuster(i2, j);\n      if (j === 0) {\n        vals[idx] = exclusive ? 0 : aVals[idx];\n      } else {\n        const prevIdx = indexAdjuster(i2, j - 1);\n        vals[idx] = exclusive ? aVals[prevIdx] + vals[prevIdx] : aVals[idx] + vals[prevIdx];\n      }\n    }\n  }\n  const result = backend2.makeTensorInfo($x.shape, resultDtype, vals);\n  if (permutation != null) {\n    const reversePermutation = backend_util_exports.getUndoAxesPermutation(permutation);\n    const reverseTransposedResult = transpose2({ inputs: { x: result }, backend: backend2, attrs: { perm: reversePermutation } });\n    backend2.disposeIntermediateTensorInfo(result);\n    backend2.disposeIntermediateTensorInfo($x);\n    return reverseTransposedResult;\n  }\n  return result;\n}\nvar cumsumConfig = {\n  kernelName: Cumsum,\n  backendName: \"cpu\",\n  kernelFunc: cumsum2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/DenseBincount.js\nfunction denseBincount2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, weights } = inputs;\n  const { size, binaryOutput } = attrs;\n  if (x.shape.length === 1) {\n    const xVals = backend2.data.get(x.dataId).values;\n    const weightsVals = backend2.data.get(weights.dataId).values;\n    const outVals = bincountImpl(xVals, weightsVals, weights.dtype, weights.shape, size);\n    return backend2.makeTensorInfo([size], weights.dtype, outVals);\n  } else if (x.shape.length === 2) {\n    const xBuf = backend2.bufferSync(x);\n    const weightsBuf = backend2.bufferSync(weights);\n    const outBuf = bincountReduceImpl(xBuf, weightsBuf, size, binaryOutput);\n    return backend2.makeTensorInfo(outBuf.shape, weights.dtype, outBuf.values);\n  }\n  throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${x.shape.length}.`);\n}\nvar denseBincountConfig = {\n  kernelName: DenseBincount,\n  backendName: \"cpu\",\n  kernelFunc: denseBincount2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/DepthToSpace.js\nfunction depthToSpace2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockSize, dataFormat } = attrs;\n  util_exports.assert(dataFormat === \"NHWC\", () => `Only NHWC dataFormat supported on CPU for depthToSpace. Got ${dataFormat}`);\n  const batchSize = x.shape[0];\n  const inputHeight = x.shape[1];\n  const inputWidth = x.shape[2];\n  const inputDepth = x.shape[3];\n  const outputHeight = inputHeight * blockSize;\n  const outputWidth = inputWidth * blockSize;\n  const outputDepth = inputDepth / (blockSize * blockSize);\n  const xValues = backend2.data.get(x.dataId).values;\n  const result = new Float32Array(batchSize * outputHeight * outputWidth * outputDepth);\n  let outputIdx = 0;\n  for (let b = 0; b < batchSize; ++b) {\n    for (let h = 0; h < outputHeight; ++h) {\n      const inH = Math.floor(h / blockSize);\n      const offsetH = h % blockSize;\n      for (let w = 0; w < outputWidth; ++w) {\n        const inW = Math.floor(w / blockSize);\n        const offsetW = w % blockSize;\n        const offsetD = (offsetH * blockSize + offsetW) * outputDepth;\n        for (let d = 0; d < outputDepth; ++d) {\n          const inD = d + offsetD;\n          const inputIdx = inD + inputDepth * (inW + inputWidth * (inH + inputHeight * b));\n          result[outputIdx++] = xValues[inputIdx];\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo([batchSize, outputHeight, outputWidth, outputDepth], x.dtype, result);\n}\nvar depthToSpaceConfig = {\n  kernelName: DepthToSpace,\n  backendName: \"cpu\",\n  kernelFunc: depthToSpace2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/DepthwiseConv2dNative.js\nfunction depthwiseConv2dNative(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dilations, dimRoundingMode } = attrs;\n  assertNotComplex([x, filter], \"depthwiseConv2DNative\");\n  const xStrides = util_exports.computeStrides(x.shape);\n  const filterStrides = util_exports.computeStrides(filter.shape);\n  let $dilations = dilations;\n  if ($dilations == null) {\n    $dilations = [1, 1];\n  }\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, $dilations), () => `Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${strides} and dilations '${$dilations}'`);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad3, dimRoundingMode, true);\n  const { filterHeight, filterWidth, dilationHeight, dilationWidth, padInfo } = convInfo;\n  const padLeft = padInfo.left;\n  const padTop = padInfo.top;\n  const chMul = convInfo.outChannels / convInfo.inChannels;\n  const y = new TensorBuffer(convInfo.outShape, x.dtype);\n  const xVals = backend2.data.get(x.dataId).values;\n  const wVals = backend2.data.get(filter.dataId).values;\n  const yVals = y.values;\n  for (let b = 0; b < convInfo.batchSize; ++b) {\n    const xOffset1 = b * xStrides[0];\n    const yOffset1 = b * y.strides[0];\n    for (let yR = 0; yR < convInfo.outHeight; ++yR) {\n      const yOffset2 = yOffset1 + yR * y.strides[1];\n      const xRCorner = yR * convInfo.strideHeight - padTop;\n      for (let wR = 0; wR < filterHeight; ++wR) {\n        const xR = xRCorner + wR * dilationHeight;\n        if (xR < 0 || xR >= convInfo.inHeight) {\n          continue;\n        }\n        const wOffset1 = wR * filterStrides[0];\n        const xOffset2 = xOffset1 + xR * xStrides[1];\n        for (let yC = 0; yC < convInfo.outWidth; ++yC) {\n          const yOffset3 = yOffset2 + yC * y.strides[2];\n          const xCCorner = yC * convInfo.strideWidth - padLeft;\n          for (let wC = 0; wC < filterWidth; ++wC) {\n            const xC = xCCorner + wC * dilationWidth;\n            if (xC < 0 || xC >= convInfo.inWidth) {\n              continue;\n            }\n            const wOffset2 = wOffset1 + wC * filterStrides[1];\n            const xOffset3 = xOffset2 + xC * convInfo.inChannels;\n            let yOffset4 = yOffset3;\n            let wOffset3 = wOffset2;\n            for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {\n              const xVal = xVals[xOffset3 + d1];\n              for (let q = 0; q < chMul; ++q) {\n                yVals[yOffset4 + q] += xVal * wVals[wOffset3 + q];\n              }\n              yOffset4 += chMul;\n              wOffset3 += chMul;\n            }\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(y.shape, y.dtype, y.values);\n}\nvar depthwiseConv2dNativeConfig = {\n  kernelName: DepthwiseConv2dNative,\n  backendName: \"cpu\",\n  kernelFunc: depthwiseConv2dNative\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/DepthwiseConv2dNativeBackpropFilter.js\nfunction depthwiseConv2dNativeBackpropFilter2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, dy } = inputs;\n  const { strides, dilations, pad: pad3, dimRoundingMode, filterShape } = attrs;\n  assertNotComplex([x, dy], \"depthwiseConv2dNativeBackpropFilter\");\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filterShape, strides, dilations, pad3, dimRoundingMode, true);\n  const { strideHeight, strideWidth, filterHeight, filterWidth } = convInfo;\n  const dW = new TensorBuffer(convInfo.filterShape, \"float32\");\n  const leftPad = convInfo.padInfo.left;\n  const topPad = convInfo.padInfo.top;\n  const chMul = convInfo.outChannels / convInfo.inChannels;\n  const xVals = backend2.data.get(x.dataId).values;\n  const xBuf = new TensorBuffer(x.shape, x.dtype, xVals);\n  const dyVals = backend2.data.get(dy.dataId).values;\n  const dyBuf = new TensorBuffer(dy.shape, dy.dtype, dyVals);\n  for (let wR = 0; wR < filterHeight; ++wR) {\n    const yRMin = Math.max(0, Math.ceil((topPad - wR) / strideHeight));\n    const yRMax = Math.min(convInfo.outHeight, (convInfo.inHeight + topPad - wR) / strideHeight);\n    for (let wC = 0; wC < filterWidth; ++wC) {\n      const yCMin = Math.max(0, Math.ceil((leftPad - wC) / strideWidth));\n      const yCMax = Math.min(convInfo.outWidth, (convInfo.inWidth + leftPad - wC) / strideWidth);\n      for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {\n        const d1 = Math.trunc(d2 / chMul);\n        const dm = d2 % chMul;\n        let dotProd = 0;\n        for (let b = 0; b < convInfo.batchSize; ++b) {\n          for (let yR = yRMin; yR < yRMax; ++yR) {\n            const xR = wR + yR * strideHeight - topPad;\n            for (let yC = yCMin; yC < yCMax; ++yC) {\n              const xC = wC + yC * strideWidth - leftPad;\n              dotProd += xBuf.get(b, xR, xC, d1) * dyBuf.get(b, yR, yC, d2);\n            }\n          }\n        }\n        dW.set(dotProd, wR, wC, d1, dm);\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dW.shape, dW.dtype, dW.values);\n}\nvar depthwiseConv2dNativeBackpropFilterConfig = {\n  kernelName: DepthwiseConv2dNativeBackpropFilter,\n  backendName: \"cpu\",\n  kernelFunc: depthwiseConv2dNativeBackpropFilter2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/DepthwiseConv2dNativeBackpropInput.js\nfunction depthwiseConv2dNativeBackpropInput2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, filter } = inputs;\n  const { strides, dilations, pad: pad3, dimRoundingMode, inputShape } = attrs;\n  assertNotComplex([dy, filter], \"depthwiseConv2DNativeBackpropInput\");\n  const dyStrides = util_exports.computeStrides(dy.shape);\n  const filterStrides = util_exports.computeStrides(filter.shape);\n  const convInfo = backend_util_exports.computeConv2DInfo(inputShape, filter.shape, strides, dilations, pad3, dimRoundingMode, true);\n  const dx = new TensorBuffer(convInfo.inShape, \"float32\");\n  const dxValues = dx.values;\n  const [dxS0, dxS1, dxS2] = dx.strides;\n  const dyValues = backend2.data.get(dy.dataId).values;\n  const [dyS0, dyS1, dyS2] = dyStrides;\n  const fltValues = backend2.data.get(filter.dataId).values;\n  const [fltS0, fltS1, fltS2] = filterStrides;\n  const { batchSize, filterHeight, filterWidth, inChannels, inHeight, inWidth, outChannels, outHeight, outWidth, strideHeight, strideWidth } = convInfo;\n  const topPad = filterHeight - 1 - convInfo.padInfo.top;\n  const leftPad = filterWidth - 1 - convInfo.padInfo.left;\n  const chMul = outChannels / inChannels;\n  for (let b = 0; b < batchSize; ++b) {\n    for (let d1 = 0; d1 < inChannels; ++d1) {\n      for (let xR = 0; xR < inHeight; ++xR) {\n        const xRCorner = xR - topPad;\n        const xRMin = Math.max(0, Math.ceil(xRCorner / strideHeight));\n        const yRMax = Math.min(outHeight, (filterHeight + xRCorner) / strideHeight);\n        for (let xC = 0; xC < inWidth; ++xC) {\n          const xCCorner = xC - leftPad;\n          const xCMin = Math.max(0, Math.ceil(xCCorner / strideWidth));\n          const yCMax = Math.min(outWidth, (filterWidth + xCCorner) / strideWidth);\n          let dotProd = 0;\n          for (let yR = xRMin; yR < yRMax; ++yR) {\n            const wR = yR * strideHeight - xRCorner;\n            for (let yC = xCMin; yC < yCMax; ++yC) {\n              const wC = yC * strideWidth - xCCorner;\n              const dyOffset = dyS0 * b + dyS1 * yR + dyS2 * yC;\n              const fltOffset = fltS0 * (filterHeight - 1 - wR) + fltS1 * (filterWidth - 1 - wC) + fltS2 * d1;\n              for (let dm = 0; dm < chMul; ++dm) {\n                const d2 = d1 * chMul + dm;\n                const pixel = dyValues[dyOffset + d2];\n                const weight = fltValues[fltOffset + dm];\n                dotProd += pixel * weight;\n              }\n            }\n          }\n          dxValues[dxS0 * b + dxS1 * xR + dxS2 * xC + d1] = dotProd;\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dx.shape, dx.dtype, dx.values);\n}\nvar depthwiseConv2dNativeBackpropInputConfig = {\n  kernelName: DepthwiseConv2dNativeBackpropInput,\n  backendName: \"cpu\",\n  kernelFunc: depthwiseConv2dNativeBackpropInput2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Diag.js\nfunction diag2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const xVals = backend2.data.get(x.dataId).values;\n  const outBuf = buffer([xSize, xSize], x.dtype);\n  const vals = outBuf.values;\n  for (let i2 = 0; i2 < xVals.length; i2++) {\n    vals[i2 * xSize + i2] = xVals[i2];\n  }\n  const outShape = [...x.shape, ...x.shape];\n  return backend2.makeTensorInfo(outShape, outBuf.dtype, outBuf.values);\n}\nvar diagConfig = {\n  kernelName: Diag,\n  backendName: \"cpu\",\n  kernelFunc: diag2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Dilation2D.js\nvar dilation2DConfig = {\n  kernelName: Dilation2D,\n  backendName: \"cpu\",\n  kernelFunc: ({ inputs, backend: backend2, attrs }) => {\n    const { x, filter } = inputs;\n    const { strides, pad: pad3, dilations } = attrs;\n    const cpuBackend = backend2;\n    const xVals = cpuBackend.data.get(x.dataId).values;\n    const xRank = x.shape.length;\n    const filterVals = cpuBackend.data.get(filter.dataId).values;\n    const filterRank = filter.shape.length;\n    const { batchSize, inHeight, inWidth, inChannels, outHeight, outWidth, padInfo, strideHeight, strideWidth, filterHeight, filterWidth, dilationHeight, dilationWidth, outShape } = backend_util_exports.computeDilation2DInfo(x.shape, filter.shape, strides, pad3, \"NHWC\", dilations);\n    const outSize = util_exports.sizeFromShape(outShape);\n    const outRank = outShape.length;\n    const outputVals = util_exports.getArrayFromDType(x.dtype, outSize);\n    for (let b = 0; b < batchSize; ++b) {\n      for (let hOut = 0; hOut < outHeight; ++hOut) {\n        const hBeg = hOut * strideHeight - padInfo.top;\n        for (let wOut = 0; wOut < outWidth; ++wOut) {\n          const wBeg = wOut * strideWidth - padInfo.left;\n          for (let d = 0; d < inChannels; ++d) {\n            let curVal = Number.MIN_SAFE_INTEGER;\n            for (let h = 0; h < filterHeight; ++h) {\n              const hIn = hBeg + h * dilationHeight;\n              if (hIn >= 0 && hIn < inHeight) {\n                for (let w = 0; w < filterWidth; ++w) {\n                  const wIn = wBeg + w * dilationWidth;\n                  if (wIn >= 0 && wIn < inWidth) {\n                    const xIndex = util_exports.locToIndex([b, hIn, wIn, d], xRank, util_exports.computeStrides(x.shape));\n                    const filterIndex = util_exports.locToIndex([h, w, d], filterRank, util_exports.computeStrides(filter.shape));\n                    const val = xVals[xIndex] + filterVals[filterIndex];\n                    if (val > curVal) {\n                      curVal = val;\n                    }\n                  }\n                }\n              }\n            }\n            const outputIndex = util_exports.locToIndex([b, hOut, wOut, d], outRank, util_exports.computeStrides(outShape));\n            outputVals[outputIndex] = curVal;\n          }\n        }\n      }\n    }\n    const dataId = cpuBackend.write(util_exports.toTypedArray(outputVals, x.dtype), outShape, x.dtype);\n    return { dataId, shape: outShape, dtype: x.dtype };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Dilation2DBackpropFilter.js\nvar dilation2DBackpropFilterConfig = {\n  kernelName: Dilation2DBackpropFilter,\n  backendName: \"cpu\",\n  kernelFunc: ({ inputs, backend: backend2, attrs }) => {\n    const { x, filter, dy } = inputs;\n    const { strides, pad: pad3, dilations } = attrs;\n    const cpuBackend = backend2;\n    const $x = util_exports.toNestedArray(x.shape, cpuBackend.data.get(x.dataId).values);\n    const $filter = util_exports.toNestedArray(filter.shape, cpuBackend.data.get(filter.dataId).values);\n    const { batchSize, inHeight, inWidth, inChannels, outHeight, outWidth, padInfo, strideHeight, strideWidth, filterHeight, filterWidth, dilationHeight, dilationWidth, outShape } = backend_util_exports.computeDilation2DInfo(x.shape, filter.shape, strides, pad3, \"NHWC\", dilations);\n    util_exports.assert(dy.rank === outShape.length, () => `Error in ${Dilation2DBackpropFilter}, dy must have the same rank as output ${outShape.length}, but got ${dy.rank}`);\n    const $dy = util_exports.toNestedArray(outShape, cpuBackend.data.get(dy.dataId).values);\n    const gradients = util_exports.makeZerosNestedTypedArray(filter.shape, filter.dtype);\n    for (let b = 0; b < batchSize; ++b) {\n      for (let hOut = 0; hOut < outHeight; ++hOut) {\n        const hBeg = hOut * strideHeight - padInfo.top;\n        for (let wOut = 0; wOut < outWidth; ++wOut) {\n          const wBeg = wOut * strideWidth - padInfo.left;\n          for (let d = 0; d < inChannels; ++d) {\n            let curVal = Number.MIN_SAFE_INTEGER;\n            let hMax = 0;\n            let wMax = 0;\n            for (let h = 0; h < filterHeight; ++h) {\n              const hIn = hBeg + h * dilationHeight;\n              if (hIn >= 0 && hIn < inHeight) {\n                for (let w = 0; w < filterWidth; ++w) {\n                  const wIn = wBeg + w * dilationWidth;\n                  if (wIn >= 0 && wIn < inWidth) {\n                    const val = $x[b][hIn][wIn][d] + $filter[h][w][d];\n                    if (val > curVal) {\n                      curVal = val;\n                      hMax = h;\n                      wMax = w;\n                    }\n                  }\n                }\n              }\n            }\n            gradients[hMax][wMax][d] += $dy[b][hOut][wOut][d];\n          }\n        }\n      }\n    }\n    const dataId = cpuBackend.write(util_exports.toTypedArray(gradients, x.dtype), filter.shape, filter.dtype);\n    return { dataId, shape: filter.shape, dtype: filter.dtype };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Dilation2DBackpropInput.js\nvar dilation2DBackpropInputConfig = {\n  kernelName: Dilation2DBackpropInput,\n  backendName: \"cpu\",\n  kernelFunc: ({ inputs, backend: backend2, attrs }) => {\n    const { x, filter, dy } = inputs;\n    const { strides, pad: pad3, dilations } = attrs;\n    const cpuBackend = backend2;\n    const $x = util_exports.toNestedArray(x.shape, cpuBackend.data.get(x.dataId).values);\n    const $filter = util_exports.toNestedArray(filter.shape, cpuBackend.data.get(filter.dataId).values);\n    const { batchSize, inHeight, inWidth, inChannels, outHeight, outWidth, padInfo, strideHeight, strideWidth, filterHeight, filterWidth, dilationHeight, dilationWidth, outShape } = backend_util_exports.computeDilation2DInfo(x.shape, filter.shape, strides, pad3, \"NHWC\", dilations);\n    util_exports.assert(dy.rank === outShape.length, () => `Error in ${Dilation2DBackpropInput}, dy must have the same rank as output ${outShape.length}, but got ${dy.rank}`);\n    const $dy = util_exports.toNestedArray(outShape, cpuBackend.data.get(dy.dataId).values);\n    const gradients = util_exports.makeZerosNestedTypedArray(x.shape, x.dtype);\n    for (let b = 0; b < batchSize; ++b) {\n      for (let hOut = 0; hOut < outHeight; ++hOut) {\n        const hBeg = hOut * strideHeight - padInfo.top;\n        for (let wOut = 0; wOut < outWidth; ++wOut) {\n          const wBeg = wOut * strideWidth - padInfo.left;\n          for (let d = 0; d < inChannels; ++d) {\n            let curVal = Number.MIN_SAFE_INTEGER;\n            let hInMax = hBeg < 0 ? 0 : hBeg;\n            let wInMax = wBeg < 0 ? 0 : wBeg;\n            for (let h = 0; h < filterHeight; ++h) {\n              const hIn = hBeg + h * dilationHeight;\n              if (hIn >= 0 && hIn < inHeight) {\n                for (let w = 0; w < filterWidth; ++w) {\n                  const wIn = wBeg + w * dilationWidth;\n                  if (wIn >= 0 && wIn < inWidth) {\n                    const val = $x[b][hIn][wIn][d] + $filter[h][w][d];\n                    if (val > curVal) {\n                      curVal = val;\n                      hInMax = hIn;\n                      wInMax = wIn;\n                    }\n                  }\n                }\n              }\n            }\n            gradients[b][hInMax][wInMax][d] += $dy[b][hOut][wOut][d];\n          }\n        }\n      }\n    }\n    const dataId = cpuBackend.write(util_exports.toTypedArray(gradients, x.dtype), x.shape, x.dtype);\n    return { dataId, shape: x.shape, dtype: x.dtype };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Sum.js\nfunction sum3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  assertNotComplex(x, \"sum\");\n  let $x;\n  if (x.dtype === \"bool\") {\n    $x = cast3({ inputs: { x }, backend: backend2, attrs: { dtype: \"int32\" } });\n  } else {\n    $x = identity2({ inputs: { x }, backend: backend2 });\n  }\n  const xRank = $x.shape.length;\n  const axes = util_exports.parseAxisParam(axis, $x.shape);\n  const permutation = backend_util_exports.getAxesPermutation(axes, xRank);\n  let reductionAxes = axes;\n  let permutedX = $x;\n  if (permutation != null) {\n    permutedX = transpose2({ inputs: { x: $x }, backend: backend2, attrs: { perm: permutation } });\n    reductionAxes = backend_util_exports.getInnerMostAxes(reductionAxes.length, xRank);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"sum\", reductionAxes, permutedX.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(permutedX.shape, reductionAxes);\n  const resultDtype = backend_util_exports.upcastType(permutedX.dtype, \"int32\");\n  let result = zeros3(backend2, outShape, resultDtype);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const vals = backend2.data.get(result.dataId).values;\n  const aVals = backend2.data.get(permutedX.dataId).values;\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let sum7 = 0;\n    for (let j = 0; j < reduceSize; ++j) {\n      sum7 += aVals[offset + j];\n    }\n    vals[i2] = sum7;\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(result.shape, axes);\n    const oldResult = result;\n    result = reshape3({ inputs: { x: result }, backend: backend2, attrs: { shape: newShape } });\n    backend2.disposeIntermediateTensorInfo(oldResult);\n  }\n  backend2.disposeIntermediateTensorInfo($x);\n  if (permutation != null) {\n    backend2.disposeIntermediateTensorInfo(permutedX);\n  }\n  return result;\n}\nvar sumConfig = {\n  kernelName: Sum,\n  backendName: \"cpu\",\n  kernelFunc: sum3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Einsum.js\nfunction einsum2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { equation } = attrs;\n  const tensors = inputs;\n  const { allDims, summedDims, idDims } = backend_util_exports.decodeEinsumEquation(equation, tensors.length);\n  backend_util_exports.checkEinsumDimSizes(allDims.length, idDims, tensors);\n  const { path, steps } = backend_util_exports.getEinsumComputePath(summedDims, idDims);\n  const nSteps = steps.length;\n  let out = null;\n  let numDimsRemaining = allDims.length;\n  const tensorsToDispose = [];\n  for (let i2 = 0; i2 < nSteps; ++i2) {\n    for (const idTerm of steps[i2]) {\n      const { permutationIndices: perm, expandDims: dimsToExpand } = backend_util_exports.getEinsumPermutation(numDimsRemaining, idDims[idTerm]);\n      let x;\n      if (backend_util_exports.isIdentityPermutation(perm)) {\n        x = tensors[idTerm];\n      } else {\n        x = transpose2({ inputs: { x: tensors[idTerm] }, backend: backend2, attrs: { perm } });\n        tensorsToDispose.push(x);\n      }\n      const targetShape = x.shape.slice();\n      for (let k = 0; k < dimsToExpand.length; ++k) {\n        targetShape.splice(dimsToExpand[k], 0, 1);\n      }\n      if (!util_exports.arraysEqual(x.shape, targetShape)) {\n        x = reshape3({ inputs: { x }, backend: backend2, attrs: { shape: targetShape } });\n        tensorsToDispose.push(x);\n      }\n      if (out === null) {\n        out = x;\n      } else {\n        out = multiply2({ inputs: { a: x, b: out }, backend: backend2 });\n        tensorsToDispose.push(out);\n      }\n    }\n    if (i2 < nSteps - 1) {\n      if (path[i2] >= 0) {\n        out = sum3({\n          inputs: { x: out },\n          backend: backend2,\n          attrs: {\n            axis: path[i2] - (allDims.length - numDimsRemaining),\n            keepDims: false\n          }\n        });\n        tensorsToDispose.push(out);\n      }\n      numDimsRemaining--;\n    }\n  }\n  for (const tensorInfo of tensorsToDispose) {\n    if (tensorInfo === out) {\n      continue;\n    }\n    backend2.disposeIntermediateTensorInfo(tensorInfo);\n  }\n  return out;\n}\nvar einsumConfig = {\n  kernelName: Einsum,\n  backendName: \"cpu\",\n  kernelFunc: einsum2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/EluGrad.js\nfunction eluGrad(args) {\n  const { inputs, backend: backend2 } = args;\n  const { dy, y } = inputs;\n  assertNotComplex([dy, y], \"eluGrad\");\n  const resultValues = new Float32Array(util_exports.sizeFromShape(y.shape));\n  const values = backend2.data.get(y.dataId).values;\n  const dyValues = backend2.data.get(dy.dataId).values;\n  for (let i2 = 0; i2 < values.length; ++i2) {\n    const v = values[i2];\n    if (v >= 1) {\n      resultValues[i2] = dyValues[i2];\n    } else {\n      resultValues[i2] = dyValues[i2] * (v + 1);\n    }\n  }\n  return backend2.makeTensorInfo(y.shape, \"float32\", resultValues);\n}\nvar eluGradConfig2 = {\n  kernelName: EluGrad,\n  backendName: \"cpu\",\n  kernelFunc: eluGrad\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Erf.js\nvar p = backend_util_exports.ERF_P;\nvar a1 = backend_util_exports.ERF_A1;\nvar a2 = backend_util_exports.ERF_A2;\nvar a3 = backend_util_exports.ERF_A3;\nvar a4 = backend_util_exports.ERF_A4;\nvar a5 = backend_util_exports.ERF_A5;\nvar erf2 = unaryKernelFunc(Erf, (xi) => {\n  const sign4 = Math.sign(xi);\n  const v = Math.abs(xi);\n  const t2 = 1 / (1 + p * v);\n  return sign4 * (1 - ((((a5 * t2 + a4) * t2 + a3) * t2 + a2) * t2 + a1) * t2 * Math.exp(-v * v));\n});\nvar erfConfig = {\n  kernelName: Erf,\n  backendName: \"cpu\",\n  kernelFunc: erf2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ExpandDims.js\nfunction expandDims3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { input: input2 } = inputs;\n  const { dim } = attrs;\n  const inputRank = input2.shape.length;\n  const newShape = input2.shape.slice();\n  let $dim = dim;\n  if (dim < 0) {\n    util_exports.assert(-(inputRank + 1) <= dim, () => `Axis must be in the interval [${-(inputRank + 1)}, ${inputRank}]`);\n    $dim = inputRank + dim + 1;\n  }\n  newShape.splice($dim, 0, 1);\n  return reshape3({ inputs: { x: input2 }, backend: backend2, attrs: { shape: newShape } });\n}\nvar expandDimsConfig = {\n  kernelName: ExpandDims,\n  backendName: \"cpu\",\n  kernelFunc: expandDims3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/RealDiv.js\nvar realDivImpl = createSimpleBinaryKernelImpl((a, b) => a / b);\nvar div2 = binaryKernelFunc(RealDiv, realDivImpl);\nvar realDivConfig = {\n  kernelName: RealDiv,\n  backendName: \"cpu\",\n  kernelFunc: div2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/fft_utils.js\nfunction fftBatch(input2, inverse, cpuBackend) {\n  const inputShape = input2.shape;\n  const batch = inputShape[0];\n  const innerDim = inputShape[1];\n  const inputVals = cpuBackend.data.get(input2.dataId);\n  const real2D = inputVals.complexTensorInfos.real;\n  const imag2D = inputVals.complexTensorInfos.imag;\n  const resultShape = [batch, innerDim];\n  const resultSize = util_exports.sizeFromShape(resultShape);\n  const resultReal = util_exports.getTypedArrayFromDType(\"float32\", resultSize);\n  const resultImag = util_exports.getTypedArrayFromDType(\"float32\", resultSize);\n  for (let b = 0; b < batch; b++) {\n    const r2 = slice2({\n      inputs: { x: real2D },\n      backend: cpuBackend,\n      attrs: { begin: [b, 0], size: [1, innerDim] }\n    });\n    const i2 = slice2({\n      inputs: { x: imag2D },\n      backend: cpuBackend,\n      attrs: { begin: [b, 0], size: [1, innerDim] }\n    });\n    const input3 = complex2({ inputs: { real: r2, imag: i2 }, backend: cpuBackend });\n    const { real: real5, imag: imag5 } = fftImpl(input3, inverse, cpuBackend);\n    const res = backend_util_exports.mergeRealAndImagArrays(real5, imag5);\n    for (let d = 0; d < innerDim; d++) {\n      const c = backend_util_exports.getComplexWithIndex(res, d);\n      resultReal[b * innerDim + d] = c.real;\n      resultImag[b * innerDim + d] = c.imag;\n    }\n    cpuBackend.disposeIntermediateTensorInfo(r2);\n    cpuBackend.disposeIntermediateTensorInfo(i2);\n    cpuBackend.disposeIntermediateTensorInfo(input3);\n  }\n  const $realInfo = cpuBackend.makeTensorInfo(resultShape, \"float32\", resultReal);\n  const $imagInfo = cpuBackend.makeTensorInfo(resultShape, \"float32\", resultImag);\n  const result = complex2({ inputs: { real: $realInfo, imag: $imagInfo }, backend: cpuBackend });\n  cpuBackend.disposeIntermediateTensorInfo($realInfo);\n  cpuBackend.disposeIntermediateTensorInfo($imagInfo);\n  return result;\n}\nfunction fftImpl(input2, inverse, cpuBackend) {\n  const inputSize = util_exports.sizeFromShape(input2.shape);\n  const inputVals = cpuBackend.data.get(input2.dataId);\n  const realVals = cpuBackend.data.get(inputVals.complexTensorInfos.real.dataId).values;\n  const imagVals = cpuBackend.data.get(inputVals.complexTensorInfos.imag.dataId).values;\n  if (isExponentOf2(inputSize)) {\n    const result = fftRadix2(realVals, imagVals, inputSize, inverse, cpuBackend);\n    const resultShape = [input2.shape[0], input2.shape[1]];\n    if (inverse) {\n      const realInfo = cpuBackend.makeTensorInfo(resultShape, \"float32\", result.real);\n      const imagInfo = cpuBackend.makeTensorInfo(resultShape, \"float32\", result.imag);\n      const sizeInfo = cpuBackend.makeTensorInfo([], \"float32\", util_exports.createScalarValue(inputSize, \"float32\"));\n      const sizeInfoCopy = identity2({ inputs: { x: sizeInfo }, backend: cpuBackend });\n      const divRealInfo = realDivConfig.kernelFunc({ inputs: { a: realInfo, b: sizeInfo }, backend: cpuBackend });\n      const divImagInfo = realDivConfig.kernelFunc({ inputs: { a: imagInfo, b: sizeInfoCopy }, backend: cpuBackend });\n      const divRealVals = cpuBackend.data.get(divRealInfo.dataId).values;\n      const divImagVals = cpuBackend.data.get(divImagInfo.dataId).values;\n      cpuBackend.disposeIntermediateTensorInfo(realInfo);\n      cpuBackend.disposeIntermediateTensorInfo(imagInfo);\n      cpuBackend.disposeIntermediateTensorInfo(sizeInfo);\n      cpuBackend.disposeIntermediateTensorInfo(sizeInfoCopy);\n      cpuBackend.disposeIntermediateTensorInfo(divRealInfo);\n      cpuBackend.disposeIntermediateTensorInfo(divImagInfo);\n      return { real: divRealVals, imag: divImagVals };\n    }\n    return result;\n  } else {\n    const data = backend_util_exports.mergeRealAndImagArrays(realVals, imagVals);\n    const rawOutput = fourierTransformByMatmul(data, inputSize, inverse);\n    return backend_util_exports.splitRealAndImagArrays(rawOutput);\n  }\n}\nfunction isExponentOf2(size) {\n  return (size & size - 1) === 0;\n}\nfunction fftRadix2(realVals, imagVals, size, inverse, cpuBackend) {\n  if (size === 1) {\n    return { real: realVals, imag: imagVals };\n  }\n  const data = backend_util_exports.mergeRealAndImagArrays(realVals, imagVals);\n  const half = size / 2;\n  const evenComplex = backend_util_exports.complexWithEvenIndex(data);\n  const evenRealVals = evenComplex.real;\n  const evenImagVals = evenComplex.imag;\n  const evenShape = [evenRealVals.length];\n  const evenRealInfo = cpuBackend.makeTensorInfo(evenShape, \"float32\", evenRealVals);\n  const evenImagInfo = cpuBackend.makeTensorInfo(evenShape, \"float32\", evenImagVals);\n  const evenTensorInfo = complex2({ inputs: { real: evenRealInfo, imag: evenImagInfo }, backend: cpuBackend });\n  const oddComplex = backend_util_exports.complexWithOddIndex(data);\n  const oddRealVals = oddComplex.real;\n  const oddImagVals = oddComplex.imag;\n  const oddShape = [oddRealVals.length];\n  const oddRealInfo = cpuBackend.makeTensorInfo(oddShape, \"float32\", oddRealVals);\n  const oddImagInfo = cpuBackend.makeTensorInfo(oddShape, \"float32\", oddImagVals);\n  const oddTensorInfo = complex2({ inputs: { real: oddRealInfo, imag: oddImagInfo }, backend: cpuBackend });\n  const $evenComplex = fftRadix2(evenRealVals, evenImagVals, half, inverse, cpuBackend);\n  const $evenRealVals = $evenComplex.real;\n  const $evenImagVals = $evenComplex.imag;\n  const $evenShape = [$evenRealVals.length];\n  const $evenRealInfo = cpuBackend.makeTensorInfo($evenShape, \"float32\", $evenRealVals);\n  const $evenImagInfo = cpuBackend.makeTensorInfo($evenShape, \"float32\", $evenImagVals);\n  const $evenTensorInfo = complex2({\n    inputs: { real: $evenRealInfo, imag: $evenImagInfo },\n    backend: cpuBackend\n  });\n  const $oddComplex = fftRadix2(oddRealVals, oddImagVals, half, inverse, cpuBackend);\n  const $oddRealVals = $oddComplex.real;\n  const $oddImagVals = $oddComplex.imag;\n  const $oddShape = [$oddRealVals.length];\n  const $oddRealInfo = cpuBackend.makeTensorInfo($oddShape, \"float32\", $oddRealVals);\n  const $oddImagInfo = cpuBackend.makeTensorInfo($oddShape, \"float32\", $oddImagVals);\n  const $oddTensorInfo = complex2({ inputs: { real: $oddRealInfo, imag: $oddImagInfo }, backend: cpuBackend });\n  const e2 = backend_util_exports.exponents(size, inverse);\n  const eShape = [e2.real.length];\n  const eRealInfo = cpuBackend.makeTensorInfo(eShape, \"float32\", e2.real);\n  const eImagInfo = cpuBackend.makeTensorInfo(eShape, \"float32\", e2.imag);\n  const complexInfo = complex2({ inputs: { real: eRealInfo, imag: eImagInfo }, backend: cpuBackend });\n  const exponentInfo = multiply2({ inputs: { a: complexInfo, b: $oddTensorInfo }, backend: cpuBackend });\n  const addPart = add4({\n    inputs: { a: $evenTensorInfo, b: exponentInfo },\n    backend: cpuBackend\n  });\n  const subPart = sub2({\n    inputs: { a: $evenTensorInfo, b: exponentInfo },\n    backend: cpuBackend\n  });\n  const addPartReal = real2({ inputs: { input: addPart }, backend: cpuBackend });\n  const subPartReal = real2({ inputs: { input: subPart }, backend: cpuBackend });\n  const addPartImag = imag2({ inputs: { input: addPart }, backend: cpuBackend });\n  const subPartImag = imag2({ inputs: { input: subPart }, backend: cpuBackend });\n  const $real = concat2({\n    inputs: [addPartReal, subPartReal],\n    backend: cpuBackend,\n    attrs: { axis: 0 }\n  });\n  const $imag = concat2({\n    inputs: [addPartImag, subPartImag],\n    backend: cpuBackend,\n    attrs: { axis: 0 }\n  });\n  const $realVals = cpuBackend.data.get($real.dataId).values;\n  const $imagVals = cpuBackend.data.get($imag.dataId).values;\n  cpuBackend.disposeIntermediateTensorInfo(evenRealInfo);\n  cpuBackend.disposeIntermediateTensorInfo(evenImagInfo);\n  cpuBackend.disposeIntermediateTensorInfo(evenTensorInfo);\n  cpuBackend.disposeIntermediateTensorInfo(oddRealInfo);\n  cpuBackend.disposeIntermediateTensorInfo(oddImagInfo);\n  cpuBackend.disposeIntermediateTensorInfo(oddTensorInfo);\n  cpuBackend.disposeIntermediateTensorInfo($evenRealInfo);\n  cpuBackend.disposeIntermediateTensorInfo($evenImagInfo);\n  cpuBackend.disposeIntermediateTensorInfo($evenTensorInfo);\n  cpuBackend.disposeIntermediateTensorInfo($oddRealInfo);\n  cpuBackend.disposeIntermediateTensorInfo($oddImagInfo);\n  cpuBackend.disposeIntermediateTensorInfo($oddTensorInfo);\n  cpuBackend.disposeIntermediateTensorInfo(eRealInfo);\n  cpuBackend.disposeIntermediateTensorInfo(eImagInfo);\n  cpuBackend.disposeIntermediateTensorInfo(complexInfo);\n  cpuBackend.disposeIntermediateTensorInfo(exponentInfo);\n  cpuBackend.disposeIntermediateTensorInfo(addPart);\n  cpuBackend.disposeIntermediateTensorInfo(subPart);\n  cpuBackend.disposeIntermediateTensorInfo(addPartReal);\n  cpuBackend.disposeIntermediateTensorInfo(addPartImag);\n  cpuBackend.disposeIntermediateTensorInfo(subPartReal);\n  cpuBackend.disposeIntermediateTensorInfo(subPartImag);\n  cpuBackend.disposeIntermediateTensorInfo($real);\n  cpuBackend.disposeIntermediateTensorInfo($imag);\n  return { real: $realVals, imag: $imagVals };\n}\nfunction fourierTransformByMatmul(data, size, inverse) {\n  const ret = new Float32Array(size * 2);\n  for (let r2 = 0; r2 < size; r2++) {\n    let real5 = 0;\n    let imag5 = 0;\n    for (let c = 0; c < size; c++) {\n      const e2 = backend_util_exports.exponent(r2 * c, size, inverse);\n      const term = backend_util_exports.getComplexWithIndex(data, c);\n      real5 += term.real * e2.real - term.imag * e2.imag;\n      imag5 += term.real * e2.imag + term.imag * e2.real;\n    }\n    if (inverse) {\n      real5 /= size;\n      imag5 /= size;\n    }\n    backend_util_exports.assignToTypedArray(ret, real5, imag5, r2);\n  }\n  return ret;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/FFT.js\nfunction fft2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const inputSize = util_exports.sizeFromShape(input2.shape);\n  const innerDimensionSize = input2.shape[input2.shape.length - 1];\n  const batch = inputSize / innerDimensionSize;\n  const input2D = reshape3({\n    inputs: { x: input2 },\n    backend: backend2,\n    attrs: { shape: [batch, innerDimensionSize] }\n  });\n  const result = fftBatch(input2D, false, backend2);\n  const resultReshaped = reshape3({ inputs: { x: result }, backend: backend2, attrs: { shape: input2.shape } });\n  backend2.disposeIntermediateTensorInfo(input2D);\n  backend2.disposeIntermediateTensorInfo(result);\n  return resultReshaped;\n}\nvar fftConfig = {\n  kernelName: FFT,\n  backendName: \"cpu\",\n  kernelFunc: fft2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Fill.js\nfunction fill2(args) {\n  const { backend: backend2, attrs } = args;\n  const { shape, value, dtype } = attrs;\n  const $dtype = dtype || util_exports.inferDtype(value);\n  const values = util_exports.getArrayFromDType($dtype, util_exports.sizeFromShape(shape));\n  fillValues(values, value, $dtype);\n  return backend2.makeTensorInfo(shape, $dtype, values);\n}\nvar fillConfig = {\n  kernelName: Fill,\n  backendName: \"cpu\",\n  kernelFunc: fill2\n};\nfunction fillValues(values, value, dtype) {\n  if (dtype === \"string\") {\n    values.fill(value);\n  } else {\n    values.fill(value);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/FlipLeftRight.js\nvar flipLeftRightConfig = {\n  kernelName: FlipLeftRight,\n  backendName: \"cpu\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { image: image2 } = inputs;\n    const cpuBackend = backend2;\n    const output = util_exports.getTypedArrayFromDType(image2.dtype, util_exports.sizeFromShape(image2.shape));\n    const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n    const imageVals = cpuBackend.data.get(image2.dataId).values;\n    for (let batchIdx = 0; batchIdx < batch; batchIdx++) {\n      const batchOffset = batchIdx * imageWidth * imageHeight * numChannels;\n      for (let row = 0; row < imageHeight; row++) {\n        const rowOffset = row * (imageWidth * numChannels);\n        for (let col = 0; col < imageWidth; col++) {\n          const colOffset = col * numChannels;\n          for (let channel = 0; channel < numChannels; channel++) {\n            const coordX = Math.round(imageWidth - col - 1);\n            const outIdx = batchOffset + rowOffset + colOffset + channel;\n            let outputValue = imageVals[outIdx];\n            if (coordX >= 0 && coordX < imageWidth) {\n              const rotatedColOffset = coordX * numChannels;\n              const imageIdx = batchOffset + rowOffset + rotatedColOffset + channel;\n              outputValue = imageVals[imageIdx];\n            }\n            output[outIdx] = outputValue;\n          }\n        }\n      }\n    }\n    const dataId = cpuBackend.write(output, image2.shape, image2.dtype);\n    return { dataId, shape: image2.shape, dtype: image2.dtype };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/FloorDiv.js\nvar floorDivImpl = createSimpleBinaryKernelImpl((a, b) => Math.floor(a / b));\nvar floorDiv2 = binaryKernelFunc(FloorDiv, floorDivImpl, null, \"int32\");\nvar floorDivConfig = {\n  kernelName: FloorDiv,\n  backendName: \"cpu\",\n  kernelFunc: floorDiv2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/FusedConv2D.js\nfunction fusedConv2D(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  let result = conv2D({\n    inputs: { x, filter },\n    backend: backend2,\n    attrs: { strides, pad: pad3, dataFormat, dilations, dimRoundingMode }\n  });\n  if (bias) {\n    const resultOld = result;\n    if (dataFormat === \"NCHW\" && bias.shape.length === 1 && bias.shape[0] !== 1) {\n      const reshapedBias = reshape3({ inputs: { x: bias }, backend: backend2, attrs: { shape: [bias.shape[0], 1, 1] } });\n      result = add4({ inputs: { a: result, b: reshapedBias }, backend: backend2 });\n      backend2.disposeIntermediateTensorInfo(reshapedBias);\n    } else {\n      result = add4({ inputs: { a: result, b: bias }, backend: backend2 });\n    }\n    backend2.disposeIntermediateTensorInfo(resultOld);\n  }\n  if (activation2) {\n    const resultOld = result;\n    if (dataFormat === \"NCHW\" && activation2 === \"prelu\" && preluActivationWeights.shape.length === 1 && preluActivationWeights.shape[0] !== 1) {\n      const reshapedAlpha = reshape3({\n        inputs: { x: preluActivationWeights },\n        backend: backend2,\n        attrs: { shape: [preluActivationWeights.shape[0], 1, 1] }\n      });\n      result = applyActivation2(backend2, result, activation2, reshapedAlpha, leakyreluAlpha);\n      backend2.disposeIntermediateTensorInfo(reshapedAlpha);\n    } else {\n      result = applyActivation2(backend2, result, activation2, preluActivationWeights, leakyreluAlpha);\n    }\n    backend2.disposeIntermediateTensorInfo(resultOld);\n  }\n  return result;\n}\nvar fusedConv2DConfig = {\n  kernelName: FusedConv2D,\n  backendName: \"cpu\",\n  kernelFunc: fusedConv2D\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/FusedDepthwiseConv2D.js\nfunction fusedDepthwiseConv2D(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  let result = depthwiseConv2dNative({\n    inputs: { x, filter },\n    backend: backend2,\n    attrs: { strides, pad: pad3, dataFormat, dilations, dimRoundingMode }\n  });\n  if (bias) {\n    const oldResult = result;\n    result = add4({ inputs: { a: result, b: bias }, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(oldResult);\n  }\n  if (activation2) {\n    const oldResult = result;\n    result = applyActivation2(backend2, result, activation2, preluActivationWeights, leakyreluAlpha);\n    backend2.disposeIntermediateTensorInfo(oldResult);\n  }\n  return result;\n}\nvar fusedDepthwiseConv2DConfig = {\n  kernelName: FusedDepthwiseConv2D,\n  backendName: \"cpu\",\n  kernelFunc: fusedDepthwiseConv2D\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/GatherNd.js\nfunction gatherNd(args) {\n  const { inputs, backend: backend2 } = args;\n  const { params, indices } = inputs;\n  const paramsSize = util_exports.sizeFromShape(params.shape);\n  const indicesShape = indices.shape;\n  const sliceRank = indicesShape[indicesShape.length - 1];\n  const [resultShape, numSlices, sliceSize, strides] = backend_util_exports.prepareAndValidate(params, indices);\n  if (numSlices === 0) {\n    return backend2.makeTensorInfo(resultShape, params.dtype, []);\n  }\n  const indicesData = backend2.data.get(indices.dataId).values;\n  const paramsBuf = backend2.bufferSync(params);\n  const outBuf = gatherNdImpl(indicesData, paramsBuf, params.dtype, numSlices, sliceRank, sliceSize, strides, params.shape, paramsSize);\n  return backend2.makeTensorInfo(resultShape, params.dtype, outBuf.values);\n}\nvar gatherNdConfig = {\n  kernelName: GatherNd,\n  backendName: \"cpu\",\n  kernelFunc: gatherNd\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/GatherV2.js\nfunction gatherV2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, indices } = inputs;\n  const { axis, batchDims } = attrs;\n  assertNotComplex([x, indices], \"gatherV2\");\n  const parsedAxis = util_exports.parseAxisParam(axis, x.shape)[0];\n  const indicesVals = backend2.data.get(indices.dataId).values;\n  const axisDim = x.shape[parsedAxis];\n  for (let i2 = 0; i2 < indicesVals.length; ++i2) {\n    const index = indicesVals[i2];\n    util_exports.assert(index <= axisDim - 1 && index >= 0, () => `GatherV2: the index value ${index} is not in [0, ${axisDim - 1}]`);\n  }\n  let $batchDims = batchDims;\n  if (batchDims == null) {\n    $batchDims = 0;\n  }\n  const indicesSize = util_exports.sizeFromShape(indices.shape);\n  const shapeInfo = backend_util_exports.segment_util.collectGatherOpShapeInfo(x, indices, parsedAxis, $batchDims);\n  const flattenX = reshape3({\n    inputs: { x },\n    backend: backend2,\n    attrs: {\n      shape: [\n        shapeInfo.batchSize,\n        shapeInfo.outerSize,\n        shapeInfo.dimSize,\n        shapeInfo.sliceSize\n      ]\n    }\n  });\n  const flattenIndex = reshape3({\n    inputs: { x: indices },\n    backend: backend2,\n    attrs: { shape: [shapeInfo.batchSize, indicesSize / shapeInfo.batchSize] }\n  });\n  const flattenOutputShape = [\n    shapeInfo.batchSize,\n    shapeInfo.outerSize,\n    indicesSize / shapeInfo.batchSize,\n    shapeInfo.sliceSize\n  ];\n  const indicesBuf = backend2.bufferSync(flattenIndex);\n  const xBuf = backend2.bufferSync(flattenX);\n  const outBuf = gatherV2Impl(xBuf, indicesBuf, flattenOutputShape);\n  backend2.disposeIntermediateTensorInfo(flattenX);\n  backend2.disposeIntermediateTensorInfo(flattenIndex);\n  return backend2.makeTensorInfo(shapeInfo.outputShape, outBuf.dtype, outBuf.values);\n}\nvar gatherV2Config = {\n  kernelName: GatherV2,\n  backendName: \"cpu\",\n  kernelFunc: gatherV2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/IFFT.js\nfunction ifft2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const inputSize = util_exports.sizeFromShape(input2.shape);\n  const innerDimensionSize = input2.shape[input2.shape.length - 1];\n  const batch = inputSize / innerDimensionSize;\n  const input2D = reshape3({\n    inputs: { x: input2 },\n    backend: backend2,\n    attrs: { shape: [batch, innerDimensionSize] }\n  });\n  const result = fftBatch(input2D, true, backend2);\n  const resultReshaped = reshape3({ inputs: { x: result }, backend: backend2, attrs: { shape: input2.shape } });\n  backend2.disposeIntermediateTensorInfo(input2D);\n  backend2.disposeIntermediateTensorInfo(result);\n  return resultReshaped;\n}\nvar ifftConfig = {\n  kernelName: IFFT,\n  backendName: \"cpu\",\n  kernelFunc: ifft2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/IsFinite.js\nvar isFinite3 = unaryKernelFunc(IsFinite, (xi) => Number.isFinite(xi) ? 1 : 0, \"bool\");\nvar isFiniteConfig = {\n  kernelName: IsFinite,\n  backendName: \"cpu\",\n  kernelFunc: isFinite3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/IsInf.js\nvar isInf2 = unaryKernelFunc(IsInf, (xi) => Math.abs(xi) === Infinity ? 1 : 0, \"bool\");\nvar isInfConfig = {\n  kernelName: IsInf,\n  backendName: \"cpu\",\n  kernelFunc: isInf2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/IsNaN.js\nvar isNaN3 = unaryKernelFunc(IsNan, (xi) => Number.isNaN(xi) ? 1 : 0, \"bool\");\nvar isNaNConfig = {\n  kernelName: IsNan,\n  backendName: \"cpu\",\n  kernelFunc: isNaN3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LinSpace.js\nfunction linSpace(args) {\n  const { backend: backend2, attrs } = args;\n  const { start, stop, num } = attrs;\n  const outVals = linSpaceImpl(start, stop, num);\n  return backend2.makeTensorInfo([outVals.length], \"float32\", outVals);\n}\nvar linSpaceConfig = {\n  kernelName: LinSpace,\n  backendName: \"cpu\",\n  kernelFunc: linSpace\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Log1p.js\nvar log1p2 = unaryKernelFunc(Log1p, (xi) => Math.log1p(xi));\nvar log1pConfig = {\n  kernelName: Log1p,\n  backendName: \"cpu\",\n  kernelFunc: log1p2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LogicalAnd.js\nvar logicalAndImpl = createSimpleBinaryKernelImpl((a, b) => a && b);\nvar logicalAnd2 = binaryKernelFunc(LogicalAnd, logicalAndImpl, null, \"bool\");\nvar logicalAndConfig = {\n  kernelName: LogicalAnd,\n  backendName: \"cpu\",\n  kernelFunc: logicalAnd2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LogicalNot.js\nvar logicalNot2 = unaryKernelFunc(LogicalNot, (xi) => xi ? 0 : 1, \"bool\");\nvar logicalNotConfig = {\n  kernelName: LogicalNot,\n  backendName: \"cpu\",\n  kernelFunc: logicalNot2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LogicalOr.js\nvar logicalOrImpl = createSimpleBinaryKernelImpl((a, b) => a || b);\nvar logicalOr2 = binaryKernelFunc(LogicalOr, logicalOrImpl, null, \"bool\");\nvar logicalOrConfig = {\n  kernelName: LogicalOr,\n  backendName: \"cpu\",\n  kernelFunc: logicalOr2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LRN.js\nfunction lRN(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { depthRadius, bias, alpha, beta } = attrs;\n  assertNotComplex(x, \"LRN\");\n  const channels = x.shape[3];\n  const maxD = channels - 1;\n  const xValues = backend2.data.get(x.dataId).values;\n  const size = util_exports.sizeFromShape(x.shape);\n  const result = new Float32Array(size);\n  function sumAcrossChannels(offset) {\n    const currentChannel = offset % channels;\n    let beginSumOffset = offset - currentChannel + Math.max(0, currentChannel - depthRadius);\n    const endSumOffset = offset - currentChannel + Math.min(currentChannel + depthRadius, maxD);\n    let sum7 = 0;\n    for (; beginSumOffset <= endSumOffset; beginSumOffset++) {\n      const z = xValues[beginSumOffset];\n      sum7 += z * z;\n    }\n    return sum7;\n  }\n  for (let offset = 0; offset < size; offset++) {\n    const sum7 = sumAcrossChannels(offset);\n    const val = xValues[offset] * Math.pow(bias + alpha * sum7, -beta);\n    result[offset] = val;\n  }\n  return backend2.makeTensorInfo(x.shape, x.dtype, result);\n}\nvar LRNConfig = {\n  kernelName: LRN,\n  backendName: \"cpu\",\n  kernelFunc: lRN\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LRNGrad.js\nfunction lRNGrad(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, y, dy } = inputs;\n  const { depthRadius, bias, alpha, beta } = attrs;\n  assertNotComplex(dy, \"LRNGrad\");\n  const dySize = util_exports.sizeFromShape(dy.shape);\n  const channels = dy.shape[3];\n  const dyValues = backend2.data.get(dy.dataId).values;\n  const xValues = backend2.data.get(x.dataId).values;\n  const yValues = backend2.data.get(y.dataId).values;\n  const result = new Float32Array(dySize);\n  const size = dySize;\n  for (let offset = 0; offset < size; offset++) {\n    const currentChannel = offset % channels;\n    const depthBegin = offset - currentChannel + Math.max(0, currentChannel - depthRadius);\n    const depthEnd = offset - currentChannel + Math.min(channels, currentChannel + depthRadius + 1);\n    let norm2 = 0;\n    for (let k = depthBegin; k < depthEnd; k++) {\n      norm2 += Math.pow(xValues[k], 2);\n    }\n    norm2 = alpha * norm2 + bias;\n    for (let k = depthBegin; k < depthEnd; k++) {\n      let dyi = -2 * alpha * beta * xValues[k] * yValues[offset] / norm2;\n      if (offset === k) {\n        dyi += Math.pow(norm2, -beta);\n      }\n      dyi *= dyValues[offset];\n      result[k] += dyi;\n    }\n  }\n  return backend2.makeTensorInfo(dy.shape, x.dtype, result);\n}\nvar LRNGradConfig = {\n  kernelName: LRNGrad,\n  backendName: \"cpu\",\n  kernelFunc: lRNGrad\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Max.js\nfunction max3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { reductionIndices, keepDims } = attrs;\n  const cpuBackend = backend2;\n  let xShape = x.shape;\n  const xRank = xShape.length;\n  const origAxes = util_exports.parseAxisParam(reductionIndices, xShape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  let xVals = cpuBackend.data.get(x.dataId).values;\n  if (permutedAxes != null) {\n    const newShape = new Array(xRank);\n    for (let i2 = 0; i2 < newShape.length; i2++) {\n      newShape[i2] = xShape[permutedAxes[i2]];\n    }\n    xVals = transposeImpl(xVals, xShape, x.dtype, permutedAxes, newShape);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n    xShape = newShape;\n  }\n  assertNotComplex(x, \"max\");\n  backend_util_exports.assertAxesAreInnerMostDims(\"max\", axes, xRank);\n  const [maxOutShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(xShape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const result = maxImpl(xVals, reduceSize, maxOutShape, x.dtype);\n  const dataId = cpuBackend.write(result, maxOutShape, x.dtype);\n  let outShape = maxOutShape;\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(maxOutShape, origAxes);\n    outShape = newShape;\n  }\n  return { dataId, shape: outShape, dtype: x.dtype };\n}\nvar maxConfig = {\n  kernelName: Max,\n  backendName: \"cpu\",\n  kernelFunc: max3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPool.js\nfunction maxPool2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  assertNotComplex(x, \"maxPool\");\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = 1;\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in maxPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  let res;\n  if (convInfo.filterWidth === 1 && convInfo.filterHeight === 1 && util_exports.arraysEqual(convInfo.inShape, convInfo.outShape)) {\n    res = identity2({ inputs: { x }, backend: backend2 });\n  } else {\n    const xValues = backend2.data.get(x.dataId).values;\n    const strides2 = util_exports.computeStrides(x.shape);\n    const buffer2 = pool2(xValues, x.shape, x.dtype, strides2, convInfo, \"max\");\n    res = backend2.makeTensorInfo(convInfo.outShape, x.dtype, buffer2.values);\n  }\n  return res;\n}\nvar maxPoolConfig = {\n  kernelName: MaxPool,\n  backendName: \"cpu\",\n  kernelFunc: maxPool2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPool3D.js\nfunction maxPool3D(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { filterSize, strides, pad: pad3, dimRoundingMode, dataFormat } = attrs;\n  assertNotComplex(x, \"maxPool3d\");\n  const convInfo = backend_util_exports.computePool3DInfo(x.shape, filterSize, strides, 1, pad3, dimRoundingMode, dataFormat);\n  const xValues = backend2.data.get(x.dataId).values;\n  const outBuf = pool3d2(xValues, x.shape, x.dtype, util_exports.computeStrides(x.shape), convInfo, \"max\");\n  return backend2.makeTensorInfo(outBuf.shape, \"float32\", outBuf.values);\n}\nvar maxPool3DConfig = {\n  kernelName: MaxPool3D,\n  backendName: \"cpu\",\n  kernelFunc: maxPool3D\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPool3DGrad.js\nfunction maxPool3DGrad(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2 } = inputs;\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  assertNotComplex([dy, input2], \"maxPool3DGrad\");\n  const convInfo = backend_util_exports.computePool3DInfo(input2.shape, filterSize, strides, 1, pad3, dimRoundingMode);\n  const inputBuf = backend2.bufferSync(input2);\n  const maxPosBuf = maxPool3dPositions(inputBuf, convInfo);\n  const strideDepth = convInfo.strideDepth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const dilationDepth = convInfo.dilationDepth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterDepth = convInfo.effectiveFilterDepth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;\n  const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n  const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n  const dx = buffer(input2.shape, \"float32\");\n  const dyBuf = backend2.bufferSync(dy);\n  for (let batch = 0; batch < convInfo.batchSize; ++batch) {\n    for (let channel = 0; channel < convInfo.inChannels; ++channel) {\n      for (let dxDepth = 0; dxDepth < convInfo.inDepth; ++dxDepth) {\n        for (let dxRow = 0; dxRow < convInfo.inHeight; ++dxRow) {\n          for (let dxCol = 0; dxCol < convInfo.inWidth; ++dxCol) {\n            const dyDepthCorner = dxDepth - padFront;\n            const dyRowCorner = dxRow - padTop;\n            const dyColCorner = dxCol - padLeft;\n            let dotProd = 0;\n            for (let wDepth = 0; wDepth < effectiveFilterDepth; wDepth += dilationDepth) {\n              const dyDepth = (dyDepthCorner + wDepth) / strideDepth;\n              if (dyDepth < 0 || dyDepth >= convInfo.outDepth || Math.floor(dyDepth) !== dyDepth) {\n                continue;\n              }\n              for (let wRow = 0; wRow < effectiveFilterHeight; wRow += dilationHeight) {\n                const dyRow = (dyRowCorner + wRow) / strideHeight;\n                if (dyRow < 0 || dyRow >= convInfo.outHeight || Math.floor(dyRow) !== dyRow) {\n                  continue;\n                }\n                for (let wCol = 0; wCol < effectiveFilterWidth; wCol += dilationWidth) {\n                  const dyCol = (dyColCorner + wCol) / strideWidth;\n                  if (dyCol < 0 || dyCol >= convInfo.outWidth || Math.floor(dyCol) !== dyCol) {\n                    continue;\n                  }\n                  const maxPos = effectiveFilterDepth * effectiveFilterHeight * effectiveFilterWidth - 1 - maxPosBuf.get(batch, dyDepth, dyRow, dyCol, channel);\n                  const curPos = wDepth * effectiveFilterHeight * effectiveFilterWidth + wRow * effectiveFilterWidth + wCol;\n                  const mask = maxPos === curPos ? 1 : 0;\n                  if (mask === 0) {\n                    continue;\n                  }\n                  const pixel = dyBuf.get(batch, dyDepth, dyRow, dyCol, channel);\n                  dotProd += pixel * mask;\n                }\n              }\n            }\n            dx.set(dotProd, batch, dxDepth, dxRow, dxCol, channel);\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dx.shape, dx.dtype, dx.values);\n}\nvar maxPool3DGradConfig2 = {\n  kernelName: MaxPool3DGrad,\n  backendName: \"cpu\",\n  kernelFunc: maxPool3DGrad\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPoolGrad.js\nfunction maxPoolGrad2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2, output } = inputs;\n  const x = input2;\n  assertNotComplex([input2, output], \"maxPoolGrad\");\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, 1, pad3, dimRoundingMode);\n  const xValues = backend2.data.get(x.dataId).values;\n  const maxPosBuf = buffer(convInfo.outShape, x.dtype, maxPoolPositions(xValues, x.shape, x.dtype, convInfo).values);\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n  const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n  const dx = buffer(x.shape, \"float32\");\n  const dyData = backend2.data.get(dy.dataId).values;\n  const dyBuf = buffer(dy.shape, \"float32\", dyData);\n  for (let b = 0; b < convInfo.batchSize; ++b) {\n    for (let d = 0; d < convInfo.inChannels; ++d) {\n      for (let dxR = 0; dxR < convInfo.inHeight; ++dxR) {\n        for (let dxC = 0; dxC < convInfo.inWidth; ++dxC) {\n          const dyRCorner = dxR - padTop;\n          const dyCCorner = dxC - padLeft;\n          let dotProd = 0;\n          for (let wR = 0; wR < effectiveFilterHeight; wR += dilationHeight) {\n            const dyR = (dyRCorner + wR) / strideHeight;\n            if (dyR < 0 || dyR >= convInfo.outHeight || Math.floor(dyR) !== dyR) {\n              continue;\n            }\n            for (let wC = 0; wC < effectiveFilterWidth; wC += dilationWidth) {\n              const dyC = (dyCCorner + wC) / strideWidth;\n              if (dyC < 0 || dyC >= convInfo.outWidth || Math.floor(dyC) !== dyC) {\n                continue;\n              }\n              const maxPos = effectiveFilterHeight * effectiveFilterWidth - 1 - maxPosBuf.get(b, dyR, dyC, d);\n              const curPos = wR * effectiveFilterWidth + wC;\n              const mask = maxPos === curPos ? 1 : 0;\n              if (mask === 0) {\n                continue;\n              }\n              const pixel = dyBuf.get(b, dyR, dyC, d);\n              dotProd += pixel * mask;\n            }\n          }\n          dx.set(dotProd, b, dxR, dxC, d);\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dx.shape, dx.dtype, dx.values);\n}\nvar maxPoolGradConfig2 = {\n  kernelName: MaxPoolGrad,\n  backendName: \"cpu\",\n  kernelFunc: maxPoolGrad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPoolWithArgmax_impl.js\nfunction maxPoolWithArgmaxImpl(xValues, xShape, dtype, includeBatchInIndex, convInfo) {\n  const strides = util_exports.computeStrides(xShape);\n  const maxPools = pool2(xValues, xShape, dtype, strides, convInfo, \"max\");\n  const maxPositions = maxPoolPositions(xValues, xShape, dtype, convInfo, true, includeBatchInIndex);\n  return [maxPools.values, maxPositions.values];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPoolWithArgmax.js\nvar maxPoolWithArgmaxConfig = {\n  kernelName: MaxPoolWithArgmax,\n  backendName: \"cpu\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { x } = inputs;\n    const { filterSize, strides, pad: pad3, includeBatchInIndex } = attrs;\n    const cpuBackend = backend2;\n    assertNotComplex(x, \"MaxPoolWithArgmax\");\n    const values = cpuBackend.data.get(x.dataId).values;\n    const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, [1, 1], pad3);\n    const [pooled, indexes] = maxPoolWithArgmaxImpl(values, x.shape, x.dtype, includeBatchInIndex, convInfo);\n    const pooledDataId = cpuBackend.write(pooled, convInfo.outShape, x.dtype);\n    const indexesDataId = cpuBackend.write(indexes, convInfo.outShape, x.dtype);\n    return [\n      { dataId: pooledDataId, shape: convInfo.outShape, dtype: x.dtype },\n      { dataId: indexesDataId, shape: convInfo.outShape, dtype: \"int32\" }\n    ];\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Mean.js\nfunction mean2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  const axes = util_exports.parseAxisParam(axis, x.shape);\n  const shapes = backend_util_exports.computeOutAndReduceShapes(x.shape, axes);\n  const reduceShape = shapes[1];\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const toDispose = [];\n  const reduceSizeScalar = backend2.makeTensorInfo([], \"float32\", new Float32Array([reduceSize]));\n  toDispose.push(reduceSizeScalar);\n  const $x = cast3({ inputs: { x }, backend: backend2, attrs: { dtype: \"float32\" } });\n  toDispose.push($x);\n  const res = div2({ inputs: { a: $x, b: reduceSizeScalar }, backend: backend2 });\n  toDispose.push(res);\n  const result = sum3({ inputs: { x: res }, backend: backend2, attrs: { axis, keepDims } });\n  toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return result;\n}\nvar meanConfig = {\n  kernelName: Mean,\n  backendName: \"cpu\",\n  kernelFunc: mean2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Min.js\nfunction min3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  assertNotComplex(x, \"min\");\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  if (permutedAxes != null) {\n    $x = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"min\", axes, $x.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes($x.shape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const vals = util_exports.makeZerosTypedArray(util_exports.sizeFromShape(outShape), $x.dtype);\n  const aVals = backend2.data.get($x.dataId).values;\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let min7 = aVals[offset];\n    for (let j = 0; j < reduceSize; ++j) {\n      const value = aVals[offset + j];\n      if (Number.isNaN(value) || value < min7) {\n        min7 = value;\n      }\n    }\n    vals[i2] = min7;\n  }\n  if (permutedAxes != null) {\n    backend2.disposeIntermediateTensorInfo($x);\n  }\n  const result = backend2.makeTensorInfo(outShape, $x.dtype, vals);\n  if (keepDims) {\n    const expandedShape = backend_util_exports.expandShapeToKeepDim(outShape, origAxes);\n    const reshapedResult = reshape3({ inputs: { x: result }, backend: backend2, attrs: { shape: expandedShape } });\n    backend2.disposeIntermediateTensorInfo(result);\n    return reshapedResult;\n  }\n  return result;\n}\nvar minConfig = {\n  kernelName: Min,\n  backendName: \"cpu\",\n  kernelFunc: min3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MirrorPad.js\nfunction mirrorPad2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { paddings, mode } = attrs;\n  assertNotComplex(x, \"mirrorPad\");\n  const outShape = paddings.map((p2, i2) => p2[0] + x.shape[i2] + p2[1]);\n  const start = paddings.map((p2) => p2[0]);\n  const end = paddings.map((p2, i2) => p2[0] + x.shape[i2]);\n  const offset = mode === \"reflect\" ? 0 : 1;\n  const xVals = backend2.data.get(x.dataId).values;\n  const xRank = x.shape.length;\n  const xStrides = util_exports.computeStrides(x.shape);\n  const resultSize = util_exports.sizeFromShape(outShape);\n  const resultRank = outShape.length;\n  const resultStrides = util_exports.computeStrides(outShape);\n  const resVals = util_exports.getTypedArrayFromDType(x.dtype, resultSize);\n  for (let i2 = 0; i2 < resultSize; i2++) {\n    let coords3 = util_exports.indexToLoc(i2, resultRank, resultStrides);\n    for (let i3 = 0; i3 < resultRank; i3++) {\n      if (coords3[i3] < start[i3]) {\n        coords3[i3] = start[i3] * 2 - coords3[i3] - offset;\n      } else if (coords3[i3] >= end[i3]) {\n        coords3[i3] = (end[i3] - 1) * 2 - coords3[i3] + offset;\n      }\n    }\n    coords3 = coords3.map((c, i3) => c - start[i3]);\n    const inIndex = util_exports.locToIndex(coords3, xRank, xStrides);\n    resVals[i2] = xVals[inIndex];\n  }\n  const outId = backend2.write(resVals, outShape, x.dtype);\n  return { dataId: outId, shape: outShape, dtype: x.dtype };\n}\nvar mirrorPadConfig = {\n  kernelName: MirrorPad,\n  backendName: \"cpu\",\n  kernelFunc: mirrorPad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Mod.js\nvar modImpl = createSimpleBinaryKernelImpl((aValue, bValue) => {\n  const rem = aValue % bValue;\n  if (aValue < 0 && bValue < 0 || aValue >= 0 && bValue >= 0) {\n    return rem;\n  } else {\n    return (rem + bValue) % bValue;\n  }\n});\nvar mod2 = binaryKernelFunc(Mod, modImpl);\nvar modConfig = {\n  kernelName: Mod,\n  backendName: \"cpu\",\n  kernelFunc: mod2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Multinomial.js\nvar seedrandom4 = __toESM(require_seedrandom2());\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Softmax.js\nfunction softmax3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { logits } = inputs;\n  const { dim } = attrs;\n  const logitsRank = logits.shape.length;\n  let $dim = dim;\n  if ($dim === -1) {\n    $dim = logitsRank - 1;\n  }\n  if ($dim !== logitsRank - 1) {\n    throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${logitsRank} and dim was ${$dim}`);\n  }\n  const axes = util_exports.parseAxisParam([$dim], logits.shape);\n  const maxLogit = max3({\n    inputs: { x: logits },\n    backend: backend2,\n    attrs: { reductionIndices: axes, keepDims: false }\n  });\n  const expandedShape = backend_util_exports.expandShapeToKeepDim(maxLogit.shape, axes);\n  const maxLogitReshaped = reshape3({ inputs: { x: maxLogit }, backend: backend2, attrs: { shape: expandedShape } });\n  const a = sub2({ inputs: { a: logits, b: maxLogitReshaped }, backend: backend2 });\n  const b = exp2({ inputs: { x: a }, backend: backend2 });\n  const sumExp = sum3({ inputs: { x: b }, backend: backend2, attrs: { axis: axes, keepDims: false } });\n  const sumReshaped = reshape3({ inputs: { x: sumExp }, backend: backend2, attrs: { shape: expandedShape } });\n  const result = div2({ inputs: { a: b, b: sumReshaped }, backend: backend2 });\n  backend2.disposeIntermediateTensorInfo(maxLogit);\n  backend2.disposeIntermediateTensorInfo(maxLogitReshaped);\n  backend2.disposeIntermediateTensorInfo(a);\n  backend2.disposeIntermediateTensorInfo(b);\n  backend2.disposeIntermediateTensorInfo(sumExp);\n  backend2.disposeIntermediateTensorInfo(sumReshaped);\n  return result;\n}\nvar softmaxConfig = {\n  kernelName: Softmax,\n  backendName: \"cpu\",\n  kernelFunc: softmax3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Multinomial.js\nfunction multinomial2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { logits } = inputs;\n  const { numSamples, seed, normalized } = attrs;\n  assertNotComplex(logits, \"multinomial\");\n  const probabilities = normalized ? logits : softmax3({ inputs: { logits }, backend: backend2, attrs: { dim: -1 } });\n  const batchSize = probabilities.shape[0];\n  const numEvents = probabilities.shape[1];\n  const probVals = backend2.data.get(probabilities.dataId).values;\n  const resShape = [batchSize, numSamples];\n  const resVals = util_exports.makeZerosTypedArray(util_exports.sizeFromShape(resShape), \"int32\");\n  for (let b = 0; b < batchSize; ++b) {\n    const offset = b * numEvents;\n    const cdf = new Float32Array(numEvents - 1);\n    cdf[0] = probVals[offset];\n    for (let event = 1; event < cdf.length; ++event) {\n      cdf[event] = cdf[event - 1] + probVals[offset + event];\n    }\n    const random = seedrandom4.alea(seed.toString());\n    const outOffset = b * numSamples;\n    for (let sampleId = 0; sampleId < numSamples; ++sampleId) {\n      const r2 = random();\n      resVals[outOffset + sampleId] = cdf.length;\n      for (let event = 0; event < cdf.length; event++) {\n        if (r2 < cdf[event]) {\n          resVals[outOffset + sampleId] = event;\n          break;\n        }\n      }\n    }\n  }\n  if (!normalized) {\n    backend2.disposeIntermediateTensorInfo(probabilities);\n  }\n  return backend2.makeTensorInfo(resShape, \"int32\", resVals);\n}\nvar multinomialConfig = {\n  kernelName: Multinomial,\n  backendName: \"cpu\",\n  kernelFunc: multinomial2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/NonMaxSuppressionV3.js\nvar nonMaxSuppressionV3Impl2 = kernel_impls_exports.nonMaxSuppressionV3Impl;\nfunction nonMaxSuppressionV3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold } = attrs;\n  assertNotComplex(boxes, \"NonMaxSuppression\");\n  const boxesVals = backend2.data.get(boxes.dataId).values;\n  const scoresVals = backend2.data.get(scores.dataId).values;\n  const { selectedIndices } = nonMaxSuppressionV3Impl2(boxesVals, scoresVals, maxOutputSize, iouThreshold, scoreThreshold);\n  return backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices));\n}\nvar nonMaxSuppressionV3Config = {\n  kernelName: NonMaxSuppressionV3,\n  backendName: \"cpu\",\n  kernelFunc: nonMaxSuppressionV3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/NonMaxSuppressionV4.js\nvar nonMaxSuppressionV4Impl2 = kernel_impls_exports.nonMaxSuppressionV4Impl;\nfunction nonMaxSuppressionV4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize } = attrs;\n  assertNotComplex(boxes, \"NonMaxSuppressionPadded\");\n  const boxesVals = backend2.data.get(boxes.dataId).values;\n  const scoresVals = backend2.data.get(scores.dataId).values;\n  const { selectedIndices, validOutputs } = nonMaxSuppressionV4Impl2(boxesVals, scoresVals, maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize);\n  return [\n    backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices)),\n    backend2.makeTensorInfo([], \"int32\", new Int32Array([validOutputs]))\n  ];\n}\nvar nonMaxSuppressionV4Config = {\n  kernelName: NonMaxSuppressionV4,\n  backendName: \"cpu\",\n  kernelFunc: nonMaxSuppressionV4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/NonMaxSuppressionV5.js\nvar nonMaxSuppressionV5Impl2 = kernel_impls_exports.nonMaxSuppressionV5Impl;\nfunction nonMaxSuppressionV5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma } = attrs;\n  assertNotComplex(boxes, \"NonMaxSuppressionWithScore\");\n  const boxesVals = backend2.data.get(boxes.dataId).values;\n  const scoresVals = backend2.data.get(scores.dataId).values;\n  const maxOutputSizeVal = maxOutputSize;\n  const iouThresholdVal = iouThreshold;\n  const scoreThresholdVal = scoreThreshold;\n  const softNmsSigmaVal = softNmsSigma;\n  const { selectedIndices, selectedScores } = nonMaxSuppressionV5Impl2(boxesVals, scoresVals, maxOutputSizeVal, iouThresholdVal, scoreThresholdVal, softNmsSigmaVal);\n  return [\n    backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices)),\n    backend2.makeTensorInfo([selectedScores.length], \"float32\", new Float32Array(selectedScores))\n  ];\n}\nvar nonMaxSuppressionV5Config = {\n  kernelName: NonMaxSuppressionV5,\n  backendName: \"cpu\",\n  kernelFunc: nonMaxSuppressionV5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/OneHot.js\nfunction oneHot2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { indices } = inputs;\n  const { depth, onValue, offValue } = attrs;\n  assertNotComplex(indices, \"oneHot\");\n  const indicesSize = util_exports.sizeFromShape(indices.shape);\n  const res = new Float32Array(indicesSize * depth);\n  res.fill(offValue);\n  const indicesVal = backend2.data.get(indices.dataId).values;\n  for (let event = 0; event < indicesSize; ++event) {\n    if (indicesVal[event] >= 0 && indicesVal[event] < depth) {\n      res[event * depth + indicesVal[event]] = onValue;\n    }\n  }\n  return backend2.makeTensorInfo([...indices.shape, depth], \"int32\", res);\n}\nvar oneHotConfig = {\n  kernelName: OneHot,\n  backendName: \"cpu\",\n  kernelFunc: oneHot2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ZerosLike.js\nfunction zerosLike2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (x.dtype === \"string\") {\n    throw new Error(\"zerosLike is not supported for string tensors\");\n  } else if (x.dtype === \"complex64\") {\n    const realPart = real2({ inputs: { input: x }, backend: backend2 });\n    const r2 = zerosLike2({ inputs: { x: realPart }, backend: backend2 });\n    const imagPart = imag2({ inputs: { input: x }, backend: backend2 });\n    const i2 = zerosLike2({ inputs: { x: imagPart }, backend: backend2 });\n    const result = complex2({ inputs: { real: r2, imag: i2 }, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(realPart);\n    backend2.disposeIntermediateTensorInfo(r2);\n    backend2.disposeIntermediateTensorInfo(imagPart);\n    backend2.disposeIntermediateTensorInfo(i2);\n    return result;\n  } else {\n    return fill2({ backend: backend2, attrs: { shape: x.shape, value: 0, dtype: x.dtype } });\n  }\n}\nvar zerosLikeConfig = {\n  kernelName: ZerosLike,\n  backendName: \"cpu\",\n  kernelFunc: zerosLike2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/OnesLike.js\nfunction onesLike2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (x.dtype === \"string\") {\n    throw new Error(\"onesLike is not supported for string tensors\");\n  } else if (x.dtype === \"complex64\") {\n    const realPart = real2({ inputs: { input: x }, backend: backend2 });\n    const r2 = onesLike2({ inputs: { x: realPart }, backend: backend2 });\n    const imagPart = imag2({ inputs: { input: x }, backend: backend2 });\n    const i2 = zerosLike2({ inputs: { x: imagPart }, backend: backend2 });\n    const result = complex2({ inputs: { real: r2, imag: i2 }, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(realPart);\n    backend2.disposeIntermediateTensorInfo(r2);\n    backend2.disposeIntermediateTensorInfo(imagPart);\n    backend2.disposeIntermediateTensorInfo(i2);\n    return result;\n  } else {\n    return fill2({ backend: backend2, attrs: { shape: x.shape, value: 1, dtype: x.dtype } });\n  }\n}\nvar onesLikeConfig = {\n  kernelName: OnesLike,\n  backendName: \"cpu\",\n  kernelFunc: onesLike2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Pack.js\nfunction pack(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { axis } = attrs;\n  if (inputs.length === 1) {\n    return expandDims3({ inputs: { input: inputs[0] }, backend: backend2, attrs: { dim: axis } });\n  }\n  const shape = inputs[0].shape;\n  const dtype = inputs[0].dtype;\n  inputs.forEach((t2) => {\n    util_exports.assertShapesMatch(shape, t2.shape, \"All tensors passed to stack must have matching shapes\");\n    util_exports.assert(dtype === t2.dtype, () => \"All tensors passed to stack must have matching dtypes\");\n  });\n  const intermediateTensorInfos = [];\n  const expandedTensors = inputs.map((t2) => {\n    const expandedT = expandDims3({ inputs: { input: t2 }, backend: backend2, attrs: { dim: axis } });\n    intermediateTensorInfos.push(expandedT);\n    return expandedT;\n  });\n  const result = concat2({ inputs: expandedTensors, backend: backend2, attrs: { axis } });\n  intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return result;\n}\nvar packConfig = {\n  kernelName: Pack,\n  backendName: \"cpu\",\n  kernelFunc: pack\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/PadV2.js\nfunction padV2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { paddings, constantValue } = attrs;\n  assertNotComplex(x, \"pad\");\n  const outShape = paddings.map((p2, i2) => p2[0] + x.shape[i2] + p2[1]);\n  const start = paddings.map((p2) => p2[0]);\n  const xVals = backend2.data.get(x.dataId).values;\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const xRank = x.shape.length;\n  const xStrides = util_exports.computeStrides(x.shape);\n  const resultSize = util_exports.sizeFromShape(outShape);\n  const resultRank = outShape.length;\n  const resultStrides = util_exports.computeStrides(outShape);\n  const resVals = util_exports.getTypedArrayFromDType(x.dtype, resultSize);\n  if (constantValue !== 0) {\n    resVals.fill(constantValue);\n  }\n  for (let i2 = 0; i2 < xSize; i2++) {\n    const coords3 = util_exports.indexToLoc(i2, xRank, xStrides);\n    const outCoords = coords3.map((c, i3) => c + start[i3]);\n    const outIndex = util_exports.locToIndex(outCoords, resultRank, resultStrides);\n    resVals[outIndex] = xVals[i2];\n  }\n  const outId = backend2.write(resVals, outShape, x.dtype);\n  return { dataId: outId, shape: outShape, dtype: x.dtype };\n}\nvar padV2Config = {\n  kernelName: PadV2,\n  backendName: \"cpu\",\n  kernelFunc: padV2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Pow.js\nvar powImpl = createSimpleBinaryKernelImpl((a, b) => Math.pow(a, b));\nvar pow2 = binaryKernelFunc(Pow, powImpl);\nvar powConfig = {\n  kernelName: Pow,\n  backendName: \"cpu\",\n  kernelFunc: pow2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Range.js\nfunction range3(args) {\n  const { backend: backend2, attrs } = args;\n  const { start, stop, dtype, step: step5 } = attrs;\n  const values = rangeImpl(start, stop, step5, dtype);\n  return backend2.makeTensorInfo([values.length], dtype, values);\n}\nvar rangeConfig = {\n  kernelName: Range,\n  backendName: \"cpu\",\n  kernelFunc: range3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Reciprocal.js\nvar reciprocal2 = unaryKernelFunc(Reciprocal, (xi) => 1 / xi);\nvar reciprocalConfig = {\n  kernelName: Reciprocal,\n  backendName: \"cpu\",\n  kernelFunc: reciprocal2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ResizeBilinear.js\nfunction resizeBilinear2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, halfPixelCenters, size } = attrs;\n  assertNotComplex(images, \"resizeBilinear\");\n  const imagesStrides = util_exports.computeStrides(images.shape);\n  const [newHeight, newWidth] = size;\n  const [batch, oldHeight, oldWidth, numChannels] = images.shape;\n  const xValues = backend2.data.get(images.dataId).values;\n  const result = new Float32Array(util_exports.sizeFromShape([batch, newHeight, newWidth, numChannels]));\n  const effectiveInputSize = [\n    alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,\n    alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth\n  ];\n  const effectiveOutputSize = [\n    alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,\n    alignCorners && newWidth > 1 ? newWidth - 1 : newWidth\n  ];\n  let outputIdx = 0;\n  const effectiveRowSizeRatio = effectiveInputSize[0] / effectiveOutputSize[0];\n  const effectiveColSizeRatio = effectiveInputSize[1] / effectiveOutputSize[1];\n  for (let b = 0; b < batch; b++) {\n    for (let r2 = 0; r2 < newHeight; r2++) {\n      let sourceFracRow;\n      if (halfPixelCenters) {\n        sourceFracRow = effectiveRowSizeRatio * (r2 + 0.5) - 0.5;\n      } else {\n        sourceFracRow = effectiveRowSizeRatio * r2;\n      }\n      const sourceRowFloor = Math.max(0, Math.floor(sourceFracRow));\n      const rowFrac = sourceFracRow - sourceRowFloor;\n      const sourceRowCeil = Math.min(oldHeight - 1, Math.ceil(sourceFracRow));\n      const topRowOffset = b * imagesStrides[0] + sourceRowFloor * imagesStrides[1];\n      const botRowOffset = b * imagesStrides[0] + sourceRowCeil * imagesStrides[1];\n      for (let c = 0; c < newWidth; c++) {\n        let sourceFracCol;\n        if (halfPixelCenters) {\n          sourceFracCol = effectiveColSizeRatio * (c + 0.5) - 0.5;\n        } else {\n          sourceFracCol = effectiveColSizeRatio * c;\n        }\n        const sourceColFloor = Math.max(0, Math.floor(sourceFracCol));\n        const colFrac = sourceFracCol - sourceColFloor;\n        const sourceColCeil = Math.min(oldWidth - 1, Math.ceil(sourceFracCol));\n        const topLeftOffest = topRowOffset + sourceColFloor * imagesStrides[2];\n        const botLeftOffset = botRowOffset + sourceColFloor * imagesStrides[2];\n        const topRightOffset = topRowOffset + sourceColCeil * imagesStrides[2];\n        const botRightOffest = botRowOffset + sourceColCeil * imagesStrides[2];\n        for (let d = 0; d < numChannels; d++) {\n          const topLeft = xValues[topLeftOffest + d];\n          const bottomLeft = xValues[botLeftOffset + d];\n          const topRight = xValues[topRightOffset + d];\n          const bottomRight = xValues[botRightOffest + d];\n          const top = topLeft + (topRight - topLeft) * colFrac;\n          const bottom = bottomLeft + (bottomRight - bottomLeft) * colFrac;\n          const newValue = top + (bottom - top) * rowFrac;\n          result[outputIdx++] = newValue;\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo([batch, newHeight, newWidth, numChannels], \"float32\", result);\n}\nvar resizeBilinearConfig = {\n  kernelName: ResizeBilinear,\n  backendName: \"cpu\",\n  kernelFunc: resizeBilinear2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ResizeBilinearGrad.js\nfunction resizeBilinearGrad(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images, dy } = inputs;\n  const { alignCorners } = attrs;\n  assertNotComplex([dy, images], \"resizeBilinearGrad\");\n  const imagesStrides = util_exports.computeStrides(images.shape);\n  const [batch, xHeight, xWidth, depth] = images.shape;\n  const [, yHeight, yWidth] = dy.shape;\n  const output = new Float32Array(batch * xHeight * xWidth * depth);\n  const effectiveXSize = [\n    alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,\n    alignCorners && yWidth > 1 ? xWidth - 1 : xWidth\n  ];\n  const effectiveYSize = [\n    alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,\n    alignCorners && yWidth > 1 ? yWidth - 1 : yWidth\n  ];\n  const heightScale = effectiveXSize[0] / effectiveYSize[0];\n  const widthScale = effectiveXSize[1] / effectiveYSize[1];\n  const dyValues = backend2.data.get(dy.dataId).values;\n  let offset = 0;\n  for (let b = 0; b < batch; b++) {\n    const bOffset = b * imagesStrides[0];\n    for (let r2 = 0; r2 < yHeight; r2++) {\n      const dxR = r2 * heightScale;\n      const topDxRIndex = Math.floor(dxR);\n      const bottomDxRIndex = Math.min(Math.ceil(dxR), xHeight - 1);\n      const topDxROffset = bOffset + topDxRIndex * imagesStrides[1];\n      const bottomDxROffset = bOffset + bottomDxRIndex * imagesStrides[1];\n      const dxRLerp = dxR - topDxRIndex;\n      const inverseDxRLerp = 1 - dxRLerp;\n      for (let c = 0; c < yWidth; c++) {\n        const dxC = c * widthScale;\n        const leftDxCIndex = Math.floor(dxC);\n        const rightDxCIndex = Math.min(Math.ceil(dxC), xWidth - 1);\n        const dxCLerp = dxC - leftDxCIndex;\n        const inverseDxCLerp = 1 - dxCLerp;\n        const topLeftRCOffset = topDxROffset + leftDxCIndex * imagesStrides[2];\n        const topRightRCOffset = topDxROffset + rightDxCIndex * imagesStrides[2];\n        const bottomLeftRCOffset = bottomDxROffset + leftDxCIndex * imagesStrides[2];\n        const bottomRightRCOffset = bottomDxROffset + rightDxCIndex * imagesStrides[2];\n        const inverseDxRLerpTimesInverseDxCLerp = inverseDxRLerp * inverseDxCLerp;\n        const inverseDxRLerpTimesDxCLerp = inverseDxRLerp * dxCLerp;\n        const dxRLerpTimesInverseDxCLerp = dxRLerp * inverseDxCLerp;\n        const dxRLerpTimesDxCLerp = dxRLerp * dxCLerp;\n        for (let d = 0; d < depth; d++) {\n          const dyVal = dyValues[offset++];\n          output[topLeftRCOffset + d] += dyVal * inverseDxRLerpTimesInverseDxCLerp;\n          output[topRightRCOffset + d] += dyVal * inverseDxRLerpTimesDxCLerp;\n          output[bottomLeftRCOffset + d] += dyVal * dxRLerpTimesInverseDxCLerp;\n          output[bottomRightRCOffset + d] += dyVal * dxRLerpTimesDxCLerp;\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo([batch, xWidth, xHeight, depth], \"float32\", output);\n}\nvar resizeBilinearGradConfig2 = {\n  kernelName: ResizeBilinearGrad,\n  backendName: \"cpu\",\n  kernelFunc: resizeBilinearGrad\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ResizeNearestNeighbor.js\nfunction resizeNearestNeighbor2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, halfPixelCenters, size } = attrs;\n  assertNotComplex(images, \"resizeNearestNeighbor\");\n  const imagesStrides = util_exports.computeStrides(images.shape);\n  const [newHeight, newWidth] = size;\n  const [batch, oldHeight, oldWidth, numChannels] = images.shape;\n  const xValues = backend2.data.get(images.dataId).values;\n  const output = new Float32Array(batch * newHeight * newWidth * numChannels);\n  const effectiveInputSize = [\n    alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,\n    alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth\n  ];\n  const effectiveOutputSize = [\n    alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,\n    alignCorners && newWidth > 1 ? newWidth - 1 : newWidth\n  ];\n  const effectiveRowSizeRatio = effectiveInputSize[0] / effectiveOutputSize[0];\n  const effectiveColSizeRatio = effectiveInputSize[1] / effectiveOutputSize[1];\n  let outputOffset = 0;\n  for (let b = 0; b < batch; b++) {\n    const batchOffset = b * imagesStrides[0];\n    for (let r2 = 0; r2 < newHeight; r2++) {\n      const sourceFracRow = halfPixelCenters ? effectiveRowSizeRatio * (r2 + 0.5) : effectiveRowSizeRatio * r2;\n      let sourceNearestRow = Math.min(oldHeight - 1, alignCorners ? Math.round(sourceFracRow) : Math.floor(sourceFracRow));\n      if (halfPixelCenters) {\n        sourceNearestRow = Math.max(0, sourceNearestRow);\n      }\n      const rowOffset = batchOffset + sourceNearestRow * imagesStrides[1];\n      for (let c = 0; c < newWidth; c++) {\n        const sourceFracCol = halfPixelCenters ? effectiveColSizeRatio * (c + 0.5) : effectiveColSizeRatio * c;\n        let sourceNearestCol = Math.min(oldWidth - 1, alignCorners ? Math.round(sourceFracCol) : Math.floor(sourceFracCol));\n        if (halfPixelCenters) {\n          sourceNearestCol = Math.max(0, sourceNearestCol);\n        }\n        const colOffset = rowOffset + sourceNearestCol * imagesStrides[2];\n        for (let d = 0; d < numChannels; d++) {\n          const newVal = xValues[colOffset + d];\n          output[outputOffset++] = newVal;\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo([batch, newHeight, newWidth, numChannels], images.dtype, output);\n}\nvar resizeNearestNeighborConfig = {\n  kernelName: ResizeNearestNeighbor,\n  backendName: \"cpu\",\n  kernelFunc: resizeNearestNeighbor2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ResizeNearestNeighborGrad.js\nfunction resizeNearestNeighborGrad(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images, dy } = inputs;\n  const { alignCorners } = attrs;\n  assertNotComplex([dy, images], \"resizeNearestNeighborGrad\");\n  const imagesStrides = util_exports.computeStrides(images.shape);\n  const dyStrides = util_exports.computeStrides(dy.shape);\n  const [batch, xHeight, xWidth, depth] = images.shape;\n  const [, yHeight, yWidth] = dy.shape;\n  const output = new Float32Array(batch * xHeight * xWidth * depth);\n  const dyValues = backend2.data.get(dy.dataId).values;\n  const effectiveXSize = [\n    alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,\n    alignCorners && yWidth > 1 ? xWidth - 1 : xWidth\n  ];\n  const effectiveYSize = [\n    alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,\n    alignCorners && yWidth > 1 ? yWidth - 1 : yWidth\n  ];\n  const heightScale = effectiveXSize[0] / effectiveYSize[0];\n  const widthScale = effectiveXSize[1] / effectiveYSize[1];\n  const invHeightScale = 1 / heightScale;\n  const invWidthScale = 1 / widthScale;\n  const winHeight = Math.ceil(invHeightScale) * 2 + 2;\n  const winWidth = Math.ceil(invWidthScale) * 2 + 2;\n  for (let b = 0; b < batch; b++) {\n    const batchOffset = b * imagesStrides[0];\n    for (let r2 = 0; r2 < xHeight; r2++) {\n      const rowOffset = batchOffset + r2 * imagesStrides[1];\n      const startRLerp = Math.floor(r2 * invHeightScale);\n      const startDyR = Math.floor(startRLerp - winHeight / 2);\n      for (let c = 0; c < xWidth; c++) {\n        const colOffset = rowOffset + c * imagesStrides[2];\n        const startCLerp = Math.floor(c * invWidthScale);\n        const startDyC = Math.floor(startCLerp - winWidth / 2);\n        for (let d = 0; d < depth; d++) {\n          let accum = 0;\n          for (let dyRIndex = 0; dyRIndex < winHeight; dyRIndex++) {\n            const dyR = dyRIndex + startDyR;\n            if (dyR < 0 || dyR >= yHeight) {\n              continue;\n            }\n            const dyROffset = batchOffset + dyR * dyStrides[1];\n            const sourceFracRow = dyR * heightScale;\n            const sourceNearestRow = Math.min(xHeight - 1, alignCorners ? Math.round(sourceFracRow) : Math.floor(sourceFracRow));\n            if (r2 !== sourceNearestRow) {\n              continue;\n            }\n            for (let dyCIndex = 0; dyCIndex < winWidth; dyCIndex++) {\n              const dyC = dyCIndex + startDyC;\n              if (dyC < 0 || dyC >= yWidth) {\n                continue;\n              }\n              const dyCOffset = dyROffset + dyC * dyStrides[2];\n              const sourceFracCol = dyC * widthScale;\n              const sourceNearestCol = Math.min(xWidth - 1, alignCorners ? Math.round(sourceFracCol) : Math.floor(sourceFracCol));\n              if (c === sourceNearestCol) {\n                accum += dyValues[dyCOffset + d];\n              }\n            }\n          }\n          output[colOffset + d] = accum;\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(images.shape, images.dtype, output);\n}\nvar resizeNearestNeighborGradConfig2 = {\n  kernelName: ResizeNearestNeighborGrad,\n  backendName: \"cpu\",\n  kernelFunc: resizeNearestNeighborGrad\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Reverse.js\nfunction reverse2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { dims } = attrs;\n  assertNotComplex(x, \"reverse\");\n  const xRank = x.shape.length;\n  const $dims = util_exports.parseAxisParam(dims, x.shape);\n  if (xRank === 0) {\n    return identity2({ inputs: { x }, backend: backend2 });\n  }\n  const outBuf = new TensorBuffer(x.shape, x.dtype);\n  const xBuf = backend2.bufferSync(x);\n  for (let i2 = 0; i2 < outBuf.size; i2++) {\n    const outLoc = outBuf.indexToLoc(i2);\n    const inLoc = outLoc.slice();\n    $dims.forEach((d) => inLoc[d] = x.shape[d] - 1 - inLoc[d]);\n    outBuf.set(xBuf.get(...inLoc), ...outLoc);\n  }\n  return backend2.makeTensorInfo(outBuf.shape, outBuf.dtype, outBuf.values);\n}\nvar reverseConfig = {\n  kernelName: Reverse,\n  backendName: \"cpu\",\n  kernelFunc: reverse2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/RotateWithOffset.js\nvar rotateWithOffsetConfig = {\n  kernelName: RotateWithOffset,\n  backendName: \"cpu\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { image: image2 } = inputs;\n    const { radians, fillValue, center } = attrs;\n    const cpuBackend = backend2;\n    const output = util_exports.getTypedArrayFromDType(image2.dtype, util_exports.sizeFromShape(image2.shape));\n    const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n    const [centerX, centerY] = backend_util_exports.getImageCenter(center, imageHeight, imageWidth);\n    const fullOpacityValue = 255;\n    const sinFactor = Math.sin(radians);\n    const cosFactor = Math.cos(radians);\n    const imageVals = cpuBackend.data.get(image2.dataId).values;\n    for (let batchIdx = 0; batchIdx < batch; batchIdx++) {\n      const batchOffset = batchIdx * imageWidth * imageHeight * numChannels;\n      for (let row = 0; row < imageHeight; row++) {\n        const rowOffset = row * (imageWidth * numChannels);\n        for (let col = 0; col < imageWidth; col++) {\n          const colOffset = col * numChannels;\n          for (let channel = 0; channel < numChannels; channel++) {\n            const coords3 = [batch, row, col, channel];\n            const x = coords3[2];\n            const y = coords3[1];\n            let coordX = (x - centerX) * cosFactor - (y - centerY) * sinFactor;\n            let coordY = (x - centerX) * sinFactor + (y - centerY) * cosFactor;\n            coordX = Math.round(coordX + centerX);\n            coordY = Math.round(coordY + centerY);\n            let outputValue = fillValue;\n            if (typeof fillValue !== \"number\") {\n              if (channel === 3) {\n                outputValue = fullOpacityValue;\n              } else {\n                outputValue = fillValue[channel];\n              }\n            }\n            if (coordX >= 0 && coordX < imageWidth && coordY >= 0 && coordY < imageHeight) {\n              const rotatedRowOffset = coordY * (imageWidth * numChannels);\n              const rotatedColOffset = coordX * numChannels;\n              const imageIdx = batchOffset + rotatedRowOffset + rotatedColOffset + channel;\n              outputValue = imageVals[imageIdx];\n            }\n            const outIdx = batchOffset + rowOffset + colOffset + channel;\n            output[outIdx] = outputValue;\n          }\n        }\n      }\n    }\n    const dataId = cpuBackend.write(output, image2.shape, image2.dtype);\n    return { dataId, shape: image2.shape, dtype: image2.dtype };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Round.js\nvar round3 = unaryKernelFunc(Round, (xi) => {\n  const base = Math.floor(xi);\n  if (xi - base < 0.5) {\n    return Math.floor(xi);\n  } else if (xi - base > 0.5) {\n    return Math.ceil(xi);\n  } else {\n    if (base % 2 === 0) {\n      return base;\n    } else {\n      return base + 1;\n    }\n  }\n});\nvar roundConfig = {\n  kernelName: Round,\n  backendName: \"cpu\",\n  kernelFunc: round3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ScatterNd.js\nfunction scatterNd(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { indices, updates } = inputs;\n  const { shape } = attrs;\n  const { sliceRank, numUpdates, sliceSize, strides, outputSize } = backend_util_exports.calculateShapes(updates, indices, shape);\n  const sumDupeIndices = true;\n  const indicesBuf = backend2.bufferSync(indices);\n  const updatesBuf = backend2.bufferSync(updates);\n  const outBuf = scatterImpl(indicesBuf, updatesBuf, shape, outputSize, sliceSize, numUpdates, sliceRank, strides, 0, sumDupeIndices);\n  return backend2.makeTensorInfo(shape, outBuf.dtype, outBuf.values);\n}\nvar scatterNdConfig = {\n  kernelName: ScatterNd,\n  backendName: \"cpu\",\n  kernelFunc: scatterNd\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SearchSorted_impl.js\nfunction lowerBound2(array2, value) {\n  let left = 0;\n  let right = array2.length;\n  let mid = 0;\n  while (left < right) {\n    mid = Math.floor((left + right) / 2);\n    if (array2[mid] < value) {\n      left = mid + 1;\n    } else {\n      right = mid;\n    }\n  }\n  return right;\n}\nfunction upperBound2(array2, value) {\n  let left = 0;\n  let right = array2.length;\n  let mid = 0;\n  while (left < right) {\n    mid = Math.floor((left + right) / 2);\n    if (array2[mid] <= value) {\n      left = mid + 1;\n    } else {\n      right = mid;\n    }\n  }\n  return right;\n}\nfunction searchSortedImpl(sortedInputs, values, batchSize, numInputs, numValues, side) {\n  const output = util_exports.getArrayFromDType(\"int32\", batchSize * numValues);\n  for (let b = 0; b < batchSize; ++b) {\n    const sortedInputsSlice = sortedInputs.slice(b * numInputs, (b + 1) * numInputs);\n    const outputOffset = b * numValues;\n    for (let i2 = 0; i2 < numValues; ++i2) {\n      output[outputOffset + i2] = side === \"left\" ? lowerBound2(sortedInputsSlice, values[i2 + outputOffset]) : upperBound2(sortedInputsSlice, values[i2 + outputOffset]);\n    }\n  }\n  return output;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SearchSorted.js\nfunction searchSorted2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { sortedSequence, values } = inputs;\n  const { side } = attrs;\n  const $sortedSequence = backend2.data.get(sortedSequence.dataId).values;\n  const $values = backend2.data.get(values.dataId).values;\n  const output = searchSortedImpl($sortedSequence, $values, sortedSequence.shape[0], sortedSequence.shape[1], values.shape[1], side);\n  return backend2.makeTensorInfo(values.shape, \"int32\", output);\n}\nvar searchSortedConfig = {\n  kernelName: SearchSorted,\n  backendName: \"cpu\",\n  kernelFunc: searchSorted2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Select.js\nfunction select2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { condition, t: t2, e: e2 } = inputs;\n  assertNotComplex([condition, t2, e2], \"select\");\n  const conditionRank = condition.shape.length;\n  const values = backend2.data.get(condition.dataId).values;\n  const tValues = backend2.data.get(t2.dataId).values;\n  const eValues = backend2.data.get(e2.dataId).values;\n  const resultDtype = upcastType(t2.dtype, e2.dtype);\n  const newValues = util_exports.makeZerosTypedArray(util_exports.sizeFromShape(t2.shape), resultDtype);\n  let index = 0;\n  const offset = conditionRank === 0 || conditionRank > 1 || t2.shape.length === 1 ? 1 : util_exports.sizeFromShape(t2.shape.slice(1));\n  for (let i2 = 0; i2 < values.length; i2++) {\n    for (let j = 0; j < offset; j++) {\n      if (values[i2] === 1) {\n        newValues[index++] = tValues[i2];\n      } else {\n        newValues[index++] = eValues[i2];\n      }\n    }\n  }\n  return backend2.makeTensorInfo(t2.shape, resultDtype, newValues);\n}\nvar selectConfig = {\n  kernelName: Select,\n  backendName: \"cpu\",\n  kernelFunc: select2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Selu.js\nvar scaleAlpha = backend_util_exports.SELU_SCALEALPHA;\nvar scale = backend_util_exports.SELU_SCALE;\nvar selu2 = unaryKernelFunc(Selu, (xi) => {\n  if (xi >= 0) {\n    return scale * xi;\n  } else {\n    return scaleAlpha * (Math.exp(xi) - 1);\n  }\n});\nvar seluConfig = {\n  kernelName: Selu,\n  backendName: \"cpu\",\n  kernelFunc: selu2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Sign.js\nvar sign2 = unaryKernelFunc(Sign, (xi) => {\n  if (xi < 0) {\n    return -1;\n  } else if (xi > 0) {\n    return 1;\n  } else {\n    return 0;\n  }\n});\nvar signConfig = {\n  kernelName: Sign,\n  backendName: \"cpu\",\n  kernelFunc: sign2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Sin.js\nvar sin2 = unaryKernelFunc(Sin, (xi) => Math.sin(xi));\nvar sinConfig = {\n  kernelName: Sin,\n  backendName: \"cpu\",\n  kernelFunc: sin2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Sinh.js\nvar sinh2 = unaryKernelFunc(Sinh, (xi) => Math.sinh(xi));\nvar sinhConfig = {\n  kernelName: Sinh,\n  backendName: \"cpu\",\n  kernelFunc: sinh2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Softplus.js\nvar epsilon2 = 11920928955078125e-23;\nvar threshold2 = Math.log(epsilon2) + 2;\nvar softplus2 = unaryKernelFunc(Softplus, (xi) => {\n  const tooLarge = xi > -threshold2;\n  const tooSmall = xi < threshold2;\n  const expX = Math.exp(xi);\n  let result;\n  if (tooSmall) {\n    result = expX;\n  } else if (tooLarge) {\n    result = xi;\n  } else {\n    result = Math.log(1 + expX);\n  }\n  return result;\n});\nvar softplusConfig = {\n  kernelName: Softplus,\n  backendName: \"cpu\",\n  kernelFunc: softplus2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SpaceToBatchND.js\nfunction spaceToBatchND2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, paddings } = attrs;\n  assertNotComplex([x], \"spaceToBatchND\");\n  const prod6 = util_exports.sizeFromShape(blockShape);\n  const completePaddings = [[0, 0]];\n  completePaddings.push(...paddings);\n  for (let i2 = 1 + blockShape.length; i2 < x.shape.length; ++i2) {\n    completePaddings.push([0, 0]);\n  }\n  const paddedX = padV2Config.kernelFunc({\n    inputs: { x },\n    backend: backend2,\n    attrs: { paddings: completePaddings, constantValue: 0 }\n  });\n  const reshapedPaddedShape = backend_util_exports.getReshaped(paddedX.shape, blockShape, prod6, false);\n  const permutedReshapedPaddedPermutation = backend_util_exports.getPermuted(reshapedPaddedShape.length, blockShape.length, false);\n  const flattenShape = backend_util_exports.getReshapedPermuted(paddedX.shape, blockShape, prod6, false);\n  const reshapeInputs = { x: paddedX };\n  const reshapeAttrs = { shape: reshapedPaddedShape };\n  const paddedXReshaped = reshape3({ inputs: reshapeInputs, backend: backend2, attrs: reshapeAttrs });\n  const transposeInputs = { x: paddedXReshaped };\n  const transposeAttrs = { perm: permutedReshapedPaddedPermutation };\n  const paddedXT = transpose2({ inputs: transposeInputs, backend: backend2, attrs: transposeAttrs });\n  const resultReshapeInputs = { x: paddedXT };\n  const resultReshapeAttrs = { shape: flattenShape };\n  const result = reshape3({ inputs: resultReshapeInputs, backend: backend2, attrs: resultReshapeAttrs });\n  backend2.disposeIntermediateTensorInfo(paddedX);\n  backend2.disposeIntermediateTensorInfo(paddedXReshaped);\n  backend2.disposeIntermediateTensorInfo(paddedXT);\n  return result;\n}\nvar spaceToBatchNDConfig = {\n  kernelName: SpaceToBatchND,\n  backendName: \"cpu\",\n  kernelFunc: spaceToBatchND2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseFillEmptyRows.js\nfunction sparseFillEmptyRows2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { indices, values, denseShape, defaultValue } = inputs;\n  if (denseShape.shape.length !== 1) {\n    throw new Error(`Dense shape must be a vector, saw:\n        ${denseShape.shape}`);\n  }\n  if (indices.shape.length !== 2) {\n    throw new Error(`Indices must be a matrix, saw:\n        ${indices.shape}`);\n  }\n  if (values.shape.length !== 1) {\n    throw new Error(`Values must be a vector, saw:\n        ${values.shape}`);\n  }\n  if (defaultValue.shape.length !== 0) {\n    throw new Error(`Default value must be a scalar, saw:\n        ${defaultValue.shape}`);\n  }\n  const $indices = backend2.data.get(indices.dataId).values;\n  const $values = backend2.data.get(values.dataId).values;\n  const $denseShape = backend2.data.get(denseShape.dataId).values;\n  const $defaultValue = backend2.data.get(defaultValue.dataId).values[0];\n  const [outputIndices, outputIndicesShape, outputValues, emptyRowIndicator, reverseIndexMap] = sparseFillEmptyRowsImpl($indices, indices.shape, indices.dtype, $values, values.dtype, $denseShape, $defaultValue);\n  return [\n    backend2.makeTensorInfo(outputIndicesShape, indices.dtype, outputIndices),\n    backend2.makeTensorInfo([outputIndicesShape[0]], values.dtype, outputValues),\n    backend2.makeTensorInfo([emptyRowIndicator.length], \"bool\", new Uint8Array(emptyRowIndicator.map((value) => Number(value)))),\n    backend2.makeTensorInfo([reverseIndexMap.length], indices.dtype, new Int32Array(reverseIndexMap))\n  ];\n}\nvar sparseFillEmptyRowsConfig = {\n  kernelName: SparseFillEmptyRows,\n  backendName: \"cpu\",\n  kernelFunc: sparseFillEmptyRows2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseReshape.js\nfunction sparseReshape2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { inputIndices, inputShape, newShape } = inputs;\n  if (inputIndices.shape.length !== 2) {\n    throw new Error(`Input indices should be a matrix but received shape\n        ${inputIndices.shape}`);\n  }\n  if (inputShape.shape.length !== 1) {\n    throw new Error(`Input shape should be a vector but received shape\n        ${inputShape.shape}`);\n  }\n  if (newShape.shape.length !== 1) {\n    throw new Error(`Target shape should be a vector but received shape ${newShape.shape}`);\n  }\n  const $inputShape = Array.from(backend2.data.get(inputShape.dataId).values);\n  const $inputIndices = backend2.data.get(inputIndices.dataId).values;\n  const targetShape = Array.from(backend2.data.get(newShape.dataId).values);\n  const [newIndices, indicesShape, outputShape] = sparseReshapeImpl($inputIndices, inputIndices.shape, inputIndices.dtype, $inputShape, targetShape);\n  return [\n    backend2.makeTensorInfo(indicesShape, inputIndices.dtype, newIndices),\n    backend2.makeTensorInfo([outputShape.length], newShape.dtype, new Int32Array(outputShape))\n  ];\n}\nvar sparseReshapeConfig = {\n  kernelName: SparseReshape,\n  backendName: \"cpu\",\n  kernelFunc: sparseReshape2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseSegmentMean.js\nfunction sparseSegmentMean2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { data, indices, segmentIds } = inputs;\n  if (data.shape.length < 1) {\n    throw new Error(`Data should be at least 1 dimensional but received scalar`);\n  }\n  if (indices.shape.length !== 1) {\n    throw new Error(`Indices should be a vector but received shape\n          ${indices.shape}`);\n  }\n  if (segmentIds.shape.length !== 1) {\n    throw new Error(`Segment ids should be a vector but received shape\n          ${segmentIds.shape}`);\n  }\n  if (indices.shape[0] !== segmentIds.shape[0]) {\n    throw new Error(`segmentIds and indices should have same size.`);\n  }\n  const $data = backend2.data.get(data.dataId).values;\n  const $indices = backend2.data.get(indices.dataId).values;\n  const $segmentIds = backend2.data.get(segmentIds.dataId).values;\n  const [outputData, outputDataShape] = sparseSegmentReductionImpl($data, data.shape, data.dtype, $indices, $segmentIds, true);\n  return backend2.makeTensorInfo(outputDataShape, data.dtype, outputData);\n}\nvar sparseSegmentMeanConfig = {\n  kernelName: SparseSegmentMean,\n  backendName: \"cpu\",\n  kernelFunc: sparseSegmentMean2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseSegmentSum.js\nfunction sparseSegmentSum2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { data, indices, segmentIds } = inputs;\n  if (data.shape.length < 1) {\n    throw new Error(`Data should be at least 1 dimensional but received scalar`);\n  }\n  if (indices.shape.length !== 1) {\n    throw new Error(`Indices should be a vector but received shape\n         ${indices.shape}`);\n  }\n  if (segmentIds.shape.length !== 1) {\n    throw new Error(`Segment ids should be a vector but received shape\n         ${segmentIds.shape}`);\n  }\n  if (indices.shape[0] !== segmentIds.shape[0]) {\n    throw new Error(`segmentIds and indices should have same size.`);\n  }\n  const $data = backend2.data.get(data.dataId).values;\n  const $indices = backend2.data.get(indices.dataId).values;\n  const $segmentIds = backend2.data.get(segmentIds.dataId).values;\n  const [outputData, outputDataShape] = sparseSegmentReductionImpl($data, data.shape, data.dtype, $indices, $segmentIds);\n  return backend2.makeTensorInfo(outputDataShape, data.dtype, outputData);\n}\nvar sparseSegmentSumConfig = {\n  kernelName: SparseSegmentSum,\n  backendName: \"cpu\",\n  kernelFunc: sparseSegmentSum2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseToDense.js\nfunction sparseToDense2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { sparseIndices, sparseValues, defaultValue } = inputs;\n  const { outputShape } = attrs;\n  const { sliceRank, numUpdates, sliceSize, strides, outputSize } = backend_util_exports.calculateShapes(sparseValues, sparseIndices, outputShape);\n  const sumDupeIndices = false;\n  const indicesBuf = backend2.bufferSync(sparseIndices);\n  let outBuf;\n  switch (sparseValues.dtype) {\n    case \"bool\": {\n      const updatesBuf = backend2.bufferSync(sparseValues);\n      const $defaultValue = Boolean(backend2.data.get(defaultValue.dataId).values[0]);\n      outBuf = scatterImpl(indicesBuf, updatesBuf, outputShape, outputSize, sliceSize, numUpdates, sliceRank, strides, $defaultValue, sumDupeIndices);\n      break;\n    }\n    case \"float32\": {\n      const updatesBuf = backend2.bufferSync(sparseValues);\n      const $defaultValue = backend2.data.get(defaultValue.dataId).values[0];\n      outBuf = scatterImpl(indicesBuf, updatesBuf, outputShape, outputSize, sliceSize, numUpdates, sliceRank, strides, $defaultValue, sumDupeIndices);\n      break;\n    }\n    case \"int32\": {\n      const updatesBuf = backend2.bufferSync(sparseValues);\n      const $defaultValue = backend2.data.get(defaultValue.dataId).values[0];\n      outBuf = scatterImpl(indicesBuf, updatesBuf, outputShape, outputSize, sliceSize, numUpdates, sliceRank, strides, $defaultValue, sumDupeIndices);\n      break;\n    }\n    case \"string\": {\n      const updatesBuf = backend2.bufferSync(sparseValues);\n      const $defaultValue = util_exports.decodeString(backend2.data.get(defaultValue.dataId).values[0]);\n      outBuf = scatterImpl(indicesBuf, updatesBuf, outputShape, outputSize, sliceSize, numUpdates, sliceRank, strides, $defaultValue, sumDupeIndices);\n      break;\n    }\n    default:\n      throw new Error(`Unsupported type ${sparseValues.dtype}`);\n  }\n  return backend2.makeTensorInfo(outputShape, outBuf.dtype, outBuf.values);\n}\nvar sparseToDenseConfig = {\n  kernelName: SparseToDense,\n  backendName: \"cpu\",\n  kernelFunc: sparseToDense2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SplitV.js\nfunction splitV(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { numOrSizeSplits, axis } = attrs;\n  const $axis = util_exports.parseAxisParam(axis, x.shape)[0];\n  const splitSizes = backend_util_exports.prepareSplitSize(x, numOrSizeSplits, $axis);\n  const begin = new Array(x.shape.length).fill(0);\n  const size = x.shape.slice();\n  return splitSizes.map((s2) => {\n    const sliceSize = [...size];\n    sliceSize[$axis] = s2;\n    const sliceT = slice2({ inputs: { x }, backend: backend2, attrs: { begin, size: sliceSize } });\n    begin[$axis] += s2;\n    return sliceT;\n  });\n}\nvar splitVConfig = {\n  kernelName: SplitV,\n  backendName: \"cpu\",\n  kernelFunc: splitV\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Square.js\nvar squareConfig = {\n  kernelName: Square,\n  backendName: \"cpu\",\n  kernelFunc: ({ inputs, backend: backend2 }) => {\n    const { x } = inputs;\n    const cpuBackend = backend2;\n    assertNotComplex(x, \"square\");\n    const values = cpuBackend.data.get(x.dataId).values;\n    const newValues = new Float32Array(values.length);\n    for (let i2 = 0; i2 < values.length; ++i2) {\n      const value = values[i2];\n      newValues[i2] = value * value;\n    }\n    const dataId = cpuBackend.write(newValues, x.shape, x.dtype);\n    return { dataId, shape: x.shape, dtype: x.dtype };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Step.js\nvar step2 = unaryKernelFunc(Step, (xi, attrs) => {\n  const stepAttrs = attrs;\n  if (isNaN(xi)) {\n    return NaN;\n  } else {\n    return xi > 0 ? 1 : stepAttrs.alpha;\n  }\n});\nvar stepConfig = {\n  kernelName: Step,\n  backendName: \"cpu\",\n  kernelFunc: step2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StridedSlice.js\nfunction stridedSlice2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask } = attrs;\n  assertNotComplex(x, \"stridedSlice\");\n  const { finalShapeSparse, finalShape, isIdentity, sliceDim0, isSimpleSlice, begin: $begin, end: $end, strides: $strides } = slice_util_exports.sliceInfo(x.shape, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask);\n  let result;\n  if (isIdentity) {\n    result = reshape3({ inputs: { x }, backend: backend2, attrs: { shape: finalShape } });\n  } else if (sliceDim0 || isSimpleSlice) {\n    util_exports.assert(x.shape.length >= 1, () => `Input must have rank at least 1, got: ${x.shape.length}`);\n    const size = slice_util_exports.computeOutShape($begin, $end, $strides);\n    const sliced = slice2({ inputs: { x }, backend: backend2, attrs: { begin: $begin, size } });\n    result = reshape3({ inputs: { x: sliced }, backend: backend2, attrs: { shape: finalShape } });\n    backend2.disposeIntermediateTensorInfo(sliced);\n  } else {\n    const xBuf = backend2.bufferSync(x);\n    const outBuf = stridedSliceImpl(finalShapeSparse, xBuf, $strides, $begin);\n    result = backend2.makeTensorInfo(finalShape, outBuf.dtype, outBuf.values);\n  }\n  return result;\n}\nvar stridedSliceConfig = {\n  kernelName: StridedSlice,\n  backendName: \"cpu\",\n  kernelFunc: stridedSlice2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StringNGrams.js\nfunction stringNGrams2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { separator, nGramWidths, leftPad, rightPad: rightPad2, padWidth, preserveShortSequences } = attrs;\n  const { data, dataSplits } = inputs;\n  const $data = backend2.data.get(data.dataId).values;\n  const $dataSplits = backend2.data.get(dataSplits.dataId).values;\n  const [nGrams, nGramsSplits] = stringNGramsImpl($data, $dataSplits, separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences);\n  return [\n    backend2.makeTensorInfo([nGrams.length], \"string\", nGrams),\n    backend2.makeTensorInfo(dataSplits.shape, \"int32\", nGramsSplits)\n  ];\n}\nvar stringNGramsConfig = {\n  kernelName: StringNGrams,\n  backendName: \"cpu\",\n  kernelFunc: stringNGrams2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StringSplit.js\nfunction stringSplit2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { skipEmpty } = attrs;\n  const { input: input2, delimiter } = inputs;\n  if (input2.dtype !== \"string\") {\n    throw new Error(\"Input must be of datatype string\");\n  }\n  if (input2.shape.length !== 1) {\n    throw new Error(`Input must be a vector, got shape: ${input2.shape}`);\n  }\n  if (delimiter.shape.length !== 0) {\n    throw new Error(`Delimiter must be a scalar, got shape: ${delimiter.shape}`);\n  }\n  const $input = backend2.data.get(input2.dataId).values;\n  const $delimiter = backend2.data.get(delimiter.dataId).values[0];\n  const [indices, values, shape] = stringSplitImpl($input, $delimiter, skipEmpty);\n  const outputSize = values.length;\n  return [\n    backend2.makeTensorInfo([outputSize, 2], \"int32\", indices),\n    backend2.makeTensorInfo([outputSize], \"string\", values),\n    backend2.makeTensorInfo([2], \"int32\", new Int32Array(shape))\n  ];\n}\nvar stringSplitConfig = {\n  kernelName: StringSplit,\n  backendName: \"cpu\",\n  kernelFunc: stringSplit2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StringToHashBucketFast.js\nfunction stringToHashBucketFast2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { numBuckets } = attrs;\n  const { input: input2 } = inputs;\n  if (input2.dtype !== \"string\") {\n    throw new Error(\"Input must be of datatype string\");\n  }\n  if (numBuckets <= 0) {\n    throw new Error(`Number of buckets must be at least 1`);\n  }\n  const $input = backend2.data.get(input2.dataId).values;\n  const output = stringToHashBucketFastImpl($input, numBuckets);\n  return backend2.makeTensorInfo(input2.shape, \"int32\", output);\n}\nvar stringToHashBucketFastConfig = {\n  kernelName: StringToHashBucketFast,\n  backendName: \"cpu\",\n  kernelFunc: stringToHashBucketFast2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Tan.js\nvar tan2 = unaryKernelFunc(Tan, (xi) => Math.tan(xi));\nvar tanConfig = {\n  kernelName: Tan,\n  backendName: \"cpu\",\n  kernelFunc: tan2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Tanh.js\nvar tanh3 = unaryKernelFunc(Tanh, (xi) => Math.tanh(xi));\nvar tanhConfig = {\n  kernelName: Tanh,\n  backendName: \"cpu\",\n  kernelFunc: tanh3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Tile.js\nfunction tile3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { reps } = attrs;\n  assertNotComplex(x, \"tile\");\n  const outBuf = tileImpl(backend2.bufferSync(x), reps);\n  return backend2.makeTensorInfo(outBuf.shape, outBuf.dtype, outBuf.values);\n}\nvar tileConfig = {\n  kernelName: Tile,\n  backendName: \"cpu\",\n  kernelFunc: tile3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/TopK.js\nfunction topK(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { k, sorted } = attrs;\n  assertNotComplex(x, \"topk\");\n  const xVals = backend2.data.get(x.dataId).values;\n  const [allTopKVals, allTopKIndices] = topKImpl(xVals, x.shape, x.dtype, k, sorted);\n  return [\n    backend2.makeTensorInfo(allTopKVals.shape, allTopKVals.dtype, allTopKVals.values),\n    backend2.makeTensorInfo(allTopKIndices.shape, allTopKIndices.dtype, allTopKIndices.values)\n  ];\n}\nvar topKConfig = {\n  kernelName: TopK,\n  backendName: \"cpu\",\n  kernelFunc: topK\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Transform.js\nfunction transform2(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { image: image2, transforms } = inputs;\n  const { interpolation, fillMode, fillValue, outputShape } = attrs;\n  const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n  const [outHeight, outWidth] = outputShape != null ? outputShape : [imageHeight, imageWidth];\n  const outShape = [batch, outHeight, outWidth, numChannels];\n  const strides = util_exports.computeStrides(image2.shape);\n  const batchStride = strides[0];\n  const rowStride = strides[1];\n  const colStride = strides[2];\n  const outVals = util_exports.getTypedArrayFromDType(image2.dtype, util_exports.sizeFromShape(outShape));\n  outVals.fill(fillValue);\n  const imageVals = backend2.data.get(image2.dataId).values;\n  const transformVals = backend2.data.get(transforms.dataId).values;\n  for (let b = 0; b < batch; ++b) {\n    const transform6 = transforms.shape[0] === 1 ? transformVals : transformVals.subarray(b * 8, b * 8 + 8);\n    for (let outY = 0; outY < outHeight; ++outY) {\n      for (let outX = 0; outX < outWidth; ++outX) {\n        for (let channel = 0; channel < numChannels; ++channel) {\n          let val;\n          const projection = transform6[6] * outX + transform6[7] * outY + 1;\n          if (projection === 0) {\n            continue;\n          }\n          const inX = (transform6[0] * outX + transform6[1] * outY + transform6[2]) / projection;\n          const inY = (transform6[3] * outX + transform6[4] * outY + transform6[5]) / projection;\n          const x = mapCoord(inX, imageWidth, fillMode);\n          const y = mapCoord(inY, imageHeight, fillMode);\n          switch (interpolation) {\n            case \"nearest\":\n              val = nearestInterpolation(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, b, y, x, channel, fillValue);\n              break;\n            case \"bilinear\":\n              val = bilinearInterpolation(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, b, y, x, channel, fillValue);\n              break;\n            default:\n              throw new Error(`Error in Transform: Expect 'nearest' or 'bilinear', but got ${interpolation}`);\n          }\n          const ind = b * batchStride + outY * rowStride + outX * colStride + channel;\n          outVals[ind] = val;\n        }\n      }\n    }\n    return backend2.makeTensorInfo(outShape, image2.dtype, outVals);\n  }\n  const dataId = backend2.write(outVals, outShape, image2.dtype);\n  return { dataId, shape: image2.shape, dtype: image2.dtype };\n}\nvar transformConfig = {\n  kernelName: Transform,\n  backendName: \"cpu\",\n  kernelFunc: transform2\n};\nfunction mapCoord(outCoord, len, mode) {\n  switch (mode) {\n    case \"reflect\":\n      return mapCoordReflect(outCoord, len);\n    case \"wrap\":\n      return mapCoordWrap(outCoord, len);\n    case \"nearest\":\n      return mapCoordNearest(outCoord, len);\n    case \"constant\":\n    default:\n      return mapCoordConstant(outCoord, len);\n  }\n}\nfunction mapCoordReflect(outCoord, len) {\n  let inCoord = outCoord;\n  if (inCoord < 0) {\n    if (len <= 1) {\n      inCoord = 0;\n    } else {\n      const sz2 = 2 * len;\n      if (inCoord < sz2) {\n        inCoord = sz2 * Math.trunc(-inCoord / sz2) + inCoord;\n      }\n      inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1;\n    }\n  } else if (inCoord > len - 1) {\n    if (len <= 1) {\n      inCoord = 0;\n    } else {\n      const sz2 = 2 * len;\n      inCoord -= sz2 * Math.trunc(inCoord / sz2);\n      if (inCoord >= len) {\n        inCoord = sz2 - inCoord - 1;\n      }\n    }\n  }\n  return util_exports.clamp(0, inCoord, len - 1);\n}\nfunction mapCoordWrap(outCoord, len) {\n  let inCoord = outCoord;\n  if (inCoord < 0) {\n    if (len <= 1) {\n      inCoord = 0;\n    } else {\n      const sz = len - 1;\n      inCoord += len * (Math.trunc(-inCoord / sz) + 1);\n    }\n  } else if (inCoord > len - 1) {\n    if (len <= 1) {\n      inCoord = 0;\n    } else {\n      const sz = len - 1;\n      inCoord -= len * Math.trunc(inCoord / sz);\n    }\n  }\n  return util_exports.clamp(0, inCoord, len - 1);\n}\nfunction mapCoordConstant(outCoord, len) {\n  return outCoord;\n}\nfunction mapCoordNearest(outCoord, len) {\n  return util_exports.clamp(0, outCoord, len - 1);\n}\nfunction readWithFillValue(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, y, x, channel, fillValue) {\n  const ind = batch * batchStride + y * rowStride + x * colStride + channel;\n  if (0 <= y && y < imageHeight && 0 <= x && x < imageWidth) {\n    return imageVals[ind];\n  } else {\n    return fillValue;\n  }\n}\nfunction nearestInterpolation(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, y, x, channel, fillValue) {\n  const $y = Math.round(y);\n  const $x = Math.round(x);\n  return readWithFillValue(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, $y, $x, channel, fillValue);\n}\nfunction bilinearInterpolation(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, y, x, channel, fillValue) {\n  const yFloor = Math.floor(y);\n  const xFloor = Math.floor(x);\n  const yCeil = yFloor + 1;\n  const xCeil = xFloor + 1;\n  const valueYFloor = (xCeil - x) * readWithFillValue(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, yFloor, xFloor, channel, fillValue) + (x - xFloor) * readWithFillValue(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, yFloor, xCeil, channel, fillValue);\n  const valueYCeil = (xCeil - x) * readWithFillValue(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, yCeil, xFloor, channel, fillValue) + (x - xFloor) * readWithFillValue(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, yCeil, xCeil, channel, fillValue);\n  return (yCeil - y) * valueYFloor + (y - yFloor) * valueYCeil;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Unique.js\nfunction unique3(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { axis } = attrs;\n  const { x } = inputs;\n  assertNotComplex(x, \"unique\");\n  const values = backend2.data.get(x.dataId).values;\n  const { outputValues, outputShape, indices } = uniqueImpl(values, axis, x.shape, x.dtype);\n  return [\n    backend2.makeTensorInfo(outputShape, x.dtype, outputValues),\n    backend2.makeTensorInfo([indices.length], \"int32\", indices)\n  ];\n}\nvar uniqueConfig = {\n  kernelName: Unique,\n  backendName: \"cpu\",\n  kernelFunc: unique3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Unpack.js\nfunction unpack(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { value } = inputs;\n  let { axis } = attrs;\n  if (axis < 0) {\n    axis += value.shape.length;\n  }\n  const valueRank = value.shape.length;\n  const num = value.shape[axis];\n  const outShape = new Array(valueRank - 1);\n  let outIndex = 0;\n  for (let i2 = 0; i2 < valueRank; i2++) {\n    if (i2 !== axis) {\n      outShape[outIndex++] = value.shape[i2];\n    }\n  }\n  const begin = new Array(valueRank).fill(0);\n  const size = value.shape.slice();\n  size[axis] = 1;\n  const res = new Array(num);\n  for (let i2 = 0; i2 < res.length; i2++) {\n    begin[axis] = i2;\n    const tempRes = slice2({ inputs: { x: value }, backend: backend2, attrs: { begin, size } });\n    res[i2] = reshape3({ inputs: { x: tempRes }, backend: backend2, attrs: { shape: outShape } });\n    backend2.disposeIntermediateTensorInfo(tempRes);\n  }\n  return res;\n}\nvar unpackConfig = {\n  kernelName: Unpack,\n  backendName: \"cpu\",\n  kernelFunc: unpack\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/UnsortedSegmentSum.js\nfunction unsortedSegmentSum2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, segmentIds } = inputs;\n  const { numSegments } = attrs;\n  assertNotComplex(x, \"unsortedSegmentSum\");\n  const xRank = x.shape.length;\n  const segmentIdsRank = segmentIds.shape.length;\n  const res = [];\n  const intermediates = [];\n  const numIters = xRank - segmentIdsRank;\n  let $segmentIds = segmentIds;\n  for (let i2 = 0; i2 < numIters; ++i2) {\n    const expanded = expandDims3({ inputs: { input: $segmentIds }, backend: backend2, attrs: { dim: i2 + 1 } });\n    $segmentIds = expanded;\n    intermediates.push(expanded);\n  }\n  for (let i2 = 0; i2 < numSegments; ++i2) {\n    const scalarValue = util_exports.createScalarValue(i2, \"int32\");\n    const segmentId = backend2.makeTensorInfo([], \"int32\", scalarValue);\n    const mask = equal2({ inputs: { a: segmentId, b: $segmentIds }, backend: backend2 });\n    const maskCasted = cast3({ inputs: { x: mask }, backend: backend2, attrs: { dtype: \"float32\" } });\n    const mul2 = multiply2({ inputs: { a: maskCasted, b: x }, backend: backend2 });\n    const sumTensorInfo = sum3({ inputs: { x: mul2 }, backend: backend2, attrs: { axis: 0, keepDims: false } });\n    res.push(sumTensorInfo);\n    intermediates.push(segmentId);\n    intermediates.push(mask);\n    intermediates.push(maskCasted);\n    intermediates.push(mul2);\n    intermediates.push(sumTensorInfo);\n  }\n  const result = pack({ inputs: res, backend: backend2, attrs: { axis: 0 } });\n  intermediates.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return result;\n}\nvar unsortedSegmentSumConfig = {\n  kernelName: UnsortedSegmentSum,\n  backendName: \"cpu\",\n  kernelFunc: unsortedSegmentSum2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/register_all_kernels.js\nvar kernelConfigs = [\n  _fusedMatMulConfig,\n  absConfig,\n  acosConfig,\n  acoshConfig,\n  addConfig,\n  addNConfig,\n  allConfig,\n  anyConfig,\n  argMaxConfig,\n  argMinConfig,\n  asinConfig,\n  asinhConfig,\n  atanConfig,\n  atan2Config,\n  atanhConfig,\n  avgPoolConfig,\n  avgPool3DConfig,\n  avgPool3DGradConfig2,\n  avgPoolGradConfig2,\n  batchMatMulConfig,\n  batchNormConfig,\n  batchToSpaceNDConfig,\n  bincountConfig,\n  broadcastArgsConfig,\n  castConfig,\n  ceilConfig,\n  clipByValueConfig,\n  complexConfig,\n  complexAbsConfig,\n  concatConfig,\n  conv2DConfig,\n  conv2DBackpropFilterConfig,\n  conv2DBackpropInputConfig,\n  conv3DConfig,\n  conv3DBackpropFilterV2Config,\n  conv3DBackpropInputV2Config,\n  cosConfig,\n  coshConfig,\n  cropAndResizeConfig,\n  cumprodConfig,\n  cumsumConfig,\n  denseBincountConfig,\n  depthToSpaceConfig,\n  depthwiseConv2dNativeConfig,\n  depthwiseConv2dNativeBackpropFilterConfig,\n  depthwiseConv2dNativeBackpropInputConfig,\n  diagConfig,\n  dilation2DConfig,\n  dilation2DBackpropFilterConfig,\n  dilation2DBackpropInputConfig,\n  einsumConfig,\n  eluConfig,\n  eluGradConfig2,\n  equalConfig,\n  erfConfig,\n  expConfig,\n  expandDimsConfig,\n  expm1Config,\n  fftConfig,\n  fillConfig,\n  flipLeftRightConfig,\n  floorConfig,\n  floorDivConfig,\n  fusedConv2DConfig,\n  fusedDepthwiseConv2DConfig,\n  gatherNdConfig,\n  gatherV2Config,\n  greaterConfig,\n  greaterEqualConfig,\n  identityConfig,\n  ifftConfig,\n  imagConfig,\n  isFiniteConfig,\n  isInfConfig,\n  isNaNConfig,\n  leakyReluConfig,\n  lessConfig,\n  lessEqualConfig,\n  linSpaceConfig,\n  logConfig,\n  log1pConfig,\n  logicalAndConfig,\n  logicalNotConfig,\n  logicalOrConfig,\n  LRNConfig,\n  LRNGradConfig,\n  maxConfig,\n  maximumConfig,\n  maxPoolConfig,\n  maxPool3DConfig,\n  maxPool3DGradConfig2,\n  maxPoolGradConfig2,\n  maxPoolWithArgmaxConfig,\n  meanConfig,\n  minConfig,\n  minimumConfig,\n  mirrorPadConfig,\n  modConfig,\n  multinomialConfig,\n  multiplyConfig,\n  negConfig,\n  nonMaxSuppressionV3Config,\n  nonMaxSuppressionV4Config,\n  nonMaxSuppressionV5Config,\n  notEqualConfig,\n  oneHotConfig,\n  onesLikeConfig,\n  packConfig,\n  padV2Config,\n  powConfig,\n  preluConfig,\n  prodConfig,\n  rangeConfig,\n  realConfig,\n  realDivConfig,\n  reciprocalConfig,\n  reluConfig,\n  relu6Config,\n  reshapeConfig,\n  resizeBilinearConfig,\n  resizeBilinearGradConfig2,\n  resizeNearestNeighborConfig,\n  resizeNearestNeighborGradConfig2,\n  reverseConfig,\n  rotateWithOffsetConfig,\n  roundConfig,\n  rsqrtConfig,\n  scatterNdConfig,\n  searchSortedConfig,\n  selectConfig,\n  seluConfig,\n  sigmoidConfig,\n  signConfig,\n  sinConfig,\n  sinhConfig,\n  sliceConfig,\n  softmaxConfig,\n  softplusConfig,\n  spaceToBatchNDConfig,\n  sparseFillEmptyRowsConfig,\n  sparseReshapeConfig,\n  sparseSegmentMeanConfig,\n  sparseSegmentSumConfig,\n  sparseToDenseConfig,\n  splitVConfig,\n  sqrtConfig,\n  squareConfig,\n  squaredDifferenceConfig,\n  stepConfig,\n  stridedSliceConfig,\n  stringNGramsConfig,\n  stringSplitConfig,\n  stringToHashBucketFastConfig,\n  subConfig,\n  sumConfig,\n  tanConfig,\n  tanhConfig,\n  tileConfig,\n  topKConfig,\n  transformConfig,\n  transposeConfig,\n  uniqueConfig,\n  unpackConfig,\n  unsortedSegmentSumConfig,\n  zerosLikeConfig\n];\nfor (const kernelConfig of kernelConfigs) {\n  registerKernel(kernelConfig);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/webgl_util.js\nvar webgl_util_exports = {};\n__export(webgl_util_exports, {\n  assertNotComplex: () => assertNotComplex2,\n  bindCanvasToFramebuffer: () => bindCanvasToFramebuffer,\n  bindColorTextureToFramebuffer: () => bindColorTextureToFramebuffer,\n  bindTextureToProgramUniformSampler: () => bindTextureToProgramUniformSampler,\n  bindTextureUnit: () => bindTextureUnit,\n  bindVertexBufferToProgramAttribute: () => bindVertexBufferToProgramAttribute,\n  callAndCheck: () => callAndCheck,\n  canBeRepresented: () => canBeRepresented,\n  createFragmentShader: () => createFragmentShader,\n  createFramebuffer: () => createFramebuffer,\n  createProgram: () => createProgram,\n  createStaticIndexBuffer: () => createStaticIndexBuffer,\n  createStaticVertexBuffer: () => createStaticVertexBuffer,\n  createTexture: () => createTexture,\n  createVertexShader: () => createVertexShader,\n  getBatchDim: () => getBatchDim,\n  getExtensionOrThrow: () => getExtensionOrThrow,\n  getFramebufferErrorMessage: () => getFramebufferErrorMessage,\n  getMaxTexturesInShader: () => getMaxTexturesInShader,\n  getNumChannels: () => getNumChannels,\n  getProgramUniformLocation: () => getProgramUniformLocation,\n  getProgramUniformLocationOrThrow: () => getProgramUniformLocationOrThrow,\n  getRowsCols: () => getRowsCols,\n  getShapeAs3D: () => getShapeAs3D,\n  getTextureShapeFromLogicalShape: () => getTextureShapeFromLogicalShape,\n  getWebGLDisjointQueryTimerVersion: () => getWebGLDisjointQueryTimerVersion,\n  getWebGLErrorMessage: () => getWebGLErrorMessage,\n  getWebGLMaxTextureSize: () => getWebGLMaxTextureSize,\n  hasExtension: () => hasExtension,\n  isCapableOfRenderingToFloatTexture: () => isCapableOfRenderingToFloatTexture,\n  isDownloadFloatTextureEnabled: () => isDownloadFloatTextureEnabled,\n  isReshapeFree: () => isReshapeFree,\n  isWebGLFenceEnabled: () => isWebGLFenceEnabled,\n  isWebGLVersionEnabled: () => isWebGLVersionEnabled,\n  linkProgram: () => linkProgram,\n  logShaderSourceAndInfoLog: () => logShaderSourceAndInfoLog,\n  resetMaxTextureSize: () => resetMaxTextureSize,\n  resetMaxTexturesInShader: () => resetMaxTexturesInShader,\n  unbindColorTextureFromFramebuffer: () => unbindColorTextureFromFramebuffer,\n  unbindTextureUnit: () => unbindTextureUnit,\n  validateFramebuffer: () => validateFramebuffer,\n  validateProgram: () => validateProgram,\n  validateTextureSize: () => validateTextureSize\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/canvas_util.js\nvar contexts = {};\nvar WEBGL_ATTRIBUTES = {\n  alpha: false,\n  antialias: false,\n  premultipliedAlpha: false,\n  preserveDrawingBuffer: false,\n  depth: false,\n  stencil: false,\n  failIfMajorPerformanceCaveat: true\n};\nfunction setWebGLContext(webGLVersion, gl) {\n  contexts[webGLVersion] = gl;\n}\nfunction getWebGLContext(webGLVersion, customCanvas) {\n  if (!(webGLVersion in contexts) || customCanvas != null) {\n    const newCtx = getWebGLRenderingContext(webGLVersion, customCanvas);\n    if (newCtx !== null) {\n      contexts[webGLVersion] = newCtx;\n    } else {\n      console.log(\"Could not get context for WebGL version\", webGLVersion);\n      return null;\n    }\n  }\n  const gl = contexts[webGLVersion];\n  if (gl == null || gl.isContextLost()) {\n    delete contexts[webGLVersion];\n    return getWebGLContext(webGLVersion);\n  }\n  gl.disable(gl.DEPTH_TEST);\n  gl.disable(gl.STENCIL_TEST);\n  gl.disable(gl.BLEND);\n  gl.disable(gl.DITHER);\n  gl.disable(gl.POLYGON_OFFSET_FILL);\n  gl.disable(gl.SAMPLE_COVERAGE);\n  gl.enable(gl.SCISSOR_TEST);\n  gl.enable(gl.CULL_FACE);\n  gl.cullFace(gl.BACK);\n  return contexts[webGLVersion];\n}\nfunction createCanvas(webGLVersion) {\n  if (typeof OffscreenCanvas !== \"undefined\" && webGLVersion === 2) {\n    return new OffscreenCanvas(300, 150);\n  } else if (typeof document !== \"undefined\") {\n    return document.createElement(\"canvas\");\n  } else {\n    throw new Error(\"Cannot create a canvas in this context\");\n  }\n}\nfunction getWebGLRenderingContext(webGLVersion, customCanvas) {\n  if (webGLVersion !== 1 && webGLVersion !== 2) {\n    throw new Error(\"Cannot get WebGL rendering context, WebGL is disabled.\");\n  }\n  const canvas = customCanvas == null ? createCanvas(webGLVersion) : customCanvas;\n  canvas.addEventListener(\"webglcontextlost\", (ev) => {\n    ev.preventDefault();\n    delete contexts[webGLVersion];\n  }, false);\n  if (webGLVersion === 1) {\n    return canvas.getContext(\"webgl\", WEBGL_ATTRIBUTES) || canvas.getContext(\"experimental-webgl\", WEBGL_ATTRIBUTES);\n  }\n  return canvas.getContext(\"webgl2\", WEBGL_ATTRIBUTES);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/tex_util.js\nvar PackingScheme;\n(function(PackingScheme2) {\n  PackingScheme2[PackingScheme2[\"DENSE\"] = 0] = \"DENSE\";\n  PackingScheme2[PackingScheme2[\"SHARED_BATCH\"] = 1] = \"SHARED_BATCH\";\n})(PackingScheme || (PackingScheme = {}));\nvar TextureUsage;\n(function(TextureUsage2) {\n  TextureUsage2[TextureUsage2[\"RENDER\"] = 0] = \"RENDER\";\n  TextureUsage2[TextureUsage2[\"UPLOAD\"] = 1] = \"UPLOAD\";\n  TextureUsage2[TextureUsage2[\"PIXELS\"] = 2] = \"PIXELS\";\n  TextureUsage2[TextureUsage2[\"DOWNLOAD\"] = 3] = \"DOWNLOAD\";\n})(TextureUsage || (TextureUsage = {}));\nvar PhysicalTextureType;\n(function(PhysicalTextureType2) {\n  PhysicalTextureType2[PhysicalTextureType2[\"UNPACKED_FLOAT16\"] = 0] = \"UNPACKED_FLOAT16\";\n  PhysicalTextureType2[PhysicalTextureType2[\"UNPACKED_FLOAT32\"] = 1] = \"UNPACKED_FLOAT32\";\n  PhysicalTextureType2[PhysicalTextureType2[\"PACKED_4X1_UNSIGNED_BYTE\"] = 2] = \"PACKED_4X1_UNSIGNED_BYTE\";\n  PhysicalTextureType2[PhysicalTextureType2[\"PACKED_2X2_FLOAT32\"] = 3] = \"PACKED_2X2_FLOAT32\";\n  PhysicalTextureType2[PhysicalTextureType2[\"PACKED_2X2_FLOAT16\"] = 4] = \"PACKED_2X2_FLOAT16\";\n})(PhysicalTextureType || (PhysicalTextureType = {}));\nfunction getUnpackedMatrixTextureShapeWidthHeight(rows, columns) {\n  return [columns, rows];\n}\nfunction getUnpackedArraySizeFromMatrixSize(matrixSize, channelsPerTexture) {\n  return matrixSize * channelsPerTexture;\n}\nfunction getDenseTexShape(shape) {\n  const size = util_exports.sizeFromShape(shape);\n  const texelsNeeded = Math.ceil(size / 4);\n  return util_exports.sizeToSquarishShape(texelsNeeded);\n}\nfunction getPackedMatrixTextureShapeWidthHeight(rows, columns) {\n  return [\n    Math.max(1, Math.ceil(columns / 2)),\n    Math.max(1, Math.ceil(rows / 2))\n  ];\n}\nfunction getPackedRGBAArraySizeFromMatrixShape(rows, columns) {\n  const [w, h] = getPackedMatrixTextureShapeWidthHeight(rows, columns);\n  return w * h * 4;\n}\nfunction getTextureConfig(gl, textureHalfFloatExtension) {\n  const glany = gl;\n  let internalFormatFloat;\n  let internalFormatHalfFloat;\n  let internalFormatPackedHalfFloat;\n  let internalFormatPackedFloat;\n  let textureFormatFloat;\n  let downloadTextureFormat;\n  let downloadUnpackNumChannels;\n  let defaultNumChannels;\n  let textureTypeHalfFloat;\n  let textureTypeFloat;\n  if (env().getNumber(\"WEBGL_VERSION\") === 2) {\n    internalFormatFloat = glany.R32F;\n    internalFormatHalfFloat = glany.R16F;\n    internalFormatPackedHalfFloat = glany.RGBA16F;\n    internalFormatPackedFloat = glany.RGBA32F;\n    textureFormatFloat = glany.RED;\n    downloadUnpackNumChannels = 4;\n    defaultNumChannels = 1;\n    textureTypeHalfFloat = glany.HALF_FLOAT;\n    textureTypeFloat = glany.FLOAT;\n    downloadTextureFormat = glany.RGBA8;\n  } else {\n    internalFormatFloat = gl.RGBA;\n    internalFormatHalfFloat = gl.RGBA;\n    internalFormatPackedHalfFloat = gl.RGBA;\n    internalFormatPackedFloat = glany.RGBA;\n    textureFormatFloat = gl.RGBA;\n    downloadUnpackNumChannels = 4;\n    defaultNumChannels = 4;\n    textureTypeHalfFloat = textureHalfFloatExtension != null ? textureHalfFloatExtension.HALF_FLOAT_OES : null;\n    textureTypeFloat = gl.FLOAT;\n    downloadTextureFormat = gl.RGBA;\n  }\n  return {\n    internalFormatFloat,\n    internalFormatHalfFloat,\n    internalFormatPackedHalfFloat,\n    internalFormatPackedFloat,\n    textureFormatFloat,\n    downloadTextureFormat,\n    downloadUnpackNumChannels,\n    defaultNumChannels,\n    textureTypeHalfFloat,\n    textureTypeFloat\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/webgl_util.js\nfunction callAndCheck(gl, func2) {\n  const returnValue = func2();\n  if (env().getBool(\"DEBUG\")) {\n    checkWebGLError(gl);\n  }\n  return returnValue;\n}\nfunction checkWebGLError(gl) {\n  const error = gl.getError();\n  if (error !== gl.NO_ERROR) {\n    throw new Error(\"WebGL Error: \" + getWebGLErrorMessage(gl, error));\n  }\n}\nvar MIN_FLOAT16 = 596e-10;\nvar MAX_FLOAT16 = 65504;\nfunction canBeRepresented(num) {\n  if (env().getBool(\"WEBGL_RENDER_FLOAT32_ENABLED\") || num === 0 || MIN_FLOAT16 < Math.abs(num) && Math.abs(num) < MAX_FLOAT16) {\n    return true;\n  }\n  return false;\n}\nfunction getWebGLErrorMessage(gl, status) {\n  switch (status) {\n    case gl.NO_ERROR:\n      return \"NO_ERROR\";\n    case gl.INVALID_ENUM:\n      return \"INVALID_ENUM\";\n    case gl.INVALID_VALUE:\n      return \"INVALID_VALUE\";\n    case gl.INVALID_OPERATION:\n      return \"INVALID_OPERATION\";\n    case gl.INVALID_FRAMEBUFFER_OPERATION:\n      return \"INVALID_FRAMEBUFFER_OPERATION\";\n    case gl.OUT_OF_MEMORY:\n      return \"OUT_OF_MEMORY\";\n    case gl.CONTEXT_LOST_WEBGL:\n      return \"CONTEXT_LOST_WEBGL\";\n    default:\n      return `Unknown error code ${status}`;\n  }\n}\nfunction getExtensionOrThrow(gl, extensionName) {\n  return throwIfNull(gl, () => gl.getExtension(extensionName), 'Extension \"' + extensionName + '\" not supported on this browser.');\n}\nfunction createVertexShader(gl, vertexShaderSource) {\n  const vertexShader = throwIfNull(gl, () => gl.createShader(gl.VERTEX_SHADER), \"Unable to create vertex WebGLShader.\");\n  callAndCheck(gl, () => gl.shaderSource(vertexShader, vertexShaderSource));\n  callAndCheck(gl, () => gl.compileShader(vertexShader));\n  if (gl.getShaderParameter(vertexShader, gl.COMPILE_STATUS) === false) {\n    console.log(gl.getShaderInfoLog(vertexShader));\n    throw new Error(\"Failed to compile vertex shader.\");\n  }\n  return vertexShader;\n}\nfunction createFragmentShader(gl, fragmentShaderSource) {\n  const fragmentShader = throwIfNull(gl, () => gl.createShader(gl.FRAGMENT_SHADER), \"Unable to create fragment WebGLShader.\");\n  callAndCheck(gl, () => gl.shaderSource(fragmentShader, fragmentShaderSource));\n  callAndCheck(gl, () => gl.compileShader(fragmentShader));\n  if (env().get(\"ENGINE_COMPILE_ONLY\")) {\n    return fragmentShader;\n  }\n  if (gl.getShaderParameter(fragmentShader, gl.COMPILE_STATUS) === false) {\n    logShaderSourceAndInfoLog(fragmentShaderSource, gl.getShaderInfoLog(fragmentShader));\n    throw new Error(\"Failed to compile fragment shader.\");\n  }\n  return fragmentShader;\n}\nvar lineNumberRegex = /ERROR: [0-9]+:([0-9]+):/g;\nfunction logShaderSourceAndInfoLog(shaderSource, shaderInfoLog) {\n  const lineNumberRegexResult = lineNumberRegex.exec(shaderInfoLog);\n  if (lineNumberRegexResult == null) {\n    console.log(`Couldn't parse line number in error: ${shaderInfoLog}`);\n    console.log(shaderSource);\n    return;\n  }\n  const lineNumber = +lineNumberRegexResult[1];\n  const shaderLines = shaderSource.split(\"\\n\");\n  const pad3 = shaderLines.length.toString().length + 2;\n  const linesWithLineNumbers = shaderLines.map((line, lineNumber2) => util_exports.rightPad((lineNumber2 + 1).toString(), pad3) + line);\n  let maxLineLength = 0;\n  for (let i2 = 0; i2 < linesWithLineNumbers.length; i2++) {\n    maxLineLength = Math.max(linesWithLineNumbers[i2].length, maxLineLength);\n  }\n  const beforeErrorLines = linesWithLineNumbers.slice(0, lineNumber - 1);\n  const errorLine = linesWithLineNumbers.slice(lineNumber - 1, lineNumber);\n  const afterErrorLines = linesWithLineNumbers.slice(lineNumber);\n  console.log(beforeErrorLines.join(\"\\n\"));\n  console.log(shaderInfoLog.split(\"\\n\")[0]);\n  console.log(`%c ${util_exports.rightPad(errorLine[0], maxLineLength)}`, \"border:1px solid red; background-color:#e3d2d2; color:#a61717\");\n  console.log(afterErrorLines.join(\"\\n\"));\n}\nfunction createProgram(gl) {\n  return throwIfNull(gl, () => gl.createProgram(), \"Unable to create WebGLProgram.\");\n}\nfunction linkProgram(gl, program) {\n  callAndCheck(gl, () => gl.linkProgram(program));\n  if (env().get(\"ENGINE_COMPILE_ONLY\")) {\n    return;\n  }\n  if (gl.getProgramParameter(program, gl.LINK_STATUS) === false) {\n    console.log(gl.getProgramInfoLog(program));\n    throw new Error(\"Failed to link vertex and fragment shaders.\");\n  }\n}\nfunction validateProgram(gl, program) {\n  callAndCheck(gl, () => gl.validateProgram(program));\n  if (gl.getProgramParameter(program, gl.VALIDATE_STATUS) === false) {\n    console.log(gl.getProgramInfoLog(program));\n    throw new Error(\"Shader program validation failed.\");\n  }\n}\nfunction createStaticVertexBuffer(gl, data) {\n  const buffer2 = throwIfNull(gl, () => gl.createBuffer(), \"Unable to create WebGLBuffer\");\n  callAndCheck(gl, () => gl.bindBuffer(gl.ARRAY_BUFFER, buffer2));\n  callAndCheck(gl, () => gl.bufferData(gl.ARRAY_BUFFER, data, gl.STATIC_DRAW));\n  return buffer2;\n}\nfunction createStaticIndexBuffer(gl, data) {\n  const buffer2 = throwIfNull(gl, () => gl.createBuffer(), \"Unable to create WebGLBuffer\");\n  callAndCheck(gl, () => gl.bindBuffer(gl.ELEMENT_ARRAY_BUFFER, buffer2));\n  callAndCheck(gl, () => gl.bufferData(gl.ELEMENT_ARRAY_BUFFER, data, gl.STATIC_DRAW));\n  return buffer2;\n}\nfunction getNumChannels() {\n  if (env().getNumber(\"WEBGL_VERSION\") === 2) {\n    return 1;\n  }\n  return 4;\n}\nfunction createTexture(gl) {\n  return throwIfNull(gl, () => gl.createTexture(), \"Unable to create WebGLTexture.\");\n}\nfunction validateTextureSize(width, height) {\n  const maxTextureSize = env().getNumber(\"WEBGL_MAX_TEXTURE_SIZE\");\n  if (width <= 0 || height <= 0) {\n    const requested = `[${width}x${height}]`;\n    throw new Error(\"Requested texture size \" + requested + \" is invalid.\");\n  }\n  if (width > maxTextureSize || height > maxTextureSize) {\n    const requested = `[${width}x${height}]`;\n    const max7 = `[${maxTextureSize}x${maxTextureSize}]`;\n    throw new Error(\"Requested texture size \" + requested + \" greater than WebGL maximum on this browser / GPU \" + max7 + \".\");\n  }\n}\nfunction createFramebuffer(gl) {\n  return throwIfNull(gl, () => gl.createFramebuffer(), \"Unable to create WebGLFramebuffer.\");\n}\nfunction bindVertexBufferToProgramAttribute(gl, program, attribute, buffer2, arrayEntriesPerItem, itemStrideInBytes, itemOffsetInBytes) {\n  const loc = gl.getAttribLocation(program, attribute);\n  if (loc === -1) {\n    return false;\n  }\n  callAndCheck(gl, () => gl.bindBuffer(gl.ARRAY_BUFFER, buffer2));\n  callAndCheck(gl, () => gl.vertexAttribPointer(loc, arrayEntriesPerItem, gl.FLOAT, false, itemStrideInBytes, itemOffsetInBytes));\n  callAndCheck(gl, () => gl.enableVertexAttribArray(loc));\n  return true;\n}\nfunction bindTextureUnit(gl, texture, textureUnit) {\n  validateTextureUnit(gl, textureUnit);\n  callAndCheck(gl, () => gl.activeTexture(gl.TEXTURE0 + textureUnit));\n  callAndCheck(gl, () => gl.bindTexture(gl.TEXTURE_2D, texture));\n}\nfunction unbindTextureUnit(gl, textureUnit) {\n  validateTextureUnit(gl, textureUnit);\n  callAndCheck(gl, () => gl.activeTexture(gl.TEXTURE0 + textureUnit));\n  callAndCheck(gl, () => gl.bindTexture(gl.TEXTURE_2D, null));\n}\nfunction getProgramUniformLocationOrThrow(gl, program, uniformName) {\n  return throwIfNull(gl, () => gl.getUniformLocation(program, uniformName), 'uniform \"' + uniformName + '\" not present in program.');\n}\nfunction getProgramUniformLocation(gl, program, uniformName) {\n  return gl.getUniformLocation(program, uniformName);\n}\nfunction bindTextureToProgramUniformSampler(gl, texture, uniformSamplerLocation, textureUnit) {\n  callAndCheck(gl, () => bindTextureUnit(gl, texture, textureUnit));\n  callAndCheck(gl, () => gl.uniform1i(uniformSamplerLocation, textureUnit));\n}\nfunction bindCanvasToFramebuffer(gl) {\n  callAndCheck(gl, () => gl.bindFramebuffer(gl.FRAMEBUFFER, null));\n  callAndCheck(gl, () => gl.viewport(0, 0, gl.canvas.width, gl.canvas.height));\n  callAndCheck(gl, () => gl.scissor(0, 0, gl.canvas.width, gl.canvas.height));\n}\nfunction bindColorTextureToFramebuffer(gl, texture, framebuffer) {\n  callAndCheck(gl, () => gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffer));\n  callAndCheck(gl, () => gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0));\n}\nfunction unbindColorTextureFromFramebuffer(gl, framebuffer) {\n  callAndCheck(gl, () => gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffer));\n  callAndCheck(gl, () => gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, null, 0));\n}\nfunction validateFramebuffer(gl) {\n  const status = gl.checkFramebufferStatus(gl.FRAMEBUFFER);\n  if (status !== gl.FRAMEBUFFER_COMPLETE) {\n    throw new Error(\"Error binding framebuffer: \" + getFramebufferErrorMessage(gl, status));\n  }\n}\nfunction getFramebufferErrorMessage(gl, status) {\n  switch (status) {\n    case gl.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:\n      return \"FRAMEBUFFER_INCOMPLETE_ATTACHMENT\";\n    case gl.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:\n      return \"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT\";\n    case gl.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:\n      return \"FRAMEBUFFER_INCOMPLETE_DIMENSIONS\";\n    case gl.FRAMEBUFFER_UNSUPPORTED:\n      return \"FRAMEBUFFER_UNSUPPORTED\";\n    default:\n      return `unknown error ${status}`;\n  }\n}\nfunction throwIfNull(gl, returnTOrNull, failureMessage) {\n  const tOrNull = callAndCheck(gl, () => returnTOrNull());\n  if (tOrNull == null) {\n    throw new Error(failureMessage);\n  }\n  return tOrNull;\n}\nfunction validateTextureUnit(gl, textureUnit) {\n  const maxTextureUnit = gl.MAX_COMBINED_TEXTURE_IMAGE_UNITS - 1;\n  const glTextureUnit = textureUnit + gl.TEXTURE0;\n  if (glTextureUnit < gl.TEXTURE0 || glTextureUnit > maxTextureUnit) {\n    const textureUnitRange = `[gl.TEXTURE0, gl.TEXTURE${maxTextureUnit}]`;\n    throw new Error(`textureUnit must be in ${textureUnitRange}.`);\n  }\n}\nfunction getBatchDim(shape, dimsToSkip = 2) {\n  return util_exports.sizeFromShape(shape.slice(0, shape.length - dimsToSkip));\n}\nfunction getRowsCols(shape) {\n  if (shape.length === 0) {\n    throw Error(\"Cannot get rows and columns of an empty shape array.\");\n  }\n  return [\n    shape.length > 1 ? shape[shape.length - 2] : 1,\n    shape[shape.length - 1]\n  ];\n}\nfunction getShapeAs3D(shape) {\n  let shapeAs3D = [1, 1, 1];\n  const isScalar = shape.length === 0 || shape.length === 1 && shape[0] === 1;\n  if (!isScalar) {\n    shapeAs3D = [getBatchDim(shape), ...getRowsCols(shape)];\n  }\n  return shapeAs3D;\n}\nfunction getTextureShapeFromLogicalShape(logShape, isPacked = false) {\n  let maxTexSize = env().getNumber(\"WEBGL_MAX_TEXTURE_SIZE\");\n  if (isPacked) {\n    maxTexSize = maxTexSize * 2;\n    logShape = logShape.map((d, i2) => i2 >= logShape.length - 2 ? util_exports.nearestLargerEven(logShape[i2]) : logShape[i2]);\n    if (logShape.length === 1) {\n      logShape = [2, logShape[0]];\n    }\n  }\n  if (logShape.length !== 2) {\n    const squeezeResult = util_exports.squeezeShape(logShape);\n    logShape = squeezeResult.newShape;\n  }\n  let size = util_exports.sizeFromShape(logShape);\n  if (logShape.length <= 1 && size <= maxTexSize) {\n    return [1, size];\n  } else if (logShape.length === 2 && logShape[0] <= maxTexSize && logShape[1] <= maxTexSize) {\n    return logShape;\n  } else if (logShape.length === 3 && logShape[0] * logShape[1] <= maxTexSize && logShape[2] <= maxTexSize) {\n    return [logShape[0] * logShape[1], logShape[2]];\n  } else if (logShape.length === 3 && logShape[0] <= maxTexSize && logShape[1] * logShape[2] <= maxTexSize) {\n    return [logShape[0], logShape[1] * logShape[2]];\n  } else if (logShape.length === 4 && logShape[0] * logShape[1] * logShape[2] <= maxTexSize && logShape[3] <= maxTexSize) {\n    return [logShape[0] * logShape[1] * logShape[2], logShape[3]];\n  } else if (logShape.length === 4 && logShape[0] <= maxTexSize && logShape[1] * logShape[2] * logShape[3] <= maxTexSize) {\n    return [logShape[0], logShape[1] * logShape[2] * logShape[3]];\n  } else {\n    if (isPacked) {\n      const batchDim = getBatchDim(logShape);\n      let rows = 2, cols = 2;\n      if (logShape.length) {\n        [rows, cols] = getRowsCols(logShape);\n      }\n      size = batchDim * (rows / 2) * (cols / 2);\n      return util_exports.sizeToSquarishShape(size).map((d) => d * 2);\n    }\n    return util_exports.sizeToSquarishShape(size);\n  }\n}\nfunction isEven(n2) {\n  return n2 % 2 === 0;\n}\nfunction isReshapeFree(shape1, shape2) {\n  shape1 = shape1.slice(-2);\n  shape2 = shape2.slice(-2);\n  if (util_exports.arraysEqual(shape1, shape2)) {\n    return true;\n  }\n  if (!shape1.length || !shape2.length) {\n    return true;\n  }\n  if (shape1[0] === 0 || shape1[1] === 0 || shape2[0] === 0 || shape2[1] === 0) {\n    return true;\n  }\n  if (shape1.length !== shape2.length) {\n    const shape1Cols = shape1.slice(-1)[0];\n    const shape2Cols = shape2.slice(-1)[0];\n    if (shape1Cols === shape2Cols) {\n      return true;\n    }\n    if (isEven(shape1Cols) && isEven(shape2Cols) && (shape1[0] === 1 || shape2[0] === 1)) {\n      return true;\n    }\n  }\n  return shape1[1] === shape2[1] && isEven(shape1[0]) && isEven(shape2[0]);\n}\nvar MAX_TEXTURE_SIZE;\nvar MAX_TEXTURES_IN_SHADER;\nfunction getWebGLMaxTextureSize(webGLVersion) {\n  if (MAX_TEXTURE_SIZE == null) {\n    const gl = getWebGLContext(webGLVersion);\n    MAX_TEXTURE_SIZE = gl.getParameter(gl.MAX_TEXTURE_SIZE);\n  }\n  return MAX_TEXTURE_SIZE;\n}\nfunction resetMaxTextureSize() {\n  MAX_TEXTURE_SIZE = null;\n}\nfunction resetMaxTexturesInShader() {\n  MAX_TEXTURES_IN_SHADER = null;\n}\nfunction getMaxTexturesInShader(webGLVersion) {\n  if (MAX_TEXTURES_IN_SHADER == null) {\n    const gl = getWebGLContext(webGLVersion);\n    MAX_TEXTURES_IN_SHADER = gl.getParameter(gl.MAX_TEXTURE_IMAGE_UNITS);\n  }\n  return Math.min(16, MAX_TEXTURES_IN_SHADER);\n}\nfunction getWebGLDisjointQueryTimerVersion(webGLVersion) {\n  if (webGLVersion === 0) {\n    return 0;\n  }\n  let queryTimerVersion;\n  const gl = getWebGLContext(webGLVersion);\n  if (hasExtension(gl, \"EXT_disjoint_timer_query_webgl2\") && webGLVersion === 2) {\n    queryTimerVersion = 2;\n  } else if (hasExtension(gl, \"EXT_disjoint_timer_query\")) {\n    queryTimerVersion = 1;\n  } else {\n    queryTimerVersion = 0;\n  }\n  return queryTimerVersion;\n}\nfunction hasExtension(gl, extensionName) {\n  const ext = gl.getExtension(extensionName);\n  return ext != null;\n}\nfunction isWebGLVersionEnabled(webGLVersion) {\n  try {\n    const gl = getWebGLContext(webGLVersion);\n    if (gl != null) {\n      return true;\n    }\n  } catch (e2) {\n    console.log(\"Error when getting WebGL context: \", e2);\n    return false;\n  }\n  return false;\n}\nfunction isCapableOfRenderingToFloatTexture(webGLVersion) {\n  if (webGLVersion === 0) {\n    return false;\n  }\n  const gl = getWebGLContext(webGLVersion);\n  if (webGLVersion === 1) {\n    if (!hasExtension(gl, \"OES_texture_float\")) {\n      return false;\n    }\n  } else {\n    if (!hasExtension(gl, \"EXT_color_buffer_float\")) {\n      return false;\n    }\n  }\n  const isFrameBufferComplete = createFloatTextureAndBindToFramebuffer(gl);\n  return isFrameBufferComplete;\n}\nfunction isDownloadFloatTextureEnabled(webGLVersion) {\n  if (webGLVersion === 0) {\n    return false;\n  }\n  const gl = getWebGLContext(webGLVersion);\n  if (webGLVersion === 1) {\n    if (!hasExtension(gl, \"OES_texture_float\")) {\n      return false;\n    }\n    if (!hasExtension(gl, \"WEBGL_color_buffer_float\")) {\n      return false;\n    }\n  } else {\n    if (hasExtension(gl, \"EXT_color_buffer_float\")) {\n      return createFloatTextureAndBindToFramebuffer(gl);\n    }\n    const COLOR_BUFFER_HALF_FLOAT = \"EXT_color_buffer_half_float\";\n    if (hasExtension(gl, COLOR_BUFFER_HALF_FLOAT)) {\n      const textureHalfFloatExtension = gl.getExtension(COLOR_BUFFER_HALF_FLOAT);\n      return createHalfFloatTextureAndBindToFramebuffer(gl, textureHalfFloatExtension);\n    }\n    return false;\n  }\n  const isFrameBufferComplete = createFloatTextureAndBindToFramebuffer(gl);\n  return isFrameBufferComplete;\n}\nfunction createFloatTextureAndBindToFramebuffer(gl) {\n  const texConfig = getTextureConfig(gl);\n  const texture = gl.createTexture();\n  gl.bindTexture(gl.TEXTURE_2D, texture);\n  const width = 1;\n  const height = 1;\n  gl.texImage2D(gl.TEXTURE_2D, 0, texConfig.internalFormatFloat, width, height, 0, texConfig.textureFormatFloat, texConfig.textureTypeFloat, null);\n  const frameBuffer = gl.createFramebuffer();\n  gl.bindFramebuffer(gl.FRAMEBUFFER, frameBuffer);\n  gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n  const isFrameBufferComplete = gl.checkFramebufferStatus(gl.FRAMEBUFFER) === gl.FRAMEBUFFER_COMPLETE;\n  gl.bindTexture(gl.TEXTURE_2D, null);\n  gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n  gl.deleteTexture(texture);\n  gl.deleteFramebuffer(frameBuffer);\n  return isFrameBufferComplete;\n}\nfunction createHalfFloatTextureAndBindToFramebuffer(gl, textureHalfFloatExtension) {\n  const texConfig = getTextureConfig(gl, textureHalfFloatExtension);\n  const texture = gl.createTexture();\n  gl.bindTexture(gl.TEXTURE_2D, texture);\n  const width = 1;\n  const height = 1;\n  gl.texImage2D(gl.TEXTURE_2D, 0, texConfig.internalFormatHalfFloat, width, height, 0, texConfig.textureFormatFloat, texConfig.textureTypeHalfFloat, null);\n  const frameBuffer = gl.createFramebuffer();\n  gl.bindFramebuffer(gl.FRAMEBUFFER, frameBuffer);\n  gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n  const isFrameBufferComplete = gl.checkFramebufferStatus(gl.FRAMEBUFFER) === gl.FRAMEBUFFER_COMPLETE;\n  gl.bindTexture(gl.TEXTURE_2D, null);\n  gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n  gl.deleteTexture(texture);\n  gl.deleteFramebuffer(frameBuffer);\n  return isFrameBufferComplete;\n}\nfunction isWebGLFenceEnabled(webGLVersion) {\n  if (webGLVersion !== 2) {\n    return false;\n  }\n  const gl = getWebGLContext(webGLVersion);\n  const isEnabled = gl.fenceSync != null;\n  return isEnabled;\n}\nfunction assertNotComplex2(tensor2, opName) {\n  if (!Array.isArray(tensor2)) {\n    tensor2 = [tensor2];\n  }\n  tensor2.forEach((t2) => {\n    if (t2 != null) {\n      util_exports.assert(t2.dtype !== \"complex64\", () => `${opName} does not support complex64 tensors in the WebGL backend.`);\n    }\n  });\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/flags_webgl.js\nvar ENV5 = env();\nENV5.registerFlag(\"HAS_WEBGL\", () => ENV5.getNumber(\"WEBGL_VERSION\") > 0);\nENV5.registerFlag(\"WEBGL_VERSION\", () => {\n  if (isWebGLVersionEnabled(2)) {\n    return 2;\n  } else if (isWebGLVersionEnabled(1)) {\n    return 1;\n  }\n  return 0;\n});\nENV5.registerFlag(\"WEBGL_CHECK_NUMERICAL_PROBLEMS\", () => false);\nENV5.registerFlag(\"WEBGL_BUFFER_SUPPORTED\", () => ENV5.get(\"WEBGL_VERSION\") === 2);\nENV5.registerFlag(\"WEBGL_CPU_FORWARD\", () => true);\nENV5.registerFlag(\"WEBGL_FORCE_F16_TEXTURES\", () => false);\nENV5.registerFlag(\"WEBGL_PACK\", () => ENV5.getBool(\"HAS_WEBGL\"));\nENV5.registerFlag(\"WEBGL_PACK_NORMALIZATION\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_PACK_CLIP\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_PACK_DEPTHWISECONV\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_PACK_BINARY_OPERATIONS\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_PACK_UNARY_OPERATIONS\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_PACK_ARRAY_OPERATIONS\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_PACK_IMAGE_OPERATIONS\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_PACK_REDUCE\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_LAZILY_UNPACK\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_CONV_IM2COL\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_MAX_TEXTURE_SIZE\", () => getWebGLMaxTextureSize(ENV5.getNumber(\"WEBGL_VERSION\")));\nENV5.registerFlag(\"WEBGL_MAX_TEXTURES_IN_SHADER\", () => getMaxTexturesInShader(ENV5.getNumber(\"WEBGL_VERSION\")));\nENV5.registerFlag(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\", () => {\n  const webGLVersion = ENV5.getNumber(\"WEBGL_VERSION\");\n  if (webGLVersion === 0) {\n    return 0;\n  }\n  return getWebGLDisjointQueryTimerVersion(webGLVersion);\n});\nENV5.registerFlag(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\", () => ENV5.getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\") > 0 && !device_util_exports.isMobile());\nENV5.registerFlag(\"WEBGL_RENDER_FLOAT32_CAPABLE\", () => isCapableOfRenderingToFloatTexture(ENV5.getNumber(\"WEBGL_VERSION\")));\nENV5.registerFlag(\"WEBGL_RENDER_FLOAT32_ENABLED\", () => {\n  return ENV5.getBool(\"WEBGL_FORCE_F16_TEXTURES\") ? false : ENV5.getBool(\"WEBGL_RENDER_FLOAT32_CAPABLE\");\n});\nENV5.registerFlag(\"WEBGL_DOWNLOAD_FLOAT_ENABLED\", () => isDownloadFloatTextureEnabled(ENV5.getNumber(\"WEBGL_VERSION\")));\nENV5.registerFlag(\"WEBGL_FENCE_API_ENABLED\", () => isWebGLFenceEnabled(ENV5.getNumber(\"WEBGL_VERSION\")));\nENV5.registerFlag(\"WEBGL_SIZE_UPLOAD_UNIFORM\", () => {\n  const useUniforms = ENV5.getBool(\"WEBGL_RENDER_FLOAT32_ENABLED\");\n  return useUniforms ? 4 : 0;\n});\nENV5.registerFlag(\"WEBGL_DELETE_TEXTURE_THRESHOLD\", () => {\n  return -1;\n}, (threshold3) => {\n  if (threshold3 < 0 && threshold3 !== -1) {\n    throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${threshold3}.`);\n  }\n});\nENV5.registerFlag(\"WEBGL_FLUSH_THRESHOLD\", () => {\n  return device_util_exports.isMobile() ? 1 : -1;\n}, (threshold3) => {\n  if (threshold3 < 0 && threshold3 !== -1) {\n    throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${threshold3}.`);\n  }\n});\nENV5.registerFlag(\"CPU_HANDOFF_SIZE_THRESHOLD\", () => 128);\nENV5.registerFlag(\"WEBGL_USE_SHAPES_UNIFORMS\", () => false);\nENV5.registerFlag(\"TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD\", () => 1e5);\nENV5.registerFlag(\"TOPK_K_CPU_HANDOFF_THRESHOLD\", () => 128);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/glsl_version.js\nfunction getGlslDifferences() {\n  let version9;\n  let attribute;\n  let varyingVs;\n  let varyingFs;\n  let texture2D;\n  let output;\n  let defineOutput;\n  let defineSpecialNaN;\n  let defineSpecialInf;\n  let defineRound;\n  if (env().getNumber(\"WEBGL_VERSION\") === 2) {\n    version9 = \"#version 300 es\";\n    attribute = \"in\";\n    varyingVs = \"out\";\n    varyingFs = \"in\";\n    texture2D = \"texture\";\n    output = \"outputColor\";\n    defineOutput = \"out vec4 outputColor;\";\n    defineSpecialNaN = `\n      bool isnan_custom(float val) {\n        uint floatToUint = floatBitsToUint(val);\n        return (floatToUint & 0x7fffffffu) > 0x7f800000u;\n      }\n\n      bvec4 isnan_custom(vec4 val) {\n        return bvec4(isnan_custom(val.x),\n          isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));\n      }\n\n      #define isnan(value) isnan_custom(value)\n    `;\n    defineSpecialInf = ``;\n    defineRound = `\n      #define round(value) newRound(value)\n      int newRound(float value) {\n        return int(floor(value + 0.5));\n      }\n\n      ivec4 newRound(vec4 value) {\n        return ivec4(floor(value + vec4(0.5)));\n      }\n    `;\n  } else {\n    version9 = \"\";\n    attribute = \"attribute\";\n    varyingVs = \"varying\";\n    varyingFs = \"varying\";\n    texture2D = \"texture2D\";\n    output = \"gl_FragColor\";\n    defineOutput = \"\";\n    defineSpecialNaN = `\n      #define isnan(value) isnan_custom(value)\n      bool isnan_custom(float val) {\n        return (val > 0. || val < 1. || val == 0.) ? false : true;\n      }\n      bvec4 isnan_custom(vec4 val) {\n        return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));\n      }\n    `;\n    defineSpecialInf = `\n      uniform float INFINITY;\n\n      bool isinf(float val) {\n        return abs(val) == INFINITY;\n      }\n      bvec4 isinf(vec4 val) {\n        return equal(abs(val), vec4(INFINITY));\n      }\n    `;\n    defineRound = `\n      int round(float value) {\n        return int(floor(value + 0.5));\n      }\n\n      ivec4 round(vec4 value) {\n        return ivec4(floor(value + vec4(0.5)));\n      }\n    `;\n  }\n  return {\n    version: version9,\n    attribute,\n    varyingVs,\n    varyingFs,\n    texture2D,\n    output,\n    defineOutput,\n    defineSpecialNaN,\n    defineSpecialInf,\n    defineRound\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/shader_compiler_util.js\nfunction getLogicalCoordinatesFromFlatIndex(coords3, shape, index = \"index\") {\n  const strides = util_exports.computeStrides(shape);\n  return strides.map((stride, i2) => {\n    const line1 = `int ${coords3[i2]} = ${index} / ${stride}`;\n    const line2 = i2 === strides.length - 1 ? `int ${coords3[i2 + 1]} = ${index} - ${coords3[i2]} * ${stride}` : `index -= ${coords3[i2]} * ${stride}`;\n    return `${line1}; ${line2};`;\n  }).join(\"\");\n}\nfunction getOutputLogicalCoordinatesFromFlatIndexByUniform(coords3, shape, index = \"index\") {\n  const strides = util_exports.computeStrides(shape);\n  return strides.map((_, i2) => {\n    const line1 = `int ${coords3[i2]} = ${index} / outShapeStrides[${i2}]`;\n    const line2 = i2 === strides.length - 1 ? `int ${coords3[i2 + 1]} = ${index} - ${coords3[i2]} * outShapeStrides[${i2}]` : `index -= ${coords3[i2]} * outShapeStrides[${i2}]`;\n    return `${line1}; ${line2};`;\n  }).join(\"\");\n}\nfunction symbolicallyComputeStrides(indicesArr, variableName) {\n  const numCoords = indicesArr.length;\n  const shape = indicesArr.map((d) => `${variableName}[${d}]`);\n  const strides = new Array(numCoords - 1);\n  strides[numCoords - 2] = shape[numCoords - 1];\n  for (let i2 = numCoords - 3; i2 >= 0; --i2) {\n    strides[i2] = `(${strides[i2 + 1]} * ${shape[i2 + 1]})`;\n  }\n  return strides;\n}\nfunction getLogicalCoordinatesFromFlatIndexByUniform(coords3, variableName, index = \"index\") {\n  const indicesArray = coords3.map((_, i2) => i2);\n  const strides = symbolicallyComputeStrides(indicesArray, variableName);\n  return strides.map((_, i2) => {\n    const line1 = `int ${coords3[i2]} = ${index} / ${strides[i2]}`;\n    const line2 = i2 === strides.length - 1 ? `int ${coords3[i2 + 1]} = ${index} - ${coords3[i2]} * ${strides[i2]}` : `index -= ${coords3[i2]} * ${strides[i2]}`;\n    return `${line1}; ${line2};`;\n  }).join(\"\");\n}\nfunction getFlatIndexFrom3D(shape) {\n  const strides = util_exports.computeStrides(shape).map((d) => d.toString());\n  return `\n  int getFlatIndex(ivec3 coords) {\n    return coords.x * ${strides[0]} + coords.y * ${strides[1]} + coords.z;\n  }\n`;\n}\nfunction getFlatIndexFrom3DOutput() {\n  return `\n  int getFlatIndex(ivec3 coords) {\n    return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;\n  }\n`;\n}\nvar ENCODE_FLOAT_SNIPPET = `\n  const float FLOAT_MAX = 1.70141184e38;\n  const float FLOAT_MIN = 1.17549435e-38;\n\n  lowp vec4 encode_float(highp float v) {\n    if (isnan(v)) {\n      return vec4(255, 255, 255, 255);\n    }\n\n    highp float av = abs(v);\n\n    if(av < FLOAT_MIN) {\n      return vec4(0.0, 0.0, 0.0, 0.0);\n    } else if(v > FLOAT_MAX) {\n      return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;\n    } else if(v < -FLOAT_MAX) {\n      return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;\n    }\n\n    highp vec4 c = vec4(0,0,0,0);\n\n    highp float e = floor(log2(av));\n    highp float m = exp2(fract(log2(av))) - 1.0;\n\n    c[2] = floor(128.0 * m);\n    m -= c[2] / 128.0;\n    c[1] = floor(32768.0 * m);\n    m -= c[1] / 32768.0;\n    c[0] = floor(8388608.0 * m);\n\n    highp float ebias = e + 127.0;\n    c[3] = floor(ebias / 2.0);\n    ebias -= c[3] * 2.0;\n    c[2] += floor(ebias) * 128.0;\n\n    c[3] += 128.0 * step(0.0, -v);\n\n    return c / 255.0;\n  }\n`;\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/shader_compiler.js\nvar { getBroadcastDims: getBroadcastDims2 } = backend_util_exports;\nfunction makeShader(inputsInfo, outputShape, program) {\n  const prefixSnippets = [];\n  inputsInfo.forEach((x) => {\n    const size = util_exports.sizeFromShape(x.shapeInfo.logicalShape);\n    if (x.shapeInfo.isUniform) {\n      prefixSnippets.push(`uniform float ${x.name}${size > 1 ? `[${size}]` : \"\"};`);\n    } else {\n      prefixSnippets.push(`uniform sampler2D ${x.name};`);\n      prefixSnippets.push(`uniform int offset${x.name};`);\n    }\n    if (program.enableShapeUniforms) {\n      const { uniformShape } = getUniformInfoFromShape(program.packedInputs, x.shapeInfo.logicalShape, x.shapeInfo.texShape);\n      switch (uniformShape.length) {\n        case 1:\n          prefixSnippets.push(`uniform int ${x.name}Shape;`);\n          break;\n        case 2:\n          prefixSnippets.push(`uniform ivec2 ${x.name}Shape;`);\n          break;\n        case 3:\n          prefixSnippets.push(`uniform ivec3 ${x.name}Shape;`);\n          break;\n        case 4:\n          prefixSnippets.push(`uniform ivec4 ${x.name}Shape;`);\n          break;\n        default:\n          break;\n      }\n      prefixSnippets.push(`uniform ivec2 ${x.name}TexShape;`);\n    }\n  });\n  if (program.enableShapeUniforms) {\n    switch (outputShape.logicalShape.length) {\n      case 1:\n        prefixSnippets.push(`uniform int outShape;`);\n        break;\n      case 2:\n        prefixSnippets.push(`uniform ivec2 outShape;`);\n        prefixSnippets.push(`uniform int outShapeStrides;`);\n        break;\n      case 3:\n        prefixSnippets.push(`uniform ivec3 outShape;`);\n        prefixSnippets.push(`uniform ivec2 outShapeStrides;`);\n        break;\n      case 4:\n        prefixSnippets.push(`uniform ivec4 outShape;`);\n        prefixSnippets.push(`uniform ivec3 outShapeStrides;`);\n        break;\n      default:\n        break;\n    }\n    prefixSnippets.push(`uniform ivec2 outTexShape;`);\n  }\n  if (program.customUniforms) {\n    program.customUniforms.forEach((d) => {\n      prefixSnippets.push(`uniform ${d.type} ${d.name}${d.arrayIndex ? `[${d.arrayIndex}]` : \"\"};`);\n    });\n  }\n  const inputPrefixSnippet = prefixSnippets.join(\"\\n\");\n  const inputSamplingSnippet = inputsInfo.map((x) => getInputSamplingSnippet(x, outputShape, program.packedInputs, program.enableShapeUniforms)).join(\"\\n\");\n  const outTexShape = outputShape.texShape;\n  const glsl = getGlslDifferences();\n  const floatTextureSampleSnippet = getFloatTextureSampleSnippet(glsl);\n  let outputSamplingSnippet;\n  let floatTextureSetOutputSnippet;\n  let shaderPrefix = getShaderPrefix(glsl);\n  if (outputShape.isPacked) {\n    outputSamplingSnippet = getPackedOutputSamplingSnippet(outputShape.logicalShape, outTexShape, program.enableShapeUniforms);\n    floatTextureSetOutputSnippet = getFloatTextureSetRGBASnippet(glsl);\n  } else {\n    outputSamplingSnippet = getOutputSamplingSnippet(outputShape.logicalShape, outTexShape, program.enableShapeUniforms);\n    floatTextureSetOutputSnippet = getFloatTextureSetRSnippet(glsl);\n  }\n  if (program.packedInputs) {\n    shaderPrefix += SHADER_PACKED_PREFIX;\n  }\n  const source = [\n    shaderPrefix,\n    floatTextureSampleSnippet,\n    floatTextureSetOutputSnippet,\n    inputPrefixSnippet,\n    outputSamplingSnippet,\n    inputSamplingSnippet,\n    program.userCode\n  ].join(\"\\n\");\n  return source;\n}\nfunction getSamplerFromInInfo(inInfo, enableShapeUniforms = false) {\n  const shape = inInfo.shapeInfo.logicalShape;\n  switch (shape.length) {\n    case 0:\n      return getSamplerScalar(inInfo, enableShapeUniforms);\n    case 1:\n      return getSampler1D(inInfo, enableShapeUniforms);\n    case 2:\n      return getSampler2D(inInfo, enableShapeUniforms);\n    case 3:\n      return getSampler3D(inInfo, enableShapeUniforms);\n    case 4:\n      return getSampler4D(inInfo, enableShapeUniforms);\n    case 5:\n      return getSampler5D(inInfo);\n    case 6:\n      return getSampler6D(inInfo);\n    default:\n      throw new Error(`${shape.length}-D input sampling is not yet supported`);\n  }\n}\nfunction getPackedSamplerFromInInfo(inInfo, enableShapeUniforms) {\n  const shape = inInfo.shapeInfo.logicalShape;\n  switch (shape.length) {\n    case 0:\n      return getPackedSamplerScalar(inInfo);\n    case 1:\n      return getPackedSampler1D(inInfo, enableShapeUniforms);\n    case 2:\n      return getPackedSampler2D(inInfo, enableShapeUniforms);\n    case 3:\n      return getPackedSampler3D(inInfo, enableShapeUniforms);\n    default:\n      return getPackedSamplerND(inInfo, enableShapeUniforms);\n  }\n}\nfunction getInputSamplingSnippet(inInfo, outShapeInfo, usesPackedTextures = false, enableShapeUniforms) {\n  let res = \"\";\n  if (usesPackedTextures) {\n    res += getPackedSamplerFromInInfo(inInfo, enableShapeUniforms);\n  } else {\n    res += getSamplerFromInInfo(inInfo, enableShapeUniforms);\n  }\n  const inShape = inInfo.shapeInfo.logicalShape;\n  const outShape = outShapeInfo.logicalShape;\n  if (inShape.length <= outShape.length) {\n    if (usesPackedTextures) {\n      res += getPackedSamplerAtOutputCoords(inInfo, outShapeInfo);\n    } else {\n      res += getSamplerAtOutputCoords(inInfo, outShapeInfo);\n    }\n  }\n  return res;\n}\nfunction getPackedOutputSamplingSnippet(outShape, outTexShape, enableShapeUniforms) {\n  switch (outShape.length) {\n    case 0:\n      return getOutputScalarCoords();\n    case 1:\n      return getOutputPacked1DCoords(outShape, outTexShape, enableShapeUniforms);\n    case 2:\n      return getOutputPacked2DCoords(outShape, outTexShape, enableShapeUniforms);\n    case 3:\n      return getOutputPacked3DCoords(outShape, outTexShape, enableShapeUniforms);\n    default:\n      return getOutputPackedNDCoords(outShape, outTexShape, enableShapeUniforms);\n  }\n}\nfunction getOutputSamplingSnippet(outShape, outTexShape, enableShapeUniforms) {\n  switch (outShape.length) {\n    case 0:\n      return getOutputScalarCoords();\n    case 1:\n      return getOutput1DCoords(outShape, outTexShape, enableShapeUniforms);\n    case 2:\n      return getOutput2DCoords(outShape, outTexShape, enableShapeUniforms);\n    case 3:\n      return getOutput3DCoords(outShape, outTexShape, enableShapeUniforms);\n    case 4:\n      return getOutput4DCoords(outShape, outTexShape, enableShapeUniforms);\n    case 5:\n      return getOutput5DCoords(outShape, outTexShape);\n    case 6:\n      return getOutput6DCoords(outShape, outTexShape);\n    default:\n      throw new Error(`${outShape.length}-D output sampling is not yet supported`);\n  }\n}\nfunction getFloatTextureSampleSnippet(glsl) {\n  return `\n    float sampleTexture(sampler2D textureSampler, vec2 uv) {\n      return ${glsl.texture2D}(textureSampler, uv).r;\n    }\n  `;\n}\nfunction getFloatTextureSetRSnippet(glsl) {\n  return `\n    void setOutput(float val) {\n      ${glsl.output} = vec4(val, 0, 0, 0);\n    }\n  `;\n}\nfunction getFloatTextureSetRGBASnippet(glsl) {\n  return `\n    void setOutput(vec4 val) {\n      ${glsl.output} = val;\n    }\n  `;\n}\nfunction getShaderPrefix(glsl) {\n  const SHADER_PREFIX = `${glsl.version}\n    precision highp float;\n    precision highp int;\n    precision highp sampler2D;\n    ${glsl.varyingFs} vec2 resultUV;\n    ${glsl.defineOutput}\n    const vec2 halfCR = vec2(0.5, 0.5);\n\n    struct ivec5\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n    };\n\n    struct ivec6\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n      int v;\n    };\n\n    uniform float NAN;\n    ${glsl.defineSpecialNaN}\n    ${glsl.defineSpecialInf}\n    ${glsl.defineRound}\n\n    int imod(int x, int y) {\n      return x - y * (x / y);\n    }\n\n    int idiv(int a, int b, float sign) {\n      int res = a / b;\n      int mod = imod(a, b);\n      if (sign < 0. && mod != 0) {\n        res -= 1;\n      }\n      return res;\n    }\n\n    //Based on the work of Dave Hoskins\n    //https://www.shadertoy.com/view/4djSRW\n    #define HASHSCALE1 443.8975\n    float random(float seed){\n      vec2 p = resultUV * seed;\n      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);\n      p3 += dot(p3, p3.yzx + 19.19);\n      return fract((p3.x + p3.y) * p3.z);\n    }\n\n    ${SAMPLE_1D_SNIPPET}\n    ${SAMPLE_2D_SNIPPET}\n    ${SAMPLE_3D_SNIPPET}\n  `;\n  return SHADER_PREFIX;\n}\nvar SAMPLE_1D_SNIPPET = `\nvec2 uvFromFlat(int texNumR, int texNumC, int index) {\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\nvec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\n  int texelIndex = index / 2;\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n`;\nvar SAMPLE_2D_SNIPPET = `\nvec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,\n  int texNumC, int row, int col) {\n  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n`;\nvar SAMPLE_3D_SNIPPET = `\nvec2 packedUVfrom3D(int texNumR, int texNumC,\n    int texelsInBatch, int texelsInLogicalRow, int b,\n    int row, int col) {\n  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n`;\nvar SHADER_PACKED_PREFIX = `\n  float getChannel(vec4 frag, vec2 innerDims) {\n    vec2 modCoord = mod(innerDims, 2.);\n    return modCoord.x == 0. ?\n      (modCoord.y == 0. ? frag.r : frag.g) :\n      (modCoord.y == 0. ? frag.b : frag.a);\n  }\n  float getChannel(vec4 frag, int dim) {\n    float modCoord = mod(float(dim), 2.);\n    return modCoord == 0. ? frag.r : frag.g;\n  }\n`;\nfunction getOutputScalarCoords() {\n  return `\n    int getOutputCoords() {\n      return 0;\n    }\n  `;\n}\nfunction getOutputPacked1DCoords(shape, texShape, enableShapeUniforms) {\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  if (packedTexShape[0] === 1) {\n    if (enableShapeUniforms) {\n      return `\n      int getOutputCoords() {\n        return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));\n      }\n    `;\n    }\n    return `\n      int getOutputCoords() {\n        return 2 * int(resultUV.x * ${packedTexShape[1]}.0);\n      }\n    `;\n  }\n  if (packedTexShape[1] === 1) {\n    if (enableShapeUniforms) {\n      return `\n      int getOutputCoords() {\n        return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));\n      }\n    `;\n    }\n    return `\n      int getOutputCoords() {\n        return 2 * int(resultUV.y * ${packedTexShape[0]}.0);\n      }\n    `;\n  }\n  if (enableShapeUniforms) {\n    return `\n    int getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n      return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);\n    }\n  `;\n  }\n  return `\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));\n      return 2 * (resTexRC.x * ${packedTexShape[1]} + resTexRC.y);\n    }\n  `;\n}\nfunction getOutput1DCoords(shape, texShape, enableShapeUniforms) {\n  if (texShape[0] === 1) {\n    if (enableShapeUniforms) {\n      return `\n      int getOutputCoords() {\n        return int(resultUV.x * float(outTexShape[1]));\n      }\n    `;\n    }\n    return `\n      int getOutputCoords() {\n        return int(resultUV.x * ${texShape[1]}.0);\n      }\n    `;\n  }\n  if (texShape[1] === 1) {\n    if (enableShapeUniforms) {\n      return `\n      int getOutputCoords() {\n        return int(resultUV.y * float(outTexShape[0]));\n      }\n    `;\n    }\n    return `\n      int getOutputCoords() {\n        return int(resultUV.y * ${texShape[0]}.0);\n      }\n    `;\n  }\n  if (enableShapeUniforms) {\n    return `\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(outTexShape[0], outTexShape[1]));\n      return resTexRC.x * outTexShape[1] + resTexRC.y;\n    }\n  `;\n  }\n  return `\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${texShape[0]}, ${texShape[1]}));\n      return resTexRC.x * ${texShape[1]} + resTexRC.y;\n    }\n  `;\n}\nfunction getOutputPacked3DCoords(shape, texShape, enableShapeUniforms) {\n  if (enableShapeUniforms) {\n    return `\n    ivec3 getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));\n      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n\n      int b = index / texelsInBatch;\n      index -= b * texelsInBatch;\n\n      int r = 2 * (index / texelsInLogicalRow);\n      int c = imod(index, texelsInLogicalRow) * 2;\n\n      return ivec3(b, r, c);\n    }\n  `;\n  }\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  const texelsInLogicalRow = Math.ceil(shape[2] / 2);\n  const texelsInBatch = texelsInLogicalRow * Math.ceil(shape[1] / 2);\n  return `\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));\n      int index = resTexRC.x * ${packedTexShape[1]} + resTexRC.y;\n\n      int b = index / ${texelsInBatch};\n      index -= b * ${texelsInBatch};\n\n      int r = 2 * (index / ${texelsInLogicalRow});\n      int c = imod(index, ${texelsInLogicalRow}) * 2;\n\n      return ivec3(b, r, c);\n    }\n  `;\n}\nfunction getOutput3DCoords(shape, texShape, enableShapeUniforms) {\n  if (enableShapeUniforms) {\n    const coordsFromIndexSnippet2 = getOutputLogicalCoordinatesFromFlatIndexByUniform([\"r\", \"c\", \"d\"], shape);\n    return `\n  ivec3 getOutputCoords() {\n    ivec2 resTexRC = ivec2(resultUV.yx *\n                           vec2(outTexShape[0], outTexShape[1]));\n    int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n    ${coordsFromIndexSnippet2}\n    return ivec3(r, c, d);\n  }\n`;\n  }\n  const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex([\"r\", \"c\", \"d\"], shape);\n  return `\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${texShape[0]}, ${texShape[1]}));\n      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;\n      ${coordsFromIndexSnippet}\n      return ivec3(r, c, d);\n    }\n  `;\n}\nfunction getOutputPackedNDCoords(shape, texShape, enableShapeUniforms) {\n  if (enableShapeUniforms) {\n    return `\n    ivec4 getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n\n      int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));\n      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));\n      int texelsInBatchN = texelsInBatch * outShape[1];\n\n      int b2 = index / texelsInBatchN;\n      index -= b2 * texelsInBatchN;\n\n      int b = index / texelsInBatch;\n      index -= b * texelsInBatch;\n\n      int r = 2 * (index / texelsInLogicalRow);\n      int c = imod(index, texelsInLogicalRow) * 2;\n\n      return ivec4(b2, b, r, c);\n    }\n  `;\n  }\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  const texelsInLogicalRow = Math.ceil(shape[shape.length - 1] / 2);\n  const texelsInBatch = texelsInLogicalRow * Math.ceil(shape[shape.length - 2] / 2);\n  let texelsInBatchN = texelsInBatch;\n  let batches = ``;\n  let coords3 = \"b, r, c\";\n  for (let b = 2; b < shape.length - 1; b++) {\n    texelsInBatchN *= shape[shape.length - b - 1];\n    batches = `\n      int b${b} = index / ${texelsInBatchN};\n      index -= b${b} * ${texelsInBatchN};\n    ` + batches;\n    coords3 = `b${b}, ` + coords3;\n  }\n  return `\n    ivec${shape.length} getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));\n      int index = resTexRC.x * ${packedTexShape[1]} + resTexRC.y;\n\n      ${batches}\n\n      int b = index / ${texelsInBatch};\n      index -= b * ${texelsInBatch};\n\n      int r = 2 * (index / ${texelsInLogicalRow});\n      int c = imod(index, ${texelsInLogicalRow}) * 2;\n\n      return ivec${shape.length}(${coords3});\n    }\n  `;\n}\nfunction getOutput4DCoords(shape, texShape, enableShapeUniforms) {\n  if (enableShapeUniforms) {\n    const coordsFromIndexSnippet2 = getOutputLogicalCoordinatesFromFlatIndexByUniform([\"r\", \"c\", \"d\", \"d2\"], shape);\n    return `\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2(outTexShape[0], outTexShape[1]));\n      int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n      ${coordsFromIndexSnippet2}\n      return ivec4(r, c, d, d2);\n    }\n  `;\n  }\n  const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex([\"r\", \"c\", \"d\", \"d2\"], shape);\n  return `\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2(${texShape[0]}, ${texShape[1]}));\n      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;\n      ${coordsFromIndexSnippet}\n      return ivec4(r, c, d, d2);\n    }\n  `;\n}\nfunction getOutput5DCoords(shape, texShape) {\n  const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex([\"r\", \"c\", \"d\", \"d2\", \"d3\"], shape);\n  return `\n    ivec5 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx * vec2(${texShape[0]},\n                             ${texShape[1]}));\n\n      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;\n\n      ${coordsFromIndexSnippet}\n\n      ivec5 outShape = ivec5(r, c, d, d2, d3);\n      return outShape;\n    }\n  `;\n}\nfunction getOutput6DCoords(shape, texShape) {\n  const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex([\"r\", \"c\", \"d\", \"d2\", \"d3\", \"d4\"], shape);\n  return `\n    ivec6 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2(${texShape[0]}, ${texShape[1]}));\n      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;\n\n      ${coordsFromIndexSnippet}\n\n      ivec6 result = ivec6(r, c, d, d2, d3, d4);\n      return result;\n    }\n  `;\n}\nfunction getOutputPacked2DCoords(shape, texShape, enableShapeUniforms) {\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  if (util_exports.arraysEqual(shape, texShape)) {\n    if (enableShapeUniforms) {\n      return `\n      ivec2 getOutputCoords() {\n        ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n        return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));\n      }\n    `;\n    }\n    return `\n      ivec2 getOutputCoords() {\n        return 2 * ivec2(resultUV.yx * vec2(${packedTexShape[0]}, ${packedTexShape[1]}));\n      }\n    `;\n  }\n  const texelsInLogicalRow = Math.ceil(shape[1] / 2);\n  if (enableShapeUniforms) {\n    return `\n    ivec2 getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n\n      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n      int r = 2 * (index / texelsInLogicalRow);\n      int c = imod(index, texelsInLogicalRow) * 2;\n\n      return ivec2(r, c);\n    }\n  `;\n  }\n  return `\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));\n\n      int index = resTexRC.x * ${packedTexShape[1]} + resTexRC.y;\n      int r = 2 * (index / ${texelsInLogicalRow});\n      int c = imod(index, ${texelsInLogicalRow}) * 2;\n\n      return ivec2(r, c);\n    }\n  `;\n}\nfunction getOutput2DCoords(shape, texShape, enableShapeUniforms) {\n  if (util_exports.arraysEqual(shape, texShape)) {\n    if (enableShapeUniforms) {\n      return `\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));\n      }\n    `;\n    }\n    return `\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2(${texShape[0]}, ${texShape[1]}));\n      }\n    `;\n  }\n  if (shape[1] === 1) {\n    if (enableShapeUniforms) {\n      return `\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(outTexShape[0], outTexShape[1]));\n        int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    `;\n    }\n    return `\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(${texShape[0]}, ${texShape[1]}));\n        int index = resTexRC.x * ${texShape[1]} + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    `;\n  }\n  if (shape[0] === 1) {\n    if (enableShapeUniforms) {\n      return `\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(outTexShape[0], outTexShape[1]));\n        int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n        return ivec2(0, index);\n      }\n    `;\n    }\n    return `\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(${texShape[0]}, ${texShape[1]}));\n        int index = resTexRC.x * ${texShape[1]} + resTexRC.y;\n        return ivec2(0, index);\n      }\n    `;\n  }\n  if (enableShapeUniforms) {\n    return `\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(outTexShape[0], outTexShape[1]));\n      int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n      int r = index / outShape[1];\n      int c = index - r * outShape[1];\n      return ivec2(r, c);\n    }\n  `;\n  }\n  return `\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${texShape[0]}, ${texShape[1]}));\n      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;\n      int r = index / ${shape[1]};\n      int c = index - r * ${shape[1]};\n      return ivec2(r, c);\n    }\n  `;\n}\nfunction getFlatOffsetUniformName(texName) {\n  return `offset${texName}`;\n}\nfunction getPackedSamplerScalar(inputInfo) {\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const glsl = getGlslDifferences();\n  return `\n    vec4 ${funcName}() {\n      return ${glsl.texture2D}(${texName}, halfCR);\n    }\n  `;\n}\nfunction getSamplerScalar(inputInfo, enableShapeUniforms) {\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  if (inputInfo.shapeInfo.isUniform) {\n    return `float ${funcName}() {return ${texName};}`;\n  }\n  const [texNumR, texNumC] = inputInfo.shapeInfo.texShape;\n  if (texNumR === 1 && texNumC === 1) {\n    return `\n      float ${funcName}() {\n        return sampleTexture(${texName}, halfCR);\n      }\n    `;\n  }\n  const offset = getFlatOffsetUniformName(texName);\n  if (enableShapeUniforms) {\n    return `\n    float ${funcName}() {\n      vec2 uv = uvFromFlat(${texName}TexShape[0], ${texName}TexShape[1], ${offset});\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n  }\n  const [tNumR, tNumC] = inputInfo.shapeInfo.texShape;\n  return `\n    float ${funcName}() {\n      vec2 uv = uvFromFlat(${tNumR}, ${tNumC}, ${offset});\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n}\nfunction getPackedSampler1D(inputInfo, enableShapeUniforms) {\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const texShape = inputInfo.shapeInfo.texShape;\n  const glsl = getGlslDifferences();\n  if (enableShapeUniforms) {\n    return `\n    vec4 ${funcName}(int index) {\n      ivec2 packedTexShape = ivec2(ceil(float(${texName}TexShape[0]) / 2.0), ceil(float(${texName}TexShape[1]) / 2.0));\n      vec2 uv = packedUVfrom1D(\n        packedTexShape[0], packedTexShape[1], index);\n      return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n  }\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  return `\n    vec4 ${funcName}(int index) {\n      vec2 uv = packedUVfrom1D(\n        ${packedTexShape[0]}, ${packedTexShape[1]}, index);\n      return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n}\nfunction getSampler1D(inputInfo, enableShapeUniforms) {\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  if (inputInfo.shapeInfo.isUniform) {\n    return `\n      float ${funcName}(int index) {\n        ${getUniformSampler(inputInfo)}\n      }\n    `;\n  }\n  const texShape = inputInfo.shapeInfo.texShape;\n  const tNumR = texShape[0];\n  const tNumC = texShape[1];\n  if (tNumC === 1 && tNumR === 1) {\n    return `\n      float ${funcName}(int index) {\n        return sampleTexture(${texName}, halfCR);\n      }\n    `;\n  }\n  const offset = getFlatOffsetUniformName(texName);\n  if (tNumC === 1) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int index) {\n        vec2 uv = vec2(0.5, (float(index + ${offset}) + 0.5) / float(${texName}TexShape[0]));\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n      float ${funcName}(int index) {\n        vec2 uv = vec2(0.5, (float(index + ${offset}) + 0.5) / ${tNumR}.0);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  if (tNumR === 1) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int index) {\n        vec2 uv = vec2((float(index + ${offset}) + 0.5) / float(${texName}TexShape[1]), 0.5);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n      float ${funcName}(int index) {\n        vec2 uv = vec2((float(index + ${offset}) + 0.5) / ${tNumC}.0, 0.5);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  if (enableShapeUniforms) {\n    return `\n    float ${funcName}(int index) {\n      vec2 uv = uvFromFlat(${texName}TexShape[0], ${texName}TexShape[1], index + ${offset});\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n  }\n  return `\n    float ${funcName}(int index) {\n      vec2 uv = uvFromFlat(${tNumR}, ${tNumC}, index + ${offset});\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n}\nfunction getPackedSampler2D(inputInfo, enableShapeUniforms) {\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const texShape = inputInfo.shapeInfo.texShape;\n  const texNumR = texShape[0];\n  const texNumC = texShape[1];\n  const glsl = getGlslDifferences();\n  if (texShape != null && util_exports.arraysEqual(shape, texShape)) {\n    if (enableShapeUniforms) {\n      return `\n      vec4 ${funcName}(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(${texName}TexShape[1], ${texName}TexShape[0]);\n\n        return ${glsl.texture2D}(${texName}, uv);\n      }\n    `;\n    }\n    return `\n      vec4 ${funcName}(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(${texNumC}.0, ${texNumR}.0);\n\n        return ${glsl.texture2D}(${texName}, uv);\n      }\n    `;\n  }\n  if (enableShapeUniforms) {\n    return `\n    vec4 ${funcName}(int row, int col) {\n      ivec2 packedTexShape = ivec2(ceil(float(${texName}TexShape[0]) / 2.0), ceil(float(${texName}TexShape[1]) / 2.0));\n      int valuesPerRow = int(ceil(float(${texName}Shape[1]) / 2.0));\n      vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);\n      return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n  }\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  const valuesPerRow = Math.ceil(shape[1] / 2);\n  return `\n    vec4 ${funcName}(int row, int col) {\n      vec2 uv = packedUVfrom2D(${valuesPerRow}, ${packedTexShape[0]}, ${packedTexShape[1]}, row, col);\n      return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n}\nfunction getSampler2D(inputInfo, enableShapeUniforms) {\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const texShape = inputInfo.shapeInfo.texShape;\n  if (texShape != null && util_exports.arraysEqual(shape, texShape)) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(${texName}TexShape[1], ${texName}TexShape[0]);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    const texNumR2 = texShape[0];\n    const texNumC2 = texShape[1];\n    return `\n    float ${funcName}(int row, int col) {\n      vec2 uv = (vec2(col, row) + halfCR) / vec2(${texNumC2}.0, ${texNumR2}.0);\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n  }\n  const { newShape, keptDims } = util_exports.squeezeShape(shape);\n  const squeezedShape = newShape;\n  if (squeezedShape.length < shape.length) {\n    const newInputInfo = squeezeInputInfo(inputInfo, squeezedShape);\n    const params = [\"row\", \"col\"];\n    return `\n      ${getSamplerFromInInfo(newInputInfo, enableShapeUniforms)}\n      float ${funcName}(int row, int col) {\n        return ${funcName}(${getSqueezedParams(params, keptDims)});\n      }\n    `;\n  }\n  if (inputInfo.shapeInfo.isUniform) {\n    return `\n      float ${funcName}(int row, int col) {\n        int index = round(dot(vec2(row, col), vec2(${shape[1]}, 1)));\n        ${getUniformSampler(inputInfo)}\n      }\n    `;\n  }\n  const texNumR = texShape[0];\n  const texNumC = texShape[1];\n  const offset = getFlatOffsetUniformName(texName);\n  if (texNumC === 1) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int row, int col) {\n        float index = dot(vec3(row, col, ${offset}), vec3(${texName}Shape[1], 1, 1));\n        vec2 uv = vec2(0.5, (index + 0.5) / float(${texName}TexShape[0]));\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n    float ${funcName}(int row, int col) {\n      float index = dot(vec3(row, col, ${offset}), vec3(${shape[1]}, 1, 1));\n      vec2 uv = vec2(0.5, (index + 0.5) / ${texNumR}.0);\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n  }\n  if (texNumR === 1) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int row, int col) {\n        float index = dot(vec3(row, col, ${offset}), vec3(${texName}Shape[1], 1, 1));\n        vec2 uv = vec2((index + 0.5) / float(${texName}TexShape[1]), 0.5);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n    float ${funcName}(int row, int col) {\n      float index = dot(vec3(row, col, ${offset}), vec3(${shape[1]}, 1, 1));\n      vec2 uv = vec2((index + 0.5) / ${texNumC}.0, 0.5);\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n  }\n  if (enableShapeUniforms) {\n    return `\n      float ${funcName}(int row, int col) {\n        // Explicitly use integer operations as dot() only works on floats.\n        int index = row * ${texName}Shape[1] + col + ${offset};\n        vec2 uv = uvFromFlat(${texName}TexShape[0], ${texName}TexShape[1], index);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  return `\n  float ${funcName}(int row, int col) {\n    // Explicitly use integer operations as dot() only works on floats.\n    int index = row * ${shape[1]} + col + ${offset};\n    vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);\n    return sampleTexture(${texName}, uv);\n  }\n`;\n}\nfunction getPackedSampler3D(inputInfo, enableShapeUniforms) {\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const texShape = inputInfo.shapeInfo.texShape;\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  if (shape[0] === 1) {\n    const squeezedShape = shape.slice(1);\n    const keptDims = [1, 2];\n    const newInputInfo = squeezeInputInfo(inputInfo, squeezedShape);\n    const params = [\"b\", \"row\", \"col\"];\n    return `\n        ${getPackedSamplerFromInInfo(newInputInfo, enableShapeUniforms)}\n        vec4 ${funcName}(int b, int row, int col) {\n          return ${funcName}(${getSqueezedParams(params, keptDims)});\n        }\n      `;\n  }\n  const glsl = getGlslDifferences();\n  if (enableShapeUniforms) {\n    return `\n    vec4 ${funcName}(int b, int row, int col) {\n      ivec2 packedTexShape = ivec2(ceil(float(${texName}TexShape[0]) / 2.0), ceil(float(${texName}TexShape[1]) / 2.0));\n      int valuesPerRow = int(ceil(float(${texName}Shape[2]) / 2.0));\n      int texelsInBatch = valuesPerRow * int(ceil(float(${texName}Shape[1]) / 2.0));\n      vec2 uv = packedUVfrom3D(\n        packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);\n      return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n  }\n  const texNumR = packedTexShape[0];\n  const texNumC = packedTexShape[1];\n  const valuesPerRow = Math.ceil(shape[2] / 2);\n  const texelsInBatch = valuesPerRow * Math.ceil(shape[1] / 2);\n  return `\n    vec4 ${funcName}(int b, int row, int col) {\n      vec2 uv = packedUVfrom3D(\n        ${texNumR}, ${texNumC}, ${texelsInBatch}, ${valuesPerRow}, b, row, col);\n      return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n}\nfunction getSampler3D(inputInfo, enableShapeUniforms) {\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const stride0 = shape[1] * shape[2];\n  const stride1 = shape[2];\n  const { newShape, keptDims } = util_exports.squeezeShape(shape);\n  const squeezedShape = newShape;\n  if (squeezedShape.length < shape.length) {\n    const newInputInfo = squeezeInputInfo(inputInfo, squeezedShape);\n    const params = [\"row\", \"col\", \"depth\"];\n    return `\n        ${getSamplerFromInInfo(newInputInfo, enableShapeUniforms)}\n        float ${funcName}(int row, int col, int depth) {\n          return ${funcName}(${getSqueezedParams(params, keptDims)});\n        }\n      `;\n  }\n  if (inputInfo.shapeInfo.isUniform) {\n    return `\n      float ${funcName}(int row, int col, int depth) {\n        int index = round(dot(vec3(row, col, depth),\n                          vec3(${stride0}, ${stride1}, 1)));\n        ${getUniformSampler(inputInfo)}\n      }\n    `;\n  }\n  const texShape = inputInfo.shapeInfo.texShape;\n  const texNumR = texShape[0];\n  const texNumC = texShape[1];\n  const flatOffset = inputInfo.shapeInfo.flatOffset;\n  if (texNumC === stride0 && flatOffset == null) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int row, int col, int depth) {\n        int stride1 = ${texName}Shape[2];\n        float texR = float(row);\n        float texC = dot(vec2(col, depth), vec2(stride1, 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${texName}TexShape[1], ${texName}TexShape[0]);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n        float ${funcName}(int row, int col, int depth) {\n          float texR = float(row);\n          float texC = dot(vec2(col, depth), vec2(${stride1}, 1));\n          vec2 uv = (vec2(texC, texR) + halfCR) /\n                     vec2(${texNumC}.0, ${texNumR}.0);\n          return sampleTexture(${texName}, uv);\n        }\n      `;\n  }\n  if (texNumC === stride1 && flatOffset == null) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int row, int col, int depth) {\n        float texR = dot(vec2(row, col), vec2(${texName}Shape[1], 1));\n        float texC = float(depth);\n        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${texName}TexShape[1], ${texName}TexShape[0]);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n    float ${funcName}(int row, int col, int depth) {\n      float texR = dot(vec2(row, col), vec2(${shape[1]}, 1));\n      float texC = float(depth);\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${texNumC}.0, ${texNumR}.0);\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n  }\n  const offset = getFlatOffsetUniformName(texName);\n  if (enableShapeUniforms) {\n    return `\n    float ${funcName}(int row, int col, int depth) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int stride0 = ${texName}Shape[1] * ${texName}Shape[2];\n      int stride1 = ${texName}Shape[2];\n      int index = row * ${stride0} + col * ${stride1} + depth + ${offset};\n      vec2 uv = uvFromFlat(${texName}TexShape[0], ${texName}TexShape[1], index);\n      return sampleTexture(${texName}, uv);\n    }\n    `;\n  }\n  return `\n      float ${funcName}(int row, int col, int depth) {\n        // Explicitly use integer operations as dot() only works on floats.\n        int index = row * ${stride0} + col * ${stride1} + depth + ${offset};\n        vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);\n        return sampleTexture(${texName}, uv);\n      }\n  `;\n}\nfunction getPackedSamplerND(inputInfo, enableShapeUniforms) {\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const glsl = getGlslDifferences();\n  if (enableShapeUniforms) {\n    return `\n    vec4 ${funcName}(int b2, int b, int row, int col) {\n      int valuesPerRow = int(ceil(float(${texName}Shape[3]) / 2.0));\n      int texelsInBatch = valuesPerRow * int(ceil(float(${texName}Shape[2]) / 2.0));\n      int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);\n      texelsInBatch *= ${texName}Shape[1];\n      index = b2 * texelsInBatch + index;\n      ivec2 packedTexShape = ivec2(ceil(float(${texName}TexShape[0]) / 2.0), ceil(float(${texName}TexShape[1]) / 2.0));\n      int texR = index / packedTexShape[1];\n      int texC = index - texR * packedTexShape[1];\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(packedTexShape[1], packedTexShape[0]); return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n  }\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const rank = shape.length;\n  const texShape = inputInfo.shapeInfo.texShape;\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  const texNumR = packedTexShape[0];\n  const texNumC = packedTexShape[1];\n  const valuesPerRow = Math.ceil(shape[rank - 1] / 2);\n  let texelsInBatch = valuesPerRow * Math.ceil(shape[rank - 2] / 2);\n  let params = `int b, int row, int col`;\n  let index = `b * ${texelsInBatch} + (row / 2) * ${valuesPerRow} + (col / 2)`;\n  for (let b = 2; b < rank - 1; b++) {\n    params = `int b${b}, ` + params;\n    texelsInBatch *= shape[rank - b - 1];\n    index = `b${b} * ${texelsInBatch} + ` + index;\n  }\n  return `\n    vec4 ${funcName}(${params}) {\n      int index = ${index};\n      int texR = index / ${texNumC};\n      int texC = index - texR * ${texNumC};\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${texNumC}, ${texNumR});\n      return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n}\nfunction getSampler4D(inputInfo, enableShapeUniforms) {\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const stride2 = shape[3];\n  const stride1 = shape[2] * stride2;\n  const stride0 = shape[1] * stride1;\n  const { newShape, keptDims } = util_exports.squeezeShape(shape);\n  if (newShape.length < shape.length) {\n    const newInputInfo = squeezeInputInfo(inputInfo, newShape);\n    const params = [\"row\", \"col\", \"depth\", \"depth2\"];\n    return `\n      ${getSamplerFromInInfo(newInputInfo, enableShapeUniforms)}\n      float ${funcName}(int row, int col, int depth, int depth2) {\n        return ${funcName}(${getSqueezedParams(params, keptDims)});\n      }\n    `;\n  }\n  if (inputInfo.shapeInfo.isUniform) {\n    return `\n      float ${funcName}(int row, int col, int depth, int depth2) {\n        int index = round(dot(vec4(row, col, depth, depth2),\n                          vec4(${stride0}, ${stride1}, ${stride2}, 1)));\n        ${getUniformSampler(inputInfo)}\n      }\n    `;\n  }\n  const flatOffset = inputInfo.shapeInfo.flatOffset;\n  const texShape = inputInfo.shapeInfo.texShape;\n  const texNumR = texShape[0];\n  const texNumC = texShape[1];\n  const stride2Str = `int stride2 = ${texName}Shape[3];`;\n  const stride1Str = `int stride1 = ${texName}Shape[2] * stride2;`;\n  const stride0Str = `int stride0 = ${texName}Shape[1] * stride1;`;\n  if (texNumC === stride0 && flatOffset == null) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int row, int col, int depth, int depth2) {\n        ${stride2Str}\n        ${stride1Str}\n        float texR = float(row);\n        float texC =\n            dot(vec3(col, depth, depth2),\n                vec3(stride1, stride2, 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${texName}TexShape[1], ${texName}TexShape[0]);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n      float ${funcName}(int row, int col, int depth, int depth2) {\n        float texR = float(row);\n        float texC =\n            dot(vec3(col, depth, depth2),\n                vec3(${stride1}, ${stride2}, 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${texNumC}.0, ${texNumR}.0);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  if (texNumC === stride2 && flatOffset == null) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int row, int col, int depth, int depth2) {\n        float texR = dot(vec3(row, col, depth),\n                         vec3(${texName}Shape[1] * ${texName}Shape[2], ${texName}Shape[2], 1));\n        float texC = float(depth2);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(${texName}TexShape[1], ${texName}TexShape[0]);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n      float ${funcName}(int row, int col, int depth, int depth2) {\n        float texR = dot(vec3(row, col, depth),\n                         vec3(${shape[1] * shape[2]}, ${shape[2]}, 1));\n        float texC = float(depth2);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(${texNumC}.0, ${texNumR}.0);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  const offset = getFlatOffsetUniformName(texName);\n  if (enableShapeUniforms) {\n    return `\n    float ${funcName}(int row, int col, int depth, int depth2) {\n      // Explicitly use integer operations as dot() only works on floats.\n      ${stride2Str}\n      ${stride1Str}\n      ${stride0Str}\n      int index = row * stride0 + col * stride1 +\n          depth * stride2 + depth2;\n      vec2 uv = uvFromFlat(${texName}TexShape[0], ${texName}TexShape[1], index + ${offset});\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n  }\n  return `\n    float ${funcName}(int row, int col, int depth, int depth2) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * ${stride0} + col * ${stride1} +\n          depth * ${stride2} + depth2;\n      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index + ${offset});\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n}\nfunction getSampler5D(inputInfo) {\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const stride3 = shape[4];\n  const stride2 = shape[3] * stride3;\n  const stride1 = shape[2] * stride2;\n  const stride0 = shape[1] * stride1;\n  const { newShape, keptDims } = util_exports.squeezeShape(shape);\n  if (newShape.length < shape.length) {\n    const newInputInfo = squeezeInputInfo(inputInfo, newShape);\n    const params = [\"row\", \"col\", \"depth\", \"depth2\", \"depth3\"];\n    return `\n      ${getSamplerFromInInfo(newInputInfo)}\n      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {\n        return ${funcName}(${getSqueezedParams(params, keptDims)});\n      }\n    `;\n  }\n  if (inputInfo.shapeInfo.isUniform) {\n    return `\n      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {\n        float index = dot(\n          vec4(row, col, depth, depth2),\n          vec4(${stride0}, ${stride1}, ${stride2}, ${stride3})) +\n          depth3;\n        ${getUniformSampler(inputInfo)}\n      }\n    `;\n  }\n  const flatOffset = inputInfo.shapeInfo.flatOffset;\n  const texShape = inputInfo.shapeInfo.texShape;\n  const texNumR = texShape[0];\n  const texNumC = texShape[1];\n  if (texNumC === stride0 && flatOffset == null) {\n    return `\n      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n                         vec4(${stride1}, ${stride2}, ${stride3}, 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${texNumC}.0, ${texNumR}.0);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  if (texNumC === stride3 && flatOffset == null) {\n    return `\n      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {\n        float texR = dot(\n          vec4(row, col, depth, depth2),\n          vec4(${shape[1] * shape[2] * shape[3]},\n               ${shape[2] * shape[3]}, ${shape[3]}, 1));\n        int texC = depth3;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(${texNumC}.0, ${texNumR}.0);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  const offset = getFlatOffsetUniformName(texName);\n  return `\n    float ${funcName}(int row, int col, int depth, int depth2, int depth3) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * ${stride0} + col * ${stride1} + depth * ${stride2} +\n          depth2 * ${stride3} + depth3 + ${offset};\n      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n}\nfunction getSampler6D(inputInfo) {\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const { newShape, keptDims } = util_exports.squeezeShape(shape);\n  if (newShape.length < shape.length) {\n    const newInputInfo = squeezeInputInfo(inputInfo, newShape);\n    const params = [\"row\", \"col\", \"depth\", \"depth2\", \"depth3\", \"depth4\"];\n    return `\n      ${getSamplerFromInInfo(newInputInfo)}\n      float ${funcName}(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        return ${funcName}(${getSqueezedParams(params, keptDims)});\n      }\n    `;\n  }\n  const stride4 = shape[5];\n  const stride3 = shape[4] * stride4;\n  const stride2 = shape[3] * stride3;\n  const stride1 = shape[2] * stride2;\n  const stride0 = shape[1] * stride1;\n  if (inputInfo.shapeInfo.isUniform) {\n    return `\n      float ${funcName}(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n        int index = round(dot(\n          vec4(row, col, depth, depth2),\n          vec4(${stride0}, ${stride1}, ${stride2}, ${stride3})) +\n          dot(\n            vec2(depth3, depth4),\n            vec2(${stride4}, 1)));\n        ${getUniformSampler(inputInfo)}\n      }\n    `;\n  }\n  const flatOffset = inputInfo.shapeInfo.flatOffset;\n  const texShape = inputInfo.shapeInfo.texShape;\n  const texNumR = texShape[0];\n  const texNumC = texShape[1];\n  if (texNumC === stride0 && flatOffset == null) {\n    return `\n      float ${funcName}(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n          vec4(${stride1}, ${stride2}, ${stride3}, ${stride4})) +\n               float(depth4);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${texNumC}.0, ${texNumR}.0);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  if (texNumC === stride4 && flatOffset == null) {\n    return `\n      float ${funcName}(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        float texR = dot(vec4(row, col, depth, depth2),\n          vec4(${shape[1] * shape[2] * shape[3] * shape[4]},\n               ${shape[2] * shape[3] * shape[4]},\n               ${shape[3] * shape[4]},\n               ${shape[4]})) + float(depth3);\n        int texC = depth4;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(${texNumC}.0, ${texNumR}.0);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  const offset = getFlatOffsetUniformName(texName);\n  return `\n    float ${funcName}(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * ${stride0} + col * ${stride1} + depth * ${stride2} +\n          depth2 * ${stride3} + depth3 * ${stride4} + depth4 + ${offset};\n      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n}\nfunction getUniformSampler(inputInfo) {\n  const texName = inputInfo.name;\n  const inSize = util_exports.sizeFromShape(inputInfo.shapeInfo.logicalShape);\n  if (inSize < 2) {\n    return `return ${texName};`;\n  }\n  return `\n    for (int i = 0; i < ${inSize}; i++) {\n      if (i == index) {\n        return ${texName}[i];\n      }\n    }\n  `;\n}\nfunction getPackedSamplerAtOutputCoords(inputInfo, outShapeInfo) {\n  const texName = inputInfo.name;\n  const texFuncSnippet = texName.charAt(0).toUpperCase() + texName.slice(1);\n  const funcName = \"get\" + texFuncSnippet + \"AtOutCoords\";\n  const inRank = inputInfo.shapeInfo.logicalShape.length;\n  const outRank = outShapeInfo.logicalShape.length;\n  const broadcastDims = getBroadcastDims2(inputInfo.shapeInfo.logicalShape, outShapeInfo.logicalShape);\n  const type = getCoordsDataType(outRank);\n  const rankDiff = outRank - inRank;\n  let coordsSnippet;\n  const fields = [\"x\", \"y\", \"z\", \"w\", \"u\", \"v\"];\n  if (inRank === 0) {\n    coordsSnippet = \"\";\n  } else if (outRank < 2 && broadcastDims.length >= 1) {\n    coordsSnippet = \"coords = 0;\";\n  } else {\n    coordsSnippet = broadcastDims.map((d) => `coords.${fields[d + rankDiff]} = 0;`).join(\"\\n\");\n  }\n  let unpackedCoordsSnippet = \"\";\n  if (outRank < 2 && inRank > 0) {\n    unpackedCoordsSnippet = \"coords\";\n  } else {\n    unpackedCoordsSnippet = inputInfo.shapeInfo.logicalShape.map((s2, i2) => `coords.${fields[i2 + rankDiff]}`).join(\", \");\n  }\n  let output = `return outputValue;`;\n  const inSize = util_exports.sizeFromShape(inputInfo.shapeInfo.logicalShape);\n  const isInputScalar = inSize === 1;\n  const outSize = util_exports.sizeFromShape(outShapeInfo.logicalShape);\n  const isOutputScalar = outSize === 1;\n  if (inRank === 1 && !isInputScalar && !isOutputScalar) {\n    output = `\n      return vec4(outputValue.xy, outputValue.xy);\n    `;\n  } else if (isInputScalar && !isOutputScalar) {\n    if (outRank === 1) {\n      output = `\n        return vec4(outputValue.x, outputValue.x, 0., 0.);\n      `;\n    } else {\n      output = `\n        return vec4(outputValue.x);\n      `;\n    }\n  } else if (broadcastDims.length) {\n    const rows = inRank - 2;\n    const cols = inRank - 1;\n    if (broadcastDims.indexOf(rows) > -1 && broadcastDims.indexOf(cols) > -1) {\n      output = `return vec4(outputValue.x);`;\n    } else if (broadcastDims.indexOf(rows) > -1) {\n      output = `return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);`;\n    } else if (broadcastDims.indexOf(cols) > -1) {\n      output = `return vec4(outputValue.xx, outputValue.zz);`;\n    }\n  }\n  return `\n    vec4 ${funcName}() {\n      ${type} coords = getOutputCoords();\n      ${coordsSnippet}\n      vec4 outputValue = get${texFuncSnippet}(${unpackedCoordsSnippet});\n      ${output}\n    }\n  `;\n}\nfunction getSamplerAtOutputCoords(inputInfo, outShapeInfo) {\n  const texName = inputInfo.name;\n  const texFuncSnippet = texName.charAt(0).toUpperCase() + texName.slice(1);\n  const funcName = \"get\" + texFuncSnippet + \"AtOutCoords\";\n  const outTexShape = outShapeInfo.texShape;\n  const inTexShape = inputInfo.shapeInfo.texShape;\n  const inRank = inputInfo.shapeInfo.logicalShape.length;\n  const outRank = outShapeInfo.logicalShape.length;\n  if (!inputInfo.shapeInfo.isUniform && inRank === outRank && inputInfo.shapeInfo.flatOffset == null && util_exports.arraysEqual(inTexShape, outTexShape)) {\n    return `\n      float ${funcName}() {\n        return sampleTexture(${texName}, resultUV);\n      }\n    `;\n  }\n  const type = getCoordsDataType(outRank);\n  const broadcastDims = getBroadcastDims2(inputInfo.shapeInfo.logicalShape, outShapeInfo.logicalShape);\n  const rankDiff = outRank - inRank;\n  let coordsSnippet;\n  const fields = [\"x\", \"y\", \"z\", \"w\", \"u\", \"v\"];\n  if (inRank === 0) {\n    coordsSnippet = \"\";\n  } else if (outRank < 2 && broadcastDims.length >= 1) {\n    coordsSnippet = \"coords = 0;\";\n  } else {\n    coordsSnippet = broadcastDims.map((d) => `coords.${fields[d + rankDiff]} = 0;`).join(\"\\n\");\n  }\n  let unpackedCoordsSnippet = \"\";\n  if (outRank < 2 && inRank > 0) {\n    unpackedCoordsSnippet = \"coords\";\n  } else {\n    unpackedCoordsSnippet = inputInfo.shapeInfo.logicalShape.map((s2, i2) => `coords.${fields[i2 + rankDiff]}`).join(\", \");\n  }\n  return `\n    float ${funcName}() {\n      ${type} coords = getOutputCoords();\n      ${coordsSnippet}\n      return get${texFuncSnippet}(${unpackedCoordsSnippet});\n    }\n  `;\n}\nfunction getCoordsDataType(rank) {\n  if (rank <= 1) {\n    return \"int\";\n  } else if (rank === 2) {\n    return \"ivec2\";\n  } else if (rank === 3) {\n    return \"ivec3\";\n  } else if (rank === 4) {\n    return \"ivec4\";\n  } else if (rank === 5) {\n    return \"ivec5\";\n  } else if (rank === 6) {\n    return \"ivec6\";\n  } else {\n    throw Error(`GPU for rank ${rank} is not yet supported`);\n  }\n}\nfunction getUniformInfoFromShape(isPacked, shape, texShape) {\n  const { newShape, keptDims } = util_exports.squeezeShape(shape);\n  const rank = shape.length;\n  const useSqueezePackedShape = isPacked && rank === 3 && shape[0] === 1;\n  const squeezeShape2 = useSqueezePackedShape ? shape.slice(1) : newShape;\n  const useSqueezeShape = !isPacked && rank > 1 && !util_exports.arraysEqual(shape, texShape) && newShape.length < rank || useSqueezePackedShape;\n  const uniformShape = useSqueezeShape ? squeezeShape2 : shape;\n  return { useSqueezeShape, uniformShape, keptDims };\n}\nfunction squeezeInputInfo(inInfo, squeezedShape) {\n  const newInputInfo = JSON.parse(JSON.stringify(inInfo));\n  newInputInfo.shapeInfo.logicalShape = squeezedShape;\n  return newInputInfo;\n}\nfunction getSqueezedParams(params, keptDims) {\n  return keptDims.map((d) => params[d]).join(\", \");\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/gpgpu_math.js\nfunction compileProgram(gpgpu, program, inputs, output) {\n  const inputInfos = inputs.map((input2, i2) => {\n    const shapeInfo = {\n      logicalShape: input2.shape,\n      texShape: input2.isUniform ? null : input2.texData.texShape,\n      isUniform: input2.isUniform,\n      isPacked: input2.isUniform ? false : input2.texData.isPacked,\n      flatOffset: null\n    };\n    if (input2.texData != null && input2.texData.slice != null && input2.texData.slice.flatOffset > 0) {\n      shapeInfo.flatOffset = input2.texData.slice.flatOffset;\n    }\n    return { name: program.variableNames[i2], shapeInfo };\n  });\n  const inShapeInfos = inputInfos.map((x) => x.shapeInfo);\n  const outShapeInfo = {\n    logicalShape: output.shape,\n    texShape: output.texData.texShape,\n    isUniform: false,\n    isPacked: output.texData.isPacked,\n    flatOffset: null\n  };\n  const source = makeShader(inputInfos, outShapeInfo, program);\n  const fragmentShader = createFragmentShader(gpgpu.gl, source);\n  const webGLProgram = gpgpu.createProgram(fragmentShader);\n  if (!env().get(\"ENGINE_COMPILE_ONLY\")) {\n    return Object.assign({\n      program,\n      fragmentShader,\n      source,\n      webGLProgram,\n      inShapeInfos,\n      outShapeInfo\n    }, getUniformLocations(gpgpu, program, webGLProgram));\n  } else {\n    return {\n      program,\n      fragmentShader,\n      source,\n      webGLProgram,\n      inShapeInfos,\n      outShapeInfo,\n      uniformLocations: null,\n      customUniformLocations: null,\n      infLoc: null,\n      nanLoc: null,\n      inShapesLocations: null,\n      inTexShapesLocations: null,\n      outShapeLocation: null,\n      outShapeStridesLocation: null,\n      outTexShapeLocation: null\n    };\n  }\n}\nfunction getUniformLocations(gpgpu, program, webGLProgram) {\n  const uniformLocations = {};\n  const inShapesLocations = {};\n  const inTexShapesLocations = {};\n  const customUniformLocations = [];\n  let outShapeLocation;\n  let outTexShapeLocation;\n  let outShapeStridesLocation;\n  let infLoc = null;\n  let nanLoc = null;\n  nanLoc = gpgpu.getUniformLocation(webGLProgram, \"NAN\", false);\n  if (env().getNumber(\"WEBGL_VERSION\") === 1) {\n    infLoc = gpgpu.getUniformLocation(webGLProgram, \"INFINITY\", false);\n  }\n  const shouldThrow = false;\n  for (let i2 = 0; i2 < program.variableNames.length; i2++) {\n    const varName = program.variableNames[i2];\n    uniformLocations[varName] = gpgpu.getUniformLocation(webGLProgram, varName, shouldThrow);\n    uniformLocations[`offset${varName}`] = gpgpu.getUniformLocation(webGLProgram, `offset${varName}`, shouldThrow);\n    if (program.enableShapeUniforms) {\n      inShapesLocations[`${varName}Shape`] = gpgpu.getUniformLocation(webGLProgram, `${varName}Shape`, shouldThrow);\n      inTexShapesLocations[`${varName}TexShape`] = gpgpu.getUniformLocation(webGLProgram, `${varName}TexShape`, shouldThrow);\n    }\n  }\n  if (program.enableShapeUniforms) {\n    outShapeLocation = gpgpu.getUniformLocation(webGLProgram, \"outShape\", shouldThrow);\n    outShapeStridesLocation = gpgpu.getUniformLocation(webGLProgram, \"outShapeStrides\", shouldThrow);\n    outTexShapeLocation = gpgpu.getUniformLocation(webGLProgram, \"outTexShape\", shouldThrow);\n  }\n  if (program.customUniforms) {\n    program.customUniforms.forEach((d, i2) => {\n      customUniformLocations[i2] = gpgpu.getUniformLocation(webGLProgram, d.name, shouldThrow);\n    });\n  }\n  return {\n    uniformLocations,\n    customUniformLocations,\n    infLoc,\n    nanLoc,\n    inShapesLocations,\n    inTexShapesLocations,\n    outShapeLocation,\n    outShapeStridesLocation,\n    outTexShapeLocation\n  };\n}\nfunction validateBinaryAndProgram(shapeInfos, inputs) {\n  if (shapeInfos.length !== inputs.length) {\n    throw Error(`Binary was compiled with ${shapeInfos.length} inputs, but was executed with ${inputs.length} inputs`);\n  }\n  shapeInfos.forEach((s2, i2) => {\n    const shapeA = s2.logicalShape;\n    const input2 = inputs[i2];\n    const shapeB = input2.shape;\n    if (!util_exports.arraysEqual(shapeA, shapeB)) {\n      throw Error(`Binary was compiled with different shapes than the current args. Shapes ${shapeA} and ${shapeB} must match`);\n    }\n    if (s2.isUniform && input2.isUniform) {\n      return;\n    }\n    const texShapeA = s2.texShape;\n    const texShapeB = input2.isUniform ? null : input2.texData.texShape;\n    if (!util_exports.arraysEqual(texShapeA, texShapeB)) {\n      throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${texShapeA} and ${texShapeB} must match`);\n    }\n  });\n}\nfunction runProgram(gpgpu, binary, inputs, output, customUniformValues) {\n  if (!binary.program.enableShapeUniforms) {\n    validateBinaryAndProgram(binary.inShapeInfos, inputs);\n    validateBinaryAndProgram([binary.outShapeInfo], [output]);\n  }\n  const outTex = output.texData.texture;\n  const outTexShape = output.texData.texShape;\n  if (output.texData.isPacked) {\n    gpgpu.setOutputPackedMatrixTexture(outTex.texture, outTexShape[0], outTexShape[1]);\n  } else {\n    gpgpu.setOutputMatrixTexture(outTex.texture, outTexShape[0], outTexShape[1]);\n  }\n  gpgpu.setProgram(binary.webGLProgram);\n  if (env().getNumber(\"WEBGL_VERSION\") === 1) {\n    if (binary.infLoc !== null) {\n      gpgpu.gl.uniform1f(binary.infLoc, Infinity);\n    }\n  }\n  if (binary.nanLoc !== null) {\n    gpgpu.gl.uniform1f(binary.nanLoc, NaN);\n  }\n  inputs.forEach((input2, i2) => {\n    const varName = binary.program.variableNames[i2];\n    const varLoc = binary.uniformLocations[varName];\n    const varOffsetLoc = binary.uniformLocations[`offset${varName}`];\n    const varShapeLoc = binary.inShapesLocations[`${varName}Shape`];\n    const varTexShapeLoc = binary.inTexShapesLocations[`${varName}TexShape`];\n    if (varShapeLoc) {\n      const { uniformShape } = getUniformInfoFromShape(binary.program.packedInputs, input2.shape, input2.texData.texShape);\n      switch (uniformShape.length) {\n        case 1:\n          gpgpu.gl.uniform1iv(varShapeLoc, new Int32Array(uniformShape));\n          break;\n        case 2:\n          gpgpu.gl.uniform2iv(varShapeLoc, new Int32Array(uniformShape));\n          break;\n        case 3:\n          gpgpu.gl.uniform3iv(varShapeLoc, new Int32Array(uniformShape));\n          break;\n        case 4:\n          gpgpu.gl.uniform4iv(varShapeLoc, new Int32Array(uniformShape));\n          break;\n        default:\n          break;\n      }\n    }\n    if (varTexShapeLoc) {\n      gpgpu.gl.uniform2i(varTexShapeLoc, input2.texData.texShape[0], input2.texData.texShape[1]);\n    }\n    if (varLoc == null) {\n      return;\n    }\n    if (input2.isUniform) {\n      if (util_exports.sizeFromShape(input2.shape) < 2) {\n        gpgpu.gl.uniform1f(varLoc, input2.uniformValues[0]);\n      } else {\n        let vals = input2.uniformValues;\n        if (!(vals instanceof Float32Array)) {\n          vals = new Float32Array(vals);\n        }\n        gpgpu.gl.uniform1fv(varLoc, vals);\n      }\n      return;\n    }\n    if (input2.texData.slice != null && varOffsetLoc != null) {\n      gpgpu.gl.uniform1i(varOffsetLoc, input2.texData.slice.flatOffset);\n    }\n    gpgpu.setInputMatrixTexture(input2.texData.texture.texture, varLoc, i2);\n  });\n  const outShapeLoc = binary.outShapeLocation;\n  if (outShapeLoc) {\n    switch (output.shape.length) {\n      case 1:\n        gpgpu.gl.uniform1iv(outShapeLoc, new Int32Array(output.shape));\n        break;\n      case 2:\n        gpgpu.gl.uniform2iv(outShapeLoc, new Int32Array(output.shape));\n        break;\n      case 3:\n        gpgpu.gl.uniform3iv(outShapeLoc, new Int32Array(output.shape));\n        break;\n      case 4:\n        gpgpu.gl.uniform4iv(outShapeLoc, new Int32Array(output.shape));\n        break;\n      default:\n        break;\n    }\n  }\n  if (binary.outShapeStridesLocation) {\n    const strides = util_exports.computeStrides(output.shape);\n    switch (output.shape.length) {\n      case 2:\n        gpgpu.gl.uniform1iv(binary.outShapeStridesLocation, new Int32Array(strides));\n        break;\n      case 3:\n        gpgpu.gl.uniform2iv(binary.outShapeStridesLocation, new Int32Array(strides));\n        break;\n      case 4:\n        gpgpu.gl.uniform3iv(binary.outShapeStridesLocation, new Int32Array(strides));\n        break;\n      default:\n        break;\n    }\n  }\n  if (binary.outTexShapeLocation) {\n    gpgpu.gl.uniform2i(binary.outTexShapeLocation, output.texData.texShape[0], output.texData.texShape[1]);\n  }\n  if (binary.program.customUniforms && customUniformValues) {\n    binary.program.customUniforms.forEach((d, i2) => {\n      const customLoc = binary.customUniformLocations[i2];\n      const customValue = customUniformValues[i2];\n      if (d.type === \"float\") {\n        gpgpu.gl.uniform1fv(customLoc, customValue);\n      } else if (d.type === \"vec2\") {\n        gpgpu.gl.uniform2fv(customLoc, customValue);\n      } else if (d.type === \"vec3\") {\n        gpgpu.gl.uniform3fv(customLoc, customValue);\n      } else if (d.type === \"vec4\") {\n        gpgpu.gl.uniform4fv(customLoc, customValue);\n      } else if (d.type === \"int\") {\n        gpgpu.gl.uniform1iv(customLoc, customValue);\n      } else if (d.type === \"ivec2\") {\n        gpgpu.gl.uniform2iv(customLoc, customValue);\n      } else if (d.type === \"ivec3\") {\n        gpgpu.gl.uniform3iv(customLoc, customValue);\n      } else if (d.type === \"ivec4\") {\n        gpgpu.gl.uniform4iv(customLoc, customValue);\n      } else {\n        throw Error(`uniform type ${d.type} is not supported yet.`);\n      }\n    });\n  }\n  gpgpu.executeProgram();\n}\nfunction makeShaderKey(program, inputs, output) {\n  let keyInputs = \"\";\n  inputs.concat(output).forEach((x) => {\n    const hasOffset = x.texData != null && x.texData.slice != null && x.texData.slice.flatOffset > 0;\n    if (program.enableShapeUniforms && !x.isUniform) {\n      const xTexShape = x.texData.texShape;\n      const { useSqueezeShape, uniformShape, keptDims } = getUniformInfoFromShape(program.packedInputs, x.shape, xTexShape);\n      let rank1 = \"\", rank2 = \"\", rank34 = \"\";\n      if (uniformShape.length === 1 && program.packedInputs) {\n        const packedTexShape = [Math.ceil(xTexShape[0] / 2), Math.ceil(xTexShape[1] / 2)];\n        rank1 = `${packedTexShape[0] > 1}_${packedTexShape[1] > 1}`;\n      } else if (uniformShape.length === 2 && !program.packedInputs) {\n        rank2 = `${uniformShape[0] > 1}_${uniformShape[1] > 1}`;\n      } else if (uniformShape.length > 2 && !program.packedInputs) {\n        const strides = util_exports.computeStrides(uniformShape);\n        rank34 = `${strides[0] === xTexShape[1]}_${strides[strides.length - 1] === xTexShape[1]}`;\n      }\n      const xRank = x.shape.length;\n      const isLogicalShapTexShapeEqual = uniformShape.length === 2 && util_exports.arraysEqual(x.shape, xTexShape);\n      const isScalar = util_exports.sizeFromShape(x.shape) === 1;\n      const broadcastDims = backend_util_exports.getBroadcastDims(x.shape, output.shape);\n      const isInOutTexShapeEqual = !program.packedInputs && xRank === output.shape.length && util_exports.arraysEqual(xTexShape, output.texData.texShape);\n      const isTexShapeGreaterThanOne = program.packedInputs || uniformShape.length > 2 ? \"\" : `${xTexShape[0] > 1}_${xTexShape[1] > 1}`;\n      keyInputs += `${xRank}_${isInOutTexShapeEqual}_${useSqueezeShape ? keptDims : \"\"}_${uniformShape.length}_${isScalar}_${broadcastDims}_${isLogicalShapTexShapeEqual}_${rank1}_${rank2}_${rank34}_${isTexShapeGreaterThanOne}_${hasOffset}`;\n    } else {\n      const texShape = x.isUniform ? \"uniform\" : x.texData.texShape;\n      keyInputs += `${x.shape}_${texShape}_${hasOffset}`;\n    }\n  });\n  const keyUserCode = program.userCode;\n  let key = program.constructor.name;\n  key += \"_\" + keyInputs + \"_\" + keyUserCode + `${env().getNumber(\"WEBGL_VERSION\")}`;\n  return key;\n}\nfunction useShapeUniforms(rank) {\n  return env().getBool(\"WEBGL_USE_SHAPES_UNIFORMS\") && rank <= 4;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/decode_matrix_gpu.js\nvar DecodeMatrixProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = false;\n    this.packedOutput = true;\n    this.outPackingScheme = PackingScheme.DENSE;\n    this.customUniforms = [{ name: \"texShape\", type: \"ivec2\" }];\n    const glsl = getGlslDifferences();\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    this.userCode = `\n      ivec3 outCoordsFromFlatIndex(int index) {\n        ${this.enableShapeUniforms ? getOutputLogicalCoordinatesFromFlatIndexByUniform([\"r\", \"c\", \"d\"], outputShape) : getLogicalCoordinatesFromFlatIndex([\"r\", \"c\", \"d\"], outputShape)}\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));\n        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getA(rc.x, rc.y, rc.z);\n        }\n\n        ${glsl.output} = result;\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/decode_matrix_packed_gpu.js\nvar DecodeMatrixPackedProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outPackingScheme = PackingScheme.DENSE;\n    this.customUniforms = [{ name: \"texShape\", type: \"ivec2\" }];\n    const glsl = getGlslDifferences();\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    this.userCode = `\n      ivec3 outCoordsFromFlatIndex(int index) {\n        ${this.enableShapeUniforms ? getOutputLogicalCoordinatesFromFlatIndexByUniform([\"r\", \"c\", \"d\"], outputShape) : getLogicalCoordinatesFromFlatIndex([\"r\", \"c\", \"d\"], outputShape)}\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));\n        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));\n        }\n\n        ${glsl.output} = result;\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_float_gpu.js\nvar EncodeFloatProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.outTexUsage = TextureUsage.DOWNLOAD;\n    const glsl = getGlslDifferences();\n    this.outputShape = outputShape;\n    this.userCode = `\n      ${ENCODE_FLOAT_SNIPPET}\n\n      void main() {\n        float x = getAAtOutCoords();\n        ${glsl.output} = encode_float(x);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_float_packed_gpu.js\nvar EncodeFloatPackedProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = false;\n    this.outTexUsage = TextureUsage.DOWNLOAD;\n    const glsl = getGlslDifferences();\n    this.outputShape = outputShape;\n    this.userCode = `\n      ${ENCODE_FLOAT_SNIPPET}\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));\n        ${glsl.output} = encode_float(x);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_matrix_gpu.js\nvar EncodeMatrixProgram = class {\n  constructor(outputShape, inputIsUnsignedByte = false) {\n    this.variableNames = [\"A\"];\n    this.customUniforms = [{ name: \"texShape\", type: \"ivec2\" }];\n    const glsl = getGlslDifferences();\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    let output = `result`;\n    if (inputIsUnsignedByte) {\n      output = `floor(result * 255. + 0.5)`;\n    }\n    this.userCode = `\n      ${this.enableShapeUniforms ? getFlatIndexFrom3DOutput() : getFlatIndexFrom3D(outputShape)}\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        int flatIndex = getFlatIndex(coords);\n        int offset = imod(flatIndex, 4);\n\n        flatIndex = idiv(flatIndex, 4, 1.);\n\n        int r = flatIndex / texShape[1];\n        int c = imod(flatIndex, texShape[1]);\n        vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);\n        vec4 values = ${glsl.texture2D}(A, uv);\n\n        float result;\n\n        if(offset == 0) {\n          result = values[0];\n        } else if(offset == 1) {\n          result = values[1];\n        } else if(offset == 2) {\n          result = values[2];\n        } else {\n          result = values[3];\n        }\n\n        ${glsl.output} = vec4(${output}, 0., 0., 0.);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_matrix_packed_gpu.js\nvar EncodeMatrixPackedProgram = class {\n  constructor(outputShape, inputIsUnsignedByte = false) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = false;\n    this.packedOutput = true;\n    this.customUniforms = [{ name: \"texShape\", type: \"ivec2\" }];\n    const glsl = getGlslDifferences();\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    let mainLoop = \"\";\n    let output = \"result\";\n    if (inputIsUnsignedByte) {\n      output = \"floor(result * 255. + 0.5)\";\n    }\n    for (let row = 0; row <= 1; row++) {\n      for (let col = 0; col <= 1; col++) {\n        const channel = row * 2 + col;\n        mainLoop += `\n          localCoords = coords;\n          if(localCoords[2] + ${col} < ${this.enableShapeUniforms ? \"outShape[2]\" : `${outputShape[2]}`}) {\n          localCoords[2] += ${col};\n          if (localCoords[1] + ${row} < ${this.enableShapeUniforms ? \"outShape[1]\" : `${outputShape[1]}`}) {\n            localCoords[1] += ${row};\n\n            flatIndex = getFlatIndex(localCoords);\n            offset = imod(flatIndex, 4);\n\n            flatIndex = idiv(flatIndex, 4, 1.);\n\n            int r = flatIndex / texShape[1];\n            int c = imod(flatIndex, texShape[1]);\n            vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);\n            values = ${glsl.texture2D}(A, uv);\n\n            if (offset == 0) {\n              result[${channel}] = values[0];\n            } else if (offset == 1) {\n              result[${channel}] = values[1];\n            } else if (offset == 2) {\n              result[${channel}] = values[2];\n            } else {\n              result[${channel}] = values[3];\n            }\n          }\n        }\n        `;\n      }\n    }\n    this.userCode = `\n        ${this.enableShapeUniforms ? getFlatIndexFrom3DOutput() : getFlatIndexFrom3D(outputShape)}\n\n        void main() {\n          ivec3 coords = getOutputCoords();\n\n          vec4 result = vec4(0.);\n          int flatIndex, r, c, offset;\n          ivec3 localCoords;\n          vec2 uv;\n          vec4 values;\n\n          ${mainLoop}\n\n          ${glsl.output} = ${output};\n        }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/gpgpu_util.js\nvar gpgpu_util_exports = {};\n__export(gpgpu_util_exports, {\n  bindVertexProgramAttributeStreams: () => bindVertexProgramAttributeStreams,\n  createBufferFromOutputTexture: () => createBufferFromOutputTexture,\n  createFloat16MatrixTexture: () => createFloat16MatrixTexture,\n  createFloat16PackedMatrixTexture: () => createFloat16PackedMatrixTexture,\n  createFloat32MatrixTexture: () => createFloat32MatrixTexture,\n  createIndexBuffer: () => createIndexBuffer,\n  createPackedMatrixTexture: () => createPackedMatrixTexture,\n  createUnsignedBytesMatrixTexture: () => createUnsignedBytesMatrixTexture,\n  createVertexBuffer: () => createVertexBuffer,\n  createVertexShader: () => createVertexShader2,\n  downloadByteEncodedFloatMatrixFromOutputTexture: () => downloadByteEncodedFloatMatrixFromOutputTexture,\n  downloadFloat32MatrixFromBuffer: () => downloadFloat32MatrixFromBuffer,\n  downloadMatrixFromPackedOutputTexture: () => downloadMatrixFromPackedOutputTexture,\n  downloadPackedMatrixFromBuffer: () => downloadPackedMatrixFromBuffer,\n  getInternalFormatForFloat16MatrixTexture: () => getInternalFormatForFloat16MatrixTexture,\n  getInternalFormatForFloat16PackedMatrixTexture: () => getInternalFormatForFloat16PackedMatrixTexture,\n  getInternalFormatForFloat32MatrixTexture: () => getInternalFormatForFloat32MatrixTexture,\n  getInternalFormatForPackedMatrixTexture: () => getInternalFormatForPackedMatrixTexture,\n  getInternalFormatForUnsignedBytesMatrixTexture: () => getInternalFormatForUnsignedBytesMatrixTexture,\n  uploadDenseMatrixToTexture: () => uploadDenseMatrixToTexture,\n  uploadPixelDataToTexture: () => uploadPixelDataToTexture\n});\nfunction createVertexShader2(gl) {\n  const glsl = getGlslDifferences();\n  const vertexShaderSource = `${glsl.version}\n    precision highp float;\n    ${glsl.attribute} vec3 clipSpacePos;\n    ${glsl.attribute} vec2 uv;\n    ${glsl.varyingVs} vec2 resultUV;\n\n    void main() {\n      gl_Position = vec4(clipSpacePos, 1);\n      resultUV = uv;\n    }`;\n  return createVertexShader(gl, vertexShaderSource);\n}\nfunction createVertexBuffer(gl) {\n  const vertexArray = new Float32Array([-1, 1, 0, 0, 1, -1, -1, 0, 0, 0, 1, 1, 0, 1, 1, 1, -1, 0, 1, 0]);\n  return createStaticVertexBuffer(gl, vertexArray);\n}\nfunction createIndexBuffer(gl) {\n  const triangleVertexIndices = new Uint16Array([0, 1, 2, 2, 1, 3]);\n  return createStaticIndexBuffer(gl, triangleVertexIndices);\n}\nfunction createAndConfigureTexture(gl, width, height, internalFormat, textureFormat, textureType) {\n  validateTextureSize(width, height);\n  const texture = createTexture(gl);\n  const tex2d = gl.TEXTURE_2D;\n  callAndCheck(gl, () => gl.bindTexture(tex2d, texture));\n  callAndCheck(gl, () => gl.texParameteri(tex2d, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE));\n  callAndCheck(gl, () => gl.texParameteri(tex2d, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE));\n  callAndCheck(gl, () => gl.texParameteri(tex2d, gl.TEXTURE_MIN_FILTER, gl.NEAREST));\n  callAndCheck(gl, () => gl.texParameteri(tex2d, gl.TEXTURE_MAG_FILTER, gl.NEAREST));\n  if (env().getNumber(\"WEBGL_VERSION\") === 1) {\n    callAndCheck(gl, () => gl.texImage2D(tex2d, 0, internalFormat, width, height, 0, textureFormat, textureType, null));\n  } else {\n    callAndCheck(gl, () => gl.texStorage2D(tex2d, 1, internalFormat, width, height));\n  }\n  callAndCheck(gl, () => gl.bindTexture(gl.TEXTURE_2D, null));\n  return { texture, texShape: [height, width] };\n}\nfunction getInternalFormatForFloat32MatrixTexture(textureConfig) {\n  return textureConfig.internalFormatFloat;\n}\nfunction createFloat32MatrixTexture(gl, rows, columns, textureConfig) {\n  const [width, height] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);\n  return createAndConfigureTexture(gl, width, height, getInternalFormatForFloat32MatrixTexture(textureConfig), textureConfig.textureFormatFloat, gl.FLOAT);\n}\nfunction getInternalFormatForFloat16MatrixTexture(textureConfig) {\n  return textureConfig.internalFormatHalfFloat;\n}\nfunction createFloat16MatrixTexture(gl, rows, columns, textureConfig) {\n  const [width, height] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);\n  return createAndConfigureTexture(gl, width, height, getInternalFormatForFloat16MatrixTexture(textureConfig), textureConfig.textureFormatFloat, textureConfig.textureTypeHalfFloat);\n}\nfunction getInternalFormatForUnsignedBytesMatrixTexture(textureConfig) {\n  return textureConfig.downloadTextureFormat;\n}\nfunction createUnsignedBytesMatrixTexture(gl, rows, columns, textureConfig) {\n  const [width, height] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);\n  return createAndConfigureTexture(gl, width, height, getInternalFormatForUnsignedBytesMatrixTexture(textureConfig), gl.RGBA, gl.UNSIGNED_BYTE);\n}\nfunction getInternalFormatForPackedMatrixTexture(textureConfig) {\n  return textureConfig.internalFormatPackedFloat;\n}\nfunction createPackedMatrixTexture(gl, rows, columns, textureConfig) {\n  const [width, height] = getPackedMatrixTextureShapeWidthHeight(rows, columns);\n  return createAndConfigureTexture(gl, width, height, getInternalFormatForPackedMatrixTexture(textureConfig), gl.RGBA, gl.FLOAT);\n}\nfunction getInternalFormatForFloat16PackedMatrixTexture(textureConfig) {\n  return textureConfig.internalFormatPackedHalfFloat;\n}\nfunction createFloat16PackedMatrixTexture(gl, rows, columns, textureConfig) {\n  const [width, height] = getPackedMatrixTextureShapeWidthHeight(rows, columns);\n  return createAndConfigureTexture(gl, width, height, getInternalFormatForFloat16PackedMatrixTexture(textureConfig), gl.RGBA, textureConfig.textureTypeHalfFloat);\n}\nfunction bindVertexProgramAttributeStreams(gl, program, vertexBuffer) {\n  const posOffset = 0;\n  const uvOffset = 3 * 4;\n  const stride = 3 * 4 + 2 * 4;\n  callAndCheck(gl, () => gl.bindBuffer(gl.ARRAY_BUFFER, vertexBuffer));\n  const success = bindVertexBufferToProgramAttribute(gl, program, \"clipSpacePos\", vertexBuffer, 3, stride, posOffset);\n  return success && bindVertexBufferToProgramAttribute(gl, program, \"uv\", vertexBuffer, 2, stride, uvOffset);\n}\nfunction uploadDenseMatrixToTexture(gl, texture, width, height, data, textureConfig) {\n  callAndCheck(gl, () => gl.bindTexture(gl.TEXTURE_2D, texture));\n  let dataForUpload, texelDataType, internalFormat;\n  if (data instanceof Uint8Array) {\n    dataForUpload = new Uint8Array(width * height * 4);\n    texelDataType = gl.UNSIGNED_BYTE;\n    internalFormat = gl.RGBA;\n  } else {\n    dataForUpload = new Float32Array(width * height * 4);\n    texelDataType = gl.FLOAT;\n    internalFormat = textureConfig.internalFormatPackedFloat;\n  }\n  dataForUpload.set(data);\n  if (env().getNumber(\"WEBGL_VERSION\") === 2) {\n    callAndCheck(gl, () => gl.texSubImage2D(gl.TEXTURE_2D, 0, 0, 0, width, height, gl.RGBA, texelDataType, dataForUpload));\n  } else {\n    callAndCheck(gl, () => gl.texImage2D(gl.TEXTURE_2D, 0, internalFormat, width, height, 0, gl.RGBA, texelDataType, dataForUpload));\n  }\n  callAndCheck(gl, () => gl.bindTexture(gl.TEXTURE_2D, null));\n}\nfunction uploadPixelDataToTexture(gl, texture, pixels) {\n  callAndCheck(gl, () => gl.bindTexture(gl.TEXTURE_2D, texture));\n  if (pixels.data instanceof Uint8Array) {\n    if (env().getNumber(\"WEBGL_VERSION\") === 2) {\n      callAndCheck(gl, () => gl.texSubImage2D(gl.TEXTURE_2D, 0, 0, 0, pixels.width, pixels.height, gl.RGBA, gl.UNSIGNED_BYTE, pixels.data));\n    } else {\n      callAndCheck(gl, () => gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, pixels.width, pixels.height, 0, gl.RGBA, gl.UNSIGNED_BYTE, pixels.data));\n    }\n  } else {\n    if (env().getNumber(\"WEBGL_VERSION\") === 2) {\n      callAndCheck(gl, () => gl.texSubImage2D(gl.TEXTURE_2D, 0, 0, 0, gl.RGBA, gl.UNSIGNED_BYTE, pixels));\n    } else {\n      callAndCheck(gl, () => gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, pixels));\n    }\n  }\n  callAndCheck(gl, () => gl.bindTexture(gl.TEXTURE_2D, null));\n}\nfunction createBufferFromOutputTexture(gl2, rows, columns, textureConfig) {\n  const buffer2 = gl2.createBuffer();\n  callAndCheck(gl2, () => gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, buffer2));\n  const bytesPerFloat = 4;\n  const valuesPerTexel = 4;\n  const bufferSizeBytes = bytesPerFloat * valuesPerTexel * rows * columns;\n  callAndCheck(gl2, () => gl2.bufferData(gl2.PIXEL_PACK_BUFFER, bufferSizeBytes, gl2.STREAM_READ));\n  callAndCheck(gl2, () => gl2.readPixels(0, 0, columns, rows, gl2.RGBA, gl2.FLOAT, 0));\n  callAndCheck(gl2, () => gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, null));\n  return buffer2;\n}\nfunction downloadFloat32MatrixFromBuffer(gl, buffer2, size) {\n  const gl2 = gl;\n  const downloadTarget = new Float32Array(size);\n  gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, buffer2);\n  gl2.getBufferSubData(gl2.PIXEL_PACK_BUFFER, 0, downloadTarget);\n  gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, null);\n  return downloadTarget;\n}\nfunction downloadByteEncodedFloatMatrixFromOutputTexture(gl, rows, columns, textureConfig) {\n  const [w, h] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);\n  const numChannels = 4;\n  const downloadTarget = new Uint8Array(getUnpackedArraySizeFromMatrixSize(rows * columns, numChannels));\n  callAndCheck(gl, () => gl.readPixels(0, 0, w, h, textureConfig.downloadTextureFormat, gl.UNSIGNED_BYTE, downloadTarget));\n  return new Float32Array(downloadTarget.buffer);\n}\nfunction downloadPackedMatrixFromBuffer(gl, buffer2, batch, rows, cols, physicalRows, physicalCols, textureConfig) {\n  const gl2 = gl;\n  const downloadTarget = new Float32Array(getPackedRGBAArraySizeFromMatrixShape(physicalRows, physicalCols));\n  gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, buffer2);\n  gl2.getBufferSubData(gl2.PIXEL_PACK_BUFFER, 0, downloadTarget);\n  gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, null);\n  return downloadTarget;\n}\nfunction downloadMatrixFromPackedOutputTexture(gl, physicalRows, physicalCols) {\n  const packedRGBA = new Float32Array(physicalRows * physicalCols * 4);\n  callAndCheck(gl, () => gl.readPixels(0, 0, physicalCols, physicalRows, gl.RGBA, gl.FLOAT, packedRGBA));\n  return packedRGBA;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/gpgpu_context.js\nvar GPGPUContext = class {\n  constructor(gl) {\n    this.outputTexture = null;\n    this.program = null;\n    this.disposed = false;\n    this.vertexAttrsAreBound = false;\n    this.itemsToPoll = [];\n    const glVersion = env().getNumber(\"WEBGL_VERSION\");\n    if (gl != null) {\n      this.gl = gl;\n      setWebGLContext(glVersion, gl);\n    } else {\n      this.gl = getWebGLContext(glVersion);\n    }\n    let COLOR_BUFFER_FLOAT = \"WEBGL_color_buffer_float\";\n    const COLOR_BUFFER_HALF_FLOAT = \"EXT_color_buffer_half_float\";\n    this.parallelCompilationExtension = this.gl.getExtension(\"KHR_parallel_shader_compile\");\n    if (env().getNumber(\"WEBGL_VERSION\") === 1) {\n      const TEXTURE_FLOAT = \"OES_texture_float\";\n      const TEXTURE_HALF_FLOAT = \"OES_texture_half_float\";\n      this.textureFloatExtension = getExtensionOrThrow(this.gl, TEXTURE_FLOAT);\n      if (hasExtension(this.gl, TEXTURE_HALF_FLOAT)) {\n        this.textureHalfFloatExtension = getExtensionOrThrow(this.gl, TEXTURE_HALF_FLOAT);\n      } else if (env().get(\"WEBGL_FORCE_F16_TEXTURES\")) {\n        throw new Error(\"GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.\");\n      }\n      this.colorBufferFloatExtension = this.gl.getExtension(COLOR_BUFFER_FLOAT);\n      if (hasExtension(this.gl, COLOR_BUFFER_HALF_FLOAT)) {\n        this.colorBufferHalfFloatExtension = getExtensionOrThrow(this.gl, COLOR_BUFFER_HALF_FLOAT);\n      } else if (env().get(\"WEBGL_FORCE_F16_TEXTURES\")) {\n        throw new Error(\"GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.\");\n      }\n    } else {\n      COLOR_BUFFER_FLOAT = \"EXT_color_buffer_float\";\n      if (hasExtension(this.gl, COLOR_BUFFER_FLOAT)) {\n        this.colorBufferFloatExtension = this.gl.getExtension(COLOR_BUFFER_FLOAT);\n      } else if (hasExtension(this.gl, COLOR_BUFFER_HALF_FLOAT)) {\n        this.colorBufferHalfFloatExtension = this.gl.getExtension(COLOR_BUFFER_HALF_FLOAT);\n      } else {\n        throw new Error(\"GL context does not support color renderable floats\");\n      }\n    }\n    this.vertexBuffer = createVertexBuffer(this.gl);\n    this.indexBuffer = createIndexBuffer(this.gl);\n    this.framebuffer = createFramebuffer(this.gl);\n    this.textureConfig = getTextureConfig(this.gl, this.textureHalfFloatExtension);\n  }\n  get debug() {\n    return env().getBool(\"DEBUG\");\n  }\n  dispose() {\n    if (this.disposed) {\n      return;\n    }\n    if (this.program != null) {\n      console.warn(\"Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing.\");\n    }\n    if (this.outputTexture != null) {\n      console.warn(\"Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.\");\n    }\n    const gl = this.gl;\n    callAndCheck(gl, () => gl.finish());\n    callAndCheck(gl, () => gl.bindFramebuffer(gl.FRAMEBUFFER, null));\n    callAndCheck(gl, () => gl.deleteFramebuffer(this.framebuffer));\n    callAndCheck(gl, () => gl.bindBuffer(gl.ARRAY_BUFFER, null));\n    callAndCheck(gl, () => gl.bindBuffer(gl.ELEMENT_ARRAY_BUFFER, null));\n    callAndCheck(gl, () => gl.deleteBuffer(this.indexBuffer));\n    this.disposed = true;\n  }\n  createFloat32MatrixTexture(rows, columns) {\n    this.throwIfDisposed();\n    return createFloat32MatrixTexture(this.gl, rows, columns, this.textureConfig);\n  }\n  createFloat16MatrixTexture(rows, columns) {\n    this.throwIfDisposed();\n    return createFloat16MatrixTexture(this.gl, rows, columns, this.textureConfig);\n  }\n  createUnsignedBytesMatrixTexture(rows, columns) {\n    this.throwIfDisposed();\n    return createUnsignedBytesMatrixTexture(this.gl, rows, columns, this.textureConfig);\n  }\n  uploadPixelDataToTexture(texture, pixels) {\n    this.throwIfDisposed();\n    uploadPixelDataToTexture(this.gl, texture, pixels);\n  }\n  uploadDenseMatrixToTexture(texture, width, height, data) {\n    this.throwIfDisposed();\n    uploadDenseMatrixToTexture(this.gl, texture, width, height, data, this.textureConfig);\n  }\n  createFloat16PackedMatrixTexture(rows, columns) {\n    this.throwIfDisposed();\n    return createFloat16PackedMatrixTexture(this.gl, rows, columns, this.textureConfig);\n  }\n  createPackedMatrixTexture(rows, columns) {\n    this.throwIfDisposed();\n    return createPackedMatrixTexture(this.gl, rows, columns, this.textureConfig);\n  }\n  deleteMatrixTexture(texture) {\n    this.throwIfDisposed();\n    if (this.outputTexture === texture) {\n      unbindColorTextureFromFramebuffer(this.gl, this.framebuffer);\n      this.outputTexture = null;\n    }\n    callAndCheck(this.gl, () => this.gl.deleteTexture(texture));\n  }\n  downloadByteEncodedFloatMatrixFromOutputTexture(texture, rows, columns) {\n    return this.downloadMatrixDriver(texture, () => downloadByteEncodedFloatMatrixFromOutputTexture(this.gl, rows, columns, this.textureConfig));\n  }\n  downloadPackedMatrixFromBuffer(buffer2, batch, rows, columns, physicalRows, physicalCols) {\n    return downloadPackedMatrixFromBuffer(this.gl, buffer2, batch, rows, columns, physicalRows, physicalCols, this.textureConfig);\n  }\n  downloadFloat32MatrixFromBuffer(buffer2, size) {\n    return downloadFloat32MatrixFromBuffer(this.gl, buffer2, size);\n  }\n  createBufferFromTexture(texture, rows, columns) {\n    this.bindTextureToFrameBuffer(texture);\n    const result = createBufferFromOutputTexture(this.gl, rows, columns, this.textureConfig);\n    this.unbindTextureToFrameBuffer();\n    return result;\n  }\n  createAndWaitForFence() {\n    const fenceContext = this.createFence(this.gl);\n    return this.pollFence(fenceContext);\n  }\n  createFence(gl) {\n    let query;\n    let isFencePassed;\n    if (env().getBool(\"WEBGL_FENCE_API_ENABLED\")) {\n      const gl2 = gl;\n      const sync = gl2.fenceSync(gl2.SYNC_GPU_COMMANDS_COMPLETE, 0);\n      gl.flush();\n      isFencePassed = () => {\n        const status = gl2.clientWaitSync(sync, 0, 0);\n        return status === gl2.ALREADY_SIGNALED || status === gl2.CONDITION_SATISFIED;\n      };\n      query = sync;\n    } else if (env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\") > 0) {\n      query = this.beginQuery();\n      this.endQuery();\n      isFencePassed = () => this.isQueryAvailable(query, env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\"));\n    } else {\n      isFencePassed = () => true;\n    }\n    return { query, isFencePassed };\n  }\n  downloadMatrixFromPackedTexture(texture, physicalRows, physicalCols) {\n    return this.downloadMatrixDriver(texture, () => downloadMatrixFromPackedOutputTexture(this.gl, physicalRows, physicalCols));\n  }\n  createProgram(fragmentShader) {\n    this.throwIfDisposed();\n    const gl = this.gl;\n    if (this.vertexShader == null) {\n      this.vertexShader = createVertexShader2(gl);\n    }\n    const program = createProgram(gl);\n    callAndCheck(gl, () => gl.attachShader(program, this.vertexShader));\n    callAndCheck(gl, () => gl.attachShader(program, fragmentShader));\n    linkProgram(gl, program);\n    if (this.debug) {\n      validateProgram(gl, program);\n    }\n    if (!this.vertexAttrsAreBound) {\n      this.setProgram(program);\n      this.vertexAttrsAreBound = bindVertexProgramAttributeStreams(gl, this.program, this.vertexBuffer);\n    }\n    return program;\n  }\n  deleteProgram(program) {\n    this.throwIfDisposed();\n    if (program === this.program) {\n      this.program = null;\n    }\n    if (program != null) {\n      callAndCheck(this.gl, () => this.gl.deleteProgram(program));\n    }\n  }\n  setProgram(program) {\n    this.throwIfDisposed();\n    this.program = program;\n    if (this.program != null && this.debug) {\n      validateProgram(this.gl, this.program);\n    }\n    callAndCheck(this.gl, () => this.gl.useProgram(program));\n  }\n  getUniformLocation(program, uniformName, shouldThrow = true) {\n    this.throwIfDisposed();\n    if (shouldThrow) {\n      return getProgramUniformLocationOrThrow(this.gl, program, uniformName);\n    } else {\n      return getProgramUniformLocation(this.gl, program, uniformName);\n    }\n  }\n  getAttributeLocation(program, attribute) {\n    this.throwIfDisposed();\n    return callAndCheck(this.gl, () => this.gl.getAttribLocation(program, attribute));\n  }\n  getUniformLocationNoThrow(program, uniformName) {\n    this.throwIfDisposed();\n    return this.gl.getUniformLocation(program, uniformName);\n  }\n  setInputMatrixTexture(inputMatrixTexture, uniformLocation, textureUnit) {\n    this.throwIfDisposed();\n    this.throwIfNoProgram();\n    bindTextureToProgramUniformSampler(this.gl, inputMatrixTexture, uniformLocation, textureUnit);\n  }\n  setOutputMatrixTexture(outputMatrixTexture, rows, columns) {\n    this.setOutputMatrixTextureDriver(outputMatrixTexture, columns, rows);\n  }\n  setOutputPackedMatrixTexture(outputPackedMatrixTexture, rows, columns) {\n    this.throwIfDisposed();\n    const [width, height] = getPackedMatrixTextureShapeWidthHeight(rows, columns);\n    this.setOutputMatrixTextureDriver(outputPackedMatrixTexture, width, height);\n  }\n  setOutputMatrixWriteRegion(startRow, numRows, startColumn, numColumns) {\n    this.setOutputMatrixWriteRegionDriver(startColumn, startRow, numColumns, numRows);\n  }\n  setOutputPackedMatrixWriteRegion(startRow, numRows, startColumn, numColumns) {\n    throw new Error(\"setOutputPackedMatrixWriteRegion not implemented.\");\n  }\n  debugValidate() {\n    if (this.program != null) {\n      validateProgram(this.gl, this.program);\n    }\n    validateFramebuffer(this.gl);\n  }\n  executeProgram() {\n    this.throwIfDisposed();\n    this.throwIfNoProgram();\n    const gl = this.gl;\n    if (this.debug) {\n      this.debugValidate();\n    }\n    callAndCheck(gl, () => gl.drawElements(gl.TRIANGLES, 6, gl.UNSIGNED_SHORT, 0));\n  }\n  blockUntilAllProgramsCompleted() {\n    this.throwIfDisposed();\n    callAndCheck(this.gl, () => this.gl.finish());\n  }\n  getQueryTimerExtension() {\n    if (this.disjointQueryTimerExtension == null) {\n      this.disjointQueryTimerExtension = getExtensionOrThrow(this.gl, env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\") === 2 ? \"EXT_disjoint_timer_query_webgl2\" : \"EXT_disjoint_timer_query\");\n    }\n    return this.disjointQueryTimerExtension;\n  }\n  getQueryTimerExtensionWebGL2() {\n    return this.getQueryTimerExtension();\n  }\n  getQueryTimerExtensionWebGL1() {\n    return this.getQueryTimerExtension();\n  }\n  beginQuery() {\n    if (env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\") === 2) {\n      const gl2 = this.gl;\n      const ext2 = this.getQueryTimerExtensionWebGL2();\n      const query2 = gl2.createQuery();\n      gl2.beginQuery(ext2.TIME_ELAPSED_EXT, query2);\n      return query2;\n    }\n    const ext = this.getQueryTimerExtensionWebGL1();\n    const query = ext.createQueryEXT();\n    ext.beginQueryEXT(ext.TIME_ELAPSED_EXT, query);\n    return query;\n  }\n  endQuery() {\n    if (env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\") === 2) {\n      const gl2 = this.gl;\n      const ext2 = this.getQueryTimerExtensionWebGL2();\n      gl2.endQuery(ext2.TIME_ELAPSED_EXT);\n      return;\n    }\n    const ext = this.getQueryTimerExtensionWebGL1();\n    ext.endQueryEXT(ext.TIME_ELAPSED_EXT);\n  }\n  async waitForQueryAndGetTime(query) {\n    await util_exports.repeatedTry(() => this.disposed || this.isQueryAvailable(query, env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\")));\n    return this.getQueryTime(query, env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\"));\n  }\n  getQueryTime(query, queryTimerVersion) {\n    if (queryTimerVersion === 0) {\n      return null;\n    }\n    if (queryTimerVersion === 2) {\n      const gl2 = this.gl;\n      const timeElapsedNanos = gl2.getQueryParameter(query, gl2.QUERY_RESULT);\n      return timeElapsedNanos / 1e6;\n    } else {\n      const ext = this.getQueryTimerExtensionWebGL1();\n      const timeElapsedNanos = ext.getQueryObjectEXT(query, ext.QUERY_RESULT_EXT);\n      return timeElapsedNanos / 1e6;\n    }\n  }\n  isQueryAvailable(query, queryTimerVersion) {\n    if (queryTimerVersion === 0) {\n      return true;\n    }\n    if (queryTimerVersion === 2) {\n      const gl2 = this.gl;\n      const ext = this.getQueryTimerExtensionWebGL2();\n      const available = gl2.getQueryParameter(query, gl2.QUERY_RESULT_AVAILABLE);\n      if (this.disjoint == null) {\n        this.disjoint = this.gl.getParameter(ext.GPU_DISJOINT_EXT);\n      }\n      return available && !this.disjoint;\n    } else {\n      const ext = this.getQueryTimerExtensionWebGL1();\n      const available = ext.getQueryObjectEXT(query, ext.QUERY_RESULT_AVAILABLE_EXT);\n      if (this.disjoint == null) {\n        this.disjoint = this.gl.getParameter(ext.GPU_DISJOINT_EXT);\n      }\n      return available && !this.disjoint;\n    }\n  }\n  pollFence(fenceContext) {\n    return new Promise((resolve) => {\n      this.addItemToPoll(() => fenceContext.isFencePassed(), () => resolve());\n    });\n  }\n  pollItems() {\n    const index = linearSearchLastTrue(this.itemsToPoll.map((x) => x.isDoneFn));\n    for (let i2 = 0; i2 <= index; ++i2) {\n      const { resolveFn } = this.itemsToPoll[i2];\n      resolveFn();\n    }\n    this.itemsToPoll = this.itemsToPoll.slice(index + 1);\n  }\n  addItemToPoll(isDoneFn, resolveFn) {\n    this.itemsToPoll.push({ isDoneFn, resolveFn });\n    if (this.itemsToPoll.length > 1) {\n      return;\n    }\n    util_exports.repeatedTry(() => {\n      this.pollItems();\n      return this.itemsToPoll.length === 0;\n    });\n  }\n  bindTextureToFrameBuffer(texture) {\n    this.throwIfDisposed();\n    bindColorTextureToFramebuffer(this.gl, texture, this.framebuffer);\n    if (this.debug) {\n      validateFramebuffer(this.gl);\n    }\n  }\n  unbindTextureToFrameBuffer() {\n    if (this.outputTexture != null) {\n      bindColorTextureToFramebuffer(this.gl, this.outputTexture, this.framebuffer);\n      if (this.debug) {\n        validateFramebuffer(this.gl);\n      }\n    } else {\n      unbindColorTextureFromFramebuffer(this.gl, this.framebuffer);\n    }\n  }\n  downloadMatrixDriver(texture, downloadAndDecode) {\n    this.bindTextureToFrameBuffer(texture);\n    const result = downloadAndDecode();\n    this.unbindTextureToFrameBuffer();\n    return result;\n  }\n  setOutputMatrixTextureDriver(outputMatrixTextureMaybePacked, width, height) {\n    this.throwIfDisposed();\n    const gl = this.gl;\n    bindColorTextureToFramebuffer(gl, outputMatrixTextureMaybePacked, this.framebuffer);\n    if (this.debug) {\n      validateFramebuffer(gl);\n    }\n    this.outputTexture = outputMatrixTextureMaybePacked;\n    callAndCheck(gl, () => gl.viewport(0, 0, width, height));\n    callAndCheck(gl, () => gl.scissor(0, 0, width, height));\n  }\n  setOutputMatrixWriteRegionDriver(x, y, width, height) {\n    this.throwIfDisposed();\n    callAndCheck(this.gl, () => this.gl.scissor(x, y, width, height));\n  }\n  throwIfDisposed() {\n    if (this.disposed) {\n      throw new Error(\"Attempted to use disposed GPGPUContext.\");\n    }\n  }\n  throwIfNoProgram() {\n    if (this.program == null) {\n      throw new Error(\"No GPU program is currently set.\");\n    }\n  }\n};\nfunction linearSearchLastTrue(arr) {\n  let i2 = 0;\n  for (; i2 < arr.length; ++i2) {\n    const isDone = arr[i2]();\n    if (!isDone) {\n      break;\n    }\n  }\n  return i2 - 1;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/shared.js\nvar { addImpl: addImplCPU, bincountImpl: bincountImplCPU, bincountReduceImpl: bincountReduceImplCPU, ceilImpl: ceilImplCPU, concatImpl: concatImplCPU, equalImpl: equalImplCPU, expImpl: expImplCPU, expm1Impl: expm1ImplCPU, floorImpl: floorImplCPU, gatherNdImpl: gatherNdImplCPU, gatherV2Impl: gatherV2ImplCPU, greaterImpl: greaterImplCPU, greaterEqualImpl: greaterEqualImplCPU, lessImpl: lessImplCPU, lessEqualImpl: lessEqualImplCPU, linSpaceImpl: linSpaceImplCPU, logImpl: logImplCPU, maxImpl: maxImplCPU, maximumImpl: maximumImplCPU, minimumImpl: minimumImplCPU, multiplyImpl: multiplyImplCPU, negImpl: negImplCPU, notEqualImpl: notEqualImplCPU, prodImpl: prodImplCPU, rangeImpl: rangeImplCPU, rsqrtImpl: rsqrtImplCPU, scatterImpl: scatterImplCPU, sigmoidImpl: sigmoidImplCPU, simpleAbsImpl: simpleAbsImplCPU, sliceImpl: sliceImplCPU, sparseFillEmptyRowsImpl: sparseFillEmptyRowsImplCPU, sparseReshapeImpl: sparseReshapeImplCPU, sparseSegmentReductionImpl: sparseSegmentReductionImplCPU, sqrtImpl: sqrtImplCPU, stridedSliceImpl: stridedSliceImplCPU, stringNGramsImpl: stringNGramsImplCPU, stringSplitImpl: stringSplitImplCPU, stringToHashBucketFastImpl: stringToHashBucketFastImplCPU, subImpl: subImplCPU, tileImpl: tileImplCPU, topKImpl: topKImplCPU, transposeImpl: transposeImplCPU, uniqueImpl: uniqueImplCPU } = shared_exports;\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/packing_util.js\nfunction getVecChannels(name, rank) {\n  return [\"x\", \"y\", \"z\", \"w\", \"u\", \"v\"].slice(0, rank).map((d) => `${name}.${d}`);\n}\nfunction getChannels(name, rank) {\n  if (rank === 1) {\n    return [name];\n  }\n  return getVecChannels(name, rank);\n}\nfunction getSourceCoords(rank, dims) {\n  if (rank === 1) {\n    return \"rc\";\n  }\n  let coords3 = \"\";\n  for (let i2 = 0; i2 < rank; i2++) {\n    coords3 += dims[i2];\n    if (i2 < rank - 1) {\n      coords3 += \",\";\n    }\n  }\n  return coords3;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/pack_gpu.js\nvar PackProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = false;\n    this.packedOutput = true;\n    this.outputShape = outputShape;\n    this.rank = outputShape.length;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    if (this.rank === 0) {\n      this.userCode = `\n        void main() {\n          setOutput(vec4(getA(), 0., 0., 0.));\n        }\n      `;\n    } else {\n      const channels = getChannels(\"rc\", this.rank);\n      const dtype = getCoordsDataType(this.rank);\n      const outOfBoundsCondition = this.getOutOfBoundsCondition(channels);\n      const setup51 = this.getSetup(channels);\n      const output = this.getOutput(channels);\n      this.userCode = `\n        void main() {\n          ${dtype} rc = getOutputCoords();\n\n          if(${outOfBoundsCondition}) {\n            setOutput(vec4(0));\n          } else {\n            ${setup51}\n\n            setOutput(vec4(${output}));\n          }\n        }\n      `;\n    }\n  }\n  getSourceCoordsArr(dims) {\n    const coords3 = [];\n    for (let row = 0; row <= 1; row++) {\n      for (let col = 0; col <= 1; col++) {\n        let coord = `${row === 0 ? \"r\" : \"rp1\"}, ${col === 0 ? \"c\" : \"cp1\"}`;\n        for (let d = 2; d < this.rank; d++) {\n          coord = `${dims[dims.length - 1 - d]},` + coord;\n        }\n        coords3.push(coord);\n      }\n    }\n    return coords3;\n  }\n  getOutOfBoundsCondition(dims) {\n    if (this.rank === 1) {\n      return `rc > ${this.enableShapeUniforms ? \"outShape\" : this.outputShape[0]}`;\n    }\n    let cond = \"\";\n    for (let i2 = this.rank - 2; i2 < this.rank; i2++) {\n      cond += `${dims[i2]} >= ${this.enableShapeUniforms ? `outShape[${i2}]` : this.outputShape[i2]}`;\n      if (i2 < this.rank - 1) {\n        cond += \"||\";\n      }\n    }\n    return cond;\n  }\n  getSetup(dims) {\n    if (this.rank === 1) {\n      return \"\";\n    }\n    const innerDims = dims.slice(-2);\n    const col = this.enableShapeUniforms ? `outShape[${this.rank} - 1]` : this.outputShape[this.rank - 1];\n    const row = this.enableShapeUniforms ? `outShape[${this.rank} - 2]` : this.outputShape[this.rank - 2];\n    return `\n      int r = ${innerDims[0]};\n      int c = ${innerDims[1]};\n      int rp1 = r + 1;\n      int cp1 = c + 1;\n\n      bool cEdge = cp1 >= ${col};\n      bool rEdge = rp1 >= ${row};\n    `;\n  }\n  getOutput(dims) {\n    const sourceCoords = this.getSourceCoordsArr(dims);\n    if (this.rank === 1) {\n      const outShape = this.enableShapeUniforms ? \"outShape\" : this.outputShape[0];\n      return `getA(rc), (rc + 1 >= ${outShape} ? 0. : getA(rc + 1)), 0, 0`;\n    }\n    return `getA(${sourceCoords[0]}),\n            cEdge ? 0. : getA(${sourceCoords[1]}),\n            rEdge ? 0. : getA(${sourceCoords[2]}),\n            rEdge || cEdge ? 0. : getA(${sourceCoords[3]})`;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/reshape_packed_gpu.js\nvar ReshapePackedProgram = class {\n  constructor(outputShape, inputShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.customUniforms = [{ name: \"inputShape\", type: \"ivec3\" }];\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    let mainLoop = ``;\n    for (let i2 = 0; i2 < 4; i2++) {\n      let thisRC = `thisRC = rc;`;\n      if (i2 % 2 === 1) {\n        thisRC += `thisRC.z += 1;`;\n      }\n      if (i2 > 1) {\n        thisRC += `thisRC.y += 1;`;\n      }\n      mainLoop += `\n        ${thisRC}\n        ${i2 > 0 ? `if(thisRC.y < rows && thisRC.z < cols){` : \"\"}\n          int flatIndex = getFlatIndex(thisRC);\n\n          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);\n          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));\n\n          result[${i2}] =\n            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);\n        ${i2 > 0 ? \"}\" : \"\"}\n      `;\n    }\n    this.userCode = `\n      ${getReshapedInputCoords(inputShape, this.enableShapeUniforms)}\n      ${this.enableShapeUniforms ? getFlatIndexFrom3DOutput() : getFlatIndexFrom3D(outputShape)}\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n\n        vec4 result = vec4(0.);\n\n        ivec3 thisRC;\n        int rows = ${this.enableShapeUniforms ? \"outShape[1]\" : outputShape[1]};\n        int cols = ${this.enableShapeUniforms ? \"outShape[2]\" : outputShape[2]};\n\n        ${mainLoop}\n\n        setOutput(result);\n      }\n    `;\n  }\n};\nfunction getReshapedInputCoords(shape, enableShapeUniforms) {\n  const coordsFromIndexSnippet = enableShapeUniforms ? getLogicalCoordinatesFromFlatIndexByUniform([\"r\", \"c\", \"d\"], \"inputShape\") : getLogicalCoordinatesFromFlatIndex([\"r\", \"c\", \"d\"], shape);\n  return `\n    ivec3 inputCoordsFromReshapedOutCoords(int index) {\n      ${coordsFromIndexSnippet}\n      return ivec3(r, c, d);\n    }\n  `;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/texture_manager.js\nvar TextureManager = class {\n  constructor(gpgpu) {\n    this.gpgpu = gpgpu;\n    this.numUsedTextures = 0;\n    this.numFreeTextures = 0;\n    this._numBytesAllocated = 0;\n    this._numBytesFree = 0;\n    this.freeTextures = {};\n    this.logEnabled = false;\n    this.usedTextures = {};\n  }\n  acquireTexture(shapeRC, usage, isPacked) {\n    const physicalTexType = getPhysicalFromLogicalTextureType(usage, isPacked);\n    const shapeKey = getKeyFromTextureShape(shapeRC, physicalTexType, isPacked);\n    if (!(shapeKey in this.freeTextures)) {\n      this.freeTextures[shapeKey] = [];\n    }\n    if (!(shapeKey in this.usedTextures)) {\n      this.usedTextures[shapeKey] = [];\n    }\n    const texBytes = computeBytes(shapeRC, physicalTexType, this.gpgpu.gl, this.gpgpu.textureConfig, isPacked);\n    if (this.freeTextures[shapeKey].length > 0) {\n      this.numFreeTextures--;\n      this.numUsedTextures++;\n      this._numBytesFree -= texBytes;\n      this.log();\n      const newTexture2 = this.freeTextures[shapeKey].shift();\n      this.usedTextures[shapeKey].push(newTexture2);\n      return newTexture2;\n    }\n    let newTexture;\n    if (physicalTexType === PhysicalTextureType.PACKED_2X2_FLOAT32) {\n      newTexture = this.gpgpu.createPackedMatrixTexture(shapeRC[0], shapeRC[1]);\n    } else if (physicalTexType === PhysicalTextureType.PACKED_2X2_FLOAT16) {\n      newTexture = this.gpgpu.createFloat16PackedMatrixTexture(shapeRC[0], shapeRC[1]);\n    } else if (physicalTexType === PhysicalTextureType.UNPACKED_FLOAT32) {\n      newTexture = this.gpgpu.createFloat32MatrixTexture(shapeRC[0], shapeRC[1]);\n    } else if (physicalTexType === PhysicalTextureType.UNPACKED_FLOAT16) {\n      newTexture = this.gpgpu.createFloat16MatrixTexture(shapeRC[0], shapeRC[1]);\n    } else if (physicalTexType === PhysicalTextureType.PACKED_4X1_UNSIGNED_BYTE) {\n      newTexture = this.gpgpu.createUnsignedBytesMatrixTexture(shapeRC[0], shapeRC[1]);\n    }\n    this.usedTextures[shapeKey].push(newTexture);\n    this.numUsedTextures++;\n    this._numBytesAllocated += texBytes;\n    this.log();\n    return newTexture;\n  }\n  releaseTexture(texture, shape, logicalTexType, isPacked) {\n    if (this.freeTextures == null) {\n      return;\n    }\n    const physicalTexType = getPhysicalFromLogicalTextureType(logicalTexType, isPacked);\n    const shapeKey = getKeyFromTextureShape(shape, physicalTexType, isPacked);\n    if (!(shapeKey in this.freeTextures)) {\n      this.freeTextures[shapeKey] = [];\n    }\n    const texBytes = computeBytes(shape, physicalTexType, this.gpgpu.gl, this.gpgpu.textureConfig, isPacked);\n    const deleteTexThreshold = env().get(\"WEBGL_DELETE_TEXTURE_THRESHOLD\");\n    if (deleteTexThreshold !== -1 && this._numBytesAllocated > deleteTexThreshold) {\n      this.gpgpu.deleteMatrixTexture(texture.texture);\n      this._numBytesAllocated -= texBytes;\n    } else {\n      this.freeTextures[shapeKey].push(texture);\n      this.numFreeTextures++;\n      this._numBytesFree += texBytes;\n    }\n    this.numUsedTextures--;\n    const texList = this.usedTextures[shapeKey];\n    const texIndex = texList.indexOf(texture);\n    if (texIndex < 0) {\n      throw new Error(\"Cannot release a texture that was never provided by this texture manager\");\n    }\n    texList.splice(texIndex, 1);\n    this.log();\n  }\n  log() {\n    if (!this.logEnabled) {\n      return;\n    }\n    const total = this.numFreeTextures + this.numUsedTextures;\n    console.log(\"Free/Used\", `${this.numFreeTextures} / ${this.numUsedTextures}`, `(${total})`);\n    const freeRatio = this._numBytesFree / this._numBytesAllocated;\n    console.log(`Bytes allocated: ${this._numBytesAllocated}`);\n    console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100 * freeRatio)}%)`);\n  }\n  get numBytesAllocated() {\n    return this._numBytesAllocated;\n  }\n  get numBytesFree() {\n    return this._numBytesFree;\n  }\n  getNumUsedTextures() {\n    return this.numUsedTextures;\n  }\n  getNumFreeTextures() {\n    return this.numFreeTextures;\n  }\n  dispose() {\n    if (this.freeTextures == null) {\n      return;\n    }\n    for (const texShape in this.freeTextures) {\n      this.freeTextures[texShape].forEach((tex) => {\n        this.gpgpu.deleteMatrixTexture(tex.texture);\n      });\n    }\n    for (const texShape in this.usedTextures) {\n      this.usedTextures[texShape].forEach((tex) => {\n        this.gpgpu.deleteMatrixTexture(tex.texture);\n      });\n    }\n    this.freeTextures = null;\n    this.usedTextures = null;\n    this.numUsedTextures = 0;\n    this.numFreeTextures = 0;\n    this._numBytesAllocated = 0;\n    this._numBytesFree = 0;\n  }\n};\nfunction numBytesForInternalFormat(gl, internalFormat) {\n  const glany = gl;\n  if (internalFormat === glany.R32F) {\n    return 4;\n  } else if (internalFormat === glany.R16F) {\n    return 2;\n  } else if (internalFormat === glany.RGBA32F) {\n    return 16;\n  } else if (internalFormat === gl.RGBA) {\n    return 16;\n  } else if (internalFormat === glany.RGBA16F) {\n    return 8;\n  } else if (internalFormat === glany.RGBA8) {\n    return 4;\n  }\n  throw new Error(`Unknown internal format ${internalFormat}`);\n}\nfunction computeBytes(shape, physicalTexType, gl, textureConfig, isPacked) {\n  const internalFormat = internalFormatForPhysicalTexType(physicalTexType, textureConfig);\n  let numElements;\n  if (isPacked) {\n    const [packedWidth, packedHeight] = getPackedMatrixTextureShapeWidthHeight(shape[0], shape[1]);\n    numElements = packedWidth * packedHeight;\n  } else {\n    const [width, height] = getUnpackedMatrixTextureShapeWidthHeight(shape[0], shape[1]);\n    numElements = width * height;\n  }\n  const bytesPerElement2 = numBytesForInternalFormat(gl, internalFormat);\n  return numElements * bytesPerElement2;\n}\nfunction internalFormatForPhysicalTexType(physicalTexType, textureConfig) {\n  switch (physicalTexType) {\n    case PhysicalTextureType.PACKED_2X2_FLOAT32:\n      return getInternalFormatForPackedMatrixTexture(textureConfig);\n    case PhysicalTextureType.PACKED_2X2_FLOAT16:\n      return getInternalFormatForFloat16PackedMatrixTexture(textureConfig);\n    case PhysicalTextureType.UNPACKED_FLOAT32:\n      return getInternalFormatForFloat32MatrixTexture(textureConfig);\n    case PhysicalTextureType.UNPACKED_FLOAT16:\n      return getInternalFormatForFloat16MatrixTexture(textureConfig);\n    case PhysicalTextureType.PACKED_4X1_UNSIGNED_BYTE:\n      return getInternalFormatForUnsignedBytesMatrixTexture(textureConfig);\n    default:\n      throw new Error(`Unknown physical texture type ${physicalTexType}`);\n  }\n}\nfunction getPhysicalTextureForRendering(isPacked) {\n  if (env().getBool(\"WEBGL_RENDER_FLOAT32_ENABLED\")) {\n    if (isPacked) {\n      return PhysicalTextureType.PACKED_2X2_FLOAT32;\n    }\n    return PhysicalTextureType.UNPACKED_FLOAT32;\n  }\n  if (isPacked) {\n    return PhysicalTextureType.PACKED_2X2_FLOAT16;\n  }\n  return PhysicalTextureType.UNPACKED_FLOAT16;\n}\nfunction getPhysicalFromLogicalTextureType(logicalTexType, isPacked) {\n  if (logicalTexType === TextureUsage.UPLOAD) {\n    return PhysicalTextureType.PACKED_2X2_FLOAT32;\n  } else if (logicalTexType === TextureUsage.RENDER || logicalTexType == null) {\n    return getPhysicalTextureForRendering(isPacked);\n  } else if (logicalTexType === TextureUsage.DOWNLOAD || logicalTexType === TextureUsage.PIXELS) {\n    return PhysicalTextureType.PACKED_4X1_UNSIGNED_BYTE;\n  }\n  throw new Error(`Unknown logical texture type ${logicalTexType}`);\n}\nfunction getKeyFromTextureShape(shapeRowsCol, physicalTexType, isPacked) {\n  return `${shapeRowsCol[0]}_${shapeRowsCol[1]}_${physicalTexType}_${isPacked}`;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/unaryop_gpu.js\nvar UnaryOpProgram = class {\n  constructor(aShape, opSnippet) {\n    this.variableNames = [\"A\"];\n    this.outputShape = aShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    this.userCode = `\n      float unaryOperation(float x) {\n        ${opSnippet}\n      }\n\n      void main() {\n        float x = getAAtOutCoords();\n        float y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    `;\n  }\n};\nvar CHECK_NAN_SNIPPET = `if (isnan(x)) return x;`;\nvar LINEAR = `return x;`;\nvar ABS = `return abs(x);`;\nvar ELU2 = `return (x >= 0.0) ? x : (exp(x) - 1.0);`;\nvar RELU = CHECK_NAN_SNIPPET + `\n  return (x < 0.0) ? 0.0 : x;\n`;\nvar RELU6 = CHECK_NAN_SNIPPET + `\n  return (x < 0.0) ? 0.0 : min(6.0, x);\n`;\nvar CLONE = \"return x;\";\nvar SIGMOID = `return 1.0 / (1.0 + exp(-1.0 * x));`;\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/unaryop_packed_gpu.js\nvar LINEAR2 = `return x;`;\nvar ELU3 = `\n  vec4 result;\n\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\n\n  return result;\n`;\nvar RELU2 = `\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n`;\nvar RELU62 = `\n  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n`;\nvar SIGMOID2 = `return 1.0 / (1.0 + exp(-1.0 * x));`;\nvar UnaryOpPackedProgram = class {\n  constructor(aShape, opSnippet) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = aShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    this.userCode = `\n      vec4 unaryOperation(vec4 x) {\n        ${opSnippet}\n      }\n\n      void main() {\n        vec4 x = getAAtOutCoords();\n        vec4 y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/unpack_gpu.js\nvar UnpackProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = false;\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    const rank = outputShape.length;\n    const channels = getChannels(\"rc\", rank);\n    const dtype = getCoordsDataType(rank);\n    const sourceCoords = getSourceCoords(rank, channels);\n    const innerDims = channels.slice(-2);\n    const coords3 = rank <= 1 ? \"rc\" : `vec2(${innerDims.join(\",\")})`;\n    this.userCode = `\n      void main() {\n        ${dtype} rc = getOutputCoords();\n        vec4 packedInput = getA(${sourceCoords});\n\n        setOutput(getChannel(packedInput, ${coords3}));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/backend_webgl.js\nvar whereImpl3 = kernel_impls_exports.whereImpl;\nvar EPSILON_FLOAT322 = 1e-7;\nvar EPSILON_FLOAT162 = 1e-4;\nvar binaryCaches = {};\nfunction getBinaryCache(webGLVersion) {\n  if (webGLVersion in binaryCaches) {\n    return binaryCaches[webGLVersion];\n  }\n  binaryCaches[webGLVersion] = {};\n  return binaryCaches[webGLVersion];\n}\nvar CPU_HANDOFF_SIZE_THRESHOLD = env().getNumber(\"CPU_HANDOFF_SIZE_THRESHOLD\");\nvar BEFORE_PAGING_CONSTANT = 600;\nfunction numMBBeforeWarning() {\n  if (env().global.screen == null) {\n    return 1024;\n  }\n  return env().global.screen.height * env().global.screen.width * window.devicePixelRatio * BEFORE_PAGING_CONSTANT / 1024 / 1024;\n}\nvar MathBackendWebGL = class extends KernelBackend {\n  constructor(gpuResource) {\n    super();\n    this.pendingRead = /* @__PURE__ */ new WeakMap();\n    this.pendingDisposal = /* @__PURE__ */ new WeakSet();\n    this.dataRefCount = /* @__PURE__ */ new WeakMap();\n    this.numBytesInGPU = 0;\n    this.uploadWaitMs = 0;\n    this.downloadWaitMs = 0;\n    this.lastGlFlushTime = 0;\n    this.warnedAboutMemory = false;\n    this.pendingDeletes = 0;\n    this.disposed = false;\n    if (!env().getBool(\"HAS_WEBGL\")) {\n      throw new Error(\"WebGL is not supported on this device\");\n    }\n    let newGPGPU;\n    if (gpuResource != null) {\n      if (gpuResource instanceof GPGPUContext) {\n        newGPGPU = gpuResource;\n      } else {\n        const gl = getWebGLContext(env().getNumber(\"WEBGL_VERSION\"), gpuResource);\n        newGPGPU = new GPGPUContext(gl);\n      }\n      this.binaryCache = {};\n      this.gpgpuCreatedLocally = false;\n    } else {\n      const gl = getWebGLContext(env().getNumber(\"WEBGL_VERSION\"));\n      newGPGPU = new GPGPUContext(gl);\n      this.binaryCache = getBinaryCache(env().getNumber(\"WEBGL_VERSION\"));\n      this.gpgpuCreatedLocally = true;\n    }\n    this.gpgpu = newGPGPU;\n    this.canvas = this.gpgpu.gl.canvas;\n    this.textureManager = new TextureManager(this.gpgpu);\n    this.numMBBeforeWarning = numMBBeforeWarning();\n    this.texData = new DataStorage(this, engine());\n  }\n  nextDataId() {\n    return MathBackendWebGL.nextDataId++;\n  }\n  numDataIds() {\n    return this.texData.numDataIds() - this.pendingDeletes;\n  }\n  write(values, shape, dtype) {\n    if (env().getBool(\"WEBGL_CHECK_NUMERICAL_PROBLEMS\") || env().getBool(\"DEBUG\")) {\n      this.checkNumericalProblems(values);\n    }\n    if (dtype === \"complex64\" && values != null) {\n      throw new Error(`Cannot write to a complex64 dtype. Please use tf.complex(real, imag).`);\n    }\n    const dataId = { id: this.nextDataId() };\n    this.texData.set(dataId, { shape, dtype, values, usage: TextureUsage.UPLOAD, refCount: 1 });\n    return dataId;\n  }\n  refCount(dataId) {\n    if (this.texData.has(dataId)) {\n      const tensorData = this.texData.get(dataId);\n      return tensorData.refCount;\n    }\n    return 0;\n  }\n  incRef(dataId) {\n    const texData = this.texData.get(dataId);\n    texData.refCount++;\n  }\n  decRef(dataId) {\n    if (this.texData.has(dataId)) {\n      const texData = this.texData.get(dataId);\n      texData.refCount--;\n    }\n  }\n  move(dataId, values, shape, dtype, refCount) {\n    if (env().getBool(\"DEBUG\")) {\n      this.checkNumericalProblems(values);\n    }\n    if (dtype === \"complex64\") {\n      throw new Error(`Cannot write to a complex64 dtype. Please use tf.complex(real, imag).`);\n    }\n    this.texData.set(dataId, { shape, dtype, values, usage: TextureUsage.UPLOAD, refCount });\n  }\n  disposeIntermediateTensorInfo(tensorInfo) {\n    this.disposeData(tensorInfo.dataId);\n  }\n  readSync(dataId) {\n    const texData = this.texData.get(dataId);\n    const { values, dtype, complexTensorInfos, slice: slice6, shape, isPacked } = texData;\n    if (slice6 != null) {\n      let program;\n      if (isPacked) {\n        program = new UnaryOpPackedProgram(shape, CLONE);\n      } else {\n        program = new UnaryOpProgram(shape, CLONE);\n      }\n      const res = this.runWebGLProgram(program, [{ dataId, shape, dtype }], dtype);\n      const data = this.readSync(res.dataId);\n      this.disposeIntermediateTensorInfo(res);\n      return data;\n    }\n    if (values != null) {\n      return this.convertAndCacheOnCPU(dataId);\n    }\n    if (dtype === \"string\") {\n      return values;\n    }\n    const shouldTimeProgram = this.activeTimers != null;\n    let start;\n    if (shouldTimeProgram) {\n      start = util_exports.now();\n    }\n    let result;\n    if (dtype === \"complex64\") {\n      const realValues = this.readSync(complexTensorInfos.real.dataId);\n      const imagValues = this.readSync(complexTensorInfos.imag.dataId);\n      result = backend_util_exports.mergeRealAndImagArrays(realValues, imagValues);\n    } else {\n      result = this.getValuesFromTexture(dataId);\n    }\n    if (shouldTimeProgram) {\n      this.downloadWaitMs += util_exports.now() - start;\n    }\n    return this.convertAndCacheOnCPU(dataId, result);\n  }\n  async read(dataId) {\n    if (this.pendingRead.has(dataId)) {\n      const subscribers2 = this.pendingRead.get(dataId);\n      return new Promise((resolve) => subscribers2.push(resolve));\n    }\n    const texData = this.texData.get(dataId);\n    const { values, shape, slice: slice6, dtype, complexTensorInfos, isPacked } = texData;\n    if (slice6 != null) {\n      let program;\n      if (isPacked) {\n        program = new UnaryOpPackedProgram(shape, CLONE);\n      } else {\n        program = new UnaryOpProgram(shape, CLONE);\n      }\n      const res = this.runWebGLProgram(program, [{ dataId, shape, dtype }], dtype);\n      const data = this.read(res.dataId);\n      this.disposeIntermediateTensorInfo(res);\n      return data;\n    }\n    if (values != null) {\n      return this.convertAndCacheOnCPU(dataId);\n    }\n    if (env().getBool(\"DEBUG\")) {\n      if (!env().getBool(\"WEBGL_DOWNLOAD_FLOAT_ENABLED\") && env().getNumber(\"WEBGL_VERSION\") === 2) {\n        throw new Error(`tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.`);\n      }\n    }\n    let buffer2 = null;\n    let tmpDownloadTarget;\n    if (dtype !== \"complex64\" && env().get(\"WEBGL_BUFFER_SUPPORTED\")) {\n      tmpDownloadTarget = this.decode(dataId);\n      const tmpData = this.texData.get(tmpDownloadTarget.dataId);\n      buffer2 = this.gpgpu.createBufferFromTexture(tmpData.texture.texture, ...getDenseTexShape(shape));\n    }\n    this.pendingRead.set(dataId, []);\n    if (dtype !== \"complex64\") {\n      await this.gpgpu.createAndWaitForFence();\n    }\n    let vals;\n    if (dtype === \"complex64\") {\n      const ps = await Promise.all([\n        this.read(complexTensorInfos.real.dataId),\n        this.read(complexTensorInfos.imag.dataId)\n      ]);\n      const realValues = ps[0];\n      const imagValues = ps[1];\n      vals = backend_util_exports.mergeRealAndImagArrays(realValues, imagValues);\n    } else if (buffer2 == null) {\n      vals = this.getValuesFromTexture(dataId);\n    } else {\n      const size = util_exports.sizeFromShape(shape);\n      vals = this.gpgpu.downloadFloat32MatrixFromBuffer(buffer2, size);\n    }\n    if (tmpDownloadTarget != null) {\n      this.disposeIntermediateTensorInfo(tmpDownloadTarget);\n    }\n    if (buffer2 != null) {\n      const gl = this.gpgpu.gl;\n      callAndCheck(gl, () => gl.deleteBuffer(buffer2));\n    }\n    const dTypeVals = this.convertAndCacheOnCPU(dataId, vals);\n    const subscribers = this.pendingRead.get(dataId);\n    this.pendingRead.delete(dataId);\n    subscribers.forEach((resolve) => resolve(dTypeVals));\n    if (this.pendingDisposal.has(dataId)) {\n      this.pendingDisposal.delete(dataId);\n      if (this.disposeData(dataId)) {\n        engine().removeDataId(dataId, this);\n      }\n      this.pendingDeletes--;\n    }\n    return dTypeVals;\n  }\n  readToGPU(dataId, options = {}) {\n    const texData = this.texData.get(dataId);\n    const { values, shape, slice: slice6, dtype, isPacked, texture } = texData;\n    if (dtype === \"complex64\") {\n      throw new Error(\"Does not support reading texture for complex64 dtype.\");\n    }\n    if (slice6 != null) {\n      let program;\n      if (isPacked) {\n        program = new UnaryOpPackedProgram(shape, CLONE);\n      } else {\n        program = new UnaryOpProgram(shape, CLONE);\n      }\n      const res = this.runWebGLProgram(program, [{ dataId, shape, dtype }], dtype);\n      const gpuResouorce = this.readToGPU(res, options);\n      this.disposeIntermediateTensorInfo(res);\n      return gpuResouorce;\n    }\n    if (texture == null) {\n      if (values != null) {\n        throw new Error(\"Data is not on GPU but on CPU.\");\n      } else {\n        throw new Error(\"There is no data on GPU or CPU.\");\n      }\n    }\n    const tmpTarget = this.decode(dataId, options.customTexShape);\n    const tensorRef = engine().makeTensorFromTensorInfo(tmpTarget);\n    const tmpData = this.texData.get(tmpTarget.dataId);\n    return Object.assign({ tensorRef }, tmpData.texture);\n  }\n  bufferSync(t2) {\n    const data = this.readSync(t2.dataId);\n    if (t2.dtype === \"string\") {\n      try {\n        const strings = data.map((d) => util_exports.decodeString(d));\n        return buffer(t2.shape, t2.dtype, strings);\n      } catch (_a) {\n        throw new Error(\"Failed to decode encoded string bytes into utf-8\");\n      }\n    }\n    return buffer(t2.shape, t2.dtype, data);\n  }\n  checkNumericalProblems(values) {\n    if (values == null) {\n      return;\n    }\n    for (let i2 = 0; i2 < values.length; i2++) {\n      const num = values[i2];\n      if (!canBeRepresented(num)) {\n        if (env().getBool(\"WEBGL_RENDER_FLOAT32_CAPABLE\")) {\n          throw Error(`The value ${num} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`);\n        }\n        throw Error(`The value ${num} cannot be represented on this device.`);\n      }\n    }\n  }\n  getValuesFromTexture(dataId) {\n    const { shape, dtype, isPacked } = this.texData.get(dataId);\n    const size = util_exports.sizeFromShape(shape);\n    if (env().getBool(\"WEBGL_DOWNLOAD_FLOAT_ENABLED\")) {\n      const tmpTarget = this.decode(dataId);\n      const tmpData2 = this.texData.get(tmpTarget.dataId);\n      const vals2 = this.gpgpu.downloadMatrixFromPackedTexture(tmpData2.texture.texture, ...getDenseTexShape(shape)).subarray(0, size);\n      this.disposeIntermediateTensorInfo(tmpTarget);\n      return vals2;\n    }\n    const shouldUsePackedProgram = env().getBool(\"WEBGL_PACK\") && isPacked === true;\n    const outputShape = shouldUsePackedProgram ? getShapeAs3D(shape) : shape;\n    const program = shouldUsePackedProgram ? new EncodeFloatPackedProgram(outputShape) : new EncodeFloatProgram(outputShape);\n    const output = this.runWebGLProgram(program, [{ shape: outputShape, dtype, dataId }], \"float32\");\n    const tmpData = this.texData.get(output.dataId);\n    const vals = this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(tmpData.texture.texture, tmpData.texShape[0], tmpData.texShape[1]).subarray(0, size);\n    this.disposeIntermediateTensorInfo(output);\n    return vals;\n  }\n  timerAvailable() {\n    return env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\") > 0;\n  }\n  time(f) {\n    const oldActiveTimers = this.activeTimers;\n    const newActiveTimers = [];\n    let outerMostTime = false;\n    if (this.programTimersStack == null) {\n      this.programTimersStack = newActiveTimers;\n      outerMostTime = true;\n    } else {\n      this.activeTimers.push(newActiveTimers);\n    }\n    this.activeTimers = newActiveTimers;\n    f();\n    const flattenedActiveTimerQueries = util_exports.flatten(this.activeTimers.map((d) => d.query)).filter((d) => d != null);\n    const flattenedActiveTimerNames = util_exports.flatten(this.activeTimers.map((d) => d.name)).filter((d) => d != null);\n    this.activeTimers = oldActiveTimers;\n    if (outerMostTime) {\n      this.programTimersStack = null;\n    }\n    const res = {\n      uploadWaitMs: this.uploadWaitMs,\n      downloadWaitMs: this.downloadWaitMs,\n      kernelMs: null,\n      wallMs: null\n    };\n    return (async () => {\n      if (env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\") > 0) {\n        const kernelMs = await Promise.all(flattenedActiveTimerQueries);\n        res[\"kernelMs\"] = util_exports.sum(kernelMs);\n        res[\"getExtraProfileInfo\"] = () => kernelMs.map((d, i2) => ({ name: flattenedActiveTimerNames[i2], ms: d })).map((d) => `${d.name}: ${d.ms}`).join(\", \");\n      } else {\n        res[\"kernelMs\"] = {\n          error: \"WebGL query timers are not supported in this environment.\"\n        };\n      }\n      this.uploadWaitMs = 0;\n      this.downloadWaitMs = 0;\n      return res;\n    })();\n  }\n  memory() {\n    return {\n      unreliable: false,\n      numBytesInGPU: this.numBytesInGPU,\n      numBytesInGPUAllocated: this.textureManager.numBytesAllocated,\n      numBytesInGPUFree: this.textureManager.numBytesFree\n    };\n  }\n  startTimer() {\n    if (env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\") > 0) {\n      return this.gpgpu.beginQuery();\n    }\n    return { startMs: util_exports.now(), endMs: null };\n  }\n  endTimer(query) {\n    if (env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\") > 0) {\n      this.gpgpu.endQuery();\n      return query;\n    }\n    query.endMs = util_exports.now();\n    return query;\n  }\n  async getQueryTime(query) {\n    if (env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\") > 0) {\n      return this.gpgpu.waitForQueryAndGetTime(query);\n    }\n    const timerQuery = query;\n    return timerQuery.endMs - timerQuery.startMs;\n  }\n  disposeData(dataId, force = false) {\n    if (this.pendingDisposal.has(dataId)) {\n      return false;\n    }\n    if (!this.texData.has(dataId)) {\n      return true;\n    }\n    if (force) {\n      this.texData.get(dataId).refCount = 0;\n    } else {\n      this.texData.get(dataId).refCount--;\n    }\n    if (!force && this.texData.get(dataId).refCount > 0) {\n      return false;\n    }\n    if (this.pendingRead.has(dataId)) {\n      this.pendingDisposal.add(dataId);\n      this.pendingDeletes++;\n      return false;\n    }\n    this.releaseGPUData(dataId);\n    const { complexTensorInfos } = this.texData.get(dataId);\n    if (complexTensorInfos != null) {\n      this.disposeData(complexTensorInfos.real.dataId, force);\n      this.disposeData(complexTensorInfos.imag.dataId, force);\n    }\n    this.texData.delete(dataId);\n    return true;\n  }\n  releaseGPUData(dataId) {\n    const { texture, dtype, texShape, usage, isPacked, slice: slice6 } = this.texData.get(dataId);\n    const key = slice6 && slice6.origDataId || dataId;\n    const refCount = this.dataRefCount.get(key);\n    if (refCount > 1) {\n      this.dataRefCount.set(key, refCount - 1);\n    } else {\n      this.dataRefCount.delete(key);\n      if (texture != null) {\n        this.numBytesInGPU -= this.computeBytes(texShape, dtype);\n        this.textureManager.releaseTexture(texture, texShape, usage, isPacked);\n      }\n    }\n    const texData = this.texData.get(dataId);\n    texData.texture = null;\n    texData.texShape = null;\n    texData.isPacked = false;\n    texData.slice = null;\n  }\n  getTexture(dataId) {\n    this.uploadToGPU(dataId);\n    return this.texData.get(dataId).texture.texture;\n  }\n  getDataInfo(dataId) {\n    return this.texData.get(dataId);\n  }\n  shouldExecuteOnCPU(inputs, sizeThreshold = CPU_HANDOFF_SIZE_THRESHOLD) {\n    return env().getBool(\"WEBGL_CPU_FORWARD\") && inputs.every((input2) => this.texData.get(input2.dataId).texture == null && util_exports.sizeFromShape(input2.shape) < sizeThreshold);\n  }\n  getGPGPUContext() {\n    return this.gpgpu;\n  }\n  where(condition) {\n    backend_util_exports.warn(\"tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead\");\n    const condVals = condition.dataSync();\n    return whereImpl3(condition.shape, condVals);\n  }\n  packedUnaryOp(x, op2, dtype) {\n    const program = new UnaryOpPackedProgram(x.shape, op2);\n    const outInfo = this.compileAndRun(program, [x], dtype);\n    return engine().makeTensorFromTensorInfo(outInfo);\n  }\n  abs(x) {\n    if (this.shouldExecuteOnCPU([x]) && x.dtype !== \"complex64\") {\n      const outValues = simpleAbsImplCPU(this.texData.get(x.dataId).values);\n      return this.makeOutput(x.shape, x.dtype, outValues);\n    }\n    if (env().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\")) {\n      return this.packedUnaryOp(x, ABS, x.dtype);\n    }\n    const program = new UnaryOpProgram(x.shape, ABS);\n    const outInfo = this.compileAndRun(program, [x]);\n    return engine().makeTensorFromTensorInfo(outInfo);\n  }\n  makeTensorInfo(shape, dtype, values) {\n    let dataId;\n    if (dtype === \"string\" && values != null && values.length > 0 && util_exports.isString(values[0])) {\n      const encodedValues = values.map((d) => util_exports.encodeString(d));\n      dataId = this.write(encodedValues, shape, dtype);\n    } else {\n      dataId = this.write(values, shape, dtype);\n    }\n    this.texData.get(dataId).usage = null;\n    return { dataId, shape, dtype };\n  }\n  makeOutput(shape, dtype, values) {\n    return engine().makeTensorFromTensorInfo(this.makeTensorInfo(shape, dtype, values), this);\n  }\n  unpackTensor(input2) {\n    const program = new UnpackProgram(input2.shape);\n    return this.runWebGLProgram(program, [input2], input2.dtype);\n  }\n  packTensor(input2) {\n    const program = new PackProgram(input2.shape);\n    const preventEagerUnpackingOutput = true;\n    return this.runWebGLProgram(program, [input2], input2.dtype, null, preventEagerUnpackingOutput);\n  }\n  packedReshape(input2, afterShape) {\n    const input3DShape = [\n      getBatchDim(input2.shape),\n      ...getRowsCols(input2.shape)\n    ];\n    const input3D = {\n      dtype: input2.dtype,\n      shape: input3DShape,\n      dataId: input2.dataId\n    };\n    const afterShapeAs3D = [\n      getBatchDim(afterShape),\n      ...getRowsCols(afterShape)\n    ];\n    const program = new ReshapePackedProgram(afterShapeAs3D, input3DShape);\n    const preventEagerUnpackingOfOutput = true;\n    const customValues = [input3DShape];\n    const output = this.runWebGLProgram(program, [input3D], input2.dtype, customValues, preventEagerUnpackingOfOutput);\n    return { dataId: output.dataId, shape: afterShape, dtype: output.dtype };\n  }\n  decode(dataId, customTexShape) {\n    const texData = this.texData.get(dataId);\n    const { isPacked, shape, dtype } = texData;\n    if (customTexShape != null) {\n      const size = util_exports.sizeFromShape(shape);\n      const texSize = customTexShape[0] * customTexShape[1] * 4;\n      util_exports.assert(size <= texSize, () => \"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.\");\n    }\n    const shapeAs3D = getShapeAs3D(shape);\n    let program;\n    if (isPacked) {\n      program = new DecodeMatrixPackedProgram(shapeAs3D);\n    } else {\n      program = new DecodeMatrixProgram(shapeAs3D);\n    }\n    const preventEagerUnpackingOfOutput = true;\n    const customValues = [customTexShape != null ? customTexShape : getDenseTexShape(shapeAs3D)];\n    const out = this.runWebGLProgram(program, [{ shape: shapeAs3D, dtype, dataId }], dtype, customValues, preventEagerUnpackingOfOutput, customTexShape);\n    return { dtype, shape, dataId: out.dataId };\n  }\n  runWebGLProgram(program, inputs, outputDtype, customUniformValues, preventEagerUnpackingOfOutput = false, customTexShape) {\n    const output = this.makeTensorInfo(program.outputShape, outputDtype);\n    const outData = this.texData.get(output.dataId);\n    if (program.packedOutput) {\n      outData.isPacked = true;\n    }\n    if (program.outPackingScheme === PackingScheme.DENSE) {\n      const texelShape = customTexShape != null ? customTexShape : getDenseTexShape(program.outputShape);\n      outData.texShape = texelShape.map((d) => d * 2);\n    }\n    if (program.outTexUsage != null) {\n      outData.usage = program.outTexUsage;\n    }\n    if (util_exports.sizeFromShape(output.shape) === 0) {\n      outData.values = util_exports.getTypedArrayFromDType(output.dtype, 0);\n      return output;\n    }\n    const dataToDispose = [];\n    const inputsData = inputs.map((input2) => {\n      if (input2.dtype === \"complex64\") {\n        throw new Error(`GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.`);\n      }\n      let texData = this.texData.get(input2.dataId);\n      if (texData.texture == null) {\n        if (!program.packedInputs && util_exports.sizeFromShape(input2.shape) <= env().getNumber(\"WEBGL_SIZE_UPLOAD_UNIFORM\")) {\n          return {\n            shape: input2.shape,\n            texData: null,\n            isUniform: true,\n            uniformValues: texData.values\n          };\n        }\n        if (program.packedInputs) {\n          texData.isPacked = true;\n          texData.shape = input2.shape;\n        }\n      }\n      this.uploadToGPU(input2.dataId);\n      if (!!texData.isPacked !== !!program.packedInputs) {\n        input2 = texData.isPacked ? this.unpackTensor(input2) : this.packTensor(input2);\n        dataToDispose.push(input2);\n        texData = this.texData.get(input2.dataId);\n      } else if (texData.isPacked && !isReshapeFree(texData.shape, input2.shape)) {\n        const savedInput = input2;\n        const targetShape = input2.shape;\n        input2.shape = texData.shape;\n        input2 = this.packedReshape(input2, targetShape);\n        dataToDispose.push(input2);\n        texData = this.texData.get(input2.dataId);\n        savedInput.shape = targetShape;\n      }\n      return { shape: input2.shape, texData, isUniform: false };\n    });\n    this.uploadToGPU(output.dataId);\n    const outputData = { shape: output.shape, texData: outData, isUniform: false };\n    const key = makeShaderKey(program, inputsData, outputData);\n    const binary = this.getAndSaveBinary(key, () => {\n      return compileProgram(this.gpgpu, program, inputsData, outputData);\n    });\n    const shouldTimeProgram = this.activeTimers != null;\n    let query;\n    if (shouldTimeProgram) {\n      query = this.startTimer();\n    }\n    if (!env().get(\"ENGINE_COMPILE_ONLY\")) {\n      runProgram(this.gpgpu, binary, inputsData, outputData, customUniformValues);\n    }\n    dataToDispose.forEach((info) => this.disposeIntermediateTensorInfo(info));\n    if (shouldTimeProgram) {\n      query = this.endTimer(query);\n      this.activeTimers.push({ name: program.constructor.name, query: this.getQueryTime(query) });\n    }\n    const glFlushThreshold = env().get(\"WEBGL_FLUSH_THRESHOLD\");\n    if (glFlushThreshold > 0) {\n      const time2 = util_exports.now();\n      if (time2 - this.lastGlFlushTime > glFlushThreshold) {\n        this.gpgpu.gl.flush();\n        this.lastGlFlushTime = time2;\n      }\n    }\n    if (!env().getBool(\"WEBGL_LAZILY_UNPACK\") && outData.isPacked && preventEagerUnpackingOfOutput === false) {\n      const unpacked = this.unpackTensor(output);\n      this.disposeIntermediateTensorInfo(output);\n      return unpacked;\n    }\n    return output;\n  }\n  compileAndRun(program, inputs, outputDtype, customUniformValues, preventEagerUnpackingOfOutput = false) {\n    outputDtype = outputDtype || inputs[0].dtype;\n    const outInfo = this.runWebGLProgram(program, inputs, outputDtype, customUniformValues, preventEagerUnpackingOfOutput);\n    return outInfo;\n  }\n  getAndSaveBinary(key, getBinary) {\n    if (!(key in this.binaryCache)) {\n      this.binaryCache[key] = getBinary();\n    }\n    return this.binaryCache[key];\n  }\n  getTextureManager() {\n    return this.textureManager;\n  }\n  dispose() {\n    if (this.disposed) {\n      return;\n    }\n    if (!env().getBool(\"IS_TEST\")) {\n      const allKeys = Object.keys(this.binaryCache);\n      allKeys.forEach((key) => {\n        this.gpgpu.deleteProgram(this.binaryCache[key].webGLProgram);\n        delete this.binaryCache[key];\n      });\n    }\n    this.textureManager.dispose();\n    if (this.canvas != null && (typeof HTMLCanvasElement !== \"undefined\" && this.canvas instanceof HTMLCanvasElement)) {\n      this.canvas.remove();\n    } else {\n      this.canvas = null;\n    }\n    if (this.gpgpuCreatedLocally) {\n      this.gpgpu.program = null;\n      this.gpgpu.dispose();\n    }\n    this.disposed = true;\n  }\n  floatPrecision() {\n    if (this.floatPrecisionValue == null) {\n      this.floatPrecisionValue = tidy(() => {\n        if (!env().get(\"WEBGL_RENDER_FLOAT32_ENABLED\")) {\n          const debugFlag = env().getBool(\"DEBUG\");\n          env().set(\"DEBUG\", false);\n          const underflowCheckValue = this.abs(scalar(1e-8)).dataSync()[0];\n          env().set(\"DEBUG\", debugFlag);\n          if (underflowCheckValue > 0) {\n            return 32;\n          }\n        }\n        return 16;\n      });\n    }\n    return this.floatPrecisionValue;\n  }\n  epsilon() {\n    return this.floatPrecision() === 32 ? EPSILON_FLOAT322 : EPSILON_FLOAT162;\n  }\n  uploadToGPU(dataId) {\n    const texData = this.texData.get(dataId);\n    const { shape, dtype, values, texture, usage, isPacked } = texData;\n    if (texture != null) {\n      return;\n    }\n    const shouldTimeProgram = this.activeTimers != null;\n    let start;\n    if (shouldTimeProgram) {\n      start = util_exports.now();\n    }\n    let texShape = texData.texShape;\n    if (texShape == null) {\n      texShape = getTextureShapeFromLogicalShape(shape, isPacked);\n      texData.texShape = texShape;\n    }\n    if (values != null) {\n      const shapeAs3D = getShapeAs3D(shape);\n      let program;\n      let width = texShape[1], height = texShape[0];\n      const isByteArray = values instanceof Uint8Array || values instanceof Uint8ClampedArray;\n      if (isPacked || !isByteArray) {\n        [width, height] = getPackedMatrixTextureShapeWidthHeight(texShape[0], texShape[1]);\n      }\n      if (isPacked) {\n        program = new EncodeMatrixPackedProgram(shapeAs3D, isByteArray);\n      } else {\n        program = new EncodeMatrixProgram(shapeAs3D, isByteArray);\n      }\n      const tempDenseInputTexShape = isByteArray ? [height, width] : texShape;\n      const tempDenseInputHandle = this.makeTensorInfo(tempDenseInputTexShape, dtype);\n      const tempDenseInputTexData = this.texData.get(tempDenseInputHandle.dataId);\n      if (isByteArray) {\n        tempDenseInputTexData.usage = TextureUsage.PIXELS;\n      } else {\n        tempDenseInputTexData.usage = TextureUsage.UPLOAD;\n      }\n      tempDenseInputTexData.texShape = tempDenseInputTexShape;\n      this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(tempDenseInputHandle.dataId), width, height, values);\n      const customValues = [[height, width]];\n      const preventEagerUnpacking = true;\n      const encodedOutputTarget = this.runWebGLProgram(program, [tempDenseInputHandle], dtype, customValues, preventEagerUnpacking);\n      const outputTexData = this.texData.get(encodedOutputTarget.dataId);\n      texData.texShape = outputTexData.texShape;\n      texData.isPacked = outputTexData.isPacked;\n      texData.usage = outputTexData.usage;\n      if (!env().get(\"ENGINE_COMPILE_ONLY\")) {\n        texData.texture = outputTexData.texture;\n        texData.values = null;\n        this.texData.delete(encodedOutputTarget.dataId);\n      } else {\n        this.disposeData(encodedOutputTarget.dataId);\n      }\n      this.disposeIntermediateTensorInfo(tempDenseInputHandle);\n      if (shouldTimeProgram) {\n        this.uploadWaitMs += util_exports.now() - start;\n      }\n    } else {\n      const newTexture = this.acquireTexture(texShape, usage, dtype, isPacked);\n      texData.texture = newTexture;\n    }\n  }\n  convertAndCacheOnCPU(dataId, float32Values) {\n    const texData = this.texData.get(dataId);\n    const { dtype } = texData;\n    this.releaseGPUData(dataId);\n    if (float32Values != null) {\n      texData.values = float32ToTypedArray(float32Values, dtype);\n    }\n    return texData.values;\n  }\n  acquireTexture(texShape, texType, dtype, isPacked) {\n    this.numBytesInGPU += this.computeBytes(texShape, dtype);\n    if (!this.warnedAboutMemory && this.numBytesInGPU > this.numMBBeforeWarning * 1024 * 1024) {\n      const mb = (this.numBytesInGPU / 1024 / 1024).toFixed(2);\n      this.warnedAboutMemory = true;\n      console.warn(`High memory usage in GPU: ${mb} MB, most likely due to a memory leak`);\n    }\n    return this.textureManager.acquireTexture(texShape, texType, isPacked);\n  }\n  computeBytes(shape, dtype) {\n    return shape[0] * shape[1] * util_exports.bytesPerElement(dtype);\n  }\n  checkCompileCompletion() {\n    for (const [, binary] of Object.entries(this.binaryCache)) {\n      this.checkCompletion_(binary);\n    }\n  }\n  async checkCompileCompletionAsync() {\n    const ps = [];\n    if (this.gpgpu.parallelCompilationExtension) {\n      for (const [, binary] of Object.entries(this.binaryCache)) {\n        ps.push(this.checkCompletionAsync_(binary));\n      }\n      return Promise.all(ps);\n    } else {\n      for (const [, binary] of Object.entries(this.binaryCache)) {\n        const p2 = new Promise((resolve) => {\n          try {\n            this.checkCompletion_(binary);\n            resolve(true);\n          } catch (error) {\n            throw error;\n          }\n        });\n        ps.push(p2);\n      }\n      return Promise.all(ps);\n    }\n  }\n  async checkCompletionAsync_(binary) {\n    if (this.gpgpu.gl.getProgramParameter(binary.webGLProgram, this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)) {\n      return this.checkCompletion_(binary);\n    } else {\n      await nextFrame();\n      return this.checkCompletionAsync_(binary);\n    }\n  }\n  checkCompletion_(binary) {\n    if (this.gpgpu.gl.getProgramParameter(binary.webGLProgram, this.gpgpu.gl.LINK_STATUS) === false) {\n      console.log(this.gpgpu.gl.getProgramInfoLog(binary.webGLProgram));\n      if (this.gpgpu.gl.getShaderParameter(binary.fragmentShader, this.gpgpu.gl.COMPILE_STATUS) === false) {\n        logShaderSourceAndInfoLog(binary.source, this.gpgpu.gl.getShaderInfoLog(binary.fragmentShader));\n        throw new Error(\"Failed to compile fragment shader.\");\n      }\n      throw new Error(\"Failed to link vertex and fragment shaders.\");\n    }\n    return true;\n  }\n  getUniformLocations() {\n    for (const [, binary] of Object.entries(this.binaryCache)) {\n      const { uniformLocations, customUniformLocations, infLoc, nanLoc, inShapesLocations, inTexShapesLocations, outShapeLocation, outShapeStridesLocation, outTexShapeLocation } = getUniformLocations(this.gpgpu, binary.program, binary.webGLProgram);\n      binary.uniformLocations = uniformLocations;\n      binary.customUniformLocations = customUniformLocations;\n      binary.infLoc = infLoc;\n      binary.nanLoc = nanLoc;\n      binary.inShapesLocations = inShapesLocations;\n      binary.inTexShapesLocations = inTexShapesLocations;\n      binary.outShapeLocation = outShapeLocation;\n      binary.outShapeStridesLocation = outShapeStridesLocation;\n      binary.outTexShapeLocation = outTexShapeLocation;\n    }\n  }\n};\nMathBackendWebGL.nextDataId = 0;\nfunction float32ToTypedArray(a, dtype) {\n  if (dtype === \"float32\" || dtype === \"complex64\") {\n    return a;\n  } else if (dtype === \"int32\" || dtype === \"bool\") {\n    const result = dtype === \"int32\" ? new Int32Array(a.length) : new Uint8Array(a.length);\n    for (let i2 = 0; i2 < result.length; ++i2) {\n      result[i2] = Math.round(a[i2]);\n    }\n    return result;\n  } else {\n    throw new Error(`Unknown dtype ${dtype}`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/version.js\nvar version6 = \"3.19.0\";\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/webgl.js\nfunction forceHalfFloat() {\n  env().set(\"WEBGL_FORCE_F16_TEXTURES\", true);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/base.js\nif (device_util_exports.isBrowser()) {\n  registerBackend(\"webgl\", () => new MathBackendWebGL(), 2);\n}\nvar webgl = { forceHalfFloat };\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/binaryop_gpu.js\nvar CHECK_NAN_SNIPPET2 = `\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n`;\nvar BinaryOpProgram = class {\n  constructor(op2, aShape, bShape) {\n    this.variableNames = [\"A\", \"B\"];\n    this.outputShape = backend_util_exports.assertAndGetBroadcastShape(aShape, bShape);\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    this.userCode = `\n      float binaryOperation(float a, float b) {\n        ${op2}\n      }\n\n      void main() {\n        float a = getAAtOutCoords();\n        float b = getBAtOutCoords();\n        setOutput(binaryOperation(a, b));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/binaryop_packed_gpu.js\nvar CHECK_NAN_SNIPPET3 = `\n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n`;\nvar BinaryOpPackedProgram = class {\n  constructor(op2, aShape, bShape, checkOutOfBounds = false) {\n    this.variableNames = [\"A\", \"B\"];\n    this.supportsBroadcasting = true;\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = backend_util_exports.assertAndGetBroadcastShape(aShape, bShape);\n    const rank = this.outputShape.length;\n    this.enableShapeUniforms = useShapeUniforms(rank);\n    let checkOutOfBoundsString = \"\";\n    if (checkOutOfBounds) {\n      if (rank === 0 || util_exports.sizeFromShape(this.outputShape) === 1) {\n        checkOutOfBoundsString = `\n          result.y = 0.;\n          result.z = 0.;\n          result.w = 0.;\n        `;\n      } else {\n        const dtype = getCoordsDataType(rank);\n        checkOutOfBoundsString = `\n          ${dtype} coords = getOutputCoords();\n        `;\n        if (rank === 1) {\n          if (this.enableShapeUniforms) {\n            checkOutOfBoundsString += `\n            result.y = (coords + 1) >= outShape ? 0. : result.y;\n            result.z = 0.;\n            result.w = 0.;\n          `;\n          } else {\n            checkOutOfBoundsString += `\n            result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;\n            result.z = 0.;\n            result.w = 0.;\n          `;\n          }\n        } else {\n          const channels = getChannels(\"coords\", rank);\n          if (this.enableShapeUniforms) {\n            checkOutOfBoundsString += `\n            bool nextRowOutOfBounds =\n              (${channels[rank - 2]} + 1) >= outShape[${rank} - 2];\n            bool nextColOutOfBounds =\n              (${channels[rank - 1]} + 1) >= outShape[${rank} - 1];\n            result.y = nextColOutOfBounds ? 0. : result.y;\n            result.z = nextRowOutOfBounds ? 0. : result.z;\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n          `;\n          } else {\n            checkOutOfBoundsString += `\n            bool nextRowOutOfBounds =\n              (${channels[rank - 2]} + 1) >= ${this.outputShape[rank - 2]};\n            bool nextColOutOfBounds =\n              (${channels[rank - 1]} + 1) >= ${this.outputShape[rank - 1]};\n            result.y = nextColOutOfBounds ? 0. : result.y;\n            result.z = nextRowOutOfBounds ? 0. : result.z;\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n          `;\n          }\n        }\n      }\n    }\n    this.userCode = `\n      vec4 binaryOperation(vec4 a, vec4 b) {\n        ${op2}\n      }\n\n      void main() {\n        vec4 a = getAAtOutCoords();\n        vec4 b = getBAtOutCoords();\n\n        vec4 result = binaryOperation(a, b);\n        ${checkOutOfBoundsString}\n\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Identity.js\nfunction identity3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  backend2.incRef(x.dataId);\n  return { dataId: x.dataId, shape: x.shape, dtype: x.dtype };\n}\nvar identityConfig2 = {\n  kernelName: Identity,\n  backendName: \"webgl\",\n  kernelFunc: identity3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Complex.js\nfunction complex3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { real: real5, imag: imag5 } = inputs;\n  const complexInfo = backend2.makeTensorInfo(real5.shape, \"complex64\");\n  const complex5 = backend2.texData.get(complexInfo.dataId);\n  const realTensorInfo = identity3({ inputs: { x: real5 }, backend: backend2 });\n  const imagTensorInfo = identity3({ inputs: { x: imag5 }, backend: backend2 });\n  complex5.complexTensorInfos = { real: realTensorInfo, imag: imagTensorInfo };\n  return complexInfo;\n}\nvar complexConfig2 = {\n  kernelName: Complex,\n  backendName: \"webgl\",\n  kernelFunc: complex3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LeakyRelu.js\nvar LEAKYRELU = `return (a < 0.) ? b * a : a;`;\nvar LEAKYRELU_PACKED = `\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n`;\nfunction leakyRelu3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { alpha } = attrs;\n  const $alpha = backend2.makeTensorInfo([], \"float32\", util_exports.createScalarValue(alpha, \"float32\"));\n  const program = env().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\") ? new BinaryOpPackedProgram(LEAKYRELU_PACKED, x.shape, $alpha.shape) : new BinaryOpProgram(LEAKYRELU, x.shape, $alpha.shape);\n  const result = backend2.runWebGLProgram(program, [x, $alpha], \"float32\");\n  backend2.disposeIntermediateTensorInfo($alpha);\n  return result;\n}\nvar leakyReluConfig2 = {\n  kernelName: LeakyRelu,\n  backendName: \"webgl\",\n  kernelFunc: leakyRelu3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Prelu.js\nvar PRELU = `return (a < 0.) ? b * a : a;`;\nvar PRELU_PACKED = `\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n`;\nfunction prelu4(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x, alpha } = inputs;\n  const program = env().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\") ? new BinaryOpPackedProgram(PRELU_PACKED, x.shape, alpha.shape) : new BinaryOpProgram(PRELU, x.shape, alpha.shape);\n  return backend2.runWebGLProgram(program, [x, alpha], \"float32\");\n}\nvar preluConfig2 = {\n  kernelName: Prelu,\n  backendName: \"webgl\",\n  kernelFunc: prelu4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/kernel_funcs_utils.js\nvar CHECK_NAN_SNIPPET_UNARY = `if (isnan(x)) return x;`;\nvar CHECK_NAN_SNIPPET_BINARY = `\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n`;\nvar CHECK_NAN_SNIPPET_BINARY_PACKED = `\n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n`;\nfunction unaryKernelFunc2({ opSnippet, packedOpSnippet, cpuKernelImpl, dtype }) {\n  return ({ inputs, backend: backend2 }) => {\n    const { x } = inputs;\n    const webglBackend = backend2;\n    const $dtype = dtype || x.dtype;\n    if (webglBackend.shouldExecuteOnCPU([x]) && cpuKernelImpl != null) {\n      const xData = webglBackend.texData.get(x.dataId);\n      const outValues = cpuKernelImpl(xData.values, $dtype);\n      return webglBackend.makeTensorInfo(x.shape, $dtype, outValues);\n    }\n    const shouldUsePackedProgram = env().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\") && packedOpSnippet != null;\n    let program;\n    if (shouldUsePackedProgram) {\n      program = new UnaryOpPackedProgram(x.shape, packedOpSnippet);\n    } else {\n      program = new UnaryOpProgram(x.shape, opSnippet);\n    }\n    return webglBackend.runWebGLProgram(program, [x], $dtype);\n  };\n}\nfunction binaryKernelFunc2({ opSnippet, packedOpSnippet, checkOutOfBounds = false, supportsComplex = false, cpuKernelImpl, dtype }) {\n  return ({ inputs, backend: backend2 }) => {\n    const { a, b } = inputs;\n    const webglBackend = backend2;\n    if (supportsComplex && a.dtype === \"complex64\") {\n      const aData = webglBackend.texData.get(a.dataId);\n      const bData = webglBackend.texData.get(b.dataId);\n      const [real5, imag5] = [\n        [aData.complexTensorInfos.real, bData.complexTensorInfos.real],\n        [aData.complexTensorInfos.imag, bData.complexTensorInfos.imag]\n      ].map((complexParts) => {\n        const [aPart, bPart] = complexParts;\n        const aHandle = {\n          dataId: aPart.dataId,\n          dtype: aPart.dtype,\n          shape: a.shape\n        };\n        const bHandle = {\n          dataId: bPart.dataId,\n          dtype: bPart.dtype,\n          shape: b.shape\n        };\n        const program2 = new BinaryOpProgram(opSnippet, a.shape, b.shape);\n        return webglBackend.runWebGLProgram(program2, [aHandle, bHandle], upcastType(aPart.dtype, bPart.dtype));\n      });\n      const complexOutput = complex3({ inputs: { real: real5, imag: imag5 }, backend: webglBackend });\n      webglBackend.disposeIntermediateTensorInfo(real5);\n      webglBackend.disposeIntermediateTensorInfo(imag5);\n      return complexOutput;\n    }\n    const $dtype = dtype || upcastType(a.dtype, b.dtype);\n    if ((a.dtype === \"string\" || b.dtype === \"string\" || webglBackend.shouldExecuteOnCPU([a, b])) && cpuKernelImpl != null) {\n      const aVals = webglBackend.texData.get(a.dataId).values;\n      const bVals = webglBackend.texData.get(b.dataId).values;\n      const decodedAVals = a.dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(aVals) : aVals;\n      const decodedBVals = a.dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(bVals) : bVals;\n      const [outValues, outShape] = cpuKernelImpl(a.shape, b.shape, decodedAVals, decodedBVals, $dtype);\n      const out = webglBackend.makeTensorInfo(outShape, $dtype);\n      const outData = webglBackend.texData.get(out.dataId);\n      outData.values = outValues;\n      return out;\n    }\n    const shouldUsePackedProgram = env().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\") && packedOpSnippet != null;\n    let program;\n    if (shouldUsePackedProgram) {\n      program = new BinaryOpPackedProgram(packedOpSnippet, a.shape, b.shape, checkOutOfBounds);\n    } else {\n      program = new BinaryOpProgram(opSnippet, a.shape, b.shape);\n    }\n    return webglBackend.runWebGLProgram(program, [a, b], $dtype);\n  };\n}\nfunction mapActivationToShaderProgram(activation2, packed = false) {\n  if (activation2 === \"linear\") {\n    if (packed) {\n      return LINEAR2;\n    }\n    return LINEAR;\n  } else if (activation2 === \"relu\") {\n    if (packed) {\n      return RELU2;\n    }\n    return RELU;\n  } else if (activation2 === \"elu\") {\n    if (packed) {\n      return ELU3;\n    }\n    return ELU2;\n  } else if (activation2 === \"relu6\") {\n    if (packed) {\n      return RELU62;\n    }\n    return RELU6;\n  } else if (activation2 === \"prelu\") {\n    if (packed) {\n      return PRELU_PACKED;\n    }\n    return PRELU;\n  } else if (activation2 === \"leakyrelu\") {\n    if (packed) {\n      return LEAKYRELU_PACKED;\n    }\n    return LEAKYRELU;\n  } else if (activation2 === \"sigmoid\") {\n    if (packed) {\n      return SIGMOID2;\n    }\n    return SIGMOID;\n  }\n  throw new Error(`Activation ${activation2} has not been implemented for the WebGL backend.`);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/mulmat_packed_gpu.js\nvar MatMulPackedProgram = class {\n  constructor(aShape, bShape, outputShape, transposeA = false, transposeB = false, addBias = false, activation2 = null, hasPreluActivation = false, hasLeakyreluActivation = false) {\n    this.variableNames = [\"matrixA\", \"matrixB\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    const sharedDim = transposeA ? aShape[1] : aShape[2];\n    const sharedDimensionPacked = Math.ceil(sharedDim / 2);\n    const aSample = transposeA ? \"i * 2, rc.y\" : \"rc.y, i * 2\";\n    const bSample = transposeB ? \"rc.z, i * 2\" : \"i * 2, rc.z\";\n    const aSwizzle = transposeA ? [\"a.xxyy\", \"a.zzww\"] : [\"a.xxzz\", \"a.yyww\"];\n    const bSwizzle = transposeB ? [\"b.xzxz\", \"b.ywyw\"] : [\"b.xyxy\", \"b.zwzw\"];\n    let activationSnippet = \"\", applyActivationSnippet = \"\";\n    if (activation2) {\n      if (hasPreluActivation) {\n        activationSnippet = `vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          ${activation2}\n        }`;\n      } else if (hasLeakyreluActivation) {\n        activationSnippet = `vec4 activation(vec4 a) {\n          vec4 b = getLeakyreluAlphaAtOutCoords();\n          ${activation2}\n        }`;\n      } else {\n        activationSnippet = `vec4 activation(vec4 x) {\n          ${activation2}\n        }`;\n      }\n      applyActivationSnippet = `result = activation(result);`;\n    }\n    const addBiasSnippet = addBias ? \"result += getBiasAtOutCoords();\" : \"\";\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivation) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    if (hasLeakyreluActivation) {\n      this.variableNames.push(\"leakyreluAlpha\");\n    }\n    let batchASnippet = \"rc.x\";\n    let batchBSnippet = \"rc.x\";\n    if (aShape[0] < bShape[0]) {\n      batchASnippet = `int(min(float(rc.x), ${aShape[0] - 1}.))`;\n    } else if (bShape[0] < aShape[0]) {\n      batchBSnippet = `int(min(float(rc.x), ${bShape[0] - 1}.))`;\n    }\n    this.userCode = `\n      ${activationSnippet}\n      // Don't use uniform for sharedDimensionPacked for performance.\n      const float sharedDimension = ${sharedDimensionPacked}.0;\n\n      vec4 dot2x2ARowBCol(ivec3 rc) {\n        vec4 result = vec4(0);\n        for (int i = 0; i < ${sharedDimensionPacked}; i++) {\n          int batchA = ${batchASnippet};\n          int batchB = ${batchBSnippet};\n          vec4 a = getMatrixA(batchA, ${aSample});\n          vec4 b = getMatrixB(batchB, ${bSample});\n\n          // These swizzled products need to be separately added.\n          // See: https://github.com/tensorflow/tfjs/issues/1735\n          result += (${aSwizzle[0]} * ${bSwizzle[0]});\n          result += (${aSwizzle[1]} * ${bSwizzle[1]});\n        }\n        return result;\n      }\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n        vec4 result = dot2x2ARowBCol(rc);\n\n        ${addBiasSnippet}\n\n        ${applyActivationSnippet}\n\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/binaryop_complex_gpu.js\nvar COMPLEX_MULTIPLY = {\n  REAL: \"return areal * breal - aimag * bimag;\",\n  IMAG: \"return areal * bimag + aimag * breal;\"\n};\nvar BinaryOpComplexProgram = class {\n  constructor(op2, aShape, bShape) {\n    this.variableNames = [\"AReal\", \"AImag\", \"BReal\", \"BImag\"];\n    this.outputShape = backend_util_exports.assertAndGetBroadcastShape(aShape, bShape);\n    this.userCode = `\n      float binaryOpComplex(\n          float areal, float aimag, float breal, float bimag) {\n        ${op2}\n      }\n\n      void main() {\n        float areal = getARealAtOutCoords();\n        float aimag = getAImagAtOutCoords();\n        float breal = getBRealAtOutCoords();\n        float bimag = getBImagAtOutCoords();\n        setOutput(binaryOpComplex(areal, aimag, breal, bimag));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Multiply.js\nvar MUL = \"return a * b;\";\nfunction multiply3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { a, b } = inputs;\n  const dtype = backend_util_exports.upcastType(a.dtype, b.dtype);\n  if (a.dtype === \"complex64\") {\n    const aData = backend2.texData.get(a.dataId);\n    const bData = backend2.texData.get(b.dataId);\n    const realProgram = new BinaryOpComplexProgram(COMPLEX_MULTIPLY.REAL, a.shape, b.shape);\n    const imagProgram = new BinaryOpComplexProgram(COMPLEX_MULTIPLY.IMAG, a.shape, b.shape);\n    const inputs2 = [\n      {\n        dataId: aData.complexTensorInfos.real.dataId,\n        dtype: aData.complexTensorInfos.real.dtype,\n        shape: a.shape\n      },\n      {\n        dataId: aData.complexTensorInfos.imag.dataId,\n        dtype: aData.complexTensorInfos.imag.dtype,\n        shape: a.shape\n      },\n      {\n        dataId: bData.complexTensorInfos.real.dataId,\n        dtype: bData.complexTensorInfos.real.dtype,\n        shape: b.shape\n      },\n      {\n        dataId: bData.complexTensorInfos.imag.dataId,\n        dtype: bData.complexTensorInfos.imag.dtype,\n        shape: b.shape\n      }\n    ];\n    const realPart = backend2.runWebGLProgram(realProgram, inputs2, \"float32\");\n    const imagPart = backend2.runWebGLProgram(imagProgram, inputs2, \"float32\");\n    const complexOutput = complex3({ inputs: { real: realPart, imag: imagPart }, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(realPart);\n    backend2.disposeIntermediateTensorInfo(imagPart);\n    return complexOutput;\n  }\n  if (backend2.shouldExecuteOnCPU([a, b])) {\n    const aData = backend2.texData.get(a.dataId);\n    const bData = backend2.texData.get(b.dataId);\n    const [outValues, outShape] = multiplyImplCPU(a.shape, b.shape, aData.values, bData.values, dtype);\n    const out = backend2.makeTensorInfo(outShape, dtype);\n    const outData = backend2.texData.get(out.dataId);\n    outData.values = outValues;\n    return out;\n  }\n  let program;\n  if (env().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")) {\n    program = new BinaryOpPackedProgram(MUL, a.shape, b.shape);\n  } else {\n    program = new BinaryOpProgram(MUL, a.shape, b.shape);\n  }\n  return backend2.runWebGLProgram(program, [a, b], dtype);\n}\nvar multiplyConfig2 = {\n  kernelName: Multiply,\n  backendName: \"webgl\",\n  kernelFunc: multiply3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/reshape.js\nfunction packedReshape(input2, afterShape, backend2) {\n  const input3DShape = [\n    getBatchDim(input2.shape),\n    ...getRowsCols(input2.shape)\n  ];\n  const input3D = {\n    dtype: input2.dtype,\n    shape: input3DShape,\n    dataId: input2.dataId\n  };\n  const afterShapeAs3D = [\n    getBatchDim(afterShape),\n    ...getRowsCols(afterShape)\n  ];\n  const program = new ReshapePackedProgram(afterShapeAs3D, input3DShape);\n  const preventEagerUnpackingOfOutput = true;\n  const customValues = [input3DShape];\n  const output = backend2.runWebGLProgram(program, [input3D], input2.dtype, customValues, preventEagerUnpackingOfOutput);\n  return { dataId: output.dataId, shape: afterShape, dtype: output.dtype };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Reshape.js\nfunction reshape4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { shape } = attrs;\n  const webglBackend = backend2;\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const $shape = util_exports.inferFromImplicitShape(shape, xSize);\n  const $xSize = util_exports.sizeFromShape($shape);\n  util_exports.assert(xSize === $xSize, () => `The new shape (${$shape}) has ${$xSize} elements and the old shape (${x.shape}) has ${xSize} elements. The new shape and old shape must have the same number of elements.`);\n  const xTexData = webglBackend.texData.get(x.dataId);\n  if (xTexData.isPacked && !isReshapeFree(x.shape, $shape) && !(xTexData.texture !== null && isReshapeFree(xTexData.shape, $shape))) {\n    return packedReshape(x, $shape, webglBackend);\n  }\n  webglBackend.incRef(x.dataId);\n  return { dataId: x.dataId, shape: $shape, dtype: x.dtype };\n}\nvar reshapeConfig2 = {\n  kernelName: Reshape,\n  backendName: \"webgl\",\n  kernelFunc: reshape4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/mean_gpu.js\nvar MeanProgram = class {\n  constructor(reduceInfo, divisor) {\n    this.variableNames = [\"x\"];\n    const { windowSize, batchSize, inSize, outSize } = reduceInfo;\n    this.outputShape = [batchSize, outSize];\n    const windowSizeNearestVec4 = Math.floor(windowSize / 4) * 4;\n    const windowSizeVec4Remainder = windowSize % 4;\n    let updateSnippet = `sumValue += dot(values, ones);`;\n    if (divisor != null) {\n      const denominator = 1 / divisor;\n      updateSnippet = `sumValue += dot(values * ${util_exports.isInt(denominator) ? denominator.toPrecision(2) : denominator}, ones);`;\n    }\n    let checkOutOfBounds = \"\";\n    if (inSize % windowSize > 0) {\n      checkOutOfBounds = `\n        if (inIdx < 0 || inIdx >= ${inSize}) {\n          return 0.0;\n        }\n      `;\n    }\n    this.userCode = `\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        ${checkOutOfBounds}\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * ${windowSize};\n\n        float sumValue = 0.0;\n\n        for (int i = 0; i < ${windowSizeNearestVec4}; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          ${updateSnippet}\n        }\n\n        int inIdx = inOffset + ${windowSizeNearestVec4};\n        if (${windowSizeVec4Remainder === 1}) {\n          vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);\n\n          ${updateSnippet}\n        } else if (${windowSizeVec4Remainder === 2}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1), 0.0, 0.0);\n\n          ${updateSnippet}\n        } else if (${windowSizeVec4Remainder === 3}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2), 0.0);\n\n          ${updateSnippet}\n        }\n        setOutput(sumValue);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/reduce_gpu.js\nvar ReduceProgram = class {\n  constructor(reduceInfo, reduceType) {\n    this.variableNames = [\"x\"];\n    const { windowSize, batchSize, inSize, outSize } = reduceInfo;\n    this.outputShape = [batchSize, outSize];\n    let initializationValue = \"0.0\";\n    let compareOp = ``;\n    if (reduceType === \"prod\") {\n      initializationValue = \"1.0\";\n    } else if (reduceType === \"min\") {\n      initializationValue = \"1.0 / 1e-20\";\n      compareOp = `min`;\n    } else if (reduceType === \"max\") {\n      initializationValue = \"-1.0 / 1e-20\";\n      compareOp = `max`;\n    }\n    let returnValue = `${reduceType}(${reduceType}(${reduceType}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;\n    if (reduceType === \"sum\") {\n      returnValue = `sumValue`;\n    } else if (reduceType === \"prod\") {\n      returnValue = `prodValue`;\n    } else if (reduceType === \"all\") {\n      returnValue = `allValue`;\n    } else if (reduceType === \"any\") {\n      returnValue = `anyValue`;\n    }\n    const windowSizeNearestVec4 = Math.floor(windowSize / 4) * 4;\n    const windowSizeVec4Remainder = windowSize % 4;\n    let updateSnippet = `\n      if (${reduceType === \"sum\"}) {\n        sumValue += dot(values, ones);\n      } else if (${reduceType === \"prod\"}) {\n        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);\n        prodValue *= tmp[0] * tmp[1];\n      } else {\n        minMaxValue = ${compareOp}(values, minMaxValue);\n        if (${reduceType === \"min\"} || ${reduceType === \"max\"}) {\n          minMaxValue = ${compareOp}(values, minMaxValue);\n          bvec4 isNaN = isnan(values);\n          if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {\n            minMaxValue = vec4(NAN);\n          }\n        }\n      }\n    `;\n    let vecType = `vec4`;\n    if (reduceType === \"all\") {\n      initializationValue = \"1.0\";\n      updateSnippet = `\n        bool reducedAllValue = all(values);\n        float floatedReducedAllValue = float(reducedAllValue);\n        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);\n      `;\n      vecType = `bvec4`;\n    } else if (reduceType === \"any\") {\n      initializationValue = \"0.0\";\n      updateSnippet = `\n        bool reducedAnyValue = any(values);\n        float floatedReducedAnyValue = float(reducedAnyValue);\n        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);\n      `;\n      vecType = `bvec4`;\n    }\n    let checkOutOfBounds = \"\";\n    if (inSize % windowSize > 0) {\n      checkOutOfBounds = `\n        if (inIdx < 0 || inIdx >= ${inSize}) {\n          return initializationValue;\n        }\n      `;\n    }\n    this.userCode = `\n      const float initializationValue = ${initializationValue};\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        ${checkOutOfBounds}\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * ${windowSize};\n\n        vec4 minMaxValue = vec4(${initializationValue});\n        float prodValue = 1.0;\n        float sumValue = 0.0;\n        float allValue = 1.0;\n        float anyValue = 0.0;\n\n        for (int i = 0; i < ${windowSizeNearestVec4}; i += 4) {\n          int inIdx = inOffset + i;\n          ${vecType} values = ${vecType}(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          ${updateSnippet}\n        }\n\n        int inIdx = inOffset + ${windowSizeNearestVec4};\n        if (${windowSizeVec4Remainder === 1}) {\n          ${vecType} values = ${vecType}(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          ${updateSnippet}\n        } else if (${windowSizeVec4Remainder === 2}) {\n          ${vecType} values = ${vecType}(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          ${updateSnippet}\n        } else if (${windowSizeVec4Remainder === 3}) {\n          ${vecType} values = ${vecType}(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          ${updateSnippet}\n        }\n        setOutput(${returnValue});\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/reduce.js\nfunction getReductionStages(inShape) {\n  const stages = [];\n  while (stages.length === 0 || stages[stages.length - 1].outSize !== 1) {\n    const outSize = stages.length ? stages[stages.length - 1].outSize : inShape[1];\n    const windowSize = backend_util_exports.computeOptimalWindowSize(outSize);\n    stages.push({\n      inSize: outSize,\n      windowSize,\n      outSize: Math.ceil(outSize / windowSize)\n    });\n  }\n  return stages;\n}\nfunction reduce(x, dtype, reductionType, backend2) {\n  const reductionStages = getReductionStages(x.shape);\n  let result = x;\n  for (let i2 = 0; i2 < reductionStages.length; i2++) {\n    const { inSize, windowSize, outSize } = reductionStages[i2];\n    let program;\n    let previousResult;\n    if (reductionType === \"mean\") {\n      program = i2 === 0 ? new MeanProgram({ windowSize, inSize, batchSize: x.shape[0], outSize }, inSize) : new MeanProgram({ windowSize, inSize, batchSize: x.shape[0], outSize });\n    } else {\n      program = new ReduceProgram({ windowSize, inSize, batchSize: x.shape[0], outSize }, reductionType);\n    }\n    previousResult = result;\n    result = backend2.runWebGLProgram(program, [result], dtype);\n    if (previousResult.dataId !== x.dataId) {\n      backend2.disposeIntermediateTensorInfo(previousResult);\n    }\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/transpose_gpu.js\nvar TransposeProgram = class {\n  constructor(aShape, newDim) {\n    this.variableNames = [\"A\"];\n    const outputShape = new Array(aShape.length);\n    for (let i2 = 0; i2 < outputShape.length; i2++) {\n      outputShape[i2] = aShape[newDim[i2]];\n    }\n    this.outputShape = outputShape;\n    this.rank = outputShape.length;\n    const dtype = getCoordsDataType(this.rank);\n    const switched = getSwitchedCoords(newDim);\n    this.userCode = `\n    void main() {\n      ${dtype} resRC = getOutputCoords();\n      setOutput(getA(${switched}));\n    }\n    `;\n  }\n};\nfunction getSwitchedCoords(newDim) {\n  const rank = newDim.length;\n  if (rank > 6) {\n    throw Error(`Transpose for rank ${rank} is not yet supported`);\n  }\n  const originalOrder = [\"resRC.x\", \"resRC.y\", \"resRC.z\", \"resRC.w\", \"resRC.u\", \"resRC.v\"];\n  const switchedCoords = new Array(rank);\n  for (let i2 = 0; i2 < newDim.length; i2++) {\n    switchedCoords[newDim[i2]] = originalOrder[i2];\n  }\n  return switchedCoords.join();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/transpose_packed_gpu.js\nvar TransposePackedProgram = class {\n  constructor(aShape, newDim) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    const outputShape = new Array(aShape.length);\n    for (let i2 = 0; i2 < outputShape.length; i2++) {\n      outputShape[i2] = aShape[newDim[i2]];\n    }\n    this.outputShape = outputShape;\n    this.rank = outputShape.length;\n    if (this.rank > 6) {\n      throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);\n    }\n    const dtype = getCoordsDataType(this.rank);\n    const outputOrder = getVecChannels(\"rc\", this.rank);\n    const switchedOrder = new Array(this.rank);\n    for (let i2 = 0; i2 < newDim.length; i2++) {\n      switchedOrder[newDim[i2]] = outputOrder[i2];\n    }\n    const innerDims = `vec2(${switchedOrder.slice(-2).join()})`;\n    const nextColumn = `++${outputOrder[this.rank - 1]} < ${outputShape[this.rank - 1]}`;\n    const getc = `getChannel(getA(${switchedOrder.join()}), ${innerDims})`;\n    this.userCode = `\n    void main() {\n      ${dtype} rc = getOutputCoords();\n      vec4 result = vec4(0.);\n      result[0] = ${getc};\n      if(${nextColumn}) {\n        result[1] = ${getc};\n      }\n      --${outputOrder[this.rank - 1]};\n      if(++${outputOrder[this.rank - 2]} < ${outputShape[this.rank - 2]}) {\n        result[2] = ${getc};\n        if(${nextColumn}) {\n          result[3] = ${getc};\n        }\n      }\n      setOutput(result);\n    }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Transpose_impl.js\nfunction transposeImpl2(x, perm, backend2) {\n  const program = env().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\") ? new TransposePackedProgram(x.shape, perm) : new TransposeProgram(x.shape, perm);\n  return backend2.runWebGLProgram(program, [x], x.dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sum_impl.js\nfunction sumImpl(x, axis, keepDims, backend2) {\n  const reductionIndices = axis;\n  const xRank = x.shape.length;\n  const origAxes = util_exports.parseAxisParam(reductionIndices, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  const sumInputIsTransposed = permutedAxes != null;\n  let sumInput = x;\n  if (sumInputIsTransposed) {\n    sumInput = transposeImpl2(x, permutedAxes, backend2);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"sum\", axes, xRank);\n  const [sumOutShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(sumInput.shape, axes);\n  let outShape = sumOutShape;\n  if (keepDims) {\n    outShape = backend_util_exports.expandShapeToKeepDim(sumOutShape, origAxes);\n  }\n  const inSize = util_exports.sizeFromShape(reduceShape);\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const batchSize = xSize / inSize;\n  const reshapedInput = reshape4({ inputs: { x: sumInput }, attrs: { shape: [batchSize, inSize] }, backend: backend2 });\n  const outType = sumOutType(x.dtype);\n  const reduced = reduce(reshapedInput, outType, \"sum\", backend2);\n  const out = reshape4({ inputs: { x: reduced }, attrs: { shape: outShape }, backend: backend2 });\n  backend2.disposeIntermediateTensorInfo(reshapedInput);\n  backend2.disposeIntermediateTensorInfo(reduced);\n  if (sumInputIsTransposed) {\n    backend2.disposeIntermediateTensorInfo(sumInput);\n  }\n  return out;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sum.js\nfunction sum4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  return sumImpl(x, axis, keepDims, backend2);\n}\nvar sumConfig2 = {\n  kernelName: Sum,\n  backendName: \"webgl\",\n  kernelFunc: sum4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Transpose.js\nfunction transpose3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { perm } = attrs;\n  const webglBackend = backend2;\n  const xRank = x.shape.length;\n  const newShape = new Array(xRank);\n  for (let i2 = 0; i2 < newShape.length; i2++) {\n    newShape[i2] = x.shape[perm[i2]];\n  }\n  let out;\n  if (webglBackend.shouldExecuteOnCPU([x])) {\n    const xTexData = webglBackend.texData.get(x.dataId);\n    const values = xTexData.values;\n    const outValues = transposeImplCPU(values, x.shape, x.dtype, perm, newShape);\n    out = webglBackend.makeTensorInfo(newShape, x.dtype);\n    const outData = webglBackend.texData.get(out.dataId);\n    outData.values = outValues;\n  } else {\n    out = transposeImpl2(x, perm, webglBackend);\n  }\n  return out;\n}\nvar transposeConfig2 = {\n  kernelName: Transpose,\n  backendName: \"webgl\",\n  kernelFunc: transpose3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/BatchMatMul_impl.js\nvar MATMUL_SHARED_DIM_THRESHOLD = 1e3;\nfunction batchMatMulImpl({ a, b, transposeA, transposeB, backend: backend2, bias = null, preluActivationWeights = null, leakyreluAlpha = 0, activation: activation2 = null }) {\n  const aRank = a.shape.length;\n  const bRank = b.shape.length;\n  const innerShapeA = transposeA ? a.shape[aRank - 2] : a.shape[aRank - 1];\n  const innerShapeB = transposeB ? b.shape[bRank - 1] : b.shape[bRank - 2];\n  const outerShapeA = transposeA ? a.shape[aRank - 1] : a.shape[aRank - 2];\n  const outerShapeB = transposeB ? b.shape[bRank - 2] : b.shape[bRank - 1];\n  const outerDimsA = a.shape.slice(0, -2);\n  const outerDimsB = b.shape.slice(0, -2);\n  const batchDimA = util_exports.sizeFromShape(outerDimsA);\n  const batchDimB = util_exports.sizeFromShape(outerDimsB);\n  const outShapeOuterDims = broadcast_util_exports.assertAndGetBroadcastShape(a.shape.slice(0, -2), b.shape.slice(0, -2));\n  const outShape = outShapeOuterDims.concat([outerShapeA, outerShapeB]);\n  util_exports.assert(innerShapeA === innerShapeB, () => `Error in matMul: inner shapes (${innerShapeA}) and (${innerShapeB}) of Tensors with shapes ${a.shape} and ${b.shape} and transposeA=${transposeA} and transposeB=${transposeB} must match.`);\n  const a3dShape = transposeA ? [batchDimA, innerShapeA, outerShapeA] : [batchDimA, outerShapeA, innerShapeA];\n  const b3dShape = transposeB ? [batchDimB, outerShapeB, innerShapeB] : [batchDimB, innerShapeB, outerShapeB];\n  const a3d = reshape4({ inputs: { x: a }, backend: backend2, attrs: { shape: a3dShape } });\n  const b3d = reshape4({ inputs: { x: b }, backend: backend2, attrs: { shape: b3dShape } });\n  const intermediates = [a3d, b3d];\n  const batchDim = Math.max(batchDimA, batchDimB);\n  const sharedDim = transposeA ? a3d.shape[1] : a3d.shape[2];\n  const hasBias = bias != null;\n  const hasPreluActivationWeights = preluActivationWeights != null;\n  const hasLeakyreluAlpha = activation2 === \"leakyrelu\";\n  const fusedActivation = activation2 != null ? mapActivationToShaderProgram(activation2, true) : null;\n  const containsFusedOps = hasBias || hasPreluActivationWeights || hasLeakyreluAlpha || fusedActivation != null;\n  let out;\n  if ((outerShapeA === 1 || outerShapeB === 1) && sharedDim > MATMUL_SHARED_DIM_THRESHOLD && containsFusedOps === false) {\n    let aVec = a3d;\n    let bVec = b3d;\n    if (transposeA) {\n      aVec = transpose3({ inputs: { x: a3d }, backend: backend2, attrs: { perm: [0, 2, 1] } });\n      intermediates.push(aVec);\n    }\n    if (transposeB) {\n      bVec = transpose3({ inputs: { x: b3d }, backend: backend2, attrs: { perm: [0, 2, 1] } });\n      intermediates.push(bVec);\n    }\n    const shouldReshapeA = outerShapeB !== 1;\n    const shouldReshapeB = outerShapeB === 1;\n    let aVec3d = aVec;\n    if (shouldReshapeA) {\n      aVec3d = reshape4({\n        inputs: { x: aVec },\n        backend: backend2,\n        attrs: { shape: [batchDim, sharedDim, 1] }\n      });\n      intermediates.push(aVec3d);\n    }\n    const axis = outerShapeB === 1 ? 2 : 1;\n    let bVec3d = bVec;\n    if (shouldReshapeB) {\n      bVec3d = reshape4({\n        inputs: { x: bVec },\n        backend: backend2,\n        attrs: { shape: [batchDim, 1, sharedDim] }\n      });\n      intermediates.push(bVec3d);\n    }\n    const product = multiply3({ inputs: { a: aVec3d, b: bVec3d }, backend: backend2 });\n    out = sum4({ inputs: { x: product }, backend: backend2, attrs: { axis, keepDims: true } });\n    intermediates.push(product);\n  } else {\n    const dtype = upcastType(a.dtype, b.dtype);\n    const program = new MatMulPackedProgram(a3dShape, b3dShape, [batchDim, outerShapeA, outerShapeB], transposeA, transposeB, hasBias, fusedActivation, hasPreluActivationWeights, hasLeakyreluAlpha);\n    const inputs = [a3d, b3d];\n    if (bias != null) {\n      inputs.push(bias);\n    }\n    if (hasPreluActivationWeights) {\n      inputs.push(preluActivationWeights);\n    }\n    if (hasLeakyreluAlpha) {\n      const $leakyreluAlpha = backend2.makeTensorInfo([], \"float32\", util_exports.createScalarValue(leakyreluAlpha, \"float32\"));\n      inputs.push($leakyreluAlpha);\n      intermediates.push($leakyreluAlpha);\n    }\n    out = backend2.runWebGLProgram(program, inputs, dtype);\n  }\n  const outReshaped = reshape4({ inputs: { x: out }, backend: backend2, attrs: { shape: outShape } });\n  intermediates.push(out);\n  for (const i2 of intermediates) {\n    backend2.disposeIntermediateTensorInfo(i2);\n  }\n  return outReshaped;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/_FusedMatMul.js\nfunction _fusedMatMul2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b, bias, preluActivationWeights } = inputs;\n  const { transposeA, transposeB, activation: activation2, leakyreluAlpha } = attrs;\n  return batchMatMulImpl({\n    a,\n    b,\n    transposeA,\n    transposeB,\n    backend: backend2,\n    bias,\n    preluActivationWeights,\n    leakyreluAlpha,\n    activation: activation2\n  });\n}\nvar _fusedMatMulConfig2 = {\n  kernelName: _FusedMatMul,\n  backendName: \"webgl\",\n  kernelFunc: _fusedMatMul2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Abs.js\nvar ABS2 = `return abs(x);`;\nfunction abs3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (backend2.shouldExecuteOnCPU([x]) && x.dtype !== \"complex64\") {\n    const xData = backend2.texData.get(x.dataId);\n    const outValues = simpleAbsImplCPU(xData.values);\n    return backend2.makeTensorInfo(x.shape, x.dtype, outValues);\n  }\n  let program;\n  if (env().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\")) {\n    program = new UnaryOpPackedProgram(x.shape, ABS2);\n  } else {\n    program = new UnaryOpProgram(x.shape, ABS2);\n  }\n  return backend2.runWebGLProgram(program, [x], x.dtype);\n}\nvar absConfig2 = {\n  kernelName: Abs,\n  backendName: \"webgl\",\n  kernelFunc: abs3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Acos.js\nvar ACOS = CHECK_NAN_SNIPPET + `\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return acos(x);\n`;\nvar acos3 = unaryKernelFunc2({ opSnippet: ACOS });\nvar acosConfig2 = {\n  kernelName: Acos,\n  backendName: \"webgl\",\n  kernelFunc: acos3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Acosh.js\nvar ACOSH = CHECK_NAN_SNIPPET + `\n  if (x < 1.0) return NAN;\nreturn log(x + sqrt(x * x - 1.0));`;\nvar acosh3 = unaryKernelFunc2({ opSnippet: ACOSH });\nvar acoshConfig2 = {\n  kernelName: Acosh,\n  backendName: \"webgl\",\n  kernelFunc: acosh3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Add.js\nvar ADD = \"return a + b;\";\nvar addKernelFunc = binaryKernelFunc2({\n  opSnippet: ADD,\n  packedOpSnippet: ADD,\n  supportsComplex: true,\n  cpuKernelImpl: addImplCPU\n});\nvar addConfig2 = {\n  kernelName: Add,\n  backendName: \"webgl\",\n  kernelFunc: addKernelFunc\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/addn_gpu.js\nvar AddNProgram = class {\n  constructor(outputShape, shapes) {\n    this.outputShape = [];\n    this.outputShape = outputShape;\n    this.variableNames = shapes.map((_, i2) => `T${i2}`);\n    const snippets = [];\n    this.variableNames.forEach((variable2) => {\n      snippets.push(`float v${variable2} = get${variable2}AtOutCoords();`);\n    });\n    const operation = this.variableNames.map((variable2) => {\n      return `v${variable2}`;\n    }).join(\" + \");\n    this.userCode = `\n      void main() {\n        ${snippets.join(\"\\n        \")}\n\n        float result = ${operation};\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/addn_packed_gpu.js\nvar AddNPackedProgram = class {\n  constructor(outputShape, shapes) {\n    this.outputShape = [];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = outputShape;\n    this.variableNames = shapes.map((_, i2) => `T${i2}`);\n    const snippets = [];\n    this.variableNames.forEach((variable2) => {\n      snippets.push(`vec4 v${variable2} = get${variable2}AtOutCoords();`);\n    });\n    const operation = this.variableNames.map((variable2) => {\n      return `v${variable2}`;\n    }).join(\" + \");\n    this.userCode = `\n      void main() {\n        ${snippets.join(\"\\n        \")}\n\n        vec4 result = ${operation};\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/AddN.js\nfunction addN3(args) {\n  const { inputs, backend: backend2 } = args;\n  const tensors = inputs;\n  if (tensors.length === 1) {\n    return identity3({ inputs: { x: tensors[0] }, backend: backend2 });\n  }\n  if (tensors.length > env().get(\"WEBGL_MAX_TEXTURES_IN_SHADER\")) {\n    const midIndex = Math.floor(tensors.length / 2);\n    const leftSide = addN3({ inputs: tensors.slice(0, midIndex), backend: backend2 });\n    const rightSide = addN3({ inputs: tensors.slice(midIndex), backend: backend2 });\n    return addN3({ inputs: [leftSide, rightSide], backend: backend2 });\n  }\n  const dtype = tensors.map((t2) => t2.dtype).reduce((d1, d2) => upcastType(d1, d2));\n  const shapes = tensors.map((t2) => t2.shape);\n  const usePackedOp = env().getBool(\"WEBGL_PACK\");\n  const program = usePackedOp ? new AddNPackedProgram(tensors[0].shape, shapes) : new AddNProgram(tensors[0].shape, shapes);\n  return backend2.runWebGLProgram(program, tensors, dtype);\n}\nvar addNConfig2 = {\n  kernelName: AddN,\n  backendName: \"webgl\",\n  kernelFunc: addN3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/All.js\nfunction all3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  const xRank = x.shape.length;\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  let permutedX = x;\n  if (permutedAxes != null) {\n    permutedX = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"all\", axes, xRank);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(permutedX.shape, axes);\n  const inSize = util_exports.sizeFromShape(reduceShape);\n  const a2D = reshape4({ inputs: { x: permutedX }, backend: backend2, attrs: { shape: [-1, inSize] } });\n  const reduced = reduce(a2D, a2D.dtype, \"all\", backend2);\n  let res;\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(outShape, origAxes);\n    res = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: newShape } });\n  } else {\n    res = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: outShape } });\n  }\n  backend2.disposeIntermediateTensorInfo(a2D);\n  backend2.disposeIntermediateTensorInfo(reduced);\n  if (permutedAxes != null) {\n    backend2.disposeIntermediateTensorInfo(permutedX);\n  }\n  return res;\n}\nvar allConfig2 = {\n  kernelName: All,\n  backendName: \"webgl\",\n  kernelFunc: all3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Any.js\nfunction any3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  const xRank = x.shape.length;\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  let permutedX = x;\n  if (permutedAxes != null) {\n    permutedX = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"any\", axes, xRank);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(permutedX.shape, axes);\n  const inSize = util_exports.sizeFromShape(reduceShape);\n  const a2D = reshape4({ inputs: { x: permutedX }, backend: backend2, attrs: { shape: [-1, inSize] } });\n  const reduced = reduce(a2D, a2D.dtype, \"any\", backend2);\n  let res;\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(outShape, origAxes);\n    res = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: newShape } });\n  } else {\n    res = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: outShape } });\n  }\n  backend2.disposeIntermediateTensorInfo(a2D);\n  backend2.disposeIntermediateTensorInfo(reduced);\n  if (permutedAxes != null) {\n    backend2.disposeIntermediateTensorInfo(permutedX);\n  }\n  return res;\n}\nvar anyConfig2 = {\n  kernelName: Any,\n  backendName: \"webgl\",\n  kernelFunc: any3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/argminmax_gpu.js\nvar ArgMinMaxProgram = class {\n  constructor(reduceInfo, op2, firstPass) {\n    this.variableNames = [\"A\"];\n    const { windowSize, batchSize, outSize } = reduceInfo;\n    if (!firstPass) {\n      this.variableNames.push(\"bestIndicesA\");\n    }\n    this.outputShape = [batchSize, outSize];\n    const compOp = op2 === \"max\" ? \">\" : \"<\";\n    const indexSnippet = firstPass ? \"inOffset + i;\" : \"round(getBestIndicesA(batch, inOffset + i));\";\n    this.userCode = `\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * ${windowSize};\n\n        int bestIndex = inOffset;\n        float bestValue = getA(batch, bestIndex);\n\n        for (int i = 0; i < ${windowSize}; i++) {\n          int inIdx = ${indexSnippet};\n          float candidate = getA(batch, inIdx);\n          if (candidate ${compOp} bestValue) {\n            bestValue = candidate;\n            bestIndex = inIdx;\n          }\n        }\n        setOutput(float(bestIndex));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/argminmax_packed_gpu.js\nvar ArgMinMaxPackedProgram = class {\n  constructor(shape, windowSize, op2, firstPass) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    util_exports.assert(shape.length > 2, () => `Packed arg${op2.charAt(0).toUpperCase() + op2.slice(1)} supports only inputs with rank above 2.`);\n    const inSize = shape[shape.length - 1];\n    const outSize = Math.ceil(inSize / windowSize);\n    this.outputShape = shape.slice(0, -1);\n    if (outSize > 1) {\n      this.outputShape.push(outSize);\n    }\n    if (!firstPass) {\n      this.variableNames.push(\"bestIndicesA\");\n    }\n    const outShape = this.outputShape;\n    const rank = outShape.length;\n    const dtype = getCoordsDataType(rank);\n    const coords3 = getChannels(\"coords\", rank);\n    let sourceLocSetup;\n    let sourceRank;\n    if (outSize === 1) {\n      sourceRank = rank + 1;\n      const sourceLocDType = getCoordsDataType(sourceRank);\n      sourceLocSetup = `\n        ${sourceLocDType} sourceLocR = ${sourceLocDType}(${coords3.join()}, 0);\n        ++${coords3[rank - 1]};\n        ${sourceLocDType} sourceLocG = ${sourceLocDType}(${coords3.join()}, 0);\n        ++${coords3[rank - 2]};\n        ${sourceLocDType} sourceLocA = ${sourceLocDType}(${coords3.join()}, 0);\n        --${coords3[rank - 1]};\n        ${sourceLocDType} sourceLocB = ${sourceLocDType}(${coords3.join()}, 0);\n        --${coords3[rank - 2]};`;\n    } else {\n      sourceRank = rank;\n      sourceLocSetup = `\n        ${dtype} sourceLocR = coords;\n        ++${coords3[rank - 1]};\n        ${dtype} sourceLocG = coords;\n        ++${coords3[rank - 2]};\n        ${dtype} sourceLocA = coords;\n        --${coords3[rank - 1]};\n        ${dtype} sourceLocB = coords;\n        --${coords3[rank - 2]};`;\n    }\n    const channels = [\"x\", \"y\", \"z\", \"w\", \"u\", \"v\"].slice(0, sourceRank);\n    const inChannel = \".\" + channels[sourceRank - 1];\n    const intChannels = channels.map((x) => \"int \" + x);\n    const srcRCoords = getChannels(\"sourceLocR\", sourceRank - 1).concat(\"inIdx.r\");\n    const srcGCoords = getChannels(\"sourceLocG\", sourceRank - 1).concat(\"inIdx.g\");\n    const srcBCoords = getChannels(\"sourceLocB\", sourceRank - 1).concat(\"inIdx.b\");\n    const srcACoords = getChannels(\"sourceLocA\", sourceRank - 1).concat(\"inIdx.a\");\n    const compOp = op2 === \"max\" ? \"greaterThan\" : \"lessThan\";\n    const fetchCandidateIdx = firstPass ? \"\" : `\n          inIdx = round(vec4(getBestIndicesAChannel(${srcRCoords.join()}),\n                             getBestIndicesAChannel(${srcGCoords.join()}),\n                             getBestIndicesAChannel(${srcBCoords.join()}),\n                             getBestIndicesAChannel(${srcACoords.join()})));`;\n    const fetchValue = `vec4(\n            getAChannel(${srcRCoords.join()}),\n            hasNextCol ? getAChannel(${srcGCoords.join()}) : 0.,\n            hasNextRow ? getAChannel(${srcBCoords.join()}) : 0.,\n            hasNextRow && hasNextCol ? getAChannel(${srcACoords.join()}) : 0.)`;\n    const getBestIndicesAChannelSnippet = firstPass ? \"\" : `\n      float getBestIndicesAChannel(${intChannels.join()}) {\n        return getChannel(getBestIndicesA(${channels.join()}),\n                                          vec2(${channels.slice(-2).join()}));\n      }`;\n    this.userCode = `\n      float getAChannel(${intChannels.join()}) {\n        return getChannel(getA(${channels.join()}),\n                               vec2(${channels.slice(-2).join()}));\n      }\n      ${getBestIndicesAChannelSnippet}\n      void main() {\n        ${dtype} coords = getOutputCoords();\n        bool hasNextCol = ${coords3[rank - 1]} < ${outShape[rank - 1] - 1};\n        bool hasNextRow = ${coords3[rank - 2]} < ${outShape[rank - 2] - 1};\n        ${sourceLocSetup}\n        ivec4 srcIdx = ivec4(sourceLocR${inChannel}, sourceLocG${inChannel},\n          sourceLocB${inChannel}, sourceLocA${inChannel}) * ${windowSize};\n        ivec4 inIdx = srcIdx;\n        vec4 bestIndex = vec4(inIdx);\n        vec4 bestValue = ${fetchValue};\n\n        for (int i = 0; i < ${windowSize}; i++) {\n          inIdx = srcIdx;\n          ${fetchCandidateIdx}\n          vec4 candidate = ${fetchValue};\n          bvec4 nan = isnan(candidate);\n          bvec4 replace = bvec4(\n            vec4(${compOp}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));\n\n          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,\n                           replace.y  ? candidate.y : bestValue.y,\n                           replace.z  ? candidate.z : bestValue.z,\n                           replace.w  ? candidate.w : bestValue.w);\n          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));\n          srcIdx++;\n        }\n        setOutput(bestIndex);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/arg_min_max.js\nfunction argReduce(backend2, x, reduceType, bestIndicesA = null) {\n  let batchSize = x.shape[0];\n  let inSize = x.shape[1];\n  if (bestIndicesA != null) {\n    batchSize = bestIndicesA.shape[0];\n    inSize = bestIndicesA.shape[1];\n  }\n  const windowSize = backend_util_exports.computeOptimalWindowSize(inSize);\n  const reduceInfo = { windowSize, inSize, batchSize, outSize: Math.ceil(inSize / windowSize) };\n  const program = new ArgMinMaxProgram(reduceInfo, reduceType, bestIndicesA == null);\n  const inputs = [x];\n  if (bestIndicesA != null) {\n    inputs.push(bestIndicesA);\n  }\n  const output = backend2.runWebGLProgram(program, inputs, \"int32\");\n  if (output.shape[1] === 1) {\n    return output;\n  }\n  const result = argReduce(backend2, x, reduceType, output);\n  backend2.disposeIntermediateTensorInfo(output);\n  return result;\n}\nfunction argReducePacked(backend2, x, reduceType, bestIndicesA = null) {\n  const inShape = bestIndicesA != null ? bestIndicesA.shape : x.shape;\n  const inSize = inShape[inShape.length - 1];\n  const windowSize = backend_util_exports.computeOptimalWindowSize(inSize);\n  const program = new ArgMinMaxPackedProgram(inShape, windowSize, reduceType, bestIndicesA == null);\n  const inputs = bestIndicesA == null ? [x] : [x, bestIndicesA];\n  const output = backend2.runWebGLProgram(program, inputs, \"int32\");\n  if (output.shape.length === x.shape.length) {\n    const result = argReducePacked(backend2, x, reduceType, output);\n    backend2.disposeIntermediateTensorInfo(output);\n    return result;\n  }\n  return output;\n}\nfunction argMinMaxReduce(backend2, x, axis, reduceType) {\n  const axes = [axis];\n  backend_util_exports.assertAxesAreInnerMostDims(\"arg\" + reduceType.charAt(0).toUpperCase() + reduceType.slice(1), axes, x.shape.length);\n  if (!env().getBool(\"WEBGL_PACK_REDUCE\") || x.shape.length <= 2) {\n    const intermediateTensorInfos = [];\n    const xtexData = backend2.texData.get(x.dataId);\n    const xIsPacked = xtexData !== null && xtexData.isPacked;\n    let xUnPacked = x;\n    if (xIsPacked) {\n      xUnPacked = backend2.unpackTensor(x);\n      intermediateTensorInfos.push(xUnPacked);\n    }\n    const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(xUnPacked.shape, axes);\n    const inSize = util_exports.sizeFromShape(reduceShape);\n    const a2D = reshape4({ inputs: { x: xUnPacked }, backend: backend2, attrs: { shape: [-1, inSize] } });\n    intermediateTensorInfos.push(a2D);\n    const reduced = argReduce(backend2, a2D, reduceType);\n    intermediateTensorInfos.push(reduced);\n    const reshaped = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: outShape } });\n    intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n    return reshaped;\n  }\n  return argReducePacked(backend2, x, reduceType);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ArgMax.js\nfunction argMax3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis } = attrs;\n  let axes = util_exports.parseAxisParam(axis, x.shape);\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  const intermediateTensorInfos = [];\n  if (permutedAxes != null) {\n    $x = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    intermediateTensorInfos.push($x);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, $x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"argMax\", [axes[0]], $x.shape.length);\n  const out = argMinMaxReduce(backend2, $x, axes[0], \"max\");\n  intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return out;\n}\nvar argMaxConfig2 = {\n  kernelName: ArgMax,\n  backendName: \"webgl\",\n  kernelFunc: argMax3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ArgMin.js\nfunction argMin3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis } = attrs;\n  let axes = util_exports.parseAxisParam(axis, x.shape);\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  const intermediateTensorInfos = [];\n  if (permutedAxes != null) {\n    $x = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    intermediateTensorInfos.push($x);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, $x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"argMin\", [axes[0]], $x.shape.length);\n  const out = argMinMaxReduce(backend2, $x, axes[0], \"min\");\n  intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return out;\n}\nvar argMinConfig2 = {\n  kernelName: ArgMin,\n  backendName: \"webgl\",\n  kernelFunc: argMin3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Asin.js\nvar ASIN = CHECK_NAN_SNIPPET + `\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return asin(x);\n`;\nvar asin3 = unaryKernelFunc2({ opSnippet: ASIN });\nvar asinConfig2 = {\n  kernelName: Asin,\n  backendName: \"webgl\",\n  kernelFunc: asin3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Asinh.js\nvar ASINH = CHECK_NAN_SNIPPET + `return log(x + sqrt(x * x + 1.0));`;\nvar asinh3 = unaryKernelFunc2({ opSnippet: ASINH });\nvar asinhConfig2 = {\n  kernelName: Asinh,\n  backendName: \"webgl\",\n  kernelFunc: asinh3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Atan.js\nvar ATAN = CHECK_NAN_SNIPPET + `\n  return atan(x);\n`;\nvar atan4 = unaryKernelFunc2({ opSnippet: ATAN });\nvar atanConfig2 = {\n  kernelName: Atan,\n  backendName: \"webgl\",\n  kernelFunc: atan4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Atan2.js\nvar ATAN2 = CHECK_NAN_SNIPPET_BINARY + `\n  return atan(a, b);\n`;\nvar ATAN2_PACKED = `\n  vec4 result = atan(a, b);\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  ` + CHECK_NAN_SNIPPET_BINARY_PACKED + `\n  return result;\n`;\nvar atan23 = binaryKernelFunc2({ opSnippet: ATAN2, packedOpSnippet: ATAN2_PACKED });\nvar atan2Config2 = {\n  kernelName: Atan2,\n  backendName: \"webgl\",\n  kernelFunc: atan23\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Atanh.js\nvar ATANH = CHECK_NAN_SNIPPET + `\n  if ((x < -1.0) || (x > 1.0)) return NAN;\nreturn (log(1.0 + x) - log(1.0 - x)) / 2.0;`;\nvar atanh3 = unaryKernelFunc2({ opSnippet: ATANH });\nvar atanhConfig2 = {\n  kernelName: Atanh,\n  backendName: \"webgl\",\n  kernelFunc: atanh3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/pool_gpu.js\nvar Pool2DProgram = class {\n  constructor(convInfo, poolType, computePositions, flattenPositions = false, includeBatchInIndex = false) {\n    this.variableNames = [\"x\"];\n    if (poolType === \"avg\" && computePositions) {\n      throw new Error(\"Cannot compute positions for average pool.\");\n    }\n    const filterWidth = convInfo.filterWidth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationHeight = convInfo.dilationHeight;\n    const dilationWidth = convInfo.dilationWidth;\n    const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n    const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n    const padTop = convInfo.padInfo.top;\n    const padLeft = convInfo.padInfo.left;\n    this.outputShape = convInfo.outShape;\n    const isAvgPool = poolType === \"avg\";\n    const batchFlattenPositionStr = `((batch  * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + d`;\n    const flattenPositionStr = `(xR * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + d`;\n    let initializationValue = \"0.0\";\n    if (!isAvgPool) {\n      initializationValue = \"-1.0 / 1e-20\";\n    }\n    if (computePositions) {\n      const compareOp2 = \">=\";\n      this.userCode = `\n        const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});\n        const ivec2 pads = ivec2(${padTop}, ${padLeft});\n\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int batch = coords[0];\n          int d = coords[3];\n\n          ivec2 xRCCorner = coords.yz * strides - pads;\n          int xRCorner = xRCCorner.x;\n          int xCCorner = xRCCorner.y;\n\n          // max/min x(?, ?, d) to get y(yR, yC, d).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n          float avgValue = 0.0;\n\n          for (int wR = 0; wR < ${effectiveFilterHeight};\n              wR += ${dilationHeight}) {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= ${convInfo.inHeight}) {\n              continue;\n            }\n\n            for (int wC = 0; wC < ${effectiveFilterWidth};\n                wC += ${dilationWidth}) {\n              int xC = xCCorner + wC;\n\n              if (xC < 0 || xC >= ${convInfo.inWidth}) {\n                continue;\n              }\n\n              float value = getX(batch, xR, xC, d);\n\n              // If a min / max value has already been found, use it. If not,\n              // use the current value.\n              float currMinMaxValue = mix(\n                  value, minMaxValue, minMaxValueFound);\n              if (value ${compareOp2} currMinMaxValue) {\n                minMaxValue = value;\n                minMaxValueFound = 1.0;\n                minMaxPosition = ${flattenPositions ? includeBatchInIndex ? batchFlattenPositionStr : flattenPositionStr : `wR * ${effectiveFilterWidth} + wC`};\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      `;\n      return;\n    }\n    const compareOp = \"max\";\n    let returnValue = `${poolType}(${poolType}(${poolType}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;\n    if (poolType === \"avg\") {\n      returnValue = `avgValue / count`;\n    }\n    const filterWidthNearestVec4 = Math.floor(filterWidth / 4) * 4;\n    const filterWidthVec4Remainder = filterWidth % 4;\n    const updateSnippet = `\n      if (${isAvgPool}) {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = ${compareOp}(values, minMaxValue);\n      }\n    `;\n    this.userCode = `\n      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});\n      const ivec2 pads = ivec2(${padTop}, ${padLeft});\n      const float initializationValue = ${initializationValue};\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xR, int xC, int d) {\n        if (xC < 0 || xC >= ${convInfo.inWidth}) {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xR, xC, d);\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d = coords[3];\n\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // max/min x(?, ?, d) to get y(yR, yC, d).\n        // ? = to be determined\n        vec4 minMaxValue = vec4(${initializationValue});\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wR = 0; wR < ${effectiveFilterHeight};\n            wR += ${dilationHeight}) {\n          int xR = xRCorner + wR;\n\n          if (xR < 0 || xR >= ${convInfo.inHeight}) {\n            continue;\n          }\n\n          for (int wC = 0; wC < ${filterWidthNearestVec4}; wC += 4) {\n            int xC = xCCorner + wC * ${dilationWidth};\n\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + ${dilationWidth}, d),\n              getValue(batch, xR, xC + 2 * ${dilationWidth}, d),\n              getValue(batch, xR, xC + 3 * ${dilationWidth}, d)\n            );\n\n            ${updateSnippet}\n          }\n\n          int xC = xCCorner + ${filterWidthNearestVec4};\n          if (${filterWidthVec4Remainder === 1}) {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              initializationValue,\n              initializationValue,\n              initializationValue\n            );\n\n            ${updateSnippet}\n          } else if (${filterWidthVec4Remainder === 2}) {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + ${dilationWidth}, d),\n              initializationValue,\n              initializationValue\n            );\n\n            ${updateSnippet}\n          } else if (${filterWidthVec4Remainder === 3}) {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + ${dilationWidth}, d),\n              getValue(batch, xR, xC + 2 * ${dilationWidth}, d),\n              initializationValue\n            );\n\n            ${updateSnippet}\n          }\n        }\n        setOutput(${returnValue});\n      }\n    `;\n  }\n};\nvar Pool3DProgram = class {\n  constructor(convInfo, poolType, computePositions, flattenPositions = false, includeBatchInIndex = false) {\n    this.variableNames = [\"x\"];\n    if (poolType === \"avg\" && computePositions) {\n      throw new Error(\"Cannot compute positions for average pool.\");\n    }\n    const filterWidth = convInfo.filterWidth;\n    const strideDepth = convInfo.strideDepth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationDepth = convInfo.dilationDepth;\n    const dilationHeight = convInfo.dilationHeight;\n    const dilationWidth = convInfo.dilationWidth;\n    const effectiveFilterDepth = convInfo.effectiveFilterDepth;\n    const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n    const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n    const padFront = convInfo.padInfo.front;\n    const padTop = convInfo.padInfo.top;\n    const padLeft = convInfo.padInfo.left;\n    this.outputShape = convInfo.outShape;\n    const isAvgPool = poolType === \"avg\";\n    let initializationValue = \"0.0\";\n    if (!isAvgPool) {\n      initializationValue = \"-1.0 / 1e-20\";\n    }\n    if (computePositions) {\n      const compareOp2 = \">=\";\n      this.userCode = `\n        const ivec3 strides =\n            ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});\n        const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});\n\n        void main() {\n          ivec5 coords = getOutputCoords();\n          int batch = coords.x;\n          int ch = coords.u;\n\n          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n          int xDCorner = xCorner.x;\n          int xRCorner = xCorner.y;\n          int xCCorner = xCorner.z;\n\n          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n\n          for (int wD = 0; wD < ${effectiveFilterDepth};\n              wD += ${dilationDepth}) {\n            int xD = xDCorner + wD;\n\n            if (xD < 0 || xD >= ${convInfo.inDepth}) {\n              continue;\n            }\n\n            for (int wR = 0; wR < ${effectiveFilterHeight};\n                wR += ${dilationHeight}) {\n              int xR = xRCorner + wR;\n\n              if (xR < 0 || xR >= ${convInfo.inHeight}) {\n                continue;\n              }\n\n              for (int wC = 0; wC < ${effectiveFilterWidth};\n                  wC += ${dilationWidth}) {\n                int xC = xCCorner + wC;\n\n                if (xC < 0 || xC >= ${convInfo.inWidth}) {\n                  continue;\n                }\n\n                float value = getX(batch, xD, xR, xC, ch);\n\n                // If a min / max value has already been found, use it. If not,\n                // use the current value.\n                float currMinMaxValue = mix(\n                    value, minMaxValue, minMaxValueFound);\n                if (value ${compareOp2} currMinMaxValue) {\n                  minMaxValue = value;\n                  minMaxValueFound = 1.0;\n                  minMaxPosition = ${flattenPositions ? includeBatchInIndex ? `(((batch * ${convInfo.inDepth} + xD) * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + ch` : `((xD * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + ch` : `wD * ${effectiveFilterHeight} * ${effectiveFilterWidth} +\n                      wR * ${effectiveFilterWidth} + wC`};\n                }\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      `;\n      return;\n    }\n    const compareOp = \"max\";\n    let returnValue = `${poolType}(${poolType}(${poolType}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;\n    if (poolType === \"avg\") {\n      returnValue = `avgValue / count`;\n    }\n    const filterWidthNearestVec4 = Math.floor(filterWidth / 4) * 4;\n    const filterWidthVec4Remainder = filterWidth % 4;\n    const updateSnippet = `\n      if (${isAvgPool}) {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = ${compareOp}(values, minMaxValue);\n      }\n    `;\n    this.userCode = `\n      const ivec3 strides =\n        ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});\n      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});\n      const float initializationValue = ${initializationValue};\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xD, int xR, int xC, int ch) {\n        if (xC < 0 || xC >= ${convInfo.inWidth}) {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xD, xR, xC, ch);\n      }\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xDCorner = xCorner.x;\n        int xRCorner = xCorner.y;\n        int xCCorner = xCorner.z;\n\n        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).\n        // ? = to be determined\n        vec4 minMaxValue = vec4(${initializationValue});\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wD = 0; wD < ${effectiveFilterDepth};\n            wD += ${dilationDepth}) {\n          int xD = xDCorner + wD;\n\n          if (xD < 0 || xD >= ${convInfo.inDepth}) {\n            continue;\n          }\n\n          for (int wR = 0; wR < ${effectiveFilterHeight};\n            wR += ${dilationHeight}) {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= ${convInfo.inHeight}) {\n              continue;\n            }\n\n            for (int wC = 0; wC < ${filterWidthNearestVec4}; wC += 4) {\n              int xC = xCCorner + wC * ${dilationWidth};\n\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + ${dilationWidth}, ch),\n                getValue(batch, xD, xR, xC + 2 * ${dilationWidth}, ch),\n                getValue(batch, xD, xR, xC + 3 * ${dilationWidth}, ch)\n              );\n\n              ${updateSnippet}\n            }\n\n            int xC = xCCorner + ${filterWidthNearestVec4};\n            if (${filterWidthVec4Remainder === 1}) {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                initializationValue,\n                initializationValue,\n                initializationValue\n              );\n\n              ${updateSnippet}\n            } else if (${filterWidthVec4Remainder === 2}) {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + ${dilationWidth}, ch),\n                initializationValue,\n                initializationValue\n              );\n\n              ${updateSnippet}\n            } else if (${filterWidthVec4Remainder === 3}) {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + ${dilationWidth}, ch),\n                getValue(batch, xD, xR, xC + 2 * ${dilationWidth}, ch),\n                initializationValue\n              );\n\n              ${updateSnippet}\n            }\n          }\n          setOutput(${returnValue});\n        }\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/AvgPool.js\nfunction avgPool3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  assertNotComplex2(x, \"avgPool\");\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = 1;\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in avgPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  if (convInfo.filterWidth === 1 && convInfo.filterHeight === 1 && util_exports.arraysEqual(convInfo.inShape, convInfo.outShape)) {\n    return identity3({ inputs: { x }, backend: backend2 });\n  }\n  const avgPoolProgram = new Pool2DProgram(convInfo, \"avg\", false);\n  return backend2.runWebGLProgram(avgPoolProgram, [x], \"float32\");\n}\nvar avgPoolConfig2 = {\n  kernelName: AvgPool,\n  backendName: \"webgl\",\n  kernelFunc: avgPool3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/AvgPool3D.js\nfunction avgPool3D2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { filterSize, strides, pad: pad3, dimRoundingMode, dataFormat } = attrs;\n  const dilations = [1, 1, 1];\n  const convInfo = backend_util_exports.computePool3DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode, dataFormat);\n  const avgPoolProgram = new Pool3DProgram(convInfo, \"avg\", false);\n  return backend2.runWebGLProgram(avgPoolProgram, [x], \"float32\");\n}\nvar avgPool3DConfig2 = {\n  kernelName: AvgPool3D,\n  backendName: \"webgl\",\n  kernelFunc: avgPool3D2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/avg_pool_backprop_gpu.js\nvar AvgPool2DBackpropProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\"];\n    this.outputShape = convInfo.inShape;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationHeight = convInfo.dilationHeight;\n    const dilationWidth = convInfo.dilationWidth;\n    const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n    const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n    const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n    const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n    const avgMultiplier = 1 / (filterHeight * filterWidth);\n    this.userCode = `\n      const ivec2 pads = ivec2(${padTop}, ${padLeft});\n      const float avgMultiplier = float(${avgMultiplier});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ${effectiveFilterHeight};\n            wR += ${dilationHeight}) {\n          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;\n\n          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < ${effectiveFilterWidth};\n            wC+= ${dilationWidth}) {\n            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;\n\n            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n\n            dotProd += dyValue * avgMultiplier;\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\nvar AvgPool3DBackpropProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\"];\n    this.outputShape = convInfo.inShape;\n    const filterDepth = convInfo.filterDepth;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const strideDepth = convInfo.strideDepth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationDepth = convInfo.dilationDepth;\n    const dilationHeight = convInfo.dilationHeight;\n    const dilationWidth = convInfo.dilationWidth;\n    const effectiveFilterDepth = convInfo.effectiveFilterDepth;\n    const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n    const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n    const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;\n    const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n    const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n    const avgMultiplier = 1 / (filterDepth * filterHeight * filterWidth);\n    this.userCode = `\n      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});\n      const float avgMultiplier = float(${avgMultiplier});\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < ${effectiveFilterDepth};\n            wD += ${dilationDepth}) {\n          float dyD = float(dyDCorner + wD) / ${strideDepth}.0;\n\n          if (dyD < 0.0 || dyD >= ${convInfo.outDepth}.0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < ${effectiveFilterHeight};\n              wR += ${dilationHeight}) {\n            float dyR = float(dyRCorner + wR) / ${strideHeight}.0;\n\n            if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < ${effectiveFilterWidth};\n                wC += ${dilationWidth}) {\n              float dyC = float(dyCCorner + wC) / ${strideWidth}.0;\n\n              if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n\n              dotProd += dyValue * avgMultiplier;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/AvgPool3DGrad.js\nfunction avgPool3DGrad2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2 } = inputs;\n  const x = input2;\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = [1, 1, 1];\n  const convInfo = backend_util_exports.computePool3DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  const avgPoolBackpropProgram = new AvgPool3DBackpropProgram(convInfo);\n  return backend2.runWebGLProgram(avgPoolBackpropProgram, [dy], x.dtype);\n}\nvar avgPool3DGradConfig3 = {\n  kernelName: AvgPool3DGrad,\n  backendName: \"webgl\",\n  kernelFunc: avgPool3DGrad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/AvgPoolGrad.js\nfunction avgPoolGrad3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2 } = inputs;\n  const x = input2;\n  assertNotComplex2([dy, input2], \"avgPoolGrad\");\n  const { filterSize, strides, pad: pad3 } = attrs;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, 1, pad3);\n  const avgPoolBackpropProgram = new AvgPool2DBackpropProgram(convInfo);\n  return backend2.runWebGLProgram(avgPoolBackpropProgram, [dy], x.dtype);\n}\nvar avgPoolGradConfig3 = {\n  kernelName: AvgPoolGrad,\n  backendName: \"webgl\",\n  kernelFunc: avgPoolGrad3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/BatchMatMul.js\nfunction batchMatMul2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b } = inputs;\n  const { transposeA, transposeB } = attrs;\n  return batchMatMulImpl({ a, b, transposeA, transposeB, backend: backend2 });\n}\nvar batchMatMulConfig2 = {\n  kernelName: BatchMatMul,\n  backendName: \"webgl\",\n  kernelFunc: batchMatMul2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/batchnorm_gpu.js\nvar BatchNormProgram = class {\n  constructor(xShape, meanShape, varianceShape, offsetShape, scaleShape, varianceEpsilon) {\n    this.outputShape = [];\n    this.variableNames = [\"x\", \"mean\", \"variance\"];\n    backend_util_exports.assertAndGetBroadcastShape(xShape, meanShape);\n    backend_util_exports.assertAndGetBroadcastShape(xShape, varianceShape);\n    let offsetSnippet = \"0.0\";\n    if (offsetShape != null) {\n      backend_util_exports.assertAndGetBroadcastShape(xShape, offsetShape);\n      this.variableNames.push(\"offset\");\n      offsetSnippet = \"getOffsetAtOutCoords()\";\n    }\n    let scaleSnippet = \"1.0\";\n    if (scaleShape != null) {\n      backend_util_exports.assertAndGetBroadcastShape(xShape, scaleShape);\n      this.variableNames.push(\"scale\");\n      scaleSnippet = \"getScaleAtOutCoords()\";\n    }\n    this.outputShape = xShape;\n    this.userCode = `\n      void main() {\n        float x = getXAtOutCoords();\n        float mean = getMeanAtOutCoords();\n        float variance = getVarianceAtOutCoords();\n        float offset = ${offsetSnippet};\n        float scale = ${scaleSnippet};\n        float inv = scale * inversesqrt(variance + float(${varianceEpsilon}));\n        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/batchnorm_packed_gpu.js\nvar BatchNormPackedProgram = class {\n  constructor(xShape, meanShape, varianceShape, offsetShape, scaleShape, varianceEpsilon) {\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.variableNames = [\"x\", \"mean\", \"variance\"];\n    backend_util_exports.assertAndGetBroadcastShape(xShape, meanShape);\n    backend_util_exports.assertAndGetBroadcastShape(xShape, varianceShape);\n    let offsetSnippet = \"vec4(0.0)\";\n    if (offsetShape != null) {\n      backend_util_exports.assertAndGetBroadcastShape(xShape, offsetShape);\n      this.variableNames.push(\"offset\");\n      offsetSnippet = \"getOffsetAtOutCoords()\";\n    }\n    let scaleSnippet = \"vec4(1.0)\";\n    if (scaleShape != null) {\n      backend_util_exports.assertAndGetBroadcastShape(xShape, scaleShape);\n      this.variableNames.push(\"scale\");\n      scaleSnippet = \"getScaleAtOutCoords()\";\n    }\n    this.outputShape = xShape;\n    this.userCode = `\n      void main() {\n        vec4 offset = ${offsetSnippet};\n        vec4 scale = ${scaleSnippet};\n\n        vec4 x = getXAtOutCoords();\n        vec4 mean = getMeanAtOutCoords();\n        vec4 variance = getVarianceAtOutCoords();\n\n        vec4 inv = scale * inversesqrt(variance + vec4(${varianceEpsilon}));\n\n        setOutput((x - mean) * inv + offset);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/BatchNorm.js\nvar batchNorm3 = ({ inputs, backend: backend2, attrs }) => {\n  const { x, mean: mean5, variance, offset, scale: scale2 } = inputs;\n  util_exports.assert(mean5.shape.length === variance.shape.length, () => \"Batch normalization gradient requires mean and variance to have equal ranks.\");\n  util_exports.assert(offset == null || mean5.shape.length === offset.shape.length, () => \"Batch normalization gradient requires mean and offset to have equal ranks.\");\n  util_exports.assert(scale2 == null || mean5.shape.length === scale2.shape.length, () => \"Batch normalization gradient requires mean and scale to have equal ranks.\");\n  let { varianceEpsilon } = attrs;\n  if (varianceEpsilon == null) {\n    varianceEpsilon = 1e-3;\n  }\n  const finalInputs = [x, mean5, variance];\n  let offsetShape = null;\n  if (offset != null) {\n    offsetShape = offset.shape;\n    finalInputs.push(offset);\n  }\n  let scaleShape = null;\n  if (scale2 != null) {\n    scaleShape = scale2.shape;\n    finalInputs.push(scale2);\n  }\n  const program = env().getBool(\"WEBGL_PACK_NORMALIZATION\") ? new BatchNormPackedProgram(x.shape, mean5.shape, variance.shape, offsetShape, scaleShape, varianceEpsilon) : new BatchNormProgram(x.shape, mean5.shape, variance.shape, offsetShape, scaleShape, varianceEpsilon);\n  const output = backend2.runWebGLProgram(program, finalInputs, finalInputs[0].dtype);\n  return output;\n};\nvar batchNormConfig2 = {\n  kernelName: FusedBatchNorm,\n  backendName: \"webgl\",\n  kernelFunc: batchNorm3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/slice_gpu.js\nvar SliceProgram = class {\n  constructor(destSize) {\n    this.variableNames = [\"source\"];\n    this.outputShape = destSize;\n    this.rank = destSize.length;\n    const dtype = getCoordsDataType(this.rank);\n    this.customUniforms = [{ name: \"start\", arrayIndex: this.rank, type: \"int\" }];\n    const sourceCoords = getCoords(this.rank);\n    let body;\n    const coordSum = destSize.map((_, i2) => {\n      return `sourceLoc.${coords[i2]} = start[${i2}] + coords.${coords[i2]};`;\n    });\n    body = `\n        ${dtype} sourceLoc;\n        ${dtype} coords = getOutputCoords();\n        ${coordSum.join(\"\\n\")}\n      `;\n    this.userCode = `\n      void main() {\n        ${body}\n        setOutput(getSource(${sourceCoords}));\n      }\n    `;\n  }\n};\nvar coords = [\"x\", \"y\", \"z\", \"w\", \"u\", \"v\"];\nfunction getCoords(rank) {\n  if (rank === 1) {\n    return \"sourceLoc\";\n  } else if (rank <= 6) {\n    return coords.slice(0, rank).map((x) => \"sourceLoc.\" + x).join(\",\");\n  } else {\n    throw Error(`Slicing for rank ${rank} is not yet supported`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/slice_packed_gpu.js\nvar SlicePackedProgram = class {\n  constructor(destSize) {\n    this.variableNames = [\"source\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = destSize;\n    this.rank = destSize.length;\n    this.customUniforms = [{ name: \"start\", arrayIndex: this.rank, type: \"int\" }];\n    const dtype = getCoordsDataType(this.rank);\n    const coords3 = getChannels(\"coords\", this.rank);\n    const sourceLoc = getChannels(\"sourceLoc\", this.rank);\n    const innerDims = this.rank === 1 ? \"sourceLoc\" : `vec2(${sourceLoc.slice(-2).join()})`;\n    const getChannel = `getChannel(getSource(${sourceLoc.join()}), ${innerDims})`;\n    const upperRow = `\n      result.x = ${getChannel};\n      if (++${coords3[this.rank - 1]} < ${destSize[this.rank - 1]}) {\n        ++${sourceLoc[this.rank - 1]};\n        result.y = ${getChannel};\n        --${sourceLoc[this.rank - 1]};\n      }\n    `;\n    const lowerRow = this.rank === 1 ? \"\" : `\n      --${coords3[this.rank - 1]};\n      if (++${coords3[this.rank - 2]} < ${destSize[this.rank - 2]}) {\n        ++${sourceLoc[this.rank - 2]};\n        result.z = ${getChannel};\n        if (++${coords3[this.rank - 1]} < ${destSize[this.rank - 1]}) {\n          ++${sourceLoc[this.rank - 1]};\n          result.w = ${getChannel};\n        }\n      }\n    `;\n    const sourceLocSetup = this.rank <= 4 ? `sourceLoc = coords +\n            ${dtype}(${destSize.map((_, i2) => `start[${i2}]`).join()});` : destSize.map((_, i2) => `${sourceLoc[i2]} = ${coords3[i2]} + start[${i2}];`).join(\"\\n\");\n    this.userCode = `\n      void main() {\n        ${dtype} coords = getOutputCoords();\n        ${dtype} sourceLoc;\n        ${sourceLocSetup}\n        vec4 result = vec4(0.);\n        ${upperRow}\n        ${lowerRow}\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Slice.js\nfunction shallowSlice(x, begin, size, backend2) {\n  const xTexData = backend2.texData.get(x.dataId);\n  const t2 = backend2.makeTensorInfo(size, x.dtype);\n  const newTexData = backend2.texData.get(t2.dataId);\n  Object.assign(newTexData, xTexData);\n  newTexData.refCount = 1;\n  newTexData.shape = size;\n  newTexData.dtype = x.dtype;\n  let flatOffset = slice_util_exports.computeFlatOffset(begin, util_exports.computeStrides(x.shape));\n  if (xTexData.slice) {\n    flatOffset += xTexData.slice.flatOffset;\n  }\n  newTexData.slice = {\n    flatOffset,\n    origDataId: xTexData.slice && xTexData.slice.origDataId || x.dataId\n  };\n  const refCount = backend2.dataRefCount.get(newTexData.slice.origDataId) || 1;\n  backend2.dataRefCount.set(newTexData.slice.origDataId, refCount + 1);\n  return t2;\n}\nfunction slice3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { begin, size } = attrs;\n  const [$begin, $size] = slice_util_exports.parseSliceParams(x, begin, size);\n  slice_util_exports.assertParamsValid(x, $begin, $size);\n  if (util_exports.sizeFromShape($size) === 0) {\n    return backend2.makeTensorInfo($size, x.dtype, []);\n  }\n  if (backend2.shouldExecuteOnCPU([x]) || x.dtype === \"string\") {\n    const xTexData = backend2.texData.get(x.dataId);\n    const outValues = sliceImplCPU(xTexData.values, $begin, $size, x.shape, x.dtype);\n    return backend2.makeTensorInfo($size, x.dtype, outValues);\n  }\n  const { isPacked } = backend2.texData.get(x.dataId);\n  const isContinous = slice_util_exports.isSliceContinous(x.shape, $begin, $size);\n  if (isPacked || !isContinous) {\n    const program = env().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\") ? new SlicePackedProgram($size) : new SliceProgram($size);\n    const customValues = [$begin];\n    return backend2.runWebGLProgram(program, [x], x.dtype, customValues);\n  }\n  backend2.uploadToGPU(x.dataId);\n  return shallowSlice(x, $begin, $size, backend2);\n}\nvar sliceConfig2 = {\n  kernelName: Slice,\n  backendName: \"webgl\",\n  kernelFunc: slice3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/BatchToSpaceND.js\nvar batchToSpaceND3 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, crops } = attrs;\n  util_exports.assert(x.shape.length <= 4, () => \"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet\");\n  const prod6 = blockShape.reduce((a, b) => a * b);\n  const reshaped = backend_util_exports.getReshaped(x.shape, blockShape, prod6);\n  const permuted = backend_util_exports.getPermuted(reshaped.length, blockShape.length);\n  const reshapedPermuted = backend_util_exports.getReshapedPermuted(x.shape, blockShape, prod6);\n  const sliceBeginCoords = backend_util_exports.getSliceBeginCoords(crops, blockShape.length);\n  const sliceSize = backend_util_exports.getSliceSize(reshapedPermuted, crops, blockShape.length);\n  const toDispose = [];\n  const reshapedIntermediate = reshape4({ inputs: { x }, backend: backend2, attrs: { shape: reshaped } });\n  const transposedIntermediate = transpose3({ inputs: { x: reshapedIntermediate }, backend: backend2, attrs: { perm: permuted } });\n  const reshapedIntermediate2 = reshape4({\n    inputs: { x: transposedIntermediate },\n    backend: backend2,\n    attrs: { shape: reshapedPermuted }\n  });\n  const sliced = slice3({\n    inputs: { x: reshapedIntermediate2 },\n    backend: backend2,\n    attrs: { begin: sliceBeginCoords, size: sliceSize }\n  });\n  toDispose.push(reshapedIntermediate);\n  toDispose.push(transposedIntermediate);\n  toDispose.push(reshapedIntermediate2);\n  toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return sliced;\n};\nvar batchToSpaceNDConfig2 = {\n  kernelName: BatchToSpaceND,\n  backendName: \"webgl\",\n  kernelFunc: batchToSpaceND3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Bincount.js\nfunction bincount3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, weights } = inputs;\n  const { size } = attrs;\n  const xVals = backend2.readSync(x.dataId);\n  const weightsVals = backend2.readSync(weights.dataId);\n  const outVals = bincountImplCPU(xVals, weightsVals, weights.dtype, weights.shape, size);\n  return backend2.makeTensorInfo([size], weights.dtype, outVals);\n}\nvar bincountConfig2 = {\n  kernelName: Bincount,\n  backendName: \"webgl\",\n  kernelFunc: bincount3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/BroadcastArgs.js\nfunction broadcastArgs3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { s0, s1 } = inputs;\n  const s0Vals = backend2.readSync(s0.dataId);\n  const s1Vals = backend2.readSync(s1.dataId);\n  const broadcastShape = backend_util_exports.assertAndGetBroadcastShape(Array.from(s0Vals), Array.from(s1Vals));\n  return backend2.makeTensorInfo([broadcastShape.length], \"int32\", Int32Array.from(broadcastShape));\n}\nvar broadcastArgsConfig2 = {\n  kernelName: BroadcastArgs,\n  backendName: \"webgl\",\n  kernelFunc: broadcastArgs3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/NotEqual.js\nvar NOT_EQUAL = `return float(a != b);`;\nvar notEqual3 = binaryKernelFunc2({ opSnippet: NOT_EQUAL, cpuKernelImpl: notEqualImplCPU, dtype: \"bool\" });\nvar notEqualConfig2 = {\n  kernelName: NotEqual,\n  backendName: \"webgl\",\n  kernelFunc: notEqual3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Real.js\nfunction real3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const inputData = backend2.texData.get(input2.dataId);\n  return identity3({ inputs: { x: inputData.complexTensorInfos.real }, backend: backend2 });\n}\nvar realConfig2 = {\n  kernelName: Real,\n  backendName: \"webgl\",\n  kernelFunc: real3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/int.js\nvar TO_INT = `return float(int(x));`;\nfunction int(input2, backend2) {\n  const program = new UnaryOpProgram(input2.shape, TO_INT);\n  const output = backend2.runWebGLProgram(program, [input2], \"int32\");\n  return { dataId: output.dataId, shape: output.shape, dtype: output.dtype };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Cast.js\nfunction cast4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { dtype } = attrs;\n  if (dtype === \"complex64\") {\n    if (x.dtype === \"complex64\") {\n      return identity3({ inputs: { x }, backend: backend2 });\n    }\n    const zerosTensor = zeros(x.shape);\n    const floatX = cast4({ inputs: { x }, backend: backend2, attrs: { dtype: \"float32\" } });\n    const result = complex3({ inputs: { real: floatX, imag: zerosTensor }, backend: backend2 });\n    zerosTensor.dispose();\n    backend2.disposeIntermediateTensorInfo(floatX);\n    return result;\n  }\n  if (x.dtype === \"complex64\") {\n    const realPart = real3({ inputs: { input: x }, backend: backend2 });\n    const result = cast4({ inputs: { x: realPart }, backend: backend2, attrs: { dtype } });\n    backend2.disposeIntermediateTensorInfo(realPart);\n    return result;\n  }\n  if (!util_exports.hasEncodingLoss(x.dtype, dtype)) {\n    const result = identity3({ inputs: { x }, backend: backend2 });\n    return { dataId: result.dataId, shape: result.shape, dtype };\n  }\n  if (dtype === \"int32\") {\n    return int(x, backend2);\n  }\n  if (dtype === \"bool\") {\n    const zerosTensorInfo = backend2.makeTensorInfo([], \"bool\", util_exports.getTypedArrayFromDType(\"bool\", 1));\n    const binaryInputs = { a: x, b: zerosTensorInfo };\n    const result = notEqual3({ inputs: binaryInputs, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(zerosTensorInfo);\n    return result;\n  }\n  throw new Error(`Error in Cast: failed to cast ${x.dtype} to ${dtype}`);\n}\nvar castConfig2 = {\n  kernelName: Cast,\n  backendName: \"webgl\",\n  kernelFunc: cast4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Ceil.js\nvar CEIL = `return ceil(x);`;\nvar ceil3 = unaryKernelFunc2({ opSnippet: CEIL, packedOpSnippet: CEIL, cpuKernelImpl: ceilImplCPU });\nvar ceilConfig2 = {\n  kernelName: Ceil,\n  backendName: \"webgl\",\n  kernelFunc: ceil3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/clip_gpu.js\nvar ClipProgram = class {\n  constructor(aShape) {\n    this.variableNames = [\"A\"];\n    this.customUniforms = [\n      { name: \"minVal\", type: \"float\" },\n      { name: \"maxVal\", type: \"float\" }\n    ];\n    this.outputShape = aShape;\n    this.userCode = `\n\n      void main() {\n        float value = getAAtOutCoords();\n        if (isnan(value)) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, minVal, maxVal));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/clip_packed_gpu.js\nvar ClipPackedProgram = class {\n  constructor(aShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.customUniforms = [\n      { name: \"minVal\", type: \"float\" },\n      { name: \"maxVal\", type: \"float\" }\n    ];\n    this.outputShape = aShape;\n    this.userCode = `\n      void main() {\n        vec4 value = getAAtOutCoords();\n\n        if (any(isnan(value))) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ClipByValue.js\nfunction clipByValue3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { clipValueMin, clipValueMax } = attrs;\n  let program;\n  if (env().getBool(\"WEBGL_PACK_CLIP\")) {\n    program = new ClipPackedProgram(x.shape);\n  } else {\n    program = new ClipProgram(x.shape);\n  }\n  const customValues = [[clipValueMin], [clipValueMax]];\n  return backend2.runWebGLProgram(program, [x], x.dtype, customValues);\n}\nvar clipByValueConfig2 = {\n  kernelName: ClipByValue,\n  backendName: \"webgl\",\n  kernelFunc: clipByValue3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/complex_abs_gpu.js\nvar ComplexAbsProgram = class {\n  constructor(shape) {\n    this.variableNames = [\"real\", \"imag\"];\n    this.outputShape = shape;\n    this.userCode = `\n      void main() {\n        float re = abs(getRealAtOutCoords());\n        float im = abs(getImagAtOutCoords());\n        float mx = max(re, im);\n\n        // sadly the length function in glsl is not underflow-safe\n        // (at least not on Intel GPUs). So the safe solution is\n        // to ensure underflow-safety in all cases.\n        setOutput(\n          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))\n        );\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ComplexAbs.js\nfunction makeComplexComponentTensorInfo(complexTensor, complexPart) {\n  return {\n    dataId: complexPart.dataId,\n    dtype: complexPart.dtype,\n    shape: complexTensor.shape\n  };\n}\nfunction complexAbs2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  const xData = backend2.texData.get(x.dataId);\n  const program = new ComplexAbsProgram(x.shape);\n  const programInputs = [\n    makeComplexComponentTensorInfo(x, xData.complexTensorInfos.real),\n    makeComplexComponentTensorInfo(x, xData.complexTensorInfos.imag)\n  ];\n  return backend2.runWebGLProgram(program, programInputs, programInputs[0].dtype);\n}\nvar complexAbsConfig2 = {\n  kernelName: ComplexAbs,\n  backendName: \"webgl\",\n  kernelFunc: complexAbs2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/concat_gpu.js\nvar ConcatProgram = class {\n  constructor(shapes) {\n    this.outputShape = [];\n    this.outputShape = backend_util_exports.computeOutShape(shapes, 1);\n    this.variableNames = shapes.map((_, i2) => `T${i2}`);\n    const offsets = new Array(shapes.length - 1);\n    offsets[0] = shapes[0][1];\n    for (let i2 = 1; i2 < offsets.length; i2++) {\n      offsets[i2] = offsets[i2 - 1] + shapes[i2][1];\n    }\n    const snippets = [`if (yC < ${offsets[0]}) setOutput(getT0(yR, yC));`];\n    for (let i2 = 1; i2 < offsets.length; i2++) {\n      const shift = offsets[i2 - 1];\n      snippets.push(`else if (yC < ${offsets[i2]}) setOutput(getT${i2}(yR, yC-${shift}));`);\n    }\n    const lastIndex = offsets.length;\n    const lastShift = offsets[offsets.length - 1];\n    snippets.push(`else setOutput(getT${lastIndex}(yR, yC-${lastShift}));`);\n    this.userCode = `\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int yR = coords.x;\n        int yC = coords.y;\n\n        ${snippets.join(\"\\n        \")}\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/concat_packed_gpu.js\nvar ConcatPackedProgram = class {\n  constructor(shapes, axis) {\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = [];\n    this.outputShape = backend_util_exports.computeOutShape(shapes, axis);\n    const shape = this.outputShape;\n    const rank = shape.length;\n    const dtype = getCoordsDataType(rank);\n    const coords3 = getChannels(\"coords\", rank);\n    const channels = [\"x\", \"y\", \"z\", \"w\", \"u\", \"v\"].slice(0, rank);\n    this.variableNames = shapes.map((_, i2) => `T${i2}`);\n    const offsets = new Array(shapes.length - 1);\n    offsets[0] = shapes[0][axis];\n    for (let i2 = 1; i2 < offsets.length; i2++) {\n      offsets[i2] = offsets[i2 - 1] + shapes[i2][axis];\n    }\n    const channel = channels[axis];\n    const lastChannels = channels.slice(-2);\n    const allChannels = channels.join();\n    let getValueSnippet = `if (${channel} < ${offsets[0]}) {\n        return getChannel(\n            getT0(${allChannels}), vec2(${lastChannels.join()}));\n        }`;\n    for (let i2 = 1; i2 < offsets.length; i2++) {\n      const shift2 = offsets[i2 - 1];\n      getValueSnippet += `\n        if (${channel} < ${offsets[i2]}  && ${channel} >= ${offsets[i2 - 1]}) {\n          return getChannel(\n            getT${i2}(${shiftedChannels(channels, channel, shift2)}),\n            vec2(${shiftedChannels(lastChannels, channel, shift2)}));\n        }`;\n    }\n    const lastIndex = offsets.length;\n    const shift = offsets[offsets.length - 1];\n    getValueSnippet += `\n        return getChannel(\n          getT${lastIndex}(${shiftedChannels(channels, channel, shift)}),\n          vec2(${shiftedChannels(lastChannels, channel, shift)}));`;\n    this.userCode = `\n      float getValue(${channels.map((x) => \"int \" + x)}) {\n        ${getValueSnippet}\n      }\n\n      void main() {\n        ${dtype} coords = getOutputCoords();\n        vec4 result = vec4(getValue(${coords3}), 0., 0., 0.);\n\n        ${coords3[rank - 1]} = ${coords3[rank - 1]} + 1;\n        if (${coords3[rank - 1]} < ${shape[rank - 1]}) {\n          result.g = getValue(${coords3});\n        }\n\n        ${coords3[rank - 2]} = ${coords3[rank - 2]} + 1;\n        if (${coords3[rank - 2]} < ${shape[rank - 2]}) {\n          result.a = getValue(${coords3});\n        }\n\n        ${coords3[rank - 1]} = ${coords3[rank - 1]} - 1;\n        if (${coords3[rank - 2]} < ${shape[rank - 2]} &&\n            ${coords3[rank - 1]} < ${shape[rank - 1]}) {\n          result.b = getValue(${coords3});\n        }\n        setOutput(result);\n      }\n    `;\n  }\n};\nfunction shiftedChannels(channels, channel, shift) {\n  const channelIdx = channels.indexOf(channel);\n  const res = channels.map((c, idx) => {\n    if (idx === channelIdx) {\n      return `${c} - ${shift}`;\n    } else {\n      return c;\n    }\n  });\n  return res.join();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Imag.js\nfunction imag3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const inputData = backend2.texData.get(input2.dataId);\n  return identity3({ inputs: { x: inputData.complexTensorInfos.imag }, backend: backend2 });\n}\nvar imagConfig2 = {\n  kernelName: Imag,\n  backendName: \"webgl\",\n  kernelFunc: imag3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Concat_impl.js\nfunction concatImpl2(inputs, axis, backend2) {\n  const dtype = inputs[0].dtype;\n  if (dtype === \"complex64\") {\n    const reals = inputs.map((t2) => real3({ inputs: { input: t2 }, backend: backend2 }));\n    const imags = inputs.map((t2) => imag3({ inputs: { input: t2 }, backend: backend2 }));\n    const realConcated = concatImpl2(reals, axis, backend2);\n    const imagConcated = concatImpl2(imags, axis, backend2);\n    const result2 = complex3({ inputs: { real: realConcated, imag: imagConcated }, backend: backend2 });\n    reals.forEach((r2) => backend2.disposeIntermediateTensorInfo(r2));\n    imags.forEach((i2) => backend2.disposeIntermediateTensorInfo(i2));\n    backend2.disposeIntermediateTensorInfo(realConcated);\n    backend2.disposeIntermediateTensorInfo(imagConcated);\n    return result2;\n  }\n  let runOnCpu = backend2.shouldExecuteOnCPU(inputs);\n  if (dtype === \"string\") {\n    runOnCpu = true;\n  }\n  if (runOnCpu) {\n    const tensors2D2 = inputs.map((t2) => {\n      const innerSize = util_exports.sizeFromShape(t2.shape.slice(axis));\n      const shape = [-1, innerSize];\n      return reshape4({ inputs: { x: t2 }, backend: backend2, attrs: { shape } });\n    });\n    const inputsValShapes = tensors2D2.map((t2) => {\n      return { vals: backend2.readSync(t2.dataId), shape: t2.shape };\n    });\n    const outShape2 = backend_util_exports.computeOutShape(tensors2D2.map((t2) => t2.shape), 1);\n    const simplyConcat = tensors2D2[0].shape[0] === 1;\n    const outVals = concatImplCPU(inputsValShapes, outShape2, dtype, simplyConcat);\n    const finalOutShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), axis);\n    const outInfo = backend2.makeTensorInfo(finalOutShape, dtype, outVals);\n    tensors2D2.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n    return outInfo;\n  }\n  const maxTexturesInShader = env().getNumber(\"WEBGL_MAX_TEXTURES_IN_SHADER\");\n  if (inputs.length > maxTexturesInShader) {\n    const reducedInputs = [];\n    for (let i2 = 0; i2 < inputs.length; i2 += maxTexturesInShader) {\n      const subArray = inputs.slice(i2, i2 + maxTexturesInShader);\n      reducedInputs.push(concatImpl2(subArray, axis, backend2));\n    }\n    const result2 = concatImpl2(reducedInputs, axis, backend2);\n    for (const i2 of reducedInputs) {\n      backend2.disposeIntermediateTensorInfo(i2);\n    }\n    return result2;\n  }\n  if (env().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\") && inputs[0].shape.length > 1) {\n    const program2 = new ConcatPackedProgram(inputs.map((t2) => t2.shape), axis);\n    return backend2.runWebGLProgram(program2, inputs, dtype);\n  }\n  const { tensors2D, outShape } = computeTensors2D(inputs, axis, backend2);\n  const program = new ConcatProgram(tensors2D.map((t2) => t2.shape));\n  const result = backend2.runWebGLProgram(program, tensors2D, dtype);\n  tensors2D.forEach((r2) => backend2.disposeIntermediateTensorInfo(r2));\n  const reshapedResult = reshape4({ inputs: { x: result }, attrs: { shape: outShape }, backend: backend2 });\n  backend2.disposeIntermediateTensorInfo(result);\n  return reshapedResult;\n}\nfunction computeTensors2D(inputs, axis, backend2) {\n  const outShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), axis);\n  const tensors2D = inputs.map((x) => reshape4({\n    inputs: { x },\n    attrs: { shape: [-1, util_exports.sizeFromShape(x.shape.slice(axis))] },\n    backend: backend2\n  }));\n  return { tensors2D, outShape };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Concat.js\nfunction concat3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { axis } = attrs;\n  const $axis = util_exports.parseAxisParam(axis, inputs[0].shape)[0];\n  const outShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), $axis);\n  if (util_exports.sizeFromShape(outShape) === 0) {\n    return backend2.makeTensorInfo(outShape, inputs[0].dtype, []);\n  }\n  const $inputs = inputs.filter((t2) => util_exports.sizeFromShape(t2.shape) > 0);\n  if ($inputs.length === 1) {\n    return identity3({ inputs: { x: $inputs[0] }, backend: backend2 });\n  }\n  const shapes = $inputs.map((t2) => t2.shape);\n  backend_util_exports.assertParamsConsistent(shapes, $axis);\n  return concatImpl2($inputs, $axis, backend2);\n}\nvar concatConfig2 = {\n  kernelName: Concat,\n  backendName: \"webgl\",\n  kernelFunc: concat3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_gpu.js\nvar Conv2DProgram = class {\n  constructor(convInfo, addBias = false, activation2 = null, hasPreluActivationWeights = false, hasLeakyreluAlpha = false) {\n    this.variableNames = [\"x\", \"W\"];\n    this.outputShape = convInfo.outShape;\n    const padTop = convInfo.padInfo.top;\n    const padLeft = convInfo.padInfo.left;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationHeight = convInfo.dilationHeight;\n    const dilationWidth = convInfo.dilationWidth;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const inputDepthNearestVec4 = Math.floor(convInfo.inChannels / 4) * 4;\n    const inputDepthVec4Remainder = convInfo.inChannels % 4;\n    const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n    const rowDim = isChannelsLast ? 1 : 2;\n    const colDim = isChannelsLast ? 2 : 3;\n    const channelDim = isChannelsLast ? 3 : 1;\n    let activationSnippet = \"\", applyActivationSnippet = \"\";\n    if (activation2) {\n      if (hasPreluActivationWeights) {\n        activationSnippet = `float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          ${activation2}\n        }`;\n      } else if (hasLeakyreluAlpha) {\n        activationSnippet = `float activation(float a) {\n          float b = getLeakyreluAlphaAtOutCoords();\n          ${activation2}\n        }`;\n      } else {\n        activationSnippet = `\n          float activation(float x) {\n            ${activation2}\n          }\n        `;\n      }\n      applyActivationSnippet = `result = activation(result);`;\n    }\n    const addBiasSnippet = addBias ? \"result += getBiasAtOutCoords();\" : \"\";\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivationWeights) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    if (hasLeakyreluAlpha) {\n      this.variableNames.push(\"leakyreluAlpha\");\n    }\n    this.userCode = `\n      ${activationSnippet}\n\n      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});\n      const ivec2 pads = ivec2(${padTop}, ${padLeft});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d2 = coords[${channelDim}];\n\n        ivec2 xRCCorner =\n            ivec2(coords[${rowDim}], coords[${colDim}]) * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ${filterHeight}; wR++) {\n          int xR = xRCorner + wR * ${dilationHeight};\n\n          if (xR < 0 || xR >= ${convInfo.inHeight}) {\n            continue;\n          }\n\n          for (int wC = 0; wC < ${filterWidth}; wC++) {\n            int xC = xCCorner + wC * ${dilationWidth};\n\n            if (xC < 0 || xC >= ${convInfo.inWidth}) {\n              continue;\n            }\n\n            for (int d1 = 0; d1 < ${inputDepthNearestVec4}; d1 += 4) {\n              vec4 wValues = vec4(\n                getW(wR, wC, d1, d2),\n                getW(wR, wC, d1 + 1, d2),\n                getW(wR, wC, d1 + 2, d2),\n                getW(wR, wC, d1 + 3, d2)\n              );\n\n              if (${isChannelsLast}) {\n                vec4 xValues = vec4(\n                  getX(batch, xR, xC, d1),\n                  getX(batch, xR, xC, d1 + 1),\n                  getX(batch, xR, xC, d1 + 2),\n                  getX(batch, xR, xC, d1 + 3)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec4 xValues = vec4(\n                  getX(batch, d1, xR, xC),\n                  getX(batch, d1 + 1, xR, xC),\n                  getX(batch, d1 + 2, xR, xC),\n                  getX(batch, d1 + 3, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n\n            if (${inputDepthVec4Remainder === 1}) {\n\n              if (${isChannelsLast}) {\n                dotProd +=\n                    getX(batch, xR, xC, ${inputDepthNearestVec4}) *\n                    getW(wR, wC, ${inputDepthNearestVec4}, d2);\n              } else {\n                dotProd +=\n                    getX(batch, ${inputDepthNearestVec4}, xR, xC) *\n                    getW(wR, wC, ${inputDepthNearestVec4}, d2);\n              }\n\n            } else if (${inputDepthVec4Remainder === 2}) {\n              vec2 wValues = vec2(\n                getW(wR, wC, ${inputDepthNearestVec4}, d2),\n                getW(wR, wC, ${inputDepthNearestVec4} + 1, d2)\n              );\n\n              if (${isChannelsLast}) {\n                vec2 xValues = vec2(\n                  getX(batch, xR, xC, ${inputDepthNearestVec4}),\n                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 1)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec2 xValues = vec2(\n                  getX(batch, ${inputDepthNearestVec4}, xR, xC),\n                  getX(batch, ${inputDepthNearestVec4} + 1, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            } else if (${inputDepthVec4Remainder === 3}) {\n              vec3 wValues = vec3(\n                getW(wR, wC, ${inputDepthNearestVec4}, d2),\n                getW(wR, wC, ${inputDepthNearestVec4} + 1, d2),\n                getW(wR, wC, ${inputDepthNearestVec4} + 2, d2)\n              );\n\n              if (${isChannelsLast}) {\n                vec3 xValues = vec3(\n                  getX(batch, xR, xC, ${inputDepthNearestVec4}),\n                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 1),\n                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec3 xValues = vec3(\n                  getX(batch, ${inputDepthNearestVec4}, xR, xC),\n                  getX(batch, ${inputDepthNearestVec4} + 1, xR, xC),\n                  getX(batch, ${inputDepthNearestVec4} + 2, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            }\n          }\n        }\n\n        float result = dotProd;\n        ${addBiasSnippet}\n        ${applyActivationSnippet}\n        setOutput(result);\n      }\n    `;\n  }\n};\nvar Conv3DProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"x\", \"W\"];\n    this.outputShape = convInfo.outShape;\n    const padFront = convInfo.padInfo.front;\n    const padTop = convInfo.padInfo.top;\n    const padLeft = convInfo.padInfo.left;\n    const strideDepth = convInfo.strideDepth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationDepth = convInfo.dilationDepth;\n    const dilationHeight = convInfo.dilationHeight;\n    const dilationWidth = convInfo.dilationWidth;\n    const filterDepth = convInfo.filterDepth;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const inputDepthNearestVec4 = Math.floor(convInfo.inChannels / 4) * 4;\n    const inputDepthVec4Remainder = convInfo.inChannels % 4;\n    this.userCode = `\n      const ivec3 strides = ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});\n      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d2 = coords.u;\n\n        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xFCorner = xFRCCorner.x;\n        int xRCorner = xFRCCorner.y;\n        int xCCorner = xFRCCorner.z;\n\n        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get\n        // y(yF, yR, yC, d2). ? = to be determined. : = across all\n        // values in that axis.\n        float dotProd = 0.0;\n        for (int wF = 0; wF < ${filterDepth}; wF++) {\n          int xF = xFCorner + wF * ${dilationDepth};\n\n          if (xF < 0 || xF >= ${convInfo.inDepth}) {\n            continue;\n          }\n\n          for (int wR = 0; wR < ${filterHeight}; wR++) {\n            int xR = xRCorner + wR * ${dilationHeight};\n\n            if (xR < 0 || xR >= ${convInfo.inHeight}) {\n              continue;\n            }\n\n            for (int wC = 0; wC < ${filterWidth}; wC++) {\n              int xC = xCCorner + wC * ${dilationWidth};\n\n              if (xC < 0 || xC >= ${convInfo.inWidth}) {\n                continue;\n              }\n\n              for (int d1 = 0; d1 < ${inputDepthNearestVec4}; d1 += 4) {\n                vec4 xValues = vec4(\n                  getX(batch, xF, xR, xC, d1),\n                  getX(batch, xF, xR, xC, d1 + 1),\n                  getX(batch, xF, xR, xC, d1 + 2),\n                  getX(batch, xF, xR, xC, d1 + 3)\n                );\n                vec4 wValues = vec4(\n                  getW(wF, wR, wC, d1, d2),\n                  getW(wF, wR, wC, d1 + 1, d2),\n                  getW(wF, wR, wC, d1 + 2, d2),\n                  getW(wF, wR, wC, d1 + 3, d2)\n                );\n\n                dotProd += dot(xValues, wValues);\n              }\n\n              if (${inputDepthVec4Remainder === 1}) {\n                dotProd +=\n                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}) *\n                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2);\n              } else if (${inputDepthVec4Remainder === 2}) {\n                vec2 xValues = vec2(\n                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}),\n                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 1)\n                );\n                vec2 wValues = vec2(\n                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2),\n                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 1, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else if (${inputDepthVec4Remainder === 3}) {\n                vec3 xValues = vec3(\n                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}),\n                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 1),\n                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 2)\n                );\n                vec3 wValues = vec3(\n                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2),\n                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 1, d2),\n                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 2, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/im2col_packed_gpu.js\nvar Im2ColPackedProgram = class {\n  constructor(outputShape, convInfo) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.customUniforms = [\n      { name: \"inputShape\", type: \"ivec4\" },\n      { name: \"pad\", type: \"ivec2\" },\n      { name: \"stride\", type: \"ivec2\" },\n      { name: \"dilation\", type: \"ivec2\" },\n      { name: \"inChannels\", type: \"int\" },\n      { name: \"itemsPerBlockRow\", type: \"int\" },\n      { name: \"outWidth\", type: \"int\" }\n    ];\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    const { dataFormat } = convInfo;\n    const glsl = getGlslDifferences();\n    const isChannelsLast = dataFormat === \"channelsLast\";\n    const rowDim = isChannelsLast ? 1 : 2;\n    const colDim = isChannelsLast ? 2 : 3;\n    const boundsCheckingSnippet = this.enableShapeUniforms ? \"if(blockIndex < outShape[2] && pos < outShape[1]) {\" : `if(blockIndex < ${outputShape[2]} && pos < ${outputShape[1]}) {`;\n    let unrolled = ``;\n    for (let row = 0; row <= 1; row++) {\n      for (let col = 0; col <= 1; col++) {\n        unrolled += `\n          blockIndex = rc.z + ${col};\n          pos = rc.y + ${row};\n\n          ${boundsCheckingSnippet}\n            offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];\n            d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);\n\n            if(d0 < inputShape[${rowDim}] && d0 >= 0) {\n              // Use custom imod instead mod. On Intel GPU, mod may generate\n              // unexpected value.\n              // https://github.com/tensorflow/tfjs/issues/5447\n              offsetX = imod(blockIndex, outWidth) * stride[1] - pad[1];\n              d1 = offsetX + dilation[1] * (imod(pos, itemsPerBlockRow) /\n                  inChannels);\n\n              if(d1 < inputShape[${colDim}] && d1 >= 0) {\n\n                ch = imod(pos, inChannels);\n\n                if (${isChannelsLast}) {\n                  innerDims = vec2(d1, ch);\n                  result[${row * 2 + col}] = getChannel(\n                    getA(rc.x, d0, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                } else {\n                  innerDims = vec2(d0, d1);\n                  result[${row * 2 + col}] = getChannel(\n                    getA(rc.x, ch, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                }\n              }\n            }\n          }\n        `;\n      }\n    }\n    this.userCode = `\n      void main() {\n        ivec3 rc = getOutputCoords();\n\n        vec4 result = vec4(0);\n\n        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\n        vec2 innerDims;\n\n        ${unrolled}\n\n        ${glsl.output} = result;\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Conv2D_impl.js\nfunction getShapeForBatchMatMul(shape, isChannelsLast) {\n  const length = shape.length;\n  if (length >= 3) {\n    return isChannelsLast ? [\n      ...shape.slice(0, -3),\n      shape[length - 3] * shape[length - 2],\n      shape[length - 1]\n    ] : [\n      ...shape.slice(0, -3),\n      shape[length - 3],\n      shape[length - 2] * shape[length - 1]\n    ];\n  } else if (!isChannelsLast && length === 1 && shape[0] > 1) {\n    return [shape[0], 1];\n  } else {\n    return null;\n  }\n}\nfunction conv2dByMatMul({ x, filter, convInfo, backend: backend2, bias = null, preluActivationWeights = null, leakyreluAlpha = 0, activation: activation2 = null }) {\n  const xShape = x.shape;\n  const xTexData = backend2.texData.get(x.dataId);\n  const sharedMatMulDim = convInfo.inChannels;\n  const outerShapeX = xShape[0] * xShape[1] * xShape[2];\n  const outerShapeFilter = convInfo.outChannels;\n  const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n  const transposeA = false;\n  const transposeB = false;\n  let out;\n  const intermediates = [];\n  if (preluActivationWeights != null) {\n    const targetShape = getShapeForBatchMatMul(preluActivationWeights.shape, isChannelsLast);\n    if (targetShape != null) {\n      preluActivationWeights = reshape4({\n        inputs: { x: preluActivationWeights },\n        backend: backend2,\n        attrs: { shape: targetShape }\n      });\n      intermediates.push(preluActivationWeights);\n    }\n  }\n  if (bias != null) {\n    const targetShape = getShapeForBatchMatMul(bias.shape, isChannelsLast);\n    if (targetShape != null) {\n      bias = reshape4({ inputs: { x: bias }, backend: backend2, attrs: { shape: targetShape } });\n      intermediates.push(bias);\n    }\n  }\n  const batchMatMulWillBeUnpacked = (outerShapeX === 1 || outerShapeFilter === 1) && sharedMatMulDim > MATMUL_SHARED_DIM_THRESHOLD;\n  const canOptimize = !batchMatMulWillBeUnpacked && xTexData.isPacked && isChannelsLast && xTexData.texture != null && xShape[2] % 2 !== 0 && util_exports.arraysEqual(xTexData.shape.slice(-3), xShape.slice(-3));\n  if (canOptimize) {\n    const targetShape = xShape[0] * xShape[1] * (xShape[2] + 1);\n    const xReshaped = {\n      dataId: x.dataId,\n      shape: [1, targetShape, convInfo.inChannels],\n      dtype: x.dtype\n    };\n    const originalXTexDataShape = xTexData.shape;\n    xTexData.shape = xTexData.shape.slice();\n    xTexData.shape[xTexData.shape.length - 2]++;\n    util_exports.assert(isReshapeFree(xTexData.shape, xReshaped.shape), () => `packed reshape ${xTexData.shape} to ${xReshaped.shape} isn't free`);\n    const filterReshaped = reshape4({\n      inputs: { x: filter },\n      backend: backend2,\n      attrs: { shape: [1, convInfo.inChannels, convInfo.outChannels] }\n    });\n    intermediates.push(filterReshaped);\n    const pointwiseConv = batchMatMulImpl({\n      a: xReshaped,\n      b: filterReshaped,\n      backend: backend2,\n      transposeA,\n      transposeB,\n      bias,\n      activation: activation2,\n      preluActivationWeights,\n      leakyreluAlpha\n    });\n    const pointwiseConvTexData = backend2.texData.get(pointwiseConv.dataId);\n    util_exports.assert(pointwiseConvTexData.isPacked, () => \"batchMatMul result is expected to be packed\");\n    xTexData.shape = originalXTexDataShape;\n    pointwiseConvTexData.shape = convInfo.outShape;\n    out = identity3({ inputs: { x: pointwiseConv }, backend: backend2 });\n    out.shape = convInfo.outShape;\n    intermediates.push(pointwiseConv);\n  } else {\n    const numCols = convInfo.outHeight * convInfo.outWidth;\n    const xReshaped = reshape4({\n      inputs: { x },\n      backend: backend2,\n      attrs: {\n        shape: isChannelsLast ? [convInfo.batchSize, numCols, convInfo.inChannels] : [convInfo.batchSize, convInfo.inChannels, numCols]\n      }\n    });\n    const filterReshaped = reshape4({\n      inputs: { x: filter },\n      backend: backend2,\n      attrs: { shape: [1, convInfo.inChannels, convInfo.outChannels] }\n    });\n    const result = batchMatMulImpl({\n      a: isChannelsLast ? xReshaped : filterReshaped,\n      b: isChannelsLast ? filterReshaped : xReshaped,\n      transposeA: !isChannelsLast,\n      transposeB,\n      backend: backend2,\n      bias,\n      activation: activation2,\n      preluActivationWeights,\n      leakyreluAlpha\n    });\n    out = reshape4({ inputs: { x: result }, backend: backend2, attrs: { shape: convInfo.outShape } });\n    intermediates.push(xReshaped);\n    intermediates.push(filterReshaped);\n    intermediates.push(result);\n  }\n  for (const i2 of intermediates) {\n    backend2.disposeIntermediateTensorInfo(i2);\n  }\n  return out;\n}\nfunction conv2dWithIm2Row({ x, filter, convInfo, backend: backend2, bias = null, preluActivationWeights = null, leakyreluAlpha = 0, activation: activation2 = null }) {\n  const { filterWidth, filterHeight, inChannels, outWidth, outHeight, dataFormat } = convInfo;\n  const isChannelsLast = dataFormat === \"channelsLast\";\n  const sharedDim = filterWidth * filterHeight * inChannels;\n  const numCols = outHeight * outWidth;\n  const x2ColShape = [convInfo.batchSize, sharedDim, numCols];\n  const transposeA = true;\n  const transposeB = false;\n  const intermediates = [];\n  if (preluActivationWeights != null) {\n    const targetShape = getShapeForBatchMatMul(preluActivationWeights.shape, isChannelsLast);\n    if (targetShape != null) {\n      preluActivationWeights = reshape4({\n        inputs: { x: preluActivationWeights },\n        backend: backend2,\n        attrs: { shape: targetShape }\n      });\n      intermediates.push(preluActivationWeights);\n    }\n  }\n  if (bias != null) {\n    const targetShape = getShapeForBatchMatMul(bias.shape, isChannelsLast);\n    if (targetShape != null) {\n      bias = reshape4({ inputs: { x: bias }, backend: backend2, attrs: { shape: targetShape } });\n      intermediates.push(bias);\n    }\n  }\n  const w2Row = reshape4({\n    inputs: { x: filter },\n    backend: backend2,\n    attrs: { shape: [1, sharedDim, util_exports.sizeFromShape(filter.shape) / sharedDim] }\n  });\n  intermediates.push(w2Row);\n  const im2ColProgram = new Im2ColPackedProgram(x2ColShape, convInfo);\n  const customValues = [\n    x.shape,\n    [convInfo.padInfo.top, convInfo.padInfo.left],\n    [convInfo.strideHeight, convInfo.strideWidth],\n    [convInfo.dilationHeight, convInfo.dilationWidth],\n    [convInfo.inChannels],\n    [convInfo.filterWidth * convInfo.inChannels],\n    [convInfo.outWidth]\n  ];\n  const im2Col = backend2.runWebGLProgram(im2ColProgram, [x], \"float32\", customValues);\n  const im2ColReshaped = reshape4({ inputs: { x: im2Col }, backend: backend2, attrs: { shape: x2ColShape } });\n  intermediates.push(im2Col);\n  intermediates.push(im2ColReshaped);\n  const hasBias = bias != null;\n  const hasPreluActivationWeights = preluActivationWeights != null;\n  const hasLeakyreluAlpha = activation2 === \"leakyrelu\";\n  const fusedActivation = activation2 ? mapActivationToShaderProgram(activation2, true) : null;\n  const matmulProgram = new MatMulPackedProgram(isChannelsLast ? im2ColReshaped.shape : w2Row.shape, isChannelsLast ? w2Row.shape : im2ColReshaped.shape, isChannelsLast ? [convInfo.batchSize, numCols, convInfo.outChannels] : [convInfo.batchSize, convInfo.outChannels, numCols], transposeA, transposeB, hasBias, fusedActivation, hasPreluActivationWeights, hasLeakyreluAlpha);\n  const inputs = isChannelsLast ? [im2ColReshaped, w2Row] : [w2Row, im2ColReshaped];\n  if (bias) {\n    inputs.push(bias);\n  }\n  if (hasPreluActivationWeights) {\n    inputs.push(preluActivationWeights);\n  }\n  if (hasLeakyreluAlpha) {\n    const $leakyreluAlpha = backend2.makeTensorInfo([], \"float32\", util_exports.createScalarValue(leakyreluAlpha, \"float32\"));\n    inputs.push($leakyreluAlpha);\n    intermediates.push($leakyreluAlpha);\n  }\n  const product = backend2.runWebGLProgram(matmulProgram, inputs, \"float32\");\n  const out = reshape4({ inputs: { x: product }, backend: backend2, attrs: { shape: convInfo.outShape } });\n  intermediates.push(product);\n  for (const i2 of intermediates) {\n    backend2.disposeIntermediateTensorInfo(i2);\n  }\n  return out;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Conv2D.js\nfunction conv2d4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode, false, $dataFormat);\n  let out;\n  if (convInfo.filterHeight === 1 && convInfo.filterWidth === 1 && convInfo.dilationHeight === 1 && convInfo.dilationWidth === 1 && convInfo.strideHeight === 1 && convInfo.strideWidth === 1 && (convInfo.padInfo.type === \"SAME\" || convInfo.padInfo.type === \"VALID\")) {\n    out = conv2dByMatMul({ x, filter, convInfo, backend: backend2 });\n  } else if (env().getBool(\"WEBGL_CONV_IM2COL\")) {\n    out = conv2dWithIm2Row({ x, filter, convInfo, backend: backend2 });\n  } else {\n    const program = new Conv2DProgram(convInfo);\n    out = backend2.runWebGLProgram(program, [x, filter], \"float32\");\n  }\n  const outReshaped = reshape4({ inputs: { x: out }, backend: backend2, attrs: { shape: convInfo.outShape } });\n  backend2.disposeIntermediateTensorInfo(out);\n  return outReshaped;\n}\nvar conv2DConfig2 = {\n  kernelName: Conv2D,\n  backendName: \"webgl\",\n  kernelFunc: conv2d4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_backprop_gpu.js\nvar Conv2DDerFilterProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"x\", \"dy\"];\n    this.outputShape = convInfo.filterShape;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const padTop = convInfo.padInfo.top;\n    const padLeft = convInfo.padInfo.left;\n    const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n    this.userCode = `\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int d2 = coords.w;\n\n        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int b = 0; b < ${convInfo.batchSize}; b++) {\n          for (int yR = 0; yR < ${convInfo.outHeight}; yR++) {\n            int xR = wR + yR * ${strideHeight} - ${padTop};\n\n            if (xR < 0 || xR >= ${convInfo.inHeight}) {\n              continue;\n            }\n\n            for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {\n              int xC = wC + yC * ${strideWidth} - ${padLeft};\n\n              if (xC < 0 || xC >= ${convInfo.inWidth}) {\n                continue;\n              }\n\n              if (${isChannelsLast}) {\n                float dyValue = getDy(b, yR, yC, d2);\n                float xValue = getX(b, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              } else {\n                float dyValue = getDy(b, d2, yR, yC);\n                float xValue = getX(b, d1, xR, xC);\n                dotProd += (xValue * dyValue);\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\nvar Conv2DDerInputProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\", \"W\"];\n    this.outputShape = convInfo.inShape;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n    const padTop = filterHeight - 1 - convInfo.padInfo.top;\n    const padLeft = filterWidth - 1 - convInfo.padInfo.left;\n    const rowDim = isChannelsLast ? 1 : 2;\n    const colDim = isChannelsLast ? 2 : 3;\n    const channelDim = isChannelsLast ? 3 : 1;\n    this.userCode = `\n      const ivec2 pads = ivec2(${padTop}, ${padLeft});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[${channelDim}];\n\n        ivec2 dyCorner = ivec2(coords[${rowDim}], coords[${colDim}]) - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ${filterHeight}; wR++) {\n          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;\n\n          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = ${filterHeight} - 1 - wR;\n\n          for (int wC = 0; wC < ${filterWidth}; wC++) {\n            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;\n\n            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = ${filterWidth} - 1 - wC;\n\n            for (int d2 = 0; d2 < ${convInfo.outChannels}; d2++) {\n\n              if (${isChannelsLast}) {\n                float xValue = getDy(batch, idyR, idyC, d2);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              } else {\n                float xValue = getDy(batch, d2, idyR, idyC);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\nvar Conv3DDerFilterProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"x\", \"dy\"];\n    this.outputShape = convInfo.filterShape;\n    const strideDepth = convInfo.strideDepth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const padFront = convInfo.padInfo.front;\n    const padTop = convInfo.padInfo.top;\n    const padLeft = convInfo.padInfo.left;\n    this.userCode = `\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int wF = coords.x;\n        int wR = coords.y;\n        int wC = coords.z;\n        int d1 = coords.w;\n        int d2 = coords.u;\n\n        float dotProd = 0.0;\n\n        for (int b = 0; b < ${convInfo.batchSize}; b++) {\n          for (int yF = 0; yF < ${convInfo.outDepth}; yF++) {\n            int xF = wF + yF * ${strideDepth} - ${padFront};\n\n            if (xF < 0 || xF >= ${convInfo.inDepth}) {\n              continue;\n            }\n\n            for (int yR = 0; yR < ${convInfo.outHeight}; yR++) {\n              int xR = wR + yR * ${strideHeight} - ${padTop};\n\n              if (xR < 0 || xR >= ${convInfo.inHeight}) {\n                continue;\n              }\n\n              for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {\n                int xC = wC + yC * ${strideWidth} - ${padLeft};\n\n                if (xC < 0 || xC >= ${convInfo.inWidth}) {\n                  continue;\n                }\n\n                float dyValue = getDy(b, yF, yR, yC, d2);\n                float xValue = getX(b, xF, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\nvar Conv3DDerInputProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\", \"W\"];\n    this.outputShape = convInfo.inShape;\n    const filterDepth = convInfo.filterDepth;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const strideDepth = convInfo.strideDepth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const padFront = filterDepth - 1 - convInfo.padInfo.front;\n    const padTop = filterHeight - 1 - convInfo.padInfo.top;\n    const padLeft = filterWidth - 1 - convInfo.padInfo.left;\n    this.userCode = `\n      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d1 = coords.u;\n\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyFCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        float dotProd = 0.0;\n        for (int wF = 0; wF < ${filterDepth}; wF++) {\n          float dyF = float(dyFCorner + wF) / ${strideDepth}.0;\n\n          if (dyF < 0.0 || dyF >= ${convInfo.outDepth}.0 || fract(dyF) > 0.0) {\n            continue;\n          }\n          int idyF = int(dyF);\n\n          int wFPerm = ${filterDepth} - 1 - wF;\n\n          for (int wR = 0; wR < ${filterHeight}; wR++) {\n            float dyR = float(dyRCorner + wR) / ${strideHeight}.0;\n\n            if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 ||\n              fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            int wRPerm = ${filterHeight} - 1 - wR;\n\n            for (int wC = 0; wC < ${filterWidth}; wC++) {\n              float dyC = float(dyCCorner + wC) / ${strideWidth}.0;\n\n              if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              int wCPerm = ${filterWidth} - 1 - wC;\n\n              for (int d2 = 0; d2 < ${convInfo.outChannels}; d2++) {\n                float xValue = getDy(batch, idyF, idyR, idyC, d2);\n                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Conv2DBackpropFilter.js\nfunction conv2DBackpropFilter3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, dy } = inputs;\n  const { strides, pad: pad3, dataFormat, dimRoundingMode, filterShape } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filterShape, strides, 1, pad3, dimRoundingMode, false, $dataFormat);\n  const program = new Conv2DDerFilterProgram(convInfo);\n  return backend2.runWebGLProgram(program, [x, dy], \"float32\");\n}\nvar conv2DBackpropFilterConfig2 = {\n  kernelName: Conv2DBackpropFilter,\n  backendName: \"webgl\",\n  kernelFunc: conv2DBackpropFilter3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Conv2DBackpropInput.js\nfunction conv2DBackpropInput3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, filter } = inputs;\n  const { inputShape, strides, pad: pad3, dataFormat, dimRoundingMode } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(inputShape, filter.shape, strides, 1, pad3, dimRoundingMode, false, $dataFormat);\n  const program = new Conv2DDerInputProgram(convInfo);\n  return backend2.runWebGLProgram(program, [dy, filter], \"float32\");\n}\nvar conv2DBackpropInputConfig2 = {\n  kernelName: Conv2DBackpropInput,\n  backendName: \"webgl\",\n  kernelFunc: conv2DBackpropInput3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Conv3D.js\nfunction conv3D2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dilations } = attrs;\n  const convInfo = backend_util_exports.computeConv3DInfo(x.shape, filter.shape, strides, dilations, pad3);\n  const program = new Conv3DProgram(convInfo);\n  return backend2.runWebGLProgram(program, [x, filter], \"float32\");\n}\nvar conv3DConfig2 = {\n  kernelName: Conv3D,\n  backendName: \"webgl\",\n  kernelFunc: conv3D2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Conv3DBackpropFilterV2.js\nfunction conv3DBackpropFilterV22(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, dy } = inputs;\n  const { strides, pad: pad3, filterShape } = attrs;\n  const convInfo = backend_util_exports.computeConv3DInfo(x.shape, filterShape, strides, 1, pad3);\n  const program = new Conv3DDerFilterProgram(convInfo);\n  return backend2.runWebGLProgram(program, [x, dy], \"float32\");\n}\nvar conv3DBackpropFilterV2Config2 = {\n  kernelName: Conv3DBackpropFilterV2,\n  backendName: \"webgl\",\n  kernelFunc: conv3DBackpropFilterV22\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Conv3DBackpropInputV2.js\nfunction conv3DBackpropInput2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, filter } = inputs;\n  const { pad: pad3, strides, inputShape } = attrs;\n  const convInfo = backend_util_exports.computeConv3DInfo(inputShape, filter.shape, strides, 1, pad3);\n  const program = new Conv3DDerInputProgram(convInfo);\n  return backend2.runWebGLProgram(program, [dy, filter], \"float32\");\n}\nvar conv3DBackpropInputConfig = {\n  kernelName: Conv3DBackpropInputV2,\n  backendName: \"webgl\",\n  kernelFunc: conv3DBackpropInput2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Cos.js\nvar COS = CHECK_NAN_SNIPPET_UNARY + `\n  return cos(x);\n`;\nvar cos3 = unaryKernelFunc2({ opSnippet: COS });\nvar cosConfig2 = {\n  kernelName: Cos,\n  backendName: \"webgl\",\n  kernelFunc: cos3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Cosh.js\nvar COSH = `\n  float e2x = exp(-x);\n  return (e2x + 1.0 / e2x) / 2.0;\n`;\nvar cosh3 = unaryKernelFunc2({ opSnippet: COSH });\nvar coshConfig2 = {\n  kernelName: Cosh,\n  backendName: \"webgl\",\n  kernelFunc: cosh3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/crop_and_resize_gpu.js\nvar CropAndResizeProgram = class {\n  constructor(imageShape, boxShape, cropSize, method, extrapolationValue) {\n    this.variableNames = [\"Image\", \"Boxes\", \"BoxInd\"];\n    this.outputShape = [];\n    const [batch, imageHeight, imageWidth, depth] = imageShape;\n    const [numBoxes] = boxShape;\n    const [cropHeight, cropWidth] = cropSize;\n    this.outputShape = [numBoxes, cropHeight, cropWidth, depth];\n    const methodId = method === \"bilinear\" ? 1 : 0;\n    const [inputHeightFloat, inputWidthFloat] = [`${imageHeight - 1}.0`, `${imageWidth - 1}.0`];\n    const [heightRatio, heightScale, inY] = cropHeight > 1 ? [\n      `${(imageHeight - 1) / (cropHeight - 1)}`,\n      \"(y2-y1) * height_ratio\",\n      `y1*${inputHeightFloat} + float(y)*(height_scale)`\n    ] : [\n      \"0.0\",\n      \"0.0\",\n      `0.5 * (y1+y2) * ${inputHeightFloat}`\n    ];\n    const [widthRatio, widthScale, inX] = cropWidth > 1 ? [\n      `${(imageWidth - 1) / (cropWidth - 1)}`,\n      \"(x2-x1) * width_ratio\",\n      `x1*${inputWidthFloat} + float(x)*(width_scale)`\n    ] : [\n      \"0.0\",\n      \"0.0\",\n      `0.5 * (x1+x2) * ${inputWidthFloat}`\n    ];\n    this.userCode = `\n      const float height_ratio = float(${heightRatio});\n      const float width_ratio = float(${widthRatio});\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int y = coords[1];\n        int x = coords[2];\n        int d = coords[3];\n\n        // get box vals\n        float y1 = getBoxes(b,0);\n        float x1 = getBoxes(b,1);\n        float y2 = getBoxes(b,2);\n        float x2 = getBoxes(b,3);\n\n        // get image in batch index\n        int bInd = round(getBoxInd(b));\n        if(bInd < 0 || bInd >= ${batch}) {\n          return;\n        }\n\n        float height_scale = ${heightScale};\n        float width_scale = ${widthScale};\n\n        float in_y = ${inY};\n        if( in_y < 0.0 || in_y > ${inputHeightFloat} ) {\n          setOutput(float(${extrapolationValue}));\n          return;\n        }\n        float in_x = ${inX};\n        if( in_x < 0.0 || in_x > ${inputWidthFloat} ) {\n          setOutput(float(${extrapolationValue}));\n          return;\n        }\n\n        vec2 sourceFracIndexCR = vec2(in_x,in_y);\n        if(${methodId} == 1) {\n          // Compute the four integer indices.\n          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);\n          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));\n\n          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);\n          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);\n          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);\n          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);\n\n          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);\n\n          float top = topLeft + (topRight - topLeft) * fracCR.x;\n          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;\n          float newValue = top + (bottom - top) * fracCR.y;\n          setOutput(newValue);\n        } else {\n          // Compute the coordinators of nearest neighbor point.\n          ivec2 sourceNearestCR = ivec2(floor(\n            sourceFracIndexCR + vec2(0.5,0.5)));\n          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);\n          setOutput(newValue);\n        }\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/CropAndResize.js\nvar cropAndResize3 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { image: image2, boxes, boxInd } = inputs;\n  const { cropSize, method, extrapolationValue } = attrs;\n  const program = new CropAndResizeProgram(image2.shape, boxes.shape, cropSize, method, extrapolationValue);\n  return backend2.runWebGLProgram(program, [image2, boxes, boxInd], \"float32\");\n};\nvar cropAndResizeConfig2 = {\n  kernelName: CropAndResize,\n  backendName: \"webgl\",\n  kernelFunc: cropAndResize3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/cum_gpu.js\nvar CumOpType;\n(function(CumOpType3) {\n  CumOpType3[\"Prod\"] = \"*\";\n  CumOpType3[\"Sum\"] = \"+\";\n})(CumOpType || (CumOpType = {}));\nvar CumProgram = class {\n  constructor(op2, outputShape, exclusive, reverse5) {\n    this.op = op2;\n    this.outputShape = outputShape;\n    this.variableNames = [\"x\"];\n    this.customUniforms = [{ name: \"index\", type: \"float\" }];\n    const rank = this.outputShape.length;\n    const initVal = this.op === CumOpType.Prod ? \"1.0\" : \"0.0\";\n    const val = exclusive ? initVal : `getX(${getCoords2(rank, \"coords\", this.op)})`;\n    const length = this.outputShape[this.outputShape.length - 1];\n    let condition = \"\";\n    let idxString = \"\";\n    if (exclusive) {\n      condition = reverse5 ? `end != ${length - 1}` : \"end != 0\";\n      idxString = reverse5 ? \"end + 1\" : \"end - 1\";\n    } else {\n      condition = reverse5 ? `end + pow2 < ${length}` : \"end >= pow2\";\n      idxString = reverse5 ? \"end + pow2\" : \"end - pow2\";\n    }\n    this.userCode = `\n      void main() {\n        ${getCoordsDataType(rank)} coords = getOutputCoords();\n        int end = ${getFinalCoord(rank, \"coords\", this.op)};\n        float val = ${val};\n        int pow2 = int(pow(2.0, index));\n        if (${condition}) {\n          int idx = ${idxString};\n          ${getFinalCoord(rank, \"coords\", this.op)} = idx;\n          val ${this.op}= getX(${getCoords2(rank, \"coords\", this.op)});\n        }\n        setOutput(val);\n      }\n    `;\n  }\n};\nfunction getCoords2(rank, name, op2) {\n  if (rank === 1) {\n    return `${name}`;\n  } else if (rank === 2) {\n    return `${name}.x, ${name}.y`;\n  } else if (rank === 3) {\n    return `${name}.x, ${name}.y, ${name}.z`;\n  } else if (rank === 4) {\n    return `${name}.x, ${name}.y, ${name}.z, ${name}.w`;\n  } else {\n    throw new Error(`Cumulative ${op2} for rank ${rank} is not yet supported`);\n  }\n}\nfunction getFinalCoord(rank, name, op2) {\n  if (rank === 1) {\n    return `${name}`;\n  } else if (rank === 2) {\n    return `${name}.y`;\n  } else if (rank === 3) {\n    return `${name}.z`;\n  } else if (rank === 4) {\n    return `${name}.w`;\n  } else {\n    throw new Error(`Cumulative ${op2} for rank ${rank} is not yet supported`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Cum_impl.js\nfunction cumImpl(op2, x, backend2, axis, exclusive, reverse5) {\n  const xRank = x.shape.length;\n  const permutation = backend_util_exports.getAxesPermutation([axis], xRank);\n  let permutedX = x;\n  if (permutation != null) {\n    permutedX = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutation } });\n  }\n  const permutedAxis = backend_util_exports.getInnerMostAxes(1, xRank)[0];\n  if (permutedAxis !== xRank - 1) {\n    throw new Error(`WebGL cumprod shader expects an inner-most axis=${x.shape.length - 1} but got axis=${axis}`);\n  }\n  const size = permutedX.shape[permutedAxis];\n  let result = identity3({ inputs: { x: permutedX }, backend: backend2 });\n  for (let i2 = 0; i2 <= Math.ceil(Math.log2(size)) - 1; i2++) {\n    const program = new CumProgram(op2, permutedX.shape, false, reverse5);\n    const customValues = [[i2]];\n    const prevResult = result;\n    result = backend2.runWebGLProgram(program, [result], result.dtype, customValues);\n    backend2.disposeIntermediateTensorInfo(prevResult);\n  }\n  if (exclusive) {\n    const program = new CumProgram(op2, permutedX.shape, exclusive, reverse5);\n    const prevResult = result;\n    result = backend2.runWebGLProgram(program, [result], result.dtype);\n    backend2.disposeIntermediateTensorInfo(prevResult);\n  }\n  if (permutation != null) {\n    const reversePermutation = backend_util_exports.getUndoAxesPermutation(permutation);\n    const reverseTransposedResult = transpose3({ inputs: { x: result }, backend: backend2, attrs: { perm: reversePermutation } });\n    backend2.disposeIntermediateTensorInfo(result);\n    backend2.disposeIntermediateTensorInfo(permutedX);\n    return reverseTransposedResult;\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Cumprod.js\nfunction cumprod3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  return cumImpl(CumOpType.Prod, x, backend2, axis, exclusive, reverse5);\n}\nvar cumprodConfig2 = {\n  kernelName: Cumprod,\n  backendName: \"webgl\",\n  kernelFunc: cumprod3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Cumsum.js\nfunction cumsum3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  return cumImpl(CumOpType.Sum, x, backend2, axis, exclusive, reverse5);\n}\nvar cumsumConfig2 = {\n  kernelName: Cumsum,\n  backendName: \"webgl\",\n  kernelFunc: cumsum3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/DenseBincount.js\nfunction denseBincount3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, weights } = inputs;\n  const { size, binaryOutput } = attrs;\n  if (x.shape.length === 1) {\n    const xVals = backend2.readSync(x.dataId);\n    const weightsVals = backend2.readSync(weights.dataId);\n    const outVals = bincountImplCPU(xVals, weightsVals, weights.dtype, weights.shape, size);\n    return backend2.makeTensorInfo([size], weights.dtype, outVals);\n  } else if (x.shape.length === 2) {\n    const xBuf = backend2.bufferSync(x);\n    const weightsBuf = backend2.bufferSync(weights);\n    const outBuf = bincountReduceImplCPU(xBuf, weightsBuf, size, binaryOutput);\n    return backend2.makeTensorInfo(outBuf.shape, weights.dtype, outBuf.values);\n  }\n  throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${x.shape.length}.`);\n}\nvar denseBincountConfig2 = {\n  kernelName: DenseBincount,\n  backendName: \"webgl\",\n  kernelFunc: denseBincount3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/depth_to_space_gpu.js\nvar DepthToSpaceProgram = class {\n  constructor(outputShape, blockSize, dataFormat) {\n    this.variableNames = [\"x\"];\n    this.outputShape = [];\n    this.outputShape = outputShape;\n    this.blockSize = blockSize;\n    this.dataFormat = dataFormat;\n    this.userCode = `\n    void main() {\n      ivec4 coords = getOutputCoords();\n      int b = coords[0];\n      int h = ${this.getHeightCoordString()};\n      int w = ${this.getWidthCoordString()};\n      int d = ${this.getDepthCoordString()};\n\n      int in_h = h / ${blockSize};\n      int offset_h = imod(h, ${blockSize});\n      int in_w = w / ${blockSize};\n      int offset_w = imod(w, ${blockSize});\n      int offset_d = (offset_h * ${blockSize} + offset_w) *\n        ${this.getOutputDepthSize()};\n      int in_d = d + offset_d;\n\n      float result = ${this.getInputSamplingString()};\n      setOutput(result);\n    }\n  `;\n  }\n  getHeightCoordString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `coords[1]`;\n    } else {\n      return `coords[2]`;\n    }\n  }\n  getWidthCoordString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `coords[2]`;\n    } else {\n      return `coords[3]`;\n    }\n  }\n  getDepthCoordString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `coords[3]`;\n    } else {\n      return `coords[1]`;\n    }\n  }\n  getOutputDepthSize() {\n    if (this.dataFormat === \"NHWC\") {\n      return this.outputShape[3];\n    } else {\n      return this.outputShape[1];\n    }\n  }\n  getInputSamplingString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `getX(b, in_h, in_w, in_d)`;\n    } else {\n      return `getX(b, in_d, in_h, in_w)`;\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/DepthToSpace.js\nfunction depthToSpace3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockSize, dataFormat } = attrs;\n  const batchSize = x.shape[0];\n  const inputHeight = dataFormat === \"NHWC\" ? x.shape[1] : x.shape[2];\n  const inputWidth = dataFormat === \"NHWC\" ? x.shape[2] : x.shape[3];\n  const inputDepth = dataFormat === \"NHWC\" ? x.shape[3] : x.shape[1];\n  const outputHeight = inputHeight * blockSize;\n  const outputWidth = inputWidth * blockSize;\n  const outputDepth = inputDepth / (blockSize * blockSize);\n  const outputShape = dataFormat === \"NHWC\" ? [batchSize, outputHeight, outputWidth, outputDepth] : [batchSize, outputDepth, outputHeight, outputWidth];\n  const program = new DepthToSpaceProgram(outputShape, blockSize, dataFormat);\n  return backend2.runWebGLProgram(program, [x], x.dtype);\n}\nvar depthToSpaceConfig2 = {\n  kernelName: DepthToSpace,\n  backendName: \"webgl\",\n  kernelFunc: depthToSpace3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_gpu_depthwise.js\nvar DepthwiseConv2DProgram = class {\n  constructor(convInfo, addBias = false, activation2 = null, hasPreluActivation = false, hasLeakyReluAlpha = false) {\n    this.variableNames = [\"x\", \"W\"];\n    this.customUniforms = [\n      { name: \"pads\", type: \"ivec2\" },\n      { name: \"strides\", type: \"ivec2\" },\n      { name: \"dilations\", type: \"ivec2\" },\n      { name: \"inDims\", type: \"ivec2\" }\n    ];\n    this.outputShape = convInfo.outShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const channelMul = convInfo.outChannels / convInfo.inChannels;\n    let activationSnippet = \"\", applyActivationSnippet = \"\";\n    if (activation2) {\n      if (hasPreluActivation) {\n        activationSnippet = `float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          ${activation2}\n        }`;\n      } else if (hasLeakyReluAlpha) {\n        activationSnippet = `float activation(float a) {\n          float b = getLeakyreluAlphaAtOutCoords();\n          ${activation2}\n        }`;\n      } else {\n        activationSnippet = `\n          float activation(float x) {\n            ${activation2}\n          }\n        `;\n      }\n      applyActivationSnippet = `result = activation(result);`;\n    }\n    const addBiasSnippet = addBias ? \"result += getBiasAtOutCoords();\" : \"\";\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivation) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    if (hasLeakyReluAlpha) {\n      this.variableNames.push(\"leakyreluAlpha\");\n    }\n    this.userCode = `\n      ${activationSnippet}\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / ${channelMul};\n        int q = d2 - d1 * ${channelMul};\n\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.\n        for (int wR = 0; wR < ${filterHeight}; wR++) {\n          int xR = xRCorner + wR * dilations[0];\n\n          if (xR < 0 || xR >= inDims[0]) {\n            continue;\n          }\n\n          for (int wC = 0; wC < ${filterWidth}; wC++) {\n            int xC = xCCorner + wC * dilations[1];\n\n            if (xC < 0 || xC >= inDims[1]) {\n              continue;\n            }\n\n            float xVal = getX(batch, xR, xC, d1);\n            float wVal = getW(wR, wC, d1, q);\n            dotProd += xVal * wVal;\n          }\n        }\n\n        float result = dotProd;\n        ${addBiasSnippet}\n        ${applyActivationSnippet}\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_packed_gpu_depthwise.js\nvar DepthwiseConvPacked2DProgram = class {\n  constructor(convInfo, addBias = false, activation2 = null, hasPreluActivation = false, hasLeakyReluAlpha = false) {\n    this.variableNames = [\"x\", \"W\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.customUniforms = [\n      { name: \"pads\", type: \"ivec2\" },\n      { name: \"strides\", type: \"ivec2\" },\n      { name: \"dilations\", type: \"ivec2\" },\n      { name: \"inDims\", type: \"ivec2\" }\n    ];\n    this.outputShape = convInfo.outShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    const channelMul = convInfo.outChannels / convInfo.inChannels;\n    const padLeft = convInfo.padInfo.left;\n    const strideWidth = convInfo.strideWidth;\n    const dilationWidth = convInfo.dilationWidth;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const texelsAcross = filterWidth;\n    let mainLoop = `\n      int xR; int xC; int xCOffset;\n      vec4 wTexel; vec4 previous; vec4 final;`;\n    for (let c = 0; c < filterWidth; c++) {\n      mainLoop += `\n          vec4 xTexelC${c * 2};\n          int xTexelC${c * 2}Ready;\n          vec4 xTexelC${c * 2 + 1};\n          int xTexelC${c * 2 + 1}Ready;\n          vec4 xC${c};`;\n    }\n    mainLoop += `\n    for (int r = 0; r < ${filterHeight}; r++) {\n      `;\n    for (let c = 0; c < filterWidth; c++) {\n      mainLoop += `\n          xTexelC${c * 2} = vec4(0.0);\n          xTexelC${c * 2}Ready = 0;\n          xTexelC${c * 2 + 1} = vec4(0.0);\n          xTexelC${c * 2 + 1}Ready = 0;\n          xC${c} = vec4(0.0);`;\n    }\n    mainLoop += `\n        xR = xRCorner + r * dilations[0];\n        if (xR >=0 && xR < inDims[0]) {\n      `;\n    for (let texelC = 0; texelC < (texelsAcross + 1) / 2; texelC++) {\n      const colIndex = texelC * 2;\n      mainLoop += `\n          xC = xCCorner + ${colIndex * dilationWidth};\n          `;\n      if (strideWidth === 1) {\n        if (colIndex < filterWidth) {\n          if (padLeft % 2 === 1) {\n            mainLoop += `\n                xCOffset = xC + 1;\n                if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${colIndex}Ready == 0) {\n                  xTexelC${colIndex} = getX(batch, xR, xCOffset, d1);\n\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if (xCOffset + 1 >= inDims[1]) {\n                    xTexelC${colIndex}.zw = vec2(0.0);\n                  }\n                  xTexelC${colIndex}Ready = 1;\n                }\n              `;\n            if (dilationWidth === 1 && colIndex > 0) {\n              mainLoop += `\n                xC${colIndex} = vec4(xTexelC${colIndex - 2}.zw, xTexelC${colIndex}.xy);\n                `;\n            } else {\n              mainLoop += `\n                  xCOffset = xC + 1 - 2;\n\n                  if (xCOffset >= 0 && xCOffset < inDims[1]) {\n                    previous = getX(batch, xR, xCOffset, d1);\n\n                    // Need to manually clear unused channels in case\n                    // we're reading from recycled texture.\n                    if (xCOffset + 1 >= inDims[1]) {\n                      previous.zw = vec2(0.0);\n                    }\n\n                    xC${colIndex} = vec4(previous.zw, xTexelC${colIndex}.xy);\n                  } else {\n                    xC${colIndex} = vec4(0.0, 0.0, xTexelC${colIndex}.xy);\n                  }\n                  `;\n            }\n          } else {\n            mainLoop += `\n                if (xC >= 0 && xC < inDims[1] && xTexelC${colIndex}Ready == 0) {\n                  xTexelC${colIndex} = getX(batch, xR, xC, d1);\n                  if (xC + 1 >= inDims[1]) {\n                    xTexelC${colIndex}.zw = vec2(0.0);\n                  }\n                  xTexelC${colIndex}Ready = 1;\n                }\n\n                xC${colIndex} = xTexelC${colIndex};\n                `;\n          }\n          if (colIndex + 1 < filterWidth) {\n            const nextTexelOffset = padLeft % 2 === 0 ? util_exports.nearestLargerEven(dilationWidth) : dilationWidth;\n            if (dilationWidth % 2 === 0 && padLeft % 2 === 1 || dilationWidth % 2 !== 0 && padLeft % 2 !== 1) {\n              mainLoop += `\n                  xCOffset = xC + imod(pads[1], 2) + ${nextTexelOffset};\n\n                  if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${colIndex + 1}Ready == 0) {\n                    xTexelC${colIndex + 1} = getX(batch, xR, xCOffset, d1);\n\n                    // Need to manually clear unused channels in case\n                    // we're reading from recycled texture.\n                    if (xCOffset + 1 >= inDims[1]) {\n                      xTexelC${colIndex + 1}.zw = vec2(0.0);\n                    }\n                    xTexelC${colIndex + 1}Ready = 1;\n                  }\n                  `;\n              if (dilationWidth > 1) {\n                mainLoop += `\n                    xCOffset -= 2;\n                    if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${colIndex}Ready == 0) {\n                      xTexelC${colIndex} = getX(batch, xR, xCOffset, d1);\n                      xTexelC${colIndex}Ready = 1;\n                    }\n                    `;\n              }\n              mainLoop += `\n                  xC${colIndex + 1} = vec4(xTexelC${colIndex}.zw, xTexelC${colIndex + 1}.xy);\n                  `;\n            } else {\n              if (nextTexelOffset === 1) {\n                mainLoop += `\n                    xC${colIndex + 1} = xTexelC${colIndex};\n                    `;\n              } else {\n                mainLoop += `\n                    xCOffset = xC + ${nextTexelOffset};\n\n                    if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${colIndex + 1}Ready == 0) {\n                      xTexelC${colIndex + 1} = getX(batch, xR, xCOffset, d1);\n                      if (xCOffset + 1 >= inDims[1]) {\n                        xTexelC${colIndex + 1}.zw = vec2(0.0);\n                      }\n                      xTexelC${colIndex + 1}Ready = 1;\n                    }\n\n                    xC${colIndex + 1} = xTexelC${colIndex + 1};\n                    `;\n              }\n            }\n          }\n        }\n      } else {\n        if (colIndex < filterWidth) {\n          if (padLeft % 2 === 1) {\n            mainLoop += `\n                xCOffset = xC + 1 - strides[1];\n                if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${colIndex}Ready == 0) {\n                  xTexelC${colIndex} = getX(batch, xR, xCOffset, d1);\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if (xCOffset + 1 >= inDims[1]) {\n                    xTexelC${colIndex}.zw = vec2(0.0);\n                  }\n                  xTexelC${colIndex}Ready = 1;\n                }\n\n                if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${colIndex + 1}Ready == 0) {\n                  xTexelC${colIndex + 1} = getX(batch, xR, xC + 1, d1);\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if (xC + 2 >= inDims[1]) {\n                    xTexelC${colIndex + 1}.zw = vec2(0.0);\n                  }\n                  xTexelC${colIndex + 1}Ready = 1;\n                }\n\n                xC${colIndex} = vec4(xTexelC${colIndex}.zw, xTexelC${colIndex + 1}.zw);\n              `;\n            if (colIndex + 1 < filterWidth) {\n              mainLoop += `\n                  final = vec4(0.0);\n                  xCOffset = xC + 1 + strides[1];\n                  if(xCOffset >= 0 && xCOffset < inDims[1]) {\n                    final = getX(batch, xR, xCOffset, d1);\n                  }\n                  xC${colIndex + 1} = vec4(xTexelC${colIndex + 1}.xy, final.xy);\n                `;\n            }\n          } else {\n            mainLoop += `\n                if(xC >= 0 && xC < inDims[1] && xTexelC${colIndex}Ready == 0) {\n                  xTexelC${colIndex} = getX(batch, xR, xC, d1);\n                  if (xC + 1 >= inDims[1]) {\n                    xTexelC${colIndex}.zw = vec2(0.0);\n                  }\n                  xTexelC${colIndex}Ready = 1;\n                }\n\n                xCOffset = xC + strides[1];\n                if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${colIndex + 1}Ready == 0) {\n                  xTexelC${colIndex + 1} = getX(batch, xR, xCOffset, d1);\n                  if (xCOffset + 1 >= inDims[1]) {\n                    xTexelC${colIndex + 1}.zw = vec2(0.);\n                  }\n                  xTexelC${colIndex + 1}Ready = 1;\n                }\n\n                xC${colIndex} = vec4(\n                  xTexelC${colIndex}.xy, xTexelC${colIndex + 1}.xy);\n              `;\n            if (colIndex + 1 < filterWidth) {\n              mainLoop += `\n                  xC${colIndex + 1} = vec4(xTexelC${colIndex}.zw, xTexelC${colIndex + 1}.zw);\n                `;\n            }\n          }\n        }\n      }\n      if (colIndex < filterWidth) {\n        mainLoop += `\n            wTexel = getW(r, ${colIndex}, d1, q);\n            dotProd += xC${colIndex} * vec4(wTexel.xz, wTexel.xz);\n          `;\n        if (colIndex + 1 < filterWidth) {\n          mainLoop += `\n              wTexel = getW(r, ${colIndex + 1}, d1, q);\n              dotProd += xC${colIndex + 1} * vec4(wTexel.xz, wTexel.xz);\n            `;\n        }\n      }\n    }\n    mainLoop += `\n    }\n  `;\n    mainLoop += `\n      }\n    `;\n    let activationSnippet = \"\", applyActivationSnippet = \"\";\n    if (activation2) {\n      if (hasPreluActivation) {\n        activationSnippet = `vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          ${activation2}\n        }`;\n      } else if (hasLeakyReluAlpha) {\n        activationSnippet = `vec4 activation(vec4 a) {\n          vec4 b = getLeakyreluAlphaAtOutCoords();\n          ${activation2}\n        }`;\n      } else {\n        activationSnippet = `vec4 activation(vec4 x) {\n          ${activation2}\n        }`;\n      }\n      applyActivationSnippet = `result = activation(result);`;\n    }\n    const addBiasSnippet = addBias ? \"result += getBiasAtOutCoords();\" : \"\";\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivation) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    if (hasLeakyReluAlpha) {\n      this.variableNames.push(\"leakyreluAlpha\");\n    }\n    this.userCode = `\n      ${activationSnippet}\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / ${channelMul};\n        int q = d2 - d1 * ${channelMul};\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.\n        vec4 dotProd = vec4(0.000000000000001);\n\n        ${mainLoop}\n\n        vec4 result = dotProd - vec4(0.000000000000001);\n        ${addBiasSnippet}\n        ${applyActivationSnippet}\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/DepthwiseConv2dNative.js\nfunction depthwiseConv2dNative2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dilations, dimRoundingMode } = attrs;\n  let $dilations = dilations;\n  if ($dilations == null) {\n    $dilations = [1, 1];\n  }\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, $dilations), () => `Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${strides} and dilations '${$dilations}'`);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad3, dimRoundingMode, true);\n  let program;\n  if (env().getBool(\"WEBGL_PACK_DEPTHWISECONV\") && convInfo.strideWidth <= 2 && convInfo.outChannels / convInfo.inChannels === 1) {\n    program = new DepthwiseConvPacked2DProgram(convInfo);\n  } else {\n    program = new DepthwiseConv2DProgram(convInfo);\n  }\n  const customValues = [\n    [convInfo.padInfo.top, convInfo.padInfo.left],\n    [convInfo.strideHeight, convInfo.strideWidth],\n    [convInfo.dilationHeight, convInfo.dilationWidth],\n    [convInfo.inHeight, convInfo.inWidth]\n  ];\n  return backend2.runWebGLProgram(program, [x, filter], \"float32\", customValues);\n}\nvar depthwiseConv2dNativeConfig2 = {\n  kernelName: DepthwiseConv2dNative,\n  backendName: \"webgl\",\n  kernelFunc: depthwiseConv2dNative2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_backprop_gpu_depthwise.js\nvar DepthwiseConv2DDerFilterProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"x\", \"dy\"];\n    this.outputShape = convInfo.filterShape;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const padTop = convInfo.padInfo.top;\n    const padLeft = convInfo.padInfo.left;\n    const channelMul = convInfo.outChannels / convInfo.inChannels;\n    this.userCode = `\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int dm = coords.w;\n        int d2 = d1 * ${channelMul} + dm;\n\n        float dotProd = 0.0;\n\n        // TO DO: Vec4 over the batch size\n        for (int b = 0; b < ${convInfo.batchSize}; b++) {\n          for (int yR = 0; yR < ${convInfo.outHeight}; yR++) {\n            int xR = wR + yR * ${strideHeight} - ${padTop};\n\n            if (xR < 0 || xR >= ${convInfo.inHeight}) {\n              continue;\n            }\n\n            for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {\n              int xC = wC + yC * ${strideWidth} - ${padLeft};\n\n              if (xC < 0 || xC >= ${convInfo.inWidth}) {\n                continue;\n              }\n\n              float dyValue = getDy(b, yR, yC, d2);\n              float xValue = getX(b, xR, xC, d1);\n              dotProd += (xValue * dyValue);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\nvar DepthwiseConv2DDerInputProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\", \"W\"];\n    this.outputShape = convInfo.inShape;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const padTop = filterHeight - 1 - convInfo.padInfo.top;\n    const padLeft = filterWidth - 1 - convInfo.padInfo.left;\n    const channelMul = convInfo.outChannels / convInfo.inChannels;\n    this.userCode = `\n      const ivec2 pads = ivec2(${padTop}, ${padLeft});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[3];\n        ivec2 dyCorner = coords.yz - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        float dotProd = 0.0;\n\n        for (int wR = 0; wR < ${filterHeight}; wR++) {\n          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;\n\n          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = ${filterHeight} - 1 - wR;\n\n          for (int wC = 0; wC < ${filterWidth}; wC++) {\n            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;\n\n            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = ${filterWidth} - 1 - wC;\n\n            // TO DO: Vec4 over the channelMul\n            for (int dm = 0; dm < ${channelMul}; dm++) {\n              int d2 = d1 * ${channelMul} + dm;\n              float xValue = getDy(batch, idyR, idyC, d2);\n              float wValue = getW(wRPerm, wCPerm, d1, dm);\n              dotProd += xValue * wValue;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/DepthwiseConv2dNativeBackpropFilter.js\nfunction depthwiseConv2dNativeBackpropFilter3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, dy } = inputs;\n  const { strides, dilations, pad: pad3, dimRoundingMode, filterShape } = attrs;\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filterShape, strides, dilations, pad3, dimRoundingMode, true);\n  const program = new DepthwiseConv2DDerFilterProgram(convInfo);\n  return backend2.runWebGLProgram(program, [x, dy], \"float32\");\n}\nvar depthwiseConv2dNativeBackpropFilterConfig2 = {\n  kernelName: DepthwiseConv2dNativeBackpropFilter,\n  backendName: \"webgl\",\n  kernelFunc: depthwiseConv2dNativeBackpropFilter3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/DepthwiseConv2dNativeBackpropInput.js\nfunction depthwiseConv2dNativeBackpropInput3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, filter } = inputs;\n  const { strides, dilations, pad: pad3, dimRoundingMode, inputShape } = attrs;\n  const convInfo = backend_util_exports.computeConv2DInfo(inputShape, filter.shape, strides, dilations, pad3, dimRoundingMode, true);\n  const program = new DepthwiseConv2DDerInputProgram(convInfo);\n  return backend2.runWebGLProgram(program, [dy, filter], \"float32\");\n}\nvar depthwiseConv2dNativeBackpropInputConfig2 = {\n  kernelName: DepthwiseConv2dNativeBackpropInput,\n  backendName: \"webgl\",\n  kernelFunc: depthwiseConv2dNativeBackpropInput3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/diag_gpu.js\nvar DiagProgram = class {\n  constructor(size) {\n    this.variableNames = [\"X\"];\n    this.outputShape = [size, size];\n    this.userCode = `\n      void main() {\n          ivec2 coords = getOutputCoords();\n          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;\n          setOutput(val);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Diag.js\nfunction diag3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  const outShape = [...x.shape, ...x.shape];\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const flat = reshape4({ inputs: { x }, backend: backend2, attrs: { shape: [xSize] } });\n  const program = new DiagProgram(xSize);\n  const res = backend2.runWebGLProgram(program, [flat], flat.dtype);\n  const out = reshape4({ inputs: { x: res }, backend: backend2, attrs: { shape: outShape } });\n  backend2.disposeIntermediateTensorInfo(flat);\n  backend2.disposeIntermediateTensorInfo(res);\n  return out;\n}\nvar diagConfig2 = {\n  kernelName: Diag,\n  backendName: \"webgl\",\n  kernelFunc: diag3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/dilation_gpu.js\nvar Dilation2DProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"x\", \"W\"];\n    this.outputShape = convInfo.outShape;\n    const { inHeight, inWidth, padInfo, strideHeight, strideWidth, filterHeight, filterWidth, dilationHeight, dilationWidth } = convInfo;\n    const { top: padTop, left: padLeft } = padInfo;\n    this.userCode = `\n      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});\n      const ivec2 pads = ivec2(${padTop}, ${padLeft});\n      const float neg_infinity = -3.4e38;\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        int d1 = coords.w;\n        ivec2 outTopLeftCorner =\n            coords.yz * strides - pads;\n        int hBeg = outTopLeftCorner.x;\n        int wBeg = outTopLeftCorner.y;\n\n        float curVal = neg_infinity;\n        for (int h = 0; h < ${filterHeight}; h++) {\n          int hIn = hBeg + h * ${dilationHeight};\n\n          if (hIn >= 0 && hIn < ${inHeight}) {\n            for (int w = 0; w < ${filterWidth}; w++) {\n              int wIn = wBeg + w * ${dilationWidth};\n\n              if (wIn >= 0 && wIn < ${inWidth}) {\n                float xVal = getX(batch, hIn, wIn, d1);\n                float wVal = getW(h, w, d1);\n\n                float val = xVal + wVal;\n                if (val > curVal) {\n                  curVal = val;\n                }\n              }\n            }\n          }\n        }\n\n        float result = curVal;\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Dilation2D.js\nfunction dilation2D(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dilations } = attrs;\n  const convInfo = backend_util_exports.computeDilation2DInfo(x.shape, filter.shape, strides, pad3, \"NHWC\", dilations);\n  let out;\n  const program = new Dilation2DProgram(convInfo);\n  out = backend2.runWebGLProgram(program, [x, filter], \"float32\");\n  const outReshaped = reshape4({ inputs: { x: out }, backend: backend2, attrs: { shape: convInfo.outShape } });\n  backend2.disposeIntermediateTensorInfo(out);\n  return outReshaped;\n}\nvar dilation2DConfig2 = {\n  kernelName: Dilation2D,\n  backendName: \"webgl\",\n  kernelFunc: dilation2D\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Einsum.js\nfunction einsum3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { equation } = attrs;\n  const tensors = inputs;\n  const { allDims, summedDims, idDims } = backend_util_exports.decodeEinsumEquation(equation, tensors.length);\n  backend_util_exports.checkEinsumDimSizes(allDims.length, idDims, tensors);\n  const { path, steps } = backend_util_exports.getEinsumComputePath(summedDims, idDims);\n  const nSteps = steps.length;\n  let out = null;\n  let numDimsRemaining = allDims.length;\n  const tensorsToDispose = [];\n  for (let i2 = 0; i2 < nSteps; ++i2) {\n    for (const idTerm of steps[i2]) {\n      const { permutationIndices: perm, expandDims: dimsToExpand } = backend_util_exports.getEinsumPermutation(numDimsRemaining, idDims[idTerm]);\n      let x;\n      if (backend_util_exports.isIdentityPermutation(perm)) {\n        x = tensors[idTerm];\n      } else {\n        x = transpose3({ inputs: { x: tensors[idTerm] }, backend: backend2, attrs: { perm } });\n        tensorsToDispose.push(x);\n      }\n      const targetShape = x.shape.slice();\n      for (let k = 0; k < dimsToExpand.length; ++k) {\n        targetShape.splice(dimsToExpand[k], 0, 1);\n      }\n      if (!util_exports.arraysEqual(x.shape, targetShape)) {\n        x = reshape4({ inputs: { x }, backend: backend2, attrs: { shape: targetShape } });\n        tensorsToDispose.push(x);\n      }\n      if (out === null) {\n        out = x;\n      } else {\n        out = multiply3({ inputs: { a: x, b: out }, backend: backend2 });\n        tensorsToDispose.push(out);\n      }\n    }\n    if (i2 < nSteps - 1) {\n      if (path[i2] >= 0) {\n        out = sum4({\n          inputs: { x: out },\n          backend: backend2,\n          attrs: {\n            axis: path[i2] - (allDims.length - numDimsRemaining),\n            keepDims: false\n          }\n        });\n        tensorsToDispose.push(out);\n      }\n      numDimsRemaining--;\n    }\n  }\n  for (const tensorInfo of tensorsToDispose) {\n    if (tensorInfo === out) {\n      continue;\n    }\n    backend2.disposeIntermediateTensorInfo(tensorInfo);\n  }\n  return out;\n}\nvar einsumConfig2 = {\n  kernelName: Einsum,\n  backendName: \"webgl\",\n  kernelFunc: einsum3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Elu.js\nvar ELU4 = `return (x >= 0.0) ? x : (exp(x) - 1.0);`;\nvar ELU_PACKED = `\n  vec4 result;\n\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\n\n  return result;\n`;\nvar elu5 = unaryKernelFunc2({ opSnippet: ELU4, packedOpSnippet: ELU_PACKED });\nvar eluConfig2 = {\n  kernelName: Elu,\n  backendName: \"webgl\",\n  kernelFunc: elu5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/EluGrad.js\nvar ELU_DER = `return (b >= 1.0) ? a : a * (b + 1.0);`;\nvar ELU_DER_PACKED = `\n  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));\n  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));\n`;\nvar eluGrad2 = (args) => {\n  const { inputs, backend: backend2 } = args;\n  const { dy, y } = inputs;\n  const program = env().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\") ? new BinaryOpPackedProgram(ELU_DER_PACKED, dy.shape, y.shape) : new BinaryOpProgram(ELU_DER, dy.shape, y.shape);\n  return backend2.runWebGLProgram(program, [dy, y], dy.dtype);\n};\nvar eluGradConfig3 = {\n  kernelName: EluGrad,\n  backendName: \"webgl\",\n  kernelFunc: eluGrad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Equal.js\nvar PACKED_EQUAL = `\n  return vec4(equal(a, b));\n`;\nvar EQUAL = `return float(a == b);`;\nvar equal3 = binaryKernelFunc2({\n  opSnippet: EQUAL,\n  packedOpSnippet: PACKED_EQUAL,\n  dtype: \"bool\",\n  cpuKernelImpl: equalImplCPU\n});\nvar equalConfig2 = {\n  kernelName: Equal,\n  backendName: \"webgl\",\n  kernelFunc: equal3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Erf.js\nvar ERF = `\n  // Error function is calculated approximately with elementary function.\n  // See \"Handbook of Mathematical Functions with Formulas,\n  // Graphs, and Mathematical Tables\", Abramowitz and Stegun.\n  float p = ${backend_util_exports.ERF_P};\n  float a1 = ${backend_util_exports.ERF_A1};\n  float a2 = ${backend_util_exports.ERF_A2};\n  float a3 = ${backend_util_exports.ERF_A3};\n  float a4 = ${backend_util_exports.ERF_A4};\n  float a5 = ${backend_util_exports.ERF_A5};\n\n  float sign = sign(x);\n  x = abs(x);\n  float t = 1.0 / (1.0 + p * x);\n  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));\n`;\nvar erf3 = unaryKernelFunc2({ opSnippet: ERF });\nvar erfConfig2 = {\n  kernelName: Erf,\n  backendName: \"webgl\",\n  kernelFunc: erf3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Exp.js\nvar EXP = CHECK_NAN_SNIPPET_UNARY + `\n  return exp(x);\n`;\nvar EXP_PACKED = `\n  vec4 result = exp(x);\n  bvec4 isNaN = isnan(x);\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n`;\nvar exp3 = unaryKernelFunc2({\n  opSnippet: EXP,\n  packedOpSnippet: EXP_PACKED,\n  cpuKernelImpl: expImplCPU,\n  dtype: \"float32\"\n});\nvar expConfig2 = {\n  kernelName: Exp,\n  backendName: \"webgl\",\n  kernelFunc: exp3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ExpandDims.js\nfunction expandDims4(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { dim } = attrs;\n  const { input: input2 } = inputs;\n  const inputRank = input2.shape.length;\n  const newShape = input2.shape.slice();\n  let $dim = dim;\n  if (dim < 0) {\n    util_exports.assert(-(inputRank + 1) <= dim, () => `Axis must be in the interval [${-(inputRank + 1)}, ${inputRank}]`);\n    $dim = inputRank + dim + 1;\n  }\n  newShape.splice($dim, 0, 1);\n  return reshape4({ inputs: { x: input2 }, backend: backend2, attrs: { shape: newShape } });\n}\nvar expandDimsConfig2 = {\n  kernelName: ExpandDims,\n  backendName: \"webgl\",\n  kernelFunc: expandDims4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Expm1.js\nvar EXPM1 = `return exp(x) - 1.0;`;\nvar expm13 = unaryKernelFunc2({ opSnippet: EXPM1, packedOpSnippet: EXPM1, cpuKernelImpl: expm1ImplCPU });\nvar expm1Config2 = {\n  kernelName: Expm1,\n  backendName: \"webgl\",\n  kernelFunc: expm13\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/fft_gpu.js\nvar FFTProgram = class {\n  constructor(component, inputShape, inverse) {\n    this.variableNames = [\"real\", \"imag\"];\n    const innerDim = inputShape[1];\n    this.outputShape = inputShape;\n    const exponentMultiplierSnippet = inverse ? `2.0 * ${Math.PI}` : `-2.0 * ${Math.PI}`;\n    const resultDenominator = inverse ? `${innerDim}.0` : \"1.0\";\n    let opString;\n    if (component === \"real\") {\n      opString = \"return real * expR - imag * expI;\";\n    } else if (component === \"imag\") {\n      opString = \"return real * expI + imag * expR;\";\n    } else {\n      throw new Error(`FFT component must be either \"real\" or \"imag\", got ${component}.`);\n    }\n    this.userCode = `\n      const float exponentMultiplier = ${exponentMultiplierSnippet};\n\n      float unaryOpComplex(float real, float expR, float imag, float expI) {\n        ${opString}\n      }\n\n      float mulMatDFT(int batch, int index) {\n        float indexRatio = float(index) / float(${innerDim});\n        float exponentMultiplierTimesIndexRatio =\n            exponentMultiplier * indexRatio;\n\n        float result = 0.0;\n\n        for (int i = 0; i < ${innerDim}; i++) {\n          // x = (-2|2 * PI / N) * index * i;\n          float x = exponentMultiplierTimesIndexRatio * float(i);\n          float expR = cos(x);\n          float expI = sin(x);\n          float real = getReal(batch, i);\n          float imag = getImag(batch, i);\n\n          result +=\n              unaryOpComplex(real, expR, imag, expI) / ${resultDenominator};\n        }\n\n        return result;\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        setOutput(mulMatDFT(coords[0], coords[1]));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FFT_impl.js\nfunction fftImpl2(x, inverse, backend2) {\n  const xData = backend2.texData.get(x.dataId);\n  const inputSize = util_exports.sizeFromShape(x.shape);\n  const innerDimensionSize = x.shape[x.shape.length - 1];\n  const batch = inputSize / innerDimensionSize;\n  const input2D = reshape4({ inputs: { x }, backend: backend2, attrs: { shape: [batch, innerDimensionSize] } });\n  const xShape = input2D.shape;\n  const realProgram = new FFTProgram(\"real\", xShape, inverse);\n  const imagProgram = new FFTProgram(\"imag\", xShape, inverse);\n  const inputs = [\n    {\n      dataId: xData.complexTensorInfos.real.dataId,\n      dtype: xData.complexTensorInfos.real.dtype,\n      shape: xShape\n    },\n    {\n      dataId: xData.complexTensorInfos.imag.dataId,\n      dtype: xData.complexTensorInfos.imag.dtype,\n      shape: xShape\n    }\n  ];\n  const realPart = backend2.runWebGLProgram(realProgram, inputs, \"float32\");\n  const imagPart = backend2.runWebGLProgram(imagProgram, inputs, \"float32\");\n  const complexOutput = complex3({ inputs: { real: realPart, imag: imagPart }, backend: backend2 });\n  backend2.disposeIntermediateTensorInfo(realPart);\n  backend2.disposeIntermediateTensorInfo(imagPart);\n  const complexOutputReshaped = reshape4({ inputs: { x: complexOutput }, backend: backend2, attrs: { shape: x.shape } });\n  backend2.disposeIntermediateTensorInfo(input2D);\n  backend2.disposeIntermediateTensorInfo(complexOutput);\n  return complexOutputReshaped;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FFT.js\nfunction fft3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  return fftImpl2(input2, false, backend2);\n}\nvar fftConfig2 = {\n  kernelName: FFT,\n  backendName: \"webgl\",\n  kernelFunc: fft3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/fill_gpu.js\nvar FillProgram = class {\n  constructor(shape, value) {\n    this.outputShape = [];\n    this.customUniforms = [{ name: \"value\", type: \"float\" }];\n    this.variableNames = [\"x\"];\n    this.outputShape = shape;\n    this.userCode = `\n      void main() {\n        // Input can be obtained from uniform value.\n        setOutput(value);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Fill.js\nfunction fill3(args) {\n  const { backend: backend2, attrs } = args;\n  const { shape, value } = attrs;\n  let { dtype } = attrs;\n  dtype = dtype || util_exports.inferDtype(value);\n  if (dtype === \"string\") {\n    const values = util_exports.getArrayFromDType(dtype, util_exports.sizeFromShape(shape));\n    values.fill(value);\n    return backend2.makeTensorInfo(shape, dtype, values);\n  } else {\n    const program = new FillProgram(shape, value);\n    const customValues = [[value]];\n    return backend2.runWebGLProgram(program, [], dtype, customValues);\n  }\n}\nvar fillConfig2 = {\n  kernelName: Fill,\n  backendName: \"webgl\",\n  kernelFunc: fill3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/flip_left_right_gpu.js\nvar FlipLeftRightProgram = class {\n  constructor(imageShape) {\n    this.variableNames = [\"Image\"];\n    this.outputShape = [];\n    const imageWidth = imageShape[2];\n    this.outputShape = imageShape;\n    this.userCode = `\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int x = coords[2];\n\n          int coordX = ${imageWidth} - x - 1;\n          float outputValue;\n          if(coordX >= 0 && coordX < ${imageWidth}) {\n            outputValue = getImage(coords[0], coords[1], coordX, coords[3]);\n          } else {\n            outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);\n          }\n          setOutput(outputValue);\n        }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FlipLeftRight.js\nvar flipLeftRightConfig2 = {\n  kernelName: FlipLeftRight,\n  backendName: \"webgl\",\n  kernelFunc: ({ inputs, backend: backend2 }) => {\n    const { image: image2 } = inputs;\n    const webglBackend = backend2;\n    const program = new FlipLeftRightProgram(image2.shape);\n    const output = webglBackend.runWebGLProgram(program, [image2], image2.dtype);\n    return output;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Floor.js\nvar FLOOR = `return floor(x);`;\nvar floor3 = unaryKernelFunc2({ opSnippet: FLOOR, packedOpSnippet: FLOOR, cpuKernelImpl: floorImplCPU });\nvar floorConfig2 = {\n  kernelName: Floor,\n  backendName: \"webgl\",\n  kernelFunc: floor3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FloorDiv.js\nvar INT_DIV = `\n  float s = sign(a) * sign(b);\n  int ia = round(a);\n  int ib = round(b);\n  if (ib != 0) {\n    // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n    return float(idiv(ia, ib, s));\n  } else {\n    return NAN;\n  }\n`;\nvar INT_DIV_PACKED = `\n  ivec4 ia = round(a);\n  ivec4 ib = round(b);\n  bvec4 cond = notEqual(ib, ivec4(0));\n  ivec4 result = ivec4(0);\n  vec4 s = sign(a) * sign(b);\n\n  // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n  if (cond[0]) {\n    result[0] = idiv(ia[0], ib[0], s[0]);\n  }\n  if (cond[1]) {\n    result[1] = idiv(ia[1], ib[1], s[1]);\n  }\n  if (cond[2]) {\n    result[2] = idiv(ia[2], ib[2], s[2]);\n  }\n  if (cond[3]) {\n    result[3] = idiv(ia[3], ib[3], s[3]);\n  }\n  return vec4(result);\n`;\nvar floorDiv3 = binaryKernelFunc2({ opSnippet: INT_DIV, packedOpSnippet: INT_DIV_PACKED, dtype: \"int32\" });\nvar floorDivConfig2 = {\n  kernelName: FloorDiv,\n  backendName: \"webgl\",\n  kernelFunc: floorDiv3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FromPixels_utils/from_pixels_gpu.js\nvar FromPixelsProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    const glsl = getGlslDifferences();\n    const [height, width] = outputShape;\n    this.outputShape = outputShape;\n    this.userCode = `\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${width}.0, ${height}.0);\n\n        vec4 values = ${glsl.texture2D}(A, uv);\n        float value;\n        if (depth == 0) {\n          value = values.r;\n        } else if (depth == 1) {\n          value = values.g;\n        } else if (depth == 2) {\n          value = values.b;\n        } else if (depth == 3) {\n          value = values.a;\n        }\n\n        setOutput(floor(value * 255.0 + 0.5));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FromPixels_utils/from_pixels_packed_gpu.js\nvar FromPixelsPackedProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = false;\n    this.packedOutput = true;\n    const glsl = getGlslDifferences();\n    const [height, width] = outputShape;\n    this.outputShape = outputShape;\n    this.userCode = `\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n\n        vec4 result = vec4(0.);\n\n        for(int row=0; row<=1; row++) {\n          for(int col=0; col<=1; col++) {\n            texC = coords[1] + row;\n            depth = coords[2] + col;\n\n            vec2 uv = (vec2(texC, texR) + halfCR) /\n                       vec2(${width}.0, ${height}.0);\n            vec4 values = ${glsl.texture2D}(A, uv);\n            float value;\n            if (depth == 0) {\n              value = values.r;\n            } else if (depth == 1) {\n              value = values.g;\n            } else if (depth == 2) {\n              value = values.b;\n            } else if (depth == 3) {\n              value = values.a;\n            }\n\n            result[row * 2 + col] = floor(value * 255.0 + 0.5);\n          }\n        }\n\n        ${glsl.output} = result;\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FromPixels.js\nvar fromPixelsConfig = {\n  kernelName: FromPixels,\n  backendName: \"webgl\",\n  kernelFunc: fromPixels2\n};\nvar fromPixels2DContext2;\nfunction fromPixels2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  let { pixels } = inputs;\n  const { numChannels } = attrs;\n  const isVideo = typeof HTMLVideoElement !== \"undefined\" && pixels instanceof HTMLVideoElement;\n  const isImage = typeof HTMLImageElement !== \"undefined\" && pixels instanceof HTMLImageElement;\n  const [width, height] = isVideo ? [\n    pixels.videoWidth,\n    pixels.videoHeight\n  ] : [pixels.width, pixels.height];\n  const texShape = [height, width];\n  const outShape = [height, width, numChannels];\n  if (isImage || isVideo) {\n    if (fromPixels2DContext2 == null) {\n      fromPixels2DContext2 = document.createElement(\"canvas\").getContext(\"2d\");\n    }\n    fromPixels2DContext2.canvas.width = width;\n    fromPixels2DContext2.canvas.height = height;\n    fromPixels2DContext2.drawImage(pixels, 0, 0, width, height);\n    pixels = fromPixels2DContext2.canvas;\n  }\n  const tempPixelHandle = backend2.makeTensorInfo(texShape, \"int32\");\n  backend2.texData.get(tempPixelHandle.dataId).usage = TextureUsage.PIXELS;\n  backend2.gpgpu.uploadPixelDataToTexture(backend2.getTexture(tempPixelHandle.dataId), pixels);\n  const program = env().getBool(\"WEBGL_PACK\") ? new FromPixelsPackedProgram(outShape) : new FromPixelsProgram(outShape);\n  const res = backend2.runWebGLProgram(program, [tempPixelHandle], \"int32\");\n  backend2.disposeData(tempPixelHandle.dataId);\n  return res;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FusedConv2D.js\nfunction fusedConv2d(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode, false, $dataFormat);\n  let out;\n  const intermediates = [];\n  if (convInfo.filterHeight === 1 && convInfo.filterWidth === 1 && convInfo.dilationHeight === 1 && convInfo.dilationWidth === 1 && convInfo.strideHeight === 1 && convInfo.strideWidth === 1 && (convInfo.padInfo.type === \"SAME\" || convInfo.padInfo.type === \"VALID\")) {\n    out = conv2dByMatMul({\n      x,\n      filter,\n      convInfo,\n      backend: backend2,\n      bias,\n      activation: activation2,\n      preluActivationWeights,\n      leakyreluAlpha\n    });\n  } else if (env().getBool(\"WEBGL_CONV_IM2COL\")) {\n    out = conv2dWithIm2Row({\n      x,\n      filter,\n      convInfo,\n      backend: backend2,\n      bias,\n      activation: activation2,\n      preluActivationWeights,\n      leakyreluAlpha\n    });\n  } else {\n    const hasBias = bias != null;\n    const hasPreluActivationWeights = preluActivationWeights != null;\n    const hasLeakyreluAlpha = activation2 === \"leakyrelu\";\n    const fusedActivation = activation2 ? mapActivationToShaderProgram(activation2, false) : null;\n    const program = new Conv2DProgram(convInfo, hasBias, fusedActivation, hasPreluActivationWeights, hasLeakyreluAlpha);\n    const inputs2 = [x, filter];\n    const alignInputWithDataFormat = (input2, dataFormat2) => {\n      if (dataFormat2 === \"NCHW\" && input2.shape.length === 1 && input2.shape[0] !== 1) {\n        const alignedInput = reshape4({\n          inputs: { x: input2 },\n          backend: backend2,\n          attrs: { shape: [input2.shape[0], 1, 1] }\n        });\n        intermediates.push(alignedInput);\n        return alignedInput;\n      }\n      return input2;\n    };\n    if (hasBias) {\n      inputs2.push(alignInputWithDataFormat(bias, dataFormat));\n    }\n    if (hasPreluActivationWeights) {\n      inputs2.push(alignInputWithDataFormat(preluActivationWeights, dataFormat));\n    }\n    if (hasLeakyreluAlpha) {\n      const $leakyreluAlpha = backend2.makeTensorInfo([], \"float32\", util_exports.createScalarValue(leakyreluAlpha, \"float32\"));\n      inputs2.push($leakyreluAlpha);\n      intermediates.push($leakyreluAlpha);\n    }\n    out = backend2.runWebGLProgram(program, inputs2, \"float32\");\n  }\n  const outReshaped = reshape4({ inputs: { x: out }, backend: backend2, attrs: { shape: convInfo.outShape } });\n  intermediates.push(out);\n  intermediates.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return outReshaped;\n}\nvar fusedConv2DConfig2 = {\n  kernelName: FusedConv2D,\n  backendName: \"webgl\",\n  kernelFunc: fusedConv2d\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FusedDepthwiseConv2D.js\nfunction fusedDepthwiseConv2D2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dilations, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  const intermediates = [];\n  let $dilations = dilations;\n  if ($dilations == null) {\n    $dilations = [1, 1];\n  }\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, $dilations), () => `Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${strides} and dilations '${$dilations}'`);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad3, dimRoundingMode, true);\n  const shouldPackDepthwiseConv = env().getBool(\"WEBGL_PACK_DEPTHWISECONV\") && convInfo.strideWidth <= 2 && convInfo.outChannels / convInfo.inChannels === 1;\n  const fusedActivation = activation2 ? mapActivationToShaderProgram(activation2, shouldPackDepthwiseConv) : null;\n  const programInputs = [x, filter];\n  const hasBias = bias != null;\n  const hasPreluActivationWeights = preluActivationWeights != null;\n  const hasLeakyreluAlpha = activation2 === \"leakyrelu\";\n  if (hasBias) {\n    programInputs.push(bias);\n  }\n  if (hasPreluActivationWeights) {\n    programInputs.push(preluActivationWeights);\n  }\n  if (hasLeakyreluAlpha) {\n    const $leakyreluAlpha = backend2.makeTensorInfo([], \"float32\", util_exports.createScalarValue(leakyreluAlpha, \"float32\"));\n    programInputs.push($leakyreluAlpha);\n    intermediates.push($leakyreluAlpha);\n  }\n  let program;\n  if (shouldPackDepthwiseConv) {\n    program = new DepthwiseConvPacked2DProgram(convInfo, hasBias, fusedActivation, hasPreluActivationWeights, hasLeakyreluAlpha);\n  } else {\n    program = new DepthwiseConv2DProgram(convInfo, hasBias, fusedActivation, hasPreluActivationWeights, hasLeakyreluAlpha);\n  }\n  const customValues = [\n    [convInfo.padInfo.top, convInfo.padInfo.left],\n    [convInfo.strideHeight, convInfo.strideWidth],\n    [convInfo.dilationHeight, convInfo.dilationWidth],\n    [convInfo.inHeight, convInfo.inWidth]\n  ];\n  const result = backend2.runWebGLProgram(program, programInputs, \"float32\", customValues);\n  intermediates.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return result;\n}\nvar fusedDepthwiseConv2DConfig2 = {\n  kernelName: FusedDepthwiseConv2D,\n  backendName: \"webgl\",\n  kernelFunc: fusedDepthwiseConv2D2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/gather_nd_gpu.js\nvar GatherNDProgram = class {\n  constructor(sliceDim, strides, shape, paramsShape) {\n    this.sliceDim = sliceDim;\n    this.strides = strides;\n    this.paramsShape = paramsShape;\n    this.variableNames = [\"x\", \"indices\"];\n    this.outputShape = shape;\n    const stridesType = getCoordsDataType(strides.length);\n    const dtype = getCoordsDataType(shape.length);\n    const strideString = this.sliceDim > 1 ? \"strides[j]\" : \"strides\";\n    const paramsShapeType = getCoordsDataType(paramsShape.length);\n    const paramsShapeString = paramsShape.length > 1 ? \"paramsShape[j]\" : \"paramsShape\";\n    this.userCode = `\n        ${stridesType} strides = ${stridesType}(${this.strides});\n        ${paramsShapeType} paramsShape = ${paramsShapeType}(${this.paramsShape});\n         void main() {\n          ${dtype} coords = getOutputCoords();\n          int flattenIndex = 0;\n          bool out_of_bounds = false;\n          for (int j = 0; j < ${this.sliceDim}; j++) {\n            int index = round(getIndices(coords[0], j));\n            out_of_bounds = out_of_bounds || index < 0;\n            out_of_bounds = out_of_bounds || index >= ${paramsShapeString};\n            flattenIndex += index * ${strideString};\n          }\n          setOutput(out_of_bounds ? 0.0 : getX(flattenIndex, coords[1]));\n        }\n      `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/GatherNd.js\nfunction gatherNd2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { params, indices } = inputs;\n  const indicesShape = indices.shape;\n  const sliceRank = indicesShape[indicesShape.length - 1];\n  const paramsSize = util_exports.sizeFromShape(params.shape);\n  const [resultShape, numSlices, sliceSize, strides] = backend_util_exports.prepareAndValidate(params, indices);\n  const flattenIndices = reshape4({ inputs: { x: indices }, backend: backend2, attrs: { shape: [numSlices, sliceRank] } });\n  const flattenX = reshape4({\n    inputs: { x: params },\n    backend: backend2,\n    attrs: { shape: [util_exports.sizeFromShape(params.shape) / sliceSize, sliceSize] }\n  });\n  if (backend2.shouldExecuteOnCPU([params, indices]) || params.dtype === \"string\") {\n    const indicesData = backend2.readSync(indices.dataId);\n    const paramsBuf = backend2.bufferSync(params);\n    const outValue = gatherNdImplCPU(indicesData, paramsBuf, params.dtype, numSlices, sliceRank, sliceSize, strides, params.shape, paramsSize);\n    return backend2.makeTensorInfo(resultShape, params.dtype, outValue.values);\n  }\n  const program = new GatherNDProgram(sliceRank, strides, [numSlices, sliceSize], params.shape);\n  const res = backend2.runWebGLProgram(program, [flattenX, flattenIndices], flattenX.dtype);\n  const reshaped = reshape4({ inputs: { x: res }, backend: backend2, attrs: { shape: resultShape } });\n  backend2.disposeIntermediateTensorInfo(flattenIndices);\n  backend2.disposeIntermediateTensorInfo(flattenX);\n  backend2.disposeIntermediateTensorInfo(res);\n  return reshaped;\n}\nvar gatherNdConfig2 = {\n  kernelName: GatherNd,\n  backendName: \"webgl\",\n  kernelFunc: gatherNd2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/gather_gpu.js\nvar GatherProgram = class {\n  constructor(aShape, outputShape) {\n    this.variableNames = [\"A\", \"indices\"];\n    this.outputShape = outputShape;\n    this.rank = outputShape.length;\n    const dtype = getCoordsDataType(this.rank);\n    const sourceCoords = getSourceCoords2(aShape, 2);\n    this.userCode = `\n      void main() {\n        ${dtype} resRC = getOutputCoords();\n        int index = int(getIndices(resRC.x, resRC.z));\n        float inBounds = (index >= 0) && (index < ${aShape[2]}) ? 1.0 : 0.0;\n        setOutput(inBounds * getA(${sourceCoords}));\n      }\n    `;\n  }\n};\nfunction getSourceCoords2(aShape, axis) {\n  const currentCoords = [\"resRC.x\", \"resRC.y\", \"resRC.z\", \"resRC.w\"];\n  const sourceCoords = [];\n  for (let i2 = 0; i2 < aShape.length; i2++) {\n    if (i2 === 2) {\n      sourceCoords.push(\"index\");\n    } else {\n      sourceCoords.push(`${currentCoords[i2]}`);\n    }\n  }\n  return sourceCoords.join();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/GatherV2.js\nfunction gatherV22(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, indices } = inputs;\n  const { axis, batchDims } = attrs;\n  const parsedAxis = util_exports.parseAxisParam(axis, x.shape)[0];\n  if (env().get(\"DEBUG\")) {\n    const indicesVals = backend2.readSync(indices.dataId);\n    const axisDim = x.shape[parsedAxis];\n    for (let i2 = 0; i2 < indicesVals.length; ++i2) {\n      const index = indicesVals[i2];\n      util_exports.assert(index <= axisDim - 1 && index >= 0, () => `GatherV2: the index value ${index} is not in [0, ${axisDim - 1}]`);\n    }\n  }\n  const shapeInfo = backend_util_exports.segment_util.collectGatherOpShapeInfo(x, indices, parsedAxis, batchDims);\n  const indicesSize = util_exports.sizeFromShape(indices.shape);\n  const toDispose = [];\n  const flattenX = reshape4({\n    inputs: { x },\n    backend: backend2,\n    attrs: {\n      shape: [\n        shapeInfo.batchSize,\n        shapeInfo.outerSize,\n        shapeInfo.dimSize,\n        shapeInfo.sliceSize\n      ]\n    }\n  });\n  const flattenIndex = reshape4({\n    inputs: { x: indices },\n    backend: backend2,\n    attrs: { shape: [shapeInfo.batchSize, indicesSize / shapeInfo.batchSize] }\n  });\n  toDispose.push(flattenX);\n  toDispose.push(flattenIndex);\n  const flattenOutputShape = [\n    shapeInfo.batchSize,\n    shapeInfo.outerSize,\n    indicesSize / shapeInfo.batchSize,\n    shapeInfo.sliceSize\n  ];\n  if (backend2.shouldExecuteOnCPU([x, indices]) || x.dtype === \"string\") {\n    const indicesBuf = backend2.bufferSync(flattenIndex);\n    const xBuf = backend2.bufferSync(flattenX);\n    const outBuf = gatherV2ImplCPU(xBuf, indicesBuf, flattenOutputShape);\n    toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n    return backend2.makeTensorInfo(shapeInfo.outputShape, outBuf.dtype, outBuf.values);\n  }\n  const program = new GatherProgram(flattenX.shape, flattenOutputShape);\n  const res = backend2.runWebGLProgram(program, [flattenX, flattenIndex], flattenX.dtype);\n  toDispose.push(res);\n  const reshaped = reshape4({ inputs: { x: res }, backend: backend2, attrs: { shape: shapeInfo.outputShape } });\n  toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return reshaped;\n}\nvar gatherV2Config2 = {\n  kernelName: GatherV2,\n  backendName: \"webgl\",\n  kernelFunc: gatherV22\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Greater.js\nvar GREATER = `return float(a > b);`;\nvar GREATER_PACKED = `\n  return vec4(greaterThan(a, b));\n`;\nvar greater4 = binaryKernelFunc2({\n  opSnippet: GREATER,\n  packedOpSnippet: GREATER_PACKED,\n  cpuKernelImpl: greaterImplCPU,\n  dtype: \"bool\"\n});\nvar greaterConfig2 = {\n  kernelName: Greater,\n  backendName: \"webgl\",\n  kernelFunc: greater4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/GreaterEqual.js\nvar GREATER_EQUAL = `return float(a >= b);`;\nvar GREATER_EQUAL_PACKED = `\n  return vec4(greaterThanEqual(a, b));\n`;\nvar greaterEqual3 = binaryKernelFunc2({\n  opSnippet: GREATER_EQUAL,\n  packedOpSnippet: GREATER_EQUAL_PACKED,\n  dtype: \"bool\",\n  cpuKernelImpl: greaterEqualImplCPU\n});\nvar greaterEqualConfig2 = {\n  kernelName: GreaterEqual,\n  backendName: \"webgl\",\n  kernelFunc: greaterEqual3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/IFFT.js\nfunction ifft3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  return fftImpl2(input2, true, backend2);\n}\nvar ifftConfig2 = {\n  kernelName: IFFT,\n  backendName: \"webgl\",\n  kernelFunc: ifft3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/IsFinite.js\nvar IS_FINITE = `return float(!isnan(x) && !isinf(x));`;\nvar isFinite4 = unaryKernelFunc2({ opSnippet: IS_FINITE, dtype: \"bool\" });\nvar isFiniteConfig2 = {\n  kernelName: IsFinite,\n  backendName: \"webgl\",\n  kernelFunc: isFinite4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/IsInf.js\nvar IS_INF = `return float(isinf(x));`;\nvar isInf3 = unaryKernelFunc2({ opSnippet: IS_INF, dtype: \"bool\" });\nvar isInfConfig2 = {\n  kernelName: IsInf,\n  backendName: \"webgl\",\n  kernelFunc: isInf3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/IsNaN.js\nvar IS_NAN = `return float(isnan(x));`;\nvar isNaN4 = unaryKernelFunc2({ opSnippet: IS_NAN, dtype: \"bool\" });\nvar isNaNConfig2 = {\n  kernelName: IsNan,\n  backendName: \"webgl\",\n  kernelFunc: isNaN4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Less.js\nvar LESS = `return float(a < b);`;\nvar LESS_PACKED = `\n  return vec4(lessThan(a, b));\n`;\nvar less4 = binaryKernelFunc2({\n  opSnippet: LESS,\n  packedOpSnippet: LESS_PACKED,\n  cpuKernelImpl: lessImplCPU,\n  dtype: \"bool\"\n});\nvar lessConfig2 = {\n  kernelName: Less,\n  backendName: \"webgl\",\n  kernelFunc: less4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LessEqual.js\nvar LESS_EQUAL = `return float(a <= b);`;\nvar LESS_EQUAL_PACKED = `\n  return vec4(lessThanEqual(a, b));\n`;\nvar lessEqual3 = binaryKernelFunc2({\n  opSnippet: LESS_EQUAL,\n  packedOpSnippet: LESS_EQUAL_PACKED,\n  cpuKernelImpl: lessEqualImplCPU,\n  dtype: \"bool\"\n});\nvar lessEqualConfig2 = {\n  kernelName: LessEqual,\n  backendName: \"webgl\",\n  kernelFunc: lessEqual3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LinSpace.js\nfunction linSpace2(args) {\n  const { backend: backend2, attrs } = args;\n  const { start, stop, num } = attrs;\n  const outVals = linSpaceImplCPU(start, stop, num);\n  return backend2.makeTensorInfo([outVals.length], \"float32\", outVals);\n}\nvar linSpaceConfig2 = {\n  kernelName: LinSpace,\n  backendName: \"webgl\",\n  kernelFunc: linSpace2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Log.js\nvar LOG = CHECK_NAN_SNIPPET_UNARY + `\n  return x < 0.0 ? 0./0. : log(x);\n`;\nvar LOG_PACKED = `\n  vec4 result = log(x);\n  bvec4 isNaN = isnan(x);\n  result.r = isNaN.r ? x.r : (x.r < 0.0 ? 0./0. : result.r);\n  result.g = isNaN.g ? x.g : (x.g < 0.0 ? 0./0. : result.g);\n  result.b = isNaN.b ? x.b : (x.b < 0.0 ? 0./0. : result.b);\n  result.a = isNaN.a ? x.a : (x.a < 0.0 ? 0./0. : result.a);\n  return result;\n`;\nvar log4 = unaryKernelFunc2({ opSnippet: LOG, packedOpSnippet: LOG_PACKED, cpuKernelImpl: logImplCPU });\nvar logConfig2 = {\n  kernelName: Log,\n  backendName: \"webgl\",\n  kernelFunc: log4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Log1p.js\nvar LOG1P = CHECK_NAN_SNIPPET_UNARY + `\n  return log(1.0 + x);\n`;\nvar log1p3 = unaryKernelFunc2({ opSnippet: LOG1P });\nvar log1pConfig2 = {\n  kernelName: Log1p,\n  backendName: \"webgl\",\n  kernelFunc: log1p3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LogicalAnd.js\nvar LOGICAL_AND = `return float(a >= 1.0 && b >= 1.0);`;\nvar LOGICAL_AND_PACKED = `\n  return vec4(\n    vec4(greaterThanEqual(a, vec4(1.0))) *\n    vec4(greaterThanEqual(b, vec4(1.0))));\n`;\nvar logicalAnd3 = binaryKernelFunc2({\n  opSnippet: LOGICAL_AND,\n  packedOpSnippet: LOGICAL_AND_PACKED,\n  dtype: \"bool\"\n});\nvar logicalAndConfig2 = {\n  kernelName: LogicalAnd,\n  backendName: \"webgl\",\n  kernelFunc: logicalAnd3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LogicalNot.js\nvar LOGICAL_NOT = `return float(!(x >= 1.0));`;\nvar logicalNot3 = unaryKernelFunc2({ opSnippet: LOGICAL_NOT });\nvar logicalNotConfig2 = {\n  kernelName: LogicalNot,\n  backendName: \"webgl\",\n  kernelFunc: logicalNot3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LogicalOr.js\nvar LOGICAL_OR = `return float(a >= 1.0 || b >= 1.0);`;\nvar LOGICAL_OR_PACKED = `\n  return min(\n    vec4(greaterThanEqual(a, vec4(1.0))) +\n    vec4(greaterThanEqual(b, vec4(1.0))),\n    vec4(1.0));\n`;\nvar logicalOr3 = binaryKernelFunc2({ opSnippet: LOGICAL_OR, packedOpSnippet: LOGICAL_OR_PACKED, dtype: \"bool\" });\nvar logicalOrConfig2 = {\n  kernelName: LogicalOr,\n  backendName: \"webgl\",\n  kernelFunc: logicalOr3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/lrn_gpu.js\nvar LRNProgram = class {\n  constructor(xShape, radius, bias, alpha, beta) {\n    this.variableNames = [\"x\"];\n    this.outputShape = [];\n    const rad = radius;\n    const maxD = xShape[3] - 1;\n    this.outputShape = xShape;\n    let powOperator;\n    const basis = `float(${bias}) + float(${alpha}) * sum`;\n    if (beta === 0.5) {\n      powOperator = `inversesqrt(${basis})`;\n    } else if (beta === 1) {\n      powOperator = `1.0/(${basis})`;\n    } else {\n      powOperator = `exp(log(${basis}) * float(-${beta}));`;\n    }\n    this.userCode = `\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n        int d = coords[3];\n        float x = getX(b, r, c, d);\n        float sum = 0.0;\n        for (int j = -${rad}; j <= ${rad}; j++) {\n          int idx = d + j;\n          if (idx >= 0 && idx <=  ${maxD}) {\n            float z = getX(b, r, c, idx);\n            sum += z * z;\n          }\n        }\n        float val = x * ${powOperator};\n        setOutput(val);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/lrn_packed_gpu.js\nvar LRNPackedProgram = class {\n  constructor(xShape, radius, bias, alpha, beta) {\n    this.variableNames = [\"x\"];\n    this.outputShape = [];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    const rad = radius;\n    const maxD = xShape[3] - 1;\n    this.outputShape = xShape;\n    let powOperator;\n    const basis = `float(${bias}) + float(${alpha}) * sum`;\n    if (beta === 0.5) {\n      powOperator = `inversesqrt(${basis})`;\n    } else if (beta === 1) {\n      powOperator = `1.0/(${basis})`;\n    } else {\n      powOperator = `exp(log(${basis}) * float(-${beta}));`;\n    }\n    this.userCode = `\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords.x;\n        int r = coords.y;\n        int c = coords.z;\n        int d = coords.w;\n\n        bool hasNextCol = d < ${this.outputShape[3]};\n        bool hasNextRow = c < ${this.outputShape[2]};\n\n        vec4 sum = vec4(0.);\n        vec4 xFragAtOutputCoords = getX(b, r, c, d);\n\n        vec4 xAtOutputCoords = vec4(\n          getChannel(xFragAtOutputCoords, vec2(c, d)),\n          hasNextCol ?\n            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,\n          hasNextRow ?\n            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0\n        );\n\n        int firstChannel = d - ${rad};\n        vec2 cache = vec2(0.);\n        if(firstChannel >= 0){\n          vec4 firstChannelFrag = getX(b, r, c, firstChannel);\n          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));\n            if(hasNextRow){\n              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));\n            }\n        }\n\n        ivec2 depth = ivec2(d, d + 1);\n        for (int j = - ${rad}; j <= ${rad}; j++) {\n          ivec2 idx = depth + j;\n          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));\n          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${maxD}));\n\n          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;\n          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;\n\n          if(depthInRange || depthPlusOneInRange){\n            vec4 z = vec4(0.);\n            vec4 xFragAtCurrentDepth;\n            z.xz = cache.xy;\n            if(depthPlusOneInRange && hasNextCol){\n              xFragAtCurrentDepth = idx.y != d ?\n                getX(b, r, c, idx.y) : xFragAtOutputCoords;\n              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));\n              if(hasNextRow){\n                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));\n              }\n            }\n            cache.xy = z.yw;\n            sum += z * z;\n          }\n        }\n        vec4 result = xAtOutputCoords * ${powOperator};\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LRN.js\nvar lrn = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { depthRadius, bias, alpha, beta } = attrs;\n  const program = env().getBool(\"WEBGL_PACK_NORMALIZATION\") ? new LRNPackedProgram(x.shape, depthRadius, bias, alpha, beta) : new LRNProgram(x.shape, depthRadius, bias, alpha, beta);\n  return backend2.runWebGLProgram(program, [x], x.dtype);\n};\nvar LRNConfig2 = {\n  kernelName: LRN,\n  backendName: \"webgl\",\n  kernelFunc: lrn\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/lrn_grad_gpu.js\nvar LRNGradProgram = class {\n  constructor(inputShape, depthRadius, bias, alpha, beta) {\n    this.variableNames = [\"inputImage\", \"outputImage\", \"dy\"];\n    this.outputShape = [];\n    this.outputShape = inputShape;\n    this.depth = inputShape[3];\n    this.depthRadius = depthRadius;\n    this.bias = bias;\n    this.alpha = alpha;\n    this.beta = beta;\n    this.userCode = `\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n\n        float result = 0.0;\n        for (int d = 0; d < ${this.depth}; ++d) {\n          int depthBegin = int(max(0.0, float(d - ${depthRadius})));\n          int depthEnd = int(min(float(${this.depth}),\n              float(d + ${depthRadius} + 1)));\n\n          const int MIN_DEPTH_BEGIN = 0;\n          const int MAX_DEPTH_END = ${this.depth};\n\n          float norm = 0.0;\n          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd) {\n              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);\n            }\n            else {\n              break;\n            }\n          }\n\n          norm = float(${alpha}) * norm + float(${bias});\n\n          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd){\n              float dyi = -2.0 * float(${alpha})\n                * float(${beta})\n                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)\n                / norm;\n              if (k == d) {\n                dyi += pow(norm, -1.0 * ${beta});\n              }\n              if (k == coords[3]) {\n                dyi *= getDy(b, r, c, d);\n                result += dyi;\n              }\n            }\n            else {\n              break;\n            }\n          }\n      }\n      setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LRNGrad.js\nvar lrnGrad = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, y, dy } = inputs;\n  const { depthRadius, bias, alpha, beta } = attrs;\n  const program = new LRNGradProgram(x.shape, depthRadius, bias, alpha, beta);\n  return backend2.runWebGLProgram(program, [x, y, dy], x.dtype);\n};\nvar LRNGradConfig2 = {\n  kernelName: LRNGrad,\n  backendName: \"webgl\",\n  kernelFunc: lrnGrad\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Max_impl.js\nfunction maxImpl2(x, reduceShape, outShape, backend2) {\n  const inSize = util_exports.sizeFromShape(reduceShape);\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const batchSize = xSize / inSize;\n  const reshapedInput = reshape4({ inputs: { x }, attrs: { shape: [batchSize, inSize] }, backend: backend2 });\n  const reduced = reduce(reshapedInput, x.dtype, \"max\", backend2);\n  const reshapedOutput = reshape4({ inputs: { x: reduced }, attrs: { shape: outShape }, backend: backend2 });\n  backend2.disposeIntermediateTensorInfo(reshapedInput);\n  backend2.disposeIntermediateTensorInfo(reduced);\n  return reshapedOutput;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Max.js\nfunction max4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { reductionIndices, keepDims } = attrs;\n  const xRank = x.shape.length;\n  const origAxes = util_exports.parseAxisParam(reductionIndices, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  const maxInputIsTransposed = permutedAxes != null;\n  const shouldExecuteOnCPU = backend2.shouldExecuteOnCPU([x]);\n  let maxInput = x;\n  if (maxInputIsTransposed) {\n    if (shouldExecuteOnCPU) {\n      const xTexData = backend2.texData.get(maxInput.dataId);\n      const values = xTexData.values;\n      const newShape = new Array(xRank);\n      for (let i2 = 0; i2 < newShape.length; i2++) {\n        newShape[i2] = x.shape[permutedAxes[i2]];\n      }\n      const maxInputValues = transposeImplCPU(values, x.shape, x.dtype, permutedAxes, newShape);\n      maxInput = backend2.makeTensorInfo(newShape, x.dtype);\n      const maxInputData = backend2.texData.get(maxInput.dataId);\n      maxInputData.values = maxInputValues;\n    } else {\n      maxInput = transposeImpl2(x, permutedAxes, backend2);\n    }\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"max\", axes, xRank);\n  const [maxOutShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(maxInput.shape, axes);\n  let outShape = maxOutShape;\n  if (keepDims) {\n    outShape = backend_util_exports.expandShapeToKeepDim(maxOutShape, origAxes);\n  }\n  let out;\n  if (shouldExecuteOnCPU) {\n    const xTexData = backend2.texData.get(maxInput.dataId);\n    const values = xTexData.values;\n    const outValues = maxImplCPU(values, util_exports.sizeFromShape(reduceShape), outShape, x.dtype);\n    out = backend2.makeTensorInfo(outShape, x.dtype);\n    const outData = backend2.texData.get(out.dataId);\n    outData.values = outValues;\n  } else {\n    out = maxImpl2(maxInput, reduceShape, outShape, backend2);\n  }\n  if (maxInputIsTransposed) {\n    backend2.disposeIntermediateTensorInfo(maxInput);\n  }\n  return out;\n}\nvar maxConfig2 = {\n  kernelName: Max,\n  backendName: \"webgl\",\n  kernelFunc: max4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Maximum.js\nvar MAXIMUM = CHECK_NAN_SNIPPET2 + `\n  return max(a, b);\n`;\nvar MAXIMUM_PACKED = `\n  vec4 result = vec4(max(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  ` + CHECK_NAN_SNIPPET3 + `\n  return result;\n`;\nvar maximum4 = binaryKernelFunc2({\n  opSnippet: MAXIMUM,\n  packedOpSnippet: MAXIMUM_PACKED,\n  cpuKernelImpl: maximumImplCPU\n});\nvar maximumConfig2 = {\n  kernelName: Maximum,\n  backendName: \"webgl\",\n  kernelFunc: maximum4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPool.js\nfunction maxPool3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  assertNotComplex2(x, \"maxPool\");\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = 1;\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in maxPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  if (convInfo.filterWidth === 1 && convInfo.filterHeight === 1 && util_exports.arraysEqual(convInfo.inShape, convInfo.outShape)) {\n    return identity3({ inputs: { x }, backend: backend2 });\n  }\n  const maxPoolProgram = new Pool2DProgram(convInfo, \"max\", false);\n  return backend2.runWebGLProgram(maxPoolProgram, [x], x.dtype);\n}\nvar maxPoolConfig2 = {\n  kernelName: MaxPool,\n  backendName: \"webgl\",\n  kernelFunc: maxPool3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPool3D.js\nfunction maxPool3d2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { filterSize, strides, pad: pad3, dataFormat, dimRoundingMode } = attrs;\n  const dilations = [1, 1, 1];\n  const convInfo = backend_util_exports.computePool3DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode, dataFormat);\n  const maxPoolProgram = new Pool3DProgram(convInfo, \"max\", false);\n  return backend2.runWebGLProgram(maxPoolProgram, [x], x.dtype);\n}\nvar maxPool3DConfig2 = {\n  kernelName: MaxPool3D,\n  backendName: \"webgl\",\n  kernelFunc: maxPool3d2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/max_pool_backprop_gpu.js\nvar MaxPool2DBackpropProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\", \"maxPos\"];\n    this.outputShape = convInfo.inShape;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationHeight = convInfo.dilationHeight;\n    const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n    const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n    const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n    const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n    const lastIndex = effectiveFilterHeight * effectiveFilterWidth - 1;\n    this.userCode = `\n      const ivec2 pads = ivec2(${padTop}, ${padLeft});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ${effectiveFilterHeight};\n          wR += ${dilationHeight}) {\n          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;\n\n          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < ${effectiveFilterWidth}; wC++) {\n            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;\n\n            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n            int maxPosValue = ${lastIndex} - int(getMaxPos(b, idyR, idyC, d));\n\n            // Get the current value, check it against the value from the\n            // position matrix.\n            int curPosValue = wR * ${effectiveFilterWidth} + wC;\n            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n            dotProd += dyValue * mask;\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\nvar MaxPool3DBackpropProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\", \"maxPos\"];\n    this.outputShape = convInfo.inShape;\n    const strideDepth = convInfo.strideDepth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationDepth = convInfo.dilationDepth;\n    const dilationHeight = convInfo.dilationHeight;\n    const dilationWidth = convInfo.dilationWidth;\n    const effectiveFilterDepth = convInfo.effectiveFilterDepth;\n    const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n    const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n    const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;\n    const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n    const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n    const lastIndex = effectiveFilterDepth * effectiveFilterHeight * effectiveFilterWidth - 1;\n    this.userCode = `\n      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < ${effectiveFilterDepth};\n           wD += ${dilationDepth}) {\n          float dyD = float(dyDCorner + wD) / ${strideDepth}.0;\n\n          if (dyD < 0.0 || dyD >= ${convInfo.outDepth}.0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < ${effectiveFilterHeight};\n              wR += ${dilationHeight}) {\n            float dyR = float(dyRCorner + wR) / ${strideHeight}.0;\n\n            if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < ${effectiveFilterWidth};\n                wC += ${dilationWidth}) {\n              float dyC = float(dyCCorner + wC) / ${strideWidth}.0;\n\n              if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n              int maxPosValue = ${lastIndex} -\n                  int(getMaxPos(batch, idyD, idyR, idyC, ch));\n\n              // Get the current value, check it against the value from the\n              // position matrix.\n              int curPosValue =\n                  wD * ${effectiveFilterHeight} * ${effectiveFilterWidth} +\n                  wR * ${effectiveFilterWidth} + wC;\n              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n              dotProd += dyValue * mask;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPool3DGrad.js\nfunction maxPool3DGrad2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2 } = inputs;\n  const x = input2;\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = [1, 1, 1];\n  const convInfo = backend_util_exports.computePool3DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  const maxPool3dPositionsProgram = new Pool3DProgram(convInfo, \"max\", true);\n  const maxPool3dPositions2 = backend2.runWebGLProgram(maxPool3dPositionsProgram, [x], x.dtype);\n  const maxPoolBackpropProgram = new MaxPool3DBackpropProgram(convInfo);\n  const result = backend2.runWebGLProgram(maxPoolBackpropProgram, [dy, maxPool3dPositions2], x.dtype);\n  backend2.disposeIntermediateTensorInfo(maxPool3dPositions2);\n  return result;\n}\nvar maxPool3DGradConfig3 = {\n  kernelName: MaxPool3DGrad,\n  backendName: \"webgl\",\n  kernelFunc: maxPool3DGrad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPoolGrad.js\nfunction maxPoolGrad3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2, output } = inputs;\n  const x = input2;\n  assertNotComplex2([input2, output], \"maxPoolGrad\");\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, 1, pad3, dimRoundingMode);\n  const getPositions = true;\n  const maxPoolPositionsProgram = new Pool2DProgram(convInfo, \"max\", getPositions);\n  const maxPoolPositions2 = backend2.runWebGLProgram(maxPoolPositionsProgram, [x], x.dtype);\n  const maxPoolBackPropProgram = new MaxPool2DBackpropProgram(convInfo);\n  const result = backend2.runWebGLProgram(maxPoolBackPropProgram, [dy, maxPoolPositions2], x.dtype);\n  backend2.disposeIntermediateTensorInfo(maxPoolPositions2);\n  return result;\n}\nvar maxPoolGradConfig3 = {\n  kernelName: MaxPoolGrad,\n  backendName: \"webgl\",\n  kernelFunc: maxPoolGrad3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPoolWithArgmax_impl.js\nfunction maxPoolWithArgmaxImpl2(x, includeBatchInIndex, convInfo, backend2) {\n  let program = new Pool2DProgram(convInfo, \"max\", false);\n  const poolOutput = backend2.runWebGLProgram(program, [x], \"float32\");\n  program = new Pool2DProgram(convInfo, \"max\", true, true, includeBatchInIndex);\n  const indexOutput = backend2.runWebGLProgram(program, [x], \"float32\");\n  return [poolOutput, indexOutput];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPoolWithArgmax.js\nvar maxPoolWithArgmaxConfig2 = {\n  kernelName: MaxPoolWithArgmax,\n  backendName: \"webgl\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { x } = inputs;\n    const { filterSize, strides, pad: pad3, includeBatchInIndex } = attrs;\n    const webglBackend = backend2;\n    util_exports.assert(x.shape.length === 4, () => `Error in maxPool: input must be rank 4 but got rank ${x.shape.length}.`);\n    const dilations = [1, 1];\n    util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in maxPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n    const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, dilations, pad3);\n    const [result, indexes] = maxPoolWithArgmaxImpl2(x, includeBatchInIndex, convInfo, webglBackend);\n    return [result, indexes];\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Mean_impl.js\nfunction meanImpl(x, reduceShape, outShape, backend2) {\n  const inSize = util_exports.sizeFromShape(reduceShape);\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const batchSize = xSize / inSize;\n  const reshapedInput = reshape4({ inputs: { x }, attrs: { shape: [batchSize, inSize] }, backend: backend2 });\n  const reduced = reduce(reshapedInput, \"float32\", \"mean\", backend2);\n  const reshapedOutput = reshape4({ inputs: { x: reduced }, attrs: { shape: outShape }, backend: backend2 });\n  backend2.disposeIntermediateTensorInfo(reshapedInput);\n  backend2.disposeIntermediateTensorInfo(reduced);\n  return reshapedOutput;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Mean.js\nvar meanConfig2 = {\n  kernelName: Mean,\n  backendName: \"webgl\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { x } = inputs;\n    const { keepDims, axis } = attrs;\n    const webglBackend = backend2;\n    const xRank = x.shape.length;\n    const origAxes = util_exports.parseAxisParam(axis, x.shape);\n    let axes = origAxes;\n    const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n    const meanInputIsTransposed = permutedAxes != null;\n    const shouldExecuteOnCPU = webglBackend.shouldExecuteOnCPU([x]);\n    const intermediates = [];\n    let meanInput = x;\n    if (meanInputIsTransposed) {\n      if (shouldExecuteOnCPU) {\n        const xTexData = webglBackend.texData.get(meanInput.dataId);\n        const values = xTexData.values;\n        const newShape = new Array(xRank);\n        for (let i2 = 0; i2 < newShape.length; i2++) {\n          newShape[i2] = x.shape[permutedAxes[i2]];\n        }\n        const meanInputValues = transposeImplCPU(values, x.shape, x.dtype, permutedAxes, newShape);\n        meanInput = webglBackend.makeTensorInfo(newShape, x.dtype);\n        const meanInputData = webglBackend.texData.get(meanInput.dataId);\n        meanInputData.values = meanInputValues;\n      } else {\n        meanInput = transposeImpl2(x, permutedAxes, webglBackend);\n      }\n      intermediates.push(meanInput);\n      axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n    }\n    backend_util_exports.assertAxesAreInnerMostDims(\"sum\", axes, xRank);\n    const [meanOutShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(meanInput.shape, axes);\n    let outShape = meanOutShape;\n    if (keepDims) {\n      outShape = backend_util_exports.expandShapeToKeepDim(meanOutShape, origAxes);\n    }\n    const out = meanImpl(meanInput, reduceShape, outShape, webglBackend);\n    for (const i2 of intermediates) {\n      webglBackend.disposeIntermediateTensorInfo(i2);\n    }\n    return out;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Min.js\nfunction min4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  const xRank = x.shape.length;\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  let permutedX = x;\n  if (permutedAxes != null) {\n    permutedX = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"min\", axes, xRank);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(permutedX.shape, axes);\n  const inSize = util_exports.sizeFromShape(reduceShape);\n  const a2D = reshape4({ inputs: { x: permutedX }, backend: backend2, attrs: { shape: [-1, inSize] } });\n  const reduced = reduce(a2D, a2D.dtype, \"min\", backend2);\n  let res;\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(outShape, origAxes);\n    res = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: newShape } });\n  } else {\n    res = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: outShape } });\n  }\n  backend2.disposeIntermediateTensorInfo(a2D);\n  backend2.disposeIntermediateTensorInfo(reduced);\n  if (permutedAxes != null) {\n    backend2.disposeIntermediateTensorInfo(permutedX);\n  }\n  return res;\n}\nvar minConfig2 = {\n  kernelName: Min,\n  backendName: \"webgl\",\n  kernelFunc: min4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Minimum.js\nvar MINIMUM = CHECK_NAN_SNIPPET2 + `\n  return min(a, b);\n`;\nvar MINIMUM_PACKED = `\n  vec4 result = vec4(min(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  ` + CHECK_NAN_SNIPPET3 + `\n  return result;\n`;\nvar minimum4 = binaryKernelFunc2({\n  opSnippet: MINIMUM,\n  packedOpSnippet: MINIMUM_PACKED,\n  cpuKernelImpl: minimumImplCPU\n});\nvar minimumConfig2 = {\n  kernelName: Minimum,\n  backendName: \"webgl\",\n  kernelFunc: minimum4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/mirror_pad_gpu.js\nvar MirrorPadProgram = class {\n  constructor(xShape, paddings, mode) {\n    this.variableNames = [\"x\"];\n    this.outputShape = paddings.map((p2, i2) => p2[0] + xShape[i2] + p2[1]);\n    const rank = xShape.length;\n    const dtype = getCoordsDataType(rank);\n    const start = paddings.map((p2) => p2[0]).join(\",\");\n    const end = paddings.map((p2, i2) => p2[0] + xShape[i2]).join(\",\");\n    const unpackedCoords = [\"coords[0]\", \"coords[1]\", \"coords[2]\", \"coords[3]\"].slice(0, rank);\n    const offset = mode === \"reflect\" ? 0 : 1;\n    if (rank === 1) {\n      this.userCode = `\n        int start = ${start};\n        int end = ${end};\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start) {\n            outC = start * 2 - outC - ${offset};\n          } else if(outC >= end) {\n            outC = (end - 1) * 2 - outC + ${offset};\n          }\n          setOutput(getX(outC - start));\n        }\n      `;\n      return;\n    }\n    this.userCode = `\n      ${dtype} start = ${dtype}(${start});\n      ${dtype} end = ${dtype}(${end});\n\n      void main() {\n        ${dtype} outC = getOutputCoords();\n        for (int i = 0; i < ${rank}; i++) {\n          if (outC[i] < start[i]) {\n            outC[i] = start[i] * 2 - outC[i] - ${offset};\n          } else if(outC[i] >= end[i]) {\n            outC[i] = (end[i] - 1) * 2 - outC[i] + ${offset};\n          }\n        }\n        ${dtype} coords = outC - start;\n        setOutput(getX(${unpackedCoords}));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/mirror_pad_packed_gpu.js\nvar MirrorPadPackedProgram = class {\n  constructor(xShape, paddings, mode) {\n    this.variableNames = [\"x\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = paddings.map((p2, i2) => p2[0] + xShape[i2] + p2[1]);\n    const rank = xShape.length;\n    const dtype = getCoordsDataType(rank);\n    const start = paddings.map((p2) => p2[0]).join(\",\");\n    const end = paddings.map((p2, i2) => p2[0] + xShape[i2]).join(\",\");\n    const coords3 = getChannels(\"rc\", rank);\n    const source = getChannels(\"source\", rank);\n    const cLimit = `${coords3[rank - 1]} < ${this.outputShape[rank - 1]}`;\n    const innerDims = rank === 1 ? \"source\" : `vec2(${source.slice(-2).join()})`;\n    const offset = mode === \"reflect\" ? 0 : 1;\n    let mainLoop = \"\";\n    if (rank === 1) {\n      const padSetup = `\n        ${dtype} source = rc;\n        if (source < start) {\n          source = start * 2 - source - ${offset};\n        } else if (source >= end) {\n          source = (end - 1) * 2 - source + ${offset};\n        }\n        source -= start;\n      `;\n      mainLoop = `\n        ${dtype} rc = outputLoc;\n        ${padSetup}\n        result[0] = getChannel(getX(${source.join()}), ${innerDims});\n        ${coords3[rank - 1]} += 1;\n        if(${cLimit}) {\n          ${padSetup}\n          result[1] = getChannel(getX(${source.join()}), ${innerDims});\n        }\n      `;\n    } else {\n      const padSetup = `\n        ${dtype} source = rc;\n        ${dtype} lt = ${dtype}(lessThan(source, start));\n        ${dtype} gte = ${dtype}(greaterThanEqual(source, end));\n        ${dtype} orig = 1 - (lt + gte);\n        source = orig * source +\n                lt * (start * 2 - source - ${offset}) +\n                gte * ((end - 1) * 2 - source + ${offset});\n        source -= start;\n      `;\n      mainLoop = `\n        ${dtype} rc = outputLoc;\n        ${padSetup}\n        result[0] = getChannel(getX(${source.join()}), ${innerDims});\n        ${coords3[rank - 1]} += 1;\n        if(${cLimit}) {\n          ${padSetup}\n          result[1] = getChannel(getX(${source.join()}), ${innerDims});\n        }\n        rc = outputLoc;\n        ${coords3[rank - 2]} += 1;\n        if(${coords3[rank - 2]} < ${this.outputShape[rank - 2]}) {\n          ${padSetup}\n          result[2] = getChannel(getX(${source.join()}), ${innerDims});\n          ${coords3[rank - 1]} += 1;\n          if(${cLimit}) {\n            ${padSetup}\n            result[3] = getChannel(getX(${source.join()}), ${innerDims});\n          }\n        }\n      `;\n    }\n    this.userCode = `\n      const ${dtype} start = ${dtype}(${start});\n      const ${dtype} end = ${dtype}(${end});\n\n      void main() {\n        ${dtype} outputLoc = getOutputCoords();\n        vec4 result = vec4(0.);\n        ${mainLoop}\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MirrorPad.js\nvar mirrorPadKernelFunc = ({ inputs, backend: backend2, attrs }) => {\n  const { x } = inputs;\n  const { paddings, mode } = attrs;\n  const program = env().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\") ? new MirrorPadPackedProgram(x.shape, paddings, mode) : new MirrorPadProgram(x.shape, paddings, mode);\n  const output = backend2.runWebGLProgram(program, [x], x.dtype);\n  return output;\n};\nvar mirrorPadConfig2 = {\n  kernelName: MirrorPad,\n  backendName: \"webgl\",\n  kernelFunc: mirrorPadKernelFunc\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Mod.js\nvar MOD = `if (b == 0.0) return NAN;\n  return mod(a, b);`;\nvar MOD_PACKED = `\n  vec4 result = mod(a, b);\n  vec4 isNaN = vec4(equal(b, vec4(0.0)));\n  ` + CHECK_NAN_SNIPPET3 + `\n  return result;\n`;\nvar mod3 = binaryKernelFunc2({\n  opSnippet: MOD,\n  packedOpSnippet: MOD_PACKED\n});\nvar modConfig2 = {\n  kernelName: Mod,\n  backendName: \"webgl\",\n  kernelFunc: mod3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/multinomial_gpu.js\nvar MultinomialProgram = class {\n  constructor(batchSize, numOutcomes, numSamples) {\n    this.variableNames = [\"probs\"];\n    this.customUniforms = [{ name: \"seed\", type: \"float\" }];\n    this.outputShape = [batchSize, numSamples];\n    this.userCode = `\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n\n        float r = random(seed);\n        float cdf = 0.0;\n\n        for (int i = 0; i < ${numOutcomes - 1}; i++) {\n          cdf += getProbs(batch, i);\n\n          if (r < cdf) {\n            setOutput(float(i));\n            return;\n          }\n        }\n\n        // If no other event happened, last event happened.\n        setOutput(float(${numOutcomes - 1}));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/RealDiv.js\nvar DIV = `\nif (a == b) {\n  return 1.0;\n};\nreturn a / b;`;\nvar DIV_PACKED = `\n  // vec4 one = vec4(equal(a, b));\n  // return one + (vec4(1.0) - one) * a / b;\n  vec4 result = a / b;\n  if(a.x == b.x) {\n    result.x = 1.;\n  }\n  if(a.y == b.y) {\n    result.y = 1.;\n  }\n  if(a.z == b.z) {\n    result.z = 1.;\n  }\n  if(a.w == b.w) {\n    result.w = 1.;\n  }\n\n  return result;\n`;\nvar realDiv = binaryKernelFunc2({ opSnippet: DIV, packedOpSnippet: DIV_PACKED, checkOutOfBounds: true });\nvar realDivConfig2 = {\n  kernelName: RealDiv,\n  backendName: \"webgl\",\n  kernelFunc: realDiv\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sub.js\nvar SUB = \"return a - b;\";\nvar sub3 = binaryKernelFunc2({\n  opSnippet: SUB,\n  packedOpSnippet: SUB,\n  supportsComplex: true,\n  cpuKernelImpl: subImplCPU\n});\nvar subConfig2 = {\n  kernelName: Sub,\n  backendName: \"webgl\",\n  kernelFunc: sub3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Softmax.js\nfunction softmax4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { logits } = inputs;\n  const { dim } = attrs;\n  const axes = util_exports.parseAxisParam([dim], logits.shape);\n  const maxLogit = max4({\n    inputs: { x: logits },\n    backend: backend2,\n    attrs: { reductionIndices: axes, keepDims: false }\n  });\n  const expandedShape = backend_util_exports.expandShapeToKeepDim(maxLogit.shape, axes);\n  const maxLogitsReshaped = reshape4({ inputs: { x: maxLogit }, backend: backend2, attrs: { shape: expandedShape } });\n  const a = sub3({ inputs: { a: logits, b: maxLogitsReshaped }, backend: backend2 });\n  const b = exp3({ inputs: { x: a }, backend: backend2 });\n  const sumExp = sum4({ inputs: { x: b }, backend: backend2, attrs: { axis: axes, keepDims: false } });\n  const sumExpReshaped = reshape4({ inputs: { x: sumExp }, backend: backend2, attrs: { shape: expandedShape } });\n  const res = realDiv({ inputs: { a: b, b: sumExpReshaped }, backend: backend2 });\n  backend2.disposeIntermediateTensorInfo(maxLogit);\n  backend2.disposeIntermediateTensorInfo(maxLogitsReshaped);\n  backend2.disposeIntermediateTensorInfo(a);\n  backend2.disposeIntermediateTensorInfo(b);\n  backend2.disposeIntermediateTensorInfo(sumExp);\n  backend2.disposeIntermediateTensorInfo(sumExpReshaped);\n  return res;\n}\nvar softmaxConfig2 = {\n  kernelName: Softmax,\n  backendName: \"webgl\",\n  kernelFunc: softmax4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Multinomial.js\nfunction multinomial3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { logits } = inputs;\n  const { numSamples, seed, normalized } = attrs;\n  const probs = normalized ? logits : softmax4({ inputs: { logits }, backend: backend2, attrs: { dim: logits.shape.length - 1 } });\n  const batchSize = probs.shape[0];\n  const numOutcomes = probs.shape[1];\n  const program = new MultinomialProgram(batchSize, numOutcomes, numSamples);\n  const customValues = [[seed]];\n  const res = backend2.runWebGLProgram(program, [probs], \"int32\", customValues);\n  if (!normalized) {\n    backend2.disposeIntermediateTensorInfo(probs);\n  }\n  return res;\n}\nvar multinomialConfig2 = {\n  kernelName: Multinomial,\n  backendName: \"webgl\",\n  kernelFunc: multinomial3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Neg.js\nvar NEG = CHECK_NAN_SNIPPET + `\n  return -x;\n`;\nvar NEG_PACKED = `\n  vec4 result = -x;\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n`;\nfunction neg3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (backend2.shouldExecuteOnCPU([x])) {\n    const xData = backend2.texData.get(x.dataId);\n    const [outValues, newShape] = negImplCPU(xData.values, x.shape, x.dtype);\n    return backend2.makeTensorInfo(newShape, x.dtype, outValues);\n  }\n  let program;\n  if (env().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\")) {\n    program = new UnaryOpPackedProgram(x.shape, NEG_PACKED);\n  } else {\n    program = new UnaryOpProgram(x.shape, NEG);\n  }\n  return backend2.runWebGLProgram(program, [x], x.dtype);\n}\nvar negConfig2 = {\n  kernelName: Neg,\n  backendName: \"webgl\",\n  kernelFunc: neg3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/NonMaxSuppressionV3.js\nvar nonMaxSuppressionV3Impl3 = kernel_impls_exports.nonMaxSuppressionV3Impl;\nfunction nonMaxSuppressionV32(args) {\n  backend_util_exports.warn(\"tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead\");\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold } = attrs;\n  const boxesVals = backend2.readSync(boxes.dataId);\n  const scoresVals = backend2.readSync(scores.dataId);\n  const { selectedIndices } = nonMaxSuppressionV3Impl3(boxesVals, scoresVals, maxOutputSize, iouThreshold, scoreThreshold);\n  return backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices));\n}\nvar nonMaxSuppressionV3Config2 = {\n  kernelName: NonMaxSuppressionV3,\n  backendName: \"webgl\",\n  kernelFunc: nonMaxSuppressionV32\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/NonMaxSuppressionV4.js\nvar nonMaxSuppressionV4Impl3 = kernel_impls_exports.nonMaxSuppressionV4Impl;\nfunction nonMaxSuppressionV42(args) {\n  backend_util_exports.warn(\"tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead\");\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize } = attrs;\n  const boxesVals = backend2.readSync(boxes.dataId);\n  const scoresVals = backend2.readSync(scores.dataId);\n  const { selectedIndices, validOutputs } = nonMaxSuppressionV4Impl3(boxesVals, scoresVals, maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize);\n  return [\n    backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices)),\n    backend2.makeTensorInfo([], \"int32\", new Int32Array([validOutputs]))\n  ];\n}\nvar nonMaxSuppressionV4Config2 = {\n  kernelName: NonMaxSuppressionV4,\n  backendName: \"webgl\",\n  kernelFunc: nonMaxSuppressionV42\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/NonMaxSuppressionV5.js\nvar nonMaxSuppressionV5Impl3 = kernel_impls_exports.nonMaxSuppressionV5Impl;\nfunction nonMaxSuppressionV52(args) {\n  backend_util_exports.warn(\"tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead\");\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma } = attrs;\n  const boxesVals = backend2.readSync(boxes.dataId);\n  const scoresVals = backend2.readSync(scores.dataId);\n  const maxOutputSizeVal = maxOutputSize;\n  const iouThresholdVal = iouThreshold;\n  const scoreThresholdVal = scoreThreshold;\n  const softNmsSigmaVal = softNmsSigma;\n  const { selectedIndices, selectedScores } = nonMaxSuppressionV5Impl3(boxesVals, scoresVals, maxOutputSizeVal, iouThresholdVal, scoreThresholdVal, softNmsSigmaVal);\n  return [\n    backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices)),\n    backend2.makeTensorInfo([selectedScores.length], \"float32\", new Float32Array(selectedScores))\n  ];\n}\nvar nonMaxSuppressionV5Config2 = {\n  kernelName: NonMaxSuppressionV5,\n  backendName: \"webgl\",\n  kernelFunc: nonMaxSuppressionV52\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/onehot_gpu.js\nvar OneHotProgram = class {\n  constructor(numIndices, depth, onValue, offValue) {\n    this.variableNames = [\"indices\"];\n    this.outputShape = [numIndices, depth];\n    this.userCode = `\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int index = round(getIndices(coords.x));\n        setOutput(mix(float(${offValue}), float(${onValue}),\n                      float(index == coords.y)));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/OneHot.js\nvar oneHot3 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { indices } = inputs;\n  const { depth, onValue, offValue } = attrs;\n  const indicesSize = util_exports.sizeFromShape(indices.shape);\n  const program = new OneHotProgram(indicesSize, depth, onValue, offValue);\n  const reshaped = reshape4({ inputs: { x: indices }, backend: backend2, attrs: { shape: [indicesSize] } });\n  const result = backend2.runWebGLProgram(program, [reshaped], indices.dtype);\n  backend2.disposeIntermediateTensorInfo(reshaped);\n  const outShape = [...indices.shape, depth];\n  const out = reshape4({ inputs: { x: result }, backend: backend2, attrs: { shape: outShape } });\n  backend2.disposeIntermediateTensorInfo(result);\n  return out;\n};\nvar oneHotConfig2 = {\n  kernelName: OneHot,\n  backendName: \"webgl\",\n  kernelFunc: oneHot3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ZerosLike.js\nfunction zerosLike3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (x.dtype === \"complex64\") {\n    const realPart = real3({ inputs: { input: x }, backend: backend2 });\n    const r2 = zerosLike3({ inputs: { x: realPart }, backend: backend2 });\n    const imagPart = imag3({ inputs: { input: x }, backend: backend2 });\n    const i2 = zerosLike3({ inputs: { x: imagPart }, backend: backend2 });\n    const result = complex3({ inputs: { real: r2, imag: i2 }, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(realPart);\n    backend2.disposeIntermediateTensorInfo(r2);\n    backend2.disposeIntermediateTensorInfo(imagPart);\n    backend2.disposeIntermediateTensorInfo(i2);\n    return result;\n  } else {\n    return fill3({\n      attrs: {\n        shape: x.shape,\n        dtype: x.dtype,\n        value: x.dtype === \"string\" ? \"\" : 0\n      },\n      backend: backend2\n    });\n  }\n}\nvar zerosLikeConfig2 = {\n  kernelName: ZerosLike,\n  backendName: \"webgl\",\n  kernelFunc: zerosLike3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/OnesLike.js\nfunction onesLike3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (x.dtype === \"string\") {\n    throw new Error(\"onesLike is not supported under string dtype\");\n  } else if (x.dtype === \"complex64\") {\n    const realPart = real3({ inputs: { input: x }, backend: backend2 });\n    const r2 = onesLike3({ inputs: { x: realPart }, backend: backend2 });\n    const imagPart = imag3({ inputs: { input: x }, backend: backend2 });\n    const i2 = zerosLike3({ inputs: { x: imagPart }, backend: backend2 });\n    const result = complex3({ inputs: { real: r2, imag: i2 }, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(realPart);\n    backend2.disposeIntermediateTensorInfo(r2);\n    backend2.disposeIntermediateTensorInfo(imagPart);\n    backend2.disposeIntermediateTensorInfo(i2);\n    return result;\n  } else {\n    return fill3({ attrs: { shape: x.shape, dtype: x.dtype, value: 1 }, backend: backend2 });\n  }\n}\nvar onesLikeConfig2 = {\n  kernelName: OnesLike,\n  backendName: \"webgl\",\n  kernelFunc: onesLike3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Pack.js\nfunction pack2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { axis } = attrs;\n  if (inputs.length === 1) {\n    return expandDims4({ inputs: { input: inputs[0] }, backend: backend2, attrs: { dim: axis } });\n  }\n  const shape = inputs[0].shape;\n  const dtype = inputs[0].dtype;\n  inputs.forEach((t2) => {\n    util_exports.assertShapesMatch(shape, t2.shape, \"All tensors passed to stack must have matching shapes\");\n    util_exports.assert(dtype === t2.dtype, () => \"All tensors passed to stack must have matching dtypes\");\n  });\n  const intermediateTensorInfos = [];\n  const expandedTensors = inputs.map((t2) => {\n    const expandedT = expandDims4({ inputs: { input: t2 }, backend: backend2, attrs: { dim: axis } });\n    intermediateTensorInfos.push(expandedT);\n    return expandedT;\n  });\n  const result = concat3({ inputs: expandedTensors, backend: backend2, attrs: { axis } });\n  intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return result;\n}\nvar packConfig2 = {\n  kernelName: Pack,\n  backendName: \"webgl\",\n  kernelFunc: pack2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/pad_gpu.js\nvar PadProgram = class {\n  constructor(xShape, paddings, constantValue) {\n    this.variableNames = [\"x\"];\n    this.customUniforms = [{ name: \"value\", type: \"float\" }];\n    this.outputShape = paddings.map((p2, i2) => p2[0] + xShape[i2] + p2[1]);\n    const rank = xShape.length;\n    const type = getCoordsDataType(rank);\n    const start = paddings.map((p2) => p2[0]).join(\",\");\n    const end = paddings.map((p2, i2) => p2[0] + xShape[i2]).join(\",\");\n    const unpackedCoords = [\"coords[0]\", \"coords[1]\", \"coords[2]\", \"coords[3]\"].slice(0, rank);\n    if (rank === 1) {\n      this.userCode = `\n        int start = ${start};\n        int end = ${end};\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start || outC >= end) {\n            setOutput(value);\n          } else {\n            setOutput(getX(outC - start));\n          }\n        }\n      `;\n      return;\n    }\n    this.userCode = `\n      ${type} start = ${type}(${start});\n      ${type} end = ${type}(${end});\n\n      void main() {\n        ${type} outC = getOutputCoords();\n        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\n          setOutput(value);\n        } else {\n          ${type} coords = outC - start;\n          setOutput(getX(${unpackedCoords}));\n        }\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/pad_packed_gpu.js\nvar PadPackedProgram = class {\n  constructor(xShape, paddings, constantValue) {\n    this.variableNames = [\"x\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.customUniforms = [{ name: \"value\", type: \"float\" }];\n    this.outputShape = paddings.map((p2, i2) => p2[0] + xShape[i2] + p2[1]);\n    const rank = xShape.length;\n    const dtype = getCoordsDataType(rank);\n    const start = paddings.map((p2) => p2[0]).join(\",\");\n    const end = paddings.map((p2, i2) => p2[0] + xShape[i2]).join(\",\");\n    const coords3 = getChannels(\"rc\", rank);\n    const source = getChannels(\"source\", rank);\n    const cLimit = `${coords3[rank - 1]} < ${this.outputShape[rank - 1]}`;\n    const innerDims = rank === 1 ? \"source\" : `vec2(${source.slice(-2).join()})`;\n    const componentSetup = [\n      `${dtype} rc = outputLoc;`,\n      `${coords3[rank - 1]} += 1;\n       if(${cLimit}) {\n      `,\n      rank === 1 ? \"\" : `}\n       rc = outputLoc;\n       ${coords3[rank - 2]} += 1;\n       if(${coords3[rank - 2]} < ${this.outputShape[rank - 2]}) {`,\n      rank === 1 ? \"\" : `  ${coords3[rank - 1]} += 1;\n         if(${cLimit}) {`\n    ];\n    const paddingArea = rank === 1 ? \"rc < start || rc >= end\" : \"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))\";\n    let mainLoop = \"\";\n    for (let i2 = 0, j = rank === 1 ? 2 : 4; i2 < j; i2++) {\n      mainLoop += `\n        ${componentSetup[i2]}\n        if (${paddingArea}) {\n          result[${i2}] = float(value);\n        } else {\n          ${dtype} source = rc - start;\n          result[${i2}] = getChannel(getX(${source.join()}), ${innerDims});\n        }\n      `;\n    }\n    mainLoop += rank === 1 ? `} ` : `}}`;\n    this.userCode = `\n      const ${dtype} start = ${dtype}(${start});\n      const ${dtype} end = ${dtype}(${end});\n\n      void main() {\n        ${dtype} outputLoc = getOutputCoords();\n        vec4 result = vec4(0.);\n        ${mainLoop}\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/PadV2.js\nvar padV22 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { paddings, constantValue } = attrs;\n  if (util_exports.sizeFromShape(x.shape) === 0) {\n    const outputShape = paddings.map((p2, i2) => p2[0] + x.shape[i2] + p2[1]);\n    return fill3({\n      backend: backend2,\n      attrs: { shape: outputShape, value: constantValue, dtype: x.dtype }\n    });\n  }\n  const program = env().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\") ? new PadPackedProgram(x.shape, paddings, constantValue) : new PadProgram(x.shape, paddings, constantValue);\n  const customValues = [[constantValue]];\n  return backend2.runWebGLProgram(program, [x], x.dtype, customValues);\n};\nvar padV2Config2 = {\n  kernelName: PadV2,\n  backendName: \"webgl\",\n  kernelFunc: padV22\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Pow.js\nvar POW = `\n  if(a < 0.0 && floor(b) < b){\n    return NAN;\n  }\n  if (b == 0.0) {\n    return 1.0;\n  }\n  return (round(mod(b, 2.0)) != 1) ?\n      pow(abs(a), b) : sign(a) * pow(abs(a), b);\n`;\nvar POW_PACKED = `\n  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.\n  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));\n  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);\n  vec4 result = multiplier * pow(abs(a), b);\n\n  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\n  bvec4 isExpZero = equal(b, vec4(0.0));\n  result.r = isExpZero.r ? 1.0 : result.r;\n  result.g = isExpZero.g ? 1.0 : result.g;\n  result.b = isExpZero.b ? 1.0 : result.b;\n  result.a = isExpZero.a ? 1.0 : result.a;\n\n  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));\n  ` + CHECK_NAN_SNIPPET3 + `\n  return result;\n`;\nvar pow3 = binaryKernelFunc2({ opSnippet: POW, packedOpSnippet: POW_PACKED });\nvar powConfig2 = {\n  kernelName: Pow,\n  backendName: \"webgl\",\n  kernelFunc: pow3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Prod.js\nfunction prod3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  const xRank = x.shape.length;\n  const toDispose = [];\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  let permutedX = x;\n  if (permutedAxes != null) {\n    permutedX = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n    toDispose.push(permutedX);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"prod\", axes, xRank);\n  let res;\n  if (backend2.shouldExecuteOnCPU([permutedX])) {\n    const xVals = backend2.texData.get(permutedX.dataId).values;\n    const { outVals, outShape, outDtype } = prodImplCPU(permutedX.shape, permutedX.dtype, xVals, axes);\n    res = backend2.makeTensorInfo(outShape, outDtype, outVals);\n  } else {\n    const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(permutedX.shape, axes);\n    const inSize = util_exports.sizeFromShape(reduceShape);\n    const a2D = reshape4({ inputs: { x: permutedX }, backend: backend2, attrs: { shape: [-1, inSize] } });\n    const outputDType = sumOutType(x.dtype);\n    const reduced = reduce(a2D, outputDType, \"prod\", backend2);\n    res = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: outShape } });\n    toDispose.push(a2D);\n    toDispose.push(reduced);\n  }\n  if (keepDims) {\n    toDispose.push(res);\n    const newShape = backend_util_exports.expandShapeToKeepDim(res.shape, origAxes);\n    res = reshape4({ inputs: { x: res }, backend: backend2, attrs: { shape: newShape } });\n  }\n  toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return res;\n}\nvar prodConfig2 = {\n  kernelName: Prod,\n  backendName: \"webgl\",\n  kernelFunc: prod3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Range.js\nvar range4 = (args) => {\n  const { backend: backend2, attrs } = args;\n  const { start, stop, step: step5, dtype } = attrs;\n  const values = rangeImplCPU(start, stop, step5, dtype);\n  return backend2.makeTensorInfo([values.length], dtype, values);\n};\nvar rangeConfig2 = {\n  kernelName: Range,\n  backendName: \"webgl\",\n  kernelFunc: range4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Reciprocal.js\nvar RECIPROCAL = `return 1.0 / x;`;\nvar reciprocal3 = unaryKernelFunc2({ opSnippet: RECIPROCAL });\nvar reciprocalConfig2 = {\n  kernelName: Reciprocal,\n  backendName: \"webgl\",\n  kernelFunc: reciprocal3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Relu.js\nvar RELU3 = CHECK_NAN_SNIPPET + `\n  return (x < 0.0) ? 0.0 : x;\n`;\nvar RELU_PACKED = `\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n`;\nvar relu3 = unaryKernelFunc2({ opSnippet: RELU3, packedOpSnippet: RELU_PACKED });\nvar reluConfig2 = {\n  kernelName: Relu,\n  backendName: \"webgl\",\n  kernelFunc: relu3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Relu6.js\nvar RELU63 = CHECK_NAN_SNIPPET + `\n  return (x < 0.0) ? 0.0 : min(6.0, x);\n`;\nvar RELU6_PACKED = `\n  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n`;\nvar relu63 = unaryKernelFunc2({ opSnippet: RELU63, packedOpSnippet: RELU6_PACKED });\nvar relu6Config2 = {\n  kernelName: Relu6,\n  backendName: \"webgl\",\n  kernelFunc: relu63\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_bilinear_gpu.js\nvar ResizeBilinearProgram = class {\n  constructor(inputShape, newHeight, newWidth, alignCorners, halfPixelCenters) {\n    this.variableNames = [\"A\"];\n    this.outputShape = [];\n    const [batch, oldHeight, oldWidth, depth] = inputShape;\n    this.outputShape = [batch, newHeight, newWidth, depth];\n    const effectiveInSize = [\n      alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,\n      alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth\n    ];\n    const effectiveOutSize = [\n      alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,\n      alignCorners && newWidth > 1 ? newWidth - 1 : newWidth\n    ];\n    let sourceFracIndexRC;\n    if (halfPixelCenters) {\n      sourceFracIndexRC = `(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)`;\n    } else {\n      sourceFracIndexRC = `vec2(yRC) * effectiveInputOverOutputRatioRC`;\n    }\n    this.userCode = `\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          ${effectiveInSize[0] / effectiveOutSize[0]},\n          ${effectiveInSize[1] / effectiveOutSize[1]});\n      const vec2 inputShapeRC = vec2(${oldHeight}.0, ${oldWidth}.0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = ${sourceFracIndexRC};\n\n        // Compute the four integer indices.\n        ivec2 sourceFloorRC = ivec2(max(sourceFracIndexRC, vec2(0.0)));\n        ivec2 sourceCeilRC = ivec2(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);\n        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);\n        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);\n        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);\n\n        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);\n\n        float top = topLeft + (topRight - topLeft) * fracRC.y;\n        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\n        float newValue = top + (bottom - top) * fracRC.x;\n\n        setOutput(newValue);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_bilinear_packed_gpu.js\nvar ResizeBilinearPackedProgram = class {\n  constructor(inputShape, newHeight, newWidth, alignCorners, halfPixelCenters) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = [];\n    const [batch, oldHeight, oldWidth, depth] = inputShape;\n    this.outputShape = [batch, newHeight, newWidth, depth];\n    const effectiveInSize = [\n      alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,\n      alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth\n    ];\n    const effectiveOutSize = [\n      alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,\n      alignCorners && newWidth > 1 ? newWidth - 1 : newWidth\n    ];\n    let sourceFracIndexRC;\n    if (halfPixelCenters) {\n      sourceFracIndexRC = `(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)`;\n    } else {\n      sourceFracIndexRC = `vec3(yRC) * effectiveInputOverOutputRatioRC`;\n    }\n    this.userCode = `\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\n          ${effectiveInSize[0] / effectiveOutSize[0]},\n          ${effectiveInSize[1] / effectiveOutSize[1]},\n          ${effectiveInSize[1] / effectiveOutSize[1]});\n      const vec3 inputShapeRC = vec3(${oldHeight}.0, ${oldWidth}.0,\n                                     ${oldWidth}.0);\n\n      float getAValue(int b, int r, int c, int d) {\n        return getChannel(getA(b, r, c, d), vec2(c, d));\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        // Calculate values for next column in yRC.z.\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n        // Fractional source index.\n        vec3 sourceFracIndexRC = ${sourceFracIndexRC};\n\n        // Compute the four integer indices.\n        ivec3 sourceFloorRC = ivec3(max(sourceFracIndexRC, vec3(0.0)));\n        ivec3 sourceCeilRC = ivec3(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        // Should we calculate next column and row elements in 2x2 packed cell.\n        bool hasNextCol = d < ${depth - 1};\n        bool hasNextRow = coords.z < ${newWidth - 1};\n\n        // In parallel, construct four corners for all four components in\n        // packed 2x2 cell.\n        vec4 topLeft = vec4(\n          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 bottomLeft = vec4(\n          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 topRight = vec4(\n          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec4 bottomRight = vec4(\n          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);\n\n        vec4 top = mix(topLeft, topRight, fracRC.yyzz);\n        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);\n        vec4 newValue = mix(top, bottom, fracRC.x);\n\n        setOutput(newValue);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ResizeBilinear.js\nfunction resizeBilinear3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, halfPixelCenters, size } = attrs;\n  const [newHeight, newWidth] = size;\n  const program = env().getBool(\"WEBGL_PACK_IMAGE_OPERATIONS\") ? new ResizeBilinearPackedProgram(images.shape, newHeight, newWidth, alignCorners, halfPixelCenters) : new ResizeBilinearProgram(images.shape, newHeight, newWidth, alignCorners, halfPixelCenters);\n  return backend2.runWebGLProgram(program, [images], \"float32\");\n}\nvar resizeBilinearConfig2 = {\n  kernelName: ResizeBilinear,\n  backendName: \"webgl\",\n  kernelFunc: resizeBilinear3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_bilinear_backprop_gpu.js\nvar ResizeBilinearBackpropProgram = class {\n  constructor(dyShape, inputShape, alignCorners) {\n    this.variableNames = [\"dy\"];\n    this.outputShape = [];\n    this.outputShape = inputShape;\n    const [, xHeight, xWidth] = inputShape;\n    const [, yHeight, yWidth] = dyShape;\n    const effectiveXSize = [\n      alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,\n      alignCorners && yWidth > 1 ? xWidth - 1 : xWidth\n    ];\n    const effectiveYSize = [\n      alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,\n      alignCorners && yWidth > 1 ? yWidth - 1 : yWidth\n    ];\n    const heightScale = effectiveXSize[0] / effectiveYSize[0];\n    const widthScale = effectiveXSize[1] / effectiveYSize[1];\n    const invHeightScale = 1 / heightScale;\n    const invWidthScale = 1 / widthScale;\n    const winHeight = Math.ceil(invHeightScale) * 2 + 2;\n    const winWidth = Math.ceil(invWidthScale) * 2 + 2;\n    this.userCode = `\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float(${heightScale});\n        const float widthScale = float(${widthScale});\n\n        const float invHeightScale = float(${invHeightScale});\n        const float invWidthScale = float(${invWidthScale});\n\n        const int winHeight = int(${winHeight});\n        const int winWidth = int(${winWidth});\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(startRLerp - float(winHeight / 2));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(startCLerp - float(winWidth / 2));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= ${yHeight}) {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= ${yWidth}) {\n              continue;\n            }\n\n            float dxR = float(dyR) * heightScale;\n            int topDxRIndex = int(floor(dxR));\n            int bottomDxRIndex = int(min(ceil(dxR), ${xHeight - 1}.0));\n            float dxRLerp = dxR - float(topDxRIndex);\n            float inverseDxRLerp = 1.0 - dxRLerp;\n\n            float dxC = float(dyC) * widthScale;\n            int leftDxCIndex = int(floor(dxC));\n            int rightDxCIndex = int(min(ceil(dxC), ${xWidth - 1}.0));\n            float dxCLerp = dxC - float(leftDxCIndex);\n            float inverseDxCLerp = 1.0 - dxCLerp;\n\n            if (r == topDxRIndex && c == leftDxCIndex) {\n              // topLeft\n              accumulator +=\n                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;\n            }\n\n            if (r == topDxRIndex && c == rightDxCIndex) {\n              // topRight\n              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == leftDxCIndex) {\n              // bottomLeft\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == rightDxCIndex) {\n              // bottomRight\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ResizeBilinearGrad.js\nfunction resizeBilinearGrad2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images, dy } = inputs;\n  const { alignCorners } = attrs;\n  const program = new ResizeBilinearBackpropProgram(dy.shape, images.shape, alignCorners);\n  return backend2.runWebGLProgram(program, [dy], dy.dtype);\n}\nvar resizeBilinearGradConfig3 = {\n  kernelName: ResizeBilinearGrad,\n  backendName: \"webgl\",\n  kernelFunc: resizeBilinearGrad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_nearest_neighbor_gpu.js\nvar ResizeNearestNeighborProgram = class {\n  constructor(inputShape, newHeight, newWidth, alignCorners, halfPixelCenters) {\n    this.variableNames = [\"A\"];\n    this.outputShape = [];\n    const [batch, oldHeight, oldWidth, depth] = inputShape;\n    this.outputShape = [batch, newHeight, newWidth, depth];\n    const effectiveInSize = [\n      alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,\n      alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth\n    ];\n    const effectiveOutSize = [\n      alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,\n      alignCorners && newWidth > 1 ? newWidth - 1 : newWidth\n    ];\n    const roundBase = alignCorners ? \"0.5\" : \"0.0\";\n    let sourceFracIndexRC;\n    if (halfPixelCenters) {\n      sourceFracIndexRC = `max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))`;\n    } else {\n      sourceFracIndexRC = `vec2(yRC) * effectiveInputOverOutputRatioRC`;\n    }\n    this.userCode = `\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          ${effectiveInSize[0] / effectiveOutSize[0]},\n          ${effectiveInSize[1] / effectiveOutSize[1]});\n      const vec2 inputShapeRC = vec2(${oldHeight}.0, ${oldWidth}.0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = ${sourceFracIndexRC};\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec2 sourceNearestRC = ivec2(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${roundBase})));\n        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);\n\n        setOutput(newValue);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_nearest_neighbor_packed_gpu.js\nvar ResizeNearestNeighborPackedProgram = class {\n  constructor(inputShape, newHeight, newWidth, alignCorners, halfPixelCenters) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = [];\n    const [batch, oldHeight, oldWidth, depth] = inputShape;\n    this.outputShape = [batch, newHeight, newWidth, depth];\n    const effectiveInSize = [\n      alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,\n      alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth\n    ];\n    const effectiveOutSize = [\n      alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,\n      alignCorners && newWidth > 1 ? newWidth - 1 : newWidth\n    ];\n    const roundBase = alignCorners ? \"0.5\" : \"0.0\";\n    let sourceFracIndexRC;\n    if (halfPixelCenters) {\n      sourceFracIndexRC = `max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))`;\n    } else {\n      sourceFracIndexRC = `vec3(yRC) * effectiveInputOverOutputRatioRC`;\n    }\n    this.userCode = `\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\n          ${effectiveInSize[0] / effectiveOutSize[0]},\n          ${effectiveInSize[1] / effectiveOutSize[1]},\n          ${effectiveInSize[1] / effectiveOutSize[1]});\n      const vec3 inputShapeRC = vec3(${oldHeight}.0, ${oldWidth}.0,\n                                     ${oldWidth}.0);\n\n      float getAValue(int b, int r, int c, int d) {\n        return getChannel(getA(b, r, c, d), vec2(c, d));\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        // Calculate values for next column in yRC.z.\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n        // Fractional source index.\n        vec3 sourceFracIndexRC = ${sourceFracIndexRC};\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec3 sourceNearestRC = ivec3(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${roundBase})));\n\n        // Should we calculate next column and row elements in 2x2 packed cell.\n        bool hasNextCol = d < ${depth - 1};\n        bool hasNextRow = coords.z < ${newWidth - 1};\n\n        vec4 newValue = vec4(\n          getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),\n          hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);\n\n        setOutput(newValue);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ResizeNearestNeighbor.js\nfunction resizeNearestNeighbor3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, halfPixelCenters, size } = attrs;\n  const [newHeight, newWidth] = size;\n  const program = env().getBool(\"WEBGL_PACK_IMAGE_OPERATIONS\") ? new ResizeNearestNeighborPackedProgram(images.shape, newHeight, newWidth, alignCorners, halfPixelCenters) : new ResizeNearestNeighborProgram(images.shape, newHeight, newWidth, alignCorners, halfPixelCenters);\n  return backend2.runWebGLProgram(program, [images], images.dtype);\n}\nvar resizeNearestNeighborConfig2 = {\n  kernelName: ResizeNearestNeighbor,\n  backendName: \"webgl\",\n  kernelFunc: resizeNearestNeighbor3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_nearest_neighbor_backprop_gpu.js\nvar ResizeNearestNeigborBackpropProgram = class {\n  constructor(dyShape, inputShape, alignCorners) {\n    this.variableNames = [\"dy\"];\n    this.outputShape = [];\n    this.outputShape = inputShape;\n    const [, xHeight, xWidth] = inputShape;\n    const [, yHeight, yWidth] = dyShape;\n    const effectiveXSize = [\n      alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,\n      alignCorners && yWidth > 1 ? xWidth - 1 : xWidth\n    ];\n    const effectiveYSize = [\n      alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,\n      alignCorners && yWidth > 1 ? yWidth - 1 : yWidth\n    ];\n    const heightScale = effectiveXSize[0] / effectiveYSize[0];\n    const widthScale = effectiveXSize[1] / effectiveYSize[1];\n    const invHeightScale = 1 / heightScale;\n    const invWidthScale = 1 / widthScale;\n    const winHeight = Math.ceil(invHeightScale) * 2 + 2;\n    const winWidth = Math.ceil(invWidthScale) * 2 + 2;\n    this.userCode = `\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float(${heightScale});\n        const float widthScale = float(${widthScale});\n\n        const float invHeightScale = float(${invHeightScale});\n        const float invWidthScale = float(${invWidthScale});\n\n        const int winHeight = int(${winHeight});\n        const int winWidth = int(${winWidth});\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(floor(startRLerp - float(winHeight / 2)));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(floor(startCLerp - float(winWidth / 2)));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= ${yHeight}) {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= ${yWidth}) {\n              continue;\n            }\n\n            float sourceFracRow =\n              float(${effectiveXSize[0]}) *\n                (float(dyR) / float(${effectiveYSize[0]}));\n\n            float sourceFracCol =\n                float(${effectiveXSize[1]}) *\n                  (float(dyC) / float(${effectiveYSize[1]}));\n\n            int sourceNearestRow = int(min(\n                float(int(${xHeight}) - 1),\n                ${alignCorners} ? float(round(sourceFracRow)) :\n                                  float(floor(sourceFracRow))));\n\n            int sourceNearestCol = int(min(\n                float(int(${xWidth}) - 1),\n                ${alignCorners} ? float(round(sourceFracCol)) :\n                                  float(floor(sourceFracCol))));\n\n            if (r == sourceNearestRow && c == sourceNearestCol) {\n              accumulator += getDy(b, dyR, dyC, d);\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ResizeNearestNeighborGrad.js\nfunction resizeNearestNeighborGrad2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images, dy } = inputs;\n  const { alignCorners } = attrs;\n  const program = new ResizeNearestNeigborBackpropProgram(dy.shape, images.shape, alignCorners);\n  return backend2.runWebGLProgram(program, [dy], dy.dtype);\n}\nvar resizeNearestNeighborGradConfig3 = {\n  kernelName: ResizeNearestNeighborGrad,\n  backendName: \"webgl\",\n  kernelFunc: resizeNearestNeighborGrad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/reverse_gpu.js\nvar ReverseProgram = class {\n  constructor(xShape, axis) {\n    this.variableNames = [\"x\"];\n    const rank = xShape.length;\n    if (rank > 4) {\n      throw new Error(`WebGL backend: Reverse of rank-${rank} tensor is not yet supported`);\n    }\n    this.outputShape = xShape;\n    if (rank === 1) {\n      this.userCode = `\n        void main() {\n          int coord = getOutputCoords();\n          setOutput(getX(${xShape[0]} - coord - 1));\n        }\n      `;\n      return;\n    }\n    const getInCoord = (i2) => {\n      if (axis.indexOf(i2) !== -1 && xShape[i2] !== 1) {\n        return `${xShape[i2]} - coords[${i2}] - 1`;\n      }\n      return `coords[${i2}]`;\n    };\n    const inCoords = xShape.map((_, i2) => getInCoord(i2)).join(\",\");\n    const type = getCoordsDataType(rank);\n    this.userCode = `\n      void main() {\n        ${type} coords = getOutputCoords();\n        setOutput(getX(${inCoords}));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/reverse_packed_gpu.js\nvar ReversePackedProgram = class {\n  constructor(xShape, axis) {\n    this.variableNames = [\"x\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    const rank = xShape.length;\n    if (rank > 4) {\n      throw new Error(`WebGL backend: Reverse of rank-${rank} tensor is not yet supported`);\n    }\n    this.outputShape = xShape;\n    const channels = getChannels(\"rc\", rank);\n    const nextColumn = `${channels[rank - 1]} + 1 < ${this.outputShape[rank - 1]}`;\n    const nextRow = `${channels[rank - 2]} + 1 < ${this.outputShape[rank - 2]}`;\n    const type = getCoordsDataType(rank);\n    if (rank === 1) {\n      this.userCode = `\n        void main(){\n          int rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = getChannel(getX(${xShape[0]} - rc - 1),\n            ${xShape[0]} - rc - 1);\n          if(${nextColumn}){\n              result.g = getChannel(getX(${xShape[0]} - (rc  + 1) - 1),\n                ${xShape[0]} - (rc  + 1) - 1);\n          }\n          setOutput(result);\n        }\n      `;\n    } else {\n      this.userCode = `\n        void main() {\n          ${type} rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = ${getR(channels.slice())};\n          if(${nextColumn}){\n            result.g = ${getG(channels.slice())};\n          }\n          if(${nextRow}) {\n            result.b = ${getB(channels.slice())};\n            if(${nextColumn}) {\n              result.a = ${getA(channels.slice())};\n            }\n          }\n          setOutput(result);\n        }\n    `;\n    }\n    function getR(channels2) {\n      return getChannel(channels2);\n    }\n    function getG(channels2) {\n      channels2[rank - 1] = \"(\" + channels2[rank - 1] + ` + 1)`;\n      return getChannel(channels2);\n    }\n    function getB(channels2) {\n      channels2[rank - 2] = \"(\" + channels2[rank - 2] + ` + 1)`;\n      return getChannel(channels2);\n    }\n    function getA(channels2) {\n      channels2[rank - 1] = \"(\" + channels2[rank - 1] + ` + 1)`;\n      channels2[rank - 2] = \"(\" + channels2[rank - 2] + ` + 1)`;\n      return getChannel(channels2);\n    }\n    function getChannel(channels2) {\n      const inCoordsArray = xShape.map((_, i2) => getInCoord(i2, channels2));\n      const inCoords = inCoordsArray.join(\",\");\n      const innerDims = inCoordsArray.slice(-2).join(\",\");\n      return `getChannel(getX(${inCoords}), vec2(${innerDims}))`;\n    }\n    function getInCoord(i2, channels1) {\n      if (axis.indexOf(i2) !== -1 && xShape[i2] !== 1) {\n        return `${xShape[i2]} - ${channels1[i2]} - 1`;\n      } else {\n        return `${channels1[i2]}`;\n      }\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Reverse.js\nfunction reverse3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { dims } = attrs;\n  const xRank = x.shape.length;\n  const $dims = util_exports.parseAxisParam(dims, x.shape);\n  if (xRank === 0) {\n    return identity3({ inputs: { x }, backend: backend2 });\n  }\n  const program = env().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\") ? new ReversePackedProgram(x.shape, $dims) : new ReverseProgram(x.shape, $dims);\n  return backend2.runWebGLProgram(program, [x], x.dtype);\n}\nvar reverseConfig2 = {\n  kernelName: Reverse,\n  backendName: \"webgl\",\n  kernelFunc: reverse3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/rotate_gpu.js\nvar RotateProgram = class {\n  constructor(imageShape, fillValue) {\n    this.variableNames = [\"Image\"];\n    this.outputShape = [];\n    this.customUniforms = [{ name: \"params\", type: \"vec4\" }];\n    const imageHeight = imageShape[1];\n    const imageWidth = imageShape[2];\n    this.outputShape = imageShape;\n    let fillSnippet = \"\";\n    if (typeof fillValue === \"number\") {\n      fillSnippet = `float outputValue = ${fillValue.toFixed(2)};`;\n    } else {\n      fillSnippet = `\n        vec3 fill = vec3(${fillValue.join(\",\")});\n        float outputValue = fill[coords[3]];`;\n    }\n    this.userCode = `\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int x = coords[2];\n          int y = coords[1];\n          float coordXFloat = (float(x) - params[0]) * params[3] -\n            (float(y) - params[1]) * params[2];\n          float coordYFloat = (float(x) - params[0]) * params[2] +\n            (float(y) - params[1]) * params[3];\n          int coordX = int(round(coordXFloat + params[0]));\n          int coordY = int(round(coordYFloat + params[1]));\n          ${fillSnippet}\n          if(coordX >= 0 && coordX < ${imageWidth} && coordY >= 0 && coordY < ${imageHeight}) {\n            outputValue = getImage(coords[0], coordY, coordX, coords[3]);\n          }\n          setOutput(outputValue);\n        }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/RotateWithOffset.js\nvar rotateWithOffsetConfig2 = {\n  kernelName: RotateWithOffset,\n  backendName: \"webgl\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { image: image2 } = inputs;\n    const { radians, fillValue, center } = attrs;\n    const webglBackend = backend2;\n    const program = new RotateProgram(image2.shape, fillValue);\n    const [centerX, centerY] = backend_util_exports.getImageCenter(center, image2.shape[1], image2.shape[2]);\n    const customValues = [[centerX, centerY, Math.sin(radians), Math.cos(radians)]];\n    const output = webglBackend.runWebGLProgram(program, [image2], image2.dtype, customValues);\n    return output;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Round.js\nvar ROUND = `\n  // OpenGL ES does not support round function.\n  // The algorithm is based on banker's rounding.\n  float base = floor(x);\n  if ((x - base) < 0.5) {\n    return floor(x);\n  } else if ((x - base) > 0.5) {\n    return ceil(x);\n  } else {\n    if (mod(base, 2.0) == 0.0) {\n      return base;\n    } else {\n      return base + 1.0;\n    }\n  }\n`;\nvar round4 = unaryKernelFunc2({ opSnippet: ROUND });\nvar roundConfig2 = {\n  kernelName: Round,\n  backendName: \"webgl\",\n  kernelFunc: round4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Rsqrt.js\nvar RSQRT = `return inversesqrt(x);`;\nvar rsqrt3 = unaryKernelFunc2({ opSnippet: RSQRT, cpuKernelImpl: rsqrtImplCPU });\nvar rsqrtConfig2 = {\n  kernelName: Rsqrt,\n  backendName: \"webgl\",\n  kernelFunc: rsqrt3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/scatter_gpu.js\nvar ScatterProgram = class {\n  constructor(updateSize, sliceDim, indicesRank, updatesRank, strides, shape, summingDupeIndex = true) {\n    this.variableNames = [\"updates\", \"indices\", \"defaultValue\"];\n    this.outputShape = shape;\n    const stridesType = getCoordsDataType(strides.length);\n    const dtype = getCoordsDataType(shape.length);\n    let indicesString = \"\";\n    if (indicesRank === 1) {\n      indicesString = \"i\";\n    } else if (indicesRank === 2) {\n      indicesString = \"i, j\";\n    }\n    const indicesSnippet = `getIndices(${indicesString})`;\n    let updatesString = \"\";\n    if (updatesRank === 1) {\n      updatesString = \"i\";\n    } else if (updatesRank === 2) {\n      updatesString = \"i, coords[1]\";\n    }\n    const updatesSnippet = `getUpdates(${updatesString})`;\n    const strideString = sliceDim > 1 ? \"strides[j]\" : \"strides\";\n    this.userCode = `\n        ${stridesType} strides = ${stridesType}(${strides});\n\n        void main() {\n          ${dtype} coords = getOutputCoords();\n          float sum = 0.0;\n          bool found = false;\n          for (int i = 0; i < ${updateSize}; i++) {\n            int flattenedIndex = 0;\n            for (int j = 0; j < ${sliceDim}; j++) {\n              int index = round(${indicesSnippet});\n              flattenedIndex += index * ${strideString};\n            }\n            if (flattenedIndex == coords[0]) {\n              sum += ${updatesSnippet};\n              found = true;\n            }\n          }\n          setOutput(mix(getDefaultValue(), sum, float(found)));\n        }\n      `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ScatterNd.js\nfunction scatterNd2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { indices, updates } = inputs;\n  const { shape } = attrs;\n  const { sliceRank, numUpdates, sliceSize, strides, outputSize } = backend_util_exports.calculateShapes(updates, indices, shape);\n  const flattenShape = [outputSize / sliceSize, sliceSize];\n  if (outputSize === 0) {\n    return backend2.makeTensorInfo(shape, indices.dtype);\n  }\n  const flattenIndices = reshape4({ inputs: { x: indices }, backend: backend2, attrs: { shape: [numUpdates, sliceRank] } });\n  const flattenX = reshape4({ inputs: { x: updates }, backend: backend2, attrs: { shape: [numUpdates, sliceSize] } });\n  const defaultValue = backend2.makeTensorInfo([], \"float32\", new Float32Array([0]));\n  const program = new ScatterProgram(numUpdates, sliceRank, flattenIndices.shape.length, flattenX.shape.length, strides, flattenShape);\n  const res = backend2.runWebGLProgram(program, [flattenX, flattenIndices, defaultValue], flattenX.dtype);\n  const reshaped = reshape4({ inputs: { x: res }, backend: backend2, attrs: { shape } });\n  backend2.disposeIntermediateTensorInfo(flattenIndices);\n  backend2.disposeIntermediateTensorInfo(flattenX);\n  backend2.disposeIntermediateTensorInfo(res);\n  backend2.disposeIntermediateTensorInfo(defaultValue);\n  return reshaped;\n}\nvar scatterNdConfig2 = {\n  kernelName: ScatterNd,\n  backendName: \"webgl\",\n  kernelFunc: scatterNd2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/search_sorted_gpu.js\nvar SearchSortedProgram = class {\n  constructor(batchSize, numInputs, numValues, side) {\n    this.variableNames = [\"sortedSequence\", \"values\"];\n    this.customUniforms = [{ name: \"numInputs\", type: \"int\" }];\n    this.outputShape = [batchSize, numValues];\n    const webGL2LoopHead = \"while (left < right) {\";\n    const webGL1LoopHead = `for (int i = 0; i < ${Math.ceil(Math.log2(numInputs + 1))}; ++i) { if (left >= right) break;`;\n    const loopHead = env().getNumber(\"WEBGL_VERSION\") === 2 ? webGL2LoopHead : webGL1LoopHead;\n    const boundComparator = side === \"left\" ? \"<\" : \"<=\";\n    this.userCode = `\n       int findBound(int batch, float value) {\n         int left = 0;\n         int right = numInputs;\n         int mid;\n         ${loopHead}\n           mid = (left + right) / 2;\n           if (getSortedSequence(batch, mid) ${boundComparator} value) {\n             left = mid + 1;\n           } else {\n             right = mid;\n           }\n         }\n         return right;\n       }\n\n       void main() {\n         ivec2 coords = getOutputCoords();\n         int batch = coords[0];\n         int valueIndex = coords[1];\n\n         float value = getValues(batch, valueIndex);\n\n         setOutput(float(findBound(batch, value)));\n       }\n     `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SearchSorted.js\nfunction searchSorted3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { sortedSequence, values } = inputs;\n  const { side } = attrs;\n  const program = new SearchSortedProgram(sortedSequence.shape[0], sortedSequence.shape[1], values.shape[1], side);\n  const customValues = [[sortedSequence.shape[1]]];\n  return backend2.runWebGLProgram(program, [sortedSequence, values], \"int32\", customValues);\n}\nvar searchSortedConfig2 = {\n  kernelName: SearchSorted,\n  backendName: \"webgl\",\n  kernelFunc: searchSorted3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/select_gpu.js\nvar SelectProgram = class {\n  constructor(cRank, shape, rank) {\n    this.variableNames = [\"c\", \"a\", \"b\"];\n    this.outputShape = shape;\n    let cCoords;\n    let abCoords;\n    if (rank > 4) {\n      throw Error(`Where for rank ${rank} is not yet supported`);\n    }\n    if (rank === 1) {\n      abCoords = `resRC`;\n      cCoords = `resRC`;\n    } else {\n      const currentCoords = [\"resRC.x\", \"resRC.y\", \"resRC.z\", \"resRC.w\"];\n      const cCoordVars = [];\n      const abCoordVars = [];\n      for (let i2 = 0; i2 < shape.length; i2++) {\n        abCoordVars.push(`${currentCoords[i2]}`);\n        if (i2 < cRank) {\n          cCoordVars.push(`${currentCoords[i2]}`);\n        }\n      }\n      cCoords = cCoordVars.join();\n      abCoords = abCoordVars.join();\n    }\n    const dtype = getCoordsDataType(rank);\n    this.userCode = `\n      void main() {\n        ${dtype} resRC = getOutputCoords();\n        float cVal = getC(${cCoords});\n        if (cVal >= 1.0) {\n          setOutput(getA(${abCoords}));\n        } else {\n          setOutput(getB(${abCoords}));\n        }\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Select.js\nfunction select3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { condition, t: t2, e: e2 } = inputs;\n  const program = new SelectProgram(condition.shape.length, t2.shape, t2.shape.length);\n  return backend2.runWebGLProgram(program, [condition, t2, e2], upcastType(t2.dtype, e2.dtype));\n}\nvar selectConfig2 = {\n  kernelName: Select,\n  backendName: \"webgl\",\n  kernelFunc: select3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Selu.js\nvar SELU = `\n  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\n  // see: https://arxiv.org/abs/1706.02515\n  float scaleAlpha = ${backend_util_exports.SELU_SCALEALPHA};\n  float scale = ${backend_util_exports.SELU_SCALE};\n  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\n`;\nvar selu3 = unaryKernelFunc2({ opSnippet: SELU });\nvar seluConfig2 = {\n  kernelName: Selu,\n  backendName: \"webgl\",\n  kernelFunc: selu3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sigmoid.js\nvar SIGMOID3 = CHECK_NAN_SNIPPET_UNARY + `\n  return 1.0 / (1.0 + exp(-1.0 * x));\n`;\nvar SIGMOID_PACKED = `\n  vec4 result = 1.0 / (1.0 + exp(-1.0 * x));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n`;\nvar sigmoid3 = unaryKernelFunc2({\n  opSnippet: SIGMOID3,\n  packedOpSnippet: SIGMOID_PACKED,\n  cpuKernelImpl: sigmoidImplCPU\n});\nvar sigmoidConfig2 = {\n  kernelName: Sigmoid,\n  backendName: \"webgl\",\n  kernelFunc: sigmoid3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sign.js\nvar SIGN = `\n  if (isnan(x)) { return 0.0; }\n  return sign(x);\n`;\nvar sign3 = unaryKernelFunc2({ opSnippet: SIGN });\nvar signConfig2 = {\n  kernelName: Sign,\n  backendName: \"webgl\",\n  kernelFunc: sign3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sin.js\nvar SIN = CHECK_NAN_SNIPPET_UNARY + `\n  return sin(x);\n`;\nvar sin3 = unaryKernelFunc2({ opSnippet: SIN });\nvar sinConfig2 = {\n  kernelName: Sin,\n  backendName: \"webgl\",\n  kernelFunc: sin3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sinh.js\nvar SINH = `\n  float e2x = exp(x);\n  return (e2x - 1.0 / e2x) / 2.0;\n`;\nvar sinh3 = unaryKernelFunc2({ opSnippet: SINH });\nvar sinhConfig2 = {\n  kernelName: Sinh,\n  backendName: \"webgl\",\n  kernelFunc: sinh3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Softplus.js\nvar SOFTPLUS = `\n  float epsilon = 1.1920928955078125e-7;\n  float threshold = log(epsilon) + 2.0;\n\n  bool too_large = x > -threshold;\n  bool too_small = x < threshold;\n\n  float result;\n  float exp_x = exp(x);\n\n  if (too_large){\n    result = x;\n  }\n  else if (too_small){\n    result = exp_x;\n  }\n  else{\n    result = log(exp_x + 1.0);\n  }\n  return result;\n`;\nvar softplus3 = unaryKernelFunc2({ opSnippet: SOFTPLUS });\nvar softplusConfig2 = {\n  kernelName: Softplus,\n  backendName: \"webgl\",\n  kernelFunc: softplus3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SpaceToBatchND.js\nvar spaceToBatchND3 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, paddings } = attrs;\n  util_exports.assert(x.shape.length <= 4, () => \"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet\");\n  const prod6 = blockShape.reduce((a, b) => a * b);\n  const completePaddings = [[0, 0]];\n  completePaddings.push(...paddings);\n  for (let i2 = 1 + blockShape.length; i2 < x.shape.length; ++i2) {\n    completePaddings.push([0, 0]);\n  }\n  const toDispose = [];\n  const paddedX = padV22({\n    inputs: { x },\n    backend: backend2,\n    attrs: { paddings: completePaddings, constantValue: 0 }\n  });\n  const reshapedPaddedShape = backend_util_exports.getReshaped(paddedX.shape, blockShape, prod6, false);\n  const permutedReshapedPaddedPermutation = backend_util_exports.getPermuted(reshapedPaddedShape.length, blockShape.length, false);\n  const flattenShape = backend_util_exports.getReshapedPermuted(paddedX.shape, blockShape, prod6, false);\n  const reshapedPaddedX = reshape4({ inputs: { x: paddedX }, backend: backend2, attrs: { shape: reshapedPaddedShape } });\n  const paddedXT = transpose3({\n    inputs: { x: reshapedPaddedX },\n    backend: backend2,\n    attrs: { perm: permutedReshapedPaddedPermutation }\n  });\n  const result = reshape4({ inputs: { x: paddedXT }, backend: backend2, attrs: { shape: flattenShape } });\n  toDispose.push(paddedX);\n  toDispose.push(reshapedPaddedX);\n  toDispose.push(paddedXT);\n  toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return result;\n};\nvar spaceToBatchNDConfig2 = {\n  kernelName: SpaceToBatchND,\n  backendName: \"webgl\",\n  kernelFunc: spaceToBatchND3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SparseFillEmptyRows.js\nfunction sparseFillEmptyRows3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { indices, values, denseShape, defaultValue } = inputs;\n  if (denseShape.shape.length !== 1) {\n    throw new Error(`Dense shape must be a vector, saw:\n         ${denseShape.shape}`);\n  }\n  if (indices.shape.length !== 2) {\n    throw new Error(`Indices must be a matrix, saw:\n         ${indices.shape}`);\n  }\n  if (values.shape.length !== 1) {\n    throw new Error(`Values must be a vector, saw:\n         ${values.shape}`);\n  }\n  if (defaultValue.shape.length !== 0) {\n    throw new Error(`Default value must be a scalar, saw:\n        ${defaultValue.shape}`);\n  }\n  const $indices = backend2.readSync(indices.dataId);\n  const $values = backend2.readSync(values.dataId);\n  const $denseShape = backend2.readSync(denseShape.dataId);\n  const $defaultValue = backend2.readSync(defaultValue.dataId)[0];\n  const [outputIndices, outputIndicesShape, outputValues, emptyRowIndicator, reverseIndexMap] = sparseFillEmptyRowsImplCPU($indices, indices.shape, indices.dtype, $values, values.dtype, $denseShape, $defaultValue);\n  return [\n    backend2.makeTensorInfo(outputIndicesShape, indices.dtype, outputIndices),\n    backend2.makeTensorInfo([outputIndicesShape[0]], values.dtype, outputValues),\n    backend2.makeTensorInfo([emptyRowIndicator.length], \"bool\", new Uint8Array(emptyRowIndicator.map((value) => Number(value)))),\n    backend2.makeTensorInfo([reverseIndexMap.length], indices.dtype, new Int32Array(reverseIndexMap))\n  ];\n}\nvar sparseFillEmptyRowsConfig2 = {\n  kernelName: SparseFillEmptyRows,\n  backendName: \"webgl\",\n  kernelFunc: sparseFillEmptyRows3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SparseReshape.js\nfunction sparseReshape3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { inputIndices, inputShape, newShape } = inputs;\n  if (inputIndices.shape.length !== 2) {\n    throw new Error(`Input indices should be a matrix but received shape ${inputIndices.shape}`);\n  }\n  if (inputShape.shape.length !== 1) {\n    throw new Error(`Input shape should be a vector but received shape ${inputShape.shape}`);\n  }\n  if (newShape.shape.length !== 1) {\n    throw new Error(`Target shape should be a vector but received shape ${newShape.shape}`);\n  }\n  const $inputShape = Array.from(backend2.readSync(inputShape.dataId));\n  const $inputIndices = backend2.readSync(inputIndices.dataId);\n  const targetShape = Array.from(backend2.readSync(newShape.dataId));\n  const [newIndices, indicesShape, outputShape] = sparseReshapeImplCPU($inputIndices, inputIndices.shape, inputIndices.dtype, $inputShape, targetShape);\n  return [\n    backend2.makeTensorInfo(indicesShape, inputIndices.dtype, newIndices),\n    backend2.makeTensorInfo([outputShape.length], newShape.dtype, new Int32Array(outputShape))\n  ];\n}\nvar sparseReshapeConfig2 = {\n  kernelName: SparseReshape,\n  backendName: \"webgl\",\n  kernelFunc: sparseReshape3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SparseSegmentMean.js\nfunction sparseSegmentMean3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { data, indices, segmentIds } = inputs;\n  if (data.shape.length < 1) {\n    throw new Error(`Data should be at least 1 dimensional but received scalar`);\n  }\n  if (indices.shape.length !== 1) {\n    throw new Error(`Indices should be a vector but received shape\n              ${indices.shape}`);\n  }\n  if (segmentIds.shape.length !== 1) {\n    throw new Error(`Segment ids should be a vector but received shape\n              ${segmentIds.shape}`);\n  }\n  const $data = backend2.readSync(data.dataId);\n  const $indices = backend2.readSync(indices.dataId);\n  const $segmentIds = backend2.readSync(segmentIds.dataId);\n  const [outputData, outputDataShape] = sparseSegmentReductionImplCPU($data, data.shape, data.dtype, $indices, $segmentIds, true);\n  return backend2.makeTensorInfo(outputDataShape, data.dtype, outputData);\n}\nvar sparseSegmentMeanConfig2 = {\n  kernelName: SparseSegmentMean,\n  backendName: \"webgl\",\n  kernelFunc: sparseSegmentMean3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SparseSegmentSum.js\nfunction sparseSegmentSum3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { data, indices, segmentIds } = inputs;\n  if (data.shape.length < 1) {\n    throw new Error(`Data should be at least 1 dimensional but received scalar`);\n  }\n  if (indices.shape.length !== 1) {\n    throw new Error(`Indices should be a vector but received shape\n             ${indices.shape}`);\n  }\n  if (segmentIds.shape.length !== 1) {\n    throw new Error(`Segment ids should be a vector but received shape\n             ${segmentIds.shape}`);\n  }\n  const $data = backend2.readSync(data.dataId);\n  const $indices = backend2.readSync(indices.dataId);\n  const $segmentIds = backend2.readSync(segmentIds.dataId);\n  const [outputData, outputDataShape] = sparseSegmentReductionImplCPU($data, data.shape, data.dtype, $indices, $segmentIds);\n  return backend2.makeTensorInfo(outputDataShape, data.dtype, outputData);\n}\nvar sparseSegmentSumConfig2 = {\n  kernelName: SparseSegmentSum,\n  backendName: \"webgl\",\n  kernelFunc: sparseSegmentSum3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SparseToDense.js\nfunction sparseToDense3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { sparseIndices, sparseValues, defaultValue } = inputs;\n  const { outputShape } = attrs;\n  const { sliceRank, numUpdates, sliceSize, strides, outputSize } = backend_util_exports.calculateShapes(sparseValues, sparseIndices, outputShape);\n  const sumDupeIndices = false;\n  if (sparseValues.dtype === \"string\") {\n    const indicesBuf = backend2.bufferSync(sparseIndices);\n    const updatesBuf = backend2.bufferSync(sparseValues);\n    const $defaultValue = util_exports.decodeString(backend2.readSync(defaultValue.dataId)[0]);\n    const outBuf = scatterImplCPU(indicesBuf, updatesBuf, outputShape, outputSize, sliceSize, numUpdates, sliceRank, strides, $defaultValue, sumDupeIndices);\n    return backend2.makeTensorInfo(outputShape, outBuf.dtype, outBuf.values);\n  }\n  const program = new ScatterProgram(numUpdates, sliceRank, sparseIndices.shape.length, sparseValues.shape.length, strides, [outputSize, 1], sumDupeIndices);\n  const res = backend2.runWebGLProgram(program, [sparseValues, sparseIndices, defaultValue], sparseValues.dtype);\n  const reshaped = reshape4({ inputs: { x: res }, backend: backend2, attrs: { shape: outputShape } });\n  backend2.disposeIntermediateTensorInfo(res);\n  return reshaped;\n}\nvar sparseToDenseConfig2 = {\n  kernelName: SparseToDense,\n  backendName: \"webgl\",\n  kernelFunc: sparseToDense3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SplitV.js\nfunction splitV2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { numOrSizeSplits, axis } = attrs;\n  const $axis = util_exports.parseAxisParam(axis, x.shape)[0];\n  const splitSizes = backend_util_exports.prepareSplitSize(x, numOrSizeSplits, $axis);\n  const xRank = x.shape.length;\n  const begin = new Array(xRank).fill(0);\n  const size = x.shape.slice();\n  return splitSizes.map((s2) => {\n    const sliceSize = [...size];\n    sliceSize[$axis] = s2;\n    const sliceT = slice3({ inputs: { x }, backend: backend2, attrs: { begin, size: sliceSize } });\n    begin[$axis] += s2;\n    return sliceT;\n  });\n}\nvar splitVConfig2 = {\n  kernelName: SplitV,\n  backendName: \"webgl\",\n  kernelFunc: splitV2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sqrt.js\nvar SQRT = `return sqrt(x);`;\nvar sqrt3 = unaryKernelFunc2({ opSnippet: SQRT, packedOpSnippet: SQRT, cpuKernelImpl: sqrtImplCPU });\nvar sqrtConfig2 = {\n  kernelName: Sqrt,\n  backendName: \"webgl\",\n  kernelFunc: sqrt3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Square.js\nvar SQUARE = `return x * x;`;\nvar square3 = unaryKernelFunc2({ opSnippet: SQUARE });\nvar squareConfig2 = {\n  kernelName: Square,\n  backendName: \"webgl\",\n  kernelFunc: square3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SquaredDifference.js\nvar SQUARED_DIFFERENCE = \"return (a - b) * (a - b);\";\nvar squaredDifference3 = binaryKernelFunc2({ opSnippet: SQUARED_DIFFERENCE, packedOpSnippet: SQUARED_DIFFERENCE });\nvar squaredDifferenceConfig2 = {\n  kernelName: SquaredDifference,\n  backendName: \"webgl\",\n  kernelFunc: squaredDifference3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Step.js\nfunction step3({ inputs, attrs, backend: backend2 }) {\n  const { x } = inputs;\n  const opSnippet = CHECK_NAN_SNIPPET + `\n    return x > 0.0 ? 1.0 : float(${attrs.alpha});\n  `;\n  const program = new UnaryOpProgram(x.shape, opSnippet);\n  return backend2.runWebGLProgram(program, [x], x.dtype);\n}\nvar stepConfig2 = {\n  kernelName: Step,\n  backendName: \"webgl\",\n  kernelFunc: step3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/strided_slice_gpu.js\nvar StridedSliceProgram = class {\n  constructor(begin, strides, size) {\n    this.variableNames = [\"x\"];\n    this.outputShape = size;\n    const rank = size.length;\n    const inputDtype = getCoordsDataType(size.length);\n    const dtype = getCoordsDataType(size.length);\n    let newCoords = \"\";\n    if (rank === 1) {\n      newCoords = \"coords * strides + begin\";\n    } else {\n      let outputAxis = 0;\n      newCoords = size.map((_, i2) => {\n        outputAxis++;\n        return size.length === 1 ? `coords * strides[${i2}] + begin[${i2}]` : `coords[${outputAxis - 1}] * strides[${i2}] + begin[${i2}]`;\n      }).join(\",\");\n    }\n    this.userCode = `\n      ${inputDtype} begin = ${inputDtype}(${begin});\n      ${inputDtype} strides = ${inputDtype}(${strides});\n\n      void main() {\n        ${dtype} coords = getOutputCoords();\n        setOutput(getX(${newCoords}));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/StridedSlice.js\nfunction stridedSlice3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask } = attrs;\n  const { finalShapeSparse, finalShape, isIdentity, sliceDim0, isSimpleSlice, begin: $begin, end: $end, strides: $strides } = slice_util_exports.sliceInfo(x.shape, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask);\n  let result;\n  if (isIdentity) {\n    result = reshape4({ inputs: { x }, backend: backend2, attrs: { shape: finalShape } });\n  } else if (sliceDim0 || isSimpleSlice) {\n    util_exports.assert(x.shape.length >= 1, () => `Input must have rank at least 1, got: ${x.shape.length}`);\n    const size = slice_util_exports.computeOutShape($begin, $end, $strides);\n    const sliced = slice3({ inputs: { x }, backend: backend2, attrs: { begin: $begin, size } });\n    result = reshape4({ inputs: { x: sliced }, backend: backend2, attrs: { shape: finalShape } });\n    backend2.disposeIntermediateTensorInfo(sliced);\n  } else {\n    const shouldExecuteOnCPU = backend2.shouldExecuteOnCPU([x]);\n    if (shouldExecuteOnCPU) {\n      const values = backend2.readSync(x.dataId);\n      const xBuf = buffer(x.shape, x.dtype, values);\n      const resultValues = stridedSliceImplCPU(finalShapeSparse, xBuf, $strides, $begin);\n      result = backend2.makeTensorInfo(finalShape, x.dtype, resultValues.values);\n    } else {\n      const program = new StridedSliceProgram($begin, $strides, finalShapeSparse);\n      result = backend2.runWebGLProgram(program, [x], x.dtype);\n    }\n  }\n  const resultReshaped = reshape4({ inputs: { x: result }, backend: backend2, attrs: { shape: finalShape } });\n  backend2.disposeIntermediateTensorInfo(result);\n  return resultReshaped;\n}\nvar stridedSliceConfig2 = {\n  kernelName: StridedSlice,\n  backendName: \"webgl\",\n  kernelFunc: stridedSlice3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/StringNGrams.js\nfunction stringNGrams3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { separator, nGramWidths, leftPad, rightPad: rightPad2, padWidth, preserveShortSequences } = attrs;\n  const { data, dataSplits } = inputs;\n  const $data = backend2.readSync(data.dataId);\n  const $dataSplits = backend2.readSync(dataSplits.dataId);\n  const [nGrams, nGramsSplits] = stringNGramsImplCPU($data, $dataSplits, separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences);\n  return [\n    backend2.makeTensorInfo([nGrams.length], \"string\", nGrams),\n    backend2.makeTensorInfo(dataSplits.shape, \"int32\", nGramsSplits)\n  ];\n}\nvar stringNGramsConfig2 = {\n  kernelName: StringNGrams,\n  backendName: \"webgl\",\n  kernelFunc: stringNGrams3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/StringSplit.js\nfunction stringSplit3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { skipEmpty } = attrs;\n  const { input: input2, delimiter } = inputs;\n  if (input2.dtype !== \"string\") {\n    throw new Error(\"Input must be of datatype string\");\n  }\n  if (input2.shape.length !== 1) {\n    throw new Error(`Input must be a vector, got shape: ${input2.shape}`);\n  }\n  if (delimiter.shape.length !== 0) {\n    throw new Error(`Delimiter must be a scalar, got shape: ${delimiter.shape}`);\n  }\n  const $input = backend2.readSync(input2.dataId);\n  const $delimiter = backend2.readSync(delimiter.dataId)[0];\n  const [indices, values, shape] = stringSplitImplCPU($input, $delimiter, skipEmpty);\n  const outputSize = values.length;\n  return [\n    backend2.makeTensorInfo([outputSize, 2], \"int32\", indices),\n    backend2.makeTensorInfo([outputSize], \"string\", values),\n    backend2.makeTensorInfo([2], \"int32\", new Int32Array(shape))\n  ];\n}\nvar stringSplitConfig2 = {\n  kernelName: StringSplit,\n  backendName: \"webgl\",\n  kernelFunc: stringSplit3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/StringToHashBucketFast.js\nfunction stringToHashBucketFast3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { numBuckets } = attrs;\n  const { input: input2 } = inputs;\n  if (input2.dtype !== \"string\") {\n    throw new Error(\"Input must be of datatype string\");\n  }\n  if (numBuckets <= 0) {\n    throw new Error(`Number of buckets must be at least 1`);\n  }\n  const $input = backend2.readSync(input2.dataId);\n  const output = stringToHashBucketFastImplCPU($input, numBuckets);\n  return backend2.makeTensorInfo(input2.shape, \"int32\", output);\n}\nvar stringToHashBucketFastConfig2 = {\n  kernelName: StringToHashBucketFast,\n  backendName: \"webgl\",\n  kernelFunc: stringToHashBucketFast3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Tan.js\nvar TAN = `return tan(x);`;\nvar tan3 = unaryKernelFunc2({ opSnippet: TAN });\nvar tanConfig2 = {\n  kernelName: Tan,\n  backendName: \"webgl\",\n  kernelFunc: tan3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Tanh.js\nvar TANH = `\n  float e2x = exp(-2.0 * abs(x));\n  return sign(x) * (1.0 - e2x) / (1.0 + e2x);\n`;\nvar tanh4 = unaryKernelFunc2({ opSnippet: TANH });\nvar tanhConfig2 = {\n  kernelName: Tanh,\n  backendName: \"webgl\",\n  kernelFunc: tanh4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/tile_gpu.js\nvar TileProgram = class {\n  constructor(aShape, reps) {\n    this.variableNames = [\"A\"];\n    const outputShape = new Array(aShape.length);\n    for (let i2 = 0; i2 < outputShape.length; i2++) {\n      outputShape[i2] = aShape[i2] * reps[i2];\n    }\n    this.outputShape = outputShape;\n    this.rank = outputShape.length;\n    const dtype = getCoordsDataType(this.rank);\n    const sourceCoords = getSourceCoords3(aShape);\n    this.userCode = `\n      void main() {\n        ${dtype} resRC = getOutputCoords();\n        setOutput(getA(${sourceCoords}));\n      }\n    `;\n  }\n};\nfunction getSourceCoords3(aShape) {\n  const rank = aShape.length;\n  if (rank > 5) {\n    throw Error(`Tile for rank ${rank} is not yet supported`);\n  }\n  if (rank === 1) {\n    return `imod(resRC, ${aShape[0]})`;\n  }\n  const currentCoords = [\"resRC.x\", \"resRC.y\", \"resRC.z\", \"resRC.w\", \"resRC.u\"];\n  const sourceCoords = [];\n  for (let i2 = 0; i2 < aShape.length; i2++) {\n    sourceCoords.push(`imod(${currentCoords[i2]}, ${aShape[i2]})`);\n  }\n  return sourceCoords.join();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Tile.js\nfunction tile4(params) {\n  const { inputs, backend: backend2, attrs } = params;\n  const { x } = inputs;\n  const { reps } = attrs;\n  if (x.dtype === \"string\" || x.shape.length > 5) {\n    const data = backend2.readSync(x.dataId);\n    const value = x.dtype === \"string\" ? data.map((d) => util_exports.decodeString(d)) : data;\n    const buf = buffer(x.shape, x.dtype, value);\n    const outBuf = tileImplCPU(buf, reps);\n    return backend2.makeTensorInfo(outBuf.shape, outBuf.dtype, outBuf.values);\n  }\n  const program = new TileProgram(x.shape, reps);\n  const output = backend2.runWebGLProgram(program, [x], x.dtype);\n  return output;\n}\nvar tileConfig2 = {\n  kernelName: Tile,\n  backendName: \"webgl\",\n  kernelFunc: tile4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/top_k_gpu.js\nvar SwapProgram = class {\n  constructor(shape) {\n    this.variableNames = [\"x\", \"indices\"];\n    this.customUniforms = [\n      { name: \"n\", type: \"int\" },\n      { name: \"firstPass\", type: \"int\" },\n      { name: \"negativeInf\", type: \"float\" },\n      { name: \"dir\", type: \"int\" },\n      { name: \"inc\", type: \"int\" }\n    ];\n    this.outputShape = shape;\n    this.userCode = `\n       void main() {\n         ivec2 coords = getOutputCoords();\n         int batch = coords[0];\n         int elemIdx = coords[1];\n\n         // We compare elements pair-wise within a group of size 2 * inc.\n         // The comparing rule for each group alternates between ascending\n         // and descending. Within each group, we compare each pair at\n         // positions i and i+inc. To decide whether an element at position i\n         // is x0 or x1, we mod it by 2 * inc, if the result is smaller than\n         // inc, it is in the first half of the group, we denote it as x0,\n         // otherwise we denote it as x1.\n         // For example, as shown in the Bitonic top K paper referenced above,\n         // Figure5(a) shows that element[1] is in the\n         // second half of the group when group size is 2, but it is in the\n         // first half of the group when group size is 4.\n\n         bool isFirstInPair = imod(elemIdx, 2 * inc) < inc;\n         int i = isFirstInPair ? elemIdx : elemIdx - inc;\n\n         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));\n         int i1 = firstPass == 1 ? i + inc : int(getIndices(batch, i + inc));\n         float x0 = i0 < n ? getX(batch, i0) : negativeInf;\n         float x1 = i1 < n ? getX(batch, i1) : negativeInf;\n\n         // Denotes which direction indices are in (ascending or descending).\n         bool reverse = imod(elemIdx, 2 * dir) >= dir;\n         bool isGreater = x0 > x1 || (x0 == x1 && i1 > i0);\n         if (reverse == isGreater) { // Elements in opposite order of direction\n           int iTemp = i0;\n           i0 = i1;\n           i1 = iTemp;\n         }\n         if (isFirstInPair) {\n            setOutput(float(i0));\n         } else {\n            setOutput(float(i1));\n         }\n       }\n     `;\n  }\n};\nvar MergeProgram = class {\n  constructor(shape) {\n    this.variableNames = [\"x\", \"indices\"];\n    this.customUniforms = [\n      { name: \"n\", type: \"int\" },\n      { name: \"firstPass\", type: \"int\" },\n      { name: \"k\", type: \"int\" }\n    ];\n    this.outputShape = shape;\n    this.userCode = `\n    void main() {\n         // Takes max of indices (0, k), (1, k + 1), (2, k + 2) ...\n         ivec2 coords = getOutputCoords();\n         int batch = coords[0];\n         int elemIdx = coords[1];\n\n         // The output size is half of the previous size.\n         // If the previous sequence is | | | | _ _ _ _  | | | |  _ _ _ _ (k=4),\n         // we only need to output the indices at positions |, the indices at\n         // positions _ can be thrown away, see Figure5(b) After Phase 2\n         // (Merge phase) in the Bitonic Top K paper referenced above.\n         // For example, the paper shows we only need to output the orange bars.\n         // The output sequence should look like this | | | | | | | |.\n         // Because the sequence is halved, to map the output index back\n         // to the previous sequence to find the corresponding value,\n         // we need to double the index. When we double the index,\n         // we basically interpolate a position, so 2i looks like\n         // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k position\n         // of each 2k positions by - elemIdx % k. E.g. for output at\n         // index 4,5,6,7, we want to get the corresponding element at\n         // original index 8,9,10,11, for output at index 8,9,10,11,\n         // we want to get the corresponding element at original index\n         // 16,17,18,19, so on and so forth.\n\n         int i = elemIdx < k ? elemIdx : (elemIdx * 2 - imod(elemIdx, k));\n         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));\n         int i1 = firstPass == 1 ? i + k : int(getIndices(batch, i + k));\n\n         float x0 = getX(batch, i0);\n         float x1 = i1 < n ? getX(batch, i1) : x0;\n\n         setOutput(x0 >= x1 ? float(i0) : float(i1));\n       }\n     `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/TopK.js\nfunction disposeIntermediateTensorInfoOrNull(backend2, tensorInfo) {\n  if (tensorInfo !== null) {\n    backend2.disposeIntermediateTensorInfo(tensorInfo);\n  }\n}\nfunction roundUpToPow2(num) {\n  let pow22 = 1;\n  while (pow22 < num) {\n    pow22 *= 2;\n  }\n  return pow22;\n}\nfunction topK2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { k, sorted } = attrs;\n  const TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD = env().getNumber(\"TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD\");\n  const TOPK_K_CPU_HANDOFF_THRESHOLD = env().getNumber(\"TOPK_K_CPU_HANDOFF_THRESHOLD\");\n  const xShape = x.shape;\n  const lastDim = xShape[xShape.length - 1];\n  if (backend2.shouldExecuteOnCPU([x]) || lastDim < TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD || k > TOPK_K_CPU_HANDOFF_THRESHOLD) {\n    const xVals = backend2.readSync(x.dataId);\n    const [allTopKVals, allTopKIndices] = topKImplCPU(xVals, xShape, x.dtype, k, sorted);\n    return [\n      backend2.makeTensorInfo(allTopKVals.shape, allTopKVals.dtype, allTopKVals.values),\n      backend2.makeTensorInfo(allTopKIndices.shape, allTopKIndices.dtype, allTopKIndices.values)\n    ];\n  }\n  if (k === 0) {\n    xShape[xShape.length - 1] = 0;\n    return [\n      backend2.makeTensorInfo(xShape, x.dtype, []),\n      backend2.makeTensorInfo(xShape, \"int32\", [])\n    ];\n  }\n  if (lastDim === 1) {\n    return [\n      x,\n      fill3({ attrs: { shape: xShape, dtype: \"int32\", value: 0 }, backend: backend2 })\n    ];\n  }\n  const xtexData = backend2.texData.get(x.dataId);\n  const xIsPacked = xtexData !== null && xtexData.isPacked;\n  const xUnPacked = xIsPacked ? backend2.unpackTensor(x) : x;\n  const xSize = util_exports.sizeFromShape(xShape);\n  const batch = xSize / lastDim;\n  const x2D = reshape4({ inputs: { x: xUnPacked }, attrs: { shape: [batch, lastDim] }, backend: backend2 });\n  if (xIsPacked) {\n    disposeIntermediateTensorInfoOrNull(backend2, xUnPacked);\n  }\n  const kPow2 = roundUpToPow2(k);\n  const lastDimPow2 = roundUpToPow2(lastDim);\n  let indices = null;\n  const getInputs = () => indices === null ? [x2D, x2D] : [x2D, indices];\n  const runSwap = (dir, inc, shape) => {\n    const inputs2 = getInputs();\n    const program = new SwapProgram(shape);\n    const fistPass = indices === null ? 1 : 0;\n    const customValues = [[lastDim], [fistPass], [Number.NEGATIVE_INFINITY], [dir], [inc]];\n    const prevIndices2 = indices;\n    indices = backend2.runWebGLProgram(program, inputs2, \"int32\", customValues);\n    disposeIntermediateTensorInfoOrNull(backend2, prevIndices2);\n  };\n  for (let len = 1; len < kPow2; len *= 2) {\n    const dir = len * 2;\n    for (let inc = len; inc >= 1; inc /= 2) {\n      runSwap(dir, inc, [batch, lastDimPow2]);\n    }\n  }\n  for (let indicesSize = lastDimPow2; indicesSize > kPow2; indicesSize /= 2) {\n    const inputs2 = getInputs();\n    const mergeProgram = new MergeProgram([batch, indicesSize / 2]);\n    const firstPass = indices === null ? 1 : 0;\n    const customValues = [[lastDim], [firstPass], [kPow2]];\n    const prevIndices2 = indices;\n    indices = backend2.runWebGLProgram(mergeProgram, inputs2, \"int32\", customValues);\n    disposeIntermediateTensorInfoOrNull(backend2, prevIndices2);\n    const len = kPow2 / 2;\n    const dir = len * 2;\n    for (let inc = len; inc >= 1; inc /= 2) {\n      runSwap(dir, inc, indices.shape);\n    }\n  }\n  let prevIndices = indices;\n  indices = slice3({ inputs: { x: indices }, backend: backend2, attrs: { begin: 0, size: [batch, k] } });\n  disposeIntermediateTensorInfoOrNull(backend2, prevIndices);\n  let values = gatherV22({ inputs: { x: x2D, indices }, backend: backend2, attrs: { axis: 1, batchDims: 1 } });\n  disposeIntermediateTensorInfoOrNull(backend2, x2D);\n  const newShape = xShape.slice(0, -1);\n  newShape.push(k);\n  prevIndices = indices;\n  indices = reshape4({ inputs: { x: indices }, attrs: { shape: newShape }, backend: backend2 });\n  disposeIntermediateTensorInfoOrNull(backend2, prevIndices);\n  const prevValues = values;\n  values = reshape4({ inputs: { x: values }, attrs: { shape: newShape }, backend: backend2 });\n  disposeIntermediateTensorInfoOrNull(backend2, prevValues);\n  return [values, indices];\n}\nvar topKConfig2 = {\n  kernelName: TopK,\n  backendName: \"webgl\",\n  kernelFunc: topK2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/transform_gpu.js\nvar TransformProgram = class {\n  constructor(imageHeight, imageWidth, interpolation, fillMode, fillValue, outShape) {\n    this.variableNames = [\"Image\", \"Transforms\"];\n    this.outputShape = outShape;\n    const interpolationModeId = interpolation === \"nearest\" ? 1 : 2;\n    let fillModeId;\n    switch (fillMode) {\n      case \"constant\":\n        fillModeId = 1;\n        break;\n      case \"reflect\":\n        fillModeId = 2;\n        break;\n      case \"wrap\":\n        fillModeId = 3;\n        break;\n      case \"nearest\":\n        fillModeId = 4;\n        break;\n      default:\n        fillModeId = 1;\n        break;\n    }\n    this.userCode = `\n            float mapCoord(float outCoord, float len) {\n              float inCoord = outCoord;\n              if(${fillModeId} == 2) {\n                if (inCoord < 0.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz2 = 2.0 * len;\n                    if (inCoord < sz2) {\n                      inCoord = sz2 * float(int(float(-inCoord / sz2))) +\n                      inCoord;\n                    }\n                    inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;\n                  }\n                } else if (inCoord > len - 1.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz2 = 2.0 * len;\n                    inCoord -= sz2 * float(int(float(inCoord / sz2)));\n                    if (inCoord >= len) {\n                      inCoord = sz2 - inCoord - 1.0;\n                    }\n                  }\n                }\n                return clamp(inCoord, 0.0, len - 1.0);\n              } else if (${fillModeId} == 3) {\n                if (inCoord < 0.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz = len - 1.0;\n                    inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);\n                  }\n                } else if (inCoord > len - 1.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz = len - 1.0;\n                    inCoord -= len * float(int(float(inCoord / sz)));\n                  }\n                }\n                return clamp(inCoord, 0.0, len - 1.0);\n              } else if (${fillModeId} == 4) {\n                return clamp(outCoord, 0.0, len - 1.0);\n              } else {\n                return outCoord;\n              }\n            }\n\n            float readWithFillValue(int batch, int coordY, int coordX,\n              int channel) {\n              float outputValue;\n              if (0 <= coordY && coordY < ${imageHeight} && 0 <= coordX && coordX < ${imageWidth}) {\n                  outputValue = getImage(batch, coordY, coordX, channel);\n              } else {\n                outputValue = float(${fillValue});\n              }\n              return outputValue;\n            }\n\n            void main() {\n              ivec4 coords = getOutputCoords();\n              float outputValue;\n              int batch = coords[0];\n              int x = coords[2];\n              int y = coords[1];\n              int channel = coords[3];\n              float xf = float(x);\n              float yf = float(y);\n              float a1 = getTransforms(batch, 0);\n              float a2 = getTransforms(batch, 1);\n              float a3 = getTransforms(batch, 2);\n              float b1 = getTransforms(batch, 3);\n              float b2 = getTransforms(batch, 4);\n              float b3 = getTransforms(batch, 5);\n              float c1 = getTransforms(batch, 6);\n              float c2 = getTransforms(batch, 7);\n              float projection = c1 * xf + c2 * yf + 1.0;\n              if (projection == 0.0) {\n                outputValue = float(${fillValue});\n              } else {\n                float inX = (a1 * xf + a2 * yf + a3) / projection;\n                float inY = (b1 * xf + b2 * yf + b3) / projection;\n                float mapX = mapCoord(inX, float(${imageWidth}));\n                float mapY = mapCoord(inY, float(${imageHeight}));\n\n                if (${interpolationModeId} == 1) {\n                  int coordY = int(round(mapY));\n                  int coordX = int(round(mapX));\n                  outputValue = readWithFillValue(batch, coordY, coordX,\n                    channel);\n                } else {\n                  float yFloor = floor(mapY);\n                  float xFloor = floor(mapX);\n                  float yCeil = yFloor + 1.0;\n                  float xCeil = xFloor + 1.0;\n                  float valueYFloor = (xCeil - mapX) *\n                  readWithFillValue(batch, int(yFloor), int(xFloor), channel) +\n                  (mapX - xFloor) *\n                  readWithFillValue(batch, int(yFloor), int(xCeil), channel);\n                  float valueYCeil = (xCeil - mapX) *\n                  readWithFillValue(batch, int(yCeil), int(xFloor), channel) +\n                  (mapX - xFloor) *\n                  readWithFillValue(batch, int(yCeil), int(xCeil), channel);\n                  outputValue = (yCeil - mapY) * valueYFloor +\n                  (mapY - yFloor) * valueYCeil;\n                }\n              }\n              setOutput(outputValue);\n            }\n        `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Transform.js\nfunction transform3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { image: image2, transforms } = inputs;\n  const { interpolation, fillMode, fillValue, outputShape } = attrs;\n  const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n  const [outHeight, outWidth] = outputShape != null ? outputShape : [imageHeight, imageWidth];\n  const outShape = [\n    batch,\n    outHeight,\n    outWidth,\n    numChannels\n  ];\n  const program = new TransformProgram(imageHeight, imageWidth, interpolation, fillMode, fillValue, outShape);\n  return backend2.runWebGLProgram(program, [image2, transforms], \"float32\");\n}\nvar transformConfig2 = {\n  kernelName: Transform,\n  backendName: \"webgl\",\n  kernelFunc: transform3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Unique.js\nfunction unique4(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { axis } = attrs;\n  const { x } = inputs;\n  assertNotComplex2(x, \"unique\");\n  console.warn(\"WARNING: \", \"UI might be locked temporarily as data is being downloaded\");\n  const values = backend2.readSync(x.dataId);\n  const { outputValues, outputShape, indices } = uniqueImplCPU(values, axis, x.shape, x.dtype);\n  return [\n    backend2.makeTensorInfo(outputShape, x.dtype, outputValues),\n    backend2.makeTensorInfo([indices.length], \"int32\", indices)\n  ];\n}\nvar uniqueConfig2 = {\n  kernelName: Unique,\n  backendName: \"webgl\",\n  kernelFunc: unique4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Unpack.js\nfunction unpack2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { value } = inputs;\n  let { axis } = attrs;\n  if (axis < 0) {\n    axis += value.shape.length;\n  }\n  const x = value;\n  const xRank = x.shape.length;\n  const num = value.shape[axis];\n  const outShape = new Array(xRank - 1);\n  let outIndex = 0;\n  for (let i2 = 0; i2 < xRank; i2++) {\n    if (i2 !== axis) {\n      outShape[outIndex++] = x.shape[i2];\n    }\n  }\n  const toDispose = [];\n  const begin = new Array(xRank).fill(0);\n  const size = x.shape.slice();\n  size[axis] = 1;\n  const res = new Array(num);\n  for (let i2 = 0; i2 < res.length; i2++) {\n    begin[axis] = i2;\n    const sliced = slice3({ inputs: { x }, backend: backend2, attrs: { begin, size } });\n    const reshaped = reshape4({ inputs: { x: sliced }, backend: backend2, attrs: { shape: outShape } });\n    res[i2] = reshaped;\n    toDispose.push(sliced);\n  }\n  toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return res;\n}\nvar unpackConfig2 = {\n  kernelName: Unpack,\n  backendName: \"webgl\",\n  kernelFunc: unpack2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/segment_gpu.js\nvar SegmentOpProgram = class {\n  constructor(segOpInfo, segOpType) {\n    this.variableNames = [\"x\", \"segmentIds\"];\n    const windowSize = segOpInfo.windowSize;\n    const batchSize = segOpInfo.batchSize;\n    const inSize = segOpInfo.inSize;\n    const numSegments = segOpInfo.numSegments;\n    const outSize = numSegments * Math.ceil(inSize / windowSize);\n    this.outputShape = [batchSize, outSize];\n    const initializationValue = \"0.0\";\n    const returnValue = `sumValue`;\n    const windowSizeNearestVec4 = Math.floor(windowSize / 4) * 4;\n    const windowSizeVec4Remainder = windowSize % 4;\n    const updateSnippet = `\n        sumValue += dot(values, segFilter);\n    `;\n    let checkValueOutOfBounds = \"\";\n    if (inSize % windowSize > 0) {\n      checkValueOutOfBounds = `\n        if (inIdx < 0 || inIdx >= ${inSize}) {\n          return initializationValue;\n        }\n      `;\n    }\n    let checkSegmentIdOutOfBounds = \"\";\n    if (inSize % windowSize > 0) {\n      checkSegmentIdOutOfBounds = `\n        if (inIdx < 0 || inIdx >= ${inSize}) {\n          return -1.0;\n        }\n      `;\n    }\n    this.userCode = `\n      const float initializationValue = ${initializationValue};\n\n      float getValue(int batch, int inIdx) {\n        ${checkValueOutOfBounds}\n        return getX(batch, inIdx);\n      }\n\n      float getSegmentIdAtIndex(int inIdx) {\n        ${checkSegmentIdOutOfBounds}\n        return getSegmentIds(inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = int(floor(float(outIdx) / float(\n          ${numSegments})) * float(${windowSize}));\n        int currentSeg = int(mod(float(outIdx), float(${numSegments})));\n\n        float sumValue = 0.0;\n\n        for (int i = 0; i < ${windowSizeNearestVec4}; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0\n          );\n\n          ${updateSnippet}\n        }\n\n        int inIdx = inOffset + ${windowSizeNearestVec4};\n        if (${windowSizeVec4Remainder === 1}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            0,\n            0,\n            0\n          );\n\n          ${updateSnippet}\n        } else if (${windowSizeVec4Remainder === 2}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n              0,\n              0\n          );\n\n          ${updateSnippet}\n        } else if (${windowSizeVec4Remainder === 3}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            0\n          );\n\n          ${updateSnippet}\n        }\n        setOutput(${returnValue});\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/UnsortedSegmentSum.js\nfunction unsortedSegmentSum3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, segmentIds } = inputs;\n  const { numSegments } = attrs;\n  const xRank = x.shape.length;\n  const toDispose = [];\n  let axis = 0;\n  const permutation = backend_util_exports.getAxesPermutation([axis], xRank);\n  let permutedX = x;\n  if (permutation != null) {\n    permutedX = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutation } });\n    toDispose.push(permutedX);\n    axis = backend_util_exports.getInnerMostAxes(1, xRank)[0];\n  }\n  const outShape = backend_util_exports.segment_util.computeOutShape(permutedX.shape, axis, numSegments);\n  const inSize = util_exports.sizeFromShape([permutedX.shape[axis]]);\n  const a2D = reshape4({ inputs: { x: permutedX }, backend: backend2, attrs: { shape: [-1, inSize] } });\n  toDispose.push(a2D);\n  const outputDType = sumOutType(x.dtype);\n  const segOpCompute = (x2, segOpType, segmentIds2, dtype, numSegments2) => {\n    const batchSize = x2.shape[0];\n    const inSize2 = x2.shape[1];\n    const windowSize = backend_util_exports.segment_util.segOpComputeOptimalWindowSize(inSize2, numSegments2);\n    const segOpInfo = { windowSize, inSize: inSize2, batchSize, numSegments: numSegments2 };\n    const program = new SegmentOpProgram(segOpInfo, segOpType);\n    const output = backend2.compileAndRun(program, [x2, segmentIds2], dtype);\n    toDispose.push(output);\n    if (output.shape[1] === numSegments2) {\n      return output;\n    }\n    const rangeInfo = range4({\n      backend: backend2,\n      attrs: { start: 0, stop: numSegments2, step: 1, dtype: \"float32\" }\n    });\n    const tileInfo = tile4({\n      inputs: { x: rangeInfo },\n      backend: backend2,\n      attrs: { reps: [inSize2 / windowSize] }\n    });\n    toDispose.push(rangeInfo);\n    toDispose.push(tileInfo);\n    const result2 = segOpCompute(output, segOpType, tileInfo, dtype, numSegments2);\n    return result2;\n  };\n  const segOpResult = segOpCompute(a2D, \"unsortedSegmentSum\", segmentIds, outputDType, numSegments);\n  const reshaped = reshape4({ inputs: { x: segOpResult }, backend: backend2, attrs: { shape: outShape } });\n  let result = reshaped;\n  if (permutation != null) {\n    toDispose.push(reshaped);\n    const perm = backend_util_exports.getUndoAxesPermutation(permutation);\n    result = transpose3({ inputs: { x: result }, backend: backend2, attrs: { perm } });\n  }\n  toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return result;\n}\nvar unsortedSegmentSumConfig2 = {\n  kernelName: UnsortedSegmentSum,\n  backendName: \"webgl\",\n  kernelFunc: unsortedSegmentSum3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/register_all_kernels.js\nvar kernelConfigs2 = [\n  _fusedMatMulConfig2,\n  absConfig2,\n  acosConfig2,\n  acoshConfig2,\n  addConfig2,\n  addNConfig2,\n  allConfig2,\n  anyConfig2,\n  argMaxConfig2,\n  argMinConfig2,\n  asinConfig2,\n  asinhConfig2,\n  atanConfig2,\n  atan2Config2,\n  atanhConfig2,\n  avgPoolConfig2,\n  avgPool3DConfig2,\n  avgPool3DGradConfig3,\n  avgPoolGradConfig3,\n  batchMatMulConfig2,\n  batchNormConfig2,\n  batchToSpaceNDConfig2,\n  bincountConfig2,\n  broadcastArgsConfig2,\n  castConfig2,\n  ceilConfig2,\n  clipByValueConfig2,\n  complexConfig2,\n  complexAbsConfig2,\n  concatConfig2,\n  conv2DConfig2,\n  conv2DBackpropFilterConfig2,\n  conv2DBackpropInputConfig2,\n  conv3DConfig2,\n  conv3DBackpropFilterV2Config2,\n  conv3DBackpropInputConfig,\n  cosConfig2,\n  coshConfig2,\n  cropAndResizeConfig2,\n  cumprodConfig2,\n  cumsumConfig2,\n  denseBincountConfig2,\n  depthToSpaceConfig2,\n  depthwiseConv2dNativeConfig2,\n  depthwiseConv2dNativeBackpropFilterConfig2,\n  depthwiseConv2dNativeBackpropInputConfig2,\n  diagConfig2,\n  dilation2DConfig2,\n  einsumConfig2,\n  eluConfig2,\n  eluGradConfig3,\n  equalConfig2,\n  erfConfig2,\n  expConfig2,\n  expandDimsConfig2,\n  expm1Config2,\n  fftConfig2,\n  fillConfig2,\n  flipLeftRightConfig2,\n  floorConfig2,\n  floorDivConfig2,\n  fromPixelsConfig,\n  fusedConv2DConfig2,\n  fusedDepthwiseConv2DConfig2,\n  gatherNdConfig2,\n  gatherV2Config2,\n  greaterConfig2,\n  greaterEqualConfig2,\n  identityConfig2,\n  ifftConfig2,\n  imagConfig2,\n  isFiniteConfig2,\n  isInfConfig2,\n  isNaNConfig2,\n  leakyReluConfig2,\n  lessConfig2,\n  lessEqualConfig2,\n  linSpaceConfig2,\n  logConfig2,\n  log1pConfig2,\n  logicalAndConfig2,\n  logicalNotConfig2,\n  logicalOrConfig2,\n  LRNConfig2,\n  LRNGradConfig2,\n  maxConfig2,\n  maximumConfig2,\n  maxPoolConfig2,\n  maxPool3DConfig2,\n  maxPool3DGradConfig3,\n  maxPoolGradConfig3,\n  maxPoolWithArgmaxConfig2,\n  meanConfig2,\n  minConfig2,\n  minimumConfig2,\n  mirrorPadConfig2,\n  modConfig2,\n  multinomialConfig2,\n  multiplyConfig2,\n  negConfig2,\n  nonMaxSuppressionV3Config2,\n  nonMaxSuppressionV4Config2,\n  nonMaxSuppressionV5Config2,\n  notEqualConfig2,\n  oneHotConfig2,\n  onesLikeConfig2,\n  packConfig2,\n  padV2Config2,\n  powConfig2,\n  preluConfig2,\n  prodConfig2,\n  rangeConfig2,\n  realConfig2,\n  realDivConfig2,\n  reciprocalConfig2,\n  reluConfig2,\n  relu6Config2,\n  reshapeConfig2,\n  resizeBilinearConfig2,\n  resizeBilinearGradConfig3,\n  resizeNearestNeighborConfig2,\n  resizeNearestNeighborGradConfig3,\n  reverseConfig2,\n  rotateWithOffsetConfig2,\n  roundConfig2,\n  rsqrtConfig2,\n  scatterNdConfig2,\n  searchSortedConfig2,\n  selectConfig2,\n  seluConfig2,\n  sigmoidConfig2,\n  signConfig2,\n  sinConfig2,\n  sinhConfig2,\n  sliceConfig2,\n  softmaxConfig2,\n  softplusConfig2,\n  spaceToBatchNDConfig2,\n  sparseFillEmptyRowsConfig2,\n  sparseReshapeConfig2,\n  sparseSegmentMeanConfig2,\n  sparseSegmentSumConfig2,\n  sparseToDenseConfig2,\n  splitVConfig2,\n  sqrtConfig2,\n  squareConfig2,\n  squaredDifferenceConfig2,\n  stepConfig2,\n  stridedSliceConfig2,\n  stringNGramsConfig2,\n  stringSplitConfig2,\n  stringToHashBucketFastConfig2,\n  subConfig2,\n  sumConfig2,\n  tanConfig2,\n  tanhConfig2,\n  tileConfig2,\n  topKConfig2,\n  transformConfig2,\n  transposeConfig2,\n  uniqueConfig2,\n  unpackConfig2,\n  unsortedSegmentSumConfig2,\n  zerosLikeConfig2\n];\nfor (const kernelConfig of kernelConfigs2) {\n  registerKernel(kernelConfig);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/types.js\nvar CppDType;\n(function(CppDType2) {\n  CppDType2[CppDType2[\"float32\"] = 0] = \"float32\";\n  CppDType2[CppDType2[\"int32\"] = 1] = \"int32\";\n  CppDType2[CppDType2[\"bool\"] = 2] = \"bool\";\n  CppDType2[CppDType2[\"string\"] = 3] = \"string\";\n  CppDType2[CppDType2[\"complex64\"] = 4] = \"complex64\";\n})(CppDType || (CppDType = {}));\nvar FusableActivation;\n(function(FusableActivation2) {\n  FusableActivation2[FusableActivation2[\"linear\"] = 0] = \"linear\";\n  FusableActivation2[FusableActivation2[\"relu\"] = 1] = \"relu\";\n  FusableActivation2[FusableActivation2[\"relu6\"] = 2] = \"relu6\";\n  FusableActivation2[FusableActivation2[\"prelu\"] = 3] = \"prelu\";\n  FusableActivation2[FusableActivation2[\"leakyrelu\"] = 4] = \"leakyrelu\";\n  FusableActivation2[FusableActivation2[\"sigmoid\"] = 5] = \"sigmoid\";\n  FusableActivation2[FusableActivation2[\"elu\"] = 6] = \"elu\";\n})(FusableActivation || (FusableActivation = {}));\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/_FusedMatMul.js\nvar wasmFusedMatMul;\nfunction setup(backend2) {\n  wasmFusedMatMul = backend2.wasm.cwrap(_FusedMatMul, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction fusedBatchMatMul(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b, bias, preluActivationWeights } = inputs;\n  if (a.dtype !== \"float32\" || b.dtype !== \"float32\") {\n    throw new Error(`_FusedMatMul for non non-float32 tensors not yet supported.`);\n  }\n  const { transposeA, transposeB, activation: activation2, leakyreluAlpha } = attrs;\n  const aId = backend2.dataIdMap.get(a.dataId).id;\n  const bId = backend2.dataIdMap.get(b.dataId).id;\n  let biasId = 0;\n  if (bias != null) {\n    const biasData = backend2.dataIdMap.get(bias.dataId);\n    if (biasData.shape.length !== 1) {\n      throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${biasData.shape.length}.`);\n    }\n    biasId = biasData.id;\n  }\n  const preluActivationWeightsId = preluActivationWeights == null ? 0 : backend2.dataIdMap.get(preluActivationWeights.dataId).id;\n  const fusedActivation = FusableActivation[activation2];\n  if (fusedActivation == null) {\n    throw new Error(`${activation2} activation not yet supported for FusedConv2D in the wasm backend.`);\n  }\n  const leftDim = transposeA ? a.shape[2] : a.shape[1];\n  const rightDim = transposeB ? b.shape[1] : b.shape[2];\n  const batchDims = broadcast_util_exports.assertAndGetBroadcastShape(a.shape.slice(0, -2), b.shape.slice(0, -2));\n  const out = backend2.makeOutput([...batchDims, leftDim, rightDim], a.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const aShapeBytes = new Uint8Array(new Int32Array(a.shape).buffer);\n  const bShapeBytes = new Uint8Array(new Int32Array(b.shape).buffer);\n  wasmFusedMatMul(aId, aShapeBytes, a.shape.length, bId, bShapeBytes, b.shape.length, transposeA, transposeB, fusedActivation, biasId, preluActivationWeightsId, leakyreluAlpha || 0, outId);\n  return out;\n}\nvar _fusedMatMulConfig3 = {\n  kernelName: _FusedMatMul,\n  backendName: \"wasm\",\n  setupFunc: setup,\n  kernelFunc: fusedBatchMatMul\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/unary_kernel.js\nfunction createUnaryKernelConfig(kernelName, outType) {\n  let wasmFunc9;\n  function setupFunc3(backend2) {\n    wasmFunc9 = backend2.wasm.cwrap(kernelName, null, [\n      \"number\",\n      \"number\",\n      \"number\"\n    ]);\n  }\n  function kernelFunc3(args) {\n    const { backend: backend2, inputs: { x } } = args;\n    const xId = backend2.dataIdMap.get(x.dataId).id;\n    const out = backend2.makeOutput(x.shape, outType || x.dtype);\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    if (util_exports.sizeFromShape(out.shape) === 0) {\n      return out;\n    }\n    wasmFunc9(xId, CppDType[x.dtype], outId);\n    return out;\n  }\n  return { kernelName, backendName: \"wasm\", setupFunc: setupFunc3, kernelFunc: kernelFunc3 };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Abs.js\nvar absConfig3 = createUnaryKernelConfig(Abs);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/binary_kernel.js\nfunction createBinaryKernelConfig(kernelName, supportsFullBroadcast19, dtype) {\n  let wasmFunc9;\n  function setupFunc3(backend2) {\n    wasmFunc9 = backend2.wasm.cwrap(kernelName, null, [\n      \"number\",\n      \"array\",\n      \"number\",\n      \"number\",\n      \"array\",\n      \"number\",\n      \"number\",\n      \"number\"\n    ]);\n  }\n  function kernelFunc3(args) {\n    const { backend: backend2, inputs } = args;\n    const { a, b } = inputs;\n    const aId = backend2.dataIdMap.get(a.dataId).id;\n    const bId = backend2.dataIdMap.get(b.dataId).id;\n    const outputType = dtype != null ? dtype : a.dtype;\n    const newShape = backend_util_exports.assertAndGetBroadcastShape(a.shape, b.shape);\n    const out = backend2.makeOutput(newShape, outputType);\n    if (util_exports.sizeFromShape(newShape) === 0) {\n      return out;\n    }\n    const aShapeBytes = new Uint8Array(new Int32Array(a.shape).buffer);\n    const bShapeBytes = new Uint8Array(new Int32Array(b.shape).buffer);\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    const kernelFunc4 = () => wasmFunc9(aId, aShapeBytes, a.shape.length, bId, bShapeBytes, b.shape.length, CppDType[a.dtype], outId);\n    kernelFunc4();\n    return out;\n  }\n  return { kernelName, backendName: \"wasm\", setupFunc: setupFunc3, kernelFunc: kernelFunc3 };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Add.js\nvar supportsFullBroadcast = true;\nvar addConfig3 = createBinaryKernelConfig(Add, supportsFullBroadcast);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/AddN.js\nvar wasmFunc;\nfunction setupFunc(backend2) {\n  wasmFunc = backend2.wasm.cwrap(AddN, null, [\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction addn(args) {\n  const { inputs, backend: backend2 } = args;\n  const out = backend2.makeOutput(inputs[0].shape, inputs[0].dtype);\n  if (util_exports.sizeFromShape(out.shape) === 0) {\n    return out;\n  }\n  const inputIds = inputs.map((x) => backend2.dataIdMap.get(x.dataId).id);\n  const inputIdsBytes = new Uint8Array(new Int32Array(inputIds).buffer);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmFunc(inputIdsBytes, inputIds.length, CppDType[out.dtype], outId);\n  return out;\n}\nvar addNConfig3 = {\n  kernelName: AddN,\n  backendName: \"wasm\",\n  setupFunc,\n  kernelFunc: addn\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Identity.js\nfunction identity4(args) {\n  const { inputs: { x }, backend: backend2 } = args;\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  const inVals = backend2.typedArrayFromHeap(x);\n  const outVals = backend2.typedArrayFromHeap(out);\n  outVals.set(inVals);\n  return out;\n}\nvar identityConfig3 = {\n  kernelName: Identity,\n  backendName: \"wasm\",\n  kernelFunc: identity4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Transpose.js\nvar wasmTranspose;\nfunction setup2(backend2) {\n  wasmTranspose = backend2.wasm.cwrap(Transpose, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\"\n  ]);\n}\nfunction transpose4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const [reducedShape, perm] = removeOneSizeDims(inputs.x.shape, attrs.perm);\n  let permIsNoOp = true;\n  for (let i2 = 0; i2 < perm.length; i2++) {\n    if (perm[i2] !== i2) {\n      permIsNoOp = false;\n    }\n  }\n  const outShape = computeOutShape4(inputs.x.shape, attrs.perm);\n  const x = {\n    dataId: inputs.x.dataId,\n    shape: reducedShape,\n    dtype: inputs.x.dtype\n  };\n  if (permIsNoOp) {\n    const cloned = identity4({ inputs, backend: backend2 });\n    cloned.shape = outShape;\n    return cloned;\n  }\n  const out = backend2.makeOutput(outShape, x.dtype);\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const permBytes = new Uint8Array(new Int32Array(perm).buffer);\n  const xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);\n  wasmTranspose(xId, xShapeBytes, x.shape.length, CppDType[x.dtype], outId, permBytes, perm.length);\n  return out;\n}\nfunction computeOutShape4(inShape, perm) {\n  const outShape = new Array(inShape.length);\n  for (let i2 = 0; i2 < outShape.length; i2++) {\n    outShape[i2] = inShape[perm[i2]];\n  }\n  return outShape;\n}\nfunction removeOneSizeDims(shape, perm) {\n  const newShape = [];\n  const newPerm = [];\n  for (let i2 = 0; i2 < shape.length; ++i2) {\n    if (shape[i2] !== 1) {\n      newShape.push(shape[i2]);\n    }\n    if (shape[perm[i2]] !== 1) {\n      newPerm.push(perm[i2]);\n    }\n  }\n  for (let i2 = 0; i2 < newPerm.length; ++i2) {\n    let minValIdx = -1;\n    for (let j = 0; j < newPerm.length; ++j) {\n      if (newPerm[j] >= i2 && (minValIdx === -1 || newPerm[minValIdx] > newPerm[j])) {\n        minValIdx = j;\n      }\n    }\n    newPerm[minValIdx] = i2;\n  }\n  return [newShape, newPerm];\n}\nvar transposeConfig3 = {\n  kernelName: Transpose,\n  backendName: \"wasm\",\n  kernelFunc: transpose4,\n  setupFunc: setup2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/kernel_utils.js\nfunction permuteAxesAndTranspose(x, axis, backend2) {\n  const xShape = x.shape;\n  const xRank = x.shape.length;\n  const originalAxes = util_exports.parseAxisParam(axis, xShape);\n  let axes = originalAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  let xTransposed = null;\n  let inputWasTransposed = false;\n  if (permutedAxes != null) {\n    const newShape = new Array(xRank);\n    for (let i2 = 0; i2 < newShape.length; i2++) {\n      newShape[i2] = xShape[permutedAxes[i2]];\n    }\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n    xTransposed = transpose4({ inputs: { x }, attrs: { perm: permutedAxes }, backend: backend2 });\n    const xId = backend2.dataIdMap.get(x.dataId).id;\n    const transposedId = backend2.dataIdMap.get(xTransposed.dataId).id;\n    if (transposedId !== xId) {\n      inputWasTransposed = true;\n    }\n  }\n  return { transposed: xTransposed, originalAxes, axes, inputWasTransposed };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/All.js\nvar wasmAll;\nfunction setup3(backend2) {\n  wasmAll = backend2.wasm.cwrap(All, null, [\"number, number, number\"]);\n}\nfunction all4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { axis, keepDims } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    input2 = transposed;\n    inputId = transposedId;\n  }\n  const inputRank = input2.shape.length;\n  backend_util_exports.assertAxesAreInnerMostDims(\"all\", axes, inputRank);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const out = backend2.makeOutput(outShape, x.dtype);\n  if (util_exports.sizeFromShape(input2.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmAll(inputId, reduceSize, outId);\n  }\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(out.shape, originalAxes);\n    out.shape = newShape;\n  }\n  return out;\n}\nvar allConfig3 = {\n  kernelName: All,\n  backendName: \"wasm\",\n  setupFunc: setup3,\n  kernelFunc: all4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Any.js\nvar wasmAny;\nfunction setup4(backend2) {\n  wasmAny = backend2.wasm.cwrap(Any, null, [\"number, number, number\"]);\n}\nfunction any4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { axis, keepDims } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    input2 = transposed;\n    inputId = transposedId;\n  }\n  const inputRank = input2.shape.length;\n  backend_util_exports.assertAxesAreInnerMostDims(\"any\", axes, inputRank);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const out = backend2.makeOutput(outShape, x.dtype);\n  if (util_exports.sizeFromShape(input2.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmAny(inputId, reduceSize, outId);\n  }\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(out.shape, originalAxes);\n    out.shape = newShape;\n  }\n  return out;\n}\nvar anyConfig3 = {\n  kernelName: Any,\n  backendName: \"wasm\",\n  setupFunc: setup4,\n  kernelFunc: any4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/ArgMax.js\nvar wasmFunc2;\nfunction setup5(backend2) {\n  wasmFunc2 = backend2.wasm.cwrap(ArgMax, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction argmax(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { axis } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    if (transposedId !== xId) {\n      input2 = transposed;\n      inputId = transposedId;\n    }\n  }\n  const outShape = input2.shape.slice(0, -1);\n  const out = backend2.makeOutput(outShape, \"int32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const outerSize = util_exports.sizeFromShape(out.shape);\n  const innerSize = input2.shape[axes[0]];\n  wasmFunc2(inputId, CppDType[input2.dtype], outerSize, innerSize, outId);\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  return out;\n}\nvar argMaxConfig3 = {\n  kernelName: ArgMax,\n  backendName: \"wasm\",\n  kernelFunc: argmax,\n  setupFunc: setup5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/AvgPool.js\nvar wasmAvgPool;\nfunction setup6(backend2) {\n  wasmAvgPool = backend2.wasm.cwrap(AvgPool, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction avgPool4(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const x = inputs.x;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, 1, pad3, dimRoundingMode);\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padRight = convInfo.padInfo.right;\n  const padBottom = convInfo.padInfo.bottom;\n  const padLeft = convInfo.padInfo.left;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const channels = convInfo.inChannels;\n  if (convInfo.dataFormat !== \"channelsLast\") {\n    throw new Error(`wasm backend does not support dataFormat:'${convInfo.dataFormat}'. Please use 'channelsLast'.`);\n  }\n  if (convInfo.dilationWidth !== 1 || convInfo.dilationHeight !== 1) {\n    throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${convInfo.dilationHeight}, ${convInfo.dilationWidth}].`);\n  }\n  const out = backend2.makeOutput(convInfo.outShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmAvgPool(xId, x.shape[0], x.shape[1], x.shape[2], filterHeight, filterWidth, padTop, padRight, padBottom, padLeft, strideHeight, strideWidth, channels, outId);\n  return out;\n}\nvar avgPoolConfig3 = {\n  kernelName: AvgPool,\n  backendName: \"wasm\",\n  setupFunc: setup6,\n  kernelFunc: avgPool4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Reshape.js\nfunction reshape5(args) {\n  const { inputs, attrs } = args;\n  const { x } = inputs;\n  const { shape } = attrs;\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const $shape = util_exports.inferFromImplicitShape(shape, xSize);\n  util_exports.assert(xSize === util_exports.sizeFromShape($shape), () => `new shape: ${$shape}, old shape: ${x.shape}. New shape and old shape must have the same number of elements.`);\n  args.backend.incRef(x.dataId);\n  return { dataId: x.dataId, shape: $shape, dtype: x.dtype };\n}\nvar reshapeConfig3 = {\n  kernelName: Reshape,\n  backendName: \"wasm\",\n  kernelFunc: reshape5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/BatchMatMul.js\nvar wasmBatchMatMul;\nfunction setup7(backend2) {\n  wasmBatchMatMul = backend2.wasm.cwrap(BatchMatMul, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction batchMatMul3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b } = inputs;\n  const { transposeA, transposeB } = attrs;\n  if (a.dtype !== \"float32\" || b.dtype !== \"float32\") {\n    throw new Error(`BatchMatMul for non non-float32 tensors not yet supported.`);\n  }\n  const aRank = a.shape.length;\n  const bRank = b.shape.length;\n  const innerShapeA = transposeA ? a.shape[aRank - 2] : a.shape[aRank - 1];\n  const innerShapeB = transposeB ? b.shape[bRank - 1] : b.shape[bRank - 2];\n  const outerShapeA = transposeA ? a.shape[aRank - 1] : a.shape[aRank - 2];\n  const outerShapeB = transposeB ? b.shape[bRank - 2] : b.shape[bRank - 1];\n  const outerDimsA = a.shape.slice(0, -2);\n  const outerDimsB = b.shape.slice(0, -2);\n  const batchDimA = util_exports.sizeFromShape(outerDimsA);\n  const batchDimB = util_exports.sizeFromShape(outerDimsB);\n  const outShapeOuterDims = broadcast_util_exports.assertAndGetBroadcastShape(a.shape.slice(0, -2), b.shape.slice(0, -2));\n  const outShape = outShapeOuterDims.concat([outerShapeA, outerShapeB]);\n  util_exports.assert(innerShapeA === innerShapeB, () => `Error in matMul: inner shapes (${innerShapeA}) and (${innerShapeB}) of Tensors with shapes ${a.shape} and ${b.shape} and transposeA=${transposeA} and transposeB=${transposeB} must match.`);\n  const a3dShape = transposeA ? [batchDimA, innerShapeA, outerShapeA] : [batchDimA, outerShapeA, innerShapeA];\n  const b3dShape = transposeB ? [batchDimB, outerShapeB, innerShapeB] : [batchDimB, innerShapeB, outerShapeB];\n  const a3d = reshape5({ inputs: { x: a }, backend: backend2, attrs: { shape: a3dShape } });\n  const b3d = reshape5({ inputs: { x: b }, backend: backend2, attrs: { shape: b3dShape } });\n  const a3dId = backend2.dataIdMap.get(a3d.dataId).id;\n  const b3dId = backend2.dataIdMap.get(b3d.dataId).id;\n  const leftDim = transposeA ? a3d.shape[2] : a3d.shape[1];\n  const rightDim = transposeB ? b3d.shape[1] : b3d.shape[2];\n  const batchDim = Math.max(batchDimA, batchDimB);\n  const out = backend2.makeOutput([batchDim, leftDim, rightDim], a3d.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const aShapeBytes = new Uint8Array(new Int32Array(a3d.shape).buffer);\n  const bShapeBytes = new Uint8Array(new Int32Array(b3d.shape).buffer);\n  wasmBatchMatMul(a3dId, aShapeBytes, a3d.shape.length, b3dId, bShapeBytes, b3d.shape.length, transposeA, transposeB, outId);\n  backend2.disposeData(a3d.dataId);\n  backend2.disposeData(b3d.dataId);\n  out.shape = outShape;\n  return out;\n}\nvar batchMatMulConfig3 = {\n  kernelName: BatchMatMul,\n  backendName: \"wasm\",\n  setupFunc: setup7,\n  kernelFunc: batchMatMul3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Slice.js\nfunction slice4(args) {\n  const { inputs: { x }, attrs: { begin, size }, backend: backend2 } = args;\n  const [begin_, size_] = slice_util_exports.parseSliceParams(x, begin, size);\n  const isContinous = slice_util_exports.isSliceContinous(x.shape, begin_, size_);\n  const xVals = backend2.readSync(x.dataId);\n  const out = backend2.makeOutput(size_, x.dtype);\n  const xStrides = util_exports.computeStrides(x.shape);\n  const outData = backend2.dataIdMap.get(out.dataId);\n  if (isContinous) {\n    const flatOffset = slice_util_exports.computeFlatOffset(begin_, xStrides);\n    if (x.dtype === \"string\") {\n      outData.stringBytes = xVals.slice(flatOffset, flatOffset + util_exports.sizeFromShape(size_));\n    } else {\n      const outVals2 = backend2.typedArrayFromHeap(out);\n      outVals2.set(xVals.subarray(flatOffset, flatOffset + util_exports.sizeFromShape(size_)));\n    }\n    return out;\n  }\n  if (x.dtype === \"string\") {\n    const res = sliceImpl(xVals, begin_, size_, x.shape, x.dtype);\n    outData.stringBytes = res;\n    return out;\n  }\n  const outVals = backend2.typedArrayFromHeap(out);\n  const rank = x.shape.length;\n  if (rank === 2) {\n    slice2d2(xVals, xStrides[0], outVals, begin_, size_);\n  } else if (rank === 3) {\n    slice3d2(xVals, xStrides[0], xStrides[1], outVals, begin_, size_);\n  } else if (rank === 4) {\n    slice4d2(xVals, xStrides[0], xStrides[1], xStrides[2], outVals, begin_, size_);\n  } else {\n    const res = sliceImpl(xVals, begin_, size_, x.shape, x.dtype);\n    outVals.set(res);\n  }\n  return out;\n}\nfunction slice2d2(xVals, xStride, outVals, begin, size) {\n  let outOffset = 0;\n  const beginI = begin[0];\n  const beginJ = begin[1];\n  const endI = beginI + size[0];\n  for (let i2 = beginI; i2 < endI; i2++) {\n    const xOffset = i2 * xStride + beginJ;\n    outVals.set(xVals.subarray(xOffset, xOffset + size[1]), outOffset);\n    outOffset += size[1];\n  }\n}\nfunction slice3d2(xVals, xStride1, xStride2, outVals, begin, size) {\n  let outOffset = 0;\n  const beginI = begin[0];\n  const beginJ = begin[1];\n  const beginK = begin[2];\n  const endI = beginI + size[0];\n  const endJ = beginJ + size[1];\n  for (let i2 = beginI; i2 < endI; i2++) {\n    for (let j = beginJ; j < endJ; j++) {\n      const xOffset = i2 * xStride1 + j * xStride2 + beginK;\n      outVals.set(xVals.subarray(xOffset, xOffset + size[2]), outOffset);\n      outOffset += size[2];\n    }\n  }\n}\nfunction slice4d2(xVals, xStride1, xStride2, xStride3, outVals, begin, size) {\n  let outOffset = 0;\n  const beginI = begin[0];\n  const beginJ = begin[1];\n  const beginK = begin[2];\n  const endI = beginI + size[0];\n  const endJ = beginJ + size[1];\n  const endK = beginK + size[2];\n  const beginL = begin[3];\n  for (let i2 = beginI; i2 < endI; i2++) {\n    for (let j = beginJ; j < endJ; j++) {\n      for (let k = beginK; k < endK; k++) {\n        const xOffset = i2 * xStride1 + j * xStride2 + k * xStride3 + beginL;\n        outVals.set(xVals.subarray(xOffset, xOffset + size[3]), outOffset);\n        outOffset += size[3];\n      }\n    }\n  }\n}\nvar sliceConfig3 = {\n  kernelName: Slice,\n  backendName: \"wasm\",\n  kernelFunc: slice4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/BatchToSpaceND.js\nfunction batchToSpaceND4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, crops } = attrs;\n  const prod6 = blockShape.reduce((a, b) => a * b);\n  const reshaped = backend_util_exports.getReshaped(x.shape, blockShape, prod6);\n  const permuted = backend_util_exports.getPermuted(reshaped.length, blockShape.length);\n  const reshapedPermuted = backend_util_exports.getReshapedPermuted(x.shape, blockShape, prod6);\n  const sliceBeginCoords = backend_util_exports.getSliceBeginCoords(crops, blockShape.length);\n  const sliceSize = backend_util_exports.getSliceSize(reshapedPermuted, crops, blockShape.length);\n  const xReshaped = reshape5({ inputs: { x }, backend: backend2, attrs: { shape: reshaped } });\n  const xTransposed = transpose4({ inputs: { x: xReshaped }, backend: backend2, attrs: { perm: permuted } });\n  const xTransposedReshaped = reshape5({ inputs: { x: xTransposed }, backend: backend2, attrs: { shape: reshapedPermuted } });\n  const result = slice4({\n    inputs: { x: xTransposedReshaped },\n    backend: backend2,\n    attrs: { begin: sliceBeginCoords, size: sliceSize }\n  });\n  backend2.disposeData(xReshaped.dataId);\n  backend2.disposeData(xTransposed.dataId);\n  backend2.disposeData(xReshaped.dataId);\n  return result;\n}\nvar batchToSpaceNDConfig3 = {\n  kernelName: BatchToSpaceND,\n  backendName: \"wasm\",\n  kernelFunc: batchToSpaceND4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Cast.js\nfunction cast5(args) {\n  const { inputs: { x }, attrs: { dtype }, backend: backend2 } = args;\n  const out = backend2.makeOutput(x.shape, dtype);\n  const inVals = backend2.typedArrayFromHeap(x);\n  const outVals = backend2.typedArrayFromHeap(out);\n  outVals.set(inVals);\n  return out;\n}\nvar castConfig3 = {\n  kernelName: Cast,\n  backendName: \"wasm\",\n  kernelFunc: cast5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Ceil.js\nvar ceilConfig3 = createUnaryKernelConfig(Ceil);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/ClipByValue.js\nvar wasmClip;\nfunction setup8(backend2) {\n  wasmClip = backend2.wasm.cwrap(ClipByValue, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction clip(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { clipValueMin, clipValueMax } = attrs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmClip(xId, clipValueMin, clipValueMax, outId);\n  return out;\n}\nvar clipByValueConfig3 = {\n  kernelName: ClipByValue,\n  backendName: \"wasm\",\n  setupFunc: setup8,\n  kernelFunc: clip\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Concat.js\nfunction concat4(args) {\n  const { inputs, backend: backend2 } = args;\n  const axis = util_exports.parseAxisParam(args.attrs.axis, inputs[0].shape)[0];\n  let outShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), axis);\n  const $inputs = inputs.filter((t2) => util_exports.sizeFromShape(t2.shape) > 0);\n  if ($inputs.length === 1) {\n    return identity4({ inputs: { x: $inputs[0] }, backend: backend2 });\n  }\n  const out = backend2.makeOutput(outShape, inputs[0].dtype);\n  if (util_exports.sizeFromShape(outShape) === 0) {\n    return out;\n  }\n  const shapes = $inputs.map((t2) => t2.shape);\n  backend_util_exports.assertParamsConsistent(shapes, axis);\n  if ($inputs[0].dtype === \"string\") {\n    const inputs2D = $inputs.map((t2) => {\n      const innerSize = util_exports.sizeFromShape(t2.shape.slice(axis));\n      const shape = [-1, innerSize];\n      return reshape5({ inputs: { x: t2 }, backend: backend2, attrs: { shape } });\n    });\n    const inputsValShapes = inputs2D.map((t2) => {\n      return { vals: backend2.readSync(t2.dataId), shape: t2.shape };\n    });\n    outShape = backend_util_exports.computeOutShape(inputs2D.map((t2) => t2.shape), 1);\n    const simplyConcat = inputs2D[0].shape[0] === 1;\n    const outVals2 = concatImpl(inputsValShapes, outShape, inputs[0].dtype, simplyConcat);\n    const finalOutShape = backend_util_exports.computeOutShape($inputs.map((t2) => t2.shape), axis);\n    out.shape = finalOutShape;\n    const outData = backend2.dataIdMap.get(out.dataId);\n    outData.stringBytes = backend_util_exports.fromStringArrayToUint8(outVals2);\n    inputs2D.forEach((t2) => backend2.disposeData(t2.dataId));\n    return out;\n  }\n  const batchDim = util_exports.sizeFromShape($inputs[0].shape.slice(0, axis));\n  let sumInnerDims = 0;\n  const innerDims = $inputs.map((input2) => {\n    const innerDim = util_exports.sizeFromShape(input2.shape.slice(axis));\n    sumInnerDims += innerDim;\n    return innerDim;\n  });\n  const inVals = $inputs.map((input2) => backend2.typedArrayFromHeap(input2));\n  const outVals = backend2.typedArrayFromHeap(out);\n  for (let b = 0; b < batchDim; b++) {\n    let outOffset = b * sumInnerDims;\n    for (let i2 = 0; i2 < inVals.length; i2++) {\n      const innerDim = innerDims[i2];\n      const inOffset = b * innerDim;\n      const vals = inVals[i2].subarray(inOffset, inOffset + innerDim);\n      outVals.set(vals, outOffset);\n      outOffset += innerDim;\n    }\n  }\n  return out;\n}\nvar concatConfig3 = {\n  kernelName: Concat,\n  backendName: \"wasm\",\n  kernelFunc: concat4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Conv2D.js\nvar wasmConv2d;\nfunction setup9(backend2) {\n  wasmConv2d = backend2.wasm.cwrap(Conv2D, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction conv2d5(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { x, filter } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const filterId = backend2.dataIdMap.get(filter.dataId).id;\n  const { strides, dilations, pad: pad3, dimRoundingMode, dataFormat } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode, false, $dataFormat);\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padRight = convInfo.padInfo.right;\n  const padBottom = convInfo.padInfo.bottom;\n  const padLeft = convInfo.padInfo.left;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const inputChannels = convInfo.inChannels;\n  const outputChannels = convInfo.outChannels;\n  const isSamePad = convInfo.padInfo.type === \"SAME\" ? 1 : 0;\n  if (convInfo.dataFormat !== \"channelsLast\") {\n    throw new Error(`wasm backend Conv2D does not support dataFormat:'${convInfo.dataFormat}'. Please use 'channelsLast'.`);\n  }\n  const out = backend2.makeOutput(convInfo.outShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmConv2d(xId, x.shape[0], x.shape[1], x.shape[2], filterId, filterHeight, filterWidth, padTop, padRight, padBottom, padLeft, isSamePad, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, outId);\n  return out;\n}\nvar conv2DConfig3 = {\n  kernelName: Conv2D,\n  backendName: \"wasm\",\n  setupFunc: setup9,\n  kernelFunc: conv2d5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Conv2DBackpropInput.js\nvar wasmConv2DBackpropInput;\nfunction setup10(backend2) {\n  wasmConv2DBackpropInput = backend2.wasm.cwrap(Conv2DBackpropInput, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction conv2DBackpropInput4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { dy, filter } = inputs;\n  const { strides, pad: pad3, dataFormat, dimRoundingMode, inputShape } = attrs;\n  const dilations = 1;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(inputShape, filter.shape, strides, dilations, pad3, dimRoundingMode, false, $dataFormat);\n  const { batchSize, filterHeight, filterWidth, inChannels, inHeight, inWidth, outChannels, outHeight, outWidth, strideHeight, strideWidth } = convInfo;\n  const topPad = filterHeight - 1 - convInfo.padInfo.top;\n  const leftPad = filterWidth - 1 - convInfo.padInfo.left;\n  const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n  const dxStrides = util_exports.computeStrides(convInfo.inShape);\n  const dyStrides = util_exports.computeStrides(dy.shape);\n  const [fltS0, fltS1, fltS2] = util_exports.computeStrides(filter.shape);\n  const xBatchStride = dxStrides[0];\n  const xRowStride = isChannelsLast ? dxStrides[1] : dxStrides[2];\n  const xColStride = isChannelsLast ? dxStrides[2] : 1;\n  const xChannelStride = isChannelsLast ? 1 : dxStrides[1];\n  const yBatchStride = dyStrides[0];\n  const yRowStride = isChannelsLast ? dyStrides[1] : dyStrides[2];\n  const yColStride = isChannelsLast ? dyStrides[2] : 1;\n  const yChannelStride = isChannelsLast ? 1 : dyStrides[1];\n  const out = backend2.makeOutput(convInfo.inShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const dyId = backend2.dataIdMap.get(dy.dataId).id;\n  const filterId = backend2.dataIdMap.get(filter.dataId).id;\n  wasmConv2DBackpropInput(dyId, filterId, batchSize, filterHeight, filterWidth, inHeight, inWidth, inChannels, outHeight, outWidth, outChannels, strideHeight, strideWidth, topPad, leftPad, fltS0, fltS1, fltS2, xBatchStride, xRowStride, xColStride, xChannelStride, yBatchStride, yRowStride, yColStride, yChannelStride, outId);\n  return out;\n}\nvar conv2DBackpropInputConfig3 = {\n  kernelName: Conv2DBackpropInput,\n  backendName: \"wasm\",\n  setupFunc: setup10,\n  kernelFunc: conv2DBackpropInput4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Cos.js\nvar cosConfig3 = createUnaryKernelConfig(Cos);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Cosh.js\nvar coshConfig3 = createUnaryKernelConfig(Cosh);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/CropAndResize.js\nvar InterpolationMethod;\n(function(InterpolationMethod2) {\n  InterpolationMethod2[InterpolationMethod2[\"bilinear\"] = 0] = \"bilinear\";\n  InterpolationMethod2[InterpolationMethod2[\"nearest\"] = 1] = \"nearest\";\n})(InterpolationMethod || (InterpolationMethod = {}));\nvar wasmCropAndResize;\nfunction setup11(backend2) {\n  wasmCropAndResize = backend2.wasm.cwrap(CropAndResize, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction cropAndResize4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { method, extrapolationValue, cropSize } = attrs;\n  const { image: image2, boxes, boxInd } = inputs;\n  const numBoxes = boxes.shape[0];\n  const [cropHeight, cropWidth] = cropSize;\n  const outShape = [numBoxes, cropHeight, cropWidth, image2.shape[3]];\n  let imagesData = backend2.dataIdMap.get(image2.dataId);\n  let castedData;\n  if (image2.dtype !== \"float32\") {\n    castedData = cast5({ backend: backend2, inputs: { x: image2 }, attrs: { dtype: \"float32\" } });\n    imagesData = backend2.dataIdMap.get(castedData.dataId);\n  }\n  const imagesId = imagesData.id;\n  const boxesId = backend2.dataIdMap.get(boxes.dataId).id;\n  const boxIndId = backend2.dataIdMap.get(boxInd.dataId).id;\n  const out = backend2.makeOutput(outShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const imagesShapeBytes = new Uint8Array(new Int32Array(image2.shape).buffer);\n  wasmCropAndResize(imagesId, boxesId, boxIndId, numBoxes, imagesShapeBytes, cropHeight, cropWidth, InterpolationMethod[method], extrapolationValue, outId);\n  if (castedData != null) {\n    backend2.disposeData(castedData.dataId);\n  }\n  return out;\n}\nvar cropAndResizeConfig3 = {\n  kernelName: CropAndResize,\n  backendName: \"wasm\",\n  setupFunc: setup11,\n  kernelFunc: cropAndResize4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Cumprod.js\nvar wasmCumprod;\nfunction setup12(backend2) {\n  wasmCumprod = backend2.wasm.cwrap(Cumprod, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction cumprod4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  const xRank = x.shape.length;\n  util_exports.assert(x.dtype === \"float32\" || x.dtype === \"int32\", () => `cumprod does not support ${x.dtype} tensors in the WASM backend`);\n  const permutation = backend_util_exports.getAxesPermutation([axis], xRank);\n  let permutedX = x;\n  if (permutation !== null) {\n    permutedX = transpose4({ inputs: { x }, attrs: { perm: permutation }, backend: backend2 });\n  }\n  const permutedAxis = backend_util_exports.getInnerMostAxes(1, xRank)[0];\n  backend_util_exports.assertAxesAreInnerMostDims(\"cumprod\", [permutedAxis], xRank);\n  const permutedOut = backend2.makeOutput(permutedX.shape, permutedX.dtype);\n  const finalDim = permutedX.shape[permutedAxis];\n  const permutedXId = backend2.dataIdMap.get(permutedX.dataId).id;\n  const permutedOutId = backend2.dataIdMap.get(permutedOut.dataId).id;\n  wasmCumprod(permutedXId, exclusive ? 1 : 0, reverse5 ? 1 : 0, finalDim, permutedOutId, CppDType[x.dtype]);\n  let out = permutedOut;\n  if (permutation !== null) {\n    const undoPermutation = backend_util_exports.getUndoAxesPermutation(permutation);\n    out = transpose4({ inputs: { x: permutedOut }, attrs: { perm: undoPermutation }, backend: backend2 });\n    backend2.disposeData(permutedX.dataId);\n    backend2.disposeData(permutedOut.dataId);\n  }\n  return out;\n}\nvar cumprodConfig3 = {\n  kernelName: Cumprod,\n  backendName: \"wasm\",\n  setupFunc: setup12,\n  kernelFunc: cumprod4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Cumsum.js\nvar wasmCumsum;\nfunction setup13(backend2) {\n  wasmCumsum = backend2.wasm.cwrap(Cumsum, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction cumsum4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  const xRank = x.shape.length;\n  util_exports.assert(x.dtype === \"float32\" || x.dtype === \"int32\", () => `cumsum does not support ${x.dtype} tensors in the WASM backend`);\n  const permutation = backend_util_exports.getAxesPermutation([axis], xRank);\n  let permutedX = x;\n  if (permutation !== null) {\n    permutedX = transpose4({ inputs: { x }, attrs: { perm: permutation }, backend: backend2 });\n  }\n  const permutedAxis = backend_util_exports.getInnerMostAxes(1, xRank)[0];\n  backend_util_exports.assertAxesAreInnerMostDims(\"cumsum\", [permutedAxis], xRank);\n  const permutedOut = backend2.makeOutput(permutedX.shape, permutedX.dtype);\n  const finalDim = permutedX.shape[permutedAxis];\n  const permutedXId = backend2.dataIdMap.get(permutedX.dataId).id;\n  const permutedOutId = backend2.dataIdMap.get(permutedOut.dataId).id;\n  wasmCumsum(permutedXId, exclusive ? 1 : 0, reverse5 ? 1 : 0, finalDim, permutedOutId, CppDType[x.dtype]);\n  let out = permutedOut;\n  if (permutation !== null) {\n    const undoPermutation = backend_util_exports.getUndoAxesPermutation(permutation);\n    out = transpose4({ inputs: { x: permutedOut }, attrs: { perm: undoPermutation }, backend: backend2 });\n    backend2.disposeData(permutedX.dataId);\n    backend2.disposeData(permutedOut.dataId);\n  }\n  return out;\n}\nvar cumsumConfig3 = {\n  kernelName: Cumsum,\n  backendName: \"wasm\",\n  setupFunc: setup13,\n  kernelFunc: cumsum4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/DepthToSpace.js\nvar wasmDepthToSpace;\nfunction setup14(backend2) {\n  wasmDepthToSpace = backend2.wasm.cwrap(DepthToSpace, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"array\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction depthToSpace4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { x } = inputs;\n  const { blockSize, dataFormat } = attrs;\n  const batchSize = x.shape[0];\n  const inputHeight = dataFormat === \"NHWC\" ? x.shape[1] : x.shape[2];\n  const inputWidth = dataFormat === \"NHWC\" ? x.shape[2] : x.shape[3];\n  const inputDepth = dataFormat === \"NHWC\" ? x.shape[3] : x.shape[1];\n  const outputHeight = inputHeight * blockSize;\n  const outputWidth = inputWidth * blockSize;\n  const outputDepth = inputDepth / (blockSize * blockSize);\n  const outputShape = dataFormat === \"NHWC\" ? [batchSize, outputHeight, outputWidth, outputDepth] : [batchSize, outputDepth, outputHeight, outputWidth];\n  const out = backend2.makeOutput(outputShape, \"float32\");\n  const xData = backend2.dataIdMap.get(x.dataId);\n  const xId = xData.id;\n  const xStridesBytes = new Uint8Array(new Int32Array(util_exports.computeStrides(x.shape)).buffer);\n  const outputShapeBytes = new Uint8Array(new Int32Array(outputShape).buffer);\n  const outStridesBytes = new Uint8Array(new Int32Array(util_exports.computeStrides(outputShape)).buffer);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const channelsLast = dataFormat === \"NHWC\" ? 1 : 0;\n  wasmDepthToSpace(xId, blockSize, channelsLast, xStridesBytes, x.shape.length - 1, outputShapeBytes, outStridesBytes, outputShape.length, outId);\n  return out;\n}\nvar depthToSpaceConfig3 = {\n  kernelName: DepthToSpace,\n  backendName: \"wasm\",\n  setupFunc: setup14,\n  kernelFunc: depthToSpace4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/DepthwiseConv2dNative.js\nvar wasmDepthwiseConv2d;\nfunction setup15(backend2) {\n  wasmDepthwiseConv2d = backend2.wasm.cwrap(DepthwiseConv2dNative, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction depthwiseConv2d5(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { x, filter } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const filterId = backend2.dataIdMap.get(filter.dataId).id;\n  const { strides, dilations, pad: pad3, dimRoundingMode } = attrs;\n  const $dilations = dilations == null ? [1, 1] : dilations;\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad3, dimRoundingMode, true);\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padRight = convInfo.padInfo.right;\n  const padBottom = convInfo.padInfo.bottom;\n  const padLeft = convInfo.padInfo.left;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const inputChannels = convInfo.inChannels;\n  const outputChannels = convInfo.outChannels;\n  const isSamePad = convInfo.padInfo.type === \"SAME\" ? 1 : 0;\n  if (convInfo.dataFormat !== \"channelsLast\") {\n    throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${convInfo.dataFormat}'. Please use 'channelsLast'.`);\n  }\n  const out = backend2.makeOutput(convInfo.outShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmDepthwiseConv2d(xId, x.shape[0], x.shape[1], x.shape[2], filterId, filterHeight, filterWidth, padTop, padRight, padBottom, padLeft, isSamePad, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, outId);\n  return out;\n}\nvar depthwiseConv2dNativeConfig3 = {\n  kernelName: DepthwiseConv2dNative,\n  backendName: \"wasm\",\n  setupFunc: setup15,\n  kernelFunc: depthwiseConv2d5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Elu.js\nvar eluConfig3 = createUnaryKernelConfig(Elu);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Equal.js\nvar supportsFullBroadcast2 = false;\nvar equalConfig3 = createBinaryKernelConfig(Equal, supportsFullBroadcast2, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Exp.js\nvar expConfig3 = createUnaryKernelConfig(Exp, \"float32\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/ExpandDims.js\nfunction expandDims5(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const { dim } = attrs;\n  const inputRank = input2.shape.length;\n  const newShape = input2.shape.slice();\n  let $dim = dim;\n  if (dim < 0) {\n    util_exports.assert(-(inputRank + 1) <= dim, () => `Axis must be in the interval [${-(inputRank + 1)}, ${inputRank}]`);\n    $dim = inputRank + dim + 1;\n  }\n  newShape.splice($dim, 0, 1);\n  return reshape5({ inputs: { x: input2 }, backend: backend2, attrs: { shape: newShape } });\n}\nvar expandDimsConfig3 = {\n  kernelName: ExpandDims,\n  backendName: \"wasm\",\n  kernelFunc: expandDims5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Fill.js\nfunction fill4(args) {\n  const { attrs: { shape, value, dtype }, backend: backend2 } = args;\n  const out = backend2.makeOutput(shape, dtype);\n  const outVals = backend2.typedArrayFromHeap(out);\n  outVals.fill(value);\n  return out;\n}\nvar fillConfig3 = {\n  kernelName: Fill,\n  backendName: \"wasm\",\n  kernelFunc: fill4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/FlipLeftRight.js\nvar wasmFlipLeftRight;\nfunction setup16(backend2) {\n  wasmFlipLeftRight = backend2.wasm.cwrap(FlipLeftRight, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction flipLeftRight2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { image: image2 } = inputs;\n  const out = backend2.makeOutput(image2.shape, image2.dtype);\n  const imageId = backend2.dataIdMap.get(image2.dataId).id;\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n  wasmFlipLeftRight(imageId, batch, imageHeight, imageWidth, numChannels, outId);\n  return out;\n}\nvar flipLeftRightConfig3 = {\n  kernelName: FlipLeftRight,\n  backendName: \"wasm\",\n  kernelFunc: flipLeftRight2,\n  setupFunc: setup16\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Floor.js\nvar floorConfig3 = createUnaryKernelConfig(Floor);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/FloorDiv.js\nvar supportsFullBroadcast3 = false;\nvar floorDivConfig3 = createBinaryKernelConfig(FloorDiv, supportsFullBroadcast3);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/FusedBatchNorm.js\nvar wasmBatchNorm;\nfunction setup17(backend2) {\n  wasmBatchNorm = backend2.wasm.cwrap(FusedBatchNorm, null, [\"number\", \"number\", \"number\", \"number\", \"number\", \"number\", \"number\"]);\n}\nfunction fusedBatchNorm(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { varianceEpsilon } = attrs;\n  const { x, mean: mean5, variance, offset, scale: scale2 } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const meanId = backend2.dataIdMap.get(mean5.dataId).id;\n  const varianceId = backend2.dataIdMap.get(variance.dataId).id;\n  const offsetId = offset != null ? backend2.dataIdMap.get(offset.dataId).id : 0;\n  const scaleId = scale2 != null ? backend2.dataIdMap.get(scale2.dataId).id : 0;\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  if (util_exports.sizeFromShape(x.shape) === 0) {\n    return out;\n  }\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmBatchNorm(xId, meanId, varianceId, offsetId, scaleId, varianceEpsilon, outId);\n  return out;\n}\nvar fusedBatchNormConfig = {\n  kernelName: FusedBatchNorm,\n  backendName: \"wasm\",\n  setupFunc: setup17,\n  kernelFunc: fusedBatchNorm\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/FusedConv2D.js\nvar wasmFusedConv2d;\nfunction setup18(backend2) {\n  wasmFusedConv2d = backend2.wasm.cwrap(FusedConv2D, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction fusedConv2d2(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dilations, dataFormat, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode);\n  const fusedActivation = FusableActivation[activation2];\n  if (fusedActivation == null) {\n    throw new Error(`${activation2} activation not yet supported for FusedConv2D in the wasm backend.`);\n  }\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const filterId = backend2.dataIdMap.get(filter.dataId).id;\n  const outputChannels = convInfo.outChannels;\n  let biasId = 0;\n  if (bias != null) {\n    const biasData = backend2.dataIdMap.get(bias.dataId);\n    if (biasData.shape.length !== 1) {\n      throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${biasData.shape.length}.`);\n    }\n    if (biasData.shape[0] !== outputChannels) {\n      throw new Error(`FusedConv2D bias shape (${biasData.shape}) does not match the number of output channels (${outputChannels})`);\n    }\n    biasId = biasData.id;\n  }\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padRight = convInfo.padInfo.right;\n  const padBottom = convInfo.padInfo.bottom;\n  const padLeft = convInfo.padInfo.left;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const inputChannels = convInfo.inChannels;\n  const isSamePad = convInfo.padInfo.type === \"SAME\" ? 1 : 0;\n  const batchSize = convInfo.batchSize;\n  const inHeight = convInfo.inHeight;\n  const inWidth = convInfo.inWidth;\n  if (dataFormat !== \"NHWC\") {\n    throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${dataFormat}'. Please use 'NHWC'.`);\n  }\n  const out = backend2.makeOutput(convInfo.outShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const preluActivationWeightsId = preluActivationWeights == null ? 0 : backend2.dataIdMap.get(preluActivationWeights.dataId).id;\n  wasmFusedConv2d(xId, batchSize, inHeight, inWidth, filterId, filterHeight, filterWidth, biasId, padTop, padRight, padBottom, padLeft, isSamePad, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, fusedActivation, preluActivationWeightsId, leakyreluAlpha || 0, outId);\n  return out;\n}\nvar fusedConv2DConfig3 = {\n  kernelName: FusedConv2D,\n  backendName: \"wasm\",\n  setupFunc: setup18,\n  kernelFunc: fusedConv2d2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/FusedDepthwiseConv2D.js\nvar wasmFusedDepthwiseConv2d;\nfunction setup19(backend2) {\n  wasmFusedDepthwiseConv2d = backend2.wasm.cwrap(FusedDepthwiseConv2D, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction fusedDepthwiseConv2d(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dilations, dataFormat, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode, true);\n  const fusedActivation = FusableActivation[activation2];\n  if (fusedActivation == null) {\n    throw new Error(`${activation2} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);\n  }\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const filterId = backend2.dataIdMap.get(filter.dataId).id;\n  const outputChannels = convInfo.outChannels;\n  let biasId = 0;\n  if (bias != null) {\n    const biasData = backend2.dataIdMap.get(bias.dataId);\n    if (biasData.shape.length !== 1) {\n      throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${biasData.shape.length}.`);\n    }\n    if (biasData.shape[0] !== outputChannels) {\n      throw new Error(`FusedDepthwiseConv2D bias shape (${biasData.shape}) does not match the number of output channels (${outputChannels})`);\n    }\n    biasId = biasData.id;\n  }\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padRight = convInfo.padInfo.right;\n  const padBottom = convInfo.padInfo.bottom;\n  const padLeft = convInfo.padInfo.left;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const inputChannels = convInfo.inChannels;\n  const isSamePad = convInfo.padInfo.type === \"SAME\" ? 1 : 0;\n  const batchSize = convInfo.batchSize;\n  const inHeight = convInfo.inHeight;\n  const inWidth = convInfo.inWidth;\n  if (dataFormat !== \"NHWC\") {\n    throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${dataFormat}'. Please use 'NHWC'.`);\n  }\n  const out = backend2.makeOutput(convInfo.outShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const preluActivationWeightsId = preluActivationWeights == null ? 0 : backend2.dataIdMap.get(preluActivationWeights.dataId).id;\n  wasmFusedDepthwiseConv2d(xId, batchSize, inHeight, inWidth, filterId, filterHeight, filterWidth, biasId, padTop, padRight, padBottom, padLeft, isSamePad, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, fusedActivation, preluActivationWeightsId, leakyreluAlpha || 0, outId);\n  return out;\n}\nvar fusedDepthwiseConv2DConfig3 = {\n  kernelName: FusedDepthwiseConv2D,\n  backendName: \"wasm\",\n  setupFunc: setup19,\n  kernelFunc: fusedDepthwiseConv2d\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/GatherNd.js\nvar wasmGatherNd;\nfunction setup20(backend2) {\n  wasmGatherNd = backend2.wasm.cwrap(GatherNd, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\"\n  ]);\n}\nfunction gatherNd3(args) {\n  const { backend: backend2, inputs } = args;\n  const { params, indices } = inputs;\n  const [resultShape, numSlices, sliceSize, strides] = gather_nd_util_exports.prepareAndValidate(params, indices);\n  const out = backend2.makeOutput(resultShape, params.dtype);\n  if (numSlices === 0) {\n    return out;\n  }\n  const indicesShape = indices.shape;\n  const sliceRank = indicesShape[indicesShape.length - 1];\n  const xData = backend2.dataIdMap.get(params.dataId);\n  const xId = xData.id;\n  const indicesData = backend2.dataIdMap.get(indices.dataId);\n  const indicesId = indicesData.id;\n  const stridesBytes = new Uint8Array(new Int32Array(strides).buffer);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmGatherNd(xId, CppDType[params.dtype], indicesId, numSlices, sliceRank, sliceSize, stridesBytes, outId);\n  return out;\n}\nvar gatherNdConfig3 = {\n  kernelName: GatherNd,\n  backendName: \"wasm\",\n  setupFunc: setup20,\n  kernelFunc: gatherNd3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/GatherV2.js\nvar wasmGather;\nfunction setup21(backend2) {\n  wasmGather = backend2.wasm.cwrap(\"Gather\", null, [\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\"\n  ]);\n}\nfunction gatherV23(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { x, indices } = inputs;\n  const { axis, batchDims } = attrs;\n  const parsedAxis = util_exports.parseAxisParam(axis, x.shape)[0];\n  const indicesVals = backend2.readSync(indices.dataId);\n  const axisDim = x.shape[parsedAxis];\n  for (let i2 = 0; i2 < indicesVals.length; ++i2) {\n    const index = indicesVals[i2];\n    util_exports.assert(index <= axisDim - 1 && index >= 0, () => `GatherV2: the index value ${index} is not in [0, ${axisDim - 1}]`);\n  }\n  const shapeInfo = backend_util_exports.segment_util.collectGatherOpShapeInfo(x, indices, parsedAxis, batchDims);\n  const flattenX = reshape5({\n    inputs: { x },\n    attrs: {\n      shape: [\n        shapeInfo.batchSize,\n        shapeInfo.outerSize,\n        shapeInfo.dimSize,\n        shapeInfo.sliceSize\n      ]\n    },\n    backend: backend2\n  });\n  const indicesSize = util_exports.sizeFromShape(indices.shape);\n  const flattenIndex = reshape5({\n    inputs: { x: indices },\n    attrs: { shape: [shapeInfo.batchSize, indicesSize / shapeInfo.batchSize] },\n    backend: backend2\n  });\n  const flattenOutputShape = [\n    shapeInfo.batchSize,\n    shapeInfo.outerSize,\n    indicesSize / shapeInfo.batchSize,\n    shapeInfo.sliceSize\n  ];\n  const out = backend2.makeOutput(flattenOutputShape, x.dtype);\n  if (util_exports.sizeFromShape(x.shape) === 0) {\n    return out;\n  }\n  const stridesSize = flattenX.shape.length - 1;\n  const xData = backend2.dataIdMap.get(flattenX.dataId);\n  const xId = xData.id;\n  const indicesData = backend2.dataIdMap.get(flattenIndex.dataId);\n  const indicesId = indicesData.id;\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const xStridesBytes = new Uint8Array(new Int32Array(util_exports.computeStrides(flattenX.shape)).buffer);\n  const outStridesBytes = new Uint8Array(new Int32Array(util_exports.computeStrides(flattenOutputShape)).buffer);\n  wasmGather(xId, CppDType[x.dtype], xStridesBytes, stridesSize, indicesId, shapeInfo.batchSize, outStridesBytes, outId);\n  backend2.disposeData(flattenX.dataId);\n  backend2.disposeData(flattenIndex.dataId);\n  out.shape = shapeInfo.outputShape;\n  return out;\n}\nvar gatherV2Config3 = {\n  kernelName: GatherV2,\n  backendName: \"wasm\",\n  setupFunc: setup21,\n  kernelFunc: gatherV23\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Greater.js\nvar supportsFullBroadcast4 = false;\nvar greaterConfig3 = createBinaryKernelConfig(Greater, supportsFullBroadcast4, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/GreaterEqual.js\nvar supportsFullBroadcast5 = false;\nvar greaterEqualConfig3 = createBinaryKernelConfig(GreaterEqual, supportsFullBroadcast5, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/LeakyRelu.js\nvar wasmFunc3;\nfunction setupFunc2(backend2) {\n  wasmFunc3 = backend2.wasm.cwrap(LeakyRelu, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction leakyRelu4(args) {\n  const { inputs: { x }, attrs: { alpha }, backend: backend2 } = args;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const out = backend2.makeOutput(x.shape, \"float32\");\n  if (util_exports.sizeFromShape(x.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmFunc3(xId, CppDType[x.dtype], alpha, outId);\n  }\n  return out;\n}\nvar leakyReluConfig3 = {\n  kernelName: LeakyRelu,\n  backendName: \"wasm\",\n  setupFunc: setupFunc2,\n  kernelFunc: leakyRelu4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Less.js\nvar supportsFullBroadcast6 = false;\nvar lessConfig3 = createBinaryKernelConfig(Less, supportsFullBroadcast6, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/LessEqual.js\nvar supportsFullBroadcast7 = false;\nvar lessEqualConfig3 = createBinaryKernelConfig(LessEqual, supportsFullBroadcast7, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Log.js\nvar logConfig3 = createUnaryKernelConfig(Log);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/LogicalAnd.js\nvar supportsFullBroadcast8 = false;\nvar logicalAndConfig3 = createBinaryKernelConfig(LogicalAnd, supportsFullBroadcast8, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/LogicalNot.js\nvar logicalNotConfig3 = createUnaryKernelConfig(LogicalNot);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/LogicalOr.js\nvar supportsFullBroadcast9 = false;\nvar logicalOrConfig3 = createBinaryKernelConfig(LogicalOr, supportsFullBroadcast9, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/LogicalXor.js\nvar supportsFullBroadcast10 = false;\nvar logicalXorConfig = createBinaryKernelConfig(LogicalXor, supportsFullBroadcast10, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Max.js\nvar wasmMax;\nfunction setup22(backend2) {\n  wasmMax = backend2.wasm.cwrap(Max, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction max5(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { reductionIndices: axis, keepDims } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    input2 = transposed;\n    inputId = transposedId;\n  }\n  const inputRank = input2.shape.length;\n  backend_util_exports.assertAxesAreInnerMostDims(\"max\", axes, inputRank);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const out = backend2.makeOutput(outShape, x.dtype);\n  if (util_exports.sizeFromShape(input2.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmMax(inputId, CppDType[x.dtype], reduceSize, outId);\n  }\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(out.shape, originalAxes);\n    out.shape = newShape;\n  }\n  return out;\n}\nvar maxConfig3 = {\n  kernelName: Max,\n  backendName: \"wasm\",\n  setupFunc: setup22,\n  kernelFunc: max5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Maximum.js\nvar supportsFullBroadcast11 = false;\nvar maximumConfig3 = createBinaryKernelConfig(Maximum, supportsFullBroadcast11);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/MaxPool.js\nvar wasmMaxPool;\nfunction setup23(backend2) {\n  wasmMaxPool = backend2.wasm.cwrap(MaxPool, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction maxPool4(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const x = inputs.x;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  util_exports.assert(x.dtype === \"float32\", () => `Error in MaxPool: only float32 input is supported. Got ${x.dtype}.`);\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, 1, pad3, dimRoundingMode);\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padRight = convInfo.padInfo.right;\n  const padBottom = convInfo.padInfo.bottom;\n  const padLeft = convInfo.padInfo.left;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const inputChannels = convInfo.inChannels;\n  const outputChannels = convInfo.outChannels;\n  if (convInfo.dataFormat !== \"channelsLast\") {\n    throw new Error(`wasm backend does not support dataFormat:'${convInfo.dataFormat}'. Please use 'channelsLast'.`);\n  }\n  const out = backend2.makeOutput(convInfo.outShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmMaxPool(xId, x.shape[0], x.shape[1], x.shape[2], filterHeight, filterWidth, padTop, padRight, padBottom, padLeft, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, outId);\n  return out;\n}\nvar maxPoolConfig3 = {\n  kernelName: MaxPool,\n  backendName: \"wasm\",\n  setupFunc: setup23,\n  kernelFunc: maxPool4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Mean.js\nvar wasmMean;\nfunction setup24(backend2) {\n  wasmMean = backend2.wasm.cwrap(Mean, null, [\"number, number, number\"]);\n}\nfunction mean3(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { axis, keepDims } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  let reductionAxes = axes;\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    if (transposedId !== xId) {\n      input2 = transposed;\n      inputId = transposedId;\n      reductionAxes = backend_util_exports.getInnerMostAxes(reductionAxes.length, input2.shape.length);\n    }\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"mean\", reductionAxes, input2.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, reductionAxes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  let castedInput = input2;\n  if (input2.dtype !== \"float32\") {\n    castedInput = cast5({ backend: backend2, inputs: { x: input2 }, attrs: { dtype: \"float32\" } });\n    inputId = backend2.dataIdMap.get(castedInput.dataId).id;\n  }\n  const out = backend2.makeOutput(outShape, \"float32\");\n  if (util_exports.sizeFromShape(input2.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmMean(inputId, reduceSize, outId);\n  }\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(out.shape, originalAxes);\n    out.shape = newShape;\n  }\n  if (input2.dtype !== \"float32\") {\n    backend2.disposeData(castedInput.dataId);\n  }\n  return out;\n}\nvar meanConfig3 = {\n  kernelName: Mean,\n  backendName: \"wasm\",\n  setupFunc: setup24,\n  kernelFunc: mean3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Min.js\nvar wasmMin;\nfunction setup25(backend2) {\n  wasmMin = backend2.wasm.cwrap(Min, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction min5(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { axis, keepDims } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    if (transposedId !== xId) {\n      input2 = transposed;\n      inputId = transposedId;\n    }\n  }\n  const inputRank = input2.shape.length;\n  backend_util_exports.assertAxesAreInnerMostDims(\"min\", axes, inputRank);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const out = backend2.makeOutput(outShape, input2.dtype);\n  if (util_exports.sizeFromShape(input2.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmMin(inputId, CppDType[x.dtype], reduceSize, outId);\n  }\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(out.shape, originalAxes);\n    out.shape = newShape;\n  }\n  return out;\n}\nvar minConfig3 = {\n  kernelName: Min,\n  backendName: \"wasm\",\n  setupFunc: setup25,\n  kernelFunc: min5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Minimum.js\nvar supportsFullBroadcast12 = false;\nvar minimumConfig3 = createBinaryKernelConfig(Minimum, supportsFullBroadcast12);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/MirrorPad.js\nvar MirrorPaddingMode;\n(function(MirrorPaddingMode2) {\n  MirrorPaddingMode2[MirrorPaddingMode2[\"reflect\"] = 0] = \"reflect\";\n  MirrorPaddingMode2[MirrorPaddingMode2[\"symmetric\"] = 1] = \"symmetric\";\n})(MirrorPaddingMode || (MirrorPaddingMode = {}));\nvar wasmMirrorPad;\nfunction setup26(backend2) {\n  wasmMirrorPad = backend2.wasm.cwrap(MirrorPad, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction mirrorPad3(args) {\n  const { inputs: { x }, backend: backend2, attrs: { paddings, mode } } = args;\n  const outShape = paddings.map((p2, i2) => p2[0] + x.shape[i2] + p2[1]);\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const out = backend2.makeOutput(outShape, x.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);\n  const prePaddingsFlat = paddings.map((padTuple) => padTuple[0]);\n  const postPaddingsFlat = paddings.map((padTuple) => padTuple[1]);\n  const prePaddingsBytes = new Uint8Array(new Int32Array(prePaddingsFlat).buffer);\n  const postPaddingsBytes = new Uint8Array(new Int32Array(postPaddingsFlat).buffer);\n  wasmMirrorPad(xId, xShapeBytes, x.shape.length, CppDType[x.dtype], prePaddingsBytes, postPaddingsBytes, MirrorPaddingMode[mode], outId);\n  return out;\n}\nvar mirrorPadConfig3 = {\n  kernelName: MirrorPad,\n  backendName: \"wasm\",\n  kernelFunc: mirrorPad3,\n  setupFunc: setup26\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Multiply.js\nvar supportsFullBroadcast13 = true;\nvar multiplyConfig3 = createBinaryKernelConfig(Multiply, supportsFullBroadcast13);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Neg.js\nvar negConfig3 = createUnaryKernelConfig(Neg);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/NonMaxSuppression_util.js\nfunction parseResultStruct(backend2, resOffset) {\n  const result = new Int32Array(backend2.wasm.HEAPU8.buffer, resOffset, 4);\n  const pSelectedIndices = result[0];\n  const selectedSize = result[1];\n  const pSelectedScores = result[2];\n  const pValidOutputs = result[3];\n  backend2.wasm._free(resOffset);\n  return { pSelectedIndices, selectedSize, pSelectedScores, pValidOutputs };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/NonMaxSuppressionV3.js\nvar wasmFunc4;\nfunction setup27(backend2) {\n  wasmFunc4 = backend2.wasm.cwrap(\n    NonMaxSuppressionV3,\n    \"number\",\n    [\n      \"number\",\n      \"number\",\n      \"number\",\n      \"number\",\n      \"number\"\n    ]\n  );\n}\nfunction kernelFunc(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { iouThreshold, maxOutputSize, scoreThreshold } = attrs;\n  const { boxes, scores } = inputs;\n  const boxesId = backend2.dataIdMap.get(boxes.dataId).id;\n  const scoresId = backend2.dataIdMap.get(scores.dataId).id;\n  const resOffset = wasmFunc4(boxesId, scoresId, maxOutputSize, iouThreshold, scoreThreshold);\n  const { pSelectedIndices, selectedSize, pSelectedScores, pValidOutputs } = parseResultStruct(backend2, resOffset);\n  backend2.wasm._free(pSelectedScores);\n  backend2.wasm._free(pValidOutputs);\n  const selectedIndicesTensor = backend2.makeOutput([selectedSize], \"int32\", pSelectedIndices);\n  return selectedIndicesTensor;\n}\nvar nonMaxSuppressionV3Config3 = {\n  kernelName: NonMaxSuppressionV3,\n  backendName: \"wasm\",\n  setupFunc: setup27,\n  kernelFunc\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/NonMaxSuppressionV4.js\nvar wasmFunc5;\nfunction setup28(backend2) {\n  wasmFunc5 = backend2.wasm.cwrap(\n    NonMaxSuppressionV4,\n    \"number\",\n    [\n      \"number\",\n      \"number\",\n      \"number\",\n      \"number\",\n      \"number\",\n      \"bool\"\n    ]\n  );\n}\nfunction nonMaxSuppressionV43(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { iouThreshold, maxOutputSize, scoreThreshold, padToMaxOutputSize } = attrs;\n  const { boxes, scores } = inputs;\n  const boxesId = backend2.dataIdMap.get(boxes.dataId).id;\n  const scoresId = backend2.dataIdMap.get(scores.dataId).id;\n  const resOffset = wasmFunc5(boxesId, scoresId, maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize);\n  const { pSelectedIndices, selectedSize, pSelectedScores, pValidOutputs } = parseResultStruct(backend2, resOffset);\n  backend2.wasm._free(pSelectedScores);\n  const selectedIndicesTensor = backend2.makeOutput([selectedSize], \"int32\", pSelectedIndices);\n  const validOutputsTensor = backend2.makeOutput([], \"int32\", pValidOutputs);\n  return [selectedIndicesTensor, validOutputsTensor];\n}\nvar nonMaxSuppressionV4Config3 = {\n  kernelName: NonMaxSuppressionV4,\n  backendName: \"wasm\",\n  setupFunc: setup28,\n  kernelFunc: nonMaxSuppressionV43\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/NonMaxSuppressionV5.js\nvar wasmFunc6;\nfunction setup29(backend2) {\n  wasmFunc6 = backend2.wasm.cwrap(\n    NonMaxSuppressionV5,\n    \"number\",\n    [\n      \"number\",\n      \"number\",\n      \"number\",\n      \"number\",\n      \"number\",\n      \"number\"\n    ]\n  );\n}\nfunction kernelFunc2(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { iouThreshold, maxOutputSize, scoreThreshold, softNmsSigma } = attrs;\n  const { boxes, scores } = inputs;\n  const boxesId = backend2.dataIdMap.get(boxes.dataId).id;\n  const scoresId = backend2.dataIdMap.get(scores.dataId).id;\n  const resOffset = wasmFunc6(boxesId, scoresId, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma);\n  const { pSelectedIndices, selectedSize, pSelectedScores, pValidOutputs } = parseResultStruct(backend2, resOffset);\n  backend2.wasm._free(pValidOutputs);\n  const selectedIndicesTensor = backend2.makeOutput([selectedSize], \"int32\", pSelectedIndices);\n  const selectedScoresTensor = backend2.makeOutput([selectedSize], \"float32\", pSelectedScores);\n  return [selectedIndicesTensor, selectedScoresTensor];\n}\nvar nonMaxSuppressionV5Config3 = {\n  kernelName: NonMaxSuppressionV5,\n  backendName: \"wasm\",\n  setupFunc: setup29,\n  kernelFunc: kernelFunc2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/NotEqual.js\nvar supportsFullBroadcast14 = false;\nvar notEqualConfig3 = createBinaryKernelConfig(NotEqual, supportsFullBroadcast14, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/OneHot.js\nvar wasmOneHot;\nfunction setup30(backend2) {\n  wasmOneHot = backend2.wasm.cwrap(OneHot, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction oneHot4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { indices } = inputs;\n  const { depth, onValue, offValue } = attrs;\n  const out = backend2.makeOutput([...indices.shape, depth], \"int32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const indicesData = backend2.dataIdMap.get(indices.dataId);\n  const indicesId = indicesData.id;\n  wasmOneHot(indicesId, depth, onValue, offValue, outId);\n  return out;\n}\nvar oneHotConfig3 = {\n  kernelName: OneHot,\n  backendName: \"wasm\",\n  setupFunc: setup30,\n  kernelFunc: oneHot4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/OnesLike.js\nfunction onesLike4(args) {\n  const { inputs: { x }, backend: backend2 } = args;\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  const outVals = backend2.typedArrayFromHeap(out);\n  outVals.fill(1);\n  return out;\n}\nvar onesLikeConfig3 = {\n  kernelName: OnesLike,\n  backendName: \"wasm\",\n  kernelFunc: onesLike4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Pack.js\nfunction pack3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { axis } = attrs;\n  if (inputs.length === 1) {\n    return expandDims5({ inputs: { input: inputs[0] }, backend: backend2, attrs: { dim: axis } });\n  }\n  const shape = inputs[0].shape;\n  const dtype = inputs[0].dtype;\n  inputs.forEach((t2) => {\n    util_exports.assertShapesMatch(shape, t2.shape, \"All tensors passed to stack must have matching shapes\");\n    util_exports.assert(dtype === t2.dtype, () => \"All tensors passed to stack must have matching dtypes\");\n  });\n  const intermediateTensorInfos = [];\n  const expandedTensors = inputs.map((t2) => {\n    const expandedT = expandDims5({ inputs: { input: t2 }, backend: backend2, attrs: { dim: axis } });\n    intermediateTensorInfos.push(expandedT);\n    return expandedT;\n  });\n  const result = concat4({ inputs: expandedTensors, backend: backend2, attrs: { axis } });\n  intermediateTensorInfos.forEach((t2) => backend2.disposeData(t2.dataId));\n  return result;\n}\nvar packConfig3 = {\n  kernelName: Pack,\n  backendName: \"wasm\",\n  kernelFunc: pack3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/PadV2.js\nvar wasmPadV2;\nfunction setup31(backend2) {\n  wasmPadV2 = backend2.wasm.cwrap(PadV2, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction pad2(args) {\n  const { inputs: { x }, backend: backend2, attrs: { paddings, constantValue } } = args;\n  const outShape = paddings.map((p2, i2) => p2[0] + x.shape[i2] + p2[1]);\n  if (util_exports.sizeFromShape(x.shape) === 0) {\n    return fill4({\n      backend: backend2,\n      attrs: { shape: outShape, value: constantValue, dtype: x.dtype }\n    });\n  }\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const out = backend2.makeOutput(outShape, x.dtype);\n  const outTensorData = backend2.dataIdMap.get(out.dataId);\n  const outId = outTensorData.id;\n  const xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);\n  const prePaddingsFlat = paddings.map((padTuple) => padTuple[0]);\n  const postPaddingsFlat = paddings.map((padTuple) => padTuple[1]);\n  const prePaddingsBytes = new Uint8Array(new Int32Array(prePaddingsFlat).buffer);\n  const postPaddingsBytes = new Uint8Array(new Int32Array(postPaddingsFlat).buffer);\n  wasmPadV2(xId, xShapeBytes, x.shape.length, CppDType[x.dtype], prePaddingsBytes, postPaddingsBytes, constantValue, outId);\n  return out;\n}\nvar padV2Config3 = {\n  kernelName: PadV2,\n  backendName: \"wasm\",\n  kernelFunc: pad2,\n  setupFunc: setup31\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Pow.js\nvar supportsFullBroadcast15 = false;\nvar powConfig3 = createBinaryKernelConfig(Pow, supportsFullBroadcast15);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Prelu.js\nvar wasmPrelu;\nfunction setup32(backend2) {\n  wasmPrelu = backend2.wasm.cwrap(Prelu, null, [\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction prelu5(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x, alpha } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const weightsId = backend2.dataIdMap.get(alpha.dataId).id;\n  let inputId = xId;\n  const input2 = x;\n  let castedInput = input2;\n  if (input2.dtype !== \"float32\") {\n    castedInput = cast5({ backend: backend2, inputs: { x }, attrs: { dtype: \"float32\" } });\n    inputId = backend2.dataIdMap.get(castedInput.dataId).id;\n  }\n  const out = backend2.makeOutput(x.shape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmPrelu(inputId, weightsId, outId);\n  if (input2.dtype !== \"float32\") {\n    backend2.disposeData(castedInput.dataId);\n  }\n  return out;\n}\nvar preluConfig3 = {\n  kernelName: Prelu,\n  backendName: \"wasm\",\n  setupFunc: setup32,\n  kernelFunc: prelu5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Prod.js\nvar wasmProd;\nfunction setup33(backend2) {\n  wasmProd = backend2.wasm.cwrap(Prod, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction prod4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { axis, keepDims } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  let reductionAxes = axes;\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    if (transposedId !== xId) {\n      input2 = transposed;\n      inputId = transposedId;\n      reductionAxes = backend_util_exports.getInnerMostAxes(reductionAxes.length, input2.shape.length);\n    }\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"prod\", reductionAxes, input2.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, reductionAxes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const out = backend2.makeOutput(outShape, input2.dtype);\n  if (util_exports.sizeFromShape(input2.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmProd(inputId, reduceSize, CppDType[out.dtype], outId);\n  }\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(out.shape, originalAxes);\n    out.shape = newShape;\n  }\n  return out;\n}\nvar prodConfig3 = {\n  kernelName: Prod,\n  backendName: \"wasm\",\n  setupFunc: setup33,\n  kernelFunc: prod4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Range.js\nvar range5 = (args) => {\n  const { backend: backend2, attrs } = args;\n  const { start, stop, step: step5, dtype } = attrs;\n  const values = rangeImpl(start, stop, step5, dtype);\n  const out = backend2.makeOutput([values.length], dtype);\n  const outVals = backend2.typedArrayFromHeap(out);\n  outVals.set(values);\n  return out;\n};\nvar rangeConfig3 = {\n  kernelName: Range,\n  backendName: \"wasm\",\n  kernelFunc: range5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/RealDiv.js\nvar supportsFullBroadcast16 = true;\nvar realDivConfig3 = createBinaryKernelConfig(RealDiv, supportsFullBroadcast16);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Relu.js\nvar reluConfig3 = createUnaryKernelConfig(Relu);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Relu6.js\nvar relu6Config3 = createUnaryKernelConfig(Relu6);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/ResizeBilinear.js\nvar wasmResizeBilinear;\nfunction setup34(backend2) {\n  wasmResizeBilinear = backend2.wasm.cwrap(ResizeBilinear, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction resizeBilinear4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, halfPixelCenters, size } = attrs;\n  const [newHeight, newWidth] = size;\n  const [batch, oldHeight, oldWidth, numChannels] = images.shape;\n  const outShape = [batch, newHeight, newWidth, numChannels];\n  let xData = backend2.dataIdMap.get(images.dataId);\n  let castedData;\n  if (xData.dtype !== \"float32\") {\n    castedData = cast5({ backend: backend2, inputs: { x: images }, attrs: { dtype: \"float32\" } });\n    xData = backend2.dataIdMap.get(castedData.dataId);\n  }\n  const xId = xData.id;\n  const out = backend2.makeOutput(outShape, \"float32\");\n  if (util_exports.sizeFromShape(images.shape) === 0) {\n    return out;\n  }\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmResizeBilinear(xId, batch, oldHeight, oldWidth, numChannels, newHeight, newWidth, alignCorners ? 1 : 0, halfPixelCenters ? 1 : 0, outId);\n  if (castedData != null) {\n    backend2.disposeData(castedData.dataId);\n  }\n  return out;\n}\nvar resizeBilinearConfig3 = {\n  kernelName: ResizeBilinear,\n  backendName: \"wasm\",\n  setupFunc: setup34,\n  kernelFunc: resizeBilinear4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/ResizeNearestNeighbor.js\nvar wasmResizeNearestNeighbor;\nfunction setup35(backend2) {\n  wasmResizeNearestNeighbor = backend2.wasm.cwrap(ResizeNearestNeighbor, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction resizeNearestNeighbor4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, halfPixelCenters, size } = attrs;\n  const [newHeight, newWidth] = size;\n  const [batch, oldHeight, oldWidth, numChannels] = images.shape;\n  const outShape = [batch, newHeight, newWidth, numChannels];\n  const out = backend2.makeOutput(outShape, \"float32\");\n  if (util_exports.sizeFromShape(images.shape) === 0) {\n    return out;\n  }\n  let xData = backend2.dataIdMap.get(images.dataId);\n  let castedData;\n  if (xData.dtype !== \"float32\") {\n    castedData = cast5({\n      backend: backend2,\n      inputs: { x: images },\n      attrs: { dtype: \"float32\" }\n    });\n    xData = backend2.dataIdMap.get(castedData.dataId);\n  }\n  const xId = xData.id;\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmResizeNearestNeighbor(xId, batch, oldHeight, oldWidth, numChannels, newHeight, newWidth, alignCorners ? 1 : 0, halfPixelCenters ? 1 : 0, outId);\n  if (castedData != null) {\n    backend2.disposeData(castedData.dataId);\n  }\n  return out;\n}\nvar resizeNearestNeighborConfig3 = {\n  kernelName: ResizeNearestNeighbor,\n  backendName: \"wasm\",\n  setupFunc: setup35,\n  kernelFunc: resizeNearestNeighbor4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Reverse.js\nvar wasmReverse;\nfunction setup36(backend2) {\n  wasmReverse = backend2.wasm.cwrap(Reverse, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction reverse4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { dims } = attrs;\n  const axes = util_exports.parseAxisParam(dims, x.shape);\n  if (x.shape.length === 0) {\n    return identity4({ inputs: { x }, backend: backend2 });\n  }\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const axesBytes = new Uint8Array(new Int32Array(axes).buffer);\n  const outShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);\n  wasmReverse(xId, axesBytes, axes.length, outShapeBytes, x.shape.length, outId);\n  const reshaped = reshape5({ inputs: { x: out }, attrs: { shape: x.shape }, backend: backend2 });\n  backend2.disposeData(out.dataId);\n  return reshaped;\n}\nvar reverseConfig3 = {\n  kernelName: Reverse,\n  backendName: \"wasm\",\n  kernelFunc: reverse4,\n  setupFunc: setup36\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/RotateWithOffset.js\nvar wasmRotate;\nfunction setup37(backend2) {\n  wasmRotate = backend2.wasm.cwrap(RotateWithOffset, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction rotateWithOffset2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { image: image2 } = inputs;\n  const { radians, fillValue, center } = attrs;\n  const out = backend2.makeOutput(image2.shape, image2.dtype);\n  const imageId = backend2.dataIdMap.get(image2.dataId).id;\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n  const [centerX, centerY] = backend_util_exports.getImageCenter(center, imageHeight, imageWidth);\n  const fillIsBlack = fillValue === 0;\n  const fullOpacityValue = 255;\n  const fillValues2 = typeof fillValue === \"number\" ? [fillValue, fillValue, fillValue, fillIsBlack ? 0 : fullOpacityValue] : [...fillValue, fullOpacityValue];\n  const fillBytes = new Uint8Array(new Int32Array(fillValues2).buffer);\n  wasmRotate(imageId, batch, imageHeight, imageWidth, numChannels, radians, centerX, centerY, fillBytes, fillValues2.length, outId);\n  return out;\n}\nvar rotateWithOffsetConfig3 = {\n  kernelName: RotateWithOffset,\n  backendName: \"wasm\",\n  kernelFunc: rotateWithOffset2,\n  setupFunc: setup37\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Round.js\nvar roundConfig3 = createUnaryKernelConfig(Round);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Rsqrt.js\nvar rsqrtConfig3 = createUnaryKernelConfig(Rsqrt);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/ScatterNd.js\nvar wasmScatterNd;\nfunction setup38(backend2) {\n  wasmScatterNd = backend2.wasm.cwrap(ScatterNd, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction scatterNd3(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { indices, updates } = inputs;\n  const { shape } = attrs;\n  const out = backend2.makeOutput(shape, updates.dtype);\n  if (util_exports.sizeFromShape(shape) === 0) {\n    return out;\n  }\n  const { sliceRank, numUpdates, sliceSize, strides, outputSize } = scatter_nd_util_exports.calculateShapes(updates, indices, shape);\n  const indicesData = backend2.dataIdMap.get(indices.dataId);\n  const indicesId = indicesData.id;\n  const updatesData = backend2.dataIdMap.get(updates.dataId);\n  const updatesId = updatesData.id;\n  const stridesBytes = new Uint8Array(new Int32Array(strides).buffer);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmScatterNd(indicesId, updatesId, CppDType[updates.dtype], sliceRank, numUpdates, sliceSize, stridesBytes, outputSize, outId);\n  return out;\n}\nvar scatterNdConfig3 = {\n  kernelName: ScatterNd,\n  backendName: \"wasm\",\n  setupFunc: setup38,\n  kernelFunc: scatterNd3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Select.js\nvar wasmSelect;\nfunction setup39(backend2) {\n  wasmSelect = backend2.wasm.cwrap(\"SelectV2\", null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction select4(args) {\n  const { inputs, backend: backend2 } = args;\n  const { condition, t: t2, e: e2 } = inputs;\n  const conditionId = backend2.dataIdMap.get(condition.dataId).id;\n  const tId = backend2.dataIdMap.get(t2.dataId).id;\n  const eId = backend2.dataIdMap.get(e2.dataId).id;\n  const out = backend2.makeOutput(t2.shape, t2.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const cRank = condition.shape.length;\n  const tRank = t2.shape.length;\n  const offset = cRank === 0 || cRank > 1 || tRank === 1 ? 1 : util_exports.sizeFromShape(t2.shape.slice(1));\n  wasmSelect(conditionId, tId, eId, offset, outId);\n  return out;\n}\nvar selectConfig3 = {\n  kernelName: Select,\n  backendName: \"wasm\",\n  kernelFunc: select4,\n  setupFunc: setup39\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Sigmoid.js\nvar wasmFunc7;\nfunction setup40(backend2) {\n  wasmFunc7 = backend2.wasm.cwrap(Sigmoid, null, [\"number\", \"number\"]);\n}\nfunction sigmoid4(args) {\n  const { backend: backend2, inputs: { x } } = args;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  if (util_exports.sizeFromShape(out.shape) === 0) {\n    return out;\n  }\n  wasmFunc7(xId, outId);\n  return out;\n}\nvar sigmoidConfig3 = {\n  kernelName: \"Sigmoid\",\n  backendName: \"wasm\",\n  setupFunc: setup40,\n  kernelFunc: sigmoid4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Sin.js\nvar sinConfig3 = createUnaryKernelConfig(Sin);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Softmax.js\nvar wasmFunc8;\nfunction setup41(backend2) {\n  wasmFunc8 = backend2.wasm.cwrap(Softmax, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction softmax5(args) {\n  const { backend: backend2, inputs: { logits }, attrs: { dim } } = args;\n  const xId = backend2.dataIdMap.get(logits.dataId).id;\n  const out = backend2.makeOutput(logits.shape, logits.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const channels = logits.shape[dim];\n  const batch = util_exports.sizeFromShape(logits.shape) / channels;\n  if (util_exports.sizeFromShape(out.shape) === 0) {\n    return out;\n  }\n  wasmFunc8(xId, outId, channels, batch);\n  return out;\n}\nvar softmaxConfig3 = {\n  kernelName: Softmax,\n  backendName: \"wasm\",\n  setupFunc: setup41,\n  kernelFunc: softmax5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SpaceToBatchND.js\nfunction spaceToBatchND4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, paddings } = attrs;\n  const prod6 = util_exports.sizeFromShape(blockShape);\n  const completePaddings = [[0, 0]];\n  completePaddings.push(...paddings);\n  for (let i2 = 1 + blockShape.length; i2 < x.shape.length; ++i2) {\n    completePaddings.push([0, 0]);\n  }\n  const paddedX = padV2Config3.kernelFunc({\n    inputs: { x },\n    backend: backend2,\n    attrs: { paddings: completePaddings, constantValue: 0 }\n  });\n  const reshapedPaddedShape = backend_util_exports.getReshaped(paddedX.shape, blockShape, prod6, false);\n  const permutedReshapedPaddedPermutation = backend_util_exports.getPermuted(reshapedPaddedShape.length, blockShape.length, false);\n  const flattenShape = backend_util_exports.getReshapedPermuted(paddedX.shape, blockShape, prod6, false);\n  const reshapeInputs = { x: paddedX };\n  const reshapeAttrs = { shape: reshapedPaddedShape };\n  const paddedXReshaped = reshape5({ inputs: reshapeInputs, backend: backend2, attrs: reshapeAttrs });\n  const transposeInputs = { x: paddedXReshaped };\n  const transposeAttrs = { perm: permutedReshapedPaddedPermutation };\n  const paddedXT = transpose4({ inputs: transposeInputs, backend: backend2, attrs: transposeAttrs });\n  const resultReshapeInputs = { x: paddedXT };\n  const resultReshapeAttrs = { shape: flattenShape };\n  const result = reshape5({ inputs: resultReshapeInputs, backend: backend2, attrs: resultReshapeAttrs });\n  backend2.disposeData(paddedX.dataId);\n  backend2.disposeData(paddedXReshaped.dataId);\n  backend2.disposeData(paddedXT.dataId);\n  return result;\n}\nvar spaceToBatchNDConfig3 = {\n  kernelName: SpaceToBatchND,\n  backendName: \"wasm\",\n  kernelFunc: spaceToBatchND4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SparseFillEmptyRows.js\nvar wasmSparseFillEmptyRows;\nfunction setup42(backend2) {\n  wasmSparseFillEmptyRows = backend2.wasm.cwrap(\"SparseFillEmptyRows\", \"number\", [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction sparseFillEmptyRows4(args) {\n  const { backend: backend2, inputs } = args;\n  const { indices, values, denseShape, defaultValue } = inputs;\n  const indicesCount = indices.shape[0];\n  const rank = indices.shape[1];\n  const denseRows = backend2.readSync(denseShape.dataId)[0];\n  const maxOutputIndicesShape = [indicesCount + denseRows, rank];\n  const indicesId = backend2.dataIdMap.get(indices.dataId).id;\n  const valuesId = backend2.dataIdMap.get(values.dataId).id;\n  const defaultValueId = backend2.dataIdMap.get(defaultValue.dataId).id;\n  const outputIndices = backend2.makeOutput(maxOutputIndicesShape, indices.dtype);\n  const outputIndicesId = backend2.dataIdMap.get(outputIndices.dataId).id;\n  const outputValues = backend2.makeOutput(maxOutputIndicesShape.slice(0, 1), values.dtype);\n  const outputValuesId = backend2.dataIdMap.get(outputValues.dataId).id;\n  const emptyRowIndicator = backend2.makeOutput([denseRows], \"bool\");\n  const emptyRowIndicatorId = backend2.dataIdMap.get(emptyRowIndicator.dataId).id;\n  const reverseIndexMap = backend2.makeOutput([indicesCount], indices.dtype);\n  const reverseIndexMapId = backend2.dataIdMap.get(reverseIndexMap.dataId).id;\n  const exceptionValues = backend2.makeOutput([4], \"int32\");\n  const exceptionValuesId = backend2.dataIdMap.get(exceptionValues.dataId).id;\n  const outputRows = wasmSparseFillEmptyRows(indicesId, valuesId, CppDType[values.dtype], indicesCount, denseRows, rank, defaultValueId, outputIndicesId, outputValuesId, emptyRowIndicatorId, reverseIndexMapId, exceptionValuesId);\n  const exceptionValuesArray = backend2.readSync(exceptionValues.dataId);\n  let exceptionMessage;\n  switch (exceptionValuesArray[0]) {\n    case 1: {\n      exceptionMessage = backend_util_exports.getSparseFillEmptyRowsIndicesDenseShapeMismatch(exceptionValuesArray[1]);\n      break;\n    }\n    case 2: {\n      exceptionMessage = backend_util_exports.getSparseFillEmptyRowsNegativeIndexErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2]);\n      break;\n    }\n    case 3:\n      exceptionMessage = backend_util_exports.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2], exceptionValuesArray[3]);\n      break;\n    default:\n      exceptionMessage = \"\";\n  }\n  backend2.disposeData(exceptionValues.dataId);\n  if (exceptionMessage) {\n    backend2.disposeData(outputIndices.dataId);\n    backend2.disposeData(outputValues.dataId);\n    backend2.disposeData(emptyRowIndicator.dataId);\n    backend2.disposeData(reverseIndexMap.dataId);\n    throw new Error(exceptionMessage);\n  }\n  let resizedIndices = outputIndices;\n  let resizedValues = outputValues;\n  if (outputRows !== maxOutputIndicesShape[0]) {\n    resizedIndices = slice4({\n      inputs: { x: outputIndices },\n      attrs: { begin: 0, size: [outputRows, rank] },\n      backend: backend2\n    });\n    resizedValues = slice4({\n      inputs: { x: outputValues },\n      attrs: { begin: 0, size: outputRows },\n      backend: backend2\n    });\n    backend2.disposeData(outputIndices.dataId);\n    backend2.disposeData(outputValues.dataId);\n  }\n  return [resizedIndices, resizedValues, emptyRowIndicator, reverseIndexMap];\n}\nvar sparseFillEmptyRowsConfig3 = {\n  kernelName: SparseFillEmptyRows,\n  backendName: \"wasm\",\n  setupFunc: setup42,\n  kernelFunc: sparseFillEmptyRows4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SparseReshape.js\nvar wasmSparseReshape;\nfunction setup43(backend2) {\n  wasmSparseReshape = backend2.wasm.cwrap(SparseReshape, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction sparseReshape4(args) {\n  const { backend: backend2, inputs } = args;\n  const { inputIndices, inputShape, newShape } = inputs;\n  if (inputIndices.shape.length !== 2) {\n    throw new Error(`Input indices should be a matrix but received shape\n        ${inputIndices.shape}`);\n  }\n  if (inputShape.shape.length !== 1) {\n    throw new Error(`Input shape should be a vector but received shape\n        ${inputShape.shape}`);\n  }\n  if (newShape.shape.length !== 1) {\n    throw new Error(`Target shape should be a vector but received shape ${newShape.shape}`);\n  }\n  const inputIndicesId = backend2.dataIdMap.get(inputIndices.dataId).id;\n  const inputShapeId = backend2.dataIdMap.get(inputShape.dataId).id;\n  const newShapeId = backend2.dataIdMap.get(newShape.dataId).id;\n  const nnz = inputIndices.shape[0];\n  const outputRank = util_exports.sizeFromShape(newShape.shape);\n  const newIndices = backend2.makeOutput([nnz, outputRank], inputIndices.dtype);\n  const newIndicesId = backend2.dataIdMap.get(newIndices.dataId).id;\n  const outputShape = backend2.makeOutput([outputRank], newShape.dtype);\n  const outputShapeId = backend2.dataIdMap.get(outputShape.dataId).id;\n  const exceptionValues = backend2.makeOutput([3], \"int32\");\n  const exceptionValuesId = backend2.dataIdMap.get(exceptionValues.dataId).id;\n  wasmSparseReshape(inputIndicesId, inputShapeId, newShapeId, nnz, newIndicesId, outputShapeId, exceptionValuesId);\n  const exceptionValuesArray = backend2.readSync(exceptionValues.dataId);\n  let exceptionMessage;\n  switch (exceptionValuesArray[0]) {\n    case 0: {\n      exceptionMessage = backend_util_exports.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2]);\n      break;\n    }\n    case 1: {\n      exceptionMessage = backend_util_exports.getSparseReshapeNegativeOutputDimErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2]);\n      break;\n    }\n    case 2:\n      exceptionMessage = backend_util_exports.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage();\n      break;\n    case 3: {\n      const inputShapeValues = Array.from(backend2.readSync(inputShape.dataId)), outputShapeValues = Array.from(backend2.readSync(outputShape.dataId));\n      exceptionMessage = backend_util_exports.getSparseReshapeInputOutputMultipleErrorMessage(inputShapeValues, outputShapeValues);\n      break;\n    }\n    case 4: {\n      const inputShapeValues = Array.from(backend2.readSync(inputShape.dataId)), outputShapeValues = Array.from(backend2.readSync(outputShape.dataId));\n      exceptionMessage = backend_util_exports.getSparseReshapeInputOutputMismatchErrorMessage(inputShapeValues, outputShapeValues);\n      break;\n    }\n    default:\n      exceptionMessage = \"\";\n  }\n  backend2.disposeData(exceptionValues.dataId);\n  if (exceptionMessage) {\n    backend2.disposeData(newIndices.dataId);\n    backend2.disposeData(outputShape.dataId);\n    throw new Error(exceptionMessage);\n  }\n  return [newIndices, outputShape];\n}\nvar sparseReshapeConfig3 = {\n  kernelName: SparseReshape,\n  backendName: \"wasm\",\n  setupFunc: setup43,\n  kernelFunc: sparseReshape4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SparseSegmentReduction.js\nvar wasmSparseSegmentReduction;\nfunction setup44(backend2) {\n  wasmSparseSegmentReduction = backend2.wasm.cwrap(\"SparseSegmentReduction\", null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction sparseSegmentReduction(args, isMean) {\n  const { backend: backend2, inputs } = args;\n  const { data, indices, segmentIds } = inputs;\n  const numIndices = indices.shape[0];\n  const segmentIdsBack = backend2.readSync(segmentIds.dataId, numIndices - 1, numIndices)[0];\n  const lastSegmentIdPlusOne = numIndices > 0 ? segmentIdsBack + 1 : 0;\n  const outputRows = lastSegmentIdPlusOne;\n  if (outputRows < 0) {\n    throw new Error(backend_util_exports.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());\n  }\n  const outputShape = data.shape.slice();\n  outputShape[0] = outputRows;\n  const dataId = backend2.dataIdMap.get(data.dataId).id;\n  const indicesId = backend2.dataIdMap.get(indices.dataId).id;\n  const segmentIdsId = backend2.dataIdMap.get(segmentIds.dataId).id;\n  const output = backend2.makeOutput(outputShape, data.dtype);\n  const outputId = backend2.dataIdMap.get(output.dataId).id;\n  const exceptionValues = backend2.makeOutput([4], \"int32\");\n  const exceptionValuesId = backend2.dataIdMap.get(exceptionValues.dataId).id;\n  wasmSparseSegmentReduction(dataId, CppDType[data.dtype], data.shape[0], indicesId, segmentIdsId, outputId, exceptionValuesId, isMean, 0);\n  const exceptionValuesArray = backend2.readSync(exceptionValues.dataId);\n  let exceptionMessage;\n  switch (exceptionValuesArray[0]) {\n    case 0: {\n      exceptionMessage = backend_util_exports.getSparseSegmentReductionNegativeSegmentIdsErrorMessage();\n      break;\n    }\n    case 1: {\n      exceptionMessage = backend_util_exports.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage();\n      break;\n    }\n    case 2:\n      exceptionMessage = backend_util_exports.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2]);\n      break;\n    case 3:\n      exceptionMessage = backend_util_exports.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2], exceptionValuesArray[3]);\n      break;\n    default:\n      exceptionMessage = \"\";\n  }\n  backend2.disposeData(exceptionValues.dataId);\n  if (exceptionMessage) {\n    backend2.disposeData(output.dataId);\n    throw new Error(exceptionMessage);\n  }\n  return output;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SparseSegmentMean.js\nfunction sparseSegmentMean4(args) {\n  return sparseSegmentReduction(args, true);\n}\nvar sparseSegmentMeanConfig3 = {\n  kernelName: SparseSegmentMean,\n  backendName: \"wasm\",\n  setupFunc: setup44,\n  kernelFunc: sparseSegmentMean4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SparseSegmentSum.js\nfunction sparseSegmentSum4(args) {\n  return sparseSegmentReduction(args, false);\n}\nvar sparseSegmentSumConfig3 = {\n  kernelName: SparseSegmentSum,\n  backendName: \"wasm\",\n  setupFunc: setup44,\n  kernelFunc: sparseSegmentSum4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SplitV.js\nfunction splitV3(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { x } = inputs;\n  const { numOrSizeSplits, axis } = attrs;\n  const $axis = util_exports.parseAxisParam(axis, x.shape)[0];\n  const splitSizes = backend_util_exports.prepareSplitSize(x, numOrSizeSplits, $axis);\n  const begin = new Array(x.shape.length).fill(0);\n  const size = x.shape.slice();\n  return splitSizes.map((s2) => {\n    const xSliceSize = [...size];\n    xSliceSize[$axis] = s2;\n    const xSlice = slice4({ inputs: { x }, attrs: { begin, size: xSliceSize }, backend: backend2 });\n    begin[$axis] += s2;\n    return xSlice;\n  });\n}\nvar splitVConfig3 = {\n  kernelName: SplitV,\n  backendName: \"wasm\",\n  kernelFunc: splitV3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Sqrt.js\nvar sqrtConfig3 = createUnaryKernelConfig(Sqrt);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Square.js\nvar squareConfig3 = createUnaryKernelConfig(Square);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SquaredDifference.js\nvar supportsFullBroadcast17 = true;\nvar squaredDifferenceConfig3 = createBinaryKernelConfig(SquaredDifference, supportsFullBroadcast17);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Step.js\nvar wasmStep;\nfunction setup45(backend2) {\n  wasmStep = backend2.wasm.cwrap(Step, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction step4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { alpha } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmStep(xId, alpha, CppDType[x.dtype], outId);\n  return out;\n}\nvar stepConfig3 = {\n  kernelName: Step,\n  backendName: \"wasm\",\n  setupFunc: setup45,\n  kernelFunc: step4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/StridedSlice.js\nvar wasmStridedSlice;\nfunction setup46(backend2) {\n  wasmStridedSlice = backend2.wasm.cwrap(StridedSlice, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"array\",\n    \"array\",\n    \"array\",\n    \"array\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction stridedSlice4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { x } = inputs;\n  const { begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask } = attrs;\n  const { finalShapeSparse, finalShape, isIdentity, sliceDim0, isSimpleSlice, begin: $begin, end: $end, strides: $strides } = slice_util_exports.sliceInfo(x.shape, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask);\n  let result;\n  if (isIdentity) {\n    result = reshape5({ inputs: { x }, backend: backend2, attrs: { shape: finalShape } });\n  } else if (sliceDim0 || isSimpleSlice) {\n    util_exports.assert(x.shape.length >= 1, () => `Input must have rank at least 1, got: ${x.shape.length}`);\n    const size = slice_util_exports.computeOutShape($begin, $end, $strides);\n    const sliced = slice4({ inputs: { x }, backend: backend2, attrs: { begin: $begin, size } });\n    result = reshape5({ inputs: { x: sliced }, backend: backend2, attrs: { shape: finalShape } });\n    backend2.disposeData(sliced.dataId);\n  } else {\n    const out = backend2.makeOutput(finalShapeSparse, \"float32\");\n    const xId = backend2.dataIdMap.get(x.dataId).id;\n    const xStridesBytes = new Uint8Array(new Int32Array(util_exports.computeStrides(x.shape)).buffer);\n    const beginBytes = new Uint8Array(new Int32Array($begin).buffer);\n    const endBytes = new Uint8Array(new Int32Array($end).buffer);\n    const stridesBytes = new Uint8Array(new Int32Array($strides).buffer);\n    const outputShapeBytes = new Uint8Array(new Int32Array(finalShapeSparse).buffer);\n    const outStridesBytes = new Uint8Array(new Int32Array(util_exports.computeStrides(finalShapeSparse)).buffer);\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmStridedSlice(xId, xStridesBytes, x.shape.length, beginBytes, endBytes, stridesBytes, outputShapeBytes, outStridesBytes, finalShapeSparse.length, outId);\n    result = reshape5({ inputs: { x: out }, backend: backend2, attrs: { shape: finalShape } });\n    backend2.disposeData(out.dataId);\n  }\n  return result;\n}\nvar stridedSliceConfig3 = {\n  kernelName: StridedSlice,\n  backendName: \"wasm\",\n  setupFunc: setup46,\n  kernelFunc: stridedSlice4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/StringNGrams.js\nfunction stringNGrams4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { data, dataSplits } = inputs;\n  const { separator, nGramWidths, leftPad, rightPad: rightPad2, padWidth, preserveShortSequences } = attrs;\n  const $data = backend2.readSync(data.dataId);\n  const $dataSplits = backend2.readSync(dataSplits.dataId);\n  const [nGrams, nGramsSplits] = stringNGramsImpl($data, $dataSplits, separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences);\n  const nGramsOut = backend2.makeOutput([nGrams.length], \"string\");\n  const nGramsOutData = backend2.dataIdMap.get(nGramsOut.dataId);\n  nGramsOutData.stringBytes = nGrams;\n  const nGramsSplitsOut = backend2.makeOutput(dataSplits.shape, \"int32\");\n  const nGramsSplitsOutVals = backend2.typedArrayFromHeap(nGramsSplitsOut);\n  nGramsSplitsOutVals.set(nGramsSplits);\n  return [nGramsOut, nGramsSplitsOut];\n}\nvar stringNGramsConfig3 = {\n  kernelName: StringNGrams,\n  backendName: \"wasm\",\n  kernelFunc: stringNGrams4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/StringSplit.js\nfunction stringSplit4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { input: input2, delimiter } = inputs;\n  const { skipEmpty } = attrs;\n  const inputVals = backend2.readSync(input2.dataId);\n  const delimiterVals = backend2.readSync(delimiter.dataId);\n  const [indices, values, shape] = stringSplitImpl(inputVals, delimiterVals[0], skipEmpty);\n  const outputSize = values.length;\n  const indicesOut = backend2.makeOutput([outputSize, 2], \"int32\");\n  const indicesOutVals = backend2.typedArrayFromHeap(indicesOut);\n  indicesOutVals.set(indices);\n  const valuesOut = backend2.makeOutput([outputSize], \"string\");\n  const valuesOutData = backend2.dataIdMap.get(valuesOut.dataId);\n  valuesOutData.stringBytes = values;\n  const shapeOut = backend2.makeOutput([2], \"int32\");\n  const shapeOutVals = backend2.typedArrayFromHeap(shapeOut);\n  shapeOutVals.set(shape);\n  return [indicesOut, valuesOut, shapeOut];\n}\nvar stringSplitConfig3 = {\n  kernelName: StringSplit,\n  backendName: \"wasm\",\n  kernelFunc: stringSplit4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/StringToHashBucketFast.js\nfunction stringToHashBucketFast4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { input: input2 } = inputs;\n  const { numBuckets } = attrs;\n  const inputVals = backend2.readSync(input2.dataId);\n  const values = stringToHashBucketFastImpl(inputVals, numBuckets);\n  const out = backend2.makeOutput(input2.shape, \"int32\");\n  const outVals = backend2.typedArrayFromHeap(out);\n  outVals.set(values);\n  return out;\n}\nvar stringToHashBucketFastConfig3 = {\n  kernelName: StringToHashBucketFast,\n  backendName: \"wasm\",\n  kernelFunc: stringToHashBucketFast4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Sub.js\nvar supportsFullBroadcast18 = true;\nvar subConfig3 = createBinaryKernelConfig(Sub, supportsFullBroadcast18);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Sum.js\nvar wasmSum;\nfunction setup47(backend2) {\n  wasmSum = backend2.wasm.cwrap(Sum, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction sum5(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { axis, keepDims } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  let reductionAxes = axes;\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    if (transposedId !== xId) {\n      input2 = transposed;\n      inputId = transposedId;\n      reductionAxes = backend_util_exports.getInnerMostAxes(reductionAxes.length, input2.shape.length);\n    }\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"sum\", reductionAxes, input2.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, reductionAxes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const out = backend2.makeOutput(outShape, input2.dtype);\n  if (util_exports.sizeFromShape(input2.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmSum(inputId, reduceSize, CppDType[out.dtype], outId);\n  }\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(out.shape, originalAxes);\n    out.shape = newShape;\n  }\n  return out;\n}\nvar sumConfig3 = {\n  kernelName: Sum,\n  backendName: \"wasm\",\n  setupFunc: setup47,\n  kernelFunc: sum5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Tan.js\nvar tanConfig3 = createUnaryKernelConfig(Tan);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Tanh.js\nvar tanhConfig3 = createUnaryKernelConfig(Tanh);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Tile.js\nvar wasmTile;\nfunction setup48(backend2) {\n  wasmTile = backend2.wasm.cwrap(Tile, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction tile5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const { reps } = attrs;\n  const newShape = new Array(x.shape.length);\n  for (let i2 = 0; i2 < newShape.length; i2++) {\n    newShape[i2] = x.shape[i2] * reps[i2];\n  }\n  const xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);\n  const newShapeBytes = new Uint8Array(new Int32Array(newShape).buffer);\n  const out = backend2.makeOutput(newShape, x.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmTile(xId, xShapeBytes, x.shape.length, newShapeBytes, newShape.length, CppDType[out.dtype], outId);\n  return out;\n}\nvar tileConfig3 = {\n  kernelName: Tile,\n  backendName: \"wasm\",\n  setupFunc: setup48,\n  kernelFunc: tile5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/TopK.js\nvar wasmTopK;\nfunction setup49(backend2) {\n  wasmTopK = backend2.wasm.cwrap(TopK, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"bool\",\n    \"number\",\n    \"number\"\n  ]);\n}\nvar topk2 = ({ inputs, backend: backend2, attrs }) => {\n  const { x } = inputs;\n  const { k, sorted } = attrs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);\n  const outputShape = x.shape.slice();\n  outputShape[outputShape.length - 1] = k;\n  const outValues = backend2.makeOutput(outputShape, x.dtype);\n  const outValuesId = backend2.dataIdMap.get(outValues.dataId).id;\n  const outIndices = backend2.makeOutput(outputShape, \"int32\");\n  const outIndicesId = backend2.dataIdMap.get(outIndices.dataId).id;\n  wasmTopK(xId, xShapeBytes, x.shape.length, CppDType[x.dtype], k, sorted, outValuesId, outIndicesId);\n  return [outValues, outIndices];\n};\nvar topKConfig3 = {\n  kernelName: TopK,\n  backendName: \"wasm\",\n  setupFunc: setup49,\n  kernelFunc: topk2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Transform.js\nvar wasmTransform;\nfunction setup50(backend2) {\n  wasmTransform = backend2.wasm.cwrap(Transform, null, [\n    \"number\",\n    \"number\",\n    \"bool\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction transform4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { image: image2, transforms } = inputs;\n  const { interpolation, fillMode, fillValue, outputShape } = attrs;\n  const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n  const [outHeight, outWidth] = outputShape != null ? outputShape : [imageHeight, imageWidth];\n  const outShape = [\n    batch,\n    outHeight,\n    outWidth,\n    numChannels\n  ];\n  const strides = new Uint8Array(new Int32Array(util_exports.computeStrides(image2.shape)).buffer);\n  const out = backend2.makeOutput(outShape, image2.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const imageData = backend2.dataIdMap.get(image2.dataId);\n  const imageId = imageData.id;\n  const transformsData = backend2.dataIdMap.get(transforms.dataId);\n  const transformsId = transformsData.id;\n  const interpolationModeId = interpolation === \"nearest\" ? 1 : 2;\n  let fillModeId;\n  switch (fillMode) {\n    case \"constant\":\n      fillModeId = 1;\n      break;\n    case \"reflect\":\n      fillModeId = 2;\n      break;\n    case \"wrap\":\n      fillModeId = 3;\n      break;\n    case \"nearest\":\n      fillModeId = 4;\n      break;\n    default:\n      fillModeId = 1;\n      break;\n  }\n  wasmTransform(imageId, transformsId, transforms.shape[0] > 1, batch, outHeight, outWidth, numChannels, imageWidth, imageHeight, strides, image2.shape.length - 1, interpolationModeId, fillModeId, fillValue, outId);\n  return out;\n}\nvar transformConfig3 = {\n  kernelName: Transform,\n  backendName: \"wasm\",\n  setupFunc: setup50,\n  kernelFunc: transform4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Unpack.js\nfunction unpack3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { value } = inputs;\n  let { axis } = attrs;\n  if (axis < 0) {\n    axis += value.shape.length;\n  }\n  const numOutputs = value.shape[axis];\n  const rank = value.shape.length;\n  const outShape = new Array(rank - 1);\n  let outIndex = 0;\n  for (let i2 = 0; i2 < rank; i2++) {\n    if (i2 !== axis) {\n      outShape[outIndex++] = value.shape[i2];\n    }\n  }\n  const outs = new Array(numOutputs);\n  const begin = new Array(rank).fill(0);\n  const size = value.shape.slice();\n  size[axis] = 1;\n  for (let i2 = 0; i2 < outs.length; i2++) {\n    begin[axis] = i2;\n    outs[i2] = slice4({ inputs: { x: value }, attrs: { begin, size }, backend: backend2 });\n  }\n  return outs.map(({ dataId, dtype }) => ({ dataId, dtype, shape: outShape }));\n}\nvar unpackConfig3 = {\n  kernelName: Unpack,\n  backendName: \"wasm\",\n  kernelFunc: unpack3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/ZerosLike.js\nfunction zerosLike4(args) {\n  const { inputs: { x }, backend: backend2 } = args;\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  const outVals = backend2.typedArrayFromHeap(out);\n  outVals.fill(0);\n  return out;\n}\nvar zerosLikeConfig3 = {\n  kernelName: ZerosLike,\n  backendName: \"wasm\",\n  kernelFunc: zerosLike4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/register_all_kernels.js\nvar kernelConfigs3 = [\n  _fusedMatMulConfig3,\n  absConfig3,\n  addConfig3,\n  addNConfig3,\n  allConfig3,\n  anyConfig3,\n  argMaxConfig3,\n  avgPoolConfig3,\n  batchMatMulConfig3,\n  batchToSpaceNDConfig3,\n  castConfig3,\n  ceilConfig3,\n  clipByValueConfig3,\n  concatConfig3,\n  conv2DConfig3,\n  conv2DBackpropInputConfig3,\n  cosConfig3,\n  coshConfig3,\n  cropAndResizeConfig3,\n  cumprodConfig3,\n  cumsumConfig3,\n  depthToSpaceConfig3,\n  depthwiseConv2dNativeConfig3,\n  eluConfig3,\n  equalConfig3,\n  expConfig3,\n  expandDimsConfig3,\n  fillConfig3,\n  flipLeftRightConfig3,\n  floorConfig3,\n  floorDivConfig3,\n  fusedBatchNormConfig,\n  fusedConv2DConfig3,\n  fusedDepthwiseConv2DConfig3,\n  gatherNdConfig3,\n  gatherV2Config3,\n  greaterConfig3,\n  greaterEqualConfig3,\n  identityConfig3,\n  leakyReluConfig3,\n  lessConfig3,\n  lessEqualConfig3,\n  logConfig3,\n  logicalAndConfig3,\n  logicalNotConfig3,\n  logicalOrConfig3,\n  logicalXorConfig,\n  maxConfig3,\n  maximumConfig3,\n  maxPoolConfig3,\n  meanConfig3,\n  minConfig3,\n  minimumConfig3,\n  mirrorPadConfig3,\n  multiplyConfig3,\n  negConfig3,\n  nonMaxSuppressionV3Config3,\n  nonMaxSuppressionV4Config3,\n  nonMaxSuppressionV5Config3,\n  notEqualConfig3,\n  oneHotConfig3,\n  onesLikeConfig3,\n  packConfig3,\n  padV2Config3,\n  powConfig3,\n  preluConfig3,\n  prodConfig3,\n  rangeConfig3,\n  realDivConfig3,\n  reluConfig3,\n  relu6Config3,\n  reshapeConfig3,\n  resizeBilinearConfig3,\n  resizeNearestNeighborConfig3,\n  reverseConfig3,\n  rotateWithOffsetConfig3,\n  roundConfig3,\n  rsqrtConfig3,\n  scatterNdConfig3,\n  selectConfig3,\n  sigmoidConfig3,\n  sinConfig3,\n  sliceConfig3,\n  softmaxConfig3,\n  spaceToBatchNDConfig3,\n  sparseFillEmptyRowsConfig3,\n  sparseReshapeConfig3,\n  sparseSegmentMeanConfig3,\n  sparseSegmentSumConfig3,\n  splitVConfig3,\n  sqrtConfig3,\n  squareConfig3,\n  squaredDifferenceConfig3,\n  stepConfig3,\n  stridedSliceConfig3,\n  stringNGramsConfig3,\n  stringSplitConfig3,\n  stringToHashBucketFastConfig3,\n  subConfig3,\n  sumConfig3,\n  tanConfig3,\n  tanhConfig3,\n  tileConfig3,\n  topKConfig3,\n  transformConfig3,\n  transposeConfig3,\n  unpackConfig3,\n  zerosLikeConfig3\n];\nfor (const kernelConfig of kernelConfigs3) {\n  registerKernel(kernelConfig);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/flags_wasm.js\nvar ENV6 = env();\nENV6.registerFlag(\n  \"WASM_HAS_SIMD_SUPPORT\",\n  async () => WebAssembly.validate(new Uint8Array([\n    0,\n    97,\n    115,\n    109,\n    1,\n    0,\n    0,\n    0,\n    1,\n    4,\n    1,\n    96,\n    0,\n    0,\n    3,\n    2,\n    1,\n    0,\n    10,\n    9,\n    1,\n    7,\n    0,\n    65,\n    0,\n    253,\n    15,\n    26,\n    11\n  ]))\n);\nENV6.registerFlag(\"WASM_HAS_MULTITHREAD_SUPPORT\", async () => {\n  if (ENV6.get(\"IS_NODE\")) {\n    return false;\n  }\n  try {\n    new MessageChannel().port1.postMessage(new SharedArrayBuffer(1));\n    return WebAssembly.validate(new Uint8Array([\n      0,\n      97,\n      115,\n      109,\n      1,\n      0,\n      0,\n      0,\n      1,\n      4,\n      1,\n      96,\n      0,\n      0,\n      3,\n      2,\n      1,\n      0,\n      5,\n      4,\n      1,\n      3,\n      1,\n      1,\n      10,\n      11,\n      1,\n      9,\n      0,\n      65,\n      0,\n      254,\n      16,\n      2,\n      0,\n      26,\n      11\n    ]));\n  } catch (e2) {\n    return false;\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/backend_wasm.js\nvar wasmFactoryThreadedSimd_import = __toESM(require_tfjs_backend_wasm_threaded_simd());\nvar import_tfjs_backend_wasm_threaded_simd_worker = __toESM(require_tfjs_backend_wasm_threaded_simd_worker());\nvar wasmFactory_import = __toESM(require_tfjs_backend_wasm());\nvar wasmFactoryThreadedSimd = wasmFactoryThreadedSimd_import.default || wasmFactoryThreadedSimd_import;\nvar wasmFactory = wasmFactory_import.default || wasmFactory_import;\nvar BackendWasm = class extends KernelBackend {\n  constructor(wasm) {\n    super();\n    this.wasm = wasm;\n    this.dataIdNextNumber = 1;\n    this.wasm.tfjs.initWithThreadsCount(threadsCount);\n    actualThreadsCount = this.wasm.tfjs.getThreadsCount();\n    this.dataIdMap = new DataStorage(this, engine());\n  }\n  write(values, shape, dtype) {\n    const dataId = { id: this.dataIdNextNumber++ };\n    this.move(dataId, values, shape, dtype, 1);\n    return dataId;\n  }\n  numDataIds() {\n    return this.dataIdMap.numDataIds();\n  }\n  async time(f) {\n    const start = util_exports.now();\n    f();\n    const kernelMs = util_exports.now() - start;\n    return { kernelMs };\n  }\n  move(dataId, values, shape, dtype, refCount) {\n    const id = this.dataIdNextNumber++;\n    if (dtype === \"string\") {\n      const stringBytes = values;\n      this.dataIdMap.set(dataId, { id, stringBytes, shape, dtype, memoryOffset: null, refCount });\n      return;\n    }\n    const size = util_exports.sizeFromShape(shape);\n    const numBytes = size * util_exports.bytesPerElement(dtype);\n    const memoryOffset = this.wasm._malloc(numBytes);\n    this.dataIdMap.set(dataId, { id, memoryOffset, shape, dtype, refCount });\n    this.wasm.tfjs.registerTensor(id, size, memoryOffset);\n    if (values != null) {\n      this.wasm.HEAPU8.set(new Uint8Array(values.buffer, values.byteOffset, numBytes), memoryOffset);\n    }\n  }\n  async read(dataId) {\n    return this.readSync(dataId);\n  }\n  readSync(dataId, start, end) {\n    const { memoryOffset, dtype, shape, stringBytes } = this.dataIdMap.get(dataId);\n    if (dtype === \"string\") {\n      if ((start == null || start === 0) && (end == null || end >= stringBytes.length)) {\n        return stringBytes;\n      }\n      return stringBytes.slice(start, end);\n    }\n    start = start || 0;\n    end = end || util_exports.sizeFromShape(shape);\n    const bytesPerElement2 = util_exports.bytesPerElement(dtype);\n    const bytes = this.wasm.HEAPU8.slice(memoryOffset + start * bytesPerElement2, memoryOffset + end * bytesPerElement2);\n    return typedArrayFromBuffer(bytes.buffer, dtype);\n  }\n  disposeData(dataId, force = false) {\n    if (this.dataIdMap.has(dataId)) {\n      const data = this.dataIdMap.get(dataId);\n      data.refCount--;\n      if (!force && data.refCount > 0) {\n        return false;\n      }\n      this.wasm._free(data.memoryOffset);\n      this.wasm.tfjs.disposeData(data.id);\n      this.dataIdMap.delete(dataId);\n    }\n    return true;\n  }\n  refCount(dataId) {\n    if (this.dataIdMap.has(dataId)) {\n      const tensorData = this.dataIdMap.get(dataId);\n      return tensorData.refCount;\n    }\n    return 0;\n  }\n  incRef(dataId) {\n    const data = this.dataIdMap.get(dataId);\n    if (data != null) {\n      data.refCount++;\n    }\n  }\n  floatPrecision() {\n    return 32;\n  }\n  getMemoryOffset(dataId) {\n    return this.dataIdMap.get(dataId).memoryOffset;\n  }\n  dispose() {\n    this.wasm.tfjs.dispose();\n    if (\"PThread\" in this.wasm) {\n      this.wasm.PThread.terminateAllThreads();\n    }\n    this.wasm = null;\n  }\n  memory() {\n    return { unreliable: false };\n  }\n  makeOutput(shape, dtype, memoryOffset) {\n    let dataId;\n    if (memoryOffset == null) {\n      dataId = this.write(null, shape, dtype);\n    } else {\n      const id = this.dataIdNextNumber++;\n      dataId = { id };\n      this.dataIdMap.set(dataId, { id, memoryOffset, shape, dtype, refCount: 1 });\n      const size = util_exports.sizeFromShape(shape);\n      this.wasm.tfjs.registerTensor(id, size, memoryOffset);\n    }\n    return { dataId, shape, dtype };\n  }\n  typedArrayFromHeap({ shape, dtype, dataId }) {\n    const buffer2 = this.wasm.HEAPU8.buffer;\n    const { memoryOffset } = this.dataIdMap.get(dataId);\n    const size = util_exports.sizeFromShape(shape);\n    switch (dtype) {\n      case \"float32\":\n        return new Float32Array(buffer2, memoryOffset, size);\n      case \"int32\":\n        return new Int32Array(buffer2, memoryOffset, size);\n      case \"bool\":\n        return new Uint8Array(buffer2, memoryOffset, size);\n      default:\n        throw new Error(`Unknown dtype ${dtype}`);\n    }\n  }\n};\nfunction createInstantiateWasmFunc(path) {\n  return (imports, callback) => {\n    util_exports.fetch(path, { credentials: \"same-origin\" }).then((response) => {\n      if (!response[\"ok\"]) {\n        imports.env.a(`failed to load wasm binary file at '${path}'`);\n      }\n      response.arrayBuffer().then((binary) => {\n        WebAssembly.instantiate(binary, imports).then((output) => {\n          callback(output.instance, output.module);\n        });\n      });\n    });\n    return {};\n  };\n}\nfunction getPathToWasmBinary(simdSupported, threadsSupported, wasmModuleFolder) {\n  if (wasmPath != null) {\n    return wasmPath;\n  }\n  let path = \"tfjs-backend-wasm.wasm\";\n  if (simdSupported && threadsSupported) {\n    path = \"tfjs-backend-wasm-threaded-simd.wasm\";\n  } else if (simdSupported) {\n    path = \"tfjs-backend-wasm-simd.wasm\";\n  }\n  if (wasmFileMap != null) {\n    if (wasmFileMap[path] != null) {\n      return wasmFileMap[path];\n    }\n  }\n  return wasmModuleFolder + path;\n}\nasync function init() {\n  const [simdSupported, threadsSupported] = await Promise.all([\n    env().getAsync(\"WASM_HAS_SIMD_SUPPORT\"),\n    env().getAsync(\"WASM_HAS_MULTITHREAD_SUPPORT\")\n  ]);\n  return new Promise((resolve, reject) => {\n    const factoryConfig = {};\n    factoryConfig.locateFile = (path, prefix) => {\n      if (path.endsWith(\".worker.js\")) {\n        const response = import_tfjs_backend_wasm_threaded_simd_worker.wasmWorkerContents.replace(/\\n/g, \"\\\\n\");\n        const blob = new Blob([response], { type: \"application/javascript\" });\n        return URL.createObjectURL(blob);\n      }\n      if (path.endsWith(\".wasm\")) {\n        return getPathToWasmBinary(simdSupported, threadsSupported, wasmPathPrefix != null ? wasmPathPrefix : prefix);\n      }\n      return prefix + path;\n    };\n    if (customFetch) {\n      factoryConfig.instantiateWasm = createInstantiateWasmFunc(getPathToWasmBinary(simdSupported, threadsSupported, wasmPathPrefix != null ? wasmPathPrefix : \"\"));\n    }\n    let initialized = false;\n    factoryConfig.onAbort = () => {\n      if (initialized) {\n        return;\n      }\n      if (initAborted) {\n        return;\n      }\n      initAborted = true;\n      const rejectMsg = \"Make sure the server can serve the `.wasm` file relative to the bundled js file. For more details see https://github.com/tensorflow/tfjs/blob/master/tfjs-backend-wasm/README.md#using-bundlers\";\n      reject({ message: rejectMsg });\n    };\n    let wasm;\n    if (threadsSupported && simdSupported && wasmPath == null) {\n      factoryConfig.mainScriptUrlOrBlob = new Blob([`var WasmBackendModuleThreadedSimd = ` + wasmFactoryThreadedSimd.toString()], { type: \"text/javascript\" });\n      wasm = wasmFactoryThreadedSimd(factoryConfig);\n    } else {\n      wasm = wasmFactory(factoryConfig);\n    }\n    wasm.then((module) => {\n      initialized = true;\n      initAborted = false;\n      const voidReturnType = null;\n      module.tfjs = {\n        init: module.cwrap(\"init\", null, []),\n        initWithThreadsCount: module.cwrap(\"init_with_threads_count\", null, [\"number\"]),\n        getThreadsCount: module.cwrap(\"get_threads_count\", \"number\", []),\n        registerTensor: module.cwrap(\"register_tensor\", null, [\n          \"number\",\n          \"number\",\n          \"number\"\n        ]),\n        disposeData: module.cwrap(\"dispose_data\", voidReturnType, [\"number\"]),\n        dispose: module.cwrap(\"dispose\", voidReturnType, [])\n      };\n      resolve({ wasm: module });\n    }).catch(reject);\n  });\n}\nfunction typedArrayFromBuffer(buffer2, dtype) {\n  switch (dtype) {\n    case \"float32\":\n      return new Float32Array(buffer2);\n    case \"int32\":\n      return new Int32Array(buffer2);\n    case \"bool\":\n      return new Uint8Array(buffer2);\n    default:\n      throw new Error(`Unknown dtype ${dtype}`);\n  }\n}\nvar wasmBinaryNames = [\n  \"tfjs-backend-wasm.wasm\",\n  \"tfjs-backend-wasm-simd.wasm\",\n  \"tfjs-backend-wasm-threaded-simd.wasm\"\n];\nvar wasmPath = null;\nvar wasmPathPrefix = null;\nvar wasmFileMap = {};\nvar initAborted = false;\nvar customFetch = false;\nfunction setWasmPath(path, usePlatformFetch = false) {\n  deprecationWarn(\"setWasmPath has been deprecated in favor of setWasmPaths and will be removed in a future release.\");\n  if (initAborted) {\n    throw new Error(\"The WASM backend was already initialized. Make sure you call `setWasmPath()` before you call `tf.setBackend()` or `tf.ready()`\");\n  }\n  wasmPath = path;\n  customFetch = usePlatformFetch;\n}\nfunction setWasmPaths(prefixOrFileMap, usePlatformFetch = false) {\n  if (initAborted) {\n    throw new Error(\"The WASM backend was already initialized. Make sure you call `setWasmPaths()` before you call `tf.setBackend()` or `tf.ready()`\");\n  }\n  if (typeof prefixOrFileMap === \"string\") {\n    wasmPathPrefix = prefixOrFileMap;\n  } else {\n    wasmFileMap = prefixOrFileMap;\n    const missingPaths = wasmBinaryNames.filter((name) => wasmFileMap[name] == null);\n    if (missingPaths.length > 0) {\n      throw new Error(`There were no entries found for the following binaries: ${missingPaths.join(\",\")}. Please either call setWasmPaths with a map providing a path for each binary, or with a string indicating the directory where all the binaries can be found.`);\n    }\n  }\n  customFetch = usePlatformFetch;\n}\nvar threadsCount = -1;\nvar actualThreadsCount = -1;\nfunction setThreadsCount(numThreads) {\n  threadsCount = numThreads;\n}\nfunction getThreadsCount() {\n  if (actualThreadsCount === -1) {\n    throw new Error(`WASM backend not initialized.`);\n  }\n  return actualThreadsCount;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/version.js\nvar version8 = \"3.19.0\";\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/base.js\nvar WASM_PRIORITY = 2;\nregisterBackend(\"wasm\", async () => {\n  const { wasm } = await init();\n  return new BackendWasm(wasm);\n}, WASM_PRIORITY);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/flags_webgpu.js\nvar ENV7 = env();\nENV7.registerFlag(\"WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE\", () => 15);\nENV7.registerFlag(\"WEBGPU_CPU_FORWARD\", () => true);\nENV7.registerFlag(\"WEBGPU_MATMUL_WORK_PER_THREAD\", () => 4);\nENV7.registerFlag(\"WEBGPU_MATMUL_PROGRAM_TYPE\", () => -1);\nENV7.registerFlag(\"WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE\", () => false);\nENV7.registerFlag(\"WEBGPU_USE_LOW_POWER_GPU\", () => false);\nENV7.registerFlag(\"WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD\", () => 1e3);\nENV7.registerFlag(\"WEBGPU_USE_PROFILE_TOOL\", () => false);\nENV7.registerFlag(\"WEBGPU_IMPORT_EXTERNAL_TEXTURE\", () => false);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/binary_op_util.js\nvar BinaryOpType;\n(function(BinaryOpType2) {\n  BinaryOpType2[BinaryOpType2[\"MUL\"] = 0] = \"MUL\";\n  BinaryOpType2[BinaryOpType2[\"ADD\"] = 1] = \"ADD\";\n  BinaryOpType2[BinaryOpType2[\"SUB\"] = 2] = \"SUB\";\n  BinaryOpType2[BinaryOpType2[\"DIV\"] = 3] = \"DIV\";\n  BinaryOpType2[BinaryOpType2[\"EQUAL\"] = 4] = \"EQUAL\";\n  BinaryOpType2[BinaryOpType2[\"GREATER\"] = 5] = \"GREATER\";\n  BinaryOpType2[BinaryOpType2[\"GREATER_EQUAL\"] = 6] = \"GREATER_EQUAL\";\n  BinaryOpType2[BinaryOpType2[\"LESS\"] = 7] = \"LESS\";\n  BinaryOpType2[BinaryOpType2[\"LESS_EQUAL\"] = 8] = \"LESS_EQUAL\";\n  BinaryOpType2[BinaryOpType2[\"LOGICAL_AND\"] = 9] = \"LOGICAL_AND\";\n  BinaryOpType2[BinaryOpType2[\"NOT_EQUAL\"] = 10] = \"NOT_EQUAL\";\n  BinaryOpType2[BinaryOpType2[\"SQUARED_DIFFERENCE\"] = 11] = \"SQUARED_DIFFERENCE\";\n  BinaryOpType2[BinaryOpType2[\"INT_DIV\"] = 12] = \"INT_DIV\";\n  BinaryOpType2[BinaryOpType2[\"POW\"] = 13] = \"POW\";\n  BinaryOpType2[BinaryOpType2[\"PRELU\"] = 14] = \"PRELU\";\n  BinaryOpType2[BinaryOpType2[\"MAX\"] = 15] = \"MAX\";\n  BinaryOpType2[BinaryOpType2[\"MIN\"] = 16] = \"MIN\";\n  BinaryOpType2[BinaryOpType2[\"COMPLEX_MULTIPLY_REAL\"] = 17] = \"COMPLEX_MULTIPLY_REAL\";\n  BinaryOpType2[BinaryOpType2[\"COMPLEX_MULTIPLY_IMAG\"] = 18] = \"COMPLEX_MULTIPLY_IMAG\";\n})(BinaryOpType || (BinaryOpType = {}));\nvar ADD2 = \"return a + b;\";\nvar COMPLEX_MULTIPLY_REAL = \"return areal * breal - aimag * bimag;\";\nvar COMPLEX_MULTIPLY_IMAG = \"return areal * bimag + aimag * breal;\";\nvar DIV2 = \"return a / b;\";\nvar MUL2 = \"return a * b;\";\nvar SQUARED_DIFFERENCE2 = \"return (a - b) * (a - b);\";\nvar SUB2 = \"return a - b;\";\nvar EQUAL2 = \"return f32(a == b);\";\nvar EQUAL_VEC4 = \"return vec4<f32>(a == b);\";\nvar GREATER2 = \"return f32(a > b);\";\nvar GREATER_VEC4 = \"return vec4<f32>(a > b);\";\nvar GREATER_EQUAL2 = \"return f32(a >= b);\";\nvar GREATER_EQUAL_VEC4 = \"return vec4<f32>(a >= b);\";\nvar LESS2 = \"return f32(a < b);\";\nvar LESS_VEC4 = \"return vec4<f32>(a < b);\";\nvar LESS_EQUAL2 = \"return f32(a <= b);\";\nvar LESS_EQUAL_VEC4 = \"return vec4<f32>(a <= b);\";\nvar LOGICAL_AND2 = \"return f32(f32(a) >= 1.0 && f32(b) >= 1.0);\";\nvar LOGICAL_AND_VEC4 = `return (vec4<f32>(a >= vec4<f32>(1.0)) *\n  vec4<f32>(b >= vec4<f32>(1.0)));`;\nvar CHECK_NAN_SNIPPET4 = `\n  if (isnan(a)) { return a; }\n  if (isnan(b)) { return b; }\n  `;\nvar CHECK_NAN_SNIPPET_VEC4 = `\n  if (isNaN.r) {\n    resultTemp.r = uniforms.NAN;\n  }\n  if (isNaN.g) {\n    resultTemp.g = uniforms.NAN;\n  }\n  if (isNaN.b) {\n    resultTemp.b = uniforms.NAN;\n  }\n  if (isNaN.a) {\n    resultTemp.a = uniforms.NAN;\n  }\n  `;\nvar INT_DIV2 = `\n  let s = sign(a) * sign(b);\n  let ia = i32(round(a));\n  let ib = i32(round(b));\n  return f32(idiv(ia, ib, s));\n  `;\nvar INT_DIV_VEC4 = `\n  let ia = vec4<i32>(round(a));\n  let ib = vec4<i32>(round(b));\n  let cond = ib != vec4<i32>(0);\n  var resultTemp = vec4<i32>(0);\n  let s = sign(a) * sign(b);\n\n  // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n  if (cond[0]) {\n    resultTemp[0] = idiv(ia[0], ib[0], s[0]);\n  }\n  if (cond[1]) {\n    resultTemp[1] = idiv(ia[1], ib[1], s[1]);\n  }\n  if (cond[2]) {\n    resultTemp[2] = idiv(ia[2], ib[2], s[2]);\n  }\n  if (cond[3]) {\n    resultTemp[3] = idiv(ia[3], ib[3], s[3]);\n  }\n  return vec4<f32>(resultTemp);\n  `;\nvar NOT_EQUAL2 = \"return f32(a != b);\";\nvar NOT_EQUAL_VEC4 = \"return vec4<f32>(a != b);\";\nvar POW2 = `\n  if(a < 0.0 && floor(b) < b) {\n    return uniforms.NAN;\n  }\n  if (b == 0.0) {\n    return 1.0;\n  }\n  if (round(abs(b) % 2.0) != 1.0) {\n    return pow(abs(a), b);\n  }\n  return sign(a) * pow(abs(a), b);\n  `;\nvar POW_VEC4 = `\n  let isModRound1Bool = vec4<i32>(round(abs(b) % vec4<f32>(2.0))) == vec4<i32>(1);\n  let isModRound1 = vec4<f32>(isModRound1Bool);\n  let multiplier = sign(a) * isModRound1 + (vec4<f32>(1.0) - isModRound1);\n  var resultTemp = multiplier * pow(abs(a), b);\n\n  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\n  let isExpZero = b == vec4<f32>(0.0);\n  if (isExpZero.r) {\n    resultTemp.r = 1.0;\n  }\n  if (isExpZero.g) {\n    resultTemp.g = 1.0;\n  }\n  if (isExpZero.b) {\n    resultTemp.b = 1.0;\n  }\n  if (isExpZero.a) {\n    resultTemp.a = 1.0;\n  }\n  let isNaN = a < vec4<f32>(0.0) & floor(b) < b;\n  ${CHECK_NAN_SNIPPET_VEC4}\n  return resultTemp;\n  `;\nvar PRELU2 = `if (a < 0.0) { return b * a; }  return a;`;\nvar PRELU_VEC4 = `\n  let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));\n  return (aLessThanZero * (b * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);\n  `;\nfunction getMinMaxString(op2, useVec4) {\n  const checkNanSnippet = useVec4 ? CHECK_NAN_SNIPPET_VEC4 : CHECK_NAN_SNIPPET4;\n  return useVec4 ? `\n    var resultTemp = vec4<f32>(${op2}(a, b));\n    let isNaN = isnanVec4(a) | isnanVec4(b);\n    ` + checkNanSnippet + `\n    return resultTemp;\n  ` : checkNanSnippet + `\n    return ${op2}(a, b);\n  `;\n}\nfunction getBinaryOpString(type, useVec4) {\n  switch (type) {\n    case BinaryOpType.MUL:\n      return MUL2;\n    case BinaryOpType.ADD:\n      return ADD2;\n    case BinaryOpType.SUB:\n      return SUB2;\n    case BinaryOpType.DIV:\n      return DIV2;\n    case BinaryOpType.EQUAL:\n      return useVec4 ? EQUAL_VEC4 : EQUAL2;\n    case BinaryOpType.GREATER:\n      return useVec4 ? GREATER_VEC4 : GREATER2;\n    case BinaryOpType.GREATER_EQUAL:\n      return useVec4 ? GREATER_EQUAL_VEC4 : GREATER_EQUAL2;\n    case BinaryOpType.LESS:\n      return useVec4 ? LESS_VEC4 : LESS2;\n    case BinaryOpType.LESS_EQUAL:\n      return useVec4 ? LESS_EQUAL_VEC4 : LESS_EQUAL2;\n    case BinaryOpType.LOGICAL_AND:\n      return useVec4 ? LOGICAL_AND_VEC4 : LOGICAL_AND2;\n    case BinaryOpType.NOT_EQUAL:\n      return useVec4 ? NOT_EQUAL_VEC4 : NOT_EQUAL2;\n    case BinaryOpType.SQUARED_DIFFERENCE:\n      return SQUARED_DIFFERENCE2;\n    case BinaryOpType.INT_DIV:\n      return useVec4 ? INT_DIV_VEC4 : INT_DIV2;\n    case BinaryOpType.PRELU:\n      return useVec4 ? PRELU_VEC4 : PRELU2;\n    case BinaryOpType.MAX:\n      return getMinMaxString(\"max\", useVec4);\n    case BinaryOpType.MIN:\n      return getMinMaxString(\"min\", useVec4);\n    case BinaryOpType.POW:\n      return useVec4 ? POW_VEC4 : POW2;\n    case BinaryOpType.COMPLEX_MULTIPLY_REAL:\n      return COMPLEX_MULTIPLY_REAL;\n    case BinaryOpType.COMPLEX_MULTIPLY_IMAG:\n      return COMPLEX_MULTIPLY_IMAG;\n    default:\n      throw new Error(`BinaryType ${type} is not implemented!`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/unary_op_util.js\nvar UnaryOpType;\n(function(UnaryOpType2) {\n  UnaryOpType2[UnaryOpType2[\"ABS\"] = 0] = \"ABS\";\n  UnaryOpType2[UnaryOpType2[\"CEIL\"] = 1] = \"CEIL\";\n  UnaryOpType2[UnaryOpType2[\"COS\"] = 2] = \"COS\";\n  UnaryOpType2[UnaryOpType2[\"COSH\"] = 3] = \"COSH\";\n  UnaryOpType2[UnaryOpType2[\"ELU\"] = 4] = \"ELU\";\n  UnaryOpType2[UnaryOpType2[\"EXP\"] = 5] = \"EXP\";\n  UnaryOpType2[UnaryOpType2[\"EXPM1\"] = 6] = \"EXPM1\";\n  UnaryOpType2[UnaryOpType2[\"FLOOR\"] = 7] = \"FLOOR\";\n  UnaryOpType2[UnaryOpType2[\"LINEAR\"] = 8] = \"LINEAR\";\n  UnaryOpType2[UnaryOpType2[\"LOG\"] = 9] = \"LOG\";\n  UnaryOpType2[UnaryOpType2[\"LOGICAL_NOT\"] = 10] = \"LOGICAL_NOT\";\n  UnaryOpType2[UnaryOpType2[\"NEG\"] = 11] = \"NEG\";\n  UnaryOpType2[UnaryOpType2[\"RELU\"] = 12] = \"RELU\";\n  UnaryOpType2[UnaryOpType2[\"RELU6\"] = 13] = \"RELU6\";\n  UnaryOpType2[UnaryOpType2[\"LEAKYRELU\"] = 14] = \"LEAKYRELU\";\n  UnaryOpType2[UnaryOpType2[\"RSQRT\"] = 15] = \"RSQRT\";\n  UnaryOpType2[UnaryOpType2[\"SIN\"] = 16] = \"SIN\";\n  UnaryOpType2[UnaryOpType2[\"SINH\"] = 17] = \"SINH\";\n  UnaryOpType2[UnaryOpType2[\"SIGMOID\"] = 18] = \"SIGMOID\";\n  UnaryOpType2[UnaryOpType2[\"SQRT\"] = 19] = \"SQRT\";\n  UnaryOpType2[UnaryOpType2[\"SQUARE\"] = 20] = \"SQUARE\";\n  UnaryOpType2[UnaryOpType2[\"TANH\"] = 21] = \"TANH\";\n  UnaryOpType2[UnaryOpType2[\"TO_INT\"] = 22] = \"TO_INT\";\n})(UnaryOpType || (UnaryOpType = {}));\nvar ABS3 = `return abs(a);`;\nvar CEIL2 = `return ceil(a);`;\nvar COS2 = `return cos(a);`;\nvar COSH2 = `\n  let e2x = exp(-a);\n  return (e2x + 1.0 / e2x) / 2.0;\n`;\nvar EXPM12 = `return exp(a) - 1.0;`;\nvar ELU5 = `if (a >= 0.0) { return a; }  return (exp(a) - 1.0);`;\nvar ELU_VEC4 = `\n  var resFloat = exp(a) - vec4<f32>(1.0);\n  if (a.r >= 0.0) {\n    resFloat.r = a.r;\n  }\n  if (a.g >= 0.0) {\n    resFloat.g = a.g;\n  }\n  if (a.b >= 0.0) {\n    resFloat.b = a.b;\n  }\n  if (a.a >= 0.0) {\n    resFloat.a = a.a;\n  }\n  return resFloat;\n`;\nvar EXP2 = `return exp(a);`;\nvar FLOOR2 = `return floor(a);`;\nvar LINEAR3 = `return a;`;\nvar LOG2 = `if (a < 0.0) { return 1.0/0.0; }\n  return log(a);`;\nvar LOGICAL_NOT2 = `return f32(!(a >= 1.0));`;\nvar NEG2 = `return -a;`;\nvar LEAKYRELU2 = `if (a < 0.0) { return uniforms.alpha * a; } return a;`;\nvar LEAKYRELU_VEC4 = `\n  let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));\n  return (aLessThanZero * (uniforms.alpha * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);\n`;\nvar RELU4 = `return select(a, 0.0, a < 0.0);`;\nvar RELU64 = \"return clamp(a, 0.0, 6.0);\";\nvar RELU6_VEC4 = \"return clamp(a, vec4<f32>(0.0, 0.0, 0.0, 0.0), vec4<f32>(6.0, 6.0, 6.0, 6.0));\";\nvar RELU_VEC4 = `\n  return select(a, vec4<f32>(0.0), a < vec4<f32>(0.0));\n`;\nvar RSQRT2 = `return 1.0/sqrt(a);`;\nvar SIGMOID4 = `return 1.0 / (1.0 + exp(-1.0 * a));`;\nvar SIN2 = `return sin(a);`;\nvar SINH2 = `\n  let e2x = exp(a);\n  return (e2x - 1.0 / e2x) / 2.0;\n`;\nvar SQRT2 = `return sqrt(a);`;\nvar SQUARE2 = `return a * a;`;\nvar TANH2 = `\n  let e2x = exp(-2.0 * abs(a));\n  return sign(a) * (1.0 - e2x) / (1.0 + e2x);\n`;\nvar TO_INT2 = `return f32(i32((a)));`;\nfunction getUnaryOpString(type, useVec4) {\n  switch (type) {\n    case UnaryOpType.ABS:\n      return ABS3;\n    case UnaryOpType.COS:\n      return COS2;\n    case UnaryOpType.COSH:\n      return COSH2;\n    case UnaryOpType.CEIL:\n      return CEIL2;\n    case UnaryOpType.ELU:\n      return useVec4 ? ELU_VEC4 : ELU5;\n    case UnaryOpType.EXP:\n      return EXP2;\n    case UnaryOpType.EXPM1:\n      return EXPM12;\n    case UnaryOpType.FLOOR:\n      return FLOOR2;\n    case UnaryOpType.LINEAR:\n      return LINEAR3;\n    case UnaryOpType.LOG:\n      return LOG2;\n    case UnaryOpType.LOGICAL_NOT:\n      return LOGICAL_NOT2;\n    case UnaryOpType.NEG:\n      return NEG2;\n    case UnaryOpType.LEAKYRELU:\n      return useVec4 ? LEAKYRELU_VEC4 : LEAKYRELU2;\n    case UnaryOpType.RELU:\n      return useVec4 ? RELU_VEC4 : RELU4;\n    case UnaryOpType.RELU6:\n      return useVec4 ? RELU6_VEC4 : RELU64;\n    case UnaryOpType.RSQRT:\n      return RSQRT2;\n    case UnaryOpType.SIGMOID:\n      return SIGMOID4;\n    case UnaryOpType.SIN:\n      return SIN2;\n    case UnaryOpType.SINH:\n      return SINH2;\n    case UnaryOpType.SQRT:\n      return SQRT2;\n    case UnaryOpType.SQUARE:\n      return SQUARE2;\n    case UnaryOpType.TANH:\n      return TANH2;\n    case UnaryOpType.TO_INT:\n      return TO_INT2;\n    default:\n      throw new Error(`BinaryType ${type} is not implemented!`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/activation_util.js\nvar typeSnippet = (component) => {\n  switch (component) {\n    case 1:\n      return \"f32\";\n    case 2:\n      return \"vec2<f32>\";\n    case 3:\n      return \"vec3<f32>\";\n    case 4:\n      return \"vec4<f32>\";\n    default:\n      throw new Error(`${component}-component is not supported.`);\n  }\n};\nfunction activationFnSnippet(activation2, hasPreluActivationWeights = false, packed = false, coordsLength = 3) {\n  if (activation2 === null) {\n    return \"\";\n  }\n  let activationOpSnippet = \"\";\n  if (activation2 === \"linear\") {\n    activationOpSnippet = getUnaryOpString(UnaryOpType.LINEAR);\n  } else if (activation2 === \"relu\") {\n    activationOpSnippet = getUnaryOpString(UnaryOpType.RELU, packed);\n  } else if (activation2 === \"elu\") {\n    activationOpSnippet = getUnaryOpString(UnaryOpType.ELU, packed);\n  } else if (activation2 === \"relu6\") {\n    activationOpSnippet = getUnaryOpString(UnaryOpType.RELU6, packed);\n  } else if (activation2 === \"prelu\") {\n    activationOpSnippet = getBinaryOpString(BinaryOpType.PRELU, packed);\n  } else if (activation2 === \"sigmoid\") {\n    activationOpSnippet = getUnaryOpString(UnaryOpType.SIGMOID, packed);\n  } else if (activation2 === \"leakyrelu\") {\n    activationOpSnippet = getUnaryOpString(UnaryOpType.LEAKYRELU, packed);\n  } else {\n    throw new Error(`Activation ${activation2} has not been implemented for the WebGPU backend.`);\n  }\n  const elementSize = packed ? 4 : 1;\n  const dataType = typeSnippet(elementSize);\n  let activationFnSnippet2 = \"\";\n  if (hasPreluActivationWeights) {\n    activationFnSnippet2 = `\n      fn activation(a : ${dataType}, coords : vec${coordsLength}<i32>) -> ${dataType} {\n        let b = getPreluActivationWeightsByOutputCoords(coords);\n        ${activationOpSnippet}\n      }`;\n  } else {\n    activationFnSnippet2 = `\n      fn activation(a : ${dataType}, coords : vec${coordsLength}<i32>) -> ${dataType} {\n        ${activationOpSnippet}\n      }`;\n  }\n  return activationFnSnippet2;\n}\nfunction biasActivationSnippet(hasBias, activation2) {\n  return `\n      ${hasBias ? \"value = value + getBiasByOutputCoords(coords);\" : \"\"}\n      ${activation2 ? \"value = activation(value, coords);\" : \"\"}\n      `;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/shader_util.js\nfunction symbolicallyComputeStrides2(indicesArr, variableName) {\n  if (Math.max(...indicesArr) > 3) {\n    throw new Error(\"Cannot symbolically compute strides for rank > 4 tensor.\");\n  }\n  const numCoords = indicesArr.length;\n  const shape = indicesArr.map((d) => `${variableName}[${d}]`);\n  const strides = new Array(numCoords - 1);\n  strides[numCoords - 2] = shape[numCoords - 1];\n  for (let i2 = numCoords - 3; i2 >= 0; --i2) {\n    strides[i2] = `(${strides[i2 + 1]} * ${shape[i2 + 1]})`;\n  }\n  return strides;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/webgpu_program.js\nvar compileProgram2 = (device, program, inputsData, output) => {\n  const outputData = { dtype: output.dtype, shape: output.shape };\n  const source = makeShader2(inputsData, outputData, program);\n  const module = device.createShaderModule({ code: source, label: program.constructor.name });\n  const pipeline = device.createComputePipeline({\n    compute: { module, entryPoint: \"main\" },\n    label: program.constructor.name,\n    layout: \"auto\"\n  });\n  return pipeline;\n};\nfunction getCoordsDataType2(rank) {\n  if (rank <= 1) {\n    return \"i32\";\n  } else if (rank === 2) {\n    return `vec2<i32>`;\n  } else if (rank === 3) {\n    return `vec3<i32>`;\n  } else if (rank === 4) {\n    return `vec4<i32>`;\n  } else if (rank === 5) {\n    return `vec5`;\n  } else if (rank === 6) {\n    return `vec6`;\n  } else {\n    throw Error(`GPU for rank ${rank} is not yet supported`);\n  }\n}\nfunction getCoordsXYZ(index) {\n  if (index === 0) {\n    return \"x\";\n  } else if (index === 1) {\n    return \"y\";\n  } else if (index === 2) {\n    return \"z\";\n  } else if (index === 3) {\n    return \"w\";\n  } else if (index === 4) {\n    return \"u\";\n  } else if (index === 5) {\n    return \"v\";\n  } else {\n    throw Error(`Index ${index} is not yet supported`);\n  }\n}\nfunction getMainHeaderAndGlobalIndexString() {\n  return `\n    ${getMainHeaderString()}\n      let index = getGlobalIndex();\n`;\n}\nfunction getMainHeaderString() {\n  return `\n  ${getWorkGroupSizeString()}\n  fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,\n          @builtin(global_invocation_id) GlobalId : vec3<u32>,\n          @builtin(num_workgroups) NumWorkgroups: vec3<u32>) {\n    localId = LocalId;\n    globalId = GlobalId;\n    numWorkgroups = NumWorkgroups;\n`;\n}\nfunction getWorkGroupSizeString() {\n  return `\n  @compute @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)\n`;\n}\nfunction makeShader2(inputInfo, outputData, program) {\n  const prefixSnippets = [];\n  prefixSnippets.push(`\n      const workGroupSizeX = ${program.workGroupSize[0]}u;\n      const workGroupSizeY = ${program.workGroupSize[1]}u;\n      const workGroupSizeZ = ${program.workGroupSize[2]}u;\n\n      var<private> localId: vec3<u32>;\n      var<private> globalId: vec3<u32>;\n      var<private> numWorkgroups: vec3<u32>;\n\n      // Only used when the y/z dimension of workgroup size is 1.\n      fn getGlobalIndex() -> i32 {\n        ${isFlatDispatch(program) ? `  return i32(globalId.x);` : `  let localInvocationIndex = localId.z * workGroupSizeX * workGroupSizeY +\n                   localId.y * workGroupSizeX + localId.x;\n               let workGroupID = (globalId - localId)/vec3<u32>(\n                   workGroupSizeX, workGroupSizeY, workGroupSizeZ);\n\n               return i32((workGroupID.z * numWorkgroups.x * numWorkgroups.y +\n                   workGroupID.y * numWorkgroups.x + workGroupID.x) *\n                   (workGroupSizeX * workGroupSizeY * workGroupSizeZ) +\n                   localInvocationIndex);\n        `}\n      }\n    `);\n  if (program.isFromPixels) {\n    prefixSnippets.push(`\n        struct Uniform {\n          size            : i32,\n          numChannels     : i32,\n          outShapeStrides : vec2<i32>,\n        };\n\n        @group(0) @binding(0) var<storage, read_write> result: array<${mapToWgslTypes(outputData.dtype, program.isVec4)}>;\n        @group(0) @binding(2) var<uniform> uniforms: Uniform;\n      `);\n    return [\n      commonSnippet,\n      prefixSnippets.join(\"\\n\"),\n      getCoordsFromIndexSnippet(outputData.shape),\n      program.getUserCode()\n    ].join(\"\\n\");\n  }\n  let preMemberIsStruct = false;\n  let currentMemberIsStruct = false;\n  let uniformDeclaration = \"struct Uniforms { NAN : f32, \";\n  program.variableNames.forEach((x, i2) => {\n    const perDataType = getCoordsDataType2(inputInfo[i2].shape.length);\n    if (perDataType === \"vec5\" || perDataType === \"vec6\") {\n      currentMemberIsStruct = true;\n    }\n    if (preMemberIsStruct || currentMemberIsStruct) {\n      uniformDeclaration += `@align(16) `;\n    }\n    preMemberIsStruct = currentMemberIsStruct;\n    uniformDeclaration += `${x.charAt(0).toLowerCase() + x.slice(1)}Shape : ${perDataType}, `;\n  });\n  const outputDataType = getCoordsDataType2(outputData.shape.length);\n  currentMemberIsStruct = outputDataType === \"vec5\" || outputDataType === \"vec6\";\n  if (preMemberIsStruct || currentMemberIsStruct) {\n    uniformDeclaration += `@align(16) `;\n  }\n  preMemberIsStruct = currentMemberIsStruct;\n  uniformDeclaration += `outShape : ${outputDataType}, `;\n  const stridesLength = outputData.shape.length - 1;\n  const stridesDataType = getCoordsDataType2(stridesLength);\n  currentMemberIsStruct = stridesDataType === \"vec5\" || stridesDataType === \"vec6\";\n  if (preMemberIsStruct || currentMemberIsStruct) {\n    uniformDeclaration += `@align(16) `;\n  }\n  preMemberIsStruct = currentMemberIsStruct;\n  uniformDeclaration += `\n         outShapeStrides: ${stridesDataType}, `;\n  if (program.size) {\n    if (preMemberIsStruct) {\n      uniformDeclaration += `@align(16) `;\n    }\n    preMemberIsStruct = false;\n    uniformDeclaration += \"size : i32, \";\n  }\n  if (program.uniforms) {\n    if (preMemberIsStruct) {\n      uniformDeclaration += `@align(16) `;\n    }\n    uniformDeclaration += program.uniforms;\n  }\n  uniformDeclaration += \"};\";\n  prefixSnippets.push(uniformDeclaration);\n  if (program.atomic) {\n    prefixSnippets.push(`\n      @group(0) @binding(0) var<storage, read_write> result: array<atomic<i32>>;\n    `);\n  } else {\n    prefixSnippets.push(`\n      @group(0) @binding(0) var<storage, read_write> result: array<${mapToWgslTypes(outputData.dtype, program.isVec4)}>;\n    `);\n  }\n  program.variableNames.forEach((x, i2) => {\n    prefixSnippets.push(`\n      @group(0) @binding(${1 + i2}) var<storage, read> ${x}: array<${program.variableTypes ? program.variableTypes[i2] : mapToWgslTypes(inputInfo[i2].dtype, program.isVec4)}>;\n        `);\n  });\n  if (uniformDeclaration !== \"\") {\n    prefixSnippets.push(`\n      @group(0) @binding(${1 + program.variableNames.length}) var<uniform> uniforms: Uniforms;\n      `);\n  }\n  const coordsSnippet = getOutputCoordsSnippet(outputData.shape, program.dispatchLayout);\n  const sources = [\n    commonSnippet,\n    prefixSnippets.join(\"\\n\"),\n    getCoordsFromIndexSnippet(outputData.shape),\n    coordsSnippet,\n    getOutputIndexFromCoordsSnippet(outputData.shape.length)\n  ];\n  if (!program.atomic) {\n    sources.push(setOutputSnippet(outputData.shape, outputData.dtype, program.isVec4));\n  }\n  const inputSnippet = inputInfo.map((x, i2) => getInputSnippet(x, outputData.shape, program.variableTypes ? program.variableTypes[i2] === \"vec4<f32>\" : program.isVec4, program.dispatchLayout.x.length === outputData.shape.length)).join(\"\\n\");\n  sources.push(inputSnippet);\n  sources.push(program.getUserCode());\n  const source = sources.join(\"\\n\");\n  return source;\n}\nfunction makeShaderKey2(program, shapes, inputsData, output) {\n  let key = program.shaderKey;\n  if (program.isFromPixels) {\n    return key;\n  }\n  const types = inputsData.map((d) => d.dtype).concat(output.dtype);\n  const broadcastDims = inputsData.map((d) => backend_util_exports.getBroadcastDims(d.shape, output.shape));\n  const inputShapesEqualsOutShape = inputsData.map((d) => util_exports.arraysEqual(d.shape, output.shape)).join(\"_\");\n  const broadcastDimsKey = broadcastDims.map((d) => d.join(\"_\")).join(\";\");\n  const flatDispatchString = isFlatDispatch(program) ? \"flatDispatch\" : \"\";\n  key += \"_\" + (program.workGroupSize ? program.workGroupSize.join(\",\") : \"\") + shapes.map((shape) => shape.length).join(\",\") + types.join(\",\") + program.variableNames.join(\",\") + broadcastDimsKey + inputShapesEqualsOutShape + flatDispatchString;\n  return key;\n}\nvar commonSnippet = `\n  struct vec5 {x: i32, y: i32, z: i32, w: i32, u: i32};\n  struct vec6 {x: i32, y: i32, z: i32, w: i32, u: i32, v: i32};\n\n  // Checks whether coordinates lie within the bounds of the shape.\n  fn coordsInBounds2D(coord : vec2<i32>, shape : vec2<i32>) -> bool {\n    return all(coord >= vec2<i32>(0)) && all(coord < shape);\n  }\n  fn coordsInBounds3D(coord : vec3<i32>, shape : vec3<i32>) -> bool {\n    return all(coord >= vec3<i32>(0)) && all(coord < shape);\n  }\n  fn coordsInBounds4D(coord : vec4<i32>, shape : vec4<i32>) -> bool {\n    return all(coord >= vec4<i32>(0)) && all(coord < shape);\n  }\n\n  fn getIndexFromCoords1D(coord : i32, shape : i32) -> i32 {\n    return coord;\n  }\n  fn getIndexFromCoords2D(coords : vec2<i32>, shape : vec2<i32>) -> i32 {\n    return dot(coords, vec2<i32>(shape.y, 1));\n  }\n  fn getIndexFromCoords3D(coords : vec3<i32>, shape : vec3<i32>) -> i32 {\n    return dot(coords, vec3<i32>(shape.y * shape.z, shape.z, 1));\n  }\n  fn getIndexFromCoords4D(coords : vec4<i32>, shape : vec4<i32>) -> i32 {\n    return dot(coords, vec4<i32>(\n        shape.y * shape.z * shape.w, shape.z * shape.w, shape.w, 1));\n  }\n  fn getIndexFromCoords5D(coords : vec5, shape : vec5) -> i32 {\n    let shapeStrides: vec5 = vec5(shape.y * shape.z * shape.w * shape.u, shape.z * shape.w * shape.u, shape.w * shape.u, shape.u, 1);\n    return coords.x*shapeStrides.x + coords.y*shapeStrides.y + coords.z*shapeStrides.z + coords.w*shapeStrides.w + coords.u*shapeStrides.u;\n  }\n  fn getIndexFromCoords6D(coords : vec6, shape : vec6) -> i32 {\n    let shapeStrides: vec6 = vec6(shape.y * shape.z * shape.w * shape.u * shape.v, shape.z * shape.w * shape.u * shape.v, shape.w * shape.u * shape.v, shape.u * shape.v, shape.v, 1);\n    return coords.x*shapeStrides.x + coords.y*shapeStrides.y + coords.z*shapeStrides.z + coords.w*shapeStrides.w + coords.u*shapeStrides.u + coords.v*shapeStrides.v;\n  }\n\n  fn idiv(a: i32, b: i32, sign: f32) -> i32 {\n    var res: i32 = a / b;\n    let mod: i32 = a % b;\n    if (sign < 0. && mod != 0) {\n      res = res - 1;\n    }\n    return res;\n  }\n\n  // NaN defination in IEEE 754-1985 is :\n  //   - sign = either 0 or 1.\n  //   - biased exponent = all 1 bits.\n  //   - fraction = anything except all 0 bits (since all 0 bits represents infinity).\n  // https://en.wikipedia.org/wiki/IEEE_754-1985#Representation_of_non-numbers\n  fn isnan(val: f32) -> bool {\n    let floatToUint: u32 = bitcast<u32>(val);\n    return (floatToUint & 0x7fffffffu) > 0x7f800000u;\n  }\n  fn isnanVec4(val : vec4<f32>) -> vec4<bool> {\n    return vec4<bool>(isnan(val[0]), isnan(val[1]), isnan(val[2]), isnan(val[3]));\n  }\n`;\nfunction getCoordsFromIndexSnippet(shape) {\n  const rank = shape.length;\n  if (rank <= 1) {\n    return `fn getCoordsFromIndex(index : i32) -> i32 { return index; }`;\n  }\n  const strides = util_exports.computeStrides(shape);\n  const dtype = getCoordsDataType2(rank);\n  const coords3 = [];\n  for (let i2 = 0; i2 < rank; i2++) {\n    coords3.push(`d${i2}`);\n  }\n  if (strides.length === 1) {\n    return `    fn getCoordsFromIndex(index : i32) -> vec2<i32> {\n      let d0 = index / uniforms.outShapeStrides; let d1 = index - d0 * uniforms.outShapeStrides;\n      return vec2<i32>(d0, d1);\n    }`;\n  }\n  let snippet;\n  snippet = \"var index2 = index;\" + strides.map((_, i2) => {\n    const line1 = `let ${coords3[i2]} = index2 / uniforms.outShapeStrides.${getCoordsXYZ(i2)}`;\n    const line2 = i2 === strides.length - 1 ? `let ${coords3[i2 + 1]} = index2 - ${coords3[i2]} * uniforms.outShapeStrides.${getCoordsXYZ(i2)}` : `index2 = index2 - ${coords3[i2]} * uniforms.outShapeStrides.${getCoordsXYZ(i2)}`;\n    return `${line1}; ${line2};`;\n  }).join(\"\");\n  return `\n    fn getCoordsFromIndex(index : i32) -> ${dtype} {\n      ${snippet}\n      return ${dtype}(${coords3.join(\",\")});\n    }\n  `;\n}\nfunction getInputAtCoordsSnippet(inputInfo, isVec4) {\n  const texName = inputInfo.name;\n  const rank = inputInfo.shape.length;\n  const type = getCoordsDataType2(rank);\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const dims = [\"d0\", \"d1\", \"d2\", \"d3\", \"d4\", \"d5\"].slice(0, rank);\n  const inputs = dims.map((d) => `${d} : i32`).join(\", \");\n  if (rank < 1) {\n    if (isVec4) {\n      return `\n        fn ${funcName}() -> vec4<f32> {\n          return vec4<f32>(${texName}[0]);\n        }\n      `;\n    }\n    return `\n      fn ${funcName}() ->f32 {\n        return f32(${texName}[0]);\n      }\n    `;\n  }\n  const shapeStr = `uniforms.${texName.charAt(0).toLowerCase() + texName.slice(1)}Shape`;\n  let rankStr = `${rank}D`;\n  if (rank === 0) {\n    rankStr = \"1D\";\n  }\n  if (isVec4) {\n    return `\n      fn ${funcName}(${inputs}) -> vec4<f32> {\n        return vec4<f32>(${texName}[getIndexFromCoords${rankStr}(${type}(${dims.join(\",\")}),\n          ${shapeStr}) / 4]);\n      }\n      `;\n  }\n  return `\n    fn ${funcName}(${inputs}) -> f32 {\n      return f32(${texName}[getIndexFromCoords${rankStr}(${type}(${dims.join(\",\")}),\n        ${shapeStr})]);\n    }\n   `;\n}\nfunction getInputByOutputSnippet(inputInfo, outShape, isVec4, isFlatDispatchLayout) {\n  const texName = inputInfo.name;\n  const texFuncSnippet = texName.charAt(0).toUpperCase() + texName.slice(1);\n  const funcName = \"get\" + texFuncSnippet + \"ByOutput\";\n  const inRank = inputInfo.shape.length;\n  const outRank = outShape.length;\n  const type = getCoordsDataType2(outRank);\n  if (util_exports.arraysEqual(inputInfo.shape, outShape) && isFlatDispatchLayout) {\n    if (isVec4) {\n      return `\n      fn ${funcName}Index(globalIndex : i32) -> vec4<f32> {\n        return vec4<f32>(${texName}[globalIndex]);\n      }\n\n      fn ${funcName}Coords(coords : ${type}) -> vec4<f32> {\n        return vec4<f32>(${texName}[${outRank > 1 ? \"getOutputIndexFromCoords(coords)\" : \"coords\"} / 4]);\n      }\n      `;\n    } else {\n      return `\n    fn ${funcName}Index(globalIndex : i32) -> f32 {\n      return f32(${texName}[globalIndex]);\n    }\n\n    fn ${funcName}Coords(coords : ${type}) -> f32 {\n      return f32(${texName}[${outRank > 1 ? \"getOutputIndexFromCoords(coords)\" : \"coords\"}]);\n    }\n    `;\n    }\n  }\n  const broadcastDims = backend_util_exports.getBroadcastDims(inputInfo.shape, outShape);\n  const rankDiff = outRank - inRank;\n  let coordsSnippet = \"\";\n  if (inRank === 0) {\n    if (isVec4) {\n      return `\n    fn ${funcName}Index(globalIndex : i32) -> vec4<f32> {\n      return get${texFuncSnippet}();\n    }\n\n    fn ${funcName}Coords(coords : ${type}) -> vec4<f32> {\n      return get${texFuncSnippet}();\n    }\n  `;\n    }\n    return `\n    fn ${funcName}Index(globalIndex : i32) -> f32{\n      return get${texFuncSnippet}();\n    }\n\n    fn ${funcName}Coords(coords : ${type}) -> f32{\n      return get${texFuncSnippet}();\n    }\n  `;\n  } else {\n    if (outRank < 2 && broadcastDims.length >= 1) {\n      coordsSnippet = \"coords = 0;\";\n    } else {\n      coordsSnippet = broadcastDims.map((d) => `coords.${getCoordsXYZ(d + rankDiff)} = 0;`).join(\"\\n\");\n    }\n  }\n  let unpackedCoordsSnippet = \"\";\n  if (outRank < 2 && inRank > 0) {\n    unpackedCoordsSnippet = \"coords\";\n  } else {\n    if (outRank > 1) {\n      const coordsType = getCoordsDataType2(inRank);\n      const coordsValues = inputInfo.shape.map((s2, i2) => `coords.${getCoordsXYZ(i2 + rankDiff)}`).join(\", \");\n      unpackedCoordsSnippet = `${coordsType}(${coordsValues})`;\n    } else {\n      unpackedCoordsSnippet = \"coords\";\n    }\n  }\n  const shapeStr = `uniforms.${texName.charAt(0).toLowerCase() + texName.slice(1)}Shape`;\n  const rankStr = `${inRank}D`;\n  if (isVec4) {\n    return `\n    fn ${funcName}Index(globalIndex : i32) -> vec4<f32> {\n      var coords = getCoordsFromIndex(globalIndex);\n      ${coordsSnippet}\n      return ${texName}[getIndexFromCoords${rankStr}(${unpackedCoordsSnippet}, ${shapeStr}) / 4];\n    }\n\n    fn ${funcName}Coords(coordsIn : ${type}) -> vec4<f32> {\n      var coords = coordsIn;\n      ${coordsSnippet}\n      return ${texName}[getIndexFromCoords${rankStr}(${unpackedCoordsSnippet}, ${shapeStr}) / 4];\n    }\n  `;\n  }\n  return `\n  fn ${funcName}Index(globalIndex : i32) -> f32 {\n    var coords = getCoordsFromIndex(globalIndex);\n    ${coordsSnippet}\n    return f32(${texName}[getIndexFromCoords${rankStr}(${unpackedCoordsSnippet}, ${shapeStr})]);\n  }\n\n  fn ${funcName}Coords(coordsIn : ${type}) -> f32 {\n    var coords = coordsIn;\n    ${coordsSnippet}\n    return f32(${texName}[getIndexFromCoords${rankStr}(${unpackedCoordsSnippet}, ${shapeStr})]);\n  }\n`;\n}\nfunction getInputSnippet(inputInfo, outShape, isVec4, isFlatDispatchLayout) {\n  let res = getInputAtCoordsSnippet(inputInfo, isVec4);\n  const inShape = inputInfo.shape;\n  if (inShape.length <= outShape.length) {\n    res += getInputByOutputSnippet(inputInfo, outShape, isVec4, isFlatDispatchLayout);\n  }\n  return res;\n}\nfunction getOutputCoordsSnippet(outShape, dispatchLayout) {\n  const { x, y = [], z = [] } = dispatchLayout;\n  const outRank = outShape.length;\n  if (x.length === outRank) {\n    const dtype2 = getCoordsDataType2(outRank);\n    const snippet2 = `fn getOutputCoords() -> ${dtype2}{\n    let globalIndex = getGlobalIndex();\n    return getCoordsFromIndex(globalIndex);\n  }\n  `;\n    return snippet2;\n  }\n  let gatherDimensionsStr = \"\";\n  const dims = [x, y, z];\n  let rank = 0;\n  for (let i2 = 0; i2 < dims.length; i2++) {\n    const arr = dims[i2];\n    if (arr.length === 0) {\n      continue;\n    }\n    rank += arr.length;\n    if (arr.length === 1) {\n      gatherDimensionsStr += `let d${arr[0]} = i32(globalId[${i2}]);`;\n    } else {\n      const strides = symbolicallyComputeStrides2(arr, \"uniforms.outShape\");\n      gatherDimensionsStr += `var index${i2} = i32(globalId[${i2}]);`;\n      for (let j = 0; j < strides.length; j++) {\n        gatherDimensionsStr += `let d${arr[j]} = index${i2} / ${strides[j]};`;\n        if (j === strides.length - 1) {\n          gatherDimensionsStr += `let d${arr[j + 1]} = index${i2} - d${arr[j]} * ${strides[j]};`;\n        } else {\n          gatherDimensionsStr += `index${i2} = index${i2} - d${arr[j]} * ${strides[j]};`;\n        }\n      }\n    }\n  }\n  const dimensions = [];\n  for (let i2 = 0; i2 < rank; i2++) {\n    dimensions.push(`d${i2}`);\n  }\n  const dtype = getCoordsDataType2(rank);\n  let snippet = `fn getOutputCoords() -> ${dtype} {\n  ${gatherDimensionsStr}\n`;\n  if (dimensions.length === 0) {\n    snippet += `return ${dtype}(0); }`;\n  } else {\n    snippet += `return ${dtype}(${dimensions.join(\",\")}); }`;\n  }\n  return snippet;\n}\nfunction getOutputIndexFromCoordsSnippet(outRank) {\n  let snippet = \"\";\n  switch (outRank) {\n    case 0:\n    case 1:\n      snippet += `\n        fn getOutputIndexFromCoords(coords : i32) -> i32 {\n          return coords;\n        }\n        `;\n      break;\n    case 2:\n      snippet += `\n        fn getOutputIndexFromCoords(coords : vec2<i32>) -> i32 {\n          return dot(coords, vec2<i32>(uniforms.outShapeStrides, 1));\n        }\n        `;\n      break;\n    case 3:\n      snippet += `\n        fn getOutputIndexFromCoords(coords : vec3<i32>) -> i32 {\n          return dot(coords, vec3<i32>(uniforms.outShapeStrides.x, uniforms.outShapeStrides.y, 1));\n        }\n        `;\n      break;\n    case 4:\n      snippet += `\n        fn getOutputIndexFromCoords(coords : vec4<i32>) -> i32 {\n          return dot(coords, vec4<i32>(\n            uniforms.outShapeStrides.x, uniforms.outShapeStrides.y, uniforms.outShapeStrides.z, 1));\n        }\n        `;\n      break;\n    case 5:\n      snippet += `\n        fn getOutputIndexFromCoords(coords : vec5) -> i32 {\n          return coords.x * uniforms.outShapeStrides.x +\n              coords.y * uniforms.outShapeStrides.y +\n              coords.z * uniforms.outShapeStrides.z +\n              coords.w * uniforms.outShapeStrides.w +\n              coords.u;\n        }\n        `;\n      break;\n    case 6:\n      snippet += `\n        fn getOutputIndexFromCoords(coords : vec6) -> i32 {\n          return coords.x * uniforms.outShapeStrides.x +\n              coords.y * uniforms.outShapeStrides.y +\n              coords.z * uniforms.outShapeStrides.z +\n              coords.w * uniforms.outShapeStrides.w +\n              coords.u * uniforms.outShapeStrides.u +\n              coords.v;\n        }\n        `;\n      break;\n    default:\n      util_exports.assert(false, () => `Unsupported ${outRank}D shape`);\n      break;\n  }\n  return snippet;\n}\nfunction isFlatDispatch(program) {\n  return program.dispatch[1] === 1 && program.dispatch[2] === 1;\n}\nfunction mapToWgslTypes(type, isVec4) {\n  if (type === \"float32\") {\n    return isVec4 ? \"vec4<f32>\" : \"f32\";\n  } else if (type === \"int32\") {\n    return isVec4 ? \"vec4<i32>\" : \"i32\";\n  } else if (type === \"bool\") {\n    return isVec4 ? \"vec4<i32>\" : \"i32\";\n  }\n  return type;\n}\nfunction setOutputSnippet(outShape, outBufferType, isVec4) {\n  const outRank = outShape.length;\n  const wgslType = mapToWgslTypes(outBufferType, isVec4);\n  let snippet;\n  if (isVec4) {\n    snippet = `fn setOutputAtIndex(flatIndex : i32, value : vec4<f32>) {\n      result[flatIndex] = ${wgslType}(value);\n    }\n    fn setOutputAtIndexI32(flatIndex : i32, value : vec4<i32>) {\n      result[flatIndex] = ${wgslType}(value);\n    }`;\n  } else {\n    snippet = `fn setOutputAtIndex(flatIndex : i32, value : f32) {\n      result[flatIndex] = ${wgslType}(value);\n    }\n    fn setOutputAtIndexI32(flatIndex : i32, value : i32) {\n      result[flatIndex] = ${wgslType}(value);\n    }`;\n  }\n  if (outRank >= 2) {\n    const dims = [\"d0\", \"d1\", \"d2\", \"d3\", \"d4\", \"d5\"].slice(0, outRank);\n    const type = getCoordsDataType2(outRank);\n    if (isVec4) {\n      snippet += `\n      fn setOutputAtCoords(${dims.map((d) => `${d} : i32`).join(\", \")}, value : vec4<f32>) {\n        let flatIndex = getOutputIndexFromCoords(${type}(${dims.join(\", \")}));\n        setOutputAtIndex(flatIndex / 4, value);\n      }\n      fn setOutputAtCoordsI32(${dims.map((d) => `${d} : i32`).join(\", \")}, value : vec4<i32>) {\n        let flatIndex = getOutputIndexFromCoords(${type}(${dims.join(\", \")}));\n        setOutputAtIndexI32(flatIndex / 4, value);\n      }\n    `;\n    } else {\n      snippet += `\n      fn setOutputAtCoords(${dims.map((d) => `${d} : i32`).join(\", \")}, value : f32) {\n        let flatIndex = getOutputIndexFromCoords(${type}(${dims.join(\", \")}));\n        setOutputAtIndex(flatIndex, value);\n      }\n      fn setOutputAtCoordsI32(${dims.map((d) => `${d} : i32`).join(\", \")}, value : i32) {\n        let flatIndex = getOutputIndexFromCoords(${type}(${dims.join(\", \")}));\n        setOutputAtIndexI32(flatIndex, value);\n      }\n    `;\n    }\n  }\n  return snippet;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/webgpu_util.js\nvar webgpu_util_exports = {};\n__export(webgpu_util_exports, {\n  ArrayBufferToTypedArray: () => ArrayBufferToTypedArray,\n  GPUBytesPerElement: () => GPUBytesPerElement,\n  MatMulProgramType: () => MatMulProgramType,\n  computeDispatch: () => computeDispatch,\n  computeWorkGroupSizeForConv2d: () => computeWorkGroupSizeForConv2d,\n  computeWorkGroupSizeForMatMul: () => computeWorkGroupSizeForMatMul,\n  computeWorkPerThreadForConv2d: () => computeWorkPerThreadForConv2d,\n  flatDispatchLayout: () => flatDispatchLayout,\n  isWebGPUSupported: () => isWebGPUSupported,\n  tilesFitEvenlyIntoShape: () => tilesFitEvenlyIntoShape\n});\nvar arrayProduct = (arr) => {\n  let product = 1;\n  for (let i2 = 0; i2 < arr.length; i2++) {\n    product *= arr[i2];\n  }\n  return product;\n};\nfunction tilesFitEvenlyIntoShape(tileSize, shape) {\n  if (tileSize.length !== shape.length) {\n    throw new Error(`Cannot compute whether rank ${tileSize.length} tiles fit evenly into rank ${shape.length} shape - ranks must match.`);\n  }\n  return shape.every((dim, dimIdx) => dim % tileSize[dimIdx] === 0);\n}\nfunction computeDispatch(layout, outputShape, workGroupSize = [1, 1, 1], elementsPerThread = [1, 1, 1]) {\n  const [dispatchX, dispatchY, dispatchZ] = [\n    Math.ceil(arrayProduct(layout.x.map((d) => outputShape[d])) / (workGroupSize[0] * elementsPerThread[0])),\n    layout.y ? Math.ceil(arrayProduct(layout.y.map((d) => outputShape[d])) / (workGroupSize[1] * elementsPerThread[1])) : 1,\n    layout.z ? Math.ceil(arrayProduct(layout.z.map((d) => outputShape[d])) / (workGroupSize[2] * elementsPerThread[2])) : 1\n  ];\n  return [dispatchX, dispatchY, dispatchZ];\n}\nfunction computeWorkGroupSizeForConv2d(layout, outputShape, isVec4 = false) {\n  if (isVec4) {\n    return [8, 8, 1];\n  }\n  const dim0 = arrayProduct(layout.x.map((d) => outputShape[d]));\n  const dim1 = arrayProduct(layout.y.map((d) => outputShape[d]));\n  if (dim0 <= 4) {\n    return [4, 16, 1];\n  }\n  if (dim1 <= 4) {\n    return [16, 4, 1];\n  }\n  return [16, 16, 1];\n}\nfunction computeWorkGroupSizeForMatMul(dimAOuter, dimInner, dimBOuter) {\n  if (dimAOuter === 1) {\n    return [32, 1, 1];\n  } else if (dimBOuter === 1) {\n    return [1, 32, 1];\n  }\n  return [8, 8, 1];\n}\nfunction computeWorkPerThreadForConv2d(layout, outputShape, isVec4 = false) {\n  if (isVec4) {\n    return [4, 4, 1];\n  }\n  const dim0 = arrayProduct(layout.x.map((d) => outputShape[d]));\n  const dim1 = arrayProduct(layout.y.map((d) => outputShape[d]));\n  if (dim0 <= 4) {\n    return [1, 2, 1];\n  }\n  if (dim1 <= 4) {\n    return [2, 1, 1];\n  }\n  return [2, 2, 1];\n}\nfunction flatDispatchLayout(shape) {\n  return { x: shape.map((d, i2) => i2) };\n}\nfunction GPUBytesPerElement(dtype) {\n  if (dtype === \"float32\" || dtype === \"int32\" || dtype === \"bool\" || dtype === \"string\") {\n    return 4;\n  } else if (dtype === \"complex64\") {\n    return 8;\n  } else {\n    throw new Error(`Unknown dtype ${dtype}`);\n  }\n}\nfunction ArrayBufferToTypedArray(data, dtype) {\n  if (dtype === \"float32\") {\n    return new Float32Array(data);\n  } else if (dtype === \"int32\") {\n    return new Int32Array(data);\n  } else if (dtype === \"bool\" || dtype === \"string\") {\n    return Uint8Array.from(new Int32Array(data));\n  } else {\n    throw new Error(`Unknown dtype ${dtype}`);\n  }\n}\nfunction isWebGPUSupported() {\n  return (typeof window !== \"undefined\" || typeof WorkerGlobalScope !== \"undefined\") && !!navigator.gpu;\n}\nvar MatMulProgramType;\n(function(MatMulProgramType2) {\n  MatMulProgramType2[MatMulProgramType2[\"MatMulPackedVec4Program\"] = 0] = \"MatMulPackedVec4Program\";\n  MatMulProgramType2[MatMulProgramType2[\"MatMulReduceProgram\"] = 1] = \"MatMulReduceProgram\";\n  MatMulProgramType2[MatMulProgramType2[\"MatMulSplitKProgram\"] = 2] = \"MatMulSplitKProgram\";\n  MatMulProgramType2[MatMulProgramType2[\"MatMulSmallOutputSizeProgram\"] = 3] = \"MatMulSmallOutputSizeProgram\";\n  MatMulProgramType2[MatMulProgramType2[\"MatMulPackedProgram\"] = 4] = \"MatMulPackedProgram\";\n  MatMulProgramType2[MatMulProgramType2[\"MatMulMax\"] = 5] = \"MatMulMax\";\n})(MatMulProgramType || (MatMulProgramType = {}));\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/matmul_packed_webgpu.js\nfunction matMulReadFnSource(batchAEqualOne, batchBEqualOne, transposeA, transposeB, fitAOuter = false, fitBOuter = false, fitInner = false, component = 1) {\n  util_exports.assert(transposeA && component === 1 || !transposeA, () => `transposeA ${transposeA} is not compatible with component size ${component}`);\n  const sampleA = `\n      let batch = ${batchAEqualOne ? \"0\" : \"batchIn\"};\n      let batchASize = uniforms.aShape[1] * uniforms.aShape[2];\n      ${transposeA ? `value = A[(batch * batchASize + col * uniforms.aShape[2] + row) / ${component}];` : `value = A[(batch * batchASize + row * uniforms.aShape[2] + col) / ${component}];`}\n\n    `;\n  let sampleB;\n  if (transposeB === false) {\n    sampleB = `value = B[(batch * batchBSize + row * uniforms.bShape[2] + col) / ${component}];`;\n  } else {\n    sampleB = `value = B[(batch * batchBSize + col * uniforms.bShape[2] + row) / ${component}];`;\n  }\n  return `\n  fn mm_readA(batchIn: i32, row: i32, colIn: i32) -> ${typeSnippet(component)} {\n    var value = ${typeSnippet(component)}(0.0);\n    let col = colIn * ${component};\n    ${fitAOuter && fitInner ? sampleA : `\n    ${transposeA ? `if(row < uniforms.dimAOuter && col < uniforms.dimInner)` : `if(row < uniforms.aShape[1] && col < uniforms.aShape[2])`}\n    {\n      ${sampleA}\n    }\n    `}\n    return value;\n  }\n\n  fn mm_readB(batchIn: i32, row: i32, colIn: i32) -> ${typeSnippet(component)} {\n    let col = colIn * ${component};\n    let batch = ${batchBEqualOne ? \"0\" : \"batchIn\"};\n    let batchBSize = uniforms.bShape[1] * uniforms.bShape[2];\n    var value = ${typeSnippet(component)}(0.0);\n    ${sampleB}\n    return value;\n  }\n  `;\n}\nfunction matMulReadWriteFnSource(hasBias, activation2, batchAEqualOne, batchBEqualOne, transposeA, transposeB, fitAOuter = false, fitBOuter = false, fitInner = false, component = 1) {\n  return `\n  ${matMulReadFnSource(batchAEqualOne, batchBEqualOne, transposeA, transposeB, fitAOuter, fitBOuter, fitInner, component)}\n  fn mm_write(batch: i32, row: i32, colIn: i32, valueIn: ${typeSnippet(component)}) {\n    let col = colIn * ${component};\n    ${fitAOuter && fitBOuter ? \"\" : \"if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)\"}\n    {\n      var value = valueIn;\n      let coords = vec3<i32>(batch, row, col);\n      ${biasActivationSnippet(hasBias, activation2)}\n      setOutputAtCoords(coords[0], coords[1], coords[2], value);\n    }\n  }\n  `;\n}\nvar writeDataToSubASnippet = (transpose6) => {\n  if (transpose6) {\n    return `\n        mm_Asub[inputRow][inputCol] = mm_readA(batch,\n          t * TileInner + inputRow,\n          globalRowStart + inputCol);\n        `;\n  } else {\n    return `\n        mm_Asub[inputRow][inputCol] = mm_readA(batch,\n          globalRowStart + inputRow,\n          t * TileInner + inputCol);\n        `;\n  }\n};\nvar readDataFromSubASnippet = (transposeA) => {\n  return transposeA ? \"let ACached = mm_Asub[k][tileRow + innerRow];\" : \"let ACached = mm_Asub[tileRow + innerRow][k];\";\n};\nfunction makeMatMulPackedSource(workPerThread, workGroupSize, transposeA = false, tileInner = 32) {\n  const tileAOuter = workPerThread[1] * workGroupSize[1];\n  const tileBOuter = workPerThread[0] * workGroupSize[0];\n  const tileAWidth = transposeA ? tileAOuter : tileInner;\n  const tileAHight = transposeA ? tileInner : tileAOuter;\n  util_exports.assert(tileAHight % workGroupSize[1] === 0 && tileAWidth % workGroupSize[0] === 0 && tileInner % workGroupSize[1] === 0, () => `tileAHight ${tileAHight} must be divisible by workGroupSize[1]${workGroupSize[1]}, tileAWidth ${tileAWidth} must be divisible by workGroupSize[0]${workGroupSize[0]}, tileInner ${tileInner} must be divisible by workGroupSize[1]${workGroupSize[1]}`);\n  const rowPerThreadA = tileAHight / workGroupSize[1];\n  const colPerThreadA = tileAWidth / workGroupSize[0];\n  const rowPerThreadB = tileInner / workGroupSize[1];\n  return `\n    var<workgroup> mm_Asub : array<array<f32, ${tileAWidth}>, ${tileAHight}>;\n    var<workgroup> mm_Bsub : array<array<f32, ${tileBOuter}>, ${tileInner}>;\n    const RowPerThread = ${workPerThread[1]};\n    const ColPerThread = ${workPerThread[0]};\n    const TileInner = ${tileInner};\n\n    @compute @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)\n    fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,\n            @builtin(global_invocation_id) GlobalId : vec3<u32>,\n            @builtin(num_workgroups) NumWorkgroups: vec3<u32>,\n            @builtin(workgroup_id) workgroupId: vec3<u32>) {\n      localId = LocalId;\n      globalId = GlobalId;\n      numWorkgroups = NumWorkgroups;\n\n      let tileRow = i32(localId.y) * RowPerThread;\n      let tileCol = i32(localId.x) * ColPerThread;\n\n      let globalRow = i32(globalId.y) * RowPerThread;\n      let globalCol = i32(globalId.x) * ColPerThread;\n      let batch = i32(globalId.z);\n      let globalRowStart = i32(workgroupId.y) * ${tileAOuter};\n\n      let numTiles = (uniforms.dimInner - 1) / TileInner + 1;\n\n      var acc : array<array<f32, ColPerThread>, RowPerThread>;\n\n      // Without this initialization strange values show up in acc.\n      for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {\n        for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {\n          acc[innerRow][innerCol] = 0.0;\n        }\n      }\n\n      let tileRowA = i32(localId.y) * ${rowPerThreadA};\n      let tileColA = i32(localId.x) * ${colPerThreadA};\n      let tileRowB = i32(localId.y) * ${rowPerThreadB};\n      // Loop over shared dimension.\n      for (var t = 0; t < numTiles; t = t + 1) {\n        // Load one tile of A into local memory.\n        for (var innerRow = 0; innerRow < ${rowPerThreadA}; innerRow = innerRow + 1) {\n          for (var innerCol = 0; innerCol < ${colPerThreadA}; innerCol = innerCol + 1) {\n            let inputRow = tileRowA + innerRow;\n            let inputCol = tileColA + innerCol;\n            ${writeDataToSubASnippet(transposeA)}\n          }\n        }\n\n        // Load one tile of B into local memory.\n        for (var innerRow = 0; innerRow < ${rowPerThreadB}; innerRow = innerRow + 1) {\n          for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {\n            let inputRow = tileRowB + innerRow;\n            let inputCol = tileCol + innerCol;\n            mm_Bsub[inputRow][inputCol] = mm_readB(batch,\n              t * TileInner + inputRow,\n              globalCol + innerCol);\n          }\n        }\n\n        workgroupBarrier();\n\n        // Compute acc values for a single thread.\n        var BCached : array<f32, ColPerThread>;\n        for (var k = 0; k < TileInner; k = k + 1) {\n          for (var inner = 0; inner < ColPerThread; inner = inner + 1) {\n            BCached[inner] = mm_Bsub[k][tileCol + inner];\n          }\n\n          for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {\n            ${readDataFromSubASnippet(transposeA)}\n            for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {\n              acc[innerRow][innerCol] = acc[innerRow][innerCol] + ACached * BCached[innerCol];\n            }\n          }\n        }\n\n        workgroupBarrier();\n      }\n\n      for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {\n        for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {\n          mm_write(batch, globalRow + innerRow, globalCol + innerCol,\n              acc[innerRow][innerCol]);\n        }\n      }\n    }\n  `;\n}\nvar readVectorASnippet = (transpose6) => {\n  return transpose6 ? `\n      mm_readA(batch, colA, globalRow),\n      mm_readA(batch, colA + 1, globalRow),\n      mm_readA(batch, colA + 2, globalRow),\n      mm_readA(batch, colA + 3, globalRow)\n  ` : `\n      mm_readA(batch, globalRow, colA),\n      mm_readA(batch, globalRow, colA + 1),\n      mm_readA(batch, globalRow, colA + 2),\n      mm_readA(batch, globalRow, colA + 3)\n  `;\n};\nfunction makeVectorMatrixProductSource(workGroupSize, transposeA = false) {\n  util_exports.assert(workGroupSize[1] === 1 && workGroupSize[2] === 1, () => `A linear work group size is required. But got ${workGroupSize}.`);\n  return `\n    const TileSize = ${workGroupSize[0] * 4};\n    var<workgroup> mm_Asub : array<vec4<f32>, ${workGroupSize[0]}>;\n\n    ${getMainHeaderString()}\n      let tileCol = i32(localId.x);\n      let globalCol = i32(globalId.x);\n      let globalRow = i32(globalId.y);\n\n      let numTiles = (uniforms.dimInner - 1) / TileSize + 1;\n      let batch = i32(globalId.z);\n      // Without this initialization strange values show up in acc.\n      var acc = 0.0;\n\n      // Loop over shared dimension.\n      for (var t = 0; t < numTiles; t = t + 1) {\n        // Load one tile of A into local memory.\n        let colA = t * TileSize + tileCol * 4;\n        mm_Asub[tileCol] = vec4<f32>(${readVectorASnippet(transposeA)});\n        workgroupBarrier();\n\n        // Compute acc values for a single thread.\n        for (var k = 0; k < TileSize / 4; k = k + 1) {\n          let rowB = t * TileSize + k * 4;\n          let BCached = vec4<f32>(mm_readB(batch, rowB, globalCol),\n                              mm_readB(batch, rowB + 1, globalCol),\n                              mm_readB(batch, rowB + 2, globalCol),\n                              mm_readB(batch, rowB + 3, globalCol));\n\n          let ACached = mm_Asub[k];\n          acc = acc + dot(ACached, BCached);\n        }\n\n        workgroupBarrier();\n      }\n\n      mm_write(batch, globalRow, globalCol, acc);\n    }\n  `;\n}\nvar MatMulPackedProgram2 = class {\n  constructor(aShape, outputShape, workPerThread, batchAEqualOne, batchBEqualOne, transposeA = false, transposeB = false, bias = null, activation2 = null, preluActivationWeights = null) {\n    this.variableNames = [\"A\", \"B\"];\n    this.uniforms = `dimAOuter : i32, dimBOuter : i32, dimInner : i32,`;\n    this.workGroupSize = [16, 16, 1];\n    this.outputShape = outputShape;\n    this.dispatchLayout = { x: [2], y: [1], z: [0] };\n    const dimInner = transposeA ? aShape[1] : aShape[2];\n    this.workGroupSize = computeWorkGroupSizeForMatMul(outputShape[1], dimInner, outputShape[2]);\n    if (outputShape[1] === 1 || outputShape[2] === 1) {\n      workPerThread = 1;\n    }\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [workPerThread, workPerThread, 1]);\n    if (util_exports.arraysEqual(this.dispatch, [1, 1, 1])) {\n      workPerThread = 1;\n      this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [workPerThread, workPerThread, 1]);\n    }\n    const addBias = bias != null;\n    const hasPreluActivationWeights = preluActivationWeights != null;\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivationWeights) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.workPerThread = workPerThread;\n    this.transposeA = transposeA;\n    this.transposeB = transposeB;\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivationWeights = hasPreluActivationWeights;\n    this.batchAEqualOne = batchAEqualOne;\n    this.batchBEqualOne = batchBEqualOne;\n    [this.fitAOuter, this.fitBOuter, this.fitInner] = this.getShapeFit(outputShape[1], outputShape[2], dimInner);\n    this.shaderKey = `matMulPacked_${this.workPerThread}_${transposeA}_${transposeB}_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.outputShape[1] > 1}_${this.batchAEqualOne}_${this.batchBEqualOne}`;\n  }\n  getShapeFit(dimAOuter, dimBOuter, dimInner) {\n    const tileAOuter = this.workGroupSize[1] * this.workPerThread;\n    const tileBOuter = this.workGroupSize[0] * this.workPerThread;\n    this.tileInner = 32;\n    if (this.outputShape[1] === 1) {\n      this.tileInner = this.workGroupSize[0] * 4;\n    }\n    const fitAOuter = dimAOuter % tileAOuter === 0;\n    const fitBOuter = dimBOuter % tileBOuter === 0;\n    const fitInner = dimInner % this.tileInner === 0;\n    return [fitAOuter, fitBOuter, fitInner];\n  }\n  getUserCode() {\n    const userCode = `\n      ${activationFnSnippet(this.activation, this.hasPreluActivationWeights)}\n      ${matMulReadWriteFnSource(this.addBias, this.activation, this.batchAEqualOne, this.batchBEqualOne, false, this.transposeB, this.fitAOuter, this.fitBOuter, this.fitInner)}\n      ${this.outputShape[1] > 1 ? makeMatMulPackedSource([this.workPerThread, this.workPerThread, 1], this.workGroupSize, this.transposeA, this.tileInner) : makeVectorMatrixProductSource(this.workGroupSize, this.transposeA)}\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/matmul_packed_vec4_webgpu.js\nvar writeDataToSubASnippet2 = (transpose6, innerAElementSize) => {\n  if (transpose6) {\n    return `\n        mm_Asub[inputRow][inputCol] = mm_readA(batch,\n          t * TileInner + inputRow,\n          globalRowStart / ${innerAElementSize} + inputCol);\n        `;\n  } else {\n    return `\n        mm_Asub[inputRow][inputCol] = mm_readA(batch,\n          globalRow + innerRow,\n          t * TileInner / ${innerAElementSize} + inputCol);\n        `;\n  }\n};\nvar calculateResultSnippet = (transposeA, innerElementSize) => {\n  if (transposeA) {\n    return `\n        let ACached0 = mm_Asub[k * InnerElementSize][localRow];\n        let ACached1 = mm_Asub[k * InnerElementSize + 1][localRow];\n        let ACached2 = mm_Asub[k * InnerElementSize + 2][localRow];\n        ${innerElementSize === 3 ? \"\" : \"let ACached3 = mm_Asub[k * InnerElementSize + 3][localRow];\"}\n        for (var i = 0; i < RowPerThread; i = i + 1) {\n          acc[i] = BCached[0] * ACached0[i] + acc[i];\n          acc[i] = BCached[1] * ACached1[i] + acc[i];\n          acc[i] = BCached[2] * ACached2[i] + acc[i];\n          ${innerElementSize === 3 ? \"\" : \"acc[i] = BCached[3] * ACached3[i] + acc[i];\"}\n        }`;\n  } else {\n    return `\n        for (var i = 0; i < RowPerThread; i = i + 1) {\n          let ACached = mm_Asub[tileRow + i][k];\n          acc[i] = BCached[0] * ACached.x + acc[i];\n          acc[i] = BCached[1] * ACached.y + acc[i];\n          acc[i] = BCached[2] * ACached.z + acc[i];\n          ${innerElementSize === 3 ? \"\" : \"acc[i] = BCached[3] * ACached.w + acc[i];\"}\n        }`;\n  }\n};\nfunction makeMatMulPackedVec4Source(workPerThread, tileAOuter, tileBOuter, tileInner, innerElementSize = 4, transposeA = false) {\n  const tileAWidth = transposeA ? tileAOuter : tileInner;\n  const tileAHight = transposeA ? tileInner : tileAOuter;\n  const innerAElementSize = transposeA ? workPerThread[1] : innerElementSize;\n  util_exports.assert((transposeA && tileAOuter === tileBOuter || (tileInner % 4 === 0 || tileInner % 3 === 0)) && workPerThread[0] === 4 && (innerElementSize === 3 || innerElementSize === 4), () => `tileInner ${tileInner} must be divisible by 4|3. ColPerThread ${workPerThread[0]} must be 4.\n           innerElementSize ${innerElementSize} must be 3|4.`);\n  return `\n  var<workgroup> mm_Asub : array<array<vec${innerAElementSize}<f32>, ${tileAWidth / innerAElementSize}>, ${tileAHight}>;\n  var<workgroup> mm_Bsub : array<array<vec4<f32>, ${tileBOuter / workPerThread[0]}>, ${tileInner}>;\n\n  const RowPerThread = ${workPerThread[1]};\n  const ColPerThread = ${workPerThread[0]};\n  const InnerElementSize = ${innerElementSize};\n  const TileInner = ${tileInner};\n\n  @compute @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)\n  fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,\n          @builtin(global_invocation_id) GlobalId : vec3<u32>,\n          @builtin(num_workgroups) NumWorkgroups: vec3<u32>,\n          @builtin(workgroup_id) workgroupId: vec3<u32>) {\n    localId = LocalId;\n    globalId = GlobalId;\n    numWorkgroups = NumWorkgroups;\n\n    let localRow = i32(localId.y);\n    let tileRow = ${tileAOuter === 1 ? \"0\" : \"localRow * RowPerThread\"};\n    let tileCol = i32(localId.x);\n\n    let globalRow = ${tileAOuter === 1 ? \"0\" : \"i32(globalId.y) * RowPerThread\"};\n    let globalCol = i32(globalId.x);\n    let batch = i32(globalId.z);\n    let globalRowStart = i32(workgroupId.y) * ${tileAOuter};\n\n    let numTiles = (uniforms.dimInner - 1) / TileInner + 1;\n\n    var acc: array<vec4<f32>, RowPerThread>;\n    var BCached : array<vec4<f32>, 4>;\n\n    // Loop over shared dimension.\n    let RowPerThreadB = TileInner / i32(workGroupSizeY);\n    let tileRowB = localRow * RowPerThreadB;\n    for (var t = 0; t < numTiles; t = t + 1) {\n        // Load one tile of A into local memory.\n        for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {\n            let inputRow = tileRow + innerRow;\n            let inputCol = tileCol;\n            ${writeDataToSubASnippet2(transposeA, innerAElementSize)}\n        }\n\n        // Load one tile of B into local memory.\n        for (var innerRow = 0; innerRow < RowPerThreadB; innerRow = innerRow + 1) {\n            let inputRow = tileRowB + innerRow;\n            let inputCol = tileCol;\n            mm_Bsub[inputRow][inputCol] = mm_readB(batch, t * TileInner + inputRow, globalCol);\n        }\n\n        workgroupBarrier();\n\n        // Compute acc values for a single thread.\n        for (var k = 0; k < TileInner / InnerElementSize; k = k + 1) {\n            BCached[0] = mm_Bsub[k * InnerElementSize][tileCol];\n            BCached[1] = mm_Bsub[k * InnerElementSize + 1][tileCol];\n            BCached[2] = mm_Bsub[k * InnerElementSize + 2][tileCol];\n            ${innerElementSize === 3 ? \"\" : \"BCached[3] = mm_Bsub[k * InnerElementSize + 3][tileCol];\"}\n\n            ${calculateResultSnippet(transposeA, innerElementSize)}\n        }\n\n        workgroupBarrier();\n    }\n\n    for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {\n        mm_write(batch, globalRow + innerRow, globalCol, acc[innerRow]);\n    }\n  }`;\n}\nvar MatMulPackedVec4Program = class {\n  constructor(aShape, outputShape, batchAEqualOne, batchBEqualOne, transposeA = false, bias = null, activation2 = null, preluActivationWeights = null) {\n    this.variableNames = [\"A\", \"B\"];\n    this.uniforms = `dimAOuter : i32, dimBOuter : i32, dimInner : i32,`;\n    this.workGroupSize = [8, 8, 1];\n    this.isVec4 = true;\n    this.outputShape = outputShape;\n    this.dispatchLayout = { x: [2], y: [1], z: [0] };\n    if (outputShape[1] === 1 && !transposeA) {\n      this.elementsPerThread = [4, 1, 1];\n    } else {\n      this.elementsPerThread = [4, 4, 1];\n    }\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, this.elementsPerThread);\n    const addBias = bias != null;\n    const hasPreluActivationWeights = preluActivationWeights != null;\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivationWeights) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.tileAOuter = outputShape[1] === 1 && !transposeA ? 1 : this.workGroupSize[1] * this.elementsPerThread[1];\n    this.tileBOuter = this.workGroupSize[0] * this.elementsPerThread[0];\n    this.tileInner = this.tileBOuter;\n    this.aShape = aShape;\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivationWeights = hasPreluActivationWeights;\n    this.batchAEqualOne = batchAEqualOne;\n    this.batchBEqualOne = batchBEqualOne;\n    this.transposeA = transposeA;\n    const dimInner = transposeA ? aShape[1] : aShape[2];\n    this.fitAOuter = outputShape[1] % this.tileAOuter === 0;\n    this.fitBOuter = outputShape[2] % this.tileBOuter === 0;\n    this.fitInner = dimInner % this.tileInner === 0;\n    this.shaderKey = `matMulPackedVec4_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.elementsPerThread}_${this.batchAEqualOne}_${this.batchBEqualOne}_${this.transposeA}`;\n  }\n  getUserCode() {\n    const userCode = `\n      ${activationFnSnippet(this.activation, this.hasPreluActivationWeights, true)}\n      ${matMulReadWriteFnSource(this.addBias, this.activation, this.batchAEqualOne, this.batchBEqualOne, false, false, this.fitAOuter, this.fitBOuter, this.fitInner, 4)}\n      ${makeMatMulPackedVec4Source(this.elementsPerThread, this.tileAOuter, this.tileBOuter, this.tileInner, 4, this.transposeA)}\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/matmul_reduce_webgpu.js\nfunction makeMatMulReduceSource() {\n  return `\n    var<workgroup> sumValues : array<f32, workGroupSizeX>;\n    ${getMainHeaderString()}\n      let coords = getOutputCoords();\n      let batch = coords[0];\n      let row = coords[1];\n      let col = coords[2];\n      var sum = 0.0;\n      let Length = uniforms.dimInner;\n      for (var k = i32(localId.x); k < Length; k = k + i32(workGroupSizeX)) {\n        let dataA = mm_readA(batch, row, k);\n        let dataB = mm_readB(batch, k, col);\n        sum = sum + dataA * dataB;\n      }\n      sumValues[localId.x] = sum;\n      workgroupBarrier();\n\n      for(var currentSize = workGroupSizeX / 2u; currentSize > 1u;\n          currentSize = currentSize / 2u) {\n        if (localId.x < currentSize)\n        {\n          sumValues[localId.x] = sumValues[localId.x] + sumValues[localId.x + currentSize];\n        }\n        workgroupBarrier();\n      }\n\n      if (localId.x == 0u) {\n        sum = sumValues[0] + sumValues[1];\n        mm_write(batch, row, col, sum);\n      }\n    }\n  `;\n}\nvar MatMulReduceProgram = class {\n  constructor(outputShape, batchAEqualOne, batchBEqualOne, transposeA = false, transposeB = false, bias = null, activation2 = null, preluActivationWeights = null) {\n    this.variableNames = [\"A\", \"B\"];\n    this.uniforms = `dimAOuter : i32, dimBOuter : i32, dimInner : i32,`;\n    this.workGroupSize = [256, 1, 1];\n    this.outputShape = outputShape;\n    this.dispatchLayout = { x: [], y: [1, 2], z: [0] };\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    const addBias = bias != null;\n    const hasPreluActivationWeights = preluActivationWeights != null;\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivationWeights) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.transposeA = transposeA;\n    this.transposeB = transposeB;\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivationWeights = hasPreluActivationWeights;\n    this.batchAEqualOne = batchAEqualOne;\n    this.batchBEqualOne = batchBEqualOne;\n    this.shaderKey = `matMulReduce_${this.activation}_${transposeA}_${transposeB}_${this.batchAEqualOne}_${this.batchBEqualOne}`;\n  }\n  getUserCode() {\n    const userCode = `\n      ${activationFnSnippet(this.activation, this.hasPreluActivationWeights)}\n      ${matMulReadWriteFnSource(this.addBias, this.activation, this.batchAEqualOne, this.batchBEqualOne, this.transposeA, this.transposeB)}\n      ${makeMatMulReduceSource()}\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/matmul_small_output_size_webgpu.js\nfunction makeMatMulSmallOutputSizeSource(workGroupSize) {\n  const tileAOuter = workGroupSize[1];\n  const tileBOuter = workGroupSize[0];\n  const tileInner = tileAOuter > tileBOuter ? tileAOuter : tileBOuter;\n  return `\n  var<workgroup> mm_Asub : array<array<f32, ${tileInner}>, ${tileAOuter}>;\n  var<workgroup> mm_Bsub : array<array<f32, ${tileBOuter}>, ${tileInner}>;\n\n  // If the output size is small for matrix multiplication, avoid to use vec4\n  // and handle some elements per thread to optimally utilize the ALU.\n  // Read data from global memory to registers firstly, then store them into\n  // shared memory, so it is instruction-Level parallelism for arithmetic\n  // operations and others handle IO operations between barrier api, makes ALU\n  // and load/store units work simultaneously, could improves the performance.\n  ${getMainHeaderString()}\n    let tileRow = i32(localId.y);\n    let tileCol = i32(localId.x);\n    let globalRow = i32(globalId.y);\n    let globalCol = i32(globalId.x);\n    let batch = i32(globalId.z);\n\n    // uniforms.dimInner should be greater than 0.\n    let numTiles = (uniforms.dimInner - 1) / ${tileInner} + 1;\n    var acc = 0.0;\n\n    var globalColA = tileCol;\n    var globalRowB = 0;\n    var regA = mm_readA(batch, globalRow, globalColA);\n    var regB0 = mm_readB(batch, globalRowB + 2 * tileRow, globalCol);\n    var regB1 = mm_readB(batch, globalRowB + 2 * tileRow + 1, globalCol);\n    globalColA = globalColA + ${tileInner};\n    globalRowB = globalRowB + ${tileInner};\n\n    for (var t = 0; t < numTiles; t = t + 1) {\n      mm_Asub[tileRow][tileCol] = regA;\n      mm_Bsub[2 * tileRow][tileCol] = regB0;\n      mm_Bsub[2 * tileRow + 1][tileCol] = regB1;\n\n      workgroupBarrier();\n\n      regA = mm_readA(batch, globalRow, globalColA);\n      regB0 = mm_readB(batch, globalRowB + 2 * tileRow, globalCol);\n      regB1 = mm_readB(batch, globalRowB + 2 * tileRow + 1, globalCol);\n      globalColA = globalColA + ${tileInner};\n      globalRowB = globalRowB + ${tileInner};\n\n      for (var k = 0; k < ${tileInner}; k = k + 1) {\n        acc = acc + mm_Asub[tileRow][k] * mm_Bsub[k][tileCol];\n      }\n      workgroupBarrier();\n    }\n\n    mm_write(batch, globalRow, globalCol, acc);\n  }\n  `;\n}\nvar MatMulSmallOutputSizeProgram = class {\n  constructor(aShape, bShape, outputShape, transposeA = false, transposeB = false, bias = null, activation2 = null, preluActivationWeights = null) {\n    this.variableNames = [\"A\", \"B\"];\n    this.uniforms = `dimAOuter : i32, dimBOuter : i32, dimInner : i32,`;\n    this.workGroupSize = [16, 8, 1];\n    this.outputShape = outputShape;\n    this.dispatchLayout = { x: [2], y: [1], z: [0] };\n    this.dispatch = [\n      Math.ceil(outputShape[2] / this.workGroupSize[0]),\n      Math.ceil(outputShape[1] / this.workGroupSize[1]),\n      outputShape[0]\n    ];\n    const addBias = bias != null;\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    const hasPreluActivationWeights = preluActivationWeights != null;\n    if (hasPreluActivationWeights) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.transposeA = transposeA;\n    this.transposeB = transposeB;\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivationWeights = hasPreluActivationWeights;\n    this.batchAEqualOne = aShape[0] === 1;\n    this.batchBEqualOne = bShape[0] === 1;\n    this.shaderKey = `matMulSmallOutputSize_${this.activation}_${transposeA}_${transposeB}_${this.batchAEqualOne}_${this.batchBEqualOne}`;\n  }\n  getUserCode() {\n    const userCode = `\n      ${activationFnSnippet(this.activation, this.hasPreluActivationWeights)}\n      ${matMulReadWriteFnSource(this.addBias, this.activation, this.batchAEqualOne, this.batchBEqualOne, this.transposeA, this.transposeB)}\n      ${makeMatMulSmallOutputSizeSource(this.workGroupSize)}\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/matmul_splitK_webgpu.js\nvar MatMulSplitKProgram = class {\n  constructor(outputShape, dimInner, batchAEqualOne, batchBEqualOne, transposeA = false, transposeB = false) {\n    this.variableNames = [\"A\", \"B\"];\n    this.uniforms = `dimAOuter : i32, dimBOuter : i32, dimInner : i32,`;\n    this.workGroupSize = [8, 8, 1];\n    this.atomic = true;\n    this.tileInner = 32;\n    util_exports.assert(outputShape[0] === 1, () => \"MatMulSplitKProgram only supports batch = 1.\");\n    this.outputShape = outputShape;\n    this.dispatchLayout = { x: [2], y: [1], z: [0, 3] };\n    this.elementsPerThread = [4, 4, this.tileInner];\n    if (this.outputShape[1] < 16) {\n      this.elementsPerThread[1] = 1;\n    }\n    if (this.outputShape[2] < 16) {\n      this.elementsPerThread[0] = 1;\n    }\n    this.dispatch = computeDispatch(this.dispatchLayout, [\n      this.outputShape[0],\n      this.outputShape[1],\n      this.outputShape[2],\n      dimInner\n    ], this.workGroupSize, this.elementsPerThread);\n    this.transposeA = transposeA;\n    this.transposeB = transposeB;\n    this.batchAEqualOne = batchAEqualOne;\n    this.batchBEqualOne = batchBEqualOne;\n    this.shaderKey = `matMulSplitK_${transposeA}_${transposeB}_${batchAEqualOne}_${batchBEqualOne}_${this.elementsPerThread}`;\n  }\n  getUserCode() {\n    const atomicAddSnippet = `\n     var oldValue = atomicLoad(&(result[flatIndex]));\n     var exchanged = false;\n     for (; !exchanged;) {\n       let newValueF32 = bitcast<f32>(oldValue) + value;\n       let newValue = bitcast<i32>(newValueF32);\n       let res = atomicCompareExchangeWeak(&(result[flatIndex]), oldValue, newValue);\n       oldValue = res.old_value;\n       exchanged = res.exchanged;\n     }\n     `;\n    const userCode = `\n      ${matMulReadFnSource(this.batchAEqualOne, this.batchBEqualOne, this.transposeA, this.transposeB)}\n      fn mm_write(batch: i32, row : i32, col : i32, valueIn : f32) {\n        if (row < uniforms.dimAOuter && col < uniforms.dimBOuter) {\n          let coords = vec3<i32>(batch, row, col);\n          let flatIndex = getOutputIndexFromCoords(coords);\n          var value = valueIn;\n          // The problem is that we should initialize output to zero before using.\n          // Otherwise, the original value will be added to the result.\n          ${atomicAddSnippet}\n        }\n      }\n\n      ${this.makeMatMulSplitKSource()}\n    `;\n    return userCode;\n  }\n  makeMatMulSplitKSource() {\n    const tileAOuter = this.workGroupSize[1] * this.elementsPerThread[1];\n    const tileBOuter = this.workGroupSize[0] * this.elementsPerThread[0];\n    const rowPerThread = this.elementsPerThread[1];\n    const colPerThread = this.elementsPerThread[0];\n    const colPerThreadA = this.tileInner / this.workGroupSize[0];\n    const rowPerThreadB = this.tileInner / this.workGroupSize[1];\n    util_exports.assert(this.tileInner % this.workGroupSize[0] === 0 && this.tileInner % this.workGroupSize[1] === 0, () => `tileInner ${this.tileInner} must be divisible by workGroupSize[0]${this.workGroupSize[0]} and workGroupSize[1]${this.workGroupSize[1]}`);\n    return `\n      var<workgroup> mm_Asub : array<array<f32, ${this.tileInner}>, ${tileAOuter}>;\n      var<workgroup> mm_Bsub : array<array<f32, ${tileBOuter}>, ${this.tileInner}>;\n      ${getMainHeaderString()}\n        let tileRow = i32(localId.y) * ${rowPerThread};\n        let tileCol = i32(localId.x) * ${colPerThread};\n\n        let globalRow = i32(globalId.y) * ${rowPerThread};\n        let globalCol = i32(globalId.x) * ${colPerThread};\n        let batch = 0;\n        let kStart = i32(globalId.z) * ${this.tileInner};\n\n        // Load one tile of A into local memory.\n        let tileColA = i32(localId.x) * ${colPerThreadA};\n        for (var innerRow = 0; innerRow < ${rowPerThread}; innerRow = innerRow + 1) {\n          for (var innerCol = 0; innerCol < ${colPerThreadA}; innerCol = innerCol + 1) {\n            let inputRow = tileRow + innerRow;\n            let inputCol = tileColA + innerCol;\n            mm_Asub[inputRow][inputCol] = mm_readA(${this.batchAEqualOne ? 0 : \"batch\"},\n                globalRow + innerRow,\n                kStart + inputCol);\n          }\n        }\n        // Load one tile of B into local memory.\n        let tileRowB = i32(localId.y) * ${rowPerThreadB};\n        for (var innerRow = 0; innerRow < ${rowPerThreadB}; innerRow = innerRow + 1) {\n          for (var innerCol = 0; innerCol < ${colPerThread}; innerCol = innerCol + 1) {\n            let inputRow = tileRowB + innerRow;\n            let inputCol = tileCol + innerCol;\n            mm_Bsub[inputRow][inputCol] = mm_readB(${this.batchBEqualOne ? 0 : \"batch\"},\n                kStart + inputRow,\n                globalCol + innerCol);\n          }\n        }\n\n        workgroupBarrier();\n\n        var acc : array<array<f32, ${colPerThread}>, ${rowPerThread}>;\n        // Loop over shared dimension. Compute acc values for a single thread.\n        for (var k = 0; k < ${this.tileInner}; k = k + 1) {\n          var BCached : array<f32, ${colPerThread}>;\n          for (var inner = 0; inner < ${colPerThread}; inner = inner + 1) {\n            BCached[inner] = mm_Bsub[k][tileCol + inner];\n          }\n\n          for (var innerRow = 0; innerRow < ${rowPerThread}; innerRow = innerRow + 1) {\n            let ACached = mm_Asub[tileRow + innerRow][k];\n            for (var innerCol = 0; innerCol < ${colPerThread}; innerCol = innerCol + 1) {\n              acc[innerRow][innerCol] = acc[innerRow][innerCol] + ACached * BCached[innerCol];\n            }\n          }\n        }\n\n        for (var innerRow = 0; innerRow < ${rowPerThread}; innerRow = innerRow + 1) {\n          for (var innerCol = 0; innerCol < ${colPerThread}; innerCol = innerCol + 1) {\n            mm_write(batch, globalRow + innerRow, globalCol + innerCol, acc[innerRow][innerCol]);\n          }\n        }\n      }\n    `;\n  }\n};\nvar BiasActivationProgram = class {\n  constructor(outputShape, bias = null, activation2 = null, preluActivationWeights = null) {\n    this.uniforms = \"\";\n    this.variableNames = [\"x\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.addBias = bias != null;\n    this.hasPreluActivationWeights = preluActivationWeights != null;\n    this.activation = activation2;\n    if (this.addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (this.hasPreluActivationWeights) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.shaderKey = `biasActivation_${activation2}`;\n  }\n  getUserCode() {\n    return `\n    ${activationFnSnippet(this.activation, this.hasPreluActivationWeights)}\n    ${getMainHeaderAndGlobalIndexString()}\n      if (index < uniforms.size) {\n        let coords = getCoordsFromIndex(index);\n        var value = getXByOutputIndex(index);\n        ${biasActivationSnippet(this.addBias, this.activation)}\n        setOutputAtIndex(index, value);\n      }\n    }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/fill_webgpu.js\nvar FillProgram2 = class {\n  constructor(shape) {\n    this.variableNames = [];\n    this.outputShape = [];\n    this.uniforms = \"value : f32,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = shape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = \"fill\";\n  }\n  getUserCode() {\n    const userCode = `\n    ${getMainHeaderAndGlobalIndexString()}\n      if (index < uniforms.size) {\n        setOutputAtIndex(index, uniforms.value);\n      }\n    }\n  `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Fill.js\nfunction fill5(args) {\n  const { backend: backend2, attrs } = args;\n  const { shape, value } = attrs;\n  let { dtype } = attrs;\n  dtype = dtype || util_exports.inferDtype(value);\n  if (dtype === \"string\") {\n    const values = util_exports.getArrayFromDType(dtype, util_exports.sizeFromShape(shape));\n    values.fill(value);\n    return backend2.makeTensorInfo(shape, dtype, values);\n  } else {\n    const program = new FillProgram2(shape);\n    const uniformData = [{ type: \"float32\", data: [value] }];\n    return backend2.runWebGPUProgram(program, [], dtype, uniformData);\n  }\n}\nvar fillConfig4 = {\n  kernelName: Fill,\n  backendName: \"webgpu\",\n  kernelFunc: fill5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Reshape.js\nfunction reshape6(args) {\n  const { inputs, attrs } = args;\n  const { x } = inputs;\n  const { shape } = attrs;\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const $shape = util_exports.inferFromImplicitShape(shape, xSize);\n  const $xSize = util_exports.sizeFromShape($shape);\n  util_exports.assert(xSize === $xSize, () => `The new shape (${$shape}) has ${$xSize} elements and the old shape (${x.shape}) has ${xSize} elements. The new shape and old shape must have the same number of elements.`);\n  args.backend.incRef(x.dataId);\n  return { dataId: x.dataId, shape: $shape, dtype: x.dtype };\n}\nvar reshapeConfig4 = {\n  kernelName: Reshape,\n  backendName: \"webgpu\",\n  kernelFunc: reshape6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/BatchMatMul_impl.js\nfunction batchMatMulImpl2({ a, b, transposeA, transposeB, backend: backend2, bias = null, preluActivationWeights = null, leakyreluAlpha = 0, activation: activation2 = null }) {\n  const aRank = a.shape.length;\n  const bRank = b.shape.length;\n  const innerShapeA = transposeA ? a.shape[aRank - 2] : a.shape[aRank - 1];\n  const innerShapeB = transposeB ? b.shape[bRank - 1] : b.shape[bRank - 2];\n  const outerShapeA = transposeA ? a.shape[aRank - 1] : a.shape[aRank - 2];\n  const outerShapeB = transposeB ? b.shape[bRank - 2] : b.shape[bRank - 1];\n  const outerDimsA = a.shape.slice(0, -2);\n  const outerDimsB = b.shape.slice(0, -2);\n  const batchDimA = util_exports.sizeFromShape(outerDimsA);\n  const batchDimB = util_exports.sizeFromShape(outerDimsB);\n  const outShapeOuterDims = broadcast_util_exports.assertAndGetBroadcastShape(a.shape.slice(0, -2), b.shape.slice(0, -2));\n  const outShape = outShapeOuterDims.concat([outerShapeA, outerShapeB]);\n  util_exports.assert(innerShapeA === innerShapeB, () => `Error in matMul: inner shapes (${innerShapeA}) and (${innerShapeB}) of Tensors with shapes ${a.shape} and ${b.shape} and transposeA=${transposeA} and transposeB=${transposeB} must match.`);\n  const a3dShape = transposeA ? [batchDimA, innerShapeA, outerShapeA] : [batchDimA, outerShapeA, innerShapeA];\n  const b3dShape = transposeB ? [batchDimB, outerShapeB, innerShapeB] : [batchDimB, innerShapeB, outerShapeB];\n  const a3d = reshape6({ inputs: { x: a }, backend: backend2, attrs: { shape: a3dShape } });\n  const b3d = reshape6({ inputs: { x: b }, backend: backend2, attrs: { shape: b3dShape } });\n  const intermediates = [a3d, b3d];\n  const batchDim = Math.max(batchDimA, batchDimB);\n  const batchAEqualOne = batchDimA === 1;\n  const batchBEqualOne = batchDimB === 1;\n  const useVec4 = (innerShapeA % 4 === 0 && !transposeA || outerShapeA % 4 === 0 && transposeA) && outerShapeB % 4 === 0 && !transposeB;\n  const inputs = [a3d, b3d];\n  const dimensions = [\n    { type: \"int32\", data: [outerShapeA] },\n    { type: \"int32\", data: [outerShapeB] },\n    { type: \"int32\", data: [innerShapeA] }\n  ];\n  let program;\n  let out;\n  const outputShape = [batchDim, outerShapeA, outerShapeB];\n  let matmulProgramType = env().get(\"WEBGPU_MATMUL_PROGRAM_TYPE\");\n  if (matmulProgramType < 0) {\n    if (outerShapeA * outerShapeB <= 128) {\n      matmulProgramType = MatMulProgramType.MatMulReduceProgram;\n    } else if (batchDim === 1 && outerShapeA <= 128 && outerShapeB <= 48 && innerShapeB >= 2e3) {\n      matmulProgramType = MatMulProgramType.MatMulSplitKProgram;\n    } else if (outerShapeA <= 16 && (outerShapeB <= 512 || innerShapeB >= 2 * outerShapeB) || outerShapeB <= 16 && (outerShapeA <= 512 || innerShapeA >= 2 * outerShapeA)) {\n      matmulProgramType = MatMulProgramType.MatMulSmallOutputSizeProgram;\n    } else if (useVec4) {\n      matmulProgramType = MatMulProgramType.MatMulPackedVec4Program;\n    } else {\n      matmulProgramType = MatMulProgramType.MatMulPackedProgram;\n    }\n  }\n  switch (matmulProgramType) {\n    case MatMulProgramType.MatMulPackedVec4Program:\n      program = new MatMulPackedVec4Program(a3dShape, outputShape, batchAEqualOne, batchBEqualOne, transposeA, bias, activation2, preluActivationWeights);\n      break;\n    case MatMulProgramType.MatMulReduceProgram:\n      program = new MatMulReduceProgram(outputShape, batchAEqualOne, batchBEqualOne, transposeA, transposeB, bias, activation2, preluActivationWeights);\n      break;\n    case MatMulProgramType.MatMulSplitKProgram: {\n      out = fill5({ backend: backend2, attrs: { shape: outputShape, value: 0, dtype: a.dtype } });\n      program = new MatMulSplitKProgram(outputShape, innerShapeB, batchAEqualOne, batchBEqualOne, transposeA, transposeB);\n      if (bias || activation2) {\n        out = backend2.runWebGPUProgram(program, inputs, a.dtype, dimensions, out);\n        const biasActivationProgram = new BiasActivationProgram(out.shape, bias, activation2, preluActivationWeights);\n        let uniformData = null;\n        const activationInputs = [out];\n        if (bias) {\n          activationInputs.push(bias);\n        }\n        if (preluActivationWeights) {\n          activationInputs.push(preluActivationWeights);\n        }\n        if (activation2 === \"leakyrelu\") {\n          uniformData = [{ type: \"float32\", data: [leakyreluAlpha] }];\n          biasActivationProgram.uniforms += \" alpha : f32,\";\n        }\n        const outActivated = backend2.runWebGPUProgram(biasActivationProgram, activationInputs, out.dtype, uniformData);\n        intermediates.push(out);\n        const outReshaped2 = reshape6({ inputs: { x: outActivated }, backend: backend2, attrs: { shape: outShape } });\n        intermediates.push(outActivated);\n        for (const i2 of intermediates) {\n          backend2.disposeData(i2.dataId);\n        }\n        return outReshaped2;\n      }\n      break;\n    }\n    case MatMulProgramType.MatMulSmallOutputSizeProgram:\n      program = new MatMulSmallOutputSizeProgram(a3dShape, b3dShape, outputShape, transposeA, transposeB, bias, activation2, preluActivationWeights);\n      break;\n    case MatMulProgramType.MatMulPackedProgram:\n      program = new MatMulPackedProgram2(a3dShape, outputShape, env().get(\"WEBGPU_MATMUL_WORK_PER_THREAD\"), batchAEqualOne, batchBEqualOne, transposeA, transposeB, bias, activation2, preluActivationWeights);\n      break;\n    default:\n      throw new Error(`Unsupported MatMulProgramType ${matmulProgramType}.`);\n  }\n  if (bias) {\n    inputs.push(bias);\n  }\n  if (preluActivationWeights) {\n    inputs.push(preluActivationWeights);\n  }\n  if (activation2 === \"leakyrelu\") {\n    dimensions.push({ type: \"float32\", data: [leakyreluAlpha] });\n    program.uniforms += \" alpha : f32,\";\n  }\n  out = backend2.runWebGPUProgram(program, inputs, a.dtype, dimensions, out);\n  const outReshaped = reshape6({ inputs: { x: out }, backend: backend2, attrs: { shape: outShape } });\n  intermediates.push(out);\n  for (const i2 of intermediates) {\n    backend2.disposeData(i2.dataId);\n  }\n  return outReshaped;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/_FusedMatMul.js\nfunction _fusedMatMul3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b, bias, preluActivationWeights } = inputs;\n  const { transposeA, transposeB, activation: activation2, leakyreluAlpha } = attrs;\n  return batchMatMulImpl2({\n    a,\n    b,\n    transposeA,\n    transposeB,\n    backend: backend2,\n    bias,\n    preluActivationWeights,\n    leakyreluAlpha,\n    activation: activation2\n  });\n}\nvar _fusedMatMulConfig4 = {\n  kernelName: _FusedMatMul,\n  backendName: \"webgpu\",\n  kernelFunc: _fusedMatMul3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/binary_op_complex_webgpu.js\nvar BinaryOpComplexProgram2 = class {\n  constructor(op2, aShape, bShape) {\n    this.variableNames = [\"AReal\", \"AImag\", \"BReal\", \"BImag\"];\n    this.workGroupSize = [128, 1, 1];\n    this.size = true;\n    this.outputShape = backend_util_exports.assertAndGetBroadcastShape(aShape, bShape);\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = `binaryOpComplex_${op2}`;\n    this.op = op2;\n  }\n  getUserCode() {\n    const opStr = getBinaryOpString(this.op, false);\n    const userCode = `\n      fn binaryOpComplex(\n          areal : f32, aimag : f32, breal : f32, bimag : f32) -> f32 {\n        ${opStr}\n      }\n\n      ${getMainHeaderAndGlobalIndexString()}\n        if(index < uniforms.size) {\n          let areal = getARealByOutputIndex(index);\n          let aimag = getAImagByOutputIndex(index);\n          let breal = getBRealByOutputIndex(index);\n          let bimag = getBImagByOutputIndex(index);\n          setOutputAtIndex(index, binaryOpComplex(areal, aimag, breal, bimag));\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/binary_op_webgpu.js\nvar BinaryOpProgram2 = class {\n  constructor(op2, aShape, bShape) {\n    this.size = true;\n    this.variableNames = [\"A\", \"B\"];\n    this.outputShape = backend_util_exports.assertAndGetBroadcastShape(aShape, bShape);\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.op = op2;\n    this.useSharedMemoryWithA = aShape.length === 1 && bShape.length > 1 && aShape[0] < 1024;\n    this.useSharedMemoryWithB = bShape.length === 1 && aShape.length > 1 && bShape[0] < 1024;\n    if (this.useSharedMemoryWithA || this.useSharedMemoryWithB) {\n      this.isVec4 = false;\n      this.lastDimensionSize = this.useSharedMemoryWithB ? bShape[0] : aShape[0];\n      this.shaderKey = `binary_${this.type}_${op2}_${this.lastDimensionSize}_${this.useSharedMemoryWithB}`;\n      this.type = \"shared\";\n      this.workGroupSize = [256, 1, 1];\n      if (this.lastDimensionSize < 256) {\n        this.workPerThread = 1;\n      } else if (this.lastDimensionSize < 512) {\n        this.workPerThread = 2;\n      } else {\n        this.workPerThread = 4;\n      }\n    } else {\n      if (util_exports.arraysEqual(aShape, bShape) && util_exports.sizeFromShape(aShape) % 4 === 0) {\n        this.isVec4 = true;\n        this.type = \"vec4\";\n        this.workPerThread = 4;\n      } else {\n        this.isVec4 = false;\n        this.type = \"plain\";\n        this.workPerThread = 1;\n      }\n      this.shaderKey = `binary_${this.type}_${op2}`;\n      this.workGroupSize = [128, 1, 1];\n    }\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [this.workPerThread, 1, 1]);\n  }\n  getUserCode() {\n    let userCode;\n    if (this.type === \"shared\") {\n      const sharedIndexSnippet = this.lastDimensionSize > 1 ? `coords[${this.outputShape.length - 1}]` : \"0\";\n      const accessDataSnippet = this.useSharedMemoryWithB ? `let a = getAByOutputCoords(coords);\n          let b = sharedBuf[${sharedIndexSnippet}];` : `let a = sharedBuf[${sharedIndexSnippet}];\n          let b = getBByOutputCoords(coords);`;\n      const opStr = getBinaryOpString(this.op, this.isVec4);\n      userCode = `\n        fn binaryOperation(a : f32, b : f32) -> f32 {\n          ${opStr}\n        }\n        var<workgroup> sharedBuf : array<f32, ${this.lastDimensionSize}>;\n        ${getMainHeaderAndGlobalIndexString()}\n\n          // Fill in the shared memory buffer. Here we need a loop to make sure\n          // that all data in A|B are uploaded when |sharedMemorySize| is larger\n          // than work group size.\n          for(var localIndex = i32(localId.x); localIndex < ${this.lastDimensionSize}; localIndex = localIndex + ${this.workGroupSize[0]}) {\n            sharedBuf[localIndex] = f32(${this.useSharedMemoryWithB ? \"B\" : \"A\"}[localIndex]);\n          }\n          workgroupBarrier();\n\n          for(var i = 0; i < ${this.workPerThread}; i = i + 1) {\n            let flatIndex = index * ${this.workPerThread} + i;\n            if(flatIndex < uniforms.size) {\n              let coords = getCoordsFromIndex(flatIndex);\n\n              ${accessDataSnippet}\n              setOutputAtIndex(flatIndex, binaryOperation(a, b));\n            }\n          }\n        }\n        `;\n    } else {\n      const dType = this.type === \"vec4\" ? \"vec4<f32>\" : \"f32\";\n      const opStr = getBinaryOpString(this.op, this.isVec4);\n      userCode = `\n       fn binaryOperation(a : ${dType}, b : ${dType}) -> ${dType} {\n         ${opStr}\n       }\n       ${getMainHeaderAndGlobalIndexString()}\n         if (index < uniforms.size) {\n           let a = getAByOutputIndex(index);\n           let b = getBByOutputIndex(index);\n           setOutputAtIndex(index, binaryOperation(a, b));\n         }\n       }\n       `;\n    }\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Identity.js\nfunction identity5(args) {\n  const { inputs } = args;\n  const { x } = inputs;\n  args.backend.incRef(x.dataId);\n  return { dataId: x.dataId, shape: x.shape, dtype: x.dtype };\n}\nvar identityConfig4 = {\n  kernelName: Identity,\n  backendName: \"webgpu\",\n  kernelFunc: identity5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Complex.js\nfunction complex4(args) {\n  const { inputs, backend: backend2 } = args;\n  const { real: real5, imag: imag5 } = inputs;\n  const complexInfo = backend2.makeTensorInfo(real5.shape, \"complex64\");\n  const complex5 = backend2.tensorMap.get(complexInfo.dataId);\n  const realTensorInfo = identity5({ inputs: { x: real5 }, backend: backend2 });\n  const imagTensorInfo = identity5({ inputs: { x: imag5 }, backend: backend2 });\n  complex5.complexTensorInfos = { real: realTensorInfo, imag: imagTensorInfo };\n  return complexInfo;\n}\nvar complexConfig3 = {\n  kernelName: Complex,\n  backendName: \"webgpu\",\n  kernelFunc: complex4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/unary_op_webgpu.js\nvar UnaryOpProgram2 = class {\n  constructor(outputShape, op2) {\n    this.variableNames = [\"A\"];\n    this.size = true;\n    const workGroupSizeX = 128;\n    this.workGroupSize = [workGroupSizeX, 1, 1];\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.op = op2;\n    this.shaderKey = `unary_${op2}`;\n  }\n  getUserCode() {\n    return `\n      fn unaryOperation(a : f32) -> f32 {\n        ${getUnaryOpString(this.op, false)}\n      }\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let a = getAByOutputIndex(index);\n          setOutputAtIndex(index, unaryOperation(a));\n        }\n      }\n      `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernel_utils/kernel_funcs_utils.js\nfunction unaryKernelFunc3({ opType, cpuKernelImpl, dtype }) {\n  return ({ inputs, backend: backend2 }) => {\n    const { x } = inputs;\n    const webgpuBackend = backend2;\n    const $dtype = dtype || x.dtype;\n    if (webgpuBackend.shouldExecuteOnCPU([x]) && cpuKernelImpl != null) {\n      const xData = webgpuBackend.tensorMap.get(x.dataId);\n      const outValues = cpuKernelImpl(xData.values, $dtype);\n      return webgpuBackend.makeTensorInfo(x.shape, $dtype, outValues);\n    }\n    const program = new UnaryOpProgram2(x.shape, opType);\n    return webgpuBackend.runWebGPUProgram(program, [x], $dtype);\n  };\n}\nfunction binaryKernelFunc3({ opType, cpuKernelImpl, supportsComplex = false, dtype }) {\n  return ({ inputs, backend: backend2 }) => {\n    const { a, b } = inputs;\n    const webgpuBackend = backend2;\n    if (supportsComplex && a.dtype === \"complex64\") {\n      const aData = webgpuBackend.tensorMap.get(a.dataId);\n      const bData = webgpuBackend.tensorMap.get(b.dataId);\n      let real5, imag5;\n      if (opType !== BinaryOpType.MUL) {\n        [real5, imag5] = [\n          [aData.complexTensorInfos.real, bData.complexTensorInfos.real],\n          [aData.complexTensorInfos.imag, bData.complexTensorInfos.imag]\n        ].map((complexParts) => {\n          const [aPart, bPart] = complexParts;\n          const aHandle = {\n            dataId: aPart.dataId,\n            dtype: aPart.dtype,\n            shape: a.shape\n          };\n          const bHandle = {\n            dataId: bPart.dataId,\n            dtype: bPart.dtype,\n            shape: b.shape\n          };\n          const program2 = new BinaryOpProgram2(opType, a.shape, b.shape);\n          return webgpuBackend.runWebGPUProgram(program2, [aHandle, bHandle], upcastType(aPart.dtype, bPart.dtype));\n        });\n      } else {\n        const realProgram = new BinaryOpComplexProgram2(BinaryOpType.COMPLEX_MULTIPLY_REAL, a.shape, b.shape);\n        const imagProgram = new BinaryOpComplexProgram2(BinaryOpType.COMPLEX_MULTIPLY_IMAG, a.shape, b.shape);\n        const inputs2 = [\n          {\n            dataId: aData.complexTensorInfos.real.dataId,\n            dtype: aData.complexTensorInfos.real.dtype,\n            shape: a.shape\n          },\n          {\n            dataId: aData.complexTensorInfos.imag.dataId,\n            dtype: aData.complexTensorInfos.imag.dtype,\n            shape: a.shape\n          },\n          {\n            dataId: bData.complexTensorInfos.real.dataId,\n            dtype: bData.complexTensorInfos.real.dtype,\n            shape: b.shape\n          },\n          {\n            dataId: bData.complexTensorInfos.imag.dataId,\n            dtype: bData.complexTensorInfos.imag.dtype,\n            shape: b.shape\n          }\n        ];\n        real5 = webgpuBackend.runWebGPUProgram(realProgram, inputs2, \"float32\");\n        imag5 = webgpuBackend.runWebGPUProgram(imagProgram, inputs2, \"float32\");\n      }\n      const complexOutput = complex4({ inputs: { real: real5, imag: imag5 }, backend: webgpuBackend });\n      webgpuBackend.disposeData(real5.dataId);\n      webgpuBackend.disposeData(imag5.dataId);\n      return complexOutput;\n    }\n    const $dtype = dtype || upcastType(a.dtype, b.dtype);\n    if ((a.dtype === \"string\" || b.dtype === \"string\" || webgpuBackend.shouldExecuteOnCPU([a, b])) && cpuKernelImpl != null) {\n      const aData = webgpuBackend.tensorMap.get(a.dataId).values;\n      const bData = webgpuBackend.tensorMap.get(b.dataId).values;\n      const decodedAVals = a.dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(aData) : aData;\n      const decodedBVals = a.dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(bData) : bData;\n      const [outValues, outShape] = cpuKernelImpl(a.shape, b.shape, decodedAVals, decodedBVals, $dtype);\n      return webgpuBackend.makeTensorInfo(outShape, $dtype, outValues);\n    }\n    const program = new BinaryOpProgram2(opType, a.shape, b.shape);\n    return webgpuBackend.runWebGPUProgram(program, [a, b], $dtype);\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernel_utils/shared.js\nvar { addImpl: addImplCPU2, ceilImpl: ceilImplCPU2, concatImpl: concatImplCPU2, equalImpl: equalImplCPU2, expImpl: expImplCPU2, expm1Impl: expm1ImplCPU2, floorImpl: floorImplCPU2, gatherNdImpl: gatherNdImplCPU2, gatherV2Impl: gatherV2ImplCPU2, greaterEqualImpl: greaterEqualImplCPU2, greaterImpl: greaterImplCPU2, lessEqualImpl: lessEqualImplCPU2, lessImpl: lessImplCPU2, logImpl: logImplCPU2, maxImpl: maxImplCPU2, maximumImpl: maximumImplCPU2, minimumImpl: minimumImplCPU2, multiplyImpl: multiplyImplCPU2, negImpl: negImplCPU2, notEqualImpl: notEqualImplCPU2, prodImpl: prodImplCPU2, rangeImpl: rangeImplCPU2, rsqrtImpl: rsqrtImplCPU2, scatterImpl: scatterImplCPU2, simpleAbsImpl: simpleAbsImplCPU2, sliceImpl: sliceImplCPU2, stridedSliceImpl: stridedSliceImplCPU2, stringNGramsImpl: stringNGramsImplCPU2, subImpl: subImplCPU2, tileImpl: tileImplCPU2, topKImpl: topKImplCPU2, transposeImpl: transposeImplCPU2, uniqueImpl: uniqueImplCPU2 } = shared_exports;\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Abs.js\nvar abs4 = unaryKernelFunc3({ opType: UnaryOpType.ABS, cpuKernelImpl: simpleAbsImplCPU2 });\nvar absConfig4 = {\n  kernelName: Abs,\n  backendName: \"webgpu\",\n  kernelFunc: abs4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Add.js\nvar addKernelFunc2 = binaryKernelFunc3({ opType: BinaryOpType.ADD, cpuKernelImpl: addImplCPU2, supportsComplex: true });\nvar addConfig4 = {\n  kernelName: Add,\n  backendName: \"webgpu\",\n  kernelFunc: addKernelFunc2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/addn_packed_webgpu.js\nvar AddNPackedProgram2 = class {\n  constructor(shapes) {\n    this.workPerThread = 4;\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = shapes[0];\n    this.variableNames = shapes.map((_, i2) => `T${i2}`);\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [this.workPerThread, 1, 1]);\n    this.shaderKey = \"addN\";\n  }\n  getUserCode() {\n    const snippets = [];\n    this.variableNames.forEach((variable2) => {\n      snippets.push(`let v${variable2} = get${variable2}ByOutputCoords(coords);`);\n    });\n    const operation = this.variableNames.map((variable2) => {\n      return `v${variable2}`;\n    }).join(\" + \");\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        for (var i = 0; i < ${this.workPerThread}; i = i + 1) {\n          let flatIndex = index * ${this.workPerThread} + i;\n          if (flatIndex < uniforms.size) {\n            let coords = getCoordsFromIndex(flatIndex);\n            ${snippets.join(\"\\n        \")}\n            setOutputAtIndex(flatIndex, ${operation});\n          }\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/AddN.js\nfunction addN4(args) {\n  const { inputs, backend: backend2 } = args;\n  const tensors = inputs;\n  if (tensors.length === 1) {\n    return identity5({ inputs: { x: tensors[0] }, backend: backend2 });\n  }\n  const dtype = tensors.map((t2) => t2.dtype).reduce((d1, d2) => upcastType(d1, d2));\n  const shapes = tensors.map((t2) => t2.shape);\n  const program = new AddNPackedProgram2(shapes);\n  return backend2.runWebGPUProgram(program, tensors, dtype);\n}\nvar addNConfig4 = {\n  kernelName: AddN,\n  backendName: \"webgpu\",\n  kernelFunc: addN4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/argminmax_webgpu.js\nvar ArgMinMaxProgram2 = class {\n  constructor(inputShape, axis, reduceType) {\n    this.workGroupSize = [64, 1, 1];\n    this.variableNames = [\"x\"];\n    this.uniforms = \"infinityValue : f32,\";\n    this.size = true;\n    const axes = [axis];\n    backend_util_exports.assertAxesAreInnerMostDims(\"arg\" + reduceType.charAt(0).toUpperCase() + reduceType.slice(1), axes, inputShape.length);\n    this.op = reduceType === \"min\" ? \"<\" : \">\";\n    const [outputShape] = backend_util_exports.computeOutAndReduceShapes(inputShape, axes);\n    this.outputShape = outputShape.length === 0 ? [1] : outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, [1, 1, 1]);\n    this.inputShape = inputShape;\n    this.shaderKey = `argMinMax${this.op}`;\n  }\n  getUserCode() {\n    const sharedMemorySnippet = `\n      var<workgroup> xBestIndices : array<i32, ${this.workGroupSize[0]}>;\n      var<workgroup> xBestValues : array<f32, ${this.workGroupSize[0]}>;\n    `;\n    const getInputShapeLastDim = () => {\n      if (this.inputShape.length === 1) {\n        return \"uniforms.xShape\";\n      } else {\n        return `uniforms.xShape.${getCoordsXYZ(this.inputShape.length - 1)}`;\n      }\n    };\n    const splitOutputCoords = () => {\n      let snippet = \"\";\n      if (this.outputShape.length === 1) {\n        if (this.inputShape.length !== 1) {\n          snippet += \"outputCoords,\";\n        }\n      } else {\n        for (let i2 = 0; i2 < this.outputShape.length; i2++) {\n          snippet += `outputCoords.${getCoordsXYZ(i2)},`;\n        }\n      }\n      return snippet;\n    };\n    const userCode = `\n      fn DIV_CEIL(a : u32, b : u32) -> u32 {\n        return ((a - 1u) / b + 1u);\n      }\n\n      ${sharedMemorySnippet}\n\n      ${getMainHeaderAndGlobalIndexString()}\n        let outputIndex = index / i32(workGroupSizeX);\n        let reduceLength = ${getInputShapeLastDim()};\n\n        var bestIndex = i32(localId.x);\n        var bestValue = uniforms.infinityValue;\n        let outputCoords = getCoordsFromIndex(outputIndex);\n        for (var k = i32(localId.x); k < reduceLength && outputIndex < uniforms.size;\n            k = k + i32(workGroupSizeX)) {\n          let candidate = getX(${splitOutputCoords()} k);\n          if (!isnan(candidate) && candidate ${this.op} bestValue) {\n            bestValue = candidate;\n            bestIndex = k;\n          }\n        }\n        xBestValues[localId.x] = bestValue;\n        xBestIndices[localId.x] = bestIndex;\n        workgroupBarrier();\n\n        var reduceSize = min(u32(reduceLength), workGroupSizeX);\n        for (var currentSize = reduceSize / 2u; reduceSize > 1u;\n            currentSize = reduceSize / 2u) {\n          let interval = DIV_CEIL(reduceSize, 2u);\n          if (localId.x < currentSize) {\n            let candidate = xBestValues[localId.x + interval];\n            if (candidate ${this.op} bestValue) {\n              bestValue = candidate;\n              xBestValues[localId.x] = bestValue;\n              xBestIndices[localId.x] = xBestIndices[localId.x + interval];\n            }\n          }\n          reduceSize = interval;\n          workgroupBarrier();\n        }\n\n        if (localId.x == 0u && outputIndex < uniforms.size) {\n          setOutputAtIndexI32(outputIndex, xBestIndices[localId.x]);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/transpose_shared_webgpu.js\nvar TransposeSharedProgram = class {\n  constructor(aShape, newDim) {\n    this.variableNames = [\"A\"];\n    this.workGroupSize = [16, 16, 1];\n    const outputShape = new Array(aShape.length);\n    for (let i2 = 0; i2 < outputShape.length; i2++) {\n      outputShape[i2] = aShape[newDim[i2]];\n    }\n    this.outputShape = outputShape;\n    this.dispatchLayout = { x: [0], y: [1] };\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [1, 1, 1]);\n    this.shaderKey = \"transposeShared\";\n  }\n  getUserCode() {\n    const userCode = `\n      const TILE_DIM = ${this.workGroupSize[0]};\n      var<workgroup> tile : array<array<f32, ${this.workGroupSize[0] + 1}>, ${this.workGroupSize[0]}>;\n      ${getWorkGroupSizeString()}\n      fn main(@builtin(local_invocation_id) localId : vec3<u32>,\n              @builtin(workgroup_id) workgroupId : vec3<u32>) {\n        var x = i32(workgroupId.x) * TILE_DIM + i32(localId.x);\n        var y = i32(workgroupId.y) * TILE_DIM + i32(localId.y);\n        let width = uniforms.outShape[0];\n        let height = uniforms.outShape[1];\n        if (x < width && y < height) {\n          tile[localId.y][localId.x] = A[y * width + x];\n        }\n        workgroupBarrier();\n\n        x = i32(workgroupId.y) * TILE_DIM + i32(localId.x);\n        y = i32(workgroupId.x) * TILE_DIM + i32(localId.y);\n        if (x < height && y < width) {\n          setOutputAtIndex((y * height + x), tile[localId.x]\n            [localId.y]);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/transpose_webgpu.js\nvar TransposeProgram2 = class {\n  constructor(aShape, newDim) {\n    this.variableNames = [\"A\"];\n    this.workPerThread = 4;\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    const outputShape = new Array(aShape.length);\n    for (let i2 = 0; i2 < outputShape.length; i2++) {\n      outputShape[i2] = aShape[newDim[i2]];\n    }\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [this.workPerThread, 1, 1]);\n    this.newDim = newDim;\n    this.shaderKey = `transpose_${newDim}`;\n  }\n  getUserCode() {\n    const dtype = getCoordsDataType2(this.outputShape.length);\n    const switched = getSwitchedCoords2(this.newDim);\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n\n        for(var i = 0; i < ${this.workPerThread}; i = i + 1) {\n          let flatIndex = index * ${this.workPerThread} + i;\n          if(flatIndex < uniforms.size) {\n            let resRC = getCoordsFromIndex(flatIndex);\n            setOutputAtIndex(flatIndex, A[getIndexFromCoords${this.outputShape.length}D(\n              ${dtype}(${switched}), uniforms.aShape)]);\n          }\n        }\n      }\n    `;\n    return userCode;\n  }\n};\nfunction getSwitchedCoords2(newDim) {\n  const rank = newDim.length;\n  if (rank > 6) {\n    throw Error(`Transpose for rank ${rank} is not yet supported`);\n  }\n  const switchedCoords = new Array(rank);\n  for (let i2 = 0; i2 < newDim.length; i2++) {\n    switchedCoords[newDim[i2]] = `resRC.${getCoordsXYZ(i2)}`;\n  }\n  return switchedCoords.join();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Transpose.js\nfunction transpose5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { perm } = attrs;\n  const webgpuBackend = backend2;\n  const xRank = x.shape.length;\n  const newShape = new Array(xRank);\n  for (let i2 = 0; i2 < newShape.length; i2++) {\n    newShape[i2] = x.shape[perm[i2]];\n  }\n  if (backend2.shouldExecuteOnCPU([x])) {\n    const xData = webgpuBackend.tensorMap.get(x.dataId);\n    const values = xData.values;\n    const outValues = transposeImplCPU2(values, x.shape, x.dtype, perm, newShape);\n    return backend2.makeTensorInfo(newShape, x.dtype, outValues);\n  }\n  if (x.shape.length === 2 && util_exports.arraysEqual(perm, [1, 0])) {\n    const program2 = new TransposeSharedProgram(x.shape, perm);\n    return webgpuBackend.runWebGPUProgram(program2, [x], x.dtype);\n  }\n  const program = new TransposeProgram2(x.shape, perm);\n  return webgpuBackend.runWebGPUProgram(program, [x], x.dtype);\n}\nvar transposeConfig4 = {\n  kernelName: Transpose,\n  backendName: \"webgpu\",\n  kernelFunc: transpose5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ArgMax.js\nfunction argMax4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis } = attrs;\n  let axes = util_exports.parseAxisParam(axis, x.shape);\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  const intermediateTensorInfos = [];\n  if (permutedAxes != null) {\n    $x = transpose5({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    intermediateTensorInfos.push($x);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, $x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"argMax\", [axes[0]], $x.shape.length);\n  const program = new ArgMinMaxProgram2($x.shape, axes[0], \"max\");\n  const uniformData = [{ type: \"float32\", data: [Number.NEGATIVE_INFINITY] }];\n  const out = backend2.runWebGPUProgram(program, [$x], \"int32\", uniformData);\n  intermediateTensorInfos.forEach((t2) => backend2.disposeData(t2.dataId));\n  return out;\n}\nvar argMaxConfig4 = {\n  kernelName: ArgMax,\n  backendName: \"webgpu\",\n  kernelFunc: argMax4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ArgMin.js\nfunction argMin4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis } = attrs;\n  let axes = util_exports.parseAxisParam(axis, x.shape);\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  const intermediateTensorInfos = [];\n  if (permutedAxes != null) {\n    $x = transpose5({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    intermediateTensorInfos.push($x);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, $x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"argMin\", [axes[0]], $x.shape.length);\n  const program = new ArgMinMaxProgram2($x.shape, axes[0], \"min\");\n  const uniformData = [{ type: \"float32\", data: [Number.POSITIVE_INFINITY] }];\n  const out = backend2.runWebGPUProgram(program, [$x], \"int32\", uniformData);\n  intermediateTensorInfos.forEach((t2) => backend2.disposeData(t2.dataId));\n  return out;\n}\nvar argMinConfig3 = {\n  kernelName: ArgMin,\n  backendName: \"webgpu\",\n  kernelFunc: argMin4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/pool2d_webgpu.js\nvar Pool2DProgram2 = class {\n  constructor(convInfo, poolType) {\n    this.variableNames = [\"x\"];\n    this.uniforms = `stride : vec2<i32>, pad : vec2<i32>, dilation : vec2<i32>, convDims : vec2<i32>, filterDims : vec2<i32>,`;\n    this.workGroupSize = [128, 1, 1];\n    this.size = true;\n    this.outputShape = convInfo.outShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = `pool2D_${poolType}`;\n    this.poolType = poolType;\n  }\n  getUserCode() {\n    let updateSnippet = `resultValue = max(value, resultValue);`;\n    if (this.poolType === \"avg\") {\n      updateSnippet = `resultValue = resultValue + value; count = count + 1.0;`;\n    }\n    let returnValue = `resultValue`;\n    if (this.poolType === \"avg\") {\n      returnValue = `resultValue / count`;\n    }\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n      if (index < uniforms.size) {\n        let coords = getCoordsFromIndex(index);\n          let batch = coords[0];\n          let xRCCorner = vec2<i32>(coords.yz) * uniforms.stride - uniforms.pad;\n          let xRCorner = xRCCorner.x;\n          let xCCorner = xRCCorner.y;\n\n          var resultValue = ${this.poolType === \"avg\" ? \"0.0\" : \"-1.0 / pow(10.0, -20.0)\"};\n          var count = 0.0;\n\n          for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + uniforms.dilation.x) {\n            let xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= uniforms.convDims.x) {\n              continue;\n            }\n\n            for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + uniforms.dilation.y) {\n              let xC = xCCorner + wC;\n              if (xC < 0 || xC >= uniforms.convDims.y) {\n                continue;\n              }\n\n              let value = getX(batch, xR, xC, coords[3]);\n              ${updateSnippet}\n            }\n          }\n\n          setOutputAtIndex(index, ${returnValue});\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/pool_filtersizeone_webgpu.js\nvar PoolWithFilterSizeEqualsOneProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"x\"];\n    this.uniforms = `stride : vec2<i32>,`;\n    this.workGroupSize = [256, 1, 1];\n    this.size = true;\n    this.outputShape = convInfo.outShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = \"poolWithFilterSizeEqualsOne\";\n  }\n  getUserCode() {\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let coords = getCoordsFromIndex(index);\n          let batch = coords[0];\n          let d = coords[3];\n\n          let xRCCorner = coords.yz * uniforms.stride;\n          let xRCorner = xRCCorner.x;\n          let xCCorner = xRCCorner.y;\n\n          let value = getX(batch, xRCorner, xCCorner, d);\n          setOutputAtIndex(index, value);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/AvgPool.js\nfunction avgPool5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = 1;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  if (convInfo.filterWidth === 1 && convInfo.filterHeight === 1 && util_exports.arraysEqual(convInfo.inShape, convInfo.outShape)) {\n    return identity5({ inputs: { x }, backend: backend2 });\n  }\n  let program;\n  const dimensions = [{ type: \"int32\", data: [convInfo.strideHeight, convInfo.strideWidth] }];\n  if (convInfo.filterHeight === 1 && convInfo.filterWidth === 1) {\n    program = new PoolWithFilterSizeEqualsOneProgram(convInfo);\n  } else {\n    program = new Pool2DProgram2(convInfo, \"avg\");\n    dimensions.push({ type: \"int32\", data: [convInfo.padInfo.top, convInfo.padInfo.left] }, {\n      type: \"int32\",\n      data: [convInfo.dilationHeight, convInfo.dilationWidth]\n    }, { type: \"int32\", data: [convInfo.inHeight, convInfo.inWidth] }, {\n      type: \"int32\",\n      data: [convInfo.effectiveFilterHeight, convInfo.effectiveFilterWidth]\n    });\n  }\n  return backend2.runWebGPUProgram(program, [x], x.dtype, dimensions);\n}\nvar avgPoolConfig4 = {\n  kernelName: AvgPool,\n  backendName: \"webgpu\",\n  kernelFunc: avgPool5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/BatchMatMul.js\nfunction batchMatMul4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b } = inputs;\n  const { transposeA, transposeB } = attrs;\n  return batchMatMulImpl2({ a, b, transposeA, transposeB, backend: backend2 });\n}\nvar batchMatMulConfig4 = {\n  kernelName: BatchMatMul,\n  backendName: \"webgpu\",\n  kernelFunc: batchMatMul4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/slice_webgpu.js\nvar SliceProgram2 = class {\n  constructor(start, destSize) {\n    this.variableNames = [\"source\"];\n    this.workPerThread = 1;\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = destSize;\n    this.rank = destSize.length;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [this.workPerThread, 1, 1]);\n    this.start = start;\n    this.uniforms = `start : ${getCoordsDataType2(start.length)}, `;\n    this.shaderKey = \"slice\";\n  }\n  getUserCode() {\n    const dtype = getCoordsDataType2(this.rank);\n    const sourceCoords = getCoords3(this.rank);\n    let coordSum;\n    if (this.start.length === 1) {\n      coordSum = this.outputShape.map((_, i2) => {\n        return `sourceLoc = uniforms.start + coords;`;\n      });\n    } else {\n      coordSum = this.outputShape.map((_, i2) => {\n        return `sourceLoc.${coords2[i2]} = uniforms.start[${i2}] + coords.${coords2[i2]};`;\n      });\n    }\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          var sourceLoc : ${dtype};\n          let coords = getCoordsFromIndex(index);\n          ${coordSum.join(\"\\n\")}\n          setOutputAtIndex(index, getSource(${sourceCoords}));\n        }\n      }\n    `;\n    return userCode;\n  }\n};\nvar coords2 = [\"x\", \"y\", \"z\", \"w\", \"u\", \"v\"];\nfunction getCoords3(rank) {\n  if (rank === 1) {\n    return \"sourceLoc\";\n  } else if (rank <= 6) {\n    return coords2.slice(0, rank).map((coord) => `sourceLoc.${coord}`).join(\",\");\n  } else {\n    throw Error(`Slicing for rank ${rank} is not yet supported`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Slice.js\nfunction slice5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { begin, size } = attrs;\n  const [$begin, $size] = slice_util_exports.parseSliceParams(x, begin, size);\n  slice_util_exports.assertParamsValid(x, $begin, $size);\n  if (backend2.shouldExecuteOnCPU([x]) || x.dtype === \"string\") {\n    const xBufferInfo = backend2.tensorMap.get(x.dataId);\n    const outValues = sliceImplCPU2(xBufferInfo.values, $begin, $size, x.shape, x.dtype);\n    return backend2.makeTensorInfo($size, x.dtype, outValues);\n  }\n  if (util_exports.sizeFromShape($size) === 0) {\n    return backend2.makeTensorInfo($size, x.dtype, []);\n  }\n  const program = new SliceProgram2($begin, $size);\n  const uniformData = [{ type: \"int32\", data: $begin }];\n  return backend2.runWebGPUProgram(program, [x], x.dtype, uniformData);\n}\nvar sliceConfig4 = {\n  kernelName: Slice,\n  backendName: \"webgpu\",\n  kernelFunc: slice5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/BatchToSpaceND.js\nvar batchToSpaceND5 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, crops } = attrs;\n  util_exports.assert(x.shape.length <= 4, () => \"batchToSpaceND for rank > 4 with a WebGPU backend not implemented yet\");\n  const prod6 = blockShape.reduce((a, b) => a * b);\n  const reshaped = backend_util_exports.getReshaped(x.shape, blockShape, prod6);\n  const permuted = backend_util_exports.getPermuted(reshaped.length, blockShape.length);\n  const reshapedPermuted = backend_util_exports.getReshapedPermuted(x.shape, blockShape, prod6);\n  const sliceBeginCoords = backend_util_exports.getSliceBeginCoords(crops, blockShape.length);\n  const sliceSize = backend_util_exports.getSliceSize(reshapedPermuted, crops, blockShape.length);\n  const toDispose = [];\n  const reshapedIntermediate = reshape6({ inputs: { x }, backend: backend2, attrs: { shape: reshaped } });\n  const transposedIntermediate = transpose5({ inputs: { x: reshapedIntermediate }, backend: backend2, attrs: { perm: permuted } });\n  const reshapedIntermediate2 = reshape6({\n    inputs: { x: transposedIntermediate },\n    backend: backend2,\n    attrs: { shape: reshapedPermuted }\n  });\n  const sliced = slice5({\n    inputs: { x: reshapedIntermediate2 },\n    backend: backend2,\n    attrs: { begin: sliceBeginCoords, size: sliceSize }\n  });\n  toDispose.push(reshapedIntermediate);\n  toDispose.push(transposedIntermediate);\n  toDispose.push(reshapedIntermediate2);\n  toDispose.forEach((t2) => backend2.disposeData(t2.dataId));\n  return sliced;\n};\nvar batchToSpaceNDConfig4 = {\n  kernelName: BatchToSpaceND,\n  backendName: \"webgpu\",\n  kernelFunc: batchToSpaceND5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/NotEqual.js\nvar notEqual4 = binaryKernelFunc3({\n  opType: BinaryOpType.NOT_EQUAL,\n  dtype: \"bool\",\n  cpuKernelImpl: notEqualImplCPU2\n});\nvar notEqualConfig4 = {\n  kernelName: NotEqual,\n  backendName: \"webgpu\",\n  kernelFunc: notEqual4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Real.js\nfunction real4(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const inputData = backend2.tensorMap.get(input2.dataId);\n  return identity5({ inputs: { x: inputData.complexTensorInfos.real }, backend: backend2 });\n}\nvar realConfig3 = {\n  kernelName: Real,\n  backendName: \"webgpu\",\n  kernelFunc: real4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernel_utils/int.js\nfunction int2(input2, backend2) {\n  const program = new UnaryOpProgram2(input2.shape, UnaryOpType.TO_INT);\n  const output = backend2.runWebGPUProgram(program, [input2], \"int32\");\n  return { dataId: output.dataId, shape: output.shape, dtype: output.dtype };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Cast.js\nfunction cast6(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { dtype } = attrs;\n  if (dtype === \"complex64\") {\n    if (x.dtype === \"complex64\") {\n      return identity5({ inputs: { x }, backend: backend2 });\n    }\n    const zerosTensor = zeros(x.shape);\n    const floatX = cast6({ inputs: { x }, backend: backend2, attrs: { dtype: \"float32\" } });\n    const result = complex4({ inputs: { real: floatX, imag: zerosTensor }, backend: backend2 });\n    zerosTensor.dispose();\n    backend2.disposeData(floatX.dataId);\n    return result;\n  }\n  if (x.dtype === \"complex64\") {\n    const realPart = real4({ inputs: { input: x }, backend: backend2 });\n    const result = cast6({ inputs: { x: realPart }, backend: backend2, attrs: { dtype } });\n    backend2.disposeData(realPart.dataId);\n    return result;\n  }\n  if (!util_exports.hasEncodingLoss(x.dtype, dtype)) {\n    const result = identity5({ inputs: { x }, backend: backend2 });\n    return { dataId: result.dataId, shape: result.shape, dtype };\n  }\n  if (dtype === \"int32\") {\n    return int2(x, backend2);\n  }\n  if (dtype === \"bool\") {\n    const zerosTensorInfo = backend2.makeTensorInfo([], \"bool\", util_exports.getTypedArrayFromDType(\"bool\", 1));\n    const binaryInputs = { a: x, b: zerosTensorInfo };\n    const result = notEqual4({ inputs: binaryInputs, backend: backend2 });\n    backend2.disposeData(zerosTensorInfo.dataId);\n    return result;\n  }\n  throw new Error(`Error in Cast: failed to cast ${x.dtype} to ${dtype}`);\n}\nvar castConfig4 = {\n  kernelName: Cast,\n  backendName: \"webgpu\",\n  kernelFunc: cast6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Ceil.js\nvar ceil4 = unaryKernelFunc3({ opType: UnaryOpType.CEIL, cpuKernelImpl: ceilImplCPU2 });\nvar ceilConfig4 = {\n  kernelName: Ceil,\n  backendName: \"webgpu\",\n  kernelFunc: ceil4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/clip_vec4_webgpu.js\nvar ClipVec4Program = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.uniforms = \"minVal : f32, maxVal : f32,\";\n    this.workPerThread = 4;\n    this.workGroupSize = [64, 1, 1];\n    this.isVec4 = true;\n    this.size = true;\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [this.workPerThread, 1, 1]);\n    this.shaderKey = \"clipVec4\";\n  }\n  getUserCode() {\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if(index < uniforms.size) {\n          let value = getAByOutputIndex(index);\n          var clampedValue : vec4<f32>;\n          for (var i = 0; i < 4; i = i + 1) {\n            if (isnan(value[i])) {\n              clampedValue[i] = value[i];\n            } else {\n              clampedValue[i] = clamp(value[i], uniforms.minVal, uniforms.maxVal);\n            }\n          }\n\n          setOutputAtIndex(index, clampedValue);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/clip_webgpu.js\nvar ClipProgram2 = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.uniforms = \"minVal : f32, maxVal : f32,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = \"clip\";\n  }\n  getUserCode() {\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if(index < uniforms.size) {\n          let value = getAByOutputIndex(index);\n          if (isnan(value)) {\n            setOutputAtIndex(index, value);\n            return;\n          }\n          setOutputAtIndex(index, clamp(value, uniforms.minVal, uniforms.maxVal));\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ClipByValue.js\nfunction clipByValue4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { clipValueMin, clipValueMax } = attrs;\n  let program;\n  const uniformData = [\n    { type: \"float32\", data: [clipValueMin] },\n    { type: \"float32\", data: [clipValueMax] }\n  ];\n  if (util_exports.sizeFromShape(x.shape) % 4 === 0) {\n    program = new ClipVec4Program(x.shape);\n  } else {\n    program = new ClipProgram2(x.shape);\n  }\n  return backend2.runWebGPUProgram(program, [x], x.dtype, uniformData);\n}\nvar clipByValueConfig4 = {\n  kernelName: ClipByValue,\n  backendName: \"webgpu\",\n  kernelFunc: clipByValue4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/concat_webgpu.js\nvar ConcatProgram2 = class {\n  constructor(shapes) {\n    this.uniforms = \"\";\n    this.workPerThread = 4;\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = backend_util_exports.computeOutShape(shapes, 1);\n    this.variableNames = shapes.map((_, i2) => `T${i2}`);\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [this.workPerThread, 1, 1]);\n    this.offsetLength = shapes.length - 1;\n    for (let i2 = 0; i2 < this.offsetLength; i2++) {\n      this.uniforms += `offset${i2} : i32,`;\n    }\n    this.shaderKey = \"concat\";\n  }\n  getUserCode() {\n    const snippets = [];\n    if (this.offsetLength > 0) {\n      snippets.push(`if (yC < uniforms.offset0){ setOutputAtCoords(coords.x, coords.y, getT0(yR, yC)); }`);\n      for (let i2 = 1; i2 < this.offsetLength; i2++) {\n        snippets.push(`else if (yC < uniforms.offset${[i2]}){ setOutputAtCoords(coords.x, coords.y, getT${i2}(yR, yC - uniforms.offset${i2 - 1})); }`);\n      }\n      const lastIndex = this.offsetLength;\n      const lastShiftIndex = this.offsetLength - 1;\n      snippets.push(`else { setOutputAtCoords(coords.x, coords.y, getT${lastIndex}(yR, yC - uniforms.offset${lastShiftIndex})); }`);\n    } else {\n      snippets.push(`setOutputAtCoords(coords.x, coords.y, getT0(yR, yC));`);\n    }\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        for(var i = 0; i < ${this.workPerThread}; i = i + 1) {\n          let flatIndex = index * ${this.workPerThread} + i;\n          if(flatIndex < uniforms.size) {\n            let coords = getCoordsFromIndex(flatIndex);\n            let yR = coords.x;\n            let yC = coords.y;\n\n            ${snippets.join(\"\\n        \")}\n          }\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Imag.js\nfunction imag4(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const inputData = backend2.tensorMap.get(input2.dataId);\n  return identity5({ inputs: { x: inputData.complexTensorInfos.imag }, backend: backend2 });\n}\nvar imagConfig3 = {\n  kernelName: Imag,\n  backendName: \"webgpu\",\n  kernelFunc: imag4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Concat_impl.js\nfunction concatImpl3(inputs, axis, backend2) {\n  const dtype = inputs[0].dtype;\n  if (dtype === \"complex64\") {\n    const reals = inputs.map((t2) => real4({ inputs: { input: t2 }, backend: backend2 }));\n    const imags = inputs.map((t2) => imag4({ inputs: { input: t2 }, backend: backend2 }));\n    const realConcated = concatImpl3(reals, axis, backend2);\n    const imagConcated = concatImpl3(imags, axis, backend2);\n    const result = complex4({ inputs: { real: realConcated, imag: imagConcated }, backend: backend2 });\n    reals.forEach((r2) => backend2.disposeData(r2.dataId));\n    imags.forEach((i2) => backend2.disposeData(i2.dataId));\n    backend2.disposeData(realConcated.dataId);\n    backend2.disposeData(imagConcated.dataId);\n    return result;\n  }\n  let runOnCpu = backend2.shouldExecuteOnCPU(inputs);\n  if (dtype === \"string\") {\n    runOnCpu = true;\n  }\n  if (runOnCpu) {\n    const tensors2D2 = inputs.map((t2) => {\n      const innerSize = util_exports.sizeFromShape(t2.shape.slice(axis));\n      const shape = [-1, innerSize];\n      return reshape6({ inputs: { x: t2 }, backend: backend2, attrs: { shape } });\n    });\n    const inputsValShapes = tensors2D2.map((t2) => {\n      return { vals: backend2.readSync(t2.dataId), shape: t2.shape };\n    });\n    const outShape2 = backend_util_exports.computeOutShape(tensors2D2.map((t2) => t2.shape), 1);\n    const simplyConcat = tensors2D2[0].shape[0] === 1;\n    const outVals = concatImplCPU2(inputsValShapes, outShape2, dtype, simplyConcat);\n    const finalOutShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), axis);\n    const outInfo = backend2.makeTensorInfo(finalOutShape, dtype, outVals);\n    tensors2D2.forEach((t2) => backend2.disposeData(t2.dataId));\n    return outInfo;\n  }\n  const maxInputNum = backend2.device.limits.maxStorageBuffersPerShaderStage - 1;\n  if (inputs.length > maxInputNum) {\n    const reducedInputs = [];\n    for (let i2 = 0; i2 < inputs.length; i2 += maxInputNum) {\n      const subArray = inputs.slice(i2, i2 + maxInputNum);\n      reducedInputs.push(concatImpl3(subArray, axis, backend2));\n    }\n    const result = concatImpl3(reducedInputs, axis, backend2);\n    for (const i2 of reducedInputs) {\n      backend2.disposeData(i2.dataId);\n    }\n    return result;\n  }\n  const { tensors2D, outShape } = computeTensors2D2(inputs, axis, backend2);\n  const shapes = tensors2D.map((t2) => t2.shape);\n  const program = new ConcatProgram2(shapes);\n  const uniformData = [];\n  const offsets = new Array(shapes.length - 1);\n  if (offsets.length > 0) {\n    offsets[0] = shapes[0][1];\n    uniformData.push({ type: \"int32\", data: [offsets[0]] });\n    for (let i2 = 1; i2 < offsets.length; i2++) {\n      offsets[i2] = offsets[i2 - 1] + shapes[i2][1];\n      uniformData.push({ type: \"int32\", data: [offsets[i2]] });\n    }\n  }\n  const res = backend2.runWebGPUProgram(program, tensors2D, tensors2D[0].dtype, uniformData);\n  tensors2D.forEach((r2) => backend2.disposeData(r2.dataId));\n  const reshapedResult = reshape6({ inputs: { x: res }, backend: backend2, attrs: { shape: outShape } });\n  backend2.disposeData(res.dataId);\n  return reshapedResult;\n}\nfunction computeTensors2D2(inputs, axis, backend2) {\n  const outShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), axis);\n  const tensors2D = inputs.map((t2) => reshape6({\n    inputs: { x: t2 },\n    backend: backend2,\n    attrs: {\n      shape: [\n        util_exports.sizeFromShape(t2.shape.slice(0, axis)),\n        util_exports.sizeFromShape(t2.shape.slice(axis))\n      ]\n    }\n  }));\n  return { tensors2D, outShape };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Concat.js\nfunction concat5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { axis } = attrs;\n  const $axis = util_exports.parseAxisParam(axis, inputs[0].shape)[0];\n  const outShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), $axis);\n  if (util_exports.sizeFromShape(outShape) === 0) {\n    return backend2.makeTensorInfo(outShape, inputs[0].dtype, []);\n  }\n  const $inputs = inputs.filter((t2) => util_exports.sizeFromShape(t2.shape) > 0);\n  if ($inputs.length === 1) {\n    return identity5({ inputs: { x: $inputs[0] }, backend: backend2 });\n  }\n  const shapes = $inputs.map((t2) => t2.shape);\n  backend_util_exports.assertParamsConsistent(shapes, $axis);\n  return concatImpl3($inputs, $axis, backend2);\n}\nvar concatConfig4 = {\n  kernelName: Concat,\n  backendName: \"webgpu\",\n  kernelFunc: concat5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/conv2d_mm_webgpu.js\nfunction conv2dCommonSnippet(isChannelsLast, fitAOuter, fitBOuter, fitInner, addBias = false, activation2 = null, hasPreluActivationWeights = false, innerElementSizeX = 4, innerElementSizeW = 4, innerElementSize = 4) {\n  const getXSnippet = (innerElementSize2) => {\n    switch (innerElementSize2) {\n      case 1:\n        return \"resData = x[xIndex];\";\n      case 3:\n        return \"resData = vec3<f32>(x[xIndex], x[xIndex + 1], x[xIndex + 2]);\";\n      case 4:\n        return \"resData = x[xIndex / 4];\";\n      default:\n        throw new Error(`innerElementSize ${innerElementSize2} is not supported.`);\n    }\n  };\n  const getWSnippet = (innerElementSize2) => {\n    switch (innerElementSize2) {\n      case 1:\n        return \"return W[row * uniforms.wShape[3] + colIn];\";\n      case 4:\n        return \"return W[row * uniforms.wShape[3] / 4 + colIn];\";\n      default:\n        throw new Error(`innerElementSize ${innerElementSize2} is not supported.`);\n    }\n  };\n  const coordASnippet = isChannelsLast ? `\n      let coord = vec4<i32>(batch, xRow, xCol, xCh);\n      ` : `\n      let coord = vec4<i32>(batch, xCh, xRow, xCol);\n      `;\n  const coordResSnippet = isChannelsLast ? `\n      let coords = vec4<i32>(\n        batch,\n        row / outWidth,\n        row % outWidth,\n        col);\n      ` : `\n      let coords = vec4<i32>(\n        batch,\n        row,\n        col / outWidth,\n        col % outWidth);\n      `;\n  const xHight = isChannelsLast ? \"uniforms.xShape[1]\" : \"uniforms.xShape[2]\";\n  const xWidth = isChannelsLast ? \"uniforms.xShape[2]\" : \"uniforms.xShape[3]\";\n  const row = isChannelsLast ? \"row\" : \"col\";\n  const col = isChannelsLast ? \"col\" : \"row\";\n  const readXSnippet = `\n      let inChannels = uniforms.wShape[2];\n      let outWidth = ${isChannelsLast ? \"uniforms.outShape[2]\" : \"uniforms.outShape[3]\"};\n      let outRow = ${row} / outWidth;\n      let outCol = ${row} % outWidth;\n\n      let WRow = ${col} / (uniforms.filterDims[1] * inChannels);\n      let WCol = ${col} / inChannels % uniforms.filterDims[1];\n      let xRow = outRow * uniforms.stride[0] + uniforms.dilation[0] * WRow - uniforms.pad[0];\n      let xCol = outCol * uniforms.stride[1] + uniforms.dilation[1] * WCol - uniforms.pad[1];\n      let xCh = ${col} % inChannels;\n      var resData = ${typeSnippet(innerElementSizeX)}(0.0);\n      // The bounds checking is always needed since we use it to pad zero for\n      // the 'same' padding type.\n      if (xRow >= 0 && xRow < ${xHight} && xCol >= 0 && xCol < ${xWidth}) {\n        ${coordASnippet}\n        let xIndex = getIndexFromCoords4D(coord, uniforms.xShape);\n        ${getXSnippet(innerElementSizeX)}\n      }\n      return resData;`;\n  const sampleX = isChannelsLast ? fitAOuter && fitInner ? `\n      let col = colIn * ${innerElementSizeX};\n      ${readXSnippet}` : `\n      let col = colIn * ${innerElementSizeX};\n      if (row < uniforms.dimAOuter && col < uniforms.dimInner) {\n        ${readXSnippet}\n      }\n      return ${typeSnippet(innerElementSizeX)}(0.0);` : fitInner && fitBOuter ? `\n      let col = colIn * ${innerElementSizeX};\n      ${readXSnippet}` : `\n      let col = colIn * ${innerElementSizeX};\n      if (row < uniforms.dimInner && col < uniforms.dimBOuter) {\n        ${readXSnippet}\n      }\n      return ${typeSnippet(innerElementSizeX)}(0.0);`;\n  const sampleW = `${getWSnippet(innerElementSizeW)}`;\n  const resType = typeSnippet(innerElementSize);\n  const aType = isChannelsLast ? typeSnippet(innerElementSizeX) : typeSnippet(innerElementSizeW);\n  const bType = isChannelsLast ? typeSnippet(innerElementSizeW) : typeSnippet(innerElementSizeX);\n  const userCode = `\n      ${activationFnSnippet(activation2, hasPreluActivationWeights, innerElementSize === 4, 4)}\n      fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${aType} {\n        ${isChannelsLast ? sampleX : sampleW}\n      }\n\n      fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${bType} {\n        ${isChannelsLast ? sampleW : sampleX}\n      }\n\n      fn mm_write(batch: i32, row : i32, colIn : i32, valueIn : ${resType}) {\n        let col = colIn * ${innerElementSize};\n        if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)\n        {\n        var value = valueIn;\n        let outWidth = ${isChannelsLast ? \"uniforms.outShape[2]\" : \"uniforms.outShape[3]\"};\n        ${coordResSnippet}\n        ${biasActivationSnippet(addBias, activation2)}\n        setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);\n        }\n      }`;\n  return userCode;\n}\nvar Conv2DMMProgram = class {\n  constructor(convInfo, dimAOuter, dimBOuter, dimInner, addBias = false, activation2 = null, hasPreluActivationWeights = false) {\n    this.variableNames = [\"x\", \"W\"];\n    this.uniforms = `filterDims : vec2<i32>, pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,`;\n    this.outputShape = convInfo.outShape;\n    this.isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n    this.isVec4 = ((convInfo.inChannels % 4 === 0 || convInfo.inChannels % 3 === 0) && this.isChannelsLast || convInfo.outWidth % 4 === 0 && !this.isChannelsLast) && convInfo.outChannels % 4 === 0;\n    this.dispatchLayout = this.isChannelsLast ? { x: [3], y: [1, 2], z: [0] } : { x: [2, 3], y: [1], z: [0] };\n    this.workGroupSize = computeWorkGroupSizeForConv2d(this.dispatchLayout, this.outputShape, this.isVec4);\n    this.elementsPerThread = computeWorkPerThreadForConv2d(this.dispatchLayout, this.outputShape, this.isVec4);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, this.elementsPerThread);\n    if (this.isVec4) {\n      if (this.isChannelsLast && convInfo.inChannels % 4 !== 0) {\n        this.innerElementSize = 3;\n        this.variableTypes = [\"f32\", \"vec4<f32>\"];\n      } else {\n        this.innerElementSize = 4;\n        this.variableTypes = [\"vec4<f32>\", \"vec4<f32>\"];\n      }\n      if (addBias) {\n        this.variableNames.push(\"bias\");\n        this.variableTypes.push(\"vec4<f32>\");\n      }\n      if (hasPreluActivationWeights) {\n        this.variableNames.push(\"preluActivationWeights\");\n        this.variableTypes.push(\"vec4<f32>\");\n      }\n    } else {\n      this.innerElementSize = this.elementsPerThread[0];\n      if (addBias) {\n        this.variableNames.push(\"bias\");\n      }\n      if (hasPreluActivationWeights) {\n        this.variableNames.push(\"preluActivationWeights\");\n      }\n    }\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivationWeights = hasPreluActivationWeights;\n    this.tileAOuter = this.workGroupSize[1] * this.elementsPerThread[1];\n    this.tileBOuter = this.workGroupSize[0] * this.elementsPerThread[0];\n    this.tileInner = Math.max(this.workGroupSize[0] * this.innerElementSize, this.workGroupSize[1]);\n    this.fitAOuter = dimAOuter % this.tileAOuter === 0;\n    this.fitBOuter = dimBOuter % this.tileBOuter === 0;\n    this.fitInner = dimInner % this.tileInner === 0;\n    this.shaderKey = `conv2DMM_${this.elementsPerThread}_${this.activation}}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.innerElementSize}_${this.isChannelsLast}`;\n  }\n  getUserCode() {\n    const matMulSource = this.isVec4 ? makeMatMulPackedVec4Source(this.elementsPerThread, this.tileAOuter, this.tileBOuter, this.tileInner, this.innerElementSize, !this.isChannelsLast) : makeMatMulPackedSource(this.elementsPerThread, this.workGroupSize, !this.isChannelsLast, this.tileInner);\n    const elementsSize = this.isVec4 ? [this.isChannelsLast ? this.innerElementSize : 4, 4, 4] : [1, 1, 1];\n    const userCode = `\n    ${conv2dCommonSnippet(this.isChannelsLast, this.fitAOuter, this.fitBOuter, this.fitInner, this.addBias, this.activation, this.hasPreluActivationWeights, elementsSize[0], elementsSize[1], elementsSize[2])}\n    ${matMulSource}\n  `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Conv2D_impl.js\nfunction getShapeForBatchMatMul2(shape, isChannelsLast) {\n  const length = shape.length;\n  if (length >= 3) {\n    return isChannelsLast ? [\n      ...shape.slice(0, -3),\n      shape[length - 3] * shape[length - 2],\n      shape[length - 1]\n    ] : [\n      ...shape.slice(0, -3),\n      shape[length - 3],\n      shape[length - 2] * shape[length - 1]\n    ];\n  } else if (!isChannelsLast && length === 1 && shape[0] > 1) {\n    return [shape[0], 1];\n  } else {\n    return null;\n  }\n}\nfunction conv2dByMatMul2({ x, filter, convInfo, backend: backend2, bias = null, preluActivationWeights = null, leakyreluAlpha = 0, activation: activation2 = null }) {\n  const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n  const transposeA = isChannelsLast ? false : true;\n  const transposeB = false;\n  const sameSize = isChannelsLast && convInfo.filterHeight === convInfo.inHeight && convInfo.filterWidth === convInfo.inWidth && convInfo.padInfo.type === \"VALID\";\n  const intermediates = [];\n  let xReshaped;\n  let filterReshaped;\n  if (sameSize) {\n    const sharedDim = convInfo.inHeight * convInfo.inWidth * convInfo.inChannels;\n    xReshaped = reshape6({\n      inputs: { x },\n      backend: backend2,\n      attrs: { shape: [1, convInfo.batchSize, sharedDim] }\n    });\n    filterReshaped = reshape6({\n      inputs: { x: filter },\n      backend: backend2,\n      attrs: { shape: [1, sharedDim, convInfo.outChannels] }\n    });\n  } else {\n    xReshaped = reshape6({\n      inputs: { x },\n      backend: backend2,\n      attrs: {\n        shape: isChannelsLast ? [\n          convInfo.batchSize,\n          convInfo.inHeight * convInfo.inWidth,\n          convInfo.inChannels\n        ] : [\n          convInfo.batchSize,\n          convInfo.inChannels,\n          convInfo.inHeight * convInfo.inWidth\n        ]\n      }\n    });\n    filterReshaped = reshape6({\n      inputs: { x: filter },\n      backend: backend2,\n      attrs: { shape: [1, convInfo.inChannels, convInfo.outChannels] }\n    });\n  }\n  intermediates.push(xReshaped);\n  intermediates.push(filterReshaped);\n  if (preluActivationWeights != null) {\n    const targetShape = getShapeForBatchMatMul2(preluActivationWeights.shape, isChannelsLast);\n    if (targetShape != null) {\n      preluActivationWeights = reshape6({\n        inputs: { x: preluActivationWeights },\n        backend: backend2,\n        attrs: { shape: targetShape }\n      });\n      intermediates.push(preluActivationWeights);\n    }\n  }\n  if (bias != null) {\n    const targetShape = getShapeForBatchMatMul2(bias.shape, isChannelsLast);\n    if (targetShape != null) {\n      bias = reshape6({ inputs: { x: bias }, backend: backend2, attrs: { shape: targetShape } });\n      intermediates.push(bias);\n    }\n  }\n  const result = batchMatMulImpl2({\n    a: isChannelsLast ? xReshaped : filterReshaped,\n    b: isChannelsLast ? filterReshaped : xReshaped,\n    transposeA,\n    transposeB,\n    backend: backend2,\n    bias,\n    activation: activation2,\n    preluActivationWeights,\n    leakyreluAlpha\n  });\n  const out = reshape6({ inputs: { x: result }, backend: backend2, attrs: { shape: convInfo.outShape } });\n  intermediates.push(result);\n  for (const i2 of intermediates) {\n    backend2.disposeData(i2.dataId);\n  }\n  return out;\n}\nfunction conv2DImpl({ x, filter, convInfo, backend: backend2, bias = null, preluActivationWeights = null, leakyreluAlpha = 0, activation: activation2 = null }) {\n  const hasBias = bias != null;\n  const hasPreluActivationWeights = preluActivationWeights != null;\n  const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n  const sameSize = isChannelsLast && convInfo.filterHeight === convInfo.inHeight && convInfo.filterWidth === convInfo.inWidth && convInfo.padInfo.type === \"VALID\";\n  if (sameSize || convInfo.filterHeight === 1 && convInfo.filterWidth === 1 && convInfo.dilationHeight === 1 && convInfo.dilationWidth === 1 && convInfo.strideHeight === 1 && convInfo.strideWidth === 1 && (convInfo.padInfo.type === \"SAME\" || convInfo.padInfo.type === \"VALID\")) {\n    return conv2dByMatMul2({\n      x,\n      filter,\n      convInfo,\n      backend: backend2,\n      bias,\n      activation: activation2,\n      preluActivationWeights,\n      leakyreluAlpha\n    });\n  }\n  const dimAOuter = isChannelsLast ? convInfo.outHeight * convInfo.outWidth : convInfo.outChannels;\n  const dimBOuter = isChannelsLast ? convInfo.outChannels : convInfo.outHeight * convInfo.outWidth;\n  const dimInner = convInfo.filterHeight * convInfo.filterWidth * convInfo.inChannels;\n  const padInfo = [convInfo.padInfo.top, convInfo.padInfo.left];\n  const dimensions = [\n    { type: \"int32\", data: [convInfo.filterHeight, convInfo.filterWidth] },\n    { type: \"int32\", data: [...padInfo] },\n    { type: \"int32\", data: [convInfo.strideHeight, convInfo.strideWidth] },\n    { type: \"int32\", data: [convInfo.dilationHeight, convInfo.dilationWidth] },\n    { type: \"int32\", data: [dimAOuter] },\n    { type: \"int32\", data: [dimBOuter] },\n    { type: \"int32\", data: [dimInner] }\n  ];\n  const program = new Conv2DMMProgram(convInfo, dimAOuter, dimBOuter, dimInner, hasBias, activation2, hasPreluActivationWeights);\n  const intermediates = [];\n  const inputVar = [x, filter];\n  if (hasBias) {\n    if (!isChannelsLast && bias.shape.length === 1) {\n      bias = reshape6({ inputs: { x: bias }, backend: backend2, attrs: { shape: [bias.shape[0], 1, 1] } });\n      intermediates.push(bias);\n    }\n    inputVar.push(bias);\n  }\n  if (hasPreluActivationWeights) {\n    if (!isChannelsLast && preluActivationWeights.shape.length === 1) {\n      preluActivationWeights = reshape6({\n        inputs: { x: preluActivationWeights },\n        backend: backend2,\n        attrs: { shape: [preluActivationWeights.shape[0], 1, 1] }\n      });\n      intermediates.push(preluActivationWeights);\n    }\n    inputVar.push(preluActivationWeights);\n  }\n  if (activation2 === \"leakyrelu\") {\n    dimensions.push({ type: \"float32\", data: [leakyreluAlpha] });\n    program.uniforms += \" alpha : f32,\";\n  }\n  const out = backend2.runWebGPUProgram(program, inputVar, x.dtype, dimensions);\n  for (const i2 of intermediates) {\n    backend2.disposeData(i2.dataId);\n  }\n  return out;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Conv2D.js\nfunction conv2d6(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode, false, $dataFormat);\n  return conv2DImpl({ x, filter, convInfo, backend: backend2 });\n}\nvar conv2DConfig4 = {\n  kernelName: Conv2D,\n  backendName: \"webgpu\",\n  kernelFunc: conv2d6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/conv_backprop_mm_webgpu.js\nfunction conv2dTransposeCommonSnippet(innerElementSize = 4) {\n  const getWSnippet = (innerElementSize2) => {\n    switch (innerElementSize2) {\n      case 1:\n        return \"return W[getIndexFromCoords4D(coord, uniforms.wShape)];\";\n      case 4:\n        return `\n            let coord1 = vec4<i32>(coordX, coordY, col + 1, rowInner);\n            let coord2 = vec4<i32>(coordX, coordY, col + 2, rowInner);\n            let coord3 = vec4<i32>(coordX, coordY, col + 3, rowInner);\n            let v0 = W[getIndexFromCoords4D(coord, uniforms.wShape)];\n            let v1 = W[getIndexFromCoords4D(coord1, uniforms.wShape)];\n            let v2 = W[getIndexFromCoords4D(coord2, uniforms.wShape)];\n            let v3 = W[getIndexFromCoords4D(coord3, uniforms.wShape)];\n            return vec4<f32>(v0, v1, v2, v3);\n            `;\n      default:\n        throw new Error(`innerElementSize ${innerElementSize2} is not supported.`);\n    }\n  };\n  const readASnippet = `\n      let outRow = row / uniforms.outShape[2];\n      let outCol = row % uniforms.outShape[2];\n\n      let WRow = col / (uniforms.filterDims[1] * uniforms.outBackprop[3]);\n      let WCol = col / uniforms.outBackprop[3] % uniforms.filterDims[1];\n      let xR = f32(outRow - uniforms.pads[0] + WRow) / f32(uniforms.stride[0]);\n      let xC = f32(outCol - uniforms.pads[1] + WCol) / f32(uniforms.stride[1]);\n      if (xR < 0.0 || xR >= f32(uniforms.outBackprop[1]) || fract(xR) > 0.0) {\n        return ${typeSnippet(innerElementSize)}(0.0);\n      }\n      if (xC < 0.0 || xC >= f32(uniforms.outBackprop[2]) || fract(xC) > 0.0) {\n        return ${typeSnippet(innerElementSize)}(0.0);\n      }\n      let coord = vec4<i32>(\n          batch,\n          i32(xR),\n          i32(xC),\n          col % uniforms.outBackprop[3]);\n      return x[getIndexFromCoords4D(coord, uniforms.xShape)/${innerElementSize}];`;\n  const sampleA = `if (row < uniforms.dimAOuter && col < uniforms.dimInner) {\n        ${readASnippet}\n      }\n      return ${typeSnippet(innerElementSize)}(0.0);`;\n  const userCode = `\n  fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${typeSnippet(innerElementSize)} {\n    let col = colIn * ${innerElementSize};\n    ${sampleA}\n  }\n\n  fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${typeSnippet(innerElementSize)} {\n    let col = colIn * ${innerElementSize};\n    let coordX = uniforms.filterDims.x - 1 -\n        row / (uniforms.filterDims[1] * uniforms.outBackprop[3]);\n    let coordY = uniforms.filterDims.y - 1 -\n        (row / uniforms.outBackprop[3]) % uniforms.filterDims[1];\n    if (row < uniforms.dimInner && col < uniforms.dimBOuter &&\n        coordX >= 0 && coordY >= 0) {\n      let rowInner = row % uniforms.outBackprop[3];\n      let coord = vec4<i32>(coordX, coordY, col, rowInner);\n      ${getWSnippet(innerElementSize)}\n    }\n    return ${typeSnippet(innerElementSize)}(0.0);\n  }\n\n  fn mm_write(batch: i32, row : i32, colIn : i32, valueInput : ${typeSnippet(innerElementSize)}) {\n    let col = colIn * ${innerElementSize};\n    if (row < uniforms.dimAOuter && (col + ${innerElementSize - 1}) < uniforms.dimBOuter) {\n      var value = valueInput;\n      let outCoord = vec4<i32>(\n          batch,\n          row / uniforms.outShape[2],\n          row % uniforms.outShape[2],\n          col);\n      result[getIndexFromCoords4D(outCoord, uniforms.outShape)/${innerElementSize}] = value;\n    }\n  }`;\n  return userCode;\n}\nvar Conv2DDerInputMMProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"x\", \"W\"];\n    this.uniforms = \"filterDims : vec2<i32>, pads : vec2<i32>, stride : vec2<i32>, outBackprop : vec4<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,\";\n    this.outputShape = convInfo.inShape;\n    util_exports.assert(convInfo.dataFormat === \"channelsLast\", () => \"TODO: NCHW is unimplemented\");\n    this.isVec4 = convInfo.inChannels % 4 === 0 && convInfo.outChannels % 4 === 0;\n    this.dispatchLayout = { x: [3], y: [1, 2], z: [0] };\n    this.workGroupSize = computeWorkGroupSizeForConv2d(this.dispatchLayout, this.outputShape, this.isVec4);\n    this.elementsPerThread = computeWorkPerThreadForConv2d(this.dispatchLayout, this.outputShape, this.isVec4);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, this.elementsPerThread);\n    if (this.isVec4) {\n      this.innerElementSize = 4;\n      this.variableTypes = [\"vec4<f32>\", \"f32\"];\n    } else {\n      this.innerElementSize = this.elementsPerThread[0];\n    }\n    this.tileAOuter = this.workGroupSize[1] * this.elementsPerThread[1];\n    this.tileBOuter = this.workGroupSize[0] * this.elementsPerThread[0];\n    this.tileInner = Math.max(this.workGroupSize[0] * this.innerElementSize, this.workGroupSize[1]);\n    this.shaderKey = `conv2DDerInputMM_${this.isVec4}_${this.elementsPerThread}_${this.innerElementSize}`;\n  }\n  getUserCode() {\n    const matMulSource = this.isVec4 ? makeMatMulPackedVec4Source(this.elementsPerThread, this.tileAOuter, this.tileBOuter, this.tileInner, this.innerElementSize) : makeMatMulPackedSource(this.elementsPerThread, this.workGroupSize);\n    const userCode = `\n    ${conv2dTransposeCommonSnippet(this.isVec4 ? 4 : 1)}\n    ${matMulSource}\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/conv_backprop_webgpu.js\nvar Conv2DDerInputProgram2 = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\", \"W\"];\n    this.uniforms = \"filterDims : vec2<i32>, pads : vec2<i32>, stride : vec2<i32>, outBackprop : vec4<i32>,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = convInfo.inShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n    this.shaderKey = `conv2DDerInput_${this.isChannelsLast}`;\n  }\n  getUserCode() {\n    const rowDim = this.isChannelsLast ? 1 : 2;\n    const colDim = this.isChannelsLast ? 2 : 3;\n    const channelDim = this.isChannelsLast ? 3 : 1;\n    return `\n    ${getMainHeaderAndGlobalIndexString()} {\n      if(index < uniforms.size) {\n        let coords = getCoordsFromIndex(index);\n        let batch = coords[0];\n        let d1 = coords[${channelDim}];\n\n        let dyCorner = vec2<i32>(coords[${rowDim}]), coords[${colDim}]) - uniforms.pads;\n        let dyRCorner = dyCorner.x;\n        let dyCCorner = dyCorner.y;\n\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\n        // ? = to be determined. : = across all values in that axis.\n        var dotProd = 0.0;\n        for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + 1) {\n          let dyR = (f32(dyRCorner) + f32(wR)) / f32(uniforms.stride.x);\n          let wRPerm = uniforms.filterDims.x - 1 - wR;\n          if (dyR < 0.0 || dyR >= f32(uniforms.outBackprop[1]) || fract(dyR) > 0.0 ||\n              wRPerm < 0) {\n            continue;\n          }\n          let idyR = dyR;\n\n          for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + 1) {\n            let dyC = (f32(dyCCorner) + f32(wC)) / f32(uniforms.stride.y);\n            let wCPerm = uniforms.filterDims.y - 1 - wC;\n            if (dyC < 0.0 || dyC >= f32(uniforms.outBackprop[2]) ||\n                fract(dyC) > 0.0 || wCPerm < 0) {\n              continue;\n            }\n            let idyC = dyC;\n\n            for (var d2 = 0; d2 < uniforms.outBackprop[3]; d2 = d2 + 1) {\n              if (${this.isChannelsLast}) {\n                let xValue = getDy(batch, idyR, idyC, d2);\n                let wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd = dotProd + xValue * wValue;\n              } else {\n                let xValue = getDy(batch, d2, idyR, idyC);\n                let wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd = dotProd + xValue * wValue;\n              }\n\n            }\n          }\n        }\n        setOutputAtIndex(index, dotProd);\n      }\n    }\n  `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Conv2DBackpropInput.js\nfunction conv2DBackpropInput5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, filter } = inputs;\n  const { inputShape, strides, pad: pad3, dataFormat, dimRoundingMode } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(inputShape, filter.shape, strides, 1, pad3, dimRoundingMode, false, $dataFormat);\n  const dimensions = [\n    { type: \"int32\", data: [convInfo.filterHeight, convInfo.filterWidth] },\n    {\n      type: \"int32\",\n      data: [\n        convInfo.filterHeight - 1 - convInfo.padInfo.top,\n        convInfo.filterWidth - 1 - convInfo.padInfo.left\n      ]\n    },\n    { type: \"int32\", data: [convInfo.strideHeight, convInfo.strideWidth] },\n    {\n      type: \"int32\",\n      data: [\n        convInfo.batchSize,\n        convInfo.outHeight,\n        convInfo.outWidth,\n        convInfo.outChannels\n      ]\n    }\n  ];\n  let program;\n  if (env().getBool(\"WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE\")) {\n    program = new Conv2DDerInputProgram2(convInfo);\n  } else {\n    program = new Conv2DDerInputMMProgram(convInfo);\n    const dimAOuter = convInfo.inShape[1] * convInfo.inShape[2];\n    const dimBOuter = convInfo.inShape[3];\n    const dimInner = convInfo.filterHeight * convInfo.filterWidth * convInfo.outChannels;\n    dimensions.push({ type: \"uint32\", data: [dimAOuter] }, { type: \"uint32\", data: [dimBOuter] }, { type: \"uint32\", data: [dimInner] });\n  }\n  return backend2.runWebGPUProgram(program, [dy, filter], \"float32\", dimensions);\n}\nvar conv2DBackpropInputConfig4 = {\n  kernelName: Conv2DBackpropInput,\n  backendName: \"webgpu\",\n  kernelFunc: conv2DBackpropInput5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Cos.js\nvar cos4 = unaryKernelFunc3({ opType: UnaryOpType.COS });\nvar cosConfig4 = {\n  kernelName: Cos,\n  backendName: \"webgpu\",\n  kernelFunc: cos4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Cosh.js\nvar cosh4 = unaryKernelFunc3({ opType: UnaryOpType.COSH });\nvar coshConfig4 = {\n  kernelName: Cosh,\n  backendName: \"webgpu\",\n  kernelFunc: cosh4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/crop_and_resize_webgpu.js\nvar CropAndResizeProgram2 = class {\n  constructor(channnel, boxShape, cropSize, method) {\n    this.variableNames = [\"Image\", \"Boxes\", \"BoxInd\"];\n    this.uniforms = \"extrapolationValue : f32,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    const [numBoxes] = boxShape;\n    this.outputShape = [numBoxes, cropSize[0], cropSize[1], channnel];\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.methodId = method === \"bilinear\" ? 1 : 0;\n    this.cropHeightBiggerThan1 = this.outputShape[1] > 1;\n    this.cropWidthBiggerThan1 = this.outputShape[2] > 1;\n    this.shaderKey = `cropAndResize_${this.methodId}_${this.cropHeightBiggerThan1}_${this.cropWidthBiggerThan1}`;\n  }\n  getUserCode() {\n    const [inputHeightFloat, inputWidthFloat] = [`f32(uniforms.imageShape[1] - 1)`, `f32(uniforms.imageShape[2] - 1)`];\n    const [heightRatio, heightScale, inY] = this.cropHeightBiggerThan1 ? [\n      `(${inputHeightFloat} / f32(uniforms.outShape[1] - 1))`,\n      \"(y2-y1) * height_ratio\",\n      `y1*${inputHeightFloat} + f32(y)*(height_scale)`\n    ] : [\n      \"0.0\",\n      \"0.0\",\n      `0.5 * (y1+y2) * ${inputHeightFloat}`\n    ];\n    const [widthRatio, widthScale, inX] = this.cropWidthBiggerThan1 ? [\n      `(${inputWidthFloat} / f32(uniforms.outShape[2] - 1))`,\n      \"(x2-x1) * width_ratio\",\n      `x1*${inputWidthFloat} + f32(x)*(width_scale)`\n    ] : [\n      \"0.0\",\n      \"0.0\",\n      `0.5 * (x1+x2) * ${inputWidthFloat}`\n    ];\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n      if (index < uniforms.size) {\n        let coords = getCoordsFromIndex(index);\n        let height_ratio = f32(${heightRatio});\n        let width_ratio = f32(${widthRatio});\n        let b = coords[0];\n        let y = coords[1];\n        let x = coords[2];\n        let d = coords[3];\n        // get box vals\n        let y1 = getBoxes(b, 0);\n        let x1 = getBoxes(b, 1);\n        let y2 = getBoxes(b, 2);\n        let x2 = getBoxes(b, 3);\n        // get image in batch index\n        let bInd = i32(round(getBoxInd(b)));\n        if(bInd < 0 || bInd >= uniforms.outShape[0]) {\n          return;\n        }\n        let height_scale = ${heightScale};\n        let width_scale = ${widthScale};\n        let in_y = ${inY};\n        if( in_y < 0.0 || in_y > ${inputHeightFloat} ) {\n          setOutputAtIndex(index, uniforms.extrapolationValue);\n          return;\n        }\n        let in_x = ${inX};\n        if( in_x < 0.0 || in_x > ${inputWidthFloat} ) {\n          setOutputAtIndex(index, uniforms.extrapolationValue);\n          return;\n        }\n        let sourceFracIndexCR = vec2<f32>(in_x,in_y);\n        if(${this.methodId} == 1) {\n          // Compute the four integer indices.\n          let sourceFloorCR = vec2<i32>(sourceFracIndexCR);\n          let sourceCeilCR = vec2<i32>(ceil(sourceFracIndexCR));\n          let topLeft = getImage(bInd, sourceFloorCR.y, sourceFloorCR.x, d);\n          let bottomLeft = getImage(bInd, sourceCeilCR.y, sourceFloorCR.x, d);\n          let topRight = getImage(bInd, sourceFloorCR.y, sourceCeilCR.x, d);\n          let bottomRight = getImage(bInd, sourceCeilCR.y, sourceCeilCR.x, d);\n          let fracCR = sourceFracIndexCR - vec2<f32>(sourceFloorCR);\n          let top = topLeft + (topRight - topLeft) * fracCR.x;\n          let bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;\n          let newValue = top + (bottom - top) * fracCR.y;\n          setOutputAtIndex(index, newValue);\n        } else {\n          // Compute the coordinators of nearest neighbor point.\n          let sourceNearestCR = vec2<i32>(floor(\n            sourceFracIndexCR + vec2<f32>(0.5,0.5)));\n          let newValue = getImage(\n            bInd, sourceNearestCR.y, sourceNearestCR.x, d);\n          setOutputAtIndex(index, newValue);\n        }\n      }\n    }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/CropAndResize.js\nvar cropAndResize5 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { image: image2, boxes, boxInd } = inputs;\n  const { cropSize, method, extrapolationValue } = attrs;\n  const program = new CropAndResizeProgram2(image2.shape[3], boxes.shape, cropSize, method);\n  const uniformData = [{ type: \"float32\", data: [extrapolationValue] }];\n  return backend2.runWebGPUProgram(program, [image2, boxes, boxInd], \"float32\", uniformData);\n};\nvar cropAndResizeConfig4 = {\n  kernelName: CropAndResize,\n  backendName: \"webgpu\",\n  kernelFunc: cropAndResize5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/cum_webgpu.js\nvar CumOpType2;\n(function(CumOpType3) {\n  CumOpType3[\"Prod\"] = \"*\";\n  CumOpType3[\"Sum\"] = \"+\";\n})(CumOpType2 || (CumOpType2 = {}));\nvar CumProgram2 = class {\n  constructor(op2, shape, exclusive, reverse5) {\n    this.variableNames = [\"x\"];\n    this.uniforms = \"index : f32,\";\n    this.size = true;\n    const workGroupSizeX = 128;\n    this.workGroupSize = [workGroupSizeX, 1, 1];\n    this.outputShape = shape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.exclusive = exclusive;\n    this.reverse = reverse5;\n    this.op = op2;\n    this.shaderKey = `cum_${this.op}_${this.exclusive}_${this.reverse}`;\n  }\n  getUserCode() {\n    const rank = this.outputShape.length;\n    const initVal = this.op === CumOpType2.Prod ? \"1.0\" : \"0.0\";\n    const val = this.exclusive ? initVal : `getX(${getCoords4(rank, \"coords\", this.op)})`;\n    const length = this.outputShape[this.outputShape.length - 1];\n    let condition = \"\";\n    let idxString = \"\";\n    if (this.exclusive) {\n      condition = this.reverse ? `end != ${length - 1}` : \"end != 0\";\n      idxString = this.reverse ? \"end + 1\" : \"end - 1\";\n    } else {\n      condition = this.reverse ? `end + pow2 < ${length}` : \"end >= pow2\";\n      idxString = this.reverse ? \"end + pow2\" : \"end - pow2\";\n    }\n    return `\n      ${getMainHeaderAndGlobalIndexString()}\n       if (index < uniforms.size) {\n         var coords = getCoordsFromIndex(index);\n\n         let end = ${getFinalCoord2(rank, \"coords\", this.op)};\n         var val = ${val};\n         let pow2 = i32(pow(2.0, uniforms.index));\n         if (${condition}) {\n           let idx = ${idxString};\n           ${getFinalCoord2(rank, \"coords\", this.op)} = idx;\n           val ${this.op}= getX(${getCoords4(rank, \"coords\", this.op)});\n         }\n         setOutputAtIndex(index, val);\n       }\n      }\n    `;\n  }\n};\nfunction getCoords4(rank, name, op2) {\n  if (rank === 1) {\n    return `${name}`;\n  } else if (rank === 2) {\n    return `${name}.x, ${name}.y`;\n  } else if (rank === 3) {\n    return `${name}.x, ${name}.y, ${name}.z`;\n  } else if (rank === 4) {\n    return `${name}.x, ${name}.y, ${name}.z, ${name}.w`;\n  } else {\n    throw Error(`Cumulative ${op2} for rank ${rank} is not yet supported`);\n  }\n}\nfunction getFinalCoord2(rank, name, op2) {\n  if (rank === 1) {\n    return `${name}`;\n  } else if (rank === 2) {\n    return `${name}.y`;\n  } else if (rank === 3) {\n    return `${name}.z`;\n  } else if (rank === 4) {\n    return `${name}.w`;\n  } else {\n    throw Error(`Cumulative ${op2} for rank ${rank} is not yet supported`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Cum_impl.js\nfunction cumImpl2(op2, x, backend2, axis, exclusive, reverse5) {\n  const xRank = x.shape.length;\n  const permutation = backend_util_exports.getAxesPermutation([axis], xRank);\n  let permutedX = x;\n  if (permutation != null) {\n    permutedX = transpose5({ inputs: { x }, backend: backend2, attrs: { perm: permutation } });\n  }\n  const permutedAxis = backend_util_exports.getInnerMostAxes(1, xRank)[0];\n  if (permutedAxis !== xRank - 1) {\n    throw new Error(`WebGPU cumprod shader expects an inner-most axis=${x.shape.length - 1} but got axis=${axis}`);\n  }\n  const size = permutedX.shape[permutedAxis];\n  let result = identity5({ inputs: { x: permutedX }, backend: backend2 });\n  for (let i2 = 0; i2 <= Math.ceil(Math.log2(size)) - 1; i2++) {\n    const program = new CumProgram2(op2, permutedX.shape, false, reverse5);\n    const prevResult = result;\n    const uniformData = [{ type: \"float32\", data: [i2] }];\n    result = backend2.runWebGPUProgram(program, [result], result.dtype, uniformData);\n    backend2.disposeData(prevResult.dataId);\n  }\n  if (exclusive) {\n    const program = new CumProgram2(op2, permutedX.shape, exclusive, reverse5);\n    const prevResult = result;\n    const uniformData = [{ type: \"float32\", data: [0] }];\n    result = backend2.runWebGPUProgram(program, [result], result.dtype, uniformData);\n    backend2.disposeData(prevResult.dataId);\n  }\n  if (permutation != null) {\n    const reversePermutation = backend_util_exports.getUndoAxesPermutation(permutation);\n    const reverseTransposedResult = transpose5({ inputs: { x: result }, backend: backend2, attrs: { perm: reversePermutation } });\n    backend2.disposeData(result.dataId);\n    backend2.disposeData(permutedX.dataId);\n    return reverseTransposedResult;\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Cumprod.js\nfunction cumprod5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  return cumImpl2(CumOpType2.Prod, x, backend2, axis, exclusive, reverse5);\n}\nvar cumprodConfig4 = {\n  kernelName: Cumprod,\n  backendName: \"webgpu\",\n  kernelFunc: cumprod5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Cumsum.js\nfunction cumsum5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  return cumImpl2(CumOpType2.Sum, x, backend2, axis, exclusive, reverse5);\n}\nvar cumsumConfig4 = {\n  kernelName: Cumsum,\n  backendName: \"webgpu\",\n  kernelFunc: cumsum5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/depth_to_space_webgpu.js\nvar DepthToSpaceProgram2 = class {\n  constructor(outputShape, dataFormat) {\n    this.variableNames = [\"x\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.uniforms = \"blockSize : i32,\";\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = `depthToSpace_${dataFormat}`;\n    this.dataFormat = dataFormat;\n  }\n  getUserCode() {\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let coords = getCoordsFromIndex(index);\n          let b = coords[0];\n          let h = ${this.getHeightCoordString()};\n          let w = ${this.getWidthCoordString()};\n          let d = ${this.getDepthCoordString()};\n\n          let in_h = h / uniforms.blockSize;\n          let offset_h = h % uniforms.blockSize;\n          let in_w = w / uniforms.blockSize;\n          let offset_w = w % uniforms.blockSize;\n          let offset_d = (offset_h * uniforms.blockSize + offset_w) *\n            ${this.getOutputDepthSize()};\n          let in_d = d + offset_d;\n\n          let rlt = ${this.getInputSamplingString()};\n          setOutputAtIndex(index, rlt);\n        }\n      }`;\n    return userCode;\n  }\n  getHeightCoordString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `coords[1]`;\n    } else {\n      return `coords[2]`;\n    }\n  }\n  getWidthCoordString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `coords[2]`;\n    } else {\n      return `coords[3]`;\n    }\n  }\n  getDepthCoordString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `coords[3]`;\n    } else {\n      return `coords[1]`;\n    }\n  }\n  getOutputDepthSize() {\n    if (this.dataFormat === \"NHWC\") {\n      return `uniforms.outShape[3]`;\n    } else {\n      return `uniforms.outShape[1]`;\n    }\n  }\n  getInputSamplingString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `getX(b, in_h, in_w, in_d)`;\n    } else {\n      return `getX(b, in_d, in_h, in_w)`;\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/DepthToSpace.js\nfunction depthToSpace5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockSize, dataFormat } = attrs;\n  const batchSize = x.shape[0];\n  const inputHeight = dataFormat === \"NHWC\" ? x.shape[1] : x.shape[2];\n  const inputWidth = dataFormat === \"NHWC\" ? x.shape[2] : x.shape[3];\n  const inputDepth = dataFormat === \"NHWC\" ? x.shape[3] : x.shape[1];\n  const outputHeight = inputHeight * blockSize;\n  const outputWidth = inputWidth * blockSize;\n  const outputDepth = inputDepth / (blockSize * blockSize);\n  const outputShape = dataFormat === \"NHWC\" ? [batchSize, outputHeight, outputWidth, outputDepth] : [batchSize, outputDepth, outputHeight, outputWidth];\n  const uniformData = [\n    { type: \"int32\", data: [blockSize] }\n  ];\n  const program = new DepthToSpaceProgram2(outputShape, dataFormat);\n  return backend2.runWebGPUProgram(program, [x], x.dtype, uniformData);\n}\nvar depthToSpaceConfig4 = {\n  kernelName: DepthToSpace,\n  backendName: \"webgpu\",\n  kernelFunc: depthToSpace5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/depthwise_conv2d_nchw_shared_webgpu.js\nvar DepthwiseConv2DNCHWSharedProgram = class {\n  constructor(outputShape, filterHeight, filterWidth, addBias = false, activation2 = null, hasPreluActivation = false) {\n    this.variableNames = [\"x\", \"W\"];\n    this.uniforms = `pad : vec2<i32>, inDims : vec2<i32>,`;\n    this.workGroupSize = [16, 16, 1];\n    this.outputShape = outputShape;\n    this.dispatchLayout = { x: [3], y: [2], z: [0, 1] };\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivation) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivation = hasPreluActivation;\n    this.filterHeight = filterHeight;\n    this.filterWidth = filterWidth;\n    this.shaderKey = `depthwiseNCHW_${this.activation}_${this.filterHeight}_${this.filterWidth}`;\n  }\n  getUserCode() {\n    const filterSize = this.filterWidth * this.filterHeight;\n    const workGroupSize = this.workGroupSize[0] * this.workGroupSize[1] * this.workGroupSize[2];\n    const tileAHeight = this.workGroupSize[1] + this.filterHeight - 1;\n    const tileAWidth = this.workGroupSize[0] + this.filterWidth - 1;\n    const userCode = `\n      ${activationFnSnippet(this.activation, this.hasPreluActivation, false, 4)}\n\n      var<workgroup> mm_Asub : array<array<f32, ${tileAWidth}>, ${tileAHeight}>;\n      var<workgroup> mm_Bsub : array<array<f32, ${this.filterWidth}>, ${this.filterHeight}>;\n      fn readX(batch : i32, channel : i32, row : i32, col : i32) -> f32 {\n        var value = 0.0;\n        if (row >=0 && row < uniforms.inDims[0] && col >=0 && col < uniforms.inDims[1])\n        {\n          value = getX(batch, channel, row, col);\n        }\n        return value;\n      }\n\n      ${getWorkGroupSizeString()}\n      fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,\n              @builtin(global_invocation_id) GlobalId : vec3<u32>,\n              @builtin(local_invocation_index) LocalIndex: u32,\n              @builtin(num_workgroups) NumWorkgroups: vec3<u32>) {\n        localId = LocalId;\n        globalId = GlobalId;\n        let localIndex = i32(LocalIndex);\n        numWorkgroups = NumWorkgroups;\n        let coords = getOutputCoords();\n        let batch = coords[0];\n        let xRCCorner = vec2<i32>(coords.zw) - uniforms.pad;\n        let channelMul = uniforms.wShape[3];\n        let d1 = coords[1] / channelMul;\n        let q = coords[1] % channelMul;\n\n        let inputRowStart = xRCCorner.x;\n        let inputColStart = xRCCorner.y;\n\n        let localRow = i32(localId.y);\n        let localCol = i32(localId.x);\n\n        // Load one tile of X into local memory.\n        for (var inputRow = localRow; inputRow < ${tileAHeight}; inputRow = inputRow + ${this.workGroupSize[1]}) {\n          for (var inputCol = localCol; inputCol < ${tileAWidth}; inputCol = inputCol + ${this.workGroupSize[0]}) {\n            let rowOffset = inputRow - localRow;\n            let colOffset = inputCol - localCol;\n            mm_Asub[inputRow][inputCol] = readX(batch, d1, inputRowStart + rowOffset, inputColStart + colOffset);\n          }\n        }\n\n        // Load one tile of W into local memory.\n        var wIndex = localIndex;\n        ${filterSize < workGroupSize ? `if (wIndex < ${filterSize})` : `for(; wIndex < ${filterSize}; wIndex = wIndex + ${workGroupSize})`}\n\n        {\n          let wRow = wIndex / ${this.filterWidth};\n          let wCol = wIndex % ${this.filterWidth};\n          mm_Bsub[wRow][wCol] = getW(wRow, wCol, d1, q);\n        }\n\n        workgroupBarrier();\n\n        var value = 0.0;\n        for (var wR = 0; wR < ${this.filterHeight}; wR = wR + 1) {\n          for (var wC = 0; wC < ${this.filterWidth}; wC = wC + 1) {\n            let xVal = mm_Asub[localRow + wR][localCol + wC];\n            let wVal = mm_Bsub[wR][wC];\n            value = fma(xVal, wVal, value);\n          }\n        }\n        ${biasActivationSnippet(this.addBias, this.activation)}\n        if (coordsInBounds4D(coords, uniforms.outShape)) {\n          setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/depthwise_conv2d_vec4_webgpu.js\nvar DepthwiseConv2DVec4Program = class {\n  constructor(convInfo, addBias = false, activation2 = null, hasPreluActivation = false) {\n    this.variableNames = [\"x\", \"W\"];\n    this.uniforms = \"pad : vec2<i32>, inDims : vec2<i32>,\";\n    this.workGroupSize = [4, 4, 4];\n    this.isVec4 = true;\n    this.outputShape = convInfo.outShape;\n    this.dispatchLayout = { x: [3], y: [2], z: [0, 1] };\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [4, 4, 1]);\n    util_exports.assert(convInfo.dataFormat === \"channelsLast\", () => \"TODO: NCHW is unimplemented\");\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivation) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.convInfo = convInfo;\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivation = hasPreluActivation;\n    this.shaderKey = `depthwiseVec4_${activation2}_${this.convInfo.filterHeight}_${this.convInfo.filterWidth}`;\n  }\n  getUserCode() {\n    const xNumber = 4 + this.convInfo.filterWidth - 1;\n    const userCode = `\n      ${activationFnSnippet(this.activation, this.hasPreluActivation, true, 4)}\n      fn readX(batch : i32, row : i32, col : i32, channel : i32) -> vec4<f32> {\n        var value = vec4<f32>(0.0);\n        if (row >=0 && row < uniforms.inDims[0] && col >=0 && col < uniforms.inDims[1])\n        {\n          value = getX(batch, row, col, channel);\n        }\n        return value;\n      }\n      ${getWorkGroupSizeString()}\n      fn main(@builtin(global_invocation_id) globalId: vec3<u32>) {\n        let batch = i32(globalId.z) / uniforms.outShape[1];\n        let r = i32(globalId.z) % uniforms.outShape[1];\n        let c = i32(globalId.y) * 4;\n        let d1 = i32(globalId.x) * 4;\n        let xRCCorner = vec2<i32>(r, c) - uniforms.pad;\n\n        let xRCorner = xRCCorner.x;\n        let xCCorner = xRCCorner.y;\n        var xVals : array<vec4<f32>, ${xNumber}>;\n        var dotProd : array<vec4<f32>, 4>;\n        dotProd[0] = vec4<f32>(0.0);\n        dotProd[1] = vec4<f32>(0.0);\n        dotProd[2] = vec4<f32>(0.0);\n        dotProd[3] = vec4<f32>(0.0);\n\n        // Use constant instead of uniform can give better performance.\n        for (var wR = 0; wR < ${this.convInfo.filterHeight}; wR = wR + 1) {\n          let xR = xRCorner + wR;\n          for (var i = 0; i < ${xNumber}; i++)\n          {\n            xVals[i] = readX(batch, xR, xCCorner + i, d1);\n          }\n          for (var wC = 0; wC < ${this.convInfo.filterWidth}; wC = wC + 1) {\n            let wValue = getW(wR, wC, d1, 0);\n            dotProd[0] = dotProd[0] + xVals[0 + wC] * wValue;\n            dotProd[1] = dotProd[1] + xVals[1 + wC] * wValue;\n            dotProd[2] = dotProd[2] + xVals[2 + wC] * wValue;\n            dotProd[3] = dotProd[3] + xVals[3 + wC] * wValue;\n          }\n        }\n\n        for (var i = 0; i < 4; i = i + 1) {\n          let coords = vec4<i32>(batch, r, c + i, d1);\n          if (coordsInBounds4D(coords, uniforms.outShape)) {\n            var value = dotProd[i];\n            ${biasActivationSnippet(this.addBias, this.activation)}\n            setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);\n          }\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/depthwise_conv2d_webgpu.js\nvar DepthwiseConv2DProgram2 = class {\n  constructor(convInfo, addBias = false, activation2 = null, hasPreluActivation = false) {\n    this.variableNames = [\"x\", \"W\"];\n    this.uniforms = `pad : vec2<i32>, inDims : vec2<i32>, filterHeight : i32,\n      filterWidth : i32, stride : vec2<i32>, dilation : vec2<i32>,`;\n    this.workGroupSize = [256, 1, 1];\n    this.outputShape = convInfo.outShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivation) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.convInfo = convInfo;\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivation = hasPreluActivation;\n    this.shaderKey = `depthwise_${this.activation}_${this.isChannelsLast}`;\n  }\n  getUserCode() {\n    const getXSnippet = this.isChannelsLast ? \"getX(batch, xR, xC, d1);\" : \"getX(batch, d1, xR, xC);\";\n    const userCode = `\n      ${activationFnSnippet(this.activation, this.hasPreluActivation, false, 4)}\n\n      ${getMainHeaderString()}\n        let coords = getOutputCoords();\n        let batch = coords[0];\n        let xRCCorner = vec2<i32>(coords.${this.isChannelsLast ? \"yz\" : \"zw\"}) * uniforms.stride - uniforms.pad;\n        let d2 = coords[${this.isChannelsLast ? 3 : 1}];\n        let channelMul = uniforms.wShape[3];\n        let d1 = d2 / channelMul;\n        let q = d2 % channelMul;\n\n        let inputRowStart = xRCCorner.x;\n        let inputColStart = xRCCorner.y;\n        let inputRowEnd = inputRowStart + uniforms.filterHeight *\n            uniforms.dilation[0];\n        let inputColEnd = inputColStart + uniforms.filterWidth *\n            uniforms.dilation[1];\n\n        // Convolve x(?, ?, d1)|x(d1, ?, ?) with w(:, :, d1, q) to get\n        // y(yR, yC, d2)|y(d2, yR, yC). ? = to be determined. : = across all\n        // values in that axis. x(?, ?, d1) and y(yR, yC, d2) is for NHWC.\n        // x(d1, ?, ?) and y(d2, yR, yC) is for NCHW.\n        var value = 0.0;\n\n        // Extract if checking out of for loop for performance.\n        if (inputRowStart >= 0 && inputColStart >= 0 &&\n          inputRowEnd < uniforms.inDims[0] &&\n              inputColEnd < uniforms.inDims[1]) {\n            for (var wR = 0; wR < uniforms.filterHeight; wR = wR + 1) {\n              let xR = inputRowStart + wR * uniforms.dilation[0];\n\n              for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {\n                let xC = inputColStart + wC * uniforms.dilation[1];\n\n                let xVal = ${getXSnippet};\n                let wVal = getW(wR, wC, d1, q);\n                value = value + xVal * wVal;\n              }\n            }\n          } else {\n            for (var wR = 0; wR < uniforms.filterHeight; wR = wR + 1) {\n              let xR = inputRowStart + wR * uniforms.dilation[0];\n\n              if (xR < 0 || xR >= uniforms.inDims[0]) {\n                continue;\n              }\n\n              for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {\n                let xC = inputColStart + wC * uniforms.dilation[1];\n\n                if (xC < 0 || xC >= uniforms.inDims[1]) {\n                  continue;\n                }\n\n                let xVal = ${getXSnippet};\n                let wVal = getW(wR, wC, d1, q);\n                value = value + xVal * wVal;\n              }\n            }\n          }\n          ${biasActivationSnippet(this.addBias, this.activation)}\n        if (coordsInBounds4D(coords, uniforms.outShape)) {\n          setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/DepthwiseConv2dNative.js\nfunction depthwiseConv2dNative3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  let $dilations = dilations;\n  if ($dilations == null) {\n    $dilations = [1, 1];\n  }\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad3, dimRoundingMode, true, $dataFormat);\n  const dimensions = [\n    { type: \"int32\", data: [convInfo.padInfo.top, convInfo.padInfo.left] },\n    { type: \"int32\", data: [convInfo.inHeight, convInfo.inWidth] }\n  ];\n  const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n  let program;\n  if (!isChannelsLast && convInfo.inHeight > 16 && convInfo.inWidth > 16 && convInfo.strideHeight === 1 && convInfo.strideWidth === 1 && convInfo.dilationWidth === 1 && convInfo.dilationHeight === 1 && convInfo.inChannels === convInfo.outChannels) {\n    program = new DepthwiseConv2DNCHWSharedProgram(convInfo.outShape, convInfo.filterHeight, convInfo.filterWidth);\n  } else if (isChannelsLast && convInfo.inHeight > 4 && convInfo.inWidth > 4 && convInfo.strideHeight === 1 && convInfo.strideWidth === 1 && convInfo.inChannels === convInfo.outChannels && convInfo.dilationHeight === 1 && convInfo.dilationWidth === 1 && convInfo.inChannels % 4 === 0) {\n    program = new DepthwiseConv2DVec4Program(convInfo);\n  } else {\n    program = new DepthwiseConv2DProgram2(convInfo);\n    dimensions.push({ type: \"int32\", data: [convInfo.filterHeight] }, { type: \"int32\", data: [convInfo.filterWidth] }, { type: \"int32\", data: [convInfo.strideHeight, convInfo.strideWidth] }, {\n      type: \"int32\",\n      data: [convInfo.dilationHeight, convInfo.dilationWidth]\n    });\n  }\n  return backend2.runWebGPUProgram(program, [x, filter], x.dtype, dimensions);\n}\nvar depthwiseConv2dNativeConfig4 = {\n  kernelName: DepthwiseConv2dNative,\n  backendName: \"webgpu\",\n  kernelFunc: depthwiseConv2dNative3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Multiply.js\nvar multiplyKernelFunc = binaryKernelFunc3({\n  opType: BinaryOpType.MUL,\n  cpuKernelImpl: multiplyImplCPU2,\n  supportsComplex: true\n});\nvar multiplyConfig4 = {\n  kernelName: Multiply,\n  backendName: \"webgpu\",\n  kernelFunc: multiplyKernelFunc\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/reduce_webgpu.js\nvar ReduceProgram2 = class {\n  constructor(reduceInfo, reduceType) {\n    this.workGroupSize = [64, 1, 1];\n    this.variableNames = [\"x\"];\n    this.uniforms = \"reduceSize : i32,\";\n    this.size = true;\n    this.inputShape = [reduceInfo.batchSize, reduceInfo.inSize];\n    const [outputShape] = backend_util_exports.computeOutAndReduceShapes(this.inputShape, [1]);\n    this.outputShape = outputShape.length === 0 ? [1] : outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, [1, 1, 1]);\n    this.reduceType = reduceType;\n    this.shaderKey = `reduce_${reduceType}`;\n  }\n  getUserCode() {\n    let reduceOp = ``;\n    let initValue = \"0.0\";\n    if (this.reduceType === \"min\" || this.reduceType === \"max\") {\n      reduceOp = `\n         if (isnan(candidate)) {\n          bestValue = uniforms.NAN;\n         } else if (!isnan(bestValue) && candidate ${this.reduceType === \"min\" ? \"<\" : \">\"} bestValue)\n           {  bestValue = candidate; }`;\n      initValue = \"f32(x[offset])\";\n    } else if (this.reduceType === \"sum\" || this.reduceType === \"mean\") {\n      reduceOp = \" bestValue = bestValue + candidate; \";\n    } else if (this.reduceType === \"prod\") {\n      reduceOp = \" bestValue = bestValue * candidate; \";\n      initValue = \"1.0\";\n    }\n    const outputSnippet = this.reduceType === \"mean\" ? `setOutputAtIndex(outputIndex, bestValue / f32(uniforms.reduceSize));` : `setOutputAtIndex(outputIndex, bestValue);`;\n    const sharedMemorySnippet = `\n         var<workgroup> xBestValues : array<f32, ${this.workGroupSize[0]}>;\n       `;\n    const userCode = `\n       fn DIV_CEIL(a : u32, b : u32) -> u32 {\n        return ((a - 1u) / b + 1u);\n       }\n\n       ${sharedMemorySnippet}\n       fn getOffset(outputIndex : i32) -> i32 {\n         let outputCoords = getCoordsFromIndex(outputIndex);\n         let offset = ${this.outputShape.length === 1 ? \"outputCoords\" : \"outputCoords[0]\"} * uniforms.reduceSize;\n          return offset;\n       }\n       ${getMainHeaderAndGlobalIndexString()}\n         let outputIndex = index / i32(workGroupSizeX);\n         let offset = getOffset(outputIndex);\n         var bestValue = ${initValue};\n         let Length = uniforms.reduceSize;\n         let WorkPerThread = DIV_CEIL(u32(Length), workGroupSizeX);\n         for (var k = i32(localId.x); k < Length && outputIndex < uniforms.size;\n             k = k + i32(workGroupSizeX)) {\n           let candidate = f32(x[offset + k]);\n           ${reduceOp}\n         }\n         xBestValues[localId.x] = bestValue;\n         workgroupBarrier();\n\n         var reduceSize = min(u32(Length), workGroupSizeX);\n         for (var currentSize = reduceSize / 2u; reduceSize > 1u;\n             currentSize = reduceSize / 2u) {\n           let interval = DIV_CEIL(reduceSize, 2u);\n           if (localId.x < currentSize) {\n            let candidate = xBestValues[localId.x + interval];\n            ${reduceOp}\n            xBestValues[localId.x] = bestValue;\n           }\n           reduceSize = interval;\n           workgroupBarrier();\n         }\n\n         if (localId.x == 0u && outputIndex < uniforms.size) {\n          ${outputSnippet}\n        }\n       }\n     `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernel_utils/reduce.js\nfunction reduce2(x, axis, keepDims, reduceType, backend2) {\n  const xRank = x.shape.length;\n  const toDispose = [];\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  let input2 = x;\n  if (permutedAxes != null) {\n    input2 = transpose5({ inputs: { x }, attrs: { perm: permutedAxes }, backend: backend2 });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n    toDispose.push(input2);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(reduceType, axes, xRank);\n  const [reduceOutShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, axes);\n  let resOutShape = reduceOutShape;\n  if (keepDims) {\n    resOutShape = backend_util_exports.expandShapeToKeepDim(reduceOutShape, origAxes);\n  }\n  let res;\n  if ((reduceType === \"max\" || reduceType === \"prod\") && backend2.shouldExecuteOnCPU([input2])) {\n    const xVals = backend2.tensorMap.get(input2.dataId).values;\n    switch (reduceType) {\n      case \"max\":\n        const outValues = maxImplCPU2(xVals, util_exports.sizeFromShape(reduceShape), resOutShape, x.dtype);\n        res = backend2.makeTensorInfo(resOutShape, x.dtype, outValues);\n        break;\n      case \"prod\":\n        const { outVals, outShape, outDtype } = prodImplCPU2(input2.shape, input2.dtype, xVals, axes);\n        res = backend2.makeTensorInfo(outShape, outDtype, outVals);\n        break;\n      default:\n        throw new Error(`${reduceType} CPU implementation is not yet supported.`);\n    }\n  } else {\n    const inSize = util_exports.sizeFromShape(reduceShape);\n    const xSize = util_exports.sizeFromShape(input2.shape);\n    const batchSize = xSize / inSize;\n    const reduceInfo = { windowSize: inSize, inSize, batchSize, outSize: 1 };\n    const dtype = reduceType === \"mean\" ? \"float32\" : sumOutType(x.dtype);\n    const uniformData = [\n      { type: \"int32\", data: [inSize] }\n    ];\n    const program = new ReduceProgram2(reduceInfo, reduceType);\n    const reduced = backend2.runWebGPUProgram(program, [input2], dtype, uniformData);\n    toDispose.push(reduced);\n    res = reshape6({ inputs: { x: reduced }, attrs: { shape: resOutShape }, backend: backend2 });\n  }\n  toDispose.forEach((t2) => backend2.disposeData(t2.dataId));\n  return res;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Sum.js\nfunction sum6(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  return reduce2(x, axis, keepDims, \"sum\", backend2);\n}\nvar sumConfig4 = {\n  kernelName: Sum,\n  backendName: \"webgpu\",\n  kernelFunc: sum6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Einsum.js\nfunction einsum4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { equation } = attrs;\n  const tensors = inputs;\n  const { allDims, summedDims, idDims } = backend_util_exports.decodeEinsumEquation(equation, tensors.length);\n  backend_util_exports.checkEinsumDimSizes(allDims.length, idDims, tensors);\n  const { path, steps } = backend_util_exports.getEinsumComputePath(summedDims, idDims);\n  const nSteps = steps.length;\n  let out = null;\n  let numDimsRemaining = allDims.length;\n  const tensorsToDispose = [];\n  for (let i2 = 0; i2 < nSteps; ++i2) {\n    for (const idTerm of steps[i2]) {\n      const { permutationIndices: perm, expandDims: dimsToExpand } = backend_util_exports.getEinsumPermutation(numDimsRemaining, idDims[idTerm]);\n      let x;\n      if (backend_util_exports.isIdentityPermutation(perm)) {\n        x = tensors[idTerm];\n      } else {\n        x = transpose5({ inputs: { x: tensors[idTerm] }, backend: backend2, attrs: { perm } });\n        tensorsToDispose.push(x);\n      }\n      const targetShape = x.shape.slice();\n      for (let k = 0; k < dimsToExpand.length; ++k) {\n        targetShape.splice(dimsToExpand[k], 0, 1);\n      }\n      if (!util_exports.arraysEqual(x.shape, targetShape)) {\n        x = reshape6({ inputs: { x }, backend: backend2, attrs: { shape: targetShape } });\n        tensorsToDispose.push(x);\n      }\n      if (out === null) {\n        out = x;\n      } else {\n        out = multiplyKernelFunc({ inputs: { a: x, b: out }, backend: backend2 });\n        tensorsToDispose.push(out);\n      }\n    }\n    if (i2 < nSteps - 1) {\n      if (path[i2] >= 0) {\n        out = sum6({\n          inputs: { x: out },\n          backend: backend2,\n          attrs: {\n            axis: path[i2] - (allDims.length - numDimsRemaining),\n            keepDims: false\n          }\n        });\n        tensorsToDispose.push(out);\n      }\n      numDimsRemaining--;\n    }\n  }\n  for (const tensorInfo of tensorsToDispose) {\n    if (tensorInfo === out) {\n      continue;\n    }\n    backend2.disposeData(tensorInfo.dataId);\n  }\n  return out;\n}\nvar einsumConfig3 = {\n  kernelName: Einsum,\n  backendName: \"webgpu\",\n  kernelFunc: einsum4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Elu.js\nvar elu6 = unaryKernelFunc3({ opType: UnaryOpType.ELU });\nvar eluConfig4 = {\n  kernelName: Elu,\n  backendName: \"webgpu\",\n  kernelFunc: elu6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Equal.js\nvar equal4 = binaryKernelFunc3({ opType: BinaryOpType.EQUAL, dtype: \"bool\", cpuKernelImpl: equalImplCPU2 });\nvar equalConfig4 = {\n  kernelName: Equal,\n  backendName: \"webgpu\",\n  kernelFunc: equal4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Exp.js\nvar exp4 = unaryKernelFunc3({\n  opType: UnaryOpType.EXP,\n  cpuKernelImpl: expImplCPU2,\n  dtype: \"float32\"\n});\nvar expConfig4 = {\n  kernelName: Exp,\n  backendName: \"webgpu\",\n  kernelFunc: exp4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ExpandDims.js\nfunction expandDims6(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { dim } = attrs;\n  const { input: input2 } = inputs;\n  const inputRank = input2.shape.length;\n  const newShape = input2.shape.slice();\n  let $dim = dim;\n  if (dim < 0) {\n    util_exports.assert(-(inputRank + 1) <= dim, () => `Axis must be in the interval [${-(inputRank + 1)}, ${inputRank}]`);\n    $dim = inputRank + dim + 1;\n  }\n  newShape.splice($dim, 0, 1);\n  return reshape6({ inputs: { x: input2 }, backend: backend2, attrs: { shape: newShape } });\n}\nvar expandDimsConfig4 = {\n  kernelName: ExpandDims,\n  backendName: \"webgpu\",\n  kernelFunc: expandDims6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Expm1.js\nvar expm14 = unaryKernelFunc3({ opType: UnaryOpType.EXPM1, cpuKernelImpl: expm1ImplCPU2 });\nvar expm1Config3 = {\n  kernelName: Expm1,\n  backendName: \"webgpu\",\n  kernelFunc: expm14\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/flip_left_right_webgpu.js\nvar FlipLeftRightProgram2 = class {\n  constructor(imageShape) {\n    this.outputShape = [];\n    this.variableNames = [\"x\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = imageShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = \"flipLeftRight\";\n  }\n  getUserCode() {\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let coords = getCoordsFromIndex(index);\n          let coordX = uniforms.xShape[2] - coords[2] - 1;\n          let outputValue = getX(coords[0], coords[1], coordX, coords[3]);\n          setOutputAtIndex(index, outputValue);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/FlipLeftRight.js\nvar flipLeftRightConfig4 = {\n  kernelName: FlipLeftRight,\n  backendName: \"webgpu\",\n  kernelFunc: ({ inputs, backend: backend2 }) => {\n    const { image: image2 } = inputs;\n    const webgpuBackend = backend2;\n    const program = new FlipLeftRightProgram2(image2.shape);\n    const output = webgpuBackend.runWebGPUProgram(program, [image2], image2.dtype);\n    return output;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Floor.js\nvar floor4 = unaryKernelFunc3({ opType: UnaryOpType.FLOOR, cpuKernelImpl: floorImplCPU2 });\nvar floorConfig4 = {\n  kernelName: Floor,\n  backendName: \"webgpu\",\n  kernelFunc: floor4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/FloorDiv.js\nvar floorDiv4 = binaryKernelFunc3({ opType: BinaryOpType.INT_DIV, dtype: \"int32\" });\nvar floorDivConfig4 = {\n  kernelName: FloorDiv,\n  backendName: \"webgpu\",\n  kernelFunc: floorDiv4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/from_pixels_webgpu.js\nvar FromPixelsProgram2 = class {\n  constructor(outputShape, numChannels, importVideo = false) {\n    this.isFromPixels = true;\n    this.outputShape = [0];\n    this.variableNames = [];\n    this.workGroupSize = [256, 1, 1];\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [numChannels, 1, 1]);\n    this.importVideo = importVideo;\n    this.shaderKey = `fromPixels_${this.importVideo}`;\n  }\n  getUserCode() {\n    const textureLoad = this.importVideo ? \"textureLoad(src, vec2<i32>(coords.yx));\" : \"textureLoad(src, vec2<i32>(coords.yx), 0)\";\n    const textureType = this.importVideo ? \"texture_external\" : \"texture_2d<f32>\";\n    return `\n      @binding(1) @group(0) var src: ${textureType};\n      ${getMainHeaderAndGlobalIndexString()}\n        let flatIndex = index * uniforms.numChannels;\n        if (flatIndex < uniforms.size) {\n          let coords = getCoordsFromIndex(flatIndex);\n          let values = ${textureLoad};\n          for (var i = 0; i < uniforms.numChannels; i = i + 1) {\n            result[flatIndex + i] = i32(floor(255.0 * values[i]));\n          }\n        }\n      }\n  `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/FromPixels.js\nvar fromPixelsConfig2 = {\n  kernelName: FromPixels,\n  backendName: \"webgpu\",\n  kernelFunc: fromPixels3\n};\nvar fromPixels2DContext3;\nvar videoToTextureMap = /* @__PURE__ */ new Map();\nfunction fromPixels3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  let { pixels } = inputs;\n  const { numChannels } = attrs;\n  if (pixels == null) {\n    throw new Error(\"pixels passed to tf.browser.fromPixels() can not be null\");\n  }\n  const isVideo = typeof HTMLVideoElement !== \"undefined\" && pixels instanceof HTMLVideoElement;\n  const isImage = typeof HTMLImageElement !== \"undefined\" && pixels instanceof HTMLImageElement;\n  const isCanvas = typeof HTMLCanvasElement !== \"undefined\" && pixels instanceof HTMLCanvasElement || typeof OffscreenCanvas !== \"undefined\" && pixels instanceof OffscreenCanvas;\n  const isImageBitmap = typeof ImageBitmap !== \"undefined\" && pixels instanceof ImageBitmap;\n  const [width, height] = isVideo ? [\n    pixels.videoWidth,\n    pixels.videoHeight\n  ] : [pixels.width, pixels.height];\n  const outputShape = [height, width, numChannels];\n  const importVideo = env().getBool(\"WEBGPU_IMPORT_EXTERNAL_TEXTURE\") && isVideo;\n  const isVideoOrImage = isVideo || isImage;\n  if (isImageBitmap || isCanvas || isVideoOrImage) {\n    let textureInfo;\n    if (importVideo) {\n      const videoElement = pixels;\n      if (!videoToTextureMap.has(videoElement) || videoToTextureMap.get(videoElement).expired) {\n        const externalTextureDescriptor = { source: videoElement };\n        videoToTextureMap.set(videoElement, backend2.device.importExternalTexture(externalTextureDescriptor));\n      }\n      textureInfo = {\n        width,\n        height,\n        format: null,\n        usage: null,\n        texture: videoToTextureMap.get(videoElement)\n      };\n    } else {\n      if (isVideoOrImage) {\n        if (fromPixels2DContext3 == null) {\n          fromPixels2DContext3 = document.createElement(\"canvas\").getContext(\"2d\");\n        }\n        fromPixels2DContext3.canvas.width = width;\n        fromPixels2DContext3.canvas.height = height;\n        fromPixels2DContext3.drawImage(pixels, 0, 0, width, height);\n        pixels = fromPixels2DContext3.canvas;\n      }\n      const usage = GPUTextureUsage.COPY_DST | GPUTextureUsage.RENDER_ATTACHMENT | GPUTextureUsage.TEXTURE_BINDING;\n      const format = \"rgba8unorm\";\n      const texture = backend2.textureManager.acquireTexture(outputShape[1], outputShape[0], format, usage);\n      backend2.queue.copyExternalImageToTexture({ source: pixels }, { texture }, [outputShape[1], outputShape[0]]);\n      textureInfo = { width, height, format, usage, texture };\n    }\n    const size = util_exports.sizeFromShape(outputShape);\n    const strides = util_exports.computeStrides(outputShape);\n    const program = new FromPixelsProgram2(outputShape, numChannels, importVideo);\n    const uniformData = [\n      { type: \"uint32\", data: [size] },\n      { type: \"uint32\", data: [numChannels] },\n      { type: \"uint32\", data: [...strides] }\n    ];\n    const input2 = backend2.makeTensorInfo([height, width], \"int32\");\n    const info = backend2.tensorMap.get(input2.dataId);\n    info.resourceInfo = textureInfo;\n    const result = backend2.runWebGPUProgram(program, [input2], \"int32\", uniformData);\n    backend2.disposeData(input2.dataId);\n    return result;\n  }\n  const imageData = pixels.data;\n  let pixelArray = imageData;\n  if (numChannels != null && numChannels !== 4) {\n    pixelArray = new Uint8Array(pixels.width * pixels.height * numChannels);\n    const dataLength = imageData.length;\n    let j = 0;\n    for (let i2 = 0; i2 < dataLength; i2++) {\n      if (i2 % 4 < numChannels) {\n        pixelArray[j++] = imageData[i2];\n      }\n    }\n  }\n  const output = backend2.makeTensorInfo(outputShape, \"int32\", new Int32Array(pixelArray));\n  backend2.uploadToGPU(output.dataId);\n  return output;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/batchnorm_webgpu.js\nvar BatchNormProgram2 = class {\n  constructor(xShape, meanShape, varianceShape, offsetShape, scaleShape) {\n    this.uniforms = \"varianceEpsilon : f32,\";\n    this.workGroupSize = [128, 1, 1];\n    this.size = true;\n    this.variableNames = [\"x\", \"mean\", \"variance\"];\n    backend_util_exports.assertAndGetBroadcastShape(xShape, meanShape);\n    backend_util_exports.assertAndGetBroadcastShape(xShape, varianceShape);\n    this.outputShape = xShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    if (offsetShape != null) {\n      backend_util_exports.assertAndGetBroadcastShape(xShape, offsetShape);\n      this.variableNames.push(\"offset\");\n    }\n    if (scaleShape != null) {\n      backend_util_exports.assertAndGetBroadcastShape(xShape, scaleShape);\n      this.variableNames.push(\"scale\");\n    }\n    this.offsetShape = offsetShape;\n    this.scaleShape = scaleShape;\n    this.shaderKey = \"batchNorm\";\n  }\n  getUserCode() {\n    let offsetSnippet = \"0.0\";\n    if (this.offsetShape != null) {\n      offsetSnippet = \"getOffsetByOutputIndex(index)\";\n    }\n    let scaleSnippet = \"1.0\";\n    if (this.scaleShape != null) {\n      scaleSnippet = \"getScaleByOutputIndex(index)\";\n    }\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size)\n        {\n          let xValue = getXByOutputIndex(index);\n          let meanValue = getMeanByOutputIndex(index);\n          let varianValue = getVarianceByOutputIndex(index);\n          let offsetValue = ${offsetSnippet};\n          let scaleValue = ${scaleSnippet};\n          let inv = scaleValue * inverseSqrt(varianValue + f32(uniforms.varianceEpsilon));\n          setOutputAtIndex(index,dot(vec3<f32>(xValue, -meanValue, offsetValue), vec3<f32>(inv, inv, 1.0)));\n        }\n      }\n  `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/FusedBatchNorm.js\nvar fusedBatchNormConfig2 = {\n  kernelName: FusedBatchNorm,\n  backendName: \"webgpu\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { x, scale: scale2, offset, mean: mean5, variance } = inputs;\n    const { varianceEpsilon } = attrs;\n    const webGPUBackend = backend2;\n    const batchNormInputs = [x, mean5, variance];\n    let offsetShape = null;\n    if (offset != null) {\n      offsetShape = offset.shape;\n      batchNormInputs.push(offset);\n    }\n    let scaleShape = null;\n    if (scale2 != null) {\n      scaleShape = scale2.shape;\n      batchNormInputs.push(scale2);\n    }\n    const program = new BatchNormProgram2(x.shape, mean5.shape, variance.shape, offsetShape, scaleShape);\n    const uniformData = [{ type: \"float32\", data: [varianceEpsilon] }];\n    return webGPUBackend.runWebGPUProgram(program, batchNormInputs, x.dtype, uniformData);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/FusedConv2D.js\nfunction fusedConv2d3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode, false, $dataFormat);\n  return conv2DImpl({\n    x,\n    filter,\n    convInfo,\n    backend: backend2,\n    bias,\n    preluActivationWeights,\n    leakyreluAlpha,\n    activation: activation2\n  });\n}\nvar fusedConv2DConfig4 = {\n  kernelName: FusedConv2D,\n  backendName: \"webgpu\",\n  kernelFunc: fusedConv2d3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/FusedDepthwiseConv2D.js\nfunction fusedDepthwiseConv2D3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dilations, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  let $dilations = dilations;\n  if ($dilations == null) {\n    $dilations = [1, 1];\n  }\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, $dilations), () => `Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${strides} and dilations '${$dilations}'`);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad3, dimRoundingMode, true);\n  const programInputs = [x, filter];\n  const hasBias = bias != null;\n  const hasPreluActivationWeights = preluActivationWeights != null;\n  if (hasBias) {\n    programInputs.push(bias);\n  }\n  if (hasPreluActivationWeights) {\n    programInputs.push(preluActivationWeights);\n  }\n  const dimensions = [\n    { type: \"int32\", data: [convInfo.padInfo.top, convInfo.padInfo.left] },\n    { type: \"int32\", data: [convInfo.inHeight, convInfo.inWidth] }\n  ];\n  let program;\n  if (convInfo.inHeight > 4 && convInfo.inWidth > 4 && convInfo.strideHeight === 1 && convInfo.strideWidth === 1 && convInfo.inChannels === convInfo.outChannels && convInfo.dilationHeight === 1 && convInfo.dilationWidth === 1 && convInfo.inChannels % 4 === 0) {\n    program = new DepthwiseConv2DVec4Program(convInfo, hasBias, activation2, hasPreluActivationWeights);\n  } else {\n    program = new DepthwiseConv2DProgram2(convInfo, hasBias, activation2, hasPreluActivationWeights);\n    dimensions.push({ type: \"int32\", data: [convInfo.filterHeight] }, { type: \"int32\", data: [convInfo.filterWidth] }, { type: \"int32\", data: [convInfo.strideHeight, convInfo.strideWidth] }, {\n      type: \"int32\",\n      data: [convInfo.dilationHeight, convInfo.dilationWidth]\n    });\n  }\n  if (activation2 === \"leakyrelu\") {\n    dimensions.push({ type: \"float32\", data: [leakyreluAlpha] });\n    program.uniforms += \" alpha : f32,\";\n  }\n  const result = backend2.runWebGPUProgram(program, programInputs, \"float32\", dimensions);\n  return result;\n}\nvar fusedDepthwiseConv2DConfig4 = {\n  kernelName: FusedDepthwiseConv2D,\n  backendName: \"webgpu\",\n  kernelFunc: fusedDepthwiseConv2D3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/gather_nd_webgpu.js\nvar GatherNDProgram2 = class {\n  constructor(sliceDim, shape) {\n    this.variableNames = [\"A\", \"indices\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = shape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = `gathernd_${sliceDim}`;\n    this.sliceDim = sliceDim;\n    this.uniforms = `sliceDim : i32, strides : ${getCoordsDataType2(sliceDim)},`;\n  }\n  getUserCode() {\n    let strideString;\n    if (this.sliceDim > 1) {\n      strideString = \"uniforms.strides[j]\";\n    } else {\n      strideString = \"uniforms.strides\";\n    }\n    const userCode = `\n        ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let coords = getCoordsFromIndex(index);\n          var flattenIndex = 0;\n          for (var j = 0; j < uniforms.sliceDim; j = j + 1) {\n            let indexTemp = i32(round(getIndices(coords[0], j)));\n            let strideNum = ${strideString};\n            flattenIndex = flattenIndex + indexTemp * strideNum;\n          }\n\n          setOutputAtIndex(index, getA(flattenIndex, coords[1]));\n        }\n      }\n      `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/GatherNd.js\nfunction gatherNd4(args) {\n  const { inputs, backend: backend2 } = args;\n  const { params, indices } = inputs;\n  const indicesShape = indices.shape;\n  const sliceRank = indicesShape[indicesShape.length - 1];\n  const paramsSize = util_exports.sizeFromShape(params.shape);\n  const [resultShape, numSlices, sliceSize, strides] = backend_util_exports.prepareAndValidate(params, indices);\n  const flattenIndices = reshape6({ inputs: { x: indices }, backend: backend2, attrs: { shape: [numSlices, sliceRank] } });\n  const flattenX = reshape6({\n    inputs: { x: params },\n    backend: backend2,\n    attrs: { shape: [util_exports.sizeFromShape(params.shape) / sliceSize, sliceSize] }\n  });\n  if (backend2.shouldExecuteOnCPU([params, indices]) || params.dtype === \"string\") {\n    const indicesData = backend2.readSync(indices.dataId);\n    const paramsBuf = backend2.bufferSync(params);\n    const outValue = gatherNdImplCPU2(indicesData, paramsBuf, params.dtype, numSlices, sliceRank, sliceSize, strides, params.shape, paramsSize);\n    return backend2.makeTensorInfo(resultShape, params.dtype, outValue.values);\n  }\n  const program = new GatherNDProgram2(sliceRank, [numSlices, sliceSize]);\n  const uniformData = [{ type: \"int32\", data: [sliceRank] }, { type: \"int32\", data: strides }];\n  const res = backend2.runWebGPUProgram(program, [flattenX, flattenIndices], flattenX.dtype, uniformData);\n  const reshaped = reshape6({ inputs: { x: res }, backend: backend2, attrs: { shape: resultShape } });\n  backend2.disposeData(flattenIndices.dataId);\n  backend2.disposeData(flattenX.dataId);\n  backend2.disposeData(res.dataId);\n  return reshaped;\n}\nvar gatherNdConfig4 = {\n  kernelName: GatherNd,\n  backendName: \"webgpu\",\n  kernelFunc: gatherNd4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/gather_webgpu.js\nvar GatherProgram2 = class {\n  constructor(aShape, outputShape) {\n    this.variableNames = [\"A\", \"indices\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = aShape.slice();\n    this.aShape = aShape;\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = `gather`;\n  }\n  getUserCode() {\n    const sourceCoords = getSourceCoords4(this.aShape);\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let resRC = getCoordsFromIndex(index);\n          let indexZ = i32(getIndices(resRC.x, resRC.z));\n          let inBounds = select(0.0, 1.0, indexZ >= 0 && indexZ < uniforms.aShape[2]);\n          setOutputAtIndex(index, inBounds * getA(${sourceCoords}));\n        }\n      }\n    `;\n    return userCode;\n  }\n};\nfunction getSourceCoords4(aShape) {\n  const currentCoords = [\"resRC.x\", \"resRC.y\", \"resRC.z\", \"resRC.w\"];\n  const sourceCoords = [];\n  for (let i2 = 0; i2 < aShape.length; i2++) {\n    if (i2 === 2) {\n      sourceCoords.push(\"indexZ\");\n    } else {\n      sourceCoords.push(`${currentCoords[i2]}`);\n    }\n  }\n  return sourceCoords.join();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/GatherV2.js\nfunction gatherV24(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, indices } = inputs;\n  const { axis, batchDims } = attrs;\n  const parsedAxis = util_exports.parseAxisParam(axis, x.shape)[0];\n  const shapeInfo = backend_util_exports.segment_util.collectGatherOpShapeInfo(x, indices, parsedAxis, batchDims);\n  const indicesSize = util_exports.sizeFromShape(indices.shape);\n  const toDispose = [];\n  const flattenX = reshape6({\n    inputs: { x },\n    backend: backend2,\n    attrs: {\n      shape: [\n        shapeInfo.batchSize,\n        shapeInfo.outerSize,\n        shapeInfo.dimSize,\n        shapeInfo.sliceSize\n      ]\n    }\n  });\n  const flattenIndex = reshape6({\n    inputs: { x: indices },\n    backend: backend2,\n    attrs: { shape: [shapeInfo.batchSize, indicesSize / shapeInfo.batchSize] }\n  });\n  toDispose.push(flattenX);\n  toDispose.push(flattenIndex);\n  const flattenOutputShape = [\n    shapeInfo.batchSize,\n    shapeInfo.outerSize,\n    indicesSize / shapeInfo.batchSize,\n    shapeInfo.sliceSize\n  ];\n  if (backend2.shouldExecuteOnCPU([x, indices])) {\n    const indicesBufferInfo = backend2.tensorMap.get(flattenIndex.dataId);\n    const indicesValues = indicesBufferInfo.values;\n    const indicesBuf = buffer(flattenIndex.shape, flattenIndex.dtype, indicesValues);\n    const xBufferInfo = backend2.tensorMap.get(flattenX.dataId);\n    const xValues = xBufferInfo.values;\n    const xBuf = buffer(flattenX.shape, flattenX.dtype, xValues);\n    const outBuf = gatherV2ImplCPU2(xBuf, indicesBuf, flattenOutputShape);\n    toDispose.forEach((t2) => backend2.disposeData(t2.dataId));\n    return backend2.makeTensorInfo(shapeInfo.outputShape, outBuf.dtype, outBuf.values);\n  }\n  const program = new GatherProgram2(flattenX.shape, flattenOutputShape);\n  const res = backend2.runWebGPUProgram(program, [flattenX, flattenIndex], flattenX.dtype);\n  toDispose.push(res);\n  const reshaped = reshape6({ inputs: { x: res }, backend: backend2, attrs: { shape: shapeInfo.outputShape } });\n  toDispose.forEach((t2) => backend2.disposeData(t2.dataId));\n  return reshaped;\n}\nvar gatherV2Config4 = {\n  kernelName: GatherV2,\n  backendName: \"webgpu\",\n  kernelFunc: gatherV24\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Greater.js\nvar greater5 = binaryKernelFunc3({\n  opType: BinaryOpType.GREATER,\n  cpuKernelImpl: greaterImplCPU2,\n  dtype: \"bool\"\n});\nvar greaterConfig4 = {\n  kernelName: Greater,\n  backendName: \"webgpu\",\n  kernelFunc: greater5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/GreaterEqual.js\nvar greaterEqual4 = binaryKernelFunc3({\n  opType: BinaryOpType.GREATER_EQUAL,\n  dtype: \"bool\",\n  cpuKernelImpl: greaterEqualImplCPU2\n});\nvar greaterEqualConfig4 = {\n  kernelName: GreaterEqual,\n  backendName: \"webgpu\",\n  kernelFunc: greaterEqual4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/LeakyRelu.js\nfunction leakyRelu5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { alpha } = attrs;\n  const uniformData = [{ type: \"float32\", data: [alpha] }];\n  const program = new UnaryOpProgram2(x.shape, UnaryOpType.LEAKYRELU);\n  program.uniforms = \"alpha : f32,\";\n  return backend2.runWebGPUProgram(program, [x], \"float32\", uniformData);\n}\nvar leakyReluConfig4 = {\n  kernelName: LeakyRelu,\n  backendName: \"webgpu\",\n  kernelFunc: leakyRelu5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Less.js\nvar less5 = binaryKernelFunc3({ opType: BinaryOpType.LESS, dtype: \"bool\", cpuKernelImpl: lessImplCPU2 });\nvar lessConfig4 = {\n  kernelName: Less,\n  backendName: \"webgpu\",\n  kernelFunc: less5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/LessEqual.js\nvar lessEqual4 = binaryKernelFunc3({\n  opType: BinaryOpType.LESS_EQUAL,\n  dtype: \"bool\",\n  cpuKernelImpl: lessEqualImplCPU2\n});\nvar lessEqualConfig4 = {\n  kernelName: LessEqual,\n  backendName: \"webgpu\",\n  kernelFunc: lessEqual4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Log.js\nvar log5 = unaryKernelFunc3({ opType: UnaryOpType.LOG, cpuKernelImpl: logImplCPU2 });\nvar logConfig4 = {\n  kernelName: Log,\n  backendName: \"webgpu\",\n  kernelFunc: log5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/LogicalAnd.js\nvar logicalAnd4 = binaryKernelFunc3({ opType: BinaryOpType.LOGICAL_AND, dtype: \"bool\" });\nvar logicalAndConfig4 = {\n  kernelName: LogicalAnd,\n  backendName: \"webgpu\",\n  kernelFunc: logicalAnd4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/LogicalNot.js\nvar logicalNot4 = unaryKernelFunc3({ opType: UnaryOpType.LOGICAL_NOT });\nvar logicalNotConfig4 = {\n  kernelName: LogicalNot,\n  backendName: \"webgpu\",\n  kernelFunc: logicalNot4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Max.js\nfunction max6(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { reductionIndices, keepDims } = attrs;\n  return reduce2(x, reductionIndices, keepDims, \"max\", backend2);\n}\nvar maxConfig4 = {\n  kernelName: Max,\n  backendName: \"webgpu\",\n  kernelFunc: max6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Maximum.js\nvar maximum5 = binaryKernelFunc3({\n  opType: BinaryOpType.MAX,\n  cpuKernelImpl: maximumImplCPU2\n});\nvar maximumConfig4 = {\n  kernelName: Maximum,\n  backendName: \"webgpu\",\n  kernelFunc: maximum5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/MaxPool.js\nfunction maxPool5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = 1;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  let program;\n  const dimensions = [];\n  if (convInfo.filterHeight === 1 && convInfo.filterWidth === 1) {\n    if (util_exports.arraysEqual(convInfo.inShape, convInfo.outShape)) {\n      return identity5({ inputs: { x }, backend: backend2 });\n    }\n    program = new PoolWithFilterSizeEqualsOneProgram(convInfo);\n    dimensions.push({ type: \"int32\", data: [convInfo.strideHeight, convInfo.strideWidth] });\n  } else {\n    program = new Pool2DProgram2(convInfo, \"max\");\n    dimensions.push({ type: \"int32\", data: [convInfo.strideHeight, convInfo.strideWidth] }, { type: \"int32\", data: [convInfo.padInfo.top, convInfo.padInfo.left] }, {\n      type: \"int32\",\n      data: [convInfo.dilationHeight, convInfo.dilationWidth]\n    }, { type: \"int32\", data: [convInfo.inHeight, convInfo.inWidth] }, {\n      type: \"int32\",\n      data: [convInfo.effectiveFilterHeight, convInfo.effectiveFilterWidth]\n    });\n  }\n  return backend2.runWebGPUProgram(program, [x], x.dtype, dimensions);\n}\nvar maxPoolConfig4 = {\n  kernelName: MaxPool,\n  backendName: \"webgpu\",\n  kernelFunc: maxPool5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Mean.js\nfunction mean4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { keepDims, axis } = attrs;\n  return reduce2(x, axis, keepDims, \"mean\", backend2);\n}\nvar meanConfig4 = {\n  kernelName: Mean,\n  backendName: \"webgpu\",\n  kernelFunc: mean4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Min.js\nfunction min6(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  return reduce2(x, axis, keepDims, \"min\", backend2);\n}\nvar minConfig4 = {\n  kernelName: Min,\n  backendName: \"webgpu\",\n  kernelFunc: min6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Minimum.js\nvar minimum5 = binaryKernelFunc3({\n  opType: BinaryOpType.MIN,\n  cpuKernelImpl: minimumImplCPU2\n});\nvar minimumConfig4 = {\n  kernelName: Minimum,\n  backendName: \"webgpu\",\n  kernelFunc: minimum5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/mirror_pad_webgpu.js\nvar MirrorPadProgram2 = class {\n  constructor(xShape, paddings, mode) {\n    this.uniforms = \"\";\n    this.variableNames = [\"x\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = paddings.map((p2, i2) => p2[0] + xShape[i2] + p2[1]);\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.xShape = xShape;\n    paddings.map((_, i2) => {\n      this.uniforms += ` pad${i2} : vec2<i32>,`;\n    });\n    this.offset = mode === \"reflect\" ? 0 : 1;\n    this.shaderKey = `mirrorPad_${mode}`;\n  }\n  getUserCode() {\n    const rank = this.xShape.length;\n    const start = this.xShape.map((_, i2) => `uniforms.pad${i2}[0]`).join(\",\");\n    const end = this.xShape.map((_, i2) => `uniforms.pad${i2}[0] + uniforms.xShape${rank > 1 ? `[${i2}]` : \"\"}`).join(\",\");\n    const shaderStart = rank === 1 ? \"start\" : \"start[i]\";\n    const shaderEnd = rank === 1 ? \"end\" : \"end[i]\";\n    const shaderOutC = rank === 1 ? \"outC\" : \"outC[i]\";\n    const dtype = getCoordsDataType2(rank);\n    const unpackedCoords = rank > 1 ? [\"coords[0]\", \"coords[1]\", \"coords[2]\", \"coords[3]\"].slice(0, rank) : \"coords\";\n    return `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let start = ${dtype}(${start});\n          let end = ${dtype}(${end});\n          var outC = getCoordsFromIndex(index);\n          for (var i = 0; i < ${rank}; i = i + 1) {\n            if (${shaderOutC} < ${shaderStart}) {\n              ${shaderOutC} = ${shaderStart} * 2 - ${shaderOutC} - ${this.offset};\n            } else if(${shaderOutC} >= ${shaderEnd}) {\n              ${shaderOutC} = (${shaderEnd} - 1) * 2 - ${shaderOutC} + ${this.offset};\n            }\n          }\n          let coords = outC - start;\n          setOutputAtIndex(index, getX(${unpackedCoords}));\n        }\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/MirrorPad.js\nvar mirrorPadConfig4 = {\n  kernelName: MirrorPad,\n  backendName: \"webgpu\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { x } = inputs;\n    const { paddings, mode } = attrs;\n    const webGPUBackend = backend2;\n    const uniformData = paddings.map((p2) => {\n      return { type: \"int32\", data: [p2[0], p2[1]] };\n    });\n    const program = new MirrorPadProgram2(x.shape, paddings, mode);\n    const output = webGPUBackend.runWebGPUProgram(program, [x], x.dtype, uniformData);\n    return output;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Neg.js\nfunction neg4(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (backend2.shouldExecuteOnCPU([x])) {\n    const xData = backend2.tensorMap.get(x.dataId);\n    const [outValues, newShape] = negImplCPU2(xData.values, x.shape, x.dtype);\n    return backend2.makeTensorInfo(newShape, x.dtype, outValues);\n  }\n  const program = new UnaryOpProgram2(x.shape, UnaryOpType.NEG);\n  return backend2.runWebGPUProgram(program, [x], x.dtype);\n}\nvar negConfig4 = {\n  kernelName: Neg,\n  backendName: \"webgpu\",\n  kernelFunc: neg4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/NonMaxSuppressionV3.js\nfunction nonMaxSuppressionV33(args) {\n  console.warn(\"tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead\");\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold } = attrs;\n  const boxesVals = backend2.readSync(boxes.dataId);\n  const scoresVals = backend2.readSync(scores.dataId);\n  const { selectedIndices } = kernel_impls_exports.nonMaxSuppressionV3Impl(boxesVals, scoresVals, maxOutputSize, iouThreshold, scoreThreshold);\n  return backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices));\n}\nvar nonMaxSuppressionV3Config4 = {\n  kernelName: NonMaxSuppressionV3,\n  backendName: \"webgpu\",\n  kernelFunc: nonMaxSuppressionV33\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/NonMaxSuppressionV5.js\nfunction nonMaxSuppressionV53(args) {\n  console.warn(\"tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead\");\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma } = attrs;\n  const boxesVals = backend2.readSync(boxes.dataId);\n  const scoresVals = backend2.readSync(scores.dataId);\n  const maxOutputSizeVal = maxOutputSize;\n  const iouThresholdVal = iouThreshold;\n  const scoreThresholdVal = scoreThreshold;\n  const softNmsSigmaVal = softNmsSigma;\n  const { selectedIndices, selectedScores } = kernel_impls_exports.nonMaxSuppressionV5Impl(boxesVals, scoresVals, maxOutputSizeVal, iouThresholdVal, scoreThresholdVal, softNmsSigmaVal);\n  return [\n    backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices)),\n    backend2.makeTensorInfo([selectedScores.length], \"float32\", new Float32Array(selectedScores))\n  ];\n}\nvar nonMaxSuppressionV5Config4 = {\n  kernelName: NonMaxSuppressionV5,\n  backendName: \"webgpu\",\n  kernelFunc: nonMaxSuppressionV53\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ZerosLike.js\nfunction zerosLike5(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (x.dtype === \"complex64\") {\n    const realPart = real4({ inputs: { input: x }, backend: backend2 });\n    const r2 = zerosLike5({ inputs: { x: realPart }, backend: backend2 });\n    const imagPart = imag4({ inputs: { input: x }, backend: backend2 });\n    const i2 = zerosLike5({ inputs: { x: imagPart }, backend: backend2 });\n    const result = complex4({ inputs: { real: r2, imag: i2 }, backend: backend2 });\n    backend2.disposeData(realPart.dataId);\n    backend2.disposeData(r2.dataId);\n    backend2.disposeData(imagPart.dataId);\n    backend2.disposeData(i2.dataId);\n    return result;\n  } else {\n    return fill5({\n      attrs: {\n        shape: x.shape,\n        dtype: x.dtype,\n        value: x.dtype === \"string\" ? \"\" : 0\n      },\n      backend: backend2\n    });\n  }\n}\nvar zerosLikeConfig4 = {\n  kernelName: ZerosLike,\n  backendName: \"webgpu\",\n  kernelFunc: zerosLike5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/OnesLike.js\nfunction onesLike5(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (x.dtype === \"string\") {\n    throw new Error(\"onesLike is not supported under string dtype\");\n  } else if (x.dtype === \"complex64\") {\n    const realPart = real4({ inputs: { input: x }, backend: backend2 });\n    const r2 = onesLike5({ inputs: { x: realPart }, backend: backend2 });\n    const imagPart = imag4({ inputs: { input: x }, backend: backend2 });\n    const i2 = zerosLike5({ inputs: { x: imagPart }, backend: backend2 });\n    const result = complex4({ inputs: { real: r2, imag: i2 }, backend: backend2 });\n    backend2.disposeData(realPart.dataId);\n    backend2.disposeData(r2.dataId);\n    backend2.disposeData(imagPart.dataId);\n    backend2.disposeData(i2.dataId);\n    return result;\n  } else {\n    return fill5({ attrs: { shape: x.shape, dtype: x.dtype, value: 1 }, backend: backend2 });\n  }\n}\nvar onesLikeConfig4 = {\n  kernelName: OnesLike,\n  backendName: \"webgpu\",\n  kernelFunc: onesLike5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Pack.js\nfunction pack4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { axis } = attrs;\n  if (inputs.length === 1) {\n    return expandDims6({ inputs: { input: inputs[0] }, backend: backend2, attrs: { dim: axis } });\n  }\n  const shape = inputs[0].shape;\n  const dtype = inputs[0].dtype;\n  inputs.forEach((t2) => {\n    util_exports.assertShapesMatch(shape, t2.shape, \"All tensors passed to stack must have matching shapes\");\n    util_exports.assert(dtype === t2.dtype, () => \"All tensors passed to stack must have matching dtypes\");\n  });\n  const intermediateTensorInfos = [];\n  const expandedTensors = inputs.map((t2) => {\n    const expandedT = expandDims6({ inputs: { input: t2 }, backend: backend2, attrs: { dim: axis } });\n    intermediateTensorInfos.push(expandedT);\n    return expandedT;\n  });\n  const result = concat5({ inputs: expandedTensors, backend: backend2, attrs: { axis } });\n  intermediateTensorInfos.forEach((t2) => backend2.disposeData(t2.dataId));\n  return result;\n}\nvar packConfig4 = {\n  kernelName: Pack,\n  backendName: \"webgpu\",\n  kernelFunc: pack4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/pad_webgpu.js\nvar PadProgram2 = class {\n  constructor(xShape, paddings) {\n    this.variableNames = [\"x\"];\n    this.uniforms = \"constantValue : f32,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = paddings.map((p2, i2) => p2[0] + xShape[i2] + p2[1]);\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    paddings.map((_, i2) => {\n      this.uniforms += ` pad${i2} : vec2<i32>,`;\n    });\n    this.xShape = xShape;\n    this.shaderKey = \"pad\";\n  }\n  getUserCode() {\n    const rank = this.xShape.length;\n    const type = getCoordsDataType2(rank);\n    const start = this.xShape.map((_, i2) => `uniforms.pad${i2}[0]`).join(\",\");\n    const end = this.xShape.map((_, i2) => `uniforms.pad${i2}[0] + uniforms.xShape${rank > 1 ? `[${i2}]` : \"\"}`).join(\",\");\n    const startValue = rank > 1 ? `${type}(${start})` : `${start}`;\n    const endValue = rank > 1 ? `${type}(${end})` : `${end}`;\n    const leftPadCondition = rank > 1 ? `any(outC < start)` : `outC < start`;\n    const rightPadCondition = rank > 1 ? `any(outC >= end)` : `outC >= end`;\n    const unpackedCoords = rank > 1 ? [\"coords[0]\", \"coords[1]\", \"coords[2]\", \"coords[3]\"].slice(0, rank) : \"coords\";\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let start = ${startValue};\n          let end = ${endValue};\n          let outC = getCoordsFromIndex(index);\n\n          if (${leftPadCondition} || ${rightPadCondition}) {\n            setOutputAtIndex(index, uniforms.constantValue);\n          } else {\n            let coords = outC - start;\n            setOutputAtIndex(index, getX(${unpackedCoords}));\n          }\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/PadV2.js\nvar padV23 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { paddings, constantValue } = attrs;\n  if (paddings.every((p2) => util_exports.arraysEqual(p2, [0, 0]))) {\n    return identity5({ inputs: { x }, backend: backend2 });\n  }\n  if (util_exports.sizeFromShape(x.shape) === 0) {\n    const outputShape = paddings.map((p2, i2) => p2[0] + x.shape[i2] + p2[1]);\n    return fill5({\n      backend: backend2,\n      attrs: { shape: outputShape, value: constantValue, dtype: x.dtype }\n    });\n  }\n  const uniformData = [{ type: \"float32\", data: [constantValue] }];\n  paddings.map((p2) => uniformData.push({ type: \"int32\", data: [p2[0], p2[1]] }));\n  const program = new PadProgram2(x.shape, paddings);\n  return backend2.runWebGPUProgram(program, [x], x.dtype, uniformData);\n};\nvar padV2Config4 = {\n  kernelName: PadV2,\n  backendName: \"webgpu\",\n  kernelFunc: padV23\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Pow.js\nvar pow4 = binaryKernelFunc3({\n  opType: BinaryOpType.POW\n});\nvar powConfig4 = {\n  kernelName: Pow,\n  backendName: \"webgpu\",\n  kernelFunc: pow4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Prelu.js\nfunction prelu6(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x, alpha } = inputs;\n  const program = new BinaryOpProgram2(BinaryOpType.PRELU, x.shape, alpha.shape);\n  return backend2.runWebGPUProgram(program, [x, alpha], \"float32\");\n}\nvar preluConfig4 = {\n  kernelName: Prelu,\n  backendName: \"webgpu\",\n  kernelFunc: prelu6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Prod.js\nfunction prod5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  return reduce2(x, axis, keepDims, \"prod\", backend2);\n}\nvar prodConfig4 = {\n  kernelName: Prod,\n  backendName: \"webgpu\",\n  kernelFunc: prod5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Range.js\nvar range6 = (args) => {\n  const { backend: backend2, attrs } = args;\n  const { start, stop, step: step5, dtype } = attrs;\n  const values = rangeImplCPU2(start, stop, step5, dtype);\n  return backend2.makeTensorInfo([values.length], dtype, values);\n};\nvar rangeConfig4 = {\n  kernelName: Range,\n  backendName: \"webgpu\",\n  kernelFunc: range6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/RealDiv.js\nvar realDiv2 = binaryKernelFunc3({ opType: BinaryOpType.DIV });\nvar realDivConfig4 = {\n  kernelName: RealDiv,\n  backendName: \"webgpu\",\n  kernelFunc: realDiv2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Relu.js\nvar relu4 = unaryKernelFunc3({ opType: UnaryOpType.RELU });\nvar reluConfig4 = {\n  kernelName: Relu,\n  backendName: \"webgpu\",\n  kernelFunc: relu4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Relu6.js\nvar relu64 = unaryKernelFunc3({ opType: UnaryOpType.RELU6 });\nvar relu6Config4 = {\n  kernelName: Relu6,\n  backendName: \"webgpu\",\n  kernelFunc: relu64\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/resize_bilinear_webgpu.js\nvar ResizeBilinearProgram2 = class {\n  constructor(inputShape, newHeight, newWidth) {\n    this.variableNames = [\"x\"];\n    this.uniforms = \"adjustHeightWidth : vec2<f32>, halfPixelCenters : f32,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = [inputShape[0], newHeight, newWidth, inputShape[3]];\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = `resizeBilinear`;\n  }\n  getUserCode() {\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n        let coords = getCoordsFromIndex(index);\n          let b = coords[0];\n          let d = coords[3];\n          let rc = coords.yz;\n\n          let effectiveInSize = vec2<f32>(\n            f32(uniforms.xShape.y) - uniforms.adjustHeightWidth[0],\n            f32(uniforms.xShape.z) - uniforms.adjustHeightWidth[1]);\n\n          let effectiveOutSize = vec2<f32>(\n            f32(uniforms.outShape.y) - uniforms.adjustHeightWidth[0],\n            f32(uniforms.outShape.z) - uniforms.adjustHeightWidth[1]);\n\n          let effectiveInputOverOutputRatioRC =\n              effectiveInSize / effectiveOutSize;\n\n          // Fractional source index\n          let sourceFracIndexRC =\n            (vec2<f32>(rc) + vec2<f32>(uniforms.halfPixelCenters)) *\n            effectiveInputOverOutputRatioRC - vec2<f32>(uniforms.halfPixelCenters);\n\n          // Compute the four integer indices.\n          let sourceFloorRC = vec2<i32>(sourceFracIndexRC);\n          let sourceCeilRC = vec2<i32>(\n            min(vec2<f32>(uniforms.xShape.yz) - vec2<f32>(1.0), ceil(sourceFracIndexRC)));\n\n          let topLeft = getX(b, sourceFloorRC.x, sourceFloorRC.y, d);\n          let bottomLeft = getX(b, sourceCeilRC.x, sourceFloorRC.y, d);\n          let topRight = getX(b, sourceFloorRC.x, sourceCeilRC.y, d);\n          let bottomRight = getX(b, sourceCeilRC.x, sourceCeilRC.y, d);\n\n          let fracRC = sourceFracIndexRC - vec2<f32>(sourceFloorRC);\n\n          let top = topLeft + (topRight - topLeft) * fracRC.y;\n          let bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\n          let newValue = top + (bottom - top) * fracRC.x;\n\n          setOutputAtIndex(index, newValue);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ResizeBilinear.js\nfunction resizeBilinear5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, size, halfPixelCenters } = attrs;\n  const [newHeight, newWidth] = size;\n  const adjustHeight = alignCorners && newHeight > 1 ? 1 : 0;\n  const adjustWidth = alignCorners && newWidth > 1 ? 1 : 0;\n  const halfPixelCentersValue = halfPixelCenters ? 0.5 : 0;\n  const uniformData = [\n    { type: \"float32\", data: [adjustHeight, adjustWidth] },\n    { type: \"float32\", data: [halfPixelCentersValue] }\n  ];\n  const program = new ResizeBilinearProgram2(images.shape, newHeight, newWidth);\n  return backend2.runWebGPUProgram(program, [images], \"float32\", uniformData);\n}\nvar resizeBilinearConfig4 = {\n  kernelName: ResizeBilinear,\n  backendName: \"webgpu\",\n  kernelFunc: resizeBilinear5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/resize_nearest_neighbor_webgpu.js\nvar ResizeNearestNeighborProgram2 = class {\n  constructor(inputShape, newHeight, newWidth, halfPixelCenters) {\n    this.variableNames = [\"x\"];\n    this.uniforms = \"adjustHeightWidth : vec2<f32>, roundBase : f32,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = [inputShape[0], newHeight, newWidth, inputShape[3]];\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.halfPixelCenters = halfPixelCenters;\n    this.shaderKey = `resizeNearest_${halfPixelCenters}`;\n  }\n  getUserCode() {\n    let sourceFracIndexRC;\n    if (this.halfPixelCenters) {\n      sourceFracIndexRC = `max((vec2<f32>(rc) + vec2<f32>(0.5)) * effectiveInputOverOutputRatioRC, vec2<f32>(0.0))`;\n    } else {\n      sourceFracIndexRC = `vec2<f32>(rc) * effectiveInputOverOutputRatioRC`;\n    }\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let coords = getCoordsFromIndex(index);\n          let b = coords[0];\n          let d = coords[3];\n          let rc = coords.yz;\n\n          let effectiveInSize = vec2<f32>(\n            f32(uniforms.xShape.y) - uniforms.adjustHeightWidth[0],\n            f32(uniforms.xShape.z) - uniforms.adjustHeightWidth[1]);\n\n          let effectiveOutSize = vec2<f32>(\n            f32(uniforms.outShape.y) - uniforms.adjustHeightWidth[0],\n            f32(uniforms.outShape.z) - uniforms.adjustHeightWidth[1]);\n\n          let effectiveInputOverOutputRatioRC =\n              effectiveInSize / effectiveOutSize;\n\n          // Fractional source index\n          let sourceFracIndexRC = ${sourceFracIndexRC};\n\n          // Compute the coordinators of nearest neighbor point.\n          let inputShapeRC = vec2<f32>(f32(uniforms.xShape.y), f32(uniforms.xShape.z));\n          let sourceNearestRC = vec2<i32>(\n            min(inputShapeRC - 1.0, floor(sourceFracIndexRC + uniforms.roundBase)));\n          let newValue = getX(b, sourceNearestRC.x, sourceNearestRC.y, d);\n\n          setOutputAtIndex(index, newValue);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ResizeNearestNeighbor.js\nfunction resizeNearestNeighbor5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, halfPixelCenters, size } = attrs;\n  const [newHeight, newWidth] = size;\n  const adjustHeight = alignCorners && newHeight > 1 ? 1 : 0;\n  const adjustWidth = alignCorners && newWidth > 1 ? 1 : 0;\n  const roundBase = alignCorners ? 0.5 : 0;\n  const uniformData = [\n    { type: \"float32\", data: [adjustHeight, adjustWidth] },\n    { type: \"float32\", data: [roundBase] }\n  ];\n  const program = new ResizeNearestNeighborProgram2(images.shape, newHeight, newWidth, halfPixelCenters);\n  return backend2.runWebGPUProgram(program, [images], images.dtype, uniformData);\n}\nvar resizeNearestNeighborConfig4 = {\n  kernelName: ResizeNearestNeighbor,\n  backendName: \"webgpu\",\n  kernelFunc: resizeNearestNeighbor5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/rotate_webgpu.js\nvar RotateProgram2 = class {\n  constructor(imageShape, fillValue) {\n    this.outputShape = [];\n    this.variableNames = [\"x\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = imageShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.uniforms = `centerX : f32, centerY : f32, sinRadians : f32,\n          cosRadians : f32,`;\n    this.shaderKey = \"rotate\";\n    this.outputShape = imageShape;\n    if (typeof fillValue === \"number\") {\n      this.uniforms += ` fillValue : f32,`;\n      this.fillSnippet = `var outputValue = uniforms.fillValue;`;\n      this.shaderKey += \"_float\";\n    } else {\n      this.uniforms += ` fillValue : vec3<f32>,`;\n      this.fillSnippet = `var outputValue = uniforms.fillValue[coords[3]];`;\n      this.shaderKey += \"_vec3\";\n    }\n  }\n  getUserCode() {\n    const userCode = `\n        ${getMainHeaderAndGlobalIndexString()}\n\n          if (index < uniforms.size) {\n            let coords = getCoordsFromIndex(index);\n            let coordXFloat = (f32(coords[2]) - uniforms.centerX) *\n                uniforms.cosRadians - (f32(coords[1]) - uniforms.centerY) *\n                uniforms.sinRadians;\n            let coordYFloat = (f32(coords[2]) - uniforms.centerX) *\n                uniforms.sinRadians + (f32(coords[1]) - uniforms.centerY) *\n                uniforms.cosRadians;\n            let coordX = i32(round(coordXFloat + uniforms.centerX));\n            let coordY = i32(round(coordYFloat + uniforms.centerY));\n            ${this.fillSnippet}\n            if(coordX >= 0 && coordX < uniforms.xShape[2] && coordY >= 0 &&\n                coordY < uniforms.xShape[1]) {\n              outputValue = getX(coords[0], coordY, coordX, coords[3]);\n            }\n            setOutputAtIndex(index, outputValue);\n          }\n        }\n      `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/RotateWithOffset.js\nvar rotateWithOffsetConfig4 = {\n  kernelName: RotateWithOffset,\n  backendName: \"webgpu\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { image: image2 } = inputs;\n    const { radians, fillValue, center } = attrs;\n    const webgpuBackend = backend2;\n    const program = new RotateProgram2(image2.shape, fillValue);\n    const [centerX, centerY] = backend_util_exports.getImageCenter(center, image2.shape[1], image2.shape[2]);\n    const uniformData = [\n      { type: \"float32\", data: [centerX] },\n      { type: \"float32\", data: [centerY] },\n      { type: \"float32\", data: [Math.sin(radians)] },\n      { type: \"float32\", data: [Math.cos(radians)] }\n    ];\n    if (typeof fillValue === \"number\") {\n      uniformData.push({ type: \"float32\", data: [Number.parseFloat(fillValue.toFixed(2))] });\n    } else {\n      uniformData.push({ type: \"float32\", data: fillValue });\n    }\n    const output = webgpuBackend.runWebGPUProgram(program, [image2], image2.dtype, uniformData);\n    return output;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Rsqrt.js\nvar rsqrt4 = unaryKernelFunc3({ opType: UnaryOpType.RSQRT, cpuKernelImpl: rsqrtImplCPU2 });\nvar rsqrtConfig4 = {\n  kernelName: Rsqrt,\n  backendName: \"webgpu\",\n  kernelFunc: rsqrt4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/scatter_optimized_webgpu.js\nvar ScatterOptimizedProgram = class {\n  constructor(flattenXShape, sliceDim, indicesRank, updatesRank, strides, shape, outputDtype, sumDupeIndices = true) {\n    this.variableNames = [\"updates\", \"indices\"];\n    this.workGroupSize = [64, 1, 1];\n    this.atomic = true;\n    this.outputShape = shape;\n    this.type = outputDtype;\n    this.sumDupeIndices = sumDupeIndices;\n    this.dispatchLayout = flatDispatchLayout(flattenXShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, flattenXShape, this.workGroupSize);\n    this.sliceDimGreaterThanOne = sliceDim > 1;\n    this.shaderKey = `scatter_${indicesRank}_${updatesRank}_${this.sliceDimGreaterThanOne}_${outputDtype}_${sumDupeIndices}`;\n    const stridesType = getCoordsDataType2(strides.length);\n    this.uniforms = `sliceDim : i32, strides: ${stridesType}, size: i32,`;\n    this.updatesRank = updatesRank;\n    this.indicesRank = indicesRank;\n  }\n  getUserCode() {\n    let indicesString = \"\";\n    if (this.indicesRank === 1) {\n      indicesString = \"coords[0]\";\n    } else if (this.indicesRank === 2) {\n      indicesString = \"coords[0], j\";\n    }\n    const indicesSnippet = `getIndices(${indicesString})`;\n    const strideString = this.sliceDimGreaterThanOne ? \"uniforms.strides[j]\" : \"uniforms.strides\";\n    let outCoordsString = \"\";\n    let getUpdatesCoordsFromFlatIndex = \"\";\n    if (this.dispatchLayout.x.length === 1) {\n      outCoordsString = \"flattenedIndex\";\n      getUpdatesCoordsFromFlatIndex = `\n      fn getUpdatesCoordsFromFlatIndex(index : i32) -> i32 {\n        return index;\n      }\n      `;\n    } else if (this.dispatchLayout.x.length === 2) {\n      outCoordsString = \"vec2<i32>(flattenedIndex, coords[1])\";\n      getUpdatesCoordsFromFlatIndex = `\n      fn getUpdatesCoordsFromFlatIndex(index : i32) -> vec2<i32> {\n        // N.B. |updates| could be a scalar tensor, conceptually representing a\n        // 2D tensor with all values equal to that. By design, its size must be\n        // the same as |outShape[1]| in one dimension, and |indicesShape[0]|\n        // gives the other.\n        let sliceSize = uniforms.outShape[1];\n        let d0 = index / sliceSize;\n        let d1 = index - d0 * sliceSize;\n        return vec2<i32>(d0, d1);\n      }\n      `;\n    }\n    const updatesString = Array.from({ length: this.updatesRank }, (_, idx) => `coords[${idx}]`);\n    const updatesSnippet = `getUpdates(${updatesString.join(\", \")})`;\n    const atomicRMW = (ptr, val) => {\n      let atomicAddSnippet = `atomicAdd(${ptr}, bitcast<i32>(${val}))`;\n      if (this.type === \"float32\") {\n        atomicAddSnippet = `\n          {\n            var oldBits = 0;\n            var newBits = bitcast<i32>(${val});\n            loop {\n              let info = atomicCompareExchangeWeak(${ptr}, oldBits, newBits);\n              if (info.exchanged) {\n                break;\n              }\n              oldBits = info.old_value;\n              let oldValue = bitcast<f32>(oldBits);\n              let newValue = oldValue + (${val});\n              newBits = bitcast<i32>(newValue);\n            }\n          }\n        `;\n      }\n      const atomicStoreSnippet = `atomicStore(${ptr}, bitcast<i32>(${val}));`;\n      return this.sumDupeIndices ? atomicAddSnippet : atomicStoreSnippet;\n    };\n    const userCode = `\n    ${getUpdatesCoordsFromFlatIndex}\n\n      ${getMainHeaderAndGlobalIndexString()}\n\n        if (index < uniforms.size) {\n          let coords = getUpdatesCoordsFromFlatIndex(index);\n          var flattenedIndex = 0;\n          for (var j = 0; j < uniforms.sliceDim; j = j + 1) {\n            let indexInside = i32(round(${indicesSnippet}));\n            flattenedIndex = flattenedIndex + indexInside * ${strideString};\n          }\n          let updateValue =\n              ${mapToWgslTypes(this.type, false)}(${updatesSnippet});\n          let flatIndex = getOutputIndexFromCoords(${outCoordsString});\n\n          ${atomicRMW(\"&result[flatIndex]\", \"updateValue\")};\n        }\n      }`;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ScatterNd.js\nfunction scatterNd4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { indices, updates } = inputs;\n  const { shape } = attrs;\n  const { sliceRank, numUpdates, sliceSize, strides, outputSize } = backend_util_exports.calculateShapes(updates, indices, shape);\n  const flattenShape = [outputSize / sliceSize, sliceSize];\n  if (outputSize === 0) {\n    return backend2.makeTensorInfo(shape, indices.dtype);\n  }\n  const flattenIndices = reshape6({ inputs: { x: indices }, backend: backend2, attrs: { shape: [numUpdates, sliceRank] } });\n  const flattenX = reshape6({ inputs: { x: updates }, backend: backend2, attrs: { shape: [numUpdates, sliceSize] } });\n  const type = flattenX.dtype;\n  const output = fill5({ backend: backend2, attrs: { shape: flattenShape, value: 0, dtype: type } });\n  const size = util_exports.sizeFromShape(flattenX.shape);\n  const uniformData = [\n    { type: \"int32\", data: [sliceRank] },\n    { type: \"int32\", data: strides },\n    { type: \"int32\", data: [size] }\n  ];\n  const program = new ScatterOptimizedProgram(flattenX.shape, sliceRank, flattenIndices.shape.length, flattenX.shape.length, strides, flattenShape, type);\n  const res = backend2.runWebGPUProgram(program, [flattenX, flattenIndices], type, uniformData, output);\n  const reshaped = reshape6({ inputs: { x: res }, backend: backend2, attrs: { shape } });\n  backend2.disposeData(flattenIndices.dataId);\n  backend2.disposeData(flattenX.dataId);\n  backend2.disposeData(res.dataId);\n  return reshaped;\n}\nvar scatterNdConfig4 = {\n  kernelName: ScatterNd,\n  backendName: \"webgpu\",\n  kernelFunc: scatterNd4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/select_webgpu.js\nvar SelectProgram2 = class {\n  constructor(cRank, shape, rank) {\n    this.variableNames = [\"c\", \"a\", \"b\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = shape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.cRank = cRank;\n    this.rank = rank;\n    this.shaderKey = \"select\";\n  }\n  getUserCode() {\n    let cCoords;\n    let abCoords;\n    if (this.rank > 4) {\n      throw Error(`Where for rank ${this.rank} is not yet supported`);\n    }\n    if (this.rank === 1) {\n      abCoords = `resRC`;\n      cCoords = `resRC`;\n    } else {\n      const currentCoords = [\"resRC.x\", \"resRC.y\", \"resRC.z\", \"resRC.w\"];\n      const cCoordVars = [];\n      const abCoordVars = [];\n      for (let i2 = 0; i2 < this.outputShape.length; i2++) {\n        abCoordVars.push(`${currentCoords[i2]}`);\n        if (i2 < this.cRank) {\n          cCoordVars.push(`${currentCoords[i2]}`);\n        }\n      }\n      cCoords = cCoordVars.join();\n      abCoords = abCoordVars.join();\n    }\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let resRC = getCoordsFromIndex(index);\n          let cVal = getC(${cCoords});\n          if (cVal >= 1.0) {\n            setOutputAtIndex(index, getA(${abCoords}));\n          } else {\n            setOutputAtIndex(index, getB(${abCoords}));\n          }\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Select.js\nfunction select5(args) {\n  const { inputs, backend: backend2 } = args;\n  const { condition, t: t2, e: e2 } = inputs;\n  const program = new SelectProgram2(condition.shape.length, t2.shape, t2.shape.length);\n  return backend2.runWebGPUProgram(program, [condition, t2, e2], upcastType(t2.dtype, e2.dtype));\n}\nvar selectConfig4 = {\n  kernelName: Select,\n  backendName: \"webgpu\",\n  kernelFunc: select5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Sigmoid.js\nvar sigmoid5 = unaryKernelFunc3({ opType: UnaryOpType.SIGMOID });\nvar sigmoidConfig4 = {\n  kernelName: Sigmoid,\n  backendName: \"webgpu\",\n  kernelFunc: sigmoid5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Sin.js\nvar sin4 = unaryKernelFunc3({ opType: UnaryOpType.SIN });\nvar sinConfig4 = {\n  kernelName: Sin,\n  backendName: \"webgpu\",\n  kernelFunc: sin4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Sinh.js\nvar sinh4 = unaryKernelFunc3({ opType: UnaryOpType.SINH });\nvar sinhConfig3 = {\n  kernelName: Sinh,\n  backendName: \"webgpu\",\n  kernelFunc: sinh4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Sub.js\nvar sub4 = binaryKernelFunc3({ opType: BinaryOpType.SUB, cpuKernelImpl: subImplCPU2, supportsComplex: true });\nvar subConfig4 = {\n  kernelName: Sub,\n  backendName: \"webgpu\",\n  kernelFunc: sub4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Softmax.js\nfunction softmax6(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { logits } = inputs;\n  const { dim } = attrs;\n  const axes = util_exports.parseAxisParam([dim], logits.shape);\n  const maxLogit = max6({\n    inputs: { x: logits },\n    backend: backend2,\n    attrs: { reductionIndices: axes, keepDims: false }\n  });\n  const expandedShape = backend_util_exports.expandShapeToKeepDim(maxLogit.shape, axes);\n  const maxLogitsReshaped = reshape6({ inputs: { x: maxLogit }, backend: backend2, attrs: { shape: expandedShape } });\n  const a = sub4({ inputs: { a: logits, b: maxLogitsReshaped }, backend: backend2 });\n  const b = exp4({ inputs: { x: a }, backend: backend2 });\n  const sumExp = sum6({ inputs: { x: b }, backend: backend2, attrs: { axis: axes, keepDims: false } });\n  const sumExpReshaped = reshape6({ inputs: { x: sumExp }, backend: backend2, attrs: { shape: expandedShape } });\n  const res = realDiv2({ inputs: { a: b, b: sumExpReshaped }, backend: backend2 });\n  backend2.disposeData(maxLogit.dataId);\n  backend2.disposeData(maxLogitsReshaped.dataId);\n  backend2.disposeData(a.dataId);\n  backend2.disposeData(b.dataId);\n  backend2.disposeData(sumExp.dataId);\n  backend2.disposeData(sumExpReshaped.dataId);\n  return res;\n}\nvar softmaxConfig4 = {\n  kernelName: Softmax,\n  backendName: \"webgpu\",\n  kernelFunc: softmax6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/SpaceToBatchND.js\nvar spaceToBatchND5 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, paddings } = attrs;\n  util_exports.assert(x.shape.length <= 4, () => \"spaceToBatchND for rank > 4 with a WebGPU backend not implemented yet\");\n  const prod6 = blockShape.reduce((a, b) => a * b);\n  const completePaddings = [[0, 0]];\n  completePaddings.push(...paddings);\n  for (let i2 = 1 + blockShape.length; i2 < x.shape.length; ++i2) {\n    completePaddings.push([0, 0]);\n  }\n  const toDispose = [];\n  const paddedX = padV23({\n    inputs: { x },\n    backend: backend2,\n    attrs: { paddings: completePaddings, constantValue: 0 }\n  });\n  const reshapedPaddedShape = backend_util_exports.getReshaped(paddedX.shape, blockShape, prod6, false);\n  const permutedReshapedPaddedPermutation = backend_util_exports.getPermuted(reshapedPaddedShape.length, blockShape.length, false);\n  const flattenShape = backend_util_exports.getReshapedPermuted(paddedX.shape, blockShape, prod6, false);\n  const reshapedPaddedX = reshape6({ inputs: { x: paddedX }, backend: backend2, attrs: { shape: reshapedPaddedShape } });\n  const paddedXT = transpose5({\n    inputs: { x: reshapedPaddedX },\n    backend: backend2,\n    attrs: { perm: permutedReshapedPaddedPermutation }\n  });\n  const result = reshape6({ inputs: { x: paddedXT }, backend: backend2, attrs: { shape: flattenShape } });\n  toDispose.push(paddedX);\n  toDispose.push(reshapedPaddedX);\n  toDispose.push(paddedXT);\n  toDispose.forEach((t2) => backend2.disposeData(t2.dataId));\n  return result;\n};\nvar spaceToBatchNDConfig4 = {\n  kernelName: SpaceToBatchND,\n  backendName: \"webgpu\",\n  kernelFunc: spaceToBatchND5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/tile_webgpu.js\nvar TileProgram2 = class {\n  constructor(aShape, reps) {\n    this.variableNames = [\"A\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    const outputShape = new Array(aShape.length);\n    for (let i2 = 0; i2 < outputShape.length; i2++) {\n      outputShape[i2] = aShape[i2] * reps[i2];\n    }\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.rank = this.outputShape.length;\n    this.shaderKey = \"tile\";\n  }\n  getUserCode() {\n    const sourceCoords = getSourceCoords5(this.rank, \"uniforms.\");\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let resRC = getCoordsFromIndex(index);\n          setOutputAtIndex(index, getA(${sourceCoords}));\n        }\n      }\n    `;\n    return userCode;\n  }\n};\nfunction getSourceCoords5(rank, uniformPrefix = \"\") {\n  if (rank >= 5) {\n    throw Error(`Tile for rank ${rank} is not yet supported`);\n  }\n  if (rank === 1) {\n    return `(resRC % ${uniformPrefix}aShape)`;\n  }\n  const currentCoords = [\"resRC.x\", \"resRC.y\", \"resRC.z\", \"resRC.w\"];\n  const sourceCoords = [];\n  for (let i2 = 0; i2 < rank; i2++) {\n    sourceCoords.push(`(${currentCoords[i2]} % ${uniformPrefix}aShape[${i2}])`);\n  }\n  return sourceCoords.join();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Tile.js\nfunction tile6(params) {\n  const { inputs, backend: backend2, attrs } = params;\n  const { x } = inputs;\n  const { reps } = attrs;\n  if (backend2.shouldExecuteOnCPU([x]) || x.dtype === \"string\" || x.shape.length >= 5) {\n    const data = backend2.readSync(x.dataId);\n    const value = x.dtype === \"string\" ? data.map((d) => util_exports.decodeString(d)) : data;\n    const buf = buffer(x.shape, x.dtype, value);\n    const outBuf = tileImplCPU2(buf, reps);\n    return backend2.makeTensorInfo(outBuf.shape, outBuf.dtype, outBuf.values);\n  }\n  const program = new TileProgram2(x.shape, reps);\n  const output = backend2.runWebGPUProgram(program, [x], x.dtype);\n  return output;\n}\nvar tileConfig4 = {\n  kernelName: Tile,\n  backendName: \"webgpu\",\n  kernelFunc: tile6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/SparseToDense.js\nfunction sparseToDense4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { sparseIndices, sparseValues, defaultValue } = inputs;\n  const { outputShape } = attrs;\n  const { sliceRank, numUpdates, sliceSize, strides, outputSize } = backend_util_exports.calculateShapes(sparseValues, sparseIndices, outputShape);\n  const sumDupeIndices = false;\n  if (sparseValues.dtype === \"string\") {\n    const indicesBuf = backend2.bufferSync(sparseIndices);\n    const updatesBuf = backend2.bufferSync(sparseValues);\n    const $defaultValue2 = util_exports.decodeString(backend2.readSync(defaultValue.dataId)[0]);\n    const outBuf = scatterImplCPU2(indicesBuf, updatesBuf, outputShape, outputSize, sliceSize, numUpdates, sliceRank, strides, $defaultValue2, sumDupeIndices);\n    return backend2.makeTensorInfo(outputShape, outBuf.dtype, outBuf.values);\n  }\n  const flattenShape = [outputSize / sliceSize, sliceSize];\n  const $sparseIndices = reshape6({\n    inputs: { x: sparseIndices },\n    backend: backend2,\n    attrs: { shape: [numUpdates, sliceRank] }\n  });\n  const $sparseValues = sparseValues.shape.length ? reshape6({\n    inputs: { x: sparseValues },\n    backend: backend2,\n    attrs: { shape: [numUpdates, sliceSize] }\n  }) : identity5({ inputs: { x: sparseValues }, backend: backend2 });\n  const type = $sparseValues.dtype;\n  const zero = backend2.makeTensorInfo([], type, util_exports.makeZerosTypedArray(1, type));\n  const $defaultValue = reshape6({\n    inputs: { x: defaultValue },\n    backend: backend2,\n    attrs: { shape: Array(flattenShape.length).fill(1) }\n  });\n  const $denseValues = tile6({ inputs: { x: $defaultValue }, backend: backend2, attrs: { reps: flattenShape } });\n  const size = util_exports.sizeFromShape([numUpdates, sliceSize]);\n  const uniformData = [\n    { type: \"int32\", data: [sliceRank] },\n    { type: \"int32\", data: strides },\n    { type: \"int32\", data: [size] }\n  ];\n  switch (numUpdates) {\n    case 0:\n      break;\n    case 1:\n      if (true) {\n        const program = new ScatterOptimizedProgram([numUpdates, sliceSize], sliceRank, $sparseIndices.shape.length, $sparseValues.shape.length, strides, flattenShape, type, sumDupeIndices);\n        backend2.runWebGPUProgram(program, [$sparseValues, $sparseIndices], type, uniformData, $denseValues);\n      }\n      break;\n    default:\n      if (true) {\n        const program = new ScatterOptimizedProgram([numUpdates, sliceSize], sliceRank, $sparseIndices.shape.length, zero.shape.length, strides, flattenShape, type, sumDupeIndices);\n        backend2.runWebGPUProgram(program, [zero, $sparseIndices], type, uniformData, $denseValues);\n      }\n      {\n        const program = new ScatterOptimizedProgram([numUpdates, sliceSize], sliceRank, $sparseIndices.shape.length, $sparseValues.shape.length, strides, flattenShape, type);\n        backend2.runWebGPUProgram(program, [$sparseValues, $sparseIndices], type, uniformData, $denseValues);\n      }\n  }\n  const denseValues = reshape6({ inputs: { x: $denseValues }, backend: backend2, attrs: { shape: outputShape } });\n  backend2.disposeData($sparseIndices.dataId);\n  backend2.disposeData($sparseValues.dataId);\n  backend2.disposeData($defaultValue.dataId);\n  backend2.disposeData(zero.dataId);\n  backend2.disposeData($denseValues.dataId);\n  return denseValues;\n}\nvar sparseToDenseConfig3 = {\n  kernelName: SparseToDense,\n  backendName: \"webgpu\",\n  kernelFunc: sparseToDense4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/SplitV.js\nfunction splitV4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { numOrSizeSplits, axis } = attrs;\n  const $axis = util_exports.parseAxisParam(axis, x.shape)[0];\n  const splitSizes = backend_util_exports.prepareSplitSize(x, numOrSizeSplits, $axis);\n  const xRank = x.shape.length;\n  const begin = new Array(xRank).fill(0);\n  const size = x.shape.slice();\n  return splitSizes.map((s2) => {\n    const sliceSize = [...size];\n    sliceSize[$axis] = s2;\n    const sliceT = slice5({ inputs: { x }, backend: backend2, attrs: { begin, size: sliceSize } });\n    begin[$axis] += s2;\n    return sliceT;\n  });\n}\nvar splitVConfig4 = {\n  kernelName: SplitV,\n  backendName: \"webgpu\",\n  kernelFunc: splitV4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Sqrt.js\nvar sqrt4 = unaryKernelFunc3({ opType: UnaryOpType.SQRT });\nvar sqrtConfig4 = {\n  kernelName: Sqrt,\n  backendName: \"webgpu\",\n  kernelFunc: sqrt4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Square.js\nvar squareConfig4 = {\n  kernelName: Square,\n  backendName: \"webgpu\",\n  kernelFunc: ({ inputs, backend: backend2 }) => {\n    const { x } = inputs;\n    const webGPUBackend = backend2;\n    const program = new UnaryOpProgram2(x.shape, UnaryOpType.SQUARE);\n    return webGPUBackend.runWebGPUProgram(program, [x], x.dtype);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/SquaredDifference.js\nvar squaredDifference4 = binaryKernelFunc3({\n  opType: BinaryOpType.SQUARED_DIFFERENCE\n});\nvar squaredDifferenceConfig4 = {\n  kernelName: SquaredDifference,\n  backendName: \"webgpu\",\n  kernelFunc: squaredDifference4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/strided_slice_webgpu.js\nvar StridedSliceProgram2 = class {\n  constructor(destSize) {\n    this.variableNames = [\"x\"];\n    this.workPerThread = 1;\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = destSize;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [this.workPerThread, 1, 1]);\n    const dtype = getCoordsDataType2(this.outputShape.length);\n    this.uniforms = `begin : ${dtype},  strides : ${dtype}, `;\n    this.shaderKey = \"stridedSlice\";\n  }\n  getUserCode() {\n    const rank = this.outputShape.length;\n    let newCoords = \"\";\n    if (rank === 1) {\n      newCoords = \"coords * uniforms.strides + uniforms.begin\";\n    } else {\n      let outputAxis = 0;\n      newCoords = this.outputShape.map((_, i2) => {\n        outputAxis++;\n        return this.outputShape.length === 1 ? `coords * uniforms.strides[${i2}] + uniforms.begin[${i2}]` : `coords[${outputAxis - 1}] * uniforms.strides[${i2}] + uniforms.begin[${i2}]`;\n      }).join(\",\");\n    }\n    const userCode = `\n       ${getMainHeaderAndGlobalIndexString()}\n         if (index < uniforms.size) {\n           let coords = getCoordsFromIndex(index);\n           setOutputAtIndex(index, getX(${newCoords}));\n         }\n       }\n     `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/StridedSlice.js\nfunction stridedSlice5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask } = attrs;\n  const { finalShapeSparse, finalShape, isIdentity, sliceDim0, isSimpleSlice, begin: $begin, end: $end, strides: $strides } = slice_util_exports.sliceInfo(x.shape, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask);\n  let result;\n  if (isIdentity) {\n    result = reshape6({ inputs: { x }, backend: backend2, attrs: { shape: finalShape } });\n  } else if (sliceDim0 || isSimpleSlice) {\n    util_exports.assert(x.shape.length >= 1, () => `Input must have rank at least 1, got: ${x.shape.length}`);\n    const size = slice_util_exports.computeOutShape($begin, $end, $strides);\n    const sliced = slice5({ inputs: { x }, backend: backend2, attrs: { begin: $begin, size } });\n    result = reshape6({ inputs: { x: sliced }, backend: backend2, attrs: { shape: finalShape } });\n    backend2.disposeData(sliced.dataId);\n  } else {\n    const shouldExecuteOnCPU = backend2.shouldExecuteOnCPU([x]);\n    if (shouldExecuteOnCPU) {\n      const values = backend2.readSync(x.dataId);\n      const xBuf = buffer(x.shape, x.dtype, values);\n      const resultValues = stridedSliceImplCPU2(finalShapeSparse, xBuf, $strides, $begin);\n      result = backend2.makeTensorInfo(finalShape, x.dtype, resultValues.values);\n    } else {\n      const program = new StridedSliceProgram2(finalShapeSparse);\n      const uniformData = [{ type: \"int32\", data: $begin }, { type: \"int32\", data: $strides }];\n      const resultValues = backend2.runWebGPUProgram(program, [x], x.dtype, uniformData);\n      result = reshape6({ inputs: { x: resultValues }, backend: backend2, attrs: { shape: finalShape } });\n      backend2.disposeData(resultValues.dataId);\n    }\n  }\n  return result;\n}\nvar stridedSliceConfig4 = {\n  kernelName: StridedSlice,\n  backendName: \"webgpu\",\n  kernelFunc: stridedSlice5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/StringNGrams.js\nfunction stringNGrams5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { separator, nGramWidths, leftPad, rightPad: rightPad2, padWidth, preserveShortSequences } = attrs;\n  const { data, dataSplits } = inputs;\n  const $data = backend2.readSync(data.dataId);\n  const $dataSplits = backend2.readSync(dataSplits.dataId);\n  const [nGrams, nGramsSplits] = stringNGramsImplCPU2($data, $dataSplits, separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences);\n  return [\n    backend2.makeTensorInfo([nGrams.length], \"string\", nGrams),\n    backend2.makeTensorInfo(dataSplits.shape, \"int32\", nGramsSplits)\n  ];\n}\nvar stringNGramsConfig4 = {\n  kernelName: StringNGrams,\n  backendName: \"webgpu\",\n  kernelFunc: stringNGrams5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Tanh.js\nvar tanh5 = unaryKernelFunc3({ opType: UnaryOpType.TANH });\nvar tanhConfig4 = {\n  kernelName: Tanh,\n  backendName: \"webgpu\",\n  kernelFunc: tanh5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/top_k_webgpu.js\nvar SwapProgram2 = class {\n  constructor(shape) {\n    this.variableNames = [\"x\", \"indices\"];\n    this.workGroupSize = [256, 1, 1];\n    this.size = true;\n    this.outputShape = shape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.uniforms = `inputSize : i32, firstPass : i32, negativeInf : f32,\n        dir : i32, inc : i32,`;\n    this.shaderKey = \"swap\";\n  }\n  getUserCode() {\n    const userCode = `\n        ${getMainHeaderAndGlobalIndexString()}\n          if (index < uniforms.size) {\n            let outC = getCoordsFromIndex(index);\n            let batch = outC[0];\n            let elemIdx = outC[1];\n            // We compare elements pair-wise within a group of size 2 * inc.\n            // The comparing rule for each group alternates between ascending\n            // and descending. Within each group, we compare each pair at\n            // positions i and i+inc. To decide whether an element at position i\n            // is x0 or x1, we mod it by 2 * inc, if the result is smaller than\n            // inc, it is in the first half of the group, we denote it as x0,\n            // otherwise we denote it as x1.\n            // For example, as shown in the Bitonic top K paper referenced\n            // above, Figure5(a) shows that element[1] is in the second half of\n            // the group when group size is 2, but it is in the first half of\n            // the group when group size is 4.\n            let isFirstInPair = elemIdx % (2 * uniforms.inc) < uniforms.inc;\n            var i = 0;\n            if (isFirstInPair) {\n              i = elemIdx;\n            } else {\n              i = elemIdx - uniforms.inc;\n            }\n\n            var i0 = 0;\n            if (uniforms.firstPass == 1) {\n              i0 = i;\n            } else {\n              i0 = i32(getIndices(batch, i));\n            }\n\n            var i1 = 0;\n            if (uniforms.firstPass == 1) {\n              i1 = i + uniforms.inc;\n            } else {\n              i1 = i32(getIndices(batch, i + uniforms.inc));\n            }\n\n            var x0 = f32(0.0);\n            var x1 = f32(0.0);\n            if (i0 < uniforms.inputSize) {\n              x0 = getX(batch, i0);\n            } else {\n              x0 = uniforms.negativeInf;\n            }\n            if (i1 < uniforms.inputSize) {\n              x1 = getX(batch, i1);\n            } else {\n              x1 = uniforms.negativeInf;\n            }\n\n            let reverse = elemIdx % (2 * uniforms.dir) >= uniforms.dir;\n            let isGreater = x0 > x1 || (x0 == x1 && i1 > i0);\n            if (reverse == isGreater) {\n              // Elements in opposite order of direction\n              let iTemp = i0;\n              i0 = i1;\n              i1 = iTemp;\n            }\n            if (isFirstInPair) {\n              setOutputAtIndex(index, f32(i0));\n            } else {\n              setOutputAtIndex(index, f32(i1));\n            }\n          }\n        }\n      `;\n    return userCode;\n  }\n};\nvar MergeProgram2 = class {\n  constructor(shape) {\n    this.variableNames = [\"x\", \"indices\"];\n    this.workGroupSize = [256, 1, 1];\n    this.size = true;\n    this.outputShape = shape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.uniforms = `inputSize : i32, firstPass : i32, k : i32,`;\n    this.shaderKey = \"merge\";\n  }\n  getUserCode() {\n    const userCode = `\n        ${getMainHeaderAndGlobalIndexString()}\n          if (index < uniforms.size) {\n            let outC = getCoordsFromIndex(index);\n            let batch = outC[0];\n            let elemIdx = outC[1];\n            // The output size is half of the previous size.\n            // If the previous sequence is | | | | _ _ _ _  | | | |  _ _ _ _\n            // (k=4), we only need to output the indices at positions |, the\n            // indices at positions _ can be thrown away, see Figure5(b) After\n            // Phase 2 (Merge phase) in the Bitonic Top K paper referenced\n            // above.\n            // For example, the paper shows we only need to output the orange\n            // bars. The output sequence should look like this | | | | | | | |.\n            // Because the sequence is halved, to map the output index back to\n            // the previous sequence to find the corresponding value, we need\n            // to double the index. When we double the index, we basically\n            // interpolate a position, so 2i looks like\n            // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k\n            // position of each 2k positions by - elemIdx % k. E.g. for output\n            // at index 4,5,6,7, we want to get the corresponding element at\n            // original index 8,9,10,11, for output at index 8,9,10,11,\n            // we want to get the corresponding element at original index\n            // 16,17,18,19, so on and so forth.\n\n            var i = 0;\n            if (elemIdx < uniforms.k) {\n              i = elemIdx;\n            } else {\n              i = elemIdx * 2 - elemIdx % uniforms.k;\n            }\n            var i0 = 0;\n            if (uniforms.firstPass == 1) {\n              i0 = i;\n            } else {\n              i0 = i32(getIndices(batch, i));\n            }\n            var i1 = 0;\n            if (uniforms.firstPass == 1) {\n              i1 = i + uniforms.k;\n            } else {\n              i1 = i32(getIndices(batch, i + uniforms.k));\n            }\n\n            let x0 = getX(batch, i0);\n            var x1 = f32(0.0);\n            if (i1 < uniforms.inputSize) {\n              x1 = getX(batch, i1);\n            } else {\n              x1 = x0;\n            }\n\n            if (x0 >= x1) {\n              setOutputAtIndex(index, f32(i0));\n            } else {\n              setOutputAtIndex(index, f32(i1));\n            }\n          }\n        }\n      `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/TopK.js\nfunction disposeIntermediateTensorInfoOrNull2(backend2, tensorInfo) {\n  if (tensorInfo !== null) {\n    backend2.disposeData(tensorInfo.dataId);\n  }\n}\nfunction roundUpToPow22(num) {\n  let pow22 = 1;\n  while (pow22 < num) {\n    pow22 *= 2;\n  }\n  return pow22;\n}\nfunction topK3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { k, sorted } = attrs;\n  const xShape = x.shape;\n  const lastDim = xShape[xShape.length - 1];\n  if (backend2.shouldExecuteOnCPU([x])) {\n    const xVals = backend2.readSync(x.dataId);\n    const [allTopKVals, allTopKIndices] = topKImplCPU2(xVals, xShape, x.dtype, k, sorted);\n    return [\n      backend2.makeTensorInfo(allTopKVals.shape, allTopKVals.dtype, allTopKVals.values),\n      backend2.makeTensorInfo(allTopKIndices.shape, allTopKIndices.dtype, allTopKIndices.values)\n    ];\n  }\n  if (k === 0) {\n    xShape[xShape.length - 1] = 0;\n    return [\n      backend2.makeTensorInfo(xShape, x.dtype, []),\n      backend2.makeTensorInfo(xShape, \"int32\", [])\n    ];\n  }\n  if (lastDim === 1) {\n    return [\n      x,\n      fill5({ attrs: { shape: xShape, dtype: \"int32\", value: 0 }, backend: backend2 })\n    ];\n  }\n  const xSize = util_exports.sizeFromShape(xShape);\n  const batch = xSize / lastDim;\n  const x2D = reshape6({ inputs: { x }, attrs: { shape: [batch, lastDim] }, backend: backend2 });\n  const kPow2 = roundUpToPow22(k);\n  const lastDimPow2 = roundUpToPow22(lastDim);\n  let indices = null;\n  const getInputs = () => indices === null ? [x2D, x2D] : [x2D, indices];\n  const runSwap = (dir, inc, shape) => {\n    const inputs2 = getInputs();\n    const program = new SwapProgram2(shape);\n    const firstPass = indices === null ? 1 : 0;\n    const uniformDataSwap = [\n      { type: \"int32\", data: [lastDim] },\n      { type: \"int32\", data: [firstPass] },\n      { type: \"float32\", data: [Number.NEGATIVE_INFINITY] },\n      { type: \"int32\", data: [dir] },\n      { type: \"int32\", data: [inc] }\n    ];\n    const prevIndices2 = indices;\n    indices = backend2.runWebGPUProgram(program, inputs2, \"int32\", uniformDataSwap);\n    disposeIntermediateTensorInfoOrNull2(backend2, prevIndices2);\n  };\n  for (let len = 1; len < kPow2; len *= 2) {\n    const dir = len * 2;\n    for (let inc = len; inc >= 1; inc /= 2) {\n      runSwap(dir, inc, [batch, lastDimPow2]);\n    }\n  }\n  for (let indicesSize = lastDimPow2; indicesSize > kPow2; indicesSize /= 2) {\n    const inputs2 = getInputs();\n    const mergeProgram = new MergeProgram2([batch, indicesSize / 2]);\n    const firstPass = indices === null ? 1 : 0;\n    const uniformDataMerge = [\n      { type: \"int32\", data: [lastDim] },\n      { type: \"int32\", data: [firstPass] },\n      { type: \"int32\", data: [kPow2] }\n    ];\n    const prevIndices2 = indices;\n    indices = backend2.runWebGPUProgram(mergeProgram, inputs2, \"int32\", uniformDataMerge);\n    disposeIntermediateTensorInfoOrNull2(backend2, prevIndices2);\n    const len = kPow2 / 2;\n    const dir = len * 2;\n    for (let inc = len; inc >= 1; inc /= 2) {\n      runSwap(dir, inc, indices.shape);\n    }\n  }\n  let prevIndices = indices;\n  indices = slice5({ inputs: { x: indices }, backend: backend2, attrs: { begin: 0, size: [batch, k] } });\n  disposeIntermediateTensorInfoOrNull2(backend2, prevIndices);\n  let values = gatherV24({ inputs: { x: x2D, indices }, backend: backend2, attrs: { axis: 1, batchDims: 1 } });\n  disposeIntermediateTensorInfoOrNull2(backend2, x2D);\n  const newShape = xShape.slice(0, -1);\n  newShape.push(k);\n  prevIndices = indices;\n  indices = reshape6({ inputs: { x: indices }, attrs: { shape: newShape }, backend: backend2 });\n  disposeIntermediateTensorInfoOrNull2(backend2, prevIndices);\n  const prevValues = values;\n  values = reshape6({ inputs: { x: values }, attrs: { shape: newShape }, backend: backend2 });\n  disposeIntermediateTensorInfoOrNull2(backend2, prevValues);\n  return [values, indices];\n}\nvar topKConfig4 = {\n  kernelName: TopK,\n  backendName: \"webgpu\",\n  kernelFunc: topK3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/transform_webgpu.js\nvar TransformProgram2 = class {\n  constructor(outShape) {\n    this.variableNames = [\"Image\", \"Transforms\"];\n    this.uniforms = \"interpolationModeId : i32, fillModeId : i32, fillValue : f32,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = outShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = \"transform\";\n  }\n  getUserCode() {\n    const userCode = `\n          fn mapCoord(outCoord : f32, len : f32) -> f32{\n            var inCoord = outCoord;\n            if(uniforms.fillModeId == 2) {\n              if (inCoord < 0.0) {\n                if (len <= 1.0) {\n                  inCoord = 0.0;\n                } else {\n                  let sz2 = 2.0 * len;\n                  if (inCoord < sz2) {\n                    inCoord = sz2 * f32(i32(f32(-inCoord / sz2))) +\n                    inCoord;\n                  }\n                  if (inCoord < -len) {\n                    inCoord = inCoord + sz2;\n                  } else {\n                    inCoord = -inCoord - 1.0;\n                  }\n                }\n              } else if (inCoord > len - 1.0) {\n                if (len <= 1.0) {\n                  inCoord = 0.0;\n                } else {\n                  let sz2 = 2.0 * len;\n                  inCoord = inCoord - sz2 * f32(i32(f32(inCoord / sz2)));\n                  if (inCoord >= len) {\n                    inCoord = sz2 - inCoord - 1.0;\n                  }\n                }\n              }\n              return clamp(inCoord, 0.0, len - 1.0);\n            } else if (uniforms.fillModeId == 3) {\n              if (inCoord < 0.0) {\n                if (len <= 1.0) {\n                  inCoord = 0.0;\n                } else {\n                  let sz = len - 1.0;\n                  inCoord = inCoord + len * (f32(i32(f32(-inCoord / sz))) + 1.0);\n                }\n              } else if (inCoord > len - 1.0) {\n                if (len <= 1.0) {\n                  inCoord = 0.0;\n                } else {\n                  let sz = len - 1.0;\n                  inCoord = inCoord - len * f32(i32(f32(inCoord / sz)));\n                }\n              }\n              return clamp(inCoord, 0.0, len - 1.0);\n            } else if (uniforms.fillModeId == 4) {\n              return clamp(outCoord, 0.0, len - 1.0);\n            }\n            return outCoord;\n          }\n          fn readWithFillValue(batch : i32, coordY : i32, coordX : i32,\n            channel : i32) -> f32 {\n            var outputValue : f32;\n            if (0 <= coordY && coordY < uniforms.imageShape[1] && 0 <= coordX && coordX < uniforms.imageShape[2]) {\n                outputValue = getImage(batch, coordY, coordX, channel);\n            } else {\n              outputValue = uniforms.fillValue;\n            }\n            return outputValue;\n          }\n\n          ${getMainHeaderAndGlobalIndexString()}\n            if (index < uniforms.size) {\n              let coords = getCoordsFromIndex(index);\n              var outputValue : f32;\n              let batch = coords[0];\n              let x = coords[2];\n              let y = coords[1];\n              let channel = coords[3];\n              let xf = f32(x);\n              let yf = f32(y);\n              let a1 = getTransforms(batch, 0);\n              let a2 = getTransforms(batch, 1);\n              let a3 = getTransforms(batch, 2);\n              let b1 = getTransforms(batch, 3);\n              let b2 = getTransforms(batch, 4);\n              let b3 = getTransforms(batch, 5);\n              let c1 = getTransforms(batch, 6);\n              let c2 = getTransforms(batch, 7);\n              let projection = c1 * xf + c2 * yf + 1.0;\n              if (projection == 0.0) {\n                outputValue = uniforms.fillValue;\n              } else {\n                let inX = (a1 * xf + a2 * yf + a3) / projection;\n                let inY = (b1 * xf + b2 * yf + b3) / projection;\n                let mapX = mapCoord(inX, f32(uniforms.imageShape[2]));\n                let mapY = mapCoord(inY, f32(uniforms.imageShape[1]));\n\n                if (uniforms.interpolationModeId == 1) {\n                  let coordY = i32(round(mapY));\n                  let coordX = i32(round(mapX));\n                  outputValue = readWithFillValue(batch, coordY, coordX,\n                    channel);\n                } else {\n                  let yFloor = floor(mapY);\n                  let xFloor = floor(mapX);\n                  let yCeil = yFloor + 1.0;\n                  let xCeil = xFloor + 1.0;\n                  let valueYFloor = (xCeil - mapX) *\n                  readWithFillValue(batch, i32(yFloor), i32(xFloor), channel) +\n                  (mapX - xFloor) *\n                  readWithFillValue(batch, i32(yFloor), i32(xCeil), channel);\n                  let valueYCeil = (xCeil - mapX) *\n                  readWithFillValue(batch, i32(yCeil), i32(xFloor), channel) +\n                  (mapX - xFloor) *\n                  readWithFillValue(batch, i32(yCeil), i32(xCeil), channel);\n                  outputValue = (yCeil - mapY) * valueYFloor +\n                  (mapY - yFloor) * valueYCeil;\n                }\n              }\n              setOutputAtIndex(index, outputValue);\n            }\n          }\n        `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Transform.js\nfunction transform5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { image: image2, transforms } = inputs;\n  const { interpolation, fillMode, fillValue, outputShape } = attrs;\n  const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n  const [outHeight, outWidth] = outputShape != null ? outputShape : [imageHeight, imageWidth];\n  const outShape = [\n    batch,\n    outHeight,\n    outWidth,\n    numChannels\n  ];\n  const program = new TransformProgram2(outShape);\n  const interpolationModeId = interpolation === \"nearest\" ? 1 : 2;\n  let fillModeId;\n  switch (fillMode) {\n    case \"constant\":\n      fillModeId = 1;\n      break;\n    case \"reflect\":\n      fillModeId = 2;\n      break;\n    case \"wrap\":\n      fillModeId = 3;\n      break;\n    case \"nearest\":\n      fillModeId = 4;\n      break;\n    default:\n      fillModeId = 1;\n      break;\n  }\n  const uniformData = [\n    { type: \"int32\", data: [interpolationModeId] },\n    { type: \"int32\", data: [fillModeId] },\n    { type: \"float32\", data: [fillValue] }\n  ];\n  return backend2.runWebGPUProgram(program, [image2, transforms], \"float32\", uniformData);\n}\nvar transformConfig4 = {\n  kernelName: Transform,\n  backendName: \"webgpu\",\n  kernelFunc: transform5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Unpack.js\nfunction unpack4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { value } = inputs;\n  let { axis } = attrs;\n  if (axis < 0) {\n    axis += value.shape.length;\n  }\n  const x = value;\n  const xRank = x.shape.length;\n  const num = value.shape[axis];\n  const outShape = new Array(xRank - 1);\n  let outIndex = 0;\n  for (let i2 = 0; i2 < xRank; i2++) {\n    if (i2 !== axis) {\n      outShape[outIndex++] = x.shape[i2];\n    }\n  }\n  const toDispose = [];\n  const begin = new Array(xRank).fill(0);\n  const size = x.shape.slice();\n  size[axis] = 1;\n  const res = new Array(num);\n  for (let i2 = 0; i2 < res.length; i2++) {\n    begin[axis] = i2;\n    const sliced = slice5({ inputs: { x }, backend: backend2, attrs: { begin, size } });\n    const reshaped = reshape6({ inputs: { x: sliced }, backend: backend2, attrs: { shape: outShape } });\n    res[i2] = reshaped;\n    toDispose.push(sliced);\n  }\n  toDispose.forEach((t2) => backend2.disposeData(t2.dataId));\n  return res;\n}\nvar unpackConfig4 = {\n  kernelName: Unpack,\n  backendName: \"webgpu\",\n  kernelFunc: unpack4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/register_all_kernels.js\nvar kernelConfigs4 = [\n  _fusedMatMulConfig4,\n  absConfig4,\n  addConfig4,\n  addNConfig4,\n  argMaxConfig4,\n  argMinConfig3,\n  avgPoolConfig4,\n  batchMatMulConfig4,\n  batchToSpaceNDConfig4,\n  castConfig4,\n  ceilConfig4,\n  clipByValueConfig4,\n  complexConfig3,\n  concatConfig4,\n  conv2DConfig4,\n  conv2DBackpropInputConfig4,\n  cosConfig4,\n  coshConfig4,\n  cropAndResizeConfig4,\n  cumprodConfig4,\n  cumsumConfig4,\n  depthToSpaceConfig4,\n  depthwiseConv2dNativeConfig4,\n  einsumConfig3,\n  eluConfig4,\n  equalConfig4,\n  expConfig4,\n  expandDimsConfig4,\n  expm1Config3,\n  fillConfig4,\n  flipLeftRightConfig4,\n  fromPixelsConfig2,\n  floorConfig4,\n  floorDivConfig4,\n  fusedBatchNormConfig2,\n  fusedConv2DConfig4,\n  fusedDepthwiseConv2DConfig4,\n  gatherNdConfig4,\n  gatherV2Config4,\n  greaterConfig4,\n  greaterEqualConfig4,\n  identityConfig4,\n  imagConfig3,\n  leakyReluConfig4,\n  lessConfig4,\n  lessEqualConfig4,\n  logConfig4,\n  logicalAndConfig4,\n  logicalNotConfig4,\n  maxConfig4,\n  maximumConfig4,\n  maxPoolConfig4,\n  meanConfig4,\n  minConfig4,\n  minimumConfig4,\n  mirrorPadConfig4,\n  multiplyConfig4,\n  negConfig4,\n  nonMaxSuppressionV3Config4,\n  nonMaxSuppressionV5Config4,\n  notEqualConfig4,\n  onesLikeConfig4,\n  packConfig4,\n  padV2Config4,\n  powConfig4,\n  preluConfig4,\n  prodConfig4,\n  rangeConfig4,\n  realConfig3,\n  realDivConfig4,\n  reluConfig4,\n  relu6Config4,\n  reshapeConfig4,\n  resizeBilinearConfig4,\n  resizeNearestNeighborConfig4,\n  rotateWithOffsetConfig4,\n  rsqrtConfig4,\n  scatterNdConfig4,\n  selectConfig4,\n  sigmoidConfig4,\n  sinConfig4,\n  sinhConfig3,\n  sliceConfig4,\n  stridedSliceConfig4,\n  stringNGramsConfig4,\n  softmaxConfig4,\n  spaceToBatchNDConfig4,\n  sparseToDenseConfig3,\n  splitVConfig4,\n  sqrtConfig4,\n  squareConfig4,\n  squaredDifferenceConfig4,\n  subConfig4,\n  sumConfig4,\n  tanhConfig4,\n  tileConfig4,\n  topKConfig4,\n  transformConfig4,\n  transposeConfig4,\n  unpackConfig4,\n  zerosLikeConfig4\n];\nfor (const kernelConfig of kernelConfigs4) {\n  registerKernel(kernelConfig);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/buffer_manager.js\nvar BufferManager = class {\n  constructor(device) {\n    this.device = device;\n    this.numUsedBuffers = 0;\n    this.numFreeBuffers = 0;\n    this.freeBuffers = /* @__PURE__ */ new Map();\n    this.usedBuffers = /* @__PURE__ */ new Map();\n    this.numBytesUsed = 0;\n    this.numBytesAllocated = 0;\n  }\n  acquireUploadBuffer(size, usage) {\n    return this.acquireBuffer(size, usage, true);\n  }\n  acquireBuffer(size, usage, mappedAtCreation = false) {\n    const key = getBufferKey(size, usage);\n    if (!this.freeBuffers.has(key)) {\n      this.freeBuffers.set(key, []);\n    }\n    if (!this.usedBuffers.has(key)) {\n      this.usedBuffers.set(key, []);\n    }\n    this.numBytesUsed += size;\n    this.numUsedBuffers++;\n    if (this.freeBuffers.get(key).length > 0) {\n      this.numFreeBuffers--;\n      const newBuffer2 = this.freeBuffers.get(key).shift();\n      this.usedBuffers.get(key).push(newBuffer2);\n      return newBuffer2;\n    }\n    this.numBytesAllocated += size;\n    const newBuffer = this.device.createBuffer({ size, usage, mappedAtCreation });\n    this.usedBuffers.get(key).push(newBuffer);\n    return newBuffer;\n  }\n  releaseBuffer(buffer2, size, usage) {\n    if (this.freeBuffers.size === 0) {\n      return;\n    }\n    const key = getBufferKey(size, usage);\n    if (!this.freeBuffers.has(key)) {\n      this.freeBuffers.set(key, []);\n    }\n    this.freeBuffers.get(key).push(buffer2);\n    this.numFreeBuffers++;\n    this.numUsedBuffers--;\n    const bufferList = this.usedBuffers.get(key);\n    const bufferIndex = bufferList.indexOf(buffer2);\n    if (bufferIndex < 0) {\n      throw new Error(\"Cannot release a buffer that was never provided by this buffer manager\");\n    }\n    bufferList.splice(bufferIndex, 1);\n    this.numBytesUsed -= size;\n  }\n  releaseUploadBuffer(buffer2, size, usage) {\n    buffer2.mapAsync(GPUMapMode.WRITE).then(() => {\n      this.releaseBuffer(buffer2, size, usage);\n    }, (err) => {\n    });\n  }\n  getNumUsedBuffers() {\n    return this.numUsedBuffers;\n  }\n  getNumFreeBuffers() {\n    return this.numFreeBuffers;\n  }\n  dispose() {\n    this.freeBuffers.forEach((buffers, key) => {\n      buffers.forEach((buffer2) => {\n        buffer2.destroy();\n      });\n    });\n    this.usedBuffers.forEach((buffers, key) => {\n      buffers.forEach((buffer2) => {\n        buffer2.destroy();\n      });\n    });\n    this.freeBuffers = /* @__PURE__ */ new Map();\n    this.usedBuffers = /* @__PURE__ */ new Map();\n    this.numUsedBuffers = 0;\n    this.numFreeBuffers = 0;\n    this.numBytesUsed = 0;\n    this.numBytesAllocated = 0;\n  }\n};\nfunction getBufferKey(size, usage) {\n  return `${size}_${usage}`;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/texture_manager.js\nvar TextureManager2 = class {\n  constructor(device) {\n    this.device = device;\n    this.numUsedTextures = 0;\n    this.numFreeTextures = 0;\n    this.freeTextures = /* @__PURE__ */ new Map();\n    this.usedTextures = /* @__PURE__ */ new Map();\n    this.numBytesUsed = 0;\n    this.numBytesAllocated = 0;\n  }\n  acquireTexture(width, height, format, usage) {\n    const bytesPerElement2 = getBytesPerElement(format);\n    const byteSize = width * height * bytesPerElement2;\n    const key = getTextureKey(width, height, format, usage);\n    if (!this.freeTextures.has(key)) {\n      this.freeTextures.set(key, []);\n    }\n    if (!this.usedTextures.has(key)) {\n      this.usedTextures.set(key, []);\n    }\n    this.numBytesUsed += byteSize;\n    this.numUsedTextures++;\n    if (this.freeTextures.get(key).length > 0) {\n      this.numFreeTextures--;\n      const newTexture2 = this.freeTextures.get(key).shift();\n      this.usedTextures.get(key).push(newTexture2);\n      return newTexture2;\n    }\n    this.numBytesAllocated += byteSize;\n    const newTexture = this.device.createTexture({\n      size: [width, height],\n      format,\n      usage\n    });\n    this.usedTextures.get(key).push(newTexture);\n    return newTexture;\n  }\n  releaseTexture(texture, width, height, format, usage) {\n    if (this.freeTextures.size === 0) {\n      return;\n    }\n    const key = getTextureKey(width, height, format, usage);\n    if (!this.freeTextures.has(key)) {\n      this.freeTextures.set(key, []);\n    }\n    this.freeTextures.get(key).push(texture);\n    this.numFreeTextures++;\n    this.numUsedTextures--;\n    const textureList = this.usedTextures.get(key);\n    const textureIndex = textureList.indexOf(texture);\n    if (textureIndex < 0) {\n      throw new Error(\"Cannot release a texture that was never provided by this texture manager\");\n    }\n    textureList.splice(textureIndex, 1);\n    const bytesPerElement2 = getBytesPerElement(format);\n    const byteSize = width * height * bytesPerElement2;\n    this.numBytesUsed -= byteSize;\n  }\n  getNumUsedTextures() {\n    return this.numUsedTextures;\n  }\n  getNumFreeTextures() {\n    return this.numFreeTextures;\n  }\n  dispose() {\n    this.freeTextures.forEach((textures, key) => {\n      textures.forEach((texture) => {\n        texture.destroy();\n      });\n    });\n    this.usedTextures.forEach((textures, key) => {\n      textures.forEach((texture) => {\n        texture.destroy();\n      });\n    });\n    this.freeTextures = /* @__PURE__ */ new Map();\n    this.usedTextures = /* @__PURE__ */ new Map();\n    this.numUsedTextures = 0;\n    this.numFreeTextures = 0;\n    this.numBytesUsed = 0;\n    this.numBytesAllocated = 0;\n  }\n};\nfunction getTextureKey(width, height, format, usage) {\n  return `${width}_${height}_${format}_${usage}`;\n}\nfunction getBytesPerElement(format) {\n  if (format === \"rgba8unorm\") {\n    return 16;\n  } else {\n    throw new Error(`${format} is not supported!`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/backend_webgpu.js\nvar CPU_HANDOFF_SIZE_THRESHOLD2 = env().getNumber(\"WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD\");\nvar reshapeDispatch = (device, program) => {\n  const MAX_COMPUTE_PER_DIMENSION_DISPATCH_SIZE = device.limits.maxComputeWorkgroupsPerDimension;\n  const layout = program[\"dispatchLayout\"];\n  const dispatch = program[\"dispatch\"];\n  if (dispatch.every((d) => d <= MAX_COMPUTE_PER_DIMENSION_DISPATCH_SIZE)) {\n    return dispatch;\n  }\n  util_exports.assert(dispatch[0] > MAX_COMPUTE_PER_DIMENSION_DISPATCH_SIZE && layout.y === void 0 && layout.z === void 0, () => \"Dispatch size exceeds WebGPU limits in Y or Z dimension.\");\n  let dispatchAverage = Math.ceil(Math.sqrt(dispatch[0]));\n  if (dispatchAverage > MAX_COMPUTE_PER_DIMENSION_DISPATCH_SIZE) {\n    dispatchAverage = Math.ceil(Math.cbrt(dispatch[0]));\n    util_exports.assert(dispatchAverage <= MAX_COMPUTE_PER_DIMENSION_DISPATCH_SIZE, () => \"Total dispatch size exceeds WebGPU maximum.\");\n    return [dispatchAverage, dispatchAverage, dispatchAverage];\n  } else {\n    return [dispatchAverage, dispatchAverage, 1];\n  }\n};\nvar WebGPUBackend = class extends KernelBackend {\n  constructor(device, supportTimeQuery = false) {\n    super();\n    this.commandQueueOwnedIds = /* @__PURE__ */ new WeakSet();\n    this.dispatchNumberInEncoder = 0;\n    this.disposed = false;\n    this.downloadWaitMs = 0;\n    this.tensorDataPendingDisposal = [];\n    this.stagingPendingDisposal = [];\n    this.uniformPendingDisposal = [];\n    this.uploadWaitMs = 0;\n    if (!isWebGPUSupported()) {\n      throw new Error(\"WebGPU is not supported on this device\");\n    }\n    this.pipelineCache = {};\n    this.device = device;\n    this.queue = device.queue;\n    this.currentCommandEncoder = null;\n    this.currentComputePass = null;\n    this.supportTimeQuery = supportTimeQuery;\n    this.bufferManager = new BufferManager(this.device);\n    this.textureManager = new TextureManager2(this.device);\n    this.tensorMap = new DataStorage(this, engine());\n    if (this.supportTimeQuery) {\n      this.querySet = this.device.createQuerySet({\n        type: \"timestamp\",\n        count: 2\n      });\n    }\n    if (env().getBool(\"WEBGPU_USE_PROFILE_TOOL\")) {\n      this.dummyCanvas = document.createElement(\"canvas\");\n      this.dummyCanvas.width = 1;\n      this.dummyCanvas.height = 1;\n      this.dummyContext = this.dummyCanvas.getContext(\"webgpu\");\n      this.dummyContext.configure({\n        device,\n        format: \"bgra8unorm\"\n      });\n      document.body.appendChild(this.dummyCanvas);\n    }\n  }\n  nextDataId() {\n    return WebGPUBackend.nextDataId++;\n  }\n  floatPrecision() {\n    return 32;\n  }\n  defaultGpuBufferUsage() {\n    return GPUBufferUsage.STORAGE | GPUBufferUsage.COPY_SRC | GPUBufferUsage.COPY_DST;\n  }\n  disposeData(dataId, force = false) {\n    if (this.tensorDataPendingDisposal.indexOf(dataId) >= 0) {\n      return false;\n    }\n    if (!this.tensorMap.has(dataId)) {\n      return true;\n    }\n    const tensorData = this.tensorMap.get(dataId);\n    this.decRef(dataId);\n    if (!force && tensorData.refCount > 0) {\n      return false;\n    }\n    if (this.commandQueueOwnedIds.has(dataId)) {\n      this.tensorDataPendingDisposal.push(dataId);\n      return false;\n    }\n    const { complexTensorInfos } = this.tensorMap.get(dataId);\n    if (complexTensorInfos != null) {\n      this.disposeData(complexTensorInfos.real.dataId, force);\n      this.disposeData(complexTensorInfos.imag.dataId, force);\n    }\n    this.releaseResource(dataId);\n    this.tensorMap.delete(dataId);\n    return true;\n  }\n  memory() {\n    return {\n      numBytesInGPU: this.bufferManager.numBytesUsed,\n      numBytesAllocatedInGPU: this.bufferManager.numBytesAllocated,\n      unreliable: false\n    };\n  }\n  releaseResource(dataId) {\n    const tensorData = this.tensorMap.get(dataId);\n    if (!tensorData || !tensorData.resourceInfo) {\n      return;\n    }\n    if (\"texture\" in tensorData.resourceInfo) {\n      const textureInfo = tensorData.resourceInfo;\n      if (textureInfo.texture instanceof GPUTexture) {\n        this.textureManager.releaseTexture(textureInfo.texture, textureInfo.width, textureInfo.height, textureInfo.format, textureInfo.usage);\n      }\n      textureInfo.texture = null;\n    } else {\n      const bufferInfo = tensorData.resourceInfo;\n      this.bufferManager.releaseBuffer(bufferInfo.buffer, bufferInfo.size, bufferInfo.usage);\n      bufferInfo.buffer = null;\n    }\n    tensorData.resourceInfo = null;\n  }\n  refCount(dataId) {\n    if (this.tensorMap.has(dataId)) {\n      const tensorData = this.tensorMap.get(dataId);\n      return tensorData.refCount;\n    }\n    return 0;\n  }\n  incRef(dataId) {\n    const tensorData = this.tensorMap.get(dataId);\n    tensorData.refCount++;\n  }\n  decRef(dataId) {\n    if (this.tensorMap.has(dataId)) {\n      const tensorData = this.tensorMap.get(dataId);\n      tensorData.refCount--;\n    }\n  }\n  write(values, shape, dtype) {\n    if (dtype === \"complex64\" && values != null) {\n      throw new Error(`Cannot write to a complex64 dtype. Please use tf.complex(real, imag).`);\n    }\n    const dataId = { id: this.nextDataId() };\n    this.tensorMap.set(dataId, { dtype, shape, values, refCount: 1 });\n    return dataId;\n  }\n  move(dataId, values, shape, dtype, refCount) {\n    if (dtype === \"complex64\") {\n      throw new Error(`Cannot write to a complex64 dtype. Please use tf.complex(real, imag).`);\n    }\n    this.tensorMap.set(dataId, { dtype, shape, values, refCount });\n  }\n  submitQueue() {\n    this.ensureComputePassEnded();\n    this.queue.submit([this.currentCommandEncoder.finish()]);\n    this.currentCommandEncoder = null;\n    this.dispatchNumberInEncoder = 0;\n    this.commandQueueOwnedIds = /* @__PURE__ */ new WeakSet();\n    this.tensorDataPendingDisposal.forEach((d) => {\n      this.releaseResource(d);\n      this.tensorMap.delete(d);\n    });\n    this.uniformPendingDisposal.forEach((d) => this.bufferManager.releaseBuffer(d.buffer, d.size, d.usage));\n    this.stagingPendingDisposal.forEach((d) => this.bufferManager.releaseUploadBuffer(d.buffer, d.size, d.usage));\n    this.tensorDataPendingDisposal = [];\n    this.uniformPendingDisposal = [];\n    this.stagingPendingDisposal = [];\n  }\n  ensureCommandEncoderReady() {\n    if (!this.currentCommandEncoder) {\n      this.currentCommandEncoder = this.device.createCommandEncoder();\n    }\n  }\n  ensureComputePassEnded() {\n    if (this.currentComputePass) {\n      this.currentComputePass.end();\n      this.currentComputePass = null;\n    }\n  }\n  getComputePass() {\n    if (!this.currentComputePass) {\n      this.currentComputePass = this.currentCommandEncoder.beginComputePass();\n    }\n    return this.currentComputePass;\n  }\n  async getBufferData(buffer2, size) {\n    const staging = this.bufferManager.acquireBuffer(size, GPUBufferUsage.COPY_DST | GPUBufferUsage.MAP_READ);\n    this.ensureCommandEncoderReady();\n    this.ensureComputePassEnded();\n    this.currentCommandEncoder.copyBufferToBuffer(buffer2, 0, staging, 0, size);\n    this.submitQueue();\n    await staging.mapAsync(GPUMapMode.READ);\n    const values = staging.getMappedRange().slice(0);\n    staging.unmap();\n    if (staging != null) {\n      this.bufferManager.releaseBuffer(staging, size, GPUBufferUsage.COPY_DST | GPUBufferUsage.MAP_READ);\n    }\n    if (env().getBool(\"WEBGPU_USE_PROFILE_TOOL\")) {\n      util_exports.assert(this.dummyContext !== void 0, () => `Fail to get context for profiling tool`);\n      this.dummyContext.getCurrentTexture();\n    }\n    return values;\n  }\n  convertAndCacheOnCPU(dataId, data) {\n    const tensorData = this.tensorMap.get(dataId);\n    this.releaseResource(dataId);\n    tensorData.values = data;\n    return tensorData.values;\n  }\n  readSync(dataId) {\n    const tensorData = this.tensorMap.get(dataId);\n    const { values } = tensorData;\n    if (values == null) {\n      throw new Error(\"WebGPU readSync is only available for CPU-resident tensors.\");\n    }\n    return values;\n  }\n  async read(dataId) {\n    if (!this.tensorMap.has(dataId)) {\n      throw new Error(`Tensor ${dataId} was not registered!`);\n    }\n    const tensorData = this.tensorMap.get(dataId);\n    const { values } = tensorData;\n    if (values != null) {\n      return this.convertAndCacheOnCPU(dataId, values);\n    }\n    let vals;\n    if (tensorData.dtype === \"complex64\") {\n      const ps = await Promise.all([\n        this.read(tensorData.complexTensorInfos.real.dataId),\n        this.read(tensorData.complexTensorInfos.imag.dataId)\n      ]);\n      const realValues = ps[0];\n      const imagValues = ps[1];\n      vals = backend_util_exports.mergeRealAndImagArrays(realValues, imagValues);\n    } else {\n      const bufferInfo = tensorData.resourceInfo;\n      const data = await this.getBufferData(bufferInfo.buffer, bufferInfo.size);\n      vals = ArrayBufferToTypedArray(data, tensorData.dtype);\n    }\n    this.convertAndCacheOnCPU(dataId, vals);\n    return vals;\n  }\n  readToGPU(dataId) {\n    const srcTensorData = this.tensorMap.get(dataId);\n    const { values, dtype, shape, resourceInfo } = srcTensorData;\n    if (dtype === \"complex64\") {\n      throw new Error(\"Does not support reading buffer for complex64 dtype.\");\n    }\n    if (resourceInfo == null) {\n      if (values != null) {\n        throw new Error(\"Data is not on GPU but on CPU.\");\n      } else {\n        throw new Error(\"There is no data on GPU or CPU.\");\n      }\n    }\n    const size = resourceInfo.size;\n    const buffer2 = this.bufferManager.acquireBuffer(size, resourceInfo.usage);\n    this.ensureCommandEncoderReady();\n    this.ensureComputePassEnded();\n    this.currentCommandEncoder.copyBufferToBuffer(resourceInfo.buffer, 0, buffer2, 0, size);\n    this.submitQueue();\n    const tensorInfo = this.makeTensorInfo(shape, dtype);\n    const tensorRef = engine().makeTensorFromTensorInfo(tensorInfo);\n    const tensorData = this.tensorMap.get(tensorInfo.dataId);\n    tensorData.resourceInfo = { size, usage: this.defaultGpuBufferUsage(), buffer: buffer2 };\n    return { tensorRef, buffer: buffer2, bufSize: size };\n  }\n  bufferSync(t2) {\n    const data = this.readSync(t2.dataId);\n    if (t2.dtype === \"string\") {\n      try {\n        const strings = data.map((d) => util_exports.decodeString(d));\n        return buffer(t2.shape, t2.dtype, strings);\n      } catch (_a) {\n        throw new Error(\"Failed to decode encoded string bytes into utf-8\");\n      }\n    }\n    return buffer(t2.shape, t2.dtype, data);\n  }\n  async time(f) {\n    const oldActiveTimers = this.activeTimers;\n    const newActiveTimers = [];\n    let outerMostTime = false;\n    if (this.programTimersStack == null) {\n      this.programTimersStack = newActiveTimers;\n      outerMostTime = true;\n    } else {\n      this.activeTimers.push(newActiveTimers);\n    }\n    this.activeTimers = newActiveTimers;\n    f();\n    const flattenedActiveTimerQueries = util_exports.flatten(this.activeTimers.map((d) => d.query)).filter((d) => d != null);\n    const flattenedActiveTimerNames = util_exports.flatten(this.activeTimers.map((d) => d.name)).filter((d) => d != null);\n    this.activeTimers = oldActiveTimers;\n    if (outerMostTime) {\n      this.programTimersStack = null;\n    }\n    const res = {\n      uploadWaitMs: this.uploadWaitMs,\n      downloadWaitMs: this.downloadWaitMs,\n      kernelMs: null,\n      wallMs: null\n    };\n    const kernelMs = await Promise.all(flattenedActiveTimerQueries);\n    res[\"kernelMs\"] = util_exports.sum(kernelMs);\n    res[\"getExtraProfileInfo\"] = () => kernelMs.map((d, i2) => ({ name: flattenedActiveTimerNames[i2], ms: d })).map((d) => `${d.name}: ${d.ms}`).join(\", \");\n    this.uploadWaitMs = 0;\n    this.downloadWaitMs = 0;\n    return res;\n  }\n  makeTensorInfo(shape, dtype, values) {\n    if (dtype === \"string\" && values != null && values.length > 0 && util_exports.isString(values[0])) {\n      values = values.map((d) => util_exports.encodeString(d));\n    }\n    const dataId = this.write(values, shape, dtype);\n    return { dataId, shape, dtype };\n  }\n  tensorToBinding(tensor2) {\n    if (!tensor2) {\n      return null;\n    }\n    const tensorData = this.tensorMap.get(tensor2.dataId);\n    if (\"texture\" in tensorData.resourceInfo) {\n      const info = tensorData.resourceInfo;\n      if (info.texture instanceof GPUExternalTexture) {\n        return info.texture;\n      } else {\n        return info.texture.createView();\n      }\n    }\n    const bufferInfo = tensorData.resourceInfo;\n    return { offset: 0, size: bufferInfo.size, buffer: bufferInfo.buffer };\n  }\n  async getQueryTime(query) {\n    if (this.supportTimeQuery) {\n      return this.getTimeFromQuerySet(query);\n    } else {\n      return 0;\n    }\n  }\n  uploadToGPU(dataId) {\n    const tensorData = this.tensorMap.get(dataId);\n    if (tensorData.resourceInfo) {\n      return;\n    }\n    const size = GPUBytesPerElement(tensorData.dtype) * util_exports.sizeFromShape(tensorData.shape);\n    const buffer2 = this.bufferManager.acquireBuffer(size, this.defaultGpuBufferUsage());\n    tensorData.resourceInfo = { size, usage: this.defaultGpuBufferUsage(), buffer: buffer2 };\n    if (tensorData.values) {\n      const stagingBuffer = this.bufferManager.acquireUploadBuffer(size, GPUBufferUsage.MAP_WRITE | GPUBufferUsage.COPY_SRC);\n      const arrayBuffer = stagingBuffer.getMappedRange();\n      if (tensorData.dtype === \"int32\" || tensorData.dtype === \"bool\") {\n        new Int32Array(arrayBuffer).set(tensorData.values);\n      } else {\n        new Float32Array(arrayBuffer).set(tensorData.values);\n      }\n      stagingBuffer.unmap();\n      this.ensureCommandEncoderReady();\n      this.ensureComputePassEnded();\n      this.currentCommandEncoder.copyBufferToBuffer(stagingBuffer, 0, buffer2, 0, size);\n      const stagingInfo = {\n        size,\n        usage: GPUBufferUsage.MAP_WRITE | GPUBufferUsage.COPY_SRC,\n        buffer: stagingBuffer\n      };\n      this.stagingPendingDisposal.push(stagingInfo);\n    }\n  }\n  makeUniforms(programUniform) {\n    let currentOffset = 0;\n    let preLength = 0;\n    const offsets = [];\n    programUniform.forEach((d) => {\n      if (d.data.length === 0) {\n        d.data = [1];\n      }\n      let baseAlignment;\n      switch (d.data.length) {\n        case 1:\n          baseAlignment = 4;\n          break;\n        case 2:\n          baseAlignment = 8;\n          break;\n        case 3:\n          baseAlignment = 16;\n          break;\n        case 4:\n          baseAlignment = 16;\n          break;\n        case 5:\n          baseAlignment = 16;\n          break;\n        case 6:\n          baseAlignment = 16;\n          break;\n        default:\n          util_exports.assert(false, () => `Unsupported ${d.data.length}D shape`);\n      }\n      if (preLength === 5 || preLength === 6) {\n        baseAlignment = 16;\n      }\n      currentOffset = Math.ceil(currentOffset / baseAlignment) * baseAlignment;\n      preLength = d.data.length;\n      offsets.push(currentOffset);\n      currentOffset += d.data.length * 4;\n    });\n    const arrayBuffer = new ArrayBuffer(currentOffset);\n    programUniform.forEach((d, i2) => {\n      const offset = offsets[i2];\n      if (d.type === \"int32\") {\n        new Int32Array(arrayBuffer, offset, d.data.length).set(d.data);\n      } else if (d.type === \"uint32\") {\n        new Uint32Array(arrayBuffer, offset, d.data.length).set(d.data);\n      } else {\n        new Float32Array(arrayBuffer, offset, d.data.length).set(d.data);\n      }\n    });\n    const uniformBuffer = this.bufferManager.acquireBuffer(currentOffset, GPUBufferUsage.COPY_DST | GPUBufferUsage.UNIFORM);\n    this.queue.writeBuffer(uniformBuffer, 0, arrayBuffer, 0, currentOffset);\n    const uniformInfo = {\n      size: currentOffset,\n      usage: GPUBufferUsage.COPY_DST | GPUBufferUsage.UNIFORM,\n      buffer: uniformBuffer\n    };\n    this.uniformPendingDisposal.push(uniformInfo);\n    return { offset: 0, size: currentOffset, buffer: uniformBuffer };\n  }\n  runWebGPUProgram(program, inputs, outputDtype, programDefinedUniform, output) {\n    if (!output) {\n      output = this.makeTensorInfo(program.outputShape, outputDtype);\n    }\n    if (util_exports.sizeFromShape(output.shape) === 0) {\n      this.tensorMap.get(output.dataId).values = util_exports.getTypedArrayFromDType(output.dtype, 0);\n      return output;\n    }\n    this.uploadToGPU(output.dataId);\n    program.dispatch = reshapeDispatch(this.device, program);\n    let programUniform = [];\n    let bufferShapes = [];\n    if (!program.isFromPixels) {\n      programUniform.push({ type: \"float32\", data: [NaN] });\n      bufferShapes = inputs.concat(output).map((d) => d.shape);\n      const uniformsType = \"int32\";\n      bufferShapes.map((d) => {\n        programUniform.push({ type: uniformsType, data: d });\n      });\n      const strides = util_exports.computeStrides(output.shape);\n      programUniform.push({ type: uniformsType, data: strides });\n      if (program.size) {\n        const size = util_exports.sizeFromShape(program.outputShape);\n        programUniform.push({ type: uniformsType, data: [program.isVec4 ? size / 4 : size] });\n      }\n    }\n    const inputsData = inputs.map((input2, i2) => {\n      if (input2.dtype === \"complex64\") {\n        throw new Error(`GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.`);\n      }\n      this.uploadToGPU(input2.dataId);\n      return {\n        dtype: this.tensorMap.get(input2.dataId).dtype,\n        shape: input2.shape,\n        name: program.variableNames[i2]\n      };\n    });\n    const key = makeShaderKey2(program, bufferShapes, inputsData, output);\n    let pipeline;\n    if (key in this.pipelineCache) {\n      pipeline = this.pipelineCache[key];\n    } else {\n      pipeline = compileProgram2(this.device, program, inputsData, output);\n      this.pipelineCache[key] = pipeline;\n    }\n    if (programDefinedUniform) {\n      programUniform = [...programUniform, ...programDefinedUniform];\n    }\n    const bindings = [\n      this.tensorToBinding(output),\n      ...inputs.map((t2) => this.tensorToBinding(t2)),\n      this.makeUniforms(programUniform)\n    ];\n    const bindGroup = this.device.createBindGroup({\n      layout: pipeline.getBindGroupLayout(0),\n      entries: bindings.map((b, i2) => ({ binding: i2, resource: b }))\n    });\n    this.ensureCommandEncoderReady();\n    const pass = this.getComputePass();\n    const shouldTimeProgram = this.activeTimers != null;\n    if (shouldTimeProgram) {\n      if (this.supportTimeQuery) {\n        pass.writeTimestamp(this.querySet, 0);\n      }\n    }\n    pass.setPipeline(pipeline);\n    pass.setBindGroup(0, bindGroup);\n    pass.dispatchWorkgroups(program.dispatch[0], program.dispatch[1], program.dispatch[2]);\n    if (shouldTimeProgram) {\n      if (this.supportTimeQuery) {\n        pass.writeTimestamp(this.querySet, 1);\n      }\n    }\n    this.dispatchNumberInEncoder++;\n    inputs.forEach((input2) => {\n      this.commandQueueOwnedIds.add(input2.dataId);\n    });\n    this.commandQueueOwnedIds.add(output.dataId);\n    if (env().get(\"WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE\") <= this.dispatchNumberInEncoder) {\n      this.submitQueue();\n    }\n    if (shouldTimeProgram) {\n      this.activeTimers.push({\n        name: program.constructor.name,\n        query: this.getQueryTime(this.querySet)\n      });\n    }\n    return output;\n  }\n  async getTimeFromQuerySet(querySet) {\n    const queryBuffer = this.bufferManager.acquireBuffer(16, GPUBufferUsage.COPY_SRC | GPUBufferUsage.QUERY_RESOLVE);\n    const dst = this.bufferManager.acquireBuffer(16, GPUBufferUsage.MAP_READ | GPUBufferUsage.COPY_DST);\n    this.ensureCommandEncoderReady();\n    this.ensureComputePassEnded();\n    this.currentCommandEncoder.resolveQuerySet(querySet, 0, 2, queryBuffer, 0);\n    this.currentCommandEncoder.copyBufferToBuffer(queryBuffer, 0, dst, 0, 16);\n    this.submitQueue();\n    await dst.mapAsync(GPUMapMode.READ);\n    const arrayBuf = new BigUint64Array(dst.getMappedRange());\n    const timeElapsedNanos = Number(arrayBuf[1] - arrayBuf[0]);\n    dst.unmap();\n    this.bufferManager.releaseBuffer(dst, 16, GPUBufferUsage.MAP_READ | GPUBufferUsage.COPY_DST);\n    this.bufferManager.releaseBuffer(queryBuffer, 16, GPUBufferUsage.COPY_SRC | GPUBufferUsage.QUERY_RESOLVE);\n    return timeElapsedNanos / 1e6;\n  }\n  shouldExecuteOnCPU(inputs, sizeThreshold = CPU_HANDOFF_SIZE_THRESHOLD2) {\n    return env().getBool(\"WEBGPU_CPU_FORWARD\") && inputs.every((input2) => this.tensorMap.get(input2.dataId).resourceInfo == null && util_exports.sizeFromShape(input2.shape) < sizeThreshold);\n  }\n  numDataIds() {\n    return this.tensorMap.numDataIds() - this.tensorDataPendingDisposal.length;\n  }\n  dispose() {\n    if (this.disposed) {\n      return;\n    }\n    this.bufferManager.dispose();\n    this.textureManager.dispose();\n    this.disposed = true;\n  }\n};\nWebGPUBackend.nextDataId = 0;\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/webgpu.js\nvar webgpu_exports = {};\n__export(webgpu_exports, {\n  WebGPUBackend: () => WebGPUBackend,\n  webgpu_util: () => webgpu_util_exports\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/index.js\nif (isWebGPUSupported()) {\n  registerBackend(\"webgpu\", async () => {\n    env().set(\"CHECK_COMPUTATION_FOR_ERRORS\", false);\n    const gpuDescriptor = {\n      powerPreference: env().get(\"WEBGPU_USE_LOW_POWER_GPU\") ? \"low-power\" : \"high-performance\"\n    };\n    const adapter = await navigator.gpu.requestAdapter(gpuDescriptor);\n    const adapterLimits = adapter.limits;\n    const deviceDescriptor = {};\n    const supportTimeQuery = adapter.features.has(\"timestamp-query\");\n    deviceDescriptor.requiredLimits = {\n      \"maxComputeWorkgroupStorageSize\": adapterLimits.maxComputeWorkgroupStorageSize,\n      \"maxComputeWorkgroupsPerDimension\": adapterLimits.maxComputeWorkgroupsPerDimension,\n      \"maxStorageBufferBindingSize\": adapterLimits.maxStorageBufferBindingSize\n    };\n    if (supportTimeQuery) {\n      deviceDescriptor.requiredFeatures = [\"timestamp-query\"];\n    } else {\n      console.warn(`This device doesn't support timestamp-query extension. Start Chrome browser with flag --disable-dawn-features=disallow_unsafe_apis then try again. Or zero will shown for the kernel time when profiling mode isenabled. Using performance.now is not workable for webgpu sinceit doesn't support synchronously to read data from GPU.`);\n    }\n    const device = await adapter.requestDevice(deviceDescriptor);\n    return new WebGPUBackend(device, supportTimeQuery);\n  }, 3);\n}\n\n// dist/tfjs.version.js\nvar e = \"3.19.0\";\nvar s = \"3.19.0\";\nvar t = \"3.19.0\";\nvar i = \"3.19.0\";\nvar n = \"3.19.0\";\nvar r = \"3.19.0\";\nvar l = \"3.19.0\";\nvar V = { tfjs: e, \"tfjs-core\": s, \"tfjs-data\": t, \"tfjs-layers\": i, \"tfjs-converter\": n, \"tfjs-backend-webgl\": r, \"tfjs-backend-wasm\": l };\nexport {\n  Abs,\n  Acos,\n  Acosh,\n  AdadeltaOptimizer,\n  AdagradOptimizer,\n  AdamOptimizer,\n  AdamaxOptimizer,\n  Add,\n  AddN,\n  All,\n  Any,\n  ArgMax,\n  ArgMin,\n  Asin,\n  Asinh,\n  Atan,\n  Atan2,\n  Atanh,\n  AvgPool,\n  AvgPool3D,\n  AvgPool3DGrad,\n  AvgPoolGrad,\n  BackendWasm,\n  BatchMatMul,\n  BatchToSpaceND,\n  Bincount,\n  BroadcastArgs,\n  BroadcastTo,\n  Callback,\n  CallbackList,\n  Cast,\n  Ceil,\n  ClipByValue,\n  Complex,\n  ComplexAbs,\n  Concat,\n  Conv2D,\n  Conv2DBackpropFilter,\n  Conv2DBackpropInput,\n  Conv3D,\n  Conv3DBackpropFilterV2,\n  Conv3DBackpropInputV2,\n  Cos,\n  Cosh,\n  CropAndResize,\n  Cumprod,\n  Cumsum,\n  CustomCallback,\n  DataStorage,\n  DenseBincount,\n  DepthToSpace,\n  DepthwiseConv2dNative,\n  DepthwiseConv2dNativeBackpropFilter,\n  DepthwiseConv2dNativeBackpropInput,\n  Diag,\n  Dilation2D,\n  Dilation2DBackpropFilter,\n  Dilation2DBackpropInput,\n  ENV,\n  EarlyStopping,\n  Einsum,\n  Elu,\n  EluGrad,\n  Environment,\n  Equal,\n  Erf,\n  Exp,\n  ExpandDims,\n  Expm1,\n  FFT,\n  Fill,\n  FlipLeftRight,\n  Floor,\n  FloorDiv,\n  FromPixels,\n  FusedBatchNorm,\n  FusedConv2D,\n  FusedDepthwiseConv2D,\n  GPGPUContext,\n  GatherNd,\n  GatherV2,\n  GraphModel,\n  Greater,\n  GreaterEqual,\n  History,\n  IFFT,\n  Identity,\n  Imag,\n  InputSpec,\n  IsFinite,\n  IsInf,\n  IsNan,\n  KernelBackend,\n  LRN,\n  LRNGrad,\n  LayerVariable,\n  LayersModel,\n  LeakyRelu,\n  Less,\n  LessEqual,\n  LinSpace,\n  Log,\n  Log1p,\n  LogSoftmax,\n  LogicalAnd,\n  LogicalNot,\n  LogicalOr,\n  LogicalXor,\n  LowerBound,\n  MathBackendWebGL,\n  Max,\n  MaxPool,\n  MaxPool3D,\n  MaxPool3DGrad,\n  MaxPoolGrad,\n  MaxPoolWithArgmax,\n  Maximum,\n  Mean,\n  Min,\n  Minimum,\n  MirrorPad,\n  Mod,\n  MomentumOptimizer,\n  Multinomial,\n  Multiply,\n  Neg,\n  NonMaxSuppressionV3,\n  NonMaxSuppressionV4,\n  NonMaxSuppressionV5,\n  NotEqual,\n  OP_SCOPE_SUFFIX,\n  OneHot,\n  OnesLike,\n  Optimizer,\n  OptimizerConstructors,\n  Pack,\n  PadV2,\n  Pool,\n  Pow,\n  Prelu,\n  Prod,\n  RMSPropOptimizer,\n  RNN,\n  Range,\n  Rank,\n  Real,\n  RealDiv,\n  Reciprocal,\n  Reduction,\n  Relu,\n  Relu6,\n  Reshape,\n  ResizeBilinear,\n  ResizeBilinearGrad,\n  ResizeNearestNeighbor,\n  ResizeNearestNeighborGrad,\n  Reverse,\n  RotateWithOffset,\n  Round,\n  Rsqrt,\n  SGDOptimizer,\n  ScatterNd,\n  SearchSorted,\n  Select,\n  Selu,\n  Sequential,\n  Sigmoid,\n  Sign,\n  Sin,\n  Sinh,\n  Slice,\n  Softmax,\n  Softplus,\n  SpaceToBatchND,\n  SparseFillEmptyRows,\n  SparseReshape,\n  SparseSegmentMean,\n  SparseSegmentSum,\n  SparseToDense,\n  SplitV,\n  Sqrt,\n  Square,\n  SquaredDifference,\n  Step,\n  StridedSlice,\n  StringNGrams,\n  StringSplit,\n  StringToHashBucketFast,\n  Sub,\n  Sum,\n  SymbolicTensor,\n  Tan,\n  Tanh,\n  Tensor,\n  TensorBuffer,\n  Tile,\n  TopK,\n  Transform,\n  Transpose,\n  Unique,\n  Unpack,\n  UnsortedSegmentSum,\n  UpperBound,\n  Variable,\n  ZerosLike,\n  _FusedMatMul,\n  abs,\n  acos,\n  acosh,\n  add2 as add,\n  addN,\n  all,\n  any,\n  argMax,\n  argMin,\n  asin,\n  asinh,\n  atan,\n  atan2,\n  atanh,\n  avgPool,\n  avgPool3d,\n  backend,\n  backend_util_exports as backend_util,\n  basicLSTMCell,\n  batchNorm,\n  batchNorm2d,\n  batchNorm3d,\n  batchNorm4d,\n  batchToSpaceND,\n  bincount,\n  booleanMaskAsync,\n  broadcastArgs,\n  broadcastTo,\n  broadcast_util_exports as broadcast_util,\n  browser_exports as browser,\n  buffer,\n  callbacks,\n  cast,\n  ceil,\n  clipByValue,\n  clone,\n  complex,\n  concat,\n  concat1d,\n  concat2d,\n  concat3d,\n  concat4d,\n  exports_constraints_exports as constraints,\n  conv1d,\n  conv2d,\n  conv2dTranspose,\n  conv3d,\n  conv3dTranspose,\n  copyRegisteredKernels,\n  cos,\n  cosh,\n  cosineWindow,\n  cumprod,\n  cumsum,\n  customGrad,\n  dist_exports2 as data,\n  denseBincount,\n  deprecationWarn,\n  depthToSpace,\n  depthwiseConv2d,\n  deregisterOp,\n  device_util_exports as device_util,\n  diag,\n  dilation2d,\n  disableDeprecationWarnings,\n  dispose,\n  disposeVariables,\n  div,\n  divNoNan,\n  dot,\n  dropout,\n  einsum,\n  elu,\n  enableDebugMode,\n  enableProdMode,\n  enclosingPowerOfTwo,\n  engine,\n  env,\n  equal,\n  erf,\n  euclideanNorm,\n  exp,\n  expandDims,\n  expm1,\n  eye,\n  fft,\n  fill,\n  findBackend,\n  findBackendFactory,\n  floor,\n  floorDiv,\n  forceHalfFloat,\n  fused_ops_exports as fused,\n  gather,\n  gatherND,\n  gather_nd_util_exports as gather_util,\n  getBackend,\n  getGradient,\n  getKernel,\n  getKernelsForBackend,\n  getThreadsCount,\n  gpgpu_util_exports as gpgpu_util,\n  grad,\n  grads,\n  greater,\n  greaterEqual,\n  ifft,\n  imag,\n  image,\n  inTopKAsync,\n  exports_initializers_exports as initializers,\n  input,\n  io_exports as io,\n  irfft,\n  isFinite2 as isFinite,\n  isInf,\n  isNaN2 as isNaN,\n  keep,\n  kernel_impls_exports as kernel_impls,\n  exports_layers_exports as layers,\n  leakyRelu,\n  less,\n  lessEqual,\n  linalg,\n  linspace,\n  loadGraphModel,\n  loadGraphModelSync,\n  loadLayersModel,\n  localResponseNormalization,\n  log2 as log,\n  log1p,\n  logSigmoid,\n  logSoftmax,\n  logSumExp,\n  logicalAnd,\n  logicalNot,\n  logicalOr,\n  logicalXor,\n  losses,\n  lowerBound,\n  matMul,\n  math_exports as math,\n  max,\n  maxPool,\n  maxPool3d,\n  maxPoolWithArgmax,\n  maximum,\n  mean,\n  memory,\n  meshgrid,\n  exports_metrics_exports as metrics,\n  min,\n  minimum,\n  mirrorPad,\n  mod,\n  model,\n  exports_models_exports as models,\n  moments,\n  movingAverage,\n  mul,\n  multiRNNCell,\n  multinomial,\n  neg,\n  nextFrame,\n  norm,\n  notEqual,\n  oneHot,\n  ones2 as ones,\n  onesLike,\n  op,\n  outerProduct,\n  pad,\n  pad1d,\n  pad2d,\n  pad3d,\n  pad4d,\n  pool,\n  pow,\n  prelu,\n  print,\n  prod,\n  profile,\n  rand,\n  randomGamma,\n  randomNormal,\n  randomStandardNormal,\n  randomUniform,\n  range,\n  ready,\n  real,\n  reciprocal,\n  registerBackend,\n  registerCallbackConstructor,\n  registerGradient,\n  registerKernel,\n  registerOp,\n  exports_regularizers_exports as regularizers,\n  relu,\n  relu6,\n  removeBackend,\n  reshape,\n  reverse,\n  reverse1d,\n  reverse2d,\n  reverse3d,\n  reverse4d,\n  rfft,\n  round2 as round,\n  rsqrt,\n  scalar,\n  scatterND,\n  scatter_nd_util_exports as scatter_util,\n  searchSorted,\n  selu,\n  separableConv2d,\n  sequential,\n  serialization_exports as serialization,\n  setBackend,\n  setPlatform,\n  setThreadsCount,\n  setWasmPath,\n  setWasmPaths,\n  setWebGLContext,\n  setdiff1dAsync,\n  sigmoid,\n  sign,\n  signal,\n  sin,\n  sinh,\n  slice,\n  slice1d,\n  slice2d,\n  slice3d,\n  slice4d,\n  slice_util_exports as slice_util,\n  softmax,\n  softplus,\n  spaceToBatchND,\n  sparse,\n  sparseToDense,\n  spectral,\n  split,\n  sqrt,\n  square,\n  squaredDifference,\n  squeeze,\n  stack,\n  step,\n  stridedSlice,\n  string,\n  sub,\n  sum2 as sum,\n  sumOutType,\n  tan,\n  tanh2 as tanh,\n  tensor,\n  tensor1d,\n  tensor2d,\n  tensor3d,\n  tensor4d,\n  tensor5d,\n  tensor6d,\n  tensor_util_exports as tensor_util,\n  test_util_exports as test_util,\n  tidy,\n  tile,\n  time,\n  topk,\n  train,\n  transpose,\n  truncatedNormal,\n  unique,\n  unregisterGradient,\n  unregisterKernel,\n  unsortedSegmentSum,\n  unstack,\n  upcastType,\n  upperBound,\n  util_exports as util,\n  valueAndGrad,\n  valueAndGrads,\n  variable,\n  variableGrads,\n  V as version,\n  version3 as version_converter,\n  version as version_core,\n  version2 as version_layers,\n  version8 as version_wasm,\n  version6 as version_webgl,\n  webgl,\n  webgl_util_exports as webgl_util,\n  webgpu_exports as webgpu,\n  where,\n  whereAsync,\n  zeros,\n  zerosLike\n};\n", "export const vertexIdentity = `\n  precision highp float;\n  attribute vec2 pos;\n  attribute vec2 uv;\n  varying vec2 vUv;\n  uniform float flipY;\n  void main(void) {\n    vUv = uv;\n    gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);\n  }\n`;\n\nexport const fragmentIdentity = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  void main(void) {\n    gl_FragColor = texture2D(texture, vUv);\n  }\n`;\n\nexport const colorMatrixWithAlpha = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform float m[20];\n  void main(void) {\n    vec4 c = texture2D(texture, vUv);\n    gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];\n    gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];\n    gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];\n    gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];\n  }\n`;\n\nexport const colorMatrixWithoutAlpha = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform float m[20];\n  void main(void) {\n    vec4 c = texture2D(texture, vUv);\n    gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];\n    gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];\n    gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];\n    gl_FragColor.a = c.a;\n  }\n`;\n\nexport const pixelate = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform vec2 size;\n  uniform sampler2D texture;\n  vec2 pixelate(vec2 coord, vec2 size) {\n    return floor( coord / size ) * size;\n  }\n  void main(void) {\n    gl_FragColor = vec4(0.0);\n    vec2 coord = pixelate(vUv, size);\n    gl_FragColor += texture2D(texture, coord);\n  }\n`;\n\nexport const blur = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform vec2 px;\n  void main(void) {\n    gl_FragColor = vec4(0.0);\n    gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;\n    gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;\n    gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;\n    gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;\n    gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;\n    gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;\n    gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;\n    gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;\n    gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;\n    gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;\n    gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;\n    gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;\n    gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;\n    gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;\n    gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;\n  }\n`;\n\nexport const convolution = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform vec2 px;\n  uniform float m[9];\n  void main(void) {\n    vec4 c11 = texture2D(texture, vUv - px); // top left\n    vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y)); // top center\n    vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y)); // top right\n    vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) ); // mid left\n    vec4 c22 = texture2D(texture, vUv); // mid center\n    vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) ); // mid right\n    vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) ); // bottom left\n    vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) ); // bottom center\n    vec4 c33 = texture2D(texture, vUv + px ); // bottom right\n    gl_FragColor = \n    c11 * m[0] + c12 * m[1] + c22 * m[2] +\n    c21 * m[3] + c22 * m[4] + c23 * m[5] +\n    c31 * m[6] + c32 * m[7] + c33 * m[8];\n    gl_FragColor.a = c22.a;\n  }\n`;\n", "/**\n * Image Filters in WebGL algoritm implementation\n * Based on: [WebGLImageFilter](https://github.com/phoboslab/WebGLImageFilter)\n */\n\nimport * as shaders from './imagefxshaders';\nimport { canvas } from './image';\nimport { log } from '../util/util';\n\nconst collect = (source, prefix, collection) => {\n  const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n  source.replace(r, (match, name) => {\n    collection[name] = 0;\n    return match;\n  });\n};\n\nclass GLProgram {\n  uniform = {};\n  attribute = {};\n  gl: WebGLRenderingContext;\n  id: WebGLProgram;\n\n  constructor(gl, vertexSource, fragmentSource) {\n    this.gl = gl;\n    const vertexShader = this.compile(vertexSource, this.gl.VERTEX_SHADER);\n    const fragmentShader = this.compile(fragmentSource, this.gl.FRAGMENT_SHADER);\n    this.id = this.gl.createProgram() as WebGLProgram;\n    if (!vertexShader || !fragmentShader) return;\n    if (!this.id) {\n      log('filter: could not create webgl program');\n      return;\n    }\n    this.gl.attachShader(this.id, vertexShader);\n    this.gl.attachShader(this.id, fragmentShader);\n    this.gl.linkProgram(this.id);\n    if (!this.gl.getProgramParameter(this.id, this.gl.LINK_STATUS)) {\n      log(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);\n      return;\n    }\n    this.gl.useProgram(this.id);\n    collect(vertexSource, 'attribute', this.attribute); // Collect attributes\n    for (const a in this.attribute) this.attribute[a] = this.gl.getAttribLocation(this.id, a);\n    collect(vertexSource, 'uniform', this.uniform); // Collect uniforms\n    collect(fragmentSource, 'uniform', this.uniform);\n    for (const u in this.uniform) this.uniform[u] = this.gl.getUniformLocation(this.id, u);\n  }\n\n  compile = (source, type): WebGLShader | null => {\n    const shader = this.gl.createShader(type) as WebGLShader;\n    if (!shader) {\n      log('filter: could not create shader');\n      return null;\n    }\n    this.gl.shaderSource(shader, source);\n    this.gl.compileShader(shader);\n    if (!this.gl.getShaderParameter(shader, this.gl.COMPILE_STATUS)) {\n      log(`filter: gl compile failed: ${this.gl.getShaderInfoLog(shader)}`);\n      return null;\n    }\n    return shader;\n  };\n}\n\n// function that is instantiated as class so it has private this members\n/**\n * @class GLImageFilter\n * @property {function} reset reset current filter chain\n * @property {function} add add specified filter to filter chain\n * @property {function} apply execute filter chain and draw result\n * @property {function} draw just draw input to result\n */\n\nexport function GLImageFilter() {\n  let drawCount = 0;\n  let sourceTexture: WebGLTexture | null = null;\n  let lastInChain = false;\n  let currentFramebufferIndex = -1;\n  let tempFramebuffers: [null, null] | [{ fbo: WebGLFramebuffer | null, texture: WebGLTexture | null }] = [null, null];\n  let filterChain: Record<string, unknown>[] = [];\n  let vertexBuffer: WebGLBuffer | null = null;\n  let currentProgram: GLProgram | null = null;\n  const fxcanvas = canvas(100, 100);\n  const shaderProgramCache = { }; // key is the shader program source, value is the compiled program\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = fxcanvas.getContext('webgl') as WebGLRenderingContext;\n  if (!gl) {\n    log('filter: cannot get webgl context');\n    return;\n  }\n  // @ts-ignore used for sanity checks outside of imagefx\n  this.gl = gl;\n\n  function resize(width, height) {\n    if (width === fxcanvas.width && height === fxcanvas.height) return; // Same width/height? Nothing to do here\n    fxcanvas.width = width;\n    fxcanvas.height = height;\n    if (!vertexBuffer) { // Create the context if we don't have it yet\n      const vertices = new Float32Array([-1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0]); // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      vertexBuffer = gl.createBuffer();\n      gl.bindBuffer(gl.ARRAY_BUFFER, vertexBuffer);\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, fxcanvas.width, fxcanvas.height);\n    tempFramebuffers = [null, null]; // Delete old temp framebuffers\n  }\n\n  function createFramebufferTexture(width, height) {\n    const fbo = gl.createFramebuffer() as WebGLFramebuffer;\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture() as WebGLTexture;\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  }\n\n  function getTempFramebuffer(index): { fbo: WebGLFramebuffer | null, texture: WebGLTexture | null } {\n    tempFramebuffers[index] = tempFramebuffers[index] || createFramebufferTexture(fxcanvas.width, fxcanvas.height);\n    return tempFramebuffers[index] as { fbo: WebGLFramebuffer, texture: WebGLTexture };\n  }\n\n  function draw(flags = 0) {\n    if (!currentProgram) return;\n    let source: WebGLTexture | null = null;\n    let target: WebGLFramebuffer | null = null;\n    let flipY = false;\n    if (drawCount === 0) source = sourceTexture; // First draw call - use the source texture\n    else source = getTempFramebuffer(currentFramebufferIndex).texture || null; // All following draw calls use the temp buffer last drawn to\n    drawCount++;\n    if (lastInChain && !(flags & DRAW.INTERMEDIATE)) { // Last filter in our chain - draw directly to the WebGL Canvas. We may also have to flip the image vertically now\n      target = null;\n      flipY = drawCount % 2 === 0;\n    } else {\n      currentFramebufferIndex = (currentFramebufferIndex + 1) % 2;\n      target = getTempFramebuffer(currentFramebufferIndex).fbo || null; // Intermediate draw call - get a temp buffer to draw to\n    }\n    gl.bindTexture(gl.TEXTURE_2D, source); // Bind the source and target and draw the two triangles\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(currentProgram.uniform['flipY'], (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  }\n\n  function compileShader(fragmentSource): GLProgram | null {\n    if (shaderProgramCache[fragmentSource]) {\n      currentProgram = shaderProgramCache[fragmentSource];\n      gl.useProgram((currentProgram ? currentProgram.id : null) || null);\n      return currentProgram as GLProgram;\n    }\n    currentProgram = new GLProgram(gl, shaders.vertexIdentity, fragmentSource);\n    if (!currentProgram) {\n      log('filter: could not get webgl program');\n      return null;\n    }\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(currentProgram.attribute['pos']);\n    gl.vertexAttribPointer(currentProgram.attribute['pos'], 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(currentProgram.attribute['uv']);\n    gl.vertexAttribPointer(currentProgram.attribute['uv'], 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    shaderProgramCache[fragmentSource] = currentProgram;\n    return currentProgram as GLProgram;\n  }\n\n  const filter = {\n    colorMatrix: (matrix) => { // general color matrix filter\n      const m = new Float32Array(matrix);\n      m[4] /= 255;\n      m[9] /= 255;\n      m[14] /= 255;\n      m[19] /= 255;\n      const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0) // Can we ignore the alpha value? Makes things a bit faster.\n        ? shaders.colorMatrixWithoutAlpha\n        : shaders.colorMatrixWithAlpha;\n      const program = compileShader(shader);\n      if (!program) return;\n      gl.uniform1fv(program.uniform['m'], m);\n      draw();\n    },\n\n    brightness: (brightness) => {\n      const b = (brightness || 0) + 1;\n      filter.colorMatrix([\n        b, 0, 0, 0, 0,\n        0, b, 0, 0, 0,\n        0, 0, b, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    saturation: (amount) => {\n      const x = (amount || 0) * 2 / 3 + 1;\n      const y = ((x - 1) * -0.5);\n      filter.colorMatrix([\n        x, y, y, 0, 0,\n        y, x, y, 0, 0,\n        y, y, x, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    desaturate: () => {\n      filter.saturation(-1);\n    },\n\n    contrast: (amount) => {\n      const v = (amount || 0) + 1;\n      const o = -128 * (v - 1);\n      filter.colorMatrix([\n        v, 0, 0, 0, o,\n        0, v, 0, 0, o,\n        0, 0, v, 0, o,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    negative: () => {\n      filter.contrast(-2);\n    },\n\n    hue: (rotation) => {\n      rotation = (rotation || 0) / 180 * Math.PI;\n      const cos = Math.cos(rotation);\n      const sin = Math.sin(rotation);\n      const lumR = 0.213;\n      const lumG = 0.715;\n      const lumB = 0.072;\n      filter.colorMatrix([\n        lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n        lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n        lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    desaturateLuminance: () => {\n      filter.colorMatrix([\n        0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n        0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n        0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    sepia: () => {\n      filter.colorMatrix([\n        0.393, 0.7689999, 0.18899999, 0, 0,\n        0.349, 0.6859999, 0.16799999, 0, 0,\n        0.272, 0.5339999, 0.13099999, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    brownie: () => {\n      filter.colorMatrix([\n        0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n        -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n        0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    vintagePinhole: () => {\n      filter.colorMatrix([\n        0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n        0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n        0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    kodachrome: () => {\n      filter.colorMatrix([\n        1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n        -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n        -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    technicolor: () => {\n      filter.colorMatrix([\n        1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n        -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n        -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    polaroid: () => {\n      filter.colorMatrix([\n        1.438, -0.062, -0.062, 0, 0,\n        -0.122, 1.378, -0.122, 0, 0,\n        -0.016, -0.016, 1.483, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    shiftToBGR: () => {\n      filter.colorMatrix([\n        0, 0, 1, 0, 0,\n        0, 1, 0, 0, 0,\n        1, 0, 0, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    convolution: (matrix) => { // general convolution Filter\n      const m = new Float32Array(matrix);\n      const pixelSizeX = 1 / fxcanvas.width;\n      const pixelSizeY = 1 / fxcanvas.height;\n      const program = compileShader(shaders.convolution);\n      if (!program) return;\n      gl.uniform1fv(program.uniform['m'], m);\n      gl.uniform2f(program.uniform['px'], pixelSizeX, pixelSizeY);\n      draw();\n    },\n\n    detectEdges: () => {\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        0, 1, 0,\n        1, -4, 1,\n        0, 1, 0,\n      ]);\n    },\n\n    sobelX: () => {\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        -1, 0, 1,\n        -2, 0, 2,\n        -1, 0, 1,\n      ]);\n    },\n\n    sobelY: () => {\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        -1, -2, -1,\n        0, 0, 0,\n        1, 2, 1,\n      ]);\n    },\n\n    sharpen: (amount) => {\n      const a = amount || 1;\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        0, -1 * a, 0,\n        -1 * a, 1 + 4 * a, -1 * a,\n        0, -1 * a, 0,\n      ]);\n    },\n\n    emboss: (size) => {\n      const s = size || 1;\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        -2 * s, -1 * s, 0,\n        -1 * s, 1, 1 * s,\n        0, 1 * s, 2 * s,\n      ]);\n    },\n\n    blur: (size) => {\n      const blurSizeX = (size / 7) / fxcanvas.width;\n      const blurSizeY = (size / 7) / fxcanvas.height;\n      const program = compileShader(shaders.blur);\n      if (!program) return;\n      // Vertical\n      gl.uniform2f(program.uniform['px'], 0, blurSizeY);\n      draw(DRAW.INTERMEDIATE);\n      // Horizontal\n      gl.uniform2f(program.uniform['px'], blurSizeX, 0);\n      draw();\n    },\n\n    pixelate: (size) => {\n      const blurSizeX = (size) / fxcanvas.width;\n      const blurSizeY = (size) / fxcanvas.height;\n      const program = compileShader(shaders.pixelate);\n      if (!program) return;\n      gl.uniform2f(program.uniform['size'], blurSizeX, blurSizeY);\n      draw();\n    },\n  };\n\n  // @ts-ignore this\n  this.add = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const func = filter[name];\n    filterChain.push({ func, args });\n  };\n\n  // @ts-ignore this\n  this.reset = function () {\n    filterChain = [];\n  };\n\n  // @ts-ignore this\n  this.get = function () {\n    return filterChain;\n  };\n\n  // @ts-ignore this\n  this.apply = function (image) {\n    resize(image.width, image.height);\n    drawCount = 0;\n    if (!sourceTexture) sourceTexture = gl.createTexture(); // Create the texture for the input image if we haven't yet\n    gl.bindTexture(gl.TEXTURE_2D, sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    for (let i = 0; i < filterChain.length; i++) {\n      lastInChain = (i === filterChain.length - 1);\n      const f = filterChain[i];\n      // @ts-ignore function assigment\n      f.func.apply(this, f.args || []);\n    }\n    return fxcanvas;\n  };\n\n  // @ts-ignore this\n  this.draw = function (image) {\n    this.add('brightness', 0);\n    return this.apply(image);\n  };\n}\n", "/**\n * Image enhancements\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from '../exports';\n\nexport async function histogramEqualization(inputImage: Tensor): Promise<Tensor> {\n  // const maxValue = 254; // using 255 results in values slightly larger than 1 due to math rounding errors\n  const squeeze = inputImage.shape.length === 4 ? tf.squeeze(inputImage) : inputImage;\n  const channels = tf.split(squeeze, 3, 2);\n  const min: Tensor[] = [tf.min(channels[0]), tf.min(channels[1]), tf.min(channels[2])];\n  const max: Tensor[] = [tf.max(channels[0]), tf.max(channels[1]), tf.max(channels[2])];\n  const absMax = await Promise.all(max.map((channel) => channel.data()));\n  const maxValue = 0.99 * Math.max(absMax[0][0], absMax[1][0], absMax[2][0]);\n  const sub = [tf.sub(channels[0], min[0]), tf.sub(channels[1], min[1]), tf.sub(channels[2], min[2])];\n  const range = [tf.sub(max[0], min[0]), tf.sub(max[1], min[1]), tf.sub(max[2], min[2])];\n  const fact = [tf.div(maxValue, range[0]), tf.div(maxValue, range[1]), tf.div(maxValue, range[2])];\n  const enh = [tf.mul(sub[0], fact[0]), tf.mul(sub[1], fact[1]), tf.mul(sub[2], fact[2])];\n  const rgb = tf.stack([enh[0], enh[1], enh[2]], 2);\n  const reshape = tf.reshape(rgb, [1, squeeze.shape[0], squeeze.shape[1], 3]);\n  tf.dispose([...channels, ...min, ...max, ...sub, ...range, ...fact, ...enh, rgb, squeeze]);\n  return reshape; // output shape is [1, height, width, 3]\n}\n", "/**\n * Image Processing algorithm implementation\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\nimport type { Input, AnyCanvas, Tensor, Config } from '../exports';\nimport { env } from '../util/env';\nimport { log } from '../util/util';\nimport * as enhance from './enhance';\n\nconst maxSize = 3840;\n// internal temp canvases\nlet inCanvas: AnyCanvas | null = null; // use global variable to avoid recreating canvas on each frame\nlet outCanvas: AnyCanvas | null = null; // use global variable to avoid recreating canvas on each frame\nlet tmpCanvas: AnyCanvas | null = null; // use global variable to avoid recreating canvas on each frame\n// @ts-ignore // imagefx is js module that should be converted to a class\nlet fx: fxImage.GLImageFilter | null; // instance of imagefx\n\nconst last: { inputSum: number, cacheDiff: number, sumMethod: number, inputTensor: undefined | Tensor } = {\n  inputSum: 0,\n  cacheDiff: 1,\n  sumMethod: 0,\n  inputTensor: undefined,\n};\n\nexport function canvas(width: number, height: number): AnyCanvas {\n  let c;\n  if (env.browser) { // browser defines canvas object\n    if (env.worker) { // if runing in web  worker use OffscreenCanvas\n      if (typeof OffscreenCanvas === 'undefined') throw new Error('canvas error: attempted to run in web worker but OffscreenCanvas is not supported');\n      c = new OffscreenCanvas(width, height);\n    } else { // otherwise use DOM canvas\n      if (typeof document === 'undefined') throw new Error('canvas error: attempted to run in browser but DOM is not defined');\n      c = document.createElement('canvas');\n      c.width = width;\n      c.height = height;\n    }\n  } else { // if not running in browser, there is no \"default\" canvas object, so we need monkey patch or fail\n    // @ts-ignore // env.canvas is an external monkey-patch\n    if (typeof env.Canvas !== 'undefined') c = new env.Canvas(width, height);\n    else if (typeof globalThis.Canvas !== 'undefined') c = new globalThis.Canvas(width, height);\n    // else throw new Error('canvas error: attempted to use canvas in nodejs without canvas support installed');\n  }\n  return c;\n}\n\n// helper function to copy canvas from input to output\nexport function copy(input: AnyCanvas, output?: AnyCanvas) {\n  const outputCanvas = output || canvas(input.width, input.height);\n  const ctx = outputCanvas.getContext('2d') as CanvasRenderingContext2D;\n  ctx.drawImage(input, 0, 0);\n  return outputCanvas;\n}\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport async function process(input: Input, config: Config, getTensor: boolean = true): Promise<{ tensor: Tensor | null, canvas: AnyCanvas | null }> {\n  if (!input) {\n    // throw new Error('input is missing');\n    if (config.debug) log('input error: input is missing');\n    return { tensor: null, canvas: null }; // video may become temporarily unavailable due to onresize\n  }\n  // sanity checks since different browsers do not implement all dom elements\n  if (\n    !(input instanceof tf.Tensor)\n    && !(typeof Image !== 'undefined' && input instanceof Image)\n    && !(typeof env.Canvas !== 'undefined' && input instanceof env.Canvas)\n    && !(typeof globalThis.Canvas !== 'undefined' && input instanceof globalThis.Canvas)\n    && !(typeof ImageData !== 'undefined' && input instanceof ImageData)\n    && !(typeof ImageBitmap !== 'undefined' && input instanceof ImageBitmap)\n    && !(typeof HTMLImageElement !== 'undefined' && input instanceof HTMLImageElement)\n    && !(typeof HTMLMediaElement !== 'undefined' && input instanceof HTMLMediaElement)\n    && !(typeof HTMLVideoElement !== 'undefined' && input instanceof HTMLVideoElement)\n    && !(typeof HTMLCanvasElement !== 'undefined' && input instanceof HTMLCanvasElement)\n    && !(typeof OffscreenCanvas !== 'undefined' && input instanceof OffscreenCanvas)\n  ) {\n    throw new Error('input error: type is not recognized');\n  }\n  if (input instanceof tf.Tensor) { // if input is tensor use as-is without filters but correct shape as needed\n    let tensor: Tensor | null = null;\n    if ((input as Tensor)['isDisposedInternal']) throw new Error('input error: attempted to use tensor but it is disposed');\n    if (!(input as Tensor)['shape']) throw new Error('input error: attempted to use tensor without a shape');\n    if ((input as Tensor).shape.length === 3) { // [height, width, 3 || 4]\n      if ((input as Tensor).shape[2] === 3) { // [height, width, 3] so add batch\n        tensor = tf.expandDims(input, 0);\n      } else if ((input as Tensor).shape[2] === 4) { // [height, width, 4] so strip alpha and add batch\n        const rgb = tf.slice3d(input, [0, 0, 0], [-1, -1, 3]);\n        tensor = tf.expandDims(rgb, 0);\n        tf.dispose(rgb);\n      }\n    } else if ((input as Tensor).shape.length === 4) { // [1, width, height, 3 || 4]\n      if ((input as Tensor).shape[3] === 3) { // [1, width, height, 3] just clone\n        tensor = tf.clone(input);\n      } else if ((input as Tensor).shape[3] === 4) { // [1, width, height, 4] so strip alpha\n        tensor = tf.slice4d(input, [0, 0, 0, 0], [-1, -1, -1, 3]);\n      }\n    }\n    // at the end shape must be [1, height, width, 3]\n    if (tensor == null || tensor.shape.length !== 4 || tensor.shape[0] !== 1 || tensor.shape[3] !== 3) throw new Error(`input error: attempted to use tensor with unrecognized shape: ${input['shape']}`);\n    if ((tensor as Tensor).dtype === 'int32') {\n      const cast = tf.cast(tensor, 'float32');\n      tf.dispose(tensor);\n      tensor = cast;\n    }\n    return { tensor, canvas: (config.filter.return ? outCanvas : null) };\n  } else {\n    // check if resizing will be needed\n    if (typeof input['readyState'] !== 'undefined' && input['readyState'] <= 2) {\n      if (config.debug) log('input stream is not ready');\n      return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize\n    }\n    const originalWidth = input['naturalWidth'] || input['videoWidth'] || input['width'] || (input['shape'] && (input['shape'][1] > 0));\n    const originalHeight = input['naturalHeight'] || input['videoHeight'] || input['height'] || (input['shape'] && (input['shape'][2] > 0));\n    if (!originalWidth || !originalHeight) {\n      if (config.debug) log('cannot determine input dimensions');\n      return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize\n    }\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = Math.trunc(targetWidth * originalHeight / originalWidth);\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = Math.trunc(targetHeight * originalWidth / originalHeight);\n    }\n\n    // create our canvas and resize it if needed\n    if ((config.filter.width || 0) > 0) targetWidth = config.filter.width;\n    else if ((config.filter.height || 0) > 0) targetWidth = originalWidth * ((config.filter.height || 0) / originalHeight);\n    if ((config.filter.height || 0) > 0) targetHeight = config.filter.height;\n    else if ((config.filter.width || 0) > 0) targetHeight = originalHeight * ((config.filter.width || 0) / originalWidth);\n    if (!targetWidth || !targetHeight) throw new Error('input error: cannot determine dimension');\n    if (!inCanvas || (inCanvas?.width !== targetWidth) || (inCanvas?.height !== targetHeight)) inCanvas = canvas(targetWidth, targetHeight);\n\n    // draw input to our canvas\n    const inCtx = inCanvas.getContext('2d') as CanvasRenderingContext2D;\n    if ((typeof ImageData !== 'undefined') && (input instanceof ImageData)) {\n      inCtx.putImageData(input, 0, 0);\n    } else {\n      if (config.filter.flip && typeof inCtx.translate !== 'undefined') {\n        inCtx.translate(originalWidth, 0);\n        inCtx.scale(-1, 1);\n        inCtx.drawImage(input as AnyCanvas, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas?.width, inCanvas?.height);\n        inCtx.setTransform(1, 0, 0, 1, 0, 0); // resets transforms to defaults\n      } else {\n        inCtx.drawImage(input as AnyCanvas, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas?.width, inCanvas?.height);\n      }\n    }\n\n    if (!outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas?.height !== outCanvas?.height)) outCanvas = canvas(inCanvas.width, inCanvas.height); // init output canvas\n\n    // imagefx transforms using gl from input canvas to output canvas\n    if (config.filter.enabled && env.webgl.supported) {\n      if (!fx) fx = env.browser ? new fxImage.GLImageFilter() : null; // && (typeof document !== 'undefined')\n      env.filter = !!fx;\n      if (!fx || !fx.add) {\n        if (config.debug) log('input process error: cannot initialize filters');\n        env.webgl.supported = false;\n        config.filter.enabled = false;\n        copy(inCanvas, outCanvas); // filter failed to initialize\n        // return { tensor: null, canvas: inCanvas };\n      } else {\n        fx.reset();\n        if (config.filter.brightness !== 0) fx.add('brightness', config.filter.brightness);\n        if (config.filter.contrast !== 0) fx.add('contrast', config.filter.contrast);\n        if (config.filter.sharpness !== 0) fx.add('sharpen', config.filter.sharpness);\n        if (config.filter.blur !== 0) fx.add('blur', config.filter.blur);\n        if (config.filter.saturation !== 0) fx.add('saturation', config.filter.saturation);\n        if (config.filter.hue !== 0) fx.add('hue', config.filter.hue);\n        if (config.filter.negative) fx.add('negative');\n        if (config.filter.sepia) fx.add('sepia');\n        if (config.filter.vintage) fx.add('brownie');\n        if (config.filter.sepia) fx.add('sepia');\n        if (config.filter.kodachrome) fx.add('kodachrome');\n        if (config.filter.technicolor) fx.add('technicolor');\n        if (config.filter.polaroid) fx.add('polaroid');\n        if (config.filter.pixelate !== 0) fx.add('pixelate', config.filter.pixelate);\n        if (fx.get() > 0) outCanvas = fx.apply(inCanvas);\n        else outCanvas = fx.draw(inCanvas);\n      }\n    } else {\n      copy(inCanvas, outCanvas); // if no filters applied, output canvas is input canvas\n      if (fx) fx = null;\n      env.filter = !!fx;\n    }\n\n    if (!getTensor) return { tensor: null, canvas: outCanvas }; // just canvas was requested\n    if (!outCanvas) throw new Error('canvas error: cannot create output');\n\n    // create tensor from image unless input was a tensor already\n    let pixels;\n    let depth = 3;\n    if ((typeof ImageData !== 'undefined' && input instanceof ImageData) || (input['data'] && input['width'] && input['height'])) { // if input is imagedata, just use it\n      if (env.browser && tf.browser) {\n        pixels = tf.browser ? tf.browser.fromPixels(input) : null;\n      } else {\n        depth = input['data'].length / input['height'] / input['width'];\n        // const arr = Uint8Array.from(input['data']);\n        const arr = new Uint8Array(input['data']['buffer']);\n        pixels = tf.tensor(arr, [input['height'], input['width'], depth], 'int32');\n      }\n    } else {\n      if (!tmpCanvas || (outCanvas.width !== tmpCanvas.width) || (outCanvas.height !== tmpCanvas.height)) tmpCanvas = canvas(outCanvas.width, outCanvas.height); // init output canvas\n      if (tf.browser && env.browser) {\n        if (config.backend === 'webgl' || config.backend === 'humangl' || config.backend === 'webgpu') {\n          pixels = tf.browser.fromPixels(outCanvas); // safe to reuse since both backend and context are gl based\n        } else {\n          tmpCanvas = copy(outCanvas); // cannot use output canvas as it already has gl context so we do a silly one more canvas\n          pixels = tf.browser.fromPixels(tmpCanvas);\n        }\n      } else {\n        const tempCanvas = copy(outCanvas); // cannot use output canvas as it already has gl context so we do a silly one more canvas\n        const tempCtx = tempCanvas.getContext('2d') as CanvasRenderingContext2D;\n        const tempData = tempCtx.getImageData(0, 0, targetWidth, targetHeight);\n        depth = tempData.data.length / targetWidth / targetHeight;\n        const arr = new Uint8Array(tempData.data.buffer);\n        pixels = tf.tensor(arr, [targetWidth, targetHeight, depth]);\n      }\n    }\n    if (depth === 4) { // rgba to rgb\n      const rgb = tf.slice3d(pixels, [0, 0, 0], [-1, -1, 3]); // strip alpha channel\n      tf.dispose(pixels);\n      pixels = rgb;\n    }\n    if (!pixels) throw new Error('input error: cannot create tensor');\n    const casted = tf.cast(pixels, 'float32');\n    const tensor = config.filter.equalization ? await enhance.histogramEqualization(casted) : tf.expandDims(casted, 0);\n    tf.dispose([pixels, casted]);\n    return { tensor, canvas: (config.filter.return ? outCanvas : null) };\n  }\n}\n\n/*\nconst checksum = async (input: Tensor): Promise<number> => { // use tf sum or js based sum loop depending on which is faster\n  const resizeFact = 48;\n  const reduced: Tensor = tf.image.resizeBilinear(input, [Math.trunc((input.shape[1] || 1) / resizeFact), Math.trunc((input.shape[2] || 1) / resizeFact)]);\n  const tfSum = async (): Promise<number> => {\n    const sumT = tf.sum(reduced);\n    const sum0 = await sumT.data();\n    tf.dispose(sumT);\n    return sum0[0];\n  };\n  const jsSum = async (): Promise<number> => {\n    const reducedData = await reduced.data(); // raw image rgb array\n    let sum0 = 0;\n    for (let i = 0; i < reducedData.length / 3; i++) sum0 += reducedData[3 * i + 2]; // look only at green value of each pixel\n    return sum0;\n  };\n  if (last.sumMethod === 0) {\n    const t0 = now();\n    await jsSum();\n    const t1 = now();\n    await tfSum();\n    const t2 = now();\n    last.sumMethod = t1 - t0 < t2 - t1 ? 1 : 2;\n  }\n  const res = last.sumMethod === 1 ? await jsSum() : await tfSum();\n  tf.dispose(reduced);\n  return res;\n};\n*/\n\nexport async function skip(config: Partial<Config>, input: Tensor) {\n  let skipFrame = false;\n  if (config.cacheSensitivity === 0 || !input.shape || input.shape.length !== 4 || input.shape[1] > 2048 || input.shape[2] > 2048) return skipFrame; // cache disabled or input is invalid or too large for cache analysis\n\n  /*\n  const checkSum = await checksum(input);\n  const diff = 100 * (Math.max(checkSum, last.inputSum) / Math.min(checkSum, last.inputSum) - 1);\n  last.inputSum = checkSum;\n  // if previous frame was skipped, skip this frame if changed more than cacheSensitivity\n  // if previous frame was not skipped, then look for cacheSensitivity or difference larger than one in previous frame to avoid resetting cache in subsequent frames unnecessarily\n  let skipFrame = diff < Math.max(config.cacheSensitivity, last.cacheDiff);\n  // if difference is above 10x threshold, don't use last value to force reset cache for significant change of scenes or images\n  last.cacheDiff = diff > 10 * config.cacheSensitivity ? 0 : diff;\n  skipFrame = skipFrame && (last.cacheDiff > 0); // if no cached diff value then force no skip\n  */\n\n  if (!last.inputTensor) {\n    last.inputTensor = tf.clone(input);\n  } else if (last.inputTensor.shape[1] !== input.shape[1] || last.inputTensor.shape[2] !== input.shape[2]) { // input resolution changed\n    tf.dispose(last.inputTensor);\n    last.inputTensor = tf.clone(input);\n  } else {\n    const t: Record<string, Tensor> = {};\n    t.diff = tf.sub(input, last.inputTensor);\n    t.squared = tf.mul(t.diff, t.diff);\n    t.sum = tf.sum(t.squared);\n    const diffSum = await t.sum.data();\n    const diffRelative = diffSum[0] / (input.shape[1] || 1) / (input.shape[2] || 1) / 255 / 3; // squared difference relative to input resolution and averaged per channel\n    tf.dispose([last.inputTensor, t.diff, t.squared, t.sum]);\n    last.inputTensor = tf.clone(input);\n    skipFrame = diffRelative <= (config.cacheSensitivity || 0);\n  }\n  return skipFrame;\n}\n\nexport async function compare(config: Partial<Config>, input1: Tensor, input2: Tensor): Promise<number> {\n  const t: Record<string, Tensor> = {};\n  if (!input1 || !input2 || input1.shape.length !== 4 || input1.shape.length !== input2.shape.length) {\n    if (!config.debug) log('invalid input tensor or tensor shapes do not match:', input1.shape, input2.shape);\n    return 0;\n  }\n  if (input1.shape[0] !== 1 || input2.shape[0] !== 1 || input1.shape[3] !== 3 || input2.shape[3] !== 3) {\n    if (!config.debug) log('input tensors must be of shape [1, height, width, 3]:', input1.shape, input2.shape);\n    return 0;\n  }\n  t.input1 = tf.clone(input1);\n  t.input2 = (input1.shape[1] !== input2.shape[1] || input1.shape[2] !== input2.shape[2]) ? tf.image.resizeBilinear(input2, [input1.shape[1], input1.shape[2]]) : tf.clone(input2);\n  t.diff = tf.sub(t.input1, t.input2);\n  t.squared = tf.mul(t.diff, t.diff);\n  t.sum = tf.sum(t.squared);\n  const diffSum = await t.sum.data();\n  const diffRelative = diffSum[0] / (input1.shape[1] || 1) / (input1.shape[2] || 1) / 255 / 3;\n  tf.dispose([t.input1, t.input2, t.diff, t.squared, t.sum]);\n  return diffRelative;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as image from '../image/image';\n\n/** Env class that holds detected capabilities */\nexport class Env {\n  /** Running in Browser */\n  browser: boolean;\n  /** Running in NodeJS */\n  node: boolean;\n  /** Running in WebWorker thread */\n  worker: boolean;\n  /** Detected platform */\n  platform: string = '';\n  /** Detected agent */\n  agent: string = '';\n  /** List of supported backends */\n  backends: string[] = [];\n  /** Has any work been performed so far */\n  initial: boolean;\n  /** Are image filters supported? */\n  filter: boolean | undefined;\n  /** TFJS instance details */\n  tfjs: {\n    version: undefined | string,\n  };\n  /** Is offscreenCanvas supported? */\n  offscreen: undefined | boolean;\n  /** Are performance counter instant values or additive */\n  perfadd: boolean = false;\n  /** WASM detected capabilities */\n  wasm: {\n    supported: undefined | boolean,\n    backend: undefined | boolean,\n    simd: undefined | boolean,\n    multithread: undefined | boolean,\n  } = {\n      supported: undefined,\n      backend: undefined,\n      simd: undefined,\n      multithread: undefined,\n    };\n  /** WebGL detected capabilities */\n  webgl: {\n    supported: undefined | boolean,\n    backend: undefined | boolean,\n    version: undefined | string,\n    renderer: undefined | string,\n  } = {\n      supported: undefined,\n      backend: undefined,\n      version: undefined,\n      renderer: undefined,\n    };\n  /** WebGPU detected capabilities */\n  webgpu: {\n    supported: undefined | boolean,\n    backend: undefined | boolean,\n    adapter: undefined | string,\n  } = {\n      supported: undefined,\n      backend: undefined,\n      adapter: undefined,\n    };\n  /** CPU info */\n  cpu: {\n    model: undefined | string,\n    flags: string[],\n  } = {\n      model: undefined,\n      flags: [],\n    };\n  /** List of supported kernels for current backend */\n  kernels: string[] = [];\n  /** MonkeyPatch for Canvas */\n  Canvas: undefined;\n  /** MonkeyPatch for Image */\n  Image: undefined;\n  /** MonkeyPatch for ImageData */\n  ImageData: undefined;\n\n  constructor() {\n    this.browser = typeof navigator !== 'undefined';\n    this.node = (typeof process !== 'undefined') && (typeof process.versions !== 'undefined') && (typeof process.versions.node !== 'undefined');\n    this.tfjs = { version: tf.version['tfjs-core'] };\n    this.offscreen = typeof OffscreenCanvas !== 'undefined';\n    this.initial = true;\n    // @ts-ignore WorkerGlobalScope evaluated in browser only\n    this.worker = this.browser && this.offscreen ? (typeof WorkerGlobalScope !== 'undefined') : undefined;\n    if (typeof navigator !== 'undefined') {\n      const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n      if (raw && raw[0]) {\n        const platformMatch = raw[0].match(/\\(([^()]+)\\)/g);\n        this.platform = (platformMatch && platformMatch[0]) ? platformMatch[0].replace(/\\(|\\)/g, '') : '';\n        this.agent = navigator.userAgent.replace(raw[0], '');\n        if (this.platform[1]) this.agent = this.agent.replace(raw[1], '');\n        this.agent = this.agent.replace(/  /g, ' ');\n        // chrome offscreencanvas gpu memory leak\n        /*\n        const isChrome = env.agent.match(/Chrome\\/.[0-9]/g);\n        const verChrome = isChrome && isChrome[0] ? isChrome[0].split('/')[1] : 0;\n        if (verChrome > 92 && verChrome < 96) {\n          log('disabling offscreenCanvas due to browser error:', isChrome ? isChrome[0] : 'unknown');\n          this.offscreen = false;\n        }\n        */\n      }\n    } else if (typeof process !== 'undefined') {\n      this.platform = `${process.platform} ${process.arch}`;\n      this.agent = `NodeJS ${process.version}`;\n    }\n  }\n\n  /** update backend information */\n  async updateBackend() {\n    // analyze backends\n    this.backends = Object.keys(tf.engine().registryFactory);\n    this.wasm.supported = typeof WebAssembly !== 'undefined';\n    this.wasm.backend = this.backends.includes('wasm');\n    if (this.wasm.supported && this.wasm.backend && tf.getBackend() === 'wasm') {\n      this.wasm.simd = await tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n      this.wasm.multithread = await tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n    }\n    const c = image.canvas(100, 100);\n    const ctx = c ? c.getContext('webgl2') : undefined; // causes too many gl contexts\n    // const ctx = typeof tf.backend().getGPGPUContext !== undefined ? tf.backend().getGPGPUContext : null;\n    this.webgl.supported = typeof ctx !== 'undefined';\n    this.webgl.backend = this.backends.includes('webgl');\n    if (this.webgl.supported && this.webgl.backend && (tf.getBackend() === 'webgl' || tf.getBackend() === 'humangl')) {\n      // @ts-ignore getGPGPUContext only exists on WebGL backend\n      const gl = tf.backend().gpgpu !== 'undefined' ? await tf.backend().getGPGPUContext().gl : null;\n      if (gl) {\n        this.webgl.version = gl.getParameter(gl.VERSION);\n        this.webgl.renderer = gl.getParameter(gl.RENDERER);\n      }\n    }\n    // @ts-ignore navigator.gpu is only defined when webgpu is available in browser\n    this.webgpu.supported = this.browser && typeof navigator['gpu'] !== 'undefined';\n    this.webgpu.backend = this.backends.includes('webgpu');\n    try {\n      // @ts-ignore navigator.gpu is only defined when webgpu is available in browser\n      if (this.webgpu.supported) this.webgpu.adapter = (await navigator['gpu'].requestAdapter()).name;\n    } catch {\n      this.webgpu.supported = false;\n    }\n    try {\n      this.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => kernel.kernelName.toLowerCase());\n    } catch { /**/ }\n  }\n\n  /** update cpu information */\n  async updateCPU() {\n    const cpu = { model: '', flags: [] };\n    if (this.node && this.platform.startsWith('linux')) {\n      /*\n      const fs = require('fs');\n      try {\n        const data = fs.readFileSync('/proc/cpuinfo').toString();\n        for (const line of data.split('\\n')) {\n          if (line.startsWith('model name')) cpu.model = line.match(/:(.*)/g)[0].replace(':', '').trim();\n          if (line.startsWith('flags')) cpu.flags = line.match(/:(.*)/g)[0].replace(':', '').trim().split(' ').sort();\n        }\n      } catch { }\n      */\n    }\n    if (!this['cpu']) Object.defineProperty(this, 'cpu', { value: cpu });\n    else this['cpu'] = cpu;\n  }\n}\n\nexport const env = new Env();\n", "import { log, join } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { GraphModel } from './types';\nimport type { Config } from '../config';\nimport * as modelsDefs from '../../models/models.json';\n\nconst options = {\n  cacheModels: true,\n  cacheSupported: true,\n  verbose: true,\n  debug: false,\n  modelBasePath: '',\n};\n\nexport type ModelInfo = {\n  name: string,\n  inCache: boolean,\n  sizeDesired: number,\n  sizeFromManifest: number,\n  sizeLoadedWeights: number,\n}\n\nexport const modelStats: Record<string, ModelInfo> = {};\n\nasync function httpHandler(url, init?): Promise<Response | null> {\n  if (options.debug) log('load model fetch:', url, init);\n  return fetch(url, init);\n}\n\nexport function setModelLoadOptions(config: Config) {\n  options.cacheModels = config.cacheModels;\n  options.verbose = config.debug;\n  options.modelBasePath = config.modelBasePath;\n}\n\nexport async function loadModel(modelPath: string | undefined): Promise<GraphModel> {\n  let modelUrl = join(options.modelBasePath, modelPath || '');\n  if (!modelUrl.toLowerCase().endsWith('.json')) modelUrl += '.json';\n  const modelPathSegments = modelUrl.includes('/') ? modelUrl.split('/') : modelUrl.split('\\\\');\n  const shortModelName = modelPathSegments[modelPathSegments.length - 1].replace('.json', '');\n  const cachedModelName = 'indexeddb://' + shortModelName; // generate short model name for cache\n  modelStats[shortModelName] = {\n    name: shortModelName,\n    sizeFromManifest: 0,\n    sizeLoadedWeights: 0,\n    sizeDesired: modelsDefs[shortModelName],\n    inCache: false,\n  };\n  options.cacheSupported = (typeof window !== 'undefined') && (typeof window.localStorage !== 'undefined') && (typeof window.indexedDB !== 'undefined'); // check if running in browser and if indexedb is available\n  let cachedModels = {};\n  try {\n    cachedModels = (options.cacheSupported && options.cacheModels) ? await tf.io.listModels() : {}; // list all models already in cache // this fails for webview although localStorage is defined\n  } catch {\n    options.cacheSupported = false;\n  }\n  modelStats[shortModelName].inCache = (options.cacheSupported && options.cacheModels) && Object.keys(cachedModels).includes(cachedModelName); // is model found in cache\n  const tfLoadOptions = typeof fetch === 'undefined' ? {} : { fetchFunc: (url, init?) => httpHandler(url, init) };\n  const model: GraphModel = new tf.GraphModel(modelStats[shortModelName].inCache ? cachedModelName : modelUrl, tfLoadOptions) as unknown as GraphModel; // create model prototype and decide if load from cache or from original modelurl\n  let loaded = false;\n  try {\n    // @ts-ignore private function\n    model.findIOHandler(); // decide how to actually load a model\n    if (options.debug) log('model load handler:', model['handler']);\n    // @ts-ignore private property\n    const artifacts = await model.handler.load(); // load manifest\n    modelStats[shortModelName].sizeFromManifest = artifacts?.weightData?.byteLength || 0;\n    model.loadSync(artifacts); // load weights\n    // @ts-ignore private property\n    modelStats[shortModelName].sizeLoadedWeights = model?.artifacts?.weightData?.byteLength || 0;\n    if (options.verbose) log('load model:', model['modelUrl'], { bytes: modelStats[shortModelName].sizeLoadedWeights }, options);\n    loaded = true;\n  } catch (err) {\n    log('error loading model:', modelUrl, err);\n  }\n  if (loaded && options.cacheModels && options.cacheSupported && !modelStats[shortModelName].inCache) { // save model to cache\n    try {\n      const saveResult = await model.save(cachedModelName);\n      log('model saved:', cachedModelName, saveResult);\n    } catch (err) {\n      log('error saving model:', modelUrl, err);\n    }\n  }\n  return model;\n}\n", "/**\n * Loader and Validator for all models used by Human\n */\n\nimport { env } from './util/env';\nimport { log } from './util/util';\nimport * as gear from './gear/gear';\nimport * as ssrnetAge from './gear/ssrnet-age';\nimport * as ssrnetGender from './gear/ssrnet-gender';\nimport * as antispoof from './face/antispoof';\nimport * as blazeface from './face/blazeface';\nimport * as blazepose from './body/blazepose';\nimport * as centernet from './object/centernet';\nimport * as efficientpose from './body/efficientpose';\nimport * as emotion from './gear/emotion';\nimport * as mobilefacenet from './face/mobilefacenet';\nimport * as facemesh from './face/facemesh';\nimport * as faceres from './face/faceres';\nimport * as handpose from './hand/handpose';\nimport * as handtrack from './hand/handtrack';\nimport * as iris from './face/iris';\nimport * as liveness from './face/liveness';\nimport * as movenet from './body/movenet';\nimport * as nanodet from './object/nanodet';\nimport * as posenet from './body/posenet';\nimport * as segmentation from './segmentation/segmentation';\nimport { modelStats, ModelInfo } from './tfjs/load';\nimport type { GraphModel } from './tfjs/types';\nimport type { Human } from './human';\n\n/** Instances of all possible TFJS Graph Models used by Human\n * - loaded as needed based on configuration\n * - initialized explictly with `human.load()` method\n * - initialized implicity on first call to `human.detect()`\n * - each model can be `null` if not loaded, instance of `GraphModel` if loaded or `Promise` if loading\n */\nexport class Models {\n  ssrnetage: null | GraphModel | Promise<GraphModel> = null;\n  gear: null | GraphModel | Promise<GraphModel> = null;\n  blazeposedetect: null | GraphModel | Promise<GraphModel> = null;\n  blazepose: null | GraphModel | Promise<GraphModel> = null;\n  centernet: null | GraphModel | Promise<GraphModel> = null;\n  efficientpose: null | GraphModel | Promise<GraphModel> = null;\n  mobilefacenet: null | GraphModel | Promise<GraphModel> = null;\n  emotion: null | GraphModel | Promise<GraphModel> = null;\n  facedetect: null | GraphModel | Promise<GraphModel> = null;\n  faceiris: null | GraphModel | Promise<GraphModel> = null;\n  facemesh: null | GraphModel | Promise<GraphModel> = null;\n  faceres: null | GraphModel | Promise<GraphModel> = null;\n  ssrnetgender: null | GraphModel | Promise<GraphModel> = null;\n  handpose: null | GraphModel | Promise<GraphModel> = null;\n  handskeleton: null | GraphModel | Promise<GraphModel> = null;\n  handtrack: null | GraphModel | Promise<GraphModel> = null;\n  liveness: null | GraphModel | Promise<GraphModel> = null;\n  movenet: null | GraphModel | Promise<GraphModel> = null;\n  nanodet: null | GraphModel | Promise<GraphModel> = null;\n  posenet: null | GraphModel | Promise<GraphModel> = null;\n  segmentation: null | GraphModel | Promise<GraphModel> = null;\n  antispoof: null | GraphModel | Promise<GraphModel> = null;\n}\n\nexport type ModelStats = {\n  numLoadedModels: number,\n  numEnabledModels: undefined,\n  numDefinedModels: number,\n  percentageLoaded: number,\n  totalSizeFromManifest: number,\n  totalSizeWeights: number,\n  totalSizeLoading: number,\n  totalSizeEnabled: undefined,\n  modelStats: ModelInfo[],\n}\n\nexport const getModelStats = (instance: Human): ModelStats => {\n  let totalSizeFromManifest = 0;\n  let totalSizeWeights = 0;\n  let totalSizeLoading = 0;\n  for (const m of Object.values(modelStats)) {\n    totalSizeFromManifest += m.sizeFromManifest;\n    totalSizeWeights += m.sizeLoadedWeights;\n    totalSizeLoading += m.sizeDesired;\n  }\n  const percentageLoaded = totalSizeLoading > 0 ? totalSizeWeights / totalSizeLoading : 0;\n  return {\n    numLoadedModels: Object.values(modelStats).length,\n    numEnabledModels: undefined,\n    numDefinedModels: Object.keys(instance.models).length,\n    percentageLoaded,\n    totalSizeFromManifest,\n    totalSizeWeights,\n    totalSizeLoading,\n    totalSizeEnabled: undefined,\n    modelStats: Object.values(modelStats),\n  };\n};\n\nexport function reset(instance: Human): void {\n  // if (instance.config.debug) log('resetting loaded models');\n  for (const model of Object.keys(instance.models)) instance.models[model as keyof Models] = null;\n}\n\n/** Load method preloads all instance.configured models on-demand */\nexport async function load(instance: Human): Promise<void> {\n  if (env.initial) reset(instance);\n  if (instance.config.hand.enabled) { // handpose model is a combo that must be loaded as a whole\n    if (!instance.models.handpose && instance.config.hand.detector?.modelPath?.includes('handdetect')) {\n      [instance.models.handpose, instance.models.handskeleton] = await handpose.load(instance.config);\n    }\n    if (!instance.models.handskeleton && instance.config.hand.landmarks && instance.config.hand.detector?.modelPath?.includes('handdetect')) {\n      [instance.models.handpose, instance.models.handskeleton] = await handpose.load(instance.config);\n    }\n  }\n  if (instance.config.body.enabled && !instance.models.blazepose && instance.config.body?.modelPath?.includes('blazepose')) instance.models.blazepose = blazepose.loadPose(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.body.enabled && !instance.models.blazeposedetect && instance.config.body['detector'] && instance.config.body['detector']['modelPath']) instance.models.blazeposedetect = blazepose.loadDetect(instance.config);\n  if (instance.config.body.enabled && !instance.models.efficientpose && instance.config.body?.modelPath?.includes('efficientpose')) instance.models.efficientpose = efficientpose.load(instance.config);\n  if (instance.config.body.enabled && !instance.models.movenet && instance.config.body?.modelPath?.includes('movenet')) instance.models.movenet = movenet.load(instance.config);\n  if (instance.config.body.enabled && !instance.models.posenet && instance.config.body?.modelPath?.includes('posenet')) instance.models.posenet = posenet.load(instance.config);\n  if (instance.config.face.enabled && !instance.models.facedetect) instance.models.facedetect = blazeface.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.antispoof?.enabled && !instance.models.antispoof) instance.models.antispoof = antispoof.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.liveness?.enabled && !instance.models.liveness) instance.models.liveness = liveness.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.description?.enabled && !instance.models.faceres) instance.models.faceres = faceres.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.emotion?.enabled && !instance.models.emotion) instance.models.emotion = emotion.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.iris?.enabled && !instance.config.face.attention?.enabled && !instance.models.faceiris) instance.models.faceiris = iris.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.mesh?.enabled && !instance.models.facemesh) instance.models.facemesh = facemesh.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['gear']?.enabled && !instance.models.gear) instance.models.gear = gear.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['ssrnet']?.enabled && !instance.models.ssrnetage) instance.models.ssrnetage = ssrnetAge.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['ssrnet']?.enabled && !instance.models.ssrnetgender) instance.models.ssrnetgender = ssrnetGender.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['mobilefacenet']?.enabled && !instance.models.mobilefacenet) instance.models.mobilefacenet = mobilefacenet.load(instance.config);\n  if (instance.config.hand.enabled && !instance.models.handtrack && instance.config.hand.detector?.modelPath?.includes('handtrack')) instance.models.handtrack = handtrack.loadDetect(instance.config);\n  if (instance.config.hand.enabled && instance.config.hand.landmarks && !instance.models.handskeleton && instance.config.hand.detector?.modelPath?.includes('handtrack')) instance.models.handskeleton = handtrack.loadSkeleton(instance.config);\n  if (instance.config.object.enabled && !instance.models.centernet && instance.config.object?.modelPath?.includes('centernet')) instance.models.centernet = centernet.load(instance.config);\n  if (instance.config.object.enabled && !instance.models.nanodet && instance.config.object?.modelPath?.includes('nanodet')) instance.models.nanodet = nanodet.load(instance.config);\n  if (instance.config.segmentation.enabled && !instance.models.segmentation) instance.models.segmentation = segmentation.load(instance.config);\n\n  // models are loaded in parallel asynchronously so lets wait until they are actually loaded\n  for await (const model of Object.keys(instance.models)) {\n    if (instance.models[model as keyof Models] && typeof instance.models[model as keyof Models] !== 'undefined') {\n      instance.models[model as keyof Models] = await instance.models[model as keyof Models];\n    }\n  }\n}\n\nexport async function validate(instance: Human): Promise<void> {\n  interface Op { name: string, category: string, op: string }\n  const simpleOps = ['const', 'placeholder', 'noop', 'pad', 'squeeze', 'add', 'sub', 'mul', 'div'];\n  for (const defined of Object.keys(instance.models)) {\n    const model: GraphModel | null = instance.models[defined as keyof Models] as GraphModel | null;\n    if (!model) continue;\n    const ops: string[] = [];\n    // @ts-ignore // executor is a private method\n    const executor = model?.executor;\n    if (executor && executor.graph.nodes) {\n      for (const kernel of Object.values(executor.graph.nodes)) {\n        const op = (kernel as Op).op.toLowerCase();\n        if (!ops.includes(op)) ops.push(op);\n      }\n    } else {\n      if (!executor && instance.config.debug) log('model signature not determined:', defined);\n    }\n    const missing: string[] = [];\n    for (const op of ops) {\n      if (!simpleOps.includes(op) // exclude simple ops\n        && !instance.env.kernels.includes(op) // check actual kernel ops\n        && !instance.env.kernels.includes(op.replace('_', '')) // check variation without _\n        && !instance.env.kernels.includes(op.replace('native', '')) // check standard variation\n        && !instance.env.kernels.includes(op.replace('v2', ''))) { // check non-versioned variation\n        missing.push(op);\n      }\n    }\n    // log('model validation ops:', defined, ops);\n    if (instance.config.debug && missing.length > 0) log('model validation failed:', defined, missing);\n  }\n}\n", "/**\n * GEAR [gender/emotion/age/race] model implementation\n *\n * Based on: [**GEAR Predictor**](https://github.com/Udolf15/GEAR-Predictor)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { Gender, Race } from '../result';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport { env } from '../util/env';\n\nexport type GearType = { age: number, gender: Gender, genderScore: number, race: Array<{ score: number, race: Race }> }\nlet model: GraphModel | null;\nconst last: Array<GearType> = [];\nconst raceNames = ['white', 'black', 'asian', 'indian', 'other'];\nconst ageWeights = [15, 23, 28, 35.5, 45.5, 55.5, 65];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function load(config: Config) {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['gear']?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<GearType> {\n  if (!model) return { age: 0, gender: 'unknown', genderScore: 0, race: [] };\n  const skipFrame = skipped < (config.face['gear']?.skipFrames || 0);\n  const skipTime = (config.face['gear']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && last[idx]) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    if (!model?.inputs[0].shape) return;\n    const t: Record<string, Tensor> = {};\n    // t.resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape[2], model?.inputs[0].shape[1]], false);\n    const box = [[0.0, 0.10, 0.90, 0.90]]; // empyrical values for top, left, bottom, right\n    t.resize = tf.image.cropAndResize(image, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n    const obj: GearType = { age: 0, gender: 'unknown', genderScore: 0, race: [] };\n    if (config.face['gear']?.enabled) [t.age, t.gender, t.race] = model.execute(t.resize, ['age_output', 'gender_output', 'race_output']) as Tensor[];\n    const gender = await t.gender.data();\n    obj.gender = gender[0] > gender[1] ? 'male' : 'female';\n    obj.genderScore = Math.round(100 * (gender[0] > gender[1] ? gender[0] : gender[1])) / 100;\n    const race = await t.race.data();\n    for (let i = 0; i < race.length; i++) {\n      if (race[i] > (config.face['gear']?.minConfidence || 0.2)) obj.race.push({ score: Math.round(100 * race[i]) / 100, race: raceNames[i] as Race });\n    }\n    obj.race.sort((a, b) => b.score - a.score);\n    // {0: 'Below20', 1: '21-25', 2: '26-30', 3: '31-40',4: '41-50', 5: '51-60', 6: 'Above60'}\n    const ageDistribution = Array.from(await t.age.data());\n    const ageSorted = ageDistribution.map((a, i) => [ageWeights[i], a]).sort((a, b) => b[1] - a[1]);\n    let age = ageSorted[0][0]; // pick best starting point\n    for (let i = 1; i < ageSorted.length; i++) age += ageSorted[i][1] * (ageSorted[i][0] - age); // adjust with each other choice by weight\n    obj.age = Math.round(10 * age) / 10;\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    last[idx] = obj;\n    lastCount = count;\n    lastTime = now();\n    resolve(obj);\n  });\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from './types';\n\nexport const constants: Record<string, Tensor | number | number[]> = {\n  tf255: 255,\n  tf1: 1,\n  tf2: 2,\n  tf05: 0.5,\n  tf127: 127.5,\n  rgb: [0.2989, 0.5870, 0.1140],\n};\n\nexport function init() {\n  constants.tf255 = tf.scalar(255, 'float32');\n  constants.tf1 = tf.scalar(1, 'float32');\n  constants.tf2 = tf.scalar(2, 'float32');\n  constants.tf05 = tf.scalar(0.5, 'float32');\n  constants.tf127 = tf.scalar(127.5, 'float32');\n  constants.rgb = tf.tensor1d([0.2989, 0.5870, 0.1140], 'float32'); // factors for red/green/blue colors when converting to grayscale\n}\n", "/**\n * Age model implementation\n *\n * Based on: [**SSR-Net**](https://github.com/shamangary/SSR-Net)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { env } from '../util/env';\nimport { constants } from '../tfjs/constants';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\n\nlet model: GraphModel | null;\nconst last: Array<{ age: number }> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function load(config: Config) {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['ssrnet'].modelPathAge);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<{ age: number }> {\n  if (!model) return { age: 0 };\n  const skipFrame = skipped < (config.face['ssrnet']?.skipFrames || 0);\n  const skipTime = (config.face['ssrnet']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipFrame && skipTime && (lastCount === count) && last[idx]?.age && (last[idx]?.age > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    if (!model?.inputs || !model.inputs[0] || !model.inputs[0].shape) return;\n    const t: Record<string, Tensor> = {};\n    t.resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    t.enhance = tf.mul(t.resize, constants.tf255);\n    const obj = { age: 0 };\n    if (config.face['ssrnet'].enabled) t.age = model.execute(t.enhance) as Tensor;\n    if (t.age) {\n      const data = await t.age.data();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    last[idx] = obj;\n    lastCount = count;\n    lastTime = now();\n    resolve(obj);\n  });\n}\n", "/**\n * Gender model implementation\n *\n * Based on: [**SSR-Net**](https://github.com/shamangary/SSR-Net)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport type { Gender } from '../result';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst last: Array<{ gender: Gender, genderScore: number }> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function load(config: Config | any) {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['ssrnet'].modelPathGender);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function predict(image: Tensor, config: Config, idx, count): Promise<{ gender: Gender, genderScore: number }> {\n  if (!model) return { gender: 'unknown', genderScore: 0 };\n  const skipFrame = skipped < (config.face['ssrnet']?.skipFrames || 0);\n  const skipTime = (config.face['ssrnet']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipFrame && skipTime && (lastCount === count) && last[idx]?.gender && (last[idx]?.genderScore > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    if (!model?.inputs[0].shape) return;\n    const t: Record<string, Tensor> = {};\n    t.resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    t.enhance = tf.tidy(() => {\n      const [red, green, blue] = tf.split(t.resize, 3, 3);\n      const redNorm = tf.mul(red, rgb[0]);\n      const greenNorm = tf.mul(green, rgb[1]);\n      const blueNorm = tf.mul(blue, rgb[2]);\n      const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n      const normalize = tf.mul(tf.sub(grayscale, constants.tf05), 2); // range grayscale:-1..1\n      return normalize;\n    });\n    const obj: { gender: Gender, genderScore: number } = { gender: 'unknown', genderScore: 0 };\n    if (config.face['ssrnet'].enabled) t.gender = model.execute(t.enhance) as Tensor;\n    const data = await t.gender.data();\n    obj.gender = data[0] > data[1] ? 'female' : 'male'; // returns two values 0..1, bigger one is prediction\n    obj.genderScore = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    last[idx] = obj;\n    lastCount = count;\n    lastTime = now();\n    resolve(obj);\n  });\n}\n", "/**\n * Anti-spoofing model implementation\n */\n\nimport { log, now } from '../util/util';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst cached: Array<number> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet lastCount = 0;\nlet lastTime = 0;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.antispoof?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<number> {\n  if (!model) return 0;\n  const skipTime = (config.face.antispoof?.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.face.antispoof?.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && cached[idx]) {\n    skipped++;\n    return cached[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape ? model.inputs[0].shape[2] : 0, model?.inputs[0].shape ? model.inputs[0].shape[1] : 0], false);\n    const res = model?.execute(resize) as Tensor;\n    const num = (await res.data())[0];\n    cached[idx] = Math.round(100 * num) / 100;\n    lastCount = count;\n    lastTime = now();\n    tf.dispose([resize, res]);\n    resolve(cached[idx]);\n  });\n}\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n * See `facemesh.ts` for entry point\n */\n\nexport const meshAnnotations: Record<string, number[]> = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  // lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291], // 11\n  // lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291], // 10\n  // lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308], // 11\n  // lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308], // 11\n  lipsUpperOuter: [185, 40, 39, 37, 0, 267, 269, 270, 409],\n  lipsLowerOuter: [61, 146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [191, 80, 81, 82, 13, 312, 311, 310, 415],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  lipsLowerSemiOuter: [76, 77, 90, 180, 85, 16, 315, 404, 320, 307, 306],\n  lipsUpperSemiOuter: [184, 74, 73, 72, 11, 302, 303, 304, 408],\n  lipsLowerSemiInner: [62, 96, 89, 179, 86, 15, 316, 403, 319, 325, 292],\n  lipsUpperSemiInner: [183, 42, 41, 38, 12, 268, 271, 272, 407],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173], // 7\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133], // 9\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190], // 7\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243], // 9\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189], // 7\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244], // 9\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245], // 9\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193], // 8\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65], // 6\n  rightEyeIris: [473, 474, 475, 476, 477], // 5\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const meshLandmarks: Record<string, number | number[]> = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, meshAnnotations['midwayBetweenEyes'][0]],\n};\n\nexport const blazeFaceLandmarks: Record<string, number | number[]> = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nexport const irisIndices: Array<{ key: string, indices: number[] }> = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] }, // 7 x 3d\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] }, // 7 x 3d\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] }, // 7 x 3d\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] }, // 7 x 3d\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] }, // 9 x 3d\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] }, // 9 x 3d\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] }, // 9 x 3d\n  { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] }, // 8 x 3d\n  { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] }, // 6 x 3d\n];\n\nexport const UV468: [number, number][] = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 0.547487020492554],\n  [0.499974012374878, 0.602371990680695],\n  [0.482113003730774, 0.471979022026062],\n  [0.500150978565216, 0.527155995368958],\n  [0.499909996986389, 0.498252987861633],\n  [0.499523013830185, 0.40106201171875],\n  [0.289712011814117, 0.380764007568359],\n  [0.499954998493195, 0.312398016452789],\n  [0.499987006187439, 0.269918978214264],\n  [0.500023007392883, 0.107050001621246],\n  [0.500023007392883, 0.666234016418457],\n  [0.5000159740448, 0.679224014282227],\n  [0.500023007392883, 0.692348003387451],\n  [0.499976992607117, 0.695277988910675],\n  [0.499976992607117, 0.70593398809433],\n  [0.499976992607117, 0.719385027885437],\n  [0.499976992607117, 0.737019002437592],\n  [0.499967992305756, 0.781370997428894],\n  [0.499816000461578, 0.562981009483337],\n  [0.473773002624512, 0.573909997940063],\n  [0.104906998574734, 0.254140973091125],\n  [0.365929991006851, 0.409575998783112],\n  [0.338757991790771, 0.41302502155304],\n  [0.311120003461838, 0.409460008144379],\n  [0.274657994508743, 0.389131009578705],\n  [0.393361985683441, 0.403706014156342],\n  [0.345234006643295, 0.344011008739471],\n  [0.370094001293182, 0.346076011657715],\n  [0.319321990013123, 0.347265005111694],\n  [0.297903001308441, 0.353591024875641],\n  [0.24779200553894, 0.410809993743896],\n  [0.396889001131058, 0.842755019664764],\n  [0.280097991228104, 0.375599980354309],\n  [0.106310002505779, 0.399955987930298],\n  [0.2099249958992, 0.391353011131287],\n  [0.355807989835739, 0.534406006336212],\n  [0.471751004457474, 0.65040397644043],\n  [0.474155008792877, 0.680191993713379],\n  [0.439785003662109, 0.657229006290436],\n  [0.414617002010345, 0.66654098033905],\n  [0.450374007225037, 0.680860996246338],\n  [0.428770989179611, 0.682690978050232],\n  [0.374971002340317, 0.727805018424988],\n  [0.486716985702515, 0.547628998756409],\n  [0.485300987958908, 0.527395009994507],\n  [0.257764995098114, 0.314490020275116],\n  [0.401223003864288, 0.455172002315521],\n  [0.429818987846375, 0.548614978790283],\n  [0.421351999044418, 0.533740997314453],\n  [0.276895999908447, 0.532056987285614],\n  [0.483370006084442, 0.499586999416351],\n  [0.33721199631691, 0.282882988452911],\n  [0.296391993761063, 0.293242990970612],\n  [0.169294998049736, 0.193813979625702],\n  [0.447580009698868, 0.302609980106354],\n  [0.392390012741089, 0.353887975215912],\n  [0.354490011930466, 0.696784019470215],\n  [0.067304998636246, 0.730105042457581],\n  [0.442739009857178, 0.572826027870178],\n  [0.457098007202148, 0.584792017936707],\n  [0.381974011659622, 0.694710969924927],\n  [0.392388999462128, 0.694203019142151],\n  [0.277076005935669, 0.271932005882263],\n  [0.422551989555359, 0.563233017921448],\n  [0.385919004678726, 0.281364023685455],\n  [0.383103013038635, 0.255840003490448],\n  [0.331431001424789, 0.119714021682739],\n  [0.229923993349075, 0.232002973556519],\n  [0.364500999450684, 0.189113974571228],\n  [0.229622006416321, 0.299540996551514],\n  [0.173287004232407, 0.278747975826263],\n  [0.472878992557526, 0.666198015213013],\n  [0.446828007698059, 0.668527007102966],\n  [0.422762006521225, 0.673889994621277],\n  [0.445307999849319, 0.580065965652466],\n  [0.388103008270264, 0.693961024284363],\n  [0.403039008378983, 0.706539988517761],\n  [0.403629004955292, 0.693953037261963],\n  [0.460041999816895, 0.557139039039612],\n  [0.431158006191254, 0.692366003990173],\n  [0.452181994915009, 0.692366003990173],\n  [0.475387006998062, 0.692366003990173],\n  [0.465828001499176, 0.779190003871918],\n  [0.472328990697861, 0.736225962638855],\n  [0.473087012767792, 0.717857003211975],\n  [0.473122000694275, 0.704625964164734],\n  [0.473033010959625, 0.695277988910675],\n  [0.427942007780075, 0.695277988910675],\n  [0.426479011774063, 0.703539967536926],\n  [0.423162013292313, 0.711845993995667],\n  [0.4183090031147, 0.720062971115112],\n  [0.390094995498657, 0.639572978019714],\n  [0.013953999616206, 0.560034036636353],\n  [0.499913990497589, 0.58014702796936],\n  [0.413199990987778, 0.69539999961853],\n  [0.409626007080078, 0.701822996139526],\n  [0.468080013990402, 0.601534962654114],\n  [0.422728985548019, 0.585985004901886],\n  [0.463079988956451, 0.593783974647522],\n  [0.37211999297142, 0.47341400384903],\n  [0.334562003612518, 0.496073007583618],\n  [0.411671012639999, 0.546965003013611],\n  [0.242175996303558, 0.14767599105835],\n  [0.290776997804642, 0.201445996761322],\n  [0.327338010072708, 0.256527006626129],\n  [0.399509996175766, 0.748921036720276],\n  [0.441727995872498, 0.261676013469696],\n  [0.429764986038208, 0.187834024429321],\n  [0.412198007106781, 0.108901023864746],\n  [0.288955003023148, 0.398952007293701],\n  [0.218936994671822, 0.435410976409912],\n  [0.41278201341629, 0.398970007896423],\n  [0.257135003805161, 0.355440020561218],\n  [0.427684992551804, 0.437960982322693],\n  [0.448339998722076, 0.536936044692993],\n  [0.178560003638268, 0.45755398273468],\n  [0.247308000922203, 0.457193970680237],\n  [0.286267012357712, 0.467674970626831],\n  [0.332827985286713, 0.460712015628815],\n  [0.368755996227264, 0.447206974029541],\n  [0.398963987827301, 0.432654976844788],\n  [0.476410001516342, 0.405806005001068],\n  [0.189241006970406, 0.523923993110657],\n  [0.228962004184723, 0.348950982093811],\n  [0.490725994110107, 0.562400996685028],\n  [0.404670000076294, 0.485132992267609],\n  [0.019469000399113, 0.401564002037048],\n  [0.426243007183075, 0.420431017875671],\n  [0.396993011236191, 0.548797011375427],\n  [0.266469985246658, 0.376977026462555],\n  [0.439121007919312, 0.51895797252655],\n  [0.032313998788595, 0.644356966018677],\n  [0.419054001569748, 0.387154996395111],\n  [0.462783008813858, 0.505746960639954],\n  [0.238978996872902, 0.779744982719421],\n  [0.198220998048782, 0.831938028335571],\n  [0.107550002634525, 0.540755033493042],\n  [0.183610007166862, 0.740257024765015],\n  [0.134409993886948, 0.333683013916016],\n  [0.385764002799988, 0.883153975009918],\n  [0.490967005491257, 0.579378008842468],\n  [0.382384985685349, 0.508572995662689],\n  [0.174399003386497, 0.397670984268188],\n  [0.318785011768341, 0.39623498916626],\n  [0.343364000320435, 0.400596976280212],\n  [0.396100014448166, 0.710216999053955],\n  [0.187885001301765, 0.588537991046906],\n  [0.430987000465393, 0.944064974784851],\n  [0.318993002176285, 0.898285031318665],\n  [0.266247987747192, 0.869701027870178],\n  [0.500023007392883, 0.190576016902924],\n  [0.499976992607117, 0.954452991485596],\n  [0.366169989109039, 0.398822009563446],\n  [0.393207013607025, 0.39553701877594],\n  [0.410373002290726, 0.391080021858215],\n  [0.194993004202843, 0.342101991176605],\n  [0.388664990663528, 0.362284004688263],\n  [0.365961998701096, 0.355970978736877],\n  [0.343364000320435, 0.355356991291046],\n  [0.318785011768341, 0.35834002494812],\n  [0.301414996385574, 0.363156020641327],\n  [0.058132998645306, 0.319076001644135],\n  [0.301414996385574, 0.387449026107788],\n  [0.499987989664078, 0.618434011936188],\n  [0.415838003158569, 0.624195992946625],\n  [0.445681989192963, 0.566076993942261],\n  [0.465844005346298, 0.620640993118286],\n  [0.49992299079895, 0.351523995399475],\n  [0.288718998432159, 0.819945991039276],\n  [0.335278987884521, 0.852819979190826],\n  [0.440512001514435, 0.902418971061707],\n  [0.128294005990028, 0.791940987110138],\n  [0.408771991729736, 0.373893976211548],\n  [0.455606997013092, 0.451801002025604],\n  [0.499877005815506, 0.908990025520325],\n  [0.375436991453171, 0.924192011356354],\n  [0.11421000212431, 0.615022003650665],\n  [0.448662012815475, 0.695277988910675],\n  [0.4480200111866, 0.704632043838501],\n  [0.447111994028091, 0.715808033943176],\n  [0.444831997156143, 0.730794012546539],\n  [0.430011987686157, 0.766808986663818],\n  [0.406787008047104, 0.685672998428345],\n  [0.400738000869751, 0.681069016456604],\n  [0.392399996519089, 0.677703022956848],\n  [0.367855995893478, 0.663918972015381],\n  [0.247923001646996, 0.601333022117615],\n  [0.452769994735718, 0.420849978923798],\n  [0.43639200925827, 0.359887003898621],\n  [0.416164010763168, 0.368713974952698],\n  [0.413385987281799, 0.692366003990173],\n  [0.228018000721931, 0.683571994304657],\n  [0.468268007040024, 0.352671027183533],\n  [0.411361992359161, 0.804327011108398],\n  [0.499989002943039, 0.469825029373169],\n  [0.479153990745544, 0.442654013633728],\n  [0.499974012374878, 0.439637005329132],\n  [0.432112008333206, 0.493588984012604],\n  [0.499886006116867, 0.866917014122009],\n  [0.49991300702095, 0.821729004383087],\n  [0.456548988819122, 0.819200992584229],\n  [0.344549000263214, 0.745438992977142],\n  [0.37890899181366, 0.574010014533997],\n  [0.374292999505997, 0.780184984207153],\n  [0.319687992334366, 0.570737957954407],\n  [0.357154995203018, 0.604269981384277],\n  [0.295284003019333, 0.621580958366394],\n  [0.447750002145767, 0.862477004528046],\n  [0.410986006259918, 0.508723020553589],\n  [0.31395098567009, 0.775308012962341],\n  [0.354128003120422, 0.812552988529205],\n  [0.324548006057739, 0.703992962837219],\n  [0.189096003770828, 0.646299958229065],\n  [0.279776990413666, 0.71465802192688],\n  [0.1338230073452, 0.682700991630554],\n  [0.336768001317978, 0.644733011722565],\n  [0.429883986711502, 0.466521978378296],\n  [0.455527991056442, 0.548622965812683],\n  [0.437114000320435, 0.558896005153656],\n  [0.467287987470627, 0.529924988746643],\n  [0.414712011814117, 0.335219979286194],\n  [0.37704598903656, 0.322777986526489],\n  [0.344107985496521, 0.320150971412659],\n  [0.312875986099243, 0.32233202457428],\n  [0.283526003360748, 0.333190023899078],\n  [0.241245999932289, 0.382785975933075],\n  [0.102986000478268, 0.468762993812561],\n  [0.267612010240555, 0.424560010433197],\n  [0.297879010438919, 0.433175981044769],\n  [0.333433985710144, 0.433878004550934],\n  [0.366427004337311, 0.426115989685059],\n  [0.396012008190155, 0.416696012020111],\n  [0.420121014118195, 0.41022801399231],\n  [0.007561000064015, 0.480777025222778],\n  [0.432949006557465, 0.569517970085144],\n  [0.458638995885849, 0.479089021682739],\n  [0.473466008901596, 0.545744001865387],\n  [0.476087987422943, 0.563830018043518],\n  [0.468472003936768, 0.555056989192963],\n  [0.433990985155106, 0.582361996173859],\n  [0.483518004417419, 0.562983989715576],\n  [0.482482999563217, 0.57784903049469],\n  [0.42645001411438, 0.389798998832703],\n  [0.438998997211456, 0.39649498462677],\n  [0.450067013502121, 0.400434017181396],\n  [0.289712011814117, 0.368252992630005],\n  [0.276670008897781, 0.363372981548309],\n  [0.517862021923065, 0.471948027610779],\n  [0.710287988185883, 0.380764007568359],\n  [0.526226997375488, 0.573909997940063],\n  [0.895093023777008, 0.254140973091125],\n  [0.634069979190826, 0.409575998783112],\n  [0.661242008209229, 0.41302502155304],\n  [0.688880026340485, 0.409460008144379],\n  [0.725341975688934, 0.389131009578705],\n  [0.606630027294159, 0.40370500087738],\n  [0.654766023159027, 0.344011008739471],\n  [0.629905998706818, 0.346076011657715],\n  [0.680678009986877, 0.347265005111694],\n  [0.702096998691559, 0.353591024875641],\n  [0.75221198797226, 0.410804986953735],\n  [0.602918028831482, 0.842862963676453],\n  [0.719901978969574, 0.375599980354309],\n  [0.893692970275879, 0.399959981441498],\n  [0.790081977844238, 0.391354024410248],\n  [0.643998026847839, 0.534487962722778],\n  [0.528249025344849, 0.65040397644043],\n  [0.525849997997284, 0.680191040039062],\n  [0.560214996337891, 0.657229006290436],\n  [0.585384011268616, 0.66654098033905],\n  [0.549625992774963, 0.680860996246338],\n  [0.57122802734375, 0.682691991329193],\n  [0.624852001667023, 0.72809898853302],\n  [0.513050019741058, 0.547281980514526],\n  [0.51509702205658, 0.527251958847046],\n  [0.742246985435486, 0.314507007598877],\n  [0.598631024360657, 0.454979002475739],\n  [0.570338010787964, 0.548575043678284],\n  [0.578631997108459, 0.533622980117798],\n  [0.723087012767792, 0.532054007053375],\n  [0.516445994377136, 0.499638974666595],\n  [0.662801027297974, 0.282917976379395],\n  [0.70362401008606, 0.293271005153656],\n  [0.830704987049103, 0.193813979625702],\n  [0.552385985851288, 0.302568018436432],\n  [0.607609987258911, 0.353887975215912],\n  [0.645429015159607, 0.696707010269165],\n  [0.932694971561432, 0.730105042457581],\n  [0.557260990142822, 0.572826027870178],\n  [0.542901992797852, 0.584792017936707],\n  [0.6180260181427, 0.694710969924927],\n  [0.607590973377228, 0.694203019142151],\n  [0.722943007946014, 0.271963000297546],\n  [0.577413976192474, 0.563166975975037],\n  [0.614082992076874, 0.281386971473694],\n  [0.616907000541687, 0.255886018276215],\n  [0.668509006500244, 0.119913995265961],\n  [0.770092010498047, 0.232020974159241],\n  [0.635536015033722, 0.189248979091644],\n  [0.77039098739624, 0.299556016921997],\n  [0.826722025871277, 0.278755009174347],\n  [0.527121007442474, 0.666198015213013],\n  [0.553171992301941, 0.668527007102966],\n  [0.577238023281097, 0.673889994621277],\n  [0.554691970348358, 0.580065965652466],\n  [0.611896991729736, 0.693961024284363],\n  [0.59696102142334, 0.706539988517761],\n  [0.596370995044708, 0.693953037261963],\n  [0.539958000183105, 0.557139039039612],\n  [0.568841993808746, 0.692366003990173],\n  [0.547818005084991, 0.692366003990173],\n  [0.52461302280426, 0.692366003990173],\n  [0.534089982509613, 0.779141008853912],\n  [0.527670979499817, 0.736225962638855],\n  [0.526912987232208, 0.717857003211975],\n  [0.526877999305725, 0.704625964164734],\n  [0.526966989040375, 0.695277988910675],\n  [0.572058022022247, 0.695277988910675],\n  [0.573521018028259, 0.703539967536926],\n  [0.57683801651001, 0.711845993995667],\n  [0.581691026687622, 0.720062971115112],\n  [0.609944999217987, 0.639909982681274],\n  [0.986046016216278, 0.560034036636353],\n  [0.5867999792099, 0.69539999961853],\n  [0.590372025966644, 0.701822996139526],\n  [0.531915009021759, 0.601536989212036],\n  [0.577268004417419, 0.585934996604919],\n  [0.536915004253387, 0.593786001205444],\n  [0.627542972564697, 0.473352015018463],\n  [0.665585994720459, 0.495950996875763],\n  [0.588353991508484, 0.546862006187439],\n  [0.757824003696442, 0.14767599105835],\n  [0.709249973297119, 0.201507985591888],\n  [0.672684013843536, 0.256581008434296],\n  [0.600408971309662, 0.74900496006012],\n  [0.55826598405838, 0.261672019958496],\n  [0.570303976535797, 0.187870979309082],\n  [0.588165998458862, 0.109044015407562],\n  [0.711045026779175, 0.398952007293701],\n  [0.781069993972778, 0.435405015945435],\n  [0.587247014045715, 0.398931980133057],\n  [0.742869973182678, 0.355445981025696],\n  [0.572156012058258, 0.437651991844177],\n  [0.55186802148819, 0.536570012569427],\n  [0.821442008018494, 0.457556009292603],\n  [0.752701997756958, 0.457181990146637],\n  [0.71375697851181, 0.467626988887787],\n  [0.66711300611496, 0.460672974586487],\n  [0.631101012229919, 0.447153985500336],\n  [0.6008620262146, 0.432473003864288],\n  [0.523481011390686, 0.405627012252808],\n  [0.810747981071472, 0.523926019668579],\n  [0.771045982837677, 0.348959028720856],\n  [0.509127020835876, 0.562718033790588],\n  [0.595292985439301, 0.485023975372314],\n  [0.980530977249146, 0.401564002037048],\n  [0.573499977588654, 0.420000016689301],\n  [0.602994978427887, 0.548687994480133],\n  [0.733529984951019, 0.376977026462555],\n  [0.560611009597778, 0.519016981124878],\n  [0.967685997486115, 0.644356966018677],\n  [0.580985009670258, 0.387160003185272],\n  [0.537728011608124, 0.505385041236877],\n  [0.760966002941132, 0.779752969741821],\n  [0.801778972148895, 0.831938028335571],\n  [0.892440974712372, 0.54076099395752],\n  [0.816350996494293, 0.740260004997253],\n  [0.865594983100891, 0.333687007427216],\n  [0.614073991775513, 0.883246004581451],\n  [0.508952975273132, 0.579437971115112],\n  [0.617941975593567, 0.508316040039062],\n  [0.825608015060425, 0.397674977779388],\n  [0.681214988231659, 0.39623498916626],\n  [0.656635999679565, 0.400596976280212],\n  [0.603900015354156, 0.710216999053955],\n  [0.81208598613739, 0.588539004325867],\n  [0.56801301240921, 0.944564998149872],\n  [0.681007981300354, 0.898285031318665],\n  [0.733752012252808, 0.869701027870178],\n  [0.633830010890961, 0.398822009563446],\n  [0.606792986392975, 0.39553701877594],\n  [0.589659988880157, 0.391062021255493],\n  [0.805015981197357, 0.342108011245728],\n  [0.611334979534149, 0.362284004688263],\n  [0.634037971496582, 0.355970978736877],\n  [0.656635999679565, 0.355356991291046],\n  [0.681214988231659, 0.35834002494812],\n  [0.698584973812103, 0.363156020641327],\n  [0.941866993904114, 0.319076001644135],\n  [0.698584973812103, 0.387449026107788],\n  [0.584177017211914, 0.624107003211975],\n  [0.554318010807037, 0.566076993942261],\n  [0.534153997898102, 0.62064003944397],\n  [0.711217999458313, 0.819975018501282],\n  [0.664629995822906, 0.852871000766754],\n  [0.559099972248077, 0.902631998062134],\n  [0.871706008911133, 0.791940987110138],\n  [0.591234028339386, 0.373893976211548],\n  [0.544341027736664, 0.451583981513977],\n  [0.624562978744507, 0.924192011356354],\n  [0.88577002286911, 0.615028977394104],\n  [0.551338016986847, 0.695277988910675],\n  [0.551980018615723, 0.704632043838501],\n  [0.552887976169586, 0.715808033943176],\n  [0.555167973041534, 0.730794012546539],\n  [0.569944024085999, 0.767035007476807],\n  [0.593203008174896, 0.685675978660583],\n  [0.599261999130249, 0.681069016456604],\n  [0.607599973678589, 0.677703022956848],\n  [0.631937980651855, 0.663500010967255],\n  [0.752032995223999, 0.601315021514893],\n  [0.547226011753082, 0.420395016670227],\n  [0.563543975353241, 0.359827995300293],\n  [0.583841025829315, 0.368713974952698],\n  [0.586614012718201, 0.692366003990173],\n  [0.771915018558502, 0.683578014373779],\n  [0.531597018241882, 0.352482974529266],\n  [0.588370978832245, 0.804440975189209],\n  [0.52079701423645, 0.442565023899078],\n  [0.567984998226166, 0.493479013442993],\n  [0.543282985687256, 0.819254994392395],\n  [0.655317008495331, 0.745514988899231],\n  [0.621008992195129, 0.574018001556396],\n  [0.625559985637665, 0.78031200170517],\n  [0.680198013782501, 0.570719003677368],\n  [0.64276397228241, 0.604337990283966],\n  [0.704662978649139, 0.621529996395111],\n  [0.552012026309967, 0.862591981887817],\n  [0.589071989059448, 0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468: Array<number> = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68: Array<number> = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33: Array<number> = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7: Array<number> = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68: Array<number> = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33: Array<number> = [33, 133, 362, 263, 1, 62, 308, 159, 145, 386, 374, 6, 102, 331, 2, 13, 14, 70, 105, 107, 336, 334, 300, 54, 10, 284, 50, 280, 234, 454, 58, 288, 152];\n\nexport const VTX7: Array<number> = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n\n// https://github.com/tensorflow/tfjs-models/blob/master/face-landmarks-detection/src/constants.ts\n// https://github.com/google/mediapipe/mediapipe/python/solutions/face_mesh_connections.py\n\ntype PairArray = Array<[number, number]>;\n\nfunction connectionsToIndices(connections: PairArray) {\n  const indices = connections.map((connection) => connection[0]);\n  indices.push(connections[connections.length - 1][1]);\n  return indices;\n}\n\nexport const pairsLips: PairArray = [\n  [61, 146], [146, 91], [91, 181], [181, 84], [84, 17], [17, 314], [314, 405], [405, 321], [321, 375], [375, 291], [61, 185], [185, 40], [40, 39], [39, 37], [37, 0], [0, 267], [267, 269], [269, 270], [270, 409], [409, 291],\n  [78, 95], [95, 88], [88, 178], [178, 87], [87, 14], [14, 317], [317, 402], [402, 318], [318, 324], [324, 308], [78, 191], [191, 80], [80, 81], [81, 82], [82, 13], [13, 312], [312, 311], [311, 310], [310, 415], [415, 308],\n];\n\nexport const pairsLeftEye: PairArray = [[263, 249], [249, 390], [390, 373], [373, 374], [374, 380], [380, 381], [381, 382], [382, 362], [263, 466], [466, 388], [388, 387], [387, 386], [386, 385], [385, 384], [384, 398], [398, 362]];\n\nexport const pairsLeftEyebrow: PairArray = [[276, 283], [283, 282], [282, 295], [295, 285], [300, 293], [293, 334], [334, 296], [296, 336]];\n\nexport const pairsLeftIris: PairArray = [[474, 475], [475, 476], [476, 477], [477, 474]];\n\nexport const pairsRightEye: PairArray = [[33, 7], [7, 163], [163, 144], [144, 145], [145, 153], [153, 154], [154, 155], [155, 133], [33, 246], [246, 161], [161, 160], [160, 159], [159, 158], [158, 157], [157, 173], [173, 133]];\n\nexport const pairsRightEyebrow: PairArray = [[46, 53], [53, 52], [52, 65], [65, 55], [70, 63], [63, 105], [105, 66], [66, 107]];\n\nexport const pairsRightIris: PairArray = [[469, 470], [470, 471], [471, 472], [472, 469]];\n\nexport const pairsFaceContour: PairArray = [\n  [10, 338], [338, 297], [297, 332], [332, 284], [284, 251], [251, 389],\n  [389, 356], [356, 454], [454, 323], [323, 361], [361, 288], [288, 397],\n  [397, 365], [365, 379], [379, 378], [378, 400], [400, 377], [377, 152],\n  [152, 148], [148, 176], [176, 149], [149, 150], [150, 136], [136, 172],\n  [172, 58], [58, 132], [132, 93], [93, 234], [234, 127], [127, 162],\n  [162, 21], [21, 54], [54, 103], [103, 67], [67, 109], [109, 10],\n];\n\nexport const contourKeypoints = {\n  lips: connectionsToIndices(pairsLips),\n  leftEye: connectionsToIndices(pairsLeftEye),\n  leftEyebrow: connectionsToIndices(pairsLeftEyebrow),\n  leftIris: connectionsToIndices(pairsLeftIris),\n  rightEye: connectionsToIndices(pairsRightEye),\n  rightEyebrow: connectionsToIndices(pairsRightEyebrow),\n  rightIris: connectionsToIndices(pairsRightIris),\n  faceOval: connectionsToIndices(pairsFaceContour),\n};\n\nexport const pairsFaceMesh: PairArray = [\n  [127, 34], [34, 139], [139, 127], [11, 0], [0, 37], [37, 11],\n  [232, 231], [231, 120], [120, 232], [72, 37], [37, 39], [39, 72],\n  [128, 121], [121, 47], [47, 128], [232, 121], [121, 128], [128, 232],\n  [104, 69], [69, 67], [67, 104], [175, 171], [171, 148], [148, 175],\n  [118, 50], [50, 101], [101, 118], [73, 39], [39, 40], [40, 73],\n  [9, 151], [151, 108], [108, 9], [48, 115], [115, 131], [131, 48],\n  [194, 204], [204, 211], [211, 194], [74, 40], [40, 185], [185, 74],\n  [80, 42], [42, 183], [183, 80], [40, 92], [92, 186], [186, 40],\n  [230, 229], [229, 118], [118, 230], [202, 212], [212, 214], [214, 202],\n  [83, 18], [18, 17], [17, 83], [76, 61], [61, 146], [146, 76],\n  [160, 29], [29, 30], [30, 160], [56, 157], [157, 173], [173, 56],\n  [106, 204], [204, 194], [194, 106], [135, 214], [214, 192], [192, 135],\n  [203, 165], [165, 98], [98, 203], [21, 71], [71, 68], [68, 21],\n  [51, 45], [45, 4], [4, 51], [144, 24], [24, 23], [23, 144],\n  [77, 146], [146, 91], [91, 77], [205, 50], [50, 187], [187, 205],\n  [201, 200], [200, 18], [18, 201], [91, 106], [106, 182], [182, 91],\n  [90, 91], [91, 181], [181, 90], [85, 84], [84, 17], [17, 85],\n  [206, 203], [203, 36], [36, 206], [148, 171], [171, 140], [140, 148],\n  [92, 40], [40, 39], [39, 92], [193, 189], [189, 244], [244, 193],\n  [159, 158], [158, 28], [28, 159], [247, 246], [246, 161], [161, 247],\n  [236, 3], [3, 196], [196, 236], [54, 68], [68, 104], [104, 54],\n  [193, 168], [168, 8], [8, 193], [117, 228], [228, 31], [31, 117],\n  [189, 193], [193, 55], [55, 189], [98, 97], [97, 99], [99, 98],\n  [126, 47], [47, 100], [100, 126], [166, 79], [79, 218], [218, 166],\n  [155, 154], [154, 26], [26, 155], [209, 49], [49, 131], [131, 209],\n  [135, 136], [136, 150], [150, 135], [47, 126], [126, 217], [217, 47],\n  [223, 52], [52, 53], [53, 223], [45, 51], [51, 134], [134, 45],\n  [211, 170], [170, 140], [140, 211], [67, 69], [69, 108], [108, 67],\n  [43, 106], [106, 91], [91, 43], [230, 119], [119, 120], [120, 230],\n  [226, 130], [130, 247], [247, 226], [63, 53], [53, 52], [52, 63],\n  [238, 20], [20, 242], [242, 238], [46, 70], [70, 156], [156, 46],\n  [78, 62], [62, 96], [96, 78], [46, 53], [53, 63], [63, 46],\n  [143, 34], [34, 227], [227, 143], [123, 117], [117, 111], [111, 123],\n  [44, 125], [125, 19], [19, 44], [236, 134], [134, 51], [51, 236],\n  [216, 206], [206, 205], [205, 216], [154, 153], [153, 22], [22, 154],\n  [39, 37], [37, 167], [167, 39], [200, 201], [201, 208], [208, 200],\n  [36, 142], [142, 100], [100, 36], [57, 212], [212, 202], [202, 57],\n  [20, 60], [60, 99], [99, 20], [28, 158], [158, 157], [157, 28],\n  [35, 226], [226, 113], [113, 35], [160, 159], [159, 27], [27, 160],\n  [204, 202], [202, 210], [210, 204], [113, 225], [225, 46], [46, 113],\n  [43, 202], [202, 204], [204, 43], [62, 76], [76, 77], [77, 62],\n  [137, 123], [123, 116], [116, 137], [41, 38], [38, 72], [72, 41],\n  [203, 129], [129, 142], [142, 203], [64, 98], [98, 240], [240, 64],\n  [49, 102], [102, 64], [64, 49], [41, 73], [73, 74], [74, 41],\n  [212, 216], [216, 207], [207, 212], [42, 74], [74, 184], [184, 42],\n  [169, 170], [170, 211], [211, 169], [170, 149], [149, 176], [176, 170],\n  [105, 66], [66, 69], [69, 105], [122, 6], [6, 168], [168, 122],\n  [123, 147], [147, 187], [187, 123], [96, 77], [77, 90], [90, 96],\n  [65, 55], [55, 107], [107, 65], [89, 90], [90, 180], [180, 89],\n  [101, 100], [100, 120], [120, 101], [63, 105], [105, 104], [104, 63],\n  [93, 137], [137, 227], [227, 93], [15, 86], [86, 85], [85, 15],\n  [129, 102], [102, 49], [49, 129], [14, 87], [87, 86], [86, 14],\n  [55, 8], [8, 9], [9, 55], [100, 47], [47, 121], [121, 100],\n  [145, 23], [23, 22], [22, 145], [88, 89], [89, 179], [179, 88],\n  [6, 122], [122, 196], [196, 6], [88, 95], [95, 96], [96, 88],\n  [138, 172], [172, 136], [136, 138], [215, 58], [58, 172], [172, 215],\n  [115, 48], [48, 219], [219, 115], [42, 80], [80, 81], [81, 42],\n  [195, 3], [3, 51], [51, 195], [43, 146], [146, 61], [61, 43],\n  [171, 175], [175, 199], [199, 171], [81, 82], [82, 38], [38, 81],\n  [53, 46], [46, 225], [225, 53], [144, 163], [163, 110], [110, 144],\n  [52, 65], [65, 66], [66, 52], [229, 228], [228, 117], [117, 229],\n  [34, 127], [127, 234], [234, 34], [107, 108], [108, 69], [69, 107],\n  [109, 108], [108, 151], [151, 109], [48, 64], [64, 235], [235, 48],\n  [62, 78], [78, 191], [191, 62], [129, 209], [209, 126], [126, 129],\n  [111, 35], [35, 143], [143, 111], [117, 123], [123, 50], [50, 117],\n  [222, 65], [65, 52], [52, 222], [19, 125], [125, 141], [141, 19],\n  [221, 55], [55, 65], [65, 221], [3, 195], [195, 197], [197, 3],\n  [25, 7], [7, 33], [33, 25], [220, 237], [237, 44], [44, 220],\n  [70, 71], [71, 139], [139, 70], [122, 193], [193, 245], [245, 122],\n  [247, 130], [130, 33], [33, 247], [71, 21], [21, 162], [162, 71],\n  [170, 169], [169, 150], [150, 170], [188, 174], [174, 196], [196, 188],\n  [216, 186], [186, 92], [92, 216], [2, 97], [97, 167], [167, 2],\n  [141, 125], [125, 241], [241, 141], [164, 167], [167, 37], [37, 164],\n  [72, 38], [38, 12], [12, 72], [38, 82], [82, 13], [13, 38],\n  [63, 68], [68, 71], [71, 63], [226, 35], [35, 111], [111, 226],\n  [101, 50], [50, 205], [205, 101], [206, 92], [92, 165], [165, 206],\n  [209, 198], [198, 217], [217, 209], [165, 167], [167, 97], [97, 165],\n  [220, 115], [115, 218], [218, 220], [133, 112], [112, 243], [243, 133],\n  [239, 238], [238, 241], [241, 239], [214, 135], [135, 169], [169, 214],\n  [190, 173], [173, 133], [133, 190], [171, 208], [208, 32], [32, 171],\n  [125, 44], [44, 237], [237, 125], [86, 87], [87, 178], [178, 86],\n  [85, 86], [86, 179], [179, 85], [84, 85], [85, 180], [180, 84],\n  [83, 84], [84, 181], [181, 83], [201, 83], [83, 182], [182, 201],\n  [137, 93], [93, 132], [132, 137], [76, 62], [62, 183], [183, 76],\n  [61, 76], [76, 184], [184, 61], [57, 61], [61, 185], [185, 57],\n  [212, 57], [57, 186], [186, 212], [214, 207], [207, 187], [187, 214],\n  [34, 143], [143, 156], [156, 34], [79, 239], [239, 237], [237, 79],\n  [123, 137], [137, 177], [177, 123], [44, 1], [1, 4], [4, 44],\n  [201, 194], [194, 32], [32, 201], [64, 102], [102, 129], [129, 64],\n  [213, 215], [215, 138], [138, 213], [59, 166], [166, 219], [219, 59],\n  [242, 99], [99, 97], [97, 242], [2, 94], [94, 141], [141, 2],\n  [75, 59], [59, 235], [235, 75], [24, 110], [110, 228], [228, 24],\n  [25, 130], [130, 226], [226, 25], [23, 24], [24, 229], [229, 23],\n  [22, 23], [23, 230], [230, 22], [26, 22], [22, 231], [231, 26],\n  [112, 26], [26, 232], [232, 112], [189, 190], [190, 243], [243, 189],\n  [221, 56], [56, 190], [190, 221], [28, 56], [56, 221], [221, 28],\n  [27, 28], [28, 222], [222, 27], [29, 27], [27, 223], [223, 29],\n  [30, 29], [29, 224], [224, 30], [247, 30], [30, 225], [225, 247],\n  [238, 79], [79, 20], [20, 238], [166, 59], [59, 75], [75, 166],\n  [60, 75], [75, 240], [240, 60], [147, 177], [177, 215], [215, 147],\n  [20, 79], [79, 166], [166, 20], [187, 147], [147, 213], [213, 187],\n  [112, 233], [233, 244], [244, 112], [233, 128], [128, 245], [245, 233],\n  [128, 114], [114, 188], [188, 128], [114, 217], [217, 174], [174, 114],\n  [131, 115], [115, 220], [220, 131], [217, 198], [198, 236], [236, 217],\n  [198, 131], [131, 134], [134, 198], [177, 132], [132, 58], [58, 177],\n  [143, 35], [35, 124], [124, 143], [110, 163], [163, 7], [7, 110],\n  [228, 110], [110, 25], [25, 228], [356, 389], [389, 368], [368, 356],\n  [11, 302], [302, 267], [267, 11], [452, 350], [350, 349], [349, 452],\n  [302, 303], [303, 269], [269, 302], [357, 343], [343, 277], [277, 357],\n  [452, 453], [453, 357], [357, 452], [333, 332], [332, 297], [297, 333],\n  [175, 152], [152, 377], [377, 175], [347, 348], [348, 330], [330, 347],\n  [303, 304], [304, 270], [270, 303], [9, 336], [336, 337], [337, 9],\n  [278, 279], [279, 360], [360, 278], [418, 262], [262, 431], [431, 418],\n  [304, 408], [408, 409], [409, 304], [310, 415], [415, 407], [407, 310],\n  [270, 409], [409, 410], [410, 270], [450, 348], [348, 347], [347, 450],\n  [422, 430], [430, 434], [434, 422], [313, 314], [314, 17], [17, 313],\n  [306, 307], [307, 375], [375, 306], [387, 388], [388, 260], [260, 387],\n  [286, 414], [414, 398], [398, 286], [335, 406], [406, 418], [418, 335],\n  [364, 367], [367, 416], [416, 364], [423, 358], [358, 327], [327, 423],\n  [251, 284], [284, 298], [298, 251], [281, 5], [5, 4], [4, 281],\n  [373, 374], [374, 253], [253, 373], [307, 320], [320, 321], [321, 307],\n  [425, 427], [427, 411], [411, 425], [421, 313], [313, 18], [18, 421],\n  [321, 405], [405, 406], [406, 321], [320, 404], [404, 405], [405, 320],\n  [315, 16], [16, 17], [17, 315], [426, 425], [425, 266], [266, 426],\n  [377, 400], [400, 369], [369, 377], [322, 391], [391, 269], [269, 322],\n  [417, 465], [465, 464], [464, 417], [386, 257], [257, 258], [258, 386],\n  [466, 260], [260, 388], [388, 466], [456, 399], [399, 419], [419, 456],\n  [284, 332], [332, 333], [333, 284], [417, 285], [285, 8], [8, 417],\n  [346, 340], [340, 261], [261, 346], [413, 441], [441, 285], [285, 413],\n  [327, 460], [460, 328], [328, 327], [355, 371], [371, 329], [329, 355],\n  [392, 439], [439, 438], [438, 392], [382, 341], [341, 256], [256, 382],\n  [429, 420], [420, 360], [360, 429], [364, 394], [394, 379], [379, 364],\n  [277, 343], [343, 437], [437, 277], [443, 444], [444, 283], [283, 443],\n  [275, 440], [440, 363], [363, 275], [431, 262], [262, 369], [369, 431],\n  [297, 338], [338, 337], [337, 297], [273, 375], [375, 321], [321, 273],\n  [450, 451], [451, 349], [349, 450], [446, 342], [342, 467], [467, 446],\n  [293, 334], [334, 282], [282, 293], [458, 461], [461, 462], [462, 458],\n  [276, 353], [353, 383], [383, 276], [308, 324], [324, 325], [325, 308],\n  [276, 300], [300, 293], [293, 276], [372, 345], [345, 447], [447, 372],\n  [352, 345], [345, 340], [340, 352], [274, 1], [1, 19], [19, 274],\n  [456, 248], [248, 281], [281, 456], [436, 427], [427, 425], [425, 436],\n  [381, 256], [256, 252], [252, 381], [269, 391], [391, 393], [393, 269],\n  [200, 199], [199, 428], [428, 200], [266, 330], [330, 329], [329, 266],\n  [287, 273], [273, 422], [422, 287], [250, 462], [462, 328], [328, 250],\n  [258, 286], [286, 384], [384, 258], [265, 353], [353, 342], [342, 265],\n  [387, 259], [259, 257], [257, 387], [424, 431], [431, 430], [430, 424],\n  [342, 353], [353, 276], [276, 342], [273, 335], [335, 424], [424, 273],\n  [292, 325], [325, 307], [307, 292], [366, 447], [447, 345], [345, 366],\n  [271, 303], [303, 302], [302, 271], [423, 266], [266, 371], [371, 423],\n  [294, 455], [455, 460], [460, 294], [279, 278], [278, 294], [294, 279],\n  [271, 272], [272, 304], [304, 271], [432, 434], [434, 427], [427, 432],\n  [272, 407], [407, 408], [408, 272], [394, 430], [430, 431], [431, 394],\n  [395, 369], [369, 400], [400, 395], [334, 333], [333, 299], [299, 334],\n  [351, 417], [417, 168], [168, 351], [352, 280], [280, 411], [411, 352],\n  [325, 319], [319, 320], [320, 325], [295, 296], [296, 336], [336, 295],\n  [319, 403], [403, 404], [404, 319], [330, 348], [348, 349], [349, 330],\n  [293, 298], [298, 333], [333, 293], [323, 454], [454, 447], [447, 323],\n  [15, 16], [16, 315], [315, 15], [358, 429], [429, 279], [279, 358],\n  [14, 15], [15, 316], [316, 14], [285, 336], [336, 9], [9, 285],\n  [329, 349], [349, 350], [350, 329], [374, 380], [380, 252], [252, 374],\n  [318, 402], [402, 403], [403, 318], [6, 197], [197, 419], [419, 6],\n  [318, 319], [319, 325], [325, 318], [367, 364], [364, 365], [365, 367],\n  [435, 367], [367, 397], [397, 435], [344, 438], [438, 439], [439, 344],\n  [272, 271], [271, 311], [311, 272], [195, 5], [5, 281], [281, 195],\n  [273, 287], [287, 291], [291, 273], [396, 428], [428, 199], [199, 396],\n  [311, 271], [271, 268], [268, 311], [283, 444], [444, 445], [445, 283],\n  [373, 254], [254, 339], [339, 373], [282, 334], [334, 296], [296, 282],\n  [449, 347], [347, 346], [346, 449], [264, 447], [447, 454], [454, 264],\n  [336, 296], [296, 299], [299, 336], [338, 10], [10, 151], [151, 338],\n  [278, 439], [439, 455], [455, 278], [292, 407], [407, 415], [415, 292],\n  [358, 371], [371, 355], [355, 358], [340, 345], [345, 372], [372, 340],\n  [346, 347], [347, 280], [280, 346], [442, 443], [443, 282], [282, 442],\n  [19, 94], [94, 370], [370, 19], [441, 442], [442, 295], [295, 441],\n  [248, 419], [419, 197], [197, 248], [263, 255], [255, 359], [359, 263],\n  [440, 275], [275, 274], [274, 440], [300, 383], [383, 368], [368, 300],\n  [351, 412], [412, 465], [465, 351], [263, 467], [467, 466], [466, 263],\n  [301, 368], [368, 389], [389, 301], [395, 378], [378, 379], [379, 395],\n  [412, 351], [351, 419], [419, 412], [436, 426], [426, 322], [322, 436],\n  [2, 164], [164, 393], [393, 2], [370, 462], [462, 461], [461, 370],\n  [164, 0], [0, 267], [267, 164], [302, 11], [11, 12], [12, 302],\n  [268, 12], [12, 13], [13, 268], [293, 300], [300, 301], [301, 293],\n  [446, 261], [261, 340], [340, 446], [330, 266], [266, 425], [425, 330],\n  [426, 423], [423, 391], [391, 426], [429, 355], [355, 437], [437, 429],\n  [391, 327], [327, 326], [326, 391], [440, 457], [457, 438], [438, 440],\n  [341, 382], [382, 362], [362, 341], [459, 457], [457, 461], [461, 459],\n  [434, 430], [430, 394], [394, 434], [414, 463], [463, 362], [362, 414],\n  [396, 369], [369, 262], [262, 396], [354, 461], [461, 457], [457, 354],\n  [316, 403], [403, 402], [402, 316], [315, 404], [404, 403], [403, 315],\n  [314, 405], [405, 404], [404, 314], [313, 406], [406, 405], [405, 313],\n  [421, 418], [418, 406], [406, 421], [366, 401], [401, 361], [361, 366],\n  [306, 408], [408, 407], [407, 306], [291, 409], [409, 408], [408, 291],\n  [287, 410], [410, 409], [409, 287], [432, 436], [436, 410], [410, 432],\n  [434, 416], [416, 411], [411, 434], [264, 368], [368, 383], [383, 264],\n  [309, 438], [438, 457], [457, 309], [352, 376], [376, 401], [401, 352],\n  [274, 275], [275, 4], [4, 274], [421, 428], [428, 262], [262, 421],\n  [294, 327], [327, 358], [358, 294], [433, 416], [416, 367], [367, 433],\n  [289, 455], [455, 439], [439, 289], [462, 370], [370, 326], [326, 462],\n  [2, 326], [326, 370], [370, 2], [305, 460], [460, 455], [455, 305],\n  [254, 449], [449, 448], [448, 254], [255, 261], [261, 446], [446, 255],\n  [253, 450], [450, 449], [449, 253], [252, 451], [451, 450], [450, 252],\n  [256, 452], [452, 451], [451, 256], [341, 453], [453, 452], [452, 341],\n  [413, 464], [464, 463], [463, 413], [441, 413], [413, 414], [414, 441],\n  [258, 442], [442, 441], [441, 258], [257, 443], [443, 442], [442, 257],\n  [259, 444], [444, 443], [443, 259], [260, 445], [445, 444], [444, 260],\n  [467, 342], [342, 445], [445, 467], [459, 458], [458, 250], [250, 459],\n  [289, 392], [392, 290], [290, 289], [290, 328], [328, 460], [460, 290],\n  [376, 433], [433, 435], [435, 376], [250, 290], [290, 392], [392, 250],\n  [411, 416], [416, 433], [433, 411], [341, 463], [463, 464], [464, 341],\n  [453, 464], [464, 465], [465, 453], [357, 465], [465, 412], [412, 357],\n  [343, 412], [412, 399], [399, 343], [360, 363], [363, 440], [440, 360],\n  [437, 399], [399, 456], [456, 437], [420, 456], [456, 363], [363, 420],\n  [401, 435], [435, 288], [288, 401], [372, 383], [383, 353], [353, 372],\n  [339, 255], [255, 249], [249, 339], [448, 261], [261, 255], [255, 448],\n  [133, 243], [243, 190], [190, 133], [133, 155], [155, 112], [112, 133],\n  [33, 246], [246, 247], [247, 33], [33, 130], [130, 25], [25, 33],\n  [398, 384], [384, 286], [286, 398], [362, 398], [398, 414], [414, 362],\n  [362, 463], [463, 341], [341, 362], [263, 359], [359, 467], [467, 263],\n  [263, 249], [249, 255], [255, 263], [466, 467], [467, 260], [260, 466],\n  [75, 60], [60, 166], [166, 75], [238, 239], [239, 79], [79, 238],\n  [162, 127], [127, 139], [139, 162], [72, 11], [11, 37], [37, 72],\n  [121, 232], [232, 120], [120, 121], [73, 72], [72, 39], [39, 73],\n  [114, 128], [128, 47], [47, 114], [233, 232], [232, 128], [128, 233],\n  [103, 104], [104, 67], [67, 103], [152, 175], [175, 148], [148, 152],\n  [119, 118], [118, 101], [101, 119], [74, 73], [73, 40], [40, 74],\n  [107, 9], [9, 108], [108, 107], [49, 48], [48, 131], [131, 49],\n  [32, 194], [194, 211], [211, 32], [184, 74], [74, 185], [185, 184],\n  [191, 80], [80, 183], [183, 191], [185, 40], [40, 186], [186, 185],\n  [119, 230], [230, 118], [118, 119], [210, 202], [202, 214], [214, 210],\n  [84, 83], [83, 17], [17, 84], [77, 76], [76, 146], [146, 77],\n  [161, 160], [160, 30], [30, 161], [190, 56], [56, 173], [173, 190],\n  [182, 106], [106, 194], [194, 182], [138, 135], [135, 192], [192, 138],\n  [129, 203], [203, 98], [98, 129], [54, 21], [21, 68], [68, 54],\n  [5, 51], [51, 4], [4, 5], [145, 144], [144, 23], [23, 145],\n  [90, 77], [77, 91], [91, 90], [207, 205], [205, 187], [187, 207],\n  [83, 201], [201, 18], [18, 83], [181, 91], [91, 182], [182, 181],\n  [180, 90], [90, 181], [181, 180], [16, 85], [85, 17], [17, 16],\n  [205, 206], [206, 36], [36, 205], [176, 148], [148, 140], [140, 176],\n  [165, 92], [92, 39], [39, 165], [245, 193], [193, 244], [244, 245],\n  [27, 159], [159, 28], [28, 27], [30, 247], [247, 161], [161, 30],\n  [174, 236], [236, 196], [196, 174], [103, 54], [54, 104], [104, 103],\n  [55, 193], [193, 8], [8, 55], [111, 117], [117, 31], [31, 111],\n  [221, 189], [189, 55], [55, 221], [240, 98], [98, 99], [99, 240],\n  [142, 126], [126, 100], [100, 142], [219, 166], [166, 218], [218, 219],\n  [112, 155], [155, 26], [26, 112], [198, 209], [209, 131], [131, 198],\n  [169, 135], [135, 150], [150, 169], [114, 47], [47, 217], [217, 114],\n  [224, 223], [223, 53], [53, 224], [220, 45], [45, 134], [134, 220],\n  [32, 211], [211, 140], [140, 32], [109, 67], [67, 108], [108, 109],\n  [146, 43], [43, 91], [91, 146], [231, 230], [230, 120], [120, 231],\n  [113, 226], [226, 247], [247, 113], [105, 63], [63, 52], [52, 105],\n  [241, 238], [238, 242], [242, 241], [124, 46], [46, 156], [156, 124],\n  [95, 78], [78, 96], [96, 95], [70, 46], [46, 63], [63, 70],\n  [116, 143], [143, 227], [227, 116], [116, 123], [123, 111], [111, 116],\n  [1, 44], [44, 19], [19, 1], [3, 236], [236, 51], [51, 3],\n  [207, 216], [216, 205], [205, 207], [26, 154], [154, 22], [22, 26],\n  [165, 39], [39, 167], [167, 165], [199, 200], [200, 208], [208, 199],\n  [101, 36], [36, 100], [100, 101], [43, 57], [57, 202], [202, 43],\n  [242, 20], [20, 99], [99, 242], [56, 28], [28, 157], [157, 56],\n  [124, 35], [35, 113], [113, 124], [29, 160], [160, 27], [27, 29],\n  [211, 204], [204, 210], [210, 211], [124, 113], [113, 46], [46, 124],\n  [106, 43], [43, 204], [204, 106], [96, 62], [62, 77], [77, 96],\n  [227, 137], [137, 116], [116, 227], [73, 41], [41, 72], [72, 73],\n  [36, 203], [203, 142], [142, 36], [235, 64], [64, 240], [240, 235],\n  [48, 49], [49, 64], [64, 48], [42, 41], [41, 74], [74, 42],\n  [214, 212], [212, 207], [207, 214], [183, 42], [42, 184], [184, 183],\n  [210, 169], [169, 211], [211, 210], [140, 170], [170, 176], [176, 140],\n  [104, 105], [105, 69], [69, 104], [193, 122], [122, 168], [168, 193],\n  [50, 123], [123, 187], [187, 50], [89, 96], [96, 90], [90, 89],\n  [66, 65], [65, 107], [107, 66], [179, 89], [89, 180], [180, 179],\n  [119, 101], [101, 120], [120, 119], [68, 63], [63, 104], [104, 68],\n  [234, 93], [93, 227], [227, 234], [16, 15], [15, 85], [85, 16],\n  [209, 129], [129, 49], [49, 209], [15, 14], [14, 86], [86, 15],\n  [107, 55], [55, 9], [9, 107], [120, 100], [100, 121], [121, 120],\n  [153, 145], [145, 22], [22, 153], [178, 88], [88, 179], [179, 178],\n  [197, 6], [6, 196], [196, 197], [89, 88], [88, 96], [96, 89],\n  [135, 138], [138, 136], [136, 135], [138, 215], [215, 172], [172, 138],\n  [218, 115], [115, 219], [219, 218], [41, 42], [42, 81], [81, 41],\n  [5, 195], [195, 51], [51, 5], [57, 43], [43, 61], [61, 57],\n  [208, 171], [171, 199], [199, 208], [41, 81], [81, 38], [38, 41],\n  [224, 53], [53, 225], [225, 224], [24, 144], [144, 110], [110, 24],\n  [105, 52], [52, 66], [66, 105], [118, 229], [229, 117], [117, 118],\n  [227, 34], [34, 234], [234, 227], [66, 107], [107, 69], [69, 66],\n  [10, 109], [109, 151], [151, 10], [219, 48], [48, 235], [235, 219],\n  [183, 62], [62, 191], [191, 183], [142, 129], [129, 126], [126, 142],\n  [116, 111], [111, 143], [143, 116], [118, 117], [117, 50], [50, 118],\n  [223, 222], [222, 52], [52, 223], [94, 19], [19, 141], [141, 94],\n  [222, 221], [221, 65], [65, 222], [196, 3], [3, 197], [197, 196],\n  [45, 220], [220, 44], [44, 45], [156, 70], [70, 139], [139, 156],\n  [188, 122], [122, 245], [245, 188], [139, 71], [71, 162], [162, 139],\n  [149, 170], [170, 150], [150, 149], [122, 188], [188, 196], [196, 122],\n  [206, 216], [216, 92], [92, 206], [164, 2], [2, 167], [167, 164],\n  [242, 141], [141, 241], [241, 242], [0, 164], [164, 37], [37, 0],\n  [11, 72], [72, 12], [12, 11], [12, 38], [38, 13], [13, 12],\n  [70, 63], [63, 71], [71, 70], [31, 226], [226, 111], [111, 31],\n  [36, 101], [101, 205], [205, 36], [203, 206], [206, 165], [165, 203],\n  [126, 209], [209, 217], [217, 126], [98, 165], [165, 97], [97, 98],\n  [237, 220], [220, 218], [218, 237], [237, 239], [239, 241], [241, 237],\n  [210, 214], [214, 169], [169, 210], [140, 171], [171, 32], [32, 140],\n  [241, 125], [125, 237], [237, 241], [179, 86], [86, 178], [178, 179],\n  [180, 85], [85, 179], [179, 180], [181, 84], [84, 180], [180, 181],\n  [182, 83], [83, 181], [181, 182], [194, 201], [201, 182], [182, 194],\n  [177, 137], [137, 132], [132, 177], [184, 76], [76, 183], [183, 184],\n  [185, 61], [61, 184], [184, 185], [186, 57], [57, 185], [185, 186],\n  [216, 212], [212, 186], [186, 216], [192, 214], [214, 187], [187, 192],\n  [139, 34], [34, 156], [156, 139], [218, 79], [79, 237], [237, 218],\n  [147, 123], [123, 177], [177, 147], [45, 44], [44, 4], [4, 45],\n  [208, 201], [201, 32], [32, 208], [98, 64], [64, 129], [129, 98],\n  [192, 213], [213, 138], [138, 192], [235, 59], [59, 219], [219, 235],\n  [141, 242], [242, 97], [97, 141], [97, 2], [2, 141], [141, 97],\n  [240, 75], [75, 235], [235, 240], [229, 24], [24, 228], [228, 229],\n  [31, 25], [25, 226], [226, 31], [230, 23], [23, 229], [229, 230],\n  [231, 22], [22, 230], [230, 231], [232, 26], [26, 231], [231, 232],\n  [233, 112], [112, 232], [232, 233], [244, 189], [189, 243], [243, 244],\n  [189, 221], [221, 190], [190, 189], [222, 28], [28, 221], [221, 222],\n  [223, 27], [27, 222], [222, 223], [224, 29], [29, 223], [223, 224],\n  [225, 30], [30, 224], [224, 225], [113, 247], [247, 225], [225, 113],\n  [99, 60], [60, 240], [240, 99], [213, 147], [147, 215], [215, 213],\n  [60, 20], [20, 166], [166, 60], [192, 187], [187, 213], [213, 192],\n  [243, 112], [112, 244], [244, 243], [244, 233], [233, 245], [245, 244],\n  [245, 128], [128, 188], [188, 245], [188, 114], [114, 174], [174, 188],\n  [134, 131], [131, 220], [220, 134], [174, 217], [217, 236], [236, 174],\n  [236, 198], [198, 134], [134, 236], [215, 177], [177, 58], [58, 215],\n  [156, 143], [143, 124], [124, 156], [25, 110], [110, 7], [7, 25],\n  [31, 228], [228, 25], [25, 31], [264, 356], [356, 368], [368, 264],\n  [0, 11], [11, 267], [267, 0], [451, 452], [452, 349], [349, 451],\n  [267, 302], [302, 269], [269, 267], [350, 357], [357, 277], [277, 350],\n  [350, 452], [452, 357], [357, 350], [299, 333], [333, 297], [297, 299],\n  [396, 175], [175, 377], [377, 396], [280, 347], [347, 330], [330, 280],\n  [269, 303], [303, 270], [270, 269], [151, 9], [9, 337], [337, 151],\n  [344, 278], [278, 360], [360, 344], [424, 418], [418, 431], [431, 424],\n  [270, 304], [304, 409], [409, 270], [272, 310], [310, 407], [407, 272],\n  [322, 270], [270, 410], [410, 322], [449, 450], [450, 347], [347, 449],\n  [432, 422], [422, 434], [434, 432], [18, 313], [313, 17], [17, 18],\n  [291, 306], [306, 375], [375, 291], [259, 387], [387, 260], [260, 259],\n  [424, 335], [335, 418], [418, 424], [434, 364], [364, 416], [416, 434],\n  [391, 423], [423, 327], [327, 391], [301, 251], [251, 298], [298, 301],\n  [275, 281], [281, 4], [4, 275], [254, 373], [373, 253], [253, 254],\n  [375, 307], [307, 321], [321, 375], [280, 425], [425, 411], [411, 280],\n  [200, 421], [421, 18], [18, 200], [335, 321], [321, 406], [406, 335],\n  [321, 320], [320, 405], [405, 321], [314, 315], [315, 17], [17, 314],\n  [423, 426], [426, 266], [266, 423], [396, 377], [377, 369], [369, 396],\n  [270, 322], [322, 269], [269, 270], [413, 417], [417, 464], [464, 413],\n  [385, 386], [386, 258], [258, 385], [248, 456], [456, 419], [419, 248],\n  [298, 284], [284, 333], [333, 298], [168, 417], [417, 8], [8, 168],\n  [448, 346], [346, 261], [261, 448], [417, 413], [413, 285], [285, 417],\n  [326, 327], [327, 328], [328, 326], [277, 355], [355, 329], [329, 277],\n  [309, 392], [392, 438], [438, 309], [381, 382], [382, 256], [256, 381],\n  [279, 429], [429, 360], [360, 279], [365, 364], [364, 379], [379, 365],\n  [355, 277], [277, 437], [437, 355], [282, 443], [443, 283], [283, 282],\n  [281, 275], [275, 363], [363, 281], [395, 431], [431, 369], [369, 395],\n  [299, 297], [297, 337], [337, 299], [335, 273], [273, 321], [321, 335],\n  [348, 450], [450, 349], [349, 348], [359, 446], [446, 467], [467, 359],\n  [283, 293], [293, 282], [282, 283], [250, 458], [458, 462], [462, 250],\n  [300, 276], [276, 383], [383, 300], [292, 308], [308, 325], [325, 292],\n  [283, 276], [276, 293], [293, 283], [264, 372], [372, 447], [447, 264],\n  [346, 352], [352, 340], [340, 346], [354, 274], [274, 19], [19, 354],\n  [363, 456], [456, 281], [281, 363], [426, 436], [436, 425], [425, 426],\n  [380, 381], [381, 252], [252, 380], [267, 269], [269, 393], [393, 267],\n  [421, 200], [200, 428], [428, 421], [371, 266], [266, 329], [329, 371],\n  [432, 287], [287, 422], [422, 432], [290, 250], [250, 328], [328, 290],\n  [385, 258], [258, 384], [384, 385], [446, 265], [265, 342], [342, 446],\n  [386, 387], [387, 257], [257, 386], [422, 424], [424, 430], [430, 422],\n  [445, 342], [342, 276], [276, 445], [422, 273], [273, 424], [424, 422],\n  [306, 292], [292, 307], [307, 306], [352, 366], [366, 345], [345, 352],\n  [268, 271], [271, 302], [302, 268], [358, 423], [423, 371], [371, 358],\n  [327, 294], [294, 460], [460, 327], [331, 279], [279, 294], [294, 331],\n  [303, 271], [271, 304], [304, 303], [436, 432], [432, 427], [427, 436],\n  [304, 272], [272, 408], [408, 304], [395, 394], [394, 431], [431, 395],\n  [378, 395], [395, 400], [400, 378], [296, 334], [334, 299], [299, 296],\n  [6, 351], [351, 168], [168, 6], [376, 352], [352, 411], [411, 376],\n  [307, 325], [325, 320], [320, 307], [285, 295], [295, 336], [336, 285],\n  [320, 319], [319, 404], [404, 320], [329, 330], [330, 349], [349, 329],\n  [334, 293], [293, 333], [333, 334], [366, 323], [323, 447], [447, 366],\n  [316, 15], [15, 315], [315, 316], [331, 358], [358, 279], [279, 331],\n  [317, 14], [14, 316], [316, 317], [8, 285], [285, 9], [9, 8],\n  [277, 329], [329, 350], [350, 277], [253, 374], [374, 252], [252, 253],\n  [319, 318], [318, 403], [403, 319], [351, 6], [6, 419], [419, 351],\n  [324, 318], [318, 325], [325, 324], [397, 367], [367, 365], [365, 397],\n  [288, 435], [435, 397], [397, 288], [278, 344], [344, 439], [439, 278],\n  [310, 272], [272, 311], [311, 310], [248, 195], [195, 281], [281, 248],\n  [375, 273], [273, 291], [291, 375], [175, 396], [396, 199], [199, 175],\n  [312, 311], [311, 268], [268, 312], [276, 283], [283, 445], [445, 276],\n  [390, 373], [373, 339], [339, 390], [295, 282], [282, 296], [296, 295],\n  [448, 449], [449, 346], [346, 448], [356, 264], [264, 454], [454, 356],\n  [337, 336], [336, 299], [299, 337], [337, 338], [338, 151], [151, 337],\n  [294, 278], [278, 455], [455, 294], [308, 292], [292, 415], [415, 308],\n  [429, 358], [358, 355], [355, 429], [265, 340], [340, 372], [372, 265],\n  [352, 346], [346, 280], [280, 352], [295, 442], [442, 282], [282, 295],\n  [354, 19], [19, 370], [370, 354], [285, 441], [441, 295], [295, 285],\n  [195, 248], [248, 197], [197, 195], [457, 440], [440, 274], [274, 457],\n  [301, 300], [300, 368], [368, 301], [417, 351], [351, 465], [465, 417],\n  [251, 301], [301, 389], [389, 251], [394, 395], [395, 379], [379, 394],\n  [399, 412], [412, 419], [419, 399], [410, 436], [436, 322], [322, 410],\n  [326, 2], [2, 393], [393, 326], [354, 370], [370, 461], [461, 354],\n  [393, 164], [164, 267], [267, 393], [268, 302], [302, 12], [12, 268],\n  [312, 268], [268, 13], [13, 312], [298, 293], [293, 301], [301, 298],\n  [265, 446], [446, 340], [340, 265], [280, 330], [330, 425], [425, 280],\n  [322, 426], [426, 391], [391, 322], [420, 429], [429, 437], [437, 420],\n  [393, 391], [391, 326], [326, 393], [344, 440], [440, 438], [438, 344],\n  [458, 459], [459, 461], [461, 458], [364, 434], [434, 394], [394, 364],\n  [428, 396], [396, 262], [262, 428], [274, 354], [354, 457], [457, 274],\n  [317, 316], [316, 402], [402, 317], [316, 315], [315, 403], [403, 316],\n  [315, 314], [314, 404], [404, 315], [314, 313], [313, 405], [405, 314],\n  [313, 421], [421, 406], [406, 313], [323, 366], [366, 361], [361, 323],\n  [292, 306], [306, 407], [407, 292], [306, 291], [291, 408], [408, 306],\n  [291, 287], [287, 409], [409, 291], [287, 432], [432, 410], [410, 287],\n  [427, 434], [434, 411], [411, 427], [372, 264], [264, 383], [383, 372],\n  [459, 309], [309, 457], [457, 459], [366, 352], [352, 401], [401, 366],\n  [1, 274], [274, 4], [4, 1], [418, 421], [421, 262], [262, 418],\n  [331, 294], [294, 358], [358, 331], [435, 433], [433, 367], [367, 435],\n  [392, 289], [289, 439], [439, 392], [328, 462], [462, 326], [326, 328],\n  [94, 2], [2, 370], [370, 94], [289, 305], [305, 455], [455, 289],\n  [339, 254], [254, 448], [448, 339], [359, 255], [255, 446], [446, 359],\n  [254, 253], [253, 449], [449, 254], [253, 252], [252, 450], [450, 253],\n  [252, 256], [256, 451], [451, 252], [256, 341], [341, 452], [452, 256],\n  [414, 413], [413, 463], [463, 414], [286, 441], [441, 414], [414, 286],\n  [286, 258], [258, 441], [441, 286], [258, 257], [257, 442], [442, 258],\n  [257, 259], [259, 443], [443, 257], [259, 260], [260, 444], [444, 259],\n  [260, 467], [467, 445], [445, 260], [309, 459], [459, 250], [250, 309],\n  [305, 289], [289, 290], [290, 305], [305, 290], [290, 460], [460, 305],\n  [401, 376], [376, 435], [435, 401], [309, 250], [250, 392], [392, 309],\n  [376, 411], [411, 433], [433, 376], [453, 341], [341, 464], [464, 453],\n  [357, 453], [453, 465], [465, 357], [343, 357], [357, 412], [412, 343],\n  [437, 343], [343, 399], [399, 437], [344, 360], [360, 440], [440, 344],\n  [420, 437], [437, 456], [456, 420], [360, 420], [420, 363], [363, 360],\n  [361, 401], [401, 288], [288, 361], [265, 372], [372, 353], [353, 265],\n  [390, 339], [339, 249], [249, 390], [339, 448], [448, 255], [255, 339],\n];\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n * See `facemesh.ts` for entry point\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as coords from './facemeshcoords';\nimport { constants } from '../tfjs/constants';\nimport type { Box, Point } from '../result';\nimport { env } from '../util/env';\n\nexport const createBox = (startEndTensor) => ({ startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]), endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]) });\n\nexport const disposeBox = (t) => tf.dispose([t.startPoint, t.endPoint]);\n\nexport const getBoxSize = (box): [number, number] => [Math.abs(box.endPoint[0] - box.startPoint[0]), Math.abs(box.endPoint[1] - box.startPoint[1])];\n\nexport const getBoxCenter = (box): [number, number, number] => [box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2, box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2, 1];\n\nexport const clampBox = (box, input): Box => (box ? [\n  Math.trunc(Math.max(0, box.startPoint[0])),\n  Math.trunc(Math.max(0, box.startPoint[1])),\n  Math.trunc(Math.min((input.shape[2] || 0), box.endPoint[0]) - Math.max(0, box.startPoint[0])),\n  Math.trunc(Math.min((input.shape[1] || 0), box.endPoint[1]) - Math.max(0, box.startPoint[1])),\n] : [0, 0, 0, 0]);\n\nexport const getRawBox = (box, input): Box => (box ? [\n  box.startPoint[0] / (input.shape[2] || 0),\n  box.startPoint[1] / (input.shape[1] || 0),\n  (box.endPoint[0] - box.startPoint[0]) / (input.shape[2] || 0),\n  (box.endPoint[1] - box.startPoint[1]) / (input.shape[1] || 0),\n] : [0, 0, 0, 0]);\n\nexport const scaleBoxCoordinates = (box, factor) => {\n  const startPoint: Point = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint: Point = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks, confidence: box.confidence };\n};\n\nexport const cutAndResize = (box, image, cropSize) => {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const cutBox = [box.startPoint[1] / h, box.startPoint[0] / w, box.endPoint[1] / h, box.endPoint[0] / w];\n  const crop = tf.image.cropAndResize(image, [cutBox], [0], cropSize);\n  const norm = tf.div(crop, constants.tf255);\n  tf.dispose(crop);\n  return norm;\n};\n\nexport const enlargeBox = (box, factor) => {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const halfSize: [number, number] = [factor * size[0] / 2, factor * size[1] / 2];\n  return { startPoint: [center[0] - halfSize[0], center[1] - halfSize[1]] as Point, endPoint: [center[0] + halfSize[0], center[1] + halfSize[1]] as Point, landmarks: box.landmarks, confidence: box.confidence };\n};\n\nexport const squarifyBox = (box) => {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const halfSize = Math.max(...size) / 2;\n  return { startPoint: [Math.round(centers[0] - halfSize), Math.round(centers[1] - halfSize)] as Point, endPoint: [Math.round(centers[0] + halfSize), Math.round(centers[1] + halfSize)] as Point, landmarks: box.landmarks, confidence: box.confidence };\n};\n\nexport const calculateLandmarksBoundingBox = (landmarks) => {\n  const x = landmarks.map((d) => d[0]);\n  const y = landmarks.map((d) => d[1]);\n  return { startPoint: [Math.min(...x), Math.min(...y)] as Point, endPoint: [Math.max(...x), Math.max(...y)] as Point, landmarks };\n};\n\nexport const fixedRotationMatrix = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n\nexport const normalizeRadians = (angle) => angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n\nexport const computeRotation = (point1, point2) => normalizeRadians(Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]));\n\nexport const radToDegrees = (rad) => rad * 180 / Math.PI;\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport const dot = (v1: number[], v2: number[]) => {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) product += v1[i] * v2[i];\n  return product;\n};\n\nexport const getColumnFrom2DArr = (arr, columnIndex) => {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) column.push(arr[i][columnIndex]);\n  return column;\n};\n\nexport const multiplyTransformMatrices = (mat1, mat2) => {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n  }\n  return product;\n};\n\nexport const buildRotationMatrix = (rotation, center) => {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n};\n\nexport const invertTransformMatrix = (matrix) => {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [-dot(rotationComponent[0], translationComponent), -dot(rotationComponent[1], translationComponent)];\n  return [rotationComponent[0].concat(invertedTranslation[0]), rotationComponent[1].concat(invertedTranslation[1]), [0, 0, 1]];\n};\n\nexport const rotatePoint = (homogeneousCoordinate, rotationMatrix) => [dot(homogeneousCoordinate, rotationMatrix[0]), dot(homogeneousCoordinate, rotationMatrix[1])];\n\nexport const xyDistanceBetweenPoints = (a, b) => Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n\nexport function generateAnchors(inputSize) {\n  const spec = inputSize === 192\n    ? { strides: [4], anchors: [1] } // facemesh-detector\n    : { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] }; // blazeface\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) anchors.push([anchorX, anchorY]);\n      }\n    }\n  }\n  return anchors;\n}\n\nexport function transformRawCoords(coordsRaw, box, angle, rotationMatrix, inputSize) {\n  const boxSize = getBoxSize(box);\n  const coordsScaled = coordsRaw.map((coord) => ([ // scaled around zero-point\n    (boxSize[0] / inputSize) * (coord[0] - (inputSize / 2)),\n    (boxSize[1] / inputSize) * (coord[1] - (inputSize / 2)),\n    (coord[2] || 0),\n  ]));\n  const largeAngle = angle && (angle !== 0) && (Math.abs(angle) > 0.2);\n  const coordsRotationMatrix = largeAngle ? buildRotationMatrix(angle, [0, 0]) : fixedRotationMatrix;\n  const coordsRotated = largeAngle ? coordsScaled.map((coord) => ([...rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n  const inverseRotationMatrix = largeAngle ? invertTransformMatrix(rotationMatrix) : fixedRotationMatrix;\n  const boxCenter = getBoxCenter(box);\n  const offsets = [dot(boxCenter, inverseRotationMatrix[0]), dot(boxCenter, inverseRotationMatrix[1])];\n  return coordsRotated.map((coord) => ([\n    Math.trunc(coord[0] + offsets[0]),\n    Math.trunc(coord[1] + offsets[1]),\n    Math.trunc(coord[2] || 0),\n  ]));\n}\n\nexport function correctFaceRotation(rotate, box, input, inputSize) {\n  const symmetryLine = (box.landmarks.length >= coords.meshLandmarks.count)\n    ? coords.meshLandmarks.symmetryLine\n    : coords.blazeFaceLandmarks.symmetryLine;\n  let angle = 0; // default\n  let rotationMatrix = fixedRotationMatrix; // default\n  let face; // default\n\n  if (rotate && env.kernels.includes('rotatewithoffset')) { // rotateWithOffset is not defined for tfjs-node\n    angle = computeRotation(box.landmarks[symmetryLine[0]], box.landmarks[symmetryLine[1]]);\n    const largeAngle = angle && (angle !== 0) && (Math.abs(angle) > 0.2);\n    if (largeAngle) { // perform rotation only if angle is sufficiently high\n      const center: Point = getBoxCenter(box);\n      const centerRaw: Point = [center[0] / input.shape[2], center[1] / input.shape[1]];\n      const rotated = tf.image.rotateWithOffset(input, angle, 0, centerRaw);\n      rotationMatrix = buildRotationMatrix(-angle, center);\n      face = cutAndResize(box, rotated, [inputSize, inputSize]);\n      tf.dispose(rotated);\n    } else {\n      face = cutAndResize(box, input, [inputSize, inputSize]);\n    }\n  } else {\n    face = cutAndResize(box, input, [inputSize, inputSize]);\n  }\n  return [angle, rotationMatrix, face];\n}\n\nexport const findFaceCenter = (mesh) => {\n  const x = mesh.map((m) => m[0]);\n  const y = mesh.map((m) => m[1]);\n  // weighted center\n  /*\n  const sum = (arr: number[]) => arr.reduce((prev, curr) => prev + curr, 0);\n  return [sum(x) / mesh.length, sum(y) / mesh.length];\n  */\n  // absolute center\n  return [Math.min(...x) + (Math.max(...x) - Math.min(...x)) / 2, Math.min(...y) + (Math.max(...y) - Math.min(...y)) / 2];\n};\n\nexport const calculateFaceBox = (mesh, previousBox) => {\n  const center = findFaceCenter(mesh);\n  const boxSize = getBoxSize(previousBox);\n  const calculatedBox = {\n    startPoint: [center[0] - boxSize[0] / 2, center[1] - boxSize[1] / 2] as Point,\n    endPoint: [center[0] + boxSize[0] / 2, center[1] + boxSize[1] / 2] as Point,\n  };\n  return calculatedBox;\n};\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n * See `facemesh.ts` for entry point\n */\n\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as util from './facemeshutil';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport type { Config } from '../config';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport { env } from '../util/env';\nimport type { Point } from '../result';\n\nconst keypointsCount = 6;\nconst faceBoxScaleFactor = 1.4;\nlet model: GraphModel | null;\nlet anchors: Tensor | null = null;\nlet inputSize = 0;\nlet inputSizeT: Tensor | null = null;\n\ntype DetectBox = { startPoint: Point, endPoint: Point, landmarks: Array<Point>, confidence: number };\n\nexport const size = () => inputSize;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.detector?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  inputSizeT = tf.scalar(inputSize, 'int32') as Tensor;\n  anchors = tf.tensor2d(util.generateAnchors(inputSize)) as Tensor;\n  return model;\n}\n\nfunction decodeBoxes(boxOutputs: Tensor) {\n  const t: Record<string, Tensor> = {};\n  t.boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  t.centers = tf.add(t.boxStarts, anchors);\n  t.boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  t.boxSizesNormalized = tf.div(t.boxSizes, inputSizeT);\n  t.centersNormalized = tf.div(t.centers, inputSizeT);\n  t.halfBoxSize = tf.div(t.boxSizesNormalized, constants.tf2);\n  t.starts = tf.sub(t.centersNormalized, t.halfBoxSize);\n  t.ends = tf.add(t.centersNormalized, t.halfBoxSize);\n  t.startNormalized = tf.mul(t.starts, inputSizeT);\n  t.endNormalized = tf.mul(t.ends, inputSizeT);\n  const boxes = tf.concat2d([t.startNormalized, t.endNormalized], 1);\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return boxes;\n}\n\nexport async function getBoxes(inputImage: Tensor, config: Config) {\n  // sanity check on input\n  if ((!inputImage) || (inputImage['isDisposedInternal']) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return [];\n  const t: Record<string, Tensor> = {};\n  t.resized = tf.image.resizeBilinear(inputImage, [inputSize, inputSize]);\n  t.div = tf.div(t.resized, constants.tf127);\n  t.normalized = tf.sub(t.div, constants.tf05);\n  const res = model?.execute(t.normalized) as Tensor[];\n  if (Array.isArray(res) && res.length > 2) { // pinto converted model?\n    const sorted = res.sort((a, b) => a.size - b.size);\n    t.concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n    t.concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n    t.concat = tf.concat([t.concat512, t.concat384], 1);\n    t.batch = tf.squeeze(t.concat, 0);\n  } else if (Array.isArray(res)) { // new facemesh-detection tfhub model\n    t.batch = tf.squeeze(res[0]);\n  } else { // original blazeface tfhub model\n    t.batch = tf.squeeze(res);\n  }\n  tf.dispose(res);\n  t.boxes = decodeBoxes(t.batch);\n  t.logits = tf.slice(t.batch, [0, 0], [-1, 1]);\n  t.sigmoid = tf.sigmoid(t.logits);\n  t.scores = tf.squeeze(t.sigmoid);\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.scores, (config.face.detector?.maxDetected || 0), (config.face.detector?.iouThreshold || 0), (config.face.detector?.minConfidence || 0));\n  const nms = await t.nms.array() as number[];\n  const boxes: Array<DetectBox> = [];\n  const scores = await t.scores.data();\n  for (let i = 0; i < nms.length; i++) {\n    const confidence = scores[nms[i]];\n    if (confidence > (config.face.detector?.minConfidence || 0)) {\n      const b: Record<string, Tensor> = {};\n      b.bbox = tf.slice(t.boxes, [nms[i], 0], [1, -1]);\n      b.slice = tf.slice(t.batch, [nms[i], keypointsCount - 1], [1, -1]);\n      b.squeeze = tf.squeeze(b.slice);\n      b.landmarks = tf.reshape(b.squeeze, [keypointsCount, -1]);\n      const points = await b.bbox.data();\n      const rawBox = {\n        startPoint: [points[0], points[1]] as Point,\n        endPoint: [points[2], points[3]] as Point,\n        landmarks: (await b.landmarks.array()) as Point[],\n        confidence,\n      };\n      const scaledBox = util.scaleBoxCoordinates(rawBox, [(inputImage.shape[2] || 0) / inputSize, (inputImage.shape[1] || 0) / inputSize]);\n      const enlargedBox = util.enlargeBox(scaledBox, config.face['scale'] || faceBoxScaleFactor);\n      const squaredBox = util.squarifyBox(enlargedBox);\n      boxes.push(squaredBox);\n      Object.keys(b).forEach((tensor) => tf.dispose(b[tensor]));\n    }\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return boxes;\n}\n", "/* eslint-disable no-multi-spaces */\n\nexport const kpt: Array<string> = [\n  'nose',            //  0\n  'leftEyeInside',   //  1\n  'leftEye',         //  2\n  'leftEyeOutside',  //  3\n  'rightEyeInside',  //  4\n  'rightEye',        //  5\n  'rightEyeOutside', //  6\n  'leftEar',         //  7\n  'rightEar',        //  8\n  'leftMouth',       //  9\n  'rightMouth',      // 10\n  'leftShoulder',    // 11\n  'rightShoulder',   // 12\n  'leftElbow',       // 13\n  'rightElbow',      // 14\n  'leftWrist',       // 15\n  'rightWrist',      // 16\n  'leftPinky',       // 17\n  'rightPinky',      // 18\n  'leftIndex',       // 19\n  'rightIndex',      // 20\n  'leftThumb',       // 21\n  'rightThumb',      // 22\n  'leftHip',         // 23\n  'rightHip',        // 24\n  'leftKnee',        // 25\n  'rightKnee',       // 26\n  'leftAnkle',       // 27\n  'rightAnkle',      // 28\n  'leftHeel',        // 29\n  'rightHeel',       // 30\n  'leftFoot',        // 31\n  'rightFoot',       // 32\n  'bodyCenter',      // 33\n  'bodyTop',         // 34\n  'leftPalm',        // 35 // z-coord not ok\n  'leftHand',        // 36 // similar to wrist but z-coord not ok\n  'rightPalm',       // 37 // z-coord not ok\n  'rightHand',       // 38 // similar to wrist but z-coord not ok\n];\n\nexport const connected: Record<string, string[]> = {\n  shoulders: ['leftShoulder', 'rightShoulder'],\n  hips: ['rightHip', 'leftHip'],\n  mouth: ['leftMouth', 'rightMouth'],\n  leftLegUpper: ['leftHip', 'leftKnee'],\n  leftLegLower: ['leftKnee', 'leftAnkle'],\n  leftFoot: ['leftAnkle', 'leftHeel', 'leftFoot'],\n  leftTorso: ['leftShoulder', 'leftHip'],\n  leftArmUpper: ['leftShoulder', 'leftElbow'],\n  leftArmLower: ['leftElbow', 'leftWrist'],\n  leftHand: ['leftWrist', 'leftPalm'],\n  leftHandPinky: ['leftPalm', 'leftPinky'],\n  leftHandIndex: ['leftPalm', 'leftIndex'],\n  leftHandThumb: ['leftPalm', 'leftThumb'],\n  leftEyeOutline: ['leftEyeInside', 'leftEyeOutside'],\n  rightLegUpper: ['rightHip', 'rightKnee'],\n  rightLegLower: ['rightKnee', 'rightAnkle'],\n  rightFoot: ['rightAnkle', 'rightHeel', 'rightFoot'],\n  rightTorso: ['rightShoulder', 'rightHip'],\n  rightArmUpper: ['rightShoulder', 'rightElbow'],\n  rightArmLower: ['rightElbow', 'rightWrist'],\n  rightHand: ['rightWrist', 'rightPalm'],\n  rightHandPinky: ['rightPalm', 'rightPinky'],\n  rightHandIndex: ['rightPalm', 'rightIndex'],\n  rightHandThumb: ['rightPalm', 'rightThumb'],\n  rightEyeOutline: ['rightEyeInside', 'rightEyeOutside'],\n};\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from '../tfjs/types';\nimport type { Box } from '../result';\nimport type { Config } from '../config';\n\ninterface DetectedBox { box: Box, boxRaw: Box, score: number }\n\nconst inputSize = 224;\nlet anchorTensor: { x, y };\nconst numLayers = 5;\nconst strides = [8, 16, 32, 32, 32];\n\nexport async function createAnchors() {\n  const anchors: Array<{ x: number, y: number }> = [];\n  let layerId = 0;\n  while (layerId < numLayers) {\n    let anchorCount = 0;\n    let lastSameStrideLayer = layerId;\n    while (lastSameStrideLayer < strides.length && strides[lastSameStrideLayer] === strides[layerId]) {\n      anchorCount += 2;\n      lastSameStrideLayer++;\n    }\n    const stride = strides[layerId];\n    const featureMapHeight = Math.ceil(inputSize / stride);\n    const featureMapWidth = Math.ceil(inputSize / stride);\n    for (let y = 0; y < featureMapHeight; ++y) {\n      for (let x = 0; x < featureMapWidth; ++x) {\n        for (let anchorId = 0; anchorId < anchorCount; ++anchorId) {\n          anchors.push({ x: (x + 0.5) / featureMapWidth, y: (y + 0.5) / featureMapHeight });\n        }\n      }\n    }\n    layerId = lastSameStrideLayer;\n  }\n  anchorTensor = { x: tf.tensor1d(anchors.map((a) => a.x)), y: tf.tensor1d(anchors.map((a) => a.y)) };\n}\n\nconst cropFactor = [5.0, 5.0];\nfunction decodeBoxes(boxesTensor, anchor): Tensor {\n  return tf.tidy(() => {\n    const split = tf.split(boxesTensor, 12, 1); // first 4 are box data [x,y,w,h] and 4 are keypoints data [x,y] for total of 12\n    let xCenter = tf.squeeze(split[0]);\n    let yCenter = tf.squeeze(split[1]);\n    let width = tf.squeeze(split[2]);\n    let height = tf.squeeze(split[3]);\n    xCenter = tf.add(tf.div(xCenter, inputSize), anchor.x);\n    yCenter = tf.add(tf.div(yCenter, inputSize), anchor.y);\n    width = tf.mul(tf.div(width, inputSize), cropFactor[0]);\n    height = tf.mul(tf.div(height, inputSize), cropFactor[1]);\n    const xMin = tf.sub(xCenter, tf.div(width, 2));\n    const yMin = tf.sub(yCenter, tf.div(height, 2));\n    const boxes = tf.stack([xMin, yMin, width, height], 1);\n    return boxes;\n  });\n}\n\nexport async function decode(boxesTensor: Tensor, logitsTensor: Tensor, config: Config, outputSize: [number, number]): Promise<DetectedBox[]> {\n  const t: Record<string, Tensor> = {};\n  t.boxes = decodeBoxes(boxesTensor, anchorTensor);\n  t.scores = tf.sigmoid(logitsTensor);\n  t.argmax = tf.argMax(t.scores);\n  const i = (await t.argmax.data())[0] as number;\n  const scores = await t.scores.data();\n  const detected: Array<{ box: Box, boxRaw: Box, score: number }> = [];\n  const minScore = (config.body['detector'] && config.body['detector']['minConfidence']) ? config.body['detector']['minConfidence'] : 0;\n  if (scores[i] >= minScore) {\n    const boxes = await t.boxes.array();\n    const boxRaw: Box = boxes[i];\n    const box: Box = [boxRaw[0] * outputSize[0], boxRaw[1] * outputSize[1], boxRaw[2] * outputSize[0], boxRaw[3] * outputSize[1]];\n    // console.log(box);\n    detected.push({ box, boxRaw, score: scores[i] });\n  }\n  /*\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.scores, 1, config.body.detector?.minConfidence || 0.1, config.body.detector?.iouThreshold || 0.1);\n  const boxes = t.boxes.arraySync();\n  const scores = t.scores.dataSync();\n  const nms = t.nms.dataSync();\n  const detected: Array<DetectedBox> = [];\n  for (const i of Array.from(nms)) {\n    const boxRaw: Box = boxes[i];\n    const box: Box = [boxRaw[0] * outputSize[0], boxRaw[0] * outputSize[1], boxRaw[3] * outputSize[0], boxRaw[2] * outputSize[1]];\n    detected.push({ box, boxRaw, score: scores[i] });\n  }\n  */\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return detected;\n}\n", "import type { Point, Box } from '../result';\n\nexport function calc(keypoints: Array<Point>, outputSize: [number, number] = [1, 1]) {\n  const coords = [keypoints.map((pt) => pt[0]), keypoints.map((pt) => pt[1])]; // all x/y coords\n  const min = [Math.min(...coords[0]), Math.min(...coords[1])];\n  const max = [Math.max(...coords[0]), Math.max(...coords[1])];\n  const box: Box = [min[0], min[1], max[0] - min[0], max[1] - min[1]];\n  const boxRaw: Box = [box[0] / outputSize[0], box[1] / outputSize[1], box[2] / outputSize[0], box[3] / outputSize[1]];\n  return { box, boxRaw };\n}\n\nexport function square(keypoints: Array<Point>, outputSize: [number, number] = [1, 1]) {\n  const coords = [keypoints.map((pt) => pt[0]), keypoints.map((pt) => pt[1])]; // all x/y coords\n  const min = [Math.min(...coords[0]), Math.min(...coords[1])];\n  const max = [Math.max(...coords[0]), Math.max(...coords[1])];\n  const center = [(min[0] + max[0]) / 2, (min[1] + max[1]) / 2]; // find center x and y coord of all fingers\n  const dist = Math.max(center[0] - min[0], center[1] - min[1], -center[0] + max[0], -center[1] + max[1]); // largest distance from center in any direction\n  const box: Box = [Math.trunc(center[0] - dist), Math.trunc(center[1] - dist), Math.trunc(2 * dist), Math.trunc(2 * dist)];\n  const boxRaw: Box = [box[0] / outputSize[0], box[1] / outputSize[1], box[2] / outputSize[0], box[3] / outputSize[1]];\n  return { box, boxRaw };\n}\n\nexport function scale(box: Box, scaleFact: number) {\n  const dist = [box[2] * scaleFact, box[3] * scaleFact];\n  const newBox: Box = [\n    box[0] - (dist[0] - box[2]) / 2,\n    box[1] - (dist[1] - box[3]) / 2,\n    dist[0],\n    dist[1],\n  ];\n  return newBox;\n}\n\nexport function crop(box: Box) { // [y1, x1, y2, x2] clamped to 0..1\n  const yxBox: Box = [Math.max(0, box[1]), Math.max(0, box[0]), Math.min(1, box[3] + box[1]), Math.min(1, box[2] + box[0])];\n  return yxBox;\n}\n", "/**\n * BlazePose model implementation\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport { log, now } from '../util/util';\nimport type { BodyKeypoint, BodyResult, BodyLandmark, Box, Point, BodyAnnotation } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport * as coords from './blazeposecoords';\nimport * as detect from './blazeposedetector';\nimport * as box from '../util/box';\n\nconst env = { initial: true };\n// const models: [GraphModel | null, GraphModel | null] = [null, null];\nconst models: { detector: GraphModel | null, landmarks: GraphModel | null } = { detector: null, landmarks: null };\nconst inputSize: { detector: [number, number], landmarks: [number, number] } = { detector: [224, 224], landmarks: [256, 256] };\nlet skipped = Number.MAX_SAFE_INTEGER;\nconst outputNodes: { detector: string[], landmarks: string[] } = {\n  landmarks: ['ld_3d', 'activation_segmentation', 'activation_heatmap', 'world_3d', 'output_poseflag'],\n  detector: [],\n};\n\nlet cache: BodyResult | null = null;\nlet cropBox: Box | undefined;\nlet padding: [number, number][] = [[0, 0], [0, 0], [0, 0], [0, 0]];\nlet lastTime = 0;\n\nconst sigmoid = (x) => (1 - (1 / (1 + Math.exp(x))));\n\nexport async function loadDetect(config: Config): Promise<GraphModel> {\n  if (env.initial) models.detector = null;\n  if (!models.detector && config.body['detector'] && config.body['detector']['modelPath'] || '') {\n    models.detector = await loadModel(config.body['detector']['modelPath']);\n    const inputs = Object.values(models.detector.modelSignature['inputs']);\n    inputSize.detector[0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize.detector[1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug && models.detector) log('cached model:', models.detector['modelUrl']);\n  await detect.createAnchors();\n  return models.detector as GraphModel;\n}\n\nexport async function loadPose(config: Config): Promise<GraphModel> {\n  if (env.initial) models.landmarks = null;\n  if (!models.landmarks) {\n    models.landmarks = await loadModel(config.body.modelPath);\n    const inputs = Object.values(models.landmarks.modelSignature['inputs']);\n    inputSize.landmarks[0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize.landmarks[1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', models.landmarks['modelUrl']);\n  return models.landmarks;\n}\n\nexport async function load(config: Config): Promise<[GraphModel | null, GraphModel | null]> {\n  if (!models.detector) await loadDetect(config);\n  if (!models.landmarks) await loadPose(config);\n  return [models.detector, models.landmarks];\n}\n\nasync function prepareImage(input: Tensor, size: number): Promise<Tensor> {\n  const t: Record<string, Tensor> = {};\n  if (!input.shape || !input.shape[1] || !input.shape[2]) return input;\n  let final: Tensor;\n  if (cropBox) {\n    t.cropped = tf.image.cropAndResize(input, [cropBox], [0], [input.shape[1], input.shape[2]]); // if we have cached box use it to crop input\n  }\n  if (input.shape[1] !== input.shape[2]) { // only pad if width different than height\n    const height: [number, number] = [\n      input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0,\n      input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0,\n    ];\n    const width: [number, number] = [\n      input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0,\n      input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0,\n    ];\n    padding = [\n      [0, 0], // dont touch batch\n      height, // height before&after\n      width, // width before&after\n      [0, 0], // dont touch rbg\n    ];\n    t.pad = tf.pad(t.cropped || input, padding); // use cropped box if it exists\n    t.resize = tf.image.resizeBilinear(t.pad, [size, size]);\n    final = tf.div(t.resize, constants.tf255);\n  } else if (input.shape[1] !== size) { // if input needs resizing\n    t.resize = tf.image.resizeBilinear(t.cropped || input, [size, size]);\n    final = tf.div(t.resize, constants.tf255);\n  } else { // if input is already in a correct resolution just normalize it\n    final = tf.div(t.cropped || input, constants.tf255);\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return final;\n}\n\nfunction rescaleKeypoints(keypoints: Array<BodyKeypoint>, outputSize: [number, number]): Array<BodyKeypoint> {\n  for (const kpt of keypoints) { // first rescale due to padding\n    kpt.position = [\n      Math.trunc(kpt.position[0] * (outputSize[0] + padding[2][0] + padding[2][1]) / outputSize[0] - padding[2][0]),\n      Math.trunc(kpt.position[1] * (outputSize[1] + padding[1][0] + padding[1][1]) / outputSize[1] - padding[1][0]),\n      kpt.position[2] as number,\n    ];\n    kpt.positionRaw = [kpt.position[0] / outputSize[0], kpt.position[1] / outputSize[1], 2 * (kpt.position[2] as number) / (outputSize[0] + outputSize[1])];\n  }\n  if (cropBox) { // second rescale due to cropping\n    for (const kpt of keypoints) {\n      kpt.positionRaw = [\n        kpt.positionRaw[0] + cropBox[1], // correct offset due to crop\n        kpt.positionRaw[1] + cropBox[0], // correct offset due to crop\n        kpt.positionRaw[2] as number,\n      ];\n      kpt.position = [\n        Math.trunc(kpt.positionRaw[0] * outputSize[0]),\n        Math.trunc(kpt.positionRaw[1] * outputSize[1]),\n        kpt.positionRaw[2] as number,\n      ];\n    }\n  }\n  return keypoints;\n}\n\nasync function fixKeypoints(keypoints: Array<BodyKeypoint>) {\n  // palm z-coord is incorrect around near-zero so we approximate it\n  const leftPalm = keypoints.find((k) => k.part === 'leftPalm') as BodyKeypoint;\n  const leftWrist = keypoints.find((k) => k.part === 'leftWrist') as BodyKeypoint;\n  const leftIndex = keypoints.find((k) => k.part === 'leftIndex') as BodyKeypoint;\n  leftPalm.position[2] = ((leftWrist.position[2] || 0) + (leftIndex.position[2] || 0)) / 2;\n  const rightPalm = keypoints.find((k) => k.part === 'rightPalm') as BodyKeypoint;\n  const rightWrist = keypoints.find((k) => k.part === 'rightWrist') as BodyKeypoint;\n  const rightIndex = keypoints.find((k) => k.part === 'rightIndex') as BodyKeypoint;\n  rightPalm.position[2] = ((rightWrist.position[2] || 0) + (rightIndex.position[2] || 0)) / 2;\n}\n\nasync function detectLandmarks(input: Tensor, config: Config, outputSize: [number, number]): Promise<BodyResult | null> {\n  /**\n   * t.ld: 39 keypoints [x,y,z,score,presence] normalized to input size\n   * t.segmentation:\n   * t.heatmap:\n   * t.world: 39 keypoints [x,y,z] normalized to -1..1\n   * t.poseflag: body score\n  */\n  const t: Record<string, Tensor> = {};\n  [t.ld/* 1,195(39*5) */, t.segmentation/* 1,256,256,1 */, t.heatmap/* 1,64,64,39 */, t.world/* 1,117(39*3) */, t.poseflag/* 1,1 */] = models.landmarks?.execute(input, outputNodes.landmarks) as Tensor[]; // run model\n  const poseScore = (await t.poseflag.data())[0];\n  const points = await t.ld.data();\n  const distances = await t.world.data();\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor])); // dont need tensors after this\n  const keypointsRelative: Array<BodyKeypoint> = [];\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    const score = sigmoid(points[depth * i + 3]);\n    const presence = sigmoid(points[depth * i + 4]);\n    const adjScore = Math.trunc(100 * score * presence * poseScore) / 100;\n    const positionRaw: Point = [points[depth * i + 0] / inputSize.landmarks[0], points[depth * i + 1] / inputSize.landmarks[1], points[depth * i + 2] + 0];\n    const position: Point = [Math.trunc(outputSize[0] * positionRaw[0]), Math.trunc(outputSize[1] * positionRaw[1]), positionRaw[2] as number];\n    const distance: Point = [distances[depth * i + 0], distances[depth * i + 1], distances[depth * i + 2] + 0];\n    keypointsRelative.push({ part: coords.kpt[i] as BodyLandmark, positionRaw, position, distance, score: adjScore });\n  }\n  if (poseScore < (config.body.minConfidence || 0)) return null;\n  fixKeypoints(keypointsRelative);\n  const keypoints: Array<BodyKeypoint> = rescaleKeypoints(keypointsRelative, outputSize); // keypoints were relative to input image which is padded\n  const kpts = keypoints.map((k) => k.position);\n  const boxes = box.calc(kpts, [outputSize[0], outputSize[1]]); // now find boxes based on rescaled keypoints\n  const annotations: Record<BodyAnnotation, Point[][]> = {} as Record<BodyAnnotation, Point[][]>;\n  for (const [name, indexes] of Object.entries(coords.connected)) {\n    const pt: Array<Point[]> = [];\n    for (let i = 0; i < indexes.length - 1; i++) {\n      const pt0 = keypoints.find((kpt) => kpt.part === indexes[i]);\n      const pt1 = keypoints.find((kpt) => kpt.part === indexes[i + 1]);\n      if (pt0 && pt1) pt.push([pt0.position, pt1.position]);\n    }\n    annotations[name] = pt;\n  }\n  const body = { id: 0, score: Math.trunc(100 * poseScore) / 100, box: boxes.box, boxRaw: boxes.boxRaw, keypoints, annotations };\n  return body;\n}\n\n/*\ninterface DetectedBox { box: Box, boxRaw: Box, score: number }\n\nfunction rescaleBoxes(boxes: Array<DetectedBox>, outputSize: [number, number]): Array<DetectedBox> {\n  for (const b of boxes) {\n    b.box = [\n      Math.trunc(b.box[0] * (outputSize[0] + padding[2][0] + padding[2][1]) / outputSize[0]),\n      Math.trunc(b.box[1] * (outputSize[1] + padding[1][0] + padding[1][1]) / outputSize[1]),\n      Math.trunc(b.box[2] * (outputSize[0] + padding[2][0] + padding[2][1]) / outputSize[0]),\n      Math.trunc(b.box[3] * (outputSize[1] + padding[1][0] + padding[1][1]) / outputSize[1]),\n    ];\n    b.boxRaw = [b.box[0] / outputSize[0], b.box[1] / outputSize[1], b.box[2] / outputSize[0], b.box[3] / outputSize[1]];\n  }\n  return boxes;\n}\n\nasync function detectBoxes(input: Tensor, config: Config, outputSize: [number, number]) {\n  const t: Record<string, Tensor> = {};\n  t.res = models.detector?.execute(input, ['Identity']) as Tensor; //\n  t.logitsRaw = tf.slice(t.res, [0, 0, 0], [1, -1, 1]);\n  t.boxesRaw = tf.slice(t.res, [0, 0, 1], [1, -1, -1]);\n  t.logits = tf.squeeze(t.logitsRaw);\n  t.boxes = tf.squeeze(t.boxesRaw);\n  const boxes = await detect.decode(t.boxes, t.logits, config, outputSize);\n  rescaleBoxes(boxes, outputSize);\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return boxes;\n}\n*/\n\nexport async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {\n  const outputSize: [number, number] = [input.shape[2] || 0, input.shape[1] || 0];\n  const skipTime = (config.body.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.body.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && cache !== null) {\n    skipped++;\n  } else {\n    const t: Record<string, Tensor> = {};\n    /*\n    if (config.body['detector'] && config.body['detector']['enabled']) {\n      t.detector = await prepareImage(input, 224);\n      const boxes = await detectBoxes(t.detector, config, outputSize);\n    }\n    */\n    t.landmarks = await prepareImage(input, 256); // padded and resized\n    cache = await detectLandmarks(t.landmarks, config, outputSize);\n    /*\n    cropBox = [0, 0, 1, 1]; // reset crop coordinates\n    if (cache?.boxRaw && config.skipAllowed) {\n      const cx = (2.0 * cache.boxRaw[0] + cache.boxRaw[2]) / 2;\n      const cy = (2.0 * cache.boxRaw[1] + cache.boxRaw[3]) / 2;\n      let size = cache.boxRaw[2] > cache.boxRaw[3] ? cache.boxRaw[2] : cache.boxRaw[3];\n      size = (size * 1.0) / 2; // enlarge and half it\n      if (cx > 0.1 && cx < 0.9 && cy > 0.1 && cy < 0.9 && size > 0.1) { // only update if box is sane\n        const y = 0; // cy - size;\n        const x = cx - size;\n        cropBox = [y, x, y + 1, x + 1]; // [y0,x0,y1,x1] used for cropping but width/height are not yet implemented so we only reposition image to center of body\n      }\n    }\n    */\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    lastTime = now();\n    skipped = 0;\n  }\n  return cache ? [cache] : [];\n}\n", "/**\n * CoCo Labels used by object detection implementations\n */\nexport const labels = [\n  { class: 1, label: 'person' },\n  { class: 2, label: 'bicycle' },\n  { class: 3, label: 'car' },\n  { class: 4, label: 'motorcycle' },\n  { class: 5, label: 'airplane' },\n  { class: 6, label: 'bus' },\n  { class: 7, label: 'train' },\n  { class: 8, label: 'truck' },\n  { class: 9, label: 'boat' },\n  { class: 10, label: 'traffic light' },\n  { class: 11, label: 'fire hydrant' },\n  { class: 12, label: 'stop sign' },\n  { class: 13, label: 'parking meter' },\n  { class: 14, label: 'bench' },\n  { class: 15, label: 'bird' },\n  { class: 16, label: 'cat' },\n  { class: 17, label: 'dog' },\n  { class: 18, label: 'horse' },\n  { class: 19, label: 'sheep' },\n  { class: 20, label: 'cow' },\n  { class: 21, label: 'elephant' },\n  { class: 22, label: 'bear' },\n  { class: 23, label: 'zebra' },\n  { class: 24, label: 'giraffe' },\n  { class: 25, label: 'backpack' },\n  { class: 26, label: 'umbrella' },\n  { class: 27, label: 'handbag' },\n  { class: 28, label: 'tie' },\n  { class: 29, label: 'suitcase' },\n  { class: 30, label: 'frisbee' },\n  { class: 31, label: 'skis' },\n  { class: 32, label: 'snowboard' },\n  { class: 33, label: 'sports ball' },\n  { class: 34, label: 'kite' },\n  { class: 35, label: 'baseball bat' },\n  { class: 36, label: 'baseball glove' },\n  { class: 37, label: 'skateboard' },\n  { class: 38, label: 'surfboard' },\n  { class: 39, label: 'tennis racket' },\n  { class: 40, label: 'bottle' },\n  { class: 41, label: 'wine glass' },\n  { class: 42, label: 'cup' },\n  { class: 43, label: 'fork' },\n  { class: 44, label: 'knife' },\n  { class: 45, label: 'spoon' },\n  { class: 46, label: 'bowl' },\n  { class: 47, label: 'banana' },\n  { class: 48, label: 'apple' },\n  { class: 49, label: 'sandwich' },\n  { class: 50, label: 'orange' },\n  { class: 51, label: 'broccoli' },\n  { class: 52, label: 'carrot' },\n  { class: 53, label: 'hot dog' },\n  { class: 54, label: 'pizza' },\n  { class: 55, label: 'donut' },\n  { class: 56, label: 'cake' },\n  { class: 57, label: 'chair' },\n  { class: 58, label: 'couch' },\n  { class: 59, label: 'potted plant' },\n  { class: 60, label: 'bed' },\n  { class: 61, label: 'dining table' },\n  { class: 62, label: 'toilet' },\n  { class: 63, label: 'tv' },\n  { class: 64, label: 'laptop' },\n  { class: 65, label: 'mouse' },\n  { class: 66, label: 'remote' },\n  { class: 67, label: 'keyboard' },\n  { class: 68, label: 'cell phone' },\n  { class: 69, label: 'microwave' },\n  { class: 70, label: 'oven' },\n  { class: 71, label: 'toaster' },\n  { class: 72, label: 'sink' },\n  { class: 73, label: 'refrigerator' },\n  { class: 74, label: 'book' },\n  { class: 75, label: 'clock' },\n  { class: 76, label: 'vase' },\n  { class: 77, label: 'scissors' },\n  { class: 78, label: 'teddy bear' },\n  { class: 79, label: 'hair drier' },\n  { class: 80, label: 'toothbrush' },\n];\n", "/**\n * CenterNet object detection model implementation\n *\n * Based on: [**NanoDet**](https://github.com/RangiLyu/nanodet)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { labels } from './labels';\nimport type { ObjectResult, ObjectType, Box } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nlet inputSize = 0;\nlet last: ObjectResult[] = [];\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) {\n    // fakeOps(['floormod'], config);\n    model = await loadModel(config.object.modelPath);\n    const inputs = Object.values(model.modelSignature['inputs']);\n    inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nasync function process(res: Tensor | null, outputShape: [number, number], config: Config) {\n  if (!res) return [];\n  const t: Record<string, Tensor> = {};\n  const results: Array<ObjectResult> = [];\n  const detections = await res.array() as number[][][];\n  t.squeeze = tf.squeeze(res);\n  const arr = tf.split(t.squeeze, 6, 1) as Tensor[]; // x1, y1, x2, y2, score, class\n  t.stack = tf.stack([arr[1], arr[0], arr[3], arr[2]], 1); // reorder dims as tf.nms expects y, x\n  t.boxes = tf.squeeze(t.stack);\n  t.scores = tf.squeeze(arr[4]);\n  t.classes = tf.squeeze(arr[5]);\n  tf.dispose([res, ...arr]);\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.scores, config.object.maxDetected, config.object.iouThreshold, (config.object.minConfidence || 0));\n  const nms = await t.nms.data();\n  let i = 0;\n  for (const id of Array.from(nms)) {\n    const score = Math.trunc(100 * detections[0][id][4]) / 100;\n    const classVal = detections[0][id][5];\n    const label = labels[classVal].label as ObjectType;\n    const [x, y] = [\n      detections[0][id][0] / inputSize,\n      detections[0][id][1] / inputSize,\n    ];\n    const boxRaw: Box = [\n      x,\n      y,\n      detections[0][id][2] / inputSize - x,\n      detections[0][id][3] / inputSize - y,\n    ];\n    const box: Box = [\n      Math.trunc(boxRaw[0] * outputShape[0]),\n      Math.trunc(boxRaw[1] * outputShape[1]),\n      Math.trunc(boxRaw[2] * outputShape[0]),\n      Math.trunc(boxRaw[3] * outputShape[1]),\n    ];\n    results.push({ id: i++, score, class: classVal, label, box, boxRaw });\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return results;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<ObjectResult[]> {\n  const skipTime = (config.object.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.object.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const outputSize = [input.shape[2] || 0, input.shape[1] || 0] as [number, number];\n    const resize = tf.image.resizeBilinear(input, [inputSize, inputSize]);\n    const objectT = config.object.enabled ? model?.execute(resize, ['tower_0/detections']) as Tensor : null;\n    lastTime = now();\n    tf.dispose(resize);\n\n    const obj = await process(objectT, outputSize, config);\n    last = obj;\n\n    resolve(obj);\n  });\n}\n", "export const kpt: Array<string> = [\n  'head',\n  'neck',\n  'rightShoulder',\n  'rightElbow',\n  'rightWrist',\n  'chest',\n  'leftShoulder',\n  'leftElbow',\n  'leftWrist',\n  'bodyCenter',\n  'rightHip',\n  'rightKnee',\n  'rightAnkle',\n  'leftHip',\n  'leftKnee',\n  'leftAnkle',\n];\n\nexport const connected: Record<string, string[]> = {\n  leftLeg: ['leftHip', 'leftKnee', 'leftAnkle'],\n  rightLeg: ['rightHip', 'rightKnee', 'rightAnkle'],\n  torso: ['leftShoulder', 'rightShoulder', 'rightHip', 'leftHip', 'leftShoulder'],\n  leftArm: ['leftShoulder', 'leftElbow', 'leftWrist'],\n  rightArm: ['rightShoulder', 'rightElbow', 'rightWrist'],\n  head: [],\n};\n", "/**\n * EfficientPose model implementation\n *\n * Based on: [**EfficientPose**](https://github.com/daniegr/EfficientPose)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport * as coords from './efficientposecoords';\nimport { constants } from '../tfjs/constants';\nimport type { BodyResult, Point, BodyLandmark, BodyAnnotation } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nlet lastTime = 0;\nconst cache: BodyResult = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} as Record<BodyAnnotation, Point[][]> };\n\n// const keypoints: Array<BodyKeypoint> = [];\n// let box: Box = [0, 0, 0, 0];\n// let boxRaw: Box = [0, 0, 0, 0];\n// let score = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.body.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// performs argmax and max functions on a 2d tensor\nasync function max2d(inputs, minScore) {\n  const [width, height] = inputs.shape;\n  const reshaped = tf.reshape(inputs, [height * width]); // combine all data\n  const max = tf.max(reshaped, 0);\n  const newScore = (await max.data())[0]; // get highest score\n  tf.dispose([reshaped, max]);\n  if (newScore > minScore) { // skip coordinate calculation is score is too low\n    const coordinates = tf.argMax(reshaped, 0);\n    const mod = tf.mod(coordinates, width);\n    const x = (await mod.data())[0];\n    const div = tf.div(coordinates, tf.scalar(width, 'int32'));\n    const y = (await div.data())[0];\n    tf.dispose([mod, div]);\n    return [x, y, newScore];\n  }\n  return [0, 0, newScore];\n}\n\nexport async function predict(image: Tensor, config: Config): Promise<BodyResult[]> {\n  const skipTime = (config.body.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.body.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && Object.keys(cache.keypoints).length > 0) {\n    skipped++;\n    return [cache];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const tensor = tf.tidy(() => {\n      if (!model?.inputs[0].shape) return null;\n      const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n      const enhance = tf.mul(resize, constants.tf2);\n      const norm = tf.sub(enhance, constants.tf1);\n      return norm;\n    });\n\n    let resT;\n    if (config.body.enabled) resT = model?.execute(tensor);\n    lastTime = now();\n    tf.dispose(tensor);\n\n    if (resT) {\n      cache.keypoints.length = 0;\n      const squeeze = resT.squeeze();\n      tf.dispose(resT);\n      // body parts are basically just a stack of 2d tensors\n      const stack = squeeze.unstack(2);\n      tf.dispose(squeeze);\n      // process each unstacked tensor as a separate body part\n      for (let id = 0; id < stack.length; id++) {\n        // actual processing to get coordinates and score\n        const [x, y, partScore] = await max2d(stack[id], config.body.minConfidence);\n        if (partScore > (config.body?.minConfidence || 0)) {\n          cache.keypoints.push({\n            score: Math.round(100 * partScore) / 100,\n            part: coords.kpt[id] as BodyLandmark,\n            positionRaw: [ // normalized to 0..1\n              // @ts-ignore model is not undefined here\n              x / model.inputs[0].shape[2], y / model.inputs[0].shape[1],\n            ],\n            position: [ // normalized to input image size\n              // @ts-ignore model is not undefined here\n              Math.round(image.shape[2] * x / model.inputs[0].shape[2]), Math.round(image.shape[1] * y / model.inputs[0].shape[1]),\n            ],\n          });\n        }\n      }\n      stack.forEach((s) => tf.dispose(s));\n    }\n    cache.score = cache.keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n    const x = cache.keypoints.map((a) => a.position[0]);\n    const y = cache.keypoints.map((a) => a.position[1]);\n    cache.box = [\n      Math.min(...x),\n      Math.min(...y),\n      Math.max(...x) - Math.min(...x),\n      Math.max(...y) - Math.min(...y),\n    ];\n    const xRaw = cache.keypoints.map((a) => a.positionRaw[0]);\n    const yRaw = cache.keypoints.map((a) => a.positionRaw[1]);\n    cache.boxRaw = [\n      Math.min(...xRaw),\n      Math.min(...yRaw),\n      Math.max(...xRaw) - Math.min(...xRaw),\n      Math.max(...yRaw) - Math.min(...yRaw),\n    ];\n    for (const [name, indexes] of Object.entries(coords.connected)) {\n      const pt: Array<Point[]> = [];\n      for (let i = 0; i < indexes.length - 1; i++) {\n        const pt0 = cache.keypoints.find((kpt) => kpt.part === indexes[i]);\n        const pt1 = cache.keypoints.find((kpt) => kpt.part === indexes[i + 1]);\n        if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n      }\n      cache.annotations[name] = pt;\n    }\n    resolve([cache]);\n  });\n}\n", "/**\n * Emotion model implementation\n *\n * [**Oarriaga**](https://github.com/oarriaga/face_classification)\n */\n\nimport type { Emotion } from '../result';\nimport { log, now } from '../util/util';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { env } from '../util/env';\nimport { constants } from '../tfjs/constants';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model: GraphModel | null;\nconst last: Array<Array<{ score: number, emotion: Emotion }>> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.emotion?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<Array<{ score: number, emotion: Emotion }>> {\n  if (!model) return [];\n  const skipFrame = skipped < (config.face.emotion?.skipFrames || 0);\n  const skipTime = (config.face.emotion?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && last[idx] && (last[idx].length > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const obj: Array<{ score: number, emotion: Emotion }> = [];\n    if (config.face.emotion?.enabled) {\n      const t: Record<string, Tensor> = {};\n      const inputSize = model?.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n      t.resize = tf.image.resizeBilinear(image, [inputSize, inputSize], false);\n      // const box = [[0.15, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n      // const resize = tf.image.cropAndResize(image, box, [0], [inputSize, inputSize]);\n      // [t.red, t.green, t.blue] = tf.split(t.resize, 3, 3);\n      // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n      // t.redNorm = tf.mul(t.red, rgb[0]);\n      // t.greenNorm = tf.mul(t.green, rgb[1]);\n      // t.blueNorm = tf.mul(t.blue, rgb[2]);\n      // t.grayscale = tf.addN([t.redNorm, t.greenNorm, t.blueNorm]);\n      t.channels = tf.mul(t.resize, constants.rgb);\n      t.grayscale = tf.sum(t.channels, 3, true);\n      t.grayscaleSub = tf.sub(t.grayscale, constants.tf05);\n      t.grayscaleMul = tf.mul(t.grayscaleSub, constants.tf2);\n      t.emotion = model?.execute(t.grayscaleMul) as Tensor; // result is already in range 0..1, no need for additional activation\n      lastTime = now();\n      const data = await t.emotion.data();\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > (config.face.emotion?.minConfidence || 0)) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] as Emotion });\n      }\n      obj.sort((a, b) => b.score - a.score);\n      Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    }\n    last[idx] = obj;\n    lastCount = count;\n    resolve(obj);\n  });\n}\n", "/**\n * EfficientPose model implementation\n *\n * Based on: [**BecauseofAI MobileFace**](https://github.com/becauseofAI/MobileFace)\n *\n * Obsolete and replaced by `faceres` that performs age/gender/descriptor analysis\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst last: Array<number[]> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['mobilefacenet'].modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n/*\n// convert to black&white to avoid colorization impact\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\nconst [red, green, blue] = tf.split(crop, 3, 3);\nconst redNorm = tf.mul(red, rgb[0]);\nconst greenNorm = tf.mul(green, rgb[1]);\nconst blueNorm = tf.mul(blue, rgb[2]);\nconst grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\nconst merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n// optional increase image contrast\n// or do it per-channel so mean is done on each channel\n// or do it based on histogram\nconst mean = merge.mean();\nconst factor = 5;\nconst contrast = merge.sub(mean).mul(factor).add(mean);\n*/\n\nexport async function predict(input: Tensor, config: Config, idx, count): Promise<number[]> {\n  if (!model) return [];\n  const skipFrame = skipped < (config.face['embedding']?.skipFrames || 0);\n  const skipTime = (config.face['embedding']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && last[idx]) {\n    skipped++;\n    return last[idx];\n  }\n  return new Promise(async (resolve) => {\n    let data: Array<number> = [];\n    if (config.face['embedding']?.enabled && model?.inputs[0].shape) {\n      const t: Record<string, Tensor> = {};\n      t.crop = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n      // do a tight crop of image and resize it to fit the model\n      // const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n      // t.crop = tf.image.cropAndResize(input, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n      t.data = model?.execute(t.crop) as Tensor;\n      /*\n      // optional normalize outputs with l2 normalization\n      const scaled = tf.tidy(() => {\n        const l2 = res.norm('euclidean');\n        const scale = res.div(l2);\n        return scale;\n      });\n\n      // optional reduce feature vector complexity\n      const reshape = tf.reshape(res, [128, 2]); // split 256 vectors into 128 x 2\n      const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n      */\n      const output = await t.data.data();\n      data = Array.from(output); // convert typed array to simple array\n    }\n    last[idx] = data;\n    lastCount = count;\n    lastTime = now();\n    resolve(data);\n  });\n}\n", "import * as coords from './facemeshcoords';\nimport * as util from './facemeshutil';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport { env } from '../util/env';\nimport { log } from '../util/util';\nimport { loadModel } from '../tfjs/load';\nimport type { Config } from '../config';\nimport type { Point } from '../result';\n\nlet model: GraphModel | null;\nlet inputSize = 0;\n\nconst irisEnlarge = 2.3;\n\nconst leftOutline = coords.meshAnnotations['leftEyeLower0'];\nconst rightOutline = coords.meshAnnotations['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.iris?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  if (inputSize === -1) inputSize = 64;\n  return model;\n}\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates and update the z coordinate to be an average of the original and the new.\nexport function replaceIrisCoords(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.irisIndices.length; i++) {\n    const { key, indices } = coords.irisIndices[i];\n    const originalIndices = coords.meshAnnotations[`${prefix}${key}`];\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0],\n          newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n\nexport const getLeftToRightEyeDepthDifference = (rawCoords) => {\n  const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n  const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n  return leftEyeZ - rightEyeZ;\n};\n\n// Returns a box describing a cropped region around the eye fit for passing to the iris model.\nexport const getEyeBox = (rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, meshSize, flip = false) => {\n  const box = util.squarifyBox(util.enlargeBox(util.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), irisEnlarge));\n  const boxSize = util.getBoxSize(box);\n  let crop = tf.image.cropAndResize(face, [[\n    box.startPoint[1] / meshSize,\n    box.startPoint[0] / meshSize, box.endPoint[1] / meshSize,\n    box.endPoint[0] / meshSize,\n  ]], [0], [inputSize, inputSize]);\n  if (flip && env.kernels.includes('flipleftright')) {\n    const flipped = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    tf.dispose(crop);\n    crop = flipped;\n  }\n  return { box, boxSize, crop };\n};\n\n// Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\nexport const getEyeCoords = (eyeData, eyeBox, eyeBoxSize, flip = false) => {\n  const eyeRawCoords: Array<Point> = [];\n  for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n    const x = eyeData[i * 3];\n    const y = eyeData[i * 3 + 1];\n    const z = eyeData[i * 3 + 2];\n    eyeRawCoords.push([\n      (flip ? (1 - (x / inputSize)) : (x / inputSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n      (y / inputSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n    ]);\n  }\n  return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n};\n\n// The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\nexport const getAdjustedIrisCoords = (rawCoords, irisCoords, direction) => {\n  const upperCenterZ = rawCoords[coords.meshAnnotations[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n  const lowerCenterZ = rawCoords[coords.meshAnnotations[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n  const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n  // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n  return irisCoords.map((coord, i) => {\n    let z = averageZ;\n    if (i === 2) {\n      z = upperCenterZ;\n    } else if (i === 4) {\n      z = lowerCenterZ;\n    }\n    return [coord[0], coord[1], z];\n  });\n};\n\nexport async function augmentIris(rawCoords, face, config, meshSize) {\n  if (!model) {\n    if (config.debug) log('face mesh iris detection requested, but model is not loaded');\n    return rawCoords;\n  }\n  const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], meshSize, true);\n  const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1], meshSize, true);\n  const combined = tf.concat([leftEyeCrop, rightEyeCrop]);\n  tf.dispose(leftEyeCrop);\n  tf.dispose(rightEyeCrop);\n  const eyePredictions = model.execute(combined) as Tensor;\n  tf.dispose(combined);\n  const eyePredictionsData = await eyePredictions.data();\n  tf.dispose(eyePredictions);\n  const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n  const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n  const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n  const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize, false);\n  const leftToRightEyeDepthDifference = getLeftToRightEyeDepthDifference(rawCoords);\n  if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n    replaceIrisCoords(rawCoords, leftEyeRawCoords, 'left', null);\n    replaceIrisCoords(rawCoords, rightEyeRawCoords, 'right', null);\n    // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged so we only update a single contour line above and below the eye.\n  } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n    replaceIrisCoords(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n  } else { // User is looking towards the left.\n    replaceIrisCoords(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n  }\n  const adjustedLeftIrisCoords = getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n  const adjustedRightIrisCoords = getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n  const newCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n  return newCoords;\n}\n", "// @tensorflow/tfjs-models/face-landmark-detection/src/constants.ts\n// https://github.com/google/mediapipe/mediapipe/python/solutions/face_mesh_connections.py\n\ntype PairArray = Array<[number, number]>;\n\nconst LIPS_CONNECTIONS: PairArray = [\n  [61, 146], [146, 91], [91, 181], [181, 84], [84, 17], [17, 314], [314, 405], [405, 321], [321, 375], [375, 291], [61, 185], [185, 40], [40, 39], [39, 37], [37, 0], [0, 267], [267, 269], [269, 270], [270, 409], [409, 291],\n  [78, 95], [95, 88], [88, 178], [178, 87], [87, 14], [14, 317], [317, 402], [402, 318], [318, 324], [324, 308], [78, 191], [191, 80], [80, 81], [81, 82], [82, 13], [13, 312], [312, 311], [311, 310], [310, 415], [415, 308],\n];\n\nconst LEFT_EYE_CONNECTIONS: PairArray = [[263, 249], [249, 390], [390, 373], [373, 374], [374, 380], [380, 381], [381, 382], [382, 362], [263, 466], [466, 388], [388, 387], [387, 386], [386, 385], [385, 384], [384, 398], [398, 362]];\n\nconst LEFT_EYEBROW_CONNECTIONS: PairArray = [[276, 283], [283, 282], [282, 295], [295, 285], [300, 293], [293, 334], [334, 296], [296, 336]];\n\nconst LEFT_IRIS_CONNECTIONS: PairArray = [[474, 475], [475, 476], [476, 477], [477, 474]];\n\nconst RIGHT_EYE_CONNECTIONS: PairArray = [[33, 7], [7, 163], [163, 144], [144, 145], [145, 153], [153, 154], [154, 155], [155, 133], [33, 246], [246, 161], [161, 160], [160, 159], [159, 158], [158, 157], [157, 173], [173, 133]];\n\nconst RIGHT_EYEBROW_CONNECTIONS: PairArray = [[46, 53], [53, 52], [52, 65], [65, 55], [70, 63], [63, 105], [105, 66], [66, 107]];\n\nconst RIGHT_IRIS_CONNECTIONS: PairArray = [[469, 470], [470, 471], [471, 472], [472, 469]];\n\nconst FACE_OVAL_CONNECTIONS: PairArray = [\n  [10, 338], [338, 297], [297, 332], [332, 284], [284, 251], [251, 389], [389, 356], [356, 454], [454, 323], [323, 361], [361, 288], [288, 397], [397, 365], [365, 379], [379, 378], [378, 400], [400, 377], [377, 152],\n  [152, 148], [148, 176], [176, 149], [149, 150], [150, 136], [136, 172], [172, 58], [58, 132], [132, 93], [93, 234], [234, 127], [127, 162], [162, 21], [21, 54], [54, 103], [103, 67], [67, 109], [109, 10],\n];\n\nexport const MEDIAPIPE_FACE_MESH_CONNECTED_KEYPOINTS_PAIRS: PairArray = [\n  [127, 34], [34, 139], [139, 127], [11, 0], [0, 37], [37, 11], [232, 231], [231, 120], [120, 232], [72, 37], [37, 39], [39, 72], [128, 121], [121, 47], [47, 128], [232, 121], [121, 128], [128, 232],\n  [104, 69], [69, 67], [67, 104], [175, 171], [171, 148], [148, 175], [118, 50], [50, 101], [101, 118], [73, 39], [39, 40], [40, 73], [9, 151], [151, 108], [108, 9], [48, 115], [115, 131], [131, 48],\n  [194, 204], [204, 211], [211, 194], [74, 40], [40, 185], [185, 74], [80, 42], [42, 183], [183, 80], [40, 92], [92, 186], [186, 40], [230, 229], [229, 118], [118, 230], [202, 212], [212, 214], [214, 202],\n  [83, 18], [18, 17], [17, 83], [76, 61], [61, 146], [146, 76], [160, 29], [29, 30], [30, 160], [56, 157], [157, 173], [173, 56], [106, 204], [204, 194], [194, 106], [135, 214], [214, 192], [192, 135],\n  [203, 165], [165, 98], [98, 203], [21, 71], [71, 68], [68, 21], [51, 45], [45, 4], [4, 51], [144, 24], [24, 23], [23, 144], [77, 146], [146, 91], [91, 77], [205, 50], [50, 187], [187, 205],\n  [201, 200], [200, 18], [18, 201], [91, 106], [106, 182], [182, 91], [90, 91], [91, 181], [181, 90], [85, 84], [84, 17], [17, 85], [206, 203], [203, 36], [36, 206], [148, 171], [171, 140], [140, 148],\n  [92, 40], [40, 39], [39, 92], [193, 189], [189, 244], [244, 193], [159, 158], [158, 28], [28, 159], [247, 246], [246, 161], [161, 247], [236, 3], [3, 196], [196, 236], [54, 68], [68, 104], [104, 54],\n  [193, 168], [168, 8], [8, 193], [117, 228], [228, 31], [31, 117], [189, 193], [193, 55], [55, 189], [98, 97], [97, 99], [99, 98], [126, 47], [47, 100], [100, 126], [166, 79], [79, 218], [218, 166],\n  [155, 154], [154, 26], [26, 155], [209, 49], [49, 131], [131, 209], [135, 136], [136, 150], [150, 135], [47, 126], [126, 217], [217, 47], [223, 52], [52, 53], [53, 223], [45, 51], [51, 134], [134, 45],\n  [211, 170], [170, 140], [140, 211], [67, 69], [69, 108], [108, 67], [43, 106], [106, 91], [91, 43], [230, 119], [119, 120], [120, 230], [226, 130], [130, 247], [247, 226], [63, 53], [53, 52], [52, 63],\n  [238, 20], [20, 242], [242, 238], [46, 70], [70, 156], [156, 46], [78, 62], [62, 96], [96, 78], [46, 53], [53, 63], [63, 46], [143, 34], [34, 227], [227, 143], [123, 117], [117, 111], [111, 123],\n  [44, 125], [125, 19], [19, 44], [236, 134], [134, 51], [51, 236], [216, 206], [206, 205], [205, 216], [154, 153], [153, 22], [22, 154], [39, 37], [37, 167], [167, 39], [200, 201], [201, 208], [208, 200],\n  [36, 142], [142, 100], [100, 36], [57, 212], [212, 202], [202, 57], [20, 60], [60, 99], [99, 20], [28, 158], [158, 157], [157, 28], [35, 226], [226, 113], [113, 35], [160, 159], [159, 27], [27, 160],\n  [204, 202], [202, 210], [210, 204], [113, 225], [225, 46], [46, 113], [43, 202], [202, 204], [204, 43], [62, 76], [76, 77], [77, 62], [137, 123], [123, 116], [116, 137], [41, 38], [38, 72], [72, 41],\n  [203, 129], [129, 142], [142, 203], [64, 98], [98, 240], [240, 64], [49, 102], [102, 64], [64, 49], [41, 73], [73, 74], [74, 41], [212, 216], [216, 207], [207, 212], [42, 74], [74, 184], [184, 42],\n  [169, 170], [170, 211], [211, 169], [170, 149], [149, 176], [176, 170], [105, 66], [66, 69], [69, 105], [122, 6], [6, 168], [168, 122], [123, 147], [147, 187], [187, 123], [96, 77], [77, 90], [90, 96],\n  [65, 55], [55, 107], [107, 65], [89, 90], [90, 180], [180, 89], [101, 100], [100, 120], [120, 101], [63, 105], [105, 104], [104, 63], [93, 137], [137, 227], [227, 93], [15, 86], [86, 85], [85, 15],\n  [129, 102], [102, 49], [49, 129], [14, 87], [87, 86], [86, 14], [55, 8], [8, 9], [9, 55], [100, 47], [47, 121], [121, 100], [145, 23], [23, 22], [22, 145], [88, 89], [89, 179], [179, 88],\n  [6, 122], [122, 196], [196, 6], [88, 95], [95, 96], [96, 88], [138, 172], [172, 136], [136, 138], [215, 58], [58, 172], [172, 215], [115, 48], [48, 219], [219, 115], [42, 80], [80, 81], [81, 42],\n  [195, 3], [3, 51], [51, 195], [43, 146], [146, 61], [61, 43], [171, 175], [175, 199], [199, 171], [81, 82], [82, 38], [38, 81], [53, 46], [46, 225], [225, 53], [144, 163], [163, 110], [110, 144],\n  [52, 65], [65, 66], [66, 52], [229, 228], [228, 117], [117, 229], [34, 127], [127, 234], [234, 34], [107, 108], [108, 69], [69, 107], [109, 108], [108, 151], [151, 109], [48, 64], [64, 235], [235, 48],\n  [62, 78], [78, 191], [191, 62], [129, 209], [209, 126], [126, 129], [111, 35], [35, 143], [143, 111], [117, 123], [123, 50], [50, 117], [222, 65], [65, 52], [52, 222], [19, 125], [125, 141], [141, 19],\n  [221, 55], [55, 65], [65, 221], [3, 195], [195, 197], [197, 3], [25, 7], [7, 33], [33, 25], [220, 237], [237, 44], [44, 220], [70, 71], [71, 139], [139, 70], [122, 193], [193, 245], [245, 122],\n  [247, 130], [130, 33], [33, 247], [71, 21], [21, 162], [162, 71], [170, 169], [169, 150], [150, 170], [188, 174], [174, 196], [196, 188], [216, 186], [186, 92], [92, 216], [2, 97], [97, 167], [167, 2],\n  [141, 125], [125, 241], [241, 141], [164, 167], [167, 37], [37, 164], [72, 38], [38, 12], [12, 72], [38, 82], [82, 13], [13, 38], [63, 68], [68, 71], [71, 63], [226, 35], [35, 111], [111, 226],\n  [101, 50], [50, 205], [205, 101], [206, 92], [92, 165], [165, 206], [209, 198], [198, 217], [217, 209], [165, 167], [167, 97], [97, 165], [220, 115], [115, 218], [218, 220], [133, 112], [112, 243], [243, 133],\n  [239, 238], [238, 241], [241, 239], [214, 135], [135, 169], [169, 214], [190, 173], [173, 133], [133, 190], [171, 208], [208, 32], [32, 171], [125, 44], [44, 237], [237, 125], [86, 87], [87, 178], [178, 86],\n  [85, 86], [86, 179], [179, 85], [84, 85], [85, 180], [180, 84], [83, 84], [84, 181], [181, 83], [201, 83], [83, 182], [182, 201], [137, 93], [93, 132], [132, 137], [76, 62], [62, 183], [183, 76],\n  [61, 76], [76, 184], [184, 61], [57, 61], [61, 185], [185, 57], [212, 57], [57, 186], [186, 212], [214, 207], [207, 187], [187, 214], [34, 143], [143, 156], [156, 34], [79, 239], [239, 237], [237, 79],\n  [123, 137], [137, 177], [177, 123], [44, 1], [1, 4], [4, 44], [201, 194], [194, 32], [32, 201], [64, 102], [102, 129], [129, 64], [213, 215], [215, 138], [138, 213], [59, 166], [166, 219], [219, 59],\n  [242, 99], [99, 97], [97, 242], [2, 94], [94, 141], [141, 2], [75, 59], [59, 235], [235, 75], [24, 110], [110, 228], [228, 24], [25, 130], [130, 226], [226, 25], [23, 24], [24, 229], [229, 23],\n  [22, 23], [23, 230], [230, 22], [26, 22], [22, 231], [231, 26], [112, 26], [26, 232], [232, 112], [189, 190], [190, 243], [243, 189], [221, 56], [56, 190], [190, 221], [28, 56], [56, 221], [221, 28],\n  [27, 28], [28, 222], [222, 27], [29, 27], [27, 223], [223, 29], [30, 29], [29, 224], [224, 30], [247, 30], [30, 225], [225, 247], [238, 79], [79, 20], [20, 238], [166, 59], [59, 75], [75, 166],\n  [60, 75], [75, 240], [240, 60], [147, 177], [177, 215], [215, 147], [20, 79], [79, 166], [166, 20], [187, 147], [147, 213], [213, 187], [112, 233], [233, 244], [244, 112], [233, 128], [128, 245], [245, 233],\n  [128, 114], [114, 188], [188, 128], [114, 217], [217, 174], [174, 114], [131, 115], [115, 220], [220, 131], [217, 198], [198, 236], [236, 217], [198, 131], [131, 134], [134, 198], [177, 132], [132, 58], [58, 177],\n  [143, 35], [35, 124], [124, 143], [110, 163], [163, 7], [7, 110], [228, 110], [110, 25], [25, 228], [356, 389], [389, 368], [368, 356], [11, 302], [302, 267], [267, 11], [452, 350], [350, 349], [349, 452],\n  [302, 303], [303, 269], [269, 302], [357, 343], [343, 277], [277, 357], [452, 453], [453, 357], [357, 452], [333, 332], [332, 297], [297, 333], [175, 152], [152, 377], [377, 175], [347, 348], [348, 330], [330, 347],\n  [303, 304], [304, 270], [270, 303], [9, 336], [336, 337], [337, 9], [278, 279], [279, 360], [360, 278], [418, 262], [262, 431], [431, 418], [304, 408], [408, 409], [409, 304], [310, 415], [415, 407], [407, 310],\n  [270, 409], [409, 410], [410, 270], [450, 348], [348, 347], [347, 450], [422, 430], [430, 434], [434, 422], [313, 314], [314, 17], [17, 313], [306, 307], [307, 375], [375, 306], [387, 388], [388, 260], [260, 387],\n  [286, 414], [414, 398], [398, 286], [335, 406], [406, 418], [418, 335], [364, 367], [367, 416], [416, 364], [423, 358], [358, 327], [327, 423], [251, 284], [284, 298], [298, 251], [281, 5], [5, 4], [4, 281],\n  [373, 374], [374, 253], [253, 373], [307, 320], [320, 321], [321, 307], [425, 427], [427, 411], [411, 425], [421, 313], [313, 18], [18, 421], [321, 405], [405, 406], [406, 321], [320, 404], [404, 405], [405, 320],\n  [315, 16], [16, 17], [17, 315], [426, 425], [425, 266], [266, 426], [377, 400], [400, 369], [369, 377], [322, 391], [391, 269], [269, 322], [417, 465], [465, 464], [464, 417], [386, 257], [257, 258], [258, 386],\n  [466, 260], [260, 388], [388, 466], [456, 399], [399, 419], [419, 456], [284, 332], [332, 333], [333, 284], [417, 285], [285, 8], [8, 417], [346, 340], [340, 261], [261, 346], [413, 441], [441, 285], [285, 413],\n  [327, 460], [460, 328], [328, 327], [355, 371], [371, 329], [329, 355], [392, 439], [439, 438], [438, 392], [382, 341], [341, 256], [256, 382], [429, 420], [420, 360], [360, 429], [364, 394], [394, 379], [379, 364],\n  [277, 343], [343, 437], [437, 277], [443, 444], [444, 283], [283, 443], [275, 440], [440, 363], [363, 275], [431, 262], [262, 369], [369, 431], [297, 338], [338, 337], [337, 297], [273, 375], [375, 321], [321, 273],\n  [450, 451], [451, 349], [349, 450], [446, 342], [342, 467], [467, 446], [293, 334], [334, 282], [282, 293], [458, 461], [461, 462], [462, 458], [276, 353], [353, 383], [383, 276], [308, 324], [324, 325], [325, 308],\n  [276, 300], [300, 293], [293, 276], [372, 345], [345, 447], [447, 372], [352, 345], [345, 340], [340, 352], [274, 1], [1, 19], [19, 274], [456, 248], [248, 281], [281, 456], [436, 427], [427, 425], [425, 436],\n  [381, 256], [256, 252], [252, 381], [269, 391], [391, 393], [393, 269], [200, 199], [199, 428], [428, 200], [266, 330], [330, 329], [329, 266], [287, 273], [273, 422], [422, 287], [250, 462], [462, 328], [328, 250],\n  [258, 286], [286, 384], [384, 258], [265, 353], [353, 342], [342, 265], [387, 259], [259, 257], [257, 387], [424, 431], [431, 430], [430, 424], [342, 353], [353, 276], [276, 342], [273, 335], [335, 424], [424, 273],\n  [292, 325], [325, 307], [307, 292], [366, 447], [447, 345], [345, 366], [271, 303], [303, 302], [302, 271], [423, 266], [266, 371], [371, 423], [294, 455], [455, 460], [460, 294], [279, 278], [278, 294], [294, 279],\n  [271, 272], [272, 304], [304, 271], [432, 434], [434, 427], [427, 432], [272, 407], [407, 408], [408, 272], [394, 430], [430, 431], [431, 394], [395, 369], [369, 400], [400, 395], [334, 333], [333, 299], [299, 334],\n  [351, 417], [417, 168], [168, 351], [352, 280], [280, 411], [411, 352], [325, 319], [319, 320], [320, 325], [295, 296], [296, 336], [336, 295], [319, 403], [403, 404], [404, 319], [330, 348], [348, 349], [349, 330],\n  [293, 298], [298, 333], [333, 293], [323, 454], [454, 447], [447, 323], [15, 16], [16, 315], [315, 15], [358, 429], [429, 279], [279, 358], [14, 15], [15, 316], [316, 14], [285, 336], [336, 9], [9, 285],\n  [329, 349], [349, 350], [350, 329], [374, 380], [380, 252], [252, 374], [318, 402], [402, 403], [403, 318], [6, 197], [197, 419], [419, 6], [318, 319], [319, 325], [325, 318], [367, 364], [364, 365], [365, 367],\n  [435, 367], [367, 397], [397, 435], [344, 438], [438, 439], [439, 344], [272, 271], [271, 311], [311, 272], [195, 5], [5, 281], [281, 195], [273, 287], [287, 291], [291, 273], [396, 428], [428, 199], [199, 396],\n  [311, 271], [271, 268], [268, 311], [283, 444], [444, 445], [445, 283], [373, 254], [254, 339], [339, 373], [282, 334], [334, 296], [296, 282], [449, 347], [347, 346], [346, 449], [264, 447], [447, 454], [454, 264],\n  [336, 296], [296, 299], [299, 336], [338, 10], [10, 151], [151, 338], [278, 439], [439, 455], [455, 278], [292, 407], [407, 415], [415, 292], [358, 371], [371, 355], [355, 358], [340, 345], [345, 372], [372, 340],\n  [346, 347], [347, 280], [280, 346], [442, 443], [443, 282], [282, 442], [19, 94], [94, 370], [370, 19], [441, 442], [442, 295], [295, 441], [248, 419], [419, 197], [197, 248], [263, 255], [255, 359], [359, 263],\n  [440, 275], [275, 274], [274, 440], [300, 383], [383, 368], [368, 300], [351, 412], [412, 465], [465, 351], [263, 467], [467, 466], [466, 263], [301, 368], [368, 389], [389, 301], [395, 378], [378, 379], [379, 395],\n  [412, 351], [351, 419], [419, 412], [436, 426], [426, 322], [322, 436], [2, 164], [164, 393], [393, 2], [370, 462], [462, 461], [461, 370], [164, 0], [0, 267], [267, 164], [302, 11], [11, 12], [12, 302],\n  [268, 12], [12, 13], [13, 268], [293, 300], [300, 301], [301, 293], [446, 261], [261, 340], [340, 446], [330, 266], [266, 425], [425, 330], [426, 423], [423, 391], [391, 426], [429, 355], [355, 437], [437, 429],\n  [391, 327], [327, 326], [326, 391], [440, 457], [457, 438], [438, 440], [341, 382], [382, 362], [362, 341], [459, 457], [457, 461], [461, 459], [434, 430], [430, 394], [394, 434], [414, 463], [463, 362], [362, 414],\n  [396, 369], [369, 262], [262, 396], [354, 461], [461, 457], [457, 354], [316, 403], [403, 402], [402, 316], [315, 404], [404, 403], [403, 315], [314, 405], [405, 404], [404, 314], [313, 406], [406, 405], [405, 313],\n  [421, 418], [418, 406], [406, 421], [366, 401], [401, 361], [361, 366], [306, 408], [408, 407], [407, 306], [291, 409], [409, 408], [408, 291], [287, 410], [410, 409], [409, 287], [432, 436], [436, 410], [410, 432],\n  [434, 416], [416, 411], [411, 434], [264, 368], [368, 383], [383, 264], [309, 438], [438, 457], [457, 309], [352, 376], [376, 401], [401, 352], [274, 275], [275, 4], [4, 274], [421, 428], [428, 262], [262, 421],\n  [294, 327], [327, 358], [358, 294], [433, 416], [416, 367], [367, 433], [289, 455], [455, 439], [439, 289], [462, 370], [370, 326], [326, 462], [2, 326], [326, 370], [370, 2], [305, 460], [460, 455], [455, 305],\n  [254, 449], [449, 448], [448, 254], [255, 261], [261, 446], [446, 255], [253, 450], [450, 449], [449, 253], [252, 451], [451, 450], [450, 252], [256, 452], [452, 451], [451, 256], [341, 453], [453, 452], [452, 341],\n  [413, 464], [464, 463], [463, 413], [441, 413], [413, 414], [414, 441], [258, 442], [442, 441], [441, 258], [257, 443], [443, 442], [442, 257], [259, 444], [444, 443], [443, 259], [260, 445], [445, 444], [444, 260],\n  [467, 342], [342, 445], [445, 467], [459, 458], [458, 250], [250, 459], [289, 392], [392, 290], [290, 289], [290, 328], [328, 460], [460, 290], [376, 433], [433, 435], [435, 376], [250, 290], [290, 392], [392, 250],\n  [411, 416], [416, 433], [433, 411], [341, 463], [463, 464], [464, 341], [453, 464], [464, 465], [465, 453], [357, 465], [465, 412], [412, 357], [343, 412], [412, 399], [399, 343], [360, 363], [363, 440], [440, 360],\n  [437, 399], [399, 456], [456, 437], [420, 456], [456, 363], [363, 420], [401, 435], [435, 288], [288, 401], [372, 383], [383, 353], [353, 372], [339, 255], [255, 249], [249, 339], [448, 261], [261, 255], [255, 448],\n  [133, 243], [243, 190], [190, 133], [133, 155], [155, 112], [112, 133], [33, 246], [246, 247], [247, 33], [33, 130], [130, 25], [25, 33], [398, 384], [384, 286], [286, 398], [362, 398], [398, 414], [414, 362],\n  [362, 463], [463, 341], [341, 362], [263, 359], [359, 467], [467, 263], [263, 249], [249, 255], [255, 263], [466, 467], [467, 260], [260, 466], [75, 60], [60, 166], [166, 75], [238, 239], [239, 79], [79, 238],\n  [162, 127], [127, 139], [139, 162], [72, 11], [11, 37], [37, 72], [121, 232], [232, 120], [120, 121], [73, 72], [72, 39], [39, 73], [114, 128], [128, 47], [47, 114], [233, 232], [232, 128], [128, 233],\n  [103, 104], [104, 67], [67, 103], [152, 175], [175, 148], [148, 152], [119, 118], [118, 101], [101, 119], [74, 73], [73, 40], [40, 74], [107, 9], [9, 108], [108, 107], [49, 48], [48, 131], [131, 49],\n  [32, 194], [194, 211], [211, 32], [184, 74], [74, 185], [185, 184], [191, 80], [80, 183], [183, 191], [185, 40], [40, 186], [186, 185], [119, 230], [230, 118], [118, 119], [210, 202], [202, 214], [214, 210],\n  [84, 83], [83, 17], [17, 84], [77, 76], [76, 146], [146, 77], [161, 160], [160, 30], [30, 161], [190, 56], [56, 173], [173, 190], [182, 106], [106, 194], [194, 182], [138, 135], [135, 192], [192, 138],\n  [129, 203], [203, 98], [98, 129], [54, 21], [21, 68], [68, 54], [5, 51], [51, 4], [4, 5], [145, 144], [144, 23], [23, 145], [90, 77], [77, 91], [91, 90], [207, 205], [205, 187], [187, 207],\n  [83, 201], [201, 18], [18, 83], [181, 91], [91, 182], [182, 181], [180, 90], [90, 181], [181, 180], [16, 85], [85, 17], [17, 16], [205, 206], [206, 36], [36, 205], [176, 148], [148, 140], [140, 176],\n  [165, 92], [92, 39], [39, 165], [245, 193], [193, 244], [244, 245], [27, 159], [159, 28], [28, 27], [30, 247], [247, 161], [161, 30], [174, 236], [236, 196], [196, 174], [103, 54], [54, 104], [104, 103],\n  [55, 193], [193, 8], [8, 55], [111, 117], [117, 31], [31, 111], [221, 189], [189, 55], [55, 221], [240, 98], [98, 99], [99, 240], [142, 126], [126, 100], [100, 142], [219, 166], [166, 218], [218, 219],\n  [112, 155], [155, 26], [26, 112], [198, 209], [209, 131], [131, 198], [169, 135], [135, 150], [150, 169], [114, 47], [47, 217], [217, 114], [224, 223], [223, 53], [53, 224], [220, 45], [45, 134], [134, 220],\n  [32, 211], [211, 140], [140, 32], [109, 67], [67, 108], [108, 109], [146, 43], [43, 91], [91, 146], [231, 230], [230, 120], [120, 231], [113, 226], [226, 247], [247, 113], [105, 63], [63, 52], [52, 105],\n  [241, 238], [238, 242], [242, 241], [124, 46], [46, 156], [156, 124], [95, 78], [78, 96], [96, 95], [70, 46], [46, 63], [63, 70], [116, 143], [143, 227], [227, 116], [116, 123], [123, 111], [111, 116],\n  [1, 44], [44, 19], [19, 1], [3, 236], [236, 51], [51, 3], [207, 216], [216, 205], [205, 207], [26, 154], [154, 22], [22, 26], [165, 39], [39, 167], [167, 165], [199, 200], [200, 208], [208, 199],\n  [101, 36], [36, 100], [100, 101], [43, 57], [57, 202], [202, 43], [242, 20], [20, 99], [99, 242], [56, 28], [28, 157], [157, 56], [124, 35], [35, 113], [113, 124], [29, 160], [160, 27], [27, 29],\n  [211, 204], [204, 210], [210, 211], [124, 113], [113, 46], [46, 124], [106, 43], [43, 204], [204, 106], [96, 62], [62, 77], [77, 96], [227, 137], [137, 116], [116, 227], [73, 41], [41, 72], [72, 73],\n  [36, 203], [203, 142], [142, 36], [235, 64], [64, 240], [240, 235], [48, 49], [49, 64], [64, 48], [42, 41], [41, 74], [74, 42], [214, 212], [212, 207], [207, 214], [183, 42], [42, 184], [184, 183],\n  [210, 169], [169, 211], [211, 210], [140, 170], [170, 176], [176, 140], [104, 105], [105, 69], [69, 104], [193, 122], [122, 168], [168, 193], [50, 123], [123, 187], [187, 50], [89, 96], [96, 90], [90, 89],\n  [66, 65], [65, 107], [107, 66], [179, 89], [89, 180], [180, 179], [119, 101], [101, 120], [120, 119], [68, 63], [63, 104], [104, 68], [234, 93], [93, 227], [227, 234], [16, 15], [15, 85], [85, 16],\n  [209, 129], [129, 49], [49, 209], [15, 14], [14, 86], [86, 15], [107, 55], [55, 9], [9, 107], [120, 100], [100, 121], [121, 120], [153, 145], [145, 22], [22, 153], [178, 88], [88, 179], [179, 178],\n  [197, 6], [6, 196], [196, 197], [89, 88], [88, 96], [96, 89], [135, 138], [138, 136], [136, 135], [138, 215], [215, 172], [172, 138], [218, 115], [115, 219], [219, 218], [41, 42], [42, 81], [81, 41],\n  [5, 195], [195, 51], [51, 5], [57, 43], [43, 61], [61, 57], [208, 171], [171, 199], [199, 208], [41, 81], [81, 38], [38, 41], [224, 53], [53, 225], [225, 224], [24, 144], [144, 110], [110, 24],\n  [105, 52], [52, 66], [66, 105], [118, 229], [229, 117], [117, 118], [227, 34], [34, 234], [234, 227], [66, 107], [107, 69], [69, 66], [10, 109], [109, 151], [151, 10], [219, 48], [48, 235], [235, 219],\n  [183, 62], [62, 191], [191, 183], [142, 129], [129, 126], [126, 142], [116, 111], [111, 143], [143, 116], [118, 117], [117, 50], [50, 118], [223, 222], [222, 52], [52, 223], [94, 19], [19, 141], [141, 94],\n  [222, 221], [221, 65], [65, 222], [196, 3], [3, 197], [197, 196], [45, 220], [220, 44], [44, 45], [156, 70], [70, 139], [139, 156], [188, 122], [122, 245], [245, 188], [139, 71], [71, 162], [162, 139],\n  [149, 170], [170, 150], [150, 149], [122, 188], [188, 196], [196, 122], [206, 216], [216, 92], [92, 206], [164, 2], [2, 167], [167, 164], [242, 141], [141, 241], [241, 242], [0, 164], [164, 37], [37, 0],\n  [11, 72], [72, 12], [12, 11], [12, 38], [38, 13], [13, 12], [70, 63], [63, 71], [71, 70], [31, 226], [226, 111], [111, 31], [36, 101], [101, 205], [205, 36], [203, 206], [206, 165], [165, 203],\n  [126, 209], [209, 217], [217, 126], [98, 165], [165, 97], [97, 98], [237, 220], [220, 218], [218, 237], [237, 239], [239, 241], [241, 237], [210, 214], [214, 169], [169, 210], [140, 171], [171, 32], [32, 140],\n  [241, 125], [125, 237], [237, 241], [179, 86], [86, 178], [178, 179], [180, 85], [85, 179], [179, 180], [181, 84], [84, 180], [180, 181], [182, 83], [83, 181], [181, 182], [194, 201], [201, 182], [182, 194],\n  [177, 137], [137, 132], [132, 177], [184, 76], [76, 183], [183, 184], [185, 61], [61, 184], [184, 185], [186, 57], [57, 185], [185, 186], [216, 212], [212, 186], [186, 216], [192, 214], [214, 187], [187, 192],\n  [139, 34], [34, 156], [156, 139], [218, 79], [79, 237], [237, 218], [147, 123], [123, 177], [177, 147], [45, 44], [44, 4], [4, 45], [208, 201], [201, 32], [32, 208], [98, 64], [64, 129], [129, 98],\n  [192, 213], [213, 138], [138, 192], [235, 59], [59, 219], [219, 235], [141, 242], [242, 97], [97, 141], [97, 2], [2, 141], [141, 97], [240, 75], [75, 235], [235, 240], [229, 24], [24, 228], [228, 229],\n  [31, 25], [25, 226], [226, 31], [230, 23], [23, 229], [229, 230], [231, 22], [22, 230], [230, 231], [232, 26], [26, 231], [231, 232], [233, 112], [112, 232], [232, 233], [244, 189], [189, 243], [243, 244],\n  [189, 221], [221, 190], [190, 189], [222, 28], [28, 221], [221, 222], [223, 27], [27, 222], [222, 223], [224, 29], [29, 223], [223, 224], [225, 30], [30, 224], [224, 225], [113, 247], [247, 225], [225, 113],\n  [99, 60], [60, 240], [240, 99], [213, 147], [147, 215], [215, 213], [60, 20], [20, 166], [166, 60], [192, 187], [187, 213], [213, 192], [243, 112], [112, 244], [244, 243], [244, 233], [233, 245], [245, 244],\n  [245, 128], [128, 188], [188, 245], [188, 114], [114, 174], [174, 188], [134, 131], [131, 220], [220, 134], [174, 217], [217, 236], [236, 174], [236, 198], [198, 134], [134, 236], [215, 177], [177, 58], [58, 215],\n  [156, 143], [143, 124], [124, 156], [25, 110], [110, 7], [7, 25], [31, 228], [228, 25], [25, 31], [264, 356], [356, 368], [368, 264], [0, 11], [11, 267], [267, 0], [451, 452], [452, 349], [349, 451],\n  [267, 302], [302, 269], [269, 267], [350, 357], [357, 277], [277, 350], [350, 452], [452, 357], [357, 350], [299, 333], [333, 297], [297, 299], [396, 175], [175, 377], [377, 396], [280, 347], [347, 330], [330, 280],\n  [269, 303], [303, 270], [270, 269], [151, 9], [9, 337], [337, 151], [344, 278], [278, 360], [360, 344], [424, 418], [418, 431], [431, 424], [270, 304], [304, 409], [409, 270], [272, 310], [310, 407], [407, 272],\n  [322, 270], [270, 410], [410, 322], [449, 450], [450, 347], [347, 449], [432, 422], [422, 434], [434, 432], [18, 313], [313, 17], [17, 18], [291, 306], [306, 375], [375, 291], [259, 387], [387, 260], [260, 259],\n  [424, 335], [335, 418], [418, 424], [434, 364], [364, 416], [416, 434], [391, 423], [423, 327], [327, 391], [301, 251], [251, 298], [298, 301], [275, 281], [281, 4], [4, 275], [254, 373], [373, 253], [253, 254],\n  [375, 307], [307, 321], [321, 375], [280, 425], [425, 411], [411, 280], [200, 421], [421, 18], [18, 200], [335, 321], [321, 406], [406, 335], [321, 320], [320, 405], [405, 321], [314, 315], [315, 17], [17, 314],\n  [423, 426], [426, 266], [266, 423], [396, 377], [377, 369], [369, 396], [270, 322], [322, 269], [269, 270], [413, 417], [417, 464], [464, 413], [385, 386], [386, 258], [258, 385], [248, 456], [456, 419], [419, 248],\n  [298, 284], [284, 333], [333, 298], [168, 417], [417, 8], [8, 168], [448, 346], [346, 261], [261, 448], [417, 413], [413, 285], [285, 417], [326, 327], [327, 328], [328, 326], [277, 355], [355, 329], [329, 277],\n  [309, 392], [392, 438], [438, 309], [381, 382], [382, 256], [256, 381], [279, 429], [429, 360], [360, 279], [365, 364], [364, 379], [379, 365], [355, 277], [277, 437], [437, 355], [282, 443], [443, 283], [283, 282],\n  [281, 275], [275, 363], [363, 281], [395, 431], [431, 369], [369, 395], [299, 297], [297, 337], [337, 299], [335, 273], [273, 321], [321, 335], [348, 450], [450, 349], [349, 348], [359, 446], [446, 467], [467, 359],\n  [283, 293], [293, 282], [282, 283], [250, 458], [458, 462], [462, 250], [300, 276], [276, 383], [383, 300], [292, 308], [308, 325], [325, 292], [283, 276], [276, 293], [293, 283], [264, 372], [372, 447], [447, 264],\n  [346, 352], [352, 340], [340, 346], [354, 274], [274, 19], [19, 354], [363, 456], [456, 281], [281, 363], [426, 436], [436, 425], [425, 426], [380, 381], [381, 252], [252, 380], [267, 269], [269, 393], [393, 267],\n  [421, 200], [200, 428], [428, 421], [371, 266], [266, 329], [329, 371], [432, 287], [287, 422], [422, 432], [290, 250], [250, 328], [328, 290], [385, 258], [258, 384], [384, 385], [446, 265], [265, 342], [342, 446],\n  [386, 387], [387, 257], [257, 386], [422, 424], [424, 430], [430, 422], [445, 342], [342, 276], [276, 445], [422, 273], [273, 424], [424, 422], [306, 292], [292, 307], [307, 306], [352, 366], [366, 345], [345, 352],\n  [268, 271], [271, 302], [302, 268], [358, 423], [423, 371], [371, 358], [327, 294], [294, 460], [460, 327], [331, 279], [279, 294], [294, 331], [303, 271], [271, 304], [304, 303], [436, 432], [432, 427], [427, 436],\n  [304, 272], [272, 408], [408, 304], [395, 394], [394, 431], [431, 395], [378, 395], [395, 400], [400, 378], [296, 334], [334, 299], [299, 296], [6, 351], [351, 168], [168, 6], [376, 352], [352, 411], [411, 376],\n  [307, 325], [325, 320], [320, 307], [285, 295], [295, 336], [336, 285], [320, 319], [319, 404], [404, 320], [329, 330], [330, 349], [349, 329], [334, 293], [293, 333], [333, 334], [366, 323], [323, 447], [447, 366],\n  [316, 15], [15, 315], [315, 316], [331, 358], [358, 279], [279, 331], [317, 14], [14, 316], [316, 317], [8, 285], [285, 9], [9, 8], [277, 329], [329, 350], [350, 277], [253, 374], [374, 252], [252, 253],\n  [319, 318], [318, 403], [403, 319], [351, 6], [6, 419], [419, 351], [324, 318], [318, 325], [325, 324], [397, 367], [367, 365], [365, 397], [288, 435], [435, 397], [397, 288], [278, 344], [344, 439], [439, 278],\n  [310, 272], [272, 311], [311, 310], [248, 195], [195, 281], [281, 248], [375, 273], [273, 291], [291, 375], [175, 396], [396, 199], [199, 175], [312, 311], [311, 268], [268, 312], [276, 283], [283, 445], [445, 276],\n  [390, 373], [373, 339], [339, 390], [295, 282], [282, 296], [296, 295], [448, 449], [449, 346], [346, 448], [356, 264], [264, 454], [454, 356], [337, 336], [336, 299], [299, 337], [337, 338], [338, 151], [151, 337],\n  [294, 278], [278, 455], [455, 294], [308, 292], [292, 415], [415, 308], [429, 358], [358, 355], [355, 429], [265, 340], [340, 372], [372, 265], [352, 346], [346, 280], [280, 352], [295, 442], [442, 282], [282, 295],\n  [354, 19], [19, 370], [370, 354], [285, 441], [441, 295], [295, 285], [195, 248], [248, 197], [197, 195], [457, 440], [440, 274], [274, 457], [301, 300], [300, 368], [368, 301], [417, 351], [351, 465], [465, 417],\n  [251, 301], [301, 389], [389, 251], [394, 395], [395, 379], [379, 394], [399, 412], [412, 419], [419, 399], [410, 436], [436, 322], [322, 410], [326, 2], [2, 393], [393, 326], [354, 370], [370, 461], [461, 354],\n  [393, 164], [164, 267], [267, 393], [268, 302], [302, 12], [12, 268], [312, 268], [268, 13], [13, 312], [298, 293], [293, 301], [301, 298], [265, 446], [446, 340], [340, 265], [280, 330], [330, 425], [425, 280],\n  [322, 426], [426, 391], [391, 322], [420, 429], [429, 437], [437, 420], [393, 391], [391, 326], [326, 393], [344, 440], [440, 438], [438, 344], [458, 459], [459, 461], [461, 458], [364, 434], [434, 394], [394, 364],\n  [428, 396], [396, 262], [262, 428], [274, 354], [354, 457], [457, 274], [317, 316], [316, 402], [402, 317], [316, 315], [315, 403], [403, 316], [315, 314], [314, 404], [404, 315], [314, 313], [313, 405], [405, 314],\n  [313, 421], [421, 406], [406, 313], [323, 366], [366, 361], [361, 323], [292, 306], [306, 407], [407, 292], [306, 291], [291, 408], [408, 306], [291, 287], [287, 409], [409, 291], [287, 432], [432, 410], [410, 287],\n  [427, 434], [434, 411], [411, 427], [372, 264], [264, 383], [383, 372], [459, 309], [309, 457], [457, 459], [366, 352], [352, 401], [401, 366], [1, 274], [274, 4], [4, 1], [418, 421], [421, 262], [262, 418],\n  [331, 294], [294, 358], [358, 331], [435, 433], [433, 367], [367, 435], [392, 289], [289, 439], [439, 392], [328, 462], [462, 326], [326, 328], [94, 2], [2, 370], [370, 94], [289, 305], [305, 455], [455, 289],\n  [339, 254], [254, 448], [448, 339], [359, 255], [255, 446], [446, 359], [254, 253], [253, 449], [449, 254], [253, 252], [252, 450], [450, 253], [252, 256], [256, 451], [451, 252], [256, 341], [341, 452], [452, 256],\n  [414, 413], [413, 463], [463, 414], [286, 441], [441, 414], [414, 286], [286, 258], [258, 441], [441, 286], [258, 257], [257, 442], [442, 258], [257, 259], [259, 443], [443, 257], [259, 260], [260, 444], [444, 259],\n  [260, 467], [467, 445], [445, 260], [309, 459], [459, 250], [250, 309], [305, 289], [289, 290], [290, 305], [305, 290], [290, 460], [460, 305], [401, 376], [376, 435], [435, 401], [309, 250], [250, 392], [392, 309],\n  [376, 411], [411, 433], [433, 376], [453, 341], [341, 464], [464, 453], [357, 453], [453, 465], [465, 357], [343, 357], [357, 412], [412, 343], [437, 343], [343, 399], [399, 437], [344, 360], [360, 440], [440, 344],\n  [420, 437], [437, 456], [456, 420], [360, 420], [420, 363], [363, 360], [361, 401], [401, 288], [288, 361], [265, 372], [372, 353], [353, 265], [390, 339], [339, 249], [249, 390], [339, 448], [448, 255], [255, 339],\n];\n\nfunction connectionsToIndices(connections: PairArray) {\n  const indices = connections.map((connection) => connection[0]);\n  indices.push(connections[connections.length - 1][1]);\n  return indices;\n}\n\nexport const MEDIAPIPE_FACE_MESH_KEYPOINTS_BY_CONTOUR = {\n  lips: connectionsToIndices(LIPS_CONNECTIONS),\n  leftEye: connectionsToIndices(LEFT_EYE_CONNECTIONS),\n  leftEyebrow: connectionsToIndices(LEFT_EYEBROW_CONNECTIONS),\n  leftIris: connectionsToIndices(LEFT_IRIS_CONNECTIONS),\n  rightEye: connectionsToIndices(RIGHT_EYE_CONNECTIONS),\n  rightEyebrow: connectionsToIndices(RIGHT_EYEBROW_CONNECTIONS),\n  rightIris: connectionsToIndices(RIGHT_IRIS_CONNECTIONS),\n  faceOval: connectionsToIndices(FACE_OVAL_CONNECTIONS),\n};\n\nconst indexLabelPairs: Array<[number, string]> = Object.entries(MEDIAPIPE_FACE_MESH_KEYPOINTS_BY_CONTOUR)\n  .map(([label, indices]) => indices.map((index) => [index, label] as [number, string]))\n  .flat();\n\nexport const MEDIAPIPE_FACE_MESH_KEYPOINTS = new Map(indexLabelPairs);\n\ntype AssignAverage = number[];\nexport interface LandmarksRefinementConfig {\n  indexesMapping: number[]; // Maps indexes of the given set of landmarks to indexes of the resulting set of landmarks. Should be non empty and contain the same amount of indexes as landmarks in the corresponding input\n  zRefinement: 'none'|'copy'|AssignAverage; // Z refinement instructions.\n}\n\nexport const LANDMARKS_REFINEMENT_LIPS_CONFIG = [\n  61, 146, 91, 181, 84, 17, 314, 405, 321, 375, 291, // Lower outer.\n  185, 40, 39, 37, 0, 267, 269, 270, 409, // Upper outer(excluding corners).\n  78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308, // Lower inner.\n  191, 80, 81, 82, 13, 312, 311, 310, 415, // Upper inner(excluding corners).\n  76, 77, 90, 180, 85, 16, 315, 404, 320, 307, 306, // Lower semi - outer.\n  184, 74, 73, 72, 11, 302, 303, 304, 408, // Upper semi - outer(excluding corners).\n  62, 96, 89, 179, 86, 15, 316, 403, 319, 325, 292, // Lower semi - inner.\n  183, 42, 41, 38, 12, 268, 271, 272, 407, // Upper semi - inner(excluding corners).\n];\n\nexport const LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG = [\n  33, 7, 163, 144, 145, 153, 154, 155, 133, // Lower contour.\n  246, 161, 160, 159, 158, 157, 173, // upper contour (excluding corners).\n  130, 25, 110, 24, 23, 22, 26, 112, 243, // Halo x2 lower contour.\n  247, 30, 29, 27, 28, 56, 190, // Halo x2 upper contour (excluding corners).\n  226, 31, 228, 229, 230, 231, 232, 233, 244, // Halo x3 lower contour.\n  113, 225, 224, 223, 222, 221, 189, // Halo x3 upper contour (excluding corners).\n  35, 124, 46, 53, 52, 65, // Halo x4 upper contour (no lower because of mesh structure) or eyebrow inner contour.\n  143, 111, 117, 118, 119, 120, 121, 128, 245, // Halo x5 lower contour.\n  156, 70, 63, 105, 66, 107, 55, 193, // Halo x5 upper contour (excluding corners) or eyebrow outer contour.\n];\n\nexport const LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG = [\n  263, 249, 390, 373, 374, 380, 381, 382, 362, // Lower contour.\n  466, 388, 387, 386, 385, 384, 398, // Upper contour (excluding corners).\n  359, 255, 339, 254, 253, 252, 256, 341, 463, // Halo x2 lower contour.\n  467, 260, 259, 257, 258, 286, 414, // Halo x2 upper contour (excluding corners).\n  446, 261, 448, 449, 450, 451, 452, 453, 464, // Halo x3 lower contour.\n  342, 445, 444, 443, 442, 441, 413, // Halo x3 upper contour (excluding corners).\n  265, 353, 276, 283, 282, 295, // Halo x4 upper contour (no lower because of mesh structure) or/ eyebrow inner contour.\n  372, 340, 346, 347, 348, 349, 350, 357, 465, // Halo x5 lower contour.\n  383, 300, 293, 334, 296, 336, 285, 417, // Halo x5 upper contour (excluding corners) or eyebrow outer contour.\n];\n\nexport const LANDMARKS_REFINEMENT_LEFT_IRIS_CONFIG = [\n  468, // Center.\n  469, // Iris right edge.\n  470, // Iris top edge.\n  471, // Iris left edge.\n  472, // Iris bottom edge.\n];\n/*\nzRefinement: [\n  33, 7, 163, 144, 145, 153, 154, 155, 133, // Lower contour.\n  246, 161, 160, 159, 158, 157, 173, // Upper contour (excluding corners).\n];\n*/\n\nexport const LANDMARKS_REFINEMENT_RIGHT_IRIS_CONFIG = [\n  473, // Center.\n  474, // Iris right edge.\n  475, // Iris top edge.\n  476, // Iris left edge.\n  477, // Iris bottom edge.\n];\n/*\nzRefinement: [\n  263, 249, 390, 373, 374, 380, 381, 382, 362, // Lower contour.\n  466, 388, 387, 386, 385, 384, 398, // Upper contour (excluding corners).\n];\n*/\n", "import * as constants from './constants';\nimport type { Tensor } from '../tfjs/types';\n\nexport async function augment(rawCoords, results: Tensor[]) {\n  const t: Record<string, Float32Array> = { // all attention models produce 2d results so it needs to be later augmented with correct z-coords\n    // mesh: results[0], // already have it in rawCoords // output_mesh_identity\n    // flag: results[1], // already processed in parent // conv_faceflag\n    lips: await results.filter((r) => r.size === 160)[0].data() as Float32Array, // 80 x 2d = 160 // output_lips\n    irisL: await results.filter((r) => r.size === 10)[0].data() as Float32Array, // 5 x 2d = 10 // output_right_iris\n    eyeL: await results.filter((r) => r.size === 142)[0].data() as Float32Array, // 71 x 2d = 142 // output_right_eye\n    irisR: await results.filter((r) => r.size === 10)[1].data() as Float32Array, // 5 x 2d = 10 // output_left_iris\n    eyeR: await results.filter((r) => r.size === 142)[1].data() as Float32Array, // 71 x 2d = 142// output_left_eye\n  };\n\n  // augment iris: adds additional 5 keypoints per eye\n  const irisLDepth = constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG.reduce((prev, curr) => prev += rawCoords[curr][2], 0) / constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG.length; // get average z-coord for iris\n  for (let i = 0; i < t.irisL.length / 2; i++) rawCoords.push([t.irisL[2 * i + 0], t.irisL[2 * i + 1], irisLDepth]);\n  const irisRDepth = constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG.reduce((prev, curr) => prev += rawCoords[curr][2], 0) / constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG.length; // get average z-coord for iris\n  for (let i = 0; i < t.irisR.length / 2; i++) rawCoords.push([t.irisR[2 * i + 0], t.irisR[2 * i + 1], irisRDepth]);\n\n  // augment eyes: replaces eye keypoints based on heuristic mapping\n  for (let i = 0; i < t.eyeL.length / 2; i++) rawCoords[constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG[i]] = [t.eyeL[2 * i + 0], t.eyeL[2 * i + 1], rawCoords[constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG[i]][2]];\n  for (let i = 0; i < t.eyeR.length / 2; i++) rawCoords[constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG[i]] = [t.eyeR[2 * i + 0], t.eyeR[2 * i + 1], rawCoords[constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG[i]][2]];\n\n  // augment lips: replaces eye keypoints based on heuristic mapping\n  for (let i = 0; i < t.lips.length / 2; i++) rawCoords[constants.LANDMARKS_REFINEMENT_LIPS_CONFIG[i]] = [t.lips[2 * i + 0], t.lips[2 * i + 1], rawCoords[constants.LANDMARKS_REFINEMENT_LIPS_CONFIG[i]][2]];\n\n  return rawCoords;\n}\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n *\n * Based on:\n * - [**MediaPipe BlazeFace**](https://drive.google.com/file/d/1f39lSzU5Oq-j_OXgS67KfN5wNsoeAZ4V/view)\n * - Facial Spacial Geometry: [**MediaPipe FaceMesh**](https://drive.google.com/file/d/1VFC_wIpw4O7xBOiTgUldl79d9LA-LsnA/view)\n * - Eye Iris Details: [**MediaPipe Iris**](https://drive.google.com/file/d/1bsWbokp9AklH2ANjCfmjqEzzxO1CNbMu/view)\n */\n\nimport { log, now } from '../util/util';\nimport { loadModel } from '../tfjs/load';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as util from './facemeshutil';\nimport * as coords from './facemeshcoords';\nimport * as iris from './iris';\nimport * as attention from './attention';\nimport { histogramEqualization } from '../image/enhance';\nimport { env } from '../util/env';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { FaceResult, FaceLandmark, Point } from '../result';\nimport type { Config } from '../config';\n\ntype DetectBox = { startPoint: Point, endPoint: Point, landmarks: Array<Point>, confidence: number };\n\nconst cache = {\n  boxes: [] as DetectBox[],\n  skipped: Number.MAX_SAFE_INTEGER,\n  timestamp: 0,\n};\n\nlet model: GraphModel | null = null;\nlet inputSize = 0;\n\nexport async function predict(input: Tensor, config: Config): Promise<FaceResult[]> {\n  // reset cached boxes\n  const skipTime = (config.face.detector?.skipTime || 0) > (now() - cache.timestamp);\n  const skipFrame = cache.skipped < (config.face.detector?.skipFrames || 0);\n  if (!config.skipAllowed || !skipTime || !skipFrame || cache.boxes.length === 0) {\n    cache.boxes = await blazeface.getBoxes(input, config); // get results from blazeface detector\n    cache.timestamp = now();\n    cache.skipped = 0;\n  } else {\n    cache.skipped++;\n  }\n  const faces: Array<FaceResult> = [];\n  const newCache: Array<DetectBox> = [];\n  let id = 0;\n  for (let i = 0; i < cache.boxes.length; i++) {\n    const box = cache.boxes[i];\n    let angle = 0;\n    let rotationMatrix;\n    const face: FaceResult = { // init face result\n      id: id++,\n      mesh: [],\n      meshRaw: [],\n      box: [0, 0, 0, 0],\n      boxRaw: [0, 0, 0, 0],\n      score: 0,\n      boxScore: 0,\n      faceScore: 0,\n      // contoursRaw: [],\n      // contours: [],\n      annotations: {} as Record<FaceLandmark, Point[]>,\n    };\n\n    // optional rotation correction based on detector data only if mesh is disabled otherwise perform it later when we have more accurate mesh data. if no rotation correction this function performs crop\n    [angle, rotationMatrix, face.tensor] = util.correctFaceRotation(config.face.detector?.rotation, box, input, config.face.mesh?.enabled ? inputSize : blazeface.size());\n    if (config?.filter?.equalization) {\n      const equilized = await histogramEqualization(face.tensor as Tensor);\n      tf.dispose(face.tensor);\n      face.tensor = equilized;\n    }\n    face.boxScore = Math.round(100 * box.confidence) / 100;\n    if (!config.face.mesh?.enabled) { // mesh not enabled, return resuts from detector only\n      face.box = util.clampBox(box, input);\n      face.boxRaw = util.getRawBox(box, input);\n      face.score = face.boxScore;\n      face.mesh = box.landmarks.map((pt) => [\n        ((box.startPoint[0] + box.endPoint[0])) / 2 + ((box.endPoint[0] + box.startPoint[0]) * pt[0] / blazeface.size()),\n        ((box.startPoint[1] + box.endPoint[1])) / 2 + ((box.endPoint[1] + box.startPoint[1]) * pt[1] / blazeface.size()),\n      ]);\n      face.meshRaw = face.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize]);\n      for (const key of Object.keys(coords.blazeFaceLandmarks)) {\n        face.annotations[key] = [face.mesh[coords.blazeFaceLandmarks[key] as number]]; // add annotations\n      }\n    } else if (!model) { // mesh enabled, but not loaded\n      if (config.debug) log('face mesh detection requested, but model is not loaded');\n    } else { // mesh enabled\n      const results = model.execute(face.tensor as Tensor) as Array<Tensor>;\n      const confidenceT = results.find((t) => t.shape[t.shape.length - 1] === 1) as Tensor;\n      const faceConfidence = await confidenceT.data();\n      face.faceScore = Math.round(100 * faceConfidence[0]) / 100;\n\n      if (face.faceScore < (config.face.detector?.minConfidence || 1)) { // low confidence in detected mesh\n        box.confidence = face.faceScore; // reset confidence of cached box\n        if (config.face.mesh?.keepInvalid) {\n          face.box = util.clampBox(box, input);\n          face.boxRaw = util.getRawBox(box, input);\n          face.score = face.boxScore;\n          face.mesh = box.landmarks.map((pt) => [\n            ((box.startPoint[0] + box.endPoint[0])) / 2 + ((box.endPoint[0] + box.startPoint[0]) * pt[0] / blazeface.size()),\n            ((box.startPoint[1] + box.endPoint[1])) / 2 + ((box.endPoint[1] + box.startPoint[1]) * pt[1] / blazeface.size()),\n          ]);\n          face.meshRaw = face.mesh.map((pt) => [pt[0] / (input.shape[2] || 1), pt[1] / (input.shape[1] || 1), (pt[2] || 0) / inputSize]);\n          for (const key of Object.keys(coords.blazeFaceLandmarks)) {\n            face.annotations[key] = [face.mesh[coords.blazeFaceLandmarks[key] as number]]; // add annotations\n          }\n        }\n      } else {\n        const meshT = results.find((t) => t.shape[t.shape.length - 1] === 1404) as Tensor;\n        const coordsReshaped = tf.reshape(meshT, [-1, 3]);\n        let rawCoords = await coordsReshaped.array();\n        tf.dispose(coordsReshaped);\n        if (config.face.attention?.enabled) {\n          rawCoords = await attention.augment(rawCoords, results); // augment iris results using attention model results\n        } else if (config.face.iris?.enabled) {\n          rawCoords = await iris.augmentIris(rawCoords, face.tensor, config, inputSize); // run iris model and augment results\n        }\n        face.mesh = util.transformRawCoords(rawCoords, box, angle, rotationMatrix, inputSize); // get processed mesh\n        face.meshRaw = face.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize]);\n        for (const key of Object.keys(coords.meshAnnotations)) face.annotations[key] = coords.meshAnnotations[key].map((index) => face.mesh[index]); // add annotations\n        face.score = face.faceScore;\n        const calculatedBox = { ...util.calculateFaceBox(face.mesh, box), confidence: box.confidence, landmarks: box.landmarks };\n        face.box = util.clampBox(calculatedBox, input);\n        face.boxRaw = util.getRawBox(calculatedBox, input);\n        /*\n        const contoursT = results.find((t) => t.shape[t.shape.length - 1] === 266) as Tensor;\n        const contoursData = contoursT && await contoursT.data(); // 133 x 2d points\n        face.contoursRaw = [];\n        for (let j = 0; j < contoursData.length / 2; j++) face.contoursRaw.push([contoursData[2 * j + 0] / inputSize, contoursData[2 * j + 1] / inputSize]);\n        face.contours = face.contoursRaw.map((c) => [Math.trunc((input.shape[2] || 1) * c[0]), Math.trunc((input.shape[1] || 1) * c[1])]);\n        */\n        newCache.push(calculatedBox);\n      }\n      tf.dispose(results);\n    }\n    if (face.score > (config.face.detector?.minConfidence || 1)) faces.push(face);\n    else tf.dispose(face.tensor);\n  }\n  cache.boxes = newCache; // reset cache\n  return faces;\n}\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  // @ts-ignore private property\n  if (config?.face?.attention?.enabled && model?.signature) {\n    // @ts-ignore private property\n    if (Object.keys(model?.signature?.outputs || {}).length < 6) model = null;\n  }\n  if (!model) {\n    if (config.face.attention?.enabled) model = await loadModel(config.face.attention?.modelPath);\n    else model = await loadModel(config.face.mesh?.modelPath);\n  } else if (config.debug) {\n    log('cached model:', model['modelUrl']);\n  }\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  return model;\n}\n\nexport const triangulation = coords.TRI468;\nexport const uvmap = coords.UV468;\n", "/**\n * FaceRes model implementation\n *\n * Returns Age, Gender, Descriptor\n * Implements Face simmilarity function\n *\n * Based on: [**HSE-FaceRes**](https://github.com/HSE-asavchenko/HSE_FaceRec_tf)\n */\n\nimport { log, now } from '../util/util';\nimport { env } from '../util/env';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport type { Gender, Race } from '../result';\n\nexport type FaceRes = { age: number, gender: Gender, genderScore: number, descriptor: number[], race?: { score: number, race: Race }[] };\n\nlet model: GraphModel | null;\nconst last: Array<{\n  age: number,\n  gender: Gender,\n  genderScore: number,\n  descriptor: number[],\n}> = [];\n\nlet lastTime = 0;\nlet lastCount = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.description?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport function enhance(input): Tensor {\n  const tensor = (input.image || input.tensor || input) as Tensor; // input received from detector is already normalized to 0..1, input is also assumed to be straightened\n  if (!model?.inputs[0].shape) return tensor; // model has no shape so no point continuing\n  const crop = tf.image.resizeBilinear(tensor, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n  const norm = tf.mul(crop, constants.tf255);\n  tf.dispose(crop);\n  return norm;\n  /*\n  // do a tight crop of image and resize it to fit the model\n  const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n  const crop = (tensor.shape.length === 3)\n    ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n    : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n  */\n  /*\n  // convert to black&white to avoid colorization impact\n  const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n  const [red, green, blue] = tf.split(crop, 3, 3);\n  const redNorm = tf.mul(red, rgb[0]);\n  const greenNorm = tf.mul(green, rgb[1]);\n  const blueNorm = tf.mul(blue, rgb[2]);\n  const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n  const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n  */\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<FaceRes> {\n  if (!model) return { age: 0, gender: 'unknown', genderScore: 0, descriptor: [] };\n  const skipFrame = skipped < (config.face.description?.skipFrames || 0);\n  const skipTime = (config.face.description?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipFrame && skipTime && (lastCount === count) && last[idx]?.age && (last[idx]?.age > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const obj = {\n      age: <number>0,\n      gender: <Gender>'unknown',\n      genderScore: <number>0,\n      descriptor: <number[]>[],\n    };\n\n    if (config.face.description?.enabled) {\n      const enhanced = enhance(image);\n      const resT = model?.execute(enhanced) as Tensor[];\n      lastTime = now();\n      tf.dispose(enhanced);\n      const genderT = await resT.find((t) => t.shape[1] === 1) as Tensor;\n      const gender = await genderT.data();\n      const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n      if (confidence > (config.face.description?.minConfidence || 0)) {\n        obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n        obj.genderScore = Math.min(0.99, confidence);\n      }\n      const argmax = tf.argMax(resT.find((t) => t.shape[1] === 100), 1);\n      const age = (await argmax.data())[0];\n      tf.dispose(argmax);\n      const ageT = resT.find((t) => t.shape[1] === 100) as Tensor;\n      const all = await ageT.data();\n      obj.age = Math.round(all[age - 1] > all[age + 1] ? 10 * age - 100 * all[age - 1] : 10 * age + 100 * all[age + 1]) / 10;\n\n      const desc = resT.find((t) => t.shape[1] === 1024);\n      // const reshape = desc.reshape([128, 8]); // reshape large 1024-element descriptor to 128 x 8\n      // const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it which leaves us with 128-element descriptor\n      const descriptor = desc ? await desc.data() : <number[]>[];\n      obj.descriptor = Array.from(descriptor);\n      resT.forEach((t) => tf.dispose(t));\n    }\n    last[idx] = obj;\n    lastCount = count;\n    resolve(obj);\n  });\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport type { Point } from '../result';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]] as Point;\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]] as Point;\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]] as Point;\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]] as Point;\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize] as Point;\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize] as Point;\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]] as Point;\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]] as Point;\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "/**\n * HandPose model implementation constants\n * See `handpose.ts` for entry point\n */\n\nexport const anchors = [\n  { x: 0.015625, y: 0.015625 },\n  { x: 0.015625, y: 0.015625 },\n  { x: 0.046875, y: 0.015625 },\n  { x: 0.046875, y: 0.015625 },\n  { x: 0.078125, y: 0.015625 },\n  { x: 0.078125, y: 0.015625 },\n  { x: 0.109375, y: 0.015625 },\n  { x: 0.109375, y: 0.015625 },\n  { x: 0.140625, y: 0.015625 },\n  { x: 0.140625, y: 0.015625 },\n  { x: 0.171875, y: 0.015625 },\n  { x: 0.171875, y: 0.015625 },\n  { x: 0.203125, y: 0.015625 },\n  { x: 0.203125, y: 0.015625 },\n  { x: 0.234375, y: 0.015625 },\n  { x: 0.234375, y: 0.015625 },\n  { x: 0.265625, y: 0.015625 },\n  { x: 0.265625, y: 0.015625 },\n  { x: 0.296875, y: 0.015625 },\n  { x: 0.296875, y: 0.015625 },\n  { x: 0.328125, y: 0.015625 },\n  { x: 0.328125, y: 0.015625 },\n  { x: 0.359375, y: 0.015625 },\n  { x: 0.359375, y: 0.015625 },\n  { x: 0.390625, y: 0.015625 },\n  { x: 0.390625, y: 0.015625 },\n  { x: 0.421875, y: 0.015625 },\n  { x: 0.421875, y: 0.015625 },\n  { x: 0.453125, y: 0.015625 },\n  { x: 0.453125, y: 0.015625 },\n  { x: 0.484375, y: 0.015625 },\n  { x: 0.484375, y: 0.015625 },\n  { x: 0.515625, y: 0.015625 },\n  { x: 0.515625, y: 0.015625 },\n  { x: 0.546875, y: 0.015625 },\n  { x: 0.546875, y: 0.015625 },\n  { x: 0.578125, y: 0.015625 },\n  { x: 0.578125, y: 0.015625 },\n  { x: 0.609375, y: 0.015625 },\n  { x: 0.609375, y: 0.015625 },\n  { x: 0.640625, y: 0.015625 },\n  { x: 0.640625, y: 0.015625 },\n  { x: 0.671875, y: 0.015625 },\n  { x: 0.671875, y: 0.015625 },\n  { x: 0.703125, y: 0.015625 },\n  { x: 0.703125, y: 0.015625 },\n  { x: 0.734375, y: 0.015625 },\n  { x: 0.734375, y: 0.015625 },\n  { x: 0.765625, y: 0.015625 },\n  { x: 0.765625, y: 0.015625 },\n  { x: 0.796875, y: 0.015625 },\n  { x: 0.796875, y: 0.015625 },\n  { x: 0.828125, y: 0.015625 },\n  { x: 0.828125, y: 0.015625 },\n  { x: 0.859375, y: 0.015625 },\n  { x: 0.859375, y: 0.015625 },\n  { x: 0.890625, y: 0.015625 },\n  { x: 0.890625, y: 0.015625 },\n  { x: 0.921875, y: 0.015625 },\n  { x: 0.921875, y: 0.015625 },\n  { x: 0.953125, y: 0.015625 },\n  { x: 0.953125, y: 0.015625 },\n  { x: 0.984375, y: 0.015625 },\n  { x: 0.984375, y: 0.015625 },\n  { x: 0.015625, y: 0.046875 },\n  { x: 0.015625, y: 0.046875 },\n  { x: 0.046875, y: 0.046875 },\n  { x: 0.046875, y: 0.046875 },\n  { x: 0.078125, y: 0.046875 },\n  { x: 0.078125, y: 0.046875 },\n  { x: 0.109375, y: 0.046875 },\n  { x: 0.109375, y: 0.046875 },\n  { x: 0.140625, y: 0.046875 },\n  { x: 0.140625, y: 0.046875 },\n  { x: 0.171875, y: 0.046875 },\n  { x: 0.171875, y: 0.046875 },\n  { x: 0.203125, y: 0.046875 },\n  { x: 0.203125, y: 0.046875 },\n  { x: 0.234375, y: 0.046875 },\n  { x: 0.234375, y: 0.046875 },\n  { x: 0.265625, y: 0.046875 },\n  { x: 0.265625, y: 0.046875 },\n  { x: 0.296875, y: 0.046875 },\n  { x: 0.296875, y: 0.046875 },\n  { x: 0.328125, y: 0.046875 },\n  { x: 0.328125, y: 0.046875 },\n  { x: 0.359375, y: 0.046875 },\n  { x: 0.359375, y: 0.046875 },\n  { x: 0.390625, y: 0.046875 },\n  { x: 0.390625, y: 0.046875 },\n  { x: 0.421875, y: 0.046875 },\n  { x: 0.421875, y: 0.046875 },\n  { x: 0.453125, y: 0.046875 },\n  { x: 0.453125, y: 0.046875 },\n  { x: 0.484375, y: 0.046875 },\n  { x: 0.484375, y: 0.046875 },\n  { x: 0.515625, y: 0.046875 },\n  { x: 0.515625, y: 0.046875 },\n  { x: 0.546875, y: 0.046875 },\n  { x: 0.546875, y: 0.046875 },\n  { x: 0.578125, y: 0.046875 },\n  { x: 0.578125, y: 0.046875 },\n  { x: 0.609375, y: 0.046875 },\n  { x: 0.609375, y: 0.046875 },\n  { x: 0.640625, y: 0.046875 },\n  { x: 0.640625, y: 0.046875 },\n  { x: 0.671875, y: 0.046875 },\n  { x: 0.671875, y: 0.046875 },\n  { x: 0.703125, y: 0.046875 },\n  { x: 0.703125, y: 0.046875 },\n  { x: 0.734375, y: 0.046875 },\n  { x: 0.734375, y: 0.046875 },\n  { x: 0.765625, y: 0.046875 },\n  { x: 0.765625, y: 0.046875 },\n  { x: 0.796875, y: 0.046875 },\n  { x: 0.796875, y: 0.046875 },\n  { x: 0.828125, y: 0.046875 },\n  { x: 0.828125, y: 0.046875 },\n  { x: 0.859375, y: 0.046875 },\n  { x: 0.859375, y: 0.046875 },\n  { x: 0.890625, y: 0.046875 },\n  { x: 0.890625, y: 0.046875 },\n  { x: 0.921875, y: 0.046875 },\n  { x: 0.921875, y: 0.046875 },\n  { x: 0.953125, y: 0.046875 },\n  { x: 0.953125, y: 0.046875 },\n  { x: 0.984375, y: 0.046875 },\n  { x: 0.984375, y: 0.046875 },\n  { x: 0.015625, y: 0.078125 },\n  { x: 0.015625, y: 0.078125 },\n  { x: 0.046875, y: 0.078125 },\n  { x: 0.046875, y: 0.078125 },\n  { x: 0.078125, y: 0.078125 },\n  { x: 0.078125, y: 0.078125 },\n  { x: 0.109375, y: 0.078125 },\n  { x: 0.109375, y: 0.078125 },\n  { x: 0.140625, y: 0.078125 },\n  { x: 0.140625, y: 0.078125 },\n  { x: 0.171875, y: 0.078125 },\n  { x: 0.171875, y: 0.078125 },\n  { x: 0.203125, y: 0.078125 },\n  { x: 0.203125, y: 0.078125 },\n  { x: 0.234375, y: 0.078125 },\n  { x: 0.234375, y: 0.078125 },\n  { x: 0.265625, y: 0.078125 },\n  { x: 0.265625, y: 0.078125 },\n  { x: 0.296875, y: 0.078125 },\n  { x: 0.296875, y: 0.078125 },\n  { x: 0.328125, y: 0.078125 },\n  { x: 0.328125, y: 0.078125 },\n  { x: 0.359375, y: 0.078125 },\n  { x: 0.359375, y: 0.078125 },\n  { x: 0.390625, y: 0.078125 },\n  { x: 0.390625, y: 0.078125 },\n  { x: 0.421875, y: 0.078125 },\n  { x: 0.421875, y: 0.078125 },\n  { x: 0.453125, y: 0.078125 },\n  { x: 0.453125, y: 0.078125 },\n  { x: 0.484375, y: 0.078125 },\n  { x: 0.484375, y: 0.078125 },\n  { x: 0.515625, y: 0.078125 },\n  { x: 0.515625, y: 0.078125 },\n  { x: 0.546875, y: 0.078125 },\n  { x: 0.546875, y: 0.078125 },\n  { x: 0.578125, y: 0.078125 },\n  { x: 0.578125, y: 0.078125 },\n  { x: 0.609375, y: 0.078125 },\n  { x: 0.609375, y: 0.078125 },\n  { x: 0.640625, y: 0.078125 },\n  { x: 0.640625, y: 0.078125 },\n  { x: 0.671875, y: 0.078125 },\n  { x: 0.671875, y: 0.078125 },\n  { x: 0.703125, y: 0.078125 },\n  { x: 0.703125, y: 0.078125 },\n  { x: 0.734375, y: 0.078125 },\n  { x: 0.734375, y: 0.078125 },\n  { x: 0.765625, y: 0.078125 },\n  { x: 0.765625, y: 0.078125 },\n  { x: 0.796875, y: 0.078125 },\n  { x: 0.796875, y: 0.078125 },\n  { x: 0.828125, y: 0.078125 },\n  { x: 0.828125, y: 0.078125 },\n  { x: 0.859375, y: 0.078125 },\n  { x: 0.859375, y: 0.078125 },\n  { x: 0.890625, y: 0.078125 },\n  { x: 0.890625, y: 0.078125 },\n  { x: 0.921875, y: 0.078125 },\n  { x: 0.921875, y: 0.078125 },\n  { x: 0.953125, y: 0.078125 },\n  { x: 0.953125, y: 0.078125 },\n  { x: 0.984375, y: 0.078125 },\n  { x: 0.984375, y: 0.078125 },\n  { x: 0.015625, y: 0.109375 },\n  { x: 0.015625, y: 0.109375 },\n  { x: 0.046875, y: 0.109375 },\n  { x: 0.046875, y: 0.109375 },\n  { x: 0.078125, y: 0.109375 },\n  { x: 0.078125, y: 0.109375 },\n  { x: 0.109375, y: 0.109375 },\n  { x: 0.109375, y: 0.109375 },\n  { x: 0.140625, y: 0.109375 },\n  { x: 0.140625, y: 0.109375 },\n  { x: 0.171875, y: 0.109375 },\n  { x: 0.171875, y: 0.109375 },\n  { x: 0.203125, y: 0.109375 },\n  { x: 0.203125, y: 0.109375 },\n  { x: 0.234375, y: 0.109375 },\n  { x: 0.234375, y: 0.109375 },\n  { x: 0.265625, y: 0.109375 },\n  { x: 0.265625, y: 0.109375 },\n  { x: 0.296875, y: 0.109375 },\n  { x: 0.296875, y: 0.109375 },\n  { x: 0.328125, y: 0.109375 },\n  { x: 0.328125, y: 0.109375 },\n  { x: 0.359375, y: 0.109375 },\n  { x: 0.359375, y: 0.109375 },\n  { x: 0.390625, y: 0.109375 },\n  { x: 0.390625, y: 0.109375 },\n  { x: 0.421875, y: 0.109375 },\n  { x: 0.421875, y: 0.109375 },\n  { x: 0.453125, y: 0.109375 },\n  { x: 0.453125, y: 0.109375 },\n  { x: 0.484375, y: 0.109375 },\n  { x: 0.484375, y: 0.109375 },\n  { x: 0.515625, y: 0.109375 },\n  { x: 0.515625, y: 0.109375 },\n  { x: 0.546875, y: 0.109375 },\n  { x: 0.546875, y: 0.109375 },\n  { x: 0.578125, y: 0.109375 },\n  { x: 0.578125, y: 0.109375 },\n  { x: 0.609375, y: 0.109375 },\n  { x: 0.609375, y: 0.109375 },\n  { x: 0.640625, y: 0.109375 },\n  { x: 0.640625, y: 0.109375 },\n  { x: 0.671875, y: 0.109375 },\n  { x: 0.671875, y: 0.109375 },\n  { x: 0.703125, y: 0.109375 },\n  { x: 0.703125, y: 0.109375 },\n  { x: 0.734375, y: 0.109375 },\n  { x: 0.734375, y: 0.109375 },\n  { x: 0.765625, y: 0.109375 },\n  { x: 0.765625, y: 0.109375 },\n  { x: 0.796875, y: 0.109375 },\n  { x: 0.796875, y: 0.109375 },\n  { x: 0.828125, y: 0.109375 },\n  { x: 0.828125, y: 0.109375 },\n  { x: 0.859375, y: 0.109375 },\n  { x: 0.859375, y: 0.109375 },\n  { x: 0.890625, y: 0.109375 },\n  { x: 0.890625, y: 0.109375 },\n  { x: 0.921875, y: 0.109375 },\n  { x: 0.921875, y: 0.109375 },\n  { x: 0.953125, y: 0.109375 },\n  { x: 0.953125, y: 0.109375 },\n  { x: 0.984375, y: 0.109375 },\n  { x: 0.984375, y: 0.109375 },\n  { x: 0.015625, y: 0.140625 },\n  { x: 0.015625, y: 0.140625 },\n  { x: 0.046875, y: 0.140625 },\n  { x: 0.046875, y: 0.140625 },\n  { x: 0.078125, y: 0.140625 },\n  { x: 0.078125, y: 0.140625 },\n  { x: 0.109375, y: 0.140625 },\n  { x: 0.109375, y: 0.140625 },\n  { x: 0.140625, y: 0.140625 },\n  { x: 0.140625, y: 0.140625 },\n  { x: 0.171875, y: 0.140625 },\n  { x: 0.171875, y: 0.140625 },\n  { x: 0.203125, y: 0.140625 },\n  { x: 0.203125, y: 0.140625 },\n  { x: 0.234375, y: 0.140625 },\n  { x: 0.234375, y: 0.140625 },\n  { x: 0.265625, y: 0.140625 },\n  { x: 0.265625, y: 0.140625 },\n  { x: 0.296875, y: 0.140625 },\n  { x: 0.296875, y: 0.140625 },\n  { x: 0.328125, y: 0.140625 },\n  { x: 0.328125, y: 0.140625 },\n  { x: 0.359375, y: 0.140625 },\n  { x: 0.359375, y: 0.140625 },\n  { x: 0.390625, y: 0.140625 },\n  { x: 0.390625, y: 0.140625 },\n  { x: 0.421875, y: 0.140625 },\n  { x: 0.421875, y: 0.140625 },\n  { x: 0.453125, y: 0.140625 },\n  { x: 0.453125, y: 0.140625 },\n  { x: 0.484375, y: 0.140625 },\n  { x: 0.484375, y: 0.140625 },\n  { x: 0.515625, y: 0.140625 },\n  { x: 0.515625, y: 0.140625 },\n  { x: 0.546875, y: 0.140625 },\n  { x: 0.546875, y: 0.140625 },\n  { x: 0.578125, y: 0.140625 },\n  { x: 0.578125, y: 0.140625 },\n  { x: 0.609375, y: 0.140625 },\n  { x: 0.609375, y: 0.140625 },\n  { x: 0.640625, y: 0.140625 },\n  { x: 0.640625, y: 0.140625 },\n  { x: 0.671875, y: 0.140625 },\n  { x: 0.671875, y: 0.140625 },\n  { x: 0.703125, y: 0.140625 },\n  { x: 0.703125, y: 0.140625 },\n  { x: 0.734375, y: 0.140625 },\n  { x: 0.734375, y: 0.140625 },\n  { x: 0.765625, y: 0.140625 },\n  { x: 0.765625, y: 0.140625 },\n  { x: 0.796875, y: 0.140625 },\n  { x: 0.796875, y: 0.140625 },\n  { x: 0.828125, y: 0.140625 },\n  { x: 0.828125, y: 0.140625 },\n  { x: 0.859375, y: 0.140625 },\n  { x: 0.859375, y: 0.140625 },\n  { x: 0.890625, y: 0.140625 },\n  { x: 0.890625, y: 0.140625 },\n  { x: 0.921875, y: 0.140625 },\n  { x: 0.921875, y: 0.140625 },\n  { x: 0.953125, y: 0.140625 },\n  { x: 0.953125, y: 0.140625 },\n  { x: 0.984375, y: 0.140625 },\n  { x: 0.984375, y: 0.140625 },\n  { x: 0.015625, y: 0.171875 },\n  { x: 0.015625, y: 0.171875 },\n  { x: 0.046875, y: 0.171875 },\n  { x: 0.046875, y: 0.171875 },\n  { x: 0.078125, y: 0.171875 },\n  { x: 0.078125, y: 0.171875 },\n  { x: 0.109375, y: 0.171875 },\n  { x: 0.109375, y: 0.171875 },\n  { x: 0.140625, y: 0.171875 },\n  { x: 0.140625, y: 0.171875 },\n  { x: 0.171875, y: 0.171875 },\n  { x: 0.171875, y: 0.171875 },\n  { x: 0.203125, y: 0.171875 },\n  { x: 0.203125, y: 0.171875 },\n  { x: 0.234375, y: 0.171875 },\n  { x: 0.234375, y: 0.171875 },\n  { x: 0.265625, y: 0.171875 },\n  { x: 0.265625, y: 0.171875 },\n  { x: 0.296875, y: 0.171875 },\n  { x: 0.296875, y: 0.171875 },\n  { x: 0.328125, y: 0.171875 },\n  { x: 0.328125, y: 0.171875 },\n  { x: 0.359375, y: 0.171875 },\n  { x: 0.359375, y: 0.171875 },\n  { x: 0.390625, y: 0.171875 },\n  { x: 0.390625, y: 0.171875 },\n  { x: 0.421875, y: 0.171875 },\n  { x: 0.421875, y: 0.171875 },\n  { x: 0.453125, y: 0.171875 },\n  { x: 0.453125, y: 0.171875 },\n  { x: 0.484375, y: 0.171875 },\n  { x: 0.484375, y: 0.171875 },\n  { x: 0.515625, y: 0.171875 },\n  { x: 0.515625, y: 0.171875 },\n  { x: 0.546875, y: 0.171875 },\n  { x: 0.546875, y: 0.171875 },\n  { x: 0.578125, y: 0.171875 },\n  { x: 0.578125, y: 0.171875 },\n  { x: 0.609375, y: 0.171875 },\n  { x: 0.609375, y: 0.171875 },\n  { x: 0.640625, y: 0.171875 },\n  { x: 0.640625, y: 0.171875 },\n  { x: 0.671875, y: 0.171875 },\n  { x: 0.671875, y: 0.171875 },\n  { x: 0.703125, y: 0.171875 },\n  { x: 0.703125, y: 0.171875 },\n  { x: 0.734375, y: 0.171875 },\n  { x: 0.734375, y: 0.171875 },\n  { x: 0.765625, y: 0.171875 },\n  { x: 0.765625, y: 0.171875 },\n  { x: 0.796875, y: 0.171875 },\n  { x: 0.796875, y: 0.171875 },\n  { x: 0.828125, y: 0.171875 },\n  { x: 0.828125, y: 0.171875 },\n  { x: 0.859375, y: 0.171875 },\n  { x: 0.859375, y: 0.171875 },\n  { x: 0.890625, y: 0.171875 },\n  { x: 0.890625, y: 0.171875 },\n  { x: 0.921875, y: 0.171875 },\n  { x: 0.921875, y: 0.171875 },\n  { x: 0.953125, y: 0.171875 },\n  { x: 0.953125, y: 0.171875 },\n  { x: 0.984375, y: 0.171875 },\n  { x: 0.984375, y: 0.171875 },\n  { x: 0.015625, y: 0.203125 },\n  { x: 0.015625, y: 0.203125 },\n  { x: 0.046875, y: 0.203125 },\n  { x: 0.046875, y: 0.203125 },\n  { x: 0.078125, y: 0.203125 },\n  { x: 0.078125, y: 0.203125 },\n  { x: 0.109375, y: 0.203125 },\n  { x: 0.109375, y: 0.203125 },\n  { x: 0.140625, y: 0.203125 },\n  { x: 0.140625, y: 0.203125 },\n  { x: 0.171875, y: 0.203125 },\n  { x: 0.171875, y: 0.203125 },\n  { x: 0.203125, y: 0.203125 },\n  { x: 0.203125, y: 0.203125 },\n  { x: 0.234375, y: 0.203125 },\n  { x: 0.234375, y: 0.203125 },\n  { x: 0.265625, y: 0.203125 },\n  { x: 0.265625, y: 0.203125 },\n  { x: 0.296875, y: 0.203125 },\n  { x: 0.296875, y: 0.203125 },\n  { x: 0.328125, y: 0.203125 },\n  { x: 0.328125, y: 0.203125 },\n  { x: 0.359375, y: 0.203125 },\n  { x: 0.359375, y: 0.203125 },\n  { x: 0.390625, y: 0.203125 },\n  { x: 0.390625, y: 0.203125 },\n  { x: 0.421875, y: 0.203125 },\n  { x: 0.421875, y: 0.203125 },\n  { x: 0.453125, y: 0.203125 },\n  { x: 0.453125, y: 0.203125 },\n  { x: 0.484375, y: 0.203125 },\n  { x: 0.484375, y: 0.203125 },\n  { x: 0.515625, y: 0.203125 },\n  { x: 0.515625, y: 0.203125 },\n  { x: 0.546875, y: 0.203125 },\n  { x: 0.546875, y: 0.203125 },\n  { x: 0.578125, y: 0.203125 },\n  { x: 0.578125, y: 0.203125 },\n  { x: 0.609375, y: 0.203125 },\n  { x: 0.609375, y: 0.203125 },\n  { x: 0.640625, y: 0.203125 },\n  { x: 0.640625, y: 0.203125 },\n  { x: 0.671875, y: 0.203125 },\n  { x: 0.671875, y: 0.203125 },\n  { x: 0.703125, y: 0.203125 },\n  { x: 0.703125, y: 0.203125 },\n  { x: 0.734375, y: 0.203125 },\n  { x: 0.734375, y: 0.203125 },\n  { x: 0.765625, y: 0.203125 },\n  { x: 0.765625, y: 0.203125 },\n  { x: 0.796875, y: 0.203125 },\n  { x: 0.796875, y: 0.203125 },\n  { x: 0.828125, y: 0.203125 },\n  { x: 0.828125, y: 0.203125 },\n  { x: 0.859375, y: 0.203125 },\n  { x: 0.859375, y: 0.203125 },\n  { x: 0.890625, y: 0.203125 },\n  { x: 0.890625, y: 0.203125 },\n  { x: 0.921875, y: 0.203125 },\n  { x: 0.921875, y: 0.203125 },\n  { x: 0.953125, y: 0.203125 },\n  { x: 0.953125, y: 0.203125 },\n  { x: 0.984375, y: 0.203125 },\n  { x: 0.984375, y: 0.203125 },\n  { x: 0.015625, y: 0.234375 },\n  { x: 0.015625, y: 0.234375 },\n  { x: 0.046875, y: 0.234375 },\n  { x: 0.046875, y: 0.234375 },\n  { x: 0.078125, y: 0.234375 },\n  { x: 0.078125, y: 0.234375 },\n  { x: 0.109375, y: 0.234375 },\n  { x: 0.109375, y: 0.234375 },\n  { x: 0.140625, y: 0.234375 },\n  { x: 0.140625, y: 0.234375 },\n  { x: 0.171875, y: 0.234375 },\n  { x: 0.171875, y: 0.234375 },\n  { x: 0.203125, y: 0.234375 },\n  { x: 0.203125, y: 0.234375 },\n  { x: 0.234375, y: 0.234375 },\n  { x: 0.234375, y: 0.234375 },\n  { x: 0.265625, y: 0.234375 },\n  { x: 0.265625, y: 0.234375 },\n  { x: 0.296875, y: 0.234375 },\n  { x: 0.296875, y: 0.234375 },\n  { x: 0.328125, y: 0.234375 },\n  { x: 0.328125, y: 0.234375 },\n  { x: 0.359375, y: 0.234375 },\n  { x: 0.359375, y: 0.234375 },\n  { x: 0.390625, y: 0.234375 },\n  { x: 0.390625, y: 0.234375 },\n  { x: 0.421875, y: 0.234375 },\n  { x: 0.421875, y: 0.234375 },\n  { x: 0.453125, y: 0.234375 },\n  { x: 0.453125, y: 0.234375 },\n  { x: 0.484375, y: 0.234375 },\n  { x: 0.484375, y: 0.234375 },\n  { x: 0.515625, y: 0.234375 },\n  { x: 0.515625, y: 0.234375 },\n  { x: 0.546875, y: 0.234375 },\n  { x: 0.546875, y: 0.234375 },\n  { x: 0.578125, y: 0.234375 },\n  { x: 0.578125, y: 0.234375 },\n  { x: 0.609375, y: 0.234375 },\n  { x: 0.609375, y: 0.234375 },\n  { x: 0.640625, y: 0.234375 },\n  { x: 0.640625, y: 0.234375 },\n  { x: 0.671875, y: 0.234375 },\n  { x: 0.671875, y: 0.234375 },\n  { x: 0.703125, y: 0.234375 },\n  { x: 0.703125, y: 0.234375 },\n  { x: 0.734375, y: 0.234375 },\n  { x: 0.734375, y: 0.234375 },\n  { x: 0.765625, y: 0.234375 },\n  { x: 0.765625, y: 0.234375 },\n  { x: 0.796875, y: 0.234375 },\n  { x: 0.796875, y: 0.234375 },\n  { x: 0.828125, y: 0.234375 },\n  { x: 0.828125, y: 0.234375 },\n  { x: 0.859375, y: 0.234375 },\n  { x: 0.859375, y: 0.234375 },\n  { x: 0.890625, y: 0.234375 },\n  { x: 0.890625, y: 0.234375 },\n  { x: 0.921875, y: 0.234375 },\n  { x: 0.921875, y: 0.234375 },\n  { x: 0.953125, y: 0.234375 },\n  { x: 0.953125, y: 0.234375 },\n  { x: 0.984375, y: 0.234375 },\n  { x: 0.984375, y: 0.234375 },\n  { x: 0.015625, y: 0.265625 },\n  { x: 0.015625, y: 0.265625 },\n  { x: 0.046875, y: 0.265625 },\n  { x: 0.046875, y: 0.265625 },\n  { x: 0.078125, y: 0.265625 },\n  { x: 0.078125, y: 0.265625 },\n  { x: 0.109375, y: 0.265625 },\n  { x: 0.109375, y: 0.265625 },\n  { x: 0.140625, y: 0.265625 },\n  { x: 0.140625, y: 0.265625 },\n  { x: 0.171875, y: 0.265625 },\n  { x: 0.171875, y: 0.265625 },\n  { x: 0.203125, y: 0.265625 },\n  { x: 0.203125, y: 0.265625 },\n  { x: 0.234375, y: 0.265625 },\n  { x: 0.234375, y: 0.265625 },\n  { x: 0.265625, y: 0.265625 },\n  { x: 0.265625, y: 0.265625 },\n  { x: 0.296875, y: 0.265625 },\n  { x: 0.296875, y: 0.265625 },\n  { x: 0.328125, y: 0.265625 },\n  { x: 0.328125, y: 0.265625 },\n  { x: 0.359375, y: 0.265625 },\n  { x: 0.359375, y: 0.265625 },\n  { x: 0.390625, y: 0.265625 },\n  { x: 0.390625, y: 0.265625 },\n  { x: 0.421875, y: 0.265625 },\n  { x: 0.421875, y: 0.265625 },\n  { x: 0.453125, y: 0.265625 },\n  { x: 0.453125, y: 0.265625 },\n  { x: 0.484375, y: 0.265625 },\n  { x: 0.484375, y: 0.265625 },\n  { x: 0.515625, y: 0.265625 },\n  { x: 0.515625, y: 0.265625 },\n  { x: 0.546875, y: 0.265625 },\n  { x: 0.546875, y: 0.265625 },\n  { x: 0.578125, y: 0.265625 },\n  { x: 0.578125, y: 0.265625 },\n  { x: 0.609375, y: 0.265625 },\n  { x: 0.609375, y: 0.265625 },\n  { x: 0.640625, y: 0.265625 },\n  { x: 0.640625, y: 0.265625 },\n  { x: 0.671875, y: 0.265625 },\n  { x: 0.671875, y: 0.265625 },\n  { x: 0.703125, y: 0.265625 },\n  { x: 0.703125, y: 0.265625 },\n  { x: 0.734375, y: 0.265625 },\n  { x: 0.734375, y: 0.265625 },\n  { x: 0.765625, y: 0.265625 },\n  { x: 0.765625, y: 0.265625 },\n  { x: 0.796875, y: 0.265625 },\n  { x: 0.796875, y: 0.265625 },\n  { x: 0.828125, y: 0.265625 },\n  { x: 0.828125, y: 0.265625 },\n  { x: 0.859375, y: 0.265625 },\n  { x: 0.859375, y: 0.265625 },\n  { x: 0.890625, y: 0.265625 },\n  { x: 0.890625, y: 0.265625 },\n  { x: 0.921875, y: 0.265625 },\n  { x: 0.921875, y: 0.265625 },\n  { x: 0.953125, y: 0.265625 },\n  { x: 0.953125, y: 0.265625 },\n  { x: 0.984375, y: 0.265625 },\n  { x: 0.984375, y: 0.265625 },\n  { x: 0.015625, y: 0.296875 },\n  { x: 0.015625, y: 0.296875 },\n  { x: 0.046875, y: 0.296875 },\n  { x: 0.046875, y: 0.296875 },\n  { x: 0.078125, y: 0.296875 },\n  { x: 0.078125, y: 0.296875 },\n  { x: 0.109375, y: 0.296875 },\n  { x: 0.109375, y: 0.296875 },\n  { x: 0.140625, y: 0.296875 },\n  { x: 0.140625, y: 0.296875 },\n  { x: 0.171875, y: 0.296875 },\n  { x: 0.171875, y: 0.296875 },\n  { x: 0.203125, y: 0.296875 },\n  { x: 0.203125, y: 0.296875 },\n  { x: 0.234375, y: 0.296875 },\n  { x: 0.234375, y: 0.296875 },\n  { x: 0.265625, y: 0.296875 },\n  { x: 0.265625, y: 0.296875 },\n  { x: 0.296875, y: 0.296875 },\n  { x: 0.296875, y: 0.296875 },\n  { x: 0.328125, y: 0.296875 },\n  { x: 0.328125, y: 0.296875 },\n  { x: 0.359375, y: 0.296875 },\n  { x: 0.359375, y: 0.296875 },\n  { x: 0.390625, y: 0.296875 },\n  { x: 0.390625, y: 0.296875 },\n  { x: 0.421875, y: 0.296875 },\n  { x: 0.421875, y: 0.296875 },\n  { x: 0.453125, y: 0.296875 },\n  { x: 0.453125, y: 0.296875 },\n  { x: 0.484375, y: 0.296875 },\n  { x: 0.484375, y: 0.296875 },\n  { x: 0.515625, y: 0.296875 },\n  { x: 0.515625, y: 0.296875 },\n  { x: 0.546875, y: 0.296875 },\n  { x: 0.546875, y: 0.296875 },\n  { x: 0.578125, y: 0.296875 },\n  { x: 0.578125, y: 0.296875 },\n  { x: 0.609375, y: 0.296875 },\n  { x: 0.609375, y: 0.296875 },\n  { x: 0.640625, y: 0.296875 },\n  { x: 0.640625, y: 0.296875 },\n  { x: 0.671875, y: 0.296875 },\n  { x: 0.671875, y: 0.296875 },\n  { x: 0.703125, y: 0.296875 },\n  { x: 0.703125, y: 0.296875 },\n  { x: 0.734375, y: 0.296875 },\n  { x: 0.734375, y: 0.296875 },\n  { x: 0.765625, y: 0.296875 },\n  { x: 0.765625, y: 0.296875 },\n  { x: 0.796875, y: 0.296875 },\n  { x: 0.796875, y: 0.296875 },\n  { x: 0.828125, y: 0.296875 },\n  { x: 0.828125, y: 0.296875 },\n  { x: 0.859375, y: 0.296875 },\n  { x: 0.859375, y: 0.296875 },\n  { x: 0.890625, y: 0.296875 },\n  { x: 0.890625, y: 0.296875 },\n  { x: 0.921875, y: 0.296875 },\n  { x: 0.921875, y: 0.296875 },\n  { x: 0.953125, y: 0.296875 },\n  { x: 0.953125, y: 0.296875 },\n  { x: 0.984375, y: 0.296875 },\n  { x: 0.984375, y: 0.296875 },\n  { x: 0.015625, y: 0.328125 },\n  { x: 0.015625, y: 0.328125 },\n  { x: 0.046875, y: 0.328125 },\n  { x: 0.046875, y: 0.328125 },\n  { x: 0.078125, y: 0.328125 },\n  { x: 0.078125, y: 0.328125 },\n  { x: 0.109375, y: 0.328125 },\n  { x: 0.109375, y: 0.328125 },\n  { x: 0.140625, y: 0.328125 },\n  { x: 0.140625, y: 0.328125 },\n  { x: 0.171875, y: 0.328125 },\n  { x: 0.171875, y: 0.328125 },\n  { x: 0.203125, y: 0.328125 },\n  { x: 0.203125, y: 0.328125 },\n  { x: 0.234375, y: 0.328125 },\n  { x: 0.234375, y: 0.328125 },\n  { x: 0.265625, y: 0.328125 },\n  { x: 0.265625, y: 0.328125 },\n  { x: 0.296875, y: 0.328125 },\n  { x: 0.296875, y: 0.328125 },\n  { x: 0.328125, y: 0.328125 },\n  { x: 0.328125, y: 0.328125 },\n  { x: 0.359375, y: 0.328125 },\n  { x: 0.359375, y: 0.328125 },\n  { x: 0.390625, y: 0.328125 },\n  { x: 0.390625, y: 0.328125 },\n  { x: 0.421875, y: 0.328125 },\n  { x: 0.421875, y: 0.328125 },\n  { x: 0.453125, y: 0.328125 },\n  { x: 0.453125, y: 0.328125 },\n  { x: 0.484375, y: 0.328125 },\n  { x: 0.484375, y: 0.328125 },\n  { x: 0.515625, y: 0.328125 },\n  { x: 0.515625, y: 0.328125 },\n  { x: 0.546875, y: 0.328125 },\n  { x: 0.546875, y: 0.328125 },\n  { x: 0.578125, y: 0.328125 },\n  { x: 0.578125, y: 0.328125 },\n  { x: 0.609375, y: 0.328125 },\n  { x: 0.609375, y: 0.328125 },\n  { x: 0.640625, y: 0.328125 },\n  { x: 0.640625, y: 0.328125 },\n  { x: 0.671875, y: 0.328125 },\n  { x: 0.671875, y: 0.328125 },\n  { x: 0.703125, y: 0.328125 },\n  { x: 0.703125, y: 0.328125 },\n  { x: 0.734375, y: 0.328125 },\n  { x: 0.734375, y: 0.328125 },\n  { x: 0.765625, y: 0.328125 },\n  { x: 0.765625, y: 0.328125 },\n  { x: 0.796875, y: 0.328125 },\n  { x: 0.796875, y: 0.328125 },\n  { x: 0.828125, y: 0.328125 },\n  { x: 0.828125, y: 0.328125 },\n  { x: 0.859375, y: 0.328125 },\n  { x: 0.859375, y: 0.328125 },\n  { x: 0.890625, y: 0.328125 },\n  { x: 0.890625, y: 0.328125 },\n  { x: 0.921875, y: 0.328125 },\n  { x: 0.921875, y: 0.328125 },\n  { x: 0.953125, y: 0.328125 },\n  { x: 0.953125, y: 0.328125 },\n  { x: 0.984375, y: 0.328125 },\n  { x: 0.984375, y: 0.328125 },\n  { x: 0.015625, y: 0.359375 },\n  { x: 0.015625, y: 0.359375 },\n  { x: 0.046875, y: 0.359375 },\n  { x: 0.046875, y: 0.359375 },\n  { x: 0.078125, y: 0.359375 },\n  { x: 0.078125, y: 0.359375 },\n  { x: 0.109375, y: 0.359375 },\n  { x: 0.109375, y: 0.359375 },\n  { x: 0.140625, y: 0.359375 },\n  { x: 0.140625, y: 0.359375 },\n  { x: 0.171875, y: 0.359375 },\n  { x: 0.171875, y: 0.359375 },\n  { x: 0.203125, y: 0.359375 },\n  { x: 0.203125, y: 0.359375 },\n  { x: 0.234375, y: 0.359375 },\n  { x: 0.234375, y: 0.359375 },\n  { x: 0.265625, y: 0.359375 },\n  { x: 0.265625, y: 0.359375 },\n  { x: 0.296875, y: 0.359375 },\n  { x: 0.296875, y: 0.359375 },\n  { x: 0.328125, y: 0.359375 },\n  { x: 0.328125, y: 0.359375 },\n  { x: 0.359375, y: 0.359375 },\n  { x: 0.359375, y: 0.359375 },\n  { x: 0.390625, y: 0.359375 },\n  { x: 0.390625, y: 0.359375 },\n  { x: 0.421875, y: 0.359375 },\n  { x: 0.421875, y: 0.359375 },\n  { x: 0.453125, y: 0.359375 },\n  { x: 0.453125, y: 0.359375 },\n  { x: 0.484375, y: 0.359375 },\n  { x: 0.484375, y: 0.359375 },\n  { x: 0.515625, y: 0.359375 },\n  { x: 0.515625, y: 0.359375 },\n  { x: 0.546875, y: 0.359375 },\n  { x: 0.546875, y: 0.359375 },\n  { x: 0.578125, y: 0.359375 },\n  { x: 0.578125, y: 0.359375 },\n  { x: 0.609375, y: 0.359375 },\n  { x: 0.609375, y: 0.359375 },\n  { x: 0.640625, y: 0.359375 },\n  { x: 0.640625, y: 0.359375 },\n  { x: 0.671875, y: 0.359375 },\n  { x: 0.671875, y: 0.359375 },\n  { x: 0.703125, y: 0.359375 },\n  { x: 0.703125, y: 0.359375 },\n  { x: 0.734375, y: 0.359375 },\n  { x: 0.734375, y: 0.359375 },\n  { x: 0.765625, y: 0.359375 },\n  { x: 0.765625, y: 0.359375 },\n  { x: 0.796875, y: 0.359375 },\n  { x: 0.796875, y: 0.359375 },\n  { x: 0.828125, y: 0.359375 },\n  { x: 0.828125, y: 0.359375 },\n  { x: 0.859375, y: 0.359375 },\n  { x: 0.859375, y: 0.359375 },\n  { x: 0.890625, y: 0.359375 },\n  { x: 0.890625, y: 0.359375 },\n  { x: 0.921875, y: 0.359375 },\n  { x: 0.921875, y: 0.359375 },\n  { x: 0.953125, y: 0.359375 },\n  { x: 0.953125, y: 0.359375 },\n  { x: 0.984375, y: 0.359375 },\n  { x: 0.984375, y: 0.359375 },\n  { x: 0.015625, y: 0.390625 },\n  { x: 0.015625, y: 0.390625 },\n  { x: 0.046875, y: 0.390625 },\n  { x: 0.046875, y: 0.390625 },\n  { x: 0.078125, y: 0.390625 },\n  { x: 0.078125, y: 0.390625 },\n  { x: 0.109375, y: 0.390625 },\n  { x: 0.109375, y: 0.390625 },\n  { x: 0.140625, y: 0.390625 },\n  { x: 0.140625, y: 0.390625 },\n  { x: 0.171875, y: 0.390625 },\n  { x: 0.171875, y: 0.390625 },\n  { x: 0.203125, y: 0.390625 },\n  { x: 0.203125, y: 0.390625 },\n  { x: 0.234375, y: 0.390625 },\n  { x: 0.234375, y: 0.390625 },\n  { x: 0.265625, y: 0.390625 },\n  { x: 0.265625, y: 0.390625 },\n  { x: 0.296875, y: 0.390625 },\n  { x: 0.296875, y: 0.390625 },\n  { x: 0.328125, y: 0.390625 },\n  { x: 0.328125, y: 0.390625 },\n  { x: 0.359375, y: 0.390625 },\n  { x: 0.359375, y: 0.390625 },\n  { x: 0.390625, y: 0.390625 },\n  { x: 0.390625, y: 0.390625 },\n  { x: 0.421875, y: 0.390625 },\n  { x: 0.421875, y: 0.390625 },\n  { x: 0.453125, y: 0.390625 },\n  { x: 0.453125, y: 0.390625 },\n  { x: 0.484375, y: 0.390625 },\n  { x: 0.484375, y: 0.390625 },\n  { x: 0.515625, y: 0.390625 },\n  { x: 0.515625, y: 0.390625 },\n  { x: 0.546875, y: 0.390625 },\n  { x: 0.546875, y: 0.390625 },\n  { x: 0.578125, y: 0.390625 },\n  { x: 0.578125, y: 0.390625 },\n  { x: 0.609375, y: 0.390625 },\n  { x: 0.609375, y: 0.390625 },\n  { x: 0.640625, y: 0.390625 },\n  { x: 0.640625, y: 0.390625 },\n  { x: 0.671875, y: 0.390625 },\n  { x: 0.671875, y: 0.390625 },\n  { x: 0.703125, y: 0.390625 },\n  { x: 0.703125, y: 0.390625 },\n  { x: 0.734375, y: 0.390625 },\n  { x: 0.734375, y: 0.390625 },\n  { x: 0.765625, y: 0.390625 },\n  { x: 0.765625, y: 0.390625 },\n  { x: 0.796875, y: 0.390625 },\n  { x: 0.796875, y: 0.390625 },\n  { x: 0.828125, y: 0.390625 },\n  { x: 0.828125, y: 0.390625 },\n  { x: 0.859375, y: 0.390625 },\n  { x: 0.859375, y: 0.390625 },\n  { x: 0.890625, y: 0.390625 },\n  { x: 0.890625, y: 0.390625 },\n  { x: 0.921875, y: 0.390625 },\n  { x: 0.921875, y: 0.390625 },\n  { x: 0.953125, y: 0.390625 },\n  { x: 0.953125, y: 0.390625 },\n  { x: 0.984375, y: 0.390625 },\n  { x: 0.984375, y: 0.390625 },\n  { x: 0.015625, y: 0.421875 },\n  { x: 0.015625, y: 0.421875 },\n  { x: 0.046875, y: 0.421875 },\n  { x: 0.046875, y: 0.421875 },\n  { x: 0.078125, y: 0.421875 },\n  { x: 0.078125, y: 0.421875 },\n  { x: 0.109375, y: 0.421875 },\n  { x: 0.109375, y: 0.421875 },\n  { x: 0.140625, y: 0.421875 },\n  { x: 0.140625, y: 0.421875 },\n  { x: 0.171875, y: 0.421875 },\n  { x: 0.171875, y: 0.421875 },\n  { x: 0.203125, y: 0.421875 },\n  { x: 0.203125, y: 0.421875 },\n  { x: 0.234375, y: 0.421875 },\n  { x: 0.234375, y: 0.421875 },\n  { x: 0.265625, y: 0.421875 },\n  { x: 0.265625, y: 0.421875 },\n  { x: 0.296875, y: 0.421875 },\n  { x: 0.296875, y: 0.421875 },\n  { x: 0.328125, y: 0.421875 },\n  { x: 0.328125, y: 0.421875 },\n  { x: 0.359375, y: 0.421875 },\n  { x: 0.359375, y: 0.421875 },\n  { x: 0.390625, y: 0.421875 },\n  { x: 0.390625, y: 0.421875 },\n  { x: 0.421875, y: 0.421875 },\n  { x: 0.421875, y: 0.421875 },\n  { x: 0.453125, y: 0.421875 },\n  { x: 0.453125, y: 0.421875 },\n  { x: 0.484375, y: 0.421875 },\n  { x: 0.484375, y: 0.421875 },\n  { x: 0.515625, y: 0.421875 },\n  { x: 0.515625, y: 0.421875 },\n  { x: 0.546875, y: 0.421875 },\n  { x: 0.546875, y: 0.421875 },\n  { x: 0.578125, y: 0.421875 },\n  { x: 0.578125, y: 0.421875 },\n  { x: 0.609375, y: 0.421875 },\n  { x: 0.609375, y: 0.421875 },\n  { x: 0.640625, y: 0.421875 },\n  { x: 0.640625, y: 0.421875 },\n  { x: 0.671875, y: 0.421875 },\n  { x: 0.671875, y: 0.421875 },\n  { x: 0.703125, y: 0.421875 },\n  { x: 0.703125, y: 0.421875 },\n  { x: 0.734375, y: 0.421875 },\n  { x: 0.734375, y: 0.421875 },\n  { x: 0.765625, y: 0.421875 },\n  { x: 0.765625, y: 0.421875 },\n  { x: 0.796875, y: 0.421875 },\n  { x: 0.796875, y: 0.421875 },\n  { x: 0.828125, y: 0.421875 },\n  { x: 0.828125, y: 0.421875 },\n  { x: 0.859375, y: 0.421875 },\n  { x: 0.859375, y: 0.421875 },\n  { x: 0.890625, y: 0.421875 },\n  { x: 0.890625, y: 0.421875 },\n  { x: 0.921875, y: 0.421875 },\n  { x: 0.921875, y: 0.421875 },\n  { x: 0.953125, y: 0.421875 },\n  { x: 0.953125, y: 0.421875 },\n  { x: 0.984375, y: 0.421875 },\n  { x: 0.984375, y: 0.421875 },\n  { x: 0.015625, y: 0.453125 },\n  { x: 0.015625, y: 0.453125 },\n  { x: 0.046875, y: 0.453125 },\n  { x: 0.046875, y: 0.453125 },\n  { x: 0.078125, y: 0.453125 },\n  { x: 0.078125, y: 0.453125 },\n  { x: 0.109375, y: 0.453125 },\n  { x: 0.109375, y: 0.453125 },\n  { x: 0.140625, y: 0.453125 },\n  { x: 0.140625, y: 0.453125 },\n  { x: 0.171875, y: 0.453125 },\n  { x: 0.171875, y: 0.453125 },\n  { x: 0.203125, y: 0.453125 },\n  { x: 0.203125, y: 0.453125 },\n  { x: 0.234375, y: 0.453125 },\n  { x: 0.234375, y: 0.453125 },\n  { x: 0.265625, y: 0.453125 },\n  { x: 0.265625, y: 0.453125 },\n  { x: 0.296875, y: 0.453125 },\n  { x: 0.296875, y: 0.453125 },\n  { x: 0.328125, y: 0.453125 },\n  { x: 0.328125, y: 0.453125 },\n  { x: 0.359375, y: 0.453125 },\n  { x: 0.359375, y: 0.453125 },\n  { x: 0.390625, y: 0.453125 },\n  { x: 0.390625, y: 0.453125 },\n  { x: 0.421875, y: 0.453125 },\n  { x: 0.421875, y: 0.453125 },\n  { x: 0.453125, y: 0.453125 },\n  { x: 0.453125, y: 0.453125 },\n  { x: 0.484375, y: 0.453125 },\n  { x: 0.484375, y: 0.453125 },\n  { x: 0.515625, y: 0.453125 },\n  { x: 0.515625, y: 0.453125 },\n  { x: 0.546875, y: 0.453125 },\n  { x: 0.546875, y: 0.453125 },\n  { x: 0.578125, y: 0.453125 },\n  { x: 0.578125, y: 0.453125 },\n  { x: 0.609375, y: 0.453125 },\n  { x: 0.609375, y: 0.453125 },\n  { x: 0.640625, y: 0.453125 },\n  { x: 0.640625, y: 0.453125 },\n  { x: 0.671875, y: 0.453125 },\n  { x: 0.671875, y: 0.453125 },\n  { x: 0.703125, y: 0.453125 },\n  { x: 0.703125, y: 0.453125 },\n  { x: 0.734375, y: 0.453125 },\n  { x: 0.734375, y: 0.453125 },\n  { x: 0.765625, y: 0.453125 },\n  { x: 0.765625, y: 0.453125 },\n  { x: 0.796875, y: 0.453125 },\n  { x: 0.796875, y: 0.453125 },\n  { x: 0.828125, y: 0.453125 },\n  { x: 0.828125, y: 0.453125 },\n  { x: 0.859375, y: 0.453125 },\n  { x: 0.859375, y: 0.453125 },\n  { x: 0.890625, y: 0.453125 },\n  { x: 0.890625, y: 0.453125 },\n  { x: 0.921875, y: 0.453125 },\n  { x: 0.921875, y: 0.453125 },\n  { x: 0.953125, y: 0.453125 },\n  { x: 0.953125, y: 0.453125 },\n  { x: 0.984375, y: 0.453125 },\n  { x: 0.984375, y: 0.453125 },\n  { x: 0.015625, y: 0.484375 },\n  { x: 0.015625, y: 0.484375 },\n  { x: 0.046875, y: 0.484375 },\n  { x: 0.046875, y: 0.484375 },\n  { x: 0.078125, y: 0.484375 },\n  { x: 0.078125, y: 0.484375 },\n  { x: 0.109375, y: 0.484375 },\n  { x: 0.109375, y: 0.484375 },\n  { x: 0.140625, y: 0.484375 },\n  { x: 0.140625, y: 0.484375 },\n  { x: 0.171875, y: 0.484375 },\n  { x: 0.171875, y: 0.484375 },\n  { x: 0.203125, y: 0.484375 },\n  { x: 0.203125, y: 0.484375 },\n  { x: 0.234375, y: 0.484375 },\n  { x: 0.234375, y: 0.484375 },\n  { x: 0.265625, y: 0.484375 },\n  { x: 0.265625, y: 0.484375 },\n  { x: 0.296875, y: 0.484375 },\n  { x: 0.296875, y: 0.484375 },\n  { x: 0.328125, y: 0.484375 },\n  { x: 0.328125, y: 0.484375 },\n  { x: 0.359375, y: 0.484375 },\n  { x: 0.359375, y: 0.484375 },\n  { x: 0.390625, y: 0.484375 },\n  { x: 0.390625, y: 0.484375 },\n  { x: 0.421875, y: 0.484375 },\n  { x: 0.421875, y: 0.484375 },\n  { x: 0.453125, y: 0.484375 },\n  { x: 0.453125, y: 0.484375 },\n  { x: 0.484375, y: 0.484375 },\n  { x: 0.484375, y: 0.484375 },\n  { x: 0.515625, y: 0.484375 },\n  { x: 0.515625, y: 0.484375 },\n  { x: 0.546875, y: 0.484375 },\n  { x: 0.546875, y: 0.484375 },\n  { x: 0.578125, y: 0.484375 },\n  { x: 0.578125, y: 0.484375 },\n  { x: 0.609375, y: 0.484375 },\n  { x: 0.609375, y: 0.484375 },\n  { x: 0.640625, y: 0.484375 },\n  { x: 0.640625, y: 0.484375 },\n  { x: 0.671875, y: 0.484375 },\n  { x: 0.671875, y: 0.484375 },\n  { x: 0.703125, y: 0.484375 },\n  { x: 0.703125, y: 0.484375 },\n  { x: 0.734375, y: 0.484375 },\n  { x: 0.734375, y: 0.484375 },\n  { x: 0.765625, y: 0.484375 },\n  { x: 0.765625, y: 0.484375 },\n  { x: 0.796875, y: 0.484375 },\n  { x: 0.796875, y: 0.484375 },\n  { x: 0.828125, y: 0.484375 },\n  { x: 0.828125, y: 0.484375 },\n  { x: 0.859375, y: 0.484375 },\n  { x: 0.859375, y: 0.484375 },\n  { x: 0.890625, y: 0.484375 },\n  { x: 0.890625, y: 0.484375 },\n  { x: 0.921875, y: 0.484375 },\n  { x: 0.921875, y: 0.484375 },\n  { x: 0.953125, y: 0.484375 },\n  { x: 0.953125, y: 0.484375 },\n  { x: 0.984375, y: 0.484375 },\n  { x: 0.984375, y: 0.484375 },\n  { x: 0.015625, y: 0.515625 },\n  { x: 0.015625, y: 0.515625 },\n  { x: 0.046875, y: 0.515625 },\n  { x: 0.046875, y: 0.515625 },\n  { x: 0.078125, y: 0.515625 },\n  { x: 0.078125, y: 0.515625 },\n  { x: 0.109375, y: 0.515625 },\n  { x: 0.109375, y: 0.515625 },\n  { x: 0.140625, y: 0.515625 },\n  { x: 0.140625, y: 0.515625 },\n  { x: 0.171875, y: 0.515625 },\n  { x: 0.171875, y: 0.515625 },\n  { x: 0.203125, y: 0.515625 },\n  { x: 0.203125, y: 0.515625 },\n  { x: 0.234375, y: 0.515625 },\n  { x: 0.234375, y: 0.515625 },\n  { x: 0.265625, y: 0.515625 },\n  { x: 0.265625, y: 0.515625 },\n  { x: 0.296875, y: 0.515625 },\n  { x: 0.296875, y: 0.515625 },\n  { x: 0.328125, y: 0.515625 },\n  { x: 0.328125, y: 0.515625 },\n  { x: 0.359375, y: 0.515625 },\n  { x: 0.359375, y: 0.515625 },\n  { x: 0.390625, y: 0.515625 },\n  { x: 0.390625, y: 0.515625 },\n  { x: 0.421875, y: 0.515625 },\n  { x: 0.421875, y: 0.515625 },\n  { x: 0.453125, y: 0.515625 },\n  { x: 0.453125, y: 0.515625 },\n  { x: 0.484375, y: 0.515625 },\n  { x: 0.484375, y: 0.515625 },\n  { x: 0.515625, y: 0.515625 },\n  { x: 0.515625, y: 0.515625 },\n  { x: 0.546875, y: 0.515625 },\n  { x: 0.546875, y: 0.515625 },\n  { x: 0.578125, y: 0.515625 },\n  { x: 0.578125, y: 0.515625 },\n  { x: 0.609375, y: 0.515625 },\n  { x: 0.609375, y: 0.515625 },\n  { x: 0.640625, y: 0.515625 },\n  { x: 0.640625, y: 0.515625 },\n  { x: 0.671875, y: 0.515625 },\n  { x: 0.671875, y: 0.515625 },\n  { x: 0.703125, y: 0.515625 },\n  { x: 0.703125, y: 0.515625 },\n  { x: 0.734375, y: 0.515625 },\n  { x: 0.734375, y: 0.515625 },\n  { x: 0.765625, y: 0.515625 },\n  { x: 0.765625, y: 0.515625 },\n  { x: 0.796875, y: 0.515625 },\n  { x: 0.796875, y: 0.515625 },\n  { x: 0.828125, y: 0.515625 },\n  { x: 0.828125, y: 0.515625 },\n  { x: 0.859375, y: 0.515625 },\n  { x: 0.859375, y: 0.515625 },\n  { x: 0.890625, y: 0.515625 },\n  { x: 0.890625, y: 0.515625 },\n  { x: 0.921875, y: 0.515625 },\n  { x: 0.921875, y: 0.515625 },\n  { x: 0.953125, y: 0.515625 },\n  { x: 0.953125, y: 0.515625 },\n  { x: 0.984375, y: 0.515625 },\n  { x: 0.984375, y: 0.515625 },\n  { x: 0.015625, y: 0.546875 },\n  { x: 0.015625, y: 0.546875 },\n  { x: 0.046875, y: 0.546875 },\n  { x: 0.046875, y: 0.546875 },\n  { x: 0.078125, y: 0.546875 },\n  { x: 0.078125, y: 0.546875 },\n  { x: 0.109375, y: 0.546875 },\n  { x: 0.109375, y: 0.546875 },\n  { x: 0.140625, y: 0.546875 },\n  { x: 0.140625, y: 0.546875 },\n  { x: 0.171875, y: 0.546875 },\n  { x: 0.171875, y: 0.546875 },\n  { x: 0.203125, y: 0.546875 },\n  { x: 0.203125, y: 0.546875 },\n  { x: 0.234375, y: 0.546875 },\n  { x: 0.234375, y: 0.546875 },\n  { x: 0.265625, y: 0.546875 },\n  { x: 0.265625, y: 0.546875 },\n  { x: 0.296875, y: 0.546875 },\n  { x: 0.296875, y: 0.546875 },\n  { x: 0.328125, y: 0.546875 },\n  { x: 0.328125, y: 0.546875 },\n  { x: 0.359375, y: 0.546875 },\n  { x: 0.359375, y: 0.546875 },\n  { x: 0.390625, y: 0.546875 },\n  { x: 0.390625, y: 0.546875 },\n  { x: 0.421875, y: 0.546875 },\n  { x: 0.421875, y: 0.546875 },\n  { x: 0.453125, y: 0.546875 },\n  { x: 0.453125, y: 0.546875 },\n  { x: 0.484375, y: 0.546875 },\n  { x: 0.484375, y: 0.546875 },\n  { x: 0.515625, y: 0.546875 },\n  { x: 0.515625, y: 0.546875 },\n  { x: 0.546875, y: 0.546875 },\n  { x: 0.546875, y: 0.546875 },\n  { x: 0.578125, y: 0.546875 },\n  { x: 0.578125, y: 0.546875 },\n  { x: 0.609375, y: 0.546875 },\n  { x: 0.609375, y: 0.546875 },\n  { x: 0.640625, y: 0.546875 },\n  { x: 0.640625, y: 0.546875 },\n  { x: 0.671875, y: 0.546875 },\n  { x: 0.671875, y: 0.546875 },\n  { x: 0.703125, y: 0.546875 },\n  { x: 0.703125, y: 0.546875 },\n  { x: 0.734375, y: 0.546875 },\n  { x: 0.734375, y: 0.546875 },\n  { x: 0.765625, y: 0.546875 },\n  { x: 0.765625, y: 0.546875 },\n  { x: 0.796875, y: 0.546875 },\n  { x: 0.796875, y: 0.546875 },\n  { x: 0.828125, y: 0.546875 },\n  { x: 0.828125, y: 0.546875 },\n  { x: 0.859375, y: 0.546875 },\n  { x: 0.859375, y: 0.546875 },\n  { x: 0.890625, y: 0.546875 },\n  { x: 0.890625, y: 0.546875 },\n  { x: 0.921875, y: 0.546875 },\n  { x: 0.921875, y: 0.546875 },\n  { x: 0.953125, y: 0.546875 },\n  { x: 0.953125, y: 0.546875 },\n  { x: 0.984375, y: 0.546875 },\n  { x: 0.984375, y: 0.546875 },\n  { x: 0.015625, y: 0.578125 },\n  { x: 0.015625, y: 0.578125 },\n  { x: 0.046875, y: 0.578125 },\n  { x: 0.046875, y: 0.578125 },\n  { x: 0.078125, y: 0.578125 },\n  { x: 0.078125, y: 0.578125 },\n  { x: 0.109375, y: 0.578125 },\n  { x: 0.109375, y: 0.578125 },\n  { x: 0.140625, y: 0.578125 },\n  { x: 0.140625, y: 0.578125 },\n  { x: 0.171875, y: 0.578125 },\n  { x: 0.171875, y: 0.578125 },\n  { x: 0.203125, y: 0.578125 },\n  { x: 0.203125, y: 0.578125 },\n  { x: 0.234375, y: 0.578125 },\n  { x: 0.234375, y: 0.578125 },\n  { x: 0.265625, y: 0.578125 },\n  { x: 0.265625, y: 0.578125 },\n  { x: 0.296875, y: 0.578125 },\n  { x: 0.296875, y: 0.578125 },\n  { x: 0.328125, y: 0.578125 },\n  { x: 0.328125, y: 0.578125 },\n  { x: 0.359375, y: 0.578125 },\n  { x: 0.359375, y: 0.578125 },\n  { x: 0.390625, y: 0.578125 },\n  { x: 0.390625, y: 0.578125 },\n  { x: 0.421875, y: 0.578125 },\n  { x: 0.421875, y: 0.578125 },\n  { x: 0.453125, y: 0.578125 },\n  { x: 0.453125, y: 0.578125 },\n  { x: 0.484375, y: 0.578125 },\n  { x: 0.484375, y: 0.578125 },\n  { x: 0.515625, y: 0.578125 },\n  { x: 0.515625, y: 0.578125 },\n  { x: 0.546875, y: 0.578125 },\n  { x: 0.546875, y: 0.578125 },\n  { x: 0.578125, y: 0.578125 },\n  { x: 0.578125, y: 0.578125 },\n  { x: 0.609375, y: 0.578125 },\n  { x: 0.609375, y: 0.578125 },\n  { x: 0.640625, y: 0.578125 },\n  { x: 0.640625, y: 0.578125 },\n  { x: 0.671875, y: 0.578125 },\n  { x: 0.671875, y: 0.578125 },\n  { x: 0.703125, y: 0.578125 },\n  { x: 0.703125, y: 0.578125 },\n  { x: 0.734375, y: 0.578125 },\n  { x: 0.734375, y: 0.578125 },\n  { x: 0.765625, y: 0.578125 },\n  { x: 0.765625, y: 0.578125 },\n  { x: 0.796875, y: 0.578125 },\n  { x: 0.796875, y: 0.578125 },\n  { x: 0.828125, y: 0.578125 },\n  { x: 0.828125, y: 0.578125 },\n  { x: 0.859375, y: 0.578125 },\n  { x: 0.859375, y: 0.578125 },\n  { x: 0.890625, y: 0.578125 },\n  { x: 0.890625, y: 0.578125 },\n  { x: 0.921875, y: 0.578125 },\n  { x: 0.921875, y: 0.578125 },\n  { x: 0.953125, y: 0.578125 },\n  { x: 0.953125, y: 0.578125 },\n  { x: 0.984375, y: 0.578125 },\n  { x: 0.984375, y: 0.578125 },\n  { x: 0.015625, y: 0.609375 },\n  { x: 0.015625, y: 0.609375 },\n  { x: 0.046875, y: 0.609375 },\n  { x: 0.046875, y: 0.609375 },\n  { x: 0.078125, y: 0.609375 },\n  { x: 0.078125, y: 0.609375 },\n  { x: 0.109375, y: 0.609375 },\n  { x: 0.109375, y: 0.609375 },\n  { x: 0.140625, y: 0.609375 },\n  { x: 0.140625, y: 0.609375 },\n  { x: 0.171875, y: 0.609375 },\n  { x: 0.171875, y: 0.609375 },\n  { x: 0.203125, y: 0.609375 },\n  { x: 0.203125, y: 0.609375 },\n  { x: 0.234375, y: 0.609375 },\n  { x: 0.234375, y: 0.609375 },\n  { x: 0.265625, y: 0.609375 },\n  { x: 0.265625, y: 0.609375 },\n  { x: 0.296875, y: 0.609375 },\n  { x: 0.296875, y: 0.609375 },\n  { x: 0.328125, y: 0.609375 },\n  { x: 0.328125, y: 0.609375 },\n  { x: 0.359375, y: 0.609375 },\n  { x: 0.359375, y: 0.609375 },\n  { x: 0.390625, y: 0.609375 },\n  { x: 0.390625, y: 0.609375 },\n  { x: 0.421875, y: 0.609375 },\n  { x: 0.421875, y: 0.609375 },\n  { x: 0.453125, y: 0.609375 },\n  { x: 0.453125, y: 0.609375 },\n  { x: 0.484375, y: 0.609375 },\n  { x: 0.484375, y: 0.609375 },\n  { x: 0.515625, y: 0.609375 },\n  { x: 0.515625, y: 0.609375 },\n  { x: 0.546875, y: 0.609375 },\n  { x: 0.546875, y: 0.609375 },\n  { x: 0.578125, y: 0.609375 },\n  { x: 0.578125, y: 0.609375 },\n  { x: 0.609375, y: 0.609375 },\n  { x: 0.609375, y: 0.609375 },\n  { x: 0.640625, y: 0.609375 },\n  { x: 0.640625, y: 0.609375 },\n  { x: 0.671875, y: 0.609375 },\n  { x: 0.671875, y: 0.609375 },\n  { x: 0.703125, y: 0.609375 },\n  { x: 0.703125, y: 0.609375 },\n  { x: 0.734375, y: 0.609375 },\n  { x: 0.734375, y: 0.609375 },\n  { x: 0.765625, y: 0.609375 },\n  { x: 0.765625, y: 0.609375 },\n  { x: 0.796875, y: 0.609375 },\n  { x: 0.796875, y: 0.609375 },\n  { x: 0.828125, y: 0.609375 },\n  { x: 0.828125, y: 0.609375 },\n  { x: 0.859375, y: 0.609375 },\n  { x: 0.859375, y: 0.609375 },\n  { x: 0.890625, y: 0.609375 },\n  { x: 0.890625, y: 0.609375 },\n  { x: 0.921875, y: 0.609375 },\n  { x: 0.921875, y: 0.609375 },\n  { x: 0.953125, y: 0.609375 },\n  { x: 0.953125, y: 0.609375 },\n  { x: 0.984375, y: 0.609375 },\n  { x: 0.984375, y: 0.609375 },\n  { x: 0.015625, y: 0.640625 },\n  { x: 0.015625, y: 0.640625 },\n  { x: 0.046875, y: 0.640625 },\n  { x: 0.046875, y: 0.640625 },\n  { x: 0.078125, y: 0.640625 },\n  { x: 0.078125, y: 0.640625 },\n  { x: 0.109375, y: 0.640625 },\n  { x: 0.109375, y: 0.640625 },\n  { x: 0.140625, y: 0.640625 },\n  { x: 0.140625, y: 0.640625 },\n  { x: 0.171875, y: 0.640625 },\n  { x: 0.171875, y: 0.640625 },\n  { x: 0.203125, y: 0.640625 },\n  { x: 0.203125, y: 0.640625 },\n  { x: 0.234375, y: 0.640625 },\n  { x: 0.234375, y: 0.640625 },\n  { x: 0.265625, y: 0.640625 },\n  { x: 0.265625, y: 0.640625 },\n  { x: 0.296875, y: 0.640625 },\n  { x: 0.296875, y: 0.640625 },\n  { x: 0.328125, y: 0.640625 },\n  { x: 0.328125, y: 0.640625 },\n  { x: 0.359375, y: 0.640625 },\n  { x: 0.359375, y: 0.640625 },\n  { x: 0.390625, y: 0.640625 },\n  { x: 0.390625, y: 0.640625 },\n  { x: 0.421875, y: 0.640625 },\n  { x: 0.421875, y: 0.640625 },\n  { x: 0.453125, y: 0.640625 },\n  { x: 0.453125, y: 0.640625 },\n  { x: 0.484375, y: 0.640625 },\n  { x: 0.484375, y: 0.640625 },\n  { x: 0.515625, y: 0.640625 },\n  { x: 0.515625, y: 0.640625 },\n  { x: 0.546875, y: 0.640625 },\n  { x: 0.546875, y: 0.640625 },\n  { x: 0.578125, y: 0.640625 },\n  { x: 0.578125, y: 0.640625 },\n  { x: 0.609375, y: 0.640625 },\n  { x: 0.609375, y: 0.640625 },\n  { x: 0.640625, y: 0.640625 },\n  { x: 0.640625, y: 0.640625 },\n  { x: 0.671875, y: 0.640625 },\n  { x: 0.671875, y: 0.640625 },\n  { x: 0.703125, y: 0.640625 },\n  { x: 0.703125, y: 0.640625 },\n  { x: 0.734375, y: 0.640625 },\n  { x: 0.734375, y: 0.640625 },\n  { x: 0.765625, y: 0.640625 },\n  { x: 0.765625, y: 0.640625 },\n  { x: 0.796875, y: 0.640625 },\n  { x: 0.796875, y: 0.640625 },\n  { x: 0.828125, y: 0.640625 },\n  { x: 0.828125, y: 0.640625 },\n  { x: 0.859375, y: 0.640625 },\n  { x: 0.859375, y: 0.640625 },\n  { x: 0.890625, y: 0.640625 },\n  { x: 0.890625, y: 0.640625 },\n  { x: 0.921875, y: 0.640625 },\n  { x: 0.921875, y: 0.640625 },\n  { x: 0.953125, y: 0.640625 },\n  { x: 0.953125, y: 0.640625 },\n  { x: 0.984375, y: 0.640625 },\n  { x: 0.984375, y: 0.640625 },\n  { x: 0.015625, y: 0.671875 },\n  { x: 0.015625, y: 0.671875 },\n  { x: 0.046875, y: 0.671875 },\n  { x: 0.046875, y: 0.671875 },\n  { x: 0.078125, y: 0.671875 },\n  { x: 0.078125, y: 0.671875 },\n  { x: 0.109375, y: 0.671875 },\n  { x: 0.109375, y: 0.671875 },\n  { x: 0.140625, y: 0.671875 },\n  { x: 0.140625, y: 0.671875 },\n  { x: 0.171875, y: 0.671875 },\n  { x: 0.171875, y: 0.671875 },\n  { x: 0.203125, y: 0.671875 },\n  { x: 0.203125, y: 0.671875 },\n  { x: 0.234375, y: 0.671875 },\n  { x: 0.234375, y: 0.671875 },\n  { x: 0.265625, y: 0.671875 },\n  { x: 0.265625, y: 0.671875 },\n  { x: 0.296875, y: 0.671875 },\n  { x: 0.296875, y: 0.671875 },\n  { x: 0.328125, y: 0.671875 },\n  { x: 0.328125, y: 0.671875 },\n  { x: 0.359375, y: 0.671875 },\n  { x: 0.359375, y: 0.671875 },\n  { x: 0.390625, y: 0.671875 },\n  { x: 0.390625, y: 0.671875 },\n  { x: 0.421875, y: 0.671875 },\n  { x: 0.421875, y: 0.671875 },\n  { x: 0.453125, y: 0.671875 },\n  { x: 0.453125, y: 0.671875 },\n  { x: 0.484375, y: 0.671875 },\n  { x: 0.484375, y: 0.671875 },\n  { x: 0.515625, y: 0.671875 },\n  { x: 0.515625, y: 0.671875 },\n  { x: 0.546875, y: 0.671875 },\n  { x: 0.546875, y: 0.671875 },\n  { x: 0.578125, y: 0.671875 },\n  { x: 0.578125, y: 0.671875 },\n  { x: 0.609375, y: 0.671875 },\n  { x: 0.609375, y: 0.671875 },\n  { x: 0.640625, y: 0.671875 },\n  { x: 0.640625, y: 0.671875 },\n  { x: 0.671875, y: 0.671875 },\n  { x: 0.671875, y: 0.671875 },\n  { x: 0.703125, y: 0.671875 },\n  { x: 0.703125, y: 0.671875 },\n  { x: 0.734375, y: 0.671875 },\n  { x: 0.734375, y: 0.671875 },\n  { x: 0.765625, y: 0.671875 },\n  { x: 0.765625, y: 0.671875 },\n  { x: 0.796875, y: 0.671875 },\n  { x: 0.796875, y: 0.671875 },\n  { x: 0.828125, y: 0.671875 },\n  { x: 0.828125, y: 0.671875 },\n  { x: 0.859375, y: 0.671875 },\n  { x: 0.859375, y: 0.671875 },\n  { x: 0.890625, y: 0.671875 },\n  { x: 0.890625, y: 0.671875 },\n  { x: 0.921875, y: 0.671875 },\n  { x: 0.921875, y: 0.671875 },\n  { x: 0.953125, y: 0.671875 },\n  { x: 0.953125, y: 0.671875 },\n  { x: 0.984375, y: 0.671875 },\n  { x: 0.984375, y: 0.671875 },\n  { x: 0.015625, y: 0.703125 },\n  { x: 0.015625, y: 0.703125 },\n  { x: 0.046875, y: 0.703125 },\n  { x: 0.046875, y: 0.703125 },\n  { x: 0.078125, y: 0.703125 },\n  { x: 0.078125, y: 0.703125 },\n  { x: 0.109375, y: 0.703125 },\n  { x: 0.109375, y: 0.703125 },\n  { x: 0.140625, y: 0.703125 },\n  { x: 0.140625, y: 0.703125 },\n  { x: 0.171875, y: 0.703125 },\n  { x: 0.171875, y: 0.703125 },\n  { x: 0.203125, y: 0.703125 },\n  { x: 0.203125, y: 0.703125 },\n  { x: 0.234375, y: 0.703125 },\n  { x: 0.234375, y: 0.703125 },\n  { x: 0.265625, y: 0.703125 },\n  { x: 0.265625, y: 0.703125 },\n  { x: 0.296875, y: 0.703125 },\n  { x: 0.296875, y: 0.703125 },\n  { x: 0.328125, y: 0.703125 },\n  { x: 0.328125, y: 0.703125 },\n  { x: 0.359375, y: 0.703125 },\n  { x: 0.359375, y: 0.703125 },\n  { x: 0.390625, y: 0.703125 },\n  { x: 0.390625, y: 0.703125 },\n  { x: 0.421875, y: 0.703125 },\n  { x: 0.421875, y: 0.703125 },\n  { x: 0.453125, y: 0.703125 },\n  { x: 0.453125, y: 0.703125 },\n  { x: 0.484375, y: 0.703125 },\n  { x: 0.484375, y: 0.703125 },\n  { x: 0.515625, y: 0.703125 },\n  { x: 0.515625, y: 0.703125 },\n  { x: 0.546875, y: 0.703125 },\n  { x: 0.546875, y: 0.703125 },\n  { x: 0.578125, y: 0.703125 },\n  { x: 0.578125, y: 0.703125 },\n  { x: 0.609375, y: 0.703125 },\n  { x: 0.609375, y: 0.703125 },\n  { x: 0.640625, y: 0.703125 },\n  { x: 0.640625, y: 0.703125 },\n  { x: 0.671875, y: 0.703125 },\n  { x: 0.671875, y: 0.703125 },\n  { x: 0.703125, y: 0.703125 },\n  { x: 0.703125, y: 0.703125 },\n  { x: 0.734375, y: 0.703125 },\n  { x: 0.734375, y: 0.703125 },\n  { x: 0.765625, y: 0.703125 },\n  { x: 0.765625, y: 0.703125 },\n  { x: 0.796875, y: 0.703125 },\n  { x: 0.796875, y: 0.703125 },\n  { x: 0.828125, y: 0.703125 },\n  { x: 0.828125, y: 0.703125 },\n  { x: 0.859375, y: 0.703125 },\n  { x: 0.859375, y: 0.703125 },\n  { x: 0.890625, y: 0.703125 },\n  { x: 0.890625, y: 0.703125 },\n  { x: 0.921875, y: 0.703125 },\n  { x: 0.921875, y: 0.703125 },\n  { x: 0.953125, y: 0.703125 },\n  { x: 0.953125, y: 0.703125 },\n  { x: 0.984375, y: 0.703125 },\n  { x: 0.984375, y: 0.703125 },\n  { x: 0.015625, y: 0.734375 },\n  { x: 0.015625, y: 0.734375 },\n  { x: 0.046875, y: 0.734375 },\n  { x: 0.046875, y: 0.734375 },\n  { x: 0.078125, y: 0.734375 },\n  { x: 0.078125, y: 0.734375 },\n  { x: 0.109375, y: 0.734375 },\n  { x: 0.109375, y: 0.734375 },\n  { x: 0.140625, y: 0.734375 },\n  { x: 0.140625, y: 0.734375 },\n  { x: 0.171875, y: 0.734375 },\n  { x: 0.171875, y: 0.734375 },\n  { x: 0.203125, y: 0.734375 },\n  { x: 0.203125, y: 0.734375 },\n  { x: 0.234375, y: 0.734375 },\n  { x: 0.234375, y: 0.734375 },\n  { x: 0.265625, y: 0.734375 },\n  { x: 0.265625, y: 0.734375 },\n  { x: 0.296875, y: 0.734375 },\n  { x: 0.296875, y: 0.734375 },\n  { x: 0.328125, y: 0.734375 },\n  { x: 0.328125, y: 0.734375 },\n  { x: 0.359375, y: 0.734375 },\n  { x: 0.359375, y: 0.734375 },\n  { x: 0.390625, y: 0.734375 },\n  { x: 0.390625, y: 0.734375 },\n  { x: 0.421875, y: 0.734375 },\n  { x: 0.421875, y: 0.734375 },\n  { x: 0.453125, y: 0.734375 },\n  { x: 0.453125, y: 0.734375 },\n  { x: 0.484375, y: 0.734375 },\n  { x: 0.484375, y: 0.734375 },\n  { x: 0.515625, y: 0.734375 },\n  { x: 0.515625, y: 0.734375 },\n  { x: 0.546875, y: 0.734375 },\n  { x: 0.546875, y: 0.734375 },\n  { x: 0.578125, y: 0.734375 },\n  { x: 0.578125, y: 0.734375 },\n  { x: 0.609375, y: 0.734375 },\n  { x: 0.609375, y: 0.734375 },\n  { x: 0.640625, y: 0.734375 },\n  { x: 0.640625, y: 0.734375 },\n  { x: 0.671875, y: 0.734375 },\n  { x: 0.671875, y: 0.734375 },\n  { x: 0.703125, y: 0.734375 },\n  { x: 0.703125, y: 0.734375 },\n  { x: 0.734375, y: 0.734375 },\n  { x: 0.734375, y: 0.734375 },\n  { x: 0.765625, y: 0.734375 },\n  { x: 0.765625, y: 0.734375 },\n  { x: 0.796875, y: 0.734375 },\n  { x: 0.796875, y: 0.734375 },\n  { x: 0.828125, y: 0.734375 },\n  { x: 0.828125, y: 0.734375 },\n  { x: 0.859375, y: 0.734375 },\n  { x: 0.859375, y: 0.734375 },\n  { x: 0.890625, y: 0.734375 },\n  { x: 0.890625, y: 0.734375 },\n  { x: 0.921875, y: 0.734375 },\n  { x: 0.921875, y: 0.734375 },\n  { x: 0.953125, y: 0.734375 },\n  { x: 0.953125, y: 0.734375 },\n  { x: 0.984375, y: 0.734375 },\n  { x: 0.984375, y: 0.734375 },\n  { x: 0.015625, y: 0.765625 },\n  { x: 0.015625, y: 0.765625 },\n  { x: 0.046875, y: 0.765625 },\n  { x: 0.046875, y: 0.765625 },\n  { x: 0.078125, y: 0.765625 },\n  { x: 0.078125, y: 0.765625 },\n  { x: 0.109375, y: 0.765625 },\n  { x: 0.109375, y: 0.765625 },\n  { x: 0.140625, y: 0.765625 },\n  { x: 0.140625, y: 0.765625 },\n  { x: 0.171875, y: 0.765625 },\n  { x: 0.171875, y: 0.765625 },\n  { x: 0.203125, y: 0.765625 },\n  { x: 0.203125, y: 0.765625 },\n  { x: 0.234375, y: 0.765625 },\n  { x: 0.234375, y: 0.765625 },\n  { x: 0.265625, y: 0.765625 },\n  { x: 0.265625, y: 0.765625 },\n  { x: 0.296875, y: 0.765625 },\n  { x: 0.296875, y: 0.765625 },\n  { x: 0.328125, y: 0.765625 },\n  { x: 0.328125, y: 0.765625 },\n  { x: 0.359375, y: 0.765625 },\n  { x: 0.359375, y: 0.765625 },\n  { x: 0.390625, y: 0.765625 },\n  { x: 0.390625, y: 0.765625 },\n  { x: 0.421875, y: 0.765625 },\n  { x: 0.421875, y: 0.765625 },\n  { x: 0.453125, y: 0.765625 },\n  { x: 0.453125, y: 0.765625 },\n  { x: 0.484375, y: 0.765625 },\n  { x: 0.484375, y: 0.765625 },\n  { x: 0.515625, y: 0.765625 },\n  { x: 0.515625, y: 0.765625 },\n  { x: 0.546875, y: 0.765625 },\n  { x: 0.546875, y: 0.765625 },\n  { x: 0.578125, y: 0.765625 },\n  { x: 0.578125, y: 0.765625 },\n  { x: 0.609375, y: 0.765625 },\n  { x: 0.609375, y: 0.765625 },\n  { x: 0.640625, y: 0.765625 },\n  { x: 0.640625, y: 0.765625 },\n  { x: 0.671875, y: 0.765625 },\n  { x: 0.671875, y: 0.765625 },\n  { x: 0.703125, y: 0.765625 },\n  { x: 0.703125, y: 0.765625 },\n  { x: 0.734375, y: 0.765625 },\n  { x: 0.734375, y: 0.765625 },\n  { x: 0.765625, y: 0.765625 },\n  { x: 0.765625, y: 0.765625 },\n  { x: 0.796875, y: 0.765625 },\n  { x: 0.796875, y: 0.765625 },\n  { x: 0.828125, y: 0.765625 },\n  { x: 0.828125, y: 0.765625 },\n  { x: 0.859375, y: 0.765625 },\n  { x: 0.859375, y: 0.765625 },\n  { x: 0.890625, y: 0.765625 },\n  { x: 0.890625, y: 0.765625 },\n  { x: 0.921875, y: 0.765625 },\n  { x: 0.921875, y: 0.765625 },\n  { x: 0.953125, y: 0.765625 },\n  { x: 0.953125, y: 0.765625 },\n  { x: 0.984375, y: 0.765625 },\n  { x: 0.984375, y: 0.765625 },\n  { x: 0.015625, y: 0.796875 },\n  { x: 0.015625, y: 0.796875 },\n  { x: 0.046875, y: 0.796875 },\n  { x: 0.046875, y: 0.796875 },\n  { x: 0.078125, y: 0.796875 },\n  { x: 0.078125, y: 0.796875 },\n  { x: 0.109375, y: 0.796875 },\n  { x: 0.109375, y: 0.796875 },\n  { x: 0.140625, y: 0.796875 },\n  { x: 0.140625, y: 0.796875 },\n  { x: 0.171875, y: 0.796875 },\n  { x: 0.171875, y: 0.796875 },\n  { x: 0.203125, y: 0.796875 },\n  { x: 0.203125, y: 0.796875 },\n  { x: 0.234375, y: 0.796875 },\n  { x: 0.234375, y: 0.796875 },\n  { x: 0.265625, y: 0.796875 },\n  { x: 0.265625, y: 0.796875 },\n  { x: 0.296875, y: 0.796875 },\n  { x: 0.296875, y: 0.796875 },\n  { x: 0.328125, y: 0.796875 },\n  { x: 0.328125, y: 0.796875 },\n  { x: 0.359375, y: 0.796875 },\n  { x: 0.359375, y: 0.796875 },\n  { x: 0.390625, y: 0.796875 },\n  { x: 0.390625, y: 0.796875 },\n  { x: 0.421875, y: 0.796875 },\n  { x: 0.421875, y: 0.796875 },\n  { x: 0.453125, y: 0.796875 },\n  { x: 0.453125, y: 0.796875 },\n  { x: 0.484375, y: 0.796875 },\n  { x: 0.484375, y: 0.796875 },\n  { x: 0.515625, y: 0.796875 },\n  { x: 0.515625, y: 0.796875 },\n  { x: 0.546875, y: 0.796875 },\n  { x: 0.546875, y: 0.796875 },\n  { x: 0.578125, y: 0.796875 },\n  { x: 0.578125, y: 0.796875 },\n  { x: 0.609375, y: 0.796875 },\n  { x: 0.609375, y: 0.796875 },\n  { x: 0.640625, y: 0.796875 },\n  { x: 0.640625, y: 0.796875 },\n  { x: 0.671875, y: 0.796875 },\n  { x: 0.671875, y: 0.796875 },\n  { x: 0.703125, y: 0.796875 },\n  { x: 0.703125, y: 0.796875 },\n  { x: 0.734375, y: 0.796875 },\n  { x: 0.734375, y: 0.796875 },\n  { x: 0.765625, y: 0.796875 },\n  { x: 0.765625, y: 0.796875 },\n  { x: 0.796875, y: 0.796875 },\n  { x: 0.796875, y: 0.796875 },\n  { x: 0.828125, y: 0.796875 },\n  { x: 0.828125, y: 0.796875 },\n  { x: 0.859375, y: 0.796875 },\n  { x: 0.859375, y: 0.796875 },\n  { x: 0.890625, y: 0.796875 },\n  { x: 0.890625, y: 0.796875 },\n  { x: 0.921875, y: 0.796875 },\n  { x: 0.921875, y: 0.796875 },\n  { x: 0.953125, y: 0.796875 },\n  { x: 0.953125, y: 0.796875 },\n  { x: 0.984375, y: 0.796875 },\n  { x: 0.984375, y: 0.796875 },\n  { x: 0.015625, y: 0.828125 },\n  { x: 0.015625, y: 0.828125 },\n  { x: 0.046875, y: 0.828125 },\n  { x: 0.046875, y: 0.828125 },\n  { x: 0.078125, y: 0.828125 },\n  { x: 0.078125, y: 0.828125 },\n  { x: 0.109375, y: 0.828125 },\n  { x: 0.109375, y: 0.828125 },\n  { x: 0.140625, y: 0.828125 },\n  { x: 0.140625, y: 0.828125 },\n  { x: 0.171875, y: 0.828125 },\n  { x: 0.171875, y: 0.828125 },\n  { x: 0.203125, y: 0.828125 },\n  { x: 0.203125, y: 0.828125 },\n  { x: 0.234375, y: 0.828125 },\n  { x: 0.234375, y: 0.828125 },\n  { x: 0.265625, y: 0.828125 },\n  { x: 0.265625, y: 0.828125 },\n  { x: 0.296875, y: 0.828125 },\n  { x: 0.296875, y: 0.828125 },\n  { x: 0.328125, y: 0.828125 },\n  { x: 0.328125, y: 0.828125 },\n  { x: 0.359375, y: 0.828125 },\n  { x: 0.359375, y: 0.828125 },\n  { x: 0.390625, y: 0.828125 },\n  { x: 0.390625, y: 0.828125 },\n  { x: 0.421875, y: 0.828125 },\n  { x: 0.421875, y: 0.828125 },\n  { x: 0.453125, y: 0.828125 },\n  { x: 0.453125, y: 0.828125 },\n  { x: 0.484375, y: 0.828125 },\n  { x: 0.484375, y: 0.828125 },\n  { x: 0.515625, y: 0.828125 },\n  { x: 0.515625, y: 0.828125 },\n  { x: 0.546875, y: 0.828125 },\n  { x: 0.546875, y: 0.828125 },\n  { x: 0.578125, y: 0.828125 },\n  { x: 0.578125, y: 0.828125 },\n  { x: 0.609375, y: 0.828125 },\n  { x: 0.609375, y: 0.828125 },\n  { x: 0.640625, y: 0.828125 },\n  { x: 0.640625, y: 0.828125 },\n  { x: 0.671875, y: 0.828125 },\n  { x: 0.671875, y: 0.828125 },\n  { x: 0.703125, y: 0.828125 },\n  { x: 0.703125, y: 0.828125 },\n  { x: 0.734375, y: 0.828125 },\n  { x: 0.734375, y: 0.828125 },\n  { x: 0.765625, y: 0.828125 },\n  { x: 0.765625, y: 0.828125 },\n  { x: 0.796875, y: 0.828125 },\n  { x: 0.796875, y: 0.828125 },\n  { x: 0.828125, y: 0.828125 },\n  { x: 0.828125, y: 0.828125 },\n  { x: 0.859375, y: 0.828125 },\n  { x: 0.859375, y: 0.828125 },\n  { x: 0.890625, y: 0.828125 },\n  { x: 0.890625, y: 0.828125 },\n  { x: 0.921875, y: 0.828125 },\n  { x: 0.921875, y: 0.828125 },\n  { x: 0.953125, y: 0.828125 },\n  { x: 0.953125, y: 0.828125 },\n  { x: 0.984375, y: 0.828125 },\n  { x: 0.984375, y: 0.828125 },\n  { x: 0.015625, y: 0.859375 },\n  { x: 0.015625, y: 0.859375 },\n  { x: 0.046875, y: 0.859375 },\n  { x: 0.046875, y: 0.859375 },\n  { x: 0.078125, y: 0.859375 },\n  { x: 0.078125, y: 0.859375 },\n  { x: 0.109375, y: 0.859375 },\n  { x: 0.109375, y: 0.859375 },\n  { x: 0.140625, y: 0.859375 },\n  { x: 0.140625, y: 0.859375 },\n  { x: 0.171875, y: 0.859375 },\n  { x: 0.171875, y: 0.859375 },\n  { x: 0.203125, y: 0.859375 },\n  { x: 0.203125, y: 0.859375 },\n  { x: 0.234375, y: 0.859375 },\n  { x: 0.234375, y: 0.859375 },\n  { x: 0.265625, y: 0.859375 },\n  { x: 0.265625, y: 0.859375 },\n  { x: 0.296875, y: 0.859375 },\n  { x: 0.296875, y: 0.859375 },\n  { x: 0.328125, y: 0.859375 },\n  { x: 0.328125, y: 0.859375 },\n  { x: 0.359375, y: 0.859375 },\n  { x: 0.359375, y: 0.859375 },\n  { x: 0.390625, y: 0.859375 },\n  { x: 0.390625, y: 0.859375 },\n  { x: 0.421875, y: 0.859375 },\n  { x: 0.421875, y: 0.859375 },\n  { x: 0.453125, y: 0.859375 },\n  { x: 0.453125, y: 0.859375 },\n  { x: 0.484375, y: 0.859375 },\n  { x: 0.484375, y: 0.859375 },\n  { x: 0.515625, y: 0.859375 },\n  { x: 0.515625, y: 0.859375 },\n  { x: 0.546875, y: 0.859375 },\n  { x: 0.546875, y: 0.859375 },\n  { x: 0.578125, y: 0.859375 },\n  { x: 0.578125, y: 0.859375 },\n  { x: 0.609375, y: 0.859375 },\n  { x: 0.609375, y: 0.859375 },\n  { x: 0.640625, y: 0.859375 },\n  { x: 0.640625, y: 0.859375 },\n  { x: 0.671875, y: 0.859375 },\n  { x: 0.671875, y: 0.859375 },\n  { x: 0.703125, y: 0.859375 },\n  { x: 0.703125, y: 0.859375 },\n  { x: 0.734375, y: 0.859375 },\n  { x: 0.734375, y: 0.859375 },\n  { x: 0.765625, y: 0.859375 },\n  { x: 0.765625, y: 0.859375 },\n  { x: 0.796875, y: 0.859375 },\n  { x: 0.796875, y: 0.859375 },\n  { x: 0.828125, y: 0.859375 },\n  { x: 0.828125, y: 0.859375 },\n  { x: 0.859375, y: 0.859375 },\n  { x: 0.859375, y: 0.859375 },\n  { x: 0.890625, y: 0.859375 },\n  { x: 0.890625, y: 0.859375 },\n  { x: 0.921875, y: 0.859375 },\n  { x: 0.921875, y: 0.859375 },\n  { x: 0.953125, y: 0.859375 },\n  { x: 0.953125, y: 0.859375 },\n  { x: 0.984375, y: 0.859375 },\n  { x: 0.984375, y: 0.859375 },\n  { x: 0.015625, y: 0.890625 },\n  { x: 0.015625, y: 0.890625 },\n  { x: 0.046875, y: 0.890625 },\n  { x: 0.046875, y: 0.890625 },\n  { x: 0.078125, y: 0.890625 },\n  { x: 0.078125, y: 0.890625 },\n  { x: 0.109375, y: 0.890625 },\n  { x: 0.109375, y: 0.890625 },\n  { x: 0.140625, y: 0.890625 },\n  { x: 0.140625, y: 0.890625 },\n  { x: 0.171875, y: 0.890625 },\n  { x: 0.171875, y: 0.890625 },\n  { x: 0.203125, y: 0.890625 },\n  { x: 0.203125, y: 0.890625 },\n  { x: 0.234375, y: 0.890625 },\n  { x: 0.234375, y: 0.890625 },\n  { x: 0.265625, y: 0.890625 },\n  { x: 0.265625, y: 0.890625 },\n  { x: 0.296875, y: 0.890625 },\n  { x: 0.296875, y: 0.890625 },\n  { x: 0.328125, y: 0.890625 },\n  { x: 0.328125, y: 0.890625 },\n  { x: 0.359375, y: 0.890625 },\n  { x: 0.359375, y: 0.890625 },\n  { x: 0.390625, y: 0.890625 },\n  { x: 0.390625, y: 0.890625 },\n  { x: 0.421875, y: 0.890625 },\n  { x: 0.421875, y: 0.890625 },\n  { x: 0.453125, y: 0.890625 },\n  { x: 0.453125, y: 0.890625 },\n  { x: 0.484375, y: 0.890625 },\n  { x: 0.484375, y: 0.890625 },\n  { x: 0.515625, y: 0.890625 },\n  { x: 0.515625, y: 0.890625 },\n  { x: 0.546875, y: 0.890625 },\n  { x: 0.546875, y: 0.890625 },\n  { x: 0.578125, y: 0.890625 },\n  { x: 0.578125, y: 0.890625 },\n  { x: 0.609375, y: 0.890625 },\n  { x: 0.609375, y: 0.890625 },\n  { x: 0.640625, y: 0.890625 },\n  { x: 0.640625, y: 0.890625 },\n  { x: 0.671875, y: 0.890625 },\n  { x: 0.671875, y: 0.890625 },\n  { x: 0.703125, y: 0.890625 },\n  { x: 0.703125, y: 0.890625 },\n  { x: 0.734375, y: 0.890625 },\n  { x: 0.734375, y: 0.890625 },\n  { x: 0.765625, y: 0.890625 },\n  { x: 0.765625, y: 0.890625 },\n  { x: 0.796875, y: 0.890625 },\n  { x: 0.796875, y: 0.890625 },\n  { x: 0.828125, y: 0.890625 },\n  { x: 0.828125, y: 0.890625 },\n  { x: 0.859375, y: 0.890625 },\n  { x: 0.859375, y: 0.890625 },\n  { x: 0.890625, y: 0.890625 },\n  { x: 0.890625, y: 0.890625 },\n  { x: 0.921875, y: 0.890625 },\n  { x: 0.921875, y: 0.890625 },\n  { x: 0.953125, y: 0.890625 },\n  { x: 0.953125, y: 0.890625 },\n  { x: 0.984375, y: 0.890625 },\n  { x: 0.984375, y: 0.890625 },\n  { x: 0.015625, y: 0.921875 },\n  { x: 0.015625, y: 0.921875 },\n  { x: 0.046875, y: 0.921875 },\n  { x: 0.046875, y: 0.921875 },\n  { x: 0.078125, y: 0.921875 },\n  { x: 0.078125, y: 0.921875 },\n  { x: 0.109375, y: 0.921875 },\n  { x: 0.109375, y: 0.921875 },\n  { x: 0.140625, y: 0.921875 },\n  { x: 0.140625, y: 0.921875 },\n  { x: 0.171875, y: 0.921875 },\n  { x: 0.171875, y: 0.921875 },\n  { x: 0.203125, y: 0.921875 },\n  { x: 0.203125, y: 0.921875 },\n  { x: 0.234375, y: 0.921875 },\n  { x: 0.234375, y: 0.921875 },\n  { x: 0.265625, y: 0.921875 },\n  { x: 0.265625, y: 0.921875 },\n  { x: 0.296875, y: 0.921875 },\n  { x: 0.296875, y: 0.921875 },\n  { x: 0.328125, y: 0.921875 },\n  { x: 0.328125, y: 0.921875 },\n  { x: 0.359375, y: 0.921875 },\n  { x: 0.359375, y: 0.921875 },\n  { x: 0.390625, y: 0.921875 },\n  { x: 0.390625, y: 0.921875 },\n  { x: 0.421875, y: 0.921875 },\n  { x: 0.421875, y: 0.921875 },\n  { x: 0.453125, y: 0.921875 },\n  { x: 0.453125, y: 0.921875 },\n  { x: 0.484375, y: 0.921875 },\n  { x: 0.484375, y: 0.921875 },\n  { x: 0.515625, y: 0.921875 },\n  { x: 0.515625, y: 0.921875 },\n  { x: 0.546875, y: 0.921875 },\n  { x: 0.546875, y: 0.921875 },\n  { x: 0.578125, y: 0.921875 },\n  { x: 0.578125, y: 0.921875 },\n  { x: 0.609375, y: 0.921875 },\n  { x: 0.609375, y: 0.921875 },\n  { x: 0.640625, y: 0.921875 },\n  { x: 0.640625, y: 0.921875 },\n  { x: 0.671875, y: 0.921875 },\n  { x: 0.671875, y: 0.921875 },\n  { x: 0.703125, y: 0.921875 },\n  { x: 0.703125, y: 0.921875 },\n  { x: 0.734375, y: 0.921875 },\n  { x: 0.734375, y: 0.921875 },\n  { x: 0.765625, y: 0.921875 },\n  { x: 0.765625, y: 0.921875 },\n  { x: 0.796875, y: 0.921875 },\n  { x: 0.796875, y: 0.921875 },\n  { x: 0.828125, y: 0.921875 },\n  { x: 0.828125, y: 0.921875 },\n  { x: 0.859375, y: 0.921875 },\n  { x: 0.859375, y: 0.921875 },\n  { x: 0.890625, y: 0.921875 },\n  { x: 0.890625, y: 0.921875 },\n  { x: 0.921875, y: 0.921875 },\n  { x: 0.921875, y: 0.921875 },\n  { x: 0.953125, y: 0.921875 },\n  { x: 0.953125, y: 0.921875 },\n  { x: 0.984375, y: 0.921875 },\n  { x: 0.984375, y: 0.921875 },\n  { x: 0.015625, y: 0.953125 },\n  { x: 0.015625, y: 0.953125 },\n  { x: 0.046875, y: 0.953125 },\n  { x: 0.046875, y: 0.953125 },\n  { x: 0.078125, y: 0.953125 },\n  { x: 0.078125, y: 0.953125 },\n  { x: 0.109375, y: 0.953125 },\n  { x: 0.109375, y: 0.953125 },\n  { x: 0.140625, y: 0.953125 },\n  { x: 0.140625, y: 0.953125 },\n  { x: 0.171875, y: 0.953125 },\n  { x: 0.171875, y: 0.953125 },\n  { x: 0.203125, y: 0.953125 },\n  { x: 0.203125, y: 0.953125 },\n  { x: 0.234375, y: 0.953125 },\n  { x: 0.234375, y: 0.953125 },\n  { x: 0.265625, y: 0.953125 },\n  { x: 0.265625, y: 0.953125 },\n  { x: 0.296875, y: 0.953125 },\n  { x: 0.296875, y: 0.953125 },\n  { x: 0.328125, y: 0.953125 },\n  { x: 0.328125, y: 0.953125 },\n  { x: 0.359375, y: 0.953125 },\n  { x: 0.359375, y: 0.953125 },\n  { x: 0.390625, y: 0.953125 },\n  { x: 0.390625, y: 0.953125 },\n  { x: 0.421875, y: 0.953125 },\n  { x: 0.421875, y: 0.953125 },\n  { x: 0.453125, y: 0.953125 },\n  { x: 0.453125, y: 0.953125 },\n  { x: 0.484375, y: 0.953125 },\n  { x: 0.484375, y: 0.953125 },\n  { x: 0.515625, y: 0.953125 },\n  { x: 0.515625, y: 0.953125 },\n  { x: 0.546875, y: 0.953125 },\n  { x: 0.546875, y: 0.953125 },\n  { x: 0.578125, y: 0.953125 },\n  { x: 0.578125, y: 0.953125 },\n  { x: 0.609375, y: 0.953125 },\n  { x: 0.609375, y: 0.953125 },\n  { x: 0.640625, y: 0.953125 },\n  { x: 0.640625, y: 0.953125 },\n  { x: 0.671875, y: 0.953125 },\n  { x: 0.671875, y: 0.953125 },\n  { x: 0.703125, y: 0.953125 },\n  { x: 0.703125, y: 0.953125 },\n  { x: 0.734375, y: 0.953125 },\n  { x: 0.734375, y: 0.953125 },\n  { x: 0.765625, y: 0.953125 },\n  { x: 0.765625, y: 0.953125 },\n  { x: 0.796875, y: 0.953125 },\n  { x: 0.796875, y: 0.953125 },\n  { x: 0.828125, y: 0.953125 },\n  { x: 0.828125, y: 0.953125 },\n  { x: 0.859375, y: 0.953125 },\n  { x: 0.859375, y: 0.953125 },\n  { x: 0.890625, y: 0.953125 },\n  { x: 0.890625, y: 0.953125 },\n  { x: 0.921875, y: 0.953125 },\n  { x: 0.921875, y: 0.953125 },\n  { x: 0.953125, y: 0.953125 },\n  { x: 0.953125, y: 0.953125 },\n  { x: 0.984375, y: 0.953125 },\n  { x: 0.984375, y: 0.953125 },\n  { x: 0.015625, y: 0.984375 },\n  { x: 0.015625, y: 0.984375 },\n  { x: 0.046875, y: 0.984375 },\n  { x: 0.046875, y: 0.984375 },\n  { x: 0.078125, y: 0.984375 },\n  { x: 0.078125, y: 0.984375 },\n  { x: 0.109375, y: 0.984375 },\n  { x: 0.109375, y: 0.984375 },\n  { x: 0.140625, y: 0.984375 },\n  { x: 0.140625, y: 0.984375 },\n  { x: 0.171875, y: 0.984375 },\n  { x: 0.171875, y: 0.984375 },\n  { x: 0.203125, y: 0.984375 },\n  { x: 0.203125, y: 0.984375 },\n  { x: 0.234375, y: 0.984375 },\n  { x: 0.234375, y: 0.984375 },\n  { x: 0.265625, y: 0.984375 },\n  { x: 0.265625, y: 0.984375 },\n  { x: 0.296875, y: 0.984375 },\n  { x: 0.296875, y: 0.984375 },\n  { x: 0.328125, y: 0.984375 },\n  { x: 0.328125, y: 0.984375 },\n  { x: 0.359375, y: 0.984375 },\n  { x: 0.359375, y: 0.984375 },\n  { x: 0.390625, y: 0.984375 },\n  { x: 0.390625, y: 0.984375 },\n  { x: 0.421875, y: 0.984375 },\n  { x: 0.421875, y: 0.984375 },\n  { x: 0.453125, y: 0.984375 },\n  { x: 0.453125, y: 0.984375 },\n  { x: 0.484375, y: 0.984375 },\n  { x: 0.484375, y: 0.984375 },\n  { x: 0.515625, y: 0.984375 },\n  { x: 0.515625, y: 0.984375 },\n  { x: 0.546875, y: 0.984375 },\n  { x: 0.546875, y: 0.984375 },\n  { x: 0.578125, y: 0.984375 },\n  { x: 0.578125, y: 0.984375 },\n  { x: 0.609375, y: 0.984375 },\n  { x: 0.609375, y: 0.984375 },\n  { x: 0.640625, y: 0.984375 },\n  { x: 0.640625, y: 0.984375 },\n  { x: 0.671875, y: 0.984375 },\n  { x: 0.671875, y: 0.984375 },\n  { x: 0.703125, y: 0.984375 },\n  { x: 0.703125, y: 0.984375 },\n  { x: 0.734375, y: 0.984375 },\n  { x: 0.734375, y: 0.984375 },\n  { x: 0.765625, y: 0.984375 },\n  { x: 0.765625, y: 0.984375 },\n  { x: 0.796875, y: 0.984375 },\n  { x: 0.796875, y: 0.984375 },\n  { x: 0.828125, y: 0.984375 },\n  { x: 0.828125, y: 0.984375 },\n  { x: 0.859375, y: 0.984375 },\n  { x: 0.859375, y: 0.984375 },\n  { x: 0.890625, y: 0.984375 },\n  { x: 0.890625, y: 0.984375 },\n  { x: 0.921875, y: 0.984375 },\n  { x: 0.921875, y: 0.984375 },\n  { x: 0.953125, y: 0.984375 },\n  { x: 0.953125, y: 0.984375 },\n  { x: 0.984375, y: 0.984375 },\n  { x: 0.984375, y: 0.984375 },\n  { x: 0.03125, y: 0.03125 },\n  { x: 0.03125, y: 0.03125 },\n  { x: 0.09375, y: 0.03125 },\n  { x: 0.09375, y: 0.03125 },\n  { x: 0.15625, y: 0.03125 },\n  { x: 0.15625, y: 0.03125 },\n  { x: 0.21875, y: 0.03125 },\n  { x: 0.21875, y: 0.03125 },\n  { x: 0.28125, y: 0.03125 },\n  { x: 0.28125, y: 0.03125 },\n  { x: 0.34375, y: 0.03125 },\n  { x: 0.34375, y: 0.03125 },\n  { x: 0.40625, y: 0.03125 },\n  { x: 0.40625, y: 0.03125 },\n  { x: 0.46875, y: 0.03125 },\n  { x: 0.46875, y: 0.03125 },\n  { x: 0.53125, y: 0.03125 },\n  { x: 0.53125, y: 0.03125 },\n  { x: 0.59375, y: 0.03125 },\n  { x: 0.59375, y: 0.03125 },\n  { x: 0.65625, y: 0.03125 },\n  { x: 0.65625, y: 0.03125 },\n  { x: 0.71875, y: 0.03125 },\n  { x: 0.71875, y: 0.03125 },\n  { x: 0.78125, y: 0.03125 },\n  { x: 0.78125, y: 0.03125 },\n  { x: 0.84375, y: 0.03125 },\n  { x: 0.84375, y: 0.03125 },\n  { x: 0.90625, y: 0.03125 },\n  { x: 0.90625, y: 0.03125 },\n  { x: 0.96875, y: 0.03125 },\n  { x: 0.96875, y: 0.03125 },\n  { x: 0.03125, y: 0.09375 },\n  { x: 0.03125, y: 0.09375 },\n  { x: 0.09375, y: 0.09375 },\n  { x: 0.09375, y: 0.09375 },\n  { x: 0.15625, y: 0.09375 },\n  { x: 0.15625, y: 0.09375 },\n  { x: 0.21875, y: 0.09375 },\n  { x: 0.21875, y: 0.09375 },\n  { x: 0.28125, y: 0.09375 },\n  { x: 0.28125, y: 0.09375 },\n  { x: 0.34375, y: 0.09375 },\n  { x: 0.34375, y: 0.09375 },\n  { x: 0.40625, y: 0.09375 },\n  { x: 0.40625, y: 0.09375 },\n  { x: 0.46875, y: 0.09375 },\n  { x: 0.46875, y: 0.09375 },\n  { x: 0.53125, y: 0.09375 },\n  { x: 0.53125, y: 0.09375 },\n  { x: 0.59375, y: 0.09375 },\n  { x: 0.59375, y: 0.09375 },\n  { x: 0.65625, y: 0.09375 },\n  { x: 0.65625, y: 0.09375 },\n  { x: 0.71875, y: 0.09375 },\n  { x: 0.71875, y: 0.09375 },\n  { x: 0.78125, y: 0.09375 },\n  { x: 0.78125, y: 0.09375 },\n  { x: 0.84375, y: 0.09375 },\n  { x: 0.84375, y: 0.09375 },\n  { x: 0.90625, y: 0.09375 },\n  { x: 0.90625, y: 0.09375 },\n  { x: 0.96875, y: 0.09375 },\n  { x: 0.96875, y: 0.09375 },\n  { x: 0.03125, y: 0.15625 },\n  { x: 0.03125, y: 0.15625 },\n  { x: 0.09375, y: 0.15625 },\n  { x: 0.09375, y: 0.15625 },\n  { x: 0.15625, y: 0.15625 },\n  { x: 0.15625, y: 0.15625 },\n  { x: 0.21875, y: 0.15625 },\n  { x: 0.21875, y: 0.15625 },\n  { x: 0.28125, y: 0.15625 },\n  { x: 0.28125, y: 0.15625 },\n  { x: 0.34375, y: 0.15625 },\n  { x: 0.34375, y: 0.15625 },\n  { x: 0.40625, y: 0.15625 },\n  { x: 0.40625, y: 0.15625 },\n  { x: 0.46875, y: 0.15625 },\n  { x: 0.46875, y: 0.15625 },\n  { x: 0.53125, y: 0.15625 },\n  { x: 0.53125, y: 0.15625 },\n  { x: 0.59375, y: 0.15625 },\n  { x: 0.59375, y: 0.15625 },\n  { x: 0.65625, y: 0.15625 },\n  { x: 0.65625, y: 0.15625 },\n  { x: 0.71875, y: 0.15625 },\n  { x: 0.71875, y: 0.15625 },\n  { x: 0.78125, y: 0.15625 },\n  { x: 0.78125, y: 0.15625 },\n  { x: 0.84375, y: 0.15625 },\n  { x: 0.84375, y: 0.15625 },\n  { x: 0.90625, y: 0.15625 },\n  { x: 0.90625, y: 0.15625 },\n  { x: 0.96875, y: 0.15625 },\n  { x: 0.96875, y: 0.15625 },\n  { x: 0.03125, y: 0.21875 },\n  { x: 0.03125, y: 0.21875 },\n  { x: 0.09375, y: 0.21875 },\n  { x: 0.09375, y: 0.21875 },\n  { x: 0.15625, y: 0.21875 },\n  { x: 0.15625, y: 0.21875 },\n  { x: 0.21875, y: 0.21875 },\n  { x: 0.21875, y: 0.21875 },\n  { x: 0.28125, y: 0.21875 },\n  { x: 0.28125, y: 0.21875 },\n  { x: 0.34375, y: 0.21875 },\n  { x: 0.34375, y: 0.21875 },\n  { x: 0.40625, y: 0.21875 },\n  { x: 0.40625, y: 0.21875 },\n  { x: 0.46875, y: 0.21875 },\n  { x: 0.46875, y: 0.21875 },\n  { x: 0.53125, y: 0.21875 },\n  { x: 0.53125, y: 0.21875 },\n  { x: 0.59375, y: 0.21875 },\n  { x: 0.59375, y: 0.21875 },\n  { x: 0.65625, y: 0.21875 },\n  { x: 0.65625, y: 0.21875 },\n  { x: 0.71875, y: 0.21875 },\n  { x: 0.71875, y: 0.21875 },\n  { x: 0.78125, y: 0.21875 },\n  { x: 0.78125, y: 0.21875 },\n  { x: 0.84375, y: 0.21875 },\n  { x: 0.84375, y: 0.21875 },\n  { x: 0.90625, y: 0.21875 },\n  { x: 0.90625, y: 0.21875 },\n  { x: 0.96875, y: 0.21875 },\n  { x: 0.96875, y: 0.21875 },\n  { x: 0.03125, y: 0.28125 },\n  { x: 0.03125, y: 0.28125 },\n  { x: 0.09375, y: 0.28125 },\n  { x: 0.09375, y: 0.28125 },\n  { x: 0.15625, y: 0.28125 },\n  { x: 0.15625, y: 0.28125 },\n  { x: 0.21875, y: 0.28125 },\n  { x: 0.21875, y: 0.28125 },\n  { x: 0.28125, y: 0.28125 },\n  { x: 0.28125, y: 0.28125 },\n  { x: 0.34375, y: 0.28125 },\n  { x: 0.34375, y: 0.28125 },\n  { x: 0.40625, y: 0.28125 },\n  { x: 0.40625, y: 0.28125 },\n  { x: 0.46875, y: 0.28125 },\n  { x: 0.46875, y: 0.28125 },\n  { x: 0.53125, y: 0.28125 },\n  { x: 0.53125, y: 0.28125 },\n  { x: 0.59375, y: 0.28125 },\n  { x: 0.59375, y: 0.28125 },\n  { x: 0.65625, y: 0.28125 },\n  { x: 0.65625, y: 0.28125 },\n  { x: 0.71875, y: 0.28125 },\n  { x: 0.71875, y: 0.28125 },\n  { x: 0.78125, y: 0.28125 },\n  { x: 0.78125, y: 0.28125 },\n  { x: 0.84375, y: 0.28125 },\n  { x: 0.84375, y: 0.28125 },\n  { x: 0.90625, y: 0.28125 },\n  { x: 0.90625, y: 0.28125 },\n  { x: 0.96875, y: 0.28125 },\n  { x: 0.96875, y: 0.28125 },\n  { x: 0.03125, y: 0.34375 },\n  { x: 0.03125, y: 0.34375 },\n  { x: 0.09375, y: 0.34375 },\n  { x: 0.09375, y: 0.34375 },\n  { x: 0.15625, y: 0.34375 },\n  { x: 0.15625, y: 0.34375 },\n  { x: 0.21875, y: 0.34375 },\n  { x: 0.21875, y: 0.34375 },\n  { x: 0.28125, y: 0.34375 },\n  { x: 0.28125, y: 0.34375 },\n  { x: 0.34375, y: 0.34375 },\n  { x: 0.34375, y: 0.34375 },\n  { x: 0.40625, y: 0.34375 },\n  { x: 0.40625, y: 0.34375 },\n  { x: 0.46875, y: 0.34375 },\n  { x: 0.46875, y: 0.34375 },\n  { x: 0.53125, y: 0.34375 },\n  { x: 0.53125, y: 0.34375 },\n  { x: 0.59375, y: 0.34375 },\n  { x: 0.59375, y: 0.34375 },\n  { x: 0.65625, y: 0.34375 },\n  { x: 0.65625, y: 0.34375 },\n  { x: 0.71875, y: 0.34375 },\n  { x: 0.71875, y: 0.34375 },\n  { x: 0.78125, y: 0.34375 },\n  { x: 0.78125, y: 0.34375 },\n  { x: 0.84375, y: 0.34375 },\n  { x: 0.84375, y: 0.34375 },\n  { x: 0.90625, y: 0.34375 },\n  { x: 0.90625, y: 0.34375 },\n  { x: 0.96875, y: 0.34375 },\n  { x: 0.96875, y: 0.34375 },\n  { x: 0.03125, y: 0.40625 },\n  { x: 0.03125, y: 0.40625 },\n  { x: 0.09375, y: 0.40625 },\n  { x: 0.09375, y: 0.40625 },\n  { x: 0.15625, y: 0.40625 },\n  { x: 0.15625, y: 0.40625 },\n  { x: 0.21875, y: 0.40625 },\n  { x: 0.21875, y: 0.40625 },\n  { x: 0.28125, y: 0.40625 },\n  { x: 0.28125, y: 0.40625 },\n  { x: 0.34375, y: 0.40625 },\n  { x: 0.34375, y: 0.40625 },\n  { x: 0.40625, y: 0.40625 },\n  { x: 0.40625, y: 0.40625 },\n  { x: 0.46875, y: 0.40625 },\n  { x: 0.46875, y: 0.40625 },\n  { x: 0.53125, y: 0.40625 },\n  { x: 0.53125, y: 0.40625 },\n  { x: 0.59375, y: 0.40625 },\n  { x: 0.59375, y: 0.40625 },\n  { x: 0.65625, y: 0.40625 },\n  { x: 0.65625, y: 0.40625 },\n  { x: 0.71875, y: 0.40625 },\n  { x: 0.71875, y: 0.40625 },\n  { x: 0.78125, y: 0.40625 },\n  { x: 0.78125, y: 0.40625 },\n  { x: 0.84375, y: 0.40625 },\n  { x: 0.84375, y: 0.40625 },\n  { x: 0.90625, y: 0.40625 },\n  { x: 0.90625, y: 0.40625 },\n  { x: 0.96875, y: 0.40625 },\n  { x: 0.96875, y: 0.40625 },\n  { x: 0.03125, y: 0.46875 },\n  { x: 0.03125, y: 0.46875 },\n  { x: 0.09375, y: 0.46875 },\n  { x: 0.09375, y: 0.46875 },\n  { x: 0.15625, y: 0.46875 },\n  { x: 0.15625, y: 0.46875 },\n  { x: 0.21875, y: 0.46875 },\n  { x: 0.21875, y: 0.46875 },\n  { x: 0.28125, y: 0.46875 },\n  { x: 0.28125, y: 0.46875 },\n  { x: 0.34375, y: 0.46875 },\n  { x: 0.34375, y: 0.46875 },\n  { x: 0.40625, y: 0.46875 },\n  { x: 0.40625, y: 0.46875 },\n  { x: 0.46875, y: 0.46875 },\n  { x: 0.46875, y: 0.46875 },\n  { x: 0.53125, y: 0.46875 },\n  { x: 0.53125, y: 0.46875 },\n  { x: 0.59375, y: 0.46875 },\n  { x: 0.59375, y: 0.46875 },\n  { x: 0.65625, y: 0.46875 },\n  { x: 0.65625, y: 0.46875 },\n  { x: 0.71875, y: 0.46875 },\n  { x: 0.71875, y: 0.46875 },\n  { x: 0.78125, y: 0.46875 },\n  { x: 0.78125, y: 0.46875 },\n  { x: 0.84375, y: 0.46875 },\n  { x: 0.84375, y: 0.46875 },\n  { x: 0.90625, y: 0.46875 },\n  { x: 0.90625, y: 0.46875 },\n  { x: 0.96875, y: 0.46875 },\n  { x: 0.96875, y: 0.46875 },\n  { x: 0.03125, y: 0.53125 },\n  { x: 0.03125, y: 0.53125 },\n  { x: 0.09375, y: 0.53125 },\n  { x: 0.09375, y: 0.53125 },\n  { x: 0.15625, y: 0.53125 },\n  { x: 0.15625, y: 0.53125 },\n  { x: 0.21875, y: 0.53125 },\n  { x: 0.21875, y: 0.53125 },\n  { x: 0.28125, y: 0.53125 },\n  { x: 0.28125, y: 0.53125 },\n  { x: 0.34375, y: 0.53125 },\n  { x: 0.34375, y: 0.53125 },\n  { x: 0.40625, y: 0.53125 },\n  { x: 0.40625, y: 0.53125 },\n  { x: 0.46875, y: 0.53125 },\n  { x: 0.46875, y: 0.53125 },\n  { x: 0.53125, y: 0.53125 },\n  { x: 0.53125, y: 0.53125 },\n  { x: 0.59375, y: 0.53125 },\n  { x: 0.59375, y: 0.53125 },\n  { x: 0.65625, y: 0.53125 },\n  { x: 0.65625, y: 0.53125 },\n  { x: 0.71875, y: 0.53125 },\n  { x: 0.71875, y: 0.53125 },\n  { x: 0.78125, y: 0.53125 },\n  { x: 0.78125, y: 0.53125 },\n  { x: 0.84375, y: 0.53125 },\n  { x: 0.84375, y: 0.53125 },\n  { x: 0.90625, y: 0.53125 },\n  { x: 0.90625, y: 0.53125 },\n  { x: 0.96875, y: 0.53125 },\n  { x: 0.96875, y: 0.53125 },\n  { x: 0.03125, y: 0.59375 },\n  { x: 0.03125, y: 0.59375 },\n  { x: 0.09375, y: 0.59375 },\n  { x: 0.09375, y: 0.59375 },\n  { x: 0.15625, y: 0.59375 },\n  { x: 0.15625, y: 0.59375 },\n  { x: 0.21875, y: 0.59375 },\n  { x: 0.21875, y: 0.59375 },\n  { x: 0.28125, y: 0.59375 },\n  { x: 0.28125, y: 0.59375 },\n  { x: 0.34375, y: 0.59375 },\n  { x: 0.34375, y: 0.59375 },\n  { x: 0.40625, y: 0.59375 },\n  { x: 0.40625, y: 0.59375 },\n  { x: 0.46875, y: 0.59375 },\n  { x: 0.46875, y: 0.59375 },\n  { x: 0.53125, y: 0.59375 },\n  { x: 0.53125, y: 0.59375 },\n  { x: 0.59375, y: 0.59375 },\n  { x: 0.59375, y: 0.59375 },\n  { x: 0.65625, y: 0.59375 },\n  { x: 0.65625, y: 0.59375 },\n  { x: 0.71875, y: 0.59375 },\n  { x: 0.71875, y: 0.59375 },\n  { x: 0.78125, y: 0.59375 },\n  { x: 0.78125, y: 0.59375 },\n  { x: 0.84375, y: 0.59375 },\n  { x: 0.84375, y: 0.59375 },\n  { x: 0.90625, y: 0.59375 },\n  { x: 0.90625, y: 0.59375 },\n  { x: 0.96875, y: 0.59375 },\n  { x: 0.96875, y: 0.59375 },\n  { x: 0.03125, y: 0.65625 },\n  { x: 0.03125, y: 0.65625 },\n  { x: 0.09375, y: 0.65625 },\n  { x: 0.09375, y: 0.65625 },\n  { x: 0.15625, y: 0.65625 },\n  { x: 0.15625, y: 0.65625 },\n  { x: 0.21875, y: 0.65625 },\n  { x: 0.21875, y: 0.65625 },\n  { x: 0.28125, y: 0.65625 },\n  { x: 0.28125, y: 0.65625 },\n  { x: 0.34375, y: 0.65625 },\n  { x: 0.34375, y: 0.65625 },\n  { x: 0.40625, y: 0.65625 },\n  { x: 0.40625, y: 0.65625 },\n  { x: 0.46875, y: 0.65625 },\n  { x: 0.46875, y: 0.65625 },\n  { x: 0.53125, y: 0.65625 },\n  { x: 0.53125, y: 0.65625 },\n  { x: 0.59375, y: 0.65625 },\n  { x: 0.59375, y: 0.65625 },\n  { x: 0.65625, y: 0.65625 },\n  { x: 0.65625, y: 0.65625 },\n  { x: 0.71875, y: 0.65625 },\n  { x: 0.71875, y: 0.65625 },\n  { x: 0.78125, y: 0.65625 },\n  { x: 0.78125, y: 0.65625 },\n  { x: 0.84375, y: 0.65625 },\n  { x: 0.84375, y: 0.65625 },\n  { x: 0.90625, y: 0.65625 },\n  { x: 0.90625, y: 0.65625 },\n  { x: 0.96875, y: 0.65625 },\n  { x: 0.96875, y: 0.65625 },\n  { x: 0.03125, y: 0.71875 },\n  { x: 0.03125, y: 0.71875 },\n  { x: 0.09375, y: 0.71875 },\n  { x: 0.09375, y: 0.71875 },\n  { x: 0.15625, y: 0.71875 },\n  { x: 0.15625, y: 0.71875 },\n  { x: 0.21875, y: 0.71875 },\n  { x: 0.21875, y: 0.71875 },\n  { x: 0.28125, y: 0.71875 },\n  { x: 0.28125, y: 0.71875 },\n  { x: 0.34375, y: 0.71875 },\n  { x: 0.34375, y: 0.71875 },\n  { x: 0.40625, y: 0.71875 },\n  { x: 0.40625, y: 0.71875 },\n  { x: 0.46875, y: 0.71875 },\n  { x: 0.46875, y: 0.71875 },\n  { x: 0.53125, y: 0.71875 },\n  { x: 0.53125, y: 0.71875 },\n  { x: 0.59375, y: 0.71875 },\n  { x: 0.59375, y: 0.71875 },\n  { x: 0.65625, y: 0.71875 },\n  { x: 0.65625, y: 0.71875 },\n  { x: 0.71875, y: 0.71875 },\n  { x: 0.71875, y: 0.71875 },\n  { x: 0.78125, y: 0.71875 },\n  { x: 0.78125, y: 0.71875 },\n  { x: 0.84375, y: 0.71875 },\n  { x: 0.84375, y: 0.71875 },\n  { x: 0.90625, y: 0.71875 },\n  { x: 0.90625, y: 0.71875 },\n  { x: 0.96875, y: 0.71875 },\n  { x: 0.96875, y: 0.71875 },\n  { x: 0.03125, y: 0.78125 },\n  { x: 0.03125, y: 0.78125 },\n  { x: 0.09375, y: 0.78125 },\n  { x: 0.09375, y: 0.78125 },\n  { x: 0.15625, y: 0.78125 },\n  { x: 0.15625, y: 0.78125 },\n  { x: 0.21875, y: 0.78125 },\n  { x: 0.21875, y: 0.78125 },\n  { x: 0.28125, y: 0.78125 },\n  { x: 0.28125, y: 0.78125 },\n  { x: 0.34375, y: 0.78125 },\n  { x: 0.34375, y: 0.78125 },\n  { x: 0.40625, y: 0.78125 },\n  { x: 0.40625, y: 0.78125 },\n  { x: 0.46875, y: 0.78125 },\n  { x: 0.46875, y: 0.78125 },\n  { x: 0.53125, y: 0.78125 },\n  { x: 0.53125, y: 0.78125 },\n  { x: 0.59375, y: 0.78125 },\n  { x: 0.59375, y: 0.78125 },\n  { x: 0.65625, y: 0.78125 },\n  { x: 0.65625, y: 0.78125 },\n  { x: 0.71875, y: 0.78125 },\n  { x: 0.71875, y: 0.78125 },\n  { x: 0.78125, y: 0.78125 },\n  { x: 0.78125, y: 0.78125 },\n  { x: 0.84375, y: 0.78125 },\n  { x: 0.84375, y: 0.78125 },\n  { x: 0.90625, y: 0.78125 },\n  { x: 0.90625, y: 0.78125 },\n  { x: 0.96875, y: 0.78125 },\n  { x: 0.96875, y: 0.78125 },\n  { x: 0.03125, y: 0.84375 },\n  { x: 0.03125, y: 0.84375 },\n  { x: 0.09375, y: 0.84375 },\n  { x: 0.09375, y: 0.84375 },\n  { x: 0.15625, y: 0.84375 },\n  { x: 0.15625, y: 0.84375 },\n  { x: 0.21875, y: 0.84375 },\n  { x: 0.21875, y: 0.84375 },\n  { x: 0.28125, y: 0.84375 },\n  { x: 0.28125, y: 0.84375 },\n  { x: 0.34375, y: 0.84375 },\n  { x: 0.34375, y: 0.84375 },\n  { x: 0.40625, y: 0.84375 },\n  { x: 0.40625, y: 0.84375 },\n  { x: 0.46875, y: 0.84375 },\n  { x: 0.46875, y: 0.84375 },\n  { x: 0.53125, y: 0.84375 },\n  { x: 0.53125, y: 0.84375 },\n  { x: 0.59375, y: 0.84375 },\n  { x: 0.59375, y: 0.84375 },\n  { x: 0.65625, y: 0.84375 },\n  { x: 0.65625, y: 0.84375 },\n  { x: 0.71875, y: 0.84375 },\n  { x: 0.71875, y: 0.84375 },\n  { x: 0.78125, y: 0.84375 },\n  { x: 0.78125, y: 0.84375 },\n  { x: 0.84375, y: 0.84375 },\n  { x: 0.84375, y: 0.84375 },\n  { x: 0.90625, y: 0.84375 },\n  { x: 0.90625, y: 0.84375 },\n  { x: 0.96875, y: 0.84375 },\n  { x: 0.96875, y: 0.84375 },\n  { x: 0.03125, y: 0.90625 },\n  { x: 0.03125, y: 0.90625 },\n  { x: 0.09375, y: 0.90625 },\n  { x: 0.09375, y: 0.90625 },\n  { x: 0.15625, y: 0.90625 },\n  { x: 0.15625, y: 0.90625 },\n  { x: 0.21875, y: 0.90625 },\n  { x: 0.21875, y: 0.90625 },\n  { x: 0.28125, y: 0.90625 },\n  { x: 0.28125, y: 0.90625 },\n  { x: 0.34375, y: 0.90625 },\n  { x: 0.34375, y: 0.90625 },\n  { x: 0.40625, y: 0.90625 },\n  { x: 0.40625, y: 0.90625 },\n  { x: 0.46875, y: 0.90625 },\n  { x: 0.46875, y: 0.90625 },\n  { x: 0.53125, y: 0.90625 },\n  { x: 0.53125, y: 0.90625 },\n  { x: 0.59375, y: 0.90625 },\n  { x: 0.59375, y: 0.90625 },\n  { x: 0.65625, y: 0.90625 },\n  { x: 0.65625, y: 0.90625 },\n  { x: 0.71875, y: 0.90625 },\n  { x: 0.71875, y: 0.90625 },\n  { x: 0.78125, y: 0.90625 },\n  { x: 0.78125, y: 0.90625 },\n  { x: 0.84375, y: 0.90625 },\n  { x: 0.84375, y: 0.90625 },\n  { x: 0.90625, y: 0.90625 },\n  { x: 0.90625, y: 0.90625 },\n  { x: 0.96875, y: 0.90625 },\n  { x: 0.96875, y: 0.90625 },\n  { x: 0.03125, y: 0.96875 },\n  { x: 0.03125, y: 0.96875 },\n  { x: 0.09375, y: 0.96875 },\n  { x: 0.09375, y: 0.96875 },\n  { x: 0.15625, y: 0.96875 },\n  { x: 0.15625, y: 0.96875 },\n  { x: 0.21875, y: 0.96875 },\n  { x: 0.21875, y: 0.96875 },\n  { x: 0.28125, y: 0.96875 },\n  { x: 0.28125, y: 0.96875 },\n  { x: 0.34375, y: 0.96875 },\n  { x: 0.34375, y: 0.96875 },\n  { x: 0.40625, y: 0.96875 },\n  { x: 0.40625, y: 0.96875 },\n  { x: 0.46875, y: 0.96875 },\n  { x: 0.46875, y: 0.96875 },\n  { x: 0.53125, y: 0.96875 },\n  { x: 0.53125, y: 0.96875 },\n  { x: 0.59375, y: 0.96875 },\n  { x: 0.59375, y: 0.96875 },\n  { x: 0.65625, y: 0.96875 },\n  { x: 0.65625, y: 0.96875 },\n  { x: 0.71875, y: 0.96875 },\n  { x: 0.71875, y: 0.96875 },\n  { x: 0.78125, y: 0.96875 },\n  { x: 0.78125, y: 0.96875 },\n  { x: 0.84375, y: 0.96875 },\n  { x: 0.84375, y: 0.96875 },\n  { x: 0.90625, y: 0.96875 },\n  { x: 0.90625, y: 0.96875 },\n  { x: 0.96875, y: 0.96875 },\n  { x: 0.96875, y: 0.96875 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n];\n", "/**\n * HandPose model implementation\n * See `handpose.ts` for entry point\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as util from './handposeutil';\nimport * as anchors from './handposeanchors';\nimport { constants } from '../tfjs/constants';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Point } from '../result';\n\nexport class HandDetector {\n  model: GraphModel;\n  anchors: number[][];\n  anchorsTensor: Tensor;\n  inputSize: number;\n  inputSizeTensor: Tensor;\n  doubleInputSizeTensor: Tensor;\n\n  constructor(model) {\n    this.model = model;\n    this.anchors = anchors.anchors.map((anchor) => [anchor.x, anchor.y]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = (this.model && this.model.inputs && this.model.inputs[0].shape) ? this.model.inputs[0].shape[2] : 0;\n    this.inputSizeTensor = tf.tensor1d([this.inputSize, this.inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([this.inputSize * 2, this.inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    const t: Record<string, Tensor> = {};\n    t.boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n    t.boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n    t.div = tf.div(t.boxOffsets, this.inputSizeTensor);\n    t.boxCenterPoints = tf.add(t.div, this.anchorsTensor);\n    t.halfBoxSizes = tf.div(t.boxSizes, this.doubleInputSizeTensor);\n    t.sub = tf.sub(t.boxCenterPoints, t.halfBoxSizes);\n    t.startPoints = tf.mul(t.sub, this.inputSizeTensor);\n    t.add = tf.add(t.boxCenterPoints, t.halfBoxSizes);\n    t.endPoints = tf.mul(t.add, this.inputSizeTensor);\n    const res = tf.concat2d([t.startPoints, t.endPoints], 1);\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return res;\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    const t: Record<string, Tensor> = {};\n    t.reshape = tf.reshape(rawPalmLandmarks, [-1, 7, 2]);\n    t.div = tf.div(t.reshape, this.inputSizeTensor);\n    t.landmarks = tf.add(t.div, this.anchors[index]);\n    const res = tf.mul(t.landmarks, this.inputSizeTensor);\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return res;\n  }\n\n  async predict(input, config): Promise<{ startPoint: Point; endPoint: Point, palmLandmarks: Point[]; confidence: number }[]> {\n    const t: Record<string, Tensor> = {};\n    t.resize = tf.image.resizeBilinear(input, [this.inputSize, this.inputSize]);\n    t.div = tf.div(t.resize, constants.tf127);\n    t.image = tf.sub(t.div, constants.tf1);\n    t.batched = this.model.execute(t.image) as Tensor;\n    t.predictions = tf.squeeze(t.batched);\n    t.slice = tf.slice(t.predictions, [0, 0], [-1, 1]);\n    t.sigmoid = tf.sigmoid(t.slice);\n    t.scores = tf.squeeze(t.sigmoid);\n    const scores = await t.scores.data();\n    t.boxes = tf.slice(t.predictions, [0, 1], [-1, 4]);\n    t.norm = this.normalizeBoxes(t.boxes);\n    // box detection is flaky so we look for 3x boxes than we need results\n    t.nms = await tf.image.nonMaxSuppressionAsync(t.norm, t.scores, 3 * config.hand.maxDetected, config.hand.iouThreshold, config.hand.minConfidence);\n    const nms = await t.nms.array() as Array<number>;\n    const hands: Array<{ startPoint: Point; endPoint: Point; palmLandmarks: Point[]; confidence: number }> = [];\n    for (const index of nms) {\n      const p: Record<string, Tensor> = {};\n      p.box = tf.slice(t.norm, [index, 0], [1, -1]);\n      p.slice = tf.slice(t.predictions, [index, 5], [1, 14]);\n      p.norm = this.normalizeLandmarks(p.slice, index);\n      p.palmLandmarks = tf.reshape(p.norm, [-1, 2]);\n      const box = await p.box.data();\n      const startPoint = box.slice(0, 2) as unknown as Point;\n      const endPoint = box.slice(2, 4) as unknown as Point;\n      const palmLandmarks = await p.palmLandmarks.array();\n      const hand = { startPoint, endPoint, palmLandmarks, confidence: scores[index] };\n      const scaled = util.scaleBoxCoordinates(hand, [input.shape[2] / this.inputSize, input.shape[1] / this.inputSize]);\n      hands.push(scaled);\n      Object.keys(p).forEach((tensor) => tf.dispose(p[tensor]));\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return hands;\n  }\n}\n", "/**\n * HandPose model implementation\n * See `handpose.ts` for entry point\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as util from './handposeutil';\nimport type * as detector from './handposedetector';\nimport { constants } from '../tfjs/constants';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport { env } from '../util/env';\nimport { now } from '../util/util';\nimport type { Point } from '../result';\n\nconst palmBoxEnlargeFactor = 5; // default 3\nconst handBoxEnlargeFactor = 1.65; // default 1.65\nconst palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];\nconst palmLandmarksPalmBase = 0;\nconst palmLandmarksMiddleFingerBase = 2;\nlet lastTime = 0;\n\nexport class HandPipeline {\n  handDetector: detector.HandDetector;\n  handPoseModel: GraphModel;\n  inputSize: number;\n  storedBoxes: Array<{ startPoint: Point; endPoint: Point; palmLandmarks: Point[]; confidence: number } | null>;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, handPoseModel) {\n    this.handDetector = handDetector;\n    this.handPoseModel = handPoseModel;\n    this.inputSize = this.handPoseModel && this.handPoseModel.inputs[0].shape ? this.handPoseModel.inputs[0].shape[2] : 0;\n    this.storedBoxes = [];\n    this.skipped = Number.MAX_SAFE_INTEGER;\n    this.detectedHands = 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    return util.enlargeBox(util.squarifyBox(boxAroundPalm), palmBoxEnlargeFactor);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    const boxAroundHand = util.enlargeBox(util.squarifyBox(boundingBox), handBoxEnlargeFactor);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < palmLandmarkIds.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[palmLandmarkIds[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = util.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...util.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      Math.trunc(coord[0] + originalBoxCenter[0]),\n      Math.trunc(coord[1] + originalBoxCenter[1]),\n      Math.trunc(coord[2]),\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames\n    let boxes;\n    const skipTime = (config.hand.skipTime || 0) > (now() - lastTime);\n    const skipFrame = this.skipped < (config.hand.skipFrames || 0);\n    if (config.skipAllowed && skipTime && skipFrame) {\n      boxes = await this.handDetector.predict(image, config);\n      this.skipped = 0;\n    }\n    if (config.skipAllowed) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxDetected) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{ landmarks: Point[], confidence: number, boxConfidence: number, fingerConfidence: number, box: { topLeft: Point, bottomRight: Point } }> = [];\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[palmLandmarksPalmBase], currentBox.palmLandmarks[palmLandmarksMiddleFingerBase]) : 0;\n        const palmCenter = util.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation && env.kernels.includes('rotatewithoffset') ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = util.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = tf.div(croppedInput, constants.tf255);\n        tf.dispose(croppedInput);\n        tf.dispose(rotatedImage);\n        const [confidenceT, keypoints] = this.handPoseModel.execute(handImage) as Array<Tensor>;\n        lastTime = now();\n        tf.dispose(handImage);\n        const confidence = (await confidenceT.data())[0];\n        tf.dispose(confidenceT);\n        if (confidence >= config.hand.minConfidence / 4) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = await keypointsReshaped.array();\n          tf.dispose(keypoints);\n          tf.dispose(keypointsReshaped);\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = { ...nextBoundingBox, confidence };\n          const result = {\n            landmarks: coords,\n            confidence,\n            boxConfidence: currentBox.confidence,\n            fingerConfidence: confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        tf.dispose(keypoints);\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), handBoxEnlargeFactor);\n        const enlarged = util.enlargeBox(util.squarifyBox(currentBox), handBoxEnlargeFactor);\n        const result = {\n          confidence: currentBox.confidence,\n          boxConfidence: currentBox.confidence,\n          fingerConfidence: 0,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n          landmarks: [],\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    if (hands.length > config.hand.maxDetected) hands.length = config.hand.maxDetected;\n    return hands;\n  }\n}\n", "/**\n * FingerPose algorithm implementation\n * See `fingerpose.ts` for entry point\n */\n\nexport const Finger = {\n  thumb: 0,\n  index: 1,\n  middle: 2,\n  ring: 3,\n  pinky: 4,\n  all: [0, 1, 2, 3, 4], // just for convenience\n  nameMapping: { 0: 'thumb', 1: 'index', 2: 'middle', 3: 'ring', 4: 'pinky' },\n  // Describes mapping of joints based on the 21 points returned by handpose.\n  // [0]     Palm\n  // [1-4]   Thumb\n  // [5-8]   Index\n  // [9-12]  Middle\n  // [13-16] Ring\n  // [17-20] Pinky\n  pointsMapping: {\n    0: [[0, 1], [1, 2], [2, 3], [3, 4]],\n    1: [[0, 5], [5, 6], [6, 7], [7, 8]],\n    2: [[0, 9], [9, 10], [10, 11], [11, 12]],\n    3: [[0, 13], [13, 14], [14, 15], [15, 16]],\n    4: [[0, 17], [17, 18], [18, 19], [19, 20]],\n  },\n  getName: (value) => Finger.nameMapping[value],\n  getPoints: (value) => Finger.pointsMapping[value],\n};\n\nexport const FingerCurl = {\n  none: 0,\n  half: 1,\n  full: 2,\n  nameMapping: { 0: 'none', 1: 'half', 2: 'full' },\n  getName: (value) => FingerCurl.nameMapping[value],\n};\n\nexport const FingerDirection = {\n  verticalUp: 0,\n  verticalDown: 1,\n  horizontalLeft: 2,\n  horizontalRight: 3,\n  diagonalUpRight: 4,\n  diagonalUpLeft: 5,\n  diagonalDownRight: 6,\n  diagonalDownLeft: 7,\n  nameMapping: { 0: 'verticalUp', 1: 'verticalDown', 2: 'horizontalLeft', 3: 'horizontalRight', 4: 'diagonalUpRight', 5: 'diagonalUpLeft', 6: 'diagonalDownRight', 7: 'diagonalDownLeft' },\n  getName: (value) => FingerDirection.nameMapping[value],\n};\n\nexport class FingerGesture {\n  name;\n  curls;\n  directions;\n  weights;\n  weightsRelative;\n\n  constructor(name) {\n    // name (should be unique)\n    this.name = name;\n    this.curls = {};\n    this.directions = {};\n    this.weights = [1.0, 1.0, 1.0, 1.0, 1.0];\n    this.weightsRelative = [1.0, 1.0, 1.0, 1.0, 1.0];\n  }\n\n  curl(finger, curl, confidence) {\n    if (typeof this.curls[finger] === 'undefined') this.curls[finger] = [];\n    this.curls[finger].push([curl, confidence]);\n  }\n\n  direction(finger, position, confidence) {\n    if (!this.directions[finger]) this.directions[finger] = [];\n    this.directions[finger].push([position, confidence]);\n  }\n\n  weight(finger, weight) {\n    this.weights[finger] = weight;\n    // recalculate relative weights\n    const total = this.weights.reduce((a, b) => a + b, 0);\n    this.weightsRelative = this.weights.map((el) => el * 5 / total);\n  }\n\n  matchAgainst(detectedCurls, detectedDirections) {\n    let confidence = 0.0;\n    // look at the detected curl of each finger and compare with\n    // the expected curl of this finger inside current gesture\n    for (const fingerIdx in detectedCurls) {\n      const detectedCurl = detectedCurls[fingerIdx];\n      const expectedCurls = this.curls[fingerIdx];\n      if (typeof expectedCurls === 'undefined') {\n        // no curl description available for this finger\n        // add default confidence of \"1\"\n        confidence += this.weightsRelative[fingerIdx];\n        continue;\n      }\n      // compare to each possible curl of this specific finger\n      for (const [expectedCurl, score] of expectedCurls) {\n        if (detectedCurl === expectedCurl) {\n          confidence += score * this.weightsRelative[fingerIdx];\n          break;\n        }\n      }\n    }\n    // same for detected direction of each finger\n    for (const fingerIdx in detectedDirections) {\n      const detectedDirection = detectedDirections[fingerIdx];\n      const expectedDirections = this.directions[fingerIdx];\n      if (typeof expectedDirections === 'undefined') {\n        // no direction description available for this finger\n        // add default confidence of \"1\"\n        confidence += this.weightsRelative[fingerIdx];\n        continue;\n      }\n      // compare to each possible direction of this specific finger\n      for (const [expectedDirection, score] of expectedDirections) {\n        if (detectedDirection === expectedDirection) {\n          confidence += score * this.weightsRelative[fingerIdx];\n          break;\n        }\n      }\n    }\n    return confidence / 10;\n  }\n}\n", "/**\n * FingerPose algorithm implementation\n * See `fingerpose.ts` for entry point\n */\n\nimport { Finger, FingerCurl, FingerDirection, FingerGesture } from './fingerdef';\n\n// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\nexport const { thumb, index, middle, ring, pinky } = Finger;\n// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\nexport const { none, half, full } = FingerCurl;\n// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\nexport const { verticalUp, verticalDown, horizontalLeft, horizontalRight, diagonalUpRight, diagonalUpLeft, diagonalDownRight, diagonalDownLeft } = FingerDirection;\n\n// describe thumbs up gesture \uD83D\uDC4D\nconst ThumbsUp = new FingerGesture('thumbs up');\nThumbsUp.curl(thumb, none, 1.0);\nThumbsUp.direction(thumb, verticalUp, 1.0);\nThumbsUp.direction(thumb, diagonalUpLeft, 0.25);\nThumbsUp.direction(thumb, diagonalUpRight, 0.25);\nfor (const finger of [Finger.index, Finger.middle, Finger.ring, Finger.pinky]) {\n  ThumbsUp.curl(finger, full, 1.0);\n  ThumbsUp.direction(finger, horizontalLeft, 1.0);\n  ThumbsUp.direction(finger, horizontalRight, 1.0);\n}\n\n// describe Victory gesture \u270C\uFE0F\nconst Victory = new FingerGesture('victory');\nVictory.curl(thumb, half, 0.5);\nVictory.curl(thumb, none, 0.5);\nVictory.direction(thumb, verticalUp, 1.0);\nVictory.direction(thumb, diagonalUpLeft, 1.0);\nVictory.curl(index, none, 1.0);\nVictory.direction(index, verticalUp, 0.75);\nVictory.direction(index, diagonalUpLeft, 1.0);\nVictory.curl(middle, none, 1.0);\nVictory.direction(middle, verticalUp, 1.0);\nVictory.direction(middle, diagonalUpLeft, 0.75);\nVictory.curl(ring, full, 1.0);\nVictory.direction(ring, verticalUp, 0.2);\nVictory.direction(ring, diagonalUpLeft, 1.0);\nVictory.direction(ring, horizontalLeft, 0.2);\nVictory.curl(pinky, full, 1.0);\nVictory.direction(pinky, verticalUp, 0.2);\nVictory.direction(pinky, diagonalUpLeft, 1.0);\nVictory.direction(pinky, horizontalLeft, 0.2);\nVictory.weight(index, 2);\nVictory.weight(middle, 2);\n\n// describe Point gesture \u270C\uFE0F\nconst Point = new FingerGesture('point');\nPoint.curl(thumb, full, 1.0);\nPoint.curl(index, none, 0.5);\nPoint.curl(middle, full, 0.5);\nPoint.curl(ring, full, 0.5);\nPoint.curl(pinky, full, 0.5);\nPoint.weight(index, 2);\nPoint.weight(middle, 2);\n\n// describe Point gesture \u270C\uFE0F\nconst MiddleFinger = new FingerGesture('middle finger');\nMiddleFinger.curl(thumb, none, 1.0);\nMiddleFinger.curl(index, full, 0.5);\nMiddleFinger.curl(middle, full, 0.5);\nMiddleFinger.curl(ring, full, 0.5);\nMiddleFinger.curl(pinky, full, 0.5);\nMiddleFinger.weight(index, 2);\nMiddleFinger.weight(middle, 2);\n\n// describe Open Palm gesture \u270C\uFE0F\nconst OpenPalm = new FingerGesture('open palm');\nOpenPalm.curl(thumb, none, 0.75);\nOpenPalm.curl(index, none, 0.75);\nOpenPalm.curl(middle, none, 0.75);\nOpenPalm.curl(ring, none, 0.75);\nOpenPalm.curl(pinky, none, 0.75);\n\nexport default [ThumbsUp, Victory, Point, MiddleFinger, OpenPalm];\n", "/**\n * FingerPose algorithm implementation constants\n *\n * Based on: [**FingerPose***](https://github.com/andypotato/fingerpose)\n */\n\nimport { Finger, FingerCurl, FingerDirection } from './fingerdef';\nimport Gestures from '../hand/fingergesture';\n\nconst minConfidence = 0.7;\nconst options = {\n  // curl estimation\n  HALF_CURL_START_LIMIT: 60.0,\n  NO_CURL_START_LIMIT: 130.0,\n  // direction estimation\n  DISTANCE_VOTE_POWER: 1.1,\n  SINGLE_ANGLE_VOTE_POWER: 0.9,\n  TOTAL_ANGLE_VOTE_POWER: 1.6,\n};\n\nfunction calculateSlope(point1x, point1y, point2x, point2y) {\n  const value = (point1y - point2y) / (point1x - point2x);\n  let slope = Math.atan(value) * 180 / Math.PI;\n  if (slope <= 0) slope = -slope;\n  else if (slope > 0) slope = 180 - slope;\n  return slope;\n}\n\n// point1, point2 are 2d or 3d point arrays (xy[z])\n// returns either a single scalar (2d) or array of two slopes (3d)\nfunction getSlopes(point1, point2) {\n  if (!point1 || !point2) return [0, 0];\n  const slopeXY = calculateSlope(point1[0], point1[1], point2[0], point2[1]);\n  if (point1.length === 2) return slopeXY;\n  const slopeYZ = calculateSlope(point1[1], point1[2], point2[1], point2[2]);\n  return [slopeXY, slopeYZ];\n}\n\nfunction angleOrientationAt(angle, weightageAt = 1.0) {\n  let isVertical = 0;\n  let isDiagonal = 0;\n  let isHorizontal = 0;\n  if (angle >= 75.0 && angle <= 105.0) isVertical = 1 * weightageAt;\n  else if (angle >= 25.0 && angle <= 155.0) isDiagonal = 1 * weightageAt;\n  else isHorizontal = 1 * weightageAt;\n  return [isVertical, isDiagonal, isHorizontal];\n}\n\nfunction estimateFingerCurl(startPoint, midPoint, endPoint) {\n  const start_mid_x_dist = startPoint[0] - midPoint[0];\n  const start_end_x_dist = startPoint[0] - endPoint[0];\n  const mid_end_x_dist = midPoint[0] - endPoint[0];\n  const start_mid_y_dist = startPoint[1] - midPoint[1];\n  const start_end_y_dist = startPoint[1] - endPoint[1];\n  const mid_end_y_dist = midPoint[1] - endPoint[1];\n  const start_mid_z_dist = startPoint[2] - midPoint[2];\n  const start_end_z_dist = startPoint[2] - endPoint[2];\n  const mid_end_z_dist = midPoint[2] - endPoint[2];\n  const start_mid_dist = Math.sqrt(start_mid_x_dist * start_mid_x_dist + start_mid_y_dist * start_mid_y_dist + start_mid_z_dist * start_mid_z_dist);\n  const start_end_dist = Math.sqrt(start_end_x_dist * start_end_x_dist + start_end_y_dist * start_end_y_dist + start_end_z_dist * start_end_z_dist);\n  const mid_end_dist = Math.sqrt(mid_end_x_dist * mid_end_x_dist + mid_end_y_dist * mid_end_y_dist + mid_end_z_dist * mid_end_z_dist);\n  let cos_in = (mid_end_dist * mid_end_dist + start_mid_dist * start_mid_dist - start_end_dist * start_end_dist) / (2 * mid_end_dist * start_mid_dist);\n  if (cos_in > 1.0) cos_in = 1.0;\n  else if (cos_in < -1.0) cos_in = -1.0;\n  let angleOfCurve = Math.acos(cos_in);\n  angleOfCurve = (57.2958 * angleOfCurve) % 180;\n  let fingerCurl;\n  if (angleOfCurve > options.NO_CURL_START_LIMIT) fingerCurl = FingerCurl.none;\n  else if (angleOfCurve > options.HALF_CURL_START_LIMIT) fingerCurl = FingerCurl.half;\n  else fingerCurl = FingerCurl.full;\n  return fingerCurl;\n}\n\nfunction estimateHorizontalDirection(start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x) {\n  let estimatedDirection;\n  if (max_dist_x === Math.abs(start_end_x_dist)) {\n    if (start_end_x_dist > 0) estimatedDirection = FingerDirection.horizontalLeft;\n    else estimatedDirection = FingerDirection.horizontalRight;\n  } else if (max_dist_x === Math.abs(start_mid_x_dist)) {\n    if (start_mid_x_dist > 0) estimatedDirection = FingerDirection.horizontalLeft;\n    else estimatedDirection = FingerDirection.horizontalRight;\n  } else {\n    if (mid_end_x_dist > 0) estimatedDirection = FingerDirection.horizontalLeft;\n    else estimatedDirection = FingerDirection.horizontalRight;\n  }\n  return estimatedDirection;\n}\n\nfunction estimateVerticalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y) {\n  let estimatedDirection;\n  if (max_dist_y === Math.abs(start_end_y_dist)) {\n    if (start_end_y_dist < 0) estimatedDirection = FingerDirection.verticalDown;\n    else estimatedDirection = FingerDirection.verticalUp;\n  } else if (max_dist_y === Math.abs(start_mid_y_dist)) {\n    if (start_mid_y_dist < 0) estimatedDirection = FingerDirection.verticalDown;\n    else estimatedDirection = FingerDirection.verticalUp;\n  } else {\n    if (mid_end_y_dist < 0) estimatedDirection = FingerDirection.verticalDown;\n    else estimatedDirection = FingerDirection.verticalUp;\n  }\n  return estimatedDirection;\n}\n\nfunction estimateDiagonalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y, start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x) {\n  let estimatedDirection;\n  const reqd_vertical_direction = estimateVerticalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y);\n  const reqd_horizontal_direction = estimateHorizontalDirection(start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x);\n  if (reqd_vertical_direction === FingerDirection.verticalUp) {\n    if (reqd_horizontal_direction === FingerDirection.horizontalLeft) estimatedDirection = FingerDirection.diagonalUpLeft;\n    else estimatedDirection = FingerDirection.diagonalUpRight;\n  } else {\n    if (reqd_horizontal_direction === FingerDirection.horizontalLeft) estimatedDirection = FingerDirection.diagonalDownLeft;\n    else estimatedDirection = FingerDirection.diagonalDownRight;\n  }\n  return estimatedDirection;\n}\n\nfunction calculateFingerDirection(startPoint, midPoint, endPoint, fingerSlopes) {\n  const start_mid_x_dist = startPoint[0] - midPoint[0];\n  const start_end_x_dist = startPoint[0] - endPoint[0];\n  const mid_end_x_dist = midPoint[0] - endPoint[0];\n  const start_mid_y_dist = startPoint[1] - midPoint[1];\n  const start_end_y_dist = startPoint[1] - endPoint[1];\n  const mid_end_y_dist = midPoint[1] - endPoint[1];\n  const max_dist_x = Math.max(Math.abs(start_mid_x_dist), Math.abs(start_end_x_dist), Math.abs(mid_end_x_dist));\n  const max_dist_y = Math.max(Math.abs(start_mid_y_dist), Math.abs(start_end_y_dist), Math.abs(mid_end_y_dist));\n  let voteVertical = 0.0;\n  let voteDiagonal = 0.0;\n  let voteHorizontal = 0.0;\n  const start_end_x_y_dist_ratio = max_dist_y / (max_dist_x + 0.00001);\n  if (start_end_x_y_dist_ratio > 1.5) voteVertical += options.DISTANCE_VOTE_POWER;\n  else if (start_end_x_y_dist_ratio > 0.66) voteDiagonal += options.DISTANCE_VOTE_POWER;\n  else voteHorizontal += options.DISTANCE_VOTE_POWER;\n  const start_mid_dist = Math.sqrt(start_mid_x_dist * start_mid_x_dist + start_mid_y_dist * start_mid_y_dist);\n  const start_end_dist = Math.sqrt(start_end_x_dist * start_end_x_dist + start_end_y_dist * start_end_y_dist);\n  const mid_end_dist = Math.sqrt(mid_end_x_dist * mid_end_x_dist + mid_end_y_dist * mid_end_y_dist);\n  const max_dist = Math.max(start_mid_dist, start_end_dist, mid_end_dist);\n  let calc_start_point_x = startPoint[0];\n  let calc_start_point_y = startPoint[1];\n  let calc_end_point_x = endPoint[0];\n  let calc_end_point_y = endPoint[1];\n  if (max_dist === start_mid_dist) {\n    calc_end_point_x = endPoint[0];\n    calc_end_point_y = endPoint[1];\n  } else if (max_dist === mid_end_dist) {\n    calc_start_point_x = midPoint[0];\n    calc_start_point_y = midPoint[1];\n  }\n  const calcStartPoint = [calc_start_point_x, calc_start_point_y];\n  const calcEndPoint = [calc_end_point_x, calc_end_point_y];\n  const totalAngle = getSlopes(calcStartPoint, calcEndPoint);\n  const votes = angleOrientationAt(totalAngle, options.TOTAL_ANGLE_VOTE_POWER);\n  voteVertical += votes[0];\n  voteDiagonal += votes[1];\n  voteHorizontal += votes[2];\n  for (const fingerSlope of fingerSlopes) {\n    const fingerVotes = angleOrientationAt(fingerSlope, options.SINGLE_ANGLE_VOTE_POWER);\n    voteVertical += fingerVotes[0];\n    voteDiagonal += fingerVotes[1];\n    voteHorizontal += fingerVotes[2];\n  }\n  // in case of tie, highest preference goes to Vertical,\n  // followed by horizontal and then diagonal\n  let estimatedDirection;\n  if (voteVertical === Math.max(voteVertical, voteDiagonal, voteHorizontal)) {\n    estimatedDirection = estimateVerticalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y);\n  } else if (voteHorizontal === Math.max(voteDiagonal, voteHorizontal)) {\n    estimatedDirection = estimateHorizontalDirection(start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x);\n  } else {\n    estimatedDirection = estimateDiagonalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y, start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x);\n  }\n  return estimatedDirection;\n}\n\nfunction estimate(landmarks) {\n  // step 1: calculate slopes\n  const slopesXY: Array<number[]> = [];\n  const slopesYZ: Array<number[]> = [];\n  const fingerCurls: Array<number> = [];\n  const fingerDirections: Array<number> = [];\n  if (!landmarks) return { curls: fingerCurls, directions: fingerDirections };\n\n  // step 1: calculate slopes\n  for (const finger of Finger.all) {\n    const points = Finger.getPoints(finger);\n    const slopeAtXY: Array<number> = [];\n    const slopeAtYZ: Array<number> = [];\n    for (const point of points) {\n      const point1 = landmarks[point[0]];\n      const point2 = landmarks[point[1]];\n      // calculate single slope\n      const slopes = getSlopes(point1, point2);\n      const slopeXY = slopes[0];\n      const slopeYZ = slopes[1];\n      slopeAtXY.push(slopeXY);\n      slopeAtYZ.push(slopeYZ);\n    }\n    slopesXY.push(slopeAtXY);\n    slopesYZ.push(slopeAtYZ);\n  }\n\n  // step 2: calculate orientations\n  for (const finger of Finger.all) {\n    // start finger predictions from palm - except for thumb\n    const pointIndexAt = (finger === Finger.thumb) ? 1 : 0;\n    const fingerPointsAt = Finger.getPoints(finger);\n    const startPoint = landmarks[fingerPointsAt[pointIndexAt][0]];\n    const midPoint = landmarks[fingerPointsAt[pointIndexAt + 1][1]];\n    const endPoint = landmarks[fingerPointsAt[3][1]];\n    // check if finger is curled\n    const fingerCurled = estimateFingerCurl(startPoint, midPoint, endPoint);\n    const fingerPosition = calculateFingerDirection(startPoint, midPoint, endPoint, slopesXY[finger].slice(pointIndexAt));\n    fingerCurls[finger] = fingerCurled;\n    fingerDirections[finger] = fingerPosition;\n  }\n  return { curls: fingerCurls, directions: fingerDirections };\n}\n\nexport function analyze(keypoints) { // get estimations of curl / direction for each finger\n  if (!keypoints || keypoints.length === 0) return null;\n  const estimatorRes = estimate(keypoints);\n  const landmarks = {};\n  for (const fingerIdx of Finger.all) {\n    landmarks[Finger.getName(fingerIdx)] = {\n      curl: FingerCurl.getName(estimatorRes.curls[fingerIdx]),\n      direction: FingerDirection.getName(estimatorRes.directions[fingerIdx]),\n    };\n  }\n  return landmarks;\n}\n\nexport function match(keypoints) { // compare gesture description to each known gesture\n  const poses: Array<{ name: string, confidence: number }> = [];\n  if (!keypoints || keypoints.length === 0) return poses;\n  const estimatorRes = estimate(keypoints);\n  for (const gesture of Gestures) {\n    const confidence = gesture.matchAgainst(estimatorRes.curls, estimatorRes.directions);\n    if (confidence >= minConfidence) poses.push({ name: gesture.name, confidence });\n  }\n  return poses;\n}\n", "/**\n * HandPose model implementation\n *\n * Based on: [**MediaPipe HandPose**](https://drive.google.com/file/d/1sv4sSb9BSNVZhLzxXJ0jBv9DqD-4jnAz/view)\n */\n\nimport { log } from '../util/util';\nimport * as handdetector from './handposedetector';\nimport * as handpipeline from './handposepipeline';\nimport * as fingerPose from './fingerpose';\nimport { loadModel } from '../tfjs/load';\nimport type { HandResult, Box, Point } from '../result';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nconst meshAnnotations = {\n  thumb: [1, 2, 3, 4],\n  index: [5, 6, 7, 8],\n  middle: [9, 10, 11, 12],\n  ring: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palm: [0],\n};\n\nlet handDetectorModel: GraphModel | null;\nlet handPoseModel: GraphModel | null;\nlet handPipeline: handpipeline.HandPipeline;\n\nexport async function predict(input: Tensor, config: Config): Promise<HandResult[]> {\n  const predictions = await handPipeline.estimateHands(input, config);\n  if (!predictions) return [];\n  const hands: Array<HandResult> = [];\n  for (let i = 0; i < predictions.length; i++) {\n    const annotations = {};\n    if (predictions[i].landmarks) {\n      for (const key of Object.keys(meshAnnotations)) {\n        annotations[key] = meshAnnotations[key].map((index) => predictions[i].landmarks[index]);\n      }\n    }\n    const keypoints = predictions[i].landmarks as unknown as Array<Point>;\n    let box: Box = [Number.MAX_SAFE_INTEGER, Number.MAX_SAFE_INTEGER, 0, 0]; // maximums so conditionals work\n    let boxRaw: Box = [0, 0, 0, 0];\n    if (keypoints && keypoints.length > 0) { // if we have landmarks, calculate box based on landmarks\n      for (const pt of keypoints) {\n        if (pt[0] < box[0]) box[0] = pt[0];\n        if (pt[1] < box[1]) box[1] = pt[1];\n        if (pt[0] > box[2]) box[2] = pt[0];\n        if (pt[1] > box[3]) box[3] = pt[1];\n      }\n      box[2] -= box[0];\n      box[3] -= box[1];\n      boxRaw = [box[0] / (input.shape[2] || 0), box[1] / (input.shape[1] || 0), box[2] / (input.shape[2] || 0), box[3] / (input.shape[1] || 0)];\n    } else { // otherwise use box from prediction\n      box = predictions[i].box ? [\n        Math.trunc(Math.max(0, predictions[i].box.topLeft[0])),\n        Math.trunc(Math.max(0, predictions[i].box.topLeft[1])),\n        Math.trunc(Math.min((input.shape[2] || 0), predictions[i].box.bottomRight[0]) - Math.max(0, predictions[i].box.topLeft[0])),\n        Math.trunc(Math.min((input.shape[1] || 0), predictions[i].box.bottomRight[1]) - Math.max(0, predictions[i].box.topLeft[1])),\n      ] : [0, 0, 0, 0];\n      boxRaw = [\n        (predictions[i].box.topLeft[0]) / (input.shape[2] || 0),\n        (predictions[i].box.topLeft[1]) / (input.shape[1] || 0),\n        (predictions[i].box.bottomRight[0] - predictions[i].box.topLeft[0]) / (input.shape[2] || 0),\n        (predictions[i].box.bottomRight[1] - predictions[i].box.topLeft[1]) / (input.shape[1] || 0),\n      ];\n    }\n    const landmarks = fingerPose.analyze(keypoints);\n    hands.push({\n      id: i,\n      score: Math.round(100 * predictions[i].confidence) / 100,\n      boxScore: Math.round(100 * predictions[i].boxConfidence) / 100,\n      fingerScore: Math.round(100 * predictions[i].fingerConfidence) / 100,\n      label: 'hand',\n      box,\n      boxRaw,\n      keypoints,\n      annotations: annotations as HandResult['annotations'],\n      landmarks: landmarks as HandResult['landmarks'],\n    });\n  }\n  return hands;\n}\n\nexport async function load(config: Config): Promise<[GraphModel | null, GraphModel | null]> {\n  if (env.initial) {\n    handDetectorModel = null;\n    handPoseModel = null;\n  }\n  if (!handDetectorModel || !handPoseModel) {\n    [handDetectorModel, handPoseModel] = await Promise.all([\n      config.hand.enabled ? loadModel(config.hand.detector?.modelPath) : null,\n      config.hand.landmarks ? loadModel(config.hand.skeleton?.modelPath) : null,\n    ]);\n  } else {\n    if (config.debug) log('cached model:', handDetectorModel['modelUrl']);\n    if (config.debug) log('cached model:', handPoseModel['modelUrl']);\n  }\n  const handDetector = new handdetector.HandDetector(handDetectorModel);\n  handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel);\n  return [handDetectorModel, handPoseModel];\n}\n", "/**\n * HandTrack model implementation\n *\n * Based on:\n * - Hand Detection & Skeleton: [**MediaPipe HandPose**](https://drive.google.com/file/d/1sv4sSb9BSNVZhLzxXJ0jBv9DqD-4jnAz/view)\n * - Hand Tracking: [**HandTracking**](https://github.com/victordibia/handtracking)\n */\n\nimport { log, now } from '../util/util';\nimport * as box from '../util/box';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { HandResult, HandType, Box, Point } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\nimport * as fingerPose from './fingerpose';\nimport { fakeOps } from '../tfjs/backend';\nimport { constants } from '../tfjs/constants';\n\nconst models: [GraphModel | null, GraphModel | null] = [null, null];\nconst modelOutputNodes = ['StatefulPartitionedCall/Postprocessor/Slice', 'StatefulPartitionedCall/Postprocessor/ExpandDims_1'];\n\nconst inputSize = [[0, 0], [0, 0]];\n\nconst classes = ['hand', 'fist', 'pinch', 'point', 'face', 'tip', 'pinchtip'];\nconst faceIndex = 4;\n\nconst boxExpandFact = 1.6;\nconst maxDetectorResolution = 512;\nconst detectorExpandFact = 1.4;\n\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet lastTime = 0;\nlet outputSize: [number, number] = [0, 0];\n\ntype HandDetectResult = {\n  id: number,\n  score: number,\n  box: Box,\n  boxRaw: Box,\n  label: HandType,\n}\n\nconst cache: {\n  boxes: Array<HandDetectResult>,\n  hands: Array<HandResult>;\n} = {\n  boxes: [],\n  hands: [],\n};\n\nconst fingerMap = {\n  /*\n  thumb: [0, 1, 2, 3, 4],\n  index: [0, 5, 6, 7, 8],\n  middle: [0, 9, 10, 11, 12],\n  ring: [0, 13, 14, 15, 16],\n  pinky: [0, 17, 18, 19, 20],\n  palm: [0],\n  */\n  thumb: [1, 2, 3, 4],\n  index: [5, 6, 7, 8],\n  middle: [9, 10, 11, 12],\n  ring: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  base: [0],\n  palm: [0, 17, 13, 9, 5, 1, 0],\n};\n\nexport async function loadDetect(config: Config): Promise<GraphModel> {\n  // HandTrack Model: Original: <https://github.com/victordibia/handtracking> TFJS Port: <https://github.com/victordibia/handtrack.js/>\n  if (env.initial) models[0] = null;\n  if (!models[0]) {\n    // handtrack model has some kernel ops defined in model but those are never referenced and non-existent in tfjs\n    // ideally need to prune the model itself\n    fakeOps(['tensorlistreserve', 'enter', 'tensorlistfromtensor', 'merge', 'loopcond', 'switch', 'exit', 'tensorliststack', 'nextiteration', 'tensorlistsetitem', 'tensorlistgetitem', 'reciprocal', 'shape', 'split', 'where'], config);\n    models[0] = await loadModel(config.hand.detector?.modelPath);\n    const inputs = Object.values(models[0].modelSignature['inputs']);\n    inputSize[0][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize[0][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', models[0]['modelUrl']);\n  return models[0];\n}\n\nexport async function loadSkeleton(config: Config): Promise<GraphModel> {\n  if (env.initial) models[1] = null;\n  if (!models[1]) {\n    models[1] = await loadModel(config.hand.skeleton?.modelPath);\n    const inputs = Object.values(models[1].modelSignature['inputs']);\n    inputSize[1][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize[1][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', models[1]['modelUrl']);\n  return models[1];\n}\n\nexport async function load(config: Config): Promise<[GraphModel | null, GraphModel | null]> {\n  if (!models[0]) await loadDetect(config);\n  if (!models[1]) await loadSkeleton(config);\n  return models;\n}\n\nasync function detectHands(input: Tensor, config: Config): Promise<HandDetectResult[]> {\n  const hands: HandDetectResult[] = [];\n  if (!input || !models[0]) return hands;\n  const t: Record<string, Tensor> = {};\n  const ratio = (input.shape[2] || 1) / (input.shape[1] || 1);\n  const height = Math.min(Math.round((input.shape[1] || 0) / 8) * 8, maxDetectorResolution); // use dynamic input size but cap at 512\n  const width = Math.round(height * ratio / 8) * 8;\n  t.resize = tf.image.resizeBilinear(input, [height, width]); // todo: resize with padding\n  t.cast = tf.cast(t.resize, 'int32');\n  [t.rawScores, t.rawBoxes] = await models[0].executeAsync(t.cast, modelOutputNodes) as Tensor[];\n  t.boxes = tf.squeeze(t.rawBoxes, [0, 2]);\n  t.scores = tf.squeeze(t.rawScores, [0]);\n  const classScores: Array<Tensor> = tf.unstack(t.scores, 1); // unstack scores based on classes\n  tf.dispose(classScores[faceIndex]);\n  classScores.splice(faceIndex, 1); // remove faces\n  t.filtered = tf.stack(classScores, 1); // restack\n  tf.dispose(classScores);\n  // t.filtered = t.scores;\n  t.max = tf.max(t.filtered, 1); // max overall score\n  t.argmax = tf.argMax(t.filtered, 1); // class index of max overall score\n  let id = 0;\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.max, (config.hand.maxDetected || 0) + 1, config.hand.iouThreshold || 0, config.hand.minConfidence || 1);\n  const nms = await t.nms.data();\n  const scores = await t.max.data();\n  const classNum = await t.argmax.data();\n  for (const nmsIndex of Array.from(nms)) { // generates results for each class\n    const boxSlice = tf.slice(t.boxes, nmsIndex, 1);\n    const boxYX = await boxSlice.data();\n    tf.dispose(boxSlice);\n    const boxData: Box = [boxYX[1], boxYX[0], boxYX[3] - boxYX[1], boxYX[2] - boxYX[0]]; // yx box reshaped to standard box\n    const boxRaw: Box = box.scale(boxData, detectorExpandFact);\n    const boxFull: Box = [Math.trunc(boxData[0] * outputSize[0]), Math.trunc(boxData[1] * outputSize[1]), Math.trunc(boxData[2] * outputSize[0]), Math.trunc(boxData[3] * outputSize[1])];\n    const score = scores[nmsIndex];\n    const label = classes[classNum[nmsIndex]] as HandType;\n    const hand: HandDetectResult = { id: id++, score, box: boxFull, boxRaw, label };\n    hands.push(hand);\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  hands.sort((a, b) => b.score - a.score);\n  if (hands.length > (config.hand.maxDetected || 1)) hands.length = (config.hand.maxDetected || 1);\n  return hands;\n}\n\nasync function detectFingers(input: Tensor, h: HandDetectResult, config: Config): Promise<HandResult> {\n  const hand: HandResult = { // initial values inherited from hand detect\n    id: h.id,\n    score: Math.round(100 * h.score) / 100,\n    boxScore: Math.round(100 * h.score) / 100,\n    fingerScore: 0,\n    box: h.box,\n    boxRaw: h.boxRaw,\n    label: h.label,\n    keypoints: [],\n    landmarks: {} as HandResult['landmarks'],\n    annotations: {} as HandResult['annotations'],\n  };\n  if (input && models[1] && config.hand.landmarks && h.score > (config.hand.minConfidence || 0)) {\n    const t: Record<string, Tensor> = {};\n    const boxCrop = [h.boxRaw[1], h.boxRaw[0], h.boxRaw[3] + h.boxRaw[1], h.boxRaw[2] + h.boxRaw[0]] as Box;\n    t.crop = tf.image.cropAndResize(input, [boxCrop], [0], [inputSize[1][0], inputSize[1][1]], 'bilinear');\n    t.div = tf.div(t.crop, constants.tf255);\n    [t.score, t.keypoints] = models[1].execute(t.div, ['Identity_1', 'Identity']) as Tensor[];\n    const rawScore = (await t.score.data())[0];\n    const score = (100 - Math.trunc(100 / (1 + Math.exp(rawScore)))) / 100; // reverse sigmoid value\n    if (score >= (config.hand.minConfidence || 0)) {\n      hand.fingerScore = score;\n      t.reshaped = tf.reshape(t.keypoints, [-1, 3]);\n      const coordsData: Point[] = await t.reshaped.array() as Point[];\n      const coordsRaw: Point[] = coordsData.map((kpt) => [kpt[0] / inputSize[1][1], kpt[1] / inputSize[1][0], (kpt[2] || 0)]);\n      const coordsNorm: Point[] = coordsRaw.map((kpt) => [kpt[0] * h.boxRaw[2], kpt[1] * h.boxRaw[3], (kpt[2] || 0)]);\n      hand.keypoints = (coordsNorm).map((kpt) => [outputSize[0] * (kpt[0] + h.boxRaw[0]), outputSize[1] * (kpt[1] + h.boxRaw[1]), (kpt[2] || 0)]);\n      hand.landmarks = fingerPose.analyze(hand.keypoints) as HandResult['landmarks']; // calculate finger gestures\n      for (const key of Object.keys(fingerMap)) { // map keypoints to per-finger annotations\n        hand.annotations[key] = fingerMap[key].map((index: number) => (hand.landmarks && hand.keypoints[index] ? hand.keypoints[index] : null));\n      }\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  }\n  return hand;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<HandResult[]> {\n  if (!models[0] || !models[1] || !models[0]?.inputs[0].shape || !models[1]?.inputs[0].shape) return []; // something is wrong with the model\n  outputSize = [input.shape[2] || 0, input.shape[1] || 0];\n  skipped++; // increment skip frames\n  const skipTime = (config.hand.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.hand.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame) {\n    return cache.hands; // return cached results without running anything\n  }\n  return new Promise(async (resolve) => {\n    const skipTimeExtended = 3 * (config.hand.skipTime || 0) > (now() - lastTime);\n    const skipFrameExtended = skipped < 3 * (config.hand.skipFrames || 0);\n    if (config.skipAllowed && cache.hands.length === config.hand.maxDetected) { // we have all detected hands so we're definitely skipping\n      cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));\n    } else if (config.skipAllowed && skipTimeExtended && skipFrameExtended && cache.hands.length > 0) { // we have some cached results: maybe not enough but anyhow continue for bit longer\n      cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));\n    } else { // finally rerun detector\n      cache.boxes = await detectHands(input, config);\n      lastTime = now();\n      cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));\n      skipped = 0;\n    }\n\n    const oldCache = [...cache.boxes];\n    cache.boxes.length = 0; // reset cache\n    if (config.cacheSensitivity > 0) {\n      for (let i = 0; i < cache.hands.length; i++) {\n        const boxKpt = box.square(cache.hands[i].keypoints, outputSize);\n        if (boxKpt.box[2] / (input.shape[2] || 1) > 0.05 && boxKpt.box[3] / (input.shape[1] || 1) > 0.05 && cache.hands[i].fingerScore && cache.hands[i].fingerScore > (config.hand.minConfidence || 0)) {\n          const boxScale = box.scale(boxKpt.box, boxExpandFact);\n          const boxScaleRaw = box.scale(boxKpt.boxRaw, boxExpandFact);\n          // const boxCrop = box.crop(boxScaleRaw);\n          cache.boxes.push({ ...oldCache[i], box: boxScale, boxRaw: boxScaleRaw });\n        }\n      }\n    }\n    for (let i = 0; i < cache.hands.length; i++) { // replace detected boxes with calculated boxes in final output\n      const bbox = box.calc(cache.hands[i].keypoints, outputSize);\n      cache.hands[i].box = bbox.box;\n      cache.hands[i].boxRaw = bbox.boxRaw;\n    }\n    resolve(cache.hands);\n  });\n}\n", "/**\n * Anti-spoofing model implementation\n */\n\nimport { log, now } from '../util/util';\nimport { loadModel } from '../tfjs/load';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst cached: Array<number> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet lastCount = 0;\nlet lastTime = 0;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.liveness?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<number> {\n  if (!model) return 0;\n  const skipTime = (config.face.liveness?.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.face.liveness?.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && cached[idx]) {\n    skipped++;\n    return cached[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape ? model.inputs[0].shape[2] : 0, model?.inputs[0].shape ? model.inputs[0].shape[1] : 0], false);\n    const res = model?.execute(resize) as Tensor;\n    const num = (await res.data())[0];\n    cached[idx] = Math.round(100 * num) / 100;\n    lastCount = count;\n    lastTime = now();\n    tf.dispose([resize, res]);\n    resolve(cached[idx]);\n  });\n}\n", "export const kpt: Array<string> = [ // used to create part labels\n  'nose',\n  'leftEye',\n  'rightEye',\n  'leftEar',\n  'rightEar',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n];\n\nexport const horizontal: Array<string[]> = [ // used to fix left vs right\n  ['leftEye', 'rightEye'],\n  ['leftEar', 'rightEar'],\n  ['leftShoulder', 'rightShoulder'],\n  ['leftElbow', 'rightElbow'],\n  ['leftWrist', 'rightWrist'],\n  ['leftHip', 'rightHip'],\n  ['leftKnee', 'rightKnee'],\n  ['leftAnkle', 'rightAnkle'],\n];\n\nexport const vertical: Array<string[]> = [ // used to remove unlikely keypoint positions\n  ['leftKnee', 'leftShoulder'],\n  ['rightKnee', 'rightShoulder'],\n  ['leftAnkle', 'leftKnee'],\n  ['rightAnkle', 'rightKnee'],\n];\n\nexport const relative: Array<string[][]> = [ // used to match relative body parts\n  [['leftHip', 'rightHip'], ['leftShoulder', 'rightShoulder']],\n  [['leftElbow', 'rightElbow'], ['leftShoulder', 'rightShoulder']],\n];\n\nexport const connected: Record<string, string[]> = { // used to create body outline in annotations\n  leftLeg: ['leftHip', 'leftKnee', 'leftAnkle'],\n  rightLeg: ['rightHip', 'rightKnee', 'rightAnkle'],\n  torso: ['leftShoulder', 'rightShoulder', 'rightHip', 'leftHip', 'leftShoulder'],\n  leftArm: ['leftShoulder', 'leftElbow', 'leftWrist'],\n  rightArm: ['rightShoulder', 'rightElbow', 'rightWrist'],\n  head: [],\n};\n", "import type { BodyKeypoint, BodyResult } from '../result';\nimport * as box from '../util/box';\nimport * as coords from './movenetcoords';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from '../tfjs/types';\n\nconst maxJitter = 0.005; // default allowed jitter is within 0.5%\n\nconst cache: {\n  keypoints: Array<BodyKeypoint>,\n  padding: [number, number][];\n} = {\n  keypoints: [],\n  padding: [[0, 0], [0, 0], [0, 0], [0, 0]],\n};\n\nexport function bodyParts(body: BodyResult) { // model sometimes mixes up left vs right keypoints so we fix them\n  for (const pair of coords.horizontal) { // fix body parts left vs right\n    const left = body.keypoints.findIndex((kp) => kp.part === pair[0]);\n    const right = body.keypoints.findIndex((kp) => kp.part === pair[1]);\n    if (body.keypoints[left] && body.keypoints[right]) {\n      if (body.keypoints[left].position[0] < body.keypoints[right].position[0]) {\n        const tmp = body.keypoints[left];\n        body.keypoints[left] = body.keypoints[right];\n        body.keypoints[right] = tmp;\n      }\n    }\n  }\n  for (const pair of coords.vertical) { // remove body parts with improbable vertical position\n    const lower = body.keypoints.findIndex((kp) => (kp && kp.part === pair[0]));\n    const higher = body.keypoints.findIndex((kp) => (kp && kp.part === pair[1]));\n    if (body.keypoints[lower] && body.keypoints[higher]) {\n      if (body.keypoints[lower].position[1] < body.keypoints[higher].position[1]) {\n        body.keypoints.splice(lower, 1);\n      }\n    }\n  }\n  for (const [pair, compare] of coords.relative) { // rearrange body parts according to their relative position\n    const left = body.keypoints.findIndex((kp) => (kp && kp.part === pair[0]));\n    const right = body.keypoints.findIndex((kp) => (kp && kp.part === pair[1]));\n    const leftTo = body.keypoints.findIndex((kp) => (kp && kp.part === compare[0]));\n    const rightTo = body.keypoints.findIndex((kp) => (kp && kp.part === compare[1]));\n    if (!body.keypoints[leftTo] || !body.keypoints[rightTo]) continue; // only if we have both compare points\n    const distanceLeft = body.keypoints[left] ? [\n      Math.abs(body.keypoints[leftTo].position[0] - body.keypoints[left].position[0]),\n      Math.abs(body.keypoints[rightTo].position[0] - body.keypoints[left].position[0]),\n    ] : [0, 0];\n    const distanceRight = body.keypoints[right] ? [\n      Math.abs(body.keypoints[rightTo].position[0] - body.keypoints[right].position[0]),\n      Math.abs(body.keypoints[leftTo].position[0] - body.keypoints[right].position[0]),\n    ] : [0, 0];\n    if (distanceLeft[0] > distanceLeft[1] || distanceRight[0] > distanceRight[1]) { // should flip keypoints\n      const tmp = body.keypoints[left];\n      body.keypoints[left] = body.keypoints[right];\n      body.keypoints[right] = tmp;\n    }\n  }\n}\n\nexport function jitter(keypoints: Array<BodyKeypoint>): Array<BodyKeypoint> {\n  for (let i = 0; i < keypoints.length; i++) {\n    if (keypoints[i] && cache.keypoints[i]) {\n      const diff = [Math.abs(keypoints[i].positionRaw[0] - cache.keypoints[i].positionRaw[0]), Math.abs(keypoints[i].positionRaw[1] - cache.keypoints[i].positionRaw[1])];\n      if (diff[0] < maxJitter && diff[1] < maxJitter) {\n        keypoints[i] = cache.keypoints[i]; // below jitter so replace keypoint\n      } else {\n        cache.keypoints[i] = keypoints[i]; // above jitter so update cache\n      }\n    } else {\n      cache.keypoints[i] = keypoints[i]; // cache for keypoint doesnt exist so create it here\n    }\n  }\n  return keypoints;\n}\n\nexport function padInput(input: Tensor, inputSize: number): Tensor {\n  const t: Record<string, Tensor> = {};\n  if (!input.shape || !input.shape[1] || !input.shape[2]) return input;\n  cache.padding = [\n    [0, 0], // dont touch batch\n    [input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0, input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0], // height before&after\n    [input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0, input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0], // width before&after\n    [0, 0], // dont touch rbg\n  ];\n  t.pad = tf.pad(input, cache.padding);\n  t.resize = tf.image.resizeBilinear(t.pad, [inputSize, inputSize]);\n  const final = tf.cast(t.resize, 'int32');\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return final;\n}\n\nexport function rescaleBody(body: BodyResult, outputSize: [number, number]): BodyResult {\n  body.keypoints = body.keypoints.filter((kpt) => kpt && kpt.position); // filter invalid keypoints\n  for (const kpt of body.keypoints) {\n    kpt.position = [\n      kpt.position[0] * (outputSize[0] + cache.padding[2][0] + cache.padding[2][1]) / outputSize[0] - cache.padding[2][0],\n      kpt.position[1] * (outputSize[1] + cache.padding[1][0] + cache.padding[1][1]) / outputSize[1] - cache.padding[1][0],\n    ];\n    kpt.positionRaw = [\n      kpt.position[0] / outputSize[0], kpt.position[1] / outputSize[1],\n    ];\n  }\n  const rescaledBoxes = box.calc(body.keypoints.map((pt) => pt.position), outputSize);\n  body.box = rescaledBoxes.box;\n  body.boxRaw = rescaledBoxes.boxRaw;\n  return body;\n}\n", "/**\n * MoveNet model implementation\n *\n * Based on: [**MoveNet**](https://blog.tensorflow.org/2021/05/next-generation-pose-detection-with-movenet-and-tensorflowjs.html)\n */\n\nimport { log, now } from '../util/util';\nimport * as box from '../util/box';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as coords from './movenetcoords';\nimport * as fix from './movenetfix';\nimport { loadModel } from '../tfjs/load';\nimport type { BodyKeypoint, BodyResult, BodyLandmark, BodyAnnotation, Box, Point } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { fakeOps } from '../tfjs/backend';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nlet inputSize = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n// const boxExpandFact = 1.5; // increase to 150%\n\nconst cache: {\n  boxes: Array<Box>, // unused\n  bodies: Array<BodyResult>;\n  last: number,\n} = {\n  boxes: [],\n  bodies: [],\n  last: 0,\n};\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) {\n    fakeOps(['size'], config);\n    model = await loadModel(config.body.modelPath);\n  } else if (config.debug) log('cached model:', model['modelUrl']);\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  if (inputSize < 64) inputSize = 256;\n  return model;\n}\n\nasync function parseSinglePose(res, config, image) {\n  const kpt = res[0][0];\n  const keypoints: Array<BodyKeypoint> = [];\n  let score = 0;\n  for (let id = 0; id < kpt.length; id++) {\n    score = kpt[id][2];\n    if (score > config.body.minConfidence) {\n      const positionRaw: Point = [kpt[id][1], kpt[id][0]];\n      keypoints.push({\n        score: Math.round(100 * score) / 100,\n        part: coords.kpt[id] as BodyLandmark,\n        positionRaw,\n        position: [ // normalized to input image size\n          Math.round((image.shape[2] || 0) * positionRaw[0]),\n          Math.round((image.shape[1] || 0) * positionRaw[1]),\n        ],\n      });\n    }\n  }\n  score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n  const bodies: Array<BodyResult> = [];\n  const newBox = box.calc(keypoints.map((pt) => pt.position), [image.shape[2], image.shape[1]]);\n  const annotations: Record<string, Point[][]> = {};\n  for (const [name, indexes] of Object.entries(coords.connected)) {\n    const pt: Array<Point[]> = [];\n    for (let i = 0; i < indexes.length - 1; i++) {\n      const pt0 = keypoints.find((kp) => kp.part === indexes[i]);\n      const pt1 = keypoints.find((kp) => kp.part === indexes[i + 1]);\n      if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n    }\n    annotations[name] = pt;\n  }\n  const body: BodyResult = { id: 0, score, box: newBox.box, boxRaw: newBox.boxRaw, keypoints, annotations };\n  fix.bodyParts(body);\n  bodies.push(body);\n  return bodies;\n}\n\nasync function parseMultiPose(res, config, image) {\n  const bodies: Array<BodyResult> = [];\n  for (let id = 0; id < res[0].length; id++) {\n    const kpt = res[0][id];\n    const totalScore = Math.round(100 * kpt[51 + 4]) / 100;\n    if (totalScore > config.body.minConfidence) {\n      const keypoints: Array<BodyKeypoint> = [];\n      for (let i = 0; i < 17; i++) {\n        const score = kpt[3 * i + 2];\n        if (score > config.body.minConfidence) {\n          const positionRaw: Point = [kpt[3 * i + 1], kpt[3 * i + 0]];\n          keypoints.push({\n            part: coords.kpt[i] as BodyLandmark,\n            score: Math.round(100 * score) / 100,\n            positionRaw,\n            position: [Math.round((image.shape[2] || 0) * positionRaw[0]), Math.round((image.shape[1] || 0) * positionRaw[1])],\n          });\n        }\n      }\n      const newBox = box.calc(keypoints.map((pt) => pt.position), [image.shape[2], image.shape[1]]);\n      // movenet-multipose has built-in box details\n      // const boxRaw: Box = [kpt[51 + 1], kpt[51 + 0], kpt[51 + 3] - kpt[51 + 1], kpt[51 + 2] - kpt[51 + 0]];\n      // const box: Box = [Math.trunc(boxRaw[0] * (image.shape[2] || 0)), Math.trunc(boxRaw[1] * (image.shape[1] || 0)), Math.trunc(boxRaw[2] * (image.shape[2] || 0)), Math.trunc(boxRaw[3] * (image.shape[1] || 0))];\n      const annotations: Record<BodyAnnotation, Point[][]> = {} as Record<BodyAnnotation, Point[][]>;\n      for (const [name, indexes] of Object.entries(coords.connected)) {\n        const pt: Array<Point[]> = [];\n        for (let i = 0; i < indexes.length - 1; i++) {\n          const pt0 = keypoints.find((kp) => kp.part === indexes[i]);\n          const pt1 = keypoints.find((kp) => kp.part === indexes[i + 1]);\n          if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n        }\n        annotations[name] = pt;\n      }\n      const body: BodyResult = { id, score: totalScore, box: newBox.box, boxRaw: newBox.boxRaw, keypoints: [...keypoints], annotations };\n      fix.bodyParts(body);\n      bodies.push(body);\n    }\n  }\n  bodies.sort((a, b) => b.score - a.score);\n  if (bodies.length > config.body.maxDetected) bodies.length = config.body.maxDetected;\n  return bodies;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {\n  if (!model || !model?.inputs[0].shape) return []; // something is wrong with the model\n  if (!config.skipAllowed) cache.boxes.length = 0; // allowed to use cache or not\n  skipped++; // increment skip frames\n  const skipTime = (config.body.skipTime || 0) > (now() - cache.last);\n  const skipFrame = skipped < (config.body.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame) {\n    return cache.bodies; // return cached results without running anything\n  }\n  return new Promise(async (resolve) => {\n    const t: Record<string, Tensor> = {};\n    skipped = 0;\n    // run detection on squared input and cached boxes\n    /*\n    cache.bodies = []; // reset bodies result\n    if (cache.boxes.length >= (config.body.maxDetected || 0)) { // if we have enough cached boxes run detection using cache\n      for (let i = 0; i < cache.boxes.length; i++) { // run detection based on cached boxes\n        t.crop = tf.image.cropAndResize(input, [cache.boxes[i]], [0], [inputSize, inputSize], 'bilinear');\n        t.cast = tf.cast(t.crop, 'int32');\n        // t.input = prepareImage(input);\n        t.res = model?.execute(t.cast) as Tensor;\n        const res = await t.res.array();\n        const newBodies = (t.res.shape[2] === 17) ? await parseSinglePose(res, config, input, cache.boxes[i]) : await parseMultiPose(res, config, input, cache.boxes[i]);\n        cache.bodies = cache.bodies.concat(newBodies);\n        Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n      }\n    }\n    if (cache.bodies.length !== config.body.maxDetected) { // did not find enough bodies based on cached boxes so run detection on full frame\n      t.input = prepareImage(input);\n      t.res = model?.execute(t.input) as Tensor;\n      const res = await t.res.array();\n      cache.bodies = (t.res.shape[2] === 17) ? await parseSinglePose(res, config, input, [0, 0, 1, 1]) : await parseMultiPose(res, config, input, [0, 0, 1, 1]);\n      for (const body of cache.bodies) rescaleBody(body, [input.shape[2] || 1, input.shape[1] || 1]);\n      Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    }\n    cache.boxes.length = 0; // reset cache\n    for (let i = 0; i < cache.bodies.length; i++) {\n      if (cache.bodies[i].keypoints.length > (coords.kpt.length / 2)) { // only update cache if we detected at least half keypoints\n        const scaledBox = box.scale(cache.bodies[i].boxRaw, boxExpandFact);\n        const cropBox = box.crop(scaledBox);\n        cache.boxes.push(cropBox);\n      }\n    }\n    */\n\n    // run detection on squared input and no cached boxes\n    t.input = fix.padInput(input, inputSize);\n    t.res = model?.execute(t.input) as Tensor;\n    cache.last = now();\n    const res = await t.res.array();\n    cache.bodies = (t.res.shape[2] === 17)\n      ? await parseSinglePose(res, config, input)\n      : await parseMultiPose(res, config, input);\n    for (const body of cache.bodies) {\n      fix.rescaleBody(body, [input.shape[2] || 1, input.shape[1] || 1]);\n      fix.jitter(body.keypoints);\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n\n    resolve(cache.bodies);\n  });\n}\n", "/**\n * NanoDet object detection model implementation\n *\n * Based on: [**MB3-CenterNet**](https://github.com/610265158/mobilenetv3_centernet)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport { labels } from './labels';\nimport type { ObjectResult, ObjectType, Box } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel;\nlet last: Array<ObjectResult> = [];\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet inputSize = 0;\n\nconst scaleBox = 2.5; // increase box size\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (!model || env.initial) {\n    model = await loadModel(config.object.modelPath);\n    const inputs = Object.values(model.modelSignature['inputs']);\n    inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nasync function process(res: Tensor[], outputShape: [number, number], config: Config) {\n  let id = 0;\n  let results: Array<ObjectResult> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(async () => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      const scoresT = tf.squeeze(res.find((a: Tensor) => (a.shape[1] === (baseSize ** 2) && (a.shape[2] || 0) === labels.length)));\n      const featuresT = tf.squeeze(res.find((a: Tensor) => (a.shape[1] === (baseSize ** 2) && (a.shape[2] || 0) < labels.length)));\n      const boxesMax = featuresT.reshape([-1, 4, featuresT.shape[1] / 4]); // reshape [output] to [4, output / 4] where number is number of different features inside each stride\n      const boxIdx = await boxesMax.argMax(2).array(); // what we need is indexes of features with highest scores, not values itself\n      const scores = await scoresT.array(); // optionally use exponential scores or just as-is\n      for (let i = 0; i < scoresT.shape[0]; i++) { // total strides (x * y matrix)\n        for (let j = 0; j < scoresT.shape[1]; j++) { // one score for each class\n          const score = scores[i][j]; // get score for current position\n          if (score > (config.object.minConfidence || 0) && j !== 61) {\n            const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n            const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n            const boxOffset = boxIdx[i].map((a: number) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n            const [x, y] = [\n              cx - (scaleBox / strideSize * boxOffset[0]),\n              cy - (scaleBox / strideSize * boxOffset[1]),\n            ];\n            const [w, h] = [\n              cx + (scaleBox / strideSize * boxOffset[2]) - x,\n              cy + (scaleBox / strideSize * boxOffset[3]) - y,\n            ];\n            let boxRaw: Box = [x, y, w, h]; // results normalized to range 0..1\n            boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))) as Box; // fix out-of-bounds coords\n            const box = [ // results normalized to input image pixels\n              boxRaw[0] * outputShape[0],\n              boxRaw[1] * outputShape[1],\n              boxRaw[2] * outputShape[0],\n              boxRaw[3] * outputShape[1],\n            ];\n            const result = {\n              id: id++,\n              // strideSize,\n              score: Math.round(100 * score) / 100,\n              class: j + 1,\n              label: labels[j].label as ObjectType,\n              // center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n              // centerRaw: [cx, cy],\n              box: box.map((a) => Math.trunc(a)) as Box,\n              boxRaw,\n            };\n            results.push(result);\n          }\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => [a.boxRaw[1], a.boxRaw[0], a.boxRaw[3], a.boxRaw[2]]); // switches coordinates from x,y to y,x as expected by tf.nms\n  const nmsScores = results.map((a) => a.score);\n  let nmsIdx: Array<number> = [];\n  if (nmsBoxes && nmsBoxes.length > 0) {\n    const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxDetected, config.object.iouThreshold, config.object.minConfidence);\n    nmsIdx = await nms.data();\n    tf.dispose(nms);\n  }\n\n  // filter & sort results\n  results = results\n    .filter((_val, idx) => nmsIdx.includes(idx))\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image: Tensor, config: Config): Promise<ObjectResult[]> {\n  const skipTime = (config.object.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.object.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  skipped = 0;\n  if (!env.kernels.includes('mod') || !env.kernels.includes('sparsetodense')) return last;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2] || 0, image.shape[1] || 0];\n    const resize = tf.image.resizeBilinear(image, [inputSize, inputSize], false);\n    const norm = tf.div(resize, constants.tf255);\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    tf.dispose(norm);\n    tf.dispose(resize);\n\n    let objectT;\n    if (config.object.enabled) objectT = model.execute(transpose);\n    lastTime = now();\n    tf.dispose(transpose);\n\n    const obj = await process(objectT as Tensor[], outputSize as [number, number], config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "/**\n * PoseNet body detection model implementation constants\n * See `posenet.ts` for entry point\n */\n\nimport type { Point, BodyResult, BodyAnnotation, BodyLandmark } from '../result';\n\nexport const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const count = partNames.length; // 17 keypoints\n\nexport const partIds = partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport function eitherPointDoesntMeetConfidence(a: number, b: number, minConfidence: number) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence: number) {\n  return connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nexport function getBoundingBox(keypoints): [number, number, number, number] {\n  const coord = keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: Number.NEGATIVE_INFINITY,\n    maxY: Number.NEGATIVE_INFINITY,\n    minX: Number.POSITIVE_INFINITY,\n    minY: Number.POSITIVE_INFINITY,\n  });\n  return [coord.minX, coord.minY, coord.maxX - coord.minX, coord.maxY - coord.minY];\n}\n\nexport function scalePoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]): Array<BodyResult> {\n  const scaleY = height / inputResolutionHeight;\n  const scaleX = width / inputResolutionWidth;\n  const scalePose = (pose, i): BodyResult => ({\n    id: i,\n    score: pose.score,\n    boxRaw: [pose.box[0] / inputResolutionWidth, pose.box[1] / inputResolutionHeight, pose.box[2] / inputResolutionWidth, pose.box[3] / inputResolutionHeight],\n    box: [Math.trunc(pose.box[0] * scaleX), Math.trunc(pose.box[1] * scaleY), Math.trunc(pose.box[2] * scaleX), Math.trunc(pose.box[3] * scaleY)],\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score: score as number,\n      part: part as BodyLandmark,\n      position: [Math.trunc(position.x * scaleX), Math.trunc(position.y * scaleY)] as Point,\n      positionRaw: [position.x / inputResolutionHeight, position.y / inputResolutionHeight] as Point,\n    })),\n    annotations: {} as Record<BodyAnnotation, Point[][]>,\n  });\n  const scaledPoses = poses.map((pose, i) => scalePose(pose, i));\n  return scaledPoses;\n}\n\n// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nexport class MaxHeap {\n  priorityQueue: Array<unknown>; // don't touch\n  numberOfElements: number;\n  getElementValue: unknown; // function call\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() { return this.numberOfElements === -1; }\n\n  size() { return this.numberOfElements + 1; }\n\n  all() { return this.priorityQueue.slice(0, this.numberOfElements + 1); }\n\n  max() { return this.priorityQueue[0]; }\n\n  swim(k) {\n    while (k > 0 && this.less(Math.floor(k / 2), k)) {\n      this.exchange(k, Math.floor(k / 2));\n      k = Math.floor(k / 2);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    // @ts-ignore getter is of unknown type\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + count),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "/**\n * PoseNet body detection model implementation\n *\n * Based on: [**PoseNet**](https://medium.com/tensorflow/real-time-human-pose-estimation-in-the-browser-with-tensorflow-js-7dd0bc881cd5)\n */\n\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { BodyResult, BodyLandmark, Box } from '../result';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\nimport * as utils from './posenetutils';\n\nlet model: GraphModel;\nconst poseNetOutputs = ['MobilenetV1/offset_2/BiasAdd'/* offsets */, 'MobilenetV1/heatmap_2/BiasAdd'/* heatmapScores */, 'MobilenetV1/displacement_fwd_2/BiasAdd'/* displacementFwd */, 'MobilenetV1/displacement_bwd_2/BiasAdd'/* displacementBwd */];\nconst localMaximumRadius = 1;\nconst outputStride = 16;\nconst squaredNmsRadius = 50 ** 2;\n\nfunction traverse(edgeId, sourceKeypoint, targetId, scores, offsets, displacements, offsetRefineStep = 2) {\n  const getDisplacement = (point) => ({\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, (displacements.shape[2] / 2) + edgeId),\n  });\n  const getStridedIndexNearPoint = (point, height, width) => ({\n    y: utils.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: utils.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  });\n\n  const [height, width] = scores.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, height, width);\n  const displacement = getDisplacement(sourceKeypointIndices);\n  const displacedPoint = utils.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, height, width);\n    const offsetPoint = utils.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetId, offsets);\n    targetKeypoint = utils.addVectors(\n      { x: targetKeypointIndices.x * outputStride, y: targetKeypointIndices.y * outputStride },\n      { x: offsetPoint.x, y: offsetPoint.y },\n    );\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, height, width);\n  const score = scores.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetId);\n  return { position: targetKeypoint, part: utils.partNames[targetId], score };\n}\n\nexport function decodePose(root, scores, offsets, displacementsFwd, displacementsBwd) {\n  const tuples = utils.poseChain.map(([parentJoinName, childJoinName]) => ([utils.partIds[parentJoinName], utils.partIds[childJoinName]]));\n  const edgesFwd = tuples.map(([, childJointId]) => childJointId);\n  const edgesBwd = tuples.map(([parentJointId]) => parentJointId);\n  const numParts = scores.shape[2]; // [21,21,17]\n  const numEdges = edgesFwd.length;\n  const keypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const rootPoint = utils.getImageCoords(root.part, outputStride, offsets);\n  keypoints[root.part.id] = {\n    score: root.score,\n    part: utils.partNames[root.part.id] as BodyLandmark,\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceId = edgesFwd[edge];\n    const targetId = edgesBwd[edge];\n    if (keypoints[sourceId] && !keypoints[targetId]) {\n      keypoints[targetId] = traverse(edge, keypoints[sourceId], targetId, scores, offsets, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceId = edgesBwd[edge];\n    const targetId = edgesFwd[edge];\n    if (keypoints[sourceId] && !keypoints[targetId]) {\n      keypoints[targetId] = traverse(edge, keypoints[sourceId], targetId, scores, offsets, displacementsFwd);\n    }\n  }\n  return keypoints;\n}\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(minConfidence, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new utils.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < minConfidence) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, scores)) queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n      }\n    }\n  }\n  return queue;\n}\n\nfunction withinRadius(poses, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId]?.position;\n    if (!correspondingKeypoint) return false;\n    return utils.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, keypoints) {\n  const notOverlappedKeypointScores = keypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinRadius(existingPoses, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / keypoints.length;\n}\n\nexport function decode(offsets, scores, displacementsFwd, displacementsBwd, maxDetected, minConfidence) {\n  const poses: Array<{ keypoints, box: Box, score: number }> = [];\n  const queue = buildPartWithScoreQueue(minConfidence, scores);\n  // Generate at most maxDetected object instances per image in decreasing root part score order.\n  while (poses.length < maxDetected && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    // @ts-ignore this one is tree walk\n    const rootImageCoords = utils.getImageCoords(root.part, outputStride, offsets);\n    // @ts-ignore this one is tree walk\n    if (withinRadius(poses, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    let keypoints = decodePose(root, scores, offsets, displacementsFwd, displacementsBwd);\n    keypoints = keypoints.filter((a) => a.score > minConfidence);\n    const score = getInstanceScore(poses, keypoints);\n    const box = utils.getBoundingBox(keypoints);\n    if (score > minConfidence) poses.push({ keypoints, box, score: Math.round(100 * score) / 100 });\n  }\n  return poses;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {\n  /** posenet is mostly obsolete\n   * caching is not implemented\n   */\n  const res = tf.tidy(() => {\n    if (!model.inputs[0].shape) return [];\n    const resized = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n    const normalized = tf.sub(tf.div(tf.cast(resized, 'float32'), 127.5), 1.0);\n    const results: Array<Tensor> = model.execute(normalized, poseNetOutputs) as Array<Tensor>;\n    const results3d = results.map((y) => tf.squeeze(y, [0]));\n    results3d[1] = tf.sigmoid(results3d[1]); // apply sigmoid on scores\n    return results3d;\n  });\n\n  const buffers = await Promise.all(res.map((tensor: Tensor) => tensor.buffer()));\n  for (const t of res) tf.dispose(t);\n\n  const decoded = await decode(buffers[0], buffers[1], buffers[2], buffers[3], config.body.maxDetected, config.body.minConfidence);\n  if (!model.inputs[0].shape) return [];\n  const scaled = utils.scalePoses(decoded, [input.shape[1], input.shape[2]], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) as BodyResult[];\n  return scaled;\n}\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (!model || env.initial) model = await loadModel(config.body.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n", "/**\n * Image segmentation for body detection model\n *\n * Based on:\n * - [**MediaPipe Meet**](https://drive.google.com/file/d/1lnP1bRi9CSqQQXUHa13159vLELYDgDu0/preview)\n * - [**MediaPipe Selfie**](https://drive.google.com/file/d/1dCfozqknMa068vVsO2j_1FgZkW_e3VWv/preview)\n */\n\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport * as image from '../image/image';\nimport { constants } from '../tfjs/constants';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\nimport type { Input, AnyCanvas } from '../exports';\n\nlet model: GraphModel;\nlet busy = false;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (!model || env.initial) model = await loadModel(config.segmentation.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function process(input: Input, background: Input | undefined, config: Config)\n: Promise<{ data: Array<number> | Tensor, canvas: AnyCanvas | null, alpha: AnyCanvas | null }> {\n  if (busy) return { data: [], canvas: null, alpha: null };\n  busy = true;\n  if (!model) await load(config);\n  const inputImage = await image.process(input, config);\n  const width = inputImage.tensor?.shape[2] || 0;\n  const height = inputImage.tensor?.shape[1] || 0;\n  if (!inputImage.tensor) return { data: [], canvas: null, alpha: null };\n  const t: Record<string, Tensor> = {};\n\n  t.resize = tf.image.resizeBilinear(inputImage.tensor, [model.inputs[0].shape ? model.inputs[0].shape[1] : 0, model.inputs[0].shape ? model.inputs[0].shape[2] : 0], false);\n  tf.dispose(inputImage.tensor);\n  t.norm = tf.div(t.resize, constants.tf255);\n  t.res = model.execute(t.norm) as Tensor;\n\n  t.squeeze = tf.squeeze(t.res, 0); // meet.shape:[1,256,256,1], selfie.shape:[1,144,256,2]\n  if (t.squeeze.shape[2] === 2) {\n    t.softmax = tf.softmax(t.squeeze); // model meet has two channels for fg and bg\n    [t.bg, t.fg] = tf.unstack(t.softmax, 2);\n    t.expand = tf.expandDims(t.fg, 2);\n    t.pad = tf.expandDims(t.expand, 0);\n    t.crop = tf.image.cropAndResize(t.pad, [[0, 0, 0.5, 0.5]], [0], [width, height]);\n    // running sofmax before unstack creates 2x2 matrix so we only take upper-left quadrant\n    // otherwise run softmax after unstack and use standard resize\n    // resizeOutput = tf.image.resizeBilinear(expand, [input.tensor?.shape[1], input.tensor?.shape[2]]);\n    t.data = tf.squeeze(t.crop, 0);\n  } else {\n    t.data = tf.image.resizeBilinear(t.squeeze, [height, width]); // model selfie has a single channel that we can use directly\n  }\n  const data = Array.from(await t.data.data()) as number[];\n\n  if (env.node && !env.Canvas && (typeof ImageData === 'undefined')) {\n    if (config.debug) log('canvas support missing');\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return { data, canvas: null, alpha: null }; // running in nodejs so return alpha array as-is\n  }\n\n  const alphaCanvas = image.canvas(width, height);\n  // @ts-ignore browser is not defined in tfjs-node\n  if (tf.browser) await tf.browser.toPixels(t.data, alphaCanvas);\n  const alphaCtx = alphaCanvas.getContext('2d') as CanvasRenderingContext2D;\n  if (config.segmentation.blur && config.segmentation.blur > 0) alphaCtx.filter = `blur(${config.segmentation.blur}px)`; // use css filter for bluring, can be done with gaussian blur manually instead\n  const alphaData = alphaCtx.getImageData(0, 0, width, height);\n\n  const compositeCanvas = image.canvas(width, height);\n  const compositeCtx = compositeCanvas.getContext('2d') as CanvasRenderingContext2D;\n  if (inputImage.canvas) compositeCtx.drawImage(inputImage.canvas, 0, 0);\n  compositeCtx.globalCompositeOperation = 'darken'; // https://developer.mozilla.org/en-US/docs/Web/API/CanvasRenderingContext2D/globalCompositeOperation // best options are: darken, color-burn, multiply\n  if (config.segmentation.blur && config.segmentation.blur > 0) compositeCtx.filter = `blur(${config.segmentation.blur}px)`; // use css filter for bluring, can be done with gaussian blur manually instead\n  compositeCtx.drawImage(alphaCanvas, 0, 0);\n  compositeCtx.globalCompositeOperation = 'source-over'; // reset composite operation\n  compositeCtx.filter = 'none'; // reset css filter\n  const compositeData = compositeCtx.getImageData(0, 0, width, height);\n  for (let i = 0; i < width * height; i++) compositeData.data[4 * i + 3] = alphaData.data[4 * i + 0]; // copy original alpha value to new composite canvas\n  compositeCtx.putImageData(compositeData, 0, 0);\n\n  let mergedCanvas: AnyCanvas | null = null;\n  if (background && compositeCanvas) { // draw background with segmentation as overlay if background is present\n    mergedCanvas = image.canvas(width, height);\n    const bgImage = await image.process(background, config);\n    tf.dispose(bgImage.tensor);\n    const ctxMerge = mergedCanvas.getContext('2d') as CanvasRenderingContext2D;\n    ctxMerge.drawImage(bgImage.canvas as HTMLCanvasElement, 0, 0, mergedCanvas.width, mergedCanvas.height);\n    ctxMerge.drawImage(compositeCanvas, 0, 0);\n  }\n\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  busy = false;\n  // return { data, canvas: mergedCanvas || compositeCanvas, alpha: alphaCanvas };\n  return { data, canvas: compositeCanvas, alpha: alphaCanvas };\n}\n", "/** TFJS custom backend registration */\n\nimport type { Human } from '../human';\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as image from '../image/image';\nimport * as models from '../models';\nimport type { AnyCanvas } from '../exports';\n// import { env } from '../env';\n\nexport const config = {\n  name: 'humangl',\n  priority: 999,\n  canvas: <null | AnyCanvas>null,\n  gl: <null | WebGL2RenderingContext>null,\n  extensions: <string[]> [],\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nfunction extensions(): void {\n  /*\n  https://www.khronos.org/registry/webgl/extensions/\n  https://webglreport.com/?v=2\n  */\n  const gl = config.gl;\n  if (!gl) return;\n  config.extensions = gl.getSupportedExtensions() as string[];\n  // gl.getExtension('KHR_parallel_shader_compile');\n}\n\n/**\n * Registers custom WebGL2 backend to be used by Human library\n *\n * @returns void\n */\nexport async function register(instance: Human): Promise<void> {\n  // force backend reload if gl context is not valid\n  if (instance.config.backend !== 'humangl') return;\n  if ((config.name in tf.engine().registry) && (!config.gl || !config.gl.getParameter(config.gl.VERSION))) {\n    log('error: humangl backend invalid context');\n    models.reset(instance);\n    /*\n    log('resetting humangl backend');\n    await tf.removeBackend(config.name);\n    await register(instance); // re-register\n    */\n  }\n  if (!tf.findBackend(config.name)) {\n    try {\n      config.canvas = await image.canvas(100, 100);\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      config.gl = config.canvas?.getContext('webgl2', config.webGLattr) as WebGL2RenderingContext;\n      const glv2 = config.gl.getParameter(config.gl.VERSION).includes('2.0');\n      if (!glv2) {\n        log('override: using fallback webgl backend as webgl 2.0 is not detected');\n        instance.config.backend = 'webgl';\n        return;\n      }\n      if (config.canvas) {\n        config.canvas.addEventListener('webglcontextlost', async (e) => {\n          log('error: humangl:', e.type);\n          log('possible browser memory leak using webgl or conflict with multiple backend registrations');\n          instance.emit('error');\n          throw new Error('backend error: webgl context lost');\n          // log('resetting humangl backend');\n          // env.initial = true;\n          // models.reset(instance);\n          // await tf.removeBackend(config.name);\n          // await register(instance); // re-register\n        });\n        config.canvas.addEventListener('webglcontextrestored', (e) => {\n          log('error: humangl context restored:', e);\n        });\n        config.canvas.addEventListener('webglcontextcreationerror', (e) => {\n          log('error: humangl context create:', e);\n        });\n      }\n    } catch (err) {\n      log('error: cannot get WebGL context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    const current = tf.backend().getGPGPUContext ? tf.backend().getGPGPUContext().gl : null;\n    if (current) {\n      log(`humangl webgl version:${current.getParameter(current.VERSION)} renderer:${current.getParameter(current.RENDERER)}`);\n    } else {\n      log('error: no current gl context:', current, config.gl);\n      return;\n    }\n    try {\n      tf.ENV.set('WEBGL_VERSION', 2);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    extensions();\n    log('backend registered:', config.name);\n  }\n}\n", "/** TFJS backend initialization and customization */\n\nimport type { Human } from '../human';\nimport { log, now } from '../util/util';\nimport { env } from '../util/env';\nimport * as humangl from './humangl';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as constants from './constants';\n\nfunction registerCustomOps() {\n  if (!env.kernels.includes('mod')) {\n    const kernelMod = {\n      kernelName: 'Mod',\n      backendName: tf.getBackend(),\n      kernelFunc: (op) => tf.tidy(() => tf.sub(op.inputs.a, tf.mul(tf.div(op.inputs.a, op.inputs.b), op.inputs.b))),\n    };\n    tf.registerKernel(kernelMod);\n    env.kernels.push('mod');\n  }\n  if (!env.kernels.includes('floormod')) {\n    const kernelMod = {\n      kernelName: 'FloorMod',\n      backendName: tf.getBackend(),\n      kernelFunc: (op) => tf.tidy(() => tf.floorDiv(op.inputs.a / op.inputs.b) * op.inputs.b + tf.mod(op.inputs.a, op.inputs.b)),\n    };\n    tf.registerKernel(kernelMod);\n    env.kernels.push('floormod');\n  }\n}\n\nexport async function check(instance: Human, force = false) {\n  instance.state = 'backend';\n  if (force || env.initial || (instance.config.backend && (instance.config.backend.length > 0) && (tf.getBackend() !== instance.config.backend))) {\n    const timeStamp = now();\n\n    if (instance.config.backend && instance.config.backend.length > 0) {\n      // detect web worker\n      // @ts-ignore ignore missing type for WorkerGlobalScope as that is the point\n      if (typeof window === 'undefined' && typeof WorkerGlobalScope !== 'undefined' && instance.config.debug) {\n        if (instance.config.debug) log('running inside web worker');\n      }\n\n      // force browser vs node backend\n      if (env.browser && instance.config.backend === 'tensorflow') {\n        if (instance.config.debug) log('override: backend set to tensorflow while running in browser');\n        instance.config.backend = 'humangl';\n      }\n      if (env.node && (instance.config.backend === 'webgl' || instance.config.backend === 'humangl')) {\n        if (instance.config.debug) log(`override: backend set to ${instance.config.backend} while running in nodejs`);\n        instance.config.backend = 'tensorflow';\n      }\n\n      // handle webgpu\n      if (env.browser && instance.config.backend === 'webgpu') {\n        if (typeof navigator === 'undefined' || typeof navigator['gpu'] === 'undefined') {\n          log('override: backend set to webgpu but browser does not support webgpu');\n          instance.config.backend = 'humangl';\n        } else {\n          const adapter = await navigator['gpu'].requestAdapter();\n          if (instance.config.debug) log('enumerated webgpu adapter:', adapter);\n          if (!adapter) {\n            log('override: backend set to webgpu but browser reports no available gpu');\n            instance.config.backend = 'humangl';\n          } else {\n            // @ts-ignore requestAdapterInfo is not in tslib\n            // eslint-disable-next-line no-undef\n            const adapterInfo = 'requestAdapterInfo' in adapter ? await (adapter as GPUAdapter).requestAdapterInfo() : undefined;\n            // if (adapter.features) adapter.features.forEach((feature) => log('webgpu features:', feature));\n            log('webgpu adapter info:', adapterInfo);\n          }\n        }\n      }\n\n      // check available backends\n      if (instance.config.backend === 'humangl') await humangl.register(instance);\n      const available = Object.keys(tf.engine().registryFactory);\n      if (instance.config.debug) log('available backends:', available);\n\n      if (!available.includes(instance.config.backend)) {\n        log(`error: backend ${instance.config.backend} not found in registry`);\n        instance.config.backend = env.node ? 'tensorflow' : 'webgl';\n        if (instance.config.debug) log(`override: setting backend ${instance.config.backend}`);\n      }\n\n      if (instance.config.debug) log('setting backend:', instance.config.backend);\n\n      // customize wasm\n      if (instance.config.backend === 'wasm') {\n        try {\n          tf.env().set('CANVAS2D_WILL_READ_FREQUENTLY', true);\n        } catch { /**/ }\n        if (instance.config.debug) log('wasm path:', instance.config.wasmPath);\n        if (typeof tf?.setWasmPaths !== 'undefined') await tf.setWasmPaths(instance.config.wasmPath, instance.config.wasmPlatformFetch);\n        else throw new Error('backend error: attempting to use wasm backend but wasm path is not set');\n        const simd = await tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n        const mt = await tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n        if (instance.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n        if (instance.config.debug && !simd) log('warning: wasm simd support is not enabled');\n      }\n\n      try {\n        await tf.setBackend(instance.config.backend);\n        await tf.ready();\n        constants.init();\n      } catch (err) {\n        log('error: cannot set backend:', instance.config.backend, err);\n        return false;\n      }\n    }\n\n    // customize humangl\n    if (tf.getBackend() === 'humangl') {\n      tf.ENV.set('CHECK_COMPUTATION_FOR_ERRORS', false);\n      tf.ENV.set('WEBGL_CPU_FORWARD', true);\n      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', false);\n      tf.ENV.set('WEBGL_USE_SHAPES_UNIFORMS', true);\n      tf.ENV.set('CPU_HANDOFF_SIZE_THRESHOLD', 256);\n      // if (!instance.config.object.enabled) tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true); // safe to use 16bit precision\n      if (typeof instance.config['deallocate'] !== 'undefined' && instance.config['deallocate']) { // hidden param\n        log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', true);\n        tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', 0);\n      }\n      if (tf.backend().getGPGPUContext) {\n        const gl = await tf.backend().getGPGPUContext().gl;\n        if (instance.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n    }\n\n    // customize webgpu\n    if (tf.getBackend() === 'webgpu') {\n      // tf.ENV.set('WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD', 512);\n      // tf.ENV.set('WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE', 0);\n      // tf.ENV.set('WEBGPU_CPU_FORWARD', true);\n    }\n\n    // wait for ready\n    tf.enableProdMode();\n    await tf.ready();\n\n    instance.performance.initBackend = Math.trunc(now() - timeStamp);\n    instance.config.backend = tf.getBackend();\n\n    await env.updateBackend(); // update env on backend init\n    registerCustomOps();\n    // await env.updateBackend(); // update env on backend init\n  }\n  return true;\n}\n\n// register fake missing tfjs ops\nexport function fakeOps(kernelNames: Array<string>, config) {\n  // if (config.debug) log('registerKernel:', kernelNames);\n  for (const kernelName of kernelNames) {\n    const kernelConfig = {\n      kernelName,\n      backendName: config.backend,\n      kernelFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },\n      // setupFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },\n      // disposeFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },\n    };\n    tf.registerKernel(kernelConfig);\n  }\n  env.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => kernel.kernelName.toLowerCase()); // re-scan registered ops\n}\n", "/**\n * Module that implements helper draw functions, exposed as human.draw\n */\n\nimport { mergeDeep, now } from '../util/util';\nimport { env } from '../util/env';\nimport { getCanvasContext, rect } from './primitives';\nimport { options } from './options';\nimport { face } from './face';\nimport { body } from './body';\nimport { hand } from './hand';\nimport { object } from './object';\nimport { gesture } from './gesture';\nimport type { Result, PersonResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\nlet drawTime = 0;\n\nexport { options } from './options';\nexport { face } from './face';\nexport { body } from './body';\nexport { hand } from './hand';\nexport { object } from './object';\nexport { gesture } from './gesture';\n\n/** draw combined person results instead of individual detection result objects */\nexport async function person(inCanvas: AnyCanvas, result: Array<PersonResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = localOptions.font;\n\n  for (let i = 0; i < result.length; i++) {\n    if (localOptions.drawBoxes) {\n      ctx.strokeStyle = localOptions.color;\n      ctx.fillStyle = localOptions.color;\n      rect(ctx, result[i].box[0], result[i].box[1], result[i].box[2], result[i].box[3], localOptions);\n      if (localOptions.drawLabels) {\n        const label = `person #${i}`;\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(label, result[i].box[0] + 3, 1 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(label, result[i].box[0] + 2, 0 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\n/** draw processed canvas */\nexport async function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas) {\n  if (!input || !output) return;\n  const ctx = getCanvasContext(output);\n  if (!ctx) return;\n  ctx.drawImage(input, 0, 0);\n}\n\n/** meta-function that performs draw for: canvas, face, body, hand */\nexport async function all(inCanvas: AnyCanvas, result: Result, drawOptions?: Partial<DrawOptions>) {\n  if (!result || !result.performance || !result || !inCanvas) return null;\n  const timeStamp = now();\n  const localOptions = mergeDeep(options, drawOptions);\n  const promise = Promise.all([\n    face(inCanvas, result.face, localOptions),\n    body(inCanvas, result.body, localOptions),\n    hand(inCanvas, result.hand, localOptions),\n    object(inCanvas, result.object, localOptions),\n    gesture(inCanvas, result.gesture, localOptions), // gestures do not have buffering\n    // person(inCanvas, result.persons, localOptions); // already included above\n  ]);\n  drawTime = env.perfadd ? drawTime + Math.round(now() - timeStamp) : Math.round(now() - timeStamp);\n  result.performance.draw = drawTime;\n  return promise;\n}\n", "import { log } from '../util/util';\nimport type { AnyCanvas } from '../exports';\nimport type { Point } from '../result';\nimport type { DrawOptions } from './options';\n\nexport const getCanvasContext = (input: AnyCanvas) => {\n  if (!input) log('draw error: invalid canvas');\n  else if (!input.getContext) log('draw error: canvas context not defined');\n  else {\n    const ctx = input.getContext('2d');\n    if (!ctx) log('draw error: cannot get canvas context');\n    else return ctx;\n  }\n  return null;\n};\n\nexport const rad2deg = (theta: number) => Math.round((theta * 180) / Math.PI);\n\nexport const colorDepth = (z: number | undefined, opt: DrawOptions): string => {\n  if (!opt.useDepth || typeof z === 'undefined') return opt.color;\n  const rgb = Uint8ClampedArray.from([127 + (2 * z), 127 - (2 * z), 255]);\n  const color = `rgba(${rgb[0]}, ${rgb[1]}, ${rgb[2]}, ${opt.alpha})`;\n  return color;\n};\n\nexport function point(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, x: number, y: number, z: number | undefined, localOptions: DrawOptions) {\n  ctx.fillStyle = colorDepth(z, localOptions);\n  ctx.beginPath();\n  ctx.arc(x, y, localOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nexport function rect(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, x: number, y: number, width: number, height: number, localOptions: DrawOptions) {\n  ctx.beginPath();\n  ctx.lineWidth = localOptions.lineWidth;\n  if (localOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.moveTo(x + localOptions.roundRect, y);\n    ctx.lineTo(x + width - localOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + localOptions.roundRect);\n    ctx.lineTo(x + width, y + height - localOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - localOptions.roundRect, y + height);\n    ctx.lineTo(x + localOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - localOptions.roundRect);\n    ctx.lineTo(x, y + localOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + localOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nexport function lines(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, points: Point[], localOptions: DrawOptions) {\n  if (points.length < 2) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = colorDepth(pt[2] || 0, localOptions);\n    ctx.lineTo(Math.trunc(pt[0]), Math.trunc(pt[1]));\n  }\n  ctx.stroke();\n  if (localOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport function curves(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, points: Point[], localOptions: DrawOptions) {\n  if (points.length < 2) return;\n  ctx.lineWidth = localOptions.lineWidth;\n  if (!localOptions.useCurves || points.length <= 2) {\n    lines(ctx, points, localOptions);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (localOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport function arrow(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, from: Point, to: Point, radius = 5) {\n  let angle;\n  let x;\n  let y;\n  ctx.beginPath();\n  ctx.moveTo(from[0], from[1]);\n  ctx.lineTo(to[0], to[1]);\n  angle = Math.atan2(to[1] - from[1], to[0] - from[0]);\n  x = radius * Math.cos(angle) + to[0];\n  y = radius * Math.sin(angle) + to[1];\n  ctx.moveTo(x, y);\n  angle += (1.0 / 3.0) * (2 * Math.PI);\n  x = radius * Math.cos(angle) + to[0];\n  y = radius * Math.sin(angle) + to[1];\n  ctx.lineTo(x, y);\n  angle += (1.0 / 3.0) * (2 * Math.PI);\n  x = radius * Math.cos(angle) + to[0];\n  y = radius * Math.sin(angle) + to[1];\n  ctx.lineTo(x, y);\n  ctx.closePath();\n  ctx.stroke();\n  ctx.fill();\n}\n", "/** Draw Options\n * - Accessed via `human.draw.options` or provided per each draw method as the drawOptions optional parameter\n */\nexport type DrawOptions = {\n  /** draw line color */\n  color: string,\n  /** alpha value used for lines */\n  alpha: number,\n  /** label color */\n  labelColor: string,\n  /** label shadow color */\n  shadowColor: string,\n  /** label font */\n  font: string,\n  /** line spacing between labels */\n  lineHeight: number,\n  /** line width for drawn lines */\n  lineWidth: number,\n  /** size of drawn points */\n  pointSize: number,\n  /** draw rounded boxes by n pixels */\n  roundRect: number,\n  /** should points be drawn? */\n  drawPoints: boolean,\n  /** should labels be drawn? */\n  drawLabels: boolean,\n  /** should face attention keypoints be highlighted */\n  drawAttention: boolean;\n  /** should detected gestures be drawn? */\n  drawGestures: boolean,\n  /** should draw boxes around detection results? */\n  drawBoxes: boolean,\n  /** should draw polygons from detection points? */\n  drawPolygons: boolean,\n  /** should draw gaze arrows? */\n  drawGaze: boolean,\n  /** should fill polygons? */\n  fillPolygons: boolean,\n  /** use z-coordinate when available */\n  useDepth: boolean,\n  /** should lines be curved? */\n  useCurves: boolean,\n}\n\n/** currently set draw options {@link DrawOptions} */\nexport const options: DrawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.6)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  alpha: 0.5,\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>18,\n  lineWidth: <number>4,\n  pointSize: <number>2,\n  roundRect: <number>8,\n  drawPoints: <boolean>false,\n  drawLabels: <boolean>true,\n  drawBoxes: <boolean>true,\n  drawAttention: <boolean>true,\n  drawGestures: <boolean>true,\n  drawPolygons: <boolean>true,\n  drawGaze: <boolean>true,\n  fillPolygons: <boolean>false,\n  useDepth: <boolean>true,\n  useCurves: <boolean>false,\n};\n", "import { TRI468 as triangulation } from '../face/facemeshcoords';\nimport { mergeDeep } from '../util/util';\nimport { getCanvasContext, rad2deg, rect, point, lines, arrow } from './primitives';\nimport { options } from './options';\nimport * as facemeshConstants from '../face/constants';\nimport type { FaceResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\nlet opt: DrawOptions;\n\nfunction drawLabels(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawLabels) {\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face: ${Math.trunc(100 * f.score)}%`);\n    if (f.genderScore) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderScore)}%`);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`distance: ${f.iris}`);\n    if (f.real) labels.push(`real: ${Math.trunc(100 * f.real)}%`);\n    if (f.live) labels.push(`live: ${Math.trunc(100 * f.live)}%`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      if (emotion.length > 3) emotion.length = 3;\n      labels.push(emotion.join(' '));\n    }\n    if (f.rotation && f.rotation.angle && f.rotation.gaze) {\n      if (f.rotation.angle.roll) labels.push(`roll: ${rad2deg(f.rotation.angle.roll)}\u00B0 yaw:${rad2deg(f.rotation.angle.yaw)}\u00B0 pitch:${rad2deg(f.rotation.angle.pitch)}\u00B0`);\n      if (f.rotation.gaze.bearing) labels.push(`gaze: ${rad2deg(f.rotation.gaze.bearing)}\u00B0`);\n    }\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = opt.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * opt.lineHeight + f.box[1];\n      if (opt.shadowColor && opt.shadowColor !== '') {\n        ctx.fillStyle = opt.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = opt.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n  }\n}\n\nfunction drawIrisElipse(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  // iris: array[center, left, top, right, bottom]\n  if (f.annotations && f.annotations['leftEyeIris'] && f.annotations['leftEyeIris'][0]) {\n    ctx.strokeStyle = opt.useDepth ? 'rgba(255, 200, 255, 0.3)' : opt.color;\n    ctx.beginPath();\n    const sizeX = Math.abs(f.annotations['leftEyeIris'][3][0] - f.annotations['leftEyeIris'][1][0]) / 2;\n    const sizeY = Math.abs(f.annotations['leftEyeIris'][4][1] - f.annotations['leftEyeIris'][2][1]) / 2;\n    ctx.ellipse(f.annotations['leftEyeIris'][0][0], f.annotations['leftEyeIris'][0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n    ctx.stroke();\n    if (opt.fillPolygons) {\n      ctx.fillStyle = opt.useDepth ? 'rgba(255, 255, 200, 0.3)' : opt.color;\n      ctx.fill();\n    }\n  }\n  if (f.annotations && f.annotations['rightEyeIris'] && f.annotations['rightEyeIris'][0]) {\n    ctx.strokeStyle = opt.useDepth ? 'rgba(255, 200, 255, 0.3)' : opt.color;\n    ctx.beginPath();\n    const sizeX = Math.abs(f.annotations['rightEyeIris'][3][0] - f.annotations['rightEyeIris'][1][0]) / 2;\n    const sizeY = Math.abs(f.annotations['rightEyeIris'][4][1] - f.annotations['rightEyeIris'][2][1]) / 2;\n    ctx.ellipse(f.annotations['rightEyeIris'][0][0], f.annotations['rightEyeIris'][0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n    ctx.stroke();\n    if (opt.fillPolygons) {\n      ctx.fillStyle = opt.useDepth ? 'rgba(255, 255, 200, 0.3)' : opt.color;\n      ctx.fill();\n    }\n  }\n}\n\nfunction drawGazeSpheres(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawGaze && f.rotation?.angle && typeof Path2D !== 'undefined') {\n    ctx.strokeStyle = 'pink';\n    const valX = (f.box[0] + f.box[2] / 2) - (f.box[3] * rad2deg(f.rotation.angle.yaw) / 90);\n    const valY = (f.box[1] + f.box[3] / 2) + (f.box[2] * rad2deg(f.rotation.angle.pitch) / 90);\n    const pathV = new Path2D(`\n      M ${f.box[0] + f.box[2] / 2} ${f.box[1]}\n      C\n        ${valX} ${f.box[1]},\n        ${valX} ${f.box[1] + f.box[3]},\n        ${f.box[0] + f.box[2] / 2} ${f.box[1] + f.box[3]}\n    `);\n    const pathH = new Path2D(`\n      M ${f.box[0]} ${f.box[1] + f.box[3] / 2}\n      C \n        ${f.box[0]} ${valY},\n        ${f.box[0] + f.box[2]} ${valY},\n        ${f.box[0] + f.box[2]} ${f.box[1] + f.box[3] / 2}\n    `);\n    ctx.stroke(pathH);\n    ctx.stroke(pathV);\n  }\n}\n\nfunction drawGazeArrows(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawGaze && f.rotation?.gaze?.strength && f.rotation?.gaze?.bearing && f.annotations['leftEyeIris'] && f.annotations['rightEyeIris'] && f.annotations['leftEyeIris'][0] && f.annotations['rightEyeIris'][0]) {\n    ctx.strokeStyle = 'pink';\n    ctx.fillStyle = 'pink';\n    const leftGaze = [\n      f.annotations['leftEyeIris'][0][0] + (Math.sin(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[3]),\n      f.annotations['leftEyeIris'][0][1] + (Math.cos(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[2]),\n    ];\n    arrow(ctx, [f.annotations['leftEyeIris'][0][0], f.annotations['leftEyeIris'][0][1]], [leftGaze[0], leftGaze[1]], 4);\n    const rightGaze = [\n      f.annotations['rightEyeIris'][0][0] + (Math.sin(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[3]),\n      f.annotations['rightEyeIris'][0][1] + (Math.cos(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[2]),\n    ];\n    arrow(ctx, [f.annotations['rightEyeIris'][0][0], f.annotations['rightEyeIris'][0][1]], [rightGaze[0], rightGaze[1]], 4);\n  }\n}\n\nfunction drawFacePolygons(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawPolygons && f.mesh.length >= 468) {\n    ctx.lineWidth = 1;\n    for (let i = 0; i < triangulation.length / 3; i++) {\n      const points = [triangulation[i * 3 + 0], triangulation[i * 3 + 1], triangulation[i * 3 + 2]].map((index) => f.mesh[index]);\n      lines(ctx, points, opt);\n    }\n    drawIrisElipse(f, ctx);\n  }\n  /*\n  if (opt.drawPolygons && f.contours.length > 1) {\n    ctx.lineWidth = 5;\n    lines(ctx, f.contours, opt);\n  }\n  ctx.lineWidth = 1;\n  */\n}\n\nfunction drawFacePoints(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawPoints && f.mesh.length >= 468) {\n    for (let i = 0; i < f.mesh.length; i++) {\n      point(ctx, f.mesh[i][0], f.mesh[i][1], f.mesh[i][2], opt);\n      if (opt.drawAttention) {\n        if (facemeshConstants.LANDMARKS_REFINEMENT_LIPS_CONFIG.includes(i)) point(ctx, f.mesh[i][0], f.mesh[i][1], (f.mesh[i][2] as number) + 127, opt);\n        if (facemeshConstants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG.includes(i)) point(ctx, f.mesh[i][0], f.mesh[i][1], (f.mesh[i][2] as number) - 127, opt);\n        if (facemeshConstants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG.includes(i)) point(ctx, f.mesh[i][0], f.mesh[i][1], (f.mesh[i][2] as number) - 127, opt);\n      }\n    }\n  }\n}\n\nfunction drawFaceBoxes(f: FaceResult, ctx) {\n  if (opt.drawBoxes) {\n    rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3], opt);\n  }\n}\n\n/** draw detected faces */\nexport async function face(inCanvas: AnyCanvas, result: Array<FaceResult>, drawOptions?: Partial<DrawOptions>) {\n  opt = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.font = opt.font;\n  ctx.strokeStyle = opt.color;\n  ctx.fillStyle = opt.color;\n  for (const f of result) {\n    drawFaceBoxes(f, ctx);\n    drawLabels(f, ctx);\n    if (f.mesh && f.mesh.length > 0) {\n      drawFacePoints(f, ctx);\n      drawFacePolygons(f, ctx);\n      drawGazeSpheres(f, ctx);\n      drawGazeArrows(f, ctx);\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext, rect, point, curves, colorDepth } from './primitives';\nimport { options } from './options';\nimport type { BodyResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\n/** draw detected bodies */\nexport async function body(inCanvas: AnyCanvas, result: Array<BodyResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    ctx.strokeStyle = localOptions.color;\n    ctx.fillStyle = localOptions.color;\n    ctx.lineWidth = localOptions.lineWidth;\n    ctx.font = localOptions.font;\n    if (localOptions.drawBoxes && result[i].box && result[i].box?.length === 4) {\n      rect(ctx, result[i].box[0], result[i].box[1], result[i].box[2], result[i].box[3], localOptions);\n      if (localOptions.drawLabels) {\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(`body ${100 * result[i].score}%`, result[i].box[0] + 3, 1 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(`body ${100 * result[i].score}%`, result[i].box[0] + 2, 0 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n      }\n    }\n    if (localOptions.drawPoints && result[i].keypoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        if (!result[i].keypoints[pt].score || (result[i].keypoints[pt].score === 0)) continue;\n        ctx.fillStyle = colorDepth(result[i].keypoints[pt].position[2], localOptions);\n        point(ctx, result[i].keypoints[pt].position[0], result[i].keypoints[pt].position[1], 0, localOptions);\n      }\n    }\n    if (localOptions.drawLabels && result[i].keypoints) {\n      ctx.font = localOptions.font;\n      for (const pt of result[i].keypoints) {\n        if (!pt.score || (pt.score === 0)) continue;\n        ctx.fillStyle = colorDepth(pt.position[2], localOptions);\n        ctx.fillText(`${pt.part} ${Math.trunc(100 * pt.score)}%`, pt.position[0] + 4, pt.position[1] + 4);\n      }\n    }\n    if (localOptions.drawPolygons && result[i].keypoints && result[i].annotations) {\n      for (const part of Object.values(result[i].annotations)) {\n        for (const connected of part) curves(ctx, connected, localOptions);\n      }\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext, rect, point, colorDepth } from './primitives';\nimport { options } from './options';\nimport type { HandResult } from '../result';\nimport type { AnyCanvas, DrawOptions, Point } from '../exports';\n\n/** draw detected hands */\nexport async function hand(inCanvas: AnyCanvas, result: Array<HandResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = localOptions.font;\n  for (const h of result) {\n    if (localOptions.drawBoxes) {\n      ctx.strokeStyle = localOptions.color;\n      ctx.fillStyle = localOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3], localOptions);\n      if (localOptions.drawLabels) {\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(`hand:${Math.trunc(100 * h.score)}%`, h.box[0] + 3, 1 + h.box[1] + localOptions.lineHeight, h.box[2]); // can use h.label\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(`hand:${Math.trunc(100 * h.score)}%`, h.box[0] + 2, 0 + h.box[1] + localOptions.lineHeight, h.box[2]); // can use h.label\n      }\n      ctx.stroke();\n    }\n    if (localOptions.drawPoints) {\n      if (h.keypoints && h.keypoints.length > 0) {\n        for (const pt of h.keypoints) {\n          ctx.fillStyle = colorDepth(pt[2], localOptions);\n          point(ctx, pt[0], pt[1], 0, localOptions);\n        }\n      }\n    }\n    if (localOptions.drawLabels && h.annotations) {\n      const addHandLabel = (part: Array<Point>, title: string) => {\n        if (!part || part.length === 0 || !part[0]) return;\n        const z = part[part.length - 1][2] || -256;\n        ctx.fillStyle = colorDepth(z, localOptions);\n        ctx.fillText(title, part[part.length - 1][0] + 4, part[part.length - 1][1] + 4);\n      };\n      ctx.font = localOptions.font;\n      addHandLabel(h.annotations['index'], 'index');\n      addHandLabel(h.annotations['middle'], 'middle');\n      addHandLabel(h.annotations['ring'], 'ring');\n      addHandLabel(h.annotations['pinky'], 'pinky');\n      addHandLabel(h.annotations['thumb'], 'thumb');\n      addHandLabel(h.annotations['palm'], 'palm');\n    }\n    if (localOptions.drawPolygons && h.annotations) {\n      const addHandLine = (part: Array<Point>) => {\n        if (!part || part.length === 0 || !part[0]) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.beginPath();\n          const z = part[i][2] || 0;\n          ctx.strokeStyle = colorDepth(i * z, localOptions);\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      ctx.lineWidth = localOptions.lineWidth;\n      addHandLine(h.annotations['index']);\n      addHandLine(h.annotations['middle']);\n      addHandLine(h.annotations['ring']);\n      addHandLine(h.annotations['pinky']);\n      addHandLine(h.annotations['thumb']);\n      // addPart(h.annotations.palm);\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext, rect } from './primitives';\nimport { options } from './options';\nimport type { ObjectResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\n/** draw detected objects */\nexport async function object(inCanvas: AnyCanvas, result: Array<ObjectResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = localOptions.font;\n  for (const h of result) {\n    if (localOptions.drawBoxes) {\n      ctx.strokeStyle = localOptions.color;\n      ctx.fillStyle = localOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3], localOptions);\n      if (localOptions.drawLabels) {\n        const label = `${h.label} ${Math.round(100 * h.score)}%`;\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + localOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + localOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext } from './primitives';\nimport { options } from './options';\nimport type { GestureResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\n/** draw detected gestures */\nexport async function gesture(inCanvas: AnyCanvas, result: Array<GestureResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  if (localOptions.drawGestures) {\n    const ctx = getCanvasContext(inCanvas);\n    if (!ctx) return;\n    ctx.font = localOptions.font;\n    ctx.fillStyle = localOptions.color;\n    let i = 1;\n    for (let j = 0; j < result.length; j++) {\n      let where: unknown[] = []; // what&where is a record\n      let what: unknown[] = []; // what&where is a record\n      [where, what] = Object.entries(result[j]);\n      if ((what.length > 1) && ((what[1] as string).length > 0)) {\n        const who = where[1] as number > 0 ? `#${where[1]}` : '';\n        const label = `${where[0]} ${who}: ${what[1]}`;\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(label, 8, 2 + (i * localOptions.lineHeight));\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(label, 6, 0 + (i * localOptions.lineHeight));\n        i += 1;\n      }\n    }\n  }\n}\n", "import type { Tensor } from '../tfjs/types';\nimport type { FaceResult } from '../result';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { meshAnnotations } from './facemeshcoords';\n\nconst expandFact = 0.1;\nconst alpha = 0.5;\n\n// point inclusion in polygon based on https://wrf.ecse.rpi.edu/Research/Short_Notes/pnpoly.html\nfunction insidePoly(x: number, y: number, polygon: Array<{ x: number, y: number }>): boolean {\n  let inside = false;\n  let j = polygon.length - 1;\n  for (let i = 0; i < polygon.length; j = i++) {\n    if (((polygon[i].y > y) !== (polygon[j].y > y)) && (x < (polygon[j].x - polygon[i].x) * (y - polygon[i].y) / (polygon[j].y - polygon[i].y) + polygon[i].x)) inside = !inside;\n  }\n  return inside;\n}\n\nexport async function mask(face: FaceResult): Promise<Tensor | undefined> {\n  if (!face.tensor) return face.tensor;\n  if (!face.mesh || face.mesh.length < 100) return face.tensor;\n  const width = face.tensor.shape[2] || 0;\n  const height = face.tensor.shape[1] || 0;\n  const buffer = await face.tensor.buffer();\n  let silhouette: Array<{ x: number, y: number }> = [];\n  for (const pt of meshAnnotations.silhouette) silhouette.push({ x: (face.mesh[pt][0] - face.box[0]) / face.box[2], y: (face.mesh[pt][1] - face.box[1]) / face.box[3] }); // add all silhouette points scaled to local box\n  if (expandFact && expandFact > 0) silhouette = silhouette.map((pt) => ({ x: pt.x > 0.5 ? pt.x + expandFact : pt.x - expandFact, y: pt.y > 0.5 ? pt.y + expandFact : pt.y - expandFact })); // expand silhouette\n  for (let x = 0; x < width; x++) {\n    for (let y = 0; y < height; y++) {\n      const inside = insidePoly(x / width, y / width, silhouette);\n      if (!inside) {\n        buffer.set(alpha * buffer.get(0, y, x, 0), 0, y, x, 0);\n        buffer.set(alpha * buffer.get(0, y, x, 1), 0, y, x, 1);\n        buffer.set(alpha * buffer.get(0, y, x, 2), 0, y, x, 2);\n      }\n    }\n  }\n  const output = buffer.toTensor();\n  tf.dispose(buffer);\n  return output;\n}\n", "import type { Point, FaceResult } from '../result';\n\ntype Vector = [number, number, number];\n\nconst calculateGaze = (face: FaceResult): { bearing: number, strength: number } => {\n  const radians = (pt1: Point, pt2: Point) => Math.atan2(pt1[1] - pt2[1], pt1[0] - pt2[0]); // function to calculate angle between any two points\n  if (!face.annotations['rightEyeIris'] || !face.annotations['leftEyeIris']) return { bearing: 0, strength: 0 };\n\n  const offsetIris = [0, -0.1]; // iris center may not align with average of eye extremes\n  const eyeRatio = 1; // factor to normalize changes x vs y\n\n  const left = (face.mesh[33][2] || 0) > (face.mesh[263][2] || 0); // pick left or right eye depending which one is closer bazed on outsize point z axis\n  const irisCenter = left ? face.mesh[473] : face.mesh[468];\n  const eyeCenter = left // eye center is average of extreme points on x axis for both x and y, ignoring y extreme points as eyelids naturally open/close more when gazing up/down so relative point is less precise\n    ? [(face.mesh[133][0] + face.mesh[33][0]) / 2, (face.mesh[133][1] + face.mesh[33][1]) / 2]\n    : [(face.mesh[263][0] + face.mesh[362][0]) / 2, (face.mesh[263][1] + face.mesh[362][1]) / 2];\n  const eyeSize = left // eye size is difference between extreme points for both x and y, used to normalize & squarify eye dimensions\n    ? [face.mesh[133][0] - face.mesh[33][0], face.mesh[23][1] - face.mesh[27][1]]\n    : [face.mesh[263][0] - face.mesh[362][0], face.mesh[253][1] - face.mesh[257][1]];\n  const eyeDiff: Point = [ // x distance between extreme point and center point normalized with eye size\n    (eyeCenter[0] - irisCenter[0]) / eyeSize[0] - offsetIris[0],\n    eyeRatio * (irisCenter[1] - eyeCenter[1]) / eyeSize[1] - offsetIris[1],\n  ];\n  let strength = Math.sqrt((eyeDiff[0] * eyeDiff[0]) + (eyeDiff[1] * eyeDiff[1])); // vector length is a diagonal between two differences\n  strength = Math.min(strength, face.boxRaw[2] / 2, face.boxRaw[3] / 2); // limit strength to half of box size to avoid clipping due to low precision\n  const bearing = (radians([0, 0], eyeDiff) + (Math.PI / 2)) % Math.PI; // using eyeDiff instead eyeCenter/irisCenter combo due to manual adjustments and rotate clockwise 90degrees\n  return { bearing, strength };\n};\n\nexport const calculateFaceAngle = (face: FaceResult, imageSize: [number, number]): {\n  angle: { pitch: number, yaw: number, roll: number },\n  matrix: [number, number, number, number, number, number, number, number, number],\n  gaze: { bearing: number, strength: number },\n} => {\n  // const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n  const normalize = (v: Vector): Vector => { // normalize vector\n    const length = Math.sqrt(v[0] * v[0] + v[1] * v[1] + v[2] * v[2]);\n    v[0] /= length;\n    v[1] /= length;\n    v[2] /= length;\n    return v;\n  };\n  const subVectors = (a: Vector, b: Vector): Vector => { // vector subtraction (a - b)\n    const x = a[0] - b[0];\n    const y = a[1] - b[1];\n    const z = a[2] - b[2];\n    return [x, y, z];\n  };\n  const crossVectors = (a: Vector, b: Vector): Vector => { // vector cross product (a x b)\n    const x = a[1] * b[2] - a[2] * b[1];\n    const y = a[2] * b[0] - a[0] * b[2];\n    const z = a[0] * b[1] - a[1] * b[0];\n    return [x, y, z];\n  };\n  // 3x3 rotation matrix to Euler angles based on https://www.geometrictools.com/Documentation/EulerAngles.pdf\n  const rotationMatrixToEulerAngle = (r: number[]): { pitch: number, yaw: number, roll: number } => {\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const [r00, _r01, _r02, r10, r11, r12, r20, r21, r22] = r;\n    let thetaX: number;\n    let thetaY: number;\n    let thetaZ: number;\n    if (r10 < 1) { // YZX calculation\n      if (r10 > -1) {\n        thetaZ = Math.asin(r10);\n        thetaY = Math.atan2(-r20, r00);\n        thetaX = Math.atan2(-r12, r11);\n      } else {\n        thetaZ = -Math.PI / 2;\n        thetaY = -Math.atan2(r21, r22);\n        thetaX = 0;\n      }\n    } else {\n      thetaZ = Math.PI / 2;\n      thetaY = Math.atan2(r21, r22);\n      thetaX = 0;\n    }\n    if (isNaN(thetaX)) thetaX = 0;\n    if (isNaN(thetaY)) thetaY = 0;\n    if (isNaN(thetaZ)) thetaZ = 0;\n    return { pitch: 2 * -thetaX, yaw: 2 * -thetaY, roll: 2 * -thetaZ };\n  };\n\n  /*\n  const meshToEulerAngle = (mesh) => { // simple Euler angle calculation based existing 3D mesh\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    return { // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees, value of 0 means center\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face // pitch is face move up/down\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye // yaw is face turn left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye // roll is face lean left/right\n    };\n  };\n  */\n\n  // initialize gaze and mesh\n  const mesh = face.meshRaw;\n  if (!mesh || mesh.length < 300) return { angle: { pitch: 0, yaw: 0, roll: 0 }, matrix: [1, 0, 0, 0, 1, 0, 0, 0, 1], gaze: { bearing: 0, strength: 0 } };\n\n  const size = Math.max(face.boxRaw[2] * imageSize[0], face.boxRaw[3] * imageSize[1]) / 1.5;\n  // top, bottom, left, right\n  const pts: Point[] = [mesh[10], mesh[152], mesh[234], mesh[454]].map((pt) => [pt[0] * imageSize[0] / size, pt[1] * imageSize[1] / size, pt[2]] as Point); // make the xyz coordinates proportional, independent of the image/box size\n\n  const y_axis = normalize(subVectors(pts[1] as Vector, pts[0] as Vector));\n  let x_axis = normalize(subVectors(pts[3] as Vector, pts[2] as Vector));\n  const z_axis = normalize(crossVectors(x_axis, y_axis));\n  // adjust x_axis to make sure that all axes are perpendicular to each other\n  x_axis = crossVectors(y_axis, z_axis);\n\n  // Rotation Matrix from Axis Vectors - http://renderdan.blogspot.com/2006/05/rotation-matrix-from-axis-vectors.html\n  // 3x3 rotation matrix is flatten to array in row-major order. Note that the rotation represented by this matrix is inverted.\n  const matrix: [number, number, number, number, number, number, number, number, number] = [\n    x_axis[0], x_axis[1], x_axis[2],\n    y_axis[0], y_axis[1], y_axis[2],\n    z_axis[0], z_axis[1], z_axis[2],\n  ];\n  const angle = rotationMatrixToEulerAngle(matrix);\n  // const angle = meshToEulerAngle(mesh);\n\n  // we have iris keypoints so we can calculate gaze direction\n  const gaze = mesh.length === 478 ? calculateGaze(face) : { bearing: 0, strength: 0 };\n\n  return { angle, matrix, gaze };\n};\n", "/**\n * Face algorithm implementation\n * Uses FaceMesh, Emotion and FaceRes models to create a unified pipeline\n */\n\nimport { log, now } from '../util/util';\nimport { env } from '../util/env';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as facemesh from './facemesh';\nimport * as emotion from '../gear/emotion';\nimport * as faceres from './faceres';\nimport * as mask from './mask';\nimport * as antispoof from './antispoof';\nimport * as liveness from './liveness';\nimport * as gear from '../gear/gear';\nimport * as ssrnetAge from '../gear/ssrnet-age';\nimport * as ssrnetGender from '../gear/ssrnet-gender';\nimport * as mobilefacenet from './mobilefacenet';\nimport type { FaceResult, Emotion, Gender, Race } from '../result';\nimport type { Tensor } from '../tfjs/types';\nimport type { Human } from '../human';\nimport { calculateFaceAngle } from './angles';\n\ntype DescRes = { age: number, gender: Gender, genderScore: number, descriptor: number[], race?: { score: number, race: Race }[] };\n\nexport const detectFace = async (instance: Human /* instance of human */, input: Tensor): Promise<FaceResult[]> => {\n  // run facemesh, includes blazeface and iris\n  // eslint-disable-next-line no-async-promise-executor\n  let timeStamp: number = now();\n  let ageRes: { age: number } | Promise<{ age: number }> | null;\n  let gearRes: gear.GearType | Promise<gear.GearType> | null;\n  let genderRes: { gender: string, genderScore: number } | Promise<{ gender: string, genderScore: number }> | null;\n  let emotionRes: { score: number, emotion: Emotion }[] | Promise<{ score: number, emotion: Emotion }[]>;\n  let mobilefacenetRes: number[] | Promise<number[]> | null;\n  let antispoofRes: number | Promise<number> | null;\n  let livenessRes: number | Promise<number> | null;\n  let descRes: DescRes | Promise<DescRes> | null;\n\n  const faceRes: Array<FaceResult> = [];\n  instance.state = 'run:face';\n\n  const faces = await facemesh.predict(input, instance.config);\n  instance.performance.face = env.perfadd ? (instance.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n  if (!input.shape || input.shape.length !== 4) return [];\n  if (!faces) return [];\n  // for (const face of faces) {\n  for (let i = 0; i < faces.length; i++) {\n    instance.analyze('Get Face');\n\n    // is something went wrong, skip the face\n    // @ts-ignore possibly undefied\n    if (!faces[i].tensor || faces[i].tensor['isDisposedInternal']) {\n      log('Face object is disposed:', faces[i].tensor);\n      continue;\n    }\n\n    // optional face mask\n    if (instance.config.face.detector?.mask) {\n      const masked = await mask.mask(faces[i]);\n      tf.dispose(faces[i].tensor);\n      faces[i].tensor = masked as Tensor;\n    }\n\n    // calculate face angles\n    const rotation = faces[i].mesh && (faces[i].mesh.length > 200) ? calculateFaceAngle(faces[i], [input.shape[2], input.shape[1]]) : null;\n\n    // run emotion, inherits face from blazeface\n    instance.analyze('Start Emotion:');\n    if (instance.config.async) {\n      emotionRes = instance.config.face.emotion?.enabled ? emotion.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : [];\n    } else {\n      instance.state = 'run:emotion';\n      timeStamp = now();\n      emotionRes = instance.config.face.emotion?.enabled ? await emotion.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : [];\n      instance.performance.emotion = env.perfadd ? (instance.performance.emotion || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End Emotion:');\n\n    // run antispoof, inherits face from blazeface\n    instance.analyze('Start AntiSpoof:');\n    if (instance.config.async) {\n      antispoofRes = instance.config.face.antispoof?.enabled ? antispoof.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n    } else {\n      instance.state = 'run:antispoof';\n      timeStamp = now();\n      antispoofRes = instance.config.face.antispoof?.enabled ? await antispoof.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n      instance.performance.antispoof = env.perfadd ? (instance.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End AntiSpoof:');\n\n    // run liveness, inherits face from blazeface\n    instance.analyze('Start Liveness:');\n    if (instance.config.async) {\n      livenessRes = instance.config.face.liveness?.enabled ? liveness.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n    } else {\n      instance.state = 'run:liveness';\n      timeStamp = now();\n      livenessRes = instance.config.face.liveness?.enabled ? await liveness.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n      instance.performance.liveness = env.perfadd ? (instance.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End Liveness:');\n\n    // run gear, inherits face from blazeface\n    instance.analyze('Start GEAR:');\n    if (instance.config.async) {\n      gearRes = instance.config.face['gear']?.enabled ? gear.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:gear';\n      timeStamp = now();\n      gearRes = instance.config.face['gear']?.enabled ? await gear.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.gear = Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End GEAR:');\n\n    // run gear, inherits face from blazeface\n    instance.analyze('Start SSRNet:');\n    if (instance.config.async) {\n      ageRes = instance.config.face['ssrnet']?.enabled ? ssrnetAge.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      genderRes = instance.config.face['ssrnet']?.enabled ? ssrnetGender.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:ssrnet';\n      timeStamp = now();\n      ageRes = instance.config.face['ssrnet']?.enabled ? await ssrnetAge.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      genderRes = instance.config.face['ssrnet']?.enabled ? await ssrnetGender.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.ssrnet = Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End SSRNet:');\n\n    // run gear, inherits face from blazeface\n    instance.analyze('Start MobileFaceNet:');\n    if (instance.config.async) {\n      mobilefacenetRes = instance.config.face['mobilefacenet']?.enabled ? mobilefacenet.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:mobilefacenet';\n      timeStamp = now();\n      mobilefacenetRes = instance.config.face['mobilefacenet']?.enabled ? await mobilefacenet.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.mobilefacenet = Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End MobileFaceNet:');\n\n    // run emotion, inherits face from blazeface\n    instance.analyze('Start Description:');\n    if (instance.config.async) {\n      descRes = instance.config.face.description?.enabled ? faceres.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:description';\n      timeStamp = now();\n      descRes = instance.config.face.description?.enabled ? await faceres.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.description = env.perfadd ? (instance.performance.description || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End Description:');\n\n    // if async wait for results\n    if (instance.config.async) {\n      [ageRes, genderRes, emotionRes, mobilefacenetRes, descRes, gearRes, antispoofRes, livenessRes] = await Promise.all([ageRes, genderRes, emotionRes, mobilefacenetRes, descRes, gearRes, antispoofRes, livenessRes]);\n    }\n    instance.analyze('Finish Face:');\n\n    if (instance.config.face['ssrnet']?.enabled && ageRes && genderRes) { // override age/gender if ssrnet model is used\n      descRes = {\n        ...(descRes as DescRes),\n        age: (ageRes as { age: number}).age,\n        gender: (genderRes as { gender: Gender, genderScore: number }).gender,\n        genderScore: (genderRes as { gender: Gender, genderScore: number }).genderScore,\n      };\n    }\n    if (instance.config.face['gear']?.enabled && gearRes) { // override age/gender/race if gear model is used\n      descRes = {\n        ...(descRes as DescRes),\n        age: (gearRes as gear.GearType).age,\n        gender: (gearRes as gear.GearType).gender,\n        genderScore: (gearRes as gear.GearType).genderScore,\n        race: (gearRes as gear.GearType).race,\n      };\n    }\n    if (instance.config.face['mobilefacenet']?.enabled && mobilefacenetRes) { // override descriptor if embedding model is used\n      (descRes as DescRes).descriptor = mobilefacenetRes as number[];\n    }\n\n    // calculate iris distance\n    // iris: array[ center, left, top, right, bottom]\n    if (!instance.config.face.iris?.enabled) {\n      // if (faces[i]?.annotations?.leftEyeIris) delete faces[i].annotations.leftEyeIris;\n      // if (faces[i]?.annotations?.rightEyeIris) delete faces[i].annotations.rightEyeIris;\n    }\n    const irisSize = (faces[i].annotations && faces[i].annotations.leftEyeIris && faces[i].annotations.leftEyeIris[0] && faces[i].annotations.rightEyeIris && faces[i].annotations.rightEyeIris[0]\n      && (faces[i].annotations.leftEyeIris.length > 0) && (faces[i].annotations.rightEyeIris.length > 0)\n      && (faces[i].annotations.leftEyeIris[0] !== null) && (faces[i].annotations.rightEyeIris[0] !== null))\n      ? Math.max(Math.abs(faces[i].annotations.leftEyeIris[3][0] - faces[i].annotations.leftEyeIris[1][0]), Math.abs(faces[i].annotations.rightEyeIris[4][1] - faces[i].annotations.rightEyeIris[2][1])) / input.shape[2]\n      : 0; // note: average human iris size is 11.7mm\n\n    // optionally return tensor\n    const tensor = instance.config.face.detector?.return ? tf.squeeze(faces[i].tensor) : null;\n    // dispose original face tensor\n    tf.dispose(faces[i].tensor);\n    // delete temp face image\n    if (faces[i].tensor) delete faces[i].tensor;\n    // combine results\n    const res: FaceResult = {\n      ...faces[i],\n      id: i,\n    };\n    if ((descRes as DescRes)?.age) res.age = (descRes as DescRes).age as number;\n    if ((descRes as DescRes)?.gender) res.gender = (descRes as DescRes).gender as Gender;\n    if ((descRes as DescRes)?.genderScore) res.genderScore = (descRes as DescRes)?.genderScore as number;\n    if ((descRes as DescRes)?.descriptor) res.embedding = (descRes as DescRes)?.descriptor as Array<number>;\n    if ((descRes as DescRes)?.race) res.race = (descRes as DescRes)?.race as { score: number, race: Race }[];\n    if (emotionRes) res.emotion = emotionRes as Array<{ score: number, emotion: Emotion }>;\n    if (antispoofRes) res.real = antispoofRes as number;\n    if (livenessRes) res.live = livenessRes as number;\n    if (irisSize && irisSize !== 0) res.iris = Math.trunc(500 / irisSize / 11.7) / 100;\n    if (rotation) res.rotation = rotation;\n    if (tensor) res.tensor = tensor;\n    faceRes.push(res);\n    instance.analyze('End Face');\n  }\n  instance.analyze('End FaceMesh:');\n  if (instance.config.async) {\n    if (instance.performance.face) delete instance.performance.face;\n    if (instance.performance.age) delete instance.performance.age;\n    if (instance.performance.gender) delete instance.performance.gender;\n    if (instance.performance.emotion) delete instance.performance.emotion;\n  }\n  return faceRes;\n};\n", "/**\n * Gesture detection algorithm\n */\n\nimport type { GestureResult, BodyResult, FaceResult, HandResult, Point } from '../result';\nimport * as fingerPose from '../hand/fingerpose';\n\n/** face gesture type */\nexport type FaceGesture =\n  `facing ${'left' | 'center' | 'right'}`\n  | `blink ${'left' | 'right'} eye`\n  | `mouth ${number}% open`\n  | `head ${'up' | 'down'}`;\n\n/** iris gesture type */\nexport type IrisGesture =\n  'facing center'\n  | `looking ${'left' | 'right' | 'up' | 'down'}`\n  | 'looking center';\n\n/** body gesture type */\nexport type BodyGesture =\n  `leaning ${'left' | 'right'}`\n  | `raise ${'left' | 'right'} hand`\n  | 'i give up';\n\n/** hand gesture type */\nexport type HandGesture =\n  `${'thumb' | 'index' | 'middle' | 'ring' | 'pinky'} forward`\n  | `${'thumb' | 'index' | 'middle' | 'ring' | 'pinky'} up`\n  | 'victory'\n  | 'thumbs up';\n\nexport const body = (res: BodyResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: BodyGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position[1] < nose.position[1]) && (rightWrist.position[1] < nose.position[1])) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position[1] < nose.position[1])) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position[1] < nose.position[1])) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder && Math.abs(leftShoulder.positionRaw[1] - rightShoulder.positionRaw[1]) > 0.1) {\n      gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position[1] > rightShoulder.position[1]) ? 'left' : 'right'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const face = (res: FaceResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: FaceGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 450) {\n      const zDiff = (res[i].mesh[33][2] || 0) - (res[i].mesh[263][2] || 0);\n      const xDiff = res[i].mesh[33][0] - res[i].mesh[263][0];\n      if (Math.abs(zDiff / xDiff) <= 0.15) gestures.push({ face: i, gesture: 'facing center' });\n      else gestures.push({ face: i, gesture: `facing ${zDiff < 0 ? 'left' : 'right'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2] || 0;\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res: FaceResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: IrisGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.leftEyeIris[0] || !res[i].annotations.rightEyeIris || !res[i].annotations.rightEyeIris[0]) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    let center = false;\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) {\n      center = true;\n      gestures.push({ iris: i, gesture: 'facing center' });\n    }\n\n    const leftIrisCenterX = Math.abs(res[i].mesh[263][0] - res[i].annotations.leftEyeIris[0][0]) / res[i].box[2];\n    const rightIrisCenterX = Math.abs(res[i].mesh[33][0] - res[i].annotations.rightEyeIris[0][0]) / res[i].box[2];\n    if (leftIrisCenterX > 0.06 || rightIrisCenterX > 0.06) center = false;\n    if (leftIrisCenterX > rightIrisCenterX) { // check eye with bigger offset\n      if (leftIrisCenterX > 0.05) gestures.push({ iris: i, gesture: 'looking right' });\n    } else {\n      if (rightIrisCenterX > 0.05) gestures.push({ iris: i, gesture: 'looking left' });\n    }\n\n    const rightIrisCenterY = Math.abs(res[i].mesh[145][1] - res[i].annotations.rightEyeIris[0][1]) / res[i].box[3];\n    const leftIrisCenterY = Math.abs(res[i].mesh[374][1] - res[i].annotations.leftEyeIris[0][1]) / res[i].box[3];\n    if (leftIrisCenterY < 0.01 || rightIrisCenterY < 0.01 || leftIrisCenterY > 0.022 || rightIrisCenterY > 0.022) center = false;\n    if (leftIrisCenterY < 0.01 || rightIrisCenterY < 0.01) gestures.push({ iris: i, gesture: 'looking down' });\n    if (leftIrisCenterY > 0.022 || rightIrisCenterY > 0.022) gestures.push({ iris: i, gesture: 'looking up' });\n\n    // still center;\n    if (center) gestures.push({ iris: i, gesture: 'looking center' });\n  }\n  return gestures;\n};\n\nexport const hand = (res: HandResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: HandGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: Point }> = [];\n    if (res[i]['annotations']) {\n      for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n        if (finger !== 'palmBase' && Array.isArray(pos) && pos[0]) fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n      }\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => ((best.position[2] || 0) < (a.position[2] || 0) ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward` as HandGesture });\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${highest.name} up` as HandGesture });\n    }\n    if (res[i]['keypoints']) {\n      const poses = fingerPose.match(res[i]['keypoints']);\n      for (const pose of poses) gestures.push({ hand: i, gesture: pose.name as HandGesture });\n    }\n  }\n  return gestures;\n};\n", "/**\n * Results interpolation for smoothening of video detection results inbetween detected frames\n */\n\nimport type { Result, FaceResult, BodyResult, HandResult, ObjectResult, GestureResult, PersonResult, Box, Point, BodyLandmark, BodyAnnotation } from '../result';\nimport type { Config } from '../config';\n\nimport * as moveNetCoords from '../body/movenetcoords';\nimport * as blazePoseCoords from '../body/blazeposecoords';\nimport * as efficientPoseCoords from '../body/efficientposecoords';\nimport { now } from './util';\nimport { env } from './env';\n\nconst bufferedResult: Result = { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0, error: null };\nlet interpolateTime = 0;\n\nexport function calc(newResult: Result, config: Config): Result {\n  const t0 = now();\n  if (!newResult) return { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0, error: null };\n  // each record is only updated using deep clone when number of detected record changes, otherwise it will converge by itself\n  // otherwise bufferedResult is a shallow clone of result plus updated local calculated values\n  // thus mixing by-reference and by-value assignments to minimize memory operations\n\n  const elapsed = Date.now() - newResult.timestamp;\n  // curve fitted: buffer = 8 - ln(delay)\n  // interpolation formula: current = ((buffer - 1) * previous + live) / buffer\n  // - at  50ms delay buffer = ~4.1 => 28% towards live data\n  // - at 250ms delay buffer = ~2.5 => 40% towards live data\n  // - at 500ms delay buffer = ~1.8 => 55% towards live data\n  // - at 750ms delay buffer = ~1.4 => 71% towards live data\n  // - at  1sec delay buffer = 1 which means live data is used\n  const bufferedFactor = elapsed < 1000 ? 8 - Math.log(elapsed + 1) : 1;\n\n  if (newResult.canvas) bufferedResult.canvas = newResult.canvas;\n  if (newResult.error) bufferedResult.error = newResult.error;\n\n  // interpolate body results\n  if (!bufferedResult.body || (newResult.body.length !== bufferedResult.body.length)) {\n    bufferedResult.body = JSON.parse(JSON.stringify(newResult.body as BodyResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.body.length; i++) {\n      const box = newResult.body[i].box // update box\n        .map((newBoxCoord, j) => ((bufferedFactor - 1) * bufferedResult.body[i].box[j] + newBoxCoord) / bufferedFactor) as Box;\n      const boxRaw = newResult.body[i].boxRaw // update boxRaw\n        .map((newBoxCoord, j) => ((bufferedFactor - 1) * bufferedResult.body[i].boxRaw[j] + newBoxCoord) / bufferedFactor) as Box;\n      const keypoints = (newResult.body[i].keypoints // update keypoints\n        .map((newKpt, j) => ({\n          score: newKpt.score,\n          part: newKpt.part as BodyLandmark,\n          position: [\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].position[0] || 0) + (newKpt.position[0] || 0)) / bufferedFactor : newKpt.position[0],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].position[1] || 0) + (newKpt.position[1] || 0)) / bufferedFactor : newKpt.position[1],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].position[2] || 0) + (newKpt.position[2] || 0)) / bufferedFactor : newKpt.position[2],\n          ],\n          positionRaw: [\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].positionRaw[0] || 0) + (newKpt.positionRaw[0] || 0)) / bufferedFactor : newKpt.positionRaw[0],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].positionRaw[1] || 0) + (newKpt.positionRaw[1] || 0)) / bufferedFactor : newKpt.positionRaw[1],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].positionRaw[2] || 0) + (newKpt.positionRaw[2] || 0)) / bufferedFactor : newKpt.positionRaw[2],\n          ],\n          distance: [\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].distance?.[0] || 0) + (newKpt.distance?.[0] || 0)) / bufferedFactor : newKpt.distance?.[0],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].distance?.[1] || 0) + (newKpt.distance?.[1] || 0)) / bufferedFactor : newKpt.distance?.[1],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].distance?.[2] || 0) + (newKpt.distance?.[2] || 0)) / bufferedFactor : newKpt.distance?.[2],\n          ],\n        }))) as Array<{ score: number, part: BodyLandmark, position: [number, number, number?], positionRaw: [number, number, number?] }>;\n\n      const annotations: Record<BodyAnnotation, Point[][]> = {} as Record<BodyAnnotation, Point[][]>; // recreate annotations\n      let coords = { connected: {} };\n      if (config.body?.modelPath?.includes('efficientpose')) coords = efficientPoseCoords;\n      else if (config.body?.modelPath?.includes('blazepose')) coords = blazePoseCoords;\n      else if (config.body?.modelPath?.includes('movenet')) coords = moveNetCoords;\n      for (const [name, indexes] of Object.entries(coords.connected as Record<string, string[]>)) {\n        const pt: Array<Point[]> = [];\n        for (let j = 0; j < indexes.length - 1; j++) {\n          const pt0 = keypoints.find((kp) => kp.part === indexes[j]);\n          const pt1 = keypoints.find((kp) => kp.part === indexes[j + 1]);\n          // if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n          if (pt0 && pt1) pt.push([pt0.position, pt1.position]);\n        }\n        annotations[name] = pt;\n      }\n      bufferedResult.body[i] = { ...newResult.body[i], box, boxRaw, keypoints, annotations: annotations as BodyResult['annotations'] }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate hand results\n  if (!bufferedResult.hand || (newResult.hand.length !== bufferedResult.hand.length)) {\n    bufferedResult.hand = JSON.parse(JSON.stringify(newResult.hand as HandResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.hand.length; i++) {\n      const box = (newResult.hand[i].box// update box\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.hand[i].box[j] + b) / bufferedFactor)) as Box;\n      const boxRaw = (newResult.hand[i].boxRaw // update boxRaw\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.hand[i].boxRaw[j] + b) / bufferedFactor)) as Box;\n      if (bufferedResult.hand[i].keypoints.length !== newResult.hand[i].keypoints.length) bufferedResult.hand[i].keypoints = newResult.hand[i].keypoints; // reset keypoints as previous frame did not have them\n      const keypoints = newResult.hand[i].keypoints && newResult.hand[i].keypoints.length > 0 ? newResult.hand[i].keypoints // update landmarks\n        .map((landmark, j) => landmark\n          .map((coord, k) => (((bufferedFactor - 1) * (bufferedResult.hand[i].keypoints[j][k] || 1) + (coord || 0)) / bufferedFactor)) as Point)\n        : [];\n      let annotations = {};\n      if (Object.keys(bufferedResult.hand[i].annotations).length !== Object.keys(newResult.hand[i].annotations).length) {\n        bufferedResult.hand[i].annotations = newResult.hand[i].annotations; // reset annotations as previous frame did not have them\n        annotations = bufferedResult.hand[i].annotations;\n      } else if (newResult.hand[i].annotations) {\n        for (const key of Object.keys(newResult.hand[i].annotations)) { // update annotations\n          annotations[key] = newResult.hand[i].annotations[key] && newResult.hand[i].annotations[key][0]\n            ? newResult.hand[i].annotations[key]\n              .map((val, j: number) => val\n                .map((coord: number, k: number) => ((bufferedFactor - 1) * bufferedResult.hand[i].annotations[key][j][k] + coord) / bufferedFactor))\n            : null;\n        }\n      }\n      bufferedResult.hand[i] = { ...newResult.hand[i], box, boxRaw, keypoints, annotations: annotations as HandResult['annotations'] }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate face results\n  if (!bufferedResult.face || (newResult.face.length !== bufferedResult.face.length)) {\n    bufferedResult.face = JSON.parse(JSON.stringify(newResult.face as FaceResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.face.length; i++) {\n      const box = (newResult.face[i].box // update box\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i].box[j] + b) / bufferedFactor)) as Box;\n      const boxRaw = (newResult.face[i].boxRaw // update boxRaw\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i].boxRaw[j] + b) / bufferedFactor)) as Box;\n      if (newResult.face[i].rotation) {\n        const rotation: {\n          matrix: [number, number, number, number, number, number, number, number, number],\n          angle: { roll: number, yaw: number, pitch: number },\n          gaze: { bearing: number, strength: number }\n        } = { matrix: [0, 0, 0, 0, 0, 0, 0, 0, 0], angle: { roll: 0, yaw: 0, pitch: 0 }, gaze: { bearing: 0, strength: 0 } };\n        rotation.matrix = newResult.face[i].rotation?.matrix as [number, number, number, number, number, number, number, number, number];\n        rotation.angle = {\n          roll: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.roll || 0) + (newResult.face[i].rotation?.angle?.roll || 0)) / bufferedFactor,\n          yaw: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.yaw || 0) + (newResult.face[i].rotation?.angle?.yaw || 0)) / bufferedFactor,\n          pitch: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.pitch || 0) + (newResult.face[i].rotation?.angle?.pitch || 0)) / bufferedFactor,\n        };\n        rotation.gaze = {\n          // not fully correct due projection on circle, also causes wrap-around draw on jump from negative to positive\n          bearing: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.gaze?.bearing || 0) + (newResult.face[i].rotation?.gaze?.bearing || 0)) / bufferedFactor,\n          strength: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.gaze?.strength || 0) + (newResult.face[i].rotation?.gaze?.strength || 0)) / bufferedFactor,\n        };\n        bufferedResult.face[i] = { ...newResult.face[i], rotation, box, boxRaw }; // shallow clone plus updated values\n      }\n      bufferedResult.face[i] = { ...newResult.face[i], box, boxRaw }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate object detection results\n  if (!bufferedResult.object || (newResult.object.length !== bufferedResult.object.length)) {\n    bufferedResult.object = JSON.parse(JSON.stringify(newResult.object as ObjectResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.object.length; i++) {\n      const box = (newResult.object[i].box // update box\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.object[i].box[j] + b) / bufferedFactor)) as Box;\n      const boxRaw = (newResult.object[i].boxRaw // update boxRaw\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.object[i].boxRaw[j] + b) / bufferedFactor)) as Box;\n      bufferedResult.object[i] = { ...newResult.object[i], box, boxRaw }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate person results\n  if (newResult.persons) {\n    const newPersons = newResult.persons; // trigger getter function\n    if (!bufferedResult.persons || (newPersons.length !== bufferedResult.persons.length)) {\n      bufferedResult.persons = JSON.parse(JSON.stringify(newPersons as PersonResult[]));\n    } else {\n      for (let i = 0; i < newPersons.length; i++) { // update person box, we don't update the rest as it's updated as reference anyhow\n        bufferedResult.persons[i].box = (newPersons[i].box\n          .map((box, j) => ((bufferedFactor - 1) * bufferedResult.persons[i].box[j] + box) / bufferedFactor)) as Box;\n      }\n    }\n  }\n\n  // just copy latest gestures without interpolation\n  if (newResult.gesture) bufferedResult.gesture = newResult.gesture as GestureResult[];\n\n  // append interpolation performance data\n  const t1 = now();\n  interpolateTime = env.perfadd ? interpolateTime + Math.round(t1 - t0) : Math.round(t1 - t0);\n  if (newResult.performance) bufferedResult.performance = { ...newResult.performance, interpolate: interpolateTime };\n\n  return bufferedResult;\n}\n", "/** Face descriptor type as number array */\nexport type Descriptor = Array<number>\nexport type MatchOptions = { order?: number, threshold?: number, multiplier?: number, min?: number, max?: number } | undefined;\n\n/** Calculates distance between two descriptors\n * @param options - calculation options\n * - order - algorithm to use\n *   Euclidean distance if `order` is 2 (default), Minkowski distance algorithm of nth order if `order` is higher than 2\n * - multiplier - by how much to enhance difference analysis in range of 1..100\n *   default is 20 which normalizes results to similarity above 0.5 can be considered a match\n */\nexport function distance(descriptor1: Descriptor, descriptor2: Descriptor, options: MatchOptions = { order: 2, multiplier: 25 }) {\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  let sum = 0;\n  for (let i = 0; i < descriptor1.length; i++) {\n    const diff = (!options.order || options.order === 2) ? (descriptor1[i] - descriptor2[i]) : (Math.abs(descriptor1[i] - descriptor2[i]));\n    sum += (!options.order || options.order === 2) ? (diff * diff) : (diff ** options.order);\n  }\n  return (options.multiplier || 20) * sum;\n}\n\n// invert distance to similarity, normalize to given range and clamp\nconst normalizeDistance = (dist, order, min, max) => {\n  if (dist === 0) return 1; // short circuit for identical inputs\n  const root = order === 2 ? Math.sqrt(dist) : dist ** (1 / order); // take root of distance\n  const norm = (1 - (root / 100) - min) / (max - min); // normalize to range\n  const clamp = Math.max(Math.min(norm, 1), 0); // clamp to 0..1\n  return clamp;\n};\n\n/** Calculates normalized similarity between two face descriptors based on their `distance`\n * @param options - calculation options\n * - order - algorithm to use\n *   Euclidean distance if `order` is 2 (default), Minkowski distance algorithm of nth order if `order` is higher than 2\n * - multiplier - by how much to enhance difference analysis in range of 1..100\n *   default is 20 which normalizes results to similarity above 0.5 can be considered a match\n * - min - normalize similarity result to a given range\n * - max - normalzie similarity resutl to a given range\n *   default is 0.2...0.8\n * Returns similarity between two face descriptors normalized to 0..1 range where 0 is no similarity and 1 is perfect similarity\n */\nexport function similarity(descriptor1: Descriptor, descriptor2: Descriptor, options: MatchOptions = { order: 2, multiplier: 25, min: 0.2, max: 0.8 }) {\n  const dist = distance(descriptor1, descriptor2, options);\n  return normalizeDistance(dist, options.order || 2, options.min || 0, options.max || 1);\n}\n\n/** Matches given descriptor to a closest entry in array of descriptors\n * @param descriptor - face descriptor\n * @param descriptors - array of face descriptors to commpare given descriptor to\n * @param options - see `similarity` method for options description\n * Returns\n * - `index` index array index where best match was found or -1 if no matches\n * - `distance` calculated `distance` of given descriptor to the best match\n * - `similarity` calculated normalized `similarity` of given descriptor to the best match\n*/\nexport function match(descriptor: Descriptor, descriptors: Array<Descriptor>, options: MatchOptions = { order: 2, multiplier: 25, threshold: 0, min: 0.2, max: 0.8 }) {\n  if (!Array.isArray(descriptor) || !Array.isArray(descriptors) || descriptor.length < 64 || descriptors.length === 0 || descriptor.length !== descriptors[0].length) { // validate input\n    return { index: -1, distance: Number.POSITIVE_INFINITY, similarity: 0 };\n  }\n  let lowestDistance = Number.MAX_SAFE_INTEGER;\n  let index = -1;\n  for (let i = 0; i < descriptors.length; i++) {\n    const res = distance(descriptor, descriptors[i], options);\n    if (res < lowestDistance) {\n      lowestDistance = res;\n      index = i;\n    }\n    if (lowestDistance < (options.threshold || 0)) break;\n  }\n  const normalizedSimilarity = normalizeDistance(lowestDistance, options.order || 2, options.min || 0, options.max || 1);\n  return { index, distance: lowestDistance, similarity: normalizedSimilarity };\n}\n", "/**\n * Analyze detection Results and sort&combine them into per-person view\n */\n\nimport type { FaceResult, BodyResult, HandResult, GestureResult, PersonResult, Box } from '../result';\n\nexport function join(faces: Array<FaceResult>, bodies: Array<BodyResult>, hands: Array<HandResult>, gestures: Array<GestureResult>, shape: Array<number> | undefined): Array<PersonResult> {\n  let id = 0;\n  const persons: Array<PersonResult> = [];\n  for (const face of faces) { // person is defined primarily by face and then we append other objects as found\n    const person: PersonResult = { id: id++, face, body: null, hands: { left: null, right: null }, gestures: [], box: [0, 0, 0, 0] };\n    for (const body of bodies) {\n      if (face.box[0] > body.box[0] // x within body\n        && face.box[0] < body.box[0] + body.box[2]\n        && face.box[1] + face.box[3] > body.box[1] // y within body\n        && face.box[1] + face.box[3] < body.box[1] + body.box[3]) {\n        person.body = body;\n      }\n    }\n    if (person.body) { // only try to join hands if body is found\n      for (const hand of hands) {\n        if (hand.box[0] + hand.box[2] > person.body.box[0] // x within body for left hand\n          && hand.box[0] + hand.box[2] < person.body.box[0] + person.body.box[2]\n          && hand.box[1] + hand.box[3] > person.body.box[1] // x within body for left hand\n          && hand.box[1] + hand.box[3] < person.body.box[1] + person.body.box[3]) {\n          if (person.hands) person.hands.left = hand;\n        }\n        if (hand.box[0] < person.body.box[0] + person.body.box[2] // x within body for right hand\n          && hand.box[0] > person.body.box[0]\n          && hand.box[1] + hand.box[3] > person.body.box[1] // x within body for right hand\n          && hand.box[1] + hand.box[3] < person.body.box[1] + person.body.box[3]) {\n          if (person.hands) person.hands.right = hand;\n        }\n      }\n    }\n    for (const gesture of gestures) { // append all gestures according to ids\n      if (gesture['face'] !== undefined && gesture['face'] === face.id) person.gestures?.push(gesture);\n      else if (gesture['iris'] !== undefined && gesture['iris'] === face.id) person.gestures?.push(gesture);\n      else if (gesture['body'] !== undefined && gesture['body'] === person.body?.id) person.gestures?.push(gesture);\n      else if (gesture['hand'] !== undefined && gesture['hand'] === person.hands?.left?.id) person.gestures?.push(gesture);\n      else if (gesture['hand'] !== undefined && gesture['hand'] === person.hands?.right?.id) person.gestures?.push(gesture);\n    }\n\n    // create new overarching box from all boxes belonging to person\n    const x: number[] = [];\n    const y: number[] = [];\n    const extractXY = (box: Box | undefined) => { // extract all [x, y] coordinates from boxes [x, y, width, height]\n      if (box && box.length === 4) {\n        x.push(box[0], box[0] + box[2]);\n        y.push(box[1], box[1] + box[3]);\n      }\n    };\n    extractXY(person.face?.box);\n    extractXY(person.body?.box);\n    extractXY(person.hands?.left?.box);\n    extractXY(person.hands?.right?.box);\n    const minX = Math.min(...x);\n    const minY = Math.min(...y);\n    person.box = [minX, minY, Math.max(...x) - minX, Math.max(...y) - minY]; // create new overarching box\n\n    // shape is known so we calculate boxRaw as well\n    if (shape && shape[1] && shape[2]) person.boxRaw = [person.box[0] / shape[2], person.box[1] / shape[1], person.box[2] / shape[2], person.box[3] / shape[1]];\n\n    persons.push(person);\n  }\n  return persons;\n}\n", "/**\n * Embedded sample images used during warmup in dataURL format\n */\n\n// data:image/jpeg;base64,\nexport const face = `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`;\n\n// data:image/jpeg;base64,\nexport const body = `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\n2Q==`;\n", "/**\n * Warmup algorithm that uses embedded images to exercise loaded models for faster future inference\n */\n\nimport { log, now, mergeDeep } from './util/util';\nimport * as sample from './sample';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as image from './image/image';\nimport { env } from './util/env';\nimport type { Config } from './config';\nimport type { Result } from './result';\nimport type { Human, Models } from './human';\nimport type { Tensor } from './tfjs/types';\n\nasync function warmupBitmap(instance: Human): Promise<Result | undefined> {\n  const b64toBlob = (base64: string, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n  let blob;\n  let res;\n  switch (instance.config.warmup) {\n    case 'face': blob = await b64toBlob(sample.face); break;\n    case 'body':\n    case 'full': blob = await b64toBlob(sample.body); break;\n    default: blob = null;\n  }\n  if (blob) {\n    const bitmap = await createImageBitmap(blob);\n    res = await instance.detect(bitmap, instance.config);\n    bitmap.close();\n  }\n  return res;\n}\n\nasync function warmupCanvas(instance: Human): Promise<Result | undefined> {\n  return new Promise((resolve) => {\n    let src;\n    // let size = 0;\n    switch (instance.config.warmup) {\n      case 'face':\n        // size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        // size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    let img: HTMLImageElement;\n    if (typeof Image !== 'undefined') img = new Image();\n    // @ts-ignore env.image is an external monkey-patch\n    else if (env.Image) img = new env.Image();\n    else return;\n    img.onload = async () => {\n      const canvas = image.canvas(img.naturalWidth, img.naturalHeight);\n      if (!canvas) {\n        log('Warmup: Canvas not found');\n        resolve(undefined);\n      } else {\n        const ctx = canvas.getContext('2d');\n        if (ctx) ctx.drawImage(img, 0, 0);\n        // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n        const tensor = await instance.image(canvas);\n        const res = await instance.detect(tensor.tensor as Tensor, instance.config);\n        resolve(res);\n      }\n    };\n    if (src) img.src = src;\n    else resolve(undefined);\n  });\n}\n\nasync function warmupNode(instance: Human): Promise<Result | undefined> {\n  const atob = (str: string) => Buffer.from(str, 'base64');\n  let img;\n  if (instance.config.warmup === 'face') img = atob(sample.face);\n  else img = atob(sample.body);\n  let res;\n  if ('node' in tf) {\n    // @ts-ignore tf.node may be undefined\n    const data = tf['node'].decodeJpeg(img);\n    const expanded = data.expandDims(0);\n    instance.tf.dispose(data);\n    // log('Input:', expanded);\n    res = await instance.detect(expanded, instance.config);\n    instance.tf.dispose(expanded);\n  } else {\n    if (instance.config.debug) log('Warmup tfjs-node not loaded');\n    /*\n    const input = await canvasJS.loadImage(img);\n    const canvas = canvasJS.createCanvas(input.width, input.height);\n    const ctx = canvas.getContext('2d');\n    ctx.drawImage(img, 0, 0, input.width, input.height);\n    res = await instance.detect(input, instance.config);\n    */\n  }\n  return res;\n}\n\nasync function runInference(instance: Human) {\n  let res: Result | undefined;\n  if (typeof createImageBitmap === 'function') res = await warmupBitmap(instance);\n  else if (typeof Image !== 'undefined' || env.Canvas !== undefined) res = await warmupCanvas(instance);\n  else res = await warmupNode(instance);\n  return res;\n}\n\n/** Runs pre-compile on all loaded models */\nexport async function runCompile(allModels: Models) {\n  const backendType = tf.getBackend();\n  const webGLBackend = tf.backend();\n  if ((backendType !== 'webgl' && backendType !== 'humangl') || (!webGLBackend || !webGLBackend.checkCompileCompletion)) {\n    // log('compile pass: skip');\n    return;\n  }\n  tf.env().set('ENGINE_COMPILE_ONLY', true);\n  const numTensorsStart = tf.engine().state.numTensors;\n  const compiledModels: string[] = [];\n  for (const [modelName, model] of Object.entries(allModels).filter(([key, val]) => (key !== null && val !== null))) {\n    const shape = (model.inputs && model.inputs[0] && model.inputs[0].shape) ? [...model.inputs[0].shape] : [1, 64, 64, 3];\n    const dtype = (model.inputs && model.inputs[0] && model.inputs[0].dtype) ? model.inputs[0].dtype : 'float32';\n    for (let dim = 0; dim < shape.length; dim++) {\n      if (shape[dim] === -1) shape[dim] = dim === 0 ? 1 : 64; // override batch number and any dynamic dimensions\n    }\n    const tensor = tf.zeros(shape, dtype);\n    // const res = await model.executeAsync(tensor); // fails with current tfjs\n    try {\n      const res = model.execute(tensor);\n      compiledModels.push(modelName);\n      if (Array.isArray(res)) res.forEach((t) => tf.dispose(t));\n      else tf.dispose(res);\n    } catch {\n      log('compile fail model:', modelName);\n    }\n    tf.dispose(tensor);\n  }\n  const kernels = await webGLBackend.checkCompileCompletionAsync();\n  webGLBackend.getUniformLocations();\n  log('compile pass models:', compiledModels);\n  log('compile pass kernels:', kernels.length);\n  tf.env().set('ENGINE_COMPILE_ONLY', false);\n  const numTensorsEnd = tf.engine().state.numTensors;\n  if ((numTensorsEnd - numTensorsStart) > 0) log('tensor leak:', numTensorsEnd - numTensorsStart);\n}\n\n/** Warmup method pre-initializes all configured models for faster inference\n * - can take significant time on startup\n * - only used in browser environments for `webgl` and `humangl` backends\n * @param userConfig?: Config\n*/\nexport async function warmup(instance: Human, userConfig?: Partial<Config>): Promise<Result | undefined> {\n  const t0 = now();\n  instance.state = 'warmup';\n  if (userConfig) instance.config = mergeDeep(instance.config, userConfig) as Config;\n  if (!instance.config.warmup || instance.config.warmup.length === 0 || instance.config.warmup === 'none') {\n    return { face: [], body: [], hand: [], gesture: [], object: [], performance: instance.performance, timestamp: now(), persons: [], error: null };\n  }\n  return new Promise(async (resolve) => {\n    await runCompile(instance.models);\n    const res = await runInference(instance);\n    const t1 = now();\n    if (instance.config.debug) log('warmup', instance.config.warmup, Math.round(t1 - t0), 'ms');\n    instance.emit('warmup');\n    resolve(res);\n  });\n}\n", "/**\n * Human main module\n * @default Human Library\n * @summary <https://github.com/vladmandic/human>\n * @author <https://github.com/vladmandic>\n * @copyright <https://github.com/vladmandic>\n * @license MIT\n */\n\n// module imports\nimport { log, now, mergeDeep, validate } from './util/util';\nimport { defaults } from './config';\nimport { env, Env } from './util/env';\nimport { setModelLoadOptions } from './tfjs/load';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as app from '../package.json';\nimport * as backend from './tfjs/backend';\nimport * as blazepose from './body/blazepose';\nimport * as centernet from './object/centernet';\nimport * as draw from './draw/draw';\nimport * as efficientpose from './body/efficientpose';\nimport * as face from './face/face';\nimport * as facemesh from './face/facemesh';\nimport * as faceres from './face/faceres';\nimport * as gesture from './gesture/gesture';\nimport * as handpose from './hand/handpose';\nimport * as handtrack from './hand/handtrack';\nimport * as humangl from './tfjs/humangl';\nimport * as image from './image/image';\nimport * as interpolate from './util/interpolate';\nimport * as match from './face/match';\nimport * as models from './models';\nimport * as movenet from './body/movenet';\nimport * as nanodet from './object/nanodet';\nimport * as persons from './util/persons';\nimport * as posenet from './body/posenet';\nimport * as segmentation from './segmentation/segmentation';\nimport * as warmups from './warmup';\n// type definitions\nimport type { Input, Tensor, DrawOptions, Config, Result, FaceResult, HandResult, BodyResult, ObjectResult, GestureResult, PersonResult, AnyCanvas, ModelStats } from './exports';\n// type exports\nexport * from './exports';\n\n/** **Human** library main class\n *\n * All methods and properties are available only as members of Human class\n *\n * - Configuration object definition: {@link Config}\n * - Results object definition: {@link Result}\n * - Possible inputs: {@link Input}\n *\n * @param userConfig - {@link Config}\n * @returns instance of {@link Human}\n */\nexport class Human {\n  /** Current version of Human library in *semver* format */\n  version: string;\n\n  /** Current configuration\n   * - Defaults: [config](https://github.com/vladmandic/human/blob/main/src/config.ts#L262)\n   */\n  config: Config;\n\n  /** Last known result of detect run\n   * - Can be accessed anytime after initial detection\n  */\n  result: Result;\n\n  /** Current state of Human library\n   * - Can be polled to determine operations that are currently executed\n   * - Progresses through: 'config', 'check', 'backend', 'load', 'run:<model>', 'idle'\n   */\n  state: string;\n\n  /** currenty processed image tensor and canvas */\n  process: { tensor: Tensor | null, canvas: AnyCanvas | null };\n\n  /** Instance of TensorFlow/JS used by Human\n   *  - Can be embedded or externally provided\n   * [TFJS API](https://js.tensorflow.org/api/latest/)\n   */\n  tf;\n\n  /** Object containing environment information used for diagnostics */\n  env: Env;\n\n  /** Draw helper classes that can draw detected objects on canvas using specified draw\n   * - canvas: draws input to canvas\n   * - options: are global settings for all draw operations, can be overriden for each draw method {@link DrawOptions}\n   * - face, body, hand, gesture, object, person: draws detected results as overlays on canvas\n   */\n  draw: { canvas: typeof draw.canvas, face: typeof draw.face, body: typeof draw.body, hand: typeof draw.hand, gesture: typeof draw.gesture, object: typeof draw.object, person: typeof draw.person, all: typeof draw.all, options: DrawOptions };\n\n  /** Currently loaded models\n   * @internal\n   * {@link Models}\n  */\n  models: models.Models;\n\n  /** Container for events dispatched by Human\n   * Possible events:\n   * - `create`: triggered when Human object is instantiated\n   * - `load`: triggered when models are loaded (explicitly or on-demand)\n   * - `image`: triggered when input image is processed\n   * - `result`: triggered when detection is complete\n   * - `warmup`: triggered when warmup is complete\n   * - `error`: triggered on some errors\n   */\n  events: EventTarget | undefined;\n  /** Reference face triangualtion array of 468 points, used for triangle references between points */\n  faceTriangulation: number[];\n  /** Refernce UV map of 468 values, used for 3D mapping of the face mesh */\n  faceUVMap: [number, number][];\n  /** Performance object that contains values for all recently performed operations */\n  performance: Record<string, number>; // perf members are dynamically defined as needed\n  #numTensors: number;\n  #analyzeMemoryLeaks: boolean;\n  #checkSanity: boolean;\n  /** WebGL debug info */\n  gl: Record<string, unknown>;\n  // definition end\n\n  /** Constructor for **Human** library that is futher used for all operations\n   * @param userConfig - user configuration object {@link Config}\n   */\n  constructor(userConfig?: Partial<Config>) {\n    this.env = env;\n    /*\n    defaults.wasmPath = tf.version['tfjs-core'].includes('-') // custom build or official build\n      ? 'https://vladmandic.github.io/tfjs/dist/'\n      : `https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${tf.version_core}/dist/`;\n    */\n    const tfVersion = (tf.version?.tfjs || tf.version_core).replace(/-(.*)/, '');\n    defaults.wasmPath = `https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${tfVersion}/dist/`;\n    defaults.modelBasePath = env.browser ? '../models/' : 'file://models/';\n    defaults.backend = env.browser ? 'humangl' : 'tensorflow';\n    this.version = app.version; // expose version property on instance of class\n    Object.defineProperty(this, 'version', { value: app.version }); // expose version property directly on class itself\n    this.config = JSON.parse(JSON.stringify(defaults));\n    Object.seal(this.config);\n    this.config.cacheModels = typeof indexedDB !== 'undefined';\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    setModelLoadOptions(this.config);\n    this.tf = tf;\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.performance = {};\n    this.events = (typeof EventTarget !== 'undefined') ? new EventTarget() : undefined;\n    // object that contains all initialized models\n    this.models = new models.Models();\n    // reexport draw methods\n    this.draw = {\n      options: draw.options as DrawOptions,\n      canvas: (input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas) => draw.canvas(input, output),\n      face: (output: AnyCanvas, result: FaceResult[], options?: Partial<DrawOptions>) => draw.face(output, result, options),\n      body: (output: AnyCanvas, result: BodyResult[], options?: Partial<DrawOptions>) => draw.body(output, result, options),\n      hand: (output: AnyCanvas, result: HandResult[], options?: Partial<DrawOptions>) => draw.hand(output, result, options),\n      gesture: (output: AnyCanvas, result: GestureResult[], options?: Partial<DrawOptions>) => draw.gesture(output, result, options),\n      object: (output: AnyCanvas, result: ObjectResult[], options?: Partial<DrawOptions>) => draw.object(output, result, options),\n      person: (output: AnyCanvas, result: PersonResult[], options?: Partial<DrawOptions>) => draw.person(output, result, options),\n      all: (output: AnyCanvas, result: Result, options?: Partial<DrawOptions>) => draw.all(output, result, options),\n    };\n    this.result = { face: [], body: [], hand: [], gesture: [], object: [], performance: {}, timestamp: 0, persons: [], error: null };\n    // export access to image processing\n    // @ts-ignore eslint-typescript cannot correctly infer type in anonymous function\n    this.process = { tensor: null, canvas: null };\n    // export raw access to underlying models\n    this.faceTriangulation = facemesh.triangulation;\n    this.faceUVMap = facemesh.uvmap;\n    // set gl info\n    this.gl = humangl.config;\n    // include platform info\n    this.emit('create');\n  }\n\n  /** internal function to measure tensor leaks */\n  analyze = (...msg: string[]) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const currentTensors = this.tf.engine().state.numTensors;\n    const previousTensors = this.#numTensors;\n    this.#numTensors = currentTensors;\n    const leaked = currentTensors - previousTensors;\n    if (leaked !== 0) log(...msg, leaked);\n  };\n\n  /** internal function for quick sanity check on inputs @hidden */\n  #sanity = (input: Input): null | string => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.env.node && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  };\n\n  /** Reset configuration to default values */\n  reset(): void {\n    const currentBackend = this.config.backend; // save backend;\n    this.config = JSON.parse(JSON.stringify(defaults));\n    this.config.backend = currentBackend;\n  }\n\n  /** Validate current configuration schema */\n  validate(userConfig?: Partial<Config>) {\n    return validate(defaults, userConfig || this.config);\n  }\n\n  /** Exports face matching methods {@link match#similarity} */\n  public similarity = match.similarity;\n  /** Exports face matching methods {@link match#distance} */\n  public distance = match.distance;\n  /** Exports face matching methods {@link match#match} */\n  public match = match.match;\n\n  /** Utility wrapper for performance.now() */\n  now(): number {\n    return now();\n  }\n\n  /** Process input as return canvas and tensor\n   *\n   * @param input - any input {@link Input}\n   * @param getTensor - should image processing also return tensor or just canvas\n   * Returns object with `tensor` and `canvas`\n   */\n  image(input: Input, getTensor: boolean = true) {\n    return image.process(input, this.config, getTensor);\n  }\n\n  /** Segmentation method takes any input and returns processed canvas with body segmentation\n   *  - Segmentation is not triggered as part of detect process\n   * @param input - {@link Input}\n   * @param background - {@link Input}\n   *  - Optional parameter background is used to fill the background with specific input\n   *  Returns:\n   *  - `data` as raw data array with per-pixel segmentation values\n   *  - `canvas` as canvas which is input image filtered with segementation data and optionally merged with background image. canvas alpha values are set to segmentation values for easy merging\n   *  - `alpha` as grayscale canvas that represents segmentation alpha values\n   */\n  async segmentation(input: Input, background?: Input): Promise<{ data: number[] | Tensor, canvas: AnyCanvas | null, alpha: AnyCanvas | null }> {\n    return segmentation.process(input, background, this.config);\n  }\n\n  /** Enhance method performs additional enhacements to face image previously detected for futher processing\n   *\n   * @param input - Tensor as provided in human.result.face[n].tensor\n   * @returns Tensor\n   */\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return faceres.enhance(input);\n  }\n\n  /** Compare two input tensors for pixel simmilarity\n   * - use `human.image` to process any valid input and get a tensor that can be used for compare\n   * - when passing manually generated tensors:\n   *  - both input tensors must be in format [1, height, width, 3]\n   *  - if resolution of tensors does not match, second tensor will be resized to match resolution of the first tensor\n   * - return value is pixel similarity score normalized by input resolution and rgb channels\n  */\n  compare(firstImageTensor: Tensor, secondImageTensor: Tensor): Promise<number> {\n    return image.compare(this.config, firstImageTensor, secondImageTensor);\n  }\n\n  /** Explicit backend initialization\n   *  - Normally done implicitly during initial load phase\n   *  - Call to explictly register and initialize TFJS backend without any other operations\n   *  - Use when changing backend during runtime\n   */\n  async init(): Promise<void> {\n    await backend.check(this, true);\n    await this.tf.ready();\n  }\n\n  /** Load method preloads all configured models on-demand\n   * - Not explicitly required as any required model is load implicitly on it's first run\n   *\n   * @param userConfig - {@link Config}\n  */\n  async load(userConfig?: Partial<Config>): Promise<void> {\n    this.state = 'load';\n    const timeStamp = now();\n    const count = Object.values(this.models).filter((model) => model).length;\n    if (userConfig) this.config = mergeDeep(this.config, userConfig) as Config;\n\n    if (this.env.initial) { // print version info on first run and check for correct backend setup\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version['tfjs-core']}`);\n      if (!await backend.check(this)) log('error: backend check failed');\n      await tf.ready();\n      if (this.env.browser) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('environment:', this.env);\n        if (this.config.debug) log('tf flags:', this.tf.ENV['flags']);\n      }\n    }\n\n    await models.load(this); // actually loads models\n    if (this.env.initial && this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors'); // print memory stats on first run\n    this.env.initial = false;\n\n    const loaded = Object.values(this.models).filter((model) => model).length;\n    if (loaded !== count) { // number of loaded models changed\n      await models.validate(this); // validate kernel ops used by model against current backend\n      this.emit('load');\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.performance.loadModels as number || 0)) this.performance.loadModels = this.env.perfadd ? (this.performance.loadModels || 0) + current : current;\n  }\n\n  /** emit event */\n  emit = (event: string) => {\n    if (this.events && this.events.dispatchEvent) this.events?.dispatchEvent(new Event(event));\n  };\n\n  /** Runs interpolation using last known result and returns smoothened result\n   * Interpolation is based on time since last known result so can be called independently\n   *\n   * @param result - {@link Result} optional use specific result set to run interpolation on\n   * @returns result - {@link Result}\n   */\n  next(result: Result = this.result): Result {\n    return interpolate.calc(result, this.config) as Result;\n  }\n\n  /** get model loading/loaded stats */\n  getModelStats(): ModelStats { return models.getModelStats(this); }\n\n  /** Warmup method pre-initializes all configured models for faster inference\n   * - can take significant time on startup\n   * - only used for `webgl` and `humangl` backends\n   * @param userConfig - {@link Config}\n   * @returns result - {@link Result}\n  */\n  async warmup(userConfig?: Partial<Config>) {\n    const t0 = now();\n    const res = await warmups.warmup(this, userConfig);\n    const t1 = now();\n    this.performance.warmup = Math.trunc(t1 - t0);\n    return res;\n  }\n\n  /** Run detect with tensorflow profiling\n   * - result object will contain total exeuction time information for top-20 kernels\n   * - actual detection object can be accessed via `human.result`\n  */\n  async profile(input: Input, userConfig?: Partial<Config>): Promise<Record<string, number>> {\n    const profile = await this.tf.profile(() => this.detect(input, userConfig));\n    const kernels: Record<string, number> = {};\n    for (const kernel of profile.kernels) { // sum kernel time values per kernel\n      if (kernels[kernel.name]) kernels[kernel.name] += kernel.kernelTimeMs;\n      else kernels[kernel.name] = kernel.kernelTimeMs;\n    }\n    const kernelArr: Array<{ name: string, ms: number }> = [];\n    Object.entries(kernels).forEach((key) => kernelArr.push({ name: key[0], ms: key[1] as unknown as number })); // convert to array\n    kernelArr.sort((a, b) => b.ms - a.ms); // sort\n    kernelArr.length = 20; // crop\n    const res: Record<string, number> = {};\n    for (const kernel of kernelArr) res[kernel.name] = kernel.ms; // create perf objects\n    return res;\n  }\n\n  /** Main detection method\n   * - Analyze configuration: {@link Config}\n   * - Pre-process input: {@link Input}\n   * - Run inference for all configured models\n   * - Process and return result: {@link Result}\n   *\n   * @param input - {@link Input}\n   * @param userConfig - {@link Config}\n   * @returns result - {@link Result}\n  */\n  async detect(input: Input, userConfig?: Partial<Config>): Promise<Result> {\n    // detection happens inside a promise\n    this.state = 'detect';\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig) as Config;\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        this.emit('error');\n        resolve({ face: [], body: [], hand: [], gesture: [], object: [], performance: this.performance, timestamp: now(), persons: [], error });\n      }\n\n      const timeStart = now();\n\n      // configure backend if needed\n      await backend.check(this);\n\n      // load models if enabled\n      await this.load();\n\n      timeStamp = now();\n      this.state = 'image';\n      const img = await image.process(input, this.config) as { canvas: AnyCanvas, tensor: Tensor };\n      this.process = img;\n      this.performance.inputProcess = this.env.perfadd ? (this.performance.inputProcess || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      this.analyze('Get Image:');\n\n      if (!img.tensor) {\n        if (this.config.debug) log('could not convert input to tensor');\n        this.emit('error');\n        resolve({ face: [], body: [], hand: [], gesture: [], object: [], performance: this.performance, timestamp: now(), persons: [], error: 'could not convert input to tensor' });\n        return;\n      }\n      this.emit('image');\n\n      timeStamp = now();\n      this.config.skipAllowed = await image.skip(this.config, img.tensor);\n      if (!this.performance.totalFrames) this.performance.totalFrames = 0;\n      if (!this.performance.cachedFrames) this.performance.cachedFrames = 0;\n      (this.performance.totalFrames as number)++;\n      if (this.config.skipAllowed) this.performance.cachedFrames++;\n      this.performance.cacheCheck = this.env.perfadd ? (this.performance.cacheCheck || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      this.analyze('Check Changed:');\n\n      // prepare where to store model results\n      // keep them with weak typing as it can be promise or not\n      let faceRes: FaceResult[] | Promise<FaceResult[]> | never[] = [];\n      let bodyRes: BodyResult[] | Promise<BodyResult[]> | never[] = [];\n      let handRes: HandResult[] | Promise<HandResult[]> | never[] = [];\n      let objectRes: ObjectResult[] | Promise<ObjectResult[]> | never[] = [];\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      this.state = 'detect:face';\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? face.detectFace(this, img.tensor) : [];\n        if (this.performance.face) delete this.performance.face;\n      } else {\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await face.detectFace(this, img.tensor) : [];\n        this.performance.face = this.env.perfadd ? (this.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n\n      if (this.config.async && (this.config.body.maxDetected === -1 || this.config.hand.maxDetected === -1)) faceRes = await faceRes; // need face result for auto-detect number of hands or bodies\n\n      // run body: can be posenet, blazepose, efficientpose, movenet\n      this.analyze('Start Body:');\n      this.state = 'detect:body';\n      const bodyConfig = this.config.body.maxDetected === -1 ? mergeDeep(this.config, { body: { maxDetected: this.config.face.enabled ? 1 * (faceRes as FaceResult[]).length : 1 } }) : this.config; // autodetect number of bodies\n      if (this.config.async) {\n        if (this.config.body.modelPath?.includes('posenet')) bodyRes = this.config.body.enabled ? posenet.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('blazepose')) bodyRes = this.config.body.enabled ? blazepose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('efficientpose')) bodyRes = this.config.body.enabled ? efficientpose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('movenet')) bodyRes = this.config.body.enabled ? movenet.predict(img.tensor, bodyConfig) : [];\n        if (this.performance.body) delete this.performance.body;\n      } else {\n        timeStamp = now();\n        if (this.config.body.modelPath?.includes('posenet')) bodyRes = this.config.body.enabled ? await posenet.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('blazepose')) bodyRes = this.config.body.enabled ? await blazepose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('efficientpose')) bodyRes = this.config.body.enabled ? await efficientpose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('movenet')) bodyRes = this.config.body.enabled ? await movenet.predict(img.tensor, bodyConfig) : [];\n        this.performance.body = this.env.perfadd ? (this.performance.body || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n      this.analyze('End Body:');\n\n      // run handpose\n      this.analyze('Start Hand:');\n      this.state = 'detect:hand';\n      const handConfig = this.config.hand.maxDetected === -1 ? mergeDeep(this.config, { hand: { maxDetected: this.config.face.enabled ? 2 * (faceRes as FaceResult[]).length : 1 } }) : this.config; // autodetect number of hands\n      if (this.config.async) {\n        if (this.config.hand.detector?.modelPath?.includes('handdetect')) handRes = this.config.hand.enabled ? handpose.predict(img.tensor, handConfig) : [];\n        else if (this.config.hand.detector?.modelPath?.includes('handtrack')) handRes = this.config.hand.enabled ? handtrack.predict(img.tensor, handConfig) : [];\n        if (this.performance.hand) delete this.performance.hand;\n      } else {\n        timeStamp = now();\n        if (this.config.hand.detector?.modelPath?.includes('handdetect')) handRes = this.config.hand.enabled ? await handpose.predict(img.tensor, handConfig) : [];\n        else if (this.config.hand.detector?.modelPath?.includes('handtrack')) handRes = this.config.hand.enabled ? await handtrack.predict(img.tensor, handConfig) : [];\n        this.performance.hand = this.env.perfadd ? (this.performance.hand || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n      this.analyze('End Hand:');\n\n      // run object detection\n      this.analyze('Start Object:');\n      this.state = 'detect:object';\n      if (this.config.async) {\n        if (this.config.object.modelPath?.includes('nanodet')) objectRes = this.config.object.enabled ? nanodet.predict(img.tensor, this.config) : [];\n        else if (this.config.object.modelPath?.includes('centernet')) objectRes = this.config.object.enabled ? centernet.predict(img.tensor, this.config) : [];\n        if (this.performance.object) delete this.performance.object;\n      } else {\n        timeStamp = now();\n        if (this.config.object.modelPath?.includes('nanodet')) objectRes = this.config.object.enabled ? await nanodet.predict(img.tensor, this.config) : [];\n        else if (this.config.object.modelPath?.includes('centernet')) objectRes = this.config.object.enabled ? await centernet.predict(img.tensor, this.config) : [];\n        this.performance.object = this.env.perfadd ? (this.performance.object || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n      this.analyze('End Object:');\n\n      // if async wait for results\n      this.state = 'detect:await';\n      if (this.config.async) [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n\n      // run gesture analysis last\n      this.state = 'detect:gesture';\n      let gestureRes: GestureResult[] = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        gestureRes = [...gesture.face(faceRes as FaceResult[]), ...gesture.body(bodyRes as BodyResult[]), ...gesture.hand(handRes as HandResult[]), ...gesture.iris(faceRes as FaceResult[])];\n        if (!this.config.async) this.performance.gesture = this.env.perfadd ? (this.performance.gesture || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n        else if (this.performance.gesture) delete this.performance.gesture;\n      }\n\n      this.performance.total = this.env.perfadd ? (this.performance.total || 0) + Math.trunc(now() - timeStart) : Math.trunc(now() - timeStart);\n      const shape = this.process?.tensor?.shape || [];\n      this.result = {\n        face: faceRes as FaceResult[],\n        body: bodyRes as BodyResult[],\n        hand: handRes as HandResult[],\n        gesture: gestureRes,\n        object: objectRes as ObjectResult[],\n        performance: this.performance,\n        canvas: this.process.canvas,\n        timestamp: Date.now(),\n        error: null,\n        get persons() { return persons.join(faceRes as FaceResult[], bodyRes as BodyResult[], handRes as HandResult[], gestureRes, shape); },\n      };\n\n      // finally dispose input tensor\n      tf.dispose(img.tensor);\n\n      // log('Result:', result);\n      this.emit('detect');\n      this.state = 'idle';\n      resolve(this.result);\n    });\n  }\n}\n\n/** Class Human as default export */\n/* eslint no-restricted-exports: [\"off\", { \"restrictedNamedExports\": [\"default\"] }] */\nexport { Human as default, match, draw, models };\n"],
-  "mappings": ";;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;AAOO,SAAS,OAAO,KAAW;AAChC,QAAM,KAAK,IAAI,KAAK;AACpB,QAAM,KAAK,GAAG,GAAG,SAAS,EAAE,SAAS,EAAE,SAAS,GAAG,GAAG,KAAK,GAAG,WAAW,EAAE,SAAS,EAAE,SAAS,GAAG,GAAG,KAAK,GAAG,WAAW,EAAE,SAAS,EAAE,SAAS,GAAG,GAAG,KAAK,GAAG,gBAAgB,EAAE,SAAS,EAAE,SAAS,GAAG,GAAG;AAExM,MAAI;AAAK,YAAQ,IAAI,IAAI,UAAU,GAAG,GAAG;AAC3C;AAGO,SAAS,KAAK,QAAgB,MAAsB;AACzD,QAAM,YAAY,OAAO,SAAS,GAAG,IAAI,KAAK;AAC9C,QAAM,WAAW,KAAK,WAAW,GAAG,KAAK,KAAK,WAAW,GAAG,KAAK,KAAK,WAAW,OAAO,KAAK,KAAK,WAAW,QAAQ,KAAK,KAAK,WAAW,OAAO;AACjJ,QAAM,OAAO,WAAW,GAAG,SAAS,GAAG,SAAS,YAAY;AAC5D,MAAI,CAAC,KAAK,kBAAkB,EAAE,SAAS,OAAO;AAAG,UAAM,IAAI,MAAM,yCAAyC,MAAM;AAChH,SAAO;AACT;AAGO,IAAM,MAAM,MAAM;AACvB,MAAI,OAAO,gBAAgB;AAAa,WAAO,YAAY,IAAI;AAC/D,SAAO,UAAU,OAAO,QAAQ,OAAO,OAAO,CAAC,IAAI,MAAO,KAAM,SAAS,CAAC;AAC5E;AAGO,SAAS,SAAS,UAA2BA,SAAyB,SAAS,UAAU,OAAoE,CAAC,GAAG;AACtK,aAAW,OAAO,OAAO,KAAKA,OAAM,GAAG;AACrC,QAAI,OAAOA,QAAO,SAAS,UAAU;AACnC,eAAS,SAAS,MAAMA,QAAO,MAAM,KAAK,IAAI;AAAA,IAChD,OAAO;AACL,YAAM,UAAU,YAAa,OAAO,SAAS,SAAS;AACtD,UAAI,CAAC;AAAS,aAAK,KAAK,EAAE,QAAQ,oBAAoB,OAAO,GAAG,UAAU,SAASA,QAAO,OAAO,CAAC;AAClG,YAAM,OAAO,YAAY,OAAO,SAAS,SAAS,OAAOA,QAAO;AAChE,UAAI,WAAW,CAAC;AAAM,aAAK,KAAK,EAAE,QAAQ,0BAA0B,OAAO,GAAG,UAAU,SAASA,QAAO,QAAQ,UAAU,OAAO,SAAS,KAAK,CAAC;AAAA,IAClJ;AAAA,EAEF;AACA,MAAIA,QAAO,SAAS,WAAW,YAAY,KAAK,SAAS;AAAG,QAAI,yBAAyB,IAAI;AAC7F,SAAO;AACT;AAGO,SAAS,aAAa,SAAS;AACpC,QAAM,WAAW,CAAC,QAAQ,OAAO,OAAO,QAAQ;AAChD,SAAO,QAAQ,OAAO,CAAC,MAAM,QAAQ;AACnC,WAAO,KAAK,OAAO,CAAC,CAAC,EAAE,QAAQ,CAAC,QAAQ;AACtC,YAAM,OAAO,KAAK;AAClB,YAAM,OAAO,IAAI;AACjB,UAAI,MAAM,QAAQ,IAAI,KAAK,MAAM,QAAQ,IAAI;AAAG,aAAK,OAAO,KAAK,OAAO,GAAG,IAAI;AAAA,eACtE,SAAS,IAAI,KAAK,SAAS,IAAI;AAAG,aAAK,OAAO,UAAU,MAAM,IAAI;AAAA;AACtE,aAAK,OAAO;AAAA,IACnB,CAAC;AACD,WAAO;AAAA,EACT,GAAG,CAAC,CAAC;AACP;;;AC6PA,IAAM,SAAiB;AAAA,EACrB,SAAS;AAAA,EACT,eAAe;AAAA,EACf,aAAa;AAAA,EACb,UAAU;AAAA,EACV,mBAAmB;AAAA,EACnB,OAAO;AAAA,EACP,OAAO;AAAA,EACP,QAAQ;AAAA,EACR,kBAAkB;AAAA,EAClB,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,QAAQ;AAAA,IACN,SAAS;AAAA,IACT,cAAc;AAAA,IACd,OAAO;AAAA,IACP,QAAQ;AAAA,IACR,MAAM;AAAA,IACN,QAAQ;AAAA,IACR,YAAY;AAAA,IACZ,UAAU;AAAA,IACV,WAAW;AAAA,IACX,MAAM;AAAA,IACN,YAAY;AAAA,IACZ,KAAK;AAAA,IACL,UAAU;AAAA,IACV,OAAO;AAAA,IACP,SAAS;AAAA,IACT,YAAY;AAAA,IACZ,aAAa;AAAA,IACb,UAAU;AAAA,IACV,UAAU;AAAA,EACZ;AAAA,EACA,SAAS;AAAA,IACP,SAAS;AAAA,EACX;AAAA,EACA,MAAM;AAAA,IACJ,SAAS;AAAA,IACT,UAAU;AAAA,MACR,WAAW;AAAA,MACX,UAAU;AAAA,MACV,aAAa;AAAA,MACb,YAAY;AAAA,MACZ,UAAU;AAAA,MACV,eAAe;AAAA,MACf,cAAc;AAAA,MACd,MAAM;AAAA,MACN,QAAQ;AAAA,IACV;AAAA,IACA,MAAM;AAAA,MACJ,SAAS;AAAA,MACT,WAAW;AAAA,MACX,aAAa;AAAA,IACf;AAAA,IACA,WAAW;AAAA,MACT,SAAS;AAAA,MACT,WAAW;AAAA,IACb;AAAA,IACA,MAAM;AAAA,MACJ,SAAS;AAAA,MACT,WAAW;AAAA,IACb;AAAA,IACA,SAAS;AAAA,MACP,SAAS;AAAA,MACT,eAAe;AAAA,MACf,YAAY;AAAA,MACZ,UAAU;AAAA,MACV,WAAW;AAAA,IACb;AAAA,IACA,aAAa;AAAA,MACX,SAAS;AAAA,MACT,WAAW;AAAA,MACX,YAAY;AAAA,MACZ,UAAU;AAAA,MACV,eAAe;AAAA,IACjB;AAAA,IACA,WAAW;AAAA,MACT,SAAS;AAAA,MACT,YAAY;AAAA,MACZ,UAAU;AAAA,MACV,WAAW;AAAA,IACb;AAAA,IACA,UAAU;AAAA,MACR,SAAS;AAAA,MACT,YAAY;AAAA,MACZ,UAAU;AAAA,MACV,WAAW;AAAA,IACb;AAAA,EACF;AAAA,EACA,MAAM;AAAA,IACJ,SAAS;AAAA,IACT,WAAW;AAAA,IACX,aAAa;AAAA,IACb,eAAe;AAAA,IACf,YAAY;AAAA,IACZ,UAAU;AAAA,EACZ;AAAA,EACA,MAAM;AAAA,IACJ,SAAS;AAAA,IACT,UAAU;AAAA,IACV,YAAY;AAAA,IACZ,UAAU;AAAA,IACV,eAAe;AAAA,IACf,cAAc;AAAA,IACd,aAAa;AAAA,IACb,WAAW;AAAA,IACX,UAAU;AAAA,MACR,WAAW;AAAA,IACb;AAAA,IACA,UAAU;AAAA,MACR,WAAW;AAAA,IACb;AAAA,EACF;AAAA,EACA,QAAQ;AAAA,IACN,SAAS;AAAA,IACT,WAAW;AAAA,IACX,eAAe;AAAA,IACf,cAAc;AAAA,IACd,aAAa;AAAA,IACb,YAAY;AAAA,IACZ,UAAU;AAAA,EACZ;AAAA,EACA,cAAc;AAAA,IACZ,SAAS;AAAA,IACT,WAAW;AAAA,IACX,MAAM;AAAA,EACR;AACF;;;ACvbA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,aAAAC;AAAA,EAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAMA,IAAI,WAAW,OAAO;AACtB,IAAIC,aAAY,OAAO;AACvB,IAAI,mBAAmB,OAAO;AAC9B,IAAI,oBAAoB,OAAO;AAC/B,IAAI,eAAe,OAAO;AAC1B,IAAI,eAAe,OAAO,UAAU;AACpC,IAAI,aAAa,CAAC,IAAI,SAAS,SAAS,YAAY;AAClD,SAAO,SAAS,GAAG,GAAG,kBAAkB,EAAE,EAAE,MAAM,OAAO,EAAE,SAAS,CAAC,EAAE,GAAG,SAAS,IAAI,GAAG,KAAK;AACjG;AACA,IAAIC,YAAW,CAAC,QAAQC,UAAS;AAC/B,WAAS,QAAQA;AACf,IAAAF,WAAU,QAAQ,MAAM,EAAE,KAAKE,MAAK,OAAO,YAAY,KAAK,CAAC;AACjE;AACA,IAAI,cAAc,CAAC,IAAI,MAAM,QAAQ,SAAS;AAC5C,MAAI,QAAQ,OAAO,SAAS,YAAY,OAAO,SAAS,YAAY;AAClE,aAAS,OAAO,kBAAkB,IAAI;AACpC,UAAI,CAAC,aAAa,KAAK,IAAI,GAAG,KAAK,QAAQ;AACzC,QAAAF,WAAU,IAAI,KAAK,EAAE,KAAK,MAAM,KAAK,MAAM,YAAY,EAAE,OAAO,iBAAiB,MAAM,GAAG,MAAM,KAAK,WAAW,CAAC;AAAA,EACvH;AACA,SAAO;AACT;AACA,IAAI,UAAU,CAAC,MAAM,YAAY,YAAY,SAAS,QAAQ,OAAO,SAAS,aAAa,IAAI,CAAC,IAAI,CAAC,GAAG;AAAA,EACtG,cAAc,CAAC,QAAQ,CAAC,KAAK,aAAaA,WAAU,QAAQ,WAAW,EAAE,OAAO,MAAM,YAAY,KAAK,CAAC,IAAI;AAAA,EAC5G;AACF;AAGA,IAAI,eAAe,WAAW;AAAA,EAC5B,8DAA8D,SAAS,QAAQ;AAC7E,WAAO,UAAU;AACjB,QAAI,OAAO;AACX,QAAI;AACF,aAAO,IAAI,YAAY,SAAS,IAAI,YAAY,OAAO,IAAI,WAAW;AAAA,QACpE;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,MACF,CAAC,CAAC,GAAG,CAAC,CAAC,EAAE;AAAA,IACX,SAAS,IAAP;AAAA,IACF;AACA,aAAS,MAAM,KAAK,MAAM,UAAU;AAClC,WAAK,MAAM,MAAM;AACjB,WAAK,OAAO,OAAO;AACnB,WAAK,WAAW,CAAC,CAAC;AAAA,IACpB;AACA,UAAM,UAAU;AAChB,WAAO,eAAe,MAAM,WAAW,cAAc,EAAE,OAAO,KAAK,CAAC;AACpE,aAAS,OAAO,KAAK;AACnB,cAAQ,OAAO,IAAI,mBAAmB;AAAA,IACxC;AACA,UAAM,SAAS;AACf,QAAI,YAAY,CAAC;AACjB,QAAI,aAAa,CAAC;AAClB,aAAS,QAAQ,OAAO,UAAU;AAChC,UAAI,KAAK,WAAWG;AACpB,UAAI,UAAU;AACZ,mBAAW;AACX,YAAIA,SAAQ,KAAK,SAAS,QAAQ,KAAK;AACrC,sBAAY,WAAW;AACvB,cAAI;AACF,mBAAO;AAAA,QACX;AACA,cAAM,SAAS,QAAQ,QAAQ,KAAK,IAAI,KAAK,GAAG,IAAI;AACpD,YAAIA;AACF,qBAAW,SAAS;AACtB,eAAO;AAAA,MACT,OAAO;AACL,iBAAS;AACT,YAAIA,SAAQ,QAAQ,SAAS,QAAQ,KAAK;AACxC,sBAAY,UAAU;AACtB,cAAI;AACF,mBAAO;AAAA,QACX;AACA,cAAM,SAAS,OAAO,QAAQ,IAAI,KAAK,GAAG,KAAK;AAC/C,YAAIA;AACF,oBAAU,SAAS;AACrB,eAAO;AAAA,MACT;AAAA,IACF;AACA,UAAM,UAAU;AAChB,aAAS,WAAW,OAAO,UAAU;AACnC,UAAI,MAAM,KAAK;AACb,eAAO,WAAW,QAAQ;AAC5B,UAAI,UAAU;AACZ,YAAI,QAAQ;AACV,iBAAO;AACT,YAAI,SAAS;AACX,iBAAO;AAAA,MACX,OAAO;AACL,YAAI,SAAS,CAAC;AACZ,iBAAO;AACT,YAAI,QAAQ,KAAK;AACf,iBAAO;AAAA,MACX;AACA,UAAI,QAAQ;AACV,eAAO,WAAW,CAAC,OAAO,QAAQ,EAAE,IAAI;AAC1C,aAAO,SAAS,QAAQ,iBAAiB,GAAG,QAAQ,iBAAiB,GAAG,QAAQ;AAAA,IAClF;AACA,UAAM,aAAa;AACnB,aAAS,SAAS,SAAS,UAAU,UAAU;AAC7C,aAAO,IAAI,MAAM,SAAS,UAAU,QAAQ;AAAA,IAC9C;AACA,UAAM,WAAW;AACjB,QAAI,UAAU,KAAK;AACnB,aAAS,WAAW,KAAK,UAAU,OAAO;AACxC,UAAI,IAAI,WAAW;AACjB,cAAM,MAAM,cAAc;AAC5B,UAAI,QAAQ,SAAS,QAAQ,cAAc,QAAQ,eAAe,QAAQ;AACxE,eAAO;AACT,UAAI,OAAO,aAAa,UAAU;AAChC,gBAAQ,UAAU,WAAW;AAAA,MAC/B,OAAO;AACL,mBAAW,CAAC,CAAC;AAAA,MACf;AACA,cAAQ,SAAS;AACjB,UAAI,QAAQ,KAAK,KAAK;AACpB,cAAM,WAAW,OAAO;AAC1B,UAAI;AACJ,WAAK,KAAK,IAAI,QAAQ,GAAG,KAAK;AAC5B,cAAM,MAAM,iBAAiB;AAAA,eACtB,OAAO,GAAG;AACjB,eAAO,WAAW,IAAI,UAAU,CAAC,GAAG,UAAU,KAAK,EAAE,IAAI;AAAA,MAC3D;AACA,UAAI,eAAe,WAAW,QAAQ,OAAO,CAAC,CAAC;AAC/C,UAAI,SAAS;AACb,eAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,MAAM,GAAG;AACzC,YAAIC,QAAO,KAAK,IAAI,GAAG,IAAI,SAAS,EAAE,GAAG,QAAQ,SAAS,IAAI,UAAU,IAAI,KAAKA,KAAI,GAAG,KAAK;AAC7F,YAAIA,QAAO,GAAG;AACZ,cAAI,QAAQ,WAAW,QAAQ,OAAOA,KAAI,CAAC;AAC3C,mBAAS,OAAO,IAAI,KAAK,EAAE,IAAI,WAAW,KAAK,CAAC;AAAA,QAClD,OAAO;AACL,mBAAS,OAAO,IAAI,YAAY;AAChC,mBAAS,OAAO,IAAI,WAAW,KAAK,CAAC;AAAA,QACvC;AAAA,MACF;AACA,aAAO,WAAW;AAClB,aAAO;AAAA,IACT;AACA,UAAM,aAAa;AACnB,aAAS,UAAU,KAAK,UAAU;AAChC,UAAI,OAAO,QAAQ;AACjB,eAAO,WAAW,KAAK,QAAQ;AACjC,UAAI,OAAO,QAAQ;AACjB,eAAO,WAAW,KAAK,QAAQ;AACjC,aAAO,SAAS,IAAI,KAAK,IAAI,MAAM,OAAO,aAAa,YAAY,WAAW,IAAI,QAAQ;AAAA,IAC5F;AACA,UAAM,YAAY;AAClB,QAAI,iBAAiB,KAAK;AAC1B,QAAI,iBAAiB,KAAK;AAC1B,QAAI,iBAAiB,iBAAiB;AACtC,QAAI,iBAAiB,iBAAiB;AACtC,QAAI,iBAAiB,iBAAiB;AACtC,QAAI,aAAa,QAAQ,cAAc;AACvC,QAAI,OAAO,QAAQ,CAAC;AACpB,UAAM,OAAO;AACb,QAAI,QAAQ,QAAQ,GAAG,IAAI;AAC3B,UAAM,QAAQ;AACd,QAAI,MAAM,QAAQ,CAAC;AACnB,UAAM,MAAM;AACZ,QAAI,OAAO,QAAQ,GAAG,IAAI;AAC1B,UAAM,OAAO;AACb,QAAI,UAAU,QAAQ,EAAE;AACxB,UAAM,UAAU;AAChB,QAAI,YAAY,SAAS,aAAa,GAAG,aAAa,GAAG,KAAK;AAC9D,UAAM,YAAY;AAClB,QAAI,qBAAqB,SAAS,aAAa,GAAG,aAAa,GAAG,IAAI;AACtE,UAAM,qBAAqB;AAC3B,QAAI,YAAY,SAAS,GAAG,aAAa,GAAG,KAAK;AACjD,UAAM,YAAY;AAClB,QAAI,gBAAgB,MAAM;AAC1B,kBAAc,QAAQ,SAAS,QAAQ;AACrC,aAAO,KAAK,WAAW,KAAK,QAAQ,IAAI,KAAK;AAAA,IAC/C;AACA,kBAAc,WAAW,SAAS,WAAW;AAC3C,UAAI,KAAK;AACP,gBAAQ,KAAK,SAAS,KAAK,kBAAkB,KAAK,QAAQ;AAC5D,aAAO,KAAK,OAAO,kBAAkB,KAAK,QAAQ;AAAA,IACpD;AACA,kBAAc,WAAW,SAAS,SAAS,OAAO;AAChD,cAAQ,SAAS;AACjB,UAAI,QAAQ,KAAK,KAAK;AACpB,cAAM,WAAW,OAAO;AAC1B,UAAI,KAAK,OAAO;AACd,eAAO;AACT,UAAI,KAAK,WAAW,GAAG;AACrB,YAAI,KAAK,GAAG,SAAS,GAAG;AACtB,cAAI,YAAY,WAAW,KAAK,GAAG,OAAO,KAAK,IAAI,SAAS,GAAG,OAAO,KAAK,IAAI,SAAS,EAAE,IAAI,IAAI;AAClG,iBAAO,KAAK,SAAS,KAAK,IAAI,KAAK,MAAM,EAAE,SAAS,KAAK;AAAA,QAC3D;AACE,iBAAO,MAAM,KAAK,IAAI,EAAE,SAAS,KAAK;AAAA,MAC1C;AACA,UAAI,eAAe,WAAW,QAAQ,OAAO,CAAC,GAAG,KAAK,QAAQ,GAAG,MAAM;AACvE,UAAI,SAAS;AACb,aAAO,MAAM;AACX,YAAI,SAAS,IAAI,IAAI,YAAY,GAAG,SAAS,IAAI,IAAI,OAAO,IAAI,YAAY,CAAC,EAAE,MAAM,MAAM,GAAG,SAAS,OAAO,SAAS,KAAK;AAC5H,cAAM;AACN,YAAI,IAAI,OAAO;AACb,iBAAO,SAAS;AAAA,aACb;AACH,iBAAO,OAAO,SAAS;AACrB,qBAAS,MAAM;AACjB,mBAAS,KAAK,SAAS;AAAA,QACzB;AAAA,MACF;AAAA,IACF;AACA,kBAAc,cAAc,SAAS,cAAc;AACjD,aAAO,KAAK;AAAA,IACd;AACA,kBAAc,sBAAsB,SAAS,sBAAsB;AACjE,aAAO,KAAK,SAAS;AAAA,IACvB;AACA,kBAAc,aAAa,SAAS,aAAa;AAC/C,aAAO,KAAK;AAAA,IACd;AACA,kBAAc,qBAAqB,SAAS,qBAAqB;AAC/D,aAAO,KAAK,QAAQ;AAAA,IACtB;AACA,kBAAc,gBAAgB,SAAS,gBAAgB;AACrD,UAAI,KAAK,WAAW;AAClB,eAAO,KAAK,GAAG,SAAS,IAAI,KAAK,KAAK,IAAI,EAAE,cAAc;AAC5D,UAAI,MAAM,KAAK,QAAQ,IAAI,KAAK,OAAO,KAAK;AAC5C,eAAS,MAAM,IAAI,MAAM,GAAG;AAC1B,aAAK,MAAM,KAAK,QAAQ;AACtB;AACJ,aAAO,KAAK,QAAQ,IAAI,MAAM,KAAK,MAAM;AAAA,IAC3C;AACA,kBAAc,SAAS,SAAS,SAAS;AACvC,aAAO,KAAK,SAAS,KAAK,KAAK,QAAQ;AAAA,IACzC;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,aAAa,SAAS,aAAa;AAC/C,aAAO,CAAC,KAAK,YAAY,KAAK,OAAO;AAAA,IACvC;AACA,kBAAc,aAAa,SAAS,aAAa;AAC/C,aAAO,KAAK,YAAY,KAAK,QAAQ;AAAA,IACvC;AACA,kBAAc,QAAQ,SAAS,QAAQ;AACrC,cAAQ,KAAK,MAAM,OAAO;AAAA,IAC5B;AACA,kBAAc,SAAS,SAAS,UAAU;AACxC,cAAQ,KAAK,MAAM,OAAO;AAAA,IAC5B;AACA,kBAAc,SAAS,SAAS,OAAO,OAAO;AAC5C,UAAI,CAAC,OAAO,KAAK;AACf,gBAAQ,UAAU,KAAK;AACzB,UAAI,KAAK,aAAa,MAAM,YAAY,KAAK,SAAS,OAAO,KAAK,MAAM,SAAS,OAAO;AACtF,eAAO;AACT,aAAO,KAAK,SAAS,MAAM,QAAQ,KAAK,QAAQ,MAAM;AAAA,IACxD;AACA,kBAAc,KAAK,cAAc;AACjC,kBAAc,YAAY,SAAS,UAAU,OAAO;AAClD,aAAO,CAAC,KAAK,GAAG,KAAK;AAAA,IACvB;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,KAAK,cAAc;AACjC,kBAAc,WAAW,SAAS,SAAS,OAAO;AAChD,aAAO,KAAK,KAAK,KAAK,IAAI;AAAA,IAC5B;AACA,kBAAc,KAAK,cAAc;AACjC,kBAAc,kBAAkB,SAAS,gBAAgB,OAAO;AAC9D,aAAO,KAAK,KAAK,KAAK,KAAK;AAAA,IAC7B;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,KAAK,cAAc;AACjC,kBAAc,cAAc,SAAS,YAAY,OAAO;AACtD,aAAO,KAAK,KAAK,KAAK,IAAI;AAAA,IAC5B;AACA,kBAAc,KAAK,cAAc;AACjC,kBAAc,qBAAqB,SAAS,mBAAmB,OAAO;AACpE,aAAO,KAAK,KAAK,KAAK,KAAK;AAAA,IAC7B;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,KAAK,cAAc;AACjC,kBAAc,UAAU,SAASC,SAAQ,OAAO;AAC9C,UAAI,CAAC,OAAO,KAAK;AACf,gBAAQ,UAAU,KAAK;AACzB,UAAI,KAAK,GAAG,KAAK;AACf,eAAO;AACT,UAAI,UAAU,KAAK,WAAW,GAAG,WAAW,MAAM,WAAW;AAC7D,UAAI,WAAW,CAAC;AACd,eAAO;AACT,UAAI,CAAC,WAAW;AACd,eAAO;AACT,UAAI,CAAC,KAAK;AACR,eAAO,KAAK,IAAI,KAAK,EAAE,WAAW,IAAI,KAAK;AAC7C,aAAO,MAAM,SAAS,IAAI,KAAK,SAAS,KAAK,MAAM,SAAS,KAAK,QAAQ,MAAM,QAAQ,IAAI,KAAK,QAAQ,IAAI,KAAK;AAAA,IACnH;AACA,kBAAc,OAAO,cAAc;AACnC,kBAAc,SAAS,SAAS,SAAS;AACvC,UAAI,CAAC,KAAK,YAAY,KAAK,GAAG,SAAS;AACrC,eAAO;AACT,aAAO,KAAK,IAAI,EAAE,IAAI,GAAG;AAAA,IAC3B;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,MAAM,SAAS,KAAK,QAAQ;AACxC,UAAI,CAAC,OAAO,MAAM;AAChB,iBAAS,UAAU,MAAM;AAC3B,UAAI,MAAM,KAAK,SAAS;AACxB,UAAI,MAAM,KAAK,OAAO;AACtB,UAAI,MAAM,KAAK,QAAQ;AACvB,UAAI,MAAM,KAAK,MAAM;AACrB,UAAI,MAAM,OAAO,SAAS;AAC1B,UAAI,MAAM,OAAO,OAAO;AACxB,UAAI,MAAM,OAAO,QAAQ;AACzB,UAAI,MAAM,OAAO,MAAM;AACvB,UAAI,MAAM,GAAG,MAAM,GAAG,MAAM,GAAG,MAAM;AACrC,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO;AACP,aAAO,SAAS,OAAO,KAAK,KAAK,OAAO,KAAK,KAAK,KAAK,QAAQ;AAAA,IACjE;AACA,kBAAc,WAAW,SAAS,SAAS,YAAY;AACrD,UAAI,CAAC,OAAO,UAAU;AACpB,qBAAa,UAAU,UAAU;AACnC,aAAO,KAAK,IAAI,WAAW,IAAI,CAAC;AAAA,IAClC;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,WAAW,SAAS,UAAU,YAAY;AACtD,UAAI,KAAK,OAAO;AACd,eAAO;AACT,UAAI,CAAC,OAAO,UAAU;AACpB,qBAAa,UAAU,UAAU;AACnC,UAAI,MAAM;AACR,YAAI,MAAM,KAAK;AAAA,UACb,KAAK;AAAA,UACL,KAAK;AAAA,UACL,WAAW;AAAA,UACX,WAAW;AAAA,QACb;AACA,eAAO,SAAS,KAAK,KAAK,SAAS,GAAG,KAAK,QAAQ;AAAA,MACrD;AACA,UAAI,WAAW,OAAO;AACpB,eAAO;AACT,UAAI,KAAK,GAAG,SAAS;AACnB,eAAO,WAAW,MAAM,IAAI,YAAY;AAC1C,UAAI,WAAW,GAAG,SAAS;AACzB,eAAO,KAAK,MAAM,IAAI,YAAY;AACpC,UAAI,KAAK,WAAW,GAAG;AACrB,YAAI,WAAW,WAAW;AACxB,iBAAO,KAAK,IAAI,EAAE,IAAI,WAAW,IAAI,CAAC;AAAA;AAEtC,iBAAO,KAAK,IAAI,EAAE,IAAI,UAAU,EAAE,IAAI;AAAA,MAC1C,WAAW,WAAW,WAAW;AAC/B,eAAO,KAAK,IAAI,WAAW,IAAI,CAAC,EAAE,IAAI;AACxC,UAAI,KAAK,GAAG,UAAU,KAAK,WAAW,GAAG,UAAU;AACjD,eAAO,WAAW,KAAK,SAAS,IAAI,WAAW,SAAS,GAAG,KAAK,QAAQ;AAC1E,UAAI,MAAM,KAAK,SAAS;AACxB,UAAI,MAAM,KAAK,OAAO;AACtB,UAAI,MAAM,KAAK,QAAQ;AACvB,UAAI,MAAM,KAAK,MAAM;AACrB,UAAI,MAAM,WAAW,SAAS;AAC9B,UAAI,MAAM,WAAW,OAAO;AAC5B,UAAI,MAAM,WAAW,QAAQ;AAC7B,UAAI,MAAM,WAAW,MAAM;AAC3B,UAAI,MAAM,GAAG,MAAM,GAAG,MAAM,GAAG,MAAM;AACrC,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM,MAAM,MAAM,MAAM,MAAM,MAAM,MAAM;AACjD,aAAO;AACP,aAAO,SAAS,OAAO,KAAK,KAAK,OAAO,KAAK,KAAK,KAAK,QAAQ;AAAA,IACjE;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,SAAS,SAAS,OAAO,SAAS;AAC9C,UAAI,CAAC,OAAO,OAAO;AACjB,kBAAU,UAAU,OAAO;AAC7B,UAAI,QAAQ,OAAO;AACjB,cAAM,MAAM,kBAAkB;AAChC,UAAI,MAAM;AACR,YAAI,CAAC,KAAK,YAAY,KAAK,SAAS,eAAe,QAAQ,QAAQ,MAAM,QAAQ,SAAS,IAAI;AAC5F,iBAAO;AAAA,QACT;AACA,YAAI,OAAO,KAAK,WAAW,KAAK,QAAQ,KAAK;AAAA,UAC3C,KAAK;AAAA,UACL,KAAK;AAAA,UACL,QAAQ;AAAA,UACR,QAAQ;AAAA,QACV;AACA,eAAO,SAAS,KAAK,KAAK,SAAS,GAAG,KAAK,QAAQ;AAAA,MACrD;AACA,UAAI,KAAK,OAAO;AACd,eAAO,KAAK,WAAW,QAAQ;AACjC,UAAI,QAAQ,KAAK;AACjB,UAAI,CAAC,KAAK,UAAU;AAClB,YAAI,KAAK,GAAG,SAAS,GAAG;AACtB,cAAI,QAAQ,GAAG,GAAG,KAAK,QAAQ,GAAG,OAAO;AACvC,mBAAO;AAAA,mBACA,QAAQ,GAAG,SAAS;AAC3B,mBAAO;AAAA,eACJ;AACH,gBAAI,WAAW,KAAK,IAAI,CAAC;AACzB,qBAAS,SAAS,IAAI,OAAO,EAAE,IAAI,CAAC;AACpC,gBAAI,OAAO,GAAG,IAAI,GAAG;AACnB,qBAAO,QAAQ,WAAW,IAAI,MAAM;AAAA,YACtC,OAAO;AACL,oBAAM,KAAK,IAAI,QAAQ,IAAI,MAAM,CAAC;AAClC,oBAAM,OAAO,IAAI,IAAI,IAAI,OAAO,CAAC;AACjC,qBAAO;AAAA,YACT;AAAA,UACF;AAAA,QACF,WAAW,QAAQ,GAAG,SAAS;AAC7B,iBAAO,KAAK,WAAW,QAAQ;AACjC,YAAI,KAAK,WAAW,GAAG;AACrB,cAAI,QAAQ,WAAW;AACrB,mBAAO,KAAK,IAAI,EAAE,IAAI,QAAQ,IAAI,CAAC;AACrC,iBAAO,KAAK,IAAI,EAAE,IAAI,OAAO,EAAE,IAAI;AAAA,QACrC,WAAW,QAAQ,WAAW;AAC5B,iBAAO,KAAK,IAAI,QAAQ,IAAI,CAAC,EAAE,IAAI;AACrC,cAAM;AAAA,MACR,OAAO;AACL,YAAI,CAAC,QAAQ;AACX,oBAAU,QAAQ,WAAW;AAC/B,YAAI,QAAQ,GAAG,IAAI;AACjB,iBAAO;AACT,YAAI,QAAQ,GAAG,KAAK,KAAK,CAAC,CAAC;AACzB,iBAAO;AACT,cAAM;AAAA,MACR;AACA,YAAM;AACN,aAAO,IAAI,IAAI,OAAO,GAAG;AACvB,iBAAS,KAAK,IAAI,GAAG,KAAK,MAAM,IAAI,SAAS,IAAI,QAAQ,SAAS,CAAC,CAAC;AACpE,YAAIC,SAAQ,KAAK,KAAK,KAAK,IAAI,MAAM,IAAI,KAAK,GAAG,GAAG,QAAQA,UAAS,KAAK,IAAI,QAAQ,GAAGA,SAAQ,EAAE,GAAG,YAAY,WAAW,MAAM,GAAG,YAAY,UAAU,IAAI,OAAO;AACvK,eAAO,UAAU,WAAW,KAAK,UAAU,GAAG,GAAG,GAAG;AAClD,oBAAU;AACV,sBAAY,WAAW,QAAQ,KAAK,QAAQ;AAC5C,sBAAY,UAAU,IAAI,OAAO;AAAA,QACnC;AACA,YAAI,UAAU,OAAO;AACnB,sBAAY;AACd,cAAM,IAAI,IAAI,SAAS;AACvB,cAAM,IAAI,IAAI,SAAS;AAAA,MACzB;AACA,aAAO;AAAA,IACT;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,SAAS,SAAS,OAAO,SAAS;AAC9C,UAAI,CAAC,OAAO,OAAO;AACjB,kBAAU,UAAU,OAAO;AAC7B,UAAI,MAAM;AACR,YAAI,OAAO,KAAK,WAAW,KAAK,QAAQ,KAAK;AAAA,UAC3C,KAAK;AAAA,UACL,KAAK;AAAA,UACL,QAAQ;AAAA,UACR,QAAQ;AAAA,QACV;AACA,eAAO,SAAS,KAAK,KAAK,SAAS,GAAG,KAAK,QAAQ;AAAA,MACrD;AACA,aAAO,KAAK,IAAI,KAAK,IAAI,OAAO,EAAE,IAAI,OAAO,CAAC;AAAA,IAChD;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,MAAM,cAAc;AAClC,kBAAc,MAAM,SAAS,MAAM;AACjC,aAAO,SAAS,CAAC,KAAK,KAAK,CAAC,KAAK,MAAM,KAAK,QAAQ;AAAA,IACtD;AACA,kBAAc,MAAM,SAAS,IAAI,OAAO;AACtC,UAAI,CAAC,OAAO,KAAK;AACf,gBAAQ,UAAU,KAAK;AACzB,aAAO,SAAS,KAAK,MAAM,MAAM,KAAK,KAAK,OAAO,MAAM,MAAM,KAAK,QAAQ;AAAA,IAC7E;AACA,kBAAc,KAAK,SAAS,GAAG,OAAO;AACpC,UAAI,CAAC,OAAO,KAAK;AACf,gBAAQ,UAAU,KAAK;AACzB,aAAO,SAAS,KAAK,MAAM,MAAM,KAAK,KAAK,OAAO,MAAM,MAAM,KAAK,QAAQ;AAAA,IAC7E;AACA,kBAAc,MAAM,SAAS,IAAI,OAAO;AACtC,UAAI,CAAC,OAAO,KAAK;AACf,gBAAQ,UAAU,KAAK;AACzB,aAAO,SAAS,KAAK,MAAM,MAAM,KAAK,KAAK,OAAO,MAAM,MAAM,KAAK,QAAQ;AAAA,IAC7E;AACA,kBAAc,YAAY,SAAS,UAAU,SAAS;AACpD,UAAI,OAAO,OAAO;AAChB,kBAAU,QAAQ,MAAM;AAC1B,WAAK,WAAW,QAAQ;AACtB,eAAO;AAAA,eACA,UAAU;AACjB,eAAO,SAAS,KAAK,OAAO,SAAS,KAAK,QAAQ,UAAU,KAAK,QAAQ,KAAK,SAAS,KAAK,QAAQ;AAAA;AAEpG,eAAO,SAAS,GAAG,KAAK,OAAO,UAAU,IAAI,KAAK,QAAQ;AAAA,IAC9D;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,aAAa,SAAS,WAAW,SAAS;AACtD,UAAI,OAAO,OAAO;AAChB,kBAAU,QAAQ,MAAM;AAC1B,WAAK,WAAW,QAAQ;AACtB,eAAO;AAAA,eACA,UAAU;AACjB,eAAO,SAAS,KAAK,QAAQ,UAAU,KAAK,QAAQ,KAAK,SAAS,KAAK,QAAQ,SAAS,KAAK,QAAQ;AAAA;AAErG,eAAO,SAAS,KAAK,QAAQ,UAAU,IAAI,KAAK,QAAQ,IAAI,IAAI,IAAI,KAAK,QAAQ;AAAA,IACrF;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,qBAAqB,SAAS,mBAAmB,SAAS;AACtE,UAAI,OAAO,OAAO;AAChB,kBAAU,QAAQ,MAAM;AAC1B,iBAAW;AACX,UAAI,YAAY;AACd,eAAO;AAAA,WACJ;AACH,YAAI,OAAO,KAAK;AAChB,YAAI,UAAU,IAAI;AAChB,cAAI,MAAM,KAAK;AACf,iBAAO,SAAS,QAAQ,UAAU,QAAQ,KAAK,SAAS,SAAS,SAAS,KAAK,QAAQ;AAAA,QACzF,WAAW,YAAY;AACrB,iBAAO,SAAS,MAAM,GAAG,KAAK,QAAQ;AAAA;AAEtC,iBAAO,SAAS,SAAS,UAAU,IAAI,GAAG,KAAK,QAAQ;AAAA,MAC3D;AAAA,IACF;AACA,kBAAc,OAAO,cAAc;AACnC,kBAAc,QAAQ,cAAc;AACpC,kBAAc,WAAW,SAAS,WAAW;AAC3C,UAAI,CAAC,KAAK;AACR,eAAO;AACT,aAAO,SAAS,KAAK,KAAK,KAAK,MAAM,KAAK;AAAA,IAC5C;AACA,kBAAc,aAAa,SAAS,aAAa;AAC/C,UAAI,KAAK;AACP,eAAO;AACT,aAAO,SAAS,KAAK,KAAK,KAAK,MAAM,IAAI;AAAA,IAC3C;AACA,kBAAc,UAAU,SAAS,QAAQ,IAAI;AAC3C,aAAO,KAAK,KAAK,UAAU,IAAI,KAAK,UAAU;AAAA,IAChD;AACA,kBAAc,YAAY,SAAS,YAAY;AAC7C,UAAI,KAAK,KAAK,MAAM,KAAK,KAAK;AAC9B,aAAO;AAAA,QACL,KAAK;AAAA,QACL,OAAO,IAAI;AAAA,QACX,OAAO,KAAK;AAAA,QACZ,OAAO;AAAA,QACP,KAAK;AAAA,QACL,OAAO,IAAI;AAAA,QACX,OAAO,KAAK;AAAA,QACZ,OAAO;AAAA,MACT;AAAA,IACF;AACA,kBAAc,YAAY,SAAS,YAAY;AAC7C,UAAI,KAAK,KAAK,MAAM,KAAK,KAAK;AAC9B,aAAO;AAAA,QACL,OAAO;AAAA,QACP,OAAO,KAAK;AAAA,QACZ,OAAO,IAAI;AAAA,QACX,KAAK;AAAA,QACL,OAAO;AAAA,QACP,OAAO,KAAK;AAAA,QACZ,OAAO,IAAI;AAAA,QACX,KAAK;AAAA,MACP;AAAA,IACF;AACA,UAAM,YAAY,SAAS,UAAU,OAAO,UAAU,IAAI;AACxD,aAAO,KAAK,MAAM,YAAY,OAAO,QAAQ,IAAI,MAAM,YAAY,OAAO,QAAQ;AAAA,IACpF;AACA,UAAM,cAAc,SAAS,YAAY,OAAO,UAAU;AACxD,aAAO,IAAI;AAAA,QACT,MAAM,KAAK,MAAM,MAAM,IAAI,MAAM,MAAM,KAAK,MAAM,MAAM;AAAA,QACxD,MAAM,KAAK,MAAM,MAAM,IAAI,MAAM,MAAM,KAAK,MAAM,MAAM;AAAA,QACxD;AAAA,MACF;AAAA,IACF;AACA,UAAM,cAAc,SAAS,YAAY,OAAO,UAAU;AACxD,aAAO,IAAI;AAAA,QACT,MAAM,MAAM,KAAK,MAAM,MAAM,KAAK,MAAM,MAAM,IAAI,MAAM;AAAA,QACxD,MAAM,MAAM,KAAK,MAAM,MAAM,KAAK,MAAM,MAAM,IAAI,MAAM;AAAA,QACxD;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACF,CAAC;AAGD,IAAI,kBAAkB,WAAW;AAAA,EAC/B,sFAAsF;AAAA,EACtF;AACF,CAAC;AAGD,IAAI,eAAe,WAAW;AAAA,EAC5B,oBAAoB;AAAA,EACpB;AACF,CAAC;AAGD,IAAI,eAAe,WAAW;AAAA,EAC5B,0EAA0E,SAAS,QAAQ;AACzF,KAAC,SAAS,SAAS,SAAS,SAAS;AACnC,eAAS,KAAK,MAAM;AAClB,YAAI,KAAK,MAAM,OAAO,KAAK;AAC3B,WAAG,OAAO,WAAW;AACnB,cAAI,KAAK,UAAU,GAAG,KAAK,GAAG,IAAI;AAClC,aAAG,KAAK,GAAG;AACX,aAAG,KAAK,GAAG;AACX,iBAAO,GAAG,KAAK,MAAM,GAAG,IAAI,KAAK;AAAA,QACnC;AACA,WAAG,IAAI;AACP,WAAG,KAAK,KAAK,GAAG;AAChB,WAAG,KAAK,KAAK,GAAG;AAChB,WAAG,KAAK,KAAK,GAAG;AAChB,WAAG,MAAM,KAAK,IAAI;AAClB,YAAI,GAAG,KAAK,GAAG;AACb,aAAG,MAAM;AAAA,QACX;AACA,WAAG,MAAM,KAAK,IAAI;AAClB,YAAI,GAAG,KAAK,GAAG;AACb,aAAG,MAAM;AAAA,QACX;AACA,WAAG,MAAM,KAAK,IAAI;AAClB,YAAI,GAAG,KAAK,GAAG;AACb,aAAG,MAAM;AAAA,QACX;AACA,eAAO;AAAA,MACT;AACA,eAASC,MAAK,GAAG,IAAI;AACnB,WAAG,IAAI,EAAE;AACT,WAAG,KAAK,EAAE;AACV,WAAG,KAAK,EAAE;AACV,WAAG,KAAK,EAAE;AACV,eAAO;AAAA,MACT;AACA,eAAS,KAAK,MAAM,MAAM;AACxB,YAAI,KAAK,IAAI,KAAK,IAAI,GAAG,QAAQ,QAAQ,KAAK,OAAO,OAAO,GAAG;AAC/D,aAAK,QAAQ,WAAW;AACtB,iBAAO,GAAG,KAAK,IAAI,aAAa;AAAA,QAClC;AACA,aAAK,SAAS,WAAW;AACvB,iBAAO,KAAK,KAAK,KAAK,IAAI,UAAU,KAAK;AAAA,QAC3C;AACA,aAAK,QAAQ;AACb,YAAI,OAAO;AACT,cAAI,OAAO,SAAS;AAClB,YAAAA,MAAK,OAAO,EAAE;AAChB,eAAK,QAAQ,WAAW;AACtB,mBAAOA,MAAK,IAAI,CAAC,CAAC;AAAA,UACpB;AAAA,QACF;AACA,eAAO;AAAA,MACT;AACA,eAAS,OAAO;AACd,YAAI,KAAK;AACT,YAAI,OAAO,SAAS,MAAM;AACxB,iBAAO,OAAO,IAAI;AAClB,mBAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,kBAAM,KAAK,WAAW,EAAE;AACxB,gBAAI,IAAI,sBAAsB;AAC9B,iBAAK,MAAM;AACX,iBAAK;AACL,iBAAK;AACL,iBAAK,MAAM;AACX,iBAAK;AACL,kBAAM,IAAI;AAAA,UACZ;AACA,kBAAQ,OAAO,KAAK;AAAA,QACtB;AACA,eAAO;AAAA,MACT;AACA,UAAI,WAAW,QAAQ,SAAS;AAC9B,gBAAQ,UAAU;AAAA,MACpB,WAAW,WAAW,QAAQ,KAAK;AACjC,gBAAQ,WAAW;AACjB,iBAAO;AAAA,QACT,CAAC;AAAA,MACH,OAAO;AACL,aAAK,OAAO;AAAA,MACd;AAAA,IACF;AAAA,MACE;AAAA,MACA,OAAO,UAAU,YAAY;AAAA,MAC7B,OAAO,UAAU,cAAc;AAAA,IACjC;AAAA,EACF;AACF,CAAC;AAGD,IAAI,iBAAiB,WAAW;AAAA,EAC9B,4EAA4E,SAAS,QAAQ;AAC3F,KAAC,SAAS,SAAS,SAAS,SAAS;AACnC,eAAS,OAAO,MAAM;AACpB,YAAI,KAAK,MAAM,UAAU;AACzB,WAAG,IAAI;AACP,WAAG,IAAI;AACP,WAAG,IAAI;AACP,WAAG,IAAI;AACP,WAAG,OAAO,WAAW;AACnB,cAAI,KAAK,GAAG,IAAI,GAAG,KAAK;AACxB,aAAG,IAAI,GAAG;AACV,aAAG,IAAI,GAAG;AACV,aAAG,IAAI,GAAG;AACV,iBAAO,GAAG,KAAK,GAAG,MAAM,KAAK,KAAK,OAAO;AAAA,QAC3C;AACA,YAAI,UAAU,OAAO,IAAI;AACvB,aAAG,IAAI;AAAA,QACT,OAAO;AACL,qBAAW;AAAA,QACb;AACA,iBAAS,IAAI,GAAG,IAAI,QAAQ,SAAS,IAAI,KAAK;AAC5C,aAAG,KAAK,QAAQ,WAAW,CAAC,IAAI;AAChC,aAAG,KAAK;AAAA,QACV;AAAA,MACF;AACA,eAASA,MAAK,GAAG,IAAI;AACnB,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,eAAO;AAAA,MACT;AACA,eAAS,KAAK,MAAM,MAAM;AACxB,YAAI,KAAK,IAAI,OAAO,IAAI,GAAG,QAAQ,QAAQ,KAAK,OAAO,OAAO,WAAW;AACvE,kBAAQ,GAAG,KAAK,MAAM,KAAK;AAAA,QAC7B;AACA,aAAK,SAAS,WAAW;AACvB,aAAG;AACD,gBAAI,MAAM,GAAG,KAAK,MAAM,IAAI,OAAO,GAAG,KAAK,MAAM,KAAK,YAAY,UAAU,MAAM,QAAQ,KAAK;AAAA,UACjG,SAAS,WAAW;AACpB,iBAAO;AAAA,QACT;AACA,aAAK,QAAQ,GAAG;AAChB,aAAK,QAAQ;AACb,YAAI,OAAO;AACT,cAAI,OAAO,SAAS;AAClB,YAAAA,MAAK,OAAO,EAAE;AAChB,eAAK,QAAQ,WAAW;AACtB,mBAAOA,MAAK,IAAI,CAAC,CAAC;AAAA,UACpB;AAAA,QACF;AACA,eAAO;AAAA,MACT;AACA,UAAI,WAAW,QAAQ,SAAS;AAC9B,gBAAQ,UAAU;AAAA,MACpB,WAAW,WAAW,QAAQ,KAAK;AACjC,gBAAQ,WAAW;AACjB,iBAAO;AAAA,QACT,CAAC;AAAA,MACH,OAAO;AACL,aAAK,SAAS;AAAA,MAChB;AAAA,IACF;AAAA,MACE;AAAA,MACA,OAAO,UAAU,YAAY;AAAA,MAC7B,OAAO,UAAU,cAAc;AAAA,IACjC;AAAA,EACF;AACF,CAAC;AAGD,IAAI,iBAAiB,WAAW;AAAA,EAC9B,4EAA4E,SAAS,QAAQ;AAC3F,KAAC,SAAS,SAAS,SAAS,SAAS;AACnC,eAAS,OAAO,MAAM;AACpB,YAAI,KAAK,MAAM,UAAU;AACzB,WAAG,OAAO,WAAW;AACnB,cAAI,KAAK,GAAG,IAAI,GAAG,MAAM;AACzB,aAAG,IAAI,GAAG;AACV,aAAG,IAAI,GAAG;AACV,aAAG,IAAI,GAAG;AACV,aAAG,IAAI,GAAG;AACV,kBAAQ,GAAG,IAAI,GAAG,IAAI,SAAS,MAAM,GAAG,IAAI,GAAG,IAAI,GAAG,KAAK,KAAK,KAAK,MAAM,MAAM;AAAA,QACnF;AACA,WAAG,IAAI;AACP,WAAG,IAAI;AACP,WAAG,IAAI;AACP,WAAG,IAAI;AACP,WAAG,IAAI;AACP,YAAI,UAAU,OAAO,IAAI;AACvB,aAAG,IAAI;AAAA,QACT,OAAO;AACL,qBAAW;AAAA,QACb;AACA,iBAAS,IAAI,GAAG,IAAI,QAAQ,SAAS,IAAI,KAAK;AAC5C,aAAG,KAAK,QAAQ,WAAW,CAAC,IAAI;AAChC,cAAI,KAAK,QAAQ,QAAQ;AACvB,eAAG,IAAI,GAAG,KAAK,KAAK,GAAG,MAAM;AAAA,UAC/B;AACA,aAAG,KAAK;AAAA,QACV;AAAA,MACF;AACA,eAASA,MAAK,GAAG,IAAI;AACnB,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,eAAO;AAAA,MACT;AACA,eAAS,KAAK,MAAM,MAAM;AACxB,YAAI,KAAK,IAAI,OAAO,IAAI,GAAG,QAAQ,QAAQ,KAAK,OAAO,OAAO,WAAW;AACvE,kBAAQ,GAAG,KAAK,MAAM,KAAK;AAAA,QAC7B;AACA,aAAK,SAAS,WAAW;AACvB,aAAG;AACD,gBAAI,MAAM,GAAG,KAAK,MAAM,IAAI,OAAO,GAAG,KAAK,MAAM,KAAK,YAAY,UAAU,MAAM,QAAQ,KAAK;AAAA,UACjG,SAAS,WAAW;AACpB,iBAAO;AAAA,QACT;AACA,aAAK,QAAQ,GAAG;AAChB,aAAK,QAAQ;AACb,YAAI,OAAO;AACT,cAAI,OAAO,SAAS;AAClB,YAAAA,MAAK,OAAO,EAAE;AAChB,eAAK,QAAQ,WAAW;AACtB,mBAAOA,MAAK,IAAI,CAAC,CAAC;AAAA,UACpB;AAAA,QACF;AACA,eAAO;AAAA,MACT;AACA,UAAI,WAAW,QAAQ,SAAS;AAC9B,gBAAQ,UAAU;AAAA,MACpB,WAAW,WAAW,QAAQ,KAAK;AACjC,gBAAQ,WAAW;AACjB,iBAAO;AAAA,QACT,CAAC;AAAA,MACH,OAAO;AACL,aAAK,SAAS;AAAA,MAChB;AAAA,IACF;AAAA,MACE;AAAA,MACA,OAAO,UAAU,YAAY;AAAA,MAC7B,OAAO,UAAU,cAAc;AAAA,IACjC;AAAA,EACF;AACF,CAAC;AAGD,IAAI,oBAAoB,WAAW;AAAA,EACjC,+EAA+E,SAAS,QAAQ;AAC9F,KAAC,SAAS,SAAS,SAAS,SAAS;AACnC,eAAS,OAAO,MAAM;AACpB,YAAI,KAAK;AACT,WAAG,OAAO,WAAW;AACnB,cAAI,IAAI,GAAG,GAAG,KAAK,GAAG,GAAG,IAAI,GAAG;AAChC,eAAK,EAAE;AACP,gBAAM,OAAO;AACb,cAAI,KAAK,MAAM;AACf,eAAK,EAAE,KAAK,IAAI;AAChB,eAAK,KAAK,OAAO;AACjB,eAAK,EAAE,KAAK,IAAI;AAChB,eAAK,KAAK,OAAO;AACjB,eAAK,EAAE,KAAK,IAAI;AAChB,eAAK,KAAK,MAAM;AAChB,eAAK,EAAE,KAAK,IAAI;AAChB,eAAK,KAAK,MAAM;AAChB,eAAK,KAAK,MAAM;AAChB,YAAE,MAAM;AACR,aAAG,IAAI,KAAK,IAAI;AAChB,iBAAO;AAAA,QACT;AACA,iBAASC,OAAM,KAAK,OAAO;AACzB,cAAI,GAAG,GAAG,IAAI,CAAC;AACf,cAAI,WAAW,QAAQ,IAAI;AACzB,gBAAI,EAAE,KAAK;AAAA,UACb,OAAO;AACL,oBAAQ,KAAK;AACb,iBAAK,IAAI,GAAG,IAAI,MAAM,QAAQ,EAAE,GAAG;AACjC,gBAAE,IAAI,KAAK,EAAE,IAAI,MAAM,KAAK,MAAM,WAAW,CAAC,IAAI,EAAE,IAAI,IAAI,MAAM;AAAA,YACpE;AAAA,UACF;AACA,iBAAO,EAAE,SAAS;AAChB,cAAE,KAAK,CAAC;AACV,eAAK,IAAI,GAAG,IAAI,KAAK,EAAE,OAAO,GAAG,EAAE;AACjC;AACF,cAAI,KAAK;AACP,gBAAI,EAAE,KAAK;AAAA;AAEX,gBAAI,EAAE;AACR,cAAI,IAAI;AACR,cAAI,IAAI;AACR,eAAK,IAAI,KAAK,IAAI,GAAG,EAAE,GAAG;AACxB,gBAAI,KAAK;AAAA,UACX;AAAA,QACF;AACA,QAAAA,OAAM,IAAI,IAAI;AAAA,MAChB;AACA,eAASD,MAAK,GAAG,IAAI;AACnB,WAAG,IAAI,EAAE,EAAE,MAAM;AACjB,WAAG,IAAI,EAAE;AACT,eAAO;AAAA,MACT;AACA,eAAS,KAAK,MAAM,MAAM;AACxB,YAAI,QAAQ;AACV,iBAAO,CAAC,IAAI,KAAK;AACnB,YAAI,KAAK,IAAI,OAAO,IAAI,GAAG,QAAQ,QAAQ,KAAK,OAAO,OAAO,WAAW;AACvE,kBAAQ,GAAG,KAAK,MAAM,KAAK;AAAA,QAC7B;AACA,aAAK,SAAS,WAAW;AACvB,aAAG;AACD,gBAAI,MAAM,GAAG,KAAK,MAAM,IAAI,OAAO,GAAG,KAAK,MAAM,KAAK,YAAY,UAAU,MAAM,QAAQ,KAAK;AAAA,UACjG,SAAS,WAAW;AACpB,iBAAO;AAAA,QACT;AACA,aAAK,QAAQ,GAAG;AAChB,aAAK,QAAQ;AACb,YAAI,OAAO;AACT,cAAI,MAAM;AACR,YAAAA,MAAK,OAAO,EAAE;AAChB,eAAK,QAAQ,WAAW;AACtB,mBAAOA,MAAK,IAAI,CAAC,CAAC;AAAA,UACpB;AAAA,QACF;AACA,eAAO;AAAA,MACT;AACA,UAAI,WAAW,QAAQ,SAAS;AAC9B,gBAAQ,UAAU;AAAA,MACpB,WAAW,WAAW,QAAQ,KAAK;AACjC,gBAAQ,WAAW;AACjB,iBAAO;AAAA,QACT,CAAC;AAAA,MACH,OAAO;AACL,aAAK,YAAY;AAAA,MACnB;AAAA,IACF;AAAA,MACE;AAAA,MACA,OAAO,UAAU,YAAY;AAAA,MAC7B,OAAO,UAAU,cAAc;AAAA,IACjC;AAAA,EACF;AACF,CAAC;AAGD,IAAI,kBAAkB,WAAW;AAAA,EAC/B,6EAA6E,SAAS,QAAQ;AAC5F,KAAC,SAAS,SAAS,SAAS,SAAS;AACnC,eAAS,OAAO,MAAM;AACpB,YAAI,KAAK;AACT,WAAG,OAAO,WAAW;AACnB,cAAI,IAAI,GAAG,GAAG,IAAI,GAAG,GAAG,KAAK,GAAG,GAAG,IAAI;AACvC,aAAG,IAAI,IAAI,IAAI,aAAa;AAC5B,cAAI,EAAE,KAAK,KAAK;AAChB,eAAK,EAAE,KAAK,KAAK,IAAI;AACrB,eAAK,KAAK;AACV,gBAAM,MAAM;AACZ,eAAK,MAAM;AACX,gBAAM,OAAO;AACb,cAAI,EAAE,MAAM,IAAI;AAChB,aAAG,IAAI;AACP,iBAAO,KAAK,IAAI,MAAM,MAAM;AAAA,QAC9B;AACA,iBAASC,OAAM,KAAK,OAAO;AACzB,cAAI,IAAI,GAAG,IAAI,GAAG,GAAG,IAAI,CAAC,GAAG,QAAQ;AACrC,cAAI,WAAW,QAAQ,IAAI;AACzB,gBAAI;AACJ,oBAAQ;AAAA,UACV,OAAO;AACL,oBAAQ,QAAQ;AAChB,gBAAI;AACJ,oBAAQ,KAAK,IAAI,OAAO,MAAM,MAAM;AAAA,UACtC;AACA,eAAK,KAAK,GAAG,IAAI,KAAK,IAAI,OAAO,EAAE,GAAG;AACpC,gBAAI;AACF,mBAAK,MAAM,YAAY,IAAI,MAAM,MAAM,MAAM;AAC/C,gBAAI,MAAM;AACR,kBAAI;AACN,iBAAK,KAAK;AACV,iBAAK,MAAM;AACX,iBAAK,KAAK;AACV,iBAAK,MAAM;AACX,gBAAI,KAAK,GAAG;AACV,kBAAI,IAAI,aAAa;AACrB,mBAAK,EAAE,IAAI,QAAQ,IAAI;AACvB,mBAAK,KAAK,KAAK,KAAK,IAAI;AAAA,YAC1B;AAAA,UACF;AACA,cAAI,MAAM,KAAK;AACb,eAAG,SAAS,MAAM,UAAU,KAAK,OAAO;AAAA,UAC1C;AACA,eAAK;AACL,eAAK,IAAI,IAAI,KAAK,IAAI,GAAG,EAAE,GAAG;AAC5B,gBAAI,EAAE,KAAK,KAAK;AAChB,iBAAK,EAAE,KAAK,KAAK,IAAI;AACrB,iBAAK,KAAK;AACV,kBAAM,MAAM;AACZ,iBAAK,MAAM;AACX,kBAAM,OAAO;AACb,cAAE,MAAM,IAAI;AAAA,UACd;AACA,cAAI,IAAI;AACR,cAAI,IAAI;AACR,cAAI,IAAI;AAAA,QACV;AACA,QAAAA,OAAM,IAAI,IAAI;AAAA,MAChB;AACA,eAASD,MAAK,GAAG,IAAI;AACnB,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE,EAAE,MAAM;AACjB,eAAO;AAAA,MACT;AACA;AACA,eAAS,KAAK,MAAM,MAAM;AACxB,YAAI,QAAQ;AACV,iBAAO,CAAC,IAAI,KAAK;AACnB,YAAI,KAAK,IAAI,OAAO,IAAI,GAAG,QAAQ,QAAQ,KAAK,OAAO,OAAO,WAAW;AACvE,kBAAQ,GAAG,KAAK,MAAM,KAAK;AAAA,QAC7B;AACA,aAAK,SAAS,WAAW;AACvB,aAAG;AACD,gBAAI,MAAM,GAAG,KAAK,MAAM,IAAI,OAAO,GAAG,KAAK,MAAM,KAAK,YAAY,UAAU,MAAM,QAAQ,KAAK;AAAA,UACjG,SAAS,WAAW;AACpB,iBAAO;AAAA,QACT;AACA,aAAK,QAAQ,GAAG;AAChB,aAAK,QAAQ;AACb,YAAI,OAAO;AACT,cAAI,MAAM;AACR,YAAAA,MAAK,OAAO,EAAE;AAChB,eAAK,QAAQ,WAAW;AACtB,mBAAOA,MAAK,IAAI,CAAC,CAAC;AAAA,UACpB;AAAA,QACF;AACA,eAAO;AAAA,MACT;AACA,UAAI,WAAW,QAAQ,SAAS;AAC9B,gBAAQ,UAAU;AAAA,MACpB,WAAW,WAAW,QAAQ,KAAK;AACjC,gBAAQ,WAAW;AACjB,iBAAO;AAAA,QACT,CAAC;AAAA,MACH,OAAO;AACL,aAAK,UAAU;AAAA,MACjB;AAAA,IACF;AAAA,MACE;AAAA,MACA,OAAO,UAAU,YAAY;AAAA,MAC7B,OAAO,UAAU,cAAc;AAAA,IACjC;AAAA,EACF;AACF,CAAC;AAGD,IAAI,iBAAiB,WAAW;AAAA,EAC9B,4EAA4E,SAAS,QAAQ;AAC3F,KAAC,SAAS,SAAS,SAAS,SAAS;AACnC,eAAS,OAAO,MAAM;AACpB,YAAI,KAAK,MAAM,UAAU;AACzB,WAAG,OAAO,WAAW;AACnB,cAAI,IAAI,GAAG,GAAG,IAAI,GAAG,GAAG,IAAI,GAAG,GAAG,IAAI,GAAG;AACzC,cAAI,KAAK,KAAK,MAAM,IAAI;AACxB,cAAI,IAAI,IAAI;AACZ,cAAI,KAAK,KAAK,MAAM,IAAI;AACxB,cAAI,IAAI,IAAI;AACZ,aAAG,IAAI,IAAI,KAAK,KAAK,MAAM,KAAK;AAChC,aAAG,IAAI,IAAI,IAAI,IAAI;AACnB,aAAG,IAAI,KAAK,KAAK,MAAM,KAAK;AAC5B,iBAAO,GAAG,IAAI,IAAI,IAAI;AAAA,QACxB;AACA,WAAG,IAAI;AACP,WAAG,IAAI;AACP,WAAG,IAAI,aAAa;AACpB,WAAG,IAAI;AACP,YAAI,SAAS,KAAK,MAAM,IAAI,GAAG;AAC7B,aAAG,IAAI,OAAO,aAAa;AAC3B,aAAG,IAAI,OAAO;AAAA,QAChB,OAAO;AACL,qBAAW;AAAA,QACb;AACA,iBAAS,IAAI,GAAG,IAAI,QAAQ,SAAS,IAAI,KAAK;AAC5C,aAAG,KAAK,QAAQ,WAAW,CAAC,IAAI;AAChC,aAAG,KAAK;AAAA,QACV;AAAA,MACF;AACA,eAASA,MAAK,GAAG,IAAI;AACnB,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,eAAO;AAAA,MACT;AACA;AACA,eAAS,KAAK,MAAM,MAAM;AACxB,YAAI,KAAK,IAAI,OAAO,IAAI,GAAG,QAAQ,QAAQ,KAAK,OAAO,OAAO,WAAW;AACvE,kBAAQ,GAAG,KAAK,MAAM,KAAK;AAAA,QAC7B;AACA,aAAK,SAAS,WAAW;AACvB,aAAG;AACD,gBAAI,MAAM,GAAG,KAAK,MAAM,IAAI,OAAO,GAAG,KAAK,MAAM,KAAK,YAAY,UAAU,MAAM,QAAQ,KAAK;AAAA,UACjG,SAAS,WAAW;AACpB,iBAAO;AAAA,QACT;AACA,aAAK,QAAQ,GAAG;AAChB,aAAK,QAAQ;AACb,YAAI,OAAO;AACT,cAAI,OAAO,SAAS;AAClB,YAAAA,MAAK,OAAO,EAAE;AAChB,eAAK,QAAQ,WAAW;AACtB,mBAAOA,MAAK,IAAI,CAAC,CAAC;AAAA,UACpB;AAAA,QACF;AACA,eAAO;AAAA,MACT;AACA,UAAI,WAAW,QAAQ,SAAS;AAC9B,gBAAQ,UAAU;AAAA,MACpB,WAAW,WAAW,QAAQ,KAAK;AACjC,gBAAQ,WAAW;AACjB,iBAAO;AAAA,QACT,CAAC;AAAA,MACH,OAAO;AACL,aAAK,SAAS;AAAA,MAChB;AAAA,IACF;AAAA,MACE;AAAA,MACA,OAAO,UAAU,YAAY;AAAA,MAC7B,OAAO,UAAU,cAAc;AAAA,IACjC;AAAA,EACF;AACF,CAAC;AAGD,IAAI,iBAAiB,WAAW;AAAA,EAC9B,sBAAsB;AAAA,EACtB;AACF,CAAC;AAGD,IAAI,qBAAqB,WAAW;AAAA,EAClC,4EAA4E,SAAS,QAAQ;AAC3F,KAAC,SAAS,SAAS,OAAO,MAAM;AAC9B,UAAI,QAAQ,KAAK,SAAS,GAAG,SAAS,IAAI,UAAU,UAAU,aAAa,KAAK,IAAI,OAAO,MAAM,GAAG,eAAe,KAAK,IAAI,GAAG,MAAM,GAAG,WAAW,eAAe,GAAGE,QAAO,QAAQ,GAAG;AACvL,eAAS,YAAY,MAAMC,UAAS,UAAU;AAC5C,YAAI,MAAM,CAAC;AACX,QAAAA,WAAUA,YAAW,OAAO,EAAE,SAAS,KAAK,IAAIA,YAAW,CAAC;AAC5D,YAAI,YAAY,OAAO;AAAA,UACrBA,SAAQ,UAAU,CAAC,MAAM,SAAS,KAAK,CAAC,IAAI,QAAQ,OAAO,SAAS,IAAI;AAAA,UACxE;AAAA,QACF,GAAG,GAAG;AACN,YAAI,OAAO,IAAI,KAAK,GAAG;AACvB,YAAI,OAAO,WAAW;AACpB,cAAI,KAAK,KAAK,EAAE,MAAM,GAAG,IAAI,YAAY,IAAI;AAC7C,iBAAO,KAAK,cAAc;AACxB,kBAAM,KAAK,KAAK;AAChB,iBAAK;AACL,gBAAI,KAAK,EAAE,CAAC;AAAA,UACd;AACA,iBAAO,MAAM,UAAU;AACrB,kBAAM;AACN,iBAAK;AACL,mBAAO;AAAA,UACT;AACA,kBAAQ,KAAK,KAAK;AAAA,QACpB;AACA,aAAK,QAAQ,WAAW;AACtB,iBAAO,KAAK,EAAE,CAAC,IAAI;AAAA,QACrB;AACA,aAAK,QAAQ,WAAW;AACtB,iBAAO,KAAK,EAAE,CAAC,IAAI;AAAA,QACrB;AACA,aAAK,SAAS;AACd,eAAO,SAAS,KAAK,CAAC,GAAG,KAAK;AAC9B,gBAAQA,SAAQ,QAAQ,YAAY,SAAS,OAAO,OAAO,cAAc,OAAO;AAC9E,cAAI,OAAO;AACT,gBAAI,MAAM,GAAG;AACX,cAAAH,MAAK,OAAO,IAAI;AAAA,YAClB;AACA,kBAAM,QAAQ,WAAW;AACvB,qBAAOA,MAAK,MAAM,CAAC,CAAC;AAAA,YACtB;AAAA,UACF;AACA,cAAI,cAAc;AAChB,iBAAK,WAAW;AAChB,mBAAO;AAAA,UACT;AACE,mBAAO;AAAA,QACX;AAAA,UACE;AAAA,UACA;AAAA,UACA,YAAYG,WAAUA,SAAQ,SAAS,QAAQ;AAAA,UAC/CA,SAAQ;AAAA,QACV;AAAA,MACF;AACA,eAAS,KAAK,KAAK;AACjB,YAAI,IAAI,SAAS,IAAI,QAAQ,KAAK,MAAM,KAAK,GAAG,IAAI,GAAG,IAAI,GAAG,IAAI,GAAG,KAAK,GAAG,IAAI,CAAC;AAClF,YAAI,CAAC,QAAQ;AACX,gBAAM,CAAC,QAAQ;AAAA,QACjB;AACA,eAAO,KAAK,OAAO;AACjB,aAAG,MAAM;AAAA,QACX;AACA,aAAK,KAAK,GAAG,KAAK,OAAO,MAAM;AAC7B,aAAG,MAAM,GAAG,IAAID,QAAO,IAAI,IAAI,KAAK,WAAW,KAAK,GAAG;AACvD,aAAG,KAAK;AAAA,QACV;AACA,SAAC,GAAG,IAAI,SAASE,SAAQ;AACvB,cAAI,IAAI,KAAK,GAAG,KAAK,GAAG,GAAG,KAAK,GAAG,GAAG,KAAK,GAAG;AAC9C,iBAAOA,WAAU;AACf,iBAAK,GAAG,KAAKF,QAAO,KAAK;AACzB,iBAAK,KAAK,QAAQ,GAAGA,SAAQ,GAAG,MAAM,GAAG,KAAKA,QAAO,KAAK,QAAQ,GAAG,MAAM;AAAA,UAC7E;AACA,aAAG,IAAI;AACP,aAAG,IAAI;AACP,iBAAO;AAAA,QACT,GAAG,KAAK;AAAA,MACV;AACA,eAASF,MAAK,GAAG,IAAI;AACnB,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE,EAAE,MAAM;AACjB,eAAO;AAAA,MACT;AACA;AACA,eAAS,SAAS,KAAK,OAAO;AAC5B,YAAI,SAAS,CAAC,GAAG,MAAM,OAAO,KAAK;AACnC,YAAI,SAAS,OAAO,UAAU;AAC5B,eAAK,QAAQ,KAAK;AAChB,gBAAI;AACF,qBAAO,KAAK,SAAS,IAAI,OAAO,QAAQ,CAAC,CAAC;AAAA,YAC5C,SAAS,IAAP;AAAA,YACF;AAAA,UACF;AAAA,QACF;AACA,eAAO,OAAO,SAAS,SAAS,OAAO,WAAW,MAAM,MAAM;AAAA,MAChE;AACA,eAAS,OAAO,MAAM,KAAK;AACzB,YAAI,aAAa,OAAO,IAAI,OAAO,IAAI;AACvC,eAAO,IAAI,WAAW,QAAQ;AAC5B,cAAIE,QAAO,KAAKA,SAAQ,SAAS,IAAIA,QAAO,KAAK,MAAM,WAAW,WAAW,GAAG;AAAA,QAClF;AACA,eAAO,SAAS,GAAG;AAAA,MACrB;AACA,eAAS,WAAW;AAClB,YAAI;AACF,cAAI;AACJ,cAAI,eAAe,MAAM,WAAW,cAAc;AAChD,kBAAM,IAAI,KAAK;AAAA,UACjB,OAAO;AACL,kBAAM,IAAI,WAAW,KAAK;AAC1B,aAAC,QAAQ,UAAU,QAAQ,UAAU,gBAAgB,GAAG;AAAA,UAC1D;AACA,iBAAO,SAAS,GAAG;AAAA,QACrB,SAAS,IAAP;AACA,cAAI,UAAU,QAAQ,WAAW,UAAU,WAAW,QAAQ;AAC9D,iBAAO,CAAC,CAAC,IAAI,KAAK,GAAG,SAAS,SAAS,QAAQ,QAAQ,SAAS,KAAK,CAAC;AAAA,QACxE;AAAA,MACF;AACA,eAAS,SAAS,GAAG;AACnB,eAAO,OAAO,aAAa,MAAM,GAAG,CAAC;AAAA,MACvC;AACA,aAAO,KAAK,OAAO,GAAG,KAAK;AAC3B,UAAI,OAAO,UAAU,YAAY,OAAO,SAAS;AAC/C,eAAO,UAAU;AACjB,YAAI;AACF,uBAAa,eAAe;AAAA,QAC9B,SAAS,IAAP;AAAA,QACF;AAAA,MACF,WAAW,OAAO,UAAU,cAAc,OAAO,KAAK;AACpD,eAAO,WAAW;AAChB,iBAAO;AAAA,QACT,CAAC;AAAA,MACH,OAAO;AACL,aAAK,SAAS,WAAW;AAAA,MAC3B;AAAA,IACF;AAAA,MACE,OAAO,SAAS,cAAc,OAAO;AAAA,MACrC,CAAC;AAAA,MACD;AAAA,IACF;AAAA,EACF;AACF,CAAC;AAGD,IAAI,sBAAsB,WAAW;AAAA,EACnC,uEAAuE,SAAS,QAAQ;AACtF,QAAI,QAAQ,aAAa;AACzB,QAAI,SAAS,eAAe;AAC5B,QAAI,SAAS,eAAe;AAC5B,QAAI,YAAY,kBAAkB;AAClC,QAAI,UAAU,gBAAgB;AAC9B,QAAI,SAAS,eAAe;AAC5B,QAAI,KAAK,mBAAmB;AAC5B,OAAG,OAAO;AACV,OAAG,SAAS;AACZ,OAAG,SAAS;AACZ,OAAG,YAAY;AACf,OAAG,UAAU;AACb,OAAG,SAAS;AACZ,WAAO,UAAU;AAAA,EACnB;AACF,CAAC;AAGD,IAAI,yBAAyB,WAAW;AAAA,EACtC,yGAAyG;AAAA,EACzG;AACF,CAAC;AAGD,IAAI,aAAa,WAAW;AAAA,EAC1B,kBAAkB;AAAA,EAClB;AACF,CAAC;AAGD,IAAI,eAAe,WAAW;AAAA,EAC5B,oBAAoB;AAAA,EACpB;AACF,CAAC;AAGD,IAAI,yBAAyB,WAAW;AAAA,EACtC,8BAA8B;AAAA,EAC9B;AACF,CAAC;AAGD,IAAI,qBAAqB,WAAW;AAAA,EAClC,0BAA0B;AAAA,EAC1B;AACF,CAAC;AAGD,IAAI,aAAa,WAAW;AAAA,EAC1B,kBAAkB;AAAA,EAClB;AACF,CAAC;AAGD,IAAI,0CAA0C,WAAW;AAAA,EACvD,4KAA4K,SAAS,QAAQ;AAC3L,QAAI,kCAAkC,MAAM;AAC1C,UAAI,aAAa,OAAO,aAAa,eAAe,SAAS,gBAAgB,SAAS,cAAc,MAAM;AAC1G,UAAI,OAAO,eAAe;AACxB,qBAAa,cAAc;AAC7B,aAAO,SAAS,gCAAgC;AAC9C,yCAAiC,kCAAkC,CAAC;AACpE,iBAAS,mBAAmB;AAC1B,cAAI,WAAW,UAAU,SAAS;AAChC,uCAA2B,WAAW,MAAM;AAAA,UAC9C;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,mBAAmB;AAC1B,cAAI,WAAW,UAAU,SAAS;AAChC,uCAA2B,WAAW,MAAM;AAAA,UAC9C;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,oBAAoB;AAC3B,cAAI,WAAW,UAAU,SAAS;AAChC,uCAA2B,WAAW,MAAM;AAAA,UAC9C;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,oBAAoB;AAC3B,cAAI,WAAW,UAAU,SAAS;AAChC,uCAA2B,WAAW,MAAM;AAAA,UAC9C;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,oBAAoB;AAC3B,cAAI,WAAW,UAAU,SAAS;AAChC,uCAA2B,WAAW,MAAM;AAAA,UAC9C;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,oBAAoB;AAC3B,cAAI,WAAW,UAAU,SAAS;AAChC,uCAA2B,WAAW,MAAM;AAAA,UAC9C;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,oBAAoB;AAC3B,cAAI,WAAW,UAAU,SAAS;AAChC,uCAA2B,WAAW,MAAM;AAAA,UAC9C;AACA,iBAAO;AAAA,QACT;AACA,YAAI,SAAS,OAAO,mCAAmC,cAAc,iCAAiC,CAAC;AACvG,YAAI,qBAAqB;AACzB,eAAO,WAAW,IAAI,QAAQ,SAAS,SAAS,QAAQ;AACtD,gCAAsB;AACtB,+BAAqB;AAAA,QACvB,CAAC;AACD,YAAI;AACJ,YAAI,OAAO,YAAY,eAAe,QAAQ,WAAW;AACvD,4BAAkB,EAAE,mBAAmB,QAAQ,UAAU,mBAAmB,GAAG,oBAAoB,QAAQ,UAAU,oBAAoB,EAAE;AAAA,QAC7I;AACA,YAAI,kBAAkB,OAAO,OAAO,CAAC,GAAG,MAAM;AAC9C,YAAI,aAAa,CAAC;AAClB,YAAI,cAAc;AAClB,YAAI,QAAQ,CAAC,QAAQ,YAAY;AAC/B,gBAAM;AAAA,QACR;AACA,YAAI,qBAAqB,OAAO,WAAW;AAC3C,YAAI,wBAAwB,OAAO,kBAAkB;AACrD,YAAI,sBAAsB,OAAO,YAAY,YAAY,OAAO,QAAQ,aAAa,YAAY,OAAO,QAAQ,SAAS,SAAS;AAClI,YAAI,yBAAyB,OAAO,6BAA6B;AACjE,YAAI,kBAAkB;AACtB,iBAAS,WAAW,MAAM;AACxB,cAAI,OAAO,eAAe;AACxB,mBAAO,OAAO,cAAc,MAAM,eAAe;AAAA,UACnD;AACA,iBAAO,kBAAkB;AAAA,QAC3B;AACA,YAAI,OAAO,WAAW,YAAY;AAClC,iBAAS,mBAAmB,IAAI;AAC9B,cAAI,cAAc;AAChB;AACF,cAAI,QAAQ;AACZ,cAAI,+BAA+B,KAAK;AAAA,QAC1C;AACA,YAAI;AACJ,YAAI;AACJ,YAAI;AACJ,YAAI,qBAAqB;AACvB,cAAI,uBAAuB;AACzB,8BAAkB,aAAa,EAAE,QAAQ,eAAe,IAAI;AAAA,UAC9D,OAAO;AACL,8BAAkB,YAAY;AAAA,UAChC;AACA,0BAAgB,MAAM;AACpB,gBAAI,CAAC,UAAU;AACb,mBAAK,WAAW;AAChB,yBAAW,aAAa;AAAA,YAC1B;AAAA,UACF;AACA,kBAAQ,SAAS,WAAW,UAAU,QAAQ;AAC5C,0BAAc;AACd,uBAAW,SAAS,aAAa,QAAQ;AACzC,mBAAO,GAAG,aAAa,UAAU,SAAS,SAAS,MAAM;AAAA,UAC3D;AACA,uBAAa,CAAC,aAAa;AACzB,gBAAI,MAAM,MAAM,UAAU,IAAI;AAC9B,gBAAI,CAAC,IAAI,QAAQ;AACf,oBAAM,IAAI,WAAW,GAAG;AAAA,YAC1B;AACA,mBAAO;AAAA,UACT;AACA,sBAAY,CAAC,UAAU,QAAQ,YAAY;AACzC,0BAAc;AACd,uBAAW,SAAS,aAAa,QAAQ;AACzC,eAAG,SAAS,UAAU,SAAS,MAAM,MAAM;AACzC,kBAAI;AACF,wBAAQ,IAAI;AAAA;AAEZ,uBAAO,KAAK,MAAM;AAAA,YACtB,CAAC;AAAA,UACH;AACA,cAAI,QAAQ,QAAQ,SAAS,GAAG;AAC9B,0BAAc,QAAQ,QAAQ,GAAG,QAAQ,OAAO,GAAG;AAAA,UACrD;AACA,uBAAa,QAAQ,QAAQ,MAAM,CAAC;AACpC,kBAAQ,MAAM,qBAAqB,SAAS,IAAI;AAC9C,gBAAI,EAAE,cAAc,aAAa;AAC/B,oBAAM;AAAA,YACR;AAAA,UACF,CAAC;AACD,kBAAQ,MAAM,sBAAsB,SAAS,QAAQ;AACnD,kBAAM;AAAA,UACR,CAAC;AACD,kBAAQ,CAAC,QAAQ,YAAY;AAC3B,gBAAI,iBAAiB,GAAG;AACtB,sBAAQ,cAAc;AACtB,oBAAM;AAAA,YACR;AACA,+BAAmB,OAAO;AAC1B,oBAAQ,QAAQ,MAAM;AAAA,UACxB;AACA,iBAAO,aAAa,WAAW;AAC7B,mBAAO;AAAA,UACT;AACA,cAAI;AACJ,cAAI;AACF,gCAAoB,uBAAuB;AAAA,UAC7C,SAAS,IAAP;AACA,oBAAQ,MAAM,yGAAyG;AACvH,kBAAM;AAAA,UACR;AACA,iBAAO,SAAS,kBAAkB;AAAA,QACpC,WAAW,sBAAsB,uBAAuB;AACtD,cAAI,uBAAuB;AACzB,8BAAkB,KAAK,SAAS;AAAA,UAClC,WAAW,OAAO,aAAa,eAAe,SAAS,eAAe;AACpE,8BAAkB,SAAS,cAAc;AAAA,UAC3C;AACA,cAAI,OAAO,eAAe,eAAe,YAAY;AACnD,8BAAkB;AAAA,UACpB;AACA,cAAI,gBAAgB,QAAQ,OAAO,MAAM,GAAG;AAC1C,8BAAkB,gBAAgB,OAAO,GAAG,gBAAgB,QAAQ,UAAU,EAAE,EAAE,YAAY,GAAG,IAAI,CAAC;AAAA,UACxG,OAAO;AACL,8BAAkB;AAAA,UACpB;AACA,cAAI,CAAC,qBAAqB;AACxB,oBAAQ,CAAC,QAAQ;AACf,kBAAI,MAAM,IAAI,eAAe;AAC7B,kBAAI,KAAK,OAAO,KAAK,KAAK;AAC1B,kBAAI,KAAK,IAAI;AACb,qBAAO,IAAI;AAAA,YACb;AACA,gBAAI,uBAAuB;AACzB,2BAAa,CAAC,QAAQ;AACpB,oBAAI,MAAM,IAAI,eAAe;AAC7B,oBAAI,KAAK,OAAO,KAAK,KAAK;AAC1B,oBAAI,eAAe;AACnB,oBAAI,KAAK,IAAI;AACb,uBAAO,IAAI,WAAW,IAAI,QAAQ;AAAA,cACpC;AAAA,YACF;AACA,wBAAY,CAAC,KAAK,QAAQ,YAAY;AACpC,kBAAI,MAAM,IAAI,eAAe;AAC7B,kBAAI,KAAK,OAAO,KAAK,IAAI;AACzB,kBAAI,eAAe;AACnB,kBAAI,SAAS,MAAM;AACjB,oBAAI,IAAI,UAAU,OAAO,IAAI,UAAU,KAAK,IAAI,UAAU;AACxD,yBAAO,IAAI,QAAQ;AACnB;AAAA,gBACF;AACA,wBAAQ;AAAA,cACV;AACA,kBAAI,UAAU;AACd,kBAAI,KAAK,IAAI;AAAA,YACf;AAAA,UACF;AACA,2BAAiB,CAAC,UAAU,SAAS,QAAQ;AAAA,QAC/C,OAAO;AAAA,QACP;AACA,YAAI,qBAAqB;AACvB,cAAI,OAAO,gBAAgB,aAAa;AACtC,mBAAO,cAAc,mBAAmB,EAAE;AAAA,UAC5C;AAAA,QACF;AACA,YAAI,eAAe,QAAQ,IAAI,KAAK,OAAO;AAC3C,YAAI,kBAAkB,QAAQ,KAAK,KAAK,OAAO;AAC/C,YAAI,qBAAqB;AACvB,wBAAc;AACd,yBAAe,CAAC,QAAQ,GAAG,UAAU,GAAG,MAAM,IAAI;AAClD,4BAAkB,CAAC,QAAQ,GAAG,UAAU,GAAG,MAAM,IAAI;AAAA,QACvD;AACA,YAAI,MAAM,OAAO,YAAY;AAC7B,YAAI,MAAM,OAAO,eAAe;AAChC,eAAO,OAAO,QAAQ,eAAe;AACrC,0BAAkB;AAClB,YAAI,OAAO;AACT,uBAAa,OAAO;AACtB,YAAI,OAAO;AACT,wBAAc,OAAO;AACvB,YAAI,OAAO;AACT,kBAAQ,OAAO;AACjB,YAAI,eAAe;AACnB,iBAAS,SAAS,MAAM;AACtB,cAAI,CAAC,SAAS;AACZ,qBAAS,QAAQ,CAAC;AACpB,cAAI,CAAC,SAAS,MAAM,OAAO;AACzB,qBAAS,MAAM,QAAQ;AACvB,gBAAI,IAAI;AAAA,UACV;AAAA,QACF;AACA,iBAAS,wBAAwB,OAAO,KAAK;AAC3C,cAAI,OAAO,YAAY,aAAa,YAAY;AAC9C,gBAAI,YAAY,EAAE,KAAK,OAAO,KAAK,OAAO,KAAK,OAAO,KAAK,MAAM;AACjE,gBAAI,OAAO,EAAE,YAAY,CAAC,GAAG,SAAS,IAAI,MAAM,MAAM,CAAC,IAAI,CAAC,UAAU,IAAI,GAAG,EAAE;AAC/E,qBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,mBAAK,WAAW,KAAK,UAAU,IAAI,IAAI;AAAA,YACzC;AACA,mBAAO,IAAI,YAAY,SAAS,MAAM,KAAK;AAAA,UAC7C;AACA,cAAI,cAAc,CAAC,GAAG,GAAG,GAAG,EAAE;AAC9B,cAAI,SAAS,IAAI,MAAM,GAAG,CAAC;AAC3B,cAAI,WAAW,IAAI,MAAM,CAAC;AAC1B,cAAI,YAAY,EAAE,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,IAAI;AACzD,sBAAY,KAAK,SAAS,MAAM;AAChC,mBAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,EAAE,IAAI;AAC3C,wBAAY,KAAK,UAAU,SAAS,IAAI;AAAA,UAC1C;AACA,cAAI,UAAU,KAAK;AACjB,wBAAY,KAAK,CAAC;AAAA,UACpB,OAAO;AACL,0BAAc,YAAY,OAAO,CAAC,GAAG,UAAU,OAAO,CAAC;AAAA,UACzD;AACA,sBAAY,KAAK,YAAY,SAAS;AACtC,cAAI,QAAQ,IAAI,WAAW,CAAC,GAAG,IAAI,KAAK,KAAK,GAAG,GAAG,GAAG,CAAC,EAAE,OAAO,aAAa,CAAC,GAAG,GAAG,GAAG,GAAG,KAAK,GAAG,KAAK,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,KAAK,GAAG,CAAC,CAAC,CAAC;AACpI,cAAI,UAAU,IAAI,YAAY,OAAO,KAAK;AAC1C,cAAI,WAAW,IAAI,YAAY,SAAS,SAAS,EAAE,KAAK,EAAE,KAAK,MAAM,EAAE,CAAC;AACxE,cAAI,cAAc,SAAS,QAAQ;AACnC,iBAAO;AAAA,QACT;AACA,YAAI,mBAAmB,CAAC;AACxB,YAAI;AACJ,iBAAS,oBAAoB;AAC3B,cAAI,iBAAiB,QAAQ;AAC3B,mBAAO,iBAAiB,IAAI;AAAA,UAC9B;AACA,cAAI;AACF,sBAAU,KAAK,CAAC;AAAA,UAClB,SAAS,MAAP;AACA,gBAAI,EAAE,gBAAgB,aAAa;AACjC,oBAAM;AAAA,YACR;AACA,kBAAM;AAAA,UACR;AACA,iBAAO,UAAU,SAAS;AAAA,QAC5B;AACA,iBAAS,eAAe,QAAQE,SAAQ;AACtC,mBAAS,KAAK,QAAQ,KAAK,SAASA,SAAQ,MAAM;AAChD,gBAAI,OAAO,kBAAkB,EAAE;AAC/B,gBAAI,MAAM;AACR,kCAAoB,IAAI,MAAM,EAAE;AAAA,YAClC;AAAA,UACF;AAAA,QACF;AACA,YAAI,WAAW;AACf,YAAI,cAAc,CAAC,UAAU;AAC3B,qBAAW;AAAA,QACb;AACA,YAAI,eAAe,QAAQ;AAC3B,YAAI,gBAAgB,QAAQ;AAC5B,YAAI,0BAA0B,QAAQ;AACtC,YAAI;AACJ,YAAI,OAAO;AACT,uBAAa,OAAO;AACtB,YAAI,gBAAgB,OAAO,oBAAoB;AAC/C,YAAI,OAAO,gBAAgB,UAAU;AACnC,gBAAM,iCAAiC;AAAA,QACzC;AACA,YAAI;AACJ,YAAI;AACJ,YAAI,QAAQ;AACZ,YAAI;AACJ,iBAAS,QAAQ,WAAW,MAAM;AAChC,cAAI,CAAC,WAAW;AACd,kBAAM,IAAI;AAAA,UACZ;AAAA,QACF;AACA,iBAAS,SAAS,OAAO;AACvB,cAAI,QAAQ,OAAO,MAAM;AACzB,iBAAO;AAAA,QACT;AACA,iBAAS,MAAM,OAAO,YAAY,UAAU,MAAM,MAAM;AACtD,cAAI,MAAM,EAAE,UAAU,SAAS,KAAK;AAClC,gBAAI,OAAO;AACX,gBAAI,QAAQ,QAAQ,QAAQ,UAAU,QAAQ,GAAG;AAC/C,kBAAI,OAAO,IAAI,UAAU,KAAK;AAC9B,qBAAO,WAAW,GAAG;AACrB,2BAAa,KAAK,MAAM,GAAG;AAAA,YAC7B;AACA,mBAAO;AAAA,UACT,GAAG,SAAS,SAAS,KAAK;AACxB,gBAAI,OAAO,WAAW,IAAI,MAAM;AAChC,+BAAmB,KAAK,IAAI;AAC5B,mBAAO;AAAA,UACT,EAAE;AACF,mBAAS,mBAAmB,MAAM;AAChC,gBAAI,eAAe;AACjB,qBAAO,aAAa,IAAI;AAC1B,gBAAI,eAAe;AACjB,qBAAO,QAAQ,IAAI;AACrB,mBAAO;AAAA,UACT;AACA,cAAI,QAAQ,SAAS,KAAK;AAC1B,cAAI,QAAQ,CAAC;AACb,cAAI,SAAS;AACb,cAAI,MAAM;AACR,qBAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,kBAAI,YAAY,IAAI,SAAS;AAC7B,kBAAI,WAAW;AACb,oBAAI,WAAW;AACb,2BAAS,UAAU;AACrB,sBAAM,MAAM,UAAU,KAAK,GAAG;AAAA,cAChC,OAAO;AACL,sBAAM,MAAM,KAAK;AAAA,cACnB;AAAA,YACF;AAAA,UACF;AACA,cAAI,MAAM,MAAM,MAAM,MAAM,KAAK;AACjC,mBAAS,OAAO,MAAM;AACpB,gBAAI,WAAW;AACb,2BAAa,MAAM;AACrB,mBAAO,mBAAmB,IAAI;AAAA,UAChC;AACA,gBAAM,OAAO,GAAG;AAChB,iBAAO;AAAA,QACT;AACA,iBAAS,MAAM,OAAO,YAAY,UAAU,MAAM;AAChD,qBAAW,YAAY,CAAC;AACxB,cAAI,cAAc,SAAS,MAAM,SAAS,MAAM;AAC9C,mBAAO,SAAS;AAAA,UAClB,CAAC;AACD,cAAI,aAAa,eAAe;AAChC,cAAI,cAAc,eAAe,CAAC,MAAM;AACtC,mBAAO,SAAS,KAAK;AAAA,UACvB;AACA,iBAAO,WAAW;AAChB,mBAAO,MAAM,OAAO,YAAY,UAAU,WAAW,IAAI;AAAA,UAC3D;AAAA,QACF;AACA,YAAI,cAAc;AAClB,iBAAS,mBAAmB,UAAU;AACpC,cAAI,cAAc,IAAI,YAAY,QAAQ;AAC1C,eAAK,SAAS,CAAC,SAAS;AACtB,gBAAI,KAAK,kBAAkB,mBAAmB;AAC5C,qBAAO,IAAI,WAAW,IAAI;AAAA,YAC5B;AACA,mBAAO,YAAY,OAAO,KAAK,aAAa,IAAI;AAAA,UAClD;AAAA,QACF;AACA,YAAI,cAAc,OAAO,gBAAgB,cAAc,IAAI,mBAAmB,MAAM,IAAI;AACxF,iBAAS,kBAAkB,MAAM,KAAK,gBAAgB;AACpD,cAAI,SAAS,MAAM;AACnB,cAAI,SAAS;AACb,iBAAO,KAAK,WAAW,EAAE,UAAU;AACjC,cAAE;AACJ,cAAI,SAAS,MAAM,MAAM,KAAK,YAAY,aAAa;AACrD,mBAAO,YAAY,OAAO,KAAK,SAAS,KAAK,MAAM,CAAC;AAAA,UACtD,OAAO;AACL,gBAAI,MAAM;AACV,mBAAO,MAAM,QAAQ;AACnB,kBAAI,KAAK,KAAK;AACd,kBAAI,EAAE,KAAK,MAAM;AACf,uBAAO,OAAO,aAAa,EAAE;AAC7B;AAAA,cACF;AACA,kBAAI,KAAK,KAAK,SAAS;AACvB,mBAAK,KAAK,QAAQ,KAAK;AACrB,uBAAO,OAAO,cAAc,KAAK,OAAO,IAAI,EAAE;AAC9C;AAAA,cACF;AACA,kBAAI,KAAK,KAAK,SAAS;AACvB,mBAAK,KAAK,QAAQ,KAAK;AACrB,sBAAM,KAAK,OAAO,KAAK,MAAM,IAAI;AAAA,cACnC,OAAO;AACL,sBAAM,KAAK,MAAM,KAAK,MAAM,KAAK,MAAM,IAAI,KAAK,SAAS;AAAA,cAC3D;AACA,kBAAI,KAAK,OAAO;AACd,uBAAO,OAAO,aAAa,EAAE;AAAA,cAC/B,OAAO;AACL,oBAAI,KAAK,KAAK;AACd,uBAAO,OAAO,aAAa,QAAQ,MAAM,IAAI,QAAQ,KAAK,IAAI;AAAA,cAChE;AAAA,YACF;AAAA,UACF;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,aAAa,KAAK,gBAAgB;AACzC,iBAAO,MAAM,kBAAkB,iBAAiB,GAAG,KAAK,cAAc,IAAI;AAAA,QAC5E;AACA,iBAAS,kBAAkB,KAAK,MAAM,QAAQ,iBAAiB;AAC7D,cAAI,EAAE,kBAAkB;AACtB,mBAAO;AACT,cAAI,WAAW;AACf,cAAI,SAAS,SAAS,kBAAkB;AACxC,mBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,gBAAI,IAAI,IAAI,WAAW,EAAE;AACzB,gBAAI,KAAK,SAAS,KAAK,OAAO;AAC5B,kBAAI,KAAK,IAAI,WAAW,EAAE,EAAE;AAC5B,kBAAI,UAAU,IAAI,SAAS,MAAM,KAAK;AAAA,YACxC;AACA,gBAAI,KAAK,KAAK;AACZ,kBAAI,UAAU;AACZ;AACF,mBAAK,YAAY;AAAA,YACnB,WAAW,KAAK,MAAM;AACpB,kBAAI,SAAS,KAAK;AAChB;AACF,mBAAK,YAAY,MAAM,KAAK;AAC5B,mBAAK,YAAY,MAAM,IAAI;AAAA,YAC7B,WAAW,KAAK,OAAO;AACrB,kBAAI,SAAS,KAAK;AAChB;AACF,mBAAK,YAAY,MAAM,KAAK;AAC5B,mBAAK,YAAY,MAAM,KAAK,IAAI;AAChC,mBAAK,YAAY,MAAM,IAAI;AAAA,YAC7B,OAAO;AACL,kBAAI,SAAS,KAAK;AAChB;AACF,mBAAK,YAAY,MAAM,KAAK;AAC5B,mBAAK,YAAY,MAAM,KAAK,KAAK;AACjC,mBAAK,YAAY,MAAM,KAAK,IAAI;AAChC,mBAAK,YAAY,MAAM,IAAI;AAAA,YAC7B;AAAA,UACF;AACA,eAAK,UAAU;AACf,iBAAO,SAAS;AAAA,QAClB;AACA,iBAAS,aAAa,KAAK,QAAQ,iBAAiB;AAClD,iBAAO,kBAAkB,KAAK,iBAAiB,GAAG,QAAQ,eAAe;AAAA,QAC3E;AACA,iBAAS,gBAAgB,KAAK;AAC5B,cAAI,MAAM;AACV,mBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,gBAAI,IAAI,IAAI,WAAW,EAAE;AACzB,gBAAI,KAAK,SAAS,KAAK;AACrB,kBAAI,UAAU,IAAI,SAAS,MAAM,IAAI,WAAW,EAAE,EAAE,IAAI;AAC1D,gBAAI,KAAK;AACP,gBAAE;AAAA,qBACK,KAAK;AACZ,qBAAO;AAAA,qBACA,KAAK;AACZ,qBAAO;AAAA;AAEP,qBAAO;AAAA,UACX;AACA,iBAAO;AAAA,QACT;AACA,YAAI,eAAe,OAAO,gBAAgB,cAAc,IAAI,mBAAmB,UAAU,IAAI;AAC7F,iBAAS,mBAAmB,QAAQ,SAAS;AAC3C,2BAAiB,EAAE,IAAI,QAAQ,OAAO;AAAA,QACxC;AACA,iBAAS,mBAAmB,KAAK,SAAS,aAAa;AACrD,mBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,6BAAiB,EAAE,aAAa,KAAK,IAAI,WAAW,EAAE;AAAA,UACxD;AACA,cAAI,CAAC;AACH,6BAAiB,EAAE,WAAW,KAAK;AAAA,QACvC;AACA,iBAAS,QAAQ,GAAG,UAAU;AAC5B,cAAI,IAAI,WAAW,GAAG;AACpB,iBAAK,WAAW,IAAI;AAAA,UACtB;AACA,iBAAO;AAAA,QACT;AACA,YAAI,SAAS,OAAO,QAAQ,QAAQ,SAAS,QAAQ,SAAS,SAAS;AACvE,YAAI,wBAAwB;AAC1B,oBAAU,OAAO;AAAA,QACnB;AACA,iBAAS,2BAA2B,KAAK;AACvC,oBAAU;AACV,iBAAO,WAAW,QAAQ,IAAI,UAAU,GAAG;AAC3C,iBAAO,YAAY,SAAS,IAAI,WAAW,GAAG;AAC9C,iBAAO,YAAY,SAAS,IAAI,WAAW,GAAG;AAC9C,iBAAO,YAAY,SAAS,IAAI,WAAW,GAAG;AAC9C,iBAAO,aAAa,UAAU,IAAI,YAAY,GAAG;AACjD,iBAAO,aAAa,UAAU,IAAI,YAAY,GAAG;AACjD,iBAAO,aAAa,UAAU,IAAI,aAAa,GAAG;AAClD,iBAAO,aAAa,UAAU,IAAI,aAAa,GAAG;AAAA,QACpD;AACA,YAAI,iBAAiB,OAAO,qBAAqB;AACjD,YAAI,wBAAwB;AAC1B,uBAAa,OAAO;AACpB,oBAAU,OAAO;AAAA,QACnB,OAAO;AACL,cAAI,OAAO,eAAe;AACxB,yBAAa,OAAO;AAAA,UACtB,OAAO;AACL,yBAAa,IAAI,YAAY,OAAO,EAAE,WAAW,iBAAiB,OAAO,WAAW,aAAa,OAAO,UAAU,KAAK,CAAC;AACxH,gBAAI,EAAE,WAAW,kBAAkB,oBAAoB;AACrD,kBAAI,6NAA6N;AACjO,kBAAI,qBAAqB;AACvB,wBAAQ,IAAI,mHAAmH;AAAA,cACjI;AACA,oBAAM,MAAM,YAAY;AAAA,YAC1B;AAAA,UACF;AAAA,QACF;AACA,YAAI,YAAY;AACd,oBAAU,WAAW;AAAA,QACvB;AACA,yBAAiB,QAAQ;AACzB,mCAA2B,OAAO;AAClC,YAAI;AACJ,YAAI,eAAe,CAAC;AACpB,YAAI,aAAa,CAAC;AAClB,YAAI,aAAa,CAAC;AAClB,YAAI,gBAAgB,CAAC;AACrB,YAAI,qBAAqB;AACzB,YAAI,gBAAgB;AACpB,YAAI,0BAA0B;AAC9B,iBAAS,mBAAmB;AAC1B,iBAAO,iBAAiB,0BAA0B;AAAA,QACpD;AACA,iBAAS,SAAS;AAChB,cAAI,OAAO,WAAW;AACpB,gBAAI,OAAO,OAAO,aAAa;AAC7B,qBAAO,YAAY,CAAC,OAAO,SAAS;AACtC,mBAAO,OAAO,UAAU,QAAQ;AAC9B,0BAAY,OAAO,UAAU,MAAM,CAAC;AAAA,YACtC;AAAA,UACF;AACA,+BAAqB,YAAY;AAAA,QACnC;AACA,iBAAS,cAAc;AACrB,+BAAqB;AACrB,cAAI;AACF;AACF,+BAAqB,UAAU;AAAA,QACjC;AACA,iBAAS,cAAc;AACrB,cAAI;AACF;AACF,kBAAQ,oBAAoB;AAC5B,0BAAgB;AAAA,QAClB;AACA,iBAAS,UAAU;AACjB,cAAI;AACF;AACF,cAAI,OAAO,YAAY;AACrB,gBAAI,OAAO,OAAO,cAAc;AAC9B,qBAAO,aAAa,CAAC,OAAO,UAAU;AACxC,mBAAO,OAAO,WAAW,QAAQ;AAC/B,2BAAa,OAAO,WAAW,MAAM,CAAC;AAAA,YACxC;AAAA,UACF;AACA,+BAAqB,aAAa;AAAA,QACpC;AACA,iBAAS,YAAY,IAAI;AACvB,uBAAa,QAAQ,EAAE;AAAA,QACzB;AACA,iBAAS,UAAU,IAAI;AACrB,qBAAW,QAAQ,EAAE;AAAA,QACvB;AACA,iBAAS,aAAa,IAAI;AACxB,wBAAc,QAAQ,EAAE;AAAA,QAC1B;AACA,YAAI,kBAAkB;AACtB,YAAI,uBAAuB;AAC3B,YAAI,wBAAwB;AAC5B,iBAAS,iBAAiB,IAAI;AAC5B;AACA,cAAI,OAAO,2BAA2B;AACpC,mBAAO,0BAA0B,eAAe;AAAA,UAClD;AAAA,QACF;AACA,iBAAS,oBAAoB,IAAI;AAC/B;AACA,cAAI,OAAO,2BAA2B;AACpC,mBAAO,0BAA0B,eAAe;AAAA,UAClD;AACA,cAAI,mBAAmB,GAAG;AACxB,gBAAI,yBAAyB,MAAM;AACjC,4BAAc,oBAAoB;AAClC,qCAAuB;AAAA,YACzB;AACA,gBAAI,uBAAuB;AACzB,kBAAI,WAAW;AACf,sCAAwB;AACxB,uBAAS;AAAA,YACX;AAAA,UACF;AAAA,QACF;AACA,eAAO,qBAAqB,CAAC;AAC7B,eAAO,qBAAqB,CAAC;AAC7B,iBAAS,MAAM,MAAM;AACnB,cAAI,wBAAwB;AAC1B,wBAAY,EAAE,OAAO,WAAW,OAAO,KAAK,CAAC;AAAA,UAC/C,OAAO;AACL,gBAAI,OAAO,YAAY;AACrB,qBAAO,WAAW,IAAI;AAAA,YACxB;AAAA,UACF;AACA,iBAAO,aAAa,OAAO;AAC3B,cAAI,IAAI;AACR,kBAAQ;AACR,uBAAa;AACb,kBAAQ;AACR,cAAI,KAAK,IAAI,YAAY,aAAa,IAAI;AAC1C,6BAAmB,EAAE;AACrB,gBAAM;AAAA,QACR;AACA,YAAI,gBAAgB;AACpB,iBAAS,UAAU,UAAU;AAC3B,iBAAO,SAAS,WAAW,aAAa;AAAA,QAC1C;AACA,iBAAS,UAAU,UAAU;AAC3B,iBAAO,SAAS,WAAW,SAAS;AAAA,QACtC;AACA,YAAI;AACJ,yBAAiB;AACjB,YAAI,CAAC,UAAU,cAAc,GAAG;AAC9B,2BAAiB,WAAW,cAAc;AAAA,QAC5C;AACA,iBAAS,UAAU,MAAM;AACvB,cAAI;AACF,gBAAI,QAAQ,kBAAkB,YAAY;AACxC,qBAAO,IAAI,WAAW,UAAU;AAAA,YAClC;AACA,gBAAI,YAAY;AACd,qBAAO,WAAW,IAAI;AAAA,YACxB,OAAO;AACL,oBAAM;AAAA,YACR;AAAA,UACF,SAAS,MAAP;AACA,kBAAM,IAAI;AAAA,UACZ;AAAA,QACF;AACA,iBAAS,mBAAmB;AAC1B,cAAI,CAAC,eAAe,sBAAsB,wBAAwB;AAChE,gBAAI,OAAO,UAAU,cAAc,CAAC,UAAU,cAAc,GAAG;AAC7D,qBAAO,MAAM,gBAAgB,EAAE,aAAa,cAAc,CAAC,EAAE,KAAK,SAAS,UAAU;AACnF,oBAAI,CAAC,SAAS,OAAO;AACnB,wBAAM,yCAAyC,iBAAiB;AAAA,gBAClE;AACA,uBAAO,SAAS,eAAe;AAAA,cACjC,CAAC,EAAE,MAAM,WAAW;AAClB,uBAAO,UAAU,cAAc;AAAA,cACjC,CAAC;AAAA,YACH,OAAO;AACL,kBAAI,WAAW;AACb,uBAAO,IAAI,QAAQ,SAAS,SAAS,QAAQ;AAC3C,4BAAU,gBAAgB,SAAS,UAAU;AAC3C,4BAAQ,IAAI,WAAW,QAAQ,CAAC;AAAA,kBAClC,GAAG,MAAM;AAAA,gBACX,CAAC;AAAA,cACH;AAAA,YACF;AAAA,UACF;AACA,iBAAO,QAAQ,QAAQ,EAAE,KAAK,WAAW;AACvC,mBAAO,UAAU,cAAc;AAAA,UACjC,CAAC;AAAA,QACH;AACA,iBAAS,aAAa;AACpB,cAAI,OAAO,EAAE,OAAO,eAAe,0BAA0B,cAAc;AAC3E,mBAAS,gBAAgB,UAAU,SAAS;AAC1C,gBAAI,WAAW,SAAS;AACxB,mBAAO,SAAS;AAChB,4BAAgB,OAAO,OAAO,sBAAsB;AACpD,wBAAY,OAAO,OAAO;AAC1B,sBAAU,OAAO,OAAO,oBAAoB;AAC5C,yBAAa;AACb,gBAAI,CAAC,wBAAwB;AAC3B,kBAAI,mBAAmB,QAAQ,cAAc;AAC7C,sBAAQ,cAAc,QAAQ,SAAS,GAAG;AACxC,wBAAQ,uBAAuB,GAAG,WAAW;AAC3C,sBAAI,CAAC,EAAE;AACL,wCAAoB,kBAAkB;AAAA,gBAC1C,CAAC;AAAA,cACH,CAAC;AAAA,YACH;AAAA,UACF;AACA,cAAI,CAAC,wBAAwB;AAC3B,6BAAiB,kBAAkB;AAAA,UACrC;AACA,mBAAS,2BAA2B,QAAQ;AAC1C,4BAAgB,OAAO,aAAa,OAAO,SAAS;AAAA,UACtD;AACA,mBAAS,uBAAuB,UAAU;AACxC,mBAAO,iBAAiB,EAAE,KAAK,SAAS,QAAQ;AAC9C,qBAAO,YAAY,YAAY,QAAQ,IAAI;AAAA,YAC7C,CAAC,EAAE,KAAK,SAAS,UAAU;AACzB,qBAAO;AAAA,YACT,CAAC,EAAE,KAAK,UAAU,SAAS,QAAQ;AACjC,kBAAI,4CAA4C,MAAM;AACtD,oBAAM,MAAM;AAAA,YACd,CAAC;AAAA,UACH;AACA,mBAAS,mBAAmB;AAC1B,gBAAI,CAAC,cAAc,OAAO,YAAY,yBAAyB,cAAc,CAAC,UAAU,cAAc,KAAK,CAAC,UAAU,cAAc,KAAK,OAAO,UAAU,YAAY;AACpK,qBAAO,MAAM,gBAAgB,EAAE,aAAa,cAAc,CAAC,EAAE,KAAK,SAAS,UAAU;AACnF,oBAAI,SAAS,YAAY,qBAAqB,UAAU,IAAI;AAC5D,uBAAO,OAAO,KAAK,4BAA4B,SAAS,QAAQ;AAC9D,sBAAI,oCAAoC,MAAM;AAC9C,sBAAI,2CAA2C;AAC/C,yBAAO,uBAAuB,0BAA0B;AAAA,gBAC1D,CAAC;AAAA,cACH,CAAC;AAAA,YACH,OAAO;AACL,qBAAO,uBAAuB,0BAA0B;AAAA,YAC1D;AAAA,UACF;AACA,cAAI,OAAO,oBAAoB;AAC7B,gBAAI;AACF,kBAAI,WAAW,OAAO,mBAAmB,MAAM,eAAe;AAC9D,qBAAO;AAAA,YACT,SAAS,IAAP;AACA,kBAAI,wDAAwD,EAAE;AAC9D,qBAAO;AAAA,YACT;AAAA,UACF;AACA,2BAAiB,EAAE,MAAM,kBAAkB;AAC3C,iBAAO,CAAC;AAAA,QACV;AACA,YAAI;AACJ,YAAI;AACJ,YAAI,aAAa,CAAC;AAClB,iBAAS,qBAAqB,YAAY;AACxC,iBAAO,WAAW,SAAS,GAAG;AAC5B,gBAAI,WAAW,WAAW,MAAM;AAChC,gBAAI,OAAO,YAAY,YAAY;AACjC,uBAAS,MAAM;AACf;AAAA,YACF;AACA,gBAAI,QAAQ,SAAS;AACrB,gBAAI,OAAO,UAAU,UAAU;AAC7B,kBAAI,SAAS,QAAQ,QAAQ;AAC3B,kCAAkB,KAAK,EAAE;AAAA,cAC3B,OAAO;AACL,kCAAkB,KAAK,EAAE,SAAS,GAAG;AAAA,cACvC;AAAA,YACF,OAAO;AACL,oBAAM,SAAS,QAAQ,SAAS,OAAO,SAAS,GAAG;AAAA,YACrD;AAAA,UACF;AAAA,QACF;AACA,iBAAS,cAAc,GAAG;AACxB,cAAI,SAAS,UAAU;AACvB,cAAI,MAAM,EAAE;AACZ,uBAAa,MAAM;AACnB,iBAAO;AAAA,QACT;AACA,iBAAS,SAAS,OAAO;AACvB,iBAAO;AAAA,QACT;AACA,iBAAS,YAAY,MAAM;AACzB,cAAI,QAAQ;AACZ,iBAAO,KAAK,QAAQ,OAAO,SAAS,GAAG;AACrC,gBAAI,IAAI,SAAS,CAAC;AAClB,mBAAO,MAAM,IAAI,IAAI,IAAI,OAAO,IAAI;AAAA,UACtC,CAAC;AAAA,QACH;AACA,iBAAS,WAAW,aAAa;AAC/B,4BAAkB,EAAE,eAAe,KAAK;AACxC,cAAI,UAAU,QAAQ,SAAS;AAC/B,iBAAO,QAAQ,SAAS;AACxB,kBAAQ,OAAO,UAAU;AACzB,wCAA8B,WAAW;AACzC,kBAAQ,eAAe,OAAO,QAAQ,eAAe,QAAQ,QAAQ,MAAM,GAAG,CAAC;AAC/E,kBAAQ,OAAO,UAAU;AAAA,QAC3B;AACA,iBAAS,aAAa,aAAa;AACjC,cAAI,UAAU,QAAQ,SAAS;AAC/B,kBAAQ,OAAO,YAAY,EAAE,OAAO,SAAS,CAAC;AAAA,QAChD;AACA,iBAAS,cAAc,aAAa;AAClC,cAAI,UAAU,QAAQ,SAAS;AAC/B,cAAI,SAAS;AACX,8BAAkB,EAAE,eAAe,KAAK;AACxC,gBAAI,SAAS,QAAQ;AACrB,oBAAQ,mBAAmB,MAAM;AAAA,UACnC;AAAA,QACF;AACA,iBAAS,MAAM,QAAQ;AACrB,eAAK,MAAM;AAAA,QACb;AACA,iBAAS,gBAAgB,IAAI;AAC3B,cAAI,cAAc,cAAc,MAAM,UAAU;AAC9C,mBAAO;AAAA,UACT;AACA,gBAAM,GAAG,EAAE;AAAA,QACb;AACA,YAAI,UAAU,EAAE,eAAe,CAAC,GAAG,gBAAgB,CAAC,GAAG,kBAAkB,CAAC,GAAG,MAAM,WAAW;AAC5F,cAAI,wBAAwB;AAC1B,oBAAQ,WAAW;AAAA,UACrB,OAAO;AACL,oBAAQ,eAAe;AAAA,UACzB;AAAA,QACF,GAAG,gBAAgB,WAAW;AAC5B,cAAI,kBAAkB;AACtB,mBAAS,KAAK,GAAG,KAAK,iBAAiB,EAAE,IAAI;AAC3C,oBAAQ,qBAAqB;AAAA,UAC/B;AAAA,QACF,GAAG,YAAY,WAAW;AACxB,0BAAgB;AAAA,QAClB,GAAG,UAAU,CAAC,GAAG,eAAe,SAAS,QAAQ;AAC/C,uBAAa;AAAA,QACf,GAAG,qBAAqB,WAAW;AACjC,mBAAS,MAAM,QAAQ,UAAU;AAC/B,gBAAI,UAAU,QAAQ,SAAS;AAC/B,gBAAI,WAAW,QAAQ,QAAQ;AAC7B,sBAAQ,mBAAmB,QAAQ,MAAM;AAAA,YAC3C;AAAA,UACF;AACA,mBAAS,KAAK,GAAG,KAAK,QAAQ,cAAc,QAAQ,EAAE,IAAI;AACxD,gBAAI,SAAS,QAAQ,cAAc;AACnC,mBAAO,UAAU;AAAA,UACnB;AACA,kBAAQ,gBAAgB,CAAC;AAAA,QAC3B,GAAG,oBAAoB,SAAS,QAAQ;AACtC,kBAAQ,gCAAgC,WAAW;AACjD,mBAAO,QAAQ,SAAS,OAAO,QAAQ;AACvC,oBAAQ,cAAc,KAAK,MAAM;AACjC,oBAAQ,eAAe,OAAO,QAAQ,eAAe,QAAQ,MAAM,GAAG,CAAC;AACvE,0CAA8B,OAAO,QAAQ,gBAAgB;AAC7D,mBAAO,UAAU;AAAA,UACnB,CAAC;AAAA,QACH,GAAG,iCAAiC,SAAS,OAAO;AAClD,4BAAkB,EAAE,gDAAgD,KAAK;AACzE,cAAI;AACF,kBAAM;AAAA,UACR,UAAE;AACA,8BAAkB,EAAE,gDAAgD,KAAK;AAAA,UAC3E;AAAA,QACF,GAAG,uBAAuB,SAAS,MAAM;AAAA,QACzC,GAAG,YAAY,WAAW;AACxB,mBAAS,MAAM,QAAQ,kBAAkB;AACvC,oBAAQ,iBAAiB,IAAI;AAAA,UAC/B;AAAA,QACF,GAAG,wBAAwB,SAAS,QAAQ,mBAAmB;AAC7D,iBAAO,YAAY,CAAC,OAAO;AACzB,gBAAI,IAAI,GAAG;AACX,gBAAI,MAAM,EAAE;AACZ,gBAAI,OAAO;AACT,sBAAQ,sCAAsC,OAAO,QAAQ;AAC/D,gBAAI,EAAE,mBAAmB,EAAE,mBAAmB,cAAc,GAAG;AAC7D,kBAAI,SAAS,QAAQ,SAAS,EAAE;AAChC,kBAAI,QAAQ;AACV,uBAAO,OAAO,YAAY,GAAG,EAAE,eAAe;AAAA,cAChD,OAAO;AACL,oBAAI,4CAA4C,MAAM,yBAAyB,EAAE,kBAAkB,qCAAqC;AAAA,cAC1I;AACA,sBAAQ,sCAAsC;AAC9C;AAAA,YACF;AACA,gBAAI,QAAQ,+BAA+B;AACzC,2DAA6C;AAAA,YAC/C,WAAW,QAAQ,eAAe;AAChC,0BAAY,CAAC;AAAA,YACf,WAAW,QAAQ,iBAAiB;AAClC,4BAAc,EAAE,SAAS;AAAA,YAC3B,WAAW,QAAQ,cAAc;AAC/B,yBAAW,EAAE,SAAS;AAAA,YACxB,WAAW,QAAQ,gBAAgB;AACjC,2BAAa,EAAE,SAAS;AAAA,YAC1B,WAAW,QAAQ,UAAU;AAC3B,qBAAO,SAAS;AAChB,kBAAI;AACF,kCAAkB,MAAM;AAC1B,kBAAI,OAAO,YAAY;AACrB,uBAAO,WAAW;AAClB,uBAAO,OAAO;AAAA,cAChB;AAAA,YACF,WAAW,QAAQ,SAAS;AAC1B,kBAAI,YAAY,EAAE,cAAc,OAAO,EAAE,OAAO;AAAA,YAClD,WAAW,QAAQ,YAAY;AAC7B,kBAAI,YAAY,EAAE,cAAc,OAAO,EAAE,OAAO;AAAA,YAClD,WAAW,QAAQ,SAAS;AAC1B,oBAAM,YAAY,EAAE,cAAc,OAAO,EAAE,OAAO;AAAA,YACpD,WAAW,EAAE,WAAW,gBAAgB;AACtC,qBAAO,YAAY,CAAC;AAAA,YACtB,WAAW,QAAQ,WAAW;AAC5B,kBAAI,OAAO,YAAY;AACrB,uBAAO,WAAW,EAAE,MAAM;AAAA,cAC5B;AAAA,YACF,OAAO;AACL,kBAAI,oCAAoC,GAAG;AAAA,YAC7C;AACA,oBAAQ,sCAAsC;AAAA,UAChD;AACA,iBAAO,UAAU,CAAC,OAAO;AACvB,gBAAI,UAAU;AACd,gBAAI,UAAU,MAAM,GAAG,WAAW,MAAM,GAAG,SAAS,OAAO,GAAG,OAAO;AACrE,kBAAM;AAAA,UACR;AACA,cAAI,qBAAqB;AACvB,mBAAO,GAAG,WAAW,SAAS,MAAM;AAClC,qBAAO,UAAU,EAAE,KAAK,CAAC;AAAA,YAC3B,CAAC;AACD,mBAAO,GAAG,SAAS,SAAS,IAAI;AAC9B,qBAAO,QAAQ,EAAE;AAAA,YACnB,CAAC;AACD,mBAAO,GAAG,gBAAgB,WAAW;AAAA,YACrC,CAAC;AAAA,UACH;AACA,iBAAO,YAAY,EAAE,OAAO,QAAQ,aAAa,OAAO,0BAA0B,YAAY,cAAc,YAAY,cAAc,WAAW,CAAC;AAAA,QACpJ,GAAG,sBAAsB,WAAW;AAClC,cAAI,gBAAgB,WAAW,2CAA2C;AAC1E,kBAAQ,cAAc,KAAK,IAAI,OAAO,aAAa,CAAC;AAAA,QACtD,GAAG,cAAc,WAAW;AAC1B,cAAI,QAAQ,cAAc,UAAU,GAAG;AACrC,oBAAQ,qBAAqB;AAC7B,oBAAQ,uBAAuB,QAAQ,cAAc,EAAE;AAAA,UACzD;AACA,iBAAO,QAAQ,cAAc,IAAI;AAAA,QACnC,EAAE;AACF,iBAAS,sBAAsB;AAC7B,cAAI,cAAc,cAAc;AAChC,cAAI,WAAW,kBAAkB,EAAE,cAAc,MAAM;AACvD,cAAI,YAAY,kBAAkB,EAAE,cAAc,MAAM;AACxD,cAAI,WAAW,WAAW;AAC1B,uCAA6B,UAAU,QAAQ;AAC/C,uBAAa,QAAQ;AAAA,QACvB;AACA,eAAO,yBAAyB;AAChC,iBAAS,iBAAiB,YAAY;AACpC,cAAI;AACF,mBAAO,oCAAoC,GAAG,GAAG,UAAU;AAC7D,cAAI;AACF,kBAAM,UAAU;AAAA,UAClB,SAAS,IAAP;AACA,4BAAgB,EAAE;AAAA,UACpB;AAAA,QACF;AACA,YAAI,kBAAkB,CAAC;AACvB,iBAAS,kBAAkB,SAAS;AAClC,cAAI,QAAQ,gBAAgB;AAC5B,cAAI,CAAC,OAAO;AACV,gBAAI,WAAW,gBAAgB;AAC7B,8BAAgB,SAAS,UAAU;AACrC,4BAAgB,WAAW,QAAQ,UAAU,IAAI,OAAO;AAAA,UAC1D;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,iBAAiB,KAAK,KAAK;AAClC,iBAAO,kBAAkB,GAAG,EAAE,GAAG;AAAA,QACnC;AACA,eAAO,sBAAsB;AAC7B,iBAAS,eAAe;AACtB,cAAI,QAAQ,IAAI,MAAM;AACtB,cAAI,CAAC,MAAM,OAAO;AAChB,gBAAI;AACF,oBAAM,IAAI,MAAM;AAAA,YAClB,SAAS,IAAP;AACA,sBAAQ;AAAA,YACV;AACA,gBAAI,CAAC,MAAM,OAAO;AAChB,qBAAO;AAAA,YACT;AAAA,UACF;AACA,iBAAO,MAAM,MAAM,SAAS;AAAA,QAC9B;AACA,iBAAS,gBAAgB,aAAa,eAAe,UAAU;AAC7D,kBAAQ,iBAAiB,KAAK,WAAW;AAAA,QAC3C;AACA,iBAAS,kBAAkB,KAAK,OAAO;AACrC,oBAAU,IAAI,KAAK,KAAK;AACxB,0BAAgB,OAAO;AAAA,QACzB;AACA,YAAI;AACJ,YAAI,qBAAqB;AACvB,gCAAsB,MAAM;AAC1B,gBAAI,KAAK,QAAQ,UAAU;AAC3B,mBAAO,GAAG,KAAK,MAAM,GAAG,KAAK;AAAA,UAC/B;AAAA,QACF,WAAW,wBAAwB;AACjC,gCAAsB,MAAM,YAAY,IAAI,IAAI,OAAO;AAAA,QACzD;AACE,gCAAsB,MAAM,YAAY,IAAI;AAC9C,YAAI,mCAAmC;AACvC,iBAAS,SAAS,OAAO;AACvB,4BAAkB,EAAE,kBAAkB,KAAK,KAAK;AAChD,iBAAO;AAAA,QACT;AACA,iBAAS,eAAe,QAAQ,IAAI;AAClC,cAAIC;AACJ,cAAI,WAAW,GAAG;AAChB,YAAAA,QAAO,KAAK,IAAI;AAAA,UAClB,YAAY,WAAW,KAAK,WAAW,MAAM,kCAAkC;AAC7E,YAAAA,QAAO,oBAAoB;AAAA,UAC7B,OAAO;AACL,qBAAS,EAAE;AACX,mBAAO;AAAA,UACT;AACA,4BAAkB,EAAE,MAAM,KAAKA,QAAO,MAAM;AAC5C,4BAAkB,EAAE,KAAK,KAAK,KAAKA,QAAO,MAAM,MAAM,MAAM;AAC5D,iBAAO;AAAA,QACT;AACA,iBAAS,iBAAiB,IAAI,KAAK;AACjC,iBAAO,eAAe,IAAI,GAAG;AAAA,QAC/B;AACA,iBAAS,kCAAkC,IAAI;AAC7C,mCAAyB,IAAI,CAAC,uBAAuB,GAAG,CAAC,kBAAkB;AAC3E,kBAAQ,WAAW;AAAA,QACrB;AACA,iBAAS,6BAA6B,QAAQ;AAC5C,cAAI,CAAC;AACH,0BAAc,MAAM;AAAA;AAEpB,wBAAY,EAAE,OAAO,iBAAiB,UAAU,OAAO,CAAC;AAAA,QAC5D;AACA,iBAAS,YAAY,cAAc;AACjC,cAAI,SAAS,QAAQ,aAAa;AAClC,cAAI,CAAC,QAAQ;AACX,mBAAO;AAAA,UACT;AACA,kBAAQ,eAAe,KAAK,MAAM;AAClC,cAAI,UAAU,QAAQ,SAAS,aAAa,eAAe,EAAE,QAAQ,kBAAkB,aAAa,YAAY;AAChH,iBAAO,UAAU;AACjB,cAAI,MAAM,EAAE,OAAO,OAAO,iBAAiB,aAAa,cAAc,OAAO,aAAa,KAAK,oBAAoB,aAAa,YAAY;AAC5I,iBAAO,aAAa,MAAM;AACxB,gBAAI,OAAO,YAAY,IAAI;AAC3B,mBAAO,YAAY,KAAK,aAAa,YAAY;AAAA,UACnD;AACA,cAAI,OAAO,QAAQ;AACjB,mBAAO,WAAW;AAClB,mBAAO,OAAO;AAAA,UAChB;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,qBAAqB,aAAa,MAAM,eAAe,KAAK;AACnE,cAAI,OAAO,sBAAsB,aAAa;AAC5C,gBAAI,qFAAqF;AACzF,mBAAO;AAAA,UACT;AACA,cAAI,eAAe,CAAC;AACpB,cAAI,QAAQ;AACZ,cAAI,2BAA2B,aAAa,WAAW,KAAK,QAAQ;AAClE,mBAAO,sCAAsC,WAAW,aAAa,MAAM,eAAe,GAAG;AAAA,UAC/F;AACA,cAAI;AACF,mBAAO;AACT,cAAI,eAAe,EAAE,cAAc,eAAe,aAAa,KAAK,aAAa;AACjF,cAAI,wBAAwB;AAC1B,yBAAa,MAAM;AACnB,wBAAY,cAAc,YAAY;AACtC,mBAAO;AAAA,UACT;AACA,iBAAO,YAAY,YAAY;AAAA,QACjC;AACA,iBAAS,0CAA0C;AACjD,iBAAO;AAAA,QACT;AACA,iBAAS,iCAAiC,gBAAgB,cAAc;AACtE,cAAI,kBAAkB,cAAc;AAClC,wBAAY,EAAE,OAAO,8BAA8B,CAAC;AAAA,UACtD,WAAW,wBAAwB;AACjC,wBAAY,EAAE,gBAAgB,gBAAgB,OAAO,qBAAqB,CAAC;AAAA,UAC7E,OAAO;AACL,gBAAI,UAAU,QAAQ,SAAS;AAC/B,gBAAI,SAAS,WAAW,QAAQ;AAChC,gBAAI,CAAC,QAAQ;AACX;AAAA,YACF;AACA,mBAAO,YAAY,EAAE,OAAO,qBAAqB,CAAC;AAAA,UACpD;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,SAAS;AAChB,gBAAM,EAAE;AAAA,QACV;AACA,iBAAS,qCAAqC;AAC5C,cAAI;AACF;AACF,cAAI;AACF;AACF,mBAAS,0IAA0I;AAAA,QACrJ;AACA,iBAAS,2BAA2B;AAClC,iBAAO;AAAA,QACT;AACA,iBAAS,uBAAuB,MAAM,KAAK,KAAK;AAC9C,2BAAiB,EAAE,WAAW,MAAM,KAAK,MAAM,GAAG;AAAA,QACpD;AACA,iBAAS,gCAAgC;AACvC,cAAI;AACF,mBAAO,WAAW,EAAE,KAAK,EAAE;AAC7B,iBAAO,UAAU;AAAA,QACnB;AACA,iBAAS,oCAAoCC,QAAO,MAAM;AACxD,cAAI,cAAc,UAAU,SAAS;AACrC,cAAI,YAAY;AAChB,iBAAO,cAAc,WAAW;AAC9B,gBAAI,wBAAwB;AAC5B,gBAAI,OAAO,WAAW,wBAAwB,CAAC;AAC/C,gBAAI,IAAI,QAAQ;AAChB,qBAAS,KAAK,GAAG,KAAK,aAAa,MAAM;AACvC,kBAAI,MAAM,UAAU,IAAI;AACxB,gCAAkB,EAAE,IAAI,MAAM;AAAA,YAChC;AACA,mBAAO,0CAA0CA,QAAO,uBAAuB,MAAM,IAAI;AAAA,UAC3F,CAAC;AAAA,QACH;AACA,YAAI,iDAAiD,CAAC;AACtD,iBAAS,sCAAsCA,QAAO,aAAa,MAAM;AACvE,yDAA+C,SAAS;AACxD,cAAI,IAAI,QAAQ;AAChB,mBAAS,KAAK,GAAG,KAAK,aAAa,MAAM;AACvC,2DAA+C,MAAM,kBAAkB,EAAE,IAAI;AAAA,UAC/E;AACA,cAAI,eAAeA,SAAQ;AAC3B,cAAI,QAAQ,CAAC,eAAe,qBAAqBA,UAAS,WAAW,CAACA,SAAQ;AAC9E,iBAAO,MAAM,MAAM,MAAM,8CAA8C;AAAA,QACzE;AACA,iBAAS,0BAA0BT,OAAM;AACvC,cAAI;AACF,uBAAW,KAAKA,QAAO,QAAQ,aAAa,UAAU,EAAE;AACxD,uCAA2B,WAAW,MAAM;AAC5C,mBAAO;AAAA,UACT,SAAS,IAAP;AAAA,UACF;AAAA,QACF;AACA,iBAAS,wBAAwB,eAAe;AAC9C,cAAI,UAAU,iBAAiB,EAAE;AACjC,0BAAgB,kBAAkB;AAClC,cAAI,iBAAiB,SAAS;AAC5B,mBAAO;AAAA,UACT;AACA,cAAI,cAAc,yBAAyB;AAC3C,cAAI,gBAAgB,aAAa;AAC/B,mBAAO;AAAA,UACT;AACA,mBAAS,UAAU,GAAG,WAAW,GAAG,WAAW,GAAG;AAChD,gBAAI,oBAAoB,WAAW,IAAI,MAAM;AAC7C,gCAAoB,KAAK,IAAI,mBAAmB,gBAAgB,SAAS;AACzE,gBAAI,UAAU,KAAK,IAAI,aAAa,QAAQ,KAAK,IAAI,eAAe,iBAAiB,GAAG,KAAK,CAAC;AAC9F,gBAAI,cAAc,0BAA0B,OAAO;AACnD,gBAAI,aAAa;AACf,qBAAO;AAAA,YACT;AAAA,UACF;AACA,iBAAO;AAAA,QACT;AACA,YAAI,WAAW,EAAE,gBAAgB,GAAG,yBAAyB,WAAW;AACtE,mBAAS,KAAK,SAAS,cAAc,SAAS,GAAG,MAAM,GAAG,EAAE,IAAI;AAC9D,qBAAS,eAAe,EAAE;AAAA,UAC5B;AACA,mBAAS,gBAAgB,CAAC;AAC1B,mBAAS,gBAAgB,CAAC;AAAA,QAC5B,GAAG,8BAA8B,WAAW;AAC1C,cAAI,CAAC,SAAS,gCAAgC;AAC5C,uBAAW,KAAK,SAAS,uBAAuB;AAChD,qBAAS,iCAAiC;AAAA,UAC5C;AAAA,QACF,GAAG,eAAe,CAAC,GAAG,WAAW,SAAS,gBAAgB,YAAY,UAAU;AAC9E,mBAAS,uBAAuB,MAAM,MAAM;AAC1C,gBAAI,KAAK,UAAU,KAAK;AACtB,qBAAO;AACT,qBAAS,MAAM,MAAM;AACnB,kBAAI,KAAK,OAAO,KAAK;AACnB,uBAAO;AAAA,YACX;AACA,mBAAO;AAAA,UACT;AACA,mBAAS,MAAM,SAAS,eAAe;AACrC,gBAAI,OAAO,SAAS,cAAc;AAClC,gBAAI,KAAK,kBAAkB,kBAAkB,uBAAuB,KAAK,UAAU,QAAQ,GAAG;AAC5F;AAAA,YACF;AAAA,UACF;AACA,mBAAS,cAAc,KAAK,EAAE,gBAAgB,YAAY,SAAS,CAAC;AACpE,mBAAS,cAAc,KAAK,SAAS,GAAG,GAAG;AACzC,mBAAO,EAAE,aAAa,EAAE;AAAA,UAC1B,CAAC;AAAA,QACH,GAAG,qBAAqB,SAAS,gBAAgB;AAC/C,mBAAS,KAAK,GAAG,KAAK,SAAS,cAAc,QAAQ,EAAE,IAAI;AACzD,gBAAI,SAAS,cAAc,IAAI,kBAAkB,gBAAgB;AAC/D,uBAAS,cAAc,OAAO,IAAI,CAAC;AACnC,gBAAE;AAAA,YACJ;AAAA,UACF;AAAA,QACF,GAAG,gCAAgC,WAAW;AAC5C,iBAAO,SAAS,kBAAkB,SAAS,oBAAoB;AAAA,QACjE,GAAG,kBAAkB,WAAW;AAC9B,cAAI,CAAC,SAAS,+BAA+B,GAAG;AAC9C;AAAA,UACF;AACA,mBAAS,KAAK,GAAG,KAAK,SAAS,cAAc,QAAQ,EAAE,IAAI;AACzD,gBAAI,OAAO,SAAS,cAAc;AAClC,qBAAS,cAAc,OAAO,IAAI,CAAC;AACnC,cAAE;AACF,iBAAK,eAAe,MAAM,MAAM,KAAK,QAAQ;AAAA,UAC/C;AAAA,QACF,GAAG,eAAe,CAAC,GAAG,2BAA2B,SAAS,QAAQ,iBAAiB;AACjF,mBAAS,KAAK,GAAG,KAAK,SAAS,cAAc,QAAQ,EAAE,IAAI;AACzD,gBAAI,SAAS,cAAc,IAAI,UAAU,WAAW,CAAC,mBAAmB,mBAAmB,SAAS,cAAc,IAAI,kBAAkB;AACtI,uBAAS,eAAe,IAAI;AAAA,YAC9B;AAAA,UACF;AAAA,QACF,GAAG,gBAAgB,SAAS,IAAI;AAC9B,cAAI,IAAI,SAAS,cAAc;AAC/B,YAAE,OAAO,oBAAoB,EAAE,iBAAiB,EAAE,mBAAmB,EAAE,UAAU;AACjF,mBAAS,cAAc,OAAO,IAAI,CAAC;AAAA,QACrC,GAAG,yBAAyB,SAAS,cAAc;AACjD,cAAI,iBAAiB,SAAS,gBAAgB,OAAO;AACnD,cAAE,SAAS;AACX,qBAAS,sBAAsB;AAC/B,qBAAS,iBAAiB;AAC1B,yBAAa,YAAY,KAAK;AAC9B,qBAAS,iBAAiB;AAC1B,cAAE,SAAS;AAAA,UACb;AACA,cAAI,aAAa,cAAc;AAC7B,yBAAa,oBAAoB;AACjC,yBAAa,OAAO,iBAAiB,aAAa,iBAAiB,gBAAgB,aAAa,UAAU;AAC1G,qBAAS,cAAc,KAAK,YAAY;AACxC,qBAAS,6BAA6B;AAAA,UACxC,OAAO;AACL,qBAAS,KAAK,GAAG,KAAK,SAAS,cAAc,QAAQ,EAAE,IAAI;AACzD,kBAAI,SAAS,cAAc,IAAI,UAAU,aAAa,UAAU,SAAS,cAAc,IAAI,mBAAmB,aAAa,iBAAiB;AAC1I,yBAAS,eAAe,IAAI;AAAA,cAC9B;AAAA,YACF;AAAA,UACF;AAAA,QACF,GAAG,gCAAgC,SAAS,cAAc,kBAAkB,aAAa,WAAW,UAAU;AAC5G,wBAAc,WAAW;AACvB,gBAAI,UAAU,WAAW,EAAE;AAC3B,8BAAkB,EAAE,WAAW,KAAK;AACpC,8BAAkB,EAAE,UAAU,KAAK,KAAK;AACxC,8BAAkB,EAAE,UAAU,KAAK,KAAK;AACxC,4CAAgC,cAAc,WAAW,kBAAkB,WAAW,OAAO;AAAA,UAC/F,CAAC;AAAA,QACH,GAAG,iCAAiC,SAAS,cAAc;AACzD,kBAAQ;AAAA,iBACD;AACH,qBAAO;AAAA,iBACJ;AACH,qBAAO,QAAQ;AAAA;AAEf,qBAAO;AAAA;AAAA,QAEb,GAAG,sBAAsB,SAAS,QAAQ;AACxC,cAAI,CAAC;AACH,mBAAO;AACT,cAAI,UAAU;AACZ,mBAAO;AACT,cAAI,UAAU;AACZ,mBAAO;AACT,iBAAO,UAAU,OAAO,WAAW,OAAO,WAAW;AAAA,QACvD,GAAG,mBAAmB,WAAW;AAC/B,iBAAO,SAAS,qBAAqB,SAAS;AAAA,QAChD,EAAE;AACF,iBAAS,gBAAgB,UAAU;AACjC,cAAI,SAAS,gBAAgB,QAAQ,IAAI;AACzC,cAAI,UAAU,QAAQ,MAAM;AAC5B,uBAAa,UAAU,SAAS,MAAM;AACtC,iBAAO;AAAA,QACT;AACA,iBAAS,yDAAyD,cAAc,cAAc,OAAO,QAAQ;AAC3G,wBAAc,WAAW;AACvB,gBAAI,UAAU,WAAW,EAAE;AAC3B,gBAAI,kBAAkB;AACtB,gBAAI,cAAc;AAChB,gCAAkB,gBAAgB,YAAY;AAAA,YAChD;AACA,8BAAkB,EAAE,WAAW,KAAK;AACpC,8BAAkB,EAAE,UAAU,KAAK,KAAK;AACxC,8BAAkB,EAAE,UAAU,KAAK,KAAK;AACxC,4CAAgC,cAAc,WAAW,GAAG,iBAAiB,OAAO;AAAA,UACtF,CAAC;AAAA,QACH;AACA,iBAAS,sDAAsD,cAAc,cAAc,OAAO,QAAQ;AACxG,yBAAe,eAAe,aAAa,YAAY,IAAI;AAC3D,mEAAyD,cAAc,cAAc,OAAO,MAAM;AAAA,QACpG;AACA,iBAAS,uBAAuB,SAAS;AACvC,iBAAO,UAAU,IAAI,aAAa,OAAO,IAAI;AAAA,QAC/C;AACA,YAAI,qBAAqB,CAAC,GAAG,OAAO,aAAa,cAAc,WAAW,GAAG,OAAO,WAAW,cAAc,SAAS,CAAC;AACvH,iBAAS,gBAAgB,QAAQ;AAC/B,mBAAS,uBAAuB,MAAM;AACtC,cAAI,aAAa,mBAAmB,YAAY,OAAO,aAAa,cAAc,SAAS,cAAc,MAAM,IAAI;AACnH,iBAAO;AAAA,QACT;AACA,iBAAS,sBAAsB,QAAQ;AACrC,iBAAO,gBAAgB,MAAM;AAAA,QAC/B;AACA,iBAAS,mDAAmD,QAAQ,OAAO,QAAQ;AACjF,cAAIU,UAAS,sBAAsB,MAAM;AACzC,cAAI,CAACA;AACH,mBAAO;AACT,cAAIA,QAAO,iBAAiB;AAC1B,8BAAkB,EAAEA,QAAO,mBAAmB,KAAK;AACnD,8BAAkB,EAAEA,QAAO,kBAAkB,KAAK,KAAK;AAAA,UACzD;AACA,cAAIA,QAAO,mBAAmB,CAACA,QAAO,6BAA6B;AACjE,gBAAIA,QAAO;AACT,cAAAA,UAASA,QAAO;AAClB,gBAAI,qBAAqB;AACzB,gBAAIA,QAAO,eAAeA,QAAO,YAAY,OAAO;AAClD,kBAAI,eAAeA,QAAO,YAAY,MAAM,aAAa,IAAI;AAC7D,mCAAqB,aAAa,OAAO,KAAK,aAAa,OAAO,KAAK,aAAa,OAAOA,QAAO,SAAS,aAAa,OAAOA,QAAO;AAAA,YACxI;AACA,YAAAA,QAAO,QAAQ;AACf,YAAAA,QAAO,SAAS;AAChB,gBAAI,oBAAoB;AACtB,cAAAA,QAAO,YAAY,MAAM,SAAS,GAAG,GAAG,OAAO,MAAM;AAAA,YACvD;AAAA,UACF,WAAWA,QAAO,iBAAiB;AACjC,gBAAI,eAAe,kBAAkB,EAAEA,QAAO,kBAAkB,KAAK;AACrE,kEAAsD,cAAc,QAAQ,OAAO,MAAM;AACzF,mBAAO;AAAA,UACT,OAAO;AACL,mBAAO;AAAA,UACT;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,gDAAgD,QAAQ,OAAO,QAAQ;AAC9E,cAAI;AACF,mBAAO,oCAAoC,GAAG,GAAG,QAAQ,OAAO,MAAM;AACxE,iBAAO,mDAAmD,QAAQ,OAAO,MAAM;AAAA,QACjF;AACA,iBAAS,oCAAoC,QAAQ,OAAO,QAAQ;AAClE,cAAIA,UAAS,sBAAsB,MAAM;AACzC,cAAIA,SAAQ;AACV,mBAAO,mDAAmD,QAAQ,OAAO,MAAM;AAAA,UACjF,OAAO;AACL,mBAAO,gDAAgD,QAAQ,OAAO,MAAM;AAAA,UAC9E;AAAA,QACF;AACA,iBAAS,sCAAsC;AAC7C,gBAAM;AAAA,QACR;AACA,iBAAS,sCAAsC,KAAK;AAClD,cAAI,MAAM,IAAI,aAAa,wBAAwB;AACnD,cAAI,KAAK;AACP,gBAAI,yBAAyB,SAASD,QAAO,SAAS;AACpD,kBAAI,4BAA4BA,QAAO,OAAO;AAAA,YAChD;AACA,gBAAI,yBAAyB,SAAS,MAAM,OAAOF,SAAQ,WAAW;AACpE,kBAAI,4BAA4B,MAAM,OAAOA,SAAQ,SAAS;AAAA,YAChE;AACA,gBAAI,2BAA2B,SAAS,MAAMA,SAAQ,MAAM,SAAS,WAAW;AAC9E,kBAAI,8BAA8B,MAAMA,SAAQ,MAAM,SAAS,SAAS;AAAA,YAC1E;AACA,mBAAO;AAAA,UACT;AAAA,QACF;AACA,iBAAS,uCAAuC,KAAK;AACnD,cAAI,MAAM,IAAI,aAAa,yBAAyB;AACpD,cAAI,KAAK;AACP,gBAAI,uBAAuB,WAAW;AACpC,qBAAO,IAAI,wBAAwB;AAAA,YACrC;AACA,gBAAI,uBAAuB,SAAS,KAAK;AACvC,kBAAI,wBAAwB,GAAG;AAAA,YACjC;AACA,gBAAI,qBAAqB,SAAS,KAAK;AACrC,kBAAI,sBAAsB,GAAG;AAAA,YAC/B;AACA,gBAAI,mBAAmB,SAAS,KAAK;AACnC,qBAAO,IAAI,oBAAoB,GAAG;AAAA,YACpC;AACA,mBAAO;AAAA,UACT;AAAA,QACF;AACA,iBAAS,kCAAkC,KAAK;AAC9C,cAAI,MAAM,IAAI,aAAa,oBAAoB;AAC/C,cAAI,KAAK;AACP,gBAAI,iBAAiB,SAAS,IAAI,MAAM;AACtC,kBAAI,oBAAoB,IAAI,IAAI;AAAA,YAClC;AACA,mBAAO;AAAA,UACT;AAAA,QACF;AACA,iBAAS,gCAAgC,KAAK;AAC5C,iBAAO,CAAC,EAAE,IAAI,iBAAiB,IAAI,aAAa,kBAAkB;AAAA,QACpE;AACA,YAAI,KAAK,EAAE,SAAS,GAAG,SAAS,CAAC,GAAG,UAAU,CAAC,GAAG,cAAc,CAAC,GAAG,eAAe,CAAC,GAAG,UAAU,CAAC,GAAG,SAAS,CAAC,GAAG,MAAM,CAAC,GAAG,UAAU,CAAC,GAAG,mBAAmB,CAAC,GAAG,SAAS,CAAC,GAAG,aAAa,CAAC,GAAG,iBAAiB,GAAG,aAAa,SAAS,YAAY,WAAW;AAC9P,cAAI,CAAC,GAAG,WAAW;AACjB,eAAG,YAAY;AAAA,UACjB;AAAA,QACF,GAAG,UAAU,SAAS,OAAO;AAC3B,cAAI,MAAM,GAAG;AACb,mBAAS,KAAK,MAAM,QAAQ,KAAK,KAAK,MAAM;AAC1C,kBAAM,MAAM;AAAA,UACd;AACA,iBAAO;AAAA,QACT,GAAG,WAAW,SAAS,QAAQA,SAAQ,SAAS,QAAQ;AACtD,cAAI,SAAS;AACb,mBAAS,KAAK,GAAG,KAAKA,SAAQ,EAAE,IAAI;AAClC,gBAAI,MAAM,SAAS,kBAAkB,EAAE,SAAS,KAAK,KAAK,KAAK;AAC/D,sBAAU,aAAa,kBAAkB,EAAE,UAAU,KAAK,KAAK,IAAI,MAAM,IAAI,SAAS,GAAG;AAAA,UAC3F;AACA,iBAAO;AAAA,QACT,GAAG,eAAe,SAASG,SAAQ,wBAAwB;AACzD,cAAI,CAACA,QAAO,6BAA6B;AACvC,YAAAA,QAAO,8BAA8BA,QAAO;AAC5C,YAAAA,QAAO,aAAa,SAAS,KAAK,OAAO;AACvC,kBAAI,KAAKA,QAAO,4BAA4B,KAAK,KAAK;AACtD,qBAAO,OAAO,WAAW,cAAc,wBAAwB,KAAK;AAAA,YACtE;AAAA,UACF;AACA,cAAI,MAAMA,QAAO,WAAW,SAAS,sBAAsB;AAC3D,cAAI,CAAC;AACH,mBAAO;AACT,cAAI,SAAS,GAAG,gBAAgB,KAAK,sBAAsB;AAC3D,iBAAO;AAAA,QACT,GAAG,iBAAiB,SAAS,KAAK,wBAAwB;AACxD,cAAI,SAAS,QAAQ,CAAC;AACtB,4BAAkB,EAAE,SAAS,KAAK,KAAK,cAAc;AACrD,cAAI,UAAU,EAAE,QAAQ,YAAY,wBAAwB,SAAS,uBAAuB,cAAc,OAAO,IAAI;AACrH,cAAI,IAAI;AACN,gBAAI,OAAO,cAAc;AAC3B,aAAG,SAAS,UAAU;AACtB,cAAI,OAAO,uBAAuB,8BAA8B,eAAe,uBAAuB,2BAA2B;AAC/H,eAAG,eAAe,OAAO;AAAA,UAC3B;AACA,iBAAO;AAAA,QACT,GAAG,oBAAoB,SAAS,eAAe;AAC7C,aAAG,iBAAiB,GAAG,SAAS;AAChC,iBAAO,MAAM,QAAQ,GAAG,kBAAkB,GAAG,eAAe;AAC5D,iBAAO,EAAE,iBAAiB,CAAC;AAAA,QAC7B,GAAG,YAAY,SAAS,eAAe;AACrC,iBAAO,GAAG,SAAS;AAAA,QACrB,GAAG,eAAe,SAAS,eAAe;AACxC,cAAI,GAAG,mBAAmB,GAAG,SAAS;AACpC,eAAG,iBAAiB;AACtB,cAAI,OAAO,aAAa;AACtB,qBAAS,0BAA0B,GAAG,SAAS,eAAe,MAAM,MAAM;AAC5E,cAAI,GAAG,SAAS,kBAAkB,GAAG,SAAS,eAAe,MAAM;AACjE,eAAG,SAAS,eAAe,MAAM,OAAO,cAAc;AACxD,gBAAM,GAAG,SAAS,eAAe,MAAM;AACvC,aAAG,SAAS,iBAAiB;AAAA,QAC/B,GAAG,gBAAgB,SAAS,SAAS;AACnC,cAAI,CAAC;AACH,sBAAU,GAAG;AACf,cAAI,QAAQ;AACV;AACF,kBAAQ,qBAAqB;AAC7B,cAAI,SAAS,QAAQ;AACrB,gDAAsC,MAAM;AAC5C,iDAAuC,MAAM;AAC7C,4CAAkC,MAAM;AACxC;AACE,mBAAO,wBAAwB,OAAO,aAAa,0BAA0B;AAAA,UAC/E;AACA,0CAAgC,MAAM;AACtC,cAAI,OAAO,OAAO,uBAAuB,KAAK,CAAC;AAC/C,eAAK,QAAQ,SAAS,KAAK;AACzB,gBAAI,CAAC,IAAI,SAAS,cAAc,KAAK,CAAC,IAAI,SAAS,OAAO,GAAG;AAC3D,qBAAO,aAAa,GAAG;AAAA,YACzB;AAAA,UACF,CAAC;AAAA,QACH,EAAE;AACF,YAAI,uCAAuC,CAAC,WAAW,aAAa,kBAAkB;AACtF,iBAAS,oCAAoC,QAAQ,YAAY;AAC/D,cAAI,IAAI,cAAc;AACtB,cAAI,kBAAkB,kBAAkB,EAAE,KAAK,MAAM;AACrD,cAAI,oBAAoB,EAAE,SAAS,CAAC,CAAC,kBAAkB,EAAE,KAAK,KAAK,KAAK,SAAS,CAAC,CAAC,kBAAkB,EAAE,KAAK,KAAK,KAAK,WAAW,CAAC,CAAC,kBAAkB,EAAE,KAAK,KAAK,KAAK,aAAa,CAAC,CAAC,kBAAkB,EAAE,KAAK,MAAM,KAAK,sBAAsB,CAAC,CAAC,kBAAkB,EAAE,KAAK,MAAM,KAAK,yBAAyB,CAAC,CAAC,kBAAkB,EAAE,KAAK,MAAM,KAAK,mBAAmB,qCAAqC,kBAAkB,gCAAgC,CAAC,CAAC,kBAAkB,EAAE,KAAK,MAAM,KAAK,cAAc,kBAAkB,EAAE,KAAK,MAAM,KAAK,cAAc,kBAAkB,EAAE,KAAK,MAAM,KAAK,2BAA2B,kBAAkB,EAAE,KAAK,MAAM,KAAK,qBAAqB,kBAAkB,EAAE,KAAK,MAAM,KAAK,0BAA0B,kBAAkB,EAAE,KAAK,MAAM,KAAK,8BAA8B,kBAAkB,EAAE,KAAK,MAAM,IAAI;AAC/zB,cAAIA,UAAS,sBAAsB,MAAM;AACzC,cAAI,CAACA,SAAQ;AACX,mBAAO;AAAA,UACT;AACA,cAAI,kBAAkB,qBAAqB;AACzC,mBAAO;AAAA,UACT;AACA,cAAI,gBAAgB,GAAG,cAAcA,SAAQ,iBAAiB;AAC9D,iBAAO;AAAA,QACT;AACA,iBAAS,iCAAiC,IAAI,KAAK;AACjD,iBAAO,oCAAoC,IAAI,GAAG;AAAA,QACpD;AACA,YAAI,WAAW,EAAE,UAAU,CAAC,GAAG,SAAS,CAAC,MAAM,CAAC,GAAG,CAAC,CAAC,GAAG,WAAW,SAAS,QAAQ,MAAM;AACxF,cAAI,UAAU,SAAS,QAAQ;AAC/B,cAAI,SAAS,KAAK,SAAS,IAAI;AAC7B,aAAC,WAAW,IAAI,MAAM,KAAK,kBAAkB,SAAS,CAAC,CAAC;AACxD,oBAAQ,SAAS;AAAA,UACnB,OAAO;AACL,oBAAQ,KAAK,IAAI;AAAA,UACnB;AAAA,QACF,GAAG,SAAS,QAAQ,KAAK,WAAW;AAClC,mBAAS,WAAW;AACpB,cAAI,MAAM,kBAAkB,EAAE,SAAS,UAAU,KAAK;AACtD,iBAAO;AAAA,QACT,GAAG,QAAQ,SAAS,KAAK;AACvB,cAAI,MAAM,aAAa,GAAG;AAC1B,iBAAO;AAAA,QACT,GAAG,OAAO,SAAS,KAAK,MAAM;AAC5B,iBAAO;AAAA,QACT,EAAE;AACF,iBAAS,UAAU,IAAI;AACrB,cAAI;AACF,mBAAO,oCAAoC,GAAG,GAAG,EAAE;AACrD,iBAAO;AAAA,QACT;AACA,iBAAS,SAAS,IAAI,YAAY,aAAa,QAAQ,WAAW;AAChE,cAAI;AACF,mBAAO,oCAAoC,GAAG,GAAG,IAAI,YAAY,aAAa,QAAQ,SAAS;AAAA,QACnG;AACA,iBAAS,UAAU,IAAI,KAAK,QAAQ,MAAM;AACxC,cAAI;AACF,mBAAO,oCAAoC,GAAG,GAAG,IAAI,KAAK,QAAQ,IAAI;AACxE,cAAI,MAAM;AACV,mBAAS,KAAK,GAAG,KAAK,QAAQ,MAAM;AAClC,gBAAI,MAAM,kBAAkB,EAAE,OAAO;AACrC,gBAAI,MAAM,kBAAkB,EAAE,MAAM,KAAK;AACzC,mBAAO;AACP,qBAAS,IAAI,GAAG,IAAI,KAAK,KAAK;AAC5B,uBAAS,UAAU,IAAI,iBAAiB,EAAE,MAAM,EAAE;AAAA,YACpD;AACA,mBAAO;AAAA,UACT;AACA,4BAAkB,EAAE,QAAQ,KAAK;AACjC,iBAAO;AAAA,QACT;AACA,iBAAS,aAAa,KAAK;AACzB,sBAAY,GAAG;AAAA,QACjB;AACA,gBAAQ,KAAK;AACb,YAAI;AACJ,YAAI,uBAAuB,CAAC,MAAM,kBAAkB,iDAAiD,WAAW,UAAU,SAAS;AACnI,YAAI,aAAa;AACjB,YAAI,gBAAgB,EAAE,mBAAmB,kBAAkB,oCAAoC,mCAAmC,+BAA+B,8BAA8B,uBAAuB,sBAAsB,0CAA0C,yCAAyC,mCAAmC,kCAAkC,SAAS,QAAQ,qCAAqC,oCAAoC,2BAA2B,0BAA0B,sBAAsB,qBAAqB,yBAAyB,wBAAwB,gCAAgC,+BAA+B,wCAAwC,uCAAuC,0BAA0B,yBAAyB,sCAAsC,qCAAqC,sCAAsC,qCAAqC,mCAAmC,kCAAkC,QAAQ,OAAO,YAAY,WAAW,WAAW,UAAU,YAAY,WAAW,UAAU,cAAc,OAAO,eAAe,eAAe,aAAa;AACvqC,YAAI,MAAM,WAAW;AACrB,YAAI,qBAAqB,OAAO,wBAAwB,WAAW;AACjE,kBAAQ,qBAAqB,OAAO,wBAAwB,OAAO,OAAO,sBAAsB,MAAM,MAAM,SAAS;AAAA,QACvH;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,2BAA2B,OAAO,8BAA8B,WAAW;AAC7E,kBAAQ,2BAA2B,OAAO,8BAA8B,OAAO,OAAO,4BAA4B,MAAM,MAAM,SAAS;AAAA,QACzI;AACA,YAAI,qBAAqB,OAAO,wBAAwB,WAAW;AACjE,kBAAQ,qBAAqB,OAAO,wBAAwB,OAAO,OAAO,sBAAsB,MAAM,MAAM,SAAS;AAAA,QACvH;AACA,YAAI,mBAAmB,OAAO,sBAAsB,WAAW;AAC7D,kBAAQ,mBAAmB,OAAO,sBAAsB,OAAO,OAAO,oBAAoB,MAAM,MAAM,SAAS;AAAA,QACjH;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,gBAAgB,MAAM,MAAM,SAAS;AAAA,QACrG;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,gBAAgB,MAAM,MAAM,SAAS;AAAA,QACrG;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,iBAAiB,OAAO,oBAAoB,WAAW;AACzD,kBAAQ,iBAAiB,OAAO,oBAAoB,OAAO,OAAO,kBAAkB,MAAM,MAAM,SAAS;AAAA,QAC3G;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,yBAAyB,OAAO,4BAA4B,WAAW;AACzE,kBAAQ,yBAAyB,OAAO,4BAA4B,OAAO,OAAO,0BAA0B,MAAM,MAAM,SAAS;AAAA,QACnI;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,iBAAiB,OAAO,oBAAoB,WAAW;AACzD,kBAAQ,iBAAiB,OAAO,oBAAoB,OAAO,OAAO,kBAAkB,MAAM,MAAM,SAAS;AAAA,QAC3G;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,kBAAkB,OAAO,qBAAqB,WAAW;AAC3D,kBAAQ,kBAAkB,OAAO,qBAAqB,OAAO,OAAO,mBAAmB,MAAM,MAAM,SAAS;AAAA,QAC9G;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,gBAAgB,MAAM,MAAM,SAAS;AAAA,QACrG;AACA,YAAI,wBAAwB,OAAO,2BAA2B,WAAW;AACvE,kBAAQ,wBAAwB,OAAO,2BAA2B,OAAO,OAAO,yBAAyB,MAAM,MAAM,SAAS;AAAA,QAChI;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,cAAc,OAAO,iBAAiB,WAAW;AACnD,kBAAQ,cAAc,OAAO,iBAAiB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAClG;AACA,YAAI,cAAc,OAAO,iBAAiB,WAAW;AACnD,kBAAQ,cAAc,OAAO,iBAAiB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAClG;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,cAAc,OAAO,iBAAiB,WAAW;AACnD,kBAAQ,cAAc,OAAO,iBAAiB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAClG;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,kBAAkB,OAAO,qBAAqB,WAAW;AAC3D,kBAAQ,kBAAkB,OAAO,qBAAqB,OAAO,OAAO,mBAAmB,MAAM,MAAM,SAAS;AAAA,QAC9G;AACA,YAAI,yBAAyB,OAAO,4BAA4B,WAAW;AACzE,kBAAQ,yBAAyB,OAAO,4BAA4B,OAAO,OAAO,0BAA0B,MAAM,MAAM,SAAS;AAAA,QACnI;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,oBAAoB,OAAO,uBAAuB,WAAW;AAC/D,kBAAQ,oBAAoB,OAAO,uBAAuB,OAAO,OAAO,qBAAqB,MAAM,MAAM,SAAS;AAAA,QACpH;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,iBAAiB,OAAO,oBAAoB,WAAW;AACzD,kBAAQ,iBAAiB,OAAO,oBAAoB,OAAO,OAAO,kBAAkB,MAAM,MAAM,SAAS;AAAA,QAC3G;AACA,YAAI,0BAA0B,OAAO,6BAA6B,WAAW;AAC3E,kBAAQ,0BAA0B,OAAO,6BAA6B,OAAO,OAAO,2BAA2B,MAAM,MAAM,SAAS;AAAA,QACtI;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,qBAAqB,OAAO,wBAAwB,WAAW;AACjE,kBAAQ,qBAAqB,OAAO,wBAAwB,OAAO,OAAO,sBAAsB,MAAM,MAAM,SAAS;AAAA,QACvH;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,oBAAoB,OAAO,uBAAuB,WAAW;AAC/D,kBAAQ,oBAAoB,OAAO,uBAAuB,OAAO,OAAO,qBAAqB,MAAM,MAAM,SAAS;AAAA,QACpH;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,+CAA+C,OAAO,kDAAkD,WAAW;AACrH,kBAAQ,+CAA+C,OAAO,kDAAkD,OAAO,OAAO,gDAAgD,MAAM,MAAM,SAAS;AAAA,QACrM;AACA,YAAI,8BAA8B,OAAO,iCAAiC,WAAW;AACnF,kBAAQ,8BAA8B,OAAO,iCAAiC,OAAO,OAAO,+BAA+B,MAAM,MAAM,SAAS;AAAA,QAClJ;AACA,YAAI,2BAA2B,OAAO,8BAA8B,WAAW;AAC7E,kBAAQ,2BAA2B,OAAO,8BAA8B,OAAO,OAAO,4BAA4B,MAAM,MAAM,SAAS;AAAA,QACzI;AACA,YAAI,kDAAkD,OAAO,qDAAqD,WAAW;AAC3H,kBAAQ,kDAAkD,OAAO,qDAAqD,OAAO,OAAO,mDAAmD,MAAM,MAAM,SAAS;AAAA,QAC9M;AACA,YAAI,qCAAqC,OAAO,wCAAwC,WAAW;AACjG,kBAAQ,qCAAqC,OAAO,wCAAwC,OAAO,OAAO,sCAAsC,MAAM,MAAM,SAAS;AAAA,QACvK;AACA,YAAI,wCAAwC,OAAO,2CAA2C,WAAW;AACvG,kBAAQ,wCAAwC,OAAO,2CAA2C,OAAO,OAAO,yCAAyC,MAAM,MAAM,SAAS;AAAA,QAChL;AACA,YAAI,wCAAwC,OAAO,2CAA2C,WAAW;AACvG,kBAAQ,wCAAwC,OAAO,2CAA2C,OAAO,OAAO,yCAAyC,MAAM,MAAM,SAAS;AAAA,QAChL;AACA,YAAI,4CAA4C,OAAO,+CAA+C,WAAW;AAC/G,kBAAQ,4CAA4C,OAAO,+CAA+C,OAAO,OAAO,6CAA6C,MAAM,MAAM,SAAS;AAAA,QAC5L;AACA,YAAI,kCAAkC,OAAO,qCAAqC,WAAW;AAC3F,kBAAQ,kCAAkC,OAAO,qCAAqC,OAAO,OAAO,mCAAmC,MAAM,MAAM,SAAS;AAAA,QAC9J;AACA,YAAI,gCAAgC,OAAO,mCAAmC,WAAW;AACvF,kBAAQ,gCAAgC,OAAO,mCAAmC,OAAO,OAAO,iCAAiC,MAAM,MAAM,SAAS;AAAA,QACxJ;AACA,YAAI,2BAA2B,OAAO,8BAA8B,WAAW;AAC7E,kBAAQ,2BAA2B,OAAO,8BAA8B,OAAO,OAAO,4BAA4B,MAAM,MAAM,SAAS;AAAA,QACzI;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,+BAA+B,OAAO,kCAAkC,WAAW;AACrF,kBAAQ,+BAA+B,OAAO,kCAAkC,OAAO,OAAO,gCAAgC,MAAM,MAAM,SAAS;AAAA,QACrJ;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC7F;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACtG;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAChG;AACA,YAAI,mBAAmB,OAAO,sBAAsB,WAAW;AAC7D,kBAAQ,mBAAmB,OAAO,sBAAsB,OAAO,OAAO,qBAAqB,MAAM,MAAM,SAAS;AAAA,QAClH;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACtG;AACA,YAAI,+CAA+C,OAAO,kDAAkD;AAC5G,eAAO,WAAW;AAClB,eAAO,sBAAsB;AAC7B,eAAO,aAAa;AACpB,eAAO,aAAa;AACpB,eAAO,gBAAgB;AACvB,eAAO,gBAAgB;AACvB,YAAI;AACJ,iBAAS,WAAW,QAAQ;AAC1B,eAAK,OAAO;AACZ,eAAK,UAAU,kCAAkC,SAAS;AAC1D,eAAK,SAAS;AAAA,QAChB;AACA,gCAAwB,SAAS,YAAY;AAC3C,cAAI,CAAC;AACH,gBAAI;AACN,cAAI,CAAC;AACH,oCAAwB;AAAA,QAC5B;AACA,iBAAS,IAAI,MAAM;AACjB,iBAAO,QAAQ;AACf,cAAI,kBAAkB,GAAG;AACvB;AAAA,UACF;AACA,cAAI,wBAAwB;AAC1B,gCAAoB,MAAM;AAC1B,wBAAY;AACZ,wBAAY,EAAE,OAAO,SAAS,CAAC;AAC/B;AAAA,UACF;AACA,iBAAO;AACP,cAAI,kBAAkB,GAAG;AACvB;AAAA,UACF;AACA,mBAAS,QAAQ;AACf,gBAAI;AACF;AACF,wBAAY;AACZ,mBAAO,eAAe;AACtB,gBAAI;AACF;AACF,wBAAY;AACZ,gCAAoB,MAAM;AAC1B,gBAAI,OAAO;AACT,qBAAO,wBAAwB;AACjC,oBAAQ;AAAA,UACV;AACA,cAAI,OAAO,cAAc;AACvB,mBAAO,aAAa,YAAY;AAChC,uBAAW,WAAW;AACpB,yBAAW,WAAW;AACpB,uBAAO,aAAa,EAAE;AAAA,cACxB,GAAG,CAAC;AACJ,oBAAM;AAAA,YACR,GAAG,CAAC;AAAA,UACN,OAAO;AACL,kBAAM;AAAA,UACR;AAAA,QACF;AACA,eAAO,SAAS;AAChB,iBAAS,KAAK,QAAQ,UAAU;AAC9B,uBAAa;AACb,cAAI,CAAC,UAAU;AACb,gBAAI,wBAAwB;AAC1B,+BAAiB,MAAM;AACvB,oBAAM;AAAA,YACR,OAAO;AAAA,YACP;AAAA,UACF;AACA,cAAI,iBAAiB,GAAG;AAAA,UACxB,OAAO;AACL,wBAAY;AAAA,UACd;AACA,mBAAS,MAAM;AAAA,QACjB;AACA,iBAAS,SAAS,MAAM;AACtB,uBAAa;AACb,cAAI,CAAC,iBAAiB,GAAG;AACvB,oBAAQ,oBAAoB;AAC5B,gBAAI,OAAO;AACT,qBAAO,UAAU,IAAI;AACvB,oBAAQ;AAAA,UACV;AACA,gBAAM,MAAM,IAAI,WAAW,IAAI,CAAC;AAAA,QAClC;AACA,YAAI,OAAO,YAAY;AACrB,cAAI,OAAO,OAAO,cAAc;AAC9B,mBAAO,aAAa,CAAC,OAAO,UAAU;AACxC,iBAAO,OAAO,WAAW,SAAS,GAAG;AACnC,mBAAO,WAAW,IAAI,EAAE;AAAA,UAC1B;AAAA,QACF;AACA,YAAI;AACJ,YAAI;AACJ,YAAI,iBAAiB;AACnB,2BAAiB,EAAE,mBAAmB,QAAQ,UAAU,mBAAmB,EAAE,OAAO,SAAS,UAAU;AACrG,mBAAO,CAAC,gBAAgB,kBAAkB,QAAQ,QAAQ,IAAI;AAAA,UAChE,CAAC,GAAG,oBAAoB,QAAQ,UAAU,oBAAoB,EAAE,OAAO,SAAS,UAAU;AACxF,mBAAO,CAAC,gBAAgB,mBAAmB,QAAQ,QAAQ,IAAI;AAAA,UACjE,CAAC,EAAE;AAAA,QACL;AACA,YAAI;AACJ,YAAI,OAAO,sBAAsB,aAAa;AAC5C,yBAAe;AAAA,QACjB,WAAW,OAAO,mCAAmC,aAAa;AAChE,yBAAe;AAAA,QACjB,OAAO;AACL,gBAAM,IAAI,MAAM,uCAAuC;AAAA,QACzD;AACA,YAAI,gBAAgB;AAClB,cAAI,aAAa,aAAa;AAC9B,uBAAa,cAAc,WAAW;AACpC,uBAAW;AACX,2BAAe,kBAAkB,QAAQ,SAAS,UAAU;AAC1D,sBAAQ,eAAe,qBAAqB,QAAQ;AAAA,YACtD,CAAC;AACD,2BAAe,mBAAmB,QAAQ,SAAS,UAAU;AAC3D,sBAAQ,eAAe,sBAAsB,QAAQ;AAAA,YACvD,CAAC;AAAA,UACH;AAAA,QACF;AACA,eAAO,+BAA+B;AAAA,MACxC;AAAA,IACF,GAAG;AACH,QAAI,OAAO,YAAY,YAAY,OAAO,WAAW;AACnD,aAAO,UAAU;AAAA,aACV,OAAO,WAAW,cAAc,OAAO;AAC9C,aAAO,CAAC,GAAG,WAAW;AACpB,eAAO;AAAA,MACT,CAAC;AAAA,aACM,OAAO,YAAY;AAC1B,cAAQ,mCAAmC;AAAA,EAC/C;AACF,CAAC;AAGD,IAAI,iDAAiD,WAAW;AAAA,EAC9D,mLAAmL,SAAS,QAAQ;AAClM,WAAO,QAAQ,qBAAqB;AAAA;AAAA,EAEtC;AACF,CAAC;AAGD,IAAI,4BAA4B,WAAW;AAAA,EACzC,8JAA8J,SAAS,QAAQ;AAC7K,QAAI,sBAAsB,MAAM;AAC9B,UAAI,aAAa,OAAO,aAAa,eAAe,SAAS,gBAAgB,SAAS,cAAc,MAAM;AAC1G,UAAI,OAAO,eAAe;AACxB,qBAAa,cAAc;AAC7B,aAAO,SAAS,oBAAoB;AAClC,6BAAqB,sBAAsB,CAAC;AAC5C,YAAI,SAAS,OAAO,uBAAuB,cAAc,qBAAqB,CAAC;AAC/E,YAAI,qBAAqB;AACzB,eAAO,WAAW,IAAI,QAAQ,SAAS,SAAS,QAAQ;AACtD,gCAAsB;AACtB,+BAAqB;AAAA,QACvB,CAAC;AACD,YAAI;AACJ,YAAI,OAAO,YAAY,eAAe,QAAQ,WAAW;AACvD,4BAAkB,EAAE,mBAAmB,QAAQ,UAAU,mBAAmB,GAAG,oBAAoB,QAAQ,UAAU,oBAAoB,EAAE;AAAA,QAC7I;AACA,YAAI,kBAAkB,OAAO,OAAO,CAAC,GAAG,MAAM;AAC9C,YAAI,aAAa,CAAC;AAClB,YAAI,cAAc;AAClB,YAAI,QAAQ,CAAC,QAAQ,YAAY;AAC/B,gBAAM;AAAA,QACR;AACA,YAAI,qBAAqB,OAAO,WAAW;AAC3C,YAAI,wBAAwB,OAAO,kBAAkB;AACrD,YAAI,sBAAsB,OAAO,YAAY,YAAY,OAAO,QAAQ,aAAa,YAAY,OAAO,QAAQ,SAAS,SAAS;AAClI,YAAI,kBAAkB;AACtB,iBAAS,WAAW,MAAM;AACxB,cAAI,OAAO,eAAe;AACxB,mBAAO,OAAO,cAAc,MAAM,eAAe;AAAA,UACnD;AACA,iBAAO,kBAAkB;AAAA,QAC3B;AACA,YAAI,OAAO,WAAW,YAAY;AAClC,iBAAS,mBAAmB,IAAI;AAC9B,cAAI,cAAc;AAChB;AACF,cAAI,QAAQ;AACZ,cAAI,+BAA+B,KAAK;AAAA,QAC1C;AACA,YAAI;AACJ,YAAI;AACJ,YAAI;AACJ,YAAI,qBAAqB;AACvB,cAAI,uBAAuB;AACzB,8BAAkB,aAAa,EAAE,QAAQ,eAAe,IAAI;AAAA,UAC9D,OAAO;AACL,8BAAkB,YAAY;AAAA,UAChC;AACA,0BAAgB,MAAM;AACpB,gBAAI,CAAC,UAAU;AACb,mBAAK,WAAW;AAChB,yBAAW,aAAa;AAAA,YAC1B;AAAA,UACF;AACA,kBAAQ,SAAS,WAAW,UAAU,QAAQ;AAC5C,0BAAc;AACd,uBAAW,SAAS,aAAa,QAAQ;AACzC,mBAAO,GAAG,aAAa,UAAU,SAAS,SAAS,MAAM;AAAA,UAC3D;AACA,uBAAa,CAAC,aAAa;AACzB,gBAAI,MAAM,MAAM,UAAU,IAAI;AAC9B,gBAAI,CAAC,IAAI,QAAQ;AACf,oBAAM,IAAI,WAAW,GAAG;AAAA,YAC1B;AACA,mBAAO;AAAA,UACT;AACA,sBAAY,CAAC,UAAU,QAAQ,YAAY;AACzC,0BAAc;AACd,uBAAW,SAAS,aAAa,QAAQ;AACzC,eAAG,SAAS,UAAU,SAAS,MAAM,MAAM;AACzC,kBAAI;AACF,wBAAQ,IAAI;AAAA;AAEZ,uBAAO,KAAK,MAAM;AAAA,YACtB,CAAC;AAAA,UACH;AACA,cAAI,QAAQ,QAAQ,SAAS,GAAG;AAC9B,0BAAc,QAAQ,QAAQ,GAAG,QAAQ,OAAO,GAAG;AAAA,UACrD;AACA,uBAAa,QAAQ,QAAQ,MAAM,CAAC;AACpC,kBAAQ,MAAM,qBAAqB,SAAS,IAAI;AAC9C,gBAAI,EAAE,cAAc,aAAa;AAC/B,oBAAM;AAAA,YACR;AAAA,UACF,CAAC;AACD,kBAAQ,MAAM,sBAAsB,SAAS,QAAQ;AACnD,kBAAM;AAAA,UACR,CAAC;AACD,kBAAQ,CAAC,QAAQ,YAAY;AAC3B,gBAAI,iBAAiB,GAAG;AACtB,sBAAQ,cAAc;AACtB,oBAAM;AAAA,YACR;AACA,+BAAmB,OAAO;AAC1B,oBAAQ,QAAQ,MAAM;AAAA,UACxB;AACA,iBAAO,aAAa,WAAW;AAC7B,mBAAO;AAAA,UACT;AAAA,QACF,WAAW,sBAAsB,uBAAuB;AACtD,cAAI,uBAAuB;AACzB,8BAAkB,KAAK,SAAS;AAAA,UAClC,WAAW,OAAO,aAAa,eAAe,SAAS,eAAe;AACpE,8BAAkB,SAAS,cAAc;AAAA,UAC3C;AACA,cAAI,YAAY;AACd,8BAAkB;AAAA,UACpB;AACA,cAAI,gBAAgB,QAAQ,OAAO,MAAM,GAAG;AAC1C,8BAAkB,gBAAgB,OAAO,GAAG,gBAAgB,QAAQ,UAAU,EAAE,EAAE,YAAY,GAAG,IAAI,CAAC;AAAA,UACxG,OAAO;AACL,8BAAkB;AAAA,UACpB;AACA;AACE,oBAAQ,CAAC,QAAQ;AACf,kBAAI,MAAM,IAAI,eAAe;AAC7B,kBAAI,KAAK,OAAO,KAAK,KAAK;AAC1B,kBAAI,KAAK,IAAI;AACb,qBAAO,IAAI;AAAA,YACb;AACA,gBAAI,uBAAuB;AACzB,2BAAa,CAAC,QAAQ;AACpB,oBAAI,MAAM,IAAI,eAAe;AAC7B,oBAAI,KAAK,OAAO,KAAK,KAAK;AAC1B,oBAAI,eAAe;AACnB,oBAAI,KAAK,IAAI;AACb,uBAAO,IAAI,WAAW,IAAI,QAAQ;AAAA,cACpC;AAAA,YACF;AACA,wBAAY,CAAC,KAAK,QAAQ,YAAY;AACpC,kBAAI,MAAM,IAAI,eAAe;AAC7B,kBAAI,KAAK,OAAO,KAAK,IAAI;AACzB,kBAAI,eAAe;AACnB,kBAAI,SAAS,MAAM;AACjB,oBAAI,IAAI,UAAU,OAAO,IAAI,UAAU,KAAK,IAAI,UAAU;AACxD,yBAAO,IAAI,QAAQ;AACnB;AAAA,gBACF;AACA,wBAAQ;AAAA,cACV;AACA,kBAAI,UAAU;AACd,kBAAI,KAAK,IAAI;AAAA,YACf;AAAA,UACF;AACA,2BAAiB,CAAC,UAAU,SAAS,QAAQ;AAAA,QAC/C,OAAO;AAAA,QACP;AACA,YAAI,MAAM,OAAO,YAAY,QAAQ,IAAI,KAAK,OAAO;AACrD,YAAI,MAAM,OAAO,eAAe,QAAQ,KAAK,KAAK,OAAO;AACzD,eAAO,OAAO,QAAQ,eAAe;AACrC,0BAAkB;AAClB,YAAI,OAAO;AACT,uBAAa,OAAO;AACtB,YAAI,OAAO;AACT,wBAAc,OAAO;AACvB,YAAI,OAAO;AACT,kBAAQ,OAAO;AACjB,YAAI,eAAe;AACnB,iBAAS,SAAS,MAAM;AACtB,cAAI,CAAC,SAAS;AACZ,qBAAS,QAAQ,CAAC;AACpB,cAAI,CAAC,SAAS,MAAM,OAAO;AACzB,qBAAS,MAAM,QAAQ;AACvB,gBAAI,IAAI;AAAA,UACV;AAAA,QACF;AACA,iBAAS,wBAAwB,OAAO,KAAK;AAC3C,cAAI,OAAO,YAAY,aAAa,YAAY;AAC9C,gBAAI,YAAY,EAAE,KAAK,OAAO,KAAK,OAAO,KAAK,OAAO,KAAK,MAAM;AACjE,gBAAI,OAAO,EAAE,YAAY,CAAC,GAAG,SAAS,IAAI,MAAM,MAAM,CAAC,IAAI,CAAC,UAAU,IAAI,GAAG,EAAE;AAC/E,qBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,mBAAK,WAAW,KAAK,UAAU,IAAI,IAAI;AAAA,YACzC;AACA,mBAAO,IAAI,YAAY,SAAS,MAAM,KAAK;AAAA,UAC7C;AACA,cAAI,cAAc,CAAC,GAAG,GAAG,GAAG,EAAE;AAC9B,cAAI,SAAS,IAAI,MAAM,GAAG,CAAC;AAC3B,cAAI,WAAW,IAAI,MAAM,CAAC;AAC1B,cAAI,YAAY,EAAE,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,IAAI;AACzD,sBAAY,KAAK,SAAS,MAAM;AAChC,mBAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,EAAE,IAAI;AAC3C,wBAAY,KAAK,UAAU,SAAS,IAAI;AAAA,UAC1C;AACA,cAAI,UAAU,KAAK;AACjB,wBAAY,KAAK,CAAC;AAAA,UACpB,OAAO;AACL,0BAAc,YAAY,OAAO,CAAC,GAAG,UAAU,OAAO,CAAC;AAAA,UACzD;AACA,sBAAY,KAAK,YAAY,SAAS;AACtC,cAAI,QAAQ,IAAI,WAAW,CAAC,GAAG,IAAI,KAAK,KAAK,GAAG,GAAG,GAAG,CAAC,EAAE,OAAO,aAAa,CAAC,GAAG,GAAG,GAAG,GAAG,KAAK,GAAG,KAAK,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,KAAK,GAAG,CAAC,CAAC,CAAC;AACpI,cAAI,UAAU,IAAI,YAAY,OAAO,KAAK;AAC1C,cAAI,WAAW,IAAI,YAAY,SAAS,SAAS,EAAE,KAAK,EAAE,KAAK,MAAM,EAAE,CAAC;AACxE,cAAI,cAAc,SAAS,QAAQ;AACnC,iBAAO;AAAA,QACT;AACA,YAAI,mBAAmB,CAAC;AACxB,YAAI;AACJ,iBAAS,oBAAoB;AAC3B,cAAI,iBAAiB,QAAQ;AAC3B,mBAAO,iBAAiB,IAAI;AAAA,UAC9B;AACA,cAAI;AACF,sBAAU,KAAK,CAAC;AAAA,UAClB,SAAS,MAAP;AACA,gBAAI,EAAE,gBAAgB,aAAa;AACjC,oBAAM;AAAA,YACR;AACA,kBAAM;AAAA,UACR;AACA,iBAAO,UAAU,SAAS;AAAA,QAC5B;AACA,iBAAS,eAAe,QAAQH,SAAQ;AACtC,mBAAS,KAAK,QAAQ,KAAK,SAASA,SAAQ,MAAM;AAChD,gBAAI,OAAO,kBAAkB,EAAE;AAC/B,gBAAI,MAAM;AACR,kCAAoB,IAAI,MAAM,EAAE;AAAA,YAClC;AAAA,UACF;AAAA,QACF;AACA,YAAI,WAAW;AACf,YAAI,cAAc,CAAC,UAAU;AAC3B,qBAAW;AAAA,QACb;AACA,YAAI;AACJ,YAAI,OAAO;AACT,uBAAa,OAAO;AACtB,YAAI,gBAAgB,OAAO,oBAAoB;AAC/C,YAAI,OAAO,gBAAgB,UAAU;AACnC,gBAAM,iCAAiC;AAAA,QACzC;AACA,YAAI;AACJ,YAAI,QAAQ;AACZ,YAAI;AACJ,iBAAS,QAAQ,WAAW,MAAM;AAChC,cAAI,CAAC,WAAW;AACd,kBAAM,IAAI;AAAA,UACZ;AAAA,QACF;AACA,iBAAS,SAAS,OAAO;AACvB,cAAI,QAAQ,OAAO,MAAM;AACzB,iBAAO;AAAA,QACT;AACA,iBAAS,MAAM,OAAO,YAAY,UAAU,MAAM,MAAM;AACtD,cAAI,MAAM,EAAE,UAAU,SAAS,KAAK;AAClC,gBAAI,OAAO;AACX,gBAAI,QAAQ,QAAQ,QAAQ,UAAU,QAAQ,GAAG;AAC/C,kBAAI,OAAO,IAAI,UAAU,KAAK;AAC9B,qBAAO,WAAW,GAAG;AACrB,2BAAa,KAAK,MAAM,GAAG;AAAA,YAC7B;AACA,mBAAO;AAAA,UACT,GAAG,SAAS,SAAS,KAAK;AACxB,gBAAI,OAAO,WAAW,IAAI,MAAM;AAChC,+BAAmB,KAAK,IAAI;AAC5B,mBAAO;AAAA,UACT,EAAE;AACF,mBAAS,mBAAmB,MAAM;AAChC,gBAAI,eAAe;AACjB,qBAAO,aAAa,IAAI;AAC1B,gBAAI,eAAe;AACjB,qBAAO,QAAQ,IAAI;AACrB,mBAAO;AAAA,UACT;AACA,cAAI,QAAQ,SAAS,KAAK;AAC1B,cAAI,QAAQ,CAAC;AACb,cAAI,SAAS;AACb,cAAI,MAAM;AACR,qBAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,kBAAI,YAAY,IAAI,SAAS;AAC7B,kBAAI,WAAW;AACb,oBAAI,WAAW;AACb,2BAAS,UAAU;AACrB,sBAAM,MAAM,UAAU,KAAK,GAAG;AAAA,cAChC,OAAO;AACL,sBAAM,MAAM,KAAK;AAAA,cACnB;AAAA,YACF;AAAA,UACF;AACA,cAAI,MAAM,MAAM,MAAM,MAAM,KAAK;AACjC,mBAAS,OAAO,MAAM;AACpB,gBAAI,WAAW;AACb,2BAAa,MAAM;AACrB,mBAAO,mBAAmB,IAAI;AAAA,UAChC;AACA,gBAAM,OAAO,GAAG;AAChB,iBAAO;AAAA,QACT;AACA,iBAAS,MAAM,OAAO,YAAY,UAAU,MAAM;AAChD,qBAAW,YAAY,CAAC;AACxB,cAAI,cAAc,SAAS,MAAM,SAAS,MAAM;AAC9C,mBAAO,SAAS;AAAA,UAClB,CAAC;AACD,cAAI,aAAa,eAAe;AAChC,cAAI,cAAc,eAAe,CAAC,MAAM;AACtC,mBAAO,SAAS,KAAK;AAAA,UACvB;AACA,iBAAO,WAAW;AAChB,mBAAO,MAAM,OAAO,YAAY,UAAU,WAAW,IAAI;AAAA,UAC3D;AAAA,QACF;AACA,YAAI,cAAc;AAClB,YAAI,cAAc,OAAO,gBAAgB,cAAc,IAAI,YAAY,MAAM,IAAI;AACjF,iBAAS,kBAAkB,MAAM,KAAK,gBAAgB;AACpD,cAAI,SAAS,MAAM;AACnB,cAAI,SAAS;AACb,iBAAO,KAAK,WAAW,EAAE,UAAU;AACjC,cAAE;AACJ,cAAI,SAAS,MAAM,MAAM,KAAK,YAAY,aAAa;AACrD,mBAAO,YAAY,OAAO,KAAK,SAAS,KAAK,MAAM,CAAC;AAAA,UACtD,OAAO;AACL,gBAAI,MAAM;AACV,mBAAO,MAAM,QAAQ;AACnB,kBAAI,KAAK,KAAK;AACd,kBAAI,EAAE,KAAK,MAAM;AACf,uBAAO,OAAO,aAAa,EAAE;AAC7B;AAAA,cACF;AACA,kBAAI,KAAK,KAAK,SAAS;AACvB,mBAAK,KAAK,QAAQ,KAAK;AACrB,uBAAO,OAAO,cAAc,KAAK,OAAO,IAAI,EAAE;AAC9C;AAAA,cACF;AACA,kBAAI,KAAK,KAAK,SAAS;AACvB,mBAAK,KAAK,QAAQ,KAAK;AACrB,sBAAM,KAAK,OAAO,KAAK,MAAM,IAAI;AAAA,cACnC,OAAO;AACL,sBAAM,KAAK,MAAM,KAAK,MAAM,KAAK,MAAM,IAAI,KAAK,SAAS;AAAA,cAC3D;AACA,kBAAI,KAAK,OAAO;AACd,uBAAO,OAAO,aAAa,EAAE;AAAA,cAC/B,OAAO;AACL,oBAAI,KAAK,KAAK;AACd,uBAAO,OAAO,aAAa,QAAQ,MAAM,IAAI,QAAQ,KAAK,IAAI;AAAA,cAChE;AAAA,YACF;AAAA,UACF;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,aAAa,KAAK,gBAAgB;AACzC,iBAAO,MAAM,kBAAkB,QAAQ,KAAK,cAAc,IAAI;AAAA,QAChE;AACA,iBAAS,kBAAkB,KAAK,MAAM,QAAQ,iBAAiB;AAC7D,cAAI,EAAE,kBAAkB;AACtB,mBAAO;AACT,cAAI,WAAW;AACf,cAAI,SAAS,SAAS,kBAAkB;AACxC,mBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,gBAAI,IAAI,IAAI,WAAW,EAAE;AACzB,gBAAI,KAAK,SAAS,KAAK,OAAO;AAC5B,kBAAI,KAAK,IAAI,WAAW,EAAE,EAAE;AAC5B,kBAAI,UAAU,IAAI,SAAS,MAAM,KAAK;AAAA,YACxC;AACA,gBAAI,KAAK,KAAK;AACZ,kBAAI,UAAU;AACZ;AACF,mBAAK,YAAY;AAAA,YACnB,WAAW,KAAK,MAAM;AACpB,kBAAI,SAAS,KAAK;AAChB;AACF,mBAAK,YAAY,MAAM,KAAK;AAC5B,mBAAK,YAAY,MAAM,IAAI;AAAA,YAC7B,WAAW,KAAK,OAAO;AACrB,kBAAI,SAAS,KAAK;AAChB;AACF,mBAAK,YAAY,MAAM,KAAK;AAC5B,mBAAK,YAAY,MAAM,KAAK,IAAI;AAChC,mBAAK,YAAY,MAAM,IAAI;AAAA,YAC7B,OAAO;AACL,kBAAI,SAAS,KAAK;AAChB;AACF,mBAAK,YAAY,MAAM,KAAK;AAC5B,mBAAK,YAAY,MAAM,KAAK,KAAK;AACjC,mBAAK,YAAY,MAAM,KAAK,IAAI;AAChC,mBAAK,YAAY,MAAM,IAAI;AAAA,YAC7B;AAAA,UACF;AACA,eAAK,UAAU;AACf,iBAAO,SAAS;AAAA,QAClB;AACA,iBAAS,aAAa,KAAK,QAAQ,iBAAiB;AAClD,iBAAO,kBAAkB,KAAK,QAAQ,QAAQ,eAAe;AAAA,QAC/D;AACA,iBAAS,gBAAgB,KAAK;AAC5B,cAAI,MAAM;AACV,mBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,gBAAI,IAAI,IAAI,WAAW,EAAE;AACzB,gBAAI,KAAK,SAAS,KAAK;AACrB,kBAAI,UAAU,IAAI,SAAS,MAAM,IAAI,WAAW,EAAE,EAAE,IAAI;AAC1D,gBAAI,KAAK;AACP,gBAAE;AAAA,qBACK,KAAK;AACZ,qBAAO;AAAA,qBACA,KAAK;AACZ,qBAAO;AAAA;AAEP,qBAAO;AAAA,UACX;AACA,iBAAO;AAAA,QACT;AACA,YAAI,eAAe,OAAO,gBAAgB,cAAc,IAAI,YAAY,UAAU,IAAI;AACtF,iBAAS,mBAAmB,QAAQ,SAAS;AAC3C,gBAAM,IAAI,QAAQ,OAAO;AAAA,QAC3B;AACA,iBAAS,mBAAmB,KAAK,SAAS,aAAa;AACrD,mBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,kBAAM,aAAa,KAAK,IAAI,WAAW,EAAE;AAAA,UAC3C;AACA,cAAI,CAAC;AACH,kBAAM,WAAW,KAAK;AAAA,QAC1B;AACA,iBAAS,QAAQ,GAAG,UAAU;AAC5B,cAAI,IAAI,WAAW,GAAG;AACpB,iBAAK,WAAW,IAAI;AAAA,UACtB;AACA,iBAAO;AAAA,QACT;AACA,YAAI,SAAS,OAAO,QAAQ,QAAQ,SAAS,QAAQ,SAAS,SAAS;AACvE,iBAAS,2BAA2B,KAAK;AACvC,oBAAU;AACV,iBAAO,WAAW,QAAQ,IAAI,UAAU,GAAG;AAC3C,iBAAO,YAAY,SAAS,IAAI,WAAW,GAAG;AAC9C,iBAAO,YAAY,SAAS,IAAI,WAAW,GAAG;AAC9C,iBAAO,YAAY,SAAS,IAAI,WAAW,GAAG;AAC9C,iBAAO,aAAa,UAAU,IAAI,YAAY,GAAG;AACjD,iBAAO,aAAa,UAAU,IAAI,YAAY,GAAG;AACjD,iBAAO,aAAa,UAAU,IAAI,aAAa,GAAG;AAClD,iBAAO,aAAa,UAAU,IAAI,aAAa,GAAG;AAAA,QACpD;AACA,YAAI,iBAAiB,OAAO,qBAAqB;AACjD,YAAI;AACJ,YAAI,eAAe,CAAC;AACpB,YAAI,aAAa,CAAC;AAClB,YAAI,gBAAgB,CAAC;AACrB,YAAI,qBAAqB;AACzB,YAAI,gBAAgB;AACpB,YAAI,0BAA0B;AAC9B,iBAAS,mBAAmB;AAC1B,iBAAO,iBAAiB,0BAA0B;AAAA,QACpD;AACA,iBAAS,SAAS;AAChB,cAAI,OAAO,WAAW;AACpB,gBAAI,OAAO,OAAO,aAAa;AAC7B,qBAAO,YAAY,CAAC,OAAO,SAAS;AACtC,mBAAO,OAAO,UAAU,QAAQ;AAC9B,0BAAY,OAAO,UAAU,MAAM,CAAC;AAAA,YACtC;AAAA,UACF;AACA,+BAAqB,YAAY;AAAA,QACnC;AACA,iBAAS,cAAc;AACrB,+BAAqB;AACrB,+BAAqB,UAAU;AAAA,QACjC;AACA,iBAAS,cAAc;AACrB,0BAAgB;AAAA,QAClB;AACA,iBAAS,UAAU;AACjB,cAAI,OAAO,YAAY;AACrB,gBAAI,OAAO,OAAO,cAAc;AAC9B,qBAAO,aAAa,CAAC,OAAO,UAAU;AACxC,mBAAO,OAAO,WAAW,QAAQ;AAC/B,2BAAa,OAAO,WAAW,MAAM,CAAC;AAAA,YACxC;AAAA,UACF;AACA,+BAAqB,aAAa;AAAA,QACpC;AACA,iBAAS,YAAY,IAAI;AACvB,uBAAa,QAAQ,EAAE;AAAA,QACzB;AACA,iBAAS,UAAU,IAAI;AACrB,qBAAW,QAAQ,EAAE;AAAA,QACvB;AACA,iBAAS,aAAa,IAAI;AACxB,wBAAc,QAAQ,EAAE;AAAA,QAC1B;AACA,YAAI,kBAAkB;AACtB,YAAI,uBAAuB;AAC3B,YAAI,wBAAwB;AAC5B,iBAAS,iBAAiB,IAAI;AAC5B;AACA,cAAI,OAAO,2BAA2B;AACpC,mBAAO,0BAA0B,eAAe;AAAA,UAClD;AAAA,QACF;AACA,iBAAS,oBAAoB,IAAI;AAC/B;AACA,cAAI,OAAO,2BAA2B;AACpC,mBAAO,0BAA0B,eAAe;AAAA,UAClD;AACA,cAAI,mBAAmB,GAAG;AACxB,gBAAI,yBAAyB,MAAM;AACjC,4BAAc,oBAAoB;AAClC,qCAAuB;AAAA,YACzB;AACA,gBAAI,uBAAuB;AACzB,kBAAI,WAAW;AACf,sCAAwB;AACxB,uBAAS;AAAA,YACX;AAAA,UACF;AAAA,QACF;AACA,eAAO,qBAAqB,CAAC;AAC7B,eAAO,qBAAqB,CAAC;AAC7B,iBAAS,MAAM,MAAM;AACnB;AACE,gBAAI,OAAO,YAAY;AACrB,qBAAO,WAAW,IAAI;AAAA,YACxB;AAAA,UACF;AACA,iBAAO,aAAa,OAAO;AAC3B,cAAI,IAAI;AACR,kBAAQ;AACR,uBAAa;AACb,kBAAQ;AACR,cAAI,KAAK,IAAI,YAAY,aAAa,IAAI;AAC1C,6BAAmB,EAAE;AACrB,gBAAM;AAAA,QACR;AACA,YAAI,gBAAgB;AACpB,iBAAS,UAAU,UAAU;AAC3B,iBAAO,SAAS,WAAW,aAAa;AAAA,QAC1C;AACA,iBAAS,UAAU,UAAU;AAC3B,iBAAO,SAAS,WAAW,SAAS;AAAA,QACtC;AACA,YAAI;AACJ,yBAAiB;AACjB,YAAI,CAAC,UAAU,cAAc,GAAG;AAC9B,2BAAiB,WAAW,cAAc;AAAA,QAC5C;AACA,iBAAS,UAAU,MAAM;AACvB,cAAI;AACF,gBAAI,QAAQ,kBAAkB,YAAY;AACxC,qBAAO,IAAI,WAAW,UAAU;AAAA,YAClC;AACA,gBAAI,YAAY;AACd,qBAAO,WAAW,IAAI;AAAA,YACxB,OAAO;AACL,oBAAM;AAAA,YACR;AAAA,UACF,SAAS,MAAP;AACA,kBAAM,IAAI;AAAA,UACZ;AAAA,QACF;AACA,iBAAS,mBAAmB;AAC1B,cAAI,CAAC,eAAe,sBAAsB,wBAAwB;AAChE,gBAAI,OAAO,UAAU,cAAc,CAAC,UAAU,cAAc,GAAG;AAC7D,qBAAO,MAAM,gBAAgB,EAAE,aAAa,cAAc,CAAC,EAAE,KAAK,SAAS,UAAU;AACnF,oBAAI,CAAC,SAAS,OAAO;AACnB,wBAAM,yCAAyC,iBAAiB;AAAA,gBAClE;AACA,uBAAO,SAAS,eAAe;AAAA,cACjC,CAAC,EAAE,MAAM,WAAW;AAClB,uBAAO,UAAU,cAAc;AAAA,cACjC,CAAC;AAAA,YACH,OAAO;AACL,kBAAI,WAAW;AACb,uBAAO,IAAI,QAAQ,SAAS,SAAS,QAAQ;AAC3C,4BAAU,gBAAgB,SAAS,UAAU;AAC3C,4BAAQ,IAAI,WAAW,QAAQ,CAAC;AAAA,kBAClC,GAAG,MAAM;AAAA,gBACX,CAAC;AAAA,cACH;AAAA,YACF;AAAA,UACF;AACA,iBAAO,QAAQ,QAAQ,EAAE,KAAK,WAAW;AACvC,mBAAO,UAAU,cAAc;AAAA,UACjC,CAAC;AAAA,QACH;AACA,iBAAS,aAAa;AACpB,cAAI,OAAO,EAAE,OAAO,eAAe,0BAA0B,cAAc;AAC3E,mBAAS,gBAAgB,UAAU,SAAS;AAC1C,gBAAI,WAAW,SAAS;AACxB,mBAAO,SAAS;AAChB,yBAAa,OAAO,OAAO;AAC3B,uCAA2B,WAAW,MAAM;AAC5C,wBAAY,OAAO,OAAO;AAC1B,sBAAU,OAAO,OAAO,oBAAoB;AAC5C,gCAAoB,kBAAkB;AAAA,UACxC;AACA,2BAAiB,kBAAkB;AACnC,mBAAS,2BAA2B,QAAQ;AAC1C,4BAAgB,OAAO,WAAW;AAAA,UACpC;AACA,mBAAS,uBAAuB,UAAU;AACxC,mBAAO,iBAAiB,EAAE,KAAK,SAAS,QAAQ;AAC9C,qBAAO,YAAY,YAAY,QAAQ,IAAI;AAAA,YAC7C,CAAC,EAAE,KAAK,SAAS,UAAU;AACzB,qBAAO;AAAA,YACT,CAAC,EAAE,KAAK,UAAU,SAAS,QAAQ;AACjC,kBAAI,4CAA4C,MAAM;AACtD,oBAAM,MAAM;AAAA,YACd,CAAC;AAAA,UACH;AACA,mBAAS,mBAAmB;AAC1B,gBAAI,CAAC,cAAc,OAAO,YAAY,yBAAyB,cAAc,CAAC,UAAU,cAAc,KAAK,CAAC,UAAU,cAAc,KAAK,OAAO,UAAU,YAAY;AACpK,qBAAO,MAAM,gBAAgB,EAAE,aAAa,cAAc,CAAC,EAAE,KAAK,SAAS,UAAU;AACnF,oBAAI,SAAS,YAAY,qBAAqB,UAAU,IAAI;AAC5D,uBAAO,OAAO,KAAK,4BAA4B,SAAS,QAAQ;AAC9D,sBAAI,oCAAoC,MAAM;AAC9C,sBAAI,2CAA2C;AAC/C,yBAAO,uBAAuB,0BAA0B;AAAA,gBAC1D,CAAC;AAAA,cACH,CAAC;AAAA,YACH,OAAO;AACL,qBAAO,uBAAuB,0BAA0B;AAAA,YAC1D;AAAA,UACF;AACA,cAAI,OAAO,oBAAoB;AAC7B,gBAAI;AACF,kBAAI,WAAW,OAAO,mBAAmB,MAAM,eAAe;AAC9D,qBAAO;AAAA,YACT,SAAS,IAAP;AACA,kBAAI,wDAAwD,EAAE;AAC9D,qBAAO;AAAA,YACT;AAAA,UACF;AACA,2BAAiB,EAAE,MAAM,kBAAkB;AAC3C,iBAAO,CAAC;AAAA,QACV;AACA,YAAI;AACJ,YAAI;AACJ,iBAAS,qBAAqB,YAAY;AACxC,iBAAO,WAAW,SAAS,GAAG;AAC5B,gBAAI,WAAW,WAAW,MAAM;AAChC,gBAAI,OAAO,YAAY,YAAY;AACjC,uBAAS,MAAM;AACf;AAAA,YACF;AACA,gBAAI,QAAQ,SAAS;AACrB,gBAAI,OAAO,UAAU,UAAU;AAC7B,kBAAI,SAAS,QAAQ,QAAQ;AAC3B,kCAAkB,KAAK,EAAE;AAAA,cAC3B,OAAO;AACL,kCAAkB,KAAK,EAAE,SAAS,GAAG;AAAA,cACvC;AAAA,YACF,OAAO;AACL,oBAAM,SAAS,QAAQ,SAAS,OAAO,SAAS,GAAG;AAAA,YACrD;AAAA,UACF;AAAA,QACF;AACA,iBAAS,SAAS,OAAO;AACvB,iBAAO;AAAA,QACT;AACA,iBAAS,YAAY,MAAM;AACzB,cAAI,QAAQ;AACZ,iBAAO,KAAK,QAAQ,OAAO,SAAS,GAAG;AACrC,gBAAI,IAAI,SAAS,CAAC;AAClB,mBAAO,MAAM,IAAI,IAAI,IAAI,OAAO,IAAI;AAAA,UACtC,CAAC;AAAA,QACH;AACA,YAAI,kBAAkB,CAAC;AACvB,iBAAS,kBAAkB,SAAS;AAClC,cAAI,QAAQ,gBAAgB;AAC5B,cAAI,CAAC,OAAO;AACV,gBAAI,WAAW,gBAAgB;AAC7B,8BAAgB,SAAS,UAAU;AACrC,4BAAgB,WAAW,QAAQ,UAAU,IAAI,OAAO;AAAA,UAC1D;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,eAAe;AACtB,cAAI,QAAQ,IAAI,MAAM;AACtB,cAAI,CAAC,MAAM,OAAO;AAChB,gBAAI;AACF,oBAAM,IAAI,MAAM;AAAA,YAClB,SAAS,IAAP;AACA,sBAAQ;AAAA,YACV;AACA,gBAAI,CAAC,MAAM,OAAO;AAChB,qBAAO;AAAA,YACT;AAAA,UACF;AACA,iBAAO,MAAM,MAAM,SAAS;AAAA,QAC9B;AACA,iBAAS,kBAAkB,KAAK,OAAO;AACrC,oBAAU,IAAI,KAAK,KAAK;AACxB,0BAAgB,OAAO;AAAA,QACzB;AACA,iBAAS,SAAS;AAChB,gBAAM,EAAE;AAAA,QACV;AACA,iBAAS,2BAA2B;AAClC,iBAAO;AAAA,QACT;AACA,iBAAS,uBAAuB,MAAM,KAAK,KAAK;AAC9C,iBAAO,WAAW,MAAM,KAAK,MAAM,GAAG;AAAA,QACxC;AACA,iBAAS,0BAA0BP,OAAM;AACvC,cAAI;AACF,uBAAW,KAAKA,QAAO,QAAQ,aAAa,UAAU,EAAE;AACxD,uCAA2B,WAAW,MAAM;AAC5C,mBAAO;AAAA,UACT,SAAS,IAAP;AAAA,UACF;AAAA,QACF;AACA,iBAAS,wBAAwB,eAAe;AAC9C,cAAI,UAAU,OAAO;AACrB,0BAAgB,kBAAkB;AAClC,cAAI,cAAc,yBAAyB;AAC3C,cAAI,gBAAgB,aAAa;AAC/B,mBAAO;AAAA,UACT;AACA,mBAAS,UAAU,GAAG,WAAW,GAAG,WAAW,GAAG;AAChD,gBAAI,oBAAoB,WAAW,IAAI,MAAM;AAC7C,gCAAoB,KAAK,IAAI,mBAAmB,gBAAgB,SAAS;AACzE,gBAAI,UAAU,KAAK,IAAI,aAAa,QAAQ,KAAK,IAAI,eAAe,iBAAiB,GAAG,KAAK,CAAC;AAC9F,gBAAI,cAAc,0BAA0B,OAAO;AACnD,gBAAI,aAAa;AACf,qBAAO;AAAA,YACT;AAAA,UACF;AACA,iBAAO;AAAA,QACT;AACA,YAAI,WAAW,EAAE,UAAU,CAAC,GAAG,SAAS,CAAC,MAAM,CAAC,GAAG,CAAC,CAAC,GAAG,WAAW,SAAS,QAAQ,MAAM;AACxF,cAAI,UAAU,SAAS,QAAQ;AAC/B,cAAI,SAAS,KAAK,SAAS,IAAI;AAC7B,aAAC,WAAW,IAAI,MAAM,KAAK,kBAAkB,SAAS,CAAC,CAAC;AACxD,oBAAQ,SAAS;AAAA,UACnB,OAAO;AACL,oBAAQ,KAAK,IAAI;AAAA,UACnB;AAAA,QACF,GAAG,SAAS,QAAQ,KAAK,WAAW;AAClC,mBAAS,WAAW;AACpB,cAAI,MAAM,OAAO,SAAS,UAAU,KAAK;AACzC,iBAAO;AAAA,QACT,GAAG,QAAQ,SAAS,KAAK;AACvB,cAAI,MAAM,aAAa,GAAG;AAC1B,iBAAO;AAAA,QACT,GAAG,OAAO,SAAS,KAAK,MAAM;AAC5B,iBAAO;AAAA,QACT,EAAE;AACF,iBAAS,UAAU,IAAI;AACrB,iBAAO;AAAA,QACT;AACA,iBAAS,SAAS,IAAI,YAAY,aAAa,QAAQ,WAAW;AAAA,QAClE;AACA,iBAAS,UAAU,IAAI,KAAK,QAAQ,MAAM;AACxC,cAAI,MAAM;AACV,mBAAS,KAAK,GAAG,KAAK,QAAQ,MAAM;AAClC,gBAAI,MAAM,OAAO,OAAO;AACxB,gBAAI,MAAM,OAAO,MAAM,KAAK;AAC5B,mBAAO;AACP,qBAAS,IAAI,GAAG,IAAI,KAAK,KAAK;AAC5B,uBAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AAAA,YACxC;AACA,mBAAO;AAAA,UACT;AACA,iBAAO,QAAQ,KAAK;AACpB,iBAAO;AAAA,QACT;AACA,iBAAS,aAAa,KAAK;AACzB,sBAAY,GAAG;AAAA,QACjB;AACA,YAAI,aAAa;AACjB,YAAI,gBAAgB,EAAE,SAAS,QAAQ,2BAA2B,0BAA0B,yBAAyB,wBAAwB,0BAA0B,yBAAyB,YAAY,WAAW,WAAW,UAAU,YAAY,WAAW,eAAe,aAAa;AAC/R,YAAI,MAAM,WAAW;AACrB,YAAI,qBAAqB,OAAO,wBAAwB,WAAW;AACjE,kBAAQ,qBAAqB,OAAO,wBAAwB,OAAO,OAAO,sBAAsB,MAAM,MAAM,SAAS;AAAA,QACvH;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,2BAA2B,OAAO,8BAA8B,WAAW;AAC7E,kBAAQ,2BAA2B,OAAO,8BAA8B,OAAO,OAAO,4BAA4B,MAAM,MAAM,SAAS;AAAA,QACzI;AACA,YAAI,qBAAqB,OAAO,wBAAwB,WAAW;AACjE,kBAAQ,qBAAqB,OAAO,wBAAwB,OAAO,OAAO,sBAAsB,MAAM,MAAM,SAAS;AAAA,QACvH;AACA,YAAI,mBAAmB,OAAO,sBAAsB,WAAW;AAC7D,kBAAQ,mBAAmB,OAAO,sBAAsB,OAAO,OAAO,oBAAoB,MAAM,MAAM,SAAS;AAAA,QACjH;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,gBAAgB,MAAM,MAAM,SAAS;AAAA,QACrG;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,gBAAgB,MAAM,MAAM,SAAS;AAAA,QACrG;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,iBAAiB,OAAO,oBAAoB,WAAW;AACzD,kBAAQ,iBAAiB,OAAO,oBAAoB,OAAO,OAAO,kBAAkB,MAAM,MAAM,SAAS;AAAA,QAC3G;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,yBAAyB,OAAO,4BAA4B,WAAW;AACzE,kBAAQ,yBAAyB,OAAO,4BAA4B,OAAO,OAAO,0BAA0B,MAAM,MAAM,SAAS;AAAA,QACnI;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,iBAAiB,OAAO,oBAAoB,WAAW;AACzD,kBAAQ,iBAAiB,OAAO,oBAAoB,OAAO,OAAO,kBAAkB,MAAM,MAAM,SAAS;AAAA,QAC3G;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,kBAAkB,OAAO,qBAAqB,WAAW;AAC3D,kBAAQ,kBAAkB,OAAO,qBAAqB,OAAO,OAAO,mBAAmB,MAAM,MAAM,SAAS;AAAA,QAC9G;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,gBAAgB,MAAM,MAAM,SAAS;AAAA,QACrG;AACA,YAAI,wBAAwB,OAAO,2BAA2B,WAAW;AACvE,kBAAQ,wBAAwB,OAAO,2BAA2B,OAAO,OAAO,yBAAyB,MAAM,MAAM,SAAS;AAAA,QAChI;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,cAAc,OAAO,iBAAiB,WAAW;AACnD,kBAAQ,cAAc,OAAO,iBAAiB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAClG;AACA,YAAI,cAAc,OAAO,iBAAiB,WAAW;AACnD,kBAAQ,cAAc,OAAO,iBAAiB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAClG;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,cAAc,OAAO,iBAAiB,WAAW;AACnD,kBAAQ,cAAc,OAAO,iBAAiB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAClG;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,kBAAkB,OAAO,qBAAqB,WAAW;AAC3D,kBAAQ,kBAAkB,OAAO,qBAAqB,OAAO,OAAO,mBAAmB,MAAM,MAAM,SAAS;AAAA,QAC9G;AACA,YAAI,yBAAyB,OAAO,4BAA4B,WAAW;AACzE,kBAAQ,yBAAyB,OAAO,4BAA4B,OAAO,OAAO,0BAA0B,MAAM,MAAM,SAAS;AAAA,QACnI;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,oBAAoB,OAAO,uBAAuB,WAAW;AAC/D,kBAAQ,oBAAoB,OAAO,uBAAuB,OAAO,OAAO,qBAAqB,MAAM,MAAM,SAAS;AAAA,QACpH;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,iBAAiB,OAAO,oBAAoB,WAAW;AACzD,kBAAQ,iBAAiB,OAAO,oBAAoB,OAAO,OAAO,kBAAkB,MAAM,MAAM,SAAS;AAAA,QAC3G;AACA,YAAI,0BAA0B,OAAO,6BAA6B,WAAW;AAC3E,kBAAQ,0BAA0B,OAAO,6BAA6B,OAAO,OAAO,2BAA2B,MAAM,MAAM,SAAS;AAAA,QACtI;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,qBAAqB,OAAO,wBAAwB,WAAW;AACjE,kBAAQ,qBAAqB,OAAO,wBAAwB,OAAO,OAAO,sBAAsB,MAAM,MAAM,SAAS;AAAA,QACvH;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,oBAAoB,OAAO,uBAAuB,WAAW;AAC/D,kBAAQ,oBAAoB,OAAO,uBAAuB,OAAO,OAAO,qBAAqB,MAAM,MAAM,SAAS;AAAA,QACpH;AACA,YAAI,+CAA+C,OAAO,kDAAkD,WAAW;AACrH,kBAAQ,+CAA+C,OAAO,kDAAkD,OAAO,OAAO,gDAAgD,MAAM,MAAM,SAAS;AAAA,QACrM;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC7F;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACtG;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAChG;AACA,YAAI,mBAAmB,OAAO,sBAAsB,WAAW;AAC7D,kBAAQ,mBAAmB,OAAO,sBAAsB,OAAO,OAAO,qBAAqB,MAAM,MAAM,SAAS;AAAA,QAClH;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACtG;AACA,eAAO,WAAW;AAClB,YAAI;AACJ,iBAAS,WAAW,QAAQ;AAC1B,eAAK,OAAO;AACZ,eAAK,UAAU,kCAAkC,SAAS;AAC1D,eAAK,SAAS;AAAA,QAChB;AACA,gCAAwB,SAAS,YAAY;AAC3C,cAAI,CAAC;AACH,gBAAI;AACN,cAAI,CAAC;AACH,oCAAwB;AAAA,QAC5B;AACA,iBAAS,IAAI,MAAM;AACjB,iBAAO,QAAQ;AACf,cAAI,kBAAkB,GAAG;AACvB;AAAA,UACF;AACA,iBAAO;AACP,cAAI,kBAAkB,GAAG;AACvB;AAAA,UACF;AACA,mBAAS,QAAQ;AACf,gBAAI;AACF;AACF,wBAAY;AACZ,mBAAO,eAAe;AACtB,gBAAI;AACF;AACF,wBAAY;AACZ,gCAAoB,MAAM;AAC1B,gBAAI,OAAO;AACT,qBAAO,wBAAwB;AACjC,oBAAQ;AAAA,UACV;AACA,cAAI,OAAO,cAAc;AACvB,mBAAO,aAAa,YAAY;AAChC,uBAAW,WAAW;AACpB,yBAAW,WAAW;AACpB,uBAAO,aAAa,EAAE;AAAA,cACxB,GAAG,CAAC;AACJ,oBAAM;AAAA,YACR,GAAG,CAAC;AAAA,UACN,OAAO;AACL,kBAAM;AAAA,UACR;AAAA,QACF;AACA,eAAO,SAAS;AAChB,iBAAS,SAAS,MAAM;AACtB,uBAAa;AACb,cAAI,CAAC,iBAAiB,GAAG;AACvB,gBAAI,OAAO;AACT,qBAAO,UAAU,IAAI;AACvB,oBAAQ;AAAA,UACV;AACA,gBAAM,MAAM,IAAI,WAAW,IAAI,CAAC;AAAA,QAClC;AACA,YAAI,OAAO,YAAY;AACrB,cAAI,OAAO,OAAO,cAAc;AAC9B,mBAAO,aAAa,CAAC,OAAO,UAAU;AACxC,iBAAO,OAAO,WAAW,SAAS,GAAG;AACnC,mBAAO,WAAW,IAAI,EAAE;AAAA,UAC1B;AAAA,QACF;AACA,YAAI;AACJ,YAAI;AACJ,YAAI,iBAAiB;AACnB,2BAAiB,EAAE,mBAAmB,QAAQ,UAAU,mBAAmB,EAAE,OAAO,SAAS,UAAU;AACrG,mBAAO,CAAC,gBAAgB,kBAAkB,QAAQ,QAAQ,IAAI;AAAA,UAChE,CAAC,GAAG,oBAAoB,QAAQ,UAAU,oBAAoB,EAAE,OAAO,SAAS,UAAU;AACxF,mBAAO,CAAC,gBAAgB,mBAAmB,QAAQ,QAAQ,IAAI;AAAA,UACjE,CAAC,EAAE;AAAA,QACL;AACA,YAAI;AACJ,YAAI,OAAO,uBAAuB,aAAa;AAC7C,yBAAe;AAAA,QACjB,WAAW,OAAO,kCAAkC,aAAa;AAC/D,yBAAe;AAAA,QACjB,OAAO;AACL,gBAAM,IAAI,MAAM,uCAAuC;AAAA,QACzD;AACA,YAAI,gBAAgB;AAClB,cAAI,aAAa,aAAa;AAC9B,uBAAa,cAAc,WAAW;AACpC,uBAAW;AACX,2BAAe,kBAAkB,QAAQ,SAAS,UAAU;AAC1D,sBAAQ,eAAe,qBAAqB,QAAQ;AAAA,YACtD,CAAC;AACD,2BAAe,mBAAmB,QAAQ,SAAS,UAAU;AAC3D,sBAAQ,eAAe,sBAAsB,QAAQ;AAAA,YACvD,CAAC;AAAA,UACH;AAAA,QACF;AACA,eAAO,mBAAmB;AAAA,MAC5B;AAAA,IACF,GAAG;AACH,QAAI,OAAO,YAAY,YAAY,OAAO,WAAW;AACnD,aAAO,UAAU;AAAA,aACV,OAAO,WAAW,cAAc,OAAO;AAC9C,aAAO,CAAC,GAAG,WAAW;AACpB,eAAO;AAAA,MACT,CAAC;AAAA,aACM,OAAO,YAAY;AAC1B,cAAQ,uBAAuB;AAAA,EACnC;AACF,CAAC;AAGD,IAAI,kBAAkB;AACtB,IAAI,kBAAkB;AACtB,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,UAAU,WAAW;AAC/B,SAAK,UAAU;AACf,SAAK,YAAY;AACjB,SAAK,OAAuB,oBAAI,QAAQ;AACxC,SAAK,eAAe;AAAA,EACtB;AAAA,EACA,IAAI,QAAQ;AACV,QAAI,CAAC,KAAK,KAAK,IAAI,MAAM,GAAG;AAC1B,WAAK,UAAU,SAAS,KAAK,SAAS,MAAM;AAAA,IAC9C;AACA,WAAO,KAAK,KAAK,IAAI,MAAM;AAAA,EAC7B;AAAA,EACA,IAAI,QAAQ,OAAO;AACjB,SAAK;AACL,SAAK,KAAK,IAAI,QAAQ,KAAK;AAAA,EAC7B;AAAA,EACA,IAAI,QAAQ;AACV,WAAO,KAAK,KAAK,IAAI,MAAM;AAAA,EAC7B;AAAA,EACA,OAAO,QAAQ;AACb,SAAK;AACL,WAAO,KAAK,KAAK,OAAO,MAAM;AAAA,EAChC;AAAA,EACA,aAAa;AACX,WAAO,KAAK;AAAA,EACd;AACF;AACA,IAAI,gBAAgB,MAAM;AAAA,EACxB,SAAS,QAAQ;AACf,WAAO,kBAAkB,UAAU;AAAA,EACrC;AAAA,EACA,OAAO,QAAQ;AACb,WAAO,kBAAkB,QAAQ;AAAA,EACnC;AAAA,EACA,iBAAiB;AACf,WAAO;AAAA,EACT;AAAA,EACA,KAAK,GAAG;AACN,WAAO,kBAAkB,MAAM;AAAA,EACjC;AAAA,EACA,KAAK,QAAQ;AACX,WAAO,kBAAkB,MAAM;AAAA,EACjC;AAAA,EACA,SAAS,QAAQ;AACf,WAAO,kBAAkB,UAAU;AAAA,EACrC;AAAA,EACA,UAAU,QAAQM,UAAS;AACzB,WAAO,kBAAkB,WAAW;AAAA,EACtC;AAAA,EACA,aAAa;AACX,WAAO,kBAAkB,YAAY;AAAA,EACvC;AAAA,EACA,YAAY,QAAQ,OAAO;AACzB,WAAO,kBAAkB,aAAa;AAAA,EACxC;AAAA,EACA,MAAM,QAAQ,OAAO,OAAO;AAC1B,WAAO,kBAAkB,OAAO;AAAA,EAClC;AAAA,EACA,KAAK,QAAQ,QAAQ,OAAO,OAAO,UAAU;AAC3C,WAAO,kBAAkB,MAAM;AAAA,EACjC;AAAA,EACA,SAAS;AACP,WAAO,kBAAkB,QAAQ;AAAA,EACnC;AAAA,EACA,iBAAiB;AACf,WAAO,kBAAkB,gBAAgB;AAAA,EAC3C;AAAA,EACA,UAAU;AACR,WAAO,KAAK,eAAe,MAAM,KAAK,kBAAkB;AAAA,EAC1D;AAAA,EACA,UAAU;AACR,WAAO,kBAAkB,SAAS;AAAA,EACpC;AACF;AACA,SAAS,kBAAkB,YAAY;AACrC,QAAM,IAAI,MAAM,IAAI,oIAAoI;AAC1J;AAGA,SAAS,QAAQ,QAAQ;AACvB,MAAI,UAAU,OAAO;AACrB,MAAIG,SAAQ;AACZ,SAAO,UAAU,GAAG;AAClB,IAAAA,SAAQ,KAAK,OAAO,IAAI,UAAU;AAClC;AACA,SAAK,QAAQ,SAASA,MAAK;AAAA,EAC7B;AACF;AACA,SAAS,aAAa,QAAQ,SAAS;AACrC,MAAI,OAAO,WAAW,QAAQ,QAAQ;AACpC,UAAM,IAAI,MAAM,yEAAyE,OAAO,iCAAiC,QAAQ,QAAQ;AAAA,EACnJ;AACA,MAAI,UAAU,OAAO;AACrB,MAAIA,SAAQ;AACZ,SAAO,UAAU,GAAG;AAClB,IAAAA,SAAQ,KAAK,OAAO,IAAI,UAAU;AAClC;AACA,SAAK,QAAQ,SAASA,MAAK;AAC3B,SAAK,SAAS,SAASA,MAAK;AAAA,EAC9B;AACF;AACA,SAAS,MAAM,MAAM,GAAG,MAAM;AAC5B,SAAO,KAAK,IAAI,MAAM,KAAK,IAAI,GAAG,IAAI,CAAC;AACzC;AACA,SAAS,kBAAkB,KAAK;AAC9B,SAAO,MAAM,MAAM,IAAI,MAAM,MAAM;AACrC;AACA,SAAS,KAAKE,SAAQ,MAAM,OAAO;AACjC,QAAM,OAAOA,QAAO;AACpB,EAAAA,QAAO,QAAQA,QAAO;AACtB,EAAAA,QAAO,SAAS;AAClB;AACA,SAAS,IAAI,KAAK;AAChB,MAAI,OAAO;AACX,WAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,MAAM;AACtC,YAAQ,IAAI;AAAA,EACd;AACA,SAAO;AACT;AACA,SAAS,YAAY,GAAG,GAAG;AACzB,QAAM,KAAK,KAAK,OAAO;AACvB,SAAO,IAAI,MAAM,IAAI,MAAM;AAC7B;AACA,SAAS,YAAY,GAAG,GAAG;AACzB,MAAI,SAAS;AACb,WAAS,KAAK,GAAG,KAAK,EAAE,QAAQ,MAAM;AACpC,UAAM,OAAO,OAAO,EAAE,GAAG,IAAI,OAAO,EAAE,GAAG;AACzC,cAAU,OAAO;AAAA,EACnB;AACA,SAAO;AACT;AACA,SAAS,OAAO,MAAM,KAAK;AACzB,MAAI,CAAC,MAAM;AACT,UAAM,IAAI,MAAM,OAAO,QAAQ,WAAW,MAAM,IAAI,CAAC;AAAA,EACvD;AACF;AACA,SAAS,kBAAkB,QAAQ,QAAQ,qBAAqB,IAAI;AAClE,SAAO,YAAY,QAAQ,MAAM,GAAG,MAAM,qBAAqB,WAAW,cAAc,mBAAmB;AAC7G;AACA,SAAS,cAAc,GAAG;AACxB,SAAO,KAAK,MAAM,MAAM,+DAA+D;AACzF;AACA,SAAS,QAAQ,KAAK,SAAS,CAAC,GAAG,iBAAiB,OAAO;AACzD,MAAI,UAAU,MAAM;AAClB,aAAS,CAAC;AAAA,EACZ;AACA,MAAI,MAAM,QAAQ,GAAG,KAAK,aAAa,GAAG,KAAK,CAAC,gBAAgB;AAC9D,aAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,cAAQ,IAAI,KAAK,QAAQ,cAAc;AAAA,IACzC;AAAA,EACF,OAAO;AACL,WAAO,KAAK,GAAG;AAAA,EACjB;AACA,SAAO;AACT;AACA,SAAS,cAAc,OAAO;AAC5B,MAAI,MAAM,WAAW,GAAG;AACtB,WAAO;AAAA,EACT;AACA,MAAIX,QAAO,MAAM;AACjB,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,IAAAA,SAAQ,MAAM;AAAA,EAChB;AACA,SAAOA;AACT;AACA,SAAS,cAAc,OAAO;AAC5B,SAAO,MAAM,WAAW;AAC1B;AACA,SAAS,YAAY,IAAI,IAAI;AAC3B,MAAI,OAAO,IAAI;AACb,WAAO;AAAA,EACT;AACA,MAAI,MAAM,QAAQ,MAAM,MAAM;AAC5B,WAAO;AAAA,EACT;AACA,MAAI,GAAG,WAAW,GAAG,QAAQ;AAC3B,WAAO;AAAA,EACT;AACA,WAAS,KAAK,GAAG,KAAK,GAAG,QAAQ,MAAM;AACrC,QAAI,GAAG,QAAQ,GAAG,KAAK;AACrB,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,MAAM,GAAG;AAChB,SAAO,IAAI,MAAM;AACnB;AACA,SAAS,KAAK,GAAG;AACf,MAAI,KAAK,QAAQ,MAAM;AACrB,WAAO,KAAK,KAAK,CAAC;AAAA,EACpB;AACA,MAAI,MAAM,UAAU;AAClB,WAAO;AAAA,EACT,WAAW,MAAM,WAAW;AAC1B,WAAO;AAAA,EACT,OAAO;AACL,UAAM,MAAM,KAAK,IAAI,IAAI,CAAC;AAC1B,YAAQ,MAAM,MAAM,MAAM;AAAA,EAC5B;AACF;AACA,SAAS,oBAAoBA,OAAM;AACjC,QAAM,QAAQ,KAAK,KAAK,KAAK,KAAKA,KAAI,CAAC;AACvC,SAAO,CAAC,OAAO,KAAK,KAAKA,QAAO,KAAK,CAAC;AACxC;AACA,SAAS,sBAAsB,IAAI;AACjC,QAAM,kBAAkB,IAAI,YAAY,EAAE;AAC1C,WAAS,KAAK,GAAG,KAAK,IAAI,EAAE,IAAI;AAC9B,oBAAgB,MAAM;AAAA,EACxB;AACA,UAAQ,eAAe;AACvB,SAAO;AACT;AACA,SAAS,SAAS,GAAGA,OAAM;AACzB,MAAIA,SAAQ,EAAE,QAAQ;AACpB,WAAO;AAAA,EACT;AACA,SAAO,IAAI,IAAI,OAAOA,QAAO,EAAE,MAAM;AACvC;AACA,SAAS,YAAY,SAAS,UAAU,CAAC,YAAY,GAAG,YAAY;AAClE,SAAO,IAAI,QAAQ,CAAC,SAAS,WAAW;AACtC,QAAI,WAAW;AACf,UAAM,QAAQ,MAAM;AAClB,UAAI,QAAQ,GAAG;AACb,gBAAQ;AACR;AAAA,MACF;AACA;AACA,YAAM,cAAc,QAAQ,QAAQ;AACpC,UAAI,cAAc,QAAQ,YAAY,YAAY;AAChD,eAAO;AACP;AAAA,MACF;AACA,iBAAW,OAAO,WAAW;AAAA,IAC/B;AACA,UAAM;AAAA,EACR,CAAC;AACH;AACA,SAAS,uBAAuB,OAAOA,OAAM;AAC3C,MAAI,YAAY;AAChB,MAAI,cAAc;AAClB,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,QAAI,MAAM,OAAO,GAAG;AAClB,mBAAa,MAAM;AAAA,IACrB,WAAW,MAAM,QAAQ,IAAI;AAC3B,UAAI,gBAAgB,IAAI;AACtB,cAAM,MAAM,yDAAyD,uBAAuB,IAAI;AAAA,MAClG;AACA,oBAAc;AAAA,IAChB,WAAW,MAAM,MAAM,GAAG;AACxB,YAAM,MAAM,gCAAgC,MAAM,cAAc,IAAI;AAAA,IACtE;AAAA,EACF;AACA,MAAI,gBAAgB,IAAI;AACtB,QAAIA,QAAO,KAAKA,UAAS,WAAW;AAClC,YAAM,MAAM,QAAQA,0CAAyC,OAAO;AAAA,IACtE;AACA,WAAO;AAAA,EACT;AACA,MAAI,cAAc,GAAG;AACnB,UAAM,MAAM,qCAAqC,kCAAkC;AAAA,EACrF;AACA,MAAIA,QAAO,cAAc,GAAG;AAC1B,UAAM,MAAM,wDAAwDA,WAAU,WAAW;AAAA,EAC3F;AACA,QAAM,WAAW,MAAM,MAAM;AAC7B,WAAS,eAAeA,QAAO;AAC/B,SAAO;AACT;AACA,SAAS,eAAe,MAAM,OAAO;AACnC,QAAM,OAAO,MAAM;AACnB,SAAO,QAAQ,OAAO,MAAM,IAAI,CAAC,IAAI,OAAO,EAAE,IAAI,CAAC,EAAE,OAAO,IAAI;AAChE,SAAO,KAAK,MAAM,CAAC,OAAO,MAAM,CAAC,QAAQ,KAAK,IAAI,GAAG,MAAM,+CAA+C,SAAS,sBAAsB,MAAM;AAC/I,SAAO,KAAK,MAAM,CAAC,OAAO,MAAM,EAAE,CAAC,GAAG,MAAM,0DAA0D,MAAM;AAC5G,SAAO,KAAK,IAAI,CAAC,MAAM,IAAI,IAAI,OAAO,IAAI,CAAC;AAC7C;AACA,SAAS,aAAa,OAAO,MAAM;AACjC,QAAM,WAAW,CAAC;AAClB,QAAM,WAAW,CAAC;AAClB,QAAM,eAAe,QAAQ,QAAQ,MAAM,QAAQ,IAAI,KAAK,KAAK,WAAW;AAC5E,QAAM,OAAO,QAAQ,QAAQ,eAAe,OAAO,eAAe,MAAM,KAAK,EAAE,KAAK;AACpF,MAAI,IAAI;AACR,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,QAAI,QAAQ,MAAM;AAChB,UAAI,KAAK,OAAO,MAAM,MAAM,QAAQ,GAAG;AACrC,cAAM,IAAI,MAAM,sBAAsB,qBAAqB,MAAM,eAAe;AAAA,MAClF;AACA,WAAK,KAAK,MAAM,QAAQ,KAAK,KAAK,OAAO,MAAM,QAAQ,GAAG;AACxD,iBAAS,KAAK,MAAM,GAAG;AACvB,iBAAS,KAAK,EAAE;AAAA,MAClB;AACA,UAAI,KAAK,MAAM,IAAI;AACjB;AAAA,MACF;AAAA,IACF;AACA,QAAI,MAAM,QAAQ,GAAG;AACnB,eAAS,KAAK,MAAM,GAAG;AACvB,eAAS,KAAK,EAAE;AAAA,IAClB;AAAA,EACF;AACA,SAAO,EAAE,UAAU,SAAS;AAC9B;AACA,SAAS,uBAAuB,OAAOA,OAAM;AAC3C,MAAI,SAAS;AACb,MAAI,SAAS,QAAQ,UAAU,WAAW;AACxC,aAAS,IAAI,aAAaA,KAAI;AAAA,EAChC,WAAW,UAAU,SAAS;AAC5B,aAAS,IAAI,WAAWA,KAAI;AAAA,EAC9B,WAAW,UAAU,QAAQ;AAC3B,aAAS,IAAI,WAAWA,KAAI;AAAA,EAC9B,OAAO;AACL,UAAM,IAAI,MAAM,qBAAqB,OAAO;AAAA,EAC9C;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,OAAOA,OAAM;AACtC,MAAI,SAAS;AACb,MAAI,SAAS,QAAQ,UAAU,WAAW;AACxC,aAAS,IAAI,aAAaA,KAAI;AAAA,EAChC,WAAW,UAAU,SAAS;AAC5B,aAAS,IAAI,WAAWA,KAAI;AAAA,EAC9B,WAAW,UAAU,QAAQ;AAC3B,aAAS,IAAI,WAAWA,KAAI;AAAA,EAC9B,WAAW,UAAU,UAAU;AAC7B,aAAS,IAAI,MAAMA,KAAI;AAAA,EACzB,OAAO;AACL,UAAM,IAAI,MAAM,qBAAqB,OAAO;AAAA,EAC9C;AACA,SAAO;AACT;AACA,SAAS,yBAAyB,MAAM,OAAO;AAC7C,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,UAAM,MAAM,KAAK;AACjB,QAAI,MAAM,GAAG,KAAK,CAAC,SAAS,GAAG,GAAG;AAChC,YAAM,MAAM,oBAAoB,iCAAiC,MAAM;AAAA,IACzE;AAAA,EACF;AACF;AACA,SAAS,aAAa,OAAO;AAC3B,SAAO,UAAU,UAAU,UAAU,eAAe,UAAU,aAAa,UAAU,WAAW,UAAU;AAC5G;AACA,SAAS,gBAAgB,SAAS,SAAS;AACzC,MAAI,YAAY,aAAa;AAC3B,WAAO;AAAA,EACT;AACA,MAAI,YAAY,aAAa,YAAY,aAAa;AACpD,WAAO;AAAA,EACT;AACA,MAAI,YAAY,WAAW,YAAY,aAAa,YAAY,aAAa;AAC3E,WAAO;AAAA,EACT;AACA,MAAI,YAAY,UAAU,YAAY,QAAQ;AAC5C,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,aAAa,GAAG;AACvB,SAAO,aAAa,gBAAgB,aAAa,cAAc,aAAa,cAAc,aAAa;AACzG;AACA,SAAS,gBAAgB,OAAO;AAC9B,MAAI,UAAU,aAAa,UAAU,SAAS;AAC5C,WAAO;AAAA,EACT,WAAW,UAAU,aAAa;AAChC,WAAO;AAAA,EACT,WAAW,UAAU,QAAQ;AAC3B,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,iBAAiB,OAAO;AAAA,EAC1C;AACF;AACA,SAAS,qBAAqB,KAAK;AACjC,MAAI,OAAO,MAAM;AACf,WAAO;AAAA,EACT;AACA,MAAI,QAAQ;AACZ,MAAI,QAAQ,CAAC,MAAM,SAAS,EAAE,MAAM;AACpC,SAAO;AACT;AACA,SAAS,SAAS,OAAO;AACvB,SAAO,OAAO,UAAU,YAAY,iBAAiB;AACvD;AACA,SAAS,UAAU,OAAO;AACxB,SAAO,OAAO,UAAU;AAC1B;AACA,SAAS,SAAS,OAAO;AACvB,SAAO,OAAO,UAAU;AAC1B;AACA,SAAS,WAAW,QAAQ;AAC1B,MAAI,MAAM,QAAQ,MAAM,GAAG;AACzB,WAAO,WAAW,OAAO,EAAE;AAAA,EAC7B;AACA,MAAI,kBAAkB,cAAc;AAClC,WAAO;AAAA,EACT,WAAW,kBAAkB,cAAc,kBAAkB,cAAc,kBAAkB,mBAAmB;AAC9G,WAAO;AAAA,EACT,WAAW,SAAS,MAAM,GAAG;AAC3B,WAAO;AAAA,EACT,WAAW,SAAS,MAAM,GAAG;AAC3B,WAAO;AAAA,EACT,WAAW,UAAU,MAAM,GAAG;AAC5B,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,WAAW,GAAG;AACrB,SAAO,CAAC,EAAE,KAAK,EAAE,eAAe,EAAE,QAAQ,EAAE;AAC9C;AACA,SAAS,eAAeA,OAAM,OAAO;AACnC,WAAS,KAAK,OAAO,KAAKA,OAAM,EAAE,IAAI;AACpC,QAAIA,QAAO,OAAO,GAAG;AACnB,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAOA;AACT;AACA,SAAS,eAAe,OAAO;AAC7B,QAAM,OAAO,MAAM;AACnB,MAAI,OAAO,GAAG;AACZ,WAAO,CAAC;AAAA,EACV;AACA,QAAMY,WAAU,IAAI,MAAM,OAAO,CAAC;AAClC,EAAAA,SAAQ,OAAO,KAAK,MAAM,OAAO;AACjC,WAAS,KAAK,OAAO,GAAG,MAAM,GAAG,EAAE,IAAI;AACrC,IAAAA,SAAQ,MAAMA,SAAQ,KAAK,KAAK,MAAM,KAAK;AAAA,EAC7C;AACA,SAAOA;AACT;AACA,SAAS,kBAAkB,QAAQ,OAAO,GAAG,YAAY,OAAO;AAC9D,QAAM,MAAM,IAAI,MAAM;AACtB,MAAI,MAAM,WAAW,GAAG;AACtB,UAAM,IAAI,MAAM,MAAM,YAAY,IAAI;AACtC,aAAS,KAAK,GAAG,KAAK,GAAG,MAAM;AAC7B,UAAI,MAAM,EAAE,SAAS;AAAA,IACvB;AAAA,EACF,OAAO;AACL,UAAM,IAAI,MAAM;AAChB,UAAM,OAAO,MAAM,MAAM,CAAC;AAC1B,UAAM,MAAM,KAAK,OAAO,CAAC,KAAK,MAAM,MAAM,CAAC,KAAK,YAAY,IAAI;AAChE,aAAS,KAAK,GAAG,KAAK,GAAG,MAAM;AAC7B,UAAI,MAAM,kBAAkB,SAAS,KAAK,KAAK,MAAM,GAAG,SAAS;AAAA,IACnE;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,cAAc,OAAO,GAAG,YAAY,OAAO;AAClD,MAAI,MAAM,WAAW,GAAG;AACtB,WAAO,EAAE;AAAA,EACX;AACA,QAAMZ,QAAO,MAAM,OAAO,CAAC,KAAK,MAAM,MAAM,CAAC,KAAK,YAAY,IAAI;AAClE,MAAIA,UAAS,GAAG;AACd,WAAO,CAAC;AAAA,EACV;AACA,MAAIA,UAAS,EAAE,QAAQ;AACrB,UAAM,IAAI,MAAM,IAAI,wCAAwC,EAAE,SAAS,YAAY,0BAA0B,KAAK;AAAA,EACpH;AACA,SAAO,kBAAkB,GAAG,OAAO,GAAG,SAAS;AACjD;AACA,SAAS,mBAAmBA,OAAM,OAAO;AACvC,QAAM,SAAS,oBAAoBA,OAAM,KAAK;AAC9C,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,WAAO,MAAM;AAAA,EACf;AACA,SAAO;AACT;AACA,SAAS,oBAAoBA,OAAM,OAAO;AACxC,MAAI,SAAS,QAAQ,UAAU,aAAa,UAAU,aAAa;AACjE,WAAO,IAAI,aAAaA,KAAI;AAAA,EAC9B,WAAW,UAAU,SAAS;AAC5B,WAAO,IAAI,WAAWA,KAAI;AAAA,EAC5B,WAAW,UAAU,QAAQ;AAC3B,WAAO,IAAI,WAAWA,KAAI;AAAA,EAC5B,OAAO;AACL,UAAM,IAAI,MAAM,qBAAqB,OAAO;AAAA,EAC9C;AACF;AACA,SAAS,0BAA0B,OAAO,OAAO;AAC/C,QAAMA,QAAO,MAAM,OAAO,CAAC,MAAM,SAAS,OAAO,MAAM,CAAC;AACxD,MAAI,SAAS,QAAQ,UAAU,WAAW;AACxC,WAAO,cAAc,OAAO,IAAI,aAAaA,KAAI,CAAC;AAAA,EACpD,WAAW,UAAU,SAAS;AAC5B,WAAO,cAAc,OAAO,IAAI,WAAWA,KAAI,CAAC;AAAA,EAClD,WAAW,UAAU,QAAQ;AAC3B,WAAO,cAAc,OAAO,IAAI,WAAWA,KAAI,CAAC;AAAA,EAClD,OAAO;AACL,UAAM,IAAI,MAAM,qBAAqB,OAAO;AAAA,EAC9C;AACF;AACA,SAAS,mCAAmC,OAAO;AACjD,QAAM,QAAQ,CAAC,YAAY;AACzB,WAAO,OAAO,UAAU,OAAO,KAAK,WAAW,GAAG,MAAM,0EAA0E,SAAS;AAAA,EAC7I,CAAC;AACH;AACA,SAAS,WAAW,MAAM,MAAMY,UAAS;AACvC,MAAI,SAAS,GAAG;AACd,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO,KAAK;AAAA,EACd;AACA,MAAIH,SAAQ,KAAK,KAAK,SAAS;AAC/B,WAAS,KAAK,GAAG,KAAK,KAAK,SAAS,GAAG,EAAE,IAAI;AAC3C,IAAAA,UAASG,SAAQ,MAAM,KAAK;AAAA,EAC9B;AACA,SAAOH;AACT;AACA,SAAS,WAAWA,QAAO,MAAMG,UAAS;AACxC,MAAI,SAAS,GAAG;AACd,WAAO,CAAC;AAAA,EACV,WAAW,SAAS,GAAG;AACrB,WAAO,CAACH,MAAK;AAAA,EACf;AACA,QAAM,OAAO,IAAI,MAAM,IAAI;AAC3B,WAAS,KAAK,GAAG,KAAK,KAAK,SAAS,GAAG,EAAE,IAAI;AAC3C,SAAK,MAAM,KAAK,MAAMA,SAAQG,SAAQ,GAAG;AACzC,IAAAH,UAAS,KAAK,MAAMG,SAAQ;AAAA,EAC9B;AACA,OAAK,KAAK,SAAS,KAAKH;AACxB,SAAO;AACT;AACA,SAAS,UAAUE,SAAQ;AACzB,SAAOA,WAAUA,QAAO,QAAQ,OAAOA,QAAO,SAAS;AACzD;AAGA,IAAI,4BAA4B;AAChC,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,SAAS;AACnB,SAAK,SAAS;AACd,SAAK,QAAQ,CAAC;AACd,SAAK,eAAe,CAAC;AACrB,SAAK,WAAW,CAAC;AACjB,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AAAA,EACxB;AAAA,EACA,YAAY,cAAc,UAAU;AAClC,QAAI,KAAK,YAAY,MAAM;AACzB,UAAI,EAAE,IAAI,EAAE,QAAQ,SAAS,KAAK,IAAI,EAAE,QAAQ,MAAM,IAAI;AACxD,gBAAQ,KAAK,YAAY,KAAK,oEAAoE,eAAe;AAAA,MACnH;AAAA,IACF;AACA,SAAK,eAAe;AACpB,SAAK,WAAW;AAAA,EAClB;AAAA,EACA,aAAa,UAAU,cAAc,SAAS;AAC5C,SAAK,aAAa,YAAY,EAAE,cAAc,QAAQ;AACtD,QAAI,KAAK,SAAS,aAAa,MAAM;AACnC,YAAM,YAAY,KAAK,SAAS;AAChC,UAAI,EAAE,IAAI,EAAE,QAAQ,SAAS,KAAK,IAAI,EAAE,QAAQ,MAAM,IAAI;AACxD,gBAAQ,KAAK,qCAAqC,aAAa,YAAY;AAAA,MAC7E;AACA,WAAK,IAAI,UAAU,SAAS;AAAA,IAC9B;AAAA,EACF;AAAA,EACA,MAAM,SAAS,UAAU;AACvB,QAAI,YAAY,KAAK,OAAO;AAC1B,aAAO,KAAK,MAAM;AAAA,IACpB;AACA,SAAK,MAAM,YAAY,MAAM,KAAK,aAAa,QAAQ;AACvD,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,IAAI,UAAU;AACZ,QAAI,YAAY,KAAK,OAAO;AAC1B,aAAO,KAAK,MAAM;AAAA,IACpB;AACA,UAAM,YAAY,KAAK,aAAa,QAAQ;AAC5C,QAAI,UAAU,SAAS,GAAG;AACxB,YAAM,IAAI,MAAM,QAAQ,4EAA4E;AAAA,IACtG;AACA,SAAK,MAAM,YAAY;AACvB,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,UAAU,UAAU;AAClB,WAAO,KAAK,IAAI,QAAQ;AAAA,EAC1B;AAAA,EACA,QAAQ,UAAU;AAChB,WAAO,KAAK,IAAI,QAAQ;AAAA,EAC1B;AAAA,EACA,WAAW;AACT,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,WAAW;AACb,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,UAAU,OAAO;AACnB,QAAI,KAAK,aAAa,aAAa,MAAM;AACvC,YAAM,IAAI,MAAM,mBAAmB,yCAAyC;AAAA,IAC9E;AACA,SAAK,MAAM,YAAY;AACvB,QAAI,KAAK,aAAa,UAAU,WAAW,MAAM;AAC/C,WAAK,aAAa,UAAU,QAAQ,KAAK;AAAA,IAC3C;AAAA,EACF;AAAA,EACA,aAAa,UAAU;AACrB,QAAI,KAAK,aAAa,aAAa,MAAM;AACvC,YAAM,IAAI,MAAM,yBAAyB,0CAA0C;AAAA,IACrF;AACA,WAAO,KAAK,aAAa,UAAU,aAAa;AAAA,EAClD;AAAA,EACA,SAAS,OAAO;AACd,SAAK,QAAQ,OAAO,OAAO,CAAC,GAAG,KAAK;AAAA,EACtC;AAAA,EACA,QAAQ;AACN,SAAK,QAAQ,CAAC;AACd,SAAK,WAAW,CAAC;AACjB,SAAK,iBAAiB;AAAA,EACxB;AAAA,EACA,mBAAmB;AACjB,QAAI,OAAO,KAAK,WAAW,eAAe,OAAO,KAAK,OAAO,aAAa,eAAe,OAAO,KAAK,OAAO,SAAS,WAAW,aAAa;AAC3I;AAAA,IACF;AACA,UAAM,YAAY,KAAK,eAAe,KAAK,OAAO,SAAS,MAAM;AACjE,QAAI,6BAA6B,WAAW;AAC1C,YAAM,YAAY,UAAU,2BAA2B,MAAM,GAAG;AAChE,gBAAU,QAAQ,CAAC,aAAa;AAC9B,cAAM,CAAC,KAAK,KAAK,IAAI,SAAS,MAAM,GAAG;AACvC,aAAK,SAAS,OAAO,WAAW,KAAK,KAAK;AAAA,MAC5C,CAAC;AAAA,IACH;AAAA,EACF;AACF;AACA,SAAS,eAAe,aAAa;AACnC,QAAM,SAAS,CAAC;AAChB,cAAY,QAAQ,+BAA+B,CAAC,OAAO,OAAO;AAChE,gBAAY,QAAQ,GAAG,IAAI,GAAG,EAAE;AAChC,WAAO,GAAG,KAAK,GAAG;AAAA,EACpB,CAAC;AACD,SAAO;AACT;AACA,SAAS,YAAY,QAAQ,MAAM,OAAO;AACxC,SAAO,mBAAmB,IAAI,KAAK,mBAAmB,SAAS,EAAE;AACnE;AACA,SAAS,WAAW,UAAU,OAAO;AACnC,UAAQ,MAAM,YAAY;AAC1B,MAAI,UAAU,UAAU,UAAU,SAAS;AACzC,WAAO,UAAU;AAAA,EACnB,WAAW,GAAG,CAAC,YAAY,OAAO;AAChC,WAAO,CAAC;AAAA,EACV;AACA,QAAM,IAAI,MAAM,oCAAoC,kBAAkB,WAAW;AACnF;AACA,SAAS,MAAM;AACb,SAAO;AACT;AACA,IAAI,MAAM;AACV,SAAS,qBAAqB,aAAa;AACzC,QAAM;AACR;AAGA,IAAI;AACJ,SAAS,qBAAqB;AAC5B,MAAI,mBAAmB,MAAM;AAC3B,QAAI;AACJ,QAAI,OAAO,WAAW,aAAa;AACjC,WAAK;AAAA,IACP,WAAW,OAAO,WAAW,aAAa;AACxC,WAAK;AAAA,IACP,WAAW,OAAO,YAAY,aAAa;AACzC,WAAK;AAAA,IACP,WAAW,OAAO,SAAS,aAAa;AACtC,WAAK;AAAA,IACP,OAAO;AACL,YAAM,IAAI,MAAM,gCAAgC;AAAA,IAClD;AACA,sBAAkB;AAAA,EACpB;AACA,SAAO;AACT;AACA,SAAS,eAAe;AACtB,QAAM,KAAK,mBAAmB;AAC9B,MAAI,GAAG,cAAc,MAAM;AACzB,OAAG,aAA6B,oBAAI,IAAI;AAAA,EAC1C;AACA,SAAO,GAAG;AACZ;AACA,SAAS,UAAU,KAAKP,QAAO;AAC7B,QAAM,YAAY,aAAa;AAC/B,MAAI,UAAU,IAAI,GAAG,GAAG;AACtB,WAAO,UAAU,IAAI,GAAG;AAAA,EAC1B,OAAO;AACL,UAAM,YAAYA,OAAM;AACxB,cAAU,IAAI,KAAK,SAAS;AAC5B,WAAO,UAAU,IAAI,GAAG;AAAA,EAC1B;AACF;AAGA,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,QAAQ;AACZ,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,MAAM;AACV,IAAI,MAAM;AACV,IAAI,SAAS;AACb,IAAI,SAAS;AACb,IAAI,OAAO;AACX,IAAI,QAAQ;AACZ,IAAI,OAAO;AACX,IAAI,QAAQ;AACZ,IAAI,QAAQ;AACZ,IAAI,UAAU;AACd,IAAI,cAAc;AAClB,IAAI,YAAY;AAChB,IAAI,gBAAgB;AACpB,IAAI,cAAc;AAClB,IAAI,iBAAiB;AACrB,IAAI,WAAW;AACf,IAAI,cAAc;AAClB,IAAI,gBAAgB;AACpB,IAAI,OAAO;AACX,IAAI,OAAO;AACX,IAAI,cAAc;AAClB,IAAI,UAAU;AACd,IAAI,aAAa;AACjB,IAAI,SAAS;AACb,IAAI,SAAS;AACb,IAAI,uBAAuB;AAC3B,IAAI,sBAAsB;AAC1B,IAAI,SAAS;AACb,IAAI,yBAAyB;AAC7B,IAAI,wBAAwB;AAC5B,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,UAAU;AACd,IAAI,SAAS;AACb,IAAI,gBAAgB;AACpB,IAAI,gBAAgB;AACpB,IAAI,eAAe;AACnB,IAAI,wBAAwB;AAC5B,IAAI,sCAAsC;AAC1C,IAAI,qCAAqC;AACzC,IAAI,OAAO;AACX,IAAI,aAAa;AACjB,IAAI,0BAA0B;AAC9B,IAAI,2BAA2B;AAC/B,IAAI,UAAU;AACd,IAAI,SAAS;AACb,IAAI,MAAM;AACV,IAAI,UAAU;AACd,IAAI,MAAM;AACV,IAAI,QAAQ;AACZ,IAAI,MAAM;AACV,IAAI,aAAa;AACjB,IAAI,QAAQ;AACZ,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,gBAAgB;AACpB,IAAI,QAAQ;AACZ,IAAI,WAAW;AACf,IAAI,iBAAiB;AACrB,IAAI,WAAW;AACf,IAAI,WAAW;AACf,IAAI,UAAU;AACd,IAAI,eAAe;AACnB,IAAI,WAAW;AACf,IAAI,OAAO;AACX,IAAI,OAAO;AACX,IAAI,WAAW;AACf,IAAI,QAAQ;AACZ,IAAI,QAAQ;AACZ,IAAI,YAAY;AAChB,IAAI,OAAO;AACX,IAAI,YAAY;AAChB,IAAI,WAAW;AACf,IAAI,MAAM;AACV,IAAI,QAAQ;AACZ,IAAI,aAAa;AACjB,IAAI,aAAa;AACjB,IAAI,YAAY;AAChB,IAAI,aAAa;AACjB,IAAI,aAAa;AACjB,IAAI,aAAa;AACjB,IAAI,MAAM;AACV,IAAI,UAAU;AACd,IAAI,MAAM;AACV,IAAI,UAAU;AACd,IAAI,UAAU;AACd,IAAI,cAAc;AAClB,IAAI,YAAY;AAChB,IAAI,gBAAgB;AACpB,IAAI,oBAAoB;AACxB,IAAI,OAAO;AACX,IAAI,MAAM;AACV,IAAI,UAAU;AACd,IAAI,YAAY;AAChB,IAAI,MAAM;AACV,IAAI,cAAc;AAClB,IAAI,WAAW;AACf,IAAI,MAAM;AACV,IAAI,WAAW;AACf,IAAI,sBAAsB;AAC1B,IAAI,sBAAsB;AAC1B,IAAI,sBAAsB;AAC1B,IAAI,WAAW;AACf,IAAI,SAAS;AACb,IAAI,OAAO;AACX,IAAI,QAAQ;AACZ,IAAI,OAAO;AACX,IAAI,MAAM;AACV,IAAI,QAAQ;AACZ,IAAI,OAAO;AACX,IAAI,QAAQ;AACZ,IAAI,OAAO;AACX,IAAI,aAAa;AACjB,IAAI,OAAO;AACX,IAAI,UAAU;AACd,IAAI,wBAAwB;AAC5B,IAAI,4BAA4B;AAChC,IAAI,iBAAiB;AACrB,IAAI,qBAAqB;AACzB,IAAI,QAAQ;AACZ,IAAI,UAAU;AACd,IAAI,QAAQ;AACZ,IAAI,QAAQ;AACZ,IAAI,YAAY;AAChB,IAAI,eAAe;AACnB,IAAI,SAAS;AACb,IAAI,OAAO;AACX,IAAI,QAAQ;AACZ,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,OAAO;AACX,IAAI,UAAU;AACd,IAAI,WAAW;AACf,IAAI,OAAO;AACX,IAAI,MAAM;AACV,IAAI,iBAAiB;AACrB,IAAI,SAAS;AACb,IAAI,UAAU;AACd,IAAI,sBAAsB;AAC1B,IAAI,gBAAgB;AACpB,IAAI,oBAAoB;AACxB,IAAI,mBAAmB;AACvB,IAAI,gBAAgB;AACpB,IAAI,oBAAoB;AACxB,IAAI,SAAS;AACb,IAAI,eAAe;AACnB,IAAI,eAAe;AACnB,IAAI,cAAc;AAClB,IAAI,yBAAyB;AAC7B,IAAI,MAAM;AACV,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,OAAO;AACX,IAAI,OAAO;AACX,IAAI,YAAY;AAChB,IAAI,YAAY;AAChB,IAAI,SAAS;AACb,IAAI,SAAS;AACb,IAAI,qBAAqB;AACzB,IAAI,aAAa;AACjB,IAAI,YAAY;AAChB,IAAI,OAAO;AACX,IAAI,aAAa;AACjB,IAAI,mBAAmB;AACvB,IAAI,eAAe;AACnB,IAAI,cAAc;AAClB,IAAI,uBAAuB;AAG3B,SAAS,QAAQ,KAAK;AACpB,MAAI,EAAE,IAAI,EAAE,QAAQ,SAAS,KAAK,IAAI,EAAE,QAAQ,MAAM,IAAI;AACxD,YAAQ,KAAK,GAAG,GAAG;AAAA,EACrB;AACF;AACA,SAASS,QAAO,KAAK;AACnB,MAAI,EAAE,IAAI,EAAE,QAAQ,SAAS,KAAK,IAAI,EAAE,QAAQ,MAAM,IAAI;AACxD,YAAQ,IAAI,GAAG,GAAG;AAAA,EACpB;AACF;AAGA,IAAI,iBAAiB,UAAU,kBAAkB,MAAsB,oBAAI,IAAI,CAAC;AAChF,IAAI,eAAe,UAAU,gBAAgB,MAAsB,oBAAI,IAAI,CAAC;AAC5E,SAAS,UAAU,YAAY,aAAa;AAC1C,QAAM,MAAM,QAAQ,YAAY,WAAW;AAC3C,SAAO,eAAe,IAAI,GAAG;AAC/B;AACA,SAAS,YAAY,YAAY;AAC/B,SAAO,aAAa,IAAI,UAAU;AACpC;AACA,SAAS,qBAAqB,aAAa;AACzC,QAAM,KAAK,eAAe,QAAQ;AAClC,QAAM,SAAS,CAAC;AAChB,SAAO,MAAM;AACX,UAAM,EAAE,MAAM,MAAM,IAAI,GAAG,KAAK;AAChC,QAAI,MAAM;AACR;AAAA,IACF;AACA,UAAM,CAAC,KAAKC,OAAM,IAAI;AACtB,UAAM,CAAC,QAAQ,IAAI,IAAI,MAAM,GAAG;AAChC,QAAI,aAAa,aAAa;AAC5B,aAAO,KAAKA,OAAM;AAAA,IACpB;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,eAAeA,SAAQ;AAC9B,QAAM,EAAE,YAAY,YAAY,IAAIA;AACpC,QAAM,MAAM,QAAQ,YAAY,WAAW;AAC3C,MAAI,eAAe,IAAI,GAAG,GAAG;AAC3B,SAAK,eAAe,4BAA4B,oCAAoC;AAAA,EACtF;AACA,iBAAe,IAAI,KAAKA,OAAM;AAChC;AACA,SAAS,iBAAiBA,SAAQ;AAChC,QAAM,EAAE,WAAW,IAAIA;AACvB,MAAI,aAAa,IAAI,UAAU,GAAG;AAChC,QAAI,IAAI,EAAE,QAAQ,OAAO,GAAG;AAC1B,WAAK,gCAAgC,aAAa;AAAA,IACpD;AAAA,EACF;AACA,eAAa,IAAI,YAAYA,OAAM;AACrC;AACA,SAAS,iBAAiB,YAAY,aAAa;AACjD,QAAM,MAAM,QAAQ,YAAY,WAAW;AAC3C,MAAI,CAAC,eAAe,IAAI,GAAG,GAAG;AAC5B,UAAM,IAAI,MAAM,eAAe,4BAA4B,gCAAgC;AAAA,EAC7F;AACA,iBAAe,OAAO,GAAG;AAC3B;AACA,SAAS,mBAAmB,YAAY;AACtC,MAAI,CAAC,aAAa,IAAI,UAAU,GAAG;AACjC,UAAM,IAAI,MAAM,iBAAiB,2CAA2C;AAAA,EAC9E;AACA,eAAa,OAAO,UAAU;AAChC;AACA,SAAS,sBAAsB,uBAAuB,gBAAgB;AACpE,QAAM,UAAU,qBAAqB,qBAAqB;AAC1D,UAAQ,QAAQ,CAAC,iBAAiB;AAChC,UAAM,kBAAkB,OAAO,OAAO,CAAC,GAAG,cAAc,EAAE,aAAa,eAAe,CAAC;AACvF,mBAAe,eAAe;AAAA,EAChC,CAAC;AACH;AACA,SAAS,QAAQ,YAAY,aAAa;AACxC,SAAO,GAAG,eAAe;AAC3B;AAGA,IAAI,eAAe,CAAC;AACpBjB,UAAS,cAAc;AAAA,EACrB,aAAa,MAAM;AAAA,EACnB,QAAQ,MAAM;AAAA,EACd,oCAAoC,MAAM;AAAA,EAC1C,eAAe,MAAM;AAAA,EACrB,mBAAmB,MAAM;AAAA,EACzB,sBAAsB,MAAM;AAAA,EAC5B,iBAAiB,MAAM;AAAA,EACvB,0BAA0B,MAAM;AAAA,EAChC,OAAO,MAAM;AAAA,EACb,gBAAgB,MAAM;AAAA,EACtB,mBAAmB,MAAM;AAAA,EACzB,uBAAuB,MAAM;AAAA,EAC7B,cAAc,MAAM;AAAA,EACpB,aAAa,MAAM;AAAA,EACnB,cAAc,MAAM;AAAA,EACpB,OAAO,MAAM;AAAA,EACb,eAAe,MAAM;AAAA,EACrB,SAAS,MAAM;AAAA,EACf,mBAAmB,MAAM;AAAA,EACzB,wBAAwB,MAAM;AAAA,EAC9B,iBAAiB,MAAM;AAAA,EACvB,WAAW,MAAM;AAAA,EACjB,YAAY,MAAM;AAAA,EAClB,YAAY,MAAM;AAAA,EAClB,wBAAwB,MAAM;AAAA,EAC9B,WAAW,MAAM;AAAA,EACjB,YAAY,MAAM;AAAA,EAClB,OAAO,MAAM;AAAA,EACb,UAAU,MAAM;AAAA,EAChB,WAAW,MAAM;AAAA,EACjB,eAAe,MAAM;AAAA,EACrB,UAAU,MAAM;AAAA,EAChB,cAAc,MAAM;AAAA,EACpB,cAAc,MAAM;AAAA,EACpB,YAAY,MAAM;AAAA,EAClB,oBAAoB,MAAM;AAAA,EAC1B,2BAA2B,MAAM;AAAA,EACjC,qBAAqB,MAAM;AAAA,EAC3B,gBAAgB,MAAM;AAAA,EACtB,mBAAmB,MAAM;AAAA,EACzB,KAAK,MAAMkB;AAAA,EACX,gBAAgB,MAAM;AAAA,EACtB,aAAa,MAAM;AAAA,EACnB,aAAa,MAAM;AAAA,EACnB,UAAU,MAAM;AAAA,EAChB,SAAS,MAAM;AAAA,EACf,cAAc,MAAM;AAAA,EACpB,eAAe,MAAM;AAAA,EACrB,qBAAqB,MAAM;AAAA,EAC3B,cAAc,MAAM;AAAA,EACpB,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,MAAM,MAAM;AAAA,EACZ,eAAe,MAAM;AAAA,EACrB,cAAc,MAAM;AACtB,CAAC;AAGD,IAAI,cAAc,QAAQ,aAAa,CAAC;AACxC,IAAI,OAAO,YAAY,WAAW;AAClC,SAAS,UAAU,KAAK;AACtB,SAAO,KAAK,WAAW,KAAK,MAAM,EAAE;AACtC;AACA,IAAI,KAAK,UAAU,kBAAkB;AACrC,IAAI,KAAK,UAAU,kBAAkB;AACrC,IAAI,KAAK,UAAU,kBAAkB;AACrC,SAAS,SAAS,KAAK;AACrB,SAAO,IAAI,IAAI,IAAI,KAAK,EAAE,CAAC;AAC7B;AACA,SAAS,OAAO,IAAI,QAAQ,UAAU;AACpC,QAAM,QAAQ,GAAG,MAAM,QAAQ,SAAS,QAAQ;AAChD,SAAO,KAAK,UAAU,MAAM,KAAK,KAAK,GAAG,MAAM,IAAI;AACrD;AACA,SAAS,QAAQ,IAAI,QAAQ;AAC3B,SAAO,OAAO,IAAI,QAAQ,CAAC;AAC7B;AACA,SAAS,QAAQ,IAAI,QAAQ;AAC3B,SAAO,OAAO,IAAI,QAAQ,CAAC;AAC7B;AACA,SAAS,SAAS,KAAK,OAAO;AAC5B,SAAO,UAAU,IAAI,MAAM,IAAI,KAAK,KAAK,EAAE,GAAG,IAAI,IAAI,KAAK,KAAK,CAAC;AACnE;AACA,SAAS,UAAU,GAAG,GAAG,OAAO,UAAU,kBAAkB,GAAG;AAC7D,MAAI,IAAI,EAAE,IAAI,CAAC,EAAE,IAAI,IAAI;AACzB,MAAI,EAAE,IAAI,EAAE,KAAK,EAAE,CAAC;AACpB,MAAI,IAAI,EAAE,IAAI,CAAC,EAAE,IAAI,IAAI;AACzB,MAAI,EAAE,IAAI,EAAE,KAAK,EAAE,CAAC;AACpB,MAAI,EAAE,IAAI,IAAI;AACd,SAAO;AACT;AACA,SAAS,uBAAuB,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG;AAChD,MAAI,EAAE,IAAI,CAAC;AACX,MAAI,SAAS,EAAE,IAAI,CAAC,EAAE,IAAI,CAAC,GAAG,EAAE;AAChC,QAAM,IAAI;AACV,MAAI,EAAE,IAAI,CAAC;AACX,MAAI,EAAE,IAAI,CAAC;AACX,MAAI,EAAE,IAAI,SAAS,GAAG,EAAE,CAAC;AACzB,SAAO,CAAC,EAAE,IAAI,CAAC,GAAG,EAAE,IAAI,CAAC,CAAC;AAC5B;AACA,SAAS,0BAA0B,IAAI,QAAQ,GAAG,GAAG;AACnD,SAAO,uBAAuB,QAAQ,IAAI,MAAM,GAAG,QAAQ,IAAI,SAAS,CAAC,GAAG,QAAQ,IAAI,SAAS,EAAE,GAAG,QAAQ,IAAI,SAAS,EAAE,GAAG,GAAG,CAAC;AACtI;AACA,SAAS,aAAa,IAAI,MAAM,GAAG,QAAQ;AACzC,MAAI,OAAO,GAAG;AACZ,UAAM,OAAO,GAAG,IAAI,MAAM,CAAC;AAC3B,UAAM,IAAI,QAAQ,IAAI,CAAC,EAAE,IAAI,EAAE;AAC/B,UAAM,IAAI,QAAQ,IAAI,MAAM,CAAC;AAC7B,UAAM,IAAI,SAAS,GAAG,EAAE,EAAE,IAAI,IAAI,EAAE,IAAI,CAAC;AACzC,UAAM,IAAI,SAAS,GAAG,EAAE,EAAE,IAAI,CAAC,EAAE,IAAI,IAAI;AACzC,WAAO,UAAU,GAAG,GAAG,IAAI;AAAA,EAC7B;AACA,MAAI,OAAO,GAAG;AACZ,UAAM,OAAO,GAAG,IAAI,MAAM,CAAC;AAC3B,UAAM,IAAI,QAAQ,IAAI,CAAC;AACvB,WAAO,UAAU,EAAE,IAAI,CAAC,EAAE,IAAI,GAAG,GAAG,QAAQ,IAAI,MAAM,CAAC,GAAG,IAAI;AAAA,EAChE;AACA,MAAI,MAAM,GAAG;AACX,UAAM,IAAI,GAAG;AACb,UAAM,IAAI,GAAG,OAAO;AACpB,UAAM,IAAI,GAAG,MAAM;AACnB,UAAM,IAAI,KAAK,KAAK;AACpB,UAAM,IAAI,OAAO,KAAK;AACtB,WAAO,SAAS,GAAG,IAAI,CAAC,EAAE,IAAI,GAAG,IAAI,CAAC,CAAC,CAAC,EAAE,IAAI,EAAE;AAAA,EAClD;AACA,SAAO;AACT;AACA,SAAS,cAAc,IAAI,MAAM,GAAG,QAAQ;AAC1C,QAAM,OAAO,GAAG,IAAI,MAAM,CAAC;AAC3B,QAAM,IAAI,QAAQ,IAAI,CAAC,EAAE,IAAI,EAAE;AAC/B,QAAM,IAAI,QAAQ,IAAI,CAAC;AACvB,QAAM,IAAI,QAAQ,IAAI,MAAM,CAAC,EAAE,IAAI,IAAI;AACvC,QAAM,IAAI,QAAQ,IAAI,MAAM,EAAE,EAAE,IAAI,EAAE;AACtC,SAAO,UAAU,SAAS,EAAE,IAAI,CAAC,GAAG,EAAE,EAAE,IAAI,SAAS,GAAG,EAAE,CAAC,EAAE,IAAI,CAAC,GAAG,EAAE,IAAI,SAAS,EAAE,IAAI,EAAE,GAAG,EAAE,CAAC,EAAE,IAAI,CAAC,GAAG,IAAI;AAClH;AACA,SAAS,cAAc,IAAI,MAAM,GAAG,QAAQ;AAC1C,QAAM,OAAO,GAAG,IAAI,MAAM,CAAC;AAC3B,QAAM,IAAI,QAAQ,IAAI,CAAC,EAAE,IAAI,EAAE;AAC/B,QAAM,IAAI,QAAQ,IAAI,CAAC;AACvB,QAAM,IAAI,QAAQ,IAAI,MAAM,CAAC,EAAE,IAAI,IAAI;AACvC,QAAM,IAAI,QAAQ,IAAI,MAAM,EAAE,EAAE,IAAI,EAAE;AACtC,QAAM,IAAI,SAAS,EAAE,IAAI,CAAC,GAAG,EAAE,EAAE,IAAI,SAAS,GAAG,EAAE,CAAC,EAAE,IAAI,CAAC;AAC3D,QAAM,IAAI,UAAU,GAAG,EAAE,IAAI,SAAS,EAAE,IAAI,EAAE,GAAG,EAAE,CAAC,EAAE,IAAI,CAAC,GAAG,IAAI;AAClE,QAAM,KAAK,QAAQ,IAAI,EAAE,EAAE,IAAI,IAAI;AACnC,QAAM,IAAI,QAAQ,IAAI,EAAE;AACxB,QAAM,IAAI,EAAE,IAAI,QAAQ,IAAI,MAAM,EAAE,CAAC,EAAE,IAAI,IAAI;AAC/C,QAAM,IAAI,EAAE,IAAI,QAAQ,IAAI,MAAM,EAAE,CAAC,EAAE,IAAI,IAAI;AAC/C,SAAO,UAAU,SAAS,GAAG,IAAI,CAAC,GAAG,EAAE,EAAE,IAAI,SAAS,GAAG,EAAE,CAAC,EAAE,IAAI,CAAC,GAAG,GAAG,IAAI,SAAS,EAAE,IAAI,CAAC,GAAG,EAAE,CAAC,EAAE,IAAI,CAAC,GAAG,IAAI;AACnH;AACA,SAAS,cAAc,IAAI,MAAM,GAAG,QAAQ;AAC1C,QAAM,OAAO,KAAK,WAAW,IAAI,IAAI;AACrC,MAAI,OAAO,IAAI;AACb,QAAI,OAAO,IAAI;AACb,aAAO,aAAa,IAAI,GAAG;AAAA,IAC7B,OAAO;AACL,aAAO,cAAc,IAAI,GAAG;AAAA,IAC9B;AAAA,EACF,WAAW,OAAO,IAAI;AACpB,WAAO,cAAc,IAAI,GAAG;AAAA,EAC9B;AACA,MAAI,IAAI;AACR,MAAI,IAAI,KAAK,IAAI,EAAE,EAAE,IAAI,GAAG;AAC5B,MAAI,IAAI,SAAS,EAAE,IAAI,EAAE,EAAE,IAAI,GAAG,CAAC,EAAE,IAAI,EAAE;AAC3C,MAAI,IAAI,CAAC,KAAK,OAAO,KAAK,KAAK;AAC/B,MAAI,IAAI,CAAC,KAAK,OAAO,KAAK,KAAK;AAC/B,MAAI,EAAE,IAAI,EAAE,EAAE,IAAI,QAAQ,IAAI,CAAC,CAAC;AAChC,MAAI,SAAS;AACb,QAAM,OAAO,MAAM,KAAK,KAAK;AAC7B,QAAM,SAAS,OAAO,MAAM,IAAI,MAAM;AACtC,KAAG;AACD,QAAI,SAAS,EAAE,IAAI,CAAC,EAAE,IAAI,EAAE,EAAE,EAAE,IAAI,QAAQ,IAAI,SAAS,CAAC,CAAC,GAAG,EAAE,EAAE,IAAI,EAAE;AACxE,QAAI,SAAS,EAAE,IAAI,EAAE,EAAE,EAAE,IAAI,QAAQ,IAAI,SAAS,EAAE,CAAC,GAAG,EAAE,EAAE,IAAI,EAAE;AAClE,QAAI,EAAE,IAAI,EAAE,EAAE;AACd,QAAI,EAAE,IAAI,EAAE,EAAE,EAAE,IAAI,QAAQ,IAAI,SAAS,EAAE,CAAC;AAC5C,QAAI,SAAS,EAAE,IAAI,EAAE,EAAE,GAAG,EAAE,EAAE,IAAI,EAAE;AACpC,QAAI,0BAA0B,IAAI,QAAQ,EAAE,GAAG,IAAI,EAAE,GAAG,EAAE,IAAI,EAAE,EAAE,CAAC;AACnE,QAAI,0BAA0B,IAAI,SAAS,IAAI,EAAE,IAAI,EAAE,EAAE,GAAG,EAAE,IAAI,QAAQ,IAAI,SAAS,EAAE,CAAC,CAAC;AAC3F,KAAC,GAAG,CAAC,IAAI,CAAC,GAAG,CAAC;AACd,cAAU;AAAA,EACZ,SAAS,WAAW;AACpB,QAAM,OAAO,GAAG,IAAI,EAAE,IAAI,GAAG,EAAE,IAAI,CAAC,CAAC;AACrC,WAAS;AACT,IAAE,KAAK,EAAE,GAAG,IAAI,MAAM,IAAI,EAAE;AAC5B,IAAE,KAAK,EAAE,GAAG,IAAI,EAAE,EAAE;AACpB,IAAE,KAAK,EAAE,GAAG,IAAI,EAAE,EAAE;AACpB,MAAI,SAAS,EAAE,IAAI,CAAC,EAAE,IAAI,EAAE,EAAE,EAAE,IAAI,QAAQ,IAAI,SAAS,CAAC,CAAC,GAAG,EAAE,EAAE,IAAI,IAAI;AAC1E,MAAI,SAAS,EAAE,IAAI,EAAE,EAAE,EAAE,IAAI,QAAQ,IAAI,SAAS,EAAE,CAAC,GAAG,EAAE,EAAE,IAAI,IAAI;AACpE,MAAI,EAAE,IAAI,EAAE,GAAG,IAAI,CAAC,CAAC;AACrB,MAAI,EAAE,IAAI,EAAE,GAAG,IAAI,CAAC,EAAE,IAAI,QAAQ,IAAI,SAAS,EAAE,CAAC,CAAC;AACnD,MAAI,SAAS,EAAE,IAAI,EAAE,EAAE,GAAG,EAAE,EAAE,IAAI,IAAI;AACtC,MAAI,0BAA0B,IAAI,QAAQ,EAAE,GAAG,IAAI,IAAI,GAAG,EAAE,IAAI,EAAE,EAAE,CAAC;AACrE,MAAI,0BAA0B,IAAI,SAAS,IAAI,EAAE,IAAI,EAAE,EAAE,GAAG,EAAE,IAAI,QAAQ,IAAI,SAAS,EAAE,CAAC,CAAC;AAC3F,GAAC,GAAG,CAAC,IAAI,CAAC,GAAG,CAAC;AACd,SAAO,UAAU,UAAU,EAAE,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,SAAS,CAAC,EAAE,IAAI,EAAE,CAAC,EAAE,IAAI,CAAC,GAAG,UAAU,EAAE,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,CAAC,GAAG,IAAI;AACxH;AAGA,SAAS,kBAAkB,OAAO,OAAO;AACvC,MAAI,UAAU,UAAU;AACtB,WAAO,aAAa,KAAK;AAAA,EAC3B;AACA,SAAO,aAAa,CAAC,KAAK,GAAG,KAAK;AACpC;AACA,SAAS,mBAAmB,GAAG,OAAO;AACpC,SAAO,aAAa,gBAAgB,UAAU,aAAa,aAAa,cAAc,UAAU,WAAW,aAAa,cAAc,UAAU;AAClJ;AACA,SAAS,aAAa,GAAG,OAAO;AAC9B,MAAI,UAAU,UAAU;AACtB,UAAM,IAAI,MAAM,2CAA2C;AAAA,EAC7D;AACA,MAAI,MAAM,QAAQ,CAAC,GAAG;AACpB,QAAI,QAAQ,CAAC;AAAA,EACf;AACA,MAAI,IAAI,EAAE,QAAQ,OAAO,GAAG;AAC1B,6BAAyB,GAAG,KAAK;AAAA,EACnC;AACA,MAAI,mBAAmB,GAAG,KAAK,GAAG;AAChC,WAAO;AAAA,EACT;AACA,MAAI,SAAS,QAAQ,UAAU,aAAa,UAAU,aAAa;AACjE,WAAO,IAAI,aAAa,CAAC;AAAA,EAC3B,WAAW,UAAU,SAAS;AAC5B,WAAO,IAAI,WAAW,CAAC;AAAA,EACzB,WAAW,UAAU,QAAQ;AAC3B,UAAM,OAAO,IAAI,WAAW,EAAE,MAAM;AACpC,aAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAI,KAAK,MAAM,EAAE,GAAG,MAAM,GAAG;AAC3B,aAAK,MAAM;AAAA,MACb;AAAA,IACF;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,qBAAqB,OAAO;AAAA,EAC9C;AACF;AACA,SAASA,OAAM;AACb,SAAO,IAAI,EAAE,SAAS,IAAI;AAC5B;AACA,SAAS,OAAO,MAAM,cAAc;AAClC,SAAO,IAAI,EAAE,SAAS,MAAM,MAAM,YAAY;AAChD;AACA,SAAS,aAAa,IAAI,WAAW,SAAS;AAC5C,aAAW,YAAY;AACvB,SAAO,IAAI,EAAE,SAAS,OAAO,IAAI,QAAQ;AAC3C;AACA,SAAS,aAAa,OAAO,WAAW,SAAS;AAC/C,aAAW,YAAY;AACvB,SAAO,IAAI,EAAE,SAAS,OAAO,OAAO,QAAQ;AAC9C;AAGA,IAAI,WAAW,MAAM;AAAA,EACnB,YAAY,cAAc,QAAQ;AAChC,SAAK,eAAe;AACpB,SAAK,SAAS;AACd,QAAI,UAAU,MAAM;AAClB,WAAK,SAAS,IAAI,OAAO;AAAA,IAC3B;AAAA,EACF;AAAA,EACA,cAAc,YAAY,QAAQ,GAAG;AACnC,QAAI;AACJ,UAAM,sBAAsB,MAAM;AAChC,gBAAU,EAAE;AAAA,IACd;AACA,QAAI;AACJ,UAAM,QAAQA,KAAI;AAClB,QAAI,KAAK,aAAa,eAAe,GAAG;AACtC,cAAQ,KAAK,aAAa,KAAK,mBAAmB;AAAA,IACpD,OAAO;AACL,0BAAoB;AACpB,iBAAW,UAAU,SAAS;AAC5B,eAAO,SAAS;AAAA,MAClB;AACA,cAAQ,QAAQ,QAAQ,EAAE,UAAUA,KAAI,IAAI,MAAM,CAAC;AAAA,IACrD;AACA,QAAI,IAAI,EAAE,QAAQ,8BAA8B,GAAG;AACjD,eAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,cAAM,SAAS,QAAQ;AACvB,eAAO,KAAK,EAAE,KAAK,CAAC,eAAe;AACjC,oCAA0B,YAAY,OAAO,OAAO,UAAU;AAAA,QAChE,CAAC;AAAA,MACH;AAAA,IACF;AACA,UAAM,gBAAgB;AAAA,MACpB;AAAA,MACA;AAAA,MACA;AAAA,MACA,QAAQ,MAAM,KAAK,CAAC,WAAW,OAAO,QAAQ;AAAA,MAC9C,WAAW,MAAM,KAAK,CAAC,WAAW,OAAO,uBAAuB,OAAO,OAAO,oBAAoB,IAAI,EAAE;AAAA,IAC1G;AACA,WAAO;AAAA,EACT;AAAA,EACA,iBAAiB,eAAe;AAC9B,UAAM,EAAE,YAAY,SAAS,QAAQ,QAAQ,UAAU,IAAI;AAC3D,YAAQ,QAAQ,CAAC,WAAW;AAC1B,cAAQ,IAAI,CAAC,OAAO,KAAK,GAAG,QAAQ,SAAS,CAAC,EAAE,KAAK,CAAC,mBAAmB;AACvE,aAAK,OAAO,iBAAiB,YAAY,QAAQ,eAAe,IAAI,eAAe,IAAI,QAAQ,eAAe,EAAE;AAAA,MAClH,CAAC;AAAA,IACH,CAAC;AAAA,EACH;AACF;AACA,SAAS,0BAA0B,MAAM,OAAO,YAAY;AAC1D,MAAI,UAAU,WAAW;AACvB,WAAO;AAAA,EACT;AACA,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,UAAM,MAAM,KAAK;AACjB,QAAI,MAAM,GAAG,KAAK,CAAC,SAAS,GAAG,GAAG;AAChC,cAAQ,KAAK,SAAS,yBAAyB,aAAa;AAC5D,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO;AACT;AACA,IAAI,SAAS,MAAM;AAAA,EACjB,iBAAiB,MAAM,QAAQ,MAAM,QAAQ,QAAQ,WAAW;AAC9D,UAAM,QAAQ,OAAO,WAAW,WAAW,SAAS,GAAG,YAAY,CAAC,IAAI,OAAO;AAC/E,UAAM,aAAa,SAAS,MAAM,EAAE;AACpC,UAAM,OAAO,OAAO;AACpB,UAAMf,QAAO,OAAO;AACpB,UAAM,QAAQ,SAAS,OAAO,MAAM,SAAS,GAAG,EAAE;AAClD,QAAI,yBAAyB;AAC7B,eAAW,SAAS,QAAQ;AAC1B,YAAM,SAAS,OAAO;AACtB,UAAI,UAAU,MAAM;AAClB,cAAM,aAAa,OAAO,SAAS,OAAO;AAC1C,cAAM,YAAY,WAAW;AAC7B,kCAA0B,GAAG,UAAU,cAAc,YAAY,IAAI,aAAa;AAAA,MACpF;AAAA,IACF;AACA,YAAQ,IAAI,KAAK,gBAAgB,WAAW,SAAS,WAAWA,WAAU,4BAA4B,aAAa,oBAAoB,aAAa,cAAc,iBAAiB,gBAAgB,kBAAkB;AAAA,EACvN;AACF;AAGA,SAAS,qBAAqB,MAAM,IAAI,GAAG;AACzC,QAAM,eAAe,CAAC;AACtB,QAAM,aAAa,CAAC;AACpB,WAAS,KAAK,GAAG,KAAK,GAAG,QAAQ,MAAM;AACrC,iBAAa,GAAG,IAAI,MAAM;AAAA,EAC5B;AACA,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,UAAMgB,QAAO,KAAK;AAClB,UAAM,aAAaA,MAAK;AACxB,eAAW,aAAa,YAAY;AAClC,YAAM,SAAS,WAAW;AAC1B,UAAI,gBAAgB;AACpB,eAAS,IAAI,GAAG,IAAI,GAAG,QAAQ,KAAK;AAClC,YAAI,aAAa,OAAO,KAAK;AAC3B,UAAAA,MAAK,QAAQ,QAAQ,CAAC,WAAW,aAAa,OAAO,MAAM,IAAI;AAC/D,0BAAgB;AAChB,qBAAWA,MAAK,MAAM;AACtB;AAAA,QACF;AAAA,MACF;AACA,UAAI,eAAe;AACjB;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,QAAM,iBAAiB,CAAC;AACxB,iBAAe,EAAE,MAAM;AACvB,QAAM,WAAW,CAAC;AAClB,WAAS,KAAK,KAAK,SAAS,GAAG,MAAM,GAAG,MAAM;AAC5C,UAAMA,QAAO,KAAK;AAClB,UAAM,aAAaA,MAAK;AACxB,aAAS,IAAI,GAAG,IAAIA,MAAK,QAAQ,QAAQ,KAAK;AAC5C,UAAI,eAAeA,MAAK,QAAQ,GAAG,KAAK;AACtC,mBAAW,aAAa,YAAY;AAClC,yBAAe,WAAW,WAAW,MAAM;AAC3C,mBAASA,MAAK,MAAM;AAAA,QACtB;AACA;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,QAAM,eAAe,CAAC;AACtB,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,UAAMA,QAAO,KAAK;AAClB,QAAI,WAAWA,MAAK,OAAO,SAASA,MAAK,KAAK;AAC5C,YAAM,eAAe,CAAC;AACtB,iBAAW,aAAaA,MAAK,QAAQ;AACnC,cAAM,YAAYA,MAAK,OAAO;AAC9B,YAAI,aAAa,UAAU,KAAK;AAC9B,uBAAa,aAAa;AAAA,QAC5B;AAAA,MACF;AACA,YAAM,aAAa,OAAO,OAAO,CAAC,GAAGA,KAAI;AACzC,iBAAW,SAAS;AACpB,iBAAW,UAAUA,MAAK;AAC1B,mBAAa,KAAK,UAAU;AAAA,IAC9B;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,uBAAuB,8BAA8B,cAAc,OAAO,MAAM;AACvF,WAAS,KAAK,aAAa,SAAS,GAAG,MAAM,GAAG,MAAM;AACpD,UAAMA,QAAO,aAAa;AAC1B,UAAM,MAAM,CAAC;AACb,IAAAA,MAAK,QAAQ,QAAQ,CAAC,MAAM;AAC1B,YAAM,aAAa,6BAA6B,EAAE;AAClD,UAAI,cAAc,MAAM;AACtB,YAAI,KAAK,UAAU;AAAA,MACrB,OAAO;AACL,YAAI,KAAK,IAAI;AAAA,MACf;AAAA,IACF,CAAC;AACD,QAAIA,MAAK,YAAY,MAAM;AACzB,YAAM,IAAI,MAAM,4DAA4DA,MAAK,aAAa;AAAA,IAChG;AACA,UAAM,iBAAiBA,MAAK,SAAS,GAAG;AACxC,eAAW,aAAaA,MAAK,QAAQ;AACnC,UAAI,EAAE,aAAa,iBAAiB;AAClC,cAAM,IAAI,MAAM,iCAAiC,yCAAyC,OAAO,KAAK,cAAc,IAAI;AAAA,MAC1H;AACA,YAAM,KAAK,MAAM,MAAM,eAAe,WAAW,CAAC;AAClD,UAAI,GAAG,UAAU,WAAW;AAC1B,cAAM,IAAI,MAAM,4BAA4BA,MAAK,qCAAqC,iDAAiD,GAAG,QAAQ;AAAA,MACpJ;AACA,YAAM,IAAIA,MAAK,OAAO;AACtB,UAAI,CAAC,YAAY,GAAG,OAAO,EAAE,KAAK,GAAG;AACnC,cAAM,IAAI,MAAM,4BAA4BA,MAAK,sCAAsC,yBAAyB,GAAG,wDAAwD,EAAE,QAAQ;AAAA,MACvL;AACA,UAAI,6BAA6B,EAAE,OAAO,MAAM;AAC9C,qCAA6B,EAAE,MAAM;AAAA,MACvC,OAAO;AACL,cAAM,cAAc,6BAA6B,EAAE;AACnD,qCAA6B,EAAE,MAAM,KAAK,aAAa,EAAE;AACzD,oBAAY,QAAQ;AAAA,MACtB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,wBAAwB;AAC5B,IAAI,6BAA6B;AACjC,IAAI,wBAAwB;AAC5B,SAAS,eAAe,MAAM,OAAO,OAAO,SAAS;AACnD,QAAMJ,WAAU,eAAe,KAAK;AACpC,QAAM,YAAY,wBAAwB,MAAM,OAAO,OAAOA,QAAO;AACrE,QAAM,OAAO,MAAM;AACnB,QAAM,YAAY,kBAAkB,MAAM,OAAO,OAAOA,UAAS,SAAS;AAC1E,QAAMK,SAAQ,CAAC,QAAQ;AACvB,MAAI,SAAS;AACX,IAAAA,OAAM,KAAK,YAAY,OAAO;AAC9B,IAAAA,OAAM,KAAK,WAAW,MAAM;AAC5B,IAAAA,OAAM,KAAK,aAAa,QAAQ;AAChC,IAAAA,OAAM,KAAK,WAAW;AAAA,EACxB;AACA,EAAAA,OAAM,KAAK,UAAU,IAAI,CAAC,OAAO,SAAS,EAAE,EAAE,KAAK,IAAI,CAAC;AACxD,SAAOA,OAAM,KAAK,IAAI;AACxB;AACA,SAAS,wBAAwB,MAAM,OAAO,OAAOL,UAAS;AAC5D,QAAM,KAAK,cAAc,KAAK;AAC9B,QAAM,UAAUA,SAAQA,SAAQ,SAAS;AACzC,QAAM,YAAY,IAAI,MAAM,OAAO,EAAE,KAAK,CAAC;AAC3C,QAAM,OAAO,MAAM;AACnB,QAAM,iBAAiB,UAAU,cAAc,oBAAoB,IAAI,IAAI;AAC3E,MAAI,OAAO,GAAG;AACZ,aAAS,MAAM,GAAG,MAAM,KAAK,SAAS,OAAO;AAC3C,YAAM,SAAS,MAAM;AACrB,eAAS,IAAI,GAAG,IAAI,SAAS,KAAK;AAChC,kBAAU,KAAK,KAAK,IAAI,UAAU,IAAI,YAAY,eAAe,SAAS,IAAI,GAAG,KAAK,EAAE,MAAM;AAAA,MAChG;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,YAAY,KAAK,MAAM,OAAO;AACrC,MAAI;AACJ,MAAI,MAAM,QAAQ,GAAG,GAAG;AACtB,aAAS,GAAG,WAAW,IAAI,GAAG,QAAQ,qBAAqB,CAAC,OAAO,WAAW,IAAI,GAAG,QAAQ,qBAAqB,CAAC;AAAA,EACrH,WAAW,SAAS,GAAG,GAAG;AACxB,aAAS,IAAI;AAAA,EACf,WAAW,UAAU,QAAQ;AAC3B,aAAS,gBAAgB,GAAG;AAAA,EAC9B,OAAO;AACL,aAAS,WAAW,IAAI,QAAQ,qBAAqB,CAAC,EAAE,SAAS;AAAA,EACnE;AACA,SAAO,SAAS,QAAQ,IAAI;AAC9B;AACA,SAAS,gBAAgB,GAAG;AAC1B,SAAO,MAAM,IAAI,UAAU;AAC7B;AACA,SAAS,kBAAkB,MAAM,OAAO,OAAOA,UAAS,WAAW,SAAS,MAAM;AAChF,QAAM,oBAAoB,UAAU,cAAc,IAAI;AACtD,QAAMZ,QAAO,MAAM;AACnB,QAAM,OAAO,MAAM;AACnB,MAAI,SAAS,GAAG;AACd,QAAI,UAAU,aAAa;AACzB,YAAM,eAAe,oBAAoB,IAAI;AAC7C,aAAO,CAAC,YAAY,aAAa,IAAI,GAAG,KAAK,CAAC;AAAA,IAChD;AACA,QAAI,UAAU,QAAQ;AACpB,aAAO,CAAC,gBAAgB,KAAK,EAAE,CAAC;AAAA,IAClC;AACA,WAAO,CAAC,KAAK,GAAG,SAAS,CAAC;AAAA,EAC5B;AACA,MAAI,SAAS,GAAG;AACd,QAAIA,QAAO,uBAAuB;AAChC,YAAM,gBAAgB,6BAA6B;AACnD,UAAI,YAAY,MAAM,KAAK,KAAK,MAAM,GAAG,aAAa,CAAC;AACvD,UAAI,WAAW,MAAM,KAAK,KAAK,OAAOA,QAAO,8BAA8B,mBAAmBA,QAAO,iBAAiB,CAAC;AACvH,UAAI,UAAU,aAAa;AACzB,oBAAY,oBAAoB,SAAS;AACzC,mBAAW,oBAAoB,QAAQ;AAAA,MACzC;AACA,aAAO;AAAA,QACL,MAAM,UAAU,IAAI,CAAC,GAAG,OAAO,YAAY,GAAG,UAAU,KAAK,KAAK,CAAC,EAAE,KAAK,IAAI,IAAI,YAAY,SAAS,IAAI,CAAC,GAAG,OAAO,YAAY,GAAG,UAAUA,QAAO,6BAA6B,KAAK,KAAK,CAAC,EAAE,KAAK,IAAI,IAAI;AAAA,MAC/M;AAAA,IACF;AACA,UAAM,cAAc,UAAU,cAAc,oBAAoB,IAAI,IAAI,MAAM,KAAK,IAAI;AACvF,WAAO;AAAA,MACL,MAAM,YAAY,IAAI,CAAC,GAAG,OAAO,YAAY,GAAG,UAAU,KAAK,KAAK,CAAC,EAAE,KAAK,IAAI,IAAI;AAAA,IACtF;AAAA,EACF;AACA,QAAM,WAAW,MAAM,MAAM,CAAC;AAC9B,QAAM,aAAaY,SAAQ,MAAM,CAAC;AAClC,QAAM,SAASA,SAAQ,KAAK;AAC5B,QAAMK,SAAQ,CAAC;AACf,MAAIjB,QAAO,uBAAuB;AAChC,aAAS,KAAK,GAAG,KAAK,4BAA4B,MAAM;AACtD,YAAM,QAAQ,KAAK;AACnB,YAAM,MAAM,QAAQ;AACpB,MAAAiB,OAAM,KAAK,GAAG,kBAAkB,KAAK,MAAM,OAAO,GAAG,GAAG,UAAU,OAAO,YAAY,WAAW,KAAK,CAAC;AAAA,IACxG;AACA,IAAAA,OAAM,KAAK,KAAK;AAChB,aAAS,KAAKjB,QAAO,4BAA4B,KAAKA,OAAM,MAAM;AAChE,YAAM,QAAQ,KAAK;AACnB,YAAM,MAAM,QAAQ;AACpB,MAAAiB,OAAM,KAAK,GAAG,kBAAkB,KAAK,MAAM,OAAO,GAAG,GAAG,UAAU,OAAO,YAAY,WAAW,OAAOjB,QAAO,CAAC,CAAC;AAAA,IAClH;AAAA,EACF,OAAO;AACL,aAAS,KAAK,GAAG,KAAKA,OAAM,MAAM;AAChC,YAAM,QAAQ,KAAK;AACnB,YAAM,MAAM,QAAQ;AACpB,MAAAiB,OAAM,KAAK,GAAG,kBAAkB,KAAK,MAAM,OAAO,GAAG,GAAG,UAAU,OAAO,YAAY,WAAW,OAAOjB,QAAO,CAAC,CAAC;AAAA,IAClH;AAAA,EACF;AACA,QAAM,MAAM,SAAS,IAAI,MAAM;AAC/B,EAAAiB,OAAM,KAAK,MAAMA,OAAM,KAAK;AAC5B,WAAS,KAAK,GAAG,KAAKA,OAAM,SAAS,GAAG,MAAM;AAC5C,IAAAA,OAAM,MAAM,MAAMA,OAAM,MAAM;AAAA,EAChC;AACA,MAAI,aAAa;AACjB,WAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,kBAAc;AAAA,EAChB;AACA,EAAAA,OAAMA,OAAM,SAAS,KAAK,MAAMA,OAAMA,OAAM,SAAS,KAAK,OAAO,SAAS,KAAK;AAC/E,SAAOA;AACT;AACA,SAAS,oBAAoB,MAAM;AACjC,QAAM,gBAAgB,CAAC;AACvB,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM,GAAG;AAC1C,kBAAc,KAAK,CAAC,KAAK,KAAK,KAAK,KAAK,EAAE,CAAC;AAAA,EAC7C;AACA,SAAO;AACT;AAGA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,OAAO,OAAO,QAAQ;AAChC,SAAK,QAAQ;AACb,SAAK,QAAQ,MAAM,MAAM;AACzB,SAAK,OAAO,cAAc,KAAK;AAC/B,QAAI,UAAU,MAAM;AAClB,YAAM,KAAK,OAAO;AAClB,aAAO,OAAO,KAAK,MAAM,MAAM,qBAAqB,sDAAsD,KAAK,QAAQ;AAAA,IACzH;AACA,QAAI,UAAU,aAAa;AACzB,YAAM,IAAI,MAAM,4JAA4J;AAAA,IAC9K;AACA,SAAK,SAAS,UAAU,kBAAkB,OAAO,KAAK,IAAI;AAC1D,SAAK,UAAU,eAAe,KAAK;AAAA,EACrC;AAAA,EACA,IAAI,UAAU,MAAM;AAClB,QAAI,KAAK,WAAW,GAAG;AACrB,aAAO,CAAC,CAAC;AAAA,IACX;AACA,WAAO,KAAK,WAAW,KAAK,MAAM,MAAM,uCAAuC,KAAK,gCAAgC,KAAK,OAAO;AAChI,UAAMR,SAAQ,KAAK,WAAW,IAAI;AAClC,SAAK,OAAOA,UAAS;AAAA,EACvB;AAAA,EACA,OAAO,MAAM;AACX,QAAI,KAAK,WAAW,GAAG;AACrB,aAAO,CAAC,CAAC;AAAA,IACX;AACA,QAAI,KAAK;AACT,eAAW,OAAO,MAAM;AACtB,UAAI,MAAM,KAAK,OAAO,KAAK,MAAM,KAAK;AACpC,cAAM,MAAM,qCAAqC,wBAAwB,KAAK;AAC9E,cAAM,IAAI,MAAM,GAAG;AAAA,MACrB;AACA;AAAA,IACF;AACA,QAAIA,SAAQ,KAAK,KAAK,SAAS;AAC/B,aAAS,KAAK,GAAG,KAAK,KAAK,SAAS,GAAG,EAAE,IAAI;AAC3C,MAAAA,UAAS,KAAK,QAAQ,MAAM,KAAK;AAAA,IACnC;AACA,WAAO,KAAK,OAAOA;AAAA,EACrB;AAAA,EACA,WAAW,MAAM;AACf,QAAI,KAAK,SAAS,GAAG;AACnB,aAAO;AAAA,IACT,WAAW,KAAK,SAAS,GAAG;AAC1B,aAAO,KAAK;AAAA,IACd;AACA,QAAIA,SAAQ,KAAK,KAAK,SAAS;AAC/B,aAAS,KAAK,GAAG,KAAK,KAAK,SAAS,GAAG,EAAE,IAAI;AAC3C,MAAAA,UAAS,KAAK,QAAQ,MAAM,KAAK;AAAA,IACnC;AACA,WAAOA;AAAA,EACT;AAAA,EACA,WAAWA,QAAO;AAChB,QAAI,KAAK,SAAS,GAAG;AACnB,aAAO,CAAC;AAAA,IACV,WAAW,KAAK,SAAS,GAAG;AAC1B,aAAO,CAACA,MAAK;AAAA,IACf;AACA,UAAM,OAAO,IAAI,MAAM,KAAK,MAAM,MAAM;AACxC,aAAS,KAAK,GAAG,KAAK,KAAK,SAAS,GAAG,EAAE,IAAI;AAC3C,WAAK,MAAM,KAAK,MAAMA,SAAQ,KAAK,QAAQ,GAAG;AAC9C,MAAAA,UAAS,KAAK,MAAM,KAAK,QAAQ;AAAA,IACnC;AACA,SAAK,KAAK,SAAS,KAAKA;AACxB,WAAO;AAAA,EACT;AAAA,EACA,IAAI,OAAO;AACT,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,WAAW;AACT,WAAO,UAAU,EAAE,WAAW,KAAK,QAAQ,KAAK,OAAO,KAAK,KAAK;AAAA,EACnE;AACF;AACA,IAAI,YAAY;AAChB,IAAI,YAAY;AAChB,IAAI,uBAAuB;AAC3B,SAAS,iBAAiB,IAAI;AAC5B,cAAY;AACd;AACA,SAAS,aAAa,SAAS;AAC7B,cAAY;AACd;AACA,SAAS,wBAAwB,IAAI;AACnC,yBAAuB;AACzB;AACA,IAAI,SAAS,MAAM;AAAA,EACjB,YAAY,OAAO,OAAO,QAAQ,IAAI;AACpC,SAAK,OAAO;AACZ,SAAK,qBAAqB;AAC1B,SAAK,QAAQ,MAAM,MAAM;AACzB,SAAK,QAAQ,SAAS;AACtB,SAAK,OAAO,cAAc,KAAK;AAC/B,SAAK,UAAU,eAAe,KAAK;AACnC,SAAK,SAAS;AACd,SAAK,KAAK;AACV,SAAK,WAAW,KAAK,OAAO,IAAI,KAAK,KAAK,SAAS,IAAI;AAAA,EACzD;AAAA,EACA,IAAI,OAAO;AACT,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,MAAM,SAAS;AACb,UAAM,OAAO,MAAM,KAAK,KAAK;AAC7B,WAAO,UAAU,OAAO,KAAK,OAAO,KAAK,OAAO,IAAI;AAAA,EACtD;AAAA,EACA,aAAa;AACX,WAAO,UAAU,OAAO,KAAK,OAAO,KAAK,OAAO,KAAK,SAAS,CAAC;AAAA,EACjE;AAAA,EACA,MAAM,QAAQ;AACZ,UAAM,OAAO,MAAM,KAAK,KAAK;AAC7B,WAAO,cAAc,KAAK,OAAO,MAAM,KAAK,UAAU,WAAW;AAAA,EACnE;AAAA,EACA,YAAY;AACV,WAAO,cAAc,KAAK,OAAO,KAAK,SAAS,GAAG,KAAK,UAAU,WAAW;AAAA,EAC9E;AAAA,EACA,MAAM,OAAO;AACX,SAAK,gBAAgB;AACrB,UAAM,OAAO,UAAU,EAAE,KAAK,KAAK,MAAM;AACzC,QAAI,KAAK,UAAU,UAAU;AAC3B,YAAM,QAAQ,MAAM;AACpB,UAAI;AACF,eAAO,MAAM,IAAI,CAAC,MAAM,aAAa,CAAC,CAAC;AAAA,MACzC,SAAS,IAAP;AACA,cAAM,IAAI,MAAM,+FAA+F;AAAA,MACjH;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,UAAUH,UAAS;AACjB,SAAK,gBAAgB;AACrB,WAAO,UAAU,EAAE,UAAU,KAAK,QAAQA,QAAO;AAAA,EACnD;AAAA,EACA,WAAW;AACT,SAAK,gBAAgB;AACrB,UAAM,OAAO,UAAU,EAAE,SAAS,KAAK,MAAM;AAC7C,QAAI,KAAK,UAAU,UAAU;AAC3B,UAAI;AACF,eAAO,KAAK,IAAI,CAAC,MAAM,aAAa,CAAC,CAAC;AAAA,MACxC,SAAS,IAAP;AACA,cAAM,IAAI,MAAM,+FAA+F;AAAA,MACjH;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,QAAQ;AACZ,SAAK,gBAAgB;AACrB,UAAM,OAAO,MAAM,UAAU,EAAE,KAAK,KAAK,MAAM;AAC/C,QAAI,KAAK,UAAU,UAAU;AAC3B,aAAO;AAAA,IACT,OAAO;AACL,aAAO,IAAI,WAAW,KAAK,MAAM;AAAA,IACnC;AAAA,EACF;AAAA,EACA,UAAU;AACR,QAAI,KAAK,YAAY;AACnB;AAAA,IACF;AACA,cAAU,EAAE,cAAc,IAAI;AAC9B,SAAK,qBAAqB;AAAA,EAC5B;AAAA,EACA,IAAI,aAAa;AACf,WAAO,KAAK;AAAA,EACd;AAAA,EACA,kBAAkB;AAChB,QAAI,KAAK,YAAY;AACnB,YAAM,IAAI,MAAM,qBAAqB;AAAA,IACvC;AAAA,EACF;AAAA,EACA,MAAM,UAAU,OAAO;AACrB,WAAO,UAAU,MAAM,MAAM,OAAO;AAAA,EACtC;AAAA,EACA,QAAQ;AACN,SAAK,gBAAgB;AACrB,WAAO,UAAU,MAAM,IAAI;AAAA,EAC7B;AAAA,EACA,SAAS,UAAU,OAAO;AACxB,UAAM,OAAO,KAAK,SAAS;AAC3B,WAAO,eAAe,MAAM,KAAK,OAAO,KAAK,OAAO,OAAO;AAAA,EAC7D;AAAA,EACA,KAAK,OAAO;AACV,SAAK,gBAAgB;AACrB,WAAO,UAAU,KAAK,MAAM,KAAK;AAAA,EACnC;AAAA,EACA,SAAS,YAAY,MAAM,MAAM,OAAO;AACtC,SAAK,gBAAgB;AACrB,WAAO,UAAU,EAAE,aAAa,MAAM,WAAW,MAAM,KAAK;AAAA,EAC9D;AACF;AACA,OAAO,eAAe,QAAQ,OAAO,aAAa;AAAA,EAChD,OAAO,CAAC,aAAa;AACnB,WAAO,CAAC,CAAC,YAAY,SAAS,QAAQ,QAAQ,SAAS,YAAY,QAAQ,SAAS,mBAAmB;AAAA,EACzG;AACF,CAAC;AACD,SAAS,uBAAuB;AAC9B,SAAO,UAAU,UAAU,MAAM;AAC/B,WAAO;AAAA,EACT,CAAC;AACH;AACA,qBAAqB;AACrB,IAAI,WAAW,cAAc,OAAO;AAAA,EAClC,YAAY,cAAc,WAAW,MAAM,UAAU;AACnD,UAAM,aAAa,OAAO,aAAa,OAAO,aAAa,QAAQ,QAAQ;AAC3E,SAAK,YAAY;AACjB,SAAK,OAAO;AAAA,EACd;AAAA,EACA,OAAO,UAAU;AACf,QAAI,SAAS,UAAU,KAAK,OAAO;AACjC,YAAM,IAAI,MAAM,2BAA2B,SAAS,8BAA8B,KAAK,mBAAmB;AAAA,IAC5G;AACA,QAAI,CAAC,YAAY,SAAS,OAAO,KAAK,KAAK,GAAG;AAC5C,YAAM,IAAI,MAAM,2BAA2B,SAAS,8BAA8B,KAAK,mBAAmB;AAAA,IAC5G;AACA,cAAU,EAAE,cAAc,IAAI;AAC9B,SAAK,SAAS,SAAS;AACvB,cAAU,EAAE,OAAO,MAAM,IAAI;AAAA,EAC/B;AAAA,EACA,UAAU;AACR,cAAU,EAAE,gBAAgB,IAAI;AAChC,SAAK,qBAAqB;AAAA,EAC5B;AACF;AACA,OAAO,eAAe,UAAU,OAAO,aAAa;AAAA,EAClD,OAAO,CAAC,aAAa;AACnB,WAAO,oBAAoB,UAAU,SAAS,UAAU,QAAQ,SAAS,kBAAkB;AAAA,EAC7F;AACF,CAAC;AAGD,IAAI,sBAAsB,CAAC;AAC3BT,UAAS,qBAAqB;AAAA,EAC5B,kBAAkB,MAAM;AAAA,EACxB,uBAAuB,MAAM;AAAA,EAC7B,gBAAgB,MAAM;AAAA,EACtB,gBAAgB,MAAM;AACxB,CAAC;AAGD,IAAI;AAAA,CACH,SAAS,OAAO;AACf,QAAM,QAAQ;AACd,QAAM,QAAQ;AACd,QAAM,QAAQ;AACd,QAAM,QAAQ;AACd,QAAM,QAAQ;AACd,QAAM,QAAQ;AACd,QAAM,QAAQ;AAChB,GAAG,SAAS,OAAO,CAAC,EAAE;AACtB,IAAI;AAAA,CACH,SAAS,oBAAoB;AAC5B,qBAAmB,aAAa;AAChC,qBAAmB,WAAW;AAC9B,qBAAmB,UAAU;AAC7B,qBAAmB,eAAe;AACpC,GAAG,sBAAsB,oBAAoB,CAAC,EAAE;AAChD,IAAI;AAAA,CACH,SAAS,mBAAmB;AAC3B,oBAAkB,aAAa;AAC/B,oBAAkB,WAAW;AAC7B,oBAAkB,UAAU;AAC5B,oBAAkB,eAAe;AACnC,GAAG,qBAAqB,mBAAmB,CAAC,EAAE;AAC9C,IAAI;AAAA,CACH,SAAS,sBAAsB;AAC9B,uBAAqB,aAAa;AAClC,uBAAqB,WAAW;AAChC,uBAAqB,UAAU;AAC/B,uBAAqB,eAAe;AACtC,GAAG,wBAAwB,sBAAsB,CAAC,EAAE;AACpD,IAAI;AAAA,CACH,SAAS,wBAAwB;AAChC,yBAAuB,aAAa;AACpC,yBAAuB,WAAW;AAClC,yBAAuB,UAAU;AACjC,yBAAuB,eAAe;AACxC,GAAG,0BAA0B,wBAAwB,CAAC,EAAE;AACxD,IAAI,gBAAgB;AAAA,EAClB,WAAW;AAAA,EACX,SAAS;AAAA,EACT,QAAQ;AAAA,EACR,aAAa;AACf;AACA,SAAS,WAAW,OAAO,OAAO;AAChC,MAAI,UAAU,YAAY,UAAU,UAAU;AAC5C,QAAI,UAAU,YAAY,UAAU,UAAU;AAC5C,aAAO;AAAA,IACT;AACA,UAAM,IAAI,MAAM,kBAAkB,cAAc,OAAO;AAAA,EACzD;AACA,SAAO,cAAc,OAAO;AAC9B;AACA,SAAS,WAAW,MAAM;AACxB,SAAO,WAAW,MAAM,OAAO;AACjC;AAGA,SAAS,eAAe,GAAG,GAAG;AAC5B,MAAI,EAAE,UAAU,EAAE,OAAO;AACvB,WAAO,CAAC,GAAG,CAAC;AAAA,EACd;AACA,QAAM,QAAQ,WAAW,EAAE,OAAO,EAAE,KAAK;AACzC,SAAO,CAAC,EAAE,KAAK,KAAK,GAAG,EAAE,KAAK,KAAK,CAAC;AACtC;AACA,SAAS,iBAAiB,GAAG,GAAG;AAC9B,SAAO,EAAE,UAAU,EAAE,OAAO,MAAM,2BAA2B,EAAE,qBAAqB,EAAE,yBAAyB;AACjH;AACA,SAAS,eAAe,SAAS,YAAY;AAC3C,SAAO,WAAW,KAAK,CAAC,MAAM,EAAE,OAAO,QAAQ,EAAE;AACnD;AACA,SAAS,sBAAsB,QAAQ;AACrC,QAAM,OAAO,CAAC;AACd,QAAM,OAAuB,oBAAI,IAAI;AACrC,sBAAoB,QAAQ,MAAM,IAAI;AACtC,SAAO;AACT;AACA,SAAS,oBAAoB,WAAW,MAAM,MAAM;AAClD,MAAI,aAAa,MAAM;AACrB;AAAA,EACF;AACA,MAAI,qBAAqB,QAAQ;AAC/B,SAAK,KAAK,SAAS;AACnB;AAAA,EACF;AACA,MAAI,CAAC,WAAW,SAAS,GAAG;AAC1B;AAAA,EACF;AACA,QAAM,WAAW;AACjB,aAAW,KAAK,UAAU;AACxB,UAAM,MAAM,SAAS;AACrB,QAAI,CAAC,KAAK,IAAI,GAAG,GAAG;AAClB,WAAK,IAAI,GAAG;AACZ,0BAAoB,KAAK,MAAM,IAAI;AAAA,IACrC;AAAA,EACF;AACF;AACA,SAAS,WAAW,KAAK;AACvB,SAAO,MAAM,QAAQ,GAAG,KAAK,OAAO,QAAQ;AAC9C;AAGA,SAAS,6BAA6B,kBAAkB;AACtD,SAAO,iBAAiB,cAAc;AACxC;AACA,IAAI,cAAc,MAAM;AAAA,EACtB,cAAc;AACZ,SAAK,sBAAsB,CAAC;AAC5B,SAAK,iBAAiB;AACtB,SAAK,WAAW;AAChB,SAAK,aAAa;AAClB,SAAK,mBAAmB;AACxB,SAAK,iBAAiB;AACtB,SAAK,gBAAgB;AACrB,SAAK,cAAc;AACnB,SAAK,aAAa,CAAC;AACnB,SAAK,oBAAoB,CAAC;AAC1B,SAAK,cAAc;AACnB,SAAK,aAA6B,oBAAI,QAAQ;AAC9C,SAAK,YAAY;AACjB,SAAK,gBAAgB;AAAA,MACnB,UAAU;AAAA,MACV,YAAY;AAAA,MACZ,WAAW;AAAA,MACX,SAAS,CAAC;AAAA,MACV,QAAQ;AAAA,MACR,IAAI,cAAc;AAChB,eAAO,MAAM,KAAK,IAAI,IAAI,KAAK,QAAQ,IAAI,CAAC,MAAM,EAAE,IAAI,CAAC,CAAC;AAAA,MAC5D;AAAA,IACF;AAAA,EACF;AAAA,EACA,UAAU;AACR,eAAW,gBAAgB,KAAK,qBAAqB;AACnD,WAAK,oBAAoB,cAAc,QAAQ;AAAA,IACjD;AAAA,EACF;AACF;AACA,IAAI,SAAS,MAAM;AAAA,EACjB,YAAY,MAAM;AAChB,SAAK,MAAM;AACX,SAAK,WAAW,CAAC;AACjB,SAAK,kBAAkB,CAAC;AACxB,SAAK,uBAAuB;AAC5B,SAAK,QAAQ,IAAI,YAAY;AAAA,EAC/B;AAAA,EACA,MAAM,QAAQ;AACZ,QAAI,KAAK,sBAAsB,MAAM;AACnC,aAAO,KAAK,mBAAmB,KAAK,MAAM;AAAA,MAC1C,CAAC;AAAA,IACH;AACA,QAAI,KAAK,mBAAmB,MAAM;AAChC;AAAA,IACF;AACA,UAAM,iBAAiB,KAAK,kBAAkB;AAC9C,aAAS,KAAK,GAAG,KAAK,eAAe,QAAQ,MAAM;AACjD,YAAM,cAAc,eAAe;AACnC,YAAM,UAAU,MAAM,KAAK,kBAAkB,WAAW,EAAE;AAC1D,UAAI,SAAS;AACX,cAAM,KAAK,WAAW,WAAW;AACjC;AAAA,MACF;AAAA,IACF;AACA,UAAM,IAAI,MAAM,wEAAwE;AAAA,EAC1F;AAAA,EACA,IAAI,UAAU;AACZ,QAAI,KAAK,sBAAsB,MAAM;AACnC,YAAM,IAAI,MAAM,YAAY,KAAK,gIAAgI;AAAA,IACnK;AACA,QAAI,KAAK,mBAAmB,MAAM;AAChC,YAAM,EAAE,MAAM,UAAU,IAAI,KAAK,gCAAgC;AACjE,UAAI,WAAW;AACb,cAAM,IAAI,MAAM,iCAAiC,yHAAyH;AAAA,MAC5K;AACA,WAAK,WAAW,IAAI;AAAA,IACtB;AACA,WAAO,KAAK;AAAA,EACd;AAAA,EACA,eAAe;AACb,WAAO,OAAO,KAAK,KAAK,eAAe;AAAA,EACzC;AAAA,EACA,YAAY,aAAa;AACvB,QAAI,EAAE,eAAe,KAAK,WAAW;AACnC,UAAI,eAAe,KAAK,iBAAiB;AACvC,cAAM,EAAE,UAAU,IAAI,KAAK,kBAAkB,WAAW;AACxD,YAAI,WAAW;AACb,iBAAO;AAAA,QACT;AAAA,MACF,OAAO;AACL,eAAO;AAAA,MACT;AAAA,IACF;AACA,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,mBAAmB,aAAa;AAC9B,QAAI,EAAE,eAAe,KAAK,kBAAkB;AAC1C,aAAO;AAAA,IACT;AACA,WAAO,KAAK,gBAAgB,aAAa;AAAA,EAC3C;AAAA,EACA,gBAAgB,aAAa,SAAS,WAAW,GAAG;AAClD,QAAI,eAAe,KAAK,iBAAiB;AACvC,WAAK,GAAG,+EAA+E;AACvF,aAAO;AAAA,IACT;AACA,SAAK,gBAAgB,eAAe,EAAE,SAAS,SAAS;AACxD,WAAO;AAAA,EACT;AAAA,EACA,MAAM,WAAW,aAAa;AAC5B,QAAI,KAAK,gBAAgB,gBAAgB,MAAM;AAC7C,YAAM,IAAI,MAAM,iBAAiB,oCAAoC;AAAA,IACvE;AACA,SAAK,cAAc;AACnB,QAAI,KAAK,SAAS,gBAAgB,MAAM;AACtC,WAAK,kBAAkB;AACvB,YAAM,EAAE,SAAS,UAAU,IAAI,KAAK,kBAAkB,WAAW;AACjE,YAAM,SAAS,YAAY,MAAM,UAAU;AAC3C,UAAI,CAAC,QAAQ;AACX,eAAO;AAAA,MACT;AAAA,IACF;AACA,SAAK,kBAAkB,KAAK,SAAS;AACrC,SAAK,uBAAuB;AAC5B,SAAK,WAAW,IAAI,SAAS,KAAK,eAAe;AACjD,WAAO;AAAA,EACT;AAAA,EACA,yBAAyB;AACvB,UAAM,UAAU,qBAAqB,KAAK,WAAW;AACrD,YAAQ,QAAQ,CAAC,WAAW;AAC1B,UAAI,OAAO,aAAa,MAAM;AAC5B,eAAO,UAAU,KAAK,eAAe;AAAA,MACvC;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,yBAAyB,aAAa;AACpC,UAAM,UAAU,qBAAqB,WAAW;AAChD,YAAQ,QAAQ,CAAC,WAAW;AAC1B,UAAI,OAAO,eAAe,MAAM;AAC9B,eAAO,YAAY,KAAK,SAAS,YAAY;AAAA,MAC/C;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,kBAAkB,aAAa;AAC7B,UAAM,uBAAuB,KAAK,gBAAgB;AAClD,QAAI,wBAAwB,MAAM;AAChC,YAAM,IAAI,MAAM,6BAA6B,qCAAqC;AAAA,IACpF;AACA,QAAI;AACF,YAAM,WAAW,qBAAqB,QAAQ;AAC9C,UAAI,YAAY,EAAE,oBAAoB,kBAAkB,OAAO,SAAS,SAAS,YAAY;AAC3F,cAAM,YAAY,EAAE,KAAK;AACzB,cAAM,UAAU,SAAS,KAAK,CAAC,oBAAoB;AACjD,cAAI,YAAY,KAAK,sBAAsB;AACzC,mBAAO;AAAA,UACT;AACA,eAAK,SAAS,eAAe;AAC7B,eAAK,qBAAqB;AAC1B,iBAAO;AAAA,QACT,CAAC,EAAE,MAAM,CAAC,QAAQ;AAChB,cAAI,YAAY,KAAK,sBAAsB;AACzC,mBAAO;AAAA,UACT;AACA,eAAK,qBAAqB;AAC1B,eAAK,6BAA6B,oBAAoB;AACtD,eAAK,IAAI,SAAS,IAAI,OAAO;AAC7B,iBAAO;AAAA,QACT,CAAC;AACD,aAAK,qBAAqB;AAC1B,eAAO,EAAE,SAAS,WAAW,KAAK;AAAA,MACpC,OAAO;AACL,aAAK,SAAS,eAAe;AAC7B,eAAO,EAAE,SAAS,MAAM,WAAW,MAAM;AAAA,MAC3C;AAAA,IACF,SAAS,KAAP;AACA,WAAK,6BAA6B,oBAAoB;AACtD,WAAK,IAAI,SAAS,IAAI,OAAO;AAC7B,aAAO,EAAE,SAAS,OAAO,WAAW,MAAM;AAAA,IAC5C;AAAA,EACF;AAAA,EACA,cAAc,aAAa;AACzB,QAAI,EAAE,eAAe,KAAK,kBAAkB;AAC1C,YAAM,IAAI,MAAM,GAAG,2CAA2C;AAAA,IAChE;AACA,QAAI,KAAK,gBAAgB,eAAe,KAAK,sBAAsB,MAAM;AACvE,WAAK;AAAA,IACP;AACA,QAAI,eAAe,KAAK,UAAU;AAChC,WAAK,yBAAyB,WAAW;AACzC,WAAK,SAAS,aAAa,QAAQ;AACnC,aAAO,KAAK,SAAS;AAAA,IACvB;AACA,WAAO,KAAK,gBAAgB;AAC5B,QAAI,KAAK,gBAAgB,aAAa;AACpC,WAAK,qBAAqB;AAC1B,WAAK,cAAc;AACnB,WAAK,kBAAkB;AAAA,IACzB;AAAA,EACF;AAAA,EACA,oBAAoB;AAClB,QAAI,OAAO,KAAK,KAAK,eAAe,EAAE,WAAW,GAAG;AAClD,YAAM,IAAI,MAAM,+BAA+B;AAAA,IACjD;AACA,WAAO,OAAO,KAAK,KAAK,eAAe,EAAE,KAAK,CAAC,GAAG,MAAM;AACtD,aAAO,KAAK,gBAAgB,GAAG,WAAW,KAAK,gBAAgB,GAAG;AAAA,IACpE,CAAC;AAAA,EACH;AAAA,EACA,kCAAkC;AAChC,UAAM,iBAAiB,KAAK,kBAAkB;AAC9C,aAAS,KAAK,GAAG,KAAK,eAAe,QAAQ,MAAM;AACjD,YAAM,cAAc,eAAe;AACnC,YAAM,EAAE,SAAS,UAAU,IAAI,KAAK,kBAAkB,WAAW;AACjE,UAAI,aAAa,SAAS;AACxB,eAAO,EAAE,MAAM,aAAa,UAAU;AAAA,MACxC;AAAA,IACF;AACA,UAAM,IAAI,MAAM,wEAAwE;AAAA,EAC1F;AAAA,EACA,SAAS,UAAU,QAAQ;AACzB,UAAM,OAAO,KAAK,MAAM,WAAW,IAAI,MAAM;AAC7C,UAAM,aAAa,KAAK;AACxB,UAAM,SAAS,KAAK,SAAS,MAAM;AACnC,UAAM,WAAW,WAAW,SAAS,MAAM;AAC3C,eAAW,YAAY,QAAQ,IAAI;AACnC,SAAK,UAAU;AACf,aAAS,KAAK,QAAQ,QAAQ,KAAK,OAAO,KAAK,OAAO,QAAQ;AAC9D,QAAI,KAAK,uBAAuB,GAAG;AACjC,WAAK,MAAM,kBAAkB,KAAK,MAAM,kBAAkB,SAAS;AAAA,IACrE;AAAA,EACF;AAAA,EACA,KAAK,UAAU,IAAI;AACjB,QAAI,OAAO;AACX,QAAI,MAAM,MAAM;AACd,UAAI,OAAO,aAAa,YAAY;AAClC,cAAM,IAAI,MAAM,qCAAqC;AAAA,MACvD;AACA,WAAK;AAAA,IACP,OAAO;AACL,UAAI,OAAO,aAAa,YAAY,EAAE,oBAAoB,SAAS;AACjE,cAAM,IAAI,MAAM,gFAAgF;AAAA,MAClG;AACA,UAAI,OAAO,OAAO,YAAY;AAC5B,cAAM,IAAI,MAAM,gFAAgF;AAAA,MAClG;AACA,aAAO;AAAA,IACT;AACA,QAAI;AACJ,WAAO,KAAK,UAAU,MAAM,KAAK,WAAW,IAAI,GAAG,MAAM,KAAK,SAAS,MAAM,GAAG,MAAM;AACpF,eAAS,GAAG;AACZ,UAAI,kBAAkB,SAAS;AAC7B,gBAAQ,MAAM,yCAAyC;AAAA,MACzD;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,UAAU,OAAO,KAAK,GAAG;AACvB,UAAM;AACN,QAAI;AACF,YAAM,MAAM,EAAE;AACd,UAAI;AACJ,aAAO;AAAA,IACT,SAAS,IAAP;AACA,UAAI;AACJ,YAAM;AAAA,IACR;AAAA,EACF;AAAA,EACA,eAAe;AACb,WAAO,OAAO;AAAA,EAChB;AAAA,EACA,iBAAiB;AACf,WAAO,OAAO;AAAA,EAChB;AAAA,EACA,MAAM,GAAG;AACP,UAAM,IAAI,OAAO,UAAU,UAAU,EAAE,EAAE,CAAC;AAC1C,UAAM,SAAS,EAAE,EAAE;AACnB,UAAM,QAAQ,CAAC,QAAQ;AAAA,MACrB,GAAG,MAAM;AACP,cAAM,QAAQ;AACd,cAAM,aAAa,EAAE,GAAG,GAAG;AAC3B,cAAM,QAAQ,EAAE,MAAM;AACtB,eAAO,OAAO;AAAA,UACZ;AAAA,UACA;AAAA,UACA;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,QAAQ,CAAC;AACf,SAAK,YAAY,KAAK,MAAM,YAAY,MAAM,QAAQ,CAAC,CAAC,GAAG,OAAO,OAAO,CAAC,CAAC;AAC3E,WAAO;AAAA,EACT;AAAA,EACA,UAAU,YAAY,QAAQ,OAAO;AACnC,QAAI,KAAK,eAAe,MAAM;AAC5B,WAAK;AAAA,IACP;AACA,UAAM,YAAY,UAAU,YAAY,KAAK,WAAW,KAAK;AAC7D,QAAI,CAAC,WAAW;AACd,YAAM,IAAI,MAAM,WAAW,2CAA2C,KAAK,cAAc;AAAA,IAC3F;AACA,WAAO,KAAK,cAAc,EAAE,YAAY,QAAQ,MAAM,CAAC;AAAA,EACzD;AAAA,EACA,yBAAyB;AACvB,WAAO,KAAK,IAAI,QAAQ,SAAS;AAAA,EACnC;AAAA,EACA,sBAAsB,YAAY,kBAAkB,UAAU;AAC5D,UAAM,kBAAkB,KAAK,QAAQ,WAAW;AAChD,QAAI,mBAAmB;AACvB,aAAS,QAAQ,CAAC,SAAS;AACzB,0BAAoB,KAAK,UAAU,cAAc,IAAI;AAAA,IACvD,CAAC;AACD,UAAM,WAAW,KAAK,MAAM,kBAAkB,KAAK,MAAM,kBAAkB,SAAS;AACpF,UAAM,gBAAgB,kBAAkB,mBAAmB,mBAAmB;AAC9E,QAAI,gBAAgB,GAAG;AACrB,YAAM,IAAI,MAAM,YAAY,KAAK,6CAA6C,0CAA0C,aAAa;AAAA,IACvI;AAAA,EACF;AAAA,EACA,cAAc,cAAc;AAC1B,QAAI;AACJ,QAAI,QAAQ,CAAC;AACb,UAAM,WAAW,KAAK,SAAS;AAC/B,UAAM,oBAAoB,KAAK,MAAM;AACrC,UAAM,qBAAqB,KAAK,MAAM;AACtC,QAAI,KAAK,uBAAuB,GAAG;AACjC,WAAK,MAAM,kBAAkB,KAAK,CAAC;AAAA,IACrC;AACA,QAAI;AACJ,QAAI,KAAK,eAAe,MAAM;AAC5B,WAAK;AAAA,IACP;AACA,QAAI;AACJ,UAAM,oBAAoB,6BAA6B,YAAY,IAAI,aAAa,aAAa,KAAK,MAAM,eAAe,OAAO,KAAK,MAAM,YAAY,OAAO;AAChK,QAAI,6BAA6B,YAAY,GAAG;AAC9C,YAAM,EAAE,YAAY,QAAQ,SAAS,OAAO,OAAO,IAAI;AACvD,UAAI,KAAK,eAAe,MAAM;AAC5B,aAAK;AAAA,MACP;AACA,YAAM,SAAS,UAAU,YAAY,KAAK,WAAW;AACrD,aAAO,UAAU,MAAM,MAAM,kCAAkC,4BAA4B,KAAK,cAAc;AAC9G,oBAAc,MAAM;AAClB,cAAM,mBAAmB,KAAK,QAAQ,WAAW;AACjD,cAAM,OAAO,WAAW,EAAE,QAAQ,SAAS,OAAO,QAAQ,SAAS,KAAK,QAAQ,CAAC;AACjF,cAAM,WAAW,MAAM,QAAQ,GAAG,IAAI,MAAM,CAAC,GAAG;AAChD,YAAI,KAAK,uBAAuB,GAAG;AACjC,eAAK,sBAAsB,YAAY,kBAAkB,QAAQ;AAAA,QACnE;AACA,cAAM,aAAa,SAAS,IAAI,CAAC,YAAY;AAC3C,cAAI,QAAQ,QAAQ,MAAM;AACxB,mBAAO;AAAA,UACT;AACA,iBAAO,KAAK,yBAAyB,OAAO;AAAA,QAC9C,CAAC;AACD,YAAI,UAAU;AACZ,gBAAM,gBAAgB,KAAK,sBAAsB,YAAY,SAAS,UAAU;AAChF,kBAAQ,KAAK,2BAA2B,aAAa;AAAA,QACvD;AACA,eAAO;AAAA,MACT;AAAA,IACF,OAAO;AACL,YAAM,EAAE,YAAY,IAAI;AACxB,YAAM,WAAW,CAAC,YAAY;AAC5B,YAAI,CAAC,UAAU;AACb;AAAA,QACF;AACA,gBAAQ,QAAQ,IAAI,CAAC,YAAY,KAAK,KAAK,KAAK,MAAM,OAAO,CAAC,CAAC;AAAA,MACjE;AACA,oBAAc,MAAM;AAClB,cAAM,mBAAmB,KAAK,QAAQ,WAAW;AACjD,cAAM,KAAK,KAAK,MAAM,YAAY,KAAK,SAAS,QAAQ,CAAC;AACzD,cAAM,OAAO,MAAM,QAAQ,GAAG,IAAI,MAAM,CAAC,GAAG;AAC5C,YAAI,KAAK,uBAAuB,GAAG;AACjC,eAAK,sBAAsB,mBAAmB,kBAAkB,IAAI;AAAA,QACtE;AACA,eAAO;AAAA,MACT;AAAA,IACF;AACA,UAAM,EAAE,QAAQ,MAAM,IAAI;AAC1B,UAAM,gBAAgB,6BAA6B,YAAY,IAAI,OAAO,aAAa;AACvF,QAAI;AACJ,SAAK;AAAA,MACH,MAAM,KAAK,MAAM;AAAA,MACjB,MAAM,KAAK,MAAM;AAAA,MACjB,MAAM;AACJ,YAAI,CAAC,KAAK,IAAI,QAAQ,OAAO,KAAK,CAAC,KAAK,MAAM,WAAW;AACvD,oBAAU,YAAY;AAAA,QACxB,OAAO;AACL,0BAAgB,KAAK,SAAS,cAAc,mBAAmB,QAAQ,MAAM,YAAY,CAAC;AAC1F,cAAI,KAAK,IAAI,QAAQ,OAAO,GAAG;AAC7B,iBAAK,SAAS,iBAAiB,aAAa;AAAA,UAC9C;AACA,oBAAU,cAAc;AAAA,QAC1B;AAAA,MACF;AAAA,IACF;AACA,QAAI,UAAU;AACZ,WAAK,YAAY,mBAAmB,QAAQ,SAAS,eAAe,OAAO,KAAK;AAAA,IAClF;AACA,QAAI,KAAK,MAAM,WAAW;AACxB,WAAK,MAAM,cAAc,QAAQ,KAAK;AAAA,QACpC,MAAM;AAAA,QACN,YAAY,KAAK,MAAM,WAAW;AAAA,QAClC,oBAAoB,KAAK,MAAM;AAAA,QAC/B,cAAc,KAAK,MAAM,aAAa;AAAA,QACtC,sBAAsB,KAAK,MAAM;AAAA,QACjC,aAAa,OAAO,KAAK,MAAM,EAAE,IAAI,CAAC,QAAQ,OAAO,QAAQ,OAAO,OAAO,KAAK,QAAQ,IAAI;AAAA,QAC5F,cAAc,QAAQ,IAAI,CAAC,SAAS,KAAK,KAAK;AAAA,QAC9C,cAAc,cAAc;AAAA,QAC5B,WAAW,cAAc;AAAA,MAC3B,CAAC;AAAA,IACH;AACA,WAAO,MAAM,QAAQ,GAAG,IAAI,UAAU,QAAQ;AAAA,EAChD;AAAA,EACA,2BAA2B,SAAS;AAClC,UAAM,QAAQ,QAAQ,IAAI,CAAC,YAAY,KAAK,KAAK,KAAK,MAAM,OAAO,CAAC,CAAC;AACrE,WAAO;AAAA,EACT;AAAA,EACA,sBAAsB,YAAY,QAAQ,SAAS;AACjD,UAAM,aAAa,YAAY,UAAU;AACzC,QAAI,cAAc,MAAM;AACtB,YAAM,eAAe,WAAW,gBAAgB,CAAC;AACjD,YAAM,gBAAgB,WAAW,iBAAiB,CAAC;AACnD,UAAI;AACJ,UAAI,WAAW,eAAe;AAC5B,eAAO,MAAM,QAAQ,MAAM,GAAG,MAAM,wDAAwD;AAC5F,6BAAqB,OAAO,KAAK,MAAM,EAAE,IAAI,CAAC,QAAQ,OAAO,IAAI;AAAA,MACnE,OAAO;AACL,6BAAqB,aAAa,IAAI,CAAC,cAAc,OAAO,UAAU;AAAA,MACxE;AACA,YAAM,sBAAsB,QAAQ,OAAO,CAAC,GAAG,OAAO,cAAc,GAAG;AACvE,aAAO,mBAAmB,OAAO,mBAAmB;AAAA,IACtD;AACA,WAAO,CAAC;AAAA,EACV;AAAA,EACA,WAAW,QAAQ,OAAO,OAAO,UAAU;AACzC,QAAI,UAAU,MAAM;AAClB,YAAM,IAAI,MAAM,+CAA+C;AAAA,IACjE;AACA,YAAQ,SAAS;AACjB,eAAW,YAAY,KAAK;AAC5B,QAAI,cAAc;AAClB,QAAI,UAAU,YAAY,SAAS,OAAO,EAAE,GAAG;AAC7C,oBAAc,OAAO,IAAI,CAAC,MAAM,aAAa,CAAC,CAAC;AAAA,IACjD;AACA,UAAM,SAAS,SAAS,MAAM,aAAa,OAAO,KAAK;AACvD,UAAM,KAAK,IAAI,OAAO,OAAO,OAAO,QAAQ,KAAK,aAAa,CAAC;AAC/D,SAAK,YAAY,IAAI,QAAQ;AAC7B,QAAI,UAAU,UAAU;AACtB,YAAM,OAAO,KAAK,MAAM,WAAW,IAAI,MAAM;AAC7C,YAAM,WAAW,qBAAqB,WAAW;AACjD,WAAK,MAAM,YAAY,WAAW,KAAK;AACvC,WAAK,QAAQ;AAAA,IACf;AACA,WAAO;AAAA,EACT;AAAA,EACA,qBAAqB,QAAQ,OAAO,OAAO,UAAU;AACnD,YAAQ,SAAS;AACjB,UAAM,aAAa,EAAE,QAAQ,OAAO,MAAM;AAC1C,WAAO,KAAK,yBAAyB,YAAY,QAAQ;AAAA,EAC3D;AAAA,EACA,yBAAyB,YAAY,UAAU;AAC7C,UAAM,EAAE,QAAQ,OAAO,MAAM,IAAI;AACjC,UAAM,KAAK,IAAI,OAAO,OAAO,OAAO,QAAQ,KAAK,aAAa,CAAC;AAC/D,SAAK,YAAY,IAAI,QAAQ;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,aAAa,cAAc,YAAY,MAAM,MAAM,OAAO;AACxD,WAAO,QAAQ,KAAK,eAAe,EAAE,SAAS;AAC9C,QAAI,SAAS,QAAQ,UAAU,aAAa,OAAO;AACjD,qBAAe,aAAa,KAAK,KAAK;AAAA,IACxC;AACA,UAAM,IAAI,IAAI,SAAS,cAAc,WAAW,MAAM,KAAK,aAAa,CAAC;AACzE,QAAI,KAAK,MAAM,oBAAoB,EAAE,SAAS,MAAM;AAClD,YAAM,IAAI,MAAM,sBAAsB,EAAE,6BAA6B;AAAA,IACvE;AACA,SAAK,MAAM,oBAAoB,EAAE,QAAQ;AACzC,SAAK,OAAO,GAAG,KAAK,OAAO;AAC3B,WAAO;AAAA,EACT;AAAA,EACA,YAAY,GAAG,UAAU;AACvB,SAAK,MAAM;AACX,QAAI,EAAE,UAAU,UAAU;AACxB,WAAK,MAAM;AAAA,IACb;AACA,QAAI,QAAQ;AACZ,QAAI,EAAE,UAAU,eAAe,EAAE,UAAU,UAAU;AACnD,cAAQ,EAAE,OAAO,gBAAgB,EAAE,KAAK;AAAA,IAC1C;AACA,SAAK,MAAM,YAAY;AACvB,QAAI,CAAC,KAAK,MAAM,WAAW,IAAI,EAAE,MAAM,GAAG;AACxC,WAAK,MAAM;AACX,WAAK,MAAM,WAAW,IAAI,EAAE,QAAQ;AAAA,QAClC,SAAS,YAAY,KAAK;AAAA,QAC1B,OAAO,EAAE;AAAA,QACT,OAAO,EAAE;AAAA,QACT;AAAA,MACF,CAAC;AAAA,IACH;AACA,QAAI,EAAE,aAAa,WAAW;AAC5B,WAAK,MAAM,CAAC;AAAA,IACd;AAAA,EACF;AAAA,EACA,OAAO,GAAG,UAAU;AAClB,SAAK,YAAY,GAAG,QAAQ;AAC5B,SAAK,QAAQ,OAAO,EAAE,MAAM;AAAA,EAC9B;AAAA,EACA,aAAa,QAAQ,UAAU;AAC7B,QAAI,KAAK,MAAM,WAAW,IAAI,MAAM,KAAK,KAAK,MAAM,WAAW,IAAI,MAAM,EAAE,YAAY,UAAU;AAC/F,WAAK,MAAM,WAAW,OAAO,MAAM;AACnC,WAAK,MAAM;AAAA,IACb;AAAA,EACF;AAAA,EACA,cAAc,GAAG;AACf,QAAI,CAAC,KAAK,MAAM,WAAW,IAAI,EAAE,MAAM,GAAG;AACxC;AAAA,IACF;AACA,UAAM,OAAO,KAAK,MAAM,WAAW,IAAI,EAAE,MAAM;AAC/C,SAAK,MAAM;AACX,QAAI,EAAE,UAAU,UAAU;AACxB,WAAK,MAAM;AACX,WAAK,MAAM,YAAY,KAAK;AAAA,IAC9B;AACA,QAAI,EAAE,UAAU,eAAe,EAAE,UAAU,UAAU;AACnD,YAAM,QAAQ,EAAE,OAAO,gBAAgB,EAAE,KAAK;AAC9C,WAAK,MAAM,YAAY;AAAA,IACzB;AACA,QAAI,KAAK,QAAQ,YAAY,EAAE,MAAM,GAAG;AACtC,WAAK,aAAa,EAAE,QAAQ,KAAK,OAAO;AAAA,IAC1C;AAAA,EACF;AAAA,EACA,mBAAmB;AACjB,eAAW,WAAW,KAAK,MAAM,qBAAqB;AACpD,YAAM,IAAI,KAAK,MAAM,oBAAoB;AACzC,WAAK,gBAAgB,CAAC;AAAA,IACxB;AAAA,EACF;AAAA,EACA,gBAAgB,GAAG;AACjB,SAAK,cAAc,CAAC;AACpB,QAAI,KAAK,MAAM,oBAAoB,EAAE,SAAS,MAAM;AAClD,aAAO,KAAK,MAAM,oBAAoB,EAAE;AAAA,IAC1C;AAAA,EACF;AAAA,EACA,SAAS;AACP,UAAM,OAAO,KAAK,QAAQ,OAAO;AACjC,SAAK,aAAa,KAAK,MAAM;AAC7B,SAAK,iBAAiB,KAAK,MAAM;AACjC,SAAK,WAAW,KAAK,MAAM;AAC3B,QAAI,KAAK,MAAM,mBAAmB,GAAG;AACnC,WAAK,aAAa;AAClB,UAAI,KAAK,WAAW,MAAM;AACxB,aAAK,UAAU,CAAC;AAAA,MAClB;AACA,WAAK,QAAQ,KAAK,uEAAuE;AAAA,IAC3F;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,QAAQ,OAAO;AACnB,SAAK,MAAM,YAAY;AACvB,UAAM,aAAa,KAAK,MAAM;AAC9B,UAAM,kBAAkB,KAAK,MAAM;AACnC,SAAK,MAAM,cAAc,UAAU,CAAC;AACpC,SAAK,MAAM,cAAc,SAAS,MAAM,MAAM;AAC9C,SAAK,MAAM,YAAY;AACvB,SAAK,MAAM,cAAc,YAAY,KAAK,IAAI,GAAG,KAAK,MAAM,cAAc,QAAQ,IAAI,CAAC,MAAM,EAAE,kBAAkB,CAAC;AAClH,SAAK,MAAM,cAAc,WAAW,KAAK,MAAM,WAAW;AAC1D,SAAK,MAAM,cAAc,aAAa,KAAK,MAAM,aAAa;AAC9D,eAAW,UAAU,KAAK,MAAM,cAAc,SAAS;AACrD,aAAO,eAAe,MAAM,OAAO;AACnC,aAAO,YAAY,MAAM,OAAO;AAAA,IAClC;AACA,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,WAAW;AACT,WAAO,KAAK,MAAM,gBAAgB,KAAK,KAAK,MAAM,gBAAgB;AAAA,EACpE;AAAA,EACA,YAAY,YAAY,QAAQ,SAAS,eAAe,OAAO,OAAO;AACpE,UAAM,WAAW,EAAE,IAAI,KAAK,MAAM,kBAAkB,YAAY,QAAQ,SAAS,MAAM;AACvF,UAAM,aAAa,YAAY,UAAU;AACzC,QAAI,cAAc,MAAM;AACtB,sBAAgB,WAAW;AAAA,IAC7B;AACA,QAAI,iBAAiB,MAAM;AACzB,eAAS,WAAW,CAAC,QAAQ;AAC3B,cAAM,IAAI,IAAI,CAAC,IAAI,OAAO;AACxB,cAAI,MAAM,MAAM;AACd,kBAAM,SAAS,QAAQ;AACvB,kBAAM,OAAO,oBAAoB,OAAO,MAAM,OAAO,KAAK;AAC1D,mBAAO,KAAK,WAAW,MAAM,OAAO,OAAO,OAAO,KAAK;AAAA,UACzD;AACA,iBAAO;AAAA,QACT,CAAC;AACD,eAAO,cAAc,IAAI,SAAS,IAAI,MAAM,IAAI,IAAI,OAAO,KAAK;AAAA,MAClE;AAAA,IACF;AACA,SAAK,MAAM,WAAW,KAAK,QAAQ;AAAA,EACrC;AAAA,EACA,KAAK,QAAQ;AACX,WAAO,OAAO;AACd,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,QAAI,KAAK,MAAM,kBAAkB,GAAG;AAClC,WAAK,MAAM,aAAa,CAAC;AAAA,IAC3B;AACA,SAAK,MAAM;AAAA,EACb;AAAA,EACA,UAAU;AACR,SAAK,MAAM;AAAA,EACb;AAAA,EACA,WAAW,MAAM;AACf,UAAM,YAAY;AAAA,MAChB,OAAO,CAAC;AAAA,MACR,MAAM;AAAA,MACN,IAAI,KAAK,MAAM;AAAA,IACjB;AACA,QAAI,MAAM;AACR,gBAAU,OAAO;AAAA,IACnB;AACA,SAAK,MAAM,WAAW,KAAK,SAAS;AACpC,SAAK,MAAM,cAAc;AAAA,EAC3B;AAAA,EACA,SAAS,QAAQ;AACf,UAAM,yBAAyB,sBAAsB,MAAM;AAC3D,UAAM,4BAA4B,IAAI,IAAI,uBAAuB,IAAI,CAAC,OAAO,GAAG,EAAE,CAAC;AACnF,aAAS,KAAK,GAAG,KAAK,KAAK,MAAM,YAAY,MAAM,QAAQ,MAAM;AAC/D,YAAM,UAAU,KAAK,MAAM,YAAY,MAAM;AAC7C,UAAI,CAAC,QAAQ,QAAQ,CAAC,0BAA0B,IAAI,QAAQ,EAAE,GAAG;AAC/D,gBAAQ,QAAQ;AAAA,MAClB;AAAA,IACF;AACA,UAAM,WAAW,KAAK,MAAM,WAAW,IAAI;AAC3C,SAAK,MAAM,cAAc,KAAK,MAAM,WAAW,WAAW,IAAI,OAAO,KAAK,MAAM,WAAW,KAAK,MAAM,WAAW,SAAS;AAC1H,2BAAuB,QAAQ,CAAC,YAAY;AAC1C,UAAI,CAAC,QAAQ,QAAQ,QAAQ,YAAY,SAAS,IAAI;AACpD,aAAK,MAAM,OAAO;AAAA,MACpB;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,UAAU,GAAG,IAAI,IAAI,mBAAmB,OAAO;AAC7C,WAAO,GAAG,SAAS,GAAG,MAAM,2CAA2C;AACvE,QAAI,MAAM,QAAQ,GAAG,UAAU,WAAW;AACxC,YAAM,IAAI,MAAM,0CAA0C,GAAG,QAAQ;AAAA,IACvE;AACA,UAAM,IAAI,KAAK,UAAU,MAAM,KAAK,UAAU,GAAG,MAAM,KAAK,QAAQ,GAAG,MAAM,KAAK,KAAK,WAAW,CAAC,CAAC;AACpG,WAAO,aAAa,QAAQ,MAAM,gDAAgD;AAClF,UAAM,eAAe,qBAAqB,KAAK,MAAM,YAAY,IAAI,CAAC;AACtE,QAAI,CAAC,oBAAoB,aAAa,WAAW,KAAK,GAAG,SAAS,GAAG;AACnE,YAAM,IAAI,MAAM,qIAAqI;AAAA,IACvJ;AACA,WAAO,KAAK,KAAK,YAAY,MAAM;AACjC,YAAM,yBAAyB,CAAC;AAChC,6BAAuB,EAAE,MAAM,MAAM,OAAO,KAAK,EAAE,KAAK,IAAI;AAC5D;AAAA,QACE;AAAA,QACA;AAAA,QACA,CAAC,OAAO,KAAK,KAAK,EAAE;AAAA,QACpB;AAAA,MACF;AACA,YAAM,SAAS,GAAG,IAAI,CAAC,MAAM,uBAAuB,EAAE,GAAG;AACzD,UAAI,KAAK,MAAM,kBAAkB,GAAG;AAClC,aAAK,MAAM,WAAW,QAAQ,CAACmB,UAAS;AACtC,qBAAW,WAAWA,MAAK,OAAO;AAChC,oBAAQ,QAAQ;AAAA,UAClB;AAAA,QACF,CAAC;AACD,aAAK,MAAM,aAAa;AAAA,MAC1B;AACA,aAAO,EAAE,OAAO,GAAG,OAAO,OAAO;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,WAAW,GAAG;AACZ,WAAO,WAAW,CAAC,GAAG,MAAM,mDAAmD;AAC/E,WAAO,IAAI,WAAW;AACpB,aAAO,OAAO,MAAM,CAAC,OAAO,cAAc,MAAM,GAAG,MAAM,kEAAkE;AAC3H,UAAI;AACJ,YAAM,WAAW,CAAC;AAClB,aAAO,QAAQ,CAAC,QAAQ,OAAO;AAC7B,iBAAS,MAAM;AAAA,MACjB,CAAC;AACD,YAAM,cAAc,CAAC,GAAG,SAAS;AAC/B,cAAM,EAAE,GAAG,CAAC,GAAG,QAAQ,IAAI,CAAC;AAC5B,eAAO,IAAI,iBAAiB,QAAQ,MAAM,4FAA4F;AACtI,eAAO,WAAW,IAAI,QAAQ,GAAG,MAAM,kGAAkG;AACzI,eAAO,IAAI;AAAA,MACb;AACA,YAAM,gBAAgB,CAAC,IAAI,UAAU;AACnC,cAAM,UAAU,IAAI,SAAS,IAAI,KAAK;AACtC,cAAM,SAAS,MAAM,QAAQ,OAAO,IAAI,UAAU,CAAC,OAAO;AAC1D,eAAO,OAAO,WAAW,OAAO,QAAQ,MAAM,qKAAqK;AACnN,eAAO,OAAO,MAAM,CAAC,OAAO,cAAc,MAAM,GAAG,MAAM,sIAAsI;AAC/L,cAAM,UAAU,CAAC;AACjB,eAAO,QAAQ,CAAC,OAAO,OAAO;AAC5B,kBAAQ,MAAM,MAAM;AAAA,QACtB,CAAC;AACD,eAAO;AAAA,MACT;AACA,aAAO,KAAK,cAAc;AAAA,QACxB;AAAA,QACA;AAAA,QACA,QAAQ;AAAA,MACV,CAAC;AAAA,IACH;AAAA,EACF;AAAA,EACA,SAAS,QAAQ;AACf,UAAM,OAAO,KAAK,MAAM,WAAW,IAAI,MAAM;AAC7C,WAAO,KAAK,QAAQ,SAAS,MAAM;AAAA,EACrC;AAAA,EACA,KAAK,QAAQ;AACX,UAAM,OAAO,KAAK,MAAM,WAAW,IAAI,MAAM;AAC7C,WAAO,KAAK,QAAQ,KAAK,MAAM;AAAA,EACjC;AAAA,EACA,UAAU,QAAQV,UAAS;AACzB,UAAM,OAAO,KAAK,MAAM,WAAW,IAAI,MAAM;AAC7C,WAAO,KAAK,QAAQ,UAAU,QAAQA,QAAO;AAAA,EAC/C;AAAA,EACA,MAAM,KAAK,OAAO;AAChB,UAAM,QAAQS,KAAI;AAClB,UAAM,aAAa,MAAM,KAAK,QAAQ,KAAK,KAAK;AAChD,eAAW,SAASA,KAAI,IAAI;AAC5B,WAAO;AAAA,EACT;AAAA,EACA,MAAM,QAAQ;AACZ,QAAI,KAAK,MAAM,eAAe,MAAM;AAClC,aAAO,UAAU,KAAK,MAAM,YAAY;AACxC,WAAK,MAAM,YAAY,MAAM,KAAK,MAAM;AAAA,IAC1C;AACA,WAAO;AAAA,EACT;AAAA,EACA,IAAI,sBAAsB;AACxB,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,QAAQ;AACN,SAAK;AACL,SAAK,MAAM,QAAQ;AACnB,SAAK,IAAI,MAAM;AACf,SAAK,QAAQ,IAAI,YAAY;AAC7B,eAAW,eAAe,KAAK,UAAU;AACvC,WAAK,yBAAyB,WAAW;AACzC,WAAK,SAAS,aAAa,QAAQ;AACnC,aAAO,KAAK,SAAS;AAAA,IACvB;AACA,SAAK,cAAc;AACnB,SAAK,kBAAkB;AACvB,SAAK,qBAAqB;AAAA,EAC5B;AACF;AACA,OAAO,eAAe;AACtB,OAAO,iBAAiB;AACxB,SAAS,KAAK,OAAO;AACnB,QAAM,SAAS,mBAAmB,cAAc,KAAK,GAAG,SAAS;AACjE,SAAO,OAAO,WAAW,QAAQ,OAAO,SAAS;AACnD;AACA,SAAS,kBAAkB;AACzB,QAAM,KAAK,mBAAmB;AAC9B,MAAI,GAAG,aAAa,MAAM;AACxB,UAAM,cAAc,IAAI,YAAY,EAAE;AACtC,OAAG,YAAY,IAAI,OAAO,WAAW;AAAA,EACvC;AACA,uBAAqB,GAAG,UAAU,GAAG;AACrC,mBAAiB,MAAM,GAAG,SAAS;AACnC,SAAO,GAAG;AACZ;AACA,IAAI,SAAS,gBAAgB;AAC7B,SAAS,IAAI,GAAG,GAAG;AACjB,QAAM,SAAS,EAAE,GAAG,EAAE;AACtB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AAGA,IAAI,sBAAsB,CAAC;AAC3BlB,UAAS,qBAAqB;AAAA,EAC5B,WAAW,MAAM;AAAA,EACjB,UAAU,MAAM;AAAA,EAChB,cAAc,MAAM;AACtB,CAAC;AACD,SAAS,sBAAsB;AAC7B,SAAO,OAAO,cAAc,eAAe,aAAa;AAC1D;AACA,IAAI;AACJ,SAAS,aAAa,OAAO;AAC3B,sBAAoB;AACtB;AACA,SAAS,SAAS,KAAK;AACrB,MAAI,sBAAsB,QAAQ;AAChC,WAAO;AAAA,EACT;AACA,MAAI,OAAO,oBAAoB,GAAG;AAChC,QAAI,CAAC,KAAK;AACR,YAAM;AAAA,IACR;AACA,QAAI,IAAI,YAAY,eAAe;AACjC,aAAO;AAAA,IACT;AACA,UAAM,IAAI,IAAI,aAAa,IAAI,WAAW,OAAO,WAAW,cAAc,OAAO,QAAQ;AACzF,QAAI,CAAC,GAAG;AACN,YAAM,SAAS;AACf,aAAO,OAAO,iBAAiB,OAAO,cAAc;AAAA,IACtD;AACA,WAAO,2TAA2T,KAAK,CAAC,KAAK,0kDAA0kD,KAAK,EAAE,OAAO,GAAG,CAAC,CAAC;AAAA,EAC56D;AACA,SAAO;AACT;AACA,SAAS,YAAY;AACnB,SAAO,OAAO,WAAW,eAAe,OAAO,YAAY,QAAQ,OAAO,sBAAsB;AAClG;AAGA,IAAI,OAAO,IAAI;AACf,KAAK,aAAa,SAAS,MAAM,OAAO,CAAC,eAAe;AACtD,MAAI,YAAY;AACd,YAAQ,KAAK,6IAA6I;AAAA,EAC5J;AACF,CAAC;AACD,KAAK,aAAa,cAAc,MAAM,UAAU,CAAC;AACjD,KAAK,aAAa,WAAW,MAAM,OAAO,YAAY,eAAe,OAAO,QAAQ,aAAa,eAAe,OAAO,QAAQ,SAAS,SAAS,WAAW;AAC5J,KAAK,aAAa,aAAa,MAAM,OAAO,cAAc,eAAe,aAAa,QAAQ,UAAU,aAAa,QAAQ,SAAS,KAAK,UAAU,SAAS,KAAK,aAAa,KAAK,UAAU,MAAM,CAAC;AACtM,KAAK,aAAa,QAAQ,MAAM,KAAK;AACrC,KAAK,aAAa,sCAAsC,MAAM,KAAK,QAAQ,OAAO,CAAC;AACnF,KAAK,aAAa,gCAAgC,MAAM,IAAI;AAC5D,KAAK,aAAa,WAAW,MAAM,KAAK;AACxC,KAAK,aAAa,gCAAgC,MAAM,IAAI;AAC5D,KAAK,aAAa,uBAAuB,MAAM,KAAK;AACpD,KAAK,aAAa,uBAAuB,MAAM,KAAK;AAGpD,SAAS,WAAW,KAAK,OAAO;AAC9B,MAAI,YAAY;AAChB,MAAI,aAAa,GAAG,GAAG;AACrB,WAAO,UAAU,WAAW,CAAC,IAAI,CAAC,IAAI,MAAM;AAAA,EAC9C;AACA,MAAI,CAAC,MAAM,QAAQ,GAAG,GAAG;AACvB,WAAO,CAAC;AAAA,EACV;AACA,QAAM,QAAQ,CAAC;AACf,SAAO,MAAM,QAAQ,SAAS,KAAK,aAAa,SAAS,KAAK,UAAU,UAAU;AAChF,UAAM,KAAK,UAAU,MAAM;AAC3B,gBAAY,UAAU;AAAA,EACxB;AACA,MAAI,MAAM,QAAQ,GAAG,KAAK,IAAI,EAAE,QAAQ,oCAAoC,GAAG;AAC7E,+BAA2B,KAAK,OAAO,CAAC,CAAC;AAAA,EAC3C;AACA,SAAO;AACT;AACA,SAAS,2BAA2B,KAAK,OAAO,SAAS;AACvD,YAAU,WAAW,CAAC;AACtB,MAAI,CAAC,MAAM,QAAQ,GAAG,KAAK,CAAC,aAAa,GAAG,GAAG;AAC7C,WAAO,MAAM,WAAW,GAAG,MAAM,eAAe,QAAQ,KAAK,IAAI,2DAA2D,MAAM,aAAa;AAC/I;AAAA,EACF;AACA,SAAO,MAAM,SAAS,GAAG,MAAM,eAAe,QAAQ,KAAK,IAAI,gDAAgD,IAAI,iBAAiB;AACpI,SAAO,IAAI,WAAW,MAAM,IAAI,MAAM,eAAe,QAAQ,KAAK,IAAI,kBAAkB,MAAM,wBAAwB,IAAI,iBAAiB;AAC3I,QAAM,WAAW,MAAM,MAAM,CAAC;AAC9B,WAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,+BAA2B,IAAI,KAAK,UAAU,QAAQ,OAAO,EAAE,CAAC;AAAA,EAClE;AACF;AACA,SAAS,YAAY,eAAe,aAAa,SAAS,cAAc;AACtE,MAAI,kBAAkB,qBAAqB;AACzC;AAAA,EACF;AACA,MAAI,iBAAiB,MAAM;AACzB,UAAM,IAAI,MAAM,gCAAgC;AAAA,EAClD;AACA,MAAI,kBAAkB,aAAa,kBAAkB,eAAe,kBAAkB,aAAa,gBAAgB,UAAU;AAC3H,UAAM,IAAI,MAAM,aAAa,uBAAuB,yBAAyB,iCAAiC,oBAAoB;AAAA,EACpI;AACF;AACA,SAAS,gBAAgB,GAAG,SAAS,cAAc,eAAe,WAAW;AAC3E,MAAI,aAAa,QAAQ;AACvB,gBAAY,cAAc,EAAE,OAAO,SAAS,YAAY;AACxD,WAAO;AAAA,EACT;AACA,MAAI,gBAAgB,WAAW,CAAC;AAChC,MAAI,kBAAkB,YAAY,CAAC,QAAQ,SAAS,SAAS,EAAE,QAAQ,YAAY,KAAK,GAAG;AACzF,oBAAgB;AAAA,EAClB;AACA,cAAY,cAAc,eAAe,SAAS,YAAY;AAC9D,MAAI,KAAK,QAAQ,CAAC,aAAa,CAAC,KAAK,CAAC,MAAM,QAAQ,CAAC,KAAK,OAAO,MAAM,YAAY,OAAO,MAAM,aAAa,OAAO,MAAM,UAAU;AAClI,UAAM,OAAO,KAAK,OAAO,SAAS,EAAE,YAAY;AAChD,UAAM,IAAI,MAAM,aAAa,uBAAuB,0DAA0D,OAAO;AAAA,EACvH;AACA,QAAM,gBAAgB,WAAW,GAAG,aAAa;AACjD,MAAI,CAAC,aAAa,CAAC,KAAK,CAAC,MAAM,QAAQ,CAAC,GAAG;AACzC,QAAI,CAAC,CAAC;AAAA,EACR;AACA,QAAM,iBAAiB;AACvB,QAAM,SAAS,kBAAkB,WAAW,aAAa,GAAG,aAAa,IAAI,QAAQ,GAAG,CAAC,GAAG,cAAc;AAC1G,SAAO,OAAO,WAAW,QAAQ,eAAe,aAAa;AAC/D;AACA,SAAS,qBAAqB,KAAK,SAAS,cAAc,eAAe,WAAW;AAClF,MAAI,CAAC,MAAM,QAAQ,GAAG,GAAG;AACvB,UAAM,IAAI,MAAM,YAAY,qBAAqB,yDAAyD;AAAA,EAC5G;AACA,QAAM,UAAU;AAChB,SAAO,QAAQ,IAAI,CAAC,IAAI,OAAO,gBAAgB,IAAI,GAAG,WAAW,OAAO,cAAc,YAAY,CAAC;AACrG;AAGA,IAAI,kBAAkB;AACtB,SAAS,GAAG,GAAG;AACb,QAAM,OAAO,OAAO,KAAK,CAAC;AAC1B,MAAI,KAAK,WAAW,GAAG;AACrB,UAAM,IAAI,MAAM,yGAAyG,KAAK,cAAc;AAAA,EAC9I;AACA,MAAI,SAAS,KAAK;AAClB,QAAM,KAAK,EAAE;AACb,MAAI,OAAO,SAAS,GAAG,GAAG;AACxB,aAAS,OAAO,UAAU,GAAG,OAAO,SAAS,CAAC;AAAA,EAChD;AACA,WAAS,SAAS;AAClB,QAAM,KAAK,IAAI,SAAS;AACtB,WAAO,WAAW,MAAM;AACxB,QAAI;AACF,YAAM,SAAS,GAAG,GAAG,IAAI;AACzB,UAAI,UAAU,MAAM,GAAG;AACrB,gBAAQ,MAAM,yCAAyC;AAAA,MACzD;AACA,aAAO,SAAS,MAAM;AACtB,aAAO;AAAA,IACT,SAAS,IAAP;AACA,aAAO,SAAS,IAAI;AACpB,YAAM;AAAA,IACR;AAAA,EACF;AACA,SAAO,eAAe,IAAI,QAAQ,EAAE,OAAO,QAAQ,cAAc,KAAK,CAAC;AACvE,SAAO;AACT;AAGA,SAAS,SAAS,OAAO,OAAO;AAC9B,QAAM,QAAQ,gBAAgB,OAAO,QAAQ,SAAS;AACtD,QAAM,QAAQ,gBAAgB,OAAO,QAAQ,SAAS;AACtD,oBAAkB,MAAM,OAAO,MAAM,OAAO,yBAAyB,MAAM,aAAa,MAAM,4CAA4C;AAC1I,QAAM,SAAS,EAAE,MAAM,OAAO,MAAM,MAAM;AAC1C,SAAO,OAAO,UAAU,SAAS,MAAM;AACzC;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,WAAW,QAAQ,OAAO,eAAe,OAAO;AACvD,MAAI,SAAS,MAAM;AACjB,YAAQ,WAAW,MAAM;AAAA,EAC3B;AACA,MAAI,UAAU,aAAa;AACzB,UAAM,IAAI,MAAM,kFAAkF;AAAA,EACpG;AACA,MAAI,CAAC,aAAa,MAAM,KAAK,CAAC,MAAM,QAAQ,MAAM,KAAK,OAAO,WAAW,YAAY,OAAO,WAAW,aAAa,OAAO,WAAW,UAAU;AAC9I,UAAM,IAAI,MAAM,0HAA0H;AAAA,EAC5I;AACA,MAAI,SAAS,MAAM;AACjB,uCAAmC,KAAK;AACxC,UAAM,eAAe,cAAc,KAAK;AACxC,UAAM,eAAe,cAAc,aAAa;AAChD,WAAO,iBAAiB,cAAc,MAAM,iCAAiC,kCAAkC,+BAA+B,cAAc;AAC5J,aAAS,KAAK,GAAG,KAAK,cAAc,QAAQ,EAAE,IAAI;AAChD,YAAM,WAAW,cAAc;AAC/B,YAAM,oBAAoB,OAAO,cAAc,SAAS,IAAI,aAAa,cAAc,MAAM,MAAM,EAAE,CAAC,IAAI;AAC1G,aAAO,cAAc,QAAQ,MAAM,OAAO,CAAC,mBAAmB,MAAM,gDAAgD,qDAAqD,UAAU;AAAA,IACrL;AAAA,EACF;AACA,MAAI,CAAC,aAAa,MAAM,KAAK,CAAC,MAAM,QAAQ,MAAM,GAAG;AACnD,aAAS,CAAC,MAAM;AAAA,EAClB;AACA,UAAQ,SAAS;AACjB,WAAS,UAAU,WAAW,aAAa,QAAQ,KAAK,IAAI,QAAQ,QAAQ,CAAC,GAAG,IAAI;AACpF,SAAO,OAAO,WAAW,QAAQ,OAAO,KAAK;AAC/C;AAGA,SAAS,OAAO,QAAQ,OAAO,OAAO;AACpC,QAAM,gBAAgB,WAAW,QAAQ,KAAK;AAC9C,SAAO,WAAW,QAAQ,OAAO,eAAe,KAAK;AACvD;AAGA,IAAI,uBAAuB;AAAA,EACzB,WAAW;AAAA,EACX,WAAW;AAAA,EACX,SAAS;AAAA,EACT,UAAU;AAAA,EACV,SAAS;AAAA,EACT,QAAQ;AAAA,EACR,aAAa;AACf;AAGA,IAAI,0BAA0B;AAC9B,eAAe,cAAc,SAAS,OAAO;AAC3C,QAAM,QAAQ,CAAC;AACf,QAAM,eAAe,CAAC;AACtB,QAAM,QAAQ,MAAM,QAAQ,OAAO,IAAI,QAAQ,IAAI,CAAC,YAAY,QAAQ,IAAI,IAAI,OAAO,KAAK,OAAO;AACnG,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,UAAM,OAAO,MAAM;AACnB,UAAM,KAAK,MAAM,QAAQ,OAAO,IAAI,QAAQ,IAAI,SAAS,QAAQ;AACjE,QAAI,GAAG,UAAU,aAAa,GAAG,UAAU,WAAW,GAAG,UAAU,UAAU,GAAG,UAAU,YAAY,GAAG,UAAU,aAAa;AAC9H,YAAM,IAAI,MAAM,gCAAgC,UAAU,GAAG,OAAO;AAAA,IACtE;AACA,UAAM,OAAO,EAAE,MAAM,OAAO,GAAG,OAAO,OAAO,GAAG,MAAM;AACtD,QAAI,GAAG,UAAU,UAAU;AACzB,YAAM,YAAY,IAAI,QAAQ,OAAO,YAAY;AAC/C,cAAM,OAAO,MAAM,GAAG,MAAM;AAC5B,cAAM,gBAAgB,KAAK,OAAO,CAAC,IAAI,MAAM,KAAK,EAAE,QAAQ,CAAC,IAAI,0BAA0B,KAAK;AAChG,cAAM,QAAQ,IAAI,WAAW,aAAa;AAC1C,YAAI,SAAS;AACb,iBAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,gBAAM,MAAM,KAAK;AACjB,gBAAM,gBAAgB,IAAI,WAAW,IAAI,YAAY,CAAC,IAAI,MAAM,CAAC,EAAE,MAAM;AACzE,gBAAM,IAAI,eAAe,MAAM;AAC/B,oBAAU;AACV,gBAAM,IAAI,KAAK,MAAM;AACrB,oBAAU,IAAI;AAAA,QAChB;AACA,gBAAQ,KAAK;AAAA,MACf,CAAC;AACD,mBAAa,KAAK,SAAS;AAAA,IAC7B,OAAO;AACL,mBAAa,KAAK,GAAG,KAAK,CAAC;AAAA,IAC7B;AACA,QAAI,SAAS,MAAM;AACjB,WAAK,QAAQ;AAAA,IACf;AACA,UAAM,KAAK,IAAI;AAAA,EACjB;AACA,QAAM,eAAe,MAAM,QAAQ,IAAI,YAAY;AACnD,SAAO,EAAE,MAAM,uBAAuB,YAAY,GAAG,MAAM;AAC7D;AACA,SAAS,cAAc,SAAS,OAAO;AACrC,QAAM,MAAM,CAAC;AACb,MAAI;AACJ,MAAI,SAAS;AACb,aAAW,QAAQ,OAAO;AACxB,UAAM,OAAO,KAAK;AAClB,UAAM,QAAQ,KAAK;AACnB,UAAM,QAAQ,KAAK;AACnB,UAAMG,QAAO,cAAc,KAAK;AAChC,QAAI;AACJ,QAAI,kBAAkB,MAAM;AAC1B,YAAM,eAAe,KAAK;AAC1B,UAAI,aAAa,UAAU,WAAW,aAAa,UAAU,UAAU;AACrE,YAAI,EAAE,SAAS,gBAAgB,WAAW,eAAe;AACvD,gBAAM,IAAI,MAAM,UAAU,KAAK,0BAA0B,aAAa,0DAA0D;AAAA,QAClI;AAAA,MACF,WAAW,aAAa,UAAU,WAAW;AAC3C,YAAI,UAAU,WAAW;AACvB,gBAAM,IAAI,MAAM,UAAU,KAAK,0BAA0B,aAAa,yDAAyD,QAAQ;AAAA,QACzI;AAAA,MACF,OAAO;AACL,cAAM,IAAI,MAAM,UAAU,KAAK,uCAAuC,aAAa,6EAA6E;AAAA,MAClK;AACA,YAAM,yBAAyB,qBAAqB,aAAa;AACjE,YAAM,aAAa,QAAQ,MAAM,QAAQ,SAASA,QAAO,sBAAsB;AAC/E,YAAM,iBAAiB,aAAa,UAAU,UAAU,IAAI,WAAW,UAAU,IAAI,IAAI,YAAY,UAAU;AAC/G,UAAI,UAAU,WAAW;AACvB,YAAI,aAAa,UAAU,WAAW,aAAa,UAAU,UAAU;AACrE,mBAAS,IAAI,aAAa,eAAe,MAAM;AAC/C,mBAAS,KAAK,GAAG,KAAK,eAAe,QAAQ,MAAM;AACjD,kBAAM,IAAI,eAAe;AACzB,mBAAO,MAAM,IAAI,aAAa,QAAQ,aAAa;AAAA,UACrD;AAAA,QACF,WAAW,aAAa,UAAU,WAAW;AAC3C,cAAI,kBAAkB,QAAQ;AAC5B,4BAAgB,kBAAkB;AAAA,UACpC;AACA,mBAAS,cAAc,cAAc;AAAA,QACvC,OAAO;AACL,gBAAM,IAAI,MAAM,iCAAiC,aAAa,gCAAgC;AAAA,QAChG;AAAA,MACF,WAAW,UAAU,SAAS;AAC5B,YAAI,aAAa,UAAU,WAAW,aAAa,UAAU,UAAU;AACrE,gBAAM,IAAI,MAAM,iCAAiC,aAAa,8BAA8B;AAAA,QAC9F;AACA,iBAAS,IAAI,WAAW,eAAe,MAAM;AAC7C,iBAAS,KAAK,GAAG,KAAK,eAAe,QAAQ,MAAM;AACjD,gBAAM,IAAI,eAAe;AACzB,iBAAO,MAAM,KAAK,MAAM,IAAI,aAAa,QAAQ,aAAa,GAAG;AAAA,QACnE;AAAA,MACF,OAAO;AACL,cAAM,IAAI,MAAM,gCAAgC,UAAU,OAAO;AAAA,MACnE;AACA,gBAAUA,QAAO;AAAA,IACnB,WAAW,UAAU,UAAU;AAC7B,YAAMkB,SAAQ,cAAc,KAAK,KAAK;AACtC,eAAS,CAAC;AACV,eAAS,KAAK,GAAG,KAAKA,QAAO,MAAM;AACjC,cAAM,aAAa,IAAI,YAAY,QAAQ,MAAM,QAAQ,SAAS,uBAAuB,CAAC,EAAE;AAC5F,kBAAU;AACV,cAAM,QAAQ,IAAI,WAAW,QAAQ,MAAM,QAAQ,SAAS,UAAU,CAAC;AACvE,eAAO,KAAK,KAAK;AACjB,kBAAU;AAAA,MACZ;AAAA,IACF,OAAO;AACL,YAAM,cAAc,qBAAqB;AACzC,YAAM,aAAa,QAAQ,MAAM,QAAQ,SAASlB,QAAO,WAAW;AACpE,UAAI,UAAU,WAAW;AACvB,iBAAS,IAAI,aAAa,UAAU;AAAA,MACtC,WAAW,UAAU,SAAS;AAC5B,iBAAS,IAAI,WAAW,UAAU;AAAA,MACpC,WAAW,UAAU,QAAQ;AAC3B,iBAAS,IAAI,WAAW,UAAU;AAAA,MACpC,WAAW,UAAU,aAAa;AAChC,iBAAS,IAAI,aAAa,UAAU;AACpC,cAAM,QAAQ,IAAI,aAAa,OAAO,SAAS,CAAC;AAChD,cAAM,SAAS,IAAI,aAAa,OAAO,SAAS,CAAC;AACjD,iBAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,gBAAM,MAAM,OAAO,KAAK;AACxB,iBAAO,MAAM,OAAO,KAAK,IAAI;AAAA,QAC/B;AACA,cAAM,aAAa,OAAO,OAAO,OAAO,SAAS;AACjD,cAAM,cAAc,OAAO,QAAQ,OAAO,SAAS;AACnD,YAAI,QAAQ,QAAQ,YAAY,WAAW;AAC3C,mBAAW,QAAQ;AACnB,oBAAY,QAAQ;AAAA,MACtB,OAAO;AACL,cAAM,IAAI,MAAM,gCAAgC,UAAU,OAAO;AAAA,MACnE;AACA,gBAAUA,QAAO;AAAA,IACnB;AACA,QAAI,UAAU,aAAa;AACzB,UAAI,QAAQ,OAAO,QAAQ,OAAO,KAAK;AAAA,IACzC;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,uBAAuB,IAAI;AAClC,MAAI,OAAO,MAAM;AACf,UAAM,IAAI,MAAM,wBAAwB,KAAK,UAAU,EAAE,GAAG;AAAA,EAC9D;AACA,MAAI,kBAAkB;AACtB,QAAM,eAAe,CAAC;AACtB,KAAG,QAAQ,CAAC,MAAM;AAChB,uBAAmB,EAAE;AACrB,iBAAa,KAAK,EAAE,eAAe,EAAE,OAAO,aAAa,IAAI,IAAI,EAAE,YAAY,CAAC,CAAC;AACjF,QAAI,EAAE,aAAa,gBAAgB,aAAa,cAAc,aAAa,aAAa;AACtF,YAAM,IAAI,MAAM,mCAAmC,EAAE,YAAY,MAAM;AAAA,IACzE;AAAA,EACF,CAAC;AACD,QAAM,IAAI,IAAI,WAAW,eAAe;AACxC,MAAI,SAAS;AACb,eAAa,QAAQ,CAAC,MAAM;AAC1B,MAAE,IAAI,IAAI,WAAW,EAAE,MAAM,GAAG,MAAM;AACtC,cAAU,EAAE;AAAA,EACd,CAAC;AACD,SAAO,EAAE;AACX;AACA,IAAI,gBAAgB,OAAO,WAAW,gBAAgB,OAAO,SAAS,eAAe,OAAO,SAAS,eAAe,OAAO,SAAS;AACpI,SAAS,iBAAiB,KAAK;AAC7B,MAAI,eAAe;AACjB,WAAO,OAAO,WAAW,GAAG;AAAA,EAC9B;AACA,SAAO,IAAI,KAAK,CAAC,GAAG,CAAC,EAAE;AACzB;AACA,SAAS,0BAA0B,SAAS;AAC1C,MAAI,eAAe;AACjB,WAAO,OAAO,KAAK,OAAO,EAAE,SAAS,QAAQ;AAAA,EAC/C;AACA,QAAM,MAAM,IAAI,WAAW,OAAO;AAClC,MAAI,KAAK;AACT,WAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,KAAK,IAAI,MAAM;AAC/C,UAAM,OAAO,aAAa,IAAI,GAAG;AAAA,EACnC;AACA,SAAO,KAAK,EAAE;AAChB;AACA,SAAS,0BAA0B,KAAK;AACtC,MAAI,eAAe;AACjB,UAAM,MAAM,OAAO,KAAK,KAAK,QAAQ;AACrC,WAAO,IAAI,OAAO,MAAM,IAAI,YAAY,IAAI,aAAa,IAAI,UAAU;AAAA,EACzE;AACA,QAAM,KAAK,KAAK,GAAG;AACnB,QAAM,UAAU,IAAI,WAAW,GAAG,MAAM;AACxC,WAAS,KAAK,GAAG,KAAK,GAAG,QAAQ,EAAE,IAAI;AACrC,YAAQ,IAAI,CAAC,GAAG,WAAW,EAAE,CAAC,GAAG,EAAE;AAAA,EACrC;AACA,SAAO,QAAQ;AACjB;AACA,SAAS,wBAAwB,SAAS;AACxC,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO,QAAQ;AAAA,EACjB;AACA,MAAI,kBAAkB;AACtB,UAAQ,QAAQ,CAAC,YAAY;AAC3B,uBAAmB,QAAQ;AAAA,EAC7B,CAAC;AACD,QAAM,OAAO,IAAI,WAAW,eAAe;AAC3C,MAAI,SAAS;AACb,UAAQ,QAAQ,CAAC,YAAY;AAC3B,SAAK,IAAI,IAAI,WAAW,OAAO,GAAG,MAAM;AACxC,cAAU,QAAQ;AAAA,EACpB,CAAC;AACD,SAAO,KAAK;AACd;AACA,SAAS,SAAS,MAAM;AACtB,QAAM,YAAY;AAClB,SAAO,KAAK,KAAK;AACjB,SAAO,KAAK,SAAS,SAAS,GAAG;AAC/B,WAAO,KAAK,MAAM,GAAG,KAAK,SAAS,CAAC;AAAA,EACtC;AACA,QAAM,QAAQ,KAAK,MAAM,SAAS;AAClC,SAAO,MAAM,MAAM,SAAS;AAC9B;AACA,SAAS,8BAA8B,WAAW,UAAU;AAC1D,QAAM,SAAS;AAAA,IACb,eAAe,UAAU;AAAA,IACzB,QAAQ,UAAU;AAAA,IAClB,aAAa,UAAU;AAAA,IACvB,aAAa,UAAU;AAAA,IACvB,iBAAiB;AAAA,EACnB;AACA,MAAI,UAAU,aAAa,MAAM;AAC/B,WAAO,YAAY,UAAU;AAAA,EAC/B;AACA,MAAI,UAAU,uBAAuB,MAAM;AACzC,WAAO,sBAAsB,UAAU;AAAA,EACzC;AACA,MAAI,UAAU,oBAAoB,MAAM;AACtC,WAAO,mBAAmB,UAAU;AAAA,EACtC;AACA,MAAI,UAAU,kBAAkB,MAAM;AACpC,WAAO,iBAAiB,UAAU;AAAA,EACpC;AACA,SAAO;AACT;AACA,eAAe,yBAAyB,WAAW,cAAc;AAC/D,QAAM,iBAAiB;AAAA,IACrB,eAAe,UAAU;AAAA,IACzB,QAAQ,UAAU;AAAA,IAClB,aAAa,UAAU;AAAA,IACvB,aAAa,UAAU;AAAA,EACzB;AACA,MAAI,UAAU,kBAAkB,MAAM;AACpC,mBAAe,iBAAiB,UAAU;AAAA,EAC5C;AACA,MAAI,UAAU,mBAAmB,MAAM;AACrC,UAAM,CAAC,aAAa,UAAU,IAAI,MAAM,aAAa,UAAU,eAAe;AAC9E,mBAAe,cAAc;AAC7B,mBAAe,aAAa;AAAA,EAC9B;AACA,MAAI,UAAU,aAAa,MAAM;AAC/B,mBAAe,YAAY,UAAU;AAAA,EACvC;AACA,MAAI,UAAU,uBAAuB,MAAM;AACzC,mBAAe,sBAAsB,UAAU;AAAA,EACjD;AACA,MAAI,UAAU,oBAAoB,MAAM;AACtC,mBAAe,mBAAmB,UAAU;AAAA,EAC9C;AACA,SAAO;AACT;AACA,SAAS,6BAA6B,gBAAgB;AACpD,MAAI,eAAe,yBAAyB,aAAa;AACvD,UAAM,IAAI,MAAM,qDAAqD;AAAA,EACvE;AACA,SAAO;AAAA,IACL,WAAW,IAAI,KAAK;AAAA,IACpB,mBAAmB;AAAA,IACnB,oBAAoB,eAAe,iBAAiB,OAAO,IAAI,iBAAiB,KAAK,UAAU,eAAe,aAAa,CAAC;AAAA,IAC5H,kBAAkB,eAAe,eAAe,OAAO,IAAI,iBAAiB,KAAK,UAAU,eAAe,WAAW,CAAC;AAAA,IACtH,iBAAiB,eAAe,cAAc,OAAO,IAAI,eAAe,WAAW;AAAA,EACrF;AACF;AACA,SAAS,6BAA6B;AACpC,QAAM,kBAAkB,CAAC,OAAO;AAC9B,QAAI,IAAI,MAAM;AACd,QAAI,KAAK;AACT,YAAQ,IAAI,aAAa,GAAG;AAC1B,YAAM;AACN,YAAM;AAAA,IACR;AACA,SAAK,CAAC;AACN,UAAM;AACN,WAAO,IAAI;AAAA,EACb;AACA,QAAM,eAAe,IAAI,YAAY,IAAI;AACzC,eAAa,KAAK;AAClB,WAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,iBAAa,MAAM,gBAAgB,EAAE;AAAA,EACvC;AACA,WAAS,KAAK,MAAM,KAAK,MAAM,MAAM;AACnC,iBAAa,MAAM,aAAa,KAAK,QAAQ;AAAA,EAC/C;AACA,SAAO;AACT;AACA,SAAS,8BAA8B;AACrC,QAAM,gBAAgB,IAAI,YAAY,EAAE;AACxC,gBAAc,KAAK;AACnB,gBAAc,MAAM;AACpB,gBAAc,MAAM;AACpB,gBAAc,MAAM;AACpB,WAAS,KAAK,GAAG,KAAK,IAAI,MAAM;AAC9B,kBAAc,MAAM,MAAM;AAAA,EAC5B;AACA,WAAS,KAAK,IAAI,KAAK,IAAI,MAAM;AAC/B,kBAAc,MAAM,cAAc,KAAK,MAAM;AAAA,EAC/C;AACA,SAAO;AACT;AACA,SAAS,4BAA4B;AACnC,QAAM,cAAc,IAAI,YAAY,EAAE;AACtC,WAAS,KAAK,GAAG,KAAK,IAAI,MAAM;AAC9B,gBAAY,MAAM;AAAA,EACpB;AACA,cAAY,KAAK,YAAY,MAAM;AACnC,SAAO;AACT;AACA,SAAS,oBAAoB;AAC3B,QAAM,eAAe,2BAA2B;AAChD,QAAM,gBAAgB,4BAA4B;AAClD,QAAM,cAAc,0BAA0B;AAC9C,SAAO,CAAC,mBAAmB;AACzB,UAAM,UAAU,IAAI,YAAY,IAAI,eAAe,MAAM;AACzD,UAAM,mBAAmB,IAAI,YAAY,OAAO;AAChD,aAASS,SAAQ,GAAGA,SAAQ,eAAe,QAAQA,UAAS;AAC1D,YAAM,cAAc,eAAeA;AACnC,YAAM,cAAc,aAAa,YAAY,eAAe,OAAO,cAAc,SAAS,cAAc,eAAe;AACvH,uBAAiBA,UAAS;AAAA,IAC5B;AACA,WAAO,IAAI,aAAa,OAAO;AAAA,EACjC;AACF;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,cAAc;AACZ,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc,CAAC;AAAA,EACtB;AAAA,EACA,OAAO,cAAc;AACnB,QAAI,iBAAiB,YAAY,MAAM;AACrC,uBAAiB,WAAW,IAAI,iBAAiB;AAAA,IACnD;AACA,WAAO,iBAAiB;AAAA,EAC1B;AAAA,EACA,OAAO,mBAAmB,YAAY;AACpC,qBAAiB,YAAY,EAAE,YAAY,KAAK,UAAU;AAAA,EAC5D;AAAA,EACA,OAAO,mBAAmB,YAAY;AACpC,qBAAiB,YAAY,EAAE,YAAY,KAAK,UAAU;AAAA,EAC5D;AAAA,EACA,OAAO,gBAAgB,KAAK;AAC1B,WAAO,iBAAiB,YAAY,KAAK,MAAM;AAAA,EACjD;AAAA,EACA,OAAO,gBAAgB,KAAK,aAAa;AACvC,WAAO,iBAAiB,YAAY,KAAK,QAAQ,WAAW;AAAA,EAC9D;AAAA,EACA,OAAO,YAAY,KAAK,aAAa,aAAa;AAChD,UAAM,gBAAgB,CAAC;AACvB,UAAM,UAAU,gBAAgB,SAAS,iBAAiB,YAAY,EAAE,cAAc,iBAAiB,YAAY,EAAE;AACrH,YAAQ,QAAQ,CAAC,WAAW;AAC1B,YAAM,UAAU,OAAO,KAAK,WAAW;AACvC,UAAI,YAAY,MAAM;AACpB,sBAAc,KAAK,OAAO;AAAA,MAC5B;AAAA,IACF,CAAC;AACD,WAAO;AAAA,EACT;AACF;AACA,IAAI,qBAAqB,CAAC,eAAe,iBAAiB,mBAAmB,UAAU;AACvF,IAAI,qBAAqB,CAAC,eAAe,iBAAiB,mBAAmB,UAAU;AACvF,IAAI,kBAAkB,CAAC,QAAQ,iBAAiB,gBAAgB,GAAG;AACnE,IAAI,kBAAkB,CAAC,KAAK,gBAAgB,iBAAiB,gBAAgB,KAAK,WAAW;AAG7F,IAAI,gBAAgB;AACpB,IAAI,mBAAmB;AACvB,IAAI,mBAAmB;AACvB,IAAI,kBAAkB;AACtB,SAAS,sBAAsB;AAC7B,MAAI,CAAC,IAAI,EAAE,QAAQ,YAAY,GAAG;AAChC,UAAM,IAAI,MAAM,yFAAyF;AAAA,EAC3G;AACA,QAAM,YAAY,OAAO,WAAW,cAAc,OAAO;AACzD,QAAM,UAAU,UAAU,aAAa,UAAU,gBAAgB,UAAU,mBAAmB,UAAU,eAAe,UAAU;AACjI,MAAI,WAAW,MAAM;AACnB,UAAM,IAAI,MAAM,2DAA2D;AAAA,EAC7E;AACA,SAAO;AACT;AACA,SAAS,cAAc,aAAa;AAClC,QAAM,KAAK,YAAY;AACvB,KAAG,kBAAkB,kBAAkB,EAAE,SAAS,YAAY,CAAC;AAC/D,KAAG,kBAAkB,iBAAiB,EAAE,SAAS,YAAY,CAAC;AAChE;AACA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,WAAW;AACrB,SAAK,YAAY,oBAAoB;AACrC,QAAI,aAAa,QAAQ,CAAC,WAAW;AACnC,YAAM,IAAI,MAAM,gEAAgE;AAAA,IAClF;AACA,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,MAAM,KAAK,gBAAgB;AACzB,QAAI,eAAe,yBAAyB,aAAa;AACvD,YAAM,IAAI,MAAM,0FAA0F;AAAA,IAC5G;AACA,WAAO,KAAK,eAAe,KAAK,WAAW,cAAc;AAAA,EAC3D;AAAA,EACA,MAAM,OAAO;AACX,WAAO,KAAK,eAAe,KAAK,SAAS;AAAA,EAC3C;AAAA,EACA,eAAe,WAAW,gBAAgB;AACxC,WAAO,IAAI,QAAQ,CAAC,SAAS,WAAW;AACtC,YAAM,cAAc,KAAK,UAAU,KAAK,eAAe,gBAAgB;AACvE,kBAAY,kBAAkB,MAAM,cAAc,WAAW;AAC7D,kBAAY,YAAY,MAAM;AAC5B,cAAM,KAAK,YAAY;AACvB,YAAI,kBAAkB,MAAM;AAC1B,gBAAM,UAAU,GAAG,YAAY,kBAAkB,UAAU;AAC3D,gBAAM,aAAa,QAAQ,YAAY,gBAAgB;AACvD,gBAAM,aAAa,WAAW,IAAI,KAAK,SAAS;AAChD,qBAAW,YAAY,MAAM;AAC3B,gBAAI,WAAW,UAAU,MAAM;AAC7B,iBAAG,MAAM;AACT,qBAAO,OAAO,IAAI,MAAM,gCAAgC,KAAK,0BAA0B,CAAC;AAAA,YAC1F,OAAO;AACL,sBAAQ,WAAW,OAAO,cAAc;AAAA,YAC1C;AAAA,UACF;AACA,qBAAW,UAAU,CAAC,UAAU;AAC9B,eAAG,MAAM;AACT,mBAAO,OAAO,WAAW,KAAK;AAAA,UAChC;AACA,kBAAQ,aAAa,MAAM,GAAG,MAAM;AAAA,QACtC,OAAO;AACL,gBAAM,qBAAqB,6BAA6B,cAAc;AACtE,gBAAM,SAAS,GAAG,YAAY,iBAAiB,WAAW;AAC1D,cAAI,YAAY,OAAO,YAAY,eAAe;AAClD,gBAAM,iBAAiB,UAAU,IAAI,EAAE,WAAW,KAAK,WAAW,mBAAmB,CAAC;AACtF,cAAI;AACJ,yBAAe,YAAY,MAAM;AAC/B,sBAAU,GAAG,YAAY,kBAAkB,WAAW;AACtD,kBAAM,aAAa,QAAQ,YAAY,gBAAgB;AACvD,kBAAM,kBAAkB,WAAW,IAAI;AAAA,cACrC,WAAW,KAAK;AAAA,cAChB;AAAA,cACA;AAAA,YACF,CAAC;AACD,4BAAgB,YAAY,MAAM,QAAQ,EAAE,mBAAmB,CAAC;AAChE,4BAAgB,UAAU,CAAC,UAAU;AACnC,0BAAY,OAAO,YAAY,eAAe;AAC9C,oBAAM,oBAAoB,UAAU,OAAO,KAAK,SAAS;AACzD,gCAAkB,YAAY,MAAM;AAClC,mBAAG,MAAM;AACT,uBAAO,OAAO,gBAAgB,KAAK;AAAA,cACrC;AACA,gCAAkB,UAAU,CAAC,WAAW;AACtC,mBAAG,MAAM;AACT,uBAAO,OAAO,gBAAgB,KAAK;AAAA,cACrC;AAAA,YACF;AAAA,UACF;AACA,yBAAe,UAAU,CAAC,UAAU;AAClC,eAAG,MAAM;AACT,mBAAO,OAAO,eAAe,KAAK;AAAA,UACpC;AACA,iBAAO,aAAa,MAAM;AACxB,gBAAI,WAAW,MAAM;AACnB,iBAAG,MAAM;AAAA,YACX,OAAO;AACL,sBAAQ,aAAa,MAAM,GAAG,MAAM;AAAA,YACtC;AAAA,UACF;AAAA,QACF;AAAA,MACF;AACA,kBAAY,UAAU,CAAC,UAAU,OAAO,YAAY,KAAK;AAAA,IAC3D,CAAC;AAAA,EACH;AACF;AACA,iBAAiB,aAAa;AAC9B,IAAI,kBAAkB,CAAC,QAAQ;AAC7B,MAAI,CAAC,IAAI,EAAE,QAAQ,YAAY,GAAG;AAChC,WAAO;AAAA,EACT,OAAO;AACL,QAAI,CAAC,MAAM,QAAQ,GAAG,KAAK,IAAI,WAAW,iBAAiB,UAAU,GAAG;AACtE,aAAO,iBAAiB,IAAI,MAAM,iBAAiB,WAAW,MAAM,CAAC;AAAA,IACvE,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AACF;AACA,iBAAiB,mBAAmB,eAAe;AACnD,iBAAiB,mBAAmB,eAAe;AACnD,SAAS,iBAAiB,WAAW;AACnC,SAAO,IAAI,iBAAiB,SAAS;AACvC;AACA,SAAS,iBAAiB,KAAK;AAC7B,SAAO,IAAI,WAAW,iBAAiB,UAAU,IAAI,IAAI,MAAM,iBAAiB,WAAW,MAAM,IAAI;AACvG;AACA,IAAI,0BAA0B,MAAM;AAAA,EAClC,cAAc;AACZ,SAAK,YAAY,oBAAoB;AAAA,EACvC;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,IAAI,QAAQ,CAAC,SAAS,WAAW;AACtC,YAAM,cAAc,KAAK,UAAU,KAAK,eAAe,gBAAgB;AACvE,kBAAY,kBAAkB,MAAM,cAAc,WAAW;AAC7D,kBAAY,YAAY,MAAM;AAC5B,cAAM,KAAK,YAAY;AACvB,cAAM,KAAK,GAAG,YAAY,iBAAiB,UAAU;AACrD,cAAM,QAAQ,GAAG,YAAY,eAAe;AAC5C,cAAM,oBAAoB,MAAM,OAAO;AACvC,0BAAkB,YAAY,MAAM;AAClC,gBAAM,MAAM,CAAC;AACb,qBAAW,QAAQ,kBAAkB,QAAQ;AAC3C,gBAAI,KAAK,aAAa,KAAK;AAAA,UAC7B;AACA,kBAAQ,GAAG;AAAA,QACb;AACA,0BAAkB,UAAU,CAAC,UAAU;AACrC,aAAG,MAAM;AACT,iBAAO,OAAO,kBAAkB,KAAK;AAAA,QACvC;AACA,WAAG,aAAa,MAAM,GAAG,MAAM;AAAA,MACjC;AACA,kBAAY,UAAU,CAAC,UAAU,OAAO,YAAY,KAAK;AAAA,IAC3D,CAAC;AAAA,EACH;AAAA,EACA,MAAM,YAAY,MAAM;AACtB,WAAO,iBAAiB,IAAI;AAC5B,WAAO,IAAI,QAAQ,CAAC,SAAS,WAAW;AACtC,YAAM,cAAc,KAAK,UAAU,KAAK,eAAe,gBAAgB;AACvE,kBAAY,kBAAkB,MAAM,cAAc,WAAW;AAC7D,kBAAY,YAAY,MAAM;AAC5B,cAAM,KAAK,YAAY;AACvB,cAAM,SAAS,GAAG,YAAY,iBAAiB,WAAW;AAC1D,cAAM,YAAY,OAAO,YAAY,eAAe;AACpD,cAAM,iBAAiB,UAAU,IAAI,IAAI;AACzC,YAAI;AACJ,uBAAe,YAAY,MAAM;AAC/B,cAAI,eAAe,UAAU,MAAM;AACjC,eAAG,MAAM;AACT,mBAAO,OAAO,IAAI,MAAM,gCAAgC,qBAAqB,CAAC;AAAA,UAChF,OAAO;AACL,kBAAM,oBAAoB,UAAU,OAAO,IAAI;AAC/C,kBAAM,kBAAkB,MAAM;AAC5B,wBAAU,GAAG,YAAY,kBAAkB,WAAW;AACtD,oBAAM,aAAa,QAAQ,YAAY,gBAAgB;AACvD,oBAAM,qBAAqB,WAAW,OAAO,IAAI;AACjD,iCAAmB,YAAY,MAAM,QAAQ,eAAe,OAAO,kBAAkB;AACrF,iCAAmB,UAAU,CAAC,UAAU,OAAO,eAAe,KAAK;AAAA,YACrE;AACA,8BAAkB,YAAY;AAC9B,8BAAkB,UAAU,CAAC,UAAU;AACrC,8BAAgB;AAChB,iBAAG,MAAM;AACT,qBAAO,OAAO,eAAe,KAAK;AAAA,YACpC;AAAA,UACF;AAAA,QACF;AACA,uBAAe,UAAU,CAAC,UAAU;AAClC,aAAG,MAAM;AACT,iBAAO,OAAO,eAAe,KAAK;AAAA,QACpC;AACA,eAAO,aAAa,MAAM;AACxB,cAAI,WAAW,MAAM;AACnB,eAAG,MAAM;AAAA,UACX,OAAO;AACL,oBAAQ,aAAa,MAAM,GAAG,MAAM;AAAA,UACtC;AAAA,QACF;AAAA,MACF;AACA,kBAAY,UAAU,CAAC,UAAU,OAAO,YAAY,KAAK;AAAA,IAC3D,CAAC;AAAA,EACH;AACF;AAGA,IAAI,iBAAiB;AACrB,IAAI,cAAc;AAClB,IAAI,cAAc;AAClB,IAAI,wBAAwB;AAC5B,IAAI,sBAAsB;AAC1B,IAAI,qBAAqB;AACzB,IAAI,wBAAwB;AAC5B,SAAS,aAAa,MAAM;AAC1B,SAAO;AAAA,IACL,MAAM,CAAC,aAAa,MAAM,WAAW,EAAE,KAAK,cAAc;AAAA,IAC1D,UAAU,CAAC,aAAa,MAAM,qBAAqB,EAAE,KAAK,cAAc;AAAA,IACxE,aAAa,CAAC,aAAa,MAAM,mBAAmB,EAAE,KAAK,cAAc;AAAA,IACzE,YAAY,CAAC,aAAa,MAAM,kBAAkB,EAAE,KAAK,cAAc;AAAA,IACvE,eAAe,CAAC,aAAa,MAAM,qBAAqB,EAAE,KAAK,cAAc;AAAA,EAC/E;AACF;AACA,SAAS,YAAY,MAAM;AACzB,aAAW,OAAO,OAAO,OAAO,IAAI,GAAG;AACrC,WAAO,aAAa,WAAW,GAAG;AAAA,EACpC;AACF;AACA,SAAS,oBAAoB,KAAK;AAChC,QAAM,QAAQ,IAAI,MAAM,cAAc;AACtC,MAAI,MAAM,SAAS,GAAG;AACpB,UAAM,IAAI,MAAM,uBAAuB,KAAK;AAAA,EAC9C;AACA,SAAO,MAAM,MAAM,GAAG,MAAM,SAAS,CAAC,EAAE,KAAK,cAAc;AAC7D;AACA,SAAS,kBAAkB,KAAK;AAC9B,SAAO,IAAI,WAAW,oBAAoB,UAAU,IAAI,IAAI,MAAM,oBAAoB,WAAW,MAAM,IAAI;AAC7G;AACA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,WAAW;AACrB,QAAI,CAAC,IAAI,EAAE,QAAQ,YAAY,KAAK,OAAO,WAAW,eAAe,OAAO,OAAO,iBAAiB,aAAa;AAC/G,YAAM,IAAI,MAAM,yDAAyD;AAAA,IAC3E;AACA,SAAK,KAAK,OAAO;AACjB,QAAI,aAAa,QAAQ,CAAC,WAAW;AACnC,YAAM,IAAI,MAAM,oEAAoE;AAAA,IACtF;AACA,SAAK,YAAY;AACjB,SAAK,OAAO,aAAa,KAAK,SAAS;AAAA,EACzC;AAAA,EACA,MAAM,KAAK,gBAAgB;AACzB,QAAI,eAAe,yBAAyB,aAAa;AACvD,YAAM,IAAI,MAAM,0FAA0F;AAAA,IAC5G,OAAO;AACL,YAAM,WAAW,KAAK,UAAU,eAAe,aAAa;AAC5D,YAAM,cAAc,KAAK,UAAU,eAAe,WAAW;AAC7D,YAAM,qBAAqB,6BAA6B,cAAc;AACtE,UAAI;AACF,aAAK,GAAG,QAAQ,KAAK,KAAK,MAAM,KAAK,UAAU,kBAAkB,CAAC;AAClE,aAAK,GAAG,QAAQ,KAAK,KAAK,UAAU,QAAQ;AAC5C,aAAK,GAAG,QAAQ,KAAK,KAAK,aAAa,WAAW;AAClD,aAAK,GAAG,QAAQ,KAAK,KAAK,YAAY,0BAA0B,eAAe,UAAU,CAAC;AAC1F,cAAM,WAAW;AAAA,UACf,QAAQ,eAAe;AAAA,UACvB,aAAa,eAAe;AAAA,UAC5B,aAAa,eAAe;AAAA,UAC5B,WAAW,eAAe,aAAa,OAAO,eAAe,YAAY;AAAA,UACzE,qBAAqB,eAAe,uBAAuB,OAAO,eAAe,sBAAsB;AAAA,UACvG,kBAAkB,eAAe,oBAAoB,OAAO,eAAe,mBAAmB;AAAA,UAC9F,gBAAgB,eAAe,kBAAkB,OAAO,eAAe,iBAAiB;AAAA,QAC1F;AACA,aAAK,GAAG,QAAQ,KAAK,KAAK,eAAe,KAAK,UAAU,QAAQ,CAAC;AACjE,eAAO,EAAE,mBAAmB;AAAA,MAC9B,SAAS,KAAP;AACA,oBAAY,KAAK,IAAI;AACrB,cAAM,IAAI,MAAM,yBAAyB,KAAK,kHAAkH,mBAAmB,wCAAwC,mBAAmB,qCAAqC,mBAAmB,kBAAkB;AAAA,MAC1T;AAAA,IACF;AAAA,EACF;AAAA,EACA,MAAM,OAAO;AACX,UAAM,OAAO,KAAK,MAAM,KAAK,GAAG,QAAQ,KAAK,KAAK,IAAI,CAAC;AACvD,QAAI,QAAQ,MAAM;AAChB,YAAM,IAAI,MAAM,kDAAkD,KAAK,YAAY;AAAA,IACrF;AACA,QAAI,KAAK,sBAAsB,QAAQ;AACrC,YAAM,IAAI,MAAM,2EAA2E;AAAA,IAC7F;AACA,UAAM,MAAM,CAAC;AACb,UAAM,WAAW,KAAK,MAAM,KAAK,GAAG,QAAQ,KAAK,KAAK,QAAQ,CAAC;AAC/D,QAAI,YAAY,MAAM;AACpB,YAAM,IAAI,MAAM,4CAA4C,KAAK,wBAAwB;AAAA,IAC3F;AACA,QAAI,gBAAgB;AACpB,UAAM,cAAc,KAAK,MAAM,KAAK,GAAG,QAAQ,KAAK,KAAK,WAAW,CAAC;AACrE,QAAI,eAAe,MAAM;AACvB,YAAM,IAAI,MAAM,gDAAgD,KAAK,yBAAyB;AAAA,IAChG;AACA,QAAI,cAAc;AAClB,UAAM,iBAAiB,KAAK,GAAG,QAAQ,KAAK,KAAK,aAAa;AAC9D,QAAI,kBAAkB,MAAM;AAC1B,YAAM,WAAW,KAAK,MAAM,cAAc;AAC1C,UAAI,SAAS,SAAS;AACtB,UAAI,cAAc,SAAS;AAC3B,UAAI,cAAc,SAAS;AAC3B,UAAI,SAAS,aAAa,MAAM;AAC9B,YAAI,YAAY,SAAS;AAAA,MAC3B;AACA,UAAI,SAAS,uBAAuB,MAAM;AACxC,YAAI,sBAAsB,SAAS;AAAA,MACrC;AACA,UAAI,SAAS,oBAAoB,MAAM;AACrC,YAAI,mBAAmB,SAAS;AAAA,MAClC;AACA,UAAI,SAAS,kBAAkB,MAAM;AACnC,YAAI,iBAAiB,SAAS;AAAA,MAChC;AAAA,IACF;AACA,UAAM,mBAAmB,KAAK,GAAG,QAAQ,KAAK,KAAK,UAAU;AAC7D,QAAI,oBAAoB,MAAM;AAC5B,YAAM,IAAI,MAAM,wDAAwD,KAAK,yBAAyB;AAAA,IACxG;AACA,QAAI,aAAa,0BAA0B,gBAAgB;AAC3D,WAAO;AAAA,EACT;AACF;AACA,oBAAoB,aAAa;AACjC,IAAI,qBAAqB,CAAC,QAAQ;AAChC,MAAI,CAAC,IAAI,EAAE,QAAQ,YAAY,GAAG;AAChC,WAAO;AAAA,EACT,OAAO;AACL,QAAI,CAAC,MAAM,QAAQ,GAAG,KAAK,IAAI,WAAW,oBAAoB,UAAU,GAAG;AACzE,aAAO,oBAAoB,IAAI,MAAM,oBAAoB,WAAW,MAAM,CAAC;AAAA,IAC7E,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AACF;AACA,iBAAiB,mBAAmB,kBAAkB;AACtD,iBAAiB,mBAAmB,kBAAkB;AACtD,SAAS,oBAAoB,WAAW;AACtC,SAAO,IAAI,oBAAoB,SAAS;AAC1C;AACA,IAAI,6BAA6B,MAAM;AAAA,EACrC,cAAc;AACZ,WAAO,IAAI,EAAE,QAAQ,YAAY,GAAG,MAAM,0CAA0C;AACpF,WAAO,OAAO,WAAW,eAAe,OAAO,OAAO,iBAAiB,aAAa,MAAM,yDAAyD;AACnJ,SAAK,KAAK,OAAO;AAAA,EACnB;AAAA,EACA,MAAM,aAAa;AACjB,UAAM,MAAM,CAAC;AACb,UAAM,SAAS,cAAc;AAC7B,UAAM,SAAS,iBAAiB;AAChC,aAAS,KAAK,GAAG,KAAK,KAAK,GAAG,QAAQ,EAAE,IAAI;AAC1C,YAAM,MAAM,KAAK,GAAG,IAAI,EAAE;AAC1B,UAAI,IAAI,WAAW,MAAM,KAAK,IAAI,SAAS,MAAM,GAAG;AAClD,cAAM,YAAY,oBAAoB,GAAG;AACzC,YAAI,aAAa,KAAK,MAAM,KAAK,GAAG,QAAQ,GAAG,CAAC;AAAA,MAClD;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,YAAY,MAAM;AACtB,WAAO,kBAAkB,IAAI;AAC7B,UAAM,OAAO,aAAa,IAAI;AAC9B,QAAI,KAAK,GAAG,QAAQ,KAAK,IAAI,KAAK,MAAM;AACtC,YAAM,IAAI,MAAM,8BAA8B,OAAO;AAAA,IACvD;AACA,UAAM,OAAO,KAAK,MAAM,KAAK,GAAG,QAAQ,KAAK,IAAI,CAAC;AAClD,gBAAY,IAAI;AAChB,WAAO;AAAA,EACT;AACF;AAGA,IAAI,oBAAoB;AACxB,IAAI,4BAA4B,MAAM;AAAA,EACpC,cAAc;AACZ,SAAK,WAAW,CAAC;AAAA,EACnB;AAAA,EACA,OAAO,cAAc;AACnB,QAAI,0BAA0B,YAAY,MAAM;AAC9C,gCAA0B,WAAW,IAAI,0BAA0B;AAAA,IACrE;AACA,WAAO,0BAA0B;AAAA,EACnC;AAAA,EACA,OAAO,gBAAgB,QAAQ,SAAS;AACtC,WAAO,UAAU,MAAM,MAAM,uCAAuC;AACpE,QAAI,OAAO,SAAS,iBAAiB,GAAG;AACtC,eAAS,OAAO,MAAM,GAAG,OAAO,QAAQ,iBAAiB,CAAC;AAAA,IAC5D;AACA,WAAO,OAAO,SAAS,GAAG,MAAM,qCAAqC;AACrE,UAAM,WAAW,0BAA0B,YAAY;AACvD,WAAO,SAAS,SAAS,WAAW,MAAM,MAAM,2DAA2D,UAAU;AACrH,aAAS,SAAS,UAAU;AAAA,EAC9B;AAAA,EACA,OAAO,WAAW,QAAQ;AACxB,UAAM,UAAU,0BAA0B,YAAY,EAAE,SAAS;AACjE,QAAI,WAAW,MAAM;AACnB,YAAM,IAAI,MAAM,yCAAyC,SAAS;AAAA,IACpE;AACA,WAAO;AAAA,EACT;AAAA,EACA,OAAO,aAAa;AAClB,WAAO,OAAO,KAAK,0BAA0B,YAAY,EAAE,QAAQ;AAAA,EACrE;AACF;AACA,SAAS,SAAS,KAAK;AACrB,MAAI,IAAI,QAAQ,iBAAiB,MAAM,IAAI;AACzC,UAAM,IAAI,MAAM,6EAA6E,0BAA0B,WAAW,EAAE,KAAK,GAAG,GAAG;AAAA,EACjJ;AACA,SAAO;AAAA,IACL,QAAQ,IAAI,MAAM,iBAAiB,EAAE;AAAA,IACrC,MAAM,IAAI,MAAM,iBAAiB,EAAE;AAAA,EACrC;AACF;AACA,eAAe,mBAAmB,WAAW,SAAS,eAAe,OAAO;AAC1E,SAAO,cAAc,SAAS,MAAM,wCAAwC,YAAY;AACxF,QAAM,eAAe,iBAAiB,gBAAgB,SAAS;AAC/D,SAAO,aAAa,SAAS,GAAG,MAAM,kEAAkE,YAAY;AACpH,SAAO,aAAa,SAAS,GAAG,MAAM,yCAAyC,aAAa,wCAAwC,YAAY;AAChJ,QAAM,cAAc,aAAa;AACjC,QAAM,eAAe,iBAAiB,gBAAgB,OAAO;AAC7D,SAAO,aAAa,SAAS,GAAG,MAAM,uEAAuE,UAAU;AACvH,SAAO,aAAa,SAAS,GAAG,MAAM,yCAAyC,aAAa,6CAA6C,UAAU;AACnJ,QAAM,cAAc,aAAa;AACjC,QAAM,eAAe,SAAS,SAAS,EAAE;AACzC,QAAM,aAAa,SAAS,SAAS,EAAE;AACvC,QAAM,aAAa,iBAAiB,SAAS,SAAS,EAAE;AACxD,QAAM,iBAAiB,MAAM,YAAY,KAAK;AAC9C,MAAI,gBAAgB,YAAY;AAC9B,UAAM,0BAA0B,WAAW,YAAY,EAAE,YAAY,UAAU;AAAA,EACjF;AACA,QAAM,aAAa,MAAM,YAAY,KAAK,cAAc;AACxD,MAAI,gBAAgB,CAAC,YAAY;AAC/B,UAAM,0BAA0B,WAAW,YAAY,EAAE,YAAY,UAAU;AAAA,EACjF;AACA,SAAO,WAAW;AACpB;AACA,eAAe,aAAa;AAC1B,QAAM,UAAU,0BAA0B,WAAW;AACrD,QAAM,MAAM,CAAC;AACb,aAAW,UAAU,SAAS;AAC5B,UAAM,YAAY,MAAM,0BAA0B,WAAW,MAAM,EAAE,WAAW;AAChF,eAAW,QAAQ,WAAW;AAC5B,YAAM,MAAM,SAAS,oBAAoB;AACzC,UAAI,OAAO,UAAU;AAAA,IACvB;AAAA,EACF;AACA,SAAO;AACT;AACA,eAAe,YAAY,KAAK;AAC9B,QAAM,gBAAgB,SAAS,GAAG;AAClC,QAAM,UAAU,0BAA0B,WAAW,cAAc,MAAM;AACzE,SAAO,QAAQ,YAAY,cAAc,IAAI;AAC/C;AACA,eAAe,UAAU,WAAW,SAAS;AAC3C,QAAM,eAAe;AACrB,SAAO,mBAAmB,WAAW,SAAS,YAAY;AAC5D;AACA,eAAe,UAAU,WAAW,SAAS;AAC3C,QAAM,eAAe;AACrB,SAAO,mBAAmB,WAAW,SAAS,YAAY;AAC5D;AAGA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,MAAM,MAAML,QAAO;AACjB,WAAO,MAAM,MAAMA,MAAK;AAAA,EAC1B;AAAA,EACA,MAAM;AACJ,WAAO,YAAY,IAAI;AAAA,EACzB;AAAA,EACA,OAAO,MAAM,UAAU;AACrB,QAAI,aAAa,WAAW,aAAa,QAAQ;AAC/C,YAAM,IAAI,MAAM,kDAAkD,UAAU;AAAA,IAC9E;AACA,QAAI,KAAK,eAAe,MAAM;AAC5B,WAAK,cAAc,IAAI,YAAY;AAAA,IACrC;AACA,WAAO,KAAK,YAAY,OAAO,IAAI;AAAA,EACrC;AAAA,EACA,OAAO,OAAO,UAAU;AACtB,WAAO,IAAI,YAAY,QAAQ,EAAE,OAAO,KAAK;AAAA,EAC/C;AACF;AACA,IAAI,IAAI,EAAE,IAAI,YAAY,GAAG;AAC3B,MAAI,EAAE,YAAY,WAAW,IAAI,gBAAgB,CAAC;AAClD,MAAI;AACF,8BAA0B,gBAAgB,oBAAoB,YAAY,IAAI,2BAA2B,CAAC;AAAA,EAC5G,SAAS,KAAP;AAAA,EACF;AACA,MAAI;AACF,8BAA0B,gBAAgB,iBAAiB,YAAY,IAAI,wBAAwB,CAAC;AAAA,EACtG,SAAS,KAAP;AAAA,EACF;AACF;AAGA,IAAI,eAAe;AAAA,EACjB,aAAa,MAAM,gBAAgB;AACrC;AACA,IAAI;AACJ,IAAI,eAAe,MAAM;AAAA,EACvB,cAAc;AACZ,SAAK,OAAO,aAAa;AACzB,SAAK,cAAc,IAAI,KAAK,KAAK,YAAY;AAAA,EAC/C;AAAA,EACA,MAAM,MAAM,cAAc;AACxB,QAAI,IAAI,EAAE,OAAO,SAAS,MAAM;AAC9B,aAAO,IAAI,EAAE,OAAO,MAAM,MAAM,YAAY;AAAA,IAC9C;AACA,QAAI,eAAe,MAAM;AACvB,oBAAc,aAAa,YAAY;AAAA,IACzC;AACA,WAAO,YAAY,MAAM,YAAY;AAAA,EACvC;AAAA,EACA,MAAM;AACJ,UAAM,QAAQ,QAAQ,OAAO;AAC7B,WAAO,MAAM,KAAK,MAAM,MAAM,KAAK;AAAA,EACrC;AAAA,EACA,OAAO,MAAM,UAAU;AACrB,QAAI,aAAa,WAAW,aAAa,QAAQ;AAC/C,YAAM,IAAI,MAAM,sDAAsD,UAAU;AAAA,IAClF;AACA,WAAO,KAAK,YAAY,OAAO,IAAI;AAAA,EACrC;AAAA,EACA,OAAO,OAAO,UAAU;AACtB,QAAI,MAAM,WAAW,GAAG;AACtB,aAAO;AAAA,IACT;AACA,WAAO,IAAI,KAAK,KAAK,YAAY,QAAQ,EAAE,OAAO,KAAK;AAAA,EACzD;AACF;AACA,IAAI,IAAI,EAAE,IAAI,SAAS,KAAK,CAAC,IAAI,EAAE,IAAI,YAAY,GAAG;AACpD,MAAI,EAAE,YAAY,QAAQ,IAAI,aAAa,CAAC;AAC9C;AAGA,SAAS,OAAO,OAAO,QAAQ,WAAW,QAAQ;AAChD,UAAQ,SAAS;AACjB,qCAAmC,KAAK;AACxC,SAAO,IAAI,aAAa,OAAO,OAAO,MAAM;AAC9C;AAGA,SAAS,MAAM,GAAG,OAAO;AACvB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,MAAI,CAAC,aAAa,KAAK,GAAG;AACxB,UAAM,IAAI,MAAM,mCAAmC,OAAO;AAAA,EAC5D;AACA,MAAI,UAAU,YAAY,GAAG,UAAU,YAAY,UAAU,YAAY,GAAG,UAAU,UAAU;AAC9F,UAAM,IAAI,MAAM,uCAAuC;AAAA,EACzD;AACA,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM;AACtB,SAAO,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC7C;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS,mBAAmB;AAC/D,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,GAAG,UAAU,OAAO;AACjC,UAAQ,IAAI,EAAE,SAAS,OAAO,CAAC;AACjC;AAGA,gBAAgB;AAChB,IAAI,aAAa;AAAA,EACf;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,aAAa,UAAU;AAGvB,IAAI,aAAa,CAAC;AAClBP,UAAS,YAAY;AAAA,EACnB,cAAc,MAAM;AAAA,EACpB,oBAAoB,MAAM;AAAA,EAC1B,yBAAyB,MAAM;AAAA,EAC/B,WAAW,MAAM;AAAA,EACjB,eAAe,MAAM;AAAA,EACrB,eAAe,MAAM;AAAA,EACrB,YAAY,MAAM;AAAA,EAClB,gBAAgB,MAAM;AAAA,EACtB,iBAAiB,MAAM;AAAA,EACvB,0BAA0B,MAAM;AAAA,EAChC,8BAA8B,MAAM;AAAA,EACpC,iBAAiB,MAAM;AAAA,EACvB,MAAM,MAAM;AAAA,EACZ,cAAc,MAAM;AAAA,EACpB,YAAY,MAAM;AAAA,EAClB,aAAa,MAAM;AAAA,EACnB,WAAW,MAAM;AAAA,EACjB,oBAAoB,MAAM;AAAA,EAC1B,oBAAoB,MAAM;AAAA,EAC1B,aAAa,MAAM;AAAA,EACnB,sBAAsB,MAAM;AAAA,EAC5B,iBAAiB,MAAM;AAAA,EACvB,qBAAqB,MAAM;AAC7B,CAAC;AAGD,IAAI,2BAA2B;AAC/B,IAAI,8BAA8B;AAClC,IAAI,qCAAqC;AACzC,SAAS,MAAM,GAAG;AAChB,SAAO,IAAI,QAAQ,CAAC,YAAY,WAAW,OAAO,CAAC,EAAE,KAAK,CAAC;AAC7D;AACA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,gBAAgB;AAC1B,QAAI,CAAC,IAAI,EAAE,QAAQ,YAAY,GAAG;AAChC,YAAM,IAAI,MAAM,qFAAqF;AAAA,IACvG;AACA,QAAI,eAAe,WAAW,iBAAiB,UAAU,GAAG;AAC1D,uBAAiB,eAAe,MAAM,iBAAiB,WAAW,MAAM;AAAA,IAC1E;AACA,QAAI,kBAAkB,QAAQ,eAAe,WAAW,GAAG;AACzD,uBAAiB;AAAA,IACnB;AACA,SAAK,oBAAoB,iBAAiB;AAC1C,SAAK,qBAAqB,iBAAiB;AAAA,EAC7C;AAAA,EACA,MAAM,KAAK,gBAAgB;AACzB,QAAI,OAAO,aAAa,aAAa;AACnC,YAAM,IAAI,MAAM,yFAAyF;AAAA,IAC3G;AACA,UAAM,aAAa,OAAO,IAAI,gBAAgB,IAAI,KAAK,CAAC,eAAe,UAAU,GAAG,EAAE,MAAM,2BAA2B,CAAC,CAAC;AACzH,QAAI,eAAe,yBAAyB,aAAa;AACvD,YAAM,IAAI,MAAM,uFAAuF;AAAA,IACzG,OAAO;AACL,YAAM,kBAAkB,CAAC;AAAA,QACvB,OAAO,CAAC,OAAO,KAAK,kBAAkB;AAAA,QACtC,SAAS,eAAe;AAAA,MAC1B,CAAC;AACD,YAAM,YAAY,8BAA8B,gBAAgB,eAAe;AAC/E,YAAM,eAAe,OAAO,IAAI,gBAAgB,IAAI,KAAK,CAAC,KAAK,UAAU,SAAS,CAAC,GAAG,EAAE,MAAM,mBAAmB,CAAC,CAAC;AACnH,YAAM,aAAa,KAAK,mBAAmB,OAAO,SAAS,cAAc,GAAG,IAAI,KAAK;AACrF,iBAAW,WAAW,KAAK;AAC3B,iBAAW,OAAO;AAClB,YAAM,MAAM,MAAM,WAAW,cAAc,IAAI,WAAW,OAAO,CAAC,CAAC;AACnE,UAAI,eAAe,cAAc,MAAM;AACrC,cAAM,mBAAmB,KAAK,oBAAoB,OAAO,SAAS,cAAc,GAAG,IAAI,KAAK;AAC5F,yBAAiB,WAAW,KAAK;AACjC,yBAAiB,OAAO;AACxB,cAAM,MAAM,MAAM,iBAAiB,cAAc,IAAI,WAAW,OAAO,CAAC,CAAC;AAAA,MAC3E;AACA,aAAO,EAAE,oBAAoB,6BAA6B,cAAc,EAAE;AAAA,IAC5E;AAAA,EACF;AACF;AACA,iBAAiB,aAAa;AAC9B,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,OAAO;AACjB,QAAI,SAAS,QAAQ,MAAM,SAAS,GAAG;AACrC,YAAM,IAAI,MAAM,wEAAwE,OAAO;AAAA,IACjG;AACA,SAAK,WAAW,MAAM;AACtB,SAAK,eAAe,MAAM,MAAM,CAAC;AAAA,EACnC;AAAA,EACA,MAAM,OAAO;AACX,WAAO,IAAI,QAAQ,CAAC,SAAS,WAAW;AACtC,YAAM,aAAa,IAAI,WAAW;AAClC,iBAAW,SAAS,CAAC,UAAU;AAC7B,cAAM,YAAY,KAAK,MAAM,MAAM,OAAO,MAAM;AAChD,cAAM,gBAAgB,UAAU;AAChC,YAAI,iBAAiB,MAAM;AACzB,iBAAO,IAAI,MAAM,4CAA4C,KAAK,SAAS,MAAM,CAAC;AAClF;AAAA,QACF;AACA,cAAM,kBAAkB,UAAU;AAClC,YAAI,mBAAmB,MAAM;AAC3B,iBAAO,IAAI,MAAM,6CAA6C,KAAK,SAAS,MAAM,CAAC;AACnF;AAAA,QACF;AACA,YAAI,KAAK,aAAa,WAAW,GAAG;AAClC,kBAAQ,EAAE,cAAc,CAAC;AACzB;AAAA,QACF;AACA,cAAM,wBAAwB,yBAAyB,WAAW,CAAC,qBAAqB,KAAK,YAAY,gBAAgB,CAAC;AAC1H,gBAAQ,qBAAqB;AAAA,MAC/B;AACA,iBAAW,UAAU,CAAC,UAAU,OAAO,sEAAsE,KAAK,SAAS,2EAA2E;AACtM,iBAAW,WAAW,KAAK,QAAQ;AAAA,IACrC,CAAC;AAAA,EACH;AAAA,EACA,YAAY,iBAAiB;AAC3B,UAAM,cAAc,CAAC;AACrB,UAAM,QAAQ,CAAC;AACf,eAAW,SAAS,iBAAiB;AACnC,kBAAY,KAAK,GAAG,MAAM,OAAO;AACjC,YAAM,KAAK,GAAG,MAAM,KAAK;AAAA,IAC3B;AACA,UAAM,aAAa,KAAK,4BAA4B,eAAe;AACnE,UAAM,WAAW,MAAM,IAAI,CAAC,SAAS,KAAK,gBAAgB,MAAM,WAAW,KAAK,CAAC;AACjF,WAAO,QAAQ,IAAI,QAAQ,EAAE,KAAK,CAAC,YAAY,CAAC,aAAa,wBAAwB,OAAO,CAAC,CAAC;AAAA,EAChG;AAAA,EACA,gBAAgB,MAAM,MAAM;AAC1B,WAAO,IAAI,QAAQ,CAAC,SAAS,WAAW;AACtC,YAAM,mBAAmB,IAAI,WAAW;AACxC,uBAAiB,SAAS,CAAC,UAAU;AACnC,cAAM,aAAa,MAAM,OAAO;AAChC,gBAAQ,UAAU;AAAA,MACpB;AACA,uBAAiB,UAAU,CAAC,UAAU,OAAO,6CAA6C,QAAQ;AAClG,uBAAiB,kBAAkB,IAAI;AAAA,IACzC,CAAC;AAAA,EACH;AAAA,EACA,4BAA4B,UAAU;AACpC,UAAM,YAAY,CAAC;AACnB,UAAM,YAAY,KAAK,aAAa,IAAI,CAAC,SAAS,SAAS,KAAK,IAAI,CAAC;AACrE,UAAM,aAAa,CAAC;AACpB,eAAW,SAAS,UAAU;AAC5B,YAAM,MAAM,QAAQ,CAAC,SAAS;AAC5B,cAAM,eAAe,SAAS,IAAI;AAClC,YAAI,UAAU,QAAQ,YAAY,MAAM,IAAI;AAC1C,gBAAM,IAAI,MAAM,uDAAuD,eAAe;AAAA,QACxF;AACA,kBAAU,KAAK,YAAY;AAC3B,YAAI,UAAU,QAAQ,YAAY,MAAM,IAAI;AAC1C,gBAAM,IAAI,MAAM,8BAA8B,gCAAgC;AAAA,QAChF,OAAO;AACL,qBAAW,QAAQ,KAAK,aAAa,UAAU,QAAQ,YAAY;AAAA,QACrE;AAAA,MACF,CAAC;AAAA,IACH;AACA,QAAI,UAAU,WAAW,KAAK,aAAa,QAAQ;AACjD,YAAM,IAAI,MAAM,wDAAwD,UAAU,oDAAoD,KAAK,aAAa,UAAU;AAAA,IACpK;AACA,WAAO;AAAA,EACT;AACF;AACA,IAAI,yBAAyB,CAAC,QAAQ;AACpC,MAAI,CAAC,IAAI,EAAE,QAAQ,YAAY,GAAG;AAChC,WAAO;AAAA,EACT,OAAO;AACL,QAAI,CAAC,MAAM,QAAQ,GAAG,KAAK,IAAI,WAAW,iBAAiB,UAAU,GAAG;AACtE,aAAO,iBAAiB,IAAI,MAAM,iBAAiB,WAAW,MAAM,CAAC;AAAA,IACvE,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AACF;AACA,iBAAiB,mBAAmB,sBAAsB;AAC1D,SAAS,iBAAiB,iBAAiB,SAAS;AAClD,SAAO,IAAI,iBAAiB,cAAc;AAC5C;AACA,SAAS,aAAa,OAAO;AAC3B,SAAO,IAAI,aAAa,KAAK;AAC/B;AAGA,SAAS,wBAAwB,UAAU,YAAY,eAAe,aAAa;AACjF,gBAAc,QAAQ;AACtB,kBAAgB,iBAAiB,OAAO,IAAI;AAC5C,gBAAc,eAAe,OAAO,IAAI;AACxC,gBAAc,eAAe,WAAW;AACxC,MAAI,kBAAkB;AACtB,QAAM,kBAAkB,CAAC,YAAY;AACnC,YAAQ,KAAK,CAAC,UAAU;AACtB,YAAM,WAAW,gBAAgB,EAAE,kBAAkB,SAAS,UAAU,cAAc;AACtF,iBAAW,QAAQ;AACnB,aAAO;AAAA,IACT,CAAC;AACD,WAAO;AAAA,EACT;AACA,WAAS,cAAc,WAAW;AAChC,WAAO,aAAa,QAAQ,MAAM,QAAQ,SAAS,KAAK,UAAU,SAAS,GAAG,MAAM,qCAAqC;AAAA,EAC3H;AACA,WAAS,cAAc,gBAAgB,cAAc;AACnD,WAAO,kBAAkB,KAAK,kBAAkB,GAAG,MAAM,oEAAoE,gBAAgB;AAC7I,WAAO,gBAAgB,KAAK,gBAAgB,GAAG,MAAM,kEAAkE,cAAc;AACrI,WAAO,gBAAgB,gBAAgB,MAAM,yEAAyE,kCAAkC,cAAc;AAAA,EACxK;AACA,SAAO,QAAQ,IAAI,SAAS,IAAI,eAAe,CAAC;AAClD;AAGA,eAAe,yBAAyB,WAAW,aAAa;AAC9D,MAAI,eAAe,MAAM;AACvB,kBAAc,CAAC;AAAA,EACjB;AACA,QAAM,YAAY,YAAY,aAAa,OAAO,IAAI,EAAE,SAAS,QAAQ,YAAY;AACrF,QAAM,WAAW,UAAU,IAAI,CAAC,aAAa,UAAU,UAAU,YAAY,aAAa,EAAE,UAAU,KAAK,CAAC,CAAC;AAC7G,QAAM,qBAAqB;AAC3B,QAAM,mBAAmB;AACzB,QAAM,YAAY,YAAY,cAAc,OAAO,MAAM,QAAQ,IAAI,QAAQ,IAAI,MAAM,wBAAwB,UAAU,YAAY,YAAY,oBAAoB,gBAAgB;AACrL,QAAM,iBAAiB,UAAU,IAAI,CAAC,aAAa,SAAS,YAAY,CAAC;AACzE,QAAM,sBAAsB;AAC5B,QAAM,oBAAoB;AAC1B,QAAM,UAAU,YAAY,cAAc,OAAO,MAAM,QAAQ,IAAI,cAAc,IAAI,MAAM,wBAAwB,gBAAgB,YAAY,YAAY,qBAAqB,iBAAiB;AACjM,SAAO;AACT;AACA,eAAe,YAAY,UAAU,iBAAiB,IAAI,aAAa,aAAa;AAClF,QAAM,eAAe,CAAC,cAAc,yBAAyB,WAAW,EAAE,YAAY,CAAC;AACvF,QAAM,eAAe,qBAAqB,YAAY;AACtD,SAAO,aAAa,UAAU,gBAAgB,WAAW;AAC3D;AACA,SAAS,qBAAqB,sBAAsB;AAClD,SAAO,OAAO,UAAU,iBAAiB,IAAI,gBAAgB;AAC3D,UAAM,yBAAyB,SAAS,IAAI,MAAM,KAAK;AACvD,UAAM,sBAAsB,CAAC;AAC7B,UAAM,eAAe,eAAe,OAAO,YAAY,IAAI,MAAM,KAAK,IAAI,CAAC;AAC3E,UAAM,yBAAyB,CAAC;AAChC,aAAS,QAAQ,CAAC,qBAAqB,eAAe;AACpD,UAAI,cAAc;AAClB,0BAAoB,QAAQ,QAAQ,CAAC,iBAAiB;AACpD,cAAM,WAAW,kBAAkB,eAAe,aAAa,aAAa,QAAQ,aAAa;AACjG,cAAM,eAAe,qBAAqB,YAAY,cAAc,aAAa,KAAK;AACtF,cAAM,8BAA8B,MAAM;AACxC,iCAAuB,cAAc;AACrC,cAAI,oBAAoB,eAAe,MAAM;AAC3C,gCAAoB,cAAc,CAAC;AAAA,UACrC;AACA,8BAAoB,YAAY,KAAK;AAAA,YACnC,eAAe;AAAA,YACf;AAAA,YACA,WAAW;AAAA,UACb,CAAC;AAAA,QACH;AACA,YAAI,eAAe,MAAM;AACvB,sBAAY,QAAQ,CAAC,YAAY,gBAAgB;AAC/C,gBAAI,eAAe,aAAa,MAAM;AACpC,0CAA4B;AAC5B,2BAAa,eAAe;AAAA,YAC9B;AAAA,UACF,CAAC;AAAA,QACH,OAAO;AACL,sCAA4B;AAAA,QAC9B;AACA,+BAAuB,KAAK,aAAa,IAAI;AAC7C,uBAAe;AAAA,MACjB,CAAC;AAAA,IACH,CAAC;AACD,QAAI,CAAC,aAAa,MAAM,CAAC,UAAU,KAAK,GAAG;AACzC,YAAM,kBAAkB,YAAY,OAAO,CAAC,GAAG,OAAO,CAAC,aAAa,GAAG;AACvE,YAAM,IAAI,MAAM,kDAAkD,gBAAgB,KAAK,IAAI;AAAA,wCACzD,uBAAuB,KAAK,IAAI,IAAI;AAAA,IACxE;AACA,UAAM,sBAAsB,uBAAuB,OAAO,CAAC,aAAa,aAAa,OAAO;AAC1F,UAAI,aAAa;AACf,oBAAY,KAAK,EAAE;AAAA,MACrB;AACA,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AACL,UAAM,YAAY,CAAC;AACnB,wBAAoB,QAAQ,CAAC,OAAO;AAClC,eAAS,IAAI,MAAM,QAAQ,CAAC,aAAa;AACvC,cAAM,WAAW,kBAAkB,CAAC,eAAe,SAAS,GAAG,IAAI,MAAM,MAAM;AAC/E,kBAAU,KAAK,QAAQ;AAAA,MACzB,CAAC;AAAA,IACH,CAAC;AACD,UAAM,UAAU,MAAM,qBAAqB,SAAS;AACpD,UAAM,mBAAmB,CAAC;AAC1B,QAAI,oBAAoB;AACxB,wBAAoB,QAAQ,CAAC,OAAO;AAClC,YAAM,aAAa,SAAS,IAAI,MAAM;AACtC,UAAI,aAAa;AACjB,eAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,sBAAc,QAAQ,oBAAoB,IAAI;AAAA,MAChD;AACA,YAAM,cAAc,IAAI,YAAY,UAAU;AAC9C,YAAM,kBAAkB,IAAI,WAAW,WAAW;AAClD,UAAI,oBAAoB;AACxB,eAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,cAAM,UAAU,IAAI,WAAW,QAAQ,oBAAoB,GAAG;AAC9D,wBAAgB,IAAI,SAAS,iBAAiB;AAC9C,6BAAqB,QAAQ;AAAA,MAC/B;AACA,YAAM,iBAAiB,oBAAoB;AAC3C,qBAAe,QAAQ,CAAC,iBAAiB;AACvC,cAAM,aAAa,YAAY,MAAM,aAAa,aAAa,aAAa,cAAc,aAAa,SAAS;AAChH,cAAM,kBAAkB,cAAc,YAAY,CAAC,aAAa,aAAa,CAAC;AAC9E,mBAAW,QAAQ,iBAAiB;AAClC,2BAAiB,QAAQ,gBAAgB;AAAA,QAC3C;AAAA,MACF,CAAC;AACD,2BAAqB;AAAA,IACvB,CAAC;AACD,WAAO;AAAA,EACT;AACF;AAGA,IAAI,yBAAyB;AAC7B,IAAI,YAAY;AAChB,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,MAAM,aAAa;AAC7B,SAAK,iBAAiB;AACtB,QAAI,eAAe,MAAM;AACvB,oBAAc,CAAC;AAAA,IACjB;AACA,SAAK,mBAAmB,YAAY;AACpC,SAAK,aAAa,YAAY;AAC9B,SAAK,qBAAqB,YAAY;AACtC,QAAI,YAAY,aAAa,MAAM;AACjC,aAAO,OAAO,YAAY,cAAc,YAAY,MAAM,6HAA6H;AACvL,WAAK,QAAQ,YAAY;AAAA,IAC3B,OAAO;AACL,WAAK,QAAQ,IAAI,EAAE,SAAS;AAAA,IAC9B;AACA,WAAO,QAAQ,QAAQ,KAAK,SAAS,GAAG,MAAM,yDAAyD;AACvG,QAAI,MAAM,QAAQ,IAAI,GAAG;AACvB,aAAO,KAAK,WAAW,GAAG,MAAM,iEAAiE,KAAK,UAAU;AAAA,IAClH;AACA,SAAK,OAAO;AACZ,QAAI,YAAY,eAAe,QAAQ,YAAY,YAAY,QAAQ,MAAM;AAC3E,YAAM,IAAI,MAAM,oEAAoE;AAAA,IACtF;AACA,SAAK,cAAc,YAAY,eAAe,CAAC;AAAA,EACjD;AAAA,EACA,MAAM,KAAK,gBAAgB;AACzB,QAAI,eAAe,yBAAyB,aAAa;AACvD,YAAM,IAAI,MAAM,yFAAyF;AAAA,IAC3G;AACA,UAAMO,SAAQ,OAAO,OAAO,EAAE,QAAQ,KAAK,eAAe,GAAG,KAAK,WAAW;AAC7E,IAAAA,OAAM,OAAO,IAAI,SAAS;AAC1B,UAAM,kBAAkB,CAAC;AAAA,MACvB,OAAO,CAAC,qBAAqB;AAAA,MAC7B,SAAS,eAAe;AAAA,IAC1B,CAAC;AACD,UAAM,iCAAiC,8BAA8B,gBAAgB,eAAe;AACpG,IAAAA,OAAM,KAAK,OAAO,cAAc,IAAI,KAAK,CAAC,KAAK,UAAU,8BAA8B,CAAC,GAAG,EAAE,MAAM,UAAU,CAAC,GAAG,YAAY;AAC7H,QAAI,eAAe,cAAc,MAAM;AACrC,MAAAA,OAAM,KAAK,OAAO,qBAAqB,IAAI,KAAK,CAAC,eAAe,UAAU,GAAG,EAAE,MAAM,uBAAuB,CAAC,GAAG,mBAAmB;AAAA,IACrI;AACA,UAAM,WAAW,MAAM,KAAK,MAAM,KAAK,MAAMA,MAAK;AAClD,QAAI,SAAS,IAAI;AACf,aAAO;AAAA,QACL,oBAAoB,6BAA6B,cAAc;AAAA,QAC/D,WAAW,CAAC,QAAQ;AAAA,MACtB;AAAA,IACF,OAAO;AACL,YAAM,IAAI,MAAM,gEAAgE,SAAS,SAAS;AAAA,IACpG;AAAA,EACF;AAAA,EACA,MAAM,OAAO;AACX,UAAM,qBAAqB,MAAM,KAAK,MAAM,KAAK,MAAM,KAAK,WAAW;AACvE,QAAI,CAAC,mBAAmB,IAAI;AAC1B,YAAM,IAAI,MAAM,cAAc,KAAK,gCAAgC,mBAAmB,+EAA+E;AAAA,IACvK;AACA,QAAI;AACJ,QAAI;AACF,kBAAY,MAAM,mBAAmB,KAAK;AAAA,IAC5C,SAAS,IAAP;AACA,UAAI,UAAU,+CAA+C,KAAK;AAClE,UAAI,KAAK,KAAK,SAAS,KAAK,GAAG;AAC7B,mBAAW;AAAA,MACb,OAAO;AACL,mBAAW;AAAA,MACb;AACA,YAAM,IAAI,MAAM,OAAO;AAAA,IACzB;AACA,UAAM,gBAAgB,UAAU;AAChC,UAAM,kBAAkB,UAAU;AAClC,QAAI,iBAAiB,QAAQ,mBAAmB,MAAM;AACpD,YAAM,IAAI,MAAM,2BAA2B,KAAK,+DAA+D;AAAA,IACjH;AACA,WAAO,yBAAyB,WAAW,CAAC,qBAAqB,KAAK,YAAY,gBAAgB,CAAC;AAAA,EACrG;AAAA,EACA,MAAM,YAAY,iBAAiB;AACjC,UAAM,aAAa,MAAM,QAAQ,KAAK,IAAI,IAAI,KAAK,KAAK,KAAK,KAAK;AAClE,UAAM,CAAC,QAAQ,MAAM,IAAI,SAAS,UAAU;AAC5C,UAAM,aAAa,KAAK,oBAAoB;AAC5C,UAAM,cAAc,CAAC;AACrB,eAAW,SAAS,iBAAiB;AACnC,kBAAY,KAAK,GAAG,MAAM,OAAO;AAAA,IACnC;AACA,UAAM,YAAY,CAAC;AACnB,UAAM,cAAc,CAAC;AACrB,eAAW,gBAAgB,iBAAiB;AAC1C,iBAAW,QAAQ,aAAa,OAAO;AACrC,YAAI,KAAK,sBAAsB,MAAM;AACnC,sBAAY,KAAK,KAAK,mBAAmB,IAAI,CAAC;AAAA,QAChD,OAAO;AACL,oBAAU,KAAK,aAAa,OAAO,MAAM;AAAA,QAC3C;AAAA,MACF;AAAA,IACF;AACA,QAAI,KAAK,oBAAoB;AAC3B,gBAAU,KAAK,GAAG,MAAM,QAAQ,IAAI,WAAW,CAAC;AAAA,IAClD;AACA,UAAM,UAAU,MAAM,yBAAyB,WAAW;AAAA,MACxD,aAAa,KAAK;AAAA,MAClB,WAAW,KAAK;AAAA,MAChB,YAAY,KAAK;AAAA,IACnB,CAAC;AACD,WAAO,CAAC,aAAa,wBAAwB,OAAO,CAAC;AAAA,EACvD;AACF;AACA,YAAY,mBAAmB;AAC/B,SAAS,SAAS,KAAK;AACrB,QAAM,YAAY,IAAI,YAAY,GAAG;AACrC,QAAM,kBAAkB,IAAI,YAAY,GAAG;AAC3C,QAAM,SAAS,IAAI,UAAU,GAAG,SAAS;AACzC,QAAM,SAAS,kBAAkB,YAAY,IAAI,UAAU,eAAe,IAAI;AAC9E,SAAO,CAAC,SAAS,KAAK,MAAM;AAC9B;AACA,SAAS,aAAa,KAAK;AACzB,SAAO,IAAI,MAAM,YAAY,gBAAgB,KAAK;AACpD;AACA,IAAI,aAAa,CAAC,KAAK,gBAAgB;AACrC,MAAI,OAAO,UAAU,gBAAgB,eAAe,QAAQ,YAAY,aAAa,OAAO;AAC1F,WAAO;AAAA,EACT,OAAO;AACL,QAAI,SAAS;AACb,QAAI,MAAM,QAAQ,GAAG,GAAG;AACtB,eAAS,IAAI,MAAM,CAAC,YAAY,aAAa,OAAO,CAAC;AAAA,IACvD,OAAO;AACL,eAAS,aAAa,GAAG;AAAA,IAC3B;AACA,QAAI,QAAQ;AACV,aAAO,KAAK,KAAK,WAAW;AAAA,IAC9B;AAAA,EACF;AACA,SAAO;AACT;AACA,iBAAiB,mBAAmB,UAAU;AAC9C,iBAAiB,mBAAmB,UAAU;AAC9C,SAAS,KAAK,MAAM,aAAa;AAC/B,SAAO,IAAI,YAAY,MAAM,WAAW;AAC1C;AACA,SAAS,mBAAmB,MAAM,aAAa;AAC7C,SAAO,KAAK,MAAM,WAAW;AAC/B;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,gBAAgB;AAC1B,SAAK,iBAAiB;AAAA,EACxB;AAAA,EACA,OAAO;AACL,WAAO,KAAK;AAAA,EACd;AACF;AACA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,aAAa;AACvB,SAAK,cAAc;AAAA,EACrB;AAAA,EACA,KAAK,gBAAgB;AACnB,WAAO,KAAK,YAAY,cAAc;AAAA,EACxC;AACF;AACA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,SAAS;AACnB,QAAI,QAAQ,MAAM;AAChB,WAAK,OAAO,MAAM,QAAQ,QAAQ,QAAQ,KAAK,CAAC;AAAA,IAClD;AACA,QAAI,QAAQ,MAAM;AAChB,WAAK,OAAO,CAAC,mBAAmB,QAAQ,QAAQ,QAAQ,KAAK,cAAc,CAAC;AAAA,IAC9E;AAAA,EACF;AACF;AACA,SAAS,WAAW,gBAAgB,aAAa,YAAY,gBAAgB;AAC3E,QAAM,OAAO;AACb,SAAO,IAAI,iBAAiB,eAAe,GAAG,IAAI,CAAC;AACrD;AACA,SAAS,eAAe,gBAAgB,aAAa,YAAY,gBAAgB;AAC/E,MAAI,UAAU,WAAW,GAAG;AAC1B,UAAM,mBAAmB,eAAe,iBAAiB,QAAQ,eAAe,eAAe;AAC/F,QAAI,kBAAkB;AACpB,aAAO,IAAI,kBAAkB,cAAc;AAAA,IAC7C,OAAO;AACL,cAAQ,KAAK,uNAAuN;AACpO,aAAO,IAAI,kBAAkB,EAAE,eAAe,eAAe,CAAC;AAAA,IAChE;AAAA,EACF,OAAO;AACL,YAAQ,KAAK,uNAAuN;AACpO,WAAO,IAAI,kBAAkB;AAAA,MAC3B,eAAe;AAAA,MACf;AAAA,MACA;AAAA,MACA;AAAA,IACF,CAAC;AAAA,EACH;AACF;AACA,SAAS,gBAAgB,aAAa;AACpC,SAAO,IAAI,iBAAiB,WAAW;AACzC;AACA,SAAS,oBAAoB,aAAa;AACxC,SAAO,IAAI,iBAAiB,WAAW;AACzC;AAGA,IAAI,eAAe,CAAC;AACpBP,UAAS,cAAc;AAAA,EACrB,iBAAiB,MAAM;AACzB,CAAC;AAGD,SAAS,QAAQ,GAAG,GAAG,aAAa,OAAO,aAAa,OAAO;AAC7D,MAAI,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AACzC,MAAI,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AACzC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,QAAM,QAAQ,EAAE,YAAY,WAAW;AACvC,SAAO,OAAO,UAAU,aAAa,QAAQ,KAAK;AACpD;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,QAAQ,SAAS,OAAO,UAAU,GAAG,WAAW,GAAG;AAC1D,MAAI,QAAQ,GAAG;AACb,UAAM,IAAI,MAAM,iDAAiD,OAAO;AAAA,EAC1E;AACA,QAAM,WAAW,gBAAgB,SAAS,WAAW,UAAU,OAAO;AACtE,QAAM,SAAS,EAAE,SAAS,SAAS;AACnC,QAAM,QAAQ,EAAE,OAAO,SAAS,SAAS;AACzC,SAAO,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAC/C;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,iBAAiB;AACxB,MAAI,EAAE,IAAI,QAAQ,IAAI;AACxB;AACA,SAAS,kBAAkB;AACzB,MAAI,EAAE,IAAI,SAAS,IAAI;AACzB;AACA,SAAS,6BAA6B;AACpC,MAAI,EAAE,IAAI,gCAAgC,KAAK;AAC/C,UAAQ,KAAK,wDAAwD;AACvE;AACA,SAAS,gBAAgB,KAAK;AAC5B,MAAI,IAAI,EAAE,QAAQ,8BAA8B,GAAG;AACjD,YAAQ,KAAK,MAAM,6EAA6E;AAAA,EAClG;AACF;AACA,wBAAwB,eAAe;AACvC,SAAS,mBAAmB;AAC1B,SAAO,iBAAiB;AAC1B;AACA,SAAS,SAAS;AAChB,SAAO;AACT;AACA,SAAS,SAAS;AAChB,SAAO,OAAO,OAAO;AACvB;AACA,SAAS,QAAQ,GAAG;AAClB,SAAO,OAAO,QAAQ,CAAC;AACzB;AACA,SAAS,KAAK,UAAU,IAAI;AAC1B,SAAO,OAAO,KAAK,UAAU,EAAE;AACjC;AACA,SAAS,QAAQ,WAAW;AAC1B,QAAM,UAAU,sBAAsB,SAAS;AAC/C,UAAQ,QAAQ,CAAC,YAAY,QAAQ,QAAQ,CAAC;AAChD;AACA,SAAS,KAAK,QAAQ;AACpB,SAAO,OAAO,KAAK,MAAM;AAC3B;AACA,SAAS,KAAK,GAAG;AACf,SAAO,OAAO,KAAK,CAAC;AACtB;AACA,SAAS,WAAW,aAAa;AAC/B,SAAO,OAAO,WAAW,WAAW;AACtC;AACA,SAAS,QAAQ;AACf,SAAO,OAAO,MAAM;AACtB;AACA,SAAS,aAAa;AACpB,SAAO,OAAO;AAChB;AACA,SAAS,cAAc,MAAM;AAC3B,SAAO,cAAc,IAAI;AAC3B;AACA,SAAS,YAAY,MAAM;AACzB,SAAO,OAAO,YAAY,IAAI;AAChC;AACA,SAAS,mBAAmB,MAAM;AAChC,SAAO,OAAO,mBAAmB,IAAI;AACvC;AACA,SAAS,gBAAgB,MAAM,SAAS,WAAW,GAAG;AACpD,SAAO,OAAO,gBAAgB,MAAM,SAAS,QAAQ;AACvD;AACA,SAAS,UAAU;AACjB,SAAO,OAAO;AAChB;AACA,SAAS,YAAY,cAAc,UAAU;AAC3C,MAAI,EAAE,YAAY,cAAc,QAAQ;AAC1C;AAGA,SAAS,MAAM,QAAQ;AACrB,QAAM,SAAS,gBAAgB,QAAQ,SAAS,MAAM;AACtD,QAAM,SAAS,EAAE,OAAO,OAAO;AAC/B,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACxC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,MAAM,QAAQ;AACrB,QAAM,SAAS,gBAAgB,QAAQ,SAAS,MAAM;AACtD,QAAM,SAAS,EAAE,OAAO,OAAO;AAC/B,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,WAAW,GAAG,MAAM,WAAW;AACtC,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,MAAI,QAAQ,MAAM;AAChB,WAAO,GAAG,MAAM,IAAI,CAAC,IAAI,OAAO,EAAE,EAAE,QAAQ;AAAA,EAC9C;AACA,SAAO,GAAG,SAAS,KAAK,QAAQ,MAAM,qCAAqC,GAAG,kCAAkC,OAAO;AACvH,OAAK,QAAQ,CAAC,SAAS;AACrB,WAAO,QAAQ,KAAK,OAAO,GAAG,MAAM,MAAM,+CAA+C,GAAG,OAAO,aAAa,MAAM;AAAA,EACxH,CAAC;AACD,MAAI,GAAG,QAAQ,GAAG;AAChB,WAAO,GAAG,MAAM;AAAA,EAClB;AACA,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,KAAK;AACrB,MAAI,GAAG,UAAU,aAAa;AAC5B,WAAO,KAAK,MAAM;AAChB,UAAI,QAAQ,KAAK,EAAE;AACnB,UAAI,QAAQ,KAAK,EAAE;AACnB,cAAQ,OAAO,UAAU,WAAW,EAAE,GAAG,MAAM,GAAG,KAAK;AACvD,cAAQ,OAAO,UAAU,WAAW,EAAE,GAAG,MAAM,GAAG,KAAK;AACvD,UAAI,WAAW;AACb,gBAAQ,IAAI,KAAK;AAAA,MACnB;AACA,aAAO,QAAQ,OAAO,KAAK;AAAA,IAC7B,CAAC;AAAA,EACH;AACA,SAAO,OAAO,UAAU,WAAW,QAAQ,KAAK;AAClD;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,iBAAiBsB,SAAQ,aAAa,YAAY;AACzD,QAAM,UAAU,gBAAgBA,SAAQ,UAAU,iBAAiB;AACnE,QAAM,eAAe,gBAAgB,aAAa,eAAe,iBAAiB;AAClF,SAAO,cAAc,QAAQ,aAAa,KAAK,OAAO,UAAU,UAAU,GAAG,MAAM,+DAA+D,YAAY;AAC9J,SAAO,QAAQ,SAAS,GAAG,MAAM,gDAAgD,QAAQ,MAAM;AAC/F,SAAO,aAAa,SAAS,GAAG,MAAM,qDAAqD,aAAa,MAAM;AAC9G,SAAO,QAAQ,MAAM,OAAO,aAAa,MAAM,IAAI,MAAM,uCAAuC,QAAQ,MAAM,UAAU,aAAa,MAAM,qEAAqE;AAChN,SAAO,aAAa,KAAK,OAAO,UAAU,UAAU,GAAG,MAAM,4DAA4D,YAAY;AACrI,QAAM,eAAe,OAAO,KAAK,SAAS,OAAO,GAAG,UAAU;AAC9D,QAAM,oBAAoB,OAAO,KAAK,cAAc,OAAO,GAAG,UAAU;AACxE,QAAM,gBAAgB,UAAU,YAAY;AAC5C,QAAM,UAAU,OAAO,eAAe,iBAAiB;AACvD,SAAO,KAAK,SAAS,OAAO;AAC9B;AACA,IAAI,kBAAkB,GAAG,EAAE,iBAAiB,CAAC;AAG7C,IAAI,yBAAyB,CAAC;AAC9BtB,UAAS,wBAAwB;AAAA,EAC/B,4BAA4B,MAAM;AAAA,EAClC,kBAAkB,MAAM;AAAA,EACxB,kBAAkB,MAAM;AAC1B,CAAC;AACD,SAAS,iBAAiB,SAAS,UAAU;AAC3C,QAAM,SAAS,QAAQ;AACvB,QAAM,OAAO,CAAC;AACd,WAAS,KAAK,GAAG,KAAK,QAAQ,MAAM;AAClC,UAAM,MAAM,SAAS,IAAI;AACzB,UAAM,IAAI,QAAQ,QAAQ;AAC1B,UAAM,IAAI,SAAS,SAAS,SAAS,IAAI,OAAO;AAChD,QAAI,IAAI,KAAK,MAAM,GAAG;AACpB,WAAK,QAAQ,GAAG;AAAA,IAClB;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,SAAS,UAAU;AAC3C,QAAM,SAAS,CAAC;AAChB,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,UAAM,QAAQ,QAAQ,QAAQ,SAAS,KAAK;AAC5C,UAAM,UAAU,SAAS,SAAS,KAAK;AACvC,UAAM,SAAS,SAAS;AACxB,QAAI,SAAS,QAAQ,UAAU,KAAK,SAAS,GAAG;AAC9C,aAAO,QAAQ,OAAO;AAAA,IACxB;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,2BAA2B,QAAQ,QAAQ;AAClD,QAAM,SAAS,CAAC;AAChB,QAAM,KAAK,KAAK,IAAI,OAAO,QAAQ,OAAO,MAAM;AAChD,WAAS,KAAK,GAAG,KAAK,IAAI,MAAM;AAC9B,QAAI,IAAI,OAAO,OAAO,SAAS,KAAK;AACpC,QAAI,KAAK,MAAM;AACb,UAAI;AAAA,IACN;AACA,QAAI,IAAI,OAAO,OAAO,SAAS,KAAK;AACpC,QAAI,KAAK,MAAM;AACb,UAAI;AAAA,IACN;AACA,QAAI,MAAM,GAAG;AACX,aAAO,QAAQ,CAAC;AAAA,IAClB,WAAW,MAAM,GAAG;AAClB,aAAO,QAAQ,CAAC;AAAA,IAClB,WAAW,MAAM,GAAG;AAClB,YAAM,SAAS,wDAAwD,cAAc;AACrF,YAAM,MAAM,MAAM;AAAA,IACpB,OAAO;AACL,aAAO,QAAQ,CAAC;AAAA,IAClB;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,kBAAkB,CAAC;AACvBA,UAAS,iBAAiB;AAAA,EACxB,YAAY,MAAM;AAAA,EAClB,iBAAiB,MAAM;AAAA,EACvB,UAAU,MAAM;AAClB,CAAC;AAGD,SAAS,SAAS,QAAQ,OAAO,OAAO;AACtC,gBAAc,MAAM;AACpB,MAAI,SAAS,QAAQ,MAAM,WAAW,GAAG;AACvC,UAAM,IAAI,MAAM,iDAAiD;AAAA,EACnE;AACA,QAAM,gBAAgB,WAAW,QAAQ,KAAK;AAC9C,MAAI,cAAc,WAAW,KAAK,cAAc,WAAW,GAAG;AAC5D,UAAM,IAAI,MAAM,kEAAkE;AAAA,EACpF;AACA,MAAI,cAAc,WAAW,KAAK,SAAS,MAAM;AAC/C,UAAM,IAAI,MAAM,yEAAyE;AAAA,EAC3F;AACA,SAAO,WAAW,QAAQ,OAAO,eAAe,KAAK;AACvD;AAGA,IAAI;AACJ,SAAS,YAAY,QAAQ,cAAc,GAAG;AAC5C,MAAI,cAAc,GAAG;AACnB,UAAM,IAAI,MAAM,gEAAgE;AAAA,EAClF;AACA,MAAI,UAAU,MAAM;AAClB,UAAM,IAAI,MAAM,0DAA0D;AAAA,EAC5E;AACA,MAAI,eAAe;AACnB,MAAI,cAAc;AAClB,MAAI,UAAU;AACd,MAAI,UAAU;AACd,MAAI,eAAe;AACnB,MAAI,gBAAgB;AACpB,MAAI,OAAO,gBAAgB,YAAY;AACrC,mBAAe;AAAA,EACjB,WAAW,OAAO,cAAc,eAAe,kBAAkB,WAAW;AAC1E,kBAAc;AAAA,EAChB,WAAW,OAAO,qBAAqB,eAAe,kBAAkB,kBAAkB;AACxF,cAAU;AAAA,EACZ,WAAW,OAAO,qBAAqB,eAAe,kBAAkB,kBAAkB;AACxF,cAAU;AAAA,EACZ,WAAW,OAAO,cAAc,MAAM;AACpC,mBAAe;AAAA,EACjB,WAAW,OAAO,gBAAgB,eAAe,kBAAkB,aAAa;AAC9E,oBAAgB;AAAA,EAClB,OAAO;AACL,UAAM,IAAI,MAAM,qPAAqP,OAAO,YAAY,MAAM;AAAA,EAChS;AACA,MAAI,SAAS;AACX,UAAM,gCAAgC;AACtC,QAAI,WAAW,OAAO,aAAa,+BAA+B;AAChE,YAAM,IAAI,MAAM,uGAAuG;AAAA,IACzH;AAAA,EACF;AACA,QAAM,SAAS,UAAU,YAAY,OAAO,WAAW;AACvD,MAAI,UAAU,MAAM;AAClB,UAAM,SAAS,EAAE,OAAO;AACxB,UAAM,QAAQ,EAAE,YAAY;AAC5B,WAAO,OAAO,UAAU,YAAY,QAAQ,KAAK;AAAA,EACnD;AACA,QAAM,CAAC,OAAO,MAAM,IAAI,UAAU;AAAA,IAChC,OAAO;AAAA,IACP,OAAO;AAAA,EACT,IAAI,CAAC,OAAO,OAAO,OAAO,MAAM;AAChC,MAAI;AACJ,MAAI,cAAc;AAChB,WAAO,OAAO,WAAW,IAAI,EAAE,aAAa,GAAG,GAAG,OAAO,MAAM,EAAE;AAAA,EACnE,WAAW,eAAe,cAAc;AACtC,WAAO,OAAO;AAAA,EAChB,WAAW,WAAW,WAAW,eAAe;AAC9C,QAAI,uBAAuB,MAAM;AAC/B,UAAI,OAAO,aAAa,aAAa;AACnC,YAAI,OAAO,oBAAoB,eAAe,OAAO,sCAAsC,aAAa;AACtG,gCAAsB,IAAI,gBAAgB,GAAG,CAAC,EAAE,WAAW,IAAI;AAAA,QACjE,OAAO;AACL,gBAAM,IAAI,MAAM,sGAAsG;AAAA,QACxH;AAAA,MACF,OAAO;AACL,8BAAsB,SAAS,cAAc,QAAQ,EAAE,WAAW,MAAM,EAAE,oBAAoB,KAAK,CAAC;AAAA,MACtG;AAAA,IACF;AACA,wBAAoB,OAAO,QAAQ;AACnC,wBAAoB,OAAO,SAAS;AACpC,wBAAoB,UAAU,QAAQ,GAAG,GAAG,OAAO,MAAM;AACzD,WAAO,oBAAoB,aAAa,GAAG,GAAG,OAAO,MAAM,EAAE;AAAA,EAC/D;AACA,MAAI;AACJ,MAAI,gBAAgB,GAAG;AACrB,aAAS,IAAI,WAAW,IAAI;AAAA,EAC9B,OAAO;AACL,UAAM,YAAY,QAAQ;AAC1B,aAAS,IAAI,WAAW,YAAY,WAAW;AAC/C,aAAS,KAAK,GAAG,KAAK,WAAW,MAAM;AACrC,eAAS,UAAU,GAAG,UAAU,aAAa,EAAE,SAAS;AACtD,eAAO,KAAK,cAAc,WAAW,KAAK,KAAK,IAAI;AAAA,MACrD;AAAA,IACF;AAAA,EACF;AACA,QAAM,WAAW,CAAC,QAAQ,OAAO,WAAW;AAC5C,SAAO,SAAS,QAAQ,UAAU,OAAO;AAC3C;AACA,SAAS,YAAY,QAAQ;AAC3B,SAAO,UAAU,QAAQ,OAAO,gBAAgB;AAClD;AACA,SAAS,8BAA8B;AACrC,SAAO,OAAO,WAAW,eAAe,OAAO,gBAAgB,eAAe,OAAO,eAAe,mBAAmB;AACzH;AACA,SAAS,iBAAiB,QAAQ;AAChC,SAAO,UAAU,QAAQ,OAAO,UAAU,KAAK,OAAO,WAAW;AACnE;AACA,SAAS,2BAA2B,QAAQ;AAC1C,SAAO,4BAA4B,KAAK,EAAE,kBAAkB,gBAAgB,iBAAiB,MAAM,KAAK,CAAC,YAAY,MAAM;AAC7H;AACA,eAAe,gBAAgB,QAAQ,cAAc,GAAG;AACtD,MAAI,SAAS;AACb,MAAI,IAAI,EAAE,QAAQ,qBAAqB,KAAK,2BAA2B,MAAM,GAAG;AAC9E,QAAI;AACJ,QAAI;AACF,oBAAc,MAAM,kBAAkB,QAAQ,EAAE,kBAAkB,OAAO,CAAC;AAAA,IAC5E,SAAS,IAAP;AACA,oBAAc;AAAA,IAChB;AACA,QAAI,eAAe,QAAQ,YAAY,UAAU,OAAO,SAAS,YAAY,WAAW,OAAO,QAAQ;AACrG,eAAS;AAAA,IACX,OAAO;AACL,eAAS;AAAA,IACX;AAAA,EACF,OAAO;AACL,aAAS;AAAA,EACX;AACA,SAAO,YAAY,QAAQ,WAAW;AACxC;AACA,eAAe,SAAS,KAAKa,SAAQ;AACnC,MAAI,OAAO,gBAAgB,KAAK,OAAO,UAAU;AACjD,MAAI,EAAE,eAAe,SAAS;AAC5B,UAAM,oBAAoB;AAC1B,WAAO,KAAK,mBAAmB,OAAO;AACtC,sBAAkB,QAAQ;AAAA,EAC5B;AACA,MAAI,KAAK,SAAS,KAAK,KAAK,SAAS,GAAG;AACtC,UAAM,IAAI,MAAM,wDAAwD,KAAK,OAAO;AAAA,EACtF;AACA,QAAM,CAAC,QAAQ,KAAK,IAAI,KAAK,MAAM,MAAM,GAAG,CAAC;AAC7C,QAAM,QAAQ,KAAK,SAAS,IAAI,IAAI,KAAK,MAAM;AAC/C,MAAI,QAAQ,KAAK,UAAU,GAAG;AAC5B,UAAM,IAAI,MAAM,0DAA0D,OAAO;AAAA,EACnF;AACA,MAAI,KAAK,UAAU,aAAa,KAAK,UAAU,SAAS;AACtD,UAAM,IAAI,MAAM,kCAAkC,KAAK,6CAA6C;AAAA,EACtG;AACA,QAAM,OAAO,MAAM,KAAK,KAAK;AAC7B,QAAM,aAAa,KAAK,UAAU,YAAY,MAAM;AACpD,QAAM,QAAQ,IAAI,kBAAkB,QAAQ,SAAS,CAAC;AACtD,WAAS,KAAK,GAAG,KAAK,SAAS,OAAO,EAAE,IAAI;AAC1C,UAAM,OAAO,CAAC,GAAG,GAAG,GAAG,GAAG;AAC1B,aAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,YAAM,QAAQ,KAAK,KAAK,QAAQ;AAChC,UAAI,KAAK,UAAU,WAAW;AAC5B,YAAI,QAAQ,KAAK,QAAQ,GAAG;AAC1B,gBAAM,IAAI,MAAM,mFAAmF,QAAQ;AAAA,QAC7G;AAAA,MACF,WAAW,KAAK,UAAU,SAAS;AACjC,YAAI,QAAQ,KAAK,QAAQ,KAAK;AAC5B,gBAAM,IAAI,MAAM,mFAAmF,QAAQ;AAAA,QAC7G;AAAA,MACF;AACA,UAAI,UAAU,GAAG;AACf,aAAK,KAAK,QAAQ;AAClB,aAAK,KAAK,QAAQ;AAClB,aAAK,KAAK,QAAQ;AAAA,MACpB,OAAO;AACL,aAAK,KAAK,QAAQ;AAAA,MACpB;AAAA,IACF;AACA,UAAM,IAAI,KAAK;AACf,UAAM,IAAI,KAAK,KAAK,MAAM,KAAK,EAAE;AACjC,UAAM,IAAI,KAAK,KAAK,MAAM,KAAK,EAAE;AACjC,UAAM,IAAI,KAAK,KAAK,MAAM,KAAK,EAAE;AACjC,UAAM,IAAI,KAAK,KAAK,MAAM,KAAK,EAAE;AAAA,EACnC;AACA,MAAIA,WAAU,MAAM;AAClB,IAAAA,QAAO,QAAQ;AACf,IAAAA,QAAO,SAAS;AAChB,UAAM,MAAMA,QAAO,WAAW,IAAI;AAClC,UAAM,YAAY,IAAI,UAAU,OAAO,OAAO,MAAM;AACpD,QAAI,aAAa,WAAW,GAAG,CAAC;AAAA,EAClC;AACA,MAAI,SAAS,KAAK;AAChB,SAAK,QAAQ;AAAA,EACf;AACA,SAAO;AACT;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,IAAI,yBAAyB,CAAC;AAC9Bb,UAAS,wBAAwB;AAAA,EAC/B,oBAAoB,MAAM;AAC5B,CAAC;AACD,SAAS,mBAAmB,SAAS,SAAS;AAC5C,QAAM,aAAa,QAAQ,MAAM;AACjC,QAAM,cAAc,QAAQ,MAAM;AAClC,MAAI,aAAa,GAAG;AAClB,UAAM,IAAI,MAAM,4EAA4E,aAAa;AAAA,EAC3G;AACA,MAAI,cAAc,GAAG;AACnB,UAAM,IAAI,MAAM,8EAA8E,cAAc;AAAA,EAC9G;AACA,MAAI,QAAQ,UAAU,SAAS;AAC7B,UAAM,IAAI,MAAM,yEAAyE,QAAQ,QAAQ;AAAA,EAC3G;AACA,MAAI,QAAQ,MAAM,cAAc,KAAK,YAAY;AAC/C,UAAM,IAAI,MAAM,iEAAiE,QAAQ,MAAM,cAAc,UAAU,YAAY;AAAA,EACrI;AACA,MAAI,cAAc,QAAQ,KAAK,MAAM,GAAG;AACtC,UAAM,IAAI,MAAM,mEAAmE,QAAQ,QAAQ;AAAA,EACrG;AACA,QAAM,eAAe,QAAQ;AAC7B,QAAM,YAAY,aAAa,aAAa,SAAS;AACrD,MAAI,UAAU;AACd,WAAS,KAAK,GAAG,KAAK,aAAa,SAAS,GAAG,EAAE,IAAI;AACnD,eAAW,aAAa;AAAA,EAC1B;AACA,QAAM,aAAa,QAAQ;AAC3B,QAAM,cAAc,aAAa,MAAM;AACvC,cAAY,IAAI;AAChB,MAAI,YAAY;AAChB,WAAS,KAAK,WAAW,KAAK,YAAY,EAAE,IAAI;AAC9C,iBAAa,WAAW;AACxB,gBAAY,KAAK,WAAW,GAAG;AAAA,EACjC;AACA,QAAMe,WAAU;AAAA,IACd,GAAG,eAAe,QAAQ,KAAK,EAAE,IAAI,CAAC,WAAW,SAAS,SAAS;AAAA,IACnE;AAAA,EACF,EAAE,MAAM,GAAG,SAAS;AACpB,SAAO,CAAC,aAAa,SAAS,WAAWA,QAAO;AAClD;AAGA,IAAI,0BAA0B,CAAC;AAC/Bf,UAAS,yBAAyB;AAAA,EAChC,iBAAiB,MAAM;AAAA,EACvB,eAAe,MAAM;AAAA,EACrB,qBAAqB,MAAM;AAC7B,CAAC;AACD,SAAS,oBAAoB,OAAO,SAAS,SAAS;AACpD,QAAM,WAAW,QAAQ,OAAO,IAAI,QAAQ,MAAM,QAAQ,OAAO,KAAK;AACtE,QAAM,WAAW,QAAQ,OAAO,IAAI,QAAQ,OAAO,IAAI;AACvD,QAAM,aAAa,6FAA6F,QAAQ,yBAAyB,QAAQ,iBAAiB,oBAAoB,2BAA2B;AACzN,MAAI,QAAQ,OAAO,UAAU;AAC3B,UAAM,IAAI,MAAM,aAAa,kBAAkB,YAAY;AAAA,EAC7D;AACA,MAAI,MAAM,SAAS,YAAY,QAAQ,OAAO,WAAW;AACvD,UAAM,IAAI,MAAM,aAAa,0BAA0B,YAAY,QAAQ,OAAO,WAAW;AAAA,EAC/F;AACA,MAAI,QAAQ,SAAS,WAAW,MAAM,SAAS,UAAU;AACvD,UAAM,IAAI,MAAM,aAAa,mBAAmB,WAAW,MAAM,SAAS,UAAU;AAAA,EACtF;AACA,WAAS,IAAI,GAAG,IAAI,UAAU,EAAE,GAAG;AACjC,QAAI,QAAQ,MAAM,OAAO,QAAQ,MAAM,IAAI;AACzC,YAAM,IAAI,MAAM,aAAa,kBAAkB,OAAO,QAAQ,MAAM,wBAAwB,OAAO,QAAQ,MAAM,MAAM;AAAA,IACzH;AAAA,EACF;AACA,WAAS,IAAI,GAAG,IAAI,QAAQ,OAAO,UAAU,EAAE,GAAG;AAChD,QAAI,QAAQ,MAAM,IAAI,cAAc,MAAM,IAAI,WAAW;AACvD,YAAM,IAAI,MAAM,aAAa,kBAAkB,IAAI,cAAc,QAAQ,MAAM,IAAI,uBAAuB,IAAI,cAAc,MAAM,IAAI,YAAY;AAAA,IACpJ;AAAA,EACF;AACF;AACA,SAAS,cAAc,SAAS,SAAS,OAAO;AAC9C,MAAI,QAAQ,OAAO,GAAG;AACpB,UAAM,IAAI,MAAM,+EAA+E,QAAQ,OAAO;AAAA,EAChH;AACA,MAAI,QAAQ,OAAO,GAAG;AACpB,UAAM,IAAI,MAAM,+EAA+E,QAAQ,OAAO;AAAA,EAChH;AACA,MAAI,QAAQ,UAAU,SAAS;AAC7B,UAAM,IAAI,MAAM,0DAA0D,QAAQ,OAAO;AAAA,EAC3F;AACA,MAAI,MAAM,SAAS,GAAG;AACpB,UAAM,IAAI,MAAM,6DAA6D,OAAO;AAAA,EACtF;AACA,MAAI,MAAM,WAAW,GAAG;AACtB,QAAI,QAAQ,SAAS,GAAG;AACtB,YAAM,IAAI,MAAM,sDAAsD,QAAQ,OAAO;AAAA,IACvF;AACA,QAAI,QAAQ,SAAS,GAAG;AACtB,YAAM,IAAI,MAAM,sDAAsD,QAAQ,OAAO;AAAA,IACvF;AAAA,EACF;AACA,sBAAoB,OAAO,SAAS,OAAO;AAC7C;AACA,SAAS,gBAAgB,SAAS,SAAS,OAAO;AAChD,QAAM,cAAc,QAAQ,MAAM;AAClC,QAAM,YAAY,cAAc,IAAI,QAAQ,MAAM,cAAc,KAAK;AACrE,QAAM,UAAU,MAAM;AACtB,MAAI,YAAY;AAChB,WAAS,KAAK,WAAW,KAAK,SAAS,EAAE,IAAI;AAC3C,iBAAa,MAAM;AAAA,EACrB;AACA,QAAM,eAAe,YAAY,IAAI,IAAI;AACzC,QAAM,aAAa,cAAc,QAAQ,KAAK,IAAI;AAClD,QAAMe,WAAU,CAAC,GAAG,eAAe,MAAM,MAAM,GAAG,SAAS,CAAC,GAAG,CAAC;AAChE,QAAMQ,cAAa,cAAc,KAAK;AACtC,SAAO,EAAE,WAAW,YAAY,WAAW,SAAAR,UAAS,YAAAQ,YAAW;AACjE;AAGA,IAAI,qBAAqB,CAAC;AAC1BvB,UAAS,oBAAoB;AAAA,EAC3B,mBAAmB,MAAM;AAAA,EACzB,mBAAmB,MAAM;AAAA,EACzB,iBAAiB,MAAM;AAAA,EACvB,mBAAmB,MAAM;AAAA,EACzB,kBAAkB,MAAM;AAAA,EACxB,YAAY,MAAM;AAAA,EAClB,kBAAkB,MAAM;AAAA,EACxB,WAAW,MAAM;AAAA,EACjB,cAAc,MAAM;AAAA,EACpB,4BAA4B,MAAM;AAAA,EAClC,aAAa,MAAM;AAAA,EACnB,2BAA2B,MAAM;AAAA,EACjC,gBAAgB,MAAM;AAAA,EACtB,uBAAuB,MAAM;AAC/B,CAAC;AACD,IAAI,WAAW;AACf,IAAI,cAAc;AAClB,SAAS,kBAAkB,QAAQ,OAAOG,OAAM;AAC9C,QAAM,YAAY,OAAO,MAAM;AAC/B,SAAO,cAAc,MAAM,QAAQ,MAAM,iBAAiB,+BAA+B,2CAA2C,aAAa;AACjJ,SAAO,cAAcA,MAAK,QAAQ,MAAM,iBAAiB,8BAA8BA,2CAA0C,aAAa;AAC9I,WAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,WAAO,MAAM,MAAMA,MAAK,OAAO,OAAO,MAAM,KAAK,MAAM,iBAAiB,qBAAqB,cAAc,QAAQ,MAAM,MAAMA,MAAK,mCAAmC,QAAQ,OAAO,MAAM,MAAM;AAAA,EACpM;AACF;AACA,SAAS,WAAWK,OAAM;AACxB,QAAM,OAAO,CAAC;AACd,MAAI,OAAO;AACX,SAAOA,QAAO,GAAG;AACf,QAAIA,QAAO,GAAG;AACZ,WAAK,KAAK,IAAI;AAAA,IAChB;AACA,IAAAA,SAAQ;AACR;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,gBAAgB,OAAO,KAAKO,UAAS;AAC5C,QAAMZ,QAAO,CAAC;AACd,WAAS,OAAO,GAAG,OAAO,MAAM,QAAQ,QAAQ;AAC9C,IAAAA,MAAK,QAAQ,KAAK,MAAM,IAAI,QAAQ,MAAM,SAASY,SAAQ,KAAK;AAAA,EAClE;AACA,SAAOZ;AACT;AACA,SAAS,sBAAsBY,UAAS,wBAAwB,eAAe,YAAY;AACzF,QAAM,aAAa,CAAC,GAAGA,QAAO;AAC9B,WAAS,KAAK,WAAW,QAAQ,KAAK,WAAW,QAAQ,MAAM;AAC7D,eAAW,KAAK,CAAC;AAAA,EACnB;AACA,WAAS,KAAK,GAAG,KAAK,eAAe,MAAM;AACzC,QAAI,OAAO,GAAG;AACZ,iBAAW,0BAA0B;AAAA,IACvC,OAAO;AACL,iBAAW,OAAO,wBAAwB,GAAG,CAAC;AAC9C,iBAAW,IAAI;AAAA,IACjB;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,gBAAgB,wBAAwB,eAAe,gBAAgB;AAC9E,MAAI,kBAAkB,wBAAwB;AAC5C,WAAO;AAAA,EACT;AACA,SAAO,kBAAkB,gBAAgB;AAC3C;AACA,SAAS,cAAc,eAAe,wBAAwB;AAC5D,QAAM,aAAa,CAAC;AACpB,WAAS,KAAK,GAAG,KAAK,eAAe,MAAM;AACzC,eAAW,KAAK,yBAAyB,EAAE;AAAA,EAC7C;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,YAAY,cAAc,qBAAqB,OAAO,KAAKA,UAAS,WAAW,SAAS,cAAc;AAC/H,QAAM,YAAY,WAAW;AAC7B,MAAI,kBAAkB,IAAI,MAAM,SAAS,GAAG,gBAAgB,IAAI,MAAM,SAAS,GAAG,oBAAoB,IAAI,MAAM,SAAS;AACzH,MAAI,aAAa,UAAU,sBAAsB,GAAG;AAClD,UAAM,YAAY,aAAa;AAC/B,UAAM,gBAAgB,sBAAsB;AAC5C,sBAAkB,2BAA2B,WAAW,WAAW,eAAe,OAAO,UAAU;AACnG,oBAAgB,0BAA0B,SAAS,WAAW,eAAe,KAAK,UAAU;AAC5F,wBAAoB,sBAAsBA,UAAS,WAAW,eAAe,UAAU;AAAA,EACzF,OAAO;AACL,aAAS,OAAO,GAAG,OAAO,WAAW,QAAQ;AAC3C,sBAAgB,QAAQ,aAAa,WAAW,OAAOA,UAAS,YAAY,MAAM,YAAY;AAC9F,oBAAc,QAAQ,YAAY,SAAS,KAAKA,UAAS,YAAY,MAAM,YAAY;AACvF,wBAAkB,QAAQ,eAAeA,UAAS,MAAM,YAAY;AAAA,IACtE;AAAA,EACF;AACA,SAAO;AAAA,IACL,OAAO;AAAA,IACP,KAAK;AAAA,IACL,SAAS;AAAA,EACX;AACF;AACA,SAAS,2BAA2B,WAAW,wBAAwB,eAAe,eAAe,YAAY;AAC/G,QAAM,aAAa,CAAC,GAAG,UAAU;AACjC,QAAM,aAAa,cAAc,eAAe,sBAAsB;AACtE,WAAS,OAAO,GAAG,OAAO,WAAW,QAAQ,QAAQ;AACnD,QAAI,WAAW,QAAQ,IAAI,IAAI,IAAI;AACjC,iBAAW,QAAQ;AAAA,IACrB,OAAO;AACL,YAAM,eAAe,gBAAgB,wBAAwB,eAAe,IAAI;AAChF,UAAI,gBAAgB,cAAc;AAClC,UAAI,YAAY,KAAK,cAAc;AACjC,wBAAgB;AAAA,MAClB;AACA,iBAAW,QAAQ;AAAA,IACrB;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,0BAA0B,SAAS,wBAAwB,eAAe,aAAa,YAAY;AAC1G,QAAM,aAAa,CAAC,GAAG,UAAU;AACjC,QAAM,aAAa,cAAc,eAAe,sBAAsB;AACtE,WAAS,OAAO,GAAG,OAAO,WAAW,QAAQ,QAAQ;AACnD,QAAI,WAAW,QAAQ,IAAI,IAAI,IAAI;AACjC,iBAAW,QAAQ,OAAO;AAAA,IAC5B,OAAO;AACL,YAAM,eAAe,gBAAgB,wBAAwB,eAAe,IAAI;AAChF,UAAI,gBAAgB,YAAY;AAChC,UAAI,UAAU,KAAK,cAAc;AAC/B,wBAAgB,OAAO;AAAA,MACzB;AACA,iBAAW,QAAQ;AAAA,IACrB;AAAA,EACF;AACA,WAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,MAAM;AAC7C,UAAM,WAAW,WAAW;AAC5B,QAAI,WAAW,MAAM,GAAG;AACtB,iBAAW,OAAO;AAAA,IACpB;AACA,eAAW,MAAM,MAAM,GAAG,WAAW,KAAK,WAAW,GAAG;AAAA,EAC1D;AACA,SAAO;AACT;AACA,SAAS,eAAeA,UAAS,MAAM,cAAc;AACnD,MAAI,SAASA,SAAQ;AACrB,MAAI,eAAe,KAAK,QAAQ,UAAU,MAAM;AAC9C,aAAS;AAAA,EACX;AACA,SAAO;AACT;AACA,SAAS,aAAa,WAAW,cAAcA,UAAS,YAAY,MAAM,cAAc;AACtF,MAAI,QAAQ,aAAa;AACzB,QAAM,SAASA,SAAQ,SAAS;AAChC,MAAI,YAAY,KAAK,QAAQ,eAAe,KAAK,QAAQ,SAAS,MAAM;AACtE,QAAI,SAAS,GAAG;AACd,cAAQ,OAAO;AAAA,IACjB,OAAO;AACL,cAAQ,OAAO;AAAA,IACjB;AAAA,EACF;AACA,QAAM,WAAW,WAAW;AAC5B,MAAI,QAAQ,GAAG;AACb,aAAS;AAAA,EACX;AACA,UAAQ,MAAM,GAAG,OAAO,WAAW,CAAC;AACpC,SAAO;AACT;AACA,SAAS,YAAY,SAAS,aAAaA,UAAS,YAAY,MAAM,cAAc;AAClF,MAAI,OAAO,YAAY;AACvB,QAAM,SAASA,SAAQ,SAAS;AAChC,MAAI,UAAU,KAAK,QAAQ,eAAe,KAAK,QAAQ,QAAQ,MAAM;AACnE,QAAI,SAAS,GAAG;AACd,aAAO,OAAO;AAAA,IAChB,OAAO;AACL,aAAO,OAAO;AAAA,IAChB;AAAA,EACF;AACA,QAAM,WAAW,WAAW;AAC5B,MAAI,OAAO,GAAG;AACZ,YAAQ;AAAA,EACV;AACA,MAAI,SAAS,GAAG;AACd,WAAO,MAAM,GAAG,MAAM,QAAQ;AAAA,EAChC,OAAO;AACL,WAAO,MAAM,IAAI,MAAM,WAAW,CAAC;AAAA,EACrC;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,OAAO,OAAOZ,OAAM;AAC5C,MAAI,kBAAkBA,MAAK;AAC3B,WAAS,KAAK,GAAG,KAAKA,MAAK,QAAQ,MAAM;AACvC,QAAIA,MAAK,MAAM,GAAG;AAChB,wBAAkB;AAClB;AAAA,IACF;AAAA,EACF;AACA,WAAS,KAAK,kBAAkB,GAAG,KAAKA,MAAK,QAAQ,MAAM;AACzD,QAAI,MAAM,MAAM,KAAKA,MAAK,QAAQ,MAAM,KAAK;AAC3C,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,OAAOY,UAAS;AACzC,MAAI,aAAa,MAAM,SAAS,IAAI,MAAM,MAAM,SAAS,KAAK;AAC9D,WAAS,KAAK,GAAG,KAAK,MAAM,SAAS,GAAG,MAAM;AAC5C,kBAAc,MAAM,MAAMA,SAAQ;AAAA,EACpC;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,GAAG,OAAOZ,OAAM;AACxC,MAAI;AACJ,QAAM,QAAQ,EAAE,MAAM;AACtB,MAAI,OAAO,UAAU,UAAU;AAC7B,aAAS,CAAC,OAAO,GAAG,IAAI,MAAM,QAAQ,CAAC,EAAE,KAAK,CAAC,CAAC;AAAA,EAClD,WAAW,MAAM,SAAS,OAAO;AAC/B,aAAS,MAAM,OAAO,IAAI,MAAM,QAAQ,MAAM,MAAM,EAAE,KAAK,CAAC,CAAC;AAAA,EAC/D,OAAO;AACL,aAAS,MAAM,MAAM;AAAA,EACvB;AACA,SAAO,QAAQ,CAAC,MAAM;AACpB,WAAO,MAAM,IAAI,MAAM,mDAAmD;AAAA,EAC5E,CAAC;AACD,MAAI;AACJ,MAAIA,SAAQ,MAAM;AAChB,YAAQ,IAAI,MAAM,KAAK,EAAE,KAAK,EAAE;AAAA,EAClC,WAAW,OAAOA,UAAS,UAAU;AACnC,YAAQ,CAACA,OAAM,GAAG,IAAI,MAAM,QAAQ,CAAC,EAAE,KAAK,EAAE,CAAC;AAAA,EACjD,WAAWA,MAAK,SAAS,OAAO;AAC9B,YAAQA,MAAK,OAAO,IAAI,MAAM,QAAQA,MAAK,MAAM,EAAE,KAAK,EAAE,CAAC;AAAA,EAC7D,OAAO;AACL,YAAQA;AAAA,EACV;AACA,UAAQ,MAAM,IAAI,CAAC,GAAG,OAAO;AAC3B,QAAI,KAAK,GAAG;AACV,aAAO;AAAA,IACT,OAAO;AACL,aAAO,MAAM,IAAI,MAAM,qDAAqD,mCAAmC,KAAK;AACpH,aAAO,EAAE,MAAM,MAAM,OAAO;AAAA,IAC9B;AAAA,EACF,CAAC;AACD,SAAO,CAAC,QAAQ,KAAK;AACvB;AACA,SAAS,UAAU,QAAQ,OAAO,KAAKY,UAAS,WAAW,SAAS,cAAc,aAAa,gBAAgB;AAC7G,MAAI;AACJ,MAAIA,YAAW,MAAM;AACnB,qBAAiB,IAAI,MAAM,MAAM,MAAM;AACvC,mBAAe,KAAK,CAAC;AAAA,EACvB,OAAO;AACL,qBAAiBA;AAAA,EACnB;AACA,MAAI,gBAAgB,SAAS,eAAe,eAAe,OAAO,GAAG;AACnE,UAAM,IAAI,MAAM,4CAA4C;AAAA,EAC9D;AACA,MAAI,eAAe;AACnB,QAAM,aAAa;AAAA,IACjB,MAAM,eAAe;AAAA,IACrB,yBAAyB;AAAA,IACzB,OAAO,MAAM,MAAM;AAAA,IACnB,KAAK,IAAI,MAAM;AAAA,IACf,SAAS,eAAe,MAAM;AAAA,IAC9B;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACA,WAAS,KAAK,GAAG,KAAK,WAAW,MAAM,MAAM;AAC3C,QAAI,iBAAiB,KAAK,KAAK,iBAAiB,GAAG;AACjD,iBAAW;AAAA,IACb;AACA,QAAI,KAAK,KAAK,cAAc;AAC1B,qBAAe;AAAA,IACjB;AAAA,EACF;AACA,MAAI,CAAC,cAAc;AACjB,eAAW,gBAAgB,KAAK,WAAW;AAC3C,eAAW;AAAA,EACb;AACA,QAAM,YAAY;AAAA,IAChB,MAAM,OAAO;AAAA,IACb,WAAW;AAAA,IACX,SAAS;AAAA,IACT,YAAY;AAAA,IACZ,UAAU;AAAA,EACZ;AACA,iBAAe,YAAY,SAAS;AACpC,MAAI,aAAa;AACjB,MAAI,YAAY;AAChB,MAAI,gBAAgB;AACpB,QAAM,kBAAkB,CAAC;AACzB,QAAM,aAAa,CAAC;AACpB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,QAAI,UAAU,QAAQ,QAAQ,GAAG;AAC/B,YAAM,MAAM,WAAW,sBAAsB;AAAA,IAC/C;AACA,UAAM,UAAU,CAAC,EAAE,UAAU,iBAAiB,KAAK;AACnD,UAAM,OAAO,OAAO;AACpB,QAAI,SAAS,IAAI;AACf,sBAAgB,KAAK,UAAU,IAAI,EAAE;AACrC;AAAA,IACF;AACA,UAAM,QAAQ,CAAC,UAAU,YAAY,KAAK,IAAI,UAAU,UAAU,KAAK,EAAE;AACzE,UAAM,aAAa;AAAA,MACjB,UAAU,QAAQ,MAAM,IAAI,IAAI;AAAA,MAChC,UAAU,QAAQ,MAAM,IAAI,OAAO,OAAO;AAAA,IAC5C;AACA,QAAI,WAAW,UAAU,QAAQ,OAAO,GAAG;AACzC,YAAM,MAAM,8CAA8C;AAAA,IAC5D;AACA,oBAAgB,iBAAiB,UAAU,QAAQ,QAAQ;AAC3D,UAAM,oBAAoB,CAAC,EAAE,UAAU,YAAY,KAAK,MAAM,UAAU,UAAU,KAAK;AACvF,QAAI,UAAU,cAAc,UAAU,UAAU;AAC9C,UAAI,SAAS;AACX,cAAM,OAAO,UAAU,MAAM,MAAM,IAAI,OAAO,UAAU,MAAM,MAAM,UAAU,MAAM;AACpF,kBAAU,MAAM,MAAM;AACtB,kBAAU,IAAI,MAAM,UAAU,MAAM,MAAM;AAC1C,YAAI,OAAO,KAAK,QAAQ,MAAM;AAC5B,gBAAM,MAAM,eAAe,UAAU,MAAM,oBAAoB,mBAAmB;AAAA,QACpF;AAAA,MACF,OAAO;AACL,kBAAU,MAAM,MAAM,UAAU,UAAU,MAAM,KAAK,GAAG,UAAU,QAAQ,KAAK,MAAM,OAAO,UAAU;AACtG,kBAAU,IAAI,MAAM,UAAU,UAAU,IAAI,KAAK,GAAG,UAAU,QAAQ,KAAK,MAAM,OAAO,UAAU;AAAA,MACpG;AACA,YAAM,qBAAqB,UAAU,QAAQ,QAAQ,KAAK,UAAU,MAAM,QAAQ,KAAK,UAAU,IAAI,QAAQ;AAC7G,mBAAa,cAAc;AAC3B,kBAAY,cAAc,OAAO,KAAK,UAAU,QAAQ,QAAQ,KAAK;AAAA,IACvE,OAAO;AACL,mBAAa,eAAe,UAAU,QAAQ,QAAQ,KAAK;AAC3D,kBAAY,cAAc,OAAO,KAAK,UAAU,QAAQ,QAAQ,KAAK;AAAA,IACvE;AACA,QAAI;AACJ,QAAI,gBAAgB;AACpB,QAAI,UAAU,cAAc,UAAU,UAAU;AAC9C,uBAAiB,UAAU,IAAI,MAAM,UAAU,MAAM;AACrD,sBAAgB;AAAA,IAClB,WAAW,SAAS;AAClB,uBAAiB;AACjB,sBAAgB;AAAA,IAClB,WAAW,mBAAmB;AAC5B,UAAI,QAAQ,GAAG;AACb,YAAI,UAAU,QAAQ,MAAM,GAAG;AAC7B,2BAAiB,CAAC;AAAA,QACpB,OAAO;AACL,2BAAiB;AAAA,QACnB;AACA,wBAAgB;AAAA,MAClB;AAAA,IACF;AACA,QAAI,eAAe;AACjB,UAAI;AACJ,UAAI,mBAAmB,KAAK,iBAAiB,MAAM,UAAU,QAAQ,MAAM,GAAG;AAC5E,gBAAQ;AAAA,MACV,OAAO;AACL,gBAAQ,KAAK,MAAM,iBAAiB,UAAU,QAAQ,GAAG,KAAK,iBAAiB,UAAU,QAAQ,QAAQ,IAAI,IAAI;AAAA,MACnH;AACA,sBAAgB,KAAK,KAAK;AAAA,IAC5B,OAAO;AACL,sBAAgB,KAAK,EAAE;AAAA,IACzB;AAAA,EACF;AACA,WAAS,WAAW,GAAG,WAAW,UAAU,wBAAwB,QAAQ,EAAE,UAAU;AACtF,UAAM,cAAc,UAAU,wBAAwB;AACtD,QAAI,eAAe,GAAG;AACpB,iBAAW,KAAK,gBAAgB,YAAY;AAAA,IAC9C,WAAW,gBAAgB,UAAU;AACnC,iBAAW,KAAK,CAAC;AAAA,IACnB;AAAA,EACF;AACA,QAAM,mBAAmB,WAAW,OAAO,CAAC,KAAK,OAAO,UAAU,wBAAwB,QAAQ,QAAQ;AAC1G,SAAO;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA,OAAO,UAAU;AAAA,IACjB,KAAK,UAAU;AAAA,IACf,SAAS,UAAU;AAAA,EACrB;AACF;AACA,SAAS,eAAe,SAAS,QAAQ;AACvC,SAAO,YAAY;AACnB,SAAO,UAAU;AACjB,SAAO,iBAAiB;AACxB,MAAI,YAAY;AAChB,SAAO,aAAa,QAAQ,SAAS;AACrC,SAAO,WAAW,QAAQ,OAAO;AACjC,SAAO,QAAQ,IAAI,MAAM,OAAO,IAAI;AACpC,SAAO,MAAM,IAAI,MAAM,OAAO,IAAI;AAClC,SAAO,UAAU,IAAI,MAAM,OAAO,IAAI;AACtC,SAAO,0BAA0B,CAAC;AAClC,SAAO,gCAAgC,CAAC;AACxC,SAAO,gCAAgC,IAAI,MAAM,OAAO,IAAI;AAC5D,WAAS,KAAK,GAAG,KAAK,QAAQ,MAAM,MAAM;AACxC,QAAI,KAAK,KAAK,QAAQ,cAAc;AAClC,YAAM,YAAY,KAAK,IAAI,OAAO,QAAQ,QAAQ,OAAO,MAAM,IAAI,QAAQ,yBAAyB,OAAO,IAAI;AAC/G,aAAO,YAAY,WAAW,aAAa;AACzC,eAAO,MAAM,aAAa;AAC1B,eAAO,IAAI,aAAa;AACxB,eAAO,QAAQ,aAAa;AAC5B,eAAO,aAAa,KAAK;AACzB,eAAO,WAAW,KAAK;AACvB,eAAO,wBAAwB,KAAK,SAAS;AAC7C,eAAO,8BAA8B,KAAK,EAAE;AAC5C,eAAO,8BAA8B,aAAa;AAAA,MACpD;AAAA,IACF,WAAW,KAAK,KAAK,QAAQ,aAAa;AACxC,aAAO,wBAAwB,KAAK,QAAQ;AAC5C,aAAO,8BAA8B,KAAK,EAAE;AAAA,IAC9C,OAAO;AACL,UAAI,cAAc,OAAO,MAAM,QAAQ;AACrC,cAAM,MAAM,sCAAsC,6BAA6B,OAAO,cAAc,OAAO,MAAM,SAAS;AAAA,MAC5H;AACA,UAAI,QAAQ,SAAS,MAAM;AACzB,eAAO,MAAM,aAAa,QAAQ,MAAM;AAAA,MAC1C;AACA,UAAI,QAAQ,OAAO,MAAM;AACvB,eAAO,IAAI,aAAa,QAAQ,IAAI;AAAA,MACtC;AACA,aAAO,QAAQ,aAAa,QAAQ,QAAQ;AAC5C,UAAI,QAAQ,YAAY,KAAK,IAAI;AAC/B,eAAO,aAAa,KAAK;AAAA,MAC3B;AACA,UAAI,QAAQ,UAAU,KAAK,IAAI;AAC7B,eAAO,WAAW,KAAK;AAAA,MACzB;AACA,UAAI,QAAQ,iBAAiB,KAAK,IAAI;AACpC,eAAO,wBAAwB,KAAK,WAAW;AAC/C,eAAO,8BAA8B,KAAK,EAAE;AAC5C,eAAO,kBAAkB,KAAK;AAAA,MAChC,OAAO;AACL,eAAO,wBAAwB,KAAK,SAAS;AAC7C,eAAO,8BAA8B,KAAK,EAAE;AAAA,MAC9C;AACA,aAAO,8BAA8B,aAAa;AAClD;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,UAAU,GAAG,GAAG,SAAS,MAAM,OAAO,YAAY;AACzD,MAAI,MAAM,IAAI;AACZ,WAAO,UAAU,IAAI,WAAW,KAAK,WAAW,IAAI,IAAI;AAAA,EAC1D,OAAO;AACL,UAAM,OAAO,IAAI,IAAI,OAAO,IAAI;AAChC,WAAO,OAAO,WAAW,KAAK,WAAW,KAAK,OAAO,WAAW,KAAK,WAAW,KAAK;AAAA,EACvF;AACF;AAGA,IAAI,wBAAwB,CAAC;AAC7Bf,UAAS,uBAAuB;AAAA,EAC9B,cAAc,MAAM;AAAA,EACpB,kBAAkB,MAAM;AAAA,EACxB,eAAe,MAAM;AACvB,CAAC;AACD,IAAI,eAAe,MAAM;AAAA,EACvB,eAAe;AACb,WAAO,KAAK,YAAY;AAAA,EAC1B;AAAA,EACA,OAAO,WAAW,KAAKiB,SAAQ;AAC7B,WAAO,IAAI,IAAIA,OAAM;AAAA,EACvB;AACF;AACA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,cAAc;AACZ,SAAK,eAAe,CAAC;AAAA,EACvB;AAAA,EACA,OAAO,SAAS;AACd,QAAI,iBAAiB,YAAY,MAAM;AACrC,uBAAiB,WAAW,IAAI,iBAAiB;AAAA,IACnD;AACA,WAAO,iBAAiB;AAAA,EAC1B;AAAA,EACA,OAAO,SAAS,KAAK;AACnB,qBAAiB,OAAO,EAAE,aAAa,IAAI,aAAa,CAAC,KAAK,IAAI,UAAU;AAAA,EAC9E;AACF;AACA,SAAS,cAAc,KAAK;AAC1B,SAAO,IAAI,aAAa,MAAM,MAAM,6EAA6E;AACjH,SAAO,OAAO,IAAI,cAAc,UAAU,MAAM,wDAAwD,OAAO,IAAI,SAAS;AAC5H,SAAO,IAAI,UAAU,SAAS,GAAG,MAAM,mFAAmF;AAC1H,mBAAiB,SAAS,GAAG;AAC/B;AAGA,IAAI,oBAAoB,CAAC;AACzBjB,UAAS,mBAAmB;AAAA,EAC1B,sBAAsB,MAAM;AAAA,EAC5B,eAAe,MAAM;AAAA,EACrB,yBAAyB,MAAM;AAAA,EAC/B,mBAAmB,MAAM;AAAA,EACzB,mBAAmB,MAAM;AAAA,EACzB,oBAAoB,MAAM;AAAA,EAC1B,qBAAqB,MAAM;AAAA,EAC3B,qBAAqB,MAAM;AAAA,EAC3B,aAAa,MAAM;AACrB,CAAC;AACD,IAAI,uBAAuB;AAC3B,IAAI,uBAAuB;AAC3B,SAAS,kBAAkB,QAAQ,UAAU,UAAU;AACrD,MAAI,YAAY,MAAM;AACpB,eAAW,YAAY;AAAA,EACzB;AACA,SAAO,sBAAsB,QAAQ,UAAU,CAAC,GAAG,MAAM,SAAS,GAAG,GAAG,QAAQ,CAAC;AACnF;AACA,SAAS,cAAc;AACrB,SAAO,OAAO,QAAQ,eAAe,MAAM,KAAK,uBAAuB;AACzE;AACA,SAAS,sBAAsB,QAAQ,UAAU,WAAW;AAC1D,MAAI,iBAAiB;AACrB,MAAI,aAAa,MAAM,KAAK,aAAa,QAAQ,GAAG;AAClD,qBAAiB;AAAA,EACnB;AACA,MAAI,aAAa,MAAM,KAAK,aAAa,QAAQ,GAAG;AAClD,qBAAiB;AAAA,EACnB;AACA,MAAI,gBAAgB;AAClB,UAAM,QAAQ,OAAO,YAAY;AACjC,UAAM,QAAQ,SAAS,YAAY;AACnC,QAAI,UAAU,OAAO;AACnB,YAAM,IAAI,MAAM,yCAAyC,oBAAoB,OAAO;AAAA,IACtF;AAAA,EACF;AACA,MAAI,MAAM,QAAQ,MAAM,KAAK,MAAM,QAAQ,QAAQ,GAAG;AACpD,UAAM,cAAc,WAAW,MAAM;AACrC,UAAM,gBAAgB,WAAW,QAAQ;AACzC,QAAI,CAAC,YAAY,aAAa,aAAa,GAAG;AAC5C,YAAM,IAAI,MAAM,0CAA0C,4BAA4B,gBAAgB;AAAA,IACxG;AAAA,EACF;AACA,QAAM,aAAa,aAAa,MAAM,IAAI,SAAS,QAAQ,MAAM;AACjE,QAAM,eAAe,aAAa,QAAQ,IAAI,WAAW,QAAQ,QAAQ;AACzE,MAAI,WAAW,WAAW,aAAa,QAAQ;AAC7C,UAAM,IAAI,MAAM,yCAAyC,WAAW,uBAAuB,aAAa;AAAA,YAChG;AAAA,YACA,eAAe;AAAA,EACzB;AACA,WAAS,KAAK,GAAG,KAAK,aAAa,QAAQ,EAAE,IAAI;AAC/C,UAAM,IAAI,WAAW;AACrB,UAAM,KAAK,aAAa;AACxB,QAAI,CAAC,UAAU,GAAG,EAAE,GAAG;AACrB,YAAM,IAAI,MAAM,yBAAyB,SAAS,eAAe,SAAS;AAAA,YACpE;AAAA,YACA,eAAe;AAAA,IACvB;AAAA,EACF;AACF;AACA,SAAS,oBAAoB,IAAI,MAAM;AACrC,KAAG,EAAE,KAAK,MAAM,KAAK,KAAK,GAAG,MAAM,KAAK,CAAC;AAC3C;AACA,SAAS,kBAAkB,QAAQ,UAAU;AAC3C,QAAM,OAAO,OAAO,aAAa,YAAY,OAAO,aAAa,YAAY,OAAO,aAAa,YAAY,CAAC,QAAQ,IAAI;AAC1H,MAAI,SAAS,MAAM,KAAK,SAAS,OAAO,EAAE,KAAK,SAAS,QAAQ,KAAK,SAAS,SAAS,EAAE,GAAG;AAC1F,WAAO,sBAAsB,QAAQ,MAAM,CAAC,GAAG,MAAM,KAAK,CAAC;AAAA,EAC7D;AACA,SAAO,sBAAsB,QAAQ,UAAU,CAAC,GAAG,MAAM,SAAS,GAAG,GAAG,CAAC,CAAC;AAC5E;AACA,SAAS,mBAAmB,GAAG,IAAI,UAAU;AAC3C,MAAI,YAAY,MAAM;AACpB,eAAW,YAAY;AAAA,EACzB;AACA,MAAI,CAAC,SAAS,GAAG,IAAI,QAAQ,GAAG;AAC9B,UAAM,IAAI,MAAM,8BAA8B,mBAAmB,IAAI;AAAA,EACvE;AACF;AACA,SAAS,SAAS,GAAG,IAAI,UAAU;AACjC,MAAI,CAAC,SAAS,CAAC,KAAK,CAAC,SAAS,EAAE,GAAG;AACjC,WAAO;AAAA,EACT;AACA,MAAI,MAAM,CAAC,KAAK,MAAM,EAAE,KAAK,KAAK,IAAI,IAAI,EAAE,IAAI,UAAU;AACxD,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,oBAAoB,QAAQ,KAAK,MAAM;AAC9C,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,QAAI,OAAO,MAAM,OAAO,OAAO,MAAM,MAAM;AACzC,YAAM,IAAI,MAAM,sBAAsB,OAAO,YAAY,cAAc,MAAM;AAAA,IAC/E;AAAA,EACF;AACF;AACA,SAAS,wBAAwB,QAAQ,UAAU;AACjD,QAAM,cAAc,IAAI,aAAa,MAAM;AAC3C,QAAM,gBAAgB,IAAI,aAAa,QAAQ;AAC/C,MAAI,YAAY,WAAW,cAAc,QAAQ;AAC/C,UAAM,IAAI,MAAM,wCAAwC,cAAc,sBAAsB,YAAY,QAAQ;AAAA,EAClH;AACA,WAAS,KAAK,GAAG,KAAK,cAAc,QAAQ,MAAM;AAChD,QAAI,YAAY,QAAQ,cAAc,KAAK;AACzC,YAAM,IAAI,MAAM,iCAAiC,YAAY,cAAc,eAAe,YAAY,aAAa;AAAA,IACrH;AAAA,EACF;AACF;AACA,SAAS,cAAc,GAAG;AACxB,WAAS,KAAK,GAAG,KAAK,EAAE,QAAQ,MAAM;AACpC,UAAM,MAAM,EAAE;AACd,QAAI,MAAM,QAAQ,GAAG,GAAG;AACtB,oBAAc,GAAG;AAAA,IACnB,OAAO;AACL,QAAE,MAAM,aAAa,GAAG;AAAA,IAC1B;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,UAAU;AAGd,SAAS,KAAK,GAAG,GAAG;AAClB,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,OAAO,GAAG,EAAE,KAAK,CAAC;AAGtB,SAAS,UAAU,GAAG,GAAG;AACvB,MAAI,KAAK,gBAAgB,GAAG,KAAK,UAAU;AAC3C,MAAI,KAAK,gBAAgB,GAAG,KAAK,UAAU;AAC3C,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,KAAK,GAAG,GAAG;AAClB,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,MAAI,GAAG,UAAU,WAAW,GAAG,UAAU,SAAS;AAChD,WAAO,SAAS,IAAI,EAAE;AAAA,EACxB;AACA,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,QAAM,QAAQ,CAAC;AACf,SAAO,OAAO,UAAU,SAAS,QAAQ,KAAK;AAChD;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,KAAK,GAAG,GAAG;AAClB,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACxC,MAAI,GAAG,UAAU,aAAa;AAC5B,UAAM,SAAS,EAAE,GAAG,GAAG;AACvB,WAAO,OAAO,UAAU,YAAY,MAAM;AAAA,EAC5C,OAAO;AACL,UAAM,SAAS,EAAE,GAAG,GAAG;AACvB,WAAO,OAAO,UAAU,KAAK,MAAM;AAAA,EACrC;AACF;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,SAAS;AACtB,SAAO,MAAM,QAAQ,OAAO,GAAG,MAAM,4DAA4D;AACjG,SAAO,QAAQ,UAAU,GAAG,MAAM,uDAAuD,QAAQ,QAAQ;AACzG,QAAM,WAAW,QAAQ,IAAI,CAAC,IAAI,OAAO,gBAAgB,IAAI,UAAU,MAAM,MAAM,CAAC;AACpF,QAAM,cAAc,SAAS;AAC7B,WAAS,QAAQ,CAAC,OAAO;AACvB,QAAI,GAAG,UAAU,YAAY,OAAO;AAClC,YAAM,IAAI,MAAM,0DAA0D;AAAA,IAC5E;AAAA,EACF,CAAC;AACD,WAAS,QAAQ,CAAC,OAAO;AACvB,QAAI,CAAC,YAAY,GAAG,OAAO,YAAY,KAAK,GAAG;AAC7C,YAAM,IAAI,MAAM,0DAA0D;AAAA,IAC5E;AAAA,EACF,CAAC;AACD,QAAM,SAAS;AACf,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,KAAK,GAAG,OAAO,MAAM,WAAW,OAAO;AAC9C,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO,MAAM;AAChD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,SAAS;AAC/B,SAAO,OAAO,UAAU,KAAK,QAAQ,KAAK;AAC5C;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,KAAK,GAAG,OAAO,MAAM,WAAW,OAAO;AAC9C,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO,MAAM;AAChD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,SAAS;AAC/B,SAAO,OAAO,UAAU,KAAK,QAAQ,KAAK;AAC5C;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,QAAQ,GAAG,OAAO,GAAG;AAC5B,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AAC3C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,KAAK;AACrB,SAAO,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAC/C;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,QAAQ,GAAG,OAAO,GAAG;AAC5B,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AAC3C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,KAAK;AACrB,SAAO,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAC/C;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,OAAO,GAAG,GAAG;AACpB,MAAI,KAAK,gBAAgB,GAAG,KAAK,OAAO;AACxC,MAAI,KAAK,gBAAgB,GAAG,KAAK,OAAO;AACxC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,sBAAsB,YAAY,aAAae,UAAS,MAAM,aAAa,QAAQ,WAAW;AACrG,QAAM,gBAAgB,WAAW;AACjC,QAAM,eAAe,CAAC,GAAG,aAAa,aAAa;AACnD,QAAM,cAAc,wBAAwB,UAAU;AACtD,SAAO,kBAAkB,YAAY,cAAcA,UAAS,WAAW,MAAM,MAAM,MAAM,WAAW;AACtG;AACA,SAAS,kBAAkB,SAAS,YAAYA,UAAS,WAAW,MAAM,cAAc,aAAa,gBAAgB;AACnH,QAAM,CAAC,cAAc,WAAW,IAAI,gBAAgB,UAAU;AAC9D,MAAI;AACJ,MAAI,eAAe,gBAAgB;AACjC,kBAAc,CAAC,cAAc,aAAa,QAAQ,IAAI,QAAQ,EAAE;AAAA,EAClE,WAAW,eAAe,iBAAiB;AACzC,kBAAc,CAAC,cAAc,aAAa,QAAQ,IAAI,QAAQ,EAAE;AAAA,EAClE,OAAO;AACL,UAAM,IAAI,MAAM,sBAAsB,YAAY;AAAA,EACpD;AACA,SAAO,kBAAkB,SAAS,aAAaA,UAAS,WAAW,MAAM,cAAc,OAAO,UAAU;AAC1G;AACA,SAAS,kBAAkB,SAAS,YAAYA,UAAS,WAAW,MAAM,cAAc,aAAa,SAAS;AAC5G,QAAM,CAAC,aAAa,cAAc,WAAW,IAAI,iBAAiB,UAAU;AAC5E,MAAI;AACJ,MAAI;AACJ,MAAI,eAAe,SAAS;AAC1B,kBAAc;AACd,kBAAc,CAAC,aAAa,cAAc,aAAa,QAAQ,IAAI,QAAQ,EAAE;AAAA,EAC/E,WAAW,eAAe,SAAS;AACjC,kBAAc;AACd,kBAAc,CAAC,aAAa,cAAc,aAAa,QAAQ,IAAI,QAAQ,EAAE;AAAA,EAC/E,OAAO;AACL,UAAM,IAAI,MAAM,sBAAsB,YAAY;AAAA,EACpD;AACA,SAAO,kBAAkB,SAAS,aAAaA,UAAS,WAAW,MAAM,OAAO,aAAa,YAAY;AAC3G;AACA,SAAS,kBAAkB,SAAS,aAAaA,UAAS,WAAW,MAAM,cAAc,YAAY,OAAO,aAAa,gBAAgB;AACvI,MAAI,CAAC,WAAW,UAAU,SAAS,UAAU,IAAI,CAAC,IAAI,IAAI,IAAI,EAAE;AAChE,MAAI,eAAe,gBAAgB;AACjC,KAAC,WAAW,UAAU,SAAS,UAAU,IAAI;AAAA,EAC/C,WAAW,eAAe,iBAAiB;AACzC,KAAC,WAAW,YAAY,UAAU,OAAO,IAAI;AAAA,EAC/C,OAAO;AACL,UAAM,IAAI,MAAM,sBAAsB,YAAY;AAAA,EACpD;AACA,QAAM,CAAC,cAAc,aAAa,EAAE,cAAc,IAAI;AACtD,QAAM,CAAC,cAAc,WAAW,IAAI,gBAAgBA,QAAO;AAC3D,QAAM,CAAC,gBAAgB,aAAa,IAAI,gBAAgB,SAAS;AACjE,QAAM,wBAAwB,uBAAuB,cAAc,cAAc;AACjF,QAAM,uBAAuB,uBAAuB,aAAa,aAAa;AAC9E,QAAM,EAAE,SAAS,WAAW,SAAS,IAAI,iBAAiB,MAAM,UAAU,SAAS,cAAc,aAAa,uBAAuB,sBAAsB,cAAc,UAAU;AACnL,QAAM,cAAc,YAAY,iBAAiB,aAAa;AAC9D,MAAI;AACJ,MAAI,eAAe,iBAAiB;AAClC,eAAW,CAAC,WAAW,aAAa,WAAW,QAAQ;AAAA,EACzD,WAAW,eAAe,gBAAgB;AACxC,eAAW,CAAC,WAAW,WAAW,UAAU,WAAW;AAAA,EACzD;AACA,SAAO;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AACA,SAAS,kBAAkB,SAAS,aAAaA,UAAS,WAAW,MAAM,YAAY,OAAO,aAAa,gBAAgB,cAAc;AACvI,MAAI,CAAC,WAAW,SAAS,UAAU,SAAS,UAAU,IAAI,CAAC,IAAI,IAAI,IAAI,IAAI,EAAE;AAC7E,MAAI,eAAe,gBAAgB;AACjC,KAAC,WAAW,SAAS,UAAU,SAAS,UAAU,IAAI;AAAA,EACxD,WAAW,eAAe,iBAAiB;AACzC,KAAC,WAAW,YAAY,SAAS,UAAU,OAAO,IAAI;AAAA,EACxD,OAAO;AACL,UAAM,IAAI,MAAM,sBAAsB,YAAY;AAAA,EACpD;AACA,QAAM,CAAC,aAAa,cAAc,aAAa,EAAE,cAAc,IAAI;AACnE,QAAM,CAAC,aAAa,cAAc,WAAW,IAAI,iBAAiBA,QAAO;AACzE,QAAM,CAAC,eAAe,gBAAgB,aAAa,IAAI,iBAAiB,SAAS;AACjF,QAAM,uBAAuB,uBAAuB,aAAa,aAAa;AAC9E,QAAM,wBAAwB,uBAAuB,cAAc,cAAc;AACjF,QAAM,uBAAuB,uBAAuB,aAAa,aAAa;AAC9E,QAAM,EAAE,SAAS,UAAU,WAAW,SAAS,IAAI,mBAAmB,MAAM,SAAS,UAAU,SAAS,aAAa,cAAc,aAAa,sBAAsB,uBAAuB,sBAAsB,YAAY;AAC/N,QAAM,cAAc,YAAY,iBAAiB,aAAa;AAC9D,MAAI;AACJ,MAAI,eAAe,iBAAiB;AAClC,eAAW,CAAC,WAAW,aAAa,UAAU,WAAW,QAAQ;AAAA,EACnE,WAAW,eAAe,gBAAgB;AACxC,eAAW,CAAC,WAAW,UAAU,WAAW,UAAU,WAAW;AAAA,EACnE;AACA,SAAO;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AACA,SAAS,qBAAqB,SAAS,WAAW,QAAQ,SAAS,cAAc;AAC/E,MAAI,WAAW,MAAM;AACnB,cAAU,kBAAkB,SAAS,WAAW,MAAM;AAAA,EACxD;AACA,QAAM,YAAY,QAAQ;AAC1B,QAAM,YAAY,QAAQ;AAC1B,QAAM,aAAa,OAAO,YAAY,YAAY,IAAI,WAAW,SAAS,GAAG,YAAY;AACzF,QAAM,aAAa,OAAO,YAAY,YAAY,IAAI,WAAW,SAAS,GAAG,YAAY;AACzF,SAAO,CAAC,YAAY,UAAU;AAChC;AACA,SAAS,qBAAqB,SAAS,WAAW,aAAa,QAAQ,SAAS,cAAc;AAC5F,MAAI,WAAW,MAAM;AACnB,cAAU,kBAAkB,SAAS,WAAW,MAAM;AAAA,EACxD;AACA,QAAM,aAAa,QAAQ;AAC3B,QAAM,YAAY,QAAQ;AAC1B,QAAM,YAAY,QAAQ;AAC1B,QAAM,eAAe,OAAO,aAAa,YAAY,IAAI,WAAW,SAAS,GAAG,YAAY;AAC5F,QAAM,aAAa,OAAO,YAAY,YAAY,IAAI,WAAW,SAAS,GAAG,YAAY;AACzF,QAAM,aAAa,OAAO,YAAY,YAAY,IAAI,WAAW,SAAS,GAAG,YAAY;AACzF,SAAO,CAAC,cAAc,YAAY,YAAY,WAAW;AAC3D;AACA,SAAS,kBAAkB,YAAY,WAAW,QAAQ,WAAW,GAAG;AACtE,QAAM,qBAAqB,uBAAuB,WAAW,QAAQ;AACrE,SAAO,KAAK,OAAO,WAAW,MAAM,SAAS,KAAK,SAAS,sBAAsB,CAAC;AACpF;AACA,SAAS,gBAAgB,OAAO;AAC9B,MAAI,OAAO,UAAU,UAAU;AAC7B,WAAO,CAAC,OAAO,OAAO,KAAK;AAAA,EAC7B;AACA,MAAI,MAAM,WAAW,GAAG;AACtB,WAAO,CAAC,MAAM,IAAI,MAAM,IAAI,CAAC;AAAA,EAC/B;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,OAAO;AAC/B,SAAO,OAAO,UAAU,WAAW,CAAC,OAAO,OAAO,KAAK,IAAI;AAC7D;AACA,SAAS,uBAAuB,YAAY,UAAU;AACpD,MAAI,YAAY,GAAG;AACjB,WAAO;AAAA,EACT;AACA,SAAO,cAAc,aAAa,MAAM,WAAW;AACrD;AACA,SAAS,iBAAiB,MAAM,UAAU,SAAS,cAAc,aAAa,cAAc,aAAa,cAAc,YAAY;AACjI,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI,OAAO,SAAS,UAAU;AAC5B,UAAM,UAAU,SAAS,IAAI,UAAU;AACvC,cAAU,EAAE,KAAK,MAAM,QAAQ,MAAM,MAAM,MAAM,OAAO,MAAM,MAAM,QAAQ;AAC5E,UAAM,WAAW,qBAAqB,CAAC,UAAU,OAAO,GAAG,cAAc,cAAc,MAAM,YAAY;AACzG,gBAAY,SAAS;AACrB,eAAW,SAAS;AAAA,EACtB,WAAW,SAAS,QAAQ;AAC1B,gBAAY,KAAK,KAAK,WAAW,YAAY;AAC7C,eAAW,KAAK,KAAK,UAAU,WAAW;AAC1C,UAAM,iBAAiB,KAAK,IAAI,IAAI,YAAY,KAAK,eAAe,eAAe,QAAQ;AAC3F,UAAM,gBAAgB,KAAK,IAAI,IAAI,WAAW,KAAK,cAAc,cAAc,OAAO;AACtF,UAAM,MAAM,KAAK,MAAM,iBAAiB,CAAC;AACzC,UAAM,SAAS,iBAAiB;AAChC,UAAM,OAAO,KAAK,MAAM,gBAAgB,CAAC;AACzC,UAAM,QAAQ,gBAAgB;AAC9B,cAAU,EAAE,KAAK,QAAQ,MAAM,OAAO,MAAM,OAAO;AAAA,EACrD,WAAW,SAAS,SAAS;AAC3B,cAAU,EAAE,KAAK,GAAG,QAAQ,GAAG,MAAM,GAAG,OAAO,GAAG,MAAM,QAAQ;AAChE,gBAAY,KAAK,MAAM,WAAW,eAAe,KAAK,YAAY;AAClE,eAAW,KAAK,MAAM,UAAU,cAAc,KAAK,WAAW;AAAA,EAChE,WAAW,OAAO,SAAS,UAAU;AACnC,UAAM,MAAM,eAAe,iBAAiB,KAAK,GAAG,KAAK,KAAK,GAAG;AACjE,UAAM,SAAS,eAAe,iBAAiB,KAAK,GAAG,KAAK,KAAK,GAAG;AACpE,UAAM,OAAO,eAAe,iBAAiB,KAAK,GAAG,KAAK,KAAK,GAAG;AAClE,UAAM,QAAQ,eAAe,iBAAiB,KAAK,GAAG,KAAK,KAAK,GAAG;AACnE,UAAM,UAAU,QAAQ,KAAK,WAAW,KAAK,SAAS,KAAK,UAAU,IAAI,UAAU;AACnF,cAAU,EAAE,KAAK,QAAQ,MAAM,OAAO,MAAM,QAAQ;AACpD,gBAAY,OAAO,WAAW,eAAe,MAAM,UAAU,eAAe,GAAG,YAAY;AAC3F,eAAW,OAAO,UAAU,cAAc,OAAO,SAAS,cAAc,GAAG,YAAY;AAAA,EACzF,OAAO;AACL,UAAM,MAAM,8BAA8B,MAAM;AAAA,EAClD;AACA,SAAO,EAAE,SAAS,WAAW,SAAS;AACxC;AACA,SAAS,mBAAmB,MAAM,SAAS,UAAU,SAAS,aAAa,cAAc,aAAa,aAAa,cAAc,aAAa,cAAc;AAC1J,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI,OAAO,SAAS,UAAU;AAC5B,UAAM,UAAU,SAAS,IAAI,UAAU;AACvC,cAAU;AAAA,MACR,KAAK;AAAA,MACL,QAAQ;AAAA,MACR,MAAM;AAAA,MACN,OAAO;AAAA,MACP,OAAO;AAAA,MACP,MAAM;AAAA,MACN,MAAM;AAAA,IACR;AACA,UAAM,WAAW,qBAAqB,CAAC,SAAS,UAAU,SAAS,CAAC,GAAG,aAAa,GAAG,aAAa,MAAM,YAAY;AACtH,eAAW,SAAS;AACpB,gBAAY,SAAS;AACrB,eAAW,SAAS;AAAA,EACtB,WAAW,SAAS,QAAQ;AAC1B,eAAW,KAAK,KAAK,UAAU,WAAW;AAC1C,gBAAY,KAAK,KAAK,WAAW,YAAY;AAC7C,eAAW,KAAK,KAAK,UAAU,WAAW;AAC1C,UAAM,iBAAiB,WAAW,KAAK,cAAc,cAAc;AACnE,UAAM,kBAAkB,YAAY,KAAK,eAAe,eAAe;AACvE,UAAM,iBAAiB,WAAW,KAAK,cAAc,cAAc;AACnE,UAAM,QAAQ,KAAK,MAAM,gBAAgB,CAAC;AAC1C,UAAM,OAAO,gBAAgB;AAC7B,UAAM,MAAM,KAAK,MAAM,iBAAiB,CAAC;AACzC,UAAM,SAAS,iBAAiB;AAChC,UAAM,OAAO,KAAK,MAAM,gBAAgB,CAAC;AACzC,UAAM,QAAQ,gBAAgB;AAC9B,cAAU,EAAE,KAAK,QAAQ,MAAM,OAAO,OAAO,MAAM,MAAM,OAAO;AAAA,EAClE,WAAW,SAAS,SAAS;AAC3B,cAAU;AAAA,MACR,KAAK;AAAA,MACL,QAAQ;AAAA,MACR,MAAM;AAAA,MACN,OAAO;AAAA,MACP,OAAO;AAAA,MACP,MAAM;AAAA,MACN,MAAM;AAAA,IACR;AACA,eAAW,KAAK,MAAM,UAAU,cAAc,KAAK,WAAW;AAC9D,gBAAY,KAAK,MAAM,WAAW,eAAe,KAAK,YAAY;AAClE,eAAW,KAAK,MAAM,UAAU,cAAc,KAAK,WAAW;AAAA,EAChE,OAAO;AACL,UAAM,MAAM,8BAA8B,MAAM;AAAA,EAClD;AACA,SAAO,EAAE,SAAS,UAAU,WAAW,SAAS;AAClD;AACA,SAAS,MAAM,OAAO,cAAc;AAClC,MAAI,CAAC,cAAc;AACjB,WAAO,KAAK,MAAM,KAAK;AAAA,EACzB;AACA,UAAQ;AAAA,SACD;AACH,aAAO,KAAK,MAAM,KAAK;AAAA,SACpB;AACH,aAAO,KAAK,KAAK,KAAK;AAAA,SACnB;AACH,aAAO,KAAK,MAAM,KAAK;AAAA;AAEvB,YAAM,IAAI,MAAM,wBAAwB,cAAc;AAAA;AAE5D;AACA,SAAS,kBAAkB,OAAO;AAChC,QAAM,CAAC,MAAM,MAAM,IAAI,IAAI,gBAAgB,KAAK;AAChD,SAAO,SAAS,KAAK,SAAS,KAAK,SAAS;AAC9C;AACA,SAAS,+BAA+BA,UAAS,WAAW;AAC1D,SAAO,kBAAkBA,QAAO,KAAK,kBAAkB,SAAS;AAClE;AACA,SAAS,wBAAwB,YAAY;AAC3C,MAAI,eAAe,QAAQ;AACzB,WAAO;AAAA,EACT,WAAW,eAAe,QAAQ;AAChC,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,sBAAsB,YAAY;AAAA,EACpD;AACF;AACA,SAAS,0BAA0B,QAAQ,MAAM,iBAAiB;AAChE,MAAI,mBAAmB,MAAM;AAC3B,QAAI,OAAO,SAAS,UAAU;AAC5B,YAAM,MAAM,YAAY,6DAA6D,+BAA+B,OAAO;AAAA,IAC7H,WAAW,OAAO,SAAS,UAAU;AACnC,aAAO,MAAM,IAAI,GAAG,MAAM,YAAY,6DAA6D,+BAA+B,OAAO;AAAA,IAC3I,WAAW,OAAO,SAAS,UAAU;AACnC,WAAK,QAAQ,CAAC,OAAO;AACnB,WAAG,QAAQ,CAAC,MAAM;AAChB,iBAAO,MAAM,CAAC,GAAG,MAAM,YAAY,6DAA6D,+BAA+B,IAAI;AAAA,QACrI,CAAC;AAAA,MACH,CAAC;AAAA,IACH,OAAO;AACL,YAAM,MAAM,YAAY,sCAAsC,MAAM;AAAA,IACtE;AAAA,EACF;AACF;AAGA,SAAS,SAAS,GAAG,OAAO;AAC1B,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW,mBAAmB;AACjE,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM;AACtB,SAAO,OAAO,UAAU,SAAS,QAAQ,KAAK;AAChD;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,SAAS,GAAG,YAAYA,UAAS,MAAM,iBAAiB;AAC/D,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW,SAAS;AACvD,QAAM,YAAY;AAClB,SAAO,+BAA+BA,UAAS,SAAS,GAAG,MAAM,wEAAwEA,2BAA0B,YAAY;AAC/K,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,mDAAmD,IAAI,OAAO;AAC3F,4BAA0B,WAAW,MAAM,eAAe;AAC1D,QAAM,SAAS,EAAE,GAAG,IAAI;AACxB,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB;AAChE,MAAI,MAAM,OAAO,UAAU,SAAS,QAAQ,KAAK;AACjD,QAAM,KAAK,KAAK,GAAG,KAAK;AACxB,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,WAAW,GAAG,YAAYA,UAAS,MAAM,iBAAiB,aAAa,SAAS;AACvF,QAAM,KAAK,gBAAgB,GAAG,KAAK,aAAa,SAAS;AACzD,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC3E;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,qDAAqD,IAAI,OAAO;AAC7F,SAAO,eAAe,SAAS,MAAM,gFAAgF,YAAY;AACjI,4BAA0B,aAAa,MAAM,eAAe;AAC5D,QAAM,SAAS,EAAE,GAAG,IAAI;AACxB,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,iBAAiB,WAAW;AAC5E,MAAI,MAAM,OAAO,UAAU,WAAW,QAAQ,KAAK;AACnD,QAAM,KAAK,KAAK,IAAI,KAAK;AACzB,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAC9E;AACA,SAAO;AACT;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,QAAQ,SAAS,OAAO,GAAG;AAClC,SAAO,QAAQ,UAAU,GAAG,MAAM,oCAAoC;AACtE,QAAM,WAAW,qBAAqB,SAAS,WAAW,UAAU,mBAAmB;AACvF,MAAI,SAAS,GAAG,UAAU,aAAa;AACrC,aAAS,QAAQ,CAAC,YAAY;AAC5B,UAAI,QAAQ,UAAU,aAAa;AACjC,cAAM,IAAI,MAAM;AAAA,uBACD,QAAQ,SAAS;AAAA,MAClC;AAAA,IACF,CAAC;AAAA,EACH;AACA,MAAI,SAAS,WAAW,GAAG;AACzB,WAAO,MAAM,SAAS,EAAE;AAAA,EAC1B;AACA,QAAM,SAAS;AACf,QAAM,OAAO,EAAE,KAAK;AACpB,SAAO,OAAO,UAAU,QAAQ,QAAQ,IAAI;AAC9C;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,SAAS,GAAG;AACnB,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW,SAAS;AACvD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,SAAS,MAAM;AACzC;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,OAAO,GAAG,OAAOZ,OAAM;AAC9B,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS,mBAAmB;AAC/D,MAAI,GAAG,SAAS,GAAG;AACjB,UAAM,IAAI,MAAM,gCAAgC;AAAA,EAClD;AACA,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,OAAO,MAAAA,MAAK;AAC5B,SAAO,OAAO,UAAU,OAAO,QAAQ,KAAK;AAC9C;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ,SAAS;AACpD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,QAAQ,GAAG,EAAE,MAAM,CAAC;AAGxB,SAAS,eAAe,YAAY,YAAY,UAAU,MAAM,GAAG,GAAG;AACpE,QAAM,cAAc,gBAAgB,YAAY,cAAc,eAAe;AAC7E,QAAM,cAAc,gBAAgB,YAAY,cAAc,eAAe;AAC7E,QAAM,YAAY,gBAAgB,UAAU,YAAY,eAAe;AACvE,QAAM,QAAQ,gBAAgB,MAAM,QAAQ,eAAe;AAC3D,QAAM,KAAK,gBAAgB,GAAG,KAAK,eAAe;AAClD,QAAM,KAAK,gBAAgB,GAAG,KAAK,eAAe;AAClD,QAAM,WAAW,OAAO,CAAC,OAAO,EAAE,GAAG,CAAC;AACtC,QAAM,WAAW,OAAO,UAAU,WAAW;AAC7C,QAAM,MAAM,KAAK,UAAU,SAAS;AACpC,QAAM,YAAY,IAAI,MAAM;AAC5B,QAAM,YAAY,IAAI,MAAM,KAAK;AACjC,QAAM,YAAY,CAAC,WAAW,SAAS;AACvC,QAAM,KAAK,MAAM,KAAK,CAAC,GAAG,CAAC,GAAG,SAAS;AACvC,QAAM,IAAI,MAAM,KAAK,CAAC,GAAG,SAAS,GAAG,SAAS;AAC9C,QAAM,IAAI,MAAM,KAAK,CAAC,GAAG,YAAY,CAAC,GAAG,SAAS;AAClD,QAAM,IAAI,MAAM,KAAK,CAAC,GAAG,YAAY,CAAC,GAAG,SAAS;AAClD,QAAM,OAAO,KAAK,IAAI,QAAQ,EAAE,GAAG,MAAM,CAAC,CAAC,GAAG,IAAI,IAAI,QAAQ,KAAK,aAAa,CAAC,CAAC,CAAC,CAAC;AACpF,QAAM,OAAO,IAAI,MAAM,IAAI,GAAG,QAAQ,CAAC,CAAC;AACxC,SAAO,CAAC,MAAM,IAAI;AACpB;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,gBAAgB,GAAG,YAAY,OAAO;AAC7C,QAAM,KAAK,gBAAgB,GAAG,KAAK,gBAAgB;AACnD,QAAM,QAAQ,WAAW,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAC/C,SAAO,GAAG,QAAQ,IAAI,WAAW,QAAQ,MAAM,iBAAiB,GAAG,+CAA+C,WAAW,QAAQ;AACrI,SAAO,MAAM,WAAW,WAAW,QAAQ,MAAM,mBAAmB,MAAM,oDAAoD,WAAW,QAAQ;AACjJ,SAAO,GAAG,MAAM,KAAK,UAAU,GAAG,MAAM,yBAAyB,GAAG,MAAM,wEAAwE,WAAW,KAAK,KAAK,SAAS,OAAO;AACvL,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,YAAY,MAAM;AAClC,SAAO,OAAO,UAAU,gBAAgB,QAAQ,KAAK;AACvD;AACA,IAAI,iBAAiB,GAAG,EAAE,gBAAgB,CAAC;AAG3C,SAAS,MAAM,GAAG;AAChB,MAAI;AACJ,MAAI,EAAE,SAAS,KAAK,EAAE,SAAS,GAAG;AAChC,UAAM,QAAQ,GAAG,CAAC,GAAG,GAAG,GAAG,EAAE,IAAI,CAAC;AAAA,EACpC,WAAW,EAAE,SAAS,GAAG;AACvB,UAAM,QAAQ,GAAG,CAAC,GAAG,GAAG,EAAE,MAAM,IAAI,EAAE,MAAM,EAAE,CAAC;AAAA,EACjD,WAAW,EAAE,SAAS,GAAG;AACvB,UAAM,QAAQ,GAAG,CAAC,GAAG,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,EAAE,CAAC;AAAA,EAC1D,OAAO;AACL,UAAM;AAAA,EACR;AACA,SAAO;AACT;AAGA,SAAS,WAAW,GAAG,OAAO,UAAU,QAAQqB,SAAQ,iBAAiB;AACvE,MAAI,mBAAmB,MAAM;AAC3B,sBAAkB;AAAA,EACpB;AACA,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,QAAQ,gBAAgB,OAAO,QAAQ,WAAW;AACxD,QAAM,YAAY,gBAAgB,UAAU,YAAY,WAAW;AACnE,MAAI;AACJ,MAAIA,WAAU,MAAM;AAClB,aAAS,gBAAgBA,SAAQ,SAAS,WAAW;AAAA,EACvD;AACA,MAAI;AACJ,MAAI,UAAU,MAAM;AAClB,cAAU,gBAAgB,QAAQ,UAAU,WAAW;AAAA,EACzD;AACA,SAAO,MAAM,SAAS,UAAU,MAAM,MAAM,8EAA8E;AAC1H,SAAO,WAAW,QAAQ,MAAM,SAAS,QAAQ,MAAM,MAAM,4EAA4E;AACzI,SAAO,UAAU,QAAQ,MAAM,SAAS,OAAO,MAAM,MAAM,2EAA2E;AACtI,QAAM,MAAM,MAAM,EAAE;AACpB,QAAM,SAAS;AAAA,IACb,GAAG;AAAA,IACH,OAAO;AAAA,IACP,QAAQ;AAAA,IACR,MAAM;AAAA,IACN,UAAU;AAAA,EACZ;AACA,QAAM,QAAQ,EAAE,gBAAgB;AAChC,QAAM,MAAM,OAAO,UAAU,gBAAgB,QAAQ,KAAK;AAC1D,SAAO,QAAQ,KAAK,GAAG,KAAK;AAC9B;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,aAAa,GAAG,OAAO,UAAU,QAAQA,SAAQ,iBAAiB;AACzE,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,QAAQ,gBAAgB,OAAO,QAAQ,WAAW;AACxD,QAAM,YAAY,gBAAgB,UAAU,YAAY,WAAW;AACnE,MAAI;AACJ,MAAIA,WAAU,MAAM;AAClB,aAAS,gBAAgBA,SAAQ,SAAS,WAAW;AAAA,EACvD;AACA,MAAI;AACJ,MAAI,UAAU,MAAM;AAClB,cAAU,gBAAgB,QAAQ,UAAU,WAAW;AAAA,EACzD;AACA,SAAO,GAAG,SAAS,GAAG,MAAM,uDAAuD,GAAG,OAAO;AAC7F,SAAO,MAAM,SAAS,KAAK,MAAM,SAAS,GAAG,MAAM,oEAAoE,MAAM,OAAO;AACpI,SAAO,UAAU,SAAS,KAAK,UAAU,SAAS,GAAG,MAAM,wEAAwE,UAAU,OAAO;AACpJ,MAAI,UAAU,MAAM;AAClB,WAAO,OAAO,SAAS,KAAK,OAAO,SAAS,GAAG,MAAM,qEAAqE,OAAO,OAAO;AAAA,EAC1I;AACA,MAAI,WAAW,MAAM;AACnB,WAAO,QAAQ,SAAS,KAAK,QAAQ,SAAS,GAAG,MAAM,sEAAsE,QAAQ,OAAO;AAAA,EAC9I;AACA,SAAO,UAAU,IAAI,OAAO,WAAW,SAAS,QAAQ,eAAe;AACzE;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,aAAa,GAAG,OAAO,UAAU,QAAQA,SAAQ,iBAAiB;AACzE,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,QAAQ,gBAAgB,OAAO,QAAQ,WAAW;AACxD,QAAM,YAAY,gBAAgB,UAAU,YAAY,WAAW;AACnE,MAAI;AACJ,MAAIA,WAAU,MAAM;AAClB,aAAS,gBAAgBA,SAAQ,SAAS,WAAW;AAAA,EACvD;AACA,MAAI;AACJ,MAAI,UAAU,MAAM;AAClB,cAAU,gBAAgB,QAAQ,UAAU,WAAW;AAAA,EACzD;AACA,SAAO,GAAG,SAAS,GAAG,MAAM,uDAAuD,GAAG,OAAO;AAC7F,SAAO,MAAM,SAAS,KAAK,MAAM,SAAS,GAAG,MAAM,oEAAoE,MAAM,OAAO;AACpI,SAAO,UAAU,SAAS,KAAK,UAAU,SAAS,GAAG,MAAM,wEAAwE,UAAU,OAAO;AACpJ,MAAI,UAAU,MAAM;AAClB,WAAO,OAAO,SAAS,KAAK,OAAO,SAAS,GAAG,MAAM,qEAAqE,OAAO,OAAO;AAAA,EAC1I;AACA,MAAI,WAAW,MAAM;AACnB,WAAO,QAAQ,SAAS,KAAK,QAAQ,SAAS,GAAG,MAAM,sEAAsE,QAAQ,OAAO;AAAA,EAC9I;AACA,SAAO,UAAU,IAAI,OAAO,WAAW,SAAS,QAAQ,eAAe;AACzE;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,aAAa,GAAG,OAAO,UAAU,QAAQA,SAAQ,iBAAiB;AACzE,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,QAAQ,gBAAgB,OAAO,QAAQ,WAAW;AACxD,QAAM,YAAY,gBAAgB,UAAU,YAAY,WAAW;AACnE,MAAI;AACJ,MAAIA,WAAU,MAAM;AAClB,aAAS,gBAAgBA,SAAQ,SAAS,WAAW;AAAA,EACvD;AACA,MAAI;AACJ,MAAI,UAAU,MAAM;AAClB,cAAU,gBAAgB,QAAQ,UAAU,WAAW;AAAA,EACzD;AACA,SAAO,GAAG,SAAS,GAAG,MAAM,uDAAuD,GAAG,OAAO;AAC7F,SAAO,MAAM,SAAS,KAAK,MAAM,SAAS,GAAG,MAAM,oEAAoE,MAAM,OAAO;AACpI,SAAO,UAAU,SAAS,KAAK,UAAU,SAAS,GAAG,MAAM,wEAAwE,UAAU,OAAO;AACpJ,MAAI,UAAU,MAAM;AAClB,WAAO,OAAO,SAAS,KAAK,OAAO,SAAS,GAAG,MAAM,qEAAqE,OAAO,OAAO;AAAA,EAC1I;AACA,MAAI,WAAW,MAAM;AACnB,WAAO,QAAQ,SAAS,KAAK,QAAQ,SAAS,GAAG,MAAM,sEAAsE,QAAQ,OAAO;AAAA,EAC9I;AACA,SAAO,UAAU,IAAI,OAAO,WAAW,SAAS,QAAQ,eAAe;AACzE;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,UAAU,GAAG,SAASrB,OAAM;AACnC,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU;AAC7C,QAAM,WAAW,gBAAgB,SAAS,WAAW,UAAU;AAC/D,SAAO,GAAG,UAAU,SAAS,MAAM,yDAAyD,GAAG,OAAO;AACtG,SAAOA,SAAQ,GAAG,MAAM,sCAAsCA,QAAO;AACrE,SAAO,SAAS,SAAS,GAAG,QAAQ,SAAS,SAAS,GAAG,MAAM,gGAAgG,GAAG,yBAAyB,SAAS,QAAQ;AAC5M,QAAM,SAAS,EAAE,GAAG,IAAI,SAAS,SAAS;AAC1C,QAAM,QAAQ,EAAE,MAAAA,MAAK;AACrB,SAAO,OAAO,UAAU,UAAU,QAAQ,KAAK;AACjD;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,eAAe,IAAI,IAAI;AAC9B,QAAM,cAAc,gBAAgB,IAAI,MAAM,iBAAiB,OAAO;AACtE,QAAM,cAAc,gBAAgB,IAAI,MAAM,iBAAiB,OAAO;AACtE,MAAI,YAAY,SAAS,GAAG;AAC1B,UAAM,IAAI,MAAM,oEAAoE,YAAY,MAAM;AAAA,EACxG;AACA,MAAI,YAAY,SAAS,GAAG;AAC1B,UAAM,IAAI,MAAM,qEAAqE,YAAY,MAAM;AAAA,EACzG;AACA,QAAM,SAAS,EAAE,IAAI,aAAa,IAAI,YAAY;AAClD,SAAO,OAAO,UAAU,eAAe,MAAM;AAC/C;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,aAAa,GAAG,OAAO;AAC9B,MAAI,SAAS,gBAAgB,GAAG,eAAe,GAAG;AAClD,QAAM,SAAS,OAAO;AACtB,MAAI,MAAM,KAAK,CAAC,MAAM,EAAE,IAAI,MAAM,IAAI,MAAM,CAAC,GAAG;AAC9C,UAAM,IAAI,MAAM,2CAA2C,SAAS;AAAA,EACtE;AACA,MAAI,MAAM,SAAS,OAAO,MAAM;AAC9B,UAAM,IAAI,MAAM,+BAA+B,MAAM,uBAAuB,OAAO,OAAO;AAAA,EAC5F;AACA,MAAI,MAAM,SAAS,OAAO,MAAM;AAC9B,UAAM,WAAW,OAAO,MAAM,MAAM;AACpC,WAAO,SAAS,SAAS,MAAM,QAAQ;AACrC,eAAS,QAAQ,CAAC;AAAA,IACpB;AACA,aAAS,QAAQ,QAAQ,QAAQ;AAAA,EACnC;AACA,QAAM,aAAa,OAAO;AAC1B,QAAM,OAAO,MAAM,KAAK,KAAK;AAC7B,WAAS,KAAK,MAAM,SAAS,GAAG,MAAM,GAAG,MAAM;AAC7C,QAAI,WAAW,QAAQ,MAAM,KAAK;AAChC,WAAK,MAAM;AAAA,IACb,WAAW,OAAO,MAAM,QAAQ,GAAG;AACjC,YAAM,IAAI,MAAM,mBAAmB,mCAAmC,SAAS;AAAA,IACjF;AAAA,EACF;AACA,QAAM,OAAO,KAAK,IAAI,CAAC,IAAI,OAAO,KAAK,IAAI,KAAK,EAAE,EAAE,OAAO,CAAC,OAAO,MAAM,CAAC;AAC1E,MAAI,KAAK,WAAW,GAAG;AACrB,WAAO,MAAM,MAAM;AAAA,EACrB;AACA,QAAM,SAAS,EAAE,GAAG,OAAO;AAC3B,QAAM,QAAQ,EAAE,KAAK;AACrB,SAAO,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC7C;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ,SAAS;AACpD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,aAAa,GAAG,cAAc,cAAc;AACnD,QAAM,KAAK,gBAAgB,GAAG,KAAK,aAAa;AAChD,SAAO,gBAAgB,cAAc,MAAM,uBAAuB,oDAAoD,gBAAgB;AACtI,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,cAAc,aAAa;AAC3C,SAAO,OAAO,UAAU,aAAa,QAAQ,KAAK;AACpD;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,UAAU,SAAS;AAC1B,SAAO,OAAO,SAAS,CAAC;AAC1B;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,UAAU,SAAS,MAAM;AAChC,SAAO,OAAO,SAAS,IAAI;AAC7B;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,UAAU,SAAS,MAAM;AAChC,SAAO,OAAO,SAAS,IAAI;AAC7B;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,UAAU,SAAS,MAAM;AAChC,SAAO,OAAO,SAAS,IAAI;AAC7B;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,QAAQ,GAAG,QAAQY,UAAS,MAAM,aAAa,QAAQ,YAAY,CAAC,GAAG,CAAC,GAAG,iBAAiB;AACnG,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU,SAAS;AACtD,QAAM,UAAU,gBAAgB,QAAQ,UAAU,UAAU,SAAS;AACrE,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,uDAAuD,IAAI,OAAO;AAC/F,SAAO,QAAQ,SAAS,GAAG,MAAM,wDAAwD,QAAQ,OAAO;AACxG,4BAA0B,UAAU,MAAM,eAAe;AACzD,QAAM,UAAU,eAAe,SAAS,IAAI,MAAM,KAAK,IAAI,MAAM;AACjE,SAAO,YAAY,QAAQ,MAAM,IAAI,MAAM,oCAAoC,8CAA8C,QAAQ,MAAM,KAAK;AAChJ,SAAO,+BAA+BA,UAAS,SAAS,GAAG,MAAM,uEAAuEA,2BAA0B,YAAY;AAC9K,QAAM,SAAS,EAAE,GAAG,KAAK,QAAQ,QAAQ;AACzC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB;AAC3E,QAAM,MAAM,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAClD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,QAAQ,GAAG,QAAQ,QAAQ,MAAM,aAAa,OAAO,WAAW,GAAG,iBAAiB;AAC3F,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AAC3C,QAAM,UAAU,gBAAgB,QAAQ,UAAU,QAAQ;AAC1D,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EACjD;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,uDAAuD,IAAI,OAAO;AAC/F,SAAO,QAAQ,SAAS,GAAG,MAAM,wDAAwD,QAAQ,OAAO;AACxG,4BAA0B,UAAU,MAAM,eAAe;AACzD,SAAO,IAAI,MAAM,OAAO,QAAQ,MAAM,IAAI,MAAM,oCAAoC,IAAI,MAAM,yCAAyC,QAAQ,MAAM,KAAK;AAC1J,SAAO,+BAA+B,QAAQ,QAAQ,GAAG,MAAM,oEAAoE,wBAAwB,WAAW;AACtK,SAAO,eAAe,OAAO,MAAM,sCAAsC,iDAAiD;AAC1H,QAAM,WAAW,QAAQ,SAAS,CAAC,GAAG,QAAQ,MAAM,IAAI,QAAQ,MAAM,IAAI,QAAQ,MAAM,EAAE,CAAC;AAC3F,QAAM,UAAU,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,GAAG,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAC1E,QAAMA,WAAU,CAAC,GAAG,MAAM;AAC1B,QAAM,YAAY,CAAC,GAAG,QAAQ;AAC9B,QAAM,mBAAmB;AACzB,QAAM,MAAM,OAAO,SAAS,UAAUA,UAAS,MAAM,kBAAkB,WAAW,eAAe;AACjG,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAClD;AACA,SAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAChE;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,qBAAqB,QAAQ,IAAI,QAAQA,UAAS,MAAM,aAAa,QAAQ,iBAAiB;AACrG,SAAO,OAAO,WAAW,GAAG,MAAM,MAAM,sBAAsB,OAAO,2BAA2B,GAAG,kBAAkB;AACrH,MAAI,WAAW;AACf,MAAI,OAAO;AACX,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,WAAO,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAC7D,eAAW,CAAC,GAAG,OAAO,IAAI,OAAO,IAAI,OAAO,EAAE;AAAA,EAChD;AACA,SAAO,SAAS,WAAW,GAAG,MAAM,qEAAqE,SAAS,SAAS;AAC3H,SAAO,KAAK,SAAS,GAAG,MAAM,4DAA4D,KAAK,MAAM;AACrG,SAAO,OAAO,SAAS,GAAG,MAAM,gEAAgE,OAAO,MAAM;AAC7G,QAAM,UAAU,eAAe,SAAS,SAAS,KAAK,SAAS;AAC/D,QAAM,WAAW,eAAe,SAAS,KAAK,MAAM,KAAK,KAAK,MAAM;AACpE,SAAO,YAAY,OAAO,MAAM,IAAI,MAAM,4CAA4C,8CAA8C,OAAO,MAAM,KAAK;AACtJ,SAAO,aAAa,OAAO,MAAM,IAAI,MAAM,6CAA6C,gDAAgD,OAAO,MAAM,KAAK;AAC1J,4BAA0B,kBAAkB,MAAM,eAAe;AACjE,QAAM,SAAS,EAAE,IAAI,MAAM,OAAO;AAClC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,iBAAiB,YAAY,SAAS;AACtF,QAAM,MAAM,OAAO,UAAU,qBAAqB,QAAQ,KAAK;AAC/D,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,sBAAsB,GAAG,EAAE,qBAAqB,CAAC;AAGrD,SAAS,iBAAiB,GAAG,QAAQ,aAAaA,UAAS,MAAM,iBAAiB;AAChF,QAAM,KAAK,gBAAgB,GAAG,KAAK,iBAAiB;AACpD,QAAM,UAAU,gBAAgB,QAAQ,UAAU,iBAAiB;AACnE,SAAO,oBAAoB,aAAa,IAAI,SAASA,UAAS,MAAM,QAAQ,eAAe;AAC7F;AACA,IAAI,kBAAkB,GAAG,EAAE,iBAAiB,CAAC;AAG7C,SAAS,QAAQ,GAAG,QAAQA,UAAS,MAAM,aAAa,SAAS,YAAY,CAAC,GAAG,GAAG,CAAC,GAAG;AACtF,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AAC3C,QAAM,UAAU,gBAAgB,QAAQ,UAAU,QAAQ;AAC1D,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC3E;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,uDAAuD,IAAI,OAAO;AAC/F,SAAO,QAAQ,SAAS,GAAG,MAAM,wDAAwD,QAAQ,OAAO;AACxG,SAAO,IAAI,MAAM,OAAO,QAAQ,MAAM,IAAI,MAAM,oCAAoC,IAAI,MAAM,yCAAyC,QAAQ,MAAM,KAAK;AAC1J,SAAO,+BAA+BA,UAAS,SAAS,GAAG,MAAM,uEAAuEA,2BAA0B,YAAY;AAC9K,SAAO,eAAe,SAAS,MAAM,sCAAsC,mDAAmD;AAC9H,QAAM,SAAS,EAAE,GAAG,KAAK,QAAQ,QAAQ;AACzC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,UAAU;AAC1D,QAAM,MAAM,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAClD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAC9E;AACA,SAAO;AACT;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,qBAAqB,QAAQ,IAAI,QAAQA,UAAS,MAAM;AAC/D,SAAO,OAAO,WAAW,GAAG,MAAM,MAAM,sBAAsB,OAAO,2BAA2B,GAAG,kBAAkB;AACrH,MAAI,WAAW;AACf,MAAI,OAAO;AACX,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,WAAO,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAC1E,eAAW,CAAC,GAAG,OAAO,IAAI,OAAO,IAAI,OAAO,IAAI,OAAO,EAAE;AAAA,EAC3D;AACA,QAAM,UAAU,SAAS;AACzB,QAAM,WAAW,KAAK,MAAM;AAC5B,SAAO,SAAS,WAAW,GAAG,MAAM,qEAAqE,SAAS,SAAS;AAC3H,SAAO,KAAK,SAAS,GAAG,MAAM,4DAA4D,KAAK,MAAM;AACrG,SAAO,OAAO,SAAS,GAAG,MAAM,gEAAgE,OAAO,MAAM;AAC7G,SAAO,YAAY,OAAO,MAAM,IAAI,MAAM,4CAA4C,8CAA8C,OAAO,MAAM,KAAK;AACtJ,SAAO,aAAa,OAAO,MAAM,IAAI,MAAM,6CAA6C,gDAAgD,OAAO,MAAM,KAAK;AAC1J,QAAM,SAAS,EAAE,IAAI,MAAM,OAAO;AAClC,QAAM,QAAQ,EAAE,KAAK,MAAM,SAAAA,UAAS,YAAY,SAAS;AACzD,QAAM,MAAM,OAAO,UAAU,uBAAuB,QAAQ,KAAK;AACjE,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAC9E;AACA,SAAO;AACT;AACA,IAAI,sBAAsB,GAAG,EAAE,qBAAqB,CAAC;AAGrD,SAAS,iBAAiB,GAAG,QAAQ,aAAaA,UAAS,MAAM;AAC/D,QAAM,KAAK,gBAAgB,GAAG,KAAK,iBAAiB;AACpD,QAAM,UAAU,gBAAgB,QAAQ,UAAU,iBAAiB;AACnE,SAAO,oBAAoB,aAAa,IAAI,SAASA,UAAS,IAAI;AACpE;AACA,IAAI,kBAAkB,GAAG,EAAE,iBAAiB,CAAC;AAG7C,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO,SAAS;AACnD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ,SAAS;AACpD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,SAAS,GAAG,OAAO,GAAG,YAAY,OAAO,WAAW,OAAO;AAClE,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,WAAW,SAAS,SAAS;AACnD,SAAO,OAAO,UAAU,SAAS,QAAQ,KAAK;AAChD;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,QAAQ,GAAG,OAAO,GAAG,YAAY,OAAO,WAAW,OAAO;AACjE,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AAC3C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,WAAW,SAAS,SAAS;AACnD,SAAO,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAC/C;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,eAAe,GAAG,SAASZ,OAAM,eAAe,OAAO;AAC9D,QAAM,KAAK,gBAAgB,GAAG,KAAK,eAAe;AAClD,QAAM,WAAW,gBAAgB,SAAS,WAAW,eAAe;AACpE,SAAO,GAAG,UAAU,SAAS,MAAM,8DAA8D,GAAG,OAAO;AAC3G,SAAO,GAAG,QAAQ,GAAG,MAAM,sEAAsE,GAAG,OAAO;AAC3G,SAAOA,SAAQ,GAAG,MAAM,sCAAsCA,QAAO;AACrE,SAAO,SAAS,SAAS,GAAG,QAAQ,SAAS,SAAS,GAAG,MAAM,+FAA+F,GAAG,yBAAyB,SAAS,QAAQ;AAC3M,QAAM,SAAS,EAAE,GAAG,IAAI,SAAS,SAAS;AAC1C,QAAM,QAAQ,EAAE,MAAAA,OAAM,aAAa;AACnC,SAAO,OAAO,UAAU,eAAe,QAAQ,KAAK;AACtD;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,cAAc,GAAG,WAAW,aAAa,QAAQ;AACxD,QAAM,KAAK,gBAAgB,GAAG,KAAK,gBAAgB,SAAS;AAC5D,QAAM,cAAc,eAAe,SAAS,GAAG,MAAM,KAAK,GAAG,MAAM;AACnE,QAAM,aAAa,eAAe,SAAS,GAAG,MAAM,KAAK,GAAG,MAAM;AAClE,QAAM,aAAa,eAAe,SAAS,GAAG,MAAM,KAAK,GAAG,MAAM;AAClE,SAAO,YAAY,GAAG,MAAM,sDAAsD,WAAW;AAC7F,SAAO,cAAc,aAAa,GAAG,MAAM;AAAA,MACvC,mBAAmB;AAAA,MACnB,GAAG,OAAO;AACd,SAAO,aAAa,aAAa,GAAG,MAAM;AAAA,MACtC,kBAAkB;AAAA,UACd,GAAG,OAAO;AAClB,SAAO,cAAc,YAAY,eAAe,GAAG,MAAM,8CAA8C,YAAY,oBAAoB,gDAAgD,GAAG,OAAO;AACjM,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,WAAW,WAAW;AACtC,SAAO,OAAO,UAAU,cAAc,QAAQ,KAAK;AACrD;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,iBAAiB,GAAG,QAAQY,UAAS,MAAM,aAAa,QAAQ,YAAY,CAAC,GAAG,CAAC,GAAG,iBAAiB;AAC5G,QAAM,KAAK,gBAAgB,GAAG,KAAK,mBAAmB,SAAS;AAC/D,QAAM,UAAU,gBAAgB,QAAQ,UAAU,mBAAmB,SAAS;AAC9E,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,gEAAgE,IAAI,OAAO;AACxG,SAAO,QAAQ,SAAS,GAAG,MAAM,iEAAiE,QAAQ,OAAO;AACjH,QAAM,aAAa,eAAe,SAAS,IAAI,MAAM,KAAK,IAAI,MAAM;AACpE,SAAO,eAAe,QAAQ,MAAM,IAAI,MAAM,uDAAuD,6DAA6D,QAAQ,MAAM,KAAK;AACrL,4BAA0B,mBAAmB,MAAM,eAAe;AAClE,QAAM,SAAS,EAAE,GAAG,KAAK,QAAQ,QAAQ;AACzC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB;AAC3E,QAAM,MAAM,OAAO,UAAU,uBAAuB,QAAQ,KAAK;AACjE,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,kBAAkB,GAAG,EAAE,iBAAiB,CAAC;AAG7C,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,YAAY,GAAG,QAAQA,UAAS,MAAM,YAAY,CAAC,GAAG,CAAC,GAAG,aAAa,QAAQ;AACtF,QAAM,KAAK,gBAAgB,GAAG,KAAK,YAAY;AAC/C,QAAM,UAAU,gBAAgB,QAAQ,UAAU,YAAY;AAC9D,SAAO,GAAG,SAAS,KAAK,GAAG,SAAS,GAAG,MAAM,gEAAgE,GAAG,OAAO;AACvH,SAAO,QAAQ,SAAS,GAAG,MAAM,4DAA4D,QAAQ,OAAO;AAC5G,SAAO,eAAe,QAAQ,MAAM,gFAAgF,YAAY;AAChI,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAC5D,mBAAe;AAAA,EACjB;AACA,QAAM,SAAS,EAAE,GAAG,KAAK,QAAQ,QAAQ;AACzC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,UAAU;AAC9C,QAAM,MAAM,OAAO,UAAU,YAAY,QAAQ,KAAK;AACtD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,OAAO,GAAG,GAAG;AACpB,MAAI,KAAK,gBAAgB,GAAG,KAAK,SAAS,mBAAmB;AAC7D,MAAI,KAAK,gBAAgB,GAAG,KAAK,SAAS,mBAAmB;AAC7D,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,OAAO,WAAW,GAAG,GAAG;AAC/B,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,aAAa,gBAAgB,WAAW,aAAa,SAAS,MAAM;AAC1E,QAAM,iBAAiB,2BAA2B,2BAA2B,WAAW,OAAO,GAAG,KAAK,GAAG,GAAG,KAAK;AAClH,QAAM,wBAAwB,YAAY,YAAY,cAAc;AACpE,QAAM,gBAAgB,YAAY,IAAI,cAAc;AACpD,QAAM,gBAAgB,YAAY,IAAI,cAAc;AACpD,QAAM,SAAS;AAAA,IACb,WAAW;AAAA,IACX,GAAG;AAAA,IACH,GAAG;AAAA,EACL;AACA,SAAO,OAAO,UAAU,QAAQ,MAAM;AACxC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,WAAW,GAAG;AACrB,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,WAAW,MAAM;AAC3C;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,UAAU,GAAG,GAAG;AACvB,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,YAAY,IAAI,IAAI,EAAE;AAC5B,QAAM,SAAS,UAAU,SAAS;AAClC,QAAM,cAAc,MAAM,IAAI,MAAM;AACpC,SAAO,MAAM,aAAa,QAAQ,SAAS;AAC7C;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,KAAK,IAAI,IAAI;AACpB,QAAM,MAAM,gBAAgB,IAAI,MAAM,KAAK;AAC3C,QAAM,MAAM,gBAAgB,IAAI,MAAM,KAAK;AAC3C,UAAQ,IAAI,SAAS,KAAK,IAAI,SAAS,OAAO,IAAI,SAAS,KAAK,IAAI,SAAS,IAAI,MAAM,+DAA+D,IAAI,YAAY,IAAI,OAAO;AACjL,QAAM,UAAU,IAAI,SAAS,IAAI,IAAI,OAAO,IAAI,MAAM;AACtD,QAAM,UAAU,IAAI,SAAS,IAAI,IAAI,OAAO,IAAI,MAAM;AACtD,SAAO,YAAY,SAAS,MAAM,gEAAgE,eAAe,UAAU;AAC3H,MAAI,IAAI,SAAS,KAAK,IAAI,SAAS,GAAG;AACpC,UAAM,OAAO,QAAQ,KAAK,CAAC,GAAG,EAAE,CAAC;AACjC,UAAM,OAAO,QAAQ,KAAK,CAAC,IAAI,CAAC,CAAC;AACjC,UAAM,OAAO,OAAO,MAAM,IAAI;AAC9B,WAAO,QAAQ,MAAM,CAAC,CAAC;AAAA,EACzB,WAAW,IAAI,SAAS,KAAK,IAAI,SAAS,GAAG;AAC3C,UAAM,OAAO,QAAQ,KAAK,CAAC,GAAG,EAAE,CAAC;AACjC,UAAM,OAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AACtD,UAAM,OAAO,OAAO,MAAM,IAAI;AAC9B,WAAO,QAAQ,MAAM,CAAC,KAAK,IAAI,CAAC;AAAA,EAClC,WAAW,IAAI,SAAS,KAAK,IAAI,SAAS,GAAG;AAC3C,UAAM,OAAO,QAAQ,KAAK,CAAC,IAAI,CAAC,CAAC;AACjC,UAAM,OAAO,OAAO,KAAK,IAAI;AAC7B,WAAO,QAAQ,MAAM,CAAC,KAAK,IAAI,CAAC;AAAA,EAClC,OAAO;AACL,UAAM,OAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AACtD,UAAM,OAAO,OAAO,KAAK,IAAI;AAC7B,WAAO;AAAA,EACT;AACF;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,QAAQ,aAAa,SAAS;AACrC,QAAM,WAAW,QAAQ,IAAI,CAAC,IAAI,OAAO,gBAAgB,IAAI,UAAU,MAAM,QAAQ,CAAC;AACtF,QAAM,QAAQ,EAAE,SAAS;AACzB,SAAO,OAAO,UAAU,QAAQ,UAAU,KAAK;AACjD;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO,SAAS;AACnD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,KAAK,GAAG;AACf,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,SAAO,GAAG,UAAU,WAAW,GAAG,UAAU,WAAW,MAAM,2CAA2C;AACxG,MAAI,GAAG,UAAU,SAAS;AACxB,SAAK,KAAK,IAAI,SAAS;AAAA,EACzB;AACA,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,qBAAqB,MAAM,MAAM;AACxC,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,QAAI,KAAK,KAAK,SAAS,KAAK,OAAO,OAAO,IAAI,IAAI;AAChD,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,WAAW,WAAW,MAAM;AACpD,QAAM,OAAO,UAAU,SAAS,UAAU;AAC1C,QAAM,MAAM,CAAC;AACb,MAAI,SAAS;AACb,MAAI,YAAY;AAChB,WAAS,MAAM,GAAG,MAAM,MAAM,OAAO;AACnC,QAAI,KAAK,QAAQ,GAAG,MAAM,IAAI;AAC5B,UAAI,KAAK,UAAU,SAAS;AAAA,IAC9B,OAAO;AACL,UAAI,KAAK,UAAU,YAAY;AAAA,IACjC;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,0BAA0B,QAAQ,MAAM;AAC/C,QAAM,WAAW,CAAC;AAClB,QAAM,OAAO,OAAO;AACpB,WAAS,MAAM,GAAG,MAAM,MAAM,OAAO;AACnC,QAAI,KAAK,QAAQ,GAAG,MAAM,IAAI;AAC5B,eAAS,KAAK,OAAO,IAAI;AAAA,IAC3B;AAAA,EACF;AACA,QAAM,cAAc,KAAK,IAAI,CAAC,QAAQ,OAAO,IAAI;AACjD,SAAO,CAAC,UAAU,WAAW;AAC/B;AACA,SAAS,qBAAqB,OAAO,MAAM;AACzC,QAAM,iBAAiB,KAAK,IAAI,CAAC,MAAM,CAAC;AACxC,SAAO,iBAAiB,OAAO,gBAAgB,IAAI;AACrD;AACA,SAAS,2BAA2B,KAAK,MAAM,MAAM;AACnD,SAAO,qBAAqB,MAAM,IAAI,GAAG,MAAM,GAAG,uDAAuD,iBAAiB,aAAa;AACzI;AACA,SAAS,mBAAmB,MAAM,MAAM;AACtC,MAAI,qBAAqB,MAAM,IAAI,GAAG;AACpC,WAAO;AAAA,EACT;AACA,QAAM,SAAS,CAAC;AAChB,WAAS,KAAK,GAAG,KAAK,MAAM,EAAE,IAAI;AAChC,QAAI,KAAK,QAAQ,EAAE,MAAM,IAAI;AAC3B,aAAO,KAAK,EAAE;AAAA,IAChB;AAAA,EACF;AACA,OAAK,QAAQ,CAAC,SAAS,OAAO,KAAK,IAAI,CAAC;AACxC,SAAO;AACT;AACA,SAAS,uBAAuB,MAAM;AACpC,SAAO,KAAK,IAAI,CAAC,MAAM,OAAO,CAAC,IAAI,IAAI,CAAC,EAAE,KAAK,CAAC,GAAG,MAAM,EAAE,KAAK,EAAE,EAAE,EAAE,IAAI,CAAC,MAAM,EAAE,EAAE;AACvF;AACA,SAAS,iBAAiB,SAAS,MAAM;AACvC,QAAM,MAAM,CAAC;AACb,WAAS,KAAK,OAAO,SAAS,KAAK,MAAM,EAAE,IAAI;AAC7C,QAAI,KAAK,EAAE;AAAA,EACb;AACA,SAAO;AACT;AAGA,SAAS,KAAK,GAAG,OAAO,MAAM,WAAW,OAAO;AAC9C,QAAM,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACxC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,kBAAkB,MAAM,SAAS;AACjD,SAAO,OAAO,UAAU,KAAK,QAAQ,KAAK;AAC5C;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,KAAK,GAAG,OAAO,MAAM,WAAW,OAAO;AAC9C,QAAM,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACxC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,SAAS;AAC/B,SAAO,OAAO,UAAU,KAAK,QAAQ,KAAK;AAC5C;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,KAAK,MAAM,MAAM;AACxB,MAAI,QAAQ,gBAAgB,MAAM,QAAQ,KAAK;AAC/C,MAAI,OAAO,gBAAgB,MAAM,OAAO,KAAK;AAC7C,GAAC,OAAO,IAAI,IAAI,eAAe,OAAO,IAAI;AAC1C,QAAM,SAAS,EAAE,GAAG,OAAO,GAAG,KAAK;AACnC,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,OAAO,OAAO,OAAO;AAC5B,OAAK,aAAa,KAAK,KAAK,UAAU,YAAY,MAAM,QAAQ,KAAK,MAAM,UAAU,aAAa;AAChG,UAAM,IAAI,MAAM,gFAAgF;AAAA,EAClG;AACA,MAAI,UAAU,YAAY,aAAa,KAAK,KAAK,EAAE,iBAAiB,aAAa;AAC/E,UAAM,IAAI,MAAM,2EAA2E;AAAA,EAC7F;AACA,QAAM,QAAQ,CAAC;AACf,QAAM,gBAAgB,CAAC;AACvB,SAAO,WAAW,OAAO,OAAO,eAAe,KAAK;AACtD;AAGA,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ,SAAS;AACpD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,QAAQ,GAAG;AAClB,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AAC3C,QAAM,QAAQ,CAAC;AACf,SAAO,OAAO,UAAU,UAAU,EAAE,GAAG,GAAG,GAAG,KAAK;AACpD;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,KAAK,GAAG,OAAO,MAAM,WAAW,OAAO;AAC9C,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,MAAI,GAAG,UAAU,QAAQ;AACvB,SAAK,KAAK,IAAI,OAAO;AAAA,EACvB;AACA,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,SAAS;AAC/B,SAAO,OAAO,UAAU,KAAK,QAAQ,KAAK;AAC5C;AACA,IAAI,OAAO,GAAG,EAAE,KAAK,CAAC;AAGtB,SAAS,MAAM,GAAG,MAAM,aAAa,OAAO,MAAM,WAAW,OAAO;AAClE,MAAI,gBAAgB,GAAG,KAAK,MAAM;AAClC,QAAM,QAAQ,SAAS,GAAG,KAAK,IAAI;AACnC,MAAI,gBAAgB,MAAM;AAC1B,MAAI,UAAU;AACZ,UAAM,OAAO,eAAe,MAAM,EAAE,KAAK;AACzC,oBAAgB,qBAAqB,MAAM,OAAO,IAAI;AAAA,EACxD;AACA,SAAO,QAAQ,OAAO,aAAa;AACrC;AACA,SAAS,SAAS,GAAG,IAAI,OAAO,MAAM;AACpC,MAAI,EAAE,SAAS,GAAG;AAChB,WAAO,IAAI,CAAC;AAAA,EACd;AACA,MAAI,EAAE,SAAS,KAAK,SAAS,MAAM;AACjC,WAAO,SAAS,QAAQ,GAAG,CAAC,EAAE,CAAC,GAAG,IAAI,IAAI;AAAA,EAC5C;AACA,MAAI,EAAE,SAAS,KAAK,OAAO,SAAS,YAAY,MAAM,QAAQ,IAAI,KAAK,KAAK,WAAW,GAAG;AACxF,QAAI,OAAO,GAAG;AACZ,aAAO,KAAK,IAAI,CAAC,GAAG,IAAI;AAAA,IAC1B;AACA,QAAI,OAAO,UAAU;AACnB,aAAO,IAAI,IAAI,CAAC,GAAG,IAAI;AAAA,IACzB;AACA,QAAI,OAAO,WAAW;AACpB,aAAO,IAAI,IAAI,CAAC,GAAG,IAAI;AAAA,IACzB;AACA,QAAI,OAAO,eAAe,OAAO,GAAG;AAClC,aAAO,KAAK,KAAK,IAAI,IAAI,CAAC,GAAG,OAAO,GAAG,OAAO,CAAC,GAAG,IAAI,CAAC;AAAA,IACzD;AACA,UAAM,IAAI,MAAM,qCAAqC,IAAI;AAAA,EAC3D;AACA,MAAI,MAAM,QAAQ,IAAI,KAAK,KAAK,WAAW,GAAG;AAC5C,QAAI,OAAO,GAAG;AACZ,aAAO,IAAI,KAAK,IAAI,CAAC,GAAG,KAAK,EAAE,GAAG,KAAK,KAAK,CAAC;AAAA,IAC/C;AACA,QAAI,OAAO,UAAU;AACnB,aAAO,IAAI,KAAK,IAAI,CAAC,GAAG,KAAK,EAAE,GAAG,KAAK,EAAE;AAAA,IAC3C;AACA,QAAI,OAAO,WAAW;AACpB,aAAO,IAAI,KAAK,IAAI,CAAC,GAAG,KAAK,EAAE,GAAG,KAAK,EAAE;AAAA,IAC3C;AACA,QAAI,OAAO,SAAS,OAAO,aAAa;AACtC,aAAO,KAAK,KAAK,OAAO,CAAC,GAAG,IAAI,CAAC;AAAA,IACnC;AACA,UAAM,IAAI,MAAM,qCAAqC,IAAI;AAAA,EAC3D;AACA,QAAM,IAAI,MAAM,gCAAgC,MAAM;AACxD;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,eAAe,GAAG,OAAO,MAAM,WAAW,OAAO;AACxD,SAAO,KAAK,GAAG,aAAa,MAAM,QAAQ;AAC5C;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACxC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,YAAY,GAAG,OAAO,GAAG;AAChC,QAAM,KAAK,gBAAgB,GAAG,KAAK,cAAc,mBAAmB;AACpE,SAAO,QAAQ,GAAG,MAAM,MAAM,oCAAoC;AAClE,QAAM,SAAS,EAAE,OAAO,GAAG;AAC3B,QAAM,QAAQ,EAAE,KAAK,KAAK;AAC1B,SAAO,OAAO,UAAU,YAAY,QAAQ,KAAK;AACnD;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,GAAG,MAAM;AACtB,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ,mBAAmB;AAC9D,SAAO,GAAG,SAAS,KAAK,QAAQ,MAAM,qCAAqC,GAAG,kCAAkC,OAAO;AACvH,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,KAAK;AACrB,SAAO,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC7C;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,KAAK,SAAS,YAAY,YAAY,QAAQ,WAAW;AAChE,MAAI,cAAc,MAAM;AACtB,iBAAa;AAAA,EACf;AACA,QAAM,OAAO,OAAO,CAAC,SAAS,UAAU,GAAG,KAAK;AAChD,QAAM,KAAK,WAAW,aAAa,UAAU;AAC7C,WAAS,KAAK,GAAG,KAAK,IAAI,EAAE,IAAI;AAC9B,SAAK,IAAI,GAAG,IAAI,EAAE;AAAA,EACpB;AACA,QAAM,MAAM,QAAQ,KAAK,SAAS,GAAG,CAAC,SAAS,UAAU,CAAC;AAC1D,MAAI,cAAc,MAAM;AACtB,WAAO;AAAA,EACT,OAAO;AACL,QAAI,WAAW,WAAW,GAAG;AAC3B,aAAO,KAAK,WAAW,KAAK,CAAC,GAAG,CAAC,WAAW,IAAI,GAAG,CAAC,CAAC;AAAA,IACvD,WAAW,WAAW,WAAW,GAAG;AAClC,aAAO,KAAK,WAAW,WAAW,KAAK,CAAC,GAAG,CAAC,GAAG,CAAC,WAAW,IAAI,WAAW,IAAI,GAAG,CAAC,CAAC;AAAA,IACrF,WAAW,WAAW,WAAW,GAAG;AAClC,aAAO,KAAK,WAAW,WAAW,WAAW,KAAK,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG;AAAA,QAC5D,WAAW;AAAA,QACX,WAAW;AAAA,QACX,WAAW;AAAA,QACX;AAAA,QACA;AAAA,MACF,CAAC;AAAA,IACH,OAAO;AACL,YAAM,IAAI,MAAM,qEAAqE,WAAW,UAAU;AAAA,IAC5G;AAAA,EACF;AACF;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,KAAK,OAAO,OAAO,OAAO;AACjC,QAAM,QAAQ,EAAE,OAAO,OAAO,MAAM;AACpC,SAAO,OAAO,UAAU,MAAM,CAAC,GAAG,KAAK;AACzC;AAGA,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS,SAAS;AACrD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,QAAQ,GAAG,SAAS,OAAO,GAAG,YAAY,GAAG;AACpD,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AAC3C,QAAM,WAAW,gBAAgB,SAAS,WAAW,UAAU,OAAO;AACtE,QAAM,SAAS,EAAE,GAAG,IAAI,SAAS,SAAS;AAC1C,QAAM,QAAQ,EAAE,MAAM,UAAU;AAChC,SAAO,OAAO,UAAU,UAAU,QAAQ,KAAK;AACjD;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,SAAS,GAAG,GAAG;AACtB,MAAI,KAAK,gBAAgB,GAAG,KAAK,WAAW,mBAAmB;AAC/D,MAAI,KAAK,gBAAgB,GAAG,KAAK,WAAW,mBAAmB;AAC/D,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,SAAS,MAAM;AACzC;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,cAAc,GAAG,GAAG;AAC3B,MAAI,KAAK,gBAAgB,GAAG,KAAK,gBAAgB,mBAAmB;AACpE,MAAI,KAAK,gBAAgB,GAAG,KAAK,gBAAgB,mBAAmB;AACpE,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,cAAc,MAAM;AAC9C;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,UAAU,GAAG;AACpB,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU;AAC7C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,YAAY,GAAG,EAAE,UAAU,CAAC;AAGhC,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,SAAS,GAAG,EAAE,OAAO,CAAC;AAG1B,SAAS,WAAW,GAAGU,SAAQ,KAAK;AAClC,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,OAAAA,OAAM;AACtB,SAAO,OAAO,UAAU,WAAW,QAAQ,KAAK;AAClD;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,MAAM,GAAG,GAAG;AACnB,MAAI,KAAK,gBAAgB,GAAG,KAAK,QAAQ,mBAAmB;AAC5D,MAAI,KAAK,gBAAgB,GAAG,KAAK,QAAQ,mBAAmB;AAC5D,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,WAAW,GAAG,GAAG;AACxB,MAAI,KAAK,gBAAgB,GAAG,KAAK,aAAa,mBAAmB;AACjE,MAAI,KAAK,gBAAgB,GAAG,KAAK,aAAa,mBAAmB;AACjE,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,WAAW,MAAM;AAC3C;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,SAAS,OAAO,MAAM,KAAK;AAClC,MAAI,OAAO,GAAG;AACZ,UAAM,IAAI,MAAM,0CAA0C;AAAA,EAC5D;AACA,QAAM,QAAQ,EAAE,OAAO,MAAM,IAAI;AACjC,SAAO,OAAO,UAAU,UAAU,CAAC,GAAG,KAAK;AAC7C;AAGA,SAAS,4BAA4B,GAAG,cAAc,GAAG,OAAO,GAAGA,SAAQ,GAAG,OAAO,KAAK;AACxF,QAAM,KAAK,gBAAgB,GAAG,KAAK,4BAA4B;AAC/D,SAAO,GAAG,SAAS,KAAK,GAAG,SAAS,GAAG,MAAM;AAAA,sBACzB,GAAG,OAAO;AAC9B,SAAO,MAAM,WAAW,GAAG,MAAM,2FAA2F,cAAc;AAC1I,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,QAAM,SAAS,EAAE,GAAG,IAAI;AACxB,QAAM,QAAQ,EAAE,aAAa,MAAM,OAAAA,QAAO,KAAK;AAC/C,QAAM,MAAM,OAAO,UAAU,KAAK,QAAQ,KAAK;AAC/C,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE,OAAO;AACL,WAAO;AAAA,EACT;AACF;AACA,IAAI,6BAA6B,GAAG,EAAE,4BAA4B,CAAC;AAGnE,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO,SAAS;AACnD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI3B,QAAO,GAAG,EAAE,KAAK,CAAC;AAGtB,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,KAAK,GAAG;AACf,SAAO,WAAW,CAAC,GAAG,MAAM,4CAA4C;AACxE,SAAO,CAAC,GAAG,OAAO;AAChB,UAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW,mBAAmB;AACjE,UAAM,MAAM,MAAM,OAAO,gBAAgB,IAAI,MAAM,SAAS,IAAI;AAChE,WAAO,OAAO,KAAK,MAAM;AACvB,YAAM,EAAE,OAAO,OAAO,OAAO,IAAI,OAAO,UAAU,MAAM,EAAE,EAAE,GAAG,CAAC,EAAE,GAAG,GAAG;AACxE,UAAI,OAAO,MAAM;AACf,0BAAkB,MAAM,OAAO,IAAI,OAAO,gFAAgF;AAAA,MAC5H;AACA,iBAAW,MAAM;AACjB,aAAO,OAAO;AAAA,IAChB,CAAC;AAAA,EACH;AACF;AACA,SAAS,MAAM,GAAG;AAChB,SAAO,WAAW,CAAC,GAAG,MAAM,6CAA6C;AACzE,SAAO,CAAC,MAAM,OAAO;AACnB,WAAO,MAAM,QAAQ,IAAI,GAAG,MAAM,kFAAkF;AACpH,UAAM,QAAQ,qBAAqB,MAAM,QAAQ,YAAY,mBAAmB;AAChF,UAAM,MAAM,MAAM,OAAO,gBAAgB,IAAI,MAAM,UAAU,IAAI;AACjE,WAAO,OAAO,KAAK,MAAM;AACvB,YAAM,EAAE,OAAO,OAAO,OAAO,IAAI,OAAO,UAAU,MAAM,EAAE,GAAG,KAAK,GAAG,OAAO,GAAG;AAC/E,UAAI,OAAO,MAAM;AACf,0BAAkB,MAAM,OAAO,IAAI,OAAO,+FAA+F;AAAA,MAC3I;AACA,iBAAW,MAAM;AACjB,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,SAAS,aAAa,GAAG;AACvB,SAAO,WAAW,CAAC,GAAG,MAAM,oDAAoD;AAChF,SAAO,CAAC,GAAG,OAAO;AAChB,WAAO,aAAa,QAAQ,MAAM,qDAAqD;AACvF,WAAO,MAAM,QAAQ,cAAc,QAAQ,MAAM,0DAA0D;AAC3G,UAAM,EAAE,OAAO,QAAQ,MAAM,IAAI,OAAO,UAAU,MAAM,EAAE,CAAC,GAAG,CAAC,CAAC,GAAG,EAAE;AACrE,eAAW,MAAM;AACjB,WAAO,EAAE,MAAM,OAAO,IAAI,MAAM;AAAA,EAClC;AACF;AACA,SAAS,cAAc,GAAG;AACxB,SAAO,WAAW,CAAC,GAAG,MAAM,qDAAqD;AACjF,SAAO,CAAC,MAAM,OAAO;AACnB,WAAO,MAAM,QAAQ,IAAI,KAAK,KAAK,MAAM,CAAC,QAAQ,eAAe,MAAM,GAAG,MAAM,oEAAoE;AACpJ,WAAO,MAAM,QAAQ,cAAc,QAAQ,MAAM,8DAA8D;AAC/G,UAAM,MAAM,OAAO,UAAU,MAAM,EAAE,GAAG,IAAI,GAAG,MAAM,EAAE;AACvD,QAAI,MAAM,MAAM;AACd,wBAAkB,IAAI,MAAM,OAAO,GAAG,OAAO,uGAAuG;AAAA,IACtJ;AACA,eAAW,IAAI,KAAK;AACpB,WAAO;AAAA,EACT;AACF;AACA,SAAS,cAAc,GAAG,SAAS;AACjC,SAAO,WAAW,CAAC,GAAG,MAAM,qDAAqD;AACjF,SAAO,WAAW,QAAQ,MAAM,QAAQ,OAAO,KAAK,QAAQ,MAAM,CAAC,MAAM,aAAa,QAAQ,GAAG,MAAM,+EAA+E;AACtL,QAAM,mBAAmB,WAAW;AACpC,MAAI,CAAC,kBAAkB;AACrB,cAAU,CAAC;AACX,eAAW,WAAW,OAAO,qBAAqB;AAChD,cAAQ,KAAK,OAAO,oBAAoB,QAAQ;AAAA,IAClD;AAAA,EACF;AACA,QAAM,wBAAwB,mBAAmB,QAAQ,OAAO,CAAC,cAAc,CAAC,UAAU,SAAS,IAAI;AACvG,QAAM,mBAAmB,QAAQ;AACjC,YAAU,QAAQ,OAAO,CAAC,cAAc,UAAU,SAAS;AAC3D,SAAO,QAAQ,SAAS,GAAG,MAAM,gGAAgG,0CAA0C;AAC3K,QAAM,mBAAmB;AACzB,QAAM,EAAE,OAAO,OAAO,OAAO,IAAI,OAAO,UAAU,GAAG,SAAS,MAAM,gBAAgB;AACpF,SAAO,OAAO,KAAK,CAAC,MAAM,KAAK,IAAI,GAAG,MAAM,8LAA8L;AAC1O,SAAO,MAAM,SAAS,GAAG,MAAM,iFAAiF,MAAM,aAAa;AACnI,QAAM,aAAa,CAAC;AACpB,UAAQ,QAAQ,CAAC,GAAG,OAAO;AACzB,QAAI,OAAO,OAAO,MAAM;AACtB,iBAAW,EAAE,QAAQ,OAAO;AAAA,IAC9B;AAAA,EACF,CAAC;AACD,MAAI,yBAAyB,MAAM;AACjC,0BAAsB,QAAQ,CAAC,MAAM,WAAW,EAAE,QAAQ,IAAI;AAAA,EAChE;AACA,SAAO,EAAE,OAAO,OAAO,WAAW;AACpC;AACA,SAAS,WAAW,GAAG;AACrB,SAAO,OAAO,WAAW,CAAC;AAC5B;AACA,SAAS,WAAW,QAAQ;AAC1B,QAAM,mBAAmB,OAAO,OAAO,CAAC,MAAM,KAAK,IAAI,EAAE;AACzD,MAAI,mBAAmB,GAAG;AACxB,UAAM,IAAI,MAAM;AAAA,oEACgD;AAAA,EAClE;AACF;AAGA,SAAS,UAAU,GAAG;AACpB,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU;AAC7C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,YAAY,GAAG;AACtB,QAAM,KAAK,gBAAgB,GAAG,KAAK,YAAY;AAC/C,QAAM,WAAW,WAAW,CAAC,OAAO;AAClC,UAAM,QAAQ,IAAI,SAAS,IAAI,EAAE,CAAC,CAAC;AACnC,UAAM,WAAW,CAAC,OAAO;AACvB,YAAM,OAAO,IAAI,IAAI,QAAQ,IAAI,EAAE,CAAC,CAAC;AACrC,aAAO;AAAA,IACT;AACA,WAAO,EAAE,OAAO,SAAS;AAAA,EAC3B,CAAC;AACD,SAAO,SAAS,EAAE;AACpB;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,KAAK,GAAG,GAAG;AAClB,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,YAAY,QAAQ,OAAO,IAAI;AACtC,QAAM,UAAU,gBAAgB,QAAQ,UAAU,YAAY;AAC9D,MAAI,SAAS,IAAI;AACf,WAAO,QAAQ,OAAO;AAAA,EACxB;AACA,MAAI,SAAS,QAAQ,OAAO,GAAG;AAC7B,UAAM,MAAM,gFAAgF,QAAQ,qBAAqB,MAAM;AAAA,EACjI;AACA,QAAM,WAAW,WAAW,CAAC,SAAS,SAAS;AAC7C,UAAM,WAAW;AACjB,UAAM,OAAO,IAAI,SAAS,MAAM,IAAI;AACpC,UAAM,UAAU,IAAI,SAAS,IAAI;AACjC,UAAM,QAAQ,IAAI,KAAK,SAAS,SAAS,GAAGA,MAAK,KAAK,IAAI,OAAO,GAAG,MAAM,QAAQ,CAAC,CAAC;AACpF,SAAK,CAAC,KAAK,CAAC;AACZ,UAAM,WAAW,CAAC,IAAI,UAAU;AAC9B,YAAM,CAAC,MAAM,IAAI;AACjB,YAAM,YAAY;AAClB,YAAM,WAAW,IAAI,MAAM;AAC3B,aAAO,IAAI,IAAI,IAAI,KAAK,IAAI,MAAM,SAAS,GAAG,QAAQ,CAAC;AAAA,IACzD;AACA,WAAO,EAAE,OAAO,SAAS;AAAA,EAC3B,CAAC;AACD,SAAO,SAAS,OAAO;AACzB;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,WAAW,GAAG,OAAO,MAAM,WAAW,OAAO;AACpD,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,OAAO,eAAe,MAAM,GAAG,KAAK;AAC1C,QAAM,OAAO,IAAI,IAAI,MAAM,IAAI;AAC/B,QAAM,IAAI,IAAI,IAAI,IAAI;AACtB,QAAM,IAAI,IAAI,CAAC;AACf,QAAM,IAAI,KAAK,GAAG,IAAI;AACtB,QAAM,IAAIA,MAAK,CAAC;AAChB,QAAM,MAAM,KAAK,QAAQ,MAAM,EAAE,KAAK,GAAG,CAAC;AAC1C,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,IAAI,OAAO,IAAI;AACrD,WAAO,QAAQ,KAAK,QAAQ;AAAA,EAC9B;AACA,SAAO;AACT;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,YAAY,GAAG,GAAG;AACzB,QAAM,KAAK,gBAAgB,GAAG,KAAK,cAAc,MAAM;AACvD,QAAM,KAAK,gBAAgB,GAAG,KAAK,cAAc,MAAM;AACvD,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,YAAY,MAAM;AAC5C;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,YAAY,GAAG;AACtB,QAAM,KAAK,gBAAgB,GAAG,KAAK,cAAc,MAAM;AACvD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,YAAY,MAAM;AAC5C;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,WAAW,GAAG,GAAG;AACxB,QAAM,KAAK,gBAAgB,GAAG,KAAK,aAAa,MAAM;AACtD,QAAM,KAAK,gBAAgB,GAAG,KAAK,aAAa,MAAM;AACtD,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,WAAW,MAAM;AAC3C;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,YAAY,GAAG,GAAG;AACzB,QAAM,KAAK,gBAAgB,GAAG,KAAK,cAAc,MAAM;AACvD,QAAM,KAAK,gBAAgB,GAAG,KAAK,cAAc,MAAM;AACvD,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,SAAO,WAAW,UAAU,GAAG,CAAC,GAAG,WAAW,WAAW,GAAG,CAAC,CAAC,CAAC;AACjE;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,IAAI,YAAY;AAChB,SAAS,cAAc,gBAAgB,QAAQ,OAAO,QAAQ;AAC5D,QAAM,kBAAkB,gBAAgB,gBAAgB,kBAAkB,cAAc;AACxF,QAAM,UAAU,gBAAgB,QAAQ,UAAU,cAAc;AAChE,QAAM,eAAe,gBAAgB,MAAM,gBAAgB,MAAM,SAAS;AAC1E,QAAM,aAAa,QAAQ,MAAM,QAAQ,MAAM,SAAS;AACxD,QAAM,oBAAoB,QAAQ,iBAAiB,CAAC,IAAI,YAAY,CAAC;AACrE,QAAM,YAAY,QAAQ,SAAS,CAAC,IAAI,UAAU,CAAC;AACnD,MAAI,kBAAkB,OAAO,GAAG;AAC9B,UAAM,IAAI,MAAM,sDAAsD;AAAA,EACxE;AACA,MAAI,kBAAkB,MAAM,OAAO,UAAU,MAAM,IAAI;AACrD,UAAM,IAAI,MAAM,gEAAgE;AAAA,EAClF;AACA,MAAI,cAAc,UAAU,KAAK,KAAK,WAAW;AAC/C,UAAM,IAAI,MAAM,qCAAqC,WAAW;AAAA,EAClE;AACA,MAAI,kBAAkB,MAAM,MAAM,WAAW;AAC3C,UAAM,IAAI,MAAM,oCAAoC,wCAAwC,kBAAkB,MAAM,IAAI;AAAA,EAC1H;AACA,QAAM,SAAS;AAAA,IACb,gBAAgB;AAAA,IAChB,QAAQ;AAAA,EACV;AACA,QAAM,QAAQ,EAAE,KAAK;AACrB,SAAO,OAAO,UAAU,cAAc,QAAQ,KAAK;AACrD;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,WAAW,gBAAgB,QAAQ;AAC1C,SAAO,aAAa,gBAAgB,QAAQ,MAAM;AACpD;AAGA,SAAS,SAAS,GAAG,YAAYiB,UAAS,MAAM,iBAAiB;AAC/D,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,QAAM,YAAY;AAClB,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,uDAAuD,IAAI,OAAO;AAC/F,SAAO,+BAA+BA,UAAS,SAAS,GAAG,MAAM,wEAAwEA,2BAA0B,YAAY;AAC/K,4BAA0B,WAAW,MAAM,eAAe;AAC1D,QAAM,SAAS,EAAE,GAAG,IAAI;AACxB,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB;AAChE,QAAM,MAAM,OAAO,UAAU,SAAS,QAAQ,KAAK;AACnD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,WAAW,GAAG,aAAa,CAAC,GAAG,GAAG,CAAC,GAAGA,UAAS,MAAM,iBAAiB,aAAa,SAAS;AACnG,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC3E;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,qDAAqD,IAAI,OAAO;AAC7F,SAAO,eAAe,SAAS,MAAM,gFAAgF,YAAY;AACjI,4BAA0B,aAAa,MAAM,eAAe;AAC5D,QAAM,SAAS,EAAE,GAAG,IAAI;AACxB,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,iBAAiB,WAAW;AAC5E,QAAM,MAAM,OAAO,UAAU,WAAW,QAAQ,KAAK;AACrD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAC9E;AACA,SAAO;AACT;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,mBAAmB,GAAG,YAAYA,UAAS,MAAM,sBAAsB,OAAO;AACrF,QAAM,KAAK,gBAAgB,GAAG,KAAK,mBAAmB;AACtD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,oBAAoB;AACpE,QAAM,SAAS,OAAO,UAAU,mBAAmB,QAAQ,KAAK;AAChE,SAAO,EAAE,QAAQ,OAAO,IAAI,SAAS,OAAO,GAAG;AACjD;AACA,IAAI,oBAAoB,GAAG,EAAE,mBAAmB,CAAC;AAGjD,SAAS,SAAS,GAAG,GAAG;AACtB,MAAI,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC1C,MAAI,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC1C,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,MAAI,GAAG,UAAU,QAAQ;AACvB,SAAK,KAAK,IAAI,OAAO;AACrB,SAAK,KAAK,IAAI,OAAO;AAAA,EACvB;AACA,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,SAAS,MAAM;AACzC;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,MAAM,GAAG,OAAO,MAAM,WAAW,OAAO;AAC/C,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,SAAS;AAC/B,SAAO,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC7C;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,MAAM,OAAO,QAAQ,WAAW;AACvC,MAAI,UAAU,aAAa;AACzB,UAAM,QAAQ,MAAM,OAAO,SAAS;AACpC,UAAM,QAAQ,MAAM,OAAO,SAAS;AACpC,WAAO,QAAQ,OAAO,KAAK;AAAA,EAC7B;AACA,QAAM,SAAS,oBAAoB,cAAc,KAAK,GAAG,KAAK;AAC9D,SAAO,OAAO,WAAW,QAAQ,OAAO,KAAK;AAC/C;AAGA,SAAS,MAAM,OAAO,QAAQ,WAAW;AACvC,MAAI,UAAU,aAAa;AACzB,UAAM,QAAQ,MAAM,OAAO,SAAS;AACpC,UAAM,QAAQ,MAAM,OAAO,SAAS;AACpC,WAAO,QAAQ,OAAO,KAAK;AAAA,EAC7B;AACA,QAAM,SAAS,mBAAmB,cAAc,KAAK,GAAG,KAAK;AAC7D,SAAO,OAAO,WAAW,QAAQ,OAAO,KAAK;AAC/C;AAGA,SAAS,SAAS,GAAG,GAAG,EAAE,WAAW,KAAK,IAAI,CAAC,GAAG;AAChD,MAAI,aAAa,QAAQ,aAAa,MAAM;AAC1C,UAAM,IAAI,UAAU,GAAG,oDAAoD;AAAA,EAC7E;AACA,MAAI,MAAM,QAAQ;AAChB,WAAO,CAAC;AAAA,EACV;AACA,MAAI,KAAK,gBAAgB,GAAG,KAAK,YAAY,aAAa,SAAS,EAAE,QAAQ,SAAS;AACtF,MAAI,MAAM,QAAQ;AAChB,WAAO,CAAC,EAAE;AAAA,EACZ;AACA,MAAI,KAAK,gBAAgB,GAAG,KAAK,YAAY,aAAa,SAAS,EAAE,QAAQ,SAAS;AACtF,QAAM,IAAI,cAAc,GAAG,KAAK;AAChC,QAAM,IAAI,cAAc,GAAG,KAAK;AAChC,MAAI,aAAa,MAAM;AACrB,SAAK,QAAQ,IAAI,CAAC,GAAG,EAAE,CAAC;AACxB,SAAK,QAAQ,IAAI,CAAC,IAAI,CAAC,CAAC;AACxB,WAAO;AAAA,MACL,OAAO,MAAM,CAAC,GAAG,CAAC,GAAG,GAAG,KAAK,GAAG,EAAE;AAAA,MAClC,OAAO,IAAI,MAAM,CAAC,GAAG,CAAC,GAAG,GAAG,KAAK,CAAC;AAAA,IACpC;AAAA,EACF;AACA,OAAK,QAAQ,IAAI,CAAC,IAAI,CAAC,CAAC;AACxB,OAAK,QAAQ,IAAI,CAAC,GAAG,EAAE,CAAC;AACxB,SAAO;AAAA,IACL,OAAO,IAAI,MAAM,CAAC,GAAG,CAAC,GAAG,GAAG,KAAK,CAAC;AAAA,IAClC,OAAO,MAAM,CAAC,GAAG,CAAC,GAAG,GAAG,KAAK,GAAG,EAAE;AAAA,EACpC;AACF;AAGA,SAAS,SAAS,GAAG,GAAG;AACtB,MAAI,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC1C,MAAI,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC1C,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,MAAI,GAAG,UAAU,QAAQ;AACvB,SAAK,KAAK,IAAI,OAAO;AACrB,SAAK,KAAK,IAAI,OAAO;AAAA,EACvB;AACA,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,SAAS,MAAM;AACzC;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,WAAW,GAAG,UAAU,MAAM;AACrC,SAAO,SAAS,aAAa,SAAS,aAAa,MAAM,+DAA+D,OAAO;AAC/H,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,MAAI,GAAG,SAAS,GAAG;AACjB,UAAM,IAAI,MAAM,gEAAgE;AAAA,EAClF;AACA,SAAO,SAAS,WAAW,GAAG,MAAM,MAAM,wCAAwC,GAAG,aAAa,SAAS,SAAS;AACpH,QAAM,cAAc,SAAS,YAAY,IAAI;AAC7C,WAAS,KAAK,GAAG,KAAK,GAAG,MAAM,MAAM;AACnC,WAAO,SAAS,IAAI,WAAW,GAAG,MAAM,uDAAuD;AAC/F,WAAO,SAAS,IAAI,MAAM,KAAK,SAAS,IAAI,MAAM,GAAG,MAAM,MAAM,eAAe,SAAS,IAAI,MAAM,KAAK,SAAS,IAAI,MAAM,GAAG,MAAM,MAAM,aAAa,MAAM,wBAAwB,yCAAyC,GAAG,MAAM,MAAM,iDAAiD,GAAG,OAAO;AAAA,EAC1S;AACA,QAAM,QAAQ,EAAE,UAAU,KAAK;AAC/B,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,WAAW,QAAQ,KAAK;AAClD;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,KAAK,GAAG,GAAG;AAClB,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,SAAS,GAAG,OAAO,MAAM,WAAW,OAAO;AAClD,MAAI,gBAAgB,GAAG,KAAK,SAAS;AACrC,QAAM,OAAO,eAAe,MAAM,EAAE,KAAK;AACzC,QAAM,QAAQ,KAAK,GAAG,MAAM,QAAQ;AACpC,MAAI,gBAAgB,MAAM;AAC1B,MAAI,CAAC,UAAU;AACb,oBAAgB,qBAAqB,MAAM,OAAO,IAAI;AAAA,EACxD;AACA,QAAM,aAAa,OAAO,IAAI,KAAK,GAAG,SAAS,GAAG,QAAQ,OAAO,aAAa,CAAC,CAAC;AAChF,QAAM,WAAW,KAAK,YAAY,MAAM,QAAQ;AAChD,SAAO,EAAE,MAAM,OAAO,SAAS;AACjC;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,cAAc,WAAW,MAAM,GAAG,GAAG;AAC5C,QAAM,QAAQ,gBAAgB,MAAM,QAAQ,cAAc;AAC1D,QAAM,KAAK,qBAAqB,GAAG,KAAK,cAAc;AACtD,QAAM,KAAK,qBAAqB,GAAG,KAAK,cAAc;AACtD,MAAI,SAAS;AACb,QAAM,YAAY,CAAC;AACnB,WAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,MAAM;AAC5C,UAAM,SAAS,UAAU,IAAI,QAAQ,GAAG,KAAK,GAAG,GAAG;AACnD,cAAU,KAAK,OAAO,EAAE;AACxB,cAAU,KAAK,OAAO,EAAE;AACxB,aAAS,OAAO;AAAA,EAClB;AACA,QAAM,OAAO,CAAC;AACd,QAAM,OAAO,CAAC;AACd,WAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,MAAM,GAAG;AAC/C,SAAK,KAAK,UAAU,GAAG;AACvB,SAAK,KAAK,UAAU,KAAK,EAAE;AAAA,EAC7B;AACA,SAAO,CAAC,MAAM,IAAI;AACpB;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,aAAa,QAAQ,YAAY,MAAM,aAAa,OAAO;AAClE,QAAM,UAAU,gBAAgB,QAAQ,UAAU,aAAa;AAC/D,QAAM,cAAc,QAAQ;AAC5B,QAAM,WAAW,QAAQ;AACzB,MAAI,cAAc,GAAG;AACnB,UAAM,IAAI,MAAM,+DAA+D,cAAc;AAAA,EAC/F;AACA,MAAI,WAAW,GAAG;AAChB,UAAM,IAAI,MAAM,gDAAgD,UAAU;AAAA,EAC5E;AACA,SAAO,QAAQ,KAAK,OAAO;AAC3B,QAAM,WAAW,aAAa,IAAI,QAAQ,SAAS,CAAC,GAAG,EAAE,CAAC,IAAI;AAC9D,QAAM,SAAS,EAAE,QAAQ,SAAS;AAClC,QAAM,QAAQ,EAAE,YAAY,MAAM,WAAW;AAC7C,QAAM,MAAM,OAAO,UAAU,aAAa,QAAQ,KAAK;AACvD,SAAO,aAAa,IAAI,QAAQ,KAAK,CAAC,IAAI,IAAI,CAAC,IAAI;AACrD;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,UAAU,GAAG,GAAG;AACvB,MAAI,KAAK,gBAAgB,GAAG,KAAK,YAAY,mBAAmB;AAChE,MAAI,KAAK,gBAAgB,GAAG,KAAK,YAAY,mBAAmB;AAChE,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,UAAU,GAAG;AACpB,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU;AAC7C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,cAAc,IAAI,IAAI;AAC7B,QAAM,MAAM,gBAAgB,IAAI,MAAM,cAAc;AACpD,QAAM,MAAM,gBAAgB,IAAI,MAAM,cAAc;AACpD,SAAO,IAAI,SAAS,KAAK,IAAI,SAAS,GAAG,MAAM,+DAA+D,IAAI,YAAY,IAAI,OAAO;AACzI,QAAM,OAAO,QAAQ,KAAK,CAAC,IAAI,CAAC,CAAC;AACjC,QAAM,OAAO,QAAQ,KAAK,CAAC,GAAG,EAAE,CAAC;AACjC,SAAO,OAAO,MAAM,IAAI;AAC1B;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,KAAK,GAAG,UAAU,gBAAgB,GAAG;AAC5C,QAAM,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACxC,MAAI,GAAG,SAAS,GAAG;AACjB,UAAM,IAAI,MAAM,oDAAoD;AAAA,EACtE;AACA,QAAM,QAAQ,EAAE,UAAU,cAAc;AACxC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,QAAQ,KAAK;AAC9C;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,OAAO,GAAG,UAAU,gBAAgB,GAAG;AAC9C,SAAO,SAAS,WAAW,GAAG,MAAM,kDAAkD;AACtF,SAAO,IAAI,GAAG,CAAC,QAAQ,GAAG,aAAa;AACzC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,OAAO,GAAG,UAAU,gBAAgB,GAAG;AAC9C,SAAO,SAAS,WAAW,KAAK,SAAS,GAAG,WAAW,KAAK,SAAS,GAAG,WAAW,GAAG,MAAM,uDAAuD;AACnJ,SAAO,IAAI,GAAG,UAAU,aAAa;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,OAAO,GAAG,UAAU,gBAAgB,GAAG;AAC9C,SAAO,SAAS,WAAW,KAAK,SAAS,GAAG,WAAW,KAAK,SAAS,GAAG,WAAW,KAAK,SAAS,GAAG,WAAW,GAAG,MAAM,uDAAuD;AAC/K,SAAO,IAAI,GAAG,UAAU,aAAa;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,OAAO,GAAG,UAAU,gBAAgB,GAAG;AAC9C,SAAO,SAAS,WAAW,KAAK,SAAS,GAAG,WAAW,KAAK,SAAS,GAAG,WAAW,KAAK,SAAS,GAAG,WAAW,KAAK,SAAS,GAAG,WAAW,GAAG,MAAM,uDAAuD;AAC3M,SAAO,IAAI,GAAG,UAAU,aAAa;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,gBAAgB,GAAG,YAAY,UAAU;AAChD,QAAM,KAAK,gBAAgB,GAAG,KAAK,gBAAgB;AACnD,SAAO,GAAG,QAAQ,IAAI,WAAW,QAAQ,MAAM,cAAc,GAAG,sCAAsC,WAAW,QAAQ;AACzH,SAAO,SAAS,WAAW,WAAW,QAAQ,MAAM,qBAAqB,SAAS,wCAAwC,WAAW,QAAQ;AAC7I,SAAO,GAAG,MAAM,OAAO,CAAC,GAAG,GAAG,OAAO;AACnC,QAAI,KAAK,KAAK,MAAM,WAAW,QAAQ;AACrC,aAAO,MAAM,IAAI,SAAS,KAAK,GAAG,KAAK,SAAS,KAAK,GAAG,MAAM,WAAW,KAAK,OAAO;AAAA,IACvF;AACA,WAAO;AAAA,EACT,GAAG,IAAI,GAAG,MAAM,4BAA4B,GAAG,MAAM,MAAM,CAAC,mBAAmB,SAAS,SAAS,sCAAsC,WAAW,SAAS,GAAG;AAC9J,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,YAAY,SAAS;AACrC,SAAO,OAAO,UAAU,gBAAgB,QAAQ,KAAK;AACvD;AACA,IAAI,iBAAiB,GAAG,EAAE,gBAAgB,CAAC;AAG3C,SAAS,MAAM,QAAQ,aAAa,aAAa,MAAM,WAAWA,UAAS,iBAAiB;AAC1F,MAAI,aAAa,MAAM;AACrB,gBAAY,CAAC,GAAG,CAAC;AAAA,EACnB;AACA,MAAIA,YAAW,MAAM;AACnB,IAAAA,WAAU;AAAA,EACZ;AACA,MAAI,SAAS,GAAG;AACd,WAAO;AAAA,EACT;AACA,QAAM,KAAK,gBAAgB,QAAQ,KAAK,SAAS;AACjD,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,SAAO,+BAA+BA,UAAS,SAAS,GAAG,MAAM,qEAAqEA,2BAA0B,YAAY;AAC5K,QAAM,WAAW,kBAAkB,IAAI,OAAO,aAAaA,UAAS,WAAW,IAAI;AACnF,QAAM,WAAW,CAAC,SAAS,gBAAgB,SAAS,aAAa;AACjE,MAAI;AACJ,MAAI,SAAS,QAAQ;AACnB,kBAAc,6BAA6B,CAAC,SAAS,cAAc,SAAS,WAAW,GAAG,QAAQ;AAAA,EACpG,OAAO;AACL,kBAAc,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAAA,EAC/B;AACA,QAAM,gBAAgB,SAAS,OAAO,KAAK,SAAS,OAAO;AAC3D,QAAM,CAAC,iBAAiB,aAAa,IAAI,6BAA6B,CAAC,SAAS,UAAU,SAAS,OAAO,GAAG,UAAU,WAAW;AAClI,QAAM,eAAe,gBAAgB,OAAO;AAC5C,QAAM,aAAa,gBAAgB,MAAM,eAAe,KAAK,UAAU,eAAe;AACtF,QAAM,YAAY,gBAAgB,QAAQ,MAAM,QAAQ,YAAY,aAAaA,UAAS,cAAc,eAAe,IAAI,MAAM,QAAQ,YAAY,aAAaA,UAAS,cAAc,eAAe;AACxM,QAAM,IAAI,UAAU;AACpB,QAAM,MAAM,gBAAgB,IAAI,eAAe,GAAG,UAAU,aAAa;AACzE,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,SAAS,6BAA6B,YAAY,YAAY,aAAa;AACzE,QAAM,WAAW,YAAY,IAAI,CAAC,MAAM,EAAE,EAAE;AAC5C,QAAM,aAAa,YAAY,IAAI,CAAC,MAAM,EAAE,EAAE;AAC9C,QAAM,iBAAiB,WAAW,OAAO,UAAU,UAAU;AAC7D,QAAM,cAAc,WAAW,IAAI,CAAC,GAAG,QAAQ,IAAI,eAAe,MAAM,KAAK,CAAC;AAC9E,QAAM,SAAS,WAAW,IAAI,CAAC,IAAI,OAAO,KAAK,YAAY,GAAG;AAC9D,QAAM,WAAW,WAAW,IAAI,CAAC,GAAG,OAAO,CAAC,SAAS,KAAK,OAAO,GAAG,CAAC;AACrE,QAAM,QAAQ,WAAW,IAAI,CAAC,GAAG,OAAO,CAAC,GAAG,YAAY,GAAG,CAAC;AAC5D,SAAO,CAAC,UAAU,KAAK;AACzB;AACA,SAAS,6BAA6B,aAAa,UAAU;AAC3D,QAAM,qBAAqB,YAAY,IAAI,CAAC,IAAI,OAAO;AACrD,WAAO,MAAM,KAAK,MAAM,SAAS,MAAM;AAAA,EACzC,CAAC;AACD,QAAM,gBAAgB,mBAAmB,IAAI,CAAC,OAAO,KAAK,CAAC;AAC3D,QAAM,gBAAgB,cAAc,IAAI,CAAC,OAAO,KAAK,MAAM,KAAK,CAAC,CAAC;AAClE,QAAM,cAAc,cAAc,IAAI,CAAC,IAAI,OAAO,KAAK,cAAc,GAAG;AACxE,SAAO,cAAc,IAAI,CAAC,GAAG,OAAO;AAClC,WAAO,CAAC,cAAc,KAAK,YAAY,GAAG;AAAA,EAC5C,CAAC;AACH;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,OAAO,GAAGU,QAAO;AACxB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,gBAAgBA,QAAO,SAAS,OAAO;AACtD,QAAM,SAAS,EAAE,GAAG,IAAI,OAAO,OAAO;AACtC,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,GAAG,OAAO,MAAM,WAAW,OAAO;AAC/C,MAAI,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACvC,MAAI,GAAG,UAAU,QAAQ;AACvB,SAAK,KAAK,IAAI,OAAO;AAAA,EACvB;AACA,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,SAAS;AAC/B,SAAO,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC7C;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,MAAM,OAAO,cAAc,OAAO;AACzC,QAAMtB,QAAO,cAAc,KAAK;AAChC,MAAI,SAAS;AACb,MAAI,SAAS,QAAQ,UAAU,WAAW;AACxC,aAAS,IAAI,aAAaA,KAAI;AAAA,EAChC,WAAW,UAAU,SAAS;AAC5B,aAAS,IAAI,WAAWA,KAAI;AAAA,EAC9B,WAAW,UAAU,QAAQ;AAC3B,aAAS,IAAI,WAAWA,KAAI;AAAA,EAC9B,OAAO;AACL,UAAM,IAAI,MAAM,qBAAqB,OAAO;AAAA,EAC9C;AACA,WAAS,KAAK,GAAG,KAAKA,OAAM,MAAM;AAChC,WAAO,MAAM,aAAa;AAAA,EAC5B;AACA,SAAO,OAAO,WAAW,QAAQ,OAAO,KAAK;AAC/C;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,IAAI,aAAa,QAAQ,oBAAoB,CAAC;AAC9C,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,OAAO,cAAc,OAAO,WAAW,MAAM;AACvD,SAAK,OAAO;AACZ,SAAK,SAAS;AACd,SAAK,QAAQ;AACb,SAAK,UAAU;AACf,SAAK,YAAY;AACjB,QAAI,KAAK,WAAW;AAClB,WAAK,QAAQ,KAAK,OAAO,KAAK,SAAS;AACvC,WAAK,QAAQ,KAAK,OAAO,KAAK,SAAS;AAAA,IACzC;AACA,UAAM,YAAY,OAAO,OAAO,KAAK,OAAO;AAC5C,SAAK,SAAS,WAAW,KAAK,UAAU,SAAS,CAAC;AAAA,EACpD;AAAA,EACA,YAAY;AACV,QAAI,CAAC,MAAM,KAAK,OAAO,GAAG;AACxB,YAAM,QAAQ,KAAK;AACnB,WAAK,UAAU;AACf,aAAO;AAAA,IACT;AACA,QAAI,SAAS;AACb,QAAI,UAAU;AACd,WAAO,CAAC,SAAS;AACf,UAAI,IAAI,IAAI;AACZ,SAAG;AACD,aAAK,IAAI,KAAK,OAAO,IAAI;AACzB,aAAK,IAAI,KAAK,OAAO,IAAI;AACzB,aAAK,KAAK,KAAK,KAAK;AAAA,MACtB,SAAS,MAAM,KAAK,OAAO;AAC3B,YAAM,OAAO,KAAK,KAAK,KAAK,KAAK,IAAI,EAAE,IAAI,EAAE;AAC7C,gBAAU,KAAK,OAAO,KAAK,SAAS,KAAK;AACzC,gBAAU,KAAK,OAAO,KAAK,SAAS,KAAK;AACzC,UAAI,CAAC,KAAK,aAAa,KAAK,iBAAiB,OAAO,GAAG;AACrD,kBAAU;AAAA,MACZ;AAAA,IACF;AACA,QAAI,CAAC,KAAK,aAAa,KAAK,iBAAiB,OAAO,GAAG;AACrD,WAAK,UAAU,KAAK,aAAa,OAAO;AAAA,IAC1C;AACA,WAAO,KAAK,aAAa,OAAO;AAAA,EAClC;AAAA,EACA,aAAa,OAAO;AAClB,QAAI,KAAK,SAAS,QAAQ,KAAK,UAAU,WAAW;AAClD,aAAO;AAAA,IACT;AACA,WAAO,KAAK,MAAM,KAAK;AAAA,EACzB;AAAA,EACA,iBAAiB,OAAO;AACtB,WAAO,SAAS,KAAK,SAAS,SAAS,KAAK;AAAA,EAC9C;AACF;AACA,IAAI,YAAY,MAAM;AAAA,EACpB,YAAYsB,QAAO,MAAM,OAAO,MAAM;AACpC,SAAK,QAAQA;AACb,SAAK,OAAO,IAAI;AAChB,SAAK,QAAQ;AACb,UAAM,YAAY,OAAO,OAAO,KAAK,OAAO;AAC5C,SAAK,QAAQ,WAAW,KAAK,UAAU,SAAS,CAAC;AACjD,SAAK,QAAQ,IAAI,YAAY,GAAG,GAAG,OAAO,OAAO,KAAK,MAAM,CAAC;AAC7D,QAAIA,SAAQ,GAAG;AACb,WAAK,IAAIA,SAAQ,IAAI;AAAA,IACvB,OAAO;AACL,WAAK,IAAIA,SAAQ,IAAI;AAAA,IACvB;AACA,SAAK,IAAI,IAAI,KAAK,KAAK,IAAI,KAAK,CAAC;AAAA,EACnC;AAAA,EACA,YAAY;AACV,QAAI,IAAI,IAAI,IAAI,GAAG,GAAG;AACtB,WAAO,MAAM;AACX,SAAG;AACD,YAAI,KAAK,MAAM,UAAU;AACzB,YAAI,IAAI,KAAK,IAAI;AAAA,MACnB,SAAS,KAAK;AACd,WAAK,IAAI;AACT,WAAK,IAAI;AACT,WAAK,IAAI,QAAQ,KAAK;AACtB,WAAK,MAAM,KAAK,KAAK,KAAK,IAAI,IAAI,KAAK,IAAI,CAAC;AAC5C,UAAI,KAAK,MAAM;AACf,UAAI,IAAI,MAAM,KAAK,IAAI,CAAC,IAAI,IAAI;AAC9B;AAAA,MACF;AAAA,IACF;AACA,QAAI,IAAI,KAAK,OAAO,KAAK,IAAI;AAC7B,QAAI,KAAK,QAAQ,GAAG;AAClB,WAAK,KAAK,IAAI,KAAK,MAAM,GAAG,IAAI,KAAK,KAAK;AAAA,IAC5C;AACA,WAAO,KAAK,aAAa,CAAC;AAAA,EAC5B;AAAA,EACA,aAAa,OAAO;AAClB,QAAI,KAAK,UAAU,WAAW;AAC5B,aAAO;AAAA,IACT;AACA,WAAO,KAAK,MAAM,KAAK;AAAA,EACzB;AACF;AACA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,OAAO,GAAG,OAAO,GAAG,OAAO,MAAM;AAC3C,SAAK,iBAAiB,MAAM,KAAK,SAAS,QAAQ,KAAK,UAAU;AACjE,SAAK,MAAM;AACX,SAAK,QAAQ,OAAO;AACpB,SAAK,QAAQ;AACb,QAAI,QAAQ,MAAM;AAChB,aAAO,KAAK,OAAO;AAAA,IACrB;AACA,QAAI,OAAO,SAAS,UAAU;AAC5B,aAAO,KAAK,SAAS;AAAA,IACvB;AACA,QAAI,CAAC,KAAK,eAAe,KAAK,KAAK,SAAS,GAAG;AAC7C,YAAM,IAAI,MAAM,0BAA0B,UAAU,kCAAkC;AAAA,IACxF;AACA,SAAK,SAAS,WAAW,KAAK,IAAI;AAAA,EACpC;AAAA,EACA,aAAa,OAAO;AAClB,QAAI,KAAK,eAAe,GAAG;AACzB,aAAO;AAAA,IACT;AACA,WAAO,KAAK,MAAM,KAAK;AAAA,EACzB;AAAA,EACA,YAAY;AACV,WAAO,KAAK,aAAa,KAAK,MAAM,KAAK,QAAQ,KAAK,OAAO,CAAC;AAAA,EAChE;AACF;AAGA,SAAS,aAAa,OAAOA,QAAO,OAAO,GAAG,QAAQ,WAAW,MAAM;AACrE,MAAI,QAAQ,MAAM;AAChB,WAAO;AAAA,EACT;AACA,MAAI,SAAS,MAAM;AACjB,YAAQ;AAAA,EACV;AACA,MAAI,UAAU,aAAa,UAAU,SAAS;AAC5C,UAAM,IAAI,MAAM,yBAAyB,OAAO;AAAA,EAClD;AACA,QAAM,SAAS,IAAI,UAAUA,QAAO,MAAM,OAAO,IAAI;AACrD,QAAM,MAAM,OAAO,OAAO,KAAK;AAC/B,WAAS,KAAK,GAAG,KAAK,IAAI,OAAO,QAAQ,MAAM;AAC7C,QAAI,OAAO,MAAM,OAAO,UAAU;AAAA,EACpC;AACA,SAAO,IAAI,SAAS;AACtB;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,cAAc,OAAO,QAAQ,GAAG,SAAS,GAAG,OAAO,MAAM;AAChE,MAAI,SAAS,QAAQ,UAAU,QAAQ;AACrC,UAAM,IAAI,MAAM,yBAAyB,OAAO;AAAA,EAClD;AACA,QAAM,YAAY,IAAI,YAAY,OAAO,QAAQ,OAAO,OAAO,IAAI;AACnE,QAAM,MAAM,OAAO,OAAO,KAAK;AAC/B,WAAS,KAAK,GAAG,KAAK,IAAI,OAAO,QAAQ,MAAM;AAC7C,QAAI,OAAO,MAAM,UAAU,UAAU;AAAA,EACvC;AACA,SAAO,IAAI,SAAS;AACtB;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,sBAAsB,OAAO,OAAO,MAAM;AACjD,MAAI,SAAS,QAAQ,UAAU,QAAQ;AACrC,UAAM,IAAI,MAAM,yBAAyB,OAAO;AAAA,EAClD;AACA,SAAO,aAAa,OAAO,GAAG,GAAG,OAAO,IAAI;AAC9C;AACA,IAAI,uBAAuB,GAAG,EAAE,sBAAsB,CAAC;AAGvD,SAAS,eAAe,OAAO,SAAS,GAAG,SAAS,GAAG,QAAQ,WAAW,MAAM;AAC9E,QAAM,MAAM,OAAO,OAAO,KAAK;AAC/B,QAAM,SAAS,IAAI,cAAc,QAAQ,QAAQ,MAAM,IAAI;AAC3D,WAAS,KAAK,GAAG,KAAK,IAAI,OAAO,QAAQ,MAAM;AAC7C,QAAI,OAAO,MAAM,OAAO,UAAU;AAAA,EACpC;AACA,SAAO,IAAI,SAAS;AACtB;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,MAAM,OAAO,MAAM,QAAQ,GAAG,QAAQ,WAAW;AACxD,MAAI,UAAU,GAAG;AACf,UAAM,IAAI,MAAM,4BAA4B;AAAA,EAC9C;AACA,QAAM,QAAQ,EAAE,OAAO,MAAM,MAAM,OAAO,MAAM;AAChD,SAAO,OAAO,UAAU,OAAO,CAAC,GAAG,KAAK;AAC1C;AAGA,SAAS,YAAY,GAAG;AACtB,QAAM,KAAK,gBAAgB,GAAG,KAAK,YAAY;AAC/C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,YAAY,MAAM;AAC5C;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,SAAS,GAAG,MAAM;AACzB,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,KAAK;AAC3B,SAAO,OAAO,UAAU,SAAS,QAAQ,KAAK;AAChD;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,WAAW,GAAG;AACrB,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,qDAAqD,GAAG,OAAO;AAC3F,SAAO,QAAQ,IAAI,CAAC;AACtB;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,WAAW,GAAG,MAAM;AAC3B,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,qDAAqD,GAAG,OAAO;AAC3F,SAAO,QAAQ,IAAI,IAAI;AACzB;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,WAAW,GAAG,MAAM;AAC3B,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,qDAAqD,GAAG,OAAO;AAC3F,SAAO,QAAQ,IAAI,IAAI;AACzB;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,WAAW,GAAG,MAAM;AAC3B,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,qDAAqD,GAAG,OAAO;AAC3F,SAAO,QAAQ,IAAI,IAAI;AACzB;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,SAAS,GAAG,EAAE,OAAO,CAAC;AAG1B,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS,SAAS;AACrD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,iBAAiB,GAAG,iBAAiB,iBAAiBV,UAAS,MAAM,WAAW,CAAC,GAAG,CAAC,GAAG,aAAa,QAAQ;AACpH,QAAM,KAAK,gBAAgB,GAAG,KAAK,iBAAiB;AACpD,QAAM,mBAAmB,gBAAgB,iBAAiB,mBAAmB,iBAAiB;AAC9F,QAAM,mBAAmB,gBAAgB,iBAAiB,mBAAmB,iBAAiB;AAC9F,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,MAAI,eAAe,QAAQ;AACzB,UAAM,IAAI,MAAM,oFAAoF;AAAA,EACtG;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,gEAAgE,IAAI,OAAO;AACxG,SAAO,iBAAiB,SAAS,GAAG,MAAM,2EAA2E,iBAAiB,OAAO;AAC7I,SAAO,iBAAiB,SAAS,GAAG,MAAM,2EAA2E,iBAAiB,OAAO;AAC7I,SAAO,iBAAiB,MAAM,OAAO,GAAG,MAAM,yFAAyF,iBAAiB,MAAM,KAAK;AACnK,SAAO,iBAAiB,MAAM,OAAO,GAAG,MAAM,yFAAyF,iBAAiB,MAAM,KAAK;AACnK,QAAM,aAAa,iBAAiB,MAAM;AAC1C,QAAM,oBAAoB,iBAAiB,MAAM;AACjD,SAAO,iBAAiB,MAAM,OAAO,aAAa,mBAAmB,MAAM,6EAA6E,aAAa,8BAA8B,iBAAiB,MAAM,KAAK;AAC/N,QAAM,YAAY,gBAAgB,KAAK,kBAAkBA,UAAS,MAAM,YAAY,QAAQ;AAC5F,QAAM,kBAAkB;AACxB,QAAM,MAAM,OAAO,WAAW,kBAAkB,iBAAiB,SAAS,UAAU;AACpF,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,kBAAkB,GAAG,EAAE,iBAAiB,CAAC;AAG7C,eAAe,gBAAgB,GAAG,GAAG;AACnC,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,SAAO,GAAG,UAAU,GAAG,OAAO,MAAM,kDAAkD,GAAG,iBAAiB,GAAG,SAAS;AACtH,SAAO,GAAG,SAAS,GAAG,MAAM,qCAAqC,GAAG,SAAS;AAC7E,SAAO,GAAG,SAAS,GAAG,MAAM,qCAAqC,GAAG,SAAS;AAC7E,QAAM,QAAQ,MAAM,GAAG,KAAK;AAC5B,QAAM,QAAQ,MAAM,GAAG,KAAK;AAC5B,QAAM,OAAO,IAAI,IAAI,KAAK;AAC1B,MAAIQ,cAAa;AACjB,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,QAAI,CAAC,KAAK,IAAI,MAAM,GAAG,GAAG;AACxB,MAAAA;AAAA,IACF;AAAA,EACF;AACA,QAAM,UAAU,IAAI,aAAa,CAACA,WAAU,GAAG,GAAG,KAAK;AACvD,QAAM,UAAU,IAAI,aAAa,CAACA,WAAU,GAAG,OAAO;AACtD,WAAS,KAAK,GAAG,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AAChD,QAAI,CAAC,KAAK,IAAI,MAAM,GAAG,GAAG;AACxB,cAAQ,OAAO,MAAM,MAAM;AAC3B,cAAQ,OAAO,MAAM;AACrB;AAAA,IACF;AAAA,EACF;AACA,SAAO,CAAC,QAAQ,SAAS,GAAG,QAAQ,SAAS,CAAC;AAChD;AACA,IAAI,iBAAiB;AAGrB,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO,SAAS;AACnD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,SAAS,GAAG,OAAOpB,OAAM;AAChC,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,mDAAmD,GAAG,aAAa;AAC/F,SAAO,MAAM,IAAI,CAAC,KAAK,GAAG,CAACA,KAAI,CAAC;AAClC;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,SAAS,GAAG,OAAOA,OAAM;AAChC,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,mDAAmD,GAAG,aAAa;AAC/F,SAAO,MAAM,IAAI,OAAOA,KAAI;AAC9B;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,SAAS,GAAG,OAAOA,OAAM;AAChC,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,mDAAmD,GAAG,aAAa;AAC/F,SAAO,MAAM,IAAI,OAAOA,KAAI;AAC9B;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,SAAS,GAAG,OAAOA,OAAM;AAChC,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,mDAAmD,GAAG,aAAa;AAC/F,SAAO,MAAM,IAAI,OAAOA,KAAI;AAC9B;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,SAAS,QAAQ,MAAM,IAAI;AAClC,QAAM,UAAU,gBAAgB,QAAQ,UAAU,WAAW,SAAS;AACtE,MAAI,QAAQ,IAAI;AACd,UAAM,QAAQ,OAAO;AAAA,EACvB;AACA,MAAI,QAAQ,QAAQ,OAAO,GAAG;AAC5B,UAAM,MAAM,4EAA4E,QAAQ,oBAAoB,KAAK;AAAA,EAC3H;AACA,QAAM,SAAS,EAAE,QAAQ,QAAQ;AACjC,QAAM,QAAQ,EAAE,IAAI;AACpB,SAAO,OAAO,UAAU,SAAS,QAAQ,KAAK;AAChD;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,KAAK,QAAQ;AACpB,SAAO,OAAO,UAAU,aAAa,MAAM,6DAA6D,OAAO,QAAQ;AACvH,QAAM,SAAS,EAAE,OAAO,OAAO;AAC/B,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,MAAM,QAAQ;AACrB,SAAO,OAAO,UAAU,aAAa,MAAM,8DAA8D,OAAO,QAAQ;AACxH,QAAM,SAAS,EAAE,OAAO,OAAO;AAC/B,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,OAAO,QAAQ;AACtB,QAAM,qBAAqB,OAAO,MAAM,OAAO,MAAM,SAAS;AAC9D,QAAM,QAAQ,OAAO,OAAO;AAC5B,MAAI;AACJ,MAAI,sBAAsB,GAAG;AAC3B,UAAM,eAAe,QAAQ,QAAQ,CAAC,OAAO,kBAAkB,CAAC;AAChE,UAAM,KAAK,YAAY;AAAA,EACzB,OAAO;AACL,UAAM,cAAc,CAAC,OAAO,KAAK,qBAAqB,EAAE;AACxD,UAAM,YAAY,QAAQ,KAAK,MAAM,GAAG,CAAC,OAAO,kBAAkB,CAAC;AACnE,UAAM,YAAY,QAAQ,KAAK,MAAM,GAAG,CAAC,OAAO,kBAAkB,CAAC;AACnE,UAAM,gBAAgB,QAAQ,MAAM,WAAW,CAAC,GAAG,CAAC,GAAG,CAAC,OAAO,qBAAqB,CAAC,CAAC,GAAG,CAAC;AAC1F,UAAM,gBAAgB,IAAI,QAAQ,MAAM,WAAW,CAAC,GAAG,CAAC,GAAG,CAAC,OAAO,qBAAqB,CAAC,CAAC,GAAG,CAAC,GAAG,OAAO,EAAE,CAAC;AAC3G,UAAM,KAAK,OAAO,CAAC,WAAW,aAAa,GAAG,CAAC;AAC/C,UAAM,KAAK,OAAO,CAAC,WAAW,aAAa,GAAG,CAAC;AAC/C,UAAM,eAAe,QAAQ,QAAQ,IAAI,EAAE,GAAG,CAAC,YAAY,IAAI,YAAY,EAAE,CAAC;AAC9E,UAAM,KAAK,YAAY;AAAA,EACzB;AACA,QAAM,KAAK,GAAG;AACd,MAAI,OAAO,SAAS,KAAK,OAAO,MAAM,OAAO,GAAG;AAC9C,UAAM,OAAO;AACb,UAAM,SAAS,OAAO,MAAM;AAC5B,UAAM,QAAQ,KAAK,CAAC,QAAQ,IAAI,MAAM,KAAK,QAAQ,IAAI,MAAM,EAAE,CAAC;AAChE,SAAK,QAAQ;AAAA,EACf;AACA,SAAO;AACT;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,OAAO,GAAG,iBAAiB,OAAO,GAAG;AAC5C,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,OAAO,EAAE,iBAAiB,KAAK;AACrC,SAAO,OAAO,UAAU,QAAQ,QAAQ,IAAI;AAC9C;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,QAAQ,WAAW;AAChC,SAAO,OAAO,UAAU,WAAW,MAAM,mDAAmD,OAAO,OAAO;AAC1G,MAAI,qBAAqB,OAAO,MAAM,OAAO,MAAM,SAAS;AAC5D,QAAM,QAAQ,OAAO,OAAO;AAC5B,MAAI;AACJ,MAAI,aAAa,QAAQ,YAAY,oBAAoB;AACvD,UAAM,QAAQ,OAAO,MAAM,IAAI,CAAC,MAAM,CAAC;AACvC,UAAMA,QAAO,OAAO,MAAM,IAAI,CAAC,MAAM,CAAC;AACtC,IAAAA,MAAK,OAAO,MAAM,SAAS,KAAK;AAChC,oBAAgB,MAAM,QAAQ,OAAOA,KAAI;AACzC,yBAAqB;AAAA,EACvB,WAAW,aAAa,QAAQ,YAAY,oBAAoB;AAC9D,UAAM,aAAa,OAAO,MAAM,IAAI,CAAC,MAAM,CAAC;AAC5C,eAAW,OAAO,MAAM,SAAS,KAAK,YAAY;AAClD,oBAAgB,OAAO,CAAC,QAAQ,MAAM,UAAU,CAAC,GAAG,OAAO,MAAM,SAAS,CAAC;AAC3E,yBAAqB;AAAA,EACvB,OAAO;AACL,oBAAgB;AAAA,EAClB;AACA,QAAM,aAAa,UAAU,aAAa;AAC1C,QAAM,eAAe,QAAQ,QAAQ,eAAe,UAAU,GAAG,CAAC,OAAO,kBAAkB,CAAC;AAC5F,QAAM,MAAM,IAAI,YAAY;AAC5B,QAAMuB,QAAO,KAAK,MAAM,qBAAqB,CAAC,IAAI;AAClD,QAAM,aAAa,KAAK,GAAG;AAC3B,QAAM,aAAa,KAAK,GAAG;AAC3B,QAAM,uBAAuB,MAAM,YAAY,CAACA,OAAM,qBAAqBA,KAAI,GAAG,WAAW,MAAM,SAAS,CAAC;AAC7G,QAAM,uBAAuB,MAAM,YAAY,CAACA,OAAM,qBAAqBA,KAAI,GAAG,WAAW,MAAM,SAAS,CAAC;AAC7G,QAAM,cAAc,cAAc,MAAM,MAAM;AAC9C,cAAY,cAAc,MAAM,SAAS,KAAKA;AAC9C,SAAO,QAAQ,QAAQ,qBAAqB,IAAI,qBAAqB,EAAE,GAAG,WAAW;AACvF;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,mBAAmB,GAAG,GAAG;AAChC,MAAI,KAAK,gBAAgB,GAAG,KAAK,mBAAmB;AACpD,MAAI,KAAK,gBAAgB,GAAG,KAAK,mBAAmB;AACpD,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,QAAM,QAAQ,CAAC;AACf,SAAO,OAAO,UAAU,mBAAmB,QAAQ,KAAK;AAC1D;AACA,IAAI,oBAAoB,GAAG,EAAE,mBAAmB,CAAC;AAGjD,SAAS,SAAS,GAAG,MAAM;AACzB,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW,mBAAmB;AACjE,SAAO,QAAQ,IAAI,aAAa,GAAG,OAAO,IAAI,EAAE,QAAQ;AAC1D;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,OAAO,SAAS,OAAO,GAAG;AACjC,QAAM,WAAW,qBAAqB,SAAS,WAAW,SAAS,mBAAmB;AACtF,SAAO,SAAS,UAAU,GAAG,MAAM,sCAAsC;AACzE,MAAI,SAAS,SAAS,GAAG;AACvB,WAAO,QAAQ,SAAS,GAAG,MAAM,MAAM,oCAAoC;AAAA,EAC7E;AACA,QAAM,SAAS;AACf,QAAM,QAAQ,EAAE,KAAK;AACrB,SAAO,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC7C;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,GAAGD,SAAQ,GAAG;AAC3B,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,OAAAA,OAAM;AACtB,SAAO,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC7C;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,cAAc,GAAG,OAAO,KAAKV,UAAS,YAAY,GAAG,UAAU,GAAG,eAAe,GAAG,cAAc,GAAG,iBAAiB,GAAG;AAChI,QAAM,KAAK,gBAAgB,GAAG,KAAK,gBAAgB,mBAAmB;AACtE,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ;AAAA,IACZ;AAAA,IACA;AAAA,IACA,SAAAA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACA,SAAO,OAAO,UAAU,cAAc,QAAQ,KAAK;AACrD;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO,SAAS;AACnD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,SAAS,QAAQ,OAAO;AAC/B,gBAAc,MAAM;AACpB,QAAM,gBAAgB,WAAW,QAAQ,KAAK;AAC9C,MAAI,cAAc,WAAW,GAAG;AAC9B,UAAM,IAAI,MAAM,oDAAoD;AAAA,EACtE;AACA,QAAM,QAAQ;AACd,SAAO,WAAW,QAAQ,OAAO,eAAe,KAAK;AACvD;AAGA,SAAS,SAAS,QAAQ,OAAO,OAAO;AACtC,gBAAc,MAAM;AACpB,MAAI,SAAS,QAAQ,MAAM,WAAW,GAAG;AACvC,UAAM,IAAI,MAAM,+CAA+C;AAAA,EACjE;AACA,QAAM,gBAAgB,WAAW,QAAQ,KAAK;AAC9C,MAAI,cAAc,WAAW,KAAK,cAAc,WAAW,GAAG;AAC5D,UAAM,IAAI,MAAM,gEAAgE;AAAA,EAClF;AACA,MAAI,cAAc,WAAW,KAAK,SAAS,MAAM;AAC/C,UAAM,IAAI,MAAM,8EAA8E;AAAA,EAChG;AACA,SAAO,WAAW,QAAQ,OAAO,eAAe,KAAK;AACvD;AAGA,SAAS,SAAS,QAAQ,OAAO,OAAO;AACtC,gBAAc,MAAM;AACpB,MAAI,SAAS,QAAQ,MAAM,WAAW,GAAG;AACvC,UAAM,IAAI,MAAM,gDAAgD;AAAA,EAClE;AACA,QAAM,gBAAgB,WAAW,QAAQ,KAAK;AAC9C,MAAI,cAAc,WAAW,KAAK,cAAc,WAAW,GAAG;AAC5D,UAAM,IAAI,MAAM,oEAAoE;AAAA,EACtF;AACA,MAAI,cAAc,WAAW,KAAK,SAAS,MAAM;AAC/C,UAAM,IAAI,MAAM,yEAAyE;AAAA,EAC3F;AACA,SAAO,WAAW,QAAQ,OAAO,eAAe,KAAK;AACvD;AAGA,SAAS,SAAS,QAAQ,OAAO,OAAO;AACtC,gBAAc,MAAM;AACpB,MAAI,SAAS,QAAQ,MAAM,WAAW,GAAG;AACvC,UAAM,IAAI,MAAM,gDAAgD;AAAA,EAClE;AACA,QAAM,gBAAgB,WAAW,QAAQ,KAAK;AAC9C,MAAI,cAAc,WAAW,KAAK,cAAc,WAAW,GAAG;AAC5D,UAAM,IAAI,MAAM,sEAAsE;AAAA,EACxF;AACA,MAAI,cAAc,WAAW,KAAK,SAAS,MAAM;AAC/C,UAAM,IAAI,MAAM,yEAAyE;AAAA,EAC3F;AACA,SAAO,WAAW,QAAQ,OAAO,eAAe,KAAK;AACvD;AAGA,SAAS,SAAS,QAAQ,OAAO,OAAO;AACtC,gBAAc,MAAM;AACpB,MAAI,SAAS,QAAQ,MAAM,WAAW,GAAG;AACvC,UAAM,IAAI,MAAM,+CAA+C;AAAA,EACjE;AACA,QAAM,gBAAgB,WAAW,QAAQ,KAAK;AAC9C,MAAI,cAAc,WAAW,KAAK,cAAc,WAAW,GAAG;AAC5D,UAAM,IAAI,MAAM,wEAAwE;AAAA,EAC1F;AACA,MAAI,cAAc,WAAW,KAAK,SAAS,MAAM;AAC/C,UAAM,IAAI,MAAM,yEAAyE;AAAA,EAC3F;AACA,UAAQ,SAAS;AACjB,SAAO,WAAW,QAAQ,OAAO,eAAe,KAAK;AACvD;AAGA,SAAS,MAAM,GAAG,IAAI,GAAG,SAAS,MAAM;AACtC,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,MAAI,GAAG,SAAS,GAAG;AACjB,UAAM,IAAI,MAAM,oDAAoD;AAAA,EACtE;AACA,QAAM,UAAU,GAAG,MAAM,GAAG,MAAM,SAAS;AAC3C,MAAI,IAAI,GAAG;AACT,UAAM,IAAI,MAAM,6CAA6C,GAAG;AAAA,EAClE;AACA,MAAI,IAAI,SAAS;AACf,UAAM,IAAI,MAAM,uDAAuD,oBAAoB,GAAG;AAAA,EAChG;AACA,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,GAAG,OAAO;AAC1B,QAAM,CAAC,QAAQ,OAAO,IAAI,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC9D,SAAO,EAAE,QAAQ,QAAQ;AAC3B;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,iBAAiB,OAAO,QAAQ,GAAG,SAAS,GAAG,OAAO,MAAM;AACnE,MAAI,SAAS,QAAQ,UAAU,QAAQ;AACrC,UAAM,IAAI,MAAM,mCAAmC;AAAA,EACrD;AACA,QAAM,YAAY,IAAI,YAAY,OAAO,QAAQ,OAAO,MAAM,IAAI;AAClE,QAAM,MAAM,OAAO,OAAO,KAAK;AAC/B,WAAS,KAAK,GAAG,KAAK,IAAI,OAAO,QAAQ,MAAM;AAC7C,QAAI,OAAO,MAAM,UAAU,UAAU;AAAA,EACvC;AACA,SAAO,IAAI,SAAS;AACtB;AACA,IAAI,kBAAkB,GAAG,EAAE,iBAAiB,CAAC;AAG7C,SAAS,QAAQ,GAAG,OAAO,GAAG;AAC5B,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU,mBAAmB;AAChE,SAAO,GAAG,OAAO,GAAG,MAAM,sCAAsC;AAChE,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,KAAK;AACrB,QAAM,CAAC,QAAQ,OAAO,IAAI,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAChE,SAAO,EAAE,QAAQ,QAAQ;AAC3B;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,oBAAoB,GAAG,YAAY,aAAa;AACvD,QAAM,KAAK,gBAAgB,GAAG,KAAK,oBAAoB;AACvD,QAAM,cAAc,gBAAgB,YAAY,cAAc,sBAAsB,OAAO;AAC3F,SAAO,MAAM,WAAW,GAAG,MAAM,kCAAkC;AACnE,QAAM,SAAS,EAAE,GAAG,IAAI,YAAY,YAAY;AAChD,QAAM,QAAQ,EAAE,YAAY;AAC5B,SAAO,OAAO,UAAU,oBAAoB,QAAQ,KAAK;AAC3D;AACA,IAAI,qBAAqB,GAAG,EAAE,oBAAoB,CAAC;AAGnD,SAAS,SAAS,GAAG,OAAO,GAAG;AAC7B,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW,mBAAmB;AACjE,SAAO,QAAQ,CAAC,GAAG,MAAM,UAAU,OAAO,GAAG,MAAM,QAAQ,MAAM,UAAU,oBAAoB,GAAG,MAAM,WAAW,GAAG,MAAM,SAAS;AACrI,QAAM,SAAS,EAAE,OAAO,GAAG;AAC3B,QAAM,QAAQ,EAAE,KAAK;AACrB,SAAO,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAC/C;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,WAAW,gBAAgB,QAAQ;AAC1C,SAAO,aAAa,gBAAgB,QAAQ,OAAO;AACrD;AAGA,SAAS,SAAS,cAAc,YAAY,MAAM,MAAM,OAAO;AAC7D,SAAO,OAAO,aAAa,cAAc,WAAW,MAAM,KAAK;AACjE;AAGA,SAAS,UAAU,WAAW,UAAU;AACtC,QAAM,UAAU,CAAC;AACjB,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,QAAI,SAAS,KAAK;AAChB,cAAQ,KAAK,EAAE;AAAA,IACjB;AAAA,EACF;AACA,QAAM,WAAW,OAAO,WAAW,OAAO;AAC1C,QAAM,MAAM,OAAO,CAAC,QAAQ,QAAQ,UAAU,MAAM,GAAG,OAAO;AAC9D,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,UAAM,MAAM,SAAS,WAAW,QAAQ,GAAG;AAC3C,UAAM,SAAS,KAAK,UAAU;AAC9B,QAAI,OAAO,IAAI,KAAK,MAAM;AAAA,EAC5B;AACA,SAAO,IAAI,SAAS;AACtB;AAGA,eAAe,YAAY,WAAW;AACpC,QAAM,aAAa,gBAAgB,WAAW,aAAa,cAAc,MAAM;AAC/E,QAAM,OAAO,MAAM,WAAW,KAAK;AACnC,QAAM,MAAM,UAAU,WAAW,OAAO,IAAI;AAC5C,MAAI,cAAc,YAAY;AAC5B,eAAW,QAAQ;AAAA,EACrB;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAGjB,eAAe,kBAAkB,SAASP,OAAM,MAAM;AACpD,QAAM,UAAU,gBAAgB,SAAS,UAAU,UAAU;AAC7D,QAAM,QAAQ,gBAAgBA,OAAM,QAAQ,YAAY,MAAM;AAC9D,QAAM,WAAW,QAAQ,OAAO,IAAI;AACpC,QAAM,UAAU,MAAM;AACtB,QAAM,cAAc,QAAQ;AAC5B,SAAO,UAAU,GAAG,MAAM,uBAAuB;AACjD,oBAAkB,YAAY,MAAM,UAAU,WAAW,OAAO,GAAG,MAAM,OAAO,mEAAmE;AACnJ,MAAI,cAAc;AAClB,WAAS,KAAK,UAAU,KAAK,WAAW,SAAS,MAAM;AACrD,mBAAe,YAAY;AAAA,EAC7B;AACA,QAAM,oBAAoB,YAAY,MAAM,GAAG,QAAQ,EAAE,OAAO,CAAC,WAAW,GAAG,YAAY,MAAM,WAAW,OAAO,CAAC;AACpH,QAAM,iBAAiB,QAAQ,SAAS,iBAAiB;AACzD,QAAM,eAAe,QAAQ,OAAO,CAAC,EAAE,CAAC;AACxC,QAAM,oBAAoB,MAAM,WAAW,YAAY;AACvD,QAAM,UAAU,QAAQ,mBAAmB,CAAC,CAAC,CAAC;AAC9C,QAAM,MAAM,OAAO,gBAAgB,SAAS,QAAQ;AACpD,MAAI,YAAY,SAAS;AACvB,YAAQ,QAAQ;AAAA,EAClB;AACA,MAAIA,UAAS,OAAO;AAClB,UAAM,QAAQ;AAAA,EAChB;AACA,UAAQ,QAAQ;AAChB,iBAAe,QAAQ;AACvB,eAAa,QAAQ;AACrB,oBAAkB,QAAQ;AAC1B,SAAO;AACT;AACA,IAAI,mBAAmB;AAGvB,SAAS,eAAe,GAAG,GAAG,OAAO,OAAO,aAAa,MAAM;AAC7D,QAAM,KAAK,gBAAgB,GAAG,KAAK,eAAe;AAClD,QAAM,KAAK,gBAAgB,GAAG,KAAK,eAAe;AAClD,QAAM,SAAS,gBAAgB,OAAO,SAAS,eAAe;AAC9D,mBAAiB,IAAI,EAAE;AACvB,SAAO,YAAY,GAAG,OAAO,GAAG,KAAK,GAAG,MAAM,2BAA2B;AACzE,QAAM,MAAM,OAAO,CAAC;AACpB,QAAM,gBAAgB,IAAI,KAAK,MAAM;AACrC,MAAI,SAAS,IAAI,IAAI,IAAI,EAAE,GAAG,aAAa;AAC3C,MAAI,YAAY;AACd,WAAO,SAAS,MAAM,MAAM,gDAAgD;AAC5E,UAAM,QAAQ,gBAAgB,OAAO,QAAQ,eAAe;AAC5D,aAAS,IAAI,QAAQ,IAAI,KAAK,IAAI,QAAQ,KAAK,CAAC,CAAC;AAAA,EACnD;AACA,SAAO,KAAK,IAAI,MAAM;AACxB;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,WAAW,SAAS,SAAS,OAAO;AAC3C,QAAM,WAAW,gBAAgB,SAAS,WAAW,aAAa,OAAO;AACzE,QAAM,WAAW,gBAAgB,SAAS,WAAW,WAAW;AAChE,gBAAc,UAAU,UAAU,KAAK;AACvC,QAAM,SAAS,EAAE,SAAS,UAAU,SAAS,SAAS;AACtD,QAAM,QAAQ,EAAE,MAAM;AACtB,SAAO,OAAO,UAAU,WAAW,QAAQ,KAAK;AAClD;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,eAAe,eAAe,cAAc,aAAa,eAAe;AAC/E,MAAI,cAAc,UAAU,SAAS;AACnC,UAAM,IAAI,MAAM,8EAA8E,cAAc,QAAQ;AAAA,EACtH;AACA,MAAI,cAAc,OAAO,GAAG;AAC1B,UAAM,IAAI,MAAM,sEAAsE,cAAc,QAAQ;AAAA,EAC9G;AACA,QAAM,WAAW,cAAc,OAAO,IAAI,cAAc,MAAM,KAAK;AACnE,QAAM,UAAU,cAAc,OAAO,IAAI,cAAc,MAAM,KAAK;AAClE,MAAI,YAAY,WAAW,SAAS;AAClC,UAAM,IAAI,MAAM,kDAAkD,YAAY,sBAAsB,UAAU;AAAA,EAChH;AACA,QAAM,YAAY,aAAa;AAC/B,MAAI,EAAE,aAAa,SAAS,KAAK,aAAa,SAAS,KAAK,cAAc,WAAW;AACnF,UAAM,IAAI,MAAM,oCAAoC,aAAa,2BAA2B,WAAW;AAAA,EACzG;AACA,MAAI,aAAa,UAAU,cAAc,OAAO;AAC9C,UAAM,IAAI,MAAM,mDAAmD;AAAA,EACrE;AACF;AAGA,SAAS,eAAe,eAAe,cAAc,aAAa,eAAe,GAAG;AAClF,QAAM,iBAAiB,gBAAgB,eAAe,iBAAiB,iBAAiB,OAAO;AAC/F,QAAM,gBAAgB,gBAAgB,cAAc,gBAAgB,iBAAiB,mBAAmB;AACxG,QAAM,gBAAgB,gBAAgB,cAAc,gBAAgB,iBAAiB,cAAc,KAAK;AACxG,iBAAe,gBAAgB,eAAe,aAAa,aAAa;AACxE,QAAM,SAAS;AAAA,IACb,eAAe;AAAA,IACf,cAAc;AAAA,IACd,cAAc;AAAA,EAChB;AACA,QAAM,QAAQ,EAAE,YAAY;AAC5B,SAAO,OAAO,UAAU,eAAe,QAAQ,KAAK;AACtD;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,UAAU,GAAG,SAAS;AAC7B,QAAM,WAAW,gBAAgB,SAAS,WAAW,YAAY,OAAO;AACxE,QAAM,KAAK,gBAAgB,GAAG,KAAK,YAAY,mBAAmB;AAClE,QAAM,SAAS,EAAE,QAAQ,IAAI,SAAS,SAAS;AAC/C,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,cAAc,GAAG,YAAY;AACpC,MAAI,cAAc,MAAM;AACtB,WAAO,EAAE,MAAM,MAAM;AAAA,EACvB;AACA,MAAI,YAAY,EAAE,OAAO,UAAU,GAAG;AACpC,WAAO;AAAA,EACT;AACA,MAAI,EAAE,MAAM,WAAW,WAAW,QAAQ;AACxC,UAAM,eAAe,CAAC;AACtB,aAAS,KAAK,GAAG,KAAK,EAAE,MAAM,QAAQ,MAAM;AAC1C,UAAI,WAAW,OAAO,QAAQ,EAAE,MAAM,OAAO,MAAM;AACjD,qBAAa,KAAK,EAAE,MAAM,GAAG;AAAA,MAC/B,OAAO;AACL,qBAAa,KAAK,WAAW,GAAG;AAAA,MAClC;AAAA,IACF;AACA,WAAO;AAAA,EACT;AACA,SAAO;AACT;AAGA,SAAS,SAAS,GAAG,MAAM,YAAY,MAAM;AAC3C,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,UAAU,WAAW,MAAM,gFAAgF,GAAG,uBAAuB;AAC/I,SAAO,QAAQ,KAAK,OAAO,GAAG,MAAM,qDAAqD,OAAO;AAChG,MAAI,SAAS,GAAG;AACd,WAAO,aAAa,SAAS,GAAG,MAAM,IAAI;AAAA,EAC5C;AACA,QAAM,cAAc,cAAc,IAAI,UAAU;AAChD,QAAM,WAAW,IAAI;AACrB,QAAM,aAAa,IAAI,MAAM,KAAK,cAAc,aAAa,GAAG,GAAG,WAAW,IAAI,GAAG,QAAQ,CAAC,GAAG,QAAQ;AACzG,SAAO,IAAI,IAAI,UAAU;AAC3B;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,oBAAoB,OAAO;AAClC,SAAO,KAAK,MAAM,KAAK,IAAI,GAAG,KAAK,KAAK,KAAK,IAAI,KAAK,IAAI,KAAK,IAAI,CAAC,CAAC,CAAC,CAAC;AACzE;AACA,SAAS,aAAa,cAAc,GAAG,GAAG;AACxC,QAAM,OAAO,IAAI,eAAe;AAChC,QAAM,YAAY,IAAI,aAAa,YAAY;AAC/C,WAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,UAAM,SAAS,IAAI,KAAK,KAAK,MAAM,eAAe,OAAO;AACzD,cAAU,MAAM,IAAI,IAAI,KAAK,IAAI,MAAM;AAAA,EACzC;AACA,SAAO,SAAS,WAAW,SAAS;AACtC;AAGA,eAAe,aAAa,aAAa,SAAS,IAAI,GAAG;AACvD,QAAM,eAAe,gBAAgB,aAAa,eAAe,QAAQ;AACzE,QAAM,WAAW,gBAAgB,SAAS,WAAW,QAAQ;AAC7D,SAAO,aAAa,OAAO,GAAG,MAAM,uEAAuE,aAAa,MAAM;AAC9H,SAAO,aAAa,OAAO,MAAM,SAAS,MAAM,MAAM,mFAAmF,aAAa,yBAAyB,SAAS,MAAM;AAC9L,oBAAkB,aAAa,MAAM,MAAM,GAAG,aAAa,MAAM,SAAS,CAAC,GAAG,SAAS,OAAO,yFAAyF;AACvL,QAAM,UAAU,aAAa,MAAM,aAAa,MAAM,SAAS;AAC/D,SAAO,IAAI,KAAK,KAAK,SAAS,MAAM,4EAA4E,qBAAqB,GAAG;AACxI,QAAM,kBAAkB,MAAM,aAAa,KAAK;AAChD,QAAM,cAAc,MAAM,SAAS,KAAK;AACxC,QAAM,CAAC,OAAOL,KAAI,IAAI,CAAC,gBAAgB,SAAS,SAAS,OAAO;AAChE,QAAM,aAAa,uBAAuB,QAAQ,KAAK;AACvD,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,UAAM,SAAS,IAAIA;AACnB,UAAM,OAAO,gBAAgB,SAAS,QAAQ,SAASA,KAAI;AAC3D,UAAM,YAAY,CAAC;AACnB,aAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,gBAAU,KAAK,EAAE,OAAO,KAAK,KAAK,OAAO,GAAG,CAAC;AAAA,IAC/C;AACA,cAAU,KAAK,CAAC,GAAG,OAAO,GAAG,QAAQ,EAAE,KAAK;AAC5C,eAAW,KAAK;AAChB,aAAS,KAAK,GAAG,KAAK,GAAG,MAAM;AAC7B,UAAI,UAAU,IAAI,UAAU,YAAY,IAAI;AAC1C,mBAAW,KAAK;AAChB;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,MAAI,gBAAgB,cAAc;AAChC,iBAAa,QAAQ;AAAA,EACvB;AACA,MAAI,YAAY,UAAU;AACxB,aAAS,QAAQ;AAAA,EACnB;AACA,SAAO,OAAO,YAAY,SAAS,OAAO,MAAM;AAClD;AACA,IAAI,cAAc;AAGlB,IAAI,oBAAoB,CAAC;AACzBH,UAAS,mBAAmB;AAAA,EAC1B,QAAQ,MAAM;AAAA,EACd,iBAAiB,MAAM;AAAA,EACvB,QAAQ,MAAM;AAChB,CAAC;AAGD,SAAS,sBAAsB,GAAG,IAAI,aAAae,UAAS,MAAM,aAAa,QAAQ,iBAAiB;AACtG,MAAI,MAAM;AACV,MAAI,EAAE,SAAS,GAAG;AAChB,UAAM,QAAQ,GAAG,CAAC,GAAG,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,EAAE,CAAC;AAAA,EAC1D;AACA,MAAI,OAAO;AACX,MAAI,KAAK,SAAS,GAAG;AACnB,WAAO,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC/D;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,iEAAiE,IAAI,QAAQ;AAC1G,SAAO,KAAK,SAAS,GAAG,MAAM,8DAA8D,KAAK,QAAQ;AACzG,SAAO,YAAY,WAAW,GAAG,MAAM,mEAAmE,cAAc;AACxH,QAAM,UAAU,eAAe,SAAS,IAAI,MAAM,KAAK,IAAI,MAAM;AACjE,QAAM,WAAW,eAAe,SAAS,KAAK,MAAM,KAAK,KAAK,MAAM;AACpE,SAAO,YAAY,YAAY,IAAI,MAAM,4CAA4C,8CAA8C,YAAY,KAAK;AACpJ,SAAO,aAAa,YAAY,IAAI,MAAM,0CAA0C,iDAAiD,YAAY,MAAM;AACvJ,4BAA0B,mBAAmB,MAAM,eAAe;AAClE,QAAM,SAAS,EAAE,GAAG,KAAK,IAAI,KAAK;AAClC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,iBAAiB,YAAY;AAC7E,SAAO,OAAO,UAAU,sBAAsB,QAAQ,KAAK;AAC7D;AACA,IAAI,uBAAuB,GAAG,EAAE,sBAAsB,CAAC;AAGvD,SAAS,qBAAqB,IAAI,GAAG,aAAa;AAChD,MAAI,eAAe,QAAQ,gBAAgB,UAAU;AACnD,WAAO;AAAA,EACT;AACA,MAAI,gBAAgB,QAAQ;AAC1B,WAAO,IAAI,IAAI,KAAK,CAAC,CAAC;AAAA,EACxB;AACA,QAAM,IAAI,MAAM,gDAAgD,cAAc;AAChF;AACA,SAAS,qBAAqB,MAAM,cAAc;AAChD,MAAI,MAAM;AACV,QAAM,aAAa,iBAAiB,KAAK,OAAO,aAAa,KAAK;AAClE,MAAI,WAAW,SAAS,GAAG;AACzB,UAAM,KAAK,KAAK,UAAU;AAAA,EAC5B;AACA,SAAO,QAAQ,KAAK,KAAK,KAAK;AAChC;AACA,SAAS,gBAAgB,GAAG,aAAa,wBAAwB,gBAAgB;AAC/E,MAAI,gBAAgB,UAAU;AAC5B,WAAO;AAAA,EACT,WAAW,gBAAgB,QAAQ;AACjC,WAAO,KAAK,CAAC;AAAA,EACf,WAAW,gBAAgB,OAAO;AAChC,WAAO,IAAI,CAAC;AAAA,EACd,WAAW,gBAAgB,SAAS;AAClC,WAAO,MAAM,CAAC;AAAA,EAChB,WAAW,gBAAgB,SAAS;AAClC,WAAO,MAAM,GAAG,sBAAsB;AAAA,EACxC,WAAW,gBAAgB,aAAa;AACtC,WAAO,UAAU,GAAG,cAAc;AAAA,EACpC,WAAW,gBAAgB,WAAW;AACpC,WAAO,QAAQ,CAAC;AAAA,EAClB;AACA,QAAM,IAAI,MAAM,4BAA4B,cAAc;AAC5D;AACA,IAAI,aAAa,CAAC,eAAe,gBAAgB;AAC/C,QAAM,eAAe,gBAAgB;AACrC,SAAO,CAAC,gBAAgB,gBAAgB;AAC1C;AAGA,SAAS,aAAa,EAAE,GAAG,QAAQ,SAAAA,UAAS,KAAK,MAAM,aAAa,QAAQ,YAAY,CAAC,GAAG,CAAC,GAAG,iBAAiB,MAAM,YAAY,cAAc,UAAU,wBAAwB,eAAe,GAAG;AACnM,gBAAc,eAAe;AAC7B,MAAI,WAAW,OAAO,MAAM,eAAe,WAAW,MAAM,OAAO;AACjE,WAAO,eAAe,QAAQ,MAAM,4CAA4C,uHAAuH;AACvM,QAAI,SAAS,OAAO,GAAG,QAAQA,UAAS,MAAM,YAAY,WAAW,eAAe;AACpF,QAAI,QAAQ,MAAM;AAChB,eAAS,KAAK,QAAQ,IAAI;AAAA,IAC5B;AACA,WAAO,gBAAgB,QAAQ,aAAa,wBAAwB,cAAc;AAAA,EACpF;AACA,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU,SAAS;AACtD,QAAM,UAAU,gBAAgB,QAAQ,UAAU,UAAU,SAAS;AACrE,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,6DAA6D,IAAI,OAAO;AACrG,SAAO,QAAQ,SAAS,GAAG,MAAM,8DAA8D,QAAQ,OAAO;AAC9G,4BAA0B,gBAAgB,MAAM,eAAe;AAC/D,QAAM,gBAAgB,eAAe,SAAS,IAAI,MAAM,KAAK,IAAI,MAAM;AACvE,SAAO,QAAQ,MAAM,OAAO,eAAe,MAAM,oCAAoC,oDAAoD,QAAQ,MAAM,KAAK;AAC5J,SAAO,+BAA+BA,UAAS,SAAS,GAAG,MAAM,uEAAuEA,2BAA0B,YAAY;AAC9K,QAAM,WAAW,kBAAkB,IAAI,OAAO,QAAQ,OAAOA,UAAS,WAAW,MAAM,eAAe;AACtG,MAAI;AACJ,MAAI,QAAQ,MAAM;AAChB,YAAQ,gBAAgB,MAAM,QAAQ,cAAc;AACpD,KAAC,KAAK,IAAI,eAAe,OAAO,EAAE;AAClC,QAAI,eAAe,QAAQ;AACzB,iCAA2B,SAAS,UAAU,MAAM,KAAK;AAAA,IAC3D,OAAO;AACL,aAAO,MAAM,MAAM,UAAU,GAAG,MAAM,2GAA2G,MAAM,MAAM,SAAS;AACtK,aAAO,MAAM,MAAM,WAAW,KAAK,MAAM,MAAM,OAAO,SAAS,eAAe,MAAM,MAAM,OAAO,GAAG,MAAM,sCAAsC,MAAM,gEAAgE,SAAS,cAAc;AAAA,IAC/O;AAAA,EACF;AACA,MAAI;AACJ,MAAI,0BAA0B,MAAM;AAClC,UAAM,aAAa,uBAAuB;AAC1C,WAAO,WAAW,UAAU,KAAK,WAAW,WAAW,GAAG,MAAM,2HAA2H,WAAW,SAAS;AAC/M,QAAI,WAAW,WAAW,GAAG;AAC3B,aAAO,WAAW,OAAO,KAAK,WAAW,OAAO,SAAS,aAAa,MAAM,oDAAoD,qEAAqE,SAAS,eAAe;AAAA,IAC/N,WAAW,WAAW,WAAW,GAAG;AAClC,UAAI;AACF,mCAA2B,YAAY,SAAS,QAAQ;AAAA,MAC1D,SAAS,IAAP;AACA,cAAM,SAAS,oDAAoD,sEAAsE,SAAS;AAClJ,cAAM,MAAM,MAAM;AAAA,MACpB;AAAA,IACF;AACA,8BAA0B,gBAAgB,wBAAwB,iBAAiB,cAAc;AAAA,EACnG;AACA,QAAM,QAAQ,CAAC,IAAI,UAAU;AAC3B,WAAO,eAAe,QAAQ,MAAM,wDAAwD,kDAAkD;AAC9I,UAAM,CAAC,UAAU,MAAM,GAAG,MAAM,IAAI;AACpC,UAAM,eAAe,qBAAqB,IAAI,GAAG,WAAW;AAC5D,WAAO,kBAAkB,SAAS,GAAG,MAAM,uHAAuH,YAAY;AAC9K,UAAM,OAAO,oBAAoB,KAAK,OAAO,cAAc,UAAUA,UAAS,IAAI;AAClF,UAAM,YAAY,qBAAqB,MAAM,cAAc,SAAS,OAAOA,UAAS,IAAI;AACxF,UAAM,MAAM,CAAC,MAAM,SAAS;AAC5B,QAAI,UAAU,MAAM;AAClB,YAAM,UAAU,qBAAqB,QAAQ,YAAY;AACzD,UAAI,KAAK,OAAO;AAAA,IAClB;AACA,WAAO;AAAA,EACT;AACA,QAAM,SAAS;AAAA,IACb,GAAG;AAAA,IACH,QAAQ;AAAA,IACR,MAAM;AAAA,IACN,wBAAwB;AAAA,EAC1B;AACA,QAAM,QAAQ;AAAA,IACZ,SAAAA;AAAA,IACA,KAAK;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA,YAAY;AAAA,IACZ;AAAA,EACF;AACA,MAAI,QAAQ,MAAM;AAChB,UAAM,WAAW,WAAW,CAAC,MAAM,SAAS,SAAS;AACnD,UAAI,MAAM,OAAO,UAAU,aAAa,QAAQ,KAAK;AACrD,WAAK,CAAC,SAAS,MAAM,GAAG,CAAC;AACzB,UAAI,cAAc;AAChB,cAAM,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,MAC/D;AACA,aAAO,EAAE,OAAO,KAAK,UAAU,MAAM;AAAA,IACvC,CAAC;AACD,WAAO,SAAS,KAAK,OAAO;AAAA,EAC9B,OAAO;AACL,UAAM,mBAAmB,WAAW,CAAC,MAAM,SAAS,OAAO,SAAS;AAClE,UAAI,MAAM,OAAO,UAAU,aAAa,QAAQ,KAAK;AACrD,WAAK,CAAC,SAAS,MAAM,KAAK,KAAK,CAAC;AAChC,UAAI,cAAc;AAChB,cAAM,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,MAC/D;AACA,aAAO,EAAE,OAAO,KAAK,UAAU,MAAM;AAAA,IACvC,CAAC;AACD,WAAO,iBAAiB,KAAK,SAAS,KAAK;AAAA,EAC7C;AACF;AACA,IAAI,UAAU,GAAG,EAAE,aAAa,CAAC;AAGjC,SAAS,qCAAqC,GAAG,IAAI,aAAaA,UAAS,MAAM,YAAY,CAAC,GAAG,CAAC,GAAG,iBAAiB;AACpH,MAAI,MAAM;AACV,MAAI,EAAE,SAAS,GAAG;AAChB,UAAM,QAAQ,GAAG,CAAC,GAAG,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,EAAE,CAAC;AAAA,EAC1D;AACA,MAAI,OAAO;AACX,MAAI,KAAK,SAAS,GAAG;AACnB,WAAO,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC/D;AACA,QAAM,SAAS,EAAE,GAAG,KAAK,IAAI,KAAK;AAClC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,iBAAiB,WAAW,YAAY;AAC5E,SAAO,OAAO,UAAU,qCAAqC,QAAQ,KAAK;AAC5E;AACA,IAAI,sCAAsC,GAAG,EAAE,qCAAqC,CAAC;AAGrF,SAAS,oCAAoC,QAAQ,IAAI,QAAQA,UAAS,MAAM,YAAY,CAAC,GAAG,CAAC,GAAG,iBAAiB;AACnH,MAAI,OAAO;AACX,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,WAAO,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC/D;AACA,QAAM,SAAS,EAAE,IAAI,MAAM,OAAO;AAClC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,iBAAiB,WAAW,YAAY,OAAO;AACnF,QAAM,MAAM,OAAO,UAAU,oCAAoC,QAAQ,KAAK;AAC9E,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,qCAAqC,GAAG,EAAE,oCAAoC,CAAC;AAGnF,SAAS,sBAAsB,EAAE,GAAG,QAAQ,SAAAA,UAAS,KAAK,MAAM,aAAa,QAAQ,YAAY,CAAC,GAAG,CAAC,GAAG,iBAAiB,MAAM,YAAY,cAAc,UAAU,wBAAwB,eAAe,GAAG;AAC5M,MAAI,WAAW,OAAO,MAAM,eAAe,WAAW,MAAM,OAAO;AACjE,QAAI,SAAS,gBAAgB,GAAG,QAAQA,UAAS,MAAM,YAAY,WAAW,eAAe;AAC7F,QAAI,QAAQ,MAAM;AAChB,eAAS,KAAK,QAAQ,IAAI;AAAA,IAC5B;AACA,WAAO,gBAAgB,QAAQ,aAAa,wBAAwB,cAAc;AAAA,EACpF;AACA,QAAM,KAAK,gBAAgB,GAAG,KAAK,mBAAmB,SAAS;AAC/D,QAAM,UAAU,gBAAgB,QAAQ,UAAU,mBAAmB,SAAS;AAC9E,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,sEAAsE,IAAI,OAAO;AAC9G,SAAO,QAAQ,SAAS,GAAG,MAAM,uEAAuE,QAAQ,OAAO;AACvH,SAAO,IAAI,MAAM,OAAO,QAAQ,MAAM,IAAI,MAAM,6DAA6D,IAAI,MAAM,qDAAqD,QAAQ,MAAM,KAAK;AAC/L,MAAI,aAAa,MAAM;AACrB,gBAAY,CAAC,GAAG,CAAC;AAAA,EACnB;AACA,SAAO,+BAA+BA,UAAS,SAAS,GAAG,MAAM,sFAAsFA,2BAA0B,YAAY;AAC7L,4BAA0B,yBAAyB,MAAM,eAAe;AACxE,QAAM,WAAW,kBAAkB,IAAI,OAAO,QAAQ,OAAOA,UAAS,WAAW,MAAM,iBAAiB,IAAI;AAC5G,MAAI;AACJ,MAAI,QAAQ,MAAM;AAChB,YAAQ,gBAAgB,MAAM,QAAQ,cAAc;AACpD,KAAC,KAAK,IAAI,eAAe,OAAO,EAAE;AAClC,+BAA2B,SAAS,UAAU,MAAM,KAAK;AAAA,EAC3D;AACA,MAAI;AACJ,MAAI,0BAA0B,MAAM;AAClC,8BAA0B,gBAAgB,wBAAwB,iBAAiB,uBAAuB;AAAA,EAC5G;AACA,QAAM,QAAQ,CAAC,IAAI,UAAU;AAC3B,WAAO,kBAAkB,SAAS,GAAG,MAAM,mHAAmH,YAAY;AAC1K,UAAM,CAAC,UAAU,MAAM,GAAG,KAAK,IAAI;AACnC,UAAM,eAAe,qBAAqB,IAAI,GAAG,WAAW;AAC5D,UAAM,OAAO,mCAAmC,KAAK,OAAO,cAAc,UAAUA,UAAS,MAAM,WAAW,eAAe;AAC7H,UAAM,YAAY,oCAAoC,MAAM,cAAc,SAAS,OAAOA,UAAS,MAAM,WAAW,eAAe;AACnI,QAAI,SAAS,MAAM;AACjB,YAAM,UAAU,qBAAqB,OAAO,YAAY;AACxD,aAAO,CAAC,MAAM,WAAW,OAAO;AAAA,IAClC;AACA,WAAO,CAAC,MAAM,SAAS;AAAA,EACzB;AACA,QAAM,SAAS;AAAA,IACb,GAAG;AAAA,IACH,QAAQ;AAAA,IACR,MAAM;AAAA,IACN,wBAAwB;AAAA,EAC1B;AACA,QAAM,QAAQ;AAAA,IACZ,SAAAA;AAAA,IACA,KAAK;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA,YAAY;AAAA,IACZ;AAAA,EACF;AACA,MAAI,QAAQ,MAAM;AAChB,UAAM,WAAW,WAAW,CAAC,MAAM,SAAS,SAAS;AACnD,UAAI,MAAM,OAAO,UAAU,sBAAsB,QAAQ,KAAK;AAC9D,WAAK,CAAC,SAAS,MAAM,GAAG,CAAC;AACzB,UAAI,cAAc;AAChB,cAAM,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,MAC/D;AACA,aAAO,EAAE,OAAO,KAAK,UAAU,MAAM;AAAA,IACvC,CAAC;AACD,WAAO,SAAS,KAAK,OAAO;AAAA,EAC9B,OAAO;AACL,UAAM,mBAAmB,WAAW,CAAC,MAAM,SAAS,OAAO,SAAS;AAClE,UAAI,MAAM,OAAO,UAAU,sBAAsB,QAAQ,KAAK;AAC9D,WAAK,CAAC,SAAS,MAAM,KAAK,KAAK,CAAC;AAChC,UAAI,cAAc;AAChB,cAAM,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,MAC/D;AACA,aAAO,EAAE,OAAO,KAAK,UAAU,MAAM;AAAA,IACvC,CAAC;AACD,WAAO,iBAAiB,KAAK,SAAS,KAAK;AAAA,EAC7C;AACF;AACA,IAAI,mBAAmB,GAAG,EAAE,sBAAsB,CAAC;AAGnD,SAAS,aAAa,EAAE,GAAG,GAAG,aAAa,OAAO,aAAa,OAAO,MAAM,YAAY,cAAc,UAAU,wBAAwB,iBAAiB,IAAI,GAAG;AAC9J,MAAI,WAAW,OAAO,MAAM,eAAe,WAAW,MAAM,OAAO;AACjE,QAAI,SAAS,OAAO,GAAG,GAAG,YAAY,UAAU;AAChD,QAAI,QAAQ,MAAM;AAChB,eAAS,KAAK,QAAQ,IAAI;AAAA,IAC5B;AACA,WAAO,gBAAgB,QAAQ,aAAa,wBAAwB,cAAc;AAAA,EACpF;AACA,MAAI,KAAK,gBAAgB,GAAG,KAAK,cAAc;AAC/C,MAAI,KAAK,gBAAgB,GAAG,KAAK,cAAc;AAC/C,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,cAAc,aAAa,GAAG,MAAM,GAAG,OAAO,KAAK,GAAG,MAAM,GAAG,OAAO;AAC5E,QAAM,cAAc,aAAa,GAAG,MAAM,GAAG,OAAO,KAAK,GAAG,MAAM,GAAG,OAAO;AAC5E,QAAM,cAAc,aAAa,GAAG,MAAM,GAAG,OAAO,KAAK,GAAG,MAAM,GAAG,OAAO;AAC5E,QAAM,cAAc,aAAa,GAAG,MAAM,GAAG,OAAO,KAAK,GAAG,MAAM,GAAG,OAAO;AAC5E,QAAM,aAAa,GAAG,MAAM,MAAM,GAAG,EAAE;AACvC,QAAM,aAAa,GAAG,MAAM,MAAM,GAAG,EAAE;AACvC,QAAM,YAAY,cAAc,UAAU;AAC1C,QAAM,YAAY,cAAc,UAAU;AAC1C,SAAO,gBAAgB,aAAa,MAAM,wCAAwC,qBAAqB,uCAAuC,GAAG,aAAa,GAAG,wBAAwB,6BAA6B,wBAAwB;AAC9O,QAAM,oBAAoB,2BAA2B,GAAG,MAAM,MAAM,GAAG,EAAE,GAAG,GAAG,MAAM,MAAM,GAAG,EAAE,CAAC;AACjG,QAAM,WAAW,kBAAkB,OAAO,CAAC,aAAa,WAAW,CAAC;AACpE,QAAM,MAAM,aAAa,QAAQ,IAAI,CAAC,WAAW,aAAa,WAAW,CAAC,IAAI,QAAQ,IAAI,CAAC,WAAW,aAAa,WAAW,CAAC;AAC/H,QAAM,MAAM,aAAa,QAAQ,IAAI,CAAC,WAAW,aAAa,WAAW,CAAC,IAAI,QAAQ,IAAI,CAAC,WAAW,aAAa,WAAW,CAAC;AAC/H,MAAI;AACJ,MAAI,QAAQ,MAAM;AAChB,YAAQ,gBAAgB,MAAM,QAAQ,cAAc;AACpD,KAAC,KAAK,IAAI,eAAe,OAAO,EAAE;AAClC,+BAA2B,UAAU,MAAM,KAAK;AAAA,EAClD;AACA,MAAI;AACJ,MAAI,0BAA0B,MAAM;AAClC,8BAA0B,gBAAgB,wBAAwB,iBAAiB,cAAc;AAAA,EACnG;AACA,QAAM,QAAQ,CAAC,IAAI,UAAU;AAC3B,UAAM,CAAC,MAAM,MAAM,GAAG,MAAM,IAAI;AAChC,UAAM,eAAe,qBAAqB,QAAQ,IAAI,EAAE,KAAK,GAAG,GAAG,WAAW;AAC9E,QAAI;AACJ,QAAI;AACJ,QAAI,CAAC,cAAc,CAAC,YAAY;AAC9B,aAAO,OAAO,cAAc,MAAM,OAAO,IAAI;AAC7C,aAAO,OAAO,MAAM,cAAc,MAAM,KAAK;AAAA,IAC/C,WAAW,CAAC,cAAc,YAAY;AACpC,aAAO,OAAO,cAAc,MAAM,OAAO,KAAK;AAC9C,aAAO,OAAO,cAAc,MAAM,MAAM,KAAK;AAAA,IAC/C,WAAW,cAAc,CAAC,YAAY;AACpC,aAAO,OAAO,MAAM,cAAc,OAAO,IAAI;AAC7C,aAAO,OAAO,MAAM,cAAc,OAAO,KAAK;AAAA,IAChD,OAAO;AACL,aAAO,OAAO,MAAM,cAAc,MAAM,IAAI;AAC5C,aAAO,OAAO,cAAc,MAAM,MAAM,IAAI;AAAA,IAC9C;AACA,QAAI,QAAQ,MAAM;AAChB,YAAM,UAAU,qBAAqB,QAAQ,YAAY;AACzD,aAAO,CAAC,MAAM,MAAM,OAAO;AAAA,IAC7B,OAAO;AACL,aAAO,CAAC,MAAM,IAAI;AAAA,IACpB;AAAA,EACF;AACA,QAAM,SAAS;AAAA,IACb,GAAG;AAAA,IACH,GAAG;AAAA,IACH,MAAM;AAAA,IACN,wBAAwB;AAAA,EAC1B;AACA,QAAM,QAAQ,EAAE,YAAY,YAAY,YAAY,aAAa,eAAe;AAChF,MAAI,QAAQ,MAAM;AAChB,UAAM,WAAW,WAAW,CAAC,MAAM,MAAM,SAAS;AAChD,YAAM,MAAM,OAAO,UAAU,cAAc,QAAQ,KAAK;AACxD,WAAK,CAAC,MAAM,MAAM,GAAG,CAAC;AACtB,aAAO,EAAE,OAAO,QAAQ,KAAK,QAAQ,GAAG,UAAU,MAAM;AAAA,IAC1D,CAAC;AACD,WAAO,SAAS,KAAK,GAAG;AAAA,EAC1B,OAAO;AACL,UAAM,mBAAmB,WAAW,CAAC,MAAM,MAAM,QAAQ,SAAS;AAChE,YAAM,MAAM,OAAO,UAAU,cAAc,QAAQ,KAAK;AACxD,WAAK,CAAC,MAAM,MAAM,KAAK,MAAM,CAAC;AAC9B,aAAO,EAAE,OAAO,QAAQ,KAAK,QAAQ,GAAG,UAAU,MAAM;AAAA,IAC1D,CAAC;AACD,WAAO,iBAAiB,KAAK,KAAK,KAAK;AAAA,EACzC;AACF;AACA,IAAI,UAAU,GAAG,EAAE,aAAa,CAAC;AAGjC,SAAS,eAAe,cAAc;AACpC,SAAO,aAAa,cAAc,MAAM,IAAI;AAC9C;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,YAAY,cAAc;AACjC,SAAO,aAAa,cAAc,KAAK,GAAG;AAC5C;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,OAAO,SAAS,aAAa,WAAW,SAAS,OAAO,WAAW,GAAG;AAC7E,MAAI,QAAQ;AACZ,QAAM,SAAS,CAAC;AAChB,SAAO,QAAQ,eAAe,QAAQ,MAAM;AAC1C,WAAO,KAAK,MAAM,SAAS,OAAO,WAAW,CAAC;AAC9C,aAAS;AAAA,EACX;AACA,MAAI,QAAQ;AACV,WAAO,QAAQ,QAAQ,MAAM;AAC3B,YAAM,SAAS,QAAQ,cAAc,QAAQ;AAC7C,YAAM,OAAO,OAAO;AAAA,QAClB,MAAM,SAAS,OAAO,cAAc,MAAM;AAAA,QAC1C,KAAK,CAAC,MAAM,GAAG,QAAQ;AAAA,MACzB,CAAC;AACD,aAAO,KAAK,IAAI;AAChB,eAAS;AAAA,IACX;AAAA,EACF;AACA,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,SAAS,CAAC,GAAG,CAAC,GAAG,WAAW,CAAC;AAAA,EACtC;AACA,SAAO,QAAQ,OAAO,MAAM,GAAG,CAAC,OAAO,QAAQ,WAAW,CAAC;AAC7D;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,SAAS,aAAa,WAAW,WAAW,WAAW,YAAY;AAChF,MAAI,aAAa,MAAM;AACrB,gBAAY,oBAAoB,WAAW;AAAA,EAC7C;AACA,QAAM,eAAe,MAAM,SAAS,aAAa,SAAS;AAC1D,QAAM,iBAAiB,IAAI,cAAc,SAAS,WAAW,CAAC;AAC9D,SAAO,KAAK,gBAAgB,SAAS;AACvC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,eAAe,QAAQ,OAAO,QAAQ,UAAU,SAAS,YAAY,qBAAqB,GAAG;AACpG,QAAM,SAAS,gBAAgB,QAAQ,SAAS,eAAe;AAC/D,QAAM,SAAS,gBAAgB,OAAO,SAAS,iBAAiB,SAAS;AACzE,QAAM,UAAU,gBAAgB,QAAQ,UAAU,iBAAiB,OAAO;AAC1E,QAAM,WAAW,OAAO,MAAM;AAC9B,SAAO,OAAO,SAAS,GAAG,MAAM,6DAA6D,OAAO,OAAO;AAC3G,SAAO,OAAO,SAAS,KAAK,OAAO,MAAM,OAAO,GAAG,MAAM,oDAAoD,6BAA6B,OAAO,QAAQ;AACzJ,SAAO,QAAQ,SAAS,KAAK,QAAQ,MAAM,OAAO,UAAU,MAAM,qDAAqD,2BAA2B,OAAO,QAAQ;AACjK,SAAO,SAAS,WAAW,GAAG,MAAM,wEAAwE,SAAS,SAAS;AAC9H,SAAO,SAAS,MAAM,KAAK,SAAS,MAAM,GAAG,MAAM,2CAA2C,UAAU;AACxG,SAAO,WAAW,cAAc,WAAW,WAAW,MAAM,+CAA+C,QAAQ;AACnH,QAAM,SAAS,EAAE,OAAO,QAAQ,OAAO,QAAQ,QAAQ,QAAQ;AAC/D,QAAM,QAAQ,EAAE,QAAQ,oBAAoB,SAAS;AACrD,QAAM,MAAM,OAAO,UAAU,eAAe,QAAQ,KAAK;AACzD,SAAO;AACT;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,eAAe,QAAQ;AAC9B,QAAM,SAAS,gBAAgB,QAAQ,SAAS,iBAAiB,SAAS;AAC1E,SAAO,OAAO,SAAS,GAAG,MAAM,6DAA6D,OAAO,OAAO;AAC3G,QAAM,SAAS,EAAE,OAAO,OAAO;AAC/B,QAAM,MAAM,OAAO,UAAU,eAAe,QAAQ,CAAC,CAAC;AACtD,SAAO;AACT;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,gBAAgB,QAAQ;AAC/B,QAAM,SAAS,gBAAgB,QAAQ,SAAS,gBAAgB;AAChE,QAAM,cAAc,OAAO,OAAO;AAClC,QAAM,WAAW,OAAO,MAAM;AAC9B,SAAO,OAAO,QAAQ,GAAG,MAAM,yEAAyE,OAAO,OAAO;AACtH,SAAO,aAAa,GAAG,MAAM,+FAA+F,WAAW;AACvI,QAAM,OAAO,IAAI,MAAM,OAAO,IAAI;AAClC,OAAK,KAAK,GAAG,GAAG,WAAW;AAC3B,OAAK,eAAe;AACpB,SAAO,KAAK,QAAQ,IAAI;AAC1B;AACA,IAAI,iBAAiB,GAAG,EAAE,gBAAgB,CAAC;AAG3C,SAAS,kBAAkB,QAAQ,SAAS,YAAY,GAAG,SAAS,KAAK;AACvE,QAAM,SAAS,gBAAgB,QAAQ,SAAS,oBAAoB,SAAS;AAC7E,SAAO,OAAO,SAAS,GAAG,MAAM,gEAAgE,OAAO,OAAO;AAC9G,QAAM,SAAS,EAAE,OAAO,OAAO;AAC/B,QAAM,QAAQ,EAAE,SAAS,WAAW,OAAO;AAC3C,QAAM,MAAM,OAAO,UAAU,kBAAkB,QAAQ,KAAK;AAC5D,SAAO;AACT;AACA,IAAI,mBAAmB,GAAG,EAAE,kBAAkB,CAAC;AAG/C,SAAS,sBAAsB,OAAO,QAAQ,eAAe,cAAc,gBAAgB,cAAc;AACvG,MAAI,gBAAgB,MAAM;AACxB,mBAAe;AAAA,EACjB;AACA,MAAI,kBAAkB,MAAM;AAC1B,qBAAiB,OAAO;AAAA,EAC1B;AACA,MAAI,gBAAgB,MAAM;AACxB,mBAAe;AAAA,EACjB;AACA,QAAM,WAAW,MAAM,MAAM;AAC7B,kBAAgB,KAAK,IAAI,eAAe,QAAQ;AAChD,SAAO,KAAK,gBAAgB,gBAAgB,GAAG,MAAM,4CAA4C,eAAe;AAChH,SAAO,MAAM,SAAS,GAAG,MAAM,+CAA+C,MAAM,OAAO;AAC3F,SAAO,MAAM,MAAM,OAAO,GAAG,MAAM,oDAAoD,MAAM,MAAM,IAAI;AACvG,SAAO,OAAO,SAAS,GAAG,MAAM,4BAA4B;AAC5D,SAAO,OAAO,MAAM,OAAO,UAAU,MAAM,sDAAsD,qBAAqB,OAAO,MAAM,IAAI;AACvI,SAAO,KAAK,gBAAgB,gBAAgB,GAAG,MAAM,4CAA4C,eAAe;AAChH,SAAO,EAAE,eAAe,cAAc,gBAAgB,aAAa;AACrE;AAGA,SAAS,mBAAmB,OAAO,QAAQ,eAAe,eAAe,KAAK,iBAAiB,OAAO,mBAAmB;AACvH,QAAM,SAAS,gBAAgB,OAAO,SAAS,qBAAqB,SAAS;AAC7E,QAAM,UAAU,gBAAgB,QAAQ,UAAU,qBAAqB,SAAS;AAChF,QAAM,SAAS,sBAAsB,QAAQ,SAAS,eAAe,cAAc,cAAc;AACjG,kBAAgB,OAAO;AACvB,iBAAe,OAAO;AACtB,mBAAiB,OAAO;AACxB,QAAM,QAAQ,EAAE,eAAe,cAAc,eAAe;AAC5D,SAAO,OAAO,UAAU,qBAAqB,EAAE,OAAO,QAAQ,QAAQ,QAAQ,GAAG,KAAK;AACxF;AACA,IAAI,oBAAoB,GAAG,EAAE,mBAAmB,CAAC;AAGjD,SAAS,aAAa,KAAK,SAAS,YAAY;AAC9C,QAAMH,SAAQ,aAAa,KAAK,SAAS,UAAU;AACnD,QAAM,iBAAiBA,SAAQ,IAAI,EAAEA,SAAQ,KAAKA;AAClD,MAAI,OAAO,gBAAgB,GAAG,OAAO;AACvC;AACA,SAAS,aAAa,KAAK,QAAQ,YAAY;AAC7C,SAAO,cAAc,KAAK,QAAQ,cAAc,iBAAiB;AACnE;AACA,SAAS,kBAAkB,GAAG,GAAG;AAC/B,SAAO,IAAI,IAAI,IAAI,IAAI,IAAI,KAAK;AAClC;AACA,SAAS,cAAc,KAAK,QAAQ,YAAY;AAC9C,MAAI,OAAO;AACX,MAAI,QAAQ,IAAI;AAChB,MAAIe,UAAS;AACb,MAAI,QAAQ;AACZ,SAAO,OAAO,OAAO;AACnB,IAAAA,UAAS,QAAQ,QAAQ,SAAS;AAClC,UAAM,gBAAgB,WAAW,QAAQ,IAAIA,QAAO;AACpD,QAAI,gBAAgB,GAAG;AACrB,aAAOA,UAAS;AAAA,IAClB,OAAO;AACL,cAAQA;AACR,cAAQ,CAAC;AAAA,IACX;AAAA,EACF;AACA,SAAO,QAAQ,OAAO,CAAC,OAAO;AAChC;AAGA,SAAS,wBAAwB,OAAO,QAAQ,eAAe,cAAc,gBAAgB;AAC3F,SAAO,uBAAuB,OAAO,QAAQ,eAAe,cAAc,gBAAgB,CAAC;AAC7F;AACA,SAAS,wBAAwB,OAAO,QAAQ,eAAe,cAAc,gBAAgB,oBAAoB;AAC/G,SAAO;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AACA,SAAS,wBAAwB,OAAO,QAAQ,eAAe,cAAc,gBAAgB,cAAc;AACzG,SAAO,uBAAuB,OAAO,QAAQ,eAAe,cAAc,gBAAgB,cAAc,IAAI;AAC9G;AACA,SAAS,uBAAuB,OAAO,QAAQ,eAAe,cAAc,gBAAgB,cAAc,qBAAqB,OAAO,qBAAqB,OAAO,qBAAqB,OAAO;AAC5L,QAAM,aAAa,CAAC;AACpB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,QAAI,OAAO,MAAM,gBAAgB;AAC/B,iBAAW,KAAK,EAAE,OAAO,OAAO,KAAK,UAAU,IAAI,oBAAoB,EAAE,CAAC;AAAA,IAC5E;AAAA,EACF;AACA,aAAW,KAAK,mBAAmB;AACnC,QAAMH,UAAS,eAAe,IAAI,OAAO,eAAe;AACxD,QAAM,kBAAkB,CAAC;AACzB,QAAM,iBAAiB,CAAC;AACxB,SAAO,gBAAgB,SAAS,iBAAiB,WAAW,SAAS,GAAG;AACtE,UAAM,YAAY,WAAW,IAAI;AACjC,UAAM,EAAE,OAAO,eAAe,UAAU,mBAAmB,IAAI;AAC/D,QAAI,gBAAgB,gBAAgB;AAClC;AAAA,IACF;AACA,QAAI,kBAAkB;AACtB,aAAS,IAAI,gBAAgB,SAAS,GAAG,KAAK,oBAAoB,EAAE,GAAG;AACrE,YAAM,MAAM,sBAAsB,OAAO,UAAU,gBAAgB,EAAE;AACrE,UAAI,OAAO,cAAc;AACvB,0BAAkB;AAClB;AAAA,MACF;AACA,gBAAU,QAAQ,UAAU,QAAQ,eAAe,cAAcA,SAAQ,GAAG;AAC5E,UAAI,UAAU,SAAS,gBAAgB;AACrC;AAAA,MACF;AAAA,IACF;AACA,cAAU,qBAAqB,gBAAgB;AAC/C,QAAI,CAAC,iBAAiB;AACpB,UAAI,UAAU,UAAU,eAAe;AACrC,wBAAgB,KAAK,QAAQ;AAC7B,uBAAe,KAAK,UAAU,KAAK;AAAA,MACrC,WAAW,UAAU,QAAQ,gBAAgB;AAC3C,qBAAa,YAAY,WAAW,mBAAmB;AAAA,MACzD;AAAA,IACF;AAAA,EACF;AACA,QAAM,eAAe,gBAAgB;AACrC,QAAM,aAAa,gBAAgB;AACnC,MAAI,sBAAsB,aAAa,GAAG;AACxC,oBAAgB,KAAK,GAAG,IAAI,MAAM,UAAU,EAAE,KAAK,CAAC,CAAC;AACrD,mBAAe,KAAK,GAAG,IAAI,MAAM,UAAU,EAAE,KAAK,CAAC,CAAC;AAAA,EACtD;AACA,QAAM,SAAS,EAAE,gBAAgB;AACjC,MAAI,oBAAoB;AACtB,WAAO,oBAAoB;AAAA,EAC7B;AACA,MAAI,oBAAoB;AACtB,WAAO,kBAAkB;AAAA,EAC3B;AACA,SAAO;AACT;AACA,SAAS,sBAAsB,OAAO,IAAI,GAAG;AAC3C,QAAM,SAAS,MAAM,SAAS,KAAK,GAAG,KAAK,IAAI,CAAC;AAChD,QAAM,SAAS,MAAM,SAAS,IAAI,GAAG,IAAI,IAAI,CAAC;AAC9C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,SAAS,QAAQ,UAAU,QAAQ;AACzC,QAAM,SAAS,QAAQ,UAAU,QAAQ;AACzC,MAAI,SAAS,KAAK,SAAS,GAAG;AAC5B,WAAO;AAAA,EACT;AACA,QAAM,mBAAmB,KAAK,IAAI,OAAO,KAAK;AAC9C,QAAM,mBAAmB,KAAK,IAAI,OAAO,KAAK;AAC9C,QAAM,mBAAmB,KAAK,IAAI,OAAO,KAAK;AAC9C,QAAM,mBAAmB,KAAK,IAAI,OAAO,KAAK;AAC9C,QAAM,mBAAmB,KAAK,IAAI,mBAAmB,kBAAkB,CAAC,IAAI,KAAK,IAAI,mBAAmB,kBAAkB,CAAC;AAC3H,SAAO,oBAAoB,QAAQ,QAAQ;AAC7C;AACA,SAAS,eAAe,cAAcA,SAAQ,KAAK;AACjD,QAAM,SAAS,KAAK,IAAIA,UAAS,MAAM,GAAG;AAC1C,SAAO,OAAO,eAAe,SAAS;AACxC;AACA,SAAS,oBAAoB,IAAI,IAAI;AACnC,SAAO,GAAG,QAAQ,GAAG,SAAS,GAAG,UAAU,GAAG,SAAS,GAAG,WAAW,GAAG;AAC1E;AAGA,eAAe,wBAAwB,OAAO,QAAQ,eAAe,eAAe,KAAK,iBAAiB,OAAO,mBAAmB;AAClI,QAAM,SAAS,gBAAgB,OAAO,SAAS,wBAAwB;AACvE,QAAM,UAAU,gBAAgB,QAAQ,UAAU,wBAAwB;AAC1E,QAAM,SAAS,sBAAsB,QAAQ,SAAS,eAAe,cAAc,cAAc;AACjG,kBAAgB,OAAO;AACvB,iBAAe,OAAO;AACtB,mBAAiB,OAAO;AACxB,QAAM,iBAAiB,MAAM,QAAQ,IAAI,CAAC,OAAO,KAAK,GAAG,QAAQ,KAAK,CAAC,CAAC;AACxE,QAAM,YAAY,eAAe;AACjC,QAAM,aAAa,eAAe;AAClC,QAAM,EAAE,gBAAgB,IAAI,wBAAwB,WAAW,YAAY,eAAe,cAAc,cAAc;AACtH,MAAI,WAAW,OAAO;AACpB,WAAO,QAAQ;AAAA,EACjB;AACA,MAAI,YAAY,QAAQ;AACtB,YAAQ,QAAQ;AAAA,EAClB;AACA,SAAO,SAAS,iBAAiB,OAAO;AAC1C;AACA,IAAI,yBAAyB;AAG7B,SAAS,4BAA4B,OAAO,QAAQ,eAAe,eAAe,KAAK,iBAAiB,OAAO,mBAAmB,eAAe,GAAG;AAClJ,QAAM,SAAS,gBAAgB,OAAO,SAAS,mBAAmB;AAClE,QAAM,UAAU,gBAAgB,QAAQ,UAAU,mBAAmB;AACrE,QAAM,SAAS,sBAAsB,QAAQ,SAAS,eAAe,cAAc,gBAAgB,YAAY;AAC/G,kBAAgB,OAAO;AACvB,iBAAe,OAAO;AACtB,mBAAiB,OAAO;AACxB,iBAAe,OAAO;AACtB,QAAM,SAAS,EAAE,OAAO,QAAQ,QAAQ,QAAQ;AAChD,QAAM,QAAQ,EAAE,eAAe,cAAc,gBAAgB,aAAa;AAC1E,QAAM,SAAS,OAAO,UAAU,qBAAqB,QAAQ,KAAK;AAClE,SAAO,EAAE,iBAAiB,OAAO,IAAI,gBAAgB,OAAO,GAAG;AACjE;AACA,IAAI,6BAA6B,GAAG,EAAE,4BAA4B,CAAC;AAGnE,eAAe,iCAAiC,OAAO,QAAQ,eAAe,eAAe,KAAK,iBAAiB,OAAO,mBAAmB,eAAe,GAAG;AAC7J,QAAM,SAAS,gBAAgB,OAAO,SAAS,wBAAwB;AACvE,QAAM,UAAU,gBAAgB,QAAQ,UAAU,wBAAwB;AAC1E,QAAM,SAAS,sBAAsB,QAAQ,SAAS,eAAe,cAAc,gBAAgB,YAAY;AAC/G,kBAAgB,OAAO;AACvB,iBAAe,OAAO;AACtB,mBAAiB,OAAO;AACxB,iBAAe,OAAO;AACtB,QAAM,iBAAiB,MAAM,QAAQ,IAAI,CAAC,OAAO,KAAK,GAAG,QAAQ,KAAK,CAAC,CAAC;AACxE,QAAM,YAAY,eAAe;AACjC,QAAM,aAAa,eAAe;AAClC,QAAM,EAAE,iBAAiB,eAAe,IAAI,wBAAwB,WAAW,YAAY,eAAe,cAAc,gBAAgB,YAAY;AACpJ,MAAI,WAAW,OAAO;AACpB,WAAO,QAAQ;AAAA,EACjB;AACA,MAAI,YAAY,QAAQ;AACtB,YAAQ,QAAQ;AAAA,EAClB;AACA,SAAO;AAAA,IACL,iBAAiB,SAAS,iBAAiB,OAAO;AAAA,IAClD,gBAAgB,SAAS,cAAc;AAAA,EACzC;AACF;AACA,IAAI,kCAAkC;AAGtC,SAAS,yBAAyB,OAAO,QAAQ,eAAe,eAAe,KAAK,iBAAiB,OAAO,mBAAmB,qBAAqB,OAAO;AACzJ,QAAM,SAAS,gBAAgB,OAAO,SAAS,mBAAmB;AAClE,QAAM,UAAU,gBAAgB,QAAQ,UAAU,mBAAmB;AACrE,QAAM,SAAS,sBAAsB,QAAQ,SAAS,eAAe,cAAc,gBAAgB,IAAI;AACvG,QAAM,iBAAiB,OAAO;AAC9B,QAAM,gBAAgB,OAAO;AAC7B,QAAM,kBAAkB,OAAO;AAC/B,QAAM,SAAS,EAAE,OAAO,QAAQ,QAAQ,QAAQ;AAChD,QAAM,QAAQ;AAAA,IACZ,eAAe;AAAA,IACf,cAAc;AAAA,IACd,gBAAgB;AAAA,IAChB;AAAA,EACF;AACA,QAAM,SAAS,OAAO,UAAU,qBAAqB,QAAQ,KAAK;AAClE,SAAO,EAAE,iBAAiB,OAAO,IAAI,cAAc,OAAO,GAAG;AAC/D;AACA,IAAI,0BAA0B,GAAG,EAAE,yBAAyB,CAAC;AAG7D,eAAe,8BAA8B,OAAO,QAAQ,eAAe,eAAe,KAAK,iBAAiB,OAAO,mBAAmB,qBAAqB,OAAO;AACpK,QAAM,SAAS,gBAAgB,OAAO,SAAS,wBAAwB;AACvE,QAAM,UAAU,gBAAgB,QAAQ,UAAU,wBAAwB;AAC1E,QAAM,SAAS,sBAAsB,QAAQ,SAAS,eAAe,cAAc,gBAAgB,IAAI;AACvG,QAAM,iBAAiB,OAAO;AAC9B,QAAM,gBAAgB,OAAO;AAC7B,QAAM,kBAAkB,OAAO;AAC/B,QAAM,CAAC,WAAW,UAAU,IAAI,MAAM,QAAQ,IAAI,CAAC,OAAO,KAAK,GAAG,QAAQ,KAAK,CAAC,CAAC;AACjF,QAAM,EAAE,iBAAiB,aAAa,IAAI,wBAAwB,WAAW,YAAY,gBAAgB,eAAe,iBAAiB,kBAAkB;AAC3J,MAAI,WAAW,OAAO;AACpB,WAAO,QAAQ;AAAA,EACjB;AACA,MAAI,YAAY,QAAQ;AACtB,YAAQ,QAAQ;AAAA,EAClB;AACA,SAAO;AAAA,IACL,iBAAiB,SAAS,iBAAiB,OAAO;AAAA,IAClD,cAAc,OAAO,cAAc,OAAO;AAAA,EAC5C;AACF;AACA,IAAI,+BAA+B;AAGnC,SAAS,gBAAgB,QAAQrB,OAAM,eAAe,OAAO,mBAAmB,OAAO;AACrF,QAAM,UAAU,gBAAgB,QAAQ,UAAU,gBAAgB;AAClE,SAAO,QAAQ,SAAS,KAAK,QAAQ,SAAS,GAAG,MAAM,gEAAgE,QAAQ,OAAO;AACtI,SAAOA,MAAK,WAAW,GAAG,MAAM,6DAA6DA,QAAO;AACpG,SAAO,qBAAqB,SAAS,iBAAiB,OAAO,MAAM,mFAAmF;AACtJ,MAAI,cAAc;AAClB,MAAI,eAAe;AACnB,MAAI,QAAQ,SAAS,GAAG;AACtB,mBAAe;AACf,kBAAc,QAAQ,SAAS,CAAC,GAAG,QAAQ,MAAM,IAAI,QAAQ,MAAM,IAAI,QAAQ,MAAM,EAAE,CAAC;AAAA,EAC1F;AACA,QAAM,CAAC,IAAIA;AACX,QAAM,SAAS,EAAE,QAAQ,YAAY;AACrC,QAAM,QAAQ,EAAE,cAAc,kBAAkB,MAAAA,MAAK;AACrD,QAAM,MAAM,OAAO,UAAU,gBAAgB,QAAQ,KAAK;AAC1D,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,iBAAiB,GAAG,EAAE,gBAAgB,CAAC;AAG3C,SAAS,uBAAuB,QAAQA,OAAM,eAAe,OAAO,mBAAmB,OAAO;AAC5F,QAAM,UAAU,gBAAgB,QAAQ,UAAU,uBAAuB;AACzE,SAAO,QAAQ,SAAS,KAAK,QAAQ,SAAS,GAAG,MAAM,uEAAuE,QAAQ,OAAO;AAC7I,SAAOA,MAAK,WAAW,GAAG,MAAM,oEAAoEA,QAAO;AAC3G,SAAO,QAAQ,UAAU,aAAa,QAAQ,UAAU,SAAS,MAAM,kDAAkD;AACzH,SAAO,qBAAqB,SAAS,iBAAiB,OAAO,MAAM,0FAA0F;AAC7J,MAAI,cAAc;AAClB,MAAI,eAAe;AACnB,MAAI,QAAQ,SAAS,GAAG;AACtB,mBAAe;AACf,kBAAc,QAAQ,SAAS,CAAC,GAAG,QAAQ,MAAM,IAAI,QAAQ,MAAM,IAAI,QAAQ,MAAM,EAAE,CAAC;AAAA,EAC1F;AACA,QAAM,CAAC,IAAIA;AACX,QAAM,SAAS,EAAE,QAAQ,YAAY;AACrC,QAAM,QAAQ,EAAE,cAAc,kBAAkB,MAAAA,MAAK;AACrD,QAAM,MAAM,OAAO,UAAU,uBAAuB,QAAQ,KAAK;AACjE,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,wBAAwB,GAAG,EAAE,uBAAuB,CAAC;AAGzD,SAAS,WAAW,QAAQ,SAAS,UAAU,WAAW,OAAO,cAAc,KAAK;AAClF,QAAM,SAAS,gBAAgB,QAAQ,SAAS,WAAW;AAC3D,QAAM,qBAAqB;AAC3B,QAAM,uBAAuB;AAC7B,QAAM,sBAAsB;AAC5B,QAAM,qBAAqB,OAAO,MAAM,KAAK,OAAO,MAAM;AAC1D,MAAI,aAAa,IAAI,SAAS,CAAC,WAAW,CAAC,GAAG,GAAG;AACjD,MAAI,IAAI,GAAG,GAAG;AACd,SAAO,OAAO,SAAS,GAAG,MAAM,yDAAyD,OAAO,OAAO;AACvG,SAAO,OAAO,MAAM,OAAO,KAAK,OAAO,MAAM,OAAO,GAAG,MAAM,0EAA0E,OAAO,MAAM,KAAK;AACzJ,SAAO,OAAO,UAAU,WAAW,OAAO,UAAU,WAAW,MAAM,sEAAsE,OAAO,QAAQ;AAC1J,SAAO,WAAW,UAAU,WAAW,UAAU,MAAM,0CAA0C,QAAQ;AACzG,MAAI,OAAO,MAAM,OAAO,GAAG;AACzB,KAAC,IAAI,GAAG,CAAC,IAAI,MAAM,QAAQ,CAAC,GAAG,GAAG,CAAC,GAAG,EAAE;AACxC,UAAM,KAAK,IAAI,IAAI,kBAAkB;AACrC,UAAM,KAAK,IAAI,GAAG,oBAAoB;AACtC,UAAM,KAAK,IAAI,GAAG,mBAAmB;AACrC,gBAAY,KAAK,KAAK,IAAI,EAAE,GAAG,EAAE;AAAA,EACnC,OAAO;AACL,gBAAY;AAAA,EACd;AACA,MAAI,WAAW,QAAQ;AACrB,UAAM,aAAa,SAAS,KAAK,OAAO,SAAS,GAAG,OAAO,GAAG,OAAO,CAAC,CAAC,GAAG,GAAG;AAC7E,iBAAa,KAAK,YAAY,kBAAkB;AAAA,EAClD;AACA,QAAM,eAAe,WAAW,UAAU,WAAW,UAAU,IAAI,QAAQ,WAAW,UAAU;AAChG,QAAM,SAAS,KAAK,IAAI,cAAc,GAAG,GAAG,OAAO;AACnD,SAAO;AACT;AACA,SAAS,KAAK,WAAW,OAAO;AAC9B,MAAI,aAAa,SAAS,CAAC,EAAE,CAAC;AAC9B,MAAI,eAAe,SAAS,CAAC,CAAC,CAAC;AAC/B,MAAI,YAAY,SAAS,CAAC,CAAC,CAAC;AAC5B,MAAI,YAAY,aAAa,WAAW,SAAS,kBAAkB;AACnE,WAASS,SAAQ,GAAGA,SAAQ,UAAU,OAAO,GAAGA,UAAS;AACvD,iBAAa,MAAM,WAAW,GAAGA,SAAQ,CAAC;AAC1C,kBAAc,MAAM,WAAWA,SAAQ,CAAC;AACxC,uBAAmB,IAAI,KAAK,UAAU,GAAG,KAAK;AAC9C,iBAAa,IAAI,KAAK,WAAW,GAAG,KAAK;AACzC,UAAM,gBAAgB,KAAK,IAAI,YAAY,MAAM,GAAG,WAAW,IAAI,CAAC,CAAC;AACrE,gBAAY,IAAI,eAAe,KAAK,UAAU,CAAC;AAC/C,UAAM,cAAc,KAAK,YAAY,OAAO,WAAW,IAAI;AAC3D,UAAM,aAAa,KAAK,MAAM,GAAG,YAAY,IAAI,GAAG,WAAW;AAC/D,UAAM,aAAa,IAAI,aAAa,UAAU;AAC9C,cAAU,IAAI,KAAK,UAAU,GAAG,KAAK,WAAW,CAAC;AACjD,UAAM,gBAAgB,IAAI,WAAW,OAAO;AAC5C,UAAM,gBAAgB,IAAI,WAAW,OAAO;AAC5C,UAAM,eAAe,IAAI,kBAAkB,UAAU;AACrD,gBAAY,IAAI,IAAI,cAAc,aAAa,GAAG,aAAa;AAC/D,UAAM,YAAY,QAAQ,WAAW,YAAY;AACjD,mBAAe,MAAM,WAAW,WAAW,YAAY;AACvD,iBAAa,MAAM,WAAW,SAAS,CAACA,MAAK,CAAC,GAAG,UAAU;AAAA,EAC7D;AACA,SAAO;AACT;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,WAAW,QAAQ,YAAY,gBAAgB,WAAW,WAAW,YAAY,YAAY,GAAG,aAAa;AACpH,QAAM,SAAS,gBAAgB,QAAQ,SAAS,aAAa,SAAS;AACtE,QAAM,cAAc,gBAAgB,YAAY,cAAc,aAAa,SAAS;AACpF,SAAO,OAAO,SAAS,GAAG,MAAM,yDAAyD,OAAO,OAAO;AACvG,SAAO,YAAY,SAAS,MAAM,YAAY,MAAM,OAAO,OAAO,MAAM,MAAM,YAAY,MAAM,OAAO,MAAM,YAAY,MAAM,OAAO,GAAG,MAAM,kEAAkE;AACjN,SAAO,eAAe,QAAQ,YAAY,WAAW,GAAG,MAAM,4EAA4E,cAAc;AACxJ,QAAM,SAAS,EAAE,OAAO,QAAQ,YAAY,YAAY;AACxD,QAAM,QAAQ,EAAE,eAAe,UAAU,WAAW,YAAY;AAChE,SAAO,OAAO,UAAU,WAAW,QAAQ,KAAK;AAClD;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,UAAU,GAAG,UAAU,UAAU;AACxC,SAAO,WAAW,MAAM,GAAG,MAAM,gDAAgD,WAAW;AAC5F,SAAO,WAAW,MAAM,GAAG,MAAM,gDAAgD,WAAW;AAC5F,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU;AAC7C,SAAO,GAAG,QAAQ,GAAG,MAAM,4CAA4C,GAAG,OAAO;AACjF,QAAM,QAAQ,GAAG;AACjB,QAAM,CAAC,GAAG,CAAC,IAAI,GAAG,MAAM,MAAM,EAAE;AAChC,MAAI,EAAE,YAAY,IAAI;AACpB,UAAM,IAAI,MAAM,yBAAyB,0DAA0D,KAAK;AAAA,EAC1G;AACA,MAAI,EAAE,YAAY,IAAI;AACpB,UAAM,IAAI,MAAM,yBAAyB,6DAA6D,KAAK;AAAA,EAC7G;AACA,MAAI,WAAW,GAAG;AAChB,eAAW;AAAA,EACb;AACA,MAAI,WAAW,GAAG;AAChB,eAAW;AAAA,EACb;AACA,QAAM,KAAK,QAAQ,MAAM,GAAG,GAAG,GAAG,OAAO,GAAG,CAAC,IAAI,CAAC,CAAC;AACnD,QAAM,IAAI,MAAM,GAAG,GAAG,GAAG,OAAO;AAChC,QAAM,KAAK,IAAI,IAAI,CAAC;AACpB,QAAM,SAAS,WAAW,UAAU,IAAI,OAAO,CAAC,UAAU,OAAO,CAAC,GAAG,aAAa,IAAI,OAAO,CAAC,UAAU,OAAO,CAAC,CAAC;AACjH,QAAM,OAAO,MAAM,CAAC,GAAG,CAAC,GAAG,GAAG,KAAK;AACnC,SAAO,QAAQ,MAAM,QAAQ,QAAQ,IAAI,CAAC,IAAI,GAAG,CAAC,CAAC,CAAC,EAAE,IAAI,CAAC,QAAQ,MAAM,QAAQ,KAAK,IAAI,CAAC,CAAC,GAAG,KAAK;AACtG;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,aAAa,IAAI;AACxB,MAAI;AACJ,MAAI,MAAM,QAAQ,EAAE,GAAG;AACrB,sBAAkB;AAClB,WAAO,MAAM,QAAQ,GAAG,SAAS,GAAG,MAAM,mEAAmE;AAC7G,UAAM,MAAM,GAAG,GAAG,MAAM;AACxB,aAAS,KAAK,GAAG,KAAK,GAAG,QAAQ,EAAE,IAAI;AACrC,aAAO,GAAG,IAAI,MAAM,OAAO,KAAK,MAAM,iEAAiE,GAAG,IAAI,MAAM,UAAU,MAAM;AAAA,IACtI;AAAA,EACF,OAAO;AACL,sBAAkB;AAClB,SAAK,MAAM,IAAI,GAAG,MAAM,IAAI,CAAC,EAAE,IAAI,CAAC,MAAM,QAAQ,GAAG,CAAC,CAAC,CAAC,CAAC;AAAA,EAC3D;AACA,SAAO,GAAG,UAAU,GAAG,GAAG,MAAM,IAAI,MAAM,oCAAoC,GAAG,yCAAyC,GAAG,GAAG,MAAM,MAAM;AAC5I,QAAM,KAAK,CAAC;AACZ,QAAM,OAAO;AACb,WAAS,KAAK,GAAG,KAAK,GAAG,QAAQ,EAAE,IAAI;AACrC,OAAG,KAAK,OAAO,KAAK,MAAM;AACxB,UAAI,IAAI,KAAK;AACb,UAAI,KAAK,GAAG;AACV,iBAAS,IAAI,GAAG,IAAI,IAAI,EAAE,GAAG;AAC3B,gBAAM,OAAO,IAAI,KAAK,IAAI,GAAG,IAAI,CAAC,CAAC,GAAG,GAAG,EAAE;AAC3C,cAAI,IAAI,GAAG,IAAI;AAAA,QACjB;AAAA,MACF;AACA,aAAO,IAAI,GAAG,KAAK,GAAG,WAAW,CAAC;AAAA,IACpC,CAAC,CAAC;AAAA,EACJ;AACA,MAAI,iBAAiB;AACnB,WAAO,MAAM,IAAI,CAAC;AAAA,EACpB,OAAO;AACL,WAAO;AAAA,EACT;AACF;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,IAAI,GAAG,eAAe,OAAO;AACpC,SAAO,EAAE,QAAQ,GAAG,MAAM,gEAAgE,EAAE,MAAM;AAClG,MAAI,EAAE,SAAS,GAAG;AAChB,WAAO,KAAK,GAAG,YAAY;AAAA,EAC7B,OAAO;AACL,UAAM,gBAAgB,EAAE,MAAM,MAAM,GAAG,EAAE,MAAM,SAAS,CAAC,EAAE,OAAO,CAAC,OAAO,SAAS,QAAQ,IAAI;AAC/F,UAAM,OAAO,QAAQ,QAAQ,GAAG;AAAA,MAC9B;AAAA,MACA,EAAE,MAAM,EAAE,MAAM,SAAS;AAAA,MACzB,EAAE,MAAM,EAAE,MAAM,SAAS;AAAA,IAC3B,CAAC,GAAG,CAAC;AACL,UAAM,OAAO,CAAC;AACd,UAAM,OAAO,CAAC;AACd,SAAK,QAAQ,CAAC,QAAQ;AACpB,YAAM,CAAC,KAAK,GAAG,IAAI,KAAK,KAAK,YAAY;AACzC,WAAK,KAAK,GAAG;AACb,WAAK,KAAK,GAAG;AAAA,IACf,CAAC;AACD,UAAM,IAAI,QAAQ,MAAM,MAAM,CAAC,GAAG,EAAE,KAAK;AACzC,UAAM,KAAK,QAAQ,MAAM,MAAM,CAAC,GAAG,EAAE,KAAK;AAC1C,WAAO,CAAC,GAAG,EAAE;AAAA,EACf;AACF;AACA,SAAS,KAAK,GAAG,eAAe,OAAO;AACrC,SAAO,OAAO,KAAK,MAAM;AACvB,WAAO,EAAE,MAAM,WAAW,GAAG,MAAM,0CAA0C,EAAE,MAAM,iBAAiB;AACtG,UAAM,IAAI,EAAE,MAAM;AAClB,UAAM,KAAK,EAAE,MAAM;AACnB,QAAI,IAAI,IAAI,CAAC;AACb,QAAI,KAAK,MAAM,CAAC;AAChB,UAAM,QAAQ,SAAS,CAAC,CAAC,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AACpC,QAAI,IAAI,MAAM,KAAK;AACnB,UAAM,QAAQ,KAAK,KAAK,KAAK;AAC7B,aAAS,IAAI,GAAG,IAAI,OAAO,EAAE,GAAG;AAC9B,YAAM,QAAQ;AACd,YAAM,QAAQ;AACd,YAAM,QAAQ;AACd,OAAC,GAAG,IAAI,CAAC,IAAI,OAAO,KAAK,MAAM;AAC7B,cAAM,SAAS,MAAM,IAAI,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,GAAG,CAAC,CAAC;AAC3C,cAAM,QAAQ,KAAK,MAAM;AACzB,cAAM,MAAM,MAAM,IAAI,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AACpC,cAAM,KAAK,MAAM,QAAQ,KAAK,CAAC,GAAG,SAAS,CAAC,CAAC,EAAE,CAAC,CAAC,GAAG,SAAS,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;AACnE,cAAM,KAAK,IAAI,KAAK,IAAI,IAAI,KAAK,CAAC;AAClC,cAAM,OAAO,IAAI,QAAQ,EAAE;AAC3B,YAAI,KAAK,MAAM,OAAO,GAAG;AACvB,cAAI,MAAM,KAAK;AAAA,QACjB,OAAO;AACL,cAAI,OAAO;AAAA,YACT;AAAA,YACA,MAAM,MAAM,CAAC,GAAG,CAAC,GAAG,CAAC,KAAK,MAAM,KAAK,GAAG,KAAK,MAAM,EAAE,CAAC;AAAA,UACxD,GAAG,CAAC;AAAA,QACN;AACA,cAAM,MAAM,IAAI,IAAI,OAAO,IAAI,EAAE,GAAG,KAAK,CAAC;AAC1C,cAAM,WAAW,MAAM,IAAI,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,GAAG,EAAE,CAAC;AAC9C,cAAM,YAAY,IAAI,KAAK,CAAC;AAC5B,cAAM,KAAK,UAAU,CAAC;AACtB,YAAI,MAAM,GAAG;AACX,eAAK,IAAI,UAAU,OAAO,WAAW,OAAO,IAAI,QAAQ,CAAC,CAAC;AAAA,QAC5D,OAAO;AACL,gBAAM,YAAY,IAAI,UAAU,OAAO,WAAW,OAAO,IAAI,QAAQ,CAAC,CAAC;AACvE,eAAK,OAAO,CAAC,MAAM,IAAI,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,EAAE,CAAC,GAAG,SAAS,GAAG,CAAC;AAAA,QACxD;AACA,cAAM,aAAa,UAAU,SAAS;AACtC,cAAM,WAAW,MAAM,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,EAAE,MAAM,KAAK,CAAC,CAAC;AACrD,YAAI,MAAM,GAAG;AACX,cAAI,IAAI,UAAU,OAAO,OAAO,UAAU,CAAC,GAAG,UAAU,CAAC;AAAA,QAC3D,OAAO;AACL,gBAAM,YAAY,IAAI,UAAU,OAAO,OAAO,UAAU,CAAC,GAAG,UAAU,CAAC;AACvE,cAAI,OAAO,CAAC,MAAM,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC,GAAG,SAAS,GAAG,CAAC;AAAA,QACrD;AACA,eAAO,CAAC,GAAG,IAAI,CAAC;AAAA,MAClB,CAAC;AACD,cAAQ,CAAC,OAAO,OAAO,KAAK,CAAC;AAAA,IAC/B;AACA,QAAI,CAAC,gBAAgB,IAAI,IAAI;AAC3B,UAAI,MAAM,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,EAAE,CAAC;AAC5B,WAAK,MAAM,IAAI,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,EAAE,CAAC;AAAA,IACjC;AACA,WAAO,CAAC,GAAG,EAAE;AAAA,EACf,CAAC;AACH;AACA,IAAI,KAAK,GAAG,EAAE,IAAI,CAAC;AAGnB,IAAI;AAAA,CACH,SAAS,YAAY;AACpB,aAAW,WAAW,UAAU,KAAK;AACrC,aAAW,WAAW,UAAU,KAAK;AACrC,aAAW,WAAW,SAAS,KAAK;AACpC,aAAW,WAAW,4BAA4B,KAAK;AACzD,GAAG,cAAc,YAAY,CAAC,EAAE;AAGhC,SAAS,qBAAqB,SAAS,SAAS,YAAY,UAAU,wBAAwB;AAC5F,QAAM,UAAU,gBAAgB,SAAS,UAAU,qBAAqB;AACxE,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,qBAAqB;AAAA,EACtE;AACA,QAAM,eAAe,YAAY,OAAO,UAAU,IAAI,SAAS,QAAQ;AACvE,MAAI,cAAc,UAAU,MAAM;AAChC,WAAO;AAAA,EACT;AACA,MAAI,cAAc,UAAU,KAAK;AAC/B,WAAO,KAAK,YAAY;AAAA,EAC1B;AACA,MAAI,cAAc,UAAU,MAAM;AAChC,QAAI,YAAY,MAAM;AACpB,aAAO,KAAK,YAAY;AAAA,IAC1B,OAAO;AACL,YAAM,kBAAkB,QAAQ,OAAO,SAAS;AAChD,YAAM,SAAS,IAAI,KAAK,YAAY,GAAG,KAAK,QAAQ,CAAC;AACrD,aAAO,kBAAkB,IAAI,IAAI,QAAQ,OAAO,eAAe,CAAC,IAAI;AAAA,IACtE;AAAA,EACF;AACA,MAAI,cAAc,UAAU,wBAAwB;AAClD,QAAI,YAAY,MAAM;AACpB,aAAO,IAAI,KAAK,YAAY,GAAG,OAAO,QAAQ,IAAI,CAAC;AAAA,IACrD,OAAO;AACL,YAAM,qBAAqB,IAAI,UAAU,MAAM,QAAQ,KAAK,CAAC;AAC7D,YAAM,cAAc,KAAK,KAAK,SAAS,oBAAoB,OAAO,CAAC,CAAC,CAAC,GAAG,SAAS;AACjF,aAAO,IAAI,KAAK,YAAY,GAAG,WAAW;AAAA,IAC5C;AAAA,EACF;AACA,QAAM,MAAM,sBAAsB,WAAW;AAC/C;AACA,IAAI,sBAAsB,GAAG,EAAE,qBAAqB,CAAC;AAGrD,SAAS,oBAAoBU,SAAQ,aAAa,SAAS,YAAY,UAAU,wBAAwB;AACvG,QAAM,UAAU,gBAAgBA,SAAQ,UAAU,oBAAoB;AACtE,QAAM,eAAe,gBAAgB,aAAa,eAAe,oBAAoB;AACrF,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,oBAAoB;AAAA,EACrE;AACA,oBAAkB,QAAQ,OAAO,aAAa,OAAO,+BAA+B;AACpF,QAAM,UAAU,IAAI,IAAI,SAAS,YAAY,CAAC;AAC9C,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,qBAAqB,GAAG,EAAE,oBAAoB,CAAC;AAGnD,SAAS,gBAAgBA,SAAQ,aAAa,MAAM,SAAS,YAAY,UAAU,wBAAwB;AACzG,QAAM,UAAU,gBAAgBA,SAAQ,UAAU,gBAAgB;AAClE,QAAM,eAAe,gBAAgB,aAAa,eAAe,gBAAgB;AACjF,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,gBAAgB;AAAA,EACjE;AACA,oBAAkB,QAAQ,OAAO,aAAa,OAAO,2BAA2B;AAChF,QAAM,MAAM,OAAO,CAAC;AACpB,QAAM,UAAU,IAAI,KAAK,KAAK,IAAI,SAAS,YAAY,GAAG,MAAM,IAAI,CAAC;AACrE,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,iBAAiB,GAAG,EAAE,gBAAgB,CAAC;AAG3C,SAAS,WAAWA,SAAQ,aAAa,SAAS,YAAY,UAAU,wBAAwB;AAC9F,MAAI,UAAU,gBAAgBA,SAAQ,UAAU,WAAW;AAC3D,QAAM,eAAe,gBAAgB,aAAa,eAAe,WAAW;AAC5E,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,WAAW;AAAA,EAC5D;AACA,oBAAkB,QAAQ,OAAO,aAAa,OAAO,sBAAsB;AAC3E,QAAM,MAAM,OAAO,CAAC;AACpB,YAAU,IAAI,IAAI,OAAO,CAAC,GAAG,OAAO,GAAG,GAAG;AAC1C,QAAM,UAAU,KAAK,IAAI,KAAK,IAAI,SAAS,YAAY,CAAC,CAAC;AACzD,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,WAAWA,SAAQ,aAAa,SAAS,QAAQ,GAAG,YAAY,UAAU,wBAAwB;AACzG,QAAM,UAAU,gBAAgBA,SAAQ,UAAU,WAAW;AAC7D,QAAM,eAAe,gBAAgB,aAAa,eAAe,WAAW;AAC5E,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,WAAW;AAAA,EAC5D;AACA,oBAAkB,QAAQ,OAAO,aAAa,OAAO,sBAAsB;AAC3E,QAAM,cAAc,OAAO,KAAK;AAChC,QAAM,QAAQ,IAAI,IAAI,cAAc,OAAO,CAAC;AAC5C,QAAM,YAAY,QAAQ,OAAO,WAAW;AAC5C,QAAM,SAAS,IAAI,OAAO,SAAS;AACnC,QAAM,UAAU,KAAK,IAAI,OAAO,GAAG,GAAG,OAAO,SAAS,CAAC,GAAG,IAAI,aAAa,MAAM,CAAC;AAClF,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,SAASA,SAAQ,aAAa,SAAS,WAAW,MAAM,YAAY,UAAU,wBAAwB;AAC7G,QAAM,UAAU,gBAAgBA,SAAQ,UAAU,SAAS;AAC3D,QAAM,eAAe,gBAAgB,aAAa,eAAe,SAAS;AAC1E,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,SAAS;AAAA,EAC1D;AACA,oBAAkB,QAAQ,OAAO,aAAa,OAAO,oBAAoB;AACzE,QAAM,MAAM,OAAO,CAAC;AACpB,QAAM,gBAAgB,OAAO,QAAQ;AACrC,QAAM,MAAM,IAAI,IAAI,SAASxB,MAAK,KAAK,cAAc,aAAa,CAAC,CAAC,CAAC;AACrE,QAAM,MAAM,IAAI,IAAI,KAAK,OAAO,GAAGA,MAAK,KAAK,IAAI,KAAK,YAAY,GAAG,aAAa,CAAC,CAAC;AACpF,QAAM,UAAU,IAAI,KAAK,GAAG;AAC5B,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,kBAAkBwB,SAAQ,aAAa,SAAS,YAAY,UAAU,wBAAwB;AACrG,QAAM,UAAU,gBAAgBA,SAAQ,UAAU,kBAAkB;AACpE,QAAM,eAAe,gBAAgB,aAAa,eAAe,kBAAkB;AACnF,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,kBAAkB;AAAA,EACnE;AACA,oBAAkB,QAAQ,OAAO,aAAa,OAAO,6BAA6B;AAClF,QAAM,UAAU,kBAAkB,SAAS,YAAY;AACvD,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,mBAAmB,GAAG,EAAE,kBAAkB,CAAC;AAG/C,SAAS,+BAA+BA,SAAQ,QAAQ;AACtD,QAAM,UAAU,gBAAgBA,SAAQ,UAAU,+BAA+B;AACjF,QAAM,UAAU,gBAAgB,QAAQ,UAAU,+BAA+B;AACjF,oBAAkB,QAAQ,OAAO,QAAQ,OAAO,0CAA0C;AAC1F,QAAM,YAAY,KAAK,OAAO;AAC9B,QAAM,gBAAgB,IAAI,SAAS,OAAO;AAC1C,QAAM,gBAAgB,MAAM,IAAI,IAAI,IAAI,OAAO,CAAC,CAAC,CAAC;AAClD,SAAO,KAAK,IAAI,WAAW,aAAa,GAAG,aAAa;AAC1D;AACA,SAAS,qBAAqB,kBAAkB,QAAQ,SAAS,iBAAiB,GAAG,YAAY,UAAU,wBAAwB;AACjI,MAAI,oBAAoB,gBAAgB,kBAAkB,oBAAoB,qBAAqB;AACnG,QAAM,UAAU,gBAAgB,QAAQ,UAAU,qBAAqB;AACvE,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,qBAAqB;AAAA,EACtE;AACA,oBAAkB,kBAAkB,OAAO,QAAQ,OAAO,gCAAgC;AAC1F,MAAI,iBAAiB,GAAG;AACtB,UAAM,uBAAuB,OAAO,cAAc;AAClD,UAAM,MAAM,OAAO,CAAC;AACpB,UAAMI,QAAO,OAAO,GAAG;AACvB,wBAAoB,KAAK,IAAI,mBAAmB,IAAI,KAAK,oBAAoB,CAAC,GAAG,IAAIA,OAAM,oBAAoB,CAAC;AAAA,EAClH;AACA,QAAM,UAAU,+BAA+B,mBAAmB,OAAO;AACzE,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,sBAAsB,GAAG,EAAE,qBAAqB,CAAC;AAGrD,SAAS,+BAA+BJ,SAAQ,QAAQ,MAAM,IAAI;AAChE,MAAI,QAAQ,IAAI;AACd,UAAM,OAAO,OAAO;AAAA,EACtB;AACA,MAAI,QAAQ,OAAO,OAAO,GAAG;AAC3B,UAAM,MAAM,mGAAmG,OAAO,oBAAoB,KAAK;AAAA,EACjJ;AACA,QAAM,WAAW,WAAW,CAACM,UAAS,SAAS,SAAS;AACtD,UAAM,WAAW;AACjB,UAAM,MAAM,UAAU,SAAS,CAAC,GAAG,GAAG,QAAQ;AAC9C,UAAM,YAAY,IAAI,KAAK,SAAS,SAAS,GAAG,GAAG;AACnD,SAAK,CAACA,UAAS,SAAS,CAAC;AACzB,UAAM,aAAa,IAAI,IAAI,WAAWA,QAAO,CAAC;AAC9C,UAAM,QAAQ,KAAK,YAAY,CAAC,GAAG,CAAC;AACpC,UAAM,WAAW,CAAC,IAAI,UAAU;AAC9B,YAAM,CAAC,SAAS,UAAU,IAAI;AAC9B,YAAM,UAAU,qBAAqB,GAAG,OAAO,CAAC,GAAG,CAAC;AACpD,aAAO;AAAA,QACL,IAAI,QAAQ,IAAI,OAAO,GAAG,IAAI,KAAK,SAAS,SAAS,GAAG,IAAI,UAAU,CAAC,CAAC;AAAA,QACxE,IAAI,QAAQ,IAAI,OAAO,GAAG,IAAI,IAAI,UAAU,GAAG,KAAK,SAAS,SAAS,CAAC,CAAC;AAAA,MAC1E;AAAA,IACF;AACA,WAAO,EAAE,OAAO,SAAS;AAAA,EAC3B,CAAC;AACD,SAAO,SAASN,SAAQ,MAAM;AAChC;AACA,SAAS,qBAAqB,cAAc,QAAQ,SAAS,iBAAiB,GAAG,YAAY,UAAU,wBAAwB;AAC7H,MAAI,gBAAgB,gBAAgB,cAAc,gBAAgB,qBAAqB;AACvF,QAAM,UAAU,gBAAgB,QAAQ,UAAU,qBAAqB;AACvE,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,qBAAqB;AAAA,EACtE;AACA,oBAAkB,cAAc,OAAO,QAAQ,OAAO,gCAAgC;AACtF,MAAI,iBAAiB,GAAG;AACtB,UAAM,uBAAuB,OAAO,cAAc;AAClD,UAAM,MAAM,OAAO,CAAC;AACpB,UAAM,aAAa,OAAO,cAAc,MAAM,EAAE;AAChD,oBAAgB,KAAK,IAAI,eAAe,IAAI,KAAK,oBAAoB,CAAC,GAAG,IAAI,sBAAsB,UAAU,CAAC;AAAA,EAChH;AACA,QAAM,UAAU,+BAA+B,eAAe,OAAO;AACrE,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,sBAAsB,GAAG,EAAE,qBAAqB,CAAC;AAGrD,SAAS,qBAAqB,SAAS,QAAQ,YAAY,cAAc;AACvE,QAAM,WAAW,gBAAgB,SAAS,WAAW,uBAAuB,OAAO;AACnF,QAAM,UAAU,gBAAgB,QAAQ,UAAU,qBAAqB;AACvE,QAAM,cAAc,gBAAgB,YAAY,cAAc,uBAAuB,OAAO;AAC5F,QAAM,gBAAgB,gBAAgB,cAAc,gBAAgB,uBAAuB,QAAQ,KAAK;AACxG,MAAI,SAAS,SAAS,GAAG;AACvB,UAAM,IAAI,MAAM;AAAA,UACV,SAAS,OAAO;AAAA,EACxB;AACA,MAAI,QAAQ,SAAS,GAAG;AACtB,UAAM,IAAI,MAAM,gDAAgD,QAAQ,OAAO;AAAA,EACjF;AACA,MAAI,YAAY,SAAS,GAAG;AAC1B,UAAM,IAAI,MAAM,qDAAqD,YAAY,OAAO;AAAA,EAC1F;AACA,MAAI,cAAc,SAAS,GAAG;AAC5B,UAAM,IAAI,MAAM,uDAAuD,cAAc,OAAO;AAAA,EAC9F;AACA,QAAM,SAAS;AAAA,IACb,SAAS;AAAA,IACT,QAAQ;AAAA,IACR,YAAY;AAAA,IACZ,cAAc;AAAA,EAChB;AACA,QAAM,SAAS,OAAO,UAAU,qBAAqB,MAAM;AAC3D,SAAO;AAAA,IACL,eAAe,OAAO;AAAA,IACtB,cAAc,OAAO;AAAA,IACrB,mBAAmB,OAAO;AAAA,IAC1B,iBAAiB,OAAO;AAAA,EAC1B;AACF;AACA,IAAI,sBAAsB,GAAG,EAAE,qBAAqB,CAAC;AAGrD,SAAS,eAAe,cAAc,YAAY,UAAU;AAC1D,QAAM,gBAAgB,gBAAgB,cAAc,gBAAgB,iBAAiB,OAAO;AAC5F,QAAM,cAAc,gBAAgB,YAAY,cAAc,iBAAiB,OAAO;AACtF,QAAM,YAAY,gBAAgB,UAAU,YAAY,iBAAiB,OAAO;AAChF,MAAI,cAAc,SAAS,GAAG;AAC5B,UAAM,IAAI,MAAM;AAAA,UACV,cAAc,OAAO;AAAA,EAC7B;AACA,MAAI,YAAY,SAAS,GAAG;AAC1B,UAAM,IAAI,MAAM,qDAAqD,YAAY,OAAO;AAAA,EAC1F;AACA,MAAI,UAAU,SAAS,GAAG;AACxB,UAAM,IAAI,MAAM,mDAAmD,UAAU,OAAO;AAAA,EACtF;AACA,QAAM,SAAS;AAAA,IACb,cAAc;AAAA,IACd,YAAY;AAAA,IACZ,UAAU;AAAA,EACZ;AACA,QAAM,SAAS,OAAO,UAAU,eAAe,MAAM;AACrD,SAAO,EAAE,eAAe,OAAO,IAAI,aAAa,OAAO,GAAG;AAC5D;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,mBAAmB,MAAM,SAAS,YAAY;AACrD,QAAM,QAAQ,gBAAgB,MAAM,QAAQ,mBAAmB;AAC/D,QAAM,WAAW,gBAAgB,SAAS,WAAW,qBAAqB,OAAO;AACjF,QAAM,cAAc,gBAAgB,YAAY,cAAc,qBAAqB,OAAO;AAC1F,MAAI,MAAM,OAAO,GAAG;AAClB,UAAM,IAAI,MAAM,2DAA2D;AAAA,EAC7E;AACA,MAAI,SAAS,SAAS,GAAG;AACvB,UAAM,IAAI,MAAM;AAAA,YACR,SAAS,OAAO;AAAA,EAC1B;AACA,MAAI,YAAY,SAAS,GAAG;AAC1B,UAAM,IAAI,MAAM;AAAA,YACR,YAAY,OAAO;AAAA,EAC7B;AACA,QAAM,SAAS;AAAA,IACb,MAAM;AAAA,IACN,SAAS;AAAA,IACT,YAAY;AAAA,EACd;AACA,SAAO,OAAO,UAAU,mBAAmB,MAAM;AACnD;AACA,IAAI,oBAAoB,GAAG,EAAE,mBAAmB,CAAC;AAGjD,SAAS,kBAAkB,MAAM,SAAS,YAAY;AACpD,QAAM,QAAQ,gBAAgB,MAAM,QAAQ,kBAAkB;AAC9D,QAAM,WAAW,gBAAgB,SAAS,WAAW,oBAAoB,OAAO;AAChF,QAAM,cAAc,gBAAgB,YAAY,cAAc,oBAAoB,OAAO;AACzF,MAAI,MAAM,OAAO,GAAG;AAClB,UAAM,IAAI,MAAM,2DAA2D;AAAA,EAC7E;AACA,MAAI,SAAS,SAAS,GAAG;AACvB,UAAM,IAAI,MAAM;AAAA,WACT,SAAS,OAAO;AAAA,EACzB;AACA,MAAI,YAAY,SAAS,GAAG;AAC1B,UAAM,IAAI,MAAM;AAAA,WACT,YAAY,OAAO;AAAA,EAC5B;AACA,QAAM,SAAS;AAAA,IACb,MAAM;AAAA,IACN,SAAS;AAAA,IACT,YAAY;AAAA,EACd;AACA,SAAO,OAAO,UAAU,kBAAkB,MAAM;AAClD;AACA,IAAI,mBAAmB,GAAG,EAAE,kBAAkB,CAAC;AAG/C,SAAS,cAAc,MAAM,YAAY,WAAW,aAAa,SAAS,WAAW,UAAU,wBAAwB;AACrH,QAAM,QAAQ,gBAAgB,MAAM,QAAQ,gBAAgB,QAAQ;AACpE,MAAI,MAAM,UAAU,UAAU;AAC5B,UAAM,IAAI,MAAM,iCAAiC;AAAA,EACnD;AACA,MAAI,MAAM,MAAM,WAAW,GAAG;AAC5B,UAAM,IAAI,MAAM,+BAA+B,MAAM,OAAO;AAAA,EAC9D;AACA,QAAM,cAAc,gBAAgB,YAAY,cAAc,cAAc;AAC5E,MAAI,YAAY,UAAU,SAAS;AACjC,UAAM,IAAI,MAAM,uCAAuC;AAAA,EACzD;AACA,QAAM,QAAQ;AAAA,IACZ;AAAA,IACA;AAAA,IACA;AAAA,IACA,UAAU;AAAA,IACV;AAAA,IACA;AAAA,EACF;AACA,QAAM,SAAS,EAAE,MAAM,OAAO,YAAY,YAAY;AACtD,QAAM,SAAS,OAAO,UAAU,cAAc,QAAQ,KAAK;AAC3D,SAAO,EAAE,QAAQ,OAAO,IAAI,cAAc,OAAO,GAAG;AACtD;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,aAAa,QAAQ,WAAW,YAAY,MAAM;AACzD,QAAM,SAAS,gBAAgB,QAAQ,SAAS,eAAe,QAAQ;AACvE,QAAM,aAAa,gBAAgB,WAAW,aAAa,eAAe,QAAQ;AAClF,MAAI,OAAO,SAAS,GAAG;AACrB,UAAM,IAAI,MAAM,+CAA+C,OAAO,OAAO;AAAA,EAC/E;AACA,MAAI,WAAW,SAAS,GAAG;AACzB,UAAM,IAAI,MAAM,mDAAmD,WAAW,OAAO;AAAA,EACvF;AACA,QAAM,QAAQ,EAAE,UAAU;AAC1B,QAAM,SAAS,EAAE,OAAO,QAAQ,WAAW,WAAW;AACtD,QAAM,SAAS,OAAO,UAAU,aAAa,QAAQ,KAAK;AAC1D,SAAO,EAAE,SAAS,OAAO,IAAI,QAAQ,OAAO,IAAI,OAAO,OAAO,GAAG;AACnE;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,wBAAwB,QAAQ,YAAY;AACnD,QAAM,SAAS,gBAAgB,QAAQ,SAAS,0BAA0B,QAAQ;AAClF,QAAM,QAAQ,EAAE,WAAW;AAC3B,MAAI,cAAc,GAAG;AACnB,UAAM,IAAI,MAAM,sCAAsC;AAAA,EACxD;AACA,QAAM,SAAS,EAAE,OAAO,OAAO;AAC/B,SAAO,OAAO,UAAU,wBAAwB,QAAQ,KAAK;AAC/D;AACA,IAAI,yBAAyB,GAAG,EAAE,wBAAwB,CAAC;AAG3D,IAAI,WAAW;AAAA,EACb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cAAc,aAAa;AAAA,EACzC,SAAS,GAAG,aAAa,OAAO,SAAS;AACvC,UAAM,EAAE,OAAO,OAAO,OAAO,IAAI,KAAK,iBAAiB,GAAG,OAAO;AACjE,QAAI,WAAW,MAAM;AACnB,YAAM,YAAY,QAAQ,IAAI,CAAC,OAAO,EAAE,MAAM,EAAE,MAAM,QAAQ,OAAO,EAAE,MAAM,EAAE;AAC/E,WAAK,eAAe,SAAS;AAAA,IAC/B,OAAO;AACL,WAAK,eAAe,MAAM;AAAA,IAC5B;AACA,YAAQ,MAAM;AACd,QAAI,YAAY;AACd,aAAO;AAAA,IACT,OAAO;AACL,YAAM,QAAQ;AACd,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,IAAI,aAAa;AACf,QAAI,KAAK,eAAe,MAAM;AAC5B,WAAK,cAAc;AAAA,IACrB;AACA,WAAO,KAAK;AAAA,EACd;AAAA,EACA,sBAAsB;AACpB,SAAK,cAAc,KAAK,aAAa;AAAA,EACvC;AAAA,EACA,iBAAiB,GAAG,SAAS;AAC3B,WAAO,cAAc,GAAG,OAAO;AAAA,EACjC;AAAA,EACA,UAAU;AACR,QAAI,KAAK,eAAe,MAAM;AAC5B,cAAQ,KAAK,WAAW;AAAA,IAC1B;AAAA,EACF;AAAA,EACA,MAAM,iBAAiB;AACrB,QAAI,KAAK,eAAe,MAAM;AAC5B,WAAK,cAAc;AAAA,IACrB;AACA,WAAO;AAAA,MACL,MAAM;AAAA,MACN,QAAQ,OAAO,KAAK,aAAa,OAAO;AAAA,IAC1C;AAAA,EACF;AAAA,EACA,MAAM,aAAa;AACjB,UAAM,IAAI,MAAM,yDAAyD;AAAA,EAC3E;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,UAAM,IAAI,MAAM,4DAA4D,KAAK,aAAa,GAAG;AAAA,EACnG;AAAA,EACA,MAAM,kBAAkB,cAAc;AACpC,SAAK,eAAe,MAAM,aAAa,GAAG,OAAO,KAAK,GAAG;AACzD,WAAO,aAAa,MAAM,CAAC;AAAA,EAC7B;AACF;AACA,OAAO,eAAe,WAAW,OAAO,aAAa;AAAA,EACnD,OAAO,CAAC,aAAa;AACnB,WAAO,SAAS,YAAY,QAAQ,SAAS,oBAAoB,QAAQ,SAAS,kBAAkB;AAAA,EACtG;AACF,CAAC;AAGD,IAAI,oBAAoB,cAAc,UAAU;AAAA,EAC9C,YAAY,cAAc,KAAK,WAAW,MAAM;AAC9C,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,MAAM;AACX,SAAK,UAAU;AACf,SAAK,mBAAmB,CAAC;AACzB,SAAK,qBAAqB,CAAC;AAC3B,QAAI,YAAY,MAAM;AACpB,WAAK,UAAU,OAAO,QAAQ,QAAQ;AAAA,IACxC;AAAA,EACF;AAAA,EACA,eAAe,mBAAmB;AAChC,UAAM,gBAAgB,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,CAAC,SAAS,KAAK,IAAI,IAAI,OAAO,KAAK,iBAAiB;AACnI,kBAAc,QAAQ,CAAC,MAAM,OAAO;AAClC,YAAM,QAAQ,OAAO,oBAAoB;AACzC,YAAM,YAAY;AAClB,UAAI,KAAK,iBAAiB,OAAO,MAAM;AACrC,aAAK,iBAAiB,MAAM;AAAA,UAC1B,cAAc,GAAG;AAAA,UACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,QAC3D;AAAA,MACF;AACA,UAAI,KAAK,mBAAmB,OAAO,MAAM;AACvC,aAAK,mBAAmB,MAAM;AAAA,UAC5B,cAAc,GAAG;AAAA,UACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,QAC3D;AAAA,MACF;AACA,YAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,SAAS,kBAAkB;AACrG,UAAI,YAAY,MAAM;AACpB;AAAA,MACF;AACA,YAAM,kBAAkB,KAAK,iBAAiB,IAAI;AAClD,YAAM,oBAAoB,KAAK,mBAAmB,IAAI;AACtD,WAAK,MAAM;AACT,cAAM,qBAAqB,KAAK,IAAI,iBAAiB,KAAK,GAAG,GAAG,IAAI,OAAO,QAAQ,GAAG,IAAI,KAAK,GAAG,CAAC;AACnG,cAAM,UAAU,IAAI,IAAI,KAAK,KAAK,mBAAmB,KAAK,OAAO,CAAC,GAAG,KAAK,KAAK,iBAAiB,KAAK,OAAO,CAAC,CAAC,GAAG,QAAQ;AACzH,cAAM,uBAAuB,KAAK,IAAI,mBAAmB,KAAK,GAAG,GAAG,IAAI,OAAO,OAAO,GAAG,IAAI,KAAK,GAAG,CAAC;AACtG,wBAAgB,OAAO,kBAAkB;AACzC,0BAAkB,OAAO,oBAAoB;AAC7C,cAAM,WAAW,KAAK,IAAI,SAAS,CAAC,KAAK,YAAY,GAAG,KAAK;AAC7D,cAAM,OAAO,QAAQ;AAAA,MACvB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,UAAU;AACR,QAAI,KAAK,sBAAsB,MAAM;AACnC,cAAQ,KAAK,iBAAiB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AACpD,cAAQ,KAAK,mBAAmB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IACxD;AAAA,EACF;AAAA,EACA,MAAM,aAAa;AACjB,UAAM,YAAY,CAAC,GAAG,KAAK,kBAAkB,GAAG,KAAK,kBAAkB;AACvE,WAAO,CAAC,MAAM,KAAK,eAAe,CAAC,EAAE,OAAO,UAAU,IAAI,CAAC,OAAO,EAAE,MAAM,EAAE,cAAc,QAAQ,EAAE,SAAS,EAAE,CAAC;AAAA,EAClH;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,mBAAe,MAAM,KAAK,kBAAkB,YAAY;AACxD,UAAM,gBAAgB,aAAa,SAAS;AAC5C,UAAM,YAAY;AAClB,SAAK,mBAAmB,aAAa,MAAM,GAAG,aAAa,EAAE,IAAI,CAAC,OAAO;AAAA,MACvE,cAAc,EAAE;AAAA,MAChB,UAAU,EAAE,OAAO,SAAS,SAAS;AAAA,IACvC,EAAE;AACF,SAAK,qBAAqB,aAAa,MAAM,eAAe,gBAAgB,CAAC,EAAE,IAAI,CAAC,OAAO;AAAA,MACzF,cAAc,EAAE;AAAA,MAChB,UAAU,EAAE,OAAO,SAAS,SAAS;AAAA,IACvC,EAAE;AAAA,EACJ;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,gBAAgB,KAAK;AAAA,MACrB,OAAO,KAAK;AAAA,MACZ,WAAW,KAAK;AAAA,IAClB;AAAA,EACF;AAAA,EACA,OAAO,WAAW,KAAKL,SAAQ;AAC7B,WAAO,IAAI,IAAIA,QAAO,iBAAiBA,QAAO,QAAQA,QAAO,UAAU;AAAA,EACzE;AACF;AACA,kBAAkB,YAAY;AAC9B,cAAc,iBAAiB;AAG/B,IAAI,mBAAmB,cAAc,UAAU;AAAA,EAC7C,YAAY,cAAc,0BAA0B,KAAK;AACvD,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,0BAA0B;AAC/B,SAAK,mBAAmB,CAAC;AAAA,EAC3B;AAAA,EACA,eAAe,mBAAmB;AAChC,UAAM,gBAAgB,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,CAAC,SAAS,KAAK,IAAI,IAAI,OAAO,KAAK,iBAAiB;AACnI,kBAAc,QAAQ,CAAC,MAAM,OAAO;AAClC,YAAM,QAAQ,OAAO,oBAAoB;AACzC,UAAI,KAAK,iBAAiB,OAAO,MAAM;AACrC,cAAM,YAAY;AAClB,aAAK,iBAAiB,MAAM;AAAA,UAC1B,cAAc,GAAG;AAAA,UACjB,UAAU,KAAK,MAAM,KAAK,MAAM,OAAO,KAAK,uBAAuB,EAAE,SAAS,SAAS,CAAC;AAAA,QAC1F;AAAA,MACF;AACA,YAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,SAAS,kBAAkB;AACrG,UAAI,YAAY,MAAM;AACpB;AAAA,MACF;AACA,YAAM,kBAAkB,KAAK,iBAAiB,IAAI;AAClD,WAAK,MAAM;AACT,cAAM,qBAAqB,KAAK,iBAAiB,OAAO,QAAQ,CAAC;AACjE,wBAAgB,OAAO,kBAAkB;AACzC,cAAM,WAAW,KAAK,IAAI,IAAI,UAAU,KAAK,KAAK,oBAAoB,OAAO,QAAQ,QAAQ,CAAC,CAAC,CAAC,GAAG,CAAC,KAAK,YAAY,GAAG,KAAK;AAC7H,cAAM,OAAO,QAAQ;AAAA,MACvB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,UAAU;AACR,QAAI,KAAK,oBAAoB,MAAM;AACjC,cAAQ,KAAK,iBAAiB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IACtD;AAAA,EACF;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,CAAC,MAAM,KAAK,eAAe,CAAC,EAAE,OAAO,KAAK,iBAAiB,IAAI,CAAC,OAAO,EAAE,MAAM,EAAE,cAAc,QAAQ,EAAE,SAAS,EAAE,CAAC;AAAA,EAC9H;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,mBAAe,MAAM,KAAK,kBAAkB,YAAY;AACxD,UAAM,YAAY;AAClB,SAAK,mBAAmB,aAAa,IAAI,CAAC,OAAO,EAAE,cAAc,EAAE,MAAM,UAAU,EAAE,OAAO,SAAS,SAAS,EAAE,EAAE;AAAA,EACpH;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,gBAAgB,KAAK;AAAA,MACrB,2BAA2B,KAAK;AAAA,IAClC;AAAA,EACF;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,WAAO,IAAI,IAAIA,QAAO,iBAAiBA,QAAO,0BAA0B;AAAA,EAC1E;AACF;AACA,iBAAiB,YAAY;AAC7B,cAAc,gBAAgB;AAG9B,IAAI,gBAAgB,cAAc,UAAU;AAAA,EAC1C,YAAY,cAAc,OAAO,OAAO,WAAW,MAAM;AACvD,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,QAAQ;AACb,SAAK,QAAQ;AACb,SAAK,UAAU;AACf,SAAK,yBAAyB,CAAC;AAC/B,SAAK,0BAA0B,CAAC;AAChC,SAAK,MAAM;AACT,WAAK,WAAW,OAAO,KAAK,EAAE,SAAS;AACvC,WAAK,WAAW,OAAO,KAAK,EAAE,SAAS;AAAA,IACzC,CAAC;AACD,QAAI,YAAY,MAAM;AACpB,WAAK,UAAU,OAAO,QAAQ,QAAQ;AAAA,IACxC;AAAA,EACF;AAAA,EACA,eAAe,mBAAmB;AAChC,UAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,CAAC,MAAM,EAAE,IAAI,IAAI,OAAO,KAAK,iBAAiB;AACxH,SAAK,MAAM;AACT,YAAM,mBAAmB,IAAI,GAAG,KAAK,QAAQ;AAC7C,YAAM,mBAAmB,IAAI,GAAG,KAAK,QAAQ;AAC7C,eAAS,QAAQ,CAAC,MAAM,OAAO;AAC7B,cAAM,QAAQ,OAAO,oBAAoB;AACzC,cAAM,YAAY;AAClB,YAAI,KAAK,uBAAuB,OAAO,MAAM;AAC3C,eAAK,uBAAuB,MAAM;AAAA,YAChC,cAAc,GAAG;AAAA,YACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,UAC3D;AAAA,QACF;AACA,YAAI,KAAK,wBAAwB,OAAO,MAAM;AAC5C,eAAK,wBAAwB,MAAM;AAAA,YACjC,cAAc,GAAG;AAAA,YACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,UAC3D;AAAA,QACF;AACA,cAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,SAAS,kBAAkB;AACrG,YAAI,YAAY,MAAM;AACpB;AAAA,QACF;AACA,cAAM,cAAc,KAAK,uBAAuB,IAAI;AACpD,cAAM,eAAe,KAAK,wBAAwB,IAAI;AACtD,cAAM,iBAAiB,KAAK,IAAI,aAAa,KAAK,KAAK,GAAG,IAAI,UAAU,IAAI,KAAK,KAAK,CAAC;AACvF,cAAM,kBAAkB,KAAK,IAAI,cAAc,KAAK,KAAK,GAAG,IAAI,OAAO,QAAQ,GAAG,IAAI,KAAK,KAAK,CAAC;AACjG,cAAM,2BAA2B,IAAI,gBAAgB,gBAAgB;AACrE,cAAM,4BAA4B,IAAI,iBAAiB,gBAAgB;AACvE,oBAAY,OAAO,cAAc;AACjC,qBAAa,OAAO,eAAe;AACnC,cAAM,WAAW,KAAK,IAAI,IAAI,0BAA0B,KAAK,KAAK,yBAAyB,GAAG,KAAK,OAAO,CAAC,GAAG,CAAC,KAAK,YAAY,GAAG,KAAK;AACxI,cAAM,OAAO,QAAQ;AAAA,MACvB,CAAC;AACD,WAAK,SAAS,OAAO,IAAI,KAAK,UAAU,KAAK,KAAK,CAAC;AACnD,WAAK,SAAS,OAAO,IAAI,KAAK,UAAU,KAAK,KAAK,CAAC;AAAA,IACrD,CAAC;AACD,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,UAAU;AACR,SAAK,SAAS,QAAQ;AACtB,SAAK,SAAS,QAAQ;AACtB,QAAI,KAAK,0BAA0B,MAAM;AACvC,cAAQ,KAAK,uBAAuB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IAC5D;AACA,QAAI,KAAK,2BAA2B,MAAM;AACxC,cAAQ,KAAK,wBAAwB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IAC7D;AAAA,EACF;AAAA,EACA,MAAM,aAAa;AACjB,UAAM,YAAY,CAAC,GAAG,KAAK,wBAAwB,GAAG,KAAK,uBAAuB;AAClF,WAAO,CAAC,MAAM,KAAK,eAAe,CAAC,EAAE,OAAO,UAAU,IAAI,CAAC,OAAO,EAAE,MAAM,EAAE,cAAc,QAAQ,EAAE,SAAS,EAAE,CAAC;AAAA,EAClH;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,mBAAe,MAAM,KAAK,kBAAkB,YAAY;AACxD,SAAK,MAAM;AACT,WAAK,SAAS,OAAO,IAAI,KAAK,OAAO,KAAK,cAAc,CAAC,CAAC;AAC1D,WAAK,SAAS,OAAO,IAAI,KAAK,OAAO,KAAK,cAAc,CAAC,CAAC;AAAA,IAC5D,CAAC;AACD,UAAM,gBAAgB,aAAa,SAAS;AAC5C,UAAM,YAAY;AAClB,SAAK,yBAAyB,aAAa,MAAM,GAAG,aAAa,EAAE,IAAI,CAAC,OAAO;AAAA,MAC7E,cAAc,EAAE;AAAA,MAChB,UAAU,EAAE,OAAO,SAAS,SAAS;AAAA,IACvC,EAAE;AACF,SAAK,0BAA0B,aAAa,MAAM,eAAe,gBAAgB,CAAC,EAAE,IAAI,CAAC,OAAO;AAAA,MAC9F,cAAc,EAAE;AAAA,MAChB,UAAU,EAAE,OAAO,SAAS,SAAS;AAAA,IACvC,EAAE;AAAA,EACJ;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,gBAAgB,KAAK;AAAA,MACrB,SAAS,KAAK;AAAA,MACd,SAAS,KAAK;AAAA,MACd,WAAW,KAAK;AAAA,IAClB;AAAA,EACF;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,WAAO,IAAI,IAAIA,QAAO,iBAAiBA,QAAO,UAAUA,QAAO,UAAUA,QAAO,UAAU;AAAA,EAC5F;AACF;AACA,cAAc,YAAY;AAC1B,cAAc,aAAa;AAG3B,IAAI,kBAAkB,cAAc,UAAU;AAAA,EAC5C,YAAY,cAAc,OAAO,OAAO,WAAW,MAAM,QAAQ,GAAG;AAClE,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,QAAQ;AACb,SAAK,QAAQ;AACb,SAAK,UAAU;AACf,SAAK,QAAQ;AACb,SAAK,yBAAyB,CAAC;AAC/B,SAAK,6BAA6B,CAAC;AACnC,SAAK,MAAM;AACT,WAAK,YAAY,OAAO,CAAC,EAAE,SAAS;AACpC,WAAK,WAAW,OAAO,KAAK,EAAE,SAAS;AAAA,IACzC,CAAC;AACD,QAAI,YAAY,MAAM;AACpB,WAAK,UAAU,OAAO,QAAQ,QAAQ;AAAA,IACxC;AAAA,EACF;AAAA,EACA,eAAe,mBAAmB;AAChC,UAAM,gBAAgB,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,CAAC,SAAS,KAAK,IAAI,IAAI,OAAO,KAAK,iBAAiB;AACnI,SAAK,MAAM;AACT,YAAM,mBAAmB,IAAI,GAAG,KAAK,QAAQ;AAC7C,YAAM,KAAK,IAAI,CAAC,KAAK,cAAc,KAAK,IAAI,KAAK,WAAW,KAAK,KAAK,GAAG,CAAC,CAAC;AAC3E,oBAAc,QAAQ,CAAC,MAAM,OAAO;AAClC,cAAM,QAAQ,OAAO,oBAAoB;AACzC,cAAM,YAAY;AAClB,YAAI,KAAK,uBAAuB,OAAO,MAAM;AAC3C,eAAK,uBAAuB,MAAM;AAAA,YAChC,cAAc,GAAG;AAAA,YACjB,UAAU,UAAU,KAAK,EAAE,SAAS,SAAS;AAAA,UAC/C;AAAA,QACF;AACA,YAAI,KAAK,2BAA2B,OAAO,MAAM;AAC/C,eAAK,2BAA2B,MAAM;AAAA,YACpC,cAAc,GAAG;AAAA,YACjB,UAAU,UAAU,KAAK,EAAE,SAAS,SAAS;AAAA,UAC/C;AAAA,QACF;AACA,cAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,SAAS,kBAAkB;AACrG,YAAI,YAAY,MAAM;AACpB;AAAA,QACF;AACA,cAAM,cAAc,KAAK,uBAAuB,IAAI;AACpD,cAAM,kBAAkB,KAAK,2BAA2B,IAAI;AAC5D,cAAM,iBAAiB,KAAK,IAAI,aAAa,KAAK,KAAK,GAAG,IAAI,UAAU,IAAI,KAAK,KAAK,CAAC;AACvF,cAAM,MAAM,IAAI,iBAAiB,KAAK,KAAK;AAC3C,cAAM,MAAM,IAAI,QAAQ;AACxB,cAAM,qBAAqB,QAAQ,KAAK,GAAG;AAC3C,oBAAY,OAAO,cAAc;AACjC,wBAAgB,OAAO,kBAAkB;AACzC,cAAM,WAAW,KAAK,IAAI,IAAI,IAAI,gBAAgB,GAAG,IAAI,gBAAgB,KAAK,oBAAoB,KAAK,OAAO,CAAC,CAAC,GAAG,KAAK;AACxH,cAAM,OAAO,QAAQ;AAAA,MACvB,CAAC;AACD,WAAK,UAAU,OAAO,KAAK,KAAK,WAAW,CAAC,CAAC;AAC7C,WAAK,SAAS,OAAO,IAAI,KAAK,UAAU,KAAK,KAAK,CAAC;AAAA,IACrD,CAAC;AACD,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,UAAU;AACR,SAAK,SAAS,QAAQ;AACtB,SAAK,UAAU,QAAQ;AACvB,QAAI,KAAK,0BAA0B,MAAM;AACvC,cAAQ,KAAK,uBAAuB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IAC5D;AACA,QAAI,KAAK,8BAA8B,MAAM;AAC3C,cAAQ,KAAK,2BAA2B,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IAChE;AAAA,EACF;AAAA,EACA,MAAM,aAAa;AACjB,UAAM,IAAI,MAAM,iDAAiD;AAAA,EACnE;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,UAAM,IAAI,MAAM,iDAAiD;AAAA,EACnE;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,gBAAgB,KAAK;AAAA,MACrB,SAAS,KAAK;AAAA,MACd,SAAS,KAAK;AAAA,MACd,WAAW,KAAK;AAAA,MAChB,SAAS,KAAK;AAAA,IAChB;AAAA,EACF;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,WAAO,IAAI,IAAIA,QAAO,iBAAiBA,QAAO,UAAUA,QAAO,UAAUA,QAAO,YAAYA,QAAO,QAAQ;AAAA,EAC7G;AACF;AACA,gBAAgB,YAAY;AAC5B,cAAc,eAAe;AAG7B,IAAI,eAAe,cAAc,UAAU;AAAA,EACzC,YAAY,cAAc;AACxB,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,gBAAgB,YAAY;AAAA,EACnC;AAAA,EACA,eAAe,mBAAmB;AAChC,UAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,CAAC,MAAM,EAAE,IAAI,IAAI,OAAO,KAAK,iBAAiB;AACxH,aAAS,QAAQ,CAAC,MAAM,OAAO;AAC7B,YAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,SAAS,kBAAkB;AACrG,UAAI,YAAY,MAAM;AACpB;AAAA,MACF;AACA,YAAM,QAAQ,OAAO,oBAAoB;AACzC,WAAK,MAAM;AACT,cAAM,WAAW,KAAK,IAAI,KAAK,GAAG,QAAQ,GAAG,KAAK;AAClD,cAAM,OAAO,QAAQ;AAAA,MACvB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,gBAAgB,cAAc;AAC5B,SAAK,eAAe;AACpB,QAAI,KAAK,KAAK,MAAM;AAClB,WAAK,EAAE,QAAQ;AAAA,IACjB;AACA,SAAK,IAAI,KAAK,OAAO,CAAC,YAAY,CAAC;AAAA,EACrC;AAAA,EACA,UAAU;AACR,SAAK,EAAE,QAAQ;AAAA,EACjB;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,CAAC,MAAM,KAAK,eAAe,CAAC;AAAA,EACrC;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,mBAAe,MAAM,KAAK,kBAAkB,YAAY;AACxD,QAAI,aAAa,WAAW,GAAG;AAC7B,YAAM,IAAI,MAAM,+CAA+C;AAAA,IACjE;AAAA,EACF;AAAA,EACA,YAAY;AACV,WAAO,EAAE,gBAAgB,KAAK,aAAa;AAAA,EAC7C;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,WAAO,IAAI,IAAIA,QAAO,eAAe;AAAA,EACvC;AACF;AACA,aAAa,YAAY;AACzB,cAAc,YAAY;AAG1B,IAAI,oBAAoB,cAAc,aAAa;AAAA,EACjD,YAAY,cAAc,UAAU,cAAc,OAAO;AACvD,UAAM,YAAY;AAClB,SAAK,eAAe;AACpB,SAAK,WAAW;AAChB,SAAK,cAAc;AACnB,SAAK,gBAAgB,CAAC;AACtB,SAAK,IAAI,OAAO,KAAK,QAAQ;AAAA,EAC/B;AAAA,EACA,eAAe,mBAAmB;AAChC,UAAM,gBAAgB,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,CAAC,SAAS,KAAK,IAAI,IAAI,OAAO,KAAK,iBAAiB;AACnI,kBAAc,QAAQ,CAAC,MAAM,OAAO;AAClC,YAAM,QAAQ,OAAO,oBAAoB;AACzC,UAAI,KAAK,cAAc,OAAO,MAAM;AAClC,cAAM,YAAY;AAClB,aAAK,cAAc,MAAM;AAAA,UACvB,cAAc,GAAG;AAAA,UACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,QAC3D;AAAA,MACF;AACA,YAAM,eAAe,KAAK,cAAc,IAAI;AAC5C,YAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,SAAS,kBAAkB;AACrG,UAAI,YAAY,MAAM;AACpB;AAAA,MACF;AACA,WAAK,MAAM;AACT,YAAI;AACJ,cAAM,kBAAkB,KAAK,IAAI,KAAK,GAAG,YAAY,GAAG,QAAQ;AAChE,YAAI,KAAK,aAAa;AACpB,qBAAW,KAAK,IAAI,KAAK,GAAG,KAAK,UAAU,IAAI,iBAAiB,KAAK,CAAC,CAAC,CAAC,GAAG,KAAK;AAAA,QAClF,OAAO;AACL,qBAAW,KAAK,IAAI,KAAK,GAAG,eAAe,GAAG,KAAK;AAAA,QACrD;AACA,qBAAa,OAAO,eAAe;AACnC,cAAM,OAAO,QAAQ;AAAA,MACvB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,UAAU;AACR,SAAK,EAAE,QAAQ;AACf,QAAI,KAAK,iBAAiB,MAAM;AAC9B,cAAQ,KAAK,cAAc,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IACnD;AAAA,EACF;AAAA,EACA,YAAY,UAAU;AACpB,SAAK,WAAW;AAAA,EAClB;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,CAAC,MAAM,KAAK,eAAe,CAAC,EAAE,OAAO,KAAK,cAAc,IAAI,CAAC,OAAO,EAAE,MAAM,EAAE,cAAc,QAAQ,EAAE,SAAS,EAAE,CAAC;AAAA,EAC3H;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,mBAAe,MAAM,KAAK,kBAAkB,YAAY;AACxD,UAAM,YAAY;AAClB,SAAK,gBAAgB,aAAa,IAAI,CAAC,OAAO,EAAE,cAAc,EAAE,MAAM,UAAU,EAAE,OAAO,SAAS,SAAS,EAAE,EAAE;AAAA,EACjH;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,gBAAgB,KAAK;AAAA,MACrB,YAAY,KAAK;AAAA,MACjB,eAAe,KAAK;AAAA,IACtB;AAAA,EACF;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,WAAO,IAAI,IAAIA,QAAO,iBAAiBA,QAAO,aAAaA,QAAO,cAAc;AAAA,EAClF;AACF;AACA,kBAAkB,YAAY;AAC9B,cAAc,iBAAiB;AAG/B,IAAI,mBAAmB,cAAc,UAAU;AAAA,EAC7C,YAAY,cAAc,QAAQ,KAAK,WAAW,GAAG,WAAW,MAAM,WAAW,OAAO;AACtF,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,QAAQ;AACb,SAAK,WAAW;AAChB,SAAK,UAAU;AACf,SAAK,yBAAyB,CAAC;AAC/B,SAAK,qBAAqB,CAAC;AAC3B,SAAK,uBAAuB,CAAC;AAC7B,SAAK,WAAW;AAChB,QAAI,YAAY,MAAM;AACpB,WAAK,UAAU,OAAO,QAAQ,QAAQ;AAAA,IACxC;AACA,QAAI,gBAAgB,MAAM;AACxB,YAAM,IAAI,MAAM,oDAAoD;AAAA,IACtE;AAAA,EACF;AAAA,EACA,eAAe,mBAAmB;AAChC,UAAM,gBAAgB,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,CAAC,SAAS,KAAK,IAAI,IAAI,OAAO,KAAK,iBAAiB;AACnI,kBAAc,QAAQ,CAAC,MAAM,OAAO;AAClC,YAAM,QAAQ,OAAO,oBAAoB;AACzC,YAAM,YAAY;AAClB,UAAI,KAAK,uBAAuB,OAAO,MAAM;AAC3C,aAAK,uBAAuB,MAAM;AAAA,UAChC,cAAc,GAAG;AAAA,UACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,QAC3D;AAAA,MACF;AACA,UAAI,KAAK,mBAAmB,OAAO,MAAM;AACvC,aAAK,mBAAmB,MAAM;AAAA,UAC5B,cAAc,GAAG;AAAA,UACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,QAC3D;AAAA,MACF;AACA,UAAI,KAAK,qBAAqB,OAAO,QAAQ,KAAK,UAAU;AAC1D,aAAK,qBAAqB,MAAM;AAAA,UAC9B,cAAc,GAAG;AAAA,UACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,QAC3D;AAAA,MACF;AACA,YAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,SAAS,kBAAkB;AACrG,UAAI,YAAY,MAAM;AACpB;AAAA,MACF;AACA,YAAM,wBAAwB,KAAK,uBAAuB,IAAI;AAC9D,YAAM,qBAAqB,KAAK,mBAAmB,IAAI;AACvD,WAAK,MAAM;AACT,cAAM,2BAA2B,KAAK,IAAI,uBAAuB,KAAK,KAAK,GAAG,IAAI,OAAO,QAAQ,GAAG,IAAI,KAAK,KAAK,CAAC;AACnH,YAAI,KAAK,UAAU;AACjB,gBAAM,sBAAsB,KAAK,qBAAqB,IAAI;AAC1D,gBAAM,yBAAyB,KAAK,IAAI,qBAAqB,KAAK,KAAK,GAAG,IAAI,UAAU,IAAI,KAAK,KAAK,CAAC;AACvG,gBAAM,mBAAmB,IAAI,IAAI,UAAU,KAAK,YAAY,GAAG,KAAK,IAAI,0BAA0B,KAAK,OAAO,sBAAsB,GAAG,KAAK,OAAO,CAAC,CAAC,CAAC;AACtJ,gBAAM,wBAAwB,KAAK,IAAI,oBAAoB,KAAK,QAAQ,GAAG,gBAAgB;AAC3F,gCAAsB,OAAO,wBAAwB;AACrD,8BAAoB,OAAO,sBAAsB;AACjD,6BAAmB,OAAO,qBAAqB;AAC/C,gBAAM,WAAW,IAAI,OAAO,qBAAqB;AACjD,gBAAM,OAAO,QAAQ;AAAA,QACvB,OAAO;AACL,gBAAM,4BAA4B,KAAK,IAAI,uBAAuB,KAAK,KAAK,GAAG,IAAI,OAAO,QAAQ,GAAG,IAAI,KAAK,KAAK,CAAC;AACpH,gBAAM,wBAAwB,KAAK,IAAI,oBAAoB,KAAK,QAAQ,GAAG,IAAI,IAAI,UAAU,KAAK,YAAY,GAAG,KAAK,KAAK,2BAA2B,KAAK,OAAO,CAAC,CAAC,CAAC;AACrK,gCAAsB,OAAO,yBAAyB;AACtD,6BAAmB,OAAO,qBAAqB;AAC/C,gBAAM,WAAW,IAAI,OAAO,qBAAqB;AACjD,gBAAM,OAAO,QAAQ;AAAA,QACvB;AAAA,MACF,CAAC;AAAA,IACH,CAAC;AACD,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,UAAU;AACR,QAAI,KAAK,0BAA0B,MAAM;AACvC,cAAQ,KAAK,uBAAuB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IAC5D;AACA,QAAI,KAAK,wBAAwB,QAAQ,KAAK,UAAU;AACtD,cAAQ,KAAK,qBAAqB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IAC1D;AACA,QAAI,KAAK,sBAAsB,MAAM;AACnC,cAAQ,KAAK,mBAAmB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IACxD;AAAA,EACF;AAAA,EACA,MAAM,aAAa;AACjB,UAAM,YAAY,CAAC,GAAG,KAAK,wBAAwB,GAAG,KAAK,kBAAkB;AAC7E,QAAI,KAAK,UAAU;AACjB,gBAAU,KAAK,GAAG,KAAK,oBAAoB;AAAA,IAC7C;AACA,WAAO,CAAC,MAAM,KAAK,eAAe,CAAC,EAAE,OAAO,UAAU,IAAI,CAAC,OAAO,EAAE,MAAM,EAAE,cAAc,QAAQ,EAAE,SAAS,EAAE,CAAC;AAAA,EAClH;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,mBAAe,MAAM,KAAK,kBAAkB,YAAY;AACxD,UAAM,gBAAgB,KAAK,WAAW,aAAa,SAAS,IAAI,aAAa,SAAS;AACtF,UAAM,YAAY;AAClB,SAAK,yBAAyB,aAAa,MAAM,GAAG,aAAa,EAAE,IAAI,CAAC,OAAO;AAAA,MAC7E,cAAc,EAAE;AAAA,MAChB,UAAU,EAAE,OAAO,SAAS,SAAS;AAAA,IACvC,EAAE;AACF,SAAK,qBAAqB,aAAa,MAAM,eAAe,gBAAgB,CAAC,EAAE,IAAI,CAAC,OAAO;AAAA,MACzF,cAAc,EAAE;AAAA,MAChB,UAAU,EAAE,OAAO,SAAS,SAAS;AAAA,IACvC,EAAE;AACF,QAAI,KAAK,UAAU;AACjB,WAAK,uBAAuB,aAAa,MAAM,gBAAgB,GAAG,gBAAgB,CAAC,EAAE,IAAI,CAAC,OAAO;AAAA,QAC/F,cAAc,EAAE;AAAA,QAChB,UAAU,EAAE,OAAO,SAAS,SAAS;AAAA,MACvC,EAAE;AAAA,IACJ;AAAA,EACF;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,gBAAgB,KAAK;AAAA,MACrB,SAAS,KAAK;AAAA,MACd,YAAY,KAAK;AAAA,MACjB,WAAW,KAAK;AAAA,MAChB,YAAY,KAAK;AAAA,IACnB;AAAA,EACF;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,WAAO,IAAI,IAAIA,QAAO,iBAAiBA,QAAO,UAAUA,QAAO,aAAaA,QAAO,YAAYA,QAAO,WAAW;AAAA,EACnH;AACF;AACA,iBAAiB,YAAY;AAC7B,cAAc,gBAAgB;AAG9B,IAAI,wBAAwB,MAAM;AAAA,EAChC,OAAO,IAAI,cAAc;AACvB,WAAO,IAAI,aAAa,YAAY;AAAA,EACtC;AAAA,EACA,OAAO,SAAS,cAAc,UAAU,cAAc,OAAO;AAC3D,WAAO,IAAI,kBAAkB,cAAc,UAAU,WAAW;AAAA,EAClE;AAAA,EACA,OAAO,QAAQ,cAAc,QAAQ,KAAK,WAAW,GAAG,WAAW,MAAM,WAAW,OAAO;AACzF,WAAO,IAAI,iBAAiB,cAAc,OAAO,UAAU,UAAU,QAAQ;AAAA,EAC/E;AAAA,EACA,OAAO,KAAK,eAAe,MAAM,QAAQ,KAAK,QAAQ,OAAO,WAAW,MAAM;AAC5E,WAAO,IAAI,cAAc,cAAc,OAAO,OAAO,QAAQ;AAAA,EAC/D;AAAA,EACA,OAAO,SAAS,eAAe,MAAM,MAAM,MAAM,WAAW,MAAM;AAChE,WAAO,IAAI,kBAAkB,cAAc,KAAK,QAAQ;AAAA,EAC1D;AAAA,EACA,OAAO,OAAO,eAAe,MAAM,QAAQ,KAAK,QAAQ,OAAO,WAAW,MAAM,QAAQ,GAAG;AACzF,WAAO,IAAI,gBAAgB,cAAc,OAAO,OAAO,UAAU,KAAK;AAAA,EACxE;AAAA,EACA,OAAO,QAAQ,cAAc,0BAA0B,KAAK;AAC1D,WAAO,IAAI,iBAAiB,cAAc,uBAAuB;AAAA,EACnE;AACF;AAGA,IAAI,QAAQ;AAAA,EACV,KAAK,sBAAsB;AAAA,EAC3B,UAAU,sBAAsB;AAAA,EAChC,UAAU,sBAAsB;AAAA,EAChC,SAAS,sBAAsB;AAAA,EAC/B,SAAS,sBAAsB;AAAA,EAC/B,QAAQ,sBAAsB;AAAA,EAC9B,MAAM,sBAAsB;AAC9B;AAGA,IAAI,iBAAiB,MAAM;AACzB,MAAI,OAAO,0BAA0B,aAAa;AAChD,WAAO;AAAA,EACT,WAAW,OAAO,iBAAiB,aAAa;AAC9C,WAAO;AAAA,EACT;AACA,SAAO,CAAC,MAAM,EAAE;AAClB,GAAG;AACH,SAAS,YAAY;AACnB,SAAO,IAAI,QAAQ,CAAC,YAAY,cAAc,MAAM,QAAQ,CAAC,CAAC;AAChE;AAGA,IAAI,uBAAuB,CAAC;AAC5BjB,UAAS,sBAAsB;AAAA,EAC7B,QAAQ,MAAM;AAAA,EACd,QAAQ,MAAM;AAAA,EACd,QAAQ,MAAM;AAAA,EACd,QAAQ,MAAM;AAAA,EACd,QAAQ,MAAM;AAAA,EACd,OAAO,MAAM;AAAA,EACb,uBAAuB,MAAM;AAAA,EAC7B,YAAY,MAAM;AAAA,EAClB,iBAAiB,MAAM;AAAA,EACvB,iBAAiB,MAAM;AAAA,EACvB,4BAA4B,MAAM;AAAA,EAClC,4BAA4B,MAAM;AAAA,EAClC,wBAAwB,MAAM;AAAA,EAC9B,oBAAoB,MAAM;AAAA,EAC1B,sBAAsB,MAAM;AAAA,EAC5B,iBAAiB,MAAM;AAAA,EACvB,qBAAqB,MAAM;AAAA,EAC3B,2BAA2B,MAAM;AAAA,EACjC,kBAAkB,MAAM;AAAA,EACxB,sBAAsB,MAAM;AAAA,EAC5B,qBAAqB,MAAM;AAAA,EAC3B,mBAAmB,MAAM;AAAA,EACzB,mBAAmB,MAAM;AAAA,EACzB,mBAAmB,MAAM;AAAA,EACzB,uBAAuB,MAAM;AAAA,EAC7B,0BAA0B,MAAM;AAAA,EAChC,2BAA2B,MAAM;AAAA,EACjC,iBAAiB,MAAM;AAAA,EACvB,mBAAmB,MAAM;AAAA,EACzB,mBAAmB,MAAM;AAAA,EACzB,yBAAyB,MAAM;AAAA,EAC/B,sBAAsB,MAAM;AAAA,EAC5B,gCAAgC,MAAM;AAAA,EACtC,sBAAsB,MAAM;AAAA,EAC5B,UAAU,MAAM;AAAA,EAChB,WAAW,MAAM;AAAA,EACjB,wBAAwB,MAAM;AAAA,EAC9B,wBAAwB,MAAM;AAAA,EAC9B,oBAAoB,MAAM;AAAA,EAC1B,kBAAkB,MAAM;AAAA,EACxB,qBAAqB,MAAM;AAAA,EAC3B,sBAAsB,MAAM;AAAA,EAC5B,sBAAsB,MAAM;AAAA,EAC5B,sBAAsB,MAAM;AAAA,EAC5B,sBAAsB,MAAM;AAAA,EAC5B,gBAAgB,MAAM;AAAA,EACtB,kBAAkB,MAAM;AAAA,EACxB,aAAa,MAAM;AAAA,EACnB,kBAAkB,MAAM;AAAA,EACxB,aAAa,MAAM;AAAA,EACnB,qBAAqB,MAAM;AAAA,EAC3B,qBAAqB,MAAM;AAAA,EAC3B,cAAc,MAAM;AAAA,EACpB,iDAAiD,MAAM;AAAA,EACvD,iDAAiD,MAAM;AAAA,EACvD,mDAAmD,MAAM;AAAA,EACzD,sDAAsD,MAAM;AAAA,EAC5D,iDAAiD,MAAM;AAAA,EACvD,iDAAiD,MAAM;AAAA,EACvD,0DAA0D,MAAM;AAAA,EAChE,+CAA+C,MAAM;AAAA,EACrD,wDAAwD,MAAM;AAAA,EAC9D,yDAAyD,MAAM;AAAA,EAC/D,8DAA8D,MAAM;AAAA,EACpE,0DAA0D,MAAM;AAAA,EAChE,wBAAwB,MAAM;AAAA,EAC9B,uBAAuB,MAAM;AAAA,EAC7B,KAAK,MAAMgB;AAAA,EACX,wBAAwB,MAAM;AAAA,EAC9B,oBAAoB,MAAM;AAAA,EAC1B,kBAAkB,MAAM;AAAA,EACxB,cAAc,MAAM;AAAA,EACpB,YAAY,MAAM;AAAA,EAClB,YAAY,MAAM;AAAA,EAClB,wBAAwB,MAAM;AAAA,EAC9B,mBAAmB,MAAM;AAAA,EACzB,YAAY,MAAM;AAAA,EAClB,eAAe,MAAM;AAAA,EACrB,qBAAqB,MAAM;AAAA,EAC3B,MAAM,MAAM;AACd,CAAC;AAGD,SAAS,uBAAuB,QAAQ,MAAM;AAC5C,QAAM,OAAO,OAAO,GAAG;AACvB,SAAO,QAAQ,CAAC,OAAO,OAAO;AAC5B,WAAO,MAAM,WAAW,MAAM,MAAM,kBAAkB,0BAA0B,iDAAiD,OAAO;AAAA,EAC1I,CAAC;AACD,SAAO,QAAQ,KAAK,OAAO,MAAM,MAAM,kBAAkB,qCAAqC,OAAO,IAAI;AACzG,QAAM,aAAa,OAAO;AAC1B,SAAO,QAAQ,CAAC,OAAO,OAAO;AAC5B,aAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,aAAO,OAAO,QAAQ,MAAM,QAAQ,WAAW,KAAK,MAAM,kBAAkB,2BAA2B,QAAQ,gDAAgD,+CAA+C,KAAK;AAAA,IACrN;AAAA,EACF,CAAC;AACH;AACA,SAAS,iBAAiB,QAAQ,MAAM;AACtC,QAAM,cAAc,OAAO,GAAG,MAAM;AACpC,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,gBAAY,SAAS,OAAO,IAAI;AAAA,EAClC;AACA,SAAO;AACT;AAGA,IAAI,wBAAwB;AAC5B,SAAS,yBAAyB,QAAQ;AACxC,MAAI,UAAU,uBAAuB;AACnC,WAAO;AAAA,EACT;AACA,SAAO,eAAe,QAAQ,KAAK,MAAM,KAAK,KAAK,MAAM,CAAC,CAAC;AAC7D;AAGA,SAAS,eAAe,QAAQ,aAAa,YAAY;AACvD,QAAM,UAAU,cAAc,OAAO,WAAW,WAAW,SAAS,OAAO;AAC3E,QAAM,UAAU,eAAe,OAAO,WAAW,WAAW,SAAS,OAAO;AAC5E,SAAO,CAAC,SAAS,OAAO;AAC1B;AAGA,SAAS,YAAY,YAAY,YAAY,OAAO,eAAe,MAAM;AACvE,MAAI,WAAW,CAAC;AAChB,MAAI,cAAc;AAChB,eAAW,SAAS,OAAO,WAAW,MAAM,CAAC,CAAC;AAC9C,aAAS,KAAK,WAAW,KAAK,KAAK;AACnC,eAAW,SAAS,OAAO,WAAW,MAAM,CAAC,CAAC;AAAA,EAChD,OAAO;AACL,eAAW,SAAS,OAAO,WAAW,EAAE;AACxC,UAAM,gBAAgB,WAAW;AACjC,aAAS,KAAK,GAAG,KAAK,eAAe,EAAE,IAAI;AACzC,iBAAW,SAAS,OAAO,CAAC,WAAW,KAAK,KAAK,WAAW,KAAK,WAAW,GAAG,CAAC;AAAA,IAClF;AACA,eAAW,SAAS,OAAO,WAAW,MAAM,gBAAgB,CAAC,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,SAAS,YAAY,cAAc,gBAAgB,eAAe,MAAM;AACtE,QAAM,WAAW,CAAC;AAClB,MAAI,cAAc;AAChB,aAAS,KAAK,cAAc;AAC5B,aAAS,KAAK,iBAAiB,GAAG,KAAK,cAAc,EAAE,IAAI;AACzD,UAAI,MAAM,IAAI,gBAAgB;AAC5B,iBAAS,KAAK,EAAE;AAChB,iBAAS,KAAK,MAAM,iBAAiB,EAAE;AAAA,MACzC,OAAO;AACL,iBAAS,KAAK,EAAE;AAAA,MAClB;AAAA,IACF;AAAA,EACF,OAAO;AACL,UAAM,sBAAsB,CAAC;AAC7B,UAAM,qBAAqB,CAAC;AAC5B,aAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,UAAI,MAAM,iBAAiB,IAAI,KAAK,KAAK,MAAM,GAAG;AAChD,2BAAmB,KAAK,EAAE;AAAA,MAC5B,OAAO;AACL,4BAAoB,KAAK,EAAE;AAAA,MAC7B;AAAA,IACF;AACA,aAAS,KAAK,GAAG,mBAAmB;AACpC,aAAS,KAAK,CAAC;AACf,aAAS,KAAK,GAAG,kBAAkB;AAAA,EACrC;AACA,SAAO;AACT;AACA,SAAS,oBAAoB,YAAY,YAAY,OAAO,eAAe,MAAM;AAC/E,QAAM,mBAAmB,CAAC;AAC1B,MAAI,cAAc;AAChB,qBAAiB,KAAK,WAAW,KAAK,KAAK;AAAA,EAC7C,OAAO;AACL,qBAAiB,KAAK,WAAW,KAAK,KAAK;AAAA,EAC7C;AACA,WAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,QAAI,MAAM,WAAW,QAAQ;AAC3B,UAAI,cAAc;AAChB,yBAAiB,KAAK,WAAW,KAAK,KAAK,WAAW,GAAG;AAAA,MAC3D,OAAO;AACL,yBAAiB,KAAK,WAAW,MAAM,WAAW,KAAK,EAAE;AAAA,MAC3D;AAAA,IACF,OAAO;AACL,uBAAiB,KAAK,WAAW,GAAG;AAAA,IACtC;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,oBAAoB,OAAO,YAAY;AAC9C,QAAM,mBAAmB,CAAC,CAAC;AAC3B,WAAS,KAAK,GAAG,KAAK,YAAY,EAAE,IAAI;AACtC,qBAAiB,KAAK,MAAM,IAAI,EAAE;AAAA,EACpC;AACA,SAAO;AACT;AACA,SAAS,aAAa,gBAAgB,OAAO,YAAY;AACvD,QAAM,YAAY,eAAe,MAAM,GAAG,CAAC;AAC3C,WAAS,KAAK,GAAG,KAAK,YAAY,EAAE,IAAI;AACtC,cAAU,KAAK,eAAe,KAAK,KAAK,MAAM,IAAI,KAAK,MAAM,IAAI,EAAE;AAAA,EACrE;AACA,SAAO;AACT;AAGA,IAAI,kBAAkB;AACtB,IAAI,aAAa;AAGjB,IAAI,QAAQ;AACZ,IAAI,SAAS;AACb,IAAI,SAAS;AACb,IAAI,SAAS;AACb,IAAI,SAAS;AACb,IAAI,SAAS;AAGb,SAAS,uBAAuB,OAAO,OAAO;AAC5C,MAAI,MAAM,WAAW,MAAM,QAAQ;AACjC,UAAM,IAAI,MAAM,gEAAgE,MAAM,iBAAiB,MAAM,SAAS;AAAA,EACxH;AACA,QAAM,SAAS,IAAI,aAAa,MAAM,SAAS,CAAC;AAChD,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM,GAAG;AAC5C,WAAO,MAAM,MAAM,KAAK;AACxB,WAAO,KAAK,KAAK,MAAM,KAAK;AAAA,EAC9B;AACA,SAAO;AACT;AACA,SAAS,uBAAuB,UAAU;AACxC,QAAM,QAAQ,IAAI,aAAa,SAAS,SAAS,CAAC;AAClD,QAAM,QAAQ,IAAI,aAAa,SAAS,SAAS,CAAC;AAClD,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM,GAAG;AAC9C,UAAM,KAAK,KAAK,SAAS;AACzB,UAAM,KAAK,KAAK,SAAS,KAAK;AAAA,EAChC;AACA,SAAO,EAAE,MAAM,OAAO,MAAM,MAAM;AACpC;AACA,SAAS,qBAAqB,UAAU;AACtC,QAAM,MAAM,KAAK,KAAK,SAAS,SAAS,CAAC;AACzC,QAAM,QAAQ,IAAI,aAAa,GAAG;AAClC,QAAM,QAAQ,IAAI,aAAa,GAAG;AAClC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM,GAAG;AAC9C,UAAM,KAAK,MAAM,KAAK,CAAC,KAAK,SAAS;AACrC,UAAM,KAAK,MAAM,KAAK,CAAC,KAAK,SAAS,KAAK;AAAA,EAC5C;AACA,SAAO,EAAE,MAAM,OAAO,MAAM,MAAM;AACpC;AACA,SAAS,oBAAoB,UAAU;AACrC,QAAM,MAAM,KAAK,MAAM,SAAS,SAAS,CAAC;AAC1C,QAAM,QAAQ,IAAI,aAAa,GAAG;AAClC,QAAM,QAAQ,IAAI,aAAa,GAAG;AAClC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM,GAAG;AAC9C,UAAM,KAAK,MAAM,KAAK,CAAC,KAAK,SAAS;AACrC,UAAM,KAAK,MAAM,KAAK,CAAC,KAAK,SAAS,KAAK;AAAA,EAC5C;AACA,SAAO,EAAE,MAAM,OAAO,MAAM,MAAM;AACpC;AACA,SAAS,oBAAoB,UAAUJ,QAAO;AAC5C,QAAM,QAAQ,SAASA,SAAQ;AAC/B,QAAM,QAAQ,SAASA,SAAQ,IAAI;AACnC,SAAO,EAAE,MAAM,OAAO,MAAM,MAAM;AACpC;AACA,SAAS,mBAAmB,MAAM,OAAO,OAAOA,QAAO;AACrD,OAAKA,SAAQ,KAAK;AAClB,OAAKA,SAAQ,IAAI,KAAK;AACxB;AACA,SAAS,UAAU,IAAI,SAAS;AAC9B,QAAM,QAAQ,IAAI,aAAa,KAAK,CAAC;AACrC,QAAM,QAAQ,IAAI,aAAa,KAAK,CAAC;AACrC,WAAS,KAAK,GAAG,KAAK,KAAK,KAAK,KAAK,CAAC,GAAG,MAAM;AAC7C,UAAM,KAAK,UAAU,IAAI,MAAM,KAAK,MAAM,KAAK;AAC/C,UAAM,MAAM,KAAK,IAAI,CAAC;AACtB,UAAM,MAAM,KAAK,IAAI,CAAC;AAAA,EACxB;AACA,SAAO,EAAE,MAAM,OAAO,MAAM,MAAM;AACpC;AACA,SAAS,SAAS,GAAG,IAAI,SAAS;AAChC,QAAM,KAAK,UAAU,IAAI,MAAM,KAAK,MAAM,IAAI;AAC9C,QAAM,QAAQ,KAAK,IAAI,CAAC;AACxB,QAAM,QAAQ,KAAK,IAAI,CAAC;AACxB,SAAO,EAAE,MAAM,OAAO,MAAM,MAAM;AACpC;AAGA,IAAI,QAAQ;AACZ,IAAI,cAAc;AAClB,IAAI,QAAQ;AACZ,IAAI,WAAW;AACf,SAAS,qBAAqB,UAAU,YAAY;AAClD,aAAW,SAAS,QAAQ,OAAO,EAAE;AACrC,QAAM,aAAa,SAAS,SAAS,SAAS,QAAQ,aAAa,EAAE,EAAE,UAAU,MAAM;AACvF,MAAI,YAAY,GAAG;AACjB,UAAM,IAAI,MAAM,+CAA+C;AAAA,EACjE,WAAW,YAAY,GAAG;AACxB,UAAM,IAAI,MAAM,6CAA6C,UAAU;AAAA,EACzE;AACA,QAAM,CAAC,aAAa,YAAY,IAAI,SAAS,MAAM,KAAK;AACxD,SAAO,YAAY,QAAQ,QAAQ,MAAM,IAAI,MAAM,2BAA2B,kCAAkC;AAChH,QAAM,aAAa,YAAY,MAAM,KAAK;AAC1C,QAAM,YAAY,WAAW;AAC7B,MAAI,eAAe,WAAW;AAC5B,UAAM,IAAI,MAAM,YAAY,qCAAqC,YAAY;AAAA,EAC/E;AACA,MAAI,YAAY,GAAG;AACjB,UAAM,IAAI,MAAM,+DAA+D;AAAA,EACjF;AACA,QAAM,UAAU,CAAC;AACjB,WAAS,KAAK,GAAG,KAAK,aAAa,QAAQ,EAAE,IAAI;AAC/C,UAAM,UAAU,aAAa;AAC7B,QAAI,CAAC,WAAW,KAAK,CAAC,cAAc,UAAU,QAAQ,OAAO,MAAM,EAAE,GAAG;AACtE,YAAM,IAAI,MAAM,uCAAuC,8CAA8C;AAAA,IACvG;AACA,QAAI,QAAQ,QAAQ,OAAO,MAAM,IAAI;AACnC,cAAQ,KAAK,OAAO;AAAA,IACtB;AAAA,EACF;AACA,WAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,EAAE,IAAI;AAC9C,UAAM,UAAU,YAAY;AAC5B,QAAI,QAAQ,QAAQ,OAAO,MAAM,MAAM,YAAY,OAAO;AACxD,cAAQ,KAAK,OAAO;AAAA,IACtB;AAAA,EACF;AACA,QAAM,SAAS,IAAI,MAAM,WAAW,MAAM;AAC1C,WAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,QAAI,IAAI,IAAI,WAAW,IAAI,MAAM,EAAE,CAAC,EAAE,SAAS,WAAW,IAAI,QAAQ;AACpE,YAAM,IAAI,MAAM,2CAA2C,WAAW,kEAAkE;AAAA,IAC1I;AACA,WAAO,MAAM,CAAC;AACd,aAAS,IAAI,GAAG,IAAI,WAAW,IAAI,QAAQ,EAAE,GAAG;AAC9C,aAAO,IAAI,KAAK,QAAQ,QAAQ,WAAW,IAAI,EAAE,CAAC;AAAA,IACpD;AAAA,EACF;AACA,QAAM,UAAU,QAAQ;AACxB,QAAM,aAAa,aAAa;AAChC,QAAM,aAAa,CAAC;AACpB,WAAS,KAAK,YAAY,KAAK,SAAS,EAAE,IAAI;AAC5C,eAAW,KAAK,EAAE;AAAA,EACpB;AACA,SAAO,EAAE,SAAS,YAAY,OAAO;AACvC;AACA,SAAS,qBAAqB,OAAO,QAAQ;AAC3C,MAAI,qBAAqB,IAAI,MAAM,KAAK;AACxC,qBAAmB,KAAK,EAAE;AAC1B,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,uBAAmB,OAAO,OAAO;AAAA,EACnC;AACA,QAAM,cAAc,CAAC;AACrB,WAAS,KAAK,GAAG,KAAK,OAAO,EAAE,IAAI;AACjC,QAAI,mBAAmB,QAAQ,IAAI;AACjC,kBAAY,KAAK,EAAE;AAAA,IACrB;AAAA,EACF;AACA,uBAAqB,mBAAmB,OAAO,CAAC,MAAM,MAAM,EAAE;AAC9D,SAAO,EAAE,oBAAoB,YAAY,YAAY;AACvD;AACA,SAAS,oBAAoB,OAAO,QAAQ,SAAS;AACnD,QAAM,WAAW,IAAI,MAAM,KAAK;AAChC,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC1C,UAAM,QAAQ,QAAQ,IAAI;AAC1B,aAAS,IAAI,GAAG,IAAI,OAAO,IAAI,QAAQ,EAAE,GAAG;AAC1C,UAAI,SAAS,OAAO,IAAI,QAAQ,QAAQ;AACtC,iBAAS,OAAO,IAAI,MAAM,MAAM;AAAA,MAClC,OAAO;AACL,eAAO,SAAS,OAAO,IAAI,QAAQ,MAAM,IAAI,MAAM,sBAAsB,SAAS,OAAO,IAAI,eAAe,qBAAqB,KAAK,UAAU,KAAK,wBAAwB,MAAM,IAAI;AAAA,MACzL;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,qBAAqB,YAAY,QAAQ;AAChD,QAAM,OAAO;AACb,QAAM,QAAQ,CAAC;AACf,MAAI,SAAS;AACb,MAAI,WAAW,WAAW,GAAG;AAC3B,SAAK,KAAK,EAAE;AAAA,EACd;AACA,WAAS,WAAW,SAAS;AAC7B,WAAS,KAAK,GAAG,KAAK,QAAQ,EAAE,IAAI;AAClC,UAAM,KAAK,CAAC,CAAC;AAAA,EACf;AACA,QAAM,sBAAsB,CAAC;AAC7B,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,YAAY,KAAK;AACvB,UAAM,cAAc,iBAAiB,QAAQ,SAAS;AACtD,eAAW,aAAa,aAAa;AACnC,UAAI,oBAAoB,QAAQ,SAAS,MAAM,IAAI;AACjD,cAAM,IAAI,KAAK,SAAS;AACxB,4BAAoB,KAAK,SAAS;AAAA,MACpC;AAAA,IACF;AAAA,EACF;AACA,SAAO,EAAE,MAAM,MAAM;AACvB;AACA,SAAS,sBAAsB,MAAM;AACnC,SAAO,KAAK,MAAM,CAAC,KAAKA,WAAU,QAAQA,MAAK;AACjD;AACA,SAAS,iBAAiB,QAAQ,KAAK;AACrC,QAAM,cAAc,CAAC;AACrB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,QAAI,OAAO,IAAI,WAAW,KAAK,OAAO,IAAI,QAAQ,GAAG,MAAM,MAAM,QAAQ,IAAI;AAC3E,kBAAY,KAAK,EAAE;AAAA,IACrB;AAAA,EACF;AACA,SAAO;AACT;AAGA,SAAS,iBAAiB,GAAG,iBAAiB,OAAO,GAAG;AACtD,MAAI,aAAa,CAAC;AAClB,MAAI,OAAO,oBAAoB,UAAU;AACvC,WAAO,EAAE,MAAM,QAAQ,oBAAoB,GAAG,MAAM,+CAA+C;AACnG,iBAAa,IAAI,MAAM,eAAe,EAAE,KAAK,EAAE,MAAM,QAAQ,eAAe;AAAA,EAC9E,OAAO;AACL,UAAM,YAAY,gBAAgB,OAAO,CAACF,SAAQ,UAAU;AAC1D,UAAI,UAAU,IAAI;AAChB,QAAAA,WAAU;AAAA,MACZ;AACA,aAAOA;AAAA,IACT,GAAG,CAAC;AACJ,WAAO,aAAa,GAAG,MAAM,yDAAyD;AACtF,UAAM,WAAW,gBAAgB,QAAQ,EAAE;AAC3C,QAAI,aAAa,IAAI;AACnB,YAAM,QAAQ,gBAAgB,OAAO,CAAC,GAAG,MAAM,IAAI,IAAI,IAAI,IAAI,CAAC;AAChE,sBAAgB,YAAY,EAAE,MAAM,QAAQ;AAAA,IAC9C;AACA,WAAO,EAAE,MAAM,UAAU,gBAAgB,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC,GAAG,MAAM,6DAA6D;AACrI,iBAAa;AAAA,EACf;AACA,SAAO;AACT;AAGA,SAAS,gDAAgD,eAAe;AACtE,SAAO;AAAA,uBACc;AACvB;AACA,SAAS,gDAAgDE,QAAO,OAAO;AACrE,SAAO,WAAWA,0BAAyB;AAC7C;AACA,SAAS,kDAAkDA,QAAO,OAAO,OAAO;AAC9E,SAAO,WAAWA,0BAAyB,YAAY;AACzD;AAGA,SAAS,yDAAyD,MAAM,MAAM;AAC5E,SAAO,iDAAiD,YAAY;AACtE;AACA,SAAS,8CAA8C,KAAK,OAAO;AACjE,SAAO,QAAQ,iCAAiC;AAClD;AACA,SAAS,uDAAuD;AAC9D,SAAO;AACT;AACA,SAAS,gDAAgD,YAAY,aAAa;AAChF,QAAMiB,cAAY,cAAc,UAAU;AAC1C,QAAMN,cAAa,cAAc,WAAW;AAC5C,SAAO,2CAA2CM;AAAA,iEACaN,2BAA0B,2BAA2B;AACtH;AACA,SAAS,gDAAgD,YAAY,aAAa;AAChF,QAAMM,cAAY,cAAc,UAAU;AAC1C,QAAMN,cAAa,cAAc,WAAW;AAC5C,SAAO,qCAAqCM,yDAAuDN,2BAA0B,0BAA0B;AACzJ;AAGA,SAAS,0DAA0D;AACjE,SAAO;AACT;AACA,SAAS,+DAA+D;AACtE,SAAO;AACT;AACA,SAAS,yDAAyD,WAAW,YAAY;AACvF,SAAO,cAAc,8BAA8B;AACrD;AACA,SAAS,uDAAuDX,QAAO,YAAY,WAAW;AAC5F,SAAO,gBAAgBA,cAAa,+BAA+B;AACrE;AAGA,IAAI,uBAAuB,CAAC;AAC5BZ,UAAS,sBAAsB;AAAA,EAC7B,0BAA0B,MAAM;AAAA,EAChC,iBAAiB,MAAM;AAAA,EACvB,+BAA+B,MAAM;AACvC,CAAC;AACD,SAAS,8BAA8B,QAAQ,aAAa;AAC1D,MAAI,OAAO;AACX,MAAI;AACJ,MAAI,UAAU,uBAAuB;AACnC,UAAM;AACN,WAAO;AAAA,EACT,OAAO;AACL,UAAM,eAAe,QAAQ,KAAK,MAAM,KAAK,KAAK,MAAM,CAAC,CAAC;AAAA,EAC5D;AACA,SAAO,CAAC,MAAM;AACZ,QAAI,MAAM,eAAe,QAAQ,QAAQ;AACvC,aAAO;AAAA,IACT,OAAO;AACL,YAAM,eAAe,QAAQ,MAAM,CAAC;AAAA,IACtC;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,QAAQ,MAAM,aAAa;AACnD,QAAM,WAAW,CAAC;AAClB,QAAM,OAAO,OAAO;AACpB,WAAS,MAAM,GAAG,MAAM,MAAM,OAAO;AACnC,QAAI,QAAQ,MAAM;AAChB,eAAS,KAAK,OAAO,IAAI;AAAA,IAC3B,OAAO;AACL,eAAS,KAAK,WAAW;AAAA,IAC3B;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,yBAAyB,GAAG,SAAS,MAAM,WAAW;AAC7D,QAAM,cAAc,QAAQ,MAAM;AAClC,QAAM,QAAQ,EAAE,MAAM;AACtB,MAAI,cAAc,GAAG;AACnB,QAAI,YAAY,CAAC,eAAe,YAAY,aAAa;AACvD,YAAM,IAAI,MAAM,sCAAsC,gBAAgB,yBAAyB,WAAW;AAAA,IAC5G;AAAA,EACF;AACA,MAAI,YAAY,GAAG;AACjB,iBAAa;AAAA,EACf;AACA,MAAI,YAAY,OAAO;AACrB,UAAM,IAAI,MAAM,cAAc;AAAA,MAC5B,SAAS;AAAA,EACb;AACA,MAAI,OAAO,WAAW;AACpB,UAAM,IAAI,MAAM,cAAc,kDAAkD,QAAQ;AAAA,EAC1F;AACA,WAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,QAAI,EAAE,MAAM,QAAQ,QAAQ,MAAM,KAAK;AACrC,YAAM,IAAI,MAAM,WAAW,QAAQ,EAAE,MAAM,wCAAwC,QAAQ,QAAQ,MAAM,MAAM;AAAA,IACjH;AAAA,EACF;AACA,QAAM,UAAU,EAAE,MAAM;AACxB,QAAM,cAAc,CAAC;AACrB,MAAI,YAAY;AAChB,MAAI,YAAY;AAChB,MAAI,YAAY;AAChB,WAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,gBAAY,KAAK,EAAE,MAAM,GAAG;AAC5B,iBAAa,EAAE,MAAM;AAAA,EACvB;AACA,WAAS,KAAK,WAAW,KAAK,MAAM,MAAM;AACxC,gBAAY,KAAK,EAAE,MAAM,GAAG;AAC5B,iBAAa,EAAE,MAAM;AAAA,EACvB;AACA,WAAS,KAAK,WAAW,KAAK,aAAa,MAAM;AAC/C,gBAAY,KAAK,QAAQ,MAAM,GAAG;AAAA,EACpC;AACA,WAAS,KAAK,OAAO,GAAG,KAAK,OAAO,MAAM;AACxC,gBAAY,KAAK,EAAE,MAAM,GAAG;AAC5B,iBAAa,EAAE,MAAM;AAAA,EACvB;AACA,SAAO,EAAE,WAAW,WAAW,WAAW,SAAS,YAAY;AACjE;AAGA,SAAS,uBAAuB,MAAM;AACpC,MAAI;AACF,WAAO,KAAK,IAAI,CAAC,QAAQ,aAAa,GAAG,CAAC;AAAA,EAC5C,SAAS,KAAP;AACA,UAAM,IAAI,MAAM,4DAA4D,KAAK;AAAA,EACnF;AACF;AACA,SAAS,uBAAuB,SAAS;AACvC,SAAO,QAAQ,IAAI,CAAC,OAAO,aAAa,EAAE,CAAC;AAC7C;AAGA,IAAI,uBAAuB,CAAC;AAC5BA,UAAS,sBAAsB;AAAA,EAC7B,yBAAyB,MAAM;AAAA,EAC/B,yBAAyB,MAAM;AAAA,EAC/B,yBAAyB,MAAM;AAAA,EAC/B,WAAW,MAAM;AACnB,CAAC;AAGD,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAK,KAAK,GAAG,SAAS,GAAG,EAAE,CAAC,EAAE;AAAA,EAC1D;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO;AAAA,MACL,GAAG,MAAM;AACP,cAAM,IAAI,OAAO,KAAK,GAAG,SAAS,CAAC;AACnC,cAAM,IAAI,KAAK,IAAI,OAAO,CAAC,GAAG,CAAC,CAAC;AAChC,eAAO,IAAI,IAAI,IAAI,CAAC,CAAC;AAAA,MACvB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO;AAAA,MACL,GAAG,MAAM;AACP,cAAM,IAAI,KAAK,IAAI,OAAO,KAAK,GAAG,SAAS,CAAC,GAAG,CAAC,CAAC;AACjD,eAAO,IAAI,IAAI,CAAC;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,2BAA2B,EAAE,OAAO,EAAE,KAAK;AAC5D,UAAM,OAAO,MAAM;AACjB,UAAI,MAAM;AACV,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,KAAK,EAAE,KAAK;AAAA,IAC7B;AACA,UAAM,OAAO,MAAM;AACjB,UAAI,MAAM;AACV,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,KAAK,EAAE,KAAK;AAAA,IAC7B;AACA,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,eAAe;AAAA,EACf,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,OAAO,CAAC;AACd,UAAM,QAAQ,CAAC,GAAG,OAAO;AACvB,WAAK,MAAM,MAAM,GAAG,MAAM;AAAA,IAC5B,CAAC;AACD,WAAO;AAAA,EACT;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,UAAU,CAAC,EAAE;AAAA,EACjC;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,UAAU,CAAC,EAAE;AAAA,EACjC;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAK,IAAI,OAAO,CAAC,GAAG,OAAO,KAAK,GAAG,SAAS,CAAC,CAAC,CAAC,CAAC,EAAE;AAAA,EAC9E;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO;AAAA,MACL,GAAG,MAAM;AACP,cAAM,IAAI,KAAK,KAAK,OAAO,CAAC,GAAG,OAAO,KAAK,GAAG,SAAS,CAAC,CAAC,CAAC;AAC1D,eAAO,IAAI,IAAI,CAAC;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,2BAA2B,EAAE,OAAO,EAAE,KAAK;AAC5D,UAAM,OAAO,MAAM;AACjB,YAAM,IAAI,KAAK,OAAO,CAAC,GAAG,OAAO,CAAC,CAAC;AACnC,UAAI,MAAM,IAAI,IAAI,IAAI,GAAG,CAAC,CAAC;AAC3B,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,KAAK,EAAE,KAAK;AAAA,IAC7B;AACA,UAAM,OAAO,MAAM;AACjB,YAAM,IAAI,KAAK,OAAO,CAAC,GAAG,OAAO,CAAC,CAAC;AACnC,UAAI,MAAM,IAAI,IAAI,IAAI,IAAI,GAAG,CAAC,CAAC,CAAC;AAChC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,KAAK,EAAE,KAAK;AAAA,IAC7B;AACA,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAK,OAAO,KAAK,GAAG,SAAS,CAAC,GAAG,CAAC,CAAC,EAAE;AAAA,EACjE;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,OAAO,CAAC,GAAG,OAAO,KAAK,GAAG,SAAS,CAAC,CAAC,CAAC,EAAE;AAAA,EACxE;AACF;AAGA,SAAS,eAAe,IAAI,QAAQ,YAAYe,UAAS,MAAM,iBAAiB;AAC9E,QAAM,MAAM,gBAAgB,IAAI,MAAM,eAAe;AACrD,QAAM,SAAS,gBAAgB,QAAQ,SAAS,eAAe;AAC/D,MAAI,OAAO;AACX,MAAI,UAAU;AACd,MAAI,eAAe;AACnB,MAAI,OAAO,SAAS,GAAG;AACrB,mBAAe;AACf,WAAO,QAAQ,KAAK,CAAC,GAAG,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAC/E,cAAU,QAAQ,QAAQ;AAAA,MACxB;AAAA,MACA,OAAO,MAAM;AAAA,MACb,OAAO,MAAM;AAAA,MACb,OAAO,MAAM;AAAA,MACb,OAAO,MAAM;AAAA,IACf,CAAC;AAAA,EACH;AACA,SAAO,KAAK,SAAS,GAAG,MAAM,0DAA0D,KAAK,OAAO;AACpG,SAAO,QAAQ,SAAS,GAAG,MAAM,6DAA6D,QAAQ,OAAO;AAC7G,4BAA0B,iBAAiB,MAAM,eAAe;AAChE,QAAM,SAAS,EAAE,IAAI,MAAM,OAAO,QAAQ;AAC1C,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB;AAChE,QAAM,MAAM,OAAO,UAAU,eAAe,QAAQ,KAAK;AACzD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAC9E;AACA,SAAO;AACT;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,WAAO;AAAA,MACL,GAAG,MAAM,cAAc,IAAI,GAAG,YAAYA,UAAS,MAAM,eAAe;AAAA,IAC1E;AAAA,EACF;AACF;AAGA,SAAS,aAAa,IAAI,QAAQ,YAAYA,UAAS,MAAM;AAC3D,QAAM,MAAM,gBAAgB,IAAI,MAAM,aAAa;AACnD,QAAM,SAAS,gBAAgB,QAAQ,SAAS,aAAa;AAC7D,SAAO,OAAO,SAAS,IAAI,MAAM,MAAM,kBAAkB,OAAO,oCAAoC,IAAI,OAAO;AAC/G,MAAI,UAAU;AACd,MAAI,OAAO;AACX,MAAI,eAAe;AACnB,MAAI,OAAO,SAAS,GAAG;AACrB,mBAAe;AACf,cAAU,QAAQ,QAAQ,CAAC,GAAG,OAAO,MAAM,IAAI,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE,CAAC;AAChF,WAAO,QAAQ,KAAK,CAAC,GAAG,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EACnE;AACA,SAAO,KAAK,SAAS,GAAG,MAAM,wDAAwD,KAAK,OAAO;AAClG,SAAO,QAAQ,SAAS,GAAG,MAAM,2DAA2D,QAAQ,OAAO;AAC3G,QAAM,SAAS,EAAE,IAAI,MAAM,OAAO,QAAQ;AAC1C,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,KAAK;AAC/C,QAAM,MAAM,OAAO,UAAU,aAAa,QAAQ,KAAK;AACvD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,KAAK,IAAI;AAC3C,WAAO,EAAE,GAAG,MAAM,YAAY,IAAI,GAAG,YAAYA,UAAS,IAAI,EAAE;AAAA,EAClE;AACF;AAGA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,EAAE,YAAY,WAAW,IAAI;AACnC,QAAI,CAAC,cAAc,CAAC,YAAY;AAC9B,aAAO;AAAA,QACL,GAAG,MAAM,OAAO,IAAI,GAAG,OAAO,IAAI;AAAA,QAClC,GAAG,MAAM,OAAO,GAAG,IAAI,MAAM,KAAK;AAAA,MACpC;AAAA,IACF,WAAW,CAAC,cAAc,YAAY;AACpC,aAAO;AAAA,QACL,GAAG,MAAM,OAAO,IAAI,GAAG,OAAO,KAAK;AAAA,QACnC,GAAG,MAAM,OAAO,IAAI,GAAG,MAAM,KAAK;AAAA,MACpC;AAAA,IACF,WAAW,cAAc,CAAC,YAAY;AACpC,aAAO;AAAA,QACL,GAAG,MAAM,OAAO,GAAG,IAAI,OAAO,IAAI;AAAA,QAClC,GAAG,MAAM,OAAO,GAAG,IAAI,OAAO,KAAK;AAAA,MACrC;AAAA,IACF,OAAO;AACL,aAAO;AAAA,QACL,GAAG,MAAM,OAAO,GAAG,IAAI,MAAM,IAAI;AAAA,QACjC,GAAG,MAAM,OAAO,IAAI,GAAG,MAAM,IAAI;AAAA,MACnC;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,YAAY,MAAM,IAAI;AAC9B,WAAO,EAAE,GAAG,MAAM,eAAe,IAAI,YAAY,KAAK,EAAE;AAAA,EAC1D;AACF;AAGA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,mBAAmB;AACzB,UAAM,aAAa,iBAAiB;AACpC,UAAM,cAAc,iBAAiB;AACrC,UAAM,OAAO,MAAM,KAAK,WAAW;AACnC,aAAS,KAAK,WAAW,SAAS,GAAG,MAAM,GAAG,MAAM;AAClD,UAAI,WAAW,QAAQ,YAAY,KAAK;AACtC,aAAK,MAAM;AAAA,MACb,WAAW,WAAW,QAAQ,GAAG;AAC/B,cAAM,IAAI,MAAM,mBAAmB,uCAAuC,eAAe;AAAA,MAC3F;AAAA,IACF;AACA,UAAM,OAAO,CAAC;AACd,aAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,UAAI,KAAK,MAAM,GAAG;AAChB,aAAK,KAAK,EAAE;AAAA,MACd;AAAA,IACF;AACA,WAAO,EAAE,GAAG,MAAM,KAAK,IAAI,MAAM,IAAI,EAAE;AAAA,EACzC;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,GAAG,MAAM,EAAE;AAAA,EAC/B;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,cAAc,aAAa,IAAI;AACvC,WAAO;AAAA,MACL,GAAG,MAAM,MAAM,WAAW,aAAa,GAAG,YAAY,GAAG,UAAU,GAAG,YAAY,CAAC,GAAG,IAAI,UAAU,EAAE,CAAC;AAAA,IACzG;AAAA,EACF;AACF;AAGA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,cAAc;AAC1B;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,eAAe;AAAA,EACf,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,SAAS,MAAM,IAAI,CAAC,OAAO,GAAG,KAAK;AACzC,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,QAAQ,eAAe,MAAM,MAAM,GAAG,KAAK,EAAE;AACnD,UAAM,aAAa,OAAO,IAAI,CAAC,OAAO,GAAG,MAAM;AAC/C,UAAM,aAAa,MAAM,IAAI,YAAY,KAAK;AAC9C,WAAO,WAAW,IAAI,CAAC,OAAO,MAAM,EAAE;AAAA,EACxC;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,QAAQ;AAAA,EAC5B,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,KAAK,OAAO,IAAI;AACvB,UAAM,EAAE,WAAW,SAAAA,UAAS,KAAK,MAAM,WAAW,IAAI;AACtD,WAAO,kBAAkB,SAAS,GAAG,MAAM,iHAAiH,YAAY;AACxK,WAAO;AAAA,MACL,GAAG,MAAM,oBAAoB,IAAI,OAAO,IAAI,SAASA,UAAS,MAAM,UAAU;AAAA,MAC9E,QAAQ,MAAM,qBAAqB,KAAK,IAAI,QAAQ,OAAOA,UAAS,MAAM,UAAU;AAAA,IACtF;AAAA,EACF;AACF;AAGA,IAAI,gCAAgC;AAAA,EAClC,YAAY;AAAA,EACZ,cAAc,CAAC,MAAM,QAAQ;AAAA,EAC7B,UAAU,CAAC,KAAK,OAAO,UAAU;AAC/B,UAAM,CAAC,IAAI,MAAM,IAAI;AACrB,UAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,gBAAgB,IAAI;AAC5D,WAAO;AAAA,MACL,IAAI,MAAM,OAAO,KAAK,QAAQA,UAAS,MAAM,YAAY,GAAG,eAAe;AAAA,MAC3E,QAAQ,MAAM,qBAAqB,KAAK,IAAI,OAAO,OAAOA,UAAS,MAAM,YAAY,eAAe;AAAA,IACtG;AAAA,EACF;AACF;AAGA,SAAS,sBAAsB,GAAG,IAAI,aAAaA,UAAS,MAAM;AAChE,MAAI,MAAM;AACV,MAAI,EAAE,SAAS,GAAG;AAChB,UAAM,QAAQ,GAAG,CAAC,GAAG,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,EAAE,CAAC;AAAA,EACtE;AACA,MAAI,OAAO;AACX,MAAI,KAAK,SAAS,GAAG;AACnB,WAAO,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC5E;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,iEAAiE,IAAI,QAAQ;AAC1G,SAAO,KAAK,SAAS,GAAG,MAAM,8DAA8D,KAAK,QAAQ;AACzG,SAAO,YAAY,WAAW,GAAG,MAAM,mEAAmE,cAAc;AACxH,SAAO,IAAI,MAAM,OAAO,YAAY,IAAI,MAAM,4CAA4C,IAAI,MAAM,yCAAyC,YAAY,KAAK;AAC9J,SAAO,KAAK,MAAM,OAAO,YAAY,IAAI,MAAM,0CAA0C,KAAK,MAAM,2CAA2C,YAAY,MAAM;AACjK,QAAM,SAAS,EAAE,GAAG,KAAK,IAAI,KAAK;AAClC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY;AAChD,SAAO,OAAO,UAAU,wBAAwB,QAAQ,KAAK;AAC/D;AACA,IAAI,uBAAuB,GAAG,EAAE,sBAAsB,CAAC;AAGvD,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,QAAQ;AAAA,EAC5B,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,WAAW,SAAAA,UAAS,KAAK,KAAK,IAAI;AAC1C,WAAO,kBAAkB,SAAS,GAAG,MAAM,iHAAiH,YAAY;AACxK,UAAM,CAAC,KAAK,OAAO,IAAI;AACvB,WAAO;AAAA,MACL,GAAG,MAAM,oBAAoB,IAAI,OAAO,IAAI,SAASA,UAAS,IAAI;AAAA,MAClE,QAAQ,MAAM,qBAAqB,KAAK,IAAI,QAAQ,OAAOA,UAAS,IAAI;AAAA,IAC1E;AAAA,EACF;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC,CAAC,GAAG,EAAE,EAAE;AAAA,EAC1D;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,KAAK,KAAK,GAAG,SAAS,CAAC,GAAG,EAAE,EAAE;AAAA,EACtD;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,WAAO;AAAA,MACL,GAAG,MAAM;AACP,cAAM,cAAc,mBAAmB,CAAC,IAAI,GAAG,EAAE,IAAI;AACrD,YAAI,MAAM,OAAO,IAAI,MAAM,WAAW,CAAC,QAAQ;AAC/C,YAAI,eAAe,MAAM;AACvB,gBAAM,UAAU,KAAK,WAAW;AAAA,QAClC;AACA,eAAO;AAAA,MACT;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,kCAAkC;AAAA,EACpC,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,QAAQ;AAAA,EAC5B,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,WAAW,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC3D,UAAM,aAAa,aAAa,OAAO,CAAC,GAAG,CAAC,IAAI;AAChD,WAAO,kBAAkB,UAAU,GAAG,MAAM,mHAAmH,aAAa;AAC5K,UAAM,CAAC,GAAG,MAAM,IAAI;AACpB,WAAO,EAAE,SAAS,GAAG,MAAM,kFAAkF,EAAE,OAAO;AACtH,WAAO,OAAO,SAAS,GAAG,MAAM,mFAAmF,OAAO,OAAO;AACjI,WAAO,EAAE,MAAM,OAAO,OAAO,MAAM,IAAI,MAAM,mEAAmE,EAAE,MAAM,qDAAqD,OAAO,MAAM,KAAK;AAC/L,WAAO,+BAA+BA,UAAS,UAAU,GAAG,MAAM,6FAA6FA,2BAA0B,cAAc;AACvM,8BAA0B,mBAAmB,MAAM,eAAe;AAClE,WAAO;AAAA,MACL,GAAG,MAAM,mCAAmC,EAAE,OAAO,IAAI,QAAQA,UAAS,MAAM,YAAY,eAAe;AAAA,MAC3G,QAAQ,MAAM,oCAAoC,GAAG,IAAI,OAAO,OAAOA,UAAS,MAAM,YAAY,eAAe;AAAA,IACnH;AAAA,EACF;AACF;AAGA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,QAAQ;AAAA,EAC5B,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,GAAG,MAAM,IAAI;AACpB,UAAM,cAAc,EAAE,GAAG,QAAQ,GAAG;AACpC,UAAM,eAAe,EAAE,GAAG,QAAQ,GAAG;AACrC,WAAO;AAAA,MACL,GAAG,MAAM,OAAO,UAAU,yBAAyB,aAAa,KAAK;AAAA,MACrE,QAAQ,MAAM,OAAO,UAAU,0BAA0B,cAAc,KAAK;AAAA,IAC9E;AAAA,EACF;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,SAAS,EAAE,IAAI,EAAE;AACvB,WAAO,EAAE,GAAG,MAAM,OAAO,UAAU,SAAS,MAAM,EAAE;AAAA,EACtD;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,IAAI,IAAI,IAAI,IAAI,OAAO,CAAC,CAAC,CAAC,GAAG,IAAI,KAAK,KAAK,KAAK,EAAE,CAAC;AACzD,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,CAAC,EAAE;AAAA,EAC/B;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,CAAC,EAAE;AAAA,EAC/B;AACF;AAGA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,cAAc,CAAC,OAAO;AAAA,EACtB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,MAAM,IAAI;AACjB,WAAO,EAAE,OAAO,MAAM,QAAQ,IAAI,OAAO,KAAK,EAAE;AAAA,EAClD;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,CAAC,CAAC,EAAE;AAAA,EACpC;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,2BAA2B,EAAE,OAAO,EAAE,KAAK;AAC5D,UAAM,OAAO,MAAM;AACjB,YAAM,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC;AACtC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,eAAO,QAAQ,KAAK,KAAK,UAAU,GAAG,EAAE,KAAK;AAAA,MAC/C;AACA,aAAO;AAAA,IACT;AACA,UAAM,OAAO,MAAM;AACjB,UAAI,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC;AACpC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,QAAQ,KAAK,KAAK,UAAU,GAAG,EAAE,KAAK;AAAA,MAC9C;AACA,YAAM,MAAM,OAAO,CAAC;AACpB,aAAO,IAAI,IAAI,KAAK,KAAK,KAAK,SAAS,CAAC,CAAC;AAAA,IAC3C;AACA,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,QAAQ,YAAY,OAAO;AAAA,EAC/C,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,gBAAgB,IAAI;AAC5B,UAAM,CAAC,GAAG,OAAO,UAAUS,OAAM,IAAI;AACrC,UAAM,aAAaA,WAAU,OAAO,OAAO,CAAC,IAAIA;AAChD,UAAM,gBAAgB,iBAAiB,MAAM,OAAO,EAAE,KAAK;AAC3D,UAAM,YAAY,CAAC;AACnB,QAAI,MAAM,SAAS,GAAG;AACpB,eAAS,KAAK,GAAG,KAAK,EAAE,MAAM,SAAS,GAAG,EAAE,IAAI;AAC9C,kBAAU,KAAK,EAAE,MAAM,GAAG;AAAA,MAC5B;AACA,gBAAU,KAAK,CAAC;AAAA,IAClB;AACA,UAAM,aAAa,IAAI,GAAG,KAAK;AAC/B,UAAM,oBAAoB,IAAI,IAAI,UAAU;AAC5C,UAAM,sBAAsB,MAAM,KAAK,UAAU,OAAO,eAAe,CAAC,CAAC;AACzE,UAAM,iBAAiB,IAAI,IAAI,IAAI,qBAAqB,mBAAmB,GAAG,mBAAmB,GAAG,OAAO,IAAI,CAAC;AAChH,UAAM,OAAO,MAAM;AACjB,UAAI,MAAM,SAAS,GAAG;AACpB,eAAO,QAAQ,IAAI,IAAI,IAAI,KAAK,QAAQ,qBAAqB,CAAC,GAAG,GAAG,GAAG,MAAM,MAAM,EAAE,CAAC,GAAG,SAAS,CAAC,GAAG,UAAU,GAAG,EAAE,KAAK;AAAA,MAC5H,OAAO;AACL,eAAO,QAAQ,IAAI,IAAI,IAAI,mBAAmB,GAAG,UAAU,GAAG,EAAE,KAAK;AAAA,MACvE;AAAA,IACF;AACA,UAAM,UAAU,MAAM;AACpB,UAAI,UAAU,IAAI,IAAI,qBAAqB,OAAO,EAAE,CAAC,GAAG,iBAAiB;AACzE,UAAI,MAAM,SAAS,GAAG;AACpB,kBAAU,KAAK,SAAS,aAAa;AAAA,MACvC;AACA,aAAO,QAAQ,SAAS,MAAM,KAAK;AAAA,IACrC;AACA,UAAM,cAAc,MAAM;AACxB,UAAI,cAAc,IAAI,IAAI,gBAAgB,UAAU,GAAG,iBAAiB;AACxE,UAAI,MAAM,SAAS,GAAG;AACpB,sBAAc,KAAK,aAAa,aAAa;AAAA,MAC/C;AACA,aAAO,QAAQ,aAAa,MAAM,KAAK;AAAA,IACzC;AACA,UAAM,WAAW,MAAM;AACrB,YAAM,wBAAwB,IAAI,YAAY,mBAAmB;AACjE,UAAI,WAAW,IAAI,IAAI,qBAAqB;AAC5C,UAAI,MAAM,SAAS,GAAG;AACpB,mBAAW,KAAK,UAAU,aAAa;AAAA,MACzC;AACA,aAAO,QAAQ,UAAU,MAAM,KAAK;AAAA,IACtC;AACA,UAAM,YAAY,MAAM;AACtB,UAAI,YAAY;AAChB,UAAI,MAAM,SAAS,GAAG;AACpB,oBAAY,KAAK,WAAW,aAAa;AAAA,MAC3C;AACA,aAAO,QAAQ,WAAW,MAAM,KAAK;AAAA,IACvC;AACA,WAAO;AAAA,MACL,GAAG;AAAA,MACH,MAAM;AAAA,MACN,UAAU;AAAA,MACV,OAAO;AAAA,MACP,QAAQ;AAAA,IACV;AAAA,EACF;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,SAAS;AAAA,EAC7B,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,GAAG,OAAO,IAAI;AACrB,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AACjD,UAAM,OAAO,MAAM;AACjB,YAAM,cAAc,EAAE;AACtB,YAAM,cAAc,QAAQ;AAC5B,YAAM,aAAa,YAAY,MAAM,GAAG,UAAU;AAClD,YAAM,YAAY,WAAW;AAC7B,YAAM,aAAa,YAAY,MAAM,MAAM,YAAY,MAAM,EAAE,MAAM,CAAC;AACtE,YAAM,YAAY,WAAW;AAC7B,YAAM,mBAAmB,WAAW,GAAG,SAAS;AAChD,YAAM,mBAAmB,WAAW,YAAY,GAAG,YAAY,IAAI,SAAS;AAC5E,YAAM,cAAc,YAAY,CAAC,YAAY,CAAC,WAAW,GAAG,UAAU,CAAC;AACvE,YAAM,SAAS,QAAQ,IAAI,WAAW;AACtC,YAAM,kBAAkB,QAAQ,SAAS,CAAC,WAAW,CAAC;AACtD,YAAM,gBAAgB,YAAY,CAAC,CAAC,SAAS,GAAG,kBAAkB,gBAAgB,CAAC;AACnF,YAAM,kBAAkB,UAAU,QAAQ,aAAa;AACvD,UAAI,aAAa,mBAAmB,iBAAiB,iBAAiB,EAAE,MAAM,WAAW;AACzF,YAAM,sBAAsB,uBAAuB,aAAa;AAChE,mBAAa,UAAU,YAAY,mBAAmB;AACtD,aAAO;AAAA,IACT;AACA,WAAO,EAAE,GAAG,MAAM,SAAS,MAAM,QAAQ;AAAA,EAC3C;AACF;AACA,SAAS,WAAW,OAAO,MAAM;AAC/B,QAAM,SAAS,CAAC;AAChB,WAAS,KAAK,OAAO,KAAK,MAAM,EAAE,IAAI;AACpC,WAAO,KAAK,EAAE;AAAA,EAChB;AACA,SAAO;AACT;AACA,SAAS,YAAY,QAAQ;AAC3B,QAAM,SAAS,CAAC;AAChB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,aAAS,IAAI,GAAG,IAAI,OAAO,IAAI,QAAQ,EAAE,GAAG;AAC1C,aAAO,KAAK,OAAO,IAAI,EAAE;AAAA,IAC3B;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,yBAAyB;AAAA,EAC3B,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,WAAO,EAAE,GAAG,MAAM,UAAU,CAAC,GAAG,GAAG,MAAM,UAAU,CAAC,EAAE;AAAA,EACxD;AACF;AAGA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,KAAK,IAAI,SAAS,EAAE;AAAA,EACxC;AACF;AAGA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,OAAAC,OAAM,IAAI;AAClB,UAAMjB,QAAO,QAAQ,GAAG,CAAC;AACzB,WAAO,EAAE,GAAG,MAAM,MAAMA,OAAM,IAAI,IAAI,IAAIiB,MAAK,CAAC,EAAE;AAAA,EACpD;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAK,GAAG,CAAC,CAAC,EAAE;AAAA,EACxC;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC,EAAE;AAAA,EAChD;AACF;AAGA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,cAAc,CAAC;AAAA,EACf,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,KAAK,IAAI;AAChB,UAAM,EAAE,KAAK,IAAI;AACjB,WAAO;AAAA,MACL,QAAQ,MAAM;AACZ,cAAM,WAAW;AACjB,cAAM,WAAW,IAAI,KAAK;AAC1B,eAAO,IAAI,IAAI,IAAI,KAAK,IAAI,MAAM,QAAQ,GAAG,QAAQ,CAAC;AAAA,MACxD;AAAA,IACF;AAAA,EACF;AACF;AAGA,SAAS,oCAAoC,GAAG,GAAG,IAAI,cAAc,GAAG,OAAO,GAAGA,SAAQ,GAAG,OAAO,KAAK;AACvG,QAAM,SAAS,EAAE,GAAG,GAAG,GAAG;AAC1B,QAAM,QAAQ,EAAE,aAAa,MAAM,OAAAA,QAAO,KAAK;AAC/C,SAAO,OAAO,UAAU,SAAS,QAAQ,KAAK;AAChD;AACA,IAAI,qCAAqC,GAAG,EAAE,oCAAoC,CAAC;AAGnF,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,EAAE,aAAa,MAAM,OAAAA,QAAO,KAAK,IAAI;AAC3C,WAAO;AAAA,MACL,GAAG,MAAM,mCAAmC,GAAG,GAAG,IAAI,aAAa,MAAMA,QAAO,IAAI;AAAA,IACtF;AAAA,EACF;AACF;AAGA,SAAS,iBAAiB,IAAI,GAAG,OAAO,UAAU;AAChD,MAAI,EAAE,OAAO,MAAM,MAAM;AACvB,QAAI,QAAQ,GAAG,qBAAqB,EAAE,OAAO,QAAQ,CAAC;AAAA,EACxD;AACA,MAAI,GAAG,OAAO,MAAM,MAAM;AACxB,SAAK,QAAQ,IAAI,qBAAqB,GAAG,OAAO,QAAQ,CAAC;AAAA,EAC3D;AACA,SAAO;AAAA,IACL,GAAG,MAAM;AACP,YAAM,KAAK,IAAI,IAAI,KAAK,MAAM,OAAO,CAAC,GAAG,GAAG,KAAK,CAAC;AAClD,aAAO;AAAA,IACT;AAAA,EACF;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,WAAW;AACjB,UAAM,EAAE,iBAAiB,IAAI;AAC7B,UAAM,IAAI,MAAM;AAChB,UAAM,IAAI,MAAM;AAChB,UAAM,WAAW,eAAe,kBAAkB,EAAE,KAAK;AACzD,UAAM,UAAU,iBAAiB,IAAI,GAAG,GAAG,QAAQ;AACnD,WAAO;AAAA,MACL,GAAG,MAAM;AACP,eAAO,QAAQ,KAAK;AAAA,MACtB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,OAAO,MAAM,IAAI,IAAI,KAAK,aAAa,GAAG,CAAC,GAAG,SAAS,CAAC;AAC9D,UAAM,OAAO,MAAM,IAAI,IAAI,KAAK,KAAK,GAAG,CAAC,GAAG,SAAS,CAAC;AACtD,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,SAAS,eAAe,IAAI,QAAQ,QAAQ,YAAYV,UAAS,MAAM,iBAAiB;AACtF,QAAM,MAAM,gBAAgB,IAAI,MAAM,eAAe;AACrD,QAAM,SAAS,gBAAgB,QAAQ,SAAS,eAAe;AAC/D,QAAM,UAAU,gBAAgB,QAAQ,UAAU,eAAe;AACjE,MAAI,OAAO;AACX,MAAI,UAAU;AACd,MAAI,WAAW;AACf,MAAI,eAAe;AACnB,MAAI,OAAO,SAAS,GAAG;AACrB,mBAAe;AACf,WAAO,QAAQ,KAAK,CAAC,GAAG,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAC/E,cAAU,QAAQ,QAAQ;AAAA,MACxB;AAAA,MACA,OAAO,MAAM;AAAA,MACb,OAAO,MAAM;AAAA,MACb,OAAO,MAAM;AAAA,MACb,OAAO,MAAM;AAAA,IACf,CAAC;AACD,eAAW,QAAQ,SAAS;AAAA,MAC1B;AAAA,MACA,QAAQ,MAAM;AAAA,MACd,QAAQ,MAAM;AAAA,MACd,QAAQ,MAAM;AAAA,MACd,QAAQ,MAAM;AAAA,IAChB,CAAC;AAAA,EACH;AACA,SAAO,KAAK,SAAS,GAAG,MAAM,0DAA0D,KAAK,OAAO;AACpG,SAAO,QAAQ,SAAS,GAAG,MAAM,6DAA6D,QAAQ,OAAO;AAC7G,SAAO,SAAS,SAAS,GAAG,MAAM,8DAA8D,SAAS,OAAO;AAChH,4BAA0B,iBAAiB,MAAM,eAAe;AAChE,QAAM,SAAS,EAAE,IAAI,MAAM,OAAO,SAAS,QAAQ,SAAS;AAC5D,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB;AAChE,QAAM,MAAM,OAAO,UAAU,eAAe,QAAQ,KAAK;AACzD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAC9E;AACA,SAAO;AACT;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,WAAO;AAAA,MACL,GAAG,MAAM,cAAc,IAAI,GAAG,GAAG,YAAYA,UAAS,MAAM,eAAe;AAAA,IAC7E;AAAA,EACF;AACF;AAGA,SAAS,aAAa,IAAI,QAAQ,QAAQ,YAAYA,UAAS,MAAM,iBAAiB;AACpF,QAAM,MAAM,gBAAgB,IAAI,MAAM,aAAa;AACnD,QAAM,SAAS,gBAAgB,QAAQ,SAAS,aAAa;AAC7D,QAAM,UAAU,gBAAgB,QAAQ,UAAU,aAAa;AAC/D,SAAO,OAAO,SAAS,IAAI,MAAM,MAAM,kBAAkB,OAAO,oCAAoC,IAAI,OAAO;AAC/G,SAAO,IAAI,SAAS,GAAG,MAAM,wDAAwD,IAAI,OAAO;AAChG,SAAO,OAAO,SAAS,GAAG,MAAM,2DAA2D,OAAO,OAAO;AACzG,4BAA0B,eAAe,MAAM,eAAe;AAC9D,QAAM,SAAS,EAAE,IAAI,KAAK,OAAO,QAAQ,QAAQ,QAAQ;AACzD,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB;AAChE,SAAO,OAAO,UAAU,aAAa,QAAQ,KAAK;AACpD;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,KAAK,IAAI;AAC3C,WAAO;AAAA,MACL,GAAG,MAAM,YAAY,IAAI,GAAG,GAAG,YAAYA,UAAS,IAAI;AAAA,IAC1D;AAAA,EACF;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,OAAO,eAAe,MAAM,EAAE,KAAK;AACzC,UAAM,SAAS,0BAA0B,EAAE,OAAO,IAAI;AACtD,UAAM,cAAc,OAAO;AAC3B,UAAM,aAAa,cAAc,WAAW;AAC5C,UAAM,OAAO,MAAM;AACjB,YAAM,kBAAkB,EAAE,MAAM,MAAM;AACtC,WAAK,QAAQ,CAAC,UAAU;AACtB,wBAAgB,SAAS;AAAA,MAC3B,CAAC;AACD,YAAM,aAAa,QAAQ,IAAI,eAAe;AAC9C,YAAM,MAAM,IAAI,IAAI,YAAY,MAAM,EAAE,OAAO,SAAS,CAAC,GAAG,UAAU;AACtE,aAAO;AAAA,IACT;AACA,WAAO,EAAE,GAAG,KAAK;AAAA,EACnB;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,WAAW;AACjB,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,eAAe,MAAM,EAAE,KAAK;AAC7C,UAAM,UAAU,iBAAiB,IAAI,GAAG,GAAG,QAAQ;AACnD,WAAO;AAAA,MACL,GAAG,MAAM;AACP,eAAO,QAAQ,KAAK;AAAA,MACtB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,OAAO,MAAM,IAAI,IAAI,KAAK,UAAU,GAAG,CAAC,GAAG,SAAS,CAAC;AAC3D,UAAM,OAAO,MAAM,IAAI,IAAI,KAAK,QAAQ,GAAG,CAAC,GAAG,SAAS,CAAC;AACzD,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,IAAI,MAAM;AAChB,UAAM,EAAE,SAAS,IAAI;AACrB,UAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE;AACxC,WAAO,EAAE,GAAG,MAAM,MAAM,IAAI,OAAO,EAAE,KAAK,EAAE;AAAA,EAC9C;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,2BAA2B,EAAE,OAAO,EAAE,KAAK;AAC5D,UAAM,OAAO,MAAM;AACjB,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,eAAO,QAAQ,KAAK,IAAI,UAAU,GAAG,EAAE,KAAK;AAAA,MAC9C;AACA,aAAO;AAAA,IACT;AACA,UAAM,OAAO,MAAM;AACjB,YAAM,MAAM,IAAI,IAAI,IAAI,MAAM,IAAI,GAAG,CAAC,CAAC,CAAC,CAAC;AACzC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,eAAO,QAAQ,KAAK,KAAK,UAAU,GAAG,EAAE,KAAK;AAAA,MAC/C;AACA,aAAO;AAAA,IACT;AACA,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,2BAA2B,EAAE,OAAO,EAAE,KAAK;AAC5D,UAAM,OAAO,MAAM;AACjB,YAAM,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC;AACtC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,eAAO,QAAQ,KAAK,KAAK,UAAU,GAAG,EAAE,KAAK;AAAA,MAC/C;AACA,aAAO;AAAA,IACT;AACA,UAAM,OAAO,MAAM;AACjB,YAAM,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC;AACtC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,eAAO,QAAQ,KAAK,KAAK,UAAU,GAAG,EAAE,KAAK;AAAA,MAC/C;AACA,aAAO;AAAA,IACT;AACA,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,IAAI,EAAE,EAAE;AAAA,EAC5B;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,SAAS;AAAA,EACxB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,UAAU,MAAM;AACtB,WAAO,EAAE,SAAS,MAAM,MAAM,QAAQ,OAAO,SAAS,EAAE;AAAA,EAC1D;AACF;AAGA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,eAAe;AAAA,EACf,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,aAAa,QAAQ,IAAI,IAAI;AACnC,WAAO,WAAW,IAAI,CAAC,OAAO,MAAM,EAAE;AAAA,EACxC;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,IAAI,MAAM;AAChB,UAAM,EAAE,SAAS,IAAI;AACrB,UAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE;AACxC,WAAO,EAAE,GAAG,MAAM,MAAM,IAAI,OAAO,EAAE,KAAK,EAAE;AAAA,EAC9C;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,GAAG,CAAC,IAAI;AAClB,UAAM,OAAO;AACb,UAAM,OAAO;AACb,UAAM,WAAW,2BAA2B,KAAK,OAAO,KAAK,KAAK;AAClE,UAAM,UAAU,MAAM;AACpB,YAAM,WAAW,KAAK,MAAM,SAAS;AACrC,UAAI,MAAM,IAAI,IAAI,IAAI,UAAU,IAAI,MAAM,IAAI,UAAU,OAAO,CAAC,CAAC,CAAC,CAAC,CAAC;AACpE,YAAM,aAAa,iBAAiB,KAAK,OAAO,QAAQ;AACxD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,KAAK,KAAK,KAAK;AAAA,IAChC;AACA,UAAM,SAAS,MAAM;AACnB,YAAM,YAAY,QAAQ,MAAM,CAAC;AACjC,YAAM,UAAU,MAAM,WAAWjB,MAAK,IAAI,GAAG,UAAU,IAAI,CAAC;AAC5D,UAAI,MAAM,IAAI,IAAI,IAAI,GAAG,OAAO,CAAC;AACjC,YAAM,aAAa,iBAAiB,KAAK,OAAO,QAAQ;AACxD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,KAAK,KAAK,KAAK;AAAA,IAChC;AACA,WAAO,EAAE,GAAG,SAAS,GAAG,OAAO;AAAA,EACjC;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,OAAO;AAAA,EAC3B,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG2B,MAAK,IAAI;AACnB,UAAMjB,QAAO,QAAQ,GAAG,CAAC;AACzB,WAAO;AAAA,MACL,GAAG,MAAM,MAAMA,OAAM,IAAI,IAAI,IAAIiB,MAAK,CAAC;AAAA,MACvC,OAAO,MAAM;AACX,YAAI,MAAM,MAAMjB,OAAM,UAAU,EAAE,GAAG,IAAI,IAAI,CAAC,CAAC;AAC/C,cAAM,aAAa,iBAAiBiB,OAAM,OAAO,GAAG,KAAK;AACzD,YAAI,WAAW,SAAS,GAAG;AACzB,gBAAM,KAAK,KAAK,UAAU;AAAA,QAC5B;AACA,eAAO,QAAQ,KAAKA,OAAM,KAAK;AAAA,MACjC;AAAA,IACF;AAAA,EACF;AACF;AAGA,SAAS,YAAY,GAAG,IAAI,MAAM;AAChC,QAAM,iBAAiB,EAAE,MAAM,MAAM;AACrC,iBAAe,QAAQ;AACvB,QAAM,aAAa,QAAQ,IAAI,cAAc;AAC7C,QAAM,WAAW,QAAQ,GAAG,MAAM,MAAM,KAAK;AAC7C,QAAM,cAAc,QAAQ,GAAG,MAAM,MAAM,IAAI;AAC/C,QAAM,KAAK,IAAI,UAAU,WAAW;AACpC,SAAO,IAAI,YAAY,EAAE;AAC3B;AACA,SAAS,aAAa,GAAG,IAAI,MAAM;AACjC,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,gBAAgB,QAAQ,KAAK;AACnC,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,YAAY;AAChB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,UAAU,GAAG,YAAY;AAAA,EACvC;AACA,QAAM,WAAW,UAAU,MAAM,MAAM;AACvC,QAAM,eAAe,SAAS,OAAO,QAAQ,KAAK,QAAQ,KAAK,MAAM;AACrE,QAAM,eAAe,aAAa,OAAO,CAAC,IAAI,MAAM,KAAK,GAAG,CAAC;AAC7D,WAAS,KAAK,YAAY;AAC1B,QAAM,oBAAoB,UAAU,QAAQ,QAAQ;AACpD,MAAI,WAAW,YAAY,mBAAmB,IAAI,aAAa;AAC/D,aAAW,SAAS,QAAQ,UAAU,KAAK;AAC3C,MAAI,gBAAgB,MAAM;AACxB,UAAM,kBAAkB,qBAAqB,uBAAuB,YAAY;AAChF,eAAW,UAAU,UAAU,eAAe;AAAA,EAChD;AACA,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,KAAK,IAAI;AACjB,QAAI,UAAU,CAAC;AACf,QAAI,SAAS,UAAU,SAAS,MAAM;AACpC,gBAAU,EAAE,MAAM,IAAI,CAAC,GAAG,OAAO,EAAE;AAAA,IACrC,WAAW,OAAO,SAAS,UAAU;AACnC,gBAAU,CAAC,IAAI;AAAA,IACjB,OAAO;AACL,gBAAU;AAAA,IACZ;AACA,WAAO,EAAE,GAAG,MAAM,aAAa,GAAG,IAAI,OAAO,EAAE;AAAA,EACjD;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,2BAA2B,EAAE,OAAO,EAAE,KAAK;AAC5D,UAAM,OAAO,MAAM;AACjB,YAAM,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC;AACtC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,eAAO,QAAQ,KAAK,KAAK,UAAU,GAAG,EAAE,KAAK;AAAA,MAC/C;AACA,aAAO;AAAA,IACT;AACA,UAAM,OAAO,MAAM;AACjB,UAAI,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC;AACpC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,QAAQ,KAAK,KAAK,UAAU,GAAG,EAAE,KAAK;AAAA,MAC9C;AACA,YAAM,MAAM,OAAO,CAAC;AACpB,aAAO,IAAI,IAAI,KAAK,KAAK,KAAK,SAAS,CAAC,CAAC;AAAA,IAC3C;AACA,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,OAAO,CAAC,CAAC,CAAC,EAAE;AAAA,EAC5C;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,UAAMjB,QAAO,IAAI,UAAU,GAAG,CAAC,GAAG,KAAK,CAAC,CAAC;AACzC,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAKA,OAAM,SAAS,CAAC,EAAE;AAAA,EACnD;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAK,KAAK,CAAC,GAAG,SAAS,CAAC,EAAE;AAAA,EACtD;AACF;AAGA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,QAAQ,IAAI,EAAE,KAAK,EAAE;AAAA,EACzC;AACF;AAGA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,cAAc,CAAC,QAAQ;AAAA,EACvB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,MAAM,IAAI;AACjB,UAAM,SAAS,EAAE,IAAI,OAAO;AAC5B,UAAM,YAAY,MAAM,OAAO,UAAU,oBAAoB,QAAQ,KAAK;AAC1E,WAAO,EAAE,QAAQ,UAAU;AAAA,EAC7B;AACF;AAGA,IAAI,kCAAkC;AAAA,EACpC,YAAY;AAAA,EACZ,cAAc,CAAC,QAAQ;AAAA,EACvB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,MAAM,IAAI;AACjB,UAAM,SAAS,EAAE,IAAI,OAAO;AAC5B,UAAM,YAAY,MAAM,OAAO,UAAU,2BAA2B,QAAQ,KAAK;AACjF,WAAO,EAAE,QAAQ,UAAU;AAAA,EAC7B;AACF;AAGA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,OAAO,eAAe,MAAM,GAAG,KAAK;AAC1C,WAAO,EAAE,GAAG,MAAM,QAAQ,IAAI,IAAI,EAAE;AAAA,EACtC;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,IAAI,IAAI,GAAG,GAAG,GAAG,CAAC,CAAC,CAAC,EAAE;AAAA,EACtD;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,WAAW;AAAA,EAC1B,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,SAAS,IAAI;AACpB,WAAO;AAAA,MACL,WAAW,MAAM,KAAK,UAAU,SAAS,GAAG,SAAS;AAAA,MACrD,GAAG,MAAM,IAAI,IAAI,KAAK,WAAW,GAAG,KAAK,CAAC;AAAA,MAC1C,GAAG,MAAM,IAAI,IAAI,KAAK,WAAW,SAAS,GAAG,GAAG,KAAK,CAAC;AAAA,IACxD;AAAA,EACF;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO;AAAA,MACL,GAAG,MAAM;AACP,cAAMA,QAAO,QAAQ,GAAG,OAAO,CAAC,CAAC;AACjC,cAAM,cAAc,OAAO,eAAe;AAC1C,cAAMgB,UAAS,OAAO,UAAU;AAChC,cAAM,qBAAqB,IAAI,IAAIA,OAAM;AACzC,cAAM,mBAAmB,IAAI,IAAI,IAAI,WAAW,GAAG,IAAI,KAAK,GAAG,SAAS,CAAC,CAAC;AAC1E,eAAO,MAAMhB,OAAM,oBAAoB,gBAAgB;AAAA,MACzD;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,GAAG,IAAI,OAAO,CAAC,GAAG,CAAC,CAAC,CAAC,EAAE;AAAA,EACvD;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC,GAAG,EAAE,EAAE;AAAA,EACrD;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,KAAK,KAAK,GAAG,SAAS,CAAC,GAAG,EAAE,EAAE;AAAA,EACtD;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,OAAO,MAAAL,MAAK,IAAI;AACxB,UAAM,aAAa,EAAE;AACrB,UAAM,CAAC,QAAQ,KAAK,IAAI,iBAAiB,GAAG,OAAOA,KAAI;AACvD,UAAM,WAAW,CAAC;AAClB,aAAS,KAAK,GAAG,KAAK,GAAG,MAAM,MAAM;AACnC,eAAS,KAAK,CAAC,OAAO,KAAK,WAAW,MAAM,OAAO,MAAM,MAAM,GAAG,CAAC;AAAA,IACrE;AACA,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,QAAQ,EAAE;AAAA,EACtC;AACF;AAGA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,IAAI,IAAI;AAChB,UAAM,WAAW;AACjB,UAAM,WAAW,IAAI,IAAI,CAAC;AAC1B,WAAO;AAAA,MACL,QAAQ,MAAM,IAAI,UAAU,IAAI,KAAK,UAAU,CAAC,GAAG,GAAG,QAAQ,GAAG,CAAC,CAAC;AAAA,IACrE;AAAA,EACF;AACF;AAGA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,QAAQ,CAAC,CAAC,EAAE;AAAA,EACxC;AACF;AAGA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,YAAY,SAAS,IAAI;AACjC,WAAO,EAAE,GAAG,MAAM,eAAe,IAAI,YAAY,QAAQ,EAAE;AAAA,EAC7D;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,KAAK,IAAI;AACjB,WAAO,EAAE,GAAG,MAAM,OAAO,IAAI,IAAI,EAAE;AAAA,EACrC;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,KAAK,KAAK,GAAG,SAAS,CAAC,GAAG,CAAC,CAAC,EAAE;AAAA,EAC9D;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,KAAK,GAAG,SAAS,GAAG,CAAC,CAAC,EAAE;AAAA,EACxD;AACF;AAGA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,MAAM,OAAO,CAAC;AACpB,UAAM,OAAO,MAAM,IAAI,IAAI,IAAI,KAAK,IAAI,GAAG,CAAC,CAAC,CAAC;AAC9C,UAAM,OAAO,MAAM,IAAI,IAAI,IAAI,KAAK,IAAI,GAAG,CAAC,CAAC,CAAC;AAC9C,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,2BAA2B,EAAE,OAAO,EAAE,KAAK;AAC5D,UAAM,OAAO,MAAM;AACjB,UAAI,MAAM;AACV,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,KAAK,EAAE,KAAK;AAAA,IAC7B;AACA,UAAM,OAAO,MAAM;AACjB,UAAI,MAAM;AACV,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,IAAI,GAAG,GAAG,EAAE,KAAK;AAAA,IAClC;AACA,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,kBAAkB,EAAE,MAAM,MAAM;AACtC,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,OAAO,eAAe,MAAM,EAAE,KAAK;AACzC,SAAK,QAAQ,CAAC,UAAU;AACtB,sBAAgB,SAAS;AAAA,IAC3B,CAAC;AACD,UAAM,aAAa,QAAQ,IAAI,eAAe;AAC9C,UAAM,OAAO,IAAI,YAAY,MAAM,EAAE,OAAO,SAAS,CAAC;AACtD,WAAO,EAAE,GAAG,MAAM,KAAK;AAAA,EACzB;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,OAAO,IAAI,CAAC,CAAC,CAAC,EAAE;AAAA,EAC5C;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,OAAO,CAAC,GAAG,OAAO,CAAC,CAAC,GAAG,EAAE,EAAE;AAAA,EACvD;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,OAAO,MAAM;AACjB,UAAI,QAAQ,UAAU,CAAC;AACvB,UAAI,EAAE,SAAS,GAAG;AAChB,iBAAS,KAAK,GAAG,KAAK,KAAK,IAAI,EAAE,IAAI;AACnC,kBAAQ,KAAK,OAAO,MAAM,IAAI,CAAC,KAAK,EAAE,MAAM,EAAE,GAAG,CAAC,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,QAChE;AAAA,MACF,WAAW,EAAE,SAAS,GAAG;AACvB,iBAAS,KAAK,GAAG,KAAK,KAAK,IAAI,EAAE,IAAI;AACnC,mBAAS,IAAI,GAAG,IAAI,KAAK,IAAI,EAAE,GAAG;AAChC,oBAAQ,KAAK,OAAO,MAAM,IAAI,CAAC,KAAK,EAAE,MAAM,IAAI,IAAI,EAAE,MAAM,EAAE,GAAG;AAAA,cAC/D,EAAE,MAAM;AAAA,cACR,EAAE,MAAM;AAAA,YACV,CAAC,CAAC;AAAA,UACJ;AAAA,QACF;AAAA,MACF,WAAW,EAAE,SAAS,GAAG;AACvB,iBAAS,KAAK,GAAG,KAAK,KAAK,IAAI,EAAE,IAAI;AACnC,mBAAS,IAAI,GAAG,IAAI,KAAK,IAAI,EAAE,GAAG;AAChC,qBAAS,IAAI,GAAG,IAAI,KAAK,IAAI,EAAE,GAAG;AAChC,sBAAQ,KAAK,OAAO,MAAM,IAAI,CAAC,KAAK,EAAE,MAAM,IAAI,IAAI,EAAE,MAAM,IAAI,IAAI,EAAE,MAAM,EAAE,GAAG,CAAC,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,YACxH;AAAA,UACF;AAAA,QACF;AAAA,MACF,WAAW,EAAE,SAAS,GAAG;AACvB,iBAAS,KAAK,GAAG,KAAK,KAAK,IAAI,EAAE,IAAI;AACnC,mBAAS,IAAI,GAAG,IAAI,KAAK,IAAI,EAAE,GAAG;AAChC,qBAAS,IAAI,GAAG,IAAI,KAAK,IAAI,EAAE,GAAG;AAChC,uBAAS,KAAK,GAAG,KAAK,KAAK,IAAI,EAAE,IAAI;AACnC,wBAAQ,KAAK,OAAO,MAAM,IAAI;AAAA,kBAC5B,KAAK,EAAE,MAAM;AAAA,kBACb,IAAI,EAAE,MAAM;AAAA,kBACZ,IAAI,EAAE,MAAM;AAAA,kBACZ,KAAK,EAAE,MAAM;AAAA,gBACf,GAAG,CAAC,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,cACtD;AAAA,YACF;AAAA,UACF;AAAA,QACF;AAAA,MACF,OAAO;AACL,cAAM,IAAI,MAAM,2DAA2D,EAAE,mBAAmB;AAAA,MAClG;AACA,aAAO;AAAA,IACT;AACA,WAAO,EAAE,GAAG,KAAK;AAAA,EACnB;AACF;AAGA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,iBAAiB;AACvB,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,WAAW,uBAAuB,IAAI;AAC5C,WAAO,EAAE,GAAG,MAAM,UAAU,IAAI,QAAQ,EAAE;AAAA,EAC5C;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,cAAc;AACpB,UAAM,EAAE,KAAK,IAAI;AACjB,WAAO,EAAE,OAAO,MAAM,MAAM,IAAI,IAAI,EAAE;AAAA,EACxC;AACF;AAGA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,cAAc,CAAC,YAAY;AAAA,EAC3B,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,UAAU,IAAI;AACrB,UAAM,OAAO,MAAM;AACjB,aAAO,oBAAoB,IAAI,UAAU;AAAA,IAC3C;AACA,WAAO,EAAE,GAAG,KAAK;AAAA,EACnB;AACF;AACA,SAAS,oBAAoB,GAAG,SAAS;AACvC,QAAM,qBAAqB,QAAQ,SAAS,UAAU,OAAO,CAAC;AAC9D,QAAM,WAAW,OAAO,GAAG,kBAAkB;AAC7C,MAAI,aAAa,aAAa,SAAS,OAAO,GAAG,OAAO,CAAC;AACzD,QAAM,WAAW,SAAS,OAAO,WAAW;AAC5C,WAAS,KAAK,GAAG,KAAK,UAAU,EAAE,IAAI;AACpC,iBAAa,WAAW,YAAY,KAAK,CAAC;AAAA,EAC5C;AACA,eAAa,WAAW,YAAY,MAAM,SAAS,OAAO,MAAM,CAAC;AACjE,QAAM,YAAY,UAAU,QAAQ;AACpC,SAAO,MAAM,YAAY,UAAU,SAAS;AAC9C;AAGA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,cAAc;AAAA,EAChB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,WAAW,kBAAkB,aAAa;AACxC,mBAAiB,cAAc;AACjC;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,GAAG;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,CAAC;AACrB;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,MAAM,UAAU;AAC9D,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,MAAM,QAAQ;AACjC;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,MAAM,UAAU;AAC9D,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,MAAM,QAAQ;AACjC;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,MAAM;AACvD,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,IAAI;AAC1B;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,MAAM;AACvD,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,IAAI;AAC1B;AAGA,qBAAqB,EAAE,UAAU,WAAW,WAAW;AACrD,OAAK,gBAAgB;AACrB,SAAO,KAAK,SAAS,GAAG,MAAM,qCAAqC;AACnE,SAAO,QAAQ,MAAM,CAAC,CAAC;AACzB;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,OAAO;AACxD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,KAAK;AACzB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC,KAAK,IAAI,CAAC;AAClC;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,MAAM,SAAS;AAC9D,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC,MAAM,OAAO,CAAC;AACtC;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,MAAM,SAAS,OAAO;AACrE,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC,MAAM,SAAS,KAAK,CAAC;AAC7C;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,MAAM,SAAS,OAAO,QAAQ;AAC7E,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC,MAAM,SAAS,OAAO,MAAM,CAAC;AACrD;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,MAAM,SAAS,OAAO,QAAQ,QAAQ;AACrF,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC,MAAM,SAAS,OAAO,QAAQ,MAAM,CAAC;AAC7D;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,SAAS,GAAG;AACnD,OAAK,gBAAgB;AACrB,SAAO,MAAM,MAAM,CAAC;AACtB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,YAAYY,UAAS,MAAM,iBAAiB;AAC9F,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,YAAYA,UAAS,MAAM,eAAe;AACjE;AAGA,qBAAqB,EAAE,UAAU,iBAAiB,SAAS,YAAY,OAAO;AAC5E,OAAK,gBAAgB;AACrB,SAAO,eAAe,MAAM,YAAY,KAAK;AAC/C;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAAS,OAAO,UAAU,QAAQS,SAAQ,iBAAiB;AACtG,OAAK,gBAAgB;AACrB,SAAO,UAAU,MAAM,OAAO,UAAU,QAAQA,SAAQ,eAAe;AACzE;AAGA,qBAAqB,EAAE,UAAU,cAAc,SAAS,OAAO;AAC7D,OAAK,gBAAgB;AACrB,SAAO,YAAY,MAAM,KAAK;AAChC;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,OAAO;AACtD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,KAAK;AACzB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,cAAc,SAAS,MAAM,MAAM;AAClE,OAAK,gBAAgB;AACrB,SAAO,YAAY,MAAM,MAAM,IAAI;AACrC;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,GAAG,MAAM;AAC1D,OAAK,gBAAgB;AACrB,MAAI,aAAa,QAAQ;AACvB,QAAI,CAAC,CAAC;AAAA,EACR;AACA,SAAO,OAAO,CAAC,MAAM,GAAG,CAAC,GAAG,IAAI;AAClC;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,QAAQ,QAAQ,MAAM,YAAY,UAAU,iBAAiB;AAC9G,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,QAAQ,QAAQ,MAAM,YAAY,UAAU,eAAe;AACjF;AAGA,qBAAqB,EAAE,UAAU,kBAAkB,SAAS,QAAQ,aAAaT,UAAS,MAAM,iBAAiB;AAC/G,OAAK,gBAAgB;AACrB,SAAO,gBAAgB,MAAM,QAAQ,aAAaA,UAAS,MAAM,eAAe;AAClF;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,QAAQA,UAAS,MAAM,YAAY,WAAW,iBAAiB;AAChH,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,QAAQA,UAAS,MAAM,YAAY,WAAW,eAAe;AACnF;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,MAAM,WAAW,UAAU;AAC7E,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,MAAM,WAAW,QAAQ;AAChD;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,MAAM,WAAW,UAAU;AAC5E,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,MAAM,WAAW,QAAQ;AAC/C;AAGA,qBAAqB,EAAE,UAAU,eAAe,SAAS,WAAW,YAAY;AAC9E,OAAK,gBAAgB;AACrB,SAAO,aAAa,MAAM,WAAW,UAAU;AACjD;AAGA,qBAAqB,EAAE,UAAU,kBAAkB,SAAS,QAAQA,UAAS,MAAM,YAAY,WAAW,iBAAiB;AACzH,OAAK,gBAAgB;AACrB,SAAO,gBAAgB,MAAM,QAAQA,UAAS,MAAM,YAAY,WAAW,eAAe;AAC5F;AAGA,qBAAqB,EAAE,UAAU,aAAa,SAAS,QAAQA,UAAS,MAAM,WAAW,YAAY;AACnG,OAAK,gBAAgB;AACrB,SAAO,WAAW,MAAM,QAAQA,UAAS,MAAM,WAAW,UAAU;AACtE;AAGA,qBAAqB,EAAE,UAAU,WAAW,SAAS,GAAG;AACtD,OAAK,gBAAgB;AACrB,SAAO,SAAS,MAAM,CAAC;AACzB;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,GAAG;AACjD,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,CAAC;AACpB;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,GAAG;AACjD,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,CAAC;AACpB;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,SAAS,GAAG;AACnD,OAAK,gBAAgB;AACrB,SAAO,MAAM,MAAM,CAAC;AACtB;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,gBAAgB,SAAS,MAAM,UAAU;AACxE,OAAK,gBAAgB;AACrB,SAAO,cAAc,MAAM,MAAM,QAAQ;AAC3C;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,aAAa,SAAS,MAAM;AAC3D,OAAK,gBAAgB;AACrB,SAAO,WAAW,MAAM,IAAI;AAC9B;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,UAAU,WAAW;AACpD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC,KAAK,IAAI,CAAC;AAClC;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,WAAW,SAAS,GAAG;AACtD,OAAK,gBAAgB;AACrB,SAAO,SAAS,MAAM,CAAC;AACzB;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,SAAS,MAAM;AAChE,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,SAAS,IAAI;AACnC;AAGA,qBAAqB,EAAE,UAAU,eAAe,SAAS,GAAG;AAC1D,OAAK,gBAAgB;AACrB,SAAO,aAAa,MAAM,CAAC;AAC7B;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,GAAG;AACrD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC;AACxB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,WAAW,WAAW;AACrD,OAAK,gBAAgB;AACrB,SAAO,UAAU,IAAI;AACvB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,OAAO,IAAI;AACpB;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAASU,QAAO;AAC3D,OAAK,gBAAgB;AACrB,SAAO,UAAU,MAAMA,MAAK;AAC9B;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAAS,GAAG;AACvD,OAAK,gBAAgB;AACrB,SAAO,UAAU,MAAM,CAAC;AAC1B;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,GAAG;AAClD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,CAAC;AACrB;AAGA,qBAAqB,EAAE,UAAU,6BAA6B,SAAS,aAAa,MAAMA,QAAO,MAAM;AACrG,OAAK,gBAAgB;AACrB,SAAO,2BAA2B,MAAM,aAAa,MAAMA,QAAO,IAAI;AACxE;AAGA,qBAAqB,EAAE,UAAU,aAAa,WAAW;AACvD,OAAK,gBAAgB;AACrB,SAAO,WAAW,IAAI;AACxB;AAGA,qBAAqB,EAAE,UAAU,aAAa,SAAS,MAAM;AAC3D,OAAK,gBAAgB;AACrB,SAAO,WAAW,MAAM,IAAI;AAC9B;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAAS,MAAM,UAAU;AACpE,OAAK,gBAAgB;AACrB,SAAO,UAAU,MAAM,MAAM,QAAQ;AACvC;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO3B,MAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,aAAa,SAAS,GAAG;AACxD,OAAK,gBAAgB;AACrB,SAAO,WAAW,MAAM,CAAC;AAC3B;AAGA,qBAAqB,EAAE,UAAU,aAAa,WAAW;AACvD,OAAK,gBAAgB;AACrB,SAAO,WAAW,IAAI;AACxB;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAAS,GAAG;AACvD,OAAK,gBAAgB;AACrB,SAAO,UAAU,MAAM,CAAC;AAC1B;AAGA,qBAAqB,EAAE,UAAU,aAAa,SAAS,GAAG;AACxD,OAAK,gBAAgB;AACrB,SAAO,WAAW,MAAM,CAAC;AAC3B;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,GAAG,YAAY,YAAY;AAC5E,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,GAAG,YAAY,UAAU;AAC/C;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,YAAYiB,UAAS,MAAM,iBAAiB;AAC9F,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,YAAYA,UAAS,MAAM,eAAe;AACjE;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,MAAM,UAAU;AAC9D,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,MAAM,QAAQ;AACjC;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,GAAG;AACrD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC;AACxB;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,MAAM,UAAU;AAC/D,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,MAAM,QAAQ;AAClC;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,MAAM,UAAU;AAC9D,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,MAAM,QAAQ;AACjC;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,GAAG;AACrD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC;AACxB;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAAS,UAAU,MAAM;AACpE,OAAK,gBAAgB;AACrB,SAAO,UAAU,MAAM,UAAU,IAAI;AACvC;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,GAAG;AACjD,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,CAAC;AACpB;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,GAAG;AACjD,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,CAAC;AACpB;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,KAAK,MAAM,UAAU;AACpE,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,KAAK,MAAM,QAAQ;AACvC;AAGA,qBAAqB,EAAE,UAAU,WAAW,SAAS,GAAG;AACtD,OAAK,gBAAgB;AACrB,SAAO,SAAS,MAAM,CAAC;AACzB;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,OAAO,UAAU,GAAG,WAAW,GAAG;AACnF,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,OAAO,SAAS,QAAQ;AAC9C;AAGA,qBAAqB,EAAE,UAAU,WAAW,WAAW;AACrD,OAAK,gBAAgB;AACrB,SAAO,SAAS,IAAI;AACtB;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,UAAU,eAAe;AACvE,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,UAAU,aAAa;AAC1C;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,aAAa,aAAae,UAAS,cAAcf,UAAS,iBAAiB;AAC1H,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,aAAa,aAAae,UAAS,cAAcf,UAAS,eAAe;AAC7F;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,MAAM;AACpD,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,IAAI;AACvB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,SAASU,QAAO;AACvD,OAAK,gBAAgB;AACrB,SAAO,MAAM,MAAMA,MAAK;AAC1B;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,MAAM,UAAU;AAC/D,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,MAAM,QAAQ;AAClC;AAGA,qBAAqB,EAAE,UAAU,aAAa,WAAW;AACvD,OAAK,gBAAgB;AACrB,SAAO,WAAW,IAAI;AACxB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAAS,GAAG;AACvD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,EAAE,KAAK;AAC9B;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,OAAO;AACzD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,KAAK;AAC5B;AAGA,qBAAqB,EAAE,UAAU,iBAAiB,SAAS,YAAY,cAAc,kBAAkB;AACrG,OAAK,gBAAgB;AACrB,SAAO,eAAe,MAAM,YAAY,cAAc,gBAAgB;AACxE;AAGA,qBAAqB,EAAE,UAAU,wBAAwB,SAAS,YAAY,cAAc,kBAAkB;AAC5G,OAAK,gBAAgB;AACrB,SAAO,sBAAsB,MAAM,YAAY,cAAc,gBAAgB;AAC/E;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,MAAM;AACxD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,IAAI;AAC3B;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,OAAO,IAAI;AACpB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,kBAAkB,SAAS,iBAAiB,iBAAiBV,UAAS,MAAM,UAAU,YAAY;AACjI,OAAK,gBAAgB;AACrB,SAAO,gBAAgB,MAAM,iBAAiB,iBAAiBA,UAAS,MAAM,UAAU,UAAU;AACpG;AAGA,qBAAqB,EAAE,UAAU,UAAU,WAAW;AACpD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,IAAI;AACrB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,SAAS,OAAOZ,OAAM;AAC7D,OAAK,gBAAgB;AACrB,SAAO,MAAM,MAAM,OAAOA,KAAI;AAChC;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,KAAK;AACvD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,GAAG;AAC1B;AAGA,qBAAqB,EAAE,UAAU,WAAW,WAAW;AACrD,OAAK,gBAAgB;AACrB,SAAO,SAAS,IAAI;AACtB;AAGA,qBAAqB,EAAE,UAAU,iBAAiB,SAAS,YAAY,UAAU;AAC/E,OAAK,gBAAgB;AACrB,SAAO,eAAe,MAAM,YAAY,QAAQ;AAClD;AAGA,qBAAqB,EAAE,UAAU,QAAQ,SAAS,iBAAiB,MAAM;AACvE,OAAK,gBAAgB;AACrB,SAAO,MAAM,MAAM,iBAAiB,IAAI;AAC1C;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,SAAS,WAAW;AACnD,OAAK,gBAAgB;AACrB,SAAO,OAAO,IAAI;AACpB;AAGA,qBAAqB,EAAE,UAAU,oBAAoB,SAAS,GAAG;AAC/D,OAAK,gBAAgB;AACrB,SAAO,kBAAkB,MAAM,CAAC;AAClC;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,MAAM;AACxD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,IAAI;AAC3B;AAGA,qBAAqB,EAAE,UAAU,QAAQ,SAAS,GAAG,MAAM;AACzD,OAAK,gBAAgB;AACrB,QAAM,qBAAqB,aAAa,SAAS,CAAC,MAAM,CAAC,IAAI,CAAC,MAAM,GAAG,CAAC;AACxE,SAAO,MAAM,oBAAoB,IAAI;AACvC;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAASsB,QAAO;AACtD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAMA,MAAK;AACzB;AAGA,qBAAqB,EAAE,UAAU,eAAe,SAAS,OAAO,KAAKV,UAAS,WAAW,SAAS,cAAc,aAAa,gBAAgB;AAC3I,OAAK,gBAAgB;AACrB,SAAO,aAAa,MAAM,OAAO,KAAKA,UAAS,WAAW,SAAS,cAAc,aAAa,cAAc;AAC9G;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,GAAG;AACjD,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,CAAC;AACpB;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,MAAM,UAAU;AAC9D,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,MAAM,QAAQ;AAClC;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,MAAM;AACrD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,IAAI;AACxB;AAGA,qBAAqB,EAAE,UAAU,SAAS,WAAW;AACnD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,MAAM;AAC1B;AAGA,qBAAqB,EAAE,UAAU,UAAU,WAAW;AACpD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,SAAS;AAC7B;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,OAAO;AAC3B;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,GAAG,QAAQ;AAC1D,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,GAAG,MAAM;AAC7B;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAAS,MAAM;AAC1D,OAAK,gBAAgB;AACrB,SAAO,UAAU,MAAM,IAAI;AAC7B;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,MAAM;AACvD,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,IAAI;AAC1B;AAGA,qBAAqB,EAAE,UAAU,qBAAqB,SAAS,YAAY,aAAa;AACtF,OAAK,gBAAgB;AACrB,SAAO,mBAAmB,MAAM,YAAY,WAAW;AACzD;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,MAAM;AACxD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,IAAI;AAC3B;AAGA,qBAAqB,EAAE,UAAU,QAAQ,SAAS,WAAW,GAAG;AAC9D,OAAK,gBAAgB;AACrB,SAAO,MAAM,WAAW,MAAM,CAAC;AACjC;AAGA,qBAAqB,EAAE,UAAU,YAAY,WAAW;AACtD,OAAK,gBAAgB;AACrB,SAAO,UAAU,IAAI;AACvB;AAGA,IAAI,iBAAiB,cAAc,MAAM;AAAA,EACvC,YAAY,SAAS;AACnB,UAAM,OAAO;AACb,WAAO,eAAe,MAAM,eAAe,SAAS;AAAA,EACtD;AACF;AACA,IAAI,eAAe,cAAc,MAAM;AAAA,EACrC,YAAY,SAAS;AACnB,UAAM,OAAO;AACb,WAAO,eAAe,MAAM,aAAa,SAAS;AAAA,EACpD;AACF;AACA,IAAI,aAAa,cAAc,MAAM;AAAA,EACnC,YAAY,SAAS;AACnB,UAAM,OAAO;AACb,WAAO,eAAe,MAAM,WAAW,SAAS;AAAA,EAClD;AACF;AACA,IAAI,sBAAsB,cAAc,MAAM;AAAA,EAC5C,YAAY,SAAS;AACnB,UAAM,OAAO;AACb,WAAO,eAAe,MAAM,oBAAoB,SAAS;AAAA,EAC3D;AACF;AACA,IAAI,iBAAiB,cAAc,MAAM;AAAA,EACvC,YAAY,SAAS;AACnB,UAAM,OAAO;AACb,WAAO,eAAe,MAAM,eAAe,SAAS;AAAA,EACtD;AACF;AAGA,IAAI,WAAW,MAAM;AAAA,EACnB,YAAY,YAAY;AACtB,SAAK,aAAa,cAAc;AAChC,SAAK,QAAwB,oBAAI,IAAI;AAAA,EACvC;AAAA,EACA,IAAI,KAAK;AACP,QAAI;AACJ,QAAI,KAAK,MAAM,IAAI,GAAG,GAAG;AACvB,cAAQ,KAAK,MAAM,IAAI,GAAG;AAC1B,WAAK,MAAM,OAAO,GAAG;AACrB,WAAK,MAAM,IAAI,KAAK,KAAK;AAAA,IAC3B;AACA,WAAO;AAAA,EACT;AAAA,EACA,IAAI,KAAK,OAAO;AACd,QAAI,KAAK,MAAM,IAAI,GAAG,GAAG;AACvB,WAAK,MAAM,OAAO,GAAG;AAAA,IACvB,WAAW,KAAK,MAAM,QAAQ,KAAK,YAAY;AAC7C,YAAM,cAAc,KAAK,MAAM,KAAK,EAAE,KAAK,EAAE;AAC7C,WAAK,MAAM,OAAO,WAAW;AAAA,IAC/B;AACA,SAAK,MAAM,IAAI,KAAK,KAAK;AAAA,EAC3B;AAAA,EACA,gBAAgB;AACd,WAAO,KAAK;AAAA,EACd;AAAA,EACA,cAAc,YAAY;AACxB,QAAI,aAAa,GAAG;AAClB,YAAM,IAAI,MAAM,4DAA4D,aAAa;AAAA,IAC3F;AACA,QAAI,KAAK,aAAa,YAAY;AAChC,eAAS,KAAK,GAAG,KAAK,KAAK,aAAa,YAAY,MAAM;AACxD,cAAM,cAAc,KAAK,MAAM,KAAK,EAAE,KAAK,EAAE;AAC7C,aAAK,MAAM,OAAO,WAAW;AAAA,MAC/B;AAAA,IACF;AACA,SAAK,aAAa;AAAA,EACpB;AACF;AAGA,SAAS,aAAa,OAAO,WAAW;AACtC,MAAI,MAAM,QAAQ,KAAK,GAAG;AACxB,QAAI,WAAW,CAAC;AAChB,aAAS,KAAK,GAAG,KAAK,WAAW,MAAM;AACrC,iBAAW,SAAS,OAAO,KAAK;AAAA,IAClC;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAM,WAAW,IAAI,MAAM,SAAS;AACpC,aAAS,KAAK,KAAK;AACnB,WAAO;AAAA,EACT;AACF;AACA,SAAS,QAAQ,KAAK,SAAS;AAC7B,MAAI,CAAC,KAAK;AACR,UAAM,IAAI,eAAe,OAAO;AAAA,EAClC;AACF;AACA,SAAS,MAAM,QAAQ,UAAU;AAC/B,MAAI,UAAU;AACd,aAAW,QAAQ,QAAQ;AACzB,QAAI,SAAS,UAAU;AACrB;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,IAAI;AAC5B,MAAI,GAAG,WAAW,GAAG;AACnB,WAAO,GAAG;AAAA,EACZ;AACA,SAAO;AACT;AACA,SAAS,OAAO,GAAG;AACjB,MAAI,MAAM,QAAQ,CAAC,GAAG;AACpB,WAAO;AAAA,EACT;AACA,SAAO,CAAC,CAAC;AACX;AACA,SAAS,YAAY,MAAM;AACzB,QAAM,eAAe,KAAK,QAAQ,wBAAwB,OAAO;AACjE,QAAM,WAAW,aAAa,QAAQ,mBAAmB,OAAO,EAAE,YAAY;AAC9E,MAAI,SAAS,OAAO,KAAK;AACvB,WAAO;AAAA,EACT;AACA,SAAO,YAAY;AACrB;AACA,SAAS,YAAY,YAAY;AAC/B,MAAI,WAAW,UAAU,GAAG;AAC1B,WAAO;AAAA,EACT;AACA,MAAI,WAAW,QAAQ,GAAG,MAAM,IAAI;AAClC,WAAO;AAAA,EACT;AACA,SAAO,WAAW,QAAQ,eAAe,CAAC,GAAG,OAAO,GAAG,YAAY,CAAC;AACtE;AACA,IAAI,yBAAyB,CAAC;AAC9B,SAAS,qBAAqB,UAAU;AACtC,MAAI,aAAa,QAAQ,aAAa,QAAQ;AAC5C,WAAO;AAAA,EACT;AACA,QAAM,OAAO,CAAC;AACd,OAAK,eAAe,SAAS,aAAa;AAC1C,OAAK,YAAY,SAAS,UAAU;AACpC,SAAO;AACT;AACA,SAAS,8BAA8BE,SAAQ;AAC7C,MAAIA,WAAU,QAAQ,OAAOA,YAAW,UAAU;AAChD;AAAA,EACF,WAAW,MAAM,QAAQA,OAAM,GAAG;AAChC,IAAAA,QAAO,QAAQ,CAAC,eAAe,8BAA8B,UAAU,CAAC;AAAA,EAC1E,OAAO;AACL,UAAM,SAAS,OAAO,KAAKA,OAAM;AACjC,eAAW,SAAS,QAAQ;AAC1B,YAAM,QAAQA,QAAO;AACrB,UAAI,SAAS,QAAQ,OAAO,UAAU,UAAU;AAC9C,YAAI,CAAC,MAAM,QAAQ,KAAK,KAAK,MAAM,YAAY,aAAa,OAAO,MAAM,aAAa,UAAU;AAC9F,UAAAA,QAAO,SAAS,MAAM;AAAA,QACxB,OAAO;AACL,wCAA8B,KAAK;AAAA,QACrC;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,uBAAuB,YAAY,gBAAgB,CAAC,GAAG,gBAAgB,CAAC,GAAG,sBAAsB,UAAU,iBAAiB,OAAO;AAC1I,MAAI,OAAO,eAAe,UAAU;AAClC,UAAM,eAAe;AACrB,QAAI;AACJ,QAAI,gBAAgB,eAAe;AACjC,WAAK,cAAc;AAAA,IACrB,WAAW,gBAAgB,wBAAwB;AACjD,WAAK,uBAAuB;AAAA,IAC9B,OAAO;AACL,WAAK,cAAc;AACnB,UAAI,MAAM,MAAM;AACd,cAAM,IAAI,WAAW,WAAW,wBAAwB;AAAA,SACvD;AAAA,gBACO,qHAAqH;AAAA,MAC/H;AAAA,IACF;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAMA,UAAS;AACf,QAAIA,QAAO,gBAAgB,QAAQA,QAAO,aAAa,MAAM;AAC3D,YAAM,IAAI,WAAW,GAAG,gDAAgD,KAAK,UAAUA,OAAM;AAAA,mCAChE;AAAA,IAC/B;AACA,UAAM,YAAYA,QAAO;AACzB,QAAI,KAAK;AACT,QAAI,aAAa,eAAe;AAC9B,OAAC,KAAK,UAAU,IAAI,cAAc;AAAA,IACpC,WAAW,aAAa,wBAAwB;AAC9C,OAAC,KAAK,UAAU,IAAI,uBAAuB;AAAA,IAC7C,WAAW,aAAa,eAAe;AACrC,OAAC,KAAK,UAAU,IAAI,cAAc;AAAA,IACpC;AACA,QAAI,OAAO,MAAM;AACf,YAAM,IAAI,WAAW,WAAW,wBAAwB;AAAA,SACrD;AAAA,gBACO,qHAAqH;AAAA,IACjI;AACA,QAAI,cAAc,MAAM;AACtB,YAAM,wBAAwB,CAAC;AAC/B,iBAAW,OAAO,OAAO,KAAK,sBAAsB,GAAG;AACrD,8BAAsB,OAAO,uBAAuB;AAAA,MACtD;AACA,iBAAW,OAAO,OAAO,KAAK,aAAa,GAAG;AAC5C,8BAAsB,OAAO,cAAc;AAAA,MAC7C;AACA,YAAM,eAAeA,QAAO;AAC5B,mBAAa,mBAAmB;AAChC,YAAM,sBAAsB,OAAO,OAAO,CAAC,GAAG,sBAAsB;AACpE,iBAAW,OAAO,OAAO,KAAK,aAAa,GAAG;AAC5C,+BAAuB,OAAO,cAAc;AAAA,MAC9C;AACA,oCAA8BA,QAAO,SAAS;AAC9C,YAAM,YAAY,WAAW,KAAKA,QAAO,WAAW,eAAe,cAAc;AACjF,+BAAyB,OAAO,OAAO,CAAC,GAAG,mBAAmB;AAC9D,aAAO;AAAA,IACT,OAAO;AACL,YAAM,sBAAsB,OAAO,OAAO,CAAC,GAAG,sBAAsB;AACpE,iBAAW,OAAO,OAAO,KAAK,aAAa,GAAG;AAC5C,+BAAuB,OAAO,cAAc;AAAA,MAC9C;AACA,YAAM,YAAY,IAAI,IAAIA,QAAO,SAAS;AAC1C,+BAAyB,OAAO,OAAO,CAAC,GAAG,mBAAmB;AAC9D,aAAO;AAAA,IACT;AAAA,EACF;AACF;AACA,SAAS,cAAc,GAAG,GAAG;AAC3B,SAAO,IAAI,IAAI,KAAK,IAAI,IAAI,IAAI;AAClC;AACA,SAAS,qBAAqB,GAAG,GAAG;AAClC,SAAO,KAAK,cAAc,GAAG,CAAC;AAChC;AACA,SAAS,QAAQ,IAAI;AACnB,MAAI,MAAM,MAAM;AACd,WAAO;AAAA,EACT;AACA,QAAM,MAAM,CAAC;AACb,aAAW,KAAK,IAAI;AAClB,QAAI,IAAI,QAAQ,CAAC,MAAM,IAAI;AACzB,UAAI,KAAK,CAAC;AAAA,IACZ;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,cAAc,KAAK;AAC1B,MAAI,OAAO,MAAM;AACf,UAAM,IAAI,WAAW,yBAAyB,KAAK,UAAU,GAAG,GAAG;AAAA,EACrE;AACA,aAAW,OAAO,KAAK;AACrB,QAAI,IAAI,eAAe,GAAG,GAAG;AAC3B,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,0BAA0B,QAAQ,OAAO,OAAO;AACvD,MAAI,SAAS,MAAM;AACjB;AAAA,EACF;AACA,MAAI,OAAO,QAAQ,KAAK,IAAI,GAAG;AAC7B,UAAM,IAAI,WAAW,GAAG,wBAAwB,4BAA4B,2BAA2B;AAAA,EACzG;AACF;AACA,SAAS,wBAAwB,GAAG,cAAc,YAAY,GAAG,YAAY,UAAU;AACrF,UAAQ,aAAa,CAAC;AACtB,UAAQ,aAAa,SAAS;AAC9B,SAAO,MAAM,QAAQ,CAAC,KAAK,EAAE,UAAU,aAAa,EAAE,UAAU,aAAa,EAAE,MAAM,CAAC,OAAO,OAAO,OAAO,YAAY;AACzH;AACA,SAAS,sBAAsB,OAAO,MAAM;AAC1C,MAAI,MAAM,QAAQ,KAAK,GAAG;AACxB,iBAAa,OAAO,MAAM,SAAS,GAAG,MAAM,GAAG,sCAAsC;AACrF,UAAM,QAAQ,CAAC,GAAG,OAAO,sBAAsB,GAAG,WAAW,KAAK,QAAQ,MAAM,CAAC;AAAA,EACnF,OAAO;AACL,iBAAa,OAAO,OAAO,UAAU,KAAK,KAAK,QAAQ,GAAG,MAAM,YAAY,0CAA0C,uBAAuB,KAAK,IAAI;AAAA,EACxJ;AACF;AACA,SAAS,uBAAuB,OAAO;AACrC,MAAI,UAAU,MAAM;AAClB,WAAO;AAAA,EACT,WAAW,MAAM,QAAQ,KAAK,GAAG;AAC/B,WAAO,MAAM,MAAM,IAAI,CAAC,MAAM,uBAAuB,CAAC,CAAC,EAAE,KAAK,GAAG,IAAI;AAAA,EACvE,WAAW,OAAO,UAAU,UAAU;AACpC,WAAO,IAAI;AAAA,EACb,OAAO;AACL,WAAO,GAAG;AAAA,EACZ;AACF;AACA,SAAS,SAAS,GAAG,QAAQ,SAAS;AACpC,MAAIc,aAAW,WAAW,OAAO,QAAQ,IAAI,aAAa,IAAI;AAC9D,MAAI;AACJ,QAAM,KAAK,IAAI,SAAS;AACtB,UAAMpB,QAAO,WAAW,OAAO,QAAQ,IAAI,aAAa,IAAI;AAC5D,QAAIA,QAAOoB,aAAW,QAAQ;AAC5B,aAAO;AAAA,IACT;AACA,IAAAA,aAAWpB;AACX,iBAAa,EAAE,GAAG,IAAI;AACtB,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,2BAA2B,gBAAgB;AAClD,MAAI,mBAAmB,QAAQ;AAC7B,WAAO;AAAA,EACT;AACA,MAAI,mBAAmB,UAAU;AAC/B,WAAO;AAAA,EACT;AACA,MAAI,mBAAmB,OAAO;AAC5B,WAAO;AAAA,EACT;AACA,SAAO;AACT;AAGA,IAAI,sBAAsB;AAC1B,SAAS,wBAAwB;AAC/B,SAAO;AACT;AACA,IAAI,eAAe,CAAC;AACpB,SAAS,OAAO,SAAS,IAAI;AAC3B,MAAI,EAAE,UAAU,eAAe;AAC7B,iBAAa,UAAU;AAAA,EACzB;AACA,eAAa,WAAW;AACxB,SAAO,SAAS,aAAa,QAAQ,SAAS;AAChD;AAGA,IAAI,2BAA2B,CAAC,iBAAiB,cAAc;AAC/D,IAAI,oCAAoC,CAAC,WAAW,UAAU;AAC9D,IAAI,4BAA4B,CAAC,SAAS,QAAQ,QAAQ;AAC1D,IAAI,yBAAyB,CAAC,OAAO,KAAK;AAC1C,IAAI,kCAAkC,CAAC,OAAO,OAAO,UAAU,KAAK;AAGpE,IAAI,UAA0B,oBAAI,IAAI;AACtC,SAAS,gBAAgB,OAAO;AAC9B,4BAA0B,0BAA0B,cAAc,KAAK;AACzE;AACA,SAAS,yBAAyB,OAAO;AACvC,4BAA0B,mCAAmC,uBAAuB,KAAK;AAC3F;AACA,SAAS,iBAAiB,OAAO;AAC/B,4BAA0B,2BAA2B,eAAe,KAAK;AAC3E;AACA,SAAS,cAAc,OAAO;AAC5B,4BAA0B,wBAAwB,YAAY,KAAK;AACrE;AACA,IAAI,kBAAkB,CAAC;AACvB,IAAI,oBAAoB;AACxB,SAAS,UAAU,MAAM,IAAI;AAC3B,kBAAgB,KAAK,IAAI;AACzB,MAAI;AACF,UAAM,MAAM,GAAG;AACf,oBAAgB,IAAI;AACpB,WAAO;AAAA,EACT,SAAS,IAAP;AACA,oBAAgB,IAAI;AACpB,UAAM;AAAA,EACR;AACF;AACA,SAAS,yBAAyB;AAChC,MAAI,gBAAgB,WAAW,GAAG;AAChC,WAAO;AAAA,EACT,OAAO;AACL,WAAO,gBAAgB,KAAK,iBAAiB,IAAI;AAAA,EACnD;AACF;AACA,SAAS,oBAAoB,YAAY;AACvC,MAAI,CAAC,kBAAkB,UAAU,GAAG;AAClC,UAAM,IAAI,MAAM,+BAA+B,aAAa,GAAG;AAAA,EACjE;AACA,SAAO,uBAAuB,IAAI;AACpC;AACA,SAAS,oBAAoB,YAAY;AACvC,MAAI,CAAC,kBAAkB,UAAU,GAAG;AAClC,UAAM,IAAI,MAAM,+BAA+B,aAAa,GAAG;AAAA,EACjE;AACA,MAAI,CAAC,QAAQ,IAAI,UAAU,GAAG;AAC5B,YAAQ,IAAI,YAAY,CAAC;AAAA,EAC3B;AACA,QAAMC,SAAQ,QAAQ,IAAI,UAAU;AACpC,UAAQ,IAAI,YAAY,QAAQ,IAAI,UAAU,IAAI,CAAC;AACnD,MAAIA,SAAQ,GAAG;AACb,UAAM,SAAS,GAAG,cAAcA;AAChC,YAAQ,IAAI,QAAQ,CAAC;AACrB,WAAO;AAAA,EACT,OAAO;AACL,WAAO;AAAA,EACT;AACF;AACA,IAAI,kBAAkB,IAAI,OAAO,iCAAiC;AAClE,SAAS,kBAAkB,MAAM;AAC/B,SAAO,CAAC,CAAC,KAAK,MAAM,eAAe;AACrC;AAGA,SAAS,UAAU,GAAG;AACpB,SAAO,MAAM,SAAS,EAAE,SAAS,GAAG,EAAE;AACxC;AACA,SAAS,UAAU,QAAQ,OAAO,KAAK;AACrC,MAAI,SAAS,MAAM;AACjB,YAAQ;AAAA,EACV;AACA,MAAI,OAAO,MAAM;AACf,UAAM,OAAO;AAAA,EACf;AACA,MAAI,QAAQ;AACZ,WAAS,KAAK,OAAO,KAAK,KAAK,EAAE,IAAI;AACnC,aAAS,OAAO;AAAA,EAClB;AACA,SAAO;AACT;AACA,SAAS,KAAK,QAAQ;AACpB,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,OAAO;AAAA,EAChB;AACA,MAAI,OAAO,OAAO;AAClB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,UAAM,QAAQ,OAAO;AACrB,QAAI,QAAQ,MAAM;AAChB,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,KAAK,QAAQ;AACpB,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,OAAO;AAAA,EAChB;AACA,MAAI,OAAO,OAAO;AAClB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,UAAM,QAAQ,OAAO;AACrB,QAAI,QAAQ,MAAM;AAChB,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,OAAO,OAAO,KAAK;AAC1B,MAAI,MAAM,OAAO;AACf,UAAM,IAAI,WAAW,QAAQ,iBAAiB,sBAAsB;AAAA,EACtE;AACA,QAAM,MAAM,CAAC;AACb,WAAS,KAAK,OAAO,KAAK,KAAK,EAAE,IAAI;AACnC,QAAI,KAAK,EAAE;AAAA,EACb;AACA,SAAO;AACT;AAGA,IAAI;AACJ,SAAS,UAAU;AACjB,MAAI,YAAY,MAAM;AACpB,eAAW,QAAQ,EAAE,QAAQ;AAAA,EAC/B;AACA,SAAO;AACT;AACA,SAAS,kBAAkB;AACzB,SAAO;AACT;AAGA,SAAS,MAAM,GAAG,OAAO;AACvB,SAAO,KAAK,GAAG,KAAK;AACtB;AACA,SAAS,YAAY,GAAG,OAAO,IAAI;AACjC,QAAM,WAAW,EAAE,MAAM,MAAM;AAC/B,MAAI,OAAO,GAAG;AACZ,WAAO,SAAS,SAAS,OAAO;AAAA,EAClC;AACA,WAAS,OAAO,MAAM,GAAG,CAAC;AAC1B,SAAO,QAAQ,GAAG,QAAQ;AAC5B;AACA,SAAS,OAAO,GAAG,IAAI;AACrB,SAAO,KAAK,MAAM;AAChB,QAAI,EAAE,MAAM,WAAW,GAAG;AACxB,YAAM,IAAI,WAAW,yDAAyD,EAAE,MAAM,gBAAgB;AAAA,IACxG;AACA,UAAM,IAAI,YAAY,GAAG,CAAC;AAC1B,WAAO,MAAM,GAAG,CAAC,GAAG,IAAI,CAAC,CAAC;AAAA,EAC5B,CAAC;AACH;AACA,SAAS,SAAS,GAAG;AACnB,QAAM,WAAW,CAAC,UAAU,EAAE,KAAK,CAAC;AACpC,SAAO,QAAQ,GAAG,QAAQ;AAC5B;AACA,SAAS,aAAa,GAAG;AACvB,MAAI,EAAE,QAAQ,GAAG;AACf,UAAM,IAAI,WAAW,wDAAwD,EAAE,OAAO;AAAA,EACxF;AACA,QAAM,WAAW,CAAC,EAAE,MAAM,IAAI,UAAU,EAAE,OAAO,CAAC,CAAC;AACnD,SAAO,QAAQ,GAAG,QAAQ;AAC5B;AACA,SAAS,oBAAoB,QAAQ,OAAOT,OAAM;AAChD,SAAO,KAAK,MAAM;AAChB,YAAQ,OAAO;AAAA,WACR;AACH,eAAO,QAAQ,QAAQ,OAAOA,KAAI;AAAA,WAC/B;AACH,eAAO,QAAQ,QAAQ,CAAC,OAAO,CAAC,GAAG,CAACA,OAAM,OAAO,MAAM,EAAE,CAAC;AAAA,WACvD;AACH,eAAO,QAAQ,QAAQ,CAAC,OAAO,GAAG,CAAC,GAAG,CAACA,OAAM,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE,CAAC;AAAA,WAC3E;AACH,eAAO,QAAQ,QAAQ,CAAC,OAAO,GAAG,GAAG,CAAC,GAAG,CAACA,OAAM,OAAO,MAAM,IAAI,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE,CAAC;AAAA,WAC/F;AACH,eAAO,MAAM,QAAQ,CAAC,OAAO,GAAG,GAAG,GAAG,CAAC,GAAG;AAAA,UACxCA;AAAA,UACA,OAAO,MAAM;AAAA,UACb,OAAO,MAAM;AAAA,UACb,OAAO,MAAM;AAAA,UACb,OAAO,MAAM;AAAA,QACf,CAAC;AAAA,WACE;AACH,eAAO,MAAM,QAAQ,CAAC,OAAO,GAAG,GAAG,GAAG,GAAG,CAAC,GAAG;AAAA,UAC3CA;AAAA,UACA,OAAO,MAAM;AAAA,UACb,OAAO,MAAM;AAAA,UACb,OAAO,MAAM;AAAA,UACb,OAAO,MAAM;AAAA,UACb,OAAO,MAAM;AAAA,QACf,CAAC;AAAA;AAED,cAAM,IAAI,WAAW,8DAA8D,OAAO,MAAM;AAAA;AAAA,EAEtG,CAAC;AACH;AACA,SAAS,mBAAmB,QAAQ,OAAOA,OAAM;AAC/C,SAAO,KAAK,MAAM;AAChB,YAAQ,OAAO;AAAA,WACR;AACH,eAAO,QAAQ,QAAQ,OAAOA,KAAI;AAAA,WAC/B;AACH,eAAO,QAAQ,QAAQ,CAAC,GAAG,KAAK,GAAG,CAAC,OAAO,MAAM,IAAIA,KAAI,CAAC;AAAA,WACvD;AACH,eAAO,QAAQ,QAAQ,CAAC,GAAG,GAAG,KAAK,GAAG,CAAC,OAAO,MAAM,IAAI,OAAO,MAAM,IAAIA,KAAI,CAAC;AAAA,WAC3E;AACH,eAAO,QAAQ,QAAQ,CAAC,GAAG,GAAG,GAAG,KAAK,GAAG,CAAC,OAAO,MAAM,IAAI,OAAO,MAAM,IAAI,OAAO,MAAM,IAAIA,KAAI,CAAC;AAAA;AAElG,cAAM,IAAI,WAAW,6DAA6D,OAAO,MAAM;AAAA;AAAA,EAErG,CAAC;AACH;AACA,SAAS,eAAe,QAAQ,OAAOA,OAAM,MAAM;AACjD,SAAO,KAAK,MAAM;AAChB,YAAQ,OAAO;AAAA,WACR;AACH,eAAO,QAAQ,QAAQ,OAAOA,KAAI;AAAA,WAC/B;AACH,gBAAQ;AAAA,eACD;AACH,mBAAO,oBAAoB,QAAQ,OAAOA,KAAI;AAAA,eAC3C;AACH,mBAAO,mBAAmB,QAAQ,OAAOA,KAAI;AAAA;AAE7C,kBAAM,IAAI,WAAW,iDAAiD,MAAM;AAAA;AAAA,WAE7E;AACH,gBAAQ;AAAA,eACD;AACH,mBAAO,oBAAoB,QAAQ,OAAOA,KAAI;AAAA,eAC3C;AACH,mBAAO,QAAQ,QAAQ,CAAC,GAAG,OAAO,CAAC,GAAG,CAAC,OAAO,MAAM,IAAIA,OAAM,OAAO,MAAM,EAAE,CAAC;AAAA,eAC3E;AACH,mBAAO,mBAAmB,QAAQ,OAAOA,KAAI;AAAA;AAE7C,kBAAM,IAAI,WAAW,iDAAiD,MAAM;AAAA;AAAA,WAE7E;AACH,gBAAQ;AAAA,eACD;AACH,mBAAO,oBAAoB,QAAQ,OAAOA,KAAI;AAAA,eAC3C;AACH,mBAAO,QAAQ,QAAQ,CAAC,GAAG,OAAO,GAAG,CAAC,GAAG,CAAC,OAAO,MAAM,IAAIA,OAAM,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE,CAAC;AAAA,eAC/F;AACH,mBAAO,QAAQ,QAAQ,CAAC,GAAG,GAAG,OAAO,CAAC,GAAG,CAAC,OAAO,MAAM,IAAI,OAAO,MAAM,IAAIA,OAAM,OAAO,MAAM,EAAE,CAAC;AAAA,eAC/F;AACH,mBAAO,mBAAmB,QAAQ,OAAOA,KAAI;AAAA;AAE7C,kBAAM,IAAI,WAAW,iDAAiD,MAAM;AAAA;AAAA;AAGhF,cAAM,IAAI,WAAW,6DAA6D,OAAO,MAAM;AAAA;AAAA,EAErG,CAAC;AACH;AACA,SAAS,YAAY,SAAS,OAAO,IAAI;AACvC,MAAI;AACJ,MAAI,OAAO,GAAG;AACZ,WAAO,QAAQ,GAAG;AAClB,QAAI,SAAS,GAAG;AACd,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AACA,MAAI,SAAS,QAAQ,GAAG,MAAM;AAC5B,WAAO;AAAA,EACT;AACA,SAAO,OAAO,SAAS,IAAI;AAC7B;AACA,SAAS,qBAAqB,GAAG,GAAG;AAClC,UAAQ,EAAE;AAAA,SACH;AACH,aAAO,SAAS,CAAC,GAAG,CAAC,CAAC;AAAA,SACnB;AACH,aAAO,SAAS,CAAC,GAAG,CAAC,GAAG,CAAC;AAAA,SACtB;AACH,aAAO,SAAS,CAAC,GAAG,CAAC,GAAG,CAAC;AAAA,SACtB;AACH,aAAO,SAAS,CAAC,GAAG,CAAC,GAAG,CAAC;AAAA;AAEzB,YAAM,IAAI,WAAW,+DAA+D,EAAE,MAAM;AAAA;AAElG;AACA,SAAS,MAAM,GAAG,IAAI;AACpB,MAAI,CAAC,MAAM,QAAQ,EAAE,GAAG;AACtB,SAAK,CAAC,EAAE;AAAA,EACV;AACA,MAAI,EAAE,SAAS,GAAG,QAAQ;AACxB,UAAM,IAAI,WAAW,0BAA0B,GAAG,+DAA+D,EAAE,OAAO;AAAA,EAC5H;AACA,SAAO,KAAK,GAAG,EAAE;AACnB;AACA,SAAS,cAAc,OAAO,QAAQ,GAAG,SAAS,GAAG,OAAO,MAAM;AAChE,SAAO,aAAa,OAAO,OAAO,QAAQ,OAAO,IAAI;AACvD;AACA,SAAS,KAAK,GAAG,GAAG,aAAa,MAAM;AACrC,MAAI,EAAE,OAAO,KAAK,EAAE,OAAO,GAAG;AAC5B,UAAM,IAAI,oBAAoB,8DAA8D,EAAE,uBAAuB,EAAE,OAAO;AAAA,EAChI;AACA,MAAI,EAAE,QAAQ,GAAG;AACf,UAAM,WAAW,EAAE,MAAM,MAAM,EAAE,EAAE;AACnC,UAAM,iBAAiB,EAAE,MAAM,MAAM,EAAE,EAAE;AACzC,QAAI,aAAa,gBAAgB;AAC/B,YAAM,IAAI,oBAAoB,gGAAgG,EAAE,wBAAwB,EAAE,OAAO;AAAA,IACnK;AAAA,EACF;AACA,MAAI,EAAE,SAAS,KAAK,EAAE,SAAS,GAAG;AAChC,UAAM,aAAa;AACnB,UAAM,aAAa;AACnB,WAAO,kBAAkB,OAAO;AAAA,MAC9B;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA,MAAM,OAAO,YAAY,EAAE,MAAM,MAAM,gBAAgB,CAAC,IAAI;AAAA,MAC5D,YAAY;AAAA,IACd,CAAC;AAAA,EACH,OAAO;AACL,UAAM,aAAa,EAAE,MAAM,MAAM;AACjC,UAAM,WAAW,WAAW,IAAI;AAChC,QAAI,QAAQ,GAAG,CAAC,IAAI,QAAQ,CAAC;AAC7B,UAAM,SAAS,EAAE,MAAM,MAAM;AAC7B,UAAM,WAAW,OAAO,IAAI;AAC5B,UAAM,iBAAiB,OAAO,IAAI;AAClC,UAAM,aAAa,CAAC,GAAG,QAAQ,QAAQ;AACvC,UAAM,OAAO,MAAM,KAAK,EAAE,QAAQ,EAAE,KAAK,GAAG,CAAC,GAAG,OAAO;AACrD,UAAI,OAAO,GAAG;AACZ,eAAO,EAAE,OAAO;AAAA,MAClB,WAAW,MAAM,EAAE,OAAO,GAAG;AAC3B,eAAO,KAAK;AAAA,MACd;AACA,aAAO;AAAA,IACT,CAAC;AACD,QAAI,QAAQ,UAAU,GAAG,IAAI,GAAG,CAAC,gBAAgB,EAAE,CAAC;AACpD,UAAM,cAAc,CAAC,GAAG,YAAY,GAAG,UAAU;AACjD,UAAM,aAAa;AACnB,UAAM,aAAa;AACnB,WAAO,QAAQ,kBAAkB,OAAO;AAAA,MACtC;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA,MAAM,OAAO,YAAY,EAAE,MAAM,MAAM,gBAAgB,CAAC,IAAI;AAAA,MAC5D,YAAY;AAAA,IACd,CAAC,GAAG,WAAW;AAAA,EACjB;AACF;AACA,SAAS,QAAQ,WAAW,SAAS,MAAM;AACzC,SAAO,KAAK,MAAM;AAChB,QAAI,MAAM,QAAQ,OAAO,GAAG;AAC1B,gBAAU,SAAS,SAAS,OAAO;AAAA,IACrC,OAAO;AACL,gBAAU,KAAK,SAAS,OAAO;AAAA,IACjC;AACA,WAAO,OAAO,WAAW,SAAS,IAAI;AAAA,EACxC,CAAC;AACH;AACA,SAAS,QAAQ,GAAG;AAClB,SAAO,IAAI,GAAG,CAAC;AACjB;AACA,SAAS,YAAY,OAAO,MAAM,YAAY;AAC5C,QAAM,YAAY,KAAK;AACvB,MAAI,KAAK,SAAS,KAAK,KAAK,SAAS,OAAO;AAC1C,UAAM,IAAI,WAAW,+BAA+B,KAAK,gCAAgC,OAAO;AAAA,EAClG;AACA,MAAI,UAAU,GAAG;AACf,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,WAAW,GAAG;AAC1B,eAAO,QAAQ,MAAM,CAAC,GAAG,UAAU,IAAI,GAAG,GAAG,CAAC,CAAC;AAAA,MACjD,OAAO;AACL,eAAO,QAAQ,MAAM,CAAC,GAAG,UAAU,IAAI,UAAU,IAAI,UAAU,IAAI,UAAU,EAAE,CAAC;AAAA,MAClF;AAAA,IACF,WAAW,eAAe,gBAAgB;AACxC,UAAI,UAAU,WAAW,GAAG;AAC1B,eAAO,QAAQ,MAAM,CAAC,GAAG,GAAG,GAAG,GAAG,UAAU,EAAE,CAAC;AAAA,MACjD,OAAO;AACL,eAAO,QAAQ,MAAM,CAAC,CAAC,EAAE,OAAO,SAAS,CAAC;AAAA,MAC5C;AAAA,IACF;AAAA,EACF,WAAW,UAAU,GAAG;AACtB,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,WAAW,GAAG;AAC1B,eAAO,QAAQ,MAAM,CAAC,GAAG,UAAU,IAAI,GAAG,CAAC,CAAC;AAAA,MAC9C,OAAO;AACL,eAAO,QAAQ,MAAM,CAAC,GAAG,UAAU,IAAI,UAAU,IAAI,UAAU,EAAE,CAAC;AAAA,MACpE;AAAA,IACF,WAAW,eAAe,gBAAgB;AACxC,UAAI,UAAU,WAAW,GAAG;AAC1B,eAAO,QAAQ,MAAM,CAAC,GAAG,GAAG,GAAG,UAAU,EAAE,CAAC;AAAA,MAC9C,OAAO;AACL,eAAO,QAAQ,MAAM,CAAC,CAAC,EAAE,OAAO,SAAS,CAAC;AAAA,MAC5C;AAAA,IACF;AAAA,EACF,WAAW,UAAU,GAAG;AACtB,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,WAAW,GAAG;AAC1B,eAAO,QAAQ,MAAM,CAAC,GAAG,UAAU,IAAI,CAAC,CAAC;AAAA,MAC3C,OAAO;AACL,eAAO,QAAQ,MAAM,CAAC,GAAG,UAAU,IAAI,UAAU,EAAE,CAAC;AAAA,MACtD;AAAA,IACF,WAAW,eAAe,gBAAgB;AACxC,UAAI,UAAU,WAAW,GAAG;AAC1B,eAAO,QAAQ,MAAM,CAAC,GAAG,GAAG,UAAU,EAAE,CAAC;AAAA,MAC3C,OAAO;AACL,eAAO,QAAQ,MAAM,CAAC,CAAC,EAAE,OAAO,SAAS,CAAC;AAAA,MAC5C;AAAA,IACF;AAAA,EACF,WAAW,QAAQ,GAAG;AACpB,WAAO;AAAA,EACT;AACA,QAAM,IAAI,WAAW,sCAAsC,KAAK,MAAM;AACxE;AACA,SAAS,QAAQ,GAAG,MAAM,YAAY;AACpC,SAAO,KAAK,MAAM;AAChB,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,oBAAgB,UAAU;AAC1B,WAAO,KAAK,GAAG,YAAY,EAAE,MAAM,MAAM,UAAU,CAAC;AAAA,EACtD,CAAC;AACH;AACA,SAAS,KAAK,GAAGsB,SAAQ,GAAG;AAC1B,MAAIA,WAAU,GAAG;AACf,UAAM,IAAI,oBAAoB,0CAA0CA,iCAAgC;AAAA,EAC1G;AACA,SAAO,IAAI,CAAC;AACd;AACA,SAAS,SAAS,GAAG;AACnB,SAAO,KAAK,MAAM,IAAI,GAAG,KAAK,IAAI,CAAC,GAAG,CAAC,CAAC,CAAC;AAC3C;AACA,SAAS,SAAS,GAAG,OAAO,YAAY,MAAM;AAC5C,SAAO,KAAK,MAAM,QAAQ,GAAG,OAAO,YAAY,IAAI,CAAC;AACvD;AACA,SAAS,YAAY,GAAG;AACtB,SAAO,KAAK,MAAM;AAChB,UAAM,IAAI,KAAK,KAAK,IAAI,KAAK,CAAC,CAAC;AAC/B,WAAO,YAAY,GAAG,GAAG,CAAC;AAAA,EAC5B,CAAC;AACH;AACA,SAAS,aAAa,GAAG,KAAK,WAAW,OAAO;AAC9C,SAAO,WAAW,EAAE,IAAI,IAAI;AAC9B;AAGA,IAAI,wBAAwB,CAAC,SAAS,UAAU,QAAQ;AACxD,IAAI,4BAA4B,CAAC,UAAU,WAAW,iBAAiB;AAGvE,SAAS,aAAa,OAAO;AAC3B,4BAA0B,uBAAuB,WAAW,KAAK;AACnE;AACA,SAAS,kBAAkB,OAAO;AAChC,4BAA0B,2BAA2B,gBAAgB,KAAK;AAC5E;AACA,IAAI,cAAc,cAAc,sBAAsB,aAAa;AAAA,EACjE,8BAA8B;AAC5B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,WAAO,CAAC;AAAA,EACV;AACF;AACA,IAAI,QAAQ,cAAc,YAAY;AAAA,EACpC,MAAM,OAAO,OAAO;AAClB,WAAO,MAAM,OAAO,KAAK;AAAA,EAC3B;AACF;AACA,MAAM,YAAY;AAClB,sBAAsB,cAAc,KAAK;AACzC,IAAI,OAAO,cAAc,YAAY;AAAA,EACnC,MAAM,OAAO,OAAO;AAClB,WAAO,MAAM,OAAO,KAAK;AAAA,EAC3B;AACF;AACA,KAAK,YAAY;AACjB,sBAAsB,cAAc,IAAI;AACxC,IAAI,WAAW,cAAc,YAAY;AAAA,EACvC,YAAY,MAAM;AAChB,UAAM;AACN,QAAI,OAAO,SAAS,UAAU;AAC5B,YAAM,IAAI,WAAW,oDAAoD,MAAM;AAAA,IACjF;AACA,QAAI,KAAK,UAAU,QAAQ;AACzB,YAAM,IAAI,WAAW,sCAAsC,MAAM;AAAA,IACnE;AACA,SAAK,QAAQ,KAAK;AAAA,EACpB;AAAA,EACA,MAAM,OAAO,OAAO;AAClB,WAAO,KAAK,MAAM,IAAI,OAAO,KAAK,KAAK,GAAG,MAAM,OAAO,KAAK,CAAC,CAAC;AAAA,EAChE;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,OAAO,KAAK;AAAA,IACd;AAAA,EACF;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,gBAAgB,cAAc,YAAY;AAAA,EAC5C,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AACtB,SAAK,SAAS,KAAK,UAAU,KAAK;AAClC,SAAK,SAAS,KAAK,UAAU,KAAK;AAClC,SAAK,OAAO,KAAK;AAAA,EACnB;AAAA,EACA,MAAM,OAAO,OAAO;AAClB,WAAO,cAAc,OAAO,KAAK,QAAQ,KAAK,QAAQ,KAAK;AAAA,EAC7D;AAAA,EACA,YAAY;AACV,WAAO,EAAE,QAAQ,KAAK,QAAQ,QAAQ,KAAK,QAAQ,MAAM,KAAK,KAAK;AAAA,EACrE;AACF;AACA,cAAc,YAAY;AAC1B,sBAAsB,cAAc,aAAa;AACjD,IAAI,eAAe,cAAc,YAAY;AAAA,EAC3C,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,iBAAiB;AACtB,SAAK,OAAO,KAAK,QAAQ,KAAK;AAC9B,SAAK,SAAS,KAAK,UAAU,KAAK;AAClC,SAAK,OAAO,KAAK;AAAA,EACnB;AAAA,EACA,MAAM,OAAO,OAAO;AAClB,YAAQ,SAAS;AACjB,QAAI,UAAU,aAAa,UAAU,SAAS;AAC5C,YAAM,IAAI,oBAAoB,uCAAuC,QAAQ;AAAA,IAC/E;AACA,WAAO,cAAc,OAAO,KAAK,MAAM,KAAK,QAAQ,OAAO,KAAK,IAAI;AAAA,EACtE;AAAA,EACA,YAAY;AACV,WAAO,EAAE,MAAM,KAAK,MAAM,QAAQ,KAAK,QAAQ,MAAM,KAAK,KAAK;AAAA,EACjE;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAChD,IAAI,kBAAkB,cAAc,YAAY;AAAA,EAC9C,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,iBAAiB;AACtB,SAAK,OAAO,KAAK,QAAQ,KAAK;AAC9B,SAAK,SAAS,KAAK,UAAU,KAAK;AAClC,SAAK,OAAO,KAAK;AAAA,EACnB;AAAA,EACA,MAAM,OAAO,OAAO;AAClB,YAAQ,SAAS;AACjB,QAAI,UAAU,aAAa,UAAU,SAAS;AAC5C,YAAM,IAAI,oBAAoB,0CAA0C,QAAQ;AAAA,IAClF;AACA,WAAO,gBAAgB,OAAO,KAAK,MAAM,KAAK,QAAQ,OAAO,KAAK,IAAI;AAAA,EACxE;AAAA,EACA,YAAY;AACV,WAAO,EAAE,MAAM,KAAK,MAAM,QAAQ,KAAK,QAAQ,MAAM,KAAK,KAAK;AAAA,EACjE;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,IAAI,YAAY,cAAc,YAAY;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,OAAO;AAAA,EAC9C;AAAA,EACA,MAAM,OAAO,OAAO;AAClB,WAAO,KAAK,MAAM;AAChB,UAAI,MAAM,WAAW,KAAK,MAAM,OAAO,MAAM,IAAI;AAC/C,cAAM,IAAI,WAAW,sEAAsE;AAAA,MAC7F,OAAO;AACL,eAAO,IAAI,KAAK,MAAM,IAAI,MAAM,EAAE,CAAC;AAAA,MACrC;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,WAAO,EAAE,MAAM,KAAK,KAAK;AAAA,EAC3B;AACF;AACA,UAAU,YAAY;AACtB,sBAAsB,cAAc,SAAS;AAC7C,SAAS,YAAY,OAAO,aAAa,gBAAgB;AACvD,MAAI;AACJ,MAAI;AACJ,kBAAgB,UAAU;AAC1B,MAAI,MAAM,WAAW,GAAG;AACtB,YAAQ,MAAM;AACd,aAAS,MAAM;AAAA,EACjB,WAAW,CAAC,GAAG,GAAG,CAAC,EAAE,QAAQ,MAAM,MAAM,MAAM,IAAI;AACjD,QAAI,eAAe,iBAAiB;AAClC,YAAM,qBAAqB,UAAU,OAAO,CAAC;AAC7C,cAAQ,MAAM,KAAK;AACnB,eAAS,MAAM,KAAK;AAAA,IACtB,WAAW,eAAe,gBAAgB;AACxC,YAAM,qBAAqB,UAAU,OAAO,GAAG,MAAM,SAAS,CAAC;AAC/D,cAAQ,MAAM,MAAM,SAAS,KAAK;AAClC,eAAS,MAAM,MAAM,SAAS,KAAK;AAAA,IACrC;AAAA,EACF,OAAO;AACL,UAAM,YAAY,UAAU,KAAK;AACjC,YAAQ,KAAK,KAAK,SAAS;AAC3B,aAAS,KAAK,KAAK,SAAS;AAAA,EAC9B;AACA,SAAO,CAAC,OAAO,MAAM;AACvB;AACA,IAAI,kBAAkB,cAAc,YAAY;AAAA,EAC9C,YAAY,MAAM;AAChB,UAAM;AACN,QAAI,KAAK,QAAQ,GAAG;AAClB,YAAM,IAAI,WAAW,wCAAwC,KAAK,OAAO;AAAA,IAC3E;AACA,SAAK,QAAQ,KAAK,SAAS,OAAO,IAAI,KAAK;AAC3C,SAAK,OAAO,KAAK,QAAQ,OAAO,UAAU,KAAK;AAC/C,iBAAa,KAAK,IAAI;AACtB,SAAK,eAAe,KAAK,gBAAgB,OAAO,WAAW,KAAK;AAChE,sBAAkB,KAAK,YAAY;AACnC,SAAK,OAAO,KAAK;AAAA,EACnB;AAAA,EACA,MAAM,OAAO,OAAO;AAClB,UAAM,OAAO,YAAY,KAAK;AAC9B,UAAM,QAAQ,KAAK;AACnB,UAAM,SAAS,KAAK;AACpB,QAAID,UAAS,KAAK;AAClB,QAAI,KAAK,SAAS,SAAS;AACzB,MAAAA,WAAU,KAAK,IAAI,GAAG,KAAK;AAAA,IAC7B,WAAW,KAAK,SAAS,UAAU;AACjC,MAAAA,WAAU,KAAK,IAAI,GAAG,MAAM;AAAA,IAC9B,OAAO;AACL,MAAAA,WAAU,KAAK,IAAI,IAAI,QAAQ,UAAU,CAAC;AAAA,IAC5C;AACA,QAAI,KAAK,iBAAiB,UAAU;AAClC,YAAM,SAAS,KAAK,KAAKA,OAAM;AAC/B,cAAQ,SAAS;AACjB,UAAI,UAAU,aAAa,UAAU,SAAS;AAC5C,cAAM,IAAI,oBAAoB,GAAG,KAAK,aAAa,4BAA4B,QAAQ;AAAA,MACzF;AACA,aAAO,gBAAgB,OAAO,GAAG,QAAQ,OAAO,KAAK,IAAI;AAAA,IAC3D,OAAO;AACL,YAAM,QAAQ,KAAK,KAAK,IAAIA,OAAM;AAClC,aAAO,cAAc,OAAO,CAAC,OAAO,OAAO,KAAK;AAAA,IAClD;AAAA,EACF;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,OAAO,KAAK;AAAA,MACZ,MAAM,KAAK;AAAA,MACX,cAAc,KAAK;AAAA,MACnB,MAAM,KAAK;AAAA,IACb;AAAA,EACF;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,IAAI,gBAAgB,cAAc,gBAAgB;AAAA,EAChD,YAAY,MAAM;AAChB,UAAM;AAAA,MACJ,OAAO;AAAA,MACP,MAAM;AAAA,MACN,cAAc;AAAA,MACd,MAAM,QAAQ,OAAO,OAAO,KAAK;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,eAAe;AACb,WAAO,gBAAgB;AAAA,EACzB;AACF;AACA,cAAc,YAAY;AAC1B,sBAAsB,cAAc,aAAa;AACjD,IAAI,eAAe,cAAc,gBAAgB;AAAA,EAC/C,YAAY,MAAM;AAChB,UAAM;AAAA,MACJ,OAAO;AAAA,MACP,MAAM;AAAA,MACN,cAAc;AAAA,MACd,MAAM,QAAQ,OAAO,OAAO,KAAK;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,eAAe;AACb,WAAO,gBAAgB;AAAA,EACzB;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAChD,IAAI,WAAW,cAAc,gBAAgB;AAAA,EAC3C,YAAY,MAAM;AAChB,UAAM;AAAA,MACJ,OAAO;AAAA,MACP,MAAM;AAAA,MACN,cAAc;AAAA,MACd,MAAM,QAAQ,OAAO,OAAO,KAAK;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,eAAe;AACb,WAAO,gBAAgB;AAAA,EACzB;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,YAAY,cAAc,gBAAgB;AAAA,EAC5C,YAAY,MAAM;AAChB,UAAM;AAAA,MACJ,OAAO;AAAA,MACP,MAAM;AAAA,MACN,cAAc;AAAA,MACd,MAAM,QAAQ,OAAO,OAAO,KAAK;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,eAAe;AACb,WAAO,gBAAgB;AAAA,EACzB;AACF;AACA,UAAU,YAAY;AACtB,sBAAsB,cAAc,SAAS;AAC7C,IAAI,cAAc,cAAc,gBAAgB;AAAA,EAC9C,YAAY,MAAM;AAChB,UAAM;AAAA,MACJ,OAAO;AAAA,MACP,MAAM;AAAA,MACN,cAAc;AAAA,MACd,MAAM,QAAQ,OAAO,OAAO,KAAK;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,eAAe;AACb,WAAO,gBAAgB;AAAA,EACzB;AACF;AACA,YAAY,YAAY;AACxB,sBAAsB,cAAc,WAAW;AAC/C,IAAI,eAAe,cAAc,gBAAgB;AAAA,EAC/C,YAAY,MAAM;AAChB,UAAM;AAAA,MACJ,OAAO;AAAA,MACP,MAAM;AAAA,MACN,cAAc;AAAA,MACd,MAAM,QAAQ,OAAO,OAAO,KAAK;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,eAAe;AACb,WAAO,gBAAgB;AAAA,EACzB;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAChD,IAAI,aAAa,cAAc,YAAY;AAAA,EACzC,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,eAAe,KAAK;AACzD,SAAK,OAAO,KAAK;AACjB,QAAI,KAAK,QAAQ,MAAM;AACrB,YAAM,IAAI,oBAAoB,gEAAgE;AAAA,IAChG;AAAA,EACF;AAAA,EACA,MAAM,OAAO,OAAO;AAClB,WAAO,KAAK,MAAM;AAChB,UAAI,MAAM,SAAS,GAAG;AACpB,cAAM,IAAI,oBAAoB,4BAA4B;AAAA,MAC5D;AACA,UAAI,MAAM,KAAK,MAAM,KAAK,KAAK;AAC7B,gBAAQ,KAAK,2EAA2E,MAAM,KAAK,MAAM,oCAAoC;AAAA,MAC/I;AACA,YAAM,kBAAkB,MAAM,KAAK,MAAM,KAAK,CAAC,MAAM,IAAI,MAAM,EAAE,IAAI;AACrE,YAAM,IAAI,cAAc,iBAAiB,GAAG,GAAG,SAAS;AACxD,UAAI,IAAI,OAAO,YAAY,CAAC;AAC5B,UAAI,MAAM,KAAK,MAAM,IAAI;AACvB,YAAI,UAAU,CAAC;AAAA,MACjB;AACA,aAAO,IAAI,KAAK,MAAM,CAAC;AAAA,IACzB,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,MAAM,KAAK;AAAA,MACX,MAAM,KAAK;AAAA,IACb;AAAA,EACF;AACF;AACA,WAAW,YAAY;AACvB,sBAAsB,cAAc,UAAU;AAC9C,IAAI,6CAA6C;AAAA,EAC/C,YAAY;AAAA,EACZ,gBAAgB;AAAA,EAChB,iBAAiB;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,eAAe;AAAA,EACf,gBAAgB;AAAA,EAChB,QAAQ;AAAA,EACR,cAAc;AAAA,EACd,gBAAgB;AAAA,EAChB,iBAAiB;AAAA,EACjB,mBAAmB;AAAA,EACnB,mBAAmB;AAAA,EACnB,SAAS;AACX;AACA,SAAS,uBAAuBP,SAAQ,gBAAgB,CAAC,GAAG;AAC1D,SAAO,uBAAuBA,SAAQ,sBAAsB,iBAAiB,OAAO,EAAE,cAAc,eAAe,aAAa;AAClI;AACA,SAAS,qBAAqB,aAAa;AACzC,SAAO,qBAAqB,WAAW;AACzC;AACA,SAAS,eAAe,YAAY;AAClC,MAAI,OAAO,eAAe,UAAU;AAClC,UAAM,YAAY,cAAc,6CAA6C,2CAA2C,cAAc;AACtI,QAAI,cAAc,gBAAgB;AAChC,aAAO,IAAI,aAAa;AAAA,IAC1B,WAAW,cAAc,iBAAiB;AACxC,aAAO,IAAI,cAAc;AAAA,IAC3B,WAAW,cAAc,YAAY;AACnC,aAAO,IAAI,SAAS;AAAA,IACtB,WAAW,cAAc,aAAa;AACpC,aAAO,IAAI,UAAU;AAAA,IACvB,WAAW,cAAc,eAAe;AACtC,aAAO,IAAI,YAAY;AAAA,IACzB,WAAW,cAAc,gBAAgB;AACvC,aAAO,IAAI,aAAa;AAAA,IAC1B,OAAO;AACL,YAAMA,UAAS,CAAC;AAChB,MAAAA,QAAO,eAAe;AACtB,MAAAA,QAAO,YAAY,CAAC;AACpB,aAAO,uBAAuBA,OAAM;AAAA,IACtC;AAAA,EACF,WAAW,sBAAsB,aAAa;AAC5C,WAAO;AAAA,EACT,OAAO;AACL,WAAO,uBAAuB,UAAU;AAAA,EAC1C;AACF;AAGA,SAAS,gBAAgB,GAAG;AAC1B,SAAO,MAAM,QAAQ,CAAC,KAAK,MAAM,QAAQ,EAAE,EAAE;AAC/C;AACA,SAAS,mBAAmB,GAAG;AAC7B,MAAI,EAAE,WAAW,GAAG;AAClB,WAAO,CAAC;AAAA,EACV;AACA,MAAI,CAAC,MAAM,QAAQ,EAAE,EAAE,GAAG;AACxB,WAAO,CAAC,CAAC;AAAA,EACX;AACA,SAAO;AACT;AACA,SAAS,oBAAoB,IAAI;AAC/B,MAAI;AACJ,MAAI,MAAM,QAAQ,EAAE,GAAG;AACrB,QAAI,GAAG,WAAW,GAAG;AACnB,YAAM,IAAI,WAAW,uCAAuC,GAAG,QAAQ;AAAA,IACzE;AACA,QAAI,GAAG;AAAA,EACT,OAAO;AACL,QAAI;AAAA,EACN;AACA,SAAO;AACT;AACA,SAAS,mBAAmB,QAAQ;AAClC,MAAI,MAAM,QAAQ,MAAM,KAAK,MAAM,QAAQ,OAAO,EAAE,GAAG;AACrD,QAAI,OAAO,WAAW,GAAG;AACvB,eAAS;AACT,aAAO,OAAO;AAAA,IAChB,OAAO;AACL,YAAM,IAAI,WAAW,iCAAiC,OAAO,QAAQ;AAAA,IACvE;AAAA,EACF,OAAO;AACL,WAAO;AAAA,EACT;AACF;AAGA,SAAS,qBAAqB,SAAS;AACrC,MAAIP,UAAS;AACb,aAAW,UAAU,SAAS;AAC5B,QAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,MAAAA,WAAU;AAAA,IACZ,OAAO;AACL,MAAAA,WAAU,OAAO,MAAM,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAAA,IAC/C;AAAA,EACF;AACA,SAAOA;AACT;AAGA,IAAI,+BAA+B;AACnC,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,KAAK,QAAQ,WAAW,OAAO,8BAA8B,YAAY,MAAM,aAAa,MAAM;AAC5G,SAAK,QAAQ,SAAS,OAAO,YAAY;AACzC,SAAK,QAAQ,IAAI;AACjB,SAAK,KAAK,sBAAsB;AAChC,WAAO,QAAQ,OAAO,+BAA+B;AACrD,SAAK,eAAe,oBAAoB,IAAI;AAC5C,SAAK,OAAO,oBAAoB,KAAK,YAAY;AACjD,SAAK,aAAa;AAClB,SAAK,aAAa;AAClB,SAAK,MAAM,SAAS,KAAK,KAAK,YAAY,KAAK,MAAM,KAAK,KAAK;AAAA,EACjE;AAAA,EACA,OAAO;AACL,SAAK,kBAAkB;AACvB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,QAAQ;AACZ,SAAK,kBAAkB;AACvB,qBAAiB,KAAK,KAAK,MAAM;AACjC,QAAI,KAAK,IAAI,OAAO,OAAO,IAAI;AAC7B,WAAK,IAAI,OAAO,MAAM;AACtB,UAAI,KAAK,cAAc,MAAM;AAC3B,aAAK,IAAI,OAAO,KAAK,WAAW,MAAM,KAAK,GAAG,CAAC;AAAA,MACjD;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,UAAU;AACR,SAAK,kBAAkB;AACvB,SAAK,IAAI,QAAQ;AAAA,EACnB;AAAA,EACA,oBAAoB;AAClB,QAAI,KAAK,IAAI,YAAY;AACvB,YAAM,IAAI,MAAM,kBAAkB,KAAK,2BAA2B;AAAA,IACpE;AAAA,EACF;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,UAAU,WAAW;AACvB,SAAK,aAAa;AAClB,SAAK,IAAI,YAAY;AAAA,EACvB;AACF;AACA,SAAS,iBAAiB,GAAG,GAAG;AAC9B,MAAI,EAAE,MAAM,SAAS,MAAM,EAAE,MAAM,SAAS,GAAG;AAC7C,UAAM,IAAI,MAAM,qBAAqB,KAAK,UAAU,EAAE,KAAK,IAAI,UAAU,KAAK,UAAU,EAAE,KAAK,CAAC;AAAA,EAClG;AACF;AACA,SAAS,cAAc,IAAI;AACzB,SAAO,GAAG,IAAI,CAAC,MAAM,EAAE,KAAK,CAAC;AAC/B;AACA,SAAS,cAAc,oBAAoB;AACzC,qBAAmB,QAAQ,CAAC,qBAAqB;AAC/C,UAAM,YAAY,iBAAiB;AACnC,cAAU,MAAM,iBAAiB,EAAE;AAAA,EACrC,CAAC;AACH;AAGA,IAAI,YAAY,MAAM;AAAA,EACpB,YAAY,MAAM;AAChB,SAAK,QAAQ,KAAK;AAClB,SAAK,QAAQ,KAAK;AAClB,QAAI,KAAK,SAAS,MAAM;AACtB,WAAK,OAAO,KAAK,MAAM;AAAA,IACzB,OAAO;AACL,WAAK,OAAO,KAAK;AAAA,IACnB;AACA,SAAK,UAAU,KAAK;AACpB,SAAK,UAAU,KAAK;AACpB,SAAK,OAAO,KAAK,QAAQ,CAAC;AAAA,EAC5B;AACF;AACA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,OAAO,OAAO,aAAa,QAAQ,UAAU,MAAM,mBAAmB;AAChF,SAAK,QAAQ;AACb,SAAK,QAAQ;AACb,SAAK,cAAc;AACnB,SAAK,SAAS;AACd,SAAK,WAAW;AAChB,SAAK,oBAAoB;AACzB,SAAK,KAAK,sBAAsB;AAChC,QAAI,QAAQ,MAAM;AAChB,WAAK,eAAe,oBAAoB,IAAI;AAC5C,WAAK,OAAO,oBAAoB,KAAK,YAAY;AAAA,IACnD;AACA,SAAK,OAAO,MAAM;AAAA,EACpB;AACF;AACA,IAAI,cAAc;AAClB,IAAI,OAAO,MAAM;AAAA,EACf,YAAY,MAAM,UAAU;AAC1B,SAAK,WAAW;AAChB,SAAK,KAAK;AACV,SAAK,gBAAgB,KAAK;AAC1B,SAAK,gBAAgB,KAAK;AAC1B,SAAK,cAAc,KAAK;AACxB,SAAK,gBAAgB,KAAK;AAC1B,SAAK,eAAe,KAAK;AACzB,SAAK,gBAAgB,KAAK;AAC1B,SAAK,aAAa,KAAK;AACvB,SAAK,cAAc,KAAK;AACxB,SAAK,cAAc,KAAK;AACxB,SAAK,eAAe,KAAK;AACzB,eAAW,SAAS,KAAK,eAAe;AACtC,UAAI,SAAS,MAAM;AACjB,cAAM,cAAc,KAAK,IAAI;AAAA,MAC/B;AAAA,IACF;AACA,SAAK,cAAc,aAAa,KAAK,IAAI;AAAA,EAC3C;AAAA,EACA,YAAY;AACV,UAAM,eAAe,CAAC;AACtB,eAAW,SAAS,KAAK,eAAe;AACtC,UAAI,SAAS,MAAM;AACjB,qBAAa,KAAK,MAAM,IAAI;AAAA,MAC9B,OAAO;AACL,qBAAa,KAAK,IAAI;AAAA,MACxB;AAAA,IACF;AACA,WAAO;AAAA,MACL,eAAe,KAAK,gBAAgB,KAAK,cAAc,OAAO;AAAA,MAC9D,eAAe;AAAA,MACf,aAAa,KAAK;AAAA,MAClB,eAAe,KAAK;AAAA,IACtB;AAAA,EACF;AACF;AACA,IAAI,eAAe;AACnB,IAAI,QAAQ,cAAc,sBAAsB,aAAa;AAAA,EAC3D,YAAY,OAAO,CAAC,GAAG;AACrB,UAAM;AACN,SAAK,YAAY;AACjB,SAAK,oBAAoB,CAAC;AAC1B,SAAK,YAAY;AACjB,SAAK,KAAK;AACV,SAAK,sBAAsB;AAC3B,SAAK,YAAY;AACjB,SAAK,kBAAkB;AACvB,SAAK,oBAAoB,CAAC;AAC1B,SAAK,uBAAuB,CAAC;AAC7B,SAAK,UAAU,CAAC;AAChB,SAAK,WAAW,CAAC;AACjB,SAAK,SAAS;AACd,SAAK,eAAe,CAAC;AACrB,SAAK,gBAAgB,CAAC;AACtB,QAAI,OAAO,KAAK;AAChB,QAAI,CAAC,MAAM;AACT,YAAM,SAAS,KAAK,aAAa;AACjC,aAAO,YAAY,MAAM,IAAI,MAAM,OAAO,MAAM;AAAA,IAClD;AACA,SAAK,OAAO;AACZ,SAAK,aAAa,KAAK,aAAa,OAAO,OAAO,KAAK;AACvD,QAAI,KAAK,cAAc,QAAQ,KAAK,mBAAmB,MAAM;AAC3D,UAAI;AACJ,UAAI,KAAK,mBAAmB,MAAM;AAChC,0BAAkB,KAAK;AAAA,MACzB,WAAW,KAAK,cAAc,MAAM;AAClC,YAAI,YAAY;AAChB,YAAI,KAAK,aAAa,MAAM;AAC1B,sBAAY,KAAK;AAAA,QACnB;AACA,0BAAkB,CAAC,SAAS,EAAE,OAAO,KAAK,UAAU;AAAA,MACtD;AACA,WAAK,kBAAkB;AACvB,UAAI,QAAQ,KAAK;AACjB,UAAI,SAAS,MAAM;AACjB,gBAAQ,KAAK;AAAA,MACf;AACA,UAAI,SAAS,MAAM;AACjB,gBAAQ;AAAA,MACV;AACA,WAAK,QAAQ;AAAA,IACf;AACA,QAAI,KAAK,WAAW,MAAM;AACxB,WAAK,iBAAiB,KAAK;AAAA,IAC7B,OAAO;AACL,WAAK,iBAAiB;AAAA,IACxB;AACA,SAAK,YAAY;AACjB,SAAK,4BAA4B;AAAA,EACnC;AAAA,EACA,OAAO,QAAQ,OAAO,WAAW;AAC/B,WAAO,MAAM,OAAO,SAAS,UAAU,SAAS;AAAA,EAClD;AAAA,EACA,eAAe,WAAW,UAAU;AAClC,QAAI,KAAK,aAAa,WAAW,GAAG;AAClC,YAAM,IAAI,aAAa,2DAA2D,WAAW;AAAA,IAC/F;AACA,QAAI,KAAK,aAAa,UAAU,WAAW;AACzC,YAAM,IAAI,WAAW,gBAAgB,oBAAoB,qCAAqC,KAAK,aAAa,uBAAuB;AAAA,IACzI;AACA,WAAO,KAAK,aAAa;AAAA,EAC3B;AAAA,EACA,WAAW,WAAW;AACpB,WAAO,iBAAiB,KAAK,eAAe,WAAW,OAAO,EAAE,YAAY;AAAA,EAC9E;AAAA,EACA,YAAY,WAAW;AACrB,WAAO,iBAAiB,KAAK,eAAe,WAAW,QAAQ,EAAE,aAAa;AAAA,EAChF;AAAA,EACA,IAAI,QAAQ;AACV,QAAI,KAAK,aAAa,SAAS,GAAG;AAChC,YAAM,IAAI,eAAe,SAAS,KAAK,2HAA2H;AAAA,IACpK,WAAW,KAAK,aAAa,WAAW,GAAG;AACzC,YAAM,IAAI,eAAe,SAAS,KAAK,4CAA4C;AAAA,IACrF;AACA,WAAO,iBAAiB,KAAK,eAAe,GAAG,OAAO,EAAE,YAAY;AAAA,EACtE;AAAA,EACA,IAAI,SAAS;AACX,QAAI,KAAK,aAAa,WAAW,GAAG;AAClC,YAAM,IAAI,eAAe,SAAS,KAAK,4BAA4B;AAAA,IACrE;AACA,QAAI,KAAK,aAAa,SAAS,GAAG;AAChC,YAAM,IAAI,eAAe,SAAS,KAAK,6HAA6H;AAAA,IACtK;AACA,WAAO,iBAAiB,KAAK,eAAe,GAAG,QAAQ,EAAE,aAAa;AAAA,EACxE;AAAA,EACA,IAAI,SAAS;AACX,WAAO,KAAK;AAAA,EACd;AAAA,EACA,kBAAkB;AAChB,WAAO,KAAK,OAAO,IAAI,CAAC,WAAW,OAAO,CAAC;AAAA,EAC7C;AAAA,EACA,IAAI,UAAU;AACZ,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,QAAQ;AACV,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,MAAM,OAAO;AACf,SAAK,SAAS;AAAA,EAChB;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,UAAU,WAAW;AACvB,SAAK,kBAAkB,QAAQ,CAAC,MAAM,EAAE,YAAY,SAAS;AAC7D,SAAK,aAAa;AAAA,EACpB;AAAA,EACA,IAAI,mBAAmB;AACrB,QAAI,KAAK,YAAY;AACnB,aAAO,KAAK,kBAAkB,OAAO,CAAC,MAAM,EAAE,SAAS;AAAA,IACzD,OAAO;AACL,aAAO,CAAC;AAAA,IACV;AAAA,EACF;AAAA,EACA,IAAI,iBAAiB,SAAS;AAC5B,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,IAAI,sBAAsB;AACxB,QAAI,KAAK,WAAW;AAClB,aAAO,KAAK,kBAAkB,OAAO,CAAC,MAAM,CAAC,EAAE,SAAS,EAAE,OAAO,KAAK,oBAAoB;AAAA,IAC5F,OAAO;AACL,aAAO,KAAK,kBAAkB,OAAO,KAAK,oBAAoB;AAAA,IAChE;AAAA,EACF;AAAA,EACA,IAAI,oBAAoB,SAAS;AAC/B,SAAK,uBAAuB;AAAA,EAC9B;AAAA,EACA,IAAI,UAAU;AACZ,WAAO,KAAK,iBAAiB,OAAO,KAAK,mBAAmB;AAAA,EAC9D;AAAA,EACA,IAAI,WAAW;AACb,WAAO,KAAK;AAAA,EACd;AAAA,EACA,cAAc;AACZ,QAAI,CAAC,KAAK,UAAU;AAClB,YAAM,IAAI,MAAM,sEAAsE;AAAA,IACxF;AAAA,EACF;AAAA,EACA,yBAAyB,QAAQ;AAC/B,aAAS,OAAO,MAAM;AACtB,QAAI,KAAK,aAAa,QAAQ,KAAK,UAAU,WAAW,GAAG;AACzD;AAAA,IACF;AACA,UAAM,YAAY,OAAO,KAAK,SAAS;AACvC,QAAI,OAAO,WAAW,UAAU,QAAQ;AACtC,YAAM,IAAI,WAAW,SAAS,KAAK,gBAAgB,UAAU,kCAAkC,OAAO,yCAAyC,QAAQ;AAAA,IACzJ;AACA,aAAS,aAAa,GAAG,aAAa,OAAO,QAAQ,cAAc;AACjE,YAAM,IAAI,OAAO;AACjB,YAAM,OAAO,UAAU;AACvB,UAAI,QAAQ,MAAM;AAChB;AAAA,MACF;AACA,YAAM,OAAO,EAAE;AACf,UAAI,KAAK,QAAQ,MAAM;AACrB,YAAI,SAAS,KAAK,MAAM;AACtB,gBAAM,IAAI,WAAW,SAAS,yCAAyC,KAAK,uBAAuB,KAAK,oBAAoB,MAAM;AAAA,QACpI;AAAA,MACF;AACA,UAAI,KAAK,WAAW,MAAM;AACxB,YAAI,OAAO,KAAK,SAAS;AACvB,gBAAM,IAAI,WAAW,SAAS,yCAAyC,KAAK,2BAA2B,KAAK,uBAAuB,MAAM;AAAA,QAC3I;AAAA,MACF;AACA,UAAI,KAAK,WAAW,MAAM;AACxB,YAAI,OAAO,KAAK,SAAS;AACvB,gBAAM,IAAI,WAAW,SAAS,yCAAyC,KAAK,2BAA2B,KAAK,uBAAuB,OAAO;AAAA,QAC5I;AAAA,MACF;AACA,UAAI,KAAK,SAAS,MAAM;AACtB,YAAI,EAAE,UAAU,KAAK,OAAO;AAC1B,gBAAM,IAAI,WAAW,SAAS,yCAAyC,KAAK,yBAAyB,KAAK,sBAAsB,EAAE,QAAQ;AAAA,QAC5I;AAAA,MACF;AACA,UAAI,KAAK,MAAM;AACb,cAAM,SAAS,EAAE;AACjB,mBAAW,OAAO,KAAK,MAAM;AAC3B,gBAAM,OAAO,OAAO,GAAG;AACvB,gBAAM,QAAQ,KAAK,KAAK;AACxB,gBAAM,eAAe,QAAQ,IAAI,OAAO,QAAQ,OAAO,OAAO,SAAS;AACvE,cAAI,SAAS,QAAQ,CAAC,OAAO,IAAI,EAAE,QAAQ,YAAY,MAAM,IAAI;AAC/D,kBAAM,IAAI,WAAW,SAAS,yCAAyC,KAAK,uBAAuB,qCAAqC,uBAAuB,SAAS;AAAA,UAC1K;AAAA,QACF;AAAA,MACF;AACA,UAAI,KAAK,SAAS,MAAM;AACtB,iBAAS,KAAK,GAAG,KAAK,KAAK,MAAM,QAAQ,EAAE,IAAI;AAC7C,gBAAM,UAAU,KAAK,MAAM;AAC3B,gBAAM,MAAM,EAAE,MAAM;AACpB,cAAI,WAAW,QAAQ,OAAO,MAAM;AAClC,gBAAI,YAAY,KAAK;AACnB,oBAAM,IAAI,WAAW,SAAS,yCAAyC,KAAK,wBAAwB,KAAK,sBAAsB,EAAE,QAAQ;AAAA,YAC3I;AAAA,UACF;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO;AAAA,EACT;AAAA,EACA,eAAe,QAAQ,QAAQ;AAC7B,QAAI,KAAK,aAAa,MAAM;AAC1B,WAAK,UAAU,QAAQ,MAAM;AAAA,IAC/B;AAAA,EACF;AAAA,EACA,YAAY,UAAU;AACpB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,gBAAgB;AACd,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,MAAM,QAAQ,QAAQ;AACpB,aAAS,UAAU,CAAC;AACpB,SAAK,kBAAkB;AACvB,UAAM,aAAa,OAAO,MAAM;AAChC,QAAI,iBAAiB;AACrB,eAAW,UAAU,YAAY;AAC/B,UAAI,EAAE,kBAAkB,iBAAiB;AACvC,yBAAiB;AACjB;AAAA,MACF;AAAA,IACF;AACA,QAAI,kBAAkB;AACtB,eAAW,UAAU,YAAY;AAC/B,UAAI,kBAAkB,gBAAgB;AACpC,0BAAkB;AAClB;AAAA,MACF;AAAA,IACF;AACA,QAAI,mBAAmB,iBAAiB;AACtC,YAAM,IAAI,WAAW,iEAAiE;AAAA,IACxF;AACA,WAAO,UAAU,KAAK,MAAM,MAAM;AAChC,UAAI,CAAC,KAAK,OAAO;AACf,aAAK,yBAAyB,MAAM;AACpC,cAAM,cAAc,CAAC;AACrB,mBAAW,SAAS,OAAO,MAAM,GAAG;AAClC,sBAAY,KAAK,MAAM,KAAK;AAAA,QAC9B;AACA,aAAK,MAAM,iBAAiB,WAAW,CAAC;AACxC,aAAK,QAAQ;AACb,YAAI,KAAK,gBAAgB;AACvB,eAAK,WAAW,KAAK,cAAc;AAAA,QACrC;AACA,YAAI,KAAK,cAAc,QAAQ,iBAAiB;AAC9C,eAAK,YAAY;AAAA,QACnB;AAAA,MACF;AACA,WAAK,yBAAyB,MAAM;AACpC,UAAI,iBAAiB;AACnB,YAAI,SAAS,KAAK,KAAK,QAAQ,MAAM;AACrC,cAAM,aAAa,OAAO,MAAM;AAChC,cAAM,iBAAiB,CAAC;AACxB,iBAAS,KAAK,YAAY;AACxB,cAAI,WAAW,QAAQ,CAAC,MAAM,IAAI;AAChC,gBAAI,EAAE,MAAM;AAAA,UACd;AACA,yBAAe,KAAK,CAAC;AAAA,QACvB;AACA,iBAAS,iBAAiB,cAAc;AACxC,YAAI,KAAK,uBAAuB,MAAM;AACpC,gBAAM,IAAI,oBAAoB,mFAAmF;AAAA,QACnH;AACA,eAAO;AAAA,MACT,OAAO;AACL,cAAM,aAAa,kBAAkB,MAAM;AAC3C,cAAM,cAAc,KAAK,mBAAmB,UAAU;AACtD,YAAI;AACJ,cAAM,cAAc,iBAAiB,MAAM;AAC3C,aAAK,6BAA6B,MAAM,QAAQ,MAAM,IAAI,WAAW,KAAK,UAAU;AACpF,YAAI,eAAe,QAAQ,YAAY,SAAS,KAAK,MAAM,QAAQ,YAAY,EAAE,GAAG;AAClF,mBAAS,YAAY,IAAI,CAAC,OAAOE,WAAU,IAAI,eAAe,aAAa,OAAO,MAAM,OAAO,MAAM,GAAG,QAAQ,KAAK,MAAMA,MAAK,CAAC;AAAA,QACnI,OAAO;AACL,mBAAS,IAAI,eAAe,aAAa,aAAa,MAAM,OAAO,MAAM,GAAG,QAAQ,KAAK,IAAI;AAAA,QAC/F;AACA,aAAK,eAAe,QAAQ,QAAQ,MAAM,MAAM,YAAY,aAAa,MAAM;AAC/E,aAAK;AACL,YAAI,KAAK,uBAAuB,MAAM;AACpC,gBAAM,IAAI,oBAAoB,mFAAmF;AAAA,QACnH;AACA,eAAO;AAAA,MACT;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,6BAA6B,YAAY;AACvC,QAAI,KAAK,mBAAmB,MAAM;AAChC;AAAA,IACF,WAAW,WAAW,WAAW,KAAK,gBAAgB,QAAQ;AAC5D,cAAQ,KAAK,iDAAiD,KAAK,UAAU,UAAU,kDAAkD,KAAK,UAAU,KAAK,eAAe,mBAAmB,KAAK,MAAM;AAAA,IAC5M,OAAO;AACL,UAAI,cAAc;AAClB,WAAK,gBAAgB,QAAQ,CAAC,WAAW,OAAO;AAC9C,YAAI,aAAa,QAAQ,WAAW,OAAO,QAAQ,WAAW,QAAQ,WAAW;AAC/E,wBAAc;AAAA,QAChB;AAAA,MACF,CAAC;AACD,UAAI,aAAa;AACf,gBAAQ,KAAK,kCAAkC,KAAK,UAAU,UAAU,8CAA8C,KAAK,SAAS,KAAK,UAAU,KAAK,eAAe,GAAG;AAAA,MAC5K;AAAA,IACF;AAAA,EACF;AAAA,EACA,IAAI,cAAc;AAChB,QAAI,KAAK,gBAAgB,QAAQ,KAAK,aAAa,WAAW,GAAG;AAC/D,YAAM,IAAI,eAAe,aAAa,KAAK,kEAAkE;AAAA,IAC/G;AACA,UAAM,kBAAkB,CAAC;AACzB,eAAWO,SAAQ,KAAK,cAAc;AACpC,YAAM,cAAc,KAAK,UAAUA,MAAK,YAAY;AACpD,UAAI,gBAAgB,QAAQ,WAAW,MAAM,IAAI;AAC/C,wBAAgB,KAAK,WAAW;AAAA,MAClC;AAAA,IACF;AACA,QAAI,gBAAgB,WAAW,GAAG;AAChC,YAAM,eAAe,KAAK,aAAa,GAAG;AAC1C,UAAI,MAAM,QAAQ,YAAY,KAAK,MAAM,QAAQ,aAAa,EAAE,KAAK,aAAa,WAAW,GAAG;AAC9F,eAAO,aAAa;AAAA,MACtB,OAAO;AACL,eAAO;AAAA,MACT;AAAA,IACF,OAAO;AACL,YAAM,IAAI,eAAe,aAAa,KAAK,gIAAgI;AAAA,IAC7K;AAAA,EACF;AAAA,EACA,cAAc;AACZ,QAAI,CAAC,KAAK,OAAO;AACf,YAAM,IAAI,aAAa,sCAAsC,KAAK,yFAAyF;AAAA,IAC7J;AACA,WAAO,qBAAqB,KAAK,OAAO;AAAA,EAC1C;AAAA,EACA,MAAM,YAAY;AAChB,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,WAAW,gBAAgB,OAAO;AAChC,WAAO,cAAc,gBAAgB,KAAK,mBAAmB,KAAK,OAAO;AAAA,EAC3E;AAAA,EACA,WAAW,SAAS;AAClB,SAAK,MAAM;AACT,YAAM,SAAS,KAAK;AACpB,UAAI,OAAO,WAAW,QAAQ,QAAQ;AACpC,cAAM,IAAI,WAAW,4CAA4C,KAAK,sCAAsC,QAAQ,uCAAuC,OAAO,qCAAqC,YAAY;AAAA,MACrN;AACA,UAAI,OAAO,WAAW,GAAG;AACvB;AAAA,MACF;AACA,YAAM,oBAAoB,CAAC;AAC3B,YAAM,cAAc,cAAc,MAAM;AACxC,eAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,EAAE,IAAI;AAC9C,cAAM,KAAK,YAAY;AACvB,cAAM,KAAK,OAAO;AAClB,cAAM,IAAI,QAAQ;AAClB,YAAI,CAAC,aAAa,YAAY,GAAG,OAAO,EAAE,KAAK,GAAG;AAChD,gBAAM,IAAI,WAAW,sBAAsB,GAAG,mDAAmD,EAAE,OAAO;AAAA,QAC5G;AACA,0BAAkB,KAAK,CAAC,IAAI,CAAC,CAAC;AAAA,MAChC;AACA,oBAAc,iBAAiB;AAAA,IACjC,CAAC;AAAA,EACH;AAAA,EACA,UAAU,MAAM,OAAO,OAAO,aAAa,aAAa,WAAW,YAAY,oBAAoB;AACjG,QAAI,KAAK,kBAAkB,QAAQ,IAAI,MAAM,IAAI;AAC/C,YAAM,IAAI,WAAW,yBAAyB,kBAAkB,KAAK,MAAM;AAAA,IAC7E;AACA,SAAK,kBAAkB,KAAK,IAAI;AAChC,QAAI,SAAS,MAAM;AACjB,cAAQ;AAAA,IACV;AACA,QAAI,KAAK,2BAA2B;AAClC,oBAAc,sBAAsB,OAAO,mBAAmB,IAAI,eAAe,OAAO;AAAA,IAC1F;AACA,UAAM,YAAY,YAAY,MAAM,OAAO,KAAK;AAChD,UAAM,SAAS,IAAI,cAAc,WAAW,OAAO,MAAM,WAAW,UAAU;AAC9E,cAAU,QAAQ;AAClB,QAAI,eAAe,MAAM;AACvB,WAAK,QAAQ,MAAM,YAAY,MAAM,OAAO,KAAK,CAAC,CAAC;AAAA,IACrD;AACA,QAAI,aAAa,MAAM;AACrB,kBAAY;AAAA,IACd;AACA,QAAI,WAAW;AACb,WAAK,kBAAkB,KAAK,MAAM;AAAA,IACpC,OAAO;AACL,WAAK,qBAAqB,KAAK,MAAM;AAAA,IACvC;AACA,WAAO;AAAA,EACT;AAAA,EACA,6BAA6B,OAAO;AAClC,SAAK,4BAA4B;AAAA,EACnC;AAAA,EACA,QAAQ,SAAS;AACf,QAAI,WAAW,QAAQ,MAAM,QAAQ,OAAO,KAAK,QAAQ,WAAW,GAAG;AACrE;AAAA,IACF;AACA,cAAU,OAAO,OAAO;AACxB,QAAI,KAAK,YAAY,UAAU,KAAK,YAAY,MAAM;AACpD,WAAK,OAAO,KAAK,GAAG,OAAO;AAAA,IAC7B;AAAA,EACF;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY,QAAQX,OAAM;AACxB,QAAI,CAAC,KAAK,iBAAiB;AACzB,UAAIA,SAAQ,MAAM;AAChB,YAAI,MAAM,QAAQA,KAAI,GAAG;AACvB,UAAAA,MAAK,QAAQ,CAAC,gBAAgB;AAC5B,gBAAI,eAAe,MAAM;AACvB,oBAAM,IAAI,UAAU,SAAS,KAAK,6DAA6D;AAAA,YACjG;AAAA,UACF,CAAC;AAAA,QACH,OAAO;AACL,gBAAM,IAAI,UAAU,SAAS,KAAK,6DAA6D;AAAA,QACjG;AAAA,MACF;AACA,aAAO;AAAA,IACT;AACA,WAAOA;AAAA,EACT;AAAA,EACA,eAAe,cAAc,eAAe,YAAY,aAAa,aAAa,cAAc,SAAS,MAAM;AAC7G,UAAM,kBAAkB,OAAO,YAAY;AAC3C,oBAAgB,OAAO,aAAa;AACpC,iBAAa,OAAO,UAAU;AAC9B,kBAAc,OAAO,WAAW;AAChC,kBAAc,mBAAmB,WAAW;AAC5C,mBAAe,mBAAmB,YAAY;AAC9C,UAAM,gBAAgB,CAAC;AACvB,UAAM,cAAc,CAAC;AACrB,UAAM,gBAAgB,CAAC;AACvB,eAAW,KAAK,iBAAiB;AAC/B,oBAAc,KAAK,EAAE,WAAW;AAChC,kBAAY,KAAK,EAAE,SAAS;AAC5B,oBAAc,KAAK,EAAE,WAAW;AAAA,IAClC;AACA,QAAI,KAAK;AAAA,MACP,eAAe;AAAA,MACf;AAAA,MACA;AAAA,MACA;AAAA,MACA,cAAc;AAAA,MACd;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF,GAAG,MAAM;AACT,aAAS,KAAK,GAAG,KAAK,cAAc,QAAQ,MAAM;AAChD,oBAAc,IAAI,cAAc;AAChC,oBAAc,IAAI,YAAY,KAAK,aAAa,SAAS;AACzD,oBAAc,IAAI,cAAc;AAAA,IAClC;AAAA,EACF;AAAA,EACA,YAAY;AACV,UAAMS,UAAS,EAAE,MAAM,KAAK,MAAM,WAAW,KAAK,UAAU;AAC5D,QAAI,KAAK,mBAAmB,MAAM;AAChC,MAAAA,QAAO,qBAAqB,KAAK;AAAA,IACnC;AACA,QAAI,KAAK,SAAS,MAAM;AACtB,MAAAA,QAAO,WAAW,KAAK;AAAA,IACzB;AACA,WAAOA;AAAA,EACT;AAAA,EACA,iBAAiB;AACf,SAAK,QAAQ,QAAQ,CAAC,WAAW,OAAO,QAAQ,CAAC;AACjD,WAAO,KAAK,QAAQ;AAAA,EACtB;AAAA,EACA,oBAAoB;AAClB,QAAI,KAAK,cAAc,GAAG;AACxB,YAAM,IAAI,MAAM,UAAU,KAAK,4BAA4B;AAAA,IAC7D;AAAA,EACF;AAAA,EACA,UAAU;AACR,QAAI,CAAC,KAAK,OAAO;AACf,YAAM,IAAI,MAAM,wBAAwB,KAAK,yCAAyC;AAAA,IACxF;AACA,QAAI,KAAK,cAAc,MAAM;AAC3B,YAAM,IAAI,MAAM,wBAAwB,KAAK,wCAAwC;AAAA,IACvF;AACA,SAAK,kBAAkB;AACvB,QAAI,uBAAuB;AAC3B,QAAI,EAAE,KAAK,cAAc,GAAG;AAC1B,6BAAuB,KAAK,eAAe;AAAA,IAC7C;AACA,WAAO,EAAE,sBAAsB,KAAK,WAAW,qBAAqB;AAAA,EACtE;AACF;AACA,SAAS,kBAAkB,cAAc;AACvC,iBAAe,OAAO,YAAY;AAClC,QAAM,SAAS,CAAC;AAChB,aAAW,KAAK,cAAc;AAC5B,WAAO,KAAK,EAAE,KAAK;AAAA,EACrB;AACA,SAAO,iBAAiB,MAAM;AAChC;AACA,SAAS,iBAAiB,cAAc;AACtC,SAAO;AACT;AACA,SAAS,gBAAgB,SAAS,OAAO,WAAW;AAClD,MAAI,SAAS,QAAQ,aAAa,QAAQ,YAAY,GAAG;AACvD,YAAQ,QAAQ;AAChB,gBAAY,QAAQ;AAAA,EACtB;AACA,MAAI,MAAM,aAAa,WAAW,GAAG;AACnC,WAAO,CAAC,OAAO;AAAA,EACjB,OAAO;AACL,UAAME,QAAO,MAAM,aAAa;AAChC,QAAIA,MAAK,cAAc,WAAW,GAAG;AACnC,aAAOA,MAAK;AAAA,IACd,OAAO;AACL,YAAM,gBAAgB,CAAC;AACvB,eAAS,KAAK,GAAG,KAAKA,MAAK,cAAc,QAAQ,MAAM;AACrD,cAAM,IAAIA,MAAK,aAAa;AAC5B,cAAM,SAASA,MAAK,cAAc;AAClC,cAAM,aAAaA,MAAK,YAAY;AACpC,cAAM,kBAAkB,gBAAgB,GAAG,QAAQ,UAAU;AAC7D,mBAAW,MAAM,iBAAiB;AAChC,cAAI,cAAc,QAAQ,EAAE,MAAM,IAAI;AACpC,0BAAc,KAAK,EAAE;AAAA,UACvB;AAAA,QACF;AAAA,MACF;AACA,aAAO;AAAA,IACT;AAAA,EACF;AACF;AAGA,IAAI,aAAa,cAAc,MAAM;AAAA,EACnC,YAAY,MAAM;AAChB,UAAM;AAAA,MACJ,OAAO,KAAK;AAAA,MACZ,MAAM,KAAK,QAAQ,OAAO,KAAK,OAAO,OAAO,OAAO,EAAE,SAAS;AAAA,IACjE,CAAC;AACD,QAAI,KAAK,aAAa,MAAM;AAC1B,WAAK,YAAY;AAAA,IACnB;AACA,QAAI,KAAK,UAAU,MAAM;AACvB,WAAK,SAAS;AAAA,IAChB;AACA,SAAK,YAAY;AACjB,SAAK,QAAQ;AACb,SAAK,SAAS,KAAK;AACnB,QAAI,KAAK,cAAc,QAAQ,KAAK,mBAAmB,MAAM;AAC3D,YAAM,IAAI,WAAW,mGAAmG;AAAA,IAC1H;AACA,QAAI,kBAAkB,KAAK;AAC3B,QAAI,mBAAmB,MAAM;AAC3B,UAAI,KAAK,cAAc,MAAM;AAC3B,cAAM,IAAI,WAAW,+EAA+E;AAAA,MACtG,OAAO;AACL,0BAAkB,CAAC,KAAK,SAAS,EAAE,OAAO,KAAK,UAAU;AAAA,MAC3D;AAAA,IACF,OAAO;AACL,UAAI,KAAK,aAAa,MAAM;AAC1B,cAAM,IAAI,WAAW,uFAAuF;AAAA,MAC9G;AAAA,IACF;AACA,UAAM,QAAQ,KAAK,SAAS;AAC5B,SAAK,kBAAkB;AACvB,SAAK,QAAQ;AACb,SAAK,YAAY,CAAC,EAAE,OAAO,gBAAgB,CAAC;AAC5C,UAAM,cAAc,IAAI,eAAe,KAAK,OAAO,KAAK,iBAAiB,MAAM,CAAC,GAAG,CAAC,GAAG,KAAK,IAAI;AAChG,gBAAY,YAAY;AACxB,gBAAY,cAAc;AAC1B,QAAI,KAAK;AAAA,MACP,eAAe;AAAA,MACf,eAAe,CAAC;AAAA,MAChB,aAAa,CAAC;AAAA,MACd,eAAe,CAAC;AAAA,MAChB,cAAc,CAAC,WAAW;AAAA,MAC1B,eAAe,CAAC,WAAW;AAAA,MAC3B,YAAY,CAAC,IAAI;AAAA,MACjB,aAAa,CAAC,IAAI;AAAA,MAClB,aAAa,CAAC,eAAe;AAAA,MAC7B,cAAc,CAAC,eAAe;AAAA,IAChC,CAAC;AAAA,EACH;AAAA,EACA,MAAM,QAAQ,QAAQ;AACpB,UAAM,IAAI,WAAW,6EAA6E,KAAK,MAAM;AAAA,EAC/G;AAAA,EACA,UAAU;AACR,WAAO,EAAE,sBAAsB,KAAK,WAAW,sBAAsB,EAAE;AAAA,EACzE;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,iBAAiB,KAAK;AAAA,MACtB,OAAO,KAAK;AAAA,MACZ,QAAQ,KAAK;AAAA,MACb,MAAM,KAAK;AAAA,IACb;AAAA,EACF;AACF;AACA,WAAW,YAAY;AACvB,sBAAsB,cAAc,UAAU;AAC9C,SAAS,MAAMF,SAAQ;AACrB,MAAIA,QAAO,cAAc,QAAQA,QAAO,SAAS,MAAM;AACrD,UAAM,IAAI,MAAM,8HAA8H;AAAA,EAChJ;AACA,MAAIA,QAAO,cAAc,QAAQA,QAAO,SAAS,MAAM;AACrD,UAAM,IAAI,WAAW,kFAAkF;AAAA,EACzG;AACA,MAAI,aAAaA,QAAO;AACxB,MAAIA,QAAO,SAAS,QAAQ,cAAc,MAAM;AAC9C,iBAAa,CAAC,IAAI,EAAE,OAAOA,QAAO,KAAK;AAAA,EACzC;AACA,MAAI,QAAQA,QAAO;AACnB,MAAI,SAAS,MAAM;AACjB,YAAQ;AAAA,EACV;AACA,QAAM,cAAc,IAAI,WAAW;AAAA,IACjC,iBAAiB;AAAA,IACjB,MAAMA,QAAO;AAAA,IACb;AAAA,IACA,QAAQA,QAAO;AAAA,EACjB,CAAC;AACD,QAAM,UAAU,YAAY,aAAa,GAAG;AAC5C,SAAO,QAAQ;AACjB;AAGA,SAAS,wBAAwB,KAAK,KAAK;AACzC,MAAI,IAAI,SAAS,QAAQ,IAAI,UAAU,IAAI,OAAO;AAChD,WAAO;AAAA,EACT;AACA,MAAI;AACF,WAAO,KAAK,KAAK,IAAI,KAAK;AAAA,EAC5B,SAAS,KAAP;AACA,UAAM,IAAI,WAAW,0BAA0B,IAAI,mDAAmD,IAAI,UAAU,IAAI,SAAS;AAAA,EACnI;AACF;AACA,IAAI,WAAW,MAAM;AAAA,EACnB,YAAY,OAAO;AACjB,SAAK,WAAW,CAAC;AACjB,SAAK,UAAU,CAAC;AAChB,SAAK,UAAU,CAAC;AAChB,QAAI,iBAAiB,UAAU;AAC7B,iBAAW,MAAM,MAAM,UAAU;AAC/B,aAAK,SAAS,MAAM,MAAM,SAAS;AACnC,YAAI,MAAM,MAAM,SAAS;AACvB,eAAK,QAAQ,MAAM,MAAM,QAAQ;AAAA,QACnC;AAAA,MACF;AAAA,IACF,OAAO;AACL,UAAI,SAAS,MAAM;AACjB;AAAA,MACF;AACA,iBAAW,QAAQ,OAAO;AACxB,aAAK,IAAI,KAAK,KAAK,KAAK,KAAK;AAAA,MAC/B;AAAA,IACF;AAAA,EACF;AAAA,EACA,IAAI,KAAK,OAAOT,OAAM;AACpB,QAAI,KAAK,SAAS,IAAI,OAAO,MAAM;AACjC,WAAK,SAAS,IAAI,MAAM,wBAAwB,KAAK,KAAK;AAC1D,WAAK,QAAQ,IAAI,QAAQ,IAAI;AAC7B,UAAIA,SAAQ,MAAM;AAChB,aAAK,QAAQ,IAAI,MAAMA;AAAA,MACzB;AAAA,IACF,OAAO;AACL,YAAM,IAAI,WAAW,uBAAuB,IAAI,YAAY,IAAI,IAAI;AAAA,IACtE;AACA,WAAO;AAAA,EACT;AAAA,EACA,QAAQ,MAAM;AACZ,SAAK,IAAI,KAAK,KAAK,KAAK,KAAK;AAAA,EAC/B;AAAA,EACA,OAAO,KAAK;AACV,WAAO,KAAK,SAAS,IAAI,OAAO;AAAA,EAClC;AAAA,EACA,QAAQ;AACN,WAAO,OAAO,KAAK,KAAK,OAAO;AAAA,EACjC;AAAA,EACA,SAAS,KAAK;AACZ,QAAI,eAAe,gBAAgB;AACjC,UAAI,KAAK,SAAS,IAAI,OAAO,MAAM;AACjC,cAAM,IAAI,WAAW,oBAAoB,IAAI,MAAM;AAAA,MACrD,OAAO;AACL,eAAO,KAAK,SAAS,IAAI;AAAA,MAC3B;AAAA,IACF,OAAO;AACL,YAAM,KAAK,KAAK,QAAQ;AACxB,UAAI,MAAM,MAAM;AACd,cAAM,IAAI,WAAW,yCAAyC,KAAK;AAAA,MACrE;AACA,aAAO,KAAK,SAAS;AAAA,IACvB;AAAA,EACF;AAAA,EACA,QAAQ,KAAK;AACX,QAAI,eAAe,gBAAgB;AACjC,UAAI,KAAK,SAAS,IAAI,OAAO,MAAM;AACjC,cAAM,IAAI,WAAW,oBAAoB,IAAI,MAAM;AAAA,MACrD,OAAO;AACL,eAAO,KAAK,QAAQ,IAAI;AAAA,MAC1B;AAAA,IACF,OAAO;AACL,YAAM,KAAK,KAAK,QAAQ;AACxB,UAAI,MAAM,MAAM;AACd,cAAM,IAAI,WAAW,yCAAyC,KAAK;AAAA,MACrE;AACA,aAAO,KAAK,QAAQ;AAAA,IACtB;AAAA,EACF;AAAA,EACA,eAAe;AACb,QAAI,KAAK,WAAW,MAAM;AACxB,cAAQ,KAAK,OAAO;AAAA,IACtB;AAAA,EACF;AACF;AACA,IAAI,eAAe,IAAI,SAAS;AAChC,IAAI,wBAAwB,IAAI,SAAS;AACzC,SAAS,sBAAsB,YAAY;AACzC,MAAI,gBAAgB,MAAM;AACxB,iBAAa,cAAc,UAAU;AAAA,EACvC;AACA,MAAI,yBAAyB,MAAM;AACjC,0BAAsB,cAAc,UAAU;AAAA,EAChD;AACF;AACA,SAAS,QAAQ,SAAS,UAAU,QAAQ,OAAO;AACjD,QAAM,WAAW,UAAU,OAAO,QAAQ,OAAO;AACjD,QAAM,eAAe,MAAM,QAAQ,OAAO;AAC1C,QAAM,aAAa,eAAe,UAAU,CAAC,OAAO;AACpD,QAAM,cAAc,WAAW,IAAI,CAAC,OAAO,GAAG,IAAI;AAClD,QAAM,eAAe,CAAC;AACtB,QAAM,YAAY,SAAS,MAAM;AACjC,aAAW,cAAc,aAAa;AACpC,QAAI,UAAU,QAAQ,UAAU,MAAM,IAAI;AACxC,mBAAa,KAAK,SAAS,SAAS,UAAU,CAAC;AAAA,IACjD,OAAO;AACL,mBAAa,KAAK,IAAI;AAAA,IACxB;AAAA,EACF;AACA,MAAI,SAAS,MAAM;AACjB,UAAM,gBAAgB;AACtB,UAAM,gBAAgB;AAAA,EACxB;AACA,QAAM,kBAAkB,YAAY,KAAK,GAAG,IAAI,MAAM,SAAS,MAAM,EAAE,KAAK,EAAE,KAAK,GAAG;AACtF,MAAI,SAAS,aAAa,IAAI,eAAe;AAC7C,MAAI;AACJ,MAAI,UAAU,MAAM;AAClB,UAAM,MAAM,qCAAqC,YAAY,QAAQ;AACrE,aAAS,IAAI;AACb,sBAAkB,IAAI;AACtB,iBAAa,IAAI,iBAAiB,MAAM;AACxC,0BAAsB,IAAI,iBAAiB,eAAe;AAAA,EAC5D;AACA,oBAAkB,CAAC;AACnB,MAAI,CAAC,UAAU;AACb,WAAO,OAAO,iBAAiB,sBAAsB,IAAI,eAAe,CAAC;AAAA,EAC3E;AACA,QAAM,mBAAmB,IAAI,SAAS,QAAQ;AAC9C,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,QAAI,SAAS,MAAM;AACjB,YAAM,aAAa,OAAO,EAAE;AAC5B,UAAI,aAAa,MAAM,eAAe;AACpC,cAAM,gBAAgB;AAAA,MACxB;AACA,UAAI,aAAa,MAAM,eAAe;AACpC,cAAM,gBAAgB;AAAA,MACxB;AAAA,IACF;AACA,UAAM,WAAW,OAAO;AACxB,UAAM,WAAW,SAAS;AAC1B,QAAI,oBAAoB,YAAY;AAClC;AAAA,IACF;AACA,UAAM,cAAc,CAAC;AACrB,UAAM,aAAa,CAAC;AACpB,UAAM,mBAAmB,CAAC;AAC1B,QAAI,aAAa;AACjB,eAAW,UAAU,SAAS,QAAQ;AACpC,YAAM,QAAQ,iBAAiB,SAAS,MAAM;AAC9C,YAAMA,QAAO,iBAAiB,QAAQ,MAAM;AAC5C,kBAAY,KAAK,KAAK;AACtB,iBAAW,KAAKA,KAAI;AACpB,UAAIA,SAAQ,MAAM;AAChB,qBAAa;AAAA,MACf;AACA,UAAI,CAAC,UAAU;AACb,wBAAgB,OAAO;AACvB,YAAI,gBAAgB,OAAO,UAAU,KAAK,CAAC,SAAS,OAAO,MAAM,KAAK,YAAY,QAAQ,OAAO,IAAI,MAAM,MAAM,CAAC,MAAM,cAAc,OAAO,YAAY,aAAa,MAAM;AAC1K,2BAAiB,KAAK,KAAK;AAAA,QAC7B;AAAA,MACF;AAAA,IACF;AACA,QAAI,YAAY;AACd,eAAS,UAAU,CAAC;AACpB,aAAO,UAAU,WAAW;AAAA,IAC9B;AACA,UAAM,gBAAgB,OAAO,SAAS,MAAM,aAAa,MAAM,CAAC;AAChE,QAAI,aAAa;AACjB,QAAI,SAAS,iBAAiB;AAC5B,mBAAa,SAAS,YAAY,aAAa,UAAU;AAAA,IAC3D;AACA,UAAM,eAAe,eAAe,QAAQ;AAC5C,UAAM,wBAAwB,MAAM,QAAQ,YAAY,IAAI,eAAe,CAAC,YAAY;AACxF,aAAS,KAAK,GAAG,KAAK,sBAAsB,QAAQ,EAAE,IAAI;AACxD,UAAI,CAAC,iBAAiB,OAAO,sBAAsB,GAAG,GAAG;AACvD,yBAAiB,IAAI,sBAAsB,KAAK,cAAc,KAAK,MAAM,QAAQ,UAAU,IAAI,WAAW,KAAK,UAAU;AAAA,MAC3H;AACA,YAAMI,SAAQ,YAAY,QAAQ,sBAAsB,IAAI,IAAI;AAChE,UAAIA,WAAU,IAAI;AAChB,qBAAaA,UAAS,cAAc;AAAA,MACtC;AAAA,IACF;AACA,QAAI,CAAC,UAAU;AACb,cAAQ,gBAAgB;AAAA,IAC1B;AAAA,EACF;AACA,mBAAiB,aAAa;AAC9B,SAAO,eAAe,eAAe,aAAa;AACpD;AACA,SAAS,qCAAqC,SAAS,UAAU;AAC/D,eAAa,OAAO,WAAW,QAAQ,QAAQ,SAAS,GAAG,MAAM,uCAAuC;AACxG,MAAI,cAAc,CAAC;AACnB,MAAI,oBAAoB,CAAC;AACzB,MAAI,QAAQ,WAAW,GAAG;AACxB,UAAM,MAAM,gDAAgD,QAAQ,IAAI,QAAQ;AAChF,kBAAc,IAAI;AAClB,wBAAoB,IAAI;AAAA,EAC1B,OAAO;AACL,UAAM,UAA0B,oBAAI,IAAI;AACxC,eAAW,UAAU,SAAS;AAC5B,YAAM,EAAE,QAAQ,aAAa,IAAI,gDAAgD,QAAQ,QAAQ;AACjG,iBAAW,kBAAkB,QAAQ;AACnC,YAAI,CAAC,QAAQ,IAAI,eAAe,IAAI,GAAG;AACrC,sBAAY,KAAK,cAAc;AAC/B,kBAAQ,IAAI,eAAe,IAAI;AAAA,QACjC;AAAA,MACF;AACA,iBAAW,QAAQ,cAAc;AAC/B,YAAI,kBAAkB,SAAS,MAAM;AACnC,4BAAkB,QAAwB,oBAAI,IAAI;AAAA,QACpD;AACA,qBAAa,MAAM,QAAQ,CAAC,cAAc,kBAAkB,MAAM,IAAI,SAAS,CAAC;AAAA,MAClF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AAAA,IACL,QAAQ;AAAA,IACR,iBAAiB,oBAAoB,iBAAiB;AAAA,EACxD;AACF;AACA,SAAS,oBAAoB,cAAc;AACzC,QAAM,kBAAkB,CAAC;AACzB,aAAW,QAAQ,cAAc;AAC/B,oBAAgB,QAAQ,aAAa,MAAM;AAAA,EAC7C;AACA,SAAO;AACT;AACA,SAAS,gDAAgD,QAAQ,UAAU;AACzE,QAAM,UAA0B,oBAAI,IAAI;AACxC,QAAM,SAAS,CAAC;AAChB,QAAM,eAAe,CAAC;AACtB,aAAW,OAAO,SAAS,MAAM,GAAG;AAClC,YAAQ,IAAI,GAAG;AAAA,EACjB;AACA,QAAM,SAAS,CAAC;AAChB,QAAM,QAAQ,CAAC;AACf,SAAO,KAAK,MAAM;AAClB,SAAO,OAAO,SAAS,GAAG;AACxB,UAAM,MAAM,OAAO,OAAO,SAAS;AACnC,QAAI,QAAQ,IAAI,IAAI,IAAI,GAAG;AACzB,aAAO,IAAI;AACX;AAAA,IACF;AACA,UAAM,cAAc,MAAM,MAAM,SAAS,OAAO,OAAO,SAAS;AAChE,QAAI,IAAI,OAAO,WAAW,KAAK,aAAa;AAC1C,aAAO,IAAI;AACX,aAAO,KAAK,GAAG;AACf,cAAQ,IAAI,IAAI,IAAI;AACpB,UAAI,aAAa;AACf,cAAM,IAAI;AAAA,MACZ;AAAA,IACF,OAAO;AACL,YAAM,KAAK,OAAO,SAAS,CAAC;AAC5B,iBAAW,UAAU,IAAI,QAAQ;AAC/B,YAAI,aAAa,OAAO,SAAS,MAAM;AACrC,uBAAa,OAAO,QAAwB,oBAAI,IAAI;AAAA,QACtD;AACA,qBAAa,OAAO,MAAM,IAAI,IAAI,IAAI;AACtC,YAAI,QAAQ,IAAI,OAAO,IAAI,GAAG;AAC5B;AAAA,QACF;AACA,eAAO,KAAK,MAAM;AAAA,MACpB;AAAA,IACF;AAAA,EACF;AACA,SAAO,EAAE,QAAQ,aAAa;AAChC;AACA,SAAS,eAAe,QAAQ;AAC9B,MAAI;AACJ,MAAI,OAAO,YAAY,aAAa,WAAW,GAAG;AAChD,mBAAe,OAAO,YAAY;AAAA,EACpC,OAAO;AACL,QAAI,YAAY;AAChB,aAAS,KAAK,GAAG,KAAK,OAAO,YAAY,aAAa,QAAQ,EAAE,IAAI;AAClE,iBAAW,gBAAgB,OAAO,YAAY,aAAa,IAAI,eAAe;AAC5E,YAAI,aAAa,OAAO,OAAO,IAAI;AACjC,sBAAY;AACZ;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,mBAAe,OAAO,YAAY,YAAY,SAAS;AAAA,EACzD;AACA,SAAO;AACT;AAGA,IAAI,OAAO,IAAI;AACf,KAAK,aAAa,sCAAsC,MAAM,KAAK,qBAAqB;AAGxF,IAAI,8BAA8B,CAAC;AACnCZ,UAAS,6BAA6B;AAAA,EACpC,SAAS,MAAM;AAAA,EACf,YAAY,MAAM;AAAA,EAClB,QAAQ,MAAM;AAAA,EACd,UAAU,MAAM;AAClB,CAAC;AAGD,SAAS,YAAY,GAAG,MAAM;AAC5B,SAAO,KAAK,MAAM,KAAK,KAAK,IAAI,GAAG,CAAC,GAAG,MAAM,IAAI,CAAC,CAAC;AACrD;AACA,IAAI,aAAa,cAAc,sBAAsB,aAAa;AAAA,EAChE,YAAY;AACV,WAAO,CAAC;AAAA,EACV;AACF;AACA,IAAI,UAAU,cAAc,WAAW;AAAA,EACrC,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,kBAAkB;AACvB,SAAK,cAAc;AACnB,SAAK,WAAW,KAAK,YAAY,OAAO,KAAK,WAAW,KAAK;AAC7D,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,OAAO,KAAK;AAAA,EACnD;AAAA,EACA,MAAM,GAAG;AACP,WAAO,KAAK,MAAM;AAChB,YAAM,QAAQ,YAAY,GAAG,KAAK,IAAI;AACtC,YAAM,UAAU,YAAY,OAAO,GAAG,KAAK,QAAQ;AACnD,aAAO,IAAI,GAAG,IAAI,SAAS,KAAK,QAAQ,GAAG,KAAK,CAAC,CAAC;AAAA,IACpD,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,WAAO,EAAE,UAAU,KAAK,UAAU,MAAM,KAAK,KAAK;AAAA,EACpD;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,WAAW,cAAc,WAAW;AAAA,EACtC,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,cAAc;AACnB,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,OAAO,KAAK;AAAA,EACnD;AAAA,EACA,MAAM,GAAG;AACP,WAAO,KAAK,MAAM,IAAI,GAAG,KAAK,QAAQ,GAAG,YAAY,GAAG,KAAK,IAAI,CAAC,CAAC,CAAC;AAAA,EACtE;AAAA,EACA,YAAY;AACV,WAAO,EAAE,MAAM,KAAK,KAAK;AAAA,EAC3B;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,SAAS,cAAc,WAAW;AAAA,EACpC,MAAM,GAAG;AACP,WAAO,KAAK,CAAC;AAAA,EACf;AACF;AACA,OAAO,YAAY;AACnB,sBAAsB,cAAc,MAAM;AAC1C,IAAI,aAAa,cAAc,WAAW;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AACvB,SAAK,cAAc;AACnB,SAAK,cAAc;AACnB,SAAK,WAAW,KAAK,YAAY,OAAO,KAAK,WAAW,KAAK;AAC7D,SAAK,WAAW,KAAK,YAAY,OAAO,KAAK,WAAW,KAAK;AAC7D,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,OAAO,KAAK;AACjD,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,OAAO,KAAK;AAAA,EACnD;AAAA,EACA,MAAM,GAAG;AACP,WAAO,KAAK,MAAM;AAChB,YAAM,QAAQ,YAAY,GAAG,KAAK,IAAI;AACtC,YAAM,UAAU,KAAK,IAAI,KAAK,MAAM,YAAY,OAAO,KAAK,UAAU,KAAK,QAAQ,CAAC,GAAG,IAAI,IAAI,KAAK,MAAM,KAAK,CAAC;AAChH,aAAO,IAAI,GAAG,IAAI,SAAS,KAAK,QAAQ,GAAG,KAAK,CAAC,CAAC;AAAA,IACpD,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,UAAU,KAAK;AAAA,MACf,UAAU,KAAK;AAAA,MACf,MAAM,KAAK;AAAA,MACX,MAAM,KAAK;AAAA,IACb;AAAA,EACF;AACF;AACA,WAAW,YAAY;AACvB,sBAAsB,cAAc,UAAU;AAC9C,IAAI,4CAA4C;AAAA,EAC9C,WAAW;AAAA,EACX,cAAc;AAAA,EACd,UAAU;AAAA,EACV,YAAY;AACd;AACA,SAAS,oBAAoB,YAAY;AACvC,SAAO,qBAAqB,UAAU;AACxC;AACA,SAAS,sBAAsBiB,SAAQ,gBAAgB,CAAC,GAAG;AACzD,SAAO,uBAAuBA,SAAQ,sBAAsB,iBAAiB,OAAO,EAAE,cAAc,eAAe,YAAY;AACjI;AACA,SAAS,cAAc,YAAY;AACjC,MAAI,cAAc,MAAM;AACtB,WAAO;AAAA,EACT;AACA,MAAI,OAAO,eAAe,UAAU;AAClC,UAAM,YAAY,cAAc,4CAA4C,0CAA0C,cAAc;AACpI,UAAMA,UAAS,EAAE,WAAW,QAAQ,CAAC,EAAE;AACvC,WAAO,sBAAsBA,OAAM;AAAA,EACrC,WAAW,sBAAsB,YAAY;AAC3C,WAAO;AAAA,EACT,OAAO;AACL,WAAO,sBAAsB,UAAU;AAAA,EACzC;AACF;AAGA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,SAAS;AAChB,SAAO,IAAI,OAAO;AACpB;AACA,SAAS,WAAWA,SAAQ;AAC1B,SAAO,IAAI,WAAWA,OAAM;AAC9B;AAGA,IAAI,+BAA+B,CAAC;AACpCjB,UAAS,8BAA8B;AAAA,EACrC,UAAU,MAAM;AAAA,EAChB,cAAc,MAAM;AAAA,EACpB,eAAe,MAAM;AAAA,EACrB,UAAU,MAAM;AAAA,EAChB,WAAW,MAAM;AAAA,EACjB,UAAU,MAAM;AAAA,EAChB,aAAa,MAAM;AAAA,EACnB,cAAc,MAAM;AAAA,EACpB,MAAM,MAAM;AAAA,EACZ,YAAY,MAAM;AAAA,EAClB,cAAc,MAAM;AAAA,EACpB,eAAe,MAAM;AAAA,EACrB,iBAAiB,MAAM;AAAA,EACvB,iBAAiB,MAAM;AAAA,EACvB,OAAO,MAAM;AACf,CAAC;AACD,SAAS,SAAS;AAChB,SAAO,IAAI,MAAM;AACnB;AACA,SAAS,QAAQ;AACf,SAAO,IAAI,KAAK;AAClB;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,eAAe,MAAM;AAC5B,SAAO,IAAI,cAAc,IAAI;AAC/B;AACA,SAAS,cAAc,MAAM;AAC3B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,UAAU,IAAI;AAC3B;AACA,SAAS,gBAAgBiB,SAAQ;AAC/B,SAAO,IAAI,gBAAgBA,OAAM;AACnC;AACA,SAAS,cAAc,MAAM;AAC3B,SAAO,IAAI,cAAc,IAAI;AAC/B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,UAAU,MAAM;AACvB,SAAO,IAAI,UAAU,IAAI;AAC3B;AACA,SAAS,YAAY,MAAM;AACzB,SAAO,IAAI,YAAY,IAAI;AAC7B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,WAAW,MAAM;AACxB,SAAO,IAAI,WAAW,IAAI;AAC5B;AAGA,IAAI,yBAAyB,CAAC;AAC9BjB,UAAS,wBAAwB;AAAA,EAC/B,OAAO,MAAM;AAAA,EACb,KAAK,MAAM;AAAA,EACX,SAAS,MAAM;AAAA,EACf,YAAY,MAAM;AAAA,EAClB,KAAK,MAAM;AAAA,EACX,cAAc,MAAM;AAAA,EACpB,SAAS,MAAM;AAAA,EACf,kBAAkB,MAAM;AAAA,EACxB,kBAAkB,MAAM;AAAA,EACxB,kBAAkB,MAAM;AAAA,EACxB,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,cAAc,MAAM;AAAA,EACpB,cAAc,MAAM;AAAA,EACpB,cAAc,MAAM;AAAA,EACpB,oBAAoB,MAAM;AAAA,EAC1B,eAAe,MAAM;AAAA,EACrB,aAAa,MAAM;AAAA,EACnB,QAAQ,MAAM;AAAA,EACd,QAAQ,MAAM;AAAA,EACd,iBAAiB,MAAM;AAAA,EACvB,QAAQ,MAAM;AAAA,EACd,iBAAiB,MAAM;AAAA,EACvB,YAAY,MAAM;AAAA,EAClB,gBAAgB,MAAM;AAAA,EACtB,YAAY,MAAM;AAAA,EAClB,OAAO,MAAM;AAAA,EACb,iBAAiB,MAAM;AAAA,EACvB,KAAK,MAAM;AAAA,EACX,SAAS,MAAM;AAAA,EACf,KAAK,MAAM;AAAA,EACX,WAAW,MAAM;AAAA,EACjB,SAAS,MAAM;AAAA,EACf,iBAAiB,MAAM;AAAA,EACvB,eAAe,MAAM;AAAA,EACrB,wBAAwB,MAAM;AAAA,EAC9B,wBAAwB,MAAM;AAAA,EAC9B,iBAAiB,MAAM;AAAA,EACvB,iBAAiB,MAAM;AAAA,EACvB,oBAAoB,MAAM;AAAA,EAC1B,oBAAoB,MAAM;AAAA,EAC1B,KAAK,MAAM;AAAA,EACX,SAAS,MAAM;AAAA,EACf,OAAO,MAAM;AAAA,EACb,YAAY,MAAM;AAAA,EAClB,oBAAoB,MAAM;AAAA,EAC1B,WAAW,MAAM;AAAA,EACjB,MAAM,MAAM;AAAA,EACZ,UAAU,MAAM;AAAA,EAChB,SAAS,MAAM;AAAA,EACf,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,cAAc,MAAM;AAAA,EACpB,cAAc,MAAM;AAAA,EACpB,cAAc,MAAM;AAAA,EACpB,SAAS,MAAM;AAAA,EACf,SAAS,MAAM;AAAA,EACf,UAAU,MAAM;AAAA,EAChB,SAAS,MAAM;AAAA,EACf,OAAO,MAAM;AAAA,EACb,MAAM,MAAM;AAAA,EACZ,cAAc,MAAM;AAAA,EACpB,SAAS,MAAM;AAAA,EACf,KAAK,MAAM;AAAA,EACX,iBAAiB,MAAM;AAAA,EACvB,WAAW,MAAM;AAAA,EACjB,eAAe,MAAM;AAAA,EACrB,SAAS,MAAM;AAAA,EACf,kBAAkB,MAAM;AAAA,EACxB,iBAAiB,MAAM;AAAA,EACvB,iBAAiB,MAAM;AAAA,EACvB,iBAAiB,MAAM;AAAA,EACvB,cAAc,MAAM;AAAA,EACpB,eAAe,MAAM;AACvB,CAAC;AAGD,eAAe,qBAAqB,MAAM;AACxC,MAAI,QAAQ,MAAM;AAChB;AAAA,EACF;AACA,QAAM,WAAW,CAAC;AAClB,QAAM,OAAO,CAAC;AACd,QAAM,mBAAmB,CAAC;AAC1B,aAAW,OAAO,MAAM;AACtB,UAAM,QAAQ,KAAK;AACnB,QAAI,OAAO,UAAU,UAAU;AAC7B,YAAM,cAAc;AACpB,eAAS,KAAK,YAAY,KAAK,CAAC;AAChC,WAAK,KAAK,GAAG;AACb,uBAAiB,KAAK,WAAW;AAAA,IACnC;AAAA,EACF;AACA,MAAI,SAAS,SAAS,GAAG;AACvB,UAAM,SAAS,MAAM,QAAQ,IAAI,QAAQ;AACzC,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,WAAK,KAAK,OAAO,OAAO,IAAI;AAAA,IAC9B;AACA,YAAQ,gBAAgB;AAAA,EAC1B;AACF;AACA,SAAS,qBAAqB,MAAM;AAClC,MAAI,QAAQ,MAAM;AAChB;AAAA,EACF;AACA,aAAW,OAAO,MAAM;AACtB,UAAM,QAAQ,KAAK;AACnB,QAAI,OAAO,UAAU,UAAU;AAC7B,YAAM,QAAQ;AAAA,IAChB;AAAA,EACF;AACF;AAGA,IAAI;AAAA,CACH,SAAS,wBAAwB;AAChC,yBAAuB,uBAAuB,YAAY,KAAK;AAC/D,yBAAuB,uBAAuB,aAAa,KAAK;AAClE,GAAG,0BAA0B,wBAAwB,CAAC,EAAE;AACxD,IAAI,yBAAyB;AAC7B,IAAI,eAAe,MAAM;AAAA,EACvB,cAAc;AACZ,SAAK,iBAAiB;AAAA,EACxB;AAAA,EACA,UAAU,QAAQ;AAChB,SAAK,SAAS;AAAA,EAChB;AAAA,EACA,MAAM,aAAa,OAAO,MAAM;AAAA,EAChC;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAAA,EAC9B;AAAA,EACA,MAAM,aAAa,OAAO,MAAM;AAAA,EAChC;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAAA,EAC9B;AAAA,EACA,MAAM,aAAa,MAAM;AAAA,EACzB;AAAA,EACA,MAAM,WAAW,MAAM;AAAA,EACvB;AAAA,EACA,SAASgC,SAAQ;AAAA,EACjB;AACF;AACA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,YAAY,cAAc,IAAI;AACxC,QAAI,cAAc,MAAM;AACtB,mBAAa,CAAC;AAAA,IAChB;AACA,SAAK,YAAY;AACjB,SAAK,cAAc;AAAA,EACrB;AAAA,EACA,OAAO,UAAU;AACf,SAAK,UAAU,KAAK,QAAQ;AAAA,EAC9B;AAAA,EACA,UAAU,QAAQ;AAChB,eAAW,YAAY,KAAK,WAAW;AACrC,eAAS,UAAU,MAAM;AAAA,IAC3B;AAAA,EACF;AAAA,EACA,SAASA,SAAQ;AACf,eAAW,YAAY,KAAK,WAAW;AACrC,eAAS,SAASA,OAAM;AAAA,IAC1B;AAAA,EACF;AAAA,EACA,MAAM,aAAa,OAAO,MAAM;AAC9B,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,eAAW,YAAY,KAAK,WAAW;AACrC,YAAM,SAAS,aAAa,OAAO,IAAI;AAAA,IACzC;AAAA,EACF;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,eAAW,YAAY,KAAK,WAAW;AACrC,YAAM,SAAS,WAAW,OAAO,IAAI;AAAA,IACvC;AAAA,EACF;AAAA,EACA,MAAM,aAAa,OAAO,MAAM;AAC9B,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,eAAW,YAAY,KAAK,WAAW;AACrC,YAAM,SAAS,aAAa,OAAO,IAAI;AAAA,IACzC;AAAA,EACF;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,eAAW,YAAY,KAAK,WAAW;AACrC,YAAM,SAAS,WAAW,OAAO,IAAI;AAAA,IACvC;AAAA,EACF;AAAA,EACA,MAAM,aAAa,MAAM;AACvB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,eAAW,YAAY,KAAK,WAAW;AACrC,YAAM,SAAS,aAAa,IAAI;AAAA,IAClC;AAAA,EACF;AAAA,EACA,MAAM,WAAW,MAAM;AACrB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,eAAW,YAAY,KAAK,WAAW;AACrC,YAAM,SAAS,WAAW,IAAI;AAAA,IAChC;AAAA,EACF;AACF;AACA,IAAI,aAAa,cAAc,aAAa;AAAA,EAC1C,cAAc;AACZ,UAAM;AAAA,EACR;AAAA,EACA,MAAM,aAAa,OAAO;AACxB,SAAK,OAAO;AACZ,SAAK,SAAS,CAAC;AAAA,EACjB;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,UAAM,YAAY,KAAK,WAAW,OAAO,IAAI,KAAK;AAClD,SAAK,QAAQ;AACb,eAAW,OAAO,MAAM;AACtB,YAAM,QAAQ,KAAK;AACnB,UAAI,OAAO,UAAU,UAAU;AAC7B,YAAI,CAAC,KAAK,OAAO,eAAe,GAAG,GAAG;AACpC,eAAK,OAAO,OAAO;AAAA,QACrB;AACA,aAAK,OAAO,OAAO,KAAK,OAAO,OAAO,QAAQ;AAAA,MAChD,OAAO;AACL,YAAI;AACJ,YAAI,OAAO,KAAK,QAAQ;AACtB,+BAAqB,KAAK,OAAO;AAAA,QACnC,OAAO;AACL,eAAK,OAAO,OAAO;AAAA,QACrB;AACA,cAAM,QAAQ,KAAK,MAAM,KAAK,KAAK,OAAO,MAAM,IAAI,OAAO,SAAS,CAAC,CAAC;AACtE,aAAK,OAAO,OAAO;AACnB,YAAI,sBAAsB,MAAM;AAC9B,6BAAmB,QAAQ;AAAA,QAC7B;AAAA,MACF;AAAA,IACF;AAAA,EACF;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,QAAI,QAAQ,MAAM;AAChB,iBAAW,OAAO,KAAK,OAAO,YAAY;AACxC,YAAI,KAAK,OAAO,QAAQ,MAAM;AAC5B;AAAA,QACF;AACA,YAAI,OAAO,KAAK,OAAO,SAAS,UAAU;AACxC,eAAK,OAAO,KAAK,OAAO,OAAO,KAAK;AAAA,QACtC,OAAO;AACL,eAAK,MAAM;AACT,kBAAM,OAAO,IAAI,IAAI,GAAG,KAAK,IAAI,GAAG,KAAK,OAAO,IAAI;AACpD,iBAAK,OAAO;AACZ,iBAAK,OAAO,KAAK,QAAQ;AACzB,iBAAK,KAAK,IAAI;AAAA,UAChB,CAAC;AAAA,QACH;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACF;AACA,IAAI,UAAU,cAAc,aAAa;AAAA,EACvC,MAAM,aAAa,MAAM;AACvB,SAAK,QAAQ,CAAC;AACd,SAAK,UAAU,CAAC;AAAA,EAClB;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,SAAK,MAAM,KAAK,KAAK;AACrB,eAAW,OAAO,MAAM;AACtB,UAAI,KAAK,QAAQ,QAAQ,MAAM;AAC7B,aAAK,QAAQ,OAAO,CAAC;AAAA,MACvB;AACA,WAAK,QAAQ,KAAK,KAAK,KAAK,IAAI;AAAA,IAClC;AAAA,EACF;AAAA,EACA,MAAM,WAAW;AACf,UAAM,WAAW,CAAC;AAClB,UAAM,OAAO,CAAC;AACd,UAAM,UAAU,CAAC;AACjB,eAAW,OAAO,KAAK,SAAS;AAC9B,YAAM,aAAa,KAAK,QAAQ;AAChC,eAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,YAAI,OAAO,WAAW,QAAQ,UAAU;AACtC,gBAAM,cAAc,WAAW;AAC/B,mBAAS,KAAK,YAAY,KAAK,CAAC;AAChC,eAAK,KAAK,GAAG;AACb,kBAAQ,KAAK,EAAE;AAAA,QACjB;AAAA,MACF;AAAA,IACF;AACA,UAAM,SAAS,MAAM,QAAQ,IAAI,QAAQ;AACzC,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,YAAM,kBAAkB,KAAK,QAAQ,KAAK,KAAK,QAAQ;AACvD,sBAAgB,QAAQ;AACxB,WAAK,QAAQ,KAAK,KAAK,QAAQ,OAAO,OAAO,IAAI;AAAA,IACnD;AAAA,EACF;AACF;AACA,IAAI,iBAAiB,cAAc,aAAa;AAAA,EAC9C,YAAY,MAAM,YAAY;AAC5B,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,UAAU,KAAK;AACpB,SAAK,gBAAgB,KAAK,iBAAiB;AAC3C,SAAK,aAAa,cAAc;AAChC,QAAI,KAAK,eAAe,QAAQ;AAC9B,WAAK,aAAa;AAAA,IACpB;AACA,QAAI,KAAK,eAAe,WAAW,KAAK,WAAW,MAAM;AACvD,YAAM,IAAI,MAAM,iHAAiH;AAAA,IACnI;AACA,QAAI,aAAa,SAAS,KAAK,UAAU,GAAG;AAC1C,WAAK,YAAY,SAAS,KAAK,UAAU,KAAK,IAAI,GAAG,KAAK,YAAY,KAAK,OAAO;AAAA,IACpF;AACA,SAAK,aAAa,KAAK;AACvB,SAAK,WAAW,KAAK;AACrB,SAAK,aAAa,KAAK;AACvB,SAAK,WAAW,KAAK;AACrB,SAAK,aAAa,KAAK;AACvB,SAAK,WAAW,KAAK;AACrB,SAAK,QAAQ,KAAK;AAAA,EACpB;AAAA,EACA,MAAM,UAAU,OAAO,OAAO,MAAM;AAClC,UAAM,KAAK,CAAC;AACZ,QAAI,KAAK,SAAS,MAAM;AACtB,YAAM,qBAAqB,IAAI;AAC/B,SAAG,KAAK,KAAK,MAAM,OAAO,OAAO,IAAI,CAAC;AAAA,IACxC;AACA,OAAG,KAAK,KAAK,cAAc,CAAC;AAC5B,UAAM,QAAQ,IAAI,EAAE;AAAA,EACtB;AAAA,EACA,MAAM,aAAa,OAAO,MAAM;AAC9B,SAAK,eAAe;AACpB,QAAI,KAAK,cAAc,MAAM;AAC3B,YAAM,qBAAqB,IAAI;AAC/B,YAAM,KAAK,WAAW,OAAO,IAAI;AAAA,IACnC;AAAA,EACF;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,UAAM,KAAK,CAAC;AACZ,QAAI,KAAK,YAAY,MAAM;AACzB,YAAM,qBAAqB,IAAI;AAC/B,SAAG,KAAK,KAAK,SAAS,OAAO,IAAI,CAAC;AAAA,IACpC;AACA,QAAI,KAAK,eAAe,SAAS;AAC/B,SAAG,KAAK,KAAK,cAAc,CAAC;AAAA,IAC9B;AACA,UAAM,QAAQ,IAAI,EAAE;AAAA,EACtB;AAAA,EACA,MAAM,aAAa,OAAO,MAAM;AAC9B,QAAI,KAAK,cAAc,MAAM;AAC3B,YAAM,qBAAqB,IAAI;AAC/B,YAAM,KAAK,WAAW,OAAO,IAAI;AAAA,IACnC;AAAA,EACF;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,UAAM,KAAK,CAAC;AACZ,QAAI,KAAK,YAAY,MAAM;AACzB,YAAM,qBAAqB,IAAI;AAC/B,SAAG,KAAK,KAAK,SAAS,OAAO,IAAI,CAAC;AAAA,IACpC;AACA,QAAI,KAAK,eAAe,SAAS;AAC/B,SAAG,KAAK,KAAK,cAAc,CAAC;AAAA,IAC9B,WAAW,aAAa,SAAS,KAAK,UAAU,GAAG;AACjD,SAAG,KAAK,KAAK,UAAU,KAAK,cAAc,OAAO,IAAI,CAAC;AAAA,IACxD;AACA,UAAM,QAAQ,IAAI,EAAE;AAAA,EACtB;AAAA,EACA,MAAM,aAAa,MAAM;AACvB,QAAI,KAAK,cAAc,MAAM;AAC3B,YAAM,qBAAqB,IAAI;AAC/B,YAAM,KAAK,WAAW,IAAI;AAAA,IAC5B;AAAA,EACF;AAAA,EACA,MAAM,WAAW,MAAM;AACrB,QAAI,KAAK,YAAY,MAAM;AACzB,YAAM,qBAAqB,IAAI;AAC/B,YAAM,KAAK,SAAS,IAAI;AAAA,IAC1B;AAAA,EACF;AACF;AACA,SAAS,qBAAqB,YAAY,YAAY;AACpD,MAAI,cAAc,MAAM;AACtB,iBAAa,CAAC;AAAA,EAChB;AACA,MAAI,sBAAsB,cAAc;AACtC,WAAO,CAAC,UAAU;AAAA,EACpB;AACA,MAAI,MAAM,QAAQ,UAAU,KAAK,WAAW,cAAc,cAAc;AACtE,WAAO;AAAA,EACT;AACA,QAAM,kBAAkB,OAAO,UAAU;AACzC,SAAO,gBAAgB,IAAI,CAAC,mBAAmB,IAAI,eAAe,gBAAgB,UAAU,CAAC;AAC/F;AACA,IAAI,8BAA8B,MAAM;AAAA,EACtC,cAAc;AAAA,EACd;AAAA,EACA,OAAO,4BAA4B,gBAAgB,qBAAqB;AACtE,iBAAa,OAAO,kBAAkB,KAAK,OAAO,UAAU,cAAc,GAAG,MAAM,8DAA8D,gBAAgB;AACjK,gCAA4B,kBAAkB,mBAAmB;AACjE,QAAI,4BAA4B,aAAa,mBAAmB,MAAM;AACpE,kCAA4B,aAAa,kBAAkB,CAAC;AAAA,IAC9D;AACA,gCAA4B,aAAa,gBAAgB,KAAK,mBAAmB;AAAA,EACnF;AAAA,EACA,OAAO,kBAAkB,qBAAqB;AAC5C,eAAW,aAAa,4BAA4B,cAAc;AAChE,YAAM,eAAe,4BAA4B,aAAa,CAAC;AAC/D,mBAAa,QAAQ,CAAC,SAAS;AAC7B,YAAI,SAAS,qBAAqB;AAChC,gBAAM,IAAI,WAAW,iCAAiC;AAAA,QACxD;AAAA,MACF,CAAC;AAAA,IACH;AAAA,EACF;AAAA,EACA,OAAO,QAAQ;AACb,gCAA4B,eAAe,CAAC;AAAA,EAC9C;AAAA,EACA,OAAO,gBAAgB,gBAAgB;AACrC,UAAM,eAAe,CAAC;AACtB,eAAW,aAAa,4BAA4B,cAAc;AAChE,YAAM,QAAQ,CAAC;AACf,UAAI,kBAAkB,OAAO;AAC3B,qBAAa,KAAK,GAAG,4BAA4B,aAAa,MAAM;AAAA,MACtE;AAAA,IACF;AACA,WAAO,aAAa,IAAI,CAAC,SAAS,IAAI,KAAK,CAAC;AAAA,EAC9C;AACF;AACA,4BAA4B,eAAe,CAAC;AAC5C,SAAS,mBAAmB,YAAY,SAAS,QAAQ,cAAc,iBAAiB,eAAe,WAAW,cAAc,iBAAiB;AAC/I,QAAM,UAAU,IAAI,QAAQ;AAC5B,QAAM,kBAAkB;AAAA,IACtB,IAAI,WAAW;AAAA,IACf,GAAG,4BAA4B,gBAAgB,OAAO;AAAA,EACxD;AACA,MAAI,cAAc,MAAM;AACtB,oBAAgB,KAAK,GAAG,UAAU;AAAA,EACpC;AACA,kBAAgB,KAAK,OAAO;AAC5B,QAAM,eAAe,IAAI,aAAa,eAAe;AACrD,eAAa,UAAU;AAAA,IACrB;AAAA,IACA;AAAA,IACA,SAAS;AAAA,IACT,OAAO;AAAA,IACP;AAAA,IACA;AAAA,IACA;AAAA,IACA,SAAS;AAAA,EACX,CAAC;AACD,SAAO,EAAE,cAAc,QAAQ;AACjC;AAGA,SAAS,YAAYf,SAAQ,gBAAgB,CAAC,GAAG,iBAAiB,OAAO;AACvE,SAAO,uBAAuBA,SAAQ,sBAAsB,iBAAiB,OAAO,EAAE,cAAc,eAAe,SAAS,cAAc;AAC5I;AAGA,SAAS,YAAY,GAAG,MAAM;AAC5B,SAAO,KAAK,MAAM;AAChB,QAAI,EAAE,UAAU,WAAW;AACzB,UAAI,KAAK,GAAG,SAAS;AAAA,IACvB;AACA,UAAM,YAAY,KAAK,QAAQ,CAAC,GAAG,MAAM,IAAI;AAC7C,UAAM,gBAAgB,KAAK,UAAU,OAAO,QAAQ,CAAC;AACrD,UAAM,QAAQ,KAAK,QAAQ,WAAW,aAAa,CAAC;AACpD,WAAO,IAAI,GAAG,KAAK;AAAA,EACrB,CAAC;AACH;AACA,SAAS,kBAAkB,OAAO,OAAO;AACvC,SAAO,KAAK,MAAM,KAAK,QAAQ,IAAI,OAAO,KAAK,CAAC,GAAG,EAAE,CAAC;AACxD;AACA,SAAS,kBAAkB,OAAO,OAAO;AACvC,SAAO,KAAK,MAAM,KAAK,IAAI,IAAI,OAAO,KAAK,CAAC,GAAG,EAAE,CAAC;AACpD;AACA,SAAS,4BAA4B,OAAO,OAAO;AACjD,SAAO,KAAK,MAAM;AAChB,UAAM,OAAO,IAAI,OAAO,KAAK;AAC7B,UAAM,cAAc,YAAY,IAAI,KAAK,GAAG,QAAQ,GAAG,OAAO,SAAS;AACvE,UAAM,YAAY,IAAI,IAAI,MAAM,WAAW,CAAC;AAC5C,WAAO,IAAI,KAAK,KAAK,WAAW,EAAE,CAAC;AAAA,EACrC,CAAC;AACH;AACA,SAAS,4BAA4B,OAAO,OAAO;AACjD,SAAO,KAAK,MAAM;AAChB,UAAM,cAAc,YAAY,OAAO,QAAQ,GAAG,OAAO,SAAS;AAClE,UAAM,WAAWnB,MAAK,KAAK,GAAG,WAAW,CAAC;AAC1C,UAAM,cAAc,YAAY,OAAO,QAAQ,GAAG,OAAO,SAAS;AAClE,UAAM,YAAYA,MAAK,KAAK,GAAG,WAAW,CAAC;AAC3C,WAAO,KAAK,QAAQ,IAAI,UAAU,SAAS,CAAC,GAAG,EAAE;AAAA,EACnD,CAAC;AACH;AACA,SAAS,aAAa,OAAO,OAAO;AAClC,SAAO,KAAK,MAAM;AAChB,UAAM,YAAY,QAAQ,GAAG,IAAI,GAAG,IAAI,OAAO,KAAK,CAAC,CAAC;AACtD,WAAO,KAAK,QAAQ,SAAS,GAAG,EAAE;AAAA,EACpC,CAAC;AACH;AACA,SAAS,MAAM,OAAO,OAAO;AAC3B,SAAO,KAAK,MAAM;AAChB,UAAM,YAAY,QAAQ,GAAG,IAAI,GAAG,IAAI,OAAO,KAAK,CAAC,CAAC;AACtD,WAAO,KAAK,WAAW,EAAE;AAAA,EAC3B,CAAC;AACH;AACA,SAAS,iBAAiB,OAAO,OAAO;AACtC,SAAO,KAAK,MAAM;AAChB,UAAM,MAAM,KAAK,IAAI,OAAO,KAAK,GAAG,EAAE;AACtC,UAAM,OAAO,IAAI,IAAI,IAAI,GAAG,KAAK,GAAG,KAAK,GAAG,EAAE;AAC9C,WAAO,QAAQ,GAAG,KAAK,GAAG,IAAI,MAAM,GAAG,CAAC,CAAC;AAAA,EAC3C,CAAC;AACH;AACA,SAAS,QAAQ,OAAO,OAAO;AAC7B,SAAO,KAAK,MAAM;AAChB,UAAMO,SAAQ,KAAK,IAAI,CAAC;AACxB,UAAM,iBAAiB,IAAI,OAAO,KAAK;AACvC,UAAM,gBAAgB,IAAI,KAAK,gBAAgB,SAAS,IAAI,IAAI,cAAc,CAAC,CAAC,GAAGA,MAAK;AACxF,WAAO,KAAK,eAAe,EAAE;AAAA,EAC/B,CAAC;AACH;AACA,SAAS,wBAAwB,QAAQ,QAAQ,aAAa,OAAO;AACnE,SAAO,KAAK,MAAM;AAChB,QAAI,YAAY;AACd,eAAS,QAAQ,MAAM;AAAA,IACzB,OAAO;AACL,YAAM,YAAY,KAAK,QAAQ,OAAO,MAAM,SAAS,GAAG,IAAI;AAC5D,eAAS,IAAI,QAAQ,SAAS;AAAA,IAChC;AACA,aAAS,YAAY,QAAQ,QAAQ,GAAG,IAAI,QAAQ,CAAC;AACrD,WAAO,IAAI,KAAK,IAAI,KAAK,QAAQ,SAAS,GAAGP,MAAK,MAAM,CAAC,GAAG,OAAO,MAAM,SAAS,CAAC,CAAC;AAAA,EACtF,CAAC;AACH;AACA,SAAS,8BAA8B,QAAQ,QAAQ,aAAa,OAAO;AACzE,SAAO,KAAK,MAAM;AAChB,UAAM,aAAa,KAAK,MAAM,SAAS,MAAM,CAAC,GAAG,OAAO;AACxD,aAAS,YAAY,QAAQ,QAAQ,GAAG,IAAI,QAAQ,CAAC;AACrD,UAAM,cAAc,OAAO;AAC3B,UAAM,eAAe,QAAQ,OAAO,YAAY,YAAY,YAAY,SAAS,EAAE,GAAG,WAAW;AACjG,WAAO,wBAAwB,cAAc,QAAQ,UAAU;AAAA,EACjE,CAAC;AACH;AACA,SAAS,8BAA8BwB,SAAQ,QAAQ;AACrD,MAAI,CAAC,aAAa,YAAYA,QAAO,OAAO,OAAO,KAAK,GAAG;AACzD,UAAM,IAAI,WAAW,8DAA8D,KAAK,UAAUA,QAAO,KAAK,SAAS,KAAK,UAAU,OAAO,KAAK,GAAG;AAAA,EACvJ;AACA,SAAO,KAAK,MAAM;AAChB,UAAM,aAAa,KAAK,MAAM;AAC9B,UAAM,eAAe,IAAI,IAAI,MAAM,CAAC;AACpC,WAAO,KAAK,IAAI,YAAY,IAAI,QAAQA,OAAM,CAAC,GAAG,MAAM,IAAI,YAAY,CAAC,CAAC;AAAA,EAC5E,CAAC;AACH;AACA,SAAS,mBAAmB,OAAO,OAAO;AACxC,SAAO,KAAK,MAAM;AAChB,QAAI;AACJ,QAAI,YAAY,OAAO,QAAQ,GAAG,IAAI,QAAQ,CAAC;AAC/C,QAAIxB,MAAK,IAAI,GAAG,IAAI,GAAG,CAAC,CAAC,CAAC;AAC1B,WAAO,KAAK,8BAA8B,OAAO,CAAC,GAAG,EAAE;AAAA,EACzD,CAAC;AACH;AACA,SAAS,0BAA0B,OAAO,OAAO;AAC/C,SAAO,KAAK,MAAM;AAChB,UAAM,cAAc,YAAY,OAAO,QAAQ,GAAG,CAAC;AACnD,UAAM,cAAc,YAAY,OAAO,QAAQ,GAAG,CAAC;AACnD,WAAO,KAAK,IAAI,OAAOA,MAAK,IAAI,aAAa,WAAW,CAAC,CAAC,GAAG,EAAE;AAAA,EACjE,CAAC;AACH;AACA,SAAS,QAAQ,OAAO,OAAO;AAC7B,SAAO,KAAK,MAAM;AAChB,UAAM,UAAUA,MAAK,KAAK,QAAQ,GAAG,KAAK,CAAC;AAC3C,WAAO,KAAK,IAAI,OAAO,IAAI,OAAO,OAAO,CAAC,GAAG,EAAE;AAAA,EACjD,CAAC;AACH;AACA,SAAS,gBAAgB,OAAO,OAAO;AACrC,SAAO,KAAK,MAAM;AAChB,UAAM,iBAAiB,YAAY,OAAO,EAAE;AAC5C,UAAM,iBAAiB,YAAY,OAAO,EAAE;AAC5C,UAAM,YAAY,IAAI,gBAAgB,cAAc;AACpD,WAAO,IAAI,KAAK,WAAW,EAAE,CAAC;AAAA,EAChC,CAAC;AACH;AACA,IAAI,YAAY;AAAA,EACd,kBAAkB;AAAA,EAClB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,SAAS,IAAI,gBAAgB;AAC3B,MAAI,OAAO,mBAAmB,UAAU;AACtC,QAAI,kBAAkB,WAAW;AAC/B,aAAO,UAAU;AAAA,IACnB;AACA,QAAI,SAAS,gBAAgB;AAC7B,QAAI,eAAe,YAAY,EAAE,SAAS,qBAAqB,GAAG;AAChE,eAAS,gBAAgB;AAAA,IAC3B;AACA,UAAM,IAAI,WAAW,MAAM;AAAA,EAC7B,OAAO;AACL,WAAO;AAAA,EACT;AACF;AAGA,SAAS,eAAe,OAAO,OAAO;AACpC,SAAO,KAAK,MAAM;AAChB,UAAM,aAAa,IAAI,KAAK,SAAS,KAAK,CAAC;AAC3C,UAAM,mBAAmB,MAAM,QAAQ,OAAO,UAAU,GAAG,MAAM,KAAK;AACtE,WAAO,KAAK,MAAM,OAAO,gBAAgB,GAAG,EAAE;AAAA,EAChD,CAAC;AACH;AACA,SAAS,oBAAoB,OAAO,OAAO;AACzC,SAAO,KAAK,MAAM,MAAM,MAAM,OAAO,OAAO,EAAE,GAAG,OAAO,OAAO,EAAE,CAAC,GAAG,SAAS,CAAC;AACjF;AACA,SAAS,cAAc,OAAO,OAAO;AACnC,SAAO,KAAK,MAAM;AAChB,WAAO,KAAK,KAAK,WAAW,MAAM,OAAO,CAAC,GAAG,MAAM,OAAO,CAAC,CAAC,CAAC,GAAG,SAAS;AAAA,EAC3E,CAAC;AACH;AACA,SAAS,eAAe,OAAO,OAAO;AACpC,SAAO,KAAK,MAAM;AAChB,WAAO,KAAK,KAAK,WAAW,MAAM,OAAO,CAAC,GAAG,MAAM,OAAO,CAAC,CAAC,CAAC,GAAG,SAAS;AAAA,EAC3E,CAAC;AACH;AACA,SAAS,eAAe,OAAO,OAAO;AACpC,SAAO,KAAK,MAAM;AAChB,WAAO,KAAK,KAAK,WAAW,MAAM,OAAO,CAAC,GAAG,MAAM,OAAO,CAAC,CAAC,CAAC,GAAG,SAAS;AAAA,EAC3E,CAAC;AACH;AACA,SAAS,UAAU,OAAO,OAAO;AAC/B,SAAO,KAAK,MAAM;AAChB,UAAM,KAAK,cAAc,OAAO,KAAK;AACrC,UAAM,KAAK,eAAe,OAAO,KAAK;AACtC,UAAM,cAAc,KAAK,IAAI,EAAE;AAC/B,WAAO,KAAK,MAAM,QAAQ,aAAa,CAAC,GAAG,IAAI,IAAI,WAAW,GAAG,CAAC,GAAG,SAAS;AAAA,EAChF,CAAC;AACH;AACA,SAAS,OAAO,OAAO,OAAO;AAC5B,SAAO,KAAK,MAAM;AAChB,UAAM,KAAK,cAAc,OAAO,KAAK;AACrC,UAAM,KAAK,eAAe,OAAO,KAAK;AACtC,UAAM,cAAc,KAAK,IAAI,EAAE;AAC/B,WAAO,KAAK,MAAM,QAAQ,aAAa,CAAC,GAAG,IAAI,IAAI,WAAW,GAAG,CAAC,GAAG,SAAS;AAAA,EAChF,CAAC;AACH;AACA,SAAS,oBAAoB,OAAO,OAAO;AACzC,SAAO,mBAAmB,OAAO,KAAK;AACxC;AACA,SAAS,0BAA0B,OAAO,OAAO;AAC/C,MAAI,MAAM,SAAS,MAAM,MAAM;AAC7B,YAAQ,QAAQ,OAAO,CAAC,MAAM,OAAO,CAAC,CAAC;AAAA,EACzC;AACA,UAAQ,OAAO,OAAO,EAAE;AACxB,MAAI,MAAM,UAAU,MAAM,OAAO;AAC/B,YAAQ,KAAK,OAAO,MAAM,KAAK;AAAA,EACjC;AACA,SAAO,KAAK,MAAM,OAAO,KAAK,GAAG,SAAS;AAC5C;AACA,IAAI,MAAM;AACV,IAAI,MAAM;AACV,IAAI,MAAM;AACV,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,OAAO;AACX,IAAI,2BAA2B;AAC/B,IAAI,SAAS;AACb,IAAI,iCAAiC;AACrC,IAAI,aAAa;AAAA,EACf;AAAA,EACA;AAAA,EACA;AAAA,EACA,yBAAyB;AAAA,EACzB,+BAA+B;AAAA,EAC/B;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,SAAS,KAAK,YAAY;AACxB,MAAI,OAAO,eAAe,YAAY,cAAc,YAAY;AAC9D,WAAO,WAAW;AAAA,EACpB,WAAW,OAAO,eAAe,YAAY,cAAc,MAAM;AAC/D,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,WAAW,kBAAkB,YAAY;AAAA,EACrD;AACF;AACA,SAAS,oBAAoB,IAAI;AAC/B,UAAQ,OAAO,MAAM,0BAA0B,IAAI;AACnD,MAAI,OAAO,OAAO,UAAU;AAC1B,WAAO;AAAA,EACT,OAAO;AACL,QAAI;AACJ,eAAW,OAAO,OAAO,KAAK,SAAS,GAAG;AACxC,UAAI,UAAU,SAAS,IAAI;AACzB,iBAAS;AACT;AAAA,MACF;AAAA,IACF;AACA,QAAI,WAAW,QAAQ;AACrB,aAAO;AAAA,IACT;AACA,eAAW,OAAO,OAAO,KAAK,UAAU,GAAG;AACzC,UAAI,WAAW,SAAS,IAAI;AAC1B,iBAAS;AACT;AAAA,MACF;AAAA,IACF;AACA,QAAI,WAAW,QAAQ;AACrB,aAAO;AAAA,IACT;AACA,WAAO,GAAG;AAAA,EACZ;AACF;AAGA,SAAS,aAAa,YAAY;AAChC,QAAM,eAAe;AAAA,IACnB,WAAW,MAAM,MAAM,QAAQ,IAAI;AAAA,IACnC,YAAY,MAAM,MAAM,SAAS,GAAG,MAAM,QAAQ,CAAC;AAAA,IACnD,QAAQ,MAAM,MAAM,KAAK,MAAM,KAAK,OAAO,QAAQ,CAAC;AAAA,IACpD,UAAU,MAAM,MAAM,OAAO,MAAM,KAAK,OAAO,QAAQ,GAAG,CAAC;AAAA,IAC3D,WAAW,MAAM,MAAM,QAAQ,MAAM,KAAK,GAAG,QAAQ,CAAC;AAAA,IACtD,OAAO,MAAM,MAAM,IAAI,IAAI;AAAA,EAC7B;AACA,eAAa,aAAa,aAAa;AACvC,eAAa,cAAc,aAAa;AACxC,eAAa,UAAU,aAAa;AACpC,eAAa,YAAY,aAAa;AACtC,eAAa,aAAa,aAAa;AACvC,eAAa,SAAS,aAAa;AACnC,MAAI,cAAc,cAAc;AAC9B,WAAO,aAAa,YAAY;AAAA,EAClC;AACA,QAAM,IAAI,WAAW,qBAAqB,YAAY;AACxD;AAGA,IAAI,8CAA8C,IAAI,OAAO;AAC7D,SAAS,yBAAyB,qBAAqB,WAAW,YAAY,OAAO;AACnF,MAAI,uBAAuB,QAAQ,OAAO,wBAAwB,YAAY,OAAO,eAAe,mBAAmB,MAAM,OAAO,aAAa,CAAC,iBAAiB,mBAAmB,GAAG;AACvL,UAAM,IAAI,MAAM,oEAAoE;AAAA,EACtF;AACA,MAAI,WAAW;AACb,UAAM,MAAM,KAAK,UAAU,mBAAmB;AAC9C,QAAI,IAAI,SAAS,6CAA6C;AAC5D,cAAQ,KAAK,mCAAmC,2CAA2C,IAAI,qJAAqJ,8CAA8C;AAAA,IACpS;AAAA,EACF;AACF;AACA,SAAS,iBAAiB,GAAG;AAC3B,MAAI,MAAM,MAAM;AACd,WAAO;AAAA,EACT,WAAW,OAAO,MAAM,UAAU;AAChC,QAAI,OAAO,eAAe,CAAC,MAAM,OAAO,WAAW;AACjD,YAAM,OAAO,OAAO,KAAK,CAAC;AAC1B,iBAAW,OAAO,MAAM;AACtB,YAAI,OAAO,QAAQ,UAAU;AAC3B,iBAAO;AAAA,QACT;AACA,YAAI,CAAC,iBAAiB,EAAE,IAAI,GAAG;AAC7B,iBAAO;AAAA,QACT;AAAA,MACF;AACA,aAAO;AAAA,IACT,OAAO;AACL,UAAI,MAAM,QAAQ,CAAC,GAAG;AACpB,mBAAW,QAAQ,GAAG;AACpB,cAAI,CAAC,iBAAiB,IAAI,GAAG;AAC3B,mBAAO;AAAA,UACT;AAAA,QACF;AACA,eAAO;AAAA,MACT,OAAO;AACL,eAAO;AAAA,MACT;AAAA,IACF;AAAA,EACF,OAAO;AACL,UAAM,QAAQ,OAAO;AACrB,WAAO,UAAU,YAAY,UAAU,YAAY,UAAU;AAAA,EAC/D;AACF;AAGA,SAAS,aAAakC,SAAQ,YAAY,WAAW,UAAU,QAAQ,KAAK;AAC1E,QAAM,iBAAiB,sBAAsBA,OAAM;AACnD,QAAM,YAAY,CAAC,gBAAgB,eAAe,gBAAgB,SAAS;AAC3E,MAAI,gBAAgB;AAClB,iBAAa,cAAc;AAC3B,gBAAY,aAAa,CAAC,MAAM,MAAM,MAAM,CAAC;AAAA,EAC/C,OAAO;AACL,iBAAa,cAAc;AAC3B,gBAAY,aAAa,CAAC,MAAM,MAAM,KAAK,KAAK,CAAC;AAAA,EACnD;AACA,MAAI,UAAU,UAAU,SAAS,MAAM,GAAG;AACxC,gBAAY,UAAU,IAAI,CAAC,OAAO,KAAK,MAAM,aAAa,EAAE,CAAC;AAAA,EAC/D;AACA,MAAI;AACJ,MAAI,CAAC,gBAAgB;AACnB,cAAU,KAAK,iBAAiB;AAChC,oBAAgB,CAAC;AACjB,eAAW,SAASA,QAAO,cAAc;AACvC,oBAAc,KAAK,GAAGA,QAAO,aAAa,MAAM;AAAA,IAClD;AAAA,EACF;AACA,UAAQ,IAAI,OAAO,UAAU,CAAC;AAC9B,WAAS,WAAW,WAAW,OAAO;AACtC,UAAQ,IAAI,OAAO,UAAU,CAAC;AAC9B,QAAM,SAASA,QAAO;AACtB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,QAAI,gBAAgB;AAClB,wBAAkB,OAAO,KAAK,WAAW,OAAO;AAAA,IAClD,OAAO;AACL,uCAAiC,OAAO,KAAK,WAAW,eAAe,OAAO;AAAA,IAChF;AACA,aAAS,OAAO,OAAO,SAAS,IAAI,MAAM,KAAK,OAAO,UAAU,CAAC;AAAA,EACnE;AACA,EAAAA,QAAO,iCAAiC;AACxC,QAAM,iBAAiB,qBAAqBA,OAAM;AAClD,QAAM,oBAAoB,qBAAqBA,QAAO,mBAAmB;AACzE,UAAQ,iBAAiB,iBAAiB,mBAAmB;AAC7D,UAAQ,qBAAqB,gBAAgB;AAC7C,UAAQ,yBAAyB,mBAAmB;AACpD,UAAQ,IAAI,OAAO,UAAU,CAAC;AAChC;AACA,SAAS,qBAAqBA,SAAQ;AACpC,MAAI;AACJ,MAAIA,QAAO,6BAA6B,MAAM;AAC5C,qBAAiB,qBAAqBA,QAAO,yBAAyB;AAAA,EACxE,OAAO;AACL,qBAAiB,qBAAqBA,QAAO,gBAAgB;AAAA,EAC/D;AACA,SAAO;AACT;AACA,SAAS,sBAAsBA,SAAQ;AACrC,MAAI,iBAAiB;AACrB,QAAM,eAAe,CAAC;AACtB,QAAM,QAAQ,CAAC;AACf,aAAW,SAASA,QAAO,cAAc;AACvC,iBAAa,KAAKA,QAAO,aAAa,MAAM;AAAA,EAC9C;AACA,aAAW,cAAc,cAAc;AACrC,QAAI,WAAW,SAAS,KAAK,WAAW,WAAW,KAAK,WAAW,GAAG,cAAc,SAAS,GAAG;AAC9F,uBAAiB;AACjB;AAAA,IACF;AACA,UAAM,KAAK,GAAG,UAAU;AAAA,EAC1B;AACA,MAAI,gBAAgB;AAClB,eAAW,SAASA,QAAO,QAAQ;AACjC,UAAI,OAAO;AACX,iBAAWb,SAAQ,MAAM,cAAc;AACrC,YAAI,MAAM,QAAQA,KAAI,MAAM,IAAI;AAC9B,cAAI,MAAM;AACR,6BAAiB;AACjB;AAAA,UACF,OAAO;AACL,mBAAO;AAAA,UACT;AAAA,QACF;AAAA,MACF;AACA,UAAI,CAAC,gBAAgB;AACnB;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,SAAS,QAAQ,WAAW,UAAU,QAAQ,KAAK;AAC1D,MAAI,OAAO;AACX,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,QAAI,KAAK,GAAG;AACV,aAAO,KAAK,MAAM,GAAG,KAAK,SAAS,CAAC,IAAI;AAAA,IAC1C;AACA,YAAQ,OAAO;AACf,WAAO,KAAK,MAAM,GAAG,UAAU,GAAG;AAClC,YAAQ,IAAI,OAAO,UAAU,MAAM,KAAK,MAAM;AAAA,EAChD;AACA,UAAQ,IAAI;AACd;AACA,SAAS,kBAAkB,OAAO,WAAW,SAAS;AACpD,MAAI;AACJ,MAAI;AACJ,MAAI;AACF,iBAAa,MAAM,aAAa,IAAI,CAAC,MAAM,KAAK,UAAU,EAAE,WAAW,CAAC,EAAE,KAAK,GAAG;AAAA,EACpF,SAAS,KAAP;AACA,iBAAa;AAAA,EACf;AACA,MAAI;AACF,kBAAc,KAAK,UAAU,MAAM,WAAW;AAAA,EAChD,SAAS,KAAP;AACA,kBAAc;AAAA,EAChB;AACA,QAAM,OAAO,MAAM;AACnB,QAAM,YAAY,MAAM,aAAa;AACrC,QAAM,SAAS;AAAA,IACb,GAAG,SAAS;AAAA,IACZ;AAAA,IACA;AAAA,IACA,MAAM,YAAY,EAAE,SAAS;AAAA,EAC/B;AACA,WAAS,QAAQ,WAAW,OAAO;AACrC;AACA,SAAS,iCAAiC,OAAO,WAAW,eAAe,SAAS;AAClF,MAAI;AACJ,MAAI;AACJ,MAAI;AACF,iBAAa,MAAM,aAAa,IAAI,CAAC,MAAM,KAAK,UAAU,EAAE,WAAW,CAAC,EAAE,KAAK,GAAG;AAAA,EACpF,SAAS,KAAP;AACA,iBAAa;AAAA,EACf;AACA,MAAI;AACF,kBAAc,KAAK,UAAU,MAAM,WAAW;AAAA,EAChD,SAAS,KAAP;AACA,kBAAc;AAAA,EAChB;AACA,QAAM,cAAc,CAAC;AACrB,aAAWA,SAAQ,MAAM,cAAc;AACrC,QAAI,iBAAiB,QAAQ,cAAc,SAAS,KAAK,cAAc,QAAQA,KAAI,MAAM,IAAI;AAC3F;AAAA,IACF;AACA,aAAS,KAAK,GAAG,KAAKA,MAAK,cAAc,QAAQ,EAAE,IAAI;AACrD,YAAM,eAAeA,MAAK,cAAc,IAAI;AAC5C,YAAM,oBAAoBA,MAAK,YAAY;AAC3C,YAAM,qBAAqBA,MAAK,cAAc;AAC9C,kBAAY,KAAK,GAAG,gBAAgB,sBAAsB,qBAAqB;AAAA,IACjF;AAAA,EACF;AACA,QAAM,OAAO,MAAM;AACnB,QAAM,YAAY,MAAM,aAAa;AACrC,QAAM,kBAAkB,YAAY,WAAW,IAAI,KAAK,YAAY;AACpE,QAAM,SAAS;AAAA,IACb,GAAG,SAAS;AAAA,IACZ;AAAA,IACA;AAAA,IACA,MAAM,YAAY,EAAE,SAAS;AAAA,IAC7B;AAAA,EACF;AACA,WAAS,QAAQ,WAAW,OAAO;AACnC,WAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,EAAE,IAAI;AAC9C,aAAS,CAAC,IAAI,IAAI,IAAI,IAAI,YAAY,GAAG,GAAG,WAAW,OAAO;AAAA,EAChE;AACF;AAGA,SAAS,6BAA6B,KAAKP,QAAO,OAAO;AACvD,UAAQ,QAAQ,kBAAkB,QAAQ,kBAAkB,QAAQ,kBAAkBA,WAAU,KAAK,OAAO,UAAU;AACxH;AACA,SAAS,oBAAoB,gBAAgB,KAAK;AAChD,MAAI,mBAAmB,MAAM;AAC3B,WAAO;AAAA,EACT,WAAW,OAAO,mBAAmB,UAAU;AAC7C,WAAO,YAAY,cAAc;AAAA,EACnC,WAAW,OAAO,mBAAmB,YAAY,OAAO,mBAAmB,WAAW;AACpF,WAAO;AAAA,EACT,WAAW,0BAA0B,OAAO;AAC1C,UAAM,UAAU,CAAC;AACjB,UAAM,cAAc,eAAe;AACnC,aAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,YAAM,OAAO,eAAe;AAC5B,UAAI,6BAA6B,KAAK,IAAI,IAAI,GAAG;AAC/C,gBAAQ,KAAK,IAAI;AAAA,MACnB,OAAO;AACL,gBAAQ,KAAK,oBAAoB,MAAM,GAAG,CAAC;AAAA,MAC7C;AAAA,IACF;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAM,SAAS,CAAC;AAChB,eAAW,eAAe,OAAO,KAAK,cAAc,GAAG;AACrD,YAAM,gBAAgB,eAAe;AACrC,UAAI,gBAAgB,UAAU,OAAO,kBAAkB,UAAU;AAC/D,eAAO,eAAe;AAAA,MACxB,OAAO;AACL,cAAM,QAAQ,YAAY,WAAW;AACrC,eAAO,SAAS,oBAAoB,eAAe,KAAK;AAAA,MAC1D;AAAA,IACF;AACA,WAAO;AAAA,EACT;AACF;AACA,SAAS,oBAAoB,UAAU,KAAK;AAC1C,MAAI,aAAa,QAAQ,aAAa,QAAQ;AAC5C,WAAO;AAAA,EACT,WAAW,OAAO,aAAa,UAAU;AACvC,WAAO,YAAY,QAAQ;AAAA,EAC7B,WAAW,OAAO,aAAa,YAAY,OAAO,aAAa,WAAW;AACxE,WAAO;AAAA,EACT,WAAW,oBAAoB,OAAO;AACpC,UAAM,UAAU,CAAC;AACjB,UAAM,cAAc,SAAS;AAC7B,aAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,YAAM,OAAO,SAAS;AACtB,UAAI,6BAA6B,KAAK,IAAI,IAAI,GAAG;AAC/C,gBAAQ,KAAK,IAAI;AAAA,MACnB,OAAO;AACL,gBAAQ,KAAK,oBAAoB,MAAM,GAAG,CAAC;AAAA,MAC7C;AAAA,IACF;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAM,SAAS,CAAC;AAChB,eAAW,SAAS,OAAO,KAAK,QAAQ,GAAG;AACzC,YAAM,UAAU,SAAS;AACzB,YAAM,QAAQ,YAAY,KAAK;AAC/B,WAAK,UAAU,UAAU,UAAU,gBAAgB,OAAO,YAAY,UAAU;AAC9E,eAAO,SAAS;AAAA,MAClB,OAAO;AACL,eAAO,SAAS,oBAAoB,SAAS,KAAK;AAAA,MACpD;AAAA,IACF;AACA,WAAO;AAAA,EACT;AACF;AAGA,IAAI,WAAW;AAGf,IAAI,YAAY,cAAc,MAAM;AAAA,EAClC,YAAY,MAAM;AAChB,UAAM,CAAC,CAAC;AACR,SAAK,iBAAiC,oBAAI,IAAI;AAC9C,SAAK,OAAO,KAAK;AACjB,QAAI,KAAK,QAAQ,MAAM;AACrB,YAAM,SAAS,KAAK,aAAa,EAAE,YAAY;AAC/C,WAAK,OAAO,OAAO,MAAM;AAAA,IAC3B;AACA,SAAK,kBAAkB;AACvB,SAAK,aAAa;AAClB,QAAI,MAAM,QAAQ,KAAK,MAAM,GAAG;AAC9B,WAAK,SAAS,KAAK,OAAO,MAAM;AAAA,IAClC,OAAO;AACL,WAAK,SAAS,CAAC,KAAK,MAAM;AAAA,IAC5B;AACA,QAAI,MAAM,QAAQ,KAAK,OAAO,GAAG;AAC/B,WAAK,UAAU,KAAK,QAAQ,MAAM;AAAA,IACpC,OAAO;AACL,WAAK,UAAU,CAAC,KAAK,OAAO;AAAA,IAC9B;AACA,QAAI,QAAQ,KAAK,MAAM,EAAE,WAAW,KAAK,OAAO,QAAQ;AACtD,YAAM,IAAI,WAAW,mGAAmG,KAAK,OAAO,IAAI,CAAC,MAAM,EAAE,IAAI,GAAG;AAAA,IAC1J;AACA,QAAI,QAAQ,KAAK,OAAO,EAAE,WAAW,KAAK,QAAQ,QAAQ;AACxD,cAAQ,KAAK,qGAAqG,KAAK,QAAQ,IAAI,CAAC,MAAM,EAAE,IAAI,GAAG;AAAA,IACrJ;AACA,SAAK,cAAc,CAAC;AACpB,SAAK,yBAAyB,CAAC;AAC/B,SAAK,2BAA2B,CAAC;AACjC,SAAK,eAAe,CAAC;AACrB,SAAK,0BAA0B,CAAC;AAChC,SAAK,4BAA4B,CAAC;AAClC,SAAK,SAAS,CAAC;AACf,SAAK,wBAAwB,CAAC;AAC9B,eAAW,KAAK,KAAK,SAAS;AAC5B,YAAM,QAAQ,EAAE;AAChB,YAAM,YAAY,EAAE;AACpB,YAAM,cAAc,EAAE;AACtB,WAAK,aAAa,KAAK,KAAK;AAC5B,WAAK,wBAAwB,KAAK,SAAS;AAC3C,WAAK,0BAA0B,KAAK,WAAW;AAAA,IACjD;AACA,eAAW,KAAK,KAAK,QAAQ;AAC3B,YAAM,QAAQ,EAAE;AAChB,YAAM,YAAY,EAAE;AACpB,YAAM,cAAc,EAAE;AACtB,cAAQ,cAAc,GAAG,0BAA0B;AACnD,cAAQ,gBAAgB,GAAG,4BAA4B;AACvD,WAAK,YAAY,KAAK,KAAK;AAC3B,WAAK,uBAAuB,KAAK,SAAS;AAC1C,WAAK,yBAAyB,KAAK,WAAW;AAAA,IAChD;AACA,SAAK,aAAa,CAAC;AACnB,SAAK,cAAc,CAAC;AACpB,SAAK,kBAAkB,CAAC;AACxB,SAAK,iBAAiB,CAAC;AACvB,SAAK,kBAAkB,CAAC;AACxB,aAAS,KAAK,GAAG,KAAK,KAAK,YAAY,QAAQ,MAAM;AACnD,YAAM,QAAQ,KAAK,YAAY;AAC/B,UAAI,EAAE,iBAAiB,aAAa;AAClC,cAAM,IAAI,UAAU,8EAA8E,KAAK,iBAAiB,2CAA2C,MAAM,aAAa,IAAI;AAAA,MAC5L;AACA,WAAK,WAAW,KAAK,MAAM,IAAI;AAC/B,WAAK,gBAAgB,KAAK,MAAM,eAAe;AAC/C,WAAK,eAAe,KAAK,MAAM,IAAI;AAAA,IACrC;AACA,eAAW,SAAS,KAAK,cAAc;AACrC,WAAK,YAAY,KAAK,MAAM,IAAI;AAAA,IAClC;AACA,SAAK,sBAAsB,KAAK,OAAO,IAAI,CAAC,MAAM,EAAE,KAAK;AACzD,SAAK,uBAAuB,KAAK,QAAQ,IAAI,CAAC,MAAM,EAAE,KAAK;AAC3D,UAAM,cAAc,CAAC;AACrB,UAAM,eAAe,CAAC;AACtB,UAAM,eAAe,CAAC;AACtB,UAAM,iBAAiB,CAAC;AACxB,UAAM,eAAe,CAAC;AACtB,UAAM,yBAAyB,CAAC;AAChC,UAAM,kBAAkB,CAAC,SAAS,gBAAgB,kBAAkB,OAAO,WAAW,gBAAgB;AACpG,UAAI,SAAS,QAAQ,aAAa,QAAQ,eAAe,MAAM;AAC7D,gBAAQ,QAAQ;AAChB,oBAAY,QAAQ;AACpB,sBAAc,QAAQ;AAAA,MACxB;AACA,YAAMO,QAAO,MAAM,aAAa;AAChC,UAAI,iBAAiB,QAAQA,KAAI,MAAM,IAAI;AACzC,cAAM,IAAI,aAAa,cAAc,QAAQ,kBAAkB,MAAM,2BAA2B;AAAA,MAClG;AACA,UAAI,eAAe,QAAQA,KAAI,MAAM,IAAI;AACvC;AAAA,MACF;AACA,WAAK,eAAe,IAAI,UAAU,QAAQ,OAAO,SAAS,CAAC;AAC3D,UAAI,EAAE,MAAM,MAAM,eAAe;AAC/B,qBAAa,MAAM,MAAM,OAAO,KAAK,YAAY,EAAE;AAAA,MACrD;AACA,UAAI,iBAAiB,QAAQA,KAAI,MAAM,IAAI;AACzC,yBAAiB,KAAKA,KAAI;AAAA,MAC5B;AACA,YAAM,mBAAmBA,MAAK,cAAc;AAC5C,eAAS,KAAK,GAAG,KAAK,kBAAkB,MAAM;AAC5C,cAAM,IAAIA,MAAK,aAAa;AAC5B,cAAM,SAASA,MAAK,cAAc;AAClC,cAAM,aAAaA,MAAK,YAAY;AACpC,cAAM,eAAeA,MAAK,cAAc;AACxC,wBAAgB,GAAG,gBAAgB,kBAAkB,QAAQ,YAAY,YAAY;AAAA,MACvF;AACA,qBAAe,KAAKA,KAAI;AACxB,aAAO,iBAAiB,QAAQA,KAAI,KAAK,GAAG;AAC1C,yBAAiB,OAAO,iBAAiB,QAAQA,KAAI,GAAG,CAAC;AAAA,MAC3D;AACA,6BAAuB,KAAKA,KAAI;AAAA,IAClC;AACA,UAAM,gBAAgB,CAAC;AACvB,UAAM,kBAAkB,CAAC;AACzB,eAAW,KAAK,KAAK,SAAS;AAC5B,sBAAgB,GAAG,eAAe,eAAe;AAAA,IACnD;AACA,UAAM,iCAAiC,uBAAuB,MAAM,EAAE,QAAQ;AAC9E,eAAWA,SAAQ,gCAAgC;AACjD,mBAAaA,MAAK,MAAMA;AACxB,UAAI,EAAEA,MAAK,MAAM,cAAc;AAC7B,oBAAYA,MAAK,MAAM;AAAA,MACzB;AACA,UAAI,QAAQ,YAAYA,MAAK;AAC7B,YAAM,gBAAgB,aAAaA,MAAK,cAAc,OAAO,OAAO,IAAI,aAAaA,MAAK,cAAc;AACxG,cAAQ,KAAK,IAAI,OAAO,aAAa;AACrC,mBAAaA,MAAK,cAAc,MAAM;AACtC,qBAAeA,MAAK,cAAc,MAAMA,MAAK;AAC7C,kBAAYA,MAAK,MAAM;AACvB,eAAS,KAAK,GAAG,KAAKA,MAAK,cAAc,QAAQ,MAAM;AACrD,cAAM,eAAeA,MAAK,cAAc;AACxC,cAAM,YAAYA,MAAK,YAAY;AACnC,cAAM,cAAc,aAAa,aAAa;AAC9C,cAAM,iBAAiB,YAAY,YAAY,OAAO,OAAO,IAAI,YAAY,YAAY;AACzF,oBAAY,YAAY,MAAM,KAAK,IAAI,QAAQ,GAAG,cAAc;AAChE,qBAAa,YAAY,MAAM;AAAA,MACjC;AAAA,IACF;AACA,UAAM,eAAe,CAAC;AACtB,eAAW,UAAU,aAAa;AAChC,YAAM,QAAQ,YAAY;AAC1B,UAAI,EAAE,SAAS,eAAe;AAC5B,qBAAa,SAAS,CAAC;AAAA,MACzB;AACA,mBAAa,OAAO,KAAK,aAAa,OAAO;AAAA,IAC/C;AACA,UAAM,gBAAgB,CAAC;AACvB,eAAW,WAAW,cAAc;AAClC,YAAM,QAAQ,aAAa;AAC3B,UAAI,EAAE,SAAS,gBAAgB;AAC7B,sBAAc,SAAS,CAAC;AAAA,MAC1B;AACA,oBAAc,OAAO,KAAK,eAAe,QAAQ;AAAA,IACnD;AACA,QAAI,YAAY,OAAO,KAAK,aAAa,EAAE,IAAI,CAAC,MAAM,SAAS,GAAG,EAAE,CAAC,EAAE,KAAK,oBAAoB;AAChG,SAAK,SAAS,CAAC;AACf,eAAW,SAAS,WAAW;AAC7B,YAAM,iBAAiB,cAAc;AACrC,qBAAe,KAAK,CAAC,GAAG,MAAM;AAC5B,cAAM,SAAS,aAAa,EAAE;AAC9B,cAAM,SAAS,aAAa,EAAE;AAC9B,YAAI,SAAS,QAAQ;AACnB,iBAAO;AAAA,QACT;AACA,YAAI,SAAS,QAAQ;AACnB,iBAAO;AAAA,QACT;AACA,eAAO;AAAA,MACT,CAAC;AACD,iBAAW,SAAS,gBAAgB;AAClC,YAAI,iBAAiB,WAAW;AAC9B,eAAK,sBAAsB,KAAK,KAAK;AAAA,QACvC;AACA,aAAK,OAAO,KAAK,KAAK;AAAA,MACxB;AAAA,IACF;AACA,SAAK,gBAAgB;AACrB,gBAAY,OAAO,KAAK,YAAY,EAAE,IAAI,CAAC,MAAM,SAAS,GAAG,EAAE,CAAC,EAAE,KAAK,oBAAoB;AAC3F,UAAM,oBAAoB,KAAK,OAAO,MAAM;AAC5C,UAAM,0BAA0B,CAAC;AACjC,eAAW,SAAS,WAAW;AAC7B,iBAAWA,SAAQ,aAAa,QAAQ;AACtC,cAAM,QAAQA,MAAK;AACnB,YAAI,SAAS,MAAM;AACjB,qBAAW,KAAKA,MAAK,cAAc;AACjC,gBAAI,kBAAkB,QAAQ,CAAC,MAAM,IAAI;AACvC,oBAAM,IAAI,aAAa,sDAAsD,eAAe,MAAM,qEAAqE,yBAAyB;AAAA,YAClM;AAAA,UACF;AACA,qBAAW,KAAKA,MAAK,eAAe;AAClC,8BAAkB,KAAK,CAAC;AAAA,UAC1B;AACA,kCAAwB,KAAK,MAAM,IAAI;AAAA,QACzC;AAAA,MACF;AAAA,IACF;AACA,SAAK,eAAe;AACpB,UAAM,WAAW,KAAK,OAAO,IAAI,CAAC,MAAM,EAAE,IAAI;AAC9C,eAAW,QAAQ,UAAU;AAC3B,YAAM,iBAAiB,SAAS,OAAO,CAAC,MAAM,MAAM,IAAI,EAAE;AAC1D,UAAI,mBAAmB,GAAG;AACxB,cAAM,IAAI,aAAa,aAAa,iBAAiB,uFAAuF,KAAK,UAAU,QAAQ,CAAC;AAAA,MACtK;AAAA,IACF;AACA,SAAK,gBAAgB,CAAC;AACtB,SAAK,eAAe,CAAC;AACrB,QAAI,KAAK;AAAA,MACP,eAAe;AAAA,MACf,eAAe,CAAC;AAAA,MAChB,aAAa,CAAC;AAAA,MACd,eAAe,CAAC;AAAA,MAChB,cAAc,KAAK;AAAA,MACnB,eAAe,KAAK;AAAA,MACpB,YAAY,KAAK,OAAO,IAAI,CAAC,MAAM,IAAI;AAAA,MACvC,aAAa,KAAK,QAAQ,IAAI,CAAC,MAAM,IAAI;AAAA,MACzC,aAAa,KAAK,OAAO,IAAI,CAAC,MAAM,EAAE,KAAK;AAAA,MAC3C,cAAc,KAAK,QAAQ,IAAI,CAAC,MAAM,EAAE,KAAK;AAAA,IAC/C,CAAC;AACD,SAAK,QAAQ;AACb,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,oBAAoB;AAClB,QAAI,KAAK,cAAc,GAAG;AACxB,YAAM,IAAI,MAAM,cAAc,KAAK,4BAA4B;AAAA,IACjE;AAAA,EACF;AAAA,EACA,UAAU;AACR,SAAK,kBAAkB;AACvB,UAAM,SAAS,EAAE,sBAAsB,MAAM,sBAAsB,EAAE;AACrE,QAAI,EAAE,KAAK,cAAc,GAAG;AAC1B,iBAAW,SAAS,KAAK,QAAQ;AAC/B,eAAO,wBAAwB,MAAM,QAAQ,EAAE;AAAA,MACjD;AACA,iBAAW,aAAa,KAAK,uBAAuB;AAClD,eAAO,wBAAwB,UAAU,QAAQ,EAAE;AAAA,MACrD;AAAA,IACF;AACA,WAAO,uBAAuB,KAAK;AACnC,WAAO;AAAA,EACT;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,UAAU,WAAW;AACvB,SAAK,OAAO,QAAQ,CAAC,UAAU;AAC7B,YAAM,kBAAkB,QAAQ,CAAC,MAAM,EAAE,YAAY,SAAS;AAAA,IAChE,CAAC;AACD,SAAK,aAAa;AAAA,EACpB;AAAA,EACA,IAAI,mBAAmB;AACrB,QAAI,KAAK,kBAAkB,SAAS,GAAG;AACrC,YAAM,IAAI,WAAW,sNAAsN;AAAA,IAC7O;AACA,QAAI,CAAC,KAAK,WAAW;AACnB,aAAO,CAAC;AAAA,IACV;AACA,QAAI,UAAU,CAAC;AACf,eAAW,SAAS,KAAK,QAAQ;AAC/B,gBAAU,QAAQ,OAAO,MAAM,gBAAgB;AAAA,IACjD;AACA,WAAO;AAAA,EACT;AAAA,EACA,IAAI,sBAAsB;AACxB,UAAM,UAAU,CAAC;AACjB,eAAW,SAAS,KAAK,QAAQ;AAC/B,cAAQ,KAAK,GAAG,MAAM,mBAAmB;AAAA,IAC3C;AACA,QAAI,CAAC,KAAK,WAAW;AACnB,YAAM,mBAAmB,CAAC;AAC1B,iBAAW,SAAS,KAAK,QAAQ;AAC/B,yBAAiB,KAAK,GAAG,MAAM,gBAAgB;AAAA,MACjD;AACA,aAAO,iBAAiB,OAAO,OAAO;AAAA,IACxC;AACA,WAAO;AAAA,EACT;AAAA,EACA,IAAI,UAAU;AACZ,WAAO,KAAK,iBAAiB,OAAO,KAAK,mBAAmB;AAAA,EAC9D;AAAA,EACA,YAAY,SAAS,SAAS,MAAM;AAClC,UAAM,eAAe,CAAC;AACtB,QAAI,oBAAoB;AACxB,eAAW,SAAS,KAAK,QAAQ;AAC/B,iBAAW,UAAU,MAAM,SAAS;AAClC,YAAI,aAAa,OAAO,iBAAiB,MAAM;AAC7C,gBAAM,IAAI,WAAW,0BAA0B,OAAO,cAAc;AAAA,QACtE;AACA,qBAAa,OAAO,gBAAgB;AACpC;AAAA,MACF;AAAA,IACF;AACA,UAAM,oBAAoB,CAAC;AAC3B,eAAW,QAAQ,SAAS;AAC1B,UAAI,gBAAgB;AACpB,UAAI,aAAa,SAAS,MAAM;AAC9B,cAAM,SAAS,KAAK,MAAM,GAAG;AAC7B,cAAM,mBAAmB,OAAO,MAAM,GAAG,EAAE,EAAE,OAAO,CAAC,OAAO,OAAO,SAAS,EAAE,CAAC;AAC/E,wBAAgB,iBAAiB,KAAK,GAAG;AAAA,MAC3C;AACA,UAAI,aAAa,kBAAkB,MAAM;AACvC,0BAAkB,KAAK,CAAC,aAAa,gBAAgB,QAAQ,KAAK,CAAC;AAAA,MACrE,WAAW,QAAQ;AACjB,cAAM,IAAI,WAAW,gDAAgD,MAAM;AAAA,MAC7E;AACA,aAAO,aAAa;AAAA,IACtB;AACA,QAAI,QAAQ;AACV,YAAM,aAAa,CAAC;AACpB,iBAAW,QAAQ,cAAc;AAC/B,mBAAW,KAAK,IAAI;AAAA,MACtB;AACA,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,IAAI,WAAW,GAAG,WAAW,aAAa,0CAA0C,YAAY;AAAA,MACxG;AAAA,IACF;AACA,kBAAc,iBAAiB;AAAA,EACjC;AAAA,EACA,gBAAgB;AACd,UAAM,YAAY,KAAK,UAAU;AACjC,UAAM,cAAc,CAAC;AACrB,gBAAY,eAAe,KAAK,aAAa;AAC7C,gBAAY,YAAY;AACxB,gBAAY,kBAAkB,eAAe;AAC7C,gBAAY,aAAa;AACzB,WAAO;AAAA,EACT;AAAA,EACA,OAAO,QAAQ,eAAe,MAAM;AAClC,UAAM,cAAc,oBAAoB,KAAK,cAAc,CAAC;AAC5D,WAAO,eAAe,KAAK,UAAU,WAAW,IAAI;AAAA,EACtD;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS,OAAO,MAAM;AACtB,YAAM,WAAW,IAAI,SAAS;AAC9B,eAAS,KAAK,GAAG,KAAK,KAAK,OAAO,QAAQ,EAAE,IAAI;AAC9C,iBAAS,IAAI,KAAK,OAAO,KAAK,OAAO,GAAG;AAAA,MAC1C;AACA,aAAO,QAAQ,KAAK,SAAS,UAAU,MAAM;AAAA,IAC/C,CAAC;AAAA,EACH;AAAA,EACA,YAAY,QAAQX,OAAM;AACxB,WAAO,KAAK,MAAM;AAChB,eAAS,OAAO,MAAM;AACtB,UAAI;AACJ,UAAIA,SAAQ,MAAM;AAChB,gBAAQ,aAAa,MAAM,OAAO,MAAM;AAAA,MAC1C,OAAO;AACL,gBAAQ,OAAOA,KAAI;AAAA,MACrB;AACA,aAAO,KAAK,iBAAiB,QAAQ,KAAK,EAAE;AAAA,IAC9C,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,UAAM,cAAc,mBAAmB,UAAU;AACjD,QAAI,YAAY,WAAW,KAAK,YAAY,QAAQ;AAClD,YAAM,IAAI,WAAW,+BAA+B,yBAAyB,KAAK,YAAY,uBAAuB;AAAA,IACvH;AACA,UAAM,uBAAuB,CAAC;AAC9B,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,MAAM;AAC9C,YAAM,QAAQ,KAAK,YAAY;AAC/B,YAAM,cAAc,YAAY;AAChC,YAAM,WAAW,MAAM,OAAO;AAC9B,2BAAqB,YAAY;AAAA,IACnC;AACA,UAAM,YAAY,OAAO,KAAK,KAAK,YAAY,EAAE,IAAI,CAAC,MAAM,SAAS,GAAG,EAAE,CAAC,EAAE,KAAK,oBAAoB;AACtG,QAAI,UAAU,SAAS,GAAG;AACxB,iBAAW,SAAS,WAAW;AAC7B,cAAM,QAAQ,KAAK,aAAa;AAChC,mBAAWW,SAAQ,OAAO;AACxB,gBAAM,QAAQA,MAAK;AACnB,cAAI,KAAK,YAAY,IAAI,CAAC,MAAM,EAAE,EAAE,EAAE,QAAQ,MAAM,EAAE,MAAM,IAAI;AAC9D;AAAA,UACF;AACA,gBAAM,eAAe,CAAC;AACtB,mBAAS,IAAI,GAAG,IAAIA,MAAK,cAAc,QAAQ,KAAK;AAClD,kBAAM,eAAeA,MAAK,cAAc;AACxC,kBAAM,aAAaA,MAAK,YAAY;AACpC,kBAAM,cAAcA,MAAK,cAAc;AACvC,kBAAM,WAAW,GAAG,aAAa,QAAQ,cAAc;AACvD,kBAAM,cAAc,qBAAqB;AACzC,yBAAa,KAAK,WAAW;AAAA,UAC/B;AACA,gBAAM,cAAc,MAAM,mBAAmB,iBAAiB,YAAY,CAAC;AAC3E,gBAAM,gBAAgB,mBAAmB,WAAW;AACpD,gBAAM,YAAY,MAAM,aAAa,QAAQA,KAAI;AACjD,mBAAS,IAAI,GAAG,IAAI,cAAc,QAAQ,KAAK;AAC7C,kBAAM,WAAW,GAAG,MAAM,QAAQ,aAAa;AAC/C,iCAAqB,YAAY,cAAc;AAAA,UACjD;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,eAAe,CAAC;AACtB,UAAM,kBAAkB,CAAC;AACzB,aAAS,KAAK,GAAG,KAAK,KAAK,aAAa,QAAQ,MAAM;AACpD,YAAM,QAAQ,KAAK,aAAa;AAChC,YAAM,YAAY,KAAK,wBAAwB;AAC/C,YAAM,cAAc,KAAK,0BAA0B;AACnD,YAAM,WAAW,GAAG,MAAM,QAAQ,aAAa;AAC/C,sBAAgB,KAAK,QAAQ;AAAA,IAC/B;AACA,aAAS,KAAK,GAAG,KAAK,gBAAgB,QAAQ,MAAM;AAClD,YAAM,MAAM,gBAAgB;AAC5B,cAAQ,OAAO,oBAAoB;AACnC,mBAAa,KAAK,qBAAqB,IAAI;AAAA,IAC7C;AACA,WAAO,iBAAiB,YAAY;AAAA,EACtC;AAAA,EACA,iBAAiB,QAAQ,OAAO;AAC9B,QAAI,SAAS,MAAM;AACjB,cAAQ,aAAa,MAAM,OAAO,MAAM;AAAA,IAC1C;AACA,UAAM,YAAY,CAAC;AACnB,aAAS,KAAK,GAAG,KAAK,KAAK,OAAO,QAAQ,EAAE,IAAI;AAC9C,YAAM,IAAI,KAAK,OAAO;AACtB,YAAM,IAAI,OAAO;AACjB,YAAMX,QAAO,MAAM;AACnB,gBAAU,EAAE,MAAM,CAAC,GAAGA,KAAI;AAAA,IAC5B;AACA,UAAM,YAAY,OAAO,KAAK,KAAK,YAAY,EAAE,IAAI,CAAC,MAAM,SAAS,GAAG,EAAE,CAAC,EAAE,KAAK,oBAAoB;AACtG,eAAW,SAAS,WAAW;AAC7B,YAAM,QAAQ,KAAK,aAAa;AAChC,iBAAWW,SAAQ,OAAO;AACxB,cAAM,QAAQA,MAAK;AACnB,cAAM,wBAAwBA,MAAK;AACnC,cAAM,yBAAyBA,MAAK;AACpC,cAAM,eAAe,IAAI,MAAM;AAC/B,mBAAW,KAAK,uBAAuB;AACrC,cAAI,EAAE,MAAM,WAAW;AACrB,yBAAa,KAAK,UAAU,EAAE,GAAG;AAAA,UACnC;AAAA,QACF;AACA,YAAI,aAAa,WAAW,sBAAsB,QAAQ;AACxD,cAAI,SAAS,CAAC;AACd,cAAI;AACJ,cAAI;AACJ,cAAI;AACJ,cAAI;AACJ,cAAIA,MAAK,YAAY,MAAM;AACzB,qBAASA,MAAK;AAAA,UAChB;AACA,cAAI,aAAa,WAAW,GAAG;AAC7B,kBAAM,CAAC,gBAAgB,YAAY,IAAI,aAAa;AACpD,gBAAI,OAAO,WAAW,MAAM;AAC1B,qBAAO,UAAU;AAAA,YACnB;AACA,6BAAiB,OAAO,MAAM,KAAK,gBAAgB,MAAM,CAAC;AAC1D,2BAAe,OAAO,MAAM,YAAY,gBAAgB,YAAY,CAAC;AACrE,8BAAkB,CAAC,cAAc;AACjC,4BAAgB,CAAC,YAAY;AAAA,UAC/B,OAAO;AACL,8BAAkB,aAAa,IAAI,CAAC,MAAM,EAAE,EAAE;AAC9C,4BAAgB,aAAa,IAAI,CAAC,MAAM,EAAE,EAAE;AAC5C,gBAAI,OAAO,WAAW,MAAM;AAC1B,qBAAO,UAAU;AAAA,YACnB;AACA,6BAAiB,OAAO,MAAM,KAAK,iBAAiB,MAAM,CAAC;AAC3D,2BAAe,OAAO,MAAM,YAAY,iBAAiB,aAAa,CAAC;AAAA,UACzE;AACA,cAAI,MAAM,qBAAqB;AAC7B,kBAAM,IAAI,oBAAoB,uHAAuH;AAAA,UACvJ;AACA,mBAAS,KAAK,GAAG,KAAK,uBAAuB,QAAQ,EAAE,IAAI;AACzD,kBAAM,IAAI,uBAAuB;AACjC,kBAAM,IAAI,eAAe;AACzB,kBAAMX,QAAO,aAAa;AAC1B,sBAAU,EAAE,MAAM,CAAC,GAAGA,KAAI;AAAA,UAC5B;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,gBAAgB,CAAC;AACvB,UAAM,cAAc,CAAC;AACrB,UAAM,eAAe,CAAC;AACtB,eAAW,KAAK,KAAK,SAAS;AAC5B,cAAQ,EAAE,MAAM,WAAW,4BAA4B,EAAE,UAAU,EAAE,IAAI;AACzE,YAAM,CAAC,SAASA,KAAI,IAAI,UAAU,EAAE;AACpC,mBAAa,KAAK,QAAQ,KAAK;AAC/B,oBAAc,KAAK,OAAO;AAC1B,kBAAY,KAAKA,KAAI;AAAA,IACvB;AACA,WAAO,CAAC,eAAe,aAAa,YAAY;AAAA,EAClD;AAAA,EACA,uBAAuB,QAAQ;AAC7B,UAAM,oBAAoB,CAAC;AAC3B,QAAI;AACJ,eAAW,SAAS,KAAK,QAAQ;AAC/B,kBAAY,iBAAiB,YAAY,IAAI;AAC7C,eAAS,oBAAoB,GAAG,oBAAoB,MAAM,aAAa,QAAQ,qBAAqB;AAClG,cAAM,UAAU,UAAU,QAAQ,OAAO,iBAAiB;AAC1D,YAAI,KAAK,eAAe,IAAI,OAAO,GAAG;AACpC,4BAAkB,WAAW;AAC7B,uBAAa;AAAA,QACf;AAAA,MACF;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,SAAS,MAAMI,QAAO;AACpB,QAAIA,UAAS,MAAM;AACjB,UAAI,KAAK,OAAO,UAAUA,QAAO;AAC/B,cAAM,IAAI,WAAW,wCAAwCA,8BAA6B,KAAK,OAAO,kBAAkB;AAAA,MAC1H,OAAO;AACL,eAAO,KAAK,OAAOA;AAAA,MACrB;AAAA,IACF,OAAO;AACL,UAAI,QAAQ,MAAM;AAChB,cAAM,IAAI,WAAW,4CAA4C;AAAA,MACnE;AAAA,IACF;AACA,eAAW,SAAS,KAAK,QAAQ;AAC/B,UAAI,MAAM,SAAS,MAAM;AACvB,eAAO;AAAA,MACT;AAAA,IACF;AACA,UAAM,IAAI,WAAW,kBAAkB,MAAM;AAAA,EAC/C;AAAA,EACA,kBAAkB;AAChB,WAAO,KAAK,MAAM;AAChB,YAAM,UAAU,CAAC;AACjB,iBAAW,SAAS,KAAK,QAAQ;AAC/B,iBAAS,YAAY,GAAG,YAAY,MAAM,aAAa,QAAQ,EAAE,WAAW;AAC1E,gBAAM,UAAU,UAAU,QAAQ,OAAO,SAAS;AAClD,cAAI,KAAK,eAAe,IAAI,OAAO,GAAG;AACpC,oBAAQ,KAAK,GAAG,MAAM,gBAAgB,CAAC;AAAA,UACzC;AAAA,QACF;AAAA,MACF;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMK,UAAS,EAAE,MAAM,KAAK,KAAK;AACjC,UAAM,oBAAoB,KAAK,uBAAuB,KAAK,MAAM;AACjE,UAAM,eAAe,CAAC;AACtB,eAAW,SAAS,KAAK,QAAQ;AAC/B,YAAM,iBAAiB,MAAM,aAAa;AAC1C,YAAM,cAAc,MAAM,UAAU;AACpC,YAAM,uBAAuB,CAAC;AAC9B,eAAS,oBAAoB,GAAG,oBAAoB,MAAM,aAAa,QAAQ,qBAAqB;AAClG,cAAME,QAAO,MAAM,aAAa;AAChC,cAAM,UAAU,UAAU,QAAQ,OAAO,iBAAiB;AAC1D,YAAI,SAAS,CAAC;AACd,YAAI,KAAK,eAAe,IAAI,OAAO,GAAG;AACpC,cAAIA,MAAK,UAAU;AACjB,gBAAI;AACF,mBAAK,UAAUA,MAAK,QAAQ;AAC5B,uBAASA,MAAK;AAAA,YAChB,SAAS,KAAP;AACA,sBAAQ,KAAK,SAAS,MAAM,uDAAuDA,MAAK,iHAAiH;AACzM,uBAAS,CAAC;AAAA,YACZ;AAAA,UACF;AACA,cAAIA,MAAK,cAAc,SAAS,GAAG;AACjC,kBAAM,WAAW,CAAC;AAClB,qBAAS,KAAK,GAAG,KAAKA,MAAK,cAAc,QAAQ,MAAM;AACrD,oBAAM,eAAeA,MAAK,cAAc;AACxC,oBAAM,YAAYA,MAAK,YAAY;AACnC,oBAAM,cAAcA,MAAK,cAAc;AACvC,oBAAM,WAAW,UAAU,QAAQ,cAAc,SAAS;AAC1D,kBAAI,eAAe,kBAAkB;AACrC,kBAAI,gBAAgB,MAAM;AACxB,+BAAe;AAAA,cACjB;AACA,uBAAS,KAAK,CAAC,aAAa,MAAM,cAAc,aAAa,MAAM,CAAC;AAAA,YACtE;AACA,iCAAqB,KAAK,QAAQ;AAAA,UACpC;AAAA,QACF;AAAA,MACF;AACA,YAAM,OAAO,CAAC;AACd,WAAK,UAAU,MAAM;AACrB,WAAK,eAAe;AACpB,WAAK,YAAY;AACjB,WAAK,kBAAkB;AACvB,mBAAa,KAAK,IAAI;AAAA,IACxB;AACA,IAAAF,QAAO,YAAY;AACnB,UAAM,cAAc,CAAC;AACrB,aAAS,KAAK,GAAG,KAAK,KAAK,YAAY,QAAQ,MAAM;AACnD,YAAM,QAAQ,KAAK,YAAY;AAC/B,YAAM,YAAY,KAAK,uBAAuB;AAC9C,YAAM,UAAU,UAAU,QAAQ,OAAO,SAAS;AAClD,UAAI,CAAC,KAAK,eAAe,IAAI,OAAO,GAAG;AACrC;AAAA,MACF;AACA,UAAI,eAAe,kBAAkB;AACrC,UAAI,iBAAiB,QAAQ,iBAAiB,QAAQ;AACpD,uBAAe;AAAA,MACjB;AACA,YAAM,cAAc,KAAK,yBAAyB;AAClD,kBAAY,KAAK,CAAC,MAAM,MAAM,cAAc,WAAW,CAAC;AAAA,IAC1D;AACA,IAAAA,QAAO,iBAAiB;AACxB,UAAM,eAAe,CAAC;AACtB,aAAS,KAAK,GAAG,KAAK,KAAK,aAAa,QAAQ,MAAM;AACpD,YAAM,QAAQ,KAAK,aAAa;AAChC,YAAM,YAAY,KAAK,wBAAwB;AAC/C,YAAM,UAAU,UAAU,QAAQ,OAAO,SAAS;AAClD,UAAI,CAAC,KAAK,eAAe,IAAI,OAAO,GAAG;AACrC;AAAA,MACF;AACA,UAAI,eAAe,kBAAkB;AACrC,UAAI,iBAAiB,QAAQ,iBAAiB,QAAQ;AACpD,uBAAe;AAAA,MACjB;AACA,YAAM,cAAc,KAAK,0BAA0B;AACnD,mBAAa,KAAK,CAAC,MAAM,MAAM,cAAc,WAAW,CAAC;AAAA,IAC3D;AACA,IAAAA,QAAO,kBAAkB;AACzB,WAAOA;AAAA,EACT;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ,gBAAgB,CAAC,GAAG,iBAAiB,OAAO;AACzE,UAAM,gBAAgB,CAAC;AACvB,UAAM,mBAAmB,CAAC;AAC1B,aAAS,mBAAmB,OAAO,UAAU;AAC3C,UAAI,EAAE,MAAM,QAAQ,mBAAmB;AACrC,yBAAiB,MAAM,QAAQ,CAAC,QAAQ;AAAA,MAC1C,OAAO;AACL,yBAAiB,MAAM,MAAM,KAAK,QAAQ;AAAA,MAC5C;AAAA,IACF;AACA,aAAS,YAAY,OAAO,UAAU;AACpC,YAAM,gBAAgB,CAAC;AACvB,UAAI;AACJ,iBAAW,aAAa,UAAU;AAChC,cAAM,mBAAmB,UAAU;AACnC,cAAM,mBAAmB,UAAU;AACnC,cAAM,qBAAqB,UAAU;AACrC,iBAAS,UAAU,MAAM,OAAO,CAAC,IAAI,UAAU;AAC/C,YAAI,EAAE,oBAAoB,gBAAgB;AACxC,6BAAmB,OAAO,QAAQ;AAClC;AAAA,QACF;AACA,cAAM,eAAe,cAAc;AACnC,YAAI,aAAa,aAAa,UAAU,kBAAkB;AACxD,6BAAmB,OAAO,QAAQ;AAClC;AAAA,QACF;AACA,cAAM,cAAc,aAAa,aAAa;AAC9C,sBAAc,KAAK,YAAY,cAAc,mBAAmB;AAAA,MAClE;AACA,UAAI,cAAc,SAAS,GAAG;AAC5B,cAAM,MAAM,iBAAiB,aAAa,GAAG,MAAM;AAAA,MACrD;AAAA,IACF;AACA,aAAS,aAAa,WAAW;AAC/B,YAAM,YAAY,UAAU;AAC5B,YAAM,QAAQ,YAAY,WAAWA,QAAO,oBAAoB,OAAOA,QAAO,mBAAmB,CAAC,CAAC;AACnG,YAAM,6BAA6B,cAAc;AACjD,oBAAc,aAAa;AAC3B,YAAM,mBAAmB,UAAU;AACnC,uBAAiB,QAAQ,CAAC,aAAa;AACrC,YAAI,EAAE,oBAAoB,QAAQ;AAChC,gBAAM,IAAI,WAAW,yDAAyD,UAAU;AAAA,QAC1F;AACA,2BAAmB,OAAO,QAAQ;AAAA,MACpC,CAAC;AAAA,IACH;AACA,UAAM,OAAOA,QAAO;AACpB,UAAM,mBAAmBA,QAAO;AAChC,eAAW,aAAa,kBAAkB;AACxC,mBAAa,SAAS;AAAA,IACxB;AACA,WAAO,CAAC,cAAc,gBAAgB,GAAG;AACvC,iBAAW,aAAa,kBAAkB;AACxC,cAAM,QAAQ,cAAc,UAAU;AACtC,YAAI,MAAM,QAAQ,kBAAkB;AAClC,gBAAM,kCAAkC,iBAAiB,MAAM;AAC/D,iBAAO,iBAAiB,MAAM;AAC9B,qBAAW,YAAY,iCAAiC;AACtD,wBAAY,OAAO,QAAQ;AAAA,UAC7B;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,eAAe,CAAC;AACtB,UAAM,gBAAgB,CAAC;AACvB,UAAM,wBAAwBA,QAAO;AACrC,eAAW,aAAa,uBAAuB;AAC7C,YAAM,YAAY,UAAU;AAC5B,YAAM,YAAY,UAAU;AAC5B,YAAM,cAAc,UAAU;AAC9B,cAAQ,aAAa,aAAa;AAClC,YAAM,QAAQ,cAAc;AAC5B,YAAM,qBAAqB,MAAM,aAAa,WAAW;AACzD,mBAAa,KAAK,mBAAmB,YAAY;AAAA,IACnD;AACA,UAAM,yBAAyBA,QAAO;AACtC,eAAW,aAAa,wBAAwB;AAC9C,YAAM,YAAY,UAAU;AAC5B,YAAM,YAAY,UAAU;AAC5B,YAAM,cAAc,UAAU;AAC9B,cAAQ,aAAa,aAAa;AAClC,YAAM,QAAQ,cAAc;AAC5B,YAAM,qBAAqB,MAAM,aAAa,WAAW;AACzD,oBAAc,KAAK,mBAAmB,YAAY;AAAA,IACpD;AACA,WAAO,IAAI,IAAI,EAAE,QAAQ,cAAc,SAAS,eAAe,KAAK,CAAC;AAAA,EACvE;AAAA,EACA,IAAI,WAAW;AACb,QAAI,KAAK,WAAW;AAClB,YAAM,IAAI,WAAW,sLAAsL;AAAA,IAC7M;AACA,eAAW,SAAS,KAAK,QAAQ;AAC/B,UAAI,MAAM,UAAU;AAClB,eAAO;AAAA,MACT;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,cAAc;AACZ,SAAK,MAAM;AACT,WAAK,OAAO,QAAQ,CAAC,UAAU;AAC7B,YAAI,MAAM,UAAU;AAClB,gBAAM,YAAY;AAAA,QACpB;AAAA,MACF,CAAC;AAAA,IACH,CAAC;AAAA,EACH;AACF;AAGA,SAAS,gCAAgC,SAAS,aAAa,YAAY;AACzE,QAAM,aAAa,YAAY;AAC/B,MAAI,WAAW,QAAQ,MAAM,QAAQ,OAAO,KAAK,QAAQ,WAAW,GAAG;AACrE,WAAO,YAAY,IAAI,CAAC,SAAS,IAAI;AAAA,EACvC;AACA,MAAI,eAAe,GAAG;AACpB,QAAI,MAAM,QAAQ,OAAO,KAAK,QAAQ,WAAW,GAAG;AAClD,aAAO;AAAA,IACT,WAAW,OAAO,YAAY,YAAY,YAAY,MAAM,SAAS;AACnE,aAAO,CAAC,QAAQ,YAAY,GAAG;AAAA,IACjC,OAAO;AACL,aAAO,CAAC,OAAO;AAAA,IACjB;AAAA,EACF;AACA,MAAI,MAAM,QAAQ,OAAO,GAAG;AAC1B,QAAI,QAAQ,WAAW,YAAY;AACjC,YAAM,IAAI,MAAM,YAAY,6BAA6B,QAAQ,wCAAwC,mFAAmF;AAAA,IAC9L;AACA,WAAO;AAAA,EACT,WAAW,OAAO,YAAY,YAAY,OAAO,KAAK,OAAO,EAAE,SAAS,KAAK,OAAO,QAAQ,OAAO,KAAK,OAAO,EAAE,QAAQ,UAAU;AACjI,UAAM,SAAS,CAAC;AAChB,gBAAY,QAAQ,CAAC,eAAe;AAClC,UAAI,cAAc,SAAS;AACzB,eAAO,KAAK,QAAQ,WAAW;AAAA,MACjC,OAAO;AACL,eAAO,KAAK,IAAI;AAAA,MAClB;AAAA,IACF,CAAC;AACD,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,2BAA2B,2BAA2B,2CAA2C,yCAAyC,8BAA8B,8BAA8B,KAAK,UAAU,OAAO,GAAG;AAAA,EACjP;AACF;AACA,SAAS,wBAAwB,aAAa,aAAa;AACzD,SAAO,gCAAgC,aAAa,aAAa,aAAa;AAChF;AACA,eAAe,mBAAmB,GAAG,cAAc,aAAa,kBAAkB;AAChF,MAAI,gBAAgB,QAAQ,oBAAoB,MAAM;AACpD,UAAM,IAAI,MAAM,6CAA6C;AAAA,EAC/D;AACA,MAAI,eAAe,MAAM;AACvB,UAAM,WAAW,KAAK,MAAM;AAC1B,UAAI,EAAE,MAAM,WAAW,GAAG;AACxB,eAAO,MAAM,CAAC;AAAA,MAChB,WAAW,EAAE,MAAM,WAAW,GAAG;AAC/B,YAAI,EAAE,MAAM,KAAK,GAAG;AAClB,gBAAM,OAAO;AACb,iBAAO,OAAO,GAAG,IAAI;AAAA,QACvB,WAAW,EAAE,MAAM,OAAO,GAAG;AAC3B,iBAAO,QAAQ,GAAG,CAAC,EAAE,MAAM,EAAE,CAAC;AAAA,QAChC,OAAO;AACL,gBAAM,IAAI,MAAM,+CAA+C,EAAE,MAAM,wEAAwE;AAAA,QACjJ;AAAA,MACF,OAAO;AACL,cAAM,IAAI,MAAM,yCAAyC,EAAE,4EAA4E;AAAA,MACzI;AAAA,IACF,CAAC;AACD,UAAM,gBAAgB,MAAM,KAAK,MAAM,SAAS,KAAK,CAAC;AACtD,YAAQ,QAAQ;AAChB,UAAM,oBAAoB,CAAC;AAC3B,kBAAc,QAAQ,CAAC,eAAe;AACpC,UAAI,YAAY,eAAe,MAAM;AACnC,cAAM,IAAI,MAAM,wEAAwE,sDAAsD;AAAA,MAChJ,OAAO;AACL,0BAAkB,KAAK,YAAY,WAAW;AAAA,MAChD;AAAA,IACF,CAAC;AACD,WAAO,SAAS,mBAAmB,SAAS;AAAA,EAC9C,OAAO;AACL,WAAO;AAAA,EACT;AACF;AACA,SAAS,qBAAqB,SAAS,eAAe;AACpD,SAAO,IAAI,SAAS,aAAa;AACnC;AAGA,IAAI,gCAAgC;AACpC,SAAS,8BAA8Be,SAAQ,aAAa;AAC1D,MAAI;AACJ,MAAI;AACJ,QAAM,iBAAiB;AACvB,OAAK,eAAe;AACpB,OAAK,eAAe;AACpB,eAAa,OAAO,MAAM,QAAQ,MAAM,MAAM,MAAM,mPAAmP,aAAa;AACpT,QAAM,cAAc,0BAA0B,SAASA,QAAO,YAAY,EAAE;AAC5E,QAAM,cAAc,0BAA0B,UAAUA,QAAO,aAAa,EAAE;AAC9E,QAAM,YAAY,YAAY,GAAG,MAAM;AACvC,eAAa,OAAO,YAAY,WAAWA,QAAO,OAAO,QAAQ,MAAM,mBAAmBA,QAAO,OAAO,2CAA2C,YAAY,yCAAyC,KAAK,UAAUA,QAAO,UAAU,IAAI;AAC5O,eAAa,OAAO,YAAY,WAAWA,QAAO,QAAQ,QAAQ,MAAM,mBAAmBA,QAAO,QAAQ,4CAA4C,YAAY,2CAA2C,KAAK,UAAUA,QAAO,WAAW,IAAI;AAClP,WAAS,SAAS,GAAG,SAAS,YAAY,QAAQ,UAAU;AAC1D,iBAAa,OAAO,YAAY,QAAQ,MAAM,OAAO,WAAW,MAAM,8BAA8BA,QAAO,WAAW,eAAe,YAAY,QAAQ,MAAM,iBAAiB,4BAA4BA,QAAO,WAAW,KAAK;AAAA,EACrO;AACA,WAAS,SAAS,GAAG,SAAS,YAAY,QAAQ,UAAU;AAC1D,iBAAa,OAAO,YAAY,QAAQ,MAAM,OAAO,WAAW,MAAM,+BAA+BA,QAAO,YAAY,eAAe,YAAY,QAAQ,MAAM,iBAAiB,4BAA4BA,QAAO,WAAW,KAAK;AAAA,EACvO;AACA,SAAO,EAAE,IAAI,aAAa,IAAI,YAAY;AAC5C;AACA,SAAS,0BAA0B,eAAe,OAAO,QAAQ;AAC/D,MAAI,kBAAkB,QAAQ;AAC5B,WAAO,CAAC,MAAM;AAAA,EAChB,WAAW,MAAM,QAAQ,MAAM,GAAG;AAChC,iBAAa,OAAO,OAAO,WAAW,MAAM,QAAQ,MAAM,wBAAwB,OAAO,gCAAgC,MAAM,uBAAuB,sBAAsB,QAAQ;AACpL,WAAO;AAAA,EACT,OAAO;AACL,UAAM,SAAS,CAAC;AAChB,eAAW,QAAQ,OAAO;AACxB,UAAI,OAAO,SAAS,MAAM;AACxB,cAAM,IAAI,WAAW,gEAAgE,sBAAsB,QAAQ;AAAA,MACrH;AACA,aAAO,KAAK,OAAO,KAAK;AAAA,IAC1B;AACA,WAAO;AAAA,EACT;AACF;AACA,SAAS,gCAAgC,MAAM;AAC7C,MAAI,KAAK,WAAW,GAAG;AACrB,UAAM,IAAI,oBAAoB,wDAAwD;AAAA,EACxF;AACA,SAAO,EAAE,IAAI,KAAK,IAAI,IAAI,KAAK,GAAG;AACpC;AACA,eAAe,WAAWA,SAAQ,SAAS,MAAM;AAC/C,QAAM,qBAAqB,KAAK,mBAAmB;AACnD,eAAa,OAAOA,QAAO,aAAa,MAAM,MAAM,gGAAgG;AACpJ,eAAa,OAAO,QAAQ,MAAM,MAAM,+FAA+F;AACvI,eAAa,OAAO,KAAK,UAAU,QAAQ,KAAK,SAAS,KAAK,OAAO,UAAU,KAAK,MAAM,GAAG,MAAM,iFAAiF,KAAK,QAAQ;AACjM,eAAa,OAAO,CAAC,sBAAsB,KAAK,kBAAkB,KAAK,OAAO,UAAU,KAAK,eAAe,GAAG,MAAM,uGAAuG,KAAK,iBAAiB;AAClP,eAAa;AAAA,IACX,KAAK,sBAAsB;AAAA,IAC3B,MAAM;AAAA,EACR;AACA,MAAIA,QAAO,YAAY;AACrB,UAAM,IAAI,MAAM,8DAA8D;AAAA,EAChF;AACA,EAAAA,QAAO,aAAa;AACpB,MAAI;AACF,UAAM,eAAe,KAAK,kBAAkB;AAC5C,QAAI;AACJ,QAAI;AACJ,QAAI,cAAc;AAChB,UAAI,gBAAgB,KAAK,cAAc,GAAG;AACxC,qBAAa,OAAO,KAAK,qBAAqB,QAAQ,KAAK,oBAAoB,KAAK,OAAO,UAAU,KAAK,iBAAiB,GAAG,MAAM,iJAAiJ,KAAK,mBAAmB;AAAA,MAC/S,OAAO;AACL,cAAM,iBAAiB,gCAAgC,KAAK,cAAc;AAC1E,gBAAQ,eAAe;AACvB,gBAAQ,eAAe;AAAA,MACzB;AAAA,IACF;AACA,UAAM,gBAAgBA,QAAO,kBAAkB;AAC/C,UAAM,YAAYA,QAAO,uBAAuB;AAChD,QAAI;AACJ,QAAI,cAAc;AAChB,wBAAkB,UAAU,MAAM,EAAE,OAAO,UAAU,IAAI,CAAC,OAAO,SAAS,EAAE,CAAC;AAAA,IAC/E,OAAO;AACL,wBAAkB,UAAU,MAAM;AAAA,IACpC;AACA,UAAM,aAAa,qBAAqB,KAAK,WAAW,KAAK,UAAU;AACvE,UAAM,UAAU,KAAK,WAAW,OAAO,IAAI,KAAK;AAChD,UAAM,EAAE,cAAc,QAAQ,IAAI;AAAA,MAChC;AAAA,MACA;AAAA,MACA,KAAK;AAAA,MACL;AAAA,MACA;AAAA,MACA,iBAAiB,SAAS,IAAI;AAAA,MAC9B;AAAA,MACA;AAAA,MACA;AAAA,IACF;AACA,iBAAa,SAASA,OAAM;AAC5B,IAAAA,QAAO,UAAU;AACjB,UAAM,aAAa,aAAa;AAChC,IAAAA,QAAO,gBAAgB;AACvB,QAAI,QAAQ,KAAK,gBAAgB,OAAO,IAAI,KAAK;AACjD,QAAI,eAAe,MAAM,QAAQ,SAAS;AAC1C,WAAO,QAAQ,KAAK,QAAQ;AAC1B,YAAM,YAAY,CAAC;AACnB,YAAM,aAAa,aAAa,KAAK;AACrC,UAAI,YAAY;AAChB,UAAI,aAAa;AACjB,UAAI,CAAC,oBAAoB;AACvB,uBAAe,MAAM,QAAQ,SAAS;AAAA,MACxC;AACA,aAAO,qBAAqB,YAAY,KAAK,kBAAkB,MAAM;AACnE,cAAM,cAAc,MAAM,aAAa,KAAK;AAC5C,YAAI,sBAAsB,YAAY,MAAM;AAC1C,kBAAQ,KAAK,uCAAuC,KAAK,oEAAoE,mJAAmJ,KAAK,kBAAkB,KAAK,wFAAwF;AACpY;AAAA,QACF;AACA,YAAI,YAAY,SAAS,MAAM;AAC7B,gBAAM,EAAE,IAAI,GAAG,IAAI,8BAA8BA,SAAQ,YAAY,KAAK;AAC1E,gBAAM,YAAY,CAAC;AACnB,oBAAU,WAAW;AACrB,oBAAU,UAAU,GAAG,GAAG,MAAM;AAChC,gBAAM,aAAa,aAAa,YAAY,SAAS;AACrD,gBAAM,gBAAgB,CAAC;AACvB,cAAI,KAAK,eAAe,MAAM;AAC5B,kBAAM,uBAAuB,wBAAwB,KAAK,aAAaA,QAAO,WAAW;AACzF,qBAAS,KAAK,GAAG,KAAK,qBAAqB,QAAQ,EAAE,IAAI;AACvD,4BAAc,KAAK,MAAM,mBAAmB,GAAG,KAAK,MAAM,qBAAqB,GAAG,CAAC;AAAA,YACrF;AAAA,UACF;AACA,gBAAM,MAAM,GAAG,OAAO,EAAE,EAAE,OAAO,aAAa;AAC9C,gBAAM,OAAO,cAAc,GAAG;AAC9B,kBAAQ,GAAG;AACX,mBAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,kBAAM,QAAQ,UAAU;AACxB,kBAAM,MAAM,KAAK;AACjB,sBAAU,SAAS;AACnB,iBAAK,GAAG;AAAA,UACV;AACA,gBAAM,aAAa,WAAW,YAAY,SAAS;AACnD,+BAAqB,SAAS;AAC9B;AACA;AAAA,QACF;AACA,YAAI,qBAAqB,aAAa,KAAK,kBAAkB,YAAY,MAAM;AAC7E,cAAI,cAAc;AAChB,gBAAI;AACJ,gBAAI,gBAAgB,KAAK,cAAc,GAAG;AACxC,wBAAU,OAAO,MAAMA,QAAO,gBAAgB,KAAK,gBAAgB,EAAE,SAAS,KAAK,kBAAkB,CAAC,CAAC;AAAA,YACzG,OAAO;AACL,wBAAU,OAAOA,QAAO,SAAS,OAAO,OAAO;AAAA,gBAC7C,WAAW,KAAK,uBAAuB,OAAO,gCAAgC,KAAK;AAAA,gBACnF,SAAS;AAAA,cACX,CAAC,CAAC;AAAA,YACJ;AACA,qBAAS,KAAK,GAAG,KAAKA,QAAO,aAAa,QAAQ,EAAE,IAAI;AACtD,wBAAU,OAAOA,QAAO,aAAa,SAAS,QAAQ;AAAA,YACxD;AAAA,UACF;AACA;AAAA,QACF;AACA,YAAIA,QAAO,eAAe;AACxB;AAAA,QACF;AAAA,MACF;AACA,YAAM,aAAa,WAAW,OAAO,SAAS;AAC9C;AACA,UAAIA,QAAO,eAAe;AACxB;AAAA,MACF;AAAA,IACF;AACA,UAAM,aAAa,WAAW;AAC9B,UAAMA,QAAO,QAAQ,SAAS;AAC9B,WAAOA,QAAO;AAAA,EAChB,UAAE;AACA,IAAAA,QAAO,aAAa;AAAA,EACtB;AACF;AACA,SAAS,iBAAiB,SAAS,MAAM;AACvC,MAAI,gBAAgB;AACpB,MAAI,KAAK,mBAAmB,MAAM;AAChC,oBAAgB,KAAK;AAAA,EACvB,WAAW,OAAO,SAAS,QAAQ,IAAI,GAAG;AACxC,oBAAgB,QAAQ;AAAA,EAC1B;AACA,SAAO;AACT;AACA,SAAS,gBAAgB,SAAS;AAChC,SAAO,OAAO,QAAQ,aAAa;AACrC;AACA,SAAS,qBAAqB,UAAU;AACtC,SAAO,OAAO,SAAS,SAAS;AAClC;AACA,eAAe,gBAAgBA,SAAQ,SAAS,MAAM;AACpD,SAAO,QAAQ,CAAC;AAChB,QAAM,aAAa,KAAK,WAAW;AACnC,QAAM,IAAIA,QAAO;AACjB,MAAI,OAAO,CAAC;AACZ,MAAI,KAAK,UAAU,GAAG;AACpB,UAAM,IAAI,oBAAoB,sCAAsC;AAAA,EACtE;AACA,eAAa,OAAO,CAAC,cAAc,KAAK,UAAU,KAAK,OAAO,UAAU,KAAK,OAAO,GAAG,MAAM,wEAAwE,KAAK,UAAU,KAAK,OAAO,GAAG;AACnM,QAAM,eAAe,qBAAqB,OAAO,IAAI,UAAU,MAAM,QAAQ,SAAS;AACtF,MAAI,cAAc;AAClB,MAAI,QAAQ;AACZ,SAAO,aAAa,QAAQ,KAAK,UAAU,MAAM;AAC/C,UAAM,cAAc,MAAM,aAAa,KAAK;AAC5C,WAAO,KAAK,MAAM;AAChB,UAAI,YAAY,OAAO;AACrB,cAAM,EAAE,IAAI,GAAG,IAAI,8BAA8BA,SAAQ,YAAY,KAAK;AAC1E,cAAM,UAAU,GAAG,OAAO,EAAE;AAC5B,cAAM,YAAY,KAAK,MAAM,EAAE,OAAO,CAAC;AACvC,gBAAQ,OAAO;AACf,YAAI,UAAU,GAAG;AACf,mBAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,iBAAK,KAAK,OAAO,CAAC,CAAC;AAAA,UACrB;AAAA,QACF;AACA,cAAM,YAAY,QAAQ,GAAG,MAAM;AACnC,iBAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,gBAAM,WAAW,UAAU;AAC3B,gBAAM,YAAY,KAAK;AACvB,eAAK,MAAM,KAAK,MAAM,KAAK,KAAK,KAAK,IAAI,WAAW,QAAQ,CAAC,CAAC;AAC9D,cAAI,QAAQ,GAAG;AACb,oBAAQ,SAAS;AAAA,UACnB;AAAA,QACF;AACA,gBAAQ,SAAS;AACjB,uBAAe;AACf,UAAE;AAAA,MACJ;AACA,aAAO;AAAA,IACT,CAAC;AACD,QAAI,YAAY,MAAM;AACpB,UAAI,YAAY;AACd,gBAAQ,KAAK,gLAAgL,KAAK,yFAAyF;AAAA,MAC7R;AACA;AAAA,IACF;AAAA,EACF;AACA,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,YAAY,KAAK;AACvB,SAAK,MAAM,IAAI,KAAK,KAAK,WAAW;AACpC,YAAQ,SAAS;AAAA,EACnB;AACA,SAAO,iBAAiB,IAAI;AAC9B;AAGA,SAAS,eAAe,WAAW;AACjC,eAAa,OAAO,YAAY,KAAK,OAAO,UAAU,SAAS,GAAG,MAAM,2DAA2D,WAAW;AAChJ;AACA,SAAS,YAAY,QAAQ,OAAO,MAAM;AACxC,MAAI,UAAU,MAAM;AAClB,WAAO,CAAC,IAAI;AAAA,EACd,WAAW,MAAM,QAAQ,MAAM,GAAG;AAChC,WAAO,OAAO,IAAI,CAAC,WAAW,oBAAoB,QAAQ,OAAO,OAAO,KAAK,CAAC;AAAA,EAChF,OAAO;AACL,WAAO,oBAAoB,QAAQ,OAAO,OAAO,KAAK;AAAA,EACxD;AACF;AACA,SAAS,qBAAqB,QAAQ,SAAS;AAC7C,SAAO,KAAK,MAAM;AAChB,QAAI,UAAU,MAAM;AAClB,aAAO;AAAA,IACT,WAAW,MAAM,QAAQ,MAAM,GAAG;AAChC,aAAO,OAAO,IAAI,CAAC,WAAW,qBAAqB,QAAQ,OAAO,CAAC;AAAA,IACrE,OAAO;AACL,aAAO,QAAQ,QAAQ,QAAQ,UAAU,UAAU,UAAU,KAAK,SAAS,OAAO,CAAC;AAAA,IACrF;AAAA,EACF,CAAC;AACH;AACA,SAAS,YAAY7B,OAAM,WAAW;AACpC,QAAM,SAAS,CAAC;AAChB,MAAI,aAAa;AACjB,MAAI,WAAW;AACf,SAAO,aAAaA,OAAM;AACxB,eAAW,aAAa;AACxB,QAAI,YAAYA,OAAM;AACpB,iBAAWA;AAAA,IACb;AACA,WAAO,KAAK,CAAC,YAAY,QAAQ,CAAC;AAClC,iBAAa;AAAA,EACf;AACA,SAAO;AACT;AACA,eAAe,QAAQ6B,SAAQ,GAAG,KAAK,WAAW,WAAW,QAAQ,SAAS,YAAY,MAAM,QAAQ,UAAU,iBAAiB,cAAc,eAAe,iBAAiB;AAC/K,MAAI,aAAa,MAAM;AACrB,gBAAY;AAAA,EACd;AACA,MAAI,UAAU,MAAM;AAClB,aAAS;AAAA,EACX;AACA,MAAI,YAAY,MAAM;AACpB,eAAW;AAAA,EACb;AACA,MAAI,gBAAgB,MAAM;AACxB,mBAAe;AAAA,EACjB;AACA,MAAI,eAAe;AACnB,MAAI,QAAQ,QAAQ,UAAU,MAAM;AAClC,mBAAe;AAAA,EACjB;AACA,MAAI,mBAAmB,MAAM;AAC3B,mBAAe;AACf,QAAI,iBAAiB,MAAM;AACzB,YAAM,IAAI,WAAW,kGAAkG;AAAA,IACzH;AAAA,EACF;AACA,QAAM,kBAAkBA,QAAO,gBAAgB,KAAK,WAAW,eAAe,iBAAiB;AAC/F,MAAI;AACJ,MAAI,mBAAmB,MAAM;AAC3B,iBAAa,OAAO,GAAG,eAAe;AAAA,EACxC;AACA,MAAI,WAAW,MAAM;AACnB,cAAU;AAAA,EACZ;AACA,QAAM,EAAE,cAAc,QAAQ,IAAI,mBAAmB,YAAY,SAAS,QAAQ,cAAc,iBAAiB,eAAe,WAAW,cAAc,eAAe;AACxK,eAAa,SAASA,OAAM;AAC5B,EAAAA,QAAO,UAAU;AACjB,QAAM,aAAa,aAAa;AAChC,EAAAA,QAAO,gBAAgB;AACvB,WAAS,QAAQ,cAAc,QAAQ,QAAQ,EAAE,OAAO;AACtD,UAAM,aAAa,aAAa,KAAK;AACrC,UAAM,YAAY,CAAC;AACnB,QAAI,iBAAiB,MAAM;AACzB,YAAM,IAAI,oBAAoB,4CAA4C;AAAA,IAC5E,OAAO;AACL,UAAI,aAAa,SAAS;AACxB,cAAM,IAAI,oBAAoB,wCAAwC;AAAA,MACxE,WAAW,UAAU;AACnB,qBAAa,QAAQ,UAAU;AAAA,MACjC;AACA,YAAM,oBAAoB,SAAS,UAAU;AAC7C,YAAM,UAAU,YAAY,iBAAiB,SAAS;AACtD,eAAS,aAAa,GAAG,aAAa,QAAQ,QAAQ,EAAE,YAAY;AAClE,cAAM,YAAY,CAAC;AACnB,cAAM,aAAa,aAAa,YAAY,SAAS;AACrD,aAAK,MAAM;AACT,gBAAM,aAAa,QAAQ,YAAY;AACvC,gBAAM,WAAW,QAAQ,YAAY;AACrC,gBAAM,WAAW,oBAAoB,mBAAmB,YAAY,WAAW,UAAU;AACzF,oBAAU,WAAW;AACrB,oBAAU,UAAU,WAAW;AAC/B,gBAAM,WAAW,qBAAqB,KAAK,QAAQ;AACnD,gBAAM,OAAO,EAAE,QAAQ;AACvB,mBAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,kBAAM,QAAQ,UAAU;AACxB,kBAAM,MAAM,KAAK;AACjB,sBAAU,SAAS;AACnB,iBAAK,GAAG;AAAA,UACV;AACA,cAAI,eAAe,QAAQ,SAAS,GAAG;AACrC,gBAAI,cAAc;AAChB,oBAAM,UAAUA,QAAO,SAAS,MAAM,QAAQ,SAAS;AACvD,uBAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,sBAAM,QAAQ,UAAU;AACxB,sBAAM,MAAM,QAAQ;AACpB,qBAAK,GAAG;AACR,0BAAU,SAAS,SAAS;AAAA,cAC9B;AAAA,YACF;AAAA,UACF;AAAA,QACF,CAAC;AACD,cAAM,aAAa,WAAW,YAAY,SAAS;AACnD,6BAAqB,SAAS;AAC9B,YAAIA,QAAO,eAAe;AACxB;AAAA,QACF;AAAA,MACF;AACA,wBAAkB,QAAQ;AAAA,IAC5B;AACA,UAAM,aAAa,WAAW,OAAO,SAAS;AAC9C,QAAIA,QAAO,eAAe;AACxB;AAAA,IACF;AAAA,EACF;AACA,QAAM,aAAa,WAAW;AAC9B,QAAMA,QAAO,QAAQ,SAAS;AAC9B,SAAOA,QAAO;AAChB;AACA,eAAe,WAAWA,SAAQ,GAAG,GAAG,OAAO,CAAC,GAAG;AACjD,MAAIA,QAAO,YAAY;AACrB,UAAM,IAAI,MAAM,8DAA8D;AAAA,EAChF;AACA,EAAAA,QAAO,aAAa;AACpB,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACF,UAAM,YAAY,KAAK,aAAa,OAAO,KAAK,KAAK;AACrD,mBAAe,SAAS;AACxB,UAAM,iBAAiB;AACvB,UAAM,mBAAmB,MAAMA,QAAO,oBAAoB,GAAG,GAAG,KAAK,cAAc,KAAK,aAAa,gBAAgB,SAAS;AAC9H,aAAS,iBAAiB;AAC1B,cAAU,iBAAiB;AAC3B,oBAAgB,iBAAiB;AACjC,QAAI,eAAe;AACnB,QAAI;AACJ,QAAI,KAAK,kBAAkB,QAAQ,KAAK,eAAe,SAAS,GAAG;AACjE,qBAAe;AACf,UAAI,KAAK,eAAe,WAAW,GAAG;AACpC,oBAAY,KAAK,eAAe;AAChC,oBAAY,KAAK,eAAe;AAAA,MAClC,WAAW,KAAK,eAAe,WAAW,GAAG;AAC3C,cAAM,IAAI,oBAAoB,+DAA+D;AAAA,MAC/F,OAAO;AACL,cAAM,IAAI,WAAW,0GAA0G,KAAK,4BAA4B;AAAA,MAClK;AACA,YAAM,kBAAkB;AACxB,YAAM,kBAAkB,MAAMA,QAAO,oBAAoB,WAAW,WAAW,MAAM,MAAM,iBAAiB,SAAS;AACrH,aAAO,gBAAgB;AACvB,aAAO,gBAAgB;AACvB,eAAS,KAAK,OAAO,IAAI;AAAA,IAC3B,WAAW,KAAK,mBAAmB,QAAQ,KAAK,kBAAkB,KAAK,KAAK,kBAAkB,GAAG;AAC/F,qBAAe;AACf,YAAM,UAAU,KAAK,MAAM,OAAO,GAAG,MAAM,MAAM,IAAI,KAAK,gBAAgB;AAC1E,YAAM,oBAAoB,OAAO,GAAG,MAAM;AAC1C,aAAO,YAAY,QAAQ,SAAS,iBAAiB;AACrD,uBAAiB;AACjB,eAAS,YAAY,QAAQ,GAAG,OAAO;AACvC,aAAO,YAAY,SAAS,SAAS,iBAAiB;AACtD,wBAAkB;AAClB,gBAAU,YAAY,SAAS,GAAG,OAAO;AACzC,eAAS,KAAK,OAAO,IAAI;AAAA,IAC3B,WAAW,KAAK,mBAAmB,MAAM;AACvC,qBAAe;AAAA,IACjB;AACA,UAAM,MAAM,OAAO,OAAO,OAAO,EAAE,OAAO,aAAa;AACvD,IAAAA,QAAO,iCAAiC;AACxC,UAAM,gBAAgBA,QAAO,kBAAkB;AAC/C,UAAM,YAAYA,QAAO,uBAAuB;AAChD,QAAI;AACJ,QAAI;AACJ,QAAI,cAAc;AAChB,MAAAA,QAAO,iBAAiB;AACxB,oBAAcA,QAAO;AACrB,wBAAkB,UAAU,MAAM,EAAE,OAAO,UAAU,IAAI,CAAC,OAAO,SAAS,EAAE,CAAC;AAAA,IAC/E,OAAO;AACL,oBAAc;AACd,eAAS,CAAC;AACV,wBAAkB,UAAU,MAAM;AAAA,IACpC;AACA,UAAM,aAAa,qBAAqB,KAAK,WAAW,KAAK,UAAU;AACvE,UAAM,MAAM,MAAM,QAAQA,SAAQ,eAAe,KAAK,WAAW,WAAW,KAAK,QAAQ,KAAK,SAAS,YAAY,aAAa,QAAQ,KAAK,SAAS,iBAAiB,KAAK,cAAc,MAAM,IAAI;AACpM,WAAO;AAAA,EACT,UAAE;AACA,IAAAA,QAAO,aAAa;AACpB,sBAAkB,QAAQ,CAAC;AAC3B,sBAAkB,SAAS,CAAC;AAC5B,sBAAkB,gBAAgB,CAAC;AACnC,sBAAkB,iBAAiB,CAAC;AACpC,sBAAkB,MAAM,SAAS;AACjC,sBAAkB,MAAM,SAAS;AACjC,QAAI,iBAAiB,MAAM;AACzB,cAAQ,aAAa;AAAA,IACvB;AAAA,EACF;AACF;AACA,SAAS,2BAA2B,SAAS;AAC3C,QAAM,OAAO,CAAC;AACd,MAAI,mBAAmB,QAAQ;AAC7B,cAAU,CAAC,OAAO;AAAA,EACpB;AACA,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC1C,UAAM,UAAU,QAAQ;AACxB,QAAI,QAAQ,SAAS,GAAG;AACtB,WAAK,KAAK,YAAY,SAAS,CAAC,CAAC;AAAA,IACnC,WAAW,QAAQ,SAAS,GAAG;AAC7B,YAAM,IAAI,MAAM,uEAAuE;AAAA,IACzF,OAAO;AACL,WAAK,KAAK,OAAO;AAAA,IACnB;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,SAAS,YAAY;AAC9C,MAAI,WAAW,MAAM;AACnB;AAAA,EACF;AACA,QAAM,eAAe,CAAC;AACtB,MAAI,sBAAsB,QAAQ;AAChC,iBAAa,KAAK,WAAW,EAAE;AAAA,EACjC,WAAW,MAAM,QAAQ,UAAU,GAAG;AACpC,eAAW,QAAQ,CAAC,OAAO,aAAa,KAAK,GAAG,EAAE,CAAC;AAAA,EACrD,WAAW,cAAc,MAAM;AAC7B,eAAW,QAAQ,YAAY;AAC7B,YAAM,YAAY,WAAW;AAC7B,mBAAa,KAAK,UAAU,EAAE;AAAA,IAChC;AAAA,EACF;AACA,QAAM,mBAAmB,CAAC;AAC1B,MAAI,mBAAmB,QAAQ;AAC7B,QAAI,aAAa,QAAQ,QAAQ,EAAE,MAAM,IAAI;AAC3C,uBAAiB,KAAK,OAAO;AAAA,IAC/B;AAAA,EACF,WAAW,MAAM,QAAQ,OAAO,GAAG;AACjC,YAAQ,QAAQ,CAAC,OAAO;AACtB,UAAI,aAAa,QAAQ,GAAG,EAAE,MAAM,IAAI;AACtC,yBAAiB,KAAK,EAAE;AAAA,MAC1B;AAAA,IACF,CAAC;AAAA,EACH,WAAW,WAAW,MAAM;AAC1B,eAAW,QAAQ,SAAS;AAC1B,YAAM,UAAU,QAAQ;AACxB,UAAI,aAAa,QAAQ,QAAQ,EAAE,MAAM,IAAI;AAC3C,yBAAiB,KAAK,OAAO;AAAA,MAC/B;AAAA,IACF;AAAA,EACF;AACA,mBAAiB,QAAQ,CAAC,OAAO;AAC/B,QAAI,CAAC,GAAG,YAAY;AAClB,SAAG,QAAQ;AAAA,IACb;AAAA,EACF,CAAC;AACH;AAGA,SAAS,aAAa,GAAG;AACvB,SAAO,aAAa;AACtB;AACA,SAAS,YAAY,GAAG;AACtB,SAAO,MAAM,QAAQ,CAAC;AACxB;AACA,SAAS,WAAW,GAAG;AACrB,SAAO,CAAC,aAAa,CAAC,KAAK,CAAC,YAAY,CAAC;AAC3C;AACA,SAAS,qBAAqB,MAAM,OAAO,QAAQ,iBAAiB,MAAM,kBAAkB,IAAI;AAC9F,MAAI,SAAS,QAAQ,MAAM,WAAW,GAAG;AACvC,QAAI,QAAQ,MAAM;AAChB,UAAI,oBAAoB;AACxB,UAAI,YAAY,IAAI,KAAK,KAAK,SAAS,GAAG;AACxC,4BAAoB;AAAA,MACtB,WAAW,WAAW,IAAI,GAAG;AAC3B,mBAAW,OAAO,MAAM;AACtB,cAAI,KAAK,eAAe,GAAG,GAAG;AAC5B,gCAAoB;AACpB;AAAA,UACF;AAAA,QACF;AAAA,MACF,OAAO;AACL,4BAAoB;AAAA,MACtB;AACA,UAAI,mBAAmB;AACrB,cAAM,IAAI,WAAW,6BAA6B,6CAA6C,MAAM;AAAA,MACvG;AAAA,IACF;AACA,WAAO,CAAC;AAAA,EACV;AACA,MAAI,QAAQ,MAAM;AAChB,WAAO,MAAM,IAAI,CAAC,SAAS,IAAI;AAAA,EACjC;AACA,MAAI;AACJ,MAAI,WAAW,IAAI,GAAG;AACpB,WAAO;AACP,aAAS,CAAC;AACV,eAAW,QAAQ,OAAO;AACxB,UAAI,KAAK,SAAS,MAAM;AACtB,cAAM,IAAI,WAAW,yBAAyB,qCAAqC,OAAO;AAAA,MAC5F;AACA,aAAO,KAAK,KAAK,KAAK;AAAA,IACxB;AAAA,EACF,WAAW,YAAY,IAAI,GAAG;AAC5B,WAAO;AACP,QAAI,KAAK,WAAW,MAAM,QAAQ;AAChC,YAAM,IAAI,WAAW,6BAA6B,gIAAgI,MAAM,sEAAsE,MAAM;AAAA,IACtQ;AACA,aAAS;AAAA,EACX,OAAO;AACL,WAAO;AACP,QAAI,MAAM,SAAS,GAAG;AACpB,YAAM,IAAI,WAAW,aAAa,2BAA2B,MAAM,4EAA4E,KAAK,OAAO;AAAA,IAC7J;AACA,aAAS,CAAC,IAAI;AAAA,EAChB;AACA,WAAS,2BAA2B,MAAM;AAC1C,MAAI,UAAU,MAAM;AAClB,aAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,UAAI,OAAO,OAAO,MAAM;AACtB;AAAA,MACF;AACA,YAAM,SAAS,OAAO;AACtB,UAAI,OAAO,MAAM,WAAW,OAAO,IAAI,QAAQ;AAC7C,cAAM,IAAI,WAAW,uBAAuB,6BAA6B,MAAM,eAAe,OAAO,IAAI,iDAAiD,OAAO,OAAO;AAAA,MAC1K;AACA,eAAS,IAAI,GAAG,IAAI,OAAO,IAAI,QAAQ,EAAE,GAAG;AAC1C,YAAI,MAAM,KAAK,CAAC,gBAAgB;AAC9B;AAAA,QACF;AACA,cAAM,MAAM,OAAO,MAAM;AACzB,cAAM,SAAS,OAAO,IAAI;AAC1B,YAAI,UAAU,QAAQ,UAAU,KAAK,QAAQ,QAAQ;AACnD,gBAAM,IAAI,WAAW,GAAG,8EAA8E,OAAO,IAAI,MAAM,GAAG,OAAO,IAAI,MAAM,4BAA4B,OAAO,IAAI,MAAM,GAAG,OAAO,IAAI,MAAM,eAAe,0CAA0C,OAAO,MAAM,iCAAiC,OAAO,MAAM,MAAM,GAAG,OAAO,MAAM,MAAM,qBAAqB,OAAO,SAAS;AAAA,QACnY;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,QAAQ,SAAS,SAAS;AACnD,QAAM,OAAO,QAAQ,OAAO,IAAI,CAAC,WAAW,OAAO,MAAM,EAAE,CAAC;AAC5D,OAAK,KAAK;AACV,QAAM,OAAO,QAAQ,QAAQ,IAAI,CAAC,WAAW,OAAO,MAAM,EAAE,CAAC;AAC7D,OAAK,KAAK;AACV,MAAI,KAAK,SAAS,GAAG;AACnB,UAAM,IAAI,WAAW,mFAAmF,KAAK,UAAU,OAAO,IAAI,CAAC,WAAW,OAAO,KAAK,CAAC,GAAG;AAAA,EAChK;AACA,MAAI,KAAK,SAAS,GAAG;AACnB,UAAM,IAAI,WAAW,oFAAoF,KAAK,UAAU,QAAQ,IAAI,CAAC,WAAW,OAAO,KAAK,CAAC,GAAG;AAAA,EAClK;AACA,MAAI,KAAK,SAAS,KAAK,KAAK,SAAS,KAAK,CAAC,aAAa,YAAY,MAAM,IAAI,GAAG;AAC/E,UAAM,IAAI,WAAW,iFAAiF,KAAK,0BAA0B,KAAK,sBAAsB;AAAA,EAClK;AACF;AACA,SAAS,gCAAgC,SAAS,SAAS,cAAc;AACvE,QAAM,YAAY;AAAA,IAChB;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACA,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC1C,UAAM,IAAI,QAAQ;AAClB,UAAM,OAAO,QAAQ;AACrB,UAAM,QAAQ,aAAa;AAC3B,QAAI,QAAQ,MAAM;AAChB;AAAA,IACF;AACA,QAAI,SAAS,yBAAyB;AACpC,UAAI,EAAE,MAAM,EAAE,MAAM,SAAS,OAAO,GAAG;AACrC,cAAM,IAAI,WAAW,2CAA2C,EAAE,+JAA+J;AAAA,MACnO;AAAA,IACF;AACA,QAAI,UAAU,QAAQ,IAAI,MAAM,IAAI;AAClC,YAAM,eAAe,EAAE,MAAM,MAAM,CAAC;AACpC,YAAM,cAAc,MAAM,MAAM,CAAC;AACjC,eAAS,IAAI,GAAG,IAAI,aAAa,QAAQ,EAAE,GAAG;AAC5C,cAAM,YAAY,aAAa;AAC/B,cAAM,SAAS,YAAY;AAC3B,YAAI,UAAU,QAAQ,cAAc,QAAQ;AAC1C,gBAAM,IAAI,WAAW,8BAA8B,EAAE,2CAA2C,+FAA+F;AAAA,QACjM;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,eAAe,MAAM,OAAO,QAAQ,iBAAiB,MAAM,kBAAkB,IAAI;AACxF,MAAI;AACJ,MAAI,MAAM,QAAQ,IAAI,GAAG;AACvB,QAAI,KAAK,WAAW,MAAM,QAAQ;AAChC,YAAM,IAAI,WAAW,6BAA6B,oIAAoI,MAAM,qCAAqC,KAAK,oBAAoB;AAAA,IAC5P;AACA,aAAS;AAAA,EACX,OAAO;AACL,QAAI,MAAM,SAAS,GAAG;AACpB,YAAM,IAAI,WAAW,qBAAqB,MAAM,UAAU,kFAAkF,KAAK,UAAU,KAAK,KAAK,IAAI;AAAA,IAC3K;AACA,aAAS,CAAC,IAAI;AAAA,EAChB;AACA,MAAI,UAAU,MAAM;AAClB,aAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,UAAI,OAAO,OAAO,MAAM;AACtB;AAAA,MACF;AACA,YAAM,SAAS,OAAO;AACtB,UAAI,OAAO,MAAM,WAAW,OAAO,IAAI,QAAQ;AAC7C,cAAM,IAAI,WAAW,uBAAuB,6BAA6B,MAAM,eAAe,OAAO,IAAI,iDAAiD,KAAK,UAAU,OAAO,KAAK,GAAG;AAAA,MAC1L;AACA,eAAS,IAAI,GAAG,IAAI,OAAO,IAAI,QAAQ,EAAE,GAAG;AAC1C,YAAI,MAAM,KAAK,CAAC,gBAAgB;AAC9B;AAAA,QACF;AACA,cAAM,MAAM,OAAO,MAAM;AACzB,cAAM,SAAS,OAAO,IAAI;AAC1B,YAAI,UAAU,MAAM;AAClB,cAAI,WAAW,KAAK;AAClB,kBAAM,IAAI,WAAW,uBAAuB,6BAA6B,MAAM,qBAAqB,KAAK,UAAU,OAAO,GAAG,8BAA8B,KAAK,UAAU,OAAO,KAAK,IAAI;AAAA,UAC5L;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,eAAe,SAAS,aAAa;AAC5C,MAAI,WAAW,QAAQ,MAAM,QAAQ,OAAO,KAAK,QAAQ,WAAW,GAAG;AACrE,WAAO,YAAY,IAAI,CAAC,SAAS,CAAC,CAAC;AAAA,EACrC;AACA,MAAI;AACJ,MAAI,OAAO,YAAY,YAAY,OAAO,YAAY,YAAY;AAChE,qBAAiB,CAAC,OAAO;AAAA,EAC3B,WAAW,MAAM,QAAQ,OAAO,KAAK,OAAO,YAAY,UAAU;AAChE,qBAAiB;AAAA,EACnB,OAAO;AACL,UAAM,IAAI,UAAU,kGAAkG,SAAS;AAAA,EACjI;AACA,MAAI,MAAM,QAAQ,cAAc,GAAG;AACjC,WAAO,YAAY,IAAI,CAAC,SAAS,cAAc;AAAA,EACjD,OAAO;AACL,UAAM,gBAAgB,CAAC;AACvB,eAAW,QAAQ,aAAa;AAC9B,UAAI,gBAAgB,eAAe,eAAe,IAAI,IAAI,eAAe,QAAQ,CAAC;AAClF,UAAI,CAAC,MAAM,QAAQ,aAAa,GAAG;AACjC,wBAAgB,CAAC,aAAa;AAAA,MAChC;AACA,oBAAc,KAAK,aAAa;AAAA,IAClC;AACA,WAAO;AAAA,EACT;AACF;AACA,IAAI,2BAA2B;AAC/B,IAAI,cAAc,cAAc,UAAU;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,aAAa;AAAA,EACpB;AAAA,EACA,QAAQ,YAAY,WAAW,UAAU,QAAQ,KAAK;AACpD,QAAI,CAAC,KAAK,OAAO;AACf,YAAM,IAAI,WAAW,8KAA8K;AAAA,IACrM;AACA,iBAAa,MAAM,YAAY,WAAW,OAAO;AAAA,EACnD;AAAA,EACA,QAAQ,MAAM;AACZ,QAAI,KAAK,QAAQ,MAAM;AACrB,WAAK,OAAO,CAAC;AAAA,IACf;AACA,SAAK,OAAO,KAAK;AACjB,QAAI,OAAO,KAAK,cAAc,UAAU;AACtC,WAAK,aAAa,aAAa,KAAK,SAAS;AAC7C,WAAK,mBAAmB;AAAA,IAC1B,OAAO;AACL,UAAI,EAAE,KAAK,qBAAqB,YAAY;AAC1C,cAAM,IAAI,WAAW,6DAA6D;AAAA,MACpF;AACA,WAAK,aAAa,KAAK;AACvB,WAAK,mBAAmB;AAAA,IAC1B;AACA,QAAI,gBAAgB,CAAC;AACrB,QAAI,CAAC,MAAM,QAAQ,KAAK,IAAI,KAAK,OAAO,KAAK,SAAS,YAAY,OAAO,KAAK,SAAS,YAAY;AACjG,WAAK,OAAO,KAAK;AACjB,iBAAW,QAAQ,KAAK,MAAM;AAC5B,YAAI,KAAK,YAAY,QAAQ,IAAI,MAAM,IAAI;AACzC,gBAAM,IAAI,WAAW,sCAAsC,4CAA4C,KAAK,aAAa;AAAA,QAC3H;AAAA,MACF;AACA,iBAAW,QAAQ,KAAK,aAAa;AACnC,YAAI,KAAK,KAAK,SAAS,MAAM;AAC3B,kBAAQ,KAAK,WAAW,gIAAgI,sBAAsB;AAAA,QAChL;AACA,sBAAc,KAAK,IAAI,KAAK,KAAK,KAAK,CAAC;AAAA,MACzC;AAAA,IACF,WAAW,MAAM,QAAQ,KAAK,IAAI,GAAG;AACnC,UAAI,KAAK,KAAK,WAAW,KAAK,QAAQ,QAAQ;AAC5C,cAAM,IAAI,WAAW,2FAA2F,KAAK,QAAQ,yCAAyC,KAAK,OAAO;AAAA,MACpL;AACA,YAAM,YAAY,KAAK;AACvB,sBAAgB,UAAU,IAAI,CAAC,OAAO,IAAI,EAAE,CAAC;AAAA,IAC/C,OAAO;AACL,YAAM,eAAe,IAAI,KAAK,IAAI;AAClC,WAAK,QAAQ,QAAQ,CAAC,MAAM;AAC1B,sBAAc,KAAK,YAAY;AAAA,MACjC,CAAC;AAAA,IACH;AACA,SAAK,gBAAgB;AACrB,SAAK,kBAAkB,CAAC;AACxB,SAAK,mBAAmB,CAAC;AACzB,SAAK,cAAc,CAAC;AACpB,aAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC/C,YAAM,QAAQ,KAAK,qBAAqB;AACxC,YAAM,OAAO,KAAK,YAAY;AAC9B,WAAK,gBAAgB,KAAK,IAAI;AAC9B,WAAK,iBAAiB,KAAK,KAAK;AAChC,WAAK,YAAY,KAAK,KAAK,cAAc,GAAG;AAAA,IAC9C;AACA,UAAM,oBAAoB,CAAC;AAC3B,SAAK,UAAU,KAAK;AACpB,SAAK,eAAe,CAAC,MAAM;AAC3B,SAAK,iBAAiB,CAAC;AACvB,cAAU,QAAQ,MAAM;AACtB,eAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC/C,YAAI,kBAAkB,QAAQ,EAAE,MAAM,IAAI;AACxC;AAAA,QACF;AACA,cAAM,eAAe,KAAK,cAAc;AACxC,YAAI,KAAK,QAAQ,SAAS,GAAG;AAC3B,eAAK,eAAe,KAAK,CAAC,cAAc,EAAE,CAAC;AAC3C,eAAK,aAAa,KAAK,KAAK,YAAY,MAAM,OAAO;AAAA,QACvD;AAAA,MACF;AAAA,IACF,CAAC;AACD,UAAM,gBAAgB,eAAe,KAAK,SAAS,KAAK,WAAW;AACnE,UAAM,eAAe,CAAC,aAAa,YAAY,iBAAiB;AAC9D,UAAI,KAAK,YAAY,SAAS,GAAG;AAC/B,qBAAa,KAAK,YAAY,eAAe,MAAM;AAAA,MACrD;AACA,WAAK,aAAa,KAAK,UAAU;AACjC,WAAK,eAAe,KAAK,CAAC,cAAc,WAAW,CAAC;AAAA,IACtD;AACA,cAAU,UAAU,MAAM;AACxB,eAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC/C,YAAI,kBAAkB,QAAQ,EAAE,MAAM,IAAI;AACxC;AAAA,QACF;AACA,cAAM,gBAAgB,cAAc;AACpC,cAAM,gBAAgB,CAAC,YAAY;AACjC,gBAAM,mBAAmB;AACzB,cAAI;AACJ,cAAI;AACJ,cAAI;AACJ,qBAAW,UAAU,SAAS;AAC5B,gBAAI,OAAO,WAAW,YAAY,CAAC,YAAY,OAAO,gBAAgB,IAAI,EAAE,QAAQ,MAAM,MAAM,IAAI;AAClG,oBAAM,cAAc,KAAK,qBAAqB;AAC9C,kBAAI,YAAY,YAAY,SAAS,OAAO,KAAK,KAAK,cAAc,QAAQ,oBAAoB;AAC9F,oBAAI,CAAC,YAAY,KAAK,EAAE,QAAQ,MAAM,MAAM,IAAI;AAC9C,0BAAQ;AAAA,gBACV,WAAW,CAAC,gBAAgB,IAAI,EAAE,QAAQ,MAAM,MAAM,IAAI;AACxD,0BAAQ;AAAA,gBACV;AAAA,cACF,WAAW,KAAK,cAAc,QAAQ,+BAA+B;AACnE,oBAAI,CAAC,YAAY,KAAK,EAAE,QAAQ,MAAM,MAAM,IAAI;AAC9C,0BAAQ;AAAA,gBACV,WAAW,CAAC,gBAAgB,IAAI,EAAE,QAAQ,MAAM,MAAM,IAAI;AACxD,0BAAQ;AAAA,gBACV;AAAA,cACF,OAAO;AACL,oBAAI,CAAC,YAAY,KAAK,EAAE,QAAQ,MAAM,MAAM,IAAI;AAC9C,0BAAQ;AAAA,gBACV,WAAW,CAAC,gBAAgB,IAAI,EAAE,QAAQ,MAAM,MAAM,IAAI;AACxD,0BAAQ;AAAA,gBACV;AAAA,cACF;AACA,kBAAI;AACJ,kBAAI,CAAC,YAAY,KAAK,EAAE,QAAQ,MAAM,MAAM,IAAI;AAC9C,yBAAS;AAAA,cACX,WAAW,CAAC,gBAAgB,IAAI,EAAE,QAAQ,MAAM,MAAM,IAAI;AACxD,yBAAS;AAAA,cACX;AACA,iCAAmB;AACnB,2BAAa,mBAAmB;AAAA,YAClC,OAAO;AACL,oBAAM,WAAW,KAAK,MAAM;AAC5B,iCAAmB;AACnB,2BAAa,mBAAmB,oBAAoB,MAAM;AAAA,YAC5D;AACA,gBAAI;AACJ,sBAAU,YAAY,MAAM;AAC1B,6BAAe;AAAA,YACjB,CAAC;AACD,yBAAa,IAAI,YAAY,YAAY;AAAA,UAC3C;AAAA,QACF;AACA,sBAAc,aAAa;AAAA,MAC7B;AAAA,IACF,CAAC;AACD,SAAK,4BAA4B,KAAK;AAAA,EACxC;AAAA,EACA,mCAAmC;AACjC,QAAI,KAAK,6BAA6B,MAAM;AAC1C;AAAA,IACF;AACA,QAAI,KAAK,iBAAiB,WAAW,KAAK,0BAA0B,QAAQ;AAC1E,cAAQ,KAAK,mJAAmJ;AAAA,IAClK;AAAA,EACF;AAAA,EACA,SAAS,GAAG,GAAG,OAAO,CAAC,GAAG;AACxB,UAAM,YAAY,KAAK,aAAa,OAAO,KAAK,KAAK;AACrD,mBAAe,SAAS;AACxB,UAAM,iBAAiB;AACvB,UAAM,mBAAmB,KAAK,sBAAsB,GAAG,GAAG,gBAAgB,SAAS;AACnF,QAAI;AACF,YAAM,MAAM,iBAAiB,GAAG,OAAO,iBAAiB,EAAE;AAC1D,WAAK,iBAAiB;AACtB,YAAM,IAAI,KAAK;AACf,YAAM,WAAW,KAAK,SAAS,GAAG,KAAK,WAAW,KAAK,SAAS,KAAK,KAAK;AAC1E,aAAO,iBAAiB,QAAQ;AAAA,IAClC,UAAE;AACA,wBAAkB,iBAAiB,IAAI,CAAC;AACxC,wBAAkB,iBAAiB,IAAI,CAAC;AAAA,IAC1C;AAAA,EACF;AAAA,EACA,MAAM,gBAAgB,SAAS,MAAM;AACnC,SAAK,iBAAiB;AACtB,WAAO,gBAAgB,MAAM,SAAS,IAAI;AAAA,EAC5C;AAAA,EACA,gBAAgB,KAAK,WAAW,OAAO,YAAY,SAAS;AAC1D,QAAI;AACJ,QAAI,SAAS,MAAM;AACjB,mBAAa;AACb,UAAI,aAAa,MAAM;AACrB,cAAM,IAAI,WAAW,MAAM,yEAAyE,WAAW;AAAA,MACjH;AAAA,IACF,WAAW,OAAO,MAAM;AACtB,UAAI,MAAM,QAAQ,GAAG,GAAG;AACtB,qBAAa,IAAI,GAAG,MAAM;AAAA,MAC5B,OAAO;AACL,qBAAa,IAAI,MAAM;AAAA,MACzB;AAAA,IACF,OAAO;AACL,YAAM,IAAI,WAAW,yDAAyD,+BAA+B;AAAA,IAC/G;AACA,WAAO;AAAA,EACT;AAAA,EACA,QAAQ,QAAQ,SAAS;AACvB,QAAI,MAAM,QAAQ,OAAO,KAAK,QAAQ,WAAW,GAAG;AAClD,YAAM,IAAI,WAAW,oDAAoD;AAAA,IAC3E;AACA,UAAM,iBAAiB,MAAM,QAAQ,OAAO;AAC5C,UAAM,cAAc,iBAAiB,UAAU,CAAC,OAAO;AACvD,UAAM,wBAAwB,KAAK,wBAAwB,WAAW;AACtE,UAAM,WAAW,IAAI,SAAS;AAC9B,QAAI,kBAAkB,QAAQ;AAC5B,eAAS,CAAC,MAAM;AAAA,IAClB;AACA,QAAI,MAAM,QAAQ,MAAM,GAAG;AACzB,UAAI,OAAO,WAAW,KAAK,OAAO,QAAQ;AACxC,cAAM,IAAI,WAAW,kCAAkC,OAAO,8DAA8D,KAAK,OAAO,UAAU;AAAA,MACpJ;AACA,eAAS,KAAK,GAAG,KAAK,KAAK,OAAO,QAAQ,EAAE,IAAI;AAC9C,iBAAS,IAAI,KAAK,OAAO,KAAK,OAAO,GAAG;AAAA,MAC1C;AAAA,IACF,OAAO;AACL,iBAAW,UAAU,KAAK,QAAQ;AAChC,cAAM,cAAc,OAAO,OAAO;AAClC,YAAI,eAAe,MAAM;AACvB,gBAAM,IAAI,WAAW,8CAA8C,OAAO,MAAM;AAAA,QAClF;AACA,iBAAS,IAAI,QAAQ,WAAW;AAAA,MAClC;AAAA,IACF;AACA,UAAM,iBAAiB,QAAQ,uBAAuB,QAAQ;AAC9D,WAAO,iBAAiB,iBAAiB,eAAe;AAAA,EAC1D;AAAA,EACA,wBAAwB,qBAAqB;AAC3C,UAAM,wBAAwB,aAAa,MAAM,oBAAoB,MAAM;AAC3E,QAAI,mBAAmB,oBAAoB;AAC3C,eAAW,SAAS,KAAK,QAAQ;AAC/B,YAAM,eAAe,MAAM,QAAQ,MAAM,MAAM,IAAI,MAAM,SAAS,CAAC,MAAM,MAAM;AAC/E,YAAM,mBAAmB,aAAa,IAAI,CAAC,WAAW,OAAO,IAAI;AACjE,eAAS,KAAK,GAAG,KAAK,oBAAoB,QAAQ,EAAE,IAAI;AACtD,cAAMpB,SAAQ,iBAAiB,QAAQ,oBAAoB,GAAG;AAC9D,YAAIA,WAAU,IAAI;AAChB,gCAAsB,MAAM,aAAaA;AACzC;AAAA,QACF;AACA,YAAI,qBAAqB,GAAG;AAC1B;AAAA,QACF;AAAA,MACF;AACA,UAAI,qBAAqB,GAAG;AAC1B;AAAA,MACF;AAAA,IACF;AACA,QAAI,mBAAmB,GAAG;AACxB,YAAM,iBAAiB,CAAC;AACxB,4BAAsB,QAAQ,CAAC,SAAS,OAAO;AAC7C,YAAI,WAAW,MAAM;AACnB,yBAAe,KAAK,oBAAoB,GAAG;AAAA,QAC7C;AAAA,MACF,CAAC;AACD,YAAM,IAAI,WAAW,mDAAmD,KAAK,UAAU,cAAc,GAAG;AAAA,IAC1G;AACA,WAAO;AAAA,EACT;AAAA,EACA,YAAY,KAAK,YAAY,IAAI,UAAU,OAAO;AAChD,WAAO,KAAK,MAAM;AAChB,YAAM,aAAa,KAAK,gBAAgB,GAAG;AAC3C,UAAI,SAAS;AACX,cAAM,IAAI,oBAAoB,+CAA+C;AAAA,MAC/E;AACA,YAAM,UAAU,YAAY,YAAY,SAAS;AACjD,YAAM,cAAc,KAAK,QAAQ,IAAI,CAAC,WAAW,CAAC,CAAC;AACnD,eAAS,aAAa,GAAG,aAAa,QAAQ,QAAQ,EAAE,YAAY;AAClE,cAAM,YAAY,KAAK,MAAM;AAC3B,gBAAM,aAAa,QAAQ,YAAY;AACvC,gBAAM,WAAW,QAAQ,YAAY;AACrC,gBAAM,WAAW,YAAY,KAAK,YAAY,QAAQ;AACtD,gBAAM,QAAQ,CAAC;AACf,cAAI,MAAM,QAAQ,QAAQ,GAAG;AAC3B,qBAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,EAAE,IAAI;AAC3C,oBAAM,KAAK,EAAE,KAAK,KAAK,OAAO,KAAK,OAAO,SAAS,IAAI,CAAC;AAAA,YAC1D;AAAA,UACF,OAAO;AACL,kBAAM,KAAK,EAAE,KAAK,KAAK,OAAO,IAAI,OAAO,SAAS,CAAC;AAAA,UACrD;AACA,gBAAM,WAAW,IAAI,SAAS,KAAK;AACnC,iBAAO,QAAQ,KAAK,SAAS,QAAQ;AAAA,QACvC,CAAC;AACD,kBAAU,QAAQ,CAAC,UAAU,OAAO,YAAY,IAAI,KAAK,QAAQ,CAAC;AAAA,MACpE;AACA,aAAO,iBAAiB,YAAY,IAAI,CAAC,aAAa,OAAO,UAAU,CAAC,CAAC,CAAC;AAAA,IAC5E,CAAC;AAAA,EACH;AAAA,EACA,QAAQ,GAAG,OAAO,CAAC,GAAG;AACpB,UAAM,kBAAkB,2BAA2B,CAAC;AACpD,mBAAe,iBAAiB,KAAK,YAAY,KAAK,iBAAiB,KAAK;AAC5E,QAAI;AACF,YAAM,YAAY,KAAK,aAAa,OAAO,KAAK,KAAK;AACrD,qBAAe,SAAS;AACxB,aAAO,KAAK,YAAY,iBAAiB,SAAS;AAAA,IACpD,UAAE;AACA,wBAAkB,iBAAiB,CAAC;AAAA,IACtC;AAAA,EACF;AAAA,EACA,eAAe,GAAG;AAChB,mBAAe,GAAG,KAAK,YAAY,KAAK,iBAAiB,IAAI;AAC7D,UAAM,aAAa,MAAM,QAAQ,CAAC,IAAI,EAAE,KAAK,GAAG,MAAM;AACtD,WAAO,KAAK,YAAY,GAAG,SAAS;AAAA,EACtC;AAAA,EACA,sBAAsB,GAAG,GAAG,iBAAiB,MAAM,WAAW;AAC5D,QAAI,KAAK,cAAc,MAAM;AAC3B,YAAM,IAAI,aAAa,8FAA8F;AAAA,IACvH;AACA,UAAM,eAAe,CAAC;AACtB,aAAS,KAAK,GAAG,KAAK,KAAK,iBAAiB,QAAQ,EAAE,IAAI;AACxD,YAAM,cAAc,KAAK,iBAAiB;AAC1C,YAAM,SAAS,KAAK,YAAY;AAChC,UAAI,WAAW,+BAA+B;AAC5C,qBAAa,KAAK,YAAY,MAAM,GAAG,YAAY,SAAS,CAAC,EAAE,OAAO,CAAC,CAAC,CAAC,CAAC;AAAA,MAC5E,OAAO;AACL,qBAAa,KAAK,WAAW;AAAA,MAC/B;AAAA,IACF;AACA,QAAI,qBAAqB,GAAG,KAAK,gBAAgB,KAAK,iBAAiB,OAAO,OAAO;AACrF,QAAI,qBAAqB,GAAG,KAAK,iBAAiB,cAAc,OAAO,QAAQ;AAC/E,sBAAkB,GAAG,GAAG,IAAI;AAC5B,oCAAgC,GAAG,KAAK,aAAa,KAAK,gBAAgB;AAC1E,QAAI,KAAK,YAAY,aAAa,QAAQ,YAAY,GAAG;AACvD,UAAI,EAAE,GAAG,MAAM,KAAK,cAAc,GAAG;AACnC,cAAM,IAAI,WAAW,mHAAmH,qBAAqB,EAAE,GAAG,MAAM,eAAe;AAAA,MACzL;AAAA,IACF;AACA,WAAO,CAAC,GAAG,CAAC;AAAA,EACd;AAAA,EACA,MAAM,oBAAoB,GAAG,GAAG,cAAc,aAAa,iBAAiB,MAAM,WAAW;AAC3F,UAAM,CAAC,YAAY,UAAU,IAAI,KAAK,sBAAsB,GAAG,GAAG,gBAAgB,SAAS;AAC3F,QAAI,gBAAgB,MAAM;AACxB,YAAM,IAAI,MAAM,qCAAqC;AAAA,IACvD;AACA,QAAI,wBAAwB;AAC5B,QAAI,eAAe,MAAM;AACvB,YAAM,eAAe,wBAAwB,aAAa,KAAK,WAAW;AAC1E,8BAAwB,CAAC;AACzB,eAAS,KAAK,GAAG,KAAK,aAAa,QAAQ,EAAE,IAAI;AAC/C,8BAAsB,KAAK,MAAM,mBAAmB,WAAW,KAAK,MAAM,aAAa,GAAG,CAAC;AAAA,MAC7F;AAAA,IACF;AACA,WAAO,CAAC,YAAY,YAAY,qBAAqB;AAAA,EACvD;AAAA,EACA,SAAS,GAAG,KAAK,WAAW,UAAU,GAAG,OAAO;AAC9C,WAAO,KAAK,MAAM;AAChB,YAAM,aAAa,KAAK,gBAAgB,KAAK,WAAW,OAAO,OAAO;AACtE,YAAM,OAAO,CAAC;AACd,UAAI,UAAU,GAAG;AACf,cAAM,IAAI,oBAAoB,sCAAsC;AAAA,MACtE;AACA,UAAI,SAAS,MAAM;AACjB,cAAM,IAAI,oBAAoB,iDAAiD;AAAA,MACjF,OAAO;AACL,cAAM,UAAU,YAAY,YAAY,SAAS;AACjD,cAAM,aAAa,SAAS,OAAO,GAAG,UAAU,CAAC;AACjD,iBAAS,aAAa,GAAG,aAAa,QAAQ,QAAQ,EAAE,YAAY;AAClE,gBAAM,aAAa,QAAQ,YAAY;AACvC,gBAAM,WAAW,QAAQ,YAAY;AACrC,gBAAM,WAAW,oBAAoB,YAAY,YAAY,WAAW,UAAU;AAClF,gBAAM,WAAW,qBAAqB,KAAK,QAAQ;AACnD,gBAAM,YAAY,EAAE,QAAQ;AAC5B,cAAI,eAAe,GAAG;AACpB,qBAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,mBAAK,KAAK,OAAO,CAAC,CAAC;AAAA,YACrB;AAAA,UACF;AACA,mBAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,kBAAM,WAAW,UAAU;AAC3B,iBAAK,MAAM,KAAK,KAAK,KAAK,IAAI,WAAW,YAAY,QAAQ,CAAC;AAAA,UAChE;AAAA,QACF;AACA,iBAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,eAAK,MAAM,IAAI,KAAK,KAAK,UAAU;AAAA,QACrC;AAAA,MACF;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,yBAAyB;AACvB,UAAM,YAAY,KAAK;AACvB,UAAM,mBAAmB,CAAC;AAC1B,aAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,YAAM,QAAQ,UAAU;AACxB,UAAI,WAAW;AACf,UAAI,MAAM,WAAW,KAAK,IAAI,GAAG;AAC/B,cAAM,WAAW,MAAM,UAAU,MAAM,GAAG,EAAE,GAAG,KAAK;AACpD,oBAAY,IAAI;AAAA,MAClB;AACA,uBAAiB,KAAK,QAAQ;AAAA,IAChC;AACA,WAAO;AAAA,EACT;AAAA,EACA,oBAAoB;AAClB,WAAO,CAAC,SAAS;AACf,YAAM,aAAa,CAAC;AACpB,YAAM,SAAS,KAAK,MAAM,GAAG,KAAK,OAAO,MAAM;AAC/C,YAAM,UAAU,KAAK,MAAM,KAAK,OAAO,QAAQ,KAAK,OAAO,SAAS,KAAK,QAAQ,MAAM;AACvF,YAAM,gBAAgB,KAAK,MAAM,KAAK,OAAO,SAAS,KAAK,QAAQ,QAAQ,KAAK,OAAO,SAAS,KAAK,QAAQ,SAAS,CAAC;AACvH,YAAM,gBAAgB,CAAC;AACvB,YAAM,oBAAoB,MAAM;AAC9B,cAAM,QAAQ,CAAC;AACf,iBAAS,KAAK,GAAG,KAAK,KAAK,OAAO,QAAQ,EAAE,IAAI;AAC9C,gBAAM,KAAK,EAAE,KAAK,KAAK,OAAO,KAAK,OAAO,OAAO,IAAI,CAAC;AAAA,QACxD;AACA,cAAM,WAAW,IAAI,SAAS,KAAK;AACnC,cAAM,UAAU,QAAQ,KAAK,SAAS,UAAU,EAAE,YAAY,KAAK,CAAC;AACpE,YAAI;AACJ,iBAAS,KAAK,GAAG,KAAK,KAAK,cAAc,QAAQ,EAAE,IAAI;AACrD,gBAAM,eAAe,KAAK,cAAc;AACxC,cAAI,OAAO,aAAa,QAAQ,KAAK,QAAQ,GAAG;AAChD,cAAI,cAAc,OAAO,MAAM;AAC7B,mBAAO,qBAAqB,MAAM,cAAc,GAAG;AAAA,UACrD;AACA,gBAAM,WAAW,KAAK,IAAI;AAC1B,qBAAW,KAAK,QAAQ;AACxB,cAAI,OAAO,GAAG;AACZ,wBAAY;AAAA,UACd,OAAO;AACL,wBAAY,KAAK,WAAW,IAAI;AAAA,UAClC;AAAA,QACF;AACA,iBAAS,KAAK,GAAG,KAAK,KAAK,eAAe,QAAQ,EAAE,IAAI;AACtD,cAAI;AACJ,cAAI,KAAK,QAAQ,SAAS,KAAK,KAAK,KAAK,QAAQ,QAAQ;AACvD,6BAAiB,WAAW;AAAA,UAC9B,OAAO;AACL,kBAAM,SAAS,KAAK,eAAe,IAAI;AACvC,kBAAM,cAAc,KAAK,eAAe,IAAI;AAC5C,6BAAiB,KAAK,OAAO,QAAQ,cAAc,QAAQ,YAAY,CAAC;AAAA,UAC1E;AACA,eAAK,cAAc;AACnB,wBAAc,KAAK,cAAc;AAAA,QACnC;AACA,oBAAY,KAAK,SAAS;AAC1B,aAAK,gBAAgB,EAAE,QAAQ,CAAC,oBAAoB;AAClD,sBAAY,KAAK,WAAW,eAAe;AAAA,QAC7C,CAAC;AACD,eAAO;AAAA,MACT;AACA,YAAM,YAAY,KAAK,0BAA0B,IAAI,CAAC,UAAU,MAAM,KAAK,CAAC;AAC5E,YAAM,aAAa;AACnB,YAAM,iBAAiB,KAAK,WAAW,SAAS,mBAAmB,YAAY,SAAS;AACxF,aAAO,CAAC,cAAc,EAAE,OAAO,aAAa;AAAA,IAC9C;AAAA,EACF;AAAA,EACA,mBAAmB;AACjB,SAAK,eAAe,CAAC,SAAS;AAC5B,aAAO,KAAK,MAAM;AAChB,cAAM,aAAa,CAAC;AACpB,YAAI;AACJ,cAAM,SAAS,KAAK,MAAM,GAAG,KAAK,OAAO,MAAM;AAC/C,cAAM,UAAU,KAAK,MAAM,KAAK,OAAO,QAAQ,KAAK,OAAO,SAAS,KAAK,QAAQ,MAAM;AACvF,cAAM,QAAQ,CAAC;AACf,iBAAS,KAAK,GAAG,KAAK,KAAK,OAAO,QAAQ,EAAE,IAAI;AAC9C,gBAAM,KAAK,EAAE,KAAK,KAAK,OAAO,KAAK,OAAO,OAAO,IAAI,CAAC;AAAA,QACxD;AACA,cAAM,WAAW,IAAI,SAAS,KAAK;AACnC,cAAM,UAAU,QAAQ,KAAK,SAAS,QAAQ;AAC9C,iBAAS,KAAK,GAAG,KAAK,KAAK,cAAc,QAAQ,EAAE,IAAI;AACrD,gBAAM,eAAe,KAAK,cAAc;AACxC,gBAAM,OAAO,KAAK,aAAa,QAAQ,KAAK,QAAQ,GAAG,CAAC;AACxD,cAAI,OAAO,GAAG;AACZ,wBAAY;AAAA,UACd,OAAO;AACL,wBAAY,KAAK,WAAW,IAAI;AAAA,UAClC;AACA,qBAAW,KAAK,SAAS;AAAA,QAC3B;AACA,iBAAS,KAAK,GAAG,KAAK,KAAK,eAAe,QAAQ,EAAE,IAAI;AACtD,gBAAM,SAAS,KAAK,eAAe,IAAI;AACvC,gBAAM,cAAc,KAAK,eAAe,IAAI;AAC5C,gBAAM,aAAa,KAAK,OAAO,QAAQ,cAAc,QAAQ,YAAY,CAAC;AAC1E,qBAAW,KAAK,UAAU;AAAA,QAC5B;AACA,eAAO;AAAA,MACT,CAAC;AAAA,IACH;AAAA,EACF;AAAA,EACA,MAAM,IAAI,GAAG,GAAG,OAAO,CAAC,GAAG;AACzB,WAAO,WAAW,MAAM,GAAG,GAAG,IAAI;AAAA,EACpC;AAAA,EACA,MAAM,WAAW,SAAS,MAAM;AAC9B,WAAO,WAAW,MAAM,SAAS,IAAI;AAAA,EACvC;AAAA,EACA,MAAM,aAAa,GAAG,GAAG;AACvB,UAAM,iBAAiB,MAAM,KAAK,oBAAoB,GAAG,CAAC;AAC1D,UAAM,SAAS,eAAe;AAC9B,UAAM,UAAU,eAAe;AAC/B,UAAM,gBAAgB,KAAK,kBAAkB;AAC7C,UAAM,UAAU,cAAc,OAAO,OAAO,OAAO,CAAC;AACpD,UAAM,aAAa,CAAC;AACpB,eAAW,QAAQ,SAAS;AAC1B,YAAM,IAAI,MAAM,KAAK,KAAK;AAC1B,iBAAW,KAAK,EAAE,EAAE;AAAA,IACtB;AACA,YAAQ,OAAO;AACf,sBAAkB,eAAe,IAAI,CAAC;AACtC,sBAAkB,eAAe,IAAI,CAAC;AACtC,WAAO,iBAAiB,UAAU;AAAA,EACpC;AAAA,EACA,gBAAgBK,SAAQ;AACtB,UAAM,eAAe,CAAC;AACtB,UAAM,gBAAgBA,WAAU,QAAQA,QAAO;AAC/C,UAAM,UAAU,gBAAgB,KAAK,mBAAmB,KAAK;AAC7D,UAAM,eAAe,KAAK,WAAW,aAAa;AAClD,aAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC1C,UAAI,iBAAiB,CAAC,QAAQ,IAAI,WAAW;AAC3C;AAAA,MACF;AACA,mBAAa,KAAK,EAAE,MAAM,QAAQ,IAAI,cAAc,QAAQ,aAAa,IAAI,CAAC;AAAA,IAChF;AACA,WAAO;AAAA,EACT;AAAA,EACA,IAAI,aAAa,MAAM;AACrB,SAAK,gBAAgB;AAAA,EACvB;AAAA,EACA,IAAI,eAAe;AACjB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,UAAU,WAAW;AACvB,QAAI,KAAK,eAAe,WAAW;AACjC,WAAK,aAAa;AAClB,WAAK,mBAAmB;AAAA,IAC1B;AAAA,EACF;AAAA,EACA,UAAU;AACR,UAAM,SAAS,MAAM,QAAQ;AAC7B,QAAI,OAAO,yBAAyB,KAAK,KAAK,aAAa,QAAQ,KAAK,kBAAkB;AACxF,YAAM,mCAAmC,OAAO,EAAE;AAClD,WAAK,WAAW,QAAQ;AACxB,aAAO,wBAAwB,mCAAmC,OAAO,EAAE;AAAA,IAC7E;AACA,WAAO;AAAA,EACT;AAAA,EACA,qBAAqB;AACnB,QAAI;AACJ,QAAI,OAAO,KAAK,SAAS,UAAU;AACjC,kBAAY,YAAY,KAAK,IAAI;AAAA,IACnC,WAAW,MAAM,QAAQ,KAAK,IAAI,GAAG;AACnC,iBAAW,QAAQ,KAAK,MAAM;AAC5B,YAAI,OAAO,SAAS,UAAU;AAC5B,gBAAM,IAAI,MAAM,oDAAoD;AAAA,QACtE;AAAA,MACF;AACA,kBAAY,KAAK,KAAK,IAAI,CAAC,SAAS,YAAY,IAAI,CAAC;AAAA,IACvD,OAAO;AACL,YAAM,cAAc,OAAO,KAAK,KAAK,IAAI;AACzC,kBAAY,CAAC;AACb,YAAM,UAAU,KAAK;AACrB,iBAAW,cAAc,aAAa;AACpC,YAAI,OAAO,QAAQ,gBAAgB,UAAU;AAC3C,oBAAU,cAAc,YAAY,QAAQ,WAAW;AAAA,QACzD,OAAO;AACL,gBAAM,IAAI,MAAM,oDAAoD;AAAA,QACtE;AAAA,MACF;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,uBAAuB;AACrB,QAAI,OAAO,KAAK,YAAY,YAAY,OAAO,KAAK,YAAY,YAAY;AAC1E,aAAO,CAAC,YAAY,oBAAoB,KAAK,OAAO,CAAC,CAAC;AAAA,IACxD,WAAW,MAAM,QAAQ,KAAK,OAAO,GAAG;AACtC,aAAO,KAAK,QAAQ,IAAI,CAAC,WAAW,YAAY,oBAAoB,MAAM,CAAC,CAAC;AAAA,IAC9E,OAAO;AACL,YAAM,qBAAqB,CAAC;AAC5B,iBAAW,OAAO,KAAK,SAAS;AAC9B,2BAAmB,OAAO,YAAY,oBAAoB,KAAK,QAAQ,IAAI,CAAC;AAAA,MAC9E;AACA,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,oBAAoB;AAClB,WAAO;AAAA,MACL,MAAM,KAAK,mBAAmB;AAAA,MAC9B,SAAS,KAAK,qBAAqB;AAAA,MACnC,kBAAkB;AAAA,QAChB,YAAY,KAAK,UAAU,aAAa;AAAA,QACxC,QAAQ,KAAK,UAAU,UAAU;AAAA,MACnC;AAAA,IACF;AAAA,EACF;AAAA,EACA,mBAAmB,gBAAgB;AACjC,QAAI,eAAe,oBAAoB,MAAM;AAC3C,YAAM,IAAI,MAAM,8CAA8C;AAAA,IAChE;AACA,QAAI,eAAe,gBAAgB,MAAM;AACvC,YAAM,IAAI,MAAM,4CAA4C;AAAA,IAC9D;AACA,QAAI,eAAe,sBAAsB,MAAM;AAC7C,YAAM,IAAI,MAAM,kDAAkD;AAAA,IACpE;AACA,UAAM,WAAW,oBAAoB,eAAe,gBAAgB;AACpE,UAAM,YAAY,YAAY,QAAQ;AACtC,QAAI;AACJ,QAAI,OAAO,eAAe,SAAS,UAAU;AAC3C,aAAO,YAAY,eAAe,IAAI;AAAA,IACxC,WAAW,MAAM,QAAQ,eAAe,IAAI,GAAG;AAC7C,aAAO,eAAe,KAAK,IAAI,CAAC,cAAc,YAAY,SAAS,CAAC;AAAA,IACtE,WAAW,eAAe,QAAQ,MAAM;AACtC,aAAO,CAAC;AACR,iBAAW,OAAO,eAAe,MAAM;AACrC,aAAK,OAAO,YAAY,eAAe,KAAK,IAAI;AAAA,MAClD;AAAA,IACF;AACA,QAAI;AACJ,QAAI,MAAM,QAAQ,eAAe,OAAO,GAAG;AACzC,gBAAU,eAAe,QAAQ,IAAI,CAAC,WAAW,YAAY,MAAM,CAAC;AAAA,IACtE,WAAW,eAAe,WAAW,MAAM;AACzC,gBAAU,CAAC;AACX,iBAAW,OAAO,eAAe,SAAS;AACxC,gBAAQ,OAAO,YAAY,eAAe,QAAQ,IAAI;AAAA,MACxD;AAAA,IACF;AACA,SAAK,QAAQ,EAAE,MAAM,SAAS,UAAU,CAAC;AAAA,EAC3C;AAAA,EACA,MAAM,KAAK,cAAcA,SAAQ;AAC/B,QAAI,OAAO,iBAAiB,UAAU;AACpC,YAAM,WAAW,WAAW,gBAAgB,YAAY;AACxD,UAAI,SAAS,WAAW,GAAG;AACzB,cAAM,IAAI,WAAW,0CAA0C,eAAe;AAAA,MAChF,WAAW,SAAS,SAAS,GAAG;AAC9B,cAAM,IAAI,WAAW,wBAAwB,SAAS,kCAAkC,eAAe;AAAA,MACzG;AACA,qBAAe,SAAS;AAAA,IAC1B;AACA,QAAI,aAAa,QAAQ,MAAM;AAC7B,YAAM,IAAI,WAAW,8GAA8G;AAAA,IACrI;AACA,UAAM,qBAAqB,MAAM,WAAW,cAAc,KAAK,gBAAgBA,OAAM,CAAC;AACtF,UAAM,eAAe;AACrB,UAAM,YAAY;AAClB,UAAM,cAAc,KAAK,OAAO,WAAW,YAAY;AACvD,UAAM,iBAAiB;AAAA,MACrB,eAAe;AAAA,MACf,QAAQ;AAAA,MACR,aAAa,8BAA8B;AAAA,MAC3C,aAAa;AAAA,IACf;AACA,UAAM,mBAAmBA,WAAU,OAAO,QAAQA,QAAO;AACzD,QAAI,oBAAoB,KAAK,aAAa,MAAM;AAC9C,qBAAe,iBAAiB,KAAK,kBAAkB;AACvD,YAAM,aAAa;AACnB,YAAM,EAAE,MAAM,qBAAqB,OAAO,qBAAqB,IAAI,MAAM,WAAW,cAAc,MAAM,KAAK,UAAU,WAAW,GAAG,UAAU;AAC/I,yBAAmB,MAAM,KAAK,GAAG,oBAAoB;AACrD,yBAAmB,OAAO,WAAW,wBAAwB,CAAC,mBAAmB,MAAM,mBAAmB,CAAC;AAAA,IAC7G;AACA,QAAI,KAAK,uBAAuB,MAAM;AACpC,YAAM,YAAY;AAClB,+BAAyB,KAAK,qBAAqB,KAAK,MAAM,SAAS;AACvE,qBAAe,sBAAsB,KAAK;AAAA,IAC5C;AACA,mBAAe,aAAa,mBAAmB;AAC/C,mBAAe,cAAc,mBAAmB;AAChD,WAAO,aAAa,KAAK,cAAc;AAAA,EACzC;AAAA,EACA,uBAAuB,qBAAqB;AAC1C,6BAAyB,qBAAqB,KAAK,IAAI;AACvD,SAAK,sBAAsB;AAAA,EAC7B;AAAA,EACA,yBAAyB;AACvB,WAAO,KAAK;AAAA,EACd;AACF;AACA,YAAY,YAAY;AACxB,sBAAsB,cAAc,WAAW;AAC/C,IAAI,aAAa,cAAc,YAAY;AAC3C;AACA,WAAW,YAAY;AACvB,sBAAsB,cAAc,UAAU;AAG9C,eAAe,cAAc,uBAAuB,eAAe;AACjE,MAAI,EAAE,mBAAmB,wBAAwB;AAC/C,4BAAwB,EAAE,eAAe,sBAAsB;AAAA,EACjE;AACA,0BAAwB;AACxB,MAAI,gBAAgB,sBAAsB;AAC1C,MAAI,cAAc,mBAAmB,MAAM;AACzC,oBAAgB,cAAc;AAAA,EAChC;AACA,QAAM,WAAW,oBAAoB,aAAa;AAClD,QAAMe,UAAS,YAAY,UAAU,aAAa;AAClD,MAAI,sBAAsB,mBAAmB,MAAM;AACjD,UAAM,eAAe,MAAM,WAAW,YAAY,sBAAsB,iBAAiB,sBAAsB,YAAYA,QAAO,QAAQ,IAAI,CAAC,WAAW,OAAO,YAAY,CAAC;AAC9K,UAAM,qBAAqB,CAAC;AAC5B,eAAW,UAAUA,QAAO,SAAS;AACnC,yBAAmB,OAAO,gBAAgB,aAAa,OAAO;AAAA,IAChE;AACA,IAAAA,QAAO,YAAY,kBAAkB;AACrC,YAAQ,YAAY;AAAA,EACtB;AACA,SAAOA;AACT;AACA,eAAe,wBAAwB,iBAAiBvB,UAAS;AAC/D,MAAIA,YAAW,MAAM;AACnB,IAAAA,WAAU,CAAC;AAAA,EACb;AACA,MAAI,OAAO,oBAAoB,UAAU;AACvC,UAAM,WAAW,WAAW,gBAAgB,iBAAiBA,QAAO;AACpE,QAAI,SAAS,WAAW,GAAG;AACzB,eAAS,KAAK,WAAW,mBAAmB,iBAAiBA,QAAO,CAAC;AAAA,IACvE,WAAW,SAAS,SAAS,GAAG;AAC9B,YAAM,IAAI,WAAW,wBAAwB,SAAS,kCAAkC,kBAAkB;AAAA,IAC5G;AACA,sBAAkB,SAAS;AAAA,EAC7B;AACA,SAAO,6BAA6B,iBAAiB,QAAQA,QAAO;AACtE;AACA,eAAe,6BAA6B,SAAS,eAAeA,UAAS;AAC3E,MAAIA,YAAW,MAAM;AACnB,IAAAA,WAAU,CAAC;AAAA,EACb;AACA,MAAI,QAAQ,QAAQ,MAAM;AACxB,UAAM,IAAI,WAAW,+GAA+G;AAAA,EACtI;AACA,QAAM,YAAY,MAAM,QAAQ,KAAK;AACrC,MAAI,gBAAgB,UAAU;AAC9B,MAAI,cAAc,mBAAmB,MAAM;AACzC,oBAAgB,cAAc;AAAA,EAChC;AACA,QAAM,SAASA,SAAQ,UAAU,OAAO,OAAOA,SAAQ;AACvD,QAAM,iBAAiB,UAAU,cAAc,QAAQ,UAAU,eAAe,QAAQ;AACxF,QAAMuB,UAAS,YAAY,oBAAoB,aAAa,GAAG,eAAe,cAAc;AAC5F,QAAM,iBAAiB,UAAU;AACjC,MAAI,kBAAkB,MAAM;AAC1B,IAAAA,QAAO,mBAAmB,cAAc;AAAA,EAC1C;AACA,MAAI,UAAU,uBAAuB,MAAM;AACzC,IAAAA,QAAO,uBAAuB,UAAU,mBAAmB;AAAA,EAC7D;AACA,MAAI,UAAU,cAAc,MAAM;AAChC,QAAI,UAAU,eAAe,MAAM;AACjC,YAAM,IAAI,WAAW,gHAAgH;AAAA,IACvI;AACA,UAAM,EAAE,cAAc,iBAAiB,IAAI,+BAA+B,UAAU,YAAY,UAAU,WAAW;AACrH,IAAAA,QAAO,YAAY,cAAc,MAAM;AACvC,QAAIA,QAAO,aAAa,QAAQ,iBAAiB,SAAS,GAAG;AAC3D,YAAMA,QAAO,UAAU,WAAW,gBAAgB;AAAA,IACpD;AACA,YAAQ,YAAY;AACpB,YAAQ,iBAAiB,IAAI,CAAC,MAAM,EAAE,MAAM,CAAC;AAAA,EAC/C;AACA,SAAOA;AACT;AACA,SAAS,+BAA+B,SAAS,OAAO;AACtD,QAAM,cAAc,WAAW,cAAc,SAAS,KAAK;AAC3D,QAAM,eAAe,CAAC;AACtB,QAAM,mBAAmB,CAAC;AAC1B,QAAM,QAAQ,CAAC,SAAS;AACtB,QAAI,KAAK,UAAU,aAAa;AAC9B,uBAAiB,KAAK,EAAE,MAAM,KAAK,MAAM,QAAQ,YAAY,KAAK,MAAM,CAAC;AAAA,IAC3E,OAAO;AACL,mBAAa,KAAK,QAAQ,YAAY,KAAK;AAAA,IAC7C;AAAA,EACF,CAAC;AACD,SAAO,EAAE,cAAc,iBAAiB;AAC1C;AACA,IAAI,aAAa,cAAc,YAAY;AAAA,EACzC,YAAY,MAAM;AAChB,UAAM,EAAE,QAAQ,CAAC,GAAG,SAAS,CAAC,EAAE,CAAC;AACjC,WAAO,QAAQ,CAAC;AAChB,SAAK,YAAY;AACjB,SAAK,QAAQ;AACb,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,OAAO,OAAO,aAAa;AAChE,QAAI,KAAK,UAAU,MAAM;AACvB,iBAAW,SAAS,KAAK,QAAQ;AAC/B,aAAK,IAAI,KAAK;AAAA,MAChB;AAAA,IACF;AAAA,EACF;AAAA,EACA,WAAW,OAAO;AAChB,UAAM,QAAQ,MAAM,aAAa,GAAG,cAAc,GAAG;AACrD,QAAI,MAAM,KAAK,CAAC,MAAM,IAAI,CAAC,GAAG;AAC5B,YAAM,IAAI,WAAW,kDAAkD,MAAM,0BAA0B,MAAM,aAAa,GAAG,aAAa,GAAG,QAAQ;AAAA,IACvJ;AAAA,EACF;AAAA,EACA,IAAI,OAAO;AACT,UAAM,uBAAuB,iBAAiB,cAAc,iBAAiB;AAC7E,QAAI;AACJ,QAAI,sBAAsB;AACxB,mBAAa;AACb,UAAI,WAAW,QAAQ,WAAW,GAAG;AACnC,cAAM,IAAI,WAAW,uHAAuH;AAAA,MAC9I;AACA,UAAI,WAAW,OAAO,WAAW,GAAG;AAClC,cAAM,IAAI,WAAW,qHAAqH;AAAA,MAC5I;AAAA,IACF;AACA,QAAI,KAAK,QAAQ,WAAW,GAAG;AAC7B,UAAI,MAAM,aAAa,WAAW,GAAG;AACnC,YAAI,MAAM,mBAAmB,MAAM;AACjC,gBAAM,IAAI,WAAW,+FAA+F;AAAA,QACtH;AACA,cAAM,IAAI,MAAM;AAAA,UACd,YAAY,MAAM;AAAA,UAClB,OAAO,MAAM;AAAA,UACb,MAAM,MAAM,OAAO;AAAA,QACrB,CAAC;AACD,cAAM,MAAM,CAAC;AAAA,MACf;AACA,UAAI,sBAAsB;AACxB,aAAK,UAAU,WAAW;AAC1B,aAAK,SAAS,WAAW;AAAA,MAC3B,OAAO;AACL,YAAI,MAAM,aAAa,WAAW,GAAG;AACnC,gBAAM,IAAI,WAAW,gHAAgH,MAAM,kBAAkB,MAAM,aAAa,0CAA0C;AAAA,QAC5N;AACA,YAAI,MAAM,aAAa,GAAG,cAAc,WAAW,GAAG;AACpD,gBAAM,IAAI,WAAW,uHAAuH;AAAA,QAC9I;AACA,aAAK,WAAW,KAAK;AACrB,aAAK,UAAU,CAAC,MAAM,aAAa,GAAG,cAAc,EAAE;AACtD,aAAK,SAAS,gBAAgB,KAAK,QAAQ,EAAE;AAAA,MAC/C;AACA,WAAK,eAAe,CAAC;AACrB,UAAI,KAAK;AAAA,QACP,eAAe;AAAA,QACf,eAAe,CAAC;AAAA,QAChB,aAAa,CAAC;AAAA,QACd,eAAe,CAAC;AAAA,QAChB,cAAc,KAAK;AAAA,QACnB,eAAe,KAAK;AAAA,QACpB,YAAY,aAAa,MAAM,KAAK,OAAO,MAAM;AAAA,QACjD,aAAa,CAAC,IAAI;AAAA,QAClB,aAAa,KAAK,OAAO,IAAI,CAAC,MAAM,EAAE,KAAK;AAAA,QAC3C,cAAc,KAAK,QAAQ,GAAG;AAAA,MAChC,CAAC;AAAA,IACH,OAAO;AACL,YAAM,eAAe,MAAM,MAAM,KAAK,QAAQ,EAAE;AAChD,UAAI,MAAM,QAAQ,YAAY,GAAG;AAC/B,cAAM,IAAI,UAAU,uHAAuH;AAAA,MAC7I;AACA,WAAK,WAAW,KAAK;AACrB,WAAK,UAAU,CAAC,YAAY;AAC5B,WAAK,aAAa,GAAG,gBAAgB,KAAK;AAC1C,WAAK,aAAa,GAAG,eAAe,CAAC,KAAK,QAAQ,GAAG,KAAK;AAAA,IAC5D;AACA,SAAK,OAAO,KAAK,KAAK;AACtB,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,MAAM;AACJ,QAAI,KAAK,OAAO,WAAW,GAAG;AAC5B,YAAM,IAAI,UAAU,mCAAmC;AAAA,IACzD;AACA,SAAK,OAAO,IAAI;AAChB,QAAI,KAAK,OAAO,WAAW,GAAG;AAC5B,WAAK,UAAU,CAAC;AAChB,WAAK,eAAe,CAAC;AACrB,WAAK,gBAAgB,CAAC;AAAA,IACxB,OAAO;AACL,YAAM,iBAAiB,KAAK,OAAO,SAAS;AAC5C,WAAK,OAAO,gBAAgB,gBAAgB,CAAC;AAC7C,WAAK,UAAU,CAAC,KAAK,OAAO,gBAAgB,MAAM;AAClD,WAAK,aAAa,GAAG,gBAAgB,KAAK;AAC1C,WAAK,aAAa,GAAG,eAAe,CAAC,KAAK,QAAQ,GAAG,KAAK;AAAA,IAC5D;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,QAAI,KAAK,SAAS,MAAM;AACtB,WAAK,MAAM;AAAA,IACb;AACA,WAAO,KAAK,MAAM,KAAK,QAAQ,MAAM;AAAA,EACvC;AAAA,EACA,MAAM,YAAY;AAChB,uBAAmB,UAAU;AAC7B,QAAI,KAAK,OAAO,WAAW,KAAK,KAAK,QAAQ,WAAW,GAAG;AACzD,YAAM,IAAI,UAAU,0EAA0E;AAAA,IAChG;AACA,SAAK,QAAQ,IAAI,YAAY;AAAA,MAC3B,QAAQ,KAAK;AAAA,MACb,SAAS,KAAK,QAAQ;AAAA,MACtB,MAAM,KAAK,OAAO;AAAA,IACpB,CAAC;AACD,SAAK,MAAM,YAAY,KAAK;AAC5B,SAAK,kBAAkB,KAAK,MAAM;AAClC,SAAK,cAAc,KAAK,MAAM;AAC9B,SAAK,yBAAyB,KAAK,MAAM;AACzC,SAAK,2BAA2B,KAAK,MAAM;AAC3C,SAAK,eAAe,KAAK,MAAM;AAC/B,SAAK,0BAA0B,KAAK,MAAM;AAC1C,SAAK,4BAA4B,KAAK,MAAM;AAC5C,SAAK,eAAe,KAAK,MAAM;AAC/B,SAAK,iBAAiB,KAAK,MAAM;AACjC,SAAK,cAAc,KAAK,MAAM;AAC9B,SAAK,aAAa,KAAK,MAAM;AAC7B,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,cAAc;AACZ,QAAI,CAAC,KAAK,OAAO;AACf,WAAK,MAAM;AAAA,IACb;AACA,WAAO,MAAM,YAAY;AAAA,EAC3B;AAAA,EACA,QAAQ,YAAY,WAAW,UAAU,QAAQ,KAAK;AACpD,QAAI,CAAC,KAAK,OAAO;AACf,WAAK,MAAM;AAAA,IACb;AACA,UAAM,QAAQ,YAAY,WAAW,OAAO;AAAA,EAC9C;AAAA,EACA,WAAW,SAAS;AAClB,QAAI,KAAK,SAAS,MAAM;AACtB,WAAK,MAAM;AAAA,IACb;AACA,SAAK,MAAM,WAAW,OAAO;AAAA,EAC/B;AAAA,EACA,SAAS,GAAG,GAAG,OAAO,CAAC,GAAG;AACxB,QAAI,CAAC,KAAK,OAAO;AACf,YAAM,IAAI,aAAa,mDAAmD;AAAA,IAC5E;AACA,WAAO,KAAK,MAAM,SAAS,GAAG,GAAG,IAAI;AAAA,EACvC;AAAA,EACA,MAAM,gBAAgB,SAAS,MAAM;AACnC,QAAI,CAAC,KAAK,OAAO;AACf,YAAM,IAAI,aAAa,mDAAmD;AAAA,IAC5E;AACA,WAAO,KAAK,MAAM,gBAAgB,SAAS,IAAI;AAAA,EACjD;AAAA,EACA,QAAQ,GAAG,OAAO,CAAC,GAAG;AACpB,QAAI,KAAK,SAAS,MAAM;AACtB,WAAK,MAAM;AAAA,IACb;AACA,WAAO,KAAK,MAAM,QAAQ,GAAG,IAAI;AAAA,EACnC;AAAA,EACA,eAAe,GAAG;AAChB,QAAI,KAAK,SAAS,MAAM;AACtB,WAAK,MAAM;AAAA,IACb;AACA,WAAO,KAAK,MAAM,eAAe,CAAC;AAAA,EACpC;AAAA,EACA,QAAQ,MAAM;AACZ,SAAK,MAAM;AACX,SAAK,MAAM,QAAQ,IAAI;AACvB,SAAK,aAAa,KAAK,MAAM;AAC7B,SAAK,mBAAmB,KAAK,MAAM;AACnC,SAAK,OAAO,KAAK,MAAM;AACvB,SAAK,UAAU,KAAK,MAAM;AAC1B,SAAK,iBAAiB,KAAK,MAAM;AACjC,SAAK,eAAe,KAAK,MAAM;AAAA,EACjC;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK,SAAS,OAAO,SAAS,KAAK,MAAM;AAAA,EAClD;AAAA,EACA,IAAI,UAAU,WAAW;AACvB,SAAK,MAAM,YAAY;AAAA,EACzB;AAAA,EACA,MAAM,IAAI,GAAG,GAAG,OAAO,CAAC,GAAG;AACzB,QAAI,CAAC,KAAK,OAAO;AACf,YAAM,IAAI,aAAa,mDAAmD;AAAA,IAC5E;AACA,WAAO,KAAK,MAAM,IAAI,GAAG,GAAG,IAAI;AAAA,EAClC;AAAA,EACA,MAAM,WAAW,SAAS,MAAM;AAC9B,QAAI,CAAC,KAAK,OAAO;AACf,YAAM,IAAI,aAAa,mDAAmD;AAAA,IAC5E;AACA,WAAO,KAAK,MAAM,WAAW,SAAS,IAAI;AAAA,EAC5C;AAAA,EACA,MAAM,aAAa,GAAG,GAAG;AACvB,WAAO,KAAK,MAAM,aAAa,GAAG,CAAC;AAAA,EACrC;AAAA,EACA,OAAO,WAAW,KAAKf,SAAQ,gBAAgB,CAAC,GAAG,iBAAiB,OAAO;AACzE,QAAI;AACJ,QAAI,mBAAmB,CAAC;AACxB,QAAIA,mBAAkB,OAAO;AAC3B,UAAI,EAAEA,QAAO,GAAG,aAAa,SAASA,QAAO,GAAG,iBAAiB,SAAS;AACxE,cAAM,IAAI,WAAW,gDAAgD;AAAA,MACvE;AACA,oBAAcA;AAAA,IAChB,OAAO;AACL,mBAAa,OAAOA,QAAO,aAAa,MAAM,MAAM,qHAAqH;AACzK,oBAAcA,QAAO;AACrB,aAAOA,QAAO;AACd,yBAAmBA;AAAA,IACrB;AACA,UAAMe,UAAS,IAAI,IAAI,gBAAgB;AACvC,QAAI,EAAEA,mBAAkB,aAAa;AACnC,YAAM,IAAI,oBAAoB,yDAAyDA,SAAQ;AAAA,IACjG;AACA,eAAW,QAAQ,aAAa;AAC9B,YAAM,iBAAiB;AACvB,YAAM,QAAQ,YAAY,MAAM,gBAAgB,cAAc;AAC9D,UAAI,gBAAgB;AAClB,cAAM,6BAA6B,IAAI;AAAA,MACzC;AACA,MAAAA,QAAO,IAAI,KAAK;AAAA,IAClB;AACA,WAAOA;AAAA,EACT;AAAA,EACA,IAAI,aAAa,MAAM;AACrB,QAAI,KAAK,SAAS,MAAM;AACtB,YAAM,IAAI,WAAW,mFAAmF;AAAA,IAC1G;AACA,SAAK,MAAM,eAAe;AAAA,EAC5B;AAAA,EACA,IAAI,eAAe;AACjB,QAAI,KAAK,SAAS,MAAM;AACtB,YAAM,IAAI,WAAW,mFAAmF;AAAA,IAC1G;AACA,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,YAAY;AACV,UAAM,SAAS,CAAC;AAChB,eAAW,SAAS,KAAK,QAAQ;AAC/B,YAAM,OAAO,CAAC;AACd,WAAK,eAAe,MAAM,aAAa;AACvC,WAAK,YAAY,MAAM,UAAU;AACjC,aAAO,KAAK,IAAI;AAAA,IAClB;AACA,WAAO,EAAE,MAAM,KAAK,MAAM,OAAO;AAAA,EACnC;AACF;AACA,WAAW,YAAY;AACvB,sBAAsB,cAAc,UAAU;AAG9C,SAAS,MAAM,MAAM;AACnB,SAAO,IAAI,YAAY,IAAI;AAC7B;AACA,SAAS,WAAWf,SAAQ;AAC1B,SAAO,IAAI,WAAWA,OAAM;AAC9B;AACA,SAAS,gBAAgB,iBAAiBR,UAAS;AACjD,MAAIA,YAAW,MAAM;AACnB,IAAAA,WAAU,CAAC;AAAA,EACb;AACA,SAAO,wBAAwB,iBAAiBA,QAAO;AACzD;AACA,SAAS,MAAMQ,SAAQ;AACrB,SAAO,MAAMA,OAAM;AACrB;AACA,SAAS,4BAA4B,gBAAgB,qBAAqB;AACxE,8BAA4B,4BAA4B,gBAAgB,mBAAmB;AAC7F;AAGA,IAAI,aAAa,cAAc,sBAAsB,aAAa;AAAA,EAChE,YAAY;AACV,WAAO,CAAC;AAAA,EACV;AACF;AACA,IAAI,OAAO,cAAc,WAAW;AAAA,EAClC,MAAM,GAAGQ,SAAQ,GAAG;AAClB,WAAO,KAAK,GAAGA,MAAK;AAAA,EACtB;AACF;AACA,KAAK,YAAY;AACjB,sBAAsB,cAAc,IAAI;AACxC,IAAI,QAAQ,cAAc,WAAW;AAAA,EACnC,MAAM,GAAG;AACP,WAAO,KAAK,CAAC;AAAA,EACf;AACF;AACA,MAAM,YAAY;AAClB,sBAAsB,cAAc,KAAK;AACzC,IAAI,QAAQ,cAAc,WAAW;AAAA,EACnC,MAAM,GAAG;AACP,WAAO,KAAK,CAAC;AAAA,EACf;AACF;AACA,MAAM,YAAY;AAClB,sBAAsB,cAAc,KAAK;AACzC,IAAI,SAAS,cAAc,WAAW;AAAA,EACpC,MAAM,GAAG;AACP,WAAO,KAAK,MAAM,QAAQ,GAAG,KAAK,CAAC,CAAC,CAAC;AAAA,EACvC;AACF;AACA,OAAO,YAAY;AACnB,sBAAsB,cAAc,MAAM;AAC1C,IAAI,SAAS,cAAc,WAAW;AAAA,EACpC,MAAM,GAAG;AACP,WAAO;AAAA,EACT;AACF;AACA,OAAO,YAAY;AACnB,sBAAsB,cAAc,MAAM;AAC1C,IAAI,WAAW,cAAc,WAAW;AAAA,EACtC,MAAM,GAAG;AACP,WAAO,QAAQ,CAAC;AAAA,EAClB;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,cAAc,cAAc,WAAW;AAAA,EACzC,MAAM,GAAG;AACP,WAAO,YAAY,CAAC;AAAA,EACtB;AACF;AACA,YAAY,YAAY;AACxB,sBAAsB,cAAc,WAAW;AAC/C,IAAI,YAAY,cAAc,WAAW;AAAA,EACvC,MAAM,GAAG;AACP,WAAO,SAAS,CAAC;AAAA,EACnB;AACF;AACA,UAAU,YAAY;AACtB,sBAAsB,cAAc,SAAS;AAC7C,IAAI,WAAW,cAAc,WAAW;AAAA,EACtC,MAAM,GAAG;AACP,WAAO,SAAS,CAAC;AAAA,EACnB;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,QAAQ,cAAc,WAAW;AAAA,EACnC,MAAM,GAAG;AACP,WAAO,MAAM,CAAC;AAAA,EAChB;AACF;AACA,MAAM,YAAY;AAClB,sBAAsB,cAAc,KAAK;AACzC,IAAI,WAAW,cAAc,WAAW;AAAA,EACtC,MAAM,GAAG,OAAO,IAAI;AAClB,WAAO,QAAQ,GAAG,IAAI;AAAA,EACxB;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,cAAc,cAAc,WAAW;AAAA,EACzC,MAAM,GAAG,OAAO,IAAI;AAClB,WAAO,WAAW,GAAG,IAAI;AAAA,EAC3B;AACF;AACA,YAAY,YAAY;AACxB,sBAAsB,cAAc,WAAW;AAC/C,IAAI,QAAQ,cAAc,WAAW;AAAA,EACnC,MAAM,GAAGA,SAAQ,GAAG;AAClB,WAAO,KAAK,MAAM,IAAI,QAAQ,IAAI,GAAGA,MAAK,CAAC,GAAG,CAAC,CAAC;AAAA,EAClD;AACF;AACA,MAAM,YAAY;AAClB,sBAAsB,cAAc,KAAK;AACzC,IAAI,OAAO,cAAc,WAAW;AAAA,EAClC,MAAM,GAAG;AACP,WAAO,KAAK,MAAM,IAAI,GAAG,MAAM,SAAS,CAAC,CAAC,CAAC,CAAC;AAAA,EAC9C;AACF;AACA,KAAK,YAAY;AACjB,sBAAsB,cAAc,IAAI;AACxC,SAAS,oBAAoB,aAAa;AACxC,SAAO,YAAY,aAAa;AAClC;AACA,SAAS,sBAAsBR,SAAQ,gBAAgB,CAAC,GAAG;AACzD,SAAO,uBAAuBA,SAAQ,sBAAsB,iBAAiB,OAAO,EAAE,cAAc,eAAe,YAAY;AACjI;AACA,SAAS,cAAc,YAAY;AACjC,MAAI,cAAc,MAAM;AACtB,UAAMA,UAAS,CAAC;AAChB,IAAAA,QAAO,eAAe;AACtB,IAAAA,QAAO,YAAY,CAAC;AACpB,WAAO,sBAAsBA,OAAM;AAAA,EACrC;AACA,MAAI,OAAO,eAAe,UAAU;AAClC,UAAMA,UAAS,CAAC;AAChB,IAAAA,QAAO,eAAe;AACtB,IAAAA,QAAO,YAAY,CAAC;AACpB,WAAO,sBAAsBA,OAAM;AAAA,EACrC,WAAW,sBAAsB,YAAY;AAC3C,WAAO;AAAA,EACT,OAAO;AACL,WAAO,sBAAsB,UAAU;AAAA,EACzC;AACF;AAGA,SAAS,iBAAiB,MAAM;AAC9B,MAAI,QAAQ,QAAQ,OAAO,SAAS,UAAU;AAC5C,UAAM,IAAI,MAAM,yFAAyF,MAAM;AAAA,EACjH;AACF;AACA,IAAI,cAAc,cAAc,sBAAsB,aAAa;AACnE;AACA,IAAI,OAAO,cAAc,YAAY;AAAA,EACnC,YAAY,MAAM;AAChB,UAAM;AACN,qBAAiB,IAAI;AACrB,SAAK,KAAK,QAAQ,QAAQ,KAAK,MAAM,OAAO,OAAO,KAAK;AACxD,SAAK,KAAK,QAAQ,QAAQ,KAAK,MAAM,OAAO,OAAO,KAAK;AACxD,SAAK,QAAQ,KAAK,OAAO;AACzB,SAAK,QAAQ,KAAK,OAAO;AAAA,EAC3B;AAAA,EACA,MAAM,GAAG;AACP,WAAO,KAAK,MAAM;AAChB,UAAI,iBAAiB,MAAM,CAAC,CAAC,CAAC;AAC9B,UAAI,KAAK,OAAO;AACd,yBAAiB,KAAK,gBAAgB,KAAK,IAAI,KAAK,IAAI,IAAI,CAAC,CAAC,CAAC,CAAC;AAAA,MAClE;AACA,UAAI,KAAK,OAAO;AACd,yBAAiB,KAAK,gBAAgB,KAAK,IAAI,KAAK,IAAI,QAAQ,CAAC,CAAC,CAAC,CAAC;AAAA,MACtE;AACA,aAAO,QAAQ,gBAAgB,CAAC,CAAC;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,WAAO,EAAE,MAAM,KAAK,IAAI,MAAM,KAAK,GAAG;AAAA,EACxC;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,WAAO,IAAI,IAAI,EAAE,IAAIA,QAAO,OAAO,IAAIA,QAAO,MAAM,CAAC;AAAA,EACvD;AACF;AACA,KAAK,YAAY;AACjB,sBAAsB,cAAc,IAAI;AACxC,SAAS,GAAG,MAAM;AAChB,mBAAiB,IAAI;AACrB,SAAO,IAAI,KAAK,EAAE,IAAI,QAAQ,OAAO,KAAK,KAAK,MAAM,IAAI,EAAE,CAAC;AAC9D;AACA,SAAS,GAAG,MAAM;AAChB,mBAAiB,IAAI;AACrB,SAAO,IAAI,KAAK,EAAE,IAAI,QAAQ,OAAO,KAAK,KAAK,MAAM,IAAI,EAAE,CAAC;AAC9D;AACA,IAAI,6CAA6C;AAAA,EAC/C,QAAQ;AACV;AACA,SAAS,qBAAqB,YAAY;AACxC,SAAO,qBAAqB,UAAU;AACxC;AACA,SAAS,uBAAuBA,SAAQ,gBAAgB,CAAC,GAAG;AAC1D,SAAO,uBAAuBA,SAAQ,sBAAsB,iBAAiB,OAAO,EAAE,cAAc,eAAe,aAAa;AAClI;AACA,SAAS,eAAe,YAAY;AAClC,MAAI,cAAc,MAAM;AACtB,WAAO;AAAA,EACT;AACA,MAAI,OAAO,eAAe,UAAU;AAClC,UAAM,YAAY,cAAc,6CAA6C,2CAA2C,cAAc;AACtI,UAAMA,UAAS,EAAE,WAAW,QAAQ,CAAC,EAAE;AACvC,WAAO,uBAAuBA,OAAM;AAAA,EACtC,WAAW,sBAAsB,aAAa;AAC5C,WAAO;AAAA,EACT,OAAO;AACL,WAAO,uBAAuB,UAAU;AAAA,EAC1C;AACF;AAGA,IAAI,OAAO,cAAc,MAAM;AAAA,EAC7B,YAAY,MAAM;AAChB,UAAM,QAAQ,OAAO,CAAC,IAAI,IAAI;AAC9B,SAAK,kBAAkB;AACvB,QAAI,QAAQ,MAAM;AAChB,WAAK,WAAW,KAAK;AAAA,IACvB;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,aAAS,oBAAoB,MAAM;AACnC,QAAI,SAAS,KAAK,MAAM;AACxB,QAAI,KAAK,YAAY,MAAM;AACzB,eAAS,YAAY,QAAQ,GAAG,KAAK,QAAQ;AAAA,IAC/C;AACA,WAAO;AAAA,EACT;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,EAAE,UAAU,KAAK,SAAS;AACzC,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,KAAK,YAAY;AACjB,sBAAsB,cAAc,IAAI;AACxC,IAAI,YAAY,cAAc,MAAM;AAAA,EAClC,YAAY,MAAM;AAChB,UAAM,QAAQ,OAAO,CAAC,IAAI,IAAI;AAC9B,SAAK,gBAAgB;AACrB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,SAAK,QAAQ,KAAK,SAAS,OAAO,KAAK,gBAAgB,KAAK;AAAA,EAC9D;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,UAAM,IAAI,oBAAoB,MAAM;AACpC,WAAO,UAAU,GAAG,KAAK,KAAK;AAAA,EAChC;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,EAAE,OAAO,KAAK,MAAM;AACnC,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,UAAU,YAAY;AACtB,sBAAsB,cAAc,SAAS;AAC7C,IAAI,QAAQ,cAAc,MAAM;AAAA,EAC9B,YAAY,MAAM;AAChB,UAAM,QAAQ,OAAO,CAAC,IAAI,IAAI;AAC9B,SAAK,4BAA4B;AACjC,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,SAAK,kBAAkB;AACvB,SAAK,mBAAmB,eAAe,KAAK,oBAAoB,KAAK,yBAAyB;AAC9F,SAAK,mBAAmB,eAAe,KAAK,gBAAgB;AAC5D,SAAK,kBAAkB,cAAc,KAAK,eAAe;AACzD,QAAI,KAAK,cAAc,MAAM;AAC3B,WAAK,aAAa;AAAA,IACpB,WAAW,MAAM,QAAQ,KAAK,UAAU,GAAG;AACzC,WAAK,aAAa,KAAK;AAAA,IACzB,WAAW,OAAO,KAAK,eAAe,UAAU;AAC9C,WAAK,aAAa,CAAC,KAAK,UAAU;AAAA,IACpC,OAAO;AACL,YAAM,IAAI,WAAW,sEAAsE,KAAK,YAAY;AAAA,IAC9G;AAAA,EACF;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,aAAa,WAAW,MAAM,CAAC;AACrC,QAAI,KAAK,cAAc,MAAM;AAC3B,iBAAW,MAAM,KAAK,YAAY;AAChC,mBAAW,KAAK,KAAK;AAAA,MACvB;AAAA,IACF;AACA,SAAK,QAAQ,KAAK,UAAU,SAAS,YAAY,WAAW,KAAK,kBAAkB,KAAK,kBAAkB,MAAM,KAAK,eAAe;AACpI,UAAM,OAAO,CAAC;AACd,QAAI,KAAK,cAAc,MAAM;AAC3B,eAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,aAAK,MAAM,WAAW;AAAA,MACxB;AAAA,IACF;AACA,SAAK,YAAY,CAAC,IAAI,UAAU;AAAA,MAC9B,MAAM,WAAW;AAAA,MACjB;AAAA,IACF,CAAC,CAAC;AACF,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,aAAS,oBAAoB,MAAM;AACnC,WAAO,MAAM,QAAQ,KAAK,MAAM,KAAK,CAAC;AAAA,EACxC;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,kBAAkB,qBAAqB,KAAK,gBAAgB;AAAA,MAC5D,kBAAkB,qBAAqB,KAAK,gBAAgB;AAAA,MAC5D,iBAAiB,oBAAoB,KAAK,eAAe;AAAA,MACzD,YAAY,KAAK;AAAA,IACnB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,MAAM,YAAY;AAClB,sBAAsB,cAAc,KAAK;AACzC,IAAI,MAAM,cAAc,MAAM;AAAA,EAC5B,YAAY,MAAM;AAChB,UAAM,QAAQ,OAAO,CAAC,IAAI,IAAI;AAC9B,SAAK,gBAAgB;AACrB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,QAAI,KAAK,SAAS,QAAQ,KAAK,UAAU,KAAK,eAAe;AAC3D,YAAM,IAAI,oBAAoB,4BAA4B,KAAK,+CAA+C;AAAA,IAChH;AACA,SAAK,QAAQ,KAAK,SAAS,OAAO,KAAK,gBAAgB,KAAK;AAAA,EAC9D;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,UAAM,IAAI,oBAAoB,MAAM;AACpC,WAAO,IAAI,CAAC;AAAA,EACd;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,EAAE,OAAO,KAAK,MAAM;AACnC,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,IAAI,YAAY;AAChB,sBAAsB,cAAc,GAAG;AACvC,IAAI,kBAAkB,cAAc,MAAM;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM,QAAQ,OAAO,CAAC,IAAI,IAAI;AAC9B,SAAK,gBAAgB;AACrB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,SAAK,QAAQ,KAAK,SAAS,OAAO,KAAK,gBAAgB,KAAK;AAAA,EAC9D;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,UAAM,IAAI,oBAAoB,MAAM;AACpC,WAAO,IAAI,GAAG,KAAK,QAAQ,GAAG,KAAK,KAAK,GAAG,SAAS,CAAC;AAAA,EACvD;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,EAAE,OAAO,KAAK,MAAM;AACnC,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,IAAI,WAAW,cAAc,MAAM;AAAA,EACjC,YAAY,MAAM;AAChB,UAAM,QAAQ,OAAO,CAAC,IAAI,IAAI;AAC9B,SAAK,eAAe;AACpB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,SAAK,UAAU,IAAI,SAAS,EAAE;AAC9B,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,eAAe,KAAK;AAAA,EAC3D;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,UAAM,IAAI,oBAAoB,MAAM;AACpC,WAAO,KAAK,QAAQ,GAAG,KAAK,IAAI;AAAA,EAClC;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,EAAE,MAAM,KAAK,KAAK;AACjC,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAG5C,SAAS,eAAe,OAAO,IAAI,MAAM;AACvC,MAAI,OAAO,UAAU,UAAU;AAC7B,WAAO,aAAa,OAAO,EAAE;AAAA,EAC/B,OAAO;AACL,QAAI,MAAM,WAAW,IAAI;AACvB,YAAM,IAAI,WAAW,OAAO,gDAAgD,0BAA0B,MAAM,kBAAkB;AAAA,IAChI;AACA,aAAS,KAAK,GAAG,KAAK,IAAI,EAAE,IAAI;AAC9B,YAAM,cAAc,MAAM;AAC1B,UAAI,CAAC,UAAU,WAAW,GAAG;AAC3B,cAAM,IAAI,WAAW,OAAO,gDAAgD,0BAA0B,KAAK,UAAU,KAAK,oCAAoC,aAAa;AAAA,MAC7K;AAAA,IACF;AACA,WAAO;AAAA,EACT;AACF;AACA,SAAS,iBAAiB,aAAa,YAAYa,UAAS,QAAQ,WAAW,GAAG;AAChF,MAAI,eAAe,MAAM;AACvB,WAAO;AAAA,EACT;AACA,QAAM,oBAAoB,cAAc,aAAa,MAAM,WAAW;AACtE,MAAI;AACJ,MAAIA,aAAY,QAAQ;AACtB,mBAAe;AAAA,EACjB,OAAO;AACL,mBAAe,cAAc,oBAAoB;AAAA,EACnD;AACA,SAAO,KAAK,OAAO,eAAe,SAAS,KAAK,MAAM;AACxD;AACA,SAAS,aAAa,SAAS,YAAY,YAAYA,UAAS;AAC9D,MAAI,WAAW,MAAM;AACnB,WAAO;AAAA,EACT;AACA,MAAIA,aAAY,SAAS;AACvB,cAAU,UAAU,aAAa,KAAK,CAAC,aAAa,YAAY,CAAC,CAAC;AAAA,EACpE,WAAWA,aAAY,QAAQ;AAC7B,cAAU,UAAU;AAAA,EACtB,OAAO;AACL,UAAM,IAAI,WAAW,2BAA2BA,WAAU;AAAA,EAC5D;AACA,SAAO;AACT;AAGA,SAAS,sBAAsB,GAAG,YAAY;AAC5C,SAAO,KAAK,MAAM;AAChB,oBAAgB,UAAU;AAC1B,QAAI,eAAe,iBAAiB;AAClC,aAAO,UAAU,GAAG,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,IAClC,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF,CAAC;AACH;AACA,SAAS,sBAAsB,GAAG,YAAY;AAC5C,SAAO,KAAK,MAAM;AAChB,oBAAgB,UAAU;AAC1B,QAAI,eAAe,iBAAiB;AAClC,aAAO,UAAU,GAAG,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,IACrC,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF,CAAC;AACH;AACA,SAAS,eAAe,GAAG,QAAQ,MAAMf,WAAU,GAAGe,WAAU,SAAS,YAAY,eAAe,GAAG;AACrG,SAAO,KAAK,MAAM;AAChB,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,oBAAgB,UAAU;AAC1B,QAAI,EAAE,MAAM,WAAW,GAAG;AACxB,YAAM,IAAI,WAAW,+DAA+D,EAAE,MAAM,iBAAiB;AAAA,IAC/G;AACA,QAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,YAAM,IAAI,WAAW,iEAAiE,OAAO,MAAM,gBAAgB;AAAA,IACrH;AACA,QAAI,QAAQ,QAAQ,KAAK,MAAM,WAAW,GAAG;AAC3C,YAAM,IAAI,WAAW,+DAA+D,OAAO,MAAM,gBAAgB;AAAA,IACnH;AACA,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC;AAAA,IAC5B;AACA,QAAIA,aAAY,UAAU;AACxB,YAAM,IAAI,oBAAoB,+EAA+E;AAAA,IAC/G;AACA,QAAI,IAAI,OAAO,GAAG,QAAQf,UAASe,aAAY,SAAS,SAAS,SAAS,OAAO,YAAY;AAC7F,QAAI,QAAQ,MAAM;AAChB,UAAI,QAAQ,GAAG,IAAI;AAAA,IACrB;AACA,WAAO;AAAA,EACT,CAAC;AACH;AACA,SAAS,yBAAyB,GAAG,QAAQ,MAAMf,WAAU,CAAC,GAAG,CAAC,GAAGe,WAAU,SAAS,YAAY,cAAc,cAAc,MAAM;AACpI,SAAO,KAAK,MAAM;AAChB,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,oBAAgB,UAAU;AAC1B,QAAI,EAAE,SAAS,KAAK,EAAE,SAAS,GAAG;AAChC,YAAM,IAAI,WAAW,6EAA6E,EAAE,OAAO;AAAA,IAC7G;AACA,QAAI,OAAO,SAAS,KAAK,OAAO,SAAS,GAAG;AAC1C,YAAM,IAAI,WAAW,8EAA8E,EAAE,OAAO;AAAA,IAC9G;AACA,QAAI,IAAI,sBAAsB,GAAG,UAAU;AAC3C,QAAIA,aAAY,UAAU;AACxB,YAAM,IAAI,oBAAoB,+EAA+E;AAAA,IAC/G;AACA,QAAI,kBAAkB,OAAO;AAAA,MAC3B,GAAG;AAAA,MACH,QAAQ;AAAA,MACR,SAAAf;AAAA,MACA,KAAKe,aAAY,SAAS,SAAS;AAAA,MACnC,WAAW;AAAA,MACX,YAAY;AAAA,MACZ;AAAA,MACA,YAAY;AAAA,IACd,CAAC;AACD,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,GAAG,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,IAC/B;AACA,WAAO;AAAA,EACT,CAAC;AACH;AACA,SAAS,eAAe,GAAG,QAAQ,MAAMf,WAAU,CAAC,GAAG,GAAG,CAAC,GAAGe,WAAU,SAAS,YAAY,cAAc;AACzG,SAAO,KAAK,MAAM;AAChB,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,oBAAgB,UAAU;AAC1B,QAAI,EAAE,SAAS,KAAK,EAAE,SAAS,GAAG;AAChC,YAAM,IAAI,WAAW,mEAAmE,EAAE,OAAO;AAAA,IACnG;AACA,QAAI,OAAO,SAAS,KAAK,OAAO,SAAS,GAAG;AAC1C,YAAM,IAAI,WAAW,oEAAoE,EAAE,OAAO;AAAA,IACpG;AACA,QAAI,IAAI,sBAAsB,GAAG,UAAU;AAC3C,QAAIA,aAAY,UAAU;AACxB,YAAM,IAAI,oBAAoB,+EAA+E;AAAA,IAC/G;AACA,QAAI,OAAO,GAAG,QAAQf,UAASe,aAAY,SAAS,SAAS,SAAS,SAAS,YAAY;AAC3F,QAAI,QAAQ,MAAM;AAChB,UAAI,QAAQ,GAAG,IAAI;AAAA,IACrB;AACA,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,GAAG,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,IAClC;AACA,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,WAAW,cAAc,MAAM;AAAA,EACjC,YAAY,MAAM,MAAM;AACtB,UAAM,IAAI;AACV,SAAK,OAAO;AACZ,SAAK,6BAA6B;AAClC,SAAK,2BAA2B;AAChC,aAAS,WAAW,IAAI;AACxB,SAAK,OAAO;AACZ,0BAAsB,KAAK,MAAM,MAAM;AACvC,QAAI,KAAK,SAAS,KAAK,KAAK,SAAS,KAAK,KAAK,SAAS,GAAG;AACzD,YAAM,IAAI,oBAAoB,qDAAqD,KAAK,+BAA+B;AAAA,IACzH;AACA,SAAK,aAAa,eAAe,KAAK,YAAY,MAAM,YAAY;AACpE,SAAK,UAAU,eAAe,KAAK,WAAW,OAAO,IAAI,KAAK,SAAS,MAAM,SAAS;AACtF,SAAK,UAAU,KAAK,WAAW,OAAO,UAAU,KAAK;AACrD,qBAAiB,KAAK,OAAO;AAC7B,SAAK,aAAa,KAAK,cAAc,OAAO,iBAAiB,KAAK;AAClE,oBAAgB,KAAK,UAAU;AAC/B,SAAK,aAAa,cAAc,KAAK,UAAU;AAC/C,SAAK,UAAU,KAAK,WAAW,OAAO,OAAO,KAAK;AAClD,SAAK,kBAAkB,eAAe,KAAK,mBAAmB,KAAK,wBAAwB;AAC3F,SAAK,iBAAiB,cAAc,KAAK,cAAc;AACvD,SAAK,kBAAkB,eAAe,KAAK,eAAe;AAC1D,SAAK,sBAAsB,eAAe,KAAK,mBAAmB;AAClE,SAAK,eAAe,eAAe,KAAK,gBAAgB,OAAO,IAAI,KAAK,cAAc,MAAM,cAAc;AAC1G,QAAI,KAAK,SAAS,MAAM,MAAM,QAAQ,KAAK,YAAY,KAAK,KAAK,aAAa,WAAW,IAAI;AAC3F,YAAM,IAAI,WAAW,iGAAiG,KAAK,UAAU,KAAK,YAAY,GAAG;AAAA,IAC3J,WAAW,KAAK,SAAS,GAAG;AAC1B,UAAI,OAAO,KAAK,iBAAiB,UAAU;AACzC,aAAK,eAAe,CAAC,KAAK,cAAc,KAAK,YAAY;AAAA,MAC3D,WAAW,KAAK,aAAa,WAAW,GAAG;AACzC,cAAM,IAAI,WAAW,0FAA0F,KAAK,UAAU,KAAK,YAAY,GAAG;AAAA,MACpJ;AAAA,IACF,WAAW,KAAK,SAAS,GAAG;AAC1B,UAAI,OAAO,KAAK,iBAAiB,UAAU;AACzC,aAAK,eAAe,CAAC,KAAK,cAAc,KAAK,cAAc,KAAK,YAAY;AAAA,MAC9E,WAAW,KAAK,aAAa,WAAW,GAAG;AACzC,cAAM,IAAI,WAAW,4FAA4F,KAAK,UAAU,KAAK,YAAY,GAAG;AAAA,MACtJ;AAAA,IACF;AAAA,EACF;AAAA,EACA,OAAO,WAAW,MAAM;AACtB,YAAQ,gBAAgB,MAAM,yCAAyC;AACvE,QAAI,OAAO,KAAK,eAAe,YAAY,CAAC,wBAAwB,KAAK,YAAY,UAAU,GAAG,CAAC,GAAG;AACpG,YAAM,IAAI,WAAW,oGAAoG,KAAK,UAAU,KAAK,UAAU,IAAI;AAAA,IAC7J;AAAA,EACF;AAAA,EACA,YAAY;AACV,UAAMb,UAAS;AAAA,MACb,YAAY,KAAK;AAAA,MACjB,SAAS,KAAK;AAAA,MACd,SAAS,KAAK;AAAA,MACd,YAAY,KAAK;AAAA,MACjB,cAAc,KAAK;AAAA,MACnB,YAAY,oBAAoB,KAAK,UAAU;AAAA,MAC/C,SAAS,KAAK;AAAA,MACd,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,qBAAqB,qBAAqB,KAAK,mBAAmB;AAAA,MAClE,gBAAgB,oBAAoB,KAAK,cAAc;AAAA,IACzD;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,IAAI,OAAO,cAAc,SAAS;AAAA,EAChC,YAAY,MAAM,MAAM;AACtB,UAAM,MAAM,IAAI;AAChB,SAAK,SAAS;AACd,SAAK,WAAW,IAAI;AACpB,SAAK,UAAU,KAAK;AACpB,0BAAsB,KAAK,SAAS,SAAS;AAC7C,SAAK,oBAAoB,eAAe,KAAK,qBAAqB,KAAK,0BAA0B;AACjG,SAAK,mBAAmB,cAAc,KAAK,gBAAgB;AAC3D,SAAK,oBAAoB,eAAe,KAAK,iBAAiB;AAAA,EAChE;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,cAAc,KAAK,eAAe,kBAAkB,IAAI,WAAW,SAAS;AAClF,QAAI,WAAW,gBAAgB,MAAM;AACnC,YAAM,IAAI,WAAW,+DAA+D,WAAW,cAAc;AAAA,IAC/G;AACA,UAAM,WAAW,WAAW;AAC5B,UAAM,cAAc,KAAK,WAAW,OAAO,CAAC,UAAU,KAAK,OAAO,CAAC;AACnE,SAAK,SAAS,KAAK,UAAU,UAAU,aAAa,MAAM,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AACrI,QAAI,KAAK,SAAS;AAChB,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,OAAO,GAAG,MAAM,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IAChI;AACA,SAAK,YAAY,CAAC,EAAE,MAAM,KAAK,OAAO,GAAG,MAAM,EAAE,CAAC,cAAc,SAAS,EAAE,CAAC;AAC5E,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS,oBAAoB,MAAM;AACnC,UAAI;AACJ,YAAM,YAAY,KAAK,QAAQ,OAAO,OAAO,KAAK,KAAK,KAAK;AAC5D,YAAM,sBAAsB,2BAA2B,KAAK,WAAW,aAAa,CAAC;AACrF,UAAI,uBAAuB,QAAQ,KAAK,SAAS,GAAG;AAClD,kBAAU,yBAAyB,QAAQ,KAAK,OAAO,KAAK,GAAG,WAAW,KAAK,SAAS,KAAK,SAAS,KAAK,YAAY,KAAK,cAAc,mBAAmB;AAAA,MAC/J,OAAO;AACL,YAAI,KAAK,SAAS,GAAG;AACnB,oBAAU,eAAe,QAAQ,KAAK,OAAO,KAAK,GAAG,WAAW,KAAK,QAAQ,IAAI,KAAK,SAAS,KAAK,YAAY,KAAK,aAAa,EAAE;AAAA,QACtI,WAAW,KAAK,SAAS,GAAG;AAC1B,oBAAU,yBAAyB,QAAQ,KAAK,OAAO,KAAK,GAAG,WAAW,KAAK,SAAS,KAAK,SAAS,KAAK,YAAY,KAAK,YAAY;AAAA,QAC1I,WAAW,KAAK,SAAS,GAAG;AAC1B,oBAAU,eAAe,QAAQ,KAAK,OAAO,KAAK,GAAG,WAAW,KAAK,SAAS,KAAK,SAAS,KAAK,YAAY,KAAK,YAAY;AAAA,QAChI,OAAO;AACL,gBAAM,IAAI,oBAAoB,uDAAuD;AAAA,QACvF;AACA,YAAI,KAAK,cAAc,MAAM;AAC3B,oBAAU,KAAK,WAAW,MAAM,OAAO;AAAA,QACzC;AAAA,MACF;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,WAAW,CAAC;AAClB,UAAM,QAAQ,KAAK,eAAe,iBAAiB,WAAW,MAAM,GAAG,WAAW,SAAS,CAAC,IAAI,WAAW,MAAM,CAAC;AAClH,aAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,YAAM,SAAS,iBAAiB,MAAM,KAAK,KAAK,WAAW,KAAK,KAAK,SAAS,KAAK,QAAQ,KAAK,OAAO,KAAK,iBAAiB,WAAW,KAAK,eAAe,KAAK,aAAa,GAAG;AACjL,eAAS,KAAK,MAAM;AAAA,IACtB;AACA,QAAI,cAAc,CAAC,WAAW,EAAE;AAChC,QAAI,KAAK,eAAe,gBAAgB;AACtC,oBAAc,YAAY,OAAO,QAAQ;AACzC,kBAAY,KAAK,KAAK,OAAO;AAAA,IAC/B,OAAO;AACL,kBAAY,KAAK,KAAK,OAAO;AAC7B,oBAAc,YAAY,OAAO,QAAQ;AAAA,IAC3C;AACA,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,SAAS,KAAK;AAAA,MACd,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,kBAAkB,oBAAoB,KAAK,gBAAgB;AAAA,IAC7D;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,OAAO,WAAW,MAAM;AACtB,QAAI,EAAE,aAAa,SAAS,OAAO,KAAK,YAAY,YAAY,KAAK,UAAU,GAAG;AAChF,YAAM,IAAI,WAAW,0EAA0E,KAAK,UAAU,KAAK,OAAO,GAAG;AAAA,IAC/H;AAAA,EACF;AACF;AACA,IAAI,UAAU,cAAc,KAAK;AAAA,EAC/B,YAAY,MAAM;AAChB,UAAM,GAAG,IAAI;AACb,YAAQ,WAAW,IAAI;AAAA,EACzB;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,MAAM,UAAU;AAC/B,WAAOA,QAAO;AACd,WAAOA;AAAA,EACT;AAAA,EACA,OAAO,WAAW,MAAM;AACtB,QAAI,OAAO,KAAK,eAAe,YAAY,CAAC,wBAAwB,KAAK,YAAY,UAAU,GAAG,CAAC,GAAG;AACpG,YAAM,IAAI,WAAW,8FAA8F,KAAK,UAAU,KAAK,UAAU,IAAI;AAAA,IACvJ;AAAA,EACF;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,UAAU,cAAc,KAAK;AAAA,EAC/B,YAAY,MAAM;AAChB,UAAM,GAAG,IAAI;AACb,YAAQ,WAAW,IAAI;AAAA,EACzB;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,MAAM,UAAU;AAC/B,WAAOA,QAAO;AACd,WAAOA;AAAA,EACT;AAAA,EACA,OAAO,WAAW,MAAM;AACtB,QAAI,OAAO,KAAK,eAAe,UAAU;AACvC,UAAI,EAAE,MAAM,QAAQ,KAAK,UAAU,MAAM,KAAK,WAAW,WAAW,KAAK,KAAK,WAAW,WAAW,KAAK;AACvG,cAAM,IAAI,WAAW,2FAA2F,KAAK,UAAU,KAAK,UAAU,IAAI;AAAA,MACpJ;AAAA,IACF;AAAA,EACF;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,kBAAkB,cAAc,QAAQ;AAAA,EAC1C,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAC5C,QAAI,KAAK,YAAY,UAAU,KAAK,YAAY,SAAS;AACvD,YAAM,IAAI,WAAW,uGAAuG,KAAK,SAAS;AAAA,IAC5I;AAAA,EACF;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,WAAW,WAAW,GAAG;AAC3B,YAAM,IAAI,WAAW,qDAAqD,KAAK,UAAU,UAAU,CAAC;AAAA,IACtG;AACA,UAAM,cAAc,KAAK,eAAe,kBAAkB,IAAI,WAAW,SAAS;AAClF,QAAI,WAAW,gBAAgB,MAAM;AACnC,YAAM,IAAI,WAAW,sEAAsE;AAAA,IAC7F;AACA,UAAM,WAAW,WAAW;AAC5B,UAAM,cAAc,KAAK,WAAW,OAAO,CAAC,KAAK,SAAS,QAAQ,CAAC;AACnE,SAAK,SAAS,KAAK,UAAU,UAAU,aAAa,WAAW,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AAC1I,QAAI,KAAK,SAAS;AAChB,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,OAAO,GAAG,WAAW,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IACrI;AACA,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,GAAG,MAAM,EAAE,CAAC,cAAc,SAAS,EAAE,CAAC,CAAC;AAC/E,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,oBAAoB,MAAM;AACvC,UAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,cAAM,IAAI,WAAW,2FAA2F,OAAO,MAAM,QAAQ;AAAA,MACvI;AACA,YAAM,aAAa,OAAO;AAC1B,YAAM,YAAY,WAAW;AAC7B,UAAI;AACJ,UAAI;AACJ,UAAI,KAAK,eAAe,iBAAiB;AACvC,gBAAQ;AACR,gBAAQ;AAAA,MACV,OAAO;AACL,gBAAQ;AACR,gBAAQ;AAAA,MACV;AACA,YAAM,SAAS,WAAW;AAC1B,YAAM,QAAQ,WAAW;AACzB,YAAM,UAAU,KAAK,WAAW;AAChC,YAAM,UAAU,KAAK,WAAW;AAChC,YAAM,UAAU,KAAK,QAAQ;AAC7B,YAAM,UAAU,KAAK,QAAQ;AAC7B,YAAM,YAAY,aAAa,QAAQ,SAAS,SAAS,KAAK,OAAO;AACrE,YAAM,WAAW,aAAa,OAAO,SAAS,SAAS,KAAK,OAAO;AACnE,YAAM,cAAc,CAAC,WAAW,WAAW,UAAU,KAAK,OAAO;AACjE,UAAI,KAAK,eAAe,gBAAgB;AACtC,iBAAS,UAAU,QAAQ,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,MACzC;AACA,UAAI,UAAU,gBAAgB,QAAQ,KAAK,OAAO,KAAK,GAAG,aAAa,KAAK,SAAS,KAAK,OAAO;AACjG,UAAI,KAAK,eAAe,gBAAgB;AACtC,kBAAU,UAAU,SAAS,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,MAC3C;AACA,UAAI,KAAK,QAAQ,MAAM;AACrB,kBAAU,QAAQ,SAAS,KAAK,KAAK,KAAK,GAAG,KAAK,UAAU;AAAA,MAC9D;AACA,UAAI,KAAK,cAAc,MAAM;AAC3B,kBAAU,KAAK,WAAW,MAAM,OAAO;AAAA,MACzC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,cAAc,WAAW,MAAM;AACrC,QAAI;AACJ,QAAI;AACJ,QAAI;AACJ,QAAI,KAAK,eAAe,iBAAiB;AACvC,oBAAc;AACd,mBAAa;AACb,kBAAY;AAAA,IACd,OAAO;AACL,oBAAc;AACd,mBAAa;AACb,kBAAY;AAAA,IACd;AACA,UAAM,UAAU,KAAK,WAAW;AAChC,UAAM,UAAU,KAAK,WAAW;AAChC,UAAM,UAAU,KAAK,QAAQ;AAC7B,UAAM,UAAU,KAAK,QAAQ;AAC7B,gBAAY,eAAe,KAAK;AAChC,gBAAY,cAAc,aAAa,YAAY,aAAa,SAAS,SAAS,KAAK,OAAO;AAC9F,gBAAY,aAAa,aAAa,YAAY,YAAY,SAAS,SAAS,KAAK,OAAO;AAC5F,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,MAAM,UAAU;AAC/B,WAAOA,QAAO;AACd,WAAOA;AAAA,EACT;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,IAAI,kBAAkB,cAAc,QAAQ;AAAA,EAC1C,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAC5C,QAAI,KAAK,YAAY,UAAU,KAAK,YAAY,SAAS;AACvD,YAAM,IAAI,WAAW,uGAAuG,KAAK,SAAS;AAAA,IAC5I;AAAA,EACF;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,WAAW,WAAW,GAAG;AAC3B,YAAM,IAAI,WAAW,qDAAqD,KAAK,UAAU,UAAU,CAAC;AAAA,IACtG;AACA,UAAM,cAAc,KAAK,eAAe,kBAAkB,IAAI,WAAW,SAAS;AAClF,QAAI,WAAW,gBAAgB,MAAM;AACnC,YAAM,IAAI,WAAW,sEAAsE;AAAA,IAC7F;AACA,UAAM,WAAW,WAAW;AAC5B,UAAM,cAAc,KAAK,WAAW,OAAO,CAAC,KAAK,SAAS,QAAQ,CAAC;AACnE,SAAK,SAAS,KAAK,UAAU,UAAU,aAAa,WAAW,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AAC1I,QAAI,KAAK,SAAS;AAChB,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,OAAO,GAAG,WAAW,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IACrI;AACA,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,GAAG,MAAM,EAAE,CAAC,cAAc,SAAS,EAAE,CAAC,CAAC;AAC/E,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,oBAAoB,MAAM;AACvC,UAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,cAAM,IAAI,WAAW,2FAA2F,OAAO,MAAM,QAAQ;AAAA,MACvI;AACA,YAAM,aAAa,OAAO;AAC1B,YAAM,YAAY,WAAW;AAC7B,UAAI;AACJ,UAAI;AACJ,UAAI;AACJ,UAAI,KAAK,eAAe,iBAAiB;AACvC,gBAAQ;AACR,gBAAQ;AACR,gBAAQ;AAAA,MACV,OAAO;AACL,gBAAQ;AACR,gBAAQ;AACR,gBAAQ;AAAA,MACV;AACA,YAAM,QAAQ,WAAW;AACzB,YAAM,SAAS,WAAW;AAC1B,YAAM,QAAQ,WAAW;AACzB,YAAM,UAAU,KAAK,WAAW;AAChC,YAAM,UAAU,KAAK,WAAW;AAChC,YAAM,UAAU,KAAK,WAAW;AAChC,YAAM,UAAU,KAAK,QAAQ;AAC7B,YAAM,UAAU,KAAK,QAAQ;AAC7B,YAAM,UAAU,KAAK,QAAQ;AAC7B,YAAM,WAAW,aAAa,OAAO,SAAS,SAAS,KAAK,OAAO;AACnE,YAAM,YAAY,aAAa,QAAQ,SAAS,SAAS,KAAK,OAAO;AACrE,YAAM,WAAW,aAAa,OAAO,SAAS,SAAS,KAAK,OAAO;AACnE,YAAM,cAAc,CAAC,WAAW,UAAU,WAAW,UAAU,KAAK,OAAO;AAC3E,UAAI,KAAK,eAAe,gBAAgB;AACtC,iBAAS,UAAU,QAAQ,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,MAC5C;AACA,UAAI,UAAU,gBAAgB,QAAQ,KAAK,OAAO,KAAK,GAAG,aAAa,KAAK,SAAS,KAAK,OAAO;AACjG,UAAI,KAAK,eAAe,gBAAgB;AACtC,kBAAU,UAAU,SAAS,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,MAC9C;AACA,UAAI,KAAK,SAAS,MAAM;AACtB,kBAAU,QAAQ,SAAS,KAAK,KAAK,KAAK,GAAG,KAAK,UAAU;AAAA,MAC9D;AACA,UAAI,KAAK,eAAe,MAAM;AAC5B,kBAAU,KAAK,WAAW,MAAM,OAAO;AAAA,MACzC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,cAAc,WAAW,MAAM;AACrC,QAAI;AACJ,QAAI;AACJ,QAAI;AACJ,QAAI;AACJ,QAAI,KAAK,eAAe,iBAAiB;AACvC,oBAAc;AACd,kBAAY;AACZ,mBAAa;AACb,kBAAY;AAAA,IACd,OAAO;AACL,oBAAc;AACd,kBAAY;AACZ,mBAAa;AACb,kBAAY;AAAA,IACd;AACA,UAAM,UAAU,KAAK,WAAW;AAChC,UAAM,UAAU,KAAK,WAAW;AAChC,UAAM,UAAU,KAAK,WAAW;AAChC,UAAM,UAAU,KAAK,QAAQ;AAC7B,UAAM,UAAU,KAAK,QAAQ;AAC7B,UAAM,UAAU,KAAK,QAAQ;AAC7B,gBAAY,eAAe,KAAK;AAChC,gBAAY,aAAa,aAAa,YAAY,YAAY,SAAS,SAAS,KAAK,OAAO;AAC5F,gBAAY,cAAc,aAAa,YAAY,aAAa,SAAS,SAAS,KAAK,OAAO;AAC9F,gBAAY,aAAa,aAAa,YAAY,YAAY,SAAS,SAAS,KAAK,OAAO;AAC5F,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,MAAM,UAAU;AAC/B,WAAOA,QAAO;AACd,WAAOA;AAAA,EACT;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,IAAI,gBAAgB,cAAc,KAAK;AAAA,EACrC,YAAY,MAAMA,SAAQ;AACxB,UAAM,MAAMA,OAAM;AAClB,SAAK,gCAAgC;AACrC,SAAK,gCAAgC;AACrC,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AACvB,QAAIA,QAAO,WAAW,MAAM;AAC1B,YAAM,IAAI,WAAW,qFAAqF;AAAA,IAC5G;AACA,QAAIA,QAAO,qBAAqB,QAAQA,QAAO,qBAAqB,QAAQA,QAAO,oBAAoB,MAAM;AAC3G,YAAM,IAAI,WAAW,oPAAoP;AAAA,IAC3Q;AACA,QAAIA,QAAO,WAAW,QAAQA,QAAO,YAAY,UAAUA,QAAO,YAAY,SAAS;AACrF,YAAM,IAAI,WAAW,gBAAgB,KAAK,uEAAuE,KAAK,UAAUA,QAAO,OAAO,GAAG;AAAA,IACnJ;AACA,SAAK,kBAAkBA,QAAO,mBAAmB,OAAO,IAAIA,QAAO;AACnE,SAAK,uBAAuB,eAAeA,QAAO,wBAAwB,KAAK,6BAA6B;AAC5G,SAAK,uBAAuB,eAAeA,QAAO,oBAAoB;AACtE,SAAK,sBAAsB,cAAcA,QAAO,mBAAmB;AACnE,SAAK,uBAAuB,eAAeA,QAAO,wBAAwB,KAAK,6BAA6B;AAC5G,SAAK,uBAAuB,eAAeA,QAAO,oBAAoB;AACtE,SAAK,sBAAsB,cAAcA,QAAO,mBAAmB;AAAA,EACrE;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,WAAW,SAAS,KAAK,OAAO,GAAG;AACrC,YAAM,IAAI,WAAW,0BAA0B,KAAK,0BAA0B,KAAK,OAAO,gCAAgC,KAAK,UAAU,UAAU,GAAG;AAAA,IACxJ;AACA,UAAM,cAAc,KAAK,eAAe,kBAAkB,IAAI,WAAW,SAAS;AAClF,QAAI,WAAW,gBAAgB,QAAQ,WAAW,eAAe,GAAG;AAClE,YAAM,IAAI,WAAW,oEAAoE,KAAK,UAAU,WAAW,YAAY,GAAG;AAAA,IACpI;AACA,UAAM,WAAW,WAAW;AAC5B,UAAM,uBAAuB,KAAK,WAAW,OAAO,CAAC,UAAU,KAAK,eAAe,CAAC;AACpF,UAAM,uBAAuB,CAAC;AAC9B,aAAS,KAAK,GAAG,KAAK,KAAK,MAAM,EAAE,IAAI;AACrC,2BAAqB,KAAK,CAAC;AAAA,IAC7B;AACA,yBAAqB,KAAK,WAAW,KAAK,iBAAiB,KAAK,OAAO;AACvE,UAAM,YAAY;AAClB,SAAK,kBAAkB,KAAK,UAAU,oBAAoB,sBAAsB,WAAW,KAAK,sBAAsB,KAAK,sBAAsB,WAAW,KAAK,mBAAmB;AACpL,SAAK,kBAAkB,KAAK,UAAU,oBAAoB,sBAAsB,WAAW,KAAK,sBAAsB,KAAK,sBAAsB,WAAW,KAAK,mBAAmB;AACpL,QAAI,KAAK,SAAS;AAChB,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,OAAO,GAAG,WAAW,KAAK,iBAAiB,KAAK,iBAAiB,WAAW,KAAK,cAAc;AAAA,IAC1I,OAAO;AACL,WAAK,OAAO;AAAA,IACd;AACA,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,KAAK,OAAO,GAAG,MAAM,EAAE,CAAC,cAAc,SAAS,EAAE,CAAC,CAAC;AAC3F,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS,oBAAoB,MAAM;AACnC,UAAI;AACJ,UAAI,KAAK,SAAS,GAAG;AACnB,cAAM,IAAI,oBAAoB,kDAAkD;AAAA,MAClF,WAAW,KAAK,SAAS,GAAG;AAC1B,YAAI,KAAK,eAAe,iBAAiB;AACvC,mBAAS,UAAU,QAAQ,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,QACzC;AACA,iBAAS,gBAAgB,QAAQ,KAAK,gBAAgB,KAAK,GAAG,KAAK,gBAAgB,KAAK,GAAG,KAAK,SAAS,KAAK,SAAS,KAAK,cAAc,MAAM;AAAA,MAClJ;AACA,UAAI,KAAK,SAAS;AAChB,iBAAS,QAAQ,QAAQ,KAAK,KAAK,KAAK,GAAG,KAAK,UAAU;AAAA,MAC5D;AACA,UAAI,KAAK,cAAc,MAAM;AAC3B,iBAAS,KAAK,WAAW,MAAM,MAAM;AAAA,MACvC;AACA,UAAI,KAAK,eAAe,iBAAiB;AACvC,iBAAS,UAAU,QAAQ,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,MACzC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,MAAM,UAAU;AAC/B,WAAOA,QAAO;AACd,WAAOA,QAAO;AACd,WAAOA,QAAO;AACd,WAAOA,QAAO;AACd,IAAAA,QAAO,0BAA0B,qBAAqB,KAAK,oBAAoB;AAC/E,IAAAA,QAAO,0BAA0B,qBAAqB,KAAK,oBAAoB;AAC/E,IAAAA,QAAO,0BAA0B,qBAAqB,KAAK,oBAAoB;AAC/E,IAAAA,QAAO,0BAA0B,qBAAqB,KAAK,oBAAoB;AAC/E,IAAAA,QAAO,yBAAyB,oBAAoB,KAAK,mBAAmB;AAC5E,IAAAA,QAAO,yBAAyB,oBAAoB,KAAK,mBAAmB;AAC5E,WAAOA;AAAA,EACT;AACF;AACA,cAAc,YAAY;AAC1B,IAAI,kBAAkB,cAAc,cAAc;AAAA,EAChD,YAAY,MAAM;AAChB,UAAM,GAAG,IAAI;AAAA,EACf;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,IAAI,SAAS,cAAc,KAAK;AAAA,EAC9B,YAAY,MAAM;AAChB,UAAM,GAAG,IAAI;AACb,WAAO,WAAW,IAAI;AACtB,SAAK,YAAY,CAAC,EAAE,MAAM,EAAE,CAAC;AAAA,EAC/B;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,MAAM,UAAU;AAC/B,WAAOA,QAAO;AACd,WAAOA,QAAO;AACd,WAAOA;AAAA,EACT;AAAA,EACA,OAAO,WAAW,MAAM;AACtB,QAAI,OAAO,KAAK,eAAe,YAAY,CAAC,wBAAwB,KAAK,YAAY,UAAU,GAAG,CAAC,GAAG;AACpG,YAAM,IAAI,WAAW,yFAAyF,KAAK,UAAU,KAAK,UAAU,IAAI;AAAA,IAClJ;AAAA,EACF;AACF;AACA,OAAO,YAAY;AACnB,sBAAsB,cAAc,MAAM;AAC1C,IAAI,aAAa,cAAc,MAAM;AAAA,EACnC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,QAAI,OAAO,KAAK,aAAa,UAAU;AACrC,WAAK,WAAW,CAAC,CAAC,KAAK,UAAU,KAAK,QAAQ,GAAG,CAAC,KAAK,UAAU,KAAK,QAAQ,CAAC;AAAA,IACjF,WAAW,OAAO,KAAK,SAAS,OAAO,UAAU;AAC/C,WAAK,WAAW;AAAA,QACd,CAAC,KAAK,SAAS,IAAI,KAAK,SAAS,EAAE;AAAA,QACnC,CAAC,KAAK,SAAS,IAAI,KAAK,SAAS,EAAE;AAAA,MACrC;AAAA,IACF,OAAO;AACL,WAAK,WAAW,KAAK;AAAA,IACvB;AACA,SAAK,aAAa,KAAK,eAAe,SAAS,iBAAiB,KAAK;AACrE,SAAK,YAAY,CAAC,EAAE,MAAM,EAAE,CAAC;AAAA,EAC/B;AAAA,EACA,mBAAmB,YAAY;AAC7B,QAAI,KAAK,eAAe,iBAAiB;AACvC,aAAO;AAAA,QACL,WAAW;AAAA,QACX,WAAW;AAAA,QACX,WAAW,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG;AAAA,QACvD,WAAW,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG;AAAA,MACzD;AAAA,IACF,OAAO;AACL,aAAO;AAAA,QACL,WAAW;AAAA,QACX,WAAW,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG;AAAA,QACvD,WAAW,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG;AAAA,QACvD,WAAW;AAAA,MACb;AAAA,IACF;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS,oBAAoB,MAAM;AACnC,UAAI,KAAK,eAAe,gBAAgB;AACtC,cAAM,UAAU,eAAe,QAAQ,KAAK,SAAS,GAAG,IAAI,OAAO,MAAM,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG,IAAI,CAAC;AAC1H,eAAO,eAAe,SAAS,KAAK,SAAS,GAAG,IAAI,OAAO,MAAM,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG,IAAI,CAAC;AAAA,MACpH,OAAO;AACL,cAAM,UAAU,eAAe,QAAQ,KAAK,SAAS,GAAG,IAAI,OAAO,MAAM,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG,IAAI,CAAC;AAC1H,eAAO,eAAe,SAAS,KAAK,SAAS,GAAG,IAAI,OAAO,MAAM,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG,IAAI,CAAC;AAAA,MACpH;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,EAAE,UAAU,KAAK,UAAU,YAAY,KAAK,WAAW;AACtE,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,WAAW,YAAY;AACvB,sBAAsB,cAAc,UAAU;AAC9C,IAAI,eAAe,cAAc,MAAM;AAAA,EACrC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,eAAe,CAAC,GAAG,CAAC;AACzB,SAAK,YAAY,CAAC,EAAE,MAAM,EAAE,CAAC;AAC7B,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,eAAe,KAAK;AACzD,SAAK,aAAa,KAAK,cAAc,OAAO,iBAAiB,KAAK;AAClE,oBAAgB,KAAK,UAAU;AAC/B,SAAK,gBAAgB,KAAK,iBAAiB,OAAO,YAAY,KAAK;AACnE,6BAAyB,KAAK,aAAa;AAAA,EAC7C;AAAA,EACA,mBAAmB,YAAY;AAC7B,QAAI,KAAK,eAAe,iBAAiB;AACvC,YAAM,SAAS,WAAW,MAAM,OAAO,OAAO,KAAK,KAAK,KAAK,WAAW;AACxE,YAAM,QAAQ,WAAW,MAAM,OAAO,OAAO,KAAK,KAAK,KAAK,WAAW;AACvE,aAAO,CAAC,WAAW,IAAI,WAAW,IAAI,QAAQ,KAAK;AAAA,IACrD,OAAO;AACL,YAAM,SAAS,WAAW,MAAM,OAAO,OAAO,KAAK,KAAK,KAAK,WAAW;AACxE,YAAM,QAAQ,WAAW,MAAM,OAAO,OAAO,KAAK,KAAK,KAAK,WAAW;AACvE,aAAO,CAAC,WAAW,IAAI,QAAQ,OAAO,WAAW,EAAE;AAAA,IACrD;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,oBAAoB,MAAM;AACvC,YAAM,aAAa,OAAO;AAC1B,UAAI,KAAK,eAAe,iBAAiB;AACvC,iBAAS,UAAU,QAAQ,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AACvC,cAAM,SAAS,KAAK,KAAK,KAAK,WAAW;AACzC,cAAM,QAAQ,KAAK,KAAK,KAAK,WAAW;AACxC,cAAM,UAAU,KAAK,kBAAkB,YAAY,MAAM,sBAAsB,QAAQ,CAAC,QAAQ,KAAK,CAAC,IAAI,MAAM,eAAe,QAAQ,CAAC,QAAQ,KAAK,CAAC;AACtJ,eAAO,UAAU,SAAS,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,MACxC,OAAO;AACL,cAAM,SAAS,KAAK,KAAK,KAAK,WAAW;AACzC,cAAM,QAAQ,KAAK,KAAK,KAAK,WAAW;AACxC,eAAO,KAAK,kBAAkB,YAAY,MAAM,sBAAsB,QAAQ,CAAC,QAAQ,KAAK,CAAC,IAAI,MAAM,eAAe,QAAQ,CAAC,QAAQ,KAAK,CAAC;AAAA,MAC/I;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,MAAM,KAAK;AAAA,MACX,YAAY,KAAK;AAAA,MACjB,eAAe,KAAK;AAAA,IACtB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAGhD,SAAS,iBAAiB,GAAG,iBAAiBF,WAAU,CAAC,GAAG,CAAC,GAAGe,WAAU,SAAS,YAAY,cAAc;AAC3G,SAAO,KAAK,MAAM;AAChB,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,oBAAgB,UAAU;AAC1B,QAAI,IAAI,sBAAsB,GAAG,UAAU;AAC3C,QAAI,EAAE,SAAS,GAAG;AAChB,YAAM,IAAI,WAAW,mEAAmE,EAAE,QAAQ;AAAA,IACpG;AACA,QAAI,gBAAgB,SAAS,GAAG;AAC9B,YAAM,IAAI,WAAW,yDAAyD,gBAAgB,QAAQ;AAAA,IACxG;AACA,QAAI,gBAAgB,GAAG,iBAAiBf,UAASe,aAAY,SAAS,SAAS,SAAS,QAAQ,YAAY;AAC5G,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,GAAG,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,IAC/B;AACA,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,kBAAkB,cAAc,SAAS;AAAA,EAC3C,YAAY,MAAM;AAChB,UAAM,GAAG,IAAI;AACb,SAAK,kBAAkB;AACvB,SAAK,kBAAkB,KAAK,mBAAmB,OAAO,IAAI,KAAK;AAC/D,SAAK,uBAAuB,eAAe,KAAK,wBAAwB,KAAK,0BAA0B;AACvG,SAAK,sBAAsB,cAAc,KAAK,mBAAmB;AACjE,SAAK,uBAAuB,eAAe,KAAK,oBAAoB;AAAA,EACtE;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,WAAW,SAAS,GAAG;AACzB,YAAM,IAAI,WAAW,uEAAuE,KAAK,UAAU,UAAU,IAAI;AAAA,IAC3H;AACA,UAAM,cAAc,KAAK,eAAe,kBAAkB,IAAI;AAC9D,QAAI,WAAW,gBAAgB,QAAQ,WAAW,eAAe,GAAG;AAClE,YAAM,IAAI,WAAW,yFAAyF,WAAW,gBAAgB;AAAA,IAC3I;AACA,UAAM,WAAW,WAAW;AAC5B,UAAM,uBAAuB;AAAA,MAC3B,KAAK,WAAW;AAAA,MAChB,KAAK,WAAW;AAAA,MAChB;AAAA,MACA,KAAK;AAAA,IACP;AACA,SAAK,kBAAkB,KAAK,UAAU,oBAAoB,sBAAsB,MAAM,KAAK,sBAAsB,KAAK,sBAAsB,MAAM,KAAK,mBAAmB;AAC1K,QAAI,KAAK,SAAS;AAChB,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,WAAW,KAAK,eAAe,GAAG,MAAM,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IACnJ,OAAO;AACL,WAAK,OAAO;AAAA,IACd;AACA,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS,oBAAoB,MAAM;AACnC,UAAI,UAAU,iBAAiB,QAAQ,KAAK,gBAAgB,KAAK,GAAG,KAAK,SAAS,KAAK,SAAS,KAAK,YAAY,IAAI;AACrH,UAAI,KAAK,SAAS;AAChB,kBAAU,QAAQ,SAAS,KAAK,KAAK,KAAK,GAAG,KAAK,UAAU;AAAA,MAC9D;AACA,UAAI,KAAK,cAAc,MAAM;AAC3B,kBAAU,KAAK,WAAW,MAAM,OAAO;AAAA,MACzC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,OAAO,KAAK,eAAe,kBAAkB,WAAW,KAAK,WAAW;AAC9E,UAAM,OAAO,KAAK,eAAe,kBAAkB,WAAW,KAAK,WAAW;AAC9E,UAAM,aAAa,KAAK,eAAe,kBAAkB,WAAW,KAAK,KAAK,kBAAkB,WAAW,KAAK,KAAK;AACrH,UAAM,UAAU,iBAAiB,MAAM,KAAK,WAAW,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AACxF,UAAM,UAAU,iBAAiB,MAAM,KAAK,WAAW,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AACxF,QAAI,KAAK,eAAe,iBAAiB;AACvC,aAAO,CAAC,WAAW,IAAI,YAAY,SAAS,OAAO;AAAA,IACrD,OAAO;AACL,aAAO,CAAC,WAAW,IAAI,SAAS,SAAS,UAAU;AAAA,IACrD;AAAA,EACF;AAAA,EACA,YAAY;AACV,UAAMb,UAAS,MAAM,UAAU;AAC/B,IAAAA,QAAO,qBAAqB,KAAK;AACjC,IAAAA,QAAO,0BAA0B,qBAAqB,KAAK,oBAAoB;AAC/E,IAAAA,QAAO,0BAA0B,qBAAqB,KAAK,oBAAoB;AAC/E,IAAAA,QAAO,yBAAyB,oBAAoB,KAAK,oBAAoB;AAC7E,WAAOA;AAAA,EACT;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AAGnD,SAAS,gBAAgB,QAAQ,cAAcgB,YAAW,cAAc;AACtE,MAAI,MAAM,QAAQ,MAAM,GAAG;AACzB,QAAI,gBAAgB,QAAQA,cAAa,MAAM;AAC7C,YAAM,IAAI,WAAW,+EAA+E;AAAA,IACtG;AACA,QAAI,gBAAgB,MAAM;AACxB,MAAAA,aAAY,OAAO,MAAM,OAAO,SAAS,cAAc,OAAO,MAAM;AACpE,eAAS,OAAO,MAAM,GAAG,OAAO,SAAS,YAAY;AAAA,IACvD;AACA,QAAI,OAAO,SAAS,GAAG;AACrB,qBAAe,OAAO,MAAM,GAAG,OAAO,MAAM;AAAA,IAC9C;AACA,aAAS,OAAO;AAAA,EAClB;AACA,WAAS,aAAa,GAAG;AACvB,QAAI,KAAK,QAAQ,MAAM,QAAQ,CAAC,GAAG;AACjC,aAAO;AAAA,IACT,OAAO;AACL,aAAO,CAAC,CAAC;AAAA,IACX;AAAA,EACF;AACA,iBAAe,aAAa,YAAY;AACxC,EAAAA,aAAY,aAAaA,UAAS;AAClC,SAAO,EAAE,QAAQ,cAAc,WAAAA,WAAU;AAC3C;AACA,SAAS,IAAI,cAAc,QAAQ,eAAe,cAAc,OAAOzB,OAAMyB,YAAW,SAAS,OAAO,qBAAqB,OAAO;AAClI,SAAO,KAAK,MAAM;AAChB,UAAM,OAAO,OAAO,MAAM;AAC1B,QAAI,OAAO,GAAG;AACZ,YAAM,IAAI,WAAW,uCAAuC,QAAQ;AAAA,IACtE;AACA,UAAM,OAAO,CAAC,GAAG,CAAC,EAAE,OAAO,OAAO,GAAG,IAAI,CAAC;AAC1C,aAAS,UAAU,QAAQ,IAAI;AAC/B,QAAIA,cAAa,MAAM;AACrB,YAAM,IAAI,oBAAoB,gFAAgF;AAAA,IAChH;AACA,QAAI,QAAQ;AACV,cAAQ,KAAK,mGAAmG;AAAA,IAClH;AACA,QAAIzB,SAAQ,MAAM;AAChB,MAAAA,QAAO,KAAK,KAAKA,OAAM,MAAM,GAAG,SAAS;AACzC,UAAIA,MAAK,SAAS,OAAO,GAAG;AAC1B,QAAAA,QAAO,WAAWA,OAAM,EAAE;AAAA,MAC5B;AACA,MAAAA,QAAO,UAAUA,OAAM,IAAI;AAAA,IAC7B;AACA,QAAI,aAAa;AACf,eAAS,QAAQ,QAAQ,CAAC;AAC1B,UAAIA,SAAQ,MAAM;AAChB,QAAAA,QAAO,QAAQA,OAAM,CAAC;AAAA,MACxB;AAAA,IACF;AACA,UAAM,iBAAiB,CAAC;AACxB,QAAI;AACJ,QAAI,SAAS;AACb,UAAM,YAAY,OAAO,MAAM;AAC/B,UAAM,gBAAgB,QAAQ,MAAM;AACpC,QAAI;AACJ,QAAIA,SAAQ,MAAM;AAChB,qBAAe,QAAQA,KAAI;AAAA,IAC7B;AACA,aAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,YAAM,eAAe,cAAc;AACnC,YAAM,cAAc,KAAK,MAAM,aAAa,cAAc,MAAM,CAAC;AACjE,UAAIA,SAAQ,MAAM;AAChB,qBAAa,YAAY;AACzB,iBAAS,YAAY;AAAA,MACvB,OAAO;AACL,cAAM,gBAAgB,KAAK,MAAM;AAC/B,gBAAM,WAAW,aAAa;AAC9B,gBAAM,cAAc,IAAI,SAAS,QAAQ,GAAG,QAAQ;AACpD,gBAAM,SAAS,KAAK,IAAI,YAAY,IAAI,QAAQ,GAAG,IAAI,OAAO,IAAI,WAAW,CAAC;AAC9E,gBAAM,YAAY,OAAO,IAAI,CAAC,OAAO,OAAO;AAC1C,mBAAO,KAAK,IAAI,YAAY,GAAG,KAAK,QAAQ,GAAG,IAAI,OAAO,WAAW,CAAC;AAAA,UACxE,CAAC;AACD,iBAAO,EAAE,QAAQ,UAAU;AAAA,QAC7B,CAAC;AACD,qBAAa,cAAc;AAC3B,iBAAS,cAAc;AAAA,MACzB;AACA,UAAI,oBAAoB;AACtB,uBAAe,KAAK,UAAU;AAAA,MAChC;AAAA,IACF;AACA,QAAI;AACJ,QAAI,oBAAoB;AACtB,YAAM,OAAO;AACb,gBAAU,MAAM,gBAAgB,IAAI;AAAA,IACtC;AACA,WAAO,CAAC,YAAY,SAAS,MAAM;AAAA,EACrC,CAAC;AACH;AACA,IAAI,MAAM,cAAc,MAAM;AAAA,EAC5B,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,QAAI;AACJ,QAAI,KAAK,QAAQ,MAAM;AACrB,YAAM,IAAI,WAAW,sDAAsD;AAAA,IAC7E,WAAW,MAAM,QAAQ,KAAK,IAAI,GAAG;AACnC,aAAO,IAAI,gBAAgB,EAAE,OAAO,KAAK,KAAK,CAAC;AAAA,IACjD,OAAO;AACL,aAAO,KAAK;AAAA,IACd;AACA,QAAI,KAAK,aAAa,MAAM;AAC1B,YAAM,IAAI,WAAW,mGAAmG;AAAA,IAC1H;AACA,SAAK,OAAO;AACZ,SAAK,kBAAkB,KAAK,mBAAmB,OAAO,QAAQ,KAAK;AACnE,SAAK,cAAc,KAAK,eAAe,OAAO,QAAQ,KAAK;AAC3D,SAAK,cAAc,KAAK,eAAe,OAAO,QAAQ,KAAK;AAC3D,SAAK,YAAY,KAAK,YAAY,OAAO,QAAQ,KAAK;AACtD,SAAK,SAAS,KAAK,UAAU,OAAO,QAAQ,KAAK;AACjD,SAAK,kBAAkB;AACvB,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAC5C,SAAK,YAAY;AACjB,SAAK,UAAU;AACf,SAAK,eAAe;AACpB,SAAK,aAAa,CAAC;AAAA,EACrB;AAAA,EACA,YAAY;AACV,QAAI,KAAK,WAAW,MAAM;AACxB,YAAM,YAAY,MAAM,QAAQ,KAAK,KAAK,SAAS,IAAI,KAAK,KAAK,UAAU,SAAS;AACpF,aAAO,OAAO,GAAG,SAAS,EAAE,IAAI,CAAC,MAAM,IAAI;AAAA,IAC7C,OAAO;AACL,aAAO,KAAK;AAAA,IACd;AAAA,EACF;AAAA,EACA,UAAU,QAAQ;AAChB,SAAK,UAAU;AAAA,EACjB;AAAA,EACA,mBAAmB,YAAY;AAC7B,QAAI,gBAAgB,UAAU,GAAG;AAC/B,mBAAa,WAAW;AAAA,IAC1B;AACA,iBAAa;AACb,QAAI,YAAY,KAAK,KAAK;AAC1B,QAAI,CAAC,MAAM,QAAQ,SAAS,GAAG;AAC7B,kBAAY,CAAC,SAAS;AAAA,IACxB;AACA,UAAM,YAAY,UAAU;AAC5B,QAAI;AACJ,QAAI,KAAK,iBAAiB;AACxB,oBAAc,CAAC,WAAW,IAAI,WAAW,IAAI,SAAS;AAAA,IACxD,OAAO;AACL,oBAAc,CAAC,WAAW,IAAI,SAAS;AAAA,IACzC;AACA,QAAI,KAAK,aAAa;AACpB,YAAM,aAAa,CAAC;AACpB,iBAAW,OAAO,WAAW;AAC3B,mBAAW,KAAK,CAAC,WAAW,IAAI,GAAG,CAAC;AAAA,MACtC;AACA,aAAO,CAAC,WAAW,EAAE,OAAO,UAAU;AAAA,IACxC,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,YAAY,QAAQA,OAAM;AACxB,WAAO,KAAK,MAAM;AAChB,UAAI,MAAM,QAAQA,KAAI,GAAG;AACvB,QAAAA,QAAOA,MAAK;AAAA,MACd;AACA,YAAM,aAAa,KAAK,kBAAkBA,QAAO;AACjD,UAAI,KAAK,aAAa;AACpB,cAAM,YAAY,KAAK,OAAO,IAAI,CAAC,OAAO,IAAI;AAC9C,eAAO,CAAC,UAAU,EAAE,OAAO,SAAS;AAAA,MACtC,OAAO;AACL,eAAO;AAAA,MACT;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,IAAI,SAAS;AACX,QAAI,KAAK,WAAW,MAAM;AACxB,YAAM,YAAY,MAAM,QAAQ,KAAK,KAAK,SAAS,IAAI,KAAK,KAAK,UAAU,SAAS;AACpF,YAAM,SAAS,CAAC;AAChB,eAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,eAAO,KAAK,IAAI;AAAA,MAClB;AACA,aAAO;AAAA,IACT,OAAO;AACL,aAAO,KAAK;AAAA,IACd;AAAA,EACF;AAAA,EACA,IAAI,OAAO,IAAI;AACb,SAAK,UAAU;AAAA,EACjB;AAAA,EACA,MAAM,YAAY;AAChB,UAAM,gBAAgB;AACtB,QAAI,KAAK,gBAAgB,MAAM;AAC7B,YAAM,IAAI,oBAAoB,kDAAkD;AAAA,IAClF;AACA,QAAI,gBAAgB,UAAU,GAAG;AAC/B,mBAAa,WAAW;AAAA,IAC1B;AACA,iBAAa;AACb,UAAM,YAAY,KAAK,WAAW,WAAW,KAAK;AAClD,UAAM,WAAW,WAAW,MAAM,CAAC;AACnC,SAAK,UAAU,KAAK,IAAI,UAAU,EAAE,OAAO,CAAC,WAAW,MAAM,GAAG,QAAQ,EAAE,CAAC;AAC3E,UAAM,iBAAiB,CAAC,WAAW,EAAE,EAAE,OAAO,WAAW,MAAM,CAAC,CAAC;AACjE,QAAI,iBAAiB,MAAM;AACzB,YAAM,IAAI,oBAAoB,kDAAkD;AAAA,IAClF,OAAO;AACL,WAAK,KAAK,MAAM,cAAc;AAAA,IAChC;AACA,QAAI;AACJ,QAAI,MAAM,QAAQ,KAAK,KAAK,SAAS,GAAG;AACtC,kBAAY,KAAK,KAAK;AAAA,IACxB,OAAO;AACL,kBAAY,CAAC,KAAK,KAAK,SAAS;AAAA,IAClC;AACA,QAAI,KAAK,aAAa,MAAM;AAC1B,UAAI,CAAC,aAAa,YAAY,KAAK,UAAU,IAAI,CAAC,SAAS,KAAK,MAAM,KAAK,MAAM,SAAS,EAAE,GAAG,SAAS,GAAG;AACzG,cAAM,IAAI,WAAW,6FAA6F,KAAK,wCAAwC,KAAK,KAAK,WAAW;AAAA,MACtL;AAAA,IACF,OAAO;AACL,WAAK,YAAY,UAAU,IAAI,CAAC,QAAQ,IAAI,UAAU,EAAE,OAAO,CAAC,MAAM,GAAG,EAAE,CAAC,CAAC;AAAA,IAC/E;AACA,QAAI,KAAK,UAAU;AACjB,WAAK,YAAY;AAAA,IACnB;AAAA,EACF;AAAA,EACA,YAAY,QAAQ,WAAW,OAAO;AACpC,SAAK,MAAM;AACT,UAAI,CAAC,KAAK,UAAU;AAClB,cAAM,IAAI,eAAe,iEAAiE;AAAA,MAC5F;AACA,YAAM,YAAY,KAAK,UAAU,GAAG,MAAM;AAC1C,UAAI,aAAa,MAAM;AACrB,cAAM,IAAI,WAAW,uUAAuU;AAAA,MAC9V;AACA,UAAI,KAAK,WAAW,MAAM;AACxB,YAAI,MAAM,QAAQ,KAAK,KAAK,SAAS,GAAG;AACtC,eAAK,UAAU,KAAK,KAAK,UAAU,IAAI,CAAC,QAAQ,MAAM,CAAC,WAAW,GAAG,CAAC,CAAC;AAAA,QACzE,OAAO;AACL,eAAK,UAAU,CAAC,MAAM,CAAC,WAAW,KAAK,KAAK,SAAS,CAAC,CAAC;AAAA,QACzD;AAAA,MACF,WAAW,UAAU,MAAM;AACzB,gBAAQ,KAAK,OAAO;AACpB,YAAI,KAAK,cAAc,MAAM;AAC3B,kBAAQ,KAAK,UAAU;AACvB,eAAK,aAAa,CAAC;AAAA,QACrB;AACA,YAAI,MAAM,QAAQ,KAAK,KAAK,SAAS,GAAG;AACtC,eAAK,UAAU,KAAK,KAAK,UAAU,IAAI,CAAC,QAAQ,MAAM,CAAC,WAAW,GAAG,CAAC,CAAC;AAAA,QACzE,OAAO;AACL,eAAK,QAAQ,KAAK,MAAM,CAAC,WAAW,KAAK,KAAK,SAAS,CAAC;AAAA,QAC1D;AAAA,MACF,OAAO;AACL,YAAI,CAAC,MAAM,QAAQ,MAAM,GAAG;AAC1B,mBAAS,CAAC,MAAM;AAAA,QAClB;AACA,YAAI,OAAO,WAAW,KAAK,QAAQ,QAAQ;AACzC,gBAAM,IAAI,WAAW,SAAS,KAAK,gBAAgB,KAAK,QAAQ,oCAAoC,OAAO,0CAA0C,QAAQ;AAAA,QAC/J;AACA,YAAI,aAAa,MAAM;AACrB,eAAK,WAAW,KAAK,KAAK,QAAQ,MAAM,CAAC;AAAA,QAC3C,OAAO;AACL,kBAAQ,KAAK,OAAO;AAAA,QACtB;AACA,iBAASI,SAAQ,GAAGA,SAAQ,KAAK,QAAQ,QAAQ,EAAEA,QAAO;AACxD,gBAAM,QAAQ,OAAOA;AACrB,gBAAM,MAAM,MAAM,QAAQ,KAAK,KAAK,SAAS,IAAI,KAAK,KAAK,UAAUA,UAAS,KAAK,KAAK;AACxF,gBAAM,gBAAgB,CAAC,WAAW,GAAG;AACrC,cAAI,CAAC,aAAa,YAAY,MAAM,OAAO,aAAa,GAAG;AACzD,kBAAM,IAAI,WAAW,SAASA,qCAAoC,KAAK,wBAAwB,iCAAiC,MAAM,OAAO;AAAA,UAC/I;AACA,eAAK,QAAQA,UAAS;AAAA,QACxB;AAAA,MACF;AACA,WAAK,UAAU,KAAK,QAAQ,IAAI,CAAC,UAAU,KAAK,MAAM,MAAM,CAAC,CAAC;AAAA,IAChE,CAAC;AAAA,EACH;AAAA,EACA,MAAM,QAAQ,QAAQ;AACpB,QAAI,eAAe,UAAU,OAAO,OAAO,OAAO;AAClD,QAAIqB,aAAY,UAAU,OAAO,OAAO,OAAO;AAC/C,QAAI,UAAU,MAAM;AAClB,eAAS,CAAC;AAAA,IACZ;AACA,UAAM,eAAe,gBAAgB,QAAQ,cAAcA,YAAW,KAAK,YAAY;AACvF,aAAS,aAAa;AACtB,mBAAe,aAAa;AAC5B,IAAAA,aAAY,aAAa;AACzB,QAAI,mBAAmB,CAAC;AACxB,QAAI,kBAAkB,CAAC;AACvB,QAAI,gBAAgB,MAAM;AACxB,aAAO,kBAAkB;AACzB,yBAAmB,iBAAiB,OAAO,YAAY;AACvD,WAAK,YAAY,CAAC;AAClB,iBAAW,SAAS,cAAc;AAChC,aAAK,UAAU,KAAK,IAAI,UAAU,EAAE,OAAO,MAAM,MAAM,CAAC,CAAC;AAAA,MAC3D;AACA,wBAAkB,gBAAgB,OAAO,KAAK,SAAS;AAAA,IACzD;AACA,QAAIA,cAAa,MAAM;AACrB,aAAO,eAAeA;AACtB,yBAAmB,iBAAiB,OAAOA,UAAS;AACpD,WAAK,eAAeA,WAAU;AAAA,IAChC;AACA,UAAM,WAAW,iBAAiB,cAAc;AAChD,QAAI,UAAU;AACZ,YAAM,YAAY,CAAC,MAAM,EAAE,OAAO,gBAAgB;AAClD,YAAM,gBAAgB,KAAK,UAAU,OAAO,eAAe;AAC3D,YAAM,oBAAoB,KAAK;AAC/B,WAAK,YAAY;AACjB,YAAM,SAAS,MAAM,MAAM,WAAW,MAAM;AAC5C,WAAK,YAAY;AACjB,aAAO;AAAA,IACT,OAAO;AACL,aAAO,MAAM,MAAM,QAAQ,MAAM;AAAA,IACnC;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAMzB,QAAO,UAAU,OAAO,OAAO,OAAO;AAC5C,YAAM,WAAW,UAAU,OAAO,OAAO,OAAO;AAChD,UAAI,eAAe,UAAU,OAAO,OAAO,OAAO;AAClD,eAAS,oBAAoB,MAAM;AACnC,UAAI,gBAAgB,MAAM;AACxB,YAAI,KAAK,UAAU;AACjB,yBAAe,KAAK;AAAA,QACtB,OAAO;AACL,yBAAe,KAAK,gBAAgB,MAAM;AAAA,QAC5C;AAAA,MACF;AACA,YAAM,YAAY,MAAM,QAAQ,KAAK,KAAK,SAAS,IAAI,KAAK,KAAK,UAAU,SAAS;AACpF,UAAI,aAAa,WAAW,WAAW;AACrC,cAAM,IAAI,WAAW,iBAAiB,qCAAqC,aAAa,0BAA0B;AAAA,MACpH;AACA,UAAI,KAAK,QAAQ;AACf,gBAAQ,KAAK,kEAAkE;AAAA,MACjF;AACA,YAAM,iBAAiB,EAAE,SAAS;AAClC,YAAM,QAAQ,CAAC,SAAS,YAAY;AAClC,cAAM,WAAW,KAAK,KAAK,KAAK,CAAC,OAAO,EAAE,OAAO,OAAO,GAAG,cAAc;AACzE,eAAO,CAAC,SAAS,IAAI,SAAS,MAAM,CAAC,CAAC;AAAA,MACxC;AACA,YAAM,aAAa,IAAI,OAAO,QAAQ,cAAc,KAAK,aAAaA,OAAM,MAAM,KAAK,QAAQ,KAAK,eAAe;AACnH,YAAM,aAAa,WAAW;AAC9B,YAAM,UAAU,WAAW;AAC3B,YAAM,SAAS,WAAW;AAC1B,UAAI,KAAK,UAAU;AACjB,aAAK,YAAY,QAAQ,QAAQ;AAAA,MACnC;AACA,YAAM,SAAS,KAAK,kBAAkB,UAAU;AAChD,UAAI,KAAK,aAAa;AACpB,eAAO,CAAC,MAAM,EAAE,OAAO,MAAM;AAAA,MAC/B,OAAO;AACL,eAAO;AAAA,MACT;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,gBAAgB,QAAQ;AACtB,WAAO,KAAK,MAAM;AAChB,UAAI,eAAe,MAAM,OAAO,KAAK;AACrC,qBAAe,KAAK,cAAc,CAAC,GAAG,CAAC,CAAC;AACxC,qBAAe,YAAY,YAAY;AACvC,UAAI,MAAM,QAAQ,KAAK,KAAK,SAAS,GAAG;AACtC,eAAO,KAAK,KAAK,UAAU,IAAI,CAAC,QAAQ,MAAM,IAAI,MAAM,cAAc,CAAC,GAAG,GAAG,CAAC,IAAI,YAAY;AAAA,MAChG,OAAO;AACL,eAAO,KAAK,KAAK,YAAY,IAAI,CAAC,MAAM,cAAc,CAAC,GAAG,KAAK,KAAK,SAAS,CAAC,CAAC,IAAI,CAAC,YAAY;AAAA,MAClG;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,IAAI,mBAAmB;AACrB,QAAI,CAAC,KAAK,WAAW;AACnB,aAAO,CAAC;AAAA,IACV;AACA,WAAO,KAAK,KAAK;AAAA,EACnB;AAAA,EACA,IAAI,sBAAsB;AACxB,QAAI,CAAC,KAAK,WAAW;AACnB,aAAO,KAAK,KAAK;AAAA,IACnB;AACA,WAAO,KAAK,KAAK;AAAA,EACnB;AAAA,EACA,6BAA6B,OAAO;AAClC,UAAM,6BAA6B,KAAK;AACxC,QAAI,KAAK,QAAQ,MAAM;AACrB,WAAK,KAAK,6BAA6B,KAAK;AAAA,IAC9C;AAAA,EACF;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMS,UAAS;AAAA,MACb,iBAAiB,KAAK;AAAA,MACtB,aAAa,KAAK;AAAA,MAClB,aAAa,KAAK;AAAA,MAClB,UAAU,KAAK;AAAA,MACf,QAAQ,KAAK;AAAA,IACf;AACA,QAAI,KAAK,gBAAgB,MAAM;AAC7B,MAAAA,QAAO,kBAAkB,KAAK;AAAA,IAChC;AACA,UAAM,aAAa,KAAK,KAAK,UAAU;AACvC,QAAI,KAAK,aAAa,MAAM,IAAI,WAAW;AACzC,MAAAA,QAAO,UAAU;AAAA,QACf,aAAa,KAAK,KAAK,aAAa;AAAA,QACpC,UAAU;AAAA,MACZ;AAAA,IACF;AACA,WAAO,OAAO,OAAO,CAAC,GAAG,YAAY,YAAYA,OAAM;AAAA,EACzD;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ,gBAAgB,CAAC,GAAG;AACjD,UAAM,aAAaA,QAAO;AAC1B,UAAM,OAAO,YAAY,YAAY,aAAa;AAClD,WAAO,IAAI,IAAI,OAAO,OAAOA,SAAQ,EAAE,KAAK,CAAC,CAAC;AAAA,EAChD;AACF;AACA,IAAI,YAAY;AAChB,sBAAsB,cAAc,GAAG;AACvC,IAAI,UAAU,cAAc,MAAM;AAClC;AACA,IAAI,gBAAgB,cAAc,QAAQ;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,qBAAqB;AAC1B,SAAK,6BAA6B;AAClC,SAAK,gCAAgC;AACrC,SAAK,2BAA2B;AAChC,SAAK,QAAQ,KAAK;AAClB,0BAAsB,KAAK,OAAO,OAAO;AACzC,SAAK,aAAa,cAAc,KAAK,cAAc,OAAO,KAAK,qBAAqB,KAAK,UAAU;AACnG,SAAK,UAAU,KAAK,WAAW,OAAO,OAAO,KAAK;AAClD,SAAK,oBAAoB,eAAe,KAAK,qBAAqB,KAAK,0BAA0B;AACjG,SAAK,uBAAuB,eAAe,KAAK,wBAAwB,KAAK,6BAA6B;AAC1G,SAAK,kBAAkB,eAAe,KAAK,mBAAmB,KAAK,wBAAwB;AAC3F,SAAK,oBAAoB,eAAe,KAAK,iBAAiB;AAC9D,SAAK,uBAAuB,eAAe,KAAK,oBAAoB;AACpE,SAAK,kBAAkB,eAAe,KAAK,eAAe;AAC1D,SAAK,mBAAmB,cAAc,KAAK,gBAAgB;AAC3D,SAAK,sBAAsB,cAAc,KAAK,mBAAmB;AACjE,SAAK,iBAAiB,cAAc,KAAK,cAAc;AACvD,SAAK,UAAU,KAAK,CAAC,GAAG,KAAK,CAAC,GAAG,KAAK,WAAW,OAAO,IAAI,KAAK,OAAO,CAAC,CAAC,CAAC;AAC3E,SAAK,mBAAmB,KAAK;AAAA,MAC3B;AAAA,MACA,KAAK,CAAC,GAAG,KAAK,oBAAoB,OAAO,IAAI,KAAK,gBAAgB,CAAC;AAAA,IACrE,CAAC;AACD,SAAK,cAAc,KAAK;AACxB,SAAK,YAAY,KAAK;AACtB,SAAK,cAAc;AACnB,SAAK,uBAAuB;AAAA,EAC9B;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,SAAK,SAAS,KAAK,UAAU,UAAU,CAAC,WAAW,WAAW,SAAS,IAAI,KAAK,KAAK,GAAG,MAAM,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AACzK,SAAK,kBAAkB,KAAK,UAAU,oBAAoB,CAAC,KAAK,OAAO,KAAK,KAAK,GAAG,MAAM,KAAK,sBAAsB,KAAK,sBAAsB,MAAM,KAAK,mBAAmB;AAC9K,QAAI,KAAK,SAAS;AAChB,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,KAAK,GAAG,MAAM,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IAC9H,OAAO;AACL,WAAK,OAAO;AAAA,IACd;AACA,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS;AACT,UAAI,OAAO,WAAW,GAAG;AACvB,cAAM,IAAI,WAAW,8CAA8C,OAAO,SAAS;AAAA,MACrF;AACA,UAAI,aAAa,OAAO;AACxB,eAAS,OAAO;AAChB,YAAM,WAAW,OAAO,eAAe,OAAO,QAAQ,OAAO;AAC7D,UAAI,IAAI,KAAK,WAAW,KAAK,UAAU,KAAK,KAAK,eAAe,MAAM;AACpE,aAAK,cAAc,oBAAoB;AAAA,UACrC,MAAM,MAAM,SAAS,MAAM;AAAA,UAC3B,MAAM,KAAK;AAAA,UACX;AAAA,UACA,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,UAAI,IAAI,KAAK,oBAAoB,KAAK,mBAAmB,KAAK,KAAK,wBAAwB,MAAM;AAC/F,aAAK,uBAAuB,oBAAoB;AAAA,UAC9C,MAAM,MAAM,SAAS,UAAU;AAAA,UAC/B,MAAM,KAAK;AAAA,UACX;AAAA,UACA,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,UAAI;AACJ,YAAM,SAAS,KAAK;AACpB,YAAM,YAAY,KAAK;AACvB,UAAI,UAAU,MAAM;AAClB,YAAI,KAAK,IAAI,QAAQ,MAAM,GAAG,KAAK,OAAO,KAAK,CAAC;AAAA,MAClD,OAAO;AACL,YAAI,KAAK,QAAQ,KAAK,OAAO,KAAK,CAAC;AAAA,MACrC;AACA,UAAI,KAAK,QAAQ,MAAM;AACrB,YAAI,QAAQ,GAAG,KAAK,KAAK,KAAK,CAAC;AAAA,MACjC;AACA,UAAI,aAAa,MAAM;AACrB,qBAAa,IAAI,YAAY,SAAS;AAAA,MACxC;AACA,UAAI,SAAS,KAAK,GAAG,KAAK,YAAY,KAAK,gBAAgB,KAAK,CAAC,CAAC;AAClE,UAAI,KAAK,cAAc,MAAM;AAC3B,iBAAS,KAAK,WAAW,MAAM,MAAM;AAAA,MACvC;AACA,aAAO,CAAC,QAAQ,MAAM;AAAA,IACxB,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMA,UAAS;AAAA,MACb,OAAO,KAAK;AAAA,MACZ,YAAY,oBAAoB,KAAK,UAAU;AAAA,MAC/C,SAAS,KAAK;AAAA,MACd,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,sBAAsB,qBAAqB,KAAK,oBAAoB;AAAA,MACpE,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,sBAAsB,qBAAqB,KAAK,oBAAoB;AAAA,MACpE,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,qBAAqB,qBAAqB,KAAK,mBAAmB;AAAA,MAClE,kBAAkB,oBAAoB,KAAK,gBAAgB;AAAA,MAC3D,qBAAqB,oBAAoB,KAAK,mBAAmB;AAAA,MACjE,gBAAgB,oBAAoB,KAAK,cAAc;AAAA,MACvD,SAAS,KAAK;AAAA,MACd,kBAAkB,KAAK;AAAA,IACzB;AACA,WAAO,OAAO,OAAO,CAAC,GAAG,YAAYA,OAAM;AAAA,EAC7C;AACF;AACA,cAAc,YAAY;AAC1B,sBAAsB,cAAc,aAAa;AACjD,IAAI,YAAY,cAAc,IAAI;AAAA,EAChC,YAAY,MAAM;AAChB,SAAK,OAAO,IAAI,cAAc,IAAI;AAClC,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,KAAK,KAAK,eAAe,MAAM;AACjC,gBAAQ,KAAK,KAAK,WAAW;AAC7B,aAAK,KAAK,cAAc;AAAA,MAC1B;AACA,UAAI,KAAK,KAAK,wBAAwB,MAAM;AAC1C,gBAAQ,KAAK,KAAK,oBAAoB;AACtC,aAAK,KAAK,uBAAuB;AAAA,MACnC;AACA,YAAMT,QAAO,UAAU,OAAO,OAAO,OAAO;AAC5C,YAAM,WAAW,UAAU,OAAO,OAAO,OAAO;AAChD,YAAM,eAAe,UAAU,OAAO,OAAO,OAAO;AACpD,aAAO,MAAM,KAAK,QAAQ,EAAE,MAAAA,OAAM,UAAU,aAAa,CAAC;AAAA,IAC5D,CAAC;AAAA,EACH;AAAA,EACA,OAAO,WAAW,KAAKS,SAAQ;AAC7B,WAAO,IAAI,IAAIA,OAAM;AAAA,EACvB;AACF;AACA,UAAU,YAAY;AACtB,sBAAsB,cAAc,SAAS;AAC7C,IAAI,UAAU,cAAc,QAAQ;AAAA,EAClC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,qBAAqB;AAC1B,SAAK,+BAA+B;AACpC,SAAK,6BAA6B;AAClC,SAAK,gCAAgC;AACrC,SAAK,2BAA2B;AAChC,QAAI,KAAK,YAAY;AACnB,YAAM,IAAI,WAAW,6DAA6D;AAAA,IACpF;AACA,SAAK,QAAQ,KAAK;AAClB,0BAAsB,KAAK,OAAO,OAAO;AACzC,SAAK,aAAa,cAAc,KAAK,eAAe,SAAS,KAAK,qBAAqB,KAAK,UAAU;AACtG,SAAK,sBAAsB,cAAc,KAAK,wBAAwB,SAAS,KAAK,+BAA+B,KAAK,mBAAmB;AAC3I,SAAK,UAAU,KAAK,WAAW,OAAO,OAAO,KAAK;AAClD,SAAK,oBAAoB,eAAe,KAAK,qBAAqB,KAAK,0BAA0B;AACjG,SAAK,uBAAuB,eAAe,KAAK,wBAAwB,KAAK,6BAA6B;AAC1G,SAAK,kBAAkB,eAAe,KAAK,mBAAmB,KAAK,wBAAwB;AAC3F,SAAK,oBAAoB,eAAe,KAAK,iBAAiB;AAC9D,SAAK,uBAAuB,eAAe,KAAK,oBAAoB;AACpE,SAAK,kBAAkB,eAAe,KAAK,eAAe;AAC1D,SAAK,mBAAmB,cAAc,KAAK,gBAAgB;AAC3D,SAAK,sBAAsB,cAAc,KAAK,mBAAmB;AACjE,SAAK,iBAAiB,cAAc,KAAK,cAAc;AACvD,SAAK,UAAU,KAAK,CAAC,GAAG,KAAK,CAAC,GAAG,KAAK,WAAW,OAAO,IAAI,KAAK,OAAO,CAAC,CAAC,CAAC;AAC3E,SAAK,mBAAmB,KAAK;AAAA,MAC3B;AAAA,MACA,KAAK,CAAC,GAAG,KAAK,oBAAoB,OAAO,IAAI,KAAK,gBAAgB,CAAC;AAAA,IACrE,CAAC;AACD,SAAK,cAAc,KAAK;AACxB,SAAK,iBAAiB,KAAK;AAC3B,SAAK,YAAY,KAAK;AACtB,SAAK,cAAc;AACnB,SAAK,uBAAuB;AAAA,EAC9B;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,WAAW,WAAW,WAAW,SAAS;AAChD,SAAK,SAAS,KAAK,UAAU,UAAU,CAAC,UAAU,KAAK,QAAQ,CAAC,GAAG,MAAM,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AACpJ,SAAK,kBAAkB,KAAK,UAAU,oBAAoB,CAAC,KAAK,OAAO,KAAK,QAAQ,CAAC,GAAG,MAAM,KAAK,sBAAsB,KAAK,sBAAsB,MAAM,KAAK,mBAAmB;AAClL,QAAI,KAAK,SAAS;AAChB,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,QAAQ,CAAC,GAAG,MAAM,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IAClI,OAAO;AACL,WAAK,OAAO;AAAA,IACd;AACA,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS;AACT,UAAI,OAAO,WAAW,GAAG;AACvB,cAAM,IAAI,WAAW,uDAAuD,OAAO,SAAS;AAAA,MAC9F;AACA,YAAM,WAAW,OAAO,eAAe,OAAO,QAAQ,OAAO;AAC7D,UAAI,WAAW,OAAO;AACtB,eAAS,OAAO;AAChB,UAAI,IAAI,KAAK,WAAW,KAAK,UAAU,KAAK,KAAK,eAAe,MAAM;AACpE,aAAK,cAAc,oBAAoB;AAAA,UACrC,MAAM,MAAM,SAAS,MAAM;AAAA,UAC3B,MAAM,KAAK;AAAA,UACX;AAAA,UACA,OAAO;AAAA,UACP,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,UAAI,IAAI,KAAK,oBAAoB,KAAK,mBAAmB,KAAK,KAAK,wBAAwB,MAAM;AAC/F,aAAK,uBAAuB,oBAAoB;AAAA,UAC9C,MAAM,MAAM,SAAS,QAAQ;AAAA,UAC7B,MAAM,KAAK;AAAA,UACX;AAAA,UACA,OAAO;AAAA,UACP,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,YAAM,SAAS,KAAK;AACpB,YAAM,YAAY,KAAK;AACvB,UAAI;AACJ,UAAI;AACJ,UAAI;AACJ,UAAI,IAAI,KAAK,WAAW,KAAK,UAAU,GAAG;AACxC,iBAAS,IAAI,QAAQ,OAAO,EAAE;AAAA,MAChC;AACA,UAAI,UAAU,KAAK,QAAQ,KAAK,OAAO,KAAK,CAAC;AAC7C,UAAI,KAAK,SAAS;AAChB,kBAAU,QAAQ,SAAS,KAAK,KAAK,KAAK,CAAC;AAAA,MAC7C;AACA,UAAI,IAAI,KAAK,oBAAoB,KAAK,mBAAmB,GAAG;AAC1D,mBAAW,IAAI,UAAU,UAAU,EAAE;AAAA,MACvC;AACA,YAAM,uBAAuB,KAAK,gBAAgB,KAAK;AACvD,YAAM,CAAC,KAAK,GAAG,IAAI,MAAM,sBAAsB,CAAC,IAAI,KAAK,OAAO,KAAK,KAAK,GAAG,qBAAqB,OAAO,CAAC;AAC1G,YAAM,cAAc,KAAK,UAAU,GAAG;AACtC,YAAM,CAAC,IAAI,IAAI,EAAE,IAAI,MAAM,SAAS,GAAG,QAAQ,OAAO,CAAC;AACvD,YAAM,CAAC,YAAY,UAAU,IAAI,MAAM,aAAa,GAAG,YAAY,OAAO,CAAC;AAC3E,UAAI,KAAK,oBAAoB,MAAM,KAAK,IAAI,UAAU,CAAC;AACvD,WAAK,KAAK,oBAAoB,MAAM,KAAK,IAAI,UAAU,CAAC;AACxD,YAAM,aAAa,KAAK,IAAI,IAAI,QAAQ,GAAG,GAAG;AAC9C,WAAK,KAAK,WAAW,MAAM,KAAK,IAAI,UAAU,CAAC;AAC/C,YAAM,IAAI,KAAK,IAAI,GAAG,QAAQ,GAAG,IAAI,KAAK,GAAG,IAAI,CAAC,CAAC,GAAG,EAAE,CAAC;AACzD,aAAO,CAAC,GAAG,CAAC;AAAA,IACd,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMA,UAAS;AAAA,MACb,OAAO,KAAK;AAAA,MACZ,YAAY,oBAAoB,KAAK,UAAU;AAAA,MAC/C,qBAAqB,oBAAoB,KAAK,mBAAmB;AAAA,MACjE,SAAS,KAAK;AAAA,MACd,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,sBAAsB,qBAAqB,KAAK,oBAAoB;AAAA,MACpE,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,sBAAsB,qBAAqB,KAAK,oBAAoB;AAAA,MACpE,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,qBAAqB,qBAAqB,KAAK,mBAAmB;AAAA,MAClE,kBAAkB,oBAAoB,KAAK,gBAAgB;AAAA,MAC3D,qBAAqB,oBAAoB,KAAK,mBAAmB;AAAA,MACjE,gBAAgB,oBAAoB,KAAK,cAAc;AAAA,MACvD,SAAS,KAAK;AAAA,MACd,kBAAkB,KAAK;AAAA,MACvB,gBAAgB,KAAK;AAAA,MACrB,YAAY;AAAA,IACd;AACA,WAAO,OAAO,OAAO,CAAC,GAAG,YAAYA,OAAM;AAAA,EAC7C;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,MAAM,cAAc,IAAI;AAAA,EAC1B,YAAY,MAAM;AAChB,QAAI,KAAK,mBAAmB,GAAG;AAC7B,cAAQ,KAAK,gHAAgH;AAAA,IAC/H;AACA,SAAK,OAAO,IAAI,QAAQ,IAAI;AAC5B,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,KAAK,KAAK,eAAe,MAAM;AACjC,gBAAQ,KAAK,KAAK,WAAW;AAC7B,aAAK,KAAK,cAAc;AAAA,MAC1B;AACA,UAAI,KAAK,KAAK,wBAAwB,MAAM;AAC1C,gBAAQ,KAAK,KAAK,oBAAoB;AACtC,aAAK,KAAK,uBAAuB;AAAA,MACnC;AACA,YAAMT,QAAO,UAAU,OAAO,OAAO,OAAO;AAC5C,YAAM,WAAW,UAAU,OAAO,OAAO,OAAO;AAChD,YAAM,eAAe,UAAU,OAAO,OAAO,OAAO;AACpD,aAAO,MAAM,KAAK,QAAQ,EAAE,MAAAA,OAAM,UAAU,aAAa,CAAC;AAAA,IAC5D,CAAC;AAAA,EACH;AAAA,EACA,OAAO,WAAW,KAAKS,SAAQ;AAC7B,QAAIA,QAAO,qBAAqB,GAAG;AACjC,MAAAA,QAAO,oBAAoB;AAAA,IAC7B;AACA,WAAO,IAAI,IAAIA,OAAM;AAAA,EACvB;AACF;AACA,IAAI,YAAY;AAChB,sBAAsB,cAAc,GAAG;AACvC,IAAI,WAAW,cAAc,QAAQ;AAAA,EACnC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,qBAAqB;AAC1B,SAAK,+BAA+B;AACpC,SAAK,6BAA6B;AAClC,SAAK,gCAAgC;AACrC,SAAK,2BAA2B;AAChC,SAAK,QAAQ,KAAK;AAClB,0BAAsB,KAAK,OAAO,OAAO;AACzC,SAAK,aAAa,cAAc,KAAK,eAAe,SAAS,KAAK,qBAAqB,KAAK,UAAU;AACtG,SAAK,sBAAsB,cAAc,KAAK,wBAAwB,SAAS,KAAK,+BAA+B,KAAK,mBAAmB;AAC3I,SAAK,UAAU,KAAK,WAAW,OAAO,OAAO,KAAK;AAClD,SAAK,oBAAoB,eAAe,KAAK,qBAAqB,KAAK,0BAA0B;AACjG,SAAK,uBAAuB,eAAe,KAAK,wBAAwB,KAAK,6BAA6B;AAC1G,SAAK,kBAAkB,eAAe,KAAK,mBAAmB,KAAK,wBAAwB;AAC3F,SAAK,iBAAiB,KAAK;AAC3B,SAAK,oBAAoB,eAAe,KAAK,iBAAiB;AAC9D,SAAK,uBAAuB,eAAe,KAAK,oBAAoB;AACpE,SAAK,kBAAkB,eAAe,KAAK,eAAe;AAC1D,SAAK,mBAAmB,cAAc,KAAK,gBAAgB;AAC3D,SAAK,sBAAsB,cAAc,KAAK,mBAAmB;AACjE,SAAK,iBAAiB,cAAc,KAAK,cAAc;AACvD,SAAK,UAAU,KAAK,CAAC,GAAG,KAAK,CAAC,GAAG,KAAK,WAAW,OAAO,IAAI,KAAK,OAAO,CAAC,CAAC,CAAC;AAC3E,SAAK,mBAAmB,KAAK;AAAA,MAC3B;AAAA,MACA,KAAK,CAAC,GAAG,KAAK,oBAAoB,OAAO,IAAI,KAAK,gBAAgB,CAAC;AAAA,IACrE,CAAC;AACD,SAAK,cAAc,KAAK;AACxB,SAAK,iBAAiB,KAAK;AAC3B,SAAK,YAAY,CAAC,KAAK,OAAO,KAAK,KAAK;AACxC,SAAK,cAAc;AACnB,SAAK,uBAAuB;AAAA,EAC9B;AAAA,EACA,MAAM,YAAY;AAChB,QAAI;AACJ,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,WAAW,WAAW,WAAW,SAAS;AAChD,SAAK,SAAS,KAAK,UAAU,UAAU,CAAC,UAAU,KAAK,QAAQ,CAAC,GAAG,MAAM,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AACpJ,SAAK,kBAAkB,KAAK,UAAU,oBAAoB,CAAC,KAAK,OAAO,KAAK,QAAQ,CAAC,GAAG,MAAM,KAAK,sBAAsB,KAAK,sBAAsB,MAAM,KAAK,mBAAmB;AAClL,QAAI;AACJ,QAAI,KAAK,SAAS;AAChB,UAAI,KAAK,gBAAgB;AACvB,cAAM,mBAAmB,KAAK;AAC9B,cAAM,gBAAgB,KAAK;AAC3B,0BAAkB,KAAK,KAAK,MAAM,mBAAmB,YAAY;AAAA,UAC/D,MAAM,OAAO,OAAO;AAClB,kBAAM,KAAK,iBAAiB,MAAM,CAAC,aAAa,CAAC;AACjD,kBAAM,KAAK,IAAI,KAAK,EAAE,MAAM,CAAC,aAAa,CAAC;AAC3C,kBAAM,SAAS,iBAAiB,MAAM,CAAC,gBAAgB,CAAC,CAAC;AACzD,mBAAO,qBAAqB,qBAAqB,IAAI,EAAE,GAAG,MAAM;AAAA,UAClE;AAAA,QACF,GAAG,GAAG,YAAY,cAAc,IAAI;AAAA,MACtC,OAAO;AACL,0BAAkB,KAAK;AAAA,MACzB;AACA,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,QAAQ,CAAC,GAAG,MAAM,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IAC7H,OAAO;AACL,WAAK,OAAO;AAAA,IACd;AACA,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAM,WAAW,OAAO,eAAe,OAAO,QAAQ,OAAO;AAC7D,eAAS;AACT,UAAI,OAAO,WAAW,GAAG;AACvB,cAAM,IAAI,WAAW,wDAAwD,OAAO,SAAS;AAAA,MAC/F;AACA,UAAI,WAAW,OAAO;AACtB,YAAM,WAAW,OAAO;AACxB,eAAS,OAAO;AAChB,UAAI,IAAI,KAAK,WAAW,KAAK,UAAU,KAAK,KAAK,eAAe,MAAM;AACpE,aAAK,cAAc,oBAAoB;AAAA,UACrC,MAAM,MAAM,SAAS,MAAM;AAAA,UAC3B,MAAM,KAAK;AAAA,UACX;AAAA,UACA,OAAO;AAAA,UACP,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,UAAI,IAAI,KAAK,oBAAoB,KAAK,mBAAmB,KAAK,KAAK,wBAAwB,MAAM;AAC/F,aAAK,uBAAuB,oBAAoB;AAAA,UAC9C,MAAM,MAAM,SAAS,QAAQ;AAAA,UAC7B,MAAM,KAAK;AAAA,UACX;AAAA,UACA,OAAO;AAAA,UACP,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,YAAM,SAAS,KAAK;AACpB,YAAM,YAAY,KAAK;AACvB,UAAI;AACJ,UAAI;AACJ,UAAI;AACJ,UAAI;AACJ,UAAI,IAAI,KAAK,WAAW,KAAK,UAAU,GAAG;AACxC,iBAAS,IAAI,QAAQ,OAAO,EAAE;AAAA,MAChC;AACA,UAAI,IAAI,KAAK,QAAQ,KAAK,OAAO,KAAK,CAAC;AACvC,UAAI,IAAI,KAAK,oBAAoB,KAAK,mBAAmB,GAAG;AAC1D,mBAAW,IAAI,UAAU,UAAU,EAAE;AAAA,MACvC;AACA,UAAI,KAAK,GAAG,KAAK,UAAU,KAAK,gBAAgB,KAAK,CAAC,CAAC;AACvD,UAAI,KAAK,SAAS;AAChB,YAAI,QAAQ,GAAG,KAAK,KAAK,KAAK,CAAC;AAAA,MACjC;AACA,YAAM,CAAC,IAAI,IAAI,IAAI,EAAE,IAAI,MAAM,GAAG,GAAG,EAAE,OAAO,CAAC;AAC/C,WAAK,KAAK,oBAAoB,MAAM,EAAE;AACtC,UAAI,KAAK,oBAAoB,MAAM,EAAE;AACrC,UAAI,KAAK,IAAI,GAAG,QAAQ,GAAG,IAAI,IAAI,KAAK,WAAW,MAAM,EAAE,CAAC,CAAC;AAC7D,UAAI,KAAK,oBAAoB,MAAM,EAAE;AACrC,YAAM,IAAI,IAAI,GAAG,KAAK,WAAW,MAAM,CAAC,CAAC;AACzC,aAAO,CAAC,GAAG,GAAG,CAAC;AAAA,IACjB,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMA,UAAS;AAAA,MACb,OAAO,KAAK;AAAA,MACZ,YAAY,oBAAoB,KAAK,UAAU;AAAA,MAC/C,qBAAqB,oBAAoB,KAAK,mBAAmB;AAAA,MACjE,SAAS,KAAK;AAAA,MACd,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,sBAAsB,qBAAqB,KAAK,oBAAoB;AAAA,MACpE,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,gBAAgB,KAAK;AAAA,MACrB,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,sBAAsB,qBAAqB,KAAK,oBAAoB;AAAA,MACpE,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,qBAAqB,qBAAqB,KAAK,mBAAmB;AAAA,MAClE,kBAAkB,oBAAoB,KAAK,gBAAgB;AAAA,MAC3D,qBAAqB,oBAAoB,KAAK,mBAAmB;AAAA,MACjE,gBAAgB,oBAAoB,KAAK,cAAc;AAAA,MACvD,SAAS,KAAK;AAAA,MACd,kBAAkB,KAAK;AAAA,MACvB,gBAAgB,KAAK;AAAA,IACvB;AACA,WAAO,OAAO,OAAO,CAAC,GAAG,YAAYA,OAAM;AAAA,EAC7C;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,OAAO,cAAc,IAAI;AAAA,EAC3B,YAAY,MAAM;AAChB,QAAI,KAAK,mBAAmB,GAAG;AAC7B,cAAQ,KAAK,gHAAgH;AAAA,IAC/H;AACA,SAAK,OAAO,IAAI,SAAS,IAAI;AAC7B,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,KAAK,KAAK,eAAe,MAAM;AACjC,gBAAQ,KAAK,KAAK,WAAW;AAC7B,aAAK,KAAK,cAAc;AAAA,MAC1B;AACA,UAAI,KAAK,KAAK,wBAAwB,MAAM;AAC1C,gBAAQ,KAAK,KAAK,oBAAoB;AACtC,aAAK,KAAK,uBAAuB;AAAA,MACnC;AACA,YAAMT,QAAO,UAAU,OAAO,OAAO,OAAO;AAC5C,YAAM,WAAW,UAAU,OAAO,OAAO,OAAO;AAChD,YAAM,eAAe,UAAU,OAAO,OAAO,OAAO;AACpD,aAAO,MAAM,KAAK,QAAQ,EAAE,MAAAA,OAAM,UAAU,aAAa,CAAC;AAAA,IAC5D,CAAC;AAAA,EACH;AAAA,EACA,OAAO,WAAW,KAAKS,SAAQ;AAC7B,QAAIA,QAAO,qBAAqB,GAAG;AACjC,MAAAA,QAAO,oBAAoB;AAAA,IAC7B;AACA,WAAO,IAAI,IAAIA,OAAM;AAAA,EACvB;AACF;AACA,KAAK,YAAY;AACjB,sBAAsB,cAAc,IAAI;AACxC,IAAI,kBAAkB,cAAc,QAAQ;AAAA,EAC1C,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,QAAQ,KAAK;AAAA,EACpB;AAAA,EACA,IAAI,YAAY;AACd,UAAM,YAAY,CAAC;AACnB,eAAW,QAAQ,KAAK,MAAM,MAAM,EAAE,QAAQ,GAAG;AAC/C,UAAI,MAAM,QAAQ,KAAK,SAAS,GAAG;AACjC,kBAAU,KAAK,GAAG,KAAK,SAAS;AAAA,MAClC,OAAO;AACL,kBAAU,KAAK,KAAK,SAAS;AAAA,MAC/B;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS;AACT,UAAI,SAAS,OAAO,MAAM,CAAC;AAC3B,YAAM,eAAe,CAAC;AACtB,iBAAW,QAAQ,KAAK,MAAM,MAAM,EAAE,QAAQ,GAAG;AAC/C,YAAI,MAAM,QAAQ,KAAK,SAAS,GAAG;AACjC,uBAAa,KAAK,OAAO,OAAO,GAAG,KAAK,UAAU,MAAM,CAAC;AAAA,QAC3D,OAAO;AACL,uBAAa,KAAK,OAAO,OAAO,GAAG,CAAC,CAAC;AAAA,QACvC;AAAA,MACF;AACA,mBAAa,QAAQ;AACrB,YAAM,kBAAkB,CAAC;AACzB,UAAI;AACJ,eAAS,KAAK,GAAG,KAAK,KAAK,MAAM,QAAQ,EAAE,IAAI;AAC7C,cAAM,OAAO,KAAK,MAAM;AACxB,iBAAS,aAAa;AACtB,YAAI,OAAO,GAAG;AACZ,uBAAa,CAAC,OAAO,EAAE,EAAE,OAAO,MAAM;AAAA,QACxC,OAAO;AACL,uBAAa,CAAC,WAAW,EAAE,EAAE,OAAO,MAAM;AAAA,QAC5C;AACA,qBAAa,KAAK,KAAK,YAAY,MAAM;AACzC,wBAAgB,KAAK,WAAW,MAAM,CAAC,CAAC;AAAA,MAC1C;AACA,eAAS,CAAC;AACV,iBAAW,cAAc,gBAAgB,MAAM,EAAE,QAAQ,GAAG;AAC1D,eAAO,KAAK,GAAG,UAAU;AAAA,MAC3B;AACA,aAAO,CAAC,WAAW,EAAE,EAAE,OAAO,MAAM;AAAA,IACtC,CAAC;AAAA,EACH;AAAA,EACA,MAAM,YAAY;AAChB,QAAI,gBAAgB,UAAU,GAAG;AAC/B,mBAAa,WAAW;AAAA,IAC1B;AACA,iBAAa;AACb,QAAI;AACJ,SAAK,MAAM,QAAQ,CAAC,MAAM,OAAO;AAC/B,gBAAU,WAAW,MAAM,MAAM;AAC/B,aAAK,MAAM,UAAU;AACrB,YAAI,MAAM,QAAQ,KAAK,SAAS,GAAG;AACjC,sBAAY,KAAK,UAAU;AAAA,QAC7B,OAAO;AACL,sBAAY,KAAK;AAAA,QACnB;AACA,qBAAa,CAAC,WAAW,IAAI,SAAS;AAAA,MACxC,CAAC;AAAA,IACH,CAAC;AACD,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAM,gBAAgB,CAAC,SAAS;AAC9B,aAAO;AAAA,QACL,aAAa,KAAK,aAAa;AAAA,QAC/B,UAAU,KAAK,UAAU;AAAA,MAC3B;AAAA,IACF;AACA,UAAM,cAAc,KAAK,MAAM,IAAI,aAAa;AAChD,UAAMA,UAAS,EAAE,SAAS,YAAY;AACtC,WAAO,OAAO,OAAO,CAAC,GAAG,YAAYA,OAAM;AAAA,EAC7C;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ,gBAAgB,CAAC,GAAG;AACjD,UAAM,QAAQ,CAAC;AACf,eAAW,cAAcA,QAAO,UAAU;AACxC,YAAM,KAAK,YAAY,YAAY,aAAa,CAAC;AAAA,IACnD;AACA,WAAO,IAAI,IAAI,EAAE,MAAM,CAAC;AAAA,EAC1B;AAAA,EACA,IAAI,mBAAmB;AACrB,QAAI,CAAC,KAAK,WAAW;AACnB,aAAO,CAAC;AAAA,IACV;AACA,UAAM,UAAU,CAAC;AACjB,eAAW,QAAQ,KAAK,OAAO;AAC7B,cAAQ,KAAK,GAAG,KAAK,gBAAgB;AAAA,IACvC;AACA,WAAO;AAAA,EACT;AAAA,EACA,IAAI,sBAAsB;AACxB,UAAM,UAAU,CAAC;AACjB,eAAW,QAAQ,KAAK,OAAO;AAC7B,cAAQ,KAAK,GAAG,KAAK,mBAAmB;AAAA,IAC1C;AACA,QAAI,CAAC,KAAK,WAAW;AACnB,YAAM,mBAAmB,CAAC;AAC1B,iBAAW,QAAQ,KAAK,OAAO;AAC7B,yBAAiB,KAAK,GAAG,KAAK,gBAAgB;AAAA,MAChD;AACA,aAAO,iBAAiB,OAAO,OAAO;AAAA,IACxC;AACA,WAAO;AAAA,EACT;AAAA,EACA,aAAa;AACX,UAAM,UAAU,CAAC;AACjB,eAAW,QAAQ,KAAK,OAAO;AAC7B,cAAQ,KAAK,GAAG,KAAK,OAAO;AAAA,IAC9B;AACA,WAAO,cAAc,OAAO;AAAA,EAC9B;AAAA,EACA,WAAW,SAAS;AAClB,UAAM,SAAS,CAAC;AAChB,eAAW,QAAQ,KAAK,OAAO;AAC7B,YAAM,YAAY,KAAK,QAAQ;AAC/B,YAAM,eAAe,QAAQ,OAAO,SAAS;AAC7C,eAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC/C,eAAO,KAAK,CAAC,KAAK,QAAQ,KAAK,aAAa,GAAG,CAAC;AAAA,MAClD;AAAA,IACF;AACA,kBAAc,MAAM;AAAA,EACtB;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,SAAS,oBAAoB,MAAM;AACjC,QAAM,EAAE,MAAM,OAAO,MAAM,WAAW,OAAO,OAAOP,UAAS,GAAG,YAAY,IAAI;AAChF,QAAM,gBAAgB,MAAM,eAAe,OAAO,YAAY,MAAM,GAAG,IAAI,IAAI,SAAS,MAAM,GAAG,IAAI;AACrG,QAAM,aAAa,MAAM,aAAa,eAAe,OAAO,QAAQ;AACpE,MAAI,CAACA,WAAUA,WAAU,GAAG;AAC1B,WAAO,KAAK,WAAW,EAAE,MAAM,CAAC;AAAA,EAClC;AACA,QAAM,QAAQ,MAAMA,OAAM,EAAE,KAAK,MAAM,EAAE,IAAI,UAAU;AACvD,SAAO,MAAM,IAAI,CAAC,MAAM,KAAK,EAAE,MAAM,CAAC,CAAC;AACzC;AAGA,IAAI,SAAS,SAAS,IAAI,IAAI;AAC5B,MAAI,KAAK,CAAC;AACV,WAAS,MAAM;AACb,QAAI,OAAO,UAAU,eAAe,KAAK,IAAI,EAAE,KAAK,GAAG,QAAQ,EAAE,IAAI;AACnE,SAAG,MAAM,GAAG;AAChB,MAAI,MAAM,QAAQ,OAAO,OAAO,0BAA0B;AACxD,aAAS,KAAK,GAAG,KAAK,OAAO,sBAAsB,EAAE,GAAG,KAAK,GAAG,QAAQ,MAAM;AAC5E,UAAI,GAAG,QAAQ,GAAG,GAAG,IAAI,KAAK,OAAO,UAAU,qBAAqB,KAAK,IAAI,GAAG,GAAG;AACjF,WAAG,GAAG,OAAO,GAAG,GAAG;AAAA,IACvB;AACF,SAAO;AACT;AACA,IAAI,YAAY,cAAc,IAAI;AAAA,EAChC,YAAY,MAAM;AAChB,QAAI,KAAK,QAAQ;AACf,YAAM,IAAI,oBAAoB,oDAAoD;AAAA,IACpF;AACA,QAAI,MAAM,QAAQ,KAAK,IAAI,GAAG;AAC5B,YAAM,IAAI,oBAAoB,gEAAgE;AAAA,IAChG;AACA,UAAM,IAAI;AACV,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,EAC9C;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,KAAK,KAAK,eAAe,MAAM;AACjC,gBAAQ,KAAK,KAAK,WAAW;AAC7B,aAAK,KAAK,cAAc;AAAA,MAC1B;AACA,UAAI,KAAK,KAAK,wBAAwB,MAAM;AAC1C,gBAAQ,KAAK,KAAK,oBAAoB;AACtC,aAAK,KAAK,uBAAuB;AAAA,MACnC;AACA,UAAI,UAAU,OAAO,cAAc;AACjC,cAAM,IAAI,WAAW,2CAA2C;AAAA,MAClE;AACA,YAAMF,QAAO,UAAU,OAAO,OAAO,OAAO;AAC5C,YAAM,WAAW,UAAU,OAAO,OAAO,OAAO;AAChD,YAAM,eAAe,UAAU,OAAO,OAAO,OAAO;AACpD,aAAO,MAAM,KAAK,QAAQ,EAAE,MAAAA,OAAM,UAAU,aAAa,CAAC;AAAA,IAC5D,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,QAAI,WAAW,KAAK,yBAAyB,UAAU;AACvD,QAAI,CAAC,KAAK,iBAAiB;AACzB,iBAAW,CAAC,SAAS,IAAI,GAAG,SAAS,MAAM,CAAC,CAAC;AAAA,IAC/C;AACA,QAAI,KAAK,aAAa;AACpB,iBAAW,CAAC,UAAU,GAAG,MAAM,CAAC,EAAE,KAAK,CAAC,WAAW,IAAI,GAAG,SAAS,MAAM,EAAE,CAAC,CAAC,CAAC;AAAA,IAChF;AACA,WAAO;AAAA,EACT;AAAA,EACA,gBAAgB,QAAQ;AACtB,WAAO,KAAK,MAAM;AAChB,YAAM,EAAE,UAAU,IAAI,KAAK;AAC3B,YAAM,aAAa,OAAO;AAC1B,YAAM,cAAc,KAAK,yBAAyB,UAAU;AAC5D,YAAM,aAAa,CAAC,YAAY,IAAI,GAAG,YAAY,MAAM,CAAC,CAAC;AAC3D,YAAM,eAAe,MAAM,UAAU;AACrC,UAAI,MAAM,QAAQ,SAAS,GAAG;AAC5B,eAAO,MAAM,UAAU,MAAM,EAAE,KAAK,YAAY;AAAA,MAClD;AACA,aAAO,CAAC,YAAY;AAAA,IACtB,CAAC;AAAA,EACH;AAAA,EACA,YAAY,QAAQ,WAAW,OAAO;AACpC,SAAK,MAAM;AACT,UAAI,CAAC,KAAK,UAAU;AAClB,cAAM,IAAI,eAAe,iEAAiE;AAAA,MAC5F;AACA,YAAM,aAAa,KAAK,UAAU,GAAG;AACrC,YAAM,cAAc,KAAK,yBAAyB,UAAU;AAC5D,YAAM,aAAa,CAAC,YAAY,IAAI,GAAG,YAAY,MAAM,CAAC,CAAC;AAC3D,YAAM,YAAY,WAAW;AAC7B,UAAI,aAAa,MAAM;AACrB,cAAM,IAAI,WAAW,uUAAuU;AAAA,MAC9V;AACA,UAAI,KAAK,UAAU,KAAK,MAAM;AAC5B,YAAI,MAAM,QAAQ,KAAK,KAAK,SAAS,GAAG;AACtC,eAAK,UAAU,KAAK,KAAK,UAAU,IAAI,MAAM,MAAM,UAAU,CAAC;AAAA,QAChE,OAAO;AACL,eAAK,UAAU,CAAC,MAAM,UAAU,CAAC;AAAA,QACnC;AAAA,MACF,WAAW,UAAU,MAAM;AACzB,gBAAQ,KAAK,OAAO;AACpB,YAAI,KAAK,cAAc,MAAM;AAC3B,kBAAQ,KAAK,UAAU;AACvB,eAAK,aAAa,CAAC;AAAA,QACrB;AACA,YAAI,MAAM,QAAQ,KAAK,KAAK,SAAS,GAAG;AACtC,eAAK,UAAU,KAAK,KAAK,UAAU,IAAI,MAAM,MAAM,UAAU,CAAC;AAAA,QAChE,OAAO;AACL,eAAK,QAAQ,KAAK,MAAM,UAAU;AAAA,QACpC;AAAA,MACF,OAAO;AACL,YAAI,CAAC,MAAM,QAAQ,MAAM,GAAG;AAC1B,mBAAS,CAAC,MAAM;AAAA,QAClB;AACA,YAAI,OAAO,WAAW,KAAK,QAAQ,QAAQ;AACzC,gBAAM,IAAI,WAAW,SAAS,KAAK,gBAAgB,KAAK,QAAQ,oCAAoC,OAAO,0CAA0C,QAAQ;AAAA,QAC/J;AACA,YAAI,UAAU;AACZ,eAAK,WAAW,KAAK,KAAK,QAAQ,MAAM,CAAC;AAAA,QAC3C,OAAO;AACL,kBAAQ,KAAK,OAAO;AAAA,QACtB;AACA,iBAASI,SAAQ,GAAGA,SAAQ,KAAK,QAAQ,QAAQ,EAAEA,QAAO;AACxD,gBAAM,QAAQ,OAAOA;AACrB,gBAAM,gBAAgB;AACtB,cAAI,CAAC,aAAa,YAAY,MAAM,OAAO,aAAa,GAAG;AACzD,kBAAM,IAAI,WAAW,SAASA,qCAAoC,KAAK,wBAAwB,iCAAiC,MAAM,OAAO;AAAA,UAC/I;AACA,eAAK,QAAQA,UAAS;AAAA,QACxB;AAAA,MACF;AACA,WAAK,UAAU,KAAK,QAAQ,IAAI,CAAC,UAAU,KAAK,MAAM,MAAM,CAAC,CAAC;AAAA,IAChE,CAAC;AAAA,EACH;AAAA,EACA,yBAAyB,YAAY;AACnC,UAAM,EAAE,YAAY,SAAS,YAAY,SAAAkB,UAAS,SAAAf,UAAS,aAAa,IAAI,KAAK;AACjF,UAAM,kBAAkB,eAAe;AACvC,UAAM,IAAI,WAAW,kBAAkB,IAAI;AAC3C,UAAM,IAAI,WAAW,kBAAkB,IAAI;AAC3C,UAAM,OAAO,iBAAiB,GAAG,WAAW,IAAIe,UAASf,SAAQ,IAAI,aAAa,EAAE;AACpF,UAAM,OAAO,iBAAiB,GAAG,WAAW,IAAIe,UAASf,SAAQ,IAAI,aAAa,EAAE;AACpF,UAAM,WAAW;AAAA,MACf,GAAG,WAAW,MAAM,GAAG,CAAC;AAAA,MACxB,GAAG,kBAAkB,CAAC,SAAS,MAAM,IAAI,IAAI,CAAC,MAAM,MAAM,OAAO;AAAA,IACnE;AACA,WAAO;AAAA,EACT;AACF;AACA,UAAU,YAAY;AACtB,IAAI,iBAAiB,cAAc,SAAS;AAAA,EAC1C,YAAY,MAAM;AAChB,UAAM,EAAE,SAAS,YAAY,SAAAA,UAAS,SAAAe,UAAS,YAAY,aAAa,IAAI;AAC5E,UAAM,OAAO,OAAO,CAAC,GAAG,MAAM,EAAE,OAAO,QAAQ,CAAC,CAAC;AACjD,SAAK,UAAU;AACf,0BAAsB,KAAK,SAAS,SAAS;AAC7C,SAAK,aAAa,eAAe,YAAY,GAAG,YAAY;AAC5D,SAAK,WAAW,QAAQ,CAAC3B,UAAS,sBAAsBA,OAAM,YAAY,CAAC;AAC3E,SAAK,UAAU,eAAeY,YAAW,GAAG,GAAG,SAAS;AACxD,SAAK,QAAQ,QAAQ,CAAC,WAAW,sBAAsB,QAAQ,SAAS,CAAC;AACzE,SAAK,UAAUe,YAAW;AAC1B,qBAAiB,KAAK,OAAO;AAC7B,SAAK,aAAa,cAAc;AAChC,oBAAgB,KAAK,UAAU;AAC/B,SAAK,eAAe,eAAe,gBAAgB,GAAG,GAAG,cAAc;AACvE,SAAK,aAAa,QAAQ,CAAC,SAAS,sBAAsB,MAAM,cAAc,CAAC;AAAA,EACjF;AAAA,EACA,MAAM,YAAY;AAChB,QAAI;AACJ,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,cAAc,KAAK,eAAe,kBAAkB,IAAI,WAAW,SAAS;AAClF,QAAI,WAAW,gBAAgB,MAAM;AACnC,YAAM,IAAI,WAAW,+DAA+D,WAAW,cAAc;AAAA,IAC/G;AACA,UAAM,WAAW,WAAW;AAC5B,UAAM,eAAe;AACrB,UAAM,cAAc,KAAK,WAAW,OAAO,CAAC,UAAU,KAAK,UAAU,YAAY,CAAC;AAClF,SAAK,SAAS,KAAK,UAAU,UAAU,aAAa,MAAM,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AACrI,UAAM,uBAAuB,KAAK,WAAW,OAAO,CAAC,KAAK,SAAS,KAAK,UAAU,YAAY,CAAC;AAC/F,SAAK,kBAAkB,KAAK,UAAU,oBAAoB,sBAAsB,MAAM,KAAK,sBAAsB,KAAK,sBAAsB,MAAM,KAAK,mBAAmB;AAC1K,QAAI,KAAK,SAAS;AAChB,UAAI;AACJ,UAAI,KAAK,gBAAgB;AACvB,cAAMvB,SAAQ,KAAK;AACnB,cAAM,UAAU,KAAK;AACrB,0BAAkB,KAAK,KAAK,MAAM,mBAAmB,YAAY;AAAA,UAC/D,MAAM,OAAO,OAAO;AAClB,kBAAM,QAAQA,OAAM,MAAM,CAAC,OAAO,CAAC;AACnC,kBAAM,QAAQ,MAAM,CAAC,OAAO,CAAC;AAC7B,kBAAM,YAAYA,OAAM,MAAM,CAAC,UAAU,CAAC,CAAC;AAC3C,mBAAO,YAAY,CAAC,OAAO,OAAO,SAAS,CAAC;AAAA,UAC9C;AAAA,QACF,GAAG,GAAG,YAAY,cAAc,IAAI;AAAA,MACtC,OAAO;AACL,0BAAkB,KAAK;AAAA,MACzB;AACA,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,UAAU,YAAY,GAAG,MAAM,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IAC1I;AACA,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,OAAO,WAAW,GAAG;AACvB,cAAM,IAAI,WAAW,8DAA8D,OAAO,SAAS;AAAA,MACrG;AACA,YAAM,WAAW,OAAO,eAAe;AACvC,YAAM,IAAI,OAAO;AACjB,YAAM,WAAW,OAAO;AACxB,YAAM,WAAW,OAAO;AACxB,YAAM,eAAe;AACrB,UAAI,IAAI,KAAK,WAAW,KAAK,UAAU,KAAK,KAAK,eAAe,MAAM;AACpE,aAAK,cAAc,oBAAoB;AAAA,UACrC,MAAM,MAAM,SAAS,CAAC;AAAA,UACtB,MAAM,KAAK;AAAA,UACX;AAAA,UACA,OAAO;AAAA,UACP,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,YAAM,cAAc,KAAK;AACzB,YAAM,eAAe,CAAC,IAAIC,OAAMI,WAAU;AACxC,YAAI,CAACJ,SAAQ,CAACA,MAAKI,SAAQ;AACzB,iBAAO;AAAA,QACT;AACA,eAAO,IAAIJ,MAAKI,SAAQ,EAAE;AAAA,MAC5B;AACA,UAAI,KAAK,aAAa,GAAG,aAAa,CAAC;AACvC,UAAI,KAAK,aAAa,GAAG,aAAa,CAAC;AACvC,UAAI,KAAK,aAAa,GAAG,aAAa,CAAC;AACvC,UAAI,KAAK,aAAa,GAAG,aAAa,CAAC;AACvC,UAAI,IAAI,KAAK,oBAAoB,KAAK,mBAAmB,KAAK,KAAK,wBAAwB,MAAM;AAC/F,aAAK,uBAAuB,oBAAoB;AAAA,UAC9C,MAAM,MAAM,SAAS,QAAQ;AAAA,UAC7B,MAAM,KAAK;AAAA,UACX;AAAA,UACA,OAAO;AAAA,UACP,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,YAAM,iBAAiB,KAAK;AAC5B,UAAI,KAAK,aAAa,UAAU,gBAAgB,CAAC;AACjD,UAAI,KAAK,aAAa,UAAU,gBAAgB,CAAC;AACjD,UAAI,KAAK,aAAa,UAAU,gBAAgB,CAAC;AACjD,UAAI,KAAK,aAAa,UAAU,gBAAgB,CAAC;AACjD,YAAM,oBAAoB;AAC1B,YAAM,CAAC,SAAS,SAAS,SAAS,OAAO,IAAI,MAAM,KAAK,OAAO,KAAK,GAAG,cAAc,iBAAiB;AACtG,YAAM,CAAC,OAAO,OAAO,OAAO,KAAK,IAAI,KAAK,UAAU,MAAM,KAAK,KAAK,KAAK,GAAG,YAAY,IAAI,CAAC,MAAM,MAAM,MAAM,IAAI;AACnH,WAAK,KAAK,UAAU,IAAI,SAAS,OAAO,KAAK,OAAO;AACpD,WAAK,KAAK,UAAU,IAAI,SAAS,OAAO,KAAK,OAAO;AACpD,WAAK,KAAK,UAAU,IAAI,SAAS,OAAO,KAAK,OAAO;AACpD,WAAK,KAAK,UAAU,IAAI,SAAS,OAAO,KAAK,OAAO;AACpD,YAAM,CAAC,YAAY,YAAY,YAAY,UAAU,IAAI,MAAM,KAAK,gBAAgB,KAAK,GAAG,cAAc,iBAAiB;AAC3H,WAAK,KAAK,cAAc,IAAI,UAAU;AACtC,WAAK,KAAK,cAAc,IAAI,UAAU;AACtC,WAAK,KAAK,cAAc,IAAI,UAAU;AACtC,WAAK,KAAK,cAAc,IAAI,UAAU;AACtC,YAAM,KAAK,KAAK,oBAAoB,MAAM,KAAK,IAAI,EAAE,CAAC;AACtD,YAAM,IAAI,KAAK,oBAAoB,MAAM,KAAK,IAAI,EAAE,CAAC;AACrD,YAAM,IAAI,KAAK,IAAI,GAAG,QAAQ,GAAG,IAAI,IAAI,KAAK,WAAW,MAAM,KAAK,IAAI,EAAE,CAAC,CAAC,CAAC;AAC7E,YAAM,IAAI,IAAI,KAAK,oBAAoB,MAAM,KAAK,IAAI,EAAE,CAAC,GAAG,KAAK,WAAW,MAAM,CAAC,CAAC;AACpF,aAAO,CAAC,GAAG,GAAG,CAAC;AAAA,IACjB,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAM,KAAK,MAAM,UAAU,GAAG,EAAE,SAAS,EAAE,IAAI,IAAI,aAAa,OAAO,IAAI,CAAC,OAAO,CAAC;AACpF,UAAMK,UAAS;AAAA,MACb,SAAS,KAAK;AAAA,MACd,YAAY,KAAK;AAAA,MACjB,SAAS,KAAK;AAAA,MACd,YAAY,KAAK;AAAA,MACjB,cAAc,KAAK;AAAA,MACnB,SAAS,KAAK;AAAA,IAChB;AACA,WAAO,OAAO,OAAO,CAAC,GAAG,YAAYA,OAAM;AAAA,EAC7C;AAAA,EACA,UAAU,GAAG,GAAG,GAAGa,UAAS;AAC1B,UAAM,MAAM,OAAO,GAAG,GAAG,KAAK,SAASA,YAAW,SAAS,KAAK,eAAe,kBAAkB,SAAS,QAAQ,KAAK,YAAY;AACnI,QAAI,GAAG;AACL,aAAO,QAAQ,KAAK,GAAG,KAAK,UAAU;AAAA,IACxC;AACA,WAAO;AAAA,EACT;AAAA,EACA,cAAc,GAAG,GAAG;AAClB,UAAMf,WAAU;AAChB,WAAO,OAAO,GAAG,GAAGA,UAAS,QAAQ,KAAK,eAAe,kBAAkB,SAAS,MAAM;AAAA,EAC5F;AACF;AACA,eAAe,YAAY;AAC3B,sBAAsB,cAAc,cAAc;AAClD,IAAI,aAAa,cAAc,UAAU;AAAA,EACvC,YAAY,MAAM;AAChB,UAAM,OAAO,IAAI,eAAe,IAAI;AACpC,UAAM,OAAO,OAAO,CAAC,GAAG,MAAM,EAAE,KAAK,CAAC,CAAC;AAAA,EACzC;AAAA,EACA,OAAO,WAAW,KAAKE,SAAQ;AAC7B,WAAO,IAAI,IAAIA,OAAM;AAAA,EACvB;AACF;AACA,WAAW,YAAY;AACvB,sBAAsB,cAAc,UAAU;AAG9C,IAAI,UAAU,cAAc,MAAM;AAAA,EAChC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,OAAO,KAAK,IAAI,KAAK,IAAI,KAAK,MAAM,CAAC,GAAG,CAAC;AAC9C,SAAK,aAAa,KAAK;AACvB,SAAK,OAAO,KAAK;AACjB,SAAK,kBAAkB;AAAA,EACzB;AAAA,EACA,cAAc,QAAQ;AACpB,QAAI,KAAK,cAAc,MAAM;AAC3B,aAAO,KAAK;AAAA,IACd;AACA,UAAM,aAAa,OAAO;AAC1B,UAAM,aAAa,CAAC;AACpB,aAAS,KAAK,GAAG,KAAK,KAAK,WAAW,QAAQ,EAAE,IAAI;AAClD,iBAAW,KAAK,KAAK,WAAW,OAAO,OAAO,WAAW,MAAM,KAAK,WAAW,GAAG;AAAA,IACpF;AACA,WAAO;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,YAAM,SAAS,oBAAoB,MAAM;AACzC,UAAI,IAAI,KAAK,QAAQ,KAAK,OAAO,GAAG;AAClC,cAAM,WAAW,OAAO,eAAe,OAAO,QAAQ,OAAO;AAC7D,cAAM,aAAa,KAAK,cAAc,MAAM;AAC5C,cAAM,SAAS,aAAa,MAAM,SAAS,QAAQ,KAAK,MAAM,YAAY,KAAK,IAAI,GAAG,MAAM,QAAQ,QAAQ;AAC5G,eAAO;AAAA,MACT;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,MAAM,KAAK;AAAA,MACX,YAAY,KAAK;AAAA,MACjB,MAAM,KAAK;AAAA,IACb;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,UAAU;AACR,WAAO,MAAM,QAAQ;AAAA,EACvB;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,mBAAmB,cAAc,QAAQ;AAAA,EAC3C,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,YAAY,CAAC,EAAE,MAAM,EAAE,CAAC;AAAA,EAC/B;AAAA,EACA,cAAc,QAAQ;AACpB,UAAM,aAAa,OAAO;AAC1B,WAAO,CAAC,WAAW,IAAI,GAAG,WAAW,EAAE;AAAA,EACzC;AACF;AACA,iBAAiB,YAAY;AAC7B,sBAAsB,cAAc,gBAAgB;AACpD,IAAI,QAAQ,cAAc,MAAM;AAAA,EAC9B,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,aAAa;AAClB,SAAK,UAAU;AACf,SAAK,SAAS;AACd,SAAK,OAAO;AACZ,SAAK,6BAA6B;AAClC,SAAK,2BAA2B;AAChC,QAAI,KAAK,mBAAmB,QAAQ,KAAK,cAAc,QAAQ,KAAK,YAAY,MAAM;AACpF,UAAI,YAAY;AAChB,UAAI,KAAK,aAAa,MAAM;AAC1B,oBAAY,KAAK;AAAA,MACnB;AACA,WAAK,kBAAkB,CAAC,WAAW,KAAK,QAAQ;AAAA,IAClD;AACA,SAAK,QAAQ,KAAK;AAClB,0BAAsB,KAAK,OAAO,OAAO;AACzC,SAAK,aAAa,cAAc,KAAK,UAAU;AAC/C,QAAI,KAAK,WAAW,MAAM;AACxB,WAAK,UAAU,KAAK;AAAA,IACtB;AACA,SAAK,oBAAoB,eAAe,KAAK,qBAAqB,KAAK,0BAA0B;AACjG,SAAK,kBAAkB,eAAe,KAAK,mBAAmB,KAAK,wBAAwB;AAC3F,SAAK,mBAAmB,cAAc,KAAK,gBAAgB;AAC3D,SAAK,iBAAiB,cAAc,KAAK,cAAc;AACvD,SAAK,oBAAoB,eAAe,KAAK,iBAAiB;AAC9D,SAAK,kBAAkB,eAAe,KAAK,eAAe;AAC1D,SAAK,sBAAsB,eAAe,KAAK,mBAAmB;AAClE,SAAK,kBAAkB;AACvB,SAAK,YAAY,CAAC,EAAE,SAAS,EAAE,CAAC;AAAA,EAClC;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,eAAe,WAAW,WAAW,SAAS;AACpD,QAAI,KAAK,UAAU,MAAM;AACvB,WAAK,SAAS,KAAK,UAAU,UAAU,CAAC,cAAc,KAAK,KAAK,GAAG,MAAM,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AACpJ,UAAI,KAAK,SAAS;AAChB,aAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,KAAK,GAAG,MAAM,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,MAC9H;AAAA,IACF;AACA,SAAK,YAAY,CAAC,EAAE,SAAS,GAAG,MAAM,EAAE,CAAC,KAAK,aAAa,EAAE,CAAC;AAC9D,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,cAAc,WAAW,MAAM;AACrC,gBAAY,YAAY,SAAS,KAAK,KAAK;AAC3C,WAAO;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,YAAM,SAAS,oBAAoB,MAAM;AACzC,YAAM,sBAAsB,2BAA2B,KAAK,WAAW,aAAa,CAAC;AACrF,UAAI;AACJ,UAAI,uBAAuB,MAAM;AAC/B,iBAAS,KAAK,QAAQ,KAAK,OAAO,KAAK,GAAG,qBAAqB,KAAK,OAAO,KAAK,KAAK,KAAK,IAAI,IAAI;AAAA,MACpG,OAAO;AACL,iBAAS,KAAK,QAAQ,KAAK,OAAO,KAAK,CAAC;AACxC,YAAI,KAAK,QAAQ,MAAM;AACrB,mBAAS,QAAQ,QAAQ,KAAK,KAAK,KAAK,CAAC;AAAA,QAC3C;AACA,YAAI,KAAK,cAAc,MAAM;AAC3B,mBAAS,KAAK,WAAW,MAAM,MAAM;AAAA,QACvC;AAAA,MACF;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,OAAO,KAAK;AAAA,MACZ,YAAY,oBAAoB,KAAK,UAAU;AAAA,MAC/C,SAAS,KAAK;AAAA,MACd,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,qBAAqB,qBAAqB,KAAK,mBAAmB;AAAA,MAClE,kBAAkB,oBAAoB,KAAK,gBAAgB;AAAA,MAC3D,gBAAgB,oBAAoB,KAAK,cAAc;AAAA,IACzD;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,MAAM,YAAY;AAClB,sBAAsB,cAAc,KAAK;AACzC,IAAI,UAAU,cAAc,MAAM;AAAA,EAChC,YAAY,MAAM;AAChB,WAAO,QAAQ,CAAC;AAChB,UAAM,IAAI;AACV,SAAK,YAAY,CAAC,EAAE,SAAS,EAAE,CAAC;AAChC,SAAK,aAAa,KAAK;AAAA,EACzB;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,eAAW,OAAO,WAAW,MAAM,CAAC,GAAG;AACrC,UAAI,OAAO,MAAM;AACf,cAAM,IAAI,WAAW,iEAAiE,WAAW,MAAM,CAAC,kHAAkH;AAAA,MAC5N;AAAA,IACF;AACA,WAAO,CAAC,WAAW,IAAI,UAAU,YAAY,CAAC,CAAC;AAAA,EACjD;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,UAAI,SAAS,oBAAoB,MAAM;AACvC,UAAI,KAAK,eAAe,mBAAmB,OAAO,OAAO,GAAG;AAC1D,cAAM,cAAc,CAAC,CAAC;AACtB,iBAAS,KAAK,GAAG,KAAK,OAAO,MAAM,EAAE,IAAI;AACvC,sBAAY,KAAK,EAAE;AAAA,QACrB;AACA,oBAAY,KAAK,CAAC;AAClB,iBAAS,UAAU,QAAQ,WAAW;AAAA,MACxC;AACA,aAAO,aAAa,MAAM;AAAA,IAC5B,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,CAAC;AAChB,QAAI,KAAK,cAAc,MAAM;AAC3B,MAAAA,QAAO,gBAAgB,KAAK;AAAA,IAC9B;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,cAAc,cAAc,MAAM;AAAA,EACpC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,kBAAkB;AACvB,SAAK,aAAa,cAAc,KAAK,UAAU;AAAA,EACjD;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,YAAM,SAAS,oBAAoB,MAAM;AACzC,aAAO,KAAK,WAAW,MAAM,MAAM;AAAA,IACrC,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,EAAE,YAAY,oBAAoB,KAAK,UAAU,EAAE;AAClE,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,YAAY,YAAY;AACxB,sBAAsB,cAAc,WAAW;AAC/C,IAAI,eAAe,cAAc,MAAM;AAAA,EACrC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,IAAI,KAAK;AACd,SAAK,YAAY,CAAC,EAAE,MAAM,EAAE,CAAC;AAAA,EAC/B;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO,CAAC,WAAW,IAAI,KAAK,GAAG,WAAW,EAAE;AAAA,EAC9C;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS,oBAAoB,MAAM;AACnC,aAAO,OAAO,QAAQ,KAAK,CAAC;AAAA,IAC9B,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,GAAG,KAAK;AAAA,IACV;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAChD,IAAI,WAAW,cAAc,MAAM;AAAA,EACjC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,cAAc,KAAK;AACxB,aAAS,KAAK,GAAG,KAAK,KAAK,YAAY,QAAQ,EAAE,IAAI;AACnD,UAAI,KAAK,UAAU,KAAK,YAAY,GAAG,GAAG;AACxC,aAAK,YAAY,MAAM;AAAA,MACzB;AAAA,IACF;AAAA,EACF;AAAA,EACA,UAAU,KAAK;AACb,WAAO,MAAM,KAAK,OAAO;AAAA,EAC3B;AAAA,EACA,oBAAoB,YAAY,aAAa;AAC3C,UAAM,WAAW;AACjB,UAAM,aAAa,YAAY,MAAM;AACrC,QAAI,QAAQ;AACZ,QAAI,UAAU;AACd,aAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,YAAM,MAAM,WAAW;AACvB,UAAI,KAAK,UAAU,GAAG,GAAG;AACvB,YAAI,YAAY,MAAM;AACpB,oBAAU;AAAA,QACZ,OAAO;AACL,gBAAM,IAAI,WAAW,0CAA0C;AAAA,QACjE;AAAA,MACF,OAAO;AACL,iBAAS;AAAA,MACX;AAAA,IACF;AACA,UAAM,eAAe,UAAU,UAAU;AACzC,QAAI,YAAY,MAAM;AACpB,UAAI,UAAU,KAAK,eAAe,UAAU,GAAG;AAC7C,cAAM,IAAI,WAAW,QAAQ;AAAA,MAC/B;AACA,iBAAW,WAAW,eAAe;AAAA,IACvC,WAAW,iBAAiB,OAAO;AACjC,YAAM,IAAI,WAAW,QAAQ;AAAA,IAC/B;AACA,WAAO;AAAA,EACT;AAAA,EACA,mBAAmB,YAAY;AAC7B,QAAI,iBAAiB;AACrB,aAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,UAAI,KAAK,UAAU,WAAW,GAAG,GAAG;AAClC,yBAAiB;AACjB;AAAA,MACF;AAAA,IACF;AACA,QAAI,gBAAgB;AAClB,aAAO,WAAW,MAAM,GAAG,CAAC,EAAE,OAAO,KAAK,WAAW;AAAA,IACvD,OAAO;AACL,aAAO,WAAW,MAAM,GAAG,CAAC,EAAE,OAAO,KAAK,oBAAoB,WAAW,MAAM,CAAC,GAAG,KAAK,WAAW,CAAC;AAAA,IACtG;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,YAAM,SAAS,oBAAoB,MAAM;AACzC,YAAM,aAAa,OAAO;AAC1B,YAAM,cAAc,WAAW,MAAM,GAAG,CAAC,EAAE,OAAO,KAAK,oBAAoB,WAAW,MAAM,CAAC,GAAG,KAAK,WAAW,CAAC;AACjH,aAAO,QAAQ,QAAQ,WAAW;AAAA,IACpC,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,aAAa,KAAK;AAAA,IACpB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,UAAU,cAAc,MAAM;AAAA,EAChC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,QAAI,KAAK,QAAQ,MAAM;AACrB,YAAM,IAAI,MAAM,iFAAiF;AAAA,IACnG;AACA,QAAI,CAAC,MAAM,QAAQ,KAAK,IAAI,GAAG;AAC7B,YAAM,IAAI,MAAM,sEAAsE,KAAK,eAAe;AAAA,IAC5G;AACA,UAAM,wBAAwB,OAAO,GAAG,KAAK,KAAK,SAAS,CAAC;AAC5D,QAAI,CAAC,aAAa,YAAY,KAAK,KAAK,MAAM,EAAE,KAAK,GAAG,qBAAqB,GAAG;AAC9E,YAAM,IAAI,MAAM,iCAAiC,KAAK,UAAU,KAAK,IAAI,IAAI,4DAA4D;AAAA,IAC3I;AACA,SAAK,OAAO,KAAK;AACjB,SAAK,qBAAqB,CAAC,CAAC,EAAE,OAAO,KAAK,IAAI;AAC9C,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,KAAK,KAAK,SAAS,EAAE,CAAC,CAAC;AAAA,EACjE;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,cAAc,WAAW,MAAM;AACrC,SAAK,KAAK,QAAQ,CAAC,KAAK,OAAO;AAC7B,kBAAY,KAAK,KAAK,WAAW;AAAA,IACnC,CAAC;AACD,WAAO;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,UAAU,oBAAoB,MAAM,GAAG,KAAK,kBAAkB;AAAA,EACvE;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,MAAM,KAAK;AAAA,IACb;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,UAAU,cAAc,MAAM;AAAA,EAChC,YAAY,MAAM;AAChB,UAAM,QAAQ,OAAO,CAAC,IAAI,IAAI;AAC9B,SAAK,kBAAkB;AACvB,QAAI,QAAQ,MAAM;AAChB,WAAK,YAAY,KAAK,aAAa,OAAO,IAAI,KAAK;AAAA,IACrD,OAAO;AACL,WAAK,YAAY;AAAA,IACnB;AAAA,EACF;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMA,UAAS,EAAE,WAAW,KAAK,UAAU;AAC3C,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,YAAY,QAAQT,OAAM;AACxB,UAAM,SAAS,oBAAoB,MAAM;AACzC,UAAM,OAAO;AACb,WAAO,IAAI,SAAS,QAAQ,KAAK,SAAS,GAAG,IAAI;AAAA,EACnD;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,YAAM,SAAS,oBAAoB,MAAM;AACzC,YAAM,OAAO;AACb,YAAM,WAAW;AACjB,YAAM,cAAc,IAAI,SAAS,QAAQ,KAAK,SAAS,GAAG,MAAM,QAAQ;AACxE,YAAM,SAAS,IAAI,QAAQ,KAAK,aAAa,OAAO,KAAK,CAAC;AAC1D,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAG3C,IAAI,YAAY,cAAc,MAAM;AAAA,EAClC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,aAAa;AAClB,SAAK,iCAAiC;AACtC,QAAI,KAAK,mBAAmB,QAAQ,KAAK,cAAc,MAAM;AAC3D,UAAI,YAAY;AAChB,UAAI,KAAK,aAAa,MAAM;AAC1B,oBAAY,KAAK;AAAA,MACnB;AACA,UAAI,KAAK,eAAe,MAAM;AAC5B,aAAK,kBAAkB,CAAC,WAAW,IAAI;AAAA,MACzC,OAAO;AACL,aAAK,kBAAkB,CAAC,SAAS,EAAE,OAAO,OAAO,KAAK,WAAW,CAAC;AAAA,MACpE;AAAA,IACF;AACA,SAAK,WAAW,KAAK;AACrB,0BAAsB,KAAK,UAAU,UAAU;AAC/C,SAAK,YAAY,KAAK;AACtB,0BAAsB,KAAK,WAAW,WAAW;AACjD,SAAK,wBAAwB,eAAe,KAAK,yBAAyB,KAAK,8BAA8B;AAC7G,SAAK,wBAAwB,eAAe,KAAK,qBAAqB;AACtE,SAAK,sBAAsB,eAAe,KAAK,mBAAmB;AAClE,SAAK,uBAAuB,cAAc,KAAK,oBAAoB;AACnE,SAAK,WAAW,KAAK;AACrB,SAAK,kBAAkB,KAAK;AAC5B,SAAK,cAAc,KAAK;AAAA,EAC1B;AAAA,EACA,MAAM,YAAY;AAChB,SAAK,aAAa,KAAK,UAAU,cAAc,CAAC,KAAK,UAAU,KAAK,SAAS,GAAG,KAAK,OAAO,KAAK,uBAAuB,KAAK,uBAAuB,MAAM,KAAK,oBAAoB;AACnL,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,6BAA6B,YAAY;AAAA,EACzC;AAAA,EACA,YAAY,QAAQA,OAAM;AACxB,WAAO,KAAK,MAAM;AAChB,UAAI,CAAC,KAAK,UAAU;AAClB,eAAO;AAAA,MACT,OAAO;AACL,iBAAS,oBAAoB,MAAM;AACnC,eAAO,SAAS,QAAQ,UAAU,MAAM,CAAC;AAAA,MAC3C;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,KAAK,eAAe,MAAM;AAC5B,aAAO,CAAC,GAAG,YAAY,KAAK,SAAS;AAAA,IACvC;AACA,UAAM,SAAS,OAAO,KAAK,WAAW;AACtC,QAAI,OAAO,WAAW,WAAW,SAAS,GAAG;AAC3C,YAAM,IAAI,WAAW,oBAAoB,KAAK,mDAAmD,YAAY;AAAA,IAC/G,OAAO;AACL,UAAI,KAAK;AACT,eAAS,IAAI,GAAG,IAAI,OAAO,QAAQ,EAAE,GAAG;AACtC,cAAM,KAAK,OAAO;AAClB,cAAM,KAAK,WAAW,IAAI;AAC1B,YAAI,MAAM,QAAQ,MAAM,QAAQ,OAAO,IAAI;AACzC,gBAAM,IAAI,WAAW,oBAAoB,KAAK,mDAAmD,YAAY;AAAA,QAC/G,WAAW,MAAM,MAAM;AACrB,iBAAO,MAAM;AAAA,QACf;AACA;AAAA,MACF;AAAA,IACF;AACA,WAAO,CAAC,WAAW,IAAI,GAAG,QAAQ,KAAK,SAAS;AAAA,EAClD;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,UAAI,SAAS,oBAAoB,MAAM;AACvC,UAAI,OAAO,UAAU,SAAS;AAC5B,iBAAS,MAAM,QAAQ,OAAO;AAAA,MAChC;AACA,YAAM,SAAS,QAAQ,KAAK,WAAW,KAAK,GAAG,QAAQ,QAAQ,CAAC,OAAO,IAAI,CAAC,CAAC;AAC7E,aAAO,QAAQ,QAAQ,mBAAmB,KAAK,mBAAmB,OAAO,KAAK,CAAC,CAAC;AAAA,IAClF,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMS,UAAS;AAAA,MACb,UAAU,KAAK;AAAA,MACf,WAAW,KAAK;AAAA,MAChB,uBAAuB,qBAAqB,KAAK,qBAAqB;AAAA,MACtE,uBAAuB,qBAAqB,KAAK,qBAAqB;AAAA,MACtE,qBAAqB,qBAAqB,KAAK,mBAAmB;AAAA,MAClE,sBAAsB,oBAAoB,KAAK,oBAAoB;AAAA,MACnE,UAAU,KAAK;AAAA,MACf,aAAa,KAAK;AAAA,IACpB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,UAAU,YAAY;AACtB,sBAAsB,cAAc,SAAS;AAG7C,IAAI,QAAQ,cAAc,MAAM;AAAA,EAC9B,YAAY,MAAM;AAChB,UAAM,QAAQ,CAAC,CAAC;AAChB,SAAK,kBAAkB;AAAA,EACzB;AAAA,EACA,cAAc,QAAQ;AACpB,UAAM,IAAI,oBAAoB;AAAA,EAChC;AAAA,EACA,gCAAgC,QAAQ,QAAQ;AAC9C,QAAI,UAAU,QAAQ,UAAU,MAAM;AACpC,aAAO;AAAA,IACT,WAAW,OAAO,SAAS,OAAO,QAAQ;AACxC,aAAO,KAAK,gCAAgC,QAAQ,MAAM;AAAA,IAC5D,WAAW,OAAO,WAAW,GAAG;AAC9B,aAAO;AAAA,IACT;AACA,UAAM,cAAc,OAAO,MAAM,GAAG,OAAO,SAAS,OAAO,MAAM;AACjE,aAAS,IAAI,GAAG,IAAI,OAAO,QAAQ,EAAE,GAAG;AACtC,YAAM,KAAK,OAAO,OAAO,SAAS,OAAO,SAAS;AAClD,YAAM,IAAI,OAAO;AACjB,UAAI,MAAM,QAAQ,KAAK,QAAQ,KAAK,KAAK,IAAI,GAAG;AAC9C,oBAAY,KAAK,IAAI;AAAA,MACvB,WAAW,OAAO,GAAG;AACnB,oBAAY,KAAK,CAAC;AAAA,MACpB,WAAW,MAAM,GAAG;AAClB,oBAAY,KAAK,EAAE;AAAA,MACrB,OAAO;AACL,YAAI,OAAO,GAAG;AACZ,gBAAM,IAAI,WAAW,0DAA0D,KAAK,UAAU,MAAM,IAAI,MAAM,KAAK,UAAU,MAAM,CAAC;AAAA,QACtI;AACA,oBAAY,KAAK,EAAE;AAAA,MACrB;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,YAAY;AAChB,QAAI,MAAM,QAAQ,UAAU,KAAK,CAAC,MAAM,QAAQ,WAAW,EAAE,GAAG;AAC9D,mBAAa,CAAC,mBAAmB,UAAU,CAAC;AAAA,IAC9C;AACA,iBAAa;AACb,QAAI,WAAW,SAAS,GAAG;AACzB,YAAM,IAAI,WAAW,wEAAwE,WAAW,kBAAkB;AAAA,IAC5H;AACA,QAAI,aAAa,CAAC;AAClB,eAAW,SAAS,YAAY;AAC9B,UAAI,SAAS,QAAQ,MAAM,OAAO,MAAM;AACtC,mBAAW,KAAK,MAAM,EAAE;AAAA,MAC1B;AAAA,IACF;AACA,iBAAa,QAAQ,UAAU;AAC/B,QAAI,WAAW,SAAS,GAAG;AACzB,YAAM,IAAI,WAAW,8EAA8E,KAAK,UAAU,UAAU,IAAI;AAAA,IAClI;AACA,QAAI,cAAc,WAAW,MAAM,OAAO,OAAO,WAAW,GAAG,MAAM,CAAC;AACtE,aAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,YAAM,QAAQ,WAAW,OAAO,OAAO,OAAO,WAAW,IAAI,MAAM,CAAC;AACpE,oBAAc,KAAK,gCAAgC,aAAa,KAAK;AAAA,IACvE;AACA,UAAM,WAAW,WAAW,IAAI,CAAC,UAAU,MAAM,MAAM;AACvD,QAAI,WAAW,QAAQ,IAAI,MAAM,MAAM,QAAQ,QAAQ,EAAE,WAAW,GAAG;AACrE,WAAK,kBAAkB;AAAA,IACzB,OAAO;AACL,WAAK,kBAAkB;AAAA,IACzB;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS;AACT,UAAI,KAAK,iBAAiB;AACxB,cAAM,iBAAiB,CAAC;AACxB,cAAM,YAAY,OAAO,IAAI,CAAC,WAAW,OAAO,IAAI;AACpD,YAAI,UAAU,QAAQ,IAAI,MAAM,IAAI;AAClC,gBAAM,UAAU,KAAK,SAAS;AAC9B,mBAAS,KAAK,QAAQ;AACpB,kBAAM,QAAQ,EAAE;AAChB,qBAAS,IAAI,GAAG,IAAI,UAAU,OAAO,EAAE,GAAG;AACxC,kBAAI,YAAY,GAAG,CAAC;AAAA,YACtB;AACA,2BAAe,KAAK,CAAC;AAAA,UACvB;AACA,iBAAO,KAAK,cAAc,cAAc;AAAA,QAC1C,OAAO;AACL,cAAI,aAAa;AACjB,qBAAW,KAAK,QAAQ;AACtB,kBAAM,QAAQ,EAAE;AAChB,gBAAI,SAAS,MAAM;AACjB,oBAAM,SAAS,EAAE;AACjB,oBAAM,YAAY,OAAO;AACzB,oBAAM,WAAW,OAAO,MAAM,CAAC,EAAE,OAAO,CAAC,SAAS,CAAC;AACnD,kBAAI,cAAc,QAAQ,GAAG,CAAC,SAAS,EAAE,OAAO,UAAU,OAAO,MAAM,CAAC,CAAC,CAAC,CAAC;AAC3E,4BAAc,UAAU,aAAa,CAAC,GAAG,CAAC,CAAC;AAC3C,4BAAc,QAAQ,aAAa,QAAQ;AAC3C,6BAAe,KAAK,WAAW;AAC/B,2BAAa;AAAA,YACf,WAAW,QAAQ,GAAG;AACpB,oBAAM,OAAO,OAAO,GAAG,KAAK,EAAE,OAAO,CAAC,CAAC,CAAC;AACxC,6BAAe,KAAK,UAAU,GAAG,IAAI,CAAC;AACtC,2BAAa;AAAA,YACf,OAAO;AACL,6BAAe,KAAK,CAAC;AAAA,YACvB;AAAA,UACF;AACA,cAAI,IAAI,KAAK,cAAc,cAAc;AACzC,gBAAM,QAAQ,EAAE;AAChB,cAAI,YAAY;AACd,gBAAI,SAAS,MAAM;AACjB,oBAAM,SAAS,EAAE;AACjB,oBAAM,SAAS,OAAO;AACtB,oBAAM,YAAY,OAAO,SAAS;AAClC,oBAAM,WAAW,CAAC,SAAS,EAAE,OAAO,OAAO,MAAM,GAAG,OAAO,SAAS,CAAC,CAAC;AACtE,kBAAI,QAAQ,UAAU,QAAQ,GAAG,CAAC,IAAI,SAAS,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC,GAAG,QAAQ;AAAA,YACtE,WAAW,QAAQ,GAAG;AACpB,oBAAM,OAAO,CAAC,QAAQ,CAAC,EAAE,OAAO,OAAO,GAAG,QAAQ,CAAC,CAAC;AACpD,kBAAI,UAAU,GAAG,IAAI;AAAA,YACvB;AAAA,UACF;AACA,iBAAO;AAAA,QACT;AAAA,MACF,OAAO;AACL,eAAO,KAAK,cAAc,MAAM;AAAA,MAClC;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa;AACb,QAAI;AACJ,QAAI,WAAW,MAAM,MAAM;AACzB,oBAAc;AAAA,IAChB,OAAO;AACL,oBAAc,WAAW,GAAG,MAAM,CAAC;AAAA,IACrC;AACA,aAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,YAAM,QAAQ,WAAW,OAAO,OAAO,OAAO,WAAW,IAAI,MAAM,CAAC;AACpE,oBAAc,KAAK,gCAAgC,aAAa,KAAK;AAAA,IACvE;AACA,QAAI,aAAa,CAAC;AAClB,eAAW,SAAS,YAAY;AAC9B,UAAI,SAAS,QAAQ,MAAM,OAAO,MAAM;AACtC,mBAAW,KAAK,MAAM,EAAE;AAAA,MAC1B;AAAA,IACF;AACA,iBAAa,QAAQ,UAAU;AAC/B,QAAI,WAAW,WAAW,GAAG;AAC3B,oBAAc,WAAW,OAAO,WAAW;AAAA,IAC7C,OAAO;AACL,oBAAc,CAAC,IAAI,EAAE,OAAO,WAAW;AAAA,IACzC;AACA,WAAO;AAAA,EACT;AAAA,EACA,YAAY,QAAQT,OAAM;AACxB,WAAO,KAAK,MAAM;AAChB,UAAIA,SAAQ,MAAM;AAChB,eAAO;AAAA,MACT;AACA,UAAI,CAAC,MAAM,QAAQA,KAAI,GAAG;AACxB,cAAM,IAAI,WAAW,2BAA2B;AAAA,MAClD;AACA,UAAI,CAAC,MAAM,QAAQ,MAAM,GAAG;AAC1B,cAAM,IAAI,WAAW,6BAA6B;AAAA,MACpD;AACA,UAAIA,MAAK,WAAW,OAAO,QAAQ;AACjC,cAAM,IAAI,WAAW,mGAAmG,OAAO,aAAaA,MAAK,SAAS;AAAA,MAC5J;AACA,UAAIA,MAAK,MAAM,CAAC,MAAM,KAAK,IAAI,GAAG;AAChC,eAAO;AAAA,MACT;AACA,MAAAA,QAAOA,MAAK,IAAI,CAAC,MAAM,KAAK,OAAO,IAAI,WAAW,GAAG,CAAC,CAAC;AACvD,UAAI,SAASA,MAAK;AAClB,eAAS,KAAK,GAAG,KAAKA,MAAK,SAAS,GAAG,EAAE,IAAI;AAC3C,iBAAS,WAAW,QAAQA,MAAK,GAAG;AAAA,MACtC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,IAAI,OAAO,cAAc,MAAM;AAAA,EAC7B,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,cAAc,QAAQ;AACpB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,OAAO,GAAG,MAAM;AAC7B,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,iBAAS,KAAK,QAAQ,OAAO,GAAG;AAAA,MAClC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,KAAK,YAAY;AACjB,sBAAsB,cAAc,IAAI;AACxC,IAAI,YAAY,cAAc,MAAM;AAAA,EAClC,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,cAAc,QAAQ;AACpB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,OAAO,GAAG,MAAM;AAC7B,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,iBAAS,IAAI,QAAQ,OAAO,GAAG;AAAA,MACjC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,UAAU,YAAY;AACtB,sBAAsB,cAAc,SAAS;AAC7C,IAAI,UAAU,cAAc,MAAM;AAAA,EAChC,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,cAAc,QAAQ;AACpB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,OAAO,GAAG,MAAM;AAC7B,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,iBAAS,KAAK,QAAQ,OAAO,GAAG;AAAA,MAClC;AACA,aAAO,IAAI,IAAI,OAAO,QAAQ,MAAM;AAAA,IACtC,CAAC;AAAA,EACH;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,WAAW,cAAc,MAAM;AAAA,EACjC,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,cAAc,QAAQ;AACpB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,OAAO;AACpB,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,iBAAS,QAAQ,QAAQ,OAAO,GAAG;AAAA,MACrC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,WAAW,cAAc,MAAM;AAAA,EACjC,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,cAAc,QAAQ;AACpB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,OAAO;AACpB,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,iBAAS,QAAQ,QAAQ,OAAO,GAAG;AAAA,MACrC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,cAAc,cAAc,MAAM;AAAA,EACpC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,eAAe;AACpB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,eAAe,KAAK;AACzD,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AAAA,EACzB;AAAA,EACA,MAAM,YAAY;AAChB,QAAI,EAAE,MAAM,QAAQ,UAAU,KAAK,MAAM,QAAQ,WAAW,EAAE,MAAM,WAAW,WAAW,GAAG;AAC3F,YAAM,IAAI,WAAW,uEAAuE;AAAA,IAC9F;AACA,iBAAa;AACb,QAAI,eAAe;AACnB,eAAW,SAAS,YAAY;AAC9B,UAAI,SAAS,MAAM;AACjB,uBAAe;AACf;AAAA,MACF;AAAA,IACF;AACA,QAAI,cAAc;AAChB;AAAA,IACF;AACA,UAAM,WAAW,CAAC;AAClB,aAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,YAAM,yBAAyB,WAAW,IAAI,MAAM;AACpD,6BAAuB,OAAO,KAAK,MAAM,CAAC;AAC1C,UAAI,SAAS;AACb,iBAAW,SAAS,UAAU;AAC5B,YAAI,aAAa,YAAY,OAAO,sBAAsB,GAAG;AAC3D,mBAAS;AACT;AAAA,QACF;AAAA,MACF;AACA,UAAI,CAAC,QAAQ;AACX,iBAAS,KAAK,sBAAsB;AAAA,MACtC;AAAA,IACF;AACA,QAAI,SAAS,SAAS,GAAG;AACvB,YAAM,IAAI,WAAW,8GAA8G,KAAK,UAAU,UAAU,CAAC;AAAA,IAC/J;AAAA,EACF;AAAA,EACA,cAAc,QAAQ;AACpB,WAAO,KAAK,MAAM;AAChB,aAAO,YAAY,QAAQ,KAAK,IAAI;AAAA,IACtC,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,QAAI,EAAE,MAAM,QAAQ,UAAU,KAAK,MAAM,QAAQ,WAAW,EAAE,IAAI;AAChE,YAAM,IAAI,WAAW,6DAA6D;AAAA,IACpF;AACA,UAAM,cAAc;AACpB,UAAM,cAAc,YAAY,GAAG,MAAM;AACzC,UAAM,OAAO,KAAK,OAAO,IAAI,YAAY,SAAS,KAAK,OAAO,KAAK;AACnE,eAAW,SAAS,YAAY,MAAM,CAAC,GAAG;AACxC,UAAI,YAAY,SAAS,QAAQ,MAAM,SAAS,MAAM;AACpD,oBAAY,QAAQ;AACpB;AAAA,MACF;AACA,kBAAY,SAAS,MAAM;AAAA,IAC7B;AACA,WAAO;AAAA,EACT;AAAA,EACA,YAAY,QAAQA,OAAM;AACxB,QAAIA,SAAQ,MAAM;AAChB,aAAO;AAAA,IACT;AACA,QAAI,CAAC,MAAM,QAAQA,KAAI,GAAG;AACxB,YAAM,IAAI,WAAW,2CAA2C;AAAA,IAClE;AACA,QAAI,CAAC,MAAM,QAAQ,MAAM,GAAG;AAC1B,YAAM,IAAI,WAAW,6CAA6C;AAAA,IACpE;AACA,QAAIA,MAAK,WAAW,OAAO,QAAQ;AACjC,YAAM,IAAI,WAAW,mCAAmCA,MAAK,qCAAqC,OAAO,SAAS;AAAA,IACpH;AACA,WAAO,KAAK,MAAM;AAChB,UAAI,eAAe;AACnB,MAAAA,MAAK,QAAQ,CAAC,MAAM;AAClB,YAAI,KAAK,MAAM;AACb,yBAAe;AACf;AAAA,QACF;AAAA,MACF,CAAC;AACD,UAAI,cAAc;AAChB,eAAO;AAAA,MACT;AACA,YAAM,cAAc,CAAC;AACrB,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,YAAIA,MAAK,OAAO,MAAM;AACpB,sBAAY,KAAK,KAAK,SAAS,OAAO,GAAG,GAAG,MAAM,CAAC;AAAA,QACrD,WAAWA,MAAK,IAAI,OAAO,OAAO,IAAI,MAAM;AAC1C,sBAAY,KAAK,WAAWA,MAAK,KAAK,EAAE,CAAC;AAAA,QAC3C,OAAO;AACL,sBAAY,KAAKA,MAAK,GAAG;AAAA,QAC3B;AAAA,MACF;AACA,YAAM,oBAAoB,OAAO,aAAa,KAAK,IAAI;AACvD,aAAO,IAAI,mBAAmB,IAAI,KAAK;AAAA,IACzC,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMS,UAAS;AAAA,MACb,QAAQ,KAAK;AAAA,IACf;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,YAAY,YAAY;AACxB,sBAAsB,cAAc,WAAW;AAC/C,SAAS,cAAc,MAAM,KAAK;AAChC,SAAO,OAAO,GAAG;AACf,YAAQ;AAAA,EACV;AACA,SAAO;AACT;AACA,SAAS,SAAS,GAAG,GAAG,MAAM;AAC5B,MAAI,EAAE,MAAM,SAAS,KAAK,EAAE,MAAM,SAAS,GAAG;AAC5C,UAAM,IAAI,oBAAoB,kEAAkE;AAAA,EAClG;AACA,eAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,uDAAuD,EAAE,MAAM,QAAQ;AACtH,eAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,uDAAuD,EAAE,MAAM,QAAQ;AACtH,MAAI,OAAO,SAAS,UAAU;AAC5B,WAAO,CAAC,MAAM,IAAI;AAAA,EACpB;AACA,MAAI,EAAE,UAAU,eAAe,EAAE,UAAU,aAAa;AACtD,UAAM,IAAI,oBAAoB,6DAA6D;AAAA,EAC7F;AACA,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,EAAE,MAAM;AACtB,MAAI,QAAQ,MAAM;AAChB,WAAO,CAAC,QAAQ,GAAG,QAAQ,CAAC;AAAA,EAC9B;AACA,QAAM,YAAY;AAClB,SAAO,KAAK,MAAM;AAChB,QAAI;AACJ,QAAI,QAAQ,OAAO;AACjB,aAAO,QAAQ;AACf,YAAM,YAAY,CAAC;AACnB,eAAS,KAAK,GAAG,KAAK,MAAM,EAAE,IAAI;AAChC,kBAAU,KAAK,CAAC;AAAA,MAClB;AACA,UAAI,QAAQ,GAAG,EAAE,MAAM,OAAO,SAAS,CAAC;AAAA,IAC1C,WAAW,QAAQ,OAAO;AACxB,aAAO,QAAQ;AACf,YAAM,YAAY,CAAC;AACnB,eAAS,KAAK,GAAG,KAAK,MAAM,EAAE,IAAI;AAChC,kBAAU,KAAK,CAAC;AAAA,MAClB;AACA,UAAI,QAAQ,GAAG,EAAE,MAAM,OAAO,SAAS,CAAC;AAAA,IAC1C,OAAO;AACL,aAAO;AAAA,IACT;AACA,QAAI;AACJ,QAAI,EAAE,MAAM,WAAW,KAAK,EAAE,MAAM,WAAW,GAAG;AAChD,UAAI,UAAU,OAAO,UAAU,IAAI;AACjC,cAAM,KAAK,IAAI,GAAG,CAAC,GAAG,UAAU,EAAE;AAAA,MACpC,OAAO;AACL,cAAM,KAAK,IAAI,UAAU,GAAG,CAAC,GAAG,CAAC,CAAC,GAAG,CAAC,GAAG,UAAU,EAAE;AAAA,MACvD;AAAA,IACF,OAAO;AACL,YAAM,OAAO,UAAU,OAAO,EAAE,MAAM,SAAS;AAC/C,YAAM,OAAO,UAAU,OAAO,EAAE,MAAM,SAAS;AAC/C,YAAM,OAAO,GAAG,GAAG,MAAM,IAAI;AAAA,IAC/B;AACA,QAAI,OAAO,GAAG;AACZ,UAAI;AACJ,UAAI,QAAQ,OAAO;AACjB,cAAM,QAAQ,QAAQ;AAAA,MACxB,OAAO;AACL,cAAM,QAAQ;AAAA,MAChB;AACA,YAAM,cAAc,CAAC;AACrB,eAAS,KAAK,KAAK,KAAK,MAAM,MAAM,EAAE,IAAI;AACxC,oBAAY,KAAK,EAAE;AAAA,MACrB;AACA,YAAM,QAAQ,KAAK,WAAW;AAAA,IAChC;AACA,QAAI,IAAI,MAAM,WAAW,GAAG;AAC1B,YAAM,WAAW,KAAK,CAAC;AAAA,IACzB;AACA,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,MAAM,cAAc,MAAM;AAAA,EAC5B,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,OAAO,KAAK;AACjB,SAAK,YAAY,KAAK,aAAa,OAAO,QAAQ,KAAK;AACvD,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AAAA,EACzB;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,OAAO,MAAM,QAAQ,UAAU,KAAK,WAAW,WAAW,KAAK,MAAM,QAAQ,WAAW,EAAE,KAAK,MAAM,QAAQ,WAAW,EAAE,GAAG,MAAM,+DAA+D;AAC/M,UAAM,SAAS,WAAW;AAC1B,UAAM,SAAS,WAAW;AAC1B,QAAI,OAAO,SAAS,KAAK,OAAO,SAAS,GAAG;AAC1C,YAAM,IAAI,oBAAoB,8DAA8D;AAAA,IAC9F;AACA,UAAM,OAAO,KAAK,cAAc,QAAQ,MAAM;AAC9C,QAAI,OAAO,KAAK,QAAQ,OAAO,KAAK,KAAK;AACvC,YAAM,IAAI,WAAW,8BAA8B,OAAO,KAAK,WAAW,OAAO,KAAK,KAAK;AAAA,IAC7F;AAAA,EACF;AAAA,EACA,cAAc,QAAQ;AACpB,QAAI,OAAO,WAAW,GAAG;AACvB,YAAM,IAAI,WAAW,oEAAoE,OAAO,kBAAkB;AAAA,IACpH;AACA,QAAI,KAAK,OAAO;AAChB,QAAI,KAAK,OAAO;AAChB,QAAI;AACJ,QAAI,CAAC,MAAM,QAAQ,KAAK,IAAI,GAAG;AAC7B,aAAO;AAAA,QACL,cAAc,KAAK,MAAM,GAAG,MAAM,MAAM;AAAA,QACxC,cAAc,KAAK,MAAM,GAAG,MAAM,MAAM;AAAA,MAC1C;AAAA,IACF,OAAO;AACL,aAAO,KAAK,KAAK,IAAI,CAAC,MAAM,OAAO,cAAc,MAAM,OAAO,IAAI,MAAM,MAAM,CAAC;AAAA,IACjF;AACA,QAAI,KAAK,WAAW;AAClB,WAAK,YAAY,IAAI,KAAK,EAAE;AAC5B,WAAK,YAAY,IAAI,KAAK,EAAE;AAAA,IAC9B;AACA,WAAO,SAAS,IAAI,IAAI,IAAI;AAAA,EAC9B;AAAA,EACA,cAAc,QAAQ,QAAQ;AAC5B,QAAI;AACJ,QAAI,CAAC,MAAM,QAAQ,KAAK,IAAI,GAAG;AAC7B,aAAO;AAAA,QACL,cAAc,KAAK,MAAM,OAAO,MAAM;AAAA,QACtC,cAAc,KAAK,MAAM,OAAO,MAAM;AAAA,MACxC;AAAA,IACF,OAAO;AACL,aAAO,KAAK;AAAA,IACd;AACA,WAAO;AAAA,EACT;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,OAAO,MAAM,QAAQ,UAAU,KAAK,WAAW,WAAW,KAAK,MAAM,QAAQ,WAAW,EAAE,KAAK,MAAM,QAAQ,WAAW,EAAE,GAAG,MAAM,+DAA+D;AAC/M,UAAM,SAAS,WAAW,GAAG,MAAM;AACnC,UAAM,SAAS,WAAW,GAAG,MAAM;AACnC,QAAI,OAAO,SAAS,KAAK,OAAO,SAAS,GAAG;AAC1C,YAAM,IAAI,oBAAoB,8DAA8D;AAAA,IAC9F;AACA,UAAM,OAAO,KAAK,cAAc,QAAQ,MAAM;AAC9C,WAAO,OAAO,KAAK,IAAI,CAAC;AACxB,WAAO,OAAO,KAAK,IAAI,CAAC;AACxB,WAAO,OAAO,GAAG,CAAC;AAClB,UAAM,cAAc,OAAO,OAAO,MAAM;AACxC,QAAI,YAAY,WAAW,GAAG;AAC5B,kBAAY,KAAK,CAAC;AAAA,IACpB;AACA,WAAO;AAAA,EACT;AAAA,EACA,YAAY,QAAQT,OAAM;AACxB,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMS,UAAS;AAAA,MACb,QAAQ,KAAK;AAAA,MACb,aAAa,KAAK;AAAA,IACpB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,IAAI,YAAY;AAChB,sBAAsB,cAAc,GAAG;AAGvC,IAAI,gBAAgB,cAAc,MAAM;AAAA,EACtC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,kBAAkB;AACvB,SAAK,SAAS,KAAK;AAAA,EACrB;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMA,UAAS,EAAE,QAAQ,KAAK,OAAO;AACrC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,YAAM,SAAS,oBAAoB,MAAM;AACzC,YAAM,SAAS,MAAM,KAAK,cAAc,OAAO,OAAO,GAAG,KAAK,MAAM,GAAG,MAAM;AAC7E,YAAM,SAAS,aAAa,QAAQ,MAAM,QAAQ,OAAO,eAAe,KAAK;AAC7E,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,cAAc,YAAY;AAC1B,sBAAsB,cAAc,aAAa;AACjD,IAAI,kBAAkB,cAAc,MAAM;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,kBAAkB;AACvB,SAAK,OAAO,KAAK;AAAA,EACnB;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMA,UAAS,EAAE,MAAM,KAAK,KAAK;AACjC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,YAAM,SAAS,oBAAoB,MAAM;AACzC,UAAI,KAAK,OAAO,KAAK,KAAK,OAAO,GAAG;AAClC,cAAM,SAAS,MAAM;AACnB,gBAAM,SAAS,KAAK,KAAK,KAAK,QAAQ,IAAI,KAAK,KAAK;AACpD,iBAAO,IAAI,QAAQ,cAAc,OAAO,OAAO,GAAG,MAAM,CAAC;AAAA,QAC3D;AACA,eAAO,aAAa,QAAQ,MAAM,QAAQ,OAAO,eAAe,KAAK;AAAA,MACvE;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,IAAI,eAAe,cAAc,MAAM;AAAA,EACrC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,kBAAkB;AACvB,SAAK,OAAO,KAAK;AACjB,SAAK,aAAa,KAAK;AAAA,EACzB;AAAA,EACA,eAAe,QAAQ;AACrB,WAAO,KAAK,cAAc,oBAAoB,MAAM,EAAE;AAAA,EACxD;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMA,UAAS,EAAE,MAAM,KAAK,KAAK;AACjC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,KAAK,OAAO,KAAK,KAAK,OAAO,GAAG;AAClC,cAAM,aAAa,KAAK,eAAe,MAAM;AAC7C,cAAM,gBAAgB,MAAM;AAC1B,gBAAM,SAAS,oBAAoB,MAAM;AACzC,gBAAMQ,SAAQ;AACd,gBAAMD,UAAS;AACf,gBAAM,SAAS,CAACC,SAAQD;AACxB,cAAI,UAAU,aAAa,cAAc,UAAU,GAAG,KAAK,IAAI;AAC/D,oBAAU,MAAM,SAAS,SAAS;AAClC,gBAAM,MAAM,IAAI,KAAK,SAAS,IAAI,KAAK,OAAO,UAAU,OAAO;AAC/D,gBAAM,IAAI,CAAC,IAAI,SAAS,KAAK;AAC7B,gBAAM,IAAI,KAAK,IAAI,QAAQ,OAAO,GAAG,IAAI,KAAK,SAAS,EAAE,GAAG,MAAM,CAAC;AACnE,iBAAO,KAAK,IAAI,GAAG,CAAC,GAAG,CAAC;AAAA,QAC1B;AACA,eAAO,aAAa,eAAe,MAAM,oBAAoB,MAAM,GAAG,OAAO,eAAe,KAAK;AAAA,MACnG;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAGhD,SAAS,mBAAmB,GAAG,OAAO,UAAU,MAAM,OAAO,WAAW,MAAM;AAC5E,MAAI;AACJ,MAAI,EAAE,SAAS,GAAG;AAChB,UAAM,YAAY,GAAG,OAAO,UAAU,MAAM,OAAO,QAAQ;AAAA,EAC7D,WAAW,EAAE,SAAS,GAAG;AACvB,UAAM,YAAY,GAAG,OAAO,UAAU,MAAM,OAAO,QAAQ;AAAA,EAC7D,WAAW,EAAE,SAAS,GAAG;AACvB,UAAM,YAAY,GAAG,OAAO,UAAU,MAAM,OAAO,QAAQ;AAAA,EAC7D,OAAO;AACL,UAAM,IAAI,oBAAoB,2DAA2D,EAAE,UAAU;AAAA,EACvG;AACA,SAAO;AACT;AACA,SAAS,gCAAgC,GAAG,OAAO,MAAM,eAAe,WAAW,MAAM;AACvF,SAAO,KAAK,MAAM;AAChB,UAAM,kBAAkB,QAAQ,GAAG,aAAa;AAChD,UAAM,QAAQ,gBAAgB;AAC9B,UAAM,WAAW,gBAAgB;AACjC,UAAM,SAAS,mBAAmB,GAAG,OAAO,UAAU,MAAM,OAAO,QAAQ;AAC3E,WAAO,CAAC,QAAQ,OAAO,QAAQ;AAAA,EACjC,CAAC;AACH;AACA,SAAS,kCAAkC,GAAG,OAAO,MAAM,eAAe,WAAW,MAAM;AACzF,SAAO,KAAK,MAAM;AAChB,UAAM,kBAAkB,QAAQ,GAAG,aAAa;AAChD,UAAM,QAAQ,gBAAgB;AAC9B,UAAM,WAAW,gBAAgB;AACjC,UAAM,cAAc,CAAC;AACrB,eAAW,QAAQ,OAAO,GAAG,EAAE,IAAI,GAAG;AACpC,UAAI,cAAc,QAAQ,IAAI,MAAM,IAAI;AACtC,oBAAY,KAAK,CAAC;AAAA,MACpB,OAAO;AACL,oBAAY,KAAK,EAAE,MAAM,KAAK;AAAA,MAChC;AAAA,IACF;AACA,UAAM,gBAAgB,QAAQ,OAAO,WAAW;AAChD,UAAM,oBAAoB,QAAQ,UAAU,WAAW;AACvD,UAAM,iBAAiB,SAAS,OAAO,OAAO,QAAQ,OAAO,WAAW;AACxE,UAAM,gBAAgB,QAAQ,OAAO,OAAO,QAAQ,MAAM,WAAW;AACrE,UAAM,SAAS,mBAAmB,GAAG,eAAe,mBAAmB,eAAe,gBAAgB,QAAQ;AAC9G,WAAO,CAAC,QAAQ,OAAO,QAAQ;AAAA,EACjC,CAAC;AACH;AACA,SAAS,yBAAyB,GAAG,OAAO,MAAM,eAAe,WAAW,MAAM;AAChF,MAAI,aAAa,YAAY,cAAc,MAAM,EAAE,KAAK,GAAG,OAAO,GAAG,EAAE,OAAO,CAAC,CAAC,GAAG;AACjF,WAAO,gCAAgC,GAAG,OAAO,MAAM,eAAe,QAAQ;AAAA,EAChF,OAAO;AACL,WAAO,kCAAkC,GAAG,OAAO,MAAM,eAAe,QAAQ;AAAA,EAClF;AACF;AACA,IAAI,qBAAqB,cAAc,MAAM;AAAA,EAC3C,YAAY,MAAM;AAChB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,UAAM,IAAI;AACV,SAAK,kBAAkB;AACvB,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,KAAK;AAC1C,SAAK,WAAW,KAAK,YAAY,OAAO,OAAO,KAAK;AACpD,SAAK,UAAU,KAAK,WAAW,OAAO,OAAO,KAAK;AAClD,SAAK,SAAS,KAAK,UAAU,OAAO,OAAO,KAAK;AAChD,SAAK,QAAQ,KAAK,SAAS,OAAO,OAAO,KAAK;AAC9C,SAAK,kBAAkB,eAAe,KAAK,mBAAmB,OAAO;AACrE,SAAK,mBAAmB,eAAe,KAAK,oBAAoB,MAAM;AACtE,SAAK,wBAAwB,eAAe,KAAK,yBAAyB,OAAO;AACjF,SAAK,4BAA4B,eAAe,KAAK,6BAA6B,MAAM;AACxF,SAAK,iBAAiB,cAAc,KAAK,cAAc;AACvD,SAAK,kBAAkB,cAAc,KAAK,eAAe;AACzD,SAAK,kBAAkB,eAAe,KAAK,eAAe;AAC1D,SAAK,mBAAmB,eAAe,KAAK,gBAAgB;AAAA,EAC9D;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,OAAO,KAAK,QAAQ,IAAI,KAAK,OAAO,KAAK,OAAO,WAAW;AACjE,UAAM,MAAM,WAAW;AACvB,QAAI,OAAO,MAAM;AACf,YAAM,IAAI,WAAW,QAAQ,mGAAmG,KAAK,UAAU,UAAU,IAAI;AAAA,IAC/J;AACA,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,WAAW,QAAQ,MAAM,EAAE,CAAC,OAAO,IAAI,EAAE,CAAC,CAAC;AACnF,UAAM,QAAQ,CAAC,GAAG;AAClB,QAAI,KAAK,OAAO;AACd,WAAK,QAAQ,KAAK,UAAU,SAAS,OAAO,MAAM,KAAK,kBAAkB,KAAK,kBAAkB,MAAM,KAAK,eAAe;AAAA,IAC5H;AACA,QAAI,KAAK,QAAQ;AACf,WAAK,OAAO,KAAK,UAAU,QAAQ,OAAO,MAAM,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IACvH;AACA,SAAK,aAAa,KAAK,UAAU,eAAe,OAAO,MAAM,KAAK,uBAAuB,MAAM,KAAK;AACpG,SAAK,iBAAiB,KAAK,UAAU,mBAAmB,OAAO,MAAM,KAAK,2BAA2B,MAAM,KAAK;AAChH,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAM,WAAW,OAAO,eAAe,OAAO,QAAQ,OAAO;AAC7D,YAAM,SAAS,oBAAoB,MAAM;AACzC,YAAM,aAAa,OAAO;AAC1B,YAAM,OAAO,WAAW;AACxB,YAAM,gBAAgB,OAAO,GAAG,IAAI;AACpC,YAAM,OAAO,KAAK,QAAQ,IAAI,KAAK,OAAO,KAAK,OAAO;AACtD,oBAAc,OAAO,MAAM,CAAC;AAC5B,YAAM,iBAAiB,aAAa,GAAG,IAAI;AAC3C,qBAAe,QAAQ,WAAW;AAClC,YAAM,sBAAsB,cAAc,MAAM;AAChD,0BAAoB,KAAK;AACzB,YAAM,oBAAoB,CAAC,aAAa,YAAY,qBAAqB,OAAO,GAAG,IAAI,EAAE,MAAM,GAAG,OAAO,CAAC,CAAC;AAC3G,YAAM,qBAAqB,MAAM;AAC/B,YAAI,mBAAmB;AACrB,gBAAM,sBAAsB,QAAQ,KAAK,WAAW,KAAK,GAAG,cAAc;AAC1E,gBAAM,0BAA0B,QAAQ,KAAK,eAAe,KAAK,GAAG,cAAc;AAClF,gBAAM,gBAAgB,KAAK,SAAS,QAAQ,KAAK,KAAK,KAAK,GAAG,cAAc,IAAI;AAChF,gBAAM,iBAAiB,KAAK,QAAQ,QAAQ,KAAK,MAAM,KAAK,GAAG,cAAc,IAAI;AACjF,iBAAO,mBAAmB,QAAQ,qBAAqB,yBAAyB,eAAe,gBAAgB,KAAK,OAAO;AAAA,QAC7H,OAAO;AACL,iBAAO,mBAAmB,QAAQ,KAAK,WAAW,KAAK,GAAG,KAAK,eAAe,KAAK,GAAG,KAAK,QAAQ,OAAO,OAAO,KAAK,KAAK,KAAK,GAAG,KAAK,SAAS,OAAO,OAAO,KAAK,MAAM,KAAK,GAAG,KAAK,OAAO;AAAA,QAChM;AAAA,MACF;AACA,UAAI,CAAC,UAAU;AACb,eAAO,mBAAmB;AAAA,MAC5B;AACA,YAAM,CAAC,gBAAgB,OAAO,QAAQ,IAAI,yBAAyB,QAAQ,KAAK,MAAM,KAAK,GAAG,KAAK,KAAK,KAAK,GAAG,eAAe,KAAK,OAAO;AAC3I,YAAM,kBAAkB,CAAC,WAAW,OAAO,aAAa;AACtD,aAAK,MAAM;AACT,gBAAM,QAAQ,IAAI;AAClB,gBAAM,YAAY,UAAU,KAAK;AACjC,gBAAM,cAAc,IAAI,IAAI,WAAW,KAAK,GAAG,KAAK;AACpD,oBAAU,MAAM,IAAI,WAAW,WAAW,CAAC;AAAA,QAC7C,CAAC;AAAA,MACH;AACA,YAAM,8BAA8B,MAAM;AACxC,wBAAgB,KAAK,YAAY,OAAO,KAAK,QAAQ;AACrD,wBAAgB,KAAK,gBAAgB,UAAU,KAAK,QAAQ;AAAA,MAC9D;AACA,kCAA4B;AAC5B,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMP,UAAS;AAAA,MACb,MAAM,KAAK;AAAA,MACX,UAAU,KAAK;AAAA,MACf,SAAS,KAAK;AAAA,MACd,QAAQ,KAAK;AAAA,MACb,OAAO,KAAK;AAAA,MACZ,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,kBAAkB,qBAAqB,KAAK,gBAAgB;AAAA,MAC5D,uBAAuB,qBAAqB,KAAK,qBAAqB;AAAA,MACtE,2BAA2B,qBAAqB,KAAK,yBAAyB;AAAA,MAC9E,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,kBAAkB,qBAAqB,KAAK,gBAAgB;AAAA,MAC5D,gBAAgB,oBAAoB,KAAK,cAAc;AAAA,MACvD,iBAAiB,oBAAoB,KAAK,eAAe;AAAA,IAC3D;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,mBAAmB,YAAY;AAC/B,sBAAsB,cAAc,kBAAkB;AACtD,IAAI,qBAAqB,cAAc,MAAM;AAAA,EAC3C,YAAY,MAAM;AAChB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,UAAM,IAAI;AACV,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,KAAK;AAC1C,QAAI,OAAO,KAAK,SAAS,UAAU;AACjC,UAAI,CAAC,OAAO,UAAU,KAAK,IAAI,GAAG;AAChC,cAAM,IAAI,MAAM,gDAAgD,KAAK,MAAM;AAAA,MAC7E;AAAA,IACF,WAAW,MAAM,QAAQ,KAAK,IAAI,GAAG;AACnC,iBAAW,QAAQ,KAAK,MAAM;AAC5B,YAAI,CAAC,OAAO,UAAU,IAAI,GAAG;AAC3B,gBAAM,IAAI,MAAM,0DAA0D,KAAK,UAAU,KAAK,IAAI,GAAG;AAAA,QACvG;AAAA,MACF;AAAA,IACF,OAAO;AACL,YAAM,IAAI,MAAM,wEAAwE,KAAK,UAAU,KAAK,IAAI,GAAG;AAAA,IACrH;AACA,SAAK,UAAU,KAAK,WAAW,OAAO,OAAO,KAAK;AAClD,SAAK,SAAS,KAAK,UAAU,OAAO,OAAO,KAAK;AAChD,SAAK,QAAQ,KAAK,SAAS,OAAO,OAAO,KAAK;AAC9C,SAAK,kBAAkB,eAAe,KAAK,mBAAmB,OAAO;AACrE,SAAK,mBAAmB,eAAe,KAAK,oBAAoB,MAAM;AACtE,SAAK,kBAAkB,eAAe,KAAK,eAAe;AAC1D,SAAK,mBAAmB,eAAe,KAAK,gBAAgB;AAC5D,SAAK,kBAAkB;AAAA,EACzB;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,QAAQ,WAAW;AACzB,QAAI,OAAO,KAAK,SAAS,UAAU;AACjC,WAAK,OAAO,CAAC,KAAK,IAAI;AAAA,IACxB;AACA,aAAS,KAAK,GAAG,KAAK,KAAK,KAAK,QAAQ,EAAE,IAAI;AAC5C,UAAI,KAAK,KAAK,MAAM,GAAG;AACrB,aAAK,KAAK,OAAO;AAAA,MACnB;AAAA,IACF;AACA,eAAW,QAAQ,KAAK,MAAM;AAC5B,UAAI,OAAO,KAAK,QAAQ,OAAO;AAC7B,cAAM,IAAI,MAAM,iBAAiB,MAAM;AAAA,MACzC;AAAA,IACF;AACA,QAAI,KAAK,KAAK,WAAW,QAAQ,KAAK,IAAI,EAAE,QAAQ;AAClD,YAAM,IAAI,MAAM,4BAA4B,KAAK,MAAM;AAAA,IACzD;AACA,UAAM,aAAa,KAAK,KAAK,IAAI,CAAC,SAAS,WAAW,KAAK;AAC3D,UAAM,YAAY;AAClB,QAAI,KAAK,OAAO;AACd,WAAK,QAAQ,KAAK,UAAU,SAAS,YAAY,WAAW,KAAK,kBAAkB,KAAK,kBAAkB,SAAS;AAAA,IACrH,OAAO;AACL,WAAK,QAAQ;AAAA,IACf;AACA,QAAI,KAAK,QAAQ;AACf,WAAK,OAAO,KAAK,UAAU,QAAQ,YAAY,WAAW,KAAK,iBAAiB,KAAK,iBAAiB,SAAS;AAAA,IACjH,OAAO;AACL,WAAK,OAAO;AAAA,IACd;AACA,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,UAAM,SAAS,oBAAoB,MAAM;AACzC,UAAM,aAAa,OAAO;AAC1B,UAAM,QAAQ,WAAW;AACzB,WAAO,KAAK,MAAM;AAChB,YAAM,WAAW;AACjB,UAAI,EAAE,MAAM,OAAO,SAAS,IAAI,QAAQ,QAAQ,KAAK,MAAM,QAAQ;AACnE,YAAM,iBAAiB,aAAa,GAAG,KAAK;AAC5C,iBAAW,OAAO,KAAK,MAAM;AAC3B,uBAAe,OAAO,WAAW;AAAA,MACnC;AACA,YAAM,YAAY,CAAC,MAAM;AACvB,YAAI,KAAK,QAAQ,EAAE,MAAM,WAAW,OAAO;AACzC,iBAAO,QAAQ,GAAG,cAAc;AAAA,QAClC,OAAO;AACL,iBAAO;AAAA,QACT;AAAA,MACF;AACA,UAAIO,UAAS,KAAK,QAAQ,UAAU,KAAK,MAAM,KAAK,CAAC,IAAI;AACzD,UAAI,SAAS,KAAK,SAAS,UAAU,KAAK,KAAK,KAAK,CAAC,IAAI;AACzD,YAAM,gBAAgB,CAAC;AACvB,YAAM,oBAAoB,CAAC;AAC3B,eAAS,KAAK,GAAG,KAAK,OAAO,EAAE,IAAI;AACjC,YAAI,KAAK,KAAK,QAAQ,EAAE,MAAM,IAAI;AAChC,wBAAc,KAAK,WAAW,GAAG;AACjC,4BAAkB,KAAK,CAAC;AAAA,QAC1B,OAAO;AACL,wBAAc,KAAK,CAAC;AACpB,4BAAkB,KAAK,WAAW,GAAG;AAAA,QACvC;AAAA,MACF;AACA,cAAQ,KAAK,OAAO,aAAa;AACjC,iBAAW,KAAK,UAAU,aAAa;AACvC,UAAIA,WAAU,MAAM;AAClB,QAAAA,UAAS,KAAKA,SAAQ,iBAAiB;AAAA,MACzC;AACA,UAAI,UAAU,MAAM;AAClB,iBAAS,KAAK,QAAQ,iBAAiB;AAAA,MACzC;AACA,aAAO,mBAAmB,QAAQ,OAAO,UAAU,QAAQA,SAAQ,KAAK,OAAO;AAAA,IACjF,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMP,UAAS;AAAA,MACb,MAAM,KAAK;AAAA,MACX,SAAS,KAAK;AAAA,MACd,QAAQ,KAAK;AAAA,MACb,OAAO,KAAK;AAAA,MACZ,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,kBAAkB,qBAAqB,KAAK,gBAAgB;AAAA,MAC5D,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,kBAAkB,qBAAqB,KAAK,gBAAgB;AAAA,IAC9D;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,mBAAmB,YAAY;AAC/B,sBAAsB,cAAc,kBAAkB;AAGtD,SAAS,iBAAiB,GAAGa,UAAS,YAAY;AAChD,SAAO,KAAK,MAAM;AAChB,QAAI,EAAE,SAAS,GAAG;AAChB,YAAM,IAAI,WAAW,kEAAkE,EAAE,gBAAgB;AAAA,IAC3G;AACA,QAAIA,YAAW,MAAM;AACnB,MAAAA,WAAU,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAAA,IAC3B;AACA,QAAIA,SAAQ,WAAW,KAAKA,SAAQ,GAAG,WAAW,KAAKA,SAAQ,GAAG,WAAW,GAAG;AAC9E,YAAM,IAAI,WAAW,6GAA6G;AAAA,IACpI;AACA,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,QAAI,eAAe,kBAAkB,eAAe,iBAAiB;AACnE,YAAM,IAAI,WAAW,wBAAwB,2EAA2E;AAAA,IAC1H;AACA,QAAI;AACJ,QAAI,eAAe,iBAAiB;AAClC,gBAAU,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAGA,SAAQ,IAAIA,SAAQ,EAAE;AAAA,IACnD,OAAO;AACL,gBAAU,CAAC,CAAC,GAAG,CAAC,GAAGA,SAAQ,IAAIA,SAAQ,IAAI,CAAC,GAAG,CAAC,CAAC;AAAA,IACnD;AACA,WAAO,IAAI,GAAG,OAAO;AAAA,EACvB,CAAC;AACH;AACA,IAAI,gBAAgB,cAAc,MAAM;AAAA,EACtC,YAAY,MAAM;AAChB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,UAAM,IAAI;AACV,SAAK,aAAa,KAAK,cAAc,OAAO,gBAAgB,IAAI,KAAK;AACrE,QAAI,KAAK,WAAW,MAAM;AACxB,WAAK,UAAU,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAAA,IAChC,WAAW,OAAO,KAAK,YAAY,UAAU;AAC3C,WAAK,UAAU,CAAC,CAAC,KAAK,SAAS,KAAK,OAAO,GAAG,CAAC,KAAK,SAAS,KAAK,OAAO,CAAC;AAAA,IAC5E,OAAO;AACL,WAAK,UAAU,KAAK;AACpB,UAAI,KAAK,QAAQ,WAAW,GAAG;AAC7B,cAAM,IAAI,WAAW,+EAA+E,KAAK,QAAQ,eAAe;AAAA,MAClI;AACA,UAAI;AACJ,UAAI;AACJ,UAAI,OAAO,KAAK,QAAQ,OAAO,UAAU;AACvC,wBAAgB,CAAC,KAAK,QAAQ,IAAI,KAAK,QAAQ,EAAE;AACjD,uBAAe,CAAC,KAAK,QAAQ,IAAI,KAAK,QAAQ,EAAE;AAAA,MAClD,OAAO;AACL,aAAK,UAAU,KAAK;AACpB,YAAI,KAAK,QAAQ,GAAG,WAAW,GAAG;AAChC,gBAAM,IAAI,WAAW,sFAAsF,KAAK,QAAQ,GAAG,eAAe;AAAA,QAC5I;AACA,wBAAgB,KAAK,QAAQ;AAC7B,YAAI,KAAK,QAAQ,GAAG,WAAW,GAAG;AAChC,gBAAM,IAAI,WAAW,qFAAqF,KAAK,QAAQ,GAAG,eAAe;AAAA,QAC3I;AACA,uBAAe,KAAK,QAAQ;AAAA,MAC9B;AACA,WAAK,UAAU,CAAC,eAAe,YAAY;AAAA,IAC7C;AACA,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,EAC9C;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,QAAI;AACJ,QAAI;AACJ,QAAI,KAAK,eAAe,iBAAiB;AACvC,UAAI,WAAW,MAAM,QAAQ,WAAW,MAAM,GAAG;AAC/C,eAAO,WAAW,KAAK,KAAK,QAAQ,GAAG,KAAK,KAAK,QAAQ,GAAG;AAAA,MAC9D,OAAO;AACL,eAAO;AAAA,MACT;AACA,UAAI,WAAW,MAAM,QAAQ,WAAW,MAAM,GAAG;AAC/C,eAAO,WAAW,KAAK,KAAK,QAAQ,GAAG,KAAK,KAAK,QAAQ,GAAG;AAAA,MAC9D,OAAO;AACL,eAAO;AAAA,MACT;AACA,aAAO,CAAC,WAAW,IAAI,WAAW,IAAI,MAAM,IAAI;AAAA,IAClD,OAAO;AACL,UAAI,WAAW,MAAM,QAAQ,WAAW,MAAM,GAAG;AAC/C,eAAO,WAAW,KAAK,KAAK,QAAQ,GAAG,KAAK,KAAK,QAAQ,GAAG;AAAA,MAC9D,OAAO;AACL,eAAO;AAAA,MACT;AACA,UAAI,WAAW,MAAM,QAAQ,WAAW,MAAM,GAAG;AAC/C,eAAO,WAAW,KAAK,KAAK,QAAQ,GAAG,KAAK,KAAK,QAAQ,GAAG;AAAA,MAC9D,OAAO;AACL,eAAO;AAAA,MACT;AACA,aAAO,CAAC,WAAW,IAAI,MAAM,MAAM,WAAW,EAAE;AAAA,IAClD;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM,iBAAiB,oBAAoB,MAAM,GAAG,KAAK,SAAS,KAAK,UAAU,CAAC;AAAA,EAChG;AAAA,EACA,YAAY;AACV,UAAMb,UAAS;AAAA,MACb,SAAS,KAAK;AAAA,MACd,YAAY,KAAK;AAAA,IACnB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,cAAc,YAAY;AAC1B,sBAAsB,cAAc,aAAa;AAGjD,SAAS,OAAO,GAAG,UAAUF,UAASe,UAAS,YAAY,UAAU;AACnE,SAAO,KAAK,MAAM;AAChB,oBAAgB,UAAU;AAC1B,kBAAc,QAAQ;AACtB,qBAAiBA,QAAO;AACxB,QAAIf,YAAW,MAAM;AACnB,MAAAA,WAAU,CAAC,GAAG,CAAC;AAAA,IACjB;AACA,QAAIe,YAAW,MAAM;AACnB,MAAAA,WAAU;AAAA,IACZ;AACA,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,QAAI,YAAY,MAAM;AACpB,iBAAW;AAAA,IACb;AACA,QAAI,sBAAsB,GAAG,UAAU;AACvC,QAAI;AACJ,UAAM,gBAAgBA,aAAY,SAAS,SAAS;AACpD,QAAI,aAAa,OAAO;AACtB,UAAI,QAAQ,GAAG,UAAUf,UAAS,aAAa;AAAA,IACjD,OAAO;AACL,UAAI;AAAA,QACF;AAAA,QACA;AAAA,QACAA;AAAA,QACA;AAAA,MACF;AAAA,IACF;AACA,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,GAAG,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,IAC/B;AACA,WAAO;AAAA,EACT,CAAC;AACH;AACA,SAAS,OAAO,GAAG,UAAUA,UAASe,UAAS,YAAY,UAAU;AACnE,SAAO,KAAK,MAAM;AAChB,oBAAgB,UAAU;AAC1B,kBAAc,QAAQ;AACtB,qBAAiBA,QAAO;AACxB,QAAIf,YAAW,MAAM;AACnB,MAAAA,WAAU,CAAC,GAAG,GAAG,CAAC;AAAA,IACpB;AACA,QAAIe,YAAW,MAAM;AACnB,MAAAA,WAAU;AAAA,IACZ;AACA,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,QAAI,YAAY,MAAM;AACpB,iBAAW;AAAA,IACb;AACA,QAAI,sBAAsB,GAAG,UAAU;AACvC,QAAI;AACJ,UAAM,gBAAgBA,aAAY,SAAS,SAAS;AACpD,QAAI,aAAa,OAAO;AACtB,UAAI,UAAU,GAAG,UAAUf,UAAS,aAAa;AAAA,IACnD,OAAO;AACL,UAAI,UAAU,GAAG,UAAUA,UAAS,aAAa;AAAA,IACnD;AACA,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,GAAG,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,IAClC;AACA,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,YAAY,cAAc,MAAM;AAAA,EAClC,YAAY,MAAM;AAChB,QAAI,KAAK,YAAY,MAAM;AACzB,WAAK,WAAW;AAAA,IAClB;AACA,UAAM,IAAI;AACV,QAAI,OAAO,KAAK,aAAa,UAAU;AACrC,WAAK,WAAW,CAAC,KAAK,QAAQ;AAAA,IAChC,WAAW,MAAM,QAAQ,KAAK,QAAQ,KAAK,KAAK,SAAS,WAAW,KAAK,OAAO,KAAK,SAAS,OAAO,UAAU;AAC7G,WAAK,WAAW,KAAK;AAAA,IACvB,OAAO;AACL,YAAM,IAAI,WAAW,qGAAqG,KAAK,UAAU,KAAK,QAAQ,GAAG;AAAA,IAC3J;AACA,0BAAsB,KAAK,UAAU,UAAU;AAC/C,QAAI,KAAK,WAAW,MAAM;AACxB,WAAK,UAAU,KAAK;AAAA,IACtB,OAAO;AACL,UAAI,OAAO,KAAK,YAAY,UAAU;AACpC,aAAK,UAAU,CAAC,KAAK,OAAO;AAAA,MAC9B,WAAW,MAAM,QAAQ,KAAK,OAAO,KAAK,KAAK,QAAQ,WAAW,KAAK,OAAO,KAAK,QAAQ,OAAO,UAAU;AAC1G,aAAK,UAAU,KAAK;AAAA,MACtB,OAAO;AACL,cAAM,IAAI,WAAW,oGAAoG,KAAK,UAAU,KAAK,OAAO,GAAG;AAAA,MACzJ;AAAA,IACF;AACA,0BAAsB,KAAK,SAAS,SAAS;AAC7C,SAAK,UAAU,KAAK,WAAW,OAAO,UAAU,KAAK;AACrD,qBAAiB,KAAK,OAAO;AAC7B,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,EAC9C;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,SAAS,iBAAiB,WAAW,IAAI,KAAK,SAAS,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AAC9F,WAAO,CAAC,WAAW,IAAI,QAAQ,WAAW,EAAE;AAAA,EAC9C;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,eAAS,YAAY,oBAAoB,MAAM,GAAG,CAAC;AACnD,YAAM,SAAS,KAAK,gBAAgB,oBAAoB,MAAM,GAAG,CAAC,KAAK,SAAS,IAAI,CAAC,GAAG,CAAC,KAAK,QAAQ,IAAI,CAAC,GAAG,KAAK,SAAS,cAAc;AAC1I,aAAO,QAAQ,QAAQ,CAAC,CAAC,CAAC;AAAA,IAC5B,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAME,UAAS;AAAA,MACb,UAAU,KAAK;AAAA,MACf,SAAS,KAAK;AAAA,MACd,SAAS,KAAK;AAAA,IAChB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,IAAI,eAAe,cAAc,UAAU;AAAA,EACzC,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,gBAAgB,QAAQ,UAAUF,UAASe,UAAS,YAAY;AAC9D,oBAAgB,UAAU;AAC1B,qBAAiBA,QAAO;AACxB,WAAO,OAAO,QAAQ,UAAUf,UAASe,UAAS,YAAY,KAAK;AAAA,EACrE;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAChD,IAAI,mBAAmB,cAAc,UAAU;AAAA,EAC7C,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,gBAAgB,QAAQ,UAAUf,UAASe,UAAS,YAAY;AAC9D,oBAAgB,UAAU;AAC1B,qBAAiBA,QAAO;AACxB,WAAO,OAAO,QAAQ,UAAUf,UAASe,UAAS,YAAY,KAAK;AAAA,EACrE;AACF;AACA,iBAAiB,YAAY;AAC7B,sBAAsB,cAAc,gBAAgB;AACpD,IAAI,YAAY,cAAc,MAAM;AAAA,EAClC,YAAY,MAAM;AAChB,QAAI,KAAK,YAAY,MAAM;AACzB,WAAK,WAAW,CAAC,GAAG,CAAC;AAAA,IACvB;AACA,UAAM,IAAI;AACV,SAAK,WAAW,MAAM,QAAQ,KAAK,QAAQ,IAAI,KAAK,WAAW,CAAC,KAAK,UAAU,KAAK,QAAQ;AAC5F,QAAI,KAAK,WAAW,MAAM;AACxB,WAAK,UAAU,KAAK;AAAA,IACtB,WAAW,MAAM,QAAQ,KAAK,OAAO,GAAG;AACtC,UAAI,KAAK,QAAQ,WAAW,GAAG;AAC7B,cAAM,IAAI,WAAW,wHAAwH,KAAK,QAAQ,SAAS;AAAA,MACrK;AACA,WAAK,UAAU,KAAK;AAAA,IACtB,OAAO;AACL,WAAK,UAAU,CAAC,KAAK,SAAS,KAAK,OAAO;AAAA,IAC5C;AACA,0BAAsB,KAAK,UAAU,UAAU;AAC/C,0BAAsB,KAAK,SAAS,SAAS;AAC7C,SAAK,UAAU,KAAK,WAAW,OAAO,UAAU,KAAK;AACrD,SAAK,aAAa,KAAK,cAAc,OAAO,iBAAiB,KAAK;AAClE,oBAAgB,KAAK,UAAU;AAC/B,qBAAiB,KAAK,OAAO;AAC7B,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,EAC9C;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,OAAO,KAAK,eAAe,kBAAkB,WAAW,KAAK,WAAW;AAC5E,QAAI,OAAO,KAAK,eAAe,kBAAkB,WAAW,KAAK,WAAW;AAC5E,WAAO,iBAAiB,MAAM,KAAK,SAAS,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AAC7E,WAAO,iBAAiB,MAAM,KAAK,SAAS,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AAC7E,QAAI,KAAK,eAAe,iBAAiB;AACvC,aAAO,CAAC,WAAW,IAAI,WAAW,IAAI,MAAM,IAAI;AAAA,IAClD,OAAO;AACL,aAAO,CAAC,WAAW,IAAI,MAAM,MAAM,WAAW,EAAE;AAAA,IAClD;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,aAAO,KAAK,gBAAgB,oBAAoB,MAAM,GAAG,KAAK,UAAU,KAAK,SAAS,KAAK,SAAS,KAAK,UAAU;AAAA,IACrH,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMb,UAAS;AAAA,MACb,UAAU,KAAK;AAAA,MACf,SAAS,KAAK;AAAA,MACd,SAAS,KAAK;AAAA,MACd,YAAY,KAAK;AAAA,IACnB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,IAAI,eAAe,cAAc,UAAU;AAAA,EACzC,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,gBAAgB,QAAQ,UAAUF,UAASe,UAAS,YAAY;AAC9D,oBAAgB,UAAU;AAC1B,qBAAiBA,QAAO;AACxB,WAAO,OAAO,QAAQ,UAAUf,UAASe,UAAS,YAAY,KAAK;AAAA,EACrE;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAChD,IAAI,mBAAmB,cAAc,UAAU;AAAA,EAC7C,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,gBAAgB,QAAQ,UAAUf,UAASe,UAAS,YAAY;AAC9D,oBAAgB,UAAU;AAC1B,qBAAiBA,QAAO;AACxB,WAAO,OAAO,QAAQ,UAAUf,UAASe,UAAS,YAAY,KAAK;AAAA,EACrE;AACF;AACA,iBAAiB,YAAY;AAC7B,sBAAsB,cAAc,gBAAgB;AACpD,IAAI,YAAY,cAAc,MAAM;AAAA,EAClC,YAAY,MAAM;AAChB,QAAI,KAAK,YAAY,MAAM;AACzB,WAAK,WAAW,CAAC,GAAG,GAAG,CAAC;AAAA,IAC1B;AACA,UAAM,IAAI;AACV,SAAK,WAAW,MAAM,QAAQ,KAAK,QAAQ,IAAI,KAAK,WAAW,CAAC,KAAK,UAAU,KAAK,UAAU,KAAK,QAAQ;AAC3G,QAAI,KAAK,WAAW,MAAM;AACxB,WAAK,UAAU,KAAK;AAAA,IACtB,WAAW,MAAM,QAAQ,KAAK,OAAO,GAAG;AACtC,UAAI,KAAK,QAAQ,WAAW,GAAG;AAC7B,cAAM,IAAI,WAAW,wHAAwH,KAAK,QAAQ,SAAS;AAAA,MACrK;AACA,WAAK,UAAU,KAAK;AAAA,IACtB,OAAO;AACL,WAAK,UAAU,CAAC,KAAK,SAAS,KAAK,SAAS,KAAK,OAAO;AAAA,IAC1D;AACA,0BAAsB,KAAK,UAAU,UAAU;AAC/C,0BAAsB,KAAK,SAAS,SAAS;AAC7C,SAAK,UAAU,KAAK,WAAW,OAAO,UAAU,KAAK;AACrD,SAAK,aAAa,KAAK,cAAc,OAAO,iBAAiB,KAAK;AAClE,oBAAgB,KAAK,UAAU;AAC/B,qBAAiB,KAAK,OAAO;AAC7B,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,EAC9C;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,SAAS,KAAK,eAAe,kBAAkB,WAAW,KAAK,WAAW;AAC9E,QAAI,OAAO,KAAK,eAAe,kBAAkB,WAAW,KAAK,WAAW;AAC5E,QAAI,OAAO,KAAK,eAAe,kBAAkB,WAAW,KAAK,WAAW;AAC5E,aAAS,iBAAiB,QAAQ,KAAK,SAAS,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AACjF,WAAO,iBAAiB,MAAM,KAAK,SAAS,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AAC7E,WAAO,iBAAiB,MAAM,KAAK,SAAS,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AAC7E,QAAI,KAAK,eAAe,iBAAiB;AACvC,aAAO,CAAC,WAAW,IAAI,WAAW,IAAI,QAAQ,MAAM,IAAI;AAAA,IAC1D,OAAO;AACL,aAAO,CAAC,WAAW,IAAI,QAAQ,MAAM,MAAM,WAAW,EAAE;AAAA,IAC1D;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,aAAO,KAAK,gBAAgB,oBAAoB,MAAM,GAAG,KAAK,UAAU,KAAK,SAAS,KAAK,SAAS,KAAK,UAAU;AAAA,IACrH,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMb,UAAS;AAAA,MACb,UAAU,KAAK;AAAA,MACf,SAAS,KAAK;AAAA,MACd,SAAS,KAAK;AAAA,MACd,YAAY,KAAK;AAAA,IACnB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,IAAI,eAAe,cAAc,UAAU;AAAA,EACzC,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,gBAAgB,QAAQ,UAAUF,UAASe,UAAS,YAAY;AAC9D,oBAAgB,UAAU;AAC1B,qBAAiBA,QAAO;AACxB,WAAO,OAAO,QAAQ,UAAUf,UAASe,UAAS,YAAY,KAAK;AAAA,EACrE;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAChD,IAAI,mBAAmB,cAAc,UAAU;AAAA,EAC7C,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,gBAAgB,QAAQ,UAAUf,UAASe,UAAS,YAAY;AAC9D,oBAAgB,UAAU;AAC1B,qBAAiBA,QAAO;AACxB,WAAO,OAAO,QAAQ,UAAUf,UAASe,UAAS,YAAY,KAAK;AAAA,EACrE;AACF;AACA,iBAAiB,YAAY;AAC7B,sBAAsB,cAAc,gBAAgB;AACpD,IAAI,kBAAkB,cAAc,MAAM;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,EAC9C;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO,CAAC,WAAW,IAAI,WAAW,EAAE;AAAA,EACtC;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,UAAM,IAAI,oBAAoB;AAAA,EAChC;AACF;AACA,IAAI,yBAAyB,cAAc,gBAAgB;AAAA,EACzD,YAAY,MAAM;AAChB,UAAM,QAAQ,CAAC,CAAC;AAAA,EAClB;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAM,SAAS,oBAAoB,MAAM;AACzC,aAAO,KAAK,QAAQ,CAAC;AAAA,IACvB,CAAC;AAAA,EACH;AACF;AACA,uBAAuB,YAAY;AACnC,sBAAsB,cAAc,sBAAsB;AAC1D,IAAI,qBAAqB,cAAc,gBAAgB;AAAA,EACrD,YAAY,MAAM;AAChB,UAAM,QAAQ,CAAC,CAAC;AAAA,EAClB;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAM,SAAS,oBAAoB,MAAM;AACzC,aAAO,IAAI,QAAQ,CAAC;AAAA,IACtB,CAAC;AAAA,EACH;AACF;AACA,mBAAmB,YAAY;AAC/B,sBAAsB,cAAc,kBAAkB;AACtD,IAAI,kBAAkB,cAAc,MAAM;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,aAAa,KAAK,cAAc,OAAO,iBAAiB,KAAK;AAClE,oBAAgB,KAAK,UAAU;AAC/B,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,EAC9C;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa;AACb,QAAI,KAAK,eAAe,gBAAgB;AACtC,aAAO,CAAC,WAAW,IAAI,WAAW,EAAE;AAAA,IACtC,OAAO;AACL,aAAO,CAAC,WAAW,IAAI,WAAW,EAAE;AAAA,IACtC;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,UAAM,IAAI,oBAAoB;AAAA,EAChC;AAAA,EACA,YAAY;AACV,UAAMb,UAAS,EAAE,YAAY,KAAK,WAAW;AAC7C,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,IAAI,yBAAyB,cAAc,gBAAgB;AAAA,EACzD,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAM,SAAS,oBAAoB,MAAM;AACzC,UAAI,KAAK,eAAe,gBAAgB;AACtC,eAAO,KAAK,QAAQ,CAAC,GAAG,CAAC,CAAC;AAAA,MAC5B,OAAO;AACL,eAAO,KAAK,QAAQ,CAAC,GAAG,CAAC,CAAC;AAAA,MAC5B;AAAA,IACF,CAAC;AAAA,EACH;AACF;AACA,uBAAuB,YAAY;AACnC,sBAAsB,cAAc,sBAAsB;AAC1D,IAAI,qBAAqB,cAAc,gBAAgB;AAAA,EACrD,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAM,SAAS,oBAAoB,MAAM;AACzC,UAAI,KAAK,eAAe,gBAAgB;AACtC,eAAO,IAAI,QAAQ,CAAC,GAAG,CAAC,CAAC;AAAA,MAC3B,OAAO;AACL,eAAO,IAAI,QAAQ,CAAC,GAAG,CAAC,CAAC;AAAA,MAC3B;AAAA,IACF,CAAC;AAAA,EACH;AACF;AACA,mBAAmB,YAAY;AAC/B,sBAAsB,cAAc,kBAAkB;AAGtD,IAAI,UAAU,cAAc,MAAM;AAAA,EAChC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,QAAQ,KAAK;AAAA,EACpB;AAAA,EACA,MAAM,YAAY;AAChB,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,IAAI,YAAY;AACd,QAAI,KAAK,SAAS,MAAM;AACtB,aAAO,KAAK,MAAM;AAAA,IACpB,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,IAAI,UAAU,OAAO;AACnB,QAAI,KAAK,SAAS,MAAM;AACtB,WAAK,MAAM,YAAY;AAAA,IACzB;AAAA,EACF;AAAA,EACA,IAAI,mBAAmB;AACrB,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,IAAI,sBAAsB;AACxB,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,IAAI,UAAU;AACZ,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,IAAI,SAAS;AACX,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,aAAa;AACX,WAAO,KAAK,MAAM,WAAW;AAAA,EAC/B;AAAA,EACA,WAAW,SAAS;AAClB,SAAK,MAAM,WAAW,OAAO;AAAA,EAC/B;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,SAAS;AAAA,QACP,aAAa,KAAK,MAAM,aAAa;AAAA,QACrC,UAAU,KAAK,MAAM,UAAU;AAAA,MACjC;AAAA,IACF;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,6BAA6B,OAAO;AAClC,UAAM,6BAA6B,KAAK;AACxC,QAAI,KAAK,SAAS,MAAM;AACtB,WAAK,MAAM,6BAA6B,KAAK;AAAA,IAC/C;AAAA,EACF;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ,gBAAgB,CAAC,GAAG;AACjD,UAAM,cAAcA,QAAO;AAC3B,UAAM,QAAQ,YAAY,aAAa,aAAa;AACpD,WAAOA,QAAO;AACd,UAAM,YAAY,EAAE,MAAM;AAC1B,WAAO,OAAO,WAAWA,OAAM;AAC/B,WAAO,IAAI,IAAI,SAAS;AAAA,EAC1B;AACF;AACA,IAAI,kBAAkB,cAAc,QAAQ;AAAA,EAC1C,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,kBAAkB;AAAA,EACzB;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,WAAW,SAAS,GAAG;AACzB,YAAM,IAAI,WAAW,gFAAgF,KAAK,UAAU,UAAU,GAAG;AAAA,IACnI;AACA,SAAK,YAAY,CAAC,EAAE,OAAO,WAAW,CAAC;AACvC,UAAM,kBAAkB,CAAC,WAAW,EAAE,EAAE,OAAO,WAAW,MAAM,CAAC,CAAC;AAClE,QAAI,CAAC,KAAK,MAAM,OAAO;AACrB,WAAK,MAAM,MAAM,eAAe;AAChC,WAAK,MAAM,QAAQ;AAAA,IACrB;AACA,UAAM,MAAM,UAAU;AAAA,EACxB;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,kBAAkB,CAAC,WAAW,EAAE,EAAE,OAAO,WAAW,MAAM,CAAC,CAAC;AAClE,UAAM,mBAAmB,KAAK,MAAM,mBAAmB,eAAe;AACtE,UAAM,YAAY,WAAW;AAC7B,WAAO,CAAC,iBAAiB,IAAI,SAAS,EAAE,OAAO,iBAAiB,MAAM,CAAC,CAAC;AAAA,EAC1E;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS,oBAAoB,MAAM;AACnC,YAAM,QAAQ,CAAC,SAAS,WAAW;AACjC,cAAM,SAAS,oBAAoB,KAAK,MAAM,KAAK,SAAS,MAAM,CAAC;AACnE,eAAO,CAAC,QAAQ,CAAC,CAAC;AAAA,MACpB;AACA,YAAM,aAAa,IAAI,OAAO,QAAQ,CAAC,GAAG,OAAO,MAAM,MAAM,OAAO,IAAI;AACxE,YAAM,IAAI,WAAW;AACrB,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,SAAS,4BAA4B,OAAO;AAC1C,4BAA0B,iCAAiC,0BAA0B,KAAK;AAC5F;AACA,IAAI,mCAAmC;AACvC,IAAI,gBAAgB,cAAc,QAAQ;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,UAAM,cAAc,KAAK,MAAM,UAAU;AACzC,UAAM,WAAW,CAAC;AAClB,aAAS,eAAe,KAAK,MAAM,aAAa;AAChD,aAAS,YAAY;AACrB,SAAK,eAAe,YAAY,QAAQ;AACxC,gBAAY,iBAAiB,YAAY,mBAAmB,OAAO,QAAQ;AAC3E,UAAM,WAAW,CAAC;AAClB,aAAS,eAAe,KAAK,MAAM,aAAa;AAChD,aAAS,YAAY;AACrB,SAAK,gBAAgB,YAAY,QAAQ;AACzC,SAAK,aAAa,OAAO,aAAa,KAAK,aAAa;AACxD,SAAK,cAAc,OAAO,cAAc,KAAK,cAAc;AAC3D,SAAK,YAAY,KAAK,cAAc,SAAS,mCAAmC,KAAK;AACrF,gCAA4B,KAAK,SAAS;AAC1C,QAAI,KAAK,SAAS;AAChB,YAAM,IAAI,oBAAoB,iEAAiE;AAAA,IACjG;AACA,SAAK,YAAY,KAAK,MAAM;AAC5B,SAAK,kBAAkB,KAAK,MAAM;AAClC,SAAK,cAAc,KAAK,MAAM;AAC9B,SAAK,kBAAkB;AACvB,SAAK,aAAa;AAClB,SAAK,YAAY,KAAK,MAAM;AAC5B,SAAK,eAAe;AAAA,EACtB;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,UAAU,OAAO;AACnB,SAAK,aAAa;AAClB,QAAI,KAAK,gBAAgB,MAAM;AAC7B,WAAK,aAAa,YAAY;AAAA,IAChC;AACA,QAAI,KAAK,iBAAiB,MAAM;AAC9B,WAAK,cAAc,YAAY;AAAA,IACjC;AAAA,EACF;AAAA,EACA,aAAa;AACX,WAAO,KAAK,aAAa,WAAW,EAAE,OAAO,KAAK,cAAc,WAAW,CAAC;AAAA,EAC9E;AAAA,EACA,WAAW,SAAS;AAClB,UAAM,aAAa,QAAQ;AAC3B,UAAM,iBAAiB,KAAK,MAAM,aAAa,CAAC;AAChD,SAAK,aAAa,WAAW,QAAQ,MAAM,GAAG,cAAc,CAAC;AAC7D,SAAK,cAAc,WAAW,QAAQ,MAAM,cAAc,CAAC;AAAA,EAC7D;AAAA,EACA,mBAAmB,YAAY;AAC7B,QAAI,cAAc,KAAK,aAAa,mBAAmB,UAAU;AACjE,QAAI,EAAE,MAAM,QAAQ,WAAW,KAAK,MAAM,QAAQ,YAAY,EAAE,IAAI;AAClE,oBAAc,CAAC,WAAW;AAAA,IAC5B;AACA,kBAAc;AACd,QAAI;AACJ,QAAI;AACJ,QAAI;AACJ,QAAI,KAAK,aAAa;AACpB,mBAAa,YAAY,MAAM,CAAC;AAChC,oBAAc,YAAY;AAAA,IAC5B,OAAO;AACL,oBAAc,YAAY;AAAA,IAC5B;AACA,kBAAc;AACd,QAAI,KAAK,cAAc,UAAU;AAC/B,kBAAY,YAAY,SAAS,MAAM;AACvC,qBAAe,CAAC,WAAW;AAAA,IAC7B,WAAW,KAAK,aAAa,MAAM;AACjC,qBAAe,CAAC,aAAa,YAAY,MAAM,CAAC;AAAA,IAClD,OAAO;AACL,qBAAe,CAAC,WAAW;AAAA,IAC7B;AACA,QAAI,KAAK,aAAa;AACpB,UAAI,KAAK,aAAa,MAAM;AAC1B,eAAO,aAAa,OAAO,UAAU,EAAE,OAAO,WAAW,MAAM,CAAC;AAAA,MAClE;AACA,aAAO,CAAC,WAAW,EAAE,OAAO,UAAU,EAAE,OAAO,WAAW,MAAM,CAAC;AAAA,IACnE;AACA,WAAO,iBAAiB,YAAY;AAAA,EACtC;AAAA,EACA,MAAM,QAAQ,QAAQ;AACpB,QAAI,eAAe,UAAU,OAAO,OAAO,OAAO;AAClD,QAAIgB,aAAY,UAAU,OAAO,OAAO,OAAO;AAC/C,QAAI,UAAU,MAAM;AAClB,eAAS,CAAC;AAAA,IACZ;AACA,UAAM,eAAe,gBAAgB,QAAQ,cAAcA,YAAW,KAAK,YAAY;AACvF,aAAS,aAAa;AACtB,mBAAe,aAAa;AAC5B,IAAAA,aAAY,aAAa;AACzB,QAAI,MAAM,QAAQ,MAAM,GAAG;AACzB,qBAAe,OAAO,MAAM,CAAC;AAC7B,eAAS,OAAO;AAAA,IAClB;AACA,SAAK,gBAAgB,QAAQ,aAAa,WAAW,MAAMA,cAAa,MAAM;AAC5E,aAAO,MAAM,MAAM,QAAQ,MAAM;AAAA,IACnC;AACA,UAAM,mBAAmB,CAAC;AAC1B,UAAM,kBAAkB,CAAC;AACzB,QAAI,gBAAgB,MAAM;AACxB,YAAM,YAAY,aAAa;AAC/B,UAAI,YAAY,IAAI,GAAG;AACrB,cAAM,IAAI,WAAW,+HAA+H;AAAA,MACtJ;AACA,aAAO,kBAAkB;AACzB,uBAAiB,KAAK,GAAG,YAAY;AACrC,YAAM,aAAa,aAAa,IAAI,CAAC,UAAU,IAAI,UAAU,EAAE,OAAO,MAAM,MAAM,CAAC,CAAC;AACpF,WAAK,aAAa,YAAY,WAAW,MAAM,GAAG,YAAY,CAAC;AAC/D,WAAK,cAAc,YAAY,WAAW,MAAM,YAAY,CAAC;AAC7D,sBAAgB,KAAK,GAAG,UAAU;AAAA,IACpC;AACA,QAAIA,cAAa,MAAM;AACrB,YAAM,IAAI,oBAAoB,uEAAuE;AAAA,IACvG;AACA,UAAM,mBAAmB,iBAAiB,cAAc;AACxD,eAAW,WAAW,kBAAkB;AACtC,UAAI,mBAAmB,mBAAmB,kBAAkB;AAC1D,cAAM,IAAI,WAAW,8GAA8G;AAAA,MACrI;AAAA,IACF;AACA,QAAI,kBAAkB;AACpB,YAAM,YAAY,CAAC,MAAM,EAAE,OAAO,gBAAgB;AAClD,YAAM,gBAAgB,KAAK,UAAU,OAAO,eAAe;AAC3D,YAAM,oBAAoB,KAAK;AAC/B,WAAK,YAAY;AACjB,YAAM,SAAS,MAAM,MAAM,WAAW,MAAM;AAC5C,WAAK,YAAY;AACjB,aAAO;AAAA,IACT,OAAO;AACL,aAAO,MAAM,MAAM,QAAQ,MAAM;AAAA,IACnC;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAM,eAAe,OAAO;AAC5B,UAAI;AACJ,UAAI;AACJ,UAAI,gBAAgB,MAAM;AACxB,YAAI,KAAK,aAAa,KAAK,QAAQ,MAAM;AACzC,eAAO,KAAK,cAAc,KAAK,QAAQ,MAAM;AAAA,MAC/C,OAAO;AACL,cAAM,eAAe,aAAa,MAAM,GAAG,aAAa,SAAS,CAAC;AAClE,cAAM,gBAAgB,aAAa,MAAM,aAAa,SAAS,CAAC;AAChE,YAAI,KAAK,aAAa,KAAK,QAAQ,OAAO,OAAO,QAAQ,EAAE,cAAc,aAAa,CAAC,CAAC;AACxF,eAAO,KAAK,cAAc,KAAK,QAAQ,OAAO,OAAO,QAAQ,EAAE,cAAc,cAAc,CAAC,CAAC;AAAA,MAC/F;AACA,UAAI;AACJ,UAAI,KAAK,aAAa;AACpB,YAAI,MAAM,QAAQ,CAAC,GAAG;AACpB,mBAAS,EAAE,MAAM,CAAC,EAAE,OAAO,KAAK,MAAM,CAAC,CAAC;AAAA,QAC1C,OAAO;AAAA,QACP;AACA,YAAI,EAAE;AACN,eAAO,KAAK;AAAA,MACd;AACA,UAAI,KAAK,iBAAiB;AACxB,eAAO,QAAQ,MAAM,CAAC;AAAA,MACxB;AACA,UAAI;AACJ,UAAI,KAAK,cAAc,UAAU;AAC/B,iBAAS,YAAY,CAAC,GAAG,IAAI,CAAC;AAAA,MAChC,WAAW,KAAK,cAAc,OAAO;AACnC,iBAAS,KAAK,GAAG,IAAI;AAAA,MACvB,WAAW,KAAK,cAAc,OAAO;AACnC,iBAAS,IAAI,KAAK,KAAK,GAAG,IAAI,CAAC;AAAA,MACjC,WAAW,KAAK,cAAc,OAAO;AACnC,iBAAS,IAAI,GAAG,IAAI;AAAA,MACtB,WAAW,KAAK,aAAa,MAAM;AACjC,iBAAS,CAAC,GAAG,IAAI;AAAA,MACnB;AACA,UAAI,KAAK,aAAa;AACpB,YAAI,KAAK,aAAa,MAAM;AAC1B,iBAAO,OAAO,OAAO,MAAM;AAAA,QAC7B;AACA,eAAO,CAAC,MAAM,EAAE,OAAO,MAAM;AAAA,MAC/B;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,YAAY,QAAQ;AAClB,SAAK,aAAa,YAAY;AAC9B,SAAK,cAAc,YAAY;AAAA,EACjC;AAAA,EACA,MAAM,YAAY;AAChB,cAAU,KAAK,aAAa,MAAM,MAAM;AACtC,WAAK,aAAa,MAAM,UAAU;AAAA,IACpC,CAAC;AACD,cAAU,KAAK,cAAc,MAAM,MAAM;AACvC,WAAK,cAAc,MAAM,UAAU;AAAA,IACrC,CAAC;AACD,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,YAAY,QAAQzB,OAAM;AACxB,QAAI,MAAM,QAAQA,KAAI,GAAG;AACvB,MAAAA,QAAOA,MAAK;AAAA,IACd;AACA,QAAI;AACJ,QAAI,KAAK,iBAAiB;AACxB,UAAI,KAAK,aAAa,MAAM;AAC1B,qBAAa,CAACA,OAAMA,KAAI;AAAA,MAC1B,OAAO;AACL,qBAAaA;AAAA,MACf;AAAA,IACF,OAAO;AACL,UAAI,KAAK,aAAa,MAAM;AAC1B,qBAAa,CAAC,MAAM,IAAI;AAAA,MAC1B,OAAO;AACL,qBAAa;AAAA,MACf;AAAA,IACF;AACA,QAAI,KAAK,aAAa;AACpB,YAAM,SAAS,KAAK,aAAa;AACjC,YAAM,YAAY,OAAO,IAAI,CAAC,UAAU,IAAI;AAC5C,UAAI,MAAM,QAAQ,UAAU,GAAG;AAC7B,eAAO,WAAW,OAAO,SAAS,EAAE,OAAO,SAAS;AAAA,MACtD,OAAO;AACL,eAAO,CAAC,UAAU,EAAE,OAAO,SAAS,EAAE,OAAO,SAAS;AAAA,MACxD;AAAA,IACF,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,IAAI,mBAAmB;AACrB,WAAO,KAAK,aAAa,iBAAiB,OAAO,KAAK,cAAc,gBAAgB;AAAA,EACtF;AAAA,EACA,IAAI,sBAAsB;AACxB,WAAO,KAAK,aAAa,oBAAoB,OAAO,KAAK,cAAc,mBAAmB;AAAA,EAC5F;AAAA,EACA,6BAA6B,OAAO;AAClC,UAAM,6BAA6B,KAAK;AACxC,QAAI,KAAK,gBAAgB,MAAM;AAC7B,WAAK,aAAa,6BAA6B,KAAK;AAAA,IACtD;AACA,QAAI,KAAK,iBAAiB,MAAM;AAC9B,WAAK,cAAc,6BAA6B,KAAK;AAAA,IACvD;AAAA,EACF;AAAA,EACA,YAAY;AACV,UAAMS,UAAS;AAAA,MACb,aAAa,KAAK;AAAA,IACpB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,UAAM,WAAW,YAAYA,QAAO,QAAQ;AAC5C,WAAOA,QAAO;AACd,QAAIA,QAAO,mBAAmB,MAAM;AAClC,YAAM,IAAI,oBAAoB,0FAA0F;AAAA,IAC1H;AACA,UAAM,YAAYA;AAClB,cAAU,WAAW;AACrB,WAAO,IAAI,IAAI,SAAS;AAAA,EAC1B;AACF;AACA,cAAc,YAAY;AAC1B,sBAAsB,cAAc,aAAa;AAGjD,SAAS,WAAW,MAAM;AACxB,SAAO,IAAI,WAAW,IAAI;AAC5B;AACA,SAAS,KAAK,MAAM;AAClB,SAAO,IAAI,IAAI,IAAI;AACrB;AACA,SAAS,KAAK,MAAM;AAClB,SAAO,IAAI,KAAK,IAAI;AACtB;AACA,SAAS,UAAU,MAAM;AACvB,SAAO,IAAI,UAAU,IAAI;AAC3B;AACA,SAAS,OAAO,MAAM;AACpB,SAAO,IAAI,MAAM,IAAI;AACvB;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,gBAAgB,MAAM;AAC7B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,OAAO,IAAI;AACxB;AACA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,WAAW,MAAM;AACxB,SAAO,IAAI,WAAW,IAAI;AAC5B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,WAAW,MAAM;AACxB,SAAO,IAAI,YAAY,IAAI;AAC7B;AACA,SAAS,MAAM,MAAM;AACnB,SAAO,IAAI,MAAM,IAAI;AACvB;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,iBAAiB,IAAI;AAClC;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,UAAU,MAAM;AACvB,SAAO,IAAI,UAAU,IAAI;AAC3B;AACA,SAAS,KAAK,MAAM;AAClB,SAAO,IAAI,KAAK,IAAI;AACtB;AACA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,YAAY,IAAI;AAC7B;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,UAAU,IAAI;AAC3B;AACA,SAAS,KAAK,MAAM;AAClB,SAAO,IAAI,IAAI,IAAI;AACrB;AACA,SAAS,oBAAoB,MAAM;AACjC,SAAO,IAAI,mBAAmB,IAAI;AACpC;AACA,SAAS,mBAAmB,MAAM;AAChC,SAAO,IAAI,mBAAmB,IAAI;AACpC;AACA,SAAS,cAAc,MAAM;AAC3B,SAAO,IAAI,cAAc,IAAI;AAC/B;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,iBAAiB,IAAI;AAClC;AACA,SAAS,UAAU,MAAM;AACvB,SAAO,iBAAiB,IAAI;AAC9B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,iBAAiB,IAAI;AAC9B;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,iBAAiB,IAAI;AAClC;AACA,SAAS,UAAU,MAAM;AACvB,SAAO,iBAAiB,IAAI;AAC9B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,iBAAiB,IAAI;AAC9B;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,iBAAiB,IAAI;AAClC;AACA,SAAS,WAAW,MAAM;AACxB,SAAO,iBAAiB,IAAI;AAC9B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,iBAAiB,IAAI;AAC9B;AACA,SAAS,uBAAuB,MAAM;AACpC,SAAO,IAAI,uBAAuB,IAAI;AACxC;AACA,SAAS,uBAAuB,MAAM;AACpC,SAAO,IAAI,uBAAuB,IAAI;AACxC;AACA,SAAS,mBAAmB,MAAM;AAChC,SAAO,IAAI,mBAAmB,IAAI;AACpC;AACA,SAAS,mBAAmB,MAAM;AAChC,SAAO,IAAI,mBAAmB,IAAI;AACpC;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,IAAI,MAAM;AACjB,SAAO,IAAI,IAAI,IAAI;AACrB;AACA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,KAAK,MAAM;AAClB,SAAO,IAAI,KAAK,IAAI;AACtB;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,UAAU,MAAM;AACvB,SAAO,IAAI,UAAU,IAAI;AAC3B;AACA,SAAS,cAAc,MAAM;AAC3B,SAAO,IAAI,cAAc,IAAI;AAC/B;AACA,SAAS,WAAW,MAAM;AACxB,SAAO,IAAI,WAAW,IAAI;AAC5B;AACA,SAAS,eAAe,MAAM;AAC5B,SAAO,IAAI,eAAe,IAAI;AAChC;AACA,SAAS,KAAK,MAAM;AAClB,SAAO,IAAI,IAAI,IAAI;AACrB;AACA,SAAS,gBAAgB,MAAM;AAC7B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,cAAc,MAAM;AAC3B,SAAO,IAAI,cAAc,IAAI;AAC/B;AACA,SAAS,gBAAgB,MAAM;AAC7B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,IAAI,kBAAkB;AACtB,IAAI,kBAAkB;AACtB,IAAI,YAAY;AAChB,IAAI,YAAY;AAChB,SAAS,cAAc,MAAM;AAC3B,SAAO,IAAI,cAAc,IAAI;AAC/B;AACA,SAAS,gBAAgB,MAAM;AAC7B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,QAAQ,IAAI;AACzB;AAGA,IAAI,0BAA0B,CAAC;AAC/BjB,UAAS,yBAAyB;AAAA,EAChC,MAAM,MAAM;AAAA,EACZ,KAAK,MAAM;AAAA,EACX,gBAAgB,MAAM;AAAA,EACtB,oBAAoB,MAAM;AAAA,EAC1B,qBAAqB,MAAM;AAAA,EAC3B,yBAAyB,MAAM;AAAA,EAC/B,iBAAiB,MAAM;AAAA,EACvB,MAAM,MAAM;AAAA,EACZ,mBAAmB,MAAM;AAAA,EACzB,6BAA6B,MAAM;AAAA,EACnC,kBAAkB,MAAM;AAAA,EACxB,KAAK,MAAM;AAAA,EACX,WAAW,MAAM;AAAA,EACjB,QAAQ,MAAM;AAAA,EACd,2BAA2B,MAAM;AACnC,CAAC;AACD,SAAS,gBAAgB,OAAO,OAAO;AACrC,SAAO,eAAe,OAAO,KAAK;AACpC;AACA,SAAS,oBAAoB,OAAO,OAAO;AACzC,SAAO,oBAAoB,OAAO,KAAK;AACzC;AACA,SAAS,2BAA2B,OAAO,OAAO;AAChD,SAAO,0BAA0B,OAAO,KAAK;AAC/C;AACA,SAAS,qBAAqB,OAAO,OAAO;AAC1C,SAAO,oBAAoB,OAAO,KAAK;AACzC;AACA,SAAS,yBAAyB,OAAO,OAAO;AAC9C,SAAO,yBAAyB,OAAO,KAAK;AAC9C;AACA,SAAS,WAAW,OAAO,OAAO;AAChC,SAAO,UAAU,OAAO,KAAK;AAC/B;AACA,SAAS,QAAQ,OAAO,OAAO;AAC7B,SAAO,OAAO,OAAO,KAAK;AAC5B;AACA,SAAS,iBAAiB,OAAO,OAAO;AACtC,SAAO,gBAAgB,OAAO,KAAK;AACrC;AACA,SAAS,mBAAmB,OAAO,OAAO;AACxC,SAAO,kBAAkB,OAAO,KAAK;AACvC;AACA,SAAS,6BAA6B,OAAO,OAAO;AAClD,SAAO,4BAA4B,OAAO,KAAK;AACjD;AACA,SAAS,MAAM,OAAO,OAAO;AAC3B,SAAO,4BAA4B,OAAO,KAAK;AACjD;AACA,SAAS,MAAM,OAAO,OAAO;AAC3B,SAAO,4BAA4B,OAAO,KAAK;AACjD;AACA,SAAS,kBAAkB,OAAO,OAAO;AACvC,SAAO,kBAAkB,OAAO,KAAK;AACvC;AACA,SAAS,KAAK,OAAO,OAAO;AAC1B,SAAO,kBAAkB,OAAO,KAAK;AACvC;AACA,SAAS,KAAK,OAAO,OAAO;AAC1B,SAAO,kBAAkB,OAAO,KAAK;AACvC;AAGA,IAAI,yBAAyB,CAAC;AAC9BA,UAAS,wBAAwB;AAAA,EAC/B,eAAe,MAAM;AACvB,CAAC;AAGD,IAAI,+BAA+B,CAAC;AACpCA,UAAS,8BAA8B;AAAA,EACrC,IAAI,MAAM;AAAA,EACV,MAAM,MAAM;AAAA,EACZ,IAAI,MAAM;AACZ,CAAC;AACD,SAAS,KAAKiB,SAAQ;AACpB,SAAO,IAAI,KAAKA,OAAM;AACxB;AACA,SAAS,IAAIA,SAAQ;AACnB,SAAO,GAAGA,OAAM;AAClB;AACA,SAAS,IAAIA,SAAQ;AACnB,SAAO,GAAGA,OAAM;AAClB;AAGA,IAAI,WAAW,cAAc,aAAa;AAAA,EACxC,cAAc;AACZ,UAAM,GAAG,SAAS;AAClB,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,SAASe,SAAQ;AACf,QAAI,EAAEA,mBAAkB,cAAc;AACpC,YAAM,IAAI,MAAM,uDAAuD;AAAA,IACzE;AACA,SAAK,QAAQA;AAAA,EACf;AACF;AACA,SAAS,MAAM,SAAS,SAAS;AAC/B,SAAO,UAAU;AACnB;AACA,SAAS,SAAS,SAAS,SAAS;AAClC,SAAO,UAAU;AACnB;AACA,IAAI,gBAAgB,cAAc,SAAS;AAAA,EACzC,YAAY,MAAM;AAChB,UAAM;AACN,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,QAAI,KAAK,oBAAoB;AAC3B,YAAM,IAAI,oBAAoB,oEAAoE;AAAA,IACpG;AACA,SAAK,UAAU,KAAK,WAAW;AAC/B,SAAK,WAAW,KAAK,IAAI,KAAK,YAAY,CAAC;AAC3C,SAAK,WAAW,KAAK,YAAY;AACjC,SAAK,UAAU,KAAK,WAAW;AAC/B,SAAK,OAAO,KAAK,QAAQ;AACzB,SAAK,WAAW,KAAK;AACrB,QAAI,CAAC,QAAQ,OAAO,KAAK,EAAE,QAAQ,KAAK,IAAI,MAAM,IAAI;AACpD,cAAQ,KAAK,uBAAuB,KAAK,gDAAgD;AACzF,WAAK,OAAO;AAAA,IACd;AACA,QAAI,KAAK,SAAS,OAAO;AACvB,WAAK,cAAc;AAAA,IACrB,WAAW,KAAK,SAAS,OAAO;AAC9B,WAAK,cAAc;AAAA,IACrB,OAAO;AACL,UAAI,KAAK,QAAQ,QAAQ,KAAK,MAAM,IAAI;AACtC,aAAK,cAAc;AAAA,MACrB,OAAO;AACL,aAAK,cAAc;AAAA,MACrB;AAAA,IACF;AACA,QAAI,KAAK,gBAAgB,OAAO;AAC9B,WAAK,YAAY;AAAA,IACnB;AAAA,EACF;AAAA,EACA,MAAM,aAAa,MAAM;AACvB,SAAK,OAAO;AACZ,SAAK,eAAe;AACpB,QAAI,KAAK,YAAY,MAAM;AACzB,WAAK,OAAO,KAAK;AAAA,IACnB,OAAO;AACL,WAAK,OAAO,KAAK,gBAAgB,QAAQ,WAAW;AAAA,IACtD;AAAA,EACF;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,UAAM,qBAAqB,IAAI;AAC/B,UAAM,UAAU,KAAK,gBAAgB,IAAI;AACzC,QAAI,WAAW,MAAM;AACnB;AAAA,IACF;AACA,QAAI,KAAK,YAAY,UAAU,KAAK,UAAU,KAAK,IAAI,GAAG;AACxD,WAAK,OAAO;AACZ,WAAK,OAAO;AAAA,IACd,OAAO;AACL,WAAK;AACL,UAAI,KAAK,QAAQ,KAAK,UAAU;AAC9B,aAAK,eAAe;AACpB,aAAK,MAAM,eAAe;AAAA,MAC5B;AAAA,IACF;AAAA,EACF;AAAA,EACA,MAAM,WAAW,MAAM;AACrB,QAAI,KAAK,eAAe,KAAK,KAAK,SAAS;AACzC,cAAQ,IAAI,SAAS,KAAK,+BAA+B;AAAA,IAC3D;AAAA,EACF;AAAA,EACA,gBAAgB,MAAM;AACpB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,UAAM,eAAe,KAAK,KAAK;AAC/B,QAAI,gBAAgB,MAAM;AACxB,cAAQ,KAAK,4BAA4B,KAAK,oDAAoD,OAAO,KAAK,IAAI,GAAG;AAAA,IACvH;AACA,WAAO;AAAA,EACT;AACF;AACA,SAAS,cAAc,MAAM;AAC3B,SAAO,IAAI,cAAc,IAAI;AAC/B;AACA,IAAI,YAAY,EAAE,cAAc;AAGhC,IAAI,OAAO,IAAI;AACf,KAAK,aAAa,6BAA6B,MAAM,OAAO,CAAC,eAAe;AAC1E,MAAI,YAAY;AACd,YAAQ,KAAK,+OAA+O;AAAA,EAC9P;AACF,CAAC;AAGD,IAAI;AAAA,CACH,SAAS,WAAW;AACnB,YAAU,UAAU,gBAAgB,KAAK;AACzC,YAAU,UAAU,cAAc,KAAK;AACvC,YAAU,UAAU,eAAe,KAAK;AACxC,YAAU,UAAU,cAAc,KAAK;AACvC,YAAU,UAAU,cAAc,KAAK;AACvC,YAAU,UAAU,cAAc,KAAK;AACvC,YAAU,UAAU,aAAa,KAAK;AACtC,YAAU,UAAU,eAAe,KAAK;AACxC,YAAU,UAAU,kBAAkB,KAAK;AAC3C,YAAU,UAAU,cAAc,KAAK;AACvC,YAAU,UAAU,aAAa,MAAM;AACvC,YAAU,UAAU,cAAc,MAAM;AACxC,YAAU,UAAU,eAAe,MAAM;AACzC,YAAU,UAAU,eAAe,MAAM;AACzC,YAAU,UAAU,iBAAiB,MAAM;AAC3C,YAAU,UAAU,eAAe,MAAM;AACzC,YAAU,UAAU,gBAAgB,MAAM;AAC1C,YAAU,UAAU,eAAe,MAAM;AACzC,YAAU,UAAU,mBAAmB,MAAM;AAC7C,YAAU,UAAU,aAAa,MAAM;AACvC,YAAU,UAAU,iBAAiB,MAAM;AAC3C,YAAU,UAAU,gBAAgB,MAAM;AAC1C,YAAU,UAAU,eAAe,MAAM;AACzC,YAAU,UAAU,eAAe,MAAM;AACzC,YAAU,UAAU,kBAAkB,OAAO;AAC7C,YAAU,UAAU,mBAAmB,OAAO;AAC9C,YAAU,UAAU,kBAAkB,OAAO;AAC7C,YAAU,UAAU,kBAAkB,OAAO;AAC7C,YAAU,UAAU,kBAAkB,OAAO;AAC7C,YAAU,UAAU,iBAAiB,OAAO;AAC5C,YAAU,UAAU,mBAAmB,OAAO;AAC9C,YAAU,UAAU,sBAAsB,OAAO;AACjD,YAAU,UAAU,kBAAkB,OAAO;AAC7C,YAAU,UAAU,iBAAiB,OAAO;AAC5C,YAAU,UAAU,kBAAkB,OAAO;AAC7C,YAAU,UAAU,mBAAmB,OAAO;AAC9C,YAAU,UAAU,mBAAmB,OAAO;AAC9C,YAAU,UAAU,qBAAqB,OAAO;AAChD,YAAU,UAAU,mBAAmB,OAAO;AAC9C,YAAU,UAAU,oBAAoB,OAAO;AAC/C,YAAU,UAAU,mBAAmB,OAAO;AAC9C,YAAU,UAAU,uBAAuB,OAAO;AAClD,YAAU,UAAU,iBAAiB,OAAO;AAC5C,YAAU,UAAU,qBAAqB,OAAO;AAChD,YAAU,UAAU,oBAAoB,OAAO;AAC/C,YAAU,UAAU,mBAAmB,OAAO;AAC9C,YAAU,UAAU,mBAAmB,OAAO;AAChD,GAAG,aAAa,WAAW,CAAC,EAAE;AAC9B,IAAI;AAAA,CACH,SAAS,WAAW;AACnB,MAAI;AACJ,GAAC,SAAS,0BAA0B;AAClC,6BAAyB,yBAAyB,YAAY,KAAK;AACnE,6BAAyB,yBAAyB,QAAQ,KAAK;AAC/D,6BAAyB,yBAAyB,QAAQ,KAAK;AAAA,EACjE,GAAG,0BAA0B,UAAU,4BAA4B,UAAU,0BAA0B,CAAC,EAAE;AAC5G,GAAG,aAAa,WAAW,CAAC,EAAE;AAG9B,IAAI,aAAa,CAAC;AAClB,SAAS,WAAW,MAAM,QAAQ;AAChC,QAAM,WAAW;AAAA,IACf,UAAU;AAAA,IACV,UAAU;AAAA,IACV,QAAQ,CAAC;AAAA,IACT,OAAO,CAAC;AAAA,IACR,gBAAgB;AAAA,EAClB;AACA,aAAW,QAAQ;AACrB;AACA,SAAS,gBAAgB,MAAM;AAC7B,SAAO,WAAW;AACpB;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,WAAW;AACpB;AAGA,SAAS,cAAc,WAAWb,OAAM,WAAW,SAAS,iBAAiB;AAC3E,QAAM,aAAaA,MAAK,YAAY;AACpC,MAAI,cAAc,WAAW,oBAAoB,QAAQ;AACvD,UAAM,QAAQ,WAAW;AACzB,UAAM,MAAM,WAAW,kBAAkB,IAAI,SAAS,WAAW,kBAAkB,SAAS,QAAQ,IAAI,WAAW;AACnH,QAAI,WAAW,SAAS,UAAU;AAChC,aAAO,UAAUA,MAAK,WAAW,WAAW,kBAAkB,WAAW,SAAS,eAAe;AAAA,IACnG;AACA,QAAI,WAAW,SAAS,WAAW;AACjC,YAAM,SAASA,MAAK,WAAW,MAAM,OAAO,GAAG;AAC/C,aAAO,OAAO,IAAI,CAAC,SAAS,UAAU,MAAM,WAAW,SAAS,eAAe,CAAC;AAAA,IAClF;AACA,UAAM,UAAU,UAAUA,MAAK,WAAW,MAAM,KAAK,EAAE,IAAI,WAAW,SAAS,eAAe;AAC9F,UAAM,OAAO,QAAQ,SAAS;AAC9B,WAAO,WAAW,SAAS,WAAW,KAAK,KAAK,aAAa,cAAc,QAAQ,OAAO,IAAI;AAAA,EAChG;AACA,QAAM,YAAYA,MAAK,WAAW;AAClC,SAAO,aAAa,UAAU;AAChC;AACA,SAAS,UAAU,MAAM,YAAY,SAAS,iBAAiB;AAC7D,QAAM,CAAC,UAAUP,MAAK,IAAI,cAAc,IAAI;AAC5C,MAAI,mBAAmB,MAAM;AAC3B,UAAM,UAAU,gBAAgB,yBAAyB,QAAQ;AACjE,QAAI,WAAW,MAAM;AACnB,aAAO;AAAA,IACT;AAAA,EACF;AACA,QAAM,YAAY,QAAQ,kBAAkB,KAAK,CAAC,eAAe;AAC/D,WAAO,CAAC,CAAC,WAAW,yBAAyB,UAAU,UAAU;AAAA,EACnE,CAAC;AACD,SAAO,cAAc,SAAS,WAAW,yBAAyB,UAAU,SAAS,GAAGA,UAAS;AACnG;AACA,SAAS,6BAA6B,MAAM,YAAY,SAAS;AAC/D,SAAO,WAAW,yBAAyB,MAAM,QAAQ,gBAAgB;AAC3E;AACA,SAAS,oBAAoB,WAAW,SAAS;AAC/C,QAAM,CAAC,UAAUA,QAAO,UAAU,IAAI,cAAc,SAAS;AAC7D,SAAO;AAAA,IACL,yBAAyB,UAAU,WAAW,QAAQ,gBAAgB;AAAA,IACtEA;AAAA,IACA;AAAA,EACF;AACF;AACA,SAAS,yBAAyB,MAAM,WAAW;AACjD,SAAO,CAAC,CAAC,YAAY,GAAG,QAAQ,cAAc;AAChD;AACA,SAAS,cAAc,MAAM;AAC3B,QAAM,QAAQ,KAAK,MAAM,GAAG;AAC5B,MAAI,MAAM,WAAW,GAAG;AACtB,WAAO,CAAC,MAAM,GAAG,MAAM;AAAA,EACzB;AACA,QAAM,WAAW,MAAM;AACvB,QAAM,aAAa,MAAM,WAAW,IAAI,MAAM,KAAK;AACnD,QAAMA,SAAQ,OAAO,MAAM,MAAM,SAAS,EAAE;AAC5C,SAAO,CAAC,UAAUA,QAAO,UAAU;AACrC;AACA,SAAS,WAAWO,OAAM,WAAW,SAAS;AAC5C,MAAI,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AACxD,MAAI,SAAS,YAAY;AACvB,WAAO,cAAc,oBAAoBA,OAAM,WAAW,OAAO;AACjE,UAAM,kBAAkB,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AACvD,aAAS,KAAK,GAAG,KAAK,GAAG,MAAM;AAC7B,sBAAgB,IAAI,KAAK,KAAK,KAAK;AACnC,sBAAgB,IAAI,KAAK,KAAK,KAAK,IAAI;AAAA,IACzC;AACA,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,YAAY,SAAS;AAC5B,SAAO,QAAQ,OAAO,UAAU,MAAM,OAAO;AAC/C;AAGA,IAAI,qBAAqB,CAAC;AAC1BnB,UAAS,oBAAoB;AAAA,EAC3B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,OAAO;AAAA,EACT;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,qBAAqB,CAAC;AAC1BA,UAAS,oBAAoB;AAAA,EAC3B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,kBAAkB,CAAC;AACvBA,UAAS,iBAAiB;AAAA,EACxB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,sBAAsB,CAAC;AAC3BA,UAAS,qBAAqB;AAAA,EAC5B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,QACjB,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,UACd;AAAA,UACA;AAAA,UACA;AAAA,UACA;AAAA,QACF;AAAA,MACF;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,UACd;AAAA,UACA;AAAA,UACA;AAAA,UACA;AAAA,QACF;AAAA,MACF;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,mBAAmB,CAAC;AACxBA,UAAS,kBAAkB;AAAA,EACzB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,QAChB,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,QAChB,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,QAChB,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,kBAAkB,CAAC;AACvBA,UAAS,iBAAiB;AAAA,EACxB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,qBAAqB,CAAC;AAC1BA,UAAS,oBAAoB;AAAA,EAC3B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,gBAAgB,CAAC;AACrBA,UAAS,eAAe;AAAA,EACtB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,EACd;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU,CAAC;AAAA,EACb;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,qBAAqB,CAAC;AAC1BA,UAAS,oBAAoB;AAAA,EAC3B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU,CAAC;AAAA,IACX,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU,CAAC;AAAA,IACX,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,gBAAgB,CAAC;AACrBA,UAAS,eAAe;AAAA,EACtB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,kBAAkB,CAAC;AACvBA,UAAS,iBAAiB;AAAA,EACxB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,mBAAmB,CAAC;AACxBA,UAAS,kBAAkB;AAAA,EACzB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,wBAAwB,CAAC;AAC7BA,UAAS,uBAAuB;AAAA,EAC9B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,QAChB,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,oBAAoB,CAAC;AACzBA,UAAS,mBAAmB;AAAA,EAC1B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,qBAAqB,CAAC;AAC1BA,UAAS,oBAAoB;AAAA,EAC3B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,QAChB,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,QAChB,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,iBAAiB,CAAC;AACtBA,UAAS,gBAAgB;AAAA,EACvB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,mBAAmB,CAAC;AACxBA,UAAS,kBAAkB;AAAA,EACzB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,iBAAiB,CAAC;AACtBA,UAAS,gBAAgB;AAAA,EACvB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,WAAW;AAAA,MACT;AAAA,MACA;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,WAAW;AAAA,MACT;AAAA,MACA;AAAA,MACA;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,yBAAyB,CAAC;AAC9BA,UAAS,wBAAwB;AAAA,EAC/B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,oBAAoB;AAAA,QACpB,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS,CAAC;AAAA,EACZ;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS,CAAC;AAAA,EACZ;AACF;AAGA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,WAAW,WAAW;AACpB,WAAO,KAAK,cAAc,KAAK,YAAY,IAAI,KAAK;AAAA,EACtD;AAAA,EACA,cAAc;AACZ,UAAM,MAAM;AAAA,MACV;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF;AACA,UAAM,cAAc,CAAC,EAAE,OAAO,GAAG,IAAI,IAAI,CAAC,QAAQ,IAAI,IAAI,CAAC;AAC3D,SAAK,YAAY,YAAY,OAAO,CAAC,KAAK,WAAW;AACnD,UAAI,OAAO,YAAY;AACvB,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AAAA,EACP;AAAA,EACA,eAAe,OAAO,YAAY,CAAC,GAAG;AACpC,UAAM,UAAU,MAAM;AACtB,UAAM,eAAe,CAAC;AACtB,UAAM,UAAU,CAAC;AACjB,UAAM,YAAY,CAAC;AACnB,UAAM,QAAQ,QAAQ,OAAO,CAAC,KAAKmB,UAAS;AAC1C,UAAIA,MAAK,QAAQ,KAAK,QAAQA,KAAI;AAClC,UAAIA,MAAK,GAAG,WAAW,aAAa,GAAG;AACrC,qBAAa,KAAK,IAAIA,MAAK,KAAK;AAAA,MAClC,WAAWA,MAAK,OAAO,SAAS;AAC9B,gBAAQ,KAAK,IAAIA,MAAK,KAAK;AAAA,MAC7B,WAAWA,MAAK,SAAS,QAAQA,MAAK,MAAM,WAAW,GAAG;AACxD,kBAAU,KAAK,IAAIA,MAAK,KAAK;AAAA,MAC/B;AACA,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AACL,QAAI,SAAS,CAAC;AACd,UAAM,UAAU,CAAC;AACjB,QAAI,qBAAqB,CAAC;AAC1B,QAAI,sBAAsB,CAAC;AAC3B,QAAI,aAAa,MAAM;AACrB,2BAAqB,KAAK,oBAAoB,UAAU,MAAM;AAC9D,4BAAsB,KAAK,oBAAoB,UAAU,OAAO;AAAA,IAClE;AACA,UAAM,WAAW,OAAO,KAAK,KAAK;AAClC,aAAS,QAAQ,CAAC,QAAQ;AACxB,YAAMA,QAAO,MAAM;AACnB,MAAAA,MAAK,WAAW,QAAQ,CAAC,MAAMP,WAAU;AACvC,cAAM,CAAC,UAAU,EAAE,UAAU,IAAI,oBAAoB,IAAI;AACzD,cAAM,YAAY,MAAM;AACxB,YAAI,UAAU,WAAW,MAAM;AAC7B,gBAAM,cAAc,UAAU,QAAQ,QAAQ,UAAU;AACxD,cAAI,gBAAgB,IAAI;AACtB,kBAAM,YAAY,GAAG,YAAY;AACjC,YAAAO,MAAK,WAAWP,UAAS;AAAA,UAC3B;AAAA,QACF;AACA,QAAAO,MAAK,OAAO,KAAK,SAAS;AAC1B,kBAAU,SAAS,KAAKA,KAAI;AAAA,MAC9B,CAAC;AAAA,IACH,CAAC;AACD,QAAI,OAAO,KAAK,mBAAmB,EAAE,WAAW,GAAG;AACjD,eAAS,QAAQ,CAAC,QAAQ;AACxB,cAAMA,QAAO,MAAM;AACnB,YAAIA,MAAK,SAAS,WAAW,GAAG;AAC9B,kBAAQ,KAAKA,KAAI;AAAA,QACnB;AAAA,MACF,CAAC;AAAA,IACH,OAAO;AACL,aAAO,KAAK,mBAAmB,EAAE,QAAQ,CAAC,SAAS;AACjD,cAAM,CAAC,QAAQ,IAAI,oBAAoB,IAAI;AAC3C,cAAMA,QAAO,MAAM;AACnB,YAAIA,SAAQ,MAAM;AAChB,UAAAA,MAAK,eAAe,oBAAoB;AACxC,kBAAQ,KAAKA,KAAI;AAAA,QACnB;AAAA,MACF,CAAC;AAAA,IACH;AACA,QAAI,OAAO,KAAK,kBAAkB,EAAE,SAAS,GAAG;AAC9C,aAAO,KAAK,kBAAkB,EAAE,QAAQ,CAAC,SAAS;AAChD,cAAM,CAAC,QAAQ,IAAI,oBAAoB,IAAI;AAC3C,cAAMA,QAAO,MAAM;AACnB,YAAIA,OAAM;AACR,UAAAA,MAAK,eAAe,mBAAmB;AACvC,iBAAO,KAAKA,KAAI;AAAA,QAClB;AAAA,MACF,CAAC;AAAA,IACH,OAAO;AACL,eAAS;AAAA,IACX;AACA,QAAI,YAAY,CAAC;AACjB,QAAI,MAAM,WAAW,QAAQ,MAAM,QAAQ,YAAY,MAAM;AAC3D,kBAAY,MAAM,QAAQ,SAAS,OAAO,CAAC,YAAY,UAAU;AAC/D,mBAAW,MAAM,UAAU,QAAQ,KAAK,YAAY,KAAK;AACzD,eAAO;AAAA,MACT,GAAG,CAAC,CAAC;AAAA,IACP;AACA,UAAM,SAAS,EAAE,OAAO,QAAQ,SAAS,SAAS,cAAc,WAAW,UAAU;AACrF,QAAI,UAAU,SAAS,GAAG;AACxB,aAAO,YAAY;AAAA,IACrB;AACA,WAAO;AAAA,EACT;AAAA,EACA,oBAAoB,SAAS;AAC3B,WAAO,OAAO,KAAK,WAAW,CAAC,CAAC,EAAE,OAAO,CAAC,MAAM,SAAS;AACvD,WAAK,QAAQ,MAAM,QAAQ;AAC3B,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AAAA,EACP;AAAA,EACA,QAAQA,OAAM;AACZ,UAAM,SAAS,gBAAgBA,MAAK,EAAE,KAAK,KAAK,UAAUA,MAAK,OAAO,CAAC;AACvE,QAAIA,MAAK,QAAQ,MAAM;AACrB,MAAAA,MAAK,OAAO,CAAC;AAAA,IACf;AACA,UAAM,UAAU;AAAA,MACd,MAAMA,MAAK;AAAA,MACX,IAAIA,MAAK;AAAA,MACT,UAAU,OAAO;AAAA,MACjB,aAAaA,MAAK,SAAS,CAAC,GAAG,IAAI,CAAC,WAAW,OAAO,WAAW,GAAG,IAAI,OAAO,MAAM,CAAC,IAAI,MAAM;AAAA,MAChG,QAAQ,CAAC;AAAA,MACT,UAAU,CAAC;AAAA,MACX,aAAa,CAAC;AAAA,MACd,YAAY,CAAC;AAAA,MACb,UAAUA,MAAK;AAAA,MACf,SAAS,OAAO;AAAA,IAClB;AACA,QAAI,OAAO,UAAU,MAAM;AACzB,cAAQ,cAAc,OAAO,OAAO,OAAO,CAAC,KAAK,UAAU;AACzD,YAAI,MAAM,QAAQ;AAAA,UAChB,MAAM,MAAM;AAAA,UACZ,iBAAiB,MAAM;AAAA,UACvB,eAAe,MAAM;AAAA,QACvB;AACA,eAAO;AAAA,MACT,GAAG,CAAC,CAAC;AAAA,IACP;AACA,QAAI,OAAO,SAAS,MAAM;AACxB,cAAQ,aAAa,OAAO,MAAM,OAAO,CAAC,KAAK,UAAU;AACvD,cAAM,OAAO,MAAM;AACnB,YAAI,QAAQ;AACZ,gBAAQ,MAAM;AAAA,eACP;AACH,oBAAQ,eAAeA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AAClE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,eAAeA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YAC9E;AACA;AAAA,eACG;AACH,oBAAQ,oBAAoBA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AACvE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,oBAAoBA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YACnF;AACA;AAAA,eACG;AACH,oBAAQ,eAAeA,MAAK,MAAM,MAAM,QAAQ,MAAM,gBAAgB,CAAC;AACvE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,eAAeA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YAC9E;AACA;AAAA,eACG;AACH,oBAAQ,qBAAqBA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AACxE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,qBAAqBA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YACpF;AACA;AAAA,eACG;AACH,oBAAQ,aAAaA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AAChE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,aAAaA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YAC5E;AACA;AAAA,eACG;AACH,oBAAQ,kBAAkBA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AACrE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,kBAAkBA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YACjF;AACA;AAAA,eACG;AACH,oBAAQ,oBAAoBA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AACvE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,oBAAoBA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YACnF;AACA;AAAA,eACG;AACH,oBAAQ,yBAAyBA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AAC5E,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,yBAAyBA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YACxF;AACA;AAAA,eACG;AACH,oBAAQ,cAAcA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AACjE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,cAAcA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YAC7E;AACA;AAAA,eACG;AACH,oBAAQ,mBAAmBA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AACtE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,mBAAmBA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YAClF;AACA;AAAA,eACG;AACH,oBAAQ,aAAaA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AAChE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,aAAaA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YAC5E;AACA;AAAA,eACG;AAAA,eACA;AACH;AAAA;AAEA,kBAAM,IAAI,MAAM,2BAA2B,MAAM,gBAAgBA,MAAK,IAAI;AAAA;AAE9E,YAAI,MAAM,QAAQ,EAAE,OAAO,KAAK;AAChC,eAAO;AAAA,MACT,GAAG,CAAC,CAAC;AAAA,IACP;AACA,WAAO;AAAA,EACT;AAAA,EACA,YAAY,aAAa;AACvB,UAAM,UAAU,YAAY;AAC5B,UAAM,eAAe,CAAC;AACtB,UAAM,UAAU,CAAC;AACjB,QAAI,QAAQ,CAAC;AACb,QAAI,WAAW,MAAM;AACnB,cAAQ,QAAQ,OAAO,CAAC,KAAKA,UAAS;AACpC,YAAIA,MAAK,QAAQ,KAAK,QAAQA,KAAI;AAClC,YAAIA,MAAK,OAAO,SAAS;AACvB,kBAAQ,KAAK,IAAIA,MAAK,KAAK;AAAA,QAC7B;AACA,eAAO;AAAA,MACT,GAAG,CAAC,CAAC;AAAA,IACP;AACA,UAAM,SAAS,CAAC;AAChB,UAAM,UAAU,CAAC;AACjB,gBAAY,UAAU,SAAS,QAAQ,CAAC,QAAQ;AAC9C,YAAM,CAAC,QAAQ,IAAI,oBAAoB,IAAI,IAAI;AAC/C,YAAMA,QAAO;AAAA,QACX,MAAM;AAAA,QACN,IAAI;AAAA,QACJ,QAAQ,CAAC;AAAA,QACT,YAAY,CAAC;AAAA,QACb,UAAU;AAAA,QACV,aAAa,CAAC;AAAA,QACd,YAAY,EAAE,OAAO,EAAE,OAAO,gBAAgB,IAAI,IAAI,GAAG,MAAM,QAAQ,EAAE;AAAA,QACzE,UAAU,CAAC;AAAA,MACb;AACA,MAAAA,MAAK,eAAe,IAAI;AACxB,aAAO,KAAKA,KAAI;AAChB,YAAM,YAAYA;AAAA,IACpB,CAAC;AACD,UAAM,WAAW,OAAO,KAAK,KAAK;AAClC,aAAS,QAAQ,CAAC,QAAQ;AACxB,YAAMA,QAAO,MAAM;AACnB,MAAAA,MAAK,WAAW,QAAQ,CAAC,MAAMP,WAAU;AACvC,cAAM,CAAC,UAAU,EAAE,UAAU,IAAI,oBAAoB,IAAI;AACzD,cAAM,YAAY,MAAM;AACxB,YAAI,UAAU,WAAW,MAAM;AAC7B,gBAAM,cAAc,UAAU,QAAQ,QAAQ,UAAU;AACxD,cAAI,gBAAgB,IAAI;AACtB,kBAAM,YAAY,GAAG,YAAY;AACjC,YAAAO,MAAK,WAAWP,UAAS;AAAA,UAC3B;AAAA,QACF;AACA,QAAAO,MAAK,OAAO,KAAK,SAAS;AAC1B,kBAAU,SAAS,KAAKA,KAAI;AAAA,MAC9B,CAAC;AAAA,IACH,CAAC;AACD,UAAM,gBAAgB,YAAY;AAClC,gBAAY,UAAU,UAAU,QAAQ,CAAC,WAAW;AAClD,YAAM,CAAC,UAAUP,MAAK,IAAI,oBAAoB,cAAc,OAAO,KAAK;AACxE,YAAMO,QAAO,MAAM;AACnB,UAAIA,SAAQ,MAAM;AAChB,QAAAA,MAAK,gBAAgBP;AACrB,gBAAQ,KAAKO,KAAI;AAAA,MACnB;AAAA,IACF,CAAC;AACD,UAAM,YAAY,KAAK,mBAAmB,WAAW;AACrD,WAAO,EAAE,OAAO,QAAQ,SAAS,SAAS,cAAc,UAAU;AAAA,EACpE;AAAA,EACA,mBAAmB,aAAa;AAC9B,WAAO;AAAA,MACL,YAAY,YAAY,UAAU;AAAA,MAClC,QAAQ,YAAY,UAAU,SAAS,OAAO,CAAC,KAAK,QAAQ;AAC1D,YAAI,IAAI,QAAQ,KAAK,mBAAmB,GAAG;AAC3C,eAAO;AAAA,MACT,GAAG,CAAC,CAAC;AAAA,MACL,SAAS,YAAY,UAAU,UAAU,OAAO,CAAC,KAAK,QAAQ;AAC5D,YAAI,IAAI,QAAQ,KAAK,mBAAmB,KAAK,YAAY,GAAG;AAC5D,eAAO;AAAA,MACT,GAAG,CAAC,CAAC;AAAA,IACP;AAAA,EACF;AAAA,EACA,mBAAmB,KAAK,UAAU;AAChC,QAAI,OAAO,IAAI;AACf,QAAI,YAAY,MAAM;AACpB,aAAO,SAAS;AAAA,IAClB;AACA,WAAO,EAAE,MAAM,OAAO,IAAI,KAAK;AAAA,EACjC;AACF;AACA,SAAS,aAAa,MAAM;AAC1B,QAAM,UAAU,IAAI,EAAE;AACtB,MAAI,OAAO,QAAQ,SAAS,aAAa;AACvC,WAAO,QAAQ,KAAK,IAAI;AAAA,EAC1B,WAAW,OAAO,WAAW,aAAa;AACxC,WAAO,IAAI,OAAO,MAAM,QAAQ,EAAE,SAAS;AAAA,EAC7C,OAAO;AACL,UAAM,IAAI,MAAM,kFAAkF;AAAA,EACpG;AACF;AACA,SAAS,iBAAiB,IAAI,UAAU;AACtC,QAAM,QAAQ,MAAM,QAAQ,EAAE,IAAI,OAAO,aAAa,MAAM,MAAM,EAAE,IAAI,aAAa,EAAE;AACvF,SAAO,WAAW,QAAQ,MAAM,YAAY;AAC9C;AACA,SAAS,eAAe,OAAO,MAAM,KAAK,WAAW,OAAO;AAC1D,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM;AACjB,WAAO,iBAAiB,MAAM,GAAG,QAAQ;AAAA,EAC3C;AACA,SAAO;AACT;AACA,SAAS,aAAa,OAAO,MAAM,KAAK;AACtC,QAAM,QAAQ,MAAM;AACpB,SAAO,QAAQ,MAAM,IAAI;AAC3B;AACA,SAAS,eAAe,OAAO,MAAM,KAAK;AACxC,QAAM,QAAQ,MAAM,SAAS,CAAC;AAC9B,QAAM,QAAQ,MAAM,QAAQ,OAAO,MAAM,OAAO,MAAM,QAAQ,OAAO,MAAM,OAAO;AAClF,SAAO,OAAO,UAAU,WAAW,QAAQ,SAAS,OAAO,EAAE;AAC/D;AACA,SAAS,gBAAgB,OAAO;AAC9B,MAAI,OAAO,UAAU,UAAU;AAC7B,YAAQ,SAAS;AAAA,EACnB;AACA,UAAQ;AAAA,SACD,SAAS;AAAA,SACT,SAAS;AACZ,aAAO;AAAA,SACJ,SAAS;AAAA,SACT,SAAS;AAAA,SACT,SAAS;AAAA,SACT,SAAS;AACZ,aAAO;AAAA,SACJ,SAAS;AACZ,aAAO;AAAA,SACJ,SAAS;AACZ,aAAO;AAAA,SACJ,SAAS;AACZ,aAAO;AAAA;AAEP,aAAO;AAAA;AAEb;AACA,SAAS,aAAa,OAAO,MAAM,KAAK;AACtC,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM,MAAM;AACvB,WAAO,MAAM,KAAK;AAAA,EACpB;AACA,SAAO;AACT;AACA,SAAS,cAAc,OAAO,MAAM,KAAK;AACvC,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM,MAAM;AACvB,WAAO,gBAAgB,MAAM,IAAI;AAAA,EACnC;AACA,SAAO;AACT;AACA,SAAS,mBAAmB,OAAO,MAAM,KAAK;AAC5C,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM,QAAQ,MAAM,KAAK,MAAM;AAC1C,WAAO,MAAM,KAAK,KAAK,IAAI,CAAC,MAAM,gBAAgB,CAAC,CAAC;AAAA,EACtD;AACA,SAAO;AACT;AACA,SAAS,sBAAsB,OAAO;AACpC,MAAI,MAAM,aAAa;AACrB,WAAO;AAAA,EACT;AACA,MAAI,MAAM,OAAO,MAAM;AACrB,WAAO,MAAM,IAAI,IAAI,CAAC,QAAQ,OAAO,IAAI,SAAS,WAAW,IAAI,OAAO,SAAS,IAAI,MAAM,EAAE,CAAC;AAAA,EAChG;AACA,SAAO,CAAC;AACV;AACA,SAAS,oBAAoB,OAAO,MAAM,KAAK;AAC7C,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM,OAAO;AACxB,WAAO,sBAAsB,MAAM,KAAK;AAAA,EAC1C;AACA,SAAO;AACT;AACA,SAAS,qBAAqB,OAAO,MAAM,KAAK;AAC9C,QAAM,QAAQ,MAAM;AACpB,MAAI,OAAO;AACT,aAAS,MAAM,KAAK,KAAK,MAAM,KAAK,EAAE,SAAS,MAAM,KAAK,IAAI,MAAM,KAAK,MAAM,CAAC,GAAG,IAAI,CAAC,MAAM,OAAO,MAAM,WAAW,IAAI,SAAS,GAAG,EAAE,CAAC;AAAA,EAC3I;AACA,SAAO;AACT;AACA,SAAS,oBAAoB,OAAO,MAAM,KAAK,WAAW,OAAO;AAC/D,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM,QAAQ,MAAM,KAAK,GAAG;AACvC,WAAO,MAAM,KAAK,EAAE,IAAI,CAAC,MAAM;AAC7B,aAAO,iBAAiB,GAAG,QAAQ;AAAA,IACrC,CAAC;AAAA,EACH;AACA,SAAO;AACT;AACA,SAAS,yBAAyB,OAAO,MAAM,KAAK;AAClD,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM,QAAQ,MAAM,KAAK,OAAO;AAC3C,WAAO,MAAM,KAAK,MAAM,IAAI,CAAC,MAAM;AACjC,aAAO,sBAAsB,CAAC;AAAA,IAChC,CAAC;AAAA,EACH;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,OAAO,MAAM,KAAK;AAC3C,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM,QAAQ,MAAM,KAAK,GAAG;AACvC,WAAO,MAAM,KAAK;AAAA,EACpB;AACA,SAAO;AACT;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAYA,OAAM,WAAW,SAAS;AACpC,SAAK,OAAOA;AACZ,SAAK,YAAY;AACjB,SAAK,UAAU;AACf,SAAK,SAAS,CAAC;AACf,SAAK,QAAQ,CAAC;AACd,SAAK,SAASA,MAAK,WAAW,IAAI,CAAC,SAAS,KAAK,SAAS,IAAI,CAAC;AAC/D,QAAIA,MAAK,YAAY,MAAM;AACzB,WAAK,QAAQ,OAAO,KAAKA,MAAK,QAAQ,EAAE,OAAO,CAAC,OAAO,QAAQ;AAC7D,cAAM,OAAO,KAAK,QAAQ,GAAG;AAC7B,eAAO;AAAA,MACT,GAAG,CAAC,CAAC;AAAA,IACP;AAAA,EACF;AAAA,EACA,SAAS,MAAM;AACb,WAAO,UAAU,MAAM,KAAK,WAAW,KAAK,OAAO;AAAA,EACrD;AAAA,EACA,QAAQ,MAAM,cAAc;AAC1B,UAAM,QAAQ,KAAK,KAAK,SAAS;AACjC,QAAI,MAAM,UAAU,MAAM;AACxB,aAAO,UAAU,MAAM,KAAK,WAAW,KAAK,OAAO;AAAA,IACrD;AACA,QAAI,MAAM,KAAK,QAAQ,MAAM,KAAK,MAAM;AACtC,aAAO,eAAe,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,IAC9D;AACA,QAAI,MAAM,KAAK,MAAM;AACnB,aAAO,eAAe,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,IAC9D;AACA,QAAI,MAAM,KAAK,MAAM;AACnB,aAAO,aAAa,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,IAC5D;AACA,QAAI,MAAM,SAAS,MAAM;AACvB,aAAO,oBAAoB,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,IACnE;AACA,QAAI,MAAM,QAAQ,MAAM;AACtB,aAAO,cAAc,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,IAC7D;AACA,QAAI,MAAM,QAAQ,MAAM;AACtB,UAAI,MAAM,KAAK,KAAK,QAAQ,MAAM,KAAK,KAAK,MAAM;AAChD,eAAO,qBAAqB,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,MACpE;AACA,UAAI,MAAM,KAAK,KAAK,MAAM;AACxB,eAAO,oBAAoB,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,MACnE;AACA,UAAI,MAAM,KAAK,SAAS,MAAM;AAC5B,eAAO,yBAAyB,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,MACxE;AACA,UAAI,MAAM,KAAK,KAAK,MAAM;AACxB,eAAO,kBAAkB,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,MACjE;AACA,UAAI,MAAM,KAAK,QAAQ,MAAM;AAC3B,eAAO,mBAAmB,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,MAClE;AAAA,IACF;AACA,WAAO;AAAA,EACT;AACF;AAGA,IAAI,4BAA4B,CAAC;AACjCnB,UAAS,2BAA2B;AAAA,EAClC,iBAAiB,MAAM;AAAA,EACvB,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,KAAK,MAAM;AAAA,EACX,KAAK,MAAM;AAAA,EACX,QAAQ,MAAM;AAAA,EACd,QAAQ,MAAM;AAAA,EACd,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,OAAO,MAAM;AAAA,EACb,SAAS,MAAM;AAAA,EACf,WAAW,MAAM;AAAA,EACjB,eAAe,MAAM;AAAA,EACrB,WAAW,MAAM;AAAA,EACjB,aAAa,MAAM;AAAA,EACnB,aAAa,MAAM;AAAA,EACnB,aAAa,MAAM;AAAA,EACnB,gBAAgB,MAAM;AAAA,EACtB,UAAU,MAAM;AAAA,EAChB,kBAAkB,MAAM;AAAA,EACxB,eAAe,MAAM;AAAA,EACrB,aAAa,MAAM;AAAA,EACnB,QAAQ,MAAM;AAAA,EACd,MAAM,MAAM;AAAA,EACZ,MAAM,MAAM;AAAA,EACZ,aAAa,MAAM;AAAA,EACnB,OAAO,MAAM;AAAA,EACb,SAAS,MAAM;AAAA,EACf,QAAQ,MAAM;AAAA,EACd,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,QAAQ,MAAM;AAAA,EACd,QAAQ,MAAM;AAAA,EACd,iBAAiB,MAAM;AAAA,EACvB,QAAQ,MAAM;AAAA,EACd,iBAAiB,MAAM;AAAA,EACvB,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,cAAc,MAAM;AAAA,EACpB,SAAS,MAAM;AAAA,EACf,QAAQ,MAAM;AAAA,EACd,eAAe,MAAM;AAAA,EACrB,cAAc,MAAM;AAAA,EACpB,iBAAiB,MAAM;AAAA,EACvB,MAAM,MAAM;AAAA,EACZ,YAAY,MAAM;AAAA,EAClB,KAAK,MAAM;AAAA,EACX,UAAU,MAAM;AAAA,EAChB,KAAK,MAAM;AAAA,EACX,SAAS,MAAM;AAAA,EACf,QAAQ,MAAM;AAAA,EACd,KAAK,MAAM;AAAA,EACX,qBAAqB,MAAM;AAAA,EAC3B,OAAO,MAAM;AAAA,EACb,KAAK,MAAM;AAAA,EACX,eAAe,MAAM;AAAA,EACrB,KAAK,MAAM;AAAA,EACX,YAAY,MAAM;AAAA,EAClB,OAAO,MAAM;AAAA,EACb,KAAK,MAAM;AAAA,EACX,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,UAAU,MAAM;AAAA,EAChB,OAAO,MAAM;AAAA,EACb,QAAQ,MAAM;AAAA,EACd,UAAU,MAAM;AAAA,EAChB,SAAS,MAAM;AAAA,EACf,cAAc,MAAM;AAAA,EACpB,MAAM,MAAM;AAAA,EACZ,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,aAAa,MAAM;AAAA,EACnB,OAAO,MAAM;AAAA,EACb,UAAU,MAAM;AAAA,EAChB,OAAO,MAAM;AAAA,EACb,OAAO,MAAM;AAAA,EACb,WAAW,MAAM;AAAA,EACjB,MAAM,MAAM;AAAA,EACZ,WAAW,MAAM;AAAA,EACjB,QAAQ,MAAM;AAAA,EACd,UAAU,MAAM;AAAA,EAChB,4BAA4B,MAAM;AAAA,EAClC,KAAK,MAAMF;AAAA,EACX,OAAO,MAAM;AAAA,EACb,YAAY,MAAM;AAAA,EAClB,YAAY,MAAM;AAAA,EAClB,WAAW,MAAM;AAAA,EACjB,YAAY,MAAM;AAAA,EAClB,YAAY,MAAM;AAAA,EAClB,WAAW,MAAM;AAAA,EACjB,YAAY,MAAM;AAAA,EAClB,QAAQ,MAAM;AAAA,EACd,YAAY,MAAM;AAAA,EAClB,QAAQ,MAAM;AAAA,EACd,KAAK,MAAM;AAAA,EACX,SAAS,MAAM;AAAA,EACf,WAAW,MAAM;AAAA,EACjB,mBAAmB,MAAM;AAAA,EACzB,SAAS,MAAM;AAAA,EACf,MAAM,MAAM;AAAA,EACZ,UAAU,MAAM;AAAA,EAChB,KAAK,MAAM;AAAA,EACX,SAAS,MAAM;AAAA,EACf,WAAW,MAAM;AAAA,EACjB,KAAK,MAAM;AAAA,EACX,SAAS,MAAM;AAAA,EACf,eAAe,MAAM;AAAA,EACrB,KAAK,MAAM;AAAA,EACX,cAAc,MAAM;AAAA,EACpB,aAAa,MAAM;AAAA,EACnB,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,UAAU,MAAM;AAAA,EAChB,QAAQ,MAAM;AAAA,EACd,MAAM,MAAM;AAAA,EACZ,UAAU,MAAM;AAAA,EAChB,IAAI,MAAM;AAAA,EACV,cAAc,MAAM;AAAA,EACpB,KAAK,MAAM;AAAA,EACX,OAAO,MAAM;AAAA,EACb,OAAO,MAAM;AAAA,EACb,OAAO,MAAM;AAAA,EACb,OAAO,MAAM;AAAA,EACb,MAAM,MAAM;AAAA,EACZ,KAAK,MAAM;AAAA,EACX,OAAO,MAAM;AAAA,EACb,OAAO,MAAM;AAAA,EACb,MAAM,MAAM;AAAA,EACZ,MAAM,MAAM;AAAA,EACZ,aAAa,MAAM;AAAA,EACnB,cAAc,MAAM;AAAA,EACpB,sBAAsB,MAAM;AAAA,EAC5B,eAAe,MAAM;AAAA,EACrB,OAAO,MAAM;AAAA,EACb,MAAM,MAAM;AAAA,EACZ,YAAY,MAAM;AAAA,EAClB,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,SAAS,MAAM;AAAA,EACf,SAAS,MAAM;AAAA,EACf,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,OAAO,MAAM;AAAA,EACb,QAAQ,MAAM;AAAA,EACd,WAAW,MAAM;AAAA,EACjB,cAAc,MAAM;AAAA,EACpB,MAAM,MAAM;AAAA,EACZ,iBAAiB,MAAM;AAAA,EACvB,gBAAgB,MAAM;AAAA,EACtB,SAAS,MAAM;AAAA,EACf,MAAM,MAAM;AAAA,EACZ,QAAQ,MAAM;AAAA,EACd,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,SAAS,MAAM;AAAA,EACf,SAAS,MAAM;AAAA,EACf,SAAS,MAAM;AAAA,EACf,SAAS,MAAM;AAAA,EACf,SAAS,MAAM;AAAA,EACf,UAAU,MAAM;AAAA,EAChB,gBAAgB,MAAM;AAAA,EACtB,QAAQ,MAAM;AAAA,EACd,eAAe,MAAM;AAAA,EACrB,UAAU,MAAM;AAAA,EAChB,OAAO,MAAM;AAAA,EACb,MAAM,MAAM;AAAA,EACZ,QAAQ,MAAM;AAAA,EACd,mBAAmB,MAAM;AAAA,EACzB,SAAS,MAAM;AAAA,EACf,OAAO,MAAM;AAAA,EACb,MAAM,MAAM;AAAA,EACZ,cAAc,MAAM;AAAA,EACpB,QAAQ,MAAM;AAAA,EACd,KAAK,MAAM;AAAA,EACX,KAAK,MAAM;AAAA,EACX,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,QAAQ,MAAM;AAAA,EACd,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,MAAM,MAAM;AAAA,EACZ,MAAM,MAAM;AAAA,EACZ,WAAW,MAAM;AAAA,EACjB,iBAAiB,MAAM;AAAA,EACvB,QAAQ,MAAM;AAAA,EACd,oBAAoB,MAAM;AAAA,EAC1B,SAAS,MAAM;AAAA,EACf,YAAY,MAAM;AAAA,EAClB,UAAU,MAAM;AAAA,EAChB,OAAO,MAAM;AAAA,EACb,YAAY,MAAM;AAAA,EAClB,OAAO,MAAM;AAAA,EACb,WAAW,MAAM;AACnB,CAAC;AAGD,IAAI,YAAY,CAACqB,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC7E,UAAQA,MAAK;AAAA,SACN;AAAA,SACA;AAAA,SACA,OAAO;AACV,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC7G;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,WAAWA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACtE;AAAA,SACK;AAAA,SACA;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SACxG;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SACxG;AAAA,SACA,OAAO;AACV,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC7G;AAAA,SACK,YAAY;AACf,aAAO,CAAC,IAAI,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAClH;AAAA,SACK,YAAY;AACf,aAAO,CAAC,IAAI,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAClH;AAAA,SACK,OAAO;AACV,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC7G;AAAA,SACK,WAAW;AACd,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACjH;AAAA,SACK,WAAW;AACd,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACjH;AAAA,SACK,OAAO;AACV,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC7G;AAAA,SACK,qBAAqB;AACxB,aAAO,CAAC,IAAI,kBAAkB,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC3H;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,aAAa,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC9E,UAAQA,MAAK;AAAA,SACN;AAAA,SACA;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC5D;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC5D;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1G;AACH,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC5D;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,QAAQ,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAClH;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D,SAAS;AACZ,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACjE;AAAA,SACK;AACH,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC5D;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D,SAAS;AACZ,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACjE;AAAA,SACK;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D,cAAc;AACjB,aAAO,CAAC,IAAI,WAAW,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACtE;AAAA,SACK;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D,SAAS;AACZ,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACjE;AAAA,SACK;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC9D;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAChE;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAChE;AAAA,SACK,YAAY;AACf,aAAO,CAAC,IAAI,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACpE;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAChE;AAAA,SACK,UAAU;AACb,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAClE;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAChE;AAAA,SACK;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D;AACH,aAAO,CAAC,IAAI,YAAY,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,gBAAgBA,OAAM,WAAW,OAAO,GAAG,cAAc,gBAAgBA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SACpL;AACH,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC5D;AACH,aAAO,CAAC,IAAI,MAAM,UAAUA,MAAK,WAAW,IAAI,WAAW,OAAO,CAAC,CAAC;AAAA,SACjE;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC5G;AACH,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAClH;AACH,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC9G;AACH,aAAO,CAAC,IAAI,MAAM,UAAUA,MAAK,WAAW,IAAI,WAAW,OAAO,CAAC,CAAC;AAAA;AAEpE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,SAAS,oCAAoC,QAAQ,QAAQ,qBAAqB,IAAI;AACpF,MAAI,OAAO,WAAW,YAAY,OAAO,WAAW,UAAU;AAC5D;AAAA,EACF;AACA,eAAa,OAAO,OAAO,WAAW,OAAO,QAAQ,MAAM,qBAAqB,WAAW,cAAc,mBAAmB;AAC5H,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,UAAM,OAAO,OAAO;AACpB,UAAM,OAAO,OAAO;AACpB,iBAAa,OAAO,OAAO,KAAK,OAAO,KAAK,SAAS,MAAM,MAAM,qBAAqB,WAAW,cAAc,mBAAmB;AAAA,EACpI;AACF;AACA,SAAS,iBAAiB,cAAc;AACtC,MAAI,OAAO,iBAAiB,YAAY,aAAa,KAAK,CAAC,QAAQ,MAAM,CAAC,GAAG;AAC3E,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,kBAAkB,SAAS,cAAc;AAClE,MAAI,eAAe,kBAAkB,kBAAkB,YAAY;AACnE,QAAM,sBAAsB,CAAC,iBAAiB,YAAY;AAC1D,MAAI,uBAAuB,QAAQ,WAAW,GAAG;AAC/C,UAAM,IAAI,MAAM,qFAAqF,cAAc;AAAA,EACrH;AACA,MAAI,qBAAqB;AACvB,YAAQ,QAAQ,CAAC,YAAY;AAC3B,qBAAe,kBAAkB,QAAQ,OAAO,YAAY;AAAA,IAC9D,CAAC;AAAA,EACH;AACA,MAAI,CAAC,iBAAiB,YAAY,GAAG;AACnC,UAAM,IAAI,MAAM,mCAAmC,cAAc;AAAA,EACnE;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,eAAe,eAAe;AACvD,MAAI,OAAO,kBAAkB,UAAU;AACrC,WAAO;AAAA,EACT;AACA,MAAI,OAAO,kBAAkB,UAAU;AACrC,WAAO;AAAA,EACT;AACA,MAAI,cAAc,WAAW,cAAc,QAAQ;AACjD,UAAM,IAAI,MAAM,oCAAoC,qBAAqB,eAAe;AAAA,EAC1F;AACA,QAAM,SAAS,CAAC;AAChB,WAAS,KAAK,GAAG,KAAK,cAAc,QAAQ,EAAE,IAAI;AAChD,UAAM,OAAO,cAAc;AAC3B,UAAM,OAAO,cAAc;AAC3B,QAAI,QAAQ,KAAK,QAAQ,KAAK,SAAS,MAAM;AAC3C,YAAM,IAAI,MAAM,oCAAoC,qBAAqB,eAAe;AAAA,IAC1F;AACA,WAAO,MAAM,QAAQ,IAAI,OAAO;AAAA,EAClC;AACA,SAAO;AACT;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,MAAM,OAAOe,UAAS,cAAc,wBAAwB,aAAa,gBAAgB;AACnG,SAAK,OAAO;AACZ,SAAK,QAAQ;AACb,SAAK,UAAUA;AACf,SAAK,eAAe;AACpB,SAAK,yBAAyB;AAC9B,SAAK,cAAc;AACnB,SAAK,iBAAiB;AACtB,SAAK,UAAU,CAAC;AAChB,SAAK,UAAU;AACf,SAAK,WAAW,OAAO,CAAC;AACxB,SAAK,KAAK,QAAQ;AAAA,EACpB;AAAA,EACA,IAAI,KAAK;AACP,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,IAAI,SAAS;AACX,WAAO,KAAK;AAAA,EACd;AAAA,EACA,cAAc,SAAS;AACrB,SAAK,QAAQ,QAAQ,CAAC,YAAY;AAChC,UAAI,WAAW,QAAQ,CAAC,QAAQ,IAAI,QAAQ,OAAO,EAAE,GAAG;AACtD,gBAAQ,OAAO,QAAQ;AAAA,MACzB;AAAA,IACF,CAAC;AACD,SAAK,UAAU,CAAC;AAChB,SAAK,UAAU;AACf,SAAK,SAAS,QAAQ;AAAA,EACxB;AAAA,EACA,OAAO;AACL,WAAO,KAAK,QAAQ;AAAA,EACtB;AAAA,EACA,KAAKtB,QAAO;AACV,QAAI,KAAK,SAAS;AAChB,YAAM,IAAI,MAAM,eAAe,KAAK,+BAA+B;AAAA,IACrE;AACA,QAAIA,SAAQ,KAAKA,UAAS,KAAK,KAAK,GAAG;AACrC,YAAM,IAAI,MAAM,4BAA4BA,8BAA6B,KAAK,KAAK,GAAG;AAAA,IACxF;AACA,UAAM,kBAAkB,KAAK,QAAQA;AACrC,QAAI,gBAAgB,SAAS;AAC3B,YAAM,IAAI,MAAM,eAAe,KAAK,8BAA8BA,4GAA2G;AAAA,IAC/K;AACA,QAAI,KAAK,gBAAgB;AACvB,sBAAgB,UAAU;AAAA,IAC5B;AACA,oBAAgB,OAAO;AACvB,WAAO,gBAAgB;AAAA,EACzB;AAAA,EACA,SAAS,SAAS;AAChB,WAAO,QAAQ,IAAI,CAACA,WAAU,KAAK,KAAKA,MAAK,CAAC;AAAA,EAChD;AAAA,EACA,MAAMA,QAAO,SAAS;AACpB,QAAI,KAAK,SAAS;AAChB,YAAM,IAAI,MAAM,eAAe,KAAK,+BAA+B;AAAA,IACrE;AACA,QAAIA,SAAQ,KAAK,CAAC,KAAK,eAAeA,UAAS,KAAK,SAAS;AAC3D,YAAM,IAAI,MAAM,2BAA2BA,oDAAmD,KAAK,SAAS;AAAA,IAC9G;AACA,UAAM,KAAK,KAAK,QAAQA,WAAU,CAAC;AACnC,QAAI,QAAQ,UAAU,KAAK,OAAO;AAChC,YAAM,IAAI,MAAM,eAAe,KAAK,8CAA8CA;AAAA,uCACjD,QAAQ,mCAAmC,KAAK,QAAQ;AAAA,IAC3F;AACA,QAAI,KAAK,KAAK,MAAM,MAAM,KAAK,gBAAgB,QAAQ,KAAK,aAAa,WAAW,IAAI;AACtF,WAAK,eAAe,QAAQ;AAAA,IAC9B;AACA,wCAAoC,KAAK,cAAc,QAAQ,OAAO,eAAe,KAAK,8CAA8CA,SAAQ;AAChJ,QAAI,GAAG,MAAM;AACX,YAAM,IAAI,MAAM,eAAe,KAAK,8CAA8CA,2CAA0C;AAAA,IAC9H;AACA,QAAI,GAAG,SAAS;AACd,YAAM,IAAI,MAAM,eAAe,KAAK,8CAA8CA,8CAA6C;AAAA,IACjI;AACA,OAAG,SAAS;AACZ,SAAK,OAAO;AACZ,OAAG,UAAU;AACb,SAAK,QAAQA,UAAS;AAAA,EACxB;AAAA,EACA,UAAU,SAAS,SAAS;AAC1B,QAAI,QAAQ,WAAW,QAAQ,QAAQ;AACrC,YAAM,IAAI,MAAM,eAAe,KAAK,kEAAkE,QAAQ,2CAA2C,QAAQ,SAAS;AAAA,IAC5K;AACA,YAAQ,QAAQ,CAAC,IAAIA,WAAU,KAAK,MAAM,IAAI,QAAQA,OAAM,CAAC;AAAA,EAC/D;AAAA,EACA,OAAO,SAAS,OAAO;AACrB,QAAI,CAAC,CAAC,SAAS,UAAU,KAAK,OAAO;AACnC,YAAM,IAAI,MAAM,wBAAwB,KAAK,oCAAoC,OAAO;AAAA,IAC1F;AACA,QAAI,CAAC,SAAS;AACZ,gBAAU,CAAC;AACX,eAAS,KAAK,GAAG,KAAK,KAAK,KAAK,GAAG,MAAM;AACvC,gBAAQ,KAAK,EAAE;AAAA,MACjB;AAAA,IACF,OAAO;AACL,gBAAU,QAAQ,MAAM,GAAG,KAAK,KAAK,CAAC;AAAA,IACxC;AACA,QAAI,QAAQ,WAAW,GAAG;AACxB,aAAO,OAAO,CAAC,GAAG,CAAC,CAAC,EAAE,OAAO,KAAK,YAAY,CAAC;AAAA,IACjD;AACA,UAAM,UAAU,KAAK,SAAS,OAAO;AACrC,wCAAoC,KAAK,cAAc,QAAQ,GAAG,OAAO,8BAA8B;AACvG,WAAO,MAAM,SAAS,CAAC;AAAA,EACzB;AAAA,EACA,OAAO,OAAO;AACZ,QAAI,CAAC,CAAC,SAAS,UAAU,KAAK,OAAO;AACnC,YAAM,IAAI,MAAM,wBAAwB,KAAK,oCAAoC,OAAO;AAAA,IAC1F;AACA,QAAI,KAAK,KAAK,MAAM,GAAG;AACrB,aAAO,OAAO,CAAC,GAAG,CAAC,CAAC,EAAE,OAAO,KAAK,YAAY,CAAC;AAAA,IACjD;AACA,UAAM,UAAU,CAAC;AACjB,aAAS,KAAK,GAAG,KAAK,KAAK,KAAK,GAAG,MAAM;AACvC,cAAQ,KAAK,EAAE;AAAA,IACjB;AACA,UAAM,UAAU,KAAK,SAAS,OAAO;AACrC,wCAAoC,KAAK,cAAc,QAAQ,GAAG,OAAO,mDAAmD,KAAK,wCAAwC,QAAQ,GAAG,QAAQ;AAC5L,WAAO,OAAO,SAAS,CAAC;AAAA,EAC1B;AAAA,EACA,QAAQ,SAAS,SAAS;AACxB,QAAI,QAAQ,UAAU,KAAK,OAAO;AAChC,YAAM,IAAI,MAAM,wBAAwB,KAAK,8BAA8B,QAAQ,OAAO;AAAA,IAC5F;AACA,QAAI,QAAQ,WAAW,QAAQ,MAAM,IAAI;AACvC,YAAM,IAAI,MAAM,sDAAsD,QAAQ,cAAc,QAAQ,MAAM,IAAI;AAAA,IAChH;AACA,UAAM,WAAW,KAAK,IAAI,GAAG,OAAO;AACpC,QAAI,CAAC,KAAK,eAAe,YAAY,KAAK,SAAS;AACjD,YAAM,IAAI,MAAM,mCAAmC,iBAAiB,KAAK,UAAU;AAAA,IACrF;AACA,SAAK,UAAU,SAAS,QAAQ,SAAS,CAAC,CAAC;AAAA,EAC7C;AAAA,EACA,MAAM,QAAQ,SAAS;AACrB,QAAI,QAAQ,UAAU,KAAK,OAAO;AAChC,YAAM,IAAI,MAAM,wBAAwB,KAAK,8BAA8B,QAAQ,OAAO;AAAA,IAC5F;AACA,QAAI,cAAc;AAClB,UAAM,oBAAoB,OAAO,IAAI,CAAC,QAAQ;AAC5C,qBAAe;AACf,aAAO;AAAA,IACT,CAAC;AACD,QAAI,gBAAgB,QAAQ,MAAM,IAAI;AACpC,YAAM,IAAI,MAAM;AAAA;AAAA,UAEZ,uCAAuC,QAAQ,OAAO;AAAA,IAC5D;AACA,QAAI,CAAC,KAAK,eAAe,OAAO,WAAW,KAAK,SAAS;AACvD,YAAM,IAAI,MAAM,2DAA2D,KAAK,eAAe,OAAO,sEAAsE;AAAA,IAC9K;AACA,UAAM,gBAAgB,gBAAgB,IAAI,IAAI,QAAQ,OAAO;AAC7D,UAAM,UAAU,CAAC;AACjB,SAAK,MAAM;AACT,gBAAU,QAAQ,SAAS,CAAC,GAAG,aAAa,aAAa,CAAC;AAC1D,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,cAAM,iBAAiB,OAAO,IAAI,IAAI,kBAAkB,KAAK;AAC7D,cAAM,WAAW,CAAC,GAAG,gBAAgB,CAAC;AACtC,cAAM,QAAQ,CAAC,GAAG,OAAO,KAAK,aAAa;AAC3C,gBAAQ,MAAM,QAAQ,MAAM,SAAS,UAAU,KAAK,GAAG,KAAK,YAAY;AAAA,MAC1E;AACA,aAAO;AAAA,IACT,CAAC;AACD,UAAM,UAAU,CAAC;AACjB,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,cAAQ,MAAM;AAAA,IAChB;AACA,SAAK,UAAU,SAAS,OAAO;AAAA,EACjC;AACF;AAGA,IAAI,aAAa,MAAM;AAAA,EACrB,YAAY,SAAS,cAAc,cAAc,iBAAiB,IAAI;AACpE,SAAK,UAAU;AACf,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,QAAI,WAAW,MAAM;AACnB,cAAQ,QAAQ,CAAC,YAAY;AAC3B,YAAI,iBAAiB,QAAQ,OAAO;AAClC,gBAAM,IAAI,MAAM,mCAAmC,mCAAmC,QAAQ,OAAO;AAAA,QACvG;AACA,4CAAoC,cAAc,QAAQ,OAAO,6BAA6B;AAC9F,aAAK,OAAO;AAAA,MACd,CAAC;AAAA,IACH;AACA,SAAK,WAAW,OAAO,CAAC;AACxB,SAAK,iBAAiB;AACtB,SAAK,KAAK,QAAQ;AAAA,EACpB;AAAA,EACA,IAAI,KAAK;AACP,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,OAAO;AACL,WAAO,IAAI,WAAW,CAAC,GAAG,KAAK,OAAO,GAAG,KAAK,cAAc,KAAK,YAAY;AAAA,EAC/E;AAAA,EACA,cAAc,SAAS;AACrB,SAAK,QAAQ,QAAQ,CAAC,YAAY;AAChC,UAAI,WAAW,QAAQ,CAAC,QAAQ,IAAI,QAAQ,EAAE,GAAG;AAC/C,gBAAQ,QAAQ;AAAA,MAClB;AAAA,IACF,CAAC;AACD,SAAK,QAAQ,SAAS;AACtB,SAAK,SAAS,QAAQ;AAAA,EACxB;AAAA,EACA,OAAO;AACL,WAAO,KAAK,QAAQ;AAAA,EACtB;AAAA,EACA,MAAM,cAAc,cAAc,cAAc,IAAI;AAClD,QAAI,iBAAiB,KAAK,cAAc;AACtC,YAAM,IAAI,MAAM,mCAAmC,mCAAmC,KAAK,cAAc;AAAA,IAC3G;AACA,QAAI,gBAAgB,MAAM,KAAK,QAAQ,WAAW,aAAa;AAC7D,YAAM,IAAI,MAAM,kCAAkC,4CAA4C,KAAK,QAAQ,kBAAkB;AAAA,IAC/H;AACA,wCAAoC,cAAc,KAAK,cAAc,6BAA6B;AAClG,UAAM,qBAAqB,kBAAkB,KAAK,cAAc,KAAK,SAAS,YAAY;AAC1F,WAAO,KAAK,MAAM;AAChB,YAAM,kBAAkB,KAAK,QAAQ,IAAI,CAAC,YAAY,QAAQ,SAAS,kBAAkB,CAAC;AAC1F,aAAO,MAAM,iBAAiB,CAAC;AAAA,IACjC,CAAC;AAAA,EACH;AAAA,EACA,QAAQ,cAAc,cAAc;AAClC,QAAI,iBAAiB,KAAK,cAAc;AACtC,YAAM,IAAI,MAAM,mCAAmC,mCAAmC,KAAK,cAAc;AAAA,IAC3G;AACA,QAAI,KAAK,KAAK,MAAM,GAAG;AACrB,YAAM,IAAI,MAAM,mCAAmC;AAAA,IACrD;AACA,UAAM,qBAAqB,kBAAkB,KAAK,cAAc,KAAK,SAAS,YAAY;AAC1F,UAAM,UAAU,KAAK,QAAQ,IAAI;AACjC,wCAAoC,QAAQ,OAAO,cAAc,6BAA6B;AAC9F,WAAO,QAAQ,SAAS,kBAAkB;AAAA,EAC5C;AAAA,EACA,SAAS,SAAS;AAChB,QAAI,QAAQ,UAAU,KAAK,cAAc;AACvC,YAAM,IAAI,MAAM,mCAAmC,QAAQ,4BAA4B,KAAK,cAAc;AAAA,IAC5G;AACA,wCAAoC,QAAQ,OAAO,KAAK,cAAc,6BAA6B;AACnG,QAAI,KAAK,mBAAmB,KAAK,KAAK,GAAG;AACvC,YAAM,IAAI,MAAM,0CAA0C;AAAA,IAC5D;AACA,SAAK,OAAO;AACZ,SAAK,QAAQ,KAAK,OAAO;AAAA,EAC3B;AAAA,EACA,OAAOT,OAAM;AACX,QAAIA,QAAO,GAAG;AACZ,YAAM,IAAI,MAAM,0DAA0DA,OAAM;AAAA,IAClF;AACA,QAAI,KAAK,mBAAmB,MAAMA,QAAO,KAAK,gBAAgB;AAC5D,YAAM,IAAI,MAAM,+BAA+BA,kCAAiC,KAAK,iBAAiB;AAAA,IACxG;AACA,UAAM,iBAAiB,IAAI,WAAW,CAAC,GAAG,KAAK,cAAc,KAAK,cAAc,KAAK,cAAc;AACnG,mBAAe,QAAQ,SAASA;AAChC,aAAS,KAAK,GAAG,KAAK,KAAK,IAAI,KAAK,QAAQ,QAAQA,KAAI,GAAG,EAAE,IAAI;AAC/D,qBAAe,QAAQ,MAAM,KAAK,QAAQ;AAAA,IAC5C;AACA,WAAO;AAAA,EACT;AAAA,EACA,QAAQ,cAAc,cAAc,cAAc;AAChD,QAAI,iBAAiB,KAAK,cAAc;AACtC,YAAM,IAAI,MAAM,mCAAmC,mCAAmC,KAAK,cAAc;AAAA,IAC3G;AACA,QAAI,eAAe,KAAK,eAAe,KAAK,QAAQ,QAAQ;AAC1D,YAAM,IAAI,MAAM,4BAA4B,+BAA+B,KAAK,QAAQ,kBAAkB;AAAA,IAC5G;AACA,QAAI,KAAK,QAAQ,iBAAiB,MAAM;AACtC,YAAM,IAAI,MAAM,oBAAoB,uBAAuB;AAAA,IAC7D;AACA,wCAAoC,KAAK,QAAQ,cAAc,OAAO,cAAc,6BAA6B;AACjH,UAAM,qBAAqB,kBAAkB,KAAK,cAAc,KAAK,SAAS,YAAY;AAC1F,WAAO,QAAQ,KAAK,QAAQ,eAAe,kBAAkB;AAAA,EAC/D;AAAA,EACA,QAAQ,cAAc,SAAS;AAC7B,QAAI,QAAQ,UAAU,KAAK,cAAc;AACvC,YAAM,IAAI,MAAM,mCAAmC,QAAQ,4BAA4B,KAAK,cAAc;AAAA,IAC5G;AACA,QAAI,eAAe,KAAK,KAAK,mBAAmB,MAAM,gBAAgB,KAAK,gBAAgB;AACzF,YAAM,IAAI,MAAM,yBAAyB,mCAAmC,KAAK,0BAA0B;AAAA,IAC7G;AACA,wCAAoC,KAAK,cAAc,QAAQ,OAAO,6BAA6B;AACnG,SAAK,OAAO;AACZ,SAAK,QAAQ,gBAAgB;AAAA,EAC/B;AAAA,EACA,OAAO,SAAS,cAAc,cAAc;AAC1C,QAAI,iBAAiB,KAAK,cAAc;AACtC,YAAM,IAAI,MAAM,mCAAmC,mCAAmC,KAAK,cAAc;AAAA,IAC3G;AACA,wCAAoC,KAAK,cAAc,cAAc,6BAA6B;AAClG,cAAU,QAAQ,MAAM,GAAG,KAAK,KAAK,CAAC;AACtC,UAAM,qBAAqB,kBAAkB,KAAK,cAAc,KAAK,SAAS,YAAY;AAC1F,QAAI,QAAQ,WAAW,GAAG;AACxB,aAAO,OAAO,CAAC,GAAG,CAAC,CAAC,EAAE,OAAO,kBAAkB,CAAC;AAAA,IAClD;AACA,WAAO,KAAK,MAAM;AAChB,YAAM,UAAU,QAAQ,IAAI,CAAC,OAAO,QAAQ,KAAK,QAAQ,KAAK,kBAAkB,CAAC;AACjF,aAAO,MAAM,SAAS,CAAC;AAAA,IACzB,CAAC;AAAA,EACH;AAAA,EACA,OAAO,cAAc,cAAc;AACjC,QAAI,CAAC,CAAC,gBAAgB,iBAAiB,KAAK,cAAc;AACxD,YAAM,IAAI,MAAM,uBAAuB,KAAK,2CAA2C,cAAc;AAAA,IACvG;AACA,wCAAoC,KAAK,cAAc,cAAc,6BAA6B;AAClG,UAAM,qBAAqB,kBAAkB,KAAK,cAAc,KAAK,SAAS,YAAY;AAC1F,QAAI,KAAK,KAAK,MAAM,GAAG;AACrB,aAAO,OAAO,CAAC,GAAG,CAAC,CAAC,EAAE,OAAO,kBAAkB,CAAC;AAAA,IAClD;AACA,WAAO,KAAK,MAAM;AAChB,YAAM,UAAU,KAAK,QAAQ,IAAI,CAAC,OAAO,QAAQ,IAAI,kBAAkB,CAAC;AACxE,aAAO,OAAO,SAAS,CAAC;AAAA,IAC1B,CAAC;AAAA,EACH;AACF;AACA,SAAS,WAAW,SAAS,cAAc,cAAc;AACvD,QAAM,QAAQ,QAAQ;AACtB,MAAI,QAAQ,MAAM,SAAS,GAAG;AAC5B,UAAM,IAAI,MAAM,oDAAoD,QAAQ,OAAO;AAAA,EACrF;AACA,MAAI,QAAQ,UAAU,cAAc;AAClC,UAAM,IAAI,MAAM,mCAAmC,QAAQ,4BAA4B,cAAc;AAAA,EACvG;AACA,QAAM,qBAAqB,QAAQ,MAAM,MAAM,CAAC;AAChD,sCAAoC,oBAAoB,cAAc,6BAA6B;AACnG,QAAM,aAAa,QAAQ,OAAO;AAClC,SAAO,IAAI,WAAW,YAAY,cAAc,KAAK;AACvD;AACA,SAAS,QAAQ,cAAc,cAAc,aAAa,gBAAgB;AACxE,SAAO,IAAI,WAAW,CAAC,GAAG,cAAc,cAAc,cAAc;AACtE;AACA,SAAS,QAAQ,SAAS,SAAS,cAAc,aAAa;AAC5D,MAAI,QAAQ,WAAW,QAAQ,MAAM,IAAI;AACvC,UAAM,IAAI,MAAM,sDAAsD,QAAQ,cAAc,QAAQ,MAAM,IAAI;AAAA,EAChH;AACA,QAAM,WAAW,KAAK,IAAI,GAAG,OAAO;AACpC,MAAI,eAAe,QAAQ,gBAAgB,MAAM,YAAY,aAAa;AACxE,UAAM,IAAI,MAAM,mCAAmC,iBAAiB,cAAc;AAAA,EACpF;AACA,QAAM,OAAO,IAAI,WAAW,CAAC,GAAG,cAAc,QAAQ,OAAO,WAAW;AACxE,QAAM,UAAU,QAAQ,SAAS,CAAC;AAClC,UAAQ,QAAQ,CAAC,OAAOS,WAAU;AAChC,SAAK,QAAQ,OAAO,QAAQA,OAAM;AAAA,EACpC,CAAC;AACD,SAAO;AACT;AACA,SAAS,OAAO,SAAS,QAAQ,cAAc;AAC7C,MAAI,cAAc;AAClB,QAAM,oBAAoB,OAAO,IAAI,CAAC,QAAQ;AAC5C,mBAAe;AACf,WAAO;AAAA,EACT,CAAC;AACD,MAAI,gBAAgB,QAAQ,MAAM,IAAI;AACpC,UAAM,IAAI,MAAM;AAAA;AAAA,UAEV,uCAAuC,QAAQ,OAAO;AAAA,EAC9D;AACA,QAAM,uBAAuB,QAAQ,MAAM,MAAM,CAAC;AAClD,QAAM,qBAAqB,kBAAkB,sBAAsB,YAAY;AAC/E,QAAM,gBAAgB,gBAAgB,IAAI,IAAI,QAAQ,OAAO;AAC7D,QAAM,UAAU,KAAK,MAAM;AACzB,UAAM,WAAW,CAAC;AAClB,cAAU,QAAQ,SAAS,CAAC,GAAG,aAAa,aAAa,CAAC;AAC1D,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,YAAM,iBAAiB,OAAO,IAAI,IAAI,kBAAkB,KAAK;AAC7D,YAAM,UAAU,CAAC,GAAG,gBAAgB,CAAC;AACrC,YAAM,QAAQ,CAAC,GAAG,OAAO,KAAK,aAAa;AAC3C,eAAS,MAAM,QAAQ,MAAM,SAAS,SAAS,KAAK,GAAG,kBAAkB;AAAA,IAC3E;AACA,YAAQ,QAAQ;AAChB,WAAO;AAAA,EACT,CAAC;AACD,QAAM,OAAO,IAAI,WAAW,CAAC,GAAG,cAAc,QAAQ,OAAO,OAAO,MAAM;AAC1E,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,SAAK,QAAQ,IAAI,QAAQ,GAAG;AAAA,EAC9B;AACA,SAAO;AACT;AAGA,IAAI,aAAa,OAAOO,OAAM,WAAW,YAAY;AACnD,UAAQA,MAAK;AAAA,SACN;AAAA,SACA,eAAe;AAClB,YAAM,WAAW,cAAc,cAAcA,OAAM,WAAW,OAAO;AACrE,YAAM,WAAW,cAAc,cAAcA,OAAM,WAAW,OAAO;AACrE,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,YAAY,MAAM,KAAK,KAAK;AAClC,UAAI,UAAU,IAAI;AAChB,eAAO,QAAQ,YAAY,UAAU,qBAAqB,MAAM,QAAQ,gBAAgB,QAAQ,aAAa;AAAA,MAC/G,OAAO;AACL,eAAO,QAAQ,YAAY,UAAU,qBAAqB,MAAM,QAAQ,gBAAgB,QAAQ,aAAa;AAAA,MAC/G;AAAA,IACF;AAAA,SACK;AAAA,SACA,kBAAkB;AACrB,YAAM,WAAW,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC/D,YAAM,WAAW,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC/D,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,aAAa,MAAM,QAAQ,YAAY,UAAU,qBAAqB,MAAM,QAAQ,gBAAgB,QAAQ,aAAa;AAC/H,YAAM,SAAS,KAAK,IAAI,CAAC,YAAY,QAAQ,EAAE;AAC/C,UAAI,YAAY,MAAM,WAAW,GAAG,KAAK;AACzC,iBAAW,QAAQ,CAAC,YAAY;AAC9B,YAAI,CAAC,QAAQ,QAAQ,OAAO,QAAQ,QAAQ,EAAE,MAAM,IAAI;AACtD,kBAAQ,QAAQ;AAAA,QAClB;AAAA,MACF,CAAC;AACD,UAAI,SAAS;AACb,aAAO,UAAU,IAAI;AACnB,cAAM,aAAa;AACnB,iBAAS,MAAM,QAAQ,YAAY,UAAU,qBAAqB,QAAQ,QAAQ,gBAAgB,QAAQ,aAAa;AACvH,cAAM,YAAY,OAAO,IAAI,CAAC,YAAY,QAAQ,EAAE;AACpD,mBAAW,QAAQ,CAAC,YAAY;AAC9B,cAAI,CAAC,QAAQ,QAAQ,OAAO,QAAQ,QAAQ,EAAE,MAAM,MAAM,UAAU,QAAQ,QAAQ,EAAE,MAAM,IAAI;AAC9F,oBAAQ,QAAQ;AAAA,UAClB;AAAA,QACF,CAAC;AACD,cAAM,cAAc,MAAM,QAAQ,YAAY,UAAU,qBAAqB,QAAQ,QAAQ,gBAAgB,QAAQ,aAAa;AAClI,oBAAY,MAAM,YAAY,GAAG,KAAK;AACtC,oBAAY,QAAQ,CAAC,YAAY;AAC/B,cAAI,CAAC,QAAQ,QAAQ,OAAO,QAAQ,QAAQ,EAAE,MAAM,MAAM,UAAU,QAAQ,QAAQ,EAAE,MAAM,IAAI;AAC9F,oBAAQ,QAAQ;AAAA,UAClB;AAAA,QACF,CAAC;AAAA,MACH;AACA,aAAO;AAAA,IACT;AAAA,SACK,YAAY;AACf,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,YAAY,IAAI,CAAC;AAAA,IAC3B;AAAA,SACK,UAAU;AACb,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,UAAI,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AACzD,UAAI,CAAC,KAAK,MAAM;AACd,eAAO,YAAY,IAAI;AAAA,MACzB;AACA,cAAQ,MAAM,KAAK,KAAK,GAAG,KAAK,CAAC,QAAQ,IAAI,IAAI,CAAC,MAAM,MAAM;AAAA,IAChE;AAAA,SACK,SAAS;AACZ,YAAM,YAAYA,MAAK,WAAW,KAAK,CAAC,SAAS,UAAU,MAAM,WAAW,OAAO,MAAM,MAAM;AAC/F,UAAI,WAAW;AACb,cAAM,OAAO,UAAU,WAAW,WAAW,OAAO;AACpD,eAAO,CAAC,YAAY,IAAI,CAAC;AAAA,MAC3B;AACA,aAAO;AAAA,IACT;AAAA,SACK,SAAS;AACZ,YAAM,UAAU,cAAc,aAAaA,OAAM,WAAW,OAAO;AACnE,YAAM,OAAO,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC7D,cAAQ,WAAW,OAAO;AAC1B,aAAO,CAAC,YAAY,IAAI,CAAC;AAAA,IAC3B;AAAA,SACK,QAAQ;AACX,YAAM,OAAO,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC7D,cAAQ,UAAU;AAClB,aAAO,CAAC,YAAY,IAAI,CAAC;AAAA,IAC3B;AAAA,SACK,iBAAiB;AACpB,YAAM,OAAO,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC7D,cAAQ,cAAc;AACtB,aAAO,CAAC,YAAY,IAAI,CAAC;AAAA,IAC3B;AAAA,SACK,iBAAiB;AACpB,YAAMhB,QAAO,cAAc,QAAQgB,OAAM,WAAW,OAAO;AAC3D,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,cAAc,cAAc,eAAeA,OAAM,WAAW,OAAO;AACzE,YAAM,iBAAiB,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC/E,YAAM,yBAAyB,cAAc,0BAA0BA,OAAM,WAAW,OAAO;AAC/F,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,cAAc,IAAI,YAAY,MAAM,OAAOhB,OAAM,cAAc,wBAAwB,aAAa,cAAc;AACxH,cAAQ,eAAe,WAAW;AAClC,aAAO,CAAC,YAAY,UAAU,OAAO,CAAC,CAAC;AAAA,IACzC;AAAA,SACK,sBAAsB;AACzB,YAAM,KAAK,cAAc,iBAAiBgB,OAAM,WAAW,OAAO;AAClE,YAAMP,SAAQ,cAAc,SAASO,OAAM,WAAW,OAAO;AAC7D,YAAM,cAAc,cAAc,UAAUA,OAAM,WAAW,OAAO;AACpE,YAAM,mBAAmB,QAAQ,eAAe,GAAG,EAAE;AACrD,uBAAiB,MAAMP,QAAO,WAAW;AACzC,aAAO,CAAC,iBAAiB,QAAQ;AAAA,IACnC;AAAA,SACK,qBAAqB;AACxB,YAAM,SAAS,cAAc,iBAAiBO,OAAM,WAAW,OAAO;AACtE,YAAM,YAAY,cAAc,SAASA,OAAM,WAAW,OAAO;AACjE,YAAM,kBAAkB,QAAQ,eAAe,OAAO,EAAE;AACxD,aAAO,CAAC,gBAAgB,KAAK,SAAS,CAAC;AAAA,IACzC;AAAA,SACK,uBAAuB;AAC1B,YAAM,WAAW,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AACxE,YAAM,gBAAgB,cAAc,WAAWA,OAAM,WAAW,OAAO;AACvE,YAAM,cAAc,cAAc,SAASA,OAAM,WAAW,OAAO;AACnE,YAAM,oBAAoB,QAAQ,eAAe,SAAS,EAAE;AAC5D,aAAO,CAAC,kBAAkB,OAAO,eAAe,WAAW,CAAC;AAAA,IAC9D;AAAA,SACK,wBAAwB;AAC3B,YAAM,YAAY,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AACzE,YAAM,iBAAiB,cAAc,WAAWA,OAAM,WAAW,OAAO;AACxE,YAAM,gBAAgB,cAAc,UAAUA,OAAM,WAAW,OAAO;AACtE,YAAM,qBAAqB,QAAQ,eAAe,UAAU,EAAE;AAC9D,yBAAmB,QAAQ,gBAAgB,aAAa;AACxD,aAAO,CAAC,mBAAmB,QAAQ;AAAA,IACrC;AAAA,SACK,uBAAuB;AAC1B,YAAM,WAAW,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AACxE,YAAM,oBAAoB,QAAQ,eAAe,SAAS,EAAE;AAC5D,YAAM,cAAc,cAAc,SAASA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,kBAAkB,OAAO,WAAW,CAAC;AAAA,IAC/C;AAAA,SACK,sBAAsB;AACzB,YAAM,UAAU,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AACvE,YAAM,cAAc,cAAc,UAAUA,OAAM,WAAW,OAAO;AACpE,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,mBAAmB,QAAQ,eAAe,QAAQ,EAAE;AAC1D,uBAAiB,MAAM,SAAS,WAAW;AAC3C,aAAO,CAAC,iBAAiB,QAAQ;AAAA,IACnC;AAAA,SACK,qBAAqB;AACxB,YAAM,SAAS,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AACtE,YAAM,kBAAkB,QAAQ,eAAe,OAAO,EAAE;AACxD,aAAO,CAAC,OAAO,gBAAgB,KAAK,GAAG,OAAO,CAAC;AAAA,IACjD;AAAA,SACK,sBAAsB;AACzB,YAAM,UAAU,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AACvE,YAAM,mBAAmB,QAAQ,eAAe,QAAQ,EAAE;AAC1D,uBAAiB,cAAc;AAC/B,aAAO,CAAC,iBAAiB,QAAQ;AAAA,IACnC;AAAA,SACK,qBAAqB;AACxB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAMP,SAAQ,cAAc,SAASO,OAAM,WAAW,OAAO;AAC7D,YAAM,cAAc,cAAc,UAAUA,OAAM,WAAW,OAAO;AACpE,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,iBAAW,QAAQP,QAAO,WAAW;AACrC,aAAO,CAAC,WAAW,QAAQ;AAAA,IAC7B;AAAA,SACK,qBAAqB;AACxB,YAAM,WAAW,cAAc,gBAAgBO,OAAM,WAAW,OAAO;AACvE,YAAM,YAAY,cAAc,SAASA,OAAM,WAAW,OAAO;AACjE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,aAAO,CAAC,WAAW,QAAQ,WAAW,cAAc,YAAY,CAAC;AAAA,IACnE;AAAA,SACK;AAAA,SACA,qBAAqB;AACxB,YAAM,iBAAiB,cAAc,WAAWA,OAAM,WAAW,OAAO;AACxE,YAAM,gBAAgB,cAAc,UAAUA,OAAM,WAAW,OAAO;AACtE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,cAAc,cAAc,eAAeA,OAAM,WAAW,OAAO;AACzE,YAAM,aAAa,QAAQ,eAAe,gBAAgB,cAAc,WAAW;AACnF,cAAQ,cAAc,UAAU;AAChC,aAAO,CAAC,WAAW,QAAQ;AAAA,IAC7B;AAAA,SACK;AAAA,SACA,mBAAmB;AACtB,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,UAAI;AACJ,UAAIA,MAAK,OAAO,qBAAqB;AACnC,2BAAmB;AAAA,MACrB,OAAO;AACL,2BAAmB;AAAA,MACrB;AACA,YAAM,cAAc,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC5E,YAAM,iBAAiBA,MAAK,OAAO,sBAAsB,KAAK;AAC9D,YAAM,aAAa,QAAQ,cAAc,cAAc,aAAa,cAAc;AAClF,cAAQ,cAAc,UAAU;AAChC,aAAO,CAAC,WAAW,QAAQ;AAAA,IAC7B;AAAA,SACK,oBAAoB;AACvB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAM,gBAAgB,cAAc,WAAWA,OAAM,WAAW,OAAO;AACvE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,aAAO,CAAC,WAAW,OAAO,eAAe,cAAc,YAAY,CAAC;AAAA,IACtE;AAAA,SACK,mBAAmB;AACtB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,cAAc,cAAc,eAAeA,OAAM,WAAW,OAAO;AACzE,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,aAAO,CAAC,WAAW,MAAM,cAAc,cAAc,WAAW,CAAC;AAAA,IACnE;AAAA,SACK,wBAAwB;AAC3B,YAAM,UAAU,cAAc,UAAUA,OAAM,WAAW,OAAO;AAChE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,aAAa,WAAW,SAAS,cAAc,YAAY;AACjE,cAAQ,cAAc,UAAU;AAChC,aAAO,CAAC,WAAW,QAAQ;AAAA,IAC7B;AAAA,SACK;AAAA,SACA,sBAAsB;AACzB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,YAAM,cAAc,cAAc,SAASA,OAAM,WAAW,OAAO;AACnE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,aAAO,CAAC,WAAW,OAAO,aAAa,YAAY,CAAC;AAAA,IACtD;AAAA,SACK,sBAAsB;AACzB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAM,cAAc,cAAc,UAAUA,OAAM,WAAW,OAAO;AACpE,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,iBAAW,SAAS,WAAW;AAC/B,aAAO,CAAC,WAAW,QAAQ;AAAA,IAC7B;AAAA,SACK,qBAAqB;AACxB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,aAAO,CAAC,WAAW,QAAQ,cAAc,YAAY,CAAC;AAAA,IACxD;AAAA,SACK,mBAAmB;AACtB,YAAM,cAAc,cAAc,UAAUA,OAAM,WAAW,OAAO;AACpE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,aAAa,OAAO,aAAa,SAAS,YAAY;AAC5D,cAAQ,cAAc,UAAU;AAChC,aAAO,CAAC,WAAW,QAAQ;AAAA,IAC7B;AAAA,SACK,oBAAoB;AACvB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,aAAO,CAAC,OAAO,WAAW,KAAK,GAAG,OAAO,CAAC;AAAA,IAC5C;AAAA,SACK,oBAAoB;AACvB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAMhB,QAAO,cAAc,QAAQgB,OAAM,WAAW,OAAO;AAC3D,YAAM,gBAAgB,QAAQ,cAAc,SAAS,EAAE;AACvD,YAAM,iBAAiB,cAAc,OAAOhB,KAAI;AAChD,cAAQ,cAAc,cAAc;AACpC,aAAO,CAAC,eAAe,QAAQ;AAAA,IACjC;AAAA;AAEE,YAAM,UAAU,aAAagB,MAAK,uBAAuB;AAAA;AAE/D;AAGA,SAAS,4BAA4BA,OAAM,WAAW,SAAS;AAC7D,QAAM,CAAC,SAAS,cAAc,IAAI,cAAc,YAAYA,OAAM,WAAW,OAAO;AACpF,QAAM,YAAY,YAAY;AAC9B,QAAM,YAAY,CAAC;AACnB,QAAM,UAAU,mBAAmB;AACnC,QAAM,cAAc,YAAY;AAChC,QAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,MAAI,WAAW;AACb,QAAI,WAAW,YAAY,GAAG;AAC5B,YAAM,IAAI,MAAM,uGAAuG;AAAA,IACzH;AACA,QAAI,CAAC,WAAW,aAAa,YAAY,GAAG;AAC1C,YAAM,IAAI,MAAM,kFAAkF;AAAA,IACpG;AAAA,EACF;AACA,MAAI,aAAa;AACf,UAAM,IAAI,MAAM,sEAAsE;AAAA,EACxF;AACA,QAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,QAAM,OAAO,WAAWA,OAAM,WAAW,OAAO;AAChD,QAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO,EAAE,YAAY;AACrF,QAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,MAAI,CAAC,SAAS,QAAQ,IAAI,cAAc,QAAQA,OAAM,WAAW,OAAO;AACxE,MAAI,WAAW;AACb,eAAW;AACX,cAAU;AAAA,EACZ;AACA,QAAM,iBAAiB,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC/E,SAAO;AAAA,IACL;AAAA,IACA,KAAK;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AACA,IAAI,aAAa,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC9E,UAAQA,MAAK;AAAA,SACN,UAAU;AACb,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO,EAAE,YAAY;AACrF,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,QAAQ,MAAM,YAAY,QAAQ,CAAC;AAAA,IACzJ;AAAA,SACK,UAAU;AACb,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,WAAWA,OAAM,WAAW,OAAO;AAChD,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO,EAAE,YAAY;AACrF,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,MAAM,YAAY,CAAC,UAAU,IAAI,UAAU,EAAE,CAAC,CAAC;AAAA,IAC7L;AAAA,SACK,gBAAgB;AACnB,YAAM,EAAE,QAAQ,KAAK,MAAM,YAAY,WAAW,SAAS,UAAU,gBAAgB,eAAe,IAAI,4BAA4BA,OAAM,WAAW,OAAO;AAC5J,aAAO,CAAC,IAAI,MAAM,OAAO;AAAA,QACvB,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO;AAAA,QAC9C,QAAQ,cAAc,UAAUA,OAAM,WAAW,OAAO;AAAA,QACxD,SAAS,CAAC,OAAO,IAAI,OAAO,EAAE;AAAA,QAC9B,KAAK;AAAA,QACL;AAAA,QACA,WAAW,CAAC,UAAU,IAAI,UAAU,EAAE;AAAA,QACtC,MAAM;AAAA,QACN,YAAY;AAAA,QACZ,wBAAwB;AAAA,QACxB;AAAA,MACF,CAAC,CAAC;AAAA,IACJ;AAAA,SACK,8BAA8B;AACjC,YAAM,EAAE,QAAQ,KAAK,MAAM,YAAY,WAAW,SAAS,UAAU,gBAAgB,eAAe,IAAI,4BAA4BA,OAAM,WAAW,OAAO;AAC5J,aAAO,CAAC,IAAI,MAAM,gBAAgB;AAAA,QAChC,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO;AAAA,QAC9C,QAAQ,cAAc,UAAUA,OAAM,WAAW,OAAO;AAAA,QACxD,SAAS,CAAC,OAAO,IAAI,OAAO,EAAE;AAAA,QAC9B,KAAK;AAAA,QACL;AAAA,QACA,WAAW,CAAC,UAAU,IAAI,UAAU,EAAE;AAAA,QACtC,MAAM;AAAA,QACN,YAAY;AAAA,QACZ,wBAAwB;AAAA,QACxB;AAAA,MACF,CAAC,CAAC;AAAA,IACJ;AAAA,SACK;AAAA,SACA,mBAAmB;AACtB,YAAM,QAAQ,cAAc,eAAeA,OAAM,WAAW,OAAO;AACnE,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,WAAWA,OAAM,WAAW,OAAO;AAChD,aAAO,CAAC,IAAI,gBAAgB,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,OAAO,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,IAAI,CAAC;AAAA,IACnK;AAAA,SACK;AAAA,SACA,mBAAmB;AACtB,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,WAAWA,OAAM,WAAW,OAAO;AAChD,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO,EAAE,YAAY;AACrF,aAAO,CAAC,IAAI,gBAAgB,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,MAAM,YAAY,CAAC,UAAU,IAAI,UAAU,EAAE,CAAC,CAAC;AAAA,IAC1M;AAAA,SACK,UAAU;AACb,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO,EAAE,YAAY;AACrF,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,CAAC,OAAO,IAAI,OAAO,IAAI,OAAO,EAAE,GAAG,MAAM,YAAY,CAAC,UAAU,IAAI,UAAU,IAAI,UAAU,EAAE,CAAC,CAAC;AAAA,IACtN;AAAA,SACK,WAAW;AACd,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,CAAC,WAAW,IAAI,WAAW,EAAE,GAAG,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,IAAI,CAAC;AAAA,IACjI;AAAA,SACK,WAAW;AACd,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,CAAC,WAAW,IAAI,WAAW,EAAE,GAAG,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,IAAI,CAAC;AAAA,IACjI;AAAA,SACK,qBAAqB;AACxB,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,YAAM,sBAAsB,cAAc,uBAAuBA,OAAM,WAAW,OAAO;AACzF,YAAM,EAAE,QAAQ,QAAQ,IAAI,IAAI,kBAAkB,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,CAAC,WAAW,IAAI,WAAW,EAAE,GAAG,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,MAAM,mBAAmB;AACjL,aAAO,CAAC,QAAQ,OAAO;AAAA,IACzB;AAAA,SACK,aAAa;AAChB,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,CAAC,WAAW,IAAI,WAAW,IAAI,WAAW,EAAE,GAAG,CAAC,OAAO,IAAI,OAAO,IAAI,OAAO,EAAE,GAAG,IAAI,CAAC;AAAA,IAC7J;AAAA,SACK,aAAa;AAChB,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,CAAC,WAAW,IAAI,WAAW,IAAI,WAAW,EAAE,GAAG,CAAC,OAAO,IAAI,OAAO,IAAI,OAAO,EAAE,GAAG,IAAI,CAAC;AAAA,IAC7J;AAAA,SACK,cAAc;AACjB,YAAMJ,WAAU,cAAc,WAAWI,OAAM,WAAW,OAAO;AACjE,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,eAAeJ,SAAQ;AAC7B,YAAM,cAAcA,SAAQ;AAC5B,YAAM,iBAAiB,UAAU;AACjC,YAAM,gBAAgB,UAAU;AAChC,aAAO,CAAC,IAAI,WAAW,cAAc,KAAKI,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,CAAC,cAAc,WAAW,GAAG,MAAM,CAAC,gBAAgB,aAAa,GAAG,MAAM,CAAC;AAAA,IACrM;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,aAAa,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC9E,UAAQA,MAAK;AAAA,SACN,QAAQ;AACX,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,aAAO,CAAC,IAAI,KAAK,OAAO,OAAO,KAAK,CAAC;AAAA,IACvC;AAAA,SACK,YAAY;AACf,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,MAAM,cAAc,OAAOA,OAAM,WAAW,OAAO;AACzD,aAAO,CAAC,IAAI,SAAS,OAAO,MAAM,GAAG,CAAC;AAAA,IACxC;AAAA,SACK,eAAe;AAClB,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,YAAY,QAAQ,YAAY,IAAI,CAAC;AAAA,IACnD;AAAA,SACK,UAAU;AACb,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,OAAO,SAAS,OAAO,SAAS,QAAQ,CAAC;AAAA,IACvD;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACtH;AAAA,SACK,YAAY;AACf,aAAO,CAAC,IAAI,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACpE;AAAA,SACK,wBAAwB;AAC3B,aAAO,CAAC,IAAI,qBAAqB,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACvL;AAAA,SACK,iBAAiB;AACpB,aAAO,CAAC,IAAI;AAAA,QACV,cAAc,SAASA,OAAM,WAAW,OAAO;AAAA,QAC/C,cAAc,UAAUA,OAAM,WAAW,OAAO;AAAA,QAChD,cAAc,UAAUA,OAAM,WAAW,OAAO;AAAA,QAChD,cAAc,SAASA,OAAM,WAAW,OAAO;AAAA,MACjD,CAAC;AAAA,IACH;AAAA,SACK,SAAS;AACZ,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,QAAQ,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC5D,aAAO,CAAC,IAAI,MAAM,OAAO,MAAM,OAAO,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACzF;AAAA,SACK,mBAAmB;AACtB,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,QAAQ,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC5D,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,gBAAgB,OAAO,OAAO,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,IAAI,CAAC;AAAA,IAC3G;AAAA,SACK,SAAS;AACZ,aAAO,CAAC,IAAI,MAAM,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACvH;AAAA,SACK,aAAa;AAChB,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACrE;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,SAAS,UAAUA,OAAM,WAAW,SAAS;AAC3C,QAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,QAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,QAAM,gBAAgB,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AAC7E,QAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,QAAM,iBAAiB,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC/E,QAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,SAAO;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AACA,IAAI,aAAa,OAAOA,OAAM,WAAW,SAAS,iBAAiB,MAAM,8BAA8B;AACrG,UAAQA,MAAK;AAAA,SACN,uBAAuB;AAC1B,YAAM,EAAE,OAAO,QAAQ,eAAe,cAAc,gBAAgB,aAAa,IAAI,UAAUA,OAAM,WAAW,OAAO;AACvH,YAAM,SAAS,MAAM,IAAI,MAAM,gCAAgC,OAAO,QAAQ,eAAe,cAAc,gBAAgB,YAAY;AACvI,aAAO,CAAC,OAAO,iBAAiB,OAAO,cAAc;AAAA,IACvD;AAAA,SACK,uBAAuB;AAC1B,YAAM,EAAE,OAAO,QAAQ,eAAe,cAAc,eAAe,IAAI,UAAUA,OAAM,WAAW,OAAO;AACzG,YAAM,qBAAqB,cAAc,sBAAsBA,OAAM,WAAW,OAAO;AACvF,YAAM,SAAS,MAAM,IAAI,MAAM,6BAA6B,OAAO,QAAQ,eAAe,cAAc,gBAAgB,kBAAkB;AAC1I,aAAO,CAAC,OAAO,iBAAiB,OAAO,YAAY;AAAA,IACrD;AAAA,SACK;AAAA,SACA,uBAAuB;AAC1B,YAAM,EAAE,OAAO,QAAQ,eAAe,cAAc,eAAe,IAAI,UAAUA,OAAM,WAAW,OAAO;AACzG,aAAO,CAAC,MAAM,IAAI,MAAM,uBAAuB,OAAO,QAAQ,eAAe,cAAc,cAAc,CAAC;AAAA,IAC5G;AAAA,SACK,SAAS;AACZ,YAAM,YAAY,IAAI,KAAK,cAAc,aAAaA,OAAM,WAAW,OAAO,GAAG,MAAM;AACvF,YAAM,SAAS,CAAC,MAAM,IAAI,WAAW,SAAS,CAAC;AAC/C,gBAAU,QAAQ;AAClB,aAAO;AAAA,IACT;AAAA,SACK,YAAY;AACf,aAAO,IAAI,eAAe,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC;AAAA,IACtH;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,aAAa,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC9E,UAAQA,MAAK;AAAA,SACN,cAAc;AACjB,YAAM,iBAAiB,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC/E,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,aAAO,CAAC,IAAI,WAAW,gBAAgB,MAAM,CAAC;AAAA,IAChD;AAAA,SACK,UAAU;AACb,YAAM,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO;AACrD,YAAM,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO;AACrD,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,SAAS,IAAI,KAAK,GAAG,GAAG,MAAM;AACpC,aAAO,CAAC,OAAO,QAAQ,OAAO,OAAO;AAAA,IACvC;AAAA,SACK,cAAc;AACjB,YAAM,iBAAiB,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC/E,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,aAAO,CAAC,IAAI,WAAW,gBAAgB,MAAM,CAAC;AAAA,IAChD;AAAA,SACK,UAAU;AACb,YAAM,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO;AACrD,YAAM,SAAS,IAAI,OAAO,CAAC;AAC3B,aAAO,CAAC,OAAO,QAAQ,OAAO,OAAO;AAAA,IACvC;AAAA,SACK,YAAY;AACf,YAAM,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO;AACrD,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,SAAS,IAAI,OAAO,GAAG,IAAI;AACjC,aAAO,CAAC,OAAO,QAAQ,OAAO,OAAO;AAAA,IACvC;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,aAAa,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC9E,UAAQA,MAAK;AAAA,SACN,SAAS;AACZ,aAAO,UAAUA,MAAK;AAAA,IACxB;AAAA,SACK;AACH,YAAM,MAAM,cAAc,WAAWA,OAAM,WAAW,OAAO;AAC7D,aAAO,CAAC,UAAUA,MAAK,MAAM,WAAW,OAAO,KAAK,GAAG;AAAA,SACpD;AACH,aAAO,CAAC,UAAUA,MAAK,MAAM,WAAW,OAAO,CAAC;AAAA,SAC7C;AAAA,SACA;AAAA,SACA,2BAA2B;AAC9B,YAAM,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO;AACzD,aAAO,CAAC,YAAY,KAAK,CAAC;AAAA,IAC5B;AAAA,SACK;AACH,aAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,EAAE,IAAI,CAAC,OAAO,YAAY,EAAE,CAAC;AAAA,SAC5E;AACH,YAAM,WAAW,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC5D,aAAO,CAAC,YAAY,QAAQ,CAAC;AAAA,SAC1B;AACH,aAAO,CAAC,IAAI,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO,EAAE,OAAO,OAAO,CAAC;AAAA,SAC9E;AACH,aAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,EAAE,IAAI,CAAC,OAAO,IAAI,SAAS,GAAG,KAAK,CAAC;AAAA,SACnF;AACH,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,EAAE,MAAM,OAAO,CAAC;AAAA,SAC3E;AACH,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,EAAE,MAAM,OAAO,CAAC;AAAA,SAC3E;AACH,aAAO,CAAC,IAAI,OAAO,CAAC,CAAC;AAAA,SAClB;AACH,YAAM,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC1D,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,cAAQ,KAAK,gGAAgG;AAC7G,cAAQ,IAAI,OAAO;AACnB,eAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,gBAAQ,IAAI,MAAM,UAAU,MAAM,KAAK,KAAK,IAAI,SAAS,CAAC,EAAE,MAAM,GAAG,SAAS,CAAC;AAAA,MACjF;AACA,aAAO,CAAC,MAAM;AAAA;AAEd,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,YAAY,MAAM;AAAA,EACpB,YAAY,UAAU,YAAY;AAChC,SAAK,WAAW;AAChB,SAAK,aAAa;AAClB,SAAK,SAAS,OAAO,CAAC;AACtB,SAAK,YAA4B,oBAAI,IAAI;AACzC,SAAK,KAAK,MAAM;AAAA,EAClB;AAAA,EACA,IAAI,KAAK;AACP,WAAO,KAAK,OAAO;AAAA,EACrB;AAAA,EACA,gBAAgB;AACd,SAAK,UAAU,QAAQ,CAAC,UAAU,MAAM,QAAQ,CAAC;AACjD,SAAK,UAAU,MAAM;AACrB,SAAK,OAAO,QAAQ;AAAA,EACtB;AAAA,EACA,OAAO;AACL,WAAO,KAAK,UAAU;AAAA,EACxB;AAAA,EACA,aAAa;AACX,WAAO,OAAO,KAAK,KAAK,GAAG,OAAO;AAAA,EACpC;AAAA,EACA,MAAM,OAAO,MAAM,QAAQ;AACzB,SAAK,uBAAuB,MAAM,MAAM;AACxC,UAAM,QAAQ,MAAM,KAAK,KAAK;AAC9B,SAAK,UAAU,QAAQ,CAAC,UAAU,MAAM,QAAQ,CAAC;AACjD,SAAK,UAAU,MAAM;AACrB,WAAO,KAAK,MAAM;AAChB,YAAM,UAAU,QAAQ,MAAM;AAC9B,YAAM,aAAa,MAAM;AACzB,YAAM,eAAe,QAAQ;AAC7B,mBAAa,OAAO,eAAe,cAAc,MAAM,kDAAkD,uCAAuC,wBAAwB;AACxK,eAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,cAAM,MAAM,MAAM;AAClB,cAAM,QAAQ,QAAQ;AACtB,aAAK,KAAK;AACV,aAAK,UAAU,IAAI,KAAK,KAAK;AAAA,MAC/B;AACA,aAAO,KAAK;AAAA,IACd,CAAC;AAAA,EACH;AAAA,EACA,MAAM,KAAK,MAAM,cAAc;AAC7B,SAAK,uBAAuB,MAAM,YAAY;AAC9C,UAAM,QAAQ,MAAM,KAAK,KAAK;AAC9B,WAAO,KAAK,MAAM;AAChB,YAAM,SAAS,CAAC;AAChB,eAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,cAAM,MAAM,MAAM;AAClB,cAAM,QAAQ,KAAK,gBAAgB,KAAK,YAAY;AACpD,eAAO,KAAK,KAAK;AAAA,MACnB;AACA,aAAO,MAAM,MAAM;AAAA,IACrB,CAAC;AAAA,EACH;AAAA,EACA,gBAAgB,KAAK,cAAc;AACjC,UAAM,SAAS,KAAK,UAAU,IAAI,GAAG;AACrC,WAAO,UAAU,OAAO,SAAS;AAAA,EACnC;AAAA,EACA,uBAAuB,KAAK,OAAO;AACjC,QAAI,IAAI,UAAU,KAAK,UAAU;AAC/B,YAAM,IAAI,MAAM,oBAAoB,KAAK,qBAAqB,IAAI,OAAO;AAAA,IAC3E;AACA,QAAI,MAAM,UAAU,KAAK,YAAY;AACnC,YAAM,IAAI,MAAM,sBAAsB,KAAK,uBAAuB,MAAM,OAAO;AAAA,IACjF;AAAA,EACF;AACF;AAGA,IAAI,aAAa,OAAOA,OAAM,WAAW,SAAS,oBAAoB;AACpE,UAAQA,MAAK;AAAA,SACN;AAAA,SACA,eAAe;AAClB,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,YAAM,YAAY,IAAI,UAAU,UAAU,UAAU;AACpD,sBAAgB,aAAaA,MAAK,MAAM,SAAS;AACjD,aAAO,CAAC,UAAU,MAAM;AAAA,IAC1B;AAAA,SACK;AAAA,SACA,uBAAuB;AAC1B,YAAM,SAAS,cAAc,eAAeA,OAAM,WAAW,SAAS,eAAe;AACrF,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,YAAY,gBAAgB,iBAAiB,OAAO,EAAE;AAC5D,aAAO,CAAC,MAAM,UAAU,OAAO,MAAM,MAAM,CAAC;AAAA,IAC9C;AAAA,SACK;AAAA,SACA,qBAAqB;AACxB,YAAM,SAAS,cAAc,eAAeA,OAAM,WAAW,SAAS,eAAe;AACrF,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,YAAY,gBAAgB,iBAAiB,OAAO,EAAE;AAC5D,aAAO,CAAC,MAAM,UAAU,KAAK,MAAM,YAAY,CAAC;AAAA,IAClD;AAAA,SACK;AAAA,SACA,qBAAqB;AACxB,YAAM,SAAS,cAAc,eAAeA,OAAM,WAAW,SAAS,eAAe;AACrF,YAAM,YAAY,gBAAgB,iBAAiB,OAAO,EAAE;AAC5D,aAAO,CAAC,UAAU,WAAW,CAAC;AAAA,IAChC;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN,kBAAkB;AACrB,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAMhB,QAAO,cAAc,QAAQgB,OAAM,WAAW,OAAO;AAC3D,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,mBAAmB,cAAc,oBAAoBA,OAAM,WAAW,OAAO;AACnF,aAAO,CAAC,IAAI,MAAM,eAAe,QAAQ,CAAChB,MAAK,IAAIA,MAAK,EAAE,GAAG,cAAc,gBAAgB,CAAC;AAAA,IAC9F;AAAA,SACK,yBAAyB;AAC5B,YAAM,SAAS,cAAc,UAAUgB,OAAM,WAAW,OAAO;AAC/D,YAAMhB,QAAO,cAAc,QAAQgB,OAAM,WAAW,OAAO;AAC3D,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,mBAAmB,cAAc,oBAAoBA,OAAM,WAAW,OAAO;AACnF,aAAO,CAAC,IAAI,MAAM,sBAAsB,QAAQ,CAAChB,MAAK,IAAIA,MAAK,EAAE,GAAG,cAAc,gBAAgB,CAAC;AAAA,IACrG;AAAA,SACK,iBAAiB;AACpB,YAAM,SAAS,cAAc,SAASgB,OAAM,WAAW,OAAO;AAC9D,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,qBAAqB,cAAc,sBAAsBA,OAAM,WAAW,OAAO;AACvF,aAAO,CAAC,IAAI,MAAM,cAAc,QAAQ,OAAO,QAAQ,UAAU,QAAQ,kBAAkB,CAAC;AAAA,IAC9F;AAAA,SACK,8BAA8B;AACjC,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,YAAM,cAAc,cAAc,eAAeA,OAAM,WAAW,OAAO;AACzE,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,gBAAgB,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AAC7E,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,MAAM,UAAU,QAAQ,YAAY,cAAc,YAAY,GAAG,SAAS,YAAY,GAAG,WAAW,WAAW,CAAC;AAAA,IAC9H;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN,SAAS;AACZ,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC/G;AAAA,SACK,YAAY;AACf,aAAO,CAAC,IAAI,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAClH;AAAA,SACK,WAAW;AACd,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACjH;AAAA,SACK,gBAAgB;AACnB,aAAO,CAAC,IAAI,aAAa,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACtH;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC9G;AAAA,SACK,aAAa;AAChB,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACnH;AAAA,SACK,cAAc;AACjB,aAAO,CAAC,IAAI,WAAW,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACpH;AAAA,SACK,cAAc;AACjB,aAAO,CAAC,IAAI,WAAW,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACtE;AAAA,SACK,aAAa;AAChB,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACnH;AAAA,SACK;AAAA,SACA,YAAY;AACf,aAAO,CAAC,IAAI,MAAM,cAAc,aAAaA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACrK;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN;AAAA,SACA;AAAA,SACA;AACH,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SACzN;AACH,aAAO,CAAC,IAAI,OAAO,cAAc,YAAYA,OAAM,WAAW,OAAO,GAAG,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3H;AACH,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SACjH;AACH,YAAM,CAAC,SAAS,cAAc,IAAI,cAAc,YAAYA,OAAM,WAAW,OAAO;AACpF,YAAM,YAAY,YAAY;AAC9B,YAAM,UAAU,mBAAmB;AACnC,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,iBAAiB,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC/E,UAAI,WAAW;AACb,YAAI,WAAW,YAAY,GAAG;AAC5B,gBAAM,IAAI,MAAM,oFAAoF;AAAA,QACtG;AACA,YAAI,CAAC,WAAW,YAAY,GAAG;AAC7B,gBAAM,IAAI,MAAM,+DAA+D;AAAA,QACjF;AAAA,MACF;AACA,YAAM,CAAC,SAAS,QAAQ,IAAI,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC1E,aAAO,CAAC,IAAI,MAAM,OAAO;AAAA,QACvB,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO;AAAA,QAC9C,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO;AAAA,QAC9C,YAAY,cAAc,cAAcA,OAAM,WAAW,OAAO;AAAA,QAChE,YAAY,cAAc,cAAcA,OAAM,WAAW,OAAO;AAAA,QAChE,MAAM;AAAA,QACN,YAAY;AAAA,QACZ,wBAAwB;AAAA,QACxB;AAAA,MACF,CAAC,CAAC;AAAA;AAEF,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN;AACH,aAAO,CAAC,IAAI,cAAc,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,YAAYA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1K;AAAA,SACA,oBAAoB;AACvB,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,YAAYA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACpU;AAAA,SACK,oBAAoB;AACvB,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,YAAYA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACpU;AAAA,SACK,OAAO;AACV,aAAO,CAAC,IAAI,2BAA2B,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC7R;AAAA,SACK,WAAW;AACd,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACnE;AAAA,SACK,cAAc;AACjB,aAAO,CAAC,IAAI,WAAW,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACtE;AAAA,SACK,iBAAiB;AACpB,aAAO,CAAC,IAAI,cAAc,cAAc,iBAAiBA,OAAM,WAAW,OAAO,GAAG,cAAc,eAAeA,OAAM,WAAW,OAAO,GAAG,cAAc,gBAAgBA,OAAM,WAAW,OAAO,GAAG,cAAc,gBAAgBA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC/P;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN,OAAO;AACV,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,QAAQ,CAAC;AAAA,IAC/E;AAAA,SACK,QAAQ;AACX,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,QAAQ,CAAC;AAAA,IAChF;AAAA,SACK,OAAO;AACV,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,QAAQ,CAAC;AAAA,IAC/E;AAAA,SACK,OAAO;AACV,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,QAAQ,CAAC;AAAA,IAC/E;AAAA,SACK,OAAO;AACV,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,QAAQ,CAAC;AAAA,IAC/E;AAAA,SACK,OAAO;AACV,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,QAAQ,CAAC;AAAA,IAC/E;AAAA,SACK,UAAU;AACb,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,IAAI,CAAC;AAAA,IACxE;AAAA,SACK,UAAU;AACb,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,IAAI,CAAC;AAAA,IACxE;AAAA,SACK,QAAQ;AACX,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,QAAQ,CAAC;AAAA,IAChF;AAAA,SACK,WAAW;AACd,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,WAAW,cAAc,WAAWA,OAAM,WAAW,OAAO;AAClE,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,WAAW,QAAQ,CAAC;AAAA,IAC9F;AAAA,SACK,UAAU;AACb,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,WAAW,cAAc,WAAWA,OAAM,WAAW,OAAO;AAClE,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,WAAW,QAAQ,CAAC;AAAA,IAC7F;AAAA,SACK;AACH,YAAM,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO;AACrD,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAMhB,QAAO,cAAc,QAAQgB,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,SAAS,GAAG,SAAShB,KAAI,CAAC;AAAA,SACnC,iBAAiB;AACpB,YAAM,KAAK,cAAc,KAAKgB,OAAM,WAAW,OAAO;AACtD,YAAM,WAAW,cAAc,WAAWA,OAAM,WAAW,OAAO;AAClE,YAAME,SAAQ,cAAc,QAAQF,OAAM,WAAW,OAAO;AAC5D,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,aAAO,CAAC,IAAI,cAAc,IAAI,UAAUE,QAAO,YAAY,CAAC;AAAA,IAC9D;AAAA;AAEE,YAAM,UAAU,aAAaF,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN;AAAA,SACA,UAAU;AACb,YAAM,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO;AACtD,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,UAAI,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAC9D,eAAS,OAAO,MAAM,GAAG,EAAE;AAC3B,aAAO,CAAC,IAAI,OAAO,QAAQ,IAAI,CAAC;AAAA,IAClC;AAAA,SACK,UAAU;AACb,YAAM,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC1D,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,aAAO,CAAC,IAAI,OAAO,QAAQ,IAAI,KAAK,SAAS,OAAO,GAAG,CAAC,CAAC;AAAA,IAC3D;AAAA,SACK,YAAY;AACf,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC1D,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,aAAO,CAAC,IAAI,OAAO,QAAQ,IAAI,KAAK,SAAS,OAAO,GAAG,MAAM,SAAS,CAAC;AAAA,IACzE;AAAA,SACK,WAAW;AACd,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,OAAO,CAAC;AACd,eAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,YAAI,KAAK,KAAK;AACZ,eAAK,KAAK,EAAE;AAAA,QACd;AAAA,MACF;AACA,YAAM,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC1D,aAAO,CAAC,IAAI,QAAQ,QAAQ,IAAI,CAAC;AAAA,IACnC;AAAA,SACK,aAAa;AAChB,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC1D,aAAO,CAAC,IAAI,QAAQ,QAAQ,IAAI,CAAC;AAAA,IACnC;AAAA,SACK,SAAS;AACZ,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAMhB,QAAO,cAAc,QAAQgB,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,OAAOhB,KAAI,CAAC;AAAA,IAC9E;AAAA,SACK,gBAAgB;AACnB,YAAM,QAAQ,cAAc,SAASgB,OAAM,WAAW,OAAO;AAC7D,YAAM,MAAM,cAAc,OAAOA,OAAM,WAAW,OAAO;AACzD,YAAMJ,WAAU,cAAc,WAAWI,OAAM,WAAW,OAAO;AACjE,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,cAAc,cAAc,eAAeA,OAAM,WAAW,OAAO;AACzE,YAAM,iBAAiB,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC/E,YAAM,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,aAAa,SAAS,OAAO,KAAKJ,UAAS,WAAW,SAAS,cAAc,aAAa,cAAc,CAAC;AAAA,IACvH;AAAA,SACK,QAAQ;AACX,aAAO,KAAK,MAAM;AAChB,cAAM,OAAO,cAAc,QAAQI,OAAM,WAAW,OAAO;AAC3D,cAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,cAAM,QAAQ,QAAQ,GAAG;AACzB,cAAM,gBAAgB,IAAI,QAAQ,QAAQ,EAAE,EAAE;AAC9C,cAAM,SAAS,QAAQ,IAAI,CAAC,YAAY;AACtC,gBAAM,YAAY,aAAa,YAAY,QAAQ,OAAO,KAAK;AAC/D,cAAI,CAAC,aAAa,CAAC,aAAa,YAAY,IAAI,QAAQ,OAAO,EAAE,OAAO,aAAa,GAAG;AACtF,kBAAM,IAAI,MAAM,wCAAwC;AAAA,UAC1D;AACA,iBAAO,YAAY,UAAU,IAAI,QAAQ,SAAS,KAAK;AAAA,QACzD,CAAC;AACD,eAAO,CAAC,IAAI,MAAM,QAAQ,IAAI,CAAC;AAAA,MACjC,CAAC;AAAA,IACH;AAAA,SACK,UAAU;AACb,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,UAAU,cAAc,UAAUA,OAAM,WAAW,OAAO;AAChE,aAAO,IAAI,QAAQ,SAAS,IAAI;AAAA,IAClC;AAAA,SACK,QAAQ;AACX,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,IAAI,CAAC;AAAA,IACtE;AAAA,SACK;AAAA,SACA,UAAU;AACb,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,kBAAkB,cAAc,mBAAmBA,OAAM,WAAW,OAAO;AACjF,YAAM,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC3D,aAAO,IAAI,MAAM,SAAS,iBAAiB,IAAI;AAAA,IACjD;AAAA,SACK,aAAa;AAChB,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,aAAO,CAAC,IAAI,UAAU,SAAS,QAAQ,KAAK,CAAC;AAAA,IAC/C;AAAA,SACK,YAAY;AACf,YAAM,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO;AACrD,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,aAAO,CAAC,IAAI,SAAS,GAAG,OAAO,CAAC;AAAA,IAClC;AAAA,SACK,iBAAiB;AACpB,YAAM,UAAU,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AACvE,YAAM,QAAQ,cAAc,eAAeA,OAAM,WAAW,OAAO;AACnE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,aAAO,CAAC,IAAI,cAAc,SAAS,cAAc,OAAO,aAAa,UAAU,aAAa,QAAQ,eAAe,IAAI,KAAK,cAAc,aAAa,KAAK,CAAC,CAAC;AAAA,IAChK;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN,uBAAuB;AAC1B,YAAM,EAAE,eAAe,cAAc,mBAAmB,gBAAgB,IAAI,IAAI,OAAO,oBAAoB,cAAc,WAAWA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,GAAG,cAAc,gBAAgBA,OAAM,WAAW,OAAO,CAAC;AAChU,aAAO;AAAA,QACL;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,MACF;AAAA,IACF;AAAA,SACK,iBAAiB;AACpB,YAAM,EAAE,eAAe,YAAY,IAAI,IAAI,OAAO,cAAc,cAAc,gBAAgBA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,GAAG,cAAc,YAAYA,OAAM,WAAW,OAAO,CAAC;AACnO,aAAO,CAAC,eAAe,WAAW;AAAA,IACpC;AAAA,SACK,qBAAqB;AACxB,YAAM,aAAa,IAAI,OAAO,kBAAkB,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,CAAC;AAC1M,aAAO,CAAC,UAAU;AAAA,IACpB;AAAA,SACK,oBAAoB;AACvB,YAAM,aAAa,IAAI,OAAO,iBAAiB,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,CAAC;AACzM,aAAO,CAAC,UAAU;AAAA,IACpB;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN,OAAO;AACV,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC/D;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAChE;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAChE;AAAA,SACK,SAAS;AACZ,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACjE;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN,gBAAgB;AACnB,YAAM,EAAE,QAAQ,aAAa,IAAI,IAAI,OAAO,aAAa,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,GAAG,cAAc,aAAaA,OAAM,WAAW,OAAO,GAAG,cAAc,eAAeA,OAAM,WAAW,OAAO,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,GAAG,cAAc,YAAYA,OAAM,WAAW,OAAO,GAAG,cAAc,YAAYA,OAAM,WAAW,OAAO,GAAG,cAAc,0BAA0BA,OAAM,WAAW,OAAO,CAAC;AAC9e,aAAO,CAAC,QAAQ,YAAY;AAAA,IAC9B;AAAA,SACK,eAAe;AAClB,YAAM,EAAE,SAAS,QAAQ,MAAM,IAAI,IAAI,OAAO,YAAY,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,aAAaA,OAAM,WAAW,OAAO,GAAG,cAAc,aAAaA,OAAM,WAAW,OAAO,CAAC;AACtN,aAAO,CAAC,SAAS,QAAQ,KAAK;AAAA,IAChC;AAAA,SACK,0BAA0B;AAC7B,YAAM,SAAS,IAAI,OAAO,uBAAuB,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,CAAC;AACxJ,aAAO,CAAC,MAAM;AAAA,IAChB;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAClH;AAAA,SACK,cAAc;AACjB,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,WAAW,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,IAAI,CAAC;AAAA,IAC5E;AAAA,SACK,WAAW;AACd,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,IAAI,CAAC;AAAA,IACzE;AAAA,SACK,WAAW;AACd,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACrH;AAAA,SACK,aAAa;AAChB,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC1K;AAAA,SACK;AAAA,SACA,OAAO;AACV,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,GAAG,cAAc,iBAAiBA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC7K;AAAA,SACK,kBAAkB;AACrB,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,eAAe,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,YAAY,QAAQ,CAAC;AAAA,IAChG;AAAA,SACK,kBAAkB;AACrB,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,aAAO,CAAC,IAAI,eAAe,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,YAAY,KAAK,CAAC;AAAA,IAC7F;AAAA,SACK,gBAAgB;AACnB,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO,EAAE,YAAY;AACrF,aAAO,CAAC,IAAI,aAAa,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,WAAW,UAAU,CAAC;AAAA,IAC/F;AAAA,SACK,eAAe;AAClB,aAAO,CAAC,IAAI,YAAY,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACzH;AAAA,SACK,iBAAiB;AACpB,aAAO,CAAC,IAAI,cAAc,cAAc,MAAMA,OAAM,WAAW,OAAO,GAAG,cAAc,MAAMA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACzH;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,SAAS,YAAYA,OAAM,WAAW,SAAS,iBAAiB,QAAQ,MAAM;AAC5E,QAAM,SAAS,CAACgB,QAAO,YAAY,aAAa;AAC9C,YAAQA,OAAM;AAAA,WACP;AACH,eAAO,MAAM,MAAM,UAAUA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACtD;AACH,eAAO,MAAM,MAAM,WAAWA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACvD;AACH,eAAO,WAAWA,QAAO,YAAY,QAAQ;AAAA,WAC1C;AACH,eAAO,MAAM,MAAM,WAAWA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACvD;AACH,eAAO,MAAM,MAAM,WAAWA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACvD;AACH,eAAO,WAAWA,QAAO,YAAY,QAAQ;AAAA,WAC1C;AACH,eAAO,MAAM,MAAM,WAAWA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACvD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,WAAWA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACvD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,WAAWA,QAAO,YAAY,UAAU,eAAe;AAAA,WAC3D;AACH,cAAM,WAAW,gBAAgBA,OAAM,EAAE;AACzC,YAAI,YAAY,SAAS,gBAAgB;AACvC,iBAAO,SAAS,eAAe,IAAI,cAAcA,QAAO,YAAY,QAAQ,CAAC;AAAA,QAC/E,OAAO;AACL,gBAAM,UAAU,aAAaA,OAAM,uBAAuB;AAAA,QAC5D;AAAA;AAEA,cAAM,UAAU,eAAeA,OAAM,uIAAuI;AAAA;AAAA,EAElL,GAAGhB,OAAM,WAAW,OAAO;AAC3B,MAAI,aAAa,UAAU,KAAK,GAAG;AACjC,WAAO,MAAM,KAAK,CAAC,SAAS,CAAC,EAAE,OAAO,IAAI,CAAC;AAAA,EAC7C;AACA,SAAO,CAAC,EAAE,OAAO,KAAK;AACxB;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,YAAY,CAAC,GAAG,iBAAiB,CAAC,GAAG,gBAAgB,CAAC,GAAG,cAAc,CAAC,GAAG;AACrF,SAAK,YAAY;AACjB,SAAK,iBAAiB;AACtB,SAAK,gBAAgB;AACrB,SAAK,cAAc;AACnB,SAAK,cAAc,EAAE,IAAI,GAAG,WAAW,IAAI,aAAa,EAAE;AAC1D,SAAK,WAAW,CAAC,KAAK,WAAW;AACjC,SAAK,SAAS;AACd,SAAK,0BAA0B;AAAA,EACjC;AAAA,EACA,SAAS,IAAI,WAAW;AACtB,WAAO,EAAE,IAAI,WAAW,aAAa,EAAE;AAAA,EACzC;AAAA,EACA,IAAI,eAAe,WAAW;AAC5B,QAAI,KAAK,aAAa,WAAW;AAC/B,WAAK,WAAW;AAChB,WAAK,0BAA0B;AAAA,IACjC;AAAA,EACF;AAAA,EACA,IAAI,iBAAiB;AACnB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,mBAAmB;AACrB,WAAO,KAAK,mBAAmB;AAAA,EACjC;AAAA,EACA,IAAI,oBAAoB;AACtB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,4BAA4B;AAC1B,UAAM,QAAQ,CAAC;AACf,aAAS,KAAK,GAAG,KAAK,KAAK,SAAS,SAAS,GAAG,MAAM;AACpD,YAAM,YAAY,KAAK,SAAS,MAAM,GAAG,KAAK,SAAS,SAAS,EAAE;AAClE,YAAM,KAAK,KAAK,qBAAqB,SAAS,CAAC;AAAA,IACjD;AACA,UAAM,KAAK,EAAE;AACb,SAAK,qBAAqB;AAAA,EAC5B;AAAA,EACA,qBAAqB,WAAW;AAC9B,WAAO,YAAY,UAAU,IAAI,CAAC,YAAY,QAAQ,OAAO,KAAK,QAAQ,gBAAgB,IAAI,KAAK,GAAG,QAAQ,aAAa,QAAQ,aAAa,EAAE,KAAK,GAAG,IAAI;AAAA,EAChK;AAAA,EACA,WAAW,SAAS;AAClB,QAAI,KAAK,UAAU;AACjB,WAAK;AACL,WAAK,WAAW,KAAK,SAAS,MAAM;AACpC,WAAK,SAAS,KAAK,KAAK,SAAS,KAAK,QAAQ,OAAO,CAAC;AACtD,WAAK,mBAAmB,QAAQ,KAAK,qBAAqB,KAAK,QAAQ,CAAC;AAAA,IAC1E;AAAA,EACF;AAAA,EACA,YAAY;AACV,QAAI,KAAK,YAAY,KAAK,SAAS,SAAS,GAAG;AAC7C,WAAK,WAAW,KAAK,SAAS,MAAM;AACpC,WAAK,SAAS,OAAO,EAAE;AACvB,WAAK,kBAAkB,MAAM;AAAA,IAC/B,OAAO;AACL,YAAM,IAAI,MAAM,yCAAyC;AAAA,IAC3D;AAAA,EACF;AAAA,EACA,gBAAgB;AACd,QAAI,KAAK,YAAY,KAAK,SAAS,SAAS,GAAG;AAC7C,WAAK,WAAW,KAAK,SAAS,MAAM;AACpC,WAAK;AACL,YAAM,UAAU,OAAO,OAAO,CAAC,GAAG,KAAK,SAAS,KAAK,SAAS,SAAS,EAAE;AACzE,cAAQ,eAAe;AACvB,cAAQ,KAAK,KAAK;AAClB,WAAK,SAAS,OAAO,IAAI,GAAG,OAAO;AACnC,WAAK,mBAAmB,OAAO,GAAG,GAAG,KAAK,qBAAqB,KAAK,QAAQ,CAAC;AAAA,IAC/E,OAAO;AACL,YAAM,IAAI,MAAM,uDAAuD;AAAA,IACzE;AAAA,EACF;AAAA,EACA,UAAU,MAAM;AACd,WAAO,KAAK,UAAU;AAAA,EACxB;AAAA,EACA,eAAe,aAAa;AAC1B,SAAK,eAAe,YAAY,MAAM;AAAA,EACxC;AAAA,EACA,eAAe,IAAI;AACjB,WAAO,KAAK,eAAe;AAAA,EAC7B;AAAA,EACA,cAAc,YAAY;AACxB,SAAK,cAAc,WAAW,MAAM;AAAA,EACtC;AAAA,EACA,cAAc,IAAI;AAChB,WAAO,KAAK,cAAc;AAAA,EAC5B;AAAA,EACA,QAAQ,SAAS;AACf,eAAW,OAAO,KAAK,gBAAgB;AACrC,WAAK,eAAe,KAAK,cAAc,OAAO;AAAA,IAChD;AACA,eAAW,OAAO,KAAK,eAAe;AACpC,WAAK,cAAc,KAAK,cAAc,OAAO;AAAA,IAC/C;AAAA,EACF;AACF;AAGA,SAAS,qBAAqB,QAAQ,SAAS,WAAW,WAAW;AACnE,QAAM,YAA4B,oBAAI,IAAI;AAC1C,QAAM,gBAAgB,CAAC;AACvB,MAAI,cAAc;AAClB,MAAI,aAAa;AACjB,QAAM,OAAuB,oBAAI,IAAI;AACrC,QAAM,iBAAiB,OAAO,KAAK,MAAM,EAAE,IAAI,CAAC,SAAS,cAAc,IAAI,EAAE,EAAE;AAC/E,MAAI,gBAAgB,CAAC;AACrB,MAAI,aAAa,MAAM;AACrB,oBAAgB,UAAU,IAAI,CAACA,UAAS,cAAcA,MAAK,IAAI,EAAE,EAAE;AAAA,EACrE;AACA,QAAM,WAAW,CAAC,GAAG,OAAO;AAC5B,SAAO,SAAS,SAAS,GAAG;AAC1B,UAAMA,QAAO,SAAS,IAAI;AAC1B,QAAI,cAAcA,KAAI,KAAK,eAAeA,KAAI,KAAK,YAAYA,KAAI,GAAG;AACpE,UAAI,eAAe,MAAM;AACvB,sBAAcA;AACd,qBAAa,YAAY,SAAS,IAAI,CAAC,UAAU,MAAM,IAAI,EAAE,OAAO,CAAC,SAAS,UAAU,IAAI,IAAI,CAAC;AAAA,MACnG;AAAA,IACF;AACA,cAAU,IAAIA,MAAK,IAAI;AACvB,QAAI,UAAUA,MAAK,SAAS,MAAM;AAChC;AAAA,IACF;AACA,QAAI,eAAe,QAAQA,MAAK,IAAI,MAAM,IAAI;AAC5C;AAAA,IACF;AACA,QAAI,cAAc,QAAQA,MAAK,IAAI,MAAM,IAAI;AAC3C;AAAA,IACF;AACA,QAAIA,MAAK,OAAO,WAAW,GAAG;AAC5B,oBAAc,KAAKA,MAAK,IAAI;AAC5B;AAAA,IACF;AACA,IAAAA,MAAK,OAAO,QAAQ,CAAC,WAAW;AAC9B,UAAI,KAAK,IAAI,OAAO,IAAI,GAAG;AACzB;AAAA,MACF;AACA,WAAK,IAAI,OAAO,IAAI;AACpB,eAAS,KAAK,MAAM;AAAA,IACtB,CAAC;AAAA,EACH;AACA,SAAO,EAAE,QAAQ,SAAS,WAAW,eAAe,aAAa,WAAW;AAC9E;AACA,SAAS,2BAA2B,OAAO,WAAW,eAAe;AACnE,QAAM,EAAE,WAAW,OAAO,IAAI;AAC9B,QAAM,WAAW,CAAC;AAClB,QAAM,aAAa,OAAO,KAAK,MAAM,EAAE,IAAI,CAAC,SAAS,cAAc,IAAI,EAAE,EAAE,EAAE,IAAI,CAAC,SAAS,MAAM,MAAM,KAAK;AAC5G,QAAM,YAAY,MAAM;AACxB,aAAW,QAAQ,CAAC,WAAW;AAC7B,QAAI,UAAU,IAAI,OAAO,IAAI,GAAG;AAC9B,eAAS,KAAK,MAAM;AAAA,IACtB;AAAA,EACF,CAAC;AACD,QAAM,QAAQ,QAAQ,CAAC,WAAW;AAChC,QAAI,UAAU,IAAI,OAAO,IAAI,GAAG;AAC9B,eAAS,KAAK,MAAM;AAAA,IACtB;AAAA,EACF,CAAC;AACD,MAAI,aAAa,MAAM;AACrB,cAAU,QAAQ,CAACA,UAAS;AAC1B,UAAI,UAAU,IAAIA,MAAK,IAAI,GAAG;AAC5B,iBAAS,KAAKA,KAAI;AAAA,MACpB;AAAA,IACF,CAAC;AAAA,EACH;AACA,QAAM,OAAuB,oBAAI,IAAI;AACrC,QAAM,eAAe,CAAC;AACtB,SAAO,SAAS,SAAS,GAAG;AAC1B,UAAMA,QAAO,SAAS,IAAI;AAC1B,SAAK,IAAIA,MAAK,IAAI;AAClB,QAAI,CAAC,UAAUA,MAAK,OAAO;AACzB,mBAAa,KAAKA,KAAI;AAAA,IACxB;AACA,IAAAA,MAAK,SAAS,QAAQ,CAAC,UAAU;AAC/B,UAAI,CAAC,KAAK,IAAI,MAAM,IAAI,KAAK,UAAU,IAAI,MAAM,IAAI,KAAK,MAAM,OAAO,MAAM,CAAC,WAAW,KAAK,IAAI,OAAO,IAAI,CAAC,GAAG;AAC/G,iBAAS,KAAK,KAAK;AAAA,MACrB;AAAA,IACF,CAAC;AAAA,EACH;AACA,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,IAAI,oBAAoB;AAAA,EACtB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,IAAI,iBAAiB;AAAA,EACnB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,SAAS,cAAcA,OAAM;AAC3B,SAAO,iBAAiB,QAAQA,MAAK,EAAE,KAAK;AAC9C;AACA,SAAS,eAAeA,OAAM;AAC5B,SAAO,kBAAkB,QAAQA,MAAK,EAAE,KAAK;AAC/C;AACA,SAAS,YAAYA,OAAM;AACzB,SAAO,eAAe,QAAQA,MAAK,EAAE,KAAK;AAC5C;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,OAAO,QAAQ;AACzB,SAAK,QAAQ;AACb,SAAK,SAAS;AACd,SAAK,cAA8B,oBAAI,IAAI;AAC3C,SAAK,aAAa,CAAC;AACnB,SAAK,YAAY;AACjB,SAAK,aAAa,CAAC;AACnB,SAAK,uBAAuB,CAAC;AAC7B,SAAK,sBAAsB,CAAC;AAC5B,SAAK,qBAAqB;AAC1B,SAAK,WAAW,MAAM;AACtB,SAAK,UAAU,MAAM;AACrB,SAAK,aAAa,MAAM;AACxB,SAAK,aAAa,MAAM;AACxB,SAAK,aAAa,MAAM;AACxB,QAAI,MAAM,aAAa,MAAM;AAC3B,aAAO,KAAK,MAAM,SAAS,EAAE,QAAQ,CAAC,SAAS;AAC7C,aAAK,qBAAqB,QAAQ,IAAI,cAAc,MAAM,UAAU,OAAO,IAAI;AAAA,MACjF,CAAC;AAAA,IACH;AAAA,EACF;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK,SAAS,KAAK,OAAO,YAAY,KAAK;AAAA,EACpD;AAAA,EACA,IAAI,sBAAsB;AACxB,WAAO,KAAK,SAAS,KAAK,OAAO,sBAAsB,KAAK;AAAA,EAC9D;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK,SAAS,KAAK,OAAO,YAAY,KAAK;AAAA,EACpD;AAAA,EACA,IAAI,UAAU,WAAW;AACvB,UAAM,YAAY,OAAO,KAAK,SAAS,EAAE,IAAI,CAAC,QAAQ,UAAU,KAAK,IAAI,CAAC,YAAY,QAAQ,EAAE,CAAC;AACjG,SAAK,aAAa,CAAC,EAAE,OAAO,GAAG,SAAS;AACxC,SAAK,aAAa;AAAA,EACpB;AAAA,EACA,IAAI,gBAAgB,iBAAiB;AACnC,SAAK,mBAAmB;AAAA,EAC1B;AAAA,EACA,IAAI,SAAS;AACX,WAAO,KAAK,QAAQ,IAAI,CAACA,UAAS;AAChC,aAAO;AAAA,QACL,MAAMA,MAAK;AAAA,QACX,OAAOA,MAAK,WAAW,WAAWA,MAAK,WAAW,SAAS,QAAQ;AAAA,QACnE,OAAOA,MAAK,WAAW,WAAWA,MAAK,WAAW,SAAS,QAAQ;AAAA,MACrE;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,IAAI,UAAU;AACZ,WAAO,KAAK,SAAS,IAAI,CAACA,UAAS;AACjC,aAAO;AAAA,QACL,MAAMA,MAAK;AAAA,QACX,OAAOA,MAAK,WAAW,WAAWA,MAAK,WAAW,SAAS,QAAQ;AAAA,QACnE,OAAOA,MAAK,WAAW,WAAWA,MAAK,WAAW,SAAS,QAAQ;AAAA,MACrE;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,IAAI,aAAa;AACf,WAAO,KAAK,QAAQ,IAAI,CAACA,UAASA,MAAK,gBAAgBA,MAAK,IAAI;AAAA,EAClE;AAAA,EACA,IAAI,cAAc;AAChB,WAAO,KAAK,SAAS,IAAI,CAACA,UAAS;AACjC,YAAM,OAAOA,MAAK,gBAAgBA,MAAK;AACvC,aAAOA,MAAK,gBAAgB,GAAG,QAAQA,MAAK,kBAAkB;AAAA,IAChE,CAAC;AAAA,EACH;AAAA,EACA,IAAI,YAAY;AACd,WAAO,OAAO,KAAK,KAAK,UAAU,EAAE,OAAO,CAAC,KAAK,QAAQ;AACvD,UAAI,OAAO,KAAK,WAAW,KAAK;AAChC,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AAAA,EACP;AAAA,EACA,kBAAkB,QAAQ,SAAS;AACjC,UAAM,eAAe,OAAO,IAAI,CAACA,UAASA,MAAK,IAAI,EAAE,KAAK;AAC1D,UAAM,gBAAgB,QAAQ,IAAI,CAACA,UAASA,MAAK,IAAI,EAAE,KAAK;AAC5D,WAAO,aAAa,KAAK,KAAK,SAAS,IAAI,OAAO,cAAc,KAAK,KAAK,SAAS;AAAA,EACrF;AAAA,EACA,QAAQ,QAAQ,SAAS;AACvB,UAAM,gBAAgB,qBAAqB,QAAQ,SAAS,KAAK,WAAW,KAAK,UAAU;AAC3F,UAAM,EAAE,eAAe,aAAa,WAAW,IAAI;AACnD,QAAI,eAAe,MAAM;AACvB,YAAM,IAAI,MAAM,qCAAqC,YAAY,oCAAoC,YAAY,8GAA8G,aAAa;AAAA,IAC9O;AACA,QAAI,cAAc,SAAS,GAAG;AAC5B,YAAM,WAAW,QAAQ,IAAI,CAAC,OAAO,GAAG,IAAI;AAC5C,YAAM,UAAU,OAAO,KAAK,MAAM;AAClC,YAAM,IAAI,MAAM,+BAA+B,uCAAuC,4CAA4C,gBAAgB;AAAA,IACpJ;AACA,WAAO,2BAA2B,KAAK,OAAO,KAAK,WAAW,aAAa;AAAA,EAC7E;AAAA,EACA,QAAQ,QAAQ,SAAS;AACvB,aAAS,KAAK,UAAU,MAAM;AAC9B,UAAM,QAAQ,OAAO,KAAK,MAAM,EAAE,KAAK;AACvC,SAAK,YAAY,MAAM;AACvB,SAAK,uBAAuB,MAAM;AAClC,cAAU,KAAK,WAAW,OAAO;AACjC,SAAK,aAAa,OAAO;AACzB,UAAM,aAAa,MAAM,IAAI,CAAC,SAAS,KAAK,MAAM,MAAM,cAAc,IAAI,EAAE,GAAG;AAC/E,UAAM,kBAAkB,QAAQ,IAAI,CAAC,SAAS,cAAc,IAAI,EAAE,EAAE;AACpE,QAAIiB,eAAc,gBAAgB,IAAI,CAAC,SAAS,KAAK,MAAM,MAAM,KAAK;AACtE,SAAK,yBAAyB;AAC9B,QAAIA,aAAY,WAAW,GAAG;AAC5B,MAAAA,eAAc,KAAK;AAAA,IACrB;AACA,UAAM,iBAAiB,KAAK,kBAAkB,YAAYA,YAAW;AACrE,QAAI,eAAe,KAAK,YAAY,IAAI,cAAc;AACtD,QAAI,gBAAgB,MAAM;AACxB,qBAAe,KAAK,QAAQ,QAAQA,YAAW;AAC/C,WAAK,YAAY,IAAI,gBAAgB,YAAY;AAAA,IACnD;AACA,UAAM,iBAAiB,CAAC;AACxB,UAAM,gBAAgB,CAAC;AACvB,WAAO,KAAK,MAAM;AAChB,YAAM,UAAU,IAAI,iBAAiB,KAAK,WAAW,gBAAgB,eAAe,KAAK,mBAAmB;AAC5G,YAAM,aAAa,OAAO,OAAO,CAAC,GAAG,KAAK,SAAS;AACnD,aAAO,KAAK,MAAM,EAAE,QAAQ,CAAC,SAAS;AACpC,cAAM,CAAC,UAAUxB,MAAK,IAAI,cAAc,IAAI;AAC5C,cAAM,UAAU,CAAC;AACjB,gBAAQA,UAAS,OAAO;AACxB,mBAAW,YAAY;AAAA,MACzB,CAAC;AACD,YAAM,gBAAgB,KAAK,mBAAmB,UAAU;AACxD,YAAM,kCAAkC,CAAC;AACzC,eAAS,KAAK,GAAG,KAAK,aAAa,QAAQ,MAAM;AAC/C,cAAMO,QAAO,aAAa;AAC1B,YAAI,CAAC,WAAWA,MAAK,OAAO;AAC1B,gBAAM,UAAU,YAAYA,OAAM,YAAY,SAAS,KAAK,gBAAgB;AAC5E,cAAI,aAAa,UAAU,OAAO,GAAG;AACnC,kBAAM,IAAI,MAAM,4BAA4BA,MAAK,kEAAkE;AAAA,UACrH;AACA,qBAAWA,MAAK,QAAQ;AACxB,eAAK,uBAAuBA,MAAK,MAAMA,OAAM,YAAY,SAAS,eAAe,iBAAiB,+BAA+B;AAAA,QACnI;AAAA,MACF;AACA,UAAI,KAAK,UAAU,MAAM;AACvB,gBAAQ,QAAQ,aAAa;AAAA,MAC/B;AACA,aAAO,QAAQ,IAAI,CAAC,SAAS,UAAU,MAAM,YAAY,OAAO,CAAC;AAAA,IACnE,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,WAAW;AAC5B,UAAM,MAAM,CAAC,EAAE,OAAO,MAAM,CAAC,GAAG,OAAO,KAAK,SAAS,EAAE,IAAI,CAAC,QAAQ,UAAU,IAAI,EAAE,IAAI,CAAC,YAAY,QAAQ,IAAI,CAAC,YAAY,QAAQ,EAAE,CAAC,CAAC;AAC1I,WAAO,IAAI,IAAI,GAAG;AAAA,EACpB;AAAA,EACA,uBAAuB,UAAUA,OAAM,WAAW,SAAS,eAAe,aAAa,iCAAiC;AACtH,QAAIA,MAAK,aAAa,aAAa,YAAY,QAAQ,QAAQ,MAAM,IAAI;AACvE;AAAA,IACF;AACA,cAAU,UAAU,QAAQ,CAAC,YAAY;AACvC,UAAI,WAAW,MAAM;AACnB,wCAAgC,QAAQ,OAAO,gCAAgC,QAAQ,OAAO,KAAKA,MAAK,SAAS;AAAA,MACnH;AAAA,IACF,CAAC;AACD,IAAAA,MAAK,OAAO,QAAQ,CAAC,WAAW;AAC9B,UAAI,OAAO,aAAa,WAAW;AACjC,cAAM,UAAU,6BAA6B,OAAO,MAAM,WAAW,OAAO;AAC5E,YAAI,WAAW,MAAM;AACnB,kBAAQ,QAAQ,CAAC,YAAY;AAC3B,gBAAI,WAAW,CAAC,QAAQ,QAAQ,CAAC,cAAc,IAAI,QAAQ,EAAE,GAAG;AAC9D,oBAAMT,UAAS,gCAAgC,QAAQ;AACvD,kBAAIA,YAAW,GAAG;AAChB,oBAAI,CAAC,KAAK,oBAAoB;AAC5B,0BAAQ,QAAQ;AAAA,gBAClB,OAAO;AACL,wBAAM,CAAC,WAAWE,MAAK,IAAI,oBAAoBO,MAAK,MAAM,OAAO;AACjE,sBAAI,KAAK,oBAAoB,YAAY;AACvC,yBAAK,oBAAoB,WAAWP,UAAS;AAAA,kBAC/C,OAAO;AACL,yBAAK,oBAAoB,aAAa,CAAC;AACvC,yBAAK,oBAAoB,WAAWA,UAAS;AAAA,kBAC/C;AAAA,gBACF;AACA,uBAAO,gCAAgC,QAAQ;AAAA,cACjD,WAAWF,WAAU,MAAM;AACzB,gDAAgC,QAAQ;AAAA,cAC1C;AAAA,YACF;AAAA,UACF,CAAC;AAAA,QACH;AAAA,MACF;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,MAAM,aAAa,QAAQ,SAAS;AAClC,WAAO,KAAK,cAAc,QAAQ,OAAO;AAAA,EAC3C;AAAA,EACA,6BAA6B;AAC3B,QAAI,CAAC,KAAK,qBAAqB;AAC7B;AAAA,IACF;AACA,WAAO,KAAK,KAAK,mBAAmB,EAAE,QAAQ,CAAC,QAAQ,KAAK,oBAAoB,KAAK,QAAQ,CAAC,YAAY,QAAQ,QAAQ,CAAC,CAAC;AAC5H,SAAK,kBAAkB;AAAA,EACzB;AAAA,EACA,oBAAoB;AAClB,QAAI,CAAC,KAAK,YAAY;AACpB;AAAA,IACF;AACA,WAAO,KAAK,KAAK,UAAU,EAAE,QAAQ,CAAC,QAAQ;AAC5C,YAAM,cAAc,KAAK,WAAW;AACpC,kBAAY,QAAQ,CAAC,YAAY;AAC/B,YAAI,WAAW,CAAC,QAAQ,QAAQ,CAAC,QAAQ,cAAc,CAAC,KAAK,QAAQ,IAAI,QAAQ,EAAE,GAAG;AACpF,kBAAQ,QAAQ;AAAA,QAClB;AAAA,MACF,CAAC;AAAA,IACH,CAAC;AAAA,EACH;AAAA,EACA,yBAAyB;AACvB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,2BAA2B;AACzB,eAAW,OAAO,KAAK,qBAAqB;AAC1C,WAAK,oBAAoB,KAAK,QAAQ,CAAC,YAAY,QAAQ,QAAQ,CAAC;AACpE,aAAO,KAAK,oBAAoB;AAAA,IAClC;AAAA,EACF;AAAA,EACA,MAAM,cAAc,QAAQ,SAAS,sBAAsB,OAAO,iBAAiB,CAAC,GAAG,gBAAgB,CAAC,GAAG;AACzG,QAAI,CAAC,qBAAqB;AACxB,eAAS,KAAK,UAAU,MAAM;AAC9B,WAAK,YAAY,MAAM;AACvB,WAAK,uBAAuB,MAAM;AAClC,gBAAU,KAAK,WAAW,OAAO;AACjC,WAAK,aAAa,OAAO;AAAA,IAC3B;AACA,QAAI;AACF,WAAK,qBAAqB,IAAI,EAAE,QAAQ,2BAA2B;AAAA,IACrE,SAAS,IAAP;AACA,cAAQ,KAAK,GAAG,OAAO;AAAA,IACzB;AACA,SAAK,yBAAyB;AAC9B,UAAM,UAAU,IAAI,iBAAiB,KAAK,WAAW,gBAAgB,eAAe,KAAK,mBAAmB;AAC5G,SAAK,aAAa,MAAM,KAAK,uBAAuB,QAAQ,SAAS,SAAS,mBAAmB;AACjG,UAAM,UAAU,QAAQ,IAAI,CAAC,SAAS,UAAU,MAAM,KAAK,YAAY,OAAO,CAAC;AAC/E,UAAM,YAAY,QAAQ,IAAI,CAAC,OAAO,GAAG,EAAE;AAC3C,UAAM,WAAW,OAAO,KAAK,MAAM,EAAE,IAAI,CAAC,SAAS,OAAO,MAAM,EAAE;AAClE,SAAK,UAA0B,oBAAI,IAAI,CAAC,GAAG,WAAW,GAAG,UAAU,GAAG,KAAK,SAAS,CAAC;AACrF,QAAI,CAAC,KAAK,oBAAoB;AAC5B,WAAK,kBAAkB;AAAA,IACzB;AACA,QAAI,KAAK,UAAU,MAAM;AACvB,cAAQ,QAAQ,KAAK,OAAO;AAAA,IAC9B;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,qBAAqB,QAAQ,gBAAgB,eAAe;AAChE,UAAM,eAAe,OAAO,OAAO,CAAC,KAAK,SAASE,WAAU;AAC1D,UAAI,KAAK,OAAOA,QAAO,QAAQ;AAC/B,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AACL,WAAO,KAAK,cAAc,cAAc,KAAK,aAAa,MAAM,gBAAgB,aAAa;AAAA,EAC/F;AAAA,EACA,MAAM,uBAAuB,QAAQ,SAAS,aAAa,qBAAqB;AAC9E,UAAM,QAAQ,OAAO,KAAK,MAAM;AAChC,UAAM,aAAa,MAAM,IAAI,CAAC,SAAS,KAAK,MAAM,MAAM,cAAc,IAAI,EAAE,GAAG;AAC/E,UAAM,kBAAkB,YAAY,IAAI,CAAC,SAAS,cAAc,IAAI,EAAE,EAAE;AACxE,QAAIwB,eAAc,gBAAgB,IAAI,CAAC,SAAS,KAAK,MAAM,MAAM,KAAK;AACtE,QAAIA,aAAY,WAAW,GAAG;AAC5B,MAAAA,eAAc,KAAK;AAAA,IACrB;AACA,UAAM,EAAE,WAAW,eAAe,aAAa,WAAW,IAAI,qBAAqB,QAAQA,cAAa,KAAK,WAAW,KAAK,UAAU;AACvI,UAAM,SAAS;AAAA,MACb,GAAG;AAAA,MACH,GAAG,KAAK,MAAM;AAAA,MACd,GAAG,KAAK,cAAc,CAAC;AAAA,IACzB,EAAE,IAAI,CAACjB,UAAS;AACd,aAAO,EAAE,MAAAA,OAAM,UAAU,QAAQ,eAAe;AAAA,IAClD,CAAC;AACD,UAAM,aAAa,OAAO,OAAO,CAAC,GAAG,KAAK,SAAS;AACnD,WAAO,KAAK,MAAM,EAAE,QAAQ,CAAC,SAAS;AACpC,YAAM,CAAC,UAAUP,MAAK,IAAI,cAAc,IAAI;AAC5C,YAAM,UAAU,CAAC;AACjB,cAAQA,UAAS,OAAO;AACxB,iBAAW,YAAY;AAAA,IACzB,CAAC;AACD,UAAM,kCAAkC,CAAC;AACzC,UAAM,gBAAgB,KAAK,mBAAmB,UAAU;AACxD,UAAM,QAAQ,CAAC;AACf,WAAO,OAAO,SAAS,GAAG;AACxB,YAAM,WAAW,KAAK,aAAa,YAAY,QAAQ,SAAS,YAAY,OAAO,eAAe,iBAAiB,iCAAiC,SAAS;AAC7J,YAAM,QAAQ,IAAI,QAAQ;AAAA,IAC5B;AACA,QAAI,eAAe,QAAQ,CAAC,qBAAqB;AAC/C,cAAQ,KAAK,iIAAiI;AAAA,IAChJ;AACA,UAAM,iBAAiBwB,aAAY,OAAO,CAACjB,UAAS,CAAC,cAAcA,KAAI,KAAK,CAAC,UAAUA,MAAK,MAAM,YAAY,OAAO,CAAC,EAAE,IAAI,CAACA,UAASA,MAAK,IAAI;AAC/I,QAAI,eAAe,SAAS,GAAG;AAC7B,UAAI,iBAAiB;AACrB,UAAI,eAAe,MAAM;AACvB,yBAAiB,wFAAwF;AAAA,MAC3G;AACA,YAAM,IAAI,MAAM,+BAA+B,6CAA6C,qDAAqD,mBAAmB,gBAAgB;AAAA,IACtL;AACA,WAAO;AAAA,EACT;AAAA,EACA,aAAa,YAAY,QAAQ,SAAS,WAAW,OAAO,eAAe,aAAa,iCAAiC,WAAW;AAClI,UAAM,WAAW,CAAC;AAClB,WAAO,OAAO,SAAS,GAAG;AACxB,YAAM,OAAO,OAAO,IAAI;AACxB,cAAQ,iBAAiB,KAAK;AAC9B,UAAI,WAAW;AACf,UAAI,KAAK,KAAK,OAAO,WAAW,cAAc,cAAc,KAAK,MAAM,WAAW,OAAO,GAAG;AAC1F,SAAC,QAAQ,IAAI,oBAAoB,KAAK,KAAK,MAAM,OAAO;AAAA,MAC1D;AACA,UAAI,UAAU,KAAK,KAAK,SAAS,MAAM;AACrC,cAAM,UAAU,YAAY,KAAK,MAAM,WAAW,SAAS,KAAK,gBAAgB;AAChF,YAAI,CAAC,UAAU;AACb,WAAC,QAAQ,IAAI,oBAAoB,KAAK,KAAK,MAAM,OAAO;AAAA,QAC1D;AACA,cAAM,iBAAiB,QAAQ;AAC/B,YAAI,aAAa,UAAU,OAAO,GAAG;AACnC,mBAAS,KAAK,QAAQ,KAAK,CAAC,OAAO;AACjC,sBAAU,YAAY;AACtB,oBAAQ,iBAAiB;AACzB,iBAAK,uBAAuB,UAAU,KAAK,MAAM,WAAW,SAAS,eAAe,aAAa,+BAA+B;AAChI,iBAAK,kBAAkB,KAAK,MAAM,QAAQ,SAAS,WAAW,OAAO,SAAS;AAC9E,mBAAO;AAAA,UACT,CAAC,CAAC;AAAA,QACJ,OAAO;AACL,oBAAU,YAAY;AACtB,eAAK,uBAAuB,UAAU,KAAK,MAAM,WAAW,SAAS,eAAe,aAAa,+BAA+B;AAChI,eAAK,kBAAkB,KAAK,MAAM,QAAQ,SAAS,WAAW,OAAO,SAAS;AAAA,QAChF;AAAA,MACF,OAAO;AACL,aAAK,kBAAkB,KAAK,MAAM,QAAQ,SAAS,WAAW,OAAO,SAAS;AAAA,MAChF;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,kBAAkBA,OAAM,QAAQ,SAAS,WAAW,OAAO,WAAW;AACpE,IAAAA,MAAK,SAAS,QAAQ,CAAC,cAAc;AACnC,YAAM,CAAC,QAAQ,IAAI,oBAAoB,UAAU,MAAM,OAAO;AAC9D,UAAI,MAAM,aAAa,CAAC,UAAU,IAAI,UAAU,IAAI,GAAG;AACrD;AAAA,MACF;AACA,UAAI,UAAU,OAAO,SAAS;AAC5B,YAAI,UAAU,WAAW,KAAK,CAAC,SAAS;AACtC,iBAAO,CAAC,CAAC,UAAU,MAAM,WAAW,OAAO;AAAA,QAC7C,CAAC,GAAG;AACF,gBAAM,YAAY;AAClB,iBAAO,KAAK,EAAE,UAAU,QAAQ,gBAAgB,MAAM,UAAU,CAAC;AAAA,QACnE;AAAA,MACF,WAAW,UAAU,WAAW,MAAM,CAAC,SAAS;AAC9C,eAAO,CAAC,CAAC,UAAU,MAAM,WAAW,OAAO;AAAA,MAC7C,CAAC,GAAG;AACF,cAAM,YAAY;AAClB,eAAO,KAAK,EAAE,UAAU,QAAQ,gBAAgB,MAAM,UAAU,CAAC;AAAA,MACnE;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,UAAU;AACR,WAAO,KAAK,KAAK,SAAS,EAAE,QAAQ,CAAC,QAAQ,KAAK,UAAU,KAAK,QAAQ,CAAC,YAAY,QAAQ,QAAQ,CAAC,CAAC;AAAA,EAC1G;AAAA,EACA,uBAAuB,QAAQ;AAC7B,WAAO,KAAK,MAAM,EAAE,QAAQ,CAAC,SAAS;AACpC,YAAM,SAAS,OAAO;AACtB,YAAM,CAAC,QAAQ,IAAI,cAAc,IAAI;AACrC,YAAMA,QAAO,KAAK,MAAM,MAAM;AAC9B,UAAIA,MAAK,WAAW,YAAYA,MAAK,WAAW,SAAS,OAAO;AAC9D,cAAM,QAAQA,MAAK,WAAW,SAAS;AACvC,cAAMkB,SAAQ,MAAM,WAAW,OAAO,MAAM,UAAU,OAAO,MAAM,MAAM,CAAC,KAAKzB,WAAU,MAAMA,YAAW,MAAM,MAAMA,YAAW,GAAG;AACpI,qBAAa,OAAOyB,QAAO,MAAM,sBAAsBlB,MAAK,mDAAmD,oBAAoB,OAAO,QAAQ;AAAA,MACpJ;AACA,UAAIA,MAAK,WAAW,YAAYA,MAAK,WAAW,SAAS,OAAO;AAC9D,qBAAa,OAAO,OAAO,UAAUA,MAAK,WAAW,SAAS,OAAO,MAAM,sBAAsBA,MAAK,kDAAkDA,MAAK,WAAW,SAAS,kBAAkB,OAAO,OAAO;AAAA,MACnN;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,UAAU,QAAQ;AAChB,UAAM,SAAS,CAAC;AAChB,eAAW,aAAa,QAAQ;AAC9B,UAAI,KAAK,cAAc,QAAQ,KAAK,WAAW,UAAU,QAAQ,KAAK,WAAW,OAAO,cAAc,MAAM;AAC1G,cAAM,UAAU,KAAK,WAAW,OAAO;AACvC,eAAO,QAAQ,QAAQ,OAAO;AAAA,MAChC,OAAO;AACL,eAAO,aAAa,OAAO;AAAA,MAC7B;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,YAAY,QAAQ;AAClB,UAAM,aAAa,OAAO,KAAK,MAAM,EAAE,OAAO,CAAC,SAAS;AACtD,YAAM,CAAC,QAAQ,IAAI,cAAc,IAAI;AACrC,aAAO,KAAK,MAAM,MAAM,aAAa;AAAA,IACvC,CAAC;AACD,QAAI,WAAW,SAAS,GAAG;AACzB,YAAM,IAAI,MAAM,uDAAuD,wCAAwC;AAAA,IACjH;AAAA,EACF;AAAA,EACA,WAAW,SAAS;AAClB,WAAO,QAAQ,IAAI,CAAC,SAAS;AAC3B,UAAI,KAAK,cAAc,QAAQ,KAAK,WAAW,WAAW,QAAQ,KAAK,WAAW,QAAQ,SAAS,MAAM;AACvG,cAAM,UAAU,KAAK,WAAW,QAAQ;AACxC,eAAO,QAAQ;AAAA,MACjB;AACA,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AAAA,EACP;AAAA,EACA,aAAa,SAAS;AACpB,YAAQ,QAAQ,CAAC,SAAS;AACxB,YAAM,CAAC,cAAc,IAAI,cAAc,IAAI;AAC3C,UAAI,CAAC,KAAK,MAAM,MAAM,iBAAiB;AACrC,cAAM,IAAI,MAAM,eAAe,iCAAiC;AAAA,MAClE;AAAA,IACF,CAAC;AAAA,EACH;AACF;AAGA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,YAAY,wBAAwB,CAAC,GAAG,eAAe,CAAC,GAAG;AACzD,SAAK,wBAAwB;AAC7B,SAAK,eAAe;AAAA,EACtB;AAAA,EACA,aAAa,MAAM,WAAW;AAC5B,SAAK,sBAAsB,QAAQ,UAAU;AAC7C,SAAK,aAAa,UAAU,MAAM;AAAA,EACpC;AAAA,EACA,yBAAyB,MAAM;AAC7B,WAAO,KAAK,sBAAsB;AAAA,EACpC;AAAA,EACA,iBAAiB,IAAI;AACnB,WAAO,KAAK,aAAa;AAAA,EAC3B;AAAA,EACA,UAAU;AACR,eAAW,OAAO,KAAK,cAAc;AACnC,WAAK,aAAa,KAAK,cAAc;AACrC,aAAO,KAAK,aAAa;AAAA,IAC3B;AACA,eAAW,QAAQ,KAAK,uBAAuB;AAC7C,WAAK,sBAAsB,MAAM,QAAQ;AACzC,aAAO,KAAK,sBAAsB;AAAA,IACpC;AAAA,EACF;AACF;AAGA,IAAI,qBAAqB;AACzB,IAAI,qBAAqB;AACzB,IAAI,aAAa,MAAM;AAAA,EACrB,YAAY,UAAU,cAAc,CAAC,GAAG,OAAO,YAAY;AACzD,SAAK,WAAW;AAChB,SAAK,cAAc;AACnB,SAAK,UAAU;AACf,SAAK,KAAK;AACV,QAAI,eAAe,MAAM;AACvB,WAAK,cAAc,CAAC;AAAA,IACtB;AACA,SAAK,kBAAkB,IAAI,gBAAgB;AAAA,EAC7C;AAAA,EACA,IAAI,eAAe;AACjB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,aAAa;AACf,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,IAAI,cAAc;AAChB,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,IAAI,SAAS;AACX,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,IAAI,UAAU;AACZ,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,IAAI,UAAU;AACZ,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,IAAI,WAAW;AACb,WAAO,KAAK,UAAU;AAAA,EACxB;AAAA,EACA,IAAI,iBAAiB;AACnB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,4BAA4B;AAC9B,WAAO,KAAK;AAAA,EACd;AAAA,EACA,gBAAgB;AACd,UAAM,OAAO,KAAK;AAClB,QAAI,KAAK,QAAQ,MAAM;AACrB,WAAK,UAAU;AAAA,IACjB,WAAW,KAAK,YAAY,eAAe,MAAM;AAC/C,WAAK,UAAU,KAAK,GAAG,mBAAmB,MAAM,KAAK,WAAW;AAAA,IAClE,OAAO;AACL,YAAM,WAAW,KAAK,GAAG,gBAAgB,MAAM,KAAK,WAAW;AAC/D,UAAI,SAAS,WAAW,GAAG;AACzB,iBAAS,KAAK,KAAK,GAAG,mBAAmB,MAAM,KAAK,WAAW,CAAC;AAAA,MAClE,WAAW,SAAS,SAAS,GAAG;AAC9B,cAAM,IAAI,MAAM,wBAAwB,SAAS,kCAAkC,CAAC,IAAI,IAAI;AAAA,MAC9F;AACA,WAAK,UAAU,SAAS;AAAA,IAC1B;AAAA,EACF;AAAA,EACA,OAAO;AACL,SAAK,cAAc;AACnB,QAAI,KAAK,QAAQ,QAAQ,MAAM;AAC7B,YAAM,IAAI,MAAM,+GAA+G;AAAA,IACjI;AACA,UAAM,aAAa,KAAK,QAAQ,KAAK;AACrC,QAAI,aAAa,UAAU,UAAU,GAAG;AACtC,aAAO,WAAW,KAAK,CAAC,cAAc,KAAK,SAAS,SAAS,CAAC;AAAA,IAChE;AACA,WAAO,KAAK,SAAS,UAAU;AAAA,EACjC;AAAA,EACA,SAAS,WAAW;AAClB,SAAK,YAAY;AACjB,UAAM,QAAQ,KAAK,UAAU;AAC7B,QAAI,YAAY,KAAK,UAAU;AAC/B,QAAI,KAAK,UAAU,uBAAuB,MAAM;AAC9C,YAAM,WAAW,KAAK,UAAU;AAChC,UAAI,SAAS,aAAa,MAAM;AAC9B,oBAAY,SAAS;AAAA,MACvB;AACA,UAAI,SAAS,wBAAwB,MAAM;AACzC,aAAK,uBAAuB,SAAS;AAAA,MACvC;AAAA,IACF;AACA,SAAK,YAAY;AACjB,SAAK,UAAU,GAAG,MAAM,SAAS,YAAY,MAAM,SAAS;AAC5D,UAAM,YAAY,KAAK,GAAG,cAAc,KAAK,UAAU,YAAY,KAAK,UAAU,WAAW;AAC7F,SAAK,WAAW,IAAI,cAAc,gBAAgB,SAAS,eAAe,OAAO,KAAK,SAAS,CAAC;AAChG,SAAK,SAAS,YAAY,KAAK,6BAA6B,SAAS;AACrE,SAAK,SAAS,kBAAkB,KAAK;AACrC,QAAI,UAAU,oBAAoB,QAAQ,UAAU,iBAAiB,QAAQ,MAAM;AACjF,YAAM,cAAc,gBAAgB,SAAS,eAAe,UAAU,gBAAgB;AACtF,WAAK,cAAc,IAAI,cAAc,WAAW;AAChD,WAAK,YAAY,YAAY,KAAK,SAAS;AAC3C,WAAK,YAAY,kBAAkB,KAAK;AACxC,WAAK,YAAY,aAAa,CAAC,GAAG,CAAC,CAAC;AAAA,IACtC;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,KAAK,cAAcF,SAAQ;AAC/B,QAAI,OAAO,iBAAiB,UAAU;AACpC,YAAM,WAAW,KAAK,GAAG,gBAAgB,YAAY;AACrD,UAAI,SAAS,WAAW,GAAG;AACzB,cAAM,IAAI,MAAM,0CAA0C,eAAe;AAAA,MAC3E,WAAW,SAAS,SAAS,GAAG;AAC9B,cAAM,IAAI,MAAM,wBAAwB,SAAS,kCAAkC,eAAe;AAAA,MACpG;AACA,qBAAe,SAAS;AAAA,IAC1B;AACA,QAAI,aAAa,QAAQ,MAAM;AAC7B,YAAM,IAAI,MAAM,6GAA6G;AAAA,IAC/H;AACA,WAAO,aAAa,KAAK,KAAK,SAAS;AAAA,EACzC;AAAA,EACA,QAAQ,QAAQA,SAAQ;AACtB,UAAM,gBAAgB,KAAK,QAAQ,QAAQ,KAAK,WAAW;AAC3D,QAAI,KAAK,sBAAsB;AAC7B,YAAM,qBAAqB,yBAAyB,SAAS,CAAC,aAAa,IAAI;AAC/E,YAAM,kBAAkB,CAAC;AACzB,yBAAmB,QAAQ,CAAC,cAAc,OAAO,gBAAgB,KAAK,qBAAqB,OAAO,YAAY;AAC9G,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT;AAAA,EACA,gBAAgB,QAAQ;AACtB,QAAI,EAAE,kBAAkB,WAAW,CAAC,MAAM,QAAQ,MAAM,GAAG;AACzD,aAAO;AAAA,IACT;AACA,aAAS,MAAM,QAAQ,MAAM,IAAI,SAAS,CAAC,MAAM;AACjD,QAAI,OAAO,WAAW,KAAK,WAAW,QAAQ;AAC5C,YAAM,IAAI,MAAM,mDAAmD,KAAK,WAAW,wCAAwC,OAAO,uBAAuB;AAAA,IAC3J;AACA,WAAO,KAAK,WAAW,OAAO,CAAC,KAAK,WAAW,OAAO;AACpD,UAAI,aAAa,OAAO;AACxB,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AAAA,EACP;AAAA,EACA,iBAAiB,SAAS;AACxB,cAAU,WAAW,KAAK;AAC1B,WAAO,CAAC,MAAM,QAAQ,OAAO,IAAI,CAAC,OAAO,IAAI;AAAA,EAC/C;AAAA,EACA,QAAQ,QAAQ,SAAS;AACvB,aAAS,KAAK,gBAAgB,MAAM;AACpC,cAAU,KAAK,iBAAiB,OAAO;AACvC,UAAM,SAAS,KAAK,SAAS,QAAQ,QAAQ,OAAO;AACpD,WAAO,OAAO,SAAS,IAAI,SAAS,OAAO;AAAA,EAC7C;AAAA,EACA,MAAM,aAAa,QAAQ,SAAS;AAClC,aAAS,KAAK,gBAAgB,MAAM;AACpC,cAAU,KAAK,iBAAiB,OAAO;AACvC,UAAM,SAAS,MAAM,KAAK,SAAS,aAAa,QAAQ,OAAO;AAC/D,WAAO,OAAO,SAAS,IAAI,SAAS,OAAO;AAAA,EAC7C;AAAA,EACA,yBAAyB;AACvB,WAAO,KAAK,SAAS,uBAAuB;AAAA,EAC9C;AAAA,EACA,6BAA6B;AAC3B,SAAK,SAAS,2BAA2B;AAAA,EAC3C;AAAA,EACA,6BAA6B,KAAK;AAChC,WAAO,OAAO,KAAK,GAAG,EAAE,OAAO,CAAC,QAAQ,QAAQ;AAC9C,aAAO,OAAO,CAAC,IAAI,IAAI;AACvB,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AAAA,EACP;AAAA,EACA,UAAU;AACR,SAAK,SAAS,QAAQ;AACtB,QAAI,KAAK,aAAa;AACpB,WAAK,YAAY,QAAQ;AAAA,IAC3B;AACA,SAAK,gBAAgB,QAAQ;AAAA,EAC/B;AACF;AACA,eAAe,eAAe,UAAUR,WAAU,CAAC,GAAG,OAAO,YAAY;AACvE,MAAI,YAAY,MAAM;AACpB,UAAM,IAAI,MAAM,wGAAwG;AAAA,EAC1H;AACA,MAAIA,YAAW,MAAM;AACnB,IAAAA,WAAU,CAAC;AAAA,EACb;AACA,MAAIA,SAAQ,aAAa,OAAO,aAAa,UAAU;AACrD,eAAW,YAAY,QAAQ;AAAA,EACjC;AACA,QAAMuB,UAAS,IAAI,WAAW,UAAUvB,UAAS,IAAI;AACrD,QAAMuB,QAAO,KAAK;AAClB,SAAOA;AACT;AACA,SAAS,mBAAmB,aAAa;AACvC,MAAI,eAAe,MAAM;AACvB,UAAM,IAAI,MAAM,4GAA4G;AAAA,EAC9H;AACA,MAAI,CAAC,YAAY,MAAM;AACrB,UAAM,IAAI,MAAM,uBAAuB,kCAAkC;AAAA,EAC3E;AACA,QAAMA,UAAS,IAAI,WAAW,WAAW;AACzC,EAAAA,QAAO,KAAK;AACZ,SAAOA;AACT;AACA,SAAS,YAAY,UAAU;AAC7B,MAAI,CAAC,SAAS,SAAS,GAAG,GAAG;AAC3B,eAAW,WAAW;AAAA,EACxB;AACA,SAAO,GAAG,WAAW,qBAAqB;AAC5C;AAGA,IAAI,WAAW;AAGf,IAAI,gBAAgB,CAAC;AACrBhC,UAAS,eAAe;AAAA,EACtB,YAAY,MAAM;AAAA,EAClB,SAAS,MAAM;AAAA,EACf,gBAAgB,MAAM;AAAA,EACtB,iBAAiB,MAAM;AAAA,EACvB,eAAe,MAAM;AAAA,EACrB,OAAO,MAAM;AAAA,EACb,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,WAAW,MAAM;AAAA,EACjB,YAAY,MAAM;AAAA,EAClB,cAAc,MAAM;AAAA,EACpB,QAAQ,MAAM;AAAA,EACd,KAAK,MAAM;AACb,CAAC;AAGD,IAAI,cAAc,QAAQ,oBAAoB,CAAC;AAG/C,IAAI,cAAc,QAAQ,oBAAoB,CAAC;AAG/C,SAAS,QAAQ,QAAQ,OAAO;AAC9B,SAAO,gBAAgB,QAAQ,KAAK;AACtC;AACA,SAAS,gBAAgB,QAAQ,OAAO,OAAuB,oBAAI,IAAI,GAAG,cAA8B,oBAAI,IAAI,GAAG;AACjH,MAAI,UAAU,MAAM;AAClB,WAAO;AAAA,EACT;AACA,MAAI,OAAO,SAAS,cAAc,kBAAkB,MAAM;AACxD,WAAO,OAAO,MAAM;AAAA,EACtB;AACA,MAAI,YAAY,IAAI,MAAM,GAAG;AAC3B,UAAM,IAAI,MAAM,wCAAwC;AAAA,EAC1D;AACA,MAAI,KAAK,IAAI,MAAM,GAAG;AACpB,WAAO,KAAK,IAAI,MAAM;AAAA,EACxB;AACA,QAAM,SAAS,MAAM,MAAM;AAC3B,MAAI,OAAO,WAAW,OAAO,UAAU,MAAM;AAC3C,UAAM,IAAI,MAAM,mEAAmE;AAAA,EACrF;AACA,MAAI,CAAC,OAAO,SAAS;AACnB,SAAK,IAAI,QAAQ,OAAO,KAAK;AAC7B,WAAO,OAAO;AAAA,EAChB,WAAW,YAAY,MAAM,GAAG;AAC9B,UAAM,iBAAiB,MAAM,QAAQ,MAAM,IAAI,CAAC,IAAI,CAAC;AACrD,gBAAY,IAAI,MAAM;AACtB,eAAW,KAAK,QAAQ;AACtB,YAAM,QAAQ,OAAO;AACrB,YAAM,cAAc,gBAAgB,OAAO,OAAO,MAAM,WAAW;AACnE,qBAAe,KAAK;AAAA,IACtB;AACA,gBAAY,OAAO,MAAM;AACzB,QAAI,OAAO,WAAW;AACpB,qBAAe,YAAY,OAAO;AAAA,IACpC;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,yCAAyC,QAAQ;AAAA,EACnE;AACF;AACA,SAAS,QAAQ,QAAQ,QAAQ,WAAW;AAC1C,SAAO,gBAAgB,QAAQ,KAAK;AACtC;AACA,SAAS,gBAAgB,QAAQ,OAAO,cAA8B,oBAAI,IAAI,GAAG;AAC/E,QAAM,SAAS,OAAO;AACtB,MAAI,YAAY,IAAI,MAAM,GAAG;AAC3B,UAAM,IAAI,MAAM,wCAAwC;AAAA,EAC1D;AACA,QAAM,SAAS,MAAM,MAAM;AAC3B,MAAI,OAAO,WAAW,OAAO,UAAU,MAAM;AAC3C,UAAM,IAAI,MAAM,mEAAmE;AAAA,EACrF;AACA,MAAI,CAAC,OAAO,SAAS;AACnB,WAAO,OAAO;AAAA,EAChB,WAAW,YAAY,MAAM,GAAG;AAC9B,UAAM,iBAAiB,MAAM,QAAQ,MAAM,IAAI,CAAC,IAAI,CAAC;AACrD,gBAAY,IAAI,MAAM;AACtB,eAAW,KAAK,QAAQ;AACtB,YAAM,WAAW,OAAO,IAAI,CAAC,MAAM,EAAE,EAAE;AACvC,YAAM,cAAc,gBAAgB,UAAU,OAAO,WAAW;AAChE,qBAAe,KAAK;AAAA,IACtB;AACA,gBAAY,OAAO,MAAM;AACzB,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,yCAAyC,QAAQ;AAAA,EACnE;AACF;AACA,SAAS,UAAU,GAAG;AACpB,MAAI,MAAM,MAAM;AACd,WAAO;AAAA,EACT;AACA,MAAI,YAAY,EAAE,EAAE,GAAG;AACrB,WAAO,EAAE,OAAO,MAAM,SAAS,KAAK;AAAA,EACtC,OAAO;AACL,WAAO,EAAE,OAAO,GAAG,SAAS,MAAM;AAAA,EACpC;AACF;AACA,eAAe,mBAAmB,QAAQ,OAAO;AAC/C,QAAM,OAAuB,oBAAI,IAAI;AACrC,kBAAgB,QAAQ,OAAO,IAAI;AACnC,aAAW,OAAO,MAAM,KAAK,KAAK,KAAK,CAAC,GAAG;AACzC,UAAM,QAAQ,KAAK,IAAI,GAAG;AAC1B,QAAI,aAAa,UAAU,KAAK,GAAG;AACjC,YAAM,cAAc,MAAM;AAC1B,WAAK,IAAI,KAAK,WAAW;AAAA,IAC3B;AAAA,EACF;AACA,QAAM,SAAS,gBAAgB,QAAQ,OAAO,IAAI;AAClD,SAAO;AACT;AACA,SAAS,YAAY,KAAK;AACxB,MAAI,gBAAgB;AACpB,MAAI,IAAI,EAAE,IAAI,YAAY,GAAG;AAC3B,oBAAgB,eAAe;AAAA,EACjC,OAAO;AACL,UAAM,EAAE,cAAc,IAAI,uBAAuB;AACjD,oBAAgB,eAAe;AAAA,EACjC;AACA,SAAO,OAAO,QAAQ,CAAC,YAAY,OAAO,GAAG,MAAM,MAAM,QAAQ,GAAG,KAAK,OAAO,QAAQ,YAAY,EAAE,eAAe,WAAW,EAAE,eAAe,YAAY,CAAC;AAChK;AACA,SAAS,aAAa,KAAK;AACzB,SAAO,OAAO,QAAQ,YAAY,GAAG,KAAK,MAAM,QAAQ,GAAG,KAAK,OAAO,QAAQ,YAAY,eAAe,UAAU,aAAa,aAAa,GAAG;AACnJ;AACA,SAAS,YAAY,OAAO;AAC1B,SAAO,UAAU,QAAQ,OAAO,UAAU,YAAY,OAAO,UAAU;AACzE;AAGA,SAAS,UAAU,WAAW;AAC5B,SAAO,QAAQ,WAAW,aAAa;AACzC;AACA,SAAS,cAAc,MAAM;AAC3B,MAAI,gBAAgB,QAAQ;AAC1B,WAAO,EAAE,OAAO,KAAK,MAAM,GAAG,SAAS,MAAM;AAAA,EAC/C,WAAW,YAAY,IAAI,GAAG;AAC5B,WAAO,EAAE,OAAO,MAAM,SAAS,KAAK;AAAA,EACtC,OAAO;AACL,WAAO,EAAE,OAAO,MAAM,SAAS,MAAM;AAAA,EACvC;AACF;AAGA,IAAI,aAAa,MAAM;AAAA,EACrB,YAAY,UAAU;AACpB,SAAK,WAAW;AAChB,SAAK,QAAQ;AACb,SAAK,MAAM;AACX,QAAI,YAAY,MAAM;AACpB,YAAM,IAAI,WAAW,iDAAiD;AAAA,IACxE;AACA,QAAI,WAAW,GAAG;AAChB,YAAM,IAAI,WAAW,2CAA2C;AAAA,IAClE;AACA,SAAK,OAAO,IAAI,MAAM,QAAQ;AAC9B,SAAK,kBAAkB,IAAI;AAAA,EAC7B;AAAA,EACA,KAAKY,QAAO;AACV,WAAOA,SAAQ,GAAG;AAChB,MAAAA,UAAS,KAAK;AAAA,IAChB;AACA,WAAOA,SAAQ,KAAK;AAAA,EACtB;AAAA,EACA,IAAIA,QAAO;AACT,QAAIA,SAAQ,GAAG;AACb,YAAM,IAAI,WAAW,qCAAqC;AAAA,IAC5D;AACA,WAAO,KAAK,KAAKA,SAAQ,KAAK;AAAA,EAChC;AAAA,EACA,IAAIA,QAAO,OAAO;AAChB,QAAIA,SAAQ,GAAG;AACb,YAAM,IAAI,WAAW,qCAAqC;AAAA,IAC5D;AACA,SAAK,KAAKA,SAAQ,KAAK,YAAY;AAAA,EACrC;AAAA,EACA,SAAS;AACP,QAAI,SAAS,KAAK,MAAM,KAAK;AAC7B,QAAI,SAAS,GAAG;AACd,eAAS,KAAK,kBAAkB;AAAA,IAClC;AACA,WAAO;AAAA,EACT;AAAA,EACA,SAAS;AACP,WAAO,KAAK,OAAO,MAAM,KAAK;AAAA,EAChC;AAAA,EACA,UAAU;AACR,WAAO,KAAK,OAAO,MAAM;AAAA,EAC3B;AAAA,EACA,KAAK,OAAO;AACV,QAAI,KAAK,OAAO,GAAG;AACjB,YAAM,IAAI,WAAW,sBAAsB;AAAA,IAC7C;AACA,SAAK,IAAI,KAAK,KAAK,KAAK;AACxB,SAAK,MAAM,KAAK,KAAK,KAAK,MAAM,CAAC;AAAA,EACnC;AAAA,EACA,QAAQ,QAAQ;AACd,eAAW,SAAS,QAAQ;AAC1B,WAAK,KAAK,KAAK;AAAA,IACjB;AAAA,EACF;AAAA,EACA,MAAM;AACJ,QAAI,KAAK,QAAQ,GAAG;AAClB,YAAM,IAAI,WAAW,uBAAuB;AAAA,IAC9C;AACA,SAAK,MAAM,KAAK,KAAK,KAAK,MAAM,CAAC;AACjC,UAAM,SAAS,KAAK,IAAI,KAAK,GAAG;AAChC,SAAK,IAAI,KAAK,KAAK,MAAM;AACzB,WAAO;AAAA,EACT;AAAA,EACA,QAAQ,OAAO;AACb,QAAI,KAAK,OAAO,GAAG;AACjB,YAAM,IAAI,WAAW,sBAAsB;AAAA,IAC7C;AACA,SAAK,QAAQ,KAAK,KAAK,KAAK,QAAQ,CAAC;AACrC,SAAK,IAAI,KAAK,OAAO,KAAK;AAAA,EAC5B;AAAA,EACA,QAAQ;AACN,QAAI,KAAK,QAAQ,GAAG;AAClB,YAAM,IAAI,WAAW,uBAAuB;AAAA,IAC9C;AACA,UAAM,SAAS,KAAK,IAAI,KAAK,KAAK;AAClC,SAAK,IAAI,KAAK,OAAO,MAAM;AAC3B,SAAK,QAAQ,KAAK,KAAK,KAAK,QAAQ,CAAC;AACrC,WAAO;AAAA,EACT;AAAA,EACA,cAAc,eAAe;AAC3B,QAAI,KAAK,QAAQ,GAAG;AAClB,YAAM,IAAI,WAAW,uBAAuB;AAAA,IAC9C;AACA,UAAMA,SAAQ,KAAK,KAAK,KAAK,QAAQ,aAAa;AAClD,UAAM,SAAS,KAAK,IAAIA,MAAK;AAC7B,SAAK,IAAIA,QAAO,KAAK,IAAI,CAAC;AAC1B,WAAO;AAAA,EACT;AACF;AAGA,IAAI,oBAAoB,cAAc,WAAW;AAAA,EAC/C,cAAc;AACZ,UAAM,kBAAkB,gBAAgB;AAAA,EAC1C;AAAA,EACA,SAAS;AACP,WAAO;AAAA,EACT;AAAA,EACA,KAAK,OAAO;AACV,QAAI,MAAM,OAAO,GAAG;AAClB,WAAK,OAAO;AAAA,IACd;AACA,UAAM,KAAK,KAAK;AAAA,EAClB;AAAA,EACA,QAAQ,OAAO;AACb,QAAI,MAAM,OAAO,GAAG;AAClB,WAAK,OAAO;AAAA,IACd;AACA,UAAM,QAAQ,KAAK;AAAA,EACrB;AAAA,EACA,SAAS;AACP,UAAM,cAAc,KAAK,WAAW;AACpC,UAAM,UAAU,IAAI,MAAM,WAAW;AACrC,UAAM,MAAM,KAAK,OAAO;AACxB,aAAS,KAAK,GAAG,KAAK,KAAK,MAAM;AAC/B,cAAQ,MAAM,KAAK,IAAI,KAAK,KAAK,KAAK,QAAQ,EAAE,CAAC;AAAA,IACnD;AACA,SAAK,OAAO;AACZ,SAAK,WAAW;AAChB,SAAK,kBAAkB,IAAI,KAAK;AAChC,SAAK,QAAQ;AACb,SAAK,MAAM;AAAA,EACb;AACF;AACA,kBAAkB,mBAAmB;AAGrC,SAAS,kBAAkB,OAAO;AAChC,SAAO,IAAI,cAAc,KAAK;AAChC;AACA,SAAS,qBAAqB,OAAO;AACnC,SAAO,IAAI,qBAAqB,KAAK;AACvC;AACA,SAAS,yBAAyB,eAAe,kBAAkB;AACjE,SAAO,IAAI,gBAAgB,eAAe,gBAAgB;AAC5D;AACA,SAAS,mBAAmB,WAAW,eAAe,gBAAgB,MAAM;AAC1E,SAAO,IAAI,YAAY,WAAW,YAAY;AAChD;AACA,IAAI,eAAe,MAAM;AAAA,EACvB,MAAM,UAAU;AACd,UAAM,SAAS,CAAC;AAChB,QAAI,IAAI,MAAM,KAAK,KAAK;AACxB,WAAO,CAAC,EAAE,MAAM;AACd,aAAO,KAAK,EAAE,KAAK;AACnB,UAAI,MAAM,KAAK,KAAK;AAAA,IACtB;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,iBAAiB;AACrB,UAAM,SAAS,KAAK,SAAS,GAAG;AAChC,UAAM,SAAS,CAAC;AAChB,QAAI,IAAI,MAAM,OAAO,KAAK;AAC1B,WAAO,CAAC,EAAE,MAAM;AACd,aAAO,KAAK,EAAE,KAAK;AACnB,UAAI,MAAM,OAAO,KAAK;AAAA,IACxB;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,eAAe;AACnB,QAAI,IAAI,MAAM,KAAK,KAAK;AACxB,WAAO,CAAC,EAAE,MAAM;AACd,UAAI,MAAM,KAAK,KAAK;AAAA,IACtB;AAAA,EACF;AAAA,EACA,MAAM,aAAa,WAAW;AAC5B,QAAI,IAAI,MAAM,KAAK,KAAK;AACxB,QAAI,iBAAiB,UAAU,EAAE,KAAK;AACtC,WAAO,CAAC,EAAE,QAAQ,gBAAgB;AAChC,UAAI,MAAM,KAAK,KAAK;AACpB,uBAAiB,UAAU,EAAE,KAAK;AAAA,IACpC;AAAA,EACF;AAAA,EACA,aAAa,SAAS;AACpB,WAAO,IAAI,0BAA0B,MAAM,OAAO;AAAA,EACpD;AAAA,EACA,OAAO,WAAW;AAChB,WAAO,IAAI,eAAe,MAAM,SAAS;AAAA,EAC3C;AAAA,EACA,IAAI,YAAY;AACd,WAAO,IAAI,YAAY,MAAM,UAAU;AAAA,EACzC;AAAA,EACA,SAAS,YAAY;AACnB,WAAO,IAAI,iBAAiB,MAAM,UAAU;AAAA,EAC9C;AAAA,EACA,eAAe,YAAY;AACzB,WAAO,IAAI,iBAAiB,MAAM,UAAU,EAAE,OAAO;AAAA,EACvD;AAAA,EACA,QAAQ,YAAY;AAClB,WAAO,IAAI,gBAAgB,MAAM,UAAU;AAAA,EAC7C;AAAA,EACA,MAAM,aAAa,GAAG;AACpB,WAAO,KAAK,IAAI,CAAC,EAAE,aAAa;AAAA,EAClC;AAAA,EACA,MAAM,cAAc,GAAG;AACrB,WAAO,KAAK,eAAe,CAAC,EAAE,aAAa,CAAC,MAAM,MAAM,IAAI;AAAA,EAC9D;AAAA,EACA,cAAc,WAAW,iBAAiB,MAAM;AAC9C,WAAO,IAAI,sBAAsB,MAAM,WAAW,cAAc;AAAA,EAClE;AAAA,EACA,iBAAiB,WAAW,iBAAiB,MAAM,QAAQ,WAAW;AACpE,UAAM,aAAa,KAAK,cAAc,WAAW,cAAc;AAC/D,WAAO,WAAW,IAAI,CAAC,MAAM,QAAQ,GAAG,KAAK,CAAC;AAAA,EAChD;AAAA,EACA,YAAY,UAAU,kBAAkB;AACtC,WAAO,IAAI,gBAAgB,kBAAkB,CAAC,MAAM,QAAQ,CAAC,GAAG,gBAAgB;AAAA,EAClF;AAAA,EACA,KAAKF,SAAQ;AACX,QAAIA,UAAS,KAAKA,WAAU,MAAM;AAChC,aAAO;AAAA,IACT;AACA,WAAO,IAAI,aAAa,MAAMA,OAAM;AAAA,EACtC;AAAA,EACA,KAAKA,SAAQ;AACX,QAAIA,UAAS,KAAKA,WAAU,MAAM;AAChC,aAAO;AAAA,IACT;AACA,WAAO,IAAI,aAAa,MAAMA,OAAM;AAAA,EACtC;AAAA,EACA,SAAS,YAAY;AACnB,WAAO,IAAI,iBAAiB,MAAM,UAAU;AAAA,EAC9C;AAAA,EACA,QAAQ,YAAY,MAAM;AACxB,WAAO,IAAI,gBAAgB,MAAM,YAAY,IAAI;AAAA,EACnD;AAAA,EACA,SAAS;AACP,WAAO,IAAI,eAAe,IAAI;AAAA,EAChC;AACF;AACA,IAAI,gBAAgB,cAAc,aAAa;AAAA,EAC7C,YAAY,OAAO;AACjB,UAAM;AACN,SAAK,QAAQ;AACb,SAAK,OAAO;AAAA,EACd;AAAA,EACA,UAAU;AACR,WAAO,YAAY,KAAK,MAAM;AAAA,EAChC;AAAA,EACA,MAAM,OAAO;AACX,QAAI,KAAK,QAAQ,KAAK,MAAM,QAAQ;AAClC,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,UAAM,OAAO,KAAK,MAAM,KAAK;AAC7B,SAAK;AACL,WAAO,EAAE,OAAO,UAAU,IAAI,GAAG,MAAM,MAAM;AAAA,EAC/C;AACF;AACA,IAAI,uBAAuB,cAAc,aAAa;AAAA,EACpD,YAAY,QAAQ;AAClB,UAAM;AACN,SAAK,SAAS;AAAA,EAChB;AAAA,EACA,UAAU;AACR,WAAO;AAAA,EACT;AAAA,EACA,MAAM,OAAO;AACX,QAAI;AACF,aAAO,KAAK,OAAO;AAAA,IACrB,SAAS,IAAP;AACA,SAAG,UAAU,mDAAmD,GAAG;AACnE,YAAM;AAAA,IACR;AAAA,EACF;AACF;AACA,IAAI,iBAAiB,cAAc,aAAa;AAAA,EAC9C,YAAY,UAAU;AACpB,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,WAAW,QAAQ,QAAQ,EAAE,OAAO,MAAM,MAAM,MAAM,CAAC;AAAA,EAC9D;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,SAAS,KAAK,MAAM,KAAK,WAAW,CAAC;AAC1D,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,KAAK,SAAS,KAAK;AAAA,EAC5B;AACF;AACA,IAAI,eAAe,cAAc,aAAa;AAAA,EAC5C,YAAY,UAAU,UAAU;AAC9B,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,WAAW;AAChB,SAAK,QAAQ;AACb,SAAK,WAAW,QAAQ,QAAQ,EAAE,OAAO,MAAM,MAAM,MAAM,CAAC;AAAA,EAC9D;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,SAAS,KAAK,MAAM,KAAK,WAAW,CAAC;AAC1D,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,KAAK,UAAU,KAAK,UAAU;AACnC,YAAM4B,YAAU,MAAM,KAAK,SAAS,KAAK;AACzC,UAAIA,UAAQ,MAAM;AAChB,eAAOA;AAAA,MACT;AACA,cAAQA,UAAQ,KAAK;AAAA,IACvB;AACA,WAAO,KAAK,SAAS,KAAK;AAAA,EAC5B;AACF;AACA,IAAI,eAAe,cAAc,aAAa;AAAA,EAC5C,YAAY,UAAU,UAAU;AAC9B,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,WAAW;AAChB,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,QAAI,KAAK,WAAW,KAAK,UAAU;AACjC,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,WAAO,KAAK,SAAS,KAAK;AAAA,EAC5B;AACF;AACA,IAAI,wBAAwB,cAAc,aAAa;AAAA,EACrD,YAAY,UAAU,WAAW,uBAAuB,MAAM;AAC5D,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,YAAY;AACjB,SAAK,uBAAuB;AAC5B,SAAK,WAAW,QAAQ,QAAQ,EAAE,OAAO,MAAM,MAAM,MAAM,CAAC;AAAA,EAC9D;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,SAAS,KAAK,MAAM,KAAK,WAAW,CAAC;AAC1D,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,aAAa;AACjB,UAAM,QAAQ,CAAC;AACf,WAAO,MAAM,SAAS,KAAK,WAAW;AACpC,YAAM,OAAO,MAAM,KAAK,SAAS,KAAK;AACtC,UAAI,KAAK,MAAM;AACb,YAAI,KAAK,wBAAwB,MAAM,SAAS,GAAG;AACjD,iBAAO,EAAE,OAAO,OAAO,MAAM,MAAM;AAAA,QACrC;AACA,eAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,MACnC;AACA,YAAM,KAAK,KAAK,KAAK;AAAA,IACvB;AACA,WAAO,EAAE,OAAO,OAAO,MAAM,MAAM;AAAA,EACrC;AACF;AACA,IAAI,iBAAiB,cAAc,aAAa;AAAA,EAC9C,YAAY,UAAU,WAAW;AAC/B,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,YAAY;AACjB,SAAK,WAAW,QAAQ,QAAQ,EAAE,OAAO,MAAM,MAAM,MAAM,CAAC;AAAA,EAC9D;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,SAAS,KAAK,MAAM,KAAK,WAAW,CAAC;AAC1D,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,MAAM;AACX,YAAM,OAAO,MAAM,KAAK,SAAS,KAAK;AACtC,UAAI,KAAK,QAAQ,KAAK,UAAU,KAAK,KAAK,GAAG;AAC3C,eAAO;AAAA,MACT;AACA,cAAQ,KAAK,KAAK;AAAA,IACpB;AAAA,EACF;AACF;AACA,IAAI,cAAc,cAAc,aAAa;AAAA,EAC3C,YAAY,UAAU,YAAY;AAChC,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,UAAM,OAAO,MAAM,KAAK,SAAS,KAAK;AACtC,QAAI,KAAK,MAAM;AACb,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,UAAM,eAAe,oBAAoB,sBAAsB,KAAK,KAAK;AACzE,UAAM,SAAS,KAAK,UAAU,KAAK,KAAK;AACxC,UAAM,gBAAgB,oBAAoB,sBAAsB,MAAM;AACtE,eAAW,MAAM,cAAc;AAC7B,UAAI,CAAC,oBAAoB,eAAe,IAAI,aAAa,GAAG;AAC1D,WAAG,QAAQ;AAAA,MACb;AAAA,IACF;AACA,WAAO,EAAE,OAAO,QAAQ,MAAM,MAAM;AAAA,EACtC;AACF;AACA,IAAI,4BAA4B,cAAc,aAAa;AAAA,EACzD,YAAY,UAAU,SAAS;AAC7B,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,UAAU;AACf,SAAK,QAAQ;AACb,SAAK,WAAW,QAAQ,QAAQ,EAAE,OAAO,MAAM,MAAM,MAAM,CAAC;AAAA,EAC9D;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,SAAS,KAAK,MAAM,KAAK,WAAW,CAAC;AAC1D,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,MAAM;AACX,UAAI;AACF,eAAO,MAAM,KAAK,SAAS,KAAK;AAAA,MAClC,SAAS,IAAP;AACA,YAAI,CAAC,KAAK,QAAQ,EAAE,GAAG;AACrB,iBAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,QACnC;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACF;AACA,IAAI,mBAAmB,cAAc,aAAa;AAAA,EAChD,YAAY,UAAU,YAAY;AAChC,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,UAAM,OAAO,MAAM,KAAK,SAAS,KAAK;AACtC,QAAI,KAAK,MAAM;AACb,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,UAAM,eAAe,oBAAoB,sBAAsB,KAAK,KAAK;AACzE,UAAM,SAAS,MAAM,KAAK,UAAU,KAAK,KAAK;AAC9C,UAAM,gBAAgB,oBAAoB,sBAAsB,MAAM;AACtE,eAAW,MAAM,cAAc;AAC7B,UAAI,CAAC,oBAAoB,eAAe,IAAI,aAAa,GAAG;AAC1D,WAAG,QAAQ;AAAA,MACb;AAAA,IACF;AACA,WAAO,EAAE,OAAO,QAAQ,MAAM,MAAM;AAAA,EACtC;AACF;AACA,IAAI,oBAAoB,cAAc,aAAa;AAAA,EACjD,cAAc;AACZ,UAAM;AACN,SAAK,cAAc,IAAI,kBAAkB;AACzC,SAAK,WAAW,QAAQ,QAAQ,EAAE,OAAO,MAAM,MAAM,MAAM,CAAC;AAAA,EAC9D;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,SAAS,KAAK,MAAM,KAAK,WAAW,CAAC;AAC1D,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,KAAK,YAAY,OAAO,MAAM,GAAG;AACtC,UAAI,CAAC,MAAM,KAAK,KAAK,GAAG;AACtB,eAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,MACnC;AAAA,IACF;AACA,WAAO,EAAE,OAAO,KAAK,YAAY,MAAM,GAAG,MAAM,MAAM;AAAA,EACxD;AACF;AACA,IAAI,kBAAkB,cAAc,kBAAkB;AAAA,EACpD,YAAY,UAAU,YAAY;AAChC,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,UAAM,OAAO,MAAM,KAAK,SAAS,KAAK;AACtC,QAAI,KAAK,MAAM;AACb,aAAO;AAAA,IACT;AACA,UAAM,eAAe,oBAAoB,sBAAsB,KAAK,KAAK;AACzE,UAAM,cAAc,KAAK,UAAU,KAAK,KAAK;AAC7C,UAAM,gBAAgB,oBAAoB,sBAAsB,WAAW;AAC3E,SAAK,YAAY,QAAQ,WAAW;AACpC,eAAW,MAAM,cAAc;AAC7B,UAAI,CAAC,oBAAoB,eAAe,IAAI,aAAa,GAAG;AAC1D,WAAG,QAAQ;AAAA,MACb;AAAA,IACF;AACA,WAAO;AAAA,EACT;AACF;AACA,IAAI,kBAAkB,cAAc,aAAa;AAAA,EAC/C,YAAY,WAAW,kBAAkB;AACvC,UAAM;AACN,SAAK,mBAAmB;AACxB,SAAK,WAAW;AAChB,SAAK,WAAW;AAChB,SAAK,gBAAgB;AAAA,EACvB;AAAA,EACA,UAAU;AACR,UAAM,oBAAoB;AAC1B,WAAO,GAAG;AAAA,EACZ;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,cAAc,KAAK,QAAQ;AAChD,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,cAAc,UAAU;AAC5B,UAAM;AACN,QAAI,KAAK,YAAY,MAAM;AACzB,YAAM,iBAAiB,MAAM,KAAK,cAAc,KAAK;AACrD,UAAI,eAAe,MAAM;AACvB,eAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,MACnC;AACA,WAAK,WAAW,eAAe;AAC/B,UAAI,KAAK,oBAAoB,MAAM;AACjC,aAAK,WAAW,KAAK,SAAS,aAAa,KAAK,gBAAgB;AAAA,MAClE;AAAA,IACF;AACA,UAAM,aAAa,MAAM,KAAK,SAAS,KAAK;AAC5C,QAAI,WAAW,MAAM;AACnB,WAAK,WAAW;AAChB,aAAO,KAAK,cAAc,QAAQ;AAAA,IACpC;AACA,WAAO;AAAA,EACT;AACF;AACA,IAAI;AAAA,CACH,SAAS,kBAAkB;AAC1B,mBAAiB,iBAAiB,UAAU,KAAK;AACjD,mBAAiB,iBAAiB,cAAc,KAAK;AACrD,mBAAiB,iBAAiB,aAAa,KAAK;AACtD,GAAG,oBAAoB,kBAAkB,CAAC,EAAE;AAC5C,IAAI,cAAc,cAAc,aAAa;AAAA,EAC3C,YAAY,WAAW,eAAe,gBAAgB,MAAM;AAC1D,UAAM;AACN,SAAK,YAAY;AACjB,SAAK,eAAe;AACpB,SAAK,QAAQ;AACb,SAAK,iBAAiB;AAAA,EACxB;AAAA,EACA,UAAU;AACR,UAAM,oBAAoB;AAC1B,WAAO,IAAI;AAAA,EACb;AAAA,EACA,MAAM,UAAU,YAAY;AAC1B,UAAM;AACN,QAAI,eAAe;AACnB,QAAI,gBAAgB;AACpB,aAAS,QAAQ,WAAW;AAC1B,UAAI,qBAAqB,cAAc;AACrC,cAAM,SAAS,UAAU,KAAK;AAC9B,eAAO;AAAA,UACL,OAAO,OAAO,KAAK,CAAC,MAAM;AACxB;AACA,gBAAI,EAAE,MAAM;AACV;AAAA,YACF;AACA,mBAAO,EAAE;AAAA,UACX,CAAC;AAAA,UACD,SAAS;AAAA,QACX;AAAA,MACF,OAAO;AACL,eAAO,EAAE,OAAO,MAAM,SAAS,KAAK;AAAA,MACtC;AAAA,IACF;AACA,UAAM,SAAS,MAAM,mBAAmB,KAAK,WAAW,OAAO;AAC/D,QAAI,iBAAiB,eAAe;AAClC,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,QAAI,gBAAgB,GAAG;AACrB,cAAQ,KAAK;AAAA,aACN,gBAAgB;AACnB,gBAAM,IAAI,MAAM,qEAAqE,KAAK,QAAQ;AAAA,aAC/F,gBAAgB;AACnB,iBAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,aAC9B,gBAAgB;AAAA;AAAA;AAAA,IAGzB;AACA,SAAK;AACL,WAAO,EAAE,OAAO,QAAQ,MAAM,MAAM;AAAA,EACtC;AAAA,EACA,MAAM,OAAO;AACX,SAAK,iBAAiB,KAAK,UAAU,KAAK,cAAc;AACxD,WAAO,KAAK;AAAA,EACd;AACF;AACA,IAAI,mBAAmB,cAAc,aAAa;AAAA,EAChD,YAAY,UAAU,YAAY;AAChC,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,aAAa;AAClB,SAAK,SAAS,IAAI,WAAW,UAAU;AAAA,EACzC;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,SAAS;AACP,WAAO,CAAC,KAAK,OAAO,OAAO,GAAG;AAC5B,YAAM,IAAI,KAAK,SAAS,KAAK;AAC7B,WAAK,OAAO,KAAK,CAAC;AAAA,IACpB;AAAA,EACF;AAAA,EACA,OAAO;AACL,SAAK,OAAO;AACZ,WAAO,KAAK,OAAO,MAAM;AAAA,EAC3B;AACF;AACA,IAAI,kBAAkB,cAAc,iBAAiB;AAAA,EACnD,YAAY,UAAU,YAAY,MAAM;AACtC,UAAM,UAAU,UAAU;AAC1B,SAAK,WAAW;AAChB,SAAK,aAAa;AAClB,SAAK,oBAAoB;AACzB,SAAK,SAAS,YAAY,KAAK,QAAQ,aAAa,IAAI,EAAE,SAAS,CAAC;AACpE,SAAK,WAAW,QAAQ,QAAQ,EAAE,OAAO,MAAM,MAAM,MAAM,CAAC;AAAA,EAC9D;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,SAAS,KAAK,MAAM,KAAK,WAAW,CAAC;AAC1D,WAAO,KAAK;AAAA,EACd;AAAA,EACA,UAAU,MAAM;AACd,WAAO,KAAK,MAAM,KAAK,OAAO,IAAI,IAAI;AAAA,EACxC;AAAA,EACA,cAAc;AACZ,WAAO,KAAK,UAAU,KAAK,OAAO,OAAO,CAAC;AAAA,EAC5C;AAAA,EACA,MAAM,aAAa;AACjB,QAAI,CAAC,KAAK,mBAAmB;AAC3B,WAAK,OAAO;AAAA,IACd;AACA,WAAO,CAAC,KAAK,OAAO,QAAQ,GAAG;AAC7B,YAAM,cAAc,KAAK,YAAY;AACrC,YAAM,SAAS,MAAM,KAAK,OAAO,cAAc,WAAW;AAC1D,UAAI,OAAO,MAAM;AACf,aAAK,oBAAoB;AAAA,MAC3B,OAAO;AACL,aAAK,OAAO;AACZ,eAAO;AAAA,MACT;AAAA,IACF;AACA,WAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,EACnC;AACF;AAGA,IAAI,UAAU,MAAM;AAAA,EAClB,cAAc;AACZ,SAAK,OAAO;AAAA,EACd;AAAA,EACA,MAAM,WAAW,iBAAiB,MAAM;AACtC,UAAM,OAAO;AACb,iBAAa,OAAO,YAAY,GAAG,MAAM;AAAA,QACrC,WAAW;AACf,QAAInC;AACJ,QAAI,KAAK,SAAS,YAAY,KAAK,QAAQ,MAAM;AAC/C,MAAAA,QAAO,KAAK;AAAA,IACd,WAAW,gBAAgB;AACzB,MAAAA,QAAO,KAAK,KAAK,KAAK,OAAO,SAAS;AAAA,IACxC,OAAO;AACL,MAAAA,QAAO,KAAK,MAAM,KAAK,OAAO,SAAS;AAAA,IACzC;AACA,WAAO,sBAAsB,YAAY;AACvC,cAAQ,MAAM,KAAK,SAAS,GAAG,iBAAiB,WAAW,gBAAgB,eAAe;AAAA,IAC5F,GAAGA,KAAI;AAAA,EACT;AAAA,EACA,YAAY,SAAS;AACnB,UAAM,OAAO;AACb,QAAIA;AACJ,QAAI,KAAK,SAAS,YAAY,QAAQ,SAAS,UAAU;AACvD,MAAAA,QAAO;AAAA,IACT,WAAW,KAAK,QAAQ,QAAQ,QAAQ,QAAQ,MAAM;AACpD,MAAAA,QAAO,KAAK,OAAO,QAAQ;AAAA,IAC7B,OAAO;AACL,MAAAA,QAAO;AAAA,IACT;AACA,WAAO,sBAAsB,aAAa,MAAM,KAAK,SAAS,GAAG,YAAY,MAAM,QAAQ,SAAS,CAAC,GAAGA,KAAI;AAAA,EAC9G;AAAA,EACA,OAAO,WAAW;AAChB,UAAM,OAAO;AACb,QAAIA;AACJ,QAAI,KAAK,SAAS,UAAU;AAC1B,MAAAA,QAAO;AAAA,IACT,OAAO;AACL,MAAAA,QAAO;AAAA,IACT;AACA,WAAO,sBAAsB,YAAY;AACvC,cAAQ,MAAM,KAAK,SAAS,GAAG,OAAO,CAAC,MAAM,KAAK,MAAM,UAAU,CAAC,CAAC,CAAC;AAAA,IACvE,GAAGA,KAAI;AAAA,EACT;AAAA,EACA,MAAM,aAAa,GAAG;AACpB,YAAQ,MAAM,KAAK,SAAS,GAAG,aAAa,CAAC;AAAA,EAC/C;AAAA,EACA,IAAI,YAAY;AACd,UAAM,OAAO;AACb,WAAO,sBAAsB,YAAY;AACvC,cAAQ,MAAM,KAAK,SAAS,GAAG,IAAI,CAAC,MAAM,KAAK,MAAM,WAAW,CAAC,CAAC,CAAC;AAAA,IACrE,GAAG,KAAK,IAAI;AAAA,EACd;AAAA,EACA,SAAS,YAAY;AACnB,UAAM,OAAO;AACb,WAAO,sBAAsB,YAAY;AACvC,cAAQ,MAAM,KAAK,SAAS,GAAG,SAAS,UAAU;AAAA,IACpD,GAAG,KAAK,IAAI;AAAA,EACd;AAAA,EACA,SAAS,YAAY;AACnB,QAAI,cAAc,MAAM;AACtB,YAAM,IAAI,WAAW,2DAA2D;AAAA,IAClF;AACA,UAAM,OAAO;AACb,WAAO,sBAAsB,aAAa,MAAM,KAAK,SAAS,GAAG,SAAS,UAAU,GAAG,KAAK,IAAI;AAAA,EAClG;AAAA,EACA,OAAOO,SAAQ;AACb,UAAM,OAAO;AACb,QAAIP;AACJ,QAAI,KAAK,QAAQ,QAAQO,UAAS,GAAG;AACnC,MAAAP,QAAO,KAAK,OAAOO;AAAA,IACrB,WAAWA,YAAW,GAAG;AACvB,MAAAP,QAAO;AAAA,IACT,WAAW,KAAK,QAAQ,SAASO,YAAW,UAAUA,UAAS,IAAI;AACjE,MAAAP,QAAO;AAAA,IACT,OAAO;AACL,MAAAA,QAAO;AAAA,IACT;AACA,WAAO,sBAAsB,YAAY;AACvC,YAAM,mBAAmB,qBAAqB,aAAa,EAAE,OAAO,MAAM,KAAK,SAAS,GAAG,MAAM,MAAM,EAAE;AACzG,aAAO,yBAAyB,iBAAiB,KAAKO,OAAM,CAAC;AAAA,IAC/D,GAAGP,KAAI;AAAA,EACT;AAAA,EACA,KAAKO,SAAQ;AACX,UAAM,OAAO;AACb,QAAIP;AACJ,QAAI,KAAK,QAAQ,QAAQO,WAAU,KAAK,KAAK,QAAQA,SAAQ;AAC3D,MAAAP,QAAO,KAAK,OAAOO;AAAA,IACrB,WAAW,KAAK,QAAQ,SAAS,KAAK,OAAOA,WAAUA,YAAW,UAAUA,UAAS,IAAI;AACvF,MAAAP,QAAO;AAAA,IACT,OAAO;AACL,MAAAA,QAAO;AAAA,IACT;AACA,WAAO,sBAAsB,aAAa,MAAM,KAAK,SAAS,GAAG,KAAKO,OAAM,GAAGP,KAAI;AAAA,EACrF;AAAA,EACA,QAAQ,YAAY,MAAM,yBAAyB,MAAM;AACvD,QAAI,cAAc,QAAQ,aAAa,GAAG;AACxC,UAAI,KAAK,QAAQ,MAAM;AACrB,cAAM,IAAI,WAAW,0DAA0D;AAAA,MACjF,OAAO;AACL,cAAM,IAAI,WAAW,mNAAmN,KAAK,gBAAgB;AAAA,MAC/P;AAAA,IACF;AACA,UAAM,OAAO;AACb,UAAM,SAAS,YAAY,KAAK,QAAQ,aAAa,IAAI,EAAE,SAAS,CAAC;AACrE,WAAO,sBAAsB,YAAY;AACvC,UAAI,QAAQ,OAAO,MAAM;AACzB,UAAI,wBAAwB;AAC1B,iBAAS,OAAO,MAAM;AAAA,MACxB;AACA,cAAQ,MAAM,KAAK,SAAS,GAAG,QAAQ,YAAY,MAAM,SAAS,CAAC;AAAA,IACrE,GAAG,KAAK,IAAI;AAAA,EACd;AAAA,EACA,KAAKO,SAAQ;AACX,UAAM,OAAO;AACb,QAAIP;AACJ,QAAI,KAAK,QAAQ,QAAQ,KAAK,OAAOO,SAAQ;AAC3C,MAAAP,QAAOO;AAAA,IACT,WAAW,KAAK,QAAQ,QAAQ,KAAK,QAAQA,SAAQ;AACnD,MAAAP,QAAO,KAAK;AAAA,IACd,OAAO;AACL,MAAAA,QAAO;AAAA,IACT;AACA,WAAO,sBAAsB,aAAa,MAAM,KAAK,SAAS,GAAG,KAAKO,OAAM,GAAGP,KAAI;AAAA,EACrF;AAAA,EACA,MAAM,UAAU;AACd,QAAI,KAAK,SAAS,UAAU;AAC1B,YAAM,IAAI,MAAM,gDAAgD;AAAA,IAClE;AACA,YAAQ,MAAM,KAAK,SAAS,GAAG,QAAQ;AAAA,EACzC;AAAA,EACA,MAAM,iBAAiB;AACrB,QAAI,KAAK,SAAS,UAAU;AAC1B,YAAM,IAAI,MAAM,gDAAgD;AAAA,IAClE;AACA,YAAQ,MAAM,KAAK,SAAS,GAAG,eAAe;AAAA,EAChD;AACF;AACA,QAAQ,kBAAkB;AAC1B,SAAS,sBAAsB,YAAYA,QAAO,MAAM;AACtD,SAAO,IAAI,cAAc,QAAQ;AAAA,IAC/B,cAAc;AACZ,YAAM,GAAG,SAAS;AAClB,WAAK,OAAOA;AAAA,IACd;AAAA,IACA,MAAM,WAAW;AACf,aAAO,WAAW;AAAA,IACpB;AAAA,EACF,EAAE;AACJ;AACA,SAAS,MAAM,OAAO;AACpB,SAAO,sBAAsB,YAAY,kBAAkB,KAAK,GAAG,MAAM,MAAM;AACjF;AACA,SAAS,IAAI,UAAU;AACrB,MAAI,CAAC,YAAY,QAAQ,GAAG;AAC1B,UAAM,IAAI,MAAM,mDAAmD;AAAA,EACrE;AACA,MAAIA;AACJ,MAAI,MAAM,QAAQ,QAAQ,GAAG;AAC3B,aAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,MAAAA,QAAOA,SAAQ,OAAO,SAAS,IAAI,OAAO,KAAK,IAAIA,OAAM,SAAS,IAAI,IAAI;AAAA,IAC5E;AAAA,EACF,WAAW,oBAAoB,QAAQ;AACrC,eAAW,MAAM,UAAU;AACzB,MAAAA,QAAOA,SAAQ,OAAO,SAAS,IAAI,OAAO,KAAK,IAAIA,OAAM,SAAS,IAAI,IAAI;AAAA,IAC5E;AAAA,EACF;AACA,SAAO,sBAAsB,YAAY;AACvC,UAAM,UAAU,MAAM,mBAAmB,UAAU,CAAC,MAAM;AACxD,UAAI,aAAa,SAAS;AACxB,eAAO,EAAE,OAAO,EAAE,SAAS,GAAG,SAAS,MAAM;AAAA,MAC/C,WAAW,YAAY,CAAC,GAAG;AACzB,eAAO,EAAE,OAAO,MAAM,SAAS,KAAK;AAAA,MACtC,OAAO;AACL,cAAM,IAAI,MAAM,2EAA2E;AAAA,MAC7F;AAAA,IACF,CAAC;AACD,WAAO,mBAAmB,SAAS,gBAAgB,QAAQ;AAAA,EAC7D,GAAGA,KAAI;AACT;AACA,SAAS,gBAAgB,MAAM;AAC7B,MAAI,SAAS,MAAM;AACjB,WAAO;AAAA,EACT;AACA,QAAM,aAAa,KAAK;AACxB,MAAI,aAAa,UAAU,GAAG;AAC5B,UAAM,QAAQ,YAAY,IAAI;AAC9B,WAAO,EAAE,OAAO,SAAS,MAAM;AAAA,EACjC;AACA,SAAO,EAAE,OAAO,MAAM,SAAS,KAAK;AACtC;AACA,SAAS,YAAY,QAAQ;AAC3B,MAAI,OAAO,WAAW,GAAG;AACvB,UAAM,IAAI,MAAM,sCAAsC;AAAA,EACxD;AACA,MAAI,OAAO,cAAc,QAAQ;AAC/B,WAAO,MAAM,MAAM;AAAA,EACrB,OAAO;AACL,WAAO,OAAO,MAAM;AAAA,EACtB;AACF;AAGA,IAAI,kBAAkB,cAAc,QAAQ;AAAA,EAC1C,YAAY,QAAQ;AAClB,UAAM;AACN,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,MAAM,WAAW;AACf,UAAM,gBAAgB,MAAM,KAAK,MAAM,SAAS;AAChD,UAAM,eAAe,cAAc,WAAW;AAC9C,UAAM,eAAe,aAAa,MAAM,IAAI,EAAE,IAAI,CAAC,SAAS;AAC1D,UAAI,KAAK,SAAS,IAAI,GAAG;AACvB,eAAO,KAAK,MAAM,GAAG,EAAE;AAAA,MACzB;AACA,aAAO;AAAA,IACT,CAAC;AACD,WAAO;AAAA,EACT;AACF;AAGA,IAAI,aAAa;AACjB,IAAI,YAAY,OAAO,KAAK;AAC5B,IAAI,cAAc,OAAO,OAAO;AAChC,IAAI,cAAc,OAAO,OAAO;AAChC,IAAI,0BAA0B,OAAO,iBAAiB;AACtD,IAAI,8BAA8B,OAAO,cAAc;AACvD,IAAI,aAAa,cAAc,QAAQ;AAAA,EACrC,YAAY,QAAQ,WAAW;AAC7B,UAAM;AACN,SAAK,QAAQ;AACb,SAAK,YAAY;AACjB,SAAK,kBAAkB;AACvB,SAAK,uBAAuB;AAC5B,SAAK,gBAAgB;AACrB,SAAK,wBAAwB;AAC7B,SAAK,YAAY;AACjB,SAAK,kBAAkB;AACvB,SAAK,OAAO,IAAI,gBAAgB,MAAM;AACtC,QAAI,CAAC,WAAW;AACd,kBAAY,CAAC;AAAA,IACf;AACA,SAAK,YAAY,UAAU,cAAc,QAAQ,QAAQ;AACzD,SAAK,kBAAkB,UAAU;AACjC,SAAK,gBAAgB,UAAU;AAC/B,SAAK,wBAAwB,UAAU;AACvC,QAAI,UAAU,iBAAiB;AAC7B,mBAAa,OAAO,UAAU,aAAa,MAAM,MAAM,gEAAgE;AACvH,WAAK,kBAAkB;AACvB,WAAK,YAAY;AAAA,IACnB,OAAO;AACL,WAAK,YAAY,UAAU,YAAY,UAAU,YAAY;AAAA,IAC/D;AAAA,EACF;AAAA,EACA,MAAM,cAAc;AAClB,QAAI,CAAC,KAAK,sBAAsB;AAC9B,YAAM,KAAK,eAAe;AAAA,IAC5B;AACA,WAAO,KAAK,wBAAwB,OAAO,KAAK,KAAK,aAAa,IAAI,KAAK;AAAA,EAC7E;AAAA,EACA,MAAM,iBAAiB;AACrB,UAAM,sBAAsB,MAAM,KAAK,oBAAoB;AAC3D,QAAI,CAAC,KAAK,mBAAmB,CAAC,qBAAqB;AACjD,YAAM,IAAI,MAAM,2DAA2D;AAAA,IAC7E,WAAW,KAAK,mBAAmB,qBAAqB;AACtD,mBAAa,OAAO,oBAAoB,WAAW,KAAK,gBAAgB,QAAQ,MAAM,yCAAyC,KAAK,gBAAgB,OAAO,SAAS,IAAI,oEAAoE,oBAAoB,OAAO,SAAS,IAAI,IAAI;AAAA,IAC1R;AACA,QAAI,CAAC,KAAK,iBAAiB;AACzB,WAAK,kBAAkB;AAAA,IACzB;AACA,UAAM,SAAS,KAAK,gBAAgB,OAAO,CAAC,UAAU,SAAS;AAC7D,eAAS,QAAQ,SAAS,QAAQ,KAAK;AACvC,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AACL,UAAM,iBAAiB,OAAO,KAAK,MAAM,EAAE,OAAO,CAAC,SAAS,OAAO,QAAQ,CAAC;AAC5E,iBAAa,OAAO,eAAe,WAAW,GAAG,MAAM,mCAAmC,eAAe,SAAS,CAAC;AACnH,QAAI,KAAK,eAAe;AACtB,iBAAW,OAAO,OAAO,KAAK,KAAK,aAAa,GAAG;AACjD,cAAMS,SAAQ,KAAK,gBAAgB,QAAQ,GAAG;AAC9C,YAAIA,WAAU,IAAI;AAChB,gBAAM,IAAI,MAAM,cAAc,MAAM,yEAAyE,KAAK,gBAAgB,SAAS,IAAI,IAAI;AAAA,QACrJ;AAAA,MACF;AAAA,IACF;AACA,SAAK,uBAAuB;AAAA,EAC9B;AAAA,EACA,MAAM,sBAAsB;AAC1B,QAAI,KAAK,WAAW;AAClB,YAAM,OAAO,MAAM,KAAK,KAAK,SAAS;AACtC,YAAM,eAAe,MAAM,KAAK,KAAK;AACrC,UAAI,aAAa,MAAM;AACrB,cAAM,IAAI,MAAM,oCAAoC;AAAA,MACtD;AACA,YAAM,YAAY,aAAa;AAC/B,YAAM,UAAU,KAAK,SAAS,WAAW,KAAK;AAC9C,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,MAAM,WAAW;AACf,QAAI,CAAC,KAAK,sBAAsB;AAC9B,YAAM,KAAK,eAAe;AAAA,IAC5B;AACA,QAAIQ,SAAQ,MAAM,KAAK,KAAK,SAAS;AACrC,QAAI,KAAK,WAAW;AAClB,MAAAA,SAAQA,OAAM,KAAK,CAAC;AAAA,IACtB;AACA,WAAOA,OAAM,IAAI,CAAC,MAAM,KAAK,gBAAgB,CAAC,CAAC;AAAA,EACjD;AAAA,EACA,gBAAgB,MAAM;AACpB,UAAM,SAAS,KAAK,SAAS,IAAI;AACjC,UAAM,WAAW,CAAC;AAClB,UAAME,UAAS,CAAC;AAChB,aAAS,KAAK,GAAG,KAAK,KAAK,gBAAgB,QAAQ,MAAM;AACvD,YAAM,MAAM,KAAK,gBAAgB;AACjC,YAAML,UAAS,KAAK,gBAAgB,KAAK,cAAc,OAAO;AAC9D,UAAI,KAAK,yBAAyB,CAACA,SAAQ;AACzC;AAAA,MACF,OAAO;AACL,cAAM,QAAQ,OAAO;AACrB,YAAI,cAAc;AAClB,YAAI,UAAU,IAAI;AAChB,cAAIA,WAAUA,QAAO,YAAY,QAAQ;AACvC,0BAAcA,QAAO;AAAA,UACvB,WAAWA,YAAWA,QAAO,YAAYA,QAAO,UAAU;AACxD,kBAAM,IAAI,MAAM,mBAAmB,8BAA8B,MAAM;AAAA,UACzE,OAAO;AACL,0BAAc;AAAA,UAChB;AAAA,QACF,OAAO;AACL,gBAAM,aAAa,OAAO,KAAK;AAC/B,cAAI,MAAM,UAAU,GAAG;AACrB,gBAAIA,WAAUA,QAAO,UAAU,QAAQ;AACrC,4BAAc,KAAK,WAAW,KAAK;AAAA,YACrC,OAAO;AACL,4BAAc;AAAA,YAChB;AAAA,UACF,WAAW,CAACA,WAAU,CAACA,QAAO,OAAO;AACnC,0BAAc;AAAA,UAChB,OAAO;AACL,oBAAQA,QAAO;AAAA,mBACR;AACH,8BAAc;AACd;AAAA,mBACG;AACH,8BAAc,KAAK,MAAM,UAAU;AACnC;AAAA,mBACG;AACH,8BAAc,KAAK,WAAW,KAAK;AACnC;AAAA;AAEA,8BAAc;AAAA;AAAA,UAEpB;AAAA,QACF;AACA,QAAAA,WAAUA,QAAO,UAAUK,QAAO,OAAO,cAAc,SAAS,OAAO;AAAA,MACzE;AAAA,IACF;AACA,QAAI,OAAO,KAAKA,OAAM,EAAE,WAAW,GAAG;AACpC,aAAO;AAAA,IACT,OAAO;AACL,aAAO,EAAE,IAAI,UAAU,IAAIA,QAAO;AAAA,IACpC;AAAA,EACF;AAAA,EACA,WAAW,OAAO;AAChB,QAAI,UAAU,OAAO,MAAM,YAAY,MAAM,QAAQ;AACnD,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,SAAS,MAAM,uBAAuB,MAAM;AAC1C,UAAM,SAAS,CAAC;AAChB,QAAI,aAAa;AACjB,UAAM,aAAa,KAAK;AACxB,QAAI,eAAe;AACnB,aAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,cAAQ;AAAA,aACD;AACH,kBAAQ,KAAK,OAAO,EAAE;AAAA,iBACf;AACH,2BAAa,KAAK;AAClB,6BAAe;AACf;AAAA,iBACG,KAAK;AACR,2BAAa,KAAK;AAClB,kBAAI,KAAK,cAAc,OAAO,KAAK,iBAAiB;AAClD;AAAA,cACF;AACA,qBAAO,KAAK,EAAE;AACd,6BAAe;AACf;AAAA;AAEA,6BAAe;AACf,2BAAa;AACb;AAAA;AAEJ;AAAA,aACG;AACH,kBAAQ,KAAK,OAAO,EAAE;AAAA,iBACf,KAAK;AACR,qBAAO,KAAK,KAAK,UAAU,YAAY,EAAE,CAAC;AAC1C,6BAAe;AACf,2BAAa,KAAK;AAClB;AAAA;AAAA;AAGJ;AAAA,aACG;AACH,kBAAQ,KAAK,OAAO,EAAE;AAAA,iBACf;AACH,6BAAe;AACf;AAAA;AAAA;AAGJ;AAAA,aACG;AACH,kBAAQ,KAAK,OAAO,EAAE;AAAA,iBACf,KAAK;AACR,qBAAO,KAAK,KAAK,UAAU,YAAY,KAAK,CAAC,CAAC;AAC9C,6BAAe;AACf,2BAAa,KAAK;AAClB;AAAA,iBACG;AACH,6BAAe;AACf;AAAA;AAEA,6BAAe;AACf;AAAA;AAEJ;AAAA,aACG;AACH,kBAAQ,KAAK,OAAO,EAAE;AAAA,iBACf;AACH,6BAAe;AACf;AAAA;AAAA;AAGJ;AAAA;AAAA;AAAA,IAGN;AACA,QAAI,iBAAiB,yBAAyB;AAC5C,aAAO,KAAK,KAAK,UAAU,YAAY,aAAa,CAAC,CAAC;AAAA,IACxD,OAAO;AACL,aAAO,KAAK,KAAK,UAAU,UAAU,CAAC;AAAA,IACxC;AACA,QAAI,wBAAwB,OAAO,WAAW,KAAK,gBAAgB,QAAQ;AACzE,YAAM,IAAI,MAAM,wCAAwC,KAAK,gBAAgB,qCAAqC,QAAQ;AAAA,IAC5H;AACA,WAAO;AAAA,EACT;AACF;AAGA,IAAI,qBAAqB,cAAc,aAAa;AAAA,EAClD,YAAY,kBAAkB;AAC5B,UAAM;AACN,SAAK,mBAAmB;AACxB,SAAK,WAAW;AAChB,SAAK,UAAU,iBAAiB,WAAW;AAC3C,UAAM,cAAc,KAAK,KAAK,KAAK,OAAO;AAC1C,QAAI,KAAK,UAAU,KAAK,cAAc,KAAK,cAAc,MAAM,CAAC,OAAO,UAAU,WAAW,GAAG;AAC7F,YAAM,IAAI,MAAM,gFAAgF,KAAK,SAAS;AAAA,IAChH;AACA,SAAK,YAAY,iBAAiB,2BAA2B;AAC7D,SAAK,eAAe,iBAAiB;AACrC,SAAK,uBAAuB,iBAAiB,wBAAwB,KAAK;AAC1E,SAAK,wBAAwB,iBAAiB;AAC9C,SAAK,wBAAwB,iBAAiB,yBAAyB;AACvE,SAAK,qBAAqB,iBAAiB,uBAAuB,QAAQ,QAAQ;AAClF,SAAK,kBAAkB,iBAAiB,oBAAoB,OAAO,OAAO;AAC1E,QAAI,CAAC,KAAK,sBAAsB,CAAC,KAAK,iBAAiB;AACrD,YAAM,IAAI,MAAM,sGAAsG;AAAA,IACxH;AAAA,EACF;AAAA,EACA,UAAU;AACR,WAAO;AAAA,EACT;AAAA,EACA,aAAa,OAAO,mBAAmB,CAAC,GAAG;AACzC,QAAI,CAAC,IAAI,EAAE,IAAI,YAAY,GAAG;AAC5B,YAAM,IAAI,MAAM,0DAA0D;AAAA,IAC5E;AACA,UAAM,qBAAqB,IAAI,mBAAmB,gBAAgB;AAClE,UAAM,mBAAmB,MAAM;AAC/B,WAAO;AAAA,EACT;AAAA,EACA,MAAM,QAAQ;AACZ,QAAI;AACF,WAAK,SAAS,MAAM,UAAU,aAAa,aAAa;AAAA,QACtD,OAAO,KAAK,yBAAyB,OAAO,OAAO,KAAK;AAAA,QACxD,OAAO;AAAA,MACT,CAAC;AAAA,IACH,SAAS,IAAP;AACA,YAAM,IAAI,MAAM,iDAAiD,GAAG,SAAS;AAAA,IAC/E;AACA,QAAI,CAAC,KAAK,QAAQ;AAChB,YAAM,IAAI,MAAM,yCAAyC;AAAA,IAC3D;AACA,UAAM,iBAAiB,OAAO,gBAAgB,OAAO;AACrD,SAAK,eAAe,IAAI,eAAe;AACvC,QAAI,CAAC,KAAK,cAAc;AACtB,WAAK,eAAe,KAAK,aAAa;AAAA,IACxC,WAAW,KAAK,aAAa,eAAe,KAAK,cAAc;AAC7D,YAAM,IAAI,MAAM,wCAAwC,KAAK,yBAAyB,KAAK,aAAa,YAAY;AAAA,IACtH;AACA,UAAM,eAAe,KAAK,aAAa,wBAAwB,KAAK,MAAM;AAC1E,SAAK,WAAW,KAAK,aAAa,eAAe;AACjD,SAAK,SAAS,UAAU,KAAK,UAAU;AACvC,SAAK,SAAS,wBAAwB,KAAK;AAC3C,iBAAa,QAAQ,KAAK,QAAQ;AAClC,SAAK,WAAW,IAAI,aAAa,KAAK,OAAO;AAC7C,SAAK,WAAW,IAAI,aAAa,KAAK,OAAO;AAC7C;AAAA,EACF;AAAA,EACA,MAAM,OAAO;AACX,QAAI,KAAK,UAAU;AACjB,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,QAAI;AACJ,QAAI;AACJ,UAAM,iBAAiB,MAAM,KAAK,aAAa;AAC/C,QAAI,KAAK,oBAAoB;AAC3B,YAAM,WAAW,KAAK,aAAa,eAAe,aAAa;AAC/D,0BAAoB,KAAK,4BAA4B,UAAU,CAAC,KAAK,WAAW,KAAK,sBAAsB,CAAC,CAAC;AAAA,IAC/G;AACA,QAAI,KAAK,iBAAiB;AACxB,YAAM,WAAW,KAAK,aAAa,eAAe,aAAa;AAC/D,uBAAiB,KAAK,4BAA4B,UAAU,CAAC,KAAK,YAAY,KAAK,SAAS,CAAC,CAAC;AAAA,IAChG;AACA,WAAO;AAAA,MACL,OAAO,EAAE,eAAe,mBAAmB,YAAY,eAAe;AAAA,MACtE,MAAM;AAAA,IACR;AAAA,EACF;AAAA,EACA,MAAM,UAAU;AACd,YAAQ,MAAM,KAAK,KAAK,GAAG;AAAA,EAC7B;AAAA,EACA,MAAM,eAAe;AACnB,UAAM,gBAAgB,CAAC;AACvB,UAAM,gBAAgB,CAAC;AACvB,QAAI,gBAAgB;AACpB,WAAO,IAAI,QAAQ,CAAC,YAAY;AAC9B,YAAM,aAAa,YAAY,MAAM;AACnC,YAAI,KAAK,oBAAoB;AAC3B,eAAK,SAAS,sBAAsB,KAAK,QAAQ;AACjD,cAAI,KAAK,SAAS,OAAO,WAAW;AAClC,oBAAQ,EAAE,eAAe,cAAc,CAAC;AAAA,UAC1C;AACA,wBAAc,KAAK,KAAK,SAAS,MAAM,GAAG,KAAK,oBAAoB,CAAC;AAAA,QACtE;AACA,YAAI,KAAK,iBAAiB;AACxB,eAAK,SAAS,uBAAuB,KAAK,QAAQ;AAClD,wBAAc,KAAK,KAAK,SAAS,MAAM,CAAC;AAAA,QAC1C;AACA,YAAI,EAAE,kBAAkB,KAAK,WAAW;AACtC,wBAAc,UAAU;AACxB,kBAAQ,EAAE,eAAe,cAAc,CAAC;AAAA,QAC1C;AAAA,MACF,GAAG,KAAK,UAAU,KAAK,eAAe,GAAG;AAAA,IAC3C,CAAC;AAAA,EACH;AAAA,EACA,OAAO;AACL,QAAI,CAAC,KAAK,UAAU;AAClB,WAAK,WAAW;AAChB,WAAK,SAAS,WAAW;AACzB,WAAK,aAAa,MAAM;AACxB,UAAI,KAAK,UAAU,QAAQ,KAAK,OAAO,UAAU,EAAE,SAAS,GAAG;AAC7D,aAAK,OAAO,UAAU,EAAE,GAAG,KAAK;AAAA,MAClC;AAAA,IACF;AAAA,EACF;AAAA,EACA,UAAU;AACR,UAAM,IAAI,MAAM,iDAAiD;AAAA,EACnE;AAAA,EACA,gBAAgB;AACd,WAAO,KAAK;AAAA,EACd;AAAA,EACA,aAAa,OAAO;AAClB,UAAM,YAAY,MAAM,GAAG;AAC3B,UAAM,WAAW,IAAI,aAAa,MAAM,SAAS,SAAS;AAC1D,UAAM,QAAQ,CAAC,MAAM,OAAO,SAAS,IAAI,MAAM,KAAK,SAAS,CAAC;AAC9D,WAAO;AAAA,EACT;AAAA,EACA,4BAA4B,UAAU,OAAO;AAC3C,UAAM,OAAO,IAAI,aAAa,aAAa,cAAc,KAAK,CAAC;AAC/D,SAAK,IAAI,UAAU,KAAK,SAAS,SAAS,MAAM;AAChD,WAAO,OAAO,MAAM,KAAK;AAAA,EAC3B;AACF;AAGA,IAAI,iBAAiB,cAAc,aAAa;AAAA,EAC9C,YAAY,oBAAoB,cAAc;AAC5C,UAAM;AACN,SAAK,qBAAqB;AAC1B,SAAK,eAAe;AACpB,SAAK,WAAW;AAChB,SAAK,SAAS;AACd,QAAI,KAAK,aAAa,GAAG;AACvB,WAAK,SAAS;AACd,WAAK,WAAW,CAAC,KAAK,aAAa,cAAc,KAAK,aAAa,WAAW;AAC9E,WAAK,aAAa,SAAS,CAAC,CAAC,GAAG,OAAO;AACvC,UAAI,KAAK,aAAa,YAAY;AAChC,cAAM,qBAAqB,KAAK,aAAa,cAAc,IAAI,KAAK,mBAAmB;AACvF,cAAM,sBAAsB,KAAK,aAAa,eAAe,IAAI,KAAK,mBAAmB;AACzF,cAAM,kBAAkB,IAAI,sBAAsB;AAClD,cAAM,mBAAmB,IAAI,uBAAuB;AACpD,cAAM,eAAe,iBAAiB;AACtC,cAAM,gBAAgB,sBAAsB;AAC5C,aAAK,UAAU,SAAS,CAAC,iBAAiB,gBAAgB,eAAe,YAAY,GAAG,CAAC,GAAG,CAAC,CAAC;AAAA,MAChG,OAAO;AACL,aAAK,UAAU,SAAS,CAAC,GAAG,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAAA,MAC9C;AAAA,IACF;AAAA,EACF;AAAA,EACA,UAAU;AACR,WAAO;AAAA,EACT;AAAA,EACA,aAAa,OAAO,oBAAoB,eAAe,CAAC,GAAG;AACzD,QAAI,CAAC,IAAI,EAAE,IAAI,YAAY,GAAG;AAC5B,YAAM,IAAI,MAAM,0DAA0D;AAAA,IAC5E;AACA,QAAI,CAAC,oBAAoB;AACvB,2BAAqB,SAAS,cAAc,OAAO;AACnD,UAAI,CAAC,aAAa,eAAe,CAAC,aAAa,cAAc;AAC3D,cAAM,IAAI,MAAM,wGAAwG;AAAA,MAC1H;AACA,yBAAmB,QAAQ,aAAa;AACxC,yBAAmB,SAAS,aAAa;AAAA,IAC3C;AACA,UAAM,iBAAiB,IAAI,eAAe,oBAAoB,YAAY;AAC1E,UAAM,eAAe,MAAM;AAC3B,WAAO;AAAA,EACT;AAAA,EACA,MAAM,QAAQ;AACZ,QAAI,KAAK,aAAa,YAAY;AAChC,mBAAa,OAAO,KAAK,aAAa,eAAe,UAAU,KAAK,aAAa,eAAe,eAAe,MAAM,+BAA+B,KAAK,aAAa,oDAAoD;AAAA,IAC5N;AACA,QAAI;AACF,WAAK,SAAS,MAAM,UAAU,aAAa,aAAa;AAAA,QACtD,OAAO;AAAA,UACL,UAAU,KAAK,aAAa;AAAA,UAC5B,YAAY,KAAK,aAAa,aAAa,KAAK,aAAa,aAAa;AAAA,UAC1E,OAAO,KAAK,mBAAmB;AAAA,UAC/B,QAAQ,KAAK,mBAAmB;AAAA,QAClC;AAAA,MACF,CAAC;AAAA,IACH,SAAS,IAAP;AACA,SAAG,UAAU,iDAAiD,GAAG;AACjE,YAAM;AAAA,IACR;AACA,QAAI,CAAC,KAAK,QAAQ;AAChB,YAAM,IAAI,MAAM,qCAAqC;AAAA,IACvD;AACA,QAAI;AACF,WAAK,mBAAmB,YAAY,KAAK;AAAA,IAC3C,SAAS,OAAP;AACA,cAAQ,IAAI,KAAK;AACjB,WAAK,mBAAmB,MAAM,OAAO,IAAI,gBAAgB,KAAK,MAAM;AAAA,IACtE;AACA,SAAK,mBAAmB,KAAK;AAC7B,SAAK,WAAW;AAChB,WAAO,IAAI,QAAQ,CAAC,YAAY;AAC9B,WAAK,mBAAmB,mBAAmB,MAAM;AAC/C,gBAAQ;AAAA,MACV;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,MAAM,OAAO;AACX,QAAI,KAAK,UAAU;AACjB,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,QAAI;AACJ,QAAI;AACF,YAAM,gBAAgB,WAAW,KAAK,kBAAkB;AAAA,IAC1D,SAAS,IAAP;AACA,YAAM,IAAI,MAAM,4CAA4C,KAAK,UAAU,EAAE,GAAG;AAAA,IAClF;AACA,QAAI,KAAK,QAAQ;AACf,UAAI;AACF,eAAO,EAAE,OAAO,KAAK,mBAAmB,GAAG,GAAG,MAAM,MAAM;AAAA,MAC5D,SAAS,IAAP;AACA,cAAM,IAAI,MAAM,oCAAoC,GAAG,SAAS;AAAA,MAClE,UAAE;AACA,YAAI,QAAQ;AAAA,MACd;AAAA,IACF,OAAO;AACL,aAAO,EAAE,OAAO,KAAK,MAAM,MAAM;AAAA,IACnC;AAAA,EACF;AAAA,EACA,eAAe;AACb,QAAI,KAAK,aAAa,eAAe,KAAK,aAAa,iBAAiB,KAAK,mBAAmB,UAAU,KAAK,aAAa,eAAe,KAAK,mBAAmB,WAAW,KAAK,aAAa,eAAe;AAC7M,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT;AAAA,EACA,mBAAmB,KAAK;AACtB,WAAO,KAAK,MAAM;AAChB,YAAM,gBAAgB,WAAW,KAAK,KAAK,SAAS,GAAG,CAAC;AACxD,UAAI;AACJ,qBAAe,MAAM,cAAc,eAAe,KAAK,SAAS,KAAK,YAAY,KAAK,UAAU,UAAU;AAC1G,YAAM,QAAQ,aAAa;AAC3B,aAAO,QAAQ,cAAc,MAAM,MAAM,CAAC,CAAC;AAAA,IAC7C,CAAC;AAAA,EACH;AAAA,EACA,MAAM,UAAU;AACd,YAAQ,MAAM,KAAK,KAAK,GAAG;AAAA,EAC7B;AAAA,EACA,OAAO;AACL,UAAM,SAAS,KAAK,OAAO,UAAU;AACrC,WAAO,QAAQ,CAAC,UAAU,MAAM,KAAK,CAAC;AACtC,QAAI;AACF,WAAK,mBAAmB,YAAY;AAAA,IACtC,SAAS,OAAP;AACA,cAAQ,IAAI,KAAK;AACjB,WAAK,mBAAmB,MAAM;AAAA,IAChC;AACA,SAAK,WAAW;AAAA,EAClB;AAAA,EACA,UAAU;AACR,UAAM,IAAI,MAAM,iDAAiD;AAAA,EACnE;AACF;AAGA,IAAI,aAAa,MAAM;AACvB;AAGA,IAAI,iBAAiB,cAAc,aAAa;AAAA,EAC9C,MAAM,WAAW;AACf,WAAO,IAAI,cAAc,MAAM,SAAS;AAAA,EAC1C;AACF;AACA,IAAI,gBAAgB,cAAc,eAAe;AAAA,EAC/C,YAAY,UAAU,WAAW;AAC/B,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,OAAO,IAAI,kBAAkB,UAAU,SAAS;AAAA,EACvD;AAAA,EACA,UAAU;AACR,WAAO,KAAK,KAAK,QAAQ;AAAA,EAC3B;AAAA,EACA,MAAM,OAAO;AACX,WAAO,KAAK,KAAK,KAAK;AAAA,EACxB;AACF;AACA,IAAI,oBAAoB,cAAc,kBAAkB;AAAA,EACtD,YAAY,UAAU,WAAW;AAC/B,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,YAAY;AACjB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ,eAAe,KAAK;AAAA,EACtD;AAAA,EACA,MAAM,OAAO;AACX,UAAM,cAAc,MAAM,KAAK,SAAS,KAAK;AAC7C,QAAI,YAAY,MAAM;AACpB,UAAI,KAAK,cAAc,IAAI;AACzB,eAAO;AAAA,MACT;AACA,WAAK,YAAY,KAAK,KAAK,SAAS;AACpC,WAAK,YAAY;AACjB,aAAO;AAAA,IACT;AACA,UAAMF,SAAQ,YAAY,MAAM,MAAM,KAAK,SAAS;AACpD,IAAAA,OAAM,KAAK,KAAK,YAAYA,OAAM;AAClC,eAAW,QAAQA,OAAM,MAAM,GAAG,EAAE,GAAG;AACrC,WAAK,YAAY,KAAK,IAAI;AAAA,IAC5B;AACA,SAAK,YAAYA,OAAMA,OAAM,SAAS;AACtC,WAAO;AAAA,EACT;AACF;AAGA,IAAI,oBAAoB,cAAc,aAAa;AAAA,EACjD,aAAa;AACX,WAAO,IAAI,aAAa,IAAI;AAAA,EAC9B;AACF;AACA,IAAI,eAAe,cAAc,eAAe;AAAA,EAC9C,YAAY,UAAU;AACpB,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,OAAO,IAAI,iBAAiB,QAAQ;AAAA,EAC3C;AAAA,EACA,UAAU;AACR,WAAO,KAAK,KAAK,QAAQ;AAAA,EAC3B;AAAA,EACA,MAAM,OAAO;AACX,WAAO,KAAK,KAAK,KAAK;AAAA,EACxB;AACF;AACA,IAAI,mBAAmB,cAAc,kBAAkB;AAAA,EACrD,YAAY,UAAU;AACpB,UAAM;AACN,SAAK,WAAW;AAChB,QAAI,IAAI,EAAE,IAAI,YAAY,GAAG;AAC3B,WAAK,UAAU,IAAI,YAAY,OAAO;AAAA,IACxC,OAAO;AACL,YAAM,EAAE,cAAc,IAAI,uBAAuB;AACjD,WAAK,UAAU,IAAI,cAAc,MAAM;AAAA,IACzC;AAAA,EACF;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,UAAM,cAAc,MAAM,KAAK,SAAS,KAAK;AAC7C,QAAI;AACJ,QAAI,YAAY,MAAM;AACpB,aAAO;AAAA,IACT,OAAO;AACL,cAAQ,YAAY;AAAA,IACtB;AACA,QAAI;AACJ,QAAI,IAAI,EAAE,IAAI,YAAY,GAAG;AAC3B,aAAO,KAAK,QAAQ,OAAO,OAAO,EAAE,QAAQ,KAAK,CAAC;AAAA,IACpD,OAAO;AACL,aAAO,KAAK,QAAQ,MAAM,OAAO,KAAK,MAAM,MAAM,CAAC;AAAA,IACrD;AACA,SAAK,YAAY,KAAK,IAAI;AAC1B,WAAO;AAAA,EACT;AACF;AAGA,IAAI,oBAAoB,cAAc,kBAAkB;AAAA,EACtD,YAAY,MAAMX,WAAU,CAAC,GAAG;AAC9B,UAAM;AACN,SAAK,OAAO;AACZ,SAAK,UAAUA;AACf,iBAAa,OAAO,gBAAgB,eAAe,IAAI,EAAE,IAAI,YAAY,IAAI,gBAAgB,QAAQ,gBAAgB,OAAO,QAAQ,MAAM,sEAAsE;AAChN,SAAK,SAASA,SAAQ,UAAU;AAChC,SAAK,YAAYA,SAAQ,aAAa,OAAO;AAAA,EAC/C;AAAA,EACA,UAAU;AACR,WAAO,cAAc,KAAK;AAAA,EAC5B;AAAA,EACA,MAAM,OAAO;AACX,QAAI,KAAK,WAAW,KAAK,gBAAgB,aAAa,KAAK,KAAK,aAAa,KAAK,KAAK,OAAO;AAC5F,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,UAAM,QAAQ,IAAI,QAAQ,CAAC,SAAS,WAAW;AAC7C,YAAM,MAAM,KAAK,SAAS,KAAK;AAC/B,UAAI,KAAK,gBAAgB,YAAY;AACnC,gBAAQ,IAAI,WAAW,KAAK,KAAK,MAAM,KAAK,QAAQ,GAAG,CAAC,CAAC;AAAA,MAC3D,OAAO;AACL,cAAM,aAAa,IAAI,WAAW;AAClC,mBAAW,SAAS,CAAC,UAAU;AAC7B,cAAI,OAAO,WAAW;AACtB,cAAI,gBAAgB,aAAa;AAC/B,mBAAO,IAAI,WAAW,IAAI;AAAA,UAC5B;AACA,cAAI,EAAE,gBAAgB,aAAa;AACjC,mBAAO,OAAO,IAAI,UAAU,mCAAmC,CAAC;AAAA,UAClE;AACA,kBAAQ,IAAI;AAAA,QACd;AACA,mBAAW,UAAU,CAAC,UAAU;AAC9B,iBAAO,OAAO,IAAI,MAAM,SAAS,CAAC;AAAA,QACpC;AACA,mBAAW,UAAU,CAAC,UAAU;AAC9B,iBAAO,OAAO,IAAI,MAAM,MAAM,IAAI,CAAC;AAAA,QACrC;AACA,cAAM,SAAS,KAAK,KAAK,MAAM,KAAK,QAAQ,GAAG;AAC/C,mBAAW,kBAAkB,MAAM;AAAA,MACrC;AACA,WAAK,SAAS;AAAA,IAChB,CAAC;AACD,WAAO,EAAE,OAAO,MAAM,OAAO,MAAM,MAAM;AAAA,EAC3C;AACF;AAGA,eAAe,iBAAiB,KAAKA,WAAU,CAAC,GAAG,WAAW;AAC5D,MAAI;AACJ,MAAI;AACJ,MAAI,OAAO,QAAQ,UAAU;AAC3B,gBAAY;AAAA,EACd,OAAO;AACL,gBAAY,IAAI;AAChB,kBAAc,0BAA0B,GAAG;AAAA,EAC7C;AACA,QAAM,WAAW,OAAO,aAAa,aAAa,OAAO,WAAW,WAAW;AAC/E,MAAI,SAAS,IAAI;AACf,UAAM,aAAa,IAAI,WAAW,MAAM,SAAS,YAAY,CAAC;AAC9D,WAAO,IAAI,kBAAkB,YAAYA,QAAO;AAAA,EAClD,OAAO;AACL,UAAM,IAAI,MAAM,SAAS,UAAU;AAAA,EACrC;AACF;AACA,IAAI,4BAA4B,CAAC,YAAY;AAC3C,QAAMF,SAAQ;AAAA,IACZ,QAAQ,QAAQ;AAAA,IAChB,SAAS,QAAQ;AAAA,IACjB,MAAM,QAAQ;AAAA,IACd,MAAM,QAAQ;AAAA,IACd,aAAa,QAAQ;AAAA,IACrB,OAAO,QAAQ;AAAA,IACf,UAAU,QAAQ;AAAA,IAClB,UAAU,QAAQ;AAAA,IAClB,WAAW,QAAQ;AAAA,EACrB;AACA,SAAOA;AACT;AAGA,SAAS,YAAY,QAAQ;AAC3B,SAAO,OAAO,WAAW,YAAY,OAAO,MAAM,GAAG,CAAC,MAAM;AAC9D;AAGA,IAAI,iBAAiB,cAAc,WAAW;AAAA,EAC5C,YAAY,QAAQE,WAAU,CAAC,GAAG;AAChC,UAAM;AACN,SAAK,QAAQ;AACb,SAAK,UAAUA;AAAA,EACjB;AAAA,EACA,MAAM,WAAW;AACf,QAAI,YAAY,KAAK,KAAK,KAAK,IAAI,EAAE,IAAI,SAAS,GAAG;AACnD,YAAM,KAAK,WAAW;AACtB,WAAK,QAAQ,GAAG,aAAa,KAAK,MAAM,MAAM,CAAC,CAAC;AAAA,IAClD;AACA,WAAO,IAAI,kBAAkB,KAAK,OAAO,KAAK,OAAO;AAAA,EACvD;AACF;AAGA,IAAI,gBAAgB,cAAc,WAAW;AAAA,EAC3C,YAAY,KAAK,cAAc,CAAC,GAAG;AACjC,UAAM;AACN,SAAK,MAAM;AACX,SAAK,cAAc;AAAA,EACrB;AAAA,EACA,MAAM,WAAW;AACf,QAAI,YAAY,KAAK,GAAG,GAAG;AACzB,aAAO,IAAI,eAAe,KAAK,KAAK,KAAK,WAAW,EAAE,SAAS;AAAA,IACjE,OAAO;AACL,aAAO,iBAAiB,KAAK,KAAK,KAAK,WAAW;AAAA,IACpD;AAAA,EACF;AACF;AAGA,SAAS,IAAI,QAAQ,YAAY,CAAC,GAAG;AACnC,SAAO,IAAI,WAAW,IAAI,cAAc,MAAM,GAAG,SAAS;AAC5D;AACA,SAAS,KAAK,GAAG;AACf,QAAM,OAAO,qBAAqB,CAAC;AACnC,SAAO,sBAAsB,YAAY,IAAI;AAC/C;AACA,SAAS,UAAU,YAAY;AAC7B,SAAO,sBAAsB,YAAY;AACvC,UAAM,MAAM,MAAM,WAAW;AAC7B,WAAO,qBAAqB,MAAM,IAAI,KAAK,CAAC;AAAA,EAC9C,CAAC;AACH;AACA,eAAe,OAAO,oBAAoB,cAAc;AACtD,SAAO,eAAe,OAAO,oBAAoB,YAAY;AAC/D;AACA,eAAe,WAAW,kBAAkB;AAC1C,SAAO,mBAAmB,OAAO,gBAAgB;AACnD;AAGA,IAAI,WAAW;AAGf,SAAS,iBAAiB,SAAS,QAAQ;AACzC,MAAI,CAAC,MAAM,QAAQ,OAAO,GAAG;AAC3B,cAAU,CAAC,OAAO;AAAA,EACpB;AACA,UAAQ,QAAQ,CAAC,OAAO;AACtB,QAAI,MAAM,MAAM;AACd,mBAAa,OAAO,GAAG,UAAU,aAAa,MAAM,GAAG,+DAA+D;AAAA,IACxH;AAAA,EACF,CAAC;AACH;AAGA,IAAI,aAAa,qBAAqB;AACtC,IAAI,iBAAiB,cAAc,cAAc;AAAA,EAC/C,cAAc;AACZ,UAAM;AACN,SAAK,YAAY;AACjB,SAAK,WAAW;AAChB,SAAK,OAAO,IAAI,YAAY,MAAM,OAAO,CAAC;AAAA,EAC5C;AAAA,EACA,aAAa;AACX,WAAO,eAAe;AAAA,EACxB;AAAA,EACA,MAAM,QAAQ,OAAO,OAAO;AAC1B,QAAI,KAAK,UAAU;AACjB,WAAK,WAAW;AAChB,UAAI,IAAI,EAAE,IAAI,SAAS,GAAG;AACxB,6BAAqB,KAAK,oPAAoP;AAAA,MAChR;AAAA,IACF;AACA,UAAM,SAAS,EAAE,IAAI,KAAK,WAAW,EAAE;AACvC,SAAK,KAAK,IAAI,QAAQ,EAAE,QAAQ,OAAO,UAAU,EAAE,CAAC;AACpD,WAAO;AAAA,EACT;AAAA,EACA,eAAe,OAAO,OAAO,QAAQ;AACnC,QAAI;AACJ,QAAI,UAAU,YAAY,UAAU,QAAQ,OAAO,SAAS,KAAK,aAAa,SAAS,OAAO,EAAE,GAAG;AACjG,YAAM,gBAAgB,OAAO,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC;AACpE,cAAQ,KAAK,MAAM,eAAe,OAAO,KAAK;AAAA,IAChD,OAAO;AACL,cAAQ,KAAK,MAAM,QAAQ,OAAO,KAAK;AAAA,IACzC;AACA,WAAO,EAAE,QAAQ,OAAO,OAAO,MAAM;AAAA,EACvC;AAAA,EACA,SAAS,QAAQ;AACf,QAAI,KAAK,KAAK,IAAI,MAAM,GAAG;AACzB,YAAM,aAAa,KAAK,KAAK,IAAI,MAAM;AACvC,aAAO,WAAW;AAAA,IACpB;AACA,WAAO;AAAA,EACT;AAAA,EACA,OAAO,QAAQ;AACb,UAAM,aAAa,KAAK,KAAK,IAAI,MAAM;AACvC,eAAW;AAAA,EACb;AAAA,EACA,OAAO,QAAQ;AACb,QAAI,KAAK,KAAK,IAAI,MAAM,GAAG;AACzB,YAAM,aAAa,KAAK,KAAK,IAAI,MAAM;AACvC,iBAAW;AAAA,IACb;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ,OAAO,OAAO,UAAU;AAC3C,SAAK,KAAK,IAAI,QAAQ,EAAE,QAAQ,OAAO,SAAS,CAAC;AAAA,EACnD;AAAA,EACA,aAAa;AACX,WAAO,KAAK,KAAK,WAAW;AAAA,EAC9B;AAAA,EACA,MAAM,KAAK,QAAQ;AACjB,WAAO,KAAK,SAAS,MAAM;AAAA,EAC7B;AAAA,EACA,SAAS,QAAQ;AACf,UAAM,EAAE,OAAO,mBAAmB,IAAI,KAAK,KAAK,IAAI,MAAM;AAC1D,QAAI,UAAU,aAAa;AACzB,YAAM,aAAa,KAAK,SAAS,mBAAmB,KAAK,MAAM;AAC/D,YAAM,aAAa,KAAK,SAAS,mBAAmB,KAAK,MAAM;AAC/D,aAAO,qBAAqB,uBAAuB,YAAY,UAAU;AAAA,IAC3E;AACA,WAAO,KAAK,KAAK,IAAI,MAAM,EAAE;AAAA,EAC/B;AAAA,EACA,WAAW,IAAI;AACb,UAAM,OAAO,KAAK,SAAS,GAAG,MAAM;AACpC,QAAI,GAAG,UAAU,UAAU;AACzB,UAAI;AACF,cAAM,UAAU,KAAK,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC;AAC5D,eAAO,OAAO,GAAG,OAAO,GAAG,OAAO,OAAO;AAAA,MAC3C,SAAS,IAAP;AACA,cAAM,IAAI,MAAM,kDAAkD;AAAA,MACpE;AAAA,IACF;AACA,WAAO,OAAO,GAAG,OAAO,GAAG,OAAO,IAAI;AAAA,EACxC;AAAA,EACA,WAAW,QAAQ,OAAO,OAAO;AAC/B,WAAO,OAAO,EAAE,yBAAyB,KAAK,eAAe,OAAO,OAAO,MAAM,GAAG,IAAI;AAAA,EAC1F;AAAA,EACA,YAAY,QAAQ,QAAQ,OAAO;AACjC,QAAI,KAAK,KAAK,IAAI,MAAM,GAAG;AACzB,WAAK,KAAK,IAAI,MAAM,EAAE;AACtB,UAAI,CAAC,SAAS,KAAK,KAAK,IAAI,MAAM,EAAE,WAAW,GAAG;AAChD,eAAO;AAAA,MACT;AACA,YAAM,EAAE,mBAAmB,IAAI,KAAK,KAAK,IAAI,MAAM;AACnD,UAAI,sBAAsB,MAAM;AAC9B,aAAK,YAAY,mBAAmB,KAAK,QAAQ,IAAI;AACrD,aAAK,YAAY,mBAAmB,KAAK,QAAQ,IAAI;AAAA,MACvD;AACA,WAAK,KAAK,OAAO,MAAM;AAAA,IACzB;AACA,WAAO;AAAA,EACT;AAAA,EACA,8BAA8B,YAAY;AACxC,SAAK,YAAY,WAAW,MAAM;AAAA,EACpC;AAAA,EACA,MAAM,KAAK,GAAG;AACZ,UAAM,QAAQ,aAAa,IAAI;AAC/B,MAAE;AACF,UAAM,WAAW,aAAa,IAAI,IAAI;AACtC,WAAO,EAAE,SAAS;AAAA,EACpB;AAAA,EACA,SAAS;AACP,WAAO;AAAA,MACL,YAAY;AAAA,MACZ,SAAS,CAAC,oHAAoH;AAAA,IAChI;AAAA,EACF;AAAA,EACA,MAAM,WAAW;AACf,qBAAiB,CAAC,SAAS,GAAG,OAAO;AACrC,UAAM,WAAW,KAAK,SAAS,UAAU,MAAM;AAC/C,WAAO,WAAW,UAAU,OAAO,QAAQ;AAAA,EAC7C;AAAA,EACA,UAAU;AAAA,EACV;AAAA,EACA,iBAAiB;AACf,WAAO;AAAA,EACT;AAAA,EACA,UAAU;AACR,WAAO,MAAM,QAAQ;AAAA,EACvB;AACF;AACA,eAAe,aAAa;AAG5B,IAAI,iBAAiB,CAAC;AACtBT,UAAS,gBAAgB;AAAA,EACvB,SAAS,MAAM;AAAA,EACf,cAAc,MAAM;AAAA,EACpB,oBAAoB,MAAM;AAAA,EAC1B,UAAU,MAAM;AAAA,EAChB,YAAY,MAAM;AAAA,EAClB,WAAW,MAAM;AAAA,EACjB,SAAS,MAAM;AAAA,EACf,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,cAAc,MAAM;AAAA,EACpB,cAAc,MAAM;AAAA,EACpB,kBAAkB,MAAM;AAAA,EACxB,aAAa,MAAM;AAAA,EACnB,eAAe,MAAM;AAAA,EACrB,UAAU,MAAM;AAAA,EAChB,cAAc,MAAM;AAAA,EACpB,SAAS,MAAM;AAAA,EACf,SAAS,MAAM;AAAA,EACf,aAAa,MAAM;AAAA,EACnB,aAAa,MAAM;AAAA,EACnB,cAAc,MAAM;AAAA,EACpB,SAAS,MAAM;AAAA,EACf,cAAc,MAAM;AAAA,EACpB,UAAU,MAAM;AAAA,EAChB,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,aAAa,MAAM;AAAA,EACnB,aAAa,MAAM;AAAA,EACnB,eAAe,MAAM;AAAA,EACrB,WAAW,MAAM;AAAA,EACjB,yBAAyB,MAAM;AAAA,EAC/B,mBAAmB,MAAM;AAAA,EACzB,4BAA4B,MAAM;AAAA,EAClC,UAAU,MAAM;AAAA,EAChB,uBAAuB,MAAM;AAAA,EAC7B,kBAAkB,MAAM;AAAA,EACxB,kBAAkB,MAAM;AAAA,EACxB,iBAAiB,MAAM;AAAA,EACvB,4BAA4B,MAAM;AAAA,EAClC,SAAS,MAAM;AAAA,EACf,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,eAAe,MAAM;AAAA,EACrB,YAAY,MAAM;AACpB,CAAC;AAGD,SAAS,cAAc,MAAM;AAC3B,QAAM,eAAe,IAAI,aAAa,KAAK,MAAM;AACjD,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,iBAAa,MAAM,KAAK,IAAI,KAAK,GAAG;AAAA,EACtC;AACA,SAAO;AACT;AACA,IAAI,OAAO,CAAC,SAAS;AACnB,QAAM,EAAE,EAAE,IAAI,KAAK;AACnB,QAAM,aAAa,KAAK;AACxB,mBAAiB,GAAG,KAAK;AACzB,MAAI,eAAe,IAAI,aAAa,aAAa,cAAc,EAAE,KAAK,CAAC;AACvE,QAAM,SAAS,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC7C,iBAAe,cAAc,MAAM;AACnC,SAAO,WAAW,WAAW,cAAc,EAAE,OAAO,EAAE,KAAK;AAC7D;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,6BAA6B,KAAK;AACzC,SAAO,CAAC,QAAQ,QAAQ,OAAO,OAAO,UAAU;AAC9C,UAAM,WAAW,qBAAqB,2BAA2B,QAAQ,MAAM;AAC/E,UAAM,aAAa,SAAS;AAC5B,UAAM,gBAAgB,aAAa,eAAe,QAAQ;AAC1D,UAAM,aAAa,aAAa,cAAc,QAAQ;AACtD,UAAM,SAAS,aAAa,uBAAuB,OAAO,UAAU;AACpE,UAAM,QAAQ,OAAO;AACrB,UAAM,QAAQ,OAAO;AACrB,UAAM,WAAW,aAAa,eAAe,MAAM;AACnD,UAAM,WAAW,aAAa,eAAe,MAAM;AACnD,UAAM,iBAAiB,qBAAqB,iBAAiB,QAAQ,QAAQ;AAC7E,UAAM,iBAAiB,qBAAqB,iBAAiB,QAAQ,QAAQ;AAC7E,QAAI,eAAe,SAAS,eAAe,WAAW,GAAG;AACvD,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,eAAO,MAAM,IAAI,MAAM,KAAK,MAAM,SAAS,MAAM,KAAK,MAAM,OAAO;AAAA,MACrE;AAAA,IACF,OAAO;AACL,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,cAAM,MAAM,aAAa,WAAW,IAAI,YAAY,aAAa;AACjE,cAAM,OAAO,IAAI,MAAM,CAAC,KAAK;AAC7B,uBAAe,QAAQ,CAAC,MAAM,KAAK,KAAK,CAAC;AACzC,cAAM,SAAS,aAAa,WAAW,MAAM,OAAO,QAAQ;AAC5D,cAAM,OAAO,IAAI,MAAM,CAAC,KAAK;AAC7B,uBAAe,QAAQ,CAAC,MAAM,KAAK,KAAK,CAAC;AACzC,cAAM,SAAS,aAAa,WAAW,MAAM,OAAO,QAAQ;AAC5D,eAAO,MAAM,IAAI,MAAM,SAAS,MAAM,OAAO;AAAA,MAC/C;AAAA,IACF;AACA,WAAO,CAAC,QAAQ,QAAQ;AAAA,EAC1B;AACF;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,MAAM,OAAO,MAAM,MAAM,IAAI;AACrC,QAAM,WAAW,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AACjD,QAAM,WAAW,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AACjD,QAAM,cAAc,SAAS,eAAe,MAAM,OAAO,WAAW;AACpE,QAAM,WAAW,SAAS,KAAK,IAAI,YAAY,MAAM;AACrD,WAAS,qBAAqB;AAAA,IAC5B,MAAM,SAAS,eAAe,MAAM,OAAO,WAAW,QAAQ;AAAA,IAC9D,MAAM,SAAS,eAAe,MAAM,OAAO,WAAW,QAAQ;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,OAAO,UAAU,OAAO,QAAQ,WAAW;AAClD,MAAI,UAAU,aAAa;AACzB,UAAM,QAAQ,OAAO,UAAU,OAAO,SAAS;AAC/C,UAAM,QAAQ,OAAO,UAAU,OAAO,SAAS;AAC/C,WAAO,SAAS,EAAE,QAAQ,EAAE,MAAM,OAAO,MAAM,MAAM,GAAG,SAAS,SAAS,CAAC;AAAA,EAC7E;AACA,QAAM,SAAS,aAAa,oBAAoB,aAAa,cAAc,KAAK,GAAG,KAAK;AACxF,SAAO,SAAS,eAAe,OAAO,OAAO,MAAM;AACrD;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,WAAS,OAAO,EAAE,MAAM;AACxB,SAAO,EAAE,QAAQ,EAAE,QAAQ,OAAO,EAAE,OAAO,OAAO,EAAE,MAAM;AAC5D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,QAAQ,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE,mBAAmB;AAClE,QAAM,UAAU,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AAChD,SAAO,SAAS,eAAe,MAAM,OAAO,MAAM,OAAO,OAAO;AAClE;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,IAAI;AAClB,MAAI,UAAU,aAAa;AACzB,QAAI,EAAE,UAAU,aAAa;AAC3B,aAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,IACvD;AACA,UAAM,kBAAkB,OAAO,UAAU,EAAE,OAAO,EAAE,KAAK;AACzD,UAAM,SAAS,MAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AACtF,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,QAAQ,MAAM,gBAAgB,GAAG,SAAS,SAAS,CAAC;AAC9F,aAAS,8BAA8B,eAAe;AACtD,aAAS,8BAA8B,MAAM;AAC7C,WAAO;AAAA,EACT;AACA,MAAI,EAAE,UAAU,aAAa;AAC3B,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,SAAS,MAAM,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AACrF,aAAS,8BAA8B,QAAQ;AAC/C,WAAO;AAAA,EACT;AACA,MAAI,CAAC,aAAa,gBAAgB,EAAE,OAAO,KAAK,GAAG;AACjD,UAAM,SAAS,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAC7D,WAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO,OAAO,OAAO,MAAM;AAAA,EAC7D;AACA,MAAI,UAAU,SAAS;AACrB,UAAM,SAAS,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC3C,UAAM,eAAe,WAAW,KAAK,MAAM;AAC3C,WAAO,SAAS,eAAe,EAAE,OAAO,SAAS,YAAY;AAAA,EAC/D;AACA,MAAI,UAAU,QAAQ;AACpB,UAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,UAAM,OAAO,aAAa,aAAa,CAAC,CAAC,GAAG,EAAE,KAAK;AACnD,UAAM,CAAC,YAAY,WAAW,IAAI,6BAA6B,CAAC,GAAG,MAAM,MAAM,IAAI,IAAI,CAAC,EAAE,EAAE,OAAO,CAAC,GAAG,OAAO,MAAM,MAAM;AAC1H,WAAO,SAAS,eAAe,aAAa,QAAQ,UAAU;AAAA,EAChE;AACA,QAAM,IAAI,MAAM,iCAAiC,EAAE,YAAY,OAAO;AACxE;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,iBAAiB,MAAM,YAAY,aAAa,OAAO;AAC9D,MAAI,eAAe,MAAM;AACvB,WAAO,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AACxC,YAAM,EAAE,GAAG,EAAE,IAAI;AACjB,YAAM,aAAa;AACnB,uBAAiB,CAAC,GAAG,CAAC,GAAG,IAAI;AAC7B,YAAM,QAAQ,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,YAAM,QAAQ,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,YAAM,eAAe,EAAE,UAAU,WAAW,qBAAqB,uBAAuB,KAAK,IAAI;AACjG,YAAM,eAAe,EAAE,UAAU,WAAW,qBAAqB,uBAAuB,KAAK,IAAI;AACjG,YAAM,SAAS,SAAS,EAAE;AAC1B,YAAM,CAAC,YAAY,WAAW,IAAI,WAAW,EAAE,OAAO,EAAE,OAAO,cAAc,cAAc,MAAM;AACjG,aAAO,WAAW,eAAe,aAAa,QAAQ,UAAU;AAAA,IAClE;AAAA,EACF;AACA,SAAO,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AACxC,UAAM,EAAE,GAAG,EAAE,IAAI;AACjB,UAAM,aAAa;AACnB,QAAI,EAAE,UAAU,eAAe,EAAE,UAAU,aAAa;AACtD,YAAM,YAAY,MAAM,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,YAAY,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAChG,YAAM,gBAAgB,WAAW,KAAK,IAAI,UAAU,MAAM;AAC1D,YAAM,QAAQ,cAAc,mBAAmB;AAC/C,YAAM,QAAQ,cAAc,mBAAmB;AAC/C,YAAM,YAAY,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACpD,YAAM,YAAY,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACpD,YAAM,YAAY,MAAM,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,YAAY,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAChG,YAAM,gBAAgB,WAAW,KAAK,IAAI,UAAU,MAAM;AAC1D,YAAM,QAAQ,cAAc,mBAAmB;AAC/C,YAAM,QAAQ,cAAc,mBAAmB;AAC/C,YAAM,YAAY,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACpD,YAAM,YAAY,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACpD,YAAM,CAAC,gBAAgB,gBAAgB,WAAW,IAAI,YAAY,EAAE,OAAO,EAAE,OAAO,WAAW,WAAW,WAAW,SAAS;AAC9H,YAAM,aAAa,WAAW,eAAe,aAAa,WAAW,cAAc;AACnF,YAAM,aAAa,WAAW,eAAe,aAAa,WAAW,cAAc;AACnF,YAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,YAAY,MAAM,WAAW,GAAG,SAAS,WAAW,CAAC;AAC/F,iBAAW,8BAA8B,SAAS;AAClD,iBAAW,8BAA8B,SAAS;AAClD,iBAAW,8BAA8B,UAAU;AACnD,iBAAW,8BAA8B,UAAU;AACnD,aAAO;AAAA,IACT,OAAO;AACL,YAAM,QAAQ,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,YAAM,QAAQ,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,YAAM,SAAS,SAAS,EAAE;AAC1B,YAAM,CAAC,YAAY,WAAW,IAAI,WAAW,EAAE,OAAO,EAAE,OAAO,OAAO,OAAO,MAAM;AACnF,aAAO,WAAW,eAAe,aAAa,QAAQ,UAAU;AAAA,IAClE;AAAA,EACF;AACF;AACA,SAAS,8BAA8B,KAAK;AAC1C,SAAO,CAAC,QAAQ,QAAQ,WAAW,WAAW,WAAW,cAAc;AACrE,UAAM,cAAc,qBAAqB,2BAA2B,QAAQ,MAAM;AAClF,UAAM,aAAa,aAAa,cAAc,WAAW;AACzD,UAAM,aAAa,YAAY;AAC/B,UAAM,gBAAgB,aAAa,eAAe,WAAW;AAC7D,UAAM,iBAAiB,aAAa,uBAAuB,WAAW,UAAU;AAChF,UAAM,iBAAiB,aAAa,uBAAuB,WAAW,UAAU;AAChF,UAAM,iBAAiB,qBAAqB,iBAAiB,QAAQ,WAAW;AAChF,UAAM,iBAAiB,qBAAqB,iBAAiB,QAAQ,WAAW;AAChF,UAAM,QAAQ,qBAAqB,uBAAuB,WAAW,SAAS;AAC9E,UAAM,QAAQ,qBAAqB,uBAAuB,WAAW,SAAS;AAC9E,UAAM,QAAQ,OAAO;AACrB,UAAM,WAAW,aAAa,eAAe,MAAM;AACnD,UAAM,QAAQ,OAAO;AACrB,UAAM,WAAW,aAAa,eAAe,MAAM;AACnD,QAAI,eAAe,SAAS,eAAe,WAAW,GAAG;AACvD,eAAS,KAAK,GAAG,KAAK,eAAe,QAAQ,MAAM;AACjD,cAAM,OAAO,KAAK,MAAM;AACxB,cAAM,OAAO,KAAK,MAAM;AACxB,cAAM,SAAS,IAAI,MAAM,OAAO,IAAI,MAAM,OAAO,IAAI,IAAI,MAAM,OAAO,IAAI,MAAM,OAAO,IAAI,EAAE;AAC7F,uBAAe,MAAM,OAAO;AAC5B,uBAAe,MAAM,OAAO;AAAA,MAC9B;AAAA,IACF,OAAO;AACL,eAAS,KAAK,GAAG,KAAK,eAAe,QAAQ,MAAM;AACjD,cAAM,MAAM,aAAa,WAAW,IAAI,YAAY,aAAa;AACjE,cAAM,OAAO,IAAI,MAAM,CAAC,KAAK;AAC7B,uBAAe,QAAQ,CAAC,MAAM,KAAK,KAAK,CAAC;AACzC,cAAM,SAAS,aAAa,WAAW,MAAM,OAAO,QAAQ;AAC5D,cAAM,OAAO,IAAI,MAAM,CAAC,KAAK;AAC7B,uBAAe,QAAQ,CAAC,MAAM,KAAK,KAAK,CAAC;AACzC,cAAM,SAAS,aAAa,WAAW,MAAM,OAAO,QAAQ;AAC5D,cAAM,WAAW,IAAI,MAAM,SAAS,IAAI,MAAM,SAAS,IAAI,IAAI,MAAM,SAAS,IAAI,MAAM,SAAS,IAAI,EAAE;AACvG,uBAAe,MAAM,SAAS;AAC9B,uBAAe,MAAM,SAAS;AAAA,MAChC;AAAA,IACF;AACA,WAAO,CAAC,gBAAgB,gBAAgB,WAAW;AAAA,EACrD;AACF;AAGA,IAAI,UAAU,6BAA6B,CAAC,GAAG,MAAM,IAAI,CAAC;AAC1D,IAAI,iBAAiB,8BAA8B,CAAC,OAAO,OAAO,OAAO,UAAU;AACjF,SAAO,EAAE,MAAM,QAAQ,OAAO,MAAM,QAAQ,MAAM;AACpD,CAAC;AACD,IAAI,OAAO,iBAAiB,KAAK,SAAS,cAAc;AACxD,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,OAAO,aAAa,cAAc,cAAcG,OAAM;AAC1E,QAAM,cAAc,aAAa,cAAc,YAAY;AAC3D,QAAM,UAAU,aAAa,oBAAoBA,OAAM,YAAY;AACnE,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,UAAM,QAAQ,MAAM;AACpB,QAAI,QAAQ,GAAG;AACb,YAAM,IAAI,MAAM,+BAA+B;AAAA,IACjD;AACA,QAAI,SAASA,OAAM;AACjB;AAAA,IACF;AACA,QAAI,cAAc,GAAG;AACnB,cAAQ,UAAU,YAAY;AAAA,IAChC,OAAO;AACL,cAAQ,UAAU;AAAA,IACpB;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,mBAAmB,MAAM,YAAYA,OAAM,eAAe,OAAO;AACxE,QAAM,UAAU,KAAK,MAAM;AAC3B,QAAM,UAAU,KAAK,MAAM;AAC3B,QAAM,SAAS,OAAO,CAAC,SAASA,KAAI,GAAG,WAAW,KAAK;AACvD,WAAS,KAAK,GAAG,KAAK,SAAS,MAAM;AACnC,aAAS,IAAI,GAAG,IAAI,SAAS,KAAK;AAChC,YAAM,QAAQ,KAAK,IAAI,IAAI,CAAC;AAC5B,UAAI,QAAQ,GAAG;AACb,cAAM,IAAI,MAAM,+BAA+B;AAAA,MACjD;AACA,UAAI,SAASA,OAAM;AACjB;AAAA,MACF;AACA,UAAI,cAAc;AAChB,eAAO,IAAI,GAAG,IAAI,KAAK;AAAA,MACzB,OAAO;AACL,YAAI,WAAW,OAAO,GAAG;AACvB,iBAAO,IAAI,OAAO,IAAI,IAAI,KAAK,IAAI,WAAW,IAAI,IAAI,CAAC,GAAG,IAAI,KAAK;AAAA,QACrE,OAAO;AACL,iBAAO,IAAI,OAAO,IAAI,IAAI,KAAK,IAAI,GAAG,IAAI,KAAK;AAAA,QACjD;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AAGA,SAAS,sBAAsB,KAAK;AAClC,SAAO,CAAC,QAAQ,OAAO,UAAU;AAC/B,UAAM,YAAY,aAAa,uBAAuB,OAAO,OAAO,MAAM;AAC1E,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,gBAAU,MAAM,IAAI,OAAO,KAAK,KAAK;AAAA,IACvC;AACA,WAAO;AAAA,EACT;AACF;AAGA,SAAS,gBAAgB,MAAM,KAAK,OAAO;AACzC,SAAO,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AAC/C,UAAM,EAAE,EAAE,IAAI;AACd,qBAAiB,GAAG,IAAI;AACxB,QAAI,EAAE,UAAU,YAAY,UAAU,UAAU;AAC9C,YAAM,IAAI,MAAM,sDAAsD;AAAA,IACxE;AACA,UAAM,aAAa;AACnB,UAAM,SAAS,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,UAAM,SAAS,SAAS,EAAE;AAC1B,UAAM,YAAY,aAAa,kBAAkB,QAAQ,KAAK;AAC9D,aAAS,KAAK,GAAG,KAAK,OAAO,EAAE,IAAI;AACjC,gBAAU,MAAM,IAAI,OAAO,KAAK,KAAK;AAAA,IACvC;AACA,WAAO,WAAW,eAAe,EAAE,OAAO,QAAQ,SAAS;AAAA,EAC7D;AACF;AACA,SAAS,wBAAwB,MAAM,WAAW,OAAO;AACvD,SAAO,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AAC/C,UAAM,EAAE,EAAE,IAAI;AACd,qBAAiB,GAAG,IAAI;AACxB,QAAI,EAAE,UAAU,YAAY,UAAU,UAAU;AAC9C,YAAM,IAAI,MAAM,sDAAsD;AAAA,IACxE;AACA,UAAM,aAAa;AACnB,UAAM,SAAS,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,SAAS,SAAS,EAAE;AAC1B,UAAM,YAAY,UAAU,QAAQ,QAAQ,KAAK;AACjD,WAAO,WAAW,eAAe,EAAE,OAAO,QAAQ,SAAS;AAAA,EAC7D;AACF;AAGA,IAAI,WAAW,sBAAsB,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AAC1D,IAAI,QAAQ,wBAAwB,MAAM,QAAQ;AAClD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,QAAQ,UAAU,OAAO,cAAc;AACzD,QAAM,UAAU,aAAa,kBAAkB,OAAO,aAAa,cAAc,QAAQ,CAAC;AAC1F,MAAI,gBAAgB,UAAU,UAAU;AACtC,QAAI,SAAS;AACb,WAAO,QAAQ,CAAC,WAAW;AACzB,YAAMA,QAAO,aAAa,cAAc,OAAO,KAAK;AACpD,cAAQ,IAAI,OAAO,MAAM,MAAM;AAC/B,gBAAUA;AAAA,IACZ,CAAC;AAAA,EACH,OAAO;AACL,QAAI,YAAY;AAChB,WAAO,QAAQ,CAAC,WAAW;AACzB,YAAM,cAAc,UAAU,WAAW,qBAAqB,uBAAuB,OAAO,IAAI,IAAI,OAAO;AAC3G,UAAI,OAAO;AACX,eAAS,MAAM,GAAG,MAAM,OAAO,MAAM,IAAI,EAAE,KAAK;AAC9C,cAAM,SAAS,MAAM,SAAS,KAAK;AACnC,iBAAS,MAAM,GAAG,MAAM,OAAO,MAAM,IAAI,EAAE,KAAK;AAC9C,kBAAQ,SAAS,OAAO,YAAY;AAAA,QACtC;AAAA,MACF;AACA,mBAAa,OAAO,MAAM;AAAA,IAC5B,CAAC;AAAA,EACH;AACA,SAAO;AACT;AAGA,IAAI,YAAY,6BAA6B,CAAC,GAAG,MAAM,MAAM,IAAI,IAAI,CAAC;AACtE,IAAI,SAAS,iBAAiB,OAAO,WAAW,MAAM,MAAM;AAC5D,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU,sBAAsB,CAAC,OAAO,KAAK,IAAI,EAAE,CAAC;AACxD,IAAI,OAAO,wBAAwB,KAAK,SAAS,SAAS;AAC1D,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY,sBAAsB,CAAC,OAAO,KAAK,MAAM,EAAE,CAAC;AAC5D,IAAI,SAAS,wBAAwB,OAAO,SAAS;AACrD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY,sBAAsB,CAAC,OAAO,KAAK,MAAM,EAAE,CAAC;AAC5D,IAAI,SAAS,wBAAwB,OAAO,SAAS;AACrD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,aAAa,WAAW,OAAO,WAAW,WAAW,WAAWY,UAAS,aAAa,YAAY;AACtH,QAAM,SAAS,OAAO,CAAC,WAAW,SAAS,GAAG,KAAK;AACnD,WAAS,KAAK,GAAG,KAAK,WAAW,MAAM;AACrC,UAAMH,SAAQ,CAAC;AACf,QAAI,eAAe;AACnB,aAAS,IAAI,GAAG,IAAI,WAAW,KAAK;AAClC,YAAM,MAAM,YAAY,KAAK,YAAY;AACzC,sBAAgB,MAAMG,SAAQ;AAC9B,MAAAH,OAAM,KAAK,GAAG;AAAA,IAChB;AACA,QAAI,eAAe,KAAK,gBAAgB,aAAa,WAAW;AAC9D,YAAM,IAAI,MAAM,oBAAoBA,8BAA6B,aAAa;AAAA,IAChF;AACA,aAAS,IAAI,GAAG,IAAI,WAAW,KAAK;AAClC,aAAO,OAAO,KAAK,YAAY,KAAK,UAAU,IAAI,GAAG,UAAU,WAAW,eAAe,YAAY,CAAC,CAAC;AAAA,IACzG;AAAA,EACF;AACA,SAAO;AACT;AAGA,SAAS,aAAa,MAAM,YAAY,oBAAoB;AAC1D,QAAM,SAAS,OAAO,oBAAoB,KAAK,KAAK;AACpD,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM,EAAE,IAAI;AACvC,UAAM,SAAS,OAAO,WAAW,EAAE;AACnC,UAAM,cAAc,OAAO,MAAM;AACjC,UAAM,WAAW,YAAY;AAC7B,UAAM,aAAa,YAAY;AAC/B,UAAM,eAAe,WAAW,WAAW,CAAC,UAAU,UAAU,CAAC;AACjE,gBAAY,KAAK,WAAW,OAAO;AACnC,UAAM,gBAAgB,KAAK,WAAW,WAAW;AACjD,QAAI,KAAK,iBAAiB,gBAAgB,KAAK,OAAO,QAAQ;AAC5D,aAAO,OAAO,MAAM,KAAK,OAAO;AAAA,IAClC;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,cAAc,6BAA6B,CAAC,GAAG,MAAM,IAAI,IAAI,IAAI,CAAC;AACtE,IAAI,WAAW,iBAAiB,SAAS,aAAa,MAAM,MAAM;AAClE,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB,6BAA6B,CAAC,GAAG,MAAM,KAAK,IAAI,IAAI,CAAC;AAC5E,IAAI,gBAAgB,iBAAiB,cAAc,kBAAkB,MAAM,MAAM;AACjF,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW,6BAA6B,CAAC,GAAG,MAAM,IAAI,IAAI,IAAI,CAAC;AACnE,IAAI,QAAQ,iBAAiB,MAAM,UAAU,MAAM,MAAM;AACzD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,6BAA6B,CAAC,GAAG,MAAM,KAAK,IAAI,IAAI,CAAC;AACzE,IAAI,aAAa,iBAAiB,WAAW,eAAe,MAAM,MAAM;AACxE,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,OAAO,MAAM,KAAK;AACtC,QAAM,SAAS,OAAO,UAAU,MAAM;AACtC,QAAM,SAAS,aAAa,oBAAoB,KAAK,SAAS;AAC9D,SAAO,KAAK;AACZ,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,WAAO,MAAM,OAAO,KAAK,KAAK;AAAA,EAChC;AACA,SAAO;AACT;AAGA,IAAI,UAAU,sBAAsB,CAAC,OAAO,KAAK,IAAI,EAAE,CAAC;AACxD,IAAI,OAAO,wBAAwB,KAAK,OAAO;AAC/C,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,OAAO,YAAY,UAAU,OAAO;AACnD,QAAM,OAAO,aAAa,uBAAuB,OAAO,aAAa,cAAc,QAAQ,CAAC;AAC5F,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,SAAS,KAAK;AACpB,QAAI,OAAO,MAAM;AACjB,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,YAAM,QAAQ,MAAM,SAAS;AAC7B,UAAI,OAAO,MAAM,KAAK,KAAK,QAAQ,MAAM;AACvC,eAAO;AAAA,MACT;AAAA,IACF;AACA,SAAK,MAAM;AAAA,EACb;AACA,SAAO;AACT;AAGA,IAAI,cAAc,6BAA6B,CAAC,QAAQ,WAAW,KAAK,IAAI,QAAQ,MAAM,CAAC;AAC3F,IAAI,WAAW,iBAAiB,SAAS,WAAW;AACpD,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,6BAA6B,CAAC,QAAQ,WAAW,KAAK,IAAI,QAAQ,MAAM,CAAC;AAC3F,IAAI,WAAW,iBAAiB,SAAS,WAAW;AACpD,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe,6BAA6B,CAAC,QAAQ,WAAW,SAAS,MAAM;AACnF,IAAI,sBAAsB,8BAA8B,CAAC,OAAO,OAAO,OAAO,UAAU;AACtF,SAAO;AAAA,IACL,MAAM,QAAQ,QAAQ,QAAQ;AAAA,IAC9B,MAAM,QAAQ,QAAQ,QAAQ;AAAA,EAChC;AACF,CAAC;AACD,IAAI,YAAY,iBAAiB,UAAU,cAAc,mBAAmB;AAC5E,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,OAAO,QAAQ,QAAQ;AACtC,QAAM,WAAW,aAAa,kBAAkB,IAAI,MAAM;AAC1D,SAAO,aAAa,CAAC,GAAG,QAAQ,UAAU,OAAO,MAAM;AACzD;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,mBAAiB,GAAG,KAAK;AACzB,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,CAAC,KAAK,QAAQ,IAAI,QAAQ,OAAO,EAAE,OAAO,EAAE,KAAK;AACvD,SAAO,SAAS,eAAe,UAAU,EAAE,OAAO,GAAG;AACvD;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe,6BAA6B,CAAC,GAAG,MAAM,MAAM,IAAI,IAAI,CAAC;AACzE,IAAI,YAAY,iBAAiB,UAAU,cAAc,MAAM,MAAM;AACrE,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,OAAO,QAAQ,OAAO,MAAM,UAAU;AAC3D,QAAM,QAAQ,OAAO;AACrB,QAAM,QAAQ,aAAa,cAAc,MAAM;AAC/C,QAAM,WAAW,aAAa,eAAe,MAAM;AACnD,QAAM,aAAa,aAAa,eAAe,QAAQ;AACvD,QAAM,SAAS,aAAa,uBAAuB,OAAO,aAAa,cAAc,QAAQ,CAAC;AAC9F,WAAS,KAAK,GAAG,KAAK,OAAO,EAAE,IAAI;AACjC,UAAM,MAAM,aAAa,WAAW,IAAI,OAAO,QAAQ;AACvD,UAAM,SAAS,IAAI,MAAM,IAAI,MAAM;AACnC,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,aAAO,MAAM,IAAI,KAAK;AAAA,IACxB;AACA,UAAM,WAAW,aAAa,WAAW,QAAQ,OAAO,UAAU;AAClE,WAAO,YAAY,MAAM;AAAA,EAC3B;AACA,SAAO;AACT;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,mBAAiB,GAAG,WAAW;AAC/B,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,IAAI,MAAM,KAAK;AAChC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,aAAS,MAAM,EAAE,MAAM,KAAK;AAAA,EAC9B;AACA,QAAM,SAAS,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC3C,QAAM,SAAS,cAAc,QAAQ,EAAE,OAAO,EAAE,OAAO,MAAM,QAAQ;AACrE,QAAM,SAAS,SAAS,MAAM,QAAQ,UAAU,EAAE,KAAK;AACvD,SAAO,EAAE,QAAQ,OAAO,UAAU,OAAO,EAAE,MAAM;AACnD;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,QAAQ,QAAQ,OAAO,eAAe;AACtD,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,QAAQ,aAAa;AACpG,QAAM,WAAW,WAAW,QAAQ,OAAO;AAC3C,QAAM,UAAU,aAAa,oBAAoB,aAAa,cAAc,QAAQ,GAAG,QAAQ;AAC/F,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC1C,UAAM,SAAS,KAAK;AACpB,QAAI,QAAQ;AACZ,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,eAAS,MAAM,SAAS;AAAA,IAC1B;AACA,YAAQ,MAAM;AAAA,EAChB;AACA,SAAO,EAAE,SAAS,UAAU,SAAS;AACvC;AACA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,mBAAiB,GAAG,MAAM;AAC1B,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACtD,QAAM,cAAc,qBAAqB,mBAAmB,MAAM,KAAK;AACvE,MAAI,gBAAgB;AACpB,MAAI,YAAY;AAChB,QAAM,0BAA0B,CAAC;AACjC,MAAI,eAAe,MAAM;AACvB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,YAAY,EAAE,CAAC;AACzF,4BAAwB,KAAK,SAAS;AACtC,oBAAgB,qBAAqB,iBAAiB,cAAc,QAAQ,KAAK;AAAA,EACnF;AACA,QAAM,QAAQ,SAAS,KAAK,IAAI,UAAU,MAAM,EAAE;AAClD,QAAM,EAAE,SAAS,UAAU,SAAS,IAAI,SAAS,UAAU,OAAO,UAAU,OAAO,OAAO,aAAa;AACvG,MAAI,cAAc;AAClB,MAAI,UAAU;AACZ,kBAAc,qBAAqB,qBAAqB,UAAU,IAAI;AAAA,EACxE;AACA,0BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,SAAO,SAAS,eAAe,aAAa,UAAU,OAAO;AAC/D;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,OAAO,MAAM,OAAO,OAAO;AAC5C,QAAM,gBAAgB,UAAU;AAChC,QAAM,8BAA8B,QAAQ,QAAQ,QAAQ;AAC5D,QAAM,8BAA8B,OAAO,SAAS,QAAQ;AAC5D,MAAI,iBAAiB,+BAA+B,6BAA6B;AAC/E,WAAO,aAAa,oBAAoB,GAAG,KAAK;AAAA,EAClD;AACA,QAAM,cAAc,KAAK,IAAI,KAAK,MAAM,OAAO,SAAS,KAAK,CAAC;AAC9D,QAAM,SAAS,aAAa,oBAAoB,aAAa,KAAK;AAClE,MAAI,OAAO,SAAS,UAAU,GAAG;AAC/B,YAAQ;AAAA,EACV;AACA,SAAO,KAAK;AACZ,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,WAAO,MAAM,OAAO,KAAK,KAAK;AAAA,EAChC;AACA,SAAO;AACT;AAGA,IAAI,YAAY,sBAAsB,CAAC,OAAO,IAAI,KAAK,KAAK,EAAE,CAAC;AAC/D,IAAI,SAAS,wBAAwB,OAAO,SAAS;AACrD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,SAAS,SAAS,OAAOW,aAAY,WAAW,YAAY,WAAWR,UAAS,cAAc,gBAAgB;AACjI,QAAM,eAAe,CAACQ,cAAa,WAAW,SAAS;AACvD,QAAM,cAAc,QAAQ;AAC5B,QAAM,cAAc,QAAQ;AAC5B,MAAIA,gBAAe,GAAG;AACpB,WAAO,OAAO,OAAO,QAAQ,KAAK;AAAA,EACpC;AACA,QAAM,SAAS,OAAO,cAAc,QAAQ,KAAK;AACjD,MAAI,OAAO,iBAAiB,UAAU;AACpC,WAAO,OAAO,KAAK,YAAY;AAAA,EACjC,WAAW,OAAO,iBAAiB,UAAU;AAC3C,WAAO,OAAO,KAAK,YAAY;AAAA,EACjC,WAAW,OAAO,iBAAiB,WAAW;AAC5C,WAAO,OAAO,KAAK,CAAC,YAAY;AAAA,EAClC;AACA,WAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,UAAMX,SAAQ,CAAC;AACf,QAAI,eAAe;AACnB,aAAS,IAAI,GAAG,IAAI,WAAW,KAAK;AAClC,YAAM,MAAM,YAAY,KAAK,YAAY;AACzC,MAAAA,OAAM,KAAK,GAAG;AACd,sBAAgB,MAAMG,SAAQ;AAAA,IAChC;AACA,QAAI,eAAe,KAAK,gBAAgBQ,cAAa,WAAW;AAC9D,YAAM,IAAI,MAAM,oBAAoBX,8BAA6B,OAAO;AAAA,IAC1E;AACA,aAAS,IAAI,GAAG,IAAI,WAAW,KAAK;AAClC,UAAI,gBAAgB;AAClB,eAAO,OAAO,eAAe,YAAY,MAAM,YAAY,KAAK,YAAY;AAAA,MAC9E,OAAO;AACL,eAAO,OAAO,eAAe,YAAY,KAAK,QAAQ,SAAS,IAAI,YAAY,KAAK,YAAY,KAAK,YAAY;AAAA,MACnH;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,cAAc,sBAAsB,CAAC,OAAO,KAAK,IAAI,KAAK,IAAI,CAAC,EAAE,EAAE;AACvE,IAAI,WAAW,gBAAgB,SAAS,CAAC,OAAO,KAAK,IAAI,KAAK,IAAI,CAAC,EAAE,EAAE;AACvE,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM,OAAOT,OAAM,OAAO,OAAO;AAClD,QAAM,cAAc,mBAAmB,iBAAiB,OAAO,OAAOA,KAAI;AAC1E,QAAM,SAAS,aAAa,cAAcA,KAAI;AAC9C,QAAM,WAAW,aAAa,eAAe,KAAK;AAClD,MAAI,aAAa;AACf,UAAM,aAAa,mBAAmB,kBAAkB,OAAO,QAAQ;AACvE,QAAI,UAAU,UAAU;AACtB,aAAO,KAAK,MAAM,YAAY,aAAa,MAAM;AAAA,IACnD;AACA,WAAO,KAAK,SAAS,YAAY,aAAa,MAAM;AAAA,EACtD;AACA,QAAM,cAAc,UAAU,WAAW,qBAAqB,uBAAuB,IAAI,IAAI;AAC7F,QAAM,QAAQ,OAAO,OAAO,OAAO,WAAW;AAC9C,QAAM,SAAS,OAAOA,OAAM,KAAK;AACjC,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM,EAAE,IAAI;AACvC,UAAM,SAAS,OAAO,WAAW,EAAE;AACnC,UAAM,QAAQ,OAAO,IAAI,CAAC,KAAK,MAAM,MAAM,MAAM,EAAE;AACnD,WAAO,IAAI,MAAM,IAAI,GAAG,KAAK,GAAG,GAAG,MAAM;AAAA,EAC3C;AACA,MAAI,UAAU,UAAU;AACtB,WAAO,qBAAqB,uBAAuB,OAAO,MAAM;AAAA,EAClE;AACA,SAAO,OAAO;AAChB;AACA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAO,MAAAA,MAAK,IAAI;AACxB,mBAAiB,GAAG,OAAO;AAC3B,QAAM,CAAC,QAAQ,KAAK,IAAI,mBAAmB,iBAAiB,GAAG,OAAOA,KAAI;AAC1E,qBAAmB,kBAAkB,GAAG,QAAQ,KAAK;AACrD,QAAM,OAAO,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AACzC,QAAM,UAAU,UAAU,MAAM,QAAQ,OAAO,EAAE,OAAO,EAAE,KAAK;AAC/D,SAAO,SAAS,eAAe,OAAO,EAAE,OAAO,OAAO;AACxD;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,wBAAwB,SAAS,cAAc,cAAc,QAAQ,aAAa,YAAY,cAAc;AACnH,QAAM,eAAe,aAAa;AAClC,QAAM,YAAY,WAAW;AAC7B,QAAM,oBAAoB,IAAI,MAAM,SAAS;AAC7C,QAAM,kBAAkB,IAAI,MAAM,YAAY;AAC9C,QAAM,OAAO,aAAa;AAC1B,MAAI,cAAc,GAAG;AACnB,QAAI,iBAAiB,GAAG;AACtB,YAAM,IAAI,MAAM,qBAAqB,gDAAgD,YAAY,CAAC;AAAA,IACpG;AACA,UAAM,gBAAgB,aAAa,kBAAkB,cAAc,CAAC;AACpE,UAAM,eAAe,aAAa,kBAAkB,aAAa,CAAC;AAClE,WAAO;AAAA,MACL;AAAA,MACA,CAAC,GAAG,IAAI;AAAA,MACR;AAAA,MACA;AAAA,MACA;AAAA,IACF;AAAA,EACF;AACA,MAAI,iBAAiB;AACrB,MAAI,iBAAiB;AACrB,QAAM,YAAY,IAAI,MAAM,SAAS,EAAE,KAAK,CAAC;AAC7C,WAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,UAAM,MAAM,QAAQ,KAAK;AACzB,QAAI,MAAM,GAAG;AACX,YAAM,IAAI,MAAM,qBAAqB,gDAAgD,IAAI,GAAG,CAAC;AAAA,IAC/F;AACA,QAAI,OAAO,WAAW;AACpB,YAAM,IAAI,MAAM,qBAAqB,kDAAkD,IAAI,KAAK,SAAS,CAAC;AAAA,IAC5G;AACA,MAAE,UAAU;AACZ,qBAAiB,kBAAkB,OAAO;AAC1C,qBAAiB;AAAA,EACnB;AACA,MAAI,cAAc;AAClB,WAAS,MAAM,GAAG,MAAM,WAAW,EAAE,KAAK;AACxC,UAAM,WAAW,UAAU,SAAS;AACpC,sBAAkB,OAAO;AACzB,kBAAc,eAAe,CAAC;AAC9B,cAAU,OAAO,KAAK,IAAI,UAAU,MAAM,CAAC;AAC3C,QAAI,MAAM,GAAG;AACX,gBAAU,QAAQ,UAAU,MAAM;AAAA,IACpC;AAAA,EACF;AACA,MAAI,eAAe,gBAAgB;AACjC,UAAM,gBAAgB;AACtB,UAAM,eAAe;AACrB,aAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,sBAAgB,MAAM;AAAA,IACxB;AACA,WAAO;AAAA,MACL;AAAA,MACA,CAAC,cAAc,IAAI;AAAA,MACnB;AAAA,MACA;AAAA,MACA;AAAA,IACF;AAAA,EACF,OAAO;AACL,UAAM,mBAAmB,UAAU,YAAY;AAC/C,UAAM,gBAAgB,aAAa,kBAAkB,cAAc,mBAAmB,IAAI;AAC1F,UAAM,eAAe,aAAa,kBAAkB,aAAa,gBAAgB;AACjF,UAAM,cAAc,IAAI,MAAM,SAAS,EAAE,KAAK,CAAC;AAC/C,aAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,YAAM,MAAM,QAAQ,KAAK;AACzB,YAAM,SAAS,YAAY;AAC3B,YAAM,WAAW,QAAQ,IAAI,IAAI,UAAU,MAAM,MAAM;AACvD,kBAAY;AACZ,eAAS,IAAI,GAAG,IAAI,MAAM,EAAE,GAAG;AAC7B,sBAAc,UAAU,OAAO,KAAK,QAAQ,KAAK,OAAO;AAAA,MAC1D;AACA,mBAAa,WAAW,OAAO;AAC/B,sBAAgB,MAAM;AAAA,IACxB;AACA,aAAS,MAAM,GAAG,MAAM,WAAW,EAAE,KAAK;AACxC,YAAM,WAAW,YAAY;AAC7B,UAAI,aAAa,GAAG;AAClB,cAAM,gBAAgB,QAAQ,IAAI,IAAI,UAAU,MAAM;AACtD,sBAAc,gBAAgB,OAAO,KAAK;AAC1C,iBAAS,MAAM,GAAG,MAAM,MAAM,EAAE,KAAK;AACnC,wBAAc,gBAAgB,OAAO,OAAO;AAAA,QAC9C;AACA,qBAAa,iBAAiB;AAAA,MAChC;AAAA,IACF;AACA,WAAO;AAAA,MACL;AAAA,MACA,CAAC,kBAAkB,IAAI;AAAA,MACvB;AAAA,MACA;AAAA,MACA;AAAA,IACF;AAAA,EACF;AACF;AAGA,SAAS,kBAAkB,cAAc,mBAAmB,YAAY,YAAY,aAAa;AAC/F,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,MAAM,kBAAkB;AAC9B,QAAM,aAAa,YAAY;AAC/B,QAAM,cAAc,CAAC;AACrB,MAAI,UAAU;AACd,MAAI,eAAe;AACnB,WAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,UAAMA,QAAO,YAAY;AACzB,QAAIA,UAAS,IAAI;AACf,UAAI,iBAAiB,IAAI;AACvB,cAAM,IAAI,MAAM,qBAAqB,yDAAyD,cAAc,CAAC,CAAC;AAAA,MAChH;AACA,qBAAe;AACf,kBAAY,KAAK,CAAC;AAAA,IACpB,OAAO;AACL,UAAIA,QAAO,GAAG;AACZ,cAAM,IAAI,MAAM,qBAAqB,8CAA8C,GAAGA,KAAI,CAAC;AAAA,MAC7F;AACA,iBAAWA;AACX,kBAAY,KAAKA,KAAI;AAAA,IACvB;AAAA,EACF;AACA,MAAI,iBAAiB,IAAI;AACvB,QAAI,WAAW,GAAG;AAChB,YAAM,IAAI,MAAM,qBAAqB,qDAAqD,CAAC;AAAA,IAC7F;AACA,UAAM,UAAU,KAAK,MAAM,YAAY,OAAO;AAC9C,QAAI,UAAU,YAAY,WAAW;AACnC,YAAM,IAAI,MAAM,qBAAqB,gDAAgD,YAAY,WAAW,CAAC;AAAA,IAC/G;AACA,gBAAY,gBAAgB;AAAA,EAC9B;AACA,QAAMoB,cAAa,aAAa,cAAc,WAAW;AACzD,MAAIA,gBAAe,WAAW;AAC5B,UAAM,IAAI,MAAM,qBAAqB,gDAAgD,YAAY,WAAW,CAAC;AAAA,EAC/G;AACA,QAAM,YAAY,WAAW;AAC7B,QAAM,eAAe,CAAC;AACtB,MAAI,YAAY,GAAG;AACjB,iBAAa,YAAY,KAAK;AAC9B,aAAS,IAAI,YAAY,GAAG,KAAK,GAAG,EAAE,GAAG;AACvC,mBAAa,KAAK,aAAa,IAAI,KAAK,WAAW,IAAI;AAAA,IACzD;AAAA,EACF;AACA,QAAM,gBAAgB,CAAC;AACvB,MAAI,aAAa,GAAG;AAClB,kBAAc,aAAa,KAAK;AAChC,aAAS,IAAI,aAAa,GAAG,KAAK,GAAG,EAAE,GAAG;AACxC,oBAAc,KAAK,cAAc,IAAI,KAAK,YAAY,IAAI;AAAA,IAC5D;AAAA,EACF;AACA,QAAM,aAAa,aAAa,kBAAkB,YAAY,MAAM,UAAU;AAC9E,WAAS,KAAK,GAAG,KAAK,KAAK,EAAE,IAAI;AAC/B,QAAI,KAAK;AACT,aAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,YAAM,aAAa,KAAK,YAAY,KAAK,aAAa;AAAA,IACxD;AACA,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,iBAAW,KAAK,aAAa,KAAK,KAAK,MAAM,KAAK,cAAc,EAAE;AAClE,YAAM,cAAc;AAAA,IACtB;AAAA,EACF;AACA,SAAO,CAAC,YAAY,CAAC,KAAK,UAAU,GAAG,WAAW;AACpD;AAGA,SAAS,2BAA2B,QAAQ,YAAY,YAAY,SAAS,YAAY,SAAS,OAAO,eAAe,GAAG;AACzH,QAAM,aAAa,QAAQ;AAC3B,QAAM,YAAY,CAAC,WAAW,IAAI,OAAO,SAAS,WAAW,EAAE;AAC/D,QAAM,SAAS,UAAU;AACzB,QAAM,uBAAuB,aAAa,IAAI,WAAW,aAAa,KAAK,IAAI;AAC/E,QAAM,aAAa;AACnB,MAAI,aAAa,GAAG;AAClB,UAAM,IAAI,MAAM,qBAAqB,wDAAwD,CAAC;AAAA,EAChG;AACA,QAAM,cAAc,WAAW,MAAM;AACrC,cAAY,KAAK;AACjB,QAAM,eAAe,YAAY,OAAO,CAAC,SAAS,UAAU,UAAU,OAAO,CAAC;AAC9E,QAAM,SAAS,aAAa,kBAAkB,YAAY,YAAY;AACtE,MAAI,eAAe,GAAG;AACpB,QAAI,aAAa,GAAG;AAClB,aAAO,KAAK,YAAY;AAAA,IAC1B;AACA,WAAO,CAAC,QAAQ,WAAW;AAAA,EAC7B;AACA,MAAI,cAAc,GAAG;AACnB,UAAM,IAAI,MAAM,qBAAqB,wDAAwD,CAAC;AAAA,EAChG;AACA,MAAI,QAAQ,GAAG,MAAM;AACrB,MAAI,qBAAqB;AACzB,MAAI,WAAW,WAAW;AAC1B,SAAO,MAAM;AACX,QAAI,YAAY;AAChB,QAAI,MAAM,YAAY;AACpB,kBAAY,WAAW;AACvB,UAAI,aAAa,WAAW;AAC1B,UAAE;AACF;AAAA,MACF;AACA,UAAI,YAAY,WAAW;AACzB,cAAM,IAAI,MAAM,qBAAqB,6DAA6D,CAAC;AAAA,MACrG;AAAA,IACF;AACA,QAAI,WAAW,KAAK,YAAY,YAAY;AAC1C,YAAM,IAAI,MAAM,qBAAqB,yDAAyD,UAAU,UAAU,CAAC;AAAA,IACrH;AACA,QAAI,WAAW,oBAAoB;AACjC,aAAO,KAAK,cAAc,qBAAqB,QAAQ,WAAW,MAAM;AAAA,IAC1E;AACA,aAAS,KAAK,OAAO,KAAK,KAAK,EAAE,IAAI;AACnC,YAAMX,SAAQ,QAAQ;AACtB,UAAIA,SAAQ,KAAKA,UAAS,UAAU,IAAI;AACtC,cAAM,IAAI,MAAM,qBAAqB,uDAAuD,IAAI,QAAQ,KAAK,UAAU,EAAE,CAAC;AAAA,MAC5H;AACA,eAAS,IAAI,GAAG,IAAI,QAAQ,KAAK;AAC/B,eAAO,WAAW,SAAS,MAAM,OAAOA,SAAQ,SAAS;AAAA,MAC3D;AAAA,IACF;AACA,QAAI,QAAQ;AACV,eAAS,IAAI,GAAG,IAAI,QAAQ,KAAK;AAC/B,eAAO,WAAW,SAAS,MAAM,MAAM;AAAA,MACzC;AAAA,IACF;AACA,YAAQ;AACR,MAAE;AACF,yBAAqB,WAAW;AAChC,eAAW;AACX,QAAI,MAAM,YAAY;AACpB;AAAA,IACF;AAAA,EACF;AACA,MAAI,qBAAqB,YAAY;AACnC,WAAO,KAAK,cAAc,qBAAqB,QAAQ,aAAa,MAAM;AAAA,EAC5E;AACA,SAAO,CAAC,QAAQ,WAAW;AAC7B;AAGA,IAAI,WAAW,sBAAsB,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AAC1D,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,wBAAwB,6BAA6B,CAAC,GAAG,MAAM;AACjE,QAAM,OAAO,IAAI;AACjB,SAAO,OAAO;AAChB,CAAC;AACD,IAAI,qBAAqB,iBAAiB,mBAAmB,qBAAqB;AAClF,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,iBAAiB,UAAU,MAAMG,UAAS,OAAO;AACxD,QAAM,SAAS,OAAO,UAAU,KAAK,KAAK;AAC1C,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM,MAAM;AACvC,UAAM,MAAM,OAAO,WAAW,EAAE;AAChC,UAAM,SAAS,IAAI,MAAM,IAAI,MAAM;AACnC,aAAS,IAAI,GAAG,IAAI,OAAO,QAAQ,KAAK;AACtC,aAAO,KAAK,IAAI,KAAKA,SAAQ,KAAK,MAAM;AAAA,IAC1C;AACA,WAAO,IAAI,KAAK,IAAI,GAAG,MAAM,GAAG,GAAG,GAAG;AAAA,EACxC;AACA,SAAO;AACT;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,WAAW,aAAa,SAAS,WAAW,UAAU,wBAAwB;AACxF,SAAK,YAAY,aAAa,aAAa,SAAS;AACpD,SAAK,cAAc;AACnB,SAAK,UAAU,aAAa,aAAa,OAAO;AAChD,SAAK,WAAW,aAAa,aAAa,SAAS;AACnD,SAAK,WAAW;AAChB,SAAK,gBAAgB;AAAA,EACvB;AAAA,EACA,YAAY,YAAY;AACtB,WAAO,KAAK,IAAI,KAAK,WAAW,IAAI,aAAa,IAAI,KAAK,UAAU,aAAa,CAAC;AAAA,EACpF;AAAA,EACA,aAAa,QAAQ,YAAY;AAC/B,UAAM,WAAW,KAAK,YAAY,UAAU;AAC5C,WAAO,KAAK,IAAI,GAAG,SAAS,IAAI,WAAW,aAAa,CAAC;AAAA,EAC3D;AAAA,EACA,aAAa,MAAM,YAAY,QAAQ,kBAAkB,WAAW,YAAY;AAC9E,aAAS,aAAa,GAAG,aAAa,WAAW,EAAE,YAAY;AAC7D,YAAM,WAAW,KAAK,YAAY,UAAU;AAC5C,YAAM,cAAc,KAAK,IAAI,GAAG,WAAW,UAAU;AACrD,YAAM,eAAe,KAAK,IAAI,GAAG,YAAY,aAAa,aAAa,GAAG;AAC1E,YAAM,YAAY,cAAc,cAAc;AAC9C,YAAM,iBAAiB,cAAc,cAAc,IAAI,IAAI,aAAa;AACxE,UAAI,YAAY;AAChB,mBAAa,cAAc,KAAK,QAAQ;AACxC,eAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,qBAAa,KAAK,iBAAiB,IAAI;AAAA,MACzC;AACA,mBAAa,eAAe,KAAK,SAAS;AAC1C,YAAM,gBAAgB,cAAc,eAAe,YAAY;AAC/D,mBAAa,gBAAgB,KAAK,UAAU;AAC5C,aAAO,mBAAmB,cAAc,IAAI,WAAW,SAAS;AAChE,YAAM,QAAQ,OAAO,mBAAmB;AACxC,UAAI,iBAAiB;AACrB,YAAM,gBAAgB,CAAC,QAAQ,IAAI,QAAQ,CAAC,UAAU,MAAM,oBAAoB,KAAK;AACrF,eAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,sBAAc,KAAK,OAAO;AAC1B,sBAAc,KAAK,SAAS;AAAA,MAC9B;AACA,eAAS,KAAK,GAAG,KAAK,YAAY,GAAG,EAAE,IAAI;AACzC,sBAAc,KAAK,iBAAiB,GAAG;AACvC,sBAAc,KAAK,SAAS;AAAA,MAC9B;AACA,UAAI,YAAY,GAAG;AACjB,sBAAc,KAAK,iBAAiB,YAAY,EAAE;AAClD,iBAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,wBAAc,KAAK,SAAS;AAC5B,wBAAc,KAAK,QAAQ;AAAA,QAC7B;AAAA,MACF,OAAO;AACL,iBAAS,KAAK,GAAG,KAAK,eAAe,GAAG,EAAE,IAAI;AAC5C,wBAAc,KAAK,QAAQ;AAC3B,wBAAc,KAAK,SAAS;AAAA,QAC9B;AACA,sBAAc,KAAK,QAAQ;AAAA,MAC7B;AAAA,IACF;AAAA,EACF;AAAA,EACA,QAAQ,MAAM,QAAQ;AACpB,UAAM,gBAAgB,KAAK;AAC3B,UAAM,aAAa,OAAO;AAC1B,QAAI,aAAa,GAAG;AAClB,UAAI,YAAY,OAAO;AACvB,UAAI,cAAc,GAAG;AACnB,cAAM,IAAI,MAAM,oCAAoC,WAAW;AAAA,MACjE;AACA,eAAS,KAAK,GAAG,KAAK,YAAY,EAAE,IAAI;AACtC,YAAI,cAAc,OAAO,OAAO;AAChC,sBAAc,eAAe,OAAO,OAAO;AAC3C,YAAI,CAAC,aAAa;AAChB,gBAAM,IAAI,MAAM,uBAAuB,OAAO,oBAAoB,cAAc,gBAAgB;AAAA,QAClG;AACA,oBAAY,OAAO;AAAA,MACrB;AACA,UAAI,cAAc,eAAe;AAC/B,cAAM,IAAI,MAAM,gDAAgD,sBAAsB,WAAW;AAAA,MACnG;AAAA,IACF;AACA,UAAM,gBAAgB,aAAa;AACnC,UAAM,eAAe,aAAa,kBAAkB,SAAS,UAAU;AACvE,QAAI,kBAAkB,KAAK,eAAe,GAAG;AAC3C,YAAM,QAAQ,IAAI,MAAM,aAAa;AACrC,eAAS,KAAK,GAAG,MAAM,eAAe,EAAE,IAAI;AAC1C,qBAAa,MAAM;AAAA,MACrB;AACA,aAAO,CAAC,OAAO,YAAY;AAAA,IAC7B;AACA,iBAAa,KAAK;AAClB,aAAS,KAAK,GAAG,MAAM,eAAe,EAAE,IAAI;AAC1C,YAAM,SAAS,OAAO,MAAM,OAAO,KAAK;AACxC,UAAI,YAAY;AAChB,WAAK,YAAY,QAAQ,CAAC,eAAe;AACvC,qBAAa,KAAK,aAAa,QAAQ,UAAU;AAAA,MACnD,CAAC;AACD,UAAI,KAAK,iBAAiB,SAAS,KAAK,cAAc,GAAG;AACvD,oBAAY;AAAA,MACd;AACA,mBAAa,MAAM,aAAa,KAAK,KAAK;AAAA,IAC5C;AACA,UAAM,SAAS,IAAI,MAAM,aAAa,cAAc;AACpD,aAAS,KAAK,GAAG,KAAK,eAAe,EAAE,IAAI;AACzC,YAAM,aAAa,OAAO;AAC1B,UAAI,iBAAiB,aAAa;AAClC,WAAK,YAAY,QAAQ,CAAC,eAAe;AACvC,cAAM,SAAS,OAAO,KAAK,KAAK,OAAO;AACvC,cAAM,YAAY,KAAK,aAAa,QAAQ,UAAU;AACtD,aAAK,aAAa,MAAM,YAAY,QAAQ,gBAAgB,WAAW,UAAU;AACjF,0BAAkB;AAAA,MACpB,CAAC;AACD,UAAI,KAAK,iBAAiB,mBAAmB,aAAa,KAAK;AAC7D,cAAM,aAAa,OAAO,KAAK,KAAK,OAAO;AAC3C,YAAI,eAAe,GAAG;AACpB;AAAA,QACF;AACA,cAAM,aAAa,aAAa,IAAI,KAAK;AACzC,cAAM,YAAY;AAClB,aAAK,aAAa,MAAM,YAAY,QAAQ,gBAAgB,WAAW,UAAU;AAAA,MACnF;AAAA,IACF;AACA,WAAO,CAAC,QAAQ,YAAY;AAAA,EAC9B;AACF;AACA,SAAS,iBAAiB,MAAM,YAAY,WAAW,aAAa,SAAS,WAAW,UAAU,wBAAwB;AACxH,SAAO,IAAI,eAAe,WAAW,aAAa,SAAS,WAAW,UAAU,sBAAsB,EAAE,QAAQ,MAAM,UAAU;AAClI;AAGA,SAAS,OAAO,KAAK,YAAY,WAAW,QAAQ;AAClD,MAAI,CAAC,IAAI,QAAQ;AACf;AAAA,EACF;AACA,MAAI,WAAW,WAAW,GAAG;AAC3B,aAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,aAAO,KAAK,IAAI,SAAS,IAAI,KAAK,CAAC,CAAC;AAAA,IACtC;AACA;AAAA,EACF;AACA,MAAI,WAAW,WAAW,GAAG;AAC3B,UAAM,YAAY,WAAW;AAC7B,QAAI,IAAI,IAAI,QAAQ,SAAS;AAC7B,WAAO,MAAM,IAAI;AACf,YAAM,QAAQ,IAAI,SAAS,GAAG,CAAC;AAC/B,UAAI,CAAC,aAAa,MAAM,WAAW,GAAG;AACpC,eAAO,KAAK,KAAK;AAAA,MACnB;AACA,YAAM,IAAI,SAAS,IAAI,CAAC;AACxB,UAAI,IAAI,QAAQ,SAAS;AAAA,IAC3B;AACA,QAAI,CAAC,aAAa,IAAI,WAAW,GAAG;AAClC,aAAO,KAAK,GAAG;AAAA,IACjB;AACA;AAAA,EACF;AACA,MAAI,aAAa;AACjB,WAAS,KAAK,GAAG,KAAK,IAAI,SAAS,GAAG,MAAM;AAC1C,QAAI,OAAO,IAAI,UAAU,WAAW,QAAQ,IAAI,GAAG,MAAM,IAAI;AAC3D,YAAM,QAAQ,IAAI,SAAS,YAAY,EAAE;AACzC,UAAI,CAAC,aAAa,MAAM,WAAW,GAAG;AACpC,eAAO,KAAK,KAAK;AAAA,MACnB;AACA,mBAAa,KAAK;AAAA,IACpB;AAAA,EACF;AACF;AACA,SAAS,gBAAgB,QAAQ,WAAW,WAAW;AACrD,QAAM,YAAY,OAAO;AACzB,QAAM,SAAS,CAAC;AAChB,MAAIQ,cAAa;AACjB,MAAI,gBAAgB;AACpB,QAAM,aAAa,IAAI,MAAM,SAAS;AACtC,WAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,UAAM,mBAAmB,OAAO;AAChC,WAAO,OAAO,KAAK,WAAW,WAAW,MAAM;AAC/C,UAAM,WAAW,OAAO,SAAS;AACjC,eAAW,MAAM;AACjB,IAAAA,eAAc;AACd,oBAAgB,KAAK,IAAI,eAAe,QAAQ;AAAA,EAClD;AACA,QAAM,UAAU,aAAa,kBAAkB,SAASA,cAAa,CAAC;AACtE,QAAM,SAAS,IAAI,MAAMA,WAAU;AACnC,QAAM,QAAQ,CAAC,WAAW,aAAa;AACvC,MAAI,IAAI;AACR,WAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,aAAS,IAAI,GAAG,IAAI,WAAW,KAAK,EAAE,GAAG;AACvC,cAAQ,IAAI,KAAK;AACjB,cAAQ,IAAI,IAAI,KAAK;AACrB,aAAO,KAAK,OAAO;AACnB,QAAE;AAAA,IACJ;AAAA,EACF;AACA,SAAO,CAAC,SAAS,QAAQ,KAAK;AAChC;AAGA,SAAS,2BAA2B,QAAQ,YAAY;AACtD,QAAM,SAAS,aAAa,kBAAkB,SAAS,OAAO,MAAM;AACpE,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,WAAO,MAAM,aAAa,cAAc,OAAO,GAAG,EAAE,OAAO,UAAU,EAAE,mBAAmB;AAAA,EAC5F;AACA,SAAO;AACT;AAGA,IAAI,UAAU,6BAA6B,CAAC,QAAQ,WAAW,SAAS,MAAM;AAC9E,IAAI,iBAAiB,8BAA8B,CAAC,OAAO,OAAO,OAAO,UAAU;AACjF,SAAO,EAAE,MAAM,QAAQ,OAAO,MAAM,QAAQ,MAAM;AACpD,CAAC;AACD,IAAI,OAAO,iBAAiB,KAAK,SAAS,cAAc;AACxD,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM,MAAM;AAC5B,QAAM,WAAW,IAAI,MAAM,KAAK,IAAI;AACpC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,aAAS,MAAM,KAAK,MAAM,MAAM,KAAK;AAAA,EACvC;AACA,QAAM,SAAS,OAAO,UAAU,KAAK,KAAK;AAC1C,WAAS,KAAK,GAAG,KAAK,OAAO,OAAO,QAAQ,EAAE,IAAI;AAChD,UAAM,SAAS,OAAO,WAAW,EAAE;AACnC,UAAM,cAAc,IAAI,MAAM,KAAK,IAAI;AACvC,aAAS,IAAI,GAAG,IAAI,YAAY,QAAQ,KAAK;AAC3C,kBAAY,KAAK,OAAO,KAAK,KAAK,MAAM;AAAA,IAC1C;AACA,UAAM,gBAAgB,KAAK,WAAW,WAAW;AACjD,WAAO,OAAO,MAAM,KAAK,OAAO;AAAA,EAClC;AACA,SAAO;AACT;AAGA,IAAI,cAAc,CAAC,GAAG,MAAM;AAC1B,QAAM,YAAY,EAAE,QAAQ,EAAE;AAC9B,SAAO,cAAc,IAAI,EAAE,QAAQ,EAAE,QAAQ;AAC/C;AACA,SAAS,OAAO,QAAQ,GAAG,OAAO,GAAG,QAAQ,OAAO,SAAS,GAAG;AAC9D,SAAO,QAAQ,MAAM;AACnB,QAAI,QAAQ,OAAO,KAAK;AACtB,YAAM,KAAK,QAAQ,OAAO;AAC1B,YAAM,KAAK,IAAI,OAAO;AACtB,YAAM,IAAI,KAAK,IAAI,EAAE;AACrB,YAAM,KAAK,MAAM,KAAK,IAAI,IAAI,IAAI,CAAC;AACnC,YAAM,KAAK,MAAM,KAAK,KAAK,IAAI,MAAM,KAAK,MAAM,EAAE,IAAI,KAAK,KAAK,KAAK,KAAK,CAAC;AAC3E,YAAM,UAAU,KAAK,IAAI,MAAM,KAAK,MAAM,IAAI,KAAK,KAAK,KAAK,EAAE,CAAC;AAChE,YAAM,WAAW,KAAK,IAAI,OAAO,KAAK,MAAM,KAAK,KAAK,MAAM,KAAK,KAAK,EAAE,CAAC;AACzE,aAAO,QAAQ,GAAG,SAAS,QAAQ;AAAA,IACrC;AACA,UAAM,KAAK,OAAO;AAClB,QAAI,KAAK;AACT,QAAI,IAAI;AACR,iBAAa,KAAK,QAAQ,MAAM,CAAC;AACjC,QAAI,YAAY,OAAO,QAAQ,EAAE,IAAI,GAAG;AACtC,mBAAa,KAAK,QAAQ,MAAM,KAAK;AAAA,IACvC;AACA,WAAO,KAAK,GAAG;AACb,mBAAa,KAAK,QAAQ,IAAI,CAAC;AAC/B;AACA;AACA,aAAO,YAAY,OAAO,KAAK,EAAE,IAAI,GAAG;AACtC,aAAK,KAAK;AAAA,MACZ;AACA,aAAO,YAAY,OAAO,IAAI,EAAE,IAAI,GAAG;AACrC,YAAI,IAAI;AAAA,MACV;AAAA,IACF;AACA,QAAI,YAAY,OAAO,OAAO,EAAE,MAAM,GAAG;AACvC,mBAAa,KAAK,QAAQ,MAAM,CAAC;AAAA,IACnC,OAAO;AACL,UAAI,IAAI;AACR,mBAAa,KAAK,QAAQ,GAAG,KAAK;AAAA,IACpC;AACA,QAAI,KAAK,GAAG;AACV,aAAO,IAAI;AAAA,IACb;AACA,QAAI,KAAK,GAAG;AACV,cAAQ,IAAI;AAAA,IACd;AAAA,EACF;AACF;AACA,SAAS,SAAS,GAAG,QAAQ,QAAQ,GAAG,QAAQ;AAC9C,QAAM,UAAU,OAAO,OAAO,SAAS;AACvC,QAAM,CAAC,OAAOpB,KAAI,IAAI,CAAC,EAAE,SAAS,SAAS,OAAO;AAClD,QAAM,cAAc,aAAa,uBAAuB,QAAQ,QAAQ,CAAC;AACzE,QAAM,iBAAiB,aAAa,uBAAuB,SAAS,QAAQ,CAAC;AAC7E,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,UAAM,SAAS,IAAIA;AACnB,UAAM,OAAO,EAAE,SAAS,QAAQ,SAASA,KAAI;AAC7C,QAAI,YAAY,IAAI,MAAM,KAAK,MAAM;AACrC,SAAK,QAAQ,CAAC,OAAOS,WAAU,UAAUA,UAAS,EAAE,OAAO,OAAAA,OAAM,CAAC;AAClE,QAAI,IAAI,UAAU,QAAQ;AACxB,aAAO,WAAW,CAAC;AACnB,kBAAY,UAAU,MAAM,GAAG,CAAC;AAAA,IAClC;AACA,QAAI,QAAQ;AACV,gBAAU,KAAK,WAAW;AAAA,IAC5B;AACA,UAAM,YAAY,IAAI;AACtB,UAAM,WAAW,YAAY,SAAS,WAAW,YAAY,CAAC;AAC9D,UAAM,cAAc,eAAe,SAAS,WAAW,YAAY,CAAC;AACpE,aAAS,KAAK,GAAG,KAAK,GAAG,MAAM;AAC7B,eAAS,MAAM,UAAU,IAAI;AAC7B,kBAAY,MAAM,UAAU,IAAI;AAAA,IAClC;AAAA,EACF;AACA,QAAM,cAAc,OAAO,MAAM;AACjC,cAAY,YAAY,SAAS,KAAK;AACtC,SAAO;AAAA,IACL,OAAO,aAAa,QAAQ,WAAW;AAAA,IACvC,OAAO,aAAa,SAAS,cAAc;AAAA,EAC7C;AACF;AAGA,SAAS,WAAW,QAAQ,MAAM,OAAO,OAAO;AAC9C,QAAM,QAAQ,aAAa,eAAe,MAAM,KAAK,EAAE;AACvD,QAAM,WAAW,CAAC,GAAG,MAAM,IAAI,CAAC;AAChC,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM;AACjC,aAAS,MAAM,MAAM;AAAA,EACvB;AACA,WAAS,KAAK,MAAM;AACpB,WAAS,KAAK,QAAQ,GAAG,KAAK,MAAM,QAAQ,MAAM;AAChD,aAAS,MAAM,MAAM;AAAA,EACvB;AACA,QAAM,iBAAiB,CAAC;AACxB,QAAM,UAAU,IAAI,WAAW,MAAM,MAAM;AAC3C,QAAM,cAAc,IAAI,aAAa,UAAU,OAAO,MAAM;AAC5D,QAAM,gBAAgB,CAAC;AACvB,QAAM,aAAa,SAAS,OAAO,KAAK,SAAS,OAAO;AACxD,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,QAAI;AACJ,QAAI,YAAY;AACd,gBAAU,OAAO,IAAI,SAAS;AAAA,IAChC,OAAO;AACL,YAAM,aAAa,CAAC;AACpB,eAAS,IAAI,GAAG,IAAI,SAAS,IAAI,KAAK;AACpC,iBAAS,KAAK,GAAG,KAAK,SAAS,IAAI,MAAM;AACvC,qBAAW,KAAK,YAAY,IAAI,GAAG,IAAI,EAAE,CAAC;AAAA,QAC5C;AAAA,MACF;AACA,gBAAU,WAAW,KAAK,GAAG;AAAA,IAC/B;AACA,QAAI,eAAe,aAAa,QAAQ;AACtC,cAAQ,MAAM,eAAe;AAAA,IAC/B,OAAO;AACL,YAAM,cAAc,OAAO,KAAK,cAAc,EAAE;AAChD,qBAAe,WAAW;AAC1B,cAAQ,MAAM;AACd,oBAAc,KAAK,EAAE;AAAA,IACvB;AAAA,EACF;AACA,QAAM,iBAAiB,SAAS,MAAM;AACtC,iBAAe,KAAK,OAAO,KAAK,cAAc,EAAE;AAChD,QAAM,eAAe,IAAI,aAAa,gBAAgB,KAAK;AAC3D,gBAAc,QAAQ,CAAC,oBAAoB,OAAO;AAChD,aAAS,IAAI,GAAG,IAAI,SAAS,IAAI,KAAK;AACpC,eAAS,KAAK,GAAG,KAAK,SAAS,IAAI,MAAM;AACvC,qBAAa,IAAI,YAAY,IAAI,GAAG,oBAAoB,EAAE,GAAG,GAAG,IAAI,EAAE;AAAA,MACxE;AAAA,IACF;AAAA,EACF,CAAC;AACD,QAAM,cAAc,MAAM,MAAM;AAChC,cAAY,SAAS,eAAe;AACpC,SAAO;AAAA,IACL,cAAc,aAAa;AAAA,IAC3B;AAAA,IACA;AAAA,EACF;AACF;AAGA,gBAAgB,OAAO,MAAM,IAAI,eAAe,GAAG,CAAC;AAGpD,IAAI,OAAO,gBAAgB,KAAK,CAAC,OAAO,MAAM,IAAI,KAAK,KAAK,IAAI,EAAE,IAAI,CAAC;AACvE,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAAa,OAAM,IAAI;AAClB,mBAAiB,CAAC,CAAC,GAAG,WAAW;AACjC,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,UAAU,aAAa,uBAAuB,WAAW,KAAK;AACpE,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,YAAQ,MAAM,MAAM,MAAM,IAAIA,SAAQ,MAAM,MAAM,MAAM;AAAA,EAC1D;AACA,SAAO,SAAS,eAAe,EAAE,OAAO,WAAW,OAAO;AAC5D;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY,6BAA6B,CAAC,QAAQ,WAAW,SAAS,IAAI,SAAS,SAAS,MAAM;AACtG,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,GAAG,OAAAA,OAAM,IAAI;AACrB,mBAAiB,CAAC,GAAGA,MAAK,GAAG,OAAO;AACpC,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,QAAQ,SAAS,KAAK,IAAIA,OAAM,MAAM,EAAE;AAC9C,QAAM,CAAC,YAAY,WAAW,IAAI,UAAU,EAAE,OAAOA,OAAM,OAAO,OAAO,OAAO,SAAS;AACzF,SAAO,SAAS,eAAe,aAAa,WAAW,UAAU;AACnE;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,IAAI,GAAG,EAAE,CAAC;AACzD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO,KAAK,IAAI,KAAK,IAAI,GAAG,EAAE,GAAG,CAAC,CAAC;AACxE,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,iBAAiB,UAAU,GAAG,aAAa,wBAAwB,gBAAgB;AAC1F,MAAI,gBAAgB,UAAU;AAC5B,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD,WAAW,gBAAgB,QAAQ;AACjC,WAAO,MAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACnD,WAAW,gBAAgB,OAAO;AAChC,WAAO,KAAK,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EAClD,WAAW,gBAAgB,SAAS;AAClC,WAAO,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACpD,WAAW,gBAAgB,SAAS;AAClC,WAAO,OAAO,EAAE,QAAQ,EAAE,GAAG,OAAO,uBAAuB,GAAG,SAAS,SAAS,CAAC;AAAA,EACnF,WAAW,gBAAgB,aAAa;AACtC,WAAO,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,eAAe,EAAE,CAAC;AAAA,EAC1F,WAAW,gBAAgB,WAAW;AACpC,WAAO,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACtD;AACA,QAAM,IAAI,MAAM,cAAc,2DAA2D;AAC3F;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,SAAS,aAAa,uBAAuB,OAAO,KAAK;AAC/D,QAAM,SAAS,aAAa,cAAc,MAAM;AAChD,eAAa,OAAO,UAAU,QAAQ,MAAM,kBAAkB,eAAe,sCAAsC,EAAE,cAAc,oFAAoF;AACvN,WAAS,OAAO,EAAE,MAAM;AACxB,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM;AACxC,MAAI,MAAM,sBAAsB,MAAM;AACpC,UAAM,QAAQ,MAAM,mBAAmB;AACvC,UAAM,QAAQ,MAAM,mBAAmB;AACvC,UAAM,QAAQ;AACd,UAAM,QAAQ;AAAA,EAChB;AACA,SAAO,EAAE,QAAQ,EAAE,QAAQ,OAAO,QAAQ,OAAO,EAAE,MAAM;AAC3D;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,EAAE,IAAI;AACjB,QAAM,EAAE,YAAY,WAAW,IAAI;AACnC,mBAAiB,CAAC,GAAG,CAAC,GAAG,QAAQ;AACjC,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,oBAAoB,uBAAuB,2BAA2B,EAAE,MAAM,MAAM,GAAG,EAAE,GAAG,EAAE,MAAM,MAAM,GAAG,EAAE,CAAC;AACtH,QAAM,WAAW,kBAAkB,OAAO,CAAC,aAAa,WAAW,CAAC;AACpE,eAAa,OAAO,gBAAgB,aAAa,MAAM,kCAAkC,qBAAqB,uCAAuC,EAAE,aAAa,EAAE,wBAAwB,6BAA6B,wBAAwB;AACnP,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,YAAY,aAAa,IAAI,MAAM,KAAK,IAAI,MAAM;AACxD,QAAM,UAAU,aAAa,IAAI,MAAM,KAAK,IAAI,MAAM;AACtD,QAAM,WAAW,aAAa,IAAI,MAAM,KAAK,IAAI,MAAM;AACvD,QAAM,WAAW,KAAK,IAAI,WAAW,SAAS;AAC9C,QAAM,YAAY,SAAS,KAAK,IAAI,IAAI,MAAM,EAAE;AAChD,QAAM,YAAY,SAAS,KAAK,IAAI,IAAI,MAAM,EAAE;AAChD,QAAM,aAAa,aAAa,eAAe,IAAI,KAAK;AACxD,QAAM,aAAa,aAAa,eAAe,IAAI,KAAK;AACxD,QAAM,CAAC,QAAQ,YAAY,UAAU,IAAI,aAAa,CAAC,WAAW,IAAI,GAAG,WAAW,EAAE,IAAI,CAAC,WAAW,IAAI,WAAW,IAAI,CAAC;AAC1H,QAAM,CAAC,YAAY,YAAY,MAAM,IAAI,aAAa,CAAC,GAAG,WAAW,IAAI,WAAW,EAAE,IAAI,CAAC,WAAW,IAAI,GAAG,WAAW,EAAE;AAC1H,QAAMtB,QAAO,UAAU;AACvB,QAAM,SAAS,OAAO,CAAC,UAAU,SAAS,QAAQ,GAAG,IAAI,KAAK;AAC9D,QAAM,UAAU,OAAO;AACvB,QAAM,YAAY,SAAS;AAC3B,WAAS,KAAK,GAAG,KAAK,UAAU,MAAM;AACpC,aAAS,KAAK,GAAG,KAAK,SAAS,MAAM,WAAW;AAC9C,eAAS,KAAK,GAAG,KAAK,UAAU,MAAM,WAAW;AAC/C,iBAAS,MAAM,GAAG,MAAM,WAAW,OAAO,WAAW;AACnD,gBAAM,SAAS,KAAK,IAAI,KAAK,WAAW,OAAO;AAC/C,gBAAM,SAAS,KAAK,IAAI,KAAK,WAAW,QAAQ;AAChD,gBAAM,SAAS,KAAK,IAAI,MAAM,WAAW,SAAS;AAClD,mBAAS,KAAK,IAAI,KAAK,QAAQ,MAAM;AACnC,qBAAS,IAAI,IAAI,IAAI,QAAQ,KAAK;AAChC,kBAAI,OAAO;AACX,uBAAS,IAAI,KAAK,IAAI,QAAQ,KAAK;AACjC,sBAAM,eAAe,KAAK,IAAI,IAAI,YAAY,CAAC,IAAI;AACnD,sBAAM,eAAe,KAAK,IAAI,IAAI,YAAY,CAAC,IAAI;AACnD,sBAAM,OAAO,UAAU,eAAe,KAAK,aAAa,IAAI;AAC5D,sBAAM,OAAO,UAAU,IAAI,aAAa,IAAI,aAAa;AACzD,wBAAQ,OAAO;AAAA,cACjB;AACA,sBAAQ,KAAKA,SAAQ,KAAK,WAAW,OAAO;AAAA,YAC9C;AAAA,UACF;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,WAAS,8BAA8B,GAAG;AAC1C,WAAS,8BAA8B,GAAG;AAC1C,SAAO,SAAS,eAAe,UAAU,OAAO,OAAO,OAAO,MAAM;AACtE;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,MAAM,uBAAuB,IAAI;AAC/C,QAAM,EAAE,YAAY,YAAY,YAAY,aAAa,eAAe,IAAI;AAC5E,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,QAAM,gBAAgB,CAAC;AACvB,QAAM,YAAY,YAAY,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,OAAO,EAAE,YAAY,WAAW,GAAG,SAAS,SAAS,CAAC;AACxG,YAAU;AACV,MAAI,MAAM;AACR,aAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,KAAK,GAAG,SAAS,SAAS,CAAC;AACpE,kBAAc,KAAK,OAAO;AAC1B,cAAU;AAAA,EACZ;AACA,MAAI,aAAa;AACf,oBAAgB,iBAAiB,UAAU,SAAS,aAAa,wBAAwB,cAAc;AACvG,kBAAc,KAAK,OAAO;AAC1B,cAAU;AAAA,EACZ;AACA,aAAW,MAAM,eAAe;AAC9B,aAAS,8BAA8B,EAAE;AAAA,EAC3C;AACA,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO,KAAK,MAAM,EAAE,CAAC;AAC1D,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,UAAU;AAChB,mBAAiB,QAAQ,MAAM;AAC/B,QAAM,OAAO,QAAQ,IAAI,CAAC,OAAO,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE,MAAM;AACpE,QAAM,SAAS,OAAO,QAAQ,GAAG,OAAO,QAAQ,GAAG,KAAK;AACxD,QAAM,UAAU,OAAO;AACvB,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,UAAM,WAAW,KAAK;AACtB,aAAS,IAAI,GAAG,IAAI,QAAQ,QAAQ,KAAK;AACvC,cAAQ,MAAM,SAAS;AAAA,IACzB;AAAA,EACF;AACA,SAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC1E;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,mBAAiB,GAAG,KAAK;AACzB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,EAAE,MAAM,MAAM;AAAA,EAC1E;AACA,uBAAqB,2BAA2B,OAAO,MAAM,GAAG,MAAM,MAAM;AAC5E,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,GAAG,OAAO,IAAI;AAC7F,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,OAAO,aAAa,oBAAoB,aAAa,cAAc,QAAQ,GAAG,GAAG,KAAK;AAC5F,QAAM,QAAQ,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC3C,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,SAAS,KAAK;AACpB,QAAIF,QAAO,MAAM;AACjB,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,YAAM,QAAQ,MAAM,SAAS;AAC7B,MAAAA,QAAOA,SAAQ;AAAA,IACjB;AACA,SAAK,MAAMA;AAAA,EACb;AACA,MAAI,gBAAgB,MAAM;AACxB,aAAS,8BAA8B,EAAE;AAAA,EAC3C;AACA,QAAM,SAAS,SAAS,eAAe,UAAU,GAAG,OAAO,IAAI;AAC/D,MAAI,UAAU;AACZ,UAAM,gBAAgB,qBAAqB,qBAAqB,UAAU,QAAQ;AAClF,UAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAC7G,aAAS,8BAA8B,MAAM;AAC7C,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,mBAAiB,GAAG,KAAK;AACzB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,EAAE,MAAM,MAAM;AAAA,EAC1E;AACA,uBAAqB,2BAA2B,OAAO,MAAM,GAAG,MAAM,MAAM;AAC5E,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,GAAG,OAAO,IAAI;AAC7F,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,OAAO,aAAa,oBAAoB,aAAa,cAAc,QAAQ,GAAG,GAAG,KAAK;AAC5F,QAAM,QAAQ,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC3C,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,SAAS,KAAK;AACpB,QAAI,SAAS,MAAM;AACnB,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,YAAM,QAAQ,MAAM,SAAS;AAC7B,eAAS,UAAU;AAAA,IACrB;AACA,SAAK,MAAM;AAAA,EACb;AACA,MAAI,gBAAgB,MAAM;AACxB,aAAS,8BAA8B,EAAE;AAAA,EAC3C;AACA,QAAM,SAAS,SAAS,eAAe,UAAU,GAAG,OAAO,IAAI;AAC/D,MAAI,UAAU;AACZ,UAAM,gBAAgB,qBAAqB,qBAAqB,UAAU,QAAQ;AAClF,UAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAC7G,aAAS,8BAA8B,MAAM;AAC7C,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,mBAAiB,GAAG,QAAQ;AAC5B,MAAI,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACpD,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,QAAM,0BAA0B,CAAC;AACjC,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,4BAAwB,KAAK,EAAE;AAC/B,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,GAAG,MAAM,MAAM;AAAA,EAC3E;AACA,SAAO,CAAC,KAAK,EAAE;AACf,uBAAqB,2BAA2B,UAAU,MAAM,GAAG,MAAM,MAAM;AAC/E,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,GAAG,OAAO,IAAI;AAC7F,QAAM,UAAU,aAAa,cAAc,QAAQ;AACnD,QAAM,OAAO,aAAa,oBAAoB,SAAS,OAAO;AAC9D,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,QAAQ,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC3C,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,SAAS,KAAK;AACpB,QAAI,OAAO,MAAM;AACjB,QAAI,WAAW;AACf,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,YAAM,QAAQ,MAAM,SAAS;AAC7B,UAAI,QAAQ,MAAM;AAChB,eAAO;AACP,mBAAW;AAAA,MACb;AAAA,IACF;AACA,SAAK,MAAM;AAAA,EACb;AACA,0BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,SAAO,SAAS,eAAe,UAAU,SAAS,IAAI;AACxD;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,mBAAiB,GAAG,QAAQ;AAC5B,MAAI,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACpD,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,QAAM,0BAA0B,CAAC;AACjC,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,4BAAwB,KAAK,EAAE;AAC/B,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,GAAG,MAAM,MAAM;AAAA,EAC3E;AACA,SAAO,CAAC,KAAK,EAAE;AACf,uBAAqB,2BAA2B,UAAU,MAAM,GAAG,MAAM,MAAM;AAC/E,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,GAAG,OAAO,IAAI;AAC7F,QAAM,UAAU,aAAa,cAAc,QAAQ;AACnD,QAAM,OAAO,aAAa,oBAAoB,SAAS,OAAO;AAC9D,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,QAAQ,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC3C,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,SAAS,KAAK;AACpB,QAAI,OAAO,MAAM;AACjB,QAAI,WAAW;AACf,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,YAAM,QAAQ,MAAM,SAAS;AAC7B,UAAI,QAAQ,MAAM;AAChB,eAAO;AACP,mBAAW;AAAA,MACb;AAAA,IACF;AACA,SAAK,MAAM;AAAA,EACb;AACA,0BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,SAAO,SAAS,eAAe,UAAU,SAAS,IAAI;AACxD;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO,KAAK,MAAM,EAAE,CAAC;AAC1D,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY,6BAA6B,CAAC,QAAQ,WAAW,KAAK,MAAM,QAAQ,MAAM,CAAC;AAC3F,IAAI,SAAS,iBAAiB,OAAO,SAAS;AAC9C,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO,KAAK,MAAM,EAAE,CAAC;AAC1D,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,SAAS,QAAQ,OAAOc,UAAS,UAAU,UAAU;AAClE,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,eAAe,aAAa,QAAQ,OAAO,oBAAoB,OAAO;AAC5E,QAAM,SAAS,OAAO,SAAS,UAAU,KAAK;AAC9C,QAAM,aAAa,OAAO;AAC1B,QAAM,qBAAqB,SAAS,SAAS,KAAK,SAAS,SAAS,KAAK,SAAS,SAAS;AAC3F,QAAM,mBAAmB,SAAS,SAAS,KAAK,SAAS,SAAS;AAClE,QAAM,mBAAmB,SAAS,SAAS;AAC3C,WAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,UAAM,oBAAoB,IAAI;AAC9B,UAAM,mBAAmB,IAAIA,SAAQ;AACrC,aAAS,IAAI,GAAG,IAAI,SAAS,YAAY,EAAE,GAAG;AAC5C,eAAS,KAAK,GAAG,KAAK,SAAS,WAAW,EAAE,IAAI;AAC9C,cAAM,WAAW,KAAK,eAAe;AACrC,cAAM,QAAQ,KAAK,IAAI,GAAG,QAAQ;AAClC,cAAM,QAAQ,KAAK,IAAI,SAAS,UAAU,wBAAwB,QAAQ;AAC1E,cAAM,kBAAkB,oBAAoB,KAAK;AACjD,iBAAS,KAAK,GAAG,KAAK,SAAS,UAAU,EAAE,IAAI;AAC7C,gBAAM,WAAW,KAAK,cAAc;AACpC,gBAAM,QAAQ,KAAK,IAAI,GAAG,QAAQ;AAClC,gBAAM,QAAQ,KAAK,IAAI,SAAS,SAAS,uBAAuB,QAAQ;AACxE,cAAI,cAAc;AAClB,cAAI,WAAW;AACf,cAAIL,UAAS;AACb,mBAAS,KAAK,OAAO,KAAK,OAAO,MAAM,gBAAgB;AACrD,kBAAM,WAAW,mBAAmB,KAAKK,SAAQ;AACjD,qBAAS,KAAK,OAAO,KAAK,OAAO,MAAM,eAAe;AACpD,oBAAM,WAAW,WAAW,KAAKA,SAAQ;AACzC,oBAAM,QAAQ,QAAQ,WAAW;AACjC,kBAAI,aAAa,SAAS,QAAQ,aAAa;AAC7C,8BAAc;AAAA,cAChB,WAAW,aAAa,OAAO;AAC7B,4BAAY;AACZ,gBAAAL;AAAA,cACF;AAAA,YACF;AACA,gBAAI,MAAM,WAAW,GAAG;AACtB;AAAA,YACF;AAAA,UACF;AACA,gBAAM,eAAe,kBAAkB,KAAK,mBAAmB;AAC/D,qBAAW,gBAAgB,aAAa,QAAQ,WAAWA,UAAS;AAAA,QACtE;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,SAAS,QAAQ,OAAO,UAAU,mBAAmB,OAAO,sBAAsB,OAAO;AACjH,QAAM,eAAe,OAAO,SAAS,UAAU,OAAO;AACtD,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,OAAO,OAAO,QAAQ,OAAO,OAAO;AAC1C,WAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,aAAS,IAAI,GAAG,IAAI,SAAS,YAAY,EAAE,GAAG;AAC5C,eAAS,KAAK,GAAG,KAAK,SAAS,WAAW,EAAE,IAAI;AAC9C,cAAM,WAAW,KAAK,eAAe;AACrC,YAAI,QAAQ;AACZ,eAAO,QAAQ,GAAG;AAChB,mBAAS;AAAA,QACX;AACA,cAAM,QAAQ,KAAK,IAAI,SAAS,UAAU,wBAAwB,QAAQ;AAC1E,iBAAS,KAAK,GAAG,KAAK,SAAS,UAAU,EAAE,IAAI;AAC7C,gBAAM,WAAW,KAAK,cAAc;AACpC,cAAI,QAAQ;AACZ,iBAAO,QAAQ,GAAG;AAChB,qBAAS;AAAA,UACX;AACA,gBAAM,QAAQ,KAAK,IAAI,SAAS,SAAS,uBAAuB,QAAQ;AACxE,cAAI,WAAW,OAAO;AACtB,cAAI,cAAc;AAClB,mBAAS,KAAK,OAAO,KAAK,OAAO,MAAM,gBAAgB;AACrD,kBAAM,KAAK,KAAK;AAChB,qBAAS,KAAK,OAAO,KAAK,OAAO,MAAM,eAAe;AACpD,oBAAM,KAAK,KAAK;AAChB,oBAAM,QAAQ,KAAK,IAAI,GAAG,IAAI,IAAI,CAAC;AACnC,kBAAI,QAAQ,UAAU;AACpB,2BAAW;AACX,oBAAI,kBAAkB;AACpB,gCAAc,wBAAwB,IAAI,SAAS,WAAW,MAAM,SAAS,UAAU,MAAM,SAAS,aAAa,KAAK,KAAK,SAAS,UAAU,MAAM,SAAS,aAAa;AAAA,gBAC9K,OAAO;AACL,gCAAc,KAAK,uBAAuB;AAAA,gBAC5C;AAAA,cACF;AAAA,YACF;AAAA,UACF;AACA,uBAAa,IAAI,aAAa,GAAG,IAAI,IAAI,CAAC;AAAA,QAC5C;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,QAAQ,SAAS,QAAQ,OAAOK,UAAS,UAAU,UAAU;AACpE,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,uBAAuB,SAAS;AACtC,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,eAAe,aAAa,QAAQ,OAAO,oBAAoB,OAAO;AAC5E,QAAM,SAAS,OAAO,SAAS,UAAU,KAAK;AAC9C,QAAM,aAAa,OAAO;AAC1B,QAAM,qBAAqB,SAAS,SAAS,KAAK,SAAS,SAAS,KAAK,SAAS,SAAS,KAAK,SAAS,SAAS;AAClH,QAAM,qBAAqB,SAAS,SAAS,KAAK,SAAS,SAAS,KAAK,SAAS,SAAS;AAC3F,QAAM,mBAAmB,SAAS,SAAS,KAAK,SAAS,SAAS;AAClE,QAAM,mBAAmB,SAAS,SAAS;AAC3C,WAAS,QAAQ,GAAG,QAAQ,SAAS,WAAW,EAAE,OAAO;AACvD,UAAM,oBAAoB,QAAQ;AAClC,UAAM,mBAAmB,QAAQA,SAAQ;AACzC,aAAS,UAAU,GAAG,UAAU,SAAS,YAAY,EAAE,SAAS;AAC9D,eAAS,SAAS,GAAG,SAAS,SAAS,UAAU,EAAE,QAAQ;AACzD,cAAM,eAAe,SAAS,cAAc;AAC5C,YAAI,YAAY;AAChB,eAAO,YAAY,GAAG;AACpB,uBAAa;AAAA,QACf;AACA,cAAM,YAAY,KAAK,IAAI,SAAS,SAAS,uBAAuB,YAAY;AAChF,cAAM,oBAAoB,oBAAoB,SAAS;AACvD,iBAAS,OAAO,GAAG,OAAO,SAAS,WAAW,EAAE,MAAM;AACpD,gBAAM,aAAa,OAAO,eAAe;AACzC,cAAI,UAAU;AACd,iBAAO,UAAU,GAAG;AAClB,uBAAW;AAAA,UACb;AACA,gBAAM,UAAU,KAAK,IAAI,SAAS,UAAU,wBAAwB,UAAU;AAC9E,gBAAM,kBAAkB,oBAAoB,OAAO;AACnD,mBAAS,OAAO,GAAG,OAAO,SAAS,UAAU,EAAE,MAAM;AACnD,kBAAM,aAAa,OAAO,cAAc;AACxC,gBAAI,UAAU;AACd,mBAAO,UAAU,GAAG;AAClB,yBAAW;AAAA,YACb;AACA,kBAAM,UAAU,KAAK,IAAI,SAAS,SAAS,uBAAuB,UAAU;AAC5E,kBAAM,kBAAkB,kBAAkB,OAAO;AACjD,gBAAI,cAAc;AAClB,gBAAI,WAAW;AACf,gBAAIL,UAAS;AACb,qBAAS,SAAS,WAAW,SAAS,WAAW,UAAU,eAAe;AACxE,oBAAM,eAAe,mBAAmB,SAASK,SAAQ;AACzD,uBAAS,OAAO,SAAS,OAAO,SAAS,QAAQ,gBAAgB;AAC/D,sBAAM,aAAa,eAAe,OAAOA,SAAQ;AACjD,yBAAS,OAAO,SAAS,OAAO,SAAS,QAAQ,eAAe;AAC9D,wBAAM,aAAa,aAAa,OAAOA,SAAQ;AAC/C,wBAAM,QAAQ,QAAQ,aAAa;AACnC,sBAAI,aAAa,SAAS,QAAQ,aAAa;AAC7C,kCAAc;AAAA,kBAChB,WAAW,aAAa,OAAO;AAC7B,gCAAY;AACZ,oBAAAL;AAAA,kBACF;AACA,sBAAI,MAAM,WAAW,GAAG;AACtB;AAAA,kBACF;AAAA,gBACF;AACA,oBAAI,MAAM,WAAW,GAAG;AACtB;AAAA,gBACF;AAAA,cACF;AACA,kBAAI,MAAM,WAAW,GAAG;AACtB;AAAA,cACF;AAAA,YACF;AACA,kBAAM,eAAe,kBAAkB;AACvC,uBAAW,gBAAgB,aAAa,QAAQ,WAAWA,UAAS;AAAA,UACtE;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,mBAAmB,MAAM,UAAU;AAC1C,QAAM,eAAe,OAAO,SAAS,UAAU,OAAO;AACtD,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,uBAAuB,SAAS;AACtC,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,UAAU,SAAS,QAAQ;AACjC,WAAS,QAAQ,GAAG,QAAQ,SAAS,WAAW,EAAE,OAAO;AACvD,aAAS,UAAU,GAAG,UAAU,SAAS,YAAY,EAAE,SAAS;AAC9D,eAAS,SAAS,GAAG,SAAS,SAAS,UAAU,EAAE,QAAQ;AACzD,cAAM,eAAe,SAAS,cAAc;AAC5C,YAAI,YAAY;AAChB,eAAO,YAAY,GAAG;AACpB,uBAAa;AAAA,QACf;AACA,cAAM,YAAY,KAAK,IAAI,SAAS,SAAS,uBAAuB,YAAY;AAChF,iBAAS,OAAO,GAAG,OAAO,SAAS,WAAW,EAAE,MAAM;AACpD,gBAAM,aAAa,OAAO,eAAe;AACzC,cAAI,UAAU;AACd,iBAAO,UAAU,GAAG;AAClB,uBAAW;AAAA,UACb;AACA,gBAAM,UAAU,KAAK,IAAI,SAAS,UAAU,wBAAwB,UAAU;AAC9E,mBAAS,OAAO,GAAG,OAAO,SAAS,UAAU,EAAE,MAAM;AACnD,kBAAM,aAAa,OAAO,cAAc;AACxC,gBAAI,UAAU;AACd,mBAAO,UAAU,GAAG;AAClB,yBAAW;AAAA,YACb;AACA,kBAAM,UAAU,KAAK,IAAI,SAAS,SAAS,uBAAuB,UAAU;AAC5E,gBAAI,WAAW,OAAO;AACtB,gBAAI,cAAc;AAClB,qBAAS,SAAS,WAAW,SAAS,WAAW,UAAU,eAAe;AACxE,oBAAM,SAAS,SAAS;AACxB,uBAAS,OAAO,SAAS,OAAO,SAAS,QAAQ,gBAAgB;AAC/D,sBAAM,OAAO,OAAO;AACpB,yBAAS,OAAO,SAAS,OAAO,SAAS,QAAQ,eAAe;AAC9D,wBAAM,OAAO,OAAO;AACpB,wBAAM,QAAQ,KAAK,IAAI,OAAO,QAAQ,MAAM,MAAM,OAAO;AACzD,sBAAI,SAAS,UAAU;AACrB,+BAAW;AACX,kCAAc,SAAS,wBAAwB,uBAAuB,OAAO,wBAAwB;AAAA,kBACvG;AAAA,gBACF;AAAA,cACF;AAAA,YACF;AACA,yBAAa,IAAI,aAAa,OAAO,QAAQ,MAAM,MAAM,OAAO;AAAA,UAClE;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,mBAAiB,GAAG,SAAS;AAC7B,QAAM,EAAE,YAAY,SAAAK,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY;AAClB,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,SAAS,GAAG,MAAM,wEAAwEA,2BAA0B,YAAY;AACjN,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,MAAI;AACJ,MAAI,SAAS,gBAAgB,KAAK,SAAS,iBAAiB,KAAK,aAAa,YAAY,SAAS,SAAS,SAAS,QAAQ,GAAG;AAC9H,UAAM,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACtD,OAAO;AACL,UAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,UAAMwB,YAAW,aAAa,eAAe,EAAE,KAAK;AACpD,UAAM,UAAU,MAAM,SAAS,EAAE,OAAO,EAAE,OAAOA,WAAU,UAAU,KAAK;AAC1E,UAAM,SAAS,eAAe,SAAS,UAAU,EAAE,OAAO,QAAQ,MAAM;AAAA,EAC1E;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAAxB,UAAS,KAAK,MAAM,iBAAiB,WAAW,IAAI;AACxE,mBAAiB,GAAG,WAAW;AAC/B,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,MAAM,iBAAiB,UAAU;AAC1H,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAM,SAAS,QAAQ,SAAS,EAAE,OAAO,EAAE,OAAO,aAAa,eAAe,EAAE,KAAK,GAAG,UAAU,KAAK;AACvG,SAAO,SAAS,eAAe,OAAO,OAAO,WAAW,OAAO,MAAM;AACvE;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,OAAO,IAAI;AAC9B,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,mBAAiB,CAAC,IAAI,MAAM,GAAG,eAAe;AAC9C,QAAM,WAAW,qBAAqB,kBAAkB,OAAO,OAAO,YAAYA,UAAS,GAAG,MAAM,eAAe;AACnH,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,uBAAuB,SAAS;AACtC,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,WAAW,uBAAuB,IAAI,SAAS,QAAQ;AAC7D,QAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,QAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,QAAM,KAAK,OAAO,OAAO,OAAO,SAAS;AACzC,QAAM,gBAAgB,KAAK,cAAc,eAAe;AACxD,QAAM,QAAQ,SAAS,WAAW,EAAE;AACpC,WAAS,QAAQ,GAAG,QAAQ,SAAS,WAAW,EAAE,OAAO;AACvD,aAAS,UAAU,GAAG,UAAU,SAAS,YAAY,EAAE,SAAS;AAC9D,eAAS,UAAU,GAAG,UAAU,SAAS,SAAS,EAAE,SAAS;AAC3D,iBAAS,QAAQ,GAAG,QAAQ,SAAS,UAAU,EAAE,OAAO;AACtD,mBAAS,QAAQ,GAAG,QAAQ,SAAS,SAAS,EAAE,OAAO;AACrD,kBAAM,gBAAgB,UAAU;AAChC,kBAAM,cAAc,QAAQ;AAC5B,kBAAM,cAAc,QAAQ;AAC5B,gBAAI,UAAU;AACd,qBAAS,SAAS,GAAG,SAAS,sBAAsB,UAAU,eAAe;AAC3E,oBAAM,WAAW,gBAAgB,UAAU;AAC3C,kBAAI,UAAU,KAAK,WAAW,SAAS,YAAY,KAAK,MAAM,OAAO,MAAM,SAAS;AAClF;AAAA,cACF;AACA,uBAAS,OAAO,GAAG,OAAO,uBAAuB,QAAQ,gBAAgB;AACvE,sBAAM,SAAS,cAAc,QAAQ;AACrC,oBAAI,QAAQ,KAAK,SAAS,SAAS,aAAa,KAAK,MAAM,KAAK,MAAM,OAAO;AAC3E;AAAA,gBACF;AACA,yBAAS,OAAO,GAAG,OAAO,sBAAsB,QAAQ,eAAe;AACrE,wBAAM,SAAS,cAAc,QAAQ;AACrC,sBAAI,QAAQ,KAAK,SAAS,SAAS,YAAY,KAAK,MAAM,KAAK,MAAM,OAAO;AAC1E;AAAA,kBACF;AACA,wBAAM,QAAQ,MAAM,IAAI,OAAO,SAAS,OAAO,OAAO,OAAO;AAC7D,6BAAW;AAAA,gBACb;AAAA,cACF;AAAA,YACF;AACA,eAAG,IAAI,UAAU,eAAe,OAAO,SAAS,OAAO,OAAO,OAAO;AAAA,UACvE;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,OAAO,IAAI;AAC9B,QAAM,IAAI;AACV,mBAAiB,CAAC,IAAI,MAAM,GAAG,aAAa;AAC5C,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,KAAK,IAAI;AAC3C,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,IAAI;AAC7F,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,QAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,QAAM,KAAK,OAAO,EAAE,OAAO,SAAS;AACpC,QAAM,gBAAgB,KAAK,eAAe;AAC1C,QAAM,SAAS,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC5C,QAAM,QAAQ,OAAO,GAAG,OAAO,WAAW,MAAM;AAChD,WAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,aAAS,IAAI,GAAG,IAAI,SAAS,YAAY,EAAE,GAAG;AAC5C,eAAS,MAAM,GAAG,MAAM,SAAS,UAAU,EAAE,KAAK;AAChD,iBAAS,MAAM,GAAG,MAAM,SAAS,SAAS,EAAE,KAAK;AAC/C,gBAAM,YAAY,MAAM;AACxB,gBAAM,YAAY,MAAM;AACxB,cAAI,UAAU;AACd,mBAAS,KAAK,GAAG,KAAK,uBAAuB,MAAM,gBAAgB;AACjE,kBAAM,OAAO,YAAY,MAAM;AAC/B,gBAAI,MAAM,KAAK,OAAO,SAAS,aAAa,KAAK,MAAM,GAAG,MAAM,KAAK;AACnE;AAAA,YACF;AACA,qBAAS,KAAK,GAAG,KAAK,sBAAsB,MAAM,eAAe;AAC/D,oBAAM,OAAO,YAAY,MAAM;AAC/B,kBAAI,MAAM,KAAK,OAAO,SAAS,YAAY,KAAK,MAAM,GAAG,MAAM,KAAK;AAClE;AAAA,cACF;AACA,oBAAM,QAAQ,MAAM,IAAI,GAAG,KAAK,KAAK,CAAC;AACtC,yBAAW;AAAA,YACb;AAAA,UACF;AACA,aAAG,IAAI,UAAU,eAAe,GAAG,KAAK,KAAK,CAAC;AAAA,QAChD;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAOS,SAAQ,QAAQ,MAAM,OAAO,SAAS,IAAI;AAC5D,eAAa,OAAO,MAAM,MAAM,WAAW,SAAS,MAAM,QAAQ,MAAM,8EAA8E;AACtJ,eAAa,OAAO,UAAU,QAAQ,MAAM,MAAM,WAAW,OAAO,MAAM,QAAQ,MAAM,4EAA4E;AACpK,eAAa,OAAOA,WAAU,QAAQ,MAAM,MAAM,WAAWA,QAAO,MAAM,QAAQ,MAAM,2EAA2E;AACnK,mBAAiB,CAAC,GAAG,OAAO,UAAUA,SAAQ,MAAM,GAAG,WAAW;AAClE,MAAI,EAAE,gBAAgB,IAAI;AAC1B,MAAI,mBAAmB,MAAM;AAC3B,sBAAkB;AAAA,EACpB;AACA,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,QAAQ,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AAC9C,QAAM,UAAU,SAAS,KAAK,IAAI,SAAS,MAAM,EAAE;AACnD,QAAM,QAAQA,UAAS,SAAS,KAAK,IAAIA,QAAO,MAAM,EAAE,SAAS,IAAI,aAAa,CAAC,CAAC,CAAC;AACrF,QAAM,UAAU,SAAS,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE,SAAS,IAAI,aAAa,CAAC,CAAC,CAAC;AACvF,QAAM,UAAU,IAAI,aAAa,MAAM,MAAM;AAC7C,QAAM,gBAAgB,QAAQ;AAC9B,QAAM,cAAc,MAAM;AAC1B,QAAM,gBAAgB,QAAQ;AAC9B,QAAM,cAAc,MAAM;AAC1B,MAAI,OAAO;AACX,MAAI,KAAK;AACT,MAAI,KAAK;AACT,MAAI,KAAK;AACT,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,YAAQ,MAAM,QAAQ,WAAW,MAAM,MAAM,MAAM,SAAS,MAAM,QAAQ,KAAK,KAAK,QAAQ,QAAQ,eAAe;AACnH,QAAI,QAAQ,eAAe;AACzB,aAAO;AAAA,IACT;AACA,QAAI,MAAM,aAAa;AACrB,WAAK;AAAA,IACP;AACA,QAAI,MAAM,aAAa;AACrB,WAAK;AAAA,IACP;AACA,QAAI,MAAM,eAAe;AACvB,WAAK;AAAA,IACP;AAAA,EACF;AACA,SAAO,SAAS,eAAe,EAAE,OAAO,EAAE,OAAO,OAAO;AAC1D;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,MAAM,IAAI;AAC9B,mBAAiB,CAAC,CAAC,GAAG,gBAAgB;AACtC,QAAM,QAAQ,WAAW,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAC/C,QAAM,WAAW,qBAAqB,YAAY,EAAE,OAAO,YAAY,KAAK;AAC5E,QAAM,WAAW,qBAAqB,YAAY,SAAS,QAAQ,WAAW,MAAM;AACpF,QAAM,mBAAmB,qBAAqB,oBAAoB,EAAE,OAAO,YAAY,KAAK;AAC5F,QAAM,mBAAmB,qBAAqB,oBAAoB,OAAO,WAAW,MAAM;AAC1F,QAAM,YAAY,qBAAqB,aAAa,kBAAkB,OAAO,WAAW,MAAM;AAC9F,QAAM,YAAY,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC3F,QAAM,cAAc,WAAW,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,SAAS,EAAE,CAAC;AACzG,QAAM,sBAAsB,SAAS,EAAE,QAAQ,EAAE,GAAG,YAAY,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,iBAAiB,EAAE,CAAC;AAC1H,QAAM,SAAS,OAAO;AAAA,IACpB,QAAQ,EAAE,GAAG,oBAAoB;AAAA,IACjC,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,kBAAkB,MAAM,UAAU;AAAA,EACpD,CAAC;AACD,WAAS,8BAA8B,SAAS;AAChD,WAAS,8BAA8B,WAAW;AAClD,WAAS,8BAA8B,mBAAmB;AAC1D,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAArB,MAAK,IAAI;AACjB,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,cAAc,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACtD,QAAM,UAAU,aAAa,OAAO,aAAa,QAAQ,OAAO,QAAQ,OAAOA,KAAI;AACnF,SAAO,SAAS,eAAe,CAACA,KAAI,GAAG,QAAQ,OAAO,OAAO;AAC/D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,IAAI,GAAG,IAAI;AACnB,QAAM,SAAS,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC5C,QAAM,SAAS,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC5C,QAAM,iBAAiB,qBAAqB,2BAA2B,MAAM,KAAK,MAAM,GAAG,MAAM,KAAK,MAAM,CAAC;AAC7G,SAAO,SAAS,eAAe,CAAC,eAAe,MAAM,GAAG,SAAS,WAAW,KAAK,cAAc,CAAC;AAClG;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe,gBAAgB,aAAa,CAAC,IAAI,UAAU;AAC7D,QAAM,YAAY;AAClB,MAAI,KAAK,UAAU,cAAc;AAC/B,WAAO,UAAU;AAAA,EACnB;AACA,SAAO,KAAK,UAAU,eAAe,UAAU,eAAe;AAChE,CAAC;AACD,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa,CAAC,SAAS;AACzB,QAAM,EAAE,EAAE,IAAI,KAAK;AACnB,QAAM,aAAa,KAAK;AACxB,QAAM,eAAe,IAAI,aAAa,aAAa,cAAc,EAAE,KAAK,CAAC;AACzE,QAAM,cAAc,WAAW,KAAK,IAAI,EAAE,MAAM;AAChD,QAAM,QAAQ,YAAY,mBAAmB;AAC7C,QAAM,QAAQ,YAAY,mBAAmB;AAC7C,QAAM,WAAW,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACnD,QAAM,WAAW,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACnD,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,UAAM,QAAQ,SAAS;AACvB,UAAM,QAAQ,SAAS;AACvB,iBAAa,MAAM,KAAK,MAAM,OAAO,KAAK;AAAA,EAC5C;AACA,SAAO,WAAW,WAAW,cAAc,EAAE,OAAO,SAAS;AAC/D;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,QAAQ,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE,mBAAmB;AAClE,QAAM,UAAU,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AAChD,SAAO,SAAS,eAAe,MAAM,OAAO,MAAM,OAAO,OAAO;AAClE;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,QAAQ,aAAa,eAAe,MAAM,OAAO,GAAG,KAAK,EAAE;AACjE,MAAI,WAAW,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,KAAK;AACvF,MAAI,aAAa,cAAc,QAAQ,MAAM,GAAG;AAC9C,WAAO,SAAS,eAAe,UAAU,OAAO,GAAG,OAAO,CAAC,CAAC;AAAA,EAC9D;AACA,QAAM,UAAU,OAAO,OAAO,CAAC,OAAO,aAAa,cAAc,GAAG,KAAK,IAAI,CAAC;AAC9E,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,GAAG,SAAS,SAAS,CAAC;AAAA,EACnE;AACA,QAAM,SAAS,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK;AAC3C,uBAAqB,uBAAuB,QAAQ,KAAK;AACzD,MAAI,QAAQ,GAAG,UAAU,aAAa;AACpC,UAAM,QAAQ,QAAQ,IAAI,CAAC,OAAO,MAAM,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,SAAS,CAAC,CAAC;AACrF,UAAM,QAAQ,QAAQ,IAAI,CAAC,OAAO,MAAM,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,SAAS,CAAC,CAAC;AACrF,UAAM,eAAe,QAAQ,EAAE,QAAQ,OAAO,SAAS,UAAU,OAAO,EAAE,MAAM,MAAM,EAAE,CAAC;AACzF,UAAM,eAAe,QAAQ,EAAE,QAAQ,OAAO,SAAS,UAAU,OAAO,EAAE,MAAM,MAAM,EAAE,CAAC;AACzF,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,cAAc,MAAM,aAAa,GAAG,SAAS,SAAS,CAAC;AACjG,UAAM,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAChE,UAAM,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAChE,aAAS,8BAA8B,YAAY;AACnD,aAAS,8BAA8B,YAAY;AACnD,WAAO;AAAA,EACT;AACA,QAAM,WAAW,QAAQ,IAAI,CAAC,OAAO;AACnC,UAAM,YAAY,aAAa,cAAc,GAAG,MAAM,MAAM,KAAK,CAAC;AAClE,UAAM,QAAQ,CAAC,IAAI,SAAS;AAC5B,WAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AAAA,EAC5E,CAAC;AACD,QAAM,kBAAkB,SAAS,IAAI,CAAC,OAAO;AAC3C,WAAO,EAAE,MAAM,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE,QAAQ,OAAO,GAAG,MAAM;AAAA,EACtE,CAAC;AACD,aAAW,qBAAqB,gBAAgB,SAAS,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,CAAC;AACjF,QAAM,eAAe,SAAS,GAAG,MAAM,OAAO;AAC9C,QAAM,UAAU,WAAW,iBAAiB,UAAU,OAAO,GAAG,OAAO,YAAY;AACnF,QAAM,gBAAgB,qBAAqB,gBAAgB,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,KAAK;AAC/F,QAAM,UAAU,SAAS,eAAe,eAAe,OAAO,GAAG,OAAO,OAAO;AAC/E,WAAS,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACnE,SAAO;AACT;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAY,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB,IAAI;AACvE,mBAAiB,CAAC,GAAG,MAAM,GAAG,QAAQ;AACtC,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,OAAO,WAAW;AAC5I,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,iBAAiB,SAAS,eAAe;AAC/C,QAAM,IAAI,IAAI,aAAa,SAAS,UAAU,EAAE,KAAK;AACrD,QAAM,WAAW,aAAa,eAAe,EAAE,KAAK;AACpD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,eAAe,SAAS;AAC9B,QAAM,aAAa,iBAAiB,SAAS,KAAK,SAAS;AAC3D,QAAM,aAAa,iBAAiB,SAAS,KAAK;AAClD,QAAM,iBAAiB,iBAAiB,IAAI,SAAS;AACrD,QAAM,eAAe,EAAE,QAAQ;AAC/B,QAAM,aAAa,iBAAiB,EAAE,QAAQ,KAAK,EAAE,QAAQ;AAC7D,QAAM,aAAa,iBAAiB,EAAE,QAAQ,KAAK;AACnD,QAAM,iBAAiB,iBAAiB,IAAI,EAAE,QAAQ;AACtD,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,QAAQ,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AAC/C,QAAM,QAAQ,EAAE;AAChB,WAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,UAAM,WAAW,IAAI;AACrB,UAAM,WAAW,IAAI;AACrB,aAAS,KAAK,GAAG,KAAK,SAAS,WAAW,EAAE,IAAI;AAC9C,YAAM,WAAW,WAAW,KAAK;AACjC,YAAM,WAAW,KAAK,SAAS,eAAe;AAC9C,eAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,cAAM,KAAK,WAAW,KAAK;AAC3B,YAAI,KAAK,KAAK,MAAM,SAAS,UAAU;AACrC;AAAA,QACF;AACA,cAAM,WAAW,KAAK,cAAc;AACpC,cAAM,WAAW,WAAW,KAAK;AACjC,iBAAS,KAAK,GAAG,KAAK,SAAS,UAAU,EAAE,IAAI;AAC7C,gBAAM,WAAW,WAAW,KAAK;AACjC,gBAAM,WAAW,KAAK,SAAS,cAAc;AAC7C,mBAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,kBAAM,KAAK,WAAW,KAAK;AAC3B,gBAAI,KAAK,KAAK,MAAM,SAAS,SAAS;AACpC;AAAA,YACF;AACA,kBAAM,WAAW,WAAW,KAAK,cAAc;AAC/C,kBAAM,WAAW,WAAW,KAAK;AACjC,gBAAI,WAAW;AACf,qBAAS,KAAK,GAAG,KAAK,SAAS,YAAY,EAAE,IAAI;AAC/C,oBAAM,OAAO,MAAM,WAAW,KAAK;AACnC,uBAAS,KAAK,GAAG,KAAK,SAAS,aAAa,EAAE,IAAI;AAChD,sBAAM,WAAW,KAAK,mBAAmB,OAAO,MAAM,WAAW;AAAA,cACnE;AACA,0BAAY,SAAS;AAAA,YACvB;AAAA,UACF;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,EAAE,OAAO,EAAE,OAAO,KAAK;AACxD;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,sBAAsB,MAAM;AACnC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,IAAI;AAClB,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,iBAAiB,YAAY,IAAI;AACzE,mBAAiB,CAAC,GAAG,EAAE,GAAG,sBAAsB;AAChD,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,aAAaA,UAAS,GAAG,MAAM,iBAAiB,OAAO,WAAW;AACnI,QAAM,EAAE,cAAc,aAAa,cAAc,YAAY,IAAI;AACjE,QAAM,iBAAiB,SAAS,eAAe;AAC/C,QAAM,KAAK,IAAI,aAAa,SAAS,aAAa,SAAS;AAC3D,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,SAAS,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC5C,QAAM,OAAO,IAAI,aAAa,EAAE,OAAO,EAAE,OAAO,KAAK;AACrD,QAAM,QAAQ,IAAI,aAAa,GAAG,OAAO,GAAG,OAAO,MAAM;AACzD,WAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,UAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,MAAM,SAAS,MAAM,YAAY,CAAC;AACjE,UAAM,QAAQ,KAAK,IAAI,SAAS,YAAY,SAAS,WAAW,SAAS,MAAM,YAAY;AAC3F,aAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,YAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,MAAM,UAAU,MAAM,WAAW,CAAC;AACjE,YAAM,QAAQ,KAAK,IAAI,SAAS,WAAW,SAAS,UAAU,UAAU,MAAM,WAAW;AACzF,eAAS,KAAK,GAAG,KAAK,SAAS,YAAY,EAAE,IAAI;AAC/C,iBAAS,KAAK,GAAG,KAAK,SAAS,aAAa,EAAE,IAAI;AAChD,cAAI,UAAU;AACd,mBAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,qBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,oBAAM,KAAK,KAAK,KAAK,eAAe;AACpC,uBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,sBAAM,KAAK,KAAK,KAAK,cAAc;AACnC,oBAAI,gBAAgB;AAClB,6BAAW,KAAK,IAAI,GAAG,IAAI,IAAI,EAAE,IAAI,MAAM,IAAI,GAAG,IAAI,IAAI,EAAE;AAAA,gBAC9D,OAAO;AACL,6BAAW,KAAK,IAAI,GAAG,IAAI,IAAI,EAAE,IAAI,MAAM,IAAI,GAAG,IAAI,IAAI,EAAE;AAAA,gBAC9D;AAAA,cACF;AAAA,YACF;AAAA,UACF;AACA,aAAG,IAAI,SAAS,IAAI,IAAI,IAAI,EAAE;AAAA,QAChC;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,YAAY,gBAAgB,IAAI;AACxE,mBAAiB,CAAC,IAAI,MAAM,GAAG,qBAAqB;AACpD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,YAAY,aAAa,eAAe,GAAG,KAAK;AACtD,MAAI,cAAc,qBAAqB,wBAAwB,UAAU;AACzE,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,GAAG,MAAM,iBAAiB,OAAO,WAAW;AACvI,QAAM,KAAK,IAAI,aAAa,SAAS,SAAS,SAAS;AACvD,QAAM,WAAW,GAAG;AACpB,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,YAAY,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACnD,QAAM,CAAC,OAAO,OAAO,KAAK,IAAI;AAC9B,QAAM,EAAE,WAAW,cAAc,aAAa,YAAY,UAAU,SAAS,aAAa,WAAW,UAAU,cAAc,YAAY,IAAI;AAC7I,gBAAc,SAAS;AACvB,QAAM,SAAS,eAAe,IAAI,SAAS,QAAQ;AACnD,QAAM,UAAU,cAAc,IAAI,SAAS,QAAQ;AACnD,QAAM,iBAAiB,gBAAgB;AACvC,QAAM,eAAe,GAAG,QAAQ;AAChC,QAAM,aAAa,iBAAiB,GAAG,QAAQ,KAAK,GAAG,QAAQ;AAC/D,QAAM,aAAa,iBAAiB,GAAG,QAAQ,KAAK;AACpD,QAAM,iBAAiB,iBAAiB,IAAI,GAAG,QAAQ;AACvD,QAAM,eAAe,UAAU;AAC/B,QAAM,aAAa,iBAAiB,UAAU,KAAK,UAAU;AAC7D,QAAM,aAAa,iBAAiB,UAAU,KAAK;AACnD,QAAM,iBAAiB,iBAAiB,IAAI,UAAU;AACtD,WAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,aAAS,KAAK,GAAG,KAAK,YAAY,EAAE,IAAI;AACtC,eAAS,KAAK,GAAG,KAAK,UAAU,EAAE,IAAI;AACpC,cAAM,WAAW,KAAK;AACtB,cAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,KAAK,WAAW,YAAY,CAAC;AAC5D,cAAM,QAAQ,KAAK,IAAI,YAAY,eAAe,YAAY,YAAY;AAC1E,iBAAS,KAAK,GAAG,KAAK,SAAS,EAAE,IAAI;AACnC,gBAAM,WAAW,KAAK;AACtB,gBAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,KAAK,WAAW,WAAW,CAAC;AAC3D,gBAAM,QAAQ,KAAK,IAAI,WAAW,cAAc,YAAY,WAAW;AACvE,cAAI,UAAU;AACd,mBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,kBAAM,KAAK,KAAK,eAAe;AAC/B,qBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,oBAAM,KAAK,KAAK,cAAc;AAC9B,oBAAM,WAAW,eAAe,IAAI,aAAa,KAAK,aAAa;AACnE,oBAAM,YAAY,SAAS,eAAe,IAAI,MAAM,SAAS,cAAc,IAAI,MAAM,QAAQ;AAC7F,uBAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,sBAAM,QAAQ,SAAS,WAAW,iBAAiB;AACnD,sBAAM,SAAS,UAAU,YAAY;AACrC,2BAAW,QAAQ;AAAA,cACrB;AAAA,YACF;AAAA,UACF;AACA,gBAAM,WAAW,eAAe,IAAI,aAAa,KAAK,aAAa,KAAK,iBAAiB;AACzF,mBAAS,YAAY;AAAA,QACvB;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,UAAU,IAAI;AAC1C,mBAAiB,CAAC,GAAG,MAAM,GAAG,QAAQ;AACtC,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,IAAI;AACvG,QAAM,EAAE,aAAa,cAAc,aAAa,eAAe,gBAAgB,eAAe,QAAQ,IAAI;AAC1G,QAAM,WAAW,QAAQ;AACzB,QAAM,UAAU,QAAQ;AACxB,QAAM,SAAS,QAAQ;AACvB,QAAM,IAAI,IAAI,aAAa,SAAS,UAAU,EAAE,KAAK;AACrD,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,QAAQ,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AAC/C,QAAM,QAAQ,EAAE;AAChB,QAAM,WAAW,aAAa,eAAe,EAAE,KAAK;AACpD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,WAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,UAAM,WAAW,IAAI,SAAS;AAC9B,UAAM,WAAW,IAAI,EAAE,QAAQ;AAC/B,aAAS,KAAK,GAAG,KAAK,SAAS,UAAU,EAAE,IAAI;AAC7C,YAAM,WAAW,WAAW,KAAK,EAAE,QAAQ;AAC3C,YAAM,WAAW,KAAK,SAAS,cAAc;AAC7C,eAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,cAAM,KAAK,WAAW,KAAK;AAC3B,YAAI,KAAK,KAAK,MAAM,SAAS,SAAS;AACpC;AAAA,QACF;AACA,cAAM,WAAW,KAAK,cAAc;AACpC,cAAM,WAAW,WAAW,KAAK,SAAS;AAC1C,iBAAS,KAAK,GAAG,KAAK,SAAS,WAAW,EAAE,IAAI;AAC9C,gBAAM,WAAW,WAAW,KAAK,EAAE,QAAQ;AAC3C,gBAAM,WAAW,KAAK,SAAS,eAAe;AAC9C,mBAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,kBAAM,KAAK,WAAW,KAAK;AAC3B,gBAAI,KAAK,KAAK,MAAM,SAAS,UAAU;AACrC;AAAA,YACF;AACA,kBAAM,WAAW,WAAW,KAAK,cAAc;AAC/C,kBAAM,WAAW,WAAW,KAAK,SAAS;AAC1C,qBAAS,KAAK,GAAG,KAAK,SAAS,UAAU,EAAE,IAAI;AAC7C,oBAAM,WAAW,WAAW,KAAK,SAAS;AAC1C,oBAAM,WAAW,KAAK,SAAS,cAAc;AAC7C,uBAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,sBAAM,KAAK,WAAW,KAAK;AAC3B,oBAAI,KAAK,KAAK,MAAM,SAAS,SAAS;AACpC;AAAA,gBACF;AACA,sBAAM,WAAW,WAAW,KAAK,cAAc;AAC/C,sBAAM,WAAW,WAAW,KAAK,SAAS;AAC1C,oBAAI,WAAW;AACf,yBAAS,KAAK,GAAG,KAAK,SAAS,YAAY,EAAE,IAAI;AAC/C,wBAAM,OAAO,MAAM,WAAW;AAC9B,2BAAS,KAAK,GAAG,KAAK,SAAS,aAAa,EAAE,IAAI;AAChD,0BAAM,WAAW,OAAO,OAAO,MAAM,WAAW;AAAA,kBAClD;AACA,8BAAY,SAAS;AAAA,gBACvB;AAAA,cACF;AAAA,YACF;AAAA,UACF;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,EAAE,OAAO,EAAE,OAAO,EAAE,MAAM;AAC3D;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,uBAAuB,MAAM;AACpC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,IAAI;AAClB,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,IAAI;AAC5C,mBAAiB,CAAC,GAAG,EAAE,GAAG,wBAAwB;AAClD,QAAM,WAAW,aAAa,eAAe,EAAE,KAAK;AACpD,QAAM,YAAY,aAAa,eAAe,GAAG,KAAK;AACtD,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,aAAaA,UAAS,GAAG,IAAI;AAC9F,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,KAAK,IAAI,aAAa,SAAS,aAAa,SAAS;AAC3D,QAAM,WAAW,GAAG;AACpB,QAAM,CAAC,MAAM,MAAM,MAAM,IAAI,IAAI,GAAG;AACpC,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,CAAC,MAAM,MAAM,MAAM,IAAI,IAAI;AACjC,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAM,CAAC,KAAK,KAAK,KAAK,GAAG,IAAI;AAC7B,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,SAAS,SAAS,QAAQ;AAChC,WAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,UAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,MAAM,WAAW,MAAM,WAAW,CAAC;AAClE,UAAM,QAAQ,KAAK,IAAI,SAAS,WAAW,SAAS,UAAU,WAAW,MAAM,WAAW;AAC1F,UAAM,WAAW,KAAK;AACtB,aAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,YAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,MAAM,SAAS,MAAM,YAAY,CAAC;AACjE,YAAM,QAAQ,KAAK,IAAI,SAAS,YAAY,SAAS,WAAW,SAAS,MAAM,YAAY;AAC3F,YAAM,WAAW,KAAK,OAAO;AAC7B,eAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,cAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,MAAM,UAAU,MAAM,WAAW,CAAC;AACjE,cAAM,QAAQ,KAAK,IAAI,SAAS,WAAW,SAAS,UAAU,UAAU,MAAM,WAAW;AACzF,cAAM,WAAW,KAAK,OAAO;AAC7B,iBAAS,KAAK,GAAG,KAAK,SAAS,YAAY,EAAE,IAAI;AAC/C,gBAAM,WAAW,KAAK,OAAO;AAC7B,mBAAS,KAAK,GAAG,KAAK,SAAS,aAAa,EAAE,IAAI;AAChD,gBAAI,UAAU;AACd,qBAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,oBAAM,WAAW,IAAI;AACrB,oBAAM,WAAW,IAAI;AACrB,uBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,sBAAM,KAAK,KAAK,KAAK,cAAc;AACnC,sBAAM,WAAW,KAAK,MAAM;AAC5B,sBAAM,WAAW,KAAK,OAAO;AAC7B,yBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,wBAAM,KAAK,KAAK,KAAK,eAAe;AACpC,wBAAM,WAAW,KAAK,MAAM;AAC5B,wBAAM,WAAW,KAAK,OAAO;AAC7B,2BAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,0BAAM,KAAK,KAAK,KAAK,cAAc;AACnC,0BAAM,WAAW,KAAK,MAAM;AAC5B,0BAAM,WAAW,KAAK,OAAO;AAC7B,+BAAW,QAAQ,WAAW,MAAM,SAAS,WAAW;AAAA,kBAC1D;AAAA,gBACF;AAAA,cACF;AAAA,YACF;AACA,qBAAS,WAAW,MAAM;AAAA,UAC5B;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,sBAAsB,MAAM;AACnC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,KAAK,MAAM,SAAAA,UAAS,WAAW,IAAI;AAC3C,mBAAiB,CAAC,EAAE,GAAG,uBAAuB;AAC9C,QAAM,YAAY,aAAa,eAAe,GAAG,KAAK;AACtD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,GAAG,IAAI;AAClG,QAAM,KAAK,IAAI,aAAa,SAAS,SAAS,SAAS;AACvD,QAAM,WAAW,GAAG;AACpB,QAAM,CAAC,MAAM,MAAM,MAAM,IAAI,IAAI,GAAG;AACpC,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,CAAC,MAAM,MAAM,MAAM,IAAI,IAAI;AACjC,QAAM,YAAY,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACnD,QAAM,CAAC,OAAO,OAAO,OAAO,KAAK,IAAI;AACrC,QAAM,EAAE,WAAW,aAAa,cAAc,aAAa,YAAY,SAAS,UAAU,SAAS,aAAa,UAAU,WAAW,UAAU,aAAa,cAAc,YAAY,IAAI;AAC1L,QAAM,WAAW,cAAc,IAAI,SAAS,QAAQ;AACpD,QAAM,SAAS,eAAe,IAAI,SAAS,QAAQ;AACnD,QAAM,UAAU,cAAc,IAAI,SAAS,QAAQ;AACnD,WAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,aAAS,KAAK,GAAG,KAAK,YAAY,EAAE,IAAI;AACtC,eAAS,KAAK,GAAG,KAAK,SAAS,EAAE,IAAI;AACnC,cAAM,WAAW,KAAK;AACtB,cAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,KAAK,WAAW,WAAW,CAAC;AAC3D,cAAM,QAAQ,KAAK,IAAI,WAAW,cAAc,YAAY,WAAW;AACvE,iBAAS,KAAK,GAAG,KAAK,UAAU,EAAE,IAAI;AACpC,gBAAM,WAAW,KAAK;AACtB,gBAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,KAAK,WAAW,YAAY,CAAC;AAC5D,gBAAM,QAAQ,KAAK,IAAI,YAAY,eAAe,YAAY,YAAY;AAC1E,mBAAS,KAAK,GAAG,KAAK,SAAS,EAAE,IAAI;AACnC,kBAAM,WAAW,KAAK;AACtB,kBAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,KAAK,WAAW,WAAW,CAAC;AAC3D,kBAAM,QAAQ,KAAK,IAAI,WAAW,cAAc,YAAY,WAAW;AACvE,gBAAI,UAAU;AACd,qBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,oBAAM,KAAK,KAAK,cAAc;AAC9B,uBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,sBAAM,KAAK,KAAK,eAAe;AAC/B,yBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,wBAAM,KAAK,KAAK,cAAc;AAC9B,wBAAM,WAAW,OAAO,IAAI,OAAO,KAAK,OAAO,KAAK,OAAO;AAC3D,wBAAM,YAAY,SAAS,cAAc,IAAI,MAAM,SAAS,eAAe,IAAI,MAAM,SAAS,cAAc,IAAI,MAAM,QAAQ;AAC9H,2BAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,0BAAM,QAAQ,SAAS,WAAW;AAClC,0BAAM,SAAS,UAAU,YAAY;AACrC,+BAAW,QAAQ;AAAA,kBACrB;AAAA,gBACF;AAAA,cACF;AAAA,YACF;AACA,qBAAS,OAAO,IAAI,OAAO,KAAK,OAAO,KAAK,OAAO,KAAK,MAAM;AAAA,UAChE;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,gBAAgB,KAAK,CAAC,OAAO,KAAK,IAAI,EAAE,CAAC;AACpD,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,OAAO,OAAO,IAAI;AACzC,QAAM,EAAE,UAAU,QAAQ,mBAAmB,IAAI;AACjD,QAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,QAAM,WAAW,MAAM,MAAM;AAC7B,QAAM,CAAC,YAAY,SAAS,IAAI;AAChC,QAAM,SAAS,OAAO,CAAC,UAAU,YAAY,WAAW,WAAW,GAAG,SAAS;AAC/E,QAAM,UAAU,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AAChD,QAAM,aAAa,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACpD,QAAM,YAAY,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACnD,QAAM,WAAW,aAAa,eAAe,OAAO,KAAK;AACzD,QAAM,YAAY,aAAa,eAAe,OAAO,KAAK;AAC1D,WAAS,IAAI,GAAG,IAAI,UAAU,KAAK;AACjC,UAAM,WAAW,IAAI;AACrB,UAAM,KAAK,QAAQ;AACnB,UAAM,KAAK,QAAQ,WAAW;AAC9B,UAAM,KAAK,QAAQ,WAAW;AAC9B,UAAM,KAAK,QAAQ,WAAW;AAC9B,UAAM,OAAO,WAAW;AACxB,QAAI,QAAQ,OAAO;AACjB;AAAA,IACF;AACA,UAAM,cAAc,aAAa,KAAK,KAAK,OAAO,cAAc,MAAM,aAAa,KAAK;AACxF,UAAM,aAAa,YAAY,KAAK,KAAK,OAAO,aAAa,MAAM,YAAY,KAAK;AACpF,aAAS,IAAI,GAAG,IAAI,YAAY,KAAK;AACnC,YAAM,OAAO,aAAa,IAAI,MAAM,cAAc,KAAK,IAAI,cAAc,OAAO,KAAK,OAAO,cAAc;AAC1G,UAAI,OAAO,KAAK,OAAO,cAAc,GAAG;AACtC,iBAAS,IAAI,GAAG,IAAI,WAAW,KAAK;AAClC,mBAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,kBAAM,MAAM,IAAI,IAAI,UAAU,KAAK,IAAI,UAAU,KAAK,IAAI,UAAU;AACpE,mBAAO,OAAO,OAAO;AAAA,UACvB;AAAA,QACF;AACA;AAAA,MACF;AACA,UAAI,WAAW,YAAY;AACzB,cAAM,SAAS,KAAK,MAAM,IAAI;AAC9B,cAAM,YAAY,KAAK,KAAK,IAAI;AAChC,cAAM,QAAQ,OAAO;AACrB,iBAAS,IAAI,GAAG,IAAI,WAAW,KAAK;AAClC,gBAAM,OAAO,YAAY,IAAI,MAAM,aAAa,KAAK,IAAI,aAAa,OAAO,KAAK,OAAO,aAAa;AACtG,cAAI,OAAO,KAAK,OAAO,aAAa,GAAG;AACrC,qBAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,oBAAM,MAAM,IAAI,IAAI,UAAU,KAAK,IAAI,UAAU,KAAK,IAAI,UAAU;AACpE,qBAAO,OAAO,OAAO;AAAA,YACvB;AACA;AAAA,UACF;AACA,gBAAM,UAAU,KAAK,MAAM,IAAI;AAC/B,gBAAM,WAAW,KAAK,KAAK,IAAI;AAC/B,gBAAM,QAAQ,OAAO;AACrB,mBAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,gBAAI,MAAM,IAAI,UAAU,SAAS,KAAK,SAAS,SAAS,KAAK,OAAO,SAAS;AAC7E,kBAAM,UAAU,UAAU;AAC1B,kBAAM,IAAI,WAAW,SAAS,KAAK,SAAS,SAAS,KAAK,OAAO,SAAS;AAC1E,kBAAM,WAAW,UAAU;AAC3B,kBAAM,IAAI,UAAU,SAAS,KAAK,YAAY,SAAS,KAAK,OAAO,SAAS;AAC5E,kBAAM,aAAa,UAAU;AAC7B,kBAAM,IAAI,WAAW,SAAS,KAAK,YAAY,SAAS,KAAK,OAAO,SAAS;AAC7E,kBAAM,cAAc,UAAU;AAC9B,kBAAM,MAAM,WAAW,WAAW,WAAW;AAC7C,kBAAM,SAAS,cAAc,cAAc,cAAc;AACzD,kBAAM,IAAI,IAAI,UAAU,KAAK,IAAI,UAAU,KAAK,IAAI,UAAU;AAC9D,mBAAO,OAAO,OAAO,OAAO,SAAS,OAAO;AAAA,UAC9C;AAAA,QACF;AAAA,MACF,OAAO;AACL,iBAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,gBAAM,OAAO,YAAY,IAAI,MAAM,aAAa,KAAK,IAAI,aAAa,OAAO,KAAK,OAAO,aAAa;AACtG,cAAI,OAAO,KAAK,OAAO,aAAa,GAAG;AACrC,qBAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,oBAAM,MAAM,IAAI,IAAI,UAAU,KAAK,IAAI,UAAU,KAAK,IAAI,UAAU;AACpE,qBAAO,OAAO,OAAO;AAAA,YACvB;AACA;AAAA,UACF;AACA,gBAAM,WAAW,KAAK,MAAM,IAAI;AAChC,gBAAM,WAAW,KAAK,MAAM,IAAI;AAChC,mBAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,kBAAM,QAAQ,IAAI,WAAW,SAAS,KAAK,WAAW,SAAS,KAAK,OAAO,SAAS;AACpF,kBAAM,SAAS,IAAI,IAAI,UAAU,KAAK,IAAI,UAAU,KAAK,IAAI,UAAU;AACvE,mBAAO,OAAO,UAAU,UAAU;AAAA,UACpC;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC1E;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,mBAAiB,GAAG,SAAS;AAC7B,QAAM,cAAc,qBAAqB,mBAAmB,CAAC,IAAI,GAAG,EAAE,MAAM,MAAM;AAClF,MAAI,KAAK;AACT,MAAI,eAAe,MAAM;AACvB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,YAAY,EAAE,CAAC;AAAA,EACpF;AACA,QAAM,eAAe,qBAAqB,iBAAiB,GAAG,EAAE,MAAM,MAAM,EAAE;AAC9E,MAAI,iBAAiB,GAAG,MAAM,SAAS,GAAG;AACxC,UAAM,IAAI,MAAM,qDAAqD,GAAG,MAAM,SAAS,kBAAkB,cAAc;AAAA,EACzH;AACA,QAAM,cAAc,WAAW,GAAG,OAAO,OAAO;AAChD,QAAM,OAAO,aAAa,mBAAmB,aAAa,cAAc,GAAG,KAAK,GAAG,WAAW;AAC9F,QAAM,QAAQ,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC3C,QAAM,WAAW,GAAG,MAAM,GAAG,MAAM,SAAS;AAC5C,QAAM,gBAAgB,WAAW,CAAC,IAAI,MAAM,KAAK,WAAW,IAAI,IAAI,CAAC,IAAI,MAAM,KAAK;AACpF,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM,UAAU;AAClD,aAAS,IAAI,GAAG,IAAI,UAAU,KAAK;AACjC,YAAM,MAAM,cAAc,IAAI,CAAC;AAC/B,UAAI,MAAM,GAAG;AACX,aAAK,OAAO,YAAY,IAAI,MAAM;AAAA,MACpC,OAAO;AACL,cAAM,UAAU,cAAc,IAAI,IAAI,CAAC;AACvC,aAAK,OAAO,YAAY,MAAM,WAAW,KAAK,WAAW,MAAM,OAAO,KAAK;AAAA,MAC7E;AAAA,IACF;AAAA,EACF;AACA,QAAM,SAAS,SAAS,eAAe,GAAG,OAAO,aAAa,IAAI;AAClE,MAAI,eAAe,MAAM;AACvB,UAAM,qBAAqB,qBAAqB,uBAAuB,WAAW;AAClF,UAAM,0BAA0B,WAAW,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,mBAAmB,EAAE,CAAC;AAC5H,aAAS,8BAA8B,MAAM;AAC7C,aAAS,8BAA8B,EAAE;AACzC,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,mBAAiB,GAAG,QAAQ;AAC5B,QAAM,cAAc,qBAAqB,mBAAmB,CAAC,IAAI,GAAG,EAAE,MAAM,MAAM;AAClF,MAAI,KAAK;AACT,MAAI,eAAe,MAAM;AACvB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,YAAY,EAAE,CAAC;AAAA,EACpF;AACA,QAAM,eAAe,qBAAqB,iBAAiB,GAAG,EAAE,MAAM,MAAM,EAAE;AAC9E,MAAI,iBAAiB,GAAG,MAAM,SAAS,GAAG;AACxC,UAAM,IAAI,MAAM,oDAAoD,GAAG,MAAM,SAAS,kBAAkB,cAAc;AAAA,EACxH;AACA,QAAM,cAAc,WAAW,GAAG,OAAO,OAAO;AAChD,QAAM,OAAO,aAAa,oBAAoB,aAAa,cAAc,GAAG,KAAK,GAAG,WAAW;AAC/F,QAAM,QAAQ,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC3C,QAAM,WAAW,GAAG,MAAM,GAAG,MAAM,SAAS;AAC5C,QAAM,gBAAgB,WAAW,CAAC,IAAI,MAAM,KAAK,WAAW,IAAI,IAAI,CAAC,IAAI,MAAM,KAAK;AACpF,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM,UAAU;AAClD,aAAS,IAAI,GAAG,IAAI,UAAU,KAAK;AACjC,YAAM,MAAM,cAAc,IAAI,CAAC;AAC/B,UAAI,MAAM,GAAG;AACX,aAAK,OAAO,YAAY,IAAI,MAAM;AAAA,MACpC,OAAO;AACL,cAAM,UAAU,cAAc,IAAI,IAAI,CAAC;AACvC,aAAK,OAAO,YAAY,MAAM,WAAW,KAAK,WAAW,MAAM,OAAO,KAAK;AAAA,MAC7E;AAAA,IACF;AAAA,EACF;AACA,QAAM,SAAS,SAAS,eAAe,GAAG,OAAO,aAAa,IAAI;AAClE,MAAI,eAAe,MAAM;AACvB,UAAM,qBAAqB,qBAAqB,uBAAuB,WAAW;AAClF,UAAM,0BAA0B,WAAW,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,mBAAmB,EAAE,CAAC;AAC5H,aAAS,8BAA8B,MAAM;AAC7C,aAAS,8BAA8B,EAAE;AACzC,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAAZ,OAAM,aAAa,IAAI;AAC/B,MAAI,EAAE,MAAM,WAAW,GAAG;AACxB,UAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,UAAM,cAAc,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACtD,UAAM,UAAU,aAAa,OAAO,aAAa,QAAQ,OAAO,QAAQ,OAAOA,KAAI;AACnF,WAAO,SAAS,eAAe,CAACA,KAAI,GAAG,QAAQ,OAAO,OAAO;AAAA,EAC/D,WAAW,EAAE,MAAM,WAAW,GAAG;AAC/B,UAAM,OAAO,SAAS,WAAW,CAAC;AAClC,UAAM,aAAa,SAAS,WAAW,OAAO;AAC9C,UAAM,SAAS,mBAAmB,MAAM,YAAYA,OAAM,YAAY;AACtE,WAAO,SAAS,eAAe,OAAO,OAAO,QAAQ,OAAO,OAAO,MAAM;AAAA,EAC3E;AACA,QAAM,IAAI,MAAM,qEAAqE,EAAE,MAAM,SAAS;AACxG;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,WAAW,WAAW,IAAI;AAClC,eAAa,OAAO,eAAe,QAAQ,MAAM,+DAA+D,YAAY;AAC5H,QAAM,YAAY,EAAE,MAAM;AAC1B,QAAM,cAAc,EAAE,MAAM;AAC5B,QAAM,aAAa,EAAE,MAAM;AAC3B,QAAM,aAAa,EAAE,MAAM;AAC3B,QAAM,eAAe,cAAc;AACnC,QAAM,cAAc,aAAa;AACjC,QAAM,cAAc,cAAc,YAAY;AAC9C,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAM,SAAS,IAAI,aAAa,YAAY,eAAe,cAAc,WAAW;AACpF,MAAI,YAAY;AAChB,WAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,aAAS,IAAI,GAAG,IAAI,cAAc,EAAE,GAAG;AACrC,YAAM,MAAM,KAAK,MAAM,IAAI,SAAS;AACpC,YAAM,UAAU,IAAI;AACpB,eAAS,IAAI,GAAG,IAAI,aAAa,EAAE,GAAG;AACpC,cAAM,MAAM,KAAK,MAAM,IAAI,SAAS;AACpC,cAAM,UAAU,IAAI;AACpB,cAAM,WAAW,UAAU,YAAY,WAAW;AAClD,iBAAS,IAAI,GAAG,IAAI,aAAa,EAAE,GAAG;AACpC,gBAAM,MAAM,IAAI;AAChB,gBAAM,WAAW,MAAM,cAAc,MAAM,cAAc,MAAM,cAAc;AAC7E,iBAAO,eAAe,QAAQ;AAAA,QAChC;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,CAAC,WAAW,cAAc,aAAa,WAAW,GAAG,EAAE,OAAO,MAAM;AACrG;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,sBAAsB,MAAM;AACnC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAY,UAAS,KAAK,MAAM,WAAW,gBAAgB,IAAI;AAC3D,mBAAiB,CAAC,GAAG,MAAM,GAAG,uBAAuB;AACrD,QAAM,WAAW,aAAa,eAAe,EAAE,KAAK;AACpD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,MAAI,aAAa;AACjB,MAAI,cAAc,MAAM;AACtB,iBAAa,CAAC,GAAG,CAAC;AAAA,EACpB;AACA,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,UAAU,GAAG,MAAM,gFAAgFA,2BAA0B,aAAa;AAC3N,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,YAAY,MAAM,iBAAiB,IAAI;AAC/H,QAAM,EAAE,cAAc,aAAa,gBAAgB,eAAe,QAAQ,IAAI;AAC9E,QAAM,UAAU,QAAQ;AACxB,QAAM,SAAS,QAAQ;AACvB,QAAM,QAAQ,SAAS,cAAc,SAAS;AAC9C,QAAM,IAAI,IAAI,aAAa,SAAS,UAAU,EAAE,KAAK;AACrD,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,QAAQ,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AAC/C,QAAM,QAAQ,EAAE;AAChB,WAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,UAAM,WAAW,IAAI,SAAS;AAC9B,UAAM,WAAW,IAAI,EAAE,QAAQ;AAC/B,aAAS,KAAK,GAAG,KAAK,SAAS,WAAW,EAAE,IAAI;AAC9C,YAAM,WAAW,WAAW,KAAK,EAAE,QAAQ;AAC3C,YAAM,WAAW,KAAK,SAAS,eAAe;AAC9C,eAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,cAAM,KAAK,WAAW,KAAK;AAC3B,YAAI,KAAK,KAAK,MAAM,SAAS,UAAU;AACrC;AAAA,QACF;AACA,cAAM,WAAW,KAAK,cAAc;AACpC,cAAM,WAAW,WAAW,KAAK,SAAS;AAC1C,iBAAS,KAAK,GAAG,KAAK,SAAS,UAAU,EAAE,IAAI;AAC7C,gBAAM,WAAW,WAAW,KAAK,EAAE,QAAQ;AAC3C,gBAAM,WAAW,KAAK,SAAS,cAAc;AAC7C,mBAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,kBAAM,KAAK,WAAW,KAAK;AAC3B,gBAAI,KAAK,KAAK,MAAM,SAAS,SAAS;AACpC;AAAA,YACF;AACA,kBAAM,WAAW,WAAW,KAAK,cAAc;AAC/C,kBAAM,WAAW,WAAW,KAAK,SAAS;AAC1C,gBAAI,WAAW;AACf,gBAAI,WAAW;AACf,qBAAS,KAAK,GAAG,KAAK,SAAS,YAAY,EAAE,IAAI;AAC/C,oBAAM,OAAO,MAAM,WAAW;AAC9B,uBAAS,IAAI,GAAG,IAAI,OAAO,EAAE,GAAG;AAC9B,sBAAM,WAAW,MAAM,OAAO,MAAM,WAAW;AAAA,cACjD;AACA,0BAAY;AACZ,0BAAY;AAAA,YACd;AAAA,UACF;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,EAAE,OAAO,EAAE,OAAO,EAAE,MAAM;AAC3D;AACA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qCAAqC,MAAM;AAClD,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,IAAI;AAClB,QAAM,EAAE,SAAAA,UAAS,WAAW,KAAK,MAAM,iBAAiB,YAAY,IAAI;AACxE,mBAAiB,CAAC,GAAG,EAAE,GAAG,qCAAqC;AAC/D,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,aAAaA,UAAS,WAAW,MAAM,iBAAiB,IAAI;AAC7H,QAAM,EAAE,cAAc,aAAa,cAAc,YAAY,IAAI;AACjE,QAAM,KAAK,IAAI,aAAa,SAAS,aAAa,SAAS;AAC3D,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,QAAQ,SAAS,cAAc,SAAS;AAC9C,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,OAAO,IAAI,aAAa,EAAE,OAAO,EAAE,OAAO,KAAK;AACrD,QAAM,SAAS,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC5C,QAAM,QAAQ,IAAI,aAAa,GAAG,OAAO,GAAG,OAAO,MAAM;AACzD,WAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,UAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,MAAM,SAAS,MAAM,YAAY,CAAC;AACjE,UAAM,QAAQ,KAAK,IAAI,SAAS,YAAY,SAAS,WAAW,SAAS,MAAM,YAAY;AAC3F,aAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,YAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,MAAM,UAAU,MAAM,WAAW,CAAC;AACjE,YAAM,QAAQ,KAAK,IAAI,SAAS,WAAW,SAAS,UAAU,UAAU,MAAM,WAAW;AACzF,eAAS,KAAK,GAAG,KAAK,SAAS,aAAa,EAAE,IAAI;AAChD,cAAM,KAAK,KAAK,MAAM,KAAK,KAAK;AAChC,cAAM,KAAK,KAAK;AAChB,YAAI,UAAU;AACd,iBAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,mBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,kBAAM,KAAK,KAAK,KAAK,eAAe;AACpC,qBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,oBAAM,KAAK,KAAK,KAAK,cAAc;AACnC,yBAAW,KAAK,IAAI,GAAG,IAAI,IAAI,EAAE,IAAI,MAAM,IAAI,GAAG,IAAI,IAAI,EAAE;AAAA,YAC9D;AAAA,UACF;AAAA,QACF;AACA,WAAG,IAAI,SAAS,IAAI,IAAI,IAAI,EAAE;AAAA,MAChC;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,4CAA4C;AAAA,EAC9C,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,oCAAoC,MAAM;AACjD,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,SAAAA,UAAS,WAAW,KAAK,MAAM,iBAAiB,WAAW,IAAI;AACvE,mBAAiB,CAAC,IAAI,MAAM,GAAG,oCAAoC;AACnE,QAAM,YAAY,aAAa,eAAe,GAAG,KAAK;AACtD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,IAAI;AACjI,QAAM,KAAK,IAAI,aAAa,SAAS,SAAS,SAAS;AACvD,QAAM,WAAW,GAAG;AACpB,QAAM,CAAC,MAAM,MAAM,IAAI,IAAI,GAAG;AAC9B,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,CAAC,MAAM,MAAM,IAAI,IAAI;AAC3B,QAAM,YAAY,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACnD,QAAM,CAAC,OAAO,OAAO,KAAK,IAAI;AAC9B,QAAM,EAAE,WAAW,cAAc,aAAa,YAAY,UAAU,SAAS,aAAa,WAAW,UAAU,cAAc,YAAY,IAAI;AAC7I,QAAM,SAAS,eAAe,IAAI,SAAS,QAAQ;AACnD,QAAM,UAAU,cAAc,IAAI,SAAS,QAAQ;AACnD,QAAM,QAAQ,cAAc;AAC5B,WAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,aAAS,KAAK,GAAG,KAAK,YAAY,EAAE,IAAI;AACtC,eAAS,KAAK,GAAG,KAAK,UAAU,EAAE,IAAI;AACpC,cAAM,WAAW,KAAK;AACtB,cAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,KAAK,WAAW,YAAY,CAAC;AAC5D,cAAM,QAAQ,KAAK,IAAI,YAAY,eAAe,YAAY,YAAY;AAC1E,iBAAS,KAAK,GAAG,KAAK,SAAS,EAAE,IAAI;AACnC,gBAAM,WAAW,KAAK;AACtB,gBAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,KAAK,WAAW,WAAW,CAAC;AAC3D,gBAAM,QAAQ,KAAK,IAAI,WAAW,cAAc,YAAY,WAAW;AACvE,cAAI,UAAU;AACd,mBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,kBAAM,KAAK,KAAK,eAAe;AAC/B,qBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,oBAAM,KAAK,KAAK,cAAc;AAC9B,oBAAM,WAAW,OAAO,IAAI,OAAO,KAAK,OAAO;AAC/C,oBAAM,YAAY,SAAS,eAAe,IAAI,MAAM,SAAS,cAAc,IAAI,MAAM,QAAQ;AAC7F,uBAAS,KAAK,GAAG,KAAK,OAAO,EAAE,IAAI;AACjC,sBAAM,KAAK,KAAK,QAAQ;AACxB,sBAAM,QAAQ,SAAS,WAAW;AAClC,sBAAM,SAAS,UAAU,YAAY;AACrC,2BAAW,QAAQ;AAAA,cACrB;AAAA,YACF;AAAA,UACF;AACA,mBAAS,OAAO,IAAI,OAAO,KAAK,OAAO,KAAK,MAAM;AAAA,QACpD;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,2CAA2C;AAAA,EAC7C,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,SAAS,OAAO,CAAC,OAAO,KAAK,GAAG,EAAE,KAAK;AAC7C,QAAM,OAAO,OAAO;AACpB,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,SAAK,KAAK,QAAQ,MAAM,MAAM;AAAA,EAChC;AACA,QAAM,WAAW,CAAC,GAAG,EAAE,OAAO,GAAG,EAAE,KAAK;AACxC,SAAO,SAAS,eAAe,UAAU,OAAO,OAAO,OAAO,MAAM;AACtE;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,SAAS,UAAU,MAAM,MAAM;AACpD,UAAM,EAAE,GAAG,OAAO,IAAI;AACtB,UAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,UAAU,IAAI;AAC1C,UAAM,aAAa;AACnB,UAAM,QAAQ,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,UAAM,QAAQ,EAAE,MAAM;AACtB,UAAM,aAAa,WAAW,KAAK,IAAI,OAAO,MAAM,EAAE;AACtD,UAAM,aAAa,OAAO,MAAM;AAChC,UAAM,EAAE,WAAW,UAAU,SAAS,YAAY,WAAW,UAAU,SAAS,cAAc,aAAa,cAAc,aAAa,gBAAgB,eAAe,SAAS,IAAI,qBAAqB,sBAAsB,EAAE,OAAO,OAAO,OAAOA,UAAS,MAAM,QAAQ,SAAS;AACpR,UAAM,UAAU,aAAa,cAAc,QAAQ;AACnD,UAAM,UAAU,SAAS;AACzB,UAAM,aAAa,aAAa,kBAAkB,EAAE,OAAO,OAAO;AAClE,aAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,eAAS,OAAO,GAAG,OAAO,WAAW,EAAE,MAAM;AAC3C,cAAM,OAAO,OAAO,eAAe,QAAQ;AAC3C,iBAAS,OAAO,GAAG,OAAO,UAAU,EAAE,MAAM;AAC1C,gBAAM,OAAO,OAAO,cAAc,QAAQ;AAC1C,mBAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,gBAAI,SAAS,OAAO;AACpB,qBAAS,IAAI,GAAG,IAAI,cAAc,EAAE,GAAG;AACrC,oBAAM,MAAM,OAAO,IAAI;AACvB,kBAAI,OAAO,KAAK,MAAM,UAAU;AAC9B,yBAAS,IAAI,GAAG,IAAI,aAAa,EAAE,GAAG;AACpC,wBAAM,MAAM,OAAO,IAAI;AACvB,sBAAI,OAAO,KAAK,MAAM,SAAS;AAC7B,0BAAM,SAAS,aAAa,WAAW,CAAC,GAAG,KAAK,KAAK,CAAC,GAAG,OAAO,aAAa,eAAe,EAAE,KAAK,CAAC;AACpG,0BAAM,cAAc,aAAa,WAAW,CAAC,GAAG,GAAG,CAAC,GAAG,YAAY,aAAa,eAAe,OAAO,KAAK,CAAC;AAC5G,0BAAM,MAAM,MAAM,UAAU,WAAW;AACvC,wBAAI,MAAM,QAAQ;AAChB,+BAAS;AAAA,oBACX;AAAA,kBACF;AAAA,gBACF;AAAA,cACF;AAAA,YACF;AACA,kBAAM,cAAc,aAAa,WAAW,CAAC,GAAG,MAAM,MAAM,CAAC,GAAG,SAAS,aAAa,eAAe,QAAQ,CAAC;AAC9G,uBAAW,eAAe;AAAA,UAC5B;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,SAAS,WAAW,MAAM,aAAa,aAAa,YAAY,EAAE,KAAK,GAAG,UAAU,EAAE,KAAK;AACjG,WAAO,EAAE,QAAQ,OAAO,UAAU,OAAO,EAAE,MAAM;AAAA,EACnD;AACF;AAGA,IAAI,iCAAiC;AAAA,EACnC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,SAAS,UAAU,MAAM,MAAM;AACpD,UAAM,EAAE,GAAG,QAAQ,GAAG,IAAI;AAC1B,UAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,UAAU,IAAI;AAC1C,UAAM,aAAa;AACnB,UAAM,KAAK,aAAa,cAAc,EAAE,OAAO,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE,MAAM;AACnF,UAAM,UAAU,aAAa,cAAc,OAAO,OAAO,WAAW,KAAK,IAAI,OAAO,MAAM,EAAE,MAAM;AAClG,UAAM,EAAE,WAAW,UAAU,SAAS,YAAY,WAAW,UAAU,SAAS,cAAc,aAAa,cAAc,aAAa,gBAAgB,eAAe,SAAS,IAAI,qBAAqB,sBAAsB,EAAE,OAAO,OAAO,OAAOA,UAAS,MAAM,QAAQ,SAAS;AACpR,iBAAa,OAAO,GAAG,SAAS,SAAS,QAAQ,MAAM,YAAY,kEAAkE,SAAS,mBAAmB,GAAG,MAAM;AAC1K,UAAM,MAAM,aAAa,cAAc,UAAU,WAAW,KAAK,IAAI,GAAG,MAAM,EAAE,MAAM;AACtF,UAAM,YAAY,aAAa,0BAA0B,OAAO,OAAO,OAAO,KAAK;AACnF,aAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,eAAS,OAAO,GAAG,OAAO,WAAW,EAAE,MAAM;AAC3C,cAAM,OAAO,OAAO,eAAe,QAAQ;AAC3C,iBAAS,OAAO,GAAG,OAAO,UAAU,EAAE,MAAM;AAC1C,gBAAM,OAAO,OAAO,cAAc,QAAQ;AAC1C,mBAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,gBAAI,SAAS,OAAO;AACpB,gBAAI,OAAO;AACX,gBAAI,OAAO;AACX,qBAAS,IAAI,GAAG,IAAI,cAAc,EAAE,GAAG;AACrC,oBAAM,MAAM,OAAO,IAAI;AACvB,kBAAI,OAAO,KAAK,MAAM,UAAU;AAC9B,yBAAS,IAAI,GAAG,IAAI,aAAa,EAAE,GAAG;AACpC,wBAAM,MAAM,OAAO,IAAI;AACvB,sBAAI,OAAO,KAAK,MAAM,SAAS;AAC7B,0BAAM,MAAM,GAAG,GAAG,KAAK,KAAK,KAAK,QAAQ,GAAG,GAAG;AAC/C,wBAAI,MAAM,QAAQ;AAChB,+BAAS;AACT,6BAAO;AACP,6BAAO;AAAA,oBACT;AAAA,kBACF;AAAA,gBACF;AAAA,cACF;AAAA,YACF;AACA,sBAAU,MAAM,MAAM,MAAM,IAAI,GAAG,MAAM,MAAM;AAAA,UACjD;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,SAAS,WAAW,MAAM,aAAa,aAAa,WAAW,EAAE,KAAK,GAAG,OAAO,OAAO,OAAO,KAAK;AACzG,WAAO,EAAE,QAAQ,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAAA,EAC5D;AACF;AAGA,IAAI,gCAAgC;AAAA,EAClC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,SAAS,UAAU,MAAM,MAAM;AACpD,UAAM,EAAE,GAAG,QAAQ,GAAG,IAAI;AAC1B,UAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,UAAU,IAAI;AAC1C,UAAM,aAAa;AACnB,UAAM,KAAK,aAAa,cAAc,EAAE,OAAO,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE,MAAM;AACnF,UAAM,UAAU,aAAa,cAAc,OAAO,OAAO,WAAW,KAAK,IAAI,OAAO,MAAM,EAAE,MAAM;AAClG,UAAM,EAAE,WAAW,UAAU,SAAS,YAAY,WAAW,UAAU,SAAS,cAAc,aAAa,cAAc,aAAa,gBAAgB,eAAe,SAAS,IAAI,qBAAqB,sBAAsB,EAAE,OAAO,OAAO,OAAOA,UAAS,MAAM,QAAQ,SAAS;AACpR,iBAAa,OAAO,GAAG,SAAS,SAAS,QAAQ,MAAM,YAAY,iEAAiE,SAAS,mBAAmB,GAAG,MAAM;AACzK,UAAM,MAAM,aAAa,cAAc,UAAU,WAAW,KAAK,IAAI,GAAG,MAAM,EAAE,MAAM;AACtF,UAAM,YAAY,aAAa,0BAA0B,EAAE,OAAO,EAAE,KAAK;AACzE,aAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,eAAS,OAAO,GAAG,OAAO,WAAW,EAAE,MAAM;AAC3C,cAAM,OAAO,OAAO,eAAe,QAAQ;AAC3C,iBAAS,OAAO,GAAG,OAAO,UAAU,EAAE,MAAM;AAC1C,gBAAM,OAAO,OAAO,cAAc,QAAQ;AAC1C,mBAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,gBAAI,SAAS,OAAO;AACpB,gBAAI,SAAS,OAAO,IAAI,IAAI;AAC5B,gBAAI,SAAS,OAAO,IAAI,IAAI;AAC5B,qBAAS,IAAI,GAAG,IAAI,cAAc,EAAE,GAAG;AACrC,oBAAM,MAAM,OAAO,IAAI;AACvB,kBAAI,OAAO,KAAK,MAAM,UAAU;AAC9B,yBAAS,IAAI,GAAG,IAAI,aAAa,EAAE,GAAG;AACpC,wBAAM,MAAM,OAAO,IAAI;AACvB,sBAAI,OAAO,KAAK,MAAM,SAAS;AAC7B,0BAAM,MAAM,GAAG,GAAG,KAAK,KAAK,KAAK,QAAQ,GAAG,GAAG;AAC/C,wBAAI,MAAM,QAAQ;AAChB,+BAAS;AACT,+BAAS;AACT,+BAAS;AAAA,oBACX;AAAA,kBACF;AAAA,gBACF;AAAA,cACF;AAAA,YACF;AACA,sBAAU,GAAG,QAAQ,QAAQ,MAAM,IAAI,GAAG,MAAM,MAAM;AAAA,UACxD;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,SAAS,WAAW,MAAM,aAAa,aAAa,WAAW,EAAE,KAAK,GAAG,EAAE,OAAO,EAAE,KAAK;AAC/F,WAAO,EAAE,QAAQ,OAAO,EAAE,OAAO,OAAO,EAAE,MAAM;AAAA,EAClD;AACF;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,mBAAiB,GAAG,KAAK;AACzB,MAAI;AACJ,MAAI,EAAE,UAAU,QAAQ;AACtB,SAAK,MAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,QAAQ,EAAE,CAAC;AAAA,EAC5E,OAAO;AACL,SAAK,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACrD;AACA,QAAM,QAAQ,GAAG,MAAM;AACvB,QAAM,OAAO,aAAa,eAAe,MAAM,GAAG,KAAK;AACvD,QAAM,cAAc,qBAAqB,mBAAmB,MAAM,KAAK;AACvE,MAAI,gBAAgB;AACpB,MAAI,YAAY;AAChB,MAAI,eAAe,MAAM;AACvB,gBAAY,WAAW,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,YAAY,EAAE,CAAC;AAC7F,oBAAgB,qBAAqB,iBAAiB,cAAc,QAAQ,KAAK;AAAA,EACnF;AACA,uBAAqB,2BAA2B,OAAO,eAAe,UAAU,MAAM,MAAM;AAC5F,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,UAAU,OAAO,aAAa;AAC7G,QAAM,cAAc,qBAAqB,WAAW,UAAU,OAAO,OAAO;AAC5E,MAAI,SAAS,OAAO,UAAU,UAAU,WAAW;AACnD,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,OAAO,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AAC9C,QAAM,QAAQ,SAAS,KAAK,IAAI,UAAU,MAAM,EAAE;AAClD,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,SAAS,KAAK;AACpB,QAAI,OAAO;AACX,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,cAAQ,MAAM,SAAS;AAAA,IACzB;AACA,SAAK,MAAM;AAAA,EACb;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,OAAO,OAAO,IAAI;AAC7E,UAAM,YAAY;AAClB,aAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC1F,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,WAAS,8BAA8B,EAAE;AACzC,MAAI,eAAe,MAAM;AACvB,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,SAAO;AACT;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,SAAS,IAAI;AACrB,QAAM,UAAU;AAChB,QAAM,EAAE,SAAS,YAAY,OAAO,IAAI,qBAAqB,qBAAqB,UAAU,QAAQ,MAAM;AAC1G,uBAAqB,oBAAoB,QAAQ,QAAQ,QAAQ,OAAO;AACxE,QAAM,EAAE,MAAM,MAAM,IAAI,qBAAqB,qBAAqB,YAAY,MAAM;AACpF,QAAM,SAAS,MAAM;AACrB,MAAI,MAAM;AACV,MAAI,mBAAmB,QAAQ;AAC/B,QAAM,mBAAmB,CAAC;AAC1B,WAAS,KAAK,GAAG,KAAK,QAAQ,EAAE,IAAI;AAClC,eAAW,UAAU,MAAM,KAAK;AAC9B,YAAM,EAAE,oBAAoB,MAAM,YAAY,aAAa,IAAI,qBAAqB,qBAAqB,kBAAkB,OAAO,OAAO;AACzI,UAAI;AACJ,UAAI,qBAAqB,sBAAsB,IAAI,GAAG;AACpD,YAAI,QAAQ;AAAA,MACd,OAAO;AACL,YAAI,WAAW,EAAE,QAAQ,EAAE,GAAG,QAAQ,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AACrF,yBAAiB,KAAK,CAAC;AAAA,MACzB;AACA,YAAM,cAAc,EAAE,MAAM,MAAM;AAClC,eAAS,IAAI,GAAG,IAAI,aAAa,QAAQ,EAAE,GAAG;AAC5C,oBAAY,OAAO,aAAa,IAAI,GAAG,CAAC;AAAA,MAC1C;AACA,UAAI,CAAC,aAAa,YAAY,EAAE,OAAO,WAAW,GAAG;AACnD,YAAI,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAChF,yBAAiB,KAAK,CAAC;AAAA,MACzB;AACA,UAAI,QAAQ,MAAM;AAChB,cAAM;AAAA,MACR,OAAO;AACL,cAAM,UAAU,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,IAAI,GAAG,SAAS,SAAS,CAAC;AAC/D,yBAAiB,KAAK,GAAG;AAAA,MAC3B;AAAA,IACF;AACA,QAAI,KAAK,SAAS,GAAG;AACnB,UAAI,KAAK,OAAO,GAAG;AACjB,cAAM,KAAK;AAAA,UACT,QAAQ,EAAE,GAAG,IAAI;AAAA,UACjB,SAAS;AAAA,UACT,OAAO;AAAA,YACL,MAAM,KAAK,OAAO,QAAQ,SAAS;AAAA,YACnC,UAAU;AAAA,UACZ;AAAA,QACF,CAAC;AACD,yBAAiB,KAAK,GAAG;AAAA,MAC3B;AACA;AAAA,IACF;AAAA,EACF;AACA,aAAW,cAAc,kBAAkB;AACzC,QAAI,eAAe,KAAK;AACtB;AAAA,IACF;AACA,aAAS,8BAA8B,UAAU;AAAA,EACnD;AACA,SAAO;AACT;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,IAAI,EAAE,IAAI;AAClB,mBAAiB,CAAC,IAAI,CAAC,GAAG,SAAS;AACnC,QAAM,eAAe,IAAI,aAAa,aAAa,cAAc,EAAE,KAAK,CAAC;AACzE,QAAM,SAAS,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC3C,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,UAAM,IAAI,OAAO;AACjB,QAAI,KAAK,GAAG;AACV,mBAAa,MAAM,SAAS;AAAA,IAC9B,OAAO;AACL,mBAAa,MAAM,SAAS,OAAO,IAAI;AAAA,IACzC;AAAA,EACF;AACA,SAAO,SAAS,eAAe,EAAE,OAAO,WAAW,YAAY;AACjE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,IAAI,qBAAqB;AAC7B,IAAI,KAAK,qBAAqB;AAC9B,IAAI,KAAK,qBAAqB;AAC9B,IAAI,KAAK,qBAAqB;AAC9B,IAAI,KAAK,qBAAqB;AAC9B,IAAI,KAAK,qBAAqB;AAC9B,IAAI,OAAO,gBAAgB,KAAK,CAAC,OAAO;AACtC,QAAM,QAAQ,KAAK,KAAK,EAAE;AAC1B,QAAM,IAAI,KAAK,IAAI,EAAE;AACrB,QAAM,KAAK,KAAK,IAAI,IAAI;AACxB,SAAO,SAAS,QAAQ,KAAK,KAAK,MAAM,KAAK,MAAM,KAAK,MAAM,KAAK,MAAM,KAAK,KAAK,IAAI,CAAC,IAAI,CAAC;AAC/F,CAAC;AACD,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,IAAI,IAAI;AAChB,QAAM,YAAY,OAAO,MAAM;AAC/B,QAAM,WAAW,OAAO,MAAM,MAAM;AACpC,MAAI,OAAO;AACX,MAAI,MAAM,GAAG;AACX,iBAAa,OAAO,EAAE,YAAY,MAAM,KAAK,MAAM,iCAAiC,EAAE,YAAY,OAAO,YAAY;AACrH,WAAO,YAAY,MAAM;AAAA,EAC3B;AACA,WAAS,OAAO,MAAM,GAAG,CAAC;AAC1B,SAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC1F;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,6BAA6B,CAAC,GAAG,MAAM,IAAI,CAAC;AAC9D,IAAI,OAAO,iBAAiB,SAAS,WAAW;AAChD,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,QAAQ,SAAS,YAAY;AAC7C,QAAM,aAAa,OAAO;AAC1B,QAAM,QAAQ,WAAW;AACzB,QAAM,WAAW,WAAW;AAC5B,QAAM,YAAY,WAAW,KAAK,IAAI,OAAO,MAAM;AACnD,QAAM,SAAS,UAAU,mBAAmB;AAC5C,QAAM,SAAS,UAAU,mBAAmB;AAC5C,QAAM,cAAc,CAAC,OAAO,QAAQ;AACpC,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,aAAa,aAAa,uBAAuB,WAAW,UAAU;AAC5E,QAAM,aAAa,aAAa,uBAAuB,WAAW,UAAU;AAC5E,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,UAAM,KAAK,OAAO;AAAA,MAChB,QAAQ,EAAE,GAAG,OAAO;AAAA,MACpB,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,CAAC,GAAG,CAAC,GAAG,MAAM,CAAC,GAAG,QAAQ,EAAE;AAAA,IAC9C,CAAC;AACD,UAAM,KAAK,OAAO;AAAA,MAChB,QAAQ,EAAE,GAAG,OAAO;AAAA,MACpB,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,CAAC,GAAG,CAAC,GAAG,MAAM,CAAC,GAAG,QAAQ,EAAE;AAAA,IAC9C,CAAC;AACD,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,IAAI,MAAM,GAAG,GAAG,SAAS,WAAW,CAAC;AAC/E,UAAM,EAAE,MAAM,OAAO,MAAM,MAAM,IAAI,QAAQ,QAAQ,SAAS,UAAU;AACxE,UAAM,MAAM,qBAAqB,uBAAuB,OAAO,KAAK;AACpE,aAAS,IAAI,GAAG,IAAI,UAAU,KAAK;AACjC,YAAM,IAAI,qBAAqB,oBAAoB,KAAK,CAAC;AACzD,iBAAW,IAAI,WAAW,KAAK,EAAE;AACjC,iBAAW,IAAI,WAAW,KAAK,EAAE;AAAA,IACnC;AACA,eAAW,8BAA8B,EAAE;AAC3C,eAAW,8BAA8B,EAAE;AAC3C,eAAW,8BAA8B,MAAM;AAAA,EACjD;AACA,QAAM,YAAY,WAAW,eAAe,aAAa,WAAW,UAAU;AAC9E,QAAM,YAAY,WAAW,eAAe,aAAa,WAAW,UAAU;AAC9E,QAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,WAAW,MAAM,UAAU,GAAG,SAAS,WAAW,CAAC;AAC7F,aAAW,8BAA8B,SAAS;AAClD,aAAW,8BAA8B,SAAS;AAClD,SAAO;AACT;AACA,SAAS,QAAQ,QAAQ,SAAS,YAAY;AAC5C,QAAMc,cAAY,aAAa,cAAc,OAAO,KAAK;AACzD,QAAM,YAAY,WAAW,KAAK,IAAI,OAAO,MAAM;AACnD,QAAM,WAAW,WAAW,KAAK,IAAI,UAAU,mBAAmB,KAAK,MAAM,EAAE;AAC/E,QAAM,WAAW,WAAW,KAAK,IAAI,UAAU,mBAAmB,KAAK,MAAM,EAAE;AAC/E,MAAI,cAAcA,WAAS,GAAG;AAC5B,UAAM,SAAS,UAAU,UAAU,UAAUA,aAAW,SAAS,UAAU;AAC3E,UAAM,cAAc,CAAC,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE;AACrD,QAAI,SAAS;AACX,YAAM,WAAW,WAAW,eAAe,aAAa,WAAW,OAAO,IAAI;AAC9E,YAAM,WAAW,WAAW,eAAe,aAAa,WAAW,OAAO,IAAI;AAC9E,YAAM,WAAW,WAAW,eAAe,CAAC,GAAG,WAAW,aAAa,kBAAkBA,aAAW,SAAS,CAAC;AAC9G,YAAM,eAAe,UAAU,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,WAAW,CAAC;AAC/E,YAAM,cAAc,cAAc,WAAW,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,GAAG,SAAS,WAAW,CAAC;AAC1G,YAAM,cAAc,cAAc,WAAW,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,aAAa,GAAG,SAAS,WAAW,CAAC;AAC9G,YAAM,cAAc,WAAW,KAAK,IAAI,YAAY,MAAM,EAAE;AAC5D,YAAM,cAAc,WAAW,KAAK,IAAI,YAAY,MAAM,EAAE;AAC5D,iBAAW,8BAA8B,QAAQ;AACjD,iBAAW,8BAA8B,QAAQ;AACjD,iBAAW,8BAA8B,QAAQ;AACjD,iBAAW,8BAA8B,YAAY;AACrD,iBAAW,8BAA8B,WAAW;AACpD,iBAAW,8BAA8B,WAAW;AACpD,aAAO,EAAE,MAAM,aAAa,MAAM,YAAY;AAAA,IAChD;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAM,OAAO,qBAAqB,uBAAuB,UAAU,QAAQ;AAC3E,UAAM,YAAY,yBAAyB,MAAMA,aAAW,OAAO;AACnE,WAAO,qBAAqB,uBAAuB,SAAS;AAAA,EAC9D;AACF;AACA,SAAS,cAAc1B,OAAM;AAC3B,UAAQA,QAAOA,QAAO,OAAO;AAC/B;AACA,SAAS,UAAU,UAAU,UAAUA,OAAM,SAAS,YAAY;AAChE,MAAIA,UAAS,GAAG;AACd,WAAO,EAAE,MAAM,UAAU,MAAM,SAAS;AAAA,EAC1C;AACA,QAAM,OAAO,qBAAqB,uBAAuB,UAAU,QAAQ;AAC3E,QAAMuB,QAAOvB,QAAO;AACpB,QAAM,cAAc,qBAAqB,qBAAqB,IAAI;AAClE,QAAM,eAAe,YAAY;AACjC,QAAM,eAAe,YAAY;AACjC,QAAM,YAAY,CAAC,aAAa,MAAM;AACtC,QAAM,eAAe,WAAW,eAAe,WAAW,WAAW,YAAY;AACjF,QAAM,eAAe,WAAW,eAAe,WAAW,WAAW,YAAY;AACjF,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,MAAM,cAAc,MAAM,aAAa,GAAG,SAAS,WAAW,CAAC;AAC3G,QAAM,aAAa,qBAAqB,oBAAoB,IAAI;AAChE,QAAM,cAAc,WAAW;AAC/B,QAAM,cAAc,WAAW;AAC/B,QAAM,WAAW,CAAC,YAAY,MAAM;AACpC,QAAM,cAAc,WAAW,eAAe,UAAU,WAAW,WAAW;AAC9E,QAAM,cAAc,WAAW,eAAe,UAAU,WAAW,WAAW;AAC9E,QAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,MAAM,aAAa,MAAM,YAAY,GAAG,SAAS,WAAW,CAAC;AACxG,QAAM,eAAe,UAAU,cAAc,cAAcuB,OAAM,SAAS,UAAU;AACpF,QAAM,gBAAgB,aAAa;AACnC,QAAM,gBAAgB,aAAa;AACnC,QAAM,aAAa,CAAC,cAAc,MAAM;AACxC,QAAM,gBAAgB,WAAW,eAAe,YAAY,WAAW,aAAa;AACpF,QAAM,gBAAgB,WAAW,eAAe,YAAY,WAAW,aAAa;AACpF,QAAM,kBAAkB,SAAS;AAAA,IAC/B,QAAQ,EAAE,MAAM,eAAe,MAAM,cAAc;AAAA,IACnD,SAAS;AAAA,EACX,CAAC;AACD,QAAM,cAAc,UAAU,aAAa,aAAaA,OAAM,SAAS,UAAU;AACjF,QAAM,eAAe,YAAY;AACjC,QAAM,eAAe,YAAY;AACjC,QAAM,YAAY,CAAC,aAAa,MAAM;AACtC,QAAM,eAAe,WAAW,eAAe,WAAW,WAAW,YAAY;AACjF,QAAM,eAAe,WAAW,eAAe,WAAW,WAAW,YAAY;AACjF,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,MAAM,cAAc,MAAM,aAAa,GAAG,SAAS,WAAW,CAAC;AAC3G,QAAM,KAAK,qBAAqB,UAAUvB,OAAM,OAAO;AACvD,QAAM,SAAS,CAAC,GAAG,KAAK,MAAM;AAC9B,QAAM,YAAY,WAAW,eAAe,QAAQ,WAAW,GAAG,IAAI;AACtE,QAAM,YAAY,WAAW,eAAe,QAAQ,WAAW,GAAG,IAAI;AACtE,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,MAAM,WAAW,MAAM,UAAU,GAAG,SAAS,WAAW,CAAC;AAClG,QAAM,eAAe,UAAU,EAAE,QAAQ,EAAE,GAAG,aAAa,GAAG,eAAe,GAAG,SAAS,WAAW,CAAC;AACrG,QAAM,UAAU,KAAK;AAAA,IACnB,QAAQ,EAAE,GAAG,iBAAiB,GAAG,aAAa;AAAA,IAC9C,SAAS;AAAA,EACX,CAAC;AACD,QAAM,UAAU,KAAK;AAAA,IACnB,QAAQ,EAAE,GAAG,iBAAiB,GAAG,aAAa;AAAA,IAC9C,SAAS;AAAA,EACX,CAAC;AACD,QAAM,cAAc,MAAM,EAAE,QAAQ,EAAE,OAAO,QAAQ,GAAG,SAAS,WAAW,CAAC;AAC7E,QAAM,cAAc,MAAM,EAAE,QAAQ,EAAE,OAAO,QAAQ,GAAG,SAAS,WAAW,CAAC;AAC7E,QAAM,cAAc,MAAM,EAAE,QAAQ,EAAE,OAAO,QAAQ,GAAG,SAAS,WAAW,CAAC;AAC7E,QAAM,cAAc,MAAM,EAAE,QAAQ,EAAE,OAAO,QAAQ,GAAG,SAAS,WAAW,CAAC;AAC7E,QAAM,QAAQ,QAAQ;AAAA,IACpB,QAAQ,CAAC,aAAa,WAAW;AAAA,IACjC,SAAS;AAAA,IACT,OAAO,EAAE,MAAM,EAAE;AAAA,EACnB,CAAC;AACD,QAAM,QAAQ,QAAQ;AAAA,IACpB,QAAQ,CAAC,aAAa,WAAW;AAAA,IACjC,SAAS;AAAA,IACT,OAAO,EAAE,MAAM,EAAE;AAAA,EACnB,CAAC;AACD,QAAM,YAAY,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACpD,QAAM,YAAY,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACpD,aAAW,8BAA8B,YAAY;AACrD,aAAW,8BAA8B,YAAY;AACrD,aAAW,8BAA8B,cAAc;AACvD,aAAW,8BAA8B,WAAW;AACpD,aAAW,8BAA8B,WAAW;AACpD,aAAW,8BAA8B,aAAa;AACtD,aAAW,8BAA8B,aAAa;AACtD,aAAW,8BAA8B,aAAa;AACtD,aAAW,8BAA8B,eAAe;AACxD,aAAW,8BAA8B,YAAY;AACrD,aAAW,8BAA8B,YAAY;AACrD,aAAW,8BAA8B,cAAc;AACvD,aAAW,8BAA8B,SAAS;AAClD,aAAW,8BAA8B,SAAS;AAClD,aAAW,8BAA8B,WAAW;AACpD,aAAW,8BAA8B,YAAY;AACrD,aAAW,8BAA8B,OAAO;AAChD,aAAW,8BAA8B,OAAO;AAChD,aAAW,8BAA8B,WAAW;AACpD,aAAW,8BAA8B,WAAW;AACpD,aAAW,8BAA8B,WAAW;AACpD,aAAW,8BAA8B,WAAW;AACpD,aAAW,8BAA8B,KAAK;AAC9C,aAAW,8BAA8B,KAAK;AAC9C,SAAO,EAAE,MAAM,WAAW,MAAM,UAAU;AAC5C;AACA,SAAS,yBAAyB,MAAMA,OAAM,SAAS;AACrD,QAAM,MAAM,IAAI,aAAaA,QAAO,CAAC;AACrC,WAAS,KAAK,GAAG,KAAKA,OAAM,MAAM;AAChC,QAAI,QAAQ;AACZ,QAAI,QAAQ;AACZ,aAAS,IAAI,GAAG,IAAIA,OAAM,KAAK;AAC7B,YAAM,KAAK,qBAAqB,SAAS,KAAK,GAAGA,OAAM,OAAO;AAC9D,YAAM,OAAO,qBAAqB,oBAAoB,MAAM,CAAC;AAC7D,eAAS,KAAK,OAAO,GAAG,OAAO,KAAK,OAAO,GAAG;AAC9C,eAAS,KAAK,OAAO,GAAG,OAAO,KAAK,OAAO,GAAG;AAAA,IAChD;AACA,QAAI,SAAS;AACX,eAASA;AACT,eAASA;AAAA,IACX;AACA,yBAAqB,mBAAmB,KAAK,OAAO,OAAO,EAAE;AAAA,EAC/D;AACA,SAAO;AACT;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM0B,cAAY,aAAa,cAAc,OAAO,KAAK;AACzD,QAAM,qBAAqB,OAAO,MAAM,OAAO,MAAM,SAAS;AAC9D,QAAM,QAAQA,cAAY;AAC1B,QAAM,UAAU,SAAS;AAAA,IACvB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,OAAO,kBAAkB,EAAE;AAAA,EAC9C,CAAC;AACD,QAAM,SAAS,SAAS,SAAS,OAAO,QAAQ;AAChD,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,OAAO,MAAM,EAAE,CAAC;AAC5G,WAAS,8BAA8B,OAAO;AAC9C,WAAS,8BAA8B,MAAM;AAC7C,SAAO;AACT;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,OAAO,MAAM,IAAI;AAChC,QAAM,SAAS,SAAS,aAAa,WAAW,KAAK;AACrD,QAAM,SAAS,aAAa,kBAAkB,QAAQ,aAAa,cAAc,KAAK,CAAC;AACvF,aAAW,QAAQ,OAAO,MAAM;AAChC,SAAO,SAAS,eAAe,OAAO,QAAQ,MAAM;AACtD;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AACA,SAAS,WAAW,QAAQ,OAAO,OAAO;AACxC,MAAI,UAAU,UAAU;AACtB,WAAO,KAAK,KAAK;AAAA,EACnB,OAAO;AACL,WAAO,KAAK,KAAK;AAAA,EACnB;AACF;AAGA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,UAAM,aAAa;AACnB,UAAM,SAAS,aAAa,uBAAuB,OAAO,OAAO,aAAa,cAAc,OAAO,KAAK,CAAC;AACzG,UAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,UAAM,YAAY,WAAW,KAAK,IAAI,OAAO,MAAM,EAAE;AACrD,aAAS,WAAW,GAAG,WAAW,OAAO,YAAY;AACnD,YAAM,cAAc,WAAW,aAAa,cAAc;AAC1D,eAAS,MAAM,GAAG,MAAM,aAAa,OAAO;AAC1C,cAAM,YAAY,OAAO,aAAa;AACtC,iBAAS,MAAM,GAAG,MAAM,YAAY,OAAO;AACzC,gBAAM,YAAY,MAAM;AACxB,mBAAS,UAAU,GAAG,UAAU,aAAa,WAAW;AACtD,kBAAM,SAAS,KAAK,MAAM,aAAa,MAAM,CAAC;AAC9C,kBAAM,SAAS,cAAc,YAAY,YAAY;AACrD,gBAAI,cAAc,UAAU;AAC5B,gBAAI,UAAU,KAAK,SAAS,YAAY;AACtC,oBAAM,mBAAmB,SAAS;AAClC,oBAAM,WAAW,cAAc,YAAY,mBAAmB;AAC9D,4BAAc,UAAU;AAAA,YAC1B;AACA,mBAAO,UAAU;AAAA,UACnB;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,SAAS,WAAW,MAAM,QAAQ,OAAO,OAAO,OAAO,KAAK;AAClE,WAAO,EAAE,QAAQ,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAAA,EAC5D;AACF;AAGA,IAAI,eAAe,6BAA6B,CAAC,GAAG,MAAM,KAAK,MAAM,IAAI,CAAC,CAAC;AAC3E,IAAI,YAAY,iBAAiB,UAAU,cAAc,MAAM,OAAO;AACtE,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAd,UAAS,KAAK,MAAM,YAAY,WAAW,iBAAiB,YAAY,aAAa,eAAe,IAAI;AAChH,MAAI,SAAS,OAAO;AAAA,IAClB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB;AAAA,EACtE,CAAC;AACD,MAAI,MAAM;AACR,UAAM,YAAY;AAClB,QAAI,eAAe,UAAU,KAAK,MAAM,WAAW,KAAK,KAAK,MAAM,OAAO,GAAG;AAC3E,YAAM,eAAe,SAAS,EAAE,QAAQ,EAAE,GAAG,KAAK,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,KAAK,MAAM,IAAI,GAAG,CAAC,EAAE,EAAE,CAAC;AACjH,eAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,aAAa,GAAG,SAAS,SAAS,CAAC;AAC3E,eAAS,8BAA8B,YAAY;AAAA,IACrD,OAAO;AACL,eAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,KAAK,GAAG,SAAS,SAAS,CAAC;AAAA,IACrE;AACA,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,MAAI,aAAa;AACf,UAAM,YAAY;AAClB,QAAI,eAAe,UAAU,gBAAgB,WAAW,uBAAuB,MAAM,WAAW,KAAK,uBAAuB,MAAM,OAAO,GAAG;AAC1I,YAAM,gBAAgB,SAAS;AAAA,QAC7B,QAAQ,EAAE,GAAG,uBAAuB;AAAA,QACpC,SAAS;AAAA,QACT,OAAO,EAAE,OAAO,CAAC,uBAAuB,MAAM,IAAI,GAAG,CAAC,EAAE;AAAA,MAC1D,CAAC;AACD,eAAS,iBAAiB,UAAU,QAAQ,aAAa,eAAe,cAAc;AACtF,eAAS,8BAA8B,aAAa;AAAA,IACtD,OAAO;AACL,eAAS,iBAAiB,UAAU,QAAQ,aAAa,wBAAwB,cAAc;AAAA,IACjG;AACA,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,SAAO;AACT;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,WAAW,iBAAiB,YAAY,aAAa,eAAe,IAAI;AAChH,MAAI,SAAS,sBAAsB;AAAA,IACjC,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB;AAAA,EACtE,CAAC;AACD,MAAI,MAAM;AACR,UAAM,YAAY;AAClB,aAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,KAAK,GAAG,SAAS,SAAS,CAAC;AACnE,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,MAAI,aAAa;AACf,UAAM,YAAY;AAClB,aAAS,iBAAiB,UAAU,QAAQ,aAAa,wBAAwB,cAAc;AAC/F,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,SAAO;AACT;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,QAAQ,QAAQ,IAAI;AAC5B,QAAM,aAAa,aAAa,cAAc,OAAO,KAAK;AAC1D,QAAM,eAAe,QAAQ;AAC7B,QAAM,YAAY,aAAa,aAAa,SAAS;AACrD,QAAM,CAAC,aAAa,WAAW,WAAWA,QAAO,IAAI,qBAAqB,mBAAmB,QAAQ,OAAO;AAC5G,MAAI,cAAc,GAAG;AACnB,WAAO,SAAS,eAAe,aAAa,OAAO,OAAO,CAAC,CAAC;AAAA,EAC9D;AACA,QAAM,cAAc,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACtD,QAAM,YAAY,SAAS,WAAW,MAAM;AAC5C,QAAM,SAAS,aAAa,aAAa,WAAW,OAAO,OAAO,WAAW,WAAW,WAAWA,UAAS,OAAO,OAAO,UAAU;AACpI,SAAO,SAAS,eAAe,aAAa,OAAO,OAAO,OAAO,MAAM;AACzE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAM,UAAU,IAAI;AAC5B,mBAAiB,CAAC,GAAG,OAAO,GAAG,UAAU;AACzC,QAAM,aAAa,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AAC9D,QAAM,cAAc,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACtD,QAAM,UAAU,EAAE,MAAM;AACxB,WAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,EAAE,IAAI;AAC9C,UAAMH,SAAQ,YAAY;AAC1B,iBAAa,OAAOA,UAAS,UAAU,KAAKA,UAAS,GAAG,MAAM,6BAA6BA,wBAAuB,UAAU,IAAI;AAAA,EAClI;AACA,MAAI,aAAa;AACjB,MAAI,aAAa,MAAM;AACrB,iBAAa;AAAA,EACf;AACA,QAAM,cAAc,aAAa,cAAc,QAAQ,KAAK;AAC5D,QAAM,YAAY,qBAAqB,aAAa,yBAAyB,GAAG,SAAS,YAAY,UAAU;AAC/G,QAAM,WAAW,SAAS;AAAA,IACxB,QAAQ,EAAE,EAAE;AAAA,IACZ,SAAS;AAAA,IACT,OAAO;AAAA,MACL,OAAO;AAAA,QACL,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,MACZ;AAAA,IACF;AAAA,EACF,CAAC;AACD,QAAM,eAAe,SAAS;AAAA,IAC5B,QAAQ,EAAE,GAAG,QAAQ;AAAA,IACrB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,UAAU,WAAW,cAAc,UAAU,SAAS,EAAE;AAAA,EAC3E,CAAC;AACD,QAAM,qBAAqB;AAAA,IACzB,UAAU;AAAA,IACV,UAAU;AAAA,IACV,cAAc,UAAU;AAAA,IACxB,UAAU;AAAA,EACZ;AACA,QAAM,aAAa,SAAS,WAAW,YAAY;AACnD,QAAM,OAAO,SAAS,WAAW,QAAQ;AACzC,QAAM,SAAS,aAAa,MAAM,YAAY,kBAAkB;AAChE,WAAS,8BAA8B,QAAQ;AAC/C,WAAS,8BAA8B,YAAY;AACnD,SAAO,SAAS,eAAe,UAAU,aAAa,OAAO,OAAO,OAAO,MAAM;AACnF;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAMiB,cAAY,aAAa,cAAc,OAAO,KAAK;AACzD,QAAM,qBAAqB,OAAO,MAAM,OAAO,MAAM,SAAS;AAC9D,QAAM,QAAQA,cAAY;AAC1B,QAAM,UAAU,SAAS;AAAA,IACvB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,OAAO,kBAAkB,EAAE;AAAA,EAC9C,CAAC;AACD,QAAM,SAAS,SAAS,SAAS,MAAM,QAAQ;AAC/C,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,OAAO,MAAM,EAAE,CAAC;AAC5G,WAAS,8BAA8B,OAAO;AAC9C,WAAS,8BAA8B,MAAM;AAC7C,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY,gBAAgB,UAAU,CAAC,OAAO,OAAO,SAAS,EAAE,IAAI,IAAI,GAAG,MAAM;AACrF,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO,KAAK,IAAI,EAAE,MAAM,WAAW,IAAI,GAAG,MAAM;AACrF,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO,OAAO,MAAM,EAAE,IAAI,IAAI,GAAG,MAAM;AAC5E,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,IAAI,IAAI;AAC7B,QAAM,UAAU,aAAa,OAAO,MAAM,GAAG;AAC7C,SAAO,SAAS,eAAe,CAAC,QAAQ,MAAM,GAAG,WAAW,OAAO;AACrE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO,KAAK,MAAM,EAAE,CAAC;AAC1D,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,6BAA6B,CAAC,GAAG,MAAM,KAAK,CAAC;AAClE,IAAI,cAAc,iBAAiB,YAAY,gBAAgB,MAAM,MAAM;AAC3E,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,gBAAgB,YAAY,CAAC,OAAO,KAAK,IAAI,GAAG,MAAM;AACxE,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,6BAA6B,CAAC,GAAG,MAAM,KAAK,CAAC;AACjE,IAAI,aAAa,iBAAiB,WAAW,eAAe,MAAM,MAAM;AACxE,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,IAAI,MAAM;AACjB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,aAAa,MAAM,OAAAJ,QAAO,KAAK,IAAI;AAC3C,mBAAiB,GAAG,KAAK;AACzB,QAAM,WAAW,EAAE,MAAM;AACzB,QAAM,OAAO,WAAW;AACxB,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAMtB,QAAO,aAAa,cAAc,EAAE,KAAK;AAC/C,QAAM,SAAS,IAAI,aAAaA,KAAI;AACpC,WAAS,kBAAkB,QAAQ;AACjC,UAAM,iBAAiB,SAAS;AAChC,QAAI,iBAAiB,SAAS,iBAAiB,KAAK,IAAI,GAAG,iBAAiB,WAAW;AACvF,UAAM,eAAe,SAAS,iBAAiB,KAAK,IAAI,iBAAiB,aAAa,IAAI;AAC1F,QAAI,OAAO;AACX,WAAO,kBAAkB,cAAc,kBAAkB;AACvD,YAAM,IAAI,QAAQ;AAClB,cAAQ,IAAI;AAAA,IACd;AACA,WAAO;AAAA,EACT;AACA,WAAS,SAAS,GAAG,SAASA,OAAM,UAAU;AAC5C,UAAM,OAAO,kBAAkB,MAAM;AACrC,UAAM,MAAM,QAAQ,UAAU,KAAK,IAAI,OAAOsB,SAAQ,MAAM,CAAC,IAAI;AACjE,WAAO,UAAU;AAAA,EACnB;AACA,SAAO,SAAS,eAAe,EAAE,OAAO,EAAE,OAAO,MAAM;AACzD;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,GAAG,IAAI;AACrB,QAAM,EAAE,aAAa,MAAM,OAAAA,QAAO,KAAK,IAAI;AAC3C,mBAAiB,IAAI,SAAS;AAC9B,QAAM,SAAS,aAAa,cAAc,GAAG,KAAK;AAClD,QAAM,WAAW,GAAG,MAAM;AAC1B,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAM,SAAS,IAAI,aAAa,MAAM;AACtC,QAAMtB,QAAO;AACb,WAAS,SAAS,GAAG,SAASA,OAAM,UAAU;AAC5C,UAAM,iBAAiB,SAAS;AAChC,UAAM,aAAa,SAAS,iBAAiB,KAAK,IAAI,GAAG,iBAAiB,WAAW;AACrF,UAAM,WAAW,SAAS,iBAAiB,KAAK,IAAI,UAAU,iBAAiB,cAAc,CAAC;AAC9F,QAAI,QAAQ;AACZ,aAAS,IAAI,YAAY,IAAI,UAAU,KAAK;AAC1C,eAAS,KAAK,IAAI,QAAQ,IAAI,CAAC;AAAA,IACjC;AACA,YAAQsB,SAAQ,QAAQ;AACxB,aAAS,IAAI,YAAY,IAAI,UAAU,KAAK;AAC1C,UAAI,MAAM,KAAKA,SAAQ,OAAO,QAAQ,KAAK,QAAQ,UAAU;AAC7D,UAAI,WAAW,GAAG;AAChB,eAAO,KAAK,IAAI,OAAO,CAAC,IAAI;AAAA,MAC9B;AACA,aAAO,SAAS;AAChB,aAAO,MAAM;AAAA,IACf;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,EAAE,OAAO,MAAM;AAC1D;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,kBAAkB,SAAS,IAAI;AACvC,QAAM,aAAa;AACnB,MAAI,SAAS,EAAE;AACf,QAAM,QAAQ,OAAO;AACrB,QAAM,WAAW,aAAa,eAAe,kBAAkB,MAAM;AACrE,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,QAAQ,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,MAAI,gBAAgB,MAAM;AACxB,UAAM,WAAW,IAAI,MAAM,KAAK;AAChC,aAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,eAAS,MAAM,OAAO,aAAa;AAAA,IACrC;AACA,YAAQ,cAAc,OAAO,QAAQ,EAAE,OAAO,cAAc,QAAQ;AACpE,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAC/D,aAAS;AAAA,EACX;AACA,mBAAiB,GAAG,KAAK;AACzB,uBAAqB,2BAA2B,OAAO,MAAM,KAAK;AAClE,QAAM,CAAC,aAAa,WAAW,IAAI,qBAAqB,0BAA0B,QAAQ,IAAI;AAC9F,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,SAAS,QAAQ,OAAO,YAAY,aAAa,EAAE,KAAK;AAC9D,QAAM,SAAS,WAAW,MAAM,QAAQ,aAAa,EAAE,KAAK;AAC5D,MAAI,WAAW;AACf,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,aAAa,QAAQ;AAChF,eAAW;AAAA,EACb;AACA,SAAO,EAAE,QAAQ,OAAO,UAAU,OAAO,EAAE,MAAM;AACnD;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,mBAAiB,GAAG,SAAS;AAC7B,QAAM,EAAE,YAAY,SAAAV,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY;AAClB,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,SAAS,GAAG,MAAM,wEAAwEA,2BAA0B,YAAY;AACjN,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,MAAI;AACJ,MAAI,SAAS,gBAAgB,KAAK,SAAS,iBAAiB,KAAK,aAAa,YAAY,SAAS,SAAS,SAAS,QAAQ,GAAG;AAC9H,UAAM,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACtD,OAAO;AACL,UAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,UAAMwB,YAAW,aAAa,eAAe,EAAE,KAAK;AACpD,UAAM,UAAU,MAAM,SAAS,EAAE,OAAO,EAAE,OAAOA,WAAU,UAAU,KAAK;AAC1E,UAAM,SAAS,eAAe,SAAS,UAAU,EAAE,OAAO,QAAQ,MAAM;AAAA,EAC1E;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAAxB,UAAS,KAAK,MAAM,iBAAiB,WAAW,IAAI;AACxE,mBAAiB,GAAG,WAAW;AAC/B,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,MAAM,iBAAiB,UAAU;AAC1H,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAM,SAAS,QAAQ,SAAS,EAAE,OAAO,EAAE,OAAO,aAAa,eAAe,EAAE,KAAK,GAAG,UAAU,KAAK;AACvG,SAAO,SAAS,eAAe,OAAO,OAAO,WAAW,OAAO,MAAM;AACvE;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,OAAO,IAAI;AAC9B,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,mBAAiB,CAAC,IAAI,MAAM,GAAG,eAAe;AAC9C,QAAM,WAAW,qBAAqB,kBAAkB,OAAO,OAAO,YAAYA,UAAS,GAAG,MAAM,eAAe;AACnH,QAAM,WAAW,SAAS,WAAW,MAAM;AAC3C,QAAM,YAAY,mBAAmB,UAAU,QAAQ;AACvD,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,uBAAuB,SAAS;AACtC,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,WAAW,uBAAuB,IAAI,SAAS,QAAQ;AAC7D,QAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,QAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,QAAM,KAAK,OAAO,OAAO,OAAO,SAAS;AACzC,QAAM,QAAQ,SAAS,WAAW,EAAE;AACpC,WAAS,QAAQ,GAAG,QAAQ,SAAS,WAAW,EAAE,OAAO;AACvD,aAAS,UAAU,GAAG,UAAU,SAAS,YAAY,EAAE,SAAS;AAC9D,eAAS,UAAU,GAAG,UAAU,SAAS,SAAS,EAAE,SAAS;AAC3D,iBAAS,QAAQ,GAAG,QAAQ,SAAS,UAAU,EAAE,OAAO;AACtD,mBAAS,QAAQ,GAAG,QAAQ,SAAS,SAAS,EAAE,OAAO;AACrD,kBAAM,gBAAgB,UAAU;AAChC,kBAAM,cAAc,QAAQ;AAC5B,kBAAM,cAAc,QAAQ;AAC5B,gBAAI,UAAU;AACd,qBAAS,SAAS,GAAG,SAAS,sBAAsB,UAAU,eAAe;AAC3E,oBAAM,WAAW,gBAAgB,UAAU;AAC3C,kBAAI,UAAU,KAAK,WAAW,SAAS,YAAY,KAAK,MAAM,OAAO,MAAM,SAAS;AAClF;AAAA,cACF;AACA,uBAAS,OAAO,GAAG,OAAO,uBAAuB,QAAQ,gBAAgB;AACvE,sBAAM,SAAS,cAAc,QAAQ;AACrC,oBAAI,QAAQ,KAAK,SAAS,SAAS,aAAa,KAAK,MAAM,KAAK,MAAM,OAAO;AAC3E;AAAA,gBACF;AACA,yBAAS,OAAO,GAAG,OAAO,sBAAsB,QAAQ,eAAe;AACrE,wBAAM,SAAS,cAAc,QAAQ;AACrC,sBAAI,QAAQ,KAAK,SAAS,SAAS,YAAY,KAAK,MAAM,KAAK,MAAM,OAAO;AAC1E;AAAA,kBACF;AACA,wBAAM,SAAS,uBAAuB,wBAAwB,uBAAuB,IAAI,UAAU,IAAI,OAAO,SAAS,OAAO,OAAO,OAAO;AAC5I,wBAAM,SAAS,SAAS,wBAAwB,uBAAuB,OAAO,uBAAuB;AACrG,wBAAMP,QAAO,WAAW,SAAS,IAAI;AACrC,sBAAIA,UAAS,GAAG;AACd;AAAA,kBACF;AACA,wBAAM,QAAQ,MAAM,IAAI,OAAO,SAAS,OAAO,OAAO,OAAO;AAC7D,6BAAW,QAAQA;AAAA,gBACrB;AAAA,cACF;AAAA,YACF;AACA,eAAG,IAAI,SAAS,OAAO,SAAS,OAAO,OAAO,OAAO;AAAA,UACvD;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,QAAQ,OAAO,IAAI;AACtC,QAAM,IAAI;AACV,mBAAiB,CAAC,QAAQ,MAAM,GAAG,aAAa;AAChD,QAAM,EAAE,YAAY,SAAAO,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,MAAM,eAAe;AAC9G,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAM,YAAY,OAAO,SAAS,UAAU,EAAE,OAAO,iBAAiB,SAAS,EAAE,OAAO,EAAE,OAAO,QAAQ,EAAE,MAAM;AACjH,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,QAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,QAAM,KAAK,OAAO,EAAE,OAAO,SAAS;AACpC,QAAM,SAAS,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC5C,QAAM,QAAQ,OAAO,GAAG,OAAO,WAAW,MAAM;AAChD,WAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,aAAS,IAAI,GAAG,IAAI,SAAS,YAAY,EAAE,GAAG;AAC5C,eAAS,MAAM,GAAG,MAAM,SAAS,UAAU,EAAE,KAAK;AAChD,iBAAS,MAAM,GAAG,MAAM,SAAS,SAAS,EAAE,KAAK;AAC/C,gBAAM,YAAY,MAAM;AACxB,gBAAM,YAAY,MAAM;AACxB,cAAI,UAAU;AACd,mBAAS,KAAK,GAAG,KAAK,uBAAuB,MAAM,gBAAgB;AACjE,kBAAM,OAAO,YAAY,MAAM;AAC/B,gBAAI,MAAM,KAAK,OAAO,SAAS,aAAa,KAAK,MAAM,GAAG,MAAM,KAAK;AACnE;AAAA,YACF;AACA,qBAAS,KAAK,GAAG,KAAK,sBAAsB,MAAM,eAAe;AAC/D,oBAAM,OAAO,YAAY,MAAM;AAC/B,kBAAI,MAAM,KAAK,OAAO,SAAS,YAAY,KAAK,MAAM,GAAG,MAAM,KAAK;AAClE;AAAA,cACF;AACA,oBAAM,SAAS,wBAAwB,uBAAuB,IAAI,UAAU,IAAI,GAAG,KAAK,KAAK,CAAC;AAC9F,oBAAM,SAAS,KAAK,uBAAuB;AAC3C,oBAAMP,QAAO,WAAW,SAAS,IAAI;AACrC,kBAAIA,UAAS,GAAG;AACd;AAAA,cACF;AACA,oBAAM,QAAQ,MAAM,IAAI,GAAG,KAAK,KAAK,CAAC;AACtC,yBAAW,QAAQA;AAAA,YACrB;AAAA,UACF;AACA,aAAG,IAAI,SAAS,GAAG,KAAK,KAAK,CAAC;AAAA,QAChC;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,sBAAsB,SAAS,QAAQ,OAAO,qBAAqB,UAAU;AACpF,QAAMO,WAAU,aAAa,eAAe,MAAM;AAClD,QAAM,WAAW,MAAM,SAAS,QAAQ,OAAOA,UAAS,UAAU,KAAK;AACvE,QAAM,eAAe,iBAAiB,SAAS,QAAQ,OAAO,UAAU,MAAM,mBAAmB;AACjG,SAAO,CAAC,SAAS,QAAQ,aAAa,MAAM;AAC9C;AAGA,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,oBAAoB,IAAI;AAChE,UAAM,aAAa;AACnB,qBAAiB,GAAG,mBAAmB;AACvC,UAAM,SAAS,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,CAAC,GAAG,CAAC,GAAG,IAAI;AAClG,UAAM,CAAC,QAAQ,OAAO,IAAI,sBAAsB,QAAQ,EAAE,OAAO,EAAE,OAAO,qBAAqB,QAAQ;AACvG,UAAM,eAAe,WAAW,MAAM,QAAQ,SAAS,UAAU,EAAE,KAAK;AACxE,UAAM,gBAAgB,WAAW,MAAM,SAAS,SAAS,UAAU,EAAE,KAAK;AAC1E,WAAO;AAAA,MACL,EAAE,QAAQ,cAAc,OAAO,SAAS,UAAU,OAAO,EAAE,MAAM;AAAA,MACjE,EAAE,QAAQ,eAAe,OAAO,SAAS,UAAU,OAAO,QAAQ;AAAA,IACpE;AAAA,EACF;AACF;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACtD,QAAM,SAAS,qBAAqB,0BAA0B,EAAE,OAAO,IAAI;AAC3E,QAAM,cAAc,OAAO;AAC3B,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,YAAY,CAAC;AACnB,QAAM,mBAAmB,SAAS,eAAe,CAAC,GAAG,WAAW,IAAI,aAAa,CAAC,UAAU,CAAC,CAAC;AAC9F,YAAU,KAAK,gBAAgB;AAC/B,QAAM,KAAK,MAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AAClF,YAAU,KAAK,EAAE;AACjB,QAAM,MAAM,KAAK,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,iBAAiB,GAAG,SAAS,SAAS,CAAC;AAC9E,YAAU,KAAK,GAAG;AAClB,QAAM,SAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,SAAS,EAAE,CAAC;AACxF,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,mBAAiB,GAAG,KAAK;AACzB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,EAAE,MAAM,MAAM;AAAA,EAC1E;AACA,uBAAqB,2BAA2B,OAAO,MAAM,GAAG,MAAM,MAAM;AAC5E,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,GAAG,OAAO,IAAI;AAC7F,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,OAAO,aAAa,oBAAoB,aAAa,cAAc,QAAQ,GAAG,GAAG,KAAK;AAC5F,QAAM,QAAQ,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC3C,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,SAAS,KAAK;AACpB,QAAI,OAAO,MAAM;AACjB,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,YAAM,QAAQ,MAAM,SAAS;AAC7B,UAAI,OAAO,MAAM,KAAK,KAAK,QAAQ,MAAM;AACvC,eAAO;AAAA,MACT;AAAA,IACF;AACA,SAAK,MAAM;AAAA,EACb;AACA,MAAI,gBAAgB,MAAM;AACxB,aAAS,8BAA8B,EAAE;AAAA,EAC3C;AACA,QAAM,SAAS,SAAS,eAAe,UAAU,GAAG,OAAO,IAAI;AAC/D,MAAI,UAAU;AACZ,UAAM,gBAAgB,qBAAqB,qBAAqB,UAAU,QAAQ;AAClF,UAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAC7G,aAAS,8BAA8B,MAAM;AAC7C,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,UAAU,KAAK,IAAI;AAC3B,mBAAiB,GAAG,WAAW;AAC/B,QAAM,WAAW,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,EAAE,MAAM,MAAM,GAAG,EAAE;AACrE,QAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE;AACxC,QAAM,MAAM,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,EAAE,MAAM,GAAG;AACxD,QAAM,SAAS,SAAS,YAAY,IAAI;AACxC,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,aAAa,eAAe,EAAE,KAAK;AACpD,QAAM,aAAa,aAAa,cAAc,QAAQ;AACtD,QAAM,aAAa,SAAS;AAC5B,QAAM,gBAAgB,aAAa,eAAe,QAAQ;AAC1D,QAAM,UAAU,aAAa,uBAAuB,EAAE,OAAO,UAAU;AACvE,WAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,QAAI,UAAU,aAAa,WAAW,IAAI,YAAY,aAAa;AACnE,aAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,UAAI,QAAQ,MAAM,MAAM,KAAK;AAC3B,gBAAQ,MAAM,MAAM,MAAM,IAAI,QAAQ,MAAM;AAAA,MAC9C,WAAW,QAAQ,OAAO,IAAI,KAAK;AACjC,gBAAQ,OAAO,IAAI,MAAM,KAAK,IAAI,QAAQ,MAAM;AAAA,MAClD;AAAA,IACF;AACA,cAAU,QAAQ,IAAI,CAAC,GAAG,OAAO,IAAI,MAAM,GAAG;AAC9C,UAAM,UAAU,aAAa,WAAW,SAAS,OAAO,QAAQ;AAChE,YAAQ,MAAM,MAAM;AAAA,EACtB;AACA,QAAM,QAAQ,SAAS,MAAM,SAAS,UAAU,EAAE,KAAK;AACvD,SAAO,EAAE,QAAQ,OAAO,OAAO,UAAU,OAAO,EAAE,MAAM;AAC1D;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU,6BAA6B,CAAC,QAAQ,WAAW;AAC7D,QAAM,MAAM,SAAS;AACrB,MAAI,SAAS,KAAK,SAAS,KAAK,UAAU,KAAK,UAAU,GAAG;AAC1D,WAAO;AAAA,EACT,OAAO;AACL,YAAQ,MAAM,UAAU;AAAA,EAC1B;AACF,CAAC;AACD,IAAI,OAAO,iBAAiB,KAAK,OAAO;AACxC,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,QAAQ,oBAAoB,CAAC;AAG/C,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,IAAI,IAAI;AAChB,QAAM,aAAa,OAAO,MAAM;AAChC,MAAI,OAAO;AACX,MAAI,SAAS,IAAI;AACf,WAAO,aAAa;AAAA,EACtB;AACA,MAAI,SAAS,aAAa,GAAG;AAC3B,UAAM,MAAM,4EAA4E,0BAA0B,MAAM;AAAA,EAC1H;AACA,QAAM,OAAO,aAAa,eAAe,CAAC,IAAI,GAAG,OAAO,KAAK;AAC7D,QAAM,WAAW,KAAK;AAAA,IACpB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,kBAAkB,MAAM,UAAU,MAAM;AAAA,EACnD,CAAC;AACD,QAAM,gBAAgB,qBAAqB,qBAAqB,SAAS,OAAO,IAAI;AACpF,QAAM,mBAAmB,SAAS,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AACjH,QAAM,IAAI,KAAK,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,iBAAiB,GAAG,SAAS,SAAS,CAAC;AAChF,QAAM,IAAI,KAAK,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,SAAS,CAAC;AACtD,QAAM,SAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,MAAM,UAAU,MAAM,EAAE,CAAC;AACnG,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAC1G,QAAM,SAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,YAAY,GAAG,SAAS,SAAS,CAAC;AAC3E,WAAS,8BAA8B,QAAQ;AAC/C,WAAS,8BAA8B,gBAAgB;AACvD,WAAS,8BAA8B,CAAC;AACxC,WAAS,8BAA8B,CAAC;AACxC,WAAS,8BAA8B,MAAM;AAC7C,WAAS,8BAA8B,WAAW;AAClD,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,YAAY,MAAM,WAAW,IAAI;AACzC,mBAAiB,QAAQ,aAAa;AACtC,QAAM,gBAAgB,aAAa,SAAS,SAAS,EAAE,QAAQ,EAAE,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,GAAG,EAAE,CAAC;AAClH,QAAM,YAAY,cAAc,MAAM;AACtC,QAAM,YAAY,cAAc,MAAM;AACtC,QAAM,WAAW,SAAS,KAAK,IAAI,cAAc,MAAM,EAAE;AACzD,QAAM,WAAW,CAAC,WAAW,UAAU;AACvC,QAAM,UAAU,aAAa,oBAAoB,aAAa,cAAc,QAAQ,GAAG,OAAO;AAC9F,WAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,UAAM,SAAS,IAAI;AACnB,UAAM,MAAM,IAAI,aAAa,YAAY,CAAC;AAC1C,QAAI,KAAK,SAAS;AAClB,aAAS,QAAQ,GAAG,QAAQ,IAAI,QAAQ,EAAE,OAAO;AAC/C,UAAI,SAAS,IAAI,QAAQ,KAAK,SAAS,SAAS;AAAA,IAClD;AACA,UAAM,SAAS,YAAY,KAAK,KAAK,SAAS,CAAC;AAC/C,UAAM,YAAY,IAAI;AACtB,aAAS,WAAW,GAAG,WAAW,YAAY,EAAE,UAAU;AACxD,YAAM,KAAK,OAAO;AAClB,cAAQ,YAAY,YAAY,IAAI;AACpC,eAAS,QAAQ,GAAG,QAAQ,IAAI,QAAQ,SAAS;AAC/C,YAAI,KAAK,IAAI,QAAQ;AACnB,kBAAQ,YAAY,YAAY;AAChC;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,MAAI,CAAC,YAAY;AACf,aAAS,8BAA8B,aAAa;AAAA,EACtD;AACA,SAAO,SAAS,eAAe,UAAU,SAAS,OAAO;AAC3D;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,qBAAqB;AACpD,SAAS,oBAAoB,MAAM;AACjC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,eAAe,IAAI;AACxD,mBAAiB,OAAO,mBAAmB;AAC3C,QAAM,YAAY,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AAClD,QAAM,aAAa,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACpD,QAAM,EAAE,gBAAgB,IAAI,yBAAyB,WAAW,YAAY,eAAe,cAAc,cAAc;AACvH,SAAO,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AACnG;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,qBAAqB;AACpD,SAAS,oBAAoB,MAAM;AACjC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,gBAAgB,mBAAmB,IAAI;AAC5E,mBAAiB,OAAO,yBAAyB;AACjD,QAAM,YAAY,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AAClD,QAAM,aAAa,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACpD,QAAM,EAAE,iBAAiB,aAAa,IAAI,yBAAyB,WAAW,YAAY,eAAe,cAAc,gBAAgB,kBAAkB;AACzJ,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AAAA,IAC1F,SAAS,eAAe,CAAC,GAAG,SAAS,IAAI,WAAW,CAAC,YAAY,CAAC,CAAC;AAAA,EACrE;AACF;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,qBAAqB;AACpD,SAAS,oBAAoB,MAAM;AACjC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,gBAAgB,aAAa,IAAI;AACtE,mBAAiB,OAAO,4BAA4B;AACpD,QAAM,YAAY,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AAClD,QAAM,aAAa,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACpD,QAAM,mBAAmB;AACzB,QAAM,kBAAkB;AACxB,QAAM,oBAAoB;AAC1B,QAAM,kBAAkB;AACxB,QAAM,EAAE,iBAAiB,eAAe,IAAI,yBAAyB,WAAW,YAAY,kBAAkB,iBAAiB,mBAAmB,eAAe;AACjK,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AAAA,IAC1F,SAAS,eAAe,CAAC,eAAe,MAAM,GAAG,WAAW,IAAI,aAAa,cAAc,CAAC;AAAA,EAC9F;AACF;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,IAAI;AACpB,QAAM,EAAE,OAAO,SAAS,SAAS,IAAI;AACrC,mBAAiB,SAAS,QAAQ;AAClC,QAAM,cAAc,aAAa,cAAc,QAAQ,KAAK;AAC5D,QAAM,MAAM,IAAI,aAAa,cAAc,KAAK;AAChD,MAAI,KAAK,QAAQ;AACjB,QAAM,aAAa,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACrD,WAAS,QAAQ,GAAG,QAAQ,aAAa,EAAE,OAAO;AAChD,QAAI,WAAW,UAAU,KAAK,WAAW,SAAS,OAAO;AACvD,UAAI,QAAQ,QAAQ,WAAW,UAAU;AAAA,IAC3C;AAAA,EACF;AACA,SAAO,SAAS,eAAe,CAAC,GAAG,QAAQ,OAAO,KAAK,GAAG,SAAS,GAAG;AACxE;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,EAAE,UAAU,UAAU;AACxB,UAAM,IAAI,MAAM,+CAA+C;AAAA,EACjE,WAAW,EAAE,UAAU,aAAa;AAClC,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,IAAI,MAAM,GAAG,GAAG,SAAS,SAAS,CAAC;AAC7E,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,WAAO;AAAA,EACT,OAAO;AACL,WAAO,MAAM,EAAE,SAAS,UAAU,OAAO,EAAE,OAAO,EAAE,OAAO,OAAO,GAAG,OAAO,EAAE,MAAM,EAAE,CAAC;AAAA,EACzF;AACF;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,EAAE,UAAU,UAAU;AACxB,UAAM,IAAI,MAAM,8CAA8C;AAAA,EAChE,WAAW,EAAE,UAAU,aAAa;AAClC,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,UAAU,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACnE,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,IAAI,MAAM,GAAG,GAAG,SAAS,SAAS,CAAC;AAC7E,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,WAAO;AAAA,EACT,OAAO;AACL,WAAO,MAAM,EAAE,SAAS,UAAU,OAAO,EAAE,OAAO,EAAE,OAAO,OAAO,GAAG,OAAO,EAAE,MAAM,EAAE,CAAC;AAAA,EACzF;AACF;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,YAAY,EAAE,QAAQ,EAAE,OAAO,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAAA,EAC9F;AACA,QAAM,QAAQ,OAAO,GAAG;AACxB,QAAM,QAAQ,OAAO,GAAG;AACxB,SAAO,QAAQ,CAAC,OAAO;AACrB,iBAAa,kBAAkB,OAAO,GAAG,OAAO,uDAAuD;AACvG,iBAAa,OAAO,UAAU,GAAG,OAAO,MAAM,uDAAuD;AAAA,EACvG,CAAC;AACD,QAAM,0BAA0B,CAAC;AACjC,QAAM,kBAAkB,OAAO,IAAI,CAAC,OAAO;AACzC,UAAM,YAAY,YAAY,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAChG,4BAAwB,KAAK,SAAS;AACtC,WAAO;AAAA,EACT,CAAC;AACD,QAAM,SAAS,QAAQ,EAAE,QAAQ,iBAAiB,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AACtF,0BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,UAAU,cAAc,IAAI;AACpC,mBAAiB,GAAG,KAAK;AACzB,QAAM,WAAW,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,EAAE,MAAM,MAAM,GAAG,EAAE;AACrE,QAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE;AACxC,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,aAAa,eAAe,EAAE,KAAK;AACpD,QAAM,aAAa,aAAa,cAAc,QAAQ;AACtD,QAAM,aAAa,SAAS;AAC5B,QAAM,gBAAgB,aAAa,eAAe,QAAQ;AAC1D,QAAM,UAAU,aAAa,uBAAuB,EAAE,OAAO,UAAU;AACvE,MAAI,kBAAkB,GAAG;AACvB,YAAQ,KAAK,aAAa;AAAA,EAC5B;AACA,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM;AACjC,UAAM,UAAU,aAAa,WAAW,IAAI,OAAO,QAAQ;AAC3D,UAAM,YAAY,QAAQ,IAAI,CAAC,GAAG,OAAO,IAAI,MAAM,GAAG;AACtD,UAAM,WAAW,aAAa,WAAW,WAAW,YAAY,aAAa;AAC7E,YAAQ,YAAY,MAAM;AAAA,EAC5B;AACA,QAAM,QAAQ,SAAS,MAAM,SAAS,UAAU,EAAE,KAAK;AACvD,SAAO,EAAE,QAAQ,OAAO,OAAO,UAAU,OAAO,EAAE,MAAM;AAC1D;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU,6BAA6B,CAAC,GAAG,MAAM,KAAK,IAAI,GAAG,CAAC,CAAC;AACnE,IAAI,OAAO,iBAAiB,KAAK,OAAO;AACxC,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,OAAO,MAAM,MAAM,IAAI;AAC5C,QAAM,SAAS,UAAU,OAAO,MAAM,OAAO,KAAK;AAClD,SAAO,SAAS,eAAe,CAAC,OAAO,MAAM,GAAG,OAAO,MAAM;AAC/D;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,gBAAgB,YAAY,CAAC,OAAO,IAAI,EAAE;AAC5D,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,kBAAkB,MAAAZ,MAAK,IAAI;AACjD,mBAAiB,QAAQ,gBAAgB;AACzC,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,CAAC,OAAO,WAAW,UAAU,WAAW,IAAI,OAAO;AACzD,QAAM,UAAU,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACjD,QAAM,SAAS,IAAI,aAAa,aAAa,cAAc,CAAC,OAAO,WAAW,UAAU,WAAW,CAAC,CAAC;AACrG,QAAM,qBAAqB;AAAA,IACzB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,IAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,EAChD;AACA,QAAM,sBAAsB;AAAA,IAC1B,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,IAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,EAChD;AACA,MAAI,YAAY;AAChB,QAAM,wBAAwB,mBAAmB,KAAK,oBAAoB;AAC1E,QAAM,wBAAwB,mBAAmB,KAAK,oBAAoB;AAC1E,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,aAAS,KAAK,GAAG,KAAK,WAAW,MAAM;AACrC,UAAI;AACJ,UAAI,kBAAkB;AACpB,wBAAgB,yBAAyB,KAAK,OAAO;AAAA,MACvD,OAAO;AACL,wBAAgB,wBAAwB;AAAA,MAC1C;AACA,YAAM,iBAAiB,KAAK,IAAI,GAAG,KAAK,MAAM,aAAa,CAAC;AAC5D,YAAM,UAAU,gBAAgB;AAChC,YAAM,gBAAgB,KAAK,IAAI,YAAY,GAAG,KAAK,KAAK,aAAa,CAAC;AACtE,YAAM,eAAe,IAAI,cAAc,KAAK,iBAAiB,cAAc;AAC3E,YAAM,eAAe,IAAI,cAAc,KAAK,gBAAgB,cAAc;AAC1E,eAAS,IAAI,GAAG,IAAI,UAAU,KAAK;AACjC,YAAI;AACJ,YAAI,kBAAkB;AACpB,0BAAgB,yBAAyB,IAAI,OAAO;AAAA,QACtD,OAAO;AACL,0BAAgB,wBAAwB;AAAA,QAC1C;AACA,cAAM,iBAAiB,KAAK,IAAI,GAAG,KAAK,MAAM,aAAa,CAAC;AAC5D,cAAM,UAAU,gBAAgB;AAChC,cAAM,gBAAgB,KAAK,IAAI,WAAW,GAAG,KAAK,KAAK,aAAa,CAAC;AACrE,cAAM,gBAAgB,eAAe,iBAAiB,cAAc;AACpE,cAAM,gBAAgB,eAAe,iBAAiB,cAAc;AACpE,cAAM,iBAAiB,eAAe,gBAAgB,cAAc;AACpE,cAAM,iBAAiB,eAAe,gBAAgB,cAAc;AACpE,iBAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,gBAAM,UAAU,QAAQ,gBAAgB;AACxC,gBAAM,aAAa,QAAQ,gBAAgB;AAC3C,gBAAM,WAAW,QAAQ,iBAAiB;AAC1C,gBAAM,cAAc,QAAQ,iBAAiB;AAC7C,gBAAM,MAAM,WAAW,WAAW,WAAW;AAC7C,gBAAM,SAAS,cAAc,cAAc,cAAc;AACzD,gBAAM,WAAW,OAAO,SAAS,OAAO;AACxC,iBAAO,eAAe;AAAA,QACxB;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,CAAC,OAAO,WAAW,UAAU,WAAW,GAAG,WAAW,MAAM;AAC7F;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,mBAAmB,MAAM;AAChC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,GAAG,IAAI;AACvB,QAAM,EAAE,aAAa,IAAI;AACzB,mBAAiB,CAAC,IAAI,MAAM,GAAG,oBAAoB;AACnD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,CAAC,OAAO,SAAS,QAAQ,KAAK,IAAI,OAAO;AAC/C,QAAM,CAAC,EAAE,SAAS,MAAM,IAAI,GAAG;AAC/B,QAAM,SAAS,IAAI,aAAa,QAAQ,UAAU,SAAS,KAAK;AAChE,QAAM,iBAAiB;AAAA,IACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,IAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,EAC5C;AACA,QAAM,iBAAiB;AAAA,IACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,IAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,EAC5C;AACA,QAAM,cAAc,eAAe,KAAK,eAAe;AACvD,QAAM,aAAa,eAAe,KAAK,eAAe;AACtD,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,MAAI,SAAS;AACb,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,UAAM,UAAU,IAAI,cAAc;AAClC,aAAS,KAAK,GAAG,KAAK,SAAS,MAAM;AACnC,YAAM,MAAM,KAAK;AACjB,YAAM,cAAc,KAAK,MAAM,GAAG;AAClC,YAAM,iBAAiB,KAAK,IAAI,KAAK,KAAK,GAAG,GAAG,UAAU,CAAC;AAC3D,YAAM,eAAe,UAAU,cAAc,cAAc;AAC3D,YAAM,kBAAkB,UAAU,iBAAiB,cAAc;AACjE,YAAM,UAAU,MAAM;AACtB,YAAM,iBAAiB,IAAI;AAC3B,eAAS,IAAI,GAAG,IAAI,QAAQ,KAAK;AAC/B,cAAM,MAAM,IAAI;AAChB,cAAM,eAAe,KAAK,MAAM,GAAG;AACnC,cAAM,gBAAgB,KAAK,IAAI,KAAK,KAAK,GAAG,GAAG,SAAS,CAAC;AACzD,cAAM,UAAU,MAAM;AACtB,cAAM,iBAAiB,IAAI;AAC3B,cAAM,kBAAkB,eAAe,eAAe,cAAc;AACpE,cAAM,mBAAmB,eAAe,gBAAgB,cAAc;AACtE,cAAM,qBAAqB,kBAAkB,eAAe,cAAc;AAC1E,cAAM,sBAAsB,kBAAkB,gBAAgB,cAAc;AAC5E,cAAM,oCAAoC,iBAAiB;AAC3D,cAAM,6BAA6B,iBAAiB;AACpD,cAAM,6BAA6B,UAAU;AAC7C,cAAM,sBAAsB,UAAU;AACtC,iBAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,gBAAM,QAAQ,SAAS;AACvB,iBAAO,kBAAkB,MAAM,QAAQ;AACvC,iBAAO,mBAAmB,MAAM,QAAQ;AACxC,iBAAO,qBAAqB,MAAM,QAAQ;AAC1C,iBAAO,sBAAsB,MAAM,QAAQ;AAAA,QAC7C;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,CAAC,OAAO,QAAQ,SAAS,KAAK,GAAG,WAAW,MAAM;AACnF;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,uBAAuB,MAAM;AACpC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,kBAAkB,MAAAA,MAAK,IAAI;AACjD,mBAAiB,QAAQ,uBAAuB;AAChD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,CAAC,OAAO,WAAW,UAAU,WAAW,IAAI,OAAO;AACzD,QAAM,UAAU,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACjD,QAAM,SAAS,IAAI,aAAa,QAAQ,YAAY,WAAW,WAAW;AAC1E,QAAM,qBAAqB;AAAA,IACzB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,IAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,EAChD;AACA,QAAM,sBAAsB;AAAA,IAC1B,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,IAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,EAChD;AACA,QAAM,wBAAwB,mBAAmB,KAAK,oBAAoB;AAC1E,QAAM,wBAAwB,mBAAmB,KAAK,oBAAoB;AAC1E,MAAI,eAAe;AACnB,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,UAAM,cAAc,IAAI,cAAc;AACtC,aAAS,KAAK,GAAG,KAAK,WAAW,MAAM;AACrC,YAAM,gBAAgB,mBAAmB,yBAAyB,KAAK,OAAO,wBAAwB;AACtG,UAAI,mBAAmB,KAAK,IAAI,YAAY,GAAG,eAAe,KAAK,MAAM,aAAa,IAAI,KAAK,MAAM,aAAa,CAAC;AACnH,UAAI,kBAAkB;AACpB,2BAAmB,KAAK,IAAI,GAAG,gBAAgB;AAAA,MACjD;AACA,YAAM,YAAY,cAAc,mBAAmB,cAAc;AACjE,eAAS,IAAI,GAAG,IAAI,UAAU,KAAK;AACjC,cAAM,gBAAgB,mBAAmB,yBAAyB,IAAI,OAAO,wBAAwB;AACrG,YAAI,mBAAmB,KAAK,IAAI,WAAW,GAAG,eAAe,KAAK,MAAM,aAAa,IAAI,KAAK,MAAM,aAAa,CAAC;AAClH,YAAI,kBAAkB;AACpB,6BAAmB,KAAK,IAAI,GAAG,gBAAgB;AAAA,QACjD;AACA,cAAM,YAAY,YAAY,mBAAmB,cAAc;AAC/D,iBAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,gBAAM,SAAS,QAAQ,YAAY;AACnC,iBAAO,kBAAkB;AAAA,QAC3B;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,CAAC,OAAO,WAAW,UAAU,WAAW,GAAG,OAAO,OAAO,MAAM;AAChG;AACA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,0BAA0B,MAAM;AACvC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,GAAG,IAAI;AACvB,QAAM,EAAE,aAAa,IAAI;AACzB,mBAAiB,CAAC,IAAI,MAAM,GAAG,2BAA2B;AAC1D,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,YAAY,aAAa,eAAe,GAAG,KAAK;AACtD,QAAM,CAAC,OAAO,SAAS,QAAQ,KAAK,IAAI,OAAO;AAC/C,QAAM,CAAC,EAAE,SAAS,MAAM,IAAI,GAAG;AAC/B,QAAM,SAAS,IAAI,aAAa,QAAQ,UAAU,SAAS,KAAK;AAChE,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,iBAAiB;AAAA,IACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,IAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,EAC5C;AACA,QAAM,iBAAiB;AAAA,IACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,IAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,EAC5C;AACA,QAAM,cAAc,eAAe,KAAK,eAAe;AACvD,QAAM,aAAa,eAAe,KAAK,eAAe;AACtD,QAAM,iBAAiB,IAAI;AAC3B,QAAM,gBAAgB,IAAI;AAC1B,QAAM,YAAY,KAAK,KAAK,cAAc,IAAI,IAAI;AAClD,QAAM,WAAW,KAAK,KAAK,aAAa,IAAI,IAAI;AAChD,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,UAAM,cAAc,IAAI,cAAc;AACtC,aAAS,KAAK,GAAG,KAAK,SAAS,MAAM;AACnC,YAAM,YAAY,cAAc,KAAK,cAAc;AACnD,YAAM,aAAa,KAAK,MAAM,KAAK,cAAc;AACjD,YAAM,WAAW,KAAK,MAAM,aAAa,YAAY,CAAC;AACtD,eAAS,IAAI,GAAG,IAAI,QAAQ,KAAK;AAC/B,cAAM,YAAY,YAAY,IAAI,cAAc;AAChD,cAAM,aAAa,KAAK,MAAM,IAAI,aAAa;AAC/C,cAAM,WAAW,KAAK,MAAM,aAAa,WAAW,CAAC;AACrD,iBAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,cAAI,QAAQ;AACZ,mBAAS,WAAW,GAAG,WAAW,WAAW,YAAY;AACvD,kBAAM,MAAM,WAAW;AACvB,gBAAI,MAAM,KAAK,OAAO,SAAS;AAC7B;AAAA,YACF;AACA,kBAAM,YAAY,cAAc,MAAM,UAAU;AAChD,kBAAM,gBAAgB,MAAM;AAC5B,kBAAM,mBAAmB,KAAK,IAAI,UAAU,GAAG,eAAe,KAAK,MAAM,aAAa,IAAI,KAAK,MAAM,aAAa,CAAC;AACnH,gBAAI,OAAO,kBAAkB;AAC3B;AAAA,YACF;AACA,qBAAS,WAAW,GAAG,WAAW,UAAU,YAAY;AACtD,oBAAM,MAAM,WAAW;AACvB,kBAAI,MAAM,KAAK,OAAO,QAAQ;AAC5B;AAAA,cACF;AACA,oBAAM,YAAY,YAAY,MAAM,UAAU;AAC9C,oBAAM,gBAAgB,MAAM;AAC5B,oBAAM,mBAAmB,KAAK,IAAI,SAAS,GAAG,eAAe,KAAK,MAAM,aAAa,IAAI,KAAK,MAAM,aAAa,CAAC;AAClH,kBAAI,MAAM,kBAAkB;AAC1B,yBAAS,SAAS,YAAY;AAAA,cAChC;AAAA,YACF;AAAA,UACF;AACA,iBAAO,YAAY,KAAK;AAAA,QAC1B;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,MAAM;AACnE;AACA,IAAI,mCAAmC;AAAA,EACrC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,mBAAiB,GAAG,SAAS;AAC7B,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,aAAa,eAAe,MAAM,EAAE,KAAK;AACvD,MAAI,UAAU,GAAG;AACf,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD;AACA,QAAM,SAAS,IAAI,aAAa,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,OAAO,SAAS,WAAW,CAAC;AAClC,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM,MAAM;AACvC,UAAM,SAAS,OAAO,WAAW,EAAE;AACnC,UAAM,QAAQ,OAAO,MAAM;AAC3B,UAAM,QAAQ,CAAC,MAAM,MAAM,KAAK,EAAE,MAAM,KAAK,IAAI,MAAM,EAAE;AACzD,WAAO,IAAI,KAAK,IAAI,GAAG,KAAK,GAAG,GAAG,MAAM;AAAA,EAC1C;AACA,SAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC1E;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,yBAAyB;AAAA,EAC3B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,UAAM,EAAE,SAAS,WAAW,OAAO,IAAI;AACvC,UAAM,aAAa;AACnB,UAAM,SAAS,aAAa,uBAAuB,OAAO,OAAO,aAAa,cAAc,OAAO,KAAK,CAAC;AACzG,UAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,UAAM,CAAC,SAAS,OAAO,IAAI,qBAAqB,eAAe,QAAQ,aAAa,UAAU;AAC9F,UAAM,mBAAmB;AACzB,UAAM,YAAY,KAAK,IAAI,OAAO;AAClC,UAAM,YAAY,KAAK,IAAI,OAAO;AAClC,UAAM,YAAY,WAAW,KAAK,IAAI,OAAO,MAAM,EAAE;AACrD,aAAS,WAAW,GAAG,WAAW,OAAO,YAAY;AACnD,YAAM,cAAc,WAAW,aAAa,cAAc;AAC1D,eAAS,MAAM,GAAG,MAAM,aAAa,OAAO;AAC1C,cAAM,YAAY,OAAO,aAAa;AACtC,iBAAS,MAAM,GAAG,MAAM,YAAY,OAAO;AACzC,gBAAM,YAAY,MAAM;AACxB,mBAAS,UAAU,GAAG,UAAU,aAAa,WAAW;AACtD,kBAAM,UAAU,CAAC,OAAO,KAAK,KAAK,OAAO;AACzC,kBAAM,IAAI,QAAQ;AAClB,kBAAM,IAAI,QAAQ;AAClB,gBAAI,UAAU,IAAI,WAAW,aAAa,IAAI,WAAW;AACzD,gBAAI,UAAU,IAAI,WAAW,aAAa,IAAI,WAAW;AACzD,qBAAS,KAAK,MAAM,SAAS,OAAO;AACpC,qBAAS,KAAK,MAAM,SAAS,OAAO;AACpC,gBAAI,cAAc;AAClB,gBAAI,OAAO,cAAc,UAAU;AACjC,kBAAI,YAAY,GAAG;AACjB,8BAAc;AAAA,cAChB,OAAO;AACL,8BAAc,UAAU;AAAA,cAC1B;AAAA,YACF;AACA,gBAAI,UAAU,KAAK,SAAS,cAAc,UAAU,KAAK,SAAS,aAAa;AAC7E,oBAAM,mBAAmB,UAAU,aAAa;AAChD,oBAAM,mBAAmB,SAAS;AAClC,oBAAM,WAAW,cAAc,mBAAmB,mBAAmB;AACrE,4BAAc,UAAU;AAAA,YAC1B;AACA,kBAAM,SAAS,cAAc,YAAY,YAAY;AACrD,mBAAO,UAAU;AAAA,UACnB;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,SAAS,WAAW,MAAM,QAAQ,OAAO,OAAO,OAAO,KAAK;AAClE,WAAO,EAAE,QAAQ,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAAA,EAC5D;AACF;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO;AAC1C,QAAM,OAAO,KAAK,MAAM,EAAE;AAC1B,MAAI,KAAK,OAAO,KAAK;AACnB,WAAO,KAAK,MAAM,EAAE;AAAA,EACtB,WAAW,KAAK,OAAO,KAAK;AAC1B,WAAO,KAAK,KAAK,EAAE;AAAA,EACrB,OAAO;AACL,QAAI,OAAO,MAAM,GAAG;AAClB,aAAO;AAAA,IACT,OAAO;AACL,aAAO,OAAO;AAAA,IAChB;AAAA,EACF;AACF,CAAC;AACD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,SAAS,QAAQ,IAAI;AAC7B,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,EAAE,WAAW,YAAY,WAAW,SAAAY,UAAS,YAAAQ,YAAW,IAAI,qBAAqB,gBAAgB,SAAS,SAAS,KAAK;AAC9H,QAAM,iBAAiB;AACvB,QAAM,aAAa,SAAS,WAAW,OAAO;AAC9C,QAAM,aAAa,SAAS,WAAW,OAAO;AAC9C,QAAM,SAAS,YAAY,YAAY,YAAY,OAAOA,aAAY,WAAW,YAAY,WAAWR,UAAS,GAAG,cAAc;AAClI,SAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,MAAM;AACnE;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,QAAQ,OAAO;AAClC,MAAI,OAAO;AACX,MAAI,QAAQ,OAAO;AACnB,MAAI,MAAM;AACV,SAAO,OAAO,OAAO;AACnB,UAAM,KAAK,OAAO,OAAO,SAAS,CAAC;AACnC,QAAI,OAAO,OAAO,OAAO;AACvB,aAAO,MAAM;AAAA,IACf,OAAO;AACL,cAAQ;AAAA,IACV;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,YAAY,QAAQ,OAAO;AAClC,MAAI,OAAO;AACX,MAAI,QAAQ,OAAO;AACnB,MAAI,MAAM;AACV,SAAO,OAAO,OAAO;AACnB,UAAM,KAAK,OAAO,OAAO,SAAS,CAAC;AACnC,QAAI,OAAO,QAAQ,OAAO;AACxB,aAAO,MAAM;AAAA,IACf,OAAO;AACL,cAAQ;AAAA,IACV;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,cAAc,QAAQ,WAAW,WAAW,WAAW,MAAM;AACrF,QAAM,SAAS,aAAa,kBAAkB,SAAS,YAAY,SAAS;AAC5E,WAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,UAAM,oBAAoB,aAAa,MAAM,IAAI,YAAY,IAAI,KAAK,SAAS;AAC/E,UAAM,eAAe,IAAI;AACzB,aAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,aAAO,eAAe,MAAM,SAAS,SAAS,YAAY,mBAAmB,OAAO,KAAK,aAAa,IAAI,YAAY,mBAAmB,OAAO,KAAK,aAAa;AAAA,IACpK;AAAA,EACF;AACA,SAAO;AACT;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,gBAAgB,OAAO,IAAI;AACnC,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,kBAAkB,SAAS,KAAK,IAAI,eAAe,MAAM,EAAE;AACjE,QAAM,UAAU,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACjD,QAAM,SAAS,iBAAiB,iBAAiB,SAAS,eAAe,MAAM,IAAI,eAAe,MAAM,IAAI,OAAO,MAAM,IAAI,IAAI;AACjI,SAAO,SAAS,eAAe,OAAO,OAAO,SAAS,MAAM;AAC9D;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,WAAW,GAAG,IAAI,GAAG,GAAG,IAAI;AACpC,mBAAiB,CAAC,WAAW,IAAI,EAAE,GAAG,QAAQ;AAC9C,QAAM,gBAAgB,UAAU,MAAM;AACtC,QAAM,SAAS,SAAS,KAAK,IAAI,UAAU,MAAM,EAAE;AACnD,QAAM,UAAU,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC7C,QAAM,UAAU,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC7C,QAAM,cAAc,WAAW,GAAG,OAAO,GAAG,KAAK;AACjD,QAAM,YAAY,aAAa,oBAAoB,aAAa,cAAc,GAAG,KAAK,GAAG,WAAW;AACpG,MAAIH,SAAQ;AACZ,QAAM,SAAS,kBAAkB,KAAK,gBAAgB,KAAK,GAAG,MAAM,WAAW,IAAI,IAAI,aAAa,cAAc,GAAG,MAAM,MAAM,CAAC,CAAC;AACnI,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,aAAS,IAAI,GAAG,IAAI,QAAQ,KAAK;AAC/B,UAAI,OAAO,QAAQ,GAAG;AACpB,kBAAUA,YAAW,QAAQ;AAAA,MAC/B,OAAO;AACL,kBAAUA,YAAW,QAAQ;AAAA,MAC/B;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,aAAa,SAAS;AACjE;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa,qBAAqB;AACtC,IAAI,QAAQ,qBAAqB;AACjC,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO;AACxC,MAAI,MAAM,GAAG;AACX,WAAO,QAAQ;AAAA,EACjB,OAAO;AACL,WAAO,cAAc,KAAK,IAAI,EAAE,IAAI;AAAA,EACtC;AACF,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO;AACxC,MAAI,KAAK,GAAG;AACV,WAAO;AAAA,EACT,WAAW,KAAK,GAAG;AACjB,WAAO;AAAA,EACT,OAAO;AACL,WAAO;AAAA,EACT;AACF,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,gBAAgB,KAAK,CAAC,OAAO,KAAK,IAAI,EAAE,CAAC;AACpD,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW;AACf,IAAI,aAAa,KAAK,IAAI,QAAQ,IAAI;AACtC,IAAI,YAAY,gBAAgB,UAAU,CAAC,OAAO;AAChD,QAAM,WAAW,KAAK,CAAC;AACvB,QAAM,WAAW,KAAK;AACtB,QAAM,OAAO,KAAK,IAAI,EAAE;AACxB,MAAI;AACJ,MAAI,UAAU;AACZ,aAAS;AAAA,EACX,WAAW,UAAU;AACnB,aAAS;AAAA,EACX,OAAO;AACL,aAAS,KAAK,IAAI,IAAI,IAAI;AAAA,EAC5B;AACA,SAAO;AACT,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAS,IAAI;AACjC,mBAAiB,CAAC,CAAC,GAAG,gBAAgB;AACtC,QAAM,QAAQ,aAAa,cAAc,UAAU;AACnD,QAAM,mBAAmB,CAAC,CAAC,GAAG,CAAC,CAAC;AAChC,mBAAiB,KAAK,GAAG,QAAQ;AACjC,WAAS,KAAK,IAAI,WAAW,QAAQ,KAAK,EAAE,MAAM,QAAQ,EAAE,IAAI;AAC9D,qBAAiB,KAAK,CAAC,GAAG,CAAC,CAAC;AAAA,EAC9B;AACA,QAAM,UAAU,YAAY,WAAW;AAAA,IACrC,QAAQ,EAAE,EAAE;AAAA,IACZ,SAAS;AAAA,IACT,OAAO,EAAE,UAAU,kBAAkB,eAAe,EAAE;AAAA,EACxD,CAAC;AACD,QAAM,sBAAsB,qBAAqB,YAAY,QAAQ,OAAO,YAAY,OAAO,KAAK;AACpG,QAAM,oCAAoC,qBAAqB,YAAY,oBAAoB,QAAQ,WAAW,QAAQ,KAAK;AAC/H,QAAM,eAAe,qBAAqB,oBAAoB,QAAQ,OAAO,YAAY,OAAO,KAAK;AACrG,QAAM,gBAAgB,EAAE,GAAG,QAAQ;AACnC,QAAM,eAAe,EAAE,OAAO,oBAAoB;AAClD,QAAM,kBAAkB,SAAS,EAAE,QAAQ,eAAe,SAAS,UAAU,OAAO,aAAa,CAAC;AAClG,QAAM,kBAAkB,EAAE,GAAG,gBAAgB;AAC7C,QAAM,iBAAiB,EAAE,MAAM,kCAAkC;AACjE,QAAM,WAAW,WAAW,EAAE,QAAQ,iBAAiB,SAAS,UAAU,OAAO,eAAe,CAAC;AACjG,QAAM,sBAAsB,EAAE,GAAG,SAAS;AAC1C,QAAM,qBAAqB,EAAE,OAAO,aAAa;AACjD,QAAM,SAAS,SAAS,EAAE,QAAQ,qBAAqB,SAAS,UAAU,OAAO,mBAAmB,CAAC;AACrG,WAAS,8BAA8B,OAAO;AAC9C,WAAS,8BAA8B,eAAe;AACtD,WAAS,8BAA8B,QAAQ;AAC/C,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,SAAS,QAAQ,YAAY,aAAa,IAAI;AACtD,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,UACV,WAAW,OAAO;AAAA,EAC1B;AACA,MAAI,QAAQ,MAAM,WAAW,GAAG;AAC9B,UAAM,IAAI,MAAM;AAAA,UACV,QAAQ,OAAO;AAAA,EACvB;AACA,MAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,UAAM,IAAI,MAAM;AAAA,UACV,OAAO,OAAO;AAAA,EACtB;AACA,MAAI,aAAa,MAAM,WAAW,GAAG;AACnC,UAAM,IAAI,MAAM;AAAA,UACV,aAAa,OAAO;AAAA,EAC5B;AACA,QAAM,WAAW,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACnD,QAAM,UAAU,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACjD,QAAM,cAAc,SAAS,KAAK,IAAI,WAAW,MAAM,EAAE;AACzD,QAAM,gBAAgB,SAAS,KAAK,IAAI,aAAa,MAAM,EAAE,OAAO;AACpE,QAAM,CAAC,eAAe,oBAAoB,cAAc,mBAAmB,eAAe,IAAI,wBAAwB,UAAU,QAAQ,OAAO,QAAQ,OAAO,SAAS,OAAO,OAAO,aAAa,aAAa;AAC/M,SAAO;AAAA,IACL,SAAS,eAAe,oBAAoB,QAAQ,OAAO,aAAa;AAAA,IACxE,SAAS,eAAe,CAAC,mBAAmB,EAAE,GAAG,OAAO,OAAO,YAAY;AAAA,IAC3E,SAAS,eAAe,CAAC,kBAAkB,MAAM,GAAG,QAAQ,IAAI,WAAW,kBAAkB,IAAI,CAAC,UAAU,OAAO,KAAK,CAAC,CAAC,CAAC;AAAA,IAC3H,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,QAAQ,OAAO,IAAI,WAAW,eAAe,CAAC;AAAA,EAClG;AACF;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,cAAc,YAAY,SAAS,IAAI;AAC/C,MAAI,aAAa,MAAM,WAAW,GAAG;AACnC,UAAM,IAAI,MAAM;AAAA,UACV,aAAa,OAAO;AAAA,EAC5B;AACA,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,UACV,WAAW,OAAO;AAAA,EAC1B;AACA,MAAI,SAAS,MAAM,WAAW,GAAG;AAC/B,UAAM,IAAI,MAAM,sDAAsD,SAAS,OAAO;AAAA,EACxF;AACA,QAAM,cAAc,MAAM,KAAK,SAAS,KAAK,IAAI,WAAW,MAAM,EAAE,MAAM;AAC1E,QAAM,gBAAgB,SAAS,KAAK,IAAI,aAAa,MAAM,EAAE;AAC7D,QAAM,cAAc,MAAM,KAAK,SAAS,KAAK,IAAI,SAAS,MAAM,EAAE,MAAM;AACxE,QAAM,CAAC,YAAY,cAAc,WAAW,IAAI,kBAAkB,eAAe,aAAa,OAAO,aAAa,OAAO,aAAa,WAAW;AACjJ,SAAO;AAAA,IACL,SAAS,eAAe,cAAc,aAAa,OAAO,UAAU;AAAA,IACpE,SAAS,eAAe,CAAC,YAAY,MAAM,GAAG,SAAS,OAAO,IAAI,WAAW,WAAW,CAAC;AAAA,EAC3F;AACF;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,mBAAmB,MAAM;AAChC,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,MAAM,SAAS,WAAW,IAAI;AACtC,MAAI,KAAK,MAAM,SAAS,GAAG;AACzB,UAAM,IAAI,MAAM,2DAA2D;AAAA,EAC7E;AACA,MAAI,QAAQ,MAAM,WAAW,GAAG;AAC9B,UAAM,IAAI,MAAM;AAAA,YACR,QAAQ,OAAO;AAAA,EACzB;AACA,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,YACR,WAAW,OAAO;AAAA,EAC5B;AACA,MAAI,QAAQ,MAAM,OAAO,WAAW,MAAM,IAAI;AAC5C,UAAM,IAAI,MAAM,+CAA+C;AAAA,EACjE;AACA,QAAM,QAAQ,SAAS,KAAK,IAAI,KAAK,MAAM,EAAE;AAC7C,QAAM,WAAW,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACnD,QAAM,cAAc,SAAS,KAAK,IAAI,WAAW,MAAM,EAAE;AACzD,QAAM,CAAC,YAAY,eAAe,IAAI,2BAA2B,OAAO,KAAK,OAAO,KAAK,OAAO,UAAU,aAAa,IAAI;AAC3H,SAAO,SAAS,eAAe,iBAAiB,KAAK,OAAO,UAAU;AACxE;AACA,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,kBAAkB,MAAM;AAC/B,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,MAAM,SAAS,WAAW,IAAI;AACtC,MAAI,KAAK,MAAM,SAAS,GAAG;AACzB,UAAM,IAAI,MAAM,2DAA2D;AAAA,EAC7E;AACA,MAAI,QAAQ,MAAM,WAAW,GAAG;AAC9B,UAAM,IAAI,MAAM;AAAA,WACT,QAAQ,OAAO;AAAA,EACxB;AACA,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,WACT,WAAW,OAAO;AAAA,EAC3B;AACA,MAAI,QAAQ,MAAM,OAAO,WAAW,MAAM,IAAI;AAC5C,UAAM,IAAI,MAAM,+CAA+C;AAAA,EACjE;AACA,QAAM,QAAQ,SAAS,KAAK,IAAI,KAAK,MAAM,EAAE;AAC7C,QAAM,WAAW,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACnD,QAAM,cAAc,SAAS,KAAK,IAAI,WAAW,MAAM,EAAE;AACzD,QAAM,CAAC,YAAY,eAAe,IAAI,2BAA2B,OAAO,KAAK,OAAO,KAAK,OAAO,UAAU,WAAW;AACrH,SAAO,SAAS,eAAe,iBAAiB,KAAK,OAAO,UAAU;AACxE;AACA,IAAI,yBAAyB;AAAA,EAC3B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,eAAe,cAAc,aAAa,IAAI;AACtD,QAAM,EAAE,YAAY,IAAI;AACxB,QAAM,EAAE,WAAW,YAAY,WAAW,SAAAG,UAAS,YAAAQ,YAAW,IAAI,qBAAqB,gBAAgB,cAAc,eAAe,WAAW;AAC/I,QAAM,iBAAiB;AACvB,QAAM,aAAa,SAAS,WAAW,aAAa;AACpD,MAAI;AACJ,UAAQ,aAAa;AAAA,SACd,QAAQ;AACX,YAAM,aAAa,SAAS,WAAW,YAAY;AACnD,YAAM,gBAAgB,QAAQ,SAAS,KAAK,IAAI,aAAa,MAAM,EAAE,OAAO,EAAE;AAC9E,eAAS,YAAY,YAAY,YAAY,aAAaA,aAAY,WAAW,YAAY,WAAWR,UAAS,eAAe,cAAc;AAC9I;AAAA,IACF;AAAA,SACK,WAAW;AACd,YAAM,aAAa,SAAS,WAAW,YAAY;AACnD,YAAM,gBAAgB,SAAS,KAAK,IAAI,aAAa,MAAM,EAAE,OAAO;AACpE,eAAS,YAAY,YAAY,YAAY,aAAaQ,aAAY,WAAW,YAAY,WAAWR,UAAS,eAAe,cAAc;AAC9I;AAAA,IACF;AAAA,SACK,SAAS;AACZ,YAAM,aAAa,SAAS,WAAW,YAAY;AACnD,YAAM,gBAAgB,SAAS,KAAK,IAAI,aAAa,MAAM,EAAE,OAAO;AACpE,eAAS,YAAY,YAAY,YAAY,aAAaQ,aAAY,WAAW,YAAY,WAAWR,UAAS,eAAe,cAAc;AAC9I;AAAA,IACF;AAAA,SACK,UAAU;AACb,YAAM,aAAa,SAAS,WAAW,YAAY;AACnD,YAAM,gBAAgB,aAAa,aAAa,SAAS,KAAK,IAAI,aAAa,MAAM,EAAE,OAAO,EAAE;AAChG,eAAS,YAAY,YAAY,YAAY,aAAaQ,aAAY,WAAW,YAAY,WAAWR,UAAS,eAAe,cAAc;AAC9I;AAAA,IACF;AAAA;AAEE,YAAM,IAAI,MAAM,oBAAoB,aAAa,OAAO;AAAA;AAE5D,SAAO,SAAS,eAAe,aAAa,OAAO,OAAO,OAAO,MAAM;AACzE;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,iBAAiB,KAAK,IAAI;AAClC,QAAM,QAAQ,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AACzD,QAAM,aAAa,qBAAqB,iBAAiB,GAAG,iBAAiB,KAAK;AAClF,QAAM,QAAQ,IAAI,MAAM,EAAE,MAAM,MAAM,EAAE,KAAK,CAAC;AAC9C,QAAMZ,QAAO,EAAE,MAAM,MAAM;AAC3B,SAAO,WAAW,IAAI,CAAC,OAAO;AAC5B,UAAM,YAAY,CAAC,GAAGA,KAAI;AAC1B,cAAU,SAAS;AACnB,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,MAAM,UAAU,EAAE,CAAC;AAC7F,UAAM,UAAU;AAChB,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AAC7C,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,aAAa;AACnB,qBAAiB,GAAG,QAAQ;AAC5B,UAAM,SAAS,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,YAAY,IAAI,aAAa,OAAO,MAAM;AAChD,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,YAAM,QAAQ,OAAO;AACrB,gBAAU,MAAM,QAAQ;AAAA,IAC1B;AACA,UAAM,SAAS,WAAW,MAAM,WAAW,EAAE,OAAO,EAAE,KAAK;AAC3D,WAAO,EAAE,QAAQ,OAAO,EAAE,OAAO,OAAO,EAAE,MAAM;AAAA,EAClD;AACF;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,IAAI,UAAU;AAC/C,QAAM,YAAY;AAClB,MAAI,MAAM,EAAE,GAAG;AACb,WAAO;AAAA,EACT,OAAO;AACL,WAAO,KAAK,IAAI,IAAI,UAAU;AAAA,EAChC;AACF,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAO,KAAK,SAAAY,UAAS,WAAW,SAAS,cAAc,aAAa,eAAe,IAAI;AAC/F,mBAAiB,GAAG,cAAc;AAClC,QAAM,EAAE,kBAAkB,YAAY,YAAY,WAAW,eAAe,OAAO,QAAQ,KAAK,MAAM,SAAS,SAAS,IAAI,mBAAmB,UAAU,EAAE,OAAO,OAAO,KAAKA,UAAS,WAAW,SAAS,cAAc,aAAa,cAAc;AACpP,MAAI;AACJ,MAAI,YAAY;AACd,aAAS,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAAA,EACtF,WAAW,aAAa,eAAe;AACrC,iBAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,yCAAyC,EAAE,MAAM,QAAQ;AACxG,UAAMZ,QAAO,mBAAmB,gBAAgB,QAAQ,MAAM,QAAQ;AACtE,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,QAAQ,MAAAA,MAAK,EAAE,CAAC;AAC1F,aAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAC5F,aAAS,8BAA8B,MAAM;AAAA,EAC/C,OAAO;AACL,UAAM,OAAO,SAAS,WAAW,CAAC;AAClC,UAAM,SAAS,iBAAiB,kBAAkB,MAAM,UAAU,MAAM;AACxE,aAAS,SAAS,eAAe,YAAY,OAAO,OAAO,OAAO,MAAM;AAAA,EAC1E;AACA,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,WAAW,aAAa,SAAS,UAAU,WAAW,UAAU,uBAAuB,IAAI;AACnG,QAAM,EAAE,MAAM,WAAW,IAAI;AAC7B,QAAM,QAAQ,SAAS,KAAK,IAAI,KAAK,MAAM,EAAE;AAC7C,QAAM,cAAc,SAAS,KAAK,IAAI,WAAW,MAAM,EAAE;AACzD,QAAM,CAAC,QAAQ,YAAY,IAAI,iBAAiB,OAAO,aAAa,WAAW,aAAa,SAAS,WAAW,UAAU,sBAAsB;AAChJ,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,OAAO,MAAM,GAAG,UAAU,MAAM;AAAA,IACzD,SAAS,eAAe,WAAW,OAAO,SAAS,YAAY;AAAA,EACjE;AACF;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,UAAU,IAAI;AACtB,QAAM,EAAE,OAAO,QAAQ,UAAU,IAAI;AACrC,MAAI,OAAO,UAAU,UAAU;AAC7B,UAAM,IAAI,MAAM,kCAAkC;AAAA,EACpD;AACA,MAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,UAAM,IAAI,MAAM,sCAAsC,OAAO,OAAO;AAAA,EACtE;AACA,MAAI,UAAU,MAAM,WAAW,GAAG;AAChC,UAAM,IAAI,MAAM,0CAA0C,UAAU,OAAO;AAAA,EAC7E;AACA,QAAM,SAAS,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AAChD,QAAM,aAAa,SAAS,KAAK,IAAI,UAAU,MAAM,EAAE,OAAO;AAC9D,QAAM,CAAC,SAAS,QAAQ,KAAK,IAAI,gBAAgB,QAAQ,YAAY,SAAS;AAC9E,QAAMoB,cAAa,OAAO;AAC1B,SAAO;AAAA,IACL,SAAS,eAAe,CAACA,aAAY,CAAC,GAAG,SAAS,OAAO;AAAA,IACzD,SAAS,eAAe,CAACA,WAAU,GAAG,UAAU,MAAM;AAAA,IACtD,SAAS,eAAe,CAAC,CAAC,GAAG,SAAS,IAAI,WAAW,KAAK,CAAC;AAAA,EAC7D;AACF;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,wBAAwB,MAAM;AACrC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,WAAW,IAAI;AACvB,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,MAAI,OAAO,UAAU,UAAU;AAC7B,UAAM,IAAI,MAAM,kCAAkC;AAAA,EACpD;AACA,MAAI,cAAc,GAAG;AACnB,UAAM,IAAI,MAAM,sCAAsC;AAAA,EACxD;AACA,QAAM,SAAS,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AAChD,QAAM,SAAS,2BAA2B,QAAQ,UAAU;AAC5D,SAAO,SAAS,eAAe,OAAO,OAAO,SAAS,MAAM;AAC9D;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,gBAAgB,KAAK,CAAC,OAAO,KAAK,IAAI,EAAE,CAAC;AACpD,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,mBAAiB,GAAG,MAAM;AAC1B,QAAM,SAAS,SAAS,SAAS,WAAW,CAAC,GAAG,IAAI;AACpD,SAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC1E;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,mBAAiB,GAAG,MAAM;AAC1B,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,CAAC,aAAa,cAAc,IAAI,SAAS,OAAO,EAAE,OAAO,EAAE,OAAO,GAAG,MAAM;AACjF,SAAO;AAAA,IACL,SAAS,eAAe,YAAY,OAAO,YAAY,OAAO,YAAY,MAAM;AAAA,IAChF,SAAS,eAAe,eAAe,OAAO,eAAe,OAAO,eAAe,MAAM;AAAA,EAC3F;AACF;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,WAAW,IAAI;AACtC,QAAM,EAAE,eAAe,UAAU,WAAW,YAAY,IAAI;AAC5D,QAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,QAAM,CAAC,WAAW,QAAQ,IAAI,eAAe,OAAO,cAAc,CAAC,aAAa,UAAU;AAC1F,QAAM,WAAW,CAAC,OAAO,WAAW,UAAU,WAAW;AACzD,QAAMR,WAAU,aAAa,eAAe,OAAO,KAAK;AACxD,QAAM,cAAcA,SAAQ;AAC5B,QAAM,YAAYA,SAAQ;AAC1B,QAAM,YAAYA,SAAQ;AAC1B,QAAM,UAAU,aAAa,uBAAuB,OAAO,OAAO,aAAa,cAAc,QAAQ,CAAC;AACtG,UAAQ,KAAK,SAAS;AACtB,QAAM,YAAY,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACnD,QAAM,gBAAgB,SAAS,KAAK,IAAI,WAAW,MAAM,EAAE;AAC3D,WAAS,IAAI,GAAG,IAAI,OAAO,EAAE,GAAG;AAC9B,UAAM,aAAa,WAAW,MAAM,OAAO,IAAI,gBAAgB,cAAc,SAAS,IAAI,GAAG,IAAI,IAAI,CAAC;AACtG,aAAS,OAAO,GAAG,OAAO,WAAW,EAAE,MAAM;AAC3C,eAAS,OAAO,GAAG,OAAO,UAAU,EAAE,MAAM;AAC1C,iBAAS,UAAU,GAAG,UAAU,aAAa,EAAE,SAAS;AACtD,cAAI;AACJ,gBAAM,aAAa,WAAW,KAAK,OAAO,WAAW,KAAK,OAAO;AACjE,cAAI,eAAe,GAAG;AACpB;AAAA,UACF;AACA,gBAAM,OAAO,WAAW,KAAK,OAAO,WAAW,KAAK,OAAO,WAAW,MAAM;AAC5E,gBAAM,OAAO,WAAW,KAAK,OAAO,WAAW,KAAK,OAAO,WAAW,MAAM;AAC5E,gBAAM,IAAI,SAAS,KAAK,YAAY,QAAQ;AAC5C,gBAAM,IAAI,SAAS,KAAK,aAAa,QAAQ;AAC7C,kBAAQ;AAAA,iBACD;AACH,oBAAM,qBAAqB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,GAAG,GAAG,GAAG,SAAS,SAAS;AAC7H;AAAA,iBACG;AACH,oBAAM,sBAAsB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,GAAG,GAAG,GAAG,SAAS,SAAS;AAC9H;AAAA;AAEA,oBAAM,IAAI,MAAM,+DAA+D,eAAe;AAAA;AAElG,gBAAM,MAAM,IAAI,cAAc,OAAO,YAAY,OAAO,YAAY;AACpE,kBAAQ,OAAO;AAAA,QACjB;AAAA,MACF;AAAA,IACF;AACA,WAAO,SAAS,eAAe,UAAU,OAAO,OAAO,OAAO;AAAA,EAChE;AACA,QAAM,SAAS,SAAS,MAAM,SAAS,UAAU,OAAO,KAAK;AAC7D,SAAO,EAAE,QAAQ,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC5D;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AACA,SAAS,SAAS,UAAU,KAAK,MAAM;AACrC,UAAQ;AAAA,SACD;AACH,aAAO,gBAAgB,UAAU,GAAG;AAAA,SACjC;AACH,aAAO,aAAa,UAAU,GAAG;AAAA,SAC9B;AACH,aAAO,gBAAgB,UAAU,GAAG;AAAA,SACjC;AAAA;AAEH,aAAO,iBAAiB,UAAU,GAAG;AAAA;AAE3C;AACA,SAAS,gBAAgB,UAAU,KAAK;AACtC,MAAI,UAAU;AACd,MAAI,UAAU,GAAG;AACf,QAAI,OAAO,GAAG;AACZ,gBAAU;AAAA,IACZ,OAAO;AACL,YAAM,MAAM,IAAI;AAChB,UAAI,UAAU,KAAK;AACjB,kBAAU,MAAM,KAAK,MAAM,CAAC,UAAU,GAAG,IAAI;AAAA,MAC/C;AACA,gBAAU,UAAU,CAAC,MAAM,UAAU,MAAM,CAAC,UAAU;AAAA,IACxD;AAAA,EACF,WAAW,UAAU,MAAM,GAAG;AAC5B,QAAI,OAAO,GAAG;AACZ,gBAAU;AAAA,IACZ,OAAO;AACL,YAAM,MAAM,IAAI;AAChB,iBAAW,MAAM,KAAK,MAAM,UAAU,GAAG;AACzC,UAAI,WAAW,KAAK;AAClB,kBAAU,MAAM,UAAU;AAAA,MAC5B;AAAA,IACF;AAAA,EACF;AACA,SAAO,aAAa,MAAM,GAAG,SAAS,MAAM,CAAC;AAC/C;AACA,SAAS,aAAa,UAAU,KAAK;AACnC,MAAI,UAAU;AACd,MAAI,UAAU,GAAG;AACf,QAAI,OAAO,GAAG;AACZ,gBAAU;AAAA,IACZ,OAAO;AACL,YAAM,KAAK,MAAM;AACjB,iBAAW,OAAO,KAAK,MAAM,CAAC,UAAU,EAAE,IAAI;AAAA,IAChD;AAAA,EACF,WAAW,UAAU,MAAM,GAAG;AAC5B,QAAI,OAAO,GAAG;AACZ,gBAAU;AAAA,IACZ,OAAO;AACL,YAAM,KAAK,MAAM;AACjB,iBAAW,MAAM,KAAK,MAAM,UAAU,EAAE;AAAA,IAC1C;AAAA,EACF;AACA,SAAO,aAAa,MAAM,GAAG,SAAS,MAAM,CAAC;AAC/C;AACA,SAAS,iBAAiB,UAAU,KAAK;AACvC,SAAO;AACT;AACA,SAAS,gBAAgB,UAAU,KAAK;AACtC,SAAO,aAAa,MAAM,GAAG,UAAU,MAAM,CAAC;AAChD;AACA,SAAS,kBAAkB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,GAAG,GAAG,SAAS,WAAW;AACjI,QAAM,MAAM,QAAQ,cAAc,IAAI,YAAY,IAAI,YAAY;AAClE,MAAI,KAAK,KAAK,IAAI,eAAe,KAAK,KAAK,IAAI,YAAY;AACzD,WAAO,UAAU;AAAA,EACnB,OAAO;AACL,WAAO;AAAA,EACT;AACF;AACA,SAAS,qBAAqB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,GAAG,GAAG,SAAS,WAAW;AACpI,QAAM,KAAK,KAAK,MAAM,CAAC;AACvB,QAAM,KAAK,KAAK,MAAM,CAAC;AACvB,SAAO,kBAAkB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,IAAI,IAAI,SAAS,SAAS;AACnI;AACA,SAAS,sBAAsB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,GAAG,GAAG,SAAS,WAAW;AACrI,QAAM,SAAS,KAAK,MAAM,CAAC;AAC3B,QAAM,SAAS,KAAK,MAAM,CAAC;AAC3B,QAAM,QAAQ,SAAS;AACvB,QAAM,QAAQ,SAAS;AACvB,QAAM,eAAe,QAAQ,KAAK,kBAAkB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,QAAQ,QAAQ,SAAS,SAAS,KAAK,IAAI,UAAU,kBAAkB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,QAAQ,OAAO,SAAS,SAAS;AACxT,QAAM,cAAc,QAAQ,KAAK,kBAAkB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,OAAO,QAAQ,SAAS,SAAS,KAAK,IAAI,UAAU,kBAAkB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,OAAO,OAAO,SAAS,SAAS;AACrT,UAAQ,QAAQ,KAAK,eAAe,IAAI,UAAU;AACpD;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,EAAE,EAAE,IAAI;AACd,mBAAiB,GAAG,QAAQ;AAC5B,QAAM,SAAS,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC3C,QAAM,EAAE,cAAc,aAAa,QAAQ,IAAI,WAAW,QAAQ,MAAM,EAAE,OAAO,EAAE,KAAK;AACxF,SAAO;AAAA,IACL,SAAS,eAAe,aAAa,EAAE,OAAO,YAAY;AAAA,IAC1D,SAAS,eAAe,CAAC,QAAQ,MAAM,GAAG,SAAS,OAAO;AAAA,EAC5D;AACF;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,IAAI;AAClB,MAAI,EAAE,KAAK,IAAI;AACf,MAAI,OAAO,GAAG;AACZ,YAAQ,MAAM,MAAM;AAAA,EACtB;AACA,QAAM,YAAY,MAAM,MAAM;AAC9B,QAAM,MAAM,MAAM,MAAM;AACxB,QAAM,WAAW,IAAI,MAAM,YAAY,CAAC;AACxC,MAAI,WAAW;AACf,WAAS,KAAK,GAAG,KAAK,WAAW,MAAM;AACrC,QAAI,OAAO,MAAM;AACf,eAAS,cAAc,MAAM,MAAM;AAAA,IACrC;AAAA,EACF;AACA,QAAM,QAAQ,IAAI,MAAM,SAAS,EAAE,KAAK,CAAC;AACzC,QAAMZ,QAAO,MAAM,MAAM,MAAM;AAC/B,EAAAA,MAAK,QAAQ;AACb,QAAM,MAAM,IAAI,MAAM,GAAG;AACzB,WAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,MAAM;AACtC,UAAM,QAAQ;AACd,UAAM,UAAU,OAAO,EAAE,QAAQ,EAAE,GAAG,MAAM,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,MAAAA,MAAK,EAAE,CAAC;AAC1F,QAAI,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC5F,aAAS,8BAA8B,OAAO;AAAA,EAChD;AACA,SAAO;AACT;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,oBAAoB,MAAM;AACjC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,WAAW,IAAI;AAC1B,QAAM,EAAE,YAAY,IAAI;AACxB,mBAAiB,GAAG,oBAAoB;AACxC,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,iBAAiB,WAAW,MAAM;AACxC,QAAM,MAAM,CAAC;AACb,QAAM,gBAAgB,CAAC;AACvB,QAAM,WAAW,QAAQ;AACzB,MAAI,cAAc;AAClB,WAAS,KAAK,GAAG,KAAK,UAAU,EAAE,IAAI;AACpC,UAAM,WAAW,YAAY,EAAE,QAAQ,EAAE,OAAO,YAAY,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,EAAE,CAAC;AAC1G,kBAAc;AACd,kBAAc,KAAK,QAAQ;AAAA,EAC7B;AACA,WAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,UAAM,cAAc,aAAa,kBAAkB,IAAI,OAAO;AAC9D,UAAM,YAAY,SAAS,eAAe,CAAC,GAAG,SAAS,WAAW;AAClE,UAAMK,QAAO,OAAO,EAAE,QAAQ,EAAE,GAAG,WAAW,GAAG,YAAY,GAAG,SAAS,SAAS,CAAC;AACnF,UAAM,aAAa,MAAM,EAAE,QAAQ,EAAE,GAAGA,MAAK,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AAChG,UAAM,OAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,YAAY,GAAG,EAAE,GAAG,SAAS,SAAS,CAAC;AAC7E,UAAM,gBAAgB,KAAK,EAAE,QAAQ,EAAE,GAAG,KAAK,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,GAAG,UAAU,MAAM,EAAE,CAAC;AAC1G,QAAI,KAAK,aAAa;AACtB,kBAAc,KAAK,SAAS;AAC5B,kBAAc,KAAKA,KAAI;AACvB,kBAAc,KAAK,UAAU;AAC7B,kBAAc,KAAK,IAAI;AACvB,kBAAc,KAAK,aAAa;AAAA,EAClC;AACA,QAAM,SAAS,KAAK,EAAE,QAAQ,KAAK,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,EAAE,CAAC;AAC1E,gBAAc,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACxE,SAAO;AACT;AACA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB;AAAA,EAClB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,WAAW,gBAAgB,eAAe;AACxC,iBAAe,YAAY;AAC7B;AAGA,IAAI,qBAAqB,CAAC;AAC1BR,UAAS,oBAAoB;AAAA,EAC3B,kBAAkB,MAAM;AAAA,EACxB,yBAAyB,MAAM;AAAA,EAC/B,+BAA+B,MAAM;AAAA,EACrC,oCAAoC,MAAM;AAAA,EAC1C,iBAAiB,MAAM;AAAA,EACvB,oCAAoC,MAAM;AAAA,EAC1C,cAAc,MAAM;AAAA,EACpB,kBAAkB,MAAM;AAAA,EACxB,sBAAsB,MAAM;AAAA,EAC5B,mBAAmB,MAAM;AAAA,EACzB,eAAe,MAAM;AAAA,EACrB,yBAAyB,MAAM;AAAA,EAC/B,0BAA0B,MAAM;AAAA,EAChC,eAAe,MAAM;AAAA,EACrB,oBAAoB,MAAM;AAAA,EAC1B,aAAa,MAAM;AAAA,EACnB,qBAAqB,MAAM;AAAA,EAC3B,4BAA4B,MAAM;AAAA,EAClC,wBAAwB,MAAM;AAAA,EAC9B,gBAAgB,MAAM;AAAA,EACtB,2BAA2B,MAAM;AAAA,EACjC,kCAAkC,MAAM;AAAA,EACxC,aAAa,MAAM;AAAA,EACnB,cAAc,MAAM;AAAA,EACpB,iCAAiC,MAAM;AAAA,EACvC,mCAAmC,MAAM;AAAA,EACzC,sBAAsB,MAAM;AAAA,EAC5B,wBAAwB,MAAM;AAAA,EAC9B,cAAc,MAAM;AAAA,EACpB,oCAAoC,MAAM;AAAA,EAC1C,+BAA+B,MAAM;AAAA,EACrC,eAAe,MAAM;AAAA,EACrB,qBAAqB,MAAM;AAAA,EAC3B,uBAAuB,MAAM;AAAA,EAC7B,aAAa,MAAM;AAAA,EACnB,2BAA2B,MAAM;AAAA,EACjC,qBAAqB,MAAM;AAAA,EAC3B,0BAA0B,MAAM;AAAA,EAChC,mCAAmC,MAAM;AAAA,EACzC,mBAAmB,MAAM;AAAA,EACzB,qBAAqB,MAAM;AAAA,EAC3B,iBAAiB,MAAM;AAAA,EACvB,qBAAqB,MAAM;AAC7B,CAAC;AAGD,IAAI,WAAW,CAAC;AAChB,IAAI,mBAAmB;AAAA,EACrB,OAAO;AAAA,EACP,WAAW;AAAA,EACX,oBAAoB;AAAA,EACpB,uBAAuB;AAAA,EACvB,OAAO;AAAA,EACP,SAAS;AAAA,EACT,8BAA8B;AAChC;AACA,SAAS,gBAAgB,cAAc,IAAI;AACzC,WAAS,gBAAgB;AAC3B;AACA,SAAS,gBAAgB,cAAc,cAAc;AACnD,MAAI,EAAE,gBAAgB,aAAa,gBAAgB,MAAM;AACvD,UAAM,SAAS,yBAAyB,cAAc,YAAY;AAClE,QAAI,WAAW,MAAM;AACnB,eAAS,gBAAgB;AAAA,IAC3B,OAAO;AACL,cAAQ,IAAI,2CAA2C,YAAY;AACnE,aAAO;AAAA,IACT;AAAA,EACF;AACA,QAAM,KAAK,SAAS;AACpB,MAAI,MAAM,QAAQ,GAAG,cAAc,GAAG;AACpC,WAAO,SAAS;AAChB,WAAO,gBAAgB,YAAY;AAAA,EACrC;AACA,KAAG,QAAQ,GAAG,UAAU;AACxB,KAAG,QAAQ,GAAG,YAAY;AAC1B,KAAG,QAAQ,GAAG,KAAK;AACnB,KAAG,QAAQ,GAAG,MAAM;AACpB,KAAG,QAAQ,GAAG,mBAAmB;AACjC,KAAG,QAAQ,GAAG,eAAe;AAC7B,KAAG,OAAO,GAAG,YAAY;AACzB,KAAG,OAAO,GAAG,SAAS;AACtB,KAAG,SAAS,GAAG,IAAI;AACnB,SAAO,SAAS;AAClB;AACA,SAAS,aAAa,cAAc;AAClC,MAAI,OAAO,oBAAoB,eAAe,iBAAiB,GAAG;AAChE,WAAO,IAAI,gBAAgB,KAAK,GAAG;AAAA,EACrC,WAAW,OAAO,aAAa,aAAa;AAC1C,WAAO,SAAS,cAAc,QAAQ;AAAA,EACxC,OAAO;AACL,UAAM,IAAI,MAAM,wCAAwC;AAAA,EAC1D;AACF;AACA,SAAS,yBAAyB,cAAc,cAAc;AAC5D,MAAI,iBAAiB,KAAK,iBAAiB,GAAG;AAC5C,UAAM,IAAI,MAAM,wDAAwD;AAAA,EAC1E;AACA,QAAMa,UAAS,gBAAgB,OAAO,aAAa,YAAY,IAAI;AACnE,EAAAA,QAAO,iBAAiB,oBAAoB,CAAC,OAAO;AAClD,OAAG,eAAe;AAClB,WAAO,SAAS;AAAA,EAClB,GAAG,KAAK;AACR,MAAI,iBAAiB,GAAG;AACtB,WAAOA,QAAO,WAAW,SAAS,gBAAgB,KAAKA,QAAO,WAAW,sBAAsB,gBAAgB;AAAA,EACjH;AACA,SAAOA,QAAO,WAAW,UAAU,gBAAgB;AACrD;AAGA,IAAI;AAAA,CACH,SAAS,gBAAgB;AACxB,iBAAe,eAAe,WAAW,KAAK;AAC9C,iBAAe,eAAe,kBAAkB,KAAK;AACvD,GAAG,kBAAkB,gBAAgB,CAAC,EAAE;AACxC,IAAI;AAAA,CACH,SAAS,eAAe;AACvB,gBAAc,cAAc,YAAY,KAAK;AAC7C,gBAAc,cAAc,YAAY,KAAK;AAC7C,gBAAc,cAAc,YAAY,KAAK;AAC7C,gBAAc,cAAc,cAAc,KAAK;AACjD,GAAG,iBAAiB,eAAe,CAAC,EAAE;AACtC,IAAI;AAAA,CACH,SAAS,sBAAsB;AAC9B,uBAAqB,qBAAqB,sBAAsB,KAAK;AACrE,uBAAqB,qBAAqB,sBAAsB,KAAK;AACrE,uBAAqB,qBAAqB,8BAA8B,KAAK;AAC7E,uBAAqB,qBAAqB,wBAAwB,KAAK;AACvE,uBAAqB,qBAAqB,wBAAwB,KAAK;AACzE,GAAG,wBAAwB,sBAAsB,CAAC,EAAE;AACpD,SAAS,yCAAyC,MAAM,SAAS;AAC/D,SAAO,CAAC,SAAS,IAAI;AACvB;AACA,SAAS,mCAAmC,YAAY,oBAAoB;AAC1E,SAAO,aAAa;AACtB;AACA,SAAS,iBAAiB,OAAO;AAC/B,QAAMV,QAAO,aAAa,cAAc,KAAK;AAC7C,QAAM,eAAe,KAAK,KAAKA,QAAO,CAAC;AACvC,SAAO,aAAa,oBAAoB,YAAY;AACtD;AACA,SAAS,uCAAuC,MAAM,SAAS;AAC7D,SAAO;AAAA,IACL,KAAK,IAAI,GAAG,KAAK,KAAK,UAAU,CAAC,CAAC;AAAA,IAClC,KAAK,IAAI,GAAG,KAAK,KAAK,OAAO,CAAC,CAAC;AAAA,EACjC;AACF;AACA,SAAS,sCAAsC,MAAM,SAAS;AAC5D,QAAM,CAAC,GAAG,CAAC,IAAI,uCAAuC,MAAM,OAAO;AACnE,SAAO,IAAI,IAAI;AACjB;AACA,SAAS,iBAAiB,IAAI,2BAA2B;AACvD,QAAM,QAAQ;AACd,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,0BAAsB,MAAM;AAC5B,8BAA0B,MAAM;AAChC,oCAAgC,MAAM;AACtC,gCAA4B,MAAM;AAClC,yBAAqB,MAAM;AAC3B,gCAA4B;AAC5B,yBAAqB;AACrB,2BAAuB,MAAM;AAC7B,uBAAmB,MAAM;AACzB,4BAAwB,MAAM;AAAA,EAChC,OAAO;AACL,0BAAsB,GAAG;AACzB,8BAA0B,GAAG;AAC7B,oCAAgC,GAAG;AACnC,gCAA4B,MAAM;AAClC,yBAAqB,GAAG;AACxB,gCAA4B;AAC5B,yBAAqB;AACrB,2BAAuB,6BAA6B,OAAO,0BAA0B,iBAAiB;AACtG,uBAAmB,GAAG;AACtB,4BAAwB,GAAG;AAAA,EAC7B;AACA,SAAO;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AAGA,SAAS,aAAa,IAAI,OAAO;AAC/B,QAAM,cAAc,MAAM;AAC1B,MAAI,IAAI,EAAE,QAAQ,OAAO,GAAG;AAC1B,oBAAgB,EAAE;AAAA,EACpB;AACA,SAAO;AACT;AACA,SAAS,gBAAgB,IAAI;AAC3B,QAAM,QAAQ,GAAG,SAAS;AAC1B,MAAI,UAAU,GAAG,UAAU;AACzB,UAAM,IAAI,MAAM,kBAAkB,qBAAqB,IAAI,KAAK,CAAC;AAAA,EACnE;AACF;AACA,IAAI,cAAc;AAClB,IAAI,cAAc;AAClB,SAAS,iBAAiB,KAAK;AAC7B,MAAI,IAAI,EAAE,QAAQ,8BAA8B,KAAK,QAAQ,KAAK,cAAc,KAAK,IAAI,GAAG,KAAK,KAAK,IAAI,GAAG,IAAI,aAAa;AAC5H,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,qBAAqB,IAAI,QAAQ;AACxC,UAAQ;AAAA,SACD,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA;AAEP,aAAO,sBAAsB;AAAA;AAEnC;AACA,SAAS,oBAAoB,IAAI,eAAe;AAC9C,SAAO,YAAY,IAAI,MAAM,GAAG,aAAa,aAAa,GAAG,gBAAgB,gBAAgB,kCAAkC;AACjI;AACA,SAAS,mBAAmB,IAAI,oBAAoB;AAClD,QAAM,eAAe,YAAY,IAAI,MAAM,GAAG,aAAa,GAAG,aAAa,GAAG,sCAAsC;AACpH,eAAa,IAAI,MAAM,GAAG,aAAa,cAAc,kBAAkB,CAAC;AACxE,eAAa,IAAI,MAAM,GAAG,cAAc,YAAY,CAAC;AACrD,MAAI,GAAG,mBAAmB,cAAc,GAAG,cAAc,MAAM,OAAO;AACpE,YAAQ,IAAI,GAAG,iBAAiB,YAAY,CAAC;AAC7C,UAAM,IAAI,MAAM,kCAAkC;AAAA,EACpD;AACA,SAAO;AACT;AACA,SAAS,qBAAqB,IAAI,sBAAsB;AACtD,QAAM,iBAAiB,YAAY,IAAI,MAAM,GAAG,aAAa,GAAG,eAAe,GAAG,wCAAwC;AAC1H,eAAa,IAAI,MAAM,GAAG,aAAa,gBAAgB,oBAAoB,CAAC;AAC5E,eAAa,IAAI,MAAM,GAAG,cAAc,cAAc,CAAC;AACvD,MAAI,IAAI,EAAE,IAAI,qBAAqB,GAAG;AACpC,WAAO;AAAA,EACT;AACA,MAAI,GAAG,mBAAmB,gBAAgB,GAAG,cAAc,MAAM,OAAO;AACtE,8BAA0B,sBAAsB,GAAG,iBAAiB,cAAc,CAAC;AACnF,UAAM,IAAI,MAAM,oCAAoC;AAAA,EACtD;AACA,SAAO;AACT;AACA,IAAI,kBAAkB;AACtB,SAAS,0BAA0B,cAAc,eAAe;AAC9D,QAAM,wBAAwB,gBAAgB,KAAK,aAAa;AAChE,MAAI,yBAAyB,MAAM;AACjC,YAAQ,IAAI,wCAAwC,eAAe;AACnE,YAAQ,IAAI,YAAY;AACxB;AAAA,EACF;AACA,QAAM,aAAa,CAAC,sBAAsB;AAC1C,QAAM,cAAc,aAAa,MAAM,IAAI;AAC3C,QAAM,OAAO,YAAY,OAAO,SAAS,EAAE,SAAS;AACpD,QAAM,uBAAuB,YAAY,IAAI,CAAC,MAAM,gBAAgB,aAAa,UAAU,cAAc,GAAG,SAAS,GAAG,IAAI,IAAI,IAAI;AACpI,MAAI,gBAAgB;AACpB,WAAS,KAAK,GAAG,KAAK,qBAAqB,QAAQ,MAAM;AACvD,oBAAgB,KAAK,IAAI,qBAAqB,IAAI,QAAQ,aAAa;AAAA,EACzE;AACA,QAAM,mBAAmB,qBAAqB,MAAM,GAAG,aAAa,CAAC;AACrE,QAAM,YAAY,qBAAqB,MAAM,aAAa,GAAG,UAAU;AACvE,QAAM,kBAAkB,qBAAqB,MAAM,UAAU;AAC7D,UAAQ,IAAI,iBAAiB,KAAK,IAAI,CAAC;AACvC,UAAQ,IAAI,cAAc,MAAM,IAAI,EAAE,EAAE;AACxC,UAAQ,IAAI,MAAM,aAAa,SAAS,UAAU,IAAI,aAAa,KAAK,+DAA+D;AACvI,UAAQ,IAAI,gBAAgB,KAAK,IAAI,CAAC;AACxC;AACA,SAAS,cAAc,IAAI;AACzB,SAAO,YAAY,IAAI,MAAM,GAAG,cAAc,GAAG,gCAAgC;AACnF;AACA,SAAS,YAAY,IAAI,SAAS;AAChC,eAAa,IAAI,MAAM,GAAG,YAAY,OAAO,CAAC;AAC9C,MAAI,IAAI,EAAE,IAAI,qBAAqB,GAAG;AACpC;AAAA,EACF;AACA,MAAI,GAAG,oBAAoB,SAAS,GAAG,WAAW,MAAM,OAAO;AAC7D,YAAQ,IAAI,GAAG,kBAAkB,OAAO,CAAC;AACzC,UAAM,IAAI,MAAM,6CAA6C;AAAA,EAC/D;AACF;AACA,SAAS,gBAAgB,IAAI,SAAS;AACpC,eAAa,IAAI,MAAM,GAAG,gBAAgB,OAAO,CAAC;AAClD,MAAI,GAAG,oBAAoB,SAAS,GAAG,eAAe,MAAM,OAAO;AACjE,YAAQ,IAAI,GAAG,kBAAkB,OAAO,CAAC;AACzC,UAAM,IAAI,MAAM,mCAAmC;AAAA,EACrD;AACF;AACA,SAAS,yBAAyB,IAAI,MAAM;AAC1C,QAAM,UAAU,YAAY,IAAI,MAAM,GAAG,aAAa,GAAG,8BAA8B;AACvF,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,cAAc,OAAO,CAAC;AAC9D,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,cAAc,MAAM,GAAG,WAAW,CAAC;AAC3E,SAAO;AACT;AACA,SAAS,wBAAwB,IAAI,MAAM;AACzC,QAAM,UAAU,YAAY,IAAI,MAAM,GAAG,aAAa,GAAG,8BAA8B;AACvF,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,sBAAsB,OAAO,CAAC;AACtE,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,sBAAsB,MAAM,GAAG,WAAW,CAAC;AACnF,SAAO;AACT;AACA,SAAS,iBAAiB;AACxB,MAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,cAAc,IAAI;AACzB,SAAO,YAAY,IAAI,MAAM,GAAG,cAAc,GAAG,gCAAgC;AACnF;AACA,SAAS,oBAAoB,OAAO,QAAQ;AAC1C,QAAM,iBAAiB,IAAI,EAAE,UAAU,wBAAwB;AAC/D,MAAI,SAAS,KAAK,UAAU,GAAG;AAC7B,UAAM,YAAY,IAAI,SAAS;AAC/B,UAAM,IAAI,MAAM,4BAA4B,YAAY,cAAc;AAAA,EACxE;AACA,MAAI,QAAQ,kBAAkB,SAAS,gBAAgB;AACrD,UAAM,YAAY,IAAI,SAAS;AAC/B,UAAM,OAAO,IAAI,kBAAkB;AACnC,UAAM,IAAI,MAAM,4BAA4B,YAAY,uDAAuD,OAAO,GAAG;AAAA,EAC3H;AACF;AACA,SAAS,kBAAkB,IAAI;AAC7B,SAAO,YAAY,IAAI,MAAM,GAAG,kBAAkB,GAAG,oCAAoC;AAC3F;AACA,SAAS,mCAAmC,IAAI,SAAS,WAAW,SAAS,qBAAqB,mBAAmB,mBAAmB;AACtI,QAAM,MAAM,GAAG,kBAAkB,SAAS,SAAS;AACnD,MAAI,QAAQ,IAAI;AACd,WAAO;AAAA,EACT;AACA,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,cAAc,OAAO,CAAC;AAC9D,eAAa,IAAI,MAAM,GAAG,oBAAoB,KAAK,qBAAqB,GAAG,OAAO,OAAO,mBAAmB,iBAAiB,CAAC;AAC9H,eAAa,IAAI,MAAM,GAAG,wBAAwB,GAAG,CAAC;AACtD,SAAO;AACT;AACA,SAAS,gBAAgB,IAAI,SAAS,aAAa;AACjD,sBAAoB,IAAI,WAAW;AACnC,eAAa,IAAI,MAAM,GAAG,cAAc,GAAG,WAAW,WAAW,CAAC;AAClE,eAAa,IAAI,MAAM,GAAG,YAAY,GAAG,YAAY,OAAO,CAAC;AAC/D;AACA,SAAS,kBAAkB,IAAI,aAAa;AAC1C,sBAAoB,IAAI,WAAW;AACnC,eAAa,IAAI,MAAM,GAAG,cAAc,GAAG,WAAW,WAAW,CAAC;AAClE,eAAa,IAAI,MAAM,GAAG,YAAY,GAAG,YAAY,IAAI,CAAC;AAC5D;AACA,SAAS,iCAAiC,IAAI,SAAS,aAAa;AAClE,SAAO,YAAY,IAAI,MAAM,GAAG,mBAAmB,SAAS,WAAW,GAAG,cAAc,cAAc,2BAA2B;AACnI;AACA,SAAS,0BAA0B,IAAI,SAAS,aAAa;AAC3D,SAAO,GAAG,mBAAmB,SAAS,WAAW;AACnD;AACA,SAAS,mCAAmC,IAAI,SAAS,wBAAwB,aAAa;AAC5F,eAAa,IAAI,MAAM,gBAAgB,IAAI,SAAS,WAAW,CAAC;AAChE,eAAa,IAAI,MAAM,GAAG,UAAU,wBAAwB,WAAW,CAAC;AAC1E;AACA,SAAS,wBAAwB,IAAI;AACnC,eAAa,IAAI,MAAM,GAAG,gBAAgB,GAAG,aAAa,IAAI,CAAC;AAC/D,eAAa,IAAI,MAAM,GAAG,SAAS,GAAG,GAAG,GAAG,OAAO,OAAO,GAAG,OAAO,MAAM,CAAC;AAC3E,eAAa,IAAI,MAAM,GAAG,QAAQ,GAAG,GAAG,GAAG,OAAO,OAAO,GAAG,OAAO,MAAM,CAAC;AAC5E;AACA,SAAS,8BAA8B,IAAI,SAAS,aAAa;AAC/D,eAAa,IAAI,MAAM,GAAG,gBAAgB,GAAG,aAAa,WAAW,CAAC;AACtE,eAAa,IAAI,MAAM,GAAG,qBAAqB,GAAG,aAAa,GAAG,mBAAmB,GAAG,YAAY,SAAS,CAAC,CAAC;AACjH;AACA,SAAS,kCAAkC,IAAI,aAAa;AAC1D,eAAa,IAAI,MAAM,GAAG,gBAAgB,GAAG,aAAa,WAAW,CAAC;AACtE,eAAa,IAAI,MAAM,GAAG,qBAAqB,GAAG,aAAa,GAAG,mBAAmB,GAAG,YAAY,MAAM,CAAC,CAAC;AAC9G;AACA,SAAS,oBAAoB,IAAI;AAC/B,QAAM,SAAS,GAAG,uBAAuB,GAAG,WAAW;AACvD,MAAI,WAAW,GAAG,sBAAsB;AACtC,UAAM,IAAI,MAAM,gCAAgC,2BAA2B,IAAI,MAAM,CAAC;AAAA,EACxF;AACF;AACA,SAAS,2BAA2B,IAAI,QAAQ;AAC9C,UAAQ;AAAA,SACD,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA;AAEP,aAAO,iBAAiB;AAAA;AAE9B;AACA,SAAS,YAAY,IAAI,eAAe,gBAAgB;AACtD,QAAM,UAAU,aAAa,IAAI,MAAM,cAAc,CAAC;AACtD,MAAI,WAAW,MAAM;AACnB,UAAM,IAAI,MAAM,cAAc;AAAA,EAChC;AACA,SAAO;AACT;AACA,SAAS,oBAAoB,IAAI,aAAa;AAC5C,QAAM,iBAAiB,GAAG,mCAAmC;AAC7D,QAAM,gBAAgB,cAAc,GAAG;AACvC,MAAI,gBAAgB,GAAG,YAAY,gBAAgB,gBAAgB;AACjE,UAAM,mBAAmB,2BAA2B;AACpD,UAAM,IAAI,MAAM,0BAA0B,mBAAmB;AAAA,EAC/D;AACF;AACA,SAAS,YAAY,OAAO,aAAa,GAAG;AAC1C,SAAO,aAAa,cAAc,MAAM,MAAM,GAAG,MAAM,SAAS,UAAU,CAAC;AAC7E;AACA,SAAS,YAAY,OAAO;AAC1B,MAAI,MAAM,WAAW,GAAG;AACtB,UAAM,MAAM,sDAAsD;AAAA,EACpE;AACA,SAAO;AAAA,IACL,MAAM,SAAS,IAAI,MAAM,MAAM,SAAS,KAAK;AAAA,IAC7C,MAAM,MAAM,SAAS;AAAA,EACvB;AACF;AACA,SAAS,aAAa,OAAO;AAC3B,MAAI,YAAY,CAAC,GAAG,GAAG,CAAC;AACxB,QAAM,WAAW,MAAM,WAAW,KAAK,MAAM,WAAW,KAAK,MAAM,OAAO;AAC1E,MAAI,CAAC,UAAU;AACb,gBAAY,CAAC,YAAY,KAAK,GAAG,GAAG,YAAY,KAAK,CAAC;AAAA,EACxD;AACA,SAAO;AACT;AACA,SAAS,gCAAgC,UAAU,WAAW,OAAO;AACnE,MAAI,aAAa,IAAI,EAAE,UAAU,wBAAwB;AACzD,MAAI,UAAU;AACZ,iBAAa,aAAa;AAC1B,eAAW,SAAS,IAAI,CAAC,GAAG,OAAO,MAAM,SAAS,SAAS,IAAI,aAAa,kBAAkB,SAAS,GAAG,IAAI,SAAS,GAAG;AAC1H,QAAI,SAAS,WAAW,GAAG;AACzB,iBAAW,CAAC,GAAG,SAAS,EAAE;AAAA,IAC5B;AAAA,EACF;AACA,MAAI,SAAS,WAAW,GAAG;AACzB,UAAM,gBAAgB,aAAa,aAAa,QAAQ;AACxD,eAAW,cAAc;AAAA,EAC3B;AACA,MAAIA,QAAO,aAAa,cAAc,QAAQ;AAC9C,MAAI,SAAS,UAAU,KAAKA,SAAQ,YAAY;AAC9C,WAAO,CAAC,GAAGA,KAAI;AAAA,EACjB,WAAW,SAAS,WAAW,KAAK,SAAS,MAAM,cAAc,SAAS,MAAM,YAAY;AAC1F,WAAO;AAAA,EACT,WAAW,SAAS,WAAW,KAAK,SAAS,KAAK,SAAS,MAAM,cAAc,SAAS,MAAM,YAAY;AACxG,WAAO,CAAC,SAAS,KAAK,SAAS,IAAI,SAAS,EAAE;AAAA,EAChD,WAAW,SAAS,WAAW,KAAK,SAAS,MAAM,cAAc,SAAS,KAAK,SAAS,MAAM,YAAY;AACxG,WAAO,CAAC,SAAS,IAAI,SAAS,KAAK,SAAS,EAAE;AAAA,EAChD,WAAW,SAAS,WAAW,KAAK,SAAS,KAAK,SAAS,KAAK,SAAS,MAAM,cAAc,SAAS,MAAM,YAAY;AACtH,WAAO,CAAC,SAAS,KAAK,SAAS,KAAK,SAAS,IAAI,SAAS,EAAE;AAAA,EAC9D,WAAW,SAAS,WAAW,KAAK,SAAS,MAAM,cAAc,SAAS,KAAK,SAAS,KAAK,SAAS,MAAM,YAAY;AACtH,WAAO,CAAC,SAAS,IAAI,SAAS,KAAK,SAAS,KAAK,SAAS,EAAE;AAAA,EAC9D,OAAO;AACL,QAAI,UAAU;AACZ,YAAM,WAAW,YAAY,QAAQ;AACrC,UAAI,OAAO,GAAG,OAAO;AACrB,UAAI,SAAS,QAAQ;AACnB,SAAC,MAAM,IAAI,IAAI,YAAY,QAAQ;AAAA,MACrC;AACA,MAAAA,QAAO,YAAY,OAAO,MAAM,OAAO;AACvC,aAAO,aAAa,oBAAoBA,KAAI,EAAE,IAAI,CAAC,MAAM,IAAI,CAAC;AAAA,IAChE;AACA,WAAO,aAAa,oBAAoBA,KAAI;AAAA,EAC9C;AACF;AACA,SAAS,OAAO,IAAI;AAClB,SAAO,KAAK,MAAM;AACpB;AACA,SAAS,cAAc,QAAQ,QAAQ;AACrC,WAAS,OAAO,MAAM,EAAE;AACxB,WAAS,OAAO,MAAM,EAAE;AACxB,MAAI,aAAa,YAAY,QAAQ,MAAM,GAAG;AAC5C,WAAO;AAAA,EACT;AACA,MAAI,CAAC,OAAO,UAAU,CAAC,OAAO,QAAQ;AACpC,WAAO;AAAA,EACT;AACA,MAAI,OAAO,OAAO,KAAK,OAAO,OAAO,KAAK,OAAO,OAAO,KAAK,OAAO,OAAO,GAAG;AAC5E,WAAO;AAAA,EACT;AACA,MAAI,OAAO,WAAW,OAAO,QAAQ;AACnC,UAAM,aAAa,OAAO,MAAM,EAAE,EAAE;AACpC,UAAM,aAAa,OAAO,MAAM,EAAE,EAAE;AACpC,QAAI,eAAe,YAAY;AAC7B,aAAO;AAAA,IACT;AACA,QAAI,OAAO,UAAU,KAAK,OAAO,UAAU,MAAM,OAAO,OAAO,KAAK,OAAO,OAAO,IAAI;AACpF,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO,OAAO,OAAO,OAAO,MAAM,OAAO,OAAO,EAAE,KAAK,OAAO,OAAO,EAAE;AACzE;AACA,IAAI;AACJ,IAAI;AACJ,SAAS,uBAAuB,cAAc;AAC5C,MAAI,oBAAoB,MAAM;AAC5B,UAAM,KAAK,gBAAgB,YAAY;AACvC,uBAAmB,GAAG,aAAa,GAAG,gBAAgB;AAAA,EACxD;AACA,SAAO;AACT;AACA,SAAS,sBAAsB;AAC7B,qBAAmB;AACrB;AACA,SAAS,2BAA2B;AAClC,2BAAyB;AAC3B;AACA,SAAS,uBAAuB,cAAc;AAC5C,MAAI,0BAA0B,MAAM;AAClC,UAAM,KAAK,gBAAgB,YAAY;AACvC,6BAAyB,GAAG,aAAa,GAAG,uBAAuB;AAAA,EACrE;AACA,SAAO,KAAK,IAAI,IAAI,sBAAsB;AAC5C;AACA,SAAS,kCAAkC,cAAc;AACvD,MAAI,iBAAiB,GAAG;AACtB,WAAO;AAAA,EACT;AACA,MAAI;AACJ,QAAM,KAAK,gBAAgB,YAAY;AACvC,MAAI,aAAa,IAAI,iCAAiC,KAAK,iBAAiB,GAAG;AAC7E,wBAAoB;AAAA,EACtB,WAAW,aAAa,IAAI,0BAA0B,GAAG;AACvD,wBAAoB;AAAA,EACtB,OAAO;AACL,wBAAoB;AAAA,EACtB;AACA,SAAO;AACT;AACA,SAAS,aAAa,IAAI,eAAe;AACvC,QAAM,MAAM,GAAG,aAAa,aAAa;AACzC,SAAO,OAAO;AAChB;AACA,SAAS,sBAAsB,cAAc;AAC3C,MAAI;AACF,UAAM,KAAK,gBAAgB,YAAY;AACvC,QAAI,MAAM,MAAM;AACd,aAAO;AAAA,IACT;AAAA,EACF,SAAS,IAAP;AACA,YAAQ,IAAI,sCAAsC,EAAE;AACpD,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,mCAAmC,cAAc;AACxD,MAAI,iBAAiB,GAAG;AACtB,WAAO;AAAA,EACT;AACA,QAAM,KAAK,gBAAgB,YAAY;AACvC,MAAI,iBAAiB,GAAG;AACtB,QAAI,CAAC,aAAa,IAAI,mBAAmB,GAAG;AAC1C,aAAO;AAAA,IACT;AAAA,EACF,OAAO;AACL,QAAI,CAAC,aAAa,IAAI,wBAAwB,GAAG;AAC/C,aAAO;AAAA,IACT;AAAA,EACF;AACA,QAAM,wBAAwB,uCAAuC,EAAE;AACvE,SAAO;AACT;AACA,SAAS,8BAA8B,cAAc;AACnD,MAAI,iBAAiB,GAAG;AACtB,WAAO;AAAA,EACT;AACA,QAAM,KAAK,gBAAgB,YAAY;AACvC,MAAI,iBAAiB,GAAG;AACtB,QAAI,CAAC,aAAa,IAAI,mBAAmB,GAAG;AAC1C,aAAO;AAAA,IACT;AACA,QAAI,CAAC,aAAa,IAAI,0BAA0B,GAAG;AACjD,aAAO;AAAA,IACT;AAAA,EACF,OAAO;AACL,QAAI,aAAa,IAAI,wBAAwB,GAAG;AAC9C,aAAO,uCAAuC,EAAE;AAAA,IAClD;AACA,UAAM,0BAA0B;AAChC,QAAI,aAAa,IAAI,uBAAuB,GAAG;AAC7C,YAAM,4BAA4B,GAAG,aAAa,uBAAuB;AACzE,aAAO,2CAA2C,IAAI,yBAAyB;AAAA,IACjF;AACA,WAAO;AAAA,EACT;AACA,QAAM,wBAAwB,uCAAuC,EAAE;AACvE,SAAO;AACT;AACA,SAAS,uCAAuC,IAAI;AAClD,QAAM,YAAY,iBAAiB,EAAE;AACrC,QAAM,UAAU,GAAG,cAAc;AACjC,KAAG,YAAY,GAAG,YAAY,OAAO;AACrC,QAAM,QAAQ;AACd,QAAM,SAAS;AACf,KAAG,WAAW,GAAG,YAAY,GAAG,UAAU,qBAAqB,OAAO,QAAQ,GAAG,UAAU,oBAAoB,UAAU,kBAAkB,IAAI;AAC/I,QAAM,cAAc,GAAG,kBAAkB;AACzC,KAAG,gBAAgB,GAAG,aAAa,WAAW;AAC9C,KAAG,qBAAqB,GAAG,aAAa,GAAG,mBAAmB,GAAG,YAAY,SAAS,CAAC;AACvF,QAAM,wBAAwB,GAAG,uBAAuB,GAAG,WAAW,MAAM,GAAG;AAC/E,KAAG,YAAY,GAAG,YAAY,IAAI;AAClC,KAAG,gBAAgB,GAAG,aAAa,IAAI;AACvC,KAAG,cAAc,OAAO;AACxB,KAAG,kBAAkB,WAAW;AAChC,SAAO;AACT;AACA,SAAS,2CAA2C,IAAI,2BAA2B;AACjF,QAAM,YAAY,iBAAiB,IAAI,yBAAyB;AAChE,QAAM,UAAU,GAAG,cAAc;AACjC,KAAG,YAAY,GAAG,YAAY,OAAO;AACrC,QAAM,QAAQ;AACd,QAAM,SAAS;AACf,KAAG,WAAW,GAAG,YAAY,GAAG,UAAU,yBAAyB,OAAO,QAAQ,GAAG,UAAU,oBAAoB,UAAU,sBAAsB,IAAI;AACvJ,QAAM,cAAc,GAAG,kBAAkB;AACzC,KAAG,gBAAgB,GAAG,aAAa,WAAW;AAC9C,KAAG,qBAAqB,GAAG,aAAa,GAAG,mBAAmB,GAAG,YAAY,SAAS,CAAC;AACvF,QAAM,wBAAwB,GAAG,uBAAuB,GAAG,WAAW,MAAM,GAAG;AAC/E,KAAG,YAAY,GAAG,YAAY,IAAI;AAClC,KAAG,gBAAgB,GAAG,aAAa,IAAI;AACvC,KAAG,cAAc,OAAO;AACxB,KAAG,kBAAkB,WAAW;AAChC,SAAO;AACT;AACA,SAAS,oBAAoB,cAAc;AACzC,MAAI,iBAAiB,GAAG;AACtB,WAAO;AAAA,EACT;AACA,QAAM,KAAK,gBAAgB,YAAY;AACvC,QAAM,YAAY,GAAG,aAAa;AAClC,SAAO;AACT;AACA,SAAS,kBAAkB,SAAS,QAAQ;AAC1C,MAAI,CAAC,MAAM,QAAQ,OAAO,GAAG;AAC3B,cAAU,CAAC,OAAO;AAAA,EACpB;AACA,UAAQ,QAAQ,CAAC,OAAO;AACtB,QAAI,MAAM,MAAM;AACd,mBAAa,OAAO,GAAG,UAAU,aAAa,MAAM,GAAG,iEAAiE;AAAA,IAC1H;AAAA,EACF,CAAC;AACH;AAGA,IAAI,OAAO,IAAI;AACf,KAAK,aAAa,aAAa,MAAM,KAAK,UAAU,eAAe,IAAI,CAAC;AACxE,KAAK,aAAa,iBAAiB,MAAM;AACvC,MAAI,sBAAsB,CAAC,GAAG;AAC5B,WAAO;AAAA,EACT,WAAW,sBAAsB,CAAC,GAAG;AACnC,WAAO;AAAA,EACT;AACA,SAAO;AACT,CAAC;AACD,KAAK,aAAa,kCAAkC,MAAM,KAAK;AAC/D,KAAK,aAAa,0BAA0B,MAAM,KAAK,IAAI,eAAe,MAAM,CAAC;AACjF,KAAK,aAAa,qBAAqB,MAAM,IAAI;AACjD,KAAK,aAAa,4BAA4B,MAAM,KAAK;AACzD,KAAK,aAAa,cAAc,MAAM,KAAK,QAAQ,WAAW,CAAC;AAC/D,KAAK,aAAa,4BAA4B,MAAM,KAAK,QAAQ,YAAY,CAAC;AAC9E,KAAK,aAAa,mBAAmB,MAAM,KAAK,QAAQ,YAAY,CAAC;AACrE,KAAK,aAAa,4BAA4B,MAAM,KAAK,QAAQ,YAAY,CAAC;AAC9E,KAAK,aAAa,gCAAgC,MAAM,KAAK,QAAQ,YAAY,CAAC;AAClF,KAAK,aAAa,+BAA+B,MAAM,KAAK,QAAQ,YAAY,CAAC;AACjF,KAAK,aAAa,+BAA+B,MAAM,KAAK,QAAQ,YAAY,CAAC;AACjF,KAAK,aAAa,+BAA+B,MAAM,KAAK,QAAQ,YAAY,CAAC;AACjF,KAAK,aAAa,qBAAqB,MAAM,KAAK,QAAQ,YAAY,CAAC;AACvE,KAAK,aAAa,uBAAuB,MAAM,KAAK,QAAQ,YAAY,CAAC;AACzE,KAAK,aAAa,qBAAqB,MAAM,KAAK,QAAQ,YAAY,CAAC;AACvE,KAAK,aAAa,0BAA0B,MAAM,uBAAuB,KAAK,UAAU,eAAe,CAAC,CAAC;AACzG,KAAK,aAAa,gCAAgC,MAAM,uBAAuB,KAAK,UAAU,eAAe,CAAC,CAAC;AAC/G,KAAK,aAAa,gDAAgD,MAAM;AACtE,QAAM,eAAe,KAAK,UAAU,eAAe;AACnD,MAAI,iBAAiB,GAAG;AACtB,WAAO;AAAA,EACT;AACA,SAAO,kCAAkC,YAAY;AACvD,CAAC;AACD,KAAK,aAAa,iDAAiD,MAAM,KAAK,UAAU,8CAA8C,IAAI,KAAK,CAAC,oBAAoB,SAAS,CAAC;AAC9K,KAAK,aAAa,gCAAgC,MAAM,mCAAmC,KAAK,UAAU,eAAe,CAAC,CAAC;AAC3H,KAAK,aAAa,gCAAgC,MAAM;AACtD,SAAO,KAAK,QAAQ,0BAA0B,IAAI,QAAQ,KAAK,QAAQ,8BAA8B;AACvG,CAAC;AACD,KAAK,aAAa,gCAAgC,MAAM,8BAA8B,KAAK,UAAU,eAAe,CAAC,CAAC;AACtH,KAAK,aAAa,2BAA2B,MAAM,oBAAoB,KAAK,UAAU,eAAe,CAAC,CAAC;AACvG,KAAK,aAAa,6BAA6B,MAAM;AACnD,QAAM,cAAc,KAAK,QAAQ,8BAA8B;AAC/D,SAAO,cAAc,IAAI;AAC3B,CAAC;AACD,KAAK,aAAa,kCAAkC,MAAM;AACxD,SAAO;AACT,GAAG,CAAC,eAAe;AACjB,MAAI,aAAa,KAAK,eAAe,IAAI;AACvC,UAAM,IAAI,MAAM,8FAA8F,aAAa;AAAA,EAC7H;AACF,CAAC;AACD,KAAK,aAAa,yBAAyB,MAAM;AAC/C,SAAO,oBAAoB,SAAS,IAAI,IAAI;AAC9C,GAAG,CAAC,eAAe;AACjB,MAAI,aAAa,KAAK,eAAe,IAAI;AACvC,UAAM,IAAI,MAAM,2FAA2F,aAAa;AAAA,EAC1H;AACF,CAAC;AACD,KAAK,aAAa,8BAA8B,MAAM,GAAG;AACzD,KAAK,aAAa,6BAA6B,MAAM,KAAK;AAC1D,KAAK,aAAa,4CAA4C,MAAM,GAAG;AACvE,KAAK,aAAa,gCAAgC,MAAM,GAAG;AAG3D,SAAS,qBAAqB;AAC5B,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,eAAW;AACX,gBAAY;AACZ,gBAAY;AACZ,gBAAY;AACZ,gBAAY;AACZ,aAAS;AACT,mBAAe;AACf,uBAAmB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAanB,uBAAmB;AACnB,kBAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAUhB,OAAO;AACL,eAAW;AACX,gBAAY;AACZ,gBAAY;AACZ,gBAAY;AACZ,gBAAY;AACZ,aAAS;AACT,mBAAe;AACf,uBAAmB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AASnB,uBAAmB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUnB,kBAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAShB;AACA,SAAO;AAAA,IACL,SAAS;AAAA,IACT;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AAGA,SAAS,mCAAmC,SAAS,OAAOS,SAAQ,SAAS;AAC3E,QAAMG,WAAU,aAAa,eAAe,KAAK;AACjD,SAAOA,SAAQ,IAAI,CAAC,QAAQ,OAAO;AACjC,UAAM,QAAQ,OAAO,QAAQ,SAASH,YAAW;AACjD,UAAM,QAAQ,OAAOG,SAAQ,SAAS,IAAI,OAAO,QAAQ,KAAK,QAAQH,YAAW,QAAQ,SAAS,WAAW,YAAY,QAAQ,SAAS;AAC1I,WAAO,GAAG,UAAU;AAAA,EACtB,CAAC,EAAE,KAAK,EAAE;AACZ;AACA,SAAS,kDAAkD,SAAS,OAAOA,SAAQ,SAAS;AAC1F,QAAMG,WAAU,aAAa,eAAe,KAAK;AACjD,SAAOA,SAAQ,IAAI,CAAC,GAAG,OAAO;AAC5B,UAAM,QAAQ,OAAO,QAAQ,SAASH,4BAA2B;AACjE,UAAM,QAAQ,OAAOG,SAAQ,SAAS,IAAI,OAAO,QAAQ,KAAK,QAAQH,YAAW,QAAQ,yBAAyB,QAAQ,YAAY,QAAQ,yBAAyB;AACvK,WAAO,GAAG,UAAU;AAAA,EACtB,CAAC,EAAE,KAAK,EAAE;AACZ;AACA,SAAS,2BAA2B,YAAY,cAAc;AAC5D,QAAM,YAAY,WAAW;AAC7B,QAAM,QAAQ,WAAW,IAAI,CAAC,MAAM,GAAG,gBAAgB,IAAI;AAC3D,QAAMG,WAAU,IAAI,MAAM,YAAY,CAAC;AACvC,EAAAA,SAAQ,YAAY,KAAK,MAAM,YAAY;AAC3C,WAAS,KAAK,YAAY,GAAG,MAAM,GAAG,EAAE,IAAI;AAC1C,IAAAA,SAAQ,MAAM,IAAIA,SAAQ,KAAK,QAAQ,MAAM,KAAK;AAAA,EACpD;AACA,SAAOA;AACT;AACA,SAAS,4CAA4C,SAAS,cAAcH,SAAQ,SAAS;AAC3F,QAAM,eAAe,QAAQ,IAAI,CAAC,GAAG,OAAO,EAAE;AAC9C,QAAMG,WAAU,2BAA2B,cAAc,YAAY;AACrE,SAAOA,SAAQ,IAAI,CAAC,GAAG,OAAO;AAC5B,UAAM,QAAQ,OAAO,QAAQ,SAASH,YAAWG,SAAQ;AACzD,UAAM,QAAQ,OAAOA,SAAQ,SAAS,IAAI,OAAO,QAAQ,KAAK,QAAQH,YAAW,QAAQ,SAASG,SAAQ,QAAQ,YAAY,QAAQ,SAASA,SAAQ;AACvJ,WAAO,GAAG,UAAU;AAAA,EACtB,CAAC,EAAE,KAAK,EAAE;AACZ;AACA,SAAS,mBAAmB,OAAO;AACjC,QAAMA,WAAU,aAAa,eAAe,KAAK,EAAE,IAAI,CAAC,MAAM,EAAE,SAAS,CAAC;AAC1E,SAAO;AAAA;AAAA,wBAEeA,SAAQ,mBAAmBA,SAAQ;AAAA;AAAA;AAG3D;AACA,SAAS,2BAA2B;AAClC,SAAO;AAAA;AAAA;AAAA;AAAA;AAKT;AACA,IAAI,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AA0C3B,IAAI,EAAE,kBAAkB,kBAAkB,IAAI;AAC9C,SAAS,WAAW,YAAY,aAAa,SAAS;AACpD,QAAM,iBAAiB,CAAC;AACxB,aAAW,QAAQ,CAAC,MAAM;AACxB,UAAMZ,QAAO,aAAa,cAAc,EAAE,UAAU,YAAY;AAChE,QAAI,EAAE,UAAU,WAAW;AACzB,qBAAe,KAAK,iBAAiB,EAAE,OAAOA,QAAO,IAAI,IAAIA,WAAU,KAAK;AAAA,IAC9E,OAAO;AACL,qBAAe,KAAK,qBAAqB,EAAE,OAAO;AAClD,qBAAe,KAAK,qBAAqB,EAAE,OAAO;AAAA,IACpD;AACA,QAAI,QAAQ,qBAAqB;AAC/B,YAAM,EAAE,aAAa,IAAI,wBAAwB,QAAQ,cAAc,EAAE,UAAU,cAAc,EAAE,UAAU,QAAQ;AACrH,cAAQ,aAAa;AAAA,aACd;AACH,yBAAe,KAAK,eAAe,EAAE,YAAY;AACjD;AAAA,aACG;AACH,yBAAe,KAAK,iBAAiB,EAAE,YAAY;AACnD;AAAA,aACG;AACH,yBAAe,KAAK,iBAAiB,EAAE,YAAY;AACnD;AAAA,aACG;AACH,yBAAe,KAAK,iBAAiB,EAAE,YAAY;AACnD;AAAA;AAEA;AAAA;AAEJ,qBAAe,KAAK,iBAAiB,EAAE,eAAe;AAAA,IACxD;AAAA,EACF,CAAC;AACD,MAAI,QAAQ,qBAAqB;AAC/B,YAAQ,YAAY,aAAa;AAAA,WAC1B;AACH,uBAAe,KAAK,uBAAuB;AAC3C;AAAA,WACG;AACH,uBAAe,KAAK,yBAAyB;AAC7C,uBAAe,KAAK,8BAA8B;AAClD;AAAA,WACG;AACH,uBAAe,KAAK,yBAAyB;AAC7C,uBAAe,KAAK,gCAAgC;AACpD;AAAA,WACG;AACH,uBAAe,KAAK,yBAAyB;AAC7C,uBAAe,KAAK,gCAAgC;AACpD;AAAA;AAEA;AAAA;AAEJ,mBAAe,KAAK,4BAA4B;AAAA,EAClD;AACA,MAAI,QAAQ,gBAAgB;AAC1B,YAAQ,eAAe,QAAQ,CAAC,MAAM;AACpC,qBAAe,KAAK,WAAW,EAAE,QAAQ,EAAE,OAAO,EAAE,aAAa,IAAI,EAAE,gBAAgB,KAAK;AAAA,IAC9F,CAAC;AAAA,EACH;AACA,QAAM,qBAAqB,eAAe,KAAK,IAAI;AACnD,QAAM,uBAAuB,WAAW,IAAI,CAAC,MAAM,wBAAwB,GAAG,aAAa,QAAQ,cAAc,QAAQ,mBAAmB,CAAC,EAAE,KAAK,IAAI;AACxJ,QAAM,cAAc,YAAY;AAChC,QAAM,OAAO,mBAAmB;AAChC,QAAM,4BAA4B,6BAA6B,IAAI;AACnE,MAAI;AACJ,MAAI;AACJ,MAAI,eAAe,gBAAgB,IAAI;AACvC,MAAI,YAAY,UAAU;AACxB,4BAAwB,+BAA+B,YAAY,cAAc,aAAa,QAAQ,mBAAmB;AACzH,mCAA+B,8BAA8B,IAAI;AAAA,EACnE,OAAO;AACL,4BAAwB,yBAAyB,YAAY,cAAc,aAAa,QAAQ,mBAAmB;AACnH,mCAA+B,2BAA2B,IAAI;AAAA,EAChE;AACA,MAAI,QAAQ,cAAc;AACxB,oBAAgB;AAAA,EAClB;AACA,QAAM,SAAS;AAAA,IACb;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA,QAAQ;AAAA,EACV,EAAE,KAAK,IAAI;AACX,SAAO;AACT;AACA,SAAS,qBAAqB,QAAQ,sBAAsB,OAAO;AACjE,QAAM,QAAQ,OAAO,UAAU;AAC/B,UAAQ,MAAM;AAAA,SACP;AACH,aAAO,iBAAiB,QAAQ,mBAAmB;AAAA,SAChD;AACH,aAAO,aAAa,QAAQ,mBAAmB;AAAA,SAC5C;AACH,aAAO,aAAa,QAAQ,mBAAmB;AAAA,SAC5C;AACH,aAAO,aAAa,QAAQ,mBAAmB;AAAA,SAC5C;AACH,aAAO,aAAa,QAAQ,mBAAmB;AAAA,SAC5C;AACH,aAAO,aAAa,MAAM;AAAA,SACvB;AACH,aAAO,aAAa,MAAM;AAAA;AAE1B,YAAM,IAAI,MAAM,GAAG,MAAM,8CAA8C;AAAA;AAE7E;AACA,SAAS,2BAA2B,QAAQ,qBAAqB;AAC/D,QAAM,QAAQ,OAAO,UAAU;AAC/B,UAAQ,MAAM;AAAA,SACP;AACH,aAAO,uBAAuB,MAAM;AAAA,SACjC;AACH,aAAO,mBAAmB,QAAQ,mBAAmB;AAAA,SAClD;AACH,aAAO,mBAAmB,QAAQ,mBAAmB;AAAA,SAClD;AACH,aAAO,mBAAmB,QAAQ,mBAAmB;AAAA;AAErD,aAAO,mBAAmB,QAAQ,mBAAmB;AAAA;AAE3D;AACA,SAAS,wBAAwB,QAAQ,cAAc,qBAAqB,OAAO,qBAAqB;AACtG,MAAI,MAAM;AACV,MAAI,oBAAoB;AACtB,WAAO,2BAA2B,QAAQ,mBAAmB;AAAA,EAC/D,OAAO;AACL,WAAO,qBAAqB,QAAQ,mBAAmB;AAAA,EACzD;AACA,QAAM,UAAU,OAAO,UAAU;AACjC,QAAM,WAAW,aAAa;AAC9B,MAAI,QAAQ,UAAU,SAAS,QAAQ;AACrC,QAAI,oBAAoB;AACtB,aAAO,+BAA+B,QAAQ,YAAY;AAAA,IAC5D,OAAO;AACL,aAAO,yBAAyB,QAAQ,YAAY;AAAA,IACtD;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,+BAA+B,UAAU,aAAa,qBAAqB;AAClF,UAAQ,SAAS;AAAA,SACV;AACH,aAAO,sBAAsB;AAAA,SAC1B;AACH,aAAO,wBAAwB,UAAU,aAAa,mBAAmB;AAAA,SACtE;AACH,aAAO,wBAAwB,UAAU,aAAa,mBAAmB;AAAA,SACtE;AACH,aAAO,wBAAwB,UAAU,aAAa,mBAAmB;AAAA;AAEzE,aAAO,wBAAwB,UAAU,aAAa,mBAAmB;AAAA;AAE/E;AACA,SAAS,yBAAyB,UAAU,aAAa,qBAAqB;AAC5E,UAAQ,SAAS;AAAA,SACV;AACH,aAAO,sBAAsB;AAAA,SAC1B;AACH,aAAO,kBAAkB,UAAU,aAAa,mBAAmB;AAAA,SAChE;AACH,aAAO,kBAAkB,UAAU,aAAa,mBAAmB;AAAA,SAChE;AACH,aAAO,kBAAkB,UAAU,aAAa,mBAAmB;AAAA,SAChE;AACH,aAAO,kBAAkB,UAAU,aAAa,mBAAmB;AAAA,SAChE;AACH,aAAO,kBAAkB,UAAU,WAAW;AAAA,SAC3C;AACH,aAAO,kBAAkB,UAAU,WAAW;AAAA;AAE9C,YAAM,IAAI,MAAM,GAAG,SAAS,+CAA+C;AAAA;AAEjF;AACA,SAAS,6BAA6B,MAAM;AAC1C,SAAO;AAAA;AAAA,eAEM,KAAK;AAAA;AAAA;AAGpB;AACA,SAAS,2BAA2B,MAAM;AACxC,SAAO;AAAA;AAAA,QAED,KAAK;AAAA;AAAA;AAGb;AACA,SAAS,8BAA8B,MAAM;AAC3C,SAAO;AAAA;AAAA,QAED,KAAK;AAAA;AAAA;AAGb;AACA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,gBAAgB,GAAG,KAAK;AAAA;AAAA;AAAA;AAAA,MAI1B,KAAK;AAAA,MACL,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,MAuBL,KAAK;AAAA,MACL,KAAK;AAAA,MACL,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,MAyBL;AAAA,MACA;AAAA,MACA;AAAA;AAEJ,SAAO;AACT;AACA,IAAI,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAaxB,IAAI,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AASxB,IAAI,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUxB,IAAI,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAY3B,SAAS,wBAAwB;AAC/B,SAAO;AAAA;AAAA;AAAA;AAAA;AAKT;AACA,SAAS,wBAAwB,OAAO,UAAU,qBAAqB;AACrE,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,MAAI,eAAe,OAAO,GAAG;AAC3B,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA,IAKT;AACA,WAAO;AAAA;AAAA,sCAE2B,eAAe;AAAA;AAAA;AAAA,EAGnD;AACA,MAAI,eAAe,OAAO,GAAG;AAC3B,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA,IAKT;AACA,WAAO;AAAA;AAAA,sCAE2B,eAAe;AAAA;AAAA;AAAA,EAGnD;AACA,MAAI,qBAAqB;AACvB,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAQT;AACA,SAAO;AAAA;AAAA;AAAA,oCAG2B,eAAe,OAAO,eAAe;AAAA,iCACxC,eAAe;AAAA;AAAA;AAGhD;AACA,SAAS,kBAAkB,OAAO,UAAU,qBAAqB;AAC/D,MAAI,SAAS,OAAO,GAAG;AACrB,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA,IAKT;AACA,WAAO;AAAA;AAAA,kCAEuB,SAAS;AAAA;AAAA;AAAA,EAGzC;AACA,MAAI,SAAS,OAAO,GAAG;AACrB,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA,IAKT;AACA,WAAO;AAAA;AAAA,kCAEuB,SAAS;AAAA;AAAA;AAAA,EAGzC;AACA,MAAI,qBAAqB;AACvB,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAOT;AACA,SAAO;AAAA;AAAA;AAAA,oCAG2B,SAAS,OAAO,SAAS;AAAA,4BACjC,SAAS;AAAA;AAAA;AAGrC;AACA,SAAS,wBAAwB,OAAO,UAAU,qBAAqB;AACrE,MAAI,qBAAqB;AACvB,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAkBT;AACA,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,QAAM,qBAAqB,KAAK,KAAK,MAAM,KAAK,CAAC;AACjD,QAAM,gBAAgB,qBAAqB,KAAK,KAAK,MAAM,KAAK,CAAC;AACjE,SAAO;AAAA;AAAA;AAAA,oCAG2B,eAAe,OAAO,eAAe;AAAA,iCACxC,eAAe;AAAA;AAAA,wBAExB;AAAA,qBACH;AAAA;AAAA,6BAEQ;AAAA,4BACD;AAAA;AAAA;AAAA;AAAA;AAK5B;AACA,SAAS,kBAAkB,OAAO,UAAU,qBAAqB;AAC/D,MAAI,qBAAqB;AACvB,UAAM,0BAA0B,kDAAkD,CAAC,KAAK,KAAK,GAAG,GAAG,KAAK;AACxG,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA,MAKL;AAAA;AAAA;AAAA;AAAA,EAIJ;AACA,QAAM,yBAAyB,mCAAmC,CAAC,KAAK,KAAK,GAAG,GAAG,KAAK;AACxF,SAAO;AAAA;AAAA;AAAA,oCAG2B,SAAS,OAAO,SAAS;AAAA,iCAC5B,SAAS;AAAA,QAClC;AAAA;AAAA;AAAA;AAIR;AACA,SAAS,wBAAwB,OAAO,UAAU,qBAAqB;AACrE,MAAI,qBAAqB;AACvB,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAuBT;AACA,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,QAAM,qBAAqB,KAAK,KAAK,MAAM,MAAM,SAAS,KAAK,CAAC;AAChE,QAAM,gBAAgB,qBAAqB,KAAK,KAAK,MAAM,MAAM,SAAS,KAAK,CAAC;AAChF,MAAI,iBAAiB;AACrB,MAAI,UAAU;AACd,MAAI,UAAU;AACd,WAAS,IAAI,GAAG,IAAI,MAAM,SAAS,GAAG,KAAK;AACzC,sBAAkB,MAAM,MAAM,SAAS,IAAI;AAC3C,cAAU;AAAA,aACD,eAAe;AAAA,kBACV,OAAO;AAAA,QACjB;AACJ,cAAU,IAAI,QAAQ;AAAA,EACxB;AACA,SAAO;AAAA,UACC,MAAM;AAAA;AAAA,oCAEoB,eAAe,OAAO,eAAe;AAAA,iCACxC,eAAe;AAAA;AAAA,QAExC;AAAA;AAAA,wBAEgB;AAAA,qBACH;AAAA;AAAA,6BAEQ;AAAA,4BACD;AAAA;AAAA,mBAET,MAAM,UAAU;AAAA;AAAA;AAGnC;AACA,SAAS,kBAAkB,OAAO,UAAU,qBAAqB;AAC/D,MAAI,qBAAqB;AACvB,UAAM,0BAA0B,kDAAkD,CAAC,KAAK,KAAK,KAAK,IAAI,GAAG,KAAK;AAC9G,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA,QAKH;AAAA;AAAA;AAAA;AAAA,EAIN;AACA,QAAM,yBAAyB,mCAAmC,CAAC,KAAK,KAAK,KAAK,IAAI,GAAG,KAAK;AAC9F,SAAO;AAAA;AAAA;AAAA,eAGM,SAAS,OAAO,SAAS;AAAA,iCACP,SAAS;AAAA,QAClC;AAAA;AAAA;AAAA;AAIR;AACA,SAAS,kBAAkB,OAAO,UAAU;AAC1C,QAAM,yBAAyB,mCAAmC,CAAC,KAAK,KAAK,KAAK,MAAM,IAAI,GAAG,KAAK;AACpG,SAAO;AAAA;AAAA,kDAEyC,SAAS;AAAA,+BAC5B,SAAS;AAAA;AAAA,iCAEP,SAAS;AAAA;AAAA,QAElC;AAAA;AAAA;AAAA;AAAA;AAAA;AAMR;AACA,SAAS,kBAAkB,OAAO,UAAU;AAC1C,QAAM,yBAAyB,mCAAmC,CAAC,KAAK,KAAK,KAAK,MAAM,MAAM,IAAI,GAAG,KAAK;AAC1G,SAAO;AAAA;AAAA;AAAA,eAGM,SAAS,OAAO,SAAS;AAAA,iCACP,SAAS;AAAA;AAAA,QAElC;AAAA;AAAA;AAAA;AAAA;AAAA;AAMR;AACA,SAAS,wBAAwB,OAAO,UAAU,qBAAqB;AACrE,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,MAAI,aAAa,YAAY,OAAO,QAAQ,GAAG;AAC7C,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAMT;AACA,WAAO;AAAA;AAAA,8CAEmC,eAAe,OAAO,eAAe;AAAA;AAAA;AAAA,EAGjF;AACA,QAAM,qBAAqB,KAAK,KAAK,MAAM,KAAK,CAAC;AACjD,MAAI,qBAAqB;AACvB,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAcT;AACA,SAAO;AAAA;AAAA;AAAA,oCAG2B,eAAe,OAAO,eAAe;AAAA;AAAA,iCAExC,eAAe;AAAA,6BACnB;AAAA,4BACD;AAAA;AAAA;AAAA;AAAA;AAK5B;AACA,SAAS,kBAAkB,OAAO,UAAU,qBAAqB;AAC/D,MAAI,aAAa,YAAY,OAAO,QAAQ,GAAG;AAC7C,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA,IAKT;AACA,WAAO;AAAA;AAAA,0CAE+B,SAAS,OAAO,SAAS;AAAA;AAAA;AAAA,EAGjE;AACA,MAAI,MAAM,OAAO,GAAG;AAClB,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAQT;AACA,WAAO;AAAA;AAAA;AAAA,sCAG2B,SAAS,OAAO,SAAS;AAAA,mCAC5B,SAAS;AAAA;AAAA;AAAA;AAAA,EAI1C;AACA,MAAI,MAAM,OAAO,GAAG;AAClB,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAQT;AACA,WAAO;AAAA;AAAA;AAAA,sCAG2B,SAAS,OAAO,SAAS;AAAA,mCAC5B,SAAS;AAAA;AAAA;AAAA;AAAA,EAI1C;AACA,MAAI,qBAAqB;AACvB,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAUT;AACA,SAAO;AAAA;AAAA;AAAA,oCAG2B,SAAS,OAAO,SAAS;AAAA,iCAC5B,SAAS;AAAA,wBAClB,MAAM;AAAA,4BACF,MAAM;AAAA;AAAA;AAAA;AAIlC;AACA,SAAS,yBAAyB,SAAS;AACzC,SAAO,SAAS;AAClB;AACA,SAAS,uBAAuB,WAAW;AACzC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,OAAO,mBAAmB;AAChC,SAAO;AAAA,WACE;AAAA,eACI,KAAK,aAAa;AAAA;AAAA;AAGjC;AACA,SAAS,iBAAiB,WAAW,qBAAqB;AACxD,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,MAAI,UAAU,UAAU,WAAW;AACjC,WAAO,SAAS,sBAAsB;AAAA,EACxC;AACA,QAAM,CAAC,SAAS,OAAO,IAAI,UAAU,UAAU;AAC/C,MAAI,YAAY,KAAK,YAAY,GAAG;AAClC,WAAO;AAAA,cACG;AAAA,+BACiB;AAAA;AAAA;AAAA,EAG7B;AACA,QAAM,SAAS,yBAAyB,OAAO;AAC/C,MAAI,qBAAqB;AACvB,WAAO;AAAA,YACC;AAAA,6BACiB,uBAAuB,uBAAuB;AAAA,6BAC9C;AAAA;AAAA;AAAA,EAG3B;AACA,QAAM,CAAC,OAAO,KAAK,IAAI,UAAU,UAAU;AAC3C,SAAO;AAAA,YACG;AAAA,6BACiB,UAAU,UAAU;AAAA,6BACpB;AAAA;AAAA;AAG7B;AACA,SAAS,mBAAmB,WAAW,qBAAqB;AAC1D,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,OAAO,mBAAmB;AAChC,MAAI,qBAAqB;AACvB,WAAO;AAAA,WACA;AAAA,gDACqC,0CAA0C;AAAA;AAAA;AAAA,eAG3E,KAAK,aAAa;AAAA;AAAA;AAAA,EAG/B;AACA,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,SAAO;AAAA,WACE;AAAA;AAAA,UAED,eAAe,OAAO,eAAe;AAAA,eAChC,KAAK,aAAa;AAAA;AAAA;AAGjC;AACA,SAAS,aAAa,WAAW,qBAAqB;AACpD,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,MAAI,UAAU,UAAU,WAAW;AACjC,WAAO;AAAA,cACG;AAAA,UACJ,kBAAkB,SAAS;AAAA;AAAA;AAAA,EAGnC;AACA,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,QAAQ,SAAS;AACvB,QAAM,QAAQ,SAAS;AACvB,MAAI,UAAU,KAAK,UAAU,GAAG;AAC9B,WAAO;AAAA,cACG;AAAA,+BACiB;AAAA;AAAA;AAAA,EAG7B;AACA,QAAM,SAAS,yBAAyB,OAAO;AAC/C,MAAI,UAAU,GAAG;AACf,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,6CAC+B,0BAA0B;AAAA,+BACxC;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,cACG;AAAA,6CAC+B,oBAAoB;AAAA,+BAClC;AAAA;AAAA;AAAA,EAG7B;AACA,MAAI,UAAU,GAAG;AACf,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,wCAC0B,0BAA0B;AAAA,+BACnC;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,cACG;AAAA,wCAC0B,oBAAoB;AAAA,+BAC7B;AAAA;AAAA;AAAA,EAG7B;AACA,MAAI,qBAAqB;AACvB,WAAO;AAAA,YACC;AAAA,6BACiB,uBAAuB,+BAA+B;AAAA,6BACtD;AAAA;AAAA;AAAA,EAG3B;AACA,SAAO;AAAA,YACG;AAAA,6BACiB,UAAU,kBAAkB;AAAA,6BAC5B;AAAA;AAAA;AAG7B;AACA,SAAS,mBAAmB,WAAW,qBAAqB;AAC1D,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,UAAU,SAAS;AACzB,QAAM,UAAU,SAAS;AACzB,QAAM,OAAO,mBAAmB;AAChC,MAAI,YAAY,QAAQ,aAAa,YAAY,OAAO,QAAQ,GAAG;AACjE,QAAI,qBAAqB;AACvB,aAAO;AAAA,aACA;AAAA,qDACwC,uBAAuB;AAAA;AAAA,iBAE3D,KAAK,aAAa;AAAA;AAAA;AAAA,IAG/B;AACA,WAAO;AAAA,aACE;AAAA,qDACwC,cAAc;AAAA;AAAA,iBAElD,KAAK,aAAa;AAAA;AAAA;AAAA,EAGjC;AACA,MAAI,qBAAqB;AACvB,WAAO;AAAA,WACA;AAAA,gDACqC,0CAA0C;AAAA,0CAChD;AAAA;AAAA,eAE3B,KAAK,aAAa;AAAA;AAAA;AAAA,EAG/B;AACA,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,QAAM,eAAe,KAAK,KAAK,MAAM,KAAK,CAAC;AAC3C,SAAO;AAAA,WACE;AAAA,iCACsB,iBAAiB,eAAe,OAAO,eAAe;AAAA,eACxE,KAAK,aAAa;AAAA;AAAA;AAGjC;AACA,SAAS,aAAa,WAAW,qBAAqB;AACpD,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,WAAW,UAAU,UAAU;AACrC,MAAI,YAAY,QAAQ,aAAa,YAAY,OAAO,QAAQ,GAAG;AACjE,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,qDACuC,uBAAuB;AAAA,+BAC7C;AAAA;AAAA;AAAA,IAG3B;AACA,UAAM,WAAW,SAAS;AAC1B,UAAM,WAAW,SAAS;AAC1B,WAAO;AAAA,YACC;AAAA,mDACuC,eAAe;AAAA,6BACrC;AAAA;AAAA;AAAA,EAG3B;AACA,QAAM,EAAE,UAAU,SAAS,IAAI,aAAa,aAAa,KAAK;AAC9D,QAAM,gBAAgB;AACtB,MAAI,cAAc,SAAS,MAAM,QAAQ;AACvC,UAAM,eAAe,iBAAiB,WAAW,aAAa;AAC9D,UAAM,SAAS,CAAC,OAAO,KAAK;AAC5B,WAAO;AAAA,QACH,qBAAqB,cAAc,mBAAmB;AAAA,cAChD;AAAA,iBACG,YAAY,kBAAkB,QAAQ,QAAQ;AAAA;AAAA;AAAA,EAG7D;AACA,MAAI,UAAU,UAAU,WAAW;AACjC,WAAO;AAAA,cACG;AAAA,qDACuC,MAAM;AAAA,UACjD,kBAAkB,SAAS;AAAA;AAAA;AAAA,EAGnC;AACA,QAAM,UAAU,SAAS;AACzB,QAAM,UAAU,SAAS;AACzB,QAAM,SAAS,yBAAyB,OAAO;AAC/C,MAAI,YAAY,GAAG;AACjB,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,2CAC6B,iBAAiB;AAAA,oDACR;AAAA,+BACrB;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,YACC;AAAA,yCAC6B,iBAAiB,MAAM;AAAA,4CACpB;AAAA,6BACf;AAAA;AAAA;AAAA,EAG3B;AACA,MAAI,YAAY,GAAG;AACjB,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,2CAC6B,iBAAiB;AAAA,+CACb;AAAA,+BAChB;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,YACC;AAAA,yCAC6B,iBAAiB,MAAM;AAAA,uCACzB;AAAA,6BACV;AAAA;AAAA;AAAA,EAG3B;AACA,MAAI,qBAAqB;AACvB,WAAO;AAAA,cACG;AAAA;AAAA,4BAEc,2BAA2B;AAAA,+BACxB,uBAAuB;AAAA,+BACvB;AAAA;AAAA;AAAA,EAG7B;AACA,SAAO;AAAA,UACC;AAAA;AAAA,wBAEc,MAAM,cAAc;AAAA,2BACjB,YAAY;AAAA,2BACZ;AAAA;AAAA;AAG3B;AACA,SAAS,mBAAmB,WAAW,qBAAqB;AAC1D,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,MAAI,MAAM,OAAO,GAAG;AAClB,UAAM,gBAAgB,MAAM,MAAM,CAAC;AACnC,UAAM,WAAW,CAAC,GAAG,CAAC;AACtB,UAAM,eAAe,iBAAiB,WAAW,aAAa;AAC9D,UAAM,SAAS,CAAC,KAAK,OAAO,KAAK;AACjC,WAAO;AAAA,UACD,2BAA2B,cAAc,mBAAmB;AAAA,eACvD;AAAA,mBACI,YAAY,kBAAkB,QAAQ,QAAQ;AAAA;AAAA;AAAA,EAG/D;AACA,QAAM,OAAO,mBAAmB;AAChC,MAAI,qBAAqB;AACvB,WAAO;AAAA,WACA;AAAA,gDACqC,0CAA0C;AAAA,0CAChD;AAAA,0DACgB;AAAA;AAAA;AAAA,eAG3C,KAAK,aAAa;AAAA;AAAA;AAAA,EAG/B;AACA,QAAM,UAAU,eAAe;AAC/B,QAAM,UAAU,eAAe;AAC/B,QAAM,eAAe,KAAK,KAAK,MAAM,KAAK,CAAC;AAC3C,QAAM,gBAAgB,eAAe,KAAK,KAAK,MAAM,KAAK,CAAC;AAC3D,SAAO;AAAA,WACE;AAAA;AAAA,UAED,YAAY,YAAY,kBAAkB;AAAA,eACrC,KAAK,aAAa;AAAA;AAAA;AAGjC;AACA,SAAS,aAAa,WAAW,qBAAqB;AACpD,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,UAAU,MAAM,KAAK,MAAM;AACjC,QAAM,UAAU,MAAM;AACtB,QAAM,EAAE,UAAU,SAAS,IAAI,aAAa,aAAa,KAAK;AAC9D,QAAM,gBAAgB;AACtB,MAAI,cAAc,SAAS,MAAM,QAAQ;AACvC,UAAM,eAAe,iBAAiB,WAAW,aAAa;AAC9D,UAAM,SAAS,CAAC,OAAO,OAAO,OAAO;AACrC,WAAO;AAAA,UACD,qBAAqB,cAAc,mBAAmB;AAAA,gBAChD;AAAA,mBACG,YAAY,kBAAkB,QAAQ,QAAQ;AAAA;AAAA;AAAA,EAG/D;AACA,MAAI,UAAU,UAAU,WAAW;AACjC,WAAO;AAAA,cACG;AAAA;AAAA,iCAEmB,YAAY;AAAA,UACnC,kBAAkB,SAAS;AAAA;AAAA;AAAA,EAGnC;AACA,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,UAAU,SAAS;AACzB,QAAM,UAAU,SAAS;AACzB,QAAM,aAAa,UAAU,UAAU;AACvC,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,wBACU;AAAA;AAAA;AAAA;AAAA,0BAIE,uBAAuB;AAAA,+BAClB;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,gBACK;AAAA;AAAA,oDAEoC;AAAA;AAAA,4BAExB,cAAc;AAAA,iCACT;AAAA;AAAA;AAAA,EAG/B;AACA,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,gDACkC;AAAA;AAAA,uDAEO,uBAAuB;AAAA,+BAC/C;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,YACC;AAAA,8CACkC,MAAM;AAAA;AAAA,qDAEC,cAAc;AAAA,6BACtC;AAAA;AAAA;AAAA,EAG3B;AACA,QAAM,SAAS,yBAAyB,OAAO;AAC/C,MAAI,qBAAqB;AACvB,WAAO;AAAA,YACC;AAAA;AAAA,sBAEU,qBAAqB;AAAA,sBACrB;AAAA,0BACI,mBAAmB,qBAAqB;AAAA,6BACrC,uBAAuB;AAAA,6BACvB;AAAA;AAAA;AAAA,EAG3B;AACA,SAAO;AAAA,cACK;AAAA;AAAA,4BAEc,mBAAmB,qBAAqB;AAAA,+BACrC,YAAY;AAAA,+BACZ;AAAA;AAAA;AAG/B;AACA,SAAS,mBAAmB,WAAW,qBAAqB;AAC1D,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,OAAO,mBAAmB;AAChC,MAAI,qBAAqB;AACvB,WAAO;AAAA,WACA;AAAA,0CAC+B;AAAA,0DACgB;AAAA;AAAA,yBAEjC;AAAA;AAAA,gDAEuB,0CAA0C;AAAA;AAAA;AAAA,mGAGS,KAAK,aAAa;AAAA;AAAA;AAAA,EAGnH;AACA,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,OAAO,MAAM;AACnB,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,QAAM,UAAU,eAAe;AAC/B,QAAM,UAAU,eAAe;AAC/B,QAAM,eAAe,KAAK,KAAK,MAAM,OAAO,KAAK,CAAC;AAClD,MAAI,gBAAgB,eAAe,KAAK,KAAK,MAAM,OAAO,KAAK,CAAC;AAChE,MAAI,SAAS;AACb,MAAIS,SAAQ,OAAO,+BAA+B;AAClD,WAAS,IAAI,GAAG,IAAI,OAAO,GAAG,KAAK;AACjC,aAAS,QAAQ,QAAQ;AACzB,qBAAiB,MAAM,OAAO,IAAI;AAClC,IAAAA,SAAQ,IAAI,OAAO,qBAAqBA;AAAA,EAC1C;AACA,SAAO;AAAA,WACE,YAAY;AAAA,oBACHA;AAAA,2BACO;AAAA,kCACO;AAAA,qDACmB,YAAY;AAAA,eAClD,KAAK,aAAa;AAAA;AAAA;AAGjC;AACA,SAAS,aAAa,WAAW,qBAAqB;AACpD,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,UAAU,MAAM;AACtB,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,EAAE,UAAU,SAAS,IAAI,aAAa,aAAa,KAAK;AAC9D,MAAI,SAAS,SAAS,MAAM,QAAQ;AAClC,UAAM,eAAe,iBAAiB,WAAW,QAAQ;AACzD,UAAM,SAAS,CAAC,OAAO,OAAO,SAAS,QAAQ;AAC/C,WAAO;AAAA,QACH,qBAAqB,cAAc,mBAAmB;AAAA,cAChD;AAAA,iBACG,YAAY,kBAAkB,QAAQ,QAAQ;AAAA;AAAA;AAAA,EAG7D;AACA,MAAI,UAAU,UAAU,WAAW;AACjC,WAAO;AAAA,cACG;AAAA;AAAA,iCAEmB,YAAY,YAAY;AAAA,UAC/C,kBAAkB,SAAS;AAAA;AAAA;AAAA,EAGnC;AACA,QAAM,aAAa,UAAU,UAAU;AACvC,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,UAAU,SAAS;AACzB,QAAM,UAAU,SAAS;AACzB,QAAM,aAAa,iBAAiB;AACpC,QAAM,aAAa,iBAAiB;AACpC,QAAM,aAAa,iBAAiB;AACpC,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,UACJ;AAAA,UACA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0BAMgB,uBAAuB;AAAA,+BAClB;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,cACG;AAAA;AAAA;AAAA;AAAA,uBAIS,YAAY;AAAA;AAAA,0BAET,cAAc;AAAA,+BACT;AAAA;AAAA;AAAA,EAG7B;AACA,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA;AAAA,gCAEkB,qBAAqB,oBAAoB;AAAA;AAAA;AAAA,yBAGhD,uBAAuB;AAAA,+BACjB;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,cACG;AAAA;AAAA,gCAEkB,MAAM,KAAK,MAAM,OAAO,MAAM;AAAA;AAAA;AAAA,yBAGrC,cAAc;AAAA,+BACR;AAAA;AAAA;AAAA,EAG7B;AACA,QAAM,SAAS,yBAAyB,OAAO;AAC/C,MAAI,qBAAqB;AACvB,WAAO;AAAA,YACC;AAAA;AAAA,QAEJ;AAAA,QACA;AAAA,QACA;AAAA;AAAA;AAAA,6BAGqB,uBAAuB,+BAA+B;AAAA,6BACtD;AAAA;AAAA;AAAA,EAG3B;AACA,SAAO;AAAA,YACG;AAAA;AAAA,0BAEc,mBAAmB;AAAA,oBACzB;AAAA,6BACS,YAAY,oBAAoB;AAAA,6BAChC;AAAA;AAAA;AAG7B;AACA,SAAS,aAAa,WAAW;AAC/B,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,UAAU,MAAM;AACtB,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,EAAE,UAAU,SAAS,IAAI,aAAa,aAAa,KAAK;AAC9D,MAAI,SAAS,SAAS,MAAM,QAAQ;AAClC,UAAM,eAAe,iBAAiB,WAAW,QAAQ;AACzD,UAAM,SAAS,CAAC,OAAO,OAAO,SAAS,UAAU,QAAQ;AACzD,WAAO;AAAA,QACH,qBAAqB,YAAY;AAAA,cAC3B;AAAA,iBACG,YAAY,kBAAkB,QAAQ,QAAQ;AAAA;AAAA;AAAA,EAG7D;AACA,MAAI,UAAU,UAAU,WAAW;AACjC,WAAO;AAAA,cACG;AAAA;AAAA;AAAA,iBAGG,YAAY,YAAY,YAAY;AAAA;AAAA,UAE3C,kBAAkB,SAAS;AAAA;AAAA;AAAA,EAGnC;AACA,QAAM,aAAa,UAAU,UAAU;AACvC,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,UAAU,SAAS;AACzB,QAAM,UAAU,SAAS;AACzB,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,WAAO;AAAA,cACG;AAAA;AAAA;AAAA,gCAGkB,YAAY,YAAY;AAAA;AAAA,0BAE9B,cAAc;AAAA,+BACT;AAAA;AAAA;AAAA,EAG7B;AACA,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,WAAO;AAAA,cACG;AAAA;AAAA;AAAA,iBAGG,MAAM,KAAK,MAAM,KAAK,MAAM;AAAA,iBAC5B,MAAM,KAAK,MAAM,OAAO,MAAM;AAAA;AAAA;AAAA,yBAGtB,cAAc;AAAA,+BACR;AAAA;AAAA;AAAA,EAG7B;AACA,QAAM,SAAS,yBAAyB,OAAO;AAC/C,SAAO;AAAA,YACG;AAAA;AAAA,0BAEc,mBAAmB,qBAAqB;AAAA,qBAC7C,sBAAsB;AAAA,6BACd,YAAY;AAAA,6BACZ;AAAA;AAAA;AAG7B;AACA,SAAS,aAAa,WAAW;AAC/B,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,EAAE,UAAU,SAAS,IAAI,aAAa,aAAa,KAAK;AAC9D,MAAI,SAAS,SAAS,MAAM,QAAQ;AAClC,UAAM,eAAe,iBAAiB,WAAW,QAAQ;AACzD,UAAM,SAAS,CAAC,OAAO,OAAO,SAAS,UAAU,UAAU,QAAQ;AACnE,WAAO;AAAA,QACH,qBAAqB,YAAY;AAAA,cAC3B;AAAA;AAAA,iBAEG,YAAY,kBAAkB,QAAQ,QAAQ;AAAA;AAAA;AAAA,EAG7D;AACA,QAAM,UAAU,MAAM;AACtB,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,UAAU,MAAM,KAAK;AAC3B,MAAI,UAAU,UAAU,WAAW;AACjC,WAAO;AAAA,cACG;AAAA;AAAA;AAAA;AAAA,iBAIG,YAAY,YAAY,YAAY;AAAA;AAAA;AAAA,mBAGlC;AAAA,UACT,kBAAkB,SAAS;AAAA;AAAA;AAAA,EAGnC;AACA,QAAM,aAAa,UAAU,UAAU;AACvC,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,UAAU,SAAS;AACzB,QAAM,UAAU,SAAS;AACzB,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,WAAO;AAAA,cACG;AAAA;AAAA;AAAA;AAAA,iBAIG,YAAY,YAAY,YAAY;AAAA;AAAA;AAAA,0BAG3B,cAAc;AAAA,+BACT;AAAA;AAAA;AAAA,EAG7B;AACA,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,WAAO;AAAA,cACG;AAAA;AAAA;AAAA,iBAGG,MAAM,KAAK,MAAM,KAAK,MAAM,KAAK,MAAM;AAAA,iBACvC,MAAM,KAAK,MAAM,KAAK,MAAM;AAAA,iBAC5B,MAAM,KAAK,MAAM;AAAA,iBACjB,MAAM;AAAA;AAAA;AAAA,yBAGE,cAAc;AAAA,+BACR;AAAA;AAAA;AAAA,EAG7B;AACA,QAAM,SAAS,yBAAyB,OAAO;AAC/C,SAAO;AAAA,YACG;AAAA;AAAA;AAAA,0BAGc,mBAAmB,qBAAqB;AAAA,qBAC7C,sBAAsB,sBAAsB;AAAA,6BACpC,YAAY;AAAA,6BACZ;AAAA;AAAA;AAG7B;AACA,SAAS,kBAAkB,WAAW;AACpC,QAAM,UAAU,UAAU;AAC1B,QAAM,SAAS,aAAa,cAAc,UAAU,UAAU,YAAY;AAC1E,MAAI,SAAS,GAAG;AACd,WAAO,UAAU;AAAA,EACnB;AACA,SAAO;AAAA,0BACiB;AAAA;AAAA,iBAET;AAAA;AAAA;AAAA;AAIjB;AACA,SAAS,+BAA+B,WAAW,cAAc;AAC/D,QAAM,UAAU,UAAU;AAC1B,QAAM,iBAAiB,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AACxE,QAAM,WAAW,QAAQ,iBAAiB;AAC1C,QAAM,SAAS,UAAU,UAAU,aAAa;AAChD,QAAM,UAAU,aAAa,aAAa;AAC1C,QAAM,gBAAgB,kBAAkB,UAAU,UAAU,cAAc,aAAa,YAAY;AACnG,QAAM,OAAO,kBAAkB,OAAO;AACtC,QAAM,WAAW,UAAU;AAC3B,MAAI;AACJ,QAAM,SAAS,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAC5C,MAAI,WAAW,GAAG;AAChB,oBAAgB;AAAA,EAClB,WAAW,UAAU,KAAK,cAAc,UAAU,GAAG;AACnD,oBAAgB;AAAA,EAClB,OAAO;AACL,oBAAgB,cAAc,IAAI,CAAC,MAAM,UAAU,OAAO,IAAI,gBAAgB,EAAE,KAAK,IAAI;AAAA,EAC3F;AACA,MAAI,wBAAwB;AAC5B,MAAI,UAAU,KAAK,SAAS,GAAG;AAC7B,4BAAwB;AAAA,EAC1B,OAAO;AACL,4BAAwB,UAAU,UAAU,aAAa,IAAI,CAAC,IAAI,OAAO,UAAU,OAAO,KAAK,WAAW,EAAE,KAAK,IAAI;AAAA,EACvH;AACA,MAAI,SAAS;AACb,QAAM,SAAS,aAAa,cAAc,UAAU,UAAU,YAAY;AAC1E,QAAM,gBAAgB,WAAW;AACjC,QAAM,UAAU,aAAa,cAAc,aAAa,YAAY;AACpE,QAAM,iBAAiB,YAAY;AACnC,MAAI,WAAW,KAAK,CAAC,iBAAiB,CAAC,gBAAgB;AACrD,aAAS;AAAA;AAAA;AAAA,EAGX,WAAW,iBAAiB,CAAC,gBAAgB;AAC3C,QAAI,YAAY,GAAG;AACjB,eAAS;AAAA;AAAA;AAAA,IAGX,OAAO;AACL,eAAS;AAAA;AAAA;AAAA,IAGX;AAAA,EACF,WAAW,cAAc,QAAQ;AAC/B,UAAM,OAAO,SAAS;AACtB,UAAM,OAAO,SAAS;AACtB,QAAI,cAAc,QAAQ,IAAI,IAAI,MAAM,cAAc,QAAQ,IAAI,IAAI,IAAI;AACxE,eAAS;AAAA,IACX,WAAW,cAAc,QAAQ,IAAI,IAAI,IAAI;AAC3C,eAAS;AAAA,IACX,WAAW,cAAc,QAAQ,IAAI,IAAI,IAAI;AAC3C,eAAS;AAAA,IACX;AAAA,EACF;AACA,SAAO;AAAA,WACE;AAAA,QACH;AAAA,QACA;AAAA,8BACsB,kBAAkB;AAAA,QACxC;AAAA;AAAA;AAGR;AACA,SAAS,yBAAyB,WAAW,cAAc;AACzD,QAAM,UAAU,UAAU;AAC1B,QAAM,iBAAiB,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AACxE,QAAM,WAAW,QAAQ,iBAAiB;AAC1C,QAAM,cAAc,aAAa;AACjC,QAAM,aAAa,UAAU,UAAU;AACvC,QAAM,SAAS,UAAU,UAAU,aAAa;AAChD,QAAM,UAAU,aAAa,aAAa;AAC1C,MAAI,CAAC,UAAU,UAAU,aAAa,WAAW,WAAW,UAAU,UAAU,cAAc,QAAQ,aAAa,YAAY,YAAY,WAAW,GAAG;AACvJ,WAAO;AAAA,cACG;AAAA,+BACiB;AAAA;AAAA;AAAA,EAG7B;AACA,QAAM,OAAO,kBAAkB,OAAO;AACtC,QAAM,gBAAgB,kBAAkB,UAAU,UAAU,cAAc,aAAa,YAAY;AACnG,QAAM,WAAW,UAAU;AAC3B,MAAI;AACJ,QAAM,SAAS,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAC5C,MAAI,WAAW,GAAG;AAChB,oBAAgB;AAAA,EAClB,WAAW,UAAU,KAAK,cAAc,UAAU,GAAG;AACnD,oBAAgB;AAAA,EAClB,OAAO;AACL,oBAAgB,cAAc,IAAI,CAAC,MAAM,UAAU,OAAO,IAAI,gBAAgB,EAAE,KAAK,IAAI;AAAA,EAC3F;AACA,MAAI,wBAAwB;AAC5B,MAAI,UAAU,KAAK,SAAS,GAAG;AAC7B,4BAAwB;AAAA,EAC1B,OAAO;AACL,4BAAwB,UAAU,UAAU,aAAa,IAAI,CAAC,IAAI,OAAO,UAAU,OAAO,KAAK,WAAW,EAAE,KAAK,IAAI;AAAA,EACvH;AACA,SAAO;AAAA,YACG;AAAA,QACJ;AAAA,QACA;AAAA,kBACU,kBAAkB;AAAA;AAAA;AAGpC;AACA,SAAS,kBAAkB,MAAM;AAC/B,MAAI,QAAQ,GAAG;AACb,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,OAAO;AACL,UAAM,MAAM,gBAAgB,2BAA2B;AAAA,EACzD;AACF;AACA,SAAS,wBAAwB,UAAU,OAAO,UAAU;AAC1D,QAAM,EAAE,UAAU,SAAS,IAAI,aAAa,aAAa,KAAK;AAC9D,QAAM,OAAO,MAAM;AACnB,QAAM,wBAAwB,YAAY,SAAS,KAAK,MAAM,OAAO;AACrE,QAAM,gBAAgB,wBAAwB,MAAM,MAAM,CAAC,IAAI;AAC/D,QAAM,kBAAkB,CAAC,YAAY,OAAO,KAAK,CAAC,aAAa,YAAY,OAAO,QAAQ,KAAK,SAAS,SAAS,QAAQ;AACzH,QAAM,eAAe,kBAAkB,gBAAgB;AACvD,SAAO,EAAE,iBAAiB,cAAc,SAAS;AACnD;AACA,SAAS,iBAAiB,QAAQ,eAAe;AAC/C,QAAM,eAAe,KAAK,MAAM,KAAK,UAAU,MAAM,CAAC;AACtD,eAAa,UAAU,eAAe;AACtC,SAAO;AACT;AACA,SAAS,kBAAkB,QAAQ,UAAU;AAC3C,SAAO,SAAS,IAAI,CAAC,MAAM,OAAO,EAAE,EAAE,KAAK,IAAI;AACjD;AAGA,SAAS,eAAe,OAAO,SAAS,QAAQ,QAAQ;AACtD,QAAM,aAAa,OAAO,IAAI,CAAC,QAAQ,OAAO;AAC5C,UAAM,YAAY;AAAA,MAChB,cAAc,OAAO;AAAA,MACrB,UAAU,OAAO,YAAY,OAAO,OAAO,QAAQ;AAAA,MACnD,WAAW,OAAO;AAAA,MAClB,UAAU,OAAO,YAAY,QAAQ,OAAO,QAAQ;AAAA,MACpD,YAAY;AAAA,IACd;AACA,QAAI,OAAO,WAAW,QAAQ,OAAO,QAAQ,SAAS,QAAQ,OAAO,QAAQ,MAAM,aAAa,GAAG;AACjG,gBAAU,aAAa,OAAO,QAAQ,MAAM;AAAA,IAC9C;AACA,WAAO,EAAE,MAAM,QAAQ,cAAc,KAAK,UAAU;AAAA,EACtD,CAAC;AACD,QAAM,eAAe,WAAW,IAAI,CAAC,MAAM,EAAE,SAAS;AACtD,QAAM,eAAe;AAAA,IACnB,cAAc,OAAO;AAAA,IACrB,UAAU,OAAO,QAAQ;AAAA,IACzB,WAAW;AAAA,IACX,UAAU,OAAO,QAAQ;AAAA,IACzB,YAAY;AAAA,EACd;AACA,QAAM,SAAS,WAAW,YAAY,cAAc,OAAO;AAC3D,QAAM,iBAAiB,qBAAqB,MAAM,IAAI,MAAM;AAC5D,QAAM,eAAe,MAAM,cAAc,cAAc;AACvD,MAAI,CAAC,IAAI,EAAE,IAAI,qBAAqB,GAAG;AACrC,WAAO,OAAO,OAAO;AAAA,MACnB;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF,GAAG,oBAAoB,OAAO,SAAS,YAAY,CAAC;AAAA,EACtD,OAAO;AACL,WAAO;AAAA,MACL;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA,kBAAkB;AAAA,MAClB,wBAAwB;AAAA,MACxB,QAAQ;AAAA,MACR,QAAQ;AAAA,MACR,mBAAmB;AAAA,MACnB,sBAAsB;AAAA,MACtB,kBAAkB;AAAA,MAClB,yBAAyB;AAAA,MACzB,qBAAqB;AAAA,IACvB;AAAA,EACF;AACF;AACA,SAAS,oBAAoB,OAAO,SAAS,cAAc;AACzD,QAAM,mBAAmB,CAAC;AAC1B,QAAM,oBAAoB,CAAC;AAC3B,QAAM,uBAAuB,CAAC;AAC9B,QAAM,yBAAyB,CAAC;AAChC,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI,SAAS;AACb,MAAI,SAAS;AACb,WAAS,MAAM,mBAAmB,cAAc,OAAO,KAAK;AAC5D,MAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,aAAS,MAAM,mBAAmB,cAAc,YAAY,KAAK;AAAA,EACnE;AACA,QAAM,cAAc;AACpB,WAAS,KAAK,GAAG,KAAK,QAAQ,cAAc,QAAQ,MAAM;AACxD,UAAM,UAAU,QAAQ,cAAc;AACtC,qBAAiB,WAAW,MAAM,mBAAmB,cAAc,SAAS,WAAW;AACvF,qBAAiB,SAAS,aAAa,MAAM,mBAAmB,cAAc,SAAS,WAAW,WAAW;AAC7G,QAAI,QAAQ,qBAAqB;AAC/B,wBAAkB,GAAG,kBAAkB,MAAM,mBAAmB,cAAc,GAAG,gBAAgB,WAAW;AAC5G,2BAAqB,GAAG,qBAAqB,MAAM,mBAAmB,cAAc,GAAG,mBAAmB,WAAW;AAAA,IACvH;AAAA,EACF;AACA,MAAI,QAAQ,qBAAqB;AAC/B,uBAAmB,MAAM,mBAAmB,cAAc,YAAY,WAAW;AACjF,8BAA0B,MAAM,mBAAmB,cAAc,mBAAmB,WAAW;AAC/F,0BAAsB,MAAM,mBAAmB,cAAc,eAAe,WAAW;AAAA,EACzF;AACA,MAAI,QAAQ,gBAAgB;AAC1B,YAAQ,eAAe,QAAQ,CAAC,GAAG,OAAO;AACxC,6BAAuB,MAAM,MAAM,mBAAmB,cAAc,EAAE,MAAM,WAAW;AAAA,IACzF,CAAC;AAAA,EACH;AACA,SAAO;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AACA,SAAS,yBAAyB,YAAY,QAAQ;AACpD,MAAI,WAAW,WAAW,OAAO,QAAQ;AACvC,UAAM,MAAM,4BAA4B,WAAW,wCAAwC,OAAO,eAAe;AAAA,EACnH;AACA,aAAW,QAAQ,CAAC,IAAI,OAAO;AAC7B,UAAM,SAAS,GAAG;AAClB,UAAM,SAAS,OAAO;AACtB,UAAM,SAAS,OAAO;AACtB,QAAI,CAAC,aAAa,YAAY,QAAQ,MAAM,GAAG;AAC7C,YAAM,MAAM,2EAA2E,cAAc,mBAAmB;AAAA,IAC1H;AACA,QAAI,GAAG,aAAa,OAAO,WAAW;AACpC;AAAA,IACF;AACA,UAAM,YAAY,GAAG;AACrB,UAAM,YAAY,OAAO,YAAY,OAAO,OAAO,QAAQ;AAC3D,QAAI,CAAC,aAAa,YAAY,WAAW,SAAS,GAAG;AACnD,YAAM,MAAM,kFAAkF,iBAAiB,sBAAsB;AAAA,IACvI;AAAA,EACF,CAAC;AACH;AACA,SAAS,WAAW,OAAO,QAAQ,QAAQ,QAAQ,qBAAqB;AACtE,MAAI,CAAC,OAAO,QAAQ,qBAAqB;AACvC,6BAAyB,OAAO,cAAc,MAAM;AACpD,6BAAyB,CAAC,OAAO,YAAY,GAAG,CAAC,MAAM,CAAC;AAAA,EAC1D;AACA,QAAM,SAAS,OAAO,QAAQ;AAC9B,QAAM,cAAc,OAAO,QAAQ;AACnC,MAAI,OAAO,QAAQ,UAAU;AAC3B,UAAM,6BAA6B,OAAO,SAAS,YAAY,IAAI,YAAY,EAAE;AAAA,EACnF,OAAO;AACL,UAAM,uBAAuB,OAAO,SAAS,YAAY,IAAI,YAAY,EAAE;AAAA,EAC7E;AACA,QAAM,WAAW,OAAO,YAAY;AACpC,MAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,QAAI,OAAO,WAAW,MAAM;AAC1B,YAAM,GAAG,UAAU,OAAO,QAAQ,QAAQ;AAAA,IAC5C;AAAA,EACF;AACA,MAAI,OAAO,WAAW,MAAM;AAC1B,UAAM,GAAG,UAAU,OAAO,QAAQ,GAAG;AAAA,EACvC;AACA,SAAO,QAAQ,CAAC,QAAQ,OAAO;AAC7B,UAAM,UAAU,OAAO,QAAQ,cAAc;AAC7C,UAAM,SAAS,OAAO,iBAAiB;AACvC,UAAM,eAAe,OAAO,iBAAiB,SAAS;AACtD,UAAM,cAAc,OAAO,kBAAkB,GAAG;AAChD,UAAM,iBAAiB,OAAO,qBAAqB,GAAG;AACtD,QAAI,aAAa;AACf,YAAM,EAAE,aAAa,IAAI,wBAAwB,OAAO,QAAQ,cAAc,OAAO,OAAO,OAAO,QAAQ,QAAQ;AACnH,cAAQ,aAAa;AAAA,aACd;AACH,gBAAM,GAAG,WAAW,aAAa,IAAI,WAAW,YAAY,CAAC;AAC7D;AAAA,aACG;AACH,gBAAM,GAAG,WAAW,aAAa,IAAI,WAAW,YAAY,CAAC;AAC7D;AAAA,aACG;AACH,gBAAM,GAAG,WAAW,aAAa,IAAI,WAAW,YAAY,CAAC;AAC7D;AAAA,aACG;AACH,gBAAM,GAAG,WAAW,aAAa,IAAI,WAAW,YAAY,CAAC;AAC7D;AAAA;AAEA;AAAA;AAAA,IAEN;AACA,QAAI,gBAAgB;AAClB,YAAM,GAAG,UAAU,gBAAgB,OAAO,QAAQ,SAAS,IAAI,OAAO,QAAQ,SAAS,EAAE;AAAA,IAC3F;AACA,QAAI,UAAU,MAAM;AAClB;AAAA,IACF;AACA,QAAI,OAAO,WAAW;AACpB,UAAI,aAAa,cAAc,OAAO,KAAK,IAAI,GAAG;AAChD,cAAM,GAAG,UAAU,QAAQ,OAAO,cAAc,EAAE;AAAA,MACpD,OAAO;AACL,YAAI,OAAO,OAAO;AAClB,YAAI,EAAE,gBAAgB,eAAe;AACnC,iBAAO,IAAI,aAAa,IAAI;AAAA,QAC9B;AACA,cAAM,GAAG,WAAW,QAAQ,IAAI;AAAA,MAClC;AACA;AAAA,IACF;AACA,QAAI,OAAO,QAAQ,SAAS,QAAQ,gBAAgB,MAAM;AACxD,YAAM,GAAG,UAAU,cAAc,OAAO,QAAQ,MAAM,UAAU;AAAA,IAClE;AACA,UAAM,sBAAsB,OAAO,QAAQ,QAAQ,SAAS,QAAQ,EAAE;AAAA,EACxE,CAAC;AACD,QAAM,cAAc,OAAO;AAC3B,MAAI,aAAa;AACf,YAAQ,OAAO,MAAM;AAAA,WACd;AACH,cAAM,GAAG,WAAW,aAAa,IAAI,WAAW,OAAO,KAAK,CAAC;AAC7D;AAAA,WACG;AACH,cAAM,GAAG,WAAW,aAAa,IAAI,WAAW,OAAO,KAAK,CAAC;AAC7D;AAAA,WACG;AACH,cAAM,GAAG,WAAW,aAAa,IAAI,WAAW,OAAO,KAAK,CAAC;AAC7D;AAAA,WACG;AACH,cAAM,GAAG,WAAW,aAAa,IAAI,WAAW,OAAO,KAAK,CAAC;AAC7D;AAAA;AAEA;AAAA;AAAA,EAEN;AACA,MAAI,OAAO,yBAAyB;AAClC,UAAMG,WAAU,aAAa,eAAe,OAAO,KAAK;AACxD,YAAQ,OAAO,MAAM;AAAA,WACd;AACH,cAAM,GAAG,WAAW,OAAO,yBAAyB,IAAI,WAAWA,QAAO,CAAC;AAC3E;AAAA,WACG;AACH,cAAM,GAAG,WAAW,OAAO,yBAAyB,IAAI,WAAWA,QAAO,CAAC;AAC3E;AAAA,WACG;AACH,cAAM,GAAG,WAAW,OAAO,yBAAyB,IAAI,WAAWA,QAAO,CAAC;AAC3E;AAAA;AAEA;AAAA;AAAA,EAEN;AACA,MAAI,OAAO,qBAAqB;AAC9B,UAAM,GAAG,UAAU,OAAO,qBAAqB,OAAO,QAAQ,SAAS,IAAI,OAAO,QAAQ,SAAS,EAAE;AAAA,EACvG;AACA,MAAI,OAAO,QAAQ,kBAAkB,qBAAqB;AACxD,WAAO,QAAQ,eAAe,QAAQ,CAAC,GAAG,OAAO;AAC/C,YAAM,YAAY,OAAO,uBAAuB;AAChD,YAAM,cAAc,oBAAoB;AACxC,UAAI,EAAE,SAAS,SAAS;AACtB,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,WAAW,EAAE,SAAS,QAAQ;AAC5B,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,WAAW,EAAE,SAAS,QAAQ;AAC5B,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,WAAW,EAAE,SAAS,QAAQ;AAC5B,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,WAAW,EAAE,SAAS,OAAO;AAC3B,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,WAAW,EAAE,SAAS,SAAS;AAC7B,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,WAAW,EAAE,SAAS,SAAS;AAC7B,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,WAAW,EAAE,SAAS,SAAS;AAC7B,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,OAAO;AACL,cAAM,MAAM,gBAAgB,EAAE,4BAA4B;AAAA,MAC5D;AAAA,IACF,CAAC;AAAA,EACH;AACA,QAAM,eAAe;AACvB;AACA,SAAS,cAAc,SAAS,QAAQ,QAAQ;AAC9C,MAAI,YAAY;AAChB,SAAO,OAAO,MAAM,EAAE,QAAQ,CAAC,MAAM;AACnC,UAAM,YAAY,EAAE,WAAW,QAAQ,EAAE,QAAQ,SAAS,QAAQ,EAAE,QAAQ,MAAM,aAAa;AAC/F,QAAI,QAAQ,uBAAuB,CAAC,EAAE,WAAW;AAC/C,YAAM,YAAY,EAAE,QAAQ;AAC5B,YAAM,EAAE,iBAAiB,cAAc,SAAS,IAAI,wBAAwB,QAAQ,cAAc,EAAE,OAAO,SAAS;AACpH,UAAI,QAAQ,IAAI,QAAQ,IAAI,SAAS;AACrC,UAAI,aAAa,WAAW,KAAK,QAAQ,cAAc;AACrD,cAAM,iBAAiB,CAAC,KAAK,KAAK,UAAU,KAAK,CAAC,GAAG,KAAK,KAAK,UAAU,KAAK,CAAC,CAAC;AAChF,gBAAQ,GAAG,eAAe,KAAK,KAAK,eAAe,KAAK;AAAA,MAC1D,WAAW,aAAa,WAAW,KAAK,CAAC,QAAQ,cAAc;AAC7D,gBAAQ,GAAG,aAAa,KAAK,KAAK,aAAa,KAAK;AAAA,MACtD,WAAW,aAAa,SAAS,KAAK,CAAC,QAAQ,cAAc;AAC3D,cAAMA,WAAU,aAAa,eAAe,YAAY;AACxD,iBAAS,GAAGA,SAAQ,OAAO,UAAU,MAAMA,SAAQA,SAAQ,SAAS,OAAO,UAAU;AAAA,MACvF;AACA,YAAM,QAAQ,EAAE,MAAM;AACtB,YAAM,6BAA6B,aAAa,WAAW,KAAK,aAAa,YAAY,EAAE,OAAO,SAAS;AAC3G,YAAM,WAAW,aAAa,cAAc,EAAE,KAAK,MAAM;AACzD,YAAM,gBAAgB,qBAAqB,iBAAiB,EAAE,OAAO,OAAO,KAAK;AACjF,YAAM,uBAAuB,CAAC,QAAQ,gBAAgB,UAAU,OAAO,MAAM,UAAU,aAAa,YAAY,WAAW,OAAO,QAAQ,QAAQ;AAClJ,YAAM,2BAA2B,QAAQ,gBAAgB,aAAa,SAAS,IAAI,KAAK,GAAG,UAAU,KAAK,KAAK,UAAU,KAAK;AAC9H,mBAAa,GAAG,SAAS,wBAAwB,kBAAkB,WAAW,MAAM,aAAa,UAAU,YAAY,iBAAiB,8BAA8B,SAAS,SAAS,UAAU,4BAA4B;AAAA,IAChO,OAAO;AACL,YAAM,WAAW,EAAE,YAAY,YAAY,EAAE,QAAQ;AACrD,mBAAa,GAAG,EAAE,SAAS,YAAY;AAAA,IACzC;AAAA,EACF,CAAC;AACD,QAAM,cAAc,QAAQ;AAC5B,MAAI,MAAM,QAAQ,YAAY;AAC9B,SAAO,MAAM,YAAY,MAAM,cAAc,GAAG,IAAI,EAAE,UAAU,eAAe;AAC/E,SAAO;AACT;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,EAAE,QAAQ,2BAA2B,KAAK,QAAQ;AAC/D;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,mBAAmB,cAAc;AACtC,SAAK,iBAAiB,CAAC,EAAE,MAAM,YAAY,MAAM,QAAQ,CAAC;AAC1D,UAAM,OAAO,mBAAmB;AAChC,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,SAAK,WAAW;AAAA;AAAA,UAEV,KAAK,sBAAsB,kDAAkD,CAAC,KAAK,KAAK,GAAG,GAAG,WAAW,IAAI,mCAAmC,CAAC,KAAK,KAAK,GAAG,GAAG,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAgB5K,KAAK;AAAA;AAAA;AAAA,EAGb;AACF;AAGA,IAAI,4BAA4B,MAAM;AAAA,EACpC,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,mBAAmB,cAAc;AACtC,SAAK,iBAAiB,CAAC,EAAE,MAAM,YAAY,MAAM,QAAQ,CAAC;AAC1D,UAAM,OAAO,mBAAmB;AAChC,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,SAAK,WAAW;AAAA;AAAA,UAEV,KAAK,sBAAsB,kDAAkD,CAAC,KAAK,KAAK,GAAG,GAAG,WAAW,IAAI,mCAAmC,CAAC,KAAK,KAAK,GAAG,GAAG,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAgB5K,KAAK;AAAA;AAAA;AAAA,EAGb;AACF;AAGA,IAAI,qBAAqB,MAAM;AAAA,EAC7B,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,aAAa;AAChC,UAAM,OAAO,mBAAmB;AAChC,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA,QACZ;AAAA;AAAA;AAAA;AAAA,UAIE,KAAK;AAAA;AAAA;AAAA,EAGb;AACF;AAGA,IAAI,2BAA2B,MAAM;AAAA,EACnC,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc,aAAa;AAChC,UAAM,OAAO,mBAAmB;AAChC,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA,QACZ;AAAA;AAAA;AAAA;AAAA;AAAA,UAKE,KAAK;AAAA;AAAA;AAAA,EAGb;AACF;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,aAAa,sBAAsB,OAAO;AACpD,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,iBAAiB,CAAC,EAAE,MAAM,YAAY,MAAM,QAAQ,CAAC;AAC1D,UAAM,OAAO,mBAAmB;AAChC,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,QAAI,SAAS;AACb,QAAI,qBAAqB;AACvB,eAAS;AAAA,IACX;AACA,SAAK,WAAW;AAAA,QACZ,KAAK,sBAAsB,yBAAyB,IAAI,mBAAmB,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,wBAatE,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAcnB,KAAK,iBAAiB;AAAA;AAAA;AAAA,EAG9B;AACF;AAGA,IAAI,4BAA4B,MAAM;AAAA,EACpC,YAAY,aAAa,sBAAsB,OAAO;AACpD,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,iBAAiB,CAAC,EAAE,MAAM,YAAY,MAAM,QAAQ,CAAC;AAC1D,UAAM,OAAO,mBAAmB;AAChC,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,QAAI,WAAW;AACf,QAAI,SAAS;AACb,QAAI,qBAAqB;AACvB,eAAS;AAAA,IACX;AACA,aAAS,MAAM,GAAG,OAAO,GAAG,OAAO;AACjC,eAAS,MAAM,GAAG,OAAO,GAAG,OAAO;AACjC,cAAM,UAAU,MAAM,IAAI;AAC1B,oBAAY;AAAA;AAAA,gCAEY,SAAS,KAAK,sBAAsB,gBAAgB,GAAG,YAAY;AAAA,8BACrE;AAAA,iCACG,SAAS,KAAK,sBAAsB,gBAAgB,GAAG,YAAY;AAAA,gCACpE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,uBAUT,KAAK;AAAA;AAAA;AAAA,uBAGL;AAAA;AAAA,uBAEA;AAAA;AAAA,uBAEA;AAAA;AAAA,uBAEA;AAAA;AAAA;AAAA;AAAA;AAAA,MAKjB;AAAA,IACF;AACA,SAAK,WAAW;AAAA,UACV,KAAK,sBAAsB,yBAAyB,IAAI,mBAAmB,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAWpF;AAAA;AAAA,YAEA,KAAK,YAAY;AAAA;AAAA;AAAA,EAG3B;AACF;AAGA,IAAI,qBAAqB,CAAC;AAC1Bf,UAAS,oBAAoB;AAAA,EAC3B,mCAAmC,MAAM;AAAA,EACzC,+BAA+B,MAAM;AAAA,EACrC,4BAA4B,MAAM;AAAA,EAClC,kCAAkC,MAAM;AAAA,EACxC,4BAA4B,MAAM;AAAA,EAClC,mBAAmB,MAAM;AAAA,EACzB,2BAA2B,MAAM;AAAA,EACjC,kCAAkC,MAAM;AAAA,EACxC,oBAAoB,MAAM;AAAA,EAC1B,oBAAoB,MAAM;AAAA,EAC1B,iDAAiD,MAAM;AAAA,EACvD,iCAAiC,MAAM;AAAA,EACvC,uCAAuC,MAAM;AAAA,EAC7C,gCAAgC,MAAM;AAAA,EACtC,0CAA0C,MAAM;AAAA,EAChD,gDAAgD,MAAM;AAAA,EACtD,0CAA0C,MAAM;AAAA,EAChD,yCAAyC,MAAM;AAAA,EAC/C,gDAAgD,MAAM;AAAA,EACtD,4BAA4B,MAAM;AAAA,EAClC,0BAA0B,MAAM;AAClC,CAAC;AACD,SAAS,oBAAoB,IAAI;AAC/B,QAAM,OAAO,mBAAmB;AAChC,QAAM,qBAAqB,GAAG,KAAK;AAAA;AAAA,MAE/B,KAAK;AAAA,MACL,KAAK;AAAA,MACL,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAMT,SAAO,mBAAmB,IAAI,kBAAkB;AAClD;AACA,SAAS,mBAAmB,IAAI;AAC9B,QAAM,cAAc,IAAI,aAAa,CAAC,IAAI,GAAG,GAAG,GAAG,GAAG,IAAI,IAAI,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,IAAI,GAAG,GAAG,CAAC,CAAC;AACrG,SAAO,yBAAyB,IAAI,WAAW;AACjD;AACA,SAAS,kBAAkB,IAAI;AAC7B,QAAM,wBAAwB,IAAI,YAAY,CAAC,GAAG,GAAG,GAAG,GAAG,GAAG,CAAC,CAAC;AAChE,SAAO,wBAAwB,IAAI,qBAAqB;AAC1D;AACA,SAAS,0BAA0B,IAAI,OAAO,QAAQ,gBAAgB,eAAe,aAAa;AAChG,sBAAoB,OAAO,MAAM;AACjC,QAAM,UAAU,cAAc,EAAE;AAChC,QAAM,QAAQ,GAAG;AACjB,eAAa,IAAI,MAAM,GAAG,YAAY,OAAO,OAAO,CAAC;AACrD,eAAa,IAAI,MAAM,GAAG,cAAc,OAAO,GAAG,gBAAgB,GAAG,aAAa,CAAC;AACnF,eAAa,IAAI,MAAM,GAAG,cAAc,OAAO,GAAG,gBAAgB,GAAG,aAAa,CAAC;AACnF,eAAa,IAAI,MAAM,GAAG,cAAc,OAAO,GAAG,oBAAoB,GAAG,OAAO,CAAC;AACjF,eAAa,IAAI,MAAM,GAAG,cAAc,OAAO,GAAG,oBAAoB,GAAG,OAAO,CAAC;AACjF,MAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,iBAAa,IAAI,MAAM,GAAG,WAAW,OAAO,GAAG,gBAAgB,OAAO,QAAQ,GAAG,eAAe,aAAa,IAAI,CAAC;AAAA,EACpH,OAAO;AACL,iBAAa,IAAI,MAAM,GAAG,aAAa,OAAO,GAAG,gBAAgB,OAAO,MAAM,CAAC;AAAA,EACjF;AACA,eAAa,IAAI,MAAM,GAAG,YAAY,GAAG,YAAY,IAAI,CAAC;AAC1D,SAAO,EAAE,SAAS,UAAU,CAAC,QAAQ,KAAK,EAAE;AAC9C;AACA,SAAS,yCAAyC,eAAe;AAC/D,SAAO,cAAc;AACvB;AACA,SAAS,2BAA2B,IAAI,MAAM,SAAS,eAAe;AACpE,QAAM,CAAC,OAAO,MAAM,IAAI,yCAAyC,MAAM,OAAO;AAC9E,SAAO,0BAA0B,IAAI,OAAO,QAAQ,yCAAyC,aAAa,GAAG,cAAc,oBAAoB,GAAG,KAAK;AACzJ;AACA,SAAS,yCAAyC,eAAe;AAC/D,SAAO,cAAc;AACvB;AACA,SAAS,2BAA2B,IAAI,MAAM,SAAS,eAAe;AACpE,QAAM,CAAC,OAAO,MAAM,IAAI,yCAAyC,MAAM,OAAO;AAC9E,SAAO,0BAA0B,IAAI,OAAO,QAAQ,yCAAyC,aAAa,GAAG,cAAc,oBAAoB,cAAc,oBAAoB;AACnL;AACA,SAAS,+CAA+C,eAAe;AACrE,SAAO,cAAc;AACvB;AACA,SAAS,iCAAiC,IAAI,MAAM,SAAS,eAAe;AAC1E,QAAM,CAAC,OAAO,MAAM,IAAI,yCAAyC,MAAM,OAAO;AAC9E,SAAO,0BAA0B,IAAI,OAAO,QAAQ,+CAA+C,aAAa,GAAG,GAAG,MAAM,GAAG,aAAa;AAC9I;AACA,SAAS,wCAAwC,eAAe;AAC9D,SAAO,cAAc;AACvB;AACA,SAAS,0BAA0B,IAAI,MAAM,SAAS,eAAe;AACnE,QAAM,CAAC,OAAO,MAAM,IAAI,uCAAuC,MAAM,OAAO;AAC5E,SAAO,0BAA0B,IAAI,OAAO,QAAQ,wCAAwC,aAAa,GAAG,GAAG,MAAM,GAAG,KAAK;AAC/H;AACA,SAAS,+CAA+C,eAAe;AACrE,SAAO,cAAc;AACvB;AACA,SAAS,iCAAiC,IAAI,MAAM,SAAS,eAAe;AAC1E,QAAM,CAAC,OAAO,MAAM,IAAI,uCAAuC,MAAM,OAAO;AAC5E,SAAO,0BAA0B,IAAI,OAAO,QAAQ,+CAA+C,aAAa,GAAG,GAAG,MAAM,cAAc,oBAAoB;AAChK;AACA,SAAS,kCAAkC,IAAI,SAAS,cAAc;AACpE,QAAM,YAAY;AAClB,QAAM,WAAW,IAAI;AACrB,QAAM,SAAS,IAAI,IAAI,IAAI;AAC3B,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,cAAc,YAAY,CAAC;AACnE,QAAM,UAAU,mCAAmC,IAAI,SAAS,gBAAgB,cAAc,GAAG,QAAQ,SAAS;AAClH,SAAO,WAAW,mCAAmC,IAAI,SAAS,MAAM,cAAc,GAAG,QAAQ,QAAQ;AAC3G;AACA,SAAS,2BAA2B,IAAI,SAAS,OAAO,QAAQ,MAAM,eAAe;AACnF,eAAa,IAAI,MAAM,GAAG,YAAY,GAAG,YAAY,OAAO,CAAC;AAC7D,MAAI,eAAe,eAAe;AAClC,MAAI,gBAAgB,YAAY;AAC9B,oBAAgB,IAAI,WAAW,QAAQ,SAAS,CAAC;AACjD,oBAAgB,GAAG;AACnB,qBAAiB,GAAG;AAAA,EACtB,OAAO;AACL,oBAAgB,IAAI,aAAa,QAAQ,SAAS,CAAC;AACnD,oBAAgB,GAAG;AACnB,qBAAiB,cAAc;AAAA,EACjC;AACA,gBAAc,IAAI,IAAI;AACtB,MAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,iBAAa,IAAI,MAAM,GAAG,cAAc,GAAG,YAAY,GAAG,GAAG,GAAG,OAAO,QAAQ,GAAG,MAAM,eAAe,aAAa,CAAC;AAAA,EACvH,OAAO;AACL,iBAAa,IAAI,MAAM,GAAG,WAAW,GAAG,YAAY,GAAG,gBAAgB,OAAO,QAAQ,GAAG,GAAG,MAAM,eAAe,aAAa,CAAC;AAAA,EACjI;AACA,eAAa,IAAI,MAAM,GAAG,YAAY,GAAG,YAAY,IAAI,CAAC;AAC5D;AACA,SAAS,yBAAyB,IAAI,SAAS,QAAQ;AACrD,eAAa,IAAI,MAAM,GAAG,YAAY,GAAG,YAAY,OAAO,CAAC;AAC7D,MAAI,OAAO,gBAAgB,YAAY;AACrC,QAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,mBAAa,IAAI,MAAM,GAAG,cAAc,GAAG,YAAY,GAAG,GAAG,GAAG,OAAO,OAAO,OAAO,QAAQ,GAAG,MAAM,GAAG,eAAe,OAAO,IAAI,CAAC;AAAA,IACtI,OAAO;AACL,mBAAa,IAAI,MAAM,GAAG,WAAW,GAAG,YAAY,GAAG,GAAG,MAAM,OAAO,OAAO,OAAO,QAAQ,GAAG,GAAG,MAAM,GAAG,eAAe,OAAO,IAAI,CAAC;AAAA,IACzI;AAAA,EACF,OAAO;AACL,QAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,mBAAa,IAAI,MAAM,GAAG,cAAc,GAAG,YAAY,GAAG,GAAG,GAAG,GAAG,MAAM,GAAG,eAAe,MAAM,CAAC;AAAA,IACpG,OAAO;AACL,mBAAa,IAAI,MAAM,GAAG,WAAW,GAAG,YAAY,GAAG,GAAG,MAAM,GAAG,MAAM,GAAG,eAAe,MAAM,CAAC;AAAA,IACpG;AAAA,EACF;AACA,eAAa,IAAI,MAAM,GAAG,YAAY,GAAG,YAAY,IAAI,CAAC;AAC5D;AACA,SAAS,8BAA8B,KAAK,MAAM,SAAS,eAAe;AACxE,QAAM,UAAU,IAAI,aAAa;AACjC,eAAa,KAAK,MAAM,IAAI,WAAW,IAAI,mBAAmB,OAAO,CAAC;AACtE,QAAM,gBAAgB;AACtB,QAAM,iBAAiB;AACvB,QAAM,kBAAkB,gBAAgB,iBAAiB,OAAO;AAChE,eAAa,KAAK,MAAM,IAAI,WAAW,IAAI,mBAAmB,iBAAiB,IAAI,WAAW,CAAC;AAC/F,eAAa,KAAK,MAAM,IAAI,WAAW,GAAG,GAAG,SAAS,MAAM,IAAI,MAAM,IAAI,OAAO,CAAC,CAAC;AACnF,eAAa,KAAK,MAAM,IAAI,WAAW,IAAI,mBAAmB,IAAI,CAAC;AACnE,SAAO;AACT;AACA,SAAS,gCAAgC,IAAI,SAASG,OAAM;AAC1D,QAAM,MAAM;AACZ,QAAM,iBAAiB,IAAI,aAAaA,KAAI;AAC5C,MAAI,WAAW,IAAI,mBAAmB,OAAO;AAC7C,MAAI,iBAAiB,IAAI,mBAAmB,GAAG,cAAc;AAC7D,MAAI,WAAW,IAAI,mBAAmB,IAAI;AAC1C,SAAO;AACT;AACA,SAAS,gDAAgD,IAAI,MAAM,SAAS,eAAe;AACzF,QAAM,CAAC,GAAG,CAAC,IAAI,yCAAyC,MAAM,OAAO;AACrE,QAAM,cAAc;AACpB,QAAM,iBAAiB,IAAI,WAAW,mCAAmC,OAAO,SAAS,WAAW,CAAC;AACrG,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,GAAG,GAAG,GAAG,cAAc,uBAAuB,GAAG,eAAe,cAAc,CAAC;AACvH,SAAO,IAAI,aAAa,eAAe,MAAM;AAC/C;AACA,SAAS,+BAA+B,IAAI,SAAS,OAAO,MAAM,MAAM,cAAc,cAAc,eAAe;AACjH,QAAM,MAAM;AACZ,QAAM,iBAAiB,IAAI,aAAa,sCAAsC,cAAc,YAAY,CAAC;AACzG,MAAI,WAAW,IAAI,mBAAmB,OAAO;AAC7C,MAAI,iBAAiB,IAAI,mBAAmB,GAAG,cAAc;AAC7D,MAAI,WAAW,IAAI,mBAAmB,IAAI;AAC1C,SAAO;AACT;AACA,SAAS,sCAAsC,IAAI,cAAc,cAAc;AAC7E,QAAM,aAAa,IAAI,aAAa,eAAe,eAAe,CAAC;AACnE,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,GAAG,cAAc,cAAc,GAAG,MAAM,GAAG,OAAO,UAAU,CAAC;AACrG,SAAO;AACT;AAGA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,IAAI;AACd,SAAK,gBAAgB;AACrB,SAAK,UAAU;AACf,SAAK,WAAW;AAChB,SAAK,sBAAsB;AAC3B,SAAK,cAAc,CAAC;AACpB,UAAM,YAAY,IAAI,EAAE,UAAU,eAAe;AACjD,QAAI,MAAM,MAAM;AACd,WAAK,KAAK;AACV,sBAAgB,WAAW,EAAE;AAAA,IAC/B,OAAO;AACL,WAAK,KAAK,gBAAgB,SAAS;AAAA,IACrC;AACA,QAAI,qBAAqB;AACzB,UAAM,0BAA0B;AAChC,SAAK,+BAA+B,KAAK,GAAG,aAAa,6BAA6B;AACtF,QAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,YAAM,gBAAgB;AACtB,YAAM,qBAAqB;AAC3B,WAAK,wBAAwB,oBAAoB,KAAK,IAAI,aAAa;AACvE,UAAI,aAAa,KAAK,IAAI,kBAAkB,GAAG;AAC7C,aAAK,4BAA4B,oBAAoB,KAAK,IAAI,kBAAkB;AAAA,MAClF,WAAW,IAAI,EAAE,IAAI,0BAA0B,GAAG;AAChD,cAAM,IAAI,MAAM,oHAAoH;AAAA,MACtI;AACA,WAAK,4BAA4B,KAAK,GAAG,aAAa,kBAAkB;AACxE,UAAI,aAAa,KAAK,IAAI,uBAAuB,GAAG;AAClD,aAAK,gCAAgC,oBAAoB,KAAK,IAAI,uBAAuB;AAAA,MAC3F,WAAW,IAAI,EAAE,IAAI,0BAA0B,GAAG;AAChD,cAAM,IAAI,MAAM,6HAA6H;AAAA,MAC/I;AAAA,IACF,OAAO;AACL,2BAAqB;AACrB,UAAI,aAAa,KAAK,IAAI,kBAAkB,GAAG;AAC7C,aAAK,4BAA4B,KAAK,GAAG,aAAa,kBAAkB;AAAA,MAC1E,WAAW,aAAa,KAAK,IAAI,uBAAuB,GAAG;AACzD,aAAK,gCAAgC,KAAK,GAAG,aAAa,uBAAuB;AAAA,MACnF,OAAO;AACL,cAAM,IAAI,MAAM,qDAAqD;AAAA,MACvE;AAAA,IACF;AACA,SAAK,eAAe,mBAAmB,KAAK,EAAE;AAC9C,SAAK,cAAc,kBAAkB,KAAK,EAAE;AAC5C,SAAK,cAAc,kBAAkB,KAAK,EAAE;AAC5C,SAAK,gBAAgB,iBAAiB,KAAK,IAAI,KAAK,yBAAyB;AAAA,EAC/E;AAAA,EACA,IAAI,QAAQ;AACV,WAAO,IAAI,EAAE,QAAQ,OAAO;AAAA,EAC9B;AAAA,EACA,UAAU;AACR,QAAI,KAAK,UAAU;AACjB;AAAA,IACF;AACA,QAAI,KAAK,WAAW,MAAM;AACxB,cAAQ,KAAK,sKAAsK;AAAA,IACrL;AACA,QAAI,KAAK,iBAAiB,MAAM;AAC9B,cAAQ,KAAK,oMAAoM;AAAA,IACnN;AACA,UAAM,KAAK,KAAK;AAChB,iBAAa,IAAI,MAAM,GAAG,OAAO,CAAC;AAClC,iBAAa,IAAI,MAAM,GAAG,gBAAgB,GAAG,aAAa,IAAI,CAAC;AAC/D,iBAAa,IAAI,MAAM,GAAG,kBAAkB,KAAK,WAAW,CAAC;AAC7D,iBAAa,IAAI,MAAM,GAAG,WAAW,GAAG,cAAc,IAAI,CAAC;AAC3D,iBAAa,IAAI,MAAM,GAAG,WAAW,GAAG,sBAAsB,IAAI,CAAC;AACnE,iBAAa,IAAI,MAAM,GAAG,aAAa,KAAK,WAAW,CAAC;AACxD,SAAK,WAAW;AAAA,EAClB;AAAA,EACA,2BAA2B,MAAM,SAAS;AACxC,SAAK,gBAAgB;AACrB,WAAO,2BAA2B,KAAK,IAAI,MAAM,SAAS,KAAK,aAAa;AAAA,EAC9E;AAAA,EACA,2BAA2B,MAAM,SAAS;AACxC,SAAK,gBAAgB;AACrB,WAAO,2BAA2B,KAAK,IAAI,MAAM,SAAS,KAAK,aAAa;AAAA,EAC9E;AAAA,EACA,iCAAiC,MAAM,SAAS;AAC9C,SAAK,gBAAgB;AACrB,WAAO,iCAAiC,KAAK,IAAI,MAAM,SAAS,KAAK,aAAa;AAAA,EACpF;AAAA,EACA,yBAAyB,SAAS,QAAQ;AACxC,SAAK,gBAAgB;AACrB,6BAAyB,KAAK,IAAI,SAAS,MAAM;AAAA,EACnD;AAAA,EACA,2BAA2B,SAAS,OAAO,QAAQ,MAAM;AACvD,SAAK,gBAAgB;AACrB,+BAA2B,KAAK,IAAI,SAAS,OAAO,QAAQ,MAAM,KAAK,aAAa;AAAA,EACtF;AAAA,EACA,iCAAiC,MAAM,SAAS;AAC9C,SAAK,gBAAgB;AACrB,WAAO,iCAAiC,KAAK,IAAI,MAAM,SAAS,KAAK,aAAa;AAAA,EACpF;AAAA,EACA,0BAA0B,MAAM,SAAS;AACvC,SAAK,gBAAgB;AACrB,WAAO,0BAA0B,KAAK,IAAI,MAAM,SAAS,KAAK,aAAa;AAAA,EAC7E;AAAA,EACA,oBAAoB,SAAS;AAC3B,SAAK,gBAAgB;AACrB,QAAI,KAAK,kBAAkB,SAAS;AAClC,wCAAkC,KAAK,IAAI,KAAK,WAAW;AAC3D,WAAK,gBAAgB;AAAA,IACvB;AACA,iBAAa,KAAK,IAAI,MAAM,KAAK,GAAG,cAAc,OAAO,CAAC;AAAA,EAC5D;AAAA,EACA,gDAAgD,SAAS,MAAM,SAAS;AACtE,WAAO,KAAK,qBAAqB,SAAS,MAAM,gDAAgD,KAAK,IAAI,MAAM,SAAS,KAAK,aAAa,CAAC;AAAA,EAC7I;AAAA,EACA,+BAA+B,SAAS,OAAO,MAAM,SAAS,cAAc,cAAc;AACxF,WAAO,+BAA+B,KAAK,IAAI,SAAS,OAAO,MAAM,SAAS,cAAc,cAAc,KAAK,aAAa;AAAA,EAC9H;AAAA,EACA,gCAAgC,SAASA,OAAM;AAC7C,WAAO,gCAAgC,KAAK,IAAI,SAASA,KAAI;AAAA,EAC/D;AAAA,EACA,wBAAwB,SAAS,MAAM,SAAS;AAC9C,SAAK,yBAAyB,OAAO;AACrC,UAAM,SAAS,8BAA8B,KAAK,IAAI,MAAM,SAAS,KAAK,aAAa;AACvF,SAAK,2BAA2B;AAChC,WAAO;AAAA,EACT;AAAA,EACA,wBAAwB;AACtB,UAAM,eAAe,KAAK,YAAY,KAAK,EAAE;AAC7C,WAAO,KAAK,UAAU,YAAY;AAAA,EACpC;AAAA,EACA,YAAY,IAAI;AACd,QAAI;AACJ,QAAI;AACJ,QAAI,IAAI,EAAE,QAAQ,yBAAyB,GAAG;AAC5C,YAAM,MAAM;AACZ,YAAM,OAAO,IAAI,UAAU,IAAI,4BAA4B,CAAC;AAC5D,SAAG,MAAM;AACT,sBAAgB,MAAM;AACpB,cAAM,SAAS,IAAI,eAAe,MAAM,GAAG,CAAC;AAC5C,eAAO,WAAW,IAAI,oBAAoB,WAAW,IAAI;AAAA,MAC3D;AACA,cAAQ;AAAA,IACV,WAAW,IAAI,EAAE,UAAU,8CAA8C,IAAI,GAAG;AAC9E,cAAQ,KAAK,WAAW;AACxB,WAAK,SAAS;AACd,sBAAgB,MAAM,KAAK,iBAAiB,OAAO,IAAI,EAAE,UAAU,8CAA8C,CAAC;AAAA,IACpH,OAAO;AACL,sBAAgB,MAAM;AAAA,IACxB;AACA,WAAO,EAAE,OAAO,cAAc;AAAA,EAChC;AAAA,EACA,gCAAgC,SAAS,cAAc,cAAc;AACnE,WAAO,KAAK,qBAAqB,SAAS,MAAM,sCAAsC,KAAK,IAAI,cAAc,YAAY,CAAC;AAAA,EAC5H;AAAA,EACA,cAAc,gBAAgB;AAC5B,SAAK,gBAAgB;AACrB,UAAM,KAAK,KAAK;AAChB,QAAI,KAAK,gBAAgB,MAAM;AAC7B,WAAK,eAAe,oBAAoB,EAAE;AAAA,IAC5C;AACA,UAAM,UAAU,cAAc,EAAE;AAChC,iBAAa,IAAI,MAAM,GAAG,aAAa,SAAS,KAAK,YAAY,CAAC;AAClE,iBAAa,IAAI,MAAM,GAAG,aAAa,SAAS,cAAc,CAAC;AAC/D,gBAAY,IAAI,OAAO;AACvB,QAAI,KAAK,OAAO;AACd,sBAAgB,IAAI,OAAO;AAAA,IAC7B;AACA,QAAI,CAAC,KAAK,qBAAqB;AAC7B,WAAK,WAAW,OAAO;AACvB,WAAK,sBAAsB,kCAAkC,IAAI,KAAK,SAAS,KAAK,YAAY;AAAA,IAClG;AACA,WAAO;AAAA,EACT;AAAA,EACA,cAAc,SAAS;AACrB,SAAK,gBAAgB;AACrB,QAAI,YAAY,KAAK,SAAS;AAC5B,WAAK,UAAU;AAAA,IACjB;AACA,QAAI,WAAW,MAAM;AACnB,mBAAa,KAAK,IAAI,MAAM,KAAK,GAAG,cAAc,OAAO,CAAC;AAAA,IAC5D;AAAA,EACF;AAAA,EACA,WAAW,SAAS;AAClB,SAAK,gBAAgB;AACrB,SAAK,UAAU;AACf,QAAI,KAAK,WAAW,QAAQ,KAAK,OAAO;AACtC,sBAAgB,KAAK,IAAI,KAAK,OAAO;AAAA,IACvC;AACA,iBAAa,KAAK,IAAI,MAAM,KAAK,GAAG,WAAW,OAAO,CAAC;AAAA,EACzD;AAAA,EACA,mBAAmB,SAAS,aAAa,cAAc,MAAM;AAC3D,SAAK,gBAAgB;AACrB,QAAI,aAAa;AACf,aAAO,iCAAiC,KAAK,IAAI,SAAS,WAAW;AAAA,IACvE,OAAO;AACL,aAAO,0BAA0B,KAAK,IAAI,SAAS,WAAW;AAAA,IAChE;AAAA,EACF;AAAA,EACA,qBAAqB,SAAS,WAAW;AACvC,SAAK,gBAAgB;AACrB,WAAO,aAAa,KAAK,IAAI,MAAM,KAAK,GAAG,kBAAkB,SAAS,SAAS,CAAC;AAAA,EAClF;AAAA,EACA,0BAA0B,SAAS,aAAa;AAC9C,SAAK,gBAAgB;AACrB,WAAO,KAAK,GAAG,mBAAmB,SAAS,WAAW;AAAA,EACxD;AAAA,EACA,sBAAsB,oBAAoB,iBAAiB,aAAa;AACtE,SAAK,gBAAgB;AACrB,SAAK,iBAAiB;AACtB,uCAAmC,KAAK,IAAI,oBAAoB,iBAAiB,WAAW;AAAA,EAC9F;AAAA,EACA,uBAAuB,qBAAqB,MAAM,SAAS;AACzD,SAAK,6BAA6B,qBAAqB,SAAS,IAAI;AAAA,EACtE;AAAA,EACA,6BAA6B,2BAA2B,MAAM,SAAS;AACrE,SAAK,gBAAgB;AACrB,UAAM,CAAC,OAAO,MAAM,IAAI,uCAAuC,MAAM,OAAO;AAC5E,SAAK,6BAA6B,2BAA2B,OAAO,MAAM;AAAA,EAC5E;AAAA,EACA,2BAA2B,UAAU,SAAS,aAAa,YAAY;AACrE,SAAK,iCAAiC,aAAa,UAAU,YAAY,OAAO;AAAA,EAClF;AAAA,EACA,iCAAiC,UAAU,SAAS,aAAa,YAAY;AAC3E,UAAM,IAAI,MAAM,mDAAmD;AAAA,EACrE;AAAA,EACA,gBAAgB;AACd,QAAI,KAAK,WAAW,MAAM;AACxB,sBAAgB,KAAK,IAAI,KAAK,OAAO;AAAA,IACvC;AACA,wBAAoB,KAAK,EAAE;AAAA,EAC7B;AAAA,EACA,iBAAiB;AACf,SAAK,gBAAgB;AACrB,SAAK,iBAAiB;AACtB,UAAM,KAAK,KAAK;AAChB,QAAI,KAAK,OAAO;AACd,WAAK,cAAc;AAAA,IACrB;AACA,iBAAa,IAAI,MAAM,GAAG,aAAa,GAAG,WAAW,GAAG,GAAG,gBAAgB,CAAC,CAAC;AAAA,EAC/E;AAAA,EACA,iCAAiC;AAC/B,SAAK,gBAAgB;AACrB,iBAAa,KAAK,IAAI,MAAM,KAAK,GAAG,OAAO,CAAC;AAAA,EAC9C;AAAA,EACA,yBAAyB;AACvB,QAAI,KAAK,+BAA+B,MAAM;AAC5C,WAAK,8BAA8B,oBAAoB,KAAK,IAAI,IAAI,EAAE,UAAU,8CAA8C,MAAM,IAAI,oCAAoC,0BAA0B;AAAA,IACxM;AACA,WAAO,KAAK;AAAA,EACd;AAAA,EACA,+BAA+B;AAC7B,WAAO,KAAK,uBAAuB;AAAA,EACrC;AAAA,EACA,+BAA+B;AAC7B,WAAO,KAAK,uBAAuB;AAAA,EACrC;AAAA,EACA,aAAa;AACX,QAAI,IAAI,EAAE,UAAU,8CAA8C,MAAM,GAAG;AACzE,YAAM,MAAM,KAAK;AACjB,YAAM,OAAO,KAAK,6BAA6B;AAC/C,YAAM,SAAS,IAAI,YAAY;AAC/B,UAAI,WAAW,KAAK,kBAAkB,MAAM;AAC5C,aAAO;AAAA,IACT;AACA,UAAM,MAAM,KAAK,6BAA6B;AAC9C,UAAM,QAAQ,IAAI,eAAe;AACjC,QAAI,cAAc,IAAI,kBAAkB,KAAK;AAC7C,WAAO;AAAA,EACT;AAAA,EACA,WAAW;AACT,QAAI,IAAI,EAAE,UAAU,8CAA8C,MAAM,GAAG;AACzE,YAAM,MAAM,KAAK;AACjB,YAAM,OAAO,KAAK,6BAA6B;AAC/C,UAAI,SAAS,KAAK,gBAAgB;AAClC;AAAA,IACF;AACA,UAAM,MAAM,KAAK,6BAA6B;AAC9C,QAAI,YAAY,IAAI,gBAAgB;AAAA,EACtC;AAAA,EACA,MAAM,uBAAuB,OAAO;AAClC,UAAM,aAAa,YAAY,MAAM,KAAK,YAAY,KAAK,iBAAiB,OAAO,IAAI,EAAE,UAAU,8CAA8C,CAAC,CAAC;AACnJ,WAAO,KAAK,aAAa,OAAO,IAAI,EAAE,UAAU,8CAA8C,CAAC;AAAA,EACjG;AAAA,EACA,aAAa,OAAO,mBAAmB;AACrC,QAAI,sBAAsB,GAAG;AAC3B,aAAO;AAAA,IACT;AACA,QAAI,sBAAsB,GAAG;AAC3B,YAAM,MAAM,KAAK;AACjB,YAAM,mBAAmB,IAAI,kBAAkB,OAAO,IAAI,YAAY;AACtE,aAAO,mBAAmB;AAAA,IAC5B,OAAO;AACL,YAAM,MAAM,KAAK,6BAA6B;AAC9C,YAAM,mBAAmB,IAAI,kBAAkB,OAAO,IAAI,gBAAgB;AAC1E,aAAO,mBAAmB;AAAA,IAC5B;AAAA,EACF;AAAA,EACA,iBAAiB,OAAO,mBAAmB;AACzC,QAAI,sBAAsB,GAAG;AAC3B,aAAO;AAAA,IACT;AACA,QAAI,sBAAsB,GAAG;AAC3B,YAAM,MAAM,KAAK;AACjB,YAAM,MAAM,KAAK,6BAA6B;AAC9C,YAAM,YAAY,IAAI,kBAAkB,OAAO,IAAI,sBAAsB;AACzE,UAAI,KAAK,YAAY,MAAM;AACzB,aAAK,WAAW,KAAK,GAAG,aAAa,IAAI,gBAAgB;AAAA,MAC3D;AACA,aAAO,aAAa,CAAC,KAAK;AAAA,IAC5B,OAAO;AACL,YAAM,MAAM,KAAK,6BAA6B;AAC9C,YAAM,YAAY,IAAI,kBAAkB,OAAO,IAAI,0BAA0B;AAC7E,UAAI,KAAK,YAAY,MAAM;AACzB,aAAK,WAAW,KAAK,GAAG,aAAa,IAAI,gBAAgB;AAAA,MAC3D;AACA,aAAO,aAAa,CAAC,KAAK;AAAA,IAC5B;AAAA,EACF;AAAA,EACA,UAAU,cAAc;AACtB,WAAO,IAAI,QAAQ,CAAC,YAAY;AAC9B,WAAK,cAAc,MAAM,aAAa,cAAc,GAAG,MAAM,QAAQ,CAAC;AAAA,IACxE,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMS,SAAQ,qBAAqB,KAAK,YAAY,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAC1E,aAAS,KAAK,GAAG,MAAMA,QAAO,EAAE,IAAI;AAClC,YAAM,EAAE,UAAU,IAAI,KAAK,YAAY;AACvC,gBAAU;AAAA,IACZ;AACA,SAAK,cAAc,KAAK,YAAY,MAAMA,SAAQ,CAAC;AAAA,EACrD;AAAA,EACA,cAAc,UAAU,WAAW;AACjC,SAAK,YAAY,KAAK,EAAE,UAAU,UAAU,CAAC;AAC7C,QAAI,KAAK,YAAY,SAAS,GAAG;AAC/B;AAAA,IACF;AACA,iBAAa,YAAY,MAAM;AAC7B,WAAK,UAAU;AACf,aAAO,KAAK,YAAY,WAAW;AAAA,IACrC,CAAC;AAAA,EACH;AAAA,EACA,yBAAyB,SAAS;AAChC,SAAK,gBAAgB;AACrB,kCAA8B,KAAK,IAAI,SAAS,KAAK,WAAW;AAChE,QAAI,KAAK,OAAO;AACd,0BAAoB,KAAK,EAAE;AAAA,IAC7B;AAAA,EACF;AAAA,EACA,6BAA6B;AAC3B,QAAI,KAAK,iBAAiB,MAAM;AAC9B,oCAA8B,KAAK,IAAI,KAAK,eAAe,KAAK,WAAW;AAC3E,UAAI,KAAK,OAAO;AACd,4BAAoB,KAAK,EAAE;AAAA,MAC7B;AAAA,IACF,OAAO;AACL,wCAAkC,KAAK,IAAI,KAAK,WAAW;AAAA,IAC7D;AAAA,EACF;AAAA,EACA,qBAAqB,SAAS,mBAAmB;AAC/C,SAAK,yBAAyB,OAAO;AACrC,UAAM,SAAS,kBAAkB;AACjC,SAAK,2BAA2B;AAChC,WAAO;AAAA,EACT;AAAA,EACA,6BAA6B,gCAAgC,OAAO,QAAQ;AAC1E,SAAK,gBAAgB;AACrB,UAAM,KAAK,KAAK;AAChB,kCAA8B,IAAI,gCAAgC,KAAK,WAAW;AAClF,QAAI,KAAK,OAAO;AACd,0BAAoB,EAAE;AAAA,IACxB;AACA,SAAK,gBAAgB;AACrB,iBAAa,IAAI,MAAM,GAAG,SAAS,GAAG,GAAG,OAAO,MAAM,CAAC;AACvD,iBAAa,IAAI,MAAM,GAAG,QAAQ,GAAG,GAAG,OAAO,MAAM,CAAC;AAAA,EACxD;AAAA,EACA,iCAAiC,GAAG,GAAG,OAAO,QAAQ;AACpD,SAAK,gBAAgB;AACrB,iBAAa,KAAK,IAAI,MAAM,KAAK,GAAG,QAAQ,GAAG,GAAG,OAAO,MAAM,CAAC;AAAA,EAClE;AAAA,EACA,kBAAkB;AAChB,QAAI,KAAK,UAAU;AACjB,YAAM,IAAI,MAAM,yCAAyC;AAAA,IAC3D;AAAA,EACF;AAAA,EACA,mBAAmB;AACjB,QAAI,KAAK,WAAW,MAAM;AACxB,YAAM,IAAI,MAAM,kCAAkC;AAAA,IACpD;AAAA,EACF;AACF;AACA,SAAS,qBAAqB,KAAK;AACjC,MAAI,KAAK;AACT,SAAO,KAAK,IAAI,QAAQ,EAAE,IAAI;AAC5B,UAAM,SAAS,IAAI,IAAI;AACvB,QAAI,CAAC,QAAQ;AACX;AAAA,IACF;AAAA,EACF;AACA,SAAO,KAAK;AACd;AAGA,IAAI,EAAE,SAAS,YAAY,cAAc,iBAAiB,oBAAoB,uBAAuB,UAAU,aAAa,YAAY,eAAe,WAAW,cAAc,SAAS,YAAY,WAAW,cAAc,WAAW,cAAc,cAAc,iBAAiB,cAAc,iBAAiB,aAAa,gBAAgB,kBAAkB,qBAAqB,UAAU,aAAa,eAAe,kBAAkB,cAAc,iBAAiB,SAAS,YAAY,SAAS,YAAY,aAAa,gBAAgB,aAAa,gBAAgB,cAAc,iBAAiB,SAAS,YAAY,cAAc,iBAAiB,UAAU,aAAa,WAAW,cAAc,WAAW,cAAc,aAAa,gBAAgB,aAAa,gBAAgB,eAAe,kBAAkB,WAAW,cAAc,yBAAyB,4BAA4B,mBAAmB,sBAAsB,4BAA4B,+BAA+B,UAAU,aAAa,kBAAkB,qBAAqB,kBAAkB,qBAAqB,iBAAiB,oBAAoB,4BAA4B,+BAA+B,SAAS,YAAY,UAAU,aAAa,UAAU,aAAa,eAAe,kBAAkB,YAAY,cAAc,IAAI;AAGpyC,SAAS,eAAe,MAAM,MAAM;AAClC,SAAO,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG,EAAE,MAAM,GAAG,IAAI,EAAE,IAAI,CAAC,MAAM,GAAG,QAAQ,GAAG;AAChF;AACA,SAAS,YAAY,MAAM,MAAM;AAC/B,MAAI,SAAS,GAAG;AACd,WAAO,CAAC,IAAI;AAAA,EACd;AACA,SAAO,eAAe,MAAM,IAAI;AAClC;AACA,SAAS,gBAAgB,MAAM,MAAM;AACnC,MAAI,SAAS,GAAG;AACd,WAAO;AAAA,EACT;AACA,MAAI,UAAU;AACd,WAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,eAAW,KAAK;AAChB,QAAI,KAAK,OAAO,GAAG;AACjB,iBAAW;AAAA,IACb;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc;AACnB,SAAK,OAAO,YAAY;AACxB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,QAAI,KAAK,SAAS,GAAG;AACnB,WAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,IAKlB,OAAO;AACL,YAAM,WAAW,YAAY,MAAM,KAAK,IAAI;AAC5C,YAAM,QAAQ,kBAAkB,KAAK,IAAI;AACzC,YAAM,uBAAuB,KAAK,wBAAwB,QAAQ;AAClE,YAAM,UAAU,KAAK,SAAS,QAAQ;AACtC,YAAM,SAAS,KAAK,UAAU,QAAQ;AACtC,WAAK,WAAW;AAAA;AAAA,YAEV;AAAA;AAAA,eAEG;AAAA;AAAA;AAAA,cAGD;AAAA;AAAA,6BAEe;AAAA;AAAA;AAAA;AAAA,IAIzB;AAAA,EACF;AAAA,EACA,mBAAmB,MAAM;AACvB,UAAM,UAAU,CAAC;AACjB,aAAS,MAAM,GAAG,OAAO,GAAG,OAAO;AACjC,eAAS,MAAM,GAAG,OAAO,GAAG,OAAO;AACjC,YAAI,QAAQ,GAAG,QAAQ,IAAI,MAAM,UAAU,QAAQ,IAAI,MAAM;AAC7D,iBAAS,IAAI,GAAG,IAAI,KAAK,MAAM,KAAK;AAClC,kBAAQ,GAAG,KAAK,KAAK,SAAS,IAAI,QAAQ;AAAA,QAC5C;AACA,gBAAQ,KAAK,KAAK;AAAA,MACpB;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,wBAAwB,MAAM;AAC5B,QAAI,KAAK,SAAS,GAAG;AACnB,aAAO,QAAQ,KAAK,sBAAsB,aAAa,KAAK,YAAY;AAAA,IAC1E;AACA,QAAI,OAAO;AACX,aAAS,KAAK,KAAK,OAAO,GAAG,KAAK,KAAK,MAAM,MAAM;AACjD,cAAQ,GAAG,KAAK,UAAU,KAAK,sBAAsB,YAAY,QAAQ,KAAK,YAAY;AAC1F,UAAI,KAAK,KAAK,OAAO,GAAG;AACtB,gBAAQ;AAAA,MACV;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,SAAS,MAAM;AACb,QAAI,KAAK,SAAS,GAAG;AACnB,aAAO;AAAA,IACT;AACA,UAAM,YAAY,KAAK,MAAM,EAAE;AAC/B,UAAM,MAAM,KAAK,sBAAsB,YAAY,KAAK,cAAc,KAAK,YAAY,KAAK,OAAO;AACnG,UAAM,MAAM,KAAK,sBAAsB,YAAY,KAAK,cAAc,KAAK,YAAY,KAAK,OAAO;AACnG,WAAO;AAAA,gBACK,UAAU;AAAA,gBACV,UAAU;AAAA;AAAA;AAAA;AAAA,4BAIE;AAAA,4BACA;AAAA;AAAA,EAE1B;AAAA,EACA,UAAU,MAAM;AACd,UAAM,eAAe,KAAK,mBAAmB,IAAI;AACjD,QAAI,KAAK,SAAS,GAAG;AACnB,YAAM,WAAW,KAAK,sBAAsB,aAAa,KAAK,YAAY;AAC1E,aAAO,wBAAwB;AAAA,IACjC;AACA,WAAO,QAAQ,aAAa;AAAA,gCACA,aAAa;AAAA,gCACb,aAAa;AAAA,yCACJ,aAAa;AAAA,EACpD;AACF;AAGA,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,aAAa,YAAY;AACnC,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,iBAAiB,CAAC,EAAE,MAAM,cAAc,MAAM,QAAQ,CAAC;AAC5D,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,QAAI,WAAW;AACf,aAAS,KAAK,GAAG,KAAK,GAAG,MAAM;AAC7B,UAAI,SAAS;AACb,UAAI,KAAK,MAAM,GAAG;AAChB,kBAAU;AAAA,MACZ;AACA,UAAI,KAAK,GAAG;AACV,kBAAU;AAAA,MACZ;AACA,kBAAY;AAAA,UACR;AAAA,UACA,KAAK,IAAI,4CAA4C;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,mBAM5C;AAAA;AAAA,UAET,KAAK,IAAI,MAAM;AAAA;AAAA,IAErB;AACA,SAAK,WAAW;AAAA,QACZ,uBAAuB,YAAY,KAAK,mBAAmB;AAAA,QAC3D,KAAK,sBAAsB,yBAAyB,IAAI,mBAAmB,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,qBAQzE,KAAK,sBAAsB,gBAAgB,YAAY;AAAA,qBACvD,KAAK,sBAAsB,gBAAgB,YAAY;AAAA;AAAA,UAElE;AAAA;AAAA;AAAA;AAAA;AAAA,EAKR;AACF;AACA,SAAS,uBAAuB,OAAO,qBAAqB;AAC1D,QAAM,yBAAyB,sBAAsB,4CAA4C,CAAC,KAAK,KAAK,GAAG,GAAG,YAAY,IAAI,mCAAmC,CAAC,KAAK,KAAK,GAAG,GAAG,KAAK;AAC3L,SAAO;AAAA;AAAA,QAED;AAAA;AAAA;AAAA;AAIR;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,OAAO;AACjB,SAAK,QAAQ;AACb,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AACvB,SAAK,qBAAqB;AAC1B,SAAK,gBAAgB;AACrB,SAAK,eAAe,CAAC;AACrB,SAAK,aAAa;AAClB,SAAK,eAAe,CAAC;AAAA,EACvB;AAAA,EACA,eAAe,SAAS,OAAO,UAAU;AACvC,UAAM,kBAAkB,kCAAkC,OAAO,QAAQ;AACzE,UAAM,WAAW,uBAAuB,SAAS,iBAAiB,QAAQ;AAC1E,QAAI,EAAE,YAAY,KAAK,eAAe;AACpC,WAAK,aAAa,YAAY,CAAC;AAAA,IACjC;AACA,QAAI,EAAE,YAAY,KAAK,eAAe;AACpC,WAAK,aAAa,YAAY,CAAC;AAAA,IACjC;AACA,UAAM,WAAW,aAAa,SAAS,iBAAiB,KAAK,MAAM,IAAI,KAAK,MAAM,eAAe,QAAQ;AACzG,QAAI,KAAK,aAAa,UAAU,SAAS,GAAG;AAC1C,WAAK;AACL,WAAK;AACL,WAAK,iBAAiB;AACtB,WAAK,IAAI;AACT,YAAM,cAAc,KAAK,aAAa,UAAU,MAAM;AACtD,WAAK,aAAa,UAAU,KAAK,WAAW;AAC5C,aAAO;AAAA,IACT;AACA,QAAI;AACJ,QAAI,oBAAoB,oBAAoB,oBAAoB;AAC9D,mBAAa,KAAK,MAAM,0BAA0B,QAAQ,IAAI,QAAQ,EAAE;AAAA,IAC1E,WAAW,oBAAoB,oBAAoB,oBAAoB;AACrE,mBAAa,KAAK,MAAM,iCAAiC,QAAQ,IAAI,QAAQ,EAAE;AAAA,IACjF,WAAW,oBAAoB,oBAAoB,kBAAkB;AACnE,mBAAa,KAAK,MAAM,2BAA2B,QAAQ,IAAI,QAAQ,EAAE;AAAA,IAC3E,WAAW,oBAAoB,oBAAoB,kBAAkB;AACnE,mBAAa,KAAK,MAAM,2BAA2B,QAAQ,IAAI,QAAQ,EAAE;AAAA,IAC3E,WAAW,oBAAoB,oBAAoB,0BAA0B;AAC3E,mBAAa,KAAK,MAAM,iCAAiC,QAAQ,IAAI,QAAQ,EAAE;AAAA,IACjF;AACA,SAAK,aAAa,UAAU,KAAK,UAAU;AAC3C,SAAK;AACL,SAAK,sBAAsB;AAC3B,SAAK,IAAI;AACT,WAAO;AAAA,EACT;AAAA,EACA,eAAe,SAAS,OAAO,gBAAgB,UAAU;AACvD,QAAI,KAAK,gBAAgB,MAAM;AAC7B;AAAA,IACF;AACA,UAAM,kBAAkB,kCAAkC,gBAAgB,QAAQ;AAClF,UAAM,WAAW,uBAAuB,OAAO,iBAAiB,QAAQ;AACxE,QAAI,EAAE,YAAY,KAAK,eAAe;AACpC,WAAK,aAAa,YAAY,CAAC;AAAA,IACjC;AACA,UAAM,WAAW,aAAa,OAAO,iBAAiB,KAAK,MAAM,IAAI,KAAK,MAAM,eAAe,QAAQ;AACvG,UAAM,qBAAqB,IAAI,EAAE,IAAI,gCAAgC;AACrE,QAAI,uBAAuB,MAAM,KAAK,qBAAqB,oBAAoB;AAC7E,WAAK,MAAM,oBAAoB,QAAQ,OAAO;AAC9C,WAAK,sBAAsB;AAAA,IAC7B,OAAO;AACL,WAAK,aAAa,UAAU,KAAK,OAAO;AACxC,WAAK;AACL,WAAK,iBAAiB;AAAA,IACxB;AACA,SAAK;AACL,UAAM,UAAU,KAAK,aAAa;AAClC,UAAM,WAAW,QAAQ,QAAQ,OAAO;AACxC,QAAI,WAAW,GAAG;AAChB,YAAM,IAAI,MAAM,0EAA0E;AAAA,IAC5F;AACA,YAAQ,OAAO,UAAU,CAAC;AAC1B,SAAK,IAAI;AAAA,EACX;AAAA,EACA,MAAM;AACJ,QAAI,CAAC,KAAK,YAAY;AACpB;AAAA,IACF;AACA,UAAM,QAAQ,KAAK,kBAAkB,KAAK;AAC1C,YAAQ,IAAI,aAAa,GAAG,KAAK,qBAAqB,KAAK,mBAAmB,IAAI,QAAQ;AAC1F,UAAM,YAAY,KAAK,gBAAgB,KAAK;AAC5C,YAAQ,IAAI,oBAAoB,KAAK,oBAAoB;AACzD,YAAQ,IAAI,iBAAiB,KAAK,kBAAkB,KAAK,MAAM,MAAM,SAAS,KAAK;AAAA,EACrF;AAAA,EACA,IAAI,oBAAoB;AACtB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,eAAe;AACjB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,qBAAqB;AACnB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,qBAAqB;AACnB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,UAAU;AACR,QAAI,KAAK,gBAAgB,MAAM;AAC7B;AAAA,IACF;AACA,eAAW,YAAY,KAAK,cAAc;AACxC,WAAK,aAAa,UAAU,QAAQ,CAAC,QAAQ;AAC3C,aAAK,MAAM,oBAAoB,IAAI,OAAO;AAAA,MAC5C,CAAC;AAAA,IACH;AACA,eAAW,YAAY,KAAK,cAAc;AACxC,WAAK,aAAa,UAAU,QAAQ,CAAC,QAAQ;AAC3C,aAAK,MAAM,oBAAoB,IAAI,OAAO;AAAA,MAC5C,CAAC;AAAA,IACH;AACA,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AACvB,SAAK,qBAAqB;AAC1B,SAAK,gBAAgB;AAAA,EACvB;AACF;AACA,SAAS,0BAA0B,IAAI,gBAAgB;AACrD,QAAM,QAAQ;AACd,MAAI,mBAAmB,MAAM,MAAM;AACjC,WAAO;AAAA,EACT,WAAW,mBAAmB,MAAM,MAAM;AACxC,WAAO;AAAA,EACT,WAAW,mBAAmB,MAAM,SAAS;AAC3C,WAAO;AAAA,EACT,WAAW,mBAAmB,GAAG,MAAM;AACrC,WAAO;AAAA,EACT,WAAW,mBAAmB,MAAM,SAAS;AAC3C,WAAO;AAAA,EACT,WAAW,mBAAmB,MAAM,OAAO;AACzC,WAAO;AAAA,EACT;AACA,QAAM,IAAI,MAAM,2BAA2B,gBAAgB;AAC7D;AACA,SAAS,aAAa,OAAO,iBAAiB,IAAI,eAAe,UAAU;AACzE,QAAM,iBAAiB,iCAAiC,iBAAiB,aAAa;AACtF,MAAI;AACJ,MAAI,UAAU;AACZ,UAAM,CAAC,aAAa,YAAY,IAAI,uCAAuC,MAAM,IAAI,MAAM,EAAE;AAC7F,kBAAc,cAAc;AAAA,EAC9B,OAAO;AACL,UAAM,CAAC,OAAO,MAAM,IAAI,yCAAyC,MAAM,IAAI,MAAM,EAAE;AACnF,kBAAc,QAAQ;AAAA,EACxB;AACA,QAAM,mBAAmB,0BAA0B,IAAI,cAAc;AACrE,SAAO,cAAc;AACvB;AACA,SAAS,iCAAiC,iBAAiB,eAAe;AACxE,UAAQ;AAAA,SACD,oBAAoB;AACvB,aAAO,wCAAwC,aAAa;AAAA,SACzD,oBAAoB;AACvB,aAAO,+CAA+C,aAAa;AAAA,SAChE,oBAAoB;AACvB,aAAO,yCAAyC,aAAa;AAAA,SAC1D,oBAAoB;AACvB,aAAO,yCAAyC,aAAa;AAAA,SAC1D,oBAAoB;AACvB,aAAO,+CAA+C,aAAa;AAAA;AAEnE,YAAM,IAAI,MAAM,iCAAiC,iBAAiB;AAAA;AAExE;AACA,SAAS,+BAA+B,UAAU;AAChD,MAAI,IAAI,EAAE,QAAQ,8BAA8B,GAAG;AACjD,QAAI,UAAU;AACZ,aAAO,oBAAoB;AAAA,IAC7B;AACA,WAAO,oBAAoB;AAAA,EAC7B;AACA,MAAI,UAAU;AACZ,WAAO,oBAAoB;AAAA,EAC7B;AACA,SAAO,oBAAoB;AAC7B;AACA,SAAS,kCAAkC,gBAAgB,UAAU;AACnE,MAAI,mBAAmB,aAAa,QAAQ;AAC1C,WAAO,oBAAoB;AAAA,EAC7B,WAAW,mBAAmB,aAAa,UAAU,kBAAkB,MAAM;AAC3E,WAAO,+BAA+B,QAAQ;AAAA,EAChD,WAAW,mBAAmB,aAAa,YAAY,mBAAmB,aAAa,QAAQ;AAC7F,WAAO,oBAAoB;AAAA,EAC7B;AACA,QAAM,IAAI,MAAM,gCAAgC,gBAAgB;AAClE;AACA,SAAS,uBAAuB,cAAc,iBAAiB,UAAU;AACvE,SAAO,GAAG,aAAa,MAAM,aAAa,MAAM,mBAAmB;AACrE;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,QAAQ,WAAW;AAC7B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAUR;AACF;AACA,IAAI,oBAAoB;AACxB,IAAI,SAAS;AACb,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,OAAO,oBAAoB;AAAA;AAAA;AAG/B,IAAI,QAAQ,oBAAoB;AAAA;AAAA;AAGhC,IAAI,QAAQ;AACZ,IAAI,UAAU;AAGd,IAAI,UAAU;AACd,IAAI,OAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUX,IAAI,QAAQ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWZ,IAAI,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWb,IAAI,WAAW;AACf,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,QAAQ,WAAW;AAC7B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAUR;AACF;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,UAAM,OAAO,YAAY;AACzB,UAAM,WAAW,YAAY,MAAM,IAAI;AACvC,UAAM,QAAQ,kBAAkB,IAAI;AACpC,UAAM,eAAe,gBAAgB,MAAM,QAAQ;AACnD,UAAM,YAAY,SAAS,MAAM,EAAE;AACnC,UAAM,UAAU,QAAQ,IAAI,OAAO,QAAQ,UAAU,KAAK,GAAG;AAC7D,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA,kCACwB;AAAA;AAAA,4CAEU;AAAA;AAAA;AAAA,EAG1C;AACF;AAGA,IAAI,aAAa,qBAAqB;AACtC,IAAI,mBAAmB;AACvB,IAAI,mBAAmB;AACvB,IAAI,eAAe,CAAC;AACpB,SAAS,eAAe,cAAc;AACpC,MAAI,gBAAgB,cAAc;AAChC,WAAO,aAAa;AAAA,EACtB;AACA,eAAa,gBAAgB,CAAC;AAC9B,SAAO,aAAa;AACtB;AACA,IAAI,6BAA6B,IAAI,EAAE,UAAU,4BAA4B;AAC7E,IAAI,yBAAyB;AAC7B,SAAS,qBAAqB;AAC5B,MAAI,IAAI,EAAE,OAAO,UAAU,MAAM;AAC/B,WAAO;AAAA,EACT;AACA,SAAO,IAAI,EAAE,OAAO,OAAO,SAAS,IAAI,EAAE,OAAO,OAAO,QAAQ,OAAO,mBAAmB,yBAAyB,OAAO;AAC5H;AACA,IAAI,mBAAmB,cAAc,cAAc;AAAA,EACjD,YAAY,aAAa;AACvB,UAAM;AACN,SAAK,cAA8B,oBAAI,QAAQ;AAC/C,SAAK,kBAAkC,oBAAI,QAAQ;AACnD,SAAK,eAA+B,oBAAI,QAAQ;AAChD,SAAK,gBAAgB;AACrB,SAAK,eAAe;AACpB,SAAK,iBAAiB;AACtB,SAAK,kBAAkB;AACvB,SAAK,oBAAoB;AACzB,SAAK,iBAAiB;AACtB,SAAK,WAAW;AAChB,QAAI,CAAC,IAAI,EAAE,QAAQ,WAAW,GAAG;AAC/B,YAAM,IAAI,MAAM,uCAAuC;AAAA,IACzD;AACA,QAAI;AACJ,QAAI,eAAe,MAAM;AACvB,UAAI,uBAAuB,cAAc;AACvC,mBAAW;AAAA,MACb,OAAO;AACL,cAAM,KAAK,gBAAgB,IAAI,EAAE,UAAU,eAAe,GAAG,WAAW;AACxE,mBAAW,IAAI,aAAa,EAAE;AAAA,MAChC;AACA,WAAK,cAAc,CAAC;AACpB,WAAK,sBAAsB;AAAA,IAC7B,OAAO;AACL,YAAM,KAAK,gBAAgB,IAAI,EAAE,UAAU,eAAe,CAAC;AAC3D,iBAAW,IAAI,aAAa,EAAE;AAC9B,WAAK,cAAc,eAAe,IAAI,EAAE,UAAU,eAAe,CAAC;AAClE,WAAK,sBAAsB;AAAA,IAC7B;AACA,SAAK,QAAQ;AACb,SAAK,SAAS,KAAK,MAAM,GAAG;AAC5B,SAAK,iBAAiB,IAAI,eAAe,KAAK,KAAK;AACnD,SAAK,qBAAqB,mBAAmB;AAC7C,SAAK,UAAU,IAAI,YAAY,MAAM,OAAO,CAAC;AAAA,EAC/C;AAAA,EACA,aAAa;AACX,WAAO,iBAAiB;AAAA,EAC1B;AAAA,EACA,aAAa;AACX,WAAO,KAAK,QAAQ,WAAW,IAAI,KAAK;AAAA,EAC1C;AAAA,EACA,MAAM,QAAQ,OAAO,OAAO;AAC1B,QAAI,IAAI,EAAE,QAAQ,gCAAgC,KAAK,IAAI,EAAE,QAAQ,OAAO,GAAG;AAC7E,WAAK,uBAAuB,MAAM;AAAA,IACpC;AACA,QAAI,UAAU,eAAe,UAAU,MAAM;AAC3C,YAAM,IAAI,MAAM,uEAAuE;AAAA,IACzF;AACA,UAAM,SAAS,EAAE,IAAI,KAAK,WAAW,EAAE;AACvC,SAAK,QAAQ,IAAI,QAAQ,EAAE,OAAO,OAAO,QAAQ,OAAO,aAAa,QAAQ,UAAU,EAAE,CAAC;AAC1F,WAAO;AAAA,EACT;AAAA,EACA,SAAS,QAAQ;AACf,QAAI,KAAK,QAAQ,IAAI,MAAM,GAAG;AAC5B,YAAM,aAAa,KAAK,QAAQ,IAAI,MAAM;AAC1C,aAAO,WAAW;AAAA,IACpB;AACA,WAAO;AAAA,EACT;AAAA,EACA,OAAO,QAAQ;AACb,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,YAAQ;AAAA,EACV;AAAA,EACA,OAAO,QAAQ;AACb,QAAI,KAAK,QAAQ,IAAI,MAAM,GAAG;AAC5B,YAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,cAAQ;AAAA,IACV;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ,OAAO,OAAO,UAAU;AAC3C,QAAI,IAAI,EAAE,QAAQ,OAAO,GAAG;AAC1B,WAAK,uBAAuB,MAAM;AAAA,IACpC;AACA,QAAI,UAAU,aAAa;AACzB,YAAM,IAAI,MAAM,uEAAuE;AAAA,IACzF;AACA,SAAK,QAAQ,IAAI,QAAQ,EAAE,OAAO,OAAO,QAAQ,OAAO,aAAa,QAAQ,SAAS,CAAC;AAAA,EACzF;AAAA,EACA,8BAA8B,YAAY;AACxC,SAAK,YAAY,WAAW,MAAM;AAAA,EACpC;AAAA,EACA,SAAS,QAAQ;AACf,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,UAAM,EAAE,QAAQ,OAAO,oBAAoB,OAAO,QAAQ,OAAO,SAAS,IAAI;AAC9E,QAAI,UAAU,MAAM;AAClB,UAAI;AACJ,UAAI,UAAU;AACZ,kBAAU,IAAI,qBAAqB,OAAO,KAAK;AAAA,MACjD,OAAO;AACL,kBAAU,IAAI,eAAe,OAAO,KAAK;AAAA,MAC3C;AACA,YAAM,MAAM,KAAK,gBAAgB,SAAS,CAAC,EAAE,QAAQ,OAAO,MAAM,CAAC,GAAG,KAAK;AAC3E,YAAM,OAAO,KAAK,SAAS,IAAI,MAAM;AACrC,WAAK,8BAA8B,GAAG;AACtC,aAAO;AAAA,IACT;AACA,QAAI,UAAU,MAAM;AAClB,aAAO,KAAK,qBAAqB,MAAM;AAAA,IACzC;AACA,QAAI,UAAU,UAAU;AACtB,aAAO;AAAA,IACT;AACA,UAAM,oBAAoB,KAAK,gBAAgB;AAC/C,QAAI;AACJ,QAAI,mBAAmB;AACrB,cAAQ,aAAa,IAAI;AAAA,IAC3B;AACA,QAAI;AACJ,QAAI,UAAU,aAAa;AACzB,YAAM,aAAa,KAAK,SAAS,mBAAmB,KAAK,MAAM;AAC/D,YAAM,aAAa,KAAK,SAAS,mBAAmB,KAAK,MAAM;AAC/D,eAAS,qBAAqB,uBAAuB,YAAY,UAAU;AAAA,IAC7E,OAAO;AACL,eAAS,KAAK,qBAAqB,MAAM;AAAA,IAC3C;AACA,QAAI,mBAAmB;AACrB,WAAK,kBAAkB,aAAa,IAAI,IAAI;AAAA,IAC9C;AACA,WAAO,KAAK,qBAAqB,QAAQ,MAAM;AAAA,EACjD;AAAA,EACA,MAAM,KAAK,QAAQ;AACjB,QAAI,KAAK,YAAY,IAAI,MAAM,GAAG;AAChC,YAAM,eAAe,KAAK,YAAY,IAAI,MAAM;AAChD,aAAO,IAAI,QAAQ,CAAC,YAAY,aAAa,KAAK,OAAO,CAAC;AAAA,IAC5D;AACA,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,UAAM,EAAE,QAAQ,OAAO,OAAO,QAAQ,OAAO,oBAAoB,SAAS,IAAI;AAC9E,QAAI,UAAU,MAAM;AAClB,UAAI;AACJ,UAAI,UAAU;AACZ,kBAAU,IAAI,qBAAqB,OAAO,KAAK;AAAA,MACjD,OAAO;AACL,kBAAU,IAAI,eAAe,OAAO,KAAK;AAAA,MAC3C;AACA,YAAM,MAAM,KAAK,gBAAgB,SAAS,CAAC,EAAE,QAAQ,OAAO,MAAM,CAAC,GAAG,KAAK;AAC3E,YAAM,OAAO,KAAK,KAAK,IAAI,MAAM;AACjC,WAAK,8BAA8B,GAAG;AACtC,aAAO;AAAA,IACT;AACA,QAAI,UAAU,MAAM;AAClB,aAAO,KAAK,qBAAqB,MAAM;AAAA,IACzC;AACA,QAAI,IAAI,EAAE,QAAQ,OAAO,GAAG;AAC1B,UAAI,CAAC,IAAI,EAAE,QAAQ,8BAA8B,KAAK,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC5F,cAAM,IAAI,MAAM,8FAA8F;AAAA,MAChH;AAAA,IACF;AACA,QAAI,UAAU;AACd,QAAI;AACJ,QAAI,UAAU,eAAe,IAAI,EAAE,IAAI,wBAAwB,GAAG;AAChE,0BAAoB,KAAK,OAAO,MAAM;AACtC,YAAM,UAAU,KAAK,QAAQ,IAAI,kBAAkB,MAAM;AACzD,gBAAU,KAAK,MAAM,wBAAwB,QAAQ,QAAQ,SAAS,GAAG,iBAAiB,KAAK,CAAC;AAAA,IAClG;AACA,SAAK,YAAY,IAAI,QAAQ,CAAC,CAAC;AAC/B,QAAI,UAAU,aAAa;AACzB,YAAM,KAAK,MAAM,sBAAsB;AAAA,IACzC;AACA,QAAI;AACJ,QAAI,UAAU,aAAa;AACzB,YAAM,KAAK,MAAM,QAAQ,IAAI;AAAA,QAC3B,KAAK,KAAK,mBAAmB,KAAK,MAAM;AAAA,QACxC,KAAK,KAAK,mBAAmB,KAAK,MAAM;AAAA,MAC1C,CAAC;AACD,YAAM,aAAa,GAAG;AACtB,YAAM,aAAa,GAAG;AACtB,aAAO,qBAAqB,uBAAuB,YAAY,UAAU;AAAA,IAC3E,WAAW,WAAW,MAAM;AAC1B,aAAO,KAAK,qBAAqB,MAAM;AAAA,IACzC,OAAO;AACL,YAAMT,QAAO,aAAa,cAAc,KAAK;AAC7C,aAAO,KAAK,MAAM,gCAAgC,SAASA,KAAI;AAAA,IACjE;AACA,QAAI,qBAAqB,MAAM;AAC7B,WAAK,8BAA8B,iBAAiB;AAAA,IACtD;AACA,QAAI,WAAW,MAAM;AACnB,YAAM,KAAK,KAAK,MAAM;AACtB,mBAAa,IAAI,MAAM,GAAG,aAAa,OAAO,CAAC;AAAA,IACjD;AACA,UAAM,YAAY,KAAK,qBAAqB,QAAQ,IAAI;AACxD,UAAM,cAAc,KAAK,YAAY,IAAI,MAAM;AAC/C,SAAK,YAAY,OAAO,MAAM;AAC9B,gBAAY,QAAQ,CAAC,YAAY,QAAQ,SAAS,CAAC;AACnD,QAAI,KAAK,gBAAgB,IAAI,MAAM,GAAG;AACpC,WAAK,gBAAgB,OAAO,MAAM;AAClC,UAAI,KAAK,YAAY,MAAM,GAAG;AAC5B,eAAO,EAAE,aAAa,QAAQ,IAAI;AAAA,MACpC;AACA,WAAK;AAAA,IACP;AACA,WAAO;AAAA,EACT;AAAA,EACA,UAAU,QAAQM,WAAU,CAAC,GAAG;AAC9B,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,UAAM,EAAE,QAAQ,OAAO,OAAO,QAAQ,OAAO,UAAU,QAAQ,IAAI;AACnE,QAAI,UAAU,aAAa;AACzB,YAAM,IAAI,MAAM,uDAAuD;AAAA,IACzE;AACA,QAAI,UAAU,MAAM;AAClB,UAAI;AACJ,UAAI,UAAU;AACZ,kBAAU,IAAI,qBAAqB,OAAO,KAAK;AAAA,MACjD,OAAO;AACL,kBAAU,IAAI,eAAe,OAAO,KAAK;AAAA,MAC3C;AACA,YAAM,MAAM,KAAK,gBAAgB,SAAS,CAAC,EAAE,QAAQ,OAAO,MAAM,CAAC,GAAG,KAAK;AAC3E,YAAM,eAAe,KAAK,UAAU,KAAKA,QAAO;AAChD,WAAK,8BAA8B,GAAG;AACtC,aAAO;AAAA,IACT;AACA,QAAI,WAAW,MAAM;AACnB,UAAI,UAAU,MAAM;AAClB,cAAM,IAAI,MAAM,gCAAgC;AAAA,MAClD,OAAO;AACL,cAAM,IAAI,MAAM,iCAAiC;AAAA,MACnD;AAAA,IACF;AACA,UAAM,YAAY,KAAK,OAAO,QAAQA,SAAQ,cAAc;AAC5D,UAAM,YAAY,OAAO,EAAE,yBAAyB,SAAS;AAC7D,UAAM,UAAU,KAAK,QAAQ,IAAI,UAAU,MAAM;AACjD,WAAO,OAAO,OAAO,EAAE,UAAU,GAAG,QAAQ,OAAO;AAAA,EACrD;AAAA,EACA,WAAW,IAAI;AACb,UAAM,OAAO,KAAK,SAAS,GAAG,MAAM;AACpC,QAAI,GAAG,UAAU,UAAU;AACzB,UAAI;AACF,cAAM,UAAU,KAAK,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC;AAC5D,eAAO,OAAO,GAAG,OAAO,GAAG,OAAO,OAAO;AAAA,MAC3C,SAAS,IAAP;AACA,cAAM,IAAI,MAAM,kDAAkD;AAAA,MACpE;AAAA,IACF;AACA,WAAO,OAAO,GAAG,OAAO,GAAG,OAAO,IAAI;AAAA,EACxC;AAAA,EACA,uBAAuB,QAAQ;AAC7B,QAAI,UAAU,MAAM;AAClB;AAAA,IACF;AACA,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,YAAM,MAAM,OAAO;AACnB,UAAI,CAAC,iBAAiB,GAAG,GAAG;AAC1B,YAAI,IAAI,EAAE,QAAQ,8BAA8B,GAAG;AACjD,gBAAM,MAAM,aAAa,kJAAkJ;AAAA,QAC7K;AACA,cAAM,MAAM,aAAa,2CAA2C;AAAA,MACtE;AAAA,IACF;AAAA,EACF;AAAA,EACA,qBAAqB,QAAQ;AAC3B,UAAM,EAAE,OAAO,OAAO,SAAS,IAAI,KAAK,QAAQ,IAAI,MAAM;AAC1D,UAAMN,QAAO,aAAa,cAAc,KAAK;AAC7C,QAAI,IAAI,EAAE,QAAQ,8BAA8B,GAAG;AACjD,YAAM,YAAY,KAAK,OAAO,MAAM;AACpC,YAAM,WAAW,KAAK,QAAQ,IAAI,UAAU,MAAM;AAClD,YAAM,QAAQ,KAAK,MAAM,gCAAgC,SAAS,QAAQ,SAAS,GAAG,iBAAiB,KAAK,CAAC,EAAE,SAAS,GAAGA,KAAI;AAC/H,WAAK,8BAA8B,SAAS;AAC5C,aAAO;AAAA,IACT;AACA,UAAM,yBAAyB,IAAI,EAAE,QAAQ,YAAY,KAAK,aAAa;AAC3E,UAAM,cAAc,yBAAyB,aAAa,KAAK,IAAI;AACnE,UAAM,UAAU,yBAAyB,IAAI,yBAAyB,WAAW,IAAI,IAAI,mBAAmB,WAAW;AACvH,UAAM,SAAS,KAAK,gBAAgB,SAAS,CAAC,EAAE,OAAO,aAAa,OAAO,OAAO,CAAC,GAAG,SAAS;AAC/F,UAAM,UAAU,KAAK,QAAQ,IAAI,OAAO,MAAM;AAC9C,UAAM,OAAO,KAAK,MAAM,gDAAgD,QAAQ,QAAQ,SAAS,QAAQ,SAAS,IAAI,QAAQ,SAAS,EAAE,EAAE,SAAS,GAAGA,KAAI;AAC3J,SAAK,8BAA8B,MAAM;AACzC,WAAO;AAAA,EACT;AAAA,EACA,iBAAiB;AACf,WAAO,IAAI,EAAE,UAAU,+CAA+C,IAAI;AAAA,EAC5E;AAAA,EACA,KAAK,GAAG;AACN,UAAM,kBAAkB,KAAK;AAC7B,UAAM,kBAAkB,CAAC;AACzB,QAAI,gBAAgB;AACpB,QAAI,KAAK,sBAAsB,MAAM;AACnC,WAAK,qBAAqB;AAC1B,sBAAgB;AAAA,IAClB,OAAO;AACL,WAAK,aAAa,KAAK,eAAe;AAAA,IACxC;AACA,SAAK,eAAe;AACpB,MAAE;AACF,UAAM,8BAA8B,aAAa,QAAQ,KAAK,aAAa,IAAI,CAAC,MAAM,EAAE,KAAK,CAAC,EAAE,OAAO,CAAC,MAAM,KAAK,IAAI;AACvH,UAAM,4BAA4B,aAAa,QAAQ,KAAK,aAAa,IAAI,CAAC,MAAM,EAAE,IAAI,CAAC,EAAE,OAAO,CAAC,MAAM,KAAK,IAAI;AACpH,SAAK,eAAe;AACpB,QAAI,eAAe;AACjB,WAAK,qBAAqB;AAAA,IAC5B;AACA,UAAM,MAAM;AAAA,MACV,cAAc,KAAK;AAAA,MACnB,gBAAgB,KAAK;AAAA,MACrB,UAAU;AAAA,MACV,QAAQ;AAAA,IACV;AACA,YAAQ,YAAY;AAClB,UAAI,IAAI,EAAE,UAAU,+CAA+C,IAAI,GAAG;AACxE,cAAM,WAAW,MAAM,QAAQ,IAAI,2BAA2B;AAC9D,YAAI,cAAc,aAAa,IAAI,QAAQ;AAC3C,YAAI,yBAAyB,MAAM,SAAS,IAAI,CAAC,GAAG,QAAQ,EAAE,MAAM,0BAA0B,KAAK,IAAI,EAAE,EAAE,EAAE,IAAI,CAAC,MAAM,GAAG,EAAE,SAAS,EAAE,IAAI,EAAE,KAAK,IAAI;AAAA,MACzJ,OAAO;AACL,YAAI,cAAc;AAAA,UAChB,OAAO;AAAA,QACT;AAAA,MACF;AACA,WAAK,eAAe;AACpB,WAAK,iBAAiB;AACtB,aAAO;AAAA,IACT,GAAG;AAAA,EACL;AAAA,EACA,SAAS;AACP,WAAO;AAAA,MACL,YAAY;AAAA,MACZ,eAAe,KAAK;AAAA,MACpB,wBAAwB,KAAK,eAAe;AAAA,MAC5C,mBAAmB,KAAK,eAAe;AAAA,IACzC;AAAA,EACF;AAAA,EACA,aAAa;AACX,QAAI,IAAI,EAAE,UAAU,+CAA+C,IAAI,GAAG;AACxE,aAAO,KAAK,MAAM,WAAW;AAAA,IAC/B;AACA,WAAO,EAAE,SAAS,aAAa,IAAI,GAAG,OAAO,KAAK;AAAA,EACpD;AAAA,EACA,SAAS,OAAO;AACd,QAAI,IAAI,EAAE,UAAU,+CAA+C,IAAI,GAAG;AACxE,WAAK,MAAM,SAAS;AACpB,aAAO;AAAA,IACT;AACA,UAAM,QAAQ,aAAa,IAAI;AAC/B,WAAO;AAAA,EACT;AAAA,EACA,MAAM,aAAa,OAAO;AACxB,QAAI,IAAI,EAAE,UAAU,+CAA+C,IAAI,GAAG;AACxE,aAAO,KAAK,MAAM,uBAAuB,KAAK;AAAA,IAChD;AACA,UAAM,aAAa;AACnB,WAAO,WAAW,QAAQ,WAAW;AAAA,EACvC;AAAA,EACA,YAAY,QAAQ,QAAQ,OAAO;AACjC,QAAI,KAAK,gBAAgB,IAAI,MAAM,GAAG;AACpC,aAAO;AAAA,IACT;AACA,QAAI,CAAC,KAAK,QAAQ,IAAI,MAAM,GAAG;AAC7B,aAAO;AAAA,IACT;AACA,QAAI,OAAO;AACT,WAAK,QAAQ,IAAI,MAAM,EAAE,WAAW;AAAA,IACtC,OAAO;AACL,WAAK,QAAQ,IAAI,MAAM,EAAE;AAAA,IAC3B;AACA,QAAI,CAAC,SAAS,KAAK,QAAQ,IAAI,MAAM,EAAE,WAAW,GAAG;AACnD,aAAO;AAAA,IACT;AACA,QAAI,KAAK,YAAY,IAAI,MAAM,GAAG;AAChC,WAAK,gBAAgB,IAAI,MAAM;AAC/B,WAAK;AACL,aAAO;AAAA,IACT;AACA,SAAK,eAAe,MAAM;AAC1B,UAAM,EAAE,mBAAmB,IAAI,KAAK,QAAQ,IAAI,MAAM;AACtD,QAAI,sBAAsB,MAAM;AAC9B,WAAK,YAAY,mBAAmB,KAAK,QAAQ,KAAK;AACtD,WAAK,YAAY,mBAAmB,KAAK,QAAQ,KAAK;AAAA,IACxD;AACA,SAAK,QAAQ,OAAO,MAAM;AAC1B,WAAO;AAAA,EACT;AAAA,EACA,eAAe,QAAQ;AACrB,UAAM,EAAE,SAAS,OAAO,UAAU,OAAO,UAAU,OAAO,OAAO,IAAI,KAAK,QAAQ,IAAI,MAAM;AAC5F,UAAM,MAAM,UAAU,OAAO,cAAc;AAC3C,UAAM,WAAW,KAAK,aAAa,IAAI,GAAG;AAC1C,QAAI,WAAW,GAAG;AAChB,WAAK,aAAa,IAAI,KAAK,WAAW,CAAC;AAAA,IACzC,OAAO;AACL,WAAK,aAAa,OAAO,GAAG;AAC5B,UAAI,WAAW,MAAM;AACnB,aAAK,iBAAiB,KAAK,aAAa,UAAU,KAAK;AACvD,aAAK,eAAe,eAAe,SAAS,UAAU,OAAO,QAAQ;AAAA,MACvE;AAAA,IACF;AACA,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,YAAQ,UAAU;AAClB,YAAQ,WAAW;AACnB,YAAQ,WAAW;AACnB,YAAQ,QAAQ;AAAA,EAClB;AAAA,EACA,WAAW,QAAQ;AACjB,SAAK,YAAY,MAAM;AACvB,WAAO,KAAK,QAAQ,IAAI,MAAM,EAAE,QAAQ;AAAA,EAC1C;AAAA,EACA,YAAY,QAAQ;AAClB,WAAO,KAAK,QAAQ,IAAI,MAAM;AAAA,EAChC;AAAA,EACA,mBAAmB,QAAQ,gBAAgB,4BAA4B;AACrE,WAAO,IAAI,EAAE,QAAQ,mBAAmB,KAAK,OAAO,MAAM,CAAC,WAAW,KAAK,QAAQ,IAAI,OAAO,MAAM,EAAE,WAAW,QAAQ,aAAa,cAAc,OAAO,KAAK,IAAI,aAAa;AAAA,EACnL;AAAA,EACA,kBAAkB;AAChB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,WAAW;AACf,yBAAqB,KAAK,uEAAuE;AACjG,UAAM,WAAW,UAAU,SAAS;AACpC,WAAO,WAAW,UAAU,OAAO,QAAQ;AAAA,EAC7C;AAAA,EACA,cAAc,GAAG,KAAK,OAAO;AAC3B,UAAM,UAAU,IAAI,qBAAqB,EAAE,OAAO,GAAG;AACrD,UAAM,UAAU,KAAK,cAAc,SAAS,CAAC,CAAC,GAAG,KAAK;AACtD,WAAO,OAAO,EAAE,yBAAyB,OAAO;AAAA,EAClD;AAAA,EACA,IAAI,GAAG;AACL,QAAI,KAAK,mBAAmB,CAAC,CAAC,CAAC,KAAK,EAAE,UAAU,aAAa;AAC3D,YAAM,YAAY,iBAAiB,KAAK,QAAQ,IAAI,EAAE,MAAM,EAAE,MAAM;AACpE,aAAO,KAAK,WAAW,EAAE,OAAO,EAAE,OAAO,SAAS;AAAA,IACpD;AACA,QAAI,IAAI,EAAE,QAAQ,6BAA6B,GAAG;AAChD,aAAO,KAAK,cAAc,GAAG,KAAK,EAAE,KAAK;AAAA,IAC3C;AACA,UAAM,UAAU,IAAI,eAAe,EAAE,OAAO,GAAG;AAC/C,UAAM,UAAU,KAAK,cAAc,SAAS,CAAC,CAAC,CAAC;AAC/C,WAAO,OAAO,EAAE,yBAAyB,OAAO;AAAA,EAClD;AAAA,EACA,eAAe,OAAO,OAAO,QAAQ;AACnC,QAAI;AACJ,QAAI,UAAU,YAAY,UAAU,QAAQ,OAAO,SAAS,KAAK,aAAa,SAAS,OAAO,EAAE,GAAG;AACjG,YAAM,gBAAgB,OAAO,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC;AACpE,eAAS,KAAK,MAAM,eAAe,OAAO,KAAK;AAAA,IACjD,OAAO;AACL,eAAS,KAAK,MAAM,QAAQ,OAAO,KAAK;AAAA,IAC1C;AACA,SAAK,QAAQ,IAAI,MAAM,EAAE,QAAQ;AACjC,WAAO,EAAE,QAAQ,OAAO,MAAM;AAAA,EAChC;AAAA,EACA,WAAW,OAAO,OAAO,QAAQ;AAC/B,WAAO,OAAO,EAAE,yBAAyB,KAAK,eAAe,OAAO,OAAO,MAAM,GAAG,IAAI;AAAA,EAC1F;AAAA,EACA,aAAa,QAAQ;AACnB,UAAM,UAAU,IAAI,cAAc,OAAO,KAAK;AAC9C,WAAO,KAAK,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO,KAAK;AAAA,EAC7D;AAAA,EACA,WAAW,QAAQ;AACjB,UAAM,UAAU,IAAI,YAAY,OAAO,KAAK;AAC5C,UAAM,8BAA8B;AACpC,WAAO,KAAK,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO,OAAO,MAAM,2BAA2B;AAAA,EAChG;AAAA,EACA,cAAc,QAAQ,YAAY;AAChC,UAAM,eAAe;AAAA,MACnB,YAAY,OAAO,KAAK;AAAA,MACxB,GAAG,YAAY,OAAO,KAAK;AAAA,IAC7B;AACA,UAAM,UAAU;AAAA,MACd,OAAO,OAAO;AAAA,MACd,OAAO;AAAA,MACP,QAAQ,OAAO;AAAA,IACjB;AACA,UAAM,iBAAiB;AAAA,MACrB,YAAY,UAAU;AAAA,MACtB,GAAG,YAAY,UAAU;AAAA,IAC3B;AACA,UAAM,UAAU,IAAI,qBAAqB,gBAAgB,YAAY;AACrE,UAAM,gCAAgC;AACtC,UAAM,eAAe,CAAC,YAAY;AAClC,UAAM,SAAS,KAAK,gBAAgB,SAAS,CAAC,OAAO,GAAG,OAAO,OAAO,cAAc,6BAA6B;AACjH,WAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO,YAAY,OAAO,OAAO,MAAM;AAAA,EACzE;AAAA,EACA,OAAO,QAAQ,gBAAgB;AAC7B,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,UAAM,EAAE,UAAU,OAAO,MAAM,IAAI;AACnC,QAAI,kBAAkB,MAAM;AAC1B,YAAMA,QAAO,aAAa,cAAc,KAAK;AAC7C,YAAM,UAAU,eAAe,KAAK,eAAe,KAAK;AACxD,mBAAa,OAAOA,SAAQ,SAAS,MAAM,2GAA2G;AAAA,IACxJ;AACA,UAAM,YAAY,aAAa,KAAK;AACpC,QAAI;AACJ,QAAI,UAAU;AACZ,gBAAU,IAAI,0BAA0B,SAAS;AAAA,IACnD,OAAO;AACL,gBAAU,IAAI,oBAAoB,SAAS;AAAA,IAC7C;AACA,UAAM,gCAAgC;AACtC,UAAM,eAAe,CAAC,kBAAkB,OAAO,iBAAiB,iBAAiB,SAAS,CAAC;AAC3F,UAAM,MAAM,KAAK,gBAAgB,SAAS,CAAC,EAAE,OAAO,WAAW,OAAO,OAAO,CAAC,GAAG,OAAO,cAAc,+BAA+B,cAAc;AACnJ,WAAO,EAAE,OAAO,OAAO,QAAQ,IAAI,OAAO;AAAA,EAC5C;AAAA,EACA,gBAAgB,SAAS,QAAQ,aAAa,qBAAqB,gCAAgC,OAAO,gBAAgB;AACxH,UAAM,SAAS,KAAK,eAAe,QAAQ,aAAa,WAAW;AACnE,UAAM,UAAU,KAAK,QAAQ,IAAI,OAAO,MAAM;AAC9C,QAAI,QAAQ,cAAc;AACxB,cAAQ,WAAW;AAAA,IACrB;AACA,QAAI,QAAQ,qBAAqB,cAAc,OAAO;AACpD,YAAM,aAAa,kBAAkB,OAAO,iBAAiB,iBAAiB,QAAQ,WAAW;AACjG,cAAQ,WAAW,WAAW,IAAI,CAAC,MAAM,IAAI,CAAC;AAAA,IAChD;AACA,QAAI,QAAQ,eAAe,MAAM;AAC/B,cAAQ,QAAQ,QAAQ;AAAA,IAC1B;AACA,QAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,cAAQ,SAAS,aAAa,uBAAuB,OAAO,OAAO,CAAC;AACpE,aAAO;AAAA,IACT;AACA,UAAM,gBAAgB,CAAC;AACvB,UAAM,aAAa,OAAO,IAAI,CAAC,WAAW;AACxC,UAAI,OAAO,UAAU,aAAa;AAChC,cAAM,IAAI,MAAM,iIAAiI;AAAA,MACnJ;AACA,UAAI,UAAU,KAAK,QAAQ,IAAI,OAAO,MAAM;AAC5C,UAAI,QAAQ,WAAW,MAAM;AAC3B,YAAI,CAAC,QAAQ,gBAAgB,aAAa,cAAc,OAAO,KAAK,KAAK,IAAI,EAAE,UAAU,2BAA2B,GAAG;AACrH,iBAAO;AAAA,YACL,OAAO,OAAO;AAAA,YACd,SAAS;AAAA,YACT,WAAW;AAAA,YACX,eAAe,QAAQ;AAAA,UACzB;AAAA,QACF;AACA,YAAI,QAAQ,cAAc;AACxB,kBAAQ,WAAW;AACnB,kBAAQ,QAAQ,OAAO;AAAA,QACzB;AAAA,MACF;AACA,WAAK,YAAY,OAAO,MAAM;AAC9B,UAAI,CAAC,CAAC,QAAQ,aAAa,CAAC,CAAC,QAAQ,cAAc;AACjD,iBAAS,QAAQ,WAAW,KAAK,aAAa,MAAM,IAAI,KAAK,WAAW,MAAM;AAC9E,sBAAc,KAAK,MAAM;AACzB,kBAAU,KAAK,QAAQ,IAAI,OAAO,MAAM;AAAA,MAC1C,WAAW,QAAQ,YAAY,CAAC,cAAc,QAAQ,OAAO,OAAO,KAAK,GAAG;AAC1E,cAAM,aAAa;AACnB,cAAM,cAAc,OAAO;AAC3B,eAAO,QAAQ,QAAQ;AACvB,iBAAS,KAAK,cAAc,QAAQ,WAAW;AAC/C,sBAAc,KAAK,MAAM;AACzB,kBAAU,KAAK,QAAQ,IAAI,OAAO,MAAM;AACxC,mBAAW,QAAQ;AAAA,MACrB;AACA,aAAO,EAAE,OAAO,OAAO,OAAO,SAAS,WAAW,MAAM;AAAA,IAC1D,CAAC;AACD,SAAK,YAAY,OAAO,MAAM;AAC9B,UAAM,aAAa,EAAE,OAAO,OAAO,OAAO,SAAS,SAAS,WAAW,MAAM;AAC7E,UAAM,MAAM,cAAc,SAAS,YAAY,UAAU;AACzD,UAAM,SAAS,KAAK,iBAAiB,KAAK,MAAM;AAC9C,aAAO,eAAe,KAAK,OAAO,SAAS,YAAY,UAAU;AAAA,IACnE,CAAC;AACD,UAAM,oBAAoB,KAAK,gBAAgB;AAC/C,QAAI;AACJ,QAAI,mBAAmB;AACrB,cAAQ,KAAK,WAAW;AAAA,IAC1B;AACA,QAAI,CAAC,IAAI,EAAE,IAAI,qBAAqB,GAAG;AACrC,iBAAW,KAAK,OAAO,QAAQ,YAAY,YAAY,mBAAmB;AAAA,IAC5E;AACA,kBAAc,QAAQ,CAAC,SAAS,KAAK,8BAA8B,IAAI,CAAC;AACxE,QAAI,mBAAmB;AACrB,cAAQ,KAAK,SAAS,KAAK;AAC3B,WAAK,aAAa,KAAK,EAAE,MAAM,QAAQ,YAAY,MAAM,OAAO,KAAK,aAAa,KAAK,EAAE,CAAC;AAAA,IAC5F;AACA,UAAM,mBAAmB,IAAI,EAAE,IAAI,uBAAuB;AAC1D,QAAI,mBAAmB,GAAG;AACxB,YAAM,QAAQ,aAAa,IAAI;AAC/B,UAAI,QAAQ,KAAK,kBAAkB,kBAAkB;AACnD,aAAK,MAAM,GAAG,MAAM;AACpB,aAAK,kBAAkB;AAAA,MACzB;AAAA,IACF;AACA,QAAI,CAAC,IAAI,EAAE,QAAQ,qBAAqB,KAAK,QAAQ,YAAY,kCAAkC,OAAO;AACxG,YAAM,WAAW,KAAK,aAAa,MAAM;AACzC,WAAK,8BAA8B,MAAM;AACzC,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT;AAAA,EACA,cAAc,SAAS,QAAQ,aAAa,qBAAqB,gCAAgC,OAAO;AACtG,kBAAc,eAAe,OAAO,GAAG;AACvC,UAAM,UAAU,KAAK,gBAAgB,SAAS,QAAQ,aAAa,qBAAqB,6BAA6B;AACrH,WAAO;AAAA,EACT;AAAA,EACA,iBAAiB,KAAK,WAAW;AAC/B,QAAI,EAAE,OAAO,KAAK,cAAc;AAC9B,WAAK,YAAY,OAAO,UAAU;AAAA,IACpC;AACA,WAAO,KAAK,YAAY;AAAA,EAC1B;AAAA,EACA,oBAAoB;AAClB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,UAAU;AACR,QAAI,KAAK,UAAU;AACjB;AAAA,IACF;AACA,QAAI,CAAC,IAAI,EAAE,QAAQ,SAAS,GAAG;AAC7B,YAAM,UAAU,OAAO,KAAK,KAAK,WAAW;AAC5C,cAAQ,QAAQ,CAAC,QAAQ;AACvB,aAAK,MAAM,cAAc,KAAK,YAAY,KAAK,YAAY;AAC3D,eAAO,KAAK,YAAY;AAAA,MAC1B,CAAC;AAAA,IACH;AACA,SAAK,eAAe,QAAQ;AAC5B,QAAI,KAAK,UAAU,SAAS,OAAO,sBAAsB,eAAe,KAAK,kBAAkB,oBAAoB;AACjH,WAAK,OAAO,OAAO;AAAA,IACrB,OAAO;AACL,WAAK,SAAS;AAAA,IAChB;AACA,QAAI,KAAK,qBAAqB;AAC5B,WAAK,MAAM,UAAU;AACrB,WAAK,MAAM,QAAQ;AAAA,IACrB;AACA,SAAK,WAAW;AAAA,EAClB;AAAA,EACA,iBAAiB;AACf,QAAI,KAAK,uBAAuB,MAAM;AACpC,WAAK,sBAAsB,KAAK,MAAM;AACpC,YAAI,CAAC,IAAI,EAAE,IAAI,8BAA8B,GAAG;AAC9C,gBAAM,YAAY,IAAI,EAAE,QAAQ,OAAO;AACvC,cAAI,EAAE,IAAI,SAAS,KAAK;AACxB,gBAAM,sBAAsB,KAAK,IAAI,OAAO,IAAI,CAAC,EAAE,SAAS,EAAE;AAC9D,cAAI,EAAE,IAAI,SAAS,SAAS;AAC5B,cAAI,sBAAsB,GAAG;AAC3B,mBAAO;AAAA,UACT;AAAA,QACF;AACA,eAAO;AAAA,MACT,CAAC;AAAA,IACH;AACA,WAAO,KAAK;AAAA,EACd;AAAA,EACA,UAAU;AACR,WAAO,KAAK,eAAe,MAAM,KAAK,mBAAmB;AAAA,EAC3D;AAAA,EACA,YAAY,QAAQ;AAClB,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,UAAM,EAAE,OAAO,OAAO,QAAQ,SAAS,OAAO,SAAS,IAAI;AAC3D,QAAI,WAAW,MAAM;AACnB;AAAA,IACF;AACA,UAAM,oBAAoB,KAAK,gBAAgB;AAC/C,QAAI;AACJ,QAAI,mBAAmB;AACrB,cAAQ,aAAa,IAAI;AAAA,IAC3B;AACA,QAAI,WAAW,QAAQ;AACvB,QAAI,YAAY,MAAM;AACpB,iBAAW,gCAAgC,OAAO,QAAQ;AAC1D,cAAQ,WAAW;AAAA,IACrB;AACA,QAAI,UAAU,MAAM;AAClB,YAAM,YAAY,aAAa,KAAK;AACpC,UAAI;AACJ,UAAI,QAAQ,SAAS,IAAI,SAAS,SAAS;AAC3C,YAAM,cAAc,kBAAkB,cAAc,kBAAkB;AACtE,UAAI,YAAY,CAAC,aAAa;AAC5B,SAAC,OAAO,MAAM,IAAI,uCAAuC,SAAS,IAAI,SAAS,EAAE;AAAA,MACnF;AACA,UAAI,UAAU;AACZ,kBAAU,IAAI,0BAA0B,WAAW,WAAW;AAAA,MAChE,OAAO;AACL,kBAAU,IAAI,oBAAoB,WAAW,WAAW;AAAA,MAC1D;AACA,YAAM,yBAAyB,cAAc,CAAC,QAAQ,KAAK,IAAI;AAC/D,YAAM,uBAAuB,KAAK,eAAe,wBAAwB,KAAK;AAC9E,YAAM,wBAAwB,KAAK,QAAQ,IAAI,qBAAqB,MAAM;AAC1E,UAAI,aAAa;AACf,8BAAsB,QAAQ,aAAa;AAAA,MAC7C,OAAO;AACL,8BAAsB,QAAQ,aAAa;AAAA,MAC7C;AACA,4BAAsB,WAAW;AACjC,WAAK,MAAM,2BAA2B,KAAK,WAAW,qBAAqB,MAAM,GAAG,OAAO,QAAQ,MAAM;AACzG,YAAM,eAAe,CAAC,CAAC,QAAQ,KAAK,CAAC;AACrC,YAAM,wBAAwB;AAC9B,YAAM,sBAAsB,KAAK,gBAAgB,SAAS,CAAC,oBAAoB,GAAG,OAAO,cAAc,qBAAqB;AAC5H,YAAM,gBAAgB,KAAK,QAAQ,IAAI,oBAAoB,MAAM;AACjE,cAAQ,WAAW,cAAc;AACjC,cAAQ,WAAW,cAAc;AACjC,cAAQ,QAAQ,cAAc;AAC9B,UAAI,CAAC,IAAI,EAAE,IAAI,qBAAqB,GAAG;AACrC,gBAAQ,UAAU,cAAc;AAChC,gBAAQ,SAAS;AACjB,aAAK,QAAQ,OAAO,oBAAoB,MAAM;AAAA,MAChD,OAAO;AACL,aAAK,YAAY,oBAAoB,MAAM;AAAA,MAC7C;AACA,WAAK,8BAA8B,oBAAoB;AACvD,UAAI,mBAAmB;AACrB,aAAK,gBAAgB,aAAa,IAAI,IAAI;AAAA,MAC5C;AAAA,IACF,OAAO;AACL,YAAM,aAAa,KAAK,eAAe,UAAU,OAAO,OAAO,QAAQ;AACvE,cAAQ,UAAU;AAAA,IACpB;AAAA,EACF;AAAA,EACA,qBAAqB,QAAQ,eAAe;AAC1C,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,UAAM,EAAE,MAAM,IAAI;AAClB,SAAK,eAAe,MAAM;AAC1B,QAAI,iBAAiB,MAAM;AACzB,cAAQ,SAAS,oBAAoB,eAAe,KAAK;AAAA,IAC3D;AACA,WAAO,QAAQ;AAAA,EACjB;AAAA,EACA,eAAe,UAAU,SAAS,OAAO,UAAU;AACjD,SAAK,iBAAiB,KAAK,aAAa,UAAU,KAAK;AACvD,QAAI,CAAC,KAAK,qBAAqB,KAAK,gBAAgB,KAAK,qBAAqB,OAAO,MAAM;AACzF,YAAM,MAAM,KAAK,gBAAgB,OAAO,MAAM,QAAQ,CAAC;AACvD,WAAK,oBAAoB;AACzB,cAAQ,KAAK,6BAA6B,yCAAyC;AAAA,IACrF;AACA,WAAO,KAAK,eAAe,eAAe,UAAU,SAAS,QAAQ;AAAA,EACvE;AAAA,EACA,aAAa,OAAO,OAAO;AACzB,WAAO,MAAM,KAAK,MAAM,KAAK,aAAa,gBAAgB,KAAK;AAAA,EACjE;AAAA,EACA,yBAAyB;AACvB,eAAW,CAAC,EAAE,MAAM,KAAK,OAAO,QAAQ,KAAK,WAAW,GAAG;AACzD,WAAK,iBAAiB,MAAM;AAAA,IAC9B;AAAA,EACF;AAAA,EACA,MAAM,8BAA8B;AAClC,UAAM,KAAK,CAAC;AACZ,QAAI,KAAK,MAAM,8BAA8B;AAC3C,iBAAW,CAAC,EAAE,MAAM,KAAK,OAAO,QAAQ,KAAK,WAAW,GAAG;AACzD,WAAG,KAAK,KAAK,sBAAsB,MAAM,CAAC;AAAA,MAC5C;AACA,aAAO,QAAQ,IAAI,EAAE;AAAA,IACvB,OAAO;AACL,iBAAW,CAAC,EAAE,MAAM,KAAK,OAAO,QAAQ,KAAK,WAAW,GAAG;AACzD,cAAM,KAAK,IAAI,QAAQ,CAAC,YAAY;AAClC,cAAI;AACF,iBAAK,iBAAiB,MAAM;AAC5B,oBAAQ,IAAI;AAAA,UACd,SAAS,OAAP;AACA,kBAAM;AAAA,UACR;AAAA,QACF,CAAC;AACD,WAAG,KAAK,EAAE;AAAA,MACZ;AACA,aAAO,QAAQ,IAAI,EAAE;AAAA,IACvB;AAAA,EACF;AAAA,EACA,MAAM,sBAAsB,QAAQ;AAClC,QAAI,KAAK,MAAM,GAAG,oBAAoB,OAAO,cAAc,KAAK,MAAM,6BAA6B,qBAAqB,GAAG;AACzH,aAAO,KAAK,iBAAiB,MAAM;AAAA,IACrC,OAAO;AACL,YAAM,UAAU;AAChB,aAAO,KAAK,sBAAsB,MAAM;AAAA,IAC1C;AAAA,EACF;AAAA,EACA,iBAAiB,QAAQ;AACvB,QAAI,KAAK,MAAM,GAAG,oBAAoB,OAAO,cAAc,KAAK,MAAM,GAAG,WAAW,MAAM,OAAO;AAC/F,cAAQ,IAAI,KAAK,MAAM,GAAG,kBAAkB,OAAO,YAAY,CAAC;AAChE,UAAI,KAAK,MAAM,GAAG,mBAAmB,OAAO,gBAAgB,KAAK,MAAM,GAAG,cAAc,MAAM,OAAO;AACnG,kCAA0B,OAAO,QAAQ,KAAK,MAAM,GAAG,iBAAiB,OAAO,cAAc,CAAC;AAC9F,cAAM,IAAI,MAAM,oCAAoC;AAAA,MACtD;AACA,YAAM,IAAI,MAAM,6CAA6C;AAAA,IAC/D;AACA,WAAO;AAAA,EACT;AAAA,EACA,sBAAsB;AACpB,eAAW,CAAC,EAAE,MAAM,KAAK,OAAO,QAAQ,KAAK,WAAW,GAAG;AACzD,YAAM,EAAE,kBAAkB,wBAAwB,QAAQ,QAAQ,mBAAmB,sBAAsB,kBAAkB,yBAAyB,oBAAoB,IAAI,oBAAoB,KAAK,OAAO,OAAO,SAAS,OAAO,YAAY;AACjP,aAAO,mBAAmB;AAC1B,aAAO,yBAAyB;AAChC,aAAO,SAAS;AAChB,aAAO,SAAS;AAChB,aAAO,oBAAoB;AAC3B,aAAO,uBAAuB;AAC9B,aAAO,mBAAmB;AAC1B,aAAO,0BAA0B;AACjC,aAAO,sBAAsB;AAAA,IAC/B;AAAA,EACF;AACF;AACA,iBAAiB,aAAa;AAC9B,SAAS,oBAAoB,GAAG,OAAO;AACrC,MAAI,UAAU,aAAa,UAAU,aAAa;AAChD,WAAO;AAAA,EACT,WAAW,UAAU,WAAW,UAAU,QAAQ;AAChD,UAAM,SAAS,UAAU,UAAU,IAAI,WAAW,EAAE,MAAM,IAAI,IAAI,WAAW,EAAE,MAAM;AACrF,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,aAAO,MAAM,KAAK,MAAM,EAAE,GAAG;AAAA,IAC/B;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,iBAAiB,OAAO;AAAA,EAC1C;AACF;AAGA,IAAI,WAAW;AAGf,SAAS,iBAAiB;AACxB,MAAI,EAAE,IAAI,4BAA4B,IAAI;AAC5C;AAGA,IAAI,oBAAoB,UAAU,GAAG;AACnC,kBAAgB,SAAS,MAAM,IAAI,iBAAiB,GAAG,CAAC;AAC1D;AACA,IAAI,QAAQ,EAAE,eAAe;AAG7B,IAAI,qBAAqB;AAAA;AAAA;AAAA;AAIzB,IAAI,kBAAkB,MAAM;AAAA,EAC1B,YAAY,KAAK,QAAQ,QAAQ;AAC/B,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,cAAc,qBAAqB,2BAA2B,QAAQ,MAAM;AACjF,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EASR;AACF;AAGA,IAAI,qBAAqB;AAAA;AAAA;AAAA;AAAA;AAAA;AAMzB,IAAI,wBAAwB,MAAM;AAAA,EAChC,YAAY,KAAK,QAAQ,QAAQ,mBAAmB,OAAO;AACzD,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,uBAAuB;AAC5B,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc,qBAAqB,2BAA2B,QAAQ,MAAM;AACjF,UAAM,OAAO,KAAK,YAAY;AAC9B,SAAK,sBAAsB,iBAAiB,IAAI;AAChD,QAAI,yBAAyB;AAC7B,QAAI,kBAAkB;AACpB,UAAI,SAAS,KAAK,aAAa,cAAc,KAAK,WAAW,MAAM,GAAG;AACpE,iCAAyB;AAAA;AAAA;AAAA;AAAA;AAAA,MAK3B,OAAO;AACL,cAAM,QAAQ,kBAAkB,IAAI;AACpC,iCAAyB;AAAA,YACrB;AAAA;AAEJ,YAAI,SAAS,GAAG;AACd,cAAI,KAAK,qBAAqB;AAC5B,sCAA0B;AAAA;AAAA;AAAA;AAAA;AAAA,UAK5B,OAAO;AACL,sCAA0B;AAAA,yCACG,KAAK,YAAY;AAAA;AAAA;AAAA;AAAA,UAIhD;AAAA,QACF,OAAO;AACL,gBAAM,WAAW,YAAY,UAAU,IAAI;AAC3C,cAAI,KAAK,qBAAqB;AAC5B,sCAA0B;AAAA;AAAA,iBAErB,SAAS,OAAO,uBAAuB;AAAA;AAAA,iBAEvC,SAAS,OAAO,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA,UAK9C,OAAO;AACL,sCAA0B;AAAA;AAAA,iBAErB,SAAS,OAAO,cAAc,KAAK,YAAY,OAAO;AAAA;AAAA,iBAEtD,SAAS,OAAO,cAAc,KAAK,YAAY,OAAO;AAAA;AAAA;AAAA;AAAA;AAAA,UAK7D;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAQA;AAAA;AAAA;AAAA;AAAA;AAAA,EAKR;AACF;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,WAAS,OAAO,EAAE,MAAM;AACxB,SAAO,EAAE,QAAQ,EAAE,QAAQ,OAAO,EAAE,OAAO,OAAO,EAAE,MAAM;AAC5D;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,MAAM,OAAO,MAAM,MAAM,IAAI;AACrC,QAAM,cAAc,SAAS,eAAe,MAAM,OAAO,WAAW;AACpE,QAAM,WAAW,SAAS,QAAQ,IAAI,YAAY,MAAM;AACxD,QAAM,iBAAiB,UAAU,EAAE,QAAQ,EAAE,GAAG,MAAM,GAAG,SAAS,SAAS,CAAC;AAC5E,QAAM,iBAAiB,UAAU,EAAE,QAAQ,EAAE,GAAG,MAAM,GAAG,SAAS,SAAS,CAAC;AAC5E,WAAS,qBAAqB,EAAE,MAAM,gBAAgB,MAAM,eAAe;AAC3E,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY;AAChB,IAAI,mBAAmB;AAAA;AAAA;AAAA;AAIvB,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAAsB,OAAM,IAAI;AAClB,QAAM,SAAS,SAAS,eAAe,CAAC,GAAG,WAAW,aAAa,kBAAkBA,QAAO,SAAS,CAAC;AACtG,QAAM,UAAU,IAAI,EAAE,QAAQ,8BAA8B,IAAI,IAAI,sBAAsB,kBAAkB,EAAE,OAAO,OAAO,KAAK,IAAI,IAAI,gBAAgB,WAAW,EAAE,OAAO,OAAO,KAAK;AACzL,QAAM,SAAS,SAAS,gBAAgB,SAAS,CAAC,GAAG,MAAM,GAAG,SAAS;AACvE,WAAS,8BAA8B,MAAM;AAC7C,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ;AACZ,IAAI,eAAe;AAAA;AAAA;AAAA;AAInB,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,GAAG,OAAAA,OAAM,IAAI;AACrB,QAAM,UAAU,IAAI,EAAE,QAAQ,8BAA8B,IAAI,IAAI,sBAAsB,cAAc,EAAE,OAAOA,OAAM,KAAK,IAAI,IAAI,gBAAgB,OAAO,EAAE,OAAOA,OAAM,KAAK;AAC/K,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAGA,MAAK,GAAG,SAAS;AAChE;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,0BAA0B;AAC9B,IAAI,2BAA2B;AAAA;AAAA;AAAA;AAI/B,IAAI,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAMtC,SAAS,iBAAiB,EAAE,WAAW,iBAAiB,eAAe,MAAM,GAAG;AAC9E,SAAO,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AACxC,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,eAAe;AACrB,UAAM,SAAS,SAAS,EAAE;AAC1B,QAAI,aAAa,mBAAmB,CAAC,CAAC,CAAC,KAAK,iBAAiB,MAAM;AACjE,YAAM,QAAQ,aAAa,QAAQ,IAAI,EAAE,MAAM;AAC/C,YAAM,YAAY,cAAc,MAAM,QAAQ,MAAM;AACpD,aAAO,aAAa,eAAe,EAAE,OAAO,QAAQ,SAAS;AAAA,IAC/D;AACA,UAAM,yBAAyB,IAAI,EAAE,QAAQ,6BAA6B,KAAK,mBAAmB;AAClG,QAAI;AACJ,QAAI,wBAAwB;AAC1B,gBAAU,IAAI,qBAAqB,EAAE,OAAO,eAAe;AAAA,IAC7D,OAAO;AACL,gBAAU,IAAI,eAAe,EAAE,OAAO,SAAS;AAAA,IACjD;AACA,WAAO,aAAa,gBAAgB,SAAS,CAAC,CAAC,GAAG,MAAM;AAAA,EAC1D;AACF;AACA,SAAS,kBAAkB,EAAE,WAAW,iBAAiB,mBAAmB,OAAO,kBAAkB,OAAO,eAAe,MAAM,GAAG;AAClI,SAAO,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AACxC,UAAM,EAAE,GAAG,EAAE,IAAI;AACjB,UAAM,eAAe;AACrB,QAAI,mBAAmB,EAAE,UAAU,aAAa;AAC9C,YAAM,QAAQ,aAAa,QAAQ,IAAI,EAAE,MAAM;AAC/C,YAAM,QAAQ,aAAa,QAAQ,IAAI,EAAE,MAAM;AAC/C,YAAM,CAAC,OAAO,KAAK,IAAI;AAAA,QACrB,CAAC,MAAM,mBAAmB,MAAM,MAAM,mBAAmB,IAAI;AAAA,QAC7D,CAAC,MAAM,mBAAmB,MAAM,MAAM,mBAAmB,IAAI;AAAA,MAC/D,EAAE,IAAI,CAAC,iBAAiB;AACtB,cAAM,CAAC,OAAO,KAAK,IAAI;AACvB,cAAM,UAAU;AAAA,UACd,QAAQ,MAAM;AAAA,UACd,OAAO,MAAM;AAAA,UACb,OAAO,EAAE;AAAA,QACX;AACA,cAAM,UAAU;AAAA,UACd,QAAQ,MAAM;AAAA,UACd,OAAO,MAAM;AAAA,UACb,OAAO,EAAE;AAAA,QACX;AACA,cAAM,WAAW,IAAI,gBAAgB,WAAW,EAAE,OAAO,EAAE,KAAK;AAChE,eAAO,aAAa,gBAAgB,UAAU,CAAC,SAAS,OAAO,GAAG,WAAW,MAAM,OAAO,MAAM,KAAK,CAAC;AAAA,MACxG,CAAC;AACD,YAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,MAAM,OAAO,MAAM,MAAM,GAAG,SAAS,aAAa,CAAC;AAC9F,mBAAa,8BAA8B,KAAK;AAChD,mBAAa,8BAA8B,KAAK;AAChD,aAAO;AAAA,IACT;AACA,UAAM,SAAS,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AACnD,SAAK,EAAE,UAAU,YAAY,EAAE,UAAU,YAAY,aAAa,mBAAmB,CAAC,GAAG,CAAC,CAAC,MAAM,iBAAiB,MAAM;AACtH,YAAM,QAAQ,aAAa,QAAQ,IAAI,EAAE,MAAM,EAAE;AACjD,YAAM,QAAQ,aAAa,QAAQ,IAAI,EAAE,MAAM,EAAE;AACjD,YAAM,eAAe,EAAE,UAAU,WAAW,qBAAqB,uBAAuB,KAAK,IAAI;AACjG,YAAM,eAAe,EAAE,UAAU,WAAW,qBAAqB,uBAAuB,KAAK,IAAI;AACjG,YAAM,CAAC,WAAW,QAAQ,IAAI,cAAc,EAAE,OAAO,EAAE,OAAO,cAAc,cAAc,MAAM;AAChG,YAAM,MAAM,aAAa,eAAe,UAAU,MAAM;AACxD,YAAM,UAAU,aAAa,QAAQ,IAAI,IAAI,MAAM;AACnD,cAAQ,SAAS;AACjB,aAAO;AAAA,IACT;AACA,UAAM,yBAAyB,IAAI,EAAE,QAAQ,8BAA8B,KAAK,mBAAmB;AACnG,QAAI;AACJ,QAAI,wBAAwB;AAC1B,gBAAU,IAAI,sBAAsB,iBAAiB,EAAE,OAAO,EAAE,OAAO,gBAAgB;AAAA,IACzF,OAAO;AACL,gBAAU,IAAI,gBAAgB,WAAW,EAAE,OAAO,EAAE,KAAK;AAAA,IAC3D;AACA,WAAO,aAAa,gBAAgB,SAAS,CAAC,GAAG,CAAC,GAAG,MAAM;AAAA,EAC7D;AACF;AACA,SAAS,6BAA6B,aAAa,SAAS,OAAO;AACjE,MAAI,gBAAgB,UAAU;AAC5B,QAAI,QAAQ;AACV,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT,WAAW,gBAAgB,QAAQ;AACjC,QAAI,QAAQ;AACV,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT,WAAW,gBAAgB,OAAO;AAChC,QAAI,QAAQ;AACV,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT,WAAW,gBAAgB,SAAS;AAClC,QAAI,QAAQ;AACV,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT,WAAW,gBAAgB,SAAS;AAClC,QAAI,QAAQ;AACV,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT,WAAW,gBAAgB,aAAa;AACtC,QAAI,QAAQ;AACV,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT,WAAW,gBAAgB,WAAW;AACpC,QAAI,QAAQ;AACV,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT;AACA,QAAM,IAAI,MAAM,cAAc,6DAA6D;AAC7F;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,QAAQ,QAAQ,aAAa,aAAa,OAAO,aAAa,OAAO,UAAU,OAAO,cAAc,MAAM,qBAAqB,OAAO,yBAAyB,OAAO;AAChL,SAAK,gBAAgB,CAAC,WAAW,SAAS;AAC1C,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,UAAM,YAAY,aAAa,OAAO,KAAK,OAAO;AAClD,UAAM,wBAAwB,KAAK,KAAK,YAAY,CAAC;AACrD,UAAM,UAAU,aAAa,gBAAgB;AAC7C,UAAM,UAAU,aAAa,gBAAgB;AAC7C,UAAM,WAAW,aAAa,CAAC,UAAU,QAAQ,IAAI,CAAC,UAAU,QAAQ;AACxE,UAAM,WAAW,aAAa,CAAC,UAAU,QAAQ,IAAI,CAAC,UAAU,QAAQ;AACxE,QAAI,oBAAoB,IAAI,yBAAyB;AACrD,QAAI,aAAa;AACf,UAAI,oBAAoB;AACtB,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,WAAW,wBAAwB;AACjC,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,OAAO;AACL,4BAAoB;AAAA,YAChB;AAAA;AAAA,MAEN;AACA,+BAAyB;AAAA,IAC3B;AACA,UAAM,iBAAiB,UAAU,oCAAoC;AACrE,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,oBAAoB;AACtB,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,QAAI,wBAAwB;AAC1B,WAAK,cAAc,KAAK,gBAAgB;AAAA,IAC1C;AACA,QAAI,gBAAgB;AACpB,QAAI,gBAAgB;AACpB,QAAI,OAAO,KAAK,OAAO,IAAI;AACzB,sBAAgB,wBAAwB,OAAO,KAAK;AAAA,IACtD,WAAW,OAAO,KAAK,OAAO,IAAI;AAChC,sBAAgB,wBAAwB,OAAO,KAAK;AAAA,IACtD;AACA,SAAK,WAAW;AAAA,QACZ;AAAA;AAAA,sCAE8B;AAAA;AAAA;AAAA;AAAA,8BAIR;AAAA,yBACL;AAAA,yBACA;AAAA,wCACe;AAAA,wCACA;AAAA;AAAA;AAAA;AAAA,uBAIjB,SAAS,QAAQ,SAAS;AAAA,uBAC1B,SAAS,QAAQ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UASvC;AAAA;AAAA,UAEA;AAAA;AAAA;AAAA;AAAA;AAAA,EAKR;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,MAAM;AAAA,EACN,MAAM;AACR;AACA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,KAAK,QAAQ,QAAQ;AAC/B,SAAK,gBAAgB,CAAC,SAAS,SAAS,SAAS,OAAO;AACxD,SAAK,cAAc,qBAAqB,2BAA2B,QAAQ,MAAM;AACjF,SAAK,WAAW;AAAA;AAAA;AAAA,UAGV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAWR;AACF;AAGA,IAAI,MAAM;AACV,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,GAAG,EAAE,IAAI;AACjB,QAAM,QAAQ,qBAAqB,WAAW,EAAE,OAAO,EAAE,KAAK;AAC9D,MAAI,EAAE,UAAU,aAAa;AAC3B,UAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,UAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,UAAM,cAAc,IAAI,uBAAuB,iBAAiB,MAAM,EAAE,OAAO,EAAE,KAAK;AACtF,UAAM,cAAc,IAAI,uBAAuB,iBAAiB,MAAM,EAAE,OAAO,EAAE,KAAK;AACtF,UAAM,UAAU;AAAA,MACd;AAAA,QACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,QACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,QACrC,OAAO,EAAE;AAAA,MACX;AAAA,MACA;AAAA,QACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,QACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,QACrC,OAAO,EAAE;AAAA,MACX;AAAA,MACA;AAAA,QACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,QACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,QACrC,OAAO,EAAE;AAAA,MACX;AAAA,MACA;AAAA,QACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,QACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,QACrC,OAAO,EAAE;AAAA,MACX;AAAA,IACF;AACA,UAAM,WAAW,SAAS,gBAAgB,aAAa,SAAS,SAAS;AACzE,UAAM,WAAW,SAAS,gBAAgB,aAAa,SAAS,SAAS;AACzE,UAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,MAAM,UAAU,MAAM,SAAS,GAAG,SAAS,SAAS,CAAC;AAChG,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,QAAQ;AAC/C,WAAO;AAAA,EACT;AACA,MAAI,SAAS,mBAAmB,CAAC,GAAG,CAAC,CAAC,GAAG;AACvC,UAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,UAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,UAAM,CAAC,WAAW,QAAQ,IAAI,gBAAgB,EAAE,OAAO,EAAE,OAAO,MAAM,QAAQ,MAAM,QAAQ,KAAK;AACjG,UAAM,MAAM,SAAS,eAAe,UAAU,KAAK;AACnD,UAAM,UAAU,SAAS,QAAQ,IAAI,IAAI,MAAM;AAC/C,YAAQ,SAAS;AACjB,WAAO;AAAA,EACT;AACA,MAAI;AACJ,MAAI,IAAI,EAAE,QAAQ,8BAA8B,GAAG;AACjD,cAAU,IAAI,sBAAsB,KAAK,EAAE,OAAO,EAAE,KAAK;AAAA,EAC3D,OAAO;AACL,cAAU,IAAI,gBAAgB,KAAK,EAAE,OAAO,EAAE,KAAK;AAAA,EACrD;AACA,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,CAAC,GAAG,KAAK;AACxD;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,QAAQ,YAAY,UAAU;AACnD,QAAM,eAAe;AAAA,IACnB,YAAY,OAAO,KAAK;AAAA,IACxB,GAAG,YAAY,OAAO,KAAK;AAAA,EAC7B;AACA,QAAM,UAAU;AAAA,IACd,OAAO,OAAO;AAAA,IACd,OAAO;AAAA,IACP,QAAQ,OAAO;AAAA,EACjB;AACA,QAAM,iBAAiB;AAAA,IACrB,YAAY,UAAU;AAAA,IACtB,GAAG,YAAY,UAAU;AAAA,EAC3B;AACA,QAAM,UAAU,IAAI,qBAAqB,gBAAgB,YAAY;AACrE,QAAM,gCAAgC;AACtC,QAAM,eAAe,CAAC,YAAY;AAClC,QAAM,SAAS,SAAS,gBAAgB,SAAS,CAAC,OAAO,GAAG,OAAO,OAAO,cAAc,6BAA6B;AACrH,SAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO,YAAY,OAAO,OAAO,MAAM;AACzE;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,eAAe;AACrB,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,SAAS,aAAa,uBAAuB,OAAO,KAAK;AAC/D,QAAM,SAAS,aAAa,cAAc,MAAM;AAChD,eAAa,OAAO,UAAU,QAAQ,MAAM,kBAAkB,eAAe,sCAAsC,EAAE,cAAc,oFAAoF;AACvN,QAAM,WAAW,aAAa,QAAQ,IAAI,EAAE,MAAM;AAClD,MAAI,SAAS,YAAY,CAAC,cAAc,EAAE,OAAO,MAAM,KAAK,EAAE,SAAS,YAAY,QAAQ,cAAc,SAAS,OAAO,MAAM,IAAI;AACjI,WAAO,cAAc,GAAG,QAAQ,YAAY;AAAA,EAC9C;AACA,eAAa,OAAO,EAAE,MAAM;AAC5B,SAAO,EAAE,QAAQ,EAAE,QAAQ,OAAO,QAAQ,OAAO,EAAE,MAAM;AAC3D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,YAAY,SAAS;AAC/B,SAAK,gBAAgB,CAAC,GAAG;AACzB,UAAM,EAAE,YAAY,WAAW,QAAQ,QAAQ,IAAI;AACnD,SAAK,cAAc,CAAC,WAAW,OAAO;AACtC,UAAM,wBAAwB,KAAK,MAAM,aAAa,CAAC,IAAI;AAC3D,UAAM,0BAA0B,aAAa;AAC7C,QAAI,gBAAgB;AACpB,QAAI,WAAW,MAAM;AACnB,YAAM,cAAc,IAAI;AACxB,sBAAgB,4BAA4B,aAAa,MAAM,WAAW,IAAI,YAAY,YAAY,CAAC,IAAI;AAAA,IAC7G;AACA,QAAI,mBAAmB;AACvB,QAAI,SAAS,aAAa,GAAG;AAC3B,yBAAmB;AAAA,oCACW;AAAA;AAAA;AAAA;AAAA,IAIhC;AACA,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA,UAIV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAQwB;AAAA;AAAA;AAAA;AAAA,8BAIJ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YASlB;AAAA;AAAA;AAAA,iCAGqB;AAAA,cACnB,4BAA4B;AAAA;AAAA;AAAA,YAG9B;AAAA,qBACS,4BAA4B;AAAA;AAAA;AAAA;AAAA;AAAA,YAKrC;AAAA,qBACS,4BAA4B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAMrC;AAAA;AAAA;AAAA;AAAA;AAAA,EAKV;AACF;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,YAAY,YAAY;AAClC,SAAK,gBAAgB,CAAC,GAAG;AACzB,UAAM,EAAE,YAAY,WAAW,QAAQ,QAAQ,IAAI;AACnD,SAAK,cAAc,CAAC,WAAW,OAAO;AACtC,QAAI,sBAAsB;AAC1B,QAAI,YAAY;AAChB,QAAI,eAAe,QAAQ;AACzB,4BAAsB;AAAA,IACxB,WAAW,eAAe,OAAO;AAC/B,4BAAsB;AACtB,kBAAY;AAAA,IACd,WAAW,eAAe,OAAO;AAC/B,4BAAsB;AACtB,kBAAY;AAAA,IACd;AACA,QAAI,cAAc,GAAG,cAAc,cAAc;AACjD,QAAI,eAAe,OAAO;AACxB,oBAAc;AAAA,IAChB,WAAW,eAAe,QAAQ;AAChC,oBAAc;AAAA,IAChB,WAAW,eAAe,OAAO;AAC/B,oBAAc;AAAA,IAChB,WAAW,eAAe,OAAO;AAC/B,oBAAc;AAAA,IAChB;AACA,UAAM,wBAAwB,KAAK,MAAM,aAAa,CAAC,IAAI;AAC3D,UAAM,0BAA0B,aAAa;AAC7C,QAAI,gBAAgB;AAAA,YACZ,eAAe;AAAA;AAAA,mBAER,eAAe;AAAA;AAAA;AAAA;AAAA,wBAIV;AAAA,cACV,eAAe,YAAY,eAAe;AAAA,0BAC9B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAQtB,QAAI,UAAU;AACd,QAAI,eAAe,OAAO;AACxB,4BAAsB;AACtB,sBAAgB;AAAA;AAAA;AAAA;AAAA;AAKhB,gBAAU;AAAA,IACZ,WAAW,eAAe,OAAO;AAC/B,4BAAsB;AACtB,sBAAgB;AAAA;AAAA;AAAA;AAAA;AAKhB,gBAAU;AAAA,IACZ;AACA,QAAI,mBAAmB;AACvB,QAAI,SAAS,aAAa,GAAG;AAC3B,yBAAmB;AAAA,oCACW;AAAA;AAAA;AAAA;AAAA,IAIhC;AACA,SAAK,WAAW;AAAA,0CACsB;AAAA;AAAA;AAAA;AAAA,UAIhC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAQwB;AAAA;AAAA,kCAEA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAMJ;AAAA;AAAA,YAElB,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAOpB;AAAA;AAAA;AAAA,iCAGqB;AAAA,cACnB,4BAA4B;AAAA,YAC9B,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAOpB;AAAA,qBACS,4BAA4B;AAAA,YACrC,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAOpB;AAAA,qBACS,4BAA4B;AAAA,YACrC,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAOpB;AAAA;AAAA,oBAEQ;AAAA;AAAA;AAAA,EAGlB;AACF;AAGA,SAAS,mBAAmB,SAAS;AACnC,QAAM,SAAS,CAAC;AAChB,SAAO,OAAO,WAAW,KAAK,OAAO,OAAO,SAAS,GAAG,YAAY,GAAG;AACrE,UAAM,UAAU,OAAO,SAAS,OAAO,OAAO,SAAS,GAAG,UAAU,QAAQ;AAC5E,UAAM,aAAa,qBAAqB,yBAAyB,OAAO;AACxE,WAAO,KAAK;AAAA,MACV,QAAQ;AAAA,MACR;AAAA,MACA,SAAS,KAAK,KAAK,UAAU,UAAU;AAAA,IACzC,CAAC;AAAA,EACH;AACA,SAAO;AACT;AACA,SAAS,OAAO,GAAG,OAAO,eAAe,UAAU;AACjD,QAAM,kBAAkB,mBAAmB,EAAE,KAAK;AAClD,MAAI,SAAS;AACb,WAAS,KAAK,GAAG,KAAK,gBAAgB,QAAQ,MAAM;AAClD,UAAM,EAAE,QAAQ,YAAY,QAAQ,IAAI,gBAAgB;AACxD,QAAI;AACJ,QAAI;AACJ,QAAI,kBAAkB,QAAQ;AAC5B,gBAAU,OAAO,IAAI,IAAI,YAAY,EAAE,YAAY,QAAQ,WAAW,EAAE,MAAM,IAAI,QAAQ,GAAG,MAAM,IAAI,IAAI,YAAY,EAAE,YAAY,QAAQ,WAAW,EAAE,MAAM,IAAI,QAAQ,CAAC;AAAA,IAC/K,OAAO;AACL,gBAAU,IAAI,cAAc,EAAE,YAAY,QAAQ,WAAW,EAAE,MAAM,IAAI,QAAQ,GAAG,aAAa;AAAA,IACnG;AACA,qBAAiB;AACjB,aAAS,SAAS,gBAAgB,SAAS,CAAC,MAAM,GAAG,KAAK;AAC1D,QAAI,eAAe,WAAW,EAAE,QAAQ;AACtC,eAAS,8BAA8B,cAAc;AAAA,IACvD;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,QAAQ,QAAQ;AAC1B,SAAK,gBAAgB,CAAC,GAAG;AACzB,UAAM,cAAc,IAAI,MAAM,OAAO,MAAM;AAC3C,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,MAAM;AAC9C,kBAAY,MAAM,OAAO,OAAO;AAAA,IAClC;AACA,SAAK,cAAc;AACnB,SAAK,OAAO,YAAY;AACxB,UAAM,QAAQ,kBAAkB,KAAK,IAAI;AACzC,UAAM,WAAW,kBAAkB,MAAM;AACzC,SAAK,WAAW;AAAA;AAAA,QAEZ;AAAA,uBACe;AAAA;AAAA;AAAA,EAGrB;AACF;AACA,SAAS,kBAAkB,QAAQ;AACjC,QAAM,OAAO,OAAO;AACpB,MAAI,OAAO,GAAG;AACZ,UAAM,MAAM,sBAAsB,2BAA2B;AAAA,EAC/D;AACA,QAAM,gBAAgB,CAAC,WAAW,WAAW,WAAW,WAAW,WAAW,SAAS;AACvF,QAAM,iBAAiB,IAAI,MAAM,IAAI;AACrC,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,mBAAe,OAAO,OAAO,cAAc;AAAA,EAC7C;AACA,SAAO,eAAe,KAAK;AAC7B;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,QAAQ,QAAQ;AAC1B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,UAAM,cAAc,IAAI,MAAM,OAAO,MAAM;AAC3C,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,MAAM;AAC9C,kBAAY,MAAM,OAAO,OAAO;AAAA,IAClC;AACA,SAAK,cAAc;AACnB,SAAK,OAAO,YAAY;AACxB,QAAI,KAAK,OAAO,GAAG;AACjB,YAAM,MAAM,6BAA6B,KAAK,4BAA4B;AAAA,IAC5E;AACA,UAAM,QAAQ,kBAAkB,KAAK,IAAI;AACzC,UAAM,cAAc,eAAe,MAAM,KAAK,IAAI;AAClD,UAAM,gBAAgB,IAAI,MAAM,KAAK,IAAI;AACzC,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,oBAAc,OAAO,OAAO,YAAY;AAAA,IAC1C;AACA,UAAM,YAAY,QAAQ,cAAc,MAAM,EAAE,EAAE,KAAK;AACvD,UAAM,aAAa,KAAK,YAAY,KAAK,OAAO,QAAQ,YAAY,KAAK,OAAO;AAChF,UAAM,OAAO,mBAAmB,cAAc,KAAK,OAAO;AAC1D,SAAK,WAAW;AAAA;AAAA,QAEZ;AAAA;AAAA,oBAEY;AAAA,WACT;AAAA,sBACW;AAAA;AAAA,UAEZ,YAAY,KAAK,OAAO;AAAA,aACrB,YAAY,KAAK,OAAO,QAAQ,YAAY,KAAK,OAAO;AAAA,sBAC/C;AAAA,aACT;AAAA,wBACW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAMtB;AACF;AAGA,SAAS,eAAe,GAAG,MAAM,UAAU;AACzC,QAAM,UAAU,IAAI,EAAE,QAAQ,6BAA6B,IAAI,IAAI,uBAAuB,EAAE,OAAO,IAAI,IAAI,IAAI,iBAAiB,EAAE,OAAO,IAAI;AAC7I,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACvD;AAGA,SAAS,QAAQ,GAAG,MAAM,UAAU,UAAU;AAC5C,QAAM,mBAAmB;AACzB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,aAAa,eAAe,kBAAkB,EAAE,KAAK;AACtE,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,QAAM,uBAAuB,gBAAgB;AAC7C,MAAI,WAAW;AACf,MAAI,sBAAsB;AACxB,eAAW,eAAe,GAAG,cAAc,QAAQ;AACnD,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAAA,EACjE;AACA,uBAAqB,2BAA2B,OAAO,MAAM,KAAK;AAClE,QAAM,CAAC,aAAa,WAAW,IAAI,qBAAqB,0BAA0B,SAAS,OAAO,IAAI;AACtG,MAAI,WAAW;AACf,MAAI,UAAU;AACZ,eAAW,qBAAqB,qBAAqB,aAAa,QAAQ;AAAA,EAC5E;AACA,QAAM,SAAS,aAAa,cAAc,WAAW;AACrD,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,YAAY,QAAQ;AAC1B,QAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,OAAO,EAAE,OAAO,CAAC,WAAW,MAAM,EAAE,GAAG,SAAS,SAAS,CAAC;AACpH,QAAM,UAAU,WAAW,EAAE,KAAK;AAClC,QAAM,UAAU,OAAO,eAAe,SAAS,OAAO,QAAQ;AAC9D,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AAC9F,WAAS,8BAA8B,aAAa;AACpD,WAAS,8BAA8B,OAAO;AAC9C,MAAI,sBAAsB;AACxB,aAAS,8BAA8B,QAAQ;AAAA,EACjD;AACA,SAAO;AACT;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,SAAO,QAAQ,GAAG,MAAM,UAAU,QAAQ;AAC5C;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,eAAe;AACrB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,IAAI,MAAM,KAAK;AAChC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,aAAS,MAAM,EAAE,MAAM,KAAK;AAAA,EAC9B;AACA,MAAI;AACJ,MAAI,aAAa,mBAAmB,CAAC,CAAC,CAAC,GAAG;AACxC,UAAM,WAAW,aAAa,QAAQ,IAAI,EAAE,MAAM;AAClD,UAAM,SAAS,SAAS;AACxB,UAAM,YAAY,iBAAiB,QAAQ,EAAE,OAAO,EAAE,OAAO,MAAM,QAAQ;AAC3E,UAAM,aAAa,eAAe,UAAU,EAAE,KAAK;AACnD,UAAM,UAAU,aAAa,QAAQ,IAAI,IAAI,MAAM;AACnD,YAAQ,SAAS;AAAA,EACnB,OAAO;AACL,UAAM,eAAe,GAAG,MAAM,YAAY;AAAA,EAC5C;AACA,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,8BAA8B;AAClC,SAAS,gBAAgB,EAAE,GAAG,GAAG,YAAY,YAAY,SAAS,UAAU,OAAO,MAAM,yBAAyB,MAAM,iBAAiB,GAAG,YAAY,cAAc,KAAK,GAAG;AAC5K,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,oBAAoB,uBAAuB,2BAA2B,EAAE,MAAM,MAAM,GAAG,EAAE,GAAG,EAAE,MAAM,MAAM,GAAG,EAAE,CAAC;AACtH,QAAM,WAAW,kBAAkB,OAAO,CAAC,aAAa,WAAW,CAAC;AACpE,eAAa,OAAO,gBAAgB,aAAa,MAAM,kCAAkC,qBAAqB,uCAAuC,EAAE,aAAa,EAAE,wBAAwB,6BAA6B,wBAAwB;AACnP,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,gBAAgB,CAAC,KAAK,GAAG;AAC/B,QAAM,WAAW,KAAK,IAAI,WAAW,SAAS;AAC9C,QAAM,YAAY,aAAa,IAAI,MAAM,KAAK,IAAI,MAAM;AACxD,QAAM,UAAU,QAAQ;AACxB,QAAM,4BAA4B,0BAA0B;AAC5D,QAAM,oBAAoB,gBAAgB;AAC1C,QAAM,kBAAkB,eAAe,OAAO,6BAA6B,aAAa,IAAI,IAAI;AAChG,QAAM,mBAAmB,WAAW,6BAA6B,qBAAqB,mBAAmB;AACzG,MAAI;AACJ,OAAK,gBAAgB,KAAK,gBAAgB,MAAM,YAAY,+BAA+B,qBAAqB,OAAO;AACrH,QAAI,OAAO;AACX,QAAI,OAAO;AACX,QAAI,YAAY;AACd,aAAO,WAAW,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,CAAC,GAAG,GAAG,CAAC,EAAE,EAAE,CAAC;AACvF,oBAAc,KAAK,IAAI;AAAA,IACzB;AACA,QAAI,YAAY;AACd,aAAO,WAAW,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,CAAC,GAAG,GAAG,CAAC,EAAE,EAAE,CAAC;AACvF,oBAAc,KAAK,IAAI;AAAA,IACzB;AACA,UAAM,iBAAiB,gBAAgB;AACvC,UAAM,iBAAiB,gBAAgB;AACvC,QAAI,SAAS;AACb,QAAI,gBAAgB;AAClB,eAAS,SAAS;AAAA,QAChB,QAAQ,EAAE,GAAG,KAAK;AAAA,QAClB,SAAS;AAAA,QACT,OAAO,EAAE,OAAO,CAAC,UAAU,WAAW,CAAC,EAAE;AAAA,MAC3C,CAAC;AACD,oBAAc,KAAK,MAAM;AAAA,IAC3B;AACA,UAAM,OAAO,gBAAgB,IAAI,IAAI;AACrC,QAAI,SAAS;AACb,QAAI,gBAAgB;AAClB,eAAS,SAAS;AAAA,QAChB,QAAQ,EAAE,GAAG,KAAK;AAAA,QAClB,SAAS;AAAA,QACT,OAAO,EAAE,OAAO,CAAC,UAAU,GAAG,SAAS,EAAE;AAAA,MAC3C,CAAC;AACD,oBAAc,KAAK,MAAM;AAAA,IAC3B;AACA,UAAM,UAAU,UAAU,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,OAAO,GAAG,SAAS,SAAS,CAAC;AACjF,UAAM,KAAK,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,UAAU,KAAK,EAAE,CAAC;AACzF,kBAAc,KAAK,OAAO;AAAA,EAC5B,OAAO;AACL,UAAM,QAAQ,WAAW,EAAE,OAAO,EAAE,KAAK;AACzC,UAAM,UAAU,IAAI,oBAAoB,UAAU,UAAU,CAAC,UAAU,aAAa,WAAW,GAAG,YAAY,YAAY,SAAS,iBAAiB,2BAA2B,iBAAiB;AAChM,UAAM,SAAS,CAAC,KAAK,GAAG;AACxB,QAAI,QAAQ,MAAM;AAChB,aAAO,KAAK,IAAI;AAAA,IAClB;AACA,QAAI,2BAA2B;AAC7B,aAAO,KAAK,sBAAsB;AAAA,IACpC;AACA,QAAI,mBAAmB;AACrB,YAAM,kBAAkB,SAAS,eAAe,CAAC,GAAG,WAAW,aAAa,kBAAkB,gBAAgB,SAAS,CAAC;AACxH,aAAO,KAAK,eAAe;AAC3B,oBAAc,KAAK,eAAe;AAAA,IACpC;AACA,UAAM,SAAS,gBAAgB,SAAS,QAAQ,KAAK;AAAA,EACvD;AACA,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAClG,gBAAc,KAAK,GAAG;AACtB,aAAW,MAAM,eAAe;AAC9B,aAAS,8BAA8B,EAAE;AAAA,EAC3C;AACA,SAAO;AACT;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,MAAM,uBAAuB,IAAI;AAC/C,QAAM,EAAE,YAAY,YAAY,YAAY,aAAa,eAAe,IAAI;AAC5E,SAAO,gBAAgB;AAAA,IACrB;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA,SAAS;AAAA,IACT;AAAA,IACA;AAAA,IACA;AAAA,IACA,YAAY;AAAA,EACd,CAAC;AACH;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AACX,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,KAAK,EAAE,UAAU,aAAa;AAC/D,UAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,UAAM,YAAY,iBAAiB,MAAM,MAAM;AAC/C,WAAO,SAAS,eAAe,EAAE,OAAO,EAAE,OAAO,SAAS;AAAA,EAC5D;AACA,MAAI;AACJ,MAAI,IAAI,EAAE,QAAQ,6BAA6B,GAAG;AAChD,cAAU,IAAI,qBAAqB,EAAE,OAAO,IAAI;AAAA,EAClD,OAAO;AACL,cAAU,IAAI,eAAe,EAAE,OAAO,IAAI;AAAA,EAC5C;AACA,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACvD;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAM/B,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,oBAAoB;AAAA;AAAA;AAGhC,IAAI,SAAS,iBAAiB,EAAE,WAAW,MAAM,CAAC;AAClD,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM;AACV,IAAI,gBAAgB,kBAAkB;AAAA,EACpC,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,iBAAiB;AAAA,EACjB,eAAe;AACjB,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,aAAa,QAAQ;AAC/B,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc;AACnB,SAAK,gBAAgB,OAAO,IAAI,CAAC,GAAG,OAAO,IAAI,IAAI;AACnD,UAAM,WAAW,CAAC;AAClB,SAAK,cAAc,QAAQ,CAAC,cAAc;AACxC,eAAS,KAAK,UAAU,kBAAkB,yBAAyB;AAAA,IACrE,CAAC;AACD,UAAM,YAAY,KAAK,cAAc,IAAI,CAAC,cAAc;AACtD,aAAO,IAAI;AAAA,IACb,CAAC,EAAE,KAAK,KAAK;AACb,SAAK,WAAW;AAAA;AAAA,UAEV,SAAS,KAAK,YAAY;AAAA;AAAA,yBAEX;AAAA;AAAA;AAAA;AAAA,EAIvB;AACF;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,aAAa,QAAQ;AAC/B,SAAK,cAAc,CAAC;AACpB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc;AACnB,SAAK,gBAAgB,OAAO,IAAI,CAAC,GAAG,OAAO,IAAI,IAAI;AACnD,UAAM,WAAW,CAAC;AAClB,SAAK,cAAc,QAAQ,CAAC,cAAc;AACxC,eAAS,KAAK,SAAS,kBAAkB,yBAAyB;AAAA,IACpE,CAAC;AACD,UAAM,YAAY,KAAK,cAAc,IAAI,CAAC,cAAc;AACtD,aAAO,IAAI;AAAA,IACb,CAAC,EAAE,KAAK,KAAK;AACb,SAAK,WAAW;AAAA;AAAA,UAEV,SAAS,KAAK,YAAY;AAAA;AAAA,wBAEZ;AAAA;AAAA;AAAA;AAAA,EAItB;AACF;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,UAAU;AAChB,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,GAAG,SAAS,SAAS,CAAC;AAAA,EACnE;AACA,MAAI,QAAQ,SAAS,IAAI,EAAE,IAAI,8BAA8B,GAAG;AAC9D,UAAM,WAAW,KAAK,MAAM,QAAQ,SAAS,CAAC;AAC9C,UAAM,WAAW,MAAM,EAAE,QAAQ,QAAQ,MAAM,GAAG,QAAQ,GAAG,SAAS,SAAS,CAAC;AAChF,UAAM,YAAY,MAAM,EAAE,QAAQ,QAAQ,MAAM,QAAQ,GAAG,SAAS,SAAS,CAAC;AAC9E,WAAO,MAAM,EAAE,QAAQ,CAAC,UAAU,SAAS,GAAG,SAAS,SAAS,CAAC;AAAA,EACnE;AACA,QAAM,QAAQ,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK,EAAE,OAAO,CAAC,IAAI,OAAO,WAAW,IAAI,EAAE,CAAC;AACjF,QAAM,SAAS,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK;AAC3C,QAAM,cAAc,IAAI,EAAE,QAAQ,YAAY;AAC9C,QAAM,UAAU,cAAc,IAAI,kBAAkB,QAAQ,GAAG,OAAO,MAAM,IAAI,IAAI,YAAY,QAAQ,GAAG,OAAO,MAAM;AACxH,SAAO,SAAS,gBAAgB,SAAS,SAAS,KAAK;AACzD;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,YAAY;AAChB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AAC1F,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAAA,EACjE;AACA,uBAAqB,2BAA2B,OAAO,MAAM,KAAK;AAClE,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,UAAU,OAAO,IAAI;AACpG,QAAM,SAAS,aAAa,cAAc,WAAW;AACrD,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,IAAI,MAAM,EAAE,EAAE,CAAC;AACpG,QAAM,UAAU,OAAO,KAAK,IAAI,OAAO,OAAO,QAAQ;AACtD,MAAI;AACJ,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,UAAU,QAAQ;AAC7E,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAAA,EAC1F,OAAO;AACL,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAAA,EAC1F;AACA,WAAS,8BAA8B,GAAG;AAC1C,WAAS,8BAA8B,OAAO;AAC9C,MAAI,gBAAgB,MAAM;AACxB,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,YAAY;AAChB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AAC1F,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAAA,EACjE;AACA,uBAAqB,2BAA2B,OAAO,MAAM,KAAK;AAClE,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,UAAU,OAAO,IAAI;AACpG,QAAM,SAAS,aAAa,cAAc,WAAW;AACrD,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,IAAI,MAAM,EAAE,EAAE,CAAC;AACpG,QAAM,UAAU,OAAO,KAAK,IAAI,OAAO,OAAO,QAAQ;AACtD,MAAI;AACJ,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,UAAU,QAAQ;AAC7E,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAAA,EAC1F,OAAO;AACL,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAAA,EAC1F;AACA,WAAS,8BAA8B,GAAG;AAC1C,WAAS,8BAA8B,OAAO;AAC9C,MAAI,gBAAgB,MAAM;AACxB,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,YAAY,KAAK,WAAW;AACtC,SAAK,gBAAgB,CAAC,GAAG;AACzB,UAAM,EAAE,YAAY,WAAW,QAAQ,IAAI;AAC3C,QAAI,CAAC,WAAW;AACd,WAAK,cAAc,KAAK,cAAc;AAAA,IACxC;AACA,SAAK,cAAc,CAAC,WAAW,OAAO;AACtC,UAAM,SAAS,QAAQ,QAAQ,MAAM;AACrC,UAAM,eAAe,YAAY,kBAAkB;AACnD,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,kCAKc;AAAA;AAAA;AAAA;AAAA;AAAA,8BAKJ;AAAA,wBACN;AAAA;AAAA,0BAEE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAQxB;AACF;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,OAAO,YAAY,KAAK,WAAW;AAC7C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,iBAAa,OAAO,MAAM,SAAS,GAAG,MAAM,aAAa,IAAI,OAAO,CAAC,EAAE,YAAY,IAAI,IAAI,MAAM,CAAC,2CAA2C;AAC7I,UAAM,SAAS,MAAM,MAAM,SAAS;AACpC,UAAM,UAAU,KAAK,KAAK,SAAS,UAAU;AAC7C,SAAK,cAAc,MAAM,MAAM,GAAG,EAAE;AACpC,QAAI,UAAU,GAAG;AACf,WAAK,YAAY,KAAK,OAAO;AAAA,IAC/B;AACA,QAAI,CAAC,WAAW;AACd,WAAK,cAAc,KAAK,cAAc;AAAA,IACxC;AACA,UAAM,WAAW,KAAK;AACtB,UAAM,OAAO,SAAS;AACtB,UAAM,QAAQ,kBAAkB,IAAI;AACpC,UAAM,UAAU,YAAY,UAAU,IAAI;AAC1C,QAAI;AACJ,QAAI;AACJ,QAAI,YAAY,GAAG;AACjB,mBAAa,OAAO;AACpB,YAAM,iBAAiB,kBAAkB,UAAU;AACnD,uBAAiB;AAAA,UACb,+BAA+B,kBAAkB,QAAQ,KAAK;AAAA,YAC5D,QAAQ,OAAO;AAAA,UACjB,+BAA+B,kBAAkB,QAAQ,KAAK;AAAA,YAC5D,QAAQ,OAAO;AAAA,UACjB,+BAA+B,kBAAkB,QAAQ,KAAK;AAAA,YAC5D,QAAQ,OAAO;AAAA,UACjB,+BAA+B,kBAAkB,QAAQ,KAAK;AAAA,YAC5D,QAAQ,OAAO;AAAA,IACvB,OAAO;AACL,mBAAa;AACb,uBAAiB;AAAA,UACb;AAAA,YACE,QAAQ,OAAO;AAAA,UACjB;AAAA,YACE,QAAQ,OAAO;AAAA,UACjB;AAAA,YACE,QAAQ,OAAO;AAAA,UACjB;AAAA,YACE,QAAQ,OAAO;AAAA,IACvB;AACA,UAAM,WAAW,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG,EAAE,MAAM,GAAG,UAAU;AACnE,UAAM,YAAY,MAAM,SAAS,aAAa;AAC9C,UAAM,cAAc,SAAS,IAAI,CAAC,MAAM,SAAS,CAAC;AAClD,UAAM,aAAa,YAAY,cAAc,aAAa,CAAC,EAAE,OAAO,SAAS;AAC7E,UAAM,aAAa,YAAY,cAAc,aAAa,CAAC,EAAE,OAAO,SAAS;AAC7E,UAAM,aAAa,YAAY,cAAc,aAAa,CAAC,EAAE,OAAO,SAAS;AAC7E,UAAM,aAAa,YAAY,cAAc,aAAa,CAAC,EAAE,OAAO,SAAS;AAC7E,UAAM,SAAS,QAAQ,QAAQ,gBAAgB;AAC/C,UAAM,oBAAoB,YAAY,KAAK;AAAA,sDACO,WAAW,KAAK;AAAA,sDAChB,WAAW,KAAK;AAAA,sDAChB,WAAW,KAAK;AAAA,sDAChB,WAAW,KAAK;AAClE,UAAM,aAAa;AAAA,0BACG,WAAW,KAAK;AAAA,uCACH,WAAW,KAAK;AAAA,uCAChB,WAAW,KAAK;AAAA,qDACF,WAAW,KAAK;AACjE,UAAM,gCAAgC,YAAY,KAAK;AAAA,qCACtB,YAAY,KAAK;AAAA,4CACV,SAAS,KAAK;AAAA,iDACT,SAAS,MAAM,EAAE,EAAE,KAAK;AAAA;AAErE,SAAK,WAAW;AAAA,0BACM,YAAY,KAAK;AAAA,iCACV,SAAS,KAAK;AAAA,sCACT,SAAS,MAAM,EAAE,EAAE,KAAK;AAAA;AAAA,QAEtD;AAAA;AAAA,UAEE;AAAA,4BACkB,QAAQ,OAAO,QAAQ,SAAS,OAAO,KAAK;AAAA,4BAC5C,QAAQ,OAAO,QAAQ,SAAS,OAAO,KAAK;AAAA,UAC9D;AAAA,yCAC+B,wBAAwB;AAAA,sBAC3C,wBAAwB,gBAAgB;AAAA;AAAA;AAAA,2BAGnC;AAAA;AAAA,8BAEG;AAAA;AAAA,YAElB;AAAA,6BACiB;AAAA;AAAA;AAAA,mBAGV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAYjB;AACF;AAGA,SAAS,UAAU,UAAU,GAAG,YAAY,eAAe,MAAM;AAC/D,MAAI,YAAY,EAAE,MAAM;AACxB,MAAI,SAAS,EAAE,MAAM;AACrB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,aAAa,MAAM;AAC/B,aAAS,aAAa,MAAM;AAAA,EAC9B;AACA,QAAM,aAAa,qBAAqB,yBAAyB,MAAM;AACvE,QAAM,aAAa,EAAE,YAAY,QAAQ,WAAW,SAAS,KAAK,KAAK,SAAS,UAAU,EAAE;AAC5F,QAAM,UAAU,IAAI,iBAAiB,YAAY,YAAY,gBAAgB,IAAI;AACjF,QAAM,SAAS,CAAC,CAAC;AACjB,MAAI,gBAAgB,MAAM;AACxB,WAAO,KAAK,YAAY;AAAA,EAC1B;AACA,QAAM,SAAS,SAAS,gBAAgB,SAAS,QAAQ,OAAO;AAChE,MAAI,OAAO,MAAM,OAAO,GAAG;AACzB,WAAO;AAAA,EACT;AACA,QAAM,SAAS,UAAU,UAAU,GAAG,YAAY,MAAM;AACxD,WAAS,8BAA8B,MAAM;AAC7C,SAAO;AACT;AACA,SAAS,gBAAgB,UAAU,GAAG,YAAY,eAAe,MAAM;AACrE,QAAM,UAAU,gBAAgB,OAAO,aAAa,QAAQ,EAAE;AAC9D,QAAM,SAAS,QAAQ,QAAQ,SAAS;AACxC,QAAM,aAAa,qBAAqB,yBAAyB,MAAM;AACvE,QAAM,UAAU,IAAI,uBAAuB,SAAS,YAAY,YAAY,gBAAgB,IAAI;AAChG,QAAM,SAAS,gBAAgB,OAAO,CAAC,CAAC,IAAI,CAAC,GAAG,YAAY;AAC5D,QAAM,SAAS,SAAS,gBAAgB,SAAS,QAAQ,OAAO;AAChE,MAAI,OAAO,MAAM,WAAW,EAAE,MAAM,QAAQ;AAC1C,UAAM,SAAS,gBAAgB,UAAU,GAAG,YAAY,MAAM;AAC9D,aAAS,8BAA8B,MAAM;AAC7C,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,gBAAgB,UAAU,GAAG,MAAM,YAAY;AACtD,QAAM,OAAO,CAAC,IAAI;AAClB,uBAAqB,2BAA2B,QAAQ,WAAW,OAAO,CAAC,EAAE,YAAY,IAAI,WAAW,MAAM,CAAC,GAAG,MAAM,EAAE,MAAM,MAAM;AACtI,MAAI,CAAC,IAAI,EAAE,QAAQ,mBAAmB,KAAK,EAAE,MAAM,UAAU,GAAG;AAC9D,UAAM,0BAA0B,CAAC;AACjC,UAAM,WAAW,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC9C,UAAM,YAAY,aAAa,QAAQ,SAAS;AAChD,QAAI,YAAY;AAChB,QAAI,WAAW;AACb,kBAAY,SAAS,aAAa,CAAC;AACnC,8BAAwB,KAAK,SAAS;AAAA,IACxC;AACA,UAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,UAAU,OAAO,IAAI;AACpG,UAAM,SAAS,aAAa,cAAc,WAAW;AACrD,UAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,IAAI,MAAM,EAAE,EAAE,CAAC;AACpG,4BAAwB,KAAK,GAAG;AAChC,UAAM,UAAU,UAAU,UAAU,KAAK,UAAU;AACnD,4BAAwB,KAAK,OAAO;AACpC,UAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACnG,4BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,WAAO;AAAA,EACT;AACA,SAAO,gBAAgB,UAAU,GAAG,UAAU;AAChD;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACpD,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,QAAM,0BAA0B,CAAC;AACjC,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,4BAAwB,KAAK,EAAE;AAC/B,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,GAAG,MAAM,MAAM;AAAA,EAC3E;AACA,uBAAqB,2BAA2B,UAAU,CAAC,KAAK,EAAE,GAAG,GAAG,MAAM,MAAM;AACpF,QAAM,MAAM,gBAAgB,UAAU,IAAI,KAAK,IAAI,KAAK;AACxD,0BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACpD,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,QAAM,0BAA0B,CAAC;AACjC,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,4BAAwB,KAAK,EAAE;AAC/B,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,GAAG,MAAM,MAAM;AAAA,EAC3E;AACA,uBAAqB,2BAA2B,UAAU,CAAC,KAAK,EAAE,GAAG,GAAG,MAAM,MAAM;AACpF,QAAM,MAAM,gBAAgB,UAAU,IAAI,KAAK,IAAI,KAAK;AACxD,0BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAM/B,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,oBAAoB;AAChC,IAAI,SAAS,iBAAiB,EAAE,WAAW,MAAM,CAAC;AAClD,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,oBAAoB;AAAA;AAAA;AAG/B,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,2BAA2B;AAAA;AAAA;AAGvC,IAAI,eAAe;AAAA;AAAA;AAAA,MAGb,kCAAkC;AAAA;AAAA;AAGxC,IAAI,SAAS,kBAAkB,EAAE,WAAW,OAAO,iBAAiB,aAAa,CAAC;AAClF,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,oBAAoB;AAAA;AAAA;AAGhC,IAAI,SAAS,iBAAiB,EAAE,WAAW,MAAM,CAAC;AAClD,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,UAAU,UAAU,kBAAkB,mBAAmB,OAAO,sBAAsB,OAAO;AACvG,SAAK,gBAAgB,CAAC,GAAG;AACzB,QAAI,aAAa,SAAS,kBAAkB;AAC1C,YAAM,IAAI,MAAM,4CAA4C;AAAA,IAC9D;AACA,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,iBAAiB,SAAS;AAChC,UAAM,gBAAgB,SAAS;AAC/B,UAAM,wBAAwB,SAAS;AACvC,UAAM,uBAAuB,SAAS;AACtC,UAAM,SAAS,SAAS,QAAQ;AAChC,UAAM,UAAU,SAAS,QAAQ;AACjC,SAAK,cAAc,SAAS;AAC5B,UAAM,YAAY,aAAa;AAC/B,UAAM,0BAA0B,cAAc,SAAS,oBAAoB,SAAS,mBAAmB,SAAS;AAChH,UAAM,qBAAqB,SAAS,SAAS,mBAAmB,SAAS;AACzE,QAAI,sBAAsB;AAC1B,QAAI,CAAC,WAAW;AACd,4BAAsB;AAAA,IACxB;AACA,QAAI,kBAAkB;AACpB,YAAM,aAAa;AACnB,WAAK,WAAW;AAAA,sCACgB,iBAAiB;AAAA,mCACpB,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAkBZ;AAAA,sBACZ;AAAA;AAAA;AAAA,kCAGY,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP;AAAA,wBACZ;AAAA;AAAA;AAAA,oCAGY,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0BAUnB;AAAA;AAAA;AAAA,mCAGS,mBAAmB,sBAAsB,0BAA0B,qBAAqB,QAAQ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAO7H;AAAA,IACF;AACA,UAAM,YAAY;AAClB,QAAI,cAAc,GAAG,YAAY,YAAY;AAC7C,QAAI,aAAa,OAAO;AACtB,oBAAc;AAAA,IAChB;AACA,UAAM,yBAAyB,KAAK,MAAM,cAAc,CAAC,IAAI;AAC7D,UAAM,2BAA2B,cAAc;AAC/C,UAAM,gBAAgB;AAAA,YACd;AAAA;AAAA;AAAA,wBAGY;AAAA;AAAA;AAGpB,SAAK,WAAW;AAAA,oCACgB,iBAAiB;AAAA,iCACpB,WAAW;AAAA,0CACF;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAMZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAkBL;AAAA;AAAA;AAAA;AAAA,gCAIF;AAAA,oBACZ;AAAA;AAAA;AAAA,gCAGY,SAAS;AAAA;AAAA;AAAA;AAAA,kCAIP;AAAA,uCACK;AAAA;AAAA;AAAA;AAAA,yCAIE;AAAA,6CACI;AAAA,6CACA;AAAA;AAAA;AAAA,cAG/B;AAAA;AAAA;AAAA,gCAGkB;AAAA,gBAChB,6BAA6B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAQ/B;AAAA,uBACS,6BAA6B;AAAA;AAAA;AAAA,yCAGX;AAAA;AAAA;AAAA;AAAA;AAAA,cAK3B;AAAA,uBACS,6BAA6B;AAAA;AAAA;AAAA,yCAGX;AAAA,6CACI;AAAA;AAAA;AAAA;AAAA,cAI/B;AAAA;AAAA;AAAA,oBAGM;AAAA;AAAA;AAAA,EAGlB;AACF;AACA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,UAAU,UAAU,kBAAkB,mBAAmB,OAAO,sBAAsB,OAAO;AACvG,SAAK,gBAAgB,CAAC,GAAG;AACzB,QAAI,aAAa,SAAS,kBAAkB;AAC1C,YAAM,IAAI,MAAM,4CAA4C;AAAA,IAC9D;AACA,UAAM,cAAc,SAAS;AAC7B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,gBAAgB,SAAS;AAC/B,UAAM,iBAAiB,SAAS;AAChC,UAAM,gBAAgB,SAAS;AAC/B,UAAM,uBAAuB,SAAS;AACtC,UAAM,wBAAwB,SAAS;AACvC,UAAM,uBAAuB,SAAS;AACtC,UAAM,WAAW,SAAS,QAAQ;AAClC,UAAM,SAAS,SAAS,QAAQ;AAChC,UAAM,UAAU,SAAS,QAAQ;AACjC,SAAK,cAAc,SAAS;AAC5B,UAAM,YAAY,aAAa;AAC/B,QAAI,sBAAsB;AAC1B,QAAI,CAAC,WAAW;AACd,4BAAsB;AAAA,IACxB;AACA,QAAI,kBAAkB;AACpB,YAAM,aAAa;AACnB,WAAK,WAAW;AAAA;AAAA,oBAEF,gBAAgB,iBAAiB;AAAA,mCAClB,aAAa,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAkBzB;AAAA,sBACZ;AAAA;AAAA;AAAA,kCAGY,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP;AAAA,wBACZ;AAAA;AAAA;AAAA,oCAGY,SAAS;AAAA;AAAA;AAAA;AAAA,sCAIP;AAAA,0BACZ;AAAA;AAAA;AAAA,sCAGY,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,4BAUnB;AAAA;AAAA;AAAA,qCAGS,mBAAmB,sBAAsB,cAAc,SAAS,mBAAmB,SAAS,oBAAoB,SAAS,mBAAmB,SAAS,oBAAoB,UAAU,SAAS,oBAAoB,SAAS,mBAAmB,SAAS,oBAAoB,QAAQ,2BAA2B;AAAA,6BACpT;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAQvB;AAAA,IACF;AACA,UAAM,YAAY;AAClB,QAAI,cAAc,GAAG,YAAY,YAAY;AAC7C,QAAI,aAAa,OAAO;AACtB,oBAAc;AAAA,IAChB;AACA,UAAM,yBAAyB,KAAK,MAAM,cAAc,CAAC,IAAI;AAC7D,UAAM,2BAA2B,cAAc;AAC/C,UAAM,gBAAgB;AAAA,YACd;AAAA;AAAA;AAAA,wBAGY;AAAA;AAAA;AAGpB,SAAK,WAAW;AAAA;AAAA,gBAEJ,gBAAgB,iBAAiB;AAAA,iCAChB,aAAa,WAAW;AAAA,0CACf;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAMZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAmBL;AAAA;AAAA;AAAA;AAAA,gCAIF;AAAA,oBACZ;AAAA;AAAA;AAAA,gCAGY,SAAS;AAAA;AAAA;AAAA;AAAA,kCAIP;AAAA,oBACd;AAAA;AAAA;AAAA,kCAGc,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP;AAAA,yCACK;AAAA;AAAA;AAAA;AAAA,+CAIM;AAAA,mDACI;AAAA,mDACA;AAAA;AAAA;AAAA,gBAGnC;AAAA;AAAA;AAAA,kCAGkB;AAAA,kBAChB,6BAA6B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gBAQ/B;AAAA,yBACS,6BAA6B;AAAA;AAAA;AAAA,+CAGP;AAAA;AAAA;AAAA;AAAA;AAAA,gBAK/B;AAAA,yBACS,6BAA6B;AAAA;AAAA;AAAA,+CAGP;AAAA,mDACI;AAAA;AAAA;AAAA;AAAA,gBAInC;AAAA;AAAA;AAAA,sBAGM;AAAA;AAAA;AAAA;AAAA,EAIpB;AACF;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,oBAAkB,GAAG,SAAS;AAC9B,QAAM,EAAE,YAAY,SAAAV,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY;AAClB,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,SAAS,GAAG,MAAM,wEAAwEA,2BAA0B,YAAY;AACjN,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,MAAI,SAAS,gBAAgB,KAAK,SAAS,iBAAiB,KAAK,aAAa,YAAY,SAAS,SAAS,SAAS,QAAQ,GAAG;AAC9H,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD;AACA,QAAM,iBAAiB,IAAI,cAAc,UAAU,OAAO,KAAK;AAC/D,SAAO,SAAS,gBAAgB,gBAAgB,CAAC,CAAC,GAAG,SAAS;AAChE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,iBAAiB,WAAW,IAAI;AACxE,QAAM,YAAY,CAAC,GAAG,GAAG,CAAC;AAC1B,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,iBAAiB,UAAU;AAClI,QAAM,iBAAiB,IAAI,cAAc,UAAU,OAAO,KAAK;AAC/D,SAAO,SAAS,gBAAgB,gBAAgB,CAAC,CAAC,GAAG,SAAS;AAChE;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,MAAM;AAAA,EACnC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,IAAI;AAC1B,SAAK,cAAc,SAAS;AAC5B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,iBAAiB,SAAS;AAChC,UAAM,gBAAgB,SAAS;AAC/B,UAAM,wBAAwB,SAAS;AACvC,UAAM,uBAAuB,SAAS;AACtC,UAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,UAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,UAAM,gBAAgB,KAAK,eAAe;AAC1C,SAAK,WAAW;AAAA,iCACa,WAAW;AAAA,0CACF;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAcV;AAAA,oBACZ;AAAA,gDAC4B;AAAA;AAAA,oCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA,kCAKX;AAAA,mBACf;AAAA,kDAC+B;AAAA;AAAA,sCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAc7C;AACF;AACA,IAAI,2BAA2B,MAAM;AAAA,EACnC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,IAAI;AAC1B,SAAK,cAAc,SAAS;AAC5B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,gBAAgB,SAAS;AAC/B,UAAM,iBAAiB,SAAS;AAChC,UAAM,gBAAgB,SAAS;AAC/B,UAAM,uBAAuB,SAAS;AACtC,UAAM,wBAAwB,SAAS;AACvC,UAAM,uBAAuB,SAAS;AACtC,UAAM,WAAW,uBAAuB,IAAI,SAAS,QAAQ;AAC7D,UAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,UAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,UAAM,gBAAgB,KAAK,cAAc,eAAe;AACxD,SAAK,WAAW;AAAA,iCACa,aAAa,WAAW;AAAA,0CACf;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAiBV;AAAA,oBACZ;AAAA,gDAC4B;AAAA;AAAA,oCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA,kCAKX;AAAA,sBACZ;AAAA,kDAC4B;AAAA;AAAA,sCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oCAMX;AAAA,wBACZ;AAAA,oDAC4B;AAAA;AAAA,wCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAe/C;AACF;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,OAAO,IAAI;AAC9B,QAAM,IAAI;AACV,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY,CAAC,GAAG,GAAG,CAAC;AAC1B,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,QAAM,yBAAyB,IAAI,yBAAyB,QAAQ;AACpE,SAAO,SAAS,gBAAgB,wBAAwB,CAAC,EAAE,GAAG,EAAE,KAAK;AACvE;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,OAAO,IAAI;AAC9B,QAAM,IAAI;AACV,oBAAkB,CAAC,IAAI,MAAM,GAAG,aAAa;AAC7C,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,KAAK,IAAI;AAC3C,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,IAAI;AAC7F,QAAM,yBAAyB,IAAI,yBAAyB,QAAQ;AACpE,SAAO,SAAS,gBAAgB,wBAAwB,CAAC,EAAE,GAAG,EAAE,KAAK;AACvE;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,EAAE,IAAI;AACjB,QAAM,EAAE,YAAY,WAAW,IAAI;AACnC,SAAO,gBAAgB,EAAE,GAAG,GAAG,YAAY,YAAY,SAAS,SAAS,CAAC;AAC5E;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,QAAQ,WAAW,eAAe,aAAa,YAAY,iBAAiB;AACtF,SAAK,cAAc,CAAC;AACpB,SAAK,gBAAgB,CAAC,KAAK,QAAQ,UAAU;AAC7C,yBAAqB,2BAA2B,QAAQ,SAAS;AACjE,yBAAqB,2BAA2B,QAAQ,aAAa;AACrE,QAAI,gBAAgB;AACpB,QAAI,eAAe,MAAM;AACvB,2BAAqB,2BAA2B,QAAQ,WAAW;AACnE,WAAK,cAAc,KAAK,QAAQ;AAChC,sBAAgB;AAAA,IAClB;AACA,QAAI,eAAe;AACnB,QAAI,cAAc,MAAM;AACtB,2BAAqB,2BAA2B,QAAQ,UAAU;AAClE,WAAK,cAAc,KAAK,OAAO;AAC/B,qBAAe;AAAA,IACjB;AACA,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,yBAKK;AAAA,wBACD;AAAA,2DACmC;AAAA;AAAA;AAAA;AAAA,EAIzD;AACF;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,QAAQ,WAAW,eAAe,aAAa,YAAY,iBAAiB;AACtF,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,gBAAgB,CAAC,KAAK,QAAQ,UAAU;AAC7C,yBAAqB,2BAA2B,QAAQ,SAAS;AACjE,yBAAqB,2BAA2B,QAAQ,aAAa;AACrE,QAAI,gBAAgB;AACpB,QAAI,eAAe,MAAM;AACvB,2BAAqB,2BAA2B,QAAQ,WAAW;AACnE,WAAK,cAAc,KAAK,QAAQ;AAChC,sBAAgB;AAAA,IAClB;AACA,QAAI,eAAe;AACnB,QAAI,cAAc,MAAM;AACtB,2BAAqB,2BAA2B,QAAQ,UAAU;AAClE,WAAK,cAAc,KAAK,OAAO;AAC/B,qBAAe;AAAA,IACjB;AACA,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA,wBAEI;AAAA,uBACD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,yDAMkC;AAAA;AAAA;AAAA;AAAA;AAAA,EAKvD;AACF;AAGA,IAAI,aAAa,CAAC,EAAE,QAAQ,SAAS,UAAU,MAAM,MAAM;AACzD,QAAM,EAAE,GAAG,MAAM,OAAO,UAAU,QAAQ,OAAOS,QAAO,IAAI;AAC5D,eAAa,OAAO,MAAM,MAAM,WAAW,SAAS,MAAM,QAAQ,MAAM,8EAA8E;AACtJ,eAAa,OAAO,UAAU,QAAQ,MAAM,MAAM,WAAW,OAAO,MAAM,QAAQ,MAAM,4EAA4E;AACpK,eAAa,OAAOA,WAAU,QAAQ,MAAM,MAAM,WAAWA,QAAO,MAAM,QAAQ,MAAM,2EAA2E;AACnK,MAAI,EAAE,gBAAgB,IAAI;AAC1B,MAAI,mBAAmB,MAAM;AAC3B,sBAAkB;AAAA,EACpB;AACA,QAAM,cAAc,CAAC,GAAG,OAAO,QAAQ;AACvC,MAAI,cAAc;AAClB,MAAI,UAAU,MAAM;AAClB,kBAAc,OAAO;AACrB,gBAAY,KAAK,MAAM;AAAA,EACzB;AACA,MAAI,aAAa;AACjB,MAAIA,WAAU,MAAM;AAClB,iBAAaA,QAAO;AACpB,gBAAY,KAAKA,OAAM;AAAA,EACzB;AACA,QAAM,UAAU,IAAI,EAAE,QAAQ,0BAA0B,IAAI,IAAI,uBAAuB,EAAE,OAAO,MAAM,OAAO,SAAS,OAAO,aAAa,YAAY,eAAe,IAAI,IAAI,iBAAiB,EAAE,OAAO,MAAM,OAAO,SAAS,OAAO,aAAa,YAAY,eAAe;AAC5Q,QAAM,SAAS,SAAS,gBAAgB,SAAS,aAAa,YAAY,GAAG,KAAK;AAClF,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,QAAQ;AAC9B,SAAK,cAAc;AACnB,SAAK,OAAO,SAAS;AACrB,UAAM,QAAQ,kBAAkB,KAAK,IAAI;AACzC,SAAK,iBAAiB,CAAC,EAAE,MAAM,SAAS,YAAY,KAAK,MAAM,MAAM,MAAM,CAAC;AAC5E,UAAM,eAAe,UAAU,KAAK,IAAI;AACxC,QAAIgB;AACJ,UAAM,WAAW,SAAS,IAAI,CAAC,GAAG,OAAO;AACvC,aAAO,aAAa,OAAO,eAAe,gBAAgB,OAAO;AAAA,IACnE,CAAC;AACD,IAAAA,QAAO;AAAA,UACD;AAAA,UACA;AAAA,UACA,SAAS,KAAK,IAAI;AAAA;AAExB,SAAK,WAAW;AAAA;AAAA,UAEVA;AAAA,8BACoB;AAAA;AAAA;AAAA,EAG5B;AACF;AACA,IAAI,SAAS,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAC1C,SAAS,UAAU,MAAM;AACvB,MAAI,SAAS,GAAG;AACd,WAAO;AAAA,EACT,WAAW,QAAQ,GAAG;AACpB,WAAO,OAAO,MAAM,GAAG,IAAI,EAAE,IAAI,CAAC,MAAM,eAAe,CAAC,EAAE,KAAK,GAAG;AAAA,EACpE,OAAO;AACL,UAAM,MAAM,oBAAoB,2BAA2B;AAAA,EAC7D;AACF;AAGA,IAAI,qBAAqB,MAAM;AAAA,EAC7B,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,QAAQ;AAC9B,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc;AACnB,SAAK,OAAO,SAAS;AACrB,SAAK,iBAAiB,CAAC,EAAE,MAAM,SAAS,YAAY,KAAK,MAAM,MAAM,MAAM,CAAC;AAC5E,UAAM,QAAQ,kBAAkB,KAAK,IAAI;AACzC,UAAM,UAAU,YAAY,UAAU,KAAK,IAAI;AAC/C,UAAM,YAAY,YAAY,aAAa,KAAK,IAAI;AACpD,UAAM,YAAY,KAAK,SAAS,IAAI,cAAc,QAAQ,UAAU,MAAM,EAAE,EAAE,KAAK;AACnF,UAAM,aAAa,wBAAwB,UAAU,KAAK,OAAO;AACjE,UAAM,WAAW;AAAA,mBACF;AAAA,cACL,QAAQ,KAAK,OAAO,QAAQ,SAAS,KAAK,OAAO;AAAA,YACnD,UAAU,KAAK,OAAO;AAAA,qBACb;AAAA,YACT,UAAU,KAAK,OAAO;AAAA;AAAA;AAG9B,UAAM,WAAW,KAAK,SAAS,IAAI,KAAK;AAAA,UAClC,QAAQ,KAAK,OAAO;AAAA,cAChB,QAAQ,KAAK,OAAO,QAAQ,SAAS,KAAK,OAAO;AAAA,YACnD,UAAU,KAAK,OAAO;AAAA,qBACb;AAAA,gBACL,QAAQ,KAAK,OAAO,QAAQ,SAAS,KAAK,OAAO;AAAA,cACnD,UAAU,KAAK,OAAO;AAAA,uBACb;AAAA;AAAA;AAAA;AAInB,UAAM,iBAAiB,KAAK,QAAQ,IAAI;AAAA,cAC9B,SAAS,SAAS,IAAI,CAAC,GAAG,OAAO,SAAS,KAAK,EAAE,KAAK,QAAQ,SAAS,IAAI,CAAC,GAAG,OAAO,GAAG,UAAU,SAAS,QAAQ,eAAe,MAAM,EAAE,KAAK,IAAI;AAC9J,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA,UACA;AAAA,UACA;AAAA;AAAA,UAEA;AAAA,UACA;AAAA;AAAA;AAAA;AAAA,EAIR;AACF;AAGA,SAAS,aAAa,GAAG,OAAOrC,OAAM,UAAU;AAC9C,QAAM,WAAW,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC9C,QAAM,KAAK,SAAS,eAAeA,OAAM,EAAE,KAAK;AAChD,QAAM,aAAa,SAAS,QAAQ,IAAI,GAAG,MAAM;AACjD,SAAO,OAAO,YAAY,QAAQ;AAClC,aAAW,WAAW;AACtB,aAAW,QAAQA;AACnB,aAAW,QAAQ,EAAE;AACrB,MAAI,aAAa,mBAAmB,kBAAkB,OAAO,aAAa,eAAe,EAAE,KAAK,CAAC;AACjG,MAAI,SAAS,OAAO;AAClB,kBAAc,SAAS,MAAM;AAAA,EAC/B;AACA,aAAW,QAAQ;AAAA,IACjB;AAAA,IACA,YAAY,SAAS,SAAS,SAAS,MAAM,cAAc,EAAE;AAAA,EAC/D;AACA,QAAM,WAAW,SAAS,aAAa,IAAI,WAAW,MAAM,UAAU,KAAK;AAC3E,WAAS,aAAa,IAAI,WAAW,MAAM,YAAY,WAAW,CAAC;AACnE,SAAO;AACT;AACA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAO,MAAAA,MAAK,IAAI;AACxB,QAAM,CAAC,QAAQ,KAAK,IAAI,mBAAmB,iBAAiB,GAAG,OAAOA,KAAI;AAC1E,qBAAmB,kBAAkB,GAAG,QAAQ,KAAK;AACrD,MAAI,aAAa,cAAc,KAAK,MAAM,GAAG;AAC3C,WAAO,SAAS,eAAe,OAAO,EAAE,OAAO,CAAC,CAAC;AAAA,EACnD;AACA,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,KAAK,EAAE,UAAU,UAAU;AAC5D,UAAM,WAAW,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC9C,UAAM,YAAY,aAAa,SAAS,QAAQ,QAAQ,OAAO,EAAE,OAAO,EAAE,KAAK;AAC/E,WAAO,SAAS,eAAe,OAAO,EAAE,OAAO,SAAS;AAAA,EAC1D;AACA,QAAM,EAAE,SAAS,IAAI,SAAS,QAAQ,IAAI,EAAE,MAAM;AAClD,QAAM,cAAc,mBAAmB,iBAAiB,EAAE,OAAO,QAAQ,KAAK;AAC9E,MAAI,YAAY,CAAC,aAAa;AAC5B,UAAM,UAAU,IAAI,EAAE,QAAQ,6BAA6B,IAAI,IAAI,mBAAmB,KAAK,IAAI,IAAI,aAAa,KAAK;AACrH,UAAM,eAAe,CAAC,MAAM;AAC5B,WAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,YAAY;AAAA,EACrE;AACA,WAAS,YAAY,EAAE,MAAM;AAC7B,SAAO,aAAa,GAAG,QAAQ,OAAO,QAAQ;AAChD;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kBAAkB,CAAC,SAAS;AAC9B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,MAAM,IAAI;AAC9B,eAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,sEAAsE;AACrH,QAAM,QAAQ,WAAW,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAC/C,QAAM,WAAW,qBAAqB,YAAY,EAAE,OAAO,YAAY,KAAK;AAC5E,QAAM,WAAW,qBAAqB,YAAY,SAAS,QAAQ,WAAW,MAAM;AACpF,QAAM,mBAAmB,qBAAqB,oBAAoB,EAAE,OAAO,YAAY,KAAK;AAC5F,QAAM,mBAAmB,qBAAqB,oBAAoB,OAAO,WAAW,MAAM;AAC1F,QAAM,YAAY,qBAAqB,aAAa,kBAAkB,OAAO,WAAW,MAAM;AAC9F,QAAM,YAAY,CAAC;AACnB,QAAM,uBAAuB,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACtG,QAAM,yBAAyB,WAAW,EAAE,QAAQ,EAAE,GAAG,qBAAqB,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,SAAS,EAAE,CAAC;AAC/H,QAAM,wBAAwB,SAAS;AAAA,IACrC,QAAQ,EAAE,GAAG,uBAAuB;AAAA,IACpC,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,iBAAiB;AAAA,EACnC,CAAC;AACD,QAAM,SAAS,OAAO;AAAA,IACpB,QAAQ,EAAE,GAAG,sBAAsB;AAAA,IACnC,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,kBAAkB,MAAM,UAAU;AAAA,EACpD,CAAC;AACD,YAAU,KAAK,oBAAoB;AACnC,YAAU,KAAK,sBAAsB;AACrC,YAAU,KAAK,qBAAqB;AACpC,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,SAAO;AACT;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAAA,MAAK,IAAI;AACjB,QAAM,QAAQ,SAAS,SAAS,EAAE,MAAM;AACxC,QAAM,cAAc,SAAS,SAAS,QAAQ,MAAM;AACpD,QAAM,UAAU,gBAAgB,OAAO,aAAa,QAAQ,OAAO,QAAQ,OAAOA,KAAI;AACtF,SAAO,SAAS,eAAe,CAACA,KAAI,GAAG,QAAQ,OAAO,OAAO;AAC/D;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,IAAI,GAAG,IAAI;AACnB,QAAM,SAAS,SAAS,SAAS,GAAG,MAAM;AAC1C,QAAM,SAAS,SAAS,SAAS,GAAG,MAAM;AAC1C,QAAM,iBAAiB,qBAAqB,2BAA2B,MAAM,KAAK,MAAM,GAAG,MAAM,KAAK,MAAM,CAAC;AAC7G,SAAO,SAAS,eAAe,CAAC,eAAe,MAAM,GAAG,SAAS,WAAW,KAAK,cAAc,CAAC;AAClG;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY;AAChB,IAAI,YAAY,kBAAkB,EAAE,WAAW,WAAW,eAAe,iBAAiB,OAAO,OAAO,CAAC;AACzG,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,YAAY,SAAS,QAAQ,IAAI,OAAO,MAAM;AACpD,SAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,UAAU,mBAAmB,KAAK,GAAG,SAAS,SAAS,CAAC;AAC1F;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS;AACb,SAAS,IAAI,QAAQ,UAAU;AAC7B,QAAM,UAAU,IAAI,eAAe,OAAO,OAAO,MAAM;AACvD,QAAM,SAAS,SAAS,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO;AAClE,SAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC3E;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,IAAI;AAClB,MAAI,UAAU,aAAa;AACzB,QAAI,EAAE,UAAU,aAAa;AAC3B,aAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,IACvD;AACA,UAAM,cAAc,MAAM,EAAE,KAAK;AACjC,UAAM,SAAS,MAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AACtF,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,QAAQ,MAAM,YAAY,GAAG,SAAS,SAAS,CAAC;AAC1F,gBAAY,QAAQ;AACpB,aAAS,8BAA8B,MAAM;AAC7C,WAAO;AAAA,EACT;AACA,MAAI,EAAE,UAAU,aAAa;AAC3B,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,SAAS,MAAM,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AACrF,aAAS,8BAA8B,QAAQ;AAC/C,WAAO;AAAA,EACT;AACA,MAAI,CAAC,aAAa,gBAAgB,EAAE,OAAO,KAAK,GAAG;AACjD,UAAM,SAAS,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAC7D,WAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO,OAAO,OAAO,MAAM;AAAA,EAC7D;AACA,MAAI,UAAU,SAAS;AACrB,WAAO,IAAI,GAAG,QAAQ;AAAA,EACxB;AACA,MAAI,UAAU,QAAQ;AACpB,UAAM,kBAAkB,SAAS,eAAe,CAAC,GAAG,QAAQ,aAAa,uBAAuB,QAAQ,CAAC,CAAC;AAC1G,UAAM,eAAe,EAAE,GAAG,GAAG,GAAG,gBAAgB;AAChD,UAAM,SAAS,UAAU,EAAE,QAAQ,cAAc,SAAS,SAAS,CAAC;AACpE,aAAS,8BAA8B,eAAe;AACtD,WAAO;AAAA,EACT;AACA,QAAM,IAAI,MAAM,iCAAiC,EAAE,YAAY,OAAO;AACxE;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AACX,IAAI,QAAQ,iBAAiB,EAAE,WAAW,MAAM,iBAAiB,MAAM,eAAe,YAAY,CAAC;AACnG,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,QAAQ;AAClB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,iBAAiB;AAAA,MACpB,EAAE,MAAM,UAAU,MAAM,QAAQ;AAAA,MAChC,EAAE,MAAM,UAAU,MAAM,QAAQ;AAAA,IAClC;AACA,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAYlB;AACF;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,QAAQ;AAClB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,iBAAiB;AAAA,MACpB,EAAE,MAAM,UAAU,MAAM,QAAQ;AAAA,MAChC,EAAE,MAAM,UAAU,MAAM,QAAQ;AAAA,IAClC;AACA,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAYlB;AACF;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,cAAc,aAAa,IAAI;AACvC,MAAI;AACJ,MAAI,IAAI,EAAE,QAAQ,iBAAiB,GAAG;AACpC,cAAU,IAAI,kBAAkB,EAAE,KAAK;AAAA,EACzC,OAAO;AACL,cAAU,IAAI,YAAY,EAAE,KAAK;AAAA,EACnC;AACA,QAAM,eAAe,CAAC,CAAC,YAAY,GAAG,CAAC,YAAY,CAAC;AACpD,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,YAAY;AACrE;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,OAAO;AACjB,SAAK,gBAAgB,CAAC,QAAQ,MAAM;AACpC,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAclB;AACF;AAGA,SAAS,+BAA+B,eAAe,aAAa;AAClE,SAAO;AAAA,IACL,QAAQ,YAAY;AAAA,IACpB,OAAO,YAAY;AAAA,IACnB,OAAO,cAAc;AAAA,EACvB;AACF;AACA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,QAAM,UAAU,IAAI,kBAAkB,EAAE,KAAK;AAC7C,QAAM,gBAAgB;AAAA,IACpB,+BAA+B,GAAG,MAAM,mBAAmB,IAAI;AAAA,IAC/D,+BAA+B,GAAG,MAAM,mBAAmB,IAAI;AAAA,EACjE;AACA,SAAO,SAAS,gBAAgB,SAAS,eAAe,cAAc,GAAG,KAAK;AAChF;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,QAAQ;AAClB,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc,qBAAqB,gBAAgB,QAAQ,CAAC;AACjE,SAAK,gBAAgB,OAAO,IAAI,CAAC,GAAG,OAAO,IAAI,IAAI;AACnD,UAAM,UAAU,IAAI,MAAM,OAAO,SAAS,CAAC;AAC3C,YAAQ,KAAK,OAAO,GAAG;AACvB,aAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,cAAQ,MAAM,QAAQ,KAAK,KAAK,OAAO,IAAI;AAAA,IAC7C;AACA,UAAM,WAAW,CAAC,YAAY,QAAQ,+BAA+B;AACrE,aAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,YAAM,QAAQ,QAAQ,KAAK;AAC3B,eAAS,KAAK,iBAAiB,QAAQ,sBAAsB,aAAa,UAAU;AAAA,IACtF;AACA,UAAM,YAAY,QAAQ;AAC1B,UAAM,YAAY,QAAQ,QAAQ,SAAS;AAC3C,aAAS,KAAK,sBAAsB,oBAAoB,cAAc;AACtE,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAMV,SAAS,KAAK,YAAY;AAAA;AAAA;AAAA,EAGlC;AACF;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,QAAQ,MAAM;AACxB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc,qBAAqB,gBAAgB,QAAQ,IAAI;AACpE,UAAM,QAAQ,KAAK;AACnB,UAAM,OAAO,MAAM;AACnB,UAAM,QAAQ,kBAAkB,IAAI;AACpC,UAAM,UAAU,YAAY,UAAU,IAAI;AAC1C,UAAM,WAAW,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG,EAAE,MAAM,GAAG,IAAI;AAC7D,SAAK,gBAAgB,OAAO,IAAI,CAAC,GAAG,OAAO,IAAI,IAAI;AACnD,UAAM,UAAU,IAAI,MAAM,OAAO,SAAS,CAAC;AAC3C,YAAQ,KAAK,OAAO,GAAG;AACvB,aAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,cAAQ,MAAM,QAAQ,KAAK,KAAK,OAAO,IAAI;AAAA,IAC7C;AACA,UAAM,UAAU,SAAS;AACzB,UAAM,eAAe,SAAS,MAAM,EAAE;AACtC,UAAM,cAAc,SAAS,KAAK;AAClC,QAAI,kBAAkB,OAAO,aAAa,QAAQ;AAAA;AAAA,oBAElC,sBAAsB,aAAa,KAAK;AAAA;AAExD,aAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,YAAM,SAAS,QAAQ,KAAK;AAC5B,yBAAmB;AAAA,cACX,aAAa,QAAQ,WAAW,cAAc,QAAQ,KAAK;AAAA;AAAA,kBAEvD,MAAM,gBAAgB,UAAU,SAAS,MAAM;AAAA,mBAC9C,gBAAgB,cAAc,SAAS,MAAM;AAAA;AAAA,IAE5D;AACA,UAAM,YAAY,QAAQ;AAC1B,UAAM,QAAQ,QAAQ,QAAQ,SAAS;AACvC,uBAAmB;AAAA;AAAA,gBAEP,aAAa,gBAAgB,UAAU,SAAS,KAAK;AAAA,iBACpD,gBAAgB,cAAc,SAAS,KAAK;AACzD,SAAK,WAAW;AAAA,uBACG,SAAS,IAAI,CAAC,MAAM,SAAS,CAAC;AAAA,UAC3C;AAAA;AAAA;AAAA;AAAA,UAIA;AAAA,sCAC4B;AAAA;AAAA,UAE5B,QAAQ,OAAO,QAAQ,QAAQ,OAAO;AAAA,cAClC,QAAQ,OAAO,QAAQ,MAAM,OAAO;AAAA,gCAClB;AAAA;AAAA;AAAA,UAGtB,QAAQ,OAAO,QAAQ,QAAQ,OAAO;AAAA,cAClC,QAAQ,OAAO,QAAQ,MAAM,OAAO;AAAA,gCAClB;AAAA;AAAA;AAAA,UAGtB,QAAQ,OAAO,QAAQ,QAAQ,OAAO;AAAA,cAClC,QAAQ,OAAO,QAAQ,MAAM,OAAO;AAAA,cACpC,QAAQ,OAAO,QAAQ,MAAM,OAAO;AAAA,gCAClB;AAAA;AAAA;AAAA;AAAA;AAAA,EAK9B;AACF;AACA,SAAS,gBAAgB,UAAU,SAAS,OAAO;AACjD,QAAM,aAAa,SAAS,QAAQ,OAAO;AAC3C,QAAM,MAAM,SAAS,IAAI,CAAC,GAAG,QAAQ;AACnC,QAAI,QAAQ,YAAY;AACtB,aAAO,GAAG,OAAO;AAAA,IACnB,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF,CAAC;AACD,SAAO,IAAI,KAAK;AAClB;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,YAAY,SAAS,QAAQ,IAAI,OAAO,MAAM;AACpD,SAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,UAAU,mBAAmB,KAAK,GAAG,SAAS,SAAS,CAAC;AAC1F;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,QAAQ,MAAM,UAAU;AAC3C,QAAM,QAAQ,OAAO,GAAG;AACxB,MAAI,UAAU,aAAa;AACzB,UAAM,QAAQ,OAAO,IAAI,CAAC,OAAO,MAAM,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,SAAS,CAAC,CAAC;AACpF,UAAM,QAAQ,OAAO,IAAI,CAAC,OAAO,MAAM,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,SAAS,CAAC,CAAC;AACpF,UAAM,eAAe,YAAY,OAAO,MAAM,QAAQ;AACtD,UAAM,eAAe,YAAY,OAAO,MAAM,QAAQ;AACtD,UAAM,UAAU,SAAS,EAAE,QAAQ,EAAE,MAAM,cAAc,MAAM,aAAa,GAAG,SAAS,SAAS,CAAC;AAClG,UAAM,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAChE,UAAM,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAChE,aAAS,8BAA8B,YAAY;AACnD,aAAS,8BAA8B,YAAY;AACnD,WAAO;AAAA,EACT;AACA,MAAI,WAAW,SAAS,mBAAmB,MAAM;AACjD,MAAI,UAAU,UAAU;AACtB,eAAW;AAAA,EACb;AACA,MAAI,UAAU;AACZ,UAAM,aAAa,OAAO,IAAI,CAAC,OAAO;AACpC,YAAM,YAAY,aAAa,cAAc,GAAG,MAAM,MAAM,IAAI,CAAC;AACjE,YAAM,QAAQ,CAAC,IAAI,SAAS;AAC5B,aAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AAAA,IAC5E,CAAC;AACD,UAAM,kBAAkB,WAAW,IAAI,CAAC,OAAO;AAC7C,aAAO,EAAE,MAAM,SAAS,SAAS,GAAG,MAAM,GAAG,OAAO,GAAG,MAAM;AAAA,IAC/D,CAAC;AACD,UAAM,YAAY,qBAAqB,gBAAgB,WAAW,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,CAAC;AAC1F,UAAM,eAAe,WAAW,GAAG,MAAM,OAAO;AAChD,UAAM,UAAU,cAAc,iBAAiB,WAAW,OAAO,YAAY;AAC7E,UAAM,gBAAgB,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,IAAI;AAC7F,UAAM,UAAU,SAAS,eAAe,eAAe,OAAO,OAAO;AACrE,eAAW,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACrE,WAAO;AAAA,EACT;AACA,QAAM,sBAAsB,IAAI,EAAE,UAAU,8BAA8B;AAC1E,MAAI,OAAO,SAAS,qBAAqB;AACvC,UAAM,gBAAgB,CAAC;AACvB,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM,qBAAqB;AAC9D,YAAM,WAAW,OAAO,MAAM,IAAI,KAAK,mBAAmB;AAC1D,oBAAc,KAAK,YAAY,UAAU,MAAM,QAAQ,CAAC;AAAA,IAC1D;AACA,UAAM,UAAU,YAAY,eAAe,MAAM,QAAQ;AACzD,eAAW,MAAM,eAAe;AAC9B,eAAS,8BAA8B,EAAE;AAAA,IAC3C;AACA,WAAO;AAAA,EACT;AACA,MAAI,IAAI,EAAE,QAAQ,6BAA6B,KAAK,OAAO,GAAG,MAAM,SAAS,GAAG;AAC9E,UAAM,WAAW,IAAI,oBAAoB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,IAAI;AAC3E,WAAO,SAAS,gBAAgB,UAAU,QAAQ,KAAK;AAAA,EACzD;AACA,QAAM,EAAE,WAAW,SAAS,IAAI,iBAAiB,QAAQ,MAAM,QAAQ;AACvE,QAAM,UAAU,IAAI,cAAc,UAAU,IAAI,CAAC,OAAO,GAAG,KAAK,CAAC;AACjE,QAAM,SAAS,SAAS,gBAAgB,SAAS,WAAW,KAAK;AACjE,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AACxG,WAAS,8BAA8B,MAAM;AAC7C,SAAO;AACT;AACA,SAAS,iBAAiB,QAAQ,MAAM,UAAU;AAChD,QAAM,WAAW,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,IAAI;AACxF,QAAM,YAAY,OAAO,IAAI,CAAC,MAAM,SAAS;AAAA,IAC3C,QAAQ,EAAE,EAAE;AAAA,IACZ,OAAO,EAAE,OAAO,CAAC,IAAI,aAAa,cAAc,EAAE,MAAM,MAAM,IAAI,CAAC,CAAC,EAAE;AAAA,IACtE,SAAS;AAAA,EACX,CAAC,CAAC;AACF,SAAO,EAAE,WAAW,SAAS;AAC/B;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,QAAQ,aAAa,eAAe,MAAM,OAAO,GAAG,KAAK,EAAE;AACjE,QAAM,WAAW,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,KAAK;AACzF,MAAI,aAAa,cAAc,QAAQ,MAAM,GAAG;AAC9C,WAAO,SAAS,eAAe,UAAU,OAAO,GAAG,OAAO,CAAC,CAAC;AAAA,EAC9D;AACA,QAAM,UAAU,OAAO,OAAO,CAAC,OAAO,aAAa,cAAc,GAAG,KAAK,IAAI,CAAC;AAC9E,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,GAAG,SAAS,SAAS,CAAC;AAAA,EACnE;AACA,QAAM,SAAS,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK;AAC3C,uBAAqB,uBAAuB,QAAQ,KAAK;AACzD,SAAO,YAAY,SAAS,OAAO,QAAQ;AAC7C;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,UAAU,UAAU,OAAO,cAAc,MAAM,4BAA4B,OAAO,oBAAoB,OAAO;AACvH,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,cAAc,SAAS;AAC5B,UAAM,SAAS,SAAS,QAAQ;AAChC,UAAM,UAAU,SAAS,QAAQ;AACjC,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,iBAAiB,SAAS;AAChC,UAAM,gBAAgB,SAAS;AAC/B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,wBAAwB,KAAK,MAAM,SAAS,aAAa,CAAC,IAAI;AACpE,UAAM,0BAA0B,SAAS,aAAa;AACtD,UAAM,iBAAiB,SAAS,eAAe;AAC/C,UAAM,SAAS,iBAAiB,IAAI;AACpC,UAAM,SAAS,iBAAiB,IAAI;AACpC,UAAM,aAAa,iBAAiB,IAAI;AACxC,QAAI,oBAAoB,IAAI,yBAAyB;AACrD,QAAI,aAAa;AACf,UAAI,2BAA2B;AAC7B,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,WAAW,mBAAmB;AAC5B,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,OAAO;AACL,4BAAoB;AAAA;AAAA,cAEd;AAAA;AAAA;AAAA,MAGR;AACA,+BAAyB;AAAA,IAC3B;AACA,UAAM,iBAAiB,UAAU,oCAAoC;AACrE,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,2BAA2B;AAC7B,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,QAAI,mBAAmB;AACrB,WAAK,cAAc,KAAK,gBAAgB;AAAA,IAC1C;AACA,SAAK,WAAW;AAAA,QACZ;AAAA;AAAA,oCAE4B,iBAAiB;AAAA,iCACpB,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,0BAKlB;AAAA;AAAA;AAAA,2BAGC,mBAAmB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAOd;AAAA,qCACK;AAAA;AAAA,gCAEL,SAAS;AAAA;AAAA;AAAA;AAAA,kCAIP;AAAA,uCACK;AAAA;AAAA,kCAEL,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oBAQhB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kBAmBF,4BAA4B;AAAA;AAAA,oBAE1B;AAAA;AAAA,0CAEsB;AAAA,mCACP;AAAA;AAAA;AAAA,kCAGD;AAAA,mCACC;AAAA;AAAA;AAAA,yBAGV,4BAA4B;AAAA;AAAA,+BAEtB;AAAA,+BACA;AAAA;AAAA;AAAA,oBAGX;AAAA;AAAA,wCAEoB;AAAA,wCACA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAKR;AAAA,gCACA;AAAA;AAAA;AAAA;AAAA;AAAA,yBAKP,4BAA4B;AAAA;AAAA,+BAEtB;AAAA,+BACA;AAAA,+BACA;AAAA;AAAA;AAAA,oBAGX;AAAA;AAAA,wCAEoB;AAAA,wCACA;AAAA,wCACA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAKR;AAAA,gCACA;AAAA,gCACA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAUtB;AAAA,UACA;AAAA;AAAA;AAAA;AAAA,EAIR;AACF;AACA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,cAAc,SAAS;AAC5B,UAAM,WAAW,SAAS,QAAQ;AAClC,UAAM,SAAS,SAAS,QAAQ;AAChC,UAAM,UAAU,SAAS,QAAQ;AACjC,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,gBAAgB,SAAS;AAC/B,UAAM,iBAAiB,SAAS;AAChC,UAAM,gBAAgB,SAAS;AAC/B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,wBAAwB,KAAK,MAAM,SAAS,aAAa,CAAC,IAAI;AACpE,UAAM,0BAA0B,SAAS,aAAa;AACtD,SAAK,WAAW;AAAA,oCACgB,gBAAgB,iBAAiB;AAAA,iCACpC,aAAa,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAgBzB;AAAA,qCACK;AAAA;AAAA,gCAEL,SAAS;AAAA;AAAA;AAAA;AAAA,kCAIP;AAAA,uCACK;AAAA;AAAA,kCAEL,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP;AAAA,yCACK;AAAA;AAAA,oCAEL,SAAS;AAAA;AAAA;AAAA;AAAA,sCAIP;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oBAiBlB,4BAA4B;AAAA;AAAA,4CAEJ;AAAA,qCACP;AAAA,2BACV,4BAA4B;AAAA;AAAA,4CAEX;AAAA,4CACA;AAAA;AAAA;AAAA,qCAGP;AAAA,qCACA;AAAA;AAAA;AAAA,2BAGV,4BAA4B;AAAA;AAAA,4CAEX;AAAA,4CACA;AAAA,4CACA;AAAA;AAAA;AAAA,qCAGP;AAAA,qCACA;AAAA,qCACA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAUnC;AACF;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,aAAa,UAAU;AACjC,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,iBAAiB;AAAA,MACpB,EAAE,MAAM,cAAc,MAAM,QAAQ;AAAA,MACpC,EAAE,MAAM,OAAO,MAAM,QAAQ;AAAA,MAC7B,EAAE,MAAM,UAAU,MAAM,QAAQ;AAAA,MAChC,EAAE,MAAM,YAAY,MAAM,QAAQ;AAAA,MAClC,EAAE,MAAM,cAAc,MAAM,MAAM;AAAA,MAClC,EAAE,MAAM,oBAAoB,MAAM,MAAM;AAAA,MACxC,EAAE,MAAM,YAAY,MAAM,MAAM;AAAA,IAClC;AACA,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,UAAM,EAAE,WAAW,IAAI;AACvB,UAAM,OAAO,mBAAmB;AAChC,UAAM,iBAAiB,eAAe;AACtC,UAAM,SAAS,iBAAiB,IAAI;AACpC,UAAM,SAAS,iBAAiB,IAAI;AACpC,UAAM,wBAAwB,KAAK,sBAAsB,wDAAwD,mBAAmB,YAAY,eAAe,YAAY;AAC3K,QAAI,WAAW;AACf,aAAS,MAAM,GAAG,OAAO,GAAG,OAAO;AACjC,eAAS,MAAM,GAAG,OAAO,GAAG,OAAO;AACjC,oBAAY;AAAA,gCACY;AAAA,yBACP;AAAA;AAAA,YAEb;AAAA;AAAA;AAAA;AAAA,iCAIqB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,mCAQE;AAAA;AAAA;AAAA;AAAA,sBAIb;AAAA;AAAA,2BAEK,MAAM,IAAI;AAAA;AAAA;AAAA;AAAA;AAAA,2BAKV,MAAM,IAAI;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,MAQ/B;AAAA,IACF;AACA,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UASV;AAAA;AAAA,UAEA,KAAK;AAAA;AAAA;AAAA,EAGb;AACF;AAGA,SAAS,uBAAuB,OAAO,gBAAgB;AACrD,QAAM,SAAS,MAAM;AACrB,MAAI,UAAU,GAAG;AACf,WAAO,iBAAiB;AAAA,MACtB,GAAG,MAAM,MAAM,GAAG,EAAE;AAAA,MACpB,MAAM,SAAS,KAAK,MAAM,SAAS;AAAA,MACnC,MAAM,SAAS;AAAA,IACjB,IAAI;AAAA,MACF,GAAG,MAAM,MAAM,GAAG,EAAE;AAAA,MACpB,MAAM,SAAS;AAAA,MACf,MAAM,SAAS,KAAK,MAAM,SAAS;AAAA,IACrC;AAAA,EACF,WAAW,CAAC,kBAAkB,WAAW,KAAK,MAAM,KAAK,GAAG;AAC1D,WAAO,CAAC,MAAM,IAAI,CAAC;AAAA,EACrB,OAAO;AACL,WAAO;AAAA,EACT;AACF;AACA,SAAS,eAAe,EAAE,GAAG,QAAQ,UAAU,SAAS,UAAU,OAAO,MAAM,yBAAyB,MAAM,iBAAiB,GAAG,YAAY,cAAc,KAAK,GAAG;AAClK,QAAM,SAAS,EAAE;AACjB,QAAM,WAAW,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC9C,QAAM,kBAAkB,SAAS;AACjC,QAAM,cAAc,OAAO,KAAK,OAAO,KAAK,OAAO;AACnD,QAAM,mBAAmB,SAAS;AAClC,QAAM,iBAAiB,SAAS,eAAe;AAC/C,QAAM,aAAa;AACnB,QAAM,aAAa;AACnB,MAAI;AACJ,QAAM,gBAAgB,CAAC;AACvB,MAAI,0BAA0B,MAAM;AAClC,UAAM,cAAc,uBAAuB,uBAAuB,OAAO,cAAc;AACvF,QAAI,eAAe,MAAM;AACvB,+BAAyB,SAAS;AAAA,QAChC,QAAQ,EAAE,GAAG,uBAAuB;AAAA,QACpC,SAAS;AAAA,QACT,OAAO,EAAE,OAAO,YAAY;AAAA,MAC9B,CAAC;AACD,oBAAc,KAAK,sBAAsB;AAAA,IAC3C;AAAA,EACF;AACA,MAAI,QAAQ,MAAM;AAChB,UAAM,cAAc,uBAAuB,KAAK,OAAO,cAAc;AACrE,QAAI,eAAe,MAAM;AACvB,aAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,KAAK,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AACzF,oBAAc,KAAK,IAAI;AAAA,IACzB;AAAA,EACF;AACA,QAAM,6BAA6B,gBAAgB,KAAK,qBAAqB,MAAM,kBAAkB;AACrG,QAAM,cAAc,CAAC,6BAA6B,SAAS,YAAY,kBAAkB,SAAS,WAAW,QAAQ,OAAO,KAAK,MAAM,KAAK,aAAa,YAAY,SAAS,MAAM,MAAM,EAAE,GAAG,OAAO,MAAM,EAAE,CAAC;AAC/M,MAAI,aAAa;AACf,UAAM,cAAc,OAAO,KAAK,OAAO,MAAM,OAAO,KAAK;AACzD,UAAM,YAAY;AAAA,MAChB,QAAQ,EAAE;AAAA,MACV,OAAO,CAAC,GAAG,aAAa,SAAS,UAAU;AAAA,MAC3C,OAAO,EAAE;AAAA,IACX;AACA,UAAM,wBAAwB,SAAS;AACvC,aAAS,QAAQ,SAAS,MAAM,MAAM;AACtC,aAAS,MAAM,SAAS,MAAM,SAAS;AACvC,iBAAa,OAAO,cAAc,SAAS,OAAO,UAAU,KAAK,GAAG,MAAM,kBAAkB,SAAS,YAAY,UAAU,kBAAkB;AAC7I,UAAM,iBAAiB,SAAS;AAAA,MAC9B,QAAQ,EAAE,GAAG,OAAO;AAAA,MACpB,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,CAAC,GAAG,SAAS,YAAY,SAAS,WAAW,EAAE;AAAA,IACjE,CAAC;AACD,kBAAc,KAAK,cAAc;AACjC,UAAM,gBAAgB,gBAAgB;AAAA,MACpC,GAAG;AAAA,MACH,GAAG;AAAA,MACH,SAAS;AAAA,MACT;AAAA,MACA;AAAA,MACA;AAAA,MACA,YAAY;AAAA,MACZ;AAAA,MACA;AAAA,IACF,CAAC;AACD,UAAM,uBAAuB,SAAS,QAAQ,IAAI,cAAc,MAAM;AACtE,iBAAa,OAAO,qBAAqB,UAAU,MAAM,6CAA6C;AACtG,aAAS,QAAQ;AACjB,yBAAqB,QAAQ,SAAS;AACtC,UAAM,UAAU,EAAE,QAAQ,EAAE,GAAG,cAAc,GAAG,SAAS,SAAS,CAAC;AACnE,QAAI,QAAQ,SAAS;AACrB,kBAAc,KAAK,aAAa;AAAA,EAClC,OAAO;AACL,UAAM,UAAU,SAAS,YAAY,SAAS;AAC9C,UAAM,YAAY,SAAS;AAAA,MACzB,QAAQ,EAAE,EAAE;AAAA,MACZ,SAAS;AAAA,MACT,OAAO;AAAA,QACL,OAAO,iBAAiB,CAAC,SAAS,WAAW,SAAS,SAAS,UAAU,IAAI,CAAC,SAAS,WAAW,SAAS,YAAY,OAAO;AAAA,MAChI;AAAA,IACF,CAAC;AACD,UAAM,iBAAiB,SAAS;AAAA,MAC9B,QAAQ,EAAE,GAAG,OAAO;AAAA,MACpB,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,CAAC,GAAG,SAAS,YAAY,SAAS,WAAW,EAAE;AAAA,IACjE,CAAC;AACD,UAAM,SAAS,gBAAgB;AAAA,MAC7B,GAAG,iBAAiB,YAAY;AAAA,MAChC,GAAG,iBAAiB,iBAAiB;AAAA,MACrC,YAAY,CAAC;AAAA,MACb;AAAA,MACA,SAAS;AAAA,MACT;AAAA,MACA,YAAY;AAAA,MACZ;AAAA,MACA;AAAA,IACF,CAAC;AACD,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,SAAS,EAAE,CAAC;AAChG,kBAAc,KAAK,SAAS;AAC5B,kBAAc,KAAK,cAAc;AACjC,kBAAc,KAAK,MAAM;AAAA,EAC3B;AACA,aAAW,MAAM,eAAe;AAC9B,aAAS,8BAA8B,EAAE;AAAA,EAC3C;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,EAAE,GAAG,QAAQ,UAAU,SAAS,UAAU,OAAO,MAAM,yBAAyB,MAAM,iBAAiB,GAAG,YAAY,cAAc,KAAK,GAAG;AACpK,QAAM,EAAE,aAAa,cAAc,YAAY,UAAU,WAAW,WAAW,IAAI;AACnF,QAAM,iBAAiB,eAAe;AACtC,QAAM,YAAY,cAAc,eAAe;AAC/C,QAAM,UAAU,YAAY;AAC5B,QAAM,aAAa,CAAC,SAAS,WAAW,WAAW,OAAO;AAC1D,QAAM,aAAa;AACnB,QAAM,aAAa;AACnB,QAAM,gBAAgB,CAAC;AACvB,MAAI,0BAA0B,MAAM;AAClC,UAAM,cAAc,uBAAuB,uBAAuB,OAAO,cAAc;AACvF,QAAI,eAAe,MAAM;AACvB,+BAAyB,SAAS;AAAA,QAChC,QAAQ,EAAE,GAAG,uBAAuB;AAAA,QACpC,SAAS;AAAA,QACT,OAAO,EAAE,OAAO,YAAY;AAAA,MAC9B,CAAC;AACD,oBAAc,KAAK,sBAAsB;AAAA,IAC3C;AAAA,EACF;AACA,MAAI,QAAQ,MAAM;AAChB,UAAM,cAAc,uBAAuB,KAAK,OAAO,cAAc;AACrE,QAAI,eAAe,MAAM;AACvB,aAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,KAAK,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AACzF,oBAAc,KAAK,IAAI;AAAA,IACzB;AAAA,EACF;AACA,QAAM,QAAQ,SAAS;AAAA,IACrB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,GAAG,WAAW,aAAa,cAAc,OAAO,KAAK,IAAI,SAAS,EAAE;AAAA,EACvF,CAAC;AACD,gBAAc,KAAK,KAAK;AACxB,QAAM,gBAAgB,IAAI,oBAAoB,YAAY,QAAQ;AAClE,QAAM,eAAe;AAAA,IACnB,EAAE;AAAA,IACF,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI;AAAA,IAC5C,CAAC,SAAS,cAAc,SAAS,WAAW;AAAA,IAC5C,CAAC,SAAS,gBAAgB,SAAS,aAAa;AAAA,IAChD,CAAC,SAAS,UAAU;AAAA,IACpB,CAAC,SAAS,cAAc,SAAS,UAAU;AAAA,IAC3C,CAAC,SAAS,QAAQ;AAAA,EACpB;AACA,QAAM,SAAS,SAAS,gBAAgB,eAAe,CAAC,CAAC,GAAG,WAAW,YAAY;AACnF,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAC1G,gBAAc,KAAK,MAAM;AACzB,gBAAc,KAAK,cAAc;AACjC,QAAM,UAAU,QAAQ;AACxB,QAAM,4BAA4B,0BAA0B;AAC5D,QAAM,oBAAoB,gBAAgB;AAC1C,QAAM,kBAAkB,cAAc,6BAA6B,aAAa,IAAI,IAAI;AACxF,QAAM,gBAAgB,IAAI,oBAAoB,iBAAiB,eAAe,QAAQ,MAAM,OAAO,iBAAiB,MAAM,QAAQ,eAAe,OAAO,iBAAiB,CAAC,SAAS,WAAW,SAAS,SAAS,WAAW,IAAI,CAAC,SAAS,WAAW,SAAS,aAAa,OAAO,GAAG,YAAY,YAAY,SAAS,iBAAiB,2BAA2B,iBAAiB;AAClX,QAAM,SAAS,iBAAiB,CAAC,gBAAgB,KAAK,IAAI,CAAC,OAAO,cAAc;AAChF,MAAI,MAAM;AACR,WAAO,KAAK,IAAI;AAAA,EAClB;AACA,MAAI,2BAA2B;AAC7B,WAAO,KAAK,sBAAsB;AAAA,EACpC;AACA,MAAI,mBAAmB;AACrB,UAAM,kBAAkB,SAAS,eAAe,CAAC,GAAG,WAAW,aAAa,kBAAkB,gBAAgB,SAAS,CAAC;AACxH,WAAO,KAAK,eAAe;AAC3B,kBAAc,KAAK,eAAe;AAAA,EACpC;AACA,QAAM,UAAU,SAAS,gBAAgB,eAAe,QAAQ,SAAS;AACzE,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,SAAS,EAAE,CAAC;AACvG,gBAAc,KAAK,OAAO;AAC1B,aAAW,MAAM,eAAe;AAC9B,aAAS,8BAA8B,EAAE;AAAA,EAC3C;AACA,SAAO;AACT;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAY,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB,IAAI;AACvE,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,OAAO,WAAW;AAC5I,MAAI;AACJ,MAAI,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,KAAK,SAAS,mBAAmB,KAAK,SAAS,kBAAkB,KAAK,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,MAAM,SAAS,QAAQ,SAAS,UAAU,SAAS,QAAQ,SAAS,UAAU;AACtQ,UAAM,eAAe,EAAE,GAAG,QAAQ,UAAU,SAAS,SAAS,CAAC;AAAA,EACjE,WAAW,IAAI,EAAE,QAAQ,mBAAmB,GAAG;AAC7C,UAAM,iBAAiB,EAAE,GAAG,QAAQ,UAAU,SAAS,SAAS,CAAC;AAAA,EACnE,OAAO;AACL,UAAM,UAAU,IAAI,cAAc,QAAQ;AAC1C,UAAM,SAAS,gBAAgB,SAAS,CAAC,GAAG,MAAM,GAAG,SAAS;AAAA,EAChE;AACA,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,SAAS,EAAE,CAAC;AAC3G,WAAS,8BAA8B,GAAG;AAC1C,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,KAAK,IAAI;AAC/B,SAAK,cAAc,SAAS;AAC5B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,SAAS,SAAS,QAAQ;AAChC,UAAM,UAAU,SAAS,QAAQ;AACjC,UAAM,iBAAiB,SAAS,eAAe;AAC/C,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAYU,SAAS;AAAA,kCACL,SAAS;AAAA,iCACV,kBAAkB;AAAA;AAAA,kCAEjB,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP,SAAS;AAAA,mCACV,iBAAiB;AAAA;AAAA,oCAEhB,SAAS;AAAA;AAAA;AAAA;AAAA,oBAIzB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAgBlB;AACF;AACA,IAAI,wBAAwB,MAAM;AAAA,EAChC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,MAAM,GAAG;AAC/B,SAAK,cAAc,SAAS;AAC5B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,iBAAiB,SAAS,eAAe;AAC/C,UAAM,SAAS,eAAe,IAAI,SAAS,QAAQ;AACnD,UAAM,UAAU,cAAc,IAAI,SAAS,QAAQ;AACnD,UAAM,SAAS,iBAAiB,IAAI;AACpC,UAAM,SAAS,iBAAiB,IAAI;AACpC,UAAM,aAAa,iBAAiB,IAAI;AACxC,SAAK,WAAW;AAAA,iCACa,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,0BAKlB;AAAA;AAAA,wCAEc,mBAAmB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAO3B;AAAA,gDACgB;AAAA;AAAA,oCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA,yBAKpB;AAAA;AAAA,kCAES;AAAA,kDACgB;AAAA;AAAA,sCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,2BAMpB;AAAA;AAAA,oCAES,SAAS;AAAA;AAAA,oBAEzB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAgBlB;AACF;AACA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,KAAK,IAAI;AAC/B,SAAK,cAAc,SAAS;AAC5B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,WAAW,SAAS,QAAQ;AAClC,UAAM,SAAS,SAAS,QAAQ;AAChC,UAAM,UAAU,SAAS,QAAQ;AACjC,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAWU,SAAS;AAAA,kCACL,SAAS;AAAA,iCACV,iBAAiB;AAAA;AAAA,kCAEhB,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP,SAAS;AAAA,mCACV,kBAAkB;AAAA;AAAA,oCAEjB,SAAS;AAAA;AAAA;AAAA;AAAA,sCAIP,SAAS;AAAA,qCACV,iBAAiB;AAAA;AAAA,sCAEhB,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAc7C;AACF;AACA,IAAI,wBAAwB,MAAM;AAAA,EAChC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,MAAM,GAAG;AAC/B,SAAK,cAAc,SAAS;AAC5B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,WAAW,cAAc,IAAI,SAAS,QAAQ;AACpD,UAAM,SAAS,eAAe,IAAI,SAAS,QAAQ;AACnD,UAAM,UAAU,cAAc,IAAI,SAAS,QAAQ;AACnD,SAAK,WAAW;AAAA,iCACa,aAAa,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAczB;AAAA,gDACgB;AAAA;AAAA,oCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA,yBAKpB;AAAA;AAAA,kCAES;AAAA,kDACgB;AAAA;AAAA,sCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,2BAMpB;AAAA;AAAA,oCAES;AAAA,oDACgB;AAAA;AAAA,wCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,6BAMpB;AAAA;AAAA,sCAES,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAW7C;AACF;AAGA,SAAS,sBAAsB,MAAM;AACnC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,IAAI;AAClB,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,iBAAiB,YAAY,IAAI;AACzE,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,aAAaA,UAAS,GAAG,MAAM,iBAAiB,OAAO,WAAW;AACnI,QAAM,UAAU,IAAI,uBAAuB,QAAQ;AACnD,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,EAAE,GAAG,SAAS;AAC7D;AACA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,YAAY,gBAAgB,IAAI;AACxE,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,GAAG,MAAM,iBAAiB,OAAO,WAAW;AACvI,QAAM,UAAU,IAAI,sBAAsB,QAAQ;AAClD,SAAO,SAAS,gBAAgB,SAAS,CAAC,IAAI,MAAM,GAAG,SAAS;AAClE;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,UAAU,IAAI;AAC1C,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,IAAI;AACvG,QAAM,UAAU,IAAI,cAAc,QAAQ;AAC1C,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,MAAM,GAAG,SAAS;AACjE;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,wBAAwB,MAAM;AACrC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,IAAI;AAClB,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,IAAI;AAC5C,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,aAAaA,UAAS,GAAG,IAAI;AAC9F,QAAM,UAAU,IAAI,uBAAuB,QAAQ;AACnD,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,EAAE,GAAG,SAAS;AAC7D;AACA,IAAI,gCAAgC;AAAA,EAClC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,KAAK,MAAM,SAAAA,UAAS,WAAW,IAAI;AAC3C,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,GAAG,IAAI;AAClG,QAAM,UAAU,IAAI,sBAAsB,QAAQ;AAClD,SAAO,SAAS,gBAAgB,SAAS,CAAC,IAAI,MAAM,GAAG,SAAS;AAClE;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM,0BAA0B;AAAA;AAAA;AAGpC,IAAI,OAAO,iBAAiB,EAAE,WAAW,IAAI,CAAC;AAC9C,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AAAA;AAAA;AAAA;AAIX,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,YAAY,UAAU,UAAU,QAAQ,oBAAoB;AACtE,SAAK,gBAAgB,CAAC,SAAS,SAAS,QAAQ;AAChD,SAAK,cAAc,CAAC;AACpB,UAAM,CAAC,OAAO,aAAa,YAAY,KAAK,IAAI;AAChD,UAAM,CAAC,QAAQ,IAAI;AACnB,UAAM,CAAC,YAAY,SAAS,IAAI;AAChC,SAAK,cAAc,CAAC,UAAU,YAAY,WAAW,KAAK;AAC1D,UAAM,WAAW,WAAW,aAAa,IAAI;AAC7C,UAAM,CAAC,kBAAkB,eAAe,IAAI,CAAC,GAAG,cAAc,OAAO,GAAG,aAAa,KAAK;AAC1F,UAAM,CAAC,aAAa,aAAa,GAAG,IAAI,aAAa,IAAI;AAAA,MACvD,IAAI,cAAc,MAAM,aAAa;AAAA,MACrC;AAAA,MACA,MAAM;AAAA,IACR,IAAI;AAAA,MACF;AAAA,MACA;AAAA,MACA,mBAAmB;AAAA,IACrB;AACA,UAAM,CAAC,YAAY,YAAY,GAAG,IAAI,YAAY,IAAI;AAAA,MACpD,IAAI,aAAa,MAAM,YAAY;AAAA,MACnC;AAAA,MACA,MAAM;AAAA,IACR,IAAI;AAAA,MACF;AAAA,MACA;AAAA,MACA,mBAAmB;AAAA,IACrB;AACA,SAAK,WAAW;AAAA,yCACqB;AAAA,wCACD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,iCAgBP;AAAA;AAAA;AAAA;AAAA,+BAIF;AAAA,8BACD;AAAA;AAAA,uBAEP;AAAA,mCACY;AAAA,4BACP;AAAA;AAAA;AAAA,uBAGL;AAAA,mCACY;AAAA,4BACP;AAAA;AAAA;AAAA;AAAA;AAAA,aAKf;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAyBX;AACF;AAGA,IAAI,iBAAiB,CAAC,SAAS;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,OAAO,OAAO,IAAI;AACzC,QAAM,EAAE,UAAU,QAAQ,mBAAmB,IAAI;AACjD,QAAM,UAAU,IAAI,qBAAqB,OAAO,OAAO,MAAM,OAAO,UAAU,QAAQ,kBAAkB;AACxG,SAAO,SAAS,gBAAgB,SAAS,CAAC,QAAQ,OAAO,MAAM,GAAG,SAAS;AAC7E;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AAAA,CACH,SAAS,YAAY;AACpB,aAAW,UAAU;AACrB,aAAW,SAAS;AACtB,GAAG,cAAc,YAAY,CAAC,EAAE;AAChC,IAAI,aAAa,MAAM;AAAA,EACrB,YAAY,KAAK,aAAa,WAAW,UAAU;AACjD,SAAK,KAAK;AACV,SAAK,cAAc;AACnB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,iBAAiB,CAAC,EAAE,MAAM,SAAS,MAAM,QAAQ,CAAC;AACvD,UAAM,OAAO,KAAK,YAAY;AAC9B,UAAM,UAAU,KAAK,OAAO,UAAU,OAAO,QAAQ;AACrD,UAAM,MAAM,YAAY,UAAU,QAAQ,WAAW,MAAM,UAAU,KAAK,EAAE;AAC5E,UAAM,SAAS,KAAK,YAAY,KAAK,YAAY,SAAS;AAC1D,QAAI,YAAY;AAChB,QAAI,YAAY;AAChB,QAAI,WAAW;AACb,kBAAY,WAAW,UAAU,SAAS,MAAM;AAChD,kBAAY,WAAW,YAAY;AAAA,IACrC,OAAO;AACL,kBAAY,WAAW,gBAAgB,WAAW;AAClD,kBAAY,WAAW,eAAe;AAAA,IACxC;AACA,SAAK,WAAW;AAAA;AAAA,UAEV,kBAAkB,IAAI;AAAA,oBACZ,cAAc,MAAM,UAAU,KAAK,EAAE;AAAA,sBACnC;AAAA;AAAA,cAER;AAAA,sBACQ;AAAA,YACV,cAAc,MAAM,UAAU,KAAK,EAAE;AAAA,gBACjC,KAAK,YAAY,WAAW,MAAM,UAAU,KAAK,EAAE;AAAA;AAAA;AAAA;AAAA;AAAA,EAKjE;AACF;AACA,SAAS,WAAW,MAAM,MAAM,KAAK;AACnC,MAAI,SAAS,GAAG;AACd,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG,WAAW;AAAA,EACvB,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG,WAAW,WAAW;AAAA,EAClC,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG,WAAW,WAAW,WAAW;AAAA,EAC7C,OAAO;AACL,UAAM,IAAI,MAAM,cAAc,gBAAgB,2BAA2B;AAAA,EAC3E;AACF;AACA,SAAS,cAAc,MAAM,MAAM,KAAK;AACtC,MAAI,SAAS,GAAG;AACd,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG;AAAA,EACZ,OAAO;AACL,UAAM,IAAI,MAAM,cAAc,gBAAgB,2BAA2B;AAAA,EAC3E;AACF;AAGA,SAAS,QAAQ,KAAK,GAAG,UAAU,MAAM,WAAW,UAAU;AAC5D,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,cAAc,qBAAqB,mBAAmB,CAAC,IAAI,GAAG,KAAK;AACzE,MAAI,YAAY;AAChB,MAAI,eAAe,MAAM;AACvB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,YAAY,EAAE,CAAC;AAAA,EAC3F;AACA,QAAM,eAAe,qBAAqB,iBAAiB,GAAG,KAAK,EAAE;AACrE,MAAI,iBAAiB,QAAQ,GAAG;AAC9B,UAAM,IAAI,MAAM,mDAAmD,EAAE,MAAM,SAAS,kBAAkB,MAAM;AAAA,EAC9G;AACA,QAAMZ,QAAO,UAAU,MAAM;AAC7B,MAAI,SAAS,UAAU,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,SAAS,CAAC;AACtE,WAAS,KAAK,GAAG,MAAM,KAAK,KAAK,KAAK,KAAKA,KAAI,CAAC,IAAI,GAAG,MAAM;AAC3D,UAAM,UAAU,IAAI,WAAW,KAAK,UAAU,OAAO,OAAO,QAAQ;AACpE,UAAM,eAAe,CAAC,CAAC,EAAE,CAAC;AAC1B,UAAM,aAAa;AACnB,aAAS,SAAS,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO,OAAO,YAAY;AAC/E,aAAS,8BAA8B,UAAU;AAAA,EACnD;AACA,MAAI,WAAW;AACb,UAAM,UAAU,IAAI,WAAW,KAAK,UAAU,OAAO,WAAW,QAAQ;AACxE,UAAM,aAAa;AACnB,aAAS,SAAS,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO,KAAK;AACjE,aAAS,8BAA8B,UAAU;AAAA,EACnD;AACA,MAAI,eAAe,MAAM;AACvB,UAAM,qBAAqB,qBAAqB,uBAAuB,WAAW;AAClF,UAAM,0BAA0B,WAAW,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,mBAAmB,EAAE,CAAC;AAC5H,aAAS,8BAA8B,MAAM;AAC7C,aAAS,8BAA8B,SAAS;AAChD,WAAO;AAAA,EACT;AACA,SAAO;AACT;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,SAAO,QAAQ,UAAU,MAAM,GAAG,UAAU,MAAM,WAAW,QAAQ;AACvE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,SAAO,QAAQ,UAAU,KAAK,GAAG,UAAU,MAAM,WAAW,QAAQ;AACtE;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAAA,OAAM,aAAa,IAAI;AAC/B,MAAI,EAAE,MAAM,WAAW,GAAG;AACxB,UAAM,QAAQ,SAAS,SAAS,EAAE,MAAM;AACxC,UAAM,cAAc,SAAS,SAAS,QAAQ,MAAM;AACpD,UAAM,UAAU,gBAAgB,OAAO,aAAa,QAAQ,OAAO,QAAQ,OAAOA,KAAI;AACtF,WAAO,SAAS,eAAe,CAACA,KAAI,GAAG,QAAQ,OAAO,OAAO;AAAA,EAC/D,WAAW,EAAE,MAAM,WAAW,GAAG;AAC/B,UAAM,OAAO,SAAS,WAAW,CAAC;AAClC,UAAM,aAAa,SAAS,WAAW,OAAO;AAC9C,UAAM,SAAS,sBAAsB,MAAM,YAAYA,OAAM,YAAY;AACzE,WAAO,SAAS,eAAe,OAAO,OAAO,QAAQ,OAAO,OAAO,MAAM;AAAA,EAC3E;AACA,QAAM,IAAI,MAAM,qEAAqE,EAAE,MAAM,SAAS;AACxG;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,aAAa,WAAW,YAAY;AAC9C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc;AACnB,SAAK,YAAY;AACjB,SAAK,aAAa;AAClB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA,gBAIJ,KAAK,qBAAqB;AAAA,gBAC1B,KAAK,oBAAoB;AAAA,gBACzB,KAAK,oBAAoB;AAAA;AAAA,uBAElB;AAAA,+BACQ;AAAA,uBACR;AAAA,+BACQ;AAAA,mCACI;AAAA,UACzB,KAAK,mBAAmB;AAAA;AAAA;AAAA,uBAGX,KAAK,uBAAuB;AAAA;AAAA;AAAA;AAAA,EAIjD;AAAA,EACA,uBAAuB;AACrB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,sBAAsB;AACpB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,sBAAsB;AACpB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,qBAAqB;AACnB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO,KAAK,YAAY;AAAA,IAC1B,OAAO;AACL,aAAO,KAAK,YAAY;AAAA,IAC1B;AAAA,EACF;AAAA,EACA,yBAAyB;AACvB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AACF;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,WAAW,WAAW,IAAI;AAClC,QAAM,YAAY,EAAE,MAAM;AAC1B,QAAM,cAAc,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AACjE,QAAM,aAAa,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AAChE,QAAM,aAAa,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AAChE,QAAM,eAAe,cAAc;AACnC,QAAM,cAAc,aAAa;AACjC,QAAM,cAAc,cAAc,YAAY;AAC9C,QAAM,cAAc,eAAe,SAAS,CAAC,WAAW,cAAc,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,cAAc,WAAW;AACpJ,QAAM,UAAU,IAAI,oBAAoB,aAAa,WAAW,UAAU;AAC1E,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACvD;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,UAAU,UAAU,OAAO,cAAc,MAAM,qBAAqB,OAAO,oBAAoB,OAAO;AAChH,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,iBAAiB;AAAA,MACpB,EAAE,MAAM,QAAQ,MAAM,QAAQ;AAAA,MAC9B,EAAE,MAAM,WAAW,MAAM,QAAQ;AAAA,MACjC,EAAE,MAAM,aAAa,MAAM,QAAQ;AAAA,MACnC,EAAE,MAAM,UAAU,MAAM,QAAQ;AAAA,IAClC;AACA,SAAK,cAAc,SAAS;AAC5B,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,aAAa,SAAS,cAAc,SAAS;AACnD,QAAI,oBAAoB,IAAI,yBAAyB;AACrD,QAAI,aAAa;AACf,UAAI,oBAAoB;AACtB,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,WAAW,mBAAmB;AAC5B,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,OAAO;AACL,4BAAoB;AAAA;AAAA,cAEd;AAAA;AAAA;AAAA,MAGR;AACA,+BAAyB;AAAA,IAC3B;AACA,UAAM,iBAAiB,UAAU,oCAAoC;AACrE,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,oBAAoB;AACtB,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,QAAI,mBAAmB;AACrB,WAAK,cAAc,KAAK,gBAAgB;AAAA,IAC1C;AACA,SAAK,WAAW;AAAA,QACZ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,wBAOgB;AAAA,4BACI;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCASI;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAOE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAcxB;AAAA,UACA;AAAA;AAAA;AAAA;AAAA,EAIR;AACF;AAGA,IAAI,+BAA+B,MAAM;AAAA,EACvC,YAAY,UAAU,UAAU,OAAO,cAAc,MAAM,qBAAqB,OAAO,oBAAoB,OAAO;AAChH,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,iBAAiB;AAAA,MACpB,EAAE,MAAM,QAAQ,MAAM,QAAQ;AAAA,MAC9B,EAAE,MAAM,WAAW,MAAM,QAAQ;AAAA,MACjC,EAAE,MAAM,aAAa,MAAM,QAAQ;AAAA,MACnC,EAAE,MAAM,UAAU,MAAM,QAAQ;AAAA,IAClC;AACA,SAAK,cAAc,SAAS;AAC5B,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,UAAM,aAAa,SAAS,cAAc,SAAS;AACnD,UAAM,UAAU,SAAS,QAAQ;AACjC,UAAM,cAAc,SAAS;AAC7B,UAAM,gBAAgB,SAAS;AAC/B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe;AACrB,QAAI,WAAW;AAAA;AAAA;AAGf,aAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,kBAAY;AAAA,wBACM,IAAI;AAAA,uBACL,IAAI;AAAA,wBACH,IAAI,IAAI;AAAA,uBACT,IAAI,IAAI;AAAA,mBACZ;AAAA,IACf;AACA,gBAAY;AAAA,0BACU;AAAA;AAEtB,aAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,kBAAY;AAAA,mBACC,IAAI;AAAA,mBACJ,IAAI;AAAA,mBACJ,IAAI,IAAI;AAAA,mBACR,IAAI,IAAI;AAAA,cACb;AAAA,IACV;AACA,gBAAY;AAAA;AAAA;AAAA;AAIZ,aAAS,SAAS,GAAG,UAAU,eAAe,KAAK,GAAG,UAAU;AAC9D,YAAM,WAAW,SAAS;AAC1B,kBAAY;AAAA,4BACU,WAAW;AAAA;AAEjC,UAAI,gBAAgB,GAAG;AACrB,YAAI,WAAW,aAAa;AAC1B,cAAI,UAAU,MAAM,GAAG;AACrB,wBAAY;AAAA;AAAA,sEAE8C;AAAA,2BAC3C;AAAA;AAAA;AAAA;AAAA;AAAA,6BAKE;AAAA;AAAA,2BAEF;AAAA;AAAA;AAGf,gBAAI,kBAAkB,KAAK,WAAW,GAAG;AACvC,0BAAY;AAAA,oBACN,0BAA0B,WAAW,gBAAgB;AAAA;AAAA,YAE7D,OAAO;AACL,0BAAY;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,wBAYF,uCAAuC;AAAA;AAAA,wBAEvC,oCAAoC;AAAA;AAAA;AAAA,YAGhD;AAAA,UACF,OAAO;AACL,wBAAY;AAAA,0DACkC;AAAA,2BAC/B;AAAA;AAAA,6BAEE;AAAA;AAAA,2BAEF;AAAA;AAAA;AAAA,oBAGP,qBAAqB;AAAA;AAAA,UAE/B;AACA,cAAI,WAAW,IAAI,aAAa;AAC9B,kBAAM,kBAAkB,UAAU,MAAM,IAAI,aAAa,kBAAkB,aAAa,IAAI;AAC5F,gBAAI,gBAAgB,MAAM,KAAK,UAAU,MAAM,KAAK,gBAAgB,MAAM,KAAK,UAAU,MAAM,GAAG;AAChG,0BAAY;AAAA,uDAC6B;AAAA;AAAA,wEAEiB,WAAW;AAAA,6BACtD,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,+BAKT,WAAW;AAAA;AAAA,6BAEb,WAAW;AAAA;AAAA;AAG1B,kBAAI,gBAAgB,GAAG;AACrB,4BAAY;AAAA;AAAA,0EAE8C;AAAA,+BAC3C;AAAA,+BACA;AAAA;AAAA;AAAA,cAGjB;AACA,0BAAY;AAAA,sBACJ,WAAW,mBAAmB,uBAAuB,WAAW;AAAA;AAAA,YAE1E,OAAO;AACL,kBAAI,oBAAoB,GAAG;AACzB,4BAAY;AAAA,wBACJ,WAAW,cAAc;AAAA;AAAA,cAEnC,OAAO;AACL,4BAAY;AAAA,sCACU;AAAA;AAAA,0EAEoC,WAAW;AAAA,+BACtD,WAAW;AAAA;AAAA,iCAET,WAAW;AAAA;AAAA,+BAEb,WAAW;AAAA;AAAA;AAAA,wBAGlB,WAAW,cAAc,WAAW;AAAA;AAAA,cAE9C;AAAA,YACF;AAAA,UACF;AAAA,QACF;AAAA,MACF,OAAO;AACL,YAAI,WAAW,aAAa;AAC1B,cAAI,UAAU,MAAM,GAAG;AACrB,wBAAY;AAAA;AAAA,qEAE6C;AAAA,2BAC1C;AAAA;AAAA;AAAA;AAAA,6BAIE;AAAA;AAAA,2BAEF;AAAA;AAAA;AAAA,iEAGsC,WAAW;AAAA,2BACjD,WAAW;AAAA;AAAA;AAAA;AAAA,6BAIT,WAAW;AAAA;AAAA,2BAEb,WAAW;AAAA;AAAA;AAAA,oBAGlB,0BAA0B,uBAAuB,WAAW;AAAA;AAEpE,gBAAI,WAAW,IAAI,aAAa;AAC9B,0BAAY;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,sBAMJ,WAAW,mBAAmB,WAAW;AAAA;AAAA,YAEnD;AAAA,UACF,OAAO;AACL,wBAAY;AAAA,yDACiC;AAAA,2BAC9B;AAAA;AAAA,6BAEE;AAAA;AAAA,2BAEF;AAAA;AAAA;AAAA;AAAA,qEAI0C,WAAW;AAAA,2BACrD,WAAW;AAAA;AAAA,6BAET,WAAW;AAAA;AAAA,2BAEb,WAAW;AAAA;AAAA;AAAA,oBAGlB;AAAA,2BACO,uBAAuB,WAAW;AAAA;AAEjD,gBAAI,WAAW,IAAI,aAAa;AAC9B,0BAAY;AAAA,sBACJ,WAAW,mBAAmB,uBAAuB,WAAW;AAAA;AAAA,YAE1E;AAAA,UACF;AAAA,QACF;AAAA,MACF;AACA,UAAI,WAAW,aAAa;AAC1B,oBAAY;AAAA,+BACW;AAAA,2BACJ;AAAA;AAEnB,YAAI,WAAW,IAAI,aAAa;AAC9B,sBAAY;AAAA,iCACW,WAAW;AAAA,6BACf,WAAW;AAAA;AAAA,QAEhC;AAAA,MACF;AAAA,IACF;AACA,gBAAY;AAAA;AAAA;AAGZ,gBAAY;AAAA;AAAA;AAGZ,QAAI,oBAAoB,IAAI,yBAAyB;AACrD,QAAI,aAAa;AACf,UAAI,oBAAoB;AACtB,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,WAAW,mBAAmB;AAC5B,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,OAAO;AACL,4BAAoB;AAAA,YAChB;AAAA;AAAA,MAEN;AACA,+BAAyB;AAAA,IAC3B;AACA,UAAM,iBAAiB,UAAU,oCAAoC;AACrE,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,oBAAoB;AACtB,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,QAAI,mBAAmB;AACrB,WAAK,cAAc,KAAK,gBAAgB;AAAA,IAC1C;AACA,SAAK,WAAW;AAAA,QACZ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,wBAOgB;AAAA,4BACI;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAOlB;AAAA;AAAA;AAAA,UAGA;AAAA,UACA;AAAA;AAAA;AAAA;AAAA,EAIR;AACF;AAGA,SAAS,uBAAuB,MAAM;AACpC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAY,UAAS,KAAK,MAAM,WAAW,gBAAgB,IAAI;AAC3D,MAAI,aAAa;AACjB,MAAI,cAAc,MAAM;AACtB,iBAAa,CAAC,GAAG,CAAC;AAAA,EACpB;AACA,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,UAAU,GAAG,MAAM,gFAAgFA,2BAA0B,aAAa;AAC3N,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,YAAY,MAAM,iBAAiB,IAAI;AAC/H,MAAI;AACJ,MAAI,IAAI,EAAE,QAAQ,0BAA0B,KAAK,SAAS,eAAe,KAAK,SAAS,cAAc,SAAS,eAAe,GAAG;AAC9H,cAAU,IAAI,6BAA6B,QAAQ;AAAA,EACrD,OAAO;AACL,cAAU,IAAI,uBAAuB,QAAQ;AAAA,EAC/C;AACA,QAAM,eAAe;AAAA,IACnB,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI;AAAA,IAC5C,CAAC,SAAS,cAAc,SAAS,WAAW;AAAA,IAC5C,CAAC,SAAS,gBAAgB,SAAS,aAAa;AAAA,IAChD,CAAC,SAAS,UAAU,SAAS,OAAO;AAAA,EACtC;AACA,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,MAAM,GAAG,WAAW,YAAY;AAC/E;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kCAAkC,MAAM;AAAA,EAC1C,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,KAAK,IAAI;AAC/B,SAAK,cAAc,SAAS;AAC5B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,SAAS,SAAS,QAAQ;AAChC,UAAM,UAAU,SAAS,QAAQ;AACjC,UAAM,aAAa,SAAS,cAAc,SAAS;AACnD,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,wBAOI;AAAA;AAAA;AAAA;AAAA;AAAA,8BAKM,SAAS;AAAA,kCACL,SAAS;AAAA,iCACV,kBAAkB;AAAA;AAAA,kCAEjB,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP,SAAS;AAAA,mCACV,iBAAiB;AAAA;AAAA,oCAEhB,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAa3C;AACF;AACA,IAAI,iCAAiC,MAAM;AAAA,EACzC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,MAAM,GAAG;AAC/B,SAAK,cAAc,SAAS;AAC5B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,SAAS,eAAe,IAAI,SAAS,QAAQ;AACnD,UAAM,UAAU,cAAc,IAAI,SAAS,QAAQ;AACnD,UAAM,aAAa,SAAS,cAAc,SAAS;AACnD,SAAK,WAAW;AAAA,iCACa,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAYZ;AAAA,gDACgB;AAAA;AAAA,oCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA,yBAKpB;AAAA;AAAA,kCAES;AAAA,kDACgB;AAAA;AAAA,sCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,2BAMpB;AAAA;AAAA;AAAA,oCAGS;AAAA,8BACN;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAU5B;AACF;AAGA,SAAS,qCAAqC,MAAM;AAClD,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,IAAI;AAClB,QAAM,EAAE,SAAAA,UAAS,WAAW,KAAK,MAAM,iBAAiB,YAAY,IAAI;AACxE,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,aAAaA,UAAS,WAAW,MAAM,iBAAiB,IAAI;AAC7H,QAAM,UAAU,IAAI,gCAAgC,QAAQ;AAC5D,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,EAAE,GAAG,SAAS;AAC7D;AACA,IAAI,6CAA6C;AAAA,EAC/C,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,oCAAoC,MAAM;AACjD,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,SAAAA,UAAS,WAAW,KAAK,MAAM,iBAAiB,WAAW,IAAI;AACvE,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,IAAI;AACjI,QAAM,UAAU,IAAI,+BAA+B,QAAQ;AAC3D,SAAO,SAAS,gBAAgB,SAAS,CAAC,IAAI,MAAM,GAAG,SAAS;AAClE;AACA,IAAI,4CAA4C;AAAA,EAC9C,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAYZ,OAAM;AAChB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,CAACA,OAAMA,KAAI;AAC9B,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAOlB;AACF;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,WAAW,CAAC,GAAG,EAAE,OAAO,GAAG,EAAE,KAAK;AACxC,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,OAAO,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,KAAK,EAAE,EAAE,CAAC;AACrF,QAAM,UAAU,IAAI,YAAY,KAAK;AACrC,QAAM,MAAM,SAAS,gBAAgB,SAAS,CAAC,IAAI,GAAG,KAAK,KAAK;AAChE,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC1F,WAAS,8BAA8B,IAAI;AAC3C,WAAS,8BAA8B,GAAG;AAC1C,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,cAAc,SAAS;AAC5B,UAAM,EAAE,UAAU,SAAS,SAAS,cAAc,aAAa,cAAc,aAAa,gBAAgB,cAAc,IAAI;AAC5H,UAAM,EAAE,KAAK,QAAQ,MAAM,QAAQ,IAAI;AACvC,SAAK,WAAW;AAAA,oCACgB,iBAAiB;AAAA,iCACpB,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAad;AAAA,iCACG;AAAA;AAAA,kCAEC;AAAA,kCACA;AAAA,qCACG;AAAA;AAAA,sCAEC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAiBpC;AACF;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAY,UAAS,KAAK,MAAM,UAAU,IAAI;AAC1C,QAAM,WAAW,qBAAqB,sBAAsB,EAAE,OAAO,OAAO,OAAOA,UAAS,MAAM,QAAQ,SAAS;AACnH,MAAI;AACJ,QAAM,UAAU,IAAI,kBAAkB,QAAQ;AAC9C,QAAM,SAAS,gBAAgB,SAAS,CAAC,GAAG,MAAM,GAAG,SAAS;AAC9D,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,SAAS,EAAE,CAAC;AAC3G,WAAS,8BAA8B,GAAG;AAC1C,SAAO;AACT;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,SAAS,IAAI;AACrB,QAAM,UAAU;AAChB,QAAM,EAAE,SAAS,YAAY,OAAO,IAAI,qBAAqB,qBAAqB,UAAU,QAAQ,MAAM;AAC1G,uBAAqB,oBAAoB,QAAQ,QAAQ,QAAQ,OAAO;AACxE,QAAM,EAAE,MAAM,MAAM,IAAI,qBAAqB,qBAAqB,YAAY,MAAM;AACpF,QAAM,SAAS,MAAM;AACrB,MAAI,MAAM;AACV,MAAI,mBAAmB,QAAQ;AAC/B,QAAM,mBAAmB,CAAC;AAC1B,WAAS,KAAK,GAAG,KAAK,QAAQ,EAAE,IAAI;AAClC,eAAW,UAAU,MAAM,KAAK;AAC9B,YAAM,EAAE,oBAAoB,MAAM,YAAY,aAAa,IAAI,qBAAqB,qBAAqB,kBAAkB,OAAO,OAAO;AACzI,UAAI;AACJ,UAAI,qBAAqB,sBAAsB,IAAI,GAAG;AACpD,YAAI,QAAQ;AAAA,MACd,OAAO;AACL,YAAI,WAAW,EAAE,QAAQ,EAAE,GAAG,QAAQ,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AACrF,yBAAiB,KAAK,CAAC;AAAA,MACzB;AACA,YAAM,cAAc,EAAE,MAAM,MAAM;AAClC,eAAS,IAAI,GAAG,IAAI,aAAa,QAAQ,EAAE,GAAG;AAC5C,oBAAY,OAAO,aAAa,IAAI,GAAG,CAAC;AAAA,MAC1C;AACA,UAAI,CAAC,aAAa,YAAY,EAAE,OAAO,WAAW,GAAG;AACnD,YAAI,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAChF,yBAAiB,KAAK,CAAC;AAAA,MACzB;AACA,UAAI,QAAQ,MAAM;AAChB,cAAM;AAAA,MACR,OAAO;AACL,cAAM,UAAU,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,IAAI,GAAG,SAAS,SAAS,CAAC;AAC/D,yBAAiB,KAAK,GAAG;AAAA,MAC3B;AAAA,IACF;AACA,QAAI,KAAK,SAAS,GAAG;AACnB,UAAI,KAAK,OAAO,GAAG;AACjB,cAAM,KAAK;AAAA,UACT,QAAQ,EAAE,GAAG,IAAI;AAAA,UACjB,SAAS;AAAA,UACT,OAAO;AAAA,YACL,MAAM,KAAK,OAAO,QAAQ,SAAS;AAAA,YACnC,UAAU;AAAA,UACZ;AAAA,QACF,CAAC;AACD,yBAAiB,KAAK,GAAG;AAAA,MAC3B;AACA;AAAA,IACF;AAAA,EACF;AACA,aAAW,cAAc,kBAAkB;AACzC,QAAI,eAAe,KAAK;AACtB;AAAA,IACF;AACA,aAAS,8BAA8B,UAAU;AAAA,EACnD;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AACX,IAAI,aAAa;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUjB,IAAI,OAAO,iBAAiB,EAAE,WAAW,MAAM,iBAAiB,WAAW,CAAC;AAC5E,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU;AACd,IAAI,iBAAiB;AAAA;AAAA;AAAA;AAIrB,IAAI,WAAW,CAAC,SAAS;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,IAAI,EAAE,IAAI;AAClB,QAAM,UAAU,IAAI,EAAE,QAAQ,8BAA8B,IAAI,IAAI,sBAAsB,gBAAgB,GAAG,OAAO,EAAE,KAAK,IAAI,IAAI,gBAAgB,SAAS,GAAG,OAAO,EAAE,KAAK;AAC7K,SAAO,SAAS,gBAAgB,SAAS,CAAC,IAAI,CAAC,GAAG,GAAG,KAAK;AAC5D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe;AAAA;AAAA;AAGnB,IAAI,QAAQ;AACZ,IAAI,SAAS,kBAAkB;AAAA,EAC7B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,OAAO;AAAA,EACP,eAAe;AACjB,CAAC;AACD,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM;AAAA;AAAA;AAAA;AAAA,cAII,qBAAqB;AAAA,eACpB,qBAAqB;AAAA,eACrB,qBAAqB;AAAA,eACrB,qBAAqB;AAAA,eACrB,qBAAqB;AAAA,eACrB,qBAAqB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAOpC,IAAI,OAAO,iBAAiB,EAAE,WAAW,IAAI,CAAC;AAC9C,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM,0BAA0B;AAAA;AAAA;AAGpC,IAAI,aAAa;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUjB,IAAI,OAAO,iBAAiB;AAAA,EAC1B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,eAAe;AAAA,EACf,OAAO;AACT,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,IAAI,IAAI;AAChB,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,YAAY,OAAO,MAAM;AAC/B,QAAM,WAAW,OAAO,MAAM,MAAM;AACpC,MAAI,OAAO;AACX,MAAI,MAAM,GAAG;AACX,iBAAa,OAAO,EAAE,YAAY,MAAM,KAAK,MAAM,iCAAiC,EAAE,YAAY,OAAO,YAAY;AACrH,WAAO,YAAY,MAAM;AAAA,EAC3B;AACA,WAAS,OAAO,MAAM,GAAG,CAAC;AAC1B,SAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC1F;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ;AACZ,IAAI,SAAS,iBAAiB,EAAE,WAAW,OAAO,iBAAiB,OAAO,eAAe,aAAa,CAAC;AACvG,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa,MAAM;AAAA,EACrB,YAAY,WAAW,YAAY,SAAS;AAC1C,SAAK,gBAAgB,CAAC,QAAQ,MAAM;AACpC,UAAM,WAAW,WAAW;AAC5B,SAAK,cAAc;AACnB,UAAM,4BAA4B,UAAU,SAAS,KAAK,OAAO,UAAU,KAAK;AAChF,UAAM,oBAAoB,UAAU,GAAG,eAAe;AACtD,QAAI;AACJ,QAAI,cAAc,QAAQ;AACxB,iBAAW;AAAA,IACb,WAAW,cAAc,QAAQ;AAC/B,iBAAW;AAAA,IACb,OAAO;AACL,YAAM,IAAI,MAAM,sDAAsD,YAAY;AAAA,IACpF;AACA,SAAK,WAAW;AAAA,yCACqB;AAAA;AAAA;AAAA,UAG/B;AAAA;AAAA;AAAA;AAAA,kDAIwC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAMpB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,yDAS2B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAWvD;AACF;AAGA,SAAS,SAAS,GAAG,SAAS,UAAU;AACtC,QAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,QAAMc,cAAY,aAAa,cAAc,EAAE,KAAK;AACpD,QAAM,qBAAqB,EAAE,MAAM,EAAE,MAAM,SAAS;AACpD,QAAM,QAAQA,cAAY;AAC1B,QAAM,UAAU,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,OAAO,kBAAkB,EAAE,EAAE,CAAC;AAC5G,QAAM,SAAS,QAAQ;AACvB,QAAM,cAAc,IAAI,WAAW,QAAQ,QAAQ,OAAO;AAC1D,QAAM,cAAc,IAAI,WAAW,QAAQ,QAAQ,OAAO;AAC1D,QAAM,SAAS;AAAA,IACb;AAAA,MACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,MACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,MACrC,OAAO;AAAA,IACT;AAAA,IACA;AAAA,MACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,MACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,MACrC,OAAO;AAAA,IACT;AAAA,EACF;AACA,QAAM,WAAW,SAAS,gBAAgB,aAAa,QAAQ,SAAS;AACxE,QAAM,WAAW,SAAS,gBAAgB,aAAa,QAAQ,SAAS;AACxE,QAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,MAAM,UAAU,MAAM,SAAS,GAAG,SAAS,SAAS,CAAC;AAChG,WAAS,8BAA8B,QAAQ;AAC/C,WAAS,8BAA8B,QAAQ;AAC/C,QAAM,wBAAwB,SAAS,EAAE,QAAQ,EAAE,GAAG,cAAc,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,EAAE,MAAM,EAAE,CAAC;AACrH,WAAS,8BAA8B,OAAO;AAC9C,WAAS,8BAA8B,aAAa;AACpD,SAAO;AACT;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,SAAO,SAAS,QAAQ,OAAO,QAAQ;AACzC;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,OAAO,OAAO;AACxB,SAAK,cAAc,CAAC;AACpB,SAAK,iBAAiB,CAAC,EAAE,MAAM,SAAS,MAAM,QAAQ,CAAC;AACvD,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAMlB;AACF;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,IAAI;AACzB,MAAI,EAAE,MAAM,IAAI;AAChB,UAAQ,SAAS,aAAa,WAAW,KAAK;AAC9C,MAAI,UAAU,UAAU;AACtB,UAAM,SAAS,aAAa,kBAAkB,OAAO,aAAa,cAAc,KAAK,CAAC;AACtF,WAAO,KAAK,KAAK;AACjB,WAAO,SAAS,eAAe,OAAO,OAAO,MAAM;AAAA,EACrD,OAAO;AACL,UAAM,UAAU,IAAI,YAAY,OAAO,KAAK;AAC5C,UAAM,eAAe,CAAC,CAAC,KAAK,CAAC;AAC7B,WAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,OAAO,YAAY;AAAA,EAClE;AACF;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,YAAY;AACtB,SAAK,gBAAgB,CAAC,OAAO;AAC7B,SAAK,cAAc,CAAC;AACpB,UAAM,aAAa,WAAW;AAC9B,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,yBAKK;AAAA;AAAA,uCAEc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAQrC;AACF;AAGA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AAC7C,UAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,UAAM,eAAe;AACrB,UAAM,UAAU,IAAI,qBAAqB,OAAO,KAAK;AACrD,UAAM,SAAS,aAAa,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO,KAAK;AAC3E,WAAO;AAAA,EACT;AACF;AAGA,IAAI,QAAQ;AACZ,IAAI,SAAS,iBAAiB,EAAE,WAAW,OAAO,iBAAiB,OAAO,eAAe,aAAa,CAAC;AACvG,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWd,IAAI,iBAAiB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAsBrB,IAAI,YAAY,kBAAkB,EAAE,WAAW,SAAS,iBAAiB,gBAAgB,OAAO,QAAQ,CAAC;AACzG,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,UAAM,OAAO,mBAAmB;AAChC,UAAM,CAAC,QAAQ,KAAK,IAAI;AACxB,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,uDAMmC,YAAY;AAAA;AAAA,wBAE3C,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAe3B;AACF;AAGA,IAAI,0BAA0B,MAAM;AAAA,EAClC,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,UAAM,OAAO,mBAAmB;AAChC,UAAM,CAAC,QAAQ,KAAK,IAAI;AACxB,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAeU,YAAY;AAAA,4BACd,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAgBvB,KAAK;AAAA;AAAA;AAAA,EAGb;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AACA,IAAI;AACJ,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,MAAI,EAAE,OAAO,IAAI;AACjB,QAAM,EAAE,YAAY,IAAI;AACxB,QAAM,UAAU,OAAO,qBAAqB,eAAe,kBAAkB;AAC7E,QAAM,UAAU,OAAO,qBAAqB,eAAe,kBAAkB;AAC7E,QAAM,CAAC,OAAO,MAAM,IAAI,UAAU;AAAA,IAChC,OAAO;AAAA,IACP,OAAO;AAAA,EACT,IAAI,CAAC,OAAO,OAAO,OAAO,MAAM;AAChC,QAAM,WAAW,CAAC,QAAQ,KAAK;AAC/B,QAAM,WAAW,CAAC,QAAQ,OAAO,WAAW;AAC5C,MAAI,WAAW,SAAS;AACtB,QAAI,wBAAwB,MAAM;AAChC,6BAAuB,SAAS,cAAc,QAAQ,EAAE,WAAW,IAAI;AAAA,IACzE;AACA,yBAAqB,OAAO,QAAQ;AACpC,yBAAqB,OAAO,SAAS;AACrC,yBAAqB,UAAU,QAAQ,GAAG,GAAG,OAAO,MAAM;AAC1D,aAAS,qBAAqB;AAAA,EAChC;AACA,QAAM,kBAAkB,SAAS,eAAe,UAAU,OAAO;AACjE,WAAS,QAAQ,IAAI,gBAAgB,MAAM,EAAE,QAAQ,aAAa;AAClE,WAAS,MAAM,yBAAyB,SAAS,WAAW,gBAAgB,MAAM,GAAG,MAAM;AAC3F,QAAM,UAAU,IAAI,EAAE,QAAQ,YAAY,IAAI,IAAI,wBAAwB,QAAQ,IAAI,IAAI,kBAAkB,QAAQ;AACpH,QAAM,MAAM,SAAS,gBAAgB,SAAS,CAAC,eAAe,GAAG,OAAO;AACxE,WAAS,YAAY,gBAAgB,MAAM;AAC3C,SAAO;AACT;AAGA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAd,UAAS,KAAK,MAAM,YAAY,WAAW,iBAAiB,YAAY,aAAa,eAAe,IAAI;AAChH,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,OAAO,WAAW;AAC5I,MAAI;AACJ,QAAM,gBAAgB,CAAC;AACvB,MAAI,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,KAAK,SAAS,mBAAmB,KAAK,SAAS,kBAAkB,KAAK,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,MAAM,SAAS,QAAQ,SAAS,UAAU,SAAS,QAAQ,SAAS,UAAU;AACtQ,UAAM,eAAe;AAAA,MACnB;AAAA,MACA;AAAA,MACA;AAAA,MACA,SAAS;AAAA,MACT;AAAA,MACA,YAAY;AAAA,MACZ;AAAA,MACA;AAAA,IACF,CAAC;AAAA,EACH,WAAW,IAAI,EAAE,QAAQ,mBAAmB,GAAG;AAC7C,UAAM,iBAAiB;AAAA,MACrB;AAAA,MACA;AAAA,MACA;AAAA,MACA,SAAS;AAAA,MACT;AAAA,MACA,YAAY;AAAA,MACZ;AAAA,MACA;AAAA,IACF,CAAC;AAAA,EACH,OAAO;AACL,UAAM,UAAU,QAAQ;AACxB,UAAM,4BAA4B,0BAA0B;AAC5D,UAAM,oBAAoB,gBAAgB;AAC1C,UAAM,kBAAkB,cAAc,6BAA6B,aAAa,KAAK,IAAI;AACzF,UAAM,UAAU,IAAI,cAAc,UAAU,SAAS,iBAAiB,2BAA2B,iBAAiB;AAClH,UAAM,UAAU,CAAC,GAAG,MAAM;AAC1B,UAAM,2BAA2B,CAAC,QAAQ,gBAAgB;AACxD,UAAI,gBAAgB,UAAU,OAAO,MAAM,WAAW,KAAK,OAAO,MAAM,OAAO,GAAG;AAChF,cAAM,eAAe,SAAS;AAAA,UAC5B,QAAQ,EAAE,GAAG,OAAO;AAAA,UACpB,SAAS;AAAA,UACT,OAAO,EAAE,OAAO,CAAC,OAAO,MAAM,IAAI,GAAG,CAAC,EAAE;AAAA,QAC1C,CAAC;AACD,sBAAc,KAAK,YAAY;AAC/B,eAAO;AAAA,MACT;AACA,aAAO;AAAA,IACT;AACA,QAAI,SAAS;AACX,cAAQ,KAAK,yBAAyB,MAAM,UAAU,CAAC;AAAA,IACzD;AACA,QAAI,2BAA2B;AAC7B,cAAQ,KAAK,yBAAyB,wBAAwB,UAAU,CAAC;AAAA,IAC3E;AACA,QAAI,mBAAmB;AACrB,YAAM,kBAAkB,SAAS,eAAe,CAAC,GAAG,WAAW,aAAa,kBAAkB,gBAAgB,SAAS,CAAC;AACxH,cAAQ,KAAK,eAAe;AAC5B,oBAAc,KAAK,eAAe;AAAA,IACpC;AACA,UAAM,SAAS,gBAAgB,SAAS,SAAS,SAAS;AAAA,EAC5D;AACA,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,SAAS,EAAE,CAAC;AAC3G,gBAAc,KAAK,GAAG;AACtB,gBAAc,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACxE,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,sBAAsB,MAAM;AACnC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,WAAW,iBAAiB,YAAY,aAAa,eAAe,IAAI;AACpG,QAAM,gBAAgB,CAAC;AACvB,MAAI,aAAa;AACjB,MAAI,cAAc,MAAM;AACtB,iBAAa,CAAC,GAAG,CAAC;AAAA,EACpB;AACA,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,UAAU,GAAG,MAAM,gFAAgFA,2BAA0B,aAAa;AAC3N,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,YAAY,MAAM,iBAAiB,IAAI;AAC/H,QAAM,0BAA0B,IAAI,EAAE,QAAQ,0BAA0B,KAAK,SAAS,eAAe,KAAK,SAAS,cAAc,SAAS,eAAe;AACzJ,QAAM,kBAAkB,cAAc,6BAA6B,aAAa,uBAAuB,IAAI;AAC3G,QAAM,gBAAgB,CAAC,GAAG,MAAM;AAChC,QAAM,UAAU,QAAQ;AACxB,QAAM,4BAA4B,0BAA0B;AAC5D,QAAM,oBAAoB,gBAAgB;AAC1C,MAAI,SAAS;AACX,kBAAc,KAAK,IAAI;AAAA,EACzB;AACA,MAAI,2BAA2B;AAC7B,kBAAc,KAAK,sBAAsB;AAAA,EAC3C;AACA,MAAI,mBAAmB;AACrB,UAAM,kBAAkB,SAAS,eAAe,CAAC,GAAG,WAAW,aAAa,kBAAkB,gBAAgB,SAAS,CAAC;AACxH,kBAAc,KAAK,eAAe;AAClC,kBAAc,KAAK,eAAe;AAAA,EACpC;AACA,MAAI;AACJ,MAAI,yBAAyB;AAC3B,cAAU,IAAI,6BAA6B,UAAU,SAAS,iBAAiB,2BAA2B,iBAAiB;AAAA,EAC7H,OAAO;AACL,cAAU,IAAI,uBAAuB,UAAU,SAAS,iBAAiB,2BAA2B,iBAAiB;AAAA,EACvH;AACA,QAAM,eAAe;AAAA,IACnB,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI;AAAA,IAC5C,CAAC,SAAS,cAAc,SAAS,WAAW;AAAA,IAC5C,CAAC,SAAS,gBAAgB,SAAS,aAAa;AAAA,IAChD,CAAC,SAAS,UAAU,SAAS,OAAO;AAAA,EACtC;AACA,QAAM,SAAS,SAAS,gBAAgB,SAAS,eAAe,WAAW,YAAY;AACvF,gBAAc,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACxE,SAAO;AACT;AACA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,YAAY,UAAUA,UAAS,OAAO,aAAa;AACjD,SAAK,WAAW;AAChB,SAAK,UAAUA;AACf,SAAK,cAAc;AACnB,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,cAAc;AACnB,UAAM,cAAc,kBAAkBA,SAAQ,MAAM;AACpD,UAAM,QAAQ,kBAAkB,MAAM,MAAM;AAC5C,UAAM,eAAe,KAAK,WAAW,IAAI,eAAe;AACxD,UAAM,kBAAkB,kBAAkB,YAAY,MAAM;AAC5D,UAAM,oBAAoB,YAAY,SAAS,IAAI,mBAAmB;AACtE,SAAK,WAAW;AAAA,UACV,yBAAyB,eAAe,KAAK;AAAA,UAC7C,iCAAiC,mBAAmB,KAAK;AAAA;AAAA,YAEvD;AAAA;AAAA;AAAA,gCAGoB,KAAK;AAAA;AAAA;AAAA,wDAGmB;AAAA,sCAClB;AAAA;AAAA;AAAA;AAAA;AAAA,EAKpC;AACF;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,QAAQ,QAAQ,IAAI;AAC5B,QAAM,eAAe,QAAQ;AAC7B,QAAM,YAAY,aAAa,aAAa,SAAS;AACrD,QAAM,aAAa,aAAa,cAAc,OAAO,KAAK;AAC1D,QAAM,CAAC,aAAa,WAAW,WAAWA,QAAO,IAAI,qBAAqB,mBAAmB,QAAQ,OAAO;AAC5G,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,WAAW,SAAS,EAAE,EAAE,CAAC;AACvH,QAAM,WAAW,SAAS;AAAA,IACxB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,aAAa,cAAc,OAAO,KAAK,IAAI,WAAW,SAAS,EAAE;AAAA,EACpF,CAAC;AACD,MAAI,SAAS,mBAAmB,CAAC,QAAQ,OAAO,CAAC,KAAK,OAAO,UAAU,UAAU;AAC/E,UAAM,cAAc,SAAS,SAAS,QAAQ,MAAM;AACpD,UAAM,YAAY,SAAS,WAAW,MAAM;AAC5C,UAAM,WAAW,gBAAgB,aAAa,WAAW,OAAO,OAAO,WAAW,WAAW,WAAWA,UAAS,OAAO,OAAO,UAAU;AACzI,WAAO,SAAS,eAAe,aAAa,OAAO,OAAO,SAAS,MAAM;AAAA,EAC3E;AACA,QAAM,UAAU,IAAI,gBAAgB,WAAWA,UAAS,CAAC,WAAW,SAAS,GAAG,OAAO,KAAK;AAC5F,QAAM,MAAM,SAAS,gBAAgB,SAAS,CAAC,UAAU,cAAc,GAAG,SAAS,KAAK;AACxF,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAClG,WAAS,8BAA8B,cAAc;AACrD,WAAS,8BAA8B,QAAQ;AAC/C,WAAS,8BAA8B,GAAG;AAC1C,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,QAAQ,aAAa;AAC/B,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,cAAc;AACnB,SAAK,OAAO,YAAY;AACxB,UAAM,QAAQ,kBAAkB,KAAK,IAAI;AACzC,UAAM,eAAe,iBAAiB,QAAQ,CAAC;AAC/C,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA;AAAA,oDAE0C,OAAO;AAAA,oCACvB;AAAA;AAAA;AAAA,EAGlC;AACF;AACA,SAAS,iBAAiB,QAAQ,MAAM;AACtC,QAAM,gBAAgB,CAAC,WAAW,WAAW,WAAW,SAAS;AACjE,QAAM,eAAe,CAAC;AACtB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,QAAI,OAAO,GAAG;AACZ,mBAAa,KAAK,OAAO;AAAA,IAC3B,OAAO;AACL,mBAAa,KAAK,GAAG,cAAc,KAAK;AAAA,IAC1C;AAAA,EACF;AACA,SAAO,aAAa,KAAK;AAC3B;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAM,UAAU,IAAI;AAC5B,QAAM,aAAa,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AAC9D,MAAI,IAAI,EAAE,IAAI,OAAO,GAAG;AACtB,UAAM,cAAc,SAAS,SAAS,QAAQ,MAAM;AACpD,UAAM,UAAU,EAAE,MAAM;AACxB,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,EAAE,IAAI;AAC9C,YAAMH,SAAQ,YAAY;AAC1B,mBAAa,OAAOA,UAAS,UAAU,KAAKA,UAAS,GAAG,MAAM,6BAA6BA,wBAAuB,UAAU,IAAI;AAAA,IAClI;AAAA,EACF;AACA,QAAM,YAAY,qBAAqB,aAAa,yBAAyB,GAAG,SAAS,YAAY,SAAS;AAC9G,QAAM,cAAc,aAAa,cAAc,QAAQ,KAAK;AAC5D,QAAM,YAAY,CAAC;AACnB,QAAM,WAAW,SAAS;AAAA,IACxB,QAAQ,EAAE,EAAE;AAAA,IACZ,SAAS;AAAA,IACT,OAAO;AAAA,MACL,OAAO;AAAA,QACL,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,MACZ;AAAA,IACF;AAAA,EACF,CAAC;AACD,QAAM,eAAe,SAAS;AAAA,IAC5B,QAAQ,EAAE,GAAG,QAAQ;AAAA,IACrB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,UAAU,WAAW,cAAc,UAAU,SAAS,EAAE;AAAA,EAC3E,CAAC;AACD,YAAU,KAAK,QAAQ;AACvB,YAAU,KAAK,YAAY;AAC3B,QAAM,qBAAqB;AAAA,IACzB,UAAU;AAAA,IACV,UAAU;AAAA,IACV,cAAc,UAAU;AAAA,IACxB,UAAU;AAAA,EACZ;AACA,MAAI,SAAS,mBAAmB,CAAC,GAAG,OAAO,CAAC,KAAK,EAAE,UAAU,UAAU;AACrE,UAAM,aAAa,SAAS,WAAW,YAAY;AACnD,UAAM,OAAO,SAAS,WAAW,QAAQ;AACzC,UAAM,SAAS,gBAAgB,MAAM,YAAY,kBAAkB;AACnE,cAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,WAAO,SAAS,eAAe,UAAU,aAAa,OAAO,OAAO,OAAO,MAAM;AAAA,EACnF;AACA,QAAM,UAAU,IAAI,cAAc,SAAS,OAAO,kBAAkB;AACpE,QAAM,MAAM,SAAS,gBAAgB,SAAS,CAAC,UAAU,YAAY,GAAG,SAAS,KAAK;AACtF,YAAU,KAAK,GAAG;AAClB,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,UAAU,YAAY,EAAE,CAAC;AAC5G,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU;AACd,IAAI,iBAAiB;AAAA;AAAA;AAGrB,IAAI,WAAW,kBAAkB;AAAA,EAC/B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,eAAe;AAAA,EACf,OAAO;AACT,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB;AACpB,IAAI,uBAAuB;AAAA;AAAA;AAG3B,IAAI,gBAAgB,kBAAkB;AAAA,EACpC,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,OAAO;AAAA,EACP,eAAe;AACjB,CAAC;AACD,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,SAAO,SAAS,QAAQ,MAAM,QAAQ;AACxC;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY;AAChB,IAAI,YAAY,iBAAiB,EAAE,WAAW,WAAW,OAAO,OAAO,CAAC;AACxE,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS;AACb,IAAI,SAAS,iBAAiB,EAAE,WAAW,QAAQ,OAAO,OAAO,CAAC;AAClE,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS;AACb,IAAI,SAAS,iBAAiB,EAAE,WAAW,QAAQ,OAAO,OAAO,CAAC;AAClE,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AACX,IAAI,cAAc;AAAA;AAAA;AAGlB,IAAI,QAAQ,kBAAkB;AAAA,EAC5B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,eAAe;AAAA,EACf,OAAO;AACT,CAAC;AACD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa;AACjB,IAAI,oBAAoB;AAAA;AAAA;AAGxB,IAAI,aAAa,kBAAkB;AAAA,EACjC,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,eAAe;AAAA,EACf,OAAO;AACT,CAAC;AACD,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,IAAI,IAAI;AAC7B,QAAM,UAAU,gBAAgB,OAAO,MAAM,GAAG;AAChD,SAAO,SAAS,eAAe,CAAC,QAAQ,MAAM,GAAG,WAAW,OAAO;AACrE;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM,0BAA0B;AAAA;AAAA;AAGpC,IAAI,aAAa;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AASjB,IAAI,OAAO,iBAAiB,EAAE,WAAW,KAAK,iBAAiB,YAAY,eAAe,WAAW,CAAC;AACtG,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,0BAA0B;AAAA;AAAA;AAGtC,IAAI,SAAS,iBAAiB,EAAE,WAAW,MAAM,CAAC;AAClD,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc;AAClB,IAAI,qBAAqB;AAAA;AAAA;AAAA;AAAA;AAKzB,IAAI,cAAc,kBAAkB;AAAA,EAClC,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,OAAO;AACT,CAAC;AACD,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc;AAClB,IAAI,cAAc,iBAAiB,EAAE,WAAW,YAAY,CAAC;AAC7D,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa;AACjB,IAAI,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAMxB,IAAI,aAAa,kBAAkB,EAAE,WAAW,YAAY,iBAAiB,mBAAmB,OAAO,OAAO,CAAC;AAC/G,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa,MAAM;AAAA,EACrB,YAAY,QAAQ,QAAQ,MAAMa,QAAO,MAAM;AAC7C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,CAAC;AACpB,UAAM,MAAM;AACZ,UAAM,OAAO,OAAO,KAAK;AACzB,SAAK,cAAc;AACnB,QAAI;AACJ,UAAM,QAAQ,SAAS,iBAAiBA;AACxC,QAAI,SAAS,KAAK;AAChB,oBAAc,eAAe;AAAA,IAC/B,WAAW,SAAS,GAAG;AACrB,oBAAc,QAAQ;AAAA,IACxB,OAAO;AACL,oBAAc,WAAW,mBAAmB;AAAA,IAC9C;AACA,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,wBASI,aAAa;AAAA;AAAA,oCAED;AAAA;AAAA;AAAA;AAAA;AAAA,0BAKV;AAAA;AAAA;AAAA;AAAA,EAIxB;AACF;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,QAAQ,QAAQ,MAAMA,QAAO,MAAM;AAC7C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,CAAC;AACpB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,UAAM,MAAM;AACZ,UAAM,OAAO,OAAO,KAAK;AACzB,SAAK,cAAc;AACnB,QAAI;AACJ,UAAM,QAAQ,SAAS,iBAAiBA;AACxC,QAAI,SAAS,KAAK;AAChB,oBAAc,eAAe;AAAA,IAC/B,WAAW,SAAS,GAAG;AACrB,oBAAc,QAAQ;AAAA,IACxB,OAAO;AACL,oBAAc,WAAW,mBAAmB;AAAA,IAC9C;AACA,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAQY,KAAK,YAAY;AAAA,gCACjB,KAAK,YAAY;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,iCAehB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,yBAWR,aAAa;AAAA;AAAA;AAAA,6DAGuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0CAqBnB;AAAA;AAAA;AAAA;AAAA,EAIxC;AACF;AAGA,IAAI,MAAM,CAAC,SAAS;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,aAAa,MAAM,OAAAA,QAAO,KAAK,IAAI;AAC3C,QAAM,UAAU,IAAI,EAAE,QAAQ,0BAA0B,IAAI,IAAI,iBAAiB,EAAE,OAAO,aAAa,MAAMA,QAAO,IAAI,IAAI,IAAI,WAAW,EAAE,OAAO,aAAa,MAAMA,QAAO,IAAI;AAClL,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACvD;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,YAAY,aAAa,MAAMA,QAAO,MAAM;AACtD,SAAK,gBAAgB,CAAC,cAAc,eAAe,IAAI;AACvD,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc;AACnB,SAAK,QAAQ,WAAW;AACxB,SAAK,cAAc;AACnB,SAAK,OAAO;AACZ,SAAK,QAAQA;AACb,SAAK,OAAO;AACZ,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAQU,KAAK;AAAA,oDACiB;AAAA,yCACX,KAAK;AAAA,0BACpB;AAAA;AAAA;AAAA,sCAGY,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,yBAelBA,0BAAyB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,yCAOTA;AAAA,0BACf;AAAA;AAAA;AAAA;AAAA,0CAIgB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAexC;AACF;AAGA,IAAI,UAAU,CAAC,SAAS;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,GAAG,IAAI;AACrB,QAAM,EAAE,aAAa,MAAM,OAAAA,QAAO,KAAK,IAAI;AAC3C,QAAM,UAAU,IAAI,eAAe,EAAE,OAAO,aAAa,MAAMA,QAAO,IAAI;AAC1E,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,GAAG,EAAE,GAAG,EAAE,KAAK;AAC9D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,GAAG,aAAa,UAAU,UAAU;AACpD,QAAM,SAAS,aAAa,cAAc,WAAW;AACrD,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,YAAY,QAAQ;AAC1B,QAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,OAAO,CAAC,WAAW,MAAM,EAAE,GAAG,SAAS,SAAS,CAAC;AAC1G,QAAM,UAAU,OAAO,eAAe,EAAE,OAAO,OAAO,QAAQ;AAC9D,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AACzG,WAAS,8BAA8B,aAAa;AACpD,WAAS,8BAA8B,OAAO;AAC9C,SAAO;AACT;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,kBAAkB,SAAS,IAAI;AACvC,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,aAAa,eAAe,kBAAkB,EAAE,KAAK;AACtE,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,QAAM,uBAAuB,gBAAgB;AAC7C,QAAM,qBAAqB,SAAS,mBAAmB,CAAC,CAAC,CAAC;AAC1D,MAAI,WAAW;AACf,MAAI,sBAAsB;AACxB,QAAI,oBAAoB;AACtB,YAAM,WAAW,SAAS,QAAQ,IAAI,SAAS,MAAM;AACrD,YAAM,SAAS,SAAS;AACxB,YAAM,WAAW,IAAI,MAAM,KAAK;AAChC,eAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,iBAAS,MAAM,EAAE,MAAM,aAAa;AAAA,MACtC;AACA,YAAM,iBAAiB,iBAAiB,QAAQ,EAAE,OAAO,EAAE,OAAO,cAAc,QAAQ;AACxF,iBAAW,SAAS,eAAe,UAAU,EAAE,KAAK;AACpD,YAAM,eAAe,SAAS,QAAQ,IAAI,SAAS,MAAM;AACzD,mBAAa,SAAS;AAAA,IACxB,OAAO;AACL,iBAAW,eAAe,GAAG,cAAc,QAAQ;AAAA,IACrD;AACA,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAAA,EACjE;AACA,uBAAqB,2BAA2B,OAAO,MAAM,KAAK;AAClE,QAAM,CAAC,aAAa,WAAW,IAAI,qBAAqB,0BAA0B,SAAS,OAAO,IAAI;AACtG,MAAI,WAAW;AACf,MAAI,UAAU;AACZ,eAAW,qBAAqB,qBAAqB,aAAa,QAAQ;AAAA,EAC5E;AACA,MAAI;AACJ,MAAI,oBAAoB;AACtB,UAAM,WAAW,SAAS,QAAQ,IAAI,SAAS,MAAM;AACrD,UAAM,SAAS,SAAS;AACxB,UAAM,YAAY,WAAW,QAAQ,aAAa,cAAc,WAAW,GAAG,UAAU,EAAE,KAAK;AAC/F,UAAM,SAAS,eAAe,UAAU,EAAE,KAAK;AAC/C,UAAM,UAAU,SAAS,QAAQ,IAAI,IAAI,MAAM;AAC/C,YAAQ,SAAS;AAAA,EACnB,OAAO;AACL,UAAM,SAAS,UAAU,aAAa,UAAU,QAAQ;AAAA,EAC1D;AACA,MAAI,sBAAsB;AACxB,aAAS,8BAA8B,QAAQ;AAAA,EACjD;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU,qBAAqB;AAAA;AAAA;AAGnC,IAAI,iBAAiB;AAAA;AAAA;AAAA,MAGf,qBAAqB;AAAA;AAAA;AAG3B,IAAI,WAAW,kBAAkB;AAAA,EAC/B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,eAAe;AACjB,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,oBAAkB,GAAG,SAAS;AAC9B,QAAM,EAAE,YAAY,SAAAV,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY;AAClB,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,SAAS,GAAG,MAAM,wEAAwEA,2BAA0B,YAAY;AACjN,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,MAAI,SAAS,gBAAgB,KAAK,SAAS,iBAAiB,KAAK,aAAa,YAAY,SAAS,SAAS,SAAS,QAAQ,GAAG;AAC9H,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD;AACA,QAAM,iBAAiB,IAAI,cAAc,UAAU,OAAO,KAAK;AAC/D,SAAO,SAAS,gBAAgB,gBAAgB,CAAC,CAAC,GAAG,EAAE,KAAK;AAC9D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,YAAY,gBAAgB,IAAI;AACxE,QAAM,YAAY,CAAC,GAAG,GAAG,CAAC;AAC1B,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,iBAAiB,UAAU;AAClI,QAAM,iBAAiB,IAAI,cAAc,UAAU,OAAO,KAAK;AAC/D,SAAO,SAAS,gBAAgB,gBAAgB,CAAC,CAAC,GAAG,EAAE,KAAK;AAC9D;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,MAAM;AAAA,EACnC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,MAAM,QAAQ;AACpC,SAAK,cAAc,SAAS;AAC5B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,iBAAiB,SAAS;AAChC,UAAM,wBAAwB,SAAS;AACvC,UAAM,uBAAuB,SAAS;AACtC,UAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,UAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,UAAM,YAAY,wBAAwB,uBAAuB;AACjE,SAAK,WAAW;AAAA,iCACa,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAcZ;AAAA,kBACd;AAAA,gDAC8B;AAAA;AAAA,oCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA,kCAKX;AAAA,kDACgB;AAAA;AAAA,sCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAOf;AAAA;AAAA;AAAA;AAAA,qCAIK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EASnC;AACF;AACA,IAAI,2BAA2B,MAAM;AAAA,EACnC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,MAAM,QAAQ;AACpC,SAAK,cAAc,SAAS;AAC5B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,gBAAgB,SAAS;AAC/B,UAAM,iBAAiB,SAAS;AAChC,UAAM,gBAAgB,SAAS;AAC/B,UAAM,uBAAuB,SAAS;AACtC,UAAM,wBAAwB,SAAS;AACvC,UAAM,uBAAuB,SAAS;AACtC,UAAM,WAAW,uBAAuB,IAAI,SAAS,QAAQ;AAC7D,UAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,UAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,UAAM,YAAY,uBAAuB,wBAAwB,uBAAuB;AACxF,SAAK,WAAW;AAAA,iCACa,aAAa,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAiBzB;AAAA,mBACb;AAAA,gDAC6B;AAAA;AAAA,oCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA,kCAKX;AAAA,sBACZ;AAAA,kDAC4B;AAAA;AAAA,sCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oCAMX;AAAA,wBACZ;AAAA,oDAC4B;AAAA;AAAA,wCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAOf;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,yBAMT,2BAA2B;AAAA,yBAC3B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAUvB;AACF;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,OAAO,IAAI;AAC9B,QAAM,IAAI;AACV,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY,CAAC,GAAG,GAAG,CAAC;AAC1B,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,QAAM,4BAA4B,IAAI,cAAc,UAAU,OAAO,IAAI;AACzE,QAAM,sBAAsB,SAAS,gBAAgB,2BAA2B,CAAC,CAAC,GAAG,EAAE,KAAK;AAC5F,QAAM,yBAAyB,IAAI,yBAAyB,QAAQ;AACpE,QAAM,SAAS,SAAS,gBAAgB,wBAAwB,CAAC,IAAI,mBAAmB,GAAG,EAAE,KAAK;AAClG,WAAS,8BAA8B,mBAAmB;AAC1D,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,QAAQ,OAAO,IAAI;AACtC,QAAM,IAAI;AACV,oBAAkB,CAAC,QAAQ,MAAM,GAAG,aAAa;AACjD,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,MAAM,eAAe;AAC9G,QAAM,eAAe;AACrB,QAAM,0BAA0B,IAAI,cAAc,UAAU,OAAO,YAAY;AAC/E,QAAM,oBAAoB,SAAS,gBAAgB,yBAAyB,CAAC,CAAC,GAAG,EAAE,KAAK;AACxF,QAAM,yBAAyB,IAAI,yBAAyB,QAAQ;AACpE,QAAM,SAAS,SAAS,gBAAgB,wBAAwB,CAAC,IAAI,iBAAiB,GAAG,EAAE,KAAK;AAChG,WAAS,8BAA8B,iBAAiB;AACxD,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,uBAAuB,GAAG,qBAAqB,UAAU,UAAU;AAC1E,MAAI,UAAU,IAAI,cAAc,UAAU,OAAO,KAAK;AACtD,QAAM,aAAa,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,SAAS;AACnE,YAAU,IAAI,cAAc,UAAU,OAAO,MAAM,MAAM,mBAAmB;AAC5E,QAAM,cAAc,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,SAAS;AACpE,SAAO,CAAC,YAAY,WAAW;AACjC;AAGA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,oBAAoB,IAAI;AAChE,UAAM,eAAe;AACrB,iBAAa,OAAO,EAAE,MAAM,WAAW,GAAG,MAAM,uDAAuD,EAAE,MAAM,SAAS;AACxH,UAAM,YAAY,CAAC,GAAG,CAAC;AACvB,iBAAa,OAAO,qBAAqB,+BAA+BA,UAAS,SAAS,GAAG,MAAM,wEAAwEA,2BAA0B,YAAY;AACjN,UAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,IAAI;AACrG,UAAM,CAAC,QAAQ,OAAO,IAAI,uBAAuB,GAAG,qBAAqB,UAAU,YAAY;AAC/F,WAAO,CAAC,QAAQ,OAAO;AAAA,EACzB;AACF;AAGA,SAAS,SAAS,GAAG,aAAa,UAAU,UAAU;AACpD,QAAM,SAAS,aAAa,cAAc,WAAW;AACrD,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,YAAY,QAAQ;AAC1B,QAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,OAAO,CAAC,WAAW,MAAM,EAAE,GAAG,SAAS,SAAS,CAAC;AAC1G,QAAM,UAAU,OAAO,eAAe,WAAW,QAAQ,QAAQ;AACjE,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AACzG,WAAS,8BAA8B,aAAa;AACpD,WAAS,8BAA8B,OAAO;AAC9C,SAAO;AACT;AAGA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,EAAE,UAAU,KAAK,IAAI;AAC3B,UAAM,eAAe;AACrB,UAAM,QAAQ,EAAE,MAAM;AACtB,UAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,QAAI,OAAO;AACX,UAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,UAAM,wBAAwB,gBAAgB;AAC9C,UAAM,qBAAqB,aAAa,mBAAmB,CAAC,CAAC,CAAC;AAC9D,UAAM,gBAAgB,CAAC;AACvB,QAAI,YAAY;AAChB,QAAI,uBAAuB;AACzB,UAAI,oBAAoB;AACtB,cAAM,WAAW,aAAa,QAAQ,IAAI,UAAU,MAAM;AAC1D,cAAM,SAAS,SAAS;AACxB,cAAM,WAAW,IAAI,MAAM,KAAK;AAChC,iBAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,mBAAS,MAAM,EAAE,MAAM,aAAa;AAAA,QACtC;AACA,cAAM,kBAAkB,iBAAiB,QAAQ,EAAE,OAAO,EAAE,OAAO,cAAc,QAAQ;AACzF,oBAAY,aAAa,eAAe,UAAU,EAAE,KAAK;AACzD,cAAM,gBAAgB,aAAa,QAAQ,IAAI,UAAU,MAAM;AAC/D,sBAAc,SAAS;AAAA,MACzB,OAAO;AACL,oBAAY,eAAe,GAAG,cAAc,YAAY;AAAA,MAC1D;AACA,oBAAc,KAAK,SAAS;AAC5B,aAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAAA,IACjE;AACA,yBAAqB,2BAA2B,OAAO,MAAM,KAAK;AAClE,UAAM,CAAC,cAAc,WAAW,IAAI,qBAAqB,0BAA0B,UAAU,OAAO,IAAI;AACxG,QAAI,WAAW;AACf,QAAI,UAAU;AACZ,iBAAW,qBAAqB,qBAAqB,cAAc,QAAQ;AAAA,IAC7E;AACA,UAAM,MAAM,SAAS,WAAW,aAAa,UAAU,YAAY;AACnE,eAAW,MAAM,eAAe;AAC9B,mBAAa,8BAA8B,EAAE;AAAA,IAC/C;AACA,WAAO;AAAA,EACT;AACF;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,YAAY;AAChB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AAC1F,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,EAAE,MAAM,MAAM;AAAA,EAC1E;AACA,uBAAqB,2BAA2B,OAAO,MAAM,KAAK;AAClE,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,UAAU,OAAO,IAAI;AACpG,QAAM,SAAS,aAAa,cAAc,WAAW;AACrD,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,IAAI,MAAM,EAAE,EAAE,CAAC;AACpG,QAAM,UAAU,OAAO,KAAK,IAAI,OAAO,OAAO,QAAQ;AACtD,MAAI;AACJ,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,UAAU,QAAQ;AAC7E,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAAA,EAC1F,OAAO;AACL,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAAA,EAC1F;AACA,WAAS,8BAA8B,GAAG;AAC1C,WAAS,8BAA8B,OAAO;AAC9C,MAAI,gBAAgB,MAAM;AACxB,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU,qBAAqB;AAAA;AAAA;AAGnC,IAAI,iBAAiB;AAAA;AAAA;AAAA,MAGf,qBAAqB;AAAA;AAAA;AAG3B,IAAI,WAAW,kBAAkB;AAAA,EAC/B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,eAAe;AACjB,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,QAAQ,UAAU,MAAM;AAClC,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,MAAM,GAAG,EAAE;AACtE,UAAM,OAAO,OAAO;AACpB,UAAM,QAAQ,kBAAkB,IAAI;AACpC,UAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE,EAAE,KAAK,GAAG;AAClD,UAAM,MAAM,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,GAAG,EAAE,KAAK,GAAG;AACjE,UAAM,iBAAiB,CAAC,aAAa,aAAa,aAAa,WAAW,EAAE,MAAM,GAAG,IAAI;AACzF,UAAM,SAAS,SAAS,YAAY,IAAI;AACxC,QAAI,SAAS,GAAG;AACd,WAAK,WAAW;AAAA,sBACA;AAAA,oBACF;AAAA;AAAA;AAAA;AAAA;AAAA,wCAKoB;AAAA;AAAA,4CAEI;AAAA;AAAA;AAAA;AAAA;AAKtC;AAAA,IACF;AACA,SAAK,WAAW;AAAA,QACZ,iBAAiB,SAAS;AAAA,QAC1B,eAAe,SAAS;AAAA;AAAA;AAAA,UAGtB;AAAA,8BACoB;AAAA;AAAA,iDAEmB;AAAA;AAAA,qDAEI;AAAA;AAAA;AAAA,UAG3C;AAAA,yBACe;AAAA;AAAA;AAAA,EAGvB;AACF;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,QAAQ,UAAU,MAAM;AAClC,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,MAAM,GAAG,EAAE;AACtE,UAAM,OAAO,OAAO;AACpB,UAAM,QAAQ,kBAAkB,IAAI;AACpC,UAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE,EAAE,KAAK,GAAG;AAClD,UAAM,MAAM,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,GAAG,EAAE,KAAK,GAAG;AACjE,UAAM,UAAU,YAAY,MAAM,IAAI;AACtC,UAAM,SAAS,YAAY,UAAU,IAAI;AACzC,UAAM,SAAS,GAAG,QAAQ,OAAO,QAAQ,KAAK,YAAY,OAAO;AACjE,UAAM,YAAY,SAAS,IAAI,WAAW,QAAQ,OAAO,MAAM,EAAE,EAAE,KAAK;AACxE,UAAM,SAAS,SAAS,YAAY,IAAI;AACxC,QAAI,WAAW;AACf,QAAI,SAAS,GAAG;AACd,YAAM,WAAW;AAAA,UACb;AAAA;AAAA,0CAEgC;AAAA;AAAA,8CAEI;AAAA;AAAA;AAAA;AAIxC,iBAAW;AAAA,UACP;AAAA,UACA;AAAA,sCAC4B,OAAO,KAAK,OAAO;AAAA,UAC/C,QAAQ,OAAO;AAAA,aACZ;AAAA,YACD;AAAA,wCAC4B,OAAO,KAAK,OAAO;AAAA;AAAA;AAAA,IAGvD,OAAO;AACL,YAAM,WAAW;AAAA,UACb;AAAA,UACA,cAAc;AAAA,UACd,eAAe;AAAA,UACf;AAAA;AAAA,6CAEmC;AAAA,kDACK;AAAA;AAAA;AAG5C,iBAAW;AAAA,UACP;AAAA,UACA;AAAA,sCAC4B,OAAO,KAAK,OAAO;AAAA,UAC/C,QAAQ,OAAO;AAAA,aACZ;AAAA,YACD;AAAA,wCAC4B,OAAO,KAAK,OAAO;AAAA;AAAA;AAAA,UAGjD,QAAQ,OAAO;AAAA,aACZ,QAAQ,OAAO,QAAQ,KAAK,YAAY,OAAO;AAAA,YAChD;AAAA,wCAC4B,OAAO,KAAK,OAAO;AAAA,YAC/C,QAAQ,OAAO;AAAA,eACZ;AAAA,cACD;AAAA,0CAC4B,OAAO,KAAK,OAAO;AAAA;AAAA;AAAA;AAAA,IAIzD;AACA,SAAK,WAAW;AAAA,cACN,iBAAiB,SAAS;AAAA,cAC1B,eAAe,SAAS;AAAA;AAAA;AAAA,UAG5B;AAAA;AAAA,UAEA;AAAA;AAAA;AAAA;AAAA,EAIR;AACF;AAGA,IAAI,sBAAsB,CAAC,EAAE,QAAQ,SAAS,UAAU,MAAM,MAAM;AAClE,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,UAAU,KAAK,IAAI;AAC3B,QAAM,UAAU,IAAI,EAAE,QAAQ,6BAA6B,IAAI,IAAI,uBAAuB,EAAE,OAAO,UAAU,IAAI,IAAI,IAAI,iBAAiB,EAAE,OAAO,UAAU,IAAI;AACjK,QAAM,SAAS,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AAC7D,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM;AAAA;AAEV,IAAI,aAAa;AAAA;AAAA;AAAA,MAGX,qBAAqB;AAAA;AAAA;AAG3B,IAAI,OAAO,kBAAkB;AAAA,EAC3B,WAAW;AAAA,EACX,iBAAiB;AACnB,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,qBAAqB,MAAM;AAAA,EAC7B,YAAY,WAAW,aAAa,YAAY;AAC9C,SAAK,gBAAgB,CAAC,OAAO;AAC7B,SAAK,iBAAiB,CAAC,EAAE,MAAM,QAAQ,MAAM,QAAQ,CAAC;AACtD,SAAK,cAAc,CAAC,WAAW,UAAU;AACzC,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAQU,cAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0BAUlB,cAAc;AAAA;AAAA;AAAA,EAGtC;AACF;AAGA,IAAI,MAAM;AAAA;AAAA;AAAA;AAAA;AAKV,IAAI,aAAa;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAmBjB,IAAI,UAAU,kBAAkB,EAAE,WAAW,KAAK,iBAAiB,YAAY,kBAAkB,KAAK,CAAC;AACvG,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM;AACV,IAAI,OAAO,kBAAkB;AAAA,EAC3B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,iBAAiB;AAAA,EACjB,eAAe;AACjB,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,IAAI,IAAI;AAChB,QAAM,OAAO,aAAa,eAAe,CAAC,GAAG,GAAG,OAAO,KAAK;AAC5D,QAAM,WAAW,KAAK;AAAA,IACpB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,kBAAkB,MAAM,UAAU,MAAM;AAAA,EACnD,CAAC;AACD,QAAM,gBAAgB,qBAAqB,qBAAqB,SAAS,OAAO,IAAI;AACpF,QAAM,oBAAoB,SAAS,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAClH,QAAM,IAAI,KAAK,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,kBAAkB,GAAG,SAAS,SAAS,CAAC;AACjF,QAAM,IAAI,KAAK,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,SAAS,CAAC;AACtD,QAAM,SAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,MAAM,UAAU,MAAM,EAAE,CAAC;AACnG,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAC7G,QAAM,MAAM,QAAQ,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,eAAe,GAAG,SAAS,SAAS,CAAC;AAC9E,WAAS,8BAA8B,QAAQ;AAC/C,WAAS,8BAA8B,iBAAiB;AACxD,WAAS,8BAA8B,CAAC;AACxC,WAAS,8BAA8B,CAAC;AACxC,WAAS,8BAA8B,MAAM;AAC7C,WAAS,8BAA8B,cAAc;AACrD,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,YAAY,MAAM,WAAW,IAAI;AACzC,QAAM,QAAQ,aAAa,SAAS,SAAS,EAAE,QAAQ,EAAE,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,OAAO,MAAM,SAAS,EAAE,EAAE,CAAC;AAC/H,QAAM,YAAY,MAAM,MAAM;AAC9B,QAAM,cAAc,MAAM,MAAM;AAChC,QAAM,UAAU,IAAI,mBAAmB,WAAW,aAAa,UAAU;AACzE,QAAM,eAAe,CAAC,CAAC,IAAI,CAAC;AAC5B,QAAM,MAAM,SAAS,gBAAgB,SAAS,CAAC,KAAK,GAAG,SAAS,YAAY;AAC5E,MAAI,CAAC,YAAY;AACf,aAAS,8BAA8B,KAAK;AAAA,EAC9C;AACA,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM,oBAAoB;AAAA;AAAA;AAG9B,IAAI,aAAa;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWjB,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,GAAG;AACpC,UAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,UAAM,CAAC,WAAW,QAAQ,IAAI,WAAW,MAAM,QAAQ,EAAE,OAAO,EAAE,KAAK;AACvE,WAAO,SAAS,eAAe,UAAU,EAAE,OAAO,SAAS;AAAA,EAC7D;AACA,MAAI;AACJ,MAAI,IAAI,EAAE,QAAQ,6BAA6B,GAAG;AAChD,cAAU,IAAI,qBAAqB,EAAE,OAAO,UAAU;AAAA,EACxD,OAAO;AACL,cAAU,IAAI,eAAe,EAAE,OAAO,GAAG;AAAA,EAC3C;AACA,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACvD;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,qBAAqB;AACpD,SAAS,qBAAqB,MAAM;AAClC,uBAAqB,KAAK,+FAA+F;AACzH,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,eAAe,IAAI;AACxD,QAAM,YAAY,SAAS,SAAS,MAAM,MAAM;AAChD,QAAM,aAAa,SAAS,SAAS,OAAO,MAAM;AAClD,QAAM,EAAE,gBAAgB,IAAI,yBAAyB,WAAW,YAAY,eAAe,cAAc,cAAc;AACvH,SAAO,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AACnG;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,qBAAqB;AACpD,SAAS,qBAAqB,MAAM;AAClC,uBAAqB,KAAK,+FAA+F;AACzH,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,gBAAgB,mBAAmB,IAAI;AAC5E,QAAM,YAAY,SAAS,SAAS,MAAM,MAAM;AAChD,QAAM,aAAa,SAAS,SAAS,OAAO,MAAM;AAClD,QAAM,EAAE,iBAAiB,aAAa,IAAI,yBAAyB,WAAW,YAAY,eAAe,cAAc,gBAAgB,kBAAkB;AACzJ,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AAAA,IAC1F,SAAS,eAAe,CAAC,GAAG,SAAS,IAAI,WAAW,CAAC,YAAY,CAAC,CAAC;AAAA,EACrE;AACF;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,qBAAqB;AACpD,SAAS,qBAAqB,MAAM;AAClC,uBAAqB,KAAK,+FAA+F;AACzH,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,gBAAgB,aAAa,IAAI;AACtE,QAAM,YAAY,SAAS,SAAS,MAAM,MAAM;AAChD,QAAM,aAAa,SAAS,SAAS,OAAO,MAAM;AAClD,QAAM,mBAAmB;AACzB,QAAM,kBAAkB;AACxB,QAAM,oBAAoB;AAC1B,QAAM,kBAAkB;AACxB,QAAM,EAAE,iBAAiB,eAAe,IAAI,yBAAyB,WAAW,YAAY,kBAAkB,iBAAiB,mBAAmB,eAAe;AACjK,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AAAA,IAC1F,SAAS,eAAe,CAAC,eAAe,MAAM,GAAG,WAAW,IAAI,aAAa,cAAc,CAAC;AAAA,EAC9F;AACF;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,YAAY,OAAO,SAAS,UAAU;AAChD,SAAK,gBAAgB,CAAC,SAAS;AAC/B,SAAK,cAAc,CAAC,YAAY,KAAK;AACrC,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA,8BAIU,oBAAoB;AAAA;AAAA;AAAA;AAAA,EAIhD;AACF;AAGA,IAAI,UAAU,CAAC,SAAS;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,IAAI;AACpB,QAAM,EAAE,OAAO,SAAS,SAAS,IAAI;AACrC,QAAM,cAAc,aAAa,cAAc,QAAQ,KAAK;AAC5D,QAAM,UAAU,IAAI,cAAc,aAAa,OAAO,SAAS,QAAQ;AACvE,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,WAAW,EAAE,EAAE,CAAC;AACxG,QAAM,SAAS,SAAS,gBAAgB,SAAS,CAAC,QAAQ,GAAG,QAAQ,KAAK;AAC1E,WAAS,8BAA8B,QAAQ;AAC/C,QAAM,WAAW,CAAC,GAAG,QAAQ,OAAO,KAAK;AACzC,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC7F,WAAS,8BAA8B,MAAM;AAC7C,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,EAAE,UAAU,aAAa;AAC3B,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,IAAI,MAAM,GAAG,GAAG,SAAS,SAAS,CAAC;AAC7E,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,WAAO;AAAA,EACT,OAAO;AACL,WAAO,MAAM;AAAA,MACX,OAAO;AAAA,QACL,OAAO,EAAE;AAAA,QACT,OAAO,EAAE;AAAA,QACT,OAAO,EAAE,UAAU,WAAW,KAAK;AAAA,MACrC;AAAA,MACA,SAAS;AAAA,IACX,CAAC;AAAA,EACH;AACF;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,EAAE,UAAU,UAAU;AACxB,UAAM,IAAI,MAAM,8CAA8C;AAAA,EAChE,WAAW,EAAE,UAAU,aAAa;AAClC,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,UAAU,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACnE,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,IAAI,MAAM,GAAG,GAAG,SAAS,SAAS,CAAC;AAC7E,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,WAAO;AAAA,EACT,OAAO;AACL,WAAO,MAAM,EAAE,OAAO,EAAE,OAAO,EAAE,OAAO,OAAO,EAAE,OAAO,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACzF;AACF;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,YAAY,EAAE,QAAQ,EAAE,OAAO,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAAA,EAC9F;AACA,QAAM,QAAQ,OAAO,GAAG;AACxB,QAAM,QAAQ,OAAO,GAAG;AACxB,SAAO,QAAQ,CAAC,OAAO;AACrB,iBAAa,kBAAkB,OAAO,GAAG,OAAO,uDAAuD;AACvG,iBAAa,OAAO,UAAU,GAAG,OAAO,MAAM,uDAAuD;AAAA,EACvG,CAAC;AACD,QAAM,0BAA0B,CAAC;AACjC,QAAM,kBAAkB,OAAO,IAAI,CAAC,OAAO;AACzC,UAAM,YAAY,YAAY,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAChG,4BAAwB,KAAK,SAAS;AACtC,WAAO;AAAA,EACT,CAAC;AACD,QAAM,SAAS,QAAQ,EAAE,QAAQ,iBAAiB,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AACtF,0BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa,MAAM;AAAA,EACrB,YAAY,QAAQ,UAAU,eAAe;AAC3C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,iBAAiB,CAAC,EAAE,MAAM,SAAS,MAAM,QAAQ,CAAC;AACvD,SAAK,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,MAAM,GAAG,EAAE;AACtE,UAAM,OAAO,OAAO;AACpB,UAAM,OAAO,kBAAkB,IAAI;AACnC,UAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE,EAAE,KAAK,GAAG;AAClD,UAAM,MAAM,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,GAAG,EAAE,KAAK,GAAG;AACjE,UAAM,iBAAiB,CAAC,aAAa,aAAa,aAAa,WAAW,EAAE,MAAM,GAAG,IAAI;AACzF,QAAI,SAAS,GAAG;AACd,WAAK,WAAW;AAAA,sBACA;AAAA,oBACF;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWd;AAAA,IACF;AACA,SAAK,WAAW;AAAA,QACZ,gBAAgB,QAAQ;AAAA,QACxB,cAAc,QAAQ;AAAA;AAAA;AAAA,UAGpB;AAAA;AAAA;AAAA;AAAA,YAIE;AAAA,2BACe;AAAA;AAAA;AAAA;AAAA,EAIzB;AACF;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,QAAQ,UAAU,eAAe;AAC3C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,iBAAiB,CAAC,EAAE,MAAM,SAAS,MAAM,QAAQ,CAAC;AACvD,SAAK,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,MAAM,GAAG,EAAE;AACtE,UAAM,OAAO,OAAO;AACpB,UAAM,QAAQ,kBAAkB,IAAI;AACpC,UAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE,EAAE,KAAK,GAAG;AAClD,UAAM,MAAM,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,GAAG,EAAE,KAAK,GAAG;AACjE,UAAM,UAAU,YAAY,MAAM,IAAI;AACtC,UAAM,SAAS,YAAY,UAAU,IAAI;AACzC,UAAM,SAAS,GAAG,QAAQ,OAAO,QAAQ,KAAK,YAAY,OAAO;AACjE,UAAM,YAAY,SAAS,IAAI,WAAW,QAAQ,OAAO,MAAM,EAAE,EAAE,KAAK;AACxE,UAAM,iBAAiB;AAAA,MACrB,GAAG;AAAA,MACH,GAAG,QAAQ,OAAO;AAAA,YACZ;AAAA;AAAA,MAEN,SAAS,IAAI,KAAK;AAAA;AAAA,SAEf,QAAQ,OAAO;AAAA,YACZ,QAAQ,OAAO,QAAQ,KAAK,YAAY,OAAO;AAAA,MACrD,SAAS,IAAI,KAAK,KAAK,QAAQ,OAAO;AAAA,cAC9B;AAAA,IACV;AACA,UAAM,cAAc,SAAS,IAAI,4BAA4B;AAC7D,QAAI,WAAW;AACf,aAAS,KAAK,GAAG,IAAI,SAAS,IAAI,IAAI,GAAG,KAAK,GAAG,MAAM;AACrD,kBAAY;AAAA,UACR,eAAe;AAAA,cACX;AAAA,mBACK;AAAA;AAAA,YAEP;AAAA,mBACO,yBAAyB,OAAO,KAAK,OAAO;AAAA;AAAA;AAAA,IAG3D;AACA,gBAAY,SAAS,IAAI,OAAO;AAChC,SAAK,WAAW;AAAA,cACN,iBAAiB,SAAS;AAAA,cAC1B,eAAe,SAAS;AAAA;AAAA;AAAA,UAG5B;AAAA;AAAA,UAEA;AAAA;AAAA;AAAA;AAAA,EAIR;AACF;AAGA,IAAI,SAAS,CAAC,SAAS;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,UAAU,cAAc,IAAI;AACpC,MAAI,aAAa,cAAc,EAAE,KAAK,MAAM,GAAG;AAC7C,UAAM,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,EAAE,MAAM,MAAM,GAAG,EAAE;AACxE,WAAO,MAAM;AAAA,MACX,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,aAAa,OAAO,eAAe,OAAO,EAAE,MAAM;AAAA,IACpE,CAAC;AAAA,EACH;AACA,QAAM,UAAU,IAAI,EAAE,QAAQ,6BAA6B,IAAI,IAAI,iBAAiB,EAAE,OAAO,UAAU,aAAa,IAAI,IAAI,WAAW,EAAE,OAAO,UAAU,aAAa;AACvK,QAAM,eAAe,CAAC,CAAC,aAAa,CAAC;AACrC,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,YAAY;AACrE;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUV,IAAI,aAAa;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,MAcX,qBAAqB;AAAA;AAAA;AAG3B,IAAI,OAAO,kBAAkB,EAAE,WAAW,KAAK,iBAAiB,WAAW,CAAC;AAC5E,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,YAAY,CAAC;AACnB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,YAAY;AAChB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AAC1F,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAC/D,cAAU,KAAK,SAAS;AAAA,EAC1B;AACA,uBAAqB,2BAA2B,QAAQ,MAAM,KAAK;AACnE,MAAI;AACJ,MAAI,SAAS,mBAAmB,CAAC,SAAS,CAAC,GAAG;AAC5C,UAAM,QAAQ,SAAS,QAAQ,IAAI,UAAU,MAAM,EAAE;AACrD,UAAM,EAAE,SAAS,UAAU,SAAS,IAAI,YAAY,UAAU,OAAO,UAAU,OAAO,OAAO,IAAI;AACjG,UAAM,SAAS,eAAe,UAAU,UAAU,OAAO;AAAA,EAC3D,OAAO;AACL,UAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,UAAU,OAAO,IAAI;AACpG,UAAM,SAAS,aAAa,cAAc,WAAW;AACrD,UAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,IAAI,MAAM,EAAE,EAAE,CAAC;AACpG,UAAM,cAAc,WAAW,EAAE,KAAK;AACtC,UAAM,UAAU,OAAO,KAAK,aAAa,QAAQ,QAAQ;AACzD,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,cAAU,KAAK,GAAG;AAClB,cAAU,KAAK,OAAO;AAAA,EACxB;AACA,MAAI,UAAU;AACZ,cAAU,KAAK,GAAG;AAClB,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,QAAQ;AAC9E,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAAA,EACtF;AACA,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,CAAC,SAAS;AACrB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,MAAM,OAAO,MAAM,IAAI;AAC5C,QAAM,SAAS,aAAa,OAAO,MAAM,OAAO,KAAK;AACrD,SAAO,SAAS,eAAe,CAAC,OAAO,MAAM,GAAG,OAAO,MAAM;AAC/D;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa;AACjB,IAAI,cAAc,iBAAiB,EAAE,WAAW,WAAW,CAAC;AAC5D,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,oBAAoB;AAAA;AAAA;AAGhC,IAAI,cAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWlB,IAAI,QAAQ,iBAAiB,EAAE,WAAW,OAAO,iBAAiB,YAAY,CAAC;AAC/E,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,oBAAoB;AAAA;AAAA;AAGjC,IAAI,eAAe;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWnB,IAAI,SAAS,iBAAiB,EAAE,WAAW,QAAQ,iBAAiB,aAAa,CAAC;AAClF,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,wBAAwB,MAAM;AAAA,EAChC,YAAY,YAAY,WAAW,UAAU,cAAc,kBAAkB;AAC3E,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,CAAC;AACpB,UAAM,CAAC,OAAO,WAAW,UAAU,KAAK,IAAI;AAC5C,SAAK,cAAc,CAAC,OAAO,WAAW,UAAU,KAAK;AACrD,UAAM,kBAAkB;AAAA,MACtB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,UAAM,mBAAmB;AAAA,MACvB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,QAAI;AACJ,QAAI,kBAAkB;AACpB,0BAAoB;AAAA,IACtB,OAAO;AACL,0BAAoB;AAAA,IACtB;AACA,SAAK,WAAW;AAAA;AAAA,YAER,gBAAgB,KAAK,iBAAiB;AAAA,YACtC,gBAAgB,KAAK,iBAAiB;AAAA,uCACX,gBAAgB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,mCASpB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAqBjC;AACF;AAGA,IAAI,8BAA8B,MAAM;AAAA,EACtC,YAAY,YAAY,WAAW,UAAU,cAAc,kBAAkB;AAC3E,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc,CAAC;AACpB,UAAM,CAAC,OAAO,WAAW,UAAU,KAAK,IAAI;AAC5C,SAAK,cAAc,CAAC,OAAO,WAAW,UAAU,KAAK;AACrD,UAAM,kBAAkB;AAAA,MACtB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,UAAM,mBAAmB;AAAA,MACvB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,QAAI;AACJ,QAAI,kBAAkB;AACpB,0BAAoB;AAAA,IACtB,OAAO;AACL,0BAAoB;AAAA,IACtB;AACA,SAAK,WAAW;AAAA;AAAA,YAER,gBAAgB,KAAK,iBAAiB;AAAA,YACtC,gBAAgB,KAAK,iBAAiB;AAAA,YACtC,gBAAgB,KAAK,iBAAiB;AAAA,uCACX,gBAAgB;AAAA,uCAChB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,mCAcJ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAQH,QAAQ;AAAA,uCACD,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAiDhD;AACF;AAGA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,kBAAkB,MAAAZ,MAAK,IAAI;AACjD,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,UAAU,IAAI,EAAE,QAAQ,6BAA6B,IAAI,IAAI,4BAA4B,OAAO,OAAO,WAAW,UAAU,cAAc,gBAAgB,IAAI,IAAI,sBAAsB,OAAO,OAAO,WAAW,UAAU,cAAc,gBAAgB;AAC/P,SAAO,SAAS,gBAAgB,SAAS,CAAC,MAAM,GAAG,SAAS;AAC9D;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gCAAgC,MAAM;AAAA,EACxC,YAAY,SAAS,YAAY,cAAc;AAC7C,SAAK,gBAAgB,CAAC,IAAI;AAC1B,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc;AACnB,UAAM,CAAC,EAAE,SAAS,MAAM,IAAI;AAC5B,UAAM,CAAC,EAAE,SAAS,MAAM,IAAI;AAC5B,UAAM,iBAAiB;AAAA,MACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,MAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,IAC5C;AACA,UAAM,iBAAiB;AAAA,MACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,MAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,IAC5C;AACA,UAAM,cAAc,eAAe,KAAK,eAAe;AACvD,UAAM,aAAa,eAAe,KAAK,eAAe;AACtD,UAAM,iBAAiB,IAAI;AAC3B,UAAM,gBAAgB,IAAI;AAC1B,UAAM,YAAY,KAAK,KAAK,cAAc,IAAI,IAAI;AAClD,UAAM,WAAW,KAAK,KAAK,aAAa,IAAI,IAAI;AAChD,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0CAUsB;AAAA,yCACD;AAAA;AAAA,6CAEI;AAAA,4CACD;AAAA;AAAA,oCAER;AAAA,mCACD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAcD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oCAQE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,sDAMkB,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,qDAMX,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EA+B5D;AACF;AAGA,SAAS,oBAAoB,MAAM;AACjC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,GAAG,IAAI;AACvB,QAAM,EAAE,aAAa,IAAI;AACzB,QAAM,UAAU,IAAI,8BAA8B,GAAG,OAAO,OAAO,OAAO,YAAY;AACtF,SAAO,SAAS,gBAAgB,SAAS,CAAC,EAAE,GAAG,GAAG,KAAK;AACzD;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,+BAA+B,MAAM;AAAA,EACvC,YAAY,YAAY,WAAW,UAAU,cAAc,kBAAkB;AAC3E,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,CAAC;AACpB,UAAM,CAAC,OAAO,WAAW,UAAU,KAAK,IAAI;AAC5C,SAAK,cAAc,CAAC,OAAO,WAAW,UAAU,KAAK;AACrD,UAAM,kBAAkB;AAAA,MACtB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,UAAM,mBAAmB;AAAA,MACvB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,UAAM,YAAY,eAAe,QAAQ;AACzC,QAAI;AACJ,QAAI,kBAAkB;AACpB,0BAAoB;AAAA,IACtB,OAAO;AACL,0BAAoB;AAAA,IACtB;AACA,SAAK,WAAW;AAAA;AAAA,YAER,gBAAgB,KAAK,iBAAiB;AAAA,YACtC,gBAAgB,KAAK,iBAAiB;AAAA,uCACX,gBAAgB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,mCASpB;AAAA;AAAA;AAAA;AAAA,8DAI2B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAM5D;AACF;AAGA,IAAI,qCAAqC,MAAM;AAAA,EAC7C,YAAY,YAAY,WAAW,UAAU,cAAc,kBAAkB;AAC3E,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc,CAAC;AACpB,UAAM,CAAC,OAAO,WAAW,UAAU,KAAK,IAAI;AAC5C,SAAK,cAAc,CAAC,OAAO,WAAW,UAAU,KAAK;AACrD,UAAM,kBAAkB;AAAA,MACtB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,UAAM,mBAAmB;AAAA,MACvB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,UAAM,YAAY,eAAe,QAAQ;AACzC,QAAI;AACJ,QAAI,kBAAkB;AACpB,0BAAoB;AAAA,IACtB,OAAO;AACL,0BAAoB;AAAA,IACtB;AACA,SAAK,WAAW;AAAA;AAAA,YAER,gBAAgB,KAAK,iBAAiB;AAAA,YACtC,gBAAgB,KAAK,iBAAiB;AAAA,YACtC,gBAAgB,KAAK,iBAAiB;AAAA,uCACX,gBAAgB;AAAA,uCAChB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,mCAcJ;AAAA;AAAA;AAAA;AAAA,8DAI2B;AAAA;AAAA;AAAA,gCAG9B,QAAQ;AAAA,uCACD,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAchD;AACF;AAGA,SAAS,uBAAuB,MAAM;AACpC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,kBAAkB,MAAAA,MAAK,IAAI;AACjD,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,UAAU,IAAI,EAAE,QAAQ,6BAA6B,IAAI,IAAI,mCAAmC,OAAO,OAAO,WAAW,UAAU,cAAc,gBAAgB,IAAI,IAAI,6BAA6B,OAAO,OAAO,WAAW,UAAU,cAAc,gBAAgB;AAC7Q,SAAO,SAAS,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO,KAAK;AACjE;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,sCAAsC,MAAM;AAAA,EAC9C,YAAY,SAAS,YAAY,cAAc;AAC7C,SAAK,gBAAgB,CAAC,IAAI;AAC1B,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc;AACnB,UAAM,CAAC,EAAE,SAAS,MAAM,IAAI;AAC5B,UAAM,CAAC,EAAE,SAAS,MAAM,IAAI;AAC5B,UAAM,iBAAiB;AAAA,MACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,MAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,IAC5C;AACA,UAAM,iBAAiB;AAAA,MACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,MAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,IAC5C;AACA,UAAM,cAAc,eAAe,KAAK,eAAe;AACvD,UAAM,aAAa,eAAe,KAAK,eAAe;AACtD,UAAM,iBAAiB,IAAI;AAC3B,UAAM,gBAAgB,IAAI;AAC1B,UAAM,YAAY,KAAK,KAAK,cAAc,IAAI,IAAI;AAClD,UAAM,WAAW,KAAK,KAAK,aAAa,IAAI,IAAI;AAChD,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0CAUsB;AAAA,yCACD;AAAA;AAAA,6CAEI;AAAA,4CACD;AAAA;AAAA,oCAER;AAAA,mCACD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAcD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oCAQE;AAAA;AAAA;AAAA;AAAA;AAAA,sBAKd,eAAe;AAAA,sCACC,eAAe;AAAA;AAAA;AAAA,wBAG7B,eAAe;AAAA,wCACC,eAAe;AAAA;AAAA;AAAA,4BAG3B;AAAA,kBACV;AAAA;AAAA;AAAA;AAAA,4BAIU;AAAA,kBACV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAahB;AACF;AAGA,SAAS,2BAA2B,MAAM;AACxC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,GAAG,IAAI;AACvB,QAAM,EAAE,aAAa,IAAI;AACzB,QAAM,UAAU,IAAI,oCAAoC,GAAG,OAAO,OAAO,OAAO,YAAY;AAC5F,SAAO,SAAS,gBAAgB,SAAS,CAAC,EAAE,GAAG,GAAG,KAAK;AACzD;AACA,IAAI,mCAAmC;AAAA,EACrC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,QAAQ,MAAM;AACxB,SAAK,gBAAgB,CAAC,GAAG;AACzB,UAAM,OAAO,OAAO;AACpB,QAAI,OAAO,GAAG;AACZ,YAAM,IAAI,MAAM,kCAAkC,kCAAkC;AAAA,IACtF;AACA,SAAK,cAAc;AACnB,QAAI,SAAS,GAAG;AACd,WAAK,WAAW;AAAA;AAAA;AAAA,2BAGK,OAAO;AAAA;AAAA;AAG5B;AAAA,IACF;AACA,UAAM,aAAa,CAAC,OAAO;AACzB,UAAI,KAAK,QAAQ,EAAE,MAAM,MAAM,OAAO,QAAQ,GAAG;AAC/C,eAAO,GAAG,OAAO,gBAAgB;AAAA,MACnC;AACA,aAAO,UAAU;AAAA,IACnB;AACA,UAAM,WAAW,OAAO,IAAI,CAAC,GAAG,OAAO,WAAW,EAAE,CAAC,EAAE,KAAK,GAAG;AAC/D,UAAM,OAAO,kBAAkB,IAAI;AACnC,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA,yBACe;AAAA;AAAA;AAAA,EAGvB;AACF;AAGA,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,QAAQ,MAAM;AACxB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,UAAM,OAAO,OAAO;AACpB,QAAI,OAAO,GAAG;AACZ,YAAM,IAAI,MAAM,kCAAkC,kCAAkC;AAAA,IACtF;AACA,SAAK,cAAc;AACnB,UAAM,WAAW,YAAY,MAAM,IAAI;AACvC,UAAM,aAAa,GAAG,SAAS,OAAO,YAAY,KAAK,YAAY,OAAO;AAC1E,UAAM,UAAU,GAAG,SAAS,OAAO,YAAY,KAAK,YAAY,OAAO;AACvE,UAAM,OAAO,kBAAkB,IAAI;AACnC,QAAI,SAAS,GAAG;AACd,WAAK,WAAW;AAAA;AAAA;AAAA;AAAA,uCAIiB,OAAO;AAAA,cAChC,OAAO;AAAA,eACN;AAAA,2CAC4B,OAAO;AAAA,kBAChC,OAAO;AAAA;AAAA;AAAA;AAAA;AAAA,IAKrB,OAAO;AACL,WAAK,WAAW;AAAA;AAAA,YAEV;AAAA;AAAA,uBAEW,KAAK,SAAS,MAAM,CAAC;AAAA,eAC7B;AAAA,yBACU,KAAK,SAAS,MAAM,CAAC;AAAA;AAAA,eAE/B;AAAA,yBACU,KAAK,SAAS,MAAM,CAAC;AAAA,iBAC7B;AAAA,2BACU,KAAK,SAAS,MAAM,CAAC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAM5C;AACA,aAAS,KAAK,WAAW;AACvB,aAAO,WAAW,SAAS;AAAA,IAC7B;AACA,aAAS,KAAK,WAAW;AACvB,gBAAU,OAAO,KAAK,MAAM,UAAU,OAAO,KAAK;AAClD,aAAO,WAAW,SAAS;AAAA,IAC7B;AACA,aAAS,KAAK,WAAW;AACvB,gBAAU,OAAO,KAAK,MAAM,UAAU,OAAO,KAAK;AAClD,aAAO,WAAW,SAAS;AAAA,IAC7B;AACA,aAAS,KAAK,WAAW;AACvB,gBAAU,OAAO,KAAK,MAAM,UAAU,OAAO,KAAK;AAClD,gBAAU,OAAO,KAAK,MAAM,UAAU,OAAO,KAAK;AAClD,aAAO,WAAW,SAAS;AAAA,IAC7B;AACA,aAAS,WAAW,WAAW;AAC7B,YAAM,gBAAgB,OAAO,IAAI,CAAC,GAAG,OAAO,WAAW,IAAI,SAAS,CAAC;AACrE,YAAM,WAAW,cAAc,KAAK,GAAG;AACvC,YAAM,YAAY,cAAc,MAAM,EAAE,EAAE,KAAK,GAAG;AAClD,aAAO,mBAAmB,mBAAmB;AAAA,IAC/C;AACA,aAAS,WAAW,IAAI,WAAW;AACjC,UAAI,KAAK,QAAQ,EAAE,MAAM,MAAM,OAAO,QAAQ,GAAG;AAC/C,eAAO,GAAG,OAAO,SAAS,UAAU;AAAA,MACtC,OAAO;AACL,eAAO,GAAG,UAAU;AAAA,MACtB;AAAA,IACF;AAAA,EACF;AACF;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,aAAa,eAAe,MAAM,EAAE,KAAK;AACvD,MAAI,UAAU,GAAG;AACf,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD;AACA,QAAM,UAAU,IAAI,EAAE,QAAQ,6BAA6B,IAAI,IAAI,qBAAqB,EAAE,OAAO,KAAK,IAAI,IAAI,eAAe,EAAE,OAAO,KAAK;AAC3I,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACvD;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,YAAY,WAAW;AACjC,SAAK,gBAAgB,CAAC,OAAO;AAC7B,SAAK,cAAc,CAAC;AACpB,SAAK,iBAAiB,CAAC,EAAE,MAAM,UAAU,MAAM,OAAO,CAAC;AACvD,UAAM,cAAc,WAAW;AAC/B,UAAM,aAAa,WAAW;AAC9B,SAAK,cAAc;AACnB,QAAI,cAAc;AAClB,QAAI,OAAO,cAAc,UAAU;AACjC,oBAAc,uBAAuB,UAAU,QAAQ,CAAC;AAAA,IAC1D,OAAO;AACL,oBAAc;AAAA,2BACO,UAAU,KAAK,GAAG;AAAA;AAAA,IAEzC;AACA,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAWR;AAAA,uCAC2B,yCAAyC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAM9E;AACF;AAGA,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,UAAM,EAAE,SAAS,WAAW,OAAO,IAAI;AACvC,UAAM,eAAe;AACrB,UAAM,UAAU,IAAI,cAAc,OAAO,OAAO,SAAS;AACzD,UAAM,CAAC,SAAS,OAAO,IAAI,qBAAqB,eAAe,QAAQ,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE;AACvG,UAAM,eAAe,CAAC,CAAC,SAAS,SAAS,KAAK,IAAI,OAAO,GAAG,KAAK,IAAI,OAAO,CAAC,CAAC;AAC9E,UAAM,SAAS,aAAa,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO,OAAO,YAAY;AACzF,WAAO;AAAA,EACT;AACF;AAGA,IAAI,QAAQ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAgBZ,IAAI,SAAS,iBAAiB,EAAE,WAAW,MAAM,CAAC;AAClD,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ;AACZ,IAAI,SAAS,iBAAiB,EAAE,WAAW,OAAO,eAAe,aAAa,CAAC;AAC/E,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,YAAY,UAAU,aAAa,aAAaY,UAAS,OAAO,mBAAmB,MAAM;AACnG,SAAK,gBAAgB,CAAC,WAAW,WAAW,cAAc;AAC1D,SAAK,cAAc;AACnB,UAAM,cAAc,kBAAkBA,SAAQ,MAAM;AACpD,UAAM,QAAQ,kBAAkB,MAAM,MAAM;AAC5C,QAAI,gBAAgB;AACpB,QAAI,gBAAgB,GAAG;AACrB,sBAAgB;AAAA,IAClB,WAAW,gBAAgB,GAAG;AAC5B,sBAAgB;AAAA,IAClB;AACA,UAAM,iBAAiB,cAAc;AACrC,QAAI,gBAAgB;AACpB,QAAI,gBAAgB,GAAG;AACrB,sBAAgB;AAAA,IAClB,WAAW,gBAAgB,GAAG;AAC5B,sBAAgB;AAAA,IAClB;AACA,UAAM,iBAAiB,cAAc;AACrC,UAAM,eAAe,WAAW,IAAI,eAAe;AACnD,SAAK,WAAW;AAAA,UACV,yBAAyB,eAAeA;AAAA;AAAA;AAAA,YAGtC;AAAA;AAAA;AAAA,gCAGoB;AAAA;AAAA,kCAEE;AAAA,kCACA;AAAA,0CACQ;AAAA;AAAA;AAAA,uBAGnB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAOrB;AACF;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,SAAS,QAAQ,IAAI;AAC7B,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,EAAE,WAAW,YAAY,WAAW,SAAAA,UAAS,YAAAQ,YAAW,IAAI,qBAAqB,gBAAgB,SAAS,SAAS,KAAK;AAC9H,QAAM,eAAe,CAACA,cAAa,WAAW,SAAS;AACvD,MAAIA,gBAAe,GAAG;AACpB,WAAO,SAAS,eAAe,OAAO,QAAQ,KAAK;AAAA,EACrD;AACA,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,YAAY,SAAS,EAAE,EAAE,CAAC;AACxH,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,YAAY,SAAS,EAAE,EAAE,CAAC;AAClH,QAAM,eAAe,SAAS,eAAe,CAAC,GAAG,WAAW,IAAI,aAAa,CAAC,CAAC,CAAC,CAAC;AACjF,QAAM,UAAU,IAAI,eAAe,YAAY,WAAW,eAAe,MAAM,QAAQ,SAAS,MAAM,QAAQR,UAAS,YAAY;AACnI,QAAM,MAAM,SAAS,gBAAgB,SAAS,CAAC,UAAU,gBAAgB,YAAY,GAAG,SAAS,KAAK;AACtG,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AACrF,WAAS,8BAA8B,cAAc;AACrD,WAAS,8BAA8B,QAAQ;AAC/C,WAAS,8BAA8B,GAAG;AAC1C,WAAS,8BAA8B,YAAY;AACnD,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,WAAW,WAAW,WAAW,MAAM;AACjD,SAAK,gBAAgB,CAAC,kBAAkB,QAAQ;AAChD,SAAK,iBAAiB,CAAC,EAAE,MAAM,aAAa,MAAM,MAAM,CAAC;AACzD,SAAK,cAAc,CAAC,WAAW,SAAS;AACxC,UAAM,iBAAiB;AACvB,UAAM,iBAAiB,uBAAuB,KAAK,KAAK,KAAK,KAAK,YAAY,CAAC,CAAC;AAChF,UAAM,WAAW,IAAI,EAAE,UAAU,eAAe,MAAM,IAAI,iBAAiB;AAC3E,UAAM,kBAAkB,SAAS,SAAS,MAAM;AAChD,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,WAKT;AAAA;AAAA,+CAEoC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAmB7C;AACF;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,gBAAgB,OAAO,IAAI;AACnC,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,UAAU,IAAI,oBAAoB,eAAe,MAAM,IAAI,eAAe,MAAM,IAAI,OAAO,MAAM,IAAI,IAAI;AAC/G,QAAM,eAAe,CAAC,CAAC,eAAe,MAAM,EAAE,CAAC;AAC/C,SAAO,SAAS,gBAAgB,SAAS,CAAC,gBAAgB,MAAM,GAAG,SAAS,YAAY;AAC1F;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,OAAO,OAAO,MAAM;AAC9B,SAAK,gBAAgB,CAAC,KAAK,KAAK,GAAG;AACnC,SAAK,cAAc;AACnB,QAAI;AACJ,QAAI;AACJ,QAAI,OAAO,GAAG;AACZ,YAAM,MAAM,kBAAkB,2BAA2B;AAAA,IAC3D;AACA,QAAI,SAAS,GAAG;AACd,iBAAW;AACX,gBAAU;AAAA,IACZ,OAAO;AACL,YAAM,gBAAgB,CAAC,WAAW,WAAW,WAAW,SAAS;AACjE,YAAM,aAAa,CAAC;AACpB,YAAM,cAAc,CAAC;AACrB,eAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,oBAAY,KAAK,GAAG,cAAc,KAAK;AACvC,YAAI,KAAK,OAAO;AACd,qBAAW,KAAK,GAAG,cAAc,KAAK;AAAA,QACxC;AAAA,MACF;AACA,gBAAU,WAAW,KAAK;AAC1B,iBAAW,YAAY,KAAK;AAAA,IAC9B;AACA,UAAM,QAAQ,kBAAkB,IAAI;AACpC,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA,4BACkB;AAAA;AAAA,2BAED;AAAA;AAAA,2BAEA;AAAA;AAAA;AAAA;AAAA,EAIzB;AACF;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,WAAW,GAAG,IAAI,GAAG,GAAG,IAAI;AACpC,QAAM,UAAU,IAAI,cAAc,UAAU,MAAM,QAAQ,GAAG,OAAO,GAAG,MAAM,MAAM;AACnF,SAAO,SAAS,gBAAgB,SAAS,CAAC,WAAW,IAAI,EAAE,GAAG,WAAW,GAAG,OAAO,GAAG,KAAK,CAAC;AAC9F;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AAAA;AAAA;AAAA,uBAGY,qBAAqB;AAAA,kBAC1B,qBAAqB;AAAA;AAAA;AAGvC,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW,0BAA0B;AAAA;AAAA;AAGzC,IAAI,iBAAiB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWrB,IAAI,WAAW,iBAAiB;AAAA,EAC9B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,eAAe;AACjB,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AAAA;AAAA;AAAA;AAIX,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM,0BAA0B;AAAA;AAAA;AAGpC,IAAI,OAAO,iBAAiB,EAAE,WAAW,IAAI,CAAC;AAC9C,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AAAA;AAAA;AAAA;AAIX,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAqBf,IAAI,YAAY,iBAAiB,EAAE,WAAW,SAAS,CAAC;AACxD,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kBAAkB,CAAC,SAAS;AAC9B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAS,IAAI;AACjC,eAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,sEAAsE;AACrH,QAAM,QAAQ,WAAW,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAC/C,QAAM,mBAAmB,CAAC,CAAC,GAAG,CAAC,CAAC;AAChC,mBAAiB,KAAK,GAAG,QAAQ;AACjC,WAAS,KAAK,IAAI,WAAW,QAAQ,KAAK,EAAE,MAAM,QAAQ,EAAE,IAAI;AAC9D,qBAAiB,KAAK,CAAC,GAAG,CAAC,CAAC;AAAA,EAC9B;AACA,QAAM,YAAY,CAAC;AACnB,QAAM,UAAU,OAAO;AAAA,IACrB,QAAQ,EAAE,EAAE;AAAA,IACZ,SAAS;AAAA,IACT,OAAO,EAAE,UAAU,kBAAkB,eAAe,EAAE;AAAA,EACxD,CAAC;AACD,QAAM,sBAAsB,qBAAqB,YAAY,QAAQ,OAAO,YAAY,OAAO,KAAK;AACpG,QAAM,oCAAoC,qBAAqB,YAAY,oBAAoB,QAAQ,WAAW,QAAQ,KAAK;AAC/H,QAAM,eAAe,qBAAqB,oBAAoB,QAAQ,OAAO,YAAY,OAAO,KAAK;AACrG,QAAM,kBAAkB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,oBAAoB,EAAE,CAAC;AACrH,QAAM,WAAW,WAAW;AAAA,IAC1B,QAAQ,EAAE,GAAG,gBAAgB;AAAA,IAC7B,SAAS;AAAA,IACT,OAAO,EAAE,MAAM,kCAAkC;AAAA,EACnD,CAAC;AACD,QAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,aAAa,EAAE,CAAC;AACtG,YAAU,KAAK,OAAO;AACtB,YAAU,KAAK,eAAe;AAC9B,YAAU,KAAK,QAAQ;AACvB,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,SAAO;AACT;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,SAAS,QAAQ,YAAY,aAAa,IAAI;AACtD,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,WACT,WAAW,OAAO;AAAA,EAC3B;AACA,MAAI,QAAQ,MAAM,WAAW,GAAG;AAC9B,UAAM,IAAI,MAAM;AAAA,WACT,QAAQ,OAAO;AAAA,EACxB;AACA,MAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,UAAM,IAAI,MAAM;AAAA,WACT,OAAO,OAAO;AAAA,EACvB;AACA,MAAI,aAAa,MAAM,WAAW,GAAG;AACnC,UAAM,IAAI,MAAM;AAAA,UACV,aAAa,OAAO;AAAA,EAC5B;AACA,QAAM,WAAW,SAAS,SAAS,QAAQ,MAAM;AACjD,QAAM,UAAU,SAAS,SAAS,OAAO,MAAM;AAC/C,QAAM,cAAc,SAAS,SAAS,WAAW,MAAM;AACvD,QAAM,gBAAgB,SAAS,SAAS,aAAa,MAAM,EAAE;AAC7D,QAAM,CAAC,eAAe,oBAAoB,cAAc,mBAAmB,eAAe,IAAI,2BAA2B,UAAU,QAAQ,OAAO,QAAQ,OAAO,SAAS,OAAO,OAAO,aAAa,aAAa;AAClN,SAAO;AAAA,IACL,SAAS,eAAe,oBAAoB,QAAQ,OAAO,aAAa;AAAA,IACxE,SAAS,eAAe,CAAC,mBAAmB,EAAE,GAAG,OAAO,OAAO,YAAY;AAAA,IAC3E,SAAS,eAAe,CAAC,kBAAkB,MAAM,GAAG,QAAQ,IAAI,WAAW,kBAAkB,IAAI,CAAC,UAAU,OAAO,KAAK,CAAC,CAAC,CAAC;AAAA,IAC3H,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,QAAQ,OAAO,IAAI,WAAW,eAAe,CAAC;AAAA,EAClG;AACF;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,cAAc,YAAY,SAAS,IAAI;AAC/C,MAAI,aAAa,MAAM,WAAW,GAAG;AACnC,UAAM,IAAI,MAAM,uDAAuD,aAAa,OAAO;AAAA,EAC7F;AACA,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM,qDAAqD,WAAW,OAAO;AAAA,EACzF;AACA,MAAI,SAAS,MAAM,WAAW,GAAG;AAC/B,UAAM,IAAI,MAAM,sDAAsD,SAAS,OAAO;AAAA,EACxF;AACA,QAAM,cAAc,MAAM,KAAK,SAAS,SAAS,WAAW,MAAM,CAAC;AACnE,QAAM,gBAAgB,SAAS,SAAS,aAAa,MAAM;AAC3D,QAAM,cAAc,MAAM,KAAK,SAAS,SAAS,SAAS,MAAM,CAAC;AACjE,QAAM,CAAC,YAAY,cAAc,WAAW,IAAI,qBAAqB,eAAe,aAAa,OAAO,aAAa,OAAO,aAAa,WAAW;AACpJ,SAAO;AAAA,IACL,SAAS,eAAe,cAAc,aAAa,OAAO,UAAU;AAAA,IACpE,SAAS,eAAe,CAAC,YAAY,MAAM,GAAG,SAAS,OAAO,IAAI,WAAW,WAAW,CAAC;AAAA,EAC3F;AACF;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,mBAAmB,MAAM;AAChC,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,MAAM,SAAS,WAAW,IAAI;AACtC,MAAI,KAAK,MAAM,SAAS,GAAG;AACzB,UAAM,IAAI,MAAM,2DAA2D;AAAA,EAC7E;AACA,MAAI,QAAQ,MAAM,WAAW,GAAG;AAC9B,UAAM,IAAI,MAAM;AAAA,gBACJ,QAAQ,OAAO;AAAA,EAC7B;AACA,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,gBACJ,WAAW,OAAO;AAAA,EAChC;AACA,QAAM,QAAQ,SAAS,SAAS,KAAK,MAAM;AAC3C,QAAM,WAAW,SAAS,SAAS,QAAQ,MAAM;AACjD,QAAM,cAAc,SAAS,SAAS,WAAW,MAAM;AACvD,QAAM,CAAC,YAAY,eAAe,IAAI,8BAA8B,OAAO,KAAK,OAAO,KAAK,OAAO,UAAU,aAAa,IAAI;AAC9H,SAAO,SAAS,eAAe,iBAAiB,KAAK,OAAO,UAAU;AACxE;AACA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,kBAAkB,MAAM;AAC/B,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,MAAM,SAAS,WAAW,IAAI;AACtC,MAAI,KAAK,MAAM,SAAS,GAAG;AACzB,UAAM,IAAI,MAAM,2DAA2D;AAAA,EAC7E;AACA,MAAI,QAAQ,MAAM,WAAW,GAAG;AAC9B,UAAM,IAAI,MAAM;AAAA,eACL,QAAQ,OAAO;AAAA,EAC5B;AACA,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,eACL,WAAW,OAAO;AAAA,EAC/B;AACA,QAAM,QAAQ,SAAS,SAAS,KAAK,MAAM;AAC3C,QAAM,WAAW,SAAS,SAAS,QAAQ,MAAM;AACjD,QAAM,cAAc,SAAS,SAAS,WAAW,MAAM;AACvD,QAAM,CAAC,YAAY,eAAe,IAAI,8BAA8B,OAAO,KAAK,OAAO,KAAK,OAAO,UAAU,WAAW;AACxH,SAAO,SAAS,eAAe,iBAAiB,KAAK,OAAO,UAAU;AACxE;AACA,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,eAAe,cAAc,aAAa,IAAI;AACtD,QAAM,EAAE,YAAY,IAAI;AACxB,QAAM,EAAE,WAAW,YAAY,WAAW,SAAAA,UAAS,YAAAQ,YAAW,IAAI,qBAAqB,gBAAgB,cAAc,eAAe,WAAW;AAC/I,QAAM,iBAAiB;AACvB,MAAI,aAAa,UAAU,UAAU;AACnC,UAAM,aAAa,SAAS,WAAW,aAAa;AACpD,UAAM,aAAa,SAAS,WAAW,YAAY;AACnD,UAAM,gBAAgB,aAAa,aAAa,SAAS,SAAS,aAAa,MAAM,EAAE,EAAE;AACzF,UAAM,SAAS,eAAe,YAAY,YAAY,aAAaA,aAAY,WAAW,YAAY,WAAWR,UAAS,eAAe,cAAc;AACvJ,WAAO,SAAS,eAAe,aAAa,OAAO,OAAO,OAAO,MAAM;AAAA,EACzE;AACA,QAAM,UAAU,IAAI,eAAe,YAAY,WAAW,cAAc,MAAM,QAAQ,aAAa,MAAM,QAAQA,UAAS,CAACQ,aAAY,CAAC,GAAG,cAAc;AACzJ,QAAM,MAAM,SAAS,gBAAgB,SAAS,CAAC,cAAc,eAAe,YAAY,GAAG,aAAa,KAAK;AAC7G,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAClG,WAAS,8BAA8B,GAAG;AAC1C,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,iBAAiB,KAAK,IAAI;AAClC,QAAM,QAAQ,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AACzD,QAAM,aAAa,qBAAqB,iBAAiB,GAAG,iBAAiB,KAAK;AAClF,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,IAAI,MAAM,KAAK,EAAE,KAAK,CAAC;AACrC,QAAMpB,QAAO,EAAE,MAAM,MAAM;AAC3B,SAAO,WAAW,IAAI,CAAC,OAAO;AAC5B,UAAM,YAAY,CAAC,GAAGA,KAAI;AAC1B,cAAU,SAAS;AACnB,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,MAAM,UAAU,EAAE,CAAC;AAC7F,UAAM,UAAU;AAChB,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AACX,IAAI,QAAQ,iBAAiB,EAAE,WAAW,MAAM,iBAAiB,MAAM,eAAe,YAAY,CAAC;AACnG,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS;AACb,IAAI,UAAU,iBAAiB,EAAE,WAAW,OAAO,CAAC;AACpD,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,qBAAqB;AACzB,IAAI,qBAAqB,kBAAkB,EAAE,WAAW,oBAAoB,iBAAiB,mBAAmB,CAAC;AACjH,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,GAAG;AACnD,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,YAAY,oBAAoB;AAAA,mCACL,MAAM;AAAA;AAEvC,QAAM,UAAU,IAAI,eAAe,EAAE,OAAO,SAAS;AACrD,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACvD;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,OAAOY,UAASZ,OAAM;AAChC,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAcA;AACnB,UAAM,OAAOA,MAAK;AAClB,UAAM,aAAa,kBAAkBA,MAAK,MAAM;AAChD,UAAM,QAAQ,kBAAkBA,MAAK,MAAM;AAC3C,QAAI,YAAY;AAChB,QAAI,SAAS,GAAG;AACd,kBAAY;AAAA,IACd,OAAO;AACL,UAAI,aAAa;AACjB,kBAAYA,MAAK,IAAI,CAAC,GAAG,OAAO;AAC9B;AACA,eAAOA,MAAK,WAAW,IAAI,oBAAoB,eAAe,QAAQ,UAAU,aAAa,gBAAgB,eAAe;AAAA,MAC9H,CAAC,EAAE,KAAK,GAAG;AAAA,IACb;AACA,SAAK,WAAW;AAAA,QACZ,sBAAsB,cAAc;AAAA,QACpC,wBAAwB,cAAcY;AAAA;AAAA;AAAA,UAGpC;AAAA,yBACe;AAAA;AAAA;AAAA,EAGvB;AACF;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAO,KAAK,SAAAA,UAAS,WAAW,SAAS,cAAc,aAAa,eAAe,IAAI;AAC/F,QAAM,EAAE,kBAAkB,YAAY,YAAY,WAAW,eAAe,OAAO,QAAQ,KAAK,MAAM,SAAS,SAAS,IAAI,mBAAmB,UAAU,EAAE,OAAO,OAAO,KAAKA,UAAS,WAAW,SAAS,cAAc,aAAa,cAAc;AACpP,MAAI;AACJ,MAAI,YAAY;AACd,aAAS,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAAA,EACtF,WAAW,aAAa,eAAe;AACrC,iBAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,yCAAyC,EAAE,MAAM,QAAQ;AACxG,UAAMZ,QAAO,mBAAmB,gBAAgB,QAAQ,MAAM,QAAQ;AACtE,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,QAAQ,MAAAA,MAAK,EAAE,CAAC;AAC1F,aAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAC5F,aAAS,8BAA8B,MAAM;AAAA,EAC/C,OAAO;AACL,UAAM,qBAAqB,SAAS,mBAAmB,CAAC,CAAC,CAAC;AAC1D,QAAI,oBAAoB;AACtB,YAAM,SAAS,SAAS,SAAS,EAAE,MAAM;AACzC,YAAM,OAAO,OAAO,EAAE,OAAO,EAAE,OAAO,MAAM;AAC5C,YAAM,eAAe,oBAAoB,kBAAkB,MAAM,UAAU,MAAM;AACjF,eAAS,SAAS,eAAe,YAAY,EAAE,OAAO,aAAa,MAAM;AAAA,IAC3E,OAAO;AACL,YAAM,UAAU,IAAI,oBAAoB,QAAQ,UAAU,gBAAgB;AAC1E,eAAS,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AAAA,IACzD;AAAA,EACF;AACA,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAC1G,WAAS,8BAA8B,MAAM;AAC7C,SAAO;AACT;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,WAAW,aAAa,SAAS,UAAU,WAAW,UAAU,uBAAuB,IAAI;AACnG,QAAM,EAAE,MAAM,WAAW,IAAI;AAC7B,QAAM,QAAQ,SAAS,SAAS,KAAK,MAAM;AAC3C,QAAM,cAAc,SAAS,SAAS,WAAW,MAAM;AACvD,QAAM,CAAC,QAAQ,YAAY,IAAI,oBAAoB,OAAO,aAAa,WAAW,aAAa,SAAS,WAAW,UAAU,sBAAsB;AACnJ,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,OAAO,MAAM,GAAG,UAAU,MAAM;AAAA,IACzD,SAAS,eAAe,WAAW,OAAO,SAAS,YAAY;AAAA,EACjE;AACF;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,UAAU,IAAI;AACtB,QAAM,EAAE,OAAO,QAAQ,UAAU,IAAI;AACrC,MAAI,OAAO,UAAU,UAAU;AAC7B,UAAM,IAAI,MAAM,kCAAkC;AAAA,EACpD;AACA,MAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,UAAM,IAAI,MAAM,sCAAsC,OAAO,OAAO;AAAA,EACtE;AACA,MAAI,UAAU,MAAM,WAAW,GAAG;AAChC,UAAM,IAAI,MAAM,0CAA0C,UAAU,OAAO;AAAA,EAC7E;AACA,QAAM,SAAS,SAAS,SAAS,OAAO,MAAM;AAC9C,QAAM,aAAa,SAAS,SAAS,UAAU,MAAM,EAAE;AACvD,QAAM,CAAC,SAAS,QAAQ,KAAK,IAAI,mBAAmB,QAAQ,YAAY,SAAS;AACjF,QAAMoB,cAAa,OAAO;AAC1B,SAAO;AAAA,IACL,SAAS,eAAe,CAACA,aAAY,CAAC,GAAG,SAAS,OAAO;AAAA,IACzD,SAAS,eAAe,CAACA,WAAU,GAAG,UAAU,MAAM;AAAA,IACtD,SAAS,eAAe,CAAC,CAAC,GAAG,SAAS,IAAI,WAAW,KAAK,CAAC;AAAA,EAC7D;AACF;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,wBAAwB,MAAM;AACrC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,WAAW,IAAI;AACvB,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,MAAI,OAAO,UAAU,UAAU;AAC7B,UAAM,IAAI,MAAM,kCAAkC;AAAA,EACpD;AACA,MAAI,cAAc,GAAG;AACnB,UAAM,IAAI,MAAM,sCAAsC;AAAA,EACxD;AACA,QAAM,SAAS,SAAS,SAAS,OAAO,MAAM;AAC9C,QAAM,SAAS,8BAA8B,QAAQ,UAAU;AAC/D,SAAO,SAAS,eAAe,OAAO,OAAO,SAAS,MAAM;AAC9D;AACA,IAAI,gCAAgC;AAAA,EAClC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM;AACV,IAAI,OAAO,iBAAiB,EAAE,WAAW,IAAI,CAAC;AAC9C,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AAAA;AAAA;AAAA;AAIX,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,QAAQ,MAAM;AACxB,SAAK,gBAAgB,CAAC,GAAG;AACzB,UAAM,cAAc,IAAI,MAAM,OAAO,MAAM;AAC3C,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,MAAM;AAC9C,kBAAY,MAAM,OAAO,MAAM,KAAK;AAAA,IACtC;AACA,SAAK,cAAc;AACnB,SAAK,OAAO,YAAY;AACxB,UAAM,QAAQ,kBAAkB,KAAK,IAAI;AACzC,UAAM,eAAe,iBAAiB,MAAM;AAC5C,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA,yBACe;AAAA;AAAA;AAAA,EAGvB;AACF;AACA,SAAS,iBAAiB,QAAQ;AAChC,QAAM,OAAO,OAAO;AACpB,MAAI,OAAO,GAAG;AACZ,UAAM,MAAM,iBAAiB,2BAA2B;AAAA,EAC1D;AACA,MAAI,SAAS,GAAG;AACd,WAAO,eAAe,OAAO;AAAA,EAC/B;AACA,QAAM,gBAAgB,CAAC,WAAW,WAAW,WAAW,WAAW,SAAS;AAC5E,QAAM,eAAe,CAAC;AACtB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,iBAAa,KAAK,QAAQ,cAAc,QAAQ,OAAO,MAAM;AAAA,EAC/D;AACA,SAAO,aAAa,KAAK;AAC3B;AAGA,SAAS,MAAM,QAAQ;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,EAAE,UAAU,YAAY,EAAE,MAAM,SAAS,GAAG;AAC9C,UAAM,OAAO,SAAS,SAAS,EAAE,MAAM;AACvC,UAAM,QAAQ,EAAE,UAAU,WAAW,KAAK,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC,IAAI;AACrF,UAAM,MAAM,OAAO,EAAE,OAAO,EAAE,OAAO,KAAK;AAC1C,UAAM,SAAS,YAAY,KAAK,IAAI;AACpC,WAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAAA,EAC1E;AACA,QAAM,UAAU,IAAI,YAAY,EAAE,OAAO,IAAI;AAC7C,QAAM,SAAS,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AAC7D,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,OAAO;AACjB,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,iBAAiB;AAAA,MACpB,EAAE,MAAM,KAAK,MAAM,MAAM;AAAA,MACzB,EAAE,MAAM,aAAa,MAAM,MAAM;AAAA,MACjC,EAAE,MAAM,eAAe,MAAM,QAAQ;AAAA,MACrC,EAAE,MAAM,OAAO,MAAM,MAAM;AAAA,MAC3B,EAAE,MAAM,OAAO,MAAM,MAAM;AAAA,IAC7B;AACA,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAyClB;AACF;AACA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,OAAO;AACjB,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,iBAAiB;AAAA,MACpB,EAAE,MAAM,KAAK,MAAM,MAAM;AAAA,MACzB,EAAE,MAAM,aAAa,MAAM,MAAM;AAAA,MACjC,EAAE,MAAM,KAAK,MAAM,MAAM;AAAA,IAC3B;AACA,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAmClB;AACF;AAGA,SAAS,oCAAoC,UAAU,YAAY;AACjE,MAAI,eAAe,MAAM;AACvB,aAAS,8BAA8B,UAAU;AAAA,EACnD;AACF;AACA,SAAS,cAAc,KAAK;AAC1B,MAAI,QAAQ;AACZ,SAAO,QAAQ,KAAK;AAClB,aAAS;AAAA,EACX;AACA,SAAO;AACT;AACA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,2CAA2C,IAAI,EAAE,UAAU,0CAA0C;AAC3G,QAAM,+BAA+B,IAAI,EAAE,UAAU,8BAA8B;AACnF,QAAM,SAAS,EAAE;AACjB,QAAM,UAAU,OAAO,OAAO,SAAS;AACvC,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,KAAK,UAAU,4CAA4C,IAAI,8BAA8B;AAC9H,UAAM,QAAQ,SAAS,SAAS,EAAE,MAAM;AACxC,UAAM,CAAC,aAAa,cAAc,IAAI,YAAY,OAAO,QAAQ,EAAE,OAAO,GAAG,MAAM;AACnF,WAAO;AAAA,MACL,SAAS,eAAe,YAAY,OAAO,YAAY,OAAO,YAAY,MAAM;AAAA,MAChF,SAAS,eAAe,eAAe,OAAO,eAAe,OAAO,eAAe,MAAM;AAAA,IAC3F;AAAA,EACF;AACA,MAAI,MAAM,GAAG;AACX,WAAO,OAAO,SAAS,KAAK;AAC5B,WAAO;AAAA,MACL,SAAS,eAAe,QAAQ,EAAE,OAAO,CAAC,CAAC;AAAA,MAC3C,SAAS,eAAe,QAAQ,SAAS,CAAC,CAAC;AAAA,IAC7C;AAAA,EACF;AACA,MAAI,YAAY,GAAG;AACjB,WAAO;AAAA,MACL;AAAA,MACA,MAAM,EAAE,OAAO,EAAE,OAAO,QAAQ,OAAO,SAAS,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,IACjF;AAAA,EACF;AACA,QAAM,WAAW,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC9C,QAAM,YAAY,aAAa,QAAQ,SAAS;AAChD,QAAM,YAAY,YAAY,SAAS,aAAa,CAAC,IAAI;AACzD,QAAM,QAAQ,aAAa,cAAc,MAAM;AAC/C,QAAM,QAAQ,QAAQ;AACtB,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,OAAO,EAAE,OAAO,CAAC,OAAO,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AACxG,MAAI,WAAW;AACb,wCAAoC,UAAU,SAAS;AAAA,EACzD;AACA,QAAM,QAAQ,cAAc,CAAC;AAC7B,QAAM,cAAc,cAAc,OAAO;AACzC,MAAI,UAAU;AACd,QAAM,YAAY,MAAM,YAAY,OAAO,CAAC,KAAK,GAAG,IAAI,CAAC,KAAK,OAAO;AACrE,QAAM,UAAU,CAAC,KAAK,KAAK,UAAU;AACnC,UAAM,UAAU,UAAU;AAC1B,UAAM,UAAU,IAAI,YAAY,KAAK;AACrC,UAAM,WAAW,YAAY,OAAO,IAAI;AACxC,UAAM,eAAe,CAAC,CAAC,OAAO,GAAG,CAAC,QAAQ,GAAG,CAAC,OAAO,iBAAiB,GAAG,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC;AACrF,UAAM,eAAe;AACrB,cAAU,SAAS,gBAAgB,SAAS,SAAS,SAAS,YAAY;AAC1E,wCAAoC,UAAU,YAAY;AAAA,EAC5D;AACA,WAAS,MAAM,GAAG,MAAM,OAAO,OAAO,GAAG;AACvC,UAAM,MAAM,MAAM;AAClB,aAAS,MAAM,KAAK,OAAO,GAAG,OAAO,GAAG;AACtC,cAAQ,KAAK,KAAK,CAAC,OAAO,WAAW,CAAC;AAAA,IACxC;AAAA,EACF;AACA,WAAS,cAAc,aAAa,cAAc,OAAO,eAAe,GAAG;AACzE,UAAM,UAAU,UAAU;AAC1B,UAAM,eAAe,IAAI,aAAa,CAAC,OAAO,cAAc,CAAC,CAAC;AAC9D,UAAM,YAAY,YAAY,OAAO,IAAI;AACzC,UAAM,eAAe,CAAC,CAAC,OAAO,GAAG,CAAC,SAAS,GAAG,CAAC,KAAK,CAAC;AACrD,UAAM,eAAe;AACrB,cAAU,SAAS,gBAAgB,cAAc,SAAS,SAAS,YAAY;AAC/E,wCAAoC,UAAU,YAAY;AAC1D,UAAM,MAAM,QAAQ;AACpB,UAAM,MAAM,MAAM;AAClB,aAAS,MAAM,KAAK,OAAO,GAAG,OAAO,GAAG;AACtC,cAAQ,KAAK,KAAK,QAAQ,KAAK;AAAA,IACjC;AAAA,EACF;AACA,MAAI,cAAc;AAClB,YAAU,OAAO,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,GAAG,MAAM,CAAC,OAAO,CAAC,EAAE,EAAE,CAAC;AACrG,sCAAoC,UAAU,WAAW;AACzD,MAAI,SAAS,UAAU,EAAE,QAAQ,EAAE,GAAG,KAAK,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,GAAG,WAAW,EAAE,EAAE,CAAC;AAC3G,sCAAoC,UAAU,GAAG;AACjD,QAAM,WAAW,OAAO,MAAM,GAAG,EAAE;AACnC,WAAS,KAAK,CAAC;AACf,gBAAc;AACd,YAAU,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AAC5F,sCAAoC,UAAU,WAAW;AACzD,QAAM,aAAa;AACnB,WAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AAC1F,sCAAoC,UAAU,UAAU;AACxD,SAAO,CAAC,QAAQ,OAAO;AACzB;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,aAAa,YAAY,eAAe,UAAU,WAAW,UAAU;AACjF,SAAK,gBAAgB,CAAC,SAAS,YAAY;AAC3C,SAAK,cAAc;AACnB,UAAM,sBAAsB,kBAAkB,YAAY,IAAI;AAC9D,QAAI;AACJ,YAAQ;AAAA,WACD;AACH,qBAAa;AACb;AAAA,WACG;AACH,qBAAa;AACb;AAAA,WACG;AACH,qBAAa;AACb;AAAA,WACG;AACH,qBAAa;AACb;AAAA;AAEA,qBAAa;AACb;AAAA;AAEJ,SAAK,WAAW;AAAA;AAAA;AAAA,mBAGD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,2BAwBQ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,2BAiBA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,4CAUiB,0CAA0C;AAAA;AAAA;AAAA,sCAGhD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,sCAwBA;AAAA;AAAA;AAAA;AAAA,mDAIa;AAAA,mDACA;AAAA;AAAA,sBAE7B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAyBpB;AACF;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,WAAW,IAAI;AACtC,QAAM,EAAE,eAAe,UAAU,WAAW,YAAY,IAAI;AAC5D,QAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,QAAM,CAAC,WAAW,QAAQ,IAAI,eAAe,OAAO,cAAc,CAAC,aAAa,UAAU;AAC1F,QAAM,WAAW;AAAA,IACf;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACA,QAAM,UAAU,IAAI,iBAAiB,aAAa,YAAY,eAAe,UAAU,WAAW,QAAQ;AAC1G,SAAO,SAAS,gBAAgB,SAAS,CAAC,QAAQ,UAAU,GAAG,SAAS;AAC1E;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,EAAE,EAAE,IAAI;AACd,oBAAkB,GAAG,QAAQ;AAC7B,UAAQ,KAAK,aAAa,4DAA4D;AACtF,QAAM,SAAS,SAAS,SAAS,EAAE,MAAM;AACzC,QAAM,EAAE,cAAc,aAAa,QAAQ,IAAI,cAAc,QAAQ,MAAM,EAAE,OAAO,EAAE,KAAK;AAC3F,SAAO;AAAA,IACL,SAAS,eAAe,aAAa,EAAE,OAAO,YAAY;AAAA,IAC1D,SAAS,eAAe,CAAC,QAAQ,MAAM,GAAG,SAAS,OAAO;AAAA,EAC5D;AACF;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,IAAI;AAClB,MAAI,EAAE,KAAK,IAAI;AACf,MAAI,OAAO,GAAG;AACZ,YAAQ,MAAM,MAAM;AAAA,EACtB;AACA,QAAM,IAAI;AACV,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,MAAM,MAAM,MAAM;AACxB,QAAM,WAAW,IAAI,MAAM,QAAQ,CAAC;AACpC,MAAI,WAAW;AACf,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM;AACjC,QAAI,OAAO,MAAM;AACf,eAAS,cAAc,EAAE,MAAM;AAAA,IACjC;AAAA,EACF;AACA,QAAM,YAAY,CAAC;AACnB,QAAM,QAAQ,IAAI,MAAM,KAAK,EAAE,KAAK,CAAC;AACrC,QAAMpB,QAAO,EAAE,MAAM,MAAM;AAC3B,EAAAA,MAAK,QAAQ;AACb,QAAM,MAAM,IAAI,MAAM,GAAG;AACzB,WAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,MAAM;AACtC,UAAM,QAAQ;AACd,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,MAAAA,MAAK,EAAE,CAAC;AAClF,UAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAClG,QAAI,MAAM;AACV,cAAU,KAAK,MAAM;AAAA,EACvB;AACA,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,WAAW,WAAW;AAChC,SAAK,gBAAgB,CAAC,KAAK,YAAY;AACvC,UAAM,aAAa,UAAU;AAC7B,UAAM,YAAY,UAAU;AAC5B,UAAM,SAAS,UAAU;AACzB,UAAM,cAAc,UAAU;AAC9B,UAAM,UAAU,cAAc,KAAK,KAAK,SAAS,UAAU;AAC3D,SAAK,cAAc,CAAC,WAAW,OAAO;AACtC,UAAM,sBAAsB;AAC5B,UAAM,cAAc;AACpB,UAAM,wBAAwB,KAAK,MAAM,aAAa,CAAC,IAAI;AAC3D,UAAM,0BAA0B,aAAa;AAC7C,UAAM,gBAAgB;AAAA;AAAA;AAGtB,QAAI,wBAAwB;AAC5B,QAAI,SAAS,aAAa,GAAG;AAC3B,8BAAwB;AAAA,oCACM;AAAA;AAAA;AAAA;AAAA,IAIhC;AACA,QAAI,4BAA4B;AAChC,QAAI,SAAS,aAAa,GAAG;AAC3B,kCAA4B;AAAA,oCACE;AAAA;AAAA;AAAA;AAAA,IAIhC;AACA,SAAK,WAAW;AAAA,0CACsB;AAAA;AAAA;AAAA,UAGhC;AAAA;AAAA;AAAA;AAAA;AAAA,UAKA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YASE,yBAAyB;AAAA,wDACmB;AAAA;AAAA;AAAA;AAAA,8BAI1B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAgBlB;AAAA;AAAA;AAAA,iCAGqB;AAAA,cACnB,4BAA4B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAiB9B;AAAA,qBACS,4BAA4B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAerC;AAAA,qBACS,4BAA4B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAerC;AAAA;AAAA,oBAEQ;AAAA;AAAA;AAAA,EAGlB;AACF;AAGA,SAAS,oBAAoB,MAAM;AACjC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,WAAW,IAAI;AAC1B,QAAM,EAAE,YAAY,IAAI;AACxB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,YAAY,CAAC;AACnB,MAAI,OAAO;AACX,QAAM,cAAc,qBAAqB,mBAAmB,CAAC,IAAI,GAAG,KAAK;AACzE,MAAI,YAAY;AAChB,MAAI,eAAe,MAAM;AACvB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,YAAY,EAAE,CAAC;AACzF,cAAU,KAAK,SAAS;AACxB,WAAO,qBAAqB,iBAAiB,GAAG,KAAK,EAAE;AAAA,EACzD;AACA,QAAM,WAAW,qBAAqB,aAAa,gBAAgB,UAAU,OAAO,MAAM,WAAW;AACrG,QAAM,SAAS,aAAa,cAAc,CAAC,UAAU,MAAM,KAAK,CAAC;AACjE,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,IAAI,MAAM,EAAE,EAAE,CAAC;AACpG,YAAU,KAAK,GAAG;AAClB,QAAM,cAAc,WAAW,EAAE,KAAK;AACtC,QAAM,eAAe,CAAC,IAAI,WAAW,aAAa,OAAO,iBAAiB;AACxE,UAAM,YAAY,GAAG,MAAM;AAC3B,UAAM,UAAU,GAAG,MAAM;AACzB,UAAM,aAAa,qBAAqB,aAAa,8BAA8B,SAAS,YAAY;AACxG,UAAM,YAAY,EAAE,YAAY,QAAQ,SAAS,WAAW,aAAa,aAAa;AACtF,UAAM,UAAU,IAAI,iBAAiB,WAAW,SAAS;AACzD,UAAM,SAAS,SAAS,cAAc,SAAS,CAAC,IAAI,WAAW,GAAG,KAAK;AACvE,cAAU,KAAK,MAAM;AACrB,QAAI,OAAO,MAAM,OAAO,cAAc;AACpC,aAAO;AAAA,IACT;AACA,UAAM,YAAY,OAAO;AAAA,MACvB,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,GAAG,MAAM,cAAc,MAAM,GAAG,OAAO,UAAU;AAAA,IACnE,CAAC;AACD,UAAM,WAAW,MAAM;AAAA,MACrB,QAAQ,EAAE,GAAG,UAAU;AAAA,MACvB,SAAS;AAAA,MACT,OAAO,EAAE,MAAM,CAAC,UAAU,UAAU,EAAE;AAAA,IACxC,CAAC;AACD,cAAU,KAAK,SAAS;AACxB,cAAU,KAAK,QAAQ;AACvB,UAAM,UAAU,aAAa,QAAQ,WAAW,UAAU,OAAO,YAAY;AAC7E,WAAO;AAAA,EACT;AACA,QAAM,cAAc,aAAa,KAAK,sBAAsB,YAAY,aAAa,WAAW;AAChG,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,YAAY,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACvG,MAAI,SAAS;AACb,MAAI,eAAe,MAAM;AACvB,cAAU,KAAK,QAAQ;AACvB,UAAM,OAAO,qBAAqB,uBAAuB,WAAW;AACpE,aAAS,WAAW,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AAAA,EACnF;AACA,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,SAAO;AACT;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB;AAAA,EACnB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,WAAW,gBAAgB,gBAAgB;AACzC,iBAAe,YAAY;AAC7B;AAGA,IAAI;AAAA,CACH,SAAS,WAAW;AACnB,YAAU,UAAU,aAAa,KAAK;AACtC,YAAU,UAAU,WAAW,KAAK;AACpC,YAAU,UAAU,UAAU,KAAK;AACnC,YAAU,UAAU,YAAY,KAAK;AACrC,YAAU,UAAU,eAAe,KAAK;AAC1C,GAAG,aAAa,WAAW,CAAC,EAAE;AAC9B,IAAI;AAAA,CACH,SAAS,oBAAoB;AAC5B,qBAAmB,mBAAmB,YAAY,KAAK;AACvD,qBAAmB,mBAAmB,UAAU,KAAK;AACrD,qBAAmB,mBAAmB,WAAW,KAAK;AACtD,qBAAmB,mBAAmB,WAAW,KAAK;AACtD,qBAAmB,mBAAmB,eAAe,KAAK;AAC1D,qBAAmB,mBAAmB,aAAa,KAAK;AACxD,qBAAmB,mBAAmB,SAAS,KAAK;AACtD,GAAG,sBAAsB,oBAAoB,CAAC,EAAE;AAGhD,IAAI;AACJ,SAAS,MAAM,UAAU;AACvB,oBAAkB,SAAS,KAAK,MAAM,cAAc,MAAM;AAAA,IACxD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,iBAAiB,MAAM;AAC9B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,MAAM,uBAAuB,IAAI;AAC/C,MAAI,EAAE,UAAU,aAAa,EAAE,UAAU,WAAW;AAClD,UAAM,IAAI,MAAM,6DAA6D;AAAA,EAC/E;AACA,QAAM,EAAE,YAAY,YAAY,YAAY,aAAa,eAAe,IAAI;AAC5E,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,SAAS;AACb,MAAI,QAAQ,MAAM;AAChB,UAAM,WAAW,SAAS,UAAU,IAAI,KAAK,MAAM;AACnD,QAAI,SAAS,MAAM,WAAW,GAAG;AAC/B,YAAM,IAAI,MAAM,uDAAuD,SAAS,MAAM,SAAS;AAAA,IACjG;AACA,aAAS,SAAS;AAAA,EACpB;AACA,QAAM,2BAA2B,0BAA0B,OAAO,IAAI,SAAS,UAAU,IAAI,uBAAuB,MAAM,EAAE;AAC5H,QAAM,kBAAkB,kBAAkB;AAC1C,MAAI,mBAAmB,MAAM;AAC3B,UAAM,IAAI,MAAM,GAAG,+EAA+E;AAAA,EACpG;AACA,QAAM,UAAU,aAAa,EAAE,MAAM,KAAK,EAAE,MAAM;AAClD,QAAM,WAAW,aAAa,EAAE,MAAM,KAAK,EAAE,MAAM;AACnD,QAAM,YAAY,uBAAuB,2BAA2B,EAAE,MAAM,MAAM,GAAG,EAAE,GAAG,EAAE,MAAM,MAAM,GAAG,EAAE,CAAC;AAC9G,QAAM,MAAM,SAAS,WAAW,CAAC,GAAG,WAAW,SAAS,QAAQ,GAAG,EAAE,KAAK;AAC1E,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,kBAAgB,KAAK,aAAa,EAAE,MAAM,QAAQ,KAAK,aAAa,EAAE,MAAM,QAAQ,YAAY,YAAY,iBAAiB,QAAQ,0BAA0B,kBAAkB,GAAG,KAAK;AACzL,SAAO;AACT;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,wBAAwB,YAAY,SAAS;AACpD,MAAI;AACJ,WAAS,WAAW,UAAU;AAC5B,gBAAY,SAAS,KAAK,MAAM,YAAY,MAAM;AAAA,MAChD;AAAA,MACA;AAAA,MACA;AAAA,IACF,CAAC;AAAA,EACH;AACA,WAAS,YAAY,MAAM;AACzB,UAAM,EAAE,SAAS,UAAU,QAAQ,EAAE,EAAE,EAAE,IAAI;AAC7C,UAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,MAAM,SAAS,WAAW,EAAE,OAAO,WAAW,EAAE,KAAK;AAC3D,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAI,aAAa,cAAc,IAAI,KAAK,MAAM,GAAG;AAC/C,aAAO;AAAA,IACT;AACA,cAAU,KAAK,SAAS,EAAE,QAAQ,KAAK;AACvC,WAAO;AAAA,EACT;AACA,SAAO,EAAE,YAAY,aAAa,QAAQ,WAAW,YAAY,YAAY,YAAY;AAC3F;AAGA,IAAI,aAAa,wBAAwB,GAAG;AAG5C,SAAS,yBAAyB,YAAY,yBAAyB,OAAO;AAC5E,MAAI;AACJ,WAAS,WAAW,UAAU;AAC5B,gBAAY,SAAS,KAAK,MAAM,YAAY,MAAM;AAAA,MAChD;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF,CAAC;AAAA,EACH;AACA,WAAS,YAAY,MAAM;AACzB,UAAM,EAAE,SAAS,UAAU,OAAO,IAAI;AACtC,UAAM,EAAE,GAAG,EAAE,IAAI;AACjB,UAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,aAAa,SAAS,OAAO,QAAQ,EAAE;AAC7C,UAAM,WAAW,qBAAqB,2BAA2B,EAAE,OAAO,EAAE,KAAK;AACjF,UAAM,MAAM,SAAS,WAAW,UAAU,UAAU;AACpD,QAAI,aAAa,cAAc,QAAQ,MAAM,GAAG;AAC9C,aAAO;AAAA,IACT;AACA,UAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,UAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,UAAM,cAAc,MAAM,UAAU,KAAK,aAAa,EAAE,MAAM,QAAQ,KAAK,aAAa,EAAE,MAAM,QAAQ,SAAS,EAAE,QAAQ,KAAK;AAChI,gBAAY;AACZ,WAAO;AAAA,EACT;AACA,SAAO,EAAE,YAAY,aAAa,QAAQ,WAAW,YAAY,YAAY,YAAY;AAC3F;AAGA,IAAI,wBAAwB;AAC5B,IAAI,aAAa,yBAAyB,KAAK,qBAAqB;AAGpE,IAAI;AACJ,SAAS,UAAU,UAAU;AAC3B,aAAW,SAAS,KAAK,MAAM,MAAM,MAAM;AAAA,IACzC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,MAAM,SAAS,WAAW,OAAO,GAAG,OAAO,OAAO,GAAG,KAAK;AAChE,MAAI,aAAa,cAAc,IAAI,KAAK,MAAM,GAAG;AAC/C,WAAO;AAAA,EACT;AACA,QAAM,WAAW,OAAO,IAAI,CAAC,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE,EAAE;AACtE,QAAM,gBAAgB,IAAI,WAAW,IAAI,WAAW,QAAQ,EAAE,MAAM;AACpE,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,WAAS,eAAe,SAAS,QAAQ,SAAS,IAAI,QAAQ,KAAK;AACnE,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb;AAAA,EACA,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,IAAI;AAC7C,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,SAAS,SAAS,mBAAmB,CAAC;AAC5C,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,UAAQ,IAAI,MAAM;AAClB,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,kBAAgB,SAAS,KAAK,MAAM,WAAW,MAAM;AAAA,IACnD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,CAAC,cAAc,IAAI,IAAI,kBAAkB,OAAO,EAAE,OAAO,MAAM,IAAI;AACzE,MAAI,aAAa;AACjB,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,QAAI,KAAK,QAAQ,IAAI;AACnB,mBAAa;AAAA,IACf;AAAA,EACF;AACA,QAAM,WAAW,iBAAiB,OAAO,EAAE,OAAO,MAAM,IAAI;AAC5D,QAAM,IAAI;AAAA,IACR,QAAQ,OAAO,EAAE;AAAA,IACjB,OAAO;AAAA,IACP,OAAO,OAAO,EAAE;AAAA,EAClB;AACA,MAAI,YAAY;AACd,UAAM,SAAS,UAAU,EAAE,QAAQ,SAAS,SAAS,CAAC;AACtD,WAAO,QAAQ;AACf,WAAO;AAAA,EACT;AACA,QAAM,MAAM,SAAS,WAAW,UAAU,EAAE,KAAK;AACjD,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,YAAY,IAAI,WAAW,IAAI,WAAW,IAAI,EAAE,MAAM;AAC5D,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,gBAAc,KAAK,aAAa,EAAE,MAAM,QAAQ,SAAS,EAAE,QAAQ,OAAO,WAAW,KAAK,MAAM;AAChG,SAAO;AACT;AACA,SAAS,iBAAiB,SAAS,MAAM;AACvC,QAAM,WAAW,IAAI,MAAM,QAAQ,MAAM;AACzC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,aAAS,MAAM,QAAQ,KAAK;AAAA,EAC9B;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,OAAO,MAAM;AACtC,QAAM,WAAW,CAAC;AAClB,QAAM,UAAU,CAAC;AACjB,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,QAAI,MAAM,QAAQ,GAAG;AACnB,eAAS,KAAK,MAAM,GAAG;AAAA,IACzB;AACA,QAAI,MAAM,KAAK,SAAS,GAAG;AACzB,cAAQ,KAAK,KAAK,GAAG;AAAA,IACvB;AAAA,EACF;AACA,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC1C,QAAI,YAAY;AAChB,aAAS,IAAI,GAAG,IAAI,QAAQ,QAAQ,EAAE,GAAG;AACvC,UAAI,QAAQ,MAAM,OAAO,cAAc,MAAM,QAAQ,aAAa,QAAQ,KAAK;AAC7E,oBAAY;AAAA,MACd;AAAA,IACF;AACA,YAAQ,aAAa;AAAA,EACvB;AACA,SAAO,CAAC,UAAU,OAAO;AAC3B;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,SAAS,wBAAwB,GAAG,MAAM,UAAU;AAClD,QAAM,SAAS,EAAE;AACjB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,eAAe,aAAa,eAAe,MAAM,MAAM;AAC7D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,cAAc;AAClB,MAAI,qBAAqB;AACzB,MAAI,gBAAgB,MAAM;AACxB,UAAM,WAAW,IAAI,MAAM,KAAK;AAChC,aAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,eAAS,MAAM,OAAO,aAAa;AAAA,IACrC;AACA,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAC/D,kBAAc,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,MAAM,aAAa,GAAG,SAAS,SAAS,CAAC;AAC5F,UAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,eAAe,SAAS,UAAU,IAAI,YAAY,MAAM,EAAE;AAChE,QAAI,iBAAiB,KAAK;AACxB,2BAAqB;AAAA,IACvB;AAAA,EACF;AACA,SAAO,EAAE,YAAY,aAAa,cAAc,MAAM,mBAAmB;AAC3E;AAGA,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,YAAU,SAAS,KAAK,MAAM,KAAK,MAAM,CAAC,wBAAwB,CAAC;AACrE;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,cAAc,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AACxG,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,aAAS;AACT,cAAU;AAAA,EACZ;AACA,QAAM,YAAY,OAAO,MAAM;AAC/B,uBAAqB,2BAA2B,OAAO,MAAM,SAAS;AACtE,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,IAAI;AACjG,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,MAAM,SAAS,WAAW,UAAU,EAAE,KAAK;AACjD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,YAAQ,SAAS,YAAY,KAAK;AAAA,EACpC;AACA,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,YAAY;AAClF,QAAI,QAAQ;AAAA,EACd;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,YAAU,SAAS,KAAK,MAAM,KAAK,MAAM,CAAC,wBAAwB,CAAC;AACrE;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,cAAc,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AACxG,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,aAAS;AACT,cAAU;AAAA,EACZ;AACA,QAAM,YAAY,OAAO,MAAM;AAC/B,uBAAqB,2BAA2B,OAAO,MAAM,SAAS;AACtE,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,IAAI;AACjG,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,MAAM,SAAS,WAAW,UAAU,EAAE,KAAK;AACjD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,YAAQ,SAAS,YAAY,KAAK;AAAA,EACpC;AACA,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,YAAY;AAClF,QAAI,QAAQ;AAAA,EACd;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,cAAY,SAAS,KAAK,MAAM,QAAQ,MAAM;AAAA,IAC5C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AAC1F,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAI,iBAAiB,KAAK;AACxB,eAAS;AACT,gBAAU;AAAA,IACZ;AAAA,EACF;AACA,QAAM,WAAW,OAAO,MAAM,MAAM,GAAG,EAAE;AACzC,QAAM,MAAM,SAAS,WAAW,UAAU,OAAO;AACjD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,YAAY,aAAa,cAAc,IAAI,KAAK;AACtD,QAAM,YAAY,OAAO,MAAM,KAAK;AACpC,YAAU,SAAS,SAAS,OAAO,QAAQ,WAAW,WAAW,KAAK;AACtE,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,gBAAc,SAAS,KAAK,MAAM,SAAS,MAAM;AAAA,IAC/C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,IAAI,OAAO;AACjB,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,EAAE,YAAY,SAAAY,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,MAAM,eAAe;AAC9G,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,YAAY,SAAS,QAAQ;AACnC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,WAAW,SAAS;AAC1B,MAAI,SAAS,eAAe,gBAAgB;AAC1C,UAAM,IAAI,MAAM,6CAA6C,SAAS,yCAAyC;AAAA,EACjH;AACA,MAAI,SAAS,kBAAkB,KAAK,SAAS,mBAAmB,GAAG;AACjE,UAAM,IAAI,MAAM,0EAA0E,SAAS,mBAAmB,SAAS,iBAAiB;AAAA,EAClJ;AACA,QAAM,MAAM,SAAS,WAAW,SAAS,UAAU,SAAS;AAC5D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,cAAY,KAAK,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,cAAc,aAAa,QAAQ,UAAU,WAAW,SAAS,cAAc,aAAa,UAAU,KAAK;AAChK,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,MAAM,IAAI;AAC1B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,SAAS,aAAa,uBAAuB,OAAO,KAAK;AAC/D,eAAa,OAAO,UAAU,aAAa,cAAc,MAAM,GAAG,MAAM,cAAc,sBAAsB,EAAE,uEAAuE;AACrL,OAAK,QAAQ,OAAO,EAAE,MAAM;AAC5B,SAAO,EAAE,QAAQ,EAAE,QAAQ,OAAO,QAAQ,OAAO,EAAE,MAAM;AAC3D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,oBAAkB,SAAS,KAAK,MAAM,aAAa,MAAM;AAAA,IACvD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,EAAE,IAAI;AACjB,QAAM,EAAE,YAAY,WAAW,IAAI;AACnC,MAAI,EAAE,UAAU,aAAa,EAAE,UAAU,WAAW;AAClD,UAAM,IAAI,MAAM,4DAA4D;AAAA,EAC9E;AACA,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,oBAAoB,uBAAuB,2BAA2B,EAAE,MAAM,MAAM,GAAG,EAAE,GAAG,EAAE,MAAM,MAAM,GAAG,EAAE,CAAC;AACtH,QAAM,WAAW,kBAAkB,OAAO,CAAC,aAAa,WAAW,CAAC;AACpE,eAAa,OAAO,gBAAgB,aAAa,MAAM,kCAAkC,qBAAqB,uCAAuC,EAAE,aAAa,EAAE,wBAAwB,6BAA6B,wBAAwB;AACnP,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,UAAU,aAAa,IAAI,MAAM,KAAK,IAAI,MAAM;AACtD,QAAM,WAAW,aAAa,IAAI,MAAM,KAAK,IAAI,MAAM;AACvD,QAAM,WAAW,KAAK,IAAI,WAAW,SAAS;AAC9C,QAAM,MAAM,SAAS,WAAW,CAAC,UAAU,SAAS,QAAQ,GAAG,IAAI,KAAK;AACxE,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,IAAI,KAAK,EAAE,MAAM;AACnE,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,IAAI,KAAK,EAAE,MAAM;AACnE,kBAAgB,OAAO,aAAa,IAAI,MAAM,QAAQ,OAAO,aAAa,IAAI,MAAM,QAAQ,YAAY,YAAY,KAAK;AACzH,WAAS,YAAY,IAAI,MAAM;AAC/B,WAAS,YAAY,IAAI,MAAM;AAC/B,MAAI,QAAQ;AACZ,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,OAAO,MAAAZ,MAAK,GAAG,SAAS,SAAS,IAAI;AACrE,QAAM,CAAC,QAAQ,KAAK,IAAI,mBAAmB,iBAAiB,GAAG,OAAOA,KAAI;AAC1E,QAAM,cAAc,mBAAmB,iBAAiB,EAAE,OAAO,QAAQ,KAAK;AAC9E,QAAM,QAAQ,SAAS,SAAS,EAAE,MAAM;AACxC,QAAM,MAAM,SAAS,WAAW,OAAO,EAAE,KAAK;AAC9C,QAAM,WAAW,aAAa,eAAe,EAAE,KAAK;AACpD,QAAM,UAAU,SAAS,UAAU,IAAI,IAAI,MAAM;AACjD,MAAI,aAAa;AACf,UAAM,aAAa,mBAAmB,kBAAkB,QAAQ,QAAQ;AACxE,QAAI,EAAE,UAAU,UAAU;AACxB,cAAQ,cAAc,MAAM,MAAM,YAAY,aAAa,aAAa,cAAc,KAAK,CAAC;AAAA,IAC9F,OAAO;AACL,YAAM,WAAW,SAAS,mBAAmB,GAAG;AAChD,eAAS,IAAI,MAAM,SAAS,YAAY,aAAa,aAAa,cAAc,KAAK,CAAC,CAAC;AAAA,IACzF;AACA,WAAO;AAAA,EACT;AACA,MAAI,EAAE,UAAU,UAAU;AACxB,UAAM,MAAM,UAAU,OAAO,QAAQ,OAAO,EAAE,OAAO,EAAE,KAAK;AAC5D,YAAQ,cAAc;AACtB,WAAO;AAAA,EACT;AACA,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,QAAM,OAAO,EAAE,MAAM;AACrB,MAAI,SAAS,GAAG;AACd,aAAS,OAAO,SAAS,IAAI,SAAS,QAAQ,KAAK;AAAA,EACrD,WAAW,SAAS,GAAG;AACrB,aAAS,OAAO,SAAS,IAAI,SAAS,IAAI,SAAS,QAAQ,KAAK;AAAA,EAClE,WAAW,SAAS,GAAG;AACrB,aAAS,OAAO,SAAS,IAAI,SAAS,IAAI,SAAS,IAAI,SAAS,QAAQ,KAAK;AAAA,EAC/E,OAAO;AACL,UAAM,MAAM,UAAU,OAAO,QAAQ,OAAO,EAAE,OAAO,EAAE,KAAK;AAC5D,YAAQ,IAAI,GAAG;AAAA,EACjB;AACA,SAAO;AACT;AACA,SAAS,SAAS,OAAO,SAAS,SAAS,OAAOA,OAAM;AACtD,MAAI,YAAY;AAChB,QAAM,SAAS,MAAM;AACrB,QAAM,SAAS,MAAM;AACrB,QAAM,OAAO,SAASA,MAAK;AAC3B,WAAS,KAAK,QAAQ,KAAK,MAAM,MAAM;AACrC,UAAM,UAAU,KAAK,UAAU;AAC/B,YAAQ,IAAI,MAAM,SAAS,SAAS,UAAUA,MAAK,EAAE,GAAG,SAAS;AACjE,iBAAaA,MAAK;AAAA,EACpB;AACF;AACA,SAAS,SAAS,OAAO,UAAU,UAAU,SAAS,OAAOA,OAAM;AACjE,MAAI,YAAY;AAChB,QAAM,SAAS,MAAM;AACrB,QAAM,SAAS,MAAM;AACrB,QAAM,SAAS,MAAM;AACrB,QAAM,OAAO,SAASA,MAAK;AAC3B,QAAM,OAAO,SAASA,MAAK;AAC3B,WAAS,KAAK,QAAQ,KAAK,MAAM,MAAM;AACrC,aAAS,IAAI,QAAQ,IAAI,MAAM,KAAK;AAClC,YAAM,UAAU,KAAK,WAAW,IAAI,WAAW;AAC/C,cAAQ,IAAI,MAAM,SAAS,SAAS,UAAUA,MAAK,EAAE,GAAG,SAAS;AACjE,mBAAaA,MAAK;AAAA,IACpB;AAAA,EACF;AACF;AACA,SAAS,SAAS,OAAO,UAAU,UAAU,UAAU,SAAS,OAAOA,OAAM;AAC3E,MAAI,YAAY;AAChB,QAAM,SAAS,MAAM;AACrB,QAAM,SAAS,MAAM;AACrB,QAAM,SAAS,MAAM;AACrB,QAAM,OAAO,SAASA,MAAK;AAC3B,QAAM,OAAO,SAASA,MAAK;AAC3B,QAAM,OAAO,SAASA,MAAK;AAC3B,QAAM,SAAS,MAAM;AACrB,WAAS,KAAK,QAAQ,KAAK,MAAM,MAAM;AACrC,aAAS,IAAI,QAAQ,IAAI,MAAM,KAAK;AAClC,eAAS,IAAI,QAAQ,IAAI,MAAM,KAAK;AAClC,cAAM,UAAU,KAAK,WAAW,IAAI,WAAW,IAAI,WAAW;AAC9D,gBAAQ,IAAI,MAAM,SAAS,SAAS,UAAUA,MAAK,EAAE,GAAG,SAAS;AACjE,qBAAaA,MAAK;AAAA,MACpB;AAAA,IACF;AAAA,EACF;AACF;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,MAAM,IAAI;AAC9B,QAAM,QAAQ,WAAW,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAC/C,QAAM,WAAW,qBAAqB,YAAY,EAAE,OAAO,YAAY,KAAK;AAC5E,QAAM,WAAW,qBAAqB,YAAY,SAAS,QAAQ,WAAW,MAAM;AACpF,QAAM,mBAAmB,qBAAqB,oBAAoB,EAAE,OAAO,YAAY,KAAK;AAC5F,QAAM,mBAAmB,qBAAqB,oBAAoB,OAAO,WAAW,MAAM;AAC1F,QAAM,YAAY,qBAAqB,aAAa,kBAAkB,OAAO,WAAW,MAAM;AAC9F,QAAM,YAAY,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC3F,QAAM,cAAc,WAAW,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,SAAS,EAAE,CAAC;AACzG,QAAM,sBAAsB,SAAS,EAAE,QAAQ,EAAE,GAAG,YAAY,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,iBAAiB,EAAE,CAAC;AAC1H,QAAM,SAAS,OAAO;AAAA,IACpB,QAAQ,EAAE,GAAG,oBAAoB;AAAA,IACjC,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,kBAAkB,MAAM,UAAU;AAAA,EACpD,CAAC;AACD,WAAS,YAAY,UAAU,MAAM;AACrC,WAAS,YAAY,YAAY,MAAM;AACvC,WAAS,YAAY,UAAU,MAAM;AACrC,SAAO;AACT;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,MAAM,GAAG,SAAS,SAAS,IAAI;AAC/D,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,KAAK;AAC9C,QAAM,SAAS,SAAS,mBAAmB,CAAC;AAC5C,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,UAAQ,IAAI,MAAM;AAClB,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,wBAAwB,IAAI;AAG9C,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,aAAW,SAAS,KAAK,MAAM,aAAa,MAAM;AAAA,IAChD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,cAAc,aAAa,IAAI;AACvC,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,WAAS,KAAK,cAAc,cAAc,KAAK;AAC/C,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,OAAO,aAAa,eAAe,KAAK,MAAM,MAAM,OAAO,GAAG,KAAK,EAAE;AAC3E,MAAI,WAAW,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,IAAI;AACtF,QAAM,UAAU,OAAO,OAAO,CAAC,OAAO,aAAa,cAAc,GAAG,KAAK,IAAI,CAAC;AAC9E,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,GAAG,SAAS,SAAS,CAAC;AAAA,EACnE;AACA,QAAM,MAAM,SAAS,WAAW,UAAU,OAAO,GAAG,KAAK;AACzD,MAAI,aAAa,cAAc,QAAQ,MAAM,GAAG;AAC9C,WAAO;AAAA,EACT;AACA,QAAM,SAAS,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK;AAC3C,uBAAqB,uBAAuB,QAAQ,IAAI;AACxD,MAAI,QAAQ,GAAG,UAAU,UAAU;AACjC,UAAM,WAAW,QAAQ,IAAI,CAAC,OAAO;AACnC,YAAM,YAAY,aAAa,cAAc,GAAG,MAAM,MAAM,IAAI,CAAC;AACjE,YAAM,QAAQ,CAAC,IAAI,SAAS;AAC5B,aAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AAAA,IAC5E,CAAC;AACD,UAAM,kBAAkB,SAAS,IAAI,CAAC,OAAO;AAC3C,aAAO,EAAE,MAAM,SAAS,SAAS,GAAG,MAAM,GAAG,OAAO,GAAG,MAAM;AAAA,IAC/D,CAAC;AACD,eAAW,qBAAqB,gBAAgB,SAAS,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,CAAC;AACjF,UAAM,eAAe,SAAS,GAAG,MAAM,OAAO;AAC9C,UAAM,WAAW,WAAW,iBAAiB,UAAU,OAAO,GAAG,OAAO,YAAY;AACpF,UAAM,gBAAgB,qBAAqB,gBAAgB,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,IAAI;AAC9F,QAAI,QAAQ;AACZ,UAAM,UAAU,SAAS,UAAU,IAAI,IAAI,MAAM;AACjD,YAAQ,cAAc,qBAAqB,uBAAuB,QAAQ;AAC1E,aAAS,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACxD,WAAO;AAAA,EACT;AACA,QAAM,WAAW,aAAa,cAAc,QAAQ,GAAG,MAAM,MAAM,GAAG,IAAI,CAAC;AAC3E,MAAI,eAAe;AACnB,QAAM,YAAY,QAAQ,IAAI,CAAC,WAAW;AACxC,UAAM,WAAW,aAAa,cAAc,OAAO,MAAM,MAAM,IAAI,CAAC;AACpE,oBAAgB;AAChB,WAAO;AAAA,EACT,CAAC;AACD,QAAM,SAAS,QAAQ,IAAI,CAAC,WAAW,SAAS,mBAAmB,MAAM,CAAC;AAC1E,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,WAAS,IAAI,GAAG,IAAI,UAAU,KAAK;AACjC,QAAI,YAAY,IAAI;AACpB,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,YAAM,WAAW,UAAU;AAC3B,YAAM,WAAW,IAAI;AACrB,YAAM,OAAO,OAAO,IAAI,SAAS,UAAU,WAAW,QAAQ;AAC9D,cAAQ,IAAI,MAAM,SAAS;AAC3B,mBAAa;AAAA,IACf;AAAA,EACF;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,eAAa,SAAS,KAAK,MAAM,QAAQ,MAAM;AAAA,IAC7C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,EAAE,SAAAY,UAAS,WAAW,KAAK,MAAM,iBAAiB,WAAW,IAAI;AACvE,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,OAAO,WAAW;AAC5I,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,YAAY,SAAS,QAAQ;AACnC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,iBAAiB,SAAS;AAChC,QAAM,YAAY,SAAS,QAAQ,SAAS,SAAS,IAAI;AACzD,MAAI,SAAS,eAAe,gBAAgB;AAC1C,UAAM,IAAI,MAAM,oDAAoD,SAAS,yCAAyC;AAAA,EACxH;AACA,QAAM,MAAM,SAAS,WAAW,SAAS,UAAU,SAAS;AAC5D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,aAAW,KAAK,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,UAAU,cAAc,aAAa,QAAQ,UAAU,WAAW,SAAS,WAAW,gBAAgB,eAAe,cAAc,aAAa,eAAe,gBAAgB,KAAK;AACxO,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,4BAA0B,SAAS,KAAK,MAAM,qBAAqB,MAAM;AAAA,IACvE;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,iBAAiB,WAAW,IAAI;AACxE,QAAM,YAAY;AAClB,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,OAAO,WAAW;AAC/I,QAAM,EAAE,WAAW,cAAc,aAAa,YAAY,UAAU,SAAS,aAAa,WAAW,UAAU,cAAc,YAAY,IAAI;AAC7I,QAAM,SAAS,eAAe,IAAI,SAAS,QAAQ;AACnD,QAAM,UAAU,cAAc,IAAI,SAAS,QAAQ;AACnD,QAAM,iBAAiB,SAAS,eAAe;AAC/C,QAAM,YAAY,aAAa,eAAe,SAAS,OAAO;AAC9D,QAAM,YAAY,aAAa,eAAe,GAAG,KAAK;AACtD,QAAM,CAAC,OAAO,OAAO,KAAK,IAAI,aAAa,eAAe,OAAO,KAAK;AACtE,QAAM,eAAe,UAAU;AAC/B,QAAM,aAAa,iBAAiB,UAAU,KAAK,UAAU;AAC7D,QAAM,aAAa,iBAAiB,UAAU,KAAK;AACnD,QAAM,iBAAiB,iBAAiB,IAAI,UAAU;AACtD,QAAM,eAAe,UAAU;AAC/B,QAAM,aAAa,iBAAiB,UAAU,KAAK,UAAU;AAC7D,QAAM,aAAa,iBAAiB,UAAU,KAAK;AACnD,QAAM,iBAAiB,iBAAiB,IAAI,UAAU;AACtD,QAAM,MAAM,SAAS,WAAW,SAAS,SAAS,SAAS;AAC3D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,OAAO,SAAS,UAAU,IAAI,GAAG,MAAM,EAAE;AAC/C,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,0BAAwB,MAAM,UAAU,WAAW,cAAc,aAAa,UAAU,SAAS,YAAY,WAAW,UAAU,aAAa,cAAc,aAAa,QAAQ,SAAS,OAAO,OAAO,OAAO,cAAc,YAAY,YAAY,gBAAgB,cAAc,YAAY,YAAY,gBAAgB,KAAK;AACjU,SAAO;AACT;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,aAAa,wBAAwB,GAAG;AAG5C,IAAI,cAAc,wBAAwB,IAAI;AAG9C,IAAI;AAAA,CACH,SAAS,sBAAsB;AAC9B,uBAAqB,qBAAqB,cAAc,KAAK;AAC7D,uBAAqB,qBAAqB,aAAa,KAAK;AAC9D,GAAG,wBAAwB,sBAAsB,CAAC,EAAE;AACpD,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,sBAAoB,SAAS,KAAK,MAAM,eAAe,MAAM;AAAA,IAC3D;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,oBAAoB,SAAS,IAAI;AACjD,QAAM,EAAE,OAAO,QAAQ,OAAO,OAAO,IAAI;AACzC,QAAM,WAAW,MAAM,MAAM;AAC7B,QAAM,CAAC,YAAY,SAAS,IAAI;AAChC,QAAM,WAAW,CAAC,UAAU,YAAY,WAAW,OAAO,MAAM,EAAE;AAClE,MAAI,aAAa,SAAS,UAAU,IAAI,OAAO,MAAM;AACrD,MAAI;AACJ,MAAI,OAAO,UAAU,WAAW;AAC9B,iBAAa,MAAM,EAAE,SAAS,UAAU,QAAQ,EAAE,GAAG,OAAO,GAAG,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AAC5F,iBAAa,SAAS,UAAU,IAAI,WAAW,MAAM;AAAA,EACvD;AACA,QAAM,WAAW,WAAW;AAC5B,QAAM,UAAU,SAAS,UAAU,IAAI,MAAM,MAAM,EAAE;AACrD,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,MAAM,SAAS,WAAW,UAAU,SAAS;AACnD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,mBAAmB,IAAI,WAAW,IAAI,WAAW,OAAO,KAAK,EAAE,MAAM;AAC3E,oBAAkB,UAAU,SAAS,UAAU,UAAU,kBAAkB,YAAY,WAAW,oBAAoB,SAAS,oBAAoB,KAAK;AACxJ,MAAI,cAAc,MAAM;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,gBAAc,SAAS,KAAK,MAAM,SAAS,MAAM;AAAA,IAC/C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,QAAM,QAAQ,EAAE,MAAM;AACtB,eAAa,OAAO,EAAE,UAAU,aAAa,EAAE,UAAU,SAAS,MAAM,4BAA4B,EAAE,mCAAmC;AACzI,QAAM,cAAc,qBAAqB,mBAAmB,CAAC,IAAI,GAAG,KAAK;AACzE,MAAI,YAAY;AAChB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,MAAM,YAAY,GAAG,SAAS,SAAS,CAAC;AAAA,EAC3F;AACA,QAAM,eAAe,qBAAqB,iBAAiB,GAAG,KAAK,EAAE;AACrE,uBAAqB,2BAA2B,WAAW,CAAC,YAAY,GAAG,KAAK;AAChF,QAAM,cAAc,SAAS,WAAW,UAAU,OAAO,UAAU,KAAK;AACxE,QAAM,WAAW,UAAU,MAAM;AACjC,QAAM,cAAc,SAAS,UAAU,IAAI,UAAU,MAAM,EAAE;AAC7D,QAAM,gBAAgB,SAAS,UAAU,IAAI,YAAY,MAAM,EAAE;AACjE,cAAY,aAAa,YAAY,IAAI,GAAG,WAAW,IAAI,GAAG,UAAU,eAAe,SAAS,EAAE,MAAM;AACxG,MAAI,MAAM;AACV,MAAI,gBAAgB,MAAM;AACxB,UAAM,kBAAkB,qBAAqB,uBAAuB,WAAW;AAC/E,UAAM,WAAW,EAAE,QAAQ,EAAE,GAAG,YAAY,GAAG,OAAO,EAAE,MAAM,gBAAgB,GAAG,SAAS,SAAS,CAAC;AACpG,aAAS,YAAY,UAAU,MAAM;AACrC,aAAS,YAAY,YAAY,MAAM;AAAA,EACzC;AACA,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,eAAa,SAAS,KAAK,MAAM,QAAQ,MAAM;AAAA,IAC7C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,QAAM,QAAQ,EAAE,MAAM;AACtB,eAAa,OAAO,EAAE,UAAU,aAAa,EAAE,UAAU,SAAS,MAAM,2BAA2B,EAAE,mCAAmC;AACxI,QAAM,cAAc,qBAAqB,mBAAmB,CAAC,IAAI,GAAG,KAAK;AACzE,MAAI,YAAY;AAChB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,MAAM,YAAY,GAAG,SAAS,SAAS,CAAC;AAAA,EAC3F;AACA,QAAM,eAAe,qBAAqB,iBAAiB,GAAG,KAAK,EAAE;AACrE,uBAAqB,2BAA2B,UAAU,CAAC,YAAY,GAAG,KAAK;AAC/E,QAAM,cAAc,SAAS,WAAW,UAAU,OAAO,UAAU,KAAK;AACxE,QAAM,WAAW,UAAU,MAAM;AACjC,QAAM,cAAc,SAAS,UAAU,IAAI,UAAU,MAAM,EAAE;AAC7D,QAAM,gBAAgB,SAAS,UAAU,IAAI,YAAY,MAAM,EAAE;AACjE,aAAW,aAAa,YAAY,IAAI,GAAG,WAAW,IAAI,GAAG,UAAU,eAAe,SAAS,EAAE,MAAM;AACvG,MAAI,MAAM;AACV,MAAI,gBAAgB,MAAM;AACxB,UAAM,kBAAkB,qBAAqB,uBAAuB,WAAW;AAC/E,UAAM,WAAW,EAAE,QAAQ,EAAE,GAAG,YAAY,GAAG,OAAO,EAAE,MAAM,gBAAgB,GAAG,SAAS,SAAS,CAAC;AACpG,aAAS,YAAY,UAAU,MAAM;AACrC,aAAS,YAAY,YAAY,MAAM;AAAA,EACzC;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,qBAAmB,SAAS,KAAK,MAAM,cAAc,MAAM;AAAA,IACzD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,WAAW,WAAW,IAAI;AAClC,QAAM,YAAY,EAAE,MAAM;AAC1B,QAAM,cAAc,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AACjE,QAAM,aAAa,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AAChE,QAAM,aAAa,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AAChE,QAAM,eAAe,cAAc;AACnC,QAAM,cAAc,aAAa;AACjC,QAAM,cAAc,cAAc,YAAY;AAC9C,QAAM,cAAc,eAAe,SAAS,CAAC,WAAW,cAAc,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,cAAc,WAAW;AACpJ,QAAM,MAAM,SAAS,WAAW,aAAa,SAAS;AACtD,QAAM,QAAQ,SAAS,UAAU,IAAI,EAAE,MAAM;AAC7C,QAAM,MAAM,MAAM;AAClB,QAAM,gBAAgB,IAAI,WAAW,IAAI,WAAW,aAAa,eAAe,EAAE,KAAK,CAAC,EAAE,MAAM;AAChG,QAAM,mBAAmB,IAAI,WAAW,IAAI,WAAW,WAAW,EAAE,MAAM;AAC1E,QAAM,kBAAkB,IAAI,WAAW,IAAI,WAAW,aAAa,eAAe,WAAW,CAAC,EAAE,MAAM;AACtG,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,eAAe,eAAe,SAAS,IAAI;AACjD,mBAAiB,KAAK,WAAW,cAAc,eAAe,EAAE,MAAM,SAAS,GAAG,kBAAkB,iBAAiB,YAAY,QAAQ,KAAK;AAC9I,SAAO;AACT;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,wBAAsB,SAAS,KAAK,MAAM,uBAAuB,MAAM;AAAA,IACrE;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,iBAAiB,MAAM;AAC9B,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,EAAE,SAAAA,UAAS,WAAW,KAAK,MAAM,gBAAgB,IAAI;AAC3D,QAAM,aAAa,aAAa,OAAO,CAAC,GAAG,CAAC,IAAI;AAChD,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,YAAY,MAAM,iBAAiB,IAAI;AAC/H,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,YAAY,SAAS,QAAQ;AACnC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,iBAAiB,SAAS;AAChC,QAAM,YAAY,SAAS,QAAQ,SAAS,SAAS,IAAI;AACzD,MAAI,SAAS,eAAe,gBAAgB;AAC1C,UAAM,IAAI,MAAM,mEAAmE,SAAS,yCAAyC;AAAA,EACvI;AACA,QAAM,MAAM,SAAS,WAAW,SAAS,UAAU,SAAS;AAC5D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,sBAAoB,KAAK,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,UAAU,cAAc,aAAa,QAAQ,UAAU,WAAW,SAAS,WAAW,gBAAgB,eAAe,cAAc,aAAa,eAAe,gBAAgB,KAAK;AACjP,SAAO;AACT;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,aAAa,wBAAwB,GAAG;AAG5C,IAAI,yBAAyB;AAC7B,IAAI,eAAe,yBAAyB,OAAO,wBAAwB,MAAM;AAGjF,IAAI,aAAa,wBAAwB,KAAK,SAAS;AAGvD,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,IAAI,IAAI;AAChB,QAAM,YAAY,OAAO,MAAM;AAC/B,QAAM,WAAW,OAAO,MAAM,MAAM;AACpC,MAAI,OAAO;AACX,MAAI,MAAM,GAAG;AACX,iBAAa,OAAO,EAAE,YAAY,MAAM,KAAK,MAAM,iCAAiC,EAAE,YAAY,OAAO,YAAY;AACrH,WAAO,YAAY,MAAM;AAAA,EAC3B;AACA,WAAS,OAAO,MAAM,GAAG,CAAC;AAC1B,SAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC1F;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,OAAO,EAAE,OAAO,OAAO,MAAM,GAAG,SAAS,SAAS,IAAI;AAC9D,QAAM,MAAM,SAAS,WAAW,OAAO,KAAK;AAC5C,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,UAAQ,KAAK,KAAK;AAClB,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,sBAAoB,SAAS,KAAK,MAAM,eAAe,MAAM;AAAA,IAC3D;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,MAAM,SAAS,WAAW,OAAO,OAAO,OAAO,KAAK;AAC1D,QAAM,UAAU,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACtD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,oBAAkB,SAAS,OAAO,aAAa,YAAY,aAAa,KAAK;AAC7E,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,IAAI,eAAe,wBAAwB,KAAK;AAGhD,IAAI,yBAAyB;AAC7B,IAAI,kBAAkB,yBAAyB,UAAU,sBAAsB;AAG/E,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,kBAAgB,SAAS,KAAK,MAAM,gBAAgB,MAAM,CAAC,UAAU,UAAU,UAAU,UAAU,UAAU,UAAU,QAAQ,CAAC;AAClI;AACA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,gBAAgB,IAAI;AAC5B,QAAM,EAAE,GAAG,MAAM,OAAO,UAAU,QAAQ,OAAOS,QAAO,IAAI;AAC5D,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,SAAS,SAAS,UAAU,IAAI,MAAM,MAAM,EAAE;AACpD,QAAM,aAAa,SAAS,UAAU,IAAI,SAAS,MAAM,EAAE;AAC3D,QAAM,WAAW,UAAU,OAAO,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE,KAAK;AAC7E,QAAM,UAAUA,WAAU,OAAO,SAAS,UAAU,IAAIA,QAAO,MAAM,EAAE,KAAK;AAC5E,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,MAAI,aAAa,cAAc,EAAE,KAAK,MAAM,GAAG;AAC7C,WAAO;AAAA,EACT;AACA,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,gBAAc,KAAK,QAAQ,YAAY,UAAU,SAAS,iBAAiB,KAAK;AAChF,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,oBAAkB,SAAS,KAAK,MAAM,aAAa,MAAM;AAAA,IACvD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAT,UAAS,KAAK,MAAM,WAAW,YAAY,iBAAiB,YAAY,aAAa,eAAe,IAAI;AAChH,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,eAAe;AACxH,QAAM,kBAAkB,kBAAkB;AAC1C,MAAI,mBAAmB,MAAM;AAC3B,UAAM,IAAI,MAAM,GAAG,+EAA+E;AAAA,EACpG;AACA,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,iBAAiB,SAAS;AAChC,MAAI,SAAS;AACb,MAAI,QAAQ,MAAM;AAChB,UAAM,WAAW,SAAS,UAAU,IAAI,KAAK,MAAM;AACnD,QAAI,SAAS,MAAM,WAAW,GAAG;AAC/B,YAAM,IAAI,MAAM,sDAAsD,SAAS,MAAM,SAAS;AAAA,IAChG;AACA,QAAI,SAAS,MAAM,OAAO,gBAAgB;AACxC,YAAM,IAAI,MAAM,2BAA2B,SAAS,wDAAwD,iBAAiB;AAAA,IAC/H;AACA,aAAS,SAAS;AAAA,EACpB;AACA,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,YAAY,SAAS,QAAQ;AACnC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,YAAY,SAAS,QAAQ,SAAS,SAAS,IAAI;AACzD,QAAM,YAAY,SAAS;AAC3B,QAAM,WAAW,SAAS;AAC1B,QAAM,UAAU,SAAS;AACzB,MAAI,eAAe,QAAQ;AACzB,UAAM,IAAI,MAAM,yDAAyD,iCAAiC;AAAA,EAC5G;AACA,QAAM,MAAM,SAAS,WAAW,SAAS,UAAU,SAAS;AAC5D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,2BAA2B,0BAA0B,OAAO,IAAI,SAAS,UAAU,IAAI,uBAAuB,MAAM,EAAE;AAC5H,kBAAgB,KAAK,WAAW,UAAU,SAAS,UAAU,cAAc,aAAa,QAAQ,QAAQ,UAAU,WAAW,SAAS,WAAW,gBAAgB,eAAe,cAAc,aAAa,eAAe,gBAAgB,iBAAiB,0BAA0B,kBAAkB,GAAG,KAAK;AAC/S,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,6BAA2B,SAAS,KAAK,MAAM,sBAAsB,MAAM;AAAA,IACzE;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,WAAW,YAAY,iBAAiB,YAAY,aAAa,eAAe,IAAI;AAChH,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,IAAI;AAC9H,QAAM,kBAAkB,kBAAkB;AAC1C,MAAI,mBAAmB,MAAM;AAC3B,UAAM,IAAI,MAAM,GAAG,wFAAwF;AAAA,EAC7G;AACA,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,iBAAiB,SAAS;AAChC,MAAI,SAAS;AACb,MAAI,QAAQ,MAAM;AAChB,UAAM,WAAW,SAAS,UAAU,IAAI,KAAK,MAAM;AACnD,QAAI,SAAS,MAAM,WAAW,GAAG;AAC/B,YAAM,IAAI,MAAM,+DAA+D,SAAS,MAAM,SAAS;AAAA,IACzG;AACA,QAAI,SAAS,MAAM,OAAO,gBAAgB;AACxC,YAAM,IAAI,MAAM,oCAAoC,SAAS,wDAAwD,iBAAiB;AAAA,IACxI;AACA,aAAS,SAAS;AAAA,EACpB;AACA,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,YAAY,SAAS,QAAQ;AACnC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,YAAY,SAAS,QAAQ,SAAS,SAAS,IAAI;AACzD,QAAM,YAAY,SAAS;AAC3B,QAAM,WAAW,SAAS;AAC1B,QAAM,UAAU,SAAS;AACzB,MAAI,eAAe,QAAQ;AACzB,UAAM,IAAI,MAAM,kEAAkE,iCAAiC;AAAA,EACrH;AACA,QAAM,MAAM,SAAS,WAAW,SAAS,UAAU,SAAS;AAC5D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,2BAA2B,0BAA0B,OAAO,IAAI,SAAS,UAAU,IAAI,uBAAuB,MAAM,EAAE;AAC5H,2BAAyB,KAAK,WAAW,UAAU,SAAS,UAAU,cAAc,aAAa,QAAQ,QAAQ,UAAU,WAAW,SAAS,WAAW,gBAAgB,eAAe,cAAc,aAAa,eAAe,gBAAgB,iBAAiB,0BAA0B,kBAAkB,GAAG,KAAK;AACxT,SAAO;AACT;AACA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,iBAAe,SAAS,KAAK,MAAM,UAAU,MAAM;AAAA,IACjD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,SAAS,UAAU,OAAO,IAAI;AACtC,QAAM,EAAE,QAAQ,QAAQ,IAAI;AAC5B,QAAM,CAAC,aAAa,WAAW,WAAWA,QAAO,IAAI,uBAAuB,mBAAmB,QAAQ,OAAO;AAC9G,QAAM,MAAM,SAAS,WAAW,aAAa,OAAO,KAAK;AACzD,MAAI,cAAc,GAAG;AACnB,WAAO;AAAA,EACT;AACA,QAAM,eAAe,QAAQ;AAC7B,QAAM,YAAY,aAAa,aAAa,SAAS;AACrD,QAAM,QAAQ,SAAS,UAAU,IAAI,OAAO,MAAM;AAClD,QAAM,MAAM,MAAM;AAClB,QAAM,cAAc,SAAS,UAAU,IAAI,QAAQ,MAAM;AACzD,QAAM,YAAY,YAAY;AAC9B,QAAM,eAAe,IAAI,WAAW,IAAI,WAAWA,QAAO,EAAE,MAAM;AAClE,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,eAAa,KAAK,SAAS,OAAO,QAAQ,WAAW,WAAW,WAAW,WAAW,cAAc,KAAK;AACzG,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,eAAa,SAAS,KAAK,MAAM,UAAU,MAAM;AAAA,IAC/C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAM,UAAU,IAAI;AAC5B,QAAM,aAAa,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AAC9D,QAAM,cAAc,SAAS,SAAS,QAAQ,MAAM;AACpD,QAAM,UAAU,EAAE,MAAM;AACxB,WAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,EAAE,IAAI;AAC9C,UAAMH,SAAQ,YAAY;AAC1B,iBAAa,OAAOA,UAAS,UAAU,KAAKA,UAAS,GAAG,MAAM,6BAA6BA,wBAAuB,UAAU,IAAI;AAAA,EAClI;AACA,QAAM,YAAY,qBAAqB,aAAa,yBAAyB,GAAG,SAAS,YAAY,SAAS;AAC9G,QAAM,WAAW,SAAS;AAAA,IACxB,QAAQ,EAAE,EAAE;AAAA,IACZ,OAAO;AAAA,MACL,OAAO;AAAA,QACL,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,MACZ;AAAA,IACF;AAAA,IACA,SAAS;AAAA,EACX,CAAC;AACD,QAAM,cAAc,aAAa,cAAc,QAAQ,KAAK;AAC5D,QAAM,eAAe,SAAS;AAAA,IAC5B,QAAQ,EAAE,GAAG,QAAQ;AAAA,IACrB,OAAO,EAAE,OAAO,CAAC,UAAU,WAAW,cAAc,UAAU,SAAS,EAAE;AAAA,IACzE,SAAS;AAAA,EACX,CAAC;AACD,QAAM,qBAAqB;AAAA,IACzB,UAAU;AAAA,IACV,UAAU;AAAA,IACV,cAAc,UAAU;AAAA,IACxB,UAAU;AAAA,EACZ;AACA,QAAM,MAAM,SAAS,WAAW,oBAAoB,EAAE,KAAK;AAC3D,MAAI,aAAa,cAAc,EAAE,KAAK,MAAM,GAAG;AAC7C,WAAO;AAAA,EACT;AACA,QAAM,cAAc,SAAS,MAAM,SAAS;AAC5C,QAAM,QAAQ,SAAS,UAAU,IAAI,SAAS,MAAM;AACpD,QAAM,MAAM,MAAM;AAClB,QAAM,cAAc,SAAS,UAAU,IAAI,aAAa,MAAM;AAC9D,QAAM,YAAY,YAAY;AAC9B,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,gBAAgB,IAAI,WAAW,IAAI,WAAW,aAAa,eAAe,SAAS,KAAK,CAAC,EAAE,MAAM;AACvG,QAAM,kBAAkB,IAAI,WAAW,IAAI,WAAW,aAAa,eAAe,kBAAkB,CAAC,EAAE,MAAM;AAC7G,aAAW,KAAK,SAAS,EAAE,QAAQ,eAAe,aAAa,WAAW,UAAU,WAAW,iBAAiB,KAAK;AACrH,WAAS,YAAY,SAAS,MAAM;AACpC,WAAS,YAAY,aAAa,MAAM;AACxC,MAAI,QAAQ,UAAU;AACtB,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,yBAAyB;AAC7B,IAAI,iBAAiB,yBAAyB,SAAS,wBAAwB,MAAM;AAGrF,IAAI,yBAAyB;AAC7B,IAAI,sBAAsB,yBAAyB,cAAc,wBAAwB,MAAM;AAG/F,IAAI;AACJ,SAAS,WAAW,UAAU;AAC5B,cAAY,SAAS,KAAK,MAAM,WAAW,MAAM;AAAA,IAC/C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,OAAAa,OAAM,GAAG,SAAS,SAAS,IAAI;AAC/D,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,SAAS;AAClD,MAAI,aAAa,cAAc,EAAE,KAAK,MAAM,GAAG;AAC7C,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,cAAU,KAAK,SAAS,EAAE,QAAQA,QAAO,KAAK;AAAA,EAChD;AACA,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,yBAAyB;AAC7B,IAAI,cAAc,yBAAyB,MAAM,wBAAwB,MAAM;AAG/E,IAAI,yBAAyB;AAC7B,IAAI,mBAAmB,yBAAyB,WAAW,wBAAwB,MAAM;AAGzF,IAAI,aAAa,wBAAwB,GAAG;AAG5C,IAAI,yBAAyB;AAC7B,IAAI,oBAAoB,yBAAyB,YAAY,wBAAwB,MAAM;AAG3F,IAAI,oBAAoB,wBAAwB,UAAU;AAG1D,IAAI,yBAAyB;AAC7B,IAAI,mBAAmB,yBAAyB,WAAW,wBAAwB,MAAM;AAGzF,IAAI,0BAA0B;AAC9B,IAAI,mBAAmB,yBAAyB,YAAY,yBAAyB,MAAM;AAG3F,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,YAAU,SAAS,KAAK,MAAM,KAAK,MAAM;AAAA,IACvC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,kBAAkB,MAAM,SAAS,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,cAAc,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AACxG,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,aAAS;AACT,cAAU;AAAA,EACZ;AACA,QAAM,YAAY,OAAO,MAAM;AAC/B,uBAAqB,2BAA2B,OAAO,MAAM,SAAS;AACtE,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,IAAI;AACjG,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,MAAM,SAAS,WAAW,UAAU,EAAE,KAAK;AACjD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,YAAQ,SAAS,SAAS,EAAE,QAAQ,YAAY,KAAK;AAAA,EACvD;AACA,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,YAAY;AAClF,QAAI,QAAQ;AAAA,EACd;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,0BAA0B;AAC9B,IAAI,iBAAiB,yBAAyB,SAAS,uBAAuB;AAG9E,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,gBAAc,SAAS,KAAK,MAAM,SAAS,MAAM;AAAA,IAC/C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,IAAI,OAAO;AACjB,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,eAAa,OAAO,EAAE,UAAU,WAAW,MAAM,0DAA0D,EAAE,QAAQ;AACrH,QAAM,EAAE,YAAY,SAAAV,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,MAAM,eAAe;AAC9G,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,YAAY,SAAS,QAAQ;AACnC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,iBAAiB,SAAS;AAChC,MAAI,SAAS,eAAe,gBAAgB;AAC1C,UAAM,IAAI,MAAM,6CAA6C,SAAS,yCAAyC;AAAA,EACjH;AACA,QAAM,MAAM,SAAS,WAAW,SAAS,UAAU,SAAS;AAC5D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,cAAY,KAAK,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,cAAc,aAAa,QAAQ,UAAU,WAAW,SAAS,gBAAgB,eAAe,cAAc,aAAa,eAAe,gBAAgB,KAAK;AACpN,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,aAAW,SAAS,KAAK,MAAM,MAAM,MAAM,CAAC,wBAAwB,CAAC;AACvE;AACA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,cAAc,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AACxG,MAAI,gBAAgB;AACpB,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAI,iBAAiB,KAAK;AACxB,eAAS;AACT,gBAAU;AACV,sBAAgB,qBAAqB,iBAAiB,cAAc,QAAQ,OAAO,MAAM,MAAM;AAAA,IACjG;AAAA,EACF;AACA,uBAAqB,2BAA2B,QAAQ,eAAe,OAAO,MAAM,MAAM;AAC1F,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,aAAa;AAC1G,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,MAAI,cAAc;AAClB,MAAI,OAAO,UAAU,WAAW;AAC9B,kBAAc,MAAM,EAAE,SAAS,UAAU,QAAQ,EAAE,GAAG,OAAO,GAAG,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AAC7F,cAAU,SAAS,UAAU,IAAI,YAAY,MAAM,EAAE;AAAA,EACvD;AACA,QAAM,MAAM,SAAS,WAAW,UAAU,SAAS;AACnD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,aAAS,SAAS,YAAY,KAAK;AAAA,EACrC;AACA,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,YAAY;AAClF,QAAI,QAAQ;AAAA,EACd;AACA,MAAI,OAAO,UAAU,WAAW;AAC9B,aAAS,YAAY,YAAY,MAAM;AAAA,EACzC;AACA,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,YAAU,SAAS,KAAK,MAAM,KAAK,MAAM;AAAA,IACvC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,cAAc,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AACxG,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAI,iBAAiB,KAAK;AACxB,eAAS;AACT,gBAAU;AAAA,IACZ;AAAA,EACF;AACA,QAAM,YAAY,OAAO,MAAM;AAC/B,uBAAqB,2BAA2B,OAAO,MAAM,SAAS;AACtE,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,IAAI;AACjG,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,MAAM,SAAS,WAAW,UAAU,OAAO,KAAK;AACtD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,YAAQ,SAAS,SAAS,EAAE,QAAQ,YAAY,KAAK;AAAA,EACvD;AACA,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,YAAY;AAClF,QAAI,QAAQ;AAAA,EACd;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,0BAA0B;AAC9B,IAAI,iBAAiB,yBAAyB,SAAS,uBAAuB;AAG9E,IAAI;AAAA,CACH,SAAS,oBAAoB;AAC5B,qBAAmB,mBAAmB,aAAa,KAAK;AACxD,qBAAmB,mBAAmB,eAAe,KAAK;AAC5D,GAAG,sBAAsB,oBAAoB,CAAC,EAAE;AAChD,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,kBAAgB,SAAS,KAAK,MAAM,WAAW,MAAM;AAAA,IACnD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,UAAU,KAAK,EAAE,IAAI;AACxE,QAAM,WAAW,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,EAAE,MAAM,MAAM,GAAG,EAAE;AACrE,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,MAAM,SAAS,WAAW,UAAU,EAAE,KAAK;AACjD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,QAAM,kBAAkB,SAAS,IAAI,CAAC,aAAa,SAAS,EAAE;AAC9D,QAAM,mBAAmB,SAAS,IAAI,CAAC,aAAa,SAAS,EAAE;AAC/D,QAAM,mBAAmB,IAAI,WAAW,IAAI,WAAW,eAAe,EAAE,MAAM;AAC9E,QAAM,oBAAoB,IAAI,WAAW,IAAI,WAAW,gBAAgB,EAAE,MAAM;AAChF,gBAAc,KAAK,aAAa,EAAE,MAAM,QAAQ,SAAS,EAAE,QAAQ,kBAAkB,mBAAmB,kBAAkB,OAAO,KAAK;AACtI,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,IAAI,0BAA0B;AAC9B,IAAI,kBAAkB,yBAAyB,UAAU,uBAAuB;AAGhF,IAAI,aAAa,wBAAwB,GAAG;AAG5C,SAAS,kBAAkB,UAAU,WAAW;AAC9C,QAAM,SAAS,IAAI,WAAW,SAAS,KAAK,OAAO,QAAQ,WAAW,CAAC;AACvE,QAAM,mBAAmB,OAAO;AAChC,QAAM,eAAe,OAAO;AAC5B,QAAM,kBAAkB,OAAO;AAC/B,QAAM,gBAAgB,OAAO;AAC7B,WAAS,KAAK,MAAM,SAAS;AAC7B,SAAO,EAAE,kBAAkB,cAAc,iBAAiB,cAAc;AAC1E;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,cAAY,SAAS,KAAK;AAAA,IACxB;AAAA,IACA;AAAA,IACA;AAAA,MACE;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,cAAc,eAAe,eAAe,IAAI;AACxD,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,UAAU,SAAS,UAAU,IAAI,MAAM,MAAM,EAAE;AACrD,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,YAAY,UAAU,SAAS,UAAU,eAAe,cAAc,cAAc;AAC1F,QAAM,EAAE,kBAAkB,cAAc,iBAAiB,cAAc,IAAI,kBAAkB,UAAU,SAAS;AAChH,WAAS,KAAK,MAAM,eAAe;AACnC,WAAS,KAAK,MAAM,aAAa;AACjC,QAAM,wBAAwB,SAAS,WAAW,CAAC,YAAY,GAAG,SAAS,gBAAgB;AAC3F,SAAO;AACT;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX;AACF;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,cAAY,SAAS,KAAK;AAAA,IACxB;AAAA,IACA;AAAA,IACA;AAAA,MACE;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,cAAc,eAAe,gBAAgB,mBAAmB,IAAI;AAC5E,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,UAAU,SAAS,UAAU,IAAI,MAAM,MAAM,EAAE;AACrD,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,YAAY,UAAU,SAAS,UAAU,eAAe,cAAc,gBAAgB,kBAAkB;AAC9G,QAAM,EAAE,kBAAkB,cAAc,iBAAiB,cAAc,IAAI,kBAAkB,UAAU,SAAS;AAChH,WAAS,KAAK,MAAM,eAAe;AACnC,QAAM,wBAAwB,SAAS,WAAW,CAAC,YAAY,GAAG,SAAS,gBAAgB;AAC3F,QAAM,qBAAqB,SAAS,WAAW,CAAC,GAAG,SAAS,aAAa;AACzE,SAAO,CAAC,uBAAuB,kBAAkB;AACnD;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,cAAY,SAAS,KAAK;AAAA,IACxB;AAAA,IACA;AAAA,IACA;AAAA,MACE;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,cAAc,eAAe,gBAAgB,aAAa,IAAI;AACtE,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,UAAU,SAAS,UAAU,IAAI,MAAM,MAAM,EAAE;AACrD,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,YAAY,UAAU,SAAS,UAAU,eAAe,cAAc,gBAAgB,YAAY;AACxG,QAAM,EAAE,kBAAkB,cAAc,iBAAiB,cAAc,IAAI,kBAAkB,UAAU,SAAS;AAChH,WAAS,KAAK,MAAM,aAAa;AACjC,QAAM,wBAAwB,SAAS,WAAW,CAAC,YAAY,GAAG,SAAS,gBAAgB;AAC3F,QAAM,uBAAuB,SAAS,WAAW,CAAC,YAAY,GAAG,WAAW,eAAe;AAC3F,SAAO,CAAC,uBAAuB,oBAAoB;AACrD;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,0BAA0B;AAC9B,IAAI,kBAAkB,yBAAyB,UAAU,yBAAyB,MAAM;AAGxF,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,eAAa,SAAS,KAAK,MAAM,QAAQ,MAAM;AAAA,IAC7C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,IAAI;AACpB,QAAM,EAAE,OAAO,SAAS,SAAS,IAAI;AACrC,QAAM,MAAM,SAAS,WAAW,CAAC,GAAG,QAAQ,OAAO,KAAK,GAAG,OAAO;AAClE,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,cAAc,SAAS,UAAU,IAAI,QAAQ,MAAM;AACzD,QAAM,YAAY,YAAY;AAC9B,aAAW,WAAW,OAAO,SAAS,UAAU,KAAK;AACrD,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,IAAI;AAC7C,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,UAAQ,KAAK,CAAC;AACd,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,YAAY,EAAE,QAAQ,EAAE,OAAO,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAAA,EAC9F;AACA,QAAM,QAAQ,OAAO,GAAG;AACxB,QAAM,QAAQ,OAAO,GAAG;AACxB,SAAO,QAAQ,CAAC,OAAO;AACrB,iBAAa,kBAAkB,OAAO,GAAG,OAAO,uDAAuD;AACvG,iBAAa,OAAO,UAAU,GAAG,OAAO,MAAM,uDAAuD;AAAA,EACvG,CAAC;AACD,QAAM,0BAA0B,CAAC;AACjC,QAAM,kBAAkB,OAAO,IAAI,CAAC,OAAO;AACzC,UAAM,YAAY,YAAY,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAChG,4BAAwB,KAAK,SAAS;AACtC,WAAO;AAAA,EACT,CAAC;AACD,QAAM,SAAS,QAAQ,EAAE,QAAQ,iBAAiB,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AACtF,0BAAwB,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACvE,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,cAAY,SAAS,KAAK,MAAM,OAAO,MAAM;AAAA,IAC3C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,UAAU,cAAc,EAAE,IAAI;AACjF,QAAM,WAAW,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,EAAE,MAAM,MAAM,GAAG,EAAE;AACrE,MAAI,aAAa,cAAc,EAAE,KAAK,MAAM,GAAG;AAC7C,WAAO,MAAM;AAAA,MACX,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,UAAU,OAAO,eAAe,OAAO,EAAE,MAAM;AAAA,IACjE,CAAC;AAAA,EACH;AACA,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,MAAM,SAAS,WAAW,UAAU,EAAE,KAAK;AACjD,QAAM,gBAAgB,SAAS,UAAU,IAAI,IAAI,MAAM;AACvD,QAAM,QAAQ,cAAc;AAC5B,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,QAAM,kBAAkB,SAAS,IAAI,CAAC,aAAa,SAAS,EAAE;AAC9D,QAAM,mBAAmB,SAAS,IAAI,CAAC,aAAa,SAAS,EAAE;AAC/D,QAAM,mBAAmB,IAAI,WAAW,IAAI,WAAW,eAAe,EAAE,MAAM;AAC9E,QAAM,oBAAoB,IAAI,WAAW,IAAI,WAAW,gBAAgB,EAAE,MAAM;AAChF,YAAU,KAAK,aAAa,EAAE,MAAM,QAAQ,SAAS,EAAE,QAAQ,kBAAkB,mBAAmB,eAAe,KAAK;AACxH,SAAO;AACT;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,IAAI,0BAA0B;AAC9B,IAAI,aAAa,yBAAyB,KAAK,uBAAuB;AAGtE,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,cAAY,SAAS,KAAK,MAAM,OAAO,MAAM;AAAA,IAC3C;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,GAAG,OAAAU,OAAM,IAAI;AACrB,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,YAAY,SAAS,UAAU,IAAIA,OAAM,MAAM,EAAE;AACvD,MAAI,UAAU;AACd,QAAM,SAAS;AACf,MAAI,cAAc;AAClB,MAAI,OAAO,UAAU,WAAW;AAC9B,kBAAc,MAAM,EAAE,SAAS,UAAU,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AACrF,cAAU,SAAS,UAAU,IAAI,YAAY,MAAM,EAAE;AAAA,EACvD;AACA,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,SAAS;AAClD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,YAAU,SAAS,WAAW,KAAK;AACnC,MAAI,OAAO,UAAU,WAAW;AAC9B,aAAS,YAAY,YAAY,MAAM;AAAA,EACzC;AACA,SAAO;AACT;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,aAAW,SAAS,KAAK,MAAM,MAAM,MAAM;AAAA,IACzC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,cAAc,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AACxG,MAAI,gBAAgB;AACpB,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAI,iBAAiB,KAAK;AACxB,eAAS;AACT,gBAAU;AACV,sBAAgB,qBAAqB,iBAAiB,cAAc,QAAQ,OAAO,MAAM,MAAM;AAAA,IACjG;AAAA,EACF;AACA,uBAAqB,2BAA2B,QAAQ,eAAe,OAAO,MAAM,MAAM;AAC1F,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,aAAa;AAC1G,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,MAAM,SAAS,WAAW,UAAU,OAAO,KAAK;AACtD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,aAAS,SAAS,YAAY,SAAS,IAAI,QAAQ,KAAK;AAAA,EAC1D;AACA,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,YAAY;AAClF,QAAI,QAAQ;AAAA,EACd;AACA,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,SAAS,CAAC,SAAS;AACrB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,MAAM,OAAO,MAAM,IAAI;AAC5C,QAAM,SAAS,UAAU,OAAO,MAAM,OAAO,KAAK;AAClD,QAAM,MAAM,SAAS,WAAW,CAAC,OAAO,MAAM,GAAG,KAAK;AACtD,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,UAAQ,IAAI,MAAM;AAClB,SAAO;AACT;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,0BAA0B;AAC9B,IAAI,iBAAiB,yBAAyB,SAAS,uBAAuB;AAG9E,IAAI,cAAc,wBAAwB,IAAI;AAG9C,IAAI,eAAe,wBAAwB,KAAK;AAGhD,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,uBAAqB,SAAS,KAAK,MAAM,gBAAgB,MAAM;AAAA,IAC7D;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,kBAAkB,MAAAtB,MAAK,IAAI;AACjD,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,CAAC,OAAO,WAAW,UAAU,WAAW,IAAI,OAAO;AACzD,QAAM,WAAW,CAAC,OAAO,WAAW,UAAU,WAAW;AACzD,MAAI,QAAQ,SAAS,UAAU,IAAI,OAAO,MAAM;AAChD,MAAI;AACJ,MAAI,MAAM,UAAU,WAAW;AAC7B,iBAAa,MAAM,EAAE,SAAS,UAAU,QAAQ,EAAE,GAAG,OAAO,GAAG,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AAC5F,YAAQ,SAAS,UAAU,IAAI,WAAW,MAAM;AAAA,EAClD;AACA,QAAM,MAAM,MAAM;AAClB,QAAM,MAAM,SAAS,WAAW,UAAU,SAAS;AACnD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,WAAO;AAAA,EACT;AACA,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,qBAAmB,KAAK,OAAO,WAAW,UAAU,aAAa,WAAW,UAAU,eAAe,IAAI,GAAG,mBAAmB,IAAI,GAAG,KAAK;AAC3I,MAAI,cAAc,MAAM;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,SAAO;AACT;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,8BAA4B,SAAS,KAAK,MAAM,uBAAuB,MAAM;AAAA,IAC3E;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,uBAAuB,MAAM;AACpC,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,kBAAkB,MAAAA,MAAK,IAAI;AACjD,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,CAAC,OAAO,WAAW,UAAU,WAAW,IAAI,OAAO;AACzD,QAAM,WAAW,CAAC,OAAO,WAAW,UAAU,WAAW;AACzD,QAAM,MAAM,SAAS,WAAW,UAAU,SAAS;AACnD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,WAAO;AAAA,EACT;AACA,MAAI,QAAQ,SAAS,UAAU,IAAI,OAAO,MAAM;AAChD,MAAI;AACJ,MAAI,MAAM,UAAU,WAAW;AAC7B,iBAAa,MAAM;AAAA,MACjB,SAAS;AAAA,MACT,QAAQ,EAAE,GAAG,OAAO;AAAA,MACpB,OAAO,EAAE,OAAO,UAAU;AAAA,IAC5B,CAAC;AACD,YAAQ,SAAS,UAAU,IAAI,WAAW,MAAM;AAAA,EAClD;AACA,QAAM,MAAM,MAAM;AAClB,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,4BAA0B,KAAK,OAAO,WAAW,UAAU,aAAa,WAAW,UAAU,eAAe,IAAI,GAAG,mBAAmB,IAAI,GAAG,KAAK;AAClJ,MAAI,cAAc,MAAM;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,SAAO;AACT;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,gBAAc,SAAS,KAAK,MAAM,SAAS,MAAM;AAAA,IAC/C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACtD,MAAI,EAAE,MAAM,WAAW,GAAG;AACxB,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD;AACA,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,YAAY,IAAI,WAAW,IAAI,WAAW,IAAI,EAAE,MAAM;AAC5D,QAAM,gBAAgB,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACnE,cAAY,KAAK,WAAW,KAAK,QAAQ,eAAe,EAAE,MAAM,QAAQ,KAAK;AAC7E,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,OAAO,EAAE,OAAO,EAAE,MAAM,GAAG,SAAS,SAAS,CAAC;AAC9F,WAAS,YAAY,IAAI,MAAM;AAC/B,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,eAAa,SAAS,KAAK,MAAM,kBAAkB,MAAM;AAAA,IACvD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,kBAAkB,MAAM;AAC/B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,SAAS,WAAW,OAAO,IAAI;AACvC,QAAM,MAAM,SAAS,WAAW,OAAO,OAAO,OAAO,KAAK;AAC1D,QAAM,UAAU,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACtD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,QAAM,CAAC,SAAS,OAAO,IAAI,qBAAqB,eAAe,QAAQ,aAAa,UAAU;AAC9F,QAAM,cAAc,cAAc;AAClC,QAAM,mBAAmB;AACzB,QAAM,cAAc,OAAO,cAAc,WAAW,CAAC,WAAW,WAAW,WAAW,cAAc,IAAI,gBAAgB,IAAI,CAAC,GAAG,WAAW,gBAAgB;AAC3J,QAAM,YAAY,IAAI,WAAW,IAAI,WAAW,WAAW,EAAE,MAAM;AACnE,aAAW,SAAS,OAAO,aAAa,YAAY,aAAa,SAAS,SAAS,SAAS,WAAW,YAAY,QAAQ,KAAK;AAChI,SAAO;AACT;AACA,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,IAAI,eAAe,wBAAwB,KAAK;AAGhD,IAAI,eAAe,wBAAwB,KAAK;AAGhD,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,kBAAgB,SAAS,KAAK,MAAM,WAAW,MAAM;AAAA,IACnD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,SAAS,QAAQ,IAAI;AAC7B,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,MAAM,SAAS,WAAW,OAAO,QAAQ,KAAK;AACpD,MAAI,aAAa,cAAc,KAAK,MAAM,GAAG;AAC3C,WAAO;AAAA,EACT;AACA,QAAM,EAAE,WAAW,YAAY,WAAW,SAAAY,UAAS,YAAAQ,YAAW,IAAI,wBAAwB,gBAAgB,SAAS,SAAS,KAAK;AACjI,QAAM,cAAc,SAAS,UAAU,IAAI,QAAQ,MAAM;AACzD,QAAM,YAAY,YAAY;AAC9B,QAAM,cAAc,SAAS,UAAU,IAAI,QAAQ,MAAM;AACzD,QAAM,YAAY,YAAY;AAC9B,QAAM,eAAe,IAAI,WAAW,IAAI,WAAWR,QAAO,EAAE,MAAM;AAClE,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,gBAAc,WAAW,WAAW,SAAS,QAAQ,QAAQ,WAAW,YAAY,WAAW,cAAcQ,aAAY,KAAK;AAC9H,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,eAAa,SAAS,KAAK,MAAM,YAAY,MAAM;AAAA,IACjD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,WAAW,GAAG,IAAI,GAAG,GAAG,IAAI;AACpC,QAAM,cAAc,SAAS,UAAU,IAAI,UAAU,MAAM,EAAE;AAC7D,QAAM,MAAM,SAAS,UAAU,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,MAAM,SAAS,UAAU,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,MAAM,SAAS,WAAW,GAAG,OAAO,GAAG,KAAK;AAClD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,QAAQ,UAAU,MAAM;AAC9B,QAAM,QAAQ,GAAG,MAAM;AACvB,QAAM,SAAS,UAAU,KAAK,QAAQ,KAAK,UAAU,IAAI,IAAI,aAAa,cAAc,GAAG,MAAM,MAAM,CAAC,CAAC;AACzG,aAAW,aAAa,KAAK,KAAK,QAAQ,KAAK;AAC/C,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,cAAY,SAAS,KAAK,MAAM,SAAS,MAAM,CAAC,UAAU,QAAQ,CAAC;AACrE;AACA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,SAAS,UAAU,QAAQ,EAAE,EAAE,EAAE,IAAI;AAC7C,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,MAAI,aAAa,cAAc,IAAI,KAAK,MAAM,GAAG;AAC/C,WAAO;AAAA,EACT;AACA,YAAU,KAAK,KAAK;AACpB,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,aAAa,wBAAwB,GAAG;AAG5C,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,cAAY,SAAS,KAAK,MAAM,SAAS,MAAM;AAAA,IAC7C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,SAAS,UAAU,QAAQ,EAAE,OAAO,GAAG,OAAO,EAAE,IAAI,EAAE,IAAI;AAClE,QAAM,MAAM,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AAClD,QAAM,MAAM,SAAS,WAAW,OAAO,OAAO,OAAO,KAAK;AAC1D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,WAAW,OAAO,MAAM;AAC9B,QAAM,QAAQ,aAAa,cAAc,OAAO,KAAK,IAAI;AACzD,MAAI,aAAa,cAAc,IAAI,KAAK,MAAM,GAAG;AAC/C,WAAO;AAAA,EACT;AACA,YAAU,KAAK,OAAO,UAAU,KAAK;AACrC,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAS,IAAI;AACjC,QAAM,QAAQ,aAAa,cAAc,UAAU;AACnD,QAAM,mBAAmB,CAAC,CAAC,GAAG,CAAC,CAAC;AAChC,mBAAiB,KAAK,GAAG,QAAQ;AACjC,WAAS,KAAK,IAAI,WAAW,QAAQ,KAAK,EAAE,MAAM,QAAQ,EAAE,IAAI;AAC9D,qBAAiB,KAAK,CAAC,GAAG,CAAC,CAAC;AAAA,EAC9B;AACA,QAAM,UAAU,aAAa,WAAW;AAAA,IACtC,QAAQ,EAAE,EAAE;AAAA,IACZ,SAAS;AAAA,IACT,OAAO,EAAE,UAAU,kBAAkB,eAAe,EAAE;AAAA,EACxD,CAAC;AACD,QAAM,sBAAsB,qBAAqB,YAAY,QAAQ,OAAO,YAAY,OAAO,KAAK;AACpG,QAAM,oCAAoC,qBAAqB,YAAY,oBAAoB,QAAQ,WAAW,QAAQ,KAAK;AAC/H,QAAM,eAAe,qBAAqB,oBAAoB,QAAQ,OAAO,YAAY,OAAO,KAAK;AACrG,QAAM,gBAAgB,EAAE,GAAG,QAAQ;AACnC,QAAM,eAAe,EAAE,OAAO,oBAAoB;AAClD,QAAM,kBAAkB,SAAS,EAAE,QAAQ,eAAe,SAAS,UAAU,OAAO,aAAa,CAAC;AAClG,QAAM,kBAAkB,EAAE,GAAG,gBAAgB;AAC7C,QAAM,iBAAiB,EAAE,MAAM,kCAAkC;AACjE,QAAM,WAAW,WAAW,EAAE,QAAQ,iBAAiB,SAAS,UAAU,OAAO,eAAe,CAAC;AACjG,QAAM,sBAAsB,EAAE,GAAG,SAAS;AAC1C,QAAM,qBAAqB,EAAE,OAAO,aAAa;AACjD,QAAM,SAAS,SAAS,EAAE,QAAQ,qBAAqB,SAAS,UAAU,OAAO,mBAAmB,CAAC;AACrG,WAAS,YAAY,QAAQ,MAAM;AACnC,WAAS,YAAY,gBAAgB,MAAM;AAC3C,WAAS,YAAY,SAAS,MAAM;AACpC,SAAO;AACT;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,4BAA0B,SAAS,KAAK,MAAM,uBAAuB,UAAU;AAAA,IAC7E;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,SAAS,UAAU,OAAO,IAAI;AACtC,QAAM,EAAE,SAAS,QAAQ,YAAY,aAAa,IAAI;AACtD,QAAM,eAAe,QAAQ,MAAM;AACnC,QAAM,OAAO,QAAQ,MAAM;AAC3B,QAAM,YAAY,SAAS,SAAS,WAAW,MAAM,EAAE;AACvD,QAAM,wBAAwB,CAAC,eAAe,WAAW,IAAI;AAC7D,QAAM,YAAY,SAAS,UAAU,IAAI,QAAQ,MAAM,EAAE;AACzD,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,iBAAiB,SAAS,UAAU,IAAI,aAAa,MAAM,EAAE;AACnE,QAAM,gBAAgB,SAAS,WAAW,uBAAuB,QAAQ,KAAK;AAC9E,QAAM,kBAAkB,SAAS,UAAU,IAAI,cAAc,MAAM,EAAE;AACrE,QAAM,eAAe,SAAS,WAAW,sBAAsB,MAAM,GAAG,CAAC,GAAG,OAAO,KAAK;AACxF,QAAM,iBAAiB,SAAS,UAAU,IAAI,aAAa,MAAM,EAAE;AACnE,QAAM,oBAAoB,SAAS,WAAW,CAAC,SAAS,GAAG,MAAM;AACjE,QAAM,sBAAsB,SAAS,UAAU,IAAI,kBAAkB,MAAM,EAAE;AAC7E,QAAM,kBAAkB,SAAS,WAAW,CAAC,YAAY,GAAG,QAAQ,KAAK;AACzE,QAAM,oBAAoB,SAAS,UAAU,IAAI,gBAAgB,MAAM,EAAE;AACzE,QAAM,kBAAkB,SAAS,WAAW,CAAC,CAAC,GAAG,OAAO;AACxD,QAAM,oBAAoB,SAAS,UAAU,IAAI,gBAAgB,MAAM,EAAE;AACzE,QAAM,aAAa,wBAAwB,WAAW,UAAU,SAAS,OAAO,QAAQ,cAAc,WAAW,MAAM,gBAAgB,iBAAiB,gBAAgB,qBAAqB,mBAAmB,iBAAiB;AACjO,QAAM,uBAAuB,SAAS,SAAS,gBAAgB,MAAM;AACrE,MAAI;AACJ,UAAQ,qBAAqB;AAAA,SACtB,GAAG;AACN,yBAAmB,qBAAqB,gDAAgD,qBAAqB,EAAE;AAC/G;AAAA,IACF;AAAA,SACK,GAAG;AACN,yBAAmB,qBAAqB,gDAAgD,qBAAqB,IAAI,qBAAqB,EAAE;AACxI;AAAA,IACF;AAAA,SACK;AACH,yBAAmB,qBAAqB,kDAAkD,qBAAqB,IAAI,qBAAqB,IAAI,qBAAqB,EAAE;AACnK;AAAA;AAEA,yBAAmB;AAAA;AAEvB,WAAS,YAAY,gBAAgB,MAAM;AAC3C,MAAI,kBAAkB;AACpB,aAAS,YAAY,cAAc,MAAM;AACzC,aAAS,YAAY,aAAa,MAAM;AACxC,aAAS,YAAY,kBAAkB,MAAM;AAC7C,aAAS,YAAY,gBAAgB,MAAM;AAC3C,UAAM,IAAI,MAAM,gBAAgB;AAAA,EAClC;AACA,MAAI,iBAAiB;AACrB,MAAI,gBAAgB;AACpB,MAAI,eAAe,sBAAsB,IAAI;AAC3C,qBAAiB,OAAO;AAAA,MACtB,QAAQ,EAAE,GAAG,cAAc;AAAA,MAC3B,OAAO,EAAE,OAAO,GAAG,MAAM,CAAC,YAAY,IAAI,EAAE;AAAA,MAC5C,SAAS;AAAA,IACX,CAAC;AACD,oBAAgB,OAAO;AAAA,MACrB,QAAQ,EAAE,GAAG,aAAa;AAAA,MAC1B,OAAO,EAAE,OAAO,GAAG,MAAM,WAAW;AAAA,MACpC,SAAS;AAAA,IACX,CAAC;AACD,aAAS,YAAY,cAAc,MAAM;AACzC,aAAS,YAAY,aAAa,MAAM;AAAA,EAC1C;AACA,SAAO,CAAC,gBAAgB,eAAe,mBAAmB,eAAe;AAC3E;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,sBAAoB,SAAS,KAAK,MAAM,eAAe,MAAM;AAAA,IAC3D;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,SAAS,UAAU,OAAO,IAAI;AACtC,QAAM,EAAE,cAAc,YAAY,SAAS,IAAI;AAC/C,MAAI,aAAa,MAAM,WAAW,GAAG;AACnC,UAAM,IAAI,MAAM;AAAA,UACV,aAAa,OAAO;AAAA,EAC5B;AACA,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,UACV,WAAW,OAAO;AAAA,EAC1B;AACA,MAAI,SAAS,MAAM,WAAW,GAAG;AAC/B,UAAM,IAAI,MAAM,sDAAsD,SAAS,OAAO;AAAA,EACxF;AACA,QAAM,iBAAiB,SAAS,UAAU,IAAI,aAAa,MAAM,EAAE;AACnE,QAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAM,aAAa,SAAS,UAAU,IAAI,SAAS,MAAM,EAAE;AAC3D,QAAM,MAAM,aAAa,MAAM;AAC/B,QAAM,aAAa,aAAa,cAAc,SAAS,KAAK;AAC5D,QAAM,aAAa,SAAS,WAAW,CAAC,KAAK,UAAU,GAAG,aAAa,KAAK;AAC5E,QAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAM,cAAc,SAAS,WAAW,CAAC,UAAU,GAAG,SAAS,KAAK;AACpE,QAAM,gBAAgB,SAAS,UAAU,IAAI,YAAY,MAAM,EAAE;AACjE,QAAM,kBAAkB,SAAS,WAAW,CAAC,CAAC,GAAG,OAAO;AACxD,QAAM,oBAAoB,SAAS,UAAU,IAAI,gBAAgB,MAAM,EAAE;AACzE,oBAAkB,gBAAgB,cAAc,YAAY,KAAK,cAAc,eAAe,iBAAiB;AAC/G,QAAM,uBAAuB,SAAS,SAAS,gBAAgB,MAAM;AACrE,MAAI;AACJ,UAAQ,qBAAqB;AAAA,SACtB,GAAG;AACN,yBAAmB,qBAAqB,yDAAyD,qBAAqB,IAAI,qBAAqB,EAAE;AACjJ;AAAA,IACF;AAAA,SACK,GAAG;AACN,yBAAmB,qBAAqB,8CAA8C,qBAAqB,IAAI,qBAAqB,EAAE;AACtI;AAAA,IACF;AAAA,SACK;AACH,yBAAmB,qBAAqB,qDAAqD;AAC7F;AAAA,SACG,GAAG;AACN,YAAM,mBAAmB,MAAM,KAAK,SAAS,SAAS,WAAW,MAAM,CAAC,GAAG,oBAAoB,MAAM,KAAK,SAAS,SAAS,YAAY,MAAM,CAAC;AAC/I,yBAAmB,qBAAqB,gDAAgD,kBAAkB,iBAAiB;AAC3H;AAAA,IACF;AAAA,SACK,GAAG;AACN,YAAM,mBAAmB,MAAM,KAAK,SAAS,SAAS,WAAW,MAAM,CAAC,GAAG,oBAAoB,MAAM,KAAK,SAAS,SAAS,YAAY,MAAM,CAAC;AAC/I,yBAAmB,qBAAqB,gDAAgD,kBAAkB,iBAAiB;AAC3H;AAAA,IACF;AAAA;AAEE,yBAAmB;AAAA;AAEvB,WAAS,YAAY,gBAAgB,MAAM;AAC3C,MAAI,kBAAkB;AACpB,aAAS,YAAY,WAAW,MAAM;AACtC,aAAS,YAAY,YAAY,MAAM;AACvC,UAAM,IAAI,MAAM,gBAAgB;AAAA,EAClC;AACA,SAAO,CAAC,YAAY,WAAW;AACjC;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,+BAA6B,SAAS,KAAK,MAAM,0BAA0B,MAAM;AAAA,IAC/E;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,uBAAuB,MAAM,QAAQ;AAC5C,QAAM,EAAE,SAAS,UAAU,OAAO,IAAI;AACtC,QAAM,EAAE,MAAM,SAAS,WAAW,IAAI;AACtC,QAAM,aAAa,QAAQ,MAAM;AACjC,QAAM,iBAAiB,SAAS,SAAS,WAAW,QAAQ,aAAa,GAAG,UAAU,EAAE;AACxF,QAAM,uBAAuB,aAAa,IAAI,iBAAiB,IAAI;AACnE,QAAM,aAAa;AACnB,MAAI,aAAa,GAAG;AAClB,UAAM,IAAI,MAAM,qBAAqB,wDAAwD,CAAC;AAAA,EAChG;AACA,QAAM,cAAc,KAAK,MAAM,MAAM;AACrC,cAAY,KAAK;AACjB,QAAM,SAAS,SAAS,UAAU,IAAI,KAAK,MAAM,EAAE;AACnD,QAAM,YAAY,SAAS,UAAU,IAAI,QAAQ,MAAM,EAAE;AACzD,QAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAM,SAAS,SAAS,WAAW,aAAa,KAAK,KAAK;AAC1D,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,kBAAkB,SAAS,WAAW,CAAC,CAAC,GAAG,OAAO;AACxD,QAAM,oBAAoB,SAAS,UAAU,IAAI,gBAAgB,MAAM,EAAE;AACzE,6BAA2B,QAAQ,SAAS,KAAK,QAAQ,KAAK,MAAM,IAAI,WAAW,cAAc,UAAU,mBAAmB,QAAQ,CAAC;AACvI,QAAM,uBAAuB,SAAS,SAAS,gBAAgB,MAAM;AACrE,MAAI;AACJ,UAAQ,qBAAqB;AAAA,SACtB,GAAG;AACN,yBAAmB,qBAAqB,wDAAwD;AAChG;AAAA,IACF;AAAA,SACK,GAAG;AACN,yBAAmB,qBAAqB,6DAA6D;AACrG;AAAA,IACF;AAAA,SACK;AACH,yBAAmB,qBAAqB,yDAAyD,qBAAqB,IAAI,qBAAqB,EAAE;AACjJ;AAAA,SACG;AACH,yBAAmB,qBAAqB,uDAAuD,qBAAqB,IAAI,qBAAqB,IAAI,qBAAqB,EAAE;AACxK;AAAA;AAEA,yBAAmB;AAAA;AAEvB,WAAS,YAAY,gBAAgB,MAAM;AAC3C,MAAI,kBAAkB;AACpB,aAAS,YAAY,OAAO,MAAM;AAClC,UAAM,IAAI,MAAM,gBAAgB;AAAA,EAClC;AACA,SAAO;AACT;AAGA,SAAS,mBAAmB,MAAM;AAChC,SAAO,uBAAuB,MAAM,IAAI;AAC1C;AACA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,kBAAkB,MAAM;AAC/B,SAAO,uBAAuB,MAAM,KAAK;AAC3C;AACA,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,iBAAiB,KAAK,IAAI;AAClC,QAAM,QAAQ,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AACzD,QAAM,aAAa,qBAAqB,iBAAiB,GAAG,iBAAiB,KAAK;AAClF,QAAM,QAAQ,IAAI,MAAM,EAAE,MAAM,MAAM,EAAE,KAAK,CAAC;AAC9C,QAAMpB,QAAO,EAAE,MAAM,MAAM;AAC3B,SAAO,WAAW,IAAI,CAAC,OAAO;AAC5B,UAAM,aAAa,CAAC,GAAGA,KAAI;AAC3B,eAAW,SAAS;AACpB,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,OAAO,MAAM,WAAW,GAAG,SAAS,SAAS,CAAC;AAC9F,UAAM,UAAU;AAChB,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,wBAAwB,IAAI;AAG9C,IAAI,gBAAgB,wBAAwB,MAAM;AAGlD,IAAI,0BAA0B;AAC9B,IAAI,2BAA2B,yBAAyB,mBAAmB,uBAAuB;AAGlG,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,aAAW,SAAS,KAAK,MAAM,MAAM,MAAM;AAAA,IACzC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAAsB,OAAM,IAAI;AAClB,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,WAAS,KAAKA,QAAO,SAAS,EAAE,QAAQ,KAAK;AAC7C,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,qBAAmB,SAAS,KAAK,MAAM,cAAc,MAAM;AAAA,IACzD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAO,KAAK,SAAAV,UAAS,WAAW,SAAS,cAAc,aAAa,eAAe,IAAI;AAC/F,QAAM,EAAE,kBAAkB,YAAY,YAAY,WAAW,eAAe,OAAO,QAAQ,KAAK,MAAM,SAAS,SAAS,IAAI,mBAAmB,UAAU,EAAE,OAAO,OAAO,KAAKA,UAAS,WAAW,SAAS,cAAc,aAAa,cAAc;AACpP,MAAI;AACJ,MAAI,YAAY;AACd,aAAS,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAAA,EACtF,WAAW,aAAa,eAAe;AACrC,iBAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,yCAAyC,EAAE,MAAM,QAAQ;AACxG,UAAMZ,QAAO,mBAAmB,gBAAgB,QAAQ,MAAM,QAAQ;AACtE,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,QAAQ,MAAAA,MAAK,EAAE,CAAC;AAC1F,aAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAC5F,aAAS,YAAY,OAAO,MAAM;AAAA,EACpC,OAAO;AACL,UAAM,MAAM,SAAS,WAAW,kBAAkB,SAAS;AAC3D,UAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,gBAAgB,IAAI,WAAW,IAAI,WAAW,aAAa,eAAe,EAAE,KAAK,CAAC,EAAE,MAAM;AAChG,UAAM,aAAa,IAAI,WAAW,IAAI,WAAW,MAAM,EAAE,MAAM;AAC/D,UAAM,WAAW,IAAI,WAAW,IAAI,WAAW,IAAI,EAAE,MAAM;AAC3D,UAAM,eAAe,IAAI,WAAW,IAAI,WAAW,QAAQ,EAAE,MAAM;AACnE,UAAM,mBAAmB,IAAI,WAAW,IAAI,WAAW,gBAAgB,EAAE,MAAM;AAC/E,UAAM,kBAAkB,IAAI,WAAW,IAAI,WAAW,aAAa,eAAe,gBAAgB,CAAC,EAAE,MAAM;AAC3G,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,qBAAiB,KAAK,eAAe,EAAE,MAAM,QAAQ,YAAY,UAAU,cAAc,kBAAkB,iBAAiB,iBAAiB,QAAQ,KAAK;AAC1J,aAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AACzF,aAAS,YAAY,IAAI,MAAM;AAAA,EACjC;AACA,SAAO;AACT;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,WAAW,IAAI;AAC7B,QAAM,EAAE,WAAW,aAAa,SAAS,UAAU,WAAW,UAAU,uBAAuB,IAAI;AACnG,QAAM,QAAQ,SAAS,SAAS,KAAK,MAAM;AAC3C,QAAM,cAAc,SAAS,SAAS,WAAW,MAAM;AACvD,QAAM,CAAC,QAAQ,YAAY,IAAI,iBAAiB,OAAO,aAAa,WAAW,aAAa,SAAS,WAAW,UAAU,sBAAsB;AAChJ,QAAM,YAAY,SAAS,WAAW,CAAC,OAAO,MAAM,GAAG,QAAQ;AAC/D,QAAM,gBAAgB,SAAS,UAAU,IAAI,UAAU,MAAM;AAC7D,gBAAc,cAAc;AAC5B,QAAM,kBAAkB,SAAS,WAAW,WAAW,OAAO,OAAO;AACrE,QAAM,sBAAsB,SAAS,mBAAmB,eAAe;AACvE,sBAAoB,IAAI,YAAY;AACpC,SAAO,CAAC,WAAW,eAAe;AACpC;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,UAAU,IAAI;AACrC,QAAM,EAAE,UAAU,IAAI;AACtB,QAAM,YAAY,SAAS,SAAS,OAAO,MAAM;AACjD,QAAM,gBAAgB,SAAS,SAAS,UAAU,MAAM;AACxD,QAAM,CAAC,SAAS,QAAQ,KAAK,IAAI,gBAAgB,WAAW,cAAc,IAAI,SAAS;AACvF,QAAMoB,cAAa,OAAO;AAC1B,QAAM,aAAa,SAAS,WAAW,CAACA,aAAY,CAAC,GAAG,OAAO;AAC/D,QAAM,iBAAiB,SAAS,mBAAmB,UAAU;AAC7D,iBAAe,IAAI,OAAO;AAC1B,QAAM,YAAY,SAAS,WAAW,CAACA,WAAU,GAAG,QAAQ;AAC5D,QAAM,gBAAgB,SAAS,UAAU,IAAI,UAAU,MAAM;AAC7D,gBAAc,cAAc;AAC5B,QAAM,WAAW,SAAS,WAAW,CAAC,CAAC,GAAG,OAAO;AACjD,QAAM,eAAe,SAAS,mBAAmB,QAAQ;AACzD,eAAa,IAAI,KAAK;AACtB,SAAO,CAAC,YAAY,WAAW,QAAQ;AACzC;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,wBAAwB,MAAM;AACrC,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,WAAW,IAAI;AACvB,QAAM,YAAY,SAAS,SAAS,OAAO,MAAM;AACjD,QAAM,SAAS,2BAA2B,WAAW,UAAU;AAC/D,QAAM,MAAM,SAAS,WAAW,OAAO,OAAO,OAAO;AACrD,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,UAAQ,IAAI,MAAM;AAClB,SAAO;AACT;AACA,IAAI,gCAAgC;AAAA,EAClC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,0BAA0B;AAC9B,IAAI,aAAa,yBAAyB,KAAK,uBAAuB;AAGtE,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,YAAU,SAAS,KAAK,MAAM,KAAK,MAAM;AAAA,IACvC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,cAAc,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AACxG,MAAI,gBAAgB;AACpB,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAI,iBAAiB,KAAK;AACxB,eAAS;AACT,gBAAU;AACV,sBAAgB,qBAAqB,iBAAiB,cAAc,QAAQ,OAAO,MAAM,MAAM;AAAA,IACjG;AAAA,EACF;AACA,uBAAqB,2BAA2B,OAAO,eAAe,OAAO,MAAM,MAAM;AACzF,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,aAAa;AAC1G,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,MAAM,SAAS,WAAW,UAAU,OAAO,KAAK;AACtD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,YAAQ,SAAS,YAAY,SAAS,IAAI,QAAQ,KAAK;AAAA,EACzD;AACA,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,YAAY;AAClF,QAAI,QAAQ;AAAA,EACd;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,aAAa,wBAAwB,GAAG;AAG5C,IAAI,cAAc,wBAAwB,IAAI;AAG9C,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,aAAW,SAAS,KAAK,MAAM,MAAM,MAAM;AAAA,IACzC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,WAAW,IAAI,MAAM,EAAE,MAAM,MAAM;AACzC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,aAAS,MAAM,EAAE,MAAM,MAAM,KAAK;AAAA,EACpC;AACA,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,QAAM,gBAAgB,IAAI,WAAW,IAAI,WAAW,QAAQ,EAAE,MAAM;AACpE,QAAM,MAAM,SAAS,WAAW,UAAU,EAAE,KAAK;AACjD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,WAAS,KAAK,aAAa,EAAE,MAAM,QAAQ,eAAe,SAAS,QAAQ,SAAS,IAAI,QAAQ,KAAK;AACrG,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,aAAW,SAAS,KAAK,MAAM,MAAM,MAAM;AAAA,IACzC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,IAAI,QAAQ,CAAC,EAAE,QAAQ,SAAS,UAAU,MAAM,MAAM;AACpD,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,QAAM,cAAc,EAAE,MAAM,MAAM;AAClC,cAAY,YAAY,SAAS,KAAK;AACtC,QAAM,YAAY,SAAS,WAAW,aAAa,EAAE,KAAK;AAC1D,QAAM,cAAc,SAAS,UAAU,IAAI,UAAU,MAAM,EAAE;AAC7D,QAAM,aAAa,SAAS,WAAW,aAAa,OAAO;AAC3D,QAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,WAAS,KAAK,aAAa,EAAE,MAAM,QAAQ,SAAS,EAAE,QAAQ,GAAG,QAAQ,aAAa,YAAY;AAClG,SAAO,CAAC,WAAW,UAAU;AAC/B;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,kBAAgB,SAAS,KAAK,MAAM,WAAW,MAAM;AAAA,IACnD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,WAAW,IAAI;AACtC,QAAM,EAAE,eAAe,UAAU,WAAW,YAAY,IAAI;AAC5D,QAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,QAAM,CAAC,WAAW,QAAQ,IAAI,eAAe,OAAO,cAAc,CAAC,aAAa,UAAU;AAC1F,QAAM,WAAW;AAAA,IACf;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACA,QAAMR,WAAU,IAAI,WAAW,IAAI,WAAW,aAAa,eAAe,OAAO,KAAK,CAAC,EAAE,MAAM;AAC/F,QAAM,MAAM,SAAS,WAAW,UAAU,OAAO,KAAK;AACtD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,YAAY,SAAS,UAAU,IAAI,OAAO,MAAM;AACtD,QAAM,UAAU,UAAU;AAC1B,QAAM,iBAAiB,SAAS,UAAU,IAAI,WAAW,MAAM;AAC/D,QAAM,eAAe,eAAe;AACpC,QAAM,sBAAsB,kBAAkB,YAAY,IAAI;AAC9D,MAAI;AACJ,UAAQ;AAAA,SACD;AACH,mBAAa;AACb;AAAA,SACG;AACH,mBAAa;AACb;AAAA,SACG;AACH,mBAAa;AACb;AAAA,SACG;AACH,mBAAa;AACb;AAAA;AAEA,mBAAa;AACb;AAAA;AAEJ,gBAAc,SAAS,cAAc,WAAW,MAAM,KAAK,GAAG,OAAO,WAAW,UAAU,aAAa,YAAY,aAAaA,UAAS,OAAO,MAAM,SAAS,GAAG,qBAAqB,YAAY,WAAW,KAAK;AACnN,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,IAAI;AAClB,MAAI,EAAE,KAAK,IAAI;AACf,MAAI,OAAO,GAAG;AACZ,YAAQ,MAAM,MAAM;AAAA,EACtB;AACA,QAAM,aAAa,MAAM,MAAM;AAC/B,QAAM,OAAO,MAAM,MAAM;AACzB,QAAM,WAAW,IAAI,MAAM,OAAO,CAAC;AACnC,MAAI,WAAW;AACf,WAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,QAAI,OAAO,MAAM;AACf,eAAS,cAAc,MAAM,MAAM;AAAA,IACrC;AAAA,EACF;AACA,QAAM,OAAO,IAAI,MAAM,UAAU;AACjC,QAAM,QAAQ,IAAI,MAAM,IAAI,EAAE,KAAK,CAAC;AACpC,QAAMZ,QAAO,MAAM,MAAM,MAAM;AAC/B,EAAAA,MAAK,QAAQ;AACb,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,UAAM,QAAQ;AACd,SAAK,MAAM,OAAO,EAAE,QAAQ,EAAE,GAAG,MAAM,GAAG,OAAO,EAAE,OAAO,MAAAA,MAAK,GAAG,SAAS,SAAS,CAAC;AAAA,EACvF;AACA,SAAO,KAAK,IAAI,CAAC,EAAE,QAAQ,MAAM,OAAO,EAAE,QAAQ,OAAO,OAAO,SAAS,EAAE;AAC7E;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,IAAI;AAC7C,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,UAAQ,KAAK,CAAC;AACd,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB;AAAA,EACnB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,WAAW,gBAAgB,gBAAgB;AACzC,iBAAe,YAAY;AAC7B;AAGA,IAAI,OAAO,IAAI;AACf,KAAK;AAAA,EACH;AAAA,EACA,YAAY,YAAY,SAAS,IAAI,WAAW;AAAA,IAC9C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC,CAAC;AACJ;AACA,KAAK,aAAa,gCAAgC,YAAY;AAC5D,MAAI,KAAK,IAAI,SAAS,GAAG;AACvB,WAAO;AAAA,EACT;AACA,MAAI;AACF,QAAI,eAAe,EAAE,MAAM,YAAY,IAAI,kBAAkB,CAAC,CAAC;AAC/D,WAAO,YAAY,SAAS,IAAI,WAAW;AAAA,MACzC;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF,CAAC,CAAC;AAAA,EACJ,SAAS,IAAP;AACA,WAAO;AAAA,EACT;AACF,CAAC;AAGD,IAAI,iCAAiC,QAAQ,wCAAwC,CAAC;AACtF,IAAI,gDAAgD,QAAQ,+CAA+C,CAAC;AAC5G,IAAI,qBAAqB,QAAQ,0BAA0B,CAAC;AAC5D,IAAI,0BAA0B,+BAA+B,WAAW;AACxE,IAAI,cAAc,mBAAmB,WAAW;AAChD,IAAI,cAAc,cAAc,cAAc;AAAA,EAC5C,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,OAAO;AACZ,SAAK,mBAAmB;AACxB,SAAK,KAAK,KAAK,qBAAqB,YAAY;AAChD,yBAAqB,KAAK,KAAK,KAAK,gBAAgB;AACpD,SAAK,YAAY,IAAI,YAAY,MAAM,OAAO,CAAC;AAAA,EACjD;AAAA,EACA,MAAM,QAAQ,OAAO,OAAO;AAC1B,UAAM,SAAS,EAAE,IAAI,KAAK,mBAAmB;AAC7C,SAAK,KAAK,QAAQ,QAAQ,OAAO,OAAO,CAAC;AACzC,WAAO;AAAA,EACT;AAAA,EACA,aAAa;AACX,WAAO,KAAK,UAAU,WAAW;AAAA,EACnC;AAAA,EACA,MAAM,KAAK,GAAG;AACZ,UAAM,QAAQ,aAAa,IAAI;AAC/B,MAAE;AACF,UAAM,WAAW,aAAa,IAAI,IAAI;AACtC,WAAO,EAAE,SAAS;AAAA,EACpB;AAAA,EACA,KAAK,QAAQ,QAAQ,OAAO,OAAO,UAAU;AAC3C,UAAM,KAAK,KAAK;AAChB,QAAI,UAAU,UAAU;AACtB,YAAM,cAAc;AACpB,WAAK,UAAU,IAAI,QAAQ,EAAE,IAAI,aAAa,OAAO,OAAO,cAAc,MAAM,SAAS,CAAC;AAC1F;AAAA,IACF;AACA,UAAMA,QAAO,aAAa,cAAc,KAAK;AAC7C,UAAM,WAAWA,QAAO,aAAa,gBAAgB,KAAK;AAC1D,UAAM,eAAe,KAAK,KAAK,QAAQ,QAAQ;AAC/C,SAAK,UAAU,IAAI,QAAQ,EAAE,IAAI,cAAc,OAAO,OAAO,SAAS,CAAC;AACvE,SAAK,KAAK,KAAK,eAAe,IAAIA,OAAM,YAAY;AACpD,QAAI,UAAU,MAAM;AAClB,WAAK,KAAK,OAAO,IAAI,IAAI,WAAW,OAAO,QAAQ,OAAO,YAAY,QAAQ,GAAG,YAAY;AAAA,IAC/F;AAAA,EACF;AAAA,EACA,MAAM,KAAK,QAAQ;AACjB,WAAO,KAAK,SAAS,MAAM;AAAA,EAC7B;AAAA,EACA,SAAS,QAAQ,OAAO,KAAK;AAC3B,UAAM,EAAE,cAAc,OAAO,OAAO,YAAY,IAAI,KAAK,UAAU,IAAI,MAAM;AAC7E,QAAI,UAAU,UAAU;AACtB,WAAK,SAAS,QAAQ,UAAU,OAAO,OAAO,QAAQ,OAAO,YAAY,SAAS;AAChF,eAAO;AAAA,MACT;AACA,aAAO,YAAY,MAAM,OAAO,GAAG;AAAA,IACrC;AACA,YAAQ,SAAS;AACjB,UAAM,OAAO,aAAa,cAAc,KAAK;AAC7C,UAAM,mBAAmB,aAAa,gBAAgB,KAAK;AAC3D,UAAM,QAAQ,KAAK,KAAK,OAAO,MAAM,eAAe,QAAQ,kBAAkB,eAAe,MAAM,gBAAgB;AACnH,WAAO,qBAAqB,MAAM,QAAQ,KAAK;AAAA,EACjD;AAAA,EACA,YAAY,QAAQ,QAAQ,OAAO;AACjC,QAAI,KAAK,UAAU,IAAI,MAAM,GAAG;AAC9B,YAAM,OAAO,KAAK,UAAU,IAAI,MAAM;AACtC,WAAK;AACL,UAAI,CAAC,SAAS,KAAK,WAAW,GAAG;AAC/B,eAAO;AAAA,MACT;AACA,WAAK,KAAK,MAAM,KAAK,YAAY;AACjC,WAAK,KAAK,KAAK,YAAY,KAAK,EAAE;AAClC,WAAK,UAAU,OAAO,MAAM;AAAA,IAC9B;AACA,WAAO;AAAA,EACT;AAAA,EACA,SAAS,QAAQ;AACf,QAAI,KAAK,UAAU,IAAI,MAAM,GAAG;AAC9B,YAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,aAAO,WAAW;AAAA,IACpB;AACA,WAAO;AAAA,EACT;AAAA,EACA,OAAO,QAAQ;AACb,UAAM,OAAO,KAAK,UAAU,IAAI,MAAM;AACtC,QAAI,QAAQ,MAAM;AAChB,WAAK;AAAA,IACP;AAAA,EACF;AAAA,EACA,iBAAiB;AACf,WAAO;AAAA,EACT;AAAA,EACA,gBAAgB,QAAQ;AACtB,WAAO,KAAK,UAAU,IAAI,MAAM,EAAE;AAAA,EACpC;AAAA,EACA,UAAU;AACR,SAAK,KAAK,KAAK,QAAQ;AACvB,QAAI,aAAa,KAAK,MAAM;AAC1B,WAAK,KAAK,QAAQ,oBAAoB;AAAA,IACxC;AACA,SAAK,OAAO;AAAA,EACd;AAAA,EACA,SAAS;AACP,WAAO,EAAE,YAAY,MAAM;AAAA,EAC7B;AAAA,EACA,WAAW,OAAO,OAAO,cAAc;AACrC,QAAI;AACJ,QAAI,gBAAgB,MAAM;AACxB,eAAS,KAAK,MAAM,MAAM,OAAO,KAAK;AAAA,IACxC,OAAO;AACL,YAAM,KAAK,KAAK;AAChB,eAAS,EAAE,GAAG;AACd,WAAK,UAAU,IAAI,QAAQ,EAAE,IAAI,cAAc,OAAO,OAAO,UAAU,EAAE,CAAC;AAC1E,YAAMA,QAAO,aAAa,cAAc,KAAK;AAC7C,WAAK,KAAK,KAAK,eAAe,IAAIA,OAAM,YAAY;AAAA,IACtD;AACA,WAAO,EAAE,QAAQ,OAAO,MAAM;AAAA,EAChC;AAAA,EACA,mBAAmB,EAAE,OAAO,OAAO,OAAO,GAAG;AAC3C,UAAM,UAAU,KAAK,KAAK,OAAO;AACjC,UAAM,EAAE,aAAa,IAAI,KAAK,UAAU,IAAI,MAAM;AAClD,UAAMA,QAAO,aAAa,cAAc,KAAK;AAC7C,YAAQ;AAAA,WACD;AACH,eAAO,IAAI,aAAa,SAAS,cAAcA,KAAI;AAAA,WAChD;AACH,eAAO,IAAI,WAAW,SAAS,cAAcA,KAAI;AAAA,WAC9C;AACH,eAAO,IAAI,WAAW,SAAS,cAAcA,KAAI;AAAA;AAEjD,cAAM,IAAI,MAAM,iBAAiB,OAAO;AAAA;AAAA,EAE9C;AACF;AACA,SAAS,0BAA0B,MAAM;AACvC,SAAO,CAAC,SAAS,aAAa;AAC5B,iBAAa,MAAM,MAAM,EAAE,aAAa,cAAc,CAAC,EAAE,KAAK,CAAC,aAAa;AAC1E,UAAI,CAAC,SAAS,OAAO;AACnB,gBAAQ,IAAI,EAAE,uCAAuC,OAAO;AAAA,MAC9D;AACA,eAAS,YAAY,EAAE,KAAK,CAAC,WAAW;AACtC,oBAAY,YAAY,QAAQ,OAAO,EAAE,KAAK,CAAC,WAAW;AACxD,mBAAS,OAAO,UAAU,OAAO,MAAM;AAAA,QACzC,CAAC;AAAA,MACH,CAAC;AAAA,IACH,CAAC;AACD,WAAO,CAAC;AAAA,EACV;AACF;AACA,SAAS,oBAAoB,eAAe,kBAAkB,kBAAkB;AAC9E,MAAI,YAAY,MAAM;AACpB,WAAO;AAAA,EACT;AACA,MAAI,OAAO;AACX,MAAI,iBAAiB,kBAAkB;AACrC,WAAO;AAAA,EACT,WAAW,eAAe;AACxB,WAAO;AAAA,EACT;AACA,MAAI,eAAe,MAAM;AACvB,QAAI,YAAY,SAAS,MAAM;AAC7B,aAAO,YAAY;AAAA,IACrB;AAAA,EACF;AACA,SAAO,mBAAmB;AAC5B;AACA,eAAe,OAAO;AACpB,QAAM,CAAC,eAAe,gBAAgB,IAAI,MAAM,QAAQ,IAAI;AAAA,IAC1D,IAAI,EAAE,SAAS,uBAAuB;AAAA,IACtC,IAAI,EAAE,SAAS,8BAA8B;AAAA,EAC/C,CAAC;AACD,SAAO,IAAI,QAAQ,CAAC,SAAS,WAAW;AACtC,UAAM,gBAAgB,CAAC;AACvB,kBAAc,aAAa,CAAC,MAAM,WAAW;AAC3C,UAAI,KAAK,SAAS,YAAY,GAAG;AAC/B,cAAM,WAAW,8CAA8C,mBAAmB,QAAQ,OAAO,KAAK;AACtG,cAAM,OAAO,IAAI,KAAK,CAAC,QAAQ,GAAG,EAAE,MAAM,yBAAyB,CAAC;AACpE,eAAO,IAAI,gBAAgB,IAAI;AAAA,MACjC;AACA,UAAI,KAAK,SAAS,OAAO,GAAG;AAC1B,eAAO,oBAAoB,eAAe,kBAAkB,kBAAkB,OAAO,iBAAiB,MAAM;AAAA,MAC9G;AACA,aAAO,SAAS;AAAA,IAClB;AACA,QAAI,aAAa;AACf,oBAAc,kBAAkB,0BAA0B,oBAAoB,eAAe,kBAAkB,kBAAkB,OAAO,iBAAiB,EAAE,CAAC;AAAA,IAC9J;AACA,QAAI,cAAc;AAClB,kBAAc,UAAU,MAAM;AAC5B,UAAI,aAAa;AACf;AAAA,MACF;AACA,UAAI,aAAa;AACf;AAAA,MACF;AACA,oBAAc;AACd,YAAM,YAAY;AAClB,aAAO,EAAE,SAAS,UAAU,CAAC;AAAA,IAC/B;AACA,QAAI;AACJ,QAAI,oBAAoB,iBAAiB,YAAY,MAAM;AACzD,oBAAc,sBAAsB,IAAI,KAAK,CAAC,yCAAyC,wBAAwB,SAAS,CAAC,GAAG,EAAE,MAAM,kBAAkB,CAAC;AACvJ,aAAO,wBAAwB,aAAa;AAAA,IAC9C,OAAO;AACL,aAAO,YAAY,aAAa;AAAA,IAClC;AACA,SAAK,KAAK,CAAC,WAAW;AACpB,oBAAc;AACd,oBAAc;AACd,YAAM,iBAAiB;AACvB,aAAO,OAAO;AAAA,QACZ,MAAM,OAAO,MAAM,QAAQ,MAAM,CAAC,CAAC;AAAA,QACnC,sBAAsB,OAAO,MAAM,2BAA2B,MAAM,CAAC,QAAQ,CAAC;AAAA,QAC9E,iBAAiB,OAAO,MAAM,qBAAqB,UAAU,CAAC,CAAC;AAAA,QAC/D,gBAAgB,OAAO,MAAM,mBAAmB,MAAM;AAAA,UACpD;AAAA,UACA;AAAA,UACA;AAAA,QACF,CAAC;AAAA,QACD,aAAa,OAAO,MAAM,gBAAgB,gBAAgB,CAAC,QAAQ,CAAC;AAAA,QACpE,SAAS,OAAO,MAAM,WAAW,gBAAgB,CAAC,CAAC;AAAA,MACrD;AACA,cAAQ,EAAE,MAAM,OAAO,CAAC;AAAA,IAC1B,CAAC,EAAE,MAAM,MAAM;AAAA,EACjB,CAAC;AACH;AACA,SAAS,qBAAqB,SAAS,OAAO;AAC5C,UAAQ;AAAA,SACD;AACH,aAAO,IAAI,aAAa,OAAO;AAAA,SAC5B;AACH,aAAO,IAAI,WAAW,OAAO;AAAA,SAC1B;AACH,aAAO,IAAI,WAAW,OAAO;AAAA;AAE7B,YAAM,IAAI,MAAM,iBAAiB,OAAO;AAAA;AAE9C;AACA,IAAI,kBAAkB;AAAA,EACpB;AAAA,EACA;AAAA,EACA;AACF;AACA,IAAI,WAAW;AACf,IAAI,iBAAiB;AACrB,IAAI,cAAc,CAAC;AACnB,IAAI,cAAc;AAClB,IAAI,cAAc;AAClB,SAAS,YAAY,MAAM,mBAAmB,OAAO;AACnD,kBAAgB,mGAAmG;AACnH,MAAI,aAAa;AACf,UAAM,IAAI,MAAM,gIAAgI;AAAA,EAClJ;AACA,aAAW;AACX,gBAAc;AAChB;AACA,SAAS,aAAa,iBAAiB,mBAAmB,OAAO;AAC/D,MAAI,aAAa;AACf,UAAM,IAAI,MAAM,iIAAiI;AAAA,EACnJ;AACA,MAAI,OAAO,oBAAoB,UAAU;AACvC,qBAAiB;AAAA,EACnB,OAAO;AACL,kBAAc;AACd,UAAM,eAAe,gBAAgB,OAAO,CAAC,SAAS,YAAY,SAAS,IAAI;AAC/E,QAAI,aAAa,SAAS,GAAG;AAC3B,YAAM,IAAI,MAAM,2DAA2D,aAAa,KAAK,GAAG,gKAAgK;AAAA,IAClQ;AAAA,EACF;AACA,gBAAc;AAChB;AACA,IAAI,eAAe;AACnB,IAAI,qBAAqB;AACzB,SAAS,gBAAgB,YAAY;AACnC,iBAAe;AACjB;AACA,SAAS,kBAAkB;AACzB,MAAI,uBAAuB,IAAI;AAC7B,UAAM,IAAI,MAAM,+BAA+B;AAAA,EACjD;AACA,SAAO;AACT;AAGA,IAAI,WAAW;AAGf,IAAI,gBAAgB;AACpB,gBAAgB,QAAQ,YAAY;AAClC,QAAM,EAAE,KAAK,IAAI,MAAM,KAAK;AAC5B,SAAO,IAAI,YAAY,IAAI;AAC7B,GAAG,aAAa;AAGhB,IAAI,OAAO,IAAI;AACf,KAAK,aAAa,qCAAqC,MAAM,EAAE;AAC/D,KAAK,aAAa,sBAAsB,MAAM,IAAI;AAClD,KAAK,aAAa,iCAAiC,MAAM,CAAC;AAC1D,KAAK,aAAa,8BAA8B,MAAM,EAAE;AACxD,KAAK,aAAa,qCAAqC,MAAM,KAAK;AAClE,KAAK,aAAa,4BAA4B,MAAM,KAAK;AACzD,KAAK,aAAa,qCAAqC,MAAM,GAAG;AAChE,KAAK,aAAa,2BAA2B,MAAM,KAAK;AACxD,KAAK,aAAa,kCAAkC,MAAM,KAAK;AAG/D,IAAI;AAAA,CACH,SAAS,eAAe;AACvB,gBAAc,cAAc,SAAS,KAAK;AAC1C,gBAAc,cAAc,SAAS,KAAK;AAC1C,gBAAc,cAAc,SAAS,KAAK;AAC1C,gBAAc,cAAc,SAAS,KAAK;AAC1C,gBAAc,cAAc,WAAW,KAAK;AAC5C,gBAAc,cAAc,aAAa,KAAK;AAC9C,gBAAc,cAAc,mBAAmB,KAAK;AACpD,gBAAc,cAAc,UAAU,KAAK;AAC3C,gBAAc,cAAc,gBAAgB,KAAK;AACjD,gBAAc,cAAc,iBAAiB,KAAK;AAClD,gBAAc,cAAc,eAAe,MAAM;AACjD,gBAAc,cAAc,wBAAwB,MAAM;AAC1D,gBAAc,cAAc,aAAa,MAAM;AAC/C,gBAAc,cAAc,SAAS,MAAM;AAC3C,gBAAc,cAAc,WAAW,MAAM;AAC7C,gBAAc,cAAc,SAAS,MAAM;AAC3C,gBAAc,cAAc,SAAS,MAAM;AAC3C,gBAAc,cAAc,2BAA2B,MAAM;AAC7D,gBAAc,cAAc,2BAA2B,MAAM;AAC/D,GAAG,iBAAiB,eAAe,CAAC,EAAE;AACtC,IAAI,OAAO;AACX,IAAI,wBAAwB;AAC5B,IAAI,wBAAwB;AAC5B,IAAI,OAAO;AACX,IAAI,OAAO;AACX,IAAI,sBAAsB;AAC1B,IAAI,OAAO;AACX,IAAI,SAAS;AACb,IAAI,aAAa;AACjB,IAAI,WAAW;AACf,IAAI,eAAe;AACnB,IAAI,iBAAiB;AACrB,IAAI,qBAAqB;AACzB,IAAI,QAAQ;AACZ,IAAI,YAAY;AAChB,IAAI,cAAc;AAClB,IAAI,kBAAkB;AACtB,IAAI,eAAe;AACnB,IAAI,mBAAmB;AAAA;AAEvB,IAAI,qBAAqB;AAAA;AAAA;AAAA;AAIzB,IAAI,yBAAyB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAc7B,IAAI,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAMf,IAAI,eAAe;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAsBnB,IAAI,aAAa;AACjB,IAAI,iBAAiB;AACrB,IAAI,OAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAYX,IAAI,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAqBX;AAAA;AAAA;AAGJ,IAAI,SAAS;AACb,IAAI,aAAa;AAAA;AAAA;AAAA;AAIjB,SAAS,gBAAgB,KAAK,SAAS;AACrC,QAAM,kBAAkB,UAAU,yBAAyB;AAC3D,SAAO,UAAU;AAAA,iCACc;AAAA;AAAA,QAEzB,kBAAkB;AAAA;AAAA,MAEpB,kBAAkB;AAAA,aACX;AAAA;AAEb;AACA,SAAS,kBAAkB,MAAM,SAAS;AACxC,UAAQ;AAAA,SACD,aAAa;AAChB,aAAO;AAAA,SACJ,aAAa;AAChB,aAAO;AAAA,SACJ,aAAa;AAChB,aAAO;AAAA,SACJ,aAAa;AAChB,aAAO;AAAA,SACJ,aAAa;AAChB,aAAO,UAAU,aAAa;AAAA,SAC3B,aAAa;AAChB,aAAO,UAAU,eAAe;AAAA,SAC7B,aAAa;AAChB,aAAO,UAAU,qBAAqB;AAAA,SACnC,aAAa;AAChB,aAAO,UAAU,YAAY;AAAA,SAC1B,aAAa;AAChB,aAAO,UAAU,kBAAkB;AAAA,SAChC,aAAa;AAChB,aAAO,UAAU,mBAAmB;AAAA,SACjC,aAAa;AAChB,aAAO,UAAU,iBAAiB;AAAA,SAC/B,aAAa;AAChB,aAAO;AAAA,SACJ,aAAa;AAChB,aAAO,UAAU,eAAe;AAAA,SAC7B,aAAa;AAChB,aAAO,UAAU,aAAa;AAAA,SAC3B,aAAa;AAChB,aAAO,gBAAgB,OAAO,OAAO;AAAA,SAClC,aAAa;AAChB,aAAO,gBAAgB,OAAO,OAAO;AAAA,SAClC,aAAa;AAChB,aAAO,UAAU,WAAW;AAAA,SACzB,aAAa;AAChB,aAAO;AAAA,SACJ,aAAa;AAChB,aAAO;AAAA;AAEP,YAAM,IAAI,MAAM,cAAc,0BAA0B;AAAA;AAE9D;AAGA,IAAI;AAAA,CACH,SAAS,cAAc;AACtB,eAAa,aAAa,SAAS,KAAK;AACxC,eAAa,aAAa,UAAU,KAAK;AACzC,eAAa,aAAa,SAAS,KAAK;AACxC,eAAa,aAAa,UAAU,KAAK;AACzC,eAAa,aAAa,SAAS,KAAK;AACxC,eAAa,aAAa,SAAS,KAAK;AACxC,eAAa,aAAa,WAAW,KAAK;AAC1C,eAAa,aAAa,WAAW,KAAK;AAC1C,eAAa,aAAa,YAAY,KAAK;AAC3C,eAAa,aAAa,SAAS,KAAK;AACxC,eAAa,aAAa,iBAAiB,MAAM;AACjD,eAAa,aAAa,SAAS,MAAM;AACzC,eAAa,aAAa,UAAU,MAAM;AAC1C,eAAa,aAAa,WAAW,MAAM;AAC3C,eAAa,aAAa,eAAe,MAAM;AAC/C,eAAa,aAAa,WAAW,MAAM;AAC3C,eAAa,aAAa,SAAS,MAAM;AACzC,eAAa,aAAa,UAAU,MAAM;AAC1C,eAAa,aAAa,aAAa,MAAM;AAC7C,eAAa,aAAa,UAAU,MAAM;AAC1C,eAAa,aAAa,YAAY,MAAM;AAC5C,eAAa,aAAa,UAAU,MAAM;AAC1C,eAAa,aAAa,YAAY,MAAM;AAC9C,GAAG,gBAAgB,cAAc,CAAC,EAAE;AACpC,IAAI,OAAO;AACX,IAAI,QAAQ;AACZ,IAAI,OAAO;AACX,IAAI,QAAQ;AAAA;AAAA;AAAA;AAIZ,IAAI,SAAS;AACb,IAAI,OAAO;AACX,IAAI,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAgBf,IAAI,OAAO;AACX,IAAI,SAAS;AACb,IAAI,UAAU;AACd,IAAI,OAAO;AAAA;AAEX,IAAI,eAAe;AACnB,IAAI,OAAO;AACX,IAAI,aAAa;AACjB,IAAI,iBAAiB;AAAA;AAAA;AAAA;AAIrB,IAAI,QAAQ;AACZ,IAAI,SAAS;AACb,IAAI,aAAa;AACjB,IAAI,YAAY;AAAA;AAAA;AAGhB,IAAI,SAAS;AACb,IAAI,WAAW;AACf,IAAI,OAAO;AACX,IAAI,QAAQ;AAAA;AAAA;AAAA;AAIZ,IAAI,QAAQ;AACZ,IAAI,UAAU;AACd,IAAI,QAAQ;AAAA;AAAA;AAAA;AAIZ,IAAI,UAAU;AACd,SAAS,iBAAiB,MAAM,SAAS;AACvC,UAAQ;AAAA,SACD,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO,UAAU,WAAW;AAAA,SACzB,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO,UAAU,iBAAiB;AAAA,SAC/B,YAAY;AACf,aAAO,UAAU,YAAY;AAAA,SAC1B,YAAY;AACf,aAAO,UAAU,aAAa;AAAA,SAC3B,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA;AAEP,YAAM,IAAI,MAAM,cAAc,0BAA0B;AAAA;AAE9D;AAGA,IAAI,cAAc,CAAC,cAAc;AAC/B,UAAQ;AAAA,SACD;AACH,aAAO;AAAA,SACJ;AACH,aAAO;AAAA,SACJ;AACH,aAAO;AAAA,SACJ;AACH,aAAO;AAAA;AAEP,YAAM,IAAI,MAAM,GAAG,uCAAuC;AAAA;AAEhE;AACA,SAAS,oBAAoB,aAAa,4BAA4B,OAAO,SAAS,OAAO,eAAe,GAAG;AAC7G,MAAI,gBAAgB,MAAM;AACxB,WAAO;AAAA,EACT;AACA,MAAI,sBAAsB;AAC1B,MAAI,gBAAgB,UAAU;AAC5B,0BAAsB,iBAAiB,YAAY,MAAM;AAAA,EAC3D,WAAW,gBAAgB,QAAQ;AACjC,0BAAsB,iBAAiB,YAAY,MAAM,MAAM;AAAA,EACjE,WAAW,gBAAgB,OAAO;AAChC,0BAAsB,iBAAiB,YAAY,KAAK,MAAM;AAAA,EAChE,WAAW,gBAAgB,SAAS;AAClC,0BAAsB,iBAAiB,YAAY,OAAO,MAAM;AAAA,EAClE,WAAW,gBAAgB,SAAS;AAClC,0BAAsB,kBAAkB,aAAa,OAAO,MAAM;AAAA,EACpE,WAAW,gBAAgB,WAAW;AACpC,0BAAsB,iBAAiB,YAAY,SAAS,MAAM;AAAA,EACpE,WAAW,gBAAgB,aAAa;AACtC,0BAAsB,iBAAiB,YAAY,WAAW,MAAM;AAAA,EACtE,OAAO;AACL,UAAM,IAAI,MAAM,cAAc,8DAA8D;AAAA,EAC9F;AACA,QAAM,cAAc,SAAS,IAAI;AACjC,QAAM,WAAW,YAAY,WAAW;AACxC,MAAI,uBAAuB;AAC3B,MAAI,2BAA2B;AAC7B,2BAAuB;AAAA,0BACD,yBAAyB,yBAAyB;AAAA;AAAA,UAElE;AAAA;AAAA,EAER,OAAO;AACL,2BAAuB;AAAA,0BACD,yBAAyB,yBAAyB;AAAA,UAClE;AAAA;AAAA,EAER;AACA,SAAO;AACT;AACA,SAAS,sBAAsB,SAAS,aAAa;AACnD,SAAO;AAAA,QACD,UAAU,mDAAmD;AAAA,QAC7D,cAAc,uCAAuC;AAAA;AAE7D;AAGA,SAAS,4BAA4B,YAAY,cAAc;AAC7D,MAAI,KAAK,IAAI,GAAG,UAAU,IAAI,GAAG;AAC/B,UAAM,IAAI,MAAM,0DAA0D;AAAA,EAC5E;AACA,QAAM,YAAY,WAAW;AAC7B,QAAM,QAAQ,WAAW,IAAI,CAAC,MAAM,GAAG,gBAAgB,IAAI;AAC3D,QAAMY,WAAU,IAAI,MAAM,YAAY,CAAC;AACvC,EAAAA,SAAQ,YAAY,KAAK,MAAM,YAAY;AAC3C,WAAS,KAAK,YAAY,GAAG,MAAM,GAAG,EAAE,IAAI;AAC1C,IAAAA,SAAQ,MAAM,IAAIA,SAAQ,KAAK,QAAQ,MAAM,KAAK;AAAA,EACpD;AACA,SAAOA;AACT;AAGA,IAAI,kBAAkB,CAAC,QAAQ,SAAS,YAAY,WAAW;AAC7D,QAAM,aAAa,EAAE,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC9D,QAAM,SAAS,YAAY,YAAY,YAAY,OAAO;AAC1D,QAAM,SAAS,OAAO,mBAAmB,EAAE,MAAM,QAAQ,OAAO,QAAQ,YAAY,KAAK,CAAC;AAC1F,QAAM,WAAW,OAAO,sBAAsB;AAAA,IAC5C,SAAS,EAAE,QAAQ,YAAY,OAAO;AAAA,IACtC,OAAO,QAAQ,YAAY;AAAA,IAC3B,QAAQ;AAAA,EACV,CAAC;AACD,SAAO;AACT;AACA,SAAS,mBAAmB,MAAM;AAChC,MAAI,QAAQ,GAAG;AACb,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,OAAO;AACL,UAAM,MAAM,gBAAgB,2BAA2B;AAAA,EACzD;AACF;AACA,SAAS,aAAaH,QAAO;AAC3B,MAAIA,WAAU,GAAG;AACf,WAAO;AAAA,EACT,WAAWA,WAAU,GAAG;AACtB,WAAO;AAAA,EACT,WAAWA,WAAU,GAAG;AACtB,WAAO;AAAA,EACT,WAAWA,WAAU,GAAG;AACtB,WAAO;AAAA,EACT,WAAWA,WAAU,GAAG;AACtB,WAAO;AAAA,EACT,WAAWA,WAAU,GAAG;AACtB,WAAO;AAAA,EACT,OAAO;AACL,UAAM,MAAM,SAASA,6BAA4B;AAAA,EACnD;AACF;AACA,SAAS,oCAAoC;AAC3C,SAAO;AAAA,MACH,oBAAoB;AAAA;AAAA;AAG1B;AACA,SAAS,sBAAsB;AAC7B,SAAO;AAAA,IACL,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAQ3B;AACA,SAAS,yBAAyB;AAChC,SAAO;AAAA;AAAA;AAGT;AACA,SAAS,YAAY,WAAW,YAAY,SAAS;AACnD,QAAM,iBAAiB,CAAC;AACxB,iBAAe,KAAK;AAAA,+BACS,QAAQ,cAAc;AAAA,+BACtB,QAAQ,cAAc;AAAA,+BACtB,QAAQ,cAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAQ3C,eAAe,OAAO,IAAI,8BAA8B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,KAW7D;AACH,MAAI,QAAQ,cAAc;AACxB,mBAAe,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,uEAO+C,eAAe,WAAW,OAAO,QAAQ,MAAM;AAAA;AAAA,OAE/G;AACH,WAAO;AAAA,MACL;AAAA,MACA,eAAe,KAAK,IAAI;AAAA,MACxB,0BAA0B,WAAW,KAAK;AAAA,MAC1C,QAAQ,YAAY;AAAA,IACtB,EAAE,KAAK,IAAI;AAAA,EACb;AACA,MAAI,oBAAoB;AACxB,MAAI,wBAAwB;AAC5B,MAAI,qBAAqB;AACzB,UAAQ,cAAc,QAAQ,CAAC,GAAG,OAAO;AACvC,UAAM,cAAc,mBAAmB,UAAU,IAAI,MAAM,MAAM;AACjE,QAAI,gBAAgB,UAAU,gBAAgB,QAAQ;AACpD,8BAAwB;AAAA,IAC1B;AACA,QAAI,qBAAqB,uBAAuB;AAC9C,4BAAsB;AAAA,IACxB;AACA,wBAAoB;AACpB,0BAAsB,GAAG,EAAE,OAAO,CAAC,EAAE,YAAY,IAAI,EAAE,MAAM,CAAC,YAAY;AAAA,EAC5E,CAAC;AACD,QAAM,iBAAiB,mBAAmB,WAAW,MAAM,MAAM;AACjE,0BAAwB,mBAAmB,UAAU,mBAAmB;AACxE,MAAI,qBAAqB,uBAAuB;AAC9C,0BAAsB;AAAA,EACxB;AACA,sBAAoB;AACpB,wBAAsB,cAAc;AACpC,QAAM,gBAAgB,WAAW,MAAM,SAAS;AAChD,QAAM,kBAAkB,mBAAmB,aAAa;AACxD,0BAAwB,oBAAoB,UAAU,oBAAoB;AAC1E,MAAI,qBAAqB,uBAAuB;AAC9C,0BAAsB;AAAA,EACxB;AACA,sBAAoB;AACpB,wBAAsB;AAAA,4BACI;AAC1B,MAAI,QAAQ,MAAM;AAChB,QAAI,mBAAmB;AACrB,4BAAsB;AAAA,IACxB;AACA,wBAAoB;AACpB,0BAAsB;AAAA,EACxB;AACA,MAAI,QAAQ,UAAU;AACpB,QAAI,mBAAmB;AACrB,4BAAsB;AAAA,IACxB;AACA,0BAAsB,QAAQ;AAAA,EAChC;AACA,wBAAsB;AACtB,iBAAe,KAAK,kBAAkB;AACtC,MAAI,QAAQ,QAAQ;AAClB,mBAAe,KAAK;AAAA;AAAA,KAEnB;AAAA,EACH,OAAO;AACL,mBAAe,KAAK;AAAA,qEAC6C,eAAe,WAAW,OAAO,QAAQ,MAAM;AAAA,KAC/G;AAAA,EACH;AACA,UAAQ,cAAc,QAAQ,CAAC,GAAG,OAAO;AACvC,mBAAe,KAAK;AAAA,2BACG,IAAI,0BAA0B,YAAY,QAAQ,gBAAgB,QAAQ,cAAc,MAAM,eAAe,UAAU,IAAI,OAAO,QAAQ,MAAM;AAAA,SAClK;AAAA,EACP,CAAC;AACD,MAAI,uBAAuB,IAAI;AAC7B,mBAAe,KAAK;AAAA,2BACG,IAAI,QAAQ,cAAc;AAAA,OAC9C;AAAA,EACL;AACA,QAAM,gBAAgB,uBAAuB,WAAW,OAAO,QAAQ,cAAc;AACrF,QAAM,UAAU;AAAA,IACd;AAAA,IACA,eAAe,KAAK,IAAI;AAAA,IACxB,0BAA0B,WAAW,KAAK;AAAA,IAC1C;AAAA,IACA,gCAAgC,WAAW,MAAM,MAAM;AAAA,EACzD;AACA,MAAI,CAAC,QAAQ,QAAQ;AACnB,YAAQ,KAAK,iBAAiB,WAAW,OAAO,WAAW,OAAO,QAAQ,MAAM,CAAC;AAAA,EACnF;AACA,QAAM,eAAe,UAAU,IAAI,CAAC,GAAG,OAAO,gBAAgB,GAAG,WAAW,OAAO,QAAQ,gBAAgB,QAAQ,cAAc,QAAQ,cAAc,QAAQ,QAAQ,QAAQ,eAAe,EAAE,WAAW,WAAW,MAAM,MAAM,CAAC,EAAE,KAAK,IAAI;AAC9O,UAAQ,KAAK,YAAY;AACzB,UAAQ,KAAK,QAAQ,YAAY,CAAC;AAClC,QAAM,SAAS,QAAQ,KAAK,IAAI;AAChC,SAAO;AACT;AACA,SAAS,eAAe,SAAS,QAAQ,YAAY,QAAQ;AAC3D,MAAI,MAAM,QAAQ;AAClB,MAAI,QAAQ,cAAc;AACxB,WAAO;AAAA,EACT;AACA,QAAM,QAAQ,WAAW,IAAI,CAAC,MAAM,EAAE,KAAK,EAAE,OAAO,OAAO,KAAK;AAChE,QAAM,gBAAgB,WAAW,IAAI,CAAC,MAAM,qBAAqB,iBAAiB,EAAE,OAAO,OAAO,KAAK,CAAC;AACxG,QAAM,4BAA4B,WAAW,IAAI,CAAC,MAAM,aAAa,YAAY,EAAE,OAAO,OAAO,KAAK,CAAC,EAAE,KAAK,GAAG;AACjH,QAAM,mBAAmB,cAAc,IAAI,CAAC,MAAM,EAAE,KAAK,GAAG,CAAC,EAAE,KAAK,GAAG;AACvE,QAAM,qBAAqB,eAAe,OAAO,IAAI,iBAAiB;AACtE,SAAO,OAAO,QAAQ,gBAAgB,QAAQ,cAAc,KAAK,GAAG,IAAI,MAAM,OAAO,IAAI,CAAC,UAAU,MAAM,MAAM,EAAE,KAAK,GAAG,IAAI,MAAM,KAAK,GAAG,IAAI,QAAQ,cAAc,KAAK,GAAG,IAAI,mBAAmB,4BAA4B;AACjO,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AA2DpB,SAAS,0BAA0B,OAAO;AACxC,QAAM,OAAO,MAAM;AACnB,MAAI,QAAQ,GAAG;AACb,WAAO;AAAA,EACT;AACA,QAAMG,WAAU,aAAa,eAAe,KAAK;AACjD,QAAM,QAAQ,mBAAmB,IAAI;AACrC,QAAM,UAAU,CAAC;AACjB,WAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,YAAQ,KAAK,IAAI,IAAI;AAAA,EACvB;AACA,MAAIA,SAAQ,WAAW,GAAG;AACxB,WAAO;AAAA;AAAA;AAAA;AAAA,EAIT;AACA,MAAI;AACJ,YAAU,wBAAwBA,SAAQ,IAAI,CAAC,GAAG,OAAO;AACvD,UAAM,QAAQ,OAAO,QAAQ,2CAA2C,aAAa,EAAE;AACvF,UAAM,QAAQ,OAAOA,SAAQ,SAAS,IAAI,OAAO,QAAQ,KAAK,iBAAiB,QAAQ,kCAAkC,aAAa,EAAE,MAAM,qBAAqB,QAAQ,kCAAkC,aAAa,EAAE;AAC5N,WAAO,GAAG,UAAU;AAAA,EACtB,CAAC,EAAE,KAAK,EAAE;AACV,SAAO;AAAA,4CACmC;AAAA,QACpC;AAAA,eACO,SAAS,QAAQ,KAAK,GAAG;AAAA;AAAA;AAGxC;AACA,SAAS,wBAAwB,WAAW,QAAQ;AAClD,QAAM,UAAU,UAAU;AAC1B,QAAM,OAAO,UAAU,MAAM;AAC7B,QAAM,OAAO,mBAAmB,IAAI;AACpC,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,OAAO,CAAC,MAAM,MAAM,MAAM,MAAM,MAAM,IAAI,EAAE,MAAM,GAAG,IAAI;AAC/D,QAAM,SAAS,KAAK,IAAI,CAAC,MAAM,GAAG,SAAS,EAAE,KAAK,IAAI;AACtD,MAAI,OAAO,GAAG;AACZ,QAAI,QAAQ;AACV,aAAO;AAAA,aACA;AAAA,6BACgB;AAAA;AAAA;AAAA,IAGzB;AACA,WAAO;AAAA,WACA;AAAA,qBACU;AAAA;AAAA;AAAA,EAGnB;AACA,QAAM,WAAW,YAAY,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC9E,MAAI,UAAU,GAAG;AACjB,MAAI,SAAS,GAAG;AACd,cAAU;AAAA,EACZ;AACA,MAAI,QAAQ;AACV,WAAO;AAAA,WACA,YAAY;AAAA,2BACI,6BAA6B,WAAW,QAAQ,KAAK,KAAK,GAAG;AAAA,YAC5E;AAAA;AAAA;AAAA,EAGV;AACA,SAAO;AAAA,SACA,YAAY;AAAA,mBACF,6BAA6B,WAAW,QAAQ,KAAK,KAAK,GAAG;AAAA,UACtE;AAAA;AAAA;AAGV;AACA,SAAS,wBAAwB,WAAW,UAAU,QAAQ,sBAAsB;AAClF,QAAM,UAAU,UAAU;AAC1B,QAAM,iBAAiB,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AACxE,QAAM,WAAW,QAAQ,iBAAiB;AAC1C,QAAM,SAAS,UAAU,MAAM;AAC/B,QAAM,UAAU,SAAS;AACzB,QAAM,OAAO,mBAAmB,OAAO;AACvC,MAAI,aAAa,YAAY,UAAU,OAAO,QAAQ,KAAK,sBAAsB;AAC/E,QAAI,QAAQ;AACV,aAAO;AAAA,WACF;AAAA,2BACgB;AAAA;AAAA;AAAA,WAGhB,2BAA2B;AAAA,2BACX,WAAW,UAAU,IAAI,qCAAqC;AAAA;AAAA;AAAA,IAGrF,OAAO;AACL,aAAO;AAAA,SACJ;AAAA,mBACU;AAAA;AAAA;AAAA,SAGV,2BAA2B;AAAA,mBACjB,WAAW,UAAU,IAAI,qCAAqC;AAAA;AAAA;AAAA,IAG7E;AAAA,EACF;AACA,QAAM,gBAAgB,qBAAqB,iBAAiB,UAAU,OAAO,QAAQ;AACrF,QAAM,WAAW,UAAU;AAC3B,MAAI,gBAAgB;AACpB,MAAI,WAAW,GAAG;AAChB,QAAI,QAAQ;AACV,aAAO;AAAA,SACJ;AAAA,kBACS;AAAA;AAAA;AAAA,SAGT,2BAA2B;AAAA,kBAClB;AAAA;AAAA;AAAA,IAGd;AACA,WAAO;AAAA,SACF;AAAA,kBACS;AAAA;AAAA;AAAA,SAGT,2BAA2B;AAAA,kBAClB;AAAA;AAAA;AAAA,EAGhB,OAAO;AACL,QAAI,UAAU,KAAK,cAAc,UAAU,GAAG;AAC5C,sBAAgB;AAAA,IAClB,OAAO;AACL,sBAAgB,cAAc,IAAI,CAAC,MAAM,UAAU,aAAa,IAAI,QAAQ,QAAQ,EAAE,KAAK,IAAI;AAAA,IACjG;AAAA,EACF;AACA,MAAI,wBAAwB;AAC5B,MAAI,UAAU,KAAK,SAAS,GAAG;AAC7B,4BAAwB;AAAA,EAC1B,OAAO;AACL,QAAI,UAAU,GAAG;AACf,YAAM,aAAa,mBAAmB,MAAM;AAC5C,YAAM,eAAe,UAAU,MAAM,IAAI,CAAC,IAAI,OAAO,UAAU,aAAa,KAAK,QAAQ,GAAG,EAAE,KAAK,IAAI;AACvG,8BAAwB,GAAG,cAAc;AAAA,IAC3C,OAAO;AACL,8BAAwB;AAAA,IAC1B;AAAA,EACF;AACA,QAAM,WAAW,YAAY,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC9E,QAAM,UAAU,GAAG;AACnB,MAAI,QAAQ;AACV,WAAO;AAAA,SACF;AAAA;AAAA,QAED;AAAA,eACO,6BAA6B,WAAW,0BAA0B;AAAA;AAAA;AAAA,SAGxE,6BAA6B;AAAA;AAAA,QAE9B;AAAA,eACO,6BAA6B,WAAW,0BAA0B;AAAA;AAAA;AAAA,EAG/E;AACA,SAAO;AAAA,OACF;AAAA;AAAA,MAED;AAAA,iBACW,6BAA6B,WAAW,0BAA0B;AAAA;AAAA;AAAA,OAG5E,6BAA6B;AAAA;AAAA,MAE9B;AAAA,iBACW,6BAA6B,WAAW,0BAA0B;AAAA;AAAA;AAGnF;AACA,SAAS,gBAAgB,WAAW,UAAU,QAAQ,sBAAsB;AAC1E,MAAI,MAAM,wBAAwB,WAAW,MAAM;AACnD,QAAM,UAAU,UAAU;AAC1B,MAAI,QAAQ,UAAU,SAAS,QAAQ;AACrC,WAAO,wBAAwB,WAAW,UAAU,QAAQ,oBAAoB;AAAA,EAClF;AACA,SAAO;AACT;AACA,SAAS,uBAAuB,UAAU,gBAAgB;AACxD,QAAM,EAAE,GAAG,IAAI,CAAC,GAAG,IAAI,CAAC,EAAE,IAAI;AAC9B,QAAM,UAAU,SAAS;AACzB,MAAI,EAAE,WAAW,SAAS;AACxB,UAAM,SAAS,mBAAmB,OAAO;AACzC,UAAM,WAAW,2BAA2B;AAAA;AAAA;AAAA;AAAA;AAK5C,WAAO;AAAA,EACT;AACA,MAAI,sBAAsB;AAC1B,QAAM,OAAO,CAAC,GAAG,GAAG,CAAC;AACrB,MAAI,OAAO;AACX,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,UAAM,MAAM,KAAK;AACjB,QAAI,IAAI,WAAW,GAAG;AACpB;AAAA,IACF;AACA,YAAQ,IAAI;AACZ,QAAI,IAAI,WAAW,GAAG;AACpB,6BAAuB,QAAQ,IAAI,qBAAqB;AAAA,IAC1D,OAAO;AACL,YAAMA,WAAU,4BAA4B,KAAK,mBAAmB;AACpE,6BAAuB,YAAY,qBAAqB;AACxD,eAAS,IAAI,GAAG,IAAIA,SAAQ,QAAQ,KAAK;AACvC,+BAAuB,QAAQ,IAAI,aAAa,QAAQA,SAAQ;AAChE,YAAI,MAAMA,SAAQ,SAAS,GAAG;AAC5B,iCAAuB,QAAQ,IAAI,IAAI,aAAa,SAAS,IAAI,QAAQA,SAAQ;AAAA,QACnF,OAAO;AACL,iCAAuB,QAAQ,aAAa,SAAS,IAAI,QAAQA,SAAQ;AAAA,QAC3E;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,QAAM,aAAa,CAAC;AACpB,WAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,eAAW,KAAK,IAAI,IAAI;AAAA,EAC1B;AACA,QAAM,QAAQ,mBAAmB,IAAI;AACrC,MAAI,UAAU,2BAA2B;AAAA,IACvC;AAAA;AAEF,MAAI,WAAW,WAAW,GAAG;AAC3B,eAAW,UAAU;AAAA,EACvB,OAAO;AACL,eAAW,UAAU,SAAS,WAAW,KAAK,GAAG;AAAA,EACnD;AACA,SAAO;AACT;AACA,SAAS,gCAAgC,SAAS;AAChD,MAAI,UAAU;AACd,UAAQ;AAAA,SACD;AAAA,SACA;AACH,iBAAW;AAAA;AAAA;AAAA;AAAA;AAKX;AAAA,SACG;AACH,iBAAW;AAAA;AAAA;AAAA;AAAA;AAKX;AAAA,SACG;AACH,iBAAW;AAAA;AAAA;AAAA;AAAA;AAKX;AAAA,SACG;AACH,iBAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAMX;AAAA,SACG;AACH,iBAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AASX;AAAA,SACG;AACH,iBAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUX;AAAA;AAEA,mBAAa,OAAO,OAAO,MAAM,eAAe,gBAAgB;AAChE;AAAA;AAEJ,SAAO;AACT;AACA,SAAS,eAAe,SAAS;AAC/B,SAAO,QAAQ,SAAS,OAAO,KAAK,QAAQ,SAAS,OAAO;AAC9D;AACA,SAAS,eAAe,MAAM,QAAQ;AACpC,MAAI,SAAS,WAAW;AACtB,WAAO,SAAS,cAAc;AAAA,EAChC,WAAW,SAAS,SAAS;AAC3B,WAAO,SAAS,cAAc;AAAA,EAChC,WAAW,SAAS,QAAQ;AAC1B,WAAO,SAAS,cAAc;AAAA,EAChC;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,UAAU,eAAe,QAAQ;AACzD,QAAM,UAAU,SAAS;AACzB,QAAM,WAAW,eAAe,eAAe,MAAM;AACrD,MAAI;AACJ,MAAI,QAAQ;AACV,cAAU;AAAA,4BACc;AAAA;AAAA;AAAA,4BAGA;AAAA;AAAA,EAE1B,OAAO;AACL,cAAU;AAAA,4BACc;AAAA;AAAA;AAAA,4BAGA;AAAA;AAAA,EAE1B;AACA,MAAI,WAAW,GAAG;AAChB,UAAM,OAAO,CAAC,MAAM,MAAM,MAAM,MAAM,MAAM,IAAI,EAAE,MAAM,GAAG,OAAO;AAClE,UAAM,OAAO,mBAAmB,OAAO;AACvC,QAAI,QAAQ;AACV,iBAAW;AAAA,6BACY,KAAK,IAAI,CAAC,MAAM,GAAG,SAAS,EAAE,KAAK,IAAI;AAAA,mDACjB,QAAQ,KAAK,KAAK,IAAI;AAAA;AAAA;AAAA,gCAGzC,KAAK,IAAI,CAAC,MAAM,GAAG,SAAS,EAAE,KAAK,IAAI;AAAA,mDACpB,QAAQ,KAAK,KAAK,IAAI;AAAA;AAAA;AAAA;AAAA,IAIrE,OAAO;AACL,iBAAW;AAAA,6BACY,KAAK,IAAI,CAAC,MAAM,GAAG,SAAS,EAAE,KAAK,IAAI;AAAA,mDACjB,QAAQ,KAAK,KAAK,IAAI;AAAA;AAAA;AAAA,gCAGzC,KAAK,IAAI,CAAC,MAAM,GAAG,SAAS,EAAE,KAAK,IAAI;AAAA,mDACpB,QAAQ,KAAK,KAAK,IAAI;AAAA;AAAA;AAAA;AAAA,IAIrE;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,sBAAsB,CAAC;AAC3Bf,UAAS,qBAAqB;AAAA,EAC5B,yBAAyB,MAAM;AAAA,EAC/B,oBAAoB,MAAM;AAAA,EAC1B,mBAAmB,MAAM;AAAA,EACzB,iBAAiB,MAAM;AAAA,EACvB,+BAA+B,MAAM;AAAA,EACrC,+BAA+B,MAAM;AAAA,EACrC,+BAA+B,MAAM;AAAA,EACrC,oBAAoB,MAAM;AAAA,EAC1B,mBAAmB,MAAM;AAAA,EACzB,yBAAyB,MAAM;AACjC,CAAC;AACD,IAAI,eAAe,CAAC,QAAQ;AAC1B,MAAI,UAAU;AACd,WAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,MAAM;AACtC,eAAW,IAAI;AAAA,EACjB;AACA,SAAO;AACT;AACA,SAAS,wBAAwB,UAAU,OAAO;AAChD,MAAI,SAAS,WAAW,MAAM,QAAQ;AACpC,UAAM,IAAI,MAAM,+BAA+B,SAAS,qCAAqC,MAAM,kCAAkC;AAAA,EACvI;AACA,SAAO,MAAM,MAAM,CAAC,KAAK,WAAW,MAAM,SAAS,YAAY,CAAC;AAClE;AACA,SAAS,gBAAgB,QAAQ,aAAa,gBAAgB,CAAC,GAAG,GAAG,CAAC,GAAG,oBAAoB,CAAC,GAAG,GAAG,CAAC,GAAG;AACtG,QAAM,CAAC,WAAW,WAAW,SAAS,IAAI;AAAA,IACxC,KAAK,KAAK,aAAa,OAAO,EAAE,IAAI,CAAC,MAAM,YAAY,EAAE,CAAC,KAAK,cAAc,KAAK,kBAAkB,GAAG;AAAA,IACvG,OAAO,IAAI,KAAK,KAAK,aAAa,OAAO,EAAE,IAAI,CAAC,MAAM,YAAY,EAAE,CAAC,KAAK,cAAc,KAAK,kBAAkB,GAAG,IAAI;AAAA,IACtH,OAAO,IAAI,KAAK,KAAK,aAAa,OAAO,EAAE,IAAI,CAAC,MAAM,YAAY,EAAE,CAAC,KAAK,cAAc,KAAK,kBAAkB,GAAG,IAAI;AAAA,EACxH;AACA,SAAO,CAAC,WAAW,WAAW,SAAS;AACzC;AACA,SAAS,8BAA8B,QAAQ,aAAa,SAAS,OAAO;AAC1E,MAAI,QAAQ;AACV,WAAO,CAAC,GAAG,GAAG,CAAC;AAAA,EACjB;AACA,QAAM,OAAO,aAAa,OAAO,EAAE,IAAI,CAAC,MAAM,YAAY,EAAE,CAAC;AAC7D,QAAM,OAAO,aAAa,OAAO,EAAE,IAAI,CAAC,MAAM,YAAY,EAAE,CAAC;AAC7D,MAAI,QAAQ,GAAG;AACb,WAAO,CAAC,GAAG,IAAI,CAAC;AAAA,EAClB;AACA,MAAI,QAAQ,GAAG;AACb,WAAO,CAAC,IAAI,GAAG,CAAC;AAAA,EAClB;AACA,SAAO,CAAC,IAAI,IAAI,CAAC;AACnB;AACA,SAAS,8BAA8B,WAAW,UAAU,WAAW;AACrE,MAAI,cAAc,GAAG;AACnB,WAAO,CAAC,IAAI,GAAG,CAAC;AAAA,EAClB,WAAW,cAAc,GAAG;AAC1B,WAAO,CAAC,GAAG,IAAI,CAAC;AAAA,EAClB;AACA,SAAO,CAAC,GAAG,GAAG,CAAC;AACjB;AACA,SAAS,8BAA8B,QAAQ,aAAa,SAAS,OAAO;AAC1E,MAAI,QAAQ;AACV,WAAO,CAAC,GAAG,GAAG,CAAC;AAAA,EACjB;AACA,QAAM,OAAO,aAAa,OAAO,EAAE,IAAI,CAAC,MAAM,YAAY,EAAE,CAAC;AAC7D,QAAM,OAAO,aAAa,OAAO,EAAE,IAAI,CAAC,MAAM,YAAY,EAAE,CAAC;AAC7D,MAAI,QAAQ,GAAG;AACb,WAAO,CAAC,GAAG,GAAG,CAAC;AAAA,EACjB;AACA,MAAI,QAAQ,GAAG;AACb,WAAO,CAAC,GAAG,GAAG,CAAC;AAAA,EACjB;AACA,SAAO,CAAC,GAAG,GAAG,CAAC;AACjB;AACA,SAAS,mBAAmB,OAAO;AACjC,SAAO,EAAE,GAAG,MAAM,IAAI,CAAC,GAAG,OAAO,EAAE,EAAE;AACvC;AACA,SAAS,mBAAmB,OAAO;AACjC,MAAI,UAAU,aAAa,UAAU,WAAW,UAAU,UAAU,UAAU,UAAU;AACtF,WAAO;AAAA,EACT,WAAW,UAAU,aAAa;AAChC,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,iBAAiB,OAAO;AAAA,EAC1C;AACF;AACA,SAAS,wBAAwB,MAAM,OAAO;AAC5C,MAAI,UAAU,WAAW;AACvB,WAAO,IAAI,aAAa,IAAI;AAAA,EAC9B,WAAW,UAAU,SAAS;AAC5B,WAAO,IAAI,WAAW,IAAI;AAAA,EAC5B,WAAW,UAAU,UAAU,UAAU,UAAU;AACjD,WAAO,WAAW,KAAK,IAAI,WAAW,IAAI,CAAC;AAAA,EAC7C,OAAO;AACL,UAAM,IAAI,MAAM,iBAAiB,OAAO;AAAA,EAC1C;AACF;AACA,SAAS,oBAAoB;AAC3B,UAAQ,OAAO,WAAW,eAAe,OAAO,sBAAsB,gBAAgB,CAAC,CAAC,UAAU;AACpG;AACA,IAAI;AAAA,CACH,SAAS,oBAAoB;AAC5B,qBAAmB,mBAAmB,6BAA6B,KAAK;AACxE,qBAAmB,mBAAmB,yBAAyB,KAAK;AACpE,qBAAmB,mBAAmB,yBAAyB,KAAK;AACpE,qBAAmB,mBAAmB,kCAAkC,KAAK;AAC7E,qBAAmB,mBAAmB,yBAAyB,KAAK;AACpE,qBAAmB,mBAAmB,eAAe,KAAK;AAC5D,GAAG,sBAAsB,oBAAoB,CAAC,EAAE;AAGhD,SAAS,mBAAmB,gBAAgB,gBAAgB,YAAY,YAAY,YAAY,OAAO,YAAY,OAAO,WAAW,OAAO,YAAY,GAAG;AACzJ,eAAa,OAAO,cAAc,cAAc,KAAK,CAAC,YAAY,MAAM,cAAc,oDAAoD,WAAW;AACrJ,QAAM,UAAU;AAAA,oBACE,iBAAiB,MAAM;AAAA;AAAA,QAEnC,aAAa,qEAAqE,gBAAgB,qEAAqE;AAAA;AAAA;AAG7K,MAAI;AACJ,MAAI,eAAe,OAAO;AACxB,cAAU,qEAAqE;AAAA,EACjF,OAAO;AACL,cAAU,qEAAqE;AAAA,EACjF;AACA,SAAO;AAAA,uDAC8C,YAAY,SAAS;AAAA,kBAC1D,YAAY,SAAS;AAAA,wBACf;AAAA,MAClB,aAAa,WAAW,UAAU;AAAA,MAClC,aAAa,4DAA4D;AAAA;AAAA,QAEvE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,uDAM+C,YAAY,SAAS;AAAA,wBACpD;AAAA,kBACN,iBAAiB,MAAM;AAAA;AAAA,kBAEvB,YAAY,SAAS;AAAA,MACjC;AAAA;AAAA;AAAA;AAIN;AACA,SAAS,wBAAwB,SAAS,aAAa,gBAAgB,gBAAgB,YAAY,YAAY,YAAY,OAAO,YAAY,OAAO,WAAW,OAAO,YAAY,GAAG;AACpL,SAAO;AAAA,IACL,mBAAmB,gBAAgB,gBAAgB,YAAY,YAAY,WAAW,WAAW,UAAU,SAAS;AAAA,2DAC7D,YAAY,SAAS;AAAA,wBACxD;AAAA,MAClB,aAAa,YAAY,KAAK;AAAA;AAAA;AAAA;AAAA,QAI5B,sBAAsB,SAAS,WAAW;AAAA;AAAA;AAAA;AAAA;AAKlD;AACA,IAAI,yBAAyB,CAAC,eAAe;AAC3C,MAAI,YAAY;AACd,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA,EAKT,OAAO;AACL,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA,EAKT;AACF;AACA,IAAI,0BAA0B,CAAC,eAAe;AAC5C,SAAO,aAAa,kDAAkD;AACxE;AACA,SAAS,uBAAuB,eAAe,eAAe,aAAa,OAAO,YAAY,IAAI;AAChG,QAAM,aAAa,cAAc,KAAK,cAAc;AACpD,QAAM,aAAa,cAAc,KAAK,cAAc;AACpD,QAAM,aAAa,aAAa,aAAa;AAC7C,QAAM,aAAa,aAAa,YAAY;AAC5C,eAAa,OAAO,aAAa,cAAc,OAAO,KAAK,aAAa,cAAc,OAAO,KAAK,YAAY,cAAc,OAAO,GAAG,MAAM,cAAc,mDAAmD,cAAc,kBAAkB,mDAAmD,cAAc,iBAAiB,kDAAkD,cAAc,IAAI;AACnY,QAAM,gBAAgB,aAAa,cAAc;AACjD,QAAM,gBAAgB,aAAa,cAAc;AACjD,QAAM,gBAAgB,YAAY,cAAc;AAChD,SAAO;AAAA,gDACuC,gBAAgB;AAAA,gDAChB,gBAAgB;AAAA,2BACrC,cAAc;AAAA,2BACd,cAAc;AAAA,wBACjB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kDAiB0B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,wCAaV;AAAA,wCACA;AAAA,wCACA;AAAA;AAAA;AAAA;AAAA,4CAII;AAAA,8CACE;AAAA;AAAA;AAAA,cAGhC,uBAAuB,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA,4CAKH;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAoB9B,wBAAwB,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAkBhD;AACA,IAAI,qBAAqB,CAAC,eAAe;AACvC,SAAO,aAAa;AAAA;AAAA;AAAA;AAAA;AAAA,MAKhB;AAAA;AAAA;AAAA;AAAA;AAAA;AAMN;AACA,SAAS,8BAA8B,eAAe,aAAa,OAAO;AACxE,eAAa,OAAO,cAAc,OAAO,KAAK,cAAc,OAAO,GAAG,MAAM,iDAAiD,gBAAgB;AAC7I,SAAO;AAAA,uBACc,cAAc,KAAK;AAAA,gDACM,cAAc;AAAA;AAAA,MAExD,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,uCAca,mBAAmB,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAqBpE;AACA,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,QAAQ,aAAa,eAAe,gBAAgB,gBAAgB,aAAa,OAAO,aAAa,OAAO,OAAO,MAAM,cAAc,MAAM,yBAAyB,MAAM;AACtL,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,IAAI,CAAC;AAC/B,SAAK,cAAc;AACnB,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE;AAC/C,UAAM,WAAW,aAAa,OAAO,KAAK,OAAO;AACjD,SAAK,gBAAgB,8BAA8B,YAAY,IAAI,UAAU,YAAY,EAAE;AAC3F,QAAI,YAAY,OAAO,KAAK,YAAY,OAAO,GAAG;AAChD,sBAAgB;AAAA,IAClB;AACA,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,eAAe,eAAe,CAAC,CAAC;AAC5H,QAAI,aAAa,YAAY,KAAK,UAAU,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG;AACtD,sBAAgB;AAChB,WAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,eAAe,eAAe,CAAC,CAAC;AAAA,IAC9H;AACA,UAAM,UAAU,QAAQ;AACxB,UAAM,4BAA4B,0BAA0B;AAC5D,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,2BAA2B;AAC7B,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,gBAAgB;AACrB,SAAK,aAAa;AAClB,SAAK,aAAa;AAClB,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,4BAA4B;AACjC,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AACtB,KAAC,KAAK,WAAW,KAAK,WAAW,KAAK,QAAQ,IAAI,KAAK,YAAY,YAAY,IAAI,YAAY,IAAI,QAAQ;AAC3G,SAAK,YAAY,gBAAgB,KAAK,iBAAiB,cAAc,cAAc,KAAK,cAAc,KAAK,aAAa,KAAK,aAAa,KAAK,YAAY,KAAK,YAAY,KAAK,KAAK,KAAK,kBAAkB,KAAK;AAAA,EACpN;AAAA,EACA,YAAY,WAAW,WAAW,UAAU;AAC1C,UAAM,aAAa,KAAK,cAAc,KAAK,KAAK;AAChD,UAAM,aAAa,KAAK,cAAc,KAAK,KAAK;AAChD,SAAK,YAAY;AACjB,QAAI,KAAK,YAAY,OAAO,GAAG;AAC7B,WAAK,YAAY,KAAK,cAAc,KAAK;AAAA,IAC3C;AACA,UAAM,YAAY,YAAY,eAAe;AAC7C,UAAM,YAAY,YAAY,eAAe;AAC7C,UAAM,WAAW,WAAW,KAAK,cAAc;AAC/C,WAAO,CAAC,WAAW,WAAW,QAAQ;AAAA,EACxC;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,oBAAoB,KAAK,YAAY,KAAK,yBAAyB;AAAA,QACnE,wBAAwB,KAAK,SAAS,KAAK,YAAY,KAAK,gBAAgB,KAAK,gBAAgB,OAAO,KAAK,YAAY,KAAK,WAAW,KAAK,WAAW,KAAK,QAAQ;AAAA,QACtK,KAAK,YAAY,KAAK,IAAI,uBAAuB,CAAC,KAAK,eAAe,KAAK,eAAe,CAAC,GAAG,KAAK,eAAe,KAAK,YAAY,KAAK,SAAS,IAAI,8BAA8B,KAAK,eAAe,KAAK,UAAU;AAAA;AAE1N,WAAO;AAAA,EACT;AACF;AAGA,IAAI,0BAA0B,CAAC,YAAY,sBAAsB;AAC/D,MAAI,YAAY;AACd,WAAO;AAAA;AAAA;AAAA,6BAGkB;AAAA;AAAA,EAE3B,OAAO;AACL,WAAO;AAAA;AAAA;AAAA,4BAGiB;AAAA;AAAA,EAE1B;AACF;AACA,IAAI,yBAAyB,CAAC,YAAY,qBAAqB;AAC7D,MAAI,YAAY;AACd,WAAO;AAAA;AAAA;AAAA;AAAA,UAID,qBAAqB,IAAI,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA,YAK5B,qBAAqB,IAAI,KAAK;AAAA;AAAA,EAExC,OAAO;AACL,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAMC,qBAAqB,IAAI,KAAK;AAAA;AAAA,EAExC;AACF;AACA,SAAS,2BAA2B,eAAe,YAAY,YAAY,WAAW,mBAAmB,GAAG,aAAa,OAAO;AAC9H,QAAM,aAAa,aAAa,aAAa;AAC7C,QAAM,aAAa,aAAa,YAAY;AAC5C,QAAM,oBAAoB,aAAa,cAAc,KAAK;AAC1D,eAAa,QAAQ,cAAc,eAAe,eAAe,YAAY,MAAM,KAAK,YAAY,MAAM,OAAO,cAAc,OAAO,MAAM,qBAAqB,KAAK,qBAAqB,IAAI,MAAM,aAAa,oDAAoD,cAAc;AAAA,8BACxP,+BAA+B;AAC3D,SAAO;AAAA,4CACmC,2BAA2B,aAAa,uBAAuB;AAAA,oDACvD,aAAa,cAAc,QAAQ;AAAA;AAAA,yBAE9D,cAAc;AAAA,yBACd,cAAc;AAAA,6BACV;AAAA,sBACP;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oBAYF,eAAe,IAAI,MAAM;AAAA;AAAA;AAAA,sBAGvB,eAAe,IAAI,MAAM;AAAA;AAAA;AAAA,gDAGC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAelC,wBAAwB,YAAY,iBAAiB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAiBrD,qBAAqB,IAAI,KAAK;AAAA;AAAA,cAE9B,uBAAuB,YAAY,gBAAgB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUjE;AACA,IAAI,0BAA0B,MAAM;AAAA,EAClC,YAAY,QAAQ,aAAa,gBAAgB,gBAAgB,aAAa,OAAO,OAAO,MAAM,cAAc,MAAM,yBAAyB,MAAM;AACnJ,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,GAAG,GAAG,CAAC;AAC7B,SAAK,SAAS;AACd,SAAK,cAAc;AACnB,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE;AAC/C,QAAI,YAAY,OAAO,KAAK,CAAC,YAAY;AACvC,WAAK,oBAAoB,CAAC,GAAG,GAAG,CAAC;AAAA,IACnC,OAAO;AACL,WAAK,oBAAoB,CAAC,GAAG,GAAG,CAAC;AAAA,IACnC;AACA,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,KAAK,iBAAiB;AACjH,UAAM,UAAU,QAAQ;AACxB,UAAM,4BAA4B,0BAA0B;AAC5D,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,2BAA2B;AAC7B,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,aAAa,YAAY,OAAO,KAAK,CAAC,aAAa,IAAI,KAAK,cAAc,KAAK,KAAK,kBAAkB;AAC3G,SAAK,aAAa,KAAK,cAAc,KAAK,KAAK,kBAAkB;AACjE,SAAK,YAAY,KAAK;AACtB,SAAK,SAAS;AACd,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,4BAA4B;AACjC,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AACtB,SAAK,aAAa;AAClB,UAAM,WAAW,aAAa,OAAO,KAAK,OAAO;AACjD,SAAK,YAAY,YAAY,KAAK,KAAK,eAAe;AACtD,SAAK,YAAY,YAAY,KAAK,KAAK,eAAe;AACtD,SAAK,WAAW,WAAW,KAAK,cAAc;AAC9C,SAAK,YAAY,oBAAoB,KAAK,cAAc,KAAK,aAAa,KAAK,aAAa,KAAK,YAAY,KAAK,qBAAqB,KAAK,kBAAkB,KAAK,kBAAkB,KAAK;AAAA,EAC5L;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,oBAAoB,KAAK,YAAY,KAAK,2BAA2B,IAAI;AAAA,QACzE,wBAAwB,KAAK,SAAS,KAAK,YAAY,KAAK,gBAAgB,KAAK,gBAAgB,OAAO,OAAO,KAAK,WAAW,KAAK,WAAW,KAAK,UAAU,CAAC;AAAA,QAC/J,2BAA2B,KAAK,mBAAmB,KAAK,YAAY,KAAK,YAAY,KAAK,WAAW,GAAG,KAAK,UAAU;AAAA;AAE3H,WAAO;AAAA,EACT;AACF;AAGA,SAAS,yBAAyB;AAChC,SAAO;AAAA;AAAA,MAEH,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AA8B1B;AACA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,aAAa,gBAAgB,gBAAgB,aAAa,OAAO,aAAa,OAAO,OAAO,MAAM,cAAc,MAAM,yBAAyB,MAAM;AAC/J,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,cAAc;AACnB,SAAK,iBAAiB,EAAE,GAAG,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE;AACjD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,UAAM,UAAU,QAAQ;AACxB,UAAM,4BAA4B,0BAA0B;AAC5D,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,2BAA2B;AAC7B,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,aAAa;AAClB,SAAK,aAAa;AAClB,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,4BAA4B;AACjC,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AACtB,SAAK,YAAY,gBAAgB,KAAK,cAAc,cAAc,cAAc,KAAK,kBAAkB,KAAK;AAAA,EAC9G;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,oBAAoB,KAAK,YAAY,KAAK,yBAAyB;AAAA,QACnE,wBAAwB,KAAK,SAAS,KAAK,YAAY,KAAK,gBAAgB,KAAK,gBAAgB,KAAK,YAAY,KAAK,UAAU;AAAA,QACjI,uBAAuB;AAAA;AAE3B,WAAO;AAAA,EACT;AACF;AAGA,SAAS,gCAAgC,eAAe;AACtD,QAAM,aAAa,cAAc;AACjC,QAAM,aAAa,cAAc;AACjC,QAAM,YAAY,aAAa,aAAa,aAAa;AACzD,SAAO;AAAA,8CACqC,eAAe;AAAA,8CACf,gBAAgB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAQ1D,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,+CAQuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAQf;AAAA,gCACA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAYE;AAAA,kCACA;AAAA;AAAA,4BAEN;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAS5B;AACA,IAAI,+BAA+B,MAAM;AAAA,EACvC,YAAY,QAAQ,QAAQ,aAAa,aAAa,OAAO,aAAa,OAAO,OAAO,MAAM,cAAc,MAAM,yBAAyB,MAAM;AAC/I,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,cAAc;AACnB,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE;AAC/C,SAAK,WAAW;AAAA,MACd,KAAK,KAAK,YAAY,KAAK,KAAK,cAAc,EAAE;AAAA,MAChD,KAAK,KAAK,YAAY,KAAK,KAAK,cAAc,EAAE;AAAA,MAChD,YAAY;AAAA,IACd;AACA,UAAM,UAAU,QAAQ;AACxB,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,UAAM,4BAA4B,0BAA0B;AAC5D,QAAI,2BAA2B;AAC7B,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,aAAa;AAClB,SAAK,aAAa;AAClB,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,4BAA4B;AACjC,SAAK,iBAAiB,OAAO,OAAO;AACpC,SAAK,iBAAiB,OAAO,OAAO;AACpC,SAAK,YAAY,yBAAyB,KAAK,cAAc,cAAc,cAAc,KAAK,kBAAkB,KAAK;AAAA,EACvH;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,oBAAoB,KAAK,YAAY,KAAK,yBAAyB;AAAA,QACnE,wBAAwB,KAAK,SAAS,KAAK,YAAY,KAAK,gBAAgB,KAAK,gBAAgB,KAAK,YAAY,KAAK,UAAU;AAAA,QACjI,gCAAgC,KAAK,aAAa;AAAA;AAEtD,WAAO;AAAA,EACT;AACF;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,aAAa,UAAU,gBAAgB,gBAAgB,aAAa,OAAO,aAAa,OAAO;AACzG,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,GAAG,GAAG,CAAC;AAC7B,SAAK,SAAS;AACd,SAAK,YAAY;AACjB,iBAAa,OAAO,YAAY,OAAO,GAAG,MAAM,8CAA8C;AAC9F,SAAK,cAAc;AACnB,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,EAAE;AAClD,SAAK,oBAAoB,CAAC,GAAG,GAAG,KAAK,SAAS;AAC9C,QAAI,KAAK,YAAY,KAAK,IAAI;AAC5B,WAAK,kBAAkB,KAAK;AAAA,IAC9B;AACA,QAAI,KAAK,YAAY,KAAK,IAAI;AAC5B,WAAK,kBAAkB,KAAK;AAAA,IAC9B;AACA,SAAK,WAAW,gBAAgB,KAAK,gBAAgB;AAAA,MACnD,KAAK,YAAY;AAAA,MACjB,KAAK,YAAY;AAAA,MACjB,KAAK,YAAY;AAAA,MACjB;AAAA,IACF,GAAG,KAAK,eAAe,KAAK,iBAAiB;AAC7C,SAAK,aAAa;AAClB,SAAK,aAAa;AAClB,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AACtB,SAAK,YAAY,gBAAgB,cAAc,cAAc,kBAAkB,kBAAkB,KAAK;AAAA,EACxG;AAAA,EACA,cAAc;AACZ,UAAM,mBAAmB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWzB,UAAM,WAAW;AAAA,QACb,mBAAmB,KAAK,gBAAgB,KAAK,gBAAgB,KAAK,YAAY,KAAK,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAQzF;AAAA;AAAA;AAAA;AAAA,QAIJ,KAAK,uBAAuB;AAAA;AAEhC,WAAO;AAAA,EACT;AAAA,EACA,yBAAyB;AACvB,UAAM,aAAa,KAAK,cAAc,KAAK,KAAK,kBAAkB;AAClE,UAAM,aAAa,KAAK,cAAc,KAAK,KAAK,kBAAkB;AAClE,UAAM,eAAe,KAAK,kBAAkB;AAC5C,UAAM,eAAe,KAAK,kBAAkB;AAC5C,UAAM,gBAAgB,KAAK,YAAY,KAAK,cAAc;AAC1D,UAAM,gBAAgB,KAAK,YAAY,KAAK,cAAc;AAC1D,iBAAa,OAAO,KAAK,YAAY,KAAK,cAAc,OAAO,KAAK,KAAK,YAAY,KAAK,cAAc,OAAO,GAAG,MAAM,aAAa,KAAK,kDAAkD,KAAK,cAAc,0BAA0B,KAAK,cAAc,IAAI;AAChQ,WAAO;AAAA,kDACuC,KAAK,eAAe;AAAA,kDACpB,gBAAgB,KAAK;AAAA,QAC/D,oBAAoB;AAAA,yCACa;AAAA,yCACA;AAAA;AAAA,4CAEG;AAAA,4CACA;AAAA;AAAA,yCAEH,KAAK;AAAA;AAAA;AAAA,0CAGJ;AAAA,4CACE;AAAA,8CACE;AAAA;AAAA;AAAA,qDAGO,KAAK,iBAAiB,IAAI;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0CAMrC;AAAA,4CACE;AAAA,8CACE;AAAA;AAAA;AAAA,qDAGO,KAAK,iBAAiB,IAAI;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,qCAQ1C,kBAAkB;AAAA;AAAA,8BAEzB,KAAK;AAAA,qCACE;AAAA,wCACG;AAAA;AAAA;AAAA;AAAA,8CAIM;AAAA;AAAA,gDAEE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,4CAMJ;AAAA,8CACE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAM5C;AACF;AACA,IAAI,wBAAwB,MAAM;AAAA,EAChC,YAAY,aAAa,OAAO,MAAM,cAAc,MAAM,yBAAyB,MAAM;AACvF,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,UAAU,QAAQ;AACvB,SAAK,4BAA4B,0BAA0B;AAC3D,SAAK,aAAa;AAClB,QAAI,KAAK,SAAS;AAChB,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,KAAK,2BAA2B;AAClC,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,YAAY,kBAAkB;AAAA,EACrC;AAAA,EACA,cAAc;AACZ,WAAO;AAAA,MACL,oBAAoB,KAAK,YAAY,KAAK,yBAAyB;AAAA,MACnE,kCAAkC;AAAA;AAAA;AAAA;AAAA,UAI9B,sBAAsB,KAAK,SAAS,KAAK,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA,EAK3D;AACF;AAGA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,OAAO;AACjB,SAAK,gBAAgB,CAAC;AACtB,SAAK,cAAc,CAAC;AACpB,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,MACf,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAMpC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,IAAI;AACzB,MAAI,EAAE,MAAM,IAAI;AAChB,UAAQ,SAAS,aAAa,WAAW,KAAK;AAC9C,MAAI,UAAU,UAAU;AACtB,UAAM,SAAS,aAAa,kBAAkB,OAAO,aAAa,cAAc,KAAK,CAAC;AACtF,WAAO,KAAK,KAAK;AACjB,WAAO,SAAS,eAAe,OAAO,OAAO,MAAM;AAAA,EACrD,OAAO;AACL,UAAM,UAAU,IAAI,aAAa,KAAK;AACtC,UAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,KAAK,EAAE,CAAC;AACvD,WAAO,SAAS,iBAAiB,SAAS,CAAC,GAAG,OAAO,WAAW;AAAA,EAClE;AACF;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,MAAM,IAAI;AAC1B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,SAAS,aAAa,uBAAuB,OAAO,KAAK;AAC/D,QAAM,SAAS,aAAa,cAAc,MAAM;AAChD,eAAa,OAAO,UAAU,QAAQ,MAAM,kBAAkB,eAAe,sCAAsC,EAAE,cAAc,oFAAoF;AACvN,OAAK,QAAQ,OAAO,EAAE,MAAM;AAC5B,SAAO,EAAE,QAAQ,EAAE,QAAQ,OAAO,QAAQ,OAAO,EAAE,MAAM;AAC3D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,iBAAiB,EAAE,GAAG,GAAG,YAAY,YAAY,SAAS,UAAU,OAAO,MAAM,yBAAyB,MAAM,iBAAiB,GAAG,YAAY,cAAc,KAAK,GAAG;AAC7K,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,oBAAoB,uBAAuB,2BAA2B,EAAE,MAAM,MAAM,GAAG,EAAE,GAAG,EAAE,MAAM,MAAM,GAAG,EAAE,CAAC;AACtH,QAAM,WAAW,kBAAkB,OAAO,CAAC,aAAa,WAAW,CAAC;AACpE,eAAa,OAAO,gBAAgB,aAAa,MAAM,kCAAkC,qBAAqB,uCAAuC,EAAE,aAAa,EAAE,wBAAwB,6BAA6B,wBAAwB;AACnP,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,gBAAgB,CAAC,KAAK,GAAG;AAC/B,QAAM,WAAW,KAAK,IAAI,WAAW,SAAS;AAC9C,QAAM,iBAAiB,cAAc;AACrC,QAAM,iBAAiB,cAAc;AACrC,QAAM,WAAW,cAAc,MAAM,KAAK,CAAC,cAAc,cAAc,MAAM,KAAK,eAAe,cAAc,MAAM,KAAK,CAAC;AAC3H,QAAM,SAAS,CAAC,KAAK,GAAG;AACxB,QAAM,aAAa;AAAA,IACjB,EAAE,MAAM,SAAS,MAAM,CAAC,WAAW,EAAE;AAAA,IACrC,EAAE,MAAM,SAAS,MAAM,CAAC,WAAW,EAAE;AAAA,IACrC,EAAE,MAAM,SAAS,MAAM,CAAC,WAAW,EAAE;AAAA,EACvC;AACA,MAAI;AACJ,MAAI;AACJ,QAAM,cAAc,CAAC,UAAU,aAAa,WAAW;AACvD,MAAI,oBAAoB,IAAI,EAAE,IAAI,4BAA4B;AAC9D,MAAI,oBAAoB,GAAG;AACzB,QAAI,cAAc,eAAe,KAAK;AACpC,0BAAoB,kBAAkB;AAAA,IACxC,WAAW,aAAa,KAAK,eAAe,OAAO,eAAe,MAAM,eAAe,KAAK;AAC1F,0BAAoB,kBAAkB;AAAA,IACxC,WAAW,eAAe,OAAO,eAAe,OAAO,eAAe,IAAI,gBAAgB,eAAe,OAAO,eAAe,OAAO,eAAe,IAAI,cAAc;AACrK,0BAAoB,kBAAkB;AAAA,IACxC,WAAW,SAAS;AAClB,0BAAoB,kBAAkB;AAAA,IACxC,OAAO;AACL,0BAAoB,kBAAkB;AAAA,IACxC;AAAA,EACF;AACA,UAAQ;AAAA,SACD,kBAAkB;AACrB,gBAAU,IAAI,wBAAwB,UAAU,aAAa,gBAAgB,gBAAgB,YAAY,MAAM,aAAa,sBAAsB;AAClJ;AAAA,SACG,kBAAkB;AACrB,gBAAU,IAAI,oBAAoB,aAAa,gBAAgB,gBAAgB,YAAY,YAAY,MAAM,aAAa,sBAAsB;AAChJ;AAAA,SACG,kBAAkB,qBAAqB;AAC1C,YAAM,MAAM,EAAE,SAAS,UAAU,OAAO,EAAE,OAAO,aAAa,OAAO,GAAG,OAAO,EAAE,MAAM,EAAE,CAAC;AAC1F,gBAAU,IAAI,oBAAoB,aAAa,aAAa,gBAAgB,gBAAgB,YAAY,UAAU;AAClH,UAAI,QAAQ,aAAa;AACvB,cAAM,SAAS,iBAAiB,SAAS,QAAQ,EAAE,OAAO,YAAY,GAAG;AACzE,cAAM,wBAAwB,IAAI,sBAAsB,IAAI,OAAO,MAAM,aAAa,sBAAsB;AAC5G,YAAI,cAAc;AAClB,cAAM,mBAAmB,CAAC,GAAG;AAC7B,YAAI,MAAM;AACR,2BAAiB,KAAK,IAAI;AAAA,QAC5B;AACA,YAAI,wBAAwB;AAC1B,2BAAiB,KAAK,sBAAsB;AAAA,QAC9C;AACA,YAAI,gBAAgB,aAAa;AAC/B,wBAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,cAAc,EAAE,CAAC;AAC1D,gCAAsB,YAAY;AAAA,QACpC;AACA,cAAM,eAAe,SAAS,iBAAiB,uBAAuB,kBAAkB,IAAI,OAAO,WAAW;AAC9G,sBAAc,KAAK,GAAG;AACtB,cAAM,eAAe,SAAS,EAAE,QAAQ,EAAE,GAAG,aAAa,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC5G,sBAAc,KAAK,YAAY;AAC/B,mBAAW,MAAM,eAAe;AAC9B,mBAAS,YAAY,GAAG,MAAM;AAAA,QAChC;AACA,eAAO;AAAA,MACT;AACA;AAAA,IACF;AAAA,SACK,kBAAkB;AACrB,gBAAU,IAAI,6BAA6B,UAAU,UAAU,aAAa,YAAY,YAAY,MAAM,aAAa,sBAAsB;AAC7I;AAAA,SACG,kBAAkB;AACrB,gBAAU,IAAI,qBAAqB,UAAU,aAAa,IAAI,EAAE,IAAI,+BAA+B,GAAG,gBAAgB,gBAAgB,YAAY,YAAY,MAAM,aAAa,sBAAsB;AACvM;AAAA;AAEA,YAAM,IAAI,MAAM,iCAAiC,oBAAoB;AAAA;AAEzE,MAAI,MAAM;AACR,WAAO,KAAK,IAAI;AAAA,EAClB;AACA,MAAI,wBAAwB;AAC1B,WAAO,KAAK,sBAAsB;AAAA,EACpC;AACA,MAAI,gBAAgB,aAAa;AAC/B,eAAW,KAAK,EAAE,MAAM,WAAW,MAAM,CAAC,cAAc,EAAE,CAAC;AAC3D,YAAQ,YAAY;AAAA,EACtB;AACA,QAAM,SAAS,iBAAiB,SAAS,QAAQ,EAAE,OAAO,YAAY,GAAG;AACzE,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAClG,gBAAc,KAAK,GAAG;AACtB,aAAW,MAAM,eAAe;AAC9B,aAAS,YAAY,GAAG,MAAM;AAAA,EAChC;AACA,SAAO;AACT;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,MAAM,uBAAuB,IAAI;AAC/C,QAAM,EAAE,YAAY,YAAY,YAAY,aAAa,eAAe,IAAI;AAC5E,SAAO,iBAAiB;AAAA,IACtB;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA,SAAS;AAAA,IACT;AAAA,IACA;AAAA,IACA;AAAA,IACA,YAAY;AAAA,EACd,CAAC;AACH;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,0BAA0B,MAAM;AAAA,EAClC,YAAY,KAAK,QAAQ,QAAQ;AAC/B,SAAK,gBAAgB,CAAC,SAAS,SAAS,SAAS,OAAO;AACxD,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,OAAO;AACZ,SAAK,cAAc,qBAAqB,2BAA2B,QAAQ,MAAM;AACjF,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY,mBAAmB;AACpC,SAAK,KAAK;AAAA,EACZ;AAAA,EACA,cAAc;AACZ,UAAM,QAAQ,kBAAkB,KAAK,IAAI,KAAK;AAC9C,UAAM,WAAW;AAAA;AAAA;AAAA,UAGX;AAAA;AAAA;AAAA,QAGF,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUtC,WAAO;AAAA,EACT;AACF;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,KAAK,QAAQ,QAAQ;AAC/B,SAAK,OAAO;AACZ,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,cAAc,qBAAqB,2BAA2B,QAAQ,MAAM;AACjF,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,KAAK;AACV,SAAK,uBAAuB,OAAO,WAAW,KAAK,OAAO,SAAS,KAAK,OAAO,KAAK;AACpF,SAAK,uBAAuB,OAAO,WAAW,KAAK,OAAO,SAAS,KAAK,OAAO,KAAK;AACpF,QAAI,KAAK,wBAAwB,KAAK,sBAAsB;AAC1D,WAAK,SAAS;AACd,WAAK,oBAAoB,KAAK,uBAAuB,OAAO,KAAK,OAAO;AACxE,WAAK,YAAY,UAAU,KAAK,QAAQ,OAAO,KAAK,qBAAqB,KAAK;AAC9E,WAAK,OAAO;AACZ,WAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,UAAI,KAAK,oBAAoB,KAAK;AAChC,aAAK,gBAAgB;AAAA,MACvB,WAAW,KAAK,oBAAoB,KAAK;AACvC,aAAK,gBAAgB;AAAA,MACvB,OAAO;AACL,aAAK,gBAAgB;AAAA,MACvB;AAAA,IACF,OAAO;AACL,UAAI,aAAa,YAAY,QAAQ,MAAM,KAAK,aAAa,cAAc,MAAM,IAAI,MAAM,GAAG;AAC5F,aAAK,SAAS;AACd,aAAK,OAAO;AACZ,aAAK,gBAAgB;AAAA,MACvB,OAAO;AACL,aAAK,SAAS;AACd,aAAK,OAAO;AACZ,aAAK,gBAAgB;AAAA,MACvB;AACA,WAAK,YAAY,UAAU,KAAK,QAAQ;AACxC,WAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAAA,IACjC;AACA,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,KAAK,eAAe,GAAG,CAAC,CAAC;AAAA,EACvH;AAAA,EACA,cAAc;AACZ,QAAI;AACJ,QAAI,KAAK,SAAS,UAAU;AAC1B,YAAM,qBAAqB,KAAK,oBAAoB,IAAI,UAAU,KAAK,YAAY,SAAS,OAAO;AACnG,YAAM,oBAAoB,KAAK,uBAAuB;AAAA,8BAC9B,yBAAyB,qBAAqB;AAAA;AAEtE,YAAM,QAAQ,kBAAkB,KAAK,IAAI,KAAK,MAAM;AACpD,iBAAW;AAAA;AAAA,YAEL;AAAA;AAAA,gDAEoC,KAAK;AAAA,UAC3C,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA,8DAKkB,KAAK,gDAAgD,KAAK,cAAc;AAAA,0CAC5F,KAAK,uBAAuB,MAAM;AAAA;AAAA;AAAA;AAAA,+BAI7C,KAAK;AAAA,sCACE,KAAK;AAAA;AAAA;AAAA;AAAA,gBAI3B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAMZ,OAAO;AACL,YAAM,QAAQ,KAAK,SAAS,SAAS,cAAc;AACnD,YAAM,QAAQ,kBAAkB,KAAK,IAAI,KAAK,MAAM;AACpD,iBAAW;AAAA,gCACe,cAAc,aAAa;AAAA,WAChD;AAAA;AAAA,SAEF,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAQvC;AACA,WAAO;AAAA,EACT;AACF;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,EAAE,IAAI;AACd,OAAK,QAAQ,OAAO,EAAE,MAAM;AAC5B,SAAO,EAAE,QAAQ,EAAE,QAAQ,OAAO,EAAE,OAAO,OAAO,EAAE,MAAM;AAC5D;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,MAAM,OAAO,MAAM,MAAM,IAAI;AACrC,QAAM,cAAc,SAAS,eAAe,MAAM,OAAO,WAAW;AACpE,QAAM,WAAW,SAAS,UAAU,IAAI,YAAY,MAAM;AAC1D,QAAM,iBAAiB,UAAU,EAAE,QAAQ,EAAE,GAAG,MAAM,GAAG,SAAS,SAAS,CAAC;AAC5E,QAAM,iBAAiB,UAAU,EAAE,QAAQ,EAAE,GAAG,MAAM,GAAG,SAAS,SAAS,CAAC;AAC5E,WAAS,qBAAqB,EAAE,MAAM,gBAAgB,MAAM,eAAe;AAC3E,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,YAAY,aAAa,KAAK;AAC5B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,OAAO;AACZ,UAAM,iBAAiB;AACvB,SAAK,gBAAgB,CAAC,gBAAgB,GAAG,CAAC;AAC1C,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,KAAK;AACV,SAAK,YAAY,SAAS;AAAA,EAC5B;AAAA,EACA,cAAc;AACZ,WAAO;AAAA;AAAA,UAED,iBAAiB,KAAK,IAAI,KAAK;AAAA;AAAA,QAEjC,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAOxC;AACF;AAGA,SAAS,iBAAiB,EAAE,QAAQ,eAAe,MAAM,GAAG;AAC1D,SAAO,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AACxC,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,gBAAgB;AACtB,UAAM,SAAS,SAAS,EAAE;AAC1B,QAAI,cAAc,mBAAmB,CAAC,CAAC,CAAC,KAAK,iBAAiB,MAAM;AAClE,YAAM,QAAQ,cAAc,UAAU,IAAI,EAAE,MAAM;AAClD,YAAM,YAAY,cAAc,MAAM,QAAQ,MAAM;AACpD,aAAO,cAAc,eAAe,EAAE,OAAO,QAAQ,SAAS;AAAA,IAChE;AACA,UAAM,UAAU,IAAI,gBAAgB,EAAE,OAAO,MAAM;AACnD,WAAO,cAAc,iBAAiB,SAAS,CAAC,CAAC,GAAG,MAAM;AAAA,EAC5D;AACF;AACA,SAAS,kBAAkB,EAAE,QAAQ,eAAe,kBAAkB,OAAO,MAAM,GAAG;AACpF,SAAO,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AACxC,UAAM,EAAE,GAAG,EAAE,IAAI;AACjB,UAAM,gBAAgB;AACtB,QAAI,mBAAmB,EAAE,UAAU,aAAa;AAC9C,YAAM,QAAQ,cAAc,UAAU,IAAI,EAAE,MAAM;AAClD,YAAM,QAAQ,cAAc,UAAU,IAAI,EAAE,MAAM;AAClD,UAAI,OAAO;AACX,UAAI,WAAW,aAAa,KAAK;AAC/B,SAAC,OAAO,KAAK,IAAI;AAAA,UACf,CAAC,MAAM,mBAAmB,MAAM,MAAM,mBAAmB,IAAI;AAAA,UAC7D,CAAC,MAAM,mBAAmB,MAAM,MAAM,mBAAmB,IAAI;AAAA,QAC/D,EAAE,IAAI,CAAC,iBAAiB;AACtB,gBAAM,CAAC,OAAO,KAAK,IAAI;AACvB,gBAAM,UAAU;AAAA,YACd,QAAQ,MAAM;AAAA,YACd,OAAO,MAAM;AAAA,YACb,OAAO,EAAE;AAAA,UACX;AACA,gBAAM,UAAU;AAAA,YACd,QAAQ,MAAM;AAAA,YACd,OAAO,MAAM;AAAA,YACb,OAAO,EAAE;AAAA,UACX;AACA,gBAAM,WAAW,IAAI,iBAAiB,QAAQ,EAAE,OAAO,EAAE,KAAK;AAC9D,iBAAO,cAAc,iBAAiB,UAAU,CAAC,SAAS,OAAO,GAAG,WAAW,MAAM,OAAO,MAAM,KAAK,CAAC;AAAA,QAC1G,CAAC;AAAA,MACH,OAAO;AACL,cAAM,cAAc,IAAI,wBAAwB,aAAa,uBAAuB,EAAE,OAAO,EAAE,KAAK;AACpG,cAAM,cAAc,IAAI,wBAAwB,aAAa,uBAAuB,EAAE,OAAO,EAAE,KAAK;AACpG,cAAM,UAAU;AAAA,UACd;AAAA,YACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,YACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,YACrC,OAAO,EAAE;AAAA,UACX;AAAA,UACA;AAAA,YACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,YACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,YACrC,OAAO,EAAE;AAAA,UACX;AAAA,UACA;AAAA,YACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,YACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,YACrC,OAAO,EAAE;AAAA,UACX;AAAA,UACA;AAAA,YACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,YACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,YACrC,OAAO,EAAE;AAAA,UACX;AAAA,QACF;AACA,gBAAQ,cAAc,iBAAiB,aAAa,SAAS,SAAS;AACtE,gBAAQ,cAAc,iBAAiB,aAAa,SAAS,SAAS;AAAA,MACxE;AACA,YAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,MAAM,OAAO,MAAM,MAAM,GAAG,SAAS,cAAc,CAAC;AAC/F,oBAAc,YAAY,MAAM,MAAM;AACtC,oBAAc,YAAY,MAAM,MAAM;AACtC,aAAO;AAAA,IACT;AACA,UAAM,SAAS,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AACnD,SAAK,EAAE,UAAU,YAAY,EAAE,UAAU,YAAY,cAAc,mBAAmB,CAAC,GAAG,CAAC,CAAC,MAAM,iBAAiB,MAAM;AACvH,YAAM,QAAQ,cAAc,UAAU,IAAI,EAAE,MAAM,EAAE;AACpD,YAAM,QAAQ,cAAc,UAAU,IAAI,EAAE,MAAM,EAAE;AACpD,YAAM,eAAe,EAAE,UAAU,WAAW,qBAAqB,uBAAuB,KAAK,IAAI;AACjG,YAAM,eAAe,EAAE,UAAU,WAAW,qBAAqB,uBAAuB,KAAK,IAAI;AACjG,YAAM,CAAC,WAAW,QAAQ,IAAI,cAAc,EAAE,OAAO,EAAE,OAAO,cAAc,cAAc,MAAM;AAChG,aAAO,cAAc,eAAe,UAAU,QAAQ,SAAS;AAAA,IACjE;AACA,UAAM,UAAU,IAAI,iBAAiB,QAAQ,EAAE,OAAO,EAAE,KAAK;AAC7D,WAAO,cAAc,iBAAiB,SAAS,CAAC,GAAG,CAAC,GAAG,MAAM;AAAA,EAC/D;AACF;AAGA,IAAI,EAAE,SAAS,aAAa,UAAU,cAAc,YAAY,gBAAgB,WAAW,eAAe,SAAS,aAAa,WAAW,eAAe,WAAW,eAAe,cAAc,kBAAkB,cAAc,kBAAkB,kBAAkB,sBAAsB,aAAa,iBAAiB,eAAe,mBAAmB,UAAU,cAAc,SAAS,aAAa,SAAS,aAAa,aAAa,iBAAiB,aAAa,iBAAiB,cAAc,kBAAkB,SAAS,aAAa,cAAc,kBAAkB,UAAU,cAAc,WAAW,eAAe,WAAW,eAAe,aAAa,iBAAiB,eAAe,mBAAmB,WAAW,eAAe,kBAAkB,sBAAsB,kBAAkB,sBAAsB,SAAS,aAAa,UAAU,cAAc,UAAU,cAAc,eAAe,mBAAmB,YAAY,eAAe,IAAI;AAG/6B,IAAI,OAAO,iBAAiB,EAAE,QAAQ,YAAY,KAAK,eAAe,kBAAkB,CAAC;AACzF,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,kBAAkB,EAAE,QAAQ,aAAa,KAAK,eAAe,aAAa,iBAAiB,KAAK,CAAC;AACtH,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,qBAAqB,MAAM;AAAA,EAC7B,YAAY,QAAQ;AAClB,SAAK,gBAAgB;AACrB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,OAAO;AAC1B,SAAK,gBAAgB,OAAO,IAAI,CAAC,GAAG,OAAO,IAAI,IAAI;AACnD,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,KAAK,eAAe,GAAG,CAAC,CAAC;AACrH,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW,CAAC;AAClB,SAAK,cAAc,QAAQ,CAAC,cAAc;AACxC,eAAS,KAAK,QAAQ,kBAAkB,kCAAkC;AAAA,IAC5E,CAAC;AACD,UAAM,YAAY,KAAK,cAAc,IAAI,CAAC,cAAc;AACtD,aAAO,IAAI;AAAA,IACb,CAAC,EAAE,KAAK,KAAK;AACb,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA,8BACZ,KAAK;AAAA,oCACC,KAAK;AAAA;AAAA;AAAA,cAG3B,SAAS,KAAK,YAAY;AAAA,0CACE;AAAA;AAAA;AAAA;AAAA;AAKtC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,UAAU;AAChB,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,GAAG,SAAS,SAAS,CAAC;AAAA,EACnE;AACA,QAAM,QAAQ,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK,EAAE,OAAO,CAAC,IAAI,OAAO,WAAW,IAAI,EAAE,CAAC;AACjF,QAAM,SAAS,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK;AAC3C,QAAM,UAAU,IAAI,mBAAmB,MAAM;AAC7C,SAAO,SAAS,iBAAiB,SAAS,SAAS,KAAK;AAC1D;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,YAAY,MAAM,YAAY;AACxC,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,OAAO;AACZ,UAAM,OAAO,CAAC,IAAI;AAClB,yBAAqB,2BAA2B,QAAQ,WAAW,OAAO,CAAC,EAAE,YAAY,IAAI,WAAW,MAAM,CAAC,GAAG,MAAM,WAAW,MAAM;AACzI,SAAK,KAAK,eAAe,QAAQ,MAAM;AACvC,UAAM,CAAC,WAAW,IAAI,qBAAqB,0BAA0B,YAAY,IAAI;AACrF,SAAK,cAAc,YAAY,WAAW,IAAI,CAAC,CAAC,IAAI;AACpD,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,CAAC,GAAG,GAAG,CAAC,CAAC;AAChF,SAAK,aAAa;AAClB,SAAK,YAAY,YAAY,KAAK;AAAA,EACpC;AAAA,EACA,cAAc;AACZ,UAAM,sBAAsB;AAAA,iDACiB,KAAK,cAAc;AAAA,gDACpB,KAAK,cAAc;AAAA;AAE/D,UAAM,uBAAuB,MAAM;AACjC,UAAI,KAAK,WAAW,WAAW,GAAG;AAChC,eAAO;AAAA,MACT,OAAO;AACL,eAAO,mBAAmB,aAAa,KAAK,WAAW,SAAS,CAAC;AAAA,MACnE;AAAA,IACF;AACA,UAAM,oBAAoB,MAAM;AAC9B,UAAI,UAAU;AACd,UAAI,KAAK,YAAY,WAAW,GAAG;AACjC,YAAI,KAAK,WAAW,WAAW,GAAG;AAChC,qBAAW;AAAA,QACb;AAAA,MACF,OAAO;AACL,iBAAS,KAAK,GAAG,KAAK,KAAK,YAAY,QAAQ,MAAM;AACnD,qBAAW,gBAAgB,aAAa,EAAE;AAAA,QAC5C;AAAA,MACF;AACA,aAAO;AAAA,IACT;AACA,UAAM,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,QAKb;AAAA;AAAA,QAEA,kCAAkC;AAAA;AAAA,6BAEb,qBAAqB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,iCAOjB,kBAAkB;AAAA,+CACJ,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,4BAexB,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAe7B,WAAO;AAAA,EACT;AACF;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,QAAQ,QAAQ;AAC1B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB,CAAC,IAAI,IAAI,CAAC;AAC/B,UAAM,cAAc,IAAI,MAAM,OAAO,MAAM;AAC3C,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,MAAM;AAC9C,kBAAY,MAAM,OAAO,OAAO;AAAA,IAClC;AACA,SAAK,cAAc;AACnB,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE;AACvC,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,GAAG,GAAG,CAAC,CAAC;AACpG,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,yBACI,KAAK,cAAc;AAAA,+CACG,KAAK,cAAc,KAAK,OAAO,KAAK,cAAc;AAAA,QACzF,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAoB3B,WAAO;AAAA,EACT;AACF;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,QAAQ,QAAQ;AAC1B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB;AACrB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,UAAM,cAAc,IAAI,MAAM,OAAO,MAAM;AAC3C,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,MAAM;AAC9C,kBAAY,MAAM,OAAO,OAAO;AAAA,IAClC;AACA,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,KAAK,eAAe,GAAG,CAAC,CAAC;AACrH,SAAK,SAAS;AACd,SAAK,YAAY,aAAa;AAAA,EAChC;AAAA,EACA,cAAc;AACZ,UAAM,QAAQ,mBAAmB,KAAK,YAAY,MAAM;AACxD,UAAM,WAAW,mBAAmB,KAAK,MAAM;AAC/C,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA,6BAEb,KAAK;AAAA,oCACE,KAAK;AAAA;AAAA;AAAA,8DAGqB,KAAK,YAAY;AAAA,gBAC/D,SAAS;AAAA;AAAA;AAAA;AAAA;AAKrB,WAAO;AAAA,EACT;AACF;AACA,SAAS,mBAAmB,QAAQ;AAClC,QAAM,OAAO,OAAO;AACpB,MAAI,OAAO,GAAG;AACZ,UAAM,MAAM,sBAAsB,2BAA2B;AAAA,EAC/D;AACA,QAAM,iBAAiB,IAAI,MAAM,IAAI;AACrC,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,mBAAe,OAAO,OAAO,SAAS,aAAa,EAAE;AAAA,EACvD;AACA,SAAO,eAAe,KAAK;AAC7B;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,gBAAgB;AACtB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,IAAI,MAAM,KAAK;AAChC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,aAAS,MAAM,EAAE,MAAM,KAAK;AAAA,EAC9B;AACA,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,GAAG;AACpC,UAAM,QAAQ,cAAc,UAAU,IAAI,EAAE,MAAM;AAClD,UAAM,SAAS,MAAM;AACrB,UAAM,YAAY,kBAAkB,QAAQ,EAAE,OAAO,EAAE,OAAO,MAAM,QAAQ;AAC5E,WAAO,SAAS,eAAe,UAAU,EAAE,OAAO,SAAS;AAAA,EAC7D;AACA,MAAI,EAAE,MAAM,WAAW,KAAK,aAAa,YAAY,MAAM,CAAC,GAAG,CAAC,CAAC,GAAG;AAClE,UAAM,WAAW,IAAI,uBAAuB,EAAE,OAAO,IAAI;AACzD,WAAO,cAAc,iBAAiB,UAAU,CAAC,CAAC,GAAG,EAAE,KAAK;AAAA,EAC9D;AACA,QAAM,UAAU,IAAI,kBAAkB,EAAE,OAAO,IAAI;AACnD,SAAO,cAAc,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AAC7D;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACpD,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,QAAM,0BAA0B,CAAC;AACjC,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,4BAAwB,KAAK,EAAE;AAC/B,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,GAAG,MAAM,MAAM;AAAA,EAC3E;AACA,uBAAqB,2BAA2B,UAAU,CAAC,KAAK,EAAE,GAAG,GAAG,MAAM,MAAM;AACpF,QAAM,UAAU,IAAI,kBAAkB,GAAG,OAAO,KAAK,IAAI,KAAK;AAC9D,QAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,OAAO,iBAAiB,EAAE,CAAC;AAC1E,QAAM,MAAM,SAAS,iBAAiB,SAAS,CAAC,EAAE,GAAG,SAAS,WAAW;AACzE,0BAAwB,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACvE,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACpD,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,QAAM,0BAA0B,CAAC;AACjC,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,4BAAwB,KAAK,EAAE;AAC/B,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,GAAG,MAAM,MAAM;AAAA,EAC3E;AACA,uBAAqB,2BAA2B,UAAU,CAAC,KAAK,EAAE,GAAG,GAAG,MAAM,MAAM;AACpF,QAAM,UAAU,IAAI,kBAAkB,GAAG,OAAO,KAAK,IAAI,KAAK;AAC9D,QAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,OAAO,iBAAiB,EAAE,CAAC;AAC1E,QAAM,MAAM,SAAS,iBAAiB,SAAS,CAAC,EAAE,GAAG,SAAS,WAAW;AACzE,0BAAwB,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACvE,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,UAAU,UAAU;AAC9B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,OAAO;AACZ,SAAK,cAAc,SAAS;AAC5B,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY,UAAU;AAC3B,SAAK,WAAW;AAAA,EAClB;AAAA,EACA,cAAc;AACZ,QAAI,gBAAgB;AACpB,QAAI,KAAK,aAAa,OAAO;AAC3B,sBAAgB;AAAA,IAClB;AACA,QAAI,cAAc;AAClB,QAAI,KAAK,aAAa,OAAO;AAC3B,oBAAc;AAAA,IAChB;AACA,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAQZ,KAAK,aAAa,QAAQ,QAAQ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gBAiBhD;AAAA;AAAA;AAAA;AAAA,oCAIoB;AAAA;AAAA;AAAA;AAIhC,WAAO;AAAA,EACT;AACF;AAGA,IAAI,qCAAqC,MAAM;AAAA,EAC7C,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,OAAO;AACZ,SAAK,cAAc,SAAS;AAC5B,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAetC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAAe,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY;AAClB,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,MAAI,SAAS,gBAAgB,KAAK,SAAS,iBAAiB,KAAK,aAAa,YAAY,SAAS,SAAS,SAAS,QAAQ,GAAG;AAC9H,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD;AACA,MAAI;AACJ,QAAM,aAAa,CAAC,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE,CAAC;AAC1F,MAAI,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,GAAG;AAC7D,cAAU,IAAI,mCAAmC,QAAQ;AAAA,EAC3D,OAAO;AACL,cAAU,IAAI,eAAe,UAAU,KAAK;AAC5C,eAAW,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI,EAAE,GAAG;AAAA,MACtF,MAAM;AAAA,MACN,MAAM,CAAC,SAAS,gBAAgB,SAAS,aAAa;AAAA,IACxD,GAAG,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,UAAU,SAAS,OAAO,EAAE,GAAG;AAAA,MACjE,MAAM;AAAA,MACN,MAAM,CAAC,SAAS,uBAAuB,SAAS,oBAAoB;AAAA,IACtE,CAAC;AAAA,EACH;AACA,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,UAAU;AACpE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,EAAE,IAAI;AACjB,QAAM,EAAE,YAAY,WAAW,IAAI;AACnC,SAAO,iBAAiB,EAAE,GAAG,GAAG,YAAY,YAAY,SAAS,SAAS,CAAC;AAC7E;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,OAAO,UAAU;AAC3B,SAAK,gBAAgB,CAAC,QAAQ;AAC9B,SAAK,gBAAgB;AACrB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,OAAO,SAAS;AACrB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,KAAK,eAAe,GAAG,CAAC,CAAC;AACrH,SAAK,QAAQ;AACb,SAAK,WAAW,WAAW,mBAAmB,MAAM,MAAM;AAC1D,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,QAAQ,mBAAmB,KAAK,IAAI;AAC1C,UAAM,eAAe,WAAW,KAAK,IAAI;AACzC,QAAI;AACJ,QAAI,KAAK,MAAM,WAAW,GAAG;AAC3B,iBAAW,KAAK,YAAY,IAAI,CAAC,GAAG,OAAO;AACzC,eAAO;AAAA,MACT,CAAC;AAAA,IACH,OAAO;AACL,iBAAW,KAAK,YAAY,IAAI,CAAC,GAAG,OAAO;AACzC,eAAO,aAAa,QAAQ,wBAAwB,gBAAgB,QAAQ;AAAA,MAC9E,CAAC;AAAA,IACH;AACA,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA,4BAEd;AAAA;AAAA,YAEhB,SAAS,KAAK,IAAI;AAAA,8CACgB;AAAA;AAAA;AAAA;AAI1C,WAAO;AAAA,EACT;AACF;AACA,IAAI,UAAU,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAC3C,SAAS,WAAW,MAAM;AACxB,MAAI,SAAS,GAAG;AACd,WAAO;AAAA,EACT,WAAW,QAAQ,GAAG;AACpB,WAAO,QAAQ,MAAM,GAAG,IAAI,EAAE,IAAI,CAAC,UAAU,aAAa,OAAO,EAAE,KAAK,GAAG;AAAA,EAC7E,OAAO;AACL,UAAM,MAAM,oBAAoB,2BAA2B;AAAA,EAC7D;AACF;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAO,MAAAZ,MAAK,IAAI;AACxB,QAAM,CAAC,QAAQ,KAAK,IAAI,mBAAmB,iBAAiB,GAAG,OAAOA,KAAI;AAC1E,qBAAmB,kBAAkB,GAAG,QAAQ,KAAK;AACrD,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,KAAK,EAAE,UAAU,UAAU;AAC5D,UAAM,cAAc,SAAS,UAAU,IAAI,EAAE,MAAM;AACnD,UAAM,YAAY,cAAc,YAAY,QAAQ,QAAQ,OAAO,EAAE,OAAO,EAAE,KAAK;AACnF,WAAO,SAAS,eAAe,OAAO,EAAE,OAAO,SAAS;AAAA,EAC1D;AACA,MAAI,aAAa,cAAc,KAAK,MAAM,GAAG;AAC3C,WAAO,SAAS,eAAe,OAAO,EAAE,OAAO,CAAC,CAAC;AAAA,EACnD;AACA,QAAM,UAAU,IAAI,cAAc,QAAQ,KAAK;AAC/C,QAAM,cAAc,CAAC,EAAE,MAAM,SAAS,MAAM,OAAO,CAAC;AACpD,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,WAAW;AACrE;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kBAAkB,CAAC,SAAS;AAC9B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,MAAM,IAAI;AAC9B,eAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,uEAAuE;AACtH,QAAM,QAAQ,WAAW,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAC/C,QAAM,WAAW,qBAAqB,YAAY,EAAE,OAAO,YAAY,KAAK;AAC5E,QAAM,WAAW,qBAAqB,YAAY,SAAS,QAAQ,WAAW,MAAM;AACpF,QAAM,mBAAmB,qBAAqB,oBAAoB,EAAE,OAAO,YAAY,KAAK;AAC5F,QAAM,mBAAmB,qBAAqB,oBAAoB,OAAO,WAAW,MAAM;AAC1F,QAAM,YAAY,qBAAqB,aAAa,kBAAkB,OAAO,WAAW,MAAM;AAC9F,QAAM,YAAY,CAAC;AACnB,QAAM,uBAAuB,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACtG,QAAM,yBAAyB,WAAW,EAAE,QAAQ,EAAE,GAAG,qBAAqB,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,SAAS,EAAE,CAAC;AAC/H,QAAM,wBAAwB,SAAS;AAAA,IACrC,QAAQ,EAAE,GAAG,uBAAuB;AAAA,IACpC,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,iBAAiB;AAAA,EACnC,CAAC;AACD,QAAM,SAAS,OAAO;AAAA,IACpB,QAAQ,EAAE,GAAG,sBAAsB;AAAA,IACnC,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,kBAAkB,MAAM,UAAU;AAAA,EACpD,CAAC;AACD,YAAU,KAAK,oBAAoB;AACnC,YAAU,KAAK,sBAAsB;AACrC,YAAU,KAAK,qBAAqB;AACpC,YAAU,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACzD,SAAO;AACT;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY,kBAAkB;AAAA,EAChC,QAAQ,aAAa;AAAA,EACrB,OAAO;AAAA,EACP,eAAe;AACjB,CAAC;AACD,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,YAAY,SAAS,UAAU,IAAI,OAAO,MAAM;AACtD,SAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,UAAU,mBAAmB,KAAK,GAAG,SAAS,SAAS,CAAC;AAC1F;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,QAAQ,UAAU;AAC9B,QAAM,UAAU,IAAI,gBAAgB,OAAO,OAAO,YAAY,MAAM;AACpE,QAAM,SAAS,SAAS,iBAAiB,SAAS,CAAC,MAAM,GAAG,OAAO;AACnE,SAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC3E;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,IAAI;AAClB,MAAI,UAAU,aAAa;AACzB,QAAI,EAAE,UAAU,aAAa;AAC3B,aAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,IACvD;AACA,UAAM,cAAc,MAAM,EAAE,KAAK;AACjC,UAAM,SAAS,MAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AACtF,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,QAAQ,MAAM,YAAY,GAAG,SAAS,SAAS,CAAC;AAC1F,gBAAY,QAAQ;AACpB,aAAS,YAAY,OAAO,MAAM;AAClC,WAAO;AAAA,EACT;AACA,MAAI,EAAE,UAAU,aAAa;AAC3B,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,SAAS,MAAM,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AACrF,aAAS,YAAY,SAAS,MAAM;AACpC,WAAO;AAAA,EACT;AACA,MAAI,CAAC,aAAa,gBAAgB,EAAE,OAAO,KAAK,GAAG;AACjD,UAAM,SAAS,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAC7D,WAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO,OAAO,OAAO,MAAM;AAAA,EAC7D;AACA,MAAI,UAAU,SAAS;AACrB,WAAO,KAAK,GAAG,QAAQ;AAAA,EACzB;AACA,MAAI,UAAU,QAAQ;AACpB,UAAM,kBAAkB,SAAS,eAAe,CAAC,GAAG,QAAQ,aAAa,uBAAuB,QAAQ,CAAC,CAAC;AAC1G,UAAM,eAAe,EAAE,GAAG,GAAG,GAAG,gBAAgB;AAChD,UAAM,SAAS,UAAU,EAAE,QAAQ,cAAc,SAAS,SAAS,CAAC;AACpE,aAAS,YAAY,gBAAgB,MAAM;AAC3C,WAAO;AAAA,EACT;AACA,QAAM,IAAI,MAAM,iCAAiC,EAAE,YAAY,OAAO;AACxE;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,iBAAiB,EAAE,QAAQ,YAAY,MAAM,eAAe,aAAa,CAAC;AACtF,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,gBAAgB;AACrB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,SAAS;AACd,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,KAAK,eAAe,GAAG,CAAC,CAAC;AACrH,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAgBtC,WAAO;AAAA,EACT;AACF;AAGA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWtC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,cAAc,aAAa,IAAI;AACvC,MAAI;AACJ,QAAM,cAAc;AAAA,IAClB,EAAE,MAAM,WAAW,MAAM,CAAC,YAAY,EAAE;AAAA,IACxC,EAAE,MAAM,WAAW,MAAM,CAAC,YAAY,EAAE;AAAA,EAC1C;AACA,MAAI,aAAa,cAAc,EAAE,KAAK,IAAI,MAAM,GAAG;AACjD,cAAU,IAAI,gBAAgB,EAAE,KAAK;AAAA,EACvC,OAAO;AACL,cAAU,IAAI,aAAa,EAAE,KAAK;AAAA,EACpC;AACA,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,WAAW;AACrE;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,QAAQ;AAClB,SAAK,WAAW;AAChB,SAAK,gBAAgB;AACrB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,qBAAqB,gBAAgB,QAAQ,CAAC;AACjE,SAAK,gBAAgB,OAAO,IAAI,CAAC,GAAG,OAAO,IAAI,IAAI;AACnD,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,KAAK,eAAe,GAAG,CAAC,CAAC;AACrH,SAAK,eAAe,OAAO,SAAS;AACpC,aAAS,KAAK,GAAG,KAAK,KAAK,cAAc,MAAM;AAC7C,WAAK,YAAY,SAAS;AAAA,IAC5B;AACA,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW,CAAC;AAClB,QAAI,KAAK,eAAe,GAAG;AACzB,eAAS,KAAK,qFAAqF;AACnG,eAAS,KAAK,GAAG,KAAK,KAAK,cAAc,MAAM;AAC7C,iBAAS,KAAK,gCAAgC,CAAC,EAAE,iDAAiD,8BAA8B,KAAK,QAAQ;AAAA,MAC/I;AACA,YAAM,YAAY,KAAK;AACvB,YAAM,iBAAiB,KAAK,eAAe;AAC3C,eAAS,KAAK,oDAAoD,qCAAqC,qBAAqB;AAAA,IAC9H,OAAO;AACL,eAAS,KAAK,uDAAuD;AAAA,IACvE;AACA,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA,6BACb,KAAK;AAAA,oCACE,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAM3B,SAAS,KAAK,YAAY;AAAA;AAAA;AAAA;AAAA;AAKpC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,YAAY,SAAS,UAAU,IAAI,OAAO,MAAM;AACtD,SAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,UAAU,mBAAmB,KAAK,GAAG,SAAS,SAAS,CAAC;AAC1F;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,QAAQ,MAAM,UAAU;AAC3C,QAAM,QAAQ,OAAO,GAAG;AACxB,MAAI,UAAU,aAAa;AACzB,UAAM,QAAQ,OAAO,IAAI,CAAC,OAAO,MAAM,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,SAAS,CAAC,CAAC;AACpF,UAAM,QAAQ,OAAO,IAAI,CAAC,OAAO,MAAM,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,SAAS,CAAC,CAAC;AACpF,UAAM,eAAe,YAAY,OAAO,MAAM,QAAQ;AACtD,UAAM,eAAe,YAAY,OAAO,MAAM,QAAQ;AACtD,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,cAAc,MAAM,aAAa,GAAG,SAAS,SAAS,CAAC;AACjG,UAAM,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACrD,UAAM,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACrD,aAAS,YAAY,aAAa,MAAM;AACxC,aAAS,YAAY,aAAa,MAAM;AACxC,WAAO;AAAA,EACT;AACA,MAAI,WAAW,SAAS,mBAAmB,MAAM;AACjD,MAAI,UAAU,UAAU;AACtB,eAAW;AAAA,EACb;AACA,MAAI,UAAU;AACZ,UAAM,aAAa,OAAO,IAAI,CAAC,OAAO;AACpC,YAAM,YAAY,aAAa,cAAc,GAAG,MAAM,MAAM,IAAI,CAAC;AACjE,YAAM,QAAQ,CAAC,IAAI,SAAS;AAC5B,aAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AAAA,IAC5E,CAAC;AACD,UAAM,kBAAkB,WAAW,IAAI,CAAC,OAAO;AAC7C,aAAO,EAAE,MAAM,SAAS,SAAS,GAAG,MAAM,GAAG,OAAO,GAAG,MAAM;AAAA,IAC/D,CAAC;AACD,UAAM,YAAY,qBAAqB,gBAAgB,WAAW,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,CAAC;AAC1F,UAAM,eAAe,WAAW,GAAG,MAAM,OAAO;AAChD,UAAM,UAAU,eAAe,iBAAiB,WAAW,OAAO,YAAY;AAC9E,UAAM,gBAAgB,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,IAAI;AAC7F,UAAM,UAAU,SAAS,eAAe,eAAe,OAAO,OAAO;AACrE,eAAW,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AAC1D,WAAO;AAAA,EACT;AACA,QAAM,cAAc,SAAS,OAAO,OAAO,kCAAkC;AAC7E,MAAI,OAAO,SAAS,aAAa;AAC/B,UAAM,gBAAgB,CAAC;AACvB,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM,aAAa;AACtD,YAAM,WAAW,OAAO,MAAM,IAAI,KAAK,WAAW;AAClD,oBAAc,KAAK,YAAY,UAAU,MAAM,QAAQ,CAAC;AAAA,IAC1D;AACA,UAAM,SAAS,YAAY,eAAe,MAAM,QAAQ;AACxD,eAAW,MAAM,eAAe;AAC9B,eAAS,YAAY,GAAG,MAAM;AAAA,IAChC;AACA,WAAO;AAAA,EACT;AACA,QAAM,EAAE,WAAW,SAAS,IAAI,kBAAkB,QAAQ,MAAM,QAAQ;AACxE,QAAM,SAAS,UAAU,IAAI,CAAC,OAAO,GAAG,KAAK;AAC7C,QAAM,UAAU,IAAI,eAAe,MAAM;AACzC,QAAM,cAAc,CAAC;AACrB,QAAM,UAAU,IAAI,MAAM,OAAO,SAAS,CAAC;AAC3C,MAAI,QAAQ,SAAS,GAAG;AACtB,YAAQ,KAAK,OAAO,GAAG;AACvB,gBAAY,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,QAAQ,EAAE,EAAE,CAAC;AACtD,aAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,cAAQ,MAAM,QAAQ,KAAK,KAAK,OAAO,IAAI;AAC3C,kBAAY,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,QAAQ,GAAG,EAAE,CAAC;AAAA,IACzD;AAAA,EACF;AACA,QAAM,MAAM,SAAS,iBAAiB,SAAS,WAAW,UAAU,GAAG,OAAO,WAAW;AACzF,YAAU,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACzD,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACrG,WAAS,YAAY,IAAI,MAAM;AAC/B,SAAO;AACT;AACA,SAAS,kBAAkB,QAAQ,MAAM,UAAU;AACjD,QAAM,WAAW,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,IAAI;AACxF,QAAM,YAAY,OAAO,IAAI,CAAC,OAAO,SAAS;AAAA,IAC5C,QAAQ,EAAE,GAAG,GAAG;AAAA,IAChB,SAAS;AAAA,IACT,OAAO;AAAA,MACL,OAAO;AAAA,QACL,aAAa,cAAc,GAAG,MAAM,MAAM,GAAG,IAAI,CAAC;AAAA,QAClD,aAAa,cAAc,GAAG,MAAM,MAAM,IAAI,CAAC;AAAA,MACjD;AAAA,IACF;AAAA,EACF,CAAC,CAAC;AACF,SAAO,EAAE,WAAW,SAAS;AAC/B;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,QAAQ,aAAa,eAAe,MAAM,OAAO,GAAG,KAAK,EAAE;AACjE,QAAM,WAAW,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,KAAK;AACzF,MAAI,aAAa,cAAc,QAAQ,MAAM,GAAG;AAC9C,WAAO,SAAS,eAAe,UAAU,OAAO,GAAG,OAAO,CAAC,CAAC;AAAA,EAC9D;AACA,QAAM,UAAU,OAAO,OAAO,CAAC,OAAO,aAAa,cAAc,GAAG,KAAK,IAAI,CAAC;AAC9E,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,GAAG,SAAS,SAAS,CAAC;AAAA,EACnE;AACA,QAAM,SAAS,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK;AAC3C,uBAAqB,uBAAuB,QAAQ,KAAK;AACzD,SAAO,YAAY,SAAS,OAAO,QAAQ;AAC7C;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,oBAAoB,gBAAgB,WAAW,WAAW,UAAU,UAAU,OAAO,cAAc,MAAM,4BAA4B,OAAO,oBAAoB,GAAG,oBAAoB,GAAG,mBAAmB,GAAG;AACvN,QAAM,cAAc,CAAC,sBAAsB;AACzC,YAAQ;AAAA,WACD;AACH,eAAO;AAAA,WACJ;AACH,eAAO;AAAA,WACJ;AACH,eAAO;AAAA;AAEP,cAAM,IAAI,MAAM,oBAAoB,qCAAqC;AAAA;AAAA,EAE/E;AACA,QAAM,cAAc,CAAC,sBAAsB;AACzC,YAAQ;AAAA,WACD;AACH,eAAO;AAAA,WACJ;AACH,eAAO;AAAA;AAEP,cAAM,IAAI,MAAM,oBAAoB,qCAAqC;AAAA;AAAA,EAE/E;AACA,QAAM,gBAAgB,iBAAiB;AAAA;AAAA,UAE/B;AAAA;AAAA;AAGR,QAAM,kBAAkB,iBAAiB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAMjC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAOR,QAAM,SAAS,iBAAiB,uBAAuB;AACvD,QAAM,SAAS,iBAAiB,uBAAuB;AACvD,QAAM,MAAM,iBAAiB,QAAQ;AACrC,QAAM,MAAM,iBAAiB,QAAQ;AACrC,QAAM,eAAe;AAAA;AAAA,uBAEA,iBAAiB,yBAAyB;AAAA,qBAC5C;AAAA,qBACA;AAAA;AAAA,mBAEF;AAAA,mBACA;AAAA;AAAA;AAAA,kBAGD;AAAA,sBACI,YAAY,iBAAiB;AAAA;AAAA;AAAA,gCAGnB,iCAAiC;AAAA,UACvD;AAAA;AAAA,UAEA,YAAY,iBAAiB;AAAA;AAAA;AAGrC,QAAM,UAAU,iBAAiB,aAAa,WAAW;AAAA,0BACjC;AAAA,QAClB,iBAAiB;AAAA,0BACC;AAAA;AAAA,UAEhB;AAAA;AAAA,eAEK,YAAY,iBAAiB,YAAY,YAAY,YAAY;AAAA,0BACtD;AAAA,QAClB,iBAAiB;AAAA,0BACC;AAAA;AAAA,UAEhB;AAAA;AAAA,eAEK,YAAY,iBAAiB;AAC1C,QAAM,UAAU,GAAG,YAAY,iBAAiB;AAChD,QAAM,UAAU,YAAY,gBAAgB;AAC5C,QAAM,QAAQ,iBAAiB,YAAY,iBAAiB,IAAI,YAAY,iBAAiB;AAC7F,QAAM,QAAQ,iBAAiB,YAAY,iBAAiB,IAAI,YAAY,iBAAiB;AAC7F,QAAM,WAAW;AAAA,QACX,oBAAoB,aAAa,2BAA2B,qBAAqB,GAAG,CAAC;AAAA,2DAClC;AAAA,UACjD,iBAAiB,UAAU;AAAA;AAAA;AAAA,2DAGsB;AAAA,UACjD,iBAAiB,UAAU;AAAA;AAAA;AAAA,kEAG6B;AAAA,4BACtC;AAAA;AAAA;AAAA;AAAA,yBAIH,iBAAiB,yBAAyB;AAAA,UACzD;AAAA,UACA,sBAAsB,SAAS,WAAW;AAAA;AAAA;AAAA;AAIlD,SAAO;AACT;AACA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,YAAY,UAAU,WAAW,WAAW,UAAU,UAAU,OAAO,cAAc,MAAM,4BAA4B,OAAO;AAC5H,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,cAAc,SAAS;AAC5B,SAAK,iBAAiB,SAAS,eAAe;AAC9C,SAAK,WAAW,SAAS,aAAa,MAAM,KAAK,SAAS,aAAa,MAAM,MAAM,KAAK,kBAAkB,SAAS,WAAW,MAAM,KAAK,CAAC,KAAK,mBAAmB,SAAS,cAAc,MAAM;AAC/L,SAAK,iBAAiB,KAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE,IAAI,EAAE,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE;AACxG,SAAK,gBAAgB,8BAA8B,KAAK,gBAAgB,KAAK,aAAa,KAAK,MAAM;AACrG,SAAK,oBAAoB,8BAA8B,KAAK,gBAAgB,KAAK,aAAa,KAAK,MAAM;AACzG,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,KAAK,iBAAiB;AACjH,QAAI,KAAK,QAAQ;AACf,UAAI,KAAK,kBAAkB,SAAS,aAAa,MAAM,GAAG;AACxD,aAAK,mBAAmB;AACxB,aAAK,gBAAgB,CAAC,OAAO,WAAW;AAAA,MAC1C,OAAO;AACL,aAAK,mBAAmB;AACxB,aAAK,gBAAgB,CAAC,aAAa,WAAW;AAAA,MAChD;AACA,UAAI,SAAS;AACX,aAAK,cAAc,KAAK,MAAM;AAC9B,aAAK,cAAc,KAAK,WAAW;AAAA,MACrC;AACA,UAAI,2BAA2B;AAC7B,aAAK,cAAc,KAAK,wBAAwB;AAChD,aAAK,cAAc,KAAK,WAAW;AAAA,MACrC;AAAA,IACF,OAAO;AACL,WAAK,mBAAmB,KAAK,kBAAkB;AAC/C,UAAI,SAAS;AACX,aAAK,cAAc,KAAK,MAAM;AAAA,MAChC;AACA,UAAI,2BAA2B;AAC7B,aAAK,cAAc,KAAK,wBAAwB;AAAA,MAClD;AAAA,IACF;AACA,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,4BAA4B;AACjC,SAAK,aAAa,KAAK,cAAc,KAAK,KAAK,kBAAkB;AACjE,SAAK,aAAa,KAAK,cAAc,KAAK,KAAK,kBAAkB;AACjE,SAAK,YAAY,KAAK,IAAI,KAAK,cAAc,KAAK,KAAK,kBAAkB,KAAK,cAAc,EAAE;AAC9F,SAAK,YAAY,YAAY,KAAK,eAAe;AACjD,SAAK,YAAY,YAAY,KAAK,eAAe;AACjD,SAAK,WAAW,WAAW,KAAK,cAAc;AAC9C,SAAK,YAAY,YAAY,KAAK,qBAAqB,KAAK,eAAe,KAAK,aAAa,KAAK,aAAa,KAAK,YAAY,KAAK,UAAU,KAAK,oBAAoB,KAAK;AAAA,EAC/K;AAAA,EACA,cAAc;AACZ,UAAM,eAAe,KAAK,SAAS,2BAA2B,KAAK,mBAAmB,KAAK,YAAY,KAAK,YAAY,KAAK,WAAW,KAAK,kBAAkB,CAAC,KAAK,cAAc,IAAI,uBAAuB,KAAK,mBAAmB,KAAK,eAAe,CAAC,KAAK,gBAAgB,KAAK,SAAS;AAC9R,UAAM,eAAe,KAAK,SAAS,CAAC,KAAK,iBAAiB,KAAK,mBAAmB,GAAG,GAAG,CAAC,IAAI,CAAC,GAAG,GAAG,CAAC;AACrG,UAAM,WAAW;AAAA,MACf,oBAAoB,KAAK,gBAAgB,KAAK,WAAW,KAAK,WAAW,KAAK,UAAU,KAAK,SAAS,KAAK,YAAY,KAAK,2BAA2B,aAAa,IAAI,aAAa,IAAI,aAAa,EAAE;AAAA,MACxM;AAAA;AAEF,WAAO;AAAA,EACT;AACF;AAGA,SAAS,wBAAwB,OAAO,gBAAgB;AACtD,QAAM,SAAS,MAAM;AACrB,MAAI,UAAU,GAAG;AACf,WAAO,iBAAiB;AAAA,MACtB,GAAG,MAAM,MAAM,GAAG,EAAE;AAAA,MACpB,MAAM,SAAS,KAAK,MAAM,SAAS;AAAA,MACnC,MAAM,SAAS;AAAA,IACjB,IAAI;AAAA,MACF,GAAG,MAAM,MAAM,GAAG,EAAE;AAAA,MACpB,MAAM,SAAS;AAAA,MACf,MAAM,SAAS,KAAK,MAAM,SAAS;AAAA,IACrC;AAAA,EACF,WAAW,CAAC,kBAAkB,WAAW,KAAK,MAAM,KAAK,GAAG;AAC1D,WAAO,CAAC,MAAM,IAAI,CAAC;AAAA,EACrB,OAAO;AACL,WAAO;AAAA,EACT;AACF;AACA,SAAS,gBAAgB,EAAE,GAAG,QAAQ,UAAU,SAAS,UAAU,OAAO,MAAM,yBAAyB,MAAM,iBAAiB,GAAG,YAAY,cAAc,KAAK,GAAG;AACnK,QAAM,iBAAiB,SAAS,eAAe;AAC/C,QAAM,aAAa,iBAAiB,QAAQ;AAC5C,QAAM,aAAa;AACnB,QAAM,WAAW,kBAAkB,SAAS,iBAAiB,SAAS,YAAY,SAAS,gBAAgB,SAAS,WAAW,SAAS,QAAQ,SAAS;AACzJ,QAAM,gBAAgB,CAAC;AACvB,MAAI;AACJ,MAAI;AACJ,MAAI,UAAU;AACZ,UAAM,YAAY,SAAS,WAAW,SAAS,UAAU,SAAS;AAClE,gBAAY,SAAS;AAAA,MACnB,QAAQ,EAAE,EAAE;AAAA,MACZ,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,CAAC,GAAG,SAAS,WAAW,SAAS,EAAE;AAAA,IACrD,CAAC;AACD,qBAAiB,SAAS;AAAA,MACxB,QAAQ,EAAE,GAAG,OAAO;AAAA,MACpB,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,CAAC,GAAG,WAAW,SAAS,WAAW,EAAE;AAAA,IACvD,CAAC;AAAA,EACH,OAAO;AACL,gBAAY,SAAS;AAAA,MACnB,QAAQ,EAAE,EAAE;AAAA,MACZ,SAAS;AAAA,MACT,OAAO;AAAA,QACL,OAAO,iBAAiB;AAAA,UACtB,SAAS;AAAA,UACT,SAAS,WAAW,SAAS;AAAA,UAC7B,SAAS;AAAA,QACX,IAAI;AAAA,UACF,SAAS;AAAA,UACT,SAAS;AAAA,UACT,SAAS,WAAW,SAAS;AAAA,QAC/B;AAAA,MACF;AAAA,IACF,CAAC;AACD,qBAAiB,SAAS;AAAA,MACxB,QAAQ,EAAE,GAAG,OAAO;AAAA,MACpB,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,CAAC,GAAG,SAAS,YAAY,SAAS,WAAW,EAAE;AAAA,IACjE,CAAC;AAAA,EACH;AACA,gBAAc,KAAK,SAAS;AAC5B,gBAAc,KAAK,cAAc;AACjC,MAAI,0BAA0B,MAAM;AAClC,UAAM,cAAc,wBAAwB,uBAAuB,OAAO,cAAc;AACxF,QAAI,eAAe,MAAM;AACvB,+BAAyB,SAAS;AAAA,QAChC,QAAQ,EAAE,GAAG,uBAAuB;AAAA,QACpC,SAAS;AAAA,QACT,OAAO,EAAE,OAAO,YAAY;AAAA,MAC9B,CAAC;AACD,oBAAc,KAAK,sBAAsB;AAAA,IAC3C;AAAA,EACF;AACA,MAAI,QAAQ,MAAM;AAChB,UAAM,cAAc,wBAAwB,KAAK,OAAO,cAAc;AACtE,QAAI,eAAe,MAAM;AACvB,aAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,KAAK,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AACzF,oBAAc,KAAK,IAAI;AAAA,IACzB;AAAA,EACF;AACA,QAAM,SAAS,iBAAiB;AAAA,IAC9B,GAAG,iBAAiB,YAAY;AAAA,IAChC,GAAG,iBAAiB,iBAAiB;AAAA,IACrC;AAAA,IACA;AAAA,IACA,SAAS;AAAA,IACT;AAAA,IACA,YAAY;AAAA,IACZ;AAAA,IACA;AAAA,EACF,CAAC;AACD,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,SAAS,EAAE,CAAC;AACtG,gBAAc,KAAK,MAAM;AACzB,aAAW,MAAM,eAAe;AAC9B,aAAS,YAAY,GAAG,MAAM;AAAA,EAChC;AACA,SAAO;AACT;AACA,SAAS,WAAW,EAAE,GAAG,QAAQ,UAAU,SAAS,UAAU,OAAO,MAAM,yBAAyB,MAAM,iBAAiB,GAAG,YAAY,cAAc,KAAK,GAAG;AAC9J,QAAM,UAAU,QAAQ;AACxB,QAAM,4BAA4B,0BAA0B;AAC5D,QAAM,iBAAiB,SAAS,eAAe;AAC/C,QAAM,WAAW,kBAAkB,SAAS,iBAAiB,SAAS,YAAY,SAAS,gBAAgB,SAAS,WAAW,SAAS,QAAQ,SAAS;AACzJ,MAAI,YAAY,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,KAAK,SAAS,mBAAmB,KAAK,SAAS,kBAAkB,KAAK,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,MAAM,SAAS,QAAQ,SAAS,UAAU,SAAS,QAAQ,SAAS,UAAU;AAClR,WAAO,gBAAgB;AAAA,MACrB;AAAA,MACA;AAAA,MACA;AAAA,MACA,SAAS;AAAA,MACT;AAAA,MACA,YAAY;AAAA,MACZ;AAAA,MACA;AAAA,IACF,CAAC;AAAA,EACH;AACA,QAAM,YAAY,iBAAiB,SAAS,YAAY,SAAS,WAAW,SAAS;AACrF,QAAM,YAAY,iBAAiB,SAAS,cAAc,SAAS,YAAY,SAAS;AACxF,QAAM,WAAW,SAAS,eAAe,SAAS,cAAc,SAAS;AACzE,QAAM,UAAU,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI;AAC5D,QAAM,aAAa;AAAA,IACjB,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE;AAAA,IACrE,EAAE,MAAM,SAAS,MAAM,CAAC,GAAG,OAAO,EAAE;AAAA,IACpC,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE;AAAA,IACrE,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,gBAAgB,SAAS,aAAa,EAAE;AAAA,IACzE,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE;AAAA,IACnC,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE;AAAA,IACnC,EAAE,MAAM,SAAS,MAAM,CAAC,QAAQ,EAAE;AAAA,EACpC;AACA,QAAM,UAAU,IAAI,gBAAgB,UAAU,WAAW,WAAW,UAAU,SAAS,aAAa,yBAAyB;AAC7H,QAAM,gBAAgB,CAAC;AACvB,QAAM,WAAW,CAAC,GAAG,MAAM;AAC3B,MAAI,SAAS;AACX,QAAI,CAAC,kBAAkB,KAAK,MAAM,WAAW,GAAG;AAC9C,aAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,KAAK,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,KAAK,MAAM,IAAI,GAAG,CAAC,EAAE,EAAE,CAAC;AACnG,oBAAc,KAAK,IAAI;AAAA,IACzB;AACA,aAAS,KAAK,IAAI;AAAA,EACpB;AACA,MAAI,2BAA2B;AAC7B,QAAI,CAAC,kBAAkB,uBAAuB,MAAM,WAAW,GAAG;AAChE,+BAAyB,SAAS;AAAA,QAChC,QAAQ,EAAE,GAAG,uBAAuB;AAAA,QACpC,SAAS;AAAA,QACT,OAAO,EAAE,OAAO,CAAC,uBAAuB,MAAM,IAAI,GAAG,CAAC,EAAE;AAAA,MAC1D,CAAC;AACD,oBAAc,KAAK,sBAAsB;AAAA,IAC3C;AACA,aAAS,KAAK,sBAAsB;AAAA,EACtC;AACA,MAAI,gBAAgB,aAAa;AAC/B,eAAW,KAAK,EAAE,MAAM,WAAW,MAAM,CAAC,cAAc,EAAE,CAAC;AAC3D,YAAQ,YAAY;AAAA,EACtB;AACA,QAAM,MAAM,SAAS,iBAAiB,SAAS,UAAU,EAAE,OAAO,UAAU;AAC5E,aAAW,MAAM,eAAe;AAC9B,aAAS,YAAY,GAAG,MAAM;AAAA,EAChC;AACA,SAAO;AACT;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAY,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB,IAAI;AACvE,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,OAAO,WAAW;AAC5I,SAAO,WAAW,EAAE,GAAG,QAAQ,UAAU,SAAS,SAAS,CAAC;AAC9D;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,6BAA6B,mBAAmB,GAAG;AAC1D,QAAM,cAAc,CAAC,sBAAsB;AACzC,YAAQ;AAAA,WACD;AACH,eAAO;AAAA,WACJ;AACH,eAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWP,cAAM,IAAI,MAAM,oBAAoB,qCAAqC;AAAA;AAAA,EAE/E;AACA,QAAM,eAAe;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,iBASN,YAAY,gBAAgB;AAAA;AAAA;AAAA,iBAG5B,YAAY,gBAAgB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8DAOiB;AAC5D,QAAM,UAAU;AAAA,UACR;AAAA;AAAA,eAEK,YAAY,gBAAgB;AACzC,QAAM,WAAW;AAAA,uDACoC,YAAY,gBAAgB;AAAA,wBAC3D;AAAA,MAClB;AAAA;AAAA;AAAA,uDAGiD,YAAY,gBAAgB;AAAA,wBAC3D;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,QAShB,YAAY,gBAAgB;AAAA;AAAA,aAEvB,YAAY,gBAAgB;AAAA;AAAA;AAAA,iEAGwB,YAAY,gBAAgB;AAAA,wBACrE;AAAA,6CACqB,mBAAmB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,iEAOC;AAAA;AAAA;AAG/D,SAAO;AACT;AACA,IAAI,0BAA0B,MAAM;AAAA,EAClC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,cAAc,SAAS;AAC5B,iBAAa,OAAO,SAAS,eAAe,gBAAgB,MAAM,6BAA6B;AAC/F,SAAK,SAAS,SAAS,aAAa,MAAM,KAAK,SAAS,cAAc,MAAM;AAC5E,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE;AAClD,SAAK,gBAAgB,8BAA8B,KAAK,gBAAgB,KAAK,aAAa,KAAK,MAAM;AACrG,SAAK,oBAAoB,8BAA8B,KAAK,gBAAgB,KAAK,aAAa,KAAK,MAAM;AACzG,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,KAAK,iBAAiB;AACjH,QAAI,KAAK,QAAQ;AACf,WAAK,mBAAmB;AACxB,WAAK,gBAAgB,CAAC,aAAa,KAAK;AAAA,IAC1C,OAAO;AACL,WAAK,mBAAmB,KAAK,kBAAkB;AAAA,IACjD;AACA,SAAK,aAAa,KAAK,cAAc,KAAK,KAAK,kBAAkB;AACjE,SAAK,aAAa,KAAK,cAAc,KAAK,KAAK,kBAAkB;AACjE,SAAK,YAAY,KAAK,IAAI,KAAK,cAAc,KAAK,KAAK,kBAAkB,KAAK,cAAc,EAAE;AAC9F,SAAK,YAAY,oBAAoB,KAAK,UAAU,KAAK,qBAAqB,KAAK;AAAA,EACrF;AAAA,EACA,cAAc;AACZ,UAAM,eAAe,KAAK,SAAS,2BAA2B,KAAK,mBAAmB,KAAK,YAAY,KAAK,YAAY,KAAK,WAAW,KAAK,gBAAgB,IAAI,uBAAuB,KAAK,mBAAmB,KAAK,aAAa;AAClO,UAAM,WAAW;AAAA,MACf,6BAA6B,KAAK,SAAS,IAAI,CAAC;AAAA,MAChD;AAAA;AAEF,WAAO;AAAA,EACT;AACF;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,MAAM,GAAG;AAC/B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,SAAS;AAC5B,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,iBAAiB,SAAS,eAAe;AAC9C,SAAK,YAAY,kBAAkB,KAAK;AAAA,EAC1C;AAAA,EACA,cAAc;AACZ,UAAM,SAAS,KAAK,iBAAiB,IAAI;AACzC,UAAM,SAAS,KAAK,iBAAiB,IAAI;AACzC,UAAM,aAAa,KAAK,iBAAiB,IAAI;AAC7C,WAAO;AAAA,MACL,kCAAkC;AAAA;AAAA;AAAA;AAAA,0BAId;AAAA;AAAA,0CAEgB,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oBA0B1C,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAiBvB;AACF;AAGA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,YAAY,gBAAgB,IAAI;AACxE,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,GAAG,MAAM,iBAAiB,OAAO,WAAW;AACvI,QAAM,aAAa;AAAA,IACjB,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE;AAAA,IACrE;AAAA,MACE,MAAM;AAAA,MACN,MAAM;AAAA,QACJ,SAAS,eAAe,IAAI,SAAS,QAAQ;AAAA,QAC7C,SAAS,cAAc,IAAI,SAAS,QAAQ;AAAA,MAC9C;AAAA,IACF;AAAA,IACA,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE;AAAA,IACrE;AAAA,MACE,MAAM;AAAA,MACN,MAAM;AAAA,QACJ,SAAS;AAAA,QACT,SAAS;AAAA,QACT,SAAS;AAAA,QACT,SAAS;AAAA,MACX;AAAA,IACF;AAAA,EACF;AACA,MAAI;AACJ,MAAI,IAAI,EAAE,QAAQ,mCAAmC,GAAG;AACtD,cAAU,IAAI,uBAAuB,QAAQ;AAAA,EAC/C,OAAO;AACL,cAAU,IAAI,wBAAwB,QAAQ;AAC9C,UAAM,YAAY,SAAS,QAAQ,KAAK,SAAS,QAAQ;AACzD,UAAM,YAAY,SAAS,QAAQ;AACnC,UAAM,WAAW,SAAS,eAAe,SAAS,cAAc,SAAS;AACzE,eAAW,KAAK,EAAE,MAAM,UAAU,MAAM,CAAC,SAAS,EAAE,GAAG,EAAE,MAAM,UAAU,MAAM,CAAC,SAAS,EAAE,GAAG,EAAE,MAAM,UAAU,MAAM,CAAC,QAAQ,EAAE,CAAC;AAAA,EACpI;AACA,SAAO,SAAS,iBAAiB,SAAS,CAAC,IAAI,MAAM,GAAG,WAAW,UAAU;AAC/E;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,iBAAiB,EAAE,QAAQ,YAAY,IAAI,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,iBAAiB,EAAE,QAAQ,YAAY,KAAK,CAAC;AACzD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,wBAAwB,MAAM;AAAA,EAChC,YAAY,UAAU,UAAU,UAAU,QAAQ;AAChD,SAAK,gBAAgB,CAAC,SAAS,SAAS,QAAQ;AAChD,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,UAAM,CAAC,QAAQ,IAAI;AACnB,SAAK,cAAc,CAAC,UAAU,SAAS,IAAI,SAAS,IAAI,QAAQ;AAChE,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,WAAW,WAAW,aAAa,IAAI;AAC5C,SAAK,wBAAwB,KAAK,YAAY,KAAK;AACnD,SAAK,uBAAuB,KAAK,YAAY,KAAK;AAClD,SAAK,YAAY,iBAAiB,KAAK,YAAY,KAAK,yBAAyB,KAAK;AAAA,EACxF;AAAA,EACA,cAAc;AACZ,UAAM,CAAC,kBAAkB,eAAe,IAAI,CAAC,mCAAmC,iCAAiC;AACjH,UAAM,CAAC,aAAa,aAAa,GAAG,IAAI,KAAK,wBAAwB;AAAA,MACnE,IAAI;AAAA,MACJ;AAAA,MACA,MAAM;AAAA,IACR,IAAI;AAAA,MACF;AAAA,MACA;AAAA,MACA,mBAAmB;AAAA,IACrB;AACA,UAAM,CAAC,YAAY,YAAY,GAAG,IAAI,KAAK,uBAAuB;AAAA,MAChE,IAAI;AAAA,MACJ;AAAA,MACA,MAAM;AAAA,IACR,IAAI;AAAA,MACF;AAAA,MACA;AAAA,MACA,mBAAmB;AAAA,IACrB;AACA,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA,iCAGT;AAAA,gCACD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,6BAeH;AAAA,4BACD;AAAA,qBACP;AAAA,mCACc;AAAA;AAAA;AAAA;AAAA,qBAId;AAAA,mCACc;AAAA;AAAA;AAAA;AAAA;AAAA,aAKtB,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAwBd,WAAO;AAAA,EACT;AACF;AAGA,IAAI,iBAAiB,CAAC,SAAS;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,OAAO,OAAO,IAAI;AACzC,QAAM,EAAE,UAAU,QAAQ,mBAAmB,IAAI;AACjD,QAAM,UAAU,IAAI,sBAAsB,OAAO,MAAM,IAAI,MAAM,OAAO,UAAU,MAAM;AACxF,QAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,kBAAkB,EAAE,CAAC;AACpE,SAAO,SAAS,iBAAiB,SAAS,CAAC,QAAQ,OAAO,MAAM,GAAG,WAAW,WAAW;AAC3F;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AAAA,CACH,SAAS,YAAY;AACpB,aAAW,UAAU;AACrB,aAAW,SAAS;AACtB,GAAG,eAAe,aAAa,CAAC,EAAE;AAClC,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,KAAK,OAAO,WAAW,UAAU;AAC3C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,OAAO;AACZ,UAAM,iBAAiB;AACvB,SAAK,gBAAgB,CAAC,gBAAgB,GAAG,CAAC;AAC1C,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AACjB,SAAK,UAAU;AACf,SAAK,KAAK;AACV,SAAK,YAAY,OAAO,KAAK,MAAM,KAAK,aAAa,KAAK;AAAA,EAC5D;AAAA,EACA,cAAc;AACZ,UAAM,OAAO,KAAK,YAAY;AAC9B,UAAM,UAAU,KAAK,OAAO,WAAW,OAAO,QAAQ;AACtD,UAAM,MAAM,KAAK,YAAY,UAAU,QAAQ,WAAW,MAAM,UAAU,KAAK,EAAE;AACjF,UAAM,SAAS,KAAK,YAAY,KAAK,YAAY,SAAS;AAC1D,QAAI,YAAY;AAChB,QAAI,YAAY;AAChB,QAAI,KAAK,WAAW;AAClB,kBAAY,KAAK,UAAU,UAAU,SAAS,MAAM;AACpD,kBAAY,KAAK,UAAU,YAAY;AAAA,IACzC,OAAO;AACL,kBAAY,KAAK,UAAU,gBAAgB,WAAW;AACtD,kBAAY,KAAK,UAAU,eAAe;AAAA,IAC5C;AACA,WAAO;AAAA,QACH,kCAAkC;AAAA;AAAA;AAAA;AAAA,qBAIrB,eAAe,MAAM,UAAU,KAAK,EAAE;AAAA,qBACtC;AAAA;AAAA,eAEN;AAAA,uBACQ;AAAA,aACV,eAAe,MAAM,UAAU,KAAK,EAAE;AAAA,iBAClC,KAAK,YAAY,WAAW,MAAM,UAAU,KAAK,EAAE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAMlE;AACF;AACA,SAAS,WAAW,MAAM,MAAM,KAAK;AACnC,MAAI,SAAS,GAAG;AACd,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG,WAAW;AAAA,EACvB,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG,WAAW,WAAW;AAAA,EAClC,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG,WAAW,WAAW,WAAW;AAAA,EAC7C,OAAO;AACL,UAAM,MAAM,cAAc,gBAAgB,2BAA2B;AAAA,EACvE;AACF;AACA,SAAS,eAAe,MAAM,MAAM,KAAK;AACvC,MAAI,SAAS,GAAG;AACd,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG;AAAA,EACZ,OAAO;AACL,UAAM,MAAM,cAAc,gBAAgB,2BAA2B;AAAA,EACvE;AACF;AAGA,SAAS,SAAS,KAAK,GAAG,UAAU,MAAM,WAAW,UAAU;AAC7D,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,cAAc,qBAAqB,mBAAmB,CAAC,IAAI,GAAG,KAAK;AACzE,MAAI,YAAY;AAChB,MAAI,eAAe,MAAM;AACvB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,YAAY,EAAE,CAAC;AAAA,EAC3F;AACA,QAAM,eAAe,qBAAqB,iBAAiB,GAAG,KAAK,EAAE;AACrE,MAAI,iBAAiB,QAAQ,GAAG;AAC9B,UAAM,IAAI,MAAM,oDAAoD,EAAE,MAAM,SAAS,kBAAkB,MAAM;AAAA,EAC/G;AACA,QAAMZ,QAAO,UAAU,MAAM;AAC7B,MAAI,SAAS,UAAU,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,SAAS,CAAC;AACtE,WAAS,KAAK,GAAG,MAAM,KAAK,KAAK,KAAK,KAAKA,KAAI,CAAC,IAAI,GAAG,MAAM;AAC3D,UAAM,UAAU,IAAI,YAAY,KAAK,UAAU,OAAO,OAAO,QAAQ;AACrE,UAAM,aAAa;AACnB,UAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,EAAE,EAAE,CAAC;AACpD,aAAS,SAAS,iBAAiB,SAAS,CAAC,MAAM,GAAG,OAAO,OAAO,WAAW;AAC/E,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,WAAW;AACb,UAAM,UAAU,IAAI,YAAY,KAAK,UAAU,OAAO,WAAW,QAAQ;AACzE,UAAM,aAAa;AACnB,UAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,CAAC,EAAE,CAAC;AACnD,aAAS,SAAS,iBAAiB,SAAS,CAAC,MAAM,GAAG,OAAO,OAAO,WAAW;AAC/E,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,eAAe,MAAM;AACvB,UAAM,qBAAqB,qBAAqB,uBAAuB,WAAW;AAClF,UAAM,0BAA0B,WAAW,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,mBAAmB,EAAE,CAAC;AAC5H,aAAS,YAAY,OAAO,MAAM;AAClC,aAAS,YAAY,UAAU,MAAM;AACrC,WAAO;AAAA,EACT;AACA,SAAO;AACT;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,SAAO,SAAS,WAAW,MAAM,GAAG,UAAU,MAAM,WAAW,QAAQ;AACzE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,SAAO,SAAS,WAAW,KAAK,GAAG,UAAU,MAAM,WAAW,QAAQ;AACxE;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,aAAa,YAAY;AACnC,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,WAAW;AAChB,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY,gBAAgB;AACjC,SAAK,aAAa;AAAA,EACpB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA,oBAItB,KAAK,qBAAqB;AAAA,oBAC1B,KAAK,oBAAoB;AAAA,oBACzB,KAAK,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAO/B,KAAK,mBAAmB;AAAA;AAAA;AAAA,sBAGhB,KAAK,uBAAuB;AAAA;AAAA;AAAA;AAI9C,WAAO;AAAA,EACT;AAAA,EACA,uBAAuB;AACrB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,sBAAsB;AACpB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,sBAAsB;AACpB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,qBAAqB;AACnB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,yBAAyB;AACvB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AACF;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,WAAW,WAAW,IAAI;AAClC,QAAM,YAAY,EAAE,MAAM;AAC1B,QAAM,cAAc,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AACjE,QAAM,aAAa,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AAChE,QAAM,aAAa,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AAChE,QAAM,eAAe,cAAc;AACnC,QAAM,cAAc,aAAa;AACjC,QAAM,cAAc,cAAc,YAAY;AAC9C,QAAM,cAAc,eAAe,SAAS,CAAC,WAAW,cAAc,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,cAAc,WAAW;AACpJ,QAAM,cAAc;AAAA,IAClB,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE;AAAA,EACrC;AACA,QAAM,UAAU,IAAI,qBAAqB,aAAa,UAAU;AAChE,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,WAAW;AACrE;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mCAAmC,MAAM;AAAA,EAC3C,YAAY,aAAa,cAAc,aAAa,UAAU,OAAO,cAAc,MAAM,qBAAqB,OAAO;AACnH,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,IAAI,CAAC;AAC/B,SAAK,cAAc;AACnB,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,EAAE;AAClD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,oBAAoB;AACtB,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,qBAAqB;AAC1B,SAAK,eAAe;AACpB,SAAK,cAAc;AACnB,SAAK,YAAY,iBAAiB,KAAK,cAAc,KAAK,gBAAgB,KAAK;AAAA,EACjF;AAAA,EACA,cAAc;AACZ,UAAM,aAAa,KAAK,cAAc,KAAK;AAC3C,UAAM,gBAAgB,KAAK,cAAc,KAAK,KAAK,cAAc,KAAK,KAAK,cAAc;AACzF,UAAM,cAAc,KAAK,cAAc,KAAK,KAAK,eAAe;AAChE,UAAM,aAAa,KAAK,cAAc,KAAK,KAAK,cAAc;AAC9D,UAAM,WAAW;AAAA,QACb,oBAAoB,KAAK,YAAY,KAAK,oBAAoB,OAAO,CAAC;AAAA;AAAA,kDAE5B,gBAAgB;AAAA,kDAChB,KAAK,iBAAiB,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,QAUrE,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,mDAuBoB,sCAAsC,KAAK,cAAc;AAAA,qDACvD,qCAAqC,KAAK,cAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UASnG,aAAa,gBAAgB,gBAAgB,gBAAgB,kBAAkB,iCAAiC;AAAA;AAAA;AAAA,gCAG1F,KAAK;AAAA,gCACL,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAOL,KAAK;AAAA,kCACH,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAM7B,sBAAsB,KAAK,SAAS,KAAK,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAMzD,WAAO;AAAA,EACT;AACF;AAGA,IAAI,6BAA6B,MAAM;AAAA,EACrC,YAAY,UAAU,UAAU,OAAO,cAAc,MAAM,qBAAqB,OAAO;AACrF,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,GAAG,GAAG,CAAC;AAC7B,SAAK,SAAS;AACd,SAAK,cAAc,SAAS;AAC5B,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,EAAE;AAClD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,GAAG,GAAG,CAAC,CAAC;AACpG,iBAAa,OAAO,SAAS,eAAe,gBAAgB,MAAM,6BAA6B;AAC/F,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,oBAAoB;AACtB,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,WAAW;AAChB,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,qBAAqB;AAC1B,SAAK,YAAY,iBAAiB,eAAe,KAAK,SAAS,gBAAgB,KAAK,SAAS;AAAA,EAC/F;AAAA,EACA,cAAc;AACZ,UAAM,UAAU,IAAI,KAAK,SAAS,cAAc;AAChD,UAAM,WAAW;AAAA,QACb,oBAAoB,KAAK,YAAY,KAAK,oBAAoB,MAAM,CAAC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,QASrE,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,uCAUQ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAQP,KAAK,SAAS;AAAA;AAAA,gCAEd;AAAA;AAAA;AAAA;AAAA,kCAIE,KAAK,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAalC,sBAAsB,KAAK,SAAS,KAAK,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAM7D,WAAO;AAAA,EACT;AACF;AAGA,IAAI,0BAA0B,MAAM;AAAA,EAClC,YAAY,UAAU,UAAU,OAAO,cAAc,MAAM,qBAAqB,OAAO;AACrF,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAAA;AAEhB,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,cAAc,SAAS;AAC5B,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,iBAAiB,SAAS,eAAe;AAC9C,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,oBAAoB;AACtB,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,WAAW;AAChB,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,qBAAqB;AAC1B,SAAK,YAAY,aAAa,KAAK,cAAc,KAAK;AAAA,EACxD;AAAA,EACA,cAAc;AACZ,UAAM,cAAc,KAAK,iBAAiB,6BAA6B;AACvE,UAAM,WAAW;AAAA,QACb,oBAAoB,KAAK,YAAY,KAAK,oBAAoB,OAAO,CAAC;AAAA;AAAA,QAEtE,oBAAoB;AAAA;AAAA;AAAA,2CAGe,KAAK,iBAAiB,OAAO;AAAA,0BAC9C,KAAK,iBAAiB,IAAI;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,6BA4BvB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,6BAoBA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAMjB,sBAAsB,KAAK,SAAS,KAAK,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAM3D,WAAO;AAAA,EACT;AACF;AAGA,SAAS,uBAAuB,MAAM;AACpC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAY,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB,IAAI;AACvE,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,MAAI,aAAa;AACjB,MAAI,cAAc,MAAM;AACtB,iBAAa,CAAC,GAAG,CAAC;AAAA,EACpB;AACA,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,YAAY,MAAM,iBAAiB,MAAM,WAAW;AAC5I,QAAM,aAAa;AAAA,IACjB,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI,EAAE;AAAA,IACrE,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,UAAU,SAAS,OAAO,EAAE;AAAA,EAC/D;AACA,QAAM,iBAAiB,SAAS,eAAe;AAC/C,MAAI;AACJ,MAAI,CAAC,kBAAkB,SAAS,WAAW,MAAM,SAAS,UAAU,MAAM,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,KAAK,SAAS,kBAAkB,KAAK,SAAS,mBAAmB,KAAK,SAAS,eAAe,SAAS,aAAa;AACpP,cAAU,IAAI,iCAAiC,SAAS,UAAU,SAAS,cAAc,SAAS,WAAW;AAAA,EAC/G,WAAW,kBAAkB,SAAS,WAAW,KAAK,SAAS,UAAU,KAAK,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,KAAK,SAAS,eAAe,SAAS,eAAe,SAAS,mBAAmB,KAAK,SAAS,kBAAkB,KAAK,SAAS,aAAa,MAAM,GAAG;AACzR,cAAU,IAAI,2BAA2B,QAAQ;AAAA,EACnD,OAAO;AACL,cAAU,IAAI,wBAAwB,QAAQ;AAC9C,eAAW,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,YAAY,EAAE,GAAG,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,WAAW,EAAE,GAAG,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE,GAAG;AAAA,MACzL,MAAM;AAAA,MACN,MAAM,CAAC,SAAS,gBAAgB,SAAS,aAAa;AAAA,IACxD,CAAC;AAAA,EACH;AACA,SAAO,SAAS,iBAAiB,SAAS,CAAC,GAAG,MAAM,GAAG,EAAE,OAAO,UAAU;AAC5E;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,qBAAqB,kBAAkB;AAAA,EACzC,QAAQ,aAAa;AAAA,EACrB,eAAe;AAAA,EACf,iBAAiB;AACnB,CAAC;AACD,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,YAAY,YAAY;AAClC,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,OAAO;AACZ,SAAK,aAAa,CAAC,WAAW,WAAW,WAAW,MAAM;AAC1D,UAAM,CAAC,WAAW,IAAI,qBAAqB,0BAA0B,KAAK,YAAY,CAAC,CAAC,CAAC;AACzF,SAAK,cAAc,YAAY,WAAW,IAAI,CAAC,CAAC,IAAI;AACpD,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,CAAC,GAAG,GAAG,CAAC,CAAC;AAChF,SAAK,aAAa;AAClB,SAAK,YAAY,UAAU;AAAA,EAC7B;AAAA,EACA,cAAc;AACZ,QAAI,WAAW;AACf,QAAI,YAAY;AAChB,QAAI,KAAK,eAAe,SAAS,KAAK,eAAe,OAAO;AAC1D,iBAAW;AAAA;AAAA;AAAA,qDAGoC,KAAK,eAAe,QAAQ,MAAM;AAAA;AAEjF,kBAAY;AAAA,IACd,WAAW,KAAK,eAAe,SAAS,KAAK,eAAe,QAAQ;AAClE,iBAAW;AAAA,IACb,WAAW,KAAK,eAAe,QAAQ;AACrC,iBAAW;AACX,kBAAY;AAAA,IACd;AACA,UAAM,gBAAgB,KAAK,eAAe,SAAS,yEAAyE;AAC5H,UAAM,sBAAsB;AAAA,mDACmB,KAAK,cAAc;AAAA;AAElE,UAAM,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,SAKZ;AAAA;AAAA;AAAA,wBAGe,KAAK,YAAY,WAAW,IAAI,iBAAiB;AAAA;AAAA;AAAA,SAGhE,kCAAkC;AAAA;AAAA;AAAA,2BAGhB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,aAMd;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAWC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAQF;AAAA;AAAA;AAAA;AAIR,WAAO;AAAA,EACT;AACF;AAGA,SAAS,QAAQ,GAAG,MAAM,UAAU,YAAY,UAAU;AACxD,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,YAAY,CAAC;AACnB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,SAAS;AACb,MAAI,gBAAgB,MAAM;AACxB,aAAS,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,MAAM,aAAa,GAAG,SAAS,SAAS,CAAC;AACvF,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAC/D,cAAU,KAAK,MAAM;AAAA,EACvB;AACA,uBAAqB,2BAA2B,YAAY,MAAM,KAAK;AACvE,QAAM,CAAC,gBAAgB,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,IAAI;AACvG,MAAI,cAAc;AAClB,MAAI,UAAU;AACZ,kBAAc,qBAAqB,qBAAqB,gBAAgB,QAAQ;AAAA,EAClF;AACA,MAAI;AACJ,OAAK,eAAe,SAAS,eAAe,WAAW,SAAS,mBAAmB,CAAC,MAAM,CAAC,GAAG;AAC5F,UAAM,QAAQ,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACpD,YAAQ;AAAA,WACD;AACH,cAAM,YAAY,YAAY,OAAO,aAAa,cAAc,WAAW,GAAG,aAAa,EAAE,KAAK;AAClG,cAAM,SAAS,eAAe,aAAa,EAAE,OAAO,SAAS;AAC7D;AAAA,WACG;AACH,cAAM,EAAE,SAAS,UAAU,SAAS,IAAI,aAAa,OAAO,OAAO,OAAO,OAAO,OAAO,IAAI;AAC5F,cAAM,SAAS,eAAe,UAAU,UAAU,OAAO;AACzD;AAAA;AAEA,cAAM,IAAI,MAAM,GAAG,qDAAqD;AAAA;AAAA,EAE9E,OAAO;AACL,UAAM,SAAS,aAAa,cAAc,WAAW;AACrD,UAAM,QAAQ,aAAa,cAAc,OAAO,KAAK;AACrD,UAAM,YAAY,QAAQ;AAC1B,UAAM,aAAa,EAAE,YAAY,QAAQ,QAAQ,WAAW,SAAS,EAAE;AACvE,UAAM,QAAQ,eAAe,SAAS,YAAY,WAAW,EAAE,KAAK;AACpE,UAAM,cAAc;AAAA,MAClB,EAAE,MAAM,SAAS,MAAM,CAAC,MAAM,EAAE;AAAA,IAClC;AACA,UAAM,UAAU,IAAI,eAAe,YAAY,UAAU;AACzD,UAAM,UAAU,SAAS,iBAAiB,SAAS,CAAC,MAAM,GAAG,OAAO,WAAW;AAC/E,cAAU,KAAK,OAAO;AACtB,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,OAAO,EAAE,OAAO,YAAY,GAAG,SAAS,SAAS,CAAC;AAAA,EAC7F;AACA,YAAU,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACzD,SAAO;AACT;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,SAAO,QAAQ,GAAG,MAAM,UAAU,OAAO,QAAQ;AACnD;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,SAAS,IAAI;AACrB,QAAM,UAAU;AAChB,QAAM,EAAE,SAAS,YAAY,OAAO,IAAI,qBAAqB,qBAAqB,UAAU,QAAQ,MAAM;AAC1G,uBAAqB,oBAAoB,QAAQ,QAAQ,QAAQ,OAAO;AACxE,QAAM,EAAE,MAAM,MAAM,IAAI,qBAAqB,qBAAqB,YAAY,MAAM;AACpF,QAAM,SAAS,MAAM;AACrB,MAAI,MAAM;AACV,MAAI,mBAAmB,QAAQ;AAC/B,QAAM,mBAAmB,CAAC;AAC1B,WAAS,KAAK,GAAG,KAAK,QAAQ,EAAE,IAAI;AAClC,eAAW,UAAU,MAAM,KAAK;AAC9B,YAAM,EAAE,oBAAoB,MAAM,YAAY,aAAa,IAAI,qBAAqB,qBAAqB,kBAAkB,OAAO,OAAO;AACzI,UAAI;AACJ,UAAI,qBAAqB,sBAAsB,IAAI,GAAG;AACpD,YAAI,QAAQ;AAAA,MACd,OAAO;AACL,YAAI,WAAW,EAAE,QAAQ,EAAE,GAAG,QAAQ,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AACrF,yBAAiB,KAAK,CAAC;AAAA,MACzB;AACA,YAAM,cAAc,EAAE,MAAM,MAAM;AAClC,eAAS,IAAI,GAAG,IAAI,aAAa,QAAQ,EAAE,GAAG;AAC5C,oBAAY,OAAO,aAAa,IAAI,GAAG,CAAC;AAAA,MAC1C;AACA,UAAI,CAAC,aAAa,YAAY,EAAE,OAAO,WAAW,GAAG;AACnD,YAAI,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAChF,yBAAiB,KAAK,CAAC;AAAA,MACzB;AACA,UAAI,QAAQ,MAAM;AAChB,cAAM;AAAA,MACR,OAAO;AACL,cAAM,mBAAmB,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,IAAI,GAAG,SAAS,SAAS,CAAC;AACxE,yBAAiB,KAAK,GAAG;AAAA,MAC3B;AAAA,IACF;AACA,QAAI,KAAK,SAAS,GAAG;AACnB,UAAI,KAAK,OAAO,GAAG;AACjB,cAAM,KAAK;AAAA,UACT,QAAQ,EAAE,GAAG,IAAI;AAAA,UACjB,SAAS;AAAA,UACT,OAAO;AAAA,YACL,MAAM,KAAK,OAAO,QAAQ,SAAS;AAAA,YACnC,UAAU;AAAA,UACZ;AAAA,QACF,CAAC;AACD,yBAAiB,KAAK,GAAG;AAAA,MAC3B;AACA;AAAA,IACF;AAAA,EACF;AACA,aAAW,cAAc,kBAAkB;AACzC,QAAI,eAAe,KAAK;AACtB;AAAA,IACF;AACA,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,iBAAiB,EAAE,QAAQ,YAAY,IAAI,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,kBAAkB,EAAE,QAAQ,aAAa,OAAO,OAAO,QAAQ,eAAe,cAAc,CAAC;AAC1G,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,iBAAiB;AAAA,EAC1B,QAAQ,YAAY;AAAA,EACpB,eAAe;AAAA,EACf,OAAO;AACT,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,IAAI,IAAI;AAChB,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,YAAY,OAAO,MAAM;AAC/B,QAAM,WAAW,OAAO,MAAM,MAAM;AACpC,MAAI,OAAO;AACX,MAAI,MAAM,GAAG;AACX,iBAAa,OAAO,EAAE,YAAY,MAAM,KAAK,MAAM,iCAAiC,EAAE,YAAY,OAAO,YAAY;AACrH,WAAO,YAAY,MAAM;AAAA,EAC3B;AACA,WAAS,OAAO,MAAM,GAAG,CAAC;AAC1B,SAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC1F;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,iBAAiB,EAAE,QAAQ,YAAY,OAAO,eAAe,cAAc,CAAC;AACzF,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,wBAAwB,MAAM;AAAA,EAChC,YAAY,YAAY;AACtB,SAAK,cAAc,CAAC;AACpB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAStC,WAAO;AAAA,EACT;AACF;AAGA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AAC7C,UAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,UAAM,gBAAgB;AACtB,UAAM,UAAU,IAAI,sBAAsB,OAAO,KAAK;AACtD,UAAM,SAAS,cAAc,iBAAiB,SAAS,CAAC,MAAM,GAAG,OAAO,KAAK;AAC7E,WAAO;AAAA,EACT;AACF;AAGA,IAAI,SAAS,iBAAiB,EAAE,QAAQ,YAAY,OAAO,eAAe,cAAc,CAAC;AACzF,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY,kBAAkB,EAAE,QAAQ,aAAa,SAAS,OAAO,QAAQ,CAAC;AAClF,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,qBAAqB,MAAM;AAAA,EAC7B,YAAY,aAAa,aAAa,cAAc,OAAO;AACzD,SAAK,eAAe;AACpB,SAAK,cAAc,CAAC,CAAC;AACrB,SAAK,gBAAgB,CAAC;AACtB,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,aAAa,GAAG,CAAC,CAAC;AAC9G,SAAK,cAAc;AACnB,SAAK,YAAY,cAAc,KAAK;AAAA,EACtC;AAAA,EACA,cAAc;AACZ,UAAM,cAAc,KAAK,cAAc,4CAA4C;AACnF,UAAM,cAAc,KAAK,cAAc,qBAAqB;AAC5D,WAAO;AAAA,uCAC4B;AAAA,QAC/B,kCAAkC;AAAA;AAAA;AAAA;AAAA,yBAIjB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAOvB;AACF;AAGA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AACA,IAAI;AACJ,IAAI,oBAAoC,oBAAI,IAAI;AAChD,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,MAAI,EAAE,OAAO,IAAI;AACjB,QAAM,EAAE,YAAY,IAAI;AACxB,MAAI,UAAU,MAAM;AAClB,UAAM,IAAI,MAAM,0DAA0D;AAAA,EAC5E;AACA,QAAM,UAAU,OAAO,qBAAqB,eAAe,kBAAkB;AAC7E,QAAM,UAAU,OAAO,qBAAqB,eAAe,kBAAkB;AAC7E,QAAM,WAAW,OAAO,sBAAsB,eAAe,kBAAkB,qBAAqB,OAAO,oBAAoB,eAAe,kBAAkB;AAChK,QAAM,gBAAgB,OAAO,gBAAgB,eAAe,kBAAkB;AAC9E,QAAM,CAAC,OAAO,MAAM,IAAI,UAAU;AAAA,IAChC,OAAO;AAAA,IACP,OAAO;AAAA,EACT,IAAI,CAAC,OAAO,OAAO,OAAO,MAAM;AAChC,QAAM,cAAc,CAAC,QAAQ,OAAO,WAAW;AAC/C,QAAM,cAAc,IAAI,EAAE,QAAQ,gCAAgC,KAAK;AACvE,QAAM,iBAAiB,WAAW;AAClC,MAAI,iBAAiB,YAAY,gBAAgB;AAC/C,QAAI;AACJ,QAAI,aAAa;AACf,YAAM,eAAe;AACrB,UAAI,CAAC,kBAAkB,IAAI,YAAY,KAAK,kBAAkB,IAAI,YAAY,EAAE,SAAS;AACvF,cAAM,4BAA4B,EAAE,QAAQ,aAAa;AACzD,0BAAkB,IAAI,cAAc,SAAS,OAAO,sBAAsB,yBAAyB,CAAC;AAAA,MACtG;AACA,oBAAc;AAAA,QACZ;AAAA,QACA;AAAA,QACA,QAAQ;AAAA,QACR,OAAO;AAAA,QACP,SAAS,kBAAkB,IAAI,YAAY;AAAA,MAC7C;AAAA,IACF,OAAO;AACL,UAAI,gBAAgB;AAClB,YAAI,wBAAwB,MAAM;AAChC,iCAAuB,SAAS,cAAc,QAAQ,EAAE,WAAW,IAAI;AAAA,QACzE;AACA,6BAAqB,OAAO,QAAQ;AACpC,6BAAqB,OAAO,SAAS;AACrC,6BAAqB,UAAU,QAAQ,GAAG,GAAG,OAAO,MAAM;AAC1D,iBAAS,qBAAqB;AAAA,MAChC;AACA,YAAM,QAAQ,gBAAgB,WAAW,gBAAgB,oBAAoB,gBAAgB;AAC7F,YAAM,SAAS;AACf,YAAM,UAAU,SAAS,eAAe,eAAe,YAAY,IAAI,YAAY,IAAI,QAAQ,KAAK;AACpG,eAAS,MAAM,2BAA2B,EAAE,QAAQ,OAAO,GAAG,EAAE,QAAQ,GAAG,CAAC,YAAY,IAAI,YAAY,EAAE,CAAC;AAC3G,oBAAc,EAAE,OAAO,QAAQ,QAAQ,OAAO,QAAQ;AAAA,IACxD;AACA,UAAMZ,QAAO,aAAa,cAAc,WAAW;AACnD,UAAMY,WAAU,aAAa,eAAe,WAAW;AACvD,UAAM,UAAU,IAAI,mBAAmB,aAAa,aAAa,WAAW;AAC5E,UAAM,cAAc;AAAA,MAClB,EAAE,MAAM,UAAU,MAAM,CAACZ,KAAI,EAAE;AAAA,MAC/B,EAAE,MAAM,UAAU,MAAM,CAAC,WAAW,EAAE;AAAA,MACtC,EAAE,MAAM,UAAU,MAAM,CAAC,GAAGY,QAAO,EAAE;AAAA,IACvC;AACA,UAAM,SAAS,SAAS,eAAe,CAAC,QAAQ,KAAK,GAAG,OAAO;AAC/D,UAAM,OAAO,SAAS,UAAU,IAAI,OAAO,MAAM;AACjD,SAAK,eAAe;AACpB,UAAM,SAAS,SAAS,iBAAiB,SAAS,CAAC,MAAM,GAAG,SAAS,WAAW;AAChF,aAAS,YAAY,OAAO,MAAM;AAClC,WAAO;AAAA,EACT;AACA,QAAM,YAAY,OAAO;AACzB,MAAI,aAAa;AACjB,MAAI,eAAe,QAAQ,gBAAgB,GAAG;AAC5C,iBAAa,IAAI,WAAW,OAAO,QAAQ,OAAO,SAAS,WAAW;AACtE,UAAM,aAAa,UAAU;AAC7B,QAAI,IAAI;AACR,aAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,UAAI,KAAK,IAAI,aAAa;AACxB,mBAAW,OAAO,UAAU;AAAA,MAC9B;AAAA,IACF;AAAA,EACF;AACA,QAAM,SAAS,SAAS,eAAe,aAAa,SAAS,IAAI,WAAW,UAAU,CAAC;AACvF,WAAS,YAAY,OAAO,MAAM;AAClC,SAAO;AACT;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,QAAQ,WAAW,eAAe,aAAa,YAAY;AACrE,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,OAAO;AACZ,SAAK,gBAAgB,CAAC,KAAK,QAAQ,UAAU;AAC7C,yBAAqB,2BAA2B,QAAQ,SAAS;AACjE,yBAAqB,2BAA2B,QAAQ,aAAa;AACrE,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,QAAI,eAAe,MAAM;AACvB,2BAAqB,2BAA2B,QAAQ,WAAW;AACnE,WAAK,cAAc,KAAK,QAAQ;AAAA,IAClC;AACA,QAAI,cAAc,MAAM;AACtB,2BAAqB,2BAA2B,QAAQ,UAAU;AAClE,WAAK,cAAc,KAAK,OAAO;AAAA,IACjC;AACA,SAAK,cAAc;AACnB,SAAK,aAAa;AAClB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,QAAI,gBAAgB;AACpB,QAAI,KAAK,eAAe,MAAM;AAC5B,sBAAgB;AAAA,IAClB;AACA,QAAI,eAAe;AACnB,QAAI,KAAK,cAAc,MAAM;AAC3B,qBAAe;AAAA,IACjB;AACA,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAMZ;AAAA,6BACD;AAAA;AAAA;AAAA;AAAA;AAAA;AAMzB,WAAO;AAAA,EACT;AACF;AAGA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,GAAG,OAAOS,SAAQ,QAAQ,MAAM,OAAO,SAAS,IAAI;AAC5D,UAAM,EAAE,gBAAgB,IAAI;AAC5B,UAAM,gBAAgB;AACtB,UAAM,kBAAkB,CAAC,GAAG,OAAO,QAAQ;AAC3C,QAAI,cAAc;AAClB,QAAI,UAAU,MAAM;AAClB,oBAAc,OAAO;AACrB,sBAAgB,KAAK,MAAM;AAAA,IAC7B;AACA,QAAI,aAAa;AACjB,QAAIA,WAAU,MAAM;AAClB,mBAAaA,QAAO;AACpB,sBAAgB,KAAKA,OAAM;AAAA,IAC7B;AACA,UAAM,UAAU,IAAI,kBAAkB,EAAE,OAAO,MAAM,OAAO,SAAS,OAAO,aAAa,UAAU;AACnG,UAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,eAAe,EAAE,CAAC;AACjE,WAAO,cAAc,iBAAiB,SAAS,iBAAiB,EAAE,OAAO,WAAW;AAAA,EACtF;AACF;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAT,UAAS,KAAK,MAAM,YAAY,WAAW,iBAAiB,YAAY,aAAa,eAAe,IAAI;AAChH,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,OAAO,WAAW;AAC5I,SAAO,WAAW;AAAA,IAChB;AAAA,IACA;AAAA,IACA;AAAA,IACA,SAAS;AAAA,IACT;AAAA,IACA;AAAA,IACA;AAAA,IACA,YAAY;AAAA,EACd,CAAC;AACH;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,sBAAsB,MAAM;AACnC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,WAAW,iBAAiB,YAAY,aAAa,eAAe,IAAI;AACpG,MAAI,aAAa;AACjB,MAAI,cAAc,MAAM;AACtB,iBAAa,CAAC,GAAG,CAAC;AAAA,EACpB;AACA,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,UAAU,GAAG,MAAM,gFAAgFA,2BAA0B,aAAa;AAC3N,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,YAAY,MAAM,iBAAiB,IAAI;AAC/H,QAAM,gBAAgB,CAAC,GAAG,MAAM;AAChC,QAAM,UAAU,QAAQ;AACxB,QAAM,4BAA4B,0BAA0B;AAC5D,MAAI,SAAS;AACX,kBAAc,KAAK,IAAI;AAAA,EACzB;AACA,MAAI,2BAA2B;AAC7B,kBAAc,KAAK,sBAAsB;AAAA,EAC3C;AACA,QAAM,aAAa;AAAA,IACjB,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI,EAAE;AAAA,IACrE,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,UAAU,SAAS,OAAO,EAAE;AAAA,EAC/D;AACA,MAAI;AACJ,MAAI,SAAS,WAAW,KAAK,SAAS,UAAU,KAAK,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,KAAK,SAAS,eAAe,SAAS,eAAe,SAAS,mBAAmB,KAAK,SAAS,kBAAkB,KAAK,SAAS,aAAa,MAAM,GAAG;AAChQ,cAAU,IAAI,2BAA2B,UAAU,SAAS,aAAa,yBAAyB;AAAA,EACpG,OAAO;AACL,cAAU,IAAI,wBAAwB,UAAU,SAAS,aAAa,yBAAyB;AAC/F,eAAW,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,YAAY,EAAE,GAAG,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,WAAW,EAAE,GAAG,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE,GAAG;AAAA,MACzL,MAAM;AAAA,MACN,MAAM,CAAC,SAAS,gBAAgB,SAAS,aAAa;AAAA,IACxD,CAAC;AAAA,EACH;AACA,MAAI,gBAAgB,aAAa;AAC/B,eAAW,KAAK,EAAE,MAAM,WAAW,MAAM,CAAC,cAAc,EAAE,CAAC;AAC3D,YAAQ,YAAY;AAAA,EACtB;AACA,QAAM,SAAS,SAAS,iBAAiB,SAAS,eAAe,WAAW,UAAU;AACtF,SAAO;AACT;AACA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,UAAU,OAAO;AAC3B,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY,YAAY;AAC7B,SAAK,WAAW;AAChB,SAAK,WAAW,6BAA6B,mBAAmB,QAAQ;AAAA,EAC1E;AAAA,EACA,cAAc;AACZ,QAAI;AACJ,QAAI,KAAK,WAAW,GAAG;AACrB,qBAAe;AAAA,IACjB,OAAO;AACL,qBAAe;AAAA,IACjB;AACA,UAAM,WAAW;AAAA,UACX,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAMd;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAQ1B,WAAO;AAAA,EACT;AACF;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,QAAQ,QAAQ,IAAI;AAC5B,QAAM,eAAe,QAAQ;AAC7B,QAAM,YAAY,aAAa,aAAa,SAAS;AACrD,QAAM,aAAa,aAAa,cAAc,OAAO,KAAK;AAC1D,QAAM,CAAC,aAAa,WAAW,WAAWA,QAAO,IAAI,qBAAqB,mBAAmB,QAAQ,OAAO;AAC5G,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,WAAW,SAAS,EAAE,EAAE,CAAC;AACvH,QAAM,WAAW,SAAS;AAAA,IACxB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,aAAa,cAAc,OAAO,KAAK,IAAI,WAAW,SAAS,EAAE;AAAA,EACpF,CAAC;AACD,MAAI,SAAS,mBAAmB,CAAC,QAAQ,OAAO,CAAC,KAAK,OAAO,UAAU,UAAU;AAC/E,UAAM,cAAc,SAAS,SAAS,QAAQ,MAAM;AACpD,UAAM,YAAY,SAAS,WAAW,MAAM;AAC5C,UAAM,WAAW,iBAAiB,aAAa,WAAW,OAAO,OAAO,WAAW,WAAW,WAAWA,UAAS,OAAO,OAAO,UAAU;AAC1I,WAAO,SAAS,eAAe,aAAa,OAAO,OAAO,SAAS,MAAM;AAAA,EAC3E;AACA,QAAM,UAAU,IAAI,iBAAiB,WAAW,CAAC,WAAW,SAAS,CAAC;AACtE,QAAM,cAAc,CAAC,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE,GAAG,EAAE,MAAM,SAAS,MAAMA,SAAQ,CAAC;AAC3F,QAAM,MAAM,SAAS,iBAAiB,SAAS,CAAC,UAAU,cAAc,GAAG,SAAS,OAAO,WAAW;AACtG,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAClG,WAAS,YAAY,eAAe,MAAM;AAC1C,WAAS,YAAY,SAAS,MAAM;AACpC,WAAS,YAAY,IAAI,MAAM;AAC/B,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,QAAQ,aAAa;AAC/B,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,OAAO,MAAM;AAChC,SAAK,SAAS;AACd,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,eAAe,iBAAiB,KAAK,MAAM;AACjD,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA,oDAKU;AAAA;AAAA;AAAA;AAIhD,WAAO;AAAA,EACT;AACF;AACA,SAAS,iBAAiB,QAAQ;AAChC,QAAM,gBAAgB,CAAC,WAAW,WAAW,WAAW,SAAS;AACjE,QAAM,eAAe,CAAC;AACtB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,QAAI,OAAO,GAAG;AACZ,mBAAa,KAAK,QAAQ;AAAA,IAC5B,OAAO;AACL,mBAAa,KAAK,GAAG,cAAc,KAAK;AAAA,IAC1C;AAAA,EACF;AACA,SAAO,aAAa,KAAK;AAC3B;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAM,UAAU,IAAI;AAC5B,QAAM,aAAa,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AAC9D,QAAM,YAAY,qBAAqB,aAAa,yBAAyB,GAAG,SAAS,YAAY,SAAS;AAC9G,QAAM,cAAc,aAAa,cAAc,QAAQ,KAAK;AAC5D,QAAM,YAAY,CAAC;AACnB,QAAM,WAAW,SAAS;AAAA,IACxB,QAAQ,EAAE,EAAE;AAAA,IACZ,SAAS;AAAA,IACT,OAAO;AAAA,MACL,OAAO;AAAA,QACL,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,MACZ;AAAA,IACF;AAAA,EACF,CAAC;AACD,QAAM,eAAe,SAAS;AAAA,IAC5B,QAAQ,EAAE,GAAG,QAAQ;AAAA,IACrB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,UAAU,WAAW,cAAc,UAAU,SAAS,EAAE;AAAA,EAC3E,CAAC;AACD,YAAU,KAAK,QAAQ;AACvB,YAAU,KAAK,YAAY;AAC3B,QAAM,qBAAqB;AAAA,IACzB,UAAU;AAAA,IACV,UAAU;AAAA,IACV,cAAc,UAAU;AAAA,IACxB,UAAU;AAAA,EACZ;AACA,MAAI,SAAS,mBAAmB,CAAC,GAAG,OAAO,CAAC,GAAG;AAC7C,UAAM,oBAAoB,SAAS,UAAU,IAAI,aAAa,MAAM;AACpE,UAAM,gBAAgB,kBAAkB;AACxC,UAAM,aAAa,OAAO,aAAa,OAAO,aAAa,OAAO,aAAa;AAC/E,UAAM,cAAc,SAAS,UAAU,IAAI,SAAS,MAAM;AAC1D,UAAM,UAAU,YAAY;AAC5B,UAAM,OAAO,OAAO,SAAS,OAAO,SAAS,OAAO,OAAO;AAC3D,UAAM,SAAS,iBAAiB,MAAM,YAAY,kBAAkB;AACpE,cAAU,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACzD,WAAO,SAAS,eAAe,UAAU,aAAa,OAAO,OAAO,OAAO,MAAM;AAAA,EACnF;AACA,QAAM,UAAU,IAAI,eAAe,SAAS,OAAO,kBAAkB;AACrE,QAAM,MAAM,SAAS,iBAAiB,SAAS,CAAC,UAAU,YAAY,GAAG,SAAS,KAAK;AACvF,YAAU,KAAK,GAAG;AAClB,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,UAAU,YAAY,EAAE,CAAC;AAC5G,YAAU,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACzD,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW,kBAAkB;AAAA,EAC/B,QAAQ,aAAa;AAAA,EACrB,eAAe;AAAA,EACf,OAAO;AACT,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,kBAAkB;AAAA,EACpC,QAAQ,aAAa;AAAA,EACrB,OAAO;AAAA,EACP,eAAe;AACjB,CAAC;AACD,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAAU,OAAM,IAAI;AAClB,QAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAACA,MAAK,EAAE,CAAC;AACvD,QAAM,UAAU,IAAI,gBAAgB,EAAE,OAAO,YAAY,SAAS;AAClE,UAAQ,WAAW;AACnB,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,WAAW,WAAW;AACvE;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,kBAAkB,EAAE,QAAQ,aAAa,MAAM,OAAO,QAAQ,eAAe,aAAa,CAAC;AACvG,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa,kBAAkB;AAAA,EACjC,QAAQ,aAAa;AAAA,EACrB,OAAO;AAAA,EACP,eAAe;AACjB,CAAC;AACD,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,iBAAiB,EAAE,QAAQ,YAAY,KAAK,eAAe,YAAY,CAAC;AACnF,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,kBAAkB,EAAE,QAAQ,aAAa,aAAa,OAAO,OAAO,CAAC;AACvF,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,iBAAiB,EAAE,QAAQ,YAAY,YAAY,CAAC;AACtE,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,kBAAkB,SAAS,IAAI;AACvC,SAAO,QAAQ,GAAG,kBAAkB,UAAU,OAAO,QAAQ;AAC/D;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW,kBAAkB;AAAA,EAC/B,QAAQ,aAAa;AAAA,EACrB,eAAe;AACjB,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAAV,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY;AAClB,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,MAAI;AACJ,QAAM,aAAa,CAAC;AACpB,MAAI,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,GAAG;AAC7D,QAAI,aAAa,YAAY,SAAS,SAAS,SAAS,QAAQ,GAAG;AACjE,aAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,IACvD;AACA,cAAU,IAAI,mCAAmC,QAAQ;AACzD,eAAW,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE,CAAC;AAAA,EACxF,OAAO;AACL,cAAU,IAAI,eAAe,UAAU,KAAK;AAC5C,eAAW,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE,GAAG,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI,EAAE,GAAG;AAAA,MAC9J,MAAM;AAAA,MACN,MAAM,CAAC,SAAS,gBAAgB,SAAS,aAAa;AAAA,IACxD,GAAG,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,UAAU,SAAS,OAAO,EAAE,GAAG;AAAA,MACjE,MAAM;AAAA,MACN,MAAM,CAAC,SAAS,uBAAuB,SAAS,oBAAoB;AAAA,IACtE,CAAC;AAAA,EACH;AACA,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,UAAU;AACpE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,UAAU,KAAK,IAAI;AAC3B,SAAO,QAAQ,GAAG,MAAM,UAAU,QAAQ,QAAQ;AACpD;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,SAAO,QAAQ,GAAG,MAAM,UAAU,OAAO,QAAQ;AACnD;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW,kBAAkB;AAAA,EAC/B,QAAQ,aAAa;AAAA,EACrB,eAAe;AACjB,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,QAAQ,UAAU,MAAM;AAClC,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,MAAM,GAAG,EAAE;AACtE,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,SAAS;AACd,aAAS,IAAI,CAAC,GAAG,OAAO;AACtB,WAAK,YAAY,OAAO;AAAA,IAC1B,CAAC;AACD,SAAK,SAAS,SAAS,YAAY,IAAI;AACvC,SAAK,YAAY,aAAa;AAAA,EAChC;AAAA,EACA,cAAc;AACZ,UAAM,OAAO,KAAK,OAAO;AACzB,UAAM,QAAQ,KAAK,OAAO,IAAI,CAAC,GAAG,OAAO,eAAe,OAAO,EAAE,KAAK,GAAG;AACzE,UAAM,MAAM,KAAK,OAAO,IAAI,CAAC,GAAG,OAAO,eAAe,0BAA0B,OAAO,IAAI,IAAI,QAAQ,IAAI,EAAE,KAAK,GAAG;AACrH,UAAM,cAAc,SAAS,IAAI,UAAU;AAC3C,UAAM,YAAY,SAAS,IAAI,QAAQ;AACvC,UAAM,aAAa,SAAS,IAAI,SAAS;AACzC,UAAM,QAAQ,mBAAmB,IAAI;AACrC,UAAM,iBAAiB,OAAO,IAAI,CAAC,aAAa,aAAa,aAAa,WAAW,EAAE,MAAM,GAAG,IAAI,IAAI;AACxG,WAAO;AAAA,QACH,kCAAkC;AAAA;AAAA,wBAElB,SAAS;AAAA,sBACX,SAAS;AAAA;AAAA,gCAEC;AAAA,kBACd,gBAAgB;AAAA,gBAClB,gBAAgB,qBAAqB,gBAAgB,KAAK;AAAA,wBAClD,iBAAiB;AAAA,gBACzB,iBAAiB,wBAAwB,gBAAgB,KAAK;AAAA;AAAA;AAAA;AAAA,yCAIrC;AAAA;AAAA;AAAA;AAAA,EAIvC;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,EAAE,UAAU,KAAK,IAAI;AAC3B,UAAM,gBAAgB;AACtB,UAAM,cAAc,SAAS,IAAI,CAAC,OAAO;AACvC,aAAO,EAAE,MAAM,SAAS,MAAM,CAAC,GAAG,IAAI,GAAG,EAAE,EAAE;AAAA,IAC/C,CAAC;AACD,UAAM,UAAU,IAAI,kBAAkB,EAAE,OAAO,UAAU,IAAI;AAC7D,UAAM,SAAS,cAAc,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,WAAW;AAChF,WAAO;AAAA,EACT;AACF;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,GAAG;AACpC,UAAM,QAAQ,SAAS,UAAU,IAAI,EAAE,MAAM;AAC7C,UAAM,CAAC,WAAW,QAAQ,IAAI,YAAY,MAAM,QAAQ,EAAE,OAAO,EAAE,KAAK;AACxE,WAAO,SAAS,eAAe,UAAU,EAAE,OAAO,SAAS;AAAA,EAC7D;AACA,QAAM,UAAU,IAAI,gBAAgB,EAAE,OAAO,YAAY,GAAG;AAC5D,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACxD;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,UAAQ,KAAK,gGAAgG;AAC7G,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,eAAe,IAAI;AACxD,QAAM,YAAY,SAAS,SAAS,MAAM,MAAM;AAChD,QAAM,aAAa,SAAS,SAAS,OAAO,MAAM;AAClD,QAAM,EAAE,gBAAgB,IAAI,qBAAqB,wBAAwB,WAAW,YAAY,eAAe,cAAc,cAAc;AAC3I,SAAO,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AACnG;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,UAAQ,KAAK,gGAAgG;AAC7G,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,gBAAgB,aAAa,IAAI;AACtE,QAAM,YAAY,SAAS,SAAS,MAAM,MAAM;AAChD,QAAM,aAAa,SAAS,SAAS,OAAO,MAAM;AAClD,QAAM,mBAAmB;AACzB,QAAM,kBAAkB;AACxB,QAAM,oBAAoB;AAC1B,QAAM,kBAAkB;AACxB,QAAM,EAAE,iBAAiB,eAAe,IAAI,qBAAqB,wBAAwB,WAAW,YAAY,kBAAkB,iBAAiB,mBAAmB,eAAe;AACrL,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AAAA,IAC1F,SAAS,eAAe,CAAC,eAAe,MAAM,GAAG,WAAW,IAAI,aAAa,cAAc,CAAC;AAAA,EAC9F;AACF;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,EAAE,UAAU,aAAa;AAC3B,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,IAAI,MAAM,GAAG,GAAG,SAAS,SAAS,CAAC;AAC7E,aAAS,YAAY,SAAS,MAAM;AACpC,aAAS,YAAY,GAAG,MAAM;AAC9B,aAAS,YAAY,SAAS,MAAM;AACpC,aAAS,YAAY,GAAG,MAAM;AAC9B,WAAO;AAAA,EACT,OAAO;AACL,WAAO,MAAM;AAAA,MACX,OAAO;AAAA,QACL,OAAO,EAAE;AAAA,QACT,OAAO,EAAE;AAAA,QACT,OAAO,EAAE,UAAU,WAAW,KAAK;AAAA,MACrC;AAAA,MACA,SAAS;AAAA,IACX,CAAC;AAAA,EACH;AACF;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,EAAE,UAAU,UAAU;AACxB,UAAM,IAAI,MAAM,8CAA8C;AAAA,EAChE,WAAW,EAAE,UAAU,aAAa;AAClC,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,UAAU,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACnE,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,IAAI,MAAM,GAAG,GAAG,SAAS,SAAS,CAAC;AAC7E,aAAS,YAAY,SAAS,MAAM;AACpC,aAAS,YAAY,GAAG,MAAM;AAC9B,aAAS,YAAY,SAAS,MAAM;AACpC,aAAS,YAAY,GAAG,MAAM;AAC9B,WAAO;AAAA,EACT,OAAO;AACL,WAAO,MAAM,EAAE,OAAO,EAAE,OAAO,EAAE,OAAO,OAAO,EAAE,OAAO,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACzF;AACF;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,YAAY,EAAE,QAAQ,EAAE,OAAO,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAAA,EAC9F;AACA,QAAM,QAAQ,OAAO,GAAG;AACxB,QAAM,QAAQ,OAAO,GAAG;AACxB,SAAO,QAAQ,CAAC,OAAO;AACrB,iBAAa,kBAAkB,OAAO,GAAG,OAAO,uDAAuD;AACvG,iBAAa,OAAO,UAAU,GAAG,OAAO,MAAM,uDAAuD;AAAA,EACvG,CAAC;AACD,QAAM,0BAA0B,CAAC;AACjC,QAAM,kBAAkB,OAAO,IAAI,CAAC,OAAO;AACzC,UAAM,YAAY,YAAY,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAChG,4BAAwB,KAAK,SAAS;AACtC,WAAO;AAAA,EACT,CAAC;AACD,QAAM,SAAS,QAAQ,EAAE,QAAQ,iBAAiB,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AACtF,0BAAwB,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACvE,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,QAAQ,UAAU;AAC5B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,MAAM,GAAG,EAAE;AACtE,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,aAAS,IAAI,CAAC,GAAG,OAAO;AACtB,WAAK,YAAY,OAAO;AAAA,IAC1B,CAAC;AACD,SAAK,SAAS;AACd,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,OAAO,KAAK,OAAO;AACzB,UAAM,OAAO,mBAAmB,IAAI;AACpC,UAAM,QAAQ,KAAK,OAAO,IAAI,CAAC,GAAG,OAAO,eAAe,OAAO,EAAE,KAAK,GAAG;AACzE,UAAM,MAAM,KAAK,OAAO,IAAI,CAAC,GAAG,OAAO,eAAe,0BAA0B,OAAO,IAAI,IAAI,QAAQ,IAAI,EAAE,KAAK,GAAG;AACrH,UAAM,aAAa,OAAO,IAAI,GAAG,QAAQ,WAAW,GAAG;AACvD,UAAM,WAAW,OAAO,IAAI,GAAG,QAAQ,SAAS,GAAG;AACnD,UAAM,mBAAmB,OAAO,IAAI,sBAAsB;AAC1D,UAAM,oBAAoB,OAAO,IAAI,qBAAqB;AAC1D,UAAM,iBAAiB,OAAO,IAAI,CAAC,aAAa,aAAa,aAAa,WAAW,EAAE,MAAM,GAAG,IAAI,IAAI;AACxG,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA,wBAElB;AAAA,sBACF;AAAA;AAAA;AAAA,gBAGN,uBAAuB;AAAA;AAAA;AAAA;AAAA,2CAII;AAAA;AAAA;AAAA;AAAA;AAKvC,WAAO;AAAA,EACT;AACF;AAGA,IAAI,SAAS,CAAC,SAAS;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,UAAU,cAAc,IAAI;AACpC,MAAI,SAAS,MAAM,CAAC,OAAO,aAAa,YAAY,IAAI,CAAC,GAAG,CAAC,CAAC,CAAC,GAAG;AAChE,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD;AACA,MAAI,aAAa,cAAc,EAAE,KAAK,MAAM,GAAG;AAC7C,UAAM,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,EAAE,MAAM,MAAM,GAAG,EAAE;AACxE,WAAO,MAAM;AAAA,MACX,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,aAAa,OAAO,eAAe,OAAO,EAAE,MAAM;AAAA,IACpE,CAAC;AAAA,EACH;AACA,QAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,aAAa,EAAE,CAAC;AAC/D,WAAS,IAAI,CAAC,OAAO,YAAY,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,GAAG,IAAI,GAAG,EAAE,EAAE,CAAC,CAAC;AAC9E,QAAM,UAAU,IAAI,YAAY,EAAE,OAAO,QAAQ;AACjD,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,WAAW;AACrE;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,kBAAkB;AAAA,EAC3B,QAAQ,aAAa;AACvB,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,GAAG,OAAAU,OAAM,IAAI;AACrB,QAAM,UAAU,IAAI,iBAAiB,aAAa,OAAO,EAAE,OAAOA,OAAM,KAAK;AAC7E,SAAO,SAAS,iBAAiB,SAAS,CAAC,GAAGA,MAAK,GAAG,SAAS;AACjE;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,SAAO,QAAQ,GAAG,MAAM,UAAU,QAAQ,QAAQ;AACpD;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,CAAC,SAAS;AACrB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,MAAM,OAAO,MAAM,IAAI;AAC5C,QAAM,SAAS,cAAc,OAAO,MAAM,OAAO,KAAK;AACtD,SAAO,SAAS,eAAe,CAAC,OAAO,MAAM,GAAG,OAAO,MAAM;AAC/D;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW,kBAAkB,EAAE,QAAQ,aAAa,IAAI,CAAC;AAC7D,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,iBAAiB,EAAE,QAAQ,YAAY,KAAK,CAAC;AACzD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,iBAAiB,EAAE,QAAQ,YAAY,MAAM,CAAC;AAC3D,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,YAAY,WAAW,UAAU;AAC3C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,CAAC,WAAW,IAAI,WAAW,UAAU,WAAW,EAAE;AACrE,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AA2CtC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,MAAAtB,OAAM,iBAAiB,IAAI;AACjD,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,eAAe,gBAAgB,YAAY,IAAI,IAAI;AACzD,QAAM,cAAc,gBAAgB,WAAW,IAAI,IAAI;AACvD,QAAM,wBAAwB,mBAAmB,MAAM;AACvD,QAAM,cAAc;AAAA,IAClB,EAAE,MAAM,WAAW,MAAM,CAAC,cAAc,WAAW,EAAE;AAAA,IACrD,EAAE,MAAM,WAAW,MAAM,CAAC,qBAAqB,EAAE;AAAA,EACnD;AACA,QAAM,UAAU,IAAI,uBAAuB,OAAO,OAAO,WAAW,QAAQ;AAC5E,SAAO,SAAS,iBAAiB,SAAS,CAAC,MAAM,GAAG,WAAW,WAAW;AAC5E;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gCAAgC,MAAM;AAAA,EACxC,YAAY,YAAY,WAAW,UAAU,kBAAkB;AAC7D,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,CAAC,WAAW,IAAI,WAAW,UAAU,WAAW,EAAE;AACrE,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,mBAAmB;AACxB,SAAK,YAAY,iBAAiB;AAAA,EACpC;AAAA,EACA,cAAc;AACZ,QAAI;AACJ,QAAI,KAAK,kBAAkB;AACzB,0BAAoB;AAAA,IACtB,OAAO;AACL,0BAAoB;AAAA,IACtB;AACA,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oCAmBN;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAYhC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,uBAAuB,MAAM;AACpC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,kBAAkB,MAAAA,MAAK,IAAI;AACjD,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,eAAe,gBAAgB,YAAY,IAAI,IAAI;AACzD,QAAM,cAAc,gBAAgB,WAAW,IAAI,IAAI;AACvD,QAAM,YAAY,eAAe,MAAM;AACvC,QAAM,cAAc;AAAA,IAClB,EAAE,MAAM,WAAW,MAAM,CAAC,cAAc,WAAW,EAAE;AAAA,IACrD,EAAE,MAAM,WAAW,MAAM,CAAC,SAAS,EAAE;AAAA,EACvC;AACA,QAAM,UAAU,IAAI,8BAA8B,OAAO,OAAO,WAAW,UAAU,gBAAgB;AACrG,SAAO,SAAS,iBAAiB,SAAS,CAAC,MAAM,GAAG,OAAO,OAAO,WAAW;AAC/E;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,YAAY,WAAW;AACjC,SAAK,cAAc,CAAC;AACpB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,WAAW;AAAA;AAEhB,SAAK,YAAY;AACjB,SAAK,cAAc;AACnB,QAAI,OAAO,cAAc,UAAU;AACjC,WAAK,YAAY;AACjB,WAAK,cAAc;AACnB,WAAK,aAAa;AAAA,IACpB,OAAO;AACL,WAAK,YAAY;AACjB,WAAK,cAAc;AACnB,WAAK,aAAa;AAAA,IACpB;AAAA,EACF;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,UACX,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAY9B,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AASf,WAAO;AAAA,EACT;AACF;AAGA,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,UAAM,EAAE,SAAS,WAAW,OAAO,IAAI;AACvC,UAAM,gBAAgB;AACtB,UAAM,UAAU,IAAI,eAAe,OAAO,OAAO,SAAS;AAC1D,UAAM,CAAC,SAAS,OAAO,IAAI,qBAAqB,eAAe,QAAQ,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE;AACvG,UAAM,cAAc;AAAA,MAClB,EAAE,MAAM,WAAW,MAAM,CAAC,OAAO,EAAE;AAAA,MACnC,EAAE,MAAM,WAAW,MAAM,CAAC,OAAO,EAAE;AAAA,MACnC,EAAE,MAAM,WAAW,MAAM,CAAC,KAAK,IAAI,OAAO,CAAC,EAAE;AAAA,MAC7C,EAAE,MAAM,WAAW,MAAM,CAAC,KAAK,IAAI,OAAO,CAAC,EAAE;AAAA,IAC/C;AACA,QAAI,OAAO,cAAc,UAAU;AACjC,kBAAY,KAAK,EAAE,MAAM,WAAW,MAAM,CAAC,OAAO,WAAW,UAAU,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC;AAAA,IACvF,OAAO;AACL,kBAAY,KAAK,EAAE,MAAM,WAAW,MAAM,UAAU,CAAC;AAAA,IACvD;AACA,UAAM,SAAS,cAAc,iBAAiB,SAAS,CAAC,MAAM,GAAG,OAAO,OAAO,WAAW;AAC1F,WAAO;AAAA,EACT;AACF;AAGA,IAAI,SAAS,iBAAiB,EAAE,QAAQ,YAAY,OAAO,eAAe,cAAc,CAAC;AACzF,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,0BAA0B,MAAM;AAAA,EAClC,YAAY,eAAe,UAAU,aAAa,aAAaY,UAAS,OAAO,aAAa,iBAAiB,MAAM;AACjH,SAAK,gBAAgB,CAAC,WAAW,SAAS;AAC1C,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,SAAS;AACd,SAAK,cAAc;AACnB,SAAK,OAAO;AACZ,SAAK,iBAAiB;AACtB,SAAK,iBAAiB,mBAAmB,aAAa;AACtD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,eAAe,KAAK,aAAa;AACtF,SAAK,yBAAyB,WAAW;AACzC,SAAK,YAAY,WAAW,eAAe,eAAe,KAAK,0BAA0B,eAAe;AACxG,UAAM,cAAc,mBAAmBA,SAAQ,MAAM;AACrD,SAAK,WAAW,4BAA4B;AAC5C,SAAK,cAAc;AACnB,SAAK,cAAc;AAAA,EACrB;AAAA,EACA,cAAc;AACZ,QAAI,gBAAgB;AACpB,QAAI,KAAK,gBAAgB,GAAG;AAC1B,sBAAgB;AAAA,IAClB,WAAW,KAAK,gBAAgB,GAAG;AACjC,sBAAgB;AAAA,IAClB;AACA,UAAM,iBAAiB,cAAc;AACrC,UAAM,eAAe,KAAK,yBAAyB,wBAAwB;AAC3E,QAAI,kBAAkB;AACtB,QAAI,gCAAgC;AACpC,QAAI,KAAK,eAAe,EAAE,WAAW,GAAG;AACtC,wBAAkB;AAClB,sCAAgC;AAAA;AAAA;AAAA;AAAA;AAAA,IAKlC,WAAW,KAAK,eAAe,EAAE,WAAW,GAAG;AAC7C,wBAAkB;AAClB,sCAAgC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAYlC;AACA,UAAM,gBAAgB,MAAM,KAAK,EAAE,QAAQ,KAAK,YAAY,GAAG,CAAC,GAAG,QAAQ,UAAU,MAAM;AAC3F,UAAM,iBAAiB,cAAc,cAAc,KAAK,IAAI;AAC5D,UAAM,YAAY,CAAC,KAAK,QAAQ;AAC9B,UAAI,mBAAmB,aAAa,qBAAqB;AACzD,UAAI,KAAK,SAAS,WAAW;AAC3B,2BAAmB;AAAA;AAAA;AAAA,yCAGc;AAAA;AAAA,qDAEY;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,2CAMV;AAAA;AAAA;AAAA;AAAA;AAAA,MAKrC;AACA,YAAM,qBAAqB,eAAe,qBAAqB;AAC/D,aAAO,KAAK,iBAAiB,mBAAmB;AAAA,IAClD;AACA,UAAM,WAAW;AAAA,MACf;AAAA;AAAA,QAEE,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0CAMA;AAAA,8DACoB;AAAA;AAAA;AAAA,gBAG9C,eAAe,KAAK,MAAM,KAAK,KAAK;AAAA,qDACC;AAAA;AAAA,YAEzC,UAAU,sBAAsB,aAAa;AAAA;AAAA;AAGrD,WAAO;AAAA,EACT;AACF;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,SAAS,QAAQ,IAAI;AAC7B,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,EAAE,WAAW,YAAY,WAAW,SAAAA,UAAS,YAAAQ,YAAW,IAAI,qBAAqB,gBAAgB,SAAS,SAAS,KAAK;AAC9H,QAAM,eAAe,CAACA,cAAa,WAAW,SAAS;AACvD,MAAIA,gBAAe,GAAG;AACpB,WAAO,SAAS,eAAe,OAAO,QAAQ,KAAK;AAAA,EACrD;AACA,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,YAAY,SAAS,EAAE,EAAE,CAAC;AACxH,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,YAAY,SAAS,EAAE,EAAE,CAAC;AAClH,QAAM,OAAO,SAAS;AACtB,QAAM,SAAS,MAAM,EAAE,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,OAAO,GAAG,OAAO,KAAK,EAAE,CAAC;AACjG,QAAMpB,QAAO,aAAa,cAAc,SAAS,KAAK;AACtD,QAAM,cAAc;AAAA,IAClB,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE;AAAA,IACnC,EAAE,MAAM,SAAS,MAAMY,SAAQ;AAAA,IAC/B,EAAE,MAAM,SAAS,MAAM,CAACZ,KAAI,EAAE;AAAA,EAChC;AACA,QAAM,UAAU,IAAI,wBAAwB,SAAS,OAAO,WAAW,eAAe,MAAM,QAAQ,SAAS,MAAM,QAAQY,UAAS,cAAc,IAAI;AACtJ,QAAM,MAAM,SAAS,iBAAiB,SAAS,CAAC,UAAU,cAAc,GAAG,MAAM,aAAa,MAAM;AACpG,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AACrF,WAAS,YAAY,eAAe,MAAM;AAC1C,WAAS,YAAY,SAAS,MAAM;AACpC,WAAS,YAAY,IAAI,MAAM;AAC/B,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,OAAO,OAAO,MAAM;AAC9B,SAAK,gBAAgB,CAAC,KAAK,KAAK,GAAG;AACnC,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,QAAQ;AACb,SAAK,OAAO;AACZ,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,QAAI;AACJ,QAAI;AACJ,QAAI,KAAK,OAAO,GAAG;AACjB,YAAM,MAAM,kBAAkB,KAAK,2BAA2B;AAAA,IAChE;AACA,QAAI,KAAK,SAAS,GAAG;AACnB,iBAAW;AACX,gBAAU;AAAA,IACZ,OAAO;AACL,YAAM,gBAAgB,CAAC,WAAW,WAAW,WAAW,SAAS;AACjE,YAAM,aAAa,CAAC;AACpB,YAAM,cAAc,CAAC;AACrB,eAAS,KAAK,GAAG,KAAK,KAAK,YAAY,QAAQ,MAAM;AACnD,oBAAY,KAAK,GAAG,cAAc,KAAK;AACvC,YAAI,KAAK,KAAK,OAAO;AACnB,qBAAW,KAAK,GAAG,cAAc,KAAK;AAAA,QACxC;AAAA,MACF;AACA,gBAAU,WAAW,KAAK;AAC1B,iBAAW,YAAY,KAAK;AAAA,IAC9B;AACA,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA,4BAGd;AAAA;AAAA,2CAEe;AAAA;AAAA,2CAEA;AAAA;AAAA;AAAA;AAAA;AAKvC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,WAAW,GAAG,IAAI,GAAG,GAAG,IAAI;AACpC,QAAM,UAAU,IAAI,eAAe,UAAU,MAAM,QAAQ,GAAG,OAAO,GAAG,MAAM,MAAM;AACpF,SAAO,SAAS,iBAAiB,SAAS,CAAC,WAAW,IAAI,EAAE,GAAG,WAAW,GAAG,OAAO,GAAG,KAAK,CAAC;AAC/F;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW,iBAAiB,EAAE,QAAQ,YAAY,QAAQ,CAAC;AAC/D,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,iBAAiB,EAAE,QAAQ,YAAY,IAAI,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,iBAAiB,EAAE,QAAQ,YAAY,KAAK,CAAC;AACzD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,kBAAkB,EAAE,QAAQ,aAAa,KAAK,eAAe,aAAa,iBAAiB,KAAK,CAAC;AAC5G,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,IAAI,IAAI;AAChB,QAAM,OAAO,aAAa,eAAe,CAAC,GAAG,GAAG,OAAO,KAAK;AAC5D,QAAM,WAAW,KAAK;AAAA,IACpB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,kBAAkB,MAAM,UAAU,MAAM;AAAA,EACnD,CAAC;AACD,QAAM,gBAAgB,qBAAqB,qBAAqB,SAAS,OAAO,IAAI;AACpF,QAAM,oBAAoB,SAAS,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAClH,QAAM,IAAI,KAAK,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,kBAAkB,GAAG,SAAS,SAAS,CAAC;AACjF,QAAM,IAAI,KAAK,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,SAAS,CAAC;AACtD,QAAM,SAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,MAAM,UAAU,MAAM,EAAE,CAAC;AACnG,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAC7G,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,eAAe,GAAG,SAAS,SAAS,CAAC;AAC/E,WAAS,YAAY,SAAS,MAAM;AACpC,WAAS,YAAY,kBAAkB,MAAM;AAC7C,WAAS,YAAY,EAAE,MAAM;AAC7B,WAAS,YAAY,EAAE,MAAM;AAC7B,WAAS,YAAY,OAAO,MAAM;AAClC,WAAS,YAAY,eAAe,MAAM;AAC1C,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kBAAkB,CAAC,SAAS;AAC9B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAS,IAAI;AACjC,eAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,uEAAuE;AACtH,QAAM,QAAQ,WAAW,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAC/C,QAAM,mBAAmB,CAAC,CAAC,GAAG,CAAC,CAAC;AAChC,mBAAiB,KAAK,GAAG,QAAQ;AACjC,WAAS,KAAK,IAAI,WAAW,QAAQ,KAAK,EAAE,MAAM,QAAQ,EAAE,IAAI;AAC9D,qBAAiB,KAAK,CAAC,GAAG,CAAC,CAAC;AAAA,EAC9B;AACA,QAAM,YAAY,CAAC;AACnB,QAAM,UAAU,OAAO;AAAA,IACrB,QAAQ,EAAE,EAAE;AAAA,IACZ,SAAS;AAAA,IACT,OAAO,EAAE,UAAU,kBAAkB,eAAe,EAAE;AAAA,EACxD,CAAC;AACD,QAAM,sBAAsB,qBAAqB,YAAY,QAAQ,OAAO,YAAY,OAAO,KAAK;AACpG,QAAM,oCAAoC,qBAAqB,YAAY,oBAAoB,QAAQ,WAAW,QAAQ,KAAK;AAC/H,QAAM,eAAe,qBAAqB,oBAAoB,QAAQ,OAAO,YAAY,OAAO,KAAK;AACrG,QAAM,kBAAkB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,oBAAoB,EAAE,CAAC;AACrH,QAAM,WAAW,WAAW;AAAA,IAC1B,QAAQ,EAAE,GAAG,gBAAgB;AAAA,IAC7B,SAAS;AAAA,IACT,OAAO,EAAE,MAAM,kCAAkC;AAAA,EACnD,CAAC;AACD,QAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,aAAa,EAAE,CAAC;AACtG,YAAU,KAAK,OAAO;AACtB,YAAU,KAAK,eAAe;AAC9B,YAAU,KAAK,QAAQ;AACvB,YAAU,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACzD,SAAO;AACT;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,QAAQ,MAAM;AACxB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,UAAM,cAAc,IAAI,MAAM,OAAO,MAAM;AAC3C,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,MAAM;AAC9C,kBAAY,MAAM,OAAO,MAAM,KAAK;AAAA,IACtC;AACA,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,OAAO,KAAK,YAAY;AAC7B,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,eAAe,iBAAiB,KAAK,MAAM,WAAW;AAC5D,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA,yCAGD;AAAA;AAAA;AAAA;AAIrC,WAAO;AAAA,EACT;AACF;AACA,SAAS,iBAAiB,MAAM,gBAAgB,IAAI;AAClD,MAAI,QAAQ,GAAG;AACb,UAAM,MAAM,iBAAiB,2BAA2B;AAAA,EAC1D;AACA,MAAI,SAAS,GAAG;AACd,WAAO,YAAY;AAAA,EACrB;AACA,QAAM,gBAAgB,CAAC,WAAW,WAAW,WAAW,SAAS;AACjE,QAAM,eAAe,CAAC;AACtB,WAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,iBAAa,KAAK,IAAI,cAAc,SAAS,uBAAuB,MAAM;AAAA,EAC5E;AACA,SAAO,aAAa,KAAK;AAC3B;AAGA,SAAS,MAAM,QAAQ;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,KAAK,EAAE,UAAU,YAAY,EAAE,MAAM,UAAU,GAAG;AACnF,UAAM,OAAO,SAAS,SAAS,EAAE,MAAM;AACvC,UAAM,QAAQ,EAAE,UAAU,WAAW,KAAK,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC,IAAI;AACrF,UAAM,MAAM,OAAO,EAAE,OAAO,EAAE,OAAO,KAAK;AAC1C,UAAM,SAAS,aAAa,KAAK,IAAI;AACrC,WAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAAA,EAC1E;AACA,QAAM,UAAU,IAAI,aAAa,EAAE,OAAO,IAAI;AAC9C,QAAM,SAAS,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AAC9D,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,eAAe,cAAc,aAAa,IAAI;AACtD,QAAM,EAAE,YAAY,IAAI;AACxB,QAAM,EAAE,WAAW,YAAY,WAAW,SAAAA,UAAS,YAAAQ,YAAW,IAAI,qBAAqB,gBAAgB,cAAc,eAAe,WAAW;AAC/I,QAAM,iBAAiB;AACvB,MAAI,aAAa,UAAU,UAAU;AACnC,UAAM,aAAa,SAAS,WAAW,aAAa;AACpD,UAAM,aAAa,SAAS,WAAW,YAAY;AACnD,UAAM,iBAAiB,aAAa,aAAa,SAAS,SAAS,aAAa,MAAM,EAAE,EAAE;AAC1F,UAAM,SAAS,gBAAgB,YAAY,YAAY,aAAaA,aAAY,WAAW,YAAY,WAAWR,UAAS,gBAAgB,cAAc;AACzJ,WAAO,SAAS,eAAe,aAAa,OAAO,OAAO,OAAO,MAAM;AAAA,EACzE;AACA,QAAM,eAAe,CAACQ,cAAa,WAAW,SAAS;AACvD,QAAM,iBAAiB,SAAS;AAAA,IAC9B,QAAQ,EAAE,GAAG,cAAc;AAAA,IAC3B,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,YAAY,SAAS,EAAE;AAAA,EAC1C,CAAC;AACD,QAAM,gBAAgB,aAAa,MAAM,SAAS,SAAS;AAAA,IACzD,QAAQ,EAAE,GAAG,aAAa;AAAA,IAC1B,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,YAAY,SAAS,EAAE;AAAA,EAC1C,CAAC,IAAI,UAAU,EAAE,QAAQ,EAAE,GAAG,aAAa,GAAG,SAAS,SAAS,CAAC;AACjE,QAAM,OAAO,cAAc;AAC3B,QAAM,OAAO,SAAS,eAAe,CAAC,GAAG,MAAM,aAAa,oBAAoB,GAAG,IAAI,CAAC;AACxF,QAAM,gBAAgB,SAAS;AAAA,IAC7B,QAAQ,EAAE,GAAG,aAAa;AAAA,IAC1B,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,MAAM,aAAa,MAAM,EAAE,KAAK,CAAC,EAAE;AAAA,EACrD,CAAC;AACD,QAAM,eAAe,MAAM,EAAE,QAAQ,EAAE,GAAG,cAAc,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AAC7G,QAAMpB,QAAO,aAAa,cAAc,CAAC,YAAY,SAAS,CAAC;AAC/D,QAAM,cAAc;AAAA,IAClB,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE;AAAA,IACnC,EAAE,MAAM,SAAS,MAAMY,SAAQ;AAAA,IAC/B,EAAE,MAAM,SAAS,MAAM,CAACZ,KAAI,EAAE;AAAA,EAChC;AACA,UAAQ;AAAA,SACD;AACH;AAAA,SACG;AACH,UAAI,MAAM;AACR,cAAM,UAAU,IAAI,wBAAwB,CAAC,YAAY,SAAS,GAAG,WAAW,eAAe,MAAM,QAAQ,cAAc,MAAM,QAAQY,UAAS,cAAc,MAAM,cAAc;AACpL,iBAAS,iBAAiB,SAAS,CAAC,eAAe,cAAc,GAAG,MAAM,aAAa,YAAY;AAAA,MACrG;AACA;AAAA;AAEA,UAAI,MAAM;AACR,cAAM,UAAU,IAAI,wBAAwB,CAAC,YAAY,SAAS,GAAG,WAAW,eAAe,MAAM,QAAQ,KAAK,MAAM,QAAQA,UAAS,cAAc,MAAM,cAAc;AAC3K,iBAAS,iBAAiB,SAAS,CAAC,MAAM,cAAc,GAAG,MAAM,aAAa,YAAY;AAAA,MAC5F;AACA;AACE,cAAM,UAAU,IAAI,wBAAwB,CAAC,YAAY,SAAS,GAAG,WAAW,eAAe,MAAM,QAAQ,cAAc,MAAM,QAAQA,UAAS,cAAc,IAAI;AACpK,iBAAS,iBAAiB,SAAS,CAAC,eAAe,cAAc,GAAG,MAAM,aAAa,YAAY;AAAA,MACrG;AAAA;AAEJ,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,GAAG,aAAa,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAC9G,WAAS,YAAY,eAAe,MAAM;AAC1C,WAAS,YAAY,cAAc,MAAM;AACzC,WAAS,YAAY,cAAc,MAAM;AACzC,WAAS,YAAY,KAAK,MAAM;AAChC,WAAS,YAAY,aAAa,MAAM;AACxC,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,iBAAiB,KAAK,IAAI;AAClC,QAAM,QAAQ,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AACzD,QAAM,aAAa,qBAAqB,iBAAiB,GAAG,iBAAiB,KAAK;AAClF,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,IAAI,MAAM,KAAK,EAAE,KAAK,CAAC;AACrC,QAAMZ,QAAO,EAAE,MAAM,MAAM;AAC3B,SAAO,WAAW,IAAI,CAAC,OAAO;AAC5B,UAAM,YAAY,CAAC,GAAGA,KAAI;AAC1B,cAAU,SAAS;AACnB,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,MAAM,UAAU,EAAE,CAAC;AAC7F,UAAM,UAAU;AAChB,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,iBAAiB,EAAE,QAAQ,YAAY,KAAK,CAAC;AACzD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AAC7C,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,gBAAgB;AACtB,UAAM,UAAU,IAAI,gBAAgB,EAAE,OAAO,YAAY,MAAM;AAC/D,WAAO,cAAc,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AAAA,EAC7D;AACF;AAGA,IAAI,qBAAqB,kBAAkB;AAAA,EACzC,QAAQ,aAAa;AACvB,CAAC;AACD,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB;AACrB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,KAAK,eAAe,GAAG,CAAC,CAAC;AACrH,UAAM,QAAQ,mBAAmB,KAAK,YAAY,MAAM;AACxD,SAAK,WAAW,WAAW,qBAAqB;AAChD,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,OAAO,KAAK,YAAY;AAC9B,QAAI,YAAY;AAChB,QAAI,SAAS,GAAG;AACd,kBAAY;AAAA,IACd,OAAO;AACL,UAAI,aAAa;AACjB,kBAAY,KAAK,YAAY,IAAI,CAAC,GAAG,OAAO;AAC1C;AACA,eAAO,KAAK,YAAY,WAAW,IAAI,6BAA6B,wBAAwB,QAAQ,UAAU,aAAa,yBAAyB,wBAAwB;AAAA,MAC9K,CAAC,EAAE,KAAK,GAAG;AAAA,IACb;AACA,UAAM,WAAW;AAAA,SACZ,kCAAkC;AAAA;AAAA;AAAA,0CAGD;AAAA;AAAA;AAAA;AAItC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAO,KAAK,SAAAY,UAAS,WAAW,SAAS,cAAc,aAAa,eAAe,IAAI;AAC/F,QAAM,EAAE,kBAAkB,YAAY,YAAY,WAAW,eAAe,OAAO,QAAQ,KAAK,MAAM,SAAS,SAAS,IAAI,mBAAmB,UAAU,EAAE,OAAO,OAAO,KAAKA,UAAS,WAAW,SAAS,cAAc,aAAa,cAAc;AACpP,MAAI;AACJ,MAAI,YAAY;AACd,aAAS,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAAA,EACtF,WAAW,aAAa,eAAe;AACrC,iBAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,yCAAyC,EAAE,MAAM,QAAQ;AACxG,UAAMZ,QAAO,mBAAmB,gBAAgB,QAAQ,MAAM,QAAQ;AACtE,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,QAAQ,MAAAA,MAAK,EAAE,CAAC;AAC1F,aAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAC5F,aAAS,YAAY,OAAO,MAAM;AAAA,EACpC,OAAO;AACL,UAAM,qBAAqB,SAAS,mBAAmB,CAAC,CAAC,CAAC;AAC1D,QAAI,oBAAoB;AACtB,YAAM,SAAS,SAAS,SAAS,EAAE,MAAM;AACzC,YAAM,OAAO,OAAO,EAAE,OAAO,EAAE,OAAO,MAAM;AAC5C,YAAM,eAAe,qBAAqB,kBAAkB,MAAM,UAAU,MAAM;AAClF,eAAS,SAAS,eAAe,YAAY,EAAE,OAAO,aAAa,MAAM;AAAA,IAC3E,OAAO;AACL,YAAM,UAAU,IAAI,qBAAqB,gBAAgB;AACzD,YAAM,cAAc,CAAC,EAAE,MAAM,SAAS,MAAM,OAAO,GAAG,EAAE,MAAM,SAAS,MAAM,SAAS,CAAC;AACvF,YAAM,eAAe,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,WAAW;AACjF,eAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,aAAa,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAClG,eAAS,YAAY,aAAa,MAAM;AAAA,IAC1C;AAAA,EACF;AACA,SAAO;AACT;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,WAAW,aAAa,SAAS,UAAU,WAAW,UAAU,uBAAuB,IAAI;AACnG,QAAM,EAAE,MAAM,WAAW,IAAI;AAC7B,QAAM,QAAQ,SAAS,SAAS,KAAK,MAAM;AAC3C,QAAM,cAAc,SAAS,SAAS,WAAW,MAAM;AACvD,QAAM,CAAC,QAAQ,YAAY,IAAI,qBAAqB,OAAO,aAAa,WAAW,aAAa,SAAS,WAAW,UAAU,sBAAsB;AACpJ,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,OAAO,MAAM,GAAG,UAAU,MAAM;AAAA,IACzD,SAAS,eAAe,WAAW,OAAO,SAAS,YAAY;AAAA,EACjE;AACF;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,iBAAiB,EAAE,QAAQ,YAAY,KAAK,CAAC;AACzD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,OAAO;AACjB,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,WAAW;AAAA;AAEhB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,UACX,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAmExC,WAAO;AAAA,EACT;AACF;AACA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,OAAO;AACjB,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,WAAW;AAChB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,UACX,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AA2DxC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,qCAAqC,UAAU,YAAY;AAClE,MAAI,eAAe,MAAM;AACvB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACF;AACA,SAAS,eAAe,KAAK;AAC3B,MAAI,QAAQ;AACZ,SAAO,QAAQ,KAAK;AAClB,aAAS;AAAA,EACX;AACA,SAAO;AACT;AACA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,SAAS,EAAE;AACjB,QAAM,UAAU,OAAO,OAAO,SAAS;AACvC,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,GAAG;AACpC,UAAM,QAAQ,SAAS,SAAS,EAAE,MAAM;AACxC,UAAM,CAAC,aAAa,cAAc,IAAI,aAAa,OAAO,QAAQ,EAAE,OAAO,GAAG,MAAM;AACpF,WAAO;AAAA,MACL,SAAS,eAAe,YAAY,OAAO,YAAY,OAAO,YAAY,MAAM;AAAA,MAChF,SAAS,eAAe,eAAe,OAAO,eAAe,OAAO,eAAe,MAAM;AAAA,IAC3F;AAAA,EACF;AACA,MAAI,MAAM,GAAG;AACX,WAAO,OAAO,SAAS,KAAK;AAC5B,WAAO;AAAA,MACL,SAAS,eAAe,QAAQ,EAAE,OAAO,CAAC,CAAC;AAAA,MAC3C,SAAS,eAAe,QAAQ,SAAS,CAAC,CAAC;AAAA,IAC7C;AAAA,EACF;AACA,MAAI,YAAY,GAAG;AACjB,WAAO;AAAA,MACL;AAAA,MACA,MAAM,EAAE,OAAO,EAAE,OAAO,QAAQ,OAAO,SAAS,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,IACjF;AAAA,EACF;AACA,QAAM,QAAQ,aAAa,cAAc,MAAM;AAC/C,QAAM,QAAQ,QAAQ;AACtB,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,OAAO,CAAC,OAAO,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAC7F,QAAM,QAAQ,eAAe,CAAC;AAC9B,QAAM,cAAc,eAAe,OAAO;AAC1C,MAAI,UAAU;AACd,QAAM,YAAY,MAAM,YAAY,OAAO,CAAC,KAAK,GAAG,IAAI,CAAC,KAAK,OAAO;AACrE,QAAM,UAAU,CAAC,KAAK,KAAK,UAAU;AACnC,UAAM,UAAU,UAAU;AAC1B,UAAM,UAAU,IAAI,aAAa,KAAK;AACtC,UAAM,YAAY,YAAY,OAAO,IAAI;AACzC,UAAM,kBAAkB;AAAA,MACtB,EAAE,MAAM,SAAS,MAAM,CAAC,OAAO,EAAE;AAAA,MACjC,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE;AAAA,MACnC,EAAE,MAAM,WAAW,MAAM,CAAC,OAAO,iBAAiB,EAAE;AAAA,MACpD,EAAE,MAAM,SAAS,MAAM,CAAC,GAAG,EAAE;AAAA,MAC7B,EAAE,MAAM,SAAS,MAAM,CAAC,GAAG,EAAE;AAAA,IAC/B;AACA,UAAM,eAAe;AACrB,cAAU,SAAS,iBAAiB,SAAS,SAAS,SAAS,eAAe;AAC9E,yCAAqC,UAAU,YAAY;AAAA,EAC7D;AACA,WAAS,MAAM,GAAG,MAAM,OAAO,OAAO,GAAG;AACvC,UAAM,MAAM,MAAM;AAClB,aAAS,MAAM,KAAK,OAAO,GAAG,OAAO,GAAG;AACtC,cAAQ,KAAK,KAAK,CAAC,OAAO,WAAW,CAAC;AAAA,IACxC;AAAA,EACF;AACA,WAAS,cAAc,aAAa,cAAc,OAAO,eAAe,GAAG;AACzE,UAAM,UAAU,UAAU;AAC1B,UAAM,eAAe,IAAI,cAAc,CAAC,OAAO,cAAc,CAAC,CAAC;AAC/D,UAAM,YAAY,YAAY,OAAO,IAAI;AACzC,UAAM,mBAAmB;AAAA,MACvB,EAAE,MAAM,SAAS,MAAM,CAAC,OAAO,EAAE;AAAA,MACjC,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE;AAAA,MACnC,EAAE,MAAM,SAAS,MAAM,CAAC,KAAK,EAAE;AAAA,IACjC;AACA,UAAM,eAAe;AACrB,cAAU,SAAS,iBAAiB,cAAc,SAAS,SAAS,gBAAgB;AACpF,yCAAqC,UAAU,YAAY;AAC3D,UAAM,MAAM,QAAQ;AACpB,UAAM,MAAM,MAAM;AAClB,aAAS,MAAM,KAAK,OAAO,GAAG,OAAO,GAAG;AACtC,cAAQ,KAAK,KAAK,QAAQ,KAAK;AAAA,IACjC;AAAA,EACF;AACA,MAAI,cAAc;AAClB,YAAU,OAAO,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,GAAG,MAAM,CAAC,OAAO,CAAC,EAAE,EAAE,CAAC;AACrG,uCAAqC,UAAU,WAAW;AAC1D,MAAI,SAAS,UAAU,EAAE,QAAQ,EAAE,GAAG,KAAK,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,GAAG,WAAW,EAAE,EAAE,CAAC;AAC3G,uCAAqC,UAAU,GAAG;AAClD,QAAM,WAAW,OAAO,MAAM,GAAG,EAAE;AACnC,WAAS,KAAK,CAAC;AACf,gBAAc;AACd,YAAU,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AAC5F,uCAAqC,UAAU,WAAW;AAC1D,QAAM,aAAa;AACnB,WAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AAC1F,uCAAqC,UAAU,UAAU;AACzD,SAAO,CAAC,QAAQ,OAAO;AACzB;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,SAAS,YAAY;AAC3C,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAgET,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAqD1C,WAAO;AAAA,EACT;AACF;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,WAAW,IAAI;AACtC,QAAM,EAAE,eAAe,UAAU,WAAW,YAAY,IAAI;AAC5D,QAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,QAAM,CAAC,WAAW,QAAQ,IAAI,eAAe,OAAO,cAAc,CAAC,aAAa,UAAU;AAC1F,QAAM,WAAW;AAAA,IACf;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACA,QAAM,UAAU,IAAI,kBAAkB,QAAQ;AAC9C,QAAM,sBAAsB,kBAAkB,YAAY,IAAI;AAC9D,MAAI;AACJ,UAAQ;AAAA,SACD;AACH,mBAAa;AACb;AAAA,SACG;AACH,mBAAa;AACb;AAAA,SACG;AACH,mBAAa;AACb;AAAA,SACG;AACH,mBAAa;AACb;AAAA;AAEA,mBAAa;AACb;AAAA;AAEJ,QAAM,cAAc;AAAA,IAClB,EAAE,MAAM,SAAS,MAAM,CAAC,mBAAmB,EAAE;AAAA,IAC7C,EAAE,MAAM,SAAS,MAAM,CAAC,UAAU,EAAE;AAAA,IACpC,EAAE,MAAM,WAAW,MAAM,CAAC,SAAS,EAAE;AAAA,EACvC;AACA,SAAO,SAAS,iBAAiB,SAAS,CAAC,QAAQ,UAAU,GAAG,WAAW,WAAW;AACxF;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,IAAI;AAClB,MAAI,EAAE,KAAK,IAAI;AACf,MAAI,OAAO,GAAG;AACZ,YAAQ,MAAM,MAAM;AAAA,EACtB;AACA,QAAM,IAAI;AACV,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,MAAM,MAAM,MAAM;AACxB,QAAM,WAAW,IAAI,MAAM,QAAQ,CAAC;AACpC,MAAI,WAAW;AACf,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM;AACjC,QAAI,OAAO,MAAM;AACf,eAAS,cAAc,EAAE,MAAM;AAAA,IACjC;AAAA,EACF;AACA,QAAM,YAAY,CAAC;AACnB,QAAM,QAAQ,IAAI,MAAM,KAAK,EAAE,KAAK,CAAC;AACrC,QAAMA,QAAO,EAAE,MAAM,MAAM;AAC3B,EAAAA,MAAK,QAAQ;AACb,QAAM,MAAM,IAAI,MAAM,GAAG;AACzB,WAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,MAAM;AACtC,UAAM,QAAQ;AACd,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,MAAAA,MAAK,EAAE,CAAC;AAClF,UAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAClG,QAAI,MAAM;AACV,cAAU,KAAK,MAAM;AAAA,EACvB;AACA,YAAU,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACzD,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB;AAAA,EACnB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,WAAW,gBAAgB,gBAAgB;AACzC,iBAAe,YAAY;AAC7B;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,QAAQ;AAClB,SAAK,SAAS;AACd,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AACtB,SAAK,cAA8B,oBAAI,IAAI;AAC3C,SAAK,cAA8B,oBAAI,IAAI;AAC3C,SAAK,eAAe;AACpB,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,oBAAoBA,OAAM,OAAO;AAC/B,WAAO,KAAK,cAAcA,OAAM,OAAO,IAAI;AAAA,EAC7C;AAAA,EACA,cAAcA,OAAM,OAAO,mBAAmB,OAAO;AACnD,UAAM,MAAM,aAAaA,OAAM,KAAK;AACpC,QAAI,CAAC,KAAK,YAAY,IAAI,GAAG,GAAG;AAC9B,WAAK,YAAY,IAAI,KAAK,CAAC,CAAC;AAAA,IAC9B;AACA,QAAI,CAAC,KAAK,YAAY,IAAI,GAAG,GAAG;AAC9B,WAAK,YAAY,IAAI,KAAK,CAAC,CAAC;AAAA,IAC9B;AACA,SAAK,gBAAgBA;AACrB,SAAK;AACL,QAAI,KAAK,YAAY,IAAI,GAAG,EAAE,SAAS,GAAG;AACxC,WAAK;AACL,YAAM,aAAa,KAAK,YAAY,IAAI,GAAG,EAAE,MAAM;AACnD,WAAK,YAAY,IAAI,GAAG,EAAE,KAAK,UAAU;AACzC,aAAO;AAAA,IACT;AACA,SAAK,qBAAqBA;AAC1B,UAAM,YAAY,KAAK,OAAO,aAAa,EAAE,MAAAA,OAAM,OAAO,iBAAiB,CAAC;AAC5E,SAAK,YAAY,IAAI,GAAG,EAAE,KAAK,SAAS;AACxC,WAAO;AAAA,EACT;AAAA,EACA,cAAc,SAASA,OAAM,OAAO;AAClC,QAAI,KAAK,YAAY,SAAS,GAAG;AAC/B;AAAA,IACF;AACA,UAAM,MAAM,aAAaA,OAAM,KAAK;AACpC,QAAI,CAAC,KAAK,YAAY,IAAI,GAAG,GAAG;AAC9B,WAAK,YAAY,IAAI,KAAK,CAAC,CAAC;AAAA,IAC9B;AACA,SAAK,YAAY,IAAI,GAAG,EAAE,KAAK,OAAO;AACtC,SAAK;AACL,SAAK;AACL,UAAM,aAAa,KAAK,YAAY,IAAI,GAAG;AAC3C,UAAM,cAAc,WAAW,QAAQ,OAAO;AAC9C,QAAI,cAAc,GAAG;AACnB,YAAM,IAAI,MAAM,wEAAwE;AAAA,IAC1F;AACA,eAAW,OAAO,aAAa,CAAC;AAChC,SAAK,gBAAgBA;AAAA,EACvB;AAAA,EACA,oBAAoB,SAASA,OAAM,OAAO;AACxC,YAAQ,SAAS,WAAW,KAAK,EAAE,KAAK,MAAM;AAC5C,WAAK,cAAc,SAASA,OAAM,KAAK;AAAA,IACzC,GAAG,CAAC,QAAQ;AAAA,IACZ,CAAC;AAAA,EACH;AAAA,EACA,oBAAoB;AAClB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,oBAAoB;AAClB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,UAAU;AACR,SAAK,YAAY,QAAQ,CAAC,SAAS,QAAQ;AACzC,cAAQ,QAAQ,CAAC,YAAY;AAC3B,gBAAQ,QAAQ;AAAA,MAClB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,YAAY,QAAQ,CAAC,SAAS,QAAQ;AACzC,cAAQ,QAAQ,CAAC,YAAY;AAC3B,gBAAQ,QAAQ;AAAA,MAClB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,cAA8B,oBAAI,IAAI;AAC3C,SAAK,cAA8B,oBAAI,IAAI;AAC3C,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AACtB,SAAK,eAAe;AACpB,SAAK,oBAAoB;AAAA,EAC3B;AACF;AACA,SAAS,aAAaA,OAAM,OAAO;AACjC,SAAO,GAAGA,SAAQ;AACpB;AAGA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,YAAY,QAAQ;AAClB,SAAK,SAAS;AACd,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AACvB,SAAK,eAA+B,oBAAI,IAAI;AAC5C,SAAK,eAA+B,oBAAI,IAAI;AAC5C,SAAK,eAAe;AACpB,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,eAAe,OAAO,QAAQ,QAAQ,OAAO;AAC3C,UAAM,mBAAmB,mBAAmB,MAAM;AAClD,UAAM,WAAW,QAAQ,SAAS;AAClC,UAAM,MAAM,cAAc,OAAO,QAAQ,QAAQ,KAAK;AACtD,QAAI,CAAC,KAAK,aAAa,IAAI,GAAG,GAAG;AAC/B,WAAK,aAAa,IAAI,KAAK,CAAC,CAAC;AAAA,IAC/B;AACA,QAAI,CAAC,KAAK,aAAa,IAAI,GAAG,GAAG;AAC/B,WAAK,aAAa,IAAI,KAAK,CAAC,CAAC;AAAA,IAC/B;AACA,SAAK,gBAAgB;AACrB,SAAK;AACL,QAAI,KAAK,aAAa,IAAI,GAAG,EAAE,SAAS,GAAG;AACzC,WAAK;AACL,YAAM,cAAc,KAAK,aAAa,IAAI,GAAG,EAAE,MAAM;AACrD,WAAK,aAAa,IAAI,GAAG,EAAE,KAAK,WAAW;AAC3C,aAAO;AAAA,IACT;AACA,SAAK,qBAAqB;AAC1B,UAAM,aAAa,KAAK,OAAO,cAAc;AAAA,MAC3C,MAAM,CAAC,OAAO,MAAM;AAAA,MACpB;AAAA,MACA;AAAA,IACF,CAAC;AACD,SAAK,aAAa,IAAI,GAAG,EAAE,KAAK,UAAU;AAC1C,WAAO;AAAA,EACT;AAAA,EACA,eAAe,SAAS,OAAO,QAAQ,QAAQ,OAAO;AACpD,QAAI,KAAK,aAAa,SAAS,GAAG;AAChC;AAAA,IACF;AACA,UAAM,MAAM,cAAc,OAAO,QAAQ,QAAQ,KAAK;AACtD,QAAI,CAAC,KAAK,aAAa,IAAI,GAAG,GAAG;AAC/B,WAAK,aAAa,IAAI,KAAK,CAAC,CAAC;AAAA,IAC/B;AACA,SAAK,aAAa,IAAI,GAAG,EAAE,KAAK,OAAO;AACvC,SAAK;AACL,SAAK;AACL,UAAM,cAAc,KAAK,aAAa,IAAI,GAAG;AAC7C,UAAM,eAAe,YAAY,QAAQ,OAAO;AAChD,QAAI,eAAe,GAAG;AACpB,YAAM,IAAI,MAAM,0EAA0E;AAAA,IAC5F;AACA,gBAAY,OAAO,cAAc,CAAC;AAClC,UAAM,mBAAmB,mBAAmB,MAAM;AAClD,UAAM,WAAW,QAAQ,SAAS;AAClC,SAAK,gBAAgB;AAAA,EACvB;AAAA,EACA,qBAAqB;AACnB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,qBAAqB;AACnB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,UAAU;AACR,SAAK,aAAa,QAAQ,CAAC,UAAU,QAAQ;AAC3C,eAAS,QAAQ,CAAC,YAAY;AAC5B,gBAAQ,QAAQ;AAAA,MAClB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,aAAa,QAAQ,CAAC,UAAU,QAAQ;AAC3C,eAAS,QAAQ,CAAC,YAAY;AAC5B,gBAAQ,QAAQ;AAAA,MAClB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,eAA+B,oBAAI,IAAI;AAC5C,SAAK,eAA+B,oBAAI,IAAI;AAC5C,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AACvB,SAAK,eAAe;AACpB,SAAK,oBAAoB;AAAA,EAC3B;AACF;AACA,SAAS,cAAc,OAAO,QAAQ,QAAQ,OAAO;AACnD,SAAO,GAAG,SAAS,UAAU,UAAU;AACzC;AACA,SAAS,mBAAmB,QAAQ;AAClC,MAAI,WAAW,cAAc;AAC3B,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,GAAG,0BAA0B;AAAA,EAC/C;AACF;AAGA,IAAI,8BAA8B,IAAI,EAAE,UAAU,mCAAmC;AACrF,IAAI,kBAAkB,CAAC,QAAQ,YAAY;AACzC,QAAM,0CAA0C,OAAO,OAAO;AAC9D,QAAM,SAAS,QAAQ;AACvB,QAAM,WAAW,QAAQ;AACzB,MAAI,SAAS,MAAM,CAAC,MAAM,KAAK,uCAAuC,GAAG;AACvE,WAAO;AAAA,EACT;AACA,eAAa,OAAO,SAAS,KAAK,2CAA2C,OAAO,MAAM,UAAU,OAAO,MAAM,QAAQ,MAAM,0DAA0D;AACzL,MAAI,kBAAkB,KAAK,KAAK,KAAK,KAAK,SAAS,EAAE,CAAC;AACtD,MAAI,kBAAkB,yCAAyC;AAC7D,sBAAkB,KAAK,KAAK,KAAK,KAAK,SAAS,EAAE,CAAC;AAClD,iBAAa,OAAO,mBAAmB,yCAAyC,MAAM,6CAA6C;AACnI,WAAO,CAAC,iBAAiB,iBAAiB,eAAe;AAAA,EAC3D,OAAO;AACL,WAAO,CAAC,iBAAiB,iBAAiB,CAAC;AAAA,EAC7C;AACF;AACA,IAAI,gBAAgB,cAAc,cAAc;AAAA,EAC9C,YAAY,QAAQ,mBAAmB,OAAO;AAC5C,UAAM;AACN,SAAK,uBAAuC,oBAAI,QAAQ;AACxD,SAAK,0BAA0B;AAC/B,SAAK,WAAW;AAChB,SAAK,iBAAiB;AACtB,SAAK,4BAA4B,CAAC;AAClC,SAAK,yBAAyB,CAAC;AAC/B,SAAK,yBAAyB,CAAC;AAC/B,SAAK,eAAe;AACpB,QAAI,CAAC,kBAAkB,GAAG;AACxB,YAAM,IAAI,MAAM,wCAAwC;AAAA,IAC1D;AACA,SAAK,gBAAgB,CAAC;AACtB,SAAK,SAAS;AACd,SAAK,QAAQ,OAAO;AACpB,SAAK,wBAAwB;AAC7B,SAAK,qBAAqB;AAC1B,SAAK,mBAAmB;AACxB,SAAK,gBAAgB,IAAI,cAAc,KAAK,MAAM;AAClD,SAAK,iBAAiB,IAAI,gBAAgB,KAAK,MAAM;AACrD,SAAK,YAAY,IAAI,YAAY,MAAM,OAAO,CAAC;AAC/C,QAAI,KAAK,kBAAkB;AACzB,WAAK,WAAW,KAAK,OAAO,eAAe;AAAA,QACzC,MAAM;AAAA,QACN,OAAO;AAAA,MACT,CAAC;AAAA,IACH;AACA,QAAI,IAAI,EAAE,QAAQ,yBAAyB,GAAG;AAC5C,WAAK,cAAc,SAAS,cAAc,QAAQ;AAClD,WAAK,YAAY,QAAQ;AACzB,WAAK,YAAY,SAAS;AAC1B,WAAK,eAAe,KAAK,YAAY,WAAW,QAAQ;AACxD,WAAK,aAAa,UAAU;AAAA,QAC1B;AAAA,QACA,QAAQ;AAAA,MACV,CAAC;AACD,eAAS,KAAK,YAAY,KAAK,WAAW;AAAA,IAC5C;AAAA,EACF;AAAA,EACA,aAAa;AACX,WAAO,cAAc;AAAA,EACvB;AAAA,EACA,iBAAiB;AACf,WAAO;AAAA,EACT;AAAA,EACA,wBAAwB;AACtB,WAAO,eAAe,UAAU,eAAe,WAAW,eAAe;AAAA,EAC3E;AAAA,EACA,YAAY,QAAQ,QAAQ,OAAO;AACjC,QAAI,KAAK,0BAA0B,QAAQ,MAAM,KAAK,GAAG;AACvD,aAAO;AAAA,IACT;AACA,QAAI,CAAC,KAAK,UAAU,IAAI,MAAM,GAAG;AAC/B,aAAO;AAAA,IACT;AACA,UAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,SAAK,OAAO,MAAM;AAClB,QAAI,CAAC,SAAS,WAAW,WAAW,GAAG;AACrC,aAAO;AAAA,IACT;AACA,QAAI,KAAK,qBAAqB,IAAI,MAAM,GAAG;AACzC,WAAK,0BAA0B,KAAK,MAAM;AAC1C,aAAO;AAAA,IACT;AACA,UAAM,EAAE,mBAAmB,IAAI,KAAK,UAAU,IAAI,MAAM;AACxD,QAAI,sBAAsB,MAAM;AAC9B,WAAK,YAAY,mBAAmB,KAAK,QAAQ,KAAK;AACtD,WAAK,YAAY,mBAAmB,KAAK,QAAQ,KAAK;AAAA,IACxD;AACA,SAAK,gBAAgB,MAAM;AAC3B,SAAK,UAAU,OAAO,MAAM;AAC5B,WAAO;AAAA,EACT;AAAA,EACA,SAAS;AACP,WAAO;AAAA,MACL,eAAe,KAAK,cAAc;AAAA,MAClC,wBAAwB,KAAK,cAAc;AAAA,MAC3C,YAAY;AAAA,IACd;AAAA,EACF;AAAA,EACA,gBAAgB,QAAQ;AACtB,UAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,QAAI,CAAC,cAAc,CAAC,WAAW,cAAc;AAC3C;AAAA,IACF;AACA,QAAI,aAAa,WAAW,cAAc;AACxC,YAAM,cAAc,WAAW;AAC/B,UAAI,YAAY,mBAAmB,YAAY;AAC7C,aAAK,eAAe,eAAe,YAAY,SAAS,YAAY,OAAO,YAAY,QAAQ,YAAY,QAAQ,YAAY,KAAK;AAAA,MACtI;AACA,kBAAY,UAAU;AAAA,IACxB,OAAO;AACL,YAAM,aAAa,WAAW;AAC9B,WAAK,cAAc,cAAc,WAAW,QAAQ,WAAW,MAAM,WAAW,KAAK;AACrF,iBAAW,SAAS;AAAA,IACtB;AACA,eAAW,eAAe;AAAA,EAC5B;AAAA,EACA,SAAS,QAAQ;AACf,QAAI,KAAK,UAAU,IAAI,MAAM,GAAG;AAC9B,YAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,aAAO,WAAW;AAAA,IACpB;AACA,WAAO;AAAA,EACT;AAAA,EACA,OAAO,QAAQ;AACb,UAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,eAAW;AAAA,EACb;AAAA,EACA,OAAO,QAAQ;AACb,QAAI,KAAK,UAAU,IAAI,MAAM,GAAG;AAC9B,YAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,iBAAW;AAAA,IACb;AAAA,EACF;AAAA,EACA,MAAM,QAAQ,OAAO,OAAO;AAC1B,QAAI,UAAU,eAAe,UAAU,MAAM;AAC3C,YAAM,IAAI,MAAM,uEAAuE;AAAA,IACzF;AACA,UAAM,SAAS,EAAE,IAAI,KAAK,WAAW,EAAE;AACvC,SAAK,UAAU,IAAI,QAAQ,EAAE,OAAO,OAAO,QAAQ,UAAU,EAAE,CAAC;AAChE,WAAO;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ,OAAO,OAAO,UAAU;AAC3C,QAAI,UAAU,aAAa;AACzB,YAAM,IAAI,MAAM,uEAAuE;AAAA,IACzF;AACA,SAAK,UAAU,IAAI,QAAQ,EAAE,OAAO,OAAO,QAAQ,SAAS,CAAC;AAAA,EAC/D;AAAA,EACA,cAAc;AACZ,SAAK,uBAAuB;AAC5B,SAAK,MAAM,OAAO,CAAC,KAAK,sBAAsB,OAAO,CAAC,CAAC;AACvD,SAAK,wBAAwB;AAC7B,SAAK,0BAA0B;AAC/B,SAAK,uBAAuC,oBAAI,QAAQ;AACxD,SAAK,0BAA0B,QAAQ,CAAC,MAAM;AAC5C,WAAK,gBAAgB,CAAC;AACtB,WAAK,UAAU,OAAO,CAAC;AAAA,IACzB,CAAC;AACD,SAAK,uBAAuB,QAAQ,CAAC,MAAM,KAAK,cAAc,cAAc,EAAE,QAAQ,EAAE,MAAM,EAAE,KAAK,CAAC;AACtG,SAAK,uBAAuB,QAAQ,CAAC,MAAM,KAAK,cAAc,oBAAoB,EAAE,QAAQ,EAAE,MAAM,EAAE,KAAK,CAAC;AAC5G,SAAK,4BAA4B,CAAC;AAClC,SAAK,yBAAyB,CAAC;AAC/B,SAAK,yBAAyB,CAAC;AAAA,EACjC;AAAA,EACA,4BAA4B;AAC1B,QAAI,CAAC,KAAK,uBAAuB;AAC/B,WAAK,wBAAwB,KAAK,OAAO,qBAAqB;AAAA,IAChE;AAAA,EACF;AAAA,EACA,yBAAyB;AACvB,QAAI,KAAK,oBAAoB;AAC3B,WAAK,mBAAmB,IAAI;AAC5B,WAAK,qBAAqB;AAAA,IAC5B;AAAA,EACF;AAAA,EACA,iBAAiB;AACf,QAAI,CAAC,KAAK,oBAAoB;AAC5B,WAAK,qBAAqB,KAAK,sBAAsB,iBAAiB;AAAA,IACxE;AACA,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,cAAc,SAASA,OAAM;AACjC,UAAM,UAAU,KAAK,cAAc,cAAcA,OAAM,eAAe,WAAW,eAAe,QAAQ;AACxG,SAAK,0BAA0B;AAC/B,SAAK,uBAAuB;AAC5B,SAAK,sBAAsB,mBAAmB,SAAS,GAAG,SAAS,GAAGA,KAAI;AAC1E,SAAK,YAAY;AACjB,UAAM,QAAQ,SAAS,WAAW,IAAI;AACtC,UAAM,SAAS,QAAQ,eAAe,EAAE,MAAM,CAAC;AAC/C,YAAQ,MAAM;AACd,QAAI,WAAW,MAAM;AACnB,WAAK,cAAc,cAAc,SAASA,OAAM,eAAe,WAAW,eAAe,QAAQ;AAAA,IACnG;AACA,QAAI,IAAI,EAAE,QAAQ,yBAAyB,GAAG;AAC5C,mBAAa,OAAO,KAAK,iBAAiB,QAAQ,MAAM,wCAAwC;AAChG,WAAK,aAAa,kBAAkB;AAAA,IACtC;AACA,WAAO;AAAA,EACT;AAAA,EACA,qBAAqB,QAAQ,MAAM;AACjC,UAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,SAAK,gBAAgB,MAAM;AAC3B,eAAW,SAAS;AACpB,WAAO,WAAW;AAAA,EACpB;AAAA,EACA,SAAS,QAAQ;AACf,UAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,UAAM,EAAE,OAAO,IAAI;AACnB,QAAI,UAAU,MAAM;AAClB,YAAM,IAAI,MAAM,6DAA6D;AAAA,IAC/E;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,KAAK,QAAQ;AACjB,QAAI,CAAC,KAAK,UAAU,IAAI,MAAM,GAAG;AAC/B,YAAM,IAAI,MAAM,UAAU,4BAA4B;AAAA,IACxD;AACA,UAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,UAAM,EAAE,OAAO,IAAI;AACnB,QAAI,UAAU,MAAM;AAClB,aAAO,KAAK,qBAAqB,QAAQ,MAAM;AAAA,IACjD;AACA,QAAI;AACJ,QAAI,WAAW,UAAU,aAAa;AACpC,YAAM,KAAK,MAAM,QAAQ,IAAI;AAAA,QAC3B,KAAK,KAAK,WAAW,mBAAmB,KAAK,MAAM;AAAA,QACnD,KAAK,KAAK,WAAW,mBAAmB,KAAK,MAAM;AAAA,MACrD,CAAC;AACD,YAAM,aAAa,GAAG;AACtB,YAAM,aAAa,GAAG;AACtB,aAAO,qBAAqB,uBAAuB,YAAY,UAAU;AAAA,IAC3E,OAAO;AACL,YAAM,aAAa,WAAW;AAC9B,YAAM,OAAO,MAAM,KAAK,cAAc,WAAW,QAAQ,WAAW,IAAI;AACxE,aAAO,wBAAwB,MAAM,WAAW,KAAK;AAAA,IACvD;AACA,SAAK,qBAAqB,QAAQ,IAAI;AACtC,WAAO;AAAA,EACT;AAAA,EACA,UAAU,QAAQ;AAChB,UAAM,gBAAgB,KAAK,UAAU,IAAI,MAAM;AAC/C,UAAM,EAAE,QAAQ,OAAO,OAAO,aAAa,IAAI;AAC/C,QAAI,UAAU,aAAa;AACzB,YAAM,IAAI,MAAM,sDAAsD;AAAA,IACxE;AACA,QAAI,gBAAgB,MAAM;AACxB,UAAI,UAAU,MAAM;AAClB,cAAM,IAAI,MAAM,gCAAgC;AAAA,MAClD,OAAO;AACL,cAAM,IAAI,MAAM,iCAAiC;AAAA,MACnD;AAAA,IACF;AACA,UAAMA,QAAO,aAAa;AAC1B,UAAM,UAAU,KAAK,cAAc,cAAcA,OAAM,aAAa,KAAK;AACzE,SAAK,0BAA0B;AAC/B,SAAK,uBAAuB;AAC5B,SAAK,sBAAsB,mBAAmB,aAAa,QAAQ,GAAG,SAAS,GAAGA,KAAI;AACtF,SAAK,YAAY;AACjB,UAAM,aAAa,KAAK,eAAe,OAAO,KAAK;AACnD,UAAM,YAAY,OAAO,EAAE,yBAAyB,UAAU;AAC9D,UAAM,aAAa,KAAK,UAAU,IAAI,WAAW,MAAM;AACvD,eAAW,eAAe,EAAE,MAAAA,OAAM,OAAO,KAAK,sBAAsB,GAAG,QAAQ,QAAQ;AACvF,WAAO,EAAE,WAAW,QAAQ,SAAS,SAASA,MAAK;AAAA,EACrD;AAAA,EACA,WAAW,IAAI;AACb,UAAM,OAAO,KAAK,SAAS,GAAG,MAAM;AACpC,QAAI,GAAG,UAAU,UAAU;AACzB,UAAI;AACF,cAAM,UAAU,KAAK,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC;AAC5D,eAAO,OAAO,GAAG,OAAO,GAAG,OAAO,OAAO;AAAA,MAC3C,SAAS,IAAP;AACA,cAAM,IAAI,MAAM,kDAAkD;AAAA,MACpE;AAAA,IACF;AACA,WAAO,OAAO,GAAG,OAAO,GAAG,OAAO,IAAI;AAAA,EACxC;AAAA,EACA,MAAM,KAAK,GAAG;AACZ,UAAM,kBAAkB,KAAK;AAC7B,UAAM,kBAAkB,CAAC;AACzB,QAAI,gBAAgB;AACpB,QAAI,KAAK,sBAAsB,MAAM;AACnC,WAAK,qBAAqB;AAC1B,sBAAgB;AAAA,IAClB,OAAO;AACL,WAAK,aAAa,KAAK,eAAe;AAAA,IACxC;AACA,SAAK,eAAe;AACpB,MAAE;AACF,UAAM,8BAA8B,aAAa,QAAQ,KAAK,aAAa,IAAI,CAAC,MAAM,EAAE,KAAK,CAAC,EAAE,OAAO,CAAC,MAAM,KAAK,IAAI;AACvH,UAAM,4BAA4B,aAAa,QAAQ,KAAK,aAAa,IAAI,CAAC,MAAM,EAAE,IAAI,CAAC,EAAE,OAAO,CAAC,MAAM,KAAK,IAAI;AACpH,SAAK,eAAe;AACpB,QAAI,eAAe;AACjB,WAAK,qBAAqB;AAAA,IAC5B;AACA,UAAM,MAAM;AAAA,MACV,cAAc,KAAK;AAAA,MACnB,gBAAgB,KAAK;AAAA,MACrB,UAAU;AAAA,MACV,QAAQ;AAAA,IACV;AACA,UAAM,WAAW,MAAM,QAAQ,IAAI,2BAA2B;AAC9D,QAAI,cAAc,aAAa,IAAI,QAAQ;AAC3C,QAAI,yBAAyB,MAAM,SAAS,IAAI,CAAC,GAAG,QAAQ,EAAE,MAAM,0BAA0B,KAAK,IAAI,EAAE,EAAE,EAAE,IAAI,CAAC,MAAM,GAAG,EAAE,SAAS,EAAE,IAAI,EAAE,KAAK,IAAI;AACvJ,SAAK,eAAe;AACpB,SAAK,iBAAiB;AACtB,WAAO;AAAA,EACT;AAAA,EACA,eAAe,OAAO,OAAO,QAAQ;AACnC,QAAI,UAAU,YAAY,UAAU,QAAQ,OAAO,SAAS,KAAK,aAAa,SAAS,OAAO,EAAE,GAAG;AACjG,eAAS,OAAO,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC;AAAA,IACzD;AACA,UAAM,SAAS,KAAK,MAAM,QAAQ,OAAO,KAAK;AAC9C,WAAO,EAAE,QAAQ,OAAO,MAAM;AAAA,EAChC;AAAA,EACA,gBAAgB,SAAS;AACvB,QAAI,CAAC,SAAS;AACZ,aAAO;AAAA,IACT;AACA,UAAM,aAAa,KAAK,UAAU,IAAI,QAAQ,MAAM;AACpD,QAAI,aAAa,WAAW,cAAc;AACxC,YAAM,OAAO,WAAW;AACxB,UAAI,KAAK,mBAAmB,oBAAoB;AAC9C,eAAO,KAAK;AAAA,MACd,OAAO;AACL,eAAO,KAAK,QAAQ,WAAW;AAAA,MACjC;AAAA,IACF;AACA,UAAM,aAAa,WAAW;AAC9B,WAAO,EAAE,QAAQ,GAAG,MAAM,WAAW,MAAM,QAAQ,WAAW,OAAO;AAAA,EACvE;AAAA,EACA,MAAM,aAAa,OAAO;AACxB,QAAI,KAAK,kBAAkB;AACzB,aAAO,KAAK,oBAAoB,KAAK;AAAA,IACvC,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,YAAY,QAAQ;AAClB,UAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,QAAI,WAAW,cAAc;AAC3B;AAAA,IACF;AACA,UAAMA,QAAO,mBAAmB,WAAW,KAAK,IAAI,aAAa,cAAc,WAAW,KAAK;AAC/F,UAAM,UAAU,KAAK,cAAc,cAAcA,OAAM,KAAK,sBAAsB,CAAC;AACnF,eAAW,eAAe,EAAE,MAAAA,OAAM,OAAO,KAAK,sBAAsB,GAAG,QAAQ,QAAQ;AACvF,QAAI,WAAW,QAAQ;AACrB,YAAM,gBAAgB,KAAK,cAAc,oBAAoBA,OAAM,eAAe,YAAY,eAAe,QAAQ;AACrH,YAAM,cAAc,cAAc,eAAe;AACjD,UAAI,WAAW,UAAU,WAAW,WAAW,UAAU,QAAQ;AAC/D,YAAI,WAAW,WAAW,EAAE,IAAI,WAAW,MAAM;AAAA,MACnD,OAAO;AACL,YAAI,aAAa,WAAW,EAAE,IAAI,WAAW,MAAM;AAAA,MACrD;AACA,oBAAc,MAAM;AACpB,WAAK,0BAA0B;AAC/B,WAAK,uBAAuB;AAC5B,WAAK,sBAAsB,mBAAmB,eAAe,GAAG,SAAS,GAAGA,KAAI;AAChF,YAAM,cAAc;AAAA,QAClB,MAAAA;AAAA,QACA,OAAO,eAAe,YAAY,eAAe;AAAA,QACjD,QAAQ;AAAA,MACV;AACA,WAAK,uBAAuB,KAAK,WAAW;AAAA,IAC9C;AAAA,EACF;AAAA,EACA,aAAa,gBAAgB;AAC3B,QAAI,gBAAgB;AACpB,QAAI,YAAY;AAChB,UAAM,UAAU,CAAC;AACjB,mBAAe,QAAQ,CAAC,MAAM;AAC5B,UAAI,EAAE,KAAK,WAAW,GAAG;AACvB,UAAE,OAAO,CAAC,CAAC;AAAA,MACb;AACA,UAAI;AACJ,cAAQ,EAAE,KAAK;AAAA,aACR;AACH,0BAAgB;AAChB;AAAA,aACG;AACH,0BAAgB;AAChB;AAAA,aACG;AACH,0BAAgB;AAChB;AAAA,aACG;AACH,0BAAgB;AAChB;AAAA,aACG;AACH,0BAAgB;AAChB;AAAA,aACG;AACH,0BAAgB;AAChB;AAAA;AAEA,uBAAa,OAAO,OAAO,MAAM,eAAe,EAAE,KAAK,eAAe;AAAA;AAE1E,UAAI,cAAc,KAAK,cAAc,GAAG;AACtC,wBAAgB;AAAA,MAClB;AACA,sBAAgB,KAAK,KAAK,gBAAgB,aAAa,IAAI;AAC3D,kBAAY,EAAE,KAAK;AACnB,cAAQ,KAAK,aAAa;AAC1B,uBAAiB,EAAE,KAAK,SAAS;AAAA,IACnC,CAAC;AACD,UAAM,cAAc,IAAI,YAAY,aAAa;AACjD,mBAAe,QAAQ,CAAC,GAAG,OAAO;AAChC,YAAM,SAAS,QAAQ;AACvB,UAAI,EAAE,SAAS,SAAS;AACtB,YAAI,WAAW,aAAa,QAAQ,EAAE,KAAK,MAAM,EAAE,IAAI,EAAE,IAAI;AAAA,MAC/D,WAAW,EAAE,SAAS,UAAU;AAC9B,YAAI,YAAY,aAAa,QAAQ,EAAE,KAAK,MAAM,EAAE,IAAI,EAAE,IAAI;AAAA,MAChE,OAAO;AACL,YAAI,aAAa,aAAa,QAAQ,EAAE,KAAK,MAAM,EAAE,IAAI,EAAE,IAAI;AAAA,MACjE;AAAA,IACF,CAAC;AACD,UAAM,gBAAgB,KAAK,cAAc,cAAc,eAAe,eAAe,WAAW,eAAe,OAAO;AACtH,SAAK,MAAM,YAAY,eAAe,GAAG,aAAa,GAAG,aAAa;AACtE,UAAM,cAAc;AAAA,MAClB,MAAM;AAAA,MACN,OAAO,eAAe,WAAW,eAAe;AAAA,MAChD,QAAQ;AAAA,IACV;AACA,SAAK,uBAAuB,KAAK,WAAW;AAC5C,WAAO,EAAE,QAAQ,GAAG,MAAM,eAAe,QAAQ,cAAc;AAAA,EACjE;AAAA,EACA,iBAAiB,SAAS,QAAQ,aAAa,uBAAuB,QAAQ;AAC5E,QAAI,CAAC,QAAQ;AACX,eAAS,KAAK,eAAe,QAAQ,aAAa,WAAW;AAAA,IAC/D;AACA,QAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,WAAK,UAAU,IAAI,OAAO,MAAM,EAAE,SAAS,aAAa,uBAAuB,OAAO,OAAO,CAAC;AAC9F,aAAO;AAAA,IACT;AACA,SAAK,YAAY,OAAO,MAAM;AAC9B,YAAQ,WAAW,gBAAgB,KAAK,QAAQ,OAAO;AACvD,QAAI,iBAAiB,CAAC;AACtB,QAAI,eAAe,CAAC;AACpB,QAAI,CAAC,QAAQ,cAAc;AACzB,qBAAe,KAAK,EAAE,MAAM,WAAW,MAAM,CAAC,GAAG,EAAE,CAAC;AACpD,qBAAe,OAAO,OAAO,MAAM,EAAE,IAAI,CAAC,MAAM,EAAE,KAAK;AACvD,YAAM,eAAe;AACrB,mBAAa,IAAI,CAAC,MAAM;AACtB,uBAAe,KAAK,EAAE,MAAM,cAAc,MAAM,EAAE,CAAC;AAAA,MACrD,CAAC;AACD,YAAMY,WAAU,aAAa,eAAe,OAAO,KAAK;AACxD,qBAAe,KAAK,EAAE,MAAM,cAAc,MAAMA,SAAQ,CAAC;AACzD,UAAI,QAAQ,MAAM;AAChB,cAAMZ,QAAO,aAAa,cAAc,QAAQ,WAAW;AAC3D,uBAAe,KAAK,EAAE,MAAM,cAAc,MAAM,CAAC,QAAQ,SAASA,QAAO,IAAIA,KAAI,EAAE,CAAC;AAAA,MACtF;AAAA,IACF;AACA,UAAM,aAAa,OAAO,IAAI,CAAC,QAAQ,OAAO;AAC5C,UAAI,OAAO,UAAU,aAAa;AAChC,cAAM,IAAI,MAAM,iIAAiI;AAAA,MACnJ;AACA,WAAK,YAAY,OAAO,MAAM;AAC9B,aAAO;AAAA,QACL,OAAO,KAAK,UAAU,IAAI,OAAO,MAAM,EAAE;AAAA,QACzC,OAAO,OAAO;AAAA,QACd,MAAM,QAAQ,cAAc;AAAA,MAC9B;AAAA,IACF,CAAC;AACD,UAAM,MAAM,eAAe,SAAS,cAAc,YAAY,MAAM;AACpE,QAAI;AACJ,QAAI,OAAO,KAAK,eAAe;AAC7B,iBAAW,KAAK,cAAc;AAAA,IAChC,OAAO;AACL,iBAAW,gBAAgB,KAAK,QAAQ,SAAS,YAAY,MAAM;AACnE,WAAK,cAAc,OAAO;AAAA,IAC5B;AACA,QAAI,uBAAuB;AACzB,uBAAiB,CAAC,GAAG,gBAAgB,GAAG,qBAAqB;AAAA,IAC/D;AACA,UAAM,WAAW;AAAA,MACf,KAAK,gBAAgB,MAAM;AAAA,MAC3B,GAAG,OAAO,IAAI,CAAC,OAAO,KAAK,gBAAgB,EAAE,CAAC;AAAA,MAC9C,KAAK,aAAa,cAAc;AAAA,IAClC;AACA,UAAM,YAAY,KAAK,OAAO,gBAAgB;AAAA,MAC5C,QAAQ,SAAS,mBAAmB,CAAC;AAAA,MACrC,SAAS,SAAS,IAAI,CAAC,GAAG,QAAQ,EAAE,SAAS,IAAI,UAAU,EAAE,EAAE;AAAA,IACjE,CAAC;AACD,SAAK,0BAA0B;AAC/B,UAAM,OAAO,KAAK,eAAe;AACjC,UAAM,oBAAoB,KAAK,gBAAgB;AAC/C,QAAI,mBAAmB;AACrB,UAAI,KAAK,kBAAkB;AACzB,aAAK,eAAe,KAAK,UAAU,CAAC;AAAA,MACtC;AAAA,IACF;AACA,SAAK,YAAY,QAAQ;AACzB,SAAK,aAAa,GAAG,SAAS;AAC9B,SAAK,mBAAmB,QAAQ,SAAS,IAAI,QAAQ,SAAS,IAAI,QAAQ,SAAS,EAAE;AACrF,QAAI,mBAAmB;AACrB,UAAI,KAAK,kBAAkB;AACzB,aAAK,eAAe,KAAK,UAAU,CAAC;AAAA,MACtC;AAAA,IACF;AACA,SAAK;AACL,WAAO,QAAQ,CAAC,WAAW;AACzB,WAAK,qBAAqB,IAAI,OAAO,MAAM;AAAA,IAC7C,CAAC;AACD,SAAK,qBAAqB,IAAI,OAAO,MAAM;AAC3C,QAAI,IAAI,EAAE,IAAI,mCAAmC,KAAK,KAAK,yBAAyB;AAClF,WAAK,YAAY;AAAA,IACnB;AACA,QAAI,mBAAmB;AACrB,WAAK,aAAa,KAAK;AAAA,QACrB,MAAM,QAAQ,YAAY;AAAA,QAC1B,OAAO,KAAK,aAAa,KAAK,QAAQ;AAAA,MACxC,CAAC;AAAA,IACH;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,oBAAoB,UAAU;AAClC,UAAM,cAAc,KAAK,cAAc,cAAc,IAAI,eAAe,WAAW,eAAe,aAAa;AAC/G,UAAM,MAAM,KAAK,cAAc,cAAc,IAAI,eAAe,WAAW,eAAe,QAAQ;AAClG,SAAK,0BAA0B;AAC/B,SAAK,uBAAuB;AAC5B,SAAK,sBAAsB,gBAAgB,UAAU,GAAG,GAAG,aAAa,CAAC;AACzE,SAAK,sBAAsB,mBAAmB,aAAa,GAAG,KAAK,GAAG,EAAE;AACxE,SAAK,YAAY;AACjB,UAAM,IAAI,SAAS,WAAW,IAAI;AAClC,UAAM,WAAW,IAAI,eAAe,IAAI,eAAe,CAAC;AACxD,UAAM,mBAAmB,OAAO,SAAS,KAAK,SAAS,EAAE;AACzD,QAAI,MAAM;AACV,SAAK,cAAc,cAAc,KAAK,IAAI,eAAe,WAAW,eAAe,QAAQ;AAC3F,SAAK,cAAc,cAAc,aAAa,IAAI,eAAe,WAAW,eAAe,aAAa;AACxG,WAAO,mBAAmB;AAAA,EAC5B;AAAA,EACA,mBAAmB,QAAQ,gBAAgB,6BAA6B;AACtE,WAAO,IAAI,EAAE,QAAQ,oBAAoB,KAAK,OAAO,MAAM,CAAC,WAAW,KAAK,UAAU,IAAI,OAAO,MAAM,EAAE,gBAAgB,QAAQ,aAAa,cAAc,OAAO,KAAK,IAAI,aAAa;AAAA,EAC3L;AAAA,EACA,aAAa;AACX,WAAO,KAAK,UAAU,WAAW,IAAI,KAAK,0BAA0B;AAAA,EACtE;AAAA,EACA,UAAU;AACR,QAAI,KAAK,UAAU;AACjB;AAAA,IACF;AACA,SAAK,cAAc,QAAQ;AAC3B,SAAK,eAAe,QAAQ;AAC5B,SAAK,WAAW;AAAA,EAClB;AACF;AACA,cAAc,aAAa;AAG3B,IAAI,iBAAiB,CAAC;AACtBH,UAAS,gBAAgB;AAAA,EACvB,eAAe,MAAM;AAAA,EACrB,aAAa,MAAM;AACrB,CAAC;AAGD,IAAI,kBAAkB,GAAG;AACvB,kBAAgB,UAAU,YAAY;AACpC,QAAI,EAAE,IAAI,gCAAgC,KAAK;AAC/C,UAAM,gBAAgB;AAAA,MACpB,iBAAiB,IAAI,EAAE,IAAI,0BAA0B,IAAI,cAAc;AAAA,IACzE;AACA,UAAM,UAAU,MAAM,UAAU,IAAI,eAAe,aAAa;AAChE,UAAM,gBAAgB,QAAQ;AAC9B,UAAM,mBAAmB,CAAC;AAC1B,UAAM,mBAAmB,QAAQ,SAAS,IAAI,iBAAiB;AAC/D,qBAAiB,iBAAiB;AAAA,MAChC,kCAAkC,cAAc;AAAA,MAChD,oCAAoC,cAAc;AAAA,MAClD,+BAA+B,cAAc;AAAA,IAC/C;AACA,QAAI,kBAAkB;AACpB,uBAAiB,mBAAmB,CAAC,iBAAiB;AAAA,IACxD,OAAO;AACL,cAAQ,KAAK,wUAAwU;AAAA,IACvV;AACA,UAAM,SAAS,MAAM,QAAQ,cAAc,gBAAgB;AAC3D,WAAO,IAAI,cAAc,QAAQ,gBAAgB;AAAA,EACnD,GAAG,CAAC;AACN;AAGA,IAAI,IAAI;AACR,IAAI,IAAI;AACR,IAAI,IAAI;AACR,IAAI,IAAI;AACR,IAAI,IAAI;AACR,IAAI,IAAI;AACR,IAAI,IAAI;AACR,IAAI,IAAI,EAAE,MAAM,GAAG,aAAa,GAAG,aAAa,GAAG,eAAe,GAAG,kBAAkB,GAAG,sBAAsB,GAAG,qBAAqB,EAAE;;;AC79xEnI,IAAM,iBAAiB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAqBvB,IAAM,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAc7B,IAAM,0BAA0B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAchC,IAAM,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAejB,IAAM,OAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAyBb,IAAM,cAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;;;AChF3B,IAAM,UAAU,CAAC,QAAQ,QAAQ,eAAe;AAC9C,QAAMyC,KAAI,IAAI,OAAO,QAAQ,SAAS,gBAAgB,IAAI;AAC1D,SAAO,QAAQA,IAAG,CAACC,QAAO,SAAS;AACjC,eAAW,QAAQ;AACnB,WAAOA;AAAA,EACT,CAAC;AACH;AAEA,IAAM,YAAN,MAAgB;AAAA,EAMd,YAAY,IAAI,cAAc,gBAAgB;AAL9C,mCAAU,CAAC;AACX,qCAAY,CAAC;AACb;AACA;AA2BA,mCAAU,CAAC,QAAQ,SAA6B;AAC9C,YAAM,SAAS,KAAK,GAAG,aAAa,IAAI;AACxC,UAAI,CAAC,QAAQ;AACX,YAAI,iCAAiC;AACrC,eAAO;AAAA,MACT;AACA,WAAK,GAAG,aAAa,QAAQ,MAAM;AACnC,WAAK,GAAG,cAAc,MAAM;AAC5B,UAAI,CAAC,KAAK,GAAG,mBAAmB,QAAQ,KAAK,GAAG,cAAc,GAAG;AAC/D,YAAI,8BAA8B,KAAK,GAAG,iBAAiB,MAAM,GAAG;AACpE,eAAO;AAAA,MACT;AACA,aAAO;AAAA,IACT;AArCE,SAAK,KAAK;AACV,UAAM,eAAe,KAAK,QAAQ,cAAc,KAAK,GAAG,aAAa;AACrE,UAAM,iBAAiB,KAAK,QAAQ,gBAAgB,KAAK,GAAG,eAAe;AAC3E,SAAK,KAAK,KAAK,GAAG,cAAc;AAChC,QAAI,CAAC,gBAAgB,CAAC;AAAgB;AACtC,QAAI,CAAC,KAAK,IAAI;AACZ,UAAI,wCAAwC;AAC5C;AAAA,IACF;AACA,SAAK,GAAG,aAAa,KAAK,IAAI,YAAY;AAC1C,SAAK,GAAG,aAAa,KAAK,IAAI,cAAc;AAC5C,SAAK,GAAG,YAAY,KAAK,EAAE;AAC3B,QAAI,CAAC,KAAK,GAAG,oBAAoB,KAAK,IAAI,KAAK,GAAG,WAAW,GAAG;AAC9D,UAAI,2BAA2B,KAAK,GAAG,kBAAkB,KAAK,EAAE,GAAG;AACnE;AAAA,IACF;AACA,SAAK,GAAG,WAAW,KAAK,EAAE;AAC1B,YAAQ,cAAc,aAAa,KAAK,SAAS;AACjD,eAAW,KAAK,KAAK;AAAW,WAAK,UAAU,KAAK,KAAK,GAAG,kBAAkB,KAAK,IAAI,CAAC;AACxF,YAAQ,cAAc,WAAW,KAAK,OAAO;AAC7C,YAAQ,gBAAgB,WAAW,KAAK,OAAO;AAC/C,eAAW,KAAK,KAAK;AAAS,WAAK,QAAQ,KAAK,KAAK,GAAG,mBAAmB,KAAK,IAAI,CAAC;AAAA,EACvF;AAgBF;AAWO,SAAS,gBAAgB;AAC9B,MAAI,YAAY;AAChB,MAAI,gBAAqC;AACzC,MAAI,cAAc;AAClB,MAAI,0BAA0B;AAC9B,MAAI,mBAAoG,CAAC,MAAM,IAAI;AACnH,MAAI,cAAyC,CAAC;AAC9C,MAAI,eAAmC;AACvC,MAAI,iBAAmC;AACvC,QAAM,WAAW,OAAO,KAAK,GAAG;AAChC,QAAM,qBAAqB,CAAE;AAC7B,QAAM,OAAO,EAAE,cAAc,EAAE;AAC/B,QAAM,KAAK,SAAS,WAAW,OAAO;AACtC,MAAI,CAAC,IAAI;AACP,QAAI,kCAAkC;AACtC;AAAA,EACF;AAEA,OAAK,KAAK;AAEV,WAAS,OAAO,OAAO,QAAQ;AAC7B,QAAI,UAAU,SAAS,SAAS,WAAW,SAAS;AAAQ;AAC5D,aAAS,QAAQ;AACjB,aAAS,SAAS;AAClB,QAAI,CAAC,cAAc;AACjB,YAAM,WAAW,IAAI,aAAa,CAAC,IAAI,IAAI,GAAG,GAAG,GAAG,IAAI,GAAG,GAAG,IAAI,GAAG,GAAG,GAAG,IAAI,GAAG,GAAG,GAAG,GAAG,IAAI,GAAG,GAAG,GAAG,GAAG,GAAG,CAAC,CAAC;AAChH,qBAAe,GAAG,aAAa;AAC/B,SAAG,WAAW,GAAG,cAAc,YAAY;AAC3C,SAAG,WAAW,GAAG,cAAc,UAAU,GAAG,WAAW;AACvD,SAAG,YAAY,GAAG,gCAAgC,IAAI;AAAA,IACxD;AACA,OAAG,SAAS,GAAG,GAAG,SAAS,OAAO,SAAS,MAAM;AACjD,uBAAmB,CAAC,MAAM,IAAI;AAAA,EAChC;AAEA,WAAS,yBAAyB,OAAO,QAAQ;AAC/C,UAAM,MAAM,GAAG,kBAAkB;AACjC,OAAG,gBAAgB,GAAG,aAAa,GAAG;AACtC,UAAM,eAAe,GAAG,mBAAmB;AAC3C,OAAG,iBAAiB,GAAG,cAAc,YAAY;AACjD,UAAM,UAAU,GAAG,cAAc;AACjC,OAAG,YAAY,GAAG,YAAY,OAAO;AACrC,OAAG,WAAW,GAAG,YAAY,GAAG,GAAG,MAAM,OAAO,QAAQ,GAAG,GAAG,MAAM,GAAG,eAAe,IAAI;AAC1F,OAAG,cAAc,GAAG,YAAY,GAAG,oBAAoB,GAAG,MAAM;AAChE,OAAG,cAAc,GAAG,YAAY,GAAG,oBAAoB,GAAG,MAAM;AAChE,OAAG,cAAc,GAAG,YAAY,GAAG,gBAAgB,GAAG,aAAa;AACnE,OAAG,cAAc,GAAG,YAAY,GAAG,gBAAgB,GAAG,aAAa;AACnE,OAAG,qBAAqB,GAAG,aAAa,GAAG,mBAAmB,GAAG,YAAY,SAAS,CAAC;AACvF,OAAG,YAAY,GAAG,YAAY,IAAI;AAClC,OAAG,gBAAgB,GAAG,aAAa,IAAI;AACvC,WAAO,EAAE,KAAK,QAAQ;AAAA,EACxB;AAEA,WAAS,mBAAmBC,QAAuE;AACjG,qBAAiBA,UAAS,iBAAiBA,WAAU,yBAAyB,SAAS,OAAO,SAAS,MAAM;AAC7G,WAAO,iBAAiBA;AAAA,EAC1B;AAEA,WAAS,KAAK,QAAQ,GAAG;AACvB,QAAI,CAAC;AAAgB;AACrB,QAAI,SAA8B;AAClC,QAAI,SAAkC;AACtC,QAAI,QAAQ;AACZ,QAAI,cAAc;AAAG,eAAS;AAAA;AACzB,eAAS,mBAAmB,uBAAuB,EAAE,WAAW;AACrE;AACA,QAAI,eAAe,EAAE,QAAQ,KAAK,eAAe;AAC/C,eAAS;AACT,cAAQ,YAAY,MAAM;AAAA,IAC5B,OAAO;AACL,iCAA2B,0BAA0B,KAAK;AAC1D,eAAS,mBAAmB,uBAAuB,EAAE,OAAO;AAAA,IAC9D;AACA,OAAG,YAAY,GAAG,YAAY,MAAM;AACpC,OAAG,gBAAgB,GAAG,aAAa,MAAM;AACzC,OAAG,UAAU,eAAe,QAAQ,UAAW,QAAQ,KAAK,CAAE;AAC9D,OAAG,WAAW,GAAG,WAAW,GAAG,CAAC;AAAA,EAClC;AAEA,WAAS,cAAc,gBAAkC;AACvD,QAAI,mBAAmB,iBAAiB;AACtC,uBAAiB,mBAAmB;AACpC,SAAG,YAAY,iBAAiB,eAAe,KAAK,SAAS,IAAI;AACjE,aAAO;AAAA,IACT;AACA,qBAAiB,IAAI,UAAU,IAAY,gBAAgB,cAAc;AACzE,QAAI,CAAC,gBAAgB;AACnB,UAAI,qCAAqC;AACzC,aAAO;AAAA,IACT;AACA,UAAM,YAAY,aAAa;AAC/B,UAAM,WAAW,IAAI;AACrB,OAAG,wBAAwB,eAAe,UAAU,MAAM;AAC1D,OAAG,oBAAoB,eAAe,UAAU,QAAQ,GAAG,GAAG,OAAO,OAAO,UAAU,IAAI,SAAS;AACnG,OAAG,wBAAwB,eAAe,UAAU,KAAK;AACzD,OAAG,oBAAoB,eAAe,UAAU,OAAO,GAAG,GAAG,OAAO,OAAO,UAAU,IAAI,SAAS;AAClG,uBAAmB,kBAAkB;AACrC,WAAO;AAAA,EACT;AAEA,QAAM,SAAS;AAAA,IACb,aAAa,CAAC,WAAW;AACvB,YAAM,IAAI,IAAI,aAAa,MAAM;AACjC,QAAE,MAAM;AACR,QAAE,MAAM;AACR,QAAE,OAAO;AACT,QAAE,OAAO;AACT,YAAM,SAAU,EAAE,QAAQ,KAAK,EAAE,OAAO,KAAK,EAAE,OAAO,KAAK,EAAE,QAAQ,KAAK,EAAE,QAAQ,KAAK,EAAE,QAAQ,KAAK,EAAE,QAAQ,KAAK,EAAE,QAAQ,IACrH,0BACA;AACZ,YAAM,UAAU,cAAc,MAAM;AACpC,UAAI,CAAC;AAAS;AACd,SAAG,WAAW,QAAQ,QAAQ,MAAM,CAAC;AACrC,WAAK;AAAA,IACP;AAAA,IAEA,YAAY,CAAC,eAAe;AAC1B,YAAM,KAAK,cAAc,KAAK;AAC9B,aAAO,YAAY;AAAA,QACjB;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,YAAY,CAAC,WAAW;AACtB,YAAM,KAAK,UAAU,KAAK,IAAI,IAAI;AAClC,YAAM,KAAM,IAAI,KAAK;AACrB,aAAO,YAAY;AAAA,QACjB;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,YAAY,MAAM;AAChB,aAAO,WAAW,EAAE;AAAA,IACtB;AAAA,IAEA,UAAU,CAAC,WAAW;AACpB,YAAM,KAAK,UAAU,KAAK;AAC1B,YAAM,IAAI,QAAQ,IAAI;AACtB,aAAO,YAAY;AAAA,QACjB;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,UAAU,MAAM;AACd,aAAO,SAAS,EAAE;AAAA,IACpB;AAAA,IAEA,KAAK,CAAC,aAAa;AACjB,kBAAY,YAAY,KAAK,MAAM,KAAK;AACxC,YAAMC,OAAM,KAAK,IAAI,QAAQ;AAC7B,YAAMC,OAAM,KAAK,IAAI,QAAQ;AAC7B,YAAM,OAAO;AACb,YAAM,OAAO;AACb,YAAM,OAAO;AACb,aAAO,YAAY;AAAA,QACjB,OAAOD,QAAO,IAAI,QAAQC,OAAO,CAAC;AAAA,QAAO,OAAOD,OAAO,CAAC,OAAQC,OAAO,CAAC;AAAA,QAAO,OAAOD,OAAO,CAAC,OAAQC,QAAO,IAAI;AAAA,QAAO;AAAA,QAAG;AAAA,QAC3H,OAAOD,OAAO,CAAC,OAAQC,OAAO;AAAA,QAAQ,OAAOD,QAAO,IAAI,QAAQC,OAAO;AAAA,QAAQ,OAAOD,OAAO,CAAC,OAAQC,OAAO;AAAA,QAAS;AAAA,QAAG;AAAA,QACzH,OAAOD,OAAO,CAAC,OAAQC,OAAO,EAAE,IAAI;AAAA,QAAQ,OAAOD,OAAO,CAAC,OAAQC,OAAO;AAAA,QAAO,OAAOD,QAAO,IAAI,QAAQC,OAAO;AAAA,QAAO;AAAA,QAAG;AAAA,QAC5H;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,qBAAqB,MAAM;AACzB,aAAO,YAAY;AAAA,QACjB;AAAA,QAAW;AAAA,QAAW;AAAA,QAAW;AAAA,QAAG;AAAA,QACpC;AAAA,QAAW;AAAA,QAAW;AAAA,QAAW;AAAA,QAAG;AAAA,QACpC;AAAA,QAAW;AAAA,QAAW;AAAA,QAAW;AAAA,QAAG;AAAA,QACpC;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,OAAO,MAAM;AACX,aAAO,YAAY;AAAA,QACjB;AAAA,QAAO;AAAA,QAAW;AAAA,QAAY;AAAA,QAAG;AAAA,QACjC;AAAA,QAAO;AAAA,QAAW;AAAA,QAAY;AAAA,QAAG;AAAA,QACjC;AAAA,QAAO;AAAA,QAAW;AAAA,QAAY;AAAA,QAAG;AAAA,QACjC;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,SAAS,MAAM;AACb,aAAO,YAAY;AAAA,QACjB;AAAA,QAAoB;AAAA,QAAqB;AAAA,QAAqB;AAAA,QAAG;AAAA,QACjE;AAAA,QAAuB;AAAA,QAAoB;AAAA,QAAqB;AAAA,QAAG;AAAA,QACnE;AAAA,QAAqB;AAAA,QAAsB;AAAA,QAAqB;AAAA,QAAG;AAAA,QACnE;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,gBAAgB,MAAM;AACpB,aAAO,YAAY;AAAA,QACjB;AAAA,QAAoB;AAAA,QAAoB;AAAA,QAAsB;AAAA,QAAG;AAAA,QACjE;AAAA,QAAqB;AAAA,QAAoB;AAAA,QAAqB;AAAA,QAAG;AAAA,QACjE;AAAA,QAAoB;AAAA,QAAqB;AAAA,QAAoB;AAAA,QAAG;AAAA,QAChE;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,YAAY,MAAM;AAChB,aAAO,YAAY;AAAA,QACjB;AAAA,QAAoB;AAAA,QAAqB;AAAA,QAAsB;AAAA,QAAG;AAAA,QAClE;AAAA,QAAsB;AAAA,QAAoB;AAAA,QAAsB;AAAA,QAAG;AAAA,QACnE;AAAA,QAAsB;AAAA,QAAqB;AAAA,QAAoB;AAAA,QAAG;AAAA,QAClE;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,aAAa,MAAM;AACjB,aAAO,YAAY;AAAA,QACjB;AAAA,QAAoB;AAAA,QAAqB;AAAA,QAAsB;AAAA,QAAG;AAAA,QAClE;AAAA,QAAqB;AAAA,QAAoB;AAAA,QAAsB;AAAA,QAAG;AAAA,QAClE;AAAA,QAAoB;AAAA,QAAqB;AAAA,QAAmB;AAAA,QAAG;AAAA,QAC/D;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,UAAU,MAAM;AACd,aAAO,YAAY;AAAA,QACjB;AAAA,QAAO;AAAA,QAAQ;AAAA,QAAQ;AAAA,QAAG;AAAA,QAC1B;AAAA,QAAQ;AAAA,QAAO;AAAA,QAAQ;AAAA,QAAG;AAAA,QAC1B;AAAA,QAAQ;AAAA,QAAQ;AAAA,QAAO;AAAA,QAAG;AAAA,QAC1B;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,YAAY,MAAM;AAChB,aAAO,YAAY;AAAA,QACjB;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,aAAa,CAAC,WAAW;AACvB,YAAM,IAAI,IAAI,aAAa,MAAM;AACjC,YAAM,aAAa,IAAI,SAAS;AAChC,YAAM,aAAa,IAAI,SAAS;AAChC,YAAM,UAAU,cAAsB,WAAW;AACjD,UAAI,CAAC;AAAS;AACd,SAAG,WAAW,QAAQ,QAAQ,MAAM,CAAC;AACrC,SAAG,UAAU,QAAQ,QAAQ,OAAO,YAAY,UAAU;AAC1D,WAAK;AAAA,IACP;AAAA,IAEA,aAAa,MAAM;AAEjB,aAAO,YAAY,KAAK,MAAM;AAAA,QAC5B;AAAA,QAAG;AAAA,QAAG;AAAA,QACN;AAAA,QAAG;AAAA,QAAI;AAAA,QACP;AAAA,QAAG;AAAA,QAAG;AAAA,MACR,CAAC;AAAA,IACH;AAAA,IAEA,QAAQ,MAAM;AAEZ,aAAO,YAAY,KAAK,MAAM;AAAA,QAC5B;AAAA,QAAI;AAAA,QAAG;AAAA,QACP;AAAA,QAAI;AAAA,QAAG;AAAA,QACP;AAAA,QAAI;AAAA,QAAG;AAAA,MACT,CAAC;AAAA,IACH;AAAA,IAEA,QAAQ,MAAM;AAEZ,aAAO,YAAY,KAAK,MAAM;AAAA,QAC5B;AAAA,QAAI;AAAA,QAAI;AAAA,QACR;AAAA,QAAG;AAAA,QAAG;AAAA,QACN;AAAA,QAAG;AAAA,QAAG;AAAA,MACR,CAAC;AAAA,IACH;AAAA,IAEA,SAAS,CAAC,WAAW;AACnB,YAAM,IAAI,UAAU;AAEpB,aAAO,YAAY,KAAK,MAAM;AAAA,QAC5B;AAAA,QAAG,KAAK;AAAA,QAAG;AAAA,QACX,KAAK;AAAA,QAAG,IAAI,IAAI;AAAA,QAAG,KAAK;AAAA,QACxB;AAAA,QAAG,KAAK;AAAA,QAAG;AAAA,MACb,CAAC;AAAA,IACH;AAAA,IAEA,QAAQ,CAACC,UAAS;AAChB,YAAMC,KAAID,SAAQ;AAElB,aAAO,YAAY,KAAK,MAAM;AAAA,QAC5B,KAAKC;AAAA,QAAG,KAAKA;AAAA,QAAG;AAAA,QAChB,KAAKA;AAAA,QAAG;AAAA,QAAG,IAAIA;AAAA,QACf;AAAA,QAAG,IAAIA;AAAA,QAAG,IAAIA;AAAA,MAChB,CAAC;AAAA,IACH;AAAA,IAEA,MAAM,CAACD,UAAS;AACd,YAAM,YAAaA,QAAO,IAAK,SAAS;AACxC,YAAM,YAAaA,QAAO,IAAK,SAAS;AACxC,YAAM,UAAU,cAAsB,IAAI;AAC1C,UAAI,CAAC;AAAS;AAEd,SAAG,UAAU,QAAQ,QAAQ,OAAO,GAAG,SAAS;AAChD,WAAK,KAAK,YAAY;AAEtB,SAAG,UAAU,QAAQ,QAAQ,OAAO,WAAW,CAAC;AAChD,WAAK;AAAA,IACP;AAAA,IAEA,UAAU,CAACA,UAAS;AAClB,YAAM,YAAaA,QAAQ,SAAS;AACpC,YAAM,YAAaA,QAAQ,SAAS;AACpC,YAAM,UAAU,cAAsB,QAAQ;AAC9C,UAAI,CAAC;AAAS;AACd,SAAG,UAAU,QAAQ,QAAQ,SAAS,WAAW,SAAS;AAC1D,WAAK;AAAA,IACP;AAAA,EACF;AAGA,OAAK,MAAM,SAAU,MAAM;AAEzB,UAAM,OAAO,MAAM,UAAU,MAAM,KAAK,WAAW,CAAC;AACpD,UAAME,QAAO,OAAO;AACpB,gBAAY,KAAK,EAAE,MAAAA,OAAM,KAAK,CAAC;AAAA,EACjC;AAGA,OAAK,QAAQ,WAAY;AACvB,kBAAc,CAAC;AAAA,EACjB;AAGA,OAAK,MAAM,WAAY;AACrB,WAAO;AAAA,EACT;AAGA,OAAK,QAAQ,SAAUC,QAAO;AAC5B,WAAOA,OAAM,OAAOA,OAAM,MAAM;AAChC,gBAAY;AACZ,QAAI,CAAC;AAAe,sBAAgB,GAAG,cAAc;AACrD,OAAG,YAAY,GAAG,YAAY,aAAa;AAC3C,OAAG,cAAc,GAAG,YAAY,GAAG,gBAAgB,GAAG,aAAa;AACnE,OAAG,cAAc,GAAG,YAAY,GAAG,gBAAgB,GAAG,aAAa;AACnE,OAAG,cAAc,GAAG,YAAY,GAAG,oBAAoB,GAAG,OAAO;AACjE,OAAG,cAAc,GAAG,YAAY,GAAG,oBAAoB,GAAG,OAAO;AACjE,OAAG,WAAW,GAAG,YAAY,GAAG,GAAG,MAAM,GAAG,MAAM,GAAG,eAAeA,MAAK;AACzE,aAASC,KAAI,GAAGA,KAAI,YAAY,QAAQA,MAAK;AAC3C,oBAAeA,OAAM,YAAY,SAAS;AAC1C,YAAM,IAAI,YAAYA;AAEtB,QAAE,KAAK,MAAM,MAAM,EAAE,QAAQ,CAAC,CAAC;AAAA,IACjC;AACA,WAAO;AAAA,EACT;AAGA,OAAK,OAAO,SAAUD,QAAO;AAC3B,SAAK,IAAI,cAAc,CAAC;AACxB,WAAO,KAAK,MAAMA,MAAK;AAAA,EACzB;AACF;;;ACjbA,eAAsB,sBAAsB,YAAqC;AAE/E,QAAME,WAAU,WAAW,MAAM,WAAW,IAAO,QAAQ,UAAU,IAAI;AACzE,QAAM,WAAc,MAAMA,UAAS,GAAG,CAAC;AACvC,QAAMC,OAAgB,CAAI,IAAI,SAAS,EAAE,GAAM,IAAI,SAAS,EAAE,GAAM,IAAI,SAAS,EAAE,CAAC;AACpF,QAAMC,OAAgB,CAAI,IAAI,SAAS,EAAE,GAAM,IAAI,SAAS,EAAE,GAAM,IAAI,SAAS,EAAE,CAAC;AACpF,QAAM,SAAS,MAAM,QAAQ,IAAIA,KAAI,IAAI,CAAC,YAAY,QAAQ,KAAK,CAAC,CAAC;AACrE,QAAM,WAAW,OAAO,KAAK,IAAI,OAAO,GAAG,IAAI,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE;AACzE,QAAMC,OAAM,CAAI,IAAI,SAAS,IAAIF,KAAI,EAAE,GAAM,IAAI,SAAS,IAAIA,KAAI,EAAE,GAAM,IAAI,SAAS,IAAIA,KAAI,EAAE,CAAC;AAClG,QAAMG,SAAQ,CAAI,IAAIF,KAAI,IAAID,KAAI,EAAE,GAAM,IAAIC,KAAI,IAAID,KAAI,EAAE,GAAM,IAAIC,KAAI,IAAID,KAAI,EAAE,CAAC;AACrF,QAAM,OAAO,CAAI,IAAI,UAAUG,OAAM,EAAE,GAAM,IAAI,UAAUA,OAAM,EAAE,GAAM,IAAI,UAAUA,OAAM,EAAE,CAAC;AAChG,QAAM,MAAM,CAAI,IAAID,KAAI,IAAI,KAAK,EAAE,GAAM,IAAIA,KAAI,IAAI,KAAK,EAAE,GAAM,IAAIA,KAAI,IAAI,KAAK,EAAE,CAAC;AACtF,QAAME,OAAS,MAAM,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,GAAG,CAAC;AAChD,QAAMC,WAAa,QAAQD,MAAK,CAAC,GAAGL,SAAQ,MAAM,IAAIA,SAAQ,MAAM,IAAI,CAAC,CAAC;AAC1E,EAAG,QAAQ,CAAC,GAAG,UAAU,GAAGC,MAAK,GAAGC,MAAK,GAAGC,MAAK,GAAGC,QAAO,GAAG,MAAM,GAAG,KAAKC,MAAKL,QAAO,CAAC;AACzF,SAAOM;AACT;;;ACZA,IAAM,UAAU;AAEhB,IAAI,WAA6B;AACjC,IAAI,YAA8B;AAClC,IAAI,YAA8B;AAElC,IAAI;AAEJ,IAAM,OAAoG;AAAA,EACxG,UAAU;AAAA,EACV,WAAW;AAAA,EACX,WAAW;AAAA,EACX,aAAa;AACf;AAEO,SAAS,OAAO,OAAe,QAA2B;AAC/D,MAAI;AACJ,MAAIC,KAAI,SAAS;AACf,QAAIA,KAAI,QAAQ;AACd,UAAI,OAAO,oBAAoB;AAAa,cAAM,IAAI,MAAM,mFAAmF;AAC/I,UAAI,IAAI,gBAAgB,OAAO,MAAM;AAAA,IACvC,OAAO;AACL,UAAI,OAAO,aAAa;AAAa,cAAM,IAAI,MAAM,kEAAkE;AACvH,UAAI,SAAS,cAAc,QAAQ;AACnC,QAAE,QAAQ;AACV,QAAE,SAAS;AAAA,IACb;AAAA,EACF,OAAO;AAEL,QAAI,OAAOA,KAAI,WAAW;AAAa,UAAI,IAAIA,KAAI,OAAO,OAAO,MAAM;AAAA,aAC9D,OAAO,WAAW,WAAW;AAAa,UAAI,IAAI,WAAW,OAAO,OAAO,MAAM;AAAA,EAE5F;AACA,SAAO;AACT;AAGO,SAAS,KAAKC,QAAkB,QAAoB;AACzD,QAAM,eAAe,UAAU,OAAOA,OAAM,OAAOA,OAAM,MAAM;AAC/D,QAAM,MAAM,aAAa,WAAW,IAAI;AACxC,MAAI,UAAUA,QAAO,GAAG,CAAC;AACzB,SAAO;AACT;AAKA,eAAsBC,SAAQD,QAAcE,SAAgBC,aAAqB,MAAoE;AACnJ,MAAI,CAACH,QAAO;AAEV,QAAIE,QAAO;AAAO,UAAI,+BAA+B;AACrD,WAAO,EAAE,QAAQ,MAAM,QAAQ,KAAK;AAAA,EACtC;AAEA,MACE,EAAEF,kBAAoB,WACnB,EAAE,OAAO,UAAU,eAAeA,kBAAiB,UACnD,EAAE,OAAOD,KAAI,WAAW,eAAeC,kBAAiBD,KAAI,WAC5D,EAAE,OAAO,WAAW,WAAW,eAAeC,kBAAiB,WAAW,WAC1E,EAAE,OAAO,cAAc,eAAeA,kBAAiB,cACvD,EAAE,OAAO,gBAAgB,eAAeA,kBAAiB,gBACzD,EAAE,OAAO,qBAAqB,eAAeA,kBAAiB,qBAC9D,EAAE,OAAO,qBAAqB,eAAeA,kBAAiB,qBAC9D,EAAE,OAAO,qBAAqB,eAAeA,kBAAiB,qBAC9D,EAAE,OAAO,sBAAsB,eAAeA,kBAAiB,sBAC/D,EAAE,OAAO,oBAAoB,eAAeA,kBAAiB,kBAChE;AACA,UAAM,IAAI,MAAM,qCAAqC;AAAA,EACvD;AACA,MAAIA,kBAAoB,QAAQ;AAC9B,QAAII,UAAwB;AAC5B,QAAKJ,OAAiB;AAAuB,YAAM,IAAI,MAAM,yDAAyD;AACtH,QAAI,CAAEA,OAAiB;AAAU,YAAM,IAAI,MAAM,sDAAsD;AACvG,QAAKA,OAAiB,MAAM,WAAW,GAAG;AACxC,UAAKA,OAAiB,MAAM,OAAO,GAAG;AACpC,QAAAI,UAAY,WAAWJ,QAAO,CAAC;AAAA,MACjC,WAAYA,OAAiB,MAAM,OAAO,GAAG;AAC3C,cAAMK,OAAS,QAAQL,QAAO,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,IAAI,IAAI,CAAC,CAAC;AACpD,QAAAI,UAAY,WAAWC,MAAK,CAAC;AAC7B,QAAG,QAAQA,IAAG;AAAA,MAChB;AAAA,IACF,WAAYL,OAAiB,MAAM,WAAW,GAAG;AAC/C,UAAKA,OAAiB,MAAM,OAAO,GAAG;AACpC,QAAAI,UAAY,MAAMJ,MAAK;AAAA,MACzB,WAAYA,OAAiB,MAAM,OAAO,GAAG;AAC3C,QAAAI,UAAY,QAAQJ,QAAO,CAAC,GAAG,GAAG,GAAG,CAAC,GAAG,CAAC,IAAI,IAAI,IAAI,CAAC,CAAC;AAAA,MAC1D;AAAA,IACF;AAEA,QAAII,WAAU,QAAQA,QAAO,MAAM,WAAW,KAAKA,QAAO,MAAM,OAAO,KAAKA,QAAO,MAAM,OAAO;AAAG,YAAM,IAAI,MAAM,iEAAiEJ,OAAM,UAAU;AACpM,QAAKI,QAAkB,UAAU,SAAS;AACxC,YAAME,QAAU,KAAKF,SAAQ,SAAS;AACtC,MAAG,QAAQA,OAAM;AACjB,MAAAA,UAASE;AAAA,IACX;AACA,WAAO,EAAE,QAAAF,SAAQ,QAASF,QAAO,OAAO,SAAS,YAAY,KAAM;AAAA,EACrE,OAAO;AAEL,QAAI,OAAOF,OAAM,kBAAkB,eAAeA,OAAM,iBAAiB,GAAG;AAC1E,UAAIE,QAAO;AAAO,YAAI,2BAA2B;AACjD,aAAO,EAAE,QAAQ,MAAM,QAAQ,SAAS;AAAA,IAC1C;AACA,UAAM,gBAAgBF,OAAM,mBAAmBA,OAAM,iBAAiBA,OAAM,YAAaA,OAAM,YAAaA,OAAM,SAAS,KAAK;AAChI,UAAM,iBAAiBA,OAAM,oBAAoBA,OAAM,kBAAkBA,OAAM,aAAcA,OAAM,YAAaA,OAAM,SAAS,KAAK;AACpI,QAAI,CAAC,iBAAiB,CAAC,gBAAgB;AACrC,UAAIE,QAAO;AAAO,YAAI,mCAAmC;AACzD,aAAO,EAAE,QAAQ,MAAM,QAAQ,SAAS;AAAA,IAC1C;AACA,QAAI,cAAc;AAClB,QAAI,eAAe;AACnB,QAAI,cAAc,SAAS;AACzB,oBAAc;AACd,qBAAe,KAAK,MAAM,cAAc,iBAAiB,aAAa;AAAA,IACxE;AACA,QAAI,eAAe,SAAS;AAC1B,qBAAe;AACf,oBAAc,KAAK,MAAM,eAAe,gBAAgB,cAAc;AAAA,IACxE;AAGA,SAAKA,QAAO,OAAO,SAAS,KAAK;AAAG,oBAAcA,QAAO,OAAO;AAAA,cACtDA,QAAO,OAAO,UAAU,KAAK;AAAG,oBAAc,kBAAkBA,QAAO,OAAO,UAAU,KAAK;AACvG,SAAKA,QAAO,OAAO,UAAU,KAAK;AAAG,qBAAeA,QAAO,OAAO;AAAA,cACxDA,QAAO,OAAO,SAAS,KAAK;AAAG,qBAAe,mBAAmBA,QAAO,OAAO,SAAS,KAAK;AACvG,QAAI,CAAC,eAAe,CAAC;AAAc,YAAM,IAAI,MAAM,yCAAyC;AAC5F,QAAI,CAAC,aAAa,qCAAU,WAAU,gBAAiB,qCAAU,YAAW;AAAe,iBAAW,OAAO,aAAa,YAAY;AAGtI,UAAM,QAAQ,SAAS,WAAW,IAAI;AACtC,QAAK,OAAO,cAAc,eAAiBF,kBAAiB,WAAY;AACtE,YAAM,aAAaA,QAAO,GAAG,CAAC;AAAA,IAChC,OAAO;AACL,UAAIE,QAAO,OAAO,QAAQ,OAAO,MAAM,cAAc,aAAa;AAChE,cAAM,UAAU,eAAe,CAAC;AAChC,cAAM,MAAM,IAAI,CAAC;AACjB,cAAM,UAAUF,QAAoB,GAAG,GAAG,eAAe,gBAAgB,GAAG,GAAG,qCAAU,OAAO,qCAAU,MAAM;AAChH,cAAM,aAAa,GAAG,GAAG,GAAG,GAAG,GAAG,CAAC;AAAA,MACrC,OAAO;AACL,cAAM,UAAUA,QAAoB,GAAG,GAAG,eAAe,gBAAgB,GAAG,GAAG,qCAAU,OAAO,qCAAU,MAAM;AAAA,MAClH;AAAA,IACF;AAEA,QAAI,CAAC,aAAc,SAAS,UAAU,UAAU,UAAW,qCAAU,aAAW,uCAAW;AAAS,kBAAY,OAAO,SAAS,OAAO,SAAS,MAAM;AAGtJ,QAAIE,QAAO,OAAO,WAAWH,KAAI,MAAM,WAAW;AAChD,UAAI,CAAC;AAAI,aAAKA,KAAI,UAAU,IAAY,cAAc,IAAI;AAC1D,MAAAA,KAAI,SAAS,CAAC,CAAC;AACf,UAAI,CAAC,MAAM,CAAC,GAAG,KAAK;AAClB,YAAIG,QAAO;AAAO,cAAI,gDAAgD;AACtE,QAAAH,KAAI,MAAM,YAAY;AACtB,QAAAG,QAAO,OAAO,UAAU;AACxB,aAAK,UAAU,SAAS;AAAA,MAE1B,OAAO;AACL,WAAG,MAAM;AACT,YAAIA,QAAO,OAAO,eAAe;AAAG,aAAG,IAAI,cAAcA,QAAO,OAAO,UAAU;AACjF,YAAIA,QAAO,OAAO,aAAa;AAAG,aAAG,IAAI,YAAYA,QAAO,OAAO,QAAQ;AAC3E,YAAIA,QAAO,OAAO,cAAc;AAAG,aAAG,IAAI,WAAWA,QAAO,OAAO,SAAS;AAC5E,YAAIA,QAAO,OAAO,SAAS;AAAG,aAAG,IAAI,QAAQA,QAAO,OAAO,IAAI;AAC/D,YAAIA,QAAO,OAAO,eAAe;AAAG,aAAG,IAAI,cAAcA,QAAO,OAAO,UAAU;AACjF,YAAIA,QAAO,OAAO,QAAQ;AAAG,aAAG,IAAI,OAAOA,QAAO,OAAO,GAAG;AAC5D,YAAIA,QAAO,OAAO;AAAU,aAAG,IAAI,UAAU;AAC7C,YAAIA,QAAO,OAAO;AAAO,aAAG,IAAI,OAAO;AACvC,YAAIA,QAAO,OAAO;AAAS,aAAG,IAAI,SAAS;AAC3C,YAAIA,QAAO,OAAO;AAAO,aAAG,IAAI,OAAO;AACvC,YAAIA,QAAO,OAAO;AAAY,aAAG,IAAI,YAAY;AACjD,YAAIA,QAAO,OAAO;AAAa,aAAG,IAAI,aAAa;AACnD,YAAIA,QAAO,OAAO;AAAU,aAAG,IAAI,UAAU;AAC7C,YAAIA,QAAO,OAAO,aAAa;AAAG,aAAG,IAAI,YAAYA,QAAO,OAAO,QAAQ;AAC3E,YAAI,GAAG,IAAI,IAAI;AAAG,sBAAY,GAAG,MAAM,QAAQ;AAAA;AAC1C,sBAAY,GAAG,KAAK,QAAQ;AAAA,MACnC;AAAA,IACF,OAAO;AACL,WAAK,UAAU,SAAS;AACxB,UAAI;AAAI,aAAK;AACb,MAAAH,KAAI,SAAS,CAAC,CAAC;AAAA,IACjB;AAEA,QAAI,CAACI;AAAW,aAAO,EAAE,QAAQ,MAAM,QAAQ,UAAU;AACzD,QAAI,CAAC;AAAW,YAAM,IAAI,MAAM,oCAAoC;AAGpE,QAAI;AACJ,QAAI,QAAQ;AACZ,QAAK,OAAO,cAAc,eAAeH,kBAAiB,aAAeA,OAAM,WAAWA,OAAM,YAAYA,OAAM,WAAY;AAC5H,UAAID,KAAI,WAAc,iBAAS;AAC7B,iBAAY,kBAAa,gBAAQ,WAAWC,MAAK,IAAI;AAAA,MACvD,OAAO;AACL,gBAAQA,OAAM,QAAQ,SAASA,OAAM,YAAYA,OAAM;AAEvD,cAAM,MAAM,IAAI,WAAWA,OAAM,QAAQ,SAAS;AAClD,iBAAY,OAAO,KAAK,CAACA,OAAM,WAAWA,OAAM,UAAU,KAAK,GAAG,OAAO;AAAA,MAC3E;AAAA,IACF,OAAO;AACL,UAAI,CAAC,aAAc,UAAU,UAAU,UAAU,SAAW,UAAU,WAAW,UAAU;AAAS,oBAAY,OAAO,UAAU,OAAO,UAAU,MAAM;AACxJ,UAAO,mBAAWD,KAAI,SAAS;AAC7B,YAAIG,QAAO,YAAY,WAAWA,QAAO,YAAY,aAAaA,QAAO,YAAY,UAAU;AAC7F,mBAAY,gBAAQ,WAAW,SAAS;AAAA,QAC1C,OAAO;AACL,sBAAY,KAAK,SAAS;AAC1B,mBAAY,gBAAQ,WAAW,SAAS;AAAA,QAC1C;AAAA,MACF,OAAO;AACL,cAAM,aAAa,KAAK,SAAS;AACjC,cAAM,UAAU,WAAW,WAAW,IAAI;AAC1C,cAAM,WAAW,QAAQ,aAAa,GAAG,GAAG,aAAa,YAAY;AACrE,gBAAQ,SAAS,KAAK,SAAS,cAAc;AAC7C,cAAM,MAAM,IAAI,WAAW,SAAS,KAAK,MAAM;AAC/C,iBAAY,OAAO,KAAK,CAAC,aAAa,cAAc,KAAK,CAAC;AAAA,MAC5D;AAAA,IACF;AACA,QAAI,UAAU,GAAG;AACf,YAAMG,OAAS,QAAQ,QAAQ,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,IAAI,IAAI,CAAC,CAAC;AACrD,MAAG,QAAQ,MAAM;AACjB,eAASA;AAAA,IACX;AACA,QAAI,CAAC;AAAQ,YAAM,IAAI,MAAM,mCAAmC;AAChE,UAAM,SAAY,KAAK,QAAQ,SAAS;AACxC,UAAMD,UAASF,QAAO,OAAO,eAAe,MAAc,sBAAsB,MAAM,IAAO,WAAW,QAAQ,CAAC;AACjH,IAAG,QAAQ,CAAC,QAAQ,MAAM,CAAC;AAC3B,WAAO,EAAE,QAAAE,SAAQ,QAASF,QAAO,OAAO,SAAS,YAAY,KAAM;AAAA,EACrE;AACF;AAgCA,eAAsB,KAAKA,SAAyBF,QAAe;AACjE,MAAI,YAAY;AAChB,MAAIE,QAAO,qBAAqB,KAAK,CAACF,OAAM,SAASA,OAAM,MAAM,WAAW,KAAKA,OAAM,MAAM,KAAK,QAAQA,OAAM,MAAM,KAAK;AAAM,WAAO;AAcxI,MAAI,CAAC,KAAK,aAAa;AACrB,SAAK,cAAiB,MAAMA,MAAK;AAAA,EACnC,WAAW,KAAK,YAAY,MAAM,OAAOA,OAAM,MAAM,MAAM,KAAK,YAAY,MAAM,OAAOA,OAAM,MAAM,IAAI;AACvG,IAAG,QAAQ,KAAK,WAAW;AAC3B,SAAK,cAAiB,MAAMA,MAAK;AAAA,EACnC,OAAO;AACL,UAAMO,KAA4B,CAAC;AACnC,IAAAA,GAAE,OAAU,IAAIP,QAAO,KAAK,WAAW;AACvC,IAAAO,GAAE,UAAa,IAAIA,GAAE,MAAMA,GAAE,IAAI;AACjC,IAAAA,GAAE,MAAS,KAAIA,GAAE,OAAO;AACxB,UAAM,UAAU,MAAMA,GAAE,IAAI,KAAK;AACjC,UAAM,eAAe,QAAQ,MAAMP,OAAM,MAAM,MAAM,MAAMA,OAAM,MAAM,MAAM,KAAK,MAAM;AACxF,IAAG,QAAQ,CAAC,KAAK,aAAaO,GAAE,MAAMA,GAAE,SAASA,GAAE,GAAG,CAAC;AACvD,SAAK,cAAiB,MAAMP,MAAK;AACjC,gBAAY,iBAAiBE,QAAO,oBAAoB;AAAA,EAC1D;AACA,SAAO;AACT;AAEA,eAAsB,QAAQA,SAAyB,QAAgB,QAAiC;AACtG,QAAMK,KAA4B,CAAC;AACnC,MAAI,CAAC,UAAU,CAAC,UAAU,OAAO,MAAM,WAAW,KAAK,OAAO,MAAM,WAAW,OAAO,MAAM,QAAQ;AAClG,QAAI,CAACL,QAAO;AAAO,UAAI,uDAAuD,OAAO,OAAO,OAAO,KAAK;AACxG,WAAO;AAAA,EACT;AACA,MAAI,OAAO,MAAM,OAAO,KAAK,OAAO,MAAM,OAAO,KAAK,OAAO,MAAM,OAAO,KAAK,OAAO,MAAM,OAAO,GAAG;AACpG,QAAI,CAACA,QAAO;AAAO,UAAI,yDAAyD,OAAO,OAAO,OAAO,KAAK;AAC1G,WAAO;AAAA,EACT;AACA,EAAAK,GAAE,SAAY,MAAM,MAAM;AAC1B,EAAAA,GAAE,SAAU,OAAO,MAAM,OAAO,OAAO,MAAM,MAAM,OAAO,MAAM,OAAO,OAAO,MAAM,KAAS,MAAM,eAAe,QAAQ,CAAC,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE,CAAC,IAAO,MAAM,MAAM;AAC/K,EAAAA,GAAE,OAAU,IAAIA,GAAE,QAAQA,GAAE,MAAM;AAClC,EAAAA,GAAE,UAAa,IAAIA,GAAE,MAAMA,GAAE,IAAI;AACjC,EAAAA,GAAE,MAAS,KAAIA,GAAE,OAAO;AACxB,QAAM,UAAU,MAAMA,GAAE,IAAI,KAAK;AACjC,QAAM,eAAe,QAAQ,MAAM,OAAO,MAAM,MAAM,MAAM,OAAO,MAAM,MAAM,KAAK,MAAM;AAC1F,EAAG,QAAQ,CAACA,GAAE,QAAQA,GAAE,QAAQA,GAAE,MAAMA,GAAE,SAASA,GAAE,GAAG,CAAC;AACzD,SAAO;AACT;;;AC5TO,IAAM,MAAN,MAAU;AAAA,EA4Ef,cAAc;AA1Ed;AAEA;AAEA;AAEA,oCAAmB;AAEnB,iCAAgB;AAEhB,oCAAqB,CAAC;AAEtB;AAEA;AAEA;AAIA;AAEA,mCAAmB;AAEnB,gCAKI;AAAA,MACA,WAAW;AAAA,MACX,SAAS;AAAA,MACT,MAAM;AAAA,MACN,aAAa;AAAA,IACf;AAEF,iCAKI;AAAA,MACA,WAAW;AAAA,MACX,SAAS;AAAA,MACT,SAAS;AAAA,MACT,UAAU;AAAA,IACZ;AAEF,kCAII;AAAA,MACA,WAAW;AAAA,MACX,SAAS;AAAA,MACT,SAAS;AAAA,IACX;AAEF,+BAGI;AAAA,MACA,OAAO;AAAA,MACP,OAAO,CAAC;AAAA,IACV;AAEF,mCAAoB,CAAC;AAErB;AAEA;AAEA;AAGE,SAAK,UAAU,OAAO,cAAc;AACpC,SAAK,OAAQ,OAAO,YAAY,eAAiB,OAAO,QAAQ,aAAa,eAAiB,OAAO,QAAQ,SAAS,SAAS;AAC/H,SAAK,OAAO,EAAE,SAAY,EAAQ,aAAa;AAC/C,SAAK,YAAY,OAAO,oBAAoB;AAC5C,SAAK,UAAU;AAEf,SAAK,SAAS,KAAK,WAAW,KAAK,YAAa,OAAO,sBAAsB,cAAe;AAC5F,QAAI,OAAO,cAAc,aAAa;AACpC,YAAM,MAAM,UAAU,UAAU,MAAM,eAAe;AACrD,UAAI,OAAO,IAAI,IAAI;AACjB,cAAM,gBAAgB,IAAI,GAAG,MAAM,eAAe;AAClD,aAAK,WAAY,iBAAiB,cAAc,KAAM,cAAc,GAAG,QAAQ,UAAU,EAAE,IAAI;AAC/F,aAAK,QAAQ,UAAU,UAAU,QAAQ,IAAI,IAAI,EAAE;AACnD,YAAI,KAAK,SAAS;AAAI,eAAK,QAAQ,KAAK,MAAM,QAAQ,IAAI,IAAI,EAAE;AAChE,aAAK,QAAQ,KAAK,MAAM,QAAQ,OAAO,GAAG;AAAA,MAU5C;AAAA,IACF,WAAW,OAAO,YAAY,aAAa;AACzC,WAAK,WAAW,GAAG,QAAQ,YAAY,QAAQ;AAC/C,WAAK,QAAQ,UAAU,QAAQ;AAAA,IACjC;AAAA,EACF;AAAA,EAGA,MAAM,gBAAgB;AAEpB,SAAK,WAAW,OAAO,KAAQ,OAAO,EAAE,eAAe;AACvD,SAAK,KAAK,YAAY,OAAO,gBAAgB;AAC7C,SAAK,KAAK,UAAU,KAAK,SAAS,SAAS,MAAM;AACjD,QAAI,KAAK,KAAK,aAAa,KAAK,KAAK,WAAc,WAAW,MAAM,QAAQ;AAC1E,WAAK,KAAK,OAAO,MAAS,IAAI,EAAE,SAAS,uBAAuB;AAChE,WAAK,KAAK,cAAc,MAAS,IAAI,EAAE,SAAS,8BAA8B;AAAA,IAChF;AACA,UAAM,IAAU,OAAO,KAAK,GAAG;AAC/B,UAAM,MAAM,IAAI,EAAE,WAAW,QAAQ,IAAI;AAEzC,SAAK,MAAM,YAAY,OAAO,QAAQ;AACtC,SAAK,MAAM,UAAU,KAAK,SAAS,SAAS,OAAO;AACnD,QAAI,KAAK,MAAM,aAAa,KAAK,MAAM,YAAe,WAAW,MAAM,WAAc,WAAW,MAAM,YAAY;AAEhH,YAAM,KAAQ,QAAQ,EAAE,UAAU,cAAc,MAAS,QAAQ,EAAE,gBAAgB,EAAE,KAAK;AAC1F,UAAI,IAAI;AACN,aAAK,MAAM,UAAU,GAAG,aAAa,GAAG,OAAO;AAC/C,aAAK,MAAM,WAAW,GAAG,aAAa,GAAG,QAAQ;AAAA,MACnD;AAAA,IACF;AAEA,SAAK,OAAO,YAAY,KAAK,WAAW,OAAO,UAAU,WAAW;AACpE,SAAK,OAAO,UAAU,KAAK,SAAS,SAAS,QAAQ;AACrD,QAAI;AAEF,UAAI,KAAK,OAAO;AAAW,aAAK,OAAO,WAAW,MAAM,UAAU,OAAO,eAAe,GAAG;AAAA,IAC7F,SAAQC,IAAN;AACA,WAAK,OAAO,YAAY;AAAA,IAC1B;AACA,QAAI;AACF,WAAK,UAAa,qBAAwB,WAAW,CAAC,EAAE,IAAI,CAAC,WAAW,OAAO,WAAW,YAAY,CAAC;AAAA,IACzG,SAAQA,IAAN;AAAA,IAAa;AAAA,EACjB;AAAA,EAGA,MAAM,YAAY;AAChB,UAAM,MAAM,EAAE,OAAO,IAAI,OAAO,CAAC,EAAE;AACnC,QAAI,KAAK,QAAQ,KAAK,SAAS,WAAW,OAAO,GAAG;AAAA,IAWpD;AACA,QAAI,CAAC,KAAK;AAAQ,aAAO,eAAe,MAAM,OAAO,EAAE,OAAO,IAAI,CAAC;AAAA;AAC9D,WAAK,SAAS;AAAA,EACrB;AACF;AAEO,IAAMC,OAAM,IAAI,IAAI;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;ACnK3B,IAAM,UAAU;AAAA,EACd,aAAa;AAAA,EACb,gBAAgB;AAAA,EAChB,SAAS;AAAA,EACT,OAAO;AAAA,EACP,eAAe;AACjB;AAUO,IAAM,aAAwC,CAAC;AAEtD,eAAe,YAAY,KAAKC,OAAiC;AAC/D,MAAI,QAAQ;AAAO,QAAI,qBAAqB,KAAKA,KAAI;AACrD,SAAO,MAAM,KAAKA,KAAI;AACxB;AAEO,SAAS,oBAAoBC,SAAgB;AAClD,UAAQ,cAAcA,QAAO;AAC7B,UAAQ,UAAUA,QAAO;AACzB,UAAQ,gBAAgBA,QAAO;AACjC;AAEA,eAAsB,UAAU,WAAoD;AAnCpF;AAoCE,MAAI,WAAW,KAAK,QAAQ,eAAe,aAAa,EAAE;AAC1D,MAAI,CAAC,SAAS,YAAY,EAAE,SAAS,OAAO;AAAG,gBAAY;AAC3D,QAAM,oBAAoB,SAAS,SAAS,GAAG,IAAI,SAAS,MAAM,GAAG,IAAI,SAAS,MAAM,IAAI;AAC5F,QAAM,iBAAiB,kBAAkB,kBAAkB,SAAS,GAAG,QAAQ,SAAS,EAAE;AAC1F,QAAM,kBAAkB,iBAAiB;AACzC,aAAW,kBAAkB;AAAA,IAC3B,MAAM;AAAA,IACN,kBAAkB;AAAA,IAClB,mBAAmB;AAAA,IACnB,aAAa,eAAW;AAAA,IACxB,SAAS;AAAA,EACX;AACA,UAAQ,iBAAkB,OAAO,WAAW,eAAiB,OAAO,OAAO,iBAAiB,eAAiB,OAAO,OAAO,cAAc;AACzI,MAAI,eAAe,CAAC;AACpB,MAAI;AACF,mBAAgB,QAAQ,kBAAkB,QAAQ,cAAe,MAAS,WAAG,WAAW,IAAI,CAAC;AAAA,EAC/F,SAAQC,IAAN;AACA,YAAQ,iBAAiB;AAAA,EAC3B;AACA,aAAW,gBAAgB,UAAW,QAAQ,kBAAkB,QAAQ,eAAgB,OAAO,KAAK,YAAY,EAAE,SAAS,eAAe;AAC1I,QAAM,gBAAgB,OAAO,UAAU,cAAc,CAAC,IAAI,EAAE,WAAW,CAAC,KAAKF,UAAU,YAAY,KAAKA,KAAI,EAAE;AAC9G,QAAMG,UAAoB,IAAO,WAAW,WAAW,gBAAgB,UAAU,kBAAkB,UAAU,aAAa;AAC1H,MAAI,SAAS;AACb,MAAI;AAEF,IAAAA,QAAM,cAAc;AACpB,QAAI,QAAQ;AAAO,UAAI,uBAAuBA,QAAM,UAAU;AAE9D,UAAM,YAAY,MAAMA,QAAM,QAAQ,KAAK;AAC3C,eAAW,gBAAgB,qBAAmB,4CAAW,eAAX,mBAAuB,eAAc;AACnF,IAAAA,QAAM,SAAS,SAAS;AAExB,eAAW,gBAAgB,sBAAoB,WAAAA,WAAA,gBAAAA,QAAO,cAAP,mBAAkB,eAAlB,mBAA8B,eAAc;AAC3F,QAAI,QAAQ;AAAS,UAAI,eAAeA,QAAM,aAAa,EAAE,OAAO,WAAW,gBAAgB,kBAAkB,GAAG,OAAO;AAC3H,aAAS;AAAA,EACX,SAAS,KAAP;AACA,QAAI,wBAAwB,UAAU,GAAG;AAAA,EAC3C;AACA,MAAI,UAAU,QAAQ,eAAe,QAAQ,kBAAkB,CAAC,WAAW,gBAAgB,SAAS;AAClG,QAAI;AACF,YAAM,aAAa,MAAMA,QAAM,KAAK,eAAe;AACnD,UAAI,gBAAgB,iBAAiB,UAAU;AAAA,IACjD,SAAS,KAAP;AACA,UAAI,uBAAuB,UAAU,GAAG;AAAA,IAC1C;AAAA,EACF;AACA,SAAOA;AACT;;;;;;ACnFA,IAAAC,kBAAA;AAAA,SAAAA,iBAAA;AAAA;AAAA;AAAA,cAAAC;AAAA,EAAA;AAAA,kBAAAC;AAAA;;;ACeA,IAAIC;AACJ,IAAMC,QAAwB,CAAC;AAC/B,IAAM,YAAY,CAAC,SAAS,SAAS,SAAS,UAAU,OAAO;AAC/D,IAAM,aAAa,CAAC,IAAI,IAAI,IAAI,MAAM,MAAM,MAAM,EAAE;AACpD,IAAI,YAAY;AAChB,IAAI,WAAW;AACf,IAAI,UAAU,OAAO;AAGrB,eAAsB,KAAKC,SAAgB;AAxB3C;AAyBE,MAAIC,KAAI;AAAS,IAAAH,SAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,SAAQ,MAAM,WAAU,KAAAE,QAAO,KAAK,YAAZ,mBAAqB,SAAS;AAAA,WACzDA,QAAO;AAAO,QAAI,iBAAiBF,OAAM,WAAW;AAC7D,SAAOA;AACT;AAGA,eAAsB,QAAQI,QAAeF,SAAgB,KAAaG,QAAkC;AAhC5G;AAiCE,MAAI,CAACL;AAAO,WAAO,EAAE,KAAK,GAAG,QAAQ,WAAW,aAAa,GAAG,MAAM,CAAC,EAAE;AACzE,QAAM,YAAY,aAAW,KAAAE,QAAO,KAAK,YAAZ,mBAAqB,eAAc;AAChE,QAAM,cAAY,KAAAA,QAAO,KAAK,YAAZ,mBAAqB,aAAY,KAAM,IAAI,IAAI;AACjE,MAAIA,QAAO,eAAe,YAAY,aAAc,cAAcG,UAAUJ,MAAK,MAAM;AACrF;AACA,WAAOA,MAAK;AAAA,EACd;AACA,YAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AAzCxC,QAAAK,KAAAC;AA0CI,QAAI,EAACP,UAAA,gBAAAA,OAAO,OAAO,GAAG;AAAO;AAC7B,UAAMQ,KAA4B,CAAC;AAEnC,UAAM,MAAM,CAAC,CAAC,GAAK,KAAM,KAAM,GAAI,CAAC;AACpC,IAAAA,GAAE,SAAY,MAAM,cAAcJ,QAAO,KAAK,CAAC,CAAC,GAAG,CAACJ,OAAM,OAAO,GAAG,MAAM,IAAIA,OAAM,OAAO,GAAG,MAAM,EAAE,CAAC;AACvG,UAAM,MAAgB,EAAE,KAAK,GAAG,QAAQ,WAAW,aAAa,GAAG,MAAM,CAAC,EAAE;AAC5E,SAAIM,MAAAJ,QAAO,KAAK,YAAZ,gBAAAI,IAAqB;AAAS,OAACE,GAAE,KAAKA,GAAE,QAAQA,GAAE,IAAI,IAAIR,OAAM,QAAQQ,GAAE,QAAQ,CAAC,cAAc,iBAAiB,aAAa,CAAC;AACpI,UAAMC,UAAS,MAAMD,GAAE,OAAO,KAAK;AACnC,QAAI,SAASC,QAAO,KAAKA,QAAO,KAAK,SAAS;AAC9C,QAAI,cAAc,KAAK,MAAM,OAAOA,QAAO,KAAKA,QAAO,KAAKA,QAAO,KAAKA,QAAO,GAAG,IAAI;AACtF,UAAM,OAAO,MAAMD,GAAE,KAAK,KAAK;AAC/B,aAASE,KAAI,GAAGA,KAAI,KAAK,QAAQA,MAAK;AACpC,UAAI,KAAKA,SAAMH,MAAAL,QAAO,KAAK,YAAZ,gBAAAK,IAAqB,kBAAiB;AAAM,YAAI,KAAK,KAAK,EAAE,OAAO,KAAK,MAAM,MAAM,KAAKG,GAAE,IAAI,KAAK,MAAM,UAAUA,IAAW,CAAC;AAAA,IACjJ;AACA,QAAI,KAAK,KAAK,CAAC,GAAG,MAAM,EAAE,QAAQ,EAAE,KAAK;AAEzC,UAAM,kBAAkB,MAAM,KAAK,MAAMF,GAAE,IAAI,KAAK,CAAC;AACrD,UAAM,YAAY,gBAAgB,IAAI,CAAC,GAAGE,OAAM,CAAC,WAAWA,KAAI,CAAC,CAAC,EAAE,KAAK,CAAC,GAAG,MAAM,EAAE,KAAK,EAAE,EAAE;AAC9F,QAAIC,OAAM,UAAU,GAAG;AACvB,aAASD,KAAI,GAAGA,KAAI,UAAU,QAAQA;AAAK,MAAAC,QAAO,UAAUD,IAAG,MAAM,UAAUA,IAAG,KAAKC;AACvF,QAAI,MAAM,KAAK,MAAM,KAAKA,IAAG,IAAI;AACjC,WAAO,KAAKH,EAAC,EAAE,QAAQ,CAACI,YAAc,QAAQJ,GAAEI,QAAO,CAAC;AACxD,IAAAX,MAAK,OAAO;AACZ,gBAAYI;AACZ,eAAW,IAAI;AACf,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;AClEO,IAAM,YAAwD;AAAA,EACnE,OAAO;AAAA,EACP,KAAK;AAAA,EACL,KAAK;AAAA,EACL,MAAM;AAAA,EACN,OAAO;AAAA,EACP,KAAK,CAAC,QAAQ,OAAQ,KAAM;AAC9B;AAEO,SAASQ,QAAO;AACrB,YAAU,QAAW,OAAO,KAAK,SAAS;AAC1C,YAAU,MAAS,OAAO,GAAG,SAAS;AACtC,YAAU,MAAS,OAAO,GAAG,SAAS;AACtC,YAAU,OAAU,OAAO,KAAK,SAAS;AACzC,YAAU,QAAW,OAAO,OAAO,SAAS;AAC5C,YAAU,MAAS,SAAS,CAAC,QAAQ,OAAQ,KAAM,GAAG,SAAS;AACjE;;;ACLA,IAAIC;AACJ,IAAMC,QAA+B,CAAC;AACtC,IAAIC,aAAY;AAChB,IAAIC,YAAW;AACf,IAAIC,WAAU,OAAO;AAGrB,eAAsBC,MAAKC,SAAgB;AACzC,MAAIC,KAAI;AAAS,IAAAP,SAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,SAAQ,MAAM,UAAUM,QAAO,KAAK,UAAU,YAAY;AAAA,WAC7DA,QAAO;AAAO,QAAI,iBAAiBN,OAAM,WAAW;AAC7D,SAAOA;AACT;AAGA,eAAsBQ,SAAQC,QAAeH,SAAgB,KAAaI,QAAyC;AA7BnH;AA8BE,MAAI,CAACV;AAAO,WAAO,EAAE,KAAK,EAAE;AAC5B,QAAM,YAAYI,cAAW,KAAAE,QAAO,KAAK,cAAZ,mBAAuB,eAAc;AAClE,QAAM,cAAY,KAAAA,QAAO,KAAK,cAAZ,mBAAuB,aAAY,KAAM,IAAI,IAAIH;AACnE,MAAIG,QAAO,eAAe,aAAa,YAAaJ,eAAcQ,YAAU,KAAAT,MAAK,SAAL,mBAAW,UAAQ,KAAAA,MAAK,SAAL,mBAAW,OAAM,GAAI;AAClH,IAAAG;AACA,WAAOH,MAAK;AAAA,EACd;AACA,EAAAG,WAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,QAAI,EAACJ,UAAA,gBAAAA,OAAO,WAAU,CAACA,OAAM,OAAO,MAAM,CAACA,OAAM,OAAO,GAAG;AAAO;AAClE,UAAMW,KAA4B,CAAC;AACnC,IAAAA,GAAE,SAAY,MAAM,eAAeF,QAAO,CAACT,OAAM,OAAO,GAAG,MAAM,IAAIA,OAAM,OAAO,GAAG,MAAM,EAAE,GAAG,KAAK;AACrG,IAAAW,GAAE,UAAa,IAAIA,GAAE,QAAQ,UAAU,KAAK;AAC5C,UAAM,MAAM,EAAE,KAAK,EAAE;AACrB,QAAIL,QAAO,KAAK,UAAU;AAAS,MAAAK,GAAE,MAAMX,OAAM,QAAQW,GAAE,OAAO;AAClE,QAAIA,GAAE,KAAK;AACT,YAAM,OAAO,MAAMA,GAAE,IAAI,KAAK;AAC9B,UAAI,MAAM,KAAK,MAAM,KAAK,KAAK,EAAE,IAAI;AAAA,IACvC;AACA,WAAO,KAAKA,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,IAAAX,MAAK,OAAO;AACZ,IAAAC,aAAYQ;AACZ,IAAAP,YAAW,IAAI;AACf,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;ACxCA,IAAIU;AACJ,IAAMC,QAAuD,CAAC;AAC9D,IAAIC,aAAY;AAChB,IAAIC,YAAW;AACf,IAAIC,WAAU,OAAO;AAGrB,IAAM,MAAM,CAAC,QAAQ,OAAQ,KAAM;AAGnC,eAAsBC,MAAKC,SAAsB;AAC/C,MAAIC,KAAI;AAAS,IAAAP,SAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,SAAQ,MAAM,UAAUM,QAAO,KAAK,UAAU,eAAe;AAAA,WAChEA,QAAO;AAAO,QAAI,iBAAiBN,OAAM,WAAW;AAC7D,SAAOA;AACT;AAGA,eAAsBQ,SAAQC,QAAeH,SAAgB,KAAKI,QAAyD;AAjC3H;AAkCE,MAAI,CAACV;AAAO,WAAO,EAAE,QAAQ,WAAW,aAAa,EAAE;AACvD,QAAM,YAAYI,cAAW,KAAAE,QAAO,KAAK,cAAZ,mBAAuB,eAAc;AAClE,QAAM,cAAY,KAAAA,QAAO,KAAK,cAAZ,mBAAuB,aAAY,KAAM,IAAI,IAAIH;AACnE,MAAIG,QAAO,eAAe,aAAa,YAAaJ,eAAcQ,YAAU,KAAAT,MAAK,SAAL,mBAAW,aAAW,KAAAA,MAAK,SAAL,mBAAW,eAAc,GAAI;AAC7H,IAAAG;AACA,WAAOH,MAAK;AAAA,EACd;AACA,EAAAG,WAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,QAAI,EAACJ,UAAA,gBAAAA,OAAO,OAAO,GAAG;AAAO;AAC7B,UAAMW,KAA4B,CAAC;AACnC,IAAAA,GAAE,SAAY,MAAM,eAAeF,QAAO,CAACT,OAAM,OAAO,GAAG,MAAM,IAAIA,OAAM,OAAO,GAAG,MAAM,EAAE,GAAG,KAAK;AACrG,IAAAW,GAAE,UAAa,KAAK,MAAM;AACxB,YAAM,CAAC,KAAK,OAAO,IAAI,IAAO,MAAMA,GAAE,QAAQ,GAAG,CAAC;AAClD,YAAM,UAAa,IAAI,KAAK,IAAI,EAAE;AAClC,YAAM,YAAe,IAAI,OAAO,IAAI,EAAE;AACtC,YAAM,WAAc,IAAI,MAAM,IAAI,EAAE;AACpC,YAAM,YAAe,KAAK,CAAC,SAAS,WAAW,QAAQ,CAAC;AACxD,YAAM,YAAe,IAAO,IAAI,WAAW,UAAU,IAAI,GAAG,CAAC;AAC7D,aAAO;AAAA,IACT,CAAC;AACD,UAAM,MAA+C,EAAE,QAAQ,WAAW,aAAa,EAAE;AACzF,QAAIL,QAAO,KAAK,UAAU;AAAS,MAAAK,GAAE,SAASX,OAAM,QAAQW,GAAE,OAAO;AACrE,UAAM,OAAO,MAAMA,GAAE,OAAO,KAAK;AACjC,QAAI,SAAS,KAAK,KAAK,KAAK,KAAK,WAAW;AAC5C,QAAI,cAAc,KAAK,KAAK,KAAK,KAAM,KAAK,MAAM,MAAM,KAAK,EAAE,IAAI,MAAQ,KAAK,MAAM,MAAM,KAAK,EAAE,IAAI;AACvG,WAAO,KAAKA,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,IAAAX,MAAK,OAAO;AACZ,IAAAC,aAAYQ;AACZ,IAAAP,YAAW,IAAI;AACf,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;ACvDA,IAAIU;AACJ,IAAM,SAAwB,CAAC;AAC/B,IAAIC,WAAU,OAAO;AACrB,IAAIC,aAAY;AAChB,IAAIC,YAAW;AAEf,eAAsBC,MAAKC,SAAqC;AAjBhE;AAkBE,MAAIC,KAAI;AAAS,IAAAN,SAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,SAAQ,MAAM,WAAU,KAAAK,QAAO,KAAK,cAAZ,mBAAuB,SAAS;AAAA,WAC3DA,QAAO;AAAO,QAAI,iBAAiBL,OAAM,WAAW;AAC7D,SAAOA;AACT;AAEA,eAAsBO,SAAQC,QAAeH,SAAgB,KAAaI,QAAgC;AAxB1G;AAyBE,MAAI,CAACT;AAAO,WAAO;AACnB,QAAM,cAAY,KAAAK,QAAO,KAAK,cAAZ,mBAAuB,aAAY,KAAM,IAAI,IAAIF;AACnE,QAAM,YAAYF,cAAW,KAAAI,QAAO,KAAK,cAAZ,mBAAuB,eAAc;AAClE,MAAIA,QAAO,eAAe,YAAY,aAAcH,eAAcO,UAAU,OAAO,MAAM;AACvF,IAAAR;AACA,WAAO,OAAO;AAAA,EAChB;AACA,EAAAA,WAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,UAAM,SAAY,MAAM,eAAeO,QAAO,EAACR,UAAA,gBAAAA,OAAO,OAAO,GAAG,SAAQA,OAAM,OAAO,GAAG,MAAM,KAAK,IAAGA,UAAA,gBAAAA,OAAO,OAAO,GAAG,SAAQA,OAAM,OAAO,GAAG,MAAM,KAAK,CAAC,GAAG,KAAK;AACnK,UAAM,MAAMA,UAAA,gBAAAA,OAAO,QAAQ;AAC3B,UAAM,OAAO,MAAM,IAAI,KAAK,GAAG;AAC/B,WAAO,OAAO,KAAK,MAAM,MAAM,GAAG,IAAI;AACtC,IAAAE,aAAYO;AACZ,IAAAN,YAAW,IAAI;AACf,IAAG,QAAQ,CAAC,QAAQ,GAAG,CAAC;AACxB,YAAQ,OAAO,IAAI;AAAA,EACrB,CAAC;AACH;;;ACtCO,IAAM,kBAA4C;AAAA,EACvD,YAAY;AAAA,IACV;AAAA,IAAI;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IACtD;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IACvD;AAAA,IAAK;AAAA,IAAI;AAAA,IAAK;AAAA,IAAI;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAI;AAAA,IAAI;AAAA,IAAK;AAAA,IAAI;AAAA,EACpD;AAAA,EAKA,gBAAgB,CAAC,KAAK,IAAI,IAAI,IAAI,GAAG,KAAK,KAAK,KAAK,GAAG;AAAA,EACvD,gBAAgB,CAAC,IAAI,KAAK,IAAI,KAAK,IAAI,IAAI,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAClE,gBAAgB,CAAC,KAAK,IAAI,IAAI,IAAI,IAAI,KAAK,KAAK,KAAK,GAAG;AAAA,EACxD,gBAAgB,CAAC,IAAI,IAAI,IAAI,KAAK,IAAI,IAAI,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACjE,oBAAoB,CAAC,IAAI,IAAI,IAAI,KAAK,IAAI,IAAI,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACrE,oBAAoB,CAAC,KAAK,IAAI,IAAI,IAAI,IAAI,KAAK,KAAK,KAAK,GAAG;AAAA,EAC5D,oBAAoB,CAAC,IAAI,IAAI,IAAI,KAAK,IAAI,IAAI,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACrE,oBAAoB,CAAC,KAAK,IAAI,IAAI,IAAI,IAAI,KAAK,KAAK,KAAK,GAAG;AAAA,EAC5D,gBAAgB,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAClD,gBAAgB,CAAC,IAAI,GAAG,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACzD,gBAAgB,CAAC,KAAK,IAAI,IAAI,IAAI,IAAI,IAAI,GAAG;AAAA,EAC7C,gBAAgB,CAAC,KAAK,IAAI,KAAK,IAAI,IAAI,IAAI,IAAI,KAAK,GAAG;AAAA,EACvD,gBAAgB,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAClD,gBAAgB,CAAC,KAAK,IAAI,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAC3D,gBAAgB,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAC5D,mBAAmB,CAAC,KAAK,IAAI,IAAI,KAAK,IAAI,KAAK,IAAI,GAAG;AAAA,EACtD,mBAAmB,CAAC,IAAI,KAAK,IAAI,IAAI,IAAI,EAAE;AAAA,EAC3C,cAAc,CAAC,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACtC,eAAe,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACjD,eAAe,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAC3D,eAAe,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACjD,eAAe,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAC3D,eAAe,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACjD,eAAe,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAC3D,eAAe,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAC3D,kBAAkB,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACzD,kBAAkB,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAC/C,aAAa,CAAC,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACrC,mBAAmB,CAAC,GAAG;AAAA,EACvB,SAAS,CAAC,CAAC;AAAA,EACX,YAAY,CAAC,CAAC;AAAA,EACd,iBAAiB,CAAC,EAAE;AAAA,EACpB,gBAAgB,CAAC,GAAG;AAAA,EACpB,YAAY,CAAC,GAAG;AAAA,EAChB,WAAW,CAAC,GAAG;AACjB;AAEO,IAAM,gBAAmD;AAAA,EAC9D,OAAO;AAAA,EACP,OAAO;AAAA,EACP,cAAc,CAAC,IAAI,gBAAgB,qBAAqB,EAAE;AAC5D;AAEO,IAAM,qBAAwD;AAAA,EACnE,SAAS;AAAA,EACT,UAAU;AAAA,EACV,MAAM;AAAA,EACN,OAAO;AAAA,EACP,SAAS;AAAA,EACT,UAAU;AAAA,EACV,cAAc,CAAC,GAAG,CAAC;AACrB;AAEO,IAAM,cAAyD;AAAA,EACpE,EAAE,KAAK,aAAa,SAAS,CAAC,GAAG,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAAA,EACzD,EAAE,KAAK,aAAa,SAAS,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAAA,EAC1D,EAAE,KAAK,aAAa,SAAS,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAAA,EAC1D,EAAE,KAAK,aAAa,SAAS,CAAC,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,CAAC,EAAE;AAAA,EACzD,EAAE,KAAK,aAAa,SAAS,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAAA,EAClE,EAAE,KAAK,aAAa,SAAS,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAAA,EAClE,EAAE,KAAK,aAAa,SAAS,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAAA,EAClE,EAAE,KAAK,gBAAgB,SAAS,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAAA,EACjE,EAAE,KAAK,gBAAgB,SAAS,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAC3D;AAEO,IAAM,QAA4B;AAAA,EACvC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,gBAAgB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,iBAAiB,gBAAgB;AAAA,EAClC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,gBAAgB,iBAAiB;AAAA,EAClC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AACvC;AAEO,IAAM,SAAwB;AAAA,EACnC;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAG;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EACtJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAClJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EACr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lJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EACrJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EACpJ;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAG;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACnJ;AAAA,EAAK;AAAA,EAAI;AAAA,EAAG;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACnJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAG;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAC9I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EACtJ;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAClJ;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAG;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACnJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACrJ;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACpJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAClJ;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACnJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACnJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EACnJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAChJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAChJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC7I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAClJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC7I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EACnJ;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACpJ;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAClJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAClJ;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAChJ;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EACpJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EACrJ;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACp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jJ;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAC9I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EACpJ;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACrJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EACpJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EACpJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAC9I;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAI;AAAA,EAClJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAChJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAChJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9I;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAChJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAClJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACpJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAG;AAwB1I,IAAM,QAAuB;AAAA,EACtB;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/E;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC1C;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAG;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAChC;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACtD;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAChD;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAC7C;AAEO,IAAM,QAAuB,CAAC,IAAI,KAAK,KAAK,KAAK,GAAG,IAAI,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG,KAAK,KAAK,GAAG,IAAI,IAAI,IAAI,KAAK,KAAK,KAAK,KAAK,KAAK,IAAI,IAAI,KAAK,IAAI,KAAK,KAAK,KAAK,IAAI,KAAK,GAAG;AAElL,IAAM,OAAsB,CAAC,IAAI,KAAK,KAAK,KAAK,GAAG,IAAI,GAAG;AAE1D,IAAM,OAAO,MAAM,IAAI,CAAC,MAAM,MAAM,EAAE;AAEtC,IAAM,OAAO,MAAM,IAAI,CAAC,MAAM,MAAM,EAAE;AAEtC,IAAM,MAAM,KAAK,IAAI,CAAC,MAAM,MAAM,EAAE;AAO3C,SAAS,qBAAqB,aAAwB;AACpD,QAAM,UAAU,YAAY,IAAI,CAAC,eAAe,WAAW,EAAE;AAC7D,UAAQ,KAAK,YAAY,YAAY,SAAS,GAAG,EAAE;AACnD,SAAO;AACT;AAEO,IAAM,YAAuB;AAAA,EACl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eAA0B,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAE/N,IAAM,mBAA8B,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAEnI,IAAM,gBAA2B,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAEhF,IAAM,gBAA2B,CAAC,CAAC,IAAI,CAAC,GAAG,CAAC,GAAG,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,IAAI,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAE1N,IAAM,oBAA+B,CAAC,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,GAAG,GAAG,CAAC,KAAK,EAAE,GAAG,CAAC,IAAI,GAAG,CAAC;AAEvH,IAAM,iBAA4B,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAEjF,IAAM,mBAA8B;AAAA,EACzC,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EACpE,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EACrE,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EACrE,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EACrE,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EACjE,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAChE;AAEO,IAAM,mBAAmB;AAAA,EAC9B,MAAM,qBAAqB,SAAS;AAAA,EACpC,SAAS,qBAAqB,YAAY;AAAA,EAC1C,aAAa,qBAAqB,gBAAgB;AAAA,EAClD,UAAU,qBAAqB,aAAa;AAAA,EAC5C,UAAU,qBAAqB,aAAa;AAAA,EAC5C,cAAc,qBAAqB,iBAAiB;AAAA,EACpD,WAAW,qBAAqB,cAAc;AAAA,EAC9C,UAAU,qBAAqB,gBAAgB;AACjD;;;ACrsBO,IAAM,aAAa,CAAC,QAA0B,CAAC,KAAK,IAAI,IAAI,SAAS,KAAK,IAAI,WAAW,EAAE,GAAG,KAAK,IAAI,IAAI,SAAS,KAAK,IAAI,WAAW,EAAE,CAAC;AAE3I,IAAM,eAAe,CAAC,QAAkC,CAAC,IAAI,WAAW,MAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM,GAAG,IAAI,WAAW,MAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM,GAAG,CAAC;AAExL,IAAM,WAAW,CAAC,KAAKO,WAAgB,MAAM;AAAA,EAClD,KAAK,MAAM,KAAK,IAAI,GAAG,IAAI,WAAW,EAAE,CAAC;AAAA,EACzC,KAAK,MAAM,KAAK,IAAI,GAAG,IAAI,WAAW,EAAE,CAAC;AAAA,EACzC,KAAK,MAAM,KAAK,IAAKA,OAAM,MAAM,MAAM,GAAI,IAAI,SAAS,EAAE,IAAI,KAAK,IAAI,GAAG,IAAI,WAAW,EAAE,CAAC;AAAA,EAC5F,KAAK,MAAM,KAAK,IAAKA,OAAM,MAAM,MAAM,GAAI,IAAI,SAAS,EAAE,IAAI,KAAK,IAAI,GAAG,IAAI,WAAW,EAAE,CAAC;AAC9F,IAAI,CAAC,GAAG,GAAG,GAAG,CAAC;AAER,IAAM,YAAY,CAAC,KAAKA,WAAgB,MAAM;AAAA,EACnD,IAAI,WAAW,MAAMA,OAAM,MAAM,MAAM;AAAA,EACvC,IAAI,WAAW,MAAMA,OAAM,MAAM,MAAM;AAAA,GACtC,IAAI,SAAS,KAAK,IAAI,WAAW,OAAOA,OAAM,MAAM,MAAM;AAAA,GAC1D,IAAI,SAAS,KAAK,IAAI,WAAW,OAAOA,OAAM,MAAM,MAAM;AAC7D,IAAI,CAAC,GAAG,GAAG,GAAG,CAAC;AAER,IAAM,sBAAsB,CAAC,KAAK,WAAW;AAClD,QAAM,aAAoB,CAAC,IAAI,WAAW,KAAK,OAAO,IAAI,IAAI,WAAW,KAAK,OAAO,EAAE;AACvF,QAAM,WAAkB,CAAC,IAAI,SAAS,KAAK,OAAO,IAAI,IAAI,SAAS,KAAK,OAAO,EAAE;AACjF,SAAO,EAAE,YAAY,UAAU,WAAW,IAAI,WAAW,YAAY,IAAI,WAAW;AACtF;AAEO,IAAM,eAAe,CAAC,KAAKC,QAAO,aAAa;AACpD,QAAM,IAAIA,OAAM,MAAM;AACtB,QAAM,IAAIA,OAAM,MAAM;AACtB,QAAM,SAAS,CAAC,IAAI,WAAW,KAAK,GAAG,IAAI,WAAW,KAAK,GAAG,IAAI,SAAS,KAAK,GAAG,IAAI,SAAS,KAAK,CAAC;AACtG,QAAM,OAAU,MAAM,cAAcA,QAAO,CAAC,MAAM,GAAG,CAAC,CAAC,GAAG,QAAQ;AAClE,QAAMC,QAAU,IAAI,MAAM,UAAU,KAAK;AACzC,EAAG,QAAQ,IAAI;AACf,SAAOA;AACT;AAEO,IAAM,aAAa,CAAC,KAAK,WAAW;AACzC,QAAM,SAAS,aAAa,GAAG;AAC/B,QAAMC,QAAO,WAAW,GAAG;AAC3B,QAAM,WAA6B,CAAC,SAASA,MAAK,KAAK,GAAG,SAASA,MAAK,KAAK,CAAC;AAC9E,SAAO,EAAE,YAAY,CAAC,OAAO,KAAK,SAAS,IAAI,OAAO,KAAK,SAAS,EAAE,GAAY,UAAU,CAAC,OAAO,KAAK,SAAS,IAAI,OAAO,KAAK,SAAS,EAAE,GAAY,WAAW,IAAI,WAAW,YAAY,IAAI,WAAW;AAChN;AAEO,IAAM,cAAc,CAAC,QAAQ;AAClC,QAAM,UAAU,aAAa,GAAG;AAChC,QAAMA,QAAO,WAAW,GAAG;AAC3B,QAAM,WAAW,KAAK,IAAI,GAAGA,KAAI,IAAI;AACrC,SAAO,EAAE,YAAY,CAAC,KAAK,MAAM,QAAQ,KAAK,QAAQ,GAAG,KAAK,MAAM,QAAQ,KAAK,QAAQ,CAAC,GAAY,UAAU,CAAC,KAAK,MAAM,QAAQ,KAAK,QAAQ,GAAG,KAAK,MAAM,QAAQ,KAAK,QAAQ,CAAC,GAAY,WAAW,IAAI,WAAW,YAAY,IAAI,WAAW;AACxP;AAEO,IAAM,gCAAgC,CAAC,cAAc;AAC1D,QAAM,IAAI,UAAU,IAAI,CAAC,MAAM,EAAE,EAAE;AACnC,QAAM,IAAI,UAAU,IAAI,CAAC,MAAM,EAAE,EAAE;AACnC,SAAO,EAAE,YAAY,CAAC,KAAK,IAAI,GAAG,CAAC,GAAG,KAAK,IAAI,GAAG,CAAC,CAAC,GAAY,UAAU,CAAC,KAAK,IAAI,GAAG,CAAC,GAAG,KAAK,IAAI,GAAG,CAAC,CAAC,GAAY,UAAU;AACjI;AAEO,IAAM,sBAAsB,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC;AAE5D,IAAM,mBAAmB,CAAC,UAAU,QAAQ,IAAI,KAAK,KAAK,KAAK,OAAO,QAAQ,KAAK,OAAO,IAAI,KAAK,GAAG;AAEtG,IAAM,kBAAkB,CAAC,QAAQ,WAAW,iBAAiB,KAAK,KAAK,IAAI,KAAK,MAAM,EAAE,OAAO,KAAK,OAAO,KAAK,OAAO,KAAK,OAAO,EAAE,CAAC;AAItI,IAAM,yBAAyB,CAAC,GAAG,MAAM,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC;AAEzE,IAAMC,OAAM,CAAC,IAAc,OAAiB;AACjD,MAAI,UAAU;AACd,WAASC,KAAI,GAAGA,KAAI,GAAG,QAAQA;AAAK,eAAW,GAAGA,MAAK,GAAGA;AAC1D,SAAO;AACT;AAEO,IAAM,qBAAqB,CAAC,KAAK,gBAAgB;AACtD,QAAM,SAAwB,CAAC;AAC/B,WAASA,KAAI,GAAGA,KAAI,IAAI,QAAQA;AAAK,WAAO,KAAK,IAAIA,IAAG,YAAY;AACpE,SAAO;AACT;AAEO,IAAM,4BAA4B,CAAC,MAAM,SAAS;AACvD,QAAM,UAA2B,CAAC;AAClC,QAAMC,QAAO,KAAK;AAClB,WAAS,MAAM,GAAG,MAAMA,OAAM,OAAO;AACnC,YAAQ,KAAK,CAAC,CAAC;AACf,aAAS,MAAM,GAAG,MAAMA,OAAM;AAAO,cAAQ,KAAK,KAAKF,KAAI,KAAK,MAAM,mBAAmB,MAAM,GAAG,CAAC,CAAC;AAAA,EACtG;AACA,SAAO;AACT;AAEO,IAAM,sBAAsB,CAAC,UAAU,WAAW;AACvD,QAAM,OAAO,KAAK,IAAI,QAAQ;AAC9B,QAAM,OAAO,KAAK,IAAI,QAAQ;AAC9B,QAAM,iBAAiB,CAAC,CAAC,MAAM,CAAC,MAAM,CAAC,GAAG,CAAC,MAAM,MAAM,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC;AACpE,QAAM,oBAAoB,uBAAuB,OAAO,IAAI,OAAO,EAAE;AACrE,QAAM,2BAA2B,0BAA0B,mBAAmB,cAAc;AAC5F,QAAM,4BAA4B,uBAAuB,CAAC,OAAO,IAAI,CAAC,OAAO,EAAE;AAC/E,SAAO,0BAA0B,0BAA0B,yBAAyB;AACtF;AAEO,IAAM,wBAAwB,CAAC,WAAW;AAC/C,QAAM,oBAAoB,CAAC,CAAC,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE,GAAG,CAAC,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE,CAAC;AACrF,QAAM,uBAAuB,CAAC,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE;AACxD,QAAM,sBAAsB,CAAC,CAACA,KAAI,kBAAkB,IAAI,oBAAoB,GAAG,CAACA,KAAI,kBAAkB,IAAI,oBAAoB,CAAC;AAC/H,SAAO,CAAC,kBAAkB,GAAG,OAAO,oBAAoB,EAAE,GAAG,kBAAkB,GAAG,OAAO,oBAAoB,EAAE,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC;AAC7H;AAEO,IAAM,cAAc,CAAC,uBAAuB,mBAAmB,CAACA,KAAI,uBAAuB,eAAe,EAAE,GAAGA,KAAI,uBAAuB,eAAe,EAAE,CAAC;AAI5J,SAAS,gBAAgBG,aAAW;AACzC,QAAM,OAAOA,gBAAc,MACvB,EAAE,SAAS,CAAC,CAAC,GAAG,SAAS,CAAC,CAAC,EAAE,IAC7B,EAAE,SAAS,CAACA,cAAY,IAAIA,cAAY,CAAC,GAAG,SAAS,CAAC,GAAG,CAAC,EAAE;AAChE,QAAMC,WAAmC,CAAC;AAC1C,WAASC,KAAI,GAAGA,KAAI,KAAK,QAAQ,QAAQA,MAAK;AAC5C,UAAM,SAAS,KAAK,QAAQA;AAC5B,UAAM,WAAW,KAAK,OAAOF,cAAY,SAAS,KAAK,MAAM;AAC7D,UAAM,WAAW,KAAK,OAAOA,cAAY,SAAS,KAAK,MAAM;AAC7D,UAAM,aAAa,KAAK,QAAQE;AAChC,aAAS,QAAQ,GAAG,QAAQ,UAAU,SAAS;AAC7C,YAAM,UAAU,UAAU,QAAQ;AAClC,eAAS,QAAQ,GAAG,QAAQ,UAAU,SAAS;AAC7C,cAAM,UAAU,UAAU,QAAQ;AAClC,iBAASC,KAAI,GAAGA,KAAI,YAAYA;AAAK,UAAAF,SAAQ,KAAK,CAAC,SAAS,OAAO,CAAC;AAAA,MACtE;AAAA,IACF;AAAA,EACF;AACA,SAAOA;AACT;AAEO,SAAS,mBAAmB,WAAW,KAAK,OAAO,gBAAgBD,aAAW;AACnF,QAAM,UAAU,WAAW,GAAG;AAC9B,QAAM,eAAe,UAAU,IAAI,CAAC,UAAW;AAAA,IAC5C,QAAQ,KAAKA,eAAc,MAAM,KAAMA,cAAY;AAAA,IACnD,QAAQ,KAAKA,eAAc,MAAM,KAAMA,cAAY;AAAA,IACnD,MAAM,MAAM;AAAA,EACf,CAAE;AACF,QAAM,aAAa,SAAU,UAAU,KAAO,KAAK,IAAI,KAAK,IAAI;AAChE,QAAM,uBAAuB,aAAa,oBAAoB,OAAO,CAAC,GAAG,CAAC,CAAC,IAAI;AAC/E,QAAM,gBAAgB,aAAa,aAAa,IAAI,CAAC,UAAW,CAAC,GAAG,YAAY,OAAO,oBAAoB,GAAG,MAAM,EAAE,CAAE,IAAI;AAC5H,QAAM,wBAAwB,aAAa,sBAAsB,cAAc,IAAI;AACnF,QAAM,YAAY,aAAa,GAAG;AAClC,QAAM,UAAU,CAACI,KAAI,WAAW,sBAAsB,EAAE,GAAGA,KAAI,WAAW,sBAAsB,EAAE,CAAC;AACnG,SAAO,cAAc,IAAI,CAAC,UAAW;AAAA,IACnC,KAAK,MAAM,MAAM,KAAK,QAAQ,EAAE;AAAA,IAChC,KAAK,MAAM,MAAM,KAAK,QAAQ,EAAE;AAAA,IAChC,KAAK,MAAM,MAAM,MAAM,CAAC;AAAA,EAC1B,CAAE;AACJ;AAEO,SAAS,oBAAoB,QAAQ,KAAKC,QAAOL,aAAW;AACjE,QAAM,eAAgB,IAAI,UAAU,UAAiB,cAAc,QACxD,cAAc,eACd,mBAAmB;AAC9B,MAAI,QAAQ;AACZ,MAAI,iBAAiB;AACrB,MAAIM;AAEJ,MAAI,UAAUC,KAAI,QAAQ,SAAS,kBAAkB,GAAG;AACtD,YAAQ,gBAAgB,IAAI,UAAU,aAAa,KAAK,IAAI,UAAU,aAAa,GAAG;AACtF,UAAM,aAAa,SAAU,UAAU,KAAO,KAAK,IAAI,KAAK,IAAI;AAChE,QAAI,YAAY;AACd,YAAM,SAAgB,aAAa,GAAG;AACtC,YAAM,YAAmB,CAAC,OAAO,KAAKF,OAAM,MAAM,IAAI,OAAO,KAAKA,OAAM,MAAM,EAAE;AAChF,YAAM,UAAa,MAAM,iBAAiBA,QAAO,OAAO,GAAG,SAAS;AACpE,uBAAiB,oBAAoB,CAAC,OAAO,MAAM;AACnD,MAAAC,QAAO,aAAa,KAAK,SAAS,CAACN,aAAWA,WAAS,CAAC;AACxD,MAAG,QAAQ,OAAO;AAAA,IACpB,OAAO;AACL,MAAAM,QAAO,aAAa,KAAKD,QAAO,CAACL,aAAWA,WAAS,CAAC;AAAA,IACxD;AAAA,EACF,OAAO;AACL,IAAAM,QAAO,aAAa,KAAKD,QAAO,CAACL,aAAWA,WAAS,CAAC;AAAA,EACxD;AACA,SAAO,CAAC,OAAO,gBAAgBM,KAAI;AACrC;AAEO,IAAM,iBAAiB,CAAC,SAAS;AACtC,QAAM,IAAI,KAAK,IAAI,CAAC,MAAM,EAAE,EAAE;AAC9B,QAAM,IAAI,KAAK,IAAI,CAAC,MAAM,EAAE,EAAE;AAO9B,SAAO,CAAC,KAAK,IAAI,GAAG,CAAC,KAAK,KAAK,IAAI,GAAG,CAAC,IAAI,KAAK,IAAI,GAAG,CAAC,KAAK,GAAG,KAAK,IAAI,GAAG,CAAC,KAAK,KAAK,IAAI,GAAG,CAAC,IAAI,KAAK,IAAI,GAAG,CAAC,KAAK,CAAC;AACxH;AAEO,IAAM,mBAAmB,CAAC,MAAM,gBAAgB;AACrD,QAAM,SAAS,eAAe,IAAI;AAClC,QAAM,UAAU,WAAW,WAAW;AACtC,QAAM,gBAAgB;AAAA,IACpB,YAAY,CAAC,OAAO,KAAK,QAAQ,KAAK,GAAG,OAAO,KAAK,QAAQ,KAAK,CAAC;AAAA,IACnE,UAAU,CAAC,OAAO,KAAK,QAAQ,KAAK,GAAG,OAAO,KAAK,QAAQ,KAAK,CAAC;AAAA,EACnE;AACA,SAAO;AACT;;;ACnMA,IAAM,iBAAiB;AACvB,IAAM,qBAAqB;AAC3B,IAAIE;AACJ,IAAI,UAAyB;AAC7B,IAAI,YAAY;AAChB,IAAI,aAA4B;AAIzB,IAAM,OAAO,MAAM;AAE1B,eAAsBC,MAAKC,SAAqC;AA1BhE;AA2BE,MAAIC,KAAI;AAAS,IAAAH,SAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,SAAQ,MAAM,WAAU,KAAAE,QAAO,KAAK,aAAZ,mBAAsB,SAAS;AAAA,WAC1DA,QAAO;AAAO,QAAI,iBAAiBF,OAAM,WAAW;AAC7D,cAAYA,OAAM,OAAO,GAAG,QAAQA,OAAM,OAAO,GAAG,MAAM,KAAK;AAC/D,eAAgB,OAAO,WAAW,OAAO;AACzC,YAAa,SAAc,gBAAgB,SAAS,CAAC;AACrD,SAAOA;AACT;AAEA,SAAS,YAAY,YAAoB;AACvC,QAAMI,KAA4B,CAAC;AACnC,EAAAA,GAAE,YAAe,MAAM,YAAY,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,CAAC,CAAC;AAClD,EAAAA,GAAE,UAAa,KAAIA,GAAE,WAAW,OAAO;AACvC,EAAAA,GAAE,WAAc,MAAM,YAAY,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,CAAC,CAAC;AACjD,EAAAA,GAAE,qBAAwB,IAAIA,GAAE,UAAU,UAAU;AACpD,EAAAA,GAAE,oBAAuB,IAAIA,GAAE,SAAS,UAAU;AAClD,EAAAA,GAAE,cAAiB,IAAIA,GAAE,oBAAoB,UAAU,GAAG;AAC1D,EAAAA,GAAE,SAAY,IAAIA,GAAE,mBAAmBA,GAAE,WAAW;AACpD,EAAAA,GAAE,OAAU,KAAIA,GAAE,mBAAmBA,GAAE,WAAW;AAClD,EAAAA,GAAE,kBAAqB,IAAIA,GAAE,QAAQ,UAAU;AAC/C,EAAAA,GAAE,gBAAmB,IAAIA,GAAE,MAAM,UAAU;AAC3C,QAAM,QAAW,SAAS,CAACA,GAAE,iBAAiBA,GAAE,aAAa,GAAG,CAAC;AACjE,SAAO,KAAKA,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,SAAO;AACT;AAEA,eAAsB,SAAS,YAAoBH,SAAgB;AArDnE;AAuDE,MAAK,CAAC,cAAgB,WAAW,yBAA2B,WAAW,MAAM,WAAW,KAAO,WAAW,MAAM,KAAK,KAAO,WAAW,MAAM,KAAK;AAAI,WAAO,CAAC;AAC9J,QAAME,KAA4B,CAAC;AACnC,EAAAA,GAAE,UAAa,MAAM,eAAe,YAAY,CAAC,WAAW,SAAS,CAAC;AACtE,EAAAA,GAAE,MAAS,IAAIA,GAAE,SAAS,UAAU,KAAK;AACzC,EAAAA,GAAE,aAAgB,IAAIA,GAAE,KAAK,UAAU,IAAI;AAC3C,QAAM,MAAMJ,UAAA,gBAAAA,OAAO,QAAQI,GAAE;AAC7B,MAAI,MAAM,QAAQ,GAAG,KAAK,IAAI,SAAS,GAAG;AACxC,UAAM,SAAS,IAAI,KAAK,CAAC,GAAG,MAAM,EAAE,OAAO,EAAE,IAAI;AACjD,IAAAA,GAAE,YAAe,OAAO,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,CAAC;AACjD,IAAAA,GAAE,YAAe,OAAO,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,CAAC;AACjD,IAAAA,GAAE,SAAY,OAAO,CAACA,GAAE,WAAWA,GAAE,SAAS,GAAG,CAAC;AAClD,IAAAA,GAAE,QAAW,QAAQA,GAAE,QAAQ,CAAC;AAAA,EAClC,WAAW,MAAM,QAAQ,GAAG,GAAG;AAC7B,IAAAA,GAAE,QAAW,QAAQ,IAAI,EAAE;AAAA,EAC7B,OAAO;AACL,IAAAA,GAAE,QAAW,QAAQ,GAAG;AAAA,EAC1B;AACA,EAAG,QAAQ,GAAG;AACd,EAAAA,GAAE,QAAQ,YAAYA,GAAE,KAAK;AAC7B,EAAAA,GAAE,SAAY,MAAMA,GAAE,OAAO,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,CAAC,CAAC;AAC5C,EAAAA,GAAE,UAAa,QAAQA,GAAE,MAAM;AAC/B,EAAAA,GAAE,SAAY,QAAQA,GAAE,OAAO;AAC/B,EAAAA,GAAE,MAAM,MAAS,MAAM,uBAAuBA,GAAE,OAAOA,GAAE,UAAS,KAAAF,QAAO,KAAK,aAAZ,mBAAsB,gBAAe,KAAK,KAAAA,QAAO,KAAK,aAAZ,mBAAsB,iBAAgB,KAAK,KAAAA,QAAO,KAAK,aAAZ,mBAAsB,kBAAiB,CAAE;AAChM,QAAM,MAAM,MAAME,GAAE,IAAI,MAAM;AAC9B,QAAM,QAA0B,CAAC;AACjC,QAAM,SAAS,MAAMA,GAAE,OAAO,KAAK;AACnC,WAASE,KAAI,GAAGA,KAAI,IAAI,QAAQA,MAAK;AACnC,UAAM,aAAa,OAAO,IAAIA;AAC9B,QAAI,gBAAc,KAAAJ,QAAO,KAAK,aAAZ,mBAAsB,kBAAiB,IAAI;AAC3D,YAAM,IAA4B,CAAC;AACnC,QAAE,OAAU,MAAME,GAAE,OAAO,CAAC,IAAIE,KAAI,CAAC,GAAG,CAAC,GAAG,EAAE,CAAC;AAC/C,QAAE,QAAW,MAAMF,GAAE,OAAO,CAAC,IAAIE,KAAI,iBAAiB,CAAC,GAAG,CAAC,GAAG,EAAE,CAAC;AACjE,QAAE,UAAa,QAAQ,EAAE,KAAK;AAC9B,QAAE,YAAe,QAAQ,EAAE,SAAS,CAAC,gBAAgB,EAAE,CAAC;AACxD,YAAM,SAAS,MAAM,EAAE,KAAK,KAAK;AACjC,YAAM,SAAS;AAAA,QACb,YAAY,CAAC,OAAO,IAAI,OAAO,EAAE;AAAA,QACjC,UAAU,CAAC,OAAO,IAAI,OAAO,EAAE;AAAA,QAC/B,WAAY,MAAM,EAAE,UAAU,MAAM;AAAA,QACpC;AAAA,MACF;AACA,YAAM,YAAiB,oBAAoB,QAAQ,EAAE,WAAW,MAAM,MAAM,KAAK,YAAY,WAAW,MAAM,MAAM,KAAK,SAAS,CAAC;AACnI,YAAM,cAAmB,WAAW,WAAWJ,QAAO,KAAK,YAAY,kBAAkB;AACzF,YAAM,aAAkB,YAAY,WAAW;AAC/C,YAAM,KAAK,UAAU;AACrB,aAAO,KAAK,CAAC,EAAE,QAAQ,CAACG,YAAc,QAAQ,EAAEA,QAAO,CAAC;AAAA,IAC1D;AAAA,EACF;AACA,SAAO,KAAKD,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,SAAO;AACT;;;ACzGA;AAAA;AAAA;AAAA;AAAA;AAEO,IAAM,MAAqB;AAAA,EAChC;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AAEO,IAAM,YAAsC;AAAA,EACjD,WAAW,CAAC,gBAAgB,eAAe;AAAA,EAC3C,MAAM,CAAC,YAAY,SAAS;AAAA,EAC5B,OAAO,CAAC,aAAa,YAAY;AAAA,EACjC,cAAc,CAAC,WAAW,UAAU;AAAA,EACpC,cAAc,CAAC,YAAY,WAAW;AAAA,EACtC,UAAU,CAAC,aAAa,YAAY,UAAU;AAAA,EAC9C,WAAW,CAAC,gBAAgB,SAAS;AAAA,EACrC,cAAc,CAAC,gBAAgB,WAAW;AAAA,EAC1C,cAAc,CAAC,aAAa,WAAW;AAAA,EACvC,UAAU,CAAC,aAAa,UAAU;AAAA,EAClC,eAAe,CAAC,YAAY,WAAW;AAAA,EACvC,eAAe,CAAC,YAAY,WAAW;AAAA,EACvC,eAAe,CAAC,YAAY,WAAW;AAAA,EACvC,gBAAgB,CAAC,iBAAiB,gBAAgB;AAAA,EAClD,eAAe,CAAC,YAAY,WAAW;AAAA,EACvC,eAAe,CAAC,aAAa,YAAY;AAAA,EACzC,WAAW,CAAC,cAAc,aAAa,WAAW;AAAA,EAClD,YAAY,CAAC,iBAAiB,UAAU;AAAA,EACxC,eAAe,CAAC,iBAAiB,YAAY;AAAA,EAC7C,eAAe,CAAC,cAAc,YAAY;AAAA,EAC1C,WAAW,CAAC,cAAc,WAAW;AAAA,EACrC,gBAAgB,CAAC,aAAa,YAAY;AAAA,EAC1C,gBAAgB,CAAC,aAAa,YAAY;AAAA,EAC1C,gBAAgB,CAAC,aAAa,YAAY;AAAA,EAC1C,iBAAiB,CAAC,kBAAkB,iBAAiB;AACvD;;;AC/DA,IAAME,aAAY;AAClB,IAAI;AACJ,IAAM,YAAY;AAClB,IAAM,UAAU,CAAC,GAAG,IAAI,IAAI,IAAI,EAAE;AAElC,eAAsB,gBAAgB;AACpC,QAAMC,WAA2C,CAAC;AAClD,MAAI,UAAU;AACd,SAAO,UAAU,WAAW;AAC1B,QAAI,cAAc;AAClB,QAAI,sBAAsB;AAC1B,WAAO,sBAAsB,QAAQ,UAAU,QAAQ,yBAAyB,QAAQ,UAAU;AAChG,qBAAe;AACf;AAAA,IACF;AACA,UAAM,SAAS,QAAQ;AACvB,UAAM,mBAAmB,KAAK,KAAKD,aAAY,MAAM;AACrD,UAAM,kBAAkB,KAAK,KAAKA,aAAY,MAAM;AACpD,aAAS,IAAI,GAAG,IAAI,kBAAkB,EAAE,GAAG;AACzC,eAAS,IAAI,GAAG,IAAI,iBAAiB,EAAE,GAAG;AACxC,iBAAS,WAAW,GAAG,WAAW,aAAa,EAAE,UAAU;AACzD,UAAAC,SAAQ,KAAK,EAAE,IAAI,IAAI,OAAO,iBAAiB,IAAI,IAAI,OAAO,iBAAiB,CAAC;AAAA,QAClF;AAAA,MACF;AAAA,IACF;AACA,cAAU;AAAA,EACZ;AACA,iBAAe,EAAE,GAAM,SAASA,SAAQ,IAAI,CAAC,MAAM,EAAE,CAAC,CAAC,GAAG,GAAM,SAASA,SAAQ,IAAI,CAAC,MAAM,EAAE,CAAC,CAAC,EAAE;AACpG;;;ACjCO,SAAS,KAAK,WAAyBC,cAA+B,CAAC,GAAG,CAAC,GAAG;AACnF,QAAMC,UAAS,CAAC,UAAU,IAAI,CAAC,OAAO,GAAG,EAAE,GAAG,UAAU,IAAI,CAAC,OAAO,GAAG,EAAE,CAAC;AAC1E,QAAMC,OAAM,CAAC,KAAK,IAAI,GAAGD,QAAO,EAAE,GAAG,KAAK,IAAI,GAAGA,QAAO,EAAE,CAAC;AAC3D,QAAME,OAAM,CAAC,KAAK,IAAI,GAAGF,QAAO,EAAE,GAAG,KAAK,IAAI,GAAGA,QAAO,EAAE,CAAC;AAC3D,QAAM,MAAW,CAACC,KAAI,IAAIA,KAAI,IAAIC,KAAI,KAAKD,KAAI,IAAIC,KAAI,KAAKD,KAAI,EAAE;AAClE,QAAM,SAAc,CAAC,IAAI,KAAKF,YAAW,IAAI,IAAI,KAAKA,YAAW,IAAI,IAAI,KAAKA,YAAW,IAAI,IAAI,KAAKA,YAAW,EAAE;AACnH,SAAO,EAAE,KAAK,OAAO;AACvB;AAEO,SAASI,QAAO,WAAyBJ,cAA+B,CAAC,GAAG,CAAC,GAAG;AACrF,QAAMC,UAAS,CAAC,UAAU,IAAI,CAAC,OAAO,GAAG,EAAE,GAAG,UAAU,IAAI,CAAC,OAAO,GAAG,EAAE,CAAC;AAC1E,QAAMC,OAAM,CAAC,KAAK,IAAI,GAAGD,QAAO,EAAE,GAAG,KAAK,IAAI,GAAGA,QAAO,EAAE,CAAC;AAC3D,QAAME,OAAM,CAAC,KAAK,IAAI,GAAGF,QAAO,EAAE,GAAG,KAAK,IAAI,GAAGA,QAAO,EAAE,CAAC;AAC3D,QAAM,SAAS,EAAEC,KAAI,KAAKC,KAAI,MAAM,IAAID,KAAI,KAAKC,KAAI,MAAM,CAAC;AAC5D,QAAM,OAAO,KAAK,IAAI,OAAO,KAAKD,KAAI,IAAI,OAAO,KAAKA,KAAI,IAAI,CAAC,OAAO,KAAKC,KAAI,IAAI,CAAC,OAAO,KAAKA,KAAI,EAAE;AACtG,QAAM,MAAW,CAAC,KAAK,MAAM,OAAO,KAAK,IAAI,GAAG,KAAK,MAAM,OAAO,KAAK,IAAI,GAAG,KAAK,MAAM,IAAI,IAAI,GAAG,KAAK,MAAM,IAAI,IAAI,CAAC;AACxH,QAAM,SAAc,CAAC,IAAI,KAAKH,YAAW,IAAI,IAAI,KAAKA,YAAW,IAAI,IAAI,KAAKA,YAAW,IAAI,IAAI,KAAKA,YAAW,EAAE;AACnH,SAAO,EAAE,KAAK,OAAO;AACvB;AAEO,SAASK,OAAM,KAAU,WAAmB;AACjD,QAAM,OAAO,CAAC,IAAI,KAAK,WAAW,IAAI,KAAK,SAAS;AACpD,QAAM,SAAc;AAAA,IAClB,IAAI,MAAM,KAAK,KAAK,IAAI,MAAM;AAAA,IAC9B,IAAI,MAAM,KAAK,KAAK,IAAI,MAAM;AAAA,IAC9B,KAAK;AAAA,IACL,KAAK;AAAA,EACP;AACA,SAAO;AACT;;;AChBA,IAAMC,OAAM,EAAE,SAAS,KAAK;AAE5B,IAAM,SAAwE,EAAE,UAAU,MAAM,WAAW,KAAK;AAChH,IAAMC,aAAyE,EAAE,UAAU,CAAC,KAAK,GAAG,GAAG,WAAW,CAAC,KAAK,GAAG,EAAE;AAC7H,IAAIC,WAAU,OAAO;AACrB,IAAM,cAA2D;AAAA,EAC/D,WAAW,CAAC,SAAS,2BAA2B,sBAAsB,YAAY,iBAAiB;AAAA,EACnG,UAAU,CAAC;AACb;AAEA,IAAI,QAA2B;AAC/B,IAAI;AACJ,IAAI,UAA8B,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AACjE,IAAIC,YAAW;AAEf,IAAMC,WAAU,CAAC,MAAO,IAAK,KAAK,IAAI,KAAK,IAAI,CAAC;AAEhD,eAAsB,WAAWC,SAAqC;AACpE,MAAIL,KAAI;AAAS,WAAO,WAAW;AACnC,MAAI,CAAC,OAAO,YAAYK,QAAO,KAAK,eAAeA,QAAO,KAAK,YAAY,gBAAgB,IAAI;AAC7F,WAAO,WAAW,MAAM,UAAUA,QAAO,KAAK,YAAY,YAAY;AACtE,UAAM,SAAS,OAAO,OAAO,OAAO,SAAS,eAAe,SAAS;AACrE,IAAAJ,WAAU,SAAS,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAC9F,IAAAA,WAAU,SAAS,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAAA,EAChG,WAAWI,QAAO,SAAS,OAAO;AAAU,QAAI,iBAAiB,OAAO,SAAS,WAAW;AAC5F,QAAa,cAAc;AAC3B,SAAO,OAAO;AAChB;AAEA,eAAsB,SAASA,SAAqC;AAClE,MAAIL,KAAI;AAAS,WAAO,YAAY;AACpC,MAAI,CAAC,OAAO,WAAW;AACrB,WAAO,YAAY,MAAM,UAAUK,QAAO,KAAK,SAAS;AACxD,UAAM,SAAS,OAAO,OAAO,OAAO,UAAU,eAAe,SAAS;AACtE,IAAAJ,WAAU,UAAU,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAC/F,IAAAA,WAAU,UAAU,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAAA,EACjG,WAAWI,QAAO;AAAO,QAAI,iBAAiB,OAAO,UAAU,WAAW;AAC1E,SAAO,OAAO;AAChB;AAQA,eAAe,aAAaC,QAAeC,OAA+B;AACxE,QAAMC,KAA4B,CAAC;AACnC,MAAI,CAACF,OAAM,SAAS,CAACA,OAAM,MAAM,MAAM,CAACA,OAAM,MAAM;AAAI,WAAOA;AAC/D,MAAI;AACJ,MAAI,SAAS;AACX,IAAAE,GAAE,UAAa,MAAM,cAAcF,QAAO,CAAC,OAAO,GAAG,CAAC,CAAC,GAAG,CAACA,OAAM,MAAM,IAAIA,OAAM,MAAM,EAAE,CAAC;AAAA,EAC5F;AACA,MAAIA,OAAM,MAAM,OAAOA,OAAM,MAAM,IAAI;AACrC,UAAM,SAA2B;AAAA,MAC/BA,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI;AAAA,MACtFA,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI;AAAA,IACxF;AACA,UAAM,QAA0B;AAAA,MAC9BA,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI;AAAA,MACtFA,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI;AAAA,IACxF;AACA,cAAU;AAAA,MACR,CAAC,GAAG,CAAC;AAAA,MACL;AAAA,MACA;AAAA,MACA,CAAC,GAAG,CAAC;AAAA,IACP;AACA,IAAAE,GAAE,MAAS,IAAIA,GAAE,WAAWF,QAAO,OAAO;AAC1C,IAAAE,GAAE,SAAY,MAAM,eAAeA,GAAE,KAAK,CAACD,OAAMA,KAAI,CAAC;AACtD,YAAW,IAAIC,GAAE,QAAQ,UAAU,KAAK;AAAA,EAC1C,WAAWF,OAAM,MAAM,OAAOC,OAAM;AAClC,IAAAC,GAAE,SAAY,MAAM,eAAeA,GAAE,WAAWF,QAAO,CAACC,OAAMA,KAAI,CAAC;AACnE,YAAW,IAAIC,GAAE,QAAQ,UAAU,KAAK;AAAA,EAC1C,OAAO;AACL,YAAW,IAAIA,GAAE,WAAWF,QAAO,UAAU,KAAK;AAAA,EACpD;AACA,SAAO,KAAKE,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,SAAO;AACT;AAEA,SAAS,iBAAiB,WAAgCC,aAAmD;AAC3G,aAAWC,QAAO,WAAW;AAC3B,IAAAA,KAAI,WAAW;AAAA,MACb,KAAK,MAAMA,KAAI,SAAS,MAAMD,YAAW,KAAK,QAAQ,GAAG,KAAK,QAAQ,GAAG,MAAMA,YAAW,KAAK,QAAQ,GAAG,EAAE;AAAA,MAC5G,KAAK,MAAMC,KAAI,SAAS,MAAMD,YAAW,KAAK,QAAQ,GAAG,KAAK,QAAQ,GAAG,MAAMA,YAAW,KAAK,QAAQ,GAAG,EAAE;AAAA,MAC5GC,KAAI,SAAS;AAAA,IACf;AACA,IAAAA,KAAI,cAAc,CAACA,KAAI,SAAS,KAAKD,YAAW,IAAIC,KAAI,SAAS,KAAKD,YAAW,IAAI,IAAKC,KAAI,SAAS,MAAiBD,YAAW,KAAKA,YAAW,GAAG;AAAA,EACxJ;AACA,MAAI,SAAS;AACX,eAAWC,QAAO,WAAW;AAC3B,MAAAA,KAAI,cAAc;AAAA,QAChBA,KAAI,YAAY,KAAK,QAAQ;AAAA,QAC7BA,KAAI,YAAY,KAAK,QAAQ;AAAA,QAC7BA,KAAI,YAAY;AAAA,MAClB;AACA,MAAAA,KAAI,WAAW;AAAA,QACb,KAAK,MAAMA,KAAI,YAAY,KAAKD,YAAW,EAAE;AAAA,QAC7C,KAAK,MAAMC,KAAI,YAAY,KAAKD,YAAW,EAAE;AAAA,QAC7CC,KAAI,YAAY;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AAEA,eAAe,aAAa,WAAgC;AAE1D,QAAM,WAAW,UAAU,KAAK,CAAC,MAAM,EAAE,SAAS,UAAU;AAC5D,QAAM,YAAY,UAAU,KAAK,CAAC,MAAM,EAAE,SAAS,WAAW;AAC9D,QAAM,YAAY,UAAU,KAAK,CAAC,MAAM,EAAE,SAAS,WAAW;AAC9D,WAAS,SAAS,OAAO,UAAU,SAAS,MAAM,MAAM,UAAU,SAAS,MAAM,MAAM;AACvF,QAAM,YAAY,UAAU,KAAK,CAAC,MAAM,EAAE,SAAS,WAAW;AAC9D,QAAM,aAAa,UAAU,KAAK,CAAC,MAAM,EAAE,SAAS,YAAY;AAChE,QAAM,aAAa,UAAU,KAAK,CAAC,MAAM,EAAE,SAAS,YAAY;AAChE,YAAU,SAAS,OAAO,WAAW,SAAS,MAAM,MAAM,WAAW,SAAS,MAAM,MAAM;AAC5F;AAEA,eAAe,gBAAgBL,QAAeM,SAAgBF,aAA0D;AAtIxH;AA8IE,QAAMF,KAA4B,CAAC;AACnC,GAACA,GAAE,IAAqBA,GAAE,cAA+BA,GAAE,SAAyBA,GAAE,OAAwBA,GAAE,QAAiB,KAAI,YAAO,cAAP,mBAAkB,QAAQF,QAAO,YAAY;AAClL,QAAM,aAAa,MAAME,GAAE,SAAS,KAAK,GAAG;AAC5C,QAAM,SAAS,MAAMA,GAAE,GAAG,KAAK;AAC/B,QAAM,YAAY,MAAMA,GAAE,MAAM,KAAK;AACrC,SAAO,KAAKA,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,QAAM,oBAAyC,CAAC;AAChD,QAAM,QAAQ;AACd,WAASI,KAAI,GAAGA,KAAI,OAAO,SAAS,OAAOA,MAAK;AAC9C,UAAM,QAAQC,SAAQ,OAAO,QAAQD,KAAI,EAAE;AAC3C,UAAM,WAAWC,SAAQ,OAAO,QAAQD,KAAI,EAAE;AAC9C,UAAM,WAAW,KAAK,MAAM,MAAM,QAAQ,WAAW,SAAS,IAAI;AAClE,UAAM,cAAqB,CAAC,OAAO,QAAQA,KAAI,KAAKE,WAAU,UAAU,IAAI,OAAO,QAAQF,KAAI,KAAKE,WAAU,UAAU,IAAI,OAAO,QAAQF,KAAI,KAAK,CAAC;AACrJ,UAAM,WAAkB,CAAC,KAAK,MAAMH,YAAW,KAAK,YAAY,EAAE,GAAG,KAAK,MAAMA,YAAW,KAAK,YAAY,EAAE,GAAG,YAAY,EAAY;AACzI,UAAMM,YAAkB,CAAC,UAAU,QAAQH,KAAI,IAAI,UAAU,QAAQA,KAAI,IAAI,UAAU,QAAQA,KAAI,KAAK,CAAC;AACzG,sBAAkB,KAAK,EAAE,MAAa,IAAIA,KAAoB,aAAa,UAAU,UAAAG,WAAU,OAAO,SAAS,CAAC;AAAA,EAClH;AACA,MAAI,aAAaJ,QAAO,KAAK,iBAAiB;AAAI,WAAO;AACzD,eAAa,iBAAiB;AAC9B,QAAM,YAAiC,iBAAiB,mBAAmBF,WAAU;AACrF,QAAM,OAAO,UAAU,IAAI,CAAC,MAAM,EAAE,QAAQ;AAC5C,QAAM,QAAY,KAAK,MAAM,CAACA,YAAW,IAAIA,YAAW,EAAE,CAAC;AAC3D,QAAMO,eAAiD,CAAC;AACxD,aAAW,CAAC,MAAM,OAAO,KAAK,OAAO,QAAe,SAAS,GAAG;AAC9D,UAAM,KAAqB,CAAC;AAC5B,aAASJ,KAAI,GAAGA,KAAI,QAAQ,SAAS,GAAGA,MAAK;AAC3C,YAAM,MAAM,UAAU,KAAK,CAACF,SAAQA,KAAI,SAAS,QAAQE,GAAE;AAC3D,YAAM,MAAM,UAAU,KAAK,CAACF,SAAQA,KAAI,SAAS,QAAQE,KAAI,EAAE;AAC/D,UAAI,OAAO;AAAK,WAAG,KAAK,CAAC,IAAI,UAAU,IAAI,QAAQ,CAAC;AAAA,IACtD;AACA,IAAAI,aAAY,QAAQ;AAAA,EACtB;AACA,QAAMC,QAAO,EAAE,IAAI,GAAG,OAAO,KAAK,MAAM,MAAM,SAAS,IAAI,KAAK,KAAK,MAAM,KAAK,QAAQ,MAAM,QAAQ,WAAW,aAAAD,aAAY;AAC7H,SAAOC;AACT;AAgCA,eAAsBC,SAAQb,QAAeM,SAAuC;AAClF,QAAMF,cAA+B,CAACJ,OAAM,MAAM,MAAM,GAAGA,OAAM,MAAM,MAAM,CAAC;AAC9E,QAAM,YAAYM,QAAO,KAAK,YAAY,KAAM,IAAI,IAAIQ;AACxD,QAAM,YAAYC,YAAWT,QAAO,KAAK,cAAc;AACvD,MAAIA,QAAO,eAAe,YAAY,aAAa,UAAU,MAAM;AACjE,IAAAS;AAAA,EACF,OAAO;AACL,UAAMb,KAA4B,CAAC;AAOnC,IAAAA,GAAE,YAAY,MAAM,aAAaF,QAAO,GAAG;AAC3C,YAAQ,MAAM,gBAAgBE,GAAE,WAAWI,SAAQF,WAAU;AAe7D,WAAO,KAAKF,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,IAAAW,YAAW,IAAI;AACf,IAAAC,WAAU;AAAA,EACZ;AACA,SAAO,QAAQ,CAAC,KAAK,IAAI,CAAC;AAC5B;;;AChPO,IAAM,SAAS;AAAA,EACpB,EAAE,OAAO,GAAG,OAAO,SAAS;AAAA,EAC5B,EAAE,OAAO,GAAG,OAAO,UAAU;AAAA,EAC7B,EAAE,OAAO,GAAG,OAAO,MAAM;AAAA,EACzB,EAAE,OAAO,GAAG,OAAO,aAAa;AAAA,EAChC,EAAE,OAAO,GAAG,OAAO,WAAW;AAAA,EAC9B,EAAE,OAAO,GAAG,OAAO,MAAM;AAAA,EACzB,EAAE,OAAO,GAAG,OAAO,QAAQ;AAAA,EAC3B,EAAE,OAAO,GAAG,OAAO,QAAQ;AAAA,EAC3B,EAAE,OAAO,GAAG,OAAO,OAAO;AAAA,EAC1B,EAAE,OAAO,IAAI,OAAO,gBAAgB;AAAA,EACpC,EAAE,OAAO,IAAI,OAAO,eAAe;AAAA,EACnC,EAAE,OAAO,IAAI,OAAO,YAAY;AAAA,EAChC,EAAE,OAAO,IAAI,OAAO,gBAAgB;AAAA,EACpC,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,MAAM;AAAA,EAC1B,EAAE,OAAO,IAAI,OAAO,MAAM;AAAA,EAC1B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,MAAM;AAAA,EAC1B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,UAAU;AAAA,EAC9B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,UAAU;AAAA,EAC9B,EAAE,OAAO,IAAI,OAAO,MAAM;AAAA,EAC1B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,UAAU;AAAA,EAC9B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,YAAY;AAAA,EAChC,EAAE,OAAO,IAAI,OAAO,cAAc;AAAA,EAClC,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,eAAe;AAAA,EACnC,EAAE,OAAO,IAAI,OAAO,iBAAiB;AAAA,EACrC,EAAE,OAAO,IAAI,OAAO,aAAa;AAAA,EACjC,EAAE,OAAO,IAAI,OAAO,YAAY;AAAA,EAChC,EAAE,OAAO,IAAI,OAAO,gBAAgB;AAAA,EACpC,EAAE,OAAO,IAAI,OAAO,SAAS;AAAA,EAC7B,EAAE,OAAO,IAAI,OAAO,aAAa;AAAA,EACjC,EAAE,OAAO,IAAI,OAAO,MAAM;AAAA,EAC1B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,SAAS;AAAA,EAC7B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,SAAS;AAAA,EAC7B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,SAAS;AAAA,EAC7B,EAAE,OAAO,IAAI,OAAO,UAAU;AAAA,EAC9B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,eAAe;AAAA,EACnC,EAAE,OAAO,IAAI,OAAO,MAAM;AAAA,EAC1B,EAAE,OAAO,IAAI,OAAO,eAAe;AAAA,EACnC,EAAE,OAAO,IAAI,OAAO,SAAS;AAAA,EAC7B,EAAE,OAAO,IAAI,OAAO,KAAK;AAAA,EACzB,EAAE,OAAO,IAAI,OAAO,SAAS;AAAA,EAC7B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,SAAS;AAAA,EAC7B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,aAAa;AAAA,EACjC,EAAE,OAAO,IAAI,OAAO,YAAY;AAAA,EAChC,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,UAAU;AAAA,EAC9B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,eAAe;AAAA,EACnC,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,aAAa;AAAA,EACjC,EAAE,OAAO,IAAI,OAAO,aAAa;AAAA,EACjC,EAAE,OAAO,IAAI,OAAO,aAAa;AACnC;;;ACrEA,IAAIC;AACJ,IAAIC,aAAY;AAChB,IAAIC,QAAuB,CAAC;AAC5B,IAAIC,YAAW;AACf,IAAIC,WAAU,OAAO;AAErB,eAAsBC,MAAKC,SAAqC;AAC9D,MAAIC,KAAI;AAAS,IAAAP,SAAQ;AACzB,MAAI,CAACA,QAAO;AAEV,IAAAA,SAAQ,MAAM,UAAUM,QAAO,OAAO,SAAS;AAC/C,UAAM,SAAS,OAAO,OAAON,OAAM,eAAe,SAAS;AAC3D,IAAAC,aAAY,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAAA,EACpF,WAAWK,QAAO;AAAO,QAAI,iBAAiBN,OAAM,WAAW;AAC/D,SAAOA;AACT;AAEA,eAAeQ,SAAQ,KAAoB,aAA+BF,SAAgB;AACxF,MAAI,CAAC;AAAK,WAAO,CAAC;AAClB,QAAMG,KAA4B,CAAC;AACnC,QAAM,UAA+B,CAAC;AACtC,QAAM,aAAa,MAAM,IAAI,MAAM;AACnC,EAAAA,GAAE,UAAa,QAAQ,GAAG;AAC1B,QAAM,MAAS,MAAMA,GAAE,SAAS,GAAG,CAAC;AACpC,EAAAA,GAAE,QAAW,MAAM,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,GAAG,CAAC;AACtD,EAAAA,GAAE,QAAW,QAAQA,GAAE,KAAK;AAC5B,EAAAA,GAAE,SAAY,QAAQ,IAAI,EAAE;AAC5B,EAAAA,GAAE,UAAa,QAAQ,IAAI,EAAE;AAC7B,EAAG,QAAQ,CAAC,KAAK,GAAG,GAAG,CAAC;AACxB,EAAAA,GAAE,MAAM,MAAS,MAAM,uBAAuBA,GAAE,OAAOA,GAAE,QAAQH,QAAO,OAAO,aAAaA,QAAO,OAAO,cAAeA,QAAO,OAAO,iBAAiB,CAAE;AAC1J,QAAM,MAAM,MAAMG,GAAE,IAAI,KAAK;AAC7B,MAAIC,KAAI;AACR,aAAW,MAAM,MAAM,KAAK,GAAG,GAAG;AAChC,UAAM,QAAQ,KAAK,MAAM,MAAM,WAAW,GAAG,IAAI,EAAE,IAAI;AACvD,UAAM,WAAW,WAAW,GAAG,IAAI;AACnC,UAAM,QAAQ,OAAO,UAAU;AAC/B,UAAM,CAAC,GAAG,CAAC,IAAI;AAAA,MACb,WAAW,GAAG,IAAI,KAAKT;AAAA,MACvB,WAAW,GAAG,IAAI,KAAKA;AAAA,IACzB;AACA,UAAM,SAAc;AAAA,MAClB;AAAA,MACA;AAAA,MACA,WAAW,GAAG,IAAI,KAAKA,aAAY;AAAA,MACnC,WAAW,GAAG,IAAI,KAAKA,aAAY;AAAA,IACrC;AACA,UAAM,MAAW;AAAA,MACf,KAAK,MAAM,OAAO,KAAK,YAAY,EAAE;AAAA,MACrC,KAAK,MAAM,OAAO,KAAK,YAAY,EAAE;AAAA,MACrC,KAAK,MAAM,OAAO,KAAK,YAAY,EAAE;AAAA,MACrC,KAAK,MAAM,OAAO,KAAK,YAAY,EAAE;AAAA,IACvC;AACA,YAAQ,KAAK,EAAE,IAAIS,MAAK,OAAO,OAAO,UAAU,OAAO,KAAK,OAAO,CAAC;AAAA,EACtE;AACA,SAAO,KAAKD,EAAC,EAAE,QAAQ,CAACE,YAAc,QAAQF,GAAEE,QAAO,CAAC;AACxD,SAAO;AACT;AAEA,eAAsBC,SAAQC,QAAeP,SAAyC;AACpF,QAAM,YAAYA,QAAO,OAAO,YAAY,KAAM,IAAI,IAAIH;AAC1D,QAAM,YAAYC,YAAWE,QAAO,OAAO,cAAc;AACzD,MAAIA,QAAO,eAAe,YAAY,aAAcJ,MAAK,SAAS,GAAI;AACpE,IAAAE;AACA,WAAOF;AAAA,EACT;AACA,EAAAE,WAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,UAAMU,cAAa,CAACD,OAAM,MAAM,MAAM,GAAGA,OAAM,MAAM,MAAM,CAAC;AAC5D,UAAM,SAAY,MAAM,eAAeA,QAAO,CAACZ,YAAWA,UAAS,CAAC;AACpE,UAAM,UAAUK,QAAO,OAAO,UAAUN,UAAA,gBAAAA,OAAO,QAAQ,QAAQ,CAAC,oBAAoB,KAAe;AACnG,IAAAG,YAAW,IAAI;AACf,IAAG,QAAQ,MAAM;AAEjB,UAAM,MAAM,MAAMK,SAAQ,SAASM,aAAYR,OAAM;AACrD,IAAAJ,QAAO;AAEP,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;AC7FA;AAAA;AAAA,mBAAAa;AAAA,EAAA,WAAAC;AAAA;AAAO,IAAMA,OAAqB;AAAA,EAChC;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AAEO,IAAMD,aAAsC;AAAA,EACjD,SAAS,CAAC,WAAW,YAAY,WAAW;AAAA,EAC5C,UAAU,CAAC,YAAY,aAAa,YAAY;AAAA,EAChD,OAAO,CAAC,gBAAgB,iBAAiB,YAAY,WAAW,cAAc;AAAA,EAC9E,SAAS,CAAC,gBAAgB,aAAa,WAAW;AAAA,EAClD,UAAU,CAAC,iBAAiB,cAAc,YAAY;AAAA,EACtD,MAAM,CAAC;AACT;;;ACVA,IAAIE;AACJ,IAAIC,YAAW;AACf,IAAMC,SAAoB,EAAE,IAAI,GAAG,WAAW,CAAC,GAAG,KAAK,CAAC,GAAG,GAAG,GAAG,CAAC,GAAG,QAAQ,CAAC,GAAG,GAAG,GAAG,CAAC,GAAG,OAAO,GAAG,aAAa,CAAC,EAAuC;AAM1J,IAAIC,WAAU,OAAO;AAErB,eAAsBC,MAAKC,SAAqC;AAC9D,MAAIC,KAAI;AAAS,IAAAN,SAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,SAAQ,MAAM,UAAUK,QAAO,KAAK,SAAS;AAAA,WAChDA,QAAO;AAAO,QAAI,iBAAiBL,OAAM,WAAW;AAC7D,SAAOA;AACT;AAGA,eAAe,MAAM,QAAQ,UAAU;AACrC,QAAM,CAAC,OAAO,MAAM,IAAI,OAAO;AAC/B,QAAM,WAAc,QAAQ,QAAQ,CAAC,SAAS,KAAK,CAAC;AACpD,QAAMO,OAAS,IAAI,UAAU,CAAC;AAC9B,QAAM,YAAY,MAAMA,KAAI,KAAK,GAAG;AACpC,EAAG,QAAQ,CAAC,UAAUA,IAAG,CAAC;AAC1B,MAAI,WAAW,UAAU;AACvB,UAAM,cAAiB,OAAO,UAAU,CAAC;AACzC,UAAMC,OAAS,IAAI,aAAa,KAAK;AACrC,UAAM,KAAK,MAAMA,KAAI,KAAK,GAAG;AAC7B,UAAMC,OAAS,IAAI,aAAgB,OAAO,OAAO,OAAO,CAAC;AACzD,UAAM,KAAK,MAAMA,KAAI,KAAK,GAAG;AAC7B,IAAG,QAAQ,CAACD,MAAKC,IAAG,CAAC;AACrB,WAAO,CAAC,GAAG,GAAG,QAAQ;AAAA,EACxB;AACA,SAAO,CAAC,GAAG,GAAG,QAAQ;AACxB;AAEA,eAAsBC,SAAQC,QAAeN,SAAuC;AAClF,QAAM,YAAYA,QAAO,KAAK,YAAY,KAAM,IAAI,IAAIJ;AACxD,QAAM,YAAYE,YAAWE,QAAO,KAAK,cAAc;AACvD,MAAIA,QAAO,eAAe,YAAY,aAAa,OAAO,KAAKH,OAAM,SAAS,EAAE,SAAS,GAAG;AAC1F,IAAAC;AACA,WAAO,CAACD,MAAK;AAAA,EACf;AACA,EAAAC,WAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AA5DxC;AA6DI,UAAMS,UAAY,KAAK,MAAM;AAC3B,UAAI,EAACZ,UAAA,gBAAAA,OAAO,OAAO,GAAG;AAAO,eAAO;AACpC,YAAM,SAAY,MAAM,eAAeW,QAAO,CAACX,OAAM,OAAO,GAAG,MAAM,IAAIA,OAAM,OAAO,GAAG,MAAM,EAAE,GAAG,KAAK;AACzG,YAAMa,WAAa,IAAI,QAAQ,UAAU,GAAG;AAC5C,YAAMC,QAAU,IAAID,UAAS,UAAU,GAAG;AAC1C,aAAOC;AAAA,IACT,CAAC;AAED,QAAI;AACJ,QAAIT,QAAO,KAAK;AAAS,aAAOL,UAAA,gBAAAA,OAAO,QAAQY;AAC/C,IAAAX,YAAW,IAAI;AACf,IAAG,QAAQW,OAAM;AAEjB,QAAI,MAAM;AACR,MAAAV,OAAM,UAAU,SAAS;AACzB,YAAMa,WAAU,KAAK,QAAQ;AAC7B,MAAG,QAAQ,IAAI;AAEf,YAAMC,SAAQD,SAAQ,QAAQ,CAAC;AAC/B,MAAG,QAAQA,QAAO;AAElB,eAAS,KAAK,GAAG,KAAKC,OAAM,QAAQ,MAAM;AAExC,cAAM,CAACC,IAAGC,IAAG,SAAS,IAAI,MAAM,MAAMF,OAAM,KAAKX,QAAO,KAAK,aAAa;AAC1E,YAAI,eAAa,KAAAA,QAAO,SAAP,mBAAa,kBAAiB,IAAI;AACjD,UAAAH,OAAM,UAAU,KAAK;AAAA,YACnB,OAAO,KAAK,MAAM,MAAM,SAAS,IAAI;AAAA,YACrC,MAAaiB,KAAI;AAAA,YACjB,aAAa;AAAA,cAEXF,KAAIjB,OAAM,OAAO,GAAG,MAAM;AAAA,cAAIkB,KAAIlB,OAAM,OAAO,GAAG,MAAM;AAAA,YAC1D;AAAA,YACA,UAAU;AAAA,cAER,KAAK,MAAMW,OAAM,MAAM,KAAKM,KAAIjB,OAAM,OAAO,GAAG,MAAM,EAAE;AAAA,cAAG,KAAK,MAAMW,OAAM,MAAM,KAAKO,KAAIlB,OAAM,OAAO,GAAG,MAAM,EAAE;AAAA,YACrH;AAAA,UACF,CAAC;AAAA,QACH;AAAA,MACF;AACA,MAAAgB,OAAM,QAAQ,CAACI,OAAS,QAAQA,EAAC,CAAC;AAAA,IACpC;AACA,IAAAlB,OAAM,QAAQA,OAAM,UAAU,OAAO,CAAC,MAAM,SAAU,KAAK,QAAQ,OAAO,KAAK,QAAQ,MAAO,CAAC;AAC/F,UAAM,IAAIA,OAAM,UAAU,IAAI,CAAC,MAAM,EAAE,SAAS,EAAE;AAClD,UAAM,IAAIA,OAAM,UAAU,IAAI,CAAC,MAAM,EAAE,SAAS,EAAE;AAClD,IAAAA,OAAM,MAAM;AAAA,MACV,KAAK,IAAI,GAAG,CAAC;AAAA,MACb,KAAK,IAAI,GAAG,CAAC;AAAA,MACb,KAAK,IAAI,GAAG,CAAC,IAAI,KAAK,IAAI,GAAG,CAAC;AAAA,MAC9B,KAAK,IAAI,GAAG,CAAC,IAAI,KAAK,IAAI,GAAG,CAAC;AAAA,IAChC;AACA,UAAM,OAAOA,OAAM,UAAU,IAAI,CAAC,MAAM,EAAE,YAAY,EAAE;AACxD,UAAM,OAAOA,OAAM,UAAU,IAAI,CAAC,MAAM,EAAE,YAAY,EAAE;AACxD,IAAAA,OAAM,SAAS;AAAA,MACb,KAAK,IAAI,GAAG,IAAI;AAAA,MAChB,KAAK,IAAI,GAAG,IAAI;AAAA,MAChB,KAAK,IAAI,GAAG,IAAI,IAAI,KAAK,IAAI,GAAG,IAAI;AAAA,MACpC,KAAK,IAAI,GAAG,IAAI,IAAI,KAAK,IAAI,GAAG,IAAI;AAAA,IACtC;AACA,eAAW,CAAC,MAAM,OAAO,KAAK,OAAO,QAAemB,UAAS,GAAG;AAC9D,YAAM,KAAqB,CAAC;AAC5B,eAASC,KAAI,GAAGA,KAAI,QAAQ,SAAS,GAAGA,MAAK;AAC3C,cAAM,MAAMpB,OAAM,UAAU,KAAK,CAACiB,SAAQA,KAAI,SAAS,QAAQG,GAAE;AACjE,cAAM,MAAMpB,OAAM,UAAU,KAAK,CAACiB,SAAQA,KAAI,SAAS,QAAQG,KAAI,EAAE;AACrE,YAAI,OAAO,OAAO,IAAI,SAASjB,QAAO,KAAK,iBAAiB,MAAM,IAAI,SAASA,QAAO,KAAK,iBAAiB;AAAI,aAAG,KAAK,CAAC,IAAI,UAAU,IAAI,QAAQ,CAAC;AAAA,MACtJ;AACA,MAAAH,OAAM,YAAY,QAAQ;AAAA,IAC5B;AACA,YAAQ,CAACA,MAAK,CAAC;AAAA,EACjB,CAAC;AACH;;;ACnHA,IAAM,cAAc,CAAC,SAAS,WAAW,QAAQ,SAAS,OAAO,YAAY,SAAS;AACtF,IAAIqB;AACJ,IAAMC,QAA0D,CAAC;AACjE,IAAIC,aAAY;AAChB,IAAIC,YAAW;AACf,IAAIC,WAAU,OAAO;AAErB,eAAsBC,MAAKC,SAAqC;AAtBhE;AAuBE,MAAIC,KAAI;AAAS,IAAAP,SAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,SAAQ,MAAM,WAAU,KAAAM,QAAO,KAAK,YAAZ,mBAAqB,SAAS;AAAA,WACzDA,QAAO;AAAO,QAAI,iBAAiBN,OAAM,WAAW;AAC7D,SAAOA;AACT;AAEA,eAAsBQ,SAAQC,QAAeH,SAAgB,KAAaI,QAAoE;AA7B9I;AA8BE,MAAI,CAACV;AAAO,WAAO,CAAC;AACpB,QAAM,YAAYI,cAAW,KAAAE,QAAO,KAAK,YAAZ,mBAAqB,eAAc;AAChE,QAAM,cAAY,KAAAA,QAAO,KAAK,YAAZ,mBAAqB,aAAY,KAAM,IAAI,IAAIH;AACjE,MAAIG,QAAO,eAAe,YAAY,aAAcJ,eAAcQ,UAAUT,MAAK,QAASA,MAAK,KAAK,SAAS,GAAI;AAC/G,IAAAG;AACA,WAAOH,MAAK;AAAA,EACd;AACA,EAAAG,WAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AAtCxC,QAAAO,KAAAC;AAuCI,UAAM,MAAkD,CAAC;AACzD,SAAID,MAAAL,QAAO,KAAK,YAAZ,gBAAAK,IAAqB,SAAS;AAChC,YAAME,KAA4B,CAAC;AACnC,YAAMC,eAAYd,UAAA,gBAAAA,OAAO,OAAO,GAAG,SAAQA,OAAM,OAAO,GAAG,MAAM,KAAK;AACtE,MAAAa,GAAE,SAAY,MAAM,eAAeJ,QAAO,CAACK,aAAWA,WAAS,GAAG,KAAK;AASvE,MAAAD,GAAE,WAAc,IAAIA,GAAE,QAAQ,UAAU,GAAG;AAC3C,MAAAA,GAAE,YAAe,KAAIA,GAAE,UAAU,GAAG,IAAI;AACxC,MAAAA,GAAE,eAAkB,IAAIA,GAAE,WAAW,UAAU,IAAI;AACnD,MAAAA,GAAE,eAAkB,IAAIA,GAAE,cAAc,UAAU,GAAG;AACrD,MAAAA,GAAE,UAAUb,UAAA,gBAAAA,OAAO,QAAQa,GAAE;AAC7B,MAAAV,YAAW,IAAI;AACf,YAAM,OAAO,MAAMU,GAAE,QAAQ,KAAK;AAClC,eAASE,KAAI,GAAGA,KAAI,KAAK,QAAQA,MAAK;AACpC,YAAI,KAAKA,SAAMH,MAAAN,QAAO,KAAK,YAAZ,gBAAAM,IAAqB,kBAAiB;AAAI,cAAI,KAAK,EAAE,OAAO,KAAK,IAAI,MAAM,KAAK,MAAM,MAAM,KAAKG,GAAE,IAAI,GAAG,GAAG,SAAS,YAAYA,IAAc,CAAC;AAAA,MAClK;AACA,UAAI,KAAK,CAAC,GAAG,MAAM,EAAE,QAAQ,EAAE,KAAK;AACpC,aAAO,KAAKF,EAAC,EAAE,QAAQ,CAACG,YAAc,QAAQH,GAAEG,QAAO,CAAC;AAAA,IAC1D;AACA,IAAAf,MAAK,OAAO;AACZ,IAAAC,aAAYQ;AACZ,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;ACtDA,IAAIO;AACJ,IAAMC,QAAwB,CAAC;AAC/B,IAAIC,aAAY;AAChB,IAAIC,YAAW;AACf,IAAIC,WAAU,OAAO;AAErB,eAAsBC,MAAKC,SAAqC;AAC9D,MAAIC,KAAI;AAAS,IAAAP,UAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,UAAQ,MAAM,UAAUM,QAAO,KAAK,iBAAiB,SAAS;AAAA,WACjEA,QAAO;AAAO,QAAI,iBAAiBN,QAAM,WAAW;AAC7D,SAAOA;AACT;AAoBA,eAAsBQ,SAAQC,QAAeH,SAAgB,KAAKI,QAA0B;AA9C5F;AA+CE,MAAI,CAACV;AAAO,WAAO,CAAC;AACpB,QAAM,YAAYI,cAAW,KAAAE,QAAO,KAAK,iBAAZ,mBAA0B,eAAc;AACrE,QAAM,cAAY,KAAAA,QAAO,KAAK,iBAAZ,mBAA0B,aAAY,KAAM,IAAI,IAAIH;AACtE,MAAIG,QAAO,eAAe,YAAY,aAAcJ,eAAcQ,UAAUT,MAAK,MAAM;AACrF,IAAAG;AACA,WAAOH,MAAK;AAAA,EACd;AACA,SAAO,IAAI,QAAQ,OAAO,YAAY;AAtDxC,QAAAU;AAuDI,QAAI,OAAsB,CAAC;AAC3B,UAAIA,MAAAL,QAAO,KAAK,iBAAZ,gBAAAK,IAA0B,aAAWX,WAAA,gBAAAA,QAAO,OAAO,GAAG,QAAO;AAC/D,YAAMY,KAA4B,CAAC;AACnC,MAAAA,GAAE,OAAU,MAAM,eAAeH,QAAO,CAACT,QAAM,OAAO,GAAG,MAAM,IAAIA,QAAM,OAAO,GAAG,MAAM,EAAE,GAAG,KAAK;AAInG,MAAAY,GAAE,OAAOZ,WAAA,gBAAAA,QAAO,QAAQY,GAAE;AAa1B,YAAM,SAAS,MAAMA,GAAE,KAAK,KAAK;AACjC,aAAO,MAAM,KAAK,MAAM;AAAA,IAC1B;AACA,IAAAX,MAAK,OAAO;AACZ,IAAAC,aAAYQ;AACZ,IAAAP,YAAW,IAAI;AACf,YAAQ,IAAI;AAAA,EACd,CAAC;AACH;;;ACzEA,IAAIU;AACJ,IAAIC,aAAY;AAEhB,IAAM,cAAc;AAEpB,IAAM,cAAqB,gBAAgB;AAC3C,IAAM,eAAsB,gBAAgB;AAE5C,IAAM,eAAe;AAAA,EACnB,YAAY,CAAC,YAAY,IAAI,YAAY,YAAY,SAAS,EAAE;AAAA,EAChE,aAAa,CAAC,aAAa,IAAI,aAAa,aAAa,SAAS,EAAE;AACtE;AAEA,IAAM,gBAAgB;AAAA,EACpB,aAAa;AAAA,EACb,aAAa;AAAA,EACb,OAAO;AAAA,EACP,gBAAgB;AAClB;AAEA,eAAsBC,OAAKC,SAAqC;AA9BhE;AA+BE,MAAIC,KAAI;AAAS,IAAAJ,UAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,UAAQ,MAAM,WAAU,KAAAG,QAAO,KAAK,SAAZ,mBAAkB,SAAS;AAAA,WACtDA,QAAO;AAAO,QAAI,iBAAiBH,QAAM,WAAW;AAC7D,EAAAC,aAAYD,QAAM,OAAO,GAAG,QAAQA,QAAM,OAAO,GAAG,MAAM,KAAK;AAC/D,MAAIC,eAAc;AAAI,IAAAA,aAAY;AAClC,SAAOD;AACT;AAGO,SAAS,kBAAkB,WAAW,WAAW,QAAQ,MAAM;AACpE,WAASK,KAAI,GAAGA,KAAW,YAAY,QAAQA,MAAK;AAClD,UAAM,EAAE,KAAK,QAAQ,IAAW,YAAYA;AAC5C,UAAM,kBAAyB,gBAAgB,GAAG,SAAS;AAC3D,QAAI,CAAC,QAAQ,KAAK,SAAS,GAAG,GAAG;AAC/B,eAAS,IAAI,GAAG,IAAI,QAAQ,QAAQ,KAAK;AACvC,cAAMC,SAAQ,QAAQ;AACtB,kBAAU,gBAAgB,MAAM;AAAA,UAC9B,UAAUA,QAAO;AAAA,UACjB,UAAUA,QAAO;AAAA,WAChB,UAAUA,QAAO,KAAK,UAAU,gBAAgB,IAAI,MAAM;AAAA,QAC7D;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACF;AAEO,IAAM,mCAAmC,CAAC,cAAc;AAC7D,QAAM,WAAW,UAAU,aAAa,WAAW,IAAI;AACvD,QAAM,YAAY,UAAU,aAAa,YAAY,IAAI;AACzD,SAAO,WAAW;AACpB;AAGO,IAAM,YAAY,CAAC,WAAWC,OAAM,qBAAqB,qBAAqB,UAAU,OAAO,UAAU;AAC9G,QAAM,MAAW,YAAiB,WAAgB,8BAA8B,CAAC,UAAU,sBAAsB,UAAU,oBAAoB,CAAC,GAAG,WAAW,CAAC;AAC/J,QAAM,UAAe,WAAW,GAAG;AACnC,MAAI,OAAU,MAAM,cAAcA,OAAM,CAAC;AAAA,IACvC,IAAI,WAAW,KAAK;AAAA,IACpB,IAAI,WAAW,KAAK;AAAA,IAAU,IAAI,SAAS,KAAK;AAAA,IAChD,IAAI,SAAS,KAAK;AAAA,EACpB,CAAC,GAAG,CAAC,CAAC,GAAG,CAACN,YAAWA,UAAS,CAAC;AAC/B,MAAI,QAAQG,KAAI,QAAQ,SAAS,eAAe,GAAG;AACjD,UAAM,UAAa,MAAM,cAAc,IAAI;AAC3C,IAAG,QAAQ,IAAI;AACf,WAAO;AAAA,EACT;AACA,SAAO,EAAE,KAAK,SAAS,KAAK;AAC9B;AAGO,IAAM,eAAe,CAAC,SAAS,QAAQ,YAAY,OAAO,UAAU;AACzE,QAAM,eAA6B,CAAC;AACpC,WAASC,KAAI,GAAGA,KAAI,cAAc,gBAAgBA,MAAK;AACrD,UAAM,IAAI,QAAQA,KAAI;AACtB,UAAM,IAAI,QAAQA,KAAI,IAAI;AAC1B,UAAM,IAAI,QAAQA,KAAI,IAAI;AAC1B,iBAAa,KAAK;AAAA,OACf,OAAQ,IAAK,IAAIJ,aAAe,IAAIA,cAAc,WAAW,KAAK,OAAO,WAAW;AAAA,MACpF,IAAIA,aAAa,WAAW,KAAK,OAAO,WAAW;AAAA,MAAI;AAAA,IAC1D,CAAC;AAAA,EACH;AACA,SAAO,EAAE,WAAW,cAAc,MAAM,aAAa,MAAM,cAAc,KAAK,EAAE;AAClF;AAGO,IAAM,wBAAwB,CAAC,WAAW,YAAY,cAAc;AACzE,QAAM,eAAe,UAAiB,gBAAgB,GAAG,sBAAsB,cAAc,cAAc;AAC3G,QAAM,eAAe,UAAiB,gBAAgB,GAAG,sBAAsB,cAAc,cAAc;AAC3G,QAAM,YAAY,eAAe,gBAAgB;AAEjD,SAAO,WAAW,IAAI,CAAC,OAAOI,OAAM;AAClC,QAAI,IAAI;AACR,QAAIA,OAAM,GAAG;AACX,UAAI;AAAA,IACN,WAAWA,OAAM,GAAG;AAClB,UAAI;AAAA,IACN;AACA,WAAO,CAAC,MAAM,IAAI,MAAM,IAAI,CAAC;AAAA,EAC/B,CAAC;AACH;AAEA,eAAsB,YAAY,WAAWE,OAAMJ,SAAQ,UAAU;AACnE,MAAI,CAACH,SAAO;AACV,QAAIG,QAAO;AAAO,UAAI,6DAA6D;AACnF,WAAO;AAAA,EACT;AACA,QAAM,EAAE,KAAK,YAAY,SAAS,gBAAgB,MAAM,YAAY,IAAI,UAAU,WAAWI,OAAM,aAAa,WAAW,IAAI,aAAa,WAAW,IAAI,UAAU,IAAI;AACzK,QAAM,EAAE,KAAK,aAAa,SAAS,iBAAiB,MAAM,aAAa,IAAI,UAAU,WAAWA,OAAM,aAAa,YAAY,IAAI,aAAa,YAAY,IAAI,UAAU,IAAI;AAC9K,QAAM,WAAc,OAAO,CAAC,aAAa,YAAY,CAAC;AACtD,EAAG,QAAQ,WAAW;AACtB,EAAG,QAAQ,YAAY;AACvB,QAAM,iBAAiBP,QAAM,QAAQ,QAAQ;AAC7C,EAAG,QAAQ,QAAQ;AACnB,QAAM,qBAAqB,MAAM,eAAe,KAAK;AACrD,EAAG,QAAQ,cAAc;AACzB,QAAM,cAAc,mBAAmB,MAAM,GAAG,cAAc,iBAAiB,CAAC;AAChF,QAAM,EAAE,WAAW,kBAAkB,MAAM,kBAAkB,IAAI,aAAa,aAAa,YAAY,gBAAgB,IAAI;AAC3H,QAAM,eAAe,mBAAmB,MAAM,cAAc,iBAAiB,CAAC;AAC9E,QAAM,EAAE,WAAW,mBAAmB,MAAM,mBAAmB,IAAI,aAAa,cAAc,aAAa,iBAAiB,KAAK;AACjI,QAAM,gCAAgC,iCAAiC,SAAS;AAChF,MAAI,KAAK,IAAI,6BAA6B,IAAI,IAAI;AAChD,sBAAkB,WAAW,kBAAkB,QAAQ,IAAI;AAC3D,sBAAkB,WAAW,mBAAmB,SAAS,IAAI;AAAA,EAE/D,WAAW,gCAAgC,GAAG;AAC5C,sBAAkB,WAAW,kBAAkB,QAAQ,CAAC,aAAa,WAAW,CAAC;AAAA,EACnF,OAAO;AACL,sBAAkB,WAAW,mBAAmB,SAAS,CAAC,aAAa,WAAW,CAAC;AAAA,EACrF;AACA,QAAM,yBAAyB,sBAAsB,WAAW,mBAAmB,MAAM;AACzF,QAAM,0BAA0B,sBAAsB,WAAW,oBAAoB,OAAO;AAC5F,QAAM,YAAY,UAAU,OAAO,sBAAsB,EAAE,OAAO,uBAAuB;AACzF,SAAO;AACT;;;AC3IA,IAAM,mBAA8B;AAAA,EACl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uBAAkC,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAEvO,IAAM,2BAAsC,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAE3I,IAAM,wBAAmC,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAExF,IAAM,wBAAmC,CAAC,CAAC,IAAI,CAAC,GAAG,CAAC,GAAG,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,IAAI,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAElO,IAAM,4BAAuC,CAAC,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,GAAG,GAAG,CAAC,KAAK,EAAE,GAAG,CAAC,IAAI,GAAG,CAAC;AAE/H,IAAM,yBAAoC,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAEzF,IAAM,wBAAmC;AAAA,EACvC,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EACpN,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAC5M;AAmJA,SAASQ,sBAAqB,aAAwB;AACpD,QAAM,UAAU,YAAY,IAAI,CAAC,eAAe,WAAW,EAAE;AAC7D,UAAQ,KAAK,YAAY,YAAY,SAAS,GAAG,EAAE;AACnD,SAAO;AACT;AAEO,IAAM,2CAA2C;AAAA,EACtD,MAAMA,sBAAqB,gBAAgB;AAAA,EAC3C,SAASA,sBAAqB,oBAAoB;AAAA,EAClD,aAAaA,sBAAqB,wBAAwB;AAAA,EAC1D,UAAUA,sBAAqB,qBAAqB;AAAA,EACpD,UAAUA,sBAAqB,qBAAqB;AAAA,EACpD,cAAcA,sBAAqB,yBAAyB;AAAA,EAC5D,WAAWA,sBAAqB,sBAAsB;AAAA,EACtD,UAAUA,sBAAqB,qBAAqB;AACtD;AAEA,IAAM,kBAA2C,OAAO,QAAQ,wCAAwC,EACrG,IAAI,CAAC,CAAC,OAAO,OAAO,MAAM,QAAQ,IAAI,CAACC,WAAU,CAACA,QAAO,KAAK,CAAqB,CAAC,EACpF,KAAK;AAED,IAAM,gCAAgC,IAAI,IAAI,eAAe;AAQ7D,IAAM,mCAAmC;AAAA,EAC9C;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9C;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACnC;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC7C;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACpC;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC7C;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACpC;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC7C;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AACtC;AAEO,IAAM,uCAAuC;AAAA,EAClD;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACrC;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9B;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EACnC;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EACzB;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACvC;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9B;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EACrB;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACxC;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AACjC;AAEO,IAAM,wCAAwC;AAAA,EACnD;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACxC;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9B;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACxC;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9B;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACxC;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9B;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACzB;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACxC;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AACrC;;;ACvOA,eAAsB,QAAQ,WAAW,SAAmB;AAC1D,QAAMC,KAAkC;AAAA,IAGtC,MAAM,MAAM,QAAQ,OAAO,CAACC,OAAMA,GAAE,SAAS,GAAG,EAAE,GAAG,KAAK;AAAA,IAC1D,OAAO,MAAM,QAAQ,OAAO,CAACA,OAAMA,GAAE,SAAS,EAAE,EAAE,GAAG,KAAK;AAAA,IAC1D,MAAM,MAAM,QAAQ,OAAO,CAACA,OAAMA,GAAE,SAAS,GAAG,EAAE,GAAG,KAAK;AAAA,IAC1D,OAAO,MAAM,QAAQ,OAAO,CAACA,OAAMA,GAAE,SAAS,EAAE,EAAE,GAAG,KAAK;AAAA,IAC1D,MAAM,MAAM,QAAQ,OAAO,CAACA,OAAMA,GAAE,SAAS,GAAG,EAAE,GAAG,KAAK;AAAA,EAC5D;AAGA,QAAM,aAAuB,qCAAqC,OAAO,CAAC,MAAM,SAAS,QAAQ,UAAU,MAAM,IAAI,CAAC,IAAc,qCAAqC;AACzK,WAASC,KAAI,GAAGA,KAAIF,GAAE,MAAM,SAAS,GAAGE;AAAK,cAAU,KAAK,CAACF,GAAE,MAAM,IAAIE,KAAI,IAAIF,GAAE,MAAM,IAAIE,KAAI,IAAI,UAAU,CAAC;AAChH,QAAM,aAAuB,sCAAsC,OAAO,CAAC,MAAM,SAAS,QAAQ,UAAU,MAAM,IAAI,CAAC,IAAc,sCAAsC;AAC3K,WAASA,KAAI,GAAGA,KAAIF,GAAE,MAAM,SAAS,GAAGE;AAAK,cAAU,KAAK,CAACF,GAAE,MAAM,IAAIE,KAAI,IAAIF,GAAE,MAAM,IAAIE,KAAI,IAAI,UAAU,CAAC;AAGhH,WAASA,KAAI,GAAGA,KAAIF,GAAE,KAAK,SAAS,GAAGE;AAAK,cAAoB,qCAAqCA,OAAM,CAACF,GAAE,KAAK,IAAIE,KAAI,IAAIF,GAAE,KAAK,IAAIE,KAAI,IAAI,UAAoB,qCAAqCA,KAAI,EAAE;AACjN,WAASA,KAAI,GAAGA,KAAIF,GAAE,KAAK,SAAS,GAAGE;AAAK,cAAoB,sCAAsCA,OAAM,CAACF,GAAE,KAAK,IAAIE,KAAI,IAAIF,GAAE,KAAK,IAAIE,KAAI,IAAI,UAAoB,sCAAsCA,KAAI,EAAE;AAGnN,WAASA,KAAI,GAAGA,KAAIF,GAAE,KAAK,SAAS,GAAGE;AAAK,cAAoB,iCAAiCA,OAAM,CAACF,GAAE,KAAK,IAAIE,KAAI,IAAIF,GAAE,KAAK,IAAIE,KAAI,IAAI,UAAoB,iCAAiCA,KAAI,EAAE;AAEzM,SAAO;AACT;;;ACHA,IAAMC,SAAQ;AAAA,EACZ,OAAO,CAAC;AAAA,EACR,SAAS,OAAO;AAAA,EAChB,WAAW;AACb;AAEA,IAAIC,UAA2B;AAC/B,IAAIC,aAAY;AAEhB,eAAsBC,UAAQC,QAAeC,SAAuC;AAlCpF;AAoCE,QAAM,cAAY,KAAAA,QAAO,KAAK,aAAZ,mBAAsB,aAAY,KAAM,IAAI,IAAIL,OAAM;AACxE,QAAM,YAAYA,OAAM,aAAW,KAAAK,QAAO,KAAK,aAAZ,mBAAsB,eAAc;AACvE,MAAI,CAACA,QAAO,eAAe,CAAC,YAAY,CAAC,aAAaL,OAAM,MAAM,WAAW,GAAG;AAC9E,IAAAA,OAAM,QAAQ,MAAgB,SAASI,QAAOC,OAAM;AACpD,IAAAL,OAAM,YAAY,IAAI;AACtB,IAAAA,OAAM,UAAU;AAAA,EAClB,OAAO;AACL,IAAAA,OAAM;AAAA,EACR;AACA,QAAM,QAA2B,CAAC;AAClC,QAAM,WAA6B,CAAC;AACpC,MAAI,KAAK;AACT,WAASM,KAAI,GAAGA,KAAIN,OAAM,MAAM,QAAQM,MAAK;AAC3C,UAAM,MAAMN,OAAM,MAAMM;AACxB,QAAI,QAAQ;AACZ,QAAI;AACJ,UAAMC,QAAmB;AAAA,MACvB,IAAI;AAAA,MACJ,MAAM,CAAC;AAAA,MACP,SAAS,CAAC;AAAA,MACV,KAAK,CAAC,GAAG,GAAG,GAAG,CAAC;AAAA,MAChB,QAAQ,CAAC,GAAG,GAAG,GAAG,CAAC;AAAA,MACnB,OAAO;AAAA,MACP,UAAU;AAAA,MACV,WAAW;AAAA,MAGX,aAAa,CAAC;AAAA,IAChB;AAGA,KAAC,OAAO,gBAAgBA,MAAK,MAAM,IAAS,qBAAoB,KAAAF,QAAO,KAAK,aAAZ,mBAAsB,UAAU,KAAKD,UAAO,KAAAC,QAAO,KAAK,SAAZ,mBAAkB,WAAUH,aAAsB,KAAK,CAAC;AACpK,SAAI,KAAAG,WAAA,gBAAAA,QAAQ,WAAR,mBAAgB,cAAc;AAChC,YAAM,YAAY,MAAM,sBAAsBE,MAAK,MAAgB;AACnE,MAAG,QAAQA,MAAK,MAAM;AACtB,MAAAA,MAAK,SAAS;AAAA,IAChB;AACA,IAAAA,MAAK,WAAW,KAAK,MAAM,MAAM,IAAI,UAAU,IAAI;AACnD,QAAI,GAAC,KAAAF,QAAO,KAAK,SAAZ,mBAAkB,UAAS;AAC9B,MAAAE,MAAK,MAAW,SAAS,KAAKH,MAAK;AACnC,MAAAG,MAAK,SAAc,UAAU,KAAKH,MAAK;AACvC,MAAAG,MAAK,QAAQA,MAAK;AAClB,MAAAA,MAAK,OAAO,IAAI,UAAU,IAAI,CAAC,OAAO;AAAA,SAClC,IAAI,WAAW,KAAK,IAAI,SAAS,MAAO,KAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM,GAAG,KAAe,KAAK;AAAA,SAC5G,IAAI,WAAW,KAAK,IAAI,SAAS,MAAO,KAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM,GAAG,KAAe,KAAK;AAAA,MAChH,CAAC;AACD,MAAAA,MAAK,UAAUA,MAAK,KAAK,IAAI,CAAC,OAAO,CAAC,GAAG,MAAMH,OAAM,MAAM,MAAM,IAAI,GAAG,MAAMA,OAAM,MAAM,MAAM,KAAK,GAAG,MAAM,KAAKF,UAAS,CAAC;AAC7H,iBAAW,OAAO,OAAO,KAAY,kBAAkB,GAAG;AACxD,QAAAK,MAAK,YAAY,OAAO,CAACA,MAAK,KAAY,mBAAmB,KAAe;AAAA,MAC9E;AAAA,IACF,WAAW,CAACN,SAAO;AACjB,UAAII,QAAO;AAAO,YAAI,wDAAwD;AAAA,IAChF,OAAO;AACL,YAAM,UAAUJ,QAAM,QAAQM,MAAK,MAAgB;AACnD,YAAM,cAAc,QAAQ,KAAK,CAACC,OAAMA,GAAE,MAAMA,GAAE,MAAM,SAAS,OAAO,CAAC;AACzE,YAAM,iBAAiB,MAAM,YAAY,KAAK;AAC9C,MAAAD,MAAK,YAAY,KAAK,MAAM,MAAM,eAAe,EAAE,IAAI;AAEvD,UAAIA,MAAK,eAAa,KAAAF,QAAO,KAAK,aAAZ,mBAAsB,kBAAiB,IAAI;AAC/D,YAAI,aAAaE,MAAK;AACtB,aAAI,KAAAF,QAAO,KAAK,SAAZ,mBAAkB,aAAa;AACjC,UAAAE,MAAK,MAAW,SAAS,KAAKH,MAAK;AACnC,UAAAG,MAAK,SAAc,UAAU,KAAKH,MAAK;AACvC,UAAAG,MAAK,QAAQA,MAAK;AAClB,UAAAA,MAAK,OAAO,IAAI,UAAU,IAAI,CAAC,OAAO;AAAA,aAClC,IAAI,WAAW,KAAK,IAAI,SAAS,MAAO,KAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM,GAAG,KAAe,KAAK;AAAA,aAC5G,IAAI,WAAW,KAAK,IAAI,SAAS,MAAO,KAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM,GAAG,KAAe,KAAK;AAAA,UAChH,CAAC;AACD,UAAAA,MAAK,UAAUA,MAAK,KAAK,IAAI,CAAC,OAAO,CAAC,GAAG,MAAMH,OAAM,MAAM,MAAM,IAAI,GAAG,MAAMA,OAAM,MAAM,MAAM,KAAK,GAAG,MAAM,KAAKF,UAAS,CAAC;AAC7H,qBAAW,OAAO,OAAO,KAAY,kBAAkB,GAAG;AACxD,YAAAK,MAAK,YAAY,OAAO,CAACA,MAAK,KAAY,mBAAmB,KAAe;AAAA,UAC9E;AAAA,QACF;AAAA,MACF,OAAO;AACL,cAAM,QAAQ,QAAQ,KAAK,CAACC,OAAMA,GAAE,MAAMA,GAAE,MAAM,SAAS,OAAO,IAAI;AACtE,cAAM,iBAAoB,QAAQ,OAAO,CAAC,IAAI,CAAC,CAAC;AAChD,YAAI,YAAY,MAAM,eAAe,MAAM;AAC3C,QAAG,QAAQ,cAAc;AACzB,aAAI,KAAAH,QAAO,KAAK,cAAZ,mBAAuB,SAAS;AAClC,sBAAY,MAAgB,QAAQ,WAAW,OAAO;AAAA,QACxD,YAAW,KAAAA,QAAO,KAAK,SAAZ,mBAAkB,SAAS;AACpC,sBAAY,MAAW,YAAY,WAAWE,MAAK,QAAQF,SAAQH,UAAS;AAAA,QAC9E;AACA,QAAAK,MAAK,OAAY,mBAAmB,WAAW,KAAK,OAAO,gBAAgBL,UAAS;AACpF,QAAAK,MAAK,UAAUA,MAAK,KAAK,IAAI,CAAC,OAAO,CAAC,GAAG,MAAMH,OAAM,MAAM,MAAM,IAAI,GAAG,MAAMA,OAAM,MAAM,MAAM,KAAK,GAAG,MAAM,KAAKF,UAAS,CAAC;AAC7H,mBAAW,OAAO,OAAO,KAAY,eAAe;AAAG,UAAAK,MAAK,YAAY,OAAc,gBAAgB,KAAK,IAAI,CAACE,WAAUF,MAAK,KAAKE,OAAM;AAC1I,QAAAF,MAAK,QAAQA,MAAK;AAClB,cAAM,gBAAgB,EAAE,GAAQ,iBAAiBA,MAAK,MAAM,GAAG,GAAG,YAAY,IAAI,YAAY,WAAW,IAAI,UAAU;AACvH,QAAAA,MAAK,MAAW,SAAS,eAAeH,MAAK;AAC7C,QAAAG,MAAK,SAAc,UAAU,eAAeH,MAAK;AAQjD,iBAAS,KAAK,aAAa;AAAA,MAC7B;AACA,MAAG,QAAQ,OAAO;AAAA,IACpB;AACA,QAAIG,MAAK,WAAS,KAAAF,QAAO,KAAK,aAAZ,mBAAsB,kBAAiB;AAAI,YAAM,KAAKE,KAAI;AAAA;AACvE,MAAG,QAAQA,MAAK,MAAM;AAAA,EAC7B;AACA,EAAAP,OAAM,QAAQ;AACd,SAAO;AACT;AAEA,eAAsBU,OAAKL,SAAqC;AAhJhE;AAiJE,MAAIM,KAAI;AAAS,IAAAV,UAAQ;AAEzB,QAAI,WAAAI,WAAA,gBAAAA,QAAQ,SAAR,mBAAc,cAAd,mBAAyB,aAAWJ,WAAA,gBAAAA,QAAO,YAAW;AAExD,QAAI,OAAO,OAAK,KAAAA,WAAA,gBAAAA,QAAO,cAAP,mBAAkB,YAAW,CAAC,CAAC,EAAE,SAAS;AAAG,MAAAA,UAAQ;AAAA,EACvE;AACA,MAAI,CAACA,SAAO;AACV,SAAI,KAAAI,QAAO,KAAK,cAAZ,mBAAuB;AAAS,MAAAJ,UAAQ,MAAM,WAAU,KAAAI,QAAO,KAAK,cAAZ,mBAAuB,SAAS;AAAA;AACvF,MAAAJ,UAAQ,MAAM,WAAU,KAAAI,QAAO,KAAK,SAAZ,mBAAkB,SAAS;AAAA,EAC1D,WAAWA,QAAO,OAAO;AACvB,QAAI,iBAAiBJ,QAAM,WAAW;AAAA,EACxC;AACA,EAAAC,aAAYD,QAAM,OAAO,GAAG,QAAQA,QAAM,OAAO,GAAG,MAAM,KAAK;AAC/D,SAAOA;AACT;AAEO,IAAM,gBAAuB;AAC7B,IAAM,QAAe;;;AC9I5B,IAAIW;AACJ,IAAMC,QAKD,CAAC;AAEN,IAAIC,aAAW;AACf,IAAIC,aAAY;AAChB,IAAIC,YAAU,OAAO;AAErB,eAAsBC,OAAKC,SAAqC;AAhChE;AAiCE,MAAIC,KAAI;AAAS,IAAAP,UAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,UAAQ,MAAM,WAAU,KAAAM,QAAO,KAAK,gBAAZ,mBAAyB,SAAS;AAAA,WAC7DA,QAAO;AAAO,QAAI,iBAAiBN,QAAM,WAAW;AAC7D,SAAOA;AACT;AAEO,SAAS,QAAQQ,QAAe;AACrC,QAAMC,UAAUD,OAAM,SAASA,OAAM,UAAUA;AAC/C,MAAI,EAACR,WAAA,gBAAAA,QAAO,OAAO,GAAG;AAAO,WAAOS;AACpC,QAAM,OAAU,MAAM,eAAeA,SAAQ,CAACT,QAAM,OAAO,GAAG,MAAM,IAAIA,QAAM,OAAO,GAAG,MAAM,EAAE,GAAG,KAAK;AACxG,QAAMU,QAAU,IAAI,MAAM,UAAU,KAAK;AACzC,EAAG,QAAQ,IAAI;AACf,SAAOA;AAkBT;AAEA,eAAsBC,UAAQC,QAAeN,SAAgB,KAAaO,QAAiC;AAjE3G;AAkEE,MAAI,CAACb;AAAO,WAAO,EAAE,KAAK,GAAG,QAAQ,WAAW,aAAa,GAAG,YAAY,CAAC,EAAE;AAC/E,QAAM,YAAYI,eAAW,KAAAE,QAAO,KAAK,gBAAZ,mBAAyB,eAAc;AACpE,QAAM,cAAY,KAAAA,QAAO,KAAK,gBAAZ,mBAAyB,aAAY,KAAM,IAAI,IAAIJ;AACrE,MAAII,QAAO,eAAe,aAAa,YAAaH,eAAcU,YAAU,KAAAZ,MAAK,SAAL,mBAAW,UAAQ,KAAAA,MAAK,SAAL,mBAAW,OAAM,GAAI;AAClH,IAAAG;AACA,WAAOH,MAAK;AAAA,EACd;AACA,EAAAG,YAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AA1ExC,QAAAU,KAAAC;AA2EI,UAAM,MAAM;AAAA,MACV,KAAa;AAAA,MACb,QAAgB;AAAA,MAChB,aAAqB;AAAA,MACrB,YAAsB,CAAC;AAAA,IACzB;AAEA,SAAID,MAAAR,QAAO,KAAK,gBAAZ,gBAAAQ,IAAyB,SAAS;AACpC,YAAM,WAAW,QAAQF,MAAK;AAC9B,YAAM,OAAOZ,WAAA,gBAAAA,QAAO,QAAQ;AAC5B,MAAAE,aAAW,IAAI;AACf,MAAG,QAAQ,QAAQ;AACnB,YAAM,UAAU,MAAM,KAAK,KAAK,CAACc,OAAMA,GAAE,MAAM,OAAO,CAAC;AACvD,YAAMC,UAAS,MAAM,QAAQ,KAAK;AAClC,YAAM,aAAa,KAAK,MAAM,MAAM,KAAK,IAAKA,QAAO,KAAK,GAAI,CAAC,IAAI;AACnE,UAAI,gBAAcF,MAAAT,QAAO,KAAK,gBAAZ,gBAAAS,IAAyB,kBAAiB,IAAI;AAC9D,YAAI,SAASE,QAAO,MAAM,MAAM,WAAW;AAC3C,YAAI,cAAc,KAAK,IAAI,MAAM,UAAU;AAAA,MAC7C;AACA,YAAMC,UAAY,OAAO,KAAK,KAAK,CAACF,OAAMA,GAAE,MAAM,OAAO,GAAG,GAAG,CAAC;AAChE,YAAMG,QAAO,MAAMD,QAAO,KAAK,GAAG;AAClC,MAAG,QAAQA,OAAM;AACjB,YAAM,OAAO,KAAK,KAAK,CAACF,OAAMA,GAAE,MAAM,OAAO,GAAG;AAChD,YAAMI,OAAM,MAAM,KAAK,KAAK;AAC5B,UAAI,MAAM,KAAK,MAAMA,KAAID,OAAM,KAAKC,KAAID,OAAM,KAAK,KAAKA,OAAM,MAAMC,KAAID,OAAM,KAAK,KAAKA,OAAM,MAAMC,KAAID,OAAM,EAAE,IAAI;AAEpH,YAAM,OAAO,KAAK,KAAK,CAACH,OAAMA,GAAE,MAAM,OAAO,IAAI;AAGjD,YAAM,aAAa,OAAO,MAAM,KAAK,KAAK,IAAc,CAAC;AACzD,UAAI,aAAa,MAAM,KAAK,UAAU;AACtC,WAAK,QAAQ,CAACA,OAAS,QAAQA,EAAC,CAAC;AAAA,IACnC;AACA,IAAAf,MAAK,OAAO;AACZ,IAAAE,aAAYU;AACZ,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;AC7GO,SAASQ,YAAW,KAAK;AAC9B,SAAO;AAAA,IACL,KAAK,IAAI,IAAI,SAAS,KAAK,IAAI,WAAW,EAAE;AAAA,IAC5C,KAAK,IAAI,IAAI,SAAS,KAAK,IAAI,WAAW,EAAE;AAAA,EAC9C;AACF;AAEO,SAASC,cAAa,KAAK;AAChC,SAAO;AAAA,IACL,IAAI,WAAW,MAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM;AAAA,IAC5D,IAAI,WAAW,MAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM;AAAA,EAC9D;AACF;AAEO,SAAS,yBAAyB,KAAKC,QAAO,UAAU;AAC7D,QAAM,IAAIA,OAAM,MAAM;AACtB,QAAM,IAAIA,OAAM,MAAM;AACtB,QAAM,QAAQ,CAAC;AAAA,IACb,IAAI,WAAW,KAAK;AAAA,IACpB,IAAI,WAAW,KAAK;AAAA,IACpB,IAAI,SAAS,KAAK;AAAA,IAClB,IAAI,SAAS,KAAK;AAAA,EACpB,CAAC;AACD,SAAU,MAAM,cAAcA,QAAO,OAAO,CAAC,CAAC,GAAG,QAAQ;AAC3D;AAEO,SAASC,qBAAoB,KAAK,QAAQ;AAC/C,QAAM,aAAa,CAAC,IAAI,WAAW,KAAK,OAAO,IAAI,IAAI,WAAW,KAAK,OAAO,EAAE;AAChF,QAAM,WAAW,CAAC,IAAI,SAAS,KAAK,OAAO,IAAI,IAAI,SAAS,KAAK,OAAO,EAAE;AAC1E,QAAM,gBAAgB,IAAI,cAAc,IAAI,CAAC,UAAU;AACrD,UAAM,cAAc,CAAC,MAAM,KAAK,OAAO,IAAI,MAAM,KAAK,OAAO,EAAE;AAC/D,WAAO;AAAA,EACT,CAAC;AACD,SAAO,EAAE,YAAY,UAAU,eAAe,YAAY,IAAI,WAAW;AAC3E;AAEO,SAASC,YAAW,KAAK,SAAS,KAAK;AAC5C,QAAM,SAASH,cAAa,GAAG;AAC/B,QAAMI,QAAOL,YAAW,GAAG;AAC3B,QAAM,cAAc,CAAC,SAASK,MAAK,KAAK,GAAG,SAASA,MAAK,KAAK,CAAC;AAC/D,QAAM,aAAa,CAAC,OAAO,KAAK,YAAY,IAAI,OAAO,KAAK,YAAY,EAAE;AAC1E,QAAM,WAAW,CAAC,OAAO,KAAK,YAAY,IAAI,OAAO,KAAK,YAAY,EAAE;AACxE,SAAO,EAAE,YAAY,UAAU,eAAe,IAAI,cAAc;AAClE;AAEO,SAASC,aAAY,KAAK;AAC/B,QAAM,UAAUL,cAAa,GAAG;AAChC,QAAMI,QAAOL,YAAW,GAAG;AAC3B,QAAM,UAAU,KAAK,IAAI,GAAGK,KAAI;AAChC,QAAM,WAAW,UAAU;AAC3B,QAAM,aAAa,CAAC,QAAQ,KAAK,UAAU,QAAQ,KAAK,QAAQ;AAChE,QAAM,WAAW,CAAC,QAAQ,KAAK,UAAU,QAAQ,KAAK,QAAQ;AAC9D,SAAO,EAAE,YAAY,UAAU,eAAe,IAAI,cAAc;AAClE;AAaO,SAASE,kBAAiB,OAAO;AACtC,SAAO,QAAQ,IAAI,KAAK,KAAK,KAAK,OAAO,QAAQ,KAAK,OAAO,IAAI,KAAK,GAAG;AAC3E;AAEO,SAASC,iBAAgB,QAAQ,QAAQ;AAC9C,QAAM,UAAU,KAAK,KAAK,IAAI,KAAK,MAAM,EAAE,OAAO,KAAK,OAAO,KAAK,OAAO,KAAK,OAAO,EAAE;AACxF,SAAOD,kBAAiB,OAAO;AACjC;AAEO,IAAME,0BAAyB,CAAC,GAAG,MAAM,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC;AAEzE,SAASC,KAAI,IAAI,IAAI;AAC1B,MAAI,UAAU;AACd,WAASC,KAAI,GAAGA,KAAI,GAAG,QAAQA,MAAK;AAClC,eAAW,GAAGA,MAAK,GAAGA;AAAA,EACxB;AACA,SAAO;AACT;AAEO,SAASC,oBAAmB,KAAK,aAAa;AACnD,QAAM,SAAwB,CAAC;AAC/B,WAASD,KAAI,GAAGA,KAAI,IAAI,QAAQA,MAAK;AACnC,WAAO,KAAK,IAAIA,IAAG,YAAY;AAAA,EACjC;AACA,SAAO;AACT;AAEO,SAASE,2BAA0B,MAAM,MAAM;AACpD,QAAM,UAA2B,CAAC;AAClC,QAAMC,QAAO,KAAK;AAClB,WAAS,MAAM,GAAG,MAAMA,OAAM,OAAO;AACnC,YAAQ,KAAK,CAAC,CAAC;AACf,aAAS,MAAM,GAAG,MAAMA,OAAM,OAAO;AACnC,cAAQ,KAAK,KAAKJ,KAAI,KAAK,MAAME,oBAAmB,MAAM,GAAG,CAAC,CAAC;AAAA,IACjE;AAAA,EACF;AACA,SAAO;AACT;AAEO,SAASG,qBAAoB,UAAU,QAAQ;AACpD,QAAM,OAAO,KAAK,IAAI,QAAQ;AAC9B,QAAM,OAAO,KAAK,IAAI,QAAQ;AAC9B,QAAM,iBAAiB,CAAC,CAAC,MAAM,CAAC,MAAM,CAAC,GAAG,CAAC,MAAM,MAAM,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC;AACpE,QAAM,oBAAoBN,wBAAuB,OAAO,IAAI,OAAO,EAAE;AACrE,QAAM,2BAA2BI,2BAA0B,mBAAmB,cAAc;AAC5F,QAAM,4BAA4BJ,wBAAuB,CAAC,OAAO,IAAI,CAAC,OAAO,EAAE;AAC/E,SAAOI,2BAA0B,0BAA0B,yBAAyB;AACtF;AAEO,SAASG,uBAAsB,QAAQ;AAC5C,QAAM,oBAAoB,CAAC,CAAC,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE,GAAG,CAAC,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE,CAAC;AACrF,QAAM,uBAAuB,CAAC,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE;AACxD,QAAM,sBAAsB;AAAA,IAC1B,CAACN,KAAI,kBAAkB,IAAI,oBAAoB;AAAA,IAC/C,CAACA,KAAI,kBAAkB,IAAI,oBAAoB;AAAA,EACjD;AACA,SAAO;AAAA,IACL,kBAAkB,GAAG,OAAO,oBAAoB,EAAE;AAAA,IAClD,kBAAkB,GAAG,OAAO,oBAAoB,EAAE;AAAA,IAClD,CAAC,GAAG,GAAG,CAAC;AAAA,EACV;AACF;AAEO,SAASO,aAAY,uBAAuB,gBAAgB;AACjE,SAAO;AAAA,IACLP,KAAI,uBAAuB,eAAe,EAAE;AAAA,IAC5CA,KAAI,uBAAuB,eAAe,EAAE;AAAA,EAC9C;AACF;;;ACpIO,IAAMQ,WAAU;AAAA,EACrB,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AACzB;;;AC13FO,IAAM,eAAN,MAAmB;AAAA,EAQxB,YAAYC,SAAO;AAPnB;AACA;AACA;AACA;AACA;AACA;AAGE,SAAK,QAAQA;AACb,SAAK,UAAkBC,SAAQ,IAAI,CAAC,WAAW,CAAC,OAAO,GAAG,OAAO,CAAC,CAAC;AACnE,SAAK,gBAAmB,SAAS,KAAK,OAAO;AAC7C,SAAK,YAAa,KAAK,SAAS,KAAK,MAAM,UAAU,KAAK,MAAM,OAAO,GAAG,QAAS,KAAK,MAAM,OAAO,GAAG,MAAM,KAAK;AACnH,SAAK,kBAAqB,SAAS,CAAC,KAAK,WAAW,KAAK,SAAS,CAAC;AACnE,SAAK,wBAA2B,SAAS,CAAC,KAAK,YAAY,GAAG,KAAK,YAAY,CAAC,CAAC;AAAA,EACnF;AAAA,EAEA,eAAe,OAAO;AACpB,UAAMC,KAA4B,CAAC;AACnC,IAAAA,GAAE,aAAgB,MAAM,OAAO,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,CAAC,CAAC;AAC9C,IAAAA,GAAE,WAAc,MAAM,OAAO,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,CAAC,CAAC;AAC5C,IAAAA,GAAE,MAAS,IAAIA,GAAE,YAAY,KAAK,eAAe;AACjD,IAAAA,GAAE,kBAAqB,KAAIA,GAAE,KAAK,KAAK,aAAa;AACpD,IAAAA,GAAE,eAAkB,IAAIA,GAAE,UAAU,KAAK,qBAAqB;AAC9D,IAAAA,GAAE,MAAS,IAAIA,GAAE,iBAAiBA,GAAE,YAAY;AAChD,IAAAA,GAAE,cAAiB,IAAIA,GAAE,KAAK,KAAK,eAAe;AAClD,IAAAA,GAAE,MAAS,KAAIA,GAAE,iBAAiBA,GAAE,YAAY;AAChD,IAAAA,GAAE,YAAe,IAAIA,GAAE,KAAK,KAAK,eAAe;AAChD,UAAM,MAAS,SAAS,CAACA,GAAE,aAAaA,GAAE,SAAS,GAAG,CAAC;AACvD,WAAO,KAAKA,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,WAAO;AAAA,EACT;AAAA,EAEA,mBAAmB,kBAAkBC,QAAO;AAC1C,UAAMF,KAA4B,CAAC;AACnC,IAAAA,GAAE,UAAa,QAAQ,kBAAkB,CAAC,IAAI,GAAG,CAAC,CAAC;AACnD,IAAAA,GAAE,MAAS,IAAIA,GAAE,SAAS,KAAK,eAAe;AAC9C,IAAAA,GAAE,YAAe,KAAIA,GAAE,KAAK,KAAK,QAAQE,OAAM;AAC/C,UAAM,MAAS,IAAIF,GAAE,WAAW,KAAK,eAAe;AACpD,WAAO,KAAKA,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,WAAO;AAAA,EACT;AAAA,EAEA,MAAM,QAAQE,QAAOC,SAAuG;AAC1H,UAAMJ,KAA4B,CAAC;AACnC,IAAAA,GAAE,SAAY,MAAM,eAAeG,QAAO,CAAC,KAAK,WAAW,KAAK,SAAS,CAAC;AAC1E,IAAAH,GAAE,MAAS,IAAIA,GAAE,QAAQ,UAAU,KAAK;AACxC,IAAAA,GAAE,QAAW,IAAIA,GAAE,KAAK,UAAU,GAAG;AACrC,IAAAA,GAAE,UAAU,KAAK,MAAM,QAAQA,GAAE,KAAK;AACtC,IAAAA,GAAE,cAAiB,QAAQA,GAAE,OAAO;AACpC,IAAAA,GAAE,QAAW,MAAMA,GAAE,aAAa,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,CAAC,CAAC;AACjD,IAAAA,GAAE,UAAa,QAAQA,GAAE,KAAK;AAC9B,IAAAA,GAAE,SAAY,QAAQA,GAAE,OAAO;AAC/B,UAAM,SAAS,MAAMA,GAAE,OAAO,KAAK;AACnC,IAAAA,GAAE,QAAW,MAAMA,GAAE,aAAa,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,CAAC,CAAC;AACjD,IAAAA,GAAE,OAAO,KAAK,eAAeA,GAAE,KAAK;AAEpC,IAAAA,GAAE,MAAM,MAAS,MAAM,uBAAuBA,GAAE,MAAMA,GAAE,QAAQ,IAAII,QAAO,KAAK,aAAaA,QAAO,KAAK,cAAcA,QAAO,KAAK,aAAa;AAChJ,UAAM,MAAM,MAAMJ,GAAE,IAAI,MAAM;AAC9B,UAAM,QAAmG,CAAC;AAC1G,eAAWE,UAAS,KAAK;AACvB,YAAMG,KAA4B,CAAC;AACnC,MAAAA,GAAE,MAAS,MAAML,GAAE,MAAM,CAACE,QAAO,CAAC,GAAG,CAAC,GAAG,EAAE,CAAC;AAC5C,MAAAG,GAAE,QAAW,MAAML,GAAE,aAAa,CAACE,QAAO,CAAC,GAAG,CAAC,GAAG,EAAE,CAAC;AACrD,MAAAG,GAAE,OAAO,KAAK,mBAAmBA,GAAE,OAAOH,MAAK;AAC/C,MAAAG,GAAE,gBAAmB,QAAQA,GAAE,MAAM,CAAC,IAAI,CAAC,CAAC;AAC5C,YAAM,MAAM,MAAMA,GAAE,IAAI,KAAK;AAC7B,YAAM,aAAa,IAAI,MAAM,GAAG,CAAC;AACjC,YAAM,WAAW,IAAI,MAAM,GAAG,CAAC;AAC/B,YAAM,gBAAgB,MAAMA,GAAE,cAAc,MAAM;AAClD,YAAMC,QAAO,EAAE,YAAY,UAAU,eAAe,YAAY,OAAOJ,QAAO;AAC9E,YAAM,SAAcK,qBAAoBD,OAAM,CAACH,OAAM,MAAM,KAAK,KAAK,WAAWA,OAAM,MAAM,KAAK,KAAK,SAAS,CAAC;AAChH,YAAM,KAAK,MAAM;AACjB,aAAO,KAAKE,EAAC,EAAE,QAAQ,CAACJ,YAAc,QAAQI,GAAEJ,QAAO,CAAC;AAAA,IAC1D;AACA,WAAO,KAAKD,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,WAAO;AAAA,EACT;AACF;;;AC5EA,IAAM,uBAAuB;AAC7B,IAAM,uBAAuB;AAC7B,IAAM,kBAAkB,CAAC,GAAG,GAAG,GAAG,IAAI,IAAI,GAAG,CAAC;AAC9C,IAAM,wBAAwB;AAC9B,IAAM,gCAAgC;AACtC,IAAIO,aAAW;AAER,IAAM,eAAN,MAAmB;AAAA,EAQxB,YAAY,cAAcC,gBAAe;AAPzC;AACA;AACA;AACA;AACA;AACA;AAGE,SAAK,eAAe;AACpB,SAAK,gBAAgBA;AACrB,SAAK,YAAY,KAAK,iBAAiB,KAAK,cAAc,OAAO,GAAG,QAAQ,KAAK,cAAc,OAAO,GAAG,MAAM,KAAK;AACpH,SAAK,cAAc,CAAC;AACpB,SAAK,UAAU,OAAO;AACtB,SAAK,gBAAgB;AAAA,EACvB;AAAA,EAGA,8BAA8B,WAAW;AACvC,UAAM,KAAK,UAAU,IAAI,CAAC,MAAM,EAAE,EAAE;AACpC,UAAM,KAAK,UAAU,IAAI,CAAC,MAAM,EAAE,EAAE;AACpC,UAAM,aAAa,CAAC,KAAK,IAAI,GAAG,EAAE,GAAG,KAAK,IAAI,GAAG,EAAE,CAAC;AACpD,UAAM,WAAW,CAAC,KAAK,IAAI,GAAG,EAAE,GAAG,KAAK,IAAI,GAAG,EAAE,CAAC;AAClD,WAAO,EAAE,YAAY,SAAS;AAAA,EAChC;AAAA,EAEA,uBAAuB,eAAe,gBAAgB;AACpD,UAAM,uBAAuB,cAAc,IAAI,CAAC,UAAeC,aAAY,CAAC,GAAG,OAAO,CAAC,GAAG,cAAc,CAAC;AACzG,UAAM,gBAAgB,KAAK,8BAA8B,oBAAoB;AAC7E,WAAYC,YAAgBC,aAAY,aAAa,GAAG,oBAAoB;AAAA,EAC9E;AAAA,EAEA,uBAAuB,WAAW;AAChC,UAAM,cAAc,KAAK,8BAA8B,SAAS;AAChE,UAAM,gBAAqBD,YAAgBC,aAAY,WAAW,GAAG,oBAAoB;AACzF,kBAAc,gBAAgB,CAAC;AAC/B,aAASC,KAAI,GAAGA,KAAI,gBAAgB,QAAQA,MAAK;AAC/C,oBAAc,cAAc,KAAK,UAAU,gBAAgBA,KAAI,MAAM,GAAG,CAAC,CAAC;AAAA,IAC5E;AACA,WAAO;AAAA,EACT;AAAA,EAEA,mBAAmB,WAAW,MAAM,OAAO,gBAAgB;AACzD,UAAM,UAAeC,YAAW,IAAI;AACpC,UAAM,cAAc,CAAC,QAAQ,KAAK,KAAK,WAAW,QAAQ,KAAK,KAAK,YAAY,QAAQ,KAAK,QAAQ,MAAM,KAAK,YAAY,CAAC;AAC7H,UAAM,eAAe,UAAU,IAAI,CAAC,UAAU;AAAA,MAC5C,YAAY,MAAM,MAAM,KAAK,KAAK,YAAY;AAAA,MAC9C,YAAY,MAAM,MAAM,KAAK,KAAK,YAAY;AAAA,MAC9C,YAAY,KAAK,MAAM;AAAA,IACzB,CAAC;AACD,UAAM,uBAA4BC,qBAAoB,OAAO,CAAC,GAAG,CAAC,CAAC;AACnE,UAAM,gBAAgB,aAAa,IAAI,CAAC,UAAU;AAChD,YAAM,UAAeL,aAAY,OAAO,oBAAoB;AAC5D,aAAO,CAAC,GAAG,SAAS,MAAM,EAAE;AAAA,IAC9B,CAAC;AACD,UAAM,wBAA6BM,uBAAsB,cAAc;AACvE,UAAM,YAAY,CAAC,GAAQC,cAAa,IAAI,GAAG,CAAC;AAChD,UAAM,oBAAoB;AAAA,MACnBC,KAAI,WAAW,sBAAsB,EAAE;AAAA,MACvCA,KAAI,WAAW,sBAAsB,EAAE;AAAA,IAC9C;AACA,WAAO,cAAc,IAAI,CAAC,UAAU;AAAA,MAClC,KAAK,MAAM,MAAM,KAAK,kBAAkB,EAAE;AAAA,MAC1C,KAAK,MAAM,MAAM,KAAK,kBAAkB,EAAE;AAAA,MAC1C,KAAK,MAAM,MAAM,EAAE;AAAA,IACrB,CAAC;AAAA,EACH;AAAA,EAEA,MAAM,cAAcC,QAAOC,SAAQ;AACjC,QAAI,cAAc;AAGlB,QAAI;AACJ,UAAM,YAAYA,QAAO,KAAK,YAAY,KAAM,IAAI,IAAIZ;AACxD,UAAM,YAAY,KAAK,WAAWY,QAAO,KAAK,cAAc;AAC5D,QAAIA,QAAO,eAAe,YAAY,WAAW;AAC/C,cAAQ,MAAM,KAAK,aAAa,QAAQD,QAAOC,OAAM;AACrD,WAAK,UAAU;AAAA,IACjB;AACA,QAAIA,QAAO;AAAa,WAAK;AAG7B,QAAI,SAAU,MAAM,SAAS,MAAQ,MAAM,WAAW,KAAK,iBAAmB,KAAK,kBAAkBA,QAAO,KAAK,eAAgB,CAACA,QAAO,KAAK,YAAY;AACxJ,WAAK,gBAAgB;AACrB,WAAK,cAAc,CAAC,GAAG,KAAK;AAE5B,UAAI,KAAK,YAAY,SAAS;AAAG,sBAAc;AAAA,IACjD;AACA,UAAM,QAAyJ,CAAC;AAGhK,aAASP,KAAI,GAAGA,KAAI,KAAK,YAAY,QAAQA,MAAK;AAChD,YAAM,aAAa,KAAK,YAAYA;AACpC,UAAI,CAAC;AAAY;AACjB,UAAIO,QAAO,KAAK,WAAW;AACzB,cAAM,QAAQA,QAAO,KAAK,WAAgBC,iBAAgB,WAAW,cAAc,wBAAwB,WAAW,cAAc,8BAA8B,IAAI;AACtK,cAAM,aAAkBJ,cAAa,UAAU;AAC/C,cAAM,uBAAuB,CAAC,WAAW,KAAKE,OAAM,MAAM,IAAI,WAAW,KAAKA,OAAM,MAAM,EAAE;AAC5F,cAAM,eAAeC,QAAO,KAAK,YAAYE,KAAI,QAAQ,SAAS,kBAAkB,IAAO,MAAM,iBAAiBH,QAAO,OAAO,GAAG,oBAAoB,IAAIA,OAAM,MAAM;AACvK,cAAM,iBAAsBJ,qBAAoB,CAAC,OAAO,UAAU;AAClE,cAAM,SAAS,cAAc,KAAK,uBAAuB,WAAW,eAAe,cAAc,IAAI;AACrG,cAAM,eAAoB,yBAAyB,QAAQ,cAAc,CAAC,KAAK,WAAW,KAAK,SAAS,CAAC;AACzG,cAAM,YAAe,IAAI,cAAc,UAAU,KAAK;AACtD,QAAG,QAAQ,YAAY;AACvB,QAAG,QAAQ,YAAY;AACvB,cAAM,CAAC,aAAa,SAAS,IAAI,KAAK,cAAc,QAAQ,SAAS;AACrE,QAAAP,aAAW,IAAI;AACf,QAAG,QAAQ,SAAS;AACpB,cAAM,cAAc,MAAM,YAAY,KAAK,GAAG;AAC9C,QAAG,QAAQ,WAAW;AACtB,YAAI,cAAcY,QAAO,KAAK,gBAAgB,GAAG;AAC/C,gBAAM,oBAAuB,QAAQ,WAAW,CAAC,IAAI,CAAC,CAAC;AACvD,gBAAM,YAAY,MAAM,kBAAkB,MAAM;AAChD,UAAG,QAAQ,SAAS;AACpB,UAAG,QAAQ,iBAAiB;AAC5B,gBAAMG,UAAS,KAAK,mBAAmB,WAAW,QAAQ,OAAO,cAAc;AAC/E,gBAAM,kBAAkB,KAAK,uBAAuBA,OAAM;AAC1D,eAAK,YAAYV,MAAK,EAAE,GAAG,iBAAiB,WAAW;AACvD,gBAAM,SAAS;AAAA,YACb,WAAWU;AAAA,YACX;AAAA,YACA,eAAe,WAAW;AAAA,YAC1B,kBAAkB;AAAA,YAClB,KAAK,EAAE,SAAS,gBAAgB,YAAY,aAAa,gBAAgB,SAAS;AAAA,UACpF;AACA,gBAAM,KAAK,MAAM;AAAA,QACnB,OAAO;AACL,eAAK,YAAYV,MAAK;AAAA,QACxB;AACA,QAAG,QAAQ,SAAS;AAAA,MACtB,OAAO;AAEL,cAAM,WAAgBF,YAAgBC,aAAY,UAAU,GAAG,oBAAoB;AACnF,cAAM,SAAS;AAAA,UACb,YAAY,WAAW;AAAA,UACvB,eAAe,WAAW;AAAA,UAC1B,kBAAkB;AAAA,UAClB,KAAK,EAAE,SAAS,SAAS,YAAY,aAAa,SAAS,SAAS;AAAA,UACpE,WAAW,CAAC;AAAA,QACd;AACA,cAAM,KAAK,MAAM;AAAA,MACnB;AAAA,IACF;AACA,SAAK,cAAc,KAAK,YAAY,OAAO,CAAC,MAAM,MAAM,IAAI;AAC5D,SAAK,gBAAgB,MAAM;AAC3B,QAAI,MAAM,SAASQ,QAAO,KAAK;AAAa,YAAM,SAASA,QAAO,KAAK;AACvE,WAAO;AAAA,EACT;AACF;;;ACpKO,IAAM,SAAS;AAAA,EACpB,OAAO;AAAA,EACP,OAAO;AAAA,EACP,QAAQ;AAAA,EACR,MAAM;AAAA,EACN,OAAO;AAAA,EACP,KAAK,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC;AAAA,EACnB,aAAa,EAAE,GAAG,SAAS,GAAG,SAAS,GAAG,UAAU,GAAG,QAAQ,GAAG,QAAQ;AAAA,EAQ1E,eAAe;AAAA,IACb,GAAG,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAAA,IAClC,GAAG,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAAA,IAClC,GAAG,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,CAAC;AAAA,IACvC,GAAG,CAAC,CAAC,GAAG,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,CAAC;AAAA,IACzC,GAAG,CAAC,CAAC,GAAG,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,CAAC;AAAA,EAC3C;AAAA,EACA,SAAS,CAAC,UAAU,OAAO,YAAY;AAAA,EACvC,WAAW,CAAC,UAAU,OAAO,cAAc;AAC7C;AAEO,IAAM,aAAa;AAAA,EACxB,MAAM;AAAA,EACN,MAAM;AAAA,EACN,MAAM;AAAA,EACN,aAAa,EAAE,GAAG,QAAQ,GAAG,QAAQ,GAAG,OAAO;AAAA,EAC/C,SAAS,CAAC,UAAU,WAAW,YAAY;AAC7C;AAEO,IAAM,kBAAkB;AAAA,EAC7B,YAAY;AAAA,EACZ,cAAc;AAAA,EACd,gBAAgB;AAAA,EAChB,iBAAiB;AAAA,EACjB,iBAAiB;AAAA,EACjB,gBAAgB;AAAA,EAChB,mBAAmB;AAAA,EACnB,kBAAkB;AAAA,EAClB,aAAa,EAAE,GAAG,cAAc,GAAG,gBAAgB,GAAG,kBAAkB,GAAG,mBAAmB,GAAG,mBAAmB,GAAG,kBAAkB,GAAG,qBAAqB,GAAG,mBAAmB;AAAA,EACvL,SAAS,CAAC,UAAU,gBAAgB,YAAY;AAClD;AAEO,IAAM,gBAAN,MAAoB;AAAA,EAOzB,YAAY,MAAM;AANlB;AACA;AACA;AACA;AACA;AAIE,SAAK,OAAO;AACZ,SAAK,QAAQ,CAAC;AACd,SAAK,aAAa,CAAC;AACnB,SAAK,UAAU,CAAC,GAAK,GAAK,GAAK,GAAK,CAAG;AACvC,SAAK,kBAAkB,CAAC,GAAK,GAAK,GAAK,GAAK,CAAG;AAAA,EACjD;AAAA,EAEA,KAAK,QAAQ,MAAM,YAAY;AAC7B,QAAI,OAAO,KAAK,MAAM,YAAY;AAAa,WAAK,MAAM,UAAU,CAAC;AACrE,SAAK,MAAM,QAAQ,KAAK,CAAC,MAAM,UAAU,CAAC;AAAA,EAC5C;AAAA,EAEA,UAAU,QAAQ,UAAU,YAAY;AACtC,QAAI,CAAC,KAAK,WAAW;AAAS,WAAK,WAAW,UAAU,CAAC;AACzD,SAAK,WAAW,QAAQ,KAAK,CAAC,UAAU,UAAU,CAAC;AAAA,EACrD;AAAA,EAEA,OAAO,QAAQ,QAAQ;AACrB,SAAK,QAAQ,UAAU;AAEvB,UAAM,QAAQ,KAAK,QAAQ,OAAO,CAAC,GAAG,MAAM,IAAI,GAAG,CAAC;AACpD,SAAK,kBAAkB,KAAK,QAAQ,IAAI,CAAC,OAAO,KAAK,IAAI,KAAK;AAAA,EAChE;AAAA,EAEA,aAAa,eAAe,oBAAoB;AAC9C,QAAI,aAAa;AAGjB,eAAW,aAAa,eAAe;AACrC,YAAM,eAAe,cAAc;AACnC,YAAM,gBAAgB,KAAK,MAAM;AACjC,UAAI,OAAO,kBAAkB,aAAa;AAGxC,sBAAc,KAAK,gBAAgB;AACnC;AAAA,MACF;AAEA,iBAAW,CAAC,cAAc,KAAK,KAAK,eAAe;AACjD,YAAI,iBAAiB,cAAc;AACjC,wBAAc,QAAQ,KAAK,gBAAgB;AAC3C;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAEA,eAAW,aAAa,oBAAoB;AAC1C,YAAM,oBAAoB,mBAAmB;AAC7C,YAAM,qBAAqB,KAAK,WAAW;AAC3C,UAAI,OAAO,uBAAuB,aAAa;AAG7C,sBAAc,KAAK,gBAAgB;AACnC;AAAA,MACF;AAEA,iBAAW,CAAC,mBAAmB,KAAK,KAAK,oBAAoB;AAC3D,YAAI,sBAAsB,mBAAmB;AAC3C,wBAAc,QAAQ,KAAK,gBAAgB;AAC3C;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,WAAO,aAAa;AAAA,EACtB;AACF;;;ACtHO,IAAM,EAAE,OAAO,OAAO,QAAQ,MAAM,MAAM,IAAI;AAE9C,IAAM,EAAE,MAAM,MAAM,KAAK,IAAI;AAE7B,IAAM,EAAE,YAAY,cAAc,gBAAgB,iBAAiB,iBAAiB,gBAAgB,mBAAmB,iBAAiB,IAAI;AAGnJ,IAAM,WAAW,IAAI,cAAc,WAAW;AAC9C,SAAS,KAAK,OAAO,MAAM,CAAG;AAC9B,SAAS,UAAU,OAAO,YAAY,CAAG;AACzC,SAAS,UAAU,OAAO,gBAAgB,IAAI;AAC9C,SAAS,UAAU,OAAO,iBAAiB,IAAI;AAC/C,WAAW,UAAU,CAAC,OAAO,OAAO,OAAO,QAAQ,OAAO,MAAM,OAAO,KAAK,GAAG;AAC7E,WAAS,KAAK,QAAQ,MAAM,CAAG;AAC/B,WAAS,UAAU,QAAQ,gBAAgB,CAAG;AAC9C,WAAS,UAAU,QAAQ,iBAAiB,CAAG;AACjD;AAGA,IAAM,UAAU,IAAI,cAAc,SAAS;AAC3C,QAAQ,KAAK,OAAO,MAAM,GAAG;AAC7B,QAAQ,KAAK,OAAO,MAAM,GAAG;AAC7B,QAAQ,UAAU,OAAO,YAAY,CAAG;AACxC,QAAQ,UAAU,OAAO,gBAAgB,CAAG;AAC5C,QAAQ,KAAK,OAAO,MAAM,CAAG;AAC7B,QAAQ,UAAU,OAAO,YAAY,IAAI;AACzC,QAAQ,UAAU,OAAO,gBAAgB,CAAG;AAC5C,QAAQ,KAAK,QAAQ,MAAM,CAAG;AAC9B,QAAQ,UAAU,QAAQ,YAAY,CAAG;AACzC,QAAQ,UAAU,QAAQ,gBAAgB,IAAI;AAC9C,QAAQ,KAAK,MAAM,MAAM,CAAG;AAC5B,QAAQ,UAAU,MAAM,YAAY,GAAG;AACvC,QAAQ,UAAU,MAAM,gBAAgB,CAAG;AAC3C,QAAQ,UAAU,MAAM,gBAAgB,GAAG;AAC3C,QAAQ,KAAK,OAAO,MAAM,CAAG;AAC7B,QAAQ,UAAU,OAAO,YAAY,GAAG;AACxC,QAAQ,UAAU,OAAO,gBAAgB,CAAG;AAC5C,QAAQ,UAAU,OAAO,gBAAgB,GAAG;AAC5C,QAAQ,OAAO,OAAO,CAAC;AACvB,QAAQ,OAAO,QAAQ,CAAC;AAGxB,IAAM,QAAQ,IAAI,cAAc,OAAO;AACvC,MAAM,KAAK,OAAO,MAAM,CAAG;AAC3B,MAAM,KAAK,OAAO,MAAM,GAAG;AAC3B,MAAM,KAAK,QAAQ,MAAM,GAAG;AAC5B,MAAM,KAAK,MAAM,MAAM,GAAG;AAC1B,MAAM,KAAK,OAAO,MAAM,GAAG;AAC3B,MAAM,OAAO,OAAO,CAAC;AACrB,MAAM,OAAO,QAAQ,CAAC;AAGtB,IAAM,eAAe,IAAI,cAAc,eAAe;AACtD,aAAa,KAAK,OAAO,MAAM,CAAG;AAClC,aAAa,KAAK,OAAO,MAAM,GAAG;AAClC,aAAa,KAAK,QAAQ,MAAM,GAAG;AACnC,aAAa,KAAK,MAAM,MAAM,GAAG;AACjC,aAAa,KAAK,OAAO,MAAM,GAAG;AAClC,aAAa,OAAO,OAAO,CAAC;AAC5B,aAAa,OAAO,QAAQ,CAAC;AAG7B,IAAM,WAAW,IAAI,cAAc,WAAW;AAC9C,SAAS,KAAK,OAAO,MAAM,IAAI;AAC/B,SAAS,KAAK,OAAO,MAAM,IAAI;AAC/B,SAAS,KAAK,QAAQ,MAAM,IAAI;AAChC,SAAS,KAAK,MAAM,MAAM,IAAI;AAC9B,SAAS,KAAK,OAAO,MAAM,IAAI;AAE/B,IAAO,wBAAQ,CAAC,UAAU,SAAS,OAAO,cAAc,QAAQ;;;ACpEhE,IAAM,gBAAgB;AACtB,IAAMI,WAAU;AAAA,EAEd,uBAAuB;AAAA,EACvB,qBAAqB;AAAA,EAErB,qBAAqB;AAAA,EACrB,yBAAyB;AAAA,EACzB,wBAAwB;AAC1B;AAEA,SAAS,eAAe,SAAS,SAAS,SAAS,SAAS;AAC1D,QAAM,SAAS,UAAU,YAAY,UAAU;AAC/C,MAAI,QAAQ,KAAK,KAAK,KAAK,IAAI,MAAM,KAAK;AAC1C,MAAI,SAAS;AAAG,YAAQ,CAAC;AAAA,WAChB,QAAQ;AAAG,YAAQ,MAAM;AAClC,SAAO;AACT;AAIA,SAAS,UAAU,QAAQ,QAAQ;AACjC,MAAI,CAAC,UAAU,CAAC;AAAQ,WAAO,CAAC,GAAG,CAAC;AACpC,QAAM,UAAU,eAAe,OAAO,IAAI,OAAO,IAAI,OAAO,IAAI,OAAO,EAAE;AACzE,MAAI,OAAO,WAAW;AAAG,WAAO;AAChC,QAAM,UAAU,eAAe,OAAO,IAAI,OAAO,IAAI,OAAO,IAAI,OAAO,EAAE;AACzE,SAAO,CAAC,SAAS,OAAO;AAC1B;AAEA,SAAS,mBAAmB,OAAO,cAAc,GAAK;AACpD,MAAI,aAAa;AACjB,MAAI,aAAa;AACjB,MAAI,eAAe;AACnB,MAAI,SAAS,MAAQ,SAAS;AAAO,iBAAa,IAAI;AAAA,WAC7C,SAAS,MAAQ,SAAS;AAAO,iBAAa,IAAI;AAAA;AACtD,mBAAe,IAAI;AACxB,SAAO,CAAC,YAAY,YAAY,YAAY;AAC9C;AAEA,SAAS,mBAAmB,YAAY,UAAU,UAAU;AAC1D,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,iBAAiB,SAAS,KAAK,SAAS;AAC9C,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,iBAAiB,SAAS,KAAK,SAAS;AAC9C,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,iBAAiB,SAAS,KAAK,SAAS;AAC9C,QAAM,iBAAiB,KAAK,KAAK,mBAAmB,mBAAmB,mBAAmB,mBAAmB,mBAAmB,gBAAgB;AAChJ,QAAM,iBAAiB,KAAK,KAAK,mBAAmB,mBAAmB,mBAAmB,mBAAmB,mBAAmB,gBAAgB;AAChJ,QAAM,eAAe,KAAK,KAAK,iBAAiB,iBAAiB,iBAAiB,iBAAiB,iBAAiB,cAAc;AAClI,MAAI,UAAU,eAAe,eAAe,iBAAiB,iBAAiB,iBAAiB,mBAAmB,IAAI,eAAe;AACrI,MAAI,SAAS;AAAK,aAAS;AAAA,WAClB,SAAS;AAAM,aAAS;AACjC,MAAI,eAAe,KAAK,KAAK,MAAM;AACnC,iBAAgB,UAAU,eAAgB;AAC1C,MAAI;AACJ,MAAI,eAAeA,SAAQ;AAAqB,iBAAa,WAAW;AAAA,WAC/D,eAAeA,SAAQ;AAAuB,iBAAa,WAAW;AAAA;AAC1E,iBAAa,WAAW;AAC7B,SAAO;AACT;AAEA,SAAS,4BAA4B,kBAAkB,kBAAkB,gBAAgB,YAAY;AACnG,MAAI;AACJ,MAAI,eAAe,KAAK,IAAI,gBAAgB,GAAG;AAC7C,QAAI,mBAAmB;AAAG,2BAAqB,gBAAgB;AAAA;AAC1D,2BAAqB,gBAAgB;AAAA,EAC5C,WAAW,eAAe,KAAK,IAAI,gBAAgB,GAAG;AACpD,QAAI,mBAAmB;AAAG,2BAAqB,gBAAgB;AAAA;AAC1D,2BAAqB,gBAAgB;AAAA,EAC5C,OAAO;AACL,QAAI,iBAAiB;AAAG,2BAAqB,gBAAgB;AAAA;AACxD,2BAAqB,gBAAgB;AAAA,EAC5C;AACA,SAAO;AACT;AAEA,SAAS,0BAA0B,kBAAkB,kBAAkB,gBAAgB,YAAY;AACjG,MAAI;AACJ,MAAI,eAAe,KAAK,IAAI,gBAAgB,GAAG;AAC7C,QAAI,mBAAmB;AAAG,2BAAqB,gBAAgB;AAAA;AAC1D,2BAAqB,gBAAgB;AAAA,EAC5C,WAAW,eAAe,KAAK,IAAI,gBAAgB,GAAG;AACpD,QAAI,mBAAmB;AAAG,2BAAqB,gBAAgB;AAAA;AAC1D,2BAAqB,gBAAgB;AAAA,EAC5C,OAAO;AACL,QAAI,iBAAiB;AAAG,2BAAqB,gBAAgB;AAAA;AACxD,2BAAqB,gBAAgB;AAAA,EAC5C;AACA,SAAO;AACT;AAEA,SAAS,0BAA0B,kBAAkB,kBAAkB,gBAAgB,YAAY,kBAAkB,kBAAkB,gBAAgB,YAAY;AACjK,MAAI;AACJ,QAAM,0BAA0B,0BAA0B,kBAAkB,kBAAkB,gBAAgB,UAAU;AACxH,QAAM,4BAA4B,4BAA4B,kBAAkB,kBAAkB,gBAAgB,UAAU;AAC5H,MAAI,4BAA4B,gBAAgB,YAAY;AAC1D,QAAI,8BAA8B,gBAAgB;AAAgB,2BAAqB,gBAAgB;AAAA;AAClG,2BAAqB,gBAAgB;AAAA,EAC5C,OAAO;AACL,QAAI,8BAA8B,gBAAgB;AAAgB,2BAAqB,gBAAgB;AAAA;AAClG,2BAAqB,gBAAgB;AAAA,EAC5C;AACA,SAAO;AACT;AAEA,SAAS,yBAAyB,YAAY,UAAU,UAAU,cAAc;AAC9E,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,iBAAiB,SAAS,KAAK,SAAS;AAC9C,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,iBAAiB,SAAS,KAAK,SAAS;AAC9C,QAAM,aAAa,KAAK,IAAI,KAAK,IAAI,gBAAgB,GAAG,KAAK,IAAI,gBAAgB,GAAG,KAAK,IAAI,cAAc,CAAC;AAC5G,QAAM,aAAa,KAAK,IAAI,KAAK,IAAI,gBAAgB,GAAG,KAAK,IAAI,gBAAgB,GAAG,KAAK,IAAI,cAAc,CAAC;AAC5G,MAAI,eAAe;AACnB,MAAI,eAAe;AACnB,MAAI,iBAAiB;AACrB,QAAM,2BAA2B,cAAc,aAAa;AAC5D,MAAI,2BAA2B;AAAK,oBAAgBA,SAAQ;AAAA,WACnD,2BAA2B;AAAM,oBAAgBA,SAAQ;AAAA;AAC7D,sBAAkBA,SAAQ;AAC/B,QAAM,iBAAiB,KAAK,KAAK,mBAAmB,mBAAmB,mBAAmB,gBAAgB;AAC1G,QAAM,iBAAiB,KAAK,KAAK,mBAAmB,mBAAmB,mBAAmB,gBAAgB;AAC1G,QAAM,eAAe,KAAK,KAAK,iBAAiB,iBAAiB,iBAAiB,cAAc;AAChG,QAAM,WAAW,KAAK,IAAI,gBAAgB,gBAAgB,YAAY;AACtE,MAAI,qBAAqB,WAAW;AACpC,MAAI,qBAAqB,WAAW;AACpC,MAAI,mBAAmB,SAAS;AAChC,MAAI,mBAAmB,SAAS;AAChC,MAAI,aAAa,gBAAgB;AAC/B,uBAAmB,SAAS;AAC5B,uBAAmB,SAAS;AAAA,EAC9B,WAAW,aAAa,cAAc;AACpC,yBAAqB,SAAS;AAC9B,yBAAqB,SAAS;AAAA,EAChC;AACA,QAAM,iBAAiB,CAAC,oBAAoB,kBAAkB;AAC9D,QAAM,eAAe,CAAC,kBAAkB,gBAAgB;AACxD,QAAM,aAAa,UAAU,gBAAgB,YAAY;AACzD,QAAM,QAAQ,mBAAmB,YAAYA,SAAQ,sBAAsB;AAC3E,kBAAgB,MAAM;AACtB,kBAAgB,MAAM;AACtB,oBAAkB,MAAM;AACxB,aAAW,eAAe,cAAc;AACtC,UAAM,cAAc,mBAAmB,aAAaA,SAAQ,uBAAuB;AACnF,oBAAgB,YAAY;AAC5B,oBAAgB,YAAY;AAC5B,sBAAkB,YAAY;AAAA,EAChC;AAGA,MAAI;AACJ,MAAI,iBAAiB,KAAK,IAAI,cAAc,cAAc,cAAc,GAAG;AACzE,yBAAqB,0BAA0B,kBAAkB,kBAAkB,gBAAgB,UAAU;AAAA,EAC/G,WAAW,mBAAmB,KAAK,IAAI,cAAc,cAAc,GAAG;AACpE,yBAAqB,4BAA4B,kBAAkB,kBAAkB,gBAAgB,UAAU;AAAA,EACjH,OAAO;AACL,yBAAqB,0BAA0B,kBAAkB,kBAAkB,gBAAgB,YAAY,kBAAkB,kBAAkB,gBAAgB,UAAU;AAAA,EAC/K;AACA,SAAO;AACT;AAEA,SAAS,SAAS,WAAW;AAE3B,QAAM,WAA4B,CAAC;AACnC,QAAM,WAA4B,CAAC;AACnC,QAAM,cAA6B,CAAC;AACpC,QAAM,mBAAkC,CAAC;AACzC,MAAI,CAAC;AAAW,WAAO,EAAE,OAAO,aAAa,YAAY,iBAAiB;AAG1E,aAAW,UAAU,OAAO,KAAK;AAC/B,UAAM,SAAS,OAAO,UAAU,MAAM;AACtC,UAAM,YAA2B,CAAC;AAClC,UAAM,YAA2B,CAAC;AAClC,eAAWC,UAAS,QAAQ;AAC1B,YAAM,SAAS,UAAUA,OAAM;AAC/B,YAAMC,UAAS,UAAUD,OAAM;AAE/B,YAAM,SAAS,UAAU,QAAQC,OAAM;AACvC,YAAM,UAAU,OAAO;AACvB,YAAM,UAAU,OAAO;AACvB,gBAAU,KAAK,OAAO;AACtB,gBAAU,KAAK,OAAO;AAAA,IACxB;AACA,aAAS,KAAK,SAAS;AACvB,aAAS,KAAK,SAAS;AAAA,EACzB;AAGA,aAAW,UAAU,OAAO,KAAK;AAE/B,UAAM,eAAgB,WAAW,OAAO,QAAS,IAAI;AACrD,UAAM,iBAAiB,OAAO,UAAU,MAAM;AAC9C,UAAM,aAAa,UAAU,eAAe,cAAc;AAC1D,UAAM,WAAW,UAAU,eAAe,eAAe,GAAG;AAC5D,UAAM,WAAW,UAAU,eAAe,GAAG;AAE7C,UAAM,eAAe,mBAAmB,YAAY,UAAU,QAAQ;AACtE,UAAM,iBAAiB,yBAAyB,YAAY,UAAU,UAAU,SAAS,QAAQ,MAAM,YAAY,CAAC;AACpH,gBAAY,UAAU;AACtB,qBAAiB,UAAU;AAAA,EAC7B;AACA,SAAO,EAAE,OAAO,aAAa,YAAY,iBAAiB;AAC5D;AAEO,SAAS,QAAQ,WAAW;AACjC,MAAI,CAAC,aAAa,UAAU,WAAW;AAAG,WAAO;AACjD,QAAM,eAAe,SAAS,SAAS;AACvC,QAAM,YAAY,CAAC;AACnB,aAAW,aAAa,OAAO,KAAK;AAClC,cAAU,OAAO,QAAQ,SAAS,KAAK;AAAA,MACrC,MAAM,WAAW,QAAQ,aAAa,MAAM,UAAU;AAAA,MACtD,WAAW,gBAAgB,QAAQ,aAAa,WAAW,UAAU;AAAA,IACvE;AAAA,EACF;AACA,SAAO;AACT;AAEO,SAAS,MAAM,WAAW;AAC/B,QAAM,QAAqD,CAAC;AAC5D,MAAI,CAAC,aAAa,UAAU,WAAW;AAAG,WAAO;AACjD,QAAM,eAAe,SAAS,SAAS;AACvC,aAAWC,YAAW,uBAAU;AAC9B,UAAM,aAAaA,SAAQ,aAAa,aAAa,OAAO,aAAa,UAAU;AACnF,QAAI,cAAc;AAAe,YAAM,KAAK,EAAE,MAAMA,SAAQ,MAAM,WAAW,CAAC;AAAA,EAChF;AACA,SAAO;AACT;;;AChOA,IAAMC,mBAAkB;AAAA,EACtB,OAAO,CAAC,GAAG,GAAG,GAAG,CAAC;AAAA,EAClB,OAAO,CAAC,GAAG,GAAG,GAAG,CAAC;AAAA,EAClB,QAAQ,CAAC,GAAG,IAAI,IAAI,EAAE;AAAA,EACtB,MAAM,CAAC,IAAI,IAAI,IAAI,EAAE;AAAA,EACrB,OAAO,CAAC,IAAI,IAAI,IAAI,EAAE;AAAA,EACtB,MAAM,CAAC,CAAC;AACV;AAEA,IAAI;AACJ,IAAI;AACJ,IAAI;AAEJ,eAAsBC,UAAQC,QAAeC,SAAuC;AAClF,QAAM,cAAc,MAAM,aAAa,cAAcD,QAAOC,OAAM;AAClE,MAAI,CAAC;AAAa,WAAO,CAAC;AAC1B,QAAM,QAA2B,CAAC;AAClC,WAASC,KAAI,GAAGA,KAAI,YAAY,QAAQA,MAAK;AAC3C,UAAMC,eAAc,CAAC;AACrB,QAAI,YAAYD,IAAG,WAAW;AAC5B,iBAAW,OAAO,OAAO,KAAKJ,gBAAe,GAAG;AAC9C,QAAAK,aAAY,OAAOL,iBAAgB,KAAK,IAAI,CAACM,WAAU,YAAYF,IAAG,UAAUE,OAAM;AAAA,MACxF;AAAA,IACF;AACA,UAAM,YAAY,YAAYF,IAAG;AACjC,QAAI,MAAW,CAAC,OAAO,kBAAkB,OAAO,kBAAkB,GAAG,CAAC;AACtE,QAAI,SAAc,CAAC,GAAG,GAAG,GAAG,CAAC;AAC7B,QAAI,aAAa,UAAU,SAAS,GAAG;AACrC,iBAAW,MAAM,WAAW;AAC1B,YAAI,GAAG,KAAK,IAAI;AAAI,cAAI,KAAK,GAAG;AAChC,YAAI,GAAG,KAAK,IAAI;AAAI,cAAI,KAAK,GAAG;AAChC,YAAI,GAAG,KAAK,IAAI;AAAI,cAAI,KAAK,GAAG;AAChC,YAAI,GAAG,KAAK,IAAI;AAAI,cAAI,KAAK,GAAG;AAAA,MAClC;AACA,UAAI,MAAM,IAAI;AACd,UAAI,MAAM,IAAI;AACd,eAAS,CAAC,IAAI,MAAMF,OAAM,MAAM,MAAM,IAAI,IAAI,MAAMA,OAAM,MAAM,MAAM,IAAI,IAAI,MAAMA,OAAM,MAAM,MAAM,IAAI,IAAI,MAAMA,OAAM,MAAM,MAAM,EAAE;AAAA,IAC1I,OAAO;AACL,YAAM,YAAYE,IAAG,MAAM;AAAA,QACzB,KAAK,MAAM,KAAK,IAAI,GAAG,YAAYA,IAAG,IAAI,QAAQ,EAAE,CAAC;AAAA,QACrD,KAAK,MAAM,KAAK,IAAI,GAAG,YAAYA,IAAG,IAAI,QAAQ,EAAE,CAAC;AAAA,QACrD,KAAK,MAAM,KAAK,IAAKF,OAAM,MAAM,MAAM,GAAI,YAAYE,IAAG,IAAI,YAAY,EAAE,IAAI,KAAK,IAAI,GAAG,YAAYA,IAAG,IAAI,QAAQ,EAAE,CAAC;AAAA,QAC1H,KAAK,MAAM,KAAK,IAAKF,OAAM,MAAM,MAAM,GAAI,YAAYE,IAAG,IAAI,YAAY,EAAE,IAAI,KAAK,IAAI,GAAG,YAAYA,IAAG,IAAI,QAAQ,EAAE,CAAC;AAAA,MAC5H,IAAI,CAAC,GAAG,GAAG,GAAG,CAAC;AACf,eAAS;AAAA,QACN,YAAYA,IAAG,IAAI,QAAQ,MAAOF,OAAM,MAAM,MAAM;AAAA,QACpD,YAAYE,IAAG,IAAI,QAAQ,MAAOF,OAAM,MAAM,MAAM;AAAA,SACpD,YAAYE,IAAG,IAAI,YAAY,KAAK,YAAYA,IAAG,IAAI,QAAQ,OAAOF,OAAM,MAAM,MAAM;AAAA,SACxF,YAAYE,IAAG,IAAI,YAAY,KAAK,YAAYA,IAAG,IAAI,QAAQ,OAAOF,OAAM,MAAM,MAAM;AAAA,MAC3F;AAAA,IACF;AACA,UAAM,YAAuB,QAAQ,SAAS;AAC9C,UAAM,KAAK;AAAA,MACT,IAAIE;AAAA,MACJ,OAAO,KAAK,MAAM,MAAM,YAAYA,IAAG,UAAU,IAAI;AAAA,MACrD,UAAU,KAAK,MAAM,MAAM,YAAYA,IAAG,aAAa,IAAI;AAAA,MAC3D,aAAa,KAAK,MAAM,MAAM,YAAYA,IAAG,gBAAgB,IAAI;AAAA,MACjE,OAAO;AAAA,MACP;AAAA,MACA;AAAA,MACA;AAAA,MACA,aAAaC;AAAA,MACb;AAAA,IACF,CAAC;AAAA,EACH;AACA,SAAO;AACT;AAEA,eAAsBE,OAAKJ,SAAiE;AApF5F;AAqFE,MAAIK,KAAI,SAAS;AACf,wBAAoB;AACpB,oBAAgB;AAAA,EAClB;AACA,MAAI,CAAC,qBAAqB,CAAC,eAAe;AACxC,KAAC,mBAAmB,aAAa,IAAI,MAAM,QAAQ,IAAI;AAAA,MACrDL,QAAO,KAAK,UAAU,WAAU,KAAAA,QAAO,KAAK,aAAZ,mBAAsB,SAAS,IAAI;AAAA,MACnEA,QAAO,KAAK,YAAY,WAAU,KAAAA,QAAO,KAAK,aAAZ,mBAAsB,SAAS,IAAI;AAAA,IACvE,CAAC;AAAA,EACH,OAAO;AACL,QAAIA,QAAO;AAAO,UAAI,iBAAiB,kBAAkB,WAAW;AACpE,QAAIA,QAAO;AAAO,UAAI,iBAAiB,cAAc,WAAW;AAAA,EAClE;AACA,QAAM,eAAe,IAAiB,aAAa,iBAAiB;AACpE,iBAAe,IAAiB,aAAa,cAAc,aAAa;AACxE,SAAO,CAAC,mBAAmB,aAAa;AAC1C;;;ACjFA,IAAMM,UAAiD,CAAC,MAAM,IAAI;AAClE,IAAM,mBAAmB,CAAC,+CAA+C,oDAAoD;AAE7H,IAAMC,aAAY,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAEjC,IAAM,UAAU,CAAC,QAAQ,QAAQ,SAAS,SAAS,QAAQ,OAAO,UAAU;AAC5E,IAAM,YAAY;AAElB,IAAM,gBAAgB;AACtB,IAAM,wBAAwB;AAC9B,IAAM,qBAAqB;AAE3B,IAAIC,YAAU,OAAO;AACrB,IAAIC,aAAW;AACf,IAAI,aAA+B,CAAC,GAAG,CAAC;AAUxC,IAAMC,SAGF;AAAA,EACF,OAAO,CAAC;AAAA,EACR,OAAO,CAAC;AACV;AAEA,IAAM,YAAY;AAAA,EAShB,OAAO,CAAC,GAAG,GAAG,GAAG,CAAC;AAAA,EAClB,OAAO,CAAC,GAAG,GAAG,GAAG,CAAC;AAAA,EAClB,QAAQ,CAAC,GAAG,IAAI,IAAI,EAAE;AAAA,EACtB,MAAM,CAAC,IAAI,IAAI,IAAI,EAAE;AAAA,EACrB,OAAO,CAAC,IAAI,IAAI,IAAI,EAAE;AAAA,EACtB,MAAM,CAAC,CAAC;AAAA,EACR,MAAM,CAAC,GAAG,IAAI,IAAI,GAAG,GAAG,GAAG,CAAC;AAC9B;AAEA,eAAsBC,YAAWC,SAAqC;AAtEtE;AAwEE,MAAIC,KAAI;AAAS,IAAAP,QAAO,KAAK;AAC7B,MAAI,CAACA,QAAO,IAAI;AAGd,YAAQ,CAAC,qBAAqB,SAAS,wBAAwB,SAAS,YAAY,UAAU,QAAQ,mBAAmB,iBAAiB,qBAAqB,qBAAqB,cAAc,SAAS,SAAS,OAAO,GAAGM,OAAM;AACpO,IAAAN,QAAO,KAAK,MAAM,WAAU,KAAAM,QAAO,KAAK,aAAZ,mBAAsB,SAAS;AAC3D,UAAM,SAAS,OAAO,OAAON,QAAO,GAAG,eAAe,SAAS;AAC/D,IAAAC,WAAU,GAAG,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AACxF,IAAAA,WAAU,GAAG,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAAA,EAC1F,WAAWK,QAAO;AAAO,QAAI,iBAAiBN,QAAO,GAAG,WAAW;AACnE,SAAOA,QAAO;AAChB;AAEA,eAAsB,aAAaM,SAAqC;AArFxE;AAsFE,MAAIC,KAAI;AAAS,IAAAP,QAAO,KAAK;AAC7B,MAAI,CAACA,QAAO,IAAI;AACd,IAAAA,QAAO,KAAK,MAAM,WAAU,KAAAM,QAAO,KAAK,aAAZ,mBAAsB,SAAS;AAC3D,UAAM,SAAS,OAAO,OAAON,QAAO,GAAG,eAAe,SAAS;AAC/D,IAAAC,WAAU,GAAG,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AACxF,IAAAA,WAAU,GAAG,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAAA,EAC1F,WAAWK,QAAO;AAAO,QAAI,iBAAiBN,QAAO,GAAG,WAAW;AACnE,SAAOA,QAAO;AAChB;AAQA,eAAe,YAAYQ,QAAeC,SAA6C;AACrF,QAAM,QAA4B,CAAC;AACnC,MAAI,CAACD,UAAS,CAACE,QAAO;AAAI,WAAO;AACjC,QAAMC,KAA4B,CAAC;AACnC,QAAM,SAASH,OAAM,MAAM,MAAM,MAAMA,OAAM,MAAM,MAAM;AACzD,QAAM,SAAS,KAAK,IAAI,KAAK,OAAOA,OAAM,MAAM,MAAM,KAAK,CAAC,IAAI,GAAG,qBAAqB;AACxF,QAAM,QAAQ,KAAK,MAAM,SAAS,QAAQ,CAAC,IAAI;AAC/C,EAAAG,GAAE,SAAY,MAAM,eAAeH,QAAO,CAAC,QAAQ,KAAK,CAAC;AACzD,EAAAG,GAAE,OAAU,KAAKA,GAAE,QAAQ,OAAO;AAClC,GAACA,GAAE,WAAWA,GAAE,QAAQ,IAAI,MAAMD,QAAO,GAAG,aAAaC,GAAE,MAAM,gBAAgB;AACjF,EAAAA,GAAE,QAAW,QAAQA,GAAE,UAAU,CAAC,GAAG,CAAC,CAAC;AACvC,EAAAA,GAAE,SAAY,QAAQA,GAAE,WAAW,CAAC,CAAC,CAAC;AACtC,QAAM,cAAgC,QAAQA,GAAE,QAAQ,CAAC;AACzD,EAAG,QAAQ,YAAY,UAAU;AACjC,cAAY,OAAO,WAAW,CAAC;AAC/B,EAAAA,GAAE,WAAc,MAAM,aAAa,CAAC;AACpC,EAAG,QAAQ,WAAW;AAEtB,EAAAA,GAAE,MAAS,IAAIA,GAAE,UAAU,CAAC;AAC5B,EAAAA,GAAE,SAAY,OAAOA,GAAE,UAAU,CAAC;AAClC,MAAI,KAAK;AACT,EAAAA,GAAE,MAAM,MAAS,MAAM,uBAAuBA,GAAE,OAAOA,GAAE,MAAMF,QAAO,KAAK,eAAe,KAAK,GAAGA,QAAO,KAAK,gBAAgB,GAAGA,QAAO,KAAK,iBAAiB,CAAC;AAC/J,QAAM,MAAM,MAAME,GAAE,IAAI,KAAK;AAC7B,QAAM,SAAS,MAAMA,GAAE,IAAI,KAAK;AAChC,QAAM,WAAW,MAAMA,GAAE,OAAO,KAAK;AACrC,aAAW,YAAY,MAAM,KAAK,GAAG,GAAG;AACtC,UAAM,WAAc,MAAMA,GAAE,OAAO,UAAU,CAAC;AAC9C,UAAM,QAAQ,MAAM,SAAS,KAAK;AAClC,IAAG,QAAQ,QAAQ;AACnB,UAAM,UAAe,CAAC,MAAM,IAAI,MAAM,IAAI,MAAM,KAAK,MAAM,IAAI,MAAM,KAAK,MAAM,EAAE;AAClF,UAAM,SAAkBC,OAAM,SAAS,kBAAkB;AACzD,UAAM,UAAe,CAAC,KAAK,MAAM,QAAQ,KAAK,WAAW,EAAE,GAAG,KAAK,MAAM,QAAQ,KAAK,WAAW,EAAE,GAAG,KAAK,MAAM,QAAQ,KAAK,WAAW,EAAE,GAAG,KAAK,MAAM,QAAQ,KAAK,WAAW,EAAE,CAAC;AACpL,UAAM,QAAQ,OAAO;AACrB,UAAM,QAAQ,QAAQ,SAAS;AAC/B,UAAMC,QAAyB,EAAE,IAAI,MAAM,OAAO,KAAK,SAAS,QAAQ,MAAM;AAC9E,UAAM,KAAKA,KAAI;AAAA,EACjB;AACA,SAAO,KAAKF,EAAC,EAAE,QAAQ,CAACG,YAAc,QAAQH,GAAEG,QAAO,CAAC;AACxD,QAAM,KAAK,CAAC,GAAG,MAAM,EAAE,QAAQ,EAAE,KAAK;AACtC,MAAI,MAAM,UAAUL,QAAO,KAAK,eAAe;AAAI,UAAM,SAAUA,QAAO,KAAK,eAAe;AAC9F,SAAO;AACT;AAEA,eAAe,cAAcD,QAAe,GAAqBC,SAAqC;AACpG,QAAMI,QAAmB;AAAA,IACvB,IAAI,EAAE;AAAA,IACN,OAAO,KAAK,MAAM,MAAM,EAAE,KAAK,IAAI;AAAA,IACnC,UAAU,KAAK,MAAM,MAAM,EAAE,KAAK,IAAI;AAAA,IACtC,aAAa;AAAA,IACb,KAAK,EAAE;AAAA,IACP,QAAQ,EAAE;AAAA,IACV,OAAO,EAAE;AAAA,IACT,WAAW,CAAC;AAAA,IACZ,WAAW,CAAC;AAAA,IACZ,aAAa,CAAC;AAAA,EAChB;AACA,MAAIL,UAASE,QAAO,MAAMD,QAAO,KAAK,aAAa,EAAE,SAASA,QAAO,KAAK,iBAAiB,IAAI;AAC7F,UAAME,KAA4B,CAAC;AACnC,UAAM,UAAU,CAAC,EAAE,OAAO,IAAI,EAAE,OAAO,IAAI,EAAE,OAAO,KAAK,EAAE,OAAO,IAAI,EAAE,OAAO,KAAK,EAAE,OAAO,EAAE;AAC/F,IAAAA,GAAE,OAAU,MAAM,cAAcH,QAAO,CAAC,OAAO,GAAG,CAAC,CAAC,GAAG,CAACO,WAAU,GAAG,IAAIA,WAAU,GAAG,EAAE,GAAG,UAAU;AACrG,IAAAJ,GAAE,MAAS,IAAIA,GAAE,MAAM,UAAU,KAAK;AACtC,KAACA,GAAE,OAAOA,GAAE,SAAS,IAAID,QAAO,GAAG,QAAQC,GAAE,KAAK,CAAC,cAAc,UAAU,CAAC;AAC5E,UAAM,YAAY,MAAMA,GAAE,MAAM,KAAK,GAAG;AACxC,UAAM,SAAS,MAAM,KAAK,MAAM,OAAO,IAAI,KAAK,IAAI,QAAQ,EAAE,KAAK;AACnE,QAAI,UAAUF,QAAO,KAAK,iBAAiB,IAAI;AAC7C,MAAAI,MAAK,cAAc;AACnB,MAAAF,GAAE,WAAc,QAAQA,GAAE,WAAW,CAAC,IAAI,CAAC,CAAC;AAC5C,YAAM,aAAsB,MAAMA,GAAE,SAAS,MAAM;AACnD,YAAM,YAAqB,WAAW,IAAI,CAACK,SAAQ,CAACA,KAAI,KAAKD,WAAU,GAAG,IAAIC,KAAI,KAAKD,WAAU,GAAG,IAAKC,KAAI,MAAM,CAAE,CAAC;AACtH,YAAM,aAAsB,UAAU,IAAI,CAACA,SAAQ,CAACA,KAAI,KAAK,EAAE,OAAO,IAAIA,KAAI,KAAK,EAAE,OAAO,IAAKA,KAAI,MAAM,CAAE,CAAC;AAC9G,MAAAH,MAAK,YAAa,WAAY,IAAI,CAACG,SAAQ,CAAC,WAAW,MAAMA,KAAI,KAAK,EAAE,OAAO,KAAK,WAAW,MAAMA,KAAI,KAAK,EAAE,OAAO,KAAMA,KAAI,MAAM,CAAE,CAAC;AAC1I,MAAAH,MAAK,YAAuB,QAAQA,MAAK,SAAS;AAClD,iBAAW,OAAO,OAAO,KAAK,SAAS,GAAG;AACxC,QAAAA,MAAK,YAAY,OAAO,UAAU,KAAK,IAAI,CAACI,WAAmBJ,MAAK,aAAaA,MAAK,UAAUI,UAASJ,MAAK,UAAUI,UAAS,IAAK;AAAA,MACxI;AAAA,IACF;AACA,WAAO,KAAKN,EAAC,EAAE,QAAQ,CAACG,YAAc,QAAQH,GAAEG,QAAO,CAAC;AAAA,EAC1D;AACA,SAAOD;AACT;AAEA,eAAsBK,UAAQV,QAAeC,SAAuC;AAvLpF;AAwLE,MAAI,CAACC,QAAO,MAAM,CAACA,QAAO,MAAM,GAAC,KAAAA,QAAO,OAAP,mBAAW,OAAO,GAAG,UAAS,GAAC,KAAAA,QAAO,OAAP,mBAAW,OAAO,GAAG;AAAO,WAAO,CAAC;AACpG,eAAa,CAACF,OAAM,MAAM,MAAM,GAAGA,OAAM,MAAM,MAAM,CAAC;AACtD,EAAAW;AACA,QAAM,YAAYV,QAAO,KAAK,YAAY,KAAM,IAAI,IAAIW;AACxD,QAAM,YAAYD,aAAWV,QAAO,KAAK,cAAc;AACvD,MAAIA,QAAO,eAAe,YAAY,WAAW;AAC/C,WAAOY,OAAM;AAAA,EACf;AACA,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,UAAM,mBAAmB,KAAKZ,QAAO,KAAK,YAAY,KAAM,IAAI,IAAIW;AACpE,UAAM,oBAAoBD,YAAU,KAAKV,QAAO,KAAK,cAAc;AACnE,QAAIA,QAAO,eAAeY,OAAM,MAAM,WAAWZ,QAAO,KAAK,aAAa;AACxE,MAAAY,OAAM,QAAQ,MAAM,QAAQ,IAAIA,OAAM,MAAM,IAAI,CAAC,YAAY,cAAcb,QAAO,SAASC,OAAM,CAAC,CAAC;AAAA,IACrG,WAAWA,QAAO,eAAe,oBAAoB,qBAAqBY,OAAM,MAAM,SAAS,GAAG;AAChG,MAAAA,OAAM,QAAQ,MAAM,QAAQ,IAAIA,OAAM,MAAM,IAAI,CAAC,YAAY,cAAcb,QAAO,SAASC,OAAM,CAAC,CAAC;AAAA,IACrG,OAAO;AACL,MAAAY,OAAM,QAAQ,MAAM,YAAYb,QAAOC,OAAM;AAC7C,MAAAW,aAAW,IAAI;AACf,MAAAC,OAAM,QAAQ,MAAM,QAAQ,IAAIA,OAAM,MAAM,IAAI,CAAC,YAAY,cAAcb,QAAO,SAASC,OAAM,CAAC,CAAC;AACnG,MAAAU,YAAU;AAAA,IACZ;AAEA,UAAM,WAAW,CAAC,GAAGE,OAAM,KAAK;AAChC,IAAAA,OAAM,MAAM,SAAS;AACrB,QAAIZ,QAAO,mBAAmB,GAAG;AAC/B,eAASa,KAAI,GAAGA,KAAID,OAAM,MAAM,QAAQC,MAAK;AAC3C,cAAM,SAAaC,QAAOF,OAAM,MAAMC,IAAG,WAAW,UAAU;AAC9D,YAAI,OAAO,IAAI,MAAMd,OAAM,MAAM,MAAM,KAAK,QAAQ,OAAO,IAAI,MAAMA,OAAM,MAAM,MAAM,KAAK,QAAQa,OAAM,MAAMC,IAAG,eAAeD,OAAM,MAAMC,IAAG,eAAeb,QAAO,KAAK,iBAAiB,IAAI;AAC/L,gBAAM,WAAeG,OAAM,OAAO,KAAK,aAAa;AACpD,gBAAM,cAAkBA,OAAM,OAAO,QAAQ,aAAa;AAE1D,UAAAS,OAAM,MAAM,KAAK,EAAE,GAAG,SAASC,KAAI,KAAK,UAAU,QAAQ,YAAY,CAAC;AAAA,QACzE;AAAA,MACF;AAAA,IACF;AACA,aAASA,KAAI,GAAGA,KAAID,OAAM,MAAM,QAAQC,MAAK;AAC3C,YAAM,OAAW,KAAKD,OAAM,MAAMC,IAAG,WAAW,UAAU;AAC1D,MAAAD,OAAM,MAAMC,IAAG,MAAM,KAAK;AAC1B,MAAAD,OAAM,MAAMC,IAAG,SAAS,KAAK;AAAA,IAC/B;AACA,YAAQD,OAAM,KAAK;AAAA,EACrB,CAAC;AACH;;;ACvNA,IAAIG;AACJ,IAAMC,UAAwB,CAAC;AAC/B,IAAIC,YAAU,OAAO;AACrB,IAAIC,aAAY;AAChB,IAAIC,aAAW;AAEf,eAAsBC,OAAKC,SAAqC;AAjBhE;AAkBE,MAAIC,KAAI;AAAS,IAAAP,UAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,UAAQ,MAAM,WAAU,KAAAM,QAAO,KAAK,aAAZ,mBAAsB,SAAS;AAAA,WAC1DA,QAAO;AAAO,QAAI,iBAAiBN,QAAM,WAAW;AAC7D,SAAOA;AACT;AAEA,eAAsBQ,UAAQC,QAAeH,SAAgB,KAAaI,QAAgC;AAxB1G;AAyBE,MAAI,CAACV;AAAO,WAAO;AACnB,QAAM,cAAY,KAAAM,QAAO,KAAK,aAAZ,mBAAsB,aAAY,KAAM,IAAI,IAAIF;AAClE,QAAM,YAAYF,eAAW,KAAAI,QAAO,KAAK,aAAZ,mBAAsB,eAAc;AACjE,MAAIA,QAAO,eAAe,YAAY,aAAcH,eAAcO,UAAUT,QAAO,MAAM;AACvF,IAAAC;AACA,WAAOD,QAAO;AAAA,EAChB;AACA,EAAAC,YAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,UAAM,SAAY,MAAM,eAAeO,QAAO,EAACT,WAAA,gBAAAA,QAAO,OAAO,GAAG,SAAQA,QAAM,OAAO,GAAG,MAAM,KAAK,IAAGA,WAAA,gBAAAA,QAAO,OAAO,GAAG,SAAQA,QAAM,OAAO,GAAG,MAAM,KAAK,CAAC,GAAG,KAAK;AACnK,UAAM,MAAMA,WAAA,gBAAAA,QAAO,QAAQ;AAC3B,UAAM,OAAO,MAAM,IAAI,KAAK,GAAG;AAC/B,IAAAC,QAAO,OAAO,KAAK,MAAM,MAAM,GAAG,IAAI;AACtC,IAAAE,aAAYO;AACZ,IAAAN,aAAW,IAAI;AACf,IAAG,QAAQ,CAAC,QAAQ,GAAG,CAAC;AACxB,YAAQH,QAAO,IAAI;AAAA,EACrB,CAAC;AACH;;;AC3CA;AAAA;AAAA,mBAAAU;AAAA,EAAA;AAAA,aAAAC;AAAA,EAAA;AAAA;AAAA;AAAO,IAAMA,OAAqB;AAAA,EAChC;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AAEO,IAAM,aAA8B;AAAA,EACzC,CAAC,WAAW,UAAU;AAAA,EACtB,CAAC,WAAW,UAAU;AAAA,EACtB,CAAC,gBAAgB,eAAe;AAAA,EAChC,CAAC,aAAa,YAAY;AAAA,EAC1B,CAAC,aAAa,YAAY;AAAA,EAC1B,CAAC,WAAW,UAAU;AAAA,EACtB,CAAC,YAAY,WAAW;AAAA,EACxB,CAAC,aAAa,YAAY;AAC5B;AAEO,IAAM,WAA4B;AAAA,EACvC,CAAC,YAAY,cAAc;AAAA,EAC3B,CAAC,aAAa,eAAe;AAAA,EAC7B,CAAC,aAAa,UAAU;AAAA,EACxB,CAAC,cAAc,WAAW;AAC5B;AAEO,IAAM,WAA8B;AAAA,EACzC,CAAC,CAAC,WAAW,UAAU,GAAG,CAAC,gBAAgB,eAAe,CAAC;AAAA,EAC3D,CAAC,CAAC,aAAa,YAAY,GAAG,CAAC,gBAAgB,eAAe,CAAC;AACjE;AAEO,IAAMD,aAAsC;AAAA,EACjD,SAAS,CAAC,WAAW,YAAY,WAAW;AAAA,EAC5C,UAAU,CAAC,YAAY,aAAa,YAAY;AAAA,EAChD,OAAO,CAAC,gBAAgB,iBAAiB,YAAY,WAAW,cAAc;AAAA,EAC9E,SAAS,CAAC,gBAAgB,aAAa,WAAW;AAAA,EAClD,UAAU,CAAC,iBAAiB,cAAc,YAAY;AAAA,EACtD,MAAM,CAAC;AACT;;;AC5CA,IAAM,YAAY;AAElB,IAAME,SAGF;AAAA,EACF,WAAW,CAAC;AAAA,EACZ,SAAS,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAC1C;AAEO,SAAS,UAAUC,OAAkB;AAC1C,aAAW,QAAe,YAAY;AACpC,UAAM,OAAOA,MAAK,UAAU,UAAU,CAAC,OAAO,GAAG,SAAS,KAAK,EAAE;AACjE,UAAM,QAAQA,MAAK,UAAU,UAAU,CAAC,OAAO,GAAG,SAAS,KAAK,EAAE;AAClE,QAAIA,MAAK,UAAU,SAASA,MAAK,UAAU,QAAQ;AACjD,UAAIA,MAAK,UAAU,MAAM,SAAS,KAAKA,MAAK,UAAU,OAAO,SAAS,IAAI;AACxE,cAAM,MAAMA,MAAK,UAAU;AAC3B,QAAAA,MAAK,UAAU,QAAQA,MAAK,UAAU;AACtC,QAAAA,MAAK,UAAU,SAAS;AAAA,MAC1B;AAAA,IACF;AAAA,EACF;AACA,aAAW,QAAe,UAAU;AAClC,UAAM,QAAQA,MAAK,UAAU,UAAU,CAAC,OAAQ,MAAM,GAAG,SAAS,KAAK,EAAG;AAC1E,UAAM,SAASA,MAAK,UAAU,UAAU,CAAC,OAAQ,MAAM,GAAG,SAAS,KAAK,EAAG;AAC3E,QAAIA,MAAK,UAAU,UAAUA,MAAK,UAAU,SAAS;AACnD,UAAIA,MAAK,UAAU,OAAO,SAAS,KAAKA,MAAK,UAAU,QAAQ,SAAS,IAAI;AAC1E,QAAAA,MAAK,UAAU,OAAO,OAAO,CAAC;AAAA,MAChC;AAAA,IACF;AAAA,EACF;AACA,aAAW,CAAC,MAAMC,QAAO,KAAY,UAAU;AAC7C,UAAM,OAAOD,MAAK,UAAU,UAAU,CAAC,OAAQ,MAAM,GAAG,SAAS,KAAK,EAAG;AACzE,UAAM,QAAQA,MAAK,UAAU,UAAU,CAAC,OAAQ,MAAM,GAAG,SAAS,KAAK,EAAG;AAC1E,UAAM,SAASA,MAAK,UAAU,UAAU,CAAC,OAAQ,MAAM,GAAG,SAASC,SAAQ,EAAG;AAC9E,UAAM,UAAUD,MAAK,UAAU,UAAU,CAAC,OAAQ,MAAM,GAAG,SAASC,SAAQ,EAAG;AAC/E,QAAI,CAACD,MAAK,UAAU,WAAW,CAACA,MAAK,UAAU;AAAU;AACzD,UAAM,eAAeA,MAAK,UAAU,QAAQ;AAAA,MAC1C,KAAK,IAAIA,MAAK,UAAU,QAAQ,SAAS,KAAKA,MAAK,UAAU,MAAM,SAAS,EAAE;AAAA,MAC9E,KAAK,IAAIA,MAAK,UAAU,SAAS,SAAS,KAAKA,MAAK,UAAU,MAAM,SAAS,EAAE;AAAA,IACjF,IAAI,CAAC,GAAG,CAAC;AACT,UAAM,gBAAgBA,MAAK,UAAU,SAAS;AAAA,MAC5C,KAAK,IAAIA,MAAK,UAAU,SAAS,SAAS,KAAKA,MAAK,UAAU,OAAO,SAAS,EAAE;AAAA,MAChF,KAAK,IAAIA,MAAK,UAAU,QAAQ,SAAS,KAAKA,MAAK,UAAU,OAAO,SAAS,EAAE;AAAA,IACjF,IAAI,CAAC,GAAG,CAAC;AACT,QAAI,aAAa,KAAK,aAAa,MAAM,cAAc,KAAK,cAAc,IAAI;AAC5E,YAAM,MAAMA,MAAK,UAAU;AAC3B,MAAAA,MAAK,UAAU,QAAQA,MAAK,UAAU;AACtC,MAAAA,MAAK,UAAU,SAAS;AAAA,IAC1B;AAAA,EACF;AACF;AAEO,SAAS,OAAO,WAAqD;AAC1E,WAASE,KAAI,GAAGA,KAAI,UAAU,QAAQA,MAAK;AACzC,QAAI,UAAUA,OAAMH,OAAM,UAAUG,KAAI;AACtC,YAAM,OAAO,CAAC,KAAK,IAAI,UAAUA,IAAG,YAAY,KAAKH,OAAM,UAAUG,IAAG,YAAY,EAAE,GAAG,KAAK,IAAI,UAAUA,IAAG,YAAY,KAAKH,OAAM,UAAUG,IAAG,YAAY,EAAE,CAAC;AAClK,UAAI,KAAK,KAAK,aAAa,KAAK,KAAK,WAAW;AAC9C,kBAAUA,MAAKH,OAAM,UAAUG;AAAA,MACjC,OAAO;AACL,QAAAH,OAAM,UAAUG,MAAK,UAAUA;AAAA,MACjC;AAAA,IACF,OAAO;AACL,MAAAH,OAAM,UAAUG,MAAK,UAAUA;AAAA,IACjC;AAAA,EACF;AACA,SAAO;AACT;AAEO,SAAS,SAASC,QAAeC,aAA2B;AACjE,QAAMC,KAA4B,CAAC;AACnC,MAAI,CAACF,OAAM,SAAS,CAACA,OAAM,MAAM,MAAM,CAACA,OAAM,MAAM;AAAI,WAAOA;AAC/D,EAAAJ,OAAM,UAAU;AAAA,IACd,CAAC,GAAG,CAAC;AAAA,IACL,CAACI,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI,GAAGA,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI,CAAC;AAAA,IACjL,CAACA,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI,GAAGA,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI,CAAC;AAAA,IACjL,CAAC,GAAG,CAAC;AAAA,EACP;AACA,EAAAE,GAAE,MAAS,IAAIF,QAAOJ,OAAM,OAAO;AACnC,EAAAM,GAAE,SAAY,MAAM,eAAeA,GAAE,KAAK,CAACD,aAAWA,WAAS,CAAC;AAChE,QAAM,QAAW,KAAKC,GAAE,QAAQ,OAAO;AACvC,SAAO,KAAKA,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,SAAO;AACT;AAEO,SAAS,YAAYN,OAAkBO,aAA0C;AACtF,EAAAP,MAAK,YAAYA,MAAK,UAAU,OAAO,CAACQ,SAAQA,QAAOA,KAAI,QAAQ;AACnE,aAAWA,QAAOR,MAAK,WAAW;AAChC,IAAAQ,KAAI,WAAW;AAAA,MACbA,KAAI,SAAS,MAAMD,YAAW,KAAKR,OAAM,QAAQ,GAAG,KAAKA,OAAM,QAAQ,GAAG,MAAMQ,YAAW,KAAKR,OAAM,QAAQ,GAAG;AAAA,MACjHS,KAAI,SAAS,MAAMD,YAAW,KAAKR,OAAM,QAAQ,GAAG,KAAKA,OAAM,QAAQ,GAAG,MAAMQ,YAAW,KAAKR,OAAM,QAAQ,GAAG;AAAA,IACnH;AACA,IAAAS,KAAI,cAAc;AAAA,MAChBA,KAAI,SAAS,KAAKD,YAAW;AAAA,MAAIC,KAAI,SAAS,KAAKD,YAAW;AAAA,IAChE;AAAA,EACF;AACA,QAAM,gBAAoB,KAAKP,MAAK,UAAU,IAAI,CAAC,OAAO,GAAG,QAAQ,GAAGO,WAAU;AAClF,EAAAP,MAAK,MAAM,cAAc;AACzB,EAAAA,MAAK,SAAS,cAAc;AAC5B,SAAOA;AACT;;;ACxFA,IAAIS;AACJ,IAAIC,aAAY;AAChB,IAAIC,YAAU,OAAO;AAGrB,IAAMC,SAIF;AAAA,EACF,OAAO,CAAC;AAAA,EACR,QAAQ,CAAC;AAAA,EACT,MAAM;AACR;AAEA,eAAsBC,OAAKC,SAAqC;AAC9D,MAAIC,KAAI;AAAS,IAAAN,UAAQ;AACzB,MAAI,CAACA,SAAO;AACV,YAAQ,CAAC,MAAM,GAAGK,OAAM;AACxB,IAAAL,UAAQ,MAAM,UAAUK,QAAO,KAAK,SAAS;AAAA,EAC/C,WAAWA,QAAO;AAAO,QAAI,iBAAiBL,QAAM,WAAW;AAC/D,EAAAC,aAAYD,QAAM,OAAO,GAAG,QAAQA,QAAM,OAAO,GAAG,MAAM,KAAK;AAC/D,MAAIC,aAAY;AAAI,IAAAA,aAAY;AAChC,SAAOD;AACT;AAEA,eAAe,gBAAgB,KAAKK,SAAQE,QAAO;AACjD,QAAMC,OAAM,IAAI,GAAG;AACnB,QAAM,YAAiC,CAAC;AACxC,MAAI,QAAQ;AACZ,WAAS,KAAK,GAAG,KAAKA,KAAI,QAAQ,MAAM;AACtC,YAAQA,KAAI,IAAI;AAChB,QAAI,QAAQH,QAAO,KAAK,eAAe;AACrC,YAAM,cAAqB,CAACG,KAAI,IAAI,IAAIA,KAAI,IAAI,EAAE;AAClD,gBAAU,KAAK;AAAA,QACb,OAAO,KAAK,MAAM,MAAM,KAAK,IAAI;AAAA,QACjC,MAAaA,KAAI;AAAA,QACjB;AAAA,QACA,UAAU;AAAA,UACR,KAAK,OAAOD,OAAM,MAAM,MAAM,KAAK,YAAY,EAAE;AAAA,UACjD,KAAK,OAAOA,OAAM,MAAM,MAAM,KAAK,YAAY,EAAE;AAAA,QACnD;AAAA,MACF,CAAC;AAAA,IACH;AAAA,EACF;AACA,UAAQ,UAAU,OAAO,CAAC,MAAM,SAAU,KAAK,QAAQ,OAAO,KAAK,QAAQ,MAAO,CAAC;AACnF,QAAM,SAA4B,CAAC;AACnC,QAAM,SAAa,KAAK,UAAU,IAAI,CAAC,OAAO,GAAG,QAAQ,GAAG,CAACA,OAAM,MAAM,IAAIA,OAAM,MAAM,EAAE,CAAC;AAC5F,QAAME,eAAyC,CAAC;AAChD,aAAW,CAAC,MAAM,OAAO,KAAK,OAAO,QAAeC,UAAS,GAAG;AAC9D,UAAM,KAAqB,CAAC;AAC5B,aAASC,KAAI,GAAGA,KAAI,QAAQ,SAAS,GAAGA,MAAK;AAC3C,YAAM,MAAM,UAAU,KAAK,CAAC,OAAO,GAAG,SAAS,QAAQA,GAAE;AACzD,YAAM,MAAM,UAAU,KAAK,CAAC,OAAO,GAAG,SAAS,QAAQA,KAAI,EAAE;AAC7D,UAAI,OAAO,OAAO,IAAI,SAASN,QAAO,KAAK,iBAAiB,MAAM,IAAI,SAASA,QAAO,KAAK,iBAAiB;AAAI,WAAG,KAAK,CAAC,IAAI,UAAU,IAAI,QAAQ,CAAC;AAAA,IACtJ;AACA,IAAAI,aAAY,QAAQ;AAAA,EACtB;AACA,QAAMG,QAAmB,EAAE,IAAI,GAAG,OAAO,KAAK,OAAO,KAAK,QAAQ,OAAO,QAAQ,WAAW,aAAAH,aAAY;AACxG,EAAI,UAAUG,KAAI;AAClB,SAAO,KAAKA,KAAI;AAChB,SAAO;AACT;AAEA,eAAe,eAAe,KAAKP,SAAQE,QAAO;AAChD,QAAM,SAA4B,CAAC;AACnC,WAAS,KAAK,GAAG,KAAK,IAAI,GAAG,QAAQ,MAAM;AACzC,UAAMC,OAAM,IAAI,GAAG;AACnB,UAAM,aAAa,KAAK,MAAM,MAAMA,KAAI,KAAK,EAAE,IAAI;AACnD,QAAI,aAAaH,QAAO,KAAK,eAAe;AAC1C,YAAM,YAAiC,CAAC;AACxC,eAASM,KAAI,GAAGA,KAAI,IAAIA,MAAK;AAC3B,cAAM,QAAQH,KAAI,IAAIG,KAAI;AAC1B,YAAI,QAAQN,QAAO,KAAK,eAAe;AACrC,gBAAM,cAAqB,CAACG,KAAI,IAAIG,KAAI,IAAIH,KAAI,IAAIG,KAAI,EAAE;AAC1D,oBAAU,KAAK;AAAA,YACb,MAAaH,KAAIG;AAAA,YACjB,OAAO,KAAK,MAAM,MAAM,KAAK,IAAI;AAAA,YACjC;AAAA,YACA,UAAU,CAAC,KAAK,OAAOJ,OAAM,MAAM,MAAM,KAAK,YAAY,EAAE,GAAG,KAAK,OAAOA,OAAM,MAAM,MAAM,KAAK,YAAY,EAAE,CAAC;AAAA,UACnH,CAAC;AAAA,QACH;AAAA,MACF;AACA,YAAM,SAAa,KAAK,UAAU,IAAI,CAAC,OAAO,GAAG,QAAQ,GAAG,CAACA,OAAM,MAAM,IAAIA,OAAM,MAAM,EAAE,CAAC;AAI5F,YAAME,eAAiD,CAAC;AACxD,iBAAW,CAAC,MAAM,OAAO,KAAK,OAAO,QAAeC,UAAS,GAAG;AAC9D,cAAM,KAAqB,CAAC;AAC5B,iBAASC,KAAI,GAAGA,KAAI,QAAQ,SAAS,GAAGA,MAAK;AAC3C,gBAAM,MAAM,UAAU,KAAK,CAAC,OAAO,GAAG,SAAS,QAAQA,GAAE;AACzD,gBAAM,MAAM,UAAU,KAAK,CAAC,OAAO,GAAG,SAAS,QAAQA,KAAI,EAAE;AAC7D,cAAI,OAAO,OAAO,IAAI,SAASN,QAAO,KAAK,iBAAiB,MAAM,IAAI,SAASA,QAAO,KAAK,iBAAiB;AAAI,eAAG,KAAK,CAAC,IAAI,UAAU,IAAI,QAAQ,CAAC;AAAA,QACtJ;AACA,QAAAI,aAAY,QAAQ;AAAA,MACtB;AACA,YAAMG,QAAmB,EAAE,IAAI,OAAO,YAAY,KAAK,OAAO,KAAK,QAAQ,OAAO,QAAQ,WAAW,CAAC,GAAG,SAAS,GAAG,aAAAH,aAAY;AACjI,MAAI,UAAUG,KAAI;AAClB,aAAO,KAAKA,KAAI;AAAA,IAClB;AAAA,EACF;AACA,SAAO,KAAK,CAAC,GAAG,MAAM,EAAE,QAAQ,EAAE,KAAK;AACvC,MAAI,OAAO,SAASP,QAAO,KAAK;AAAa,WAAO,SAASA,QAAO,KAAK;AACzE,SAAO;AACT;AAEA,eAAsBQ,UAAQC,QAAeT,SAAuC;AAClF,MAAI,CAACL,WAAS,EAACA,WAAA,gBAAAA,QAAO,OAAO,GAAG;AAAO,WAAO,CAAC;AAC/C,MAAI,CAACK,QAAO;AAAa,IAAAF,OAAM,MAAM,SAAS;AAC9C,EAAAD;AACA,QAAM,YAAYG,QAAO,KAAK,YAAY,KAAM,IAAI,IAAIF,OAAM;AAC9D,QAAM,YAAYD,aAAWG,QAAO,KAAK,cAAc;AACvD,MAAIA,QAAO,eAAe,YAAY,WAAW;AAC/C,WAAOF,OAAM;AAAA,EACf;AACA,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,UAAMY,KAA4B,CAAC;AACnC,IAAAb,YAAU;AAmCV,IAAAa,GAAE,QAAY,SAASD,QAAOb,UAAS;AACvC,IAAAc,GAAE,MAAMf,WAAA,gBAAAA,QAAO,QAAQe,GAAE;AACzB,IAAAZ,OAAM,OAAO,IAAI;AACjB,UAAM,MAAM,MAAMY,GAAE,IAAI,MAAM;AAC9B,IAAAZ,OAAM,SAAUY,GAAE,IAAI,MAAM,OAAO,KAC/B,MAAM,gBAAgB,KAAKV,SAAQS,MAAK,IACxC,MAAM,eAAe,KAAKT,SAAQS,MAAK;AAC3C,eAAWF,SAAQT,OAAM,QAAQ;AAC/B,MAAI,YAAYS,OAAM,CAACE,OAAM,MAAM,MAAM,GAAGA,OAAM,MAAM,MAAM,CAAC,CAAC;AAChE,MAAI,OAAOF,MAAK,SAAS;AAAA,IAC3B;AACA,WAAO,KAAKG,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AAExD,YAAQb,OAAM,MAAM;AAAA,EACtB,CAAC;AACH;;;AC1KA,IAAIc;AACJ,IAAIC,QAA4B,CAAC;AACjC,IAAIC,aAAW;AACf,IAAIC,YAAU,OAAO;AACrB,IAAIC,aAAY;AAEhB,IAAM,WAAW;AAEjB,eAAsBC,OAAKC,SAAqC;AAC9D,MAAI,CAACN,WAASO,KAAI,SAAS;AACzB,IAAAP,UAAQ,MAAM,UAAUM,QAAO,OAAO,SAAS;AAC/C,UAAM,SAAS,OAAO,OAAON,QAAM,eAAe,SAAS;AAC3D,IAAAI,aAAY,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAAA,EACpF,WAAWE,QAAO;AAAO,QAAI,iBAAiBN,QAAM,WAAW;AAC/D,SAAOA;AACT;AAEA,eAAeQ,SAAQ,KAAe,aAA+BF,SAAgB;AACnF,MAAI,KAAK;AACT,MAAI,UAA+B,CAAC;AACpC,aAAW,cAAc,CAAC,GAAG,GAAG,CAAC,GAAG;AAElC,IAAG,KAAK,YAAY;AAClB,YAAM,WAAW,aAAa;AAE9B,YAAM,UAAa,QAAQ,IAAI,KAAK,CAAC,MAAe,EAAE,MAAM,OAAQ,YAAY,MAAO,EAAE,MAAM,MAAM,OAAO,OAAO,MAAO,CAAC;AAC3H,YAAM,YAAe,QAAQ,IAAI,KAAK,CAAC,MAAe,EAAE,MAAM,OAAQ,YAAY,MAAO,EAAE,MAAM,MAAM,KAAK,OAAO,MAAO,CAAC;AAC3H,YAAM,WAAW,UAAU,QAAQ,CAAC,IAAI,GAAG,UAAU,MAAM,KAAK,CAAC,CAAC;AAClE,YAAM,SAAS,MAAM,SAAS,OAAO,CAAC,EAAE,MAAM;AAC9C,YAAM,SAAS,MAAM,QAAQ,MAAM;AACnC,eAASG,KAAI,GAAGA,KAAI,QAAQ,MAAM,IAAIA,MAAK;AACzC,iBAAS,IAAI,GAAG,IAAI,QAAQ,MAAM,IAAI,KAAK;AACzC,gBAAM,QAAQ,OAAOA,IAAG;AACxB,cAAI,SAASH,QAAO,OAAO,iBAAiB,MAAM,MAAM,IAAI;AAC1D,kBAAM,MAAM,MAAM,KAAK,MAAMG,KAAI,QAAQ,KAAK;AAC9C,kBAAM,MAAM,MAAM,KAAK,MAAMA,KAAI,QAAQ,KAAK;AAC9C,kBAAM,YAAY,OAAOA,IAAG,IAAI,CAAC,MAAc,KAAK,WAAW,aAAaL,WAAU;AACtF,kBAAM,CAAC,GAAG,CAAC,IAAI;AAAA,cACb,KAAM,WAAW,aAAa,UAAU;AAAA,cACxC,KAAM,WAAW,aAAa,UAAU;AAAA,YAC1C;AACA,kBAAM,CAAC,GAAG,CAAC,IAAI;AAAA,cACb,KAAM,WAAW,aAAa,UAAU,KAAM;AAAA,cAC9C,KAAM,WAAW,aAAa,UAAU,KAAM;AAAA,YAChD;AACA,gBAAI,SAAc,CAAC,GAAG,GAAG,GAAG,CAAC;AAC7B,qBAAS,OAAO,IAAI,CAAC,MAAM,KAAK,IAAI,GAAG,KAAK,IAAI,GAAG,CAAC,CAAC,CAAC;AACtD,kBAAM,MAAM;AAAA,cACV,OAAO,KAAK,YAAY;AAAA,cACxB,OAAO,KAAK,YAAY;AAAA,cACxB,OAAO,KAAK,YAAY;AAAA,cACxB,OAAO,KAAK,YAAY;AAAA,YAC1B;AACA,kBAAM,SAAS;AAAA,cACb,IAAI;AAAA,cAEJ,OAAO,KAAK,MAAM,MAAM,KAAK,IAAI;AAAA,cACjC,OAAO,IAAI;AAAA,cACX,OAAO,OAAO,GAAG;AAAA,cAGjB,KAAK,IAAI,IAAI,CAAC,MAAM,KAAK,MAAM,CAAC,CAAC;AAAA,cACjC;AAAA,YACF;AACA,oBAAQ,KAAK,MAAM;AAAA,UACrB;AAAA,QACF;AAAA,MACF;AAAA,IACF,CAAC;AAAA,EACH;AAEA,MAAI,QAAQ,CAACM,OAAS,QAAQA,EAAC,CAAC;AAIhC,QAAM,WAAW,QAAQ,IAAI,CAAC,MAAM,CAAC,EAAE,OAAO,IAAI,EAAE,OAAO,IAAI,EAAE,OAAO,IAAI,EAAE,OAAO,EAAE,CAAC;AACxF,QAAM,YAAY,QAAQ,IAAI,CAAC,MAAM,EAAE,KAAK;AAC5C,MAAI,SAAwB,CAAC;AAC7B,MAAI,YAAY,SAAS,SAAS,GAAG;AACnC,UAAM,MAAM,MAAS,MAAM,uBAAuB,UAAU,WAAWJ,QAAO,OAAO,aAAaA,QAAO,OAAO,cAAcA,QAAO,OAAO,aAAa;AACzJ,aAAS,MAAM,IAAI,KAAK;AACxB,IAAG,QAAQ,GAAG;AAAA,EAChB;AAGA,YAAU,QACP,OAAO,CAAC,MAAM,QAAQ,OAAO,SAAS,GAAG,CAAC,EAC1C,KAAK,CAAC,GAAG,MAAO,EAAE,QAAQ,EAAE,KAAM;AAErC,SAAO;AACT;AAEA,eAAsBK,UAAQC,QAAeN,SAAyC;AACpF,QAAM,YAAYA,QAAO,OAAO,YAAY,KAAM,IAAI,IAAIJ;AAC1D,QAAM,YAAYC,aAAWG,QAAO,OAAO,cAAc;AACzD,MAAIA,QAAO,eAAe,YAAY,aAAcL,MAAK,SAAS,GAAI;AACpE,IAAAE;AACA,WAAOF;AAAA,EACT;AACA,EAAAE,YAAU;AACV,MAAI,CAACI,KAAI,QAAQ,SAAS,KAAK,KAAK,CAACA,KAAI,QAAQ,SAAS,eAAe;AAAG,WAAON;AACnF,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,UAAMY,cAAa,CAACD,OAAM,MAAM,MAAM,GAAGA,OAAM,MAAM,MAAM,CAAC;AAC5D,UAAM,SAAY,MAAM,eAAeA,QAAO,CAACR,YAAWA,UAAS,GAAG,KAAK;AAC3E,UAAMU,QAAU,IAAI,QAAQ,UAAU,KAAK;AAC3C,UAAMC,aAAYD,MAAK,UAAU,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAC7C,IAAG,QAAQA,KAAI;AACf,IAAG,QAAQ,MAAM;AAEjB,QAAI;AACJ,QAAIR,QAAO,OAAO;AAAS,gBAAUN,QAAM,QAAQe,UAAS;AAC5D,IAAAb,aAAW,IAAI;AACf,IAAG,QAAQa,UAAS;AAEpB,UAAM,MAAM,MAAMP,SAAQ,SAAqBK,aAAgCP,OAAM;AACrF,IAAAL,QAAO;AACP,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;AC/HO,IAAM,YAAY;AAAA,EACvB;AAAA,EAAQ;AAAA,EAAW;AAAA,EAAY;AAAA,EAAW;AAAA,EAAY;AAAA,EACtD;AAAA,EAAiB;AAAA,EAAa;AAAA,EAAc;AAAA,EAAa;AAAA,EACzD;AAAA,EAAW;AAAA,EAAY;AAAA,EAAY;AAAA,EAAa;AAAA,EAAa;AAC/D;AAEO,IAAMe,SAAQ,UAAU;AAExB,IAAM,UAAU,UAAU,OAAO,CAAC,QAAQ,WAAWC,OAAM;AAChE,SAAO,aAAaA;AACpB,SAAO;AACT,GAAG,CAAC,CAAC;AAEL,IAAM,qBAAqB;AAAA,EACzB,CAAC,WAAW,cAAc;AAAA,EAAG,CAAC,aAAa,cAAc;AAAA,EACzD,CAAC,aAAa,WAAW;AAAA,EAAG,CAAC,WAAW,UAAU;AAAA,EAClD,CAAC,YAAY,WAAW;AAAA,EAAG,CAAC,YAAY,eAAe;AAAA,EACvD,CAAC,cAAc,eAAe;AAAA,EAAG,CAAC,cAAc,YAAY;AAAA,EAC5D,CAAC,YAAY,WAAW;AAAA,EAAG,CAAC,aAAa,YAAY;AAAA,EACrD,CAAC,gBAAgB,eAAe;AAAA,EAAG,CAAC,WAAW,UAAU;AAC3D;AACO,IAAM,uBAAuB,mBAAmB,IAAI,CAAC,CAAC,YAAY,UAAU,MAAO,CAAC,QAAQ,aAAa,QAAQ,WAAW,CAAE;AAE9H,IAAM,YAAY;AAAA,EACvB,CAAC,QAAQ,SAAS;AAAA,EAAG,CAAC,WAAW,SAAS;AAAA,EAAG,CAAC,QAAQ,UAAU;AAAA,EAChE,CAAC,YAAY,UAAU;AAAA,EAAG,CAAC,QAAQ,cAAc;AAAA,EACjD,CAAC,gBAAgB,WAAW;AAAA,EAAG,CAAC,aAAa,WAAW;AAAA,EACxD,CAAC,gBAAgB,SAAS;AAAA,EAAG,CAAC,WAAW,UAAU;AAAA,EACnD,CAAC,YAAY,WAAW;AAAA,EAAG,CAAC,QAAQ,eAAe;AAAA,EACnD,CAAC,iBAAiB,YAAY;AAAA,EAAG,CAAC,cAAc,YAAY;AAAA,EAC5D,CAAC,iBAAiB,UAAU;AAAA,EAAG,CAAC,YAAY,WAAW;AAAA,EACvD,CAAC,aAAa,YAAY;AAC5B;AAgBO,SAAS,eAAe,WAA6C;AAC1E,QAAM,QAAQ,UAAU,OAAO,CAAC,EAAE,MAAM,MAAM,MAAM,KAAK,GAAG,EAAE,UAAU,EAAE,GAAG,EAAE,EAAE,OAAO;AAAA,IACtF,MAAM,KAAK,IAAI,MAAM,CAAC;AAAA,IACtB,MAAM,KAAK,IAAI,MAAM,CAAC;AAAA,IACtB,MAAM,KAAK,IAAI,MAAM,CAAC;AAAA,IACtB,MAAM,KAAK,IAAI,MAAM,CAAC;AAAA,EACxB,IAAI;AAAA,IACF,MAAM,OAAO;AAAA,IACb,MAAM,OAAO;AAAA,IACb,MAAM,OAAO;AAAA,IACb,MAAM,OAAO;AAAA,EACf,CAAC;AACD,SAAO,CAAC,MAAM,MAAM,MAAM,MAAM,MAAM,OAAO,MAAM,MAAM,MAAM,OAAO,MAAM,IAAI;AAClF;AAEO,SAAS,WAAW,OAAO,CAAC,QAAQ,KAAK,GAAG,CAAC,uBAAuB,oBAAoB,GAAsB;AACnH,QAAM,SAAS,SAAS;AACxB,QAAM,SAAS,QAAQ;AACvB,QAAM,YAAY,CAAC,MAAMC,QAAmB;AAAA,IAC1C,IAAIA;AAAA,IACJ,OAAO,KAAK;AAAA,IACZ,QAAQ,CAAC,KAAK,IAAI,KAAK,sBAAsB,KAAK,IAAI,KAAK,uBAAuB,KAAK,IAAI,KAAK,sBAAsB,KAAK,IAAI,KAAK,qBAAqB;AAAA,IACzJ,KAAK,CAAC,KAAK,MAAM,KAAK,IAAI,KAAK,MAAM,GAAG,KAAK,MAAM,KAAK,IAAI,KAAK,MAAM,GAAG,KAAK,MAAM,KAAK,IAAI,KAAK,MAAM,GAAG,KAAK,MAAM,KAAK,IAAI,KAAK,MAAM,CAAC;AAAA,IAC5I,WAAW,KAAK,UAAU,IAAI,CAAC,EAAE,OAAO,MAAM,SAAS,OAAO;AAAA,MAC5D;AAAA,MACA;AAAA,MACA,UAAU,CAAC,KAAK,MAAM,SAAS,IAAI,MAAM,GAAG,KAAK,MAAM,SAAS,IAAI,MAAM,CAAC;AAAA,MAC3E,aAAa,CAAC,SAAS,IAAI,uBAAuB,SAAS,IAAI,qBAAqB;AAAA,IACtF,EAAE;AAAA,IACF,aAAa,CAAC;AAAA,EAChB;AACA,QAAM,cAAc,MAAM,IAAI,CAAC,MAAMA,OAAM,UAAU,MAAMA,EAAC,CAAC;AAC7D,SAAO;AACT;AAGO,IAAM,UAAN,MAAc;AAAA,EAKnB,YAAYC,UAAS,iBAAiB;AAJtC;AACA;AACA;AAGE,SAAK,gBAAgB,IAAI,MAAMA,QAAO;AACtC,SAAK,mBAAmB;AACxB,SAAK,kBAAkB;AAAA,EACzB;AAAA,EAEA,QAAQ,GAAG;AACT,SAAK,cAAc,EAAE,KAAK,oBAAoB;AAC9C,SAAK,KAAK,KAAK,gBAAgB;AAAA,EACjC;AAAA,EAEA,UAAU;AACR,UAAMC,OAAM,KAAK,cAAc;AAC/B,SAAK,SAAS,GAAG,KAAK,kBAAkB;AACxC,SAAK,KAAK,CAAC;AACX,SAAK,cAAc,KAAK,mBAAmB,KAAK;AAChD,WAAOA;AAAA,EACT;AAAA,EAEA,QAAQ;AAAE,WAAO,KAAK,qBAAqB;AAAA,EAAI;AAAA,EAE/C,OAAO;AAAE,WAAO,KAAK,mBAAmB;AAAA,EAAG;AAAA,EAE3C,MAAM;AAAE,WAAO,KAAK,cAAc,MAAM,GAAG,KAAK,mBAAmB,CAAC;AAAA,EAAG;AAAA,EAEvE,MAAM;AAAE,WAAO,KAAK,cAAc;AAAA,EAAI;AAAA,EAEtC,KAAK,GAAG;AACN,WAAO,IAAI,KAAK,KAAK,KAAK,KAAK,MAAM,IAAI,CAAC,GAAG,CAAC,GAAG;AAC/C,WAAK,SAAS,GAAG,KAAK,MAAM,IAAI,CAAC,CAAC;AAClC,UAAI,KAAK,MAAM,IAAI,CAAC;AAAA,IACtB;AAAA,EACF;AAAA,EAEA,KAAK,GAAG;AACN,WAAO,IAAI,KAAK,KAAK,kBAAkB;AACrC,UAAI,IAAI,IAAI;AACZ,UAAI,IAAI,KAAK,oBAAoB,KAAK,KAAK,GAAG,IAAI,CAAC;AAAG;AACtD,UAAI,CAAC,KAAK,KAAK,GAAG,CAAC;AAAG;AACtB,WAAK,SAAS,GAAG,CAAC;AAClB,UAAI;AAAA,IACN;AAAA,EACF;AAAA,EAEA,WAAWF,IAAG;AAEZ,WAAO,KAAK,gBAAgB,KAAK,cAAcA,GAAE;AAAA,EACnD;AAAA,EAEA,KAAKA,IAAG,GAAG;AACT,WAAO,KAAK,WAAWA,EAAC,IAAI,KAAK,WAAW,CAAC;AAAA,EAC/C;AAAA,EAEA,SAASA,IAAG,GAAG;AACb,UAAMG,KAAI,KAAK,cAAcH;AAC7B,SAAK,cAAcA,MAAK,KAAK,cAAc;AAC3C,SAAK,cAAc,KAAKG;AAAA,EAC1B;AACF;AAEO,SAAS,eAAe,GAAG,GAAG,UAAU,SAAS;AACtD,SAAO;AAAA,IACL,GAAG,QAAQ,IAAI,GAAG,GAAG,QAAQ;AAAA,IAC7B,GAAG,QAAQ,IAAI,GAAG,GAAG,WAAWC,MAAK;AAAA,EACvC;AACF;AAEO,SAAS,eAAe,MAAMC,eAAc,SAAS;AAC1D,QAAM,EAAE,UAAU,UAAU,IAAI,SAAS,IAAI;AAC7C,QAAM,EAAE,GAAG,EAAE,IAAI,eAAe,UAAU,UAAU,UAAU,OAAO;AACrE,SAAO;AAAA,IACL,GAAG,KAAK,WAAWA,gBAAe;AAAA,IAClC,GAAG,KAAK,WAAWA,gBAAe;AAAA,EACpC;AACF;AAUO,SAASC,OAAM,GAAGC,MAAKC,MAAK;AACjC,MAAI,IAAID;AAAK,WAAOA;AACpB,MAAI,IAAIC;AAAK,WAAOA;AACpB,SAAO;AACT;AAEO,SAAS,gBAAgB,IAAI,IAAI,IAAI,IAAI;AAC9C,QAAM,KAAK,KAAK;AAChB,QAAM,KAAK,KAAK;AAChB,SAAO,KAAK,KAAK,KAAK;AACxB;AAEO,SAAS,WAAW,GAAG,GAAG;AAC/B,SAAO,EAAE,GAAG,EAAE,IAAI,EAAE,GAAG,GAAG,EAAE,IAAI,EAAE,EAAE;AACtC;;;ACnLA,IAAIC;AACJ,IAAM,iBAAiB,CAAC,gCAA6C,iCAAoD,0CAA+D,wCAA6D;AACrP,IAAM,qBAAqB;AAC3B,IAAM,eAAe;AACrB,IAAM,mBAAmB,MAAM;AAE/B,SAAS,SAAS,QAAQ,gBAAgB,UAAU,QAAQ,SAAS,eAAe,mBAAmB,GAAG;AACxG,QAAM,kBAAkB,CAACC,YAAW;AAAA,IAClC,GAAG,cAAc,IAAIA,OAAM,GAAGA,OAAM,GAAG,MAAM;AAAA,IAC7C,GAAG,cAAc,IAAIA,OAAM,GAAGA,OAAM,GAAI,cAAc,MAAM,KAAK,IAAK,MAAM;AAAA,EAC9E;AACA,QAAM,2BAA2B,CAACA,QAAOC,SAAQC,YAAW;AAAA,IAC1D,GAASC,OAAM,KAAK,MAAMH,OAAM,IAAI,YAAY,GAAG,GAAGC,UAAS,CAAC;AAAA,IAChE,GAASE,OAAM,KAAK,MAAMH,OAAM,IAAI,YAAY,GAAG,GAAGE,SAAQ,CAAC;AAAA,EACjE;AAEA,QAAM,CAAC,QAAQ,KAAK,IAAI,OAAO;AAE/B,QAAM,wBAAwB,yBAAyB,eAAe,UAAU,QAAQ,KAAK;AAC7F,QAAM,eAAe,gBAAgB,qBAAqB;AAC1D,QAAM,iBAAuB,WAAW,eAAe,UAAU,YAAY;AAC7E,MAAI,iBAAiB;AACrB,WAASE,KAAI,GAAGA,KAAI,kBAAkBA,MAAK;AACzC,UAAM,wBAAwB,yBAAyB,gBAAgB,QAAQ,KAAK;AACpF,UAAM,cAAoB,eAAe,sBAAsB,GAAG,sBAAsB,GAAG,UAAU,OAAO;AAC5G,qBAAuB;AAAA,MACrB,EAAE,GAAG,sBAAsB,IAAI,cAAc,GAAG,sBAAsB,IAAI,aAAa;AAAA,MACvF,EAAE,GAAG,YAAY,GAAG,GAAG,YAAY,EAAE;AAAA,IACvC;AAAA,EACF;AACA,QAAM,wBAAwB,yBAAyB,gBAAgB,QAAQ,KAAK;AACpF,QAAM,QAAQ,OAAO,IAAI,sBAAsB,GAAG,sBAAsB,GAAG,QAAQ;AACnF,SAAO,EAAE,UAAU,gBAAgB,MAAY,UAAU,WAAW,MAAM;AAC5E;AAEO,SAAS,WAAW,MAAM,QAAQ,SAAS,kBAAkB,kBAAkB;AACpF,QAAM,SAAe,UAAU,IAAI,CAAC,CAAC,gBAAgB,aAAa,MAAO,CAAO,QAAQ,iBAAuB,QAAQ,cAAc,CAAE;AACvI,QAAM,WAAW,OAAO,IAAI,CAAC,CAAC,EAAE,YAAY,MAAM,YAAY;AAC9D,QAAM,WAAW,OAAO,IAAI,CAAC,CAAC,aAAa,MAAM,aAAa;AAC9D,QAAM,WAAW,OAAO,MAAM;AAC9B,QAAM,WAAW,SAAS;AAC1B,QAAM,YAAY,IAAI,MAAM,QAAQ;AAEpC,QAAM,YAAkB,eAAe,KAAK,MAAM,cAAc,OAAO;AACvE,YAAU,KAAK,KAAK,MAAM;AAAA,IACxB,OAAO,KAAK;AAAA,IACZ,MAAY,UAAU,KAAK,KAAK;AAAA,IAChC,UAAU;AAAA,EACZ;AAEA,WAAS,OAAO,WAAW,GAAG,QAAQ,GAAG,EAAE,MAAM;AAC/C,UAAM,WAAW,SAAS;AAC1B,UAAM,WAAW,SAAS;AAC1B,QAAI,UAAU,aAAa,CAAC,UAAU,WAAW;AAC/C,gBAAU,YAAY,SAAS,MAAM,UAAU,WAAW,UAAU,QAAQ,SAAS,gBAAgB;AAAA,IACvG;AAAA,EACF;AAEA,WAAS,OAAO,GAAG,OAAO,UAAU,EAAE,MAAM;AAC1C,UAAM,WAAW,SAAS;AAC1B,UAAM,WAAW,SAAS;AAC1B,QAAI,UAAU,aAAa,CAAC,UAAU,WAAW;AAC/C,gBAAU,YAAY,SAAS,MAAM,UAAU,WAAW,UAAU,QAAQ,SAAS,gBAAgB;AAAA,IACvG;AAAA,EACF;AACA,SAAO;AACT;AAEA,SAAS,4BAA4B,YAAY,OAAO,UAAU,UAAU,QAAQ;AAClF,QAAM,CAAC,QAAQ,KAAK,IAAI,OAAO;AAC/B,MAAI,eAAe;AACnB,QAAM,SAAS,KAAK,IAAI,WAAW,oBAAoB,CAAC;AACxD,QAAM,OAAO,KAAK,IAAI,WAAW,qBAAqB,GAAG,MAAM;AAC/D,WAAS,WAAW,QAAQ,WAAW,MAAM,EAAE,UAAU;AACvD,UAAM,SAAS,KAAK,IAAI,WAAW,oBAAoB,CAAC;AACxD,UAAM,OAAO,KAAK,IAAI,WAAW,qBAAqB,GAAG,KAAK;AAC9D,aAAS,WAAW,QAAQ,WAAW,MAAM,EAAE,UAAU;AACvD,UAAI,OAAO,IAAI,UAAU,UAAU,UAAU,IAAI,OAAO;AACtD,uBAAe;AACf;AAAA,MACF;AAAA,IACF;AACA,QAAI,CAAC;AAAc;AAAA,EACrB;AACA,SAAO;AACT;AAEO,SAAS,wBAAwBC,gBAAe,QAAQ;AAC7D,QAAM,CAAC,QAAQ,OAAO,YAAY,IAAI,OAAO;AAC7C,QAAM,QAAQ,IAAU,QAAQ,SAAS,QAAQ,cAAc,CAAC,EAAE,MAAM,MAAM,KAAK;AACnF,WAAS,WAAW,GAAG,WAAW,QAAQ,EAAE,UAAU;AACpD,aAAS,WAAW,GAAG,WAAW,OAAO,EAAE,UAAU;AACnD,eAAS,aAAa,GAAG,aAAa,cAAc,EAAE,YAAY;AAChE,cAAM,QAAQ,OAAO,IAAI,UAAU,UAAU,UAAU;AAEvD,YAAI,QAAQA;AAAe;AAE3B,YAAI,4BAA4B,YAAY,OAAO,UAAU,UAAU,MAAM;AAAG,gBAAM,QAAQ,EAAE,OAAO,MAAM,EAAE,UAAU,UAAU,IAAI,WAAW,EAAE,CAAC;AAAA,MACvJ;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AAEA,SAAS,aAAa,OAAO,EAAE,GAAG,EAAE,GAAG,YAAY;AACjD,SAAO,MAAM,KAAK,CAAC,EAAE,UAAU,MAAM;AAxHvC;AAyHI,UAAM,yBAAwB,eAAU,gBAAV,mBAAuB;AACrD,QAAI,CAAC;AAAuB,aAAO;AACnC,WAAa,gBAAgB,GAAG,GAAG,sBAAsB,GAAG,sBAAsB,CAAC,KAAK;AAAA,EAC1F,CAAC;AACH;AAEA,SAAS,iBAAiB,eAAe,WAAW;AAClD,QAAM,8BAA8B,UAAU,OAAO,CAAC,QAAQ,EAAE,UAAU,MAAM,GAAG,eAAe;AAChG,QAAI,CAAC,aAAa,eAAe,UAAU,UAAU;AAAG,gBAAU;AAClE,WAAO;AAAA,EACT,GAAG,CAAG;AACN,SAAO,8BAA8B,UAAU;AACjD;AAEO,SAAS,OAAO,SAAS,QAAQ,kBAAkB,kBAAkB,aAAaA,gBAAe;AACtG,QAAM,QAAuD,CAAC;AAC9D,QAAM,QAAQ,wBAAwBA,gBAAe,MAAM;AAE3D,SAAO,MAAM,SAAS,eAAe,CAAC,MAAM,MAAM,GAAG;AAEnD,UAAM,OAAO,MAAM,QAAQ;AAG3B,UAAM,kBAAwB,eAAe,KAAK,MAAM,cAAc,OAAO;AAE7E,QAAI,aAAa,OAAO,iBAAiB,KAAK,KAAK,EAAE;AAAG;AAExD,QAAI,YAAY,WAAW,MAAM,QAAQ,SAAS,kBAAkB,gBAAgB;AACpF,gBAAY,UAAU,OAAO,CAAC,MAAM,EAAE,QAAQA,cAAa;AAC3D,UAAM,QAAQ,iBAAiB,OAAO,SAAS;AAC/C,UAAM,MAAY,eAAe,SAAS;AAC1C,QAAI,QAAQA;AAAe,YAAM,KAAK,EAAE,WAAW,KAAK,OAAO,KAAK,MAAM,MAAM,KAAK,IAAI,IAAI,CAAC;AAAA,EAChG;AACA,SAAO;AACT;AAEA,eAAsBC,UAAQC,QAAeC,SAAuC;AAIlF,QAAM,MAAS,KAAK,MAAM;AACxB,QAAI,CAACT,QAAM,OAAO,GAAG;AAAO,aAAO,CAAC;AACpC,UAAM,UAAa,MAAM,eAAeQ,QAAO,CAACR,QAAM,OAAO,GAAG,MAAM,IAAIA,QAAM,OAAO,GAAG,MAAM,EAAE,CAAC;AACnG,UAAM,aAAgB,IAAO,IAAO,KAAK,SAAS,SAAS,GAAG,KAAK,GAAG,CAAG;AACzE,UAAM,UAAyBA,QAAM,QAAQ,YAAY,cAAc;AACvE,UAAM,YAAY,QAAQ,IAAI,CAAC,MAAS,QAAQ,GAAG,CAAC,CAAC,CAAC,CAAC;AACvD,cAAU,KAAQ,QAAQ,UAAU,EAAE;AACtC,WAAO;AAAA,EACT,CAAC;AAED,QAAM,UAAU,MAAM,QAAQ,IAAI,IAAI,IAAI,CAACU,YAAmBA,QAAO,OAAO,CAAC,CAAC;AAC9E,aAAWC,MAAK;AAAK,IAAG,QAAQA,EAAC;AAEjC,QAAM,UAAU,MAAM,OAAO,QAAQ,IAAI,QAAQ,IAAI,QAAQ,IAAI,QAAQ,IAAIF,QAAO,KAAK,aAAaA,QAAO,KAAK,aAAa;AAC/H,MAAI,CAACT,QAAM,OAAO,GAAG;AAAO,WAAO,CAAC;AACpC,QAAM,SAAe,WAAW,SAAS,CAACQ,OAAM,MAAM,IAAIA,OAAM,MAAM,EAAE,GAAG,CAACR,QAAM,OAAO,GAAG,MAAM,IAAIA,QAAM,OAAO,GAAG,MAAM,EAAE,CAAC;AAC/H,SAAO;AACT;AAEA,eAAsBY,OAAKH,SAAqC;AAC9D,MAAI,CAACT,WAASa,KAAI;AAAS,IAAAb,UAAQ,MAAM,UAAUS,QAAO,KAAK,SAAS;AAAA,WAC/DA,QAAO;AAAO,QAAI,iBAAiBT,QAAM,WAAW;AAC7D,SAAOA;AACT;;;ACtKA,IAAIc;AACJ,IAAI,OAAO;AAEX,eAAsBC,OAAKC,SAAqC;AAC9D,MAAI,CAACF,WAASG,KAAI;AAAS,IAAAH,UAAQ,MAAM,UAAUE,QAAO,aAAa,SAAS;AAAA,WACvEA,QAAO;AAAO,QAAI,iBAAiBF,QAAM,WAAW;AAC7D,SAAOA;AACT;AAEA,eAAsBI,SAAQC,QAAc,YAA+BH,SACoB;AA5B/F;AA6BE,MAAI;AAAM,WAAO,EAAE,MAAM,CAAC,GAAG,QAAQ,MAAM,OAAO,KAAK;AACvD,SAAO;AACP,MAAI,CAACF;AAAO,UAAMC,OAAKC,OAAM;AAC7B,QAAM,aAAa,MAAYE,SAAQC,QAAOH,OAAM;AACpD,QAAM,UAAQ,gBAAW,WAAX,mBAAmB,MAAM,OAAM;AAC7C,QAAM,WAAS,gBAAW,WAAX,mBAAmB,MAAM,OAAM;AAC9C,MAAI,CAAC,WAAW;AAAQ,WAAO,EAAE,MAAM,CAAC,GAAG,QAAQ,MAAM,OAAO,KAAK;AACrE,QAAMI,KAA4B,CAAC;AAEnC,EAAAA,GAAE,SAAY,MAAM,eAAe,WAAW,QAAQ,CAACN,QAAM,OAAO,GAAG,QAAQA,QAAM,OAAO,GAAG,MAAM,KAAK,GAAGA,QAAM,OAAO,GAAG,QAAQA,QAAM,OAAO,GAAG,MAAM,KAAK,CAAC,GAAG,KAAK;AACzK,EAAG,QAAQ,WAAW,MAAM;AAC5B,EAAAM,GAAE,OAAU,IAAIA,GAAE,QAAQ,UAAU,KAAK;AACzC,EAAAA,GAAE,MAAMN,QAAM,QAAQM,GAAE,IAAI;AAE5B,EAAAA,GAAE,UAAa,QAAQA,GAAE,KAAK,CAAC;AAC/B,MAAIA,GAAE,QAAQ,MAAM,OAAO,GAAG;AAC5B,IAAAA,GAAE,UAAa,QAAQA,GAAE,OAAO;AAChC,KAACA,GAAE,IAAIA,GAAE,EAAE,IAAO,QAAQA,GAAE,SAAS,CAAC;AACtC,IAAAA,GAAE,SAAY,WAAWA,GAAE,IAAI,CAAC;AAChC,IAAAA,GAAE,MAAS,WAAWA,GAAE,QAAQ,CAAC;AACjC,IAAAA,GAAE,OAAU,MAAM,cAAcA,GAAE,KAAK,CAAC,CAAC,GAAG,GAAG,KAAK,GAAG,CAAC,GAAG,CAAC,CAAC,GAAG,CAAC,OAAO,MAAM,CAAC;AAI/E,IAAAA,GAAE,OAAU,QAAQA,GAAE,MAAM,CAAC;AAAA,EAC/B,OAAO;AACL,IAAAA,GAAE,OAAU,MAAM,eAAeA,GAAE,SAAS,CAAC,QAAQ,KAAK,CAAC;AAAA,EAC7D;AACA,QAAM,OAAO,MAAM,KAAK,MAAMA,GAAE,KAAK,KAAK,CAAC;AAE3C,MAAIH,KAAI,QAAQ,CAACA,KAAI,UAAW,OAAO,cAAc,aAAc;AACjE,QAAID,QAAO;AAAO,UAAI,wBAAwB;AAC9C,WAAO,KAAKI,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,WAAO,EAAE,MAAM,QAAQ,MAAM,OAAO,KAAK;AAAA,EAC3C;AAEA,QAAM,cAAoB,OAAO,OAAO,MAAM;AAE9C,MAAO;AAAS,UAAS,gBAAQ,SAASD,GAAE,MAAM,WAAW;AAC7D,QAAM,WAAW,YAAY,WAAW,IAAI;AAC5C,MAAIJ,QAAO,aAAa,QAAQA,QAAO,aAAa,OAAO;AAAG,aAAS,SAAS,QAAQA,QAAO,aAAa;AAC5G,QAAM,YAAY,SAAS,aAAa,GAAG,GAAG,OAAO,MAAM;AAE3D,QAAM,kBAAwB,OAAO,OAAO,MAAM;AAClD,QAAM,eAAe,gBAAgB,WAAW,IAAI;AACpD,MAAI,WAAW;AAAQ,iBAAa,UAAU,WAAW,QAAQ,GAAG,CAAC;AACrE,eAAa,2BAA2B;AACxC,MAAIA,QAAO,aAAa,QAAQA,QAAO,aAAa,OAAO;AAAG,iBAAa,SAAS,QAAQA,QAAO,aAAa;AAChH,eAAa,UAAU,aAAa,GAAG,CAAC;AACxC,eAAa,2BAA2B;AACxC,eAAa,SAAS;AACtB,QAAM,gBAAgB,aAAa,aAAa,GAAG,GAAG,OAAO,MAAM;AACnE,WAASM,KAAI,GAAGA,KAAI,QAAQ,QAAQA;AAAK,kBAAc,KAAK,IAAIA,KAAI,KAAK,UAAU,KAAK,IAAIA,KAAI;AAChG,eAAa,aAAa,eAAe,GAAG,CAAC;AAE7C,MAAI,eAAiC;AACrC,MAAI,cAAc,iBAAiB;AACjC,mBAAqB,OAAO,OAAO,MAAM;AACzC,UAAM,UAAU,MAAYJ,SAAQ,YAAYF,OAAM;AACtD,IAAG,QAAQ,QAAQ,MAAM;AACzB,UAAM,WAAW,aAAa,WAAW,IAAI;AAC7C,aAAS,UAAU,QAAQ,QAA6B,GAAG,GAAG,aAAa,OAAO,aAAa,MAAM;AACrG,aAAS,UAAU,iBAAiB,GAAG,CAAC;AAAA,EAC1C;AAEA,SAAO,KAAKI,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,SAAO;AAEP,SAAO,EAAE,MAAM,QAAQ,iBAAiB,OAAO,YAAY;AAC7D;;;AxC9DO,IAAM,SAAN,MAAa;AAAA,EAAb;AACL,qCAAqD;AACrD,gCAAgD;AAChD,2CAA2D;AAC3D,qCAAqD;AACrD,qCAAqD;AACrD,yCAAyD;AACzD,yCAAyD;AACzD,mCAAmD;AACnD,sCAAsD;AACtD,oCAAoD;AACpD,oCAAoD;AACpD,mCAAmD;AACnD,wCAAwD;AACxD,oCAAoD;AACpD,wCAAwD;AACxD,qCAAqD;AACrD,oCAAoD;AACpD,mCAAmD;AACnD,mCAAmD;AACnD,mCAAmD;AACnD,wCAAwD;AACxD,qCAAqD;AAAA;AACvD;AAcO,IAAM,gBAAgB,CAAC,aAAgC;AAC5D,MAAI,wBAAwB;AAC5B,MAAI,mBAAmB;AACvB,MAAI,mBAAmB;AACvB,aAAW,KAAK,OAAO,OAAO,UAAU,GAAG;AACzC,6BAAyB,EAAE;AAC3B,wBAAoB,EAAE;AACtB,wBAAoB,EAAE;AAAA,EACxB;AACA,QAAM,mBAAmB,mBAAmB,IAAI,mBAAmB,mBAAmB;AACtF,SAAO;AAAA,IACL,iBAAiB,OAAO,OAAO,UAAU,EAAE;AAAA,IAC3C,kBAAkB;AAAA,IAClB,kBAAkB,OAAO,KAAK,SAAS,MAAM,EAAE;AAAA,IAC/C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA,kBAAkB;AAAA,IAClB,YAAY,OAAO,OAAO,UAAU;AAAA,EACtC;AACF;AAEO,SAAS,MAAM,UAAuB;AAE3C,aAAWE,WAAS,OAAO,KAAK,SAAS,MAAM;AAAG,aAAS,OAAOA,WAAyB;AAC7F;AAGA,eAAsBC,OAAK,UAAgC;AAtG3D;AAuGE,MAAIC,KAAI;AAAS,UAAM,QAAQ;AAC/B,MAAI,SAAS,OAAO,KAAK,SAAS;AAChC,QAAI,CAAC,SAAS,OAAO,cAAY,oBAAS,OAAO,KAAK,aAArB,mBAA+B,cAA/B,mBAA0C,SAAS,gBAAe;AACjG,OAAC,SAAS,OAAO,UAAU,SAAS,OAAO,YAAY,IAAI,MAAeD,OAAK,SAAS,MAAM;AAAA,IAChG;AACA,QAAI,CAAC,SAAS,OAAO,gBAAgB,SAAS,OAAO,KAAK,eAAa,oBAAS,OAAO,KAAK,aAArB,mBAA+B,cAA/B,mBAA0C,SAAS,gBAAe;AACvI,OAAC,SAAS,OAAO,UAAU,SAAS,OAAO,YAAY,IAAI,MAAeA,OAAK,SAAS,MAAM;AAAA,IAChG;AAAA,EACF;AACA,MAAI,SAAS,OAAO,KAAK,WAAW,CAAC,SAAS,OAAO,eAAa,oBAAS,OAAO,SAAhB,mBAAsB,cAAtB,mBAAiC,SAAS;AAAc,aAAS,OAAO,YAAsB,SAAS,SAAS,MAAM;AAExL,MAAI,SAAS,OAAO,KAAK,WAAW,CAAC,SAAS,OAAO,mBAAmB,SAAS,OAAO,KAAK,eAAe,SAAS,OAAO,KAAK,YAAY;AAAc,aAAS,OAAO,kBAA4B,WAAW,SAAS,MAAM;AACjO,MAAI,SAAS,OAAO,KAAK,WAAW,CAAC,SAAS,OAAO,mBAAiB,oBAAS,OAAO,SAAhB,mBAAsB,cAAtB,mBAAiC,SAAS;AAAkB,aAAS,OAAO,gBAA8BA,MAAK,SAAS,MAAM;AACpM,MAAI,SAAS,OAAO,KAAK,WAAW,CAAC,SAAS,OAAO,aAAW,oBAAS,OAAO,SAAhB,mBAAsB,cAAtB,mBAAiC,SAAS;AAAY,aAAS,OAAO,UAAkBA,OAAK,SAAS,MAAM;AAC5K,MAAI,SAAS,OAAO,KAAK,WAAW,CAAC,SAAS,OAAO,aAAW,oBAAS,OAAO,SAAhB,mBAAsB,cAAtB,mBAAiC,SAAS;AAAY,aAAS,OAAO,UAAkBA,OAAK,SAAS,MAAM;AAC5K,MAAI,SAAS,OAAO,KAAK,WAAW,CAAC,SAAS,OAAO;AAAY,aAAS,OAAO,aAAuBA,MAAK,SAAS,MAAM;AAC5H,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,cAArB,mBAAgC,YAAW,CAAC,SAAS,OAAO;AAAW,aAAS,OAAO,YAAsBA,MAAK,SAAS,MAAM;AACrK,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,aAArB,mBAA+B,YAAW,CAAC,SAAS,OAAO;AAAU,aAAS,OAAO,WAAoBA,OAAK,SAAS,MAAM;AACjK,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,gBAArB,mBAAkC,YAAW,CAAC,SAAS,OAAO;AAAS,aAAS,OAAO,UAAkBA,OAAK,SAAS,MAAM;AACjK,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,YAArB,mBAA8B,YAAW,CAAC,SAAS,OAAO;AAAS,aAAS,OAAO,UAAkBA,MAAK,SAAS,MAAM;AAC7J,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,SAArB,mBAA2B,YAAW,GAAC,cAAS,OAAO,KAAK,cAArB,mBAAgC,YAAW,CAAC,SAAS,OAAO;AAAU,aAAS,OAAO,WAAgBA,OAAK,SAAS,MAAM;AACrM,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,SAArB,mBAA2B,YAAW,CAAC,SAAS,OAAO;AAAU,aAAS,OAAO,WAAoBA,OAAK,SAAS,MAAM;AAE7J,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,YAArB,mBAA8B,YAAW,CAAC,SAAS,OAAO;AAAM,aAAS,OAAO,OAAY,KAAK,SAAS,MAAM;AAEpJ,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,cAArB,mBAAgC,YAAW,CAAC,SAAS,OAAO;AAAW,aAAS,OAAO,YAAsBA,MAAK,SAAS,MAAM;AAErK,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,cAArB,mBAAgC,YAAW,CAAC,SAAS,OAAO;AAAc,aAAS,OAAO,eAA4BA,MAAK,SAAS,MAAM;AAE9K,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,qBAArB,mBAAuC,YAAW,CAAC,SAAS,OAAO;AAAe,aAAS,OAAO,gBAA8BA,MAAK,SAAS,MAAM;AACxL,MAAI,SAAS,OAAO,KAAK,WAAW,CAAC,SAAS,OAAO,eAAa,oBAAS,OAAO,KAAK,aAArB,mBAA+B,cAA/B,mBAA0C,SAAS;AAAc,aAAS,OAAO,YAAsBE,YAAW,SAAS,MAAM;AACnM,MAAI,SAAS,OAAO,KAAK,WAAW,SAAS,OAAO,KAAK,aAAa,CAAC,SAAS,OAAO,kBAAgB,oBAAS,OAAO,KAAK,aAArB,mBAA+B,cAA/B,mBAA0C,SAAS;AAAc,aAAS,OAAO,eAAyB,aAAa,SAAS,MAAM;AAC7O,MAAI,SAAS,OAAO,OAAO,WAAW,CAAC,SAAS,OAAO,eAAa,oBAAS,OAAO,WAAhB,mBAAwB,cAAxB,mBAAmC,SAAS;AAAc,aAAS,OAAO,YAAsBF,MAAK,SAAS,MAAM;AACxL,MAAI,SAAS,OAAO,OAAO,WAAW,CAAC,SAAS,OAAO,aAAW,oBAAS,OAAO,WAAhB,mBAAwB,cAAxB,mBAAmC,SAAS;AAAY,aAAS,OAAO,UAAkBA,OAAK,SAAS,MAAM;AAChL,MAAI,SAAS,OAAO,aAAa,WAAW,CAAC,SAAS,OAAO;AAAc,aAAS,OAAO,eAA4BA,OAAK,SAAS,MAAM;AAG3I,mBAAiBD,WAAS,OAAO,KAAK,SAAS,MAAM,GAAG;AACtD,QAAI,SAAS,OAAOA,YAA0B,OAAO,SAAS,OAAOA,aAA2B,aAAa;AAC3G,eAAS,OAAOA,WAAyB,MAAM,SAAS,OAAOA;AAAA,IACjE;AAAA,EACF;AACF;AAEA,eAAsBI,UAAS,UAAgC;AAE7D,QAAM,YAAY,CAAC,SAAS,eAAe,QAAQ,OAAO,WAAW,OAAO,OAAO,OAAO,KAAK;AAC/F,aAAW,WAAW,OAAO,KAAK,SAAS,MAAM,GAAG;AAClD,UAAMJ,UAA2B,SAAS,OAAO;AACjD,QAAI,CAACA;AAAO;AACZ,UAAM,MAAgB,CAAC;AAEvB,UAAM,WAAWA,WAAA,gBAAAA,QAAO;AACxB,QAAI,YAAY,SAAS,MAAM,OAAO;AACpC,iBAAW,UAAU,OAAO,OAAO,SAAS,MAAM,KAAK,GAAG;AACxD,cAAMK,MAAM,OAAc,GAAG,YAAY;AACzC,YAAI,CAAC,IAAI,SAASA,GAAE;AAAG,cAAI,KAAKA,GAAE;AAAA,MACpC;AAAA,IACF,OAAO;AACL,UAAI,CAAC,YAAY,SAAS,OAAO;AAAO,YAAI,mCAAmC,OAAO;AAAA,IACxF;AACA,UAAM,UAAoB,CAAC;AAC3B,eAAWA,OAAM,KAAK;AACpB,UAAI,CAAC,UAAU,SAASA,GAAE,KACrB,CAAC,SAAS,IAAI,QAAQ,SAASA,GAAE,KACjC,CAAC,SAAS,IAAI,QAAQ,SAASA,IAAG,QAAQ,KAAK,EAAE,CAAC,KAClD,CAAC,SAAS,IAAI,QAAQ,SAASA,IAAG,QAAQ,UAAU,EAAE,CAAC,KACvD,CAAC,SAAS,IAAI,QAAQ,SAASA,IAAG,QAAQ,MAAM,EAAE,CAAC,GAAG;AACzD,gBAAQ,KAAKA,GAAE;AAAA,MACjB;AAAA,IACF;AAEA,QAAI,SAAS,OAAO,SAAS,QAAQ,SAAS;AAAG,UAAI,4BAA4B,SAAS,OAAO;AAAA,EACnG;AACF;;;AyCvKO,IAAMC,UAAS;AAAA,EACpB,MAAM;AAAA,EACN,UAAU;AAAA,EACV,QAA0B;AAAA,EAC1B,IAAmC;AAAA,EACnC,YAAuB,CAAC;AAAA,EACxB,WAAW;AAAA,IACT,OAAO;AAAA,IACP,WAAW;AAAA,IACX,oBAAoB;AAAA,IACpB,uBAAuB;AAAA,IACvB,OAAO;AAAA,IACP,SAAS;AAAA,IACT,8BAA8B;AAAA,IAC9B,gBAAgB;AAAA,EAClB;AACF;AAEA,SAAS,aAAmB;AAK1B,QAAM,KAAKA,QAAO;AAClB,MAAI,CAAC;AAAI;AACT,EAAAA,QAAO,aAAa,GAAG,uBAAuB;AAEhD;AAOA,eAAsB,SAAS,UAAgC;AA5C/D;AA8CE,MAAI,SAAS,OAAO,YAAY;AAAW;AAC3C,MAAKA,QAAO,QAAW,OAAO,EAAE,aAAc,CAACA,QAAO,MAAM,CAACA,QAAO,GAAG,aAAaA,QAAO,GAAG,OAAO,IAAI;AACvG,QAAI,wCAAwC;AAC5C,IAAO,MAAM,QAAQ;AAAA,EAMvB;AACA,MAAI,CAAI,YAAYA,QAAO,IAAI,GAAG;AAChC,QAAI;AACF,MAAAA,QAAO,SAAS,MAAY,OAAO,KAAK,GAAG;AAAA,IAC7C,SAAS,KAAP;AACA,UAAI,gCAAgC,GAAG;AACvC;AAAA,IACF;AACA,QAAI;AACF,MAAAA,QAAO,MAAK,KAAAA,QAAO,WAAP,mBAAe,WAAW,UAAUA,QAAO;AACvD,YAAM,OAAOA,QAAO,GAAG,aAAaA,QAAO,GAAG,OAAO,EAAE,SAAS,KAAK;AACrE,UAAI,CAAC,MAAM;AACT,YAAI,qEAAqE;AACzE,iBAAS,OAAO,UAAU;AAC1B;AAAA,MACF;AACA,UAAIA,QAAO,QAAQ;AACjB,QAAAA,QAAO,OAAO,iBAAiB,oBAAoB,OAAOC,OAAM;AAC9D,cAAI,mBAAmBA,GAAE,IAAI;AAC7B,cAAI,0FAA0F;AAC9F,mBAAS,KAAK,OAAO;AACrB,gBAAM,IAAI,MAAM,mCAAmC;AAAA,QAMrD,CAAC;AACD,QAAAD,QAAO,OAAO,iBAAiB,wBAAwB,CAACC,OAAM;AAC5D,cAAI,oCAAoCA,EAAC;AAAA,QAC3C,CAAC;AACD,QAAAD,QAAO,OAAO,iBAAiB,6BAA6B,CAACC,OAAM;AACjE,cAAI,kCAAkCA,EAAC;AAAA,QACzC,CAAC;AAAA,MACH;AAAA,IACF,SAAS,KAAP;AACA,UAAI,oCAAoC,GAAG;AAC3C;AAAA,IACF;AACA,QAAI;AACF,MAAG,gBAAgB,GAAGD,QAAO,EAAE;AAAA,IACjC,SAAS,KAAP;AACA,UAAI,oCAAoC,GAAG;AAC3C;AAAA,IACF;AACA,QAAI;AACF,YAAM,MAAM,IAAO,aAAaA,QAAO,EAAE;AACzC,MAAG,gBAAgBA,QAAO,MAAM,MAAM,IAAO,iBAAiB,GAAG,GAAGA,QAAO,QAAQ;AAAA,IACrF,SAAS,KAAP;AACA,UAAI,yCAAyC,GAAG;AAChD;AAAA,IACF;AACA,QAAI;AACF,YAAM,UAAa,qBAAqB,OAAO;AAC/C,cAAQ,QAAQ,CAAC,iBAAiB;AAChC,cAAM,kBAAkB,EAAE,GAAG,cAAc,aAAaA,QAAO,KAAK;AACpE,QAAG,eAAe,eAAe;AAAA,MACnC,CAAC;AAAA,IACH,SAAS,KAAP;AACA,UAAI,oDAAoD,GAAG;AAC3D;AAAA,IACF;AACA,UAAM,UAAa,QAAQ,EAAE,kBAAqB,QAAQ,EAAE,gBAAgB,EAAE,KAAK;AACnF,QAAI,SAAS;AACX,UAAI,yBAAyB,QAAQ,aAAa,QAAQ,OAAO,cAAc,QAAQ,aAAa,QAAQ,QAAQ,GAAG;AAAA,IACzH,OAAO;AACL,UAAI,iCAAiC,SAASA,QAAO,EAAE;AACvD;AAAA,IACF;AACA,QAAI;AACF,MAAG,IAAI,IAAI,iBAAiB,CAAC;AAAA,IAC/B,SAAS,KAAP;AACA,UAAI,0CAA0C,GAAG;AACjD;AAAA,IACF;AACA,eAAW;AACX,QAAI,uBAAuBA,QAAO,IAAI;AAAA,EACxC;AACF;;;AC5HA,SAAS,oBAAoB;AAC3B,MAAI,CAACE,KAAI,QAAQ,SAAS,KAAK,GAAG;AAChC,UAAM,YAAY;AAAA,MAChB,YAAY;AAAA,MACZ,aAAgB,WAAW;AAAA,MAC3B,YAAY,CAACC,QAAU,KAAK,MAAS,IAAIA,IAAG,OAAO,GAAM,IAAO,IAAIA,IAAG,OAAO,GAAGA,IAAG,OAAO,CAAC,GAAGA,IAAG,OAAO,CAAC,CAAC,CAAC;AAAA,IAC9G;AACA,IAAG,eAAe,SAAS;AAC3B,IAAAD,KAAI,QAAQ,KAAK,KAAK;AAAA,EACxB;AACA,MAAI,CAACA,KAAI,QAAQ,SAAS,UAAU,GAAG;AACrC,UAAM,YAAY;AAAA,MAChB,YAAY;AAAA,MACZ,aAAgB,WAAW;AAAA,MAC3B,YAAY,CAACC,QAAU,KAAK,MAAS,SAASA,IAAG,OAAO,IAAIA,IAAG,OAAO,CAAC,IAAIA,IAAG,OAAO,IAAO,IAAIA,IAAG,OAAO,GAAGA,IAAG,OAAO,CAAC,CAAC;AAAA,IAC3H;AACA,IAAG,eAAe,SAAS;AAC3B,IAAAD,KAAI,QAAQ,KAAK,UAAU;AAAA,EAC7B;AACF;AAEA,eAAsB,MAAM,UAAiB,QAAQ,OAAO;AAC1D,WAAS,QAAQ;AACjB,MAAI,SAASA,KAAI,WAAY,SAAS,OAAO,WAAY,SAAS,OAAO,QAAQ,SAAS,KAAU,WAAW,MAAM,SAAS,OAAO,SAAW;AAC9I,UAAM,YAAY,IAAI;AAEtB,QAAI,SAAS,OAAO,WAAW,SAAS,OAAO,QAAQ,SAAS,GAAG;AAGjE,UAAI,OAAO,WAAW,eAAe,OAAO,sBAAsB,eAAe,SAAS,OAAO,OAAO;AACtG,YAAI,SAAS,OAAO;AAAO,cAAI,2BAA2B;AAAA,MAC5D;AAGA,UAAIA,KAAI,WAAW,SAAS,OAAO,YAAY,cAAc;AAC3D,YAAI,SAAS,OAAO;AAAO,cAAI,8DAA8D;AAC7F,iBAAS,OAAO,UAAU;AAAA,MAC5B;AACA,UAAIA,KAAI,SAAS,SAAS,OAAO,YAAY,WAAW,SAAS,OAAO,YAAY,YAAY;AAC9F,YAAI,SAAS,OAAO;AAAO,cAAI,4BAA4B,SAAS,OAAO,iCAAiC;AAC5G,iBAAS,OAAO,UAAU;AAAA,MAC5B;AAGA,UAAIA,KAAI,WAAW,SAAS,OAAO,YAAY,UAAU;AACvD,YAAI,OAAO,cAAc,eAAe,OAAO,UAAU,WAAW,aAAa;AAC/E,cAAI,qEAAqE;AACzE,mBAAS,OAAO,UAAU;AAAA,QAC5B,OAAO;AACL,gBAAM,UAAU,MAAM,UAAU,OAAO,eAAe;AACtD,cAAI,SAAS,OAAO;AAAO,gBAAI,8BAA8B,OAAO;AACpE,cAAI,CAAC,SAAS;AACZ,gBAAI,sEAAsE;AAC1E,qBAAS,OAAO,UAAU;AAAA,UAC5B,OAAO;AAGL,kBAAM,cAAc,wBAAwB,UAAU,MAAO,QAAuB,mBAAmB,IAAI;AAE3G,gBAAI,wBAAwB,WAAW;AAAA,UACzC;AAAA,QACF;AAAA,MACF;AAGA,UAAI,SAAS,OAAO,YAAY;AAAW,cAAc,SAAS,QAAQ;AAC1E,YAAM,YAAY,OAAO,KAAQ,OAAO,EAAE,eAAe;AACzD,UAAI,SAAS,OAAO;AAAO,YAAI,uBAAuB,SAAS;AAE/D,UAAI,CAAC,UAAU,SAAS,SAAS,OAAO,OAAO,GAAG;AAChD,YAAI,kBAAkB,SAAS,OAAO,+BAA+B;AACrE,iBAAS,OAAO,UAAUA,KAAI,OAAO,eAAe;AACpD,YAAI,SAAS,OAAO;AAAO,cAAI,6BAA6B,SAAS,OAAO,SAAS;AAAA,MACvF;AAEA,UAAI,SAAS,OAAO;AAAO,YAAI,oBAAoB,SAAS,OAAO,OAAO;AAG1E,UAAI,SAAS,OAAO,YAAY,QAAQ;AACtC,YAAI;AACF,UAAG,IAAI,EAAE,IAAI,iCAAiC,IAAI;AAAA,QACpD,SAAQE,IAAN;AAAA,QAAa;AACf,YAAI,SAAS,OAAO;AAAO,cAAI,cAAc,SAAS,OAAO,QAAQ;AACrE,YAAI,QAAO,qDAAI,kBAAiB;AAAa,gBAAS,aAAa,SAAS,OAAO,UAAU,SAAS,OAAO,iBAAiB;AAAA;AACzH,gBAAM,IAAI,MAAM,wEAAwE;AAC7F,cAAM,OAAO,MAAS,IAAI,EAAE,SAAS,uBAAuB;AAC5D,cAAM,KAAK,MAAS,IAAI,EAAE,SAAS,8BAA8B;AACjE,YAAI,SAAS,OAAO;AAAO,cAAI,mBAAmB,OAAO,SAAS,aAAa,KAAK,kBAAkB,kBAAkB;AACxH,YAAI,SAAS,OAAO,SAAS,CAAC;AAAM,cAAI,2CAA2C;AAAA,MACrF;AAEA,UAAI;AACF,cAAS,WAAW,SAAS,OAAO,OAAO;AAC3C,cAAS,MAAM;AACf,QAAUC,MAAK;AAAA,MACjB,SAAS,KAAP;AACA,YAAI,8BAA8B,SAAS,OAAO,SAAS,GAAG;AAC9D,eAAO;AAAA,MACT;AAAA,IACF;AAGA,QAAO,WAAW,MAAM,WAAW;AACjC,MAAG,IAAI,IAAI,gCAAgC,KAAK;AAChD,MAAG,IAAI,IAAI,qBAAqB,IAAI;AAEpC,MAAG,IAAI,IAAI,6BAA6B,IAAI;AAC5C,MAAG,IAAI,IAAI,8BAA8B,GAAG;AAE5C,UAAI,OAAO,SAAS,OAAO,kBAAkB,eAAe,SAAS,OAAO,eAAe;AACzF,YAAI,mDAAmD,IAAI;AAC3D,QAAG,IAAI,IAAI,kCAAkC,CAAC;AAAA,MAChD;AACA,UAAO,QAAQ,EAAE,iBAAiB;AAChC,cAAM,KAAK,MAAS,QAAQ,EAAE,gBAAgB,EAAE;AAChD,YAAI,SAAS,OAAO;AAAO,cAAI,cAAc,GAAG,aAAa,GAAG,OAAO,cAAc,GAAG,aAAa,GAAG,QAAQ,GAAG;AAAA,MACrH;AAAA,IACF;AAGA,QAAO,WAAW,MAAM,UAAU;AAAA,IAIlC;AAGA,IAAG,eAAe;AAClB,UAAS,MAAM;AAEf,aAAS,YAAY,cAAc,KAAK,MAAM,IAAI,IAAI,SAAS;AAC/D,aAAS,OAAO,UAAa,WAAW;AAExC,UAAMH,KAAI,cAAc;AACxB,sBAAkB;AAAA,EAEpB;AACA,SAAO;AACT;AAGO,SAAS,QAAQ,aAA4BI,SAAQ;AAE1D,aAAW,cAAc,aAAa;AACpC,UAAM,eAAe;AAAA,MACnB;AAAA,MACA,aAAaA,QAAO;AAAA,MACpB,YAAY,MAAM;AAAE,YAAIA,QAAO;AAAO,cAAI,cAAc,YAAYA,QAAO,OAAO;AAAA,MAAG;AAAA,IAGvF;AACA,IAAG,eAAe,YAAY;AAAA,EAChC;AACA,EAAAJ,KAAI,UAAa,qBAAwB,WAAW,CAAC,EAAE,IAAI,CAAC,WAAW,OAAO,WAAW,YAAY,CAAC;AACxG;;;ACnKA;AAAA;AAAA,aAAAK;AAAA,EAAA;AAAA,gBAAAC;AAAA,EAAA;AAAA;AAAA;AAAA;AAAA,iBAAAC;AAAA,EAAA;AAAA;;;ACKO,IAAM,mBAAmB,CAACC,WAAqB;AACpD,MAAI,CAACA;AAAO,QAAI,4BAA4B;AAAA,WACnC,CAACA,OAAM;AAAY,QAAI,wCAAwC;AAAA,OACnE;AACH,UAAM,MAAMA,OAAM,WAAW,IAAI;AACjC,QAAI,CAAC;AAAK,UAAI,uCAAuC;AAAA;AAChD,aAAO;AAAA,EACd;AACA,SAAO;AACT;AAEO,IAAM,UAAU,CAAC,UAAkB,KAAK,MAAO,QAAQ,MAAO,KAAK,EAAE;AAErE,IAAM,aAAa,CAAC,GAAuBC,SAA6B;AAC7E,MAAI,CAACA,KAAI,YAAY,OAAO,MAAM;AAAa,WAAOA,KAAI;AAC1D,QAAMC,OAAM,kBAAkB,KAAK,CAAC,MAAO,IAAI,GAAI,MAAO,IAAI,GAAI,GAAG,CAAC;AACtE,QAAM,QAAQ,QAAQA,KAAI,OAAOA,KAAI,OAAOA,KAAI,OAAOD,KAAI;AAC3D,SAAO;AACT;AAEO,SAAS,MAAM,KAAmE,GAAW,GAAW,GAAuB,cAA2B;AAC/J,MAAI,YAAY,WAAW,GAAG,YAAY;AAC1C,MAAI,UAAU;AACd,MAAI,IAAI,GAAG,GAAG,aAAa,WAAW,GAAG,IAAI,KAAK,EAAE;AACpD,MAAI,KAAK;AACX;AAEO,SAAS,KAAK,KAAmE,GAAW,GAAW,OAAe,QAAgB,cAA2B;AACtK,MAAI,UAAU;AACd,MAAI,YAAY,aAAa;AAC7B,MAAI,aAAa,WAAW;AAC1B,UAAM,MAAM,IAAI,IAAI,SAAS;AAC7B,UAAM,MAAM,IAAI,IAAI,UAAU;AAC9B,QAAI,QAAQ,IAAI,IAAI,QAAQ,GAAG,SAAS,GAAG,GAAG,GAAG,IAAI,KAAK,EAAE;AAAA,EAC9D,OAAO;AACL,QAAI,OAAO,IAAI,aAAa,WAAW,CAAC;AACxC,QAAI,OAAO,IAAI,QAAQ,aAAa,WAAW,CAAC;AAChD,QAAI,iBAAiB,IAAI,OAAO,GAAG,IAAI,OAAO,IAAI,aAAa,SAAS;AACxE,QAAI,OAAO,IAAI,OAAO,IAAI,SAAS,aAAa,SAAS;AACzD,QAAI,iBAAiB,IAAI,OAAO,IAAI,QAAQ,IAAI,QAAQ,aAAa,WAAW,IAAI,MAAM;AAC1F,QAAI,OAAO,IAAI,aAAa,WAAW,IAAI,MAAM;AACjD,QAAI,iBAAiB,GAAG,IAAI,QAAQ,GAAG,IAAI,SAAS,aAAa,SAAS;AAC1E,QAAI,OAAO,GAAG,IAAI,aAAa,SAAS;AACxC,QAAI,iBAAiB,GAAG,GAAG,IAAI,aAAa,WAAW,CAAC;AACxD,QAAI,UAAU;AAAA,EAChB;AACA,MAAI,OAAO;AACb;AAEO,SAAS,MAAM,KAAmE,QAAiB,cAA2B;AACnI,MAAI,OAAO,SAAS;AAAG;AACvB,MAAI,UAAU;AACd,MAAI,OAAO,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE;AACrC,aAAW,MAAM,QAAQ;AACvB,QAAI,cAAc,WAAW,GAAG,MAAM,GAAG,YAAY;AACrD,QAAI,OAAO,KAAK,MAAM,GAAG,EAAE,GAAG,KAAK,MAAM,GAAG,EAAE,CAAC;AAAA,EACjD;AACA,MAAI,OAAO;AACX,MAAI,aAAa,cAAc;AAC7B,QAAI,UAAU;AACd,QAAI,KAAK;AAAA,EACX;AACF;AAEO,SAAS,OAAO,KAAmE,QAAiB,cAA2B;AACpI,MAAI,OAAO,SAAS;AAAG;AACvB,MAAI,YAAY,aAAa;AAC7B,MAAI,CAAC,aAAa,aAAa,OAAO,UAAU,GAAG;AACjD,UAAM,KAAK,QAAQ,YAAY;AAC/B;AAAA,EACF;AACA,MAAI,OAAO,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE;AACrC,WAASE,KAAI,GAAGA,KAAI,OAAO,SAAS,GAAGA,MAAK;AAC1C,UAAM,MAAM,OAAOA,IAAG,KAAK,OAAOA,KAAI,GAAG,MAAM;AAC/C,UAAM,MAAM,OAAOA,IAAG,KAAK,OAAOA,KAAI,GAAG,MAAM;AAC/C,QAAI,iBAAiB,OAAOA,IAAG,IAAI,OAAOA,IAAG,IAAI,IAAI,EAAE;AAAA,EACzD;AACA,MAAI,iBAAiB,OAAO,OAAO,SAAS,GAAG,IAAI,OAAO,OAAO,SAAS,GAAG,IAAI,OAAO,OAAO,SAAS,GAAG,IAAI,OAAO,OAAO,SAAS,GAAG,EAAE;AAC3I,MAAI,OAAO;AACX,MAAI,aAAa,cAAc;AAC7B,QAAI,UAAU;AACd,QAAI,KAAK;AAAA,EACX;AACF;AAEO,SAAS,MAAM,KAAmE,MAAa,IAAW,SAAS,GAAG;AAC3H,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI,UAAU;AACd,MAAI,OAAO,KAAK,IAAI,KAAK,EAAE;AAC3B,MAAI,OAAO,GAAG,IAAI,GAAG,EAAE;AACvB,UAAQ,KAAK,MAAM,GAAG,KAAK,KAAK,IAAI,GAAG,KAAK,KAAK,EAAE;AACnD,MAAI,SAAS,KAAK,IAAI,KAAK,IAAI,GAAG;AAClC,MAAI,SAAS,KAAK,IAAI,KAAK,IAAI,GAAG;AAClC,MAAI,OAAO,GAAG,CAAC;AACf,WAAU,IAAM,KAAQ,IAAI,KAAK;AACjC,MAAI,SAAS,KAAK,IAAI,KAAK,IAAI,GAAG;AAClC,MAAI,SAAS,KAAK,IAAI,KAAK,IAAI,GAAG;AAClC,MAAI,OAAO,GAAG,CAAC;AACf,WAAU,IAAM,KAAQ,IAAI,KAAK;AACjC,MAAI,SAAS,KAAK,IAAI,KAAK,IAAI,GAAG;AAClC,MAAI,SAAS,KAAK,IAAI,KAAK,IAAI,GAAG;AAClC,MAAI,OAAO,GAAG,CAAC;AACf,MAAI,UAAU;AACd,MAAI,OAAO;AACX,MAAI,KAAK;AACX;;;ACnEO,IAAMC,WAAuB;AAAA,EAClC,OAAe;AAAA,EACf,YAAoB;AAAA,EACpB,aAAqB;AAAA,EACrB,OAAO;AAAA,EACP,MAAc;AAAA,EACd,YAAoB;AAAA,EACpB,WAAmB;AAAA,EACnB,WAAmB;AAAA,EACnB,WAAmB;AAAA,EACnB,YAAqB;AAAA,EACrB,YAAqB;AAAA,EACrB,WAAoB;AAAA,EACpB,eAAwB;AAAA,EACxB,cAAuB;AAAA,EACvB,cAAuB;AAAA,EACvB,UAAmB;AAAA,EACnB,cAAuB;AAAA,EACvB,UAAmB;AAAA,EACnB,WAAoB;AACtB;;;ACzDA,IAAI;AAEJ,SAAS,WAAW,GAAe,KAAmE;AACpG,MAAI,IAAI,YAAY;AAElB,UAAMC,UAAkB,CAAC;AACzB,IAAAA,QAAO,KAAK,SAAS,KAAK,MAAM,MAAM,EAAE,KAAK,IAAI;AACjD,QAAI,EAAE;AAAa,MAAAA,QAAO,KAAK,GAAG,EAAE,UAAU,MAAM,KAAK,MAAM,MAAM,EAAE,WAAW,IAAI;AACtF,QAAI,EAAE;AAAK,MAAAA,QAAO,KAAK,QAAQ,EAAE,OAAO,IAAI;AAC5C,QAAI,EAAE;AAAM,MAAAA,QAAO,KAAK,aAAa,EAAE,MAAM;AAC7C,QAAI,EAAE;AAAM,MAAAA,QAAO,KAAK,SAAS,KAAK,MAAM,MAAM,EAAE,IAAI,IAAI;AAC5D,QAAI,EAAE;AAAM,MAAAA,QAAO,KAAK,SAAS,KAAK,MAAM,MAAM,EAAE,IAAI,IAAI;AAC5D,QAAI,EAAE,WAAW,EAAE,QAAQ,SAAS,GAAG;AACrC,YAAMC,WAAU,EAAE,QAAQ,IAAI,CAAC,MAAM,GAAG,KAAK,MAAM,MAAM,EAAE,KAAK,MAAM,EAAE,SAAS;AACjF,UAAIA,SAAQ,SAAS;AAAG,QAAAA,SAAQ,SAAS;AACzC,MAAAD,QAAO,KAAKC,SAAQ,KAAK,GAAG,CAAC;AAAA,IAC/B;AACA,QAAI,EAAE,YAAY,EAAE,SAAS,SAAS,EAAE,SAAS,MAAM;AACrD,UAAI,EAAE,SAAS,MAAM;AAAM,QAAAD,QAAO,KAAK,SAAS,QAAQ,EAAE,SAAS,MAAM,IAAI,aAAU,QAAQ,EAAE,SAAS,MAAM,GAAG,eAAY,QAAQ,EAAE,SAAS,MAAM,KAAK,OAAI;AACjK,UAAI,EAAE,SAAS,KAAK;AAAS,QAAAA,QAAO,KAAK,SAAS,QAAQ,EAAE,SAAS,KAAK,OAAO,OAAI;AAAA,IACvF;AACA,QAAIA,QAAO,WAAW;AAAG,MAAAA,QAAO,KAAK,MAAM;AAC3C,QAAI,YAAY,IAAI;AACpB,aAASE,KAAIF,QAAO,SAAS,GAAGE,MAAK,GAAGA,MAAK;AAC3C,YAAM,IAAI,KAAK,IAAI,EAAE,IAAI,IAAI,CAAC;AAC9B,YAAM,IAAIA,KAAI,IAAI,aAAa,EAAE,IAAI;AACrC,UAAI,IAAI,eAAe,IAAI,gBAAgB,IAAI;AAC7C,YAAI,YAAY,IAAI;AACpB,YAAI,SAASF,QAAOE,KAAI,IAAI,GAAG,IAAI,EAAE;AAAA,MACvC;AACA,UAAI,YAAY,IAAI;AACpB,UAAI,SAASF,QAAOE,KAAI,IAAI,GAAG,IAAI,EAAE;AAAA,IACvC;AAAA,EACF;AACF;AAEA,SAAS,eAAe,GAAe,KAAmE;AAExG,MAAI,EAAE,eAAe,EAAE,YAAY,kBAAkB,EAAE,YAAY,eAAe,IAAI;AACpF,QAAI,cAAc,IAAI,WAAW,6BAA6B,IAAI;AAClE,QAAI,UAAU;AACd,UAAM,QAAQ,KAAK,IAAI,EAAE,YAAY,eAAe,GAAG,KAAK,EAAE,YAAY,eAAe,GAAG,EAAE,IAAI;AAClG,UAAM,QAAQ,KAAK,IAAI,EAAE,YAAY,eAAe,GAAG,KAAK,EAAE,YAAY,eAAe,GAAG,EAAE,IAAI;AAClG,QAAI,QAAQ,EAAE,YAAY,eAAe,GAAG,IAAI,EAAE,YAAY,eAAe,GAAG,IAAI,OAAO,OAAO,GAAG,GAAG,IAAI,KAAK,EAAE;AACnH,QAAI,OAAO;AACX,QAAI,IAAI,cAAc;AACpB,UAAI,YAAY,IAAI,WAAW,6BAA6B,IAAI;AAChE,UAAI,KAAK;AAAA,IACX;AAAA,EACF;AACA,MAAI,EAAE,eAAe,EAAE,YAAY,mBAAmB,EAAE,YAAY,gBAAgB,IAAI;AACtF,QAAI,cAAc,IAAI,WAAW,6BAA6B,IAAI;AAClE,QAAI,UAAU;AACd,UAAM,QAAQ,KAAK,IAAI,EAAE,YAAY,gBAAgB,GAAG,KAAK,EAAE,YAAY,gBAAgB,GAAG,EAAE,IAAI;AACpG,UAAM,QAAQ,KAAK,IAAI,EAAE,YAAY,gBAAgB,GAAG,KAAK,EAAE,YAAY,gBAAgB,GAAG,EAAE,IAAI;AACpG,QAAI,QAAQ,EAAE,YAAY,gBAAgB,GAAG,IAAI,EAAE,YAAY,gBAAgB,GAAG,IAAI,OAAO,OAAO,GAAG,GAAG,IAAI,KAAK,EAAE;AACrH,QAAI,OAAO;AACX,QAAI,IAAI,cAAc;AACpB,UAAI,YAAY,IAAI,WAAW,6BAA6B,IAAI;AAChE,UAAI,KAAK;AAAA,IACX;AAAA,EACF;AACF;AAEA,SAAS,gBAAgB,GAAe,KAAmE;AAxE3G;AAyEE,MAAI,IAAI,cAAY,OAAE,aAAF,mBAAY,UAAS,OAAO,WAAW,aAAa;AACtE,QAAI,cAAc;AAClB,UAAM,OAAQ,EAAE,IAAI,KAAK,EAAE,IAAI,KAAK,IAAM,EAAE,IAAI,KAAK,QAAQ,EAAE,SAAS,MAAM,GAAG,IAAI;AACrF,UAAM,OAAQ,EAAE,IAAI,KAAK,EAAE,IAAI,KAAK,IAAM,EAAE,IAAI,KAAK,QAAQ,EAAE,SAAS,MAAM,KAAK,IAAI;AACvF,UAAM,QAAQ,IAAI,OAAO;AAAA,UACnB,EAAE,IAAI,KAAK,EAAE,IAAI,KAAK,KAAK,EAAE,IAAI;AAAA;AAAA,UAEjC,QAAQ,EAAE,IAAI;AAAA,UACd,QAAQ,EAAE,IAAI,KAAK,EAAE,IAAI;AAAA,UACzB,EAAE,IAAI,KAAK,EAAE,IAAI,KAAK,KAAK,EAAE,IAAI,KAAK,EAAE,IAAI;AAAA,KACjD;AACD,UAAM,QAAQ,IAAI,OAAO;AAAA,UACnB,EAAE,IAAI,MAAM,EAAE,IAAI,KAAK,EAAE,IAAI,KAAK;AAAA;AAAA,UAElC,EAAE,IAAI,MAAM;AAAA,UACZ,EAAE,IAAI,KAAK,EAAE,IAAI,MAAM;AAAA,UACvB,EAAE,IAAI,KAAK,EAAE,IAAI,MAAM,EAAE,IAAI,KAAK,EAAE,IAAI,KAAK;AAAA,KAClD;AACD,QAAI,OAAO,KAAK;AAChB,QAAI,OAAO,KAAK;AAAA,EAClB;AACF;AAEA,SAAS,eAAe,GAAe,KAAmE;AAhG1G;AAiGE,MAAI,IAAI,cAAY,aAAE,aAAF,mBAAY,SAAZ,mBAAkB,eAAY,aAAE,aAAF,mBAAY,SAAZ,mBAAkB,YAAW,EAAE,YAAY,kBAAkB,EAAE,YAAY,mBAAmB,EAAE,YAAY,eAAe,MAAM,EAAE,YAAY,gBAAgB,IAAI;AACnN,QAAI,cAAc;AAClB,QAAI,YAAY;AAChB,UAAM,WAAW;AAAA,MACf,EAAE,YAAY,eAAe,GAAG,KAAM,KAAK,IAAI,EAAE,SAAS,KAAK,OAAO,IAAI,EAAE,SAAS,KAAK,WAAW,EAAE,IAAI;AAAA,MAC3G,EAAE,YAAY,eAAe,GAAG,KAAM,KAAK,IAAI,EAAE,SAAS,KAAK,OAAO,IAAI,EAAE,SAAS,KAAK,WAAW,EAAE,IAAI;AAAA,IAC7G;AACA,UAAM,KAAK,CAAC,EAAE,YAAY,eAAe,GAAG,IAAI,EAAE,YAAY,eAAe,GAAG,EAAE,GAAG,CAAC,SAAS,IAAI,SAAS,EAAE,GAAG,CAAC;AAClH,UAAM,YAAY;AAAA,MAChB,EAAE,YAAY,gBAAgB,GAAG,KAAM,KAAK,IAAI,EAAE,SAAS,KAAK,OAAO,IAAI,EAAE,SAAS,KAAK,WAAW,EAAE,IAAI;AAAA,MAC5G,EAAE,YAAY,gBAAgB,GAAG,KAAM,KAAK,IAAI,EAAE,SAAS,KAAK,OAAO,IAAI,EAAE,SAAS,KAAK,WAAW,EAAE,IAAI;AAAA,IAC9G;AACA,UAAM,KAAK,CAAC,EAAE,YAAY,gBAAgB,GAAG,IAAI,EAAE,YAAY,gBAAgB,GAAG,EAAE,GAAG,CAAC,UAAU,IAAI,UAAU,EAAE,GAAG,CAAC;AAAA,EACxH;AACF;AAEA,SAAS,iBAAiB,GAAe,KAAmE;AAC1G,MAAI,IAAI,gBAAgB,EAAE,KAAK,UAAU,KAAK;AAC5C,QAAI,YAAY;AAChB,aAASA,KAAI,GAAGA,KAAI,OAAc,SAAS,GAAGA,MAAK;AACjD,YAAM,SAAS,CAAC,OAAcA,KAAI,IAAI,IAAI,OAAcA,KAAI,IAAI,IAAI,OAAcA,KAAI,IAAI,EAAE,EAAE,IAAI,CAACC,WAAU,EAAE,KAAKA,OAAM;AAC1H,YAAM,KAAK,QAAQ,GAAG;AAAA,IACxB;AACA,mBAAe,GAAG,GAAG;AAAA,EACvB;AAQF;AAEA,SAAS,eAAe,GAAe,KAAmE;AACxG,MAAI,IAAI,cAAc,EAAE,KAAK,UAAU,KAAK;AAC1C,aAASD,KAAI,GAAGA,KAAI,EAAE,KAAK,QAAQA,MAAK;AACtC,YAAM,KAAK,EAAE,KAAKA,IAAG,IAAI,EAAE,KAAKA,IAAG,IAAI,EAAE,KAAKA,IAAG,IAAI,GAAG;AACxD,UAAI,IAAI,eAAe;AACrB,YAAsB,iCAAiC,SAASA,EAAC;AAAG,gBAAM,KAAK,EAAE,KAAKA,IAAG,IAAI,EAAE,KAAKA,IAAG,IAAK,EAAE,KAAKA,IAAG,KAAgB,KAAK,GAAG;AAC9I,YAAsB,qCAAqC,SAASA,EAAC;AAAG,gBAAM,KAAK,EAAE,KAAKA,IAAG,IAAI,EAAE,KAAKA,IAAG,IAAK,EAAE,KAAKA,IAAG,KAAgB,KAAK,GAAG;AAClJ,YAAsB,sCAAsC,SAASA,EAAC;AAAG,gBAAM,KAAK,EAAE,KAAKA,IAAG,IAAI,EAAE,KAAKA,IAAG,IAAK,EAAE,KAAKA,IAAG,KAAgB,KAAK,GAAG;AAAA,MACrJ;AAAA,IACF;AAAA,EACF;AACF;AAEA,SAAS,cAAc,GAAe,KAAK;AACzC,MAAI,IAAI,WAAW;AACjB,SAAK,KAAK,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,GAAG;AAAA,EACvD;AACF;AAGA,eAAsB,KAAKE,WAAqB,QAA2B,aAAoC;AAC7G,QAAM,UAAUC,UAAS,WAAW;AACpC,MAAI,CAAC,UAAU,CAACD;AAAU;AAC1B,QAAM,MAAM,iBAAiBA,SAAQ;AACrC,MAAI,CAAC;AAAK;AACV,MAAI,OAAO,IAAI;AACf,MAAI,cAAc,IAAI;AACtB,MAAI,YAAY,IAAI;AACpB,aAAW,KAAK,QAAQ;AACtB,kBAAc,GAAG,GAAG;AACpB,eAAW,GAAG,GAAG;AACjB,QAAI,EAAE,QAAQ,EAAE,KAAK,SAAS,GAAG;AAC/B,qBAAe,GAAG,GAAG;AACrB,uBAAiB,GAAG,GAAG;AACvB,sBAAgB,GAAG,GAAG;AACtB,qBAAe,GAAG,GAAG;AAAA,IACvB;AAAA,EACF;AACF;;;AClKA,eAAsB,KAAKE,WAAqB,QAA2B,aAAoC;AAP/G;AAQE,QAAM,eAAe,UAAUC,UAAS,WAAW;AACnD,MAAI,CAAC,UAAU,CAACD;AAAU;AAC1B,QAAM,MAAM,iBAAiBA,SAAQ;AACrC,MAAI,CAAC;AAAK;AACV,MAAI,WAAW;AACf,WAASE,KAAI,GAAGA,KAAI,OAAO,QAAQA,MAAK;AACtC,QAAI,cAAc,aAAa;AAC/B,QAAI,YAAY,aAAa;AAC7B,QAAI,YAAY,aAAa;AAC7B,QAAI,OAAO,aAAa;AACxB,QAAI,aAAa,aAAa,OAAOA,IAAG,SAAO,YAAOA,IAAG,QAAV,mBAAe,YAAW,GAAG;AAC1E,WAAK,KAAK,OAAOA,IAAG,IAAI,IAAI,OAAOA,IAAG,IAAI,IAAI,OAAOA,IAAG,IAAI,IAAI,OAAOA,IAAG,IAAI,IAAI,YAAY;AAC9F,UAAI,aAAa,YAAY;AAC3B,YAAI,aAAa,eAAe,aAAa,gBAAgB,IAAI;AAC/D,cAAI,YAAY,aAAa;AAC7B,cAAI,SAAS,QAAQ,MAAM,OAAOA,IAAG,UAAU,OAAOA,IAAG,IAAI,KAAK,GAAG,IAAI,OAAOA,IAAG,IAAI,KAAK,aAAa,YAAY,OAAOA,IAAG,IAAI,EAAE;AAAA,QACvI;AACA,YAAI,YAAY,aAAa;AAC7B,YAAI,SAAS,QAAQ,MAAM,OAAOA,IAAG,UAAU,OAAOA,IAAG,IAAI,KAAK,GAAG,IAAI,OAAOA,IAAG,IAAI,KAAK,aAAa,YAAY,OAAOA,IAAG,IAAI,EAAE;AAAA,MACvI;AAAA,IACF;AACA,QAAI,aAAa,cAAc,OAAOA,IAAG,WAAW;AAClD,eAAS,KAAK,GAAG,KAAK,OAAOA,IAAG,UAAU,QAAQ,MAAM;AACtD,YAAI,CAAC,OAAOA,IAAG,UAAU,IAAI,SAAU,OAAOA,IAAG,UAAU,IAAI,UAAU;AAAI;AAC7E,YAAI,YAAY,WAAW,OAAOA,IAAG,UAAU,IAAI,SAAS,IAAI,YAAY;AAC5E,cAAM,KAAK,OAAOA,IAAG,UAAU,IAAI,SAAS,IAAI,OAAOA,IAAG,UAAU,IAAI,SAAS,IAAI,GAAG,YAAY;AAAA,MACtG;AAAA,IACF;AACA,QAAI,aAAa,cAAc,OAAOA,IAAG,WAAW;AAClD,UAAI,OAAO,aAAa;AACxB,iBAAW,MAAM,OAAOA,IAAG,WAAW;AACpC,YAAI,CAAC,GAAG,SAAU,GAAG,UAAU;AAAI;AACnC,YAAI,YAAY,WAAW,GAAG,SAAS,IAAI,YAAY;AACvD,YAAI,SAAS,GAAG,GAAG,QAAQ,KAAK,MAAM,MAAM,GAAG,KAAK,MAAM,GAAG,SAAS,KAAK,GAAG,GAAG,SAAS,KAAK,CAAC;AAAA,MAClG;AAAA,IACF;AACA,QAAI,aAAa,gBAAgB,OAAOA,IAAG,aAAa,OAAOA,IAAG,aAAa;AAC7E,iBAAW,QAAQ,OAAO,OAAO,OAAOA,IAAG,WAAW,GAAG;AACvD,mBAAWC,cAAa;AAAM,iBAAO,KAAKA,YAAW,YAAY;AAAA,MACnE;AAAA,IACF;AAAA,EACF;AACF;;;AC3CA,eAAsB,KAAKC,WAAqB,QAA2B,aAAoC;AAC7G,QAAM,eAAe,UAAUC,UAAS,WAAW;AACnD,MAAI,CAAC,UAAU,CAACD;AAAU;AAC1B,QAAM,MAAM,iBAAiBA,SAAQ;AACrC,MAAI,CAAC;AAAK;AACV,MAAI,WAAW;AACf,MAAI,OAAO,aAAa;AACxB,aAAW,KAAK,QAAQ;AACtB,QAAI,aAAa,WAAW;AAC1B,UAAI,cAAc,aAAa;AAC/B,UAAI,YAAY,aAAa;AAC7B,WAAK,KAAK,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,YAAY;AAC9D,UAAI,aAAa,YAAY;AAC3B,YAAI,aAAa,eAAe,aAAa,gBAAgB,IAAI;AAC/D,cAAI,YAAY,aAAa;AAC7B,cAAI,SAAS,QAAQ,KAAK,MAAM,MAAM,EAAE,KAAK,MAAM,EAAE,IAAI,KAAK,GAAG,IAAI,EAAE,IAAI,KAAK,aAAa,YAAY,EAAE,IAAI,EAAE;AAAA,QACnH;AACA,YAAI,YAAY,aAAa;AAC7B,YAAI,SAAS,QAAQ,KAAK,MAAM,MAAM,EAAE,KAAK,MAAM,EAAE,IAAI,KAAK,GAAG,IAAI,EAAE,IAAI,KAAK,aAAa,YAAY,EAAE,IAAI,EAAE;AAAA,MACnH;AACA,UAAI,OAAO;AAAA,IACb;AACA,QAAI,aAAa,YAAY;AAC3B,UAAI,EAAE,aAAa,EAAE,UAAU,SAAS,GAAG;AACzC,mBAAW,MAAM,EAAE,WAAW;AAC5B,cAAI,YAAY,WAAW,GAAG,IAAI,YAAY;AAC9C,gBAAM,KAAK,GAAG,IAAI,GAAG,IAAI,GAAG,YAAY;AAAA,QAC1C;AAAA,MACF;AAAA,IACF;AACA,QAAI,aAAa,cAAc,EAAE,aAAa;AAC5C,YAAM,eAAe,CAAC,MAAoB,UAAkB;AAC1D,YAAI,CAAC,QAAQ,KAAK,WAAW,KAAK,CAAC,KAAK;AAAI;AAC5C,cAAM,IAAI,KAAK,KAAK,SAAS,GAAG,MAAM;AACtC,YAAI,YAAY,WAAW,GAAG,YAAY;AAC1C,YAAI,SAAS,OAAO,KAAK,KAAK,SAAS,GAAG,KAAK,GAAG,KAAK,KAAK,SAAS,GAAG,KAAK,CAAC;AAAA,MAChF;AACA,UAAI,OAAO,aAAa;AACxB,mBAAa,EAAE,YAAY,UAAU,OAAO;AAC5C,mBAAa,EAAE,YAAY,WAAW,QAAQ;AAC9C,mBAAa,EAAE,YAAY,SAAS,MAAM;AAC1C,mBAAa,EAAE,YAAY,UAAU,OAAO;AAC5C,mBAAa,EAAE,YAAY,UAAU,OAAO;AAC5C,mBAAa,EAAE,YAAY,SAAS,MAAM;AAAA,IAC5C;AACA,QAAI,aAAa,gBAAgB,EAAE,aAAa;AAC9C,YAAM,cAAc,CAAC,SAAuB;AAC1C,YAAI,CAAC,QAAQ,KAAK,WAAW,KAAK,CAAC,KAAK;AAAI;AAC5C,iBAASE,KAAI,GAAGA,KAAI,KAAK,QAAQA,MAAK;AACpC,cAAI,UAAU;AACd,gBAAM,IAAI,KAAKA,IAAG,MAAM;AACxB,cAAI,cAAc,WAAWA,KAAI,GAAG,YAAY;AAChD,cAAI,OAAO,KAAKA,KAAI,IAAIA,KAAI,IAAI,GAAG,IAAI,KAAKA,KAAI,IAAIA,KAAI,IAAI,GAAG,EAAE;AACjE,cAAI,OAAO,KAAKA,IAAG,IAAI,KAAKA,IAAG,EAAE;AACjC,cAAI,OAAO;AAAA,QACb;AAAA,MACF;AACA,UAAI,YAAY,aAAa;AAC7B,kBAAY,EAAE,YAAY,QAAQ;AAClC,kBAAY,EAAE,YAAY,SAAS;AACnC,kBAAY,EAAE,YAAY,OAAO;AACjC,kBAAY,EAAE,YAAY,QAAQ;AAClC,kBAAY,EAAE,YAAY,QAAQ;AAAA,IAEpC;AAAA,EACF;AACF;;;AClEA,eAAsB,OAAOC,WAAqB,QAA6B,aAAoC;AACjH,QAAM,eAAe,UAAUC,UAAS,WAAW;AACnD,MAAI,CAAC,UAAU,CAACD;AAAU;AAC1B,QAAM,MAAM,iBAAiBA,SAAQ;AACrC,MAAI,CAAC;AAAK;AACV,MAAI,WAAW;AACf,MAAI,OAAO,aAAa;AACxB,aAAW,KAAK,QAAQ;AACtB,QAAI,aAAa,WAAW;AAC1B,UAAI,cAAc,aAAa;AAC/B,UAAI,YAAY,aAAa;AAC7B,WAAK,KAAK,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,YAAY;AAC9D,UAAI,aAAa,YAAY;AAC3B,cAAM,QAAQ,GAAG,EAAE,SAAS,KAAK,MAAM,MAAM,EAAE,KAAK;AACpD,YAAI,aAAa,eAAe,aAAa,gBAAgB,IAAI;AAC/D,cAAI,YAAY,aAAa;AAC7B,cAAI,SAAS,OAAO,EAAE,IAAI,KAAK,GAAG,IAAI,EAAE,IAAI,KAAK,aAAa,YAAY,EAAE,IAAI,EAAE;AAAA,QACpF;AACA,YAAI,YAAY,aAAa;AAC7B,YAAI,SAAS,OAAO,EAAE,IAAI,KAAK,GAAG,IAAI,EAAE,IAAI,KAAK,aAAa,YAAY,EAAE,IAAI,EAAE;AAAA,MACpF;AACA,UAAI,OAAO;AAAA,IACb;AAAA,EACF;AACF;;;ACxBA,eAAsB,QAAQE,WAAqB,QAA8B,aAAoC;AACnH,QAAM,eAAe,UAAUC,UAAS,WAAW;AACnD,MAAI,CAAC,UAAU,CAACD;AAAU;AAC1B,MAAI,aAAa,cAAc;AAC7B,UAAM,MAAM,iBAAiBA,SAAQ;AACrC,QAAI,CAAC;AAAK;AACV,QAAI,OAAO,aAAa;AACxB,QAAI,YAAY,aAAa;AAC7B,QAAIE,KAAI;AACR,aAAS,IAAI,GAAG,IAAI,OAAO,QAAQ,KAAK;AACtC,UAAIC,SAAmB,CAAC;AACxB,UAAI,OAAkB,CAAC;AACvB,OAACA,QAAO,IAAI,IAAI,OAAO,QAAQ,OAAO,EAAE;AACxC,UAAK,KAAK,SAAS,KAAQ,KAAK,GAAc,SAAS,GAAI;AACzD,cAAM,MAAMA,OAAM,KAAe,IAAI,IAAIA,OAAM,OAAO;AACtD,cAAM,QAAQ,GAAGA,OAAM,MAAM,QAAQ,KAAK;AAC1C,YAAI,aAAa,eAAe,aAAa,gBAAgB,IAAI;AAC/D,cAAI,YAAY,aAAa;AAC7B,cAAI,SAAS,OAAO,GAAG,IAAKD,KAAI,aAAa,UAAW;AAAA,QAC1D;AACA,YAAI,YAAY,aAAa;AAC7B,YAAI,SAAS,OAAO,GAAG,IAAKA,KAAI,aAAa,UAAW;AACxD,QAAAA,MAAK;AAAA,MACP;AAAA,IACF;AAAA,EACF;AACF;;;APjBA,IAAI,WAAW;AAUf,eAAsB,OAAOE,WAAqB,QAA6B,aAAoC;AACjH,QAAM,eAAe,UAAUC,UAAS,WAAW;AACnD,MAAI,CAAC,UAAU,CAACD;AAAU;AAC1B,QAAM,MAAM,iBAAiBA,SAAQ;AACrC,MAAI,CAAC;AAAK;AACV,MAAI,WAAW;AACf,MAAI,OAAO,aAAa;AAExB,WAASE,KAAI,GAAGA,KAAI,OAAO,QAAQA,MAAK;AACtC,QAAI,aAAa,WAAW;AAC1B,UAAI,cAAc,aAAa;AAC/B,UAAI,YAAY,aAAa;AAC7B,WAAK,KAAK,OAAOA,IAAG,IAAI,IAAI,OAAOA,IAAG,IAAI,IAAI,OAAOA,IAAG,IAAI,IAAI,OAAOA,IAAG,IAAI,IAAI,YAAY;AAC9F,UAAI,aAAa,YAAY;AAC3B,cAAM,QAAQ,WAAWA;AACzB,YAAI,aAAa,eAAe,aAAa,gBAAgB,IAAI;AAC/D,cAAI,YAAY,aAAa;AAC7B,cAAI,SAAS,OAAO,OAAOA,IAAG,IAAI,KAAK,GAAG,IAAI,OAAOA,IAAG,IAAI,KAAK,aAAa,YAAY,OAAOA,IAAG,IAAI,EAAE;AAAA,QAC5G;AACA,YAAI,YAAY,aAAa;AAC7B,YAAI,SAAS,OAAO,OAAOA,IAAG,IAAI,KAAK,GAAG,IAAI,OAAOA,IAAG,IAAI,KAAK,aAAa,YAAY,OAAOA,IAAG,IAAI,EAAE;AAAA,MAC5G;AACA,UAAI,OAAO;AAAA,IACb;AAAA,EACF;AACF;AAGA,eAAsBC,QAAOC,QAAwD,QAAmB;AACtG,MAAI,CAACA,UAAS,CAAC;AAAQ;AACvB,QAAM,MAAM,iBAAiB,MAAM;AACnC,MAAI,CAAC;AAAK;AACV,MAAI,UAAUA,QAAO,GAAG,CAAC;AAC3B;AAGA,eAAsBC,KAAIL,WAAqB,QAAgB,aAAoC;AACjG,MAAI,CAAC,UAAU,CAAC,OAAO,eAAe,CAAC,UAAU,CAACA;AAAU,WAAO;AACnE,QAAM,YAAY,IAAI;AACtB,QAAM,eAAe,UAAUC,UAAS,WAAW;AACnD,QAAM,UAAU,QAAQ,IAAI;AAAA,IAC1B,KAAKD,WAAU,OAAO,MAAM,YAAY;AAAA,IACxC,KAAKA,WAAU,OAAO,MAAM,YAAY;AAAA,IACxC,KAAKA,WAAU,OAAO,MAAM,YAAY;AAAA,IACxC,OAAOA,WAAU,OAAO,QAAQ,YAAY;AAAA,IAC5C,QAAQA,WAAU,OAAO,SAAS,YAAY;AAAA,EAEhD,CAAC;AACD,aAAWM,KAAI,UAAU,WAAW,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAChG,SAAO,YAAY,OAAO;AAC1B,SAAO;AACT;;;AQxEA,IAAM,aAAa;AACnB,IAAM,QAAQ;AAGd,SAAS,WAAW,GAAW,GAAW,SAAmD;AAC3F,MAAI,SAAS;AACb,MAAI,IAAI,QAAQ,SAAS;AACzB,WAASC,KAAI,GAAGA,KAAI,QAAQ,QAAQ,IAAIA,MAAK;AAC3C,QAAM,QAAQA,IAAG,IAAI,MAAQ,QAAQ,GAAG,IAAI,KAAQ,KAAK,QAAQ,GAAG,IAAI,QAAQA,IAAG,MAAM,IAAI,QAAQA,IAAG,MAAM,QAAQ,GAAG,IAAI,QAAQA,IAAG,KAAK,QAAQA,IAAG;AAAI,eAAS,CAAC;AAAA,EACxK;AACA,SAAO;AACT;AAEA,eAAsB,KAAKC,OAA+C;AACxE,MAAI,CAACA,MAAK;AAAQ,WAAOA,MAAK;AAC9B,MAAI,CAACA,MAAK,QAAQA,MAAK,KAAK,SAAS;AAAK,WAAOA,MAAK;AACtD,QAAM,QAAQA,MAAK,OAAO,MAAM,MAAM;AACtC,QAAM,SAASA,MAAK,OAAO,MAAM,MAAM;AACvC,QAAMC,UAAS,MAAMD,MAAK,OAAO,OAAO;AACxC,MAAI,aAA8C,CAAC;AACnD,aAAW,MAAM,gBAAgB;AAAY,eAAW,KAAK,EAAE,IAAIA,MAAK,KAAK,IAAI,KAAKA,MAAK,IAAI,MAAMA,MAAK,IAAI,IAAI,IAAIA,MAAK,KAAK,IAAI,KAAKA,MAAK,IAAI,MAAMA,MAAK,IAAI,GAAG,CAAC;AACrK,MAAI,cAAc,aAAa;AAAG,iBAAa,WAAW,IAAI,CAAC,QAAQ,EAAE,GAAG,GAAG,IAAI,MAAM,GAAG,IAAI,aAAa,GAAG,IAAI,YAAY,GAAG,GAAG,IAAI,MAAM,GAAG,IAAI,aAAa,GAAG,IAAI,WAAW,EAAE;AACxL,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,aAAS,IAAI,GAAG,IAAI,QAAQ,KAAK;AAC/B,YAAM,SAAS,WAAW,IAAI,OAAO,IAAI,OAAO,UAAU;AAC1D,UAAI,CAAC,QAAQ;AACX,QAAAC,QAAO,IAAI,QAAQA,QAAO,IAAI,GAAG,GAAG,GAAG,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC;AACrD,QAAAA,QAAO,IAAI,QAAQA,QAAO,IAAI,GAAG,GAAG,GAAG,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC;AACrD,QAAAA,QAAO,IAAI,QAAQA,QAAO,IAAI,GAAG,GAAG,GAAG,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC;AAAA,MACvD;AAAA,IACF;AAAA,EACF;AACA,QAAM,SAASA,QAAO,SAAS;AAC/B,EAAG,QAAQA,OAAM;AACjB,SAAO;AACT;;;ACpCA,IAAM,gBAAgB,CAACC,UAA4D;AACjF,QAAM,UAAU,CAAC,KAAY,QAAe,KAAK,MAAM,IAAI,KAAK,IAAI,IAAI,IAAI,KAAK,IAAI,EAAE;AACvF,MAAI,CAACA,MAAK,YAAY,mBAAmB,CAACA,MAAK,YAAY;AAAgB,WAAO,EAAE,SAAS,GAAG,UAAU,EAAE;AAE5G,QAAM,aAAa,CAAC,GAAG,IAAI;AAC3B,QAAM,WAAW;AAEjB,QAAM,QAAQA,MAAK,KAAK,IAAI,MAAM,MAAMA,MAAK,KAAK,KAAK,MAAM;AAC7D,QAAM,aAAa,OAAOA,MAAK,KAAK,OAAOA,MAAK,KAAK;AACrD,QAAM,YAAY,OACd,EAAEA,MAAK,KAAK,KAAK,KAAKA,MAAK,KAAK,IAAI,MAAM,IAAIA,MAAK,KAAK,KAAK,KAAKA,MAAK,KAAK,IAAI,MAAM,CAAC,IACvF,EAAEA,MAAK,KAAK,KAAK,KAAKA,MAAK,KAAK,KAAK,MAAM,IAAIA,MAAK,KAAK,KAAK,KAAKA,MAAK,KAAK,KAAK,MAAM,CAAC;AAC7F,QAAM,UAAU,OACZ,CAACA,MAAK,KAAK,KAAK,KAAKA,MAAK,KAAK,IAAI,IAAIA,MAAK,KAAK,IAAI,KAAKA,MAAK,KAAK,IAAI,EAAE,IAC1E,CAACA,MAAK,KAAK,KAAK,KAAKA,MAAK,KAAK,KAAK,IAAIA,MAAK,KAAK,KAAK,KAAKA,MAAK,KAAK,KAAK,EAAE;AACjF,QAAM,UAAiB;AAAA,KACpB,UAAU,KAAK,WAAW,MAAM,QAAQ,KAAK,WAAW;AAAA,IACzD,YAAY,WAAW,KAAK,UAAU,MAAM,QAAQ,KAAK,WAAW;AAAA,EACtE;AACA,MAAI,WAAW,KAAK,KAAM,QAAQ,KAAK,QAAQ,KAAO,QAAQ,KAAK,QAAQ,EAAG;AAC9E,aAAW,KAAK,IAAI,UAAUA,MAAK,OAAO,KAAK,GAAGA,MAAK,OAAO,KAAK,CAAC;AACpE,QAAM,WAAW,QAAQ,CAAC,GAAG,CAAC,GAAG,OAAO,IAAK,KAAK,KAAK,KAAM,KAAK;AAClE,SAAO,EAAE,SAAS,SAAS;AAC7B;AAEO,IAAM,qBAAqB,CAACA,OAAkB,cAIhD;AAEH,QAAM,YAAY,CAAC,MAAsB;AACvC,UAAM,SAAS,KAAK,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE,EAAE;AAChE,MAAE,MAAM;AACR,MAAE,MAAM;AACR,MAAE,MAAM;AACR,WAAO;AAAA,EACT;AACA,QAAM,aAAa,CAAC,GAAW,MAAsB;AACnD,UAAM,IAAI,EAAE,KAAK,EAAE;AACnB,UAAM,IAAI,EAAE,KAAK,EAAE;AACnB,UAAM,IAAI,EAAE,KAAK,EAAE;AACnB,WAAO,CAAC,GAAG,GAAG,CAAC;AAAA,EACjB;AACA,QAAM,eAAe,CAAC,GAAW,MAAsB;AACrD,UAAM,IAAI,EAAE,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE;AACjC,UAAM,IAAI,EAAE,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE;AACjC,UAAM,IAAI,EAAE,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE;AACjC,WAAO,CAAC,GAAG,GAAG,CAAC;AAAA,EACjB;AAEA,QAAM,6BAA6B,CAACC,OAA8D;AAEhG,UAAM,CAAC,KAAK,MAAM,MAAM,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG,IAAIA;AACxD,QAAI;AACJ,QAAI;AACJ,QAAI;AACJ,QAAI,MAAM,GAAG;AACX,UAAI,MAAM,IAAI;AACZ,iBAAS,KAAK,KAAK,GAAG;AACtB,iBAAS,KAAK,MAAM,CAAC,KAAK,GAAG;AAC7B,iBAAS,KAAK,MAAM,CAAC,KAAK,GAAG;AAAA,MAC/B,OAAO;AACL,iBAAS,CAAC,KAAK,KAAK;AACpB,iBAAS,CAAC,KAAK,MAAM,KAAK,GAAG;AAC7B,iBAAS;AAAA,MACX;AAAA,IACF,OAAO;AACL,eAAS,KAAK,KAAK;AACnB,eAAS,KAAK,MAAM,KAAK,GAAG;AAC5B,eAAS;AAAA,IACX;AACA,QAAI,MAAM,MAAM;AAAG,eAAS;AAC5B,QAAI,MAAM,MAAM;AAAG,eAAS;AAC5B,QAAI,MAAM,MAAM;AAAG,eAAS;AAC5B,WAAO,EAAE,OAAO,IAAI,CAAC,QAAQ,KAAK,IAAI,CAAC,QAAQ,MAAM,IAAI,CAAC,OAAO;AAAA,EACnE;AAcA,QAAM,OAAOD,MAAK;AAClB,MAAI,CAAC,QAAQ,KAAK,SAAS;AAAK,WAAO,EAAE,OAAO,EAAE,OAAO,GAAG,KAAK,GAAG,MAAM,EAAE,GAAG,QAAQ,CAAC,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,CAAC,GAAG,MAAM,EAAE,SAAS,GAAG,UAAU,EAAE,EAAE;AAEtJ,QAAME,QAAO,KAAK,IAAIF,MAAK,OAAO,KAAK,UAAU,IAAIA,MAAK,OAAO,KAAK,UAAU,EAAE,IAAI;AAEtF,QAAM,MAAe,CAAC,KAAK,KAAK,KAAK,MAAM,KAAK,MAAM,KAAK,IAAI,EAAE,IAAI,CAAC,OAAO,CAAC,GAAG,KAAK,UAAU,KAAKE,OAAM,GAAG,KAAK,UAAU,KAAKA,OAAM,GAAG,EAAE,CAAU;AAEvJ,QAAM,SAAS,UAAU,WAAW,IAAI,IAAc,IAAI,EAAY,CAAC;AACvE,MAAI,SAAS,UAAU,WAAW,IAAI,IAAc,IAAI,EAAY,CAAC;AACrE,QAAM,SAAS,UAAU,aAAa,QAAQ,MAAM,CAAC;AAErD,WAAS,aAAa,QAAQ,MAAM;AAIpC,QAAM,SAAmF;AAAA,IACvF,OAAO;AAAA,IAAI,OAAO;AAAA,IAAI,OAAO;AAAA,IAC7B,OAAO;AAAA,IAAI,OAAO;AAAA,IAAI,OAAO;AAAA,IAC7B,OAAO;AAAA,IAAI,OAAO;AAAA,IAAI,OAAO;AAAA,EAC/B;AACA,QAAM,QAAQ,2BAA2B,MAAM;AAI/C,QAAM,OAAO,KAAK,WAAW,MAAM,cAAcF,KAAI,IAAI,EAAE,SAAS,GAAG,UAAU,EAAE;AAEnF,SAAO,EAAE,OAAO,QAAQ,KAAK;AAC/B;;;AChGO,IAAM,aAAa,OAAO,UAAyCG,WAAyC;AAzBnH;AA4BE,MAAI,YAAoB,IAAI;AAC5B,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AAEJ,QAAM,UAA6B,CAAC;AACpC,WAAS,QAAQ;AAEjB,QAAM,QAAQ,MAAeC,UAAQD,QAAO,SAAS,MAAM;AAC3D,WAAS,YAAY,OAAOE,KAAI,WAAW,SAAS,YAAY,QAAQ,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AACzI,MAAI,CAACF,OAAM,SAASA,OAAM,MAAM,WAAW;AAAG,WAAO,CAAC;AACtD,MAAI,CAAC;AAAO,WAAO,CAAC;AAEpB,WAASG,KAAI,GAAGA,KAAI,MAAM,QAAQA,MAAK;AACrC,aAAS,QAAQ,UAAU;AAI3B,QAAI,CAAC,MAAMA,IAAG,UAAU,MAAMA,IAAG,OAAO,uBAAuB;AAC7D,UAAI,4BAA4B,MAAMA,IAAG,MAAM;AAC/C;AAAA,IACF;AAGA,SAAI,cAAS,OAAO,KAAK,aAArB,mBAA+B,MAAM;AACvC,YAAM,SAAS,MAAW,KAAK,MAAMA,GAAE;AACvC,MAAG,QAAQ,MAAMA,IAAG,MAAM;AAC1B,YAAMA,IAAG,SAAS;AAAA,IACpB;AAGA,UAAM,WAAW,MAAMA,IAAG,QAAS,MAAMA,IAAG,KAAK,SAAS,MAAO,mBAAmB,MAAMA,KAAI,CAACH,OAAM,MAAM,IAAIA,OAAM,MAAM,EAAE,CAAC,IAAI;AAGlI,aAAS,QAAQ,gBAAgB;AACjC,QAAI,SAAS,OAAO,OAAO;AACzB,qBAAa,cAAS,OAAO,KAAK,YAArB,mBAA8B,WAAkBC,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI,CAAC;AAAA,IAC9I,OAAO;AACL,eAAS,QAAQ;AACjB,kBAAY,IAAI;AAChB,qBAAa,cAAS,OAAO,KAAK,YAArB,mBAA8B,WAAU,MAAcF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI,CAAC;AAClJ,eAAS,YAAY,UAAUD,KAAI,WAAW,SAAS,YAAY,WAAW,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,IACjJ;AACA,aAAS,QAAQ,cAAc;AAG/B,aAAS,QAAQ,kBAAkB;AACnC,QAAI,SAAS,OAAO,OAAO;AACzB,uBAAe,cAAS,OAAO,KAAK,cAArB,mBAAgC,WAAoBD,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAAA,IACnJ,OAAO;AACL,eAAS,QAAQ;AACjB,kBAAY,IAAI;AAChB,uBAAe,cAAS,OAAO,KAAK,cAArB,mBAAgC,WAAU,MAAgBF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AACvJ,eAAS,YAAY,YAAYD,KAAI,WAAW,SAAS,YAAY,aAAa,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,IACrJ;AACA,aAAS,QAAQ,gBAAgB;AAGjC,aAAS,QAAQ,iBAAiB;AAClC,QAAI,SAAS,OAAO,OAAO;AACzB,sBAAc,cAAS,OAAO,KAAK,aAArB,mBAA+B,WAAmBD,UAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAAA,IAChJ,OAAO;AACL,eAAS,QAAQ;AACjB,kBAAY,IAAI;AAChB,sBAAc,cAAS,OAAO,KAAK,aAArB,mBAA+B,WAAU,MAAeF,UAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AACpJ,eAAS,YAAY,WAAWD,KAAI,WAAW,SAAS,YAAY,aAAa,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,IACpJ;AACA,aAAS,QAAQ,eAAe;AAGhC,aAAS,QAAQ,aAAa;AAC9B,QAAI,SAAS,OAAO,OAAO;AACzB,kBAAU,cAAS,OAAO,KAAK,YAArB,mBAA8B,WAAe,QAAQ,MAAMC,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAAA,IACvI,OAAO;AACL,eAAS,QAAQ;AACjB,kBAAY,IAAI;AAChB,kBAAU,cAAS,OAAO,KAAK,YAArB,mBAA8B,WAAU,MAAW,QAAQ,MAAMA,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAC3I,eAAS,YAAY,OAAO,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,IAC1D;AACA,aAAS,QAAQ,WAAW;AAG5B,aAAS,QAAQ,eAAe;AAChC,QAAI,SAAS,OAAO,OAAO;AACzB,iBAAS,cAAS,OAAO,KAAK,cAArB,mBAAgC,WAAoBF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAC3I,oBAAY,cAAS,OAAO,KAAK,cAArB,mBAAgC,WAAuBF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAAA,IACnJ,OAAO;AACL,eAAS,QAAQ;AACjB,kBAAY,IAAI;AAChB,iBAAS,cAAS,OAAO,KAAK,cAArB,mBAAgC,WAAU,MAAgBF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AACjJ,oBAAY,cAAS,OAAO,KAAK,cAArB,mBAAgC,WAAU,MAAmBF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AACvJ,eAAS,YAAY,SAAS,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,IAC5D;AACA,aAAS,QAAQ,aAAa;AAG9B,aAAS,QAAQ,sBAAsB;AACvC,QAAI,SAAS,OAAO,OAAO;AACzB,2BAAmB,cAAS,OAAO,KAAK,qBAArB,mBAAuC,WAAwBF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAAA,IAClK,OAAO;AACL,eAAS,QAAQ;AACjB,kBAAY,IAAI;AAChB,2BAAmB,cAAS,OAAO,KAAK,qBAArB,mBAAuC,WAAU,MAAoBF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AACtK,eAAS,YAAY,gBAAgB,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,IACnE;AACA,aAAS,QAAQ,oBAAoB;AAGrC,aAAS,QAAQ,oBAAoB;AACrC,QAAI,SAAS,OAAO,OAAO;AACzB,kBAAU,cAAS,OAAO,KAAK,gBAArB,mBAAkC,WAAkBF,UAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAAA,IAC9I,OAAO;AACL,eAAS,QAAQ;AACjB,kBAAY,IAAI;AAChB,kBAAU,cAAS,OAAO,KAAK,gBAArB,mBAAkC,WAAU,MAAcF,UAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAClJ,eAAS,YAAY,cAAcD,KAAI,WAAW,SAAS,YAAY,eAAe,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,IACzJ;AACA,aAAS,QAAQ,kBAAkB;AAGnC,QAAI,SAAS,OAAO,OAAO;AACzB,OAAC,QAAQ,WAAW,YAAY,kBAAkB,SAAS,SAAS,cAAc,WAAW,IAAI,MAAM,QAAQ,IAAI,CAAC,QAAQ,WAAW,YAAY,kBAAkB,SAAS,SAAS,cAAc,WAAW,CAAC;AAAA,IACnN;AACA,aAAS,QAAQ,cAAc;AAE/B,UAAI,cAAS,OAAO,KAAK,cAArB,mBAAgC,YAAW,UAAU,WAAW;AAClE,gBAAU;AAAA,QACR,GAAI;AAAA,QACJ,KAAM,OAA0B;AAAA,QAChC,QAAS,UAAsD;AAAA,QAC/D,aAAc,UAAsD;AAAA,MACtE;AAAA,IACF;AACA,UAAI,cAAS,OAAO,KAAK,YAArB,mBAA8B,YAAW,SAAS;AACpD,gBAAU;AAAA,QACR,GAAI;AAAA,QACJ,KAAM,QAA0B;AAAA,QAChC,QAAS,QAA0B;AAAA,QACnC,aAAc,QAA0B;AAAA,QACxC,MAAO,QAA0B;AAAA,MACnC;AAAA,IACF;AACA,UAAI,cAAS,OAAO,KAAK,qBAArB,mBAAuC,YAAW,kBAAkB;AACtE,MAAC,QAAoB,aAAa;AAAA,IACpC;AAIA,QAAI,GAAC,cAAS,OAAO,KAAK,SAArB,mBAA2B,UAAS;AAAA,IAGzC;AACA,UAAM,WAAY,MAAMC,IAAG,eAAe,MAAMA,IAAG,YAAY,eAAe,MAAMA,IAAG,YAAY,YAAY,MAAM,MAAMA,IAAG,YAAY,gBAAgB,MAAMA,IAAG,YAAY,aAAa,MACtL,MAAMA,IAAG,YAAY,YAAY,SAAS,KAAO,MAAMA,IAAG,YAAY,aAAa,SAAS,KAC5F,MAAMA,IAAG,YAAY,YAAY,OAAO,QAAU,MAAMA,IAAG,YAAY,aAAa,OAAO,OAC7F,KAAK,IAAI,KAAK,IAAI,MAAMA,IAAG,YAAY,YAAY,GAAG,KAAK,MAAMA,IAAG,YAAY,YAAY,GAAG,EAAE,GAAG,KAAK,IAAI,MAAMA,IAAG,YAAY,aAAa,GAAG,KAAK,MAAMA,IAAG,YAAY,aAAa,GAAG,EAAE,CAAC,IAAIH,OAAM,MAAM,KAC/M;AAGJ,UAAMI,YAAS,cAAS,OAAO,KAAK,aAArB,mBAA+B,UAAY,QAAQ,MAAMD,IAAG,MAAM,IAAI;AAErF,IAAG,QAAQ,MAAMA,IAAG,MAAM;AAE1B,QAAI,MAAMA,IAAG;AAAQ,aAAO,MAAMA,IAAG;AAErC,UAAM,MAAkB;AAAA,MACtB,GAAG,MAAMA;AAAA,MACT,IAAIA;AAAA,IACN;AACA,QAAK,mCAAqB;AAAK,UAAI,MAAO,QAAoB;AAC9D,QAAK,mCAAqB;AAAQ,UAAI,SAAU,QAAoB;AACpE,QAAK,mCAAqB;AAAa,UAAI,cAAe,mCAAqB;AAC/E,QAAK,mCAAqB;AAAY,UAAI,YAAa,mCAAqB;AAC5E,QAAK,mCAAqB;AAAM,UAAI,OAAQ,mCAAqB;AACjE,QAAI;AAAY,UAAI,UAAU;AAC9B,QAAI;AAAc,UAAI,OAAO;AAC7B,QAAI;AAAa,UAAI,OAAO;AAC5B,QAAI,YAAY,aAAa;AAAG,UAAI,OAAO,KAAK,MAAM,MAAM,WAAW,IAAI,IAAI;AAC/E,QAAI;AAAU,UAAI,WAAW;AAC7B,QAAIC;AAAQ,UAAI,SAASA;AACzB,YAAQ,KAAK,GAAG;AAChB,aAAS,QAAQ,UAAU;AAAA,EAC7B;AACA,WAAS,QAAQ,eAAe;AAChC,MAAI,SAAS,OAAO,OAAO;AACzB,QAAI,SAAS,YAAY;AAAM,aAAO,SAAS,YAAY;AAC3D,QAAI,SAAS,YAAY;AAAK,aAAO,SAAS,YAAY;AAC1D,QAAI,SAAS,YAAY;AAAQ,aAAO,SAAS,YAAY;AAC7D,QAAI,SAAS,YAAY;AAAS,aAAO,SAAS,YAAY;AAAA,EAChE;AACA,SAAO;AACT;;;AC/LO,IAAMC,QAAO,CAAC,QAAuC;AAC1D,MAAI,CAAC;AAAK,WAAO,CAAC;AAClB,QAAM,WAA0D,CAAC;AACjE,WAASC,KAAI,GAAGA,KAAI,IAAI,QAAQA,MAAK;AAEnC,UAAM,YAAY,IAAIA,IAAG,UAAU,KAAK,CAAC,MAAO,EAAE,SAAS,WAAY;AACvE,UAAM,aAAa,IAAIA,IAAG,UAAU,KAAK,CAAC,MAAO,EAAE,SAAS,YAAa;AACzE,UAAM,OAAO,IAAIA,IAAG,UAAU,KAAK,CAAC,MAAO,EAAE,SAAS,MAAO;AAC7D,QAAI,QAAQ,aAAa,cAAe,UAAU,SAAS,KAAK,KAAK,SAAS,MAAQ,WAAW,SAAS,KAAK,KAAK,SAAS;AAAK,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,YAAY,CAAC;AAAA,aACxK,QAAQ,aAAc,UAAU,SAAS,KAAK,KAAK,SAAS;AAAK,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,kBAAkB,CAAC;AAAA,aACtH,QAAQ,cAAe,WAAW,SAAS,KAAK,KAAK,SAAS;AAAK,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,mBAAmB,CAAC;AAGlI,UAAM,eAAe,IAAIA,IAAG,UAAU,KAAK,CAAC,MAAO,EAAE,SAAS,cAAe;AAC7E,UAAM,gBAAgB,IAAIA,IAAG,UAAU,KAAK,CAAC,MAAO,EAAE,SAAS,eAAgB;AAC/E,QAAI,gBAAgB,iBAAiB,KAAK,IAAI,aAAa,YAAY,KAAK,cAAc,YAAY,EAAE,IAAI,KAAK;AAC/G,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,WAAY,aAAa,SAAS,KAAK,cAAc,SAAS,KAAM,SAAS,UAAU,CAAC;AAAA,IAC5H;AAAA,EACF;AACA,SAAO;AACT;AAEO,IAAMC,QAAO,CAAC,QAAuC;AAC1D,MAAI,CAAC;AAAK,WAAO,CAAC;AAClB,QAAM,WAA0D,CAAC;AACjE,WAASD,KAAI,GAAGA,KAAI,IAAI,QAAQA,MAAK;AACnC,QAAI,IAAIA,IAAG,QAAQ,IAAIA,IAAG,KAAK,SAAS,KAAK;AAC3C,YAAM,SAAS,IAAIA,IAAG,KAAK,IAAI,MAAM,MAAM,IAAIA,IAAG,KAAK,KAAK,MAAM;AAClE,YAAM,QAAQ,IAAIA,IAAG,KAAK,IAAI,KAAK,IAAIA,IAAG,KAAK,KAAK;AACpD,UAAI,KAAK,IAAI,QAAQ,KAAK,KAAK;AAAM,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,gBAAgB,CAAC;AAAA;AACnF,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,UAAU,QAAQ,IAAI,SAAS,UAAU,CAAC;AACjF,YAAM,WAAW,KAAK,IAAI,IAAIA,IAAG,KAAK,KAAK,KAAK,IAAIA,IAAG,KAAK,KAAK,EAAE,IAAI,KAAK,IAAI,IAAIA,IAAG,KAAK,KAAK,KAAK,IAAIA,IAAG,KAAK,KAAK,EAAE;AACzH,UAAI,WAAW;AAAK,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,iBAAiB,CAAC;AACxE,YAAM,YAAY,KAAK,IAAI,IAAIA,IAAG,KAAK,KAAK,KAAK,IAAIA,IAAG,KAAK,KAAK,EAAE,IAAI,KAAK,IAAI,IAAIA,IAAG,KAAK,KAAK,KAAK,IAAIA,IAAG,KAAK,KAAK,EAAE;AAC1H,UAAI,YAAY;AAAK,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,kBAAkB,CAAC;AAC1E,YAAM,YAAY,KAAK,IAAI,KAAK,MAAM,KAAK,IAAI,IAAIA,IAAG,KAAK,IAAI,KAAK,IAAIA,IAAG,KAAK,IAAI,EAAE,IAAI,KAAK,IAAI,IAAIA,IAAG,KAAK,IAAI,KAAK,IAAIA,IAAG,KAAK,KAAK,EAAE,CAAC;AAC5I,UAAI,YAAY;AAAI,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,SAAS,KAAK,MAAM,SAAS,UAAU,CAAC;AAC9F,YAAM,YAAY,IAAIA,IAAG,KAAK,KAAK,MAAM;AACzC,UAAI,KAAK,IAAI,SAAS,IAAI;AAAI,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,QAAQ,YAAY,IAAI,OAAO,SAAS,CAAC;AAAA,IAC3G;AAAA,EACF;AACA,SAAO;AACT;AAEO,IAAME,QAAO,CAAC,QAAuC;AAC1D,MAAI,CAAC;AAAK,WAAO,CAAC;AAClB,QAAM,WAA0D,CAAC;AACjE,WAASF,KAAI,GAAGA,KAAI,IAAI,QAAQA,MAAK;AACnC,QAAI,CAAC,IAAIA,IAAG,eAAe,CAAC,IAAIA,IAAG,YAAY,eAAe,CAAC,IAAIA,IAAG,YAAY,YAAY,MAAM,CAAC,IAAIA,IAAG,YAAY,gBAAgB,CAAC,IAAIA,IAAG,YAAY,aAAa;AAAI;AAC7K,UAAM,YAAY,IAAIA,IAAG,YAAY,YAAY,GAAG,KAAK,IAAIA,IAAG,YAAY,YAAY,GAAG;AAC3F,UAAM,YAAY,IAAIA,IAAG,YAAY,YAAY,GAAG,KAAK,IAAIA,IAAG,YAAY,YAAY,GAAG;AAC3F,UAAM,WAAW,KAAK,IAAI,YAAY,SAAS;AAE/C,UAAM,aAAa,IAAIA,IAAG,YAAY,aAAa,GAAG,KAAK,IAAIA,IAAG,YAAY,aAAa,GAAG;AAC9F,UAAM,aAAa,IAAIA,IAAG,YAAY,aAAa,GAAG,KAAK,IAAIA,IAAG,YAAY,aAAa,GAAG;AAC9F,UAAM,YAAY,KAAK,IAAI,aAAa,UAAU;AAElD,QAAI,SAAS;AACb,UAAM,aAAa,KAAK,IAAI,WAAW,SAAS,IAAI,KAAK,IAAI,UAAU,SAAS;AAChF,QAAI,aAAa,MAAM;AACrB,eAAS;AACT,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,gBAAgB,CAAC;AAAA,IACrD;AAEA,UAAM,kBAAkB,KAAK,IAAI,IAAIA,IAAG,KAAK,KAAK,KAAK,IAAIA,IAAG,YAAY,YAAY,GAAG,EAAE,IAAI,IAAIA,IAAG,IAAI;AAC1G,UAAM,mBAAmB,KAAK,IAAI,IAAIA,IAAG,KAAK,IAAI,KAAK,IAAIA,IAAG,YAAY,aAAa,GAAG,EAAE,IAAI,IAAIA,IAAG,IAAI;AAC3G,QAAI,kBAAkB,QAAQ,mBAAmB;AAAM,eAAS;AAChE,QAAI,kBAAkB,kBAAkB;AACtC,UAAI,kBAAkB;AAAM,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,gBAAgB,CAAC;AAAA,IACjF,OAAO;AACL,UAAI,mBAAmB;AAAM,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,eAAe,CAAC;AAAA,IACjF;AAEA,UAAM,mBAAmB,KAAK,IAAI,IAAIA,IAAG,KAAK,KAAK,KAAK,IAAIA,IAAG,YAAY,aAAa,GAAG,EAAE,IAAI,IAAIA,IAAG,IAAI;AAC5G,UAAM,kBAAkB,KAAK,IAAI,IAAIA,IAAG,KAAK,KAAK,KAAK,IAAIA,IAAG,YAAY,YAAY,GAAG,EAAE,IAAI,IAAIA,IAAG,IAAI;AAC1G,QAAI,kBAAkB,QAAQ,mBAAmB,QAAQ,kBAAkB,SAAS,mBAAmB;AAAO,eAAS;AACvH,QAAI,kBAAkB,QAAQ,mBAAmB;AAAM,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,eAAe,CAAC;AACzG,QAAI,kBAAkB,SAAS,mBAAmB;AAAO,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,aAAa,CAAC;AAGzG,QAAI;AAAQ,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,iBAAiB,CAAC;AAAA,EAClE;AACA,SAAO;AACT;AAEO,IAAMG,QAAO,CAAC,QAAuC;AAC1D,MAAI,CAAC;AAAK,WAAO,CAAC;AAClB,QAAM,WAA0D,CAAC;AACjE,WAASH,KAAI,GAAGA,KAAI,IAAI,QAAQA,MAAK;AACnC,UAAM,UAAoD,CAAC;AAC3D,QAAI,IAAIA,IAAG,gBAAgB;AACzB,iBAAW,CAAC,QAAQ,GAAG,KAAK,OAAO,QAAQ,IAAIA,IAAG,cAAc,GAAG;AACjE,YAAI,WAAW,cAAc,MAAM,QAAQ,GAAG,KAAK,IAAI;AAAI,kBAAQ,KAAK,EAAE,MAAM,OAAO,YAAY,GAAG,UAAU,IAAI,GAAG,CAAC;AAAA,MAC1H;AAAA,IACF;AACA,QAAI,WAAW,QAAQ,SAAS,GAAG;AACjC,YAAM,UAAU,QAAQ,OAAO,CAAC,MAAM,OAAQ,KAAK,SAAS,MAAM,MAAM,EAAE,SAAS,MAAM,KAAK,OAAO,CAAE;AACvG,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,GAAG,QAAQ,eAA8B,CAAC;AAC5E,YAAM,UAAU,QAAQ,OAAO,CAAC,MAAM,MAAO,KAAK,SAAS,KAAK,EAAE,SAAS,KAAK,OAAO,CAAE;AACzF,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,GAAG,QAAQ,UAAyB,CAAC;AAAA,IACzE;AACA,QAAI,IAAIA,IAAG,cAAc;AACvB,YAAM,QAAmB,MAAM,IAAIA,IAAG,YAAY;AAClD,iBAAW,QAAQ;AAAO,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,KAAK,KAAoB,CAAC;AAAA,IACxF;AAAA,EACF;AACA,SAAO;AACT;;;AC/HA,IAAM,iBAAyB,EAAE,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,SAAS,CAAC,GAAG,QAAQ,CAAC,GAAG,SAAS,CAAC,GAAG,aAAa,CAAC,GAAG,WAAW,GAAG,OAAO,KAAK;AAChJ,IAAI,kBAAkB;AAEf,SAASI,MAAK,WAAmBC,SAAwB;AAhBhE;AAiBE,QAAM,KAAK,IAAI;AACf,MAAI,CAAC;AAAW,WAAO,EAAE,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,SAAS,CAAC,GAAG,QAAQ,CAAC,GAAG,SAAS,CAAC,GAAG,aAAa,CAAC,GAAG,WAAW,GAAG,OAAO,KAAK;AAKxI,QAAM,UAAU,KAAK,IAAI,IAAI,UAAU;AAQvC,QAAM,iBAAiB,UAAU,MAAO,IAAI,KAAK,IAAI,UAAU,CAAC,IAAI;AAEpE,MAAI,UAAU;AAAQ,mBAAe,SAAS,UAAU;AACxD,MAAI,UAAU;AAAO,mBAAe,QAAQ,UAAU;AAGtD,MAAI,CAAC,eAAe,QAAS,UAAU,KAAK,WAAW,eAAe,KAAK,QAAS;AAClF,mBAAe,OAAO,KAAK,MAAM,KAAK,UAAU,UAAU,IAAoB,CAAC;AAAA,EACjF,OAAO;AACL,aAASC,KAAI,GAAGA,KAAI,UAAU,KAAK,QAAQA,MAAK;AAC9C,YAAM,MAAM,UAAU,KAAKA,IAAG,IAC3B,IAAI,CAAC,aAAa,QAAQ,iBAAiB,KAAK,eAAe,KAAKA,IAAG,IAAI,KAAK,eAAe,cAAc;AAChH,YAAM,SAAS,UAAU,KAAKA,IAAG,OAC9B,IAAI,CAAC,aAAa,QAAQ,iBAAiB,KAAK,eAAe,KAAKA,IAAG,OAAO,KAAK,eAAe,cAAc;AACnH,YAAM,YAAa,UAAU,KAAKA,IAAG,UAClC,IAAI,CAAC,QAAQ,MAAG;AA9CzB,YAAAC,KAAAC,KAAAC,KAAAC,KAAAC,KAAAC,KAAAC,KAAAC,KAAAC;AA8C6B;AAAA,UACnB,OAAO,OAAO;AAAA,UACd,MAAM,OAAO;AAAA,UACb,UAAU;AAAA,YACR,eAAe,KAAKT,IAAG,UAAU,OAAO,iBAAiB,MAAM,eAAe,KAAKA,IAAG,UAAU,GAAG,SAAS,MAAM,MAAM,OAAO,SAAS,MAAM,MAAM,iBAAiB,OAAO,SAAS;AAAA,YACrL,eAAe,KAAKA,IAAG,UAAU,OAAO,iBAAiB,MAAM,eAAe,KAAKA,IAAG,UAAU,GAAG,SAAS,MAAM,MAAM,OAAO,SAAS,MAAM,MAAM,iBAAiB,OAAO,SAAS;AAAA,YACrL,eAAe,KAAKA,IAAG,UAAU,OAAO,iBAAiB,MAAM,eAAe,KAAKA,IAAG,UAAU,GAAG,SAAS,MAAM,MAAM,OAAO,SAAS,MAAM,MAAM,iBAAiB,OAAO,SAAS;AAAA,UACvL;AAAA,UACA,aAAa;AAAA,YACX,eAAe,KAAKA,IAAG,UAAU,OAAO,iBAAiB,MAAM,eAAe,KAAKA,IAAG,UAAU,GAAG,YAAY,MAAM,MAAM,OAAO,YAAY,MAAM,MAAM,iBAAiB,OAAO,YAAY;AAAA,YAC9L,eAAe,KAAKA,IAAG,UAAU,OAAO,iBAAiB,MAAM,eAAe,KAAKA,IAAG,UAAU,GAAG,YAAY,MAAM,MAAM,OAAO,YAAY,MAAM,MAAM,iBAAiB,OAAO,YAAY;AAAA,YAC9L,eAAe,KAAKA,IAAG,UAAU,OAAO,iBAAiB,MAAM,eAAe,KAAKA,IAAG,UAAU,GAAG,YAAY,MAAM,MAAM,OAAO,YAAY,MAAM,MAAM,iBAAiB,OAAO,YAAY;AAAA,UAChM;AAAA,UACA,UAAU;AAAA,YACR,eAAe,KAAKA,IAAG,UAAU,OAAO,iBAAiB,QAAMC,MAAA,eAAe,KAAKD,IAAG,UAAU,GAAG,aAApC,gBAAAC,IAA+C,OAAM,QAAMC,MAAA,OAAO,aAAP,gBAAAA,IAAkB,OAAM,MAAM,kBAAiBC,MAAA,OAAO,aAAP,gBAAAA,IAAkB;AAAA,YAC3L,eAAe,KAAKH,IAAG,UAAU,OAAO,iBAAiB,QAAMI,MAAA,eAAe,KAAKJ,IAAG,UAAU,GAAG,aAApC,gBAAAI,IAA+C,OAAM,QAAMC,MAAA,OAAO,aAAP,gBAAAA,IAAkB,OAAM,MAAM,kBAAiBC,MAAA,OAAO,aAAP,gBAAAA,IAAkB;AAAA,YAC3L,eAAe,KAAKN,IAAG,UAAU,OAAO,iBAAiB,QAAMO,MAAA,eAAe,KAAKP,IAAG,UAAU,GAAG,aAApC,gBAAAO,IAA+C,OAAM,QAAMC,MAAA,OAAO,aAAP,gBAAAA,IAAkB,OAAM,MAAM,kBAAiBC,MAAA,OAAO,aAAP,gBAAAA,IAAkB;AAAA,UAC7L;AAAA,QACF;AAAA,OAAE;AAEJ,YAAMC,eAAiD,CAAC;AACxD,UAAIC,UAAS,EAAE,WAAW,CAAC,EAAE;AAC7B,WAAI,WAAAZ,QAAO,SAAP,mBAAa,cAAb,mBAAwB,SAAS;AAAkB,QAAAY,UAAS;AAAA,gBACvD,WAAAZ,QAAO,SAAP,mBAAa,cAAb,mBAAwB,SAAS;AAAc,QAAAY,UAAS;AAAA,gBACxD,WAAAZ,QAAO,SAAP,mBAAa,cAAb,mBAAwB,SAAS;AAAY,QAAAY,UAAS;AAC/D,iBAAW,CAAC,MAAM,OAAO,KAAK,OAAO,QAAQA,QAAO,SAAqC,GAAG;AAC1F,cAAM,KAAqB,CAAC;AAC5B,iBAAS,IAAI,GAAG,IAAI,QAAQ,SAAS,GAAG,KAAK;AAC3C,gBAAM,MAAM,UAAU,KAAK,CAAC,OAAO,GAAG,SAAS,QAAQ,EAAE;AACzD,gBAAM,MAAM,UAAU,KAAK,CAAC,OAAO,GAAG,SAAS,QAAQ,IAAI,EAAE;AAE7D,cAAI,OAAO;AAAK,eAAG,KAAK,CAAC,IAAI,UAAU,IAAI,QAAQ,CAAC;AAAA,QACtD;AACA,QAAAD,aAAY,QAAQ;AAAA,MACtB;AACA,qBAAe,KAAKV,MAAK,EAAE,GAAG,UAAU,KAAKA,KAAI,KAAK,QAAQ,WAAW,aAAaU,aAAyC;AAAA,IACjI;AAAA,EACF;AAGA,MAAI,CAAC,eAAe,QAAS,UAAU,KAAK,WAAW,eAAe,KAAK,QAAS;AAClF,mBAAe,OAAO,KAAK,MAAM,KAAK,UAAU,UAAU,IAAoB,CAAC;AAAA,EACjF,OAAO;AACL,aAASV,KAAI,GAAGA,KAAI,UAAU,KAAK,QAAQA,MAAK;AAC9C,YAAM,MAAO,UAAU,KAAKA,IAAG,IAC5B,IAAI,CAAC,GAAG,QAAQ,iBAAiB,KAAK,eAAe,KAAKA,IAAG,IAAI,KAAK,KAAK,cAAc;AAC5F,YAAM,SAAU,UAAU,KAAKA,IAAG,OAC/B,IAAI,CAAC,GAAG,QAAQ,iBAAiB,KAAK,eAAe,KAAKA,IAAG,OAAO,KAAK,KAAK,cAAc;AAC/F,UAAI,eAAe,KAAKA,IAAG,UAAU,WAAW,UAAU,KAAKA,IAAG,UAAU;AAAQ,uBAAe,KAAKA,IAAG,YAAY,UAAU,KAAKA,IAAG;AACzI,YAAM,YAAY,UAAU,KAAKA,IAAG,aAAa,UAAU,KAAKA,IAAG,UAAU,SAAS,IAAI,UAAU,KAAKA,IAAG,UACzG,IAAI,CAAC,UAAU,MAAM,SACnB,IAAI,CAAC,OAAO,QAAS,iBAAiB,MAAM,eAAe,KAAKA,IAAG,UAAU,GAAG,MAAM,MAAM,SAAS,MAAM,cAAe,CAAU,IACrI,CAAC;AACL,UAAIU,eAAc,CAAC;AACnB,UAAI,OAAO,KAAK,eAAe,KAAKV,IAAG,WAAW,EAAE,WAAW,OAAO,KAAK,UAAU,KAAKA,IAAG,WAAW,EAAE,QAAQ;AAChH,uBAAe,KAAKA,IAAG,cAAc,UAAU,KAAKA,IAAG;AACvD,QAAAU,eAAc,eAAe,KAAKV,IAAG;AAAA,MACvC,WAAW,UAAU,KAAKA,IAAG,aAAa;AACxC,mBAAW,OAAO,OAAO,KAAK,UAAU,KAAKA,IAAG,WAAW,GAAG;AAC5D,UAAAU,aAAY,OAAO,UAAU,KAAKV,IAAG,YAAY,QAAQ,UAAU,KAAKA,IAAG,YAAY,KAAK,KACxF,UAAU,KAAKA,IAAG,YAAY,KAC7B,IAAI,CAAC,KAAK,MAAc,IACtB,IAAI,CAAC,OAAe,QAAgB,iBAAiB,KAAK,eAAe,KAAKA,IAAG,YAAY,KAAK,GAAG,KAAK,SAAS,cAAc,CAAC,IACrI;AAAA,QACN;AAAA,MACF;AACA,qBAAe,KAAKA,MAAK,EAAE,GAAG,UAAU,KAAKA,KAAI,KAAK,QAAQ,WAAW,aAAaU,aAAyC;AAAA,IACjI;AAAA,EACF;AAGA,MAAI,CAAC,eAAe,QAAS,UAAU,KAAK,WAAW,eAAe,KAAK,QAAS;AAClF,mBAAe,OAAO,KAAK,MAAM,KAAK,UAAU,UAAU,IAAoB,CAAC;AAAA,EACjF,OAAO;AACL,aAASV,KAAI,GAAGA,KAAI,UAAU,KAAK,QAAQA,MAAK;AAC9C,YAAM,MAAO,UAAU,KAAKA,IAAG,IAC5B,IAAI,CAAC,GAAG,QAAQ,iBAAiB,KAAK,eAAe,KAAKA,IAAG,IAAI,KAAK,KAAK,cAAc;AAC5F,YAAM,SAAU,UAAU,KAAKA,IAAG,OAC/B,IAAI,CAAC,GAAG,QAAQ,iBAAiB,KAAK,eAAe,KAAKA,IAAG,OAAO,KAAK,KAAK,cAAc;AAC/F,UAAI,UAAU,KAAKA,IAAG,UAAU;AAC9B,cAAM,WAIF,EAAE,QAAQ,CAAC,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,CAAC,GAAG,OAAO,EAAE,MAAM,GAAG,KAAK,GAAG,OAAO,EAAE,GAAG,MAAM,EAAE,SAAS,GAAG,UAAU,EAAE,EAAE;AACnH,iBAAS,UAAS,eAAU,KAAKA,IAAG,aAAlB,mBAA4B;AAC9C,iBAAS,QAAQ;AAAA,UACf,QAAQ,iBAAiB,QAAM,0BAAe,KAAKA,IAAG,aAAvB,mBAAiC,UAAjC,mBAAwC,SAAQ,QAAM,qBAAU,KAAKA,IAAG,aAAlB,mBAA4B,UAA5B,mBAAmC,SAAQ,MAAM;AAAA,UACtI,OAAO,iBAAiB,QAAM,0BAAe,KAAKA,IAAG,aAAvB,mBAAiC,UAAjC,mBAAwC,QAAO,QAAM,qBAAU,KAAKA,IAAG,aAAlB,mBAA4B,UAA5B,mBAAmC,QAAO,MAAM;AAAA,UACnI,SAAS,iBAAiB,QAAM,0BAAe,KAAKA,IAAG,aAAvB,mBAAiC,UAAjC,mBAAwC,UAAS,QAAM,qBAAU,KAAKA,IAAG,aAAlB,mBAA4B,UAA5B,mBAAmC,UAAS,MAAM;AAAA,QAC3I;AACA,iBAAS,OAAO;AAAA,UAEd,WAAW,iBAAiB,QAAM,0BAAe,KAAKA,IAAG,aAAvB,mBAAiC,SAAjC,mBAAuC,YAAW,QAAM,qBAAU,KAAKA,IAAG,aAAlB,mBAA4B,SAA5B,mBAAkC,YAAW,MAAM;AAAA,UAC7I,YAAY,iBAAiB,QAAM,0BAAe,KAAKA,IAAG,aAAvB,mBAAiC,SAAjC,mBAAuC,aAAY,QAAM,qBAAU,KAAKA,IAAG,aAAlB,mBAA4B,SAA5B,mBAAkC,aAAY,MAAM;AAAA,QAClJ;AACA,uBAAe,KAAKA,MAAK,EAAE,GAAG,UAAU,KAAKA,KAAI,UAAU,KAAK,OAAO;AAAA,MACzE;AACA,qBAAe,KAAKA,MAAK,EAAE,GAAG,UAAU,KAAKA,KAAI,KAAK,OAAO;AAAA,IAC/D;AAAA,EACF;AAGA,MAAI,CAAC,eAAe,UAAW,UAAU,OAAO,WAAW,eAAe,OAAO,QAAS;AACxF,mBAAe,SAAS,KAAK,MAAM,KAAK,UAAU,UAAU,MAAwB,CAAC;AAAA,EACvF,OAAO;AACL,aAASA,KAAI,GAAGA,KAAI,UAAU,OAAO,QAAQA,MAAK;AAChD,YAAM,MAAO,UAAU,OAAOA,IAAG,IAC9B,IAAI,CAAC,GAAG,QAAQ,iBAAiB,KAAK,eAAe,OAAOA,IAAG,IAAI,KAAK,KAAK,cAAc;AAC9F,YAAM,SAAU,UAAU,OAAOA,IAAG,OACjC,IAAI,CAAC,GAAG,QAAQ,iBAAiB,KAAK,eAAe,OAAOA,IAAG,OAAO,KAAK,KAAK,cAAc;AACjG,qBAAe,OAAOA,MAAK,EAAE,GAAG,UAAU,OAAOA,KAAI,KAAK,OAAO;AAAA,IACnE;AAAA,EACF;AAGA,MAAI,UAAU,SAAS;AACrB,UAAM,aAAa,UAAU;AAC7B,QAAI,CAAC,eAAe,WAAY,WAAW,WAAW,eAAe,QAAQ,QAAS;AACpF,qBAAe,UAAU,KAAK,MAAM,KAAK,UAAU,UAA4B,CAAC;AAAA,IAClF,OAAO;AACL,eAASA,KAAI,GAAGA,KAAI,WAAW,QAAQA,MAAK;AAC1C,uBAAe,QAAQA,IAAG,MAAO,WAAWA,IAAG,IAC5C,IAAI,CAAC,KAAK,QAAQ,iBAAiB,KAAK,eAAe,QAAQA,IAAG,IAAI,KAAK,OAAO,cAAc;AAAA,MACrG;AAAA,IACF;AAAA,EACF;AAGA,MAAI,UAAU;AAAS,mBAAe,UAAU,UAAU;AAG1D,QAAM,KAAK,IAAI;AACf,oBAAkBY,KAAI,UAAU,kBAAkB,KAAK,MAAM,KAAK,EAAE,IAAI,KAAK,MAAM,KAAK,EAAE;AAC1F,MAAI,UAAU;AAAa,mBAAe,cAAc,EAAE,GAAG,UAAU,aAAa,aAAa,gBAAgB;AAEjH,SAAO;AACT;;;ACvLA;AAAA;AAAA;AAAA,eAAAC;AAAA,EAAA;AAAA;AAWO,SAAS,SAAS,aAAyB,aAAyBC,WAAwB,EAAE,OAAO,GAAG,YAAY,GAAG,GAAG;AAE/H,MAAIC,OAAM;AACV,WAASC,KAAI,GAAGA,KAAI,YAAY,QAAQA,MAAK;AAC3C,UAAM,OAAQ,CAACF,SAAQ,SAASA,SAAQ,UAAU,IAAM,YAAYE,MAAK,YAAYA,MAAO,KAAK,IAAI,YAAYA,MAAK,YAAYA,GAAE;AACpI,IAAAD,QAAQ,CAACD,SAAQ,SAASA,SAAQ,UAAU,IAAM,OAAO,OAAS,QAAQA,SAAQ;AAAA,EACpF;AACA,UAAQA,SAAQ,cAAc,MAAMC;AACtC;AAGA,IAAM,oBAAoB,CAAC,MAAM,OAAOE,MAAKC,SAAQ;AACnD,MAAI,SAAS;AAAG,WAAO;AACvB,QAAM,OAAO,UAAU,IAAI,KAAK,KAAK,IAAI,IAAI,SAAS,IAAI;AAC1D,QAAMC,SAAQ,IAAK,OAAO,MAAOF,SAAQC,OAAMD;AAC/C,QAAMG,SAAQ,KAAK,IAAI,KAAK,IAAID,OAAM,CAAC,GAAG,CAAC;AAC3C,SAAOC;AACT;AAaO,SAAS,WAAW,aAAyB,aAAyBN,WAAwB,EAAE,OAAO,GAAG,YAAY,IAAI,KAAK,KAAK,KAAK,IAAI,GAAG;AACrJ,QAAM,OAAO,SAAS,aAAa,aAAaA,QAAO;AACvD,SAAO,kBAAkB,MAAMA,SAAQ,SAAS,GAAGA,SAAQ,OAAO,GAAGA,SAAQ,OAAO,CAAC;AACvF;AAWO,SAASD,OAAM,YAAwB,aAAgCC,WAAwB,EAAE,OAAO,GAAG,YAAY,IAAI,WAAW,GAAG,KAAK,KAAK,KAAK,IAAI,GAAG;AACpK,MAAI,CAAC,MAAM,QAAQ,UAAU,KAAK,CAAC,MAAM,QAAQ,WAAW,KAAK,WAAW,SAAS,MAAM,YAAY,WAAW,KAAK,WAAW,WAAW,YAAY,GAAG,QAAQ;AAClK,WAAO,EAAE,OAAO,IAAI,UAAU,OAAO,mBAAmB,YAAY,EAAE;AAAA,EACxE;AACA,MAAI,iBAAiB,OAAO;AAC5B,MAAIO,SAAQ;AACZ,WAASL,KAAI,GAAGA,KAAI,YAAY,QAAQA,MAAK;AAC3C,UAAM,MAAM,SAAS,YAAY,YAAYA,KAAIF,QAAO;AACxD,QAAI,MAAM,gBAAgB;AACxB,uBAAiB;AACjB,MAAAO,SAAQL;AAAA,IACV;AACA,QAAI,kBAAkBF,SAAQ,aAAa;AAAI;AAAA,EACjD;AACA,QAAM,uBAAuB,kBAAkB,gBAAgBA,SAAQ,SAAS,GAAGA,SAAQ,OAAO,GAAGA,SAAQ,OAAO,CAAC;AACrH,SAAO,EAAE,OAAAO,QAAO,UAAU,gBAAgB,YAAY,qBAAqB;AAC7E;;;ACjEO,SAASC,MAAK,OAA0B,QAA2B,OAA0B,UAAgC,OAAuD;AAN3L;AAOE,MAAI,KAAK;AACT,QAAM,UAA+B,CAAC;AACtC,aAAWC,SAAQ,OAAO;AACxB,UAAMC,UAAuB,EAAE,IAAI,MAAM,MAAAD,OAAM,MAAM,MAAM,OAAO,EAAE,MAAM,MAAM,OAAO,KAAK,GAAG,UAAU,CAAC,GAAG,KAAK,CAAC,GAAG,GAAG,GAAG,CAAC,EAAE;AAC/H,eAAWE,SAAQ,QAAQ;AACzB,UAAIF,MAAK,IAAI,KAAKE,MAAK,IAAI,MACtBF,MAAK,IAAI,KAAKE,MAAK,IAAI,KAAKA,MAAK,IAAI,MACrCF,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKE,MAAK,IAAI,MACrCF,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKE,MAAK,IAAI,KAAKA,MAAK,IAAI,IAAI;AAC1D,QAAAD,QAAO,OAAOC;AAAA,MAChB;AAAA,IACF;AACA,QAAID,QAAO,MAAM;AACf,iBAAWE,SAAQ,OAAO;AACxB,YAAIA,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,MAC3CE,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,KAAKA,QAAO,KAAK,IAAI,MACjEE,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,MAC5CE,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,KAAKA,QAAO,KAAK,IAAI,IAAI;AACxE,cAAIA,QAAO;AAAO,YAAAA,QAAO,MAAM,OAAOE;AAAA,QACxC;AACA,YAAIA,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,KAAKA,QAAO,KAAK,IAAI,MAClDE,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,MAC9BE,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,MAC5CE,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,KAAKA,QAAO,KAAK,IAAI,IAAI;AACxE,cAAIA,QAAO;AAAO,YAAAA,QAAO,MAAM,QAAQE;AAAA,QACzC;AAAA,MACF;AAAA,IACF;AACA,eAAWC,YAAW,UAAU;AAC9B,UAAIA,SAAQ,YAAY,UAAaA,SAAQ,YAAYJ,MAAK;AAAI,cAAAC,QAAO,aAAP,mBAAiB,KAAKG;AAAA,eAC/EA,SAAQ,YAAY,UAAaA,SAAQ,YAAYJ,MAAK;AAAI,cAAAC,QAAO,aAAP,mBAAiB,KAAKG;AAAA,eACpFA,SAAQ,YAAY,UAAaA,SAAQ,cAAY,KAAAH,QAAO,SAAP,mBAAa;AAAI,cAAAA,QAAO,aAAP,mBAAiB,KAAKG;AAAA,eAC5FA,SAAQ,YAAY,UAAaA,SAAQ,cAAY,WAAAH,QAAO,UAAP,mBAAc,SAAd,mBAAoB;AAAI,cAAAA,QAAO,aAAP,mBAAiB,KAAKG;AAAA,eACnGA,SAAQ,YAAY,UAAaA,SAAQ,cAAY,WAAAH,QAAO,UAAP,mBAAc,UAAd,mBAAqB;AAAI,cAAAA,QAAO,aAAP,mBAAiB,KAAKG;AAAA,IAC/G;AAGA,UAAM,IAAc,CAAC;AACrB,UAAM,IAAc,CAAC;AACrB,UAAM,YAAY,CAAC,QAAyB;AAC1C,UAAI,OAAO,IAAI,WAAW,GAAG;AAC3B,UAAE,KAAK,IAAI,IAAI,IAAI,KAAK,IAAI,EAAE;AAC9B,UAAE,KAAK,IAAI,IAAI,IAAI,KAAK,IAAI,EAAE;AAAA,MAChC;AAAA,IACF;AACA,eAAU,KAAAH,QAAO,SAAP,mBAAa,GAAG;AAC1B,eAAU,KAAAA,QAAO,SAAP,mBAAa,GAAG;AAC1B,eAAU,WAAAA,QAAO,UAAP,mBAAc,SAAd,mBAAoB,GAAG;AACjC,eAAU,WAAAA,QAAO,UAAP,mBAAc,UAAd,mBAAqB,GAAG;AAClC,UAAM,OAAO,KAAK,IAAI,GAAG,CAAC;AAC1B,UAAM,OAAO,KAAK,IAAI,GAAG,CAAC;AAC1B,IAAAA,QAAO,MAAM,CAAC,MAAM,MAAM,KAAK,IAAI,GAAG,CAAC,IAAI,MAAM,KAAK,IAAI,GAAG,CAAC,IAAI,IAAI;AAGtE,QAAI,SAAS,MAAM,MAAM,MAAM;AAAI,MAAAA,QAAO,SAAS,CAACA,QAAO,IAAI,KAAK,MAAM,IAAIA,QAAO,IAAI,KAAK,MAAM,IAAIA,QAAO,IAAI,KAAK,MAAM,IAAIA,QAAO,IAAI,KAAK,MAAM,EAAE;AAE1J,YAAQ,KAAKA,OAAM;AAAA,EACrB;AACA,SAAO;AACT;;;AC7DO,IAAMI,QAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AA0Jb,IAAMC,QAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;;;ACjJpB,eAAe,aAAa,UAA8C;AACxE,QAAM,YAAY,CAAC,QAAgB,OAAO,+BAA+B,MAAM,QAAQ,eAAe,QAAQ,EAAE,KAAK,CAACC,SAAQA,KAAI,KAAK,CAAC;AACxI,MAAI;AACJ,MAAI;AACJ,UAAQ,SAAS,OAAO;AAAA,SACjB;AAAQ,aAAO,MAAM,UAAiBC,KAAI;AAAG;AAAA,SAC7C;AAAA,SACA;AAAQ,aAAO,MAAM,UAAiBC,KAAI;AAAG;AAAA;AACzC,aAAO;AAAA;AAElB,MAAI,MAAM;AACR,UAAM,SAAS,MAAM,kBAAkB,IAAI;AAC3C,UAAM,MAAM,SAAS,OAAO,QAAQ,SAAS,MAAM;AACnD,WAAO,MAAM;AAAA,EACf;AACA,SAAO;AACT;AAEA,eAAe,aAAa,UAA8C;AACxE,SAAO,IAAI,QAAQ,CAAC,YAAY;AAC9B,QAAI;AAEJ,YAAQ,SAAS,OAAO;AAAA,WACjB;AAEH,cAAM,4BAAmCD;AACzC;AAAA,WACG;AAAA,WACA;AAEH,cAAM,4BAAmCC;AACzC;AAAA;AAEA,cAAM;AAAA;AAGV,QAAI;AACJ,QAAI,OAAO,UAAU;AAAa,YAAM,IAAI,MAAM;AAAA,aAEzCC,KAAI;AAAO,YAAM,IAAIA,KAAI,MAAM;AAAA;AACnC;AACL,QAAI,SAAS,YAAY;AACvB,YAAMC,UAAe,OAAO,IAAI,cAAc,IAAI,aAAa;AAC/D,UAAI,CAACA,SAAQ;AACX,YAAI,0BAA0B;AAC9B,gBAAQ,MAAS;AAAA,MACnB,OAAO;AACL,cAAM,MAAMA,QAAO,WAAW,IAAI;AAClC,YAAI;AAAK,cAAI,UAAU,KAAK,GAAG,CAAC;AAEhC,cAAMC,UAAS,MAAM,SAAS,MAAMD,OAAM;AAC1C,cAAM,MAAM,MAAM,SAAS,OAAOC,QAAO,QAAkB,SAAS,MAAM;AAC1E,gBAAQ,GAAG;AAAA,MACb;AAAA,IACF;AACA,QAAI;AAAK,UAAI,MAAM;AAAA;AACd,cAAQ,MAAS;AAAA,EACxB,CAAC;AACH;AAEA,eAAe,WAAW,UAA8C;AACtE,QAAMC,QAAO,CAAC,QAAgB,OAAO,KAAK,KAAK,QAAQ;AACvD,MAAI;AACJ,MAAI,SAAS,OAAO,WAAW;AAAQ,UAAMA,MAAYL,KAAI;AAAA;AACxD,UAAMK,MAAYJ,KAAI;AAC3B,MAAI;AACJ,MAAI,UAAU,kBAAI;AAEhB,UAAM,OAAU,SAAQ,WAAW,GAAG;AACtC,UAAM,WAAW,KAAK,WAAW,CAAC;AAClC,aAAS,GAAG,QAAQ,IAAI;AAExB,UAAM,MAAM,SAAS,OAAO,UAAU,SAAS,MAAM;AACrD,aAAS,GAAG,QAAQ,QAAQ;AAAA,EAC9B,OAAO;AACL,QAAI,SAAS,OAAO;AAAO,UAAI,6BAA6B;AAAA,EAQ9D;AACA,SAAO;AACT;AAEA,eAAe,aAAa,UAAiB;AAC3C,MAAI;AACJ,MAAI,OAAO,sBAAsB;AAAY,UAAM,MAAM,aAAa,QAAQ;AAAA,WACrE,OAAO,UAAU,eAAeC,KAAI,WAAW;AAAW,UAAM,MAAM,aAAa,QAAQ;AAAA;AAC/F,UAAM,MAAM,WAAW,QAAQ;AACpC,SAAO;AACT;AAGA,eAAsB,WAAW,WAAmB;AAClD,QAAM,cAAiB,WAAW;AAClC,QAAM,eAAkB,QAAQ;AAChC,MAAK,gBAAgB,WAAW,gBAAgB,cAAe,CAAC,gBAAgB,CAAC,aAAa,yBAAyB;AAErH;AAAA,EACF;AACA,EAAG,IAAI,EAAE,IAAI,uBAAuB,IAAI;AACxC,QAAM,kBAAqB,OAAO,EAAE,MAAM;AAC1C,QAAM,iBAA2B,CAAC;AAClC,aAAW,CAAC,WAAWI,OAAK,KAAK,OAAO,QAAQ,SAAS,EAAE,OAAO,CAAC,CAAC,KAAK,GAAG,MAAO,QAAQ,QAAQ,QAAQ,IAAK,GAAG;AACjH,UAAM,QAASA,QAAM,UAAUA,QAAM,OAAO,MAAMA,QAAM,OAAO,GAAG,QAAS,CAAC,GAAGA,QAAM,OAAO,GAAG,KAAK,IAAI,CAAC,GAAG,IAAI,IAAI,CAAC;AACrH,UAAM,QAASA,QAAM,UAAUA,QAAM,OAAO,MAAMA,QAAM,OAAO,GAAG,QAASA,QAAM,OAAO,GAAG,QAAQ;AACnG,aAAS,MAAM,GAAG,MAAM,MAAM,QAAQ,OAAO;AAC3C,UAAI,MAAM,SAAS;AAAI,cAAM,OAAO,QAAQ,IAAI,IAAI;AAAA,IACtD;AACA,UAAMF,UAAY,MAAM,OAAO,KAAK;AAEpC,QAAI;AACF,YAAM,MAAME,QAAM,QAAQF,OAAM;AAChC,qBAAe,KAAK,SAAS;AAC7B,UAAI,MAAM,QAAQ,GAAG;AAAG,YAAI,QAAQ,CAACG,OAAS,QAAQA,EAAC,CAAC;AAAA;AACnD,QAAG,QAAQ,GAAG;AAAA,IACrB,SAAQC,IAAN;AACA,UAAI,uBAAuB,SAAS;AAAA,IACtC;AACA,IAAG,QAAQJ,OAAM;AAAA,EACnB;AACA,QAAM,UAAU,MAAM,aAAa,4BAA4B;AAC/D,eAAa,oBAAoB;AACjC,MAAI,wBAAwB,cAAc;AAC1C,MAAI,yBAAyB,QAAQ,MAAM;AAC3C,EAAG,IAAI,EAAE,IAAI,uBAAuB,KAAK;AACzC,QAAM,gBAAmB,OAAO,EAAE,MAAM;AACxC,MAAK,gBAAgB,kBAAmB;AAAG,QAAI,gBAAgB,gBAAgB,eAAe;AAChG;AAOA,eAAsB,OAAO,UAAiB,YAA2D;AACvG,QAAM,KAAK,IAAI;AACf,WAAS,QAAQ;AACjB,MAAI;AAAY,aAAS,SAAS,UAAU,SAAS,QAAQ,UAAU;AACvE,MAAI,CAAC,SAAS,OAAO,UAAU,SAAS,OAAO,OAAO,WAAW,KAAK,SAAS,OAAO,WAAW,QAAQ;AACvG,WAAO,EAAE,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,SAAS,CAAC,GAAG,QAAQ,CAAC,GAAG,aAAa,SAAS,aAAa,WAAW,IAAI,GAAG,SAAS,CAAC,GAAG,OAAO,KAAK;AAAA,EAChJ;AACA,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,UAAM,WAAW,SAAS,MAAM;AAChC,UAAM,MAAM,MAAM,aAAa,QAAQ;AACvC,UAAM,KAAK,IAAI;AACf,QAAI,SAAS,OAAO;AAAO,UAAI,UAAU,SAAS,OAAO,QAAQ,KAAK,MAAM,KAAK,EAAE,GAAG,IAAI;AAC1F,aAAS,KAAK,QAAQ;AACtB,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;ACvKA;AAsDO,IAAM,QAAN,MAAY;AAAA,EAuEjB,YAAY,YAA8B;AArE1C;AAKA;AAKA;AAMA;AAGA;AAMA;AAGA;AAOA;AAMA;AAWA;AAEA;AAEA;AAEA;AACA;AACA;AACA;AAEA;AA2DA,mCAAU,IAAI,QAAkB;AAC9B,UAAI,CAAC,mBAAK;AAAqB;AAC/B,YAAM,iBAAiB,KAAK,GAAG,OAAO,EAAE,MAAM;AAC9C,YAAM,kBAAkB,mBAAK;AAC7B,yBAAK,aAAc;AACnB,YAAM,SAAS,iBAAiB;AAChC,UAAI,WAAW;AAAG,YAAI,GAAG,KAAK,MAAM;AAAA,IACtC;AAGA,gCAAU,CAACK,WAAgC;AACzC,UAAI,CAAC,mBAAK;AAAc,eAAO;AAC/B,UAAI,CAACA;AAAO,eAAO;AACnB,UAAI,KAAK,IAAI,QAAQ,EAAEA,kBAAoB;AAAS,eAAO;AAC3D,UAAI;AACF,aAAK,GAAG,WAAW;AAAA,MACrB,SAAQC,IAAN;AACA,eAAO;AAAA,MACT;AACA,aAAO;AAAA,IACT;AAeA,wBAAO,cAAmB;AAE1B,wBAAO,YAAiB;AAExB,wBAAO,SAAcC;AAoGrB,gCAAO,CAAC,UAAkB;AA7T5B;AA8TI,UAAI,KAAK,UAAU,KAAK,OAAO;AAAe,mBAAK,WAAL,mBAAa,cAAc,IAAI,MAAM,KAAK;AAAA,IAC1F;AA/TF;AA8HI,SAAK,MAAMC;AAMX,UAAM,eAAa,KAAG,MAAH,mBAAY,SAAW,SAAc,QAAQ,SAAS,EAAE;AAC3E,WAAS,WAAW,8DAA8D;AAClF,WAAS,gBAAgBA,KAAI,UAAU,eAAe;AACtD,WAAS,UAAUA,KAAI,UAAU,YAAY;AAC7C,SAAK,UAAcC;AACnB,WAAO,eAAe,MAAM,WAAW,EAAE,OAAWA,SAAQ,CAAC;AAC7D,SAAK,SAAS,KAAK,MAAM,KAAK,UAAU,MAAQ,CAAC;AACjD,WAAO,KAAK,KAAK,MAAM;AACvB,SAAK,OAAO,cAAc,OAAO,cAAc;AAC/C,QAAI;AAAY,WAAK,SAAS,UAAU,KAAK,QAAQ,UAAU;AAC/D,wBAAoB,KAAK,MAAM;AAC/B,SAAK,KAAK;AACV,SAAK,QAAQ;AACb,uBAAK,aAAc;AACnB,uBAAK,qBAAsB;AAC3B,uBAAK,cAAe;AACpB,SAAK,cAAc,CAAC;AACpB,SAAK,SAAU,OAAO,gBAAgB,cAAe,IAAI,YAAY,IAAI;AAEzE,SAAK,SAAS,IAAW,OAAO;AAEhC,SAAK,OAAO;AAAA,MACV,SAAcC;AAAA,MACd,QAAQ,CAACL,QAAwD,WAA2BM,QAAON,QAAO,MAAM;AAAA,MAChH,MAAM,CAAC,QAAmB,QAAsBK,aAAwC,KAAK,QAAQ,QAAQA,QAAO;AAAA,MACpH,MAAM,CAAC,QAAmB,QAAsBA,aAAwC,KAAK,QAAQ,QAAQA,QAAO;AAAA,MACpH,MAAM,CAAC,QAAmB,QAAsBA,aAAwC,KAAK,QAAQ,QAAQA,QAAO;AAAA,MACpH,SAAS,CAAC,QAAmB,QAAyBA,aAAwC,QAAQ,QAAQ,QAAQA,QAAO;AAAA,MAC7H,QAAQ,CAAC,QAAmB,QAAwBA,aAAwC,OAAO,QAAQ,QAAQA,QAAO;AAAA,MAC1H,QAAQ,CAAC,QAAmB,QAAwBA,aAAwC,OAAO,QAAQ,QAAQA,QAAO;AAAA,MAC1H,KAAK,CAAC,QAAmB,QAAgBA,aAAwCE,KAAI,QAAQ,QAAQF,QAAO;AAAA,IAC9G;AACA,SAAK,SAAS,EAAE,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,SAAS,CAAC,GAAG,QAAQ,CAAC,GAAG,aAAa,CAAC,GAAG,WAAW,GAAG,SAAS,CAAC,GAAG,OAAO,KAAK;AAG/H,SAAK,UAAU,EAAE,QAAQ,MAAM,QAAQ,KAAK;AAE5C,SAAK,oBAA6B;AAClC,SAAK,YAAqB;AAE1B,SAAK,KAAaG;AAElB,SAAK,KAAK,QAAQ;AAAA,EACpB;AAAA,EA0BA,QAAc;AACZ,UAAM,iBAAiB,KAAK,OAAO;AACnC,SAAK,SAAS,KAAK,MAAM,KAAK,UAAU,MAAQ,CAAC;AACjD,SAAK,OAAO,UAAU;AAAA,EACxB;AAAA,EAGA,SAAS,YAA8B;AACrC,WAAO,SAAS,QAAU,cAAc,KAAK,MAAM;AAAA,EACrD;AAAA,EAUA,MAAc;AACZ,WAAO,IAAI;AAAA,EACb;AAAA,EAQA,MAAMR,QAAcS,aAAqB,MAAM;AAC7C,WAAaC,SAAQV,QAAO,KAAK,QAAQS,UAAS;AAAA,EACpD;AAAA,EAYA,MAAM,aAAaT,QAAc,YAA6G;AAC5I,WAAoBU,SAAQV,QAAO,YAAY,KAAK,MAAM;AAAA,EAC5D;AAAA,EAQA,QAAQA,QAA8B;AACpC,WAAe,QAAQA,MAAK;AAAA,EAC9B;AAAA,EASA,QAAQ,kBAA0B,mBAA4C;AAC5E,WAAa,QAAQ,KAAK,QAAQ,kBAAkB,iBAAiB;AAAA,EACvE;AAAA,EAOA,MAAM,OAAsB;AAC1B,UAAc,MAAM,MAAM,IAAI;AAC9B,UAAM,KAAK,GAAG,MAAM;AAAA,EACtB;AAAA,EAOA,MAAM,KAAK,YAA6C;AACtD,SAAK,QAAQ;AACb,UAAM,YAAY,IAAI;AACtB,UAAMW,SAAQ,OAAO,OAAO,KAAK,MAAM,EAAE,OAAO,CAACC,YAAUA,OAAK,EAAE;AAClE,QAAI;AAAY,WAAK,SAAS,UAAU,KAAK,QAAQ,UAAU;AAE/D,QAAI,KAAK,IAAI,SAAS;AACpB,UAAI,KAAK,OAAO;AAAO,YAAI,YAAY,KAAK,SAAS;AACrD,UAAI,KAAK,OAAO;AAAO,YAAI,iBAAiB,KAAK,GAAG,QAAQ,cAAc;AAC1E,UAAI,CAAC,MAAc,MAAM,IAAI;AAAG,YAAI,6BAA6B;AACjE,YAAS,MAAM;AACf,UAAI,KAAK,IAAI,SAAS;AACpB,YAAI,KAAK,OAAO;AAAO,cAAI,kBAAkB,KAAK,MAAM;AACxD,YAAI,KAAK,OAAO;AAAO,cAAI,gBAAgB,KAAK,GAAG;AACnD,YAAI,KAAK,OAAO;AAAO,cAAI,aAAa,KAAK,GAAG,IAAI,QAAQ;AAAA,MAC9D;AAAA,IACF;AAEA,UAAaC,OAAK,IAAI;AACtB,QAAI,KAAK,IAAI,WAAW,KAAK,OAAO;AAAO,UAAI,oBAAoB,KAAK,GAAG,OAAO,EAAE,MAAM,UAAU,SAAS,KAAK,GAAG,OAAO,EAAE,MAAM,YAAY,SAAS;AACzJ,SAAK,IAAI,UAAU;AAEnB,UAAM,SAAS,OAAO,OAAO,KAAK,MAAM,EAAE,OAAO,CAACD,YAAUA,OAAK,EAAE;AACnE,QAAI,WAAWD,QAAO;AACpB,YAAaG,UAAS,IAAI;AAC1B,WAAK,KAAK,MAAM;AAAA,IAClB;AAEA,UAAM,UAAU,KAAK,MAAM,IAAI,IAAI,SAAS;AAC5C,QAAI,WAAW,KAAK,YAAY,cAAwB;AAAI,WAAK,YAAY,aAAa,KAAK,IAAI,WAAW,KAAK,YAAY,cAAc,KAAK,UAAU;AAAA,EAC9J;AAAA,EAaA,KAAK,SAAiB,KAAK,QAAgB;AACzC,WAAmBC,MAAK,QAAQ,KAAK,MAAM;AAAA,EAC7C;AAAA,EAGA,gBAA4B;AAAE,WAAc,cAAc,IAAI;AAAA,EAAG;AAAA,EAQjE,MAAM,OAAO,YAA8B;AACzC,UAAM,KAAK,IAAI;AACf,UAAM,MAAM,MAAc,OAAO,MAAM,UAAU;AACjD,UAAM,KAAK,IAAI;AACf,SAAK,YAAY,SAAS,KAAK,MAAM,KAAK,EAAE;AAC5C,WAAO;AAAA,EACT;AAAA,EAMA,MAAM,QAAQf,QAAc,YAA+D;AACzF,UAAMgB,WAAU,MAAM,KAAK,GAAG,QAAQ,MAAM,KAAK,OAAOhB,QAAO,UAAU,CAAC;AAC1E,UAAM,UAAkC,CAAC;AACzC,eAAW,UAAUgB,SAAQ,SAAS;AACpC,UAAI,QAAQ,OAAO;AAAO,gBAAQ,OAAO,SAAS,OAAO;AAAA;AACpD,gBAAQ,OAAO,QAAQ,OAAO;AAAA,IACrC;AACA,UAAM,YAAiD,CAAC;AACxD,WAAO,QAAQ,OAAO,EAAE,QAAQ,CAAC,QAAQ,UAAU,KAAK,EAAE,MAAM,IAAI,IAAI,IAAI,IAAI,GAAwB,CAAC,CAAC;AAC1G,cAAU,KAAK,CAAC,GAAG,MAAM,EAAE,KAAK,EAAE,EAAE;AACpC,cAAU,SAAS;AACnB,UAAM,MAA8B,CAAC;AACrC,eAAW,UAAU;AAAW,UAAI,OAAO,QAAQ,OAAO;AAC1D,WAAO;AAAA,EACT;AAAA,EAYA,MAAM,OAAOhB,QAAc,YAA+C;AAExE,SAAK,QAAQ;AACb,WAAO,IAAI,QAAQ,OAAO,YAAY;AA7X1C;AA8XM,WAAK,QAAQ;AACb,UAAI;AAGJ,WAAK,SAAS,UAAU,KAAK,QAAQ,UAAU;AAG/C,WAAK,QAAQ;AACb,YAAM,QAAQ,mBAAK,SAAL,WAAaA;AAC3B,UAAI,OAAO;AACT,YAAI,OAAOA,MAAK;AAChB,aAAK,KAAK,OAAO;AACjB,gBAAQ,EAAE,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,SAAS,CAAC,GAAG,QAAQ,CAAC,GAAG,aAAa,KAAK,aAAa,WAAW,IAAI,GAAG,SAAS,CAAC,GAAG,MAAM,CAAC;AAAA,MACxI;AAEA,YAAM,YAAY,IAAI;AAGtB,YAAc,MAAM,IAAI;AAGxB,YAAM,KAAK,KAAK;AAEhB,kBAAY,IAAI;AAChB,WAAK,QAAQ;AACb,YAAM,MAAM,MAAYU,SAAQV,QAAO,KAAK,MAAM;AAClD,WAAK,UAAU;AACf,WAAK,YAAY,eAAe,KAAK,IAAI,WAAW,KAAK,YAAY,gBAAgB,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AACtJ,WAAK,QAAQ,YAAY;AAEzB,UAAI,CAAC,IAAI,QAAQ;AACf,YAAI,KAAK,OAAO;AAAO,cAAI,mCAAmC;AAC9D,aAAK,KAAK,OAAO;AACjB,gBAAQ,EAAE,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,SAAS,CAAC,GAAG,QAAQ,CAAC,GAAG,aAAa,KAAK,aAAa,WAAW,IAAI,GAAG,SAAS,CAAC,GAAG,OAAO,oCAAoC,CAAC;AAC3K;AAAA,MACF;AACA,WAAK,KAAK,OAAO;AAEjB,kBAAY,IAAI;AAChB,WAAK,OAAO,cAAc,MAAY,KAAK,KAAK,QAAQ,IAAI,MAAM;AAClE,UAAI,CAAC,KAAK,YAAY;AAAa,aAAK,YAAY,cAAc;AAClE,UAAI,CAAC,KAAK,YAAY;AAAc,aAAK,YAAY,eAAe;AACpE,MAAC,KAAK,YAAY;AAClB,UAAI,KAAK,OAAO;AAAa,aAAK,YAAY;AAC9C,WAAK,YAAY,aAAa,KAAK,IAAI,WAAW,KAAK,YAAY,cAAc,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAClJ,WAAK,QAAQ,gBAAgB;AAI7B,UAAI,UAA0D,CAAC;AAC/D,UAAI,UAA0D,CAAC;AAC/D,UAAI,UAA0D,CAAC;AAC/D,UAAI,YAAgE,CAAC;AAGrE,WAAK,QAAQ;AACb,UAAI,KAAK,OAAO,OAAO;AACrB,kBAAU,KAAK,OAAO,KAAK,UAAe,WAAW,MAAM,IAAI,MAAM,IAAI,CAAC;AAC1E,YAAI,KAAK,YAAY;AAAM,iBAAO,KAAK,YAAY;AAAA,MACrD,OAAO;AACL,oBAAY,IAAI;AAChB,kBAAU,KAAK,OAAO,KAAK,UAAU,MAAW,WAAW,MAAM,IAAI,MAAM,IAAI,CAAC;AAChF,aAAK,YAAY,OAAO,KAAK,IAAI,WAAW,KAAK,YAAY,QAAQ,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,MACxI;AAEA,UAAI,KAAK,OAAO,UAAU,KAAK,OAAO,KAAK,gBAAgB,MAAM,KAAK,OAAO,KAAK,gBAAgB;AAAK,kBAAU,MAAM;AAGvH,WAAK,QAAQ,aAAa;AAC1B,WAAK,QAAQ;AACb,YAAM,aAAa,KAAK,OAAO,KAAK,gBAAgB,KAAK,UAAU,KAAK,QAAQ,EAAE,MAAM,EAAE,aAAa,KAAK,OAAO,KAAK,UAAU,IAAK,QAAyB,SAAS,EAAE,EAAE,CAAC,IAAI,KAAK;AACvL,UAAI,KAAK,OAAO,OAAO;AACrB,aAAI,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAY,oBAAU,KAAK,OAAO,KAAK,UAAkBiB,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBAC5H,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAc,oBAAU,KAAK,OAAO,KAAK,UAAoBA,SAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBACrI,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAkB,oBAAU,KAAK,OAAO,KAAK,UAAwBA,SAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBAC7I,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAY,oBAAU,KAAK,OAAO,KAAK,UAAkBA,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAC1I,YAAI,KAAK,YAAY;AAAM,iBAAO,KAAK,YAAY;AAAA,MACrD,OAAO;AACL,oBAAY,IAAI;AAChB,aAAI,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAY,oBAAU,KAAK,OAAO,KAAK,UAAU,MAAcA,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBAClI,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAc,oBAAU,KAAK,OAAO,KAAK,UAAU,MAAgBA,SAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBAC3I,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAkB,oBAAU,KAAK,OAAO,KAAK,UAAU,MAAoBA,SAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBACnJ,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAY,oBAAU,KAAK,OAAO,KAAK,UAAU,MAAcA,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAChJ,aAAK,YAAY,OAAO,KAAK,IAAI,WAAW,KAAK,YAAY,QAAQ,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,MACxI;AACA,WAAK,QAAQ,WAAW;AAGxB,WAAK,QAAQ,aAAa;AAC1B,WAAK,QAAQ;AACb,YAAM,aAAa,KAAK,OAAO,KAAK,gBAAgB,KAAK,UAAU,KAAK,QAAQ,EAAE,MAAM,EAAE,aAAa,KAAK,OAAO,KAAK,UAAU,IAAK,QAAyB,SAAS,EAAE,EAAE,CAAC,IAAI,KAAK;AACvL,UAAI,KAAK,OAAO,OAAO;AACrB,aAAI,gBAAK,OAAO,KAAK,aAAjB,mBAA2B,cAA3B,mBAAsC,SAAS;AAAe,oBAAU,KAAK,OAAO,KAAK,UAAmBA,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBAC1I,gBAAK,OAAO,KAAK,aAAjB,mBAA2B,cAA3B,mBAAsC,SAAS;AAAc,oBAAU,KAAK,OAAO,KAAK,UAAoBA,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AACxJ,YAAI,KAAK,YAAY;AAAM,iBAAO,KAAK,YAAY;AAAA,MACrD,OAAO;AACL,oBAAY,IAAI;AAChB,aAAI,gBAAK,OAAO,KAAK,aAAjB,mBAA2B,cAA3B,mBAAsC,SAAS;AAAe,oBAAU,KAAK,OAAO,KAAK,UAAU,MAAeA,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBAChJ,gBAAK,OAAO,KAAK,aAAjB,mBAA2B,cAA3B,mBAAsC,SAAS;AAAc,oBAAU,KAAK,OAAO,KAAK,UAAU,MAAgBA,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAC9J,aAAK,YAAY,OAAO,KAAK,IAAI,WAAW,KAAK,YAAY,QAAQ,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,MACxI;AACA,WAAK,QAAQ,WAAW;AAGxB,WAAK,QAAQ,eAAe;AAC5B,WAAK,QAAQ;AACb,UAAI,KAAK,OAAO,OAAO;AACrB,aAAI,UAAK,OAAO,OAAO,cAAnB,mBAA8B,SAAS;AAAY,sBAAY,KAAK,OAAO,OAAO,UAAkBA,UAAQ,IAAI,QAAQ,KAAK,MAAM,IAAI,CAAC;AAAA,kBACnI,UAAK,OAAO,OAAO,cAAnB,mBAA8B,SAAS;AAAc,sBAAY,KAAK,OAAO,OAAO,UAAoBA,SAAQ,IAAI,QAAQ,KAAK,MAAM,IAAI,CAAC;AACrJ,YAAI,KAAK,YAAY;AAAQ,iBAAO,KAAK,YAAY;AAAA,MACvD,OAAO;AACL,oBAAY,IAAI;AAChB,aAAI,UAAK,OAAO,OAAO,cAAnB,mBAA8B,SAAS;AAAY,sBAAY,KAAK,OAAO,OAAO,UAAU,MAAcA,UAAQ,IAAI,QAAQ,KAAK,MAAM,IAAI,CAAC;AAAA,kBACzI,UAAK,OAAO,OAAO,cAAnB,mBAA8B,SAAS;AAAc,sBAAY,KAAK,OAAO,OAAO,UAAU,MAAgBA,SAAQ,IAAI,QAAQ,KAAK,MAAM,IAAI,CAAC;AAC3J,aAAK,YAAY,SAAS,KAAK,IAAI,WAAW,KAAK,YAAY,UAAU,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,MAC5I;AACA,WAAK,QAAQ,aAAa;AAG1B,WAAK,QAAQ;AACb,UAAI,KAAK,OAAO;AAAO,SAAC,SAAS,SAAS,SAAS,SAAS,IAAI,MAAM,QAAQ,IAAI,CAAC,SAAS,SAAS,SAAS,SAAS,CAAC;AAGxH,WAAK,QAAQ;AACb,UAAI,aAA8B,CAAC;AACnC,UAAI,KAAK,OAAO,QAAQ,SAAS;AAC/B,oBAAY,IAAI;AAChB,qBAAa,CAAC,GAAWC,MAAK,OAAuB,GAAG,GAAWC,MAAK,OAAuB,GAAG,GAAWC,MAAK,OAAuB,GAAG,GAAWC,MAAK,OAAuB,CAAC;AACpL,YAAI,CAAC,KAAK,OAAO;AAAO,eAAK,YAAY,UAAU,KAAK,IAAI,WAAW,KAAK,YAAY,WAAW,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,iBAC3J,KAAK,YAAY;AAAS,iBAAO,KAAK,YAAY;AAAA,MAC7D;AAEA,WAAK,YAAY,QAAQ,KAAK,IAAI,WAAW,KAAK,YAAY,SAAS,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AACxI,YAAM,UAAQ,gBAAK,YAAL,mBAAc,WAAd,mBAAsB,UAAS,CAAC;AAC9C,WAAK,SAAS;AAAA,QACZ,MAAM;AAAA,QACN,MAAM;AAAA,QACN,MAAM;AAAA,QACN,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,aAAa,KAAK;AAAA,QAClB,QAAQ,KAAK,QAAQ;AAAA,QACrB,WAAW,KAAK,IAAI;AAAA,QACpB,OAAO;AAAA,QACP,IAAI,UAAU;AAAE,iBAAeC,MAAK,SAAyB,SAAyB,SAAyB,YAAY,KAAK;AAAA,QAAG;AAAA,MACrI;AAGA,MAAG,QAAQ,IAAI,MAAM;AAGrB,WAAK,KAAK,QAAQ;AAClB,WAAK,QAAQ;AACb,cAAQ,KAAK,MAAM;AAAA,IACrB,CAAC;AAAA,EACH;AACF;AAvaE;AACA;AACA;AAuEA;",
-  "names": ["config", "log2", "__defProp", "__export", "all5", "cache", "size", "compare", "log22", "copy", "init2", "mask", "options", "count2", "now2", "index", "canvas", "object", "strides", "log", "config", "now", "node", "lines", "size2", "labels", "outputSize", "scale2", "alpha", "half", "middle", "labels2", "inputSize", "padding", "lastTime", "model2", "constants", "maxSize", "node2", "outputNodes", "match", "skipped", "strides2", "body", "r", "match", "index", "cos", "sin", "size", "s", "func", "image", "i", "squeeze", "min", "max", "sub", "range", "rgb", "reshape", "env", "input", "process", "config", "getTensor", "tensor", "rgb", "cast", "t", "e", "env", "init", "config", "e", "model", "models_exports", "load", "validate", "model", "last", "config", "env", "image", "count", "_a", "_b", "t", "gender", "i", "age", "tensor", "init", "model", "last", "lastCount", "lastTime", "skipped", "load", "config", "env", "predict", "image", "count", "t", "tensor", "model", "last", "lastCount", "lastTime", "skipped", "load", "config", "env", "predict", "image", "count", "t", "tensor", "model", "skipped", "lastCount", "lastTime", "load", "config", "env", "predict", "image", "count", "input", "image", "norm", "size", "dot", "i", "size", "inputSize", "anchors", "i", "n", "dot", "input", "face", "env", "model", "load", "config", "env", "t", "tensor", "i", "inputSize", "anchors", "outputSize", "coords", "min", "max", "square", "scale", "env", "inputSize", "skipped", "lastTime", "sigmoid", "config", "input", "size", "t", "tensor", "outputSize", "kpt", "config", "i", "sigmoid", "inputSize", "distance", "annotations", "body", "predict", "lastTime", "skipped", "model", "inputSize", "last", "lastTime", "skipped", "load", "config", "env", "process", "t", "i", "tensor", "predict", "input", "outputSize", "connected", "kpt", "model", "lastTime", "cache", "skipped", "load", "config", "env", "max", "mod", "div", "predict", "image", "tensor", "enhance", "norm", "squeeze", "stack", "x", "y", "kpt", "s", "connected", "i", "model", "last", "lastCount", "lastTime", "skipped", "load", "config", "env", "predict", "image", "count", "_a", "_b", "t", "inputSize", "i", "tensor", "model", "last", "lastCount", "lastTime", "skipped", "load", "config", "env", "predict", "input", "count", "_a", "t", "model", "inputSize", "load", "config", "env", "i", "index", "face", "connectionsToIndices", "index", "t", "r", "i", "cache", "model", "inputSize", "predict", "input", "config", "i", "face", "t", "index", "load", "env", "model", "last", "lastTime", "lastCount", "skipped", "load", "config", "env", "input", "tensor", "norm", "predict", "image", "count", "_a", "_b", "t", "gender", "argmax", "age", "all", "getBoxSize", "getBoxCenter", "image", "scaleBoxCoordinates", "enlargeBox", "size", "squarifyBox", "normalizeRadians", "computeRotation", "buildTranslationMatrix", "dot", "i", "getColumnFrom2DArr", "multiplyTransformMatrices", "size", "buildRotationMatrix", "invertTransformMatrix", "rotatePoint", "anchors", "model", "anchors", "t", "tensor", "index", "input", "config", "p", "hand", "scaleBoxCoordinates", "lastTime", "handPoseModel", "rotatePoint", "enlargeBox", "squarifyBox", "i", "getBoxSize", "buildRotationMatrix", "invertTransformMatrix", "getBoxCenter", "dot", "image", "config", "computeRotation", "env", "coords", "options", "point", "point2", "gesture", "meshAnnotations", "predict", "input", "config", "i", "annotations", "index", "load", "env", "models", "inputSize", "skipped", "lastTime", "cache", "loadDetect", "config", "env", "input", "config", "models", "t", "scale", "hand", "tensor", "inputSize", "kpt", "index", "predict", "skipped", "lastTime", "cache", "i", "square", "model", "cached", "skipped", "lastCount", "lastTime", "load", "config", "env", "predict", "image", "count", "connected", "kpt", "cache", "body", "compare", "i", "input", "inputSize", "t", "tensor", "outputSize", "kpt", "model", "inputSize", "skipped", "cache", "load", "config", "env", "image", "kpt", "annotations", "connected", "i", "body", "predict", "input", "t", "tensor", "model", "last", "lastTime", "skipped", "inputSize", "load", "config", "env", "process", "i", "t", "predict", "image", "outputSize", "norm", "transpose", "count", "i", "i", "maxSize", "max", "t", "count", "outputStride", "clamp", "min", "max", "model", "point", "height", "width", "clamp", "i", "minConfidence", "predict", "input", "config", "tensor", "t", "load", "env", "model", "load", "config", "env", "process", "input", "t", "tensor", "i", "model", "load", "env", "loadDetect", "validate", "op", "config", "e", "env", "op", "e", "init", "config", "all", "canvas", "options", "input", "opt", "rgb", "i", "options", "labels", "emotion", "i", "index", "inCanvas", "options", "inCanvas", "options", "i", "connected", "inCanvas", "options", "i", "inCanvas", "options", "inCanvas", "options", "i", "where", "inCanvas", "options", "i", "canvas", "input", "all", "env", "i", "face", "buffer", "face", "r", "size", "input", "predict", "env", "i", "tensor", "body", "i", "face", "iris", "hand", "calc", "config", "i", "_a", "_b", "_c", "_d", "_e", "_f", "_g", "_h", "_i", "annotations", "coords", "env", "match", "options", "sum", "i", "min", "max", "norm", "clamp", "index", "join", "face", "person", "body", "hand", "gesture", "face", "body", "res", "face", "body", "env", "canvas", "tensor", "atob", "model", "t", "e", "input", "e", "match", "env", "version", "options", "canvas", "all", "config", "getTensor", "process", "count", "model", "load", "validate", "calc", "profile", "predict", "face", "body", "hand", "iris", "join"]
+  "sourcesContent": ["import type { Config } from '../exports';\n\n/**\n * Simple helper functions used accross codebase\n */\n\n// helper function: wrapper around console output\nexport function log(...msg): void {\n  const dt = new Date();\n  const ts = `${dt.getHours().toString().padStart(2, '0')}:${dt.getMinutes().toString().padStart(2, '0')}:${dt.getSeconds().toString().padStart(2, '0')}.${dt.getMilliseconds().toString().padStart(3, '0')}`;\n  // eslint-disable-next-line no-console\n  if (msg) console.log(ts, 'Human:', ...msg);\n}\n\n// helper function: join two paths\nexport function join(folder: string, file: string): string {\n  const separator = folder.endsWith('/') ? '' : '/';\n  const skipJoin = file.startsWith('.') || file.startsWith('/') || file.startsWith('http:') || file.startsWith('https:') || file.startsWith('file:');\n  const path = skipJoin ? `${file}` : `${folder}${separator}${file}`;\n  if (!path.toLocaleLowerCase().includes('.json')) throw new Error(`modelpath error: expecting json file: ${path}`);\n  return path;\n}\n\n// helper function: gets elapsed time on both browser and nodejs\nexport const now = () => {\n  if (typeof performance !== 'undefined') return performance.now();\n  return parseInt((Number(process.hrtime.bigint()) / 1000 / 1000).toString());\n};\n\n// helper function: checks current config validity\nexport function validate(defaults: Partial<Config>, config: Partial<Config>, parent = 'config', msgs: Array<{ reason: string, where: string, expected?: string }> = []) {\n  for (const key of Object.keys(config)) {\n    if (typeof config[key] === 'object') {\n      validate(defaults[key], config[key], key, msgs);\n    } else {\n      const defined = defaults && (typeof defaults[key] !== 'undefined');\n      if (!defined) msgs.push({ reason: 'unknown property', where: `${parent}.${key} = ${config[key]}` });\n      const same = defaults && typeof defaults[key] === typeof config[key];\n      if (defined && !same) msgs.push({ reason: 'property type mismatch', where: `${parent}.${key} = ${config[key]}`, expected: typeof defaults[key] });\n    }\n    // ok = ok && defined && same;\n  }\n  if (config.debug && parent === 'config' && msgs.length > 0) log('invalid configuration', msgs);\n  return msgs;\n}\n\n// helper function: perform deep merge of multiple objects so it allows full inheritance with overrides\nexport function mergeDeep(...objects) {\n  const isObject = (obj) => obj && typeof obj === 'object';\n  return objects.reduce((prev, obj) => {\n    Object.keys(obj || {}).forEach((key) => {\n      const pVal = prev[key];\n      const oVal = obj[key];\n      if (Array.isArray(pVal) && Array.isArray(oVal)) prev[key] = pVal.concat(...oVal);\n      else if (isObject(pVal) && isObject(oVal)) prev[key] = mergeDeep(pVal, oVal);\n      else prev[key] = oVal;\n    });\n    return prev;\n  }, {});\n}\n\n// helper function: return min and max from input array\nexport const minmax = (data: Array<number>) => data.reduce((acc: Array<number>, val) => {\n  acc[0] = (acc[0] === undefined || val < acc[0]) ? val : acc[0];\n  acc[1] = (acc[1] === undefined || val > acc[1]) ? val : acc[1];\n  return acc;\n}, []);\n\n// helper function: async wait\nexport async function wait(time: number) {\n  const waiting = new Promise((resolve) => { setTimeout(() => resolve(true), time); });\n  await waiting;\n}\n", "/* eslint-disable indent */\n/* eslint-disable no-multi-spaces */\n\n/** Generic config type inherited by all module types */\nexport interface GenericConfig {\n  /** is module enabled? */\n  enabled: boolean,\n  /** path to model json file (relative to `modelBasePath` */\n  modelPath: string,\n  /** how many max frames to go without re-running model if cached results are acceptable\n   * for two-phase models such as face and hand caching applies to bounding boxes detection only */\n  skipFrames: number,\n  /** how many max milliseconds to go without re-running model if cached results are acceptable\n  * for two-phase models such as face and hand caching applies to bounding boxes detection only */\n  skipTime: number,\n}\n\n/** Detector part of face configuration */\nexport interface FaceDetectorConfig extends GenericConfig {\n  /** is face rotation correction performed after detecting face?\n   * used to correctly analyze faces under high angles\n  */\n  rotation: boolean,\n  /** maximum number of detected faces */\n  maxDetected: number,\n  /** minimum confidence for a detected face before results are discarded */\n  minConfidence: number,\n  /** minimum overlap between two detected faces before one is discarded */\n  iouThreshold: number,\n  /** should child models perform on masked image of a face */\n  mask: boolean,\n  /** should face detection return processed and cropped face tensor that can with an external model for addtional processing?\n   * if enabled it must be manually deallocated to avoid memory leak */\n  return: boolean,\n}\n\n/** Mesh part of face configuration */\nexport interface FaceMeshConfig extends GenericConfig {\n  /** Keep detected faces that cannot be verified using facemesh */\n  keepInvalid: boolean\n}\n\n/** Iris part of face configuration */\nexport interface FaceIrisConfig extends GenericConfig {}\n\n/** Attention part of face configuration */\nexport interface FaceAttentionConfig extends GenericConfig {}\n\n/** Description or face embedding part of face configuration\n * - also used by age and gender detection\n */\nexport interface FaceDescriptionConfig extends GenericConfig {\n  /** minimum confidence for a detected face before results are discarded */\n  minConfidence: number,\n}\n\n/** Emotion part of face configuration */\nexport interface FaceEmotionConfig extends GenericConfig {\n  /** minimum confidence for a detected face before results are discarded */\n  minConfidence: number,\n}\n\n/** Anti-spoofing part of face configuration */\nexport interface FaceAntiSpoofConfig extends GenericConfig {}\n\n/** Liveness part of face configuration */\nexport interface FaceLivenessConfig extends GenericConfig {}\n\n/** Gear part of face configuration */\nexport interface FaceGearConfig extends GenericConfig {\n  /** minimum confidence for a detected race before results are discarded */\n  minConfidence: number,\n}\n\n/** Configures all face-specific options: face detection, mesh analysis, age, gender, emotion detection and face description */\nexport interface FaceConfig extends GenericConfig {\n  detector: Partial<FaceDetectorConfig>,\n  mesh: Partial<FaceMeshConfig>,\n  attention: Partial<FaceAttentionConfig>,\n  iris: Partial<FaceIrisConfig>,\n  description: Partial<FaceDescriptionConfig>,\n  emotion: Partial<FaceEmotionConfig>,\n  antispoof: Partial<FaceAntiSpoofConfig>,\n  liveness: Partial<FaceLivenessConfig>,\n  gear: Partial<FaceGearConfig>,\n}\n\n/** Configures all body detection specific options */\nexport interface BodyConfig extends GenericConfig {\n  /** maximum number of detected bodies */\n  maxDetected: number,\n  /** minimum confidence for a detected body before results are discarded */\n  minConfidence: number,\n  /* experimental\n  /** experimental: detector used for body model before actual analysis\n  detector?: {\n    /** experimental: enable body detector before body landmarks\n    enabled: boolean,\n    /** experimental: path to optional body detector model json file\n    modelPath: string,\n    /** experimental: minimum confidence for a detected body before results are discarded\n    minConfidence: number,\n    /** experimental: minimum overlap between two detected bodies before one is discarded\n    iouThreshold: number\n  },\n  */\n}\n\n/** Configures all hand detection specific options */\nexport interface HandConfig extends GenericConfig {\n  /** should hand rotation correction be performed after hand detection? */\n  rotation: boolean,\n  /** minimum confidence for a detected hand before results are discarded */\n  minConfidence: number,\n  /** minimum overlap between two detected hands before one is discarded */\n  iouThreshold: number,\n  /** maximum number of detected hands */\n  maxDetected: number,\n  /** should hand landmarks be detected or just return detected hand box */\n  landmarks: boolean,\n  detector: {\n    /** path to hand detector model json */\n    modelPath?: string,\n  },\n  skeleton: {\n    /** path to hand skeleton model json */\n    modelPath?: string,\n  },\n}\n\n/** Configures all object detection specific options */\nexport interface ObjectConfig extends GenericConfig {\n  /** minimum confidence for a detected objects before results are discarded */\n  minConfidence: number,\n  /** minimum overlap between two detected objects before one is discarded */\n  iouThreshold: number,\n  /** maximum number of detected objects */\n  maxDetected: number,\n}\n\n/** Configures all body segmentation module\n * removes background from input containing person\n * if segmentation is enabled it will run as preprocessing task before any other model\n * alternatively leave it disabled and use it on-demand using human.segmentation method which can\n * remove background or replace it with user-provided background\n*/\nexport interface SegmentationConfig extends GenericConfig {\n  /** blur segmentation output by <number> pixels for more realistic image */\n  blur: number,\n}\n\n/** Run input through image filters before inference\n * - available only in Browser environments\n * - image filters run with near-zero latency as they are executed on the GPU using WebGL\n*/\nexport interface FilterConfig {\n  /** are image filters enabled? */\n  enabled: boolean,\n  /** perform image histogram equalization\n   * - equalization is performed on input as a whole and detected face before its passed for further analysis\n  */\n  equalization: boolean,\n  /** resize input width\n  * - if both width and height are set to 0, there is no resizing\n  * - if just one is set, second one is scaled automatically\n  * - if both are set, values are used as-is\n  */\n  width: number,\n  /** resize input height\n  * - if both width and height are set to 0, there is no resizing\n  * - if just one is set, second one is scaled automatically\n  * - if both are set, values are used as-is\n  */\n  height: number,\n  /** return processed canvas imagedata in result */\n  return: boolean,\n  /** flip input as mirror image */\n  flip: boolean,\n  /** range: -1 (darken) to 1 (lighten) */\n  brightness: number,\n  /** range: -1 (reduce contrast) to 1 (increase contrast) */\n  contrast: number,\n  /** range: 0 (no sharpening) to 1 (maximum sharpening) */\n  sharpness: number,\n  /** range: 0 (no blur) to N (blur radius in pixels) */\n  blur: number\n  /** range: -1 (reduce saturation) to 1 (increase saturation) */\n  saturation: number,\n  /** range: 0 (no change) to 360 (hue rotation in degrees) */\n  hue: number,\n  /** image negative */\n  negative: boolean,\n  /** image sepia colors */\n  sepia: boolean,\n  /** image vintage colors */\n  vintage: boolean,\n  /** image kodachrome colors */\n  kodachrome: boolean,\n  /** image technicolor colors */\n  technicolor: boolean,\n  /** image polaroid camera effect */\n  polaroid: boolean,\n  /** range: 0 (no pixelate) to N (number of pixels to pixelate) */\n  pixelate: number,\n}\n\n/** Controlls gesture detection */\nexport interface GestureConfig {\n  /** is gesture detection enabled? */\n  enabled: boolean,\n}\n/** Possible TensorFlow backends */\nexport type BackendType = ['cpu', 'wasm', 'webgl', 'humangl', 'tensorflow', 'webgpu'];\n\n/** Possible values for `human.warmup` */\nexport type WarmupType = ['' | 'none' | 'face' | 'full' | 'body'];\n\n/**\n * Configuration interface definition for **Human** library\n * Contains all configurable parameters\n * Defaults: [config](https://github.com/vladmandic/human/blob/main/src/config.ts#L262)\n */\nexport interface Config {\n  /** Backend used for TFJS operations\n   * valid build-in backends are:\n   * - Browser: `cpu`, `wasm`, `webgl`, `humangl`, `webgpu`\n   * - NodeJS: `cpu`, `wasm`, `tensorflow`\n   * default: `humangl` for browser and `tensorflow` for nodejs\n  */\n  backend: '' | 'cpu' | 'wasm' | 'webgl' | 'humangl' | 'tensorflow' | 'webgpu',\n\n  /** Path to *.wasm files if backend is set to `wasm`\n   *\n   * default: auto-detects to link to CDN `jsdelivr` when running in browser\n  */\n  wasmPath: string,\n\n  /** Force WASM loader to use platform fetch\n   *\n   * default: auto-detects to link to CDN `jsdelivr` when running in browser\n  */\n  wasmPlatformFetch: boolean,\n\n  /** Print debug statements to console\n   *\n   * default: `true`\n  */\n  debug: boolean,\n\n  /** Perform model loading and inference concurrently or sequentially\n   *\n   * default: `true`\n  */\n  async: boolean,\n\n  /** What to use for `human.warmup()`\n   * - warmup pre-initializes all models for faster inference but can take significant time on startup\n   * - used by `webgl`, `humangl` and `webgpu` backends\n   *\n   * default: `full`\n  */\n  warmup: '' | 'none' | 'face' | 'full' | 'body',\n\n  /** Base model path (typically starting with file://, http:// or https://) for all models\n   * - individual modelPath values are relative to this path\n   *\n   * default: `../models/` for browsers and `file://models/` for nodejs\n  */\n  modelBasePath: string,\n\n  /** Cache models in IndexDB on first sucessfull load\n   * default: true if indexdb is available (browsers), false if its not (nodejs)\n   */\n  cacheModels: boolean,\n\n  /** Cache sensitivity\n   * - values 0..1 where 0.01 means reset cache if input changed more than 1%\n   * - set to 0 to disable caching\n   *\n   * default: 0.7\n  */\n  cacheSensitivity: number;\n\n  /** Perform immediate garbage collection on deallocated tensors instead of caching them */\n  deallocate: boolean;\n\n  /** Internal Variable */\n  skipAllowed: boolean;\n\n  /** Filter config {@link FilterConfig} */\n  filter: Partial<FilterConfig>,\n\n  /** Gesture config {@link GestureConfig} */\n  gesture: Partial<GestureConfig>;\n\n  /** Face config {@link FaceConfig} */\n  face: Partial<FaceConfig>,\n\n  /** Body config {@link BodyConfig} */\n  body: Partial<BodyConfig>,\n\n  /** Hand config {@link HandConfig} */\n  hand: Partial<HandConfig>,\n\n  /** Object config {@link ObjectConfig} */\n  object: Partial<ObjectConfig>,\n\n  /** Segmentation config {@link SegmentationConfig} */\n  segmentation: Partial<SegmentationConfig>,\n}\n\n/** - [See all default Config values...](https://github.com/vladmandic/human/blob/main/src/config.ts#L262) */\nconst config: Config = {\n  backend: '',\n  modelBasePath: '',\n  cacheModels: true,\n  wasmPath: '',\n  wasmPlatformFetch: false,\n  debug: false,\n  async: true,\n  warmup: 'full',\n  cacheSensitivity: 0.70,\n  skipAllowed: false,\n  deallocate: false,\n  filter: {\n    enabled: true,\n    equalization: false,\n    width: 0,\n    height: 0,\n    flip: false,\n    return: true,\n    brightness: 0,\n    contrast: 0,\n    sharpness: 0,\n    blur: 0,\n    saturation: 0,\n    hue: 0,\n    negative: false,\n    sepia: false,\n    vintage: false,\n    kodachrome: false,\n    technicolor: false,\n    polaroid: false,\n    pixelate: 0,\n  },\n  gesture: {\n    enabled: true,\n  },\n  face: {\n    enabled: true,\n    detector: {\n      modelPath: 'blazeface.json',\n      rotation: true,\n      maxDetected: 1,\n      skipFrames: 99,\n      skipTime: 2500,\n      minConfidence: 0.2,\n      iouThreshold: 0.1,\n      mask: false,\n      return: false,\n    },\n    mesh: {\n      enabled: true,\n      modelPath: 'facemesh.json',\n      keepInvalid: false,\n    },\n    attention: {\n      enabled: false,\n      modelPath: 'facemesh-attention.json',\n    },\n    iris: {\n      enabled: true,\n      modelPath: 'iris.json',\n    },\n    emotion: {\n      enabled: true,\n      minConfidence: 0.1,\n      skipFrames: 99,\n      skipTime: 1500,\n      modelPath: 'emotion.json',\n    },\n    description: {\n      enabled: true,\n      modelPath: 'faceres.json',\n      skipFrames: 99,\n      skipTime: 3000,\n      minConfidence: 0.1,\n    },\n    antispoof: {\n      enabled: false,\n      skipFrames: 99,\n      skipTime: 4000,\n      modelPath: 'antispoof.json',\n    },\n    liveness: {\n      enabled: false,\n      skipFrames: 99,\n      skipTime: 4000,\n      modelPath: 'liveness.json',\n    },\n  },\n  body: {\n    enabled: true,\n    modelPath: 'movenet-lightning.json',\n    maxDetected: -1,\n    minConfidence: 0.3,\n    skipFrames: 1,\n    skipTime: 200,\n  },\n  hand: {\n    enabled: true,\n    rotation: true,\n    skipFrames: 99,\n    skipTime: 1000,\n    minConfidence: 0.50,\n    iouThreshold: 0.2,\n    maxDetected: -1,\n    landmarks: true,\n    detector: {\n      modelPath: 'handtrack.json',\n    },\n    skeleton: {\n      modelPath: 'handlandmark-full.json',\n    },\n  },\n  object: {\n    enabled: false,\n    modelPath: 'mb3-centernet.json',\n    minConfidence: 0.2,\n    iouThreshold: 0.4,\n    maxDetected: 10,\n    skipFrames: 99,\n    skipTime: 2000,\n  },\n  segmentation: {\n    enabled: false,\n    modelPath: 'selfie.json',\n    blur: 8,\n  },\n};\n\nexport { config as defaults };\n", "/*\n  Human\n  homepage: <https://github.com/vladmandic/human>\n  author: <https://github.com/vladmandic>'\n*/\n\nvar __create = Object.create;\nvar __defProp = Object.defineProperty;\nvar __getOwnPropDesc = Object.getOwnPropertyDescriptor;\nvar __getOwnPropNames = Object.getOwnPropertyNames;\nvar __getProtoOf = Object.getPrototypeOf;\nvar __hasOwnProp = Object.prototype.hasOwnProperty;\nvar __commonJS = (cb, mod4) => function __require() {\n  return mod4 || (0, cb[__getOwnPropNames(cb)[0]])((mod4 = { exports: {} }).exports, mod4), mod4.exports;\n};\nvar __export = (target, all5) => {\n  for (var name in all5)\n    __defProp(target, name, { get: all5[name], enumerable: true });\n};\nvar __copyProps = (to, from, except, desc) => {\n  if (from && typeof from === \"object\" || typeof from === \"function\") {\n    for (let key of __getOwnPropNames(from))\n      if (!__hasOwnProp.call(to, key) && key !== except)\n        __defProp(to, key, { get: () => from[key], enumerable: !(desc = __getOwnPropDesc(from, key)) || desc.enumerable });\n  }\n  return to;\n};\nvar __toESM = (mod4, isNodeMode, target) => (target = mod4 != null ? __create(__getProtoOf(mod4)) : {}, __copyProps(\n  isNodeMode || !mod4 || !mod4.__esModule ? __defProp(target, \"default\", { value: mod4, enumerable: true }) : target,\n  mod4\n));\n\n// node_modules/.pnpm/long@4.0.0/node_modules/long/src/long.js\nvar require_long = __commonJS({\n  \"node_modules/.pnpm/long@4.0.0/node_modules/long/src/long.js\"(exports, module) {\n    module.exports = Long2;\n    var wasm = null;\n    try {\n      wasm = new WebAssembly.Instance(new WebAssembly.Module(new Uint8Array([\n        0,\n        97,\n        115,\n        109,\n        1,\n        0,\n        0,\n        0,\n        1,\n        13,\n        2,\n        96,\n        0,\n        1,\n        127,\n        96,\n        4,\n        127,\n        127,\n        127,\n        127,\n        1,\n        127,\n        3,\n        7,\n        6,\n        0,\n        1,\n        1,\n        1,\n        1,\n        1,\n        6,\n        6,\n        1,\n        127,\n        1,\n        65,\n        0,\n        11,\n        7,\n        50,\n        6,\n        3,\n        109,\n        117,\n        108,\n        0,\n        1,\n        5,\n        100,\n        105,\n        118,\n        95,\n        115,\n        0,\n        2,\n        5,\n        100,\n        105,\n        118,\n        95,\n        117,\n        0,\n        3,\n        5,\n        114,\n        101,\n        109,\n        95,\n        115,\n        0,\n        4,\n        5,\n        114,\n        101,\n        109,\n        95,\n        117,\n        0,\n        5,\n        8,\n        103,\n        101,\n        116,\n        95,\n        104,\n        105,\n        103,\n        104,\n        0,\n        0,\n        10,\n        191,\n        1,\n        6,\n        4,\n        0,\n        35,\n        0,\n        11,\n        36,\n        1,\n        1,\n        126,\n        32,\n        0,\n        173,\n        32,\n        1,\n        173,\n        66,\n        32,\n        134,\n        132,\n        32,\n        2,\n        173,\n        32,\n        3,\n        173,\n        66,\n        32,\n        134,\n        132,\n        126,\n        34,\n        4,\n        66,\n        32,\n        135,\n        167,\n        36,\n        0,\n        32,\n        4,\n        167,\n        11,\n        36,\n        1,\n        1,\n        126,\n        32,\n        0,\n        173,\n        32,\n        1,\n        173,\n        66,\n        32,\n        134,\n        132,\n        32,\n        2,\n        173,\n        32,\n        3,\n        173,\n        66,\n        32,\n        134,\n        132,\n        127,\n        34,\n        4,\n        66,\n        32,\n        135,\n        167,\n        36,\n        0,\n        32,\n        4,\n        167,\n        11,\n        36,\n        1,\n        1,\n        126,\n        32,\n        0,\n        173,\n        32,\n        1,\n        173,\n        66,\n        32,\n        134,\n        132,\n        32,\n        2,\n        173,\n        32,\n        3,\n        173,\n        66,\n        32,\n        134,\n        132,\n        128,\n        34,\n        4,\n        66,\n        32,\n        135,\n        167,\n        36,\n        0,\n        32,\n        4,\n        167,\n        11,\n        36,\n        1,\n        1,\n        126,\n        32,\n        0,\n        173,\n        32,\n        1,\n        173,\n        66,\n        32,\n        134,\n        132,\n        32,\n        2,\n        173,\n        32,\n        3,\n        173,\n        66,\n        32,\n        134,\n        132,\n        129,\n        34,\n        4,\n        66,\n        32,\n        135,\n        167,\n        36,\n        0,\n        32,\n        4,\n        167,\n        11,\n        36,\n        1,\n        1,\n        126,\n        32,\n        0,\n        173,\n        32,\n        1,\n        173,\n        66,\n        32,\n        134,\n        132,\n        32,\n        2,\n        173,\n        32,\n        3,\n        173,\n        66,\n        32,\n        134,\n        132,\n        130,\n        34,\n        4,\n        66,\n        32,\n        135,\n        167,\n        36,\n        0,\n        32,\n        4,\n        167,\n        11\n      ])), {}).exports;\n    } catch (e2) {\n    }\n    function Long2(low, high, unsigned) {\n      this.low = low | 0;\n      this.high = high | 0;\n      this.unsigned = !!unsigned;\n    }\n    Long2.prototype.__isLong__;\n    Object.defineProperty(Long2.prototype, \"__isLong__\", { value: true });\n    function isLong(obj) {\n      return (obj && obj[\"__isLong__\"]) === true;\n    }\n    Long2.isLong = isLong;\n    var INT_CACHE = {};\n    var UINT_CACHE = {};\n    function fromInt(value, unsigned) {\n      var obj, cachedObj, cache;\n      if (unsigned) {\n        value >>>= 0;\n        if (cache = 0 <= value && value < 256) {\n          cachedObj = UINT_CACHE[value];\n          if (cachedObj)\n            return cachedObj;\n        }\n        obj = fromBits(value, (value | 0) < 0 ? -1 : 0, true);\n        if (cache)\n          UINT_CACHE[value] = obj;\n        return obj;\n      } else {\n        value |= 0;\n        if (cache = -128 <= value && value < 128) {\n          cachedObj = INT_CACHE[value];\n          if (cachedObj)\n            return cachedObj;\n        }\n        obj = fromBits(value, value < 0 ? -1 : 0, false);\n        if (cache)\n          INT_CACHE[value] = obj;\n        return obj;\n      }\n    }\n    Long2.fromInt = fromInt;\n    function fromNumber(value, unsigned) {\n      if (isNaN(value))\n        return unsigned ? UZERO : ZERO;\n      if (unsigned) {\n        if (value < 0)\n          return UZERO;\n        if (value >= TWO_PWR_64_DBL)\n          return MAX_UNSIGNED_VALUE;\n      } else {\n        if (value <= -TWO_PWR_63_DBL)\n          return MIN_VALUE;\n        if (value + 1 >= TWO_PWR_63_DBL)\n          return MAX_VALUE;\n      }\n      if (value < 0)\n        return fromNumber(-value, unsigned).neg();\n      return fromBits(value % TWO_PWR_32_DBL | 0, value / TWO_PWR_32_DBL | 0, unsigned);\n    }\n    Long2.fromNumber = fromNumber;\n    function fromBits(lowBits, highBits, unsigned) {\n      return new Long2(lowBits, highBits, unsigned);\n    }\n    Long2.fromBits = fromBits;\n    var pow_dbl = Math.pow;\n    function fromString(str, unsigned, radix) {\n      if (str.length === 0)\n        throw Error(\"empty string\");\n      if (str === \"NaN\" || str === \"Infinity\" || str === \"+Infinity\" || str === \"-Infinity\")\n        return ZERO;\n      if (typeof unsigned === \"number\") {\n        radix = unsigned, unsigned = false;\n      } else {\n        unsigned = !!unsigned;\n      }\n      radix = radix || 10;\n      if (radix < 2 || 36 < radix)\n        throw RangeError(\"radix\");\n      var p2;\n      if ((p2 = str.indexOf(\"-\")) > 0)\n        throw Error(\"interior hyphen\");\n      else if (p2 === 0) {\n        return fromString(str.substring(1), unsigned, radix).neg();\n      }\n      var radixToPower = fromNumber(pow_dbl(radix, 8));\n      var result = ZERO;\n      for (var i2 = 0; i2 < str.length; i2 += 8) {\n        var size = Math.min(8, str.length - i2), value = parseInt(str.substring(i2, i2 + size), radix);\n        if (size < 8) {\n          var power = fromNumber(pow_dbl(radix, size));\n          result = result.mul(power).add(fromNumber(value));\n        } else {\n          result = result.mul(radixToPower);\n          result = result.add(fromNumber(value));\n        }\n      }\n      result.unsigned = unsigned;\n      return result;\n    }\n    Long2.fromString = fromString;\n    function fromValue(val, unsigned) {\n      if (typeof val === \"number\")\n        return fromNumber(val, unsigned);\n      if (typeof val === \"string\")\n        return fromString(val, unsigned);\n      return fromBits(val.low, val.high, typeof unsigned === \"boolean\" ? unsigned : val.unsigned);\n    }\n    Long2.fromValue = fromValue;\n    var TWO_PWR_16_DBL = 1 << 16;\n    var TWO_PWR_24_DBL = 1 << 24;\n    var TWO_PWR_32_DBL = TWO_PWR_16_DBL * TWO_PWR_16_DBL;\n    var TWO_PWR_64_DBL = TWO_PWR_32_DBL * TWO_PWR_32_DBL;\n    var TWO_PWR_63_DBL = TWO_PWR_64_DBL / 2;\n    var TWO_PWR_24 = fromInt(TWO_PWR_24_DBL);\n    var ZERO = fromInt(0);\n    Long2.ZERO = ZERO;\n    var UZERO = fromInt(0, true);\n    Long2.UZERO = UZERO;\n    var ONE = fromInt(1);\n    Long2.ONE = ONE;\n    var UONE = fromInt(1, true);\n    Long2.UONE = UONE;\n    var NEG_ONE = fromInt(-1);\n    Long2.NEG_ONE = NEG_ONE;\n    var MAX_VALUE = fromBits(4294967295 | 0, 2147483647 | 0, false);\n    Long2.MAX_VALUE = MAX_VALUE;\n    var MAX_UNSIGNED_VALUE = fromBits(4294967295 | 0, 4294967295 | 0, true);\n    Long2.MAX_UNSIGNED_VALUE = MAX_UNSIGNED_VALUE;\n    var MIN_VALUE = fromBits(0, 2147483648 | 0, false);\n    Long2.MIN_VALUE = MIN_VALUE;\n    var LongPrototype = Long2.prototype;\n    LongPrototype.toInt = function toInt() {\n      return this.unsigned ? this.low >>> 0 : this.low;\n    };\n    LongPrototype.toNumber = function toNumber() {\n      if (this.unsigned)\n        return (this.high >>> 0) * TWO_PWR_32_DBL + (this.low >>> 0);\n      return this.high * TWO_PWR_32_DBL + (this.low >>> 0);\n    };\n    LongPrototype.toString = function toString(radix) {\n      radix = radix || 10;\n      if (radix < 2 || 36 < radix)\n        throw RangeError(\"radix\");\n      if (this.isZero())\n        return \"0\";\n      if (this.isNegative()) {\n        if (this.eq(MIN_VALUE)) {\n          var radixLong = fromNumber(radix), div3 = this.div(radixLong), rem1 = div3.mul(radixLong).sub(this);\n          return div3.toString(radix) + rem1.toInt().toString(radix);\n        } else\n          return \"-\" + this.neg().toString(radix);\n      }\n      var radixToPower = fromNumber(pow_dbl(radix, 6), this.unsigned), rem = this;\n      var result = \"\";\n      while (true) {\n        var remDiv = rem.div(radixToPower), intval = rem.sub(remDiv.mul(radixToPower)).toInt() >>> 0, digits = intval.toString(radix);\n        rem = remDiv;\n        if (rem.isZero())\n          return digits + result;\n        else {\n          while (digits.length < 6)\n            digits = \"0\" + digits;\n          result = \"\" + digits + result;\n        }\n      }\n    };\n    LongPrototype.getHighBits = function getHighBits() {\n      return this.high;\n    };\n    LongPrototype.getHighBitsUnsigned = function getHighBitsUnsigned() {\n      return this.high >>> 0;\n    };\n    LongPrototype.getLowBits = function getLowBits() {\n      return this.low;\n    };\n    LongPrototype.getLowBitsUnsigned = function getLowBitsUnsigned() {\n      return this.low >>> 0;\n    };\n    LongPrototype.getNumBitsAbs = function getNumBitsAbs() {\n      if (this.isNegative())\n        return this.eq(MIN_VALUE) ? 64 : this.neg().getNumBitsAbs();\n      var val = this.high != 0 ? this.high : this.low;\n      for (var bit = 31; bit > 0; bit--)\n        if ((val & 1 << bit) != 0)\n          break;\n      return this.high != 0 ? bit + 33 : bit + 1;\n    };\n    LongPrototype.isZero = function isZero() {\n      return this.high === 0 && this.low === 0;\n    };\n    LongPrototype.eqz = LongPrototype.isZero;\n    LongPrototype.isNegative = function isNegative() {\n      return !this.unsigned && this.high < 0;\n    };\n    LongPrototype.isPositive = function isPositive() {\n      return this.unsigned || this.high >= 0;\n    };\n    LongPrototype.isOdd = function isOdd() {\n      return (this.low & 1) === 1;\n    };\n    LongPrototype.isEven = function isEven2() {\n      return (this.low & 1) === 0;\n    };\n    LongPrototype.equals = function equals(other) {\n      if (!isLong(other))\n        other = fromValue(other);\n      if (this.unsigned !== other.unsigned && this.high >>> 31 === 1 && other.high >>> 31 === 1)\n        return false;\n      return this.high === other.high && this.low === other.low;\n    };\n    LongPrototype.eq = LongPrototype.equals;\n    LongPrototype.notEquals = function notEquals(other) {\n      return !this.eq(other);\n    };\n    LongPrototype.neq = LongPrototype.notEquals;\n    LongPrototype.ne = LongPrototype.notEquals;\n    LongPrototype.lessThan = function lessThan(other) {\n      return this.comp(other) < 0;\n    };\n    LongPrototype.lt = LongPrototype.lessThan;\n    LongPrototype.lessThanOrEqual = function lessThanOrEqual(other) {\n      return this.comp(other) <= 0;\n    };\n    LongPrototype.lte = LongPrototype.lessThanOrEqual;\n    LongPrototype.le = LongPrototype.lessThanOrEqual;\n    LongPrototype.greaterThan = function greaterThan(other) {\n      return this.comp(other) > 0;\n    };\n    LongPrototype.gt = LongPrototype.greaterThan;\n    LongPrototype.greaterThanOrEqual = function greaterThanOrEqual(other) {\n      return this.comp(other) >= 0;\n    };\n    LongPrototype.gte = LongPrototype.greaterThanOrEqual;\n    LongPrototype.ge = LongPrototype.greaterThanOrEqual;\n    LongPrototype.compare = function compare(other) {\n      if (!isLong(other))\n        other = fromValue(other);\n      if (this.eq(other))\n        return 0;\n      var thisNeg = this.isNegative(), otherNeg = other.isNegative();\n      if (thisNeg && !otherNeg)\n        return -1;\n      if (!thisNeg && otherNeg)\n        return 1;\n      if (!this.unsigned)\n        return this.sub(other).isNegative() ? -1 : 1;\n      return other.high >>> 0 > this.high >>> 0 || other.high === this.high && other.low >>> 0 > this.low >>> 0 ? -1 : 1;\n    };\n    LongPrototype.comp = LongPrototype.compare;\n    LongPrototype.negate = function negate() {\n      if (!this.unsigned && this.eq(MIN_VALUE))\n        return MIN_VALUE;\n      return this.not().add(ONE);\n    };\n    LongPrototype.neg = LongPrototype.negate;\n    LongPrototype.add = function add5(addend) {\n      if (!isLong(addend))\n        addend = fromValue(addend);\n      var a48 = this.high >>> 16;\n      var a32 = this.high & 65535;\n      var a16 = this.low >>> 16;\n      var a00 = this.low & 65535;\n      var b48 = addend.high >>> 16;\n      var b32 = addend.high & 65535;\n      var b16 = addend.low >>> 16;\n      var b00 = addend.low & 65535;\n      var c48 = 0, c32 = 0, c16 = 0, c00 = 0;\n      c00 += a00 + b00;\n      c16 += c00 >>> 16;\n      c00 &= 65535;\n      c16 += a16 + b16;\n      c32 += c16 >>> 16;\n      c16 &= 65535;\n      c32 += a32 + b32;\n      c48 += c32 >>> 16;\n      c32 &= 65535;\n      c48 += a48 + b48;\n      c48 &= 65535;\n      return fromBits(c16 << 16 | c00, c48 << 16 | c32, this.unsigned);\n    };\n    LongPrototype.subtract = function subtract(subtrahend) {\n      if (!isLong(subtrahend))\n        subtrahend = fromValue(subtrahend);\n      return this.add(subtrahend.neg());\n    };\n    LongPrototype.sub = LongPrototype.subtract;\n    LongPrototype.multiply = function multiply4(multiplier) {\n      if (this.isZero())\n        return ZERO;\n      if (!isLong(multiplier))\n        multiplier = fromValue(multiplier);\n      if (wasm) {\n        var low = wasm.mul(\n          this.low,\n          this.high,\n          multiplier.low,\n          multiplier.high\n        );\n        return fromBits(low, wasm.get_high(), this.unsigned);\n      }\n      if (multiplier.isZero())\n        return ZERO;\n      if (this.eq(MIN_VALUE))\n        return multiplier.isOdd() ? MIN_VALUE : ZERO;\n      if (multiplier.eq(MIN_VALUE))\n        return this.isOdd() ? MIN_VALUE : ZERO;\n      if (this.isNegative()) {\n        if (multiplier.isNegative())\n          return this.neg().mul(multiplier.neg());\n        else\n          return this.neg().mul(multiplier).neg();\n      } else if (multiplier.isNegative())\n        return this.mul(multiplier.neg()).neg();\n      if (this.lt(TWO_PWR_24) && multiplier.lt(TWO_PWR_24))\n        return fromNumber(this.toNumber() * multiplier.toNumber(), this.unsigned);\n      var a48 = this.high >>> 16;\n      var a32 = this.high & 65535;\n      var a16 = this.low >>> 16;\n      var a00 = this.low & 65535;\n      var b48 = multiplier.high >>> 16;\n      var b32 = multiplier.high & 65535;\n      var b16 = multiplier.low >>> 16;\n      var b00 = multiplier.low & 65535;\n      var c48 = 0, c32 = 0, c16 = 0, c00 = 0;\n      c00 += a00 * b00;\n      c16 += c00 >>> 16;\n      c00 &= 65535;\n      c16 += a16 * b00;\n      c32 += c16 >>> 16;\n      c16 &= 65535;\n      c16 += a00 * b16;\n      c32 += c16 >>> 16;\n      c16 &= 65535;\n      c32 += a32 * b00;\n      c48 += c32 >>> 16;\n      c32 &= 65535;\n      c32 += a16 * b16;\n      c48 += c32 >>> 16;\n      c32 &= 65535;\n      c32 += a00 * b32;\n      c48 += c32 >>> 16;\n      c32 &= 65535;\n      c48 += a48 * b00 + a32 * b16 + a16 * b32 + a00 * b48;\n      c48 &= 65535;\n      return fromBits(c16 << 16 | c00, c48 << 16 | c32, this.unsigned);\n    };\n    LongPrototype.mul = LongPrototype.multiply;\n    LongPrototype.divide = function divide(divisor) {\n      if (!isLong(divisor))\n        divisor = fromValue(divisor);\n      if (divisor.isZero())\n        throw Error(\"division by zero\");\n      if (wasm) {\n        if (!this.unsigned && this.high === -2147483648 && divisor.low === -1 && divisor.high === -1) {\n          return this;\n        }\n        var low = (this.unsigned ? wasm.div_u : wasm.div_s)(\n          this.low,\n          this.high,\n          divisor.low,\n          divisor.high\n        );\n        return fromBits(low, wasm.get_high(), this.unsigned);\n      }\n      if (this.isZero())\n        return this.unsigned ? UZERO : ZERO;\n      var approx, rem, res;\n      if (!this.unsigned) {\n        if (this.eq(MIN_VALUE)) {\n          if (divisor.eq(ONE) || divisor.eq(NEG_ONE))\n            return MIN_VALUE;\n          else if (divisor.eq(MIN_VALUE))\n            return ONE;\n          else {\n            var halfThis = this.shr(1);\n            approx = halfThis.div(divisor).shl(1);\n            if (approx.eq(ZERO)) {\n              return divisor.isNegative() ? ONE : NEG_ONE;\n            } else {\n              rem = this.sub(divisor.mul(approx));\n              res = approx.add(rem.div(divisor));\n              return res;\n            }\n          }\n        } else if (divisor.eq(MIN_VALUE))\n          return this.unsigned ? UZERO : ZERO;\n        if (this.isNegative()) {\n          if (divisor.isNegative())\n            return this.neg().div(divisor.neg());\n          return this.neg().div(divisor).neg();\n        } else if (divisor.isNegative())\n          return this.div(divisor.neg()).neg();\n        res = ZERO;\n      } else {\n        if (!divisor.unsigned)\n          divisor = divisor.toUnsigned();\n        if (divisor.gt(this))\n          return UZERO;\n        if (divisor.gt(this.shru(1)))\n          return UONE;\n        res = UZERO;\n      }\n      rem = this;\n      while (rem.gte(divisor)) {\n        approx = Math.max(1, Math.floor(rem.toNumber() / divisor.toNumber()));\n        var log22 = Math.ceil(Math.log(approx) / Math.LN2), delta = log22 <= 48 ? 1 : pow_dbl(2, log22 - 48), approxRes = fromNumber(approx), approxRem = approxRes.mul(divisor);\n        while (approxRem.isNegative() || approxRem.gt(rem)) {\n          approx -= delta;\n          approxRes = fromNumber(approx, this.unsigned);\n          approxRem = approxRes.mul(divisor);\n        }\n        if (approxRes.isZero())\n          approxRes = ONE;\n        res = res.add(approxRes);\n        rem = rem.sub(approxRem);\n      }\n      return res;\n    };\n    LongPrototype.div = LongPrototype.divide;\n    LongPrototype.modulo = function modulo(divisor) {\n      if (!isLong(divisor))\n        divisor = fromValue(divisor);\n      if (wasm) {\n        var low = (this.unsigned ? wasm.rem_u : wasm.rem_s)(\n          this.low,\n          this.high,\n          divisor.low,\n          divisor.high\n        );\n        return fromBits(low, wasm.get_high(), this.unsigned);\n      }\n      return this.sub(this.div(divisor).mul(divisor));\n    };\n    LongPrototype.mod = LongPrototype.modulo;\n    LongPrototype.rem = LongPrototype.modulo;\n    LongPrototype.not = function not() {\n      return fromBits(~this.low, ~this.high, this.unsigned);\n    };\n    LongPrototype.and = function and(other) {\n      if (!isLong(other))\n        other = fromValue(other);\n      return fromBits(this.low & other.low, this.high & other.high, this.unsigned);\n    };\n    LongPrototype.or = function or(other) {\n      if (!isLong(other))\n        other = fromValue(other);\n      return fromBits(this.low | other.low, this.high | other.high, this.unsigned);\n    };\n    LongPrototype.xor = function xor(other) {\n      if (!isLong(other))\n        other = fromValue(other);\n      return fromBits(this.low ^ other.low, this.high ^ other.high, this.unsigned);\n    };\n    LongPrototype.shiftLeft = function shiftLeft(numBits) {\n      if (isLong(numBits))\n        numBits = numBits.toInt();\n      if ((numBits &= 63) === 0)\n        return this;\n      else if (numBits < 32)\n        return fromBits(this.low << numBits, this.high << numBits | this.low >>> 32 - numBits, this.unsigned);\n      else\n        return fromBits(0, this.low << numBits - 32, this.unsigned);\n    };\n    LongPrototype.shl = LongPrototype.shiftLeft;\n    LongPrototype.shiftRight = function shiftRight(numBits) {\n      if (isLong(numBits))\n        numBits = numBits.toInt();\n      if ((numBits &= 63) === 0)\n        return this;\n      else if (numBits < 32)\n        return fromBits(this.low >>> numBits | this.high << 32 - numBits, this.high >> numBits, this.unsigned);\n      else\n        return fromBits(this.high >> numBits - 32, this.high >= 0 ? 0 : -1, this.unsigned);\n    };\n    LongPrototype.shr = LongPrototype.shiftRight;\n    LongPrototype.shiftRightUnsigned = function shiftRightUnsigned(numBits) {\n      if (isLong(numBits))\n        numBits = numBits.toInt();\n      numBits &= 63;\n      if (numBits === 0)\n        return this;\n      else {\n        var high = this.high;\n        if (numBits < 32) {\n          var low = this.low;\n          return fromBits(low >>> numBits | high << 32 - numBits, high >>> numBits, this.unsigned);\n        } else if (numBits === 32)\n          return fromBits(high, 0, this.unsigned);\n        else\n          return fromBits(high >>> numBits - 32, 0, this.unsigned);\n      }\n    };\n    LongPrototype.shru = LongPrototype.shiftRightUnsigned;\n    LongPrototype.shr_u = LongPrototype.shiftRightUnsigned;\n    LongPrototype.toSigned = function toSigned() {\n      if (!this.unsigned)\n        return this;\n      return fromBits(this.low, this.high, false);\n    };\n    LongPrototype.toUnsigned = function toUnsigned() {\n      if (this.unsigned)\n        return this;\n      return fromBits(this.low, this.high, true);\n    };\n    LongPrototype.toBytes = function toBytes(le) {\n      return le ? this.toBytesLE() : this.toBytesBE();\n    };\n    LongPrototype.toBytesLE = function toBytesLE() {\n      var hi = this.high, lo = this.low;\n      return [\n        lo & 255,\n        lo >>> 8 & 255,\n        lo >>> 16 & 255,\n        lo >>> 24,\n        hi & 255,\n        hi >>> 8 & 255,\n        hi >>> 16 & 255,\n        hi >>> 24\n      ];\n    };\n    LongPrototype.toBytesBE = function toBytesBE() {\n      var hi = this.high, lo = this.low;\n      return [\n        hi >>> 24,\n        hi >>> 16 & 255,\n        hi >>> 8 & 255,\n        hi & 255,\n        lo >>> 24,\n        lo >>> 16 & 255,\n        lo >>> 8 & 255,\n        lo & 255\n      ];\n    };\n    Long2.fromBytes = function fromBytes(bytes, unsigned, le) {\n      return le ? Long2.fromBytesLE(bytes, unsigned) : Long2.fromBytesBE(bytes, unsigned);\n    };\n    Long2.fromBytesLE = function fromBytesLE(bytes, unsigned) {\n      return new Long2(\n        bytes[0] | bytes[1] << 8 | bytes[2] << 16 | bytes[3] << 24,\n        bytes[4] | bytes[5] << 8 | bytes[6] << 16 | bytes[7] << 24,\n        unsigned\n      );\n    };\n    Long2.fromBytesBE = function fromBytesBE(bytes, unsigned) {\n      return new Long2(\n        bytes[4] << 24 | bytes[5] << 16 | bytes[6] << 8 | bytes[7],\n        bytes[0] << 24 | bytes[1] << 16 | bytes[2] << 8 | bytes[3],\n        unsigned\n      );\n    };\n  }\n});\n\n// (disabled):node_modules/.pnpm/node-fetch@2.6.7/node_modules/node-fetch/browser.js\nvar require_browser = __commonJS({\n  \"(disabled):node_modules/.pnpm/node-fetch@2.6.7/node_modules/node-fetch/browser.js\"() {\n  }\n});\n\n// (disabled):util\nvar require_util = __commonJS({\n  \"(disabled):util\"() {\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/alea.js\nvar require_alea = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/alea.js\"(exports, module) {\n    (function(global2, module2, define2) {\n      function Alea(seed) {\n        var me = this, mash = Mash();\n        me.next = function() {\n          var t2 = 2091639 * me.s0 + me.c * 23283064365386963e-26;\n          me.s0 = me.s1;\n          me.s1 = me.s2;\n          return me.s2 = t2 - (me.c = t2 | 0);\n        };\n        me.c = 1;\n        me.s0 = mash(\" \");\n        me.s1 = mash(\" \");\n        me.s2 = mash(\" \");\n        me.s0 -= mash(seed);\n        if (me.s0 < 0) {\n          me.s0 += 1;\n        }\n        me.s1 -= mash(seed);\n        if (me.s1 < 0) {\n          me.s1 += 1;\n        }\n        me.s2 -= mash(seed);\n        if (me.s2 < 0) {\n          me.s2 += 1;\n        }\n        mash = null;\n      }\n      function copy(f, t2) {\n        t2.c = f.c;\n        t2.s0 = f.s0;\n        t2.s1 = f.s1;\n        t2.s2 = f.s2;\n        return t2;\n      }\n      function impl(seed, opts) {\n        var xg = new Alea(seed), state = opts && opts.state, prng = xg.next;\n        prng.int32 = function() {\n          return xg.next() * 4294967296 | 0;\n        };\n        prng.double = function() {\n          return prng() + (prng() * 2097152 | 0) * 11102230246251565e-32;\n        };\n        prng.quick = prng;\n        if (state) {\n          if (typeof state == \"object\")\n            copy(state, xg);\n          prng.state = function() {\n            return copy(xg, {});\n          };\n        }\n        return prng;\n      }\n      function Mash() {\n        var n2 = 4022871197;\n        var mash = function(data) {\n          data = String(data);\n          for (var i2 = 0; i2 < data.length; i2++) {\n            n2 += data.charCodeAt(i2);\n            var h = 0.02519603282416938 * n2;\n            n2 = h >>> 0;\n            h -= n2;\n            h *= n2;\n            n2 = h >>> 0;\n            h -= n2;\n            n2 += h * 4294967296;\n          }\n          return (n2 >>> 0) * 23283064365386963e-26;\n        };\n        return mash;\n      }\n      if (module2 && module2.exports) {\n        module2.exports = impl;\n      } else if (define2 && define2.amd) {\n        define2(function() {\n          return impl;\n        });\n      } else {\n        this.alea = impl;\n      }\n    })(\n      exports,\n      typeof module == \"object\" && module,\n      typeof define == \"function\" && define\n    );\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xor128.js\nvar require_xor128 = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xor128.js\"(exports, module) {\n    (function(global2, module2, define2) {\n      function XorGen(seed) {\n        var me = this, strseed = \"\";\n        me.x = 0;\n        me.y = 0;\n        me.z = 0;\n        me.w = 0;\n        me.next = function() {\n          var t2 = me.x ^ me.x << 11;\n          me.x = me.y;\n          me.y = me.z;\n          me.z = me.w;\n          return me.w ^= me.w >>> 19 ^ t2 ^ t2 >>> 8;\n        };\n        if (seed === (seed | 0)) {\n          me.x = seed;\n        } else {\n          strseed += seed;\n        }\n        for (var k = 0; k < strseed.length + 64; k++) {\n          me.x ^= strseed.charCodeAt(k) | 0;\n          me.next();\n        }\n      }\n      function copy(f, t2) {\n        t2.x = f.x;\n        t2.y = f.y;\n        t2.z = f.z;\n        t2.w = f.w;\n        return t2;\n      }\n      function impl(seed, opts) {\n        var xg = new XorGen(seed), state = opts && opts.state, prng = function() {\n          return (xg.next() >>> 0) / 4294967296;\n        };\n        prng.double = function() {\n          do {\n            var top = xg.next() >>> 11, bot = (xg.next() >>> 0) / 4294967296, result = (top + bot) / (1 << 21);\n          } while (result === 0);\n          return result;\n        };\n        prng.int32 = xg.next;\n        prng.quick = prng;\n        if (state) {\n          if (typeof state == \"object\")\n            copy(state, xg);\n          prng.state = function() {\n            return copy(xg, {});\n          };\n        }\n        return prng;\n      }\n      if (module2 && module2.exports) {\n        module2.exports = impl;\n      } else if (define2 && define2.amd) {\n        define2(function() {\n          return impl;\n        });\n      } else {\n        this.xor128 = impl;\n      }\n    })(\n      exports,\n      typeof module == \"object\" && module,\n      typeof define == \"function\" && define\n    );\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xorwow.js\nvar require_xorwow = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xorwow.js\"(exports, module) {\n    (function(global2, module2, define2) {\n      function XorGen(seed) {\n        var me = this, strseed = \"\";\n        me.next = function() {\n          var t2 = me.x ^ me.x >>> 2;\n          me.x = me.y;\n          me.y = me.z;\n          me.z = me.w;\n          me.w = me.v;\n          return (me.d = me.d + 362437 | 0) + (me.v = me.v ^ me.v << 4 ^ (t2 ^ t2 << 1)) | 0;\n        };\n        me.x = 0;\n        me.y = 0;\n        me.z = 0;\n        me.w = 0;\n        me.v = 0;\n        if (seed === (seed | 0)) {\n          me.x = seed;\n        } else {\n          strseed += seed;\n        }\n        for (var k = 0; k < strseed.length + 64; k++) {\n          me.x ^= strseed.charCodeAt(k) | 0;\n          if (k == strseed.length) {\n            me.d = me.x << 10 ^ me.x >>> 4;\n          }\n          me.next();\n        }\n      }\n      function copy(f, t2) {\n        t2.x = f.x;\n        t2.y = f.y;\n        t2.z = f.z;\n        t2.w = f.w;\n        t2.v = f.v;\n        t2.d = f.d;\n        return t2;\n      }\n      function impl(seed, opts) {\n        var xg = new XorGen(seed), state = opts && opts.state, prng = function() {\n          return (xg.next() >>> 0) / 4294967296;\n        };\n        prng.double = function() {\n          do {\n            var top = xg.next() >>> 11, bot = (xg.next() >>> 0) / 4294967296, result = (top + bot) / (1 << 21);\n          } while (result === 0);\n          return result;\n        };\n        prng.int32 = xg.next;\n        prng.quick = prng;\n        if (state) {\n          if (typeof state == \"object\")\n            copy(state, xg);\n          prng.state = function() {\n            return copy(xg, {});\n          };\n        }\n        return prng;\n      }\n      if (module2 && module2.exports) {\n        module2.exports = impl;\n      } else if (define2 && define2.amd) {\n        define2(function() {\n          return impl;\n        });\n      } else {\n        this.xorwow = impl;\n      }\n    })(\n      exports,\n      typeof module == \"object\" && module,\n      typeof define == \"function\" && define\n    );\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xorshift7.js\nvar require_xorshift7 = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xorshift7.js\"(exports, module) {\n    (function(global2, module2, define2) {\n      function XorGen(seed) {\n        var me = this;\n        me.next = function() {\n          var X = me.x, i2 = me.i, t2, v, w;\n          t2 = X[i2];\n          t2 ^= t2 >>> 7;\n          v = t2 ^ t2 << 24;\n          t2 = X[i2 + 1 & 7];\n          v ^= t2 ^ t2 >>> 10;\n          t2 = X[i2 + 3 & 7];\n          v ^= t2 ^ t2 >>> 3;\n          t2 = X[i2 + 4 & 7];\n          v ^= t2 ^ t2 << 7;\n          t2 = X[i2 + 7 & 7];\n          t2 = t2 ^ t2 << 13;\n          v ^= t2 ^ t2 << 9;\n          X[i2] = v;\n          me.i = i2 + 1 & 7;\n          return v;\n        };\n        function init2(me2, seed2) {\n          var j, w, X = [];\n          if (seed2 === (seed2 | 0)) {\n            w = X[0] = seed2;\n          } else {\n            seed2 = \"\" + seed2;\n            for (j = 0; j < seed2.length; ++j) {\n              X[j & 7] = X[j & 7] << 15 ^ seed2.charCodeAt(j) + X[j + 1 & 7] << 13;\n            }\n          }\n          while (X.length < 8)\n            X.push(0);\n          for (j = 0; j < 8 && X[j] === 0; ++j)\n            ;\n          if (j == 8)\n            w = X[7] = -1;\n          else\n            w = X[j];\n          me2.x = X;\n          me2.i = 0;\n          for (j = 256; j > 0; --j) {\n            me2.next();\n          }\n        }\n        init2(me, seed);\n      }\n      function copy(f, t2) {\n        t2.x = f.x.slice();\n        t2.i = f.i;\n        return t2;\n      }\n      function impl(seed, opts) {\n        if (seed == null)\n          seed = +new Date();\n        var xg = new XorGen(seed), state = opts && opts.state, prng = function() {\n          return (xg.next() >>> 0) / 4294967296;\n        };\n        prng.double = function() {\n          do {\n            var top = xg.next() >>> 11, bot = (xg.next() >>> 0) / 4294967296, result = (top + bot) / (1 << 21);\n          } while (result === 0);\n          return result;\n        };\n        prng.int32 = xg.next;\n        prng.quick = prng;\n        if (state) {\n          if (state.x)\n            copy(state, xg);\n          prng.state = function() {\n            return copy(xg, {});\n          };\n        }\n        return prng;\n      }\n      if (module2 && module2.exports) {\n        module2.exports = impl;\n      } else if (define2 && define2.amd) {\n        define2(function() {\n          return impl;\n        });\n      } else {\n        this.xorshift7 = impl;\n      }\n    })(\n      exports,\n      typeof module == \"object\" && module,\n      typeof define == \"function\" && define\n    );\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xor4096.js\nvar require_xor4096 = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xor4096.js\"(exports, module) {\n    (function(global2, module2, define2) {\n      function XorGen(seed) {\n        var me = this;\n        me.next = function() {\n          var w = me.w, X = me.X, i2 = me.i, t2, v;\n          me.w = w = w + 1640531527 | 0;\n          v = X[i2 + 34 & 127];\n          t2 = X[i2 = i2 + 1 & 127];\n          v ^= v << 13;\n          t2 ^= t2 << 17;\n          v ^= v >>> 15;\n          t2 ^= t2 >>> 12;\n          v = X[i2] = v ^ t2;\n          me.i = i2;\n          return v + (w ^ w >>> 16) | 0;\n        };\n        function init2(me2, seed2) {\n          var t2, v, i2, j, w, X = [], limit = 128;\n          if (seed2 === (seed2 | 0)) {\n            v = seed2;\n            seed2 = null;\n          } else {\n            seed2 = seed2 + \"\\0\";\n            v = 0;\n            limit = Math.max(limit, seed2.length);\n          }\n          for (i2 = 0, j = -32; j < limit; ++j) {\n            if (seed2)\n              v ^= seed2.charCodeAt((j + 32) % seed2.length);\n            if (j === 0)\n              w = v;\n            v ^= v << 10;\n            v ^= v >>> 15;\n            v ^= v << 4;\n            v ^= v >>> 13;\n            if (j >= 0) {\n              w = w + 1640531527 | 0;\n              t2 = X[j & 127] ^= v + w;\n              i2 = 0 == t2 ? i2 + 1 : 0;\n            }\n          }\n          if (i2 >= 128) {\n            X[(seed2 && seed2.length || 0) & 127] = -1;\n          }\n          i2 = 127;\n          for (j = 4 * 128; j > 0; --j) {\n            v = X[i2 + 34 & 127];\n            t2 = X[i2 = i2 + 1 & 127];\n            v ^= v << 13;\n            t2 ^= t2 << 17;\n            v ^= v >>> 15;\n            t2 ^= t2 >>> 12;\n            X[i2] = v ^ t2;\n          }\n          me2.w = w;\n          me2.X = X;\n          me2.i = i2;\n        }\n        init2(me, seed);\n      }\n      function copy(f, t2) {\n        t2.i = f.i;\n        t2.w = f.w;\n        t2.X = f.X.slice();\n        return t2;\n      }\n      ;\n      function impl(seed, opts) {\n        if (seed == null)\n          seed = +new Date();\n        var xg = new XorGen(seed), state = opts && opts.state, prng = function() {\n          return (xg.next() >>> 0) / 4294967296;\n        };\n        prng.double = function() {\n          do {\n            var top = xg.next() >>> 11, bot = (xg.next() >>> 0) / 4294967296, result = (top + bot) / (1 << 21);\n          } while (result === 0);\n          return result;\n        };\n        prng.int32 = xg.next;\n        prng.quick = prng;\n        if (state) {\n          if (state.X)\n            copy(state, xg);\n          prng.state = function() {\n            return copy(xg, {});\n          };\n        }\n        return prng;\n      }\n      if (module2 && module2.exports) {\n        module2.exports = impl;\n      } else if (define2 && define2.amd) {\n        define2(function() {\n          return impl;\n        });\n      } else {\n        this.xor4096 = impl;\n      }\n    })(\n      exports,\n      typeof module == \"object\" && module,\n      typeof define == \"function\" && define\n    );\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/tychei.js\nvar require_tychei = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/tychei.js\"(exports, module) {\n    (function(global2, module2, define2) {\n      function XorGen(seed) {\n        var me = this, strseed = \"\";\n        me.next = function() {\n          var b = me.b, c = me.c, d = me.d, a = me.a;\n          b = b << 25 ^ b >>> 7 ^ c;\n          c = c - d | 0;\n          d = d << 24 ^ d >>> 8 ^ a;\n          a = a - b | 0;\n          me.b = b = b << 20 ^ b >>> 12 ^ c;\n          me.c = c = c - d | 0;\n          me.d = d << 16 ^ c >>> 16 ^ a;\n          return me.a = a - b | 0;\n        };\n        me.a = 0;\n        me.b = 0;\n        me.c = 2654435769 | 0;\n        me.d = 1367130551;\n        if (seed === Math.floor(seed)) {\n          me.a = seed / 4294967296 | 0;\n          me.b = seed | 0;\n        } else {\n          strseed += seed;\n        }\n        for (var k = 0; k < strseed.length + 20; k++) {\n          me.b ^= strseed.charCodeAt(k) | 0;\n          me.next();\n        }\n      }\n      function copy(f, t2) {\n        t2.a = f.a;\n        t2.b = f.b;\n        t2.c = f.c;\n        t2.d = f.d;\n        return t2;\n      }\n      ;\n      function impl(seed, opts) {\n        var xg = new XorGen(seed), state = opts && opts.state, prng = function() {\n          return (xg.next() >>> 0) / 4294967296;\n        };\n        prng.double = function() {\n          do {\n            var top = xg.next() >>> 11, bot = (xg.next() >>> 0) / 4294967296, result = (top + bot) / (1 << 21);\n          } while (result === 0);\n          return result;\n        };\n        prng.int32 = xg.next;\n        prng.quick = prng;\n        if (state) {\n          if (typeof state == \"object\")\n            copy(state, xg);\n          prng.state = function() {\n            return copy(xg, {});\n          };\n        }\n        return prng;\n      }\n      if (module2 && module2.exports) {\n        module2.exports = impl;\n      } else if (define2 && define2.amd) {\n        define2(function() {\n          return impl;\n        });\n      } else {\n        this.tychei = impl;\n      }\n    })(\n      exports,\n      typeof module == \"object\" && module,\n      typeof define == \"function\" && define\n    );\n  }\n});\n\n// (disabled):crypto\nvar require_crypto = __commonJS({\n  \"(disabled):crypto\"() {\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/seedrandom.js\nvar require_seedrandom = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/seedrandom.js\"(exports, module) {\n    (function(global2, pool3, math) {\n      var width = 256, chunks = 6, digits = 52, rngname = \"random\", startdenom = math.pow(width, chunks), significance = math.pow(2, digits), overflow = significance * 2, mask = width - 1, nodecrypto;\n      function seedrandom5(seed, options, callback) {\n        var key = [];\n        options = options == true ? { entropy: true } : options || {};\n        var shortseed = mixkey(flatten4(\n          options.entropy ? [seed, tostring(pool3)] : seed == null ? autoseed() : seed,\n          3\n        ), key);\n        var arc4 = new ARC4(key);\n        var prng = function() {\n          var n2 = arc4.g(chunks), d = startdenom, x = 0;\n          while (n2 < significance) {\n            n2 = (n2 + x) * width;\n            d *= width;\n            x = arc4.g(1);\n          }\n          while (n2 >= overflow) {\n            n2 /= 2;\n            d /= 2;\n            x >>>= 1;\n          }\n          return (n2 + x) / d;\n        };\n        prng.int32 = function() {\n          return arc4.g(4) | 0;\n        };\n        prng.quick = function() {\n          return arc4.g(4) / 4294967296;\n        };\n        prng.double = prng;\n        mixkey(tostring(arc4.S), pool3);\n        return (options.pass || callback || function(prng2, seed2, is_math_call, state) {\n          if (state) {\n            if (state.S) {\n              copy(state, arc4);\n            }\n            prng2.state = function() {\n              return copy(arc4, {});\n            };\n          }\n          if (is_math_call) {\n            math[rngname] = prng2;\n            return seed2;\n          } else\n            return prng2;\n        })(\n          prng,\n          shortseed,\n          \"global\" in options ? options.global : this == math,\n          options.state\n        );\n      }\n      function ARC4(key) {\n        var t2, keylen = key.length, me = this, i2 = 0, j = me.i = me.j = 0, s2 = me.S = [];\n        if (!keylen) {\n          key = [keylen++];\n        }\n        while (i2 < width) {\n          s2[i2] = i2++;\n        }\n        for (i2 = 0; i2 < width; i2++) {\n          s2[i2] = s2[j = mask & j + key[i2 % keylen] + (t2 = s2[i2])];\n          s2[j] = t2;\n        }\n        (me.g = function(count2) {\n          var t3, r2 = 0, i3 = me.i, j2 = me.j, s3 = me.S;\n          while (count2--) {\n            t3 = s3[i3 = mask & i3 + 1];\n            r2 = r2 * width + s3[mask & (s3[i3] = s3[j2 = mask & j2 + t3]) + (s3[j2] = t3)];\n          }\n          me.i = i3;\n          me.j = j2;\n          return r2;\n        })(width);\n      }\n      function copy(f, t2) {\n        t2.i = f.i;\n        t2.j = f.j;\n        t2.S = f.S.slice();\n        return t2;\n      }\n      ;\n      function flatten4(obj, depth) {\n        var result = [], typ = typeof obj, prop;\n        if (depth && typ == \"object\") {\n          for (prop in obj) {\n            try {\n              result.push(flatten4(obj[prop], depth - 1));\n            } catch (e2) {\n            }\n          }\n        }\n        return result.length ? result : typ == \"string\" ? obj : obj + \"\\0\";\n      }\n      function mixkey(seed, key) {\n        var stringseed = seed + \"\", smear, j = 0;\n        while (j < stringseed.length) {\n          key[mask & j] = mask & (smear ^= key[mask & j] * 19) + stringseed.charCodeAt(j++);\n        }\n        return tostring(key);\n      }\n      function autoseed() {\n        try {\n          var out;\n          if (nodecrypto && (out = nodecrypto.randomBytes)) {\n            out = out(width);\n          } else {\n            out = new Uint8Array(width);\n            (global2.crypto || global2.msCrypto).getRandomValues(out);\n          }\n          return tostring(out);\n        } catch (e2) {\n          var browser = global2.navigator, plugins = browser && browser.plugins;\n          return [+new Date(), global2, plugins, global2.screen, tostring(pool3)];\n        }\n      }\n      function tostring(a) {\n        return String.fromCharCode.apply(0, a);\n      }\n      mixkey(math.random(), pool3);\n      if (typeof module == \"object\" && module.exports) {\n        module.exports = seedrandom5;\n        try {\n          nodecrypto = require_crypto();\n        } catch (ex) {\n        }\n      } else if (typeof define == \"function\" && define.amd) {\n        define(function() {\n          return seedrandom5;\n        });\n      } else {\n        math[\"seed\" + rngname] = seedrandom5;\n      }\n    })(\n      typeof self !== \"undefined\" ? self : exports,\n      [],\n      Math\n    );\n  }\n});\n\n// node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/index.js\nvar require_seedrandom2 = __commonJS({\n  \"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/index.js\"(exports, module) {\n    var alea5 = require_alea();\n    var xor128 = require_xor128();\n    var xorwow = require_xorwow();\n    var xorshift7 = require_xorshift7();\n    var xor4096 = require_xor4096();\n    var tychei = require_tychei();\n    var sr = require_seedrandom();\n    sr.alea = alea5;\n    sr.xor128 = xor128;\n    sr.xorwow = xorwow;\n    sr.xorshift7 = xorshift7;\n    sr.xor4096 = xor4096;\n    sr.tychei = tychei;\n    module.exports = sr;\n  }\n});\n\n// (disabled):node_modules/.pnpm/string_decoder@1.3.0/node_modules/string_decoder/lib/string_decoder.js\nvar require_string_decoder = __commonJS({\n  \"(disabled):node_modules/.pnpm/string_decoder@1.3.0/node_modules/string_decoder/lib/string_decoder.js\"() {\n  }\n});\n\n// (disabled):fs\nvar require_fs = __commonJS({\n  \"(disabled):fs\"() {\n  }\n});\n\n// (disabled):path\nvar require_path = __commonJS({\n  \"(disabled):path\"() {\n  }\n});\n\n// (disabled):worker_threads\nvar require_worker_threads = __commonJS({\n  \"(disabled):worker_threads\"() {\n  }\n});\n\n// (disabled):perf_hooks\nvar require_perf_hooks = __commonJS({\n  \"(disabled):perf_hooks\"() {\n  }\n});\n\n// (disabled):os\nvar require_os = __commonJS({\n  \"(disabled):os\"() {\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.js\nvar require_tfjs_backend_wasm_threaded_simd = __commonJS({\n  \"node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.js\"(exports, module) {\n    var WasmBackendModuleThreadedSimd2 = (() => {\n      var _scriptDir = typeof document !== \"undefined\" && document.currentScript ? document.currentScript.src : void 0;\n      if (typeof __filename !== \"undefined\")\n        _scriptDir = _scriptDir || __filename;\n      return function(WasmBackendModuleThreadedSimd3) {\n        WasmBackendModuleThreadedSimd3 = WasmBackendModuleThreadedSimd3 || {};\n        function GROWABLE_HEAP_I8() {\n          if (wasmMemory.buffer != buffer2) {\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n          }\n          return HEAP8;\n        }\n        function GROWABLE_HEAP_U8() {\n          if (wasmMemory.buffer != buffer2) {\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n          }\n          return HEAPU8;\n        }\n        function GROWABLE_HEAP_I16() {\n          if (wasmMemory.buffer != buffer2) {\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n          }\n          return HEAP16;\n        }\n        function GROWABLE_HEAP_U16() {\n          if (wasmMemory.buffer != buffer2) {\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n          }\n          return HEAPU16;\n        }\n        function GROWABLE_HEAP_I32() {\n          if (wasmMemory.buffer != buffer2) {\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n          }\n          return HEAP32;\n        }\n        function GROWABLE_HEAP_F32() {\n          if (wasmMemory.buffer != buffer2) {\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n          }\n          return HEAPF32;\n        }\n        function GROWABLE_HEAP_F64() {\n          if (wasmMemory.buffer != buffer2) {\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n          }\n          return HEAPF64;\n        }\n        var Module = typeof WasmBackendModuleThreadedSimd3 !== \"undefined\" ? WasmBackendModuleThreadedSimd3 : {};\n        var readyPromiseResolve, readyPromiseReject;\n        Module[\"ready\"] = new Promise(function(resolve, reject) {\n          readyPromiseResolve = resolve;\n          readyPromiseReject = reject;\n        });\n        var beforeListeners;\n        if (typeof process !== \"undefined\" && process.listeners) {\n          beforeListeners = { uncaughtException: process.listeners(\"uncaughtException\"), unhandledRejection: process.listeners(\"unhandledRejection\") };\n        }\n        var moduleOverrides = Object.assign({}, Module);\n        var arguments_ = [];\n        var thisProgram = \"./this.program\";\n        var quit_ = (status, toThrow) => {\n          throw toThrow;\n        };\n        var ENVIRONMENT_IS_WEB = typeof window === \"object\";\n        var ENVIRONMENT_IS_WORKER = typeof importScripts === \"function\";\n        var ENVIRONMENT_IS_NODE = typeof process === \"object\" && typeof process.versions === \"object\" && typeof process.versions.node === \"string\";\n        var ENVIRONMENT_IS_PTHREAD = Module[\"ENVIRONMENT_IS_PTHREAD\"] || false;\n        var scriptDirectory = \"\";\n        function locateFile(path) {\n          if (Module[\"locateFile\"]) {\n            return Module[\"locateFile\"](path, scriptDirectory);\n          }\n          return scriptDirectory + path;\n        }\n        var read_, readAsync, readBinary, setWindowTitle;\n        function logExceptionOnExit(e2) {\n          if (e2 instanceof ExitStatus)\n            return;\n          let toLog = e2;\n          err(\"exiting due to exception: \" + toLog);\n        }\n        var fs;\n        var nodePath;\n        var requireNodeFS;\n        if (ENVIRONMENT_IS_NODE) {\n          if (ENVIRONMENT_IS_WORKER) {\n            scriptDirectory = require_path().dirname(scriptDirectory) + \"/\";\n          } else {\n            scriptDirectory = __dirname + \"/\";\n          }\n          requireNodeFS = () => {\n            if (!nodePath) {\n              fs = require_fs();\n              nodePath = require_path();\n            }\n          };\n          read_ = function shell_read(filename, binary) {\n            requireNodeFS();\n            filename = nodePath[\"normalize\"](filename);\n            return fs.readFileSync(filename, binary ? void 0 : \"utf8\");\n          };\n          readBinary = (filename) => {\n            var ret = read_(filename, true);\n            if (!ret.buffer) {\n              ret = new Uint8Array(ret);\n            }\n            return ret;\n          };\n          readAsync = (filename, onload, onerror) => {\n            requireNodeFS();\n            filename = nodePath[\"normalize\"](filename);\n            fs.readFile(filename, function(err2, data) {\n              if (err2)\n                onerror(err2);\n              else\n                onload(data.buffer);\n            });\n          };\n          if (process[\"argv\"].length > 1) {\n            thisProgram = process[\"argv\"][1].replace(/\\\\/g, \"/\");\n          }\n          arguments_ = process[\"argv\"].slice(2);\n          process[\"on\"](\"uncaughtException\", function(ex) {\n            if (!(ex instanceof ExitStatus)) {\n              throw ex;\n            }\n          });\n          process[\"on\"](\"unhandledRejection\", function(reason) {\n            throw reason;\n          });\n          quit_ = (status, toThrow) => {\n            if (keepRuntimeAlive()) {\n              process[\"exitCode\"] = status;\n              throw toThrow;\n            }\n            logExceptionOnExit(toThrow);\n            process[\"exit\"](status);\n          };\n          Module[\"inspect\"] = function() {\n            return \"[Emscripten Module object]\";\n          };\n          let nodeWorkerThreads;\n          try {\n            nodeWorkerThreads = require_worker_threads();\n          } catch (e2) {\n            console.error('The \"worker_threads\" module is not supported in this node.js build - perhaps a newer version is needed?');\n            throw e2;\n          }\n          global.Worker = nodeWorkerThreads.Worker;\n        } else if (ENVIRONMENT_IS_WEB || ENVIRONMENT_IS_WORKER) {\n          if (ENVIRONMENT_IS_WORKER) {\n            scriptDirectory = self.location.href;\n          } else if (typeof document !== \"undefined\" && document.currentScript) {\n            scriptDirectory = document.currentScript.src;\n          }\n          if (typeof _scriptDir !== \"undefined\" && _scriptDir) {\n            scriptDirectory = _scriptDir;\n          }\n          if (scriptDirectory.indexOf(\"blob:\") !== 0) {\n            scriptDirectory = scriptDirectory.substr(0, scriptDirectory.replace(/[?#].*/, \"\").lastIndexOf(\"/\") + 1);\n          } else {\n            scriptDirectory = \"\";\n          }\n          if (!ENVIRONMENT_IS_NODE) {\n            read_ = (url) => {\n              var xhr = new XMLHttpRequest();\n              xhr.open(\"GET\", url, false);\n              xhr.send(null);\n              return xhr.responseText;\n            };\n            if (ENVIRONMENT_IS_WORKER) {\n              readBinary = (url) => {\n                var xhr = new XMLHttpRequest();\n                xhr.open(\"GET\", url, false);\n                xhr.responseType = \"arraybuffer\";\n                xhr.send(null);\n                return new Uint8Array(xhr.response);\n              };\n            }\n            readAsync = (url, onload, onerror) => {\n              var xhr = new XMLHttpRequest();\n              xhr.open(\"GET\", url, true);\n              xhr.responseType = \"arraybuffer\";\n              xhr.onload = () => {\n                if (xhr.status == 200 || xhr.status == 0 && xhr.response) {\n                  onload(xhr.response);\n                  return;\n                }\n                onerror();\n              };\n              xhr.onerror = onerror;\n              xhr.send(null);\n            };\n          }\n          setWindowTitle = (title) => document.title = title;\n        } else {\n        }\n        if (ENVIRONMENT_IS_NODE) {\n          if (typeof performance === \"undefined\") {\n            global.performance = require_perf_hooks().performance;\n          }\n        }\n        var defaultPrint = console.log.bind(console);\n        var defaultPrintErr = console.warn.bind(console);\n        if (ENVIRONMENT_IS_NODE) {\n          requireNodeFS();\n          defaultPrint = (str) => fs.writeSync(1, str + \"\\n\");\n          defaultPrintErr = (str) => fs.writeSync(2, str + \"\\n\");\n        }\n        var out = Module[\"print\"] || defaultPrint;\n        var err = Module[\"printErr\"] || defaultPrintErr;\n        Object.assign(Module, moduleOverrides);\n        moduleOverrides = null;\n        if (Module[\"arguments\"])\n          arguments_ = Module[\"arguments\"];\n        if (Module[\"thisProgram\"])\n          thisProgram = Module[\"thisProgram\"];\n        if (Module[\"quit\"])\n          quit_ = Module[\"quit\"];\n        var POINTER_SIZE = 4;\n        function warnOnce(text) {\n          if (!warnOnce.shown)\n            warnOnce.shown = {};\n          if (!warnOnce.shown[text]) {\n            warnOnce.shown[text] = 1;\n            err(text);\n          }\n        }\n        function convertJsFunctionToWasm(func2, sig) {\n          if (typeof WebAssembly.Function === \"function\") {\n            var typeNames = { \"i\": \"i32\", \"j\": \"i64\", \"f\": \"f32\", \"d\": \"f64\" };\n            var type = { parameters: [], results: sig[0] == \"v\" ? [] : [typeNames[sig[0]]] };\n            for (var i2 = 1; i2 < sig.length; ++i2) {\n              type.parameters.push(typeNames[sig[i2]]);\n            }\n            return new WebAssembly.Function(type, func2);\n          }\n          var typeSection = [1, 0, 1, 96];\n          var sigRet = sig.slice(0, 1);\n          var sigParam = sig.slice(1);\n          var typeCodes = { \"i\": 127, \"j\": 126, \"f\": 125, \"d\": 124 };\n          typeSection.push(sigParam.length);\n          for (var i2 = 0; i2 < sigParam.length; ++i2) {\n            typeSection.push(typeCodes[sigParam[i2]]);\n          }\n          if (sigRet == \"v\") {\n            typeSection.push(0);\n          } else {\n            typeSection = typeSection.concat([1, typeCodes[sigRet]]);\n          }\n          typeSection[1] = typeSection.length - 2;\n          var bytes = new Uint8Array([0, 97, 115, 109, 1, 0, 0, 0].concat(typeSection, [2, 7, 1, 1, 101, 1, 102, 0, 0, 7, 5, 1, 1, 102, 0, 0]));\n          var module2 = new WebAssembly.Module(bytes);\n          var instance = new WebAssembly.Instance(module2, { \"e\": { \"f\": func2 } });\n          var wrappedFunc = instance.exports[\"f\"];\n          return wrappedFunc;\n        }\n        var freeTableIndexes = [];\n        var functionsInTableMap;\n        function getEmptyTableSlot() {\n          if (freeTableIndexes.length) {\n            return freeTableIndexes.pop();\n          }\n          try {\n            wasmTable.grow(1);\n          } catch (err2) {\n            if (!(err2 instanceof RangeError)) {\n              throw err2;\n            }\n            throw \"Unable to grow wasm table. Set ALLOW_TABLE_GROWTH.\";\n          }\n          return wasmTable.length - 1;\n        }\n        function updateTableMap(offset, count2) {\n          for (var i2 = offset; i2 < offset + count2; i2++) {\n            var item = getWasmTableEntry(i2);\n            if (item) {\n              functionsInTableMap.set(item, i2);\n            }\n          }\n        }\n        var tempRet0 = 0;\n        var setTempRet0 = (value) => {\n          tempRet0 = value;\n        };\n        var Atomics_load = Atomics.load;\n        var Atomics_store = Atomics.store;\n        var Atomics_compareExchange = Atomics.compareExchange;\n        var wasmBinary;\n        if (Module[\"wasmBinary\"])\n          wasmBinary = Module[\"wasmBinary\"];\n        var noExitRuntime = Module[\"noExitRuntime\"] || true;\n        if (typeof WebAssembly !== \"object\") {\n          abort(\"no native wasm support detected\");\n        }\n        var wasmMemory;\n        var wasmModule;\n        var ABORT = false;\n        var EXITSTATUS;\n        function assert3(condition, text) {\n          if (!condition) {\n            abort(text);\n          }\n        }\n        function getCFunc(ident) {\n          var func2 = Module[\"_\" + ident];\n          return func2;\n        }\n        function ccall(ident, returnType, argTypes, args, opts) {\n          var toC = { \"string\": function(str) {\n            var ret2 = 0;\n            if (str !== null && str !== void 0 && str !== 0) {\n              var len = (str.length << 2) + 1;\n              ret2 = stackAlloc(len);\n              stringToUTF8(str, ret2, len);\n            }\n            return ret2;\n          }, \"array\": function(arr) {\n            var ret2 = stackAlloc(arr.length);\n            writeArrayToMemory(arr, ret2);\n            return ret2;\n          } };\n          function convertReturnValue(ret2) {\n            if (returnType === \"string\")\n              return UTF8ToString(ret2);\n            if (returnType === \"boolean\")\n              return Boolean(ret2);\n            return ret2;\n          }\n          var func2 = getCFunc(ident);\n          var cArgs = [];\n          var stack2 = 0;\n          if (args) {\n            for (var i2 = 0; i2 < args.length; i2++) {\n              var converter = toC[argTypes[i2]];\n              if (converter) {\n                if (stack2 === 0)\n                  stack2 = stackSave();\n                cArgs[i2] = converter(args[i2]);\n              } else {\n                cArgs[i2] = args[i2];\n              }\n            }\n          }\n          var ret = func2.apply(null, cArgs);\n          function onDone(ret2) {\n            if (stack2 !== 0)\n              stackRestore(stack2);\n            return convertReturnValue(ret2);\n          }\n          ret = onDone(ret);\n          return ret;\n        }\n        function cwrap(ident, returnType, argTypes, opts) {\n          argTypes = argTypes || [];\n          var numericArgs = argTypes.every(function(type) {\n            return type === \"number\";\n          });\n          var numericRet = returnType !== \"string\";\n          if (numericRet && numericArgs && !opts) {\n            return getCFunc(ident);\n          }\n          return function() {\n            return ccall(ident, returnType, argTypes, arguments, opts);\n          };\n        }\n        var ALLOC_STACK = 1;\n        function TextDecoderWrapper(encoding) {\n          var textDecoder = new TextDecoder(encoding);\n          this.decode = (data) => {\n            if (data.buffer instanceof SharedArrayBuffer) {\n              data = new Uint8Array(data);\n            }\n            return textDecoder.decode.call(textDecoder, data);\n          };\n        }\n        var UTF8Decoder = typeof TextDecoder !== \"undefined\" ? new TextDecoderWrapper(\"utf8\") : void 0;\n        function UTF8ArrayToString(heap, idx, maxBytesToRead) {\n          var endIdx = idx + maxBytesToRead;\n          var endPtr = idx;\n          while (heap[endPtr] && !(endPtr >= endIdx))\n            ++endPtr;\n          if (endPtr - idx > 16 && heap.subarray && UTF8Decoder) {\n            return UTF8Decoder.decode(heap.subarray(idx, endPtr));\n          } else {\n            var str = \"\";\n            while (idx < endPtr) {\n              var u0 = heap[idx++];\n              if (!(u0 & 128)) {\n                str += String.fromCharCode(u0);\n                continue;\n              }\n              var u1 = heap[idx++] & 63;\n              if ((u0 & 224) == 192) {\n                str += String.fromCharCode((u0 & 31) << 6 | u1);\n                continue;\n              }\n              var u2 = heap[idx++] & 63;\n              if ((u0 & 240) == 224) {\n                u0 = (u0 & 15) << 12 | u1 << 6 | u2;\n              } else {\n                u0 = (u0 & 7) << 18 | u1 << 12 | u2 << 6 | heap[idx++] & 63;\n              }\n              if (u0 < 65536) {\n                str += String.fromCharCode(u0);\n              } else {\n                var ch = u0 - 65536;\n                str += String.fromCharCode(55296 | ch >> 10, 56320 | ch & 1023);\n              }\n            }\n          }\n          return str;\n        }\n        function UTF8ToString(ptr, maxBytesToRead) {\n          return ptr ? UTF8ArrayToString(GROWABLE_HEAP_U8(), ptr, maxBytesToRead) : \"\";\n        }\n        function stringToUTF8Array(str, heap, outIdx, maxBytesToWrite) {\n          if (!(maxBytesToWrite > 0))\n            return 0;\n          var startIdx = outIdx;\n          var endIdx = outIdx + maxBytesToWrite - 1;\n          for (var i2 = 0; i2 < str.length; ++i2) {\n            var u = str.charCodeAt(i2);\n            if (u >= 55296 && u <= 57343) {\n              var u1 = str.charCodeAt(++i2);\n              u = 65536 + ((u & 1023) << 10) | u1 & 1023;\n            }\n            if (u <= 127) {\n              if (outIdx >= endIdx)\n                break;\n              heap[outIdx++] = u;\n            } else if (u <= 2047) {\n              if (outIdx + 1 >= endIdx)\n                break;\n              heap[outIdx++] = 192 | u >> 6;\n              heap[outIdx++] = 128 | u & 63;\n            } else if (u <= 65535) {\n              if (outIdx + 2 >= endIdx)\n                break;\n              heap[outIdx++] = 224 | u >> 12;\n              heap[outIdx++] = 128 | u >> 6 & 63;\n              heap[outIdx++] = 128 | u & 63;\n            } else {\n              if (outIdx + 3 >= endIdx)\n                break;\n              heap[outIdx++] = 240 | u >> 18;\n              heap[outIdx++] = 128 | u >> 12 & 63;\n              heap[outIdx++] = 128 | u >> 6 & 63;\n              heap[outIdx++] = 128 | u & 63;\n            }\n          }\n          heap[outIdx] = 0;\n          return outIdx - startIdx;\n        }\n        function stringToUTF8(str, outPtr, maxBytesToWrite) {\n          return stringToUTF8Array(str, GROWABLE_HEAP_U8(), outPtr, maxBytesToWrite);\n        }\n        function lengthBytesUTF8(str) {\n          var len = 0;\n          for (var i2 = 0; i2 < str.length; ++i2) {\n            var u = str.charCodeAt(i2);\n            if (u >= 55296 && u <= 57343)\n              u = 65536 + ((u & 1023) << 10) | str.charCodeAt(++i2) & 1023;\n            if (u <= 127)\n              ++len;\n            else if (u <= 2047)\n              len += 2;\n            else if (u <= 65535)\n              len += 3;\n            else\n              len += 4;\n          }\n          return len;\n        }\n        var UTF16Decoder = typeof TextDecoder !== \"undefined\" ? new TextDecoderWrapper(\"utf-16le\") : void 0;\n        function writeArrayToMemory(array2, buffer3) {\n          GROWABLE_HEAP_I8().set(array2, buffer3);\n        }\n        function writeAsciiToMemory(str, buffer3, dontAddNull) {\n          for (var i2 = 0; i2 < str.length; ++i2) {\n            GROWABLE_HEAP_I8()[buffer3++ >> 0] = str.charCodeAt(i2);\n          }\n          if (!dontAddNull)\n            GROWABLE_HEAP_I8()[buffer3 >> 0] = 0;\n        }\n        function alignUp(x, multiple) {\n          if (x % multiple > 0) {\n            x += multiple - x % multiple;\n          }\n          return x;\n        }\n        var buffer2, HEAP8, HEAPU8, HEAP16, HEAPU16, HEAP32, HEAPU32, HEAPF32, HEAPF64;\n        if (ENVIRONMENT_IS_PTHREAD) {\n          buffer2 = Module[\"buffer\"];\n        }\n        function updateGlobalBufferAndViews(buf) {\n          buffer2 = buf;\n          Module[\"HEAP8\"] = HEAP8 = new Int8Array(buf);\n          Module[\"HEAP16\"] = HEAP16 = new Int16Array(buf);\n          Module[\"HEAP32\"] = HEAP32 = new Int32Array(buf);\n          Module[\"HEAPU8\"] = HEAPU8 = new Uint8Array(buf);\n          Module[\"HEAPU16\"] = HEAPU16 = new Uint16Array(buf);\n          Module[\"HEAPU32\"] = HEAPU32 = new Uint32Array(buf);\n          Module[\"HEAPF32\"] = HEAPF32 = new Float32Array(buf);\n          Module[\"HEAPF64\"] = HEAPF64 = new Float64Array(buf);\n        }\n        var INITIAL_MEMORY = Module[\"INITIAL_MEMORY\"] || 16777216;\n        if (ENVIRONMENT_IS_PTHREAD) {\n          wasmMemory = Module[\"wasmMemory\"];\n          buffer2 = Module[\"buffer\"];\n        } else {\n          if (Module[\"wasmMemory\"]) {\n            wasmMemory = Module[\"wasmMemory\"];\n          } else {\n            wasmMemory = new WebAssembly.Memory({ \"initial\": INITIAL_MEMORY / 65536, \"maximum\": 2147483648 / 65536, \"shared\": true });\n            if (!(wasmMemory.buffer instanceof SharedArrayBuffer)) {\n              err(\"requested a shared WebAssembly.Memory but the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag\");\n              if (ENVIRONMENT_IS_NODE) {\n                console.log(\"(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)\");\n              }\n              throw Error(\"bad memory\");\n            }\n          }\n        }\n        if (wasmMemory) {\n          buffer2 = wasmMemory.buffer;\n        }\n        INITIAL_MEMORY = buffer2.byteLength;\n        updateGlobalBufferAndViews(buffer2);\n        var wasmTable;\n        var __ATPRERUN__ = [];\n        var __ATINIT__ = [];\n        var __ATEXIT__ = [];\n        var __ATPOSTRUN__ = [];\n        var runtimeInitialized = false;\n        var runtimeExited = false;\n        var runtimeKeepaliveCounter = 0;\n        function keepRuntimeAlive() {\n          return noExitRuntime || runtimeKeepaliveCounter > 0;\n        }\n        function preRun() {\n          if (Module[\"preRun\"]) {\n            if (typeof Module[\"preRun\"] == \"function\")\n              Module[\"preRun\"] = [Module[\"preRun\"]];\n            while (Module[\"preRun\"].length) {\n              addOnPreRun(Module[\"preRun\"].shift());\n            }\n          }\n          callRuntimeCallbacks(__ATPRERUN__);\n        }\n        function initRuntime() {\n          runtimeInitialized = true;\n          if (ENVIRONMENT_IS_PTHREAD)\n            return;\n          callRuntimeCallbacks(__ATINIT__);\n        }\n        function exitRuntime() {\n          if (ENVIRONMENT_IS_PTHREAD)\n            return;\n          PThread.terminateAllThreads();\n          runtimeExited = true;\n        }\n        function postRun() {\n          if (ENVIRONMENT_IS_PTHREAD)\n            return;\n          if (Module[\"postRun\"]) {\n            if (typeof Module[\"postRun\"] == \"function\")\n              Module[\"postRun\"] = [Module[\"postRun\"]];\n            while (Module[\"postRun\"].length) {\n              addOnPostRun(Module[\"postRun\"].shift());\n            }\n          }\n          callRuntimeCallbacks(__ATPOSTRUN__);\n        }\n        function addOnPreRun(cb) {\n          __ATPRERUN__.unshift(cb);\n        }\n        function addOnInit(cb) {\n          __ATINIT__.unshift(cb);\n        }\n        function addOnPostRun(cb) {\n          __ATPOSTRUN__.unshift(cb);\n        }\n        var runDependencies = 0;\n        var runDependencyWatcher = null;\n        var dependenciesFulfilled = null;\n        function addRunDependency(id) {\n          runDependencies++;\n          if (Module[\"monitorRunDependencies\"]) {\n            Module[\"monitorRunDependencies\"](runDependencies);\n          }\n        }\n        function removeRunDependency(id) {\n          runDependencies--;\n          if (Module[\"monitorRunDependencies\"]) {\n            Module[\"monitorRunDependencies\"](runDependencies);\n          }\n          if (runDependencies == 0) {\n            if (runDependencyWatcher !== null) {\n              clearInterval(runDependencyWatcher);\n              runDependencyWatcher = null;\n            }\n            if (dependenciesFulfilled) {\n              var callback = dependenciesFulfilled;\n              dependenciesFulfilled = null;\n              callback();\n            }\n          }\n        }\n        Module[\"preloadedImages\"] = {};\n        Module[\"preloadedAudios\"] = {};\n        function abort(what) {\n          if (ENVIRONMENT_IS_PTHREAD) {\n            postMessage({ \"cmd\": \"onAbort\", \"arg\": what });\n          } else {\n            if (Module[\"onAbort\"]) {\n              Module[\"onAbort\"](what);\n            }\n          }\n          what = \"Aborted(\" + what + \")\";\n          err(what);\n          ABORT = true;\n          EXITSTATUS = 1;\n          what += \". Build with -s ASSERTIONS=1 for more info.\";\n          var e2 = new WebAssembly.RuntimeError(what);\n          readyPromiseReject(e2);\n          throw e2;\n        }\n        var dataURIPrefix = \"data:application/octet-stream;base64,\";\n        function isDataURI(filename) {\n          return filename.startsWith(dataURIPrefix);\n        }\n        function isFileURI(filename) {\n          return filename.startsWith(\"file://\");\n        }\n        var wasmBinaryFile;\n        wasmBinaryFile = \"tfjs-backend-wasm-threaded-simd.wasm\";\n        if (!isDataURI(wasmBinaryFile)) {\n          wasmBinaryFile = locateFile(wasmBinaryFile);\n        }\n        function getBinary(file) {\n          try {\n            if (file == wasmBinaryFile && wasmBinary) {\n              return new Uint8Array(wasmBinary);\n            }\n            if (readBinary) {\n              return readBinary(file);\n            } else {\n              throw \"both async and sync fetching of the wasm failed\";\n            }\n          } catch (err2) {\n            abort(err2);\n          }\n        }\n        function getBinaryPromise() {\n          if (!wasmBinary && (ENVIRONMENT_IS_WEB || ENVIRONMENT_IS_WORKER)) {\n            if (typeof fetch === \"function\" && !isFileURI(wasmBinaryFile)) {\n              return fetch(wasmBinaryFile, { credentials: \"same-origin\" }).then(function(response) {\n                if (!response[\"ok\"]) {\n                  throw \"failed to load wasm binary file at '\" + wasmBinaryFile + \"'\";\n                }\n                return response[\"arrayBuffer\"]();\n              }).catch(function() {\n                return getBinary(wasmBinaryFile);\n              });\n            } else {\n              if (readAsync) {\n                return new Promise(function(resolve, reject) {\n                  readAsync(wasmBinaryFile, function(response) {\n                    resolve(new Uint8Array(response));\n                  }, reject);\n                });\n              }\n            }\n          }\n          return Promise.resolve().then(function() {\n            return getBinary(wasmBinaryFile);\n          });\n        }\n        function createWasm() {\n          var info = { \"env\": asmLibraryArg, \"wasi_snapshot_preview1\": asmLibraryArg };\n          function receiveInstance(instance, module2) {\n            var exports3 = instance.exports;\n            Module[\"asm\"] = exports3;\n            registerTlsInit(Module[\"asm\"][\"emscripten_tls_init\"]);\n            wasmTable = Module[\"asm\"][\"__indirect_function_table\"];\n            addOnInit(Module[\"asm\"][\"__wasm_call_ctors\"]);\n            wasmModule = module2;\n            if (!ENVIRONMENT_IS_PTHREAD) {\n              var numWorkersToLoad = PThread.unusedWorkers.length;\n              PThread.unusedWorkers.forEach(function(w) {\n                PThread.loadWasmModuleToWorker(w, function() {\n                  if (!--numWorkersToLoad)\n                    removeRunDependency(\"wasm-instantiate\");\n                });\n              });\n            }\n          }\n          if (!ENVIRONMENT_IS_PTHREAD) {\n            addRunDependency(\"wasm-instantiate\");\n          }\n          function receiveInstantiationResult(result) {\n            receiveInstance(result[\"instance\"], result[\"module\"]);\n          }\n          function instantiateArrayBuffer(receiver) {\n            return getBinaryPromise().then(function(binary) {\n              return WebAssembly.instantiate(binary, info);\n            }).then(function(instance) {\n              return instance;\n            }).then(receiver, function(reason) {\n              err(\"failed to asynchronously prepare wasm: \" + reason);\n              abort(reason);\n            });\n          }\n          function instantiateAsync() {\n            if (!wasmBinary && typeof WebAssembly.instantiateStreaming === \"function\" && !isDataURI(wasmBinaryFile) && !isFileURI(wasmBinaryFile) && typeof fetch === \"function\") {\n              return fetch(wasmBinaryFile, { credentials: \"same-origin\" }).then(function(response) {\n                var result = WebAssembly.instantiateStreaming(response, info);\n                return result.then(receiveInstantiationResult, function(reason) {\n                  err(\"wasm streaming compile failed: \" + reason);\n                  err(\"falling back to ArrayBuffer instantiation\");\n                  return instantiateArrayBuffer(receiveInstantiationResult);\n                });\n              });\n            } else {\n              return instantiateArrayBuffer(receiveInstantiationResult);\n            }\n          }\n          if (Module[\"instantiateWasm\"]) {\n            try {\n              var exports2 = Module[\"instantiateWasm\"](info, receiveInstance);\n              return exports2;\n            } catch (e2) {\n              err(\"Module.instantiateWasm callback failed with error: \" + e2);\n              return false;\n            }\n          }\n          instantiateAsync().catch(readyPromiseReject);\n          return {};\n        }\n        var tempDouble;\n        var tempI64;\n        var ASM_CONSTS = {};\n        function callRuntimeCallbacks(callbacks2) {\n          while (callbacks2.length > 0) {\n            var callback = callbacks2.shift();\n            if (typeof callback == \"function\") {\n              callback(Module);\n              continue;\n            }\n            var func2 = callback.func;\n            if (typeof func2 === \"number\") {\n              if (callback.arg === void 0) {\n                getWasmTableEntry(func2)();\n              } else {\n                getWasmTableEntry(func2)(callback.arg);\n              }\n            } else {\n              func2(callback.arg === void 0 ? null : callback.arg);\n            }\n          }\n        }\n        function withStackSave(f) {\n          var stack2 = stackSave();\n          var ret = f();\n          stackRestore(stack2);\n          return ret;\n        }\n        function demangle(func2) {\n          return func2;\n        }\n        function demangleAll(text) {\n          var regex = /\\b_Z[\\w\\d_]+/g;\n          return text.replace(regex, function(x) {\n            var y = demangle(x);\n            return x === y ? x : y + \" [\" + x + \"]\";\n          });\n        }\n        function killThread(pthread_ptr) {\n          GROWABLE_HEAP_I32()[pthread_ptr >> 2] = 0;\n          var pthread = PThread.pthreads[pthread_ptr];\n          delete PThread.pthreads[pthread_ptr];\n          pthread.worker.terminate();\n          __emscripten_thread_free_data(pthread_ptr);\n          PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(pthread.worker), 1);\n          pthread.worker.pthread = void 0;\n        }\n        function cancelThread(pthread_ptr) {\n          var pthread = PThread.pthreads[pthread_ptr];\n          pthread.worker.postMessage({ \"cmd\": \"cancel\" });\n        }\n        function cleanupThread(pthread_ptr) {\n          var pthread = PThread.pthreads[pthread_ptr];\n          if (pthread) {\n            GROWABLE_HEAP_I32()[pthread_ptr >> 2] = 0;\n            var worker = pthread.worker;\n            PThread.returnWorkerToPool(worker);\n          }\n        }\n        function _exit(status) {\n          exit(status);\n        }\n        function handleException(e2) {\n          if (e2 instanceof ExitStatus || e2 == \"unwind\") {\n            return EXITSTATUS;\n          }\n          quit_(1, e2);\n        }\n        var PThread = { unusedWorkers: [], runningWorkers: [], tlsInitFunctions: [], init: function() {\n          if (ENVIRONMENT_IS_PTHREAD) {\n            PThread.initWorker();\n          } else {\n            PThread.initMainThread();\n          }\n        }, initMainThread: function() {\n          var pthreadPoolSize = 8;\n          for (var i2 = 0; i2 < pthreadPoolSize; ++i2) {\n            PThread.allocateUnusedWorker();\n          }\n        }, initWorker: function() {\n          noExitRuntime = false;\n        }, pthreads: {}, setExitStatus: function(status) {\n          EXITSTATUS = status;\n        }, terminateAllThreads: function() {\n          for (var t2 in PThread.pthreads) {\n            var pthread = PThread.pthreads[t2];\n            if (pthread && pthread.worker) {\n              PThread.returnWorkerToPool(pthread.worker);\n            }\n          }\n          for (var i2 = 0; i2 < PThread.unusedWorkers.length; ++i2) {\n            var worker = PThread.unusedWorkers[i2];\n            worker.terminate();\n          }\n          PThread.unusedWorkers = [];\n        }, returnWorkerToPool: function(worker) {\n          PThread.runWithoutMainThreadQueuedCalls(function() {\n            delete PThread.pthreads[worker.pthread.threadInfoStruct];\n            PThread.unusedWorkers.push(worker);\n            PThread.runningWorkers.splice(PThread.runningWorkers.indexOf(worker), 1);\n            __emscripten_thread_free_data(worker.pthread.threadInfoStruct);\n            worker.pthread = void 0;\n          });\n        }, runWithoutMainThreadQueuedCalls: function(func2) {\n          GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls >> 2] = 0;\n          try {\n            func2();\n          } finally {\n            GROWABLE_HEAP_I32()[__emscripten_allow_main_runtime_queued_calls >> 2] = 1;\n          }\n        }, receiveObjectTransfer: function(data) {\n        }, threadInit: function() {\n          for (var i2 in PThread.tlsInitFunctions) {\n            PThread.tlsInitFunctions[i2]();\n          }\n        }, loadWasmModuleToWorker: function(worker, onFinishedLoading) {\n          worker.onmessage = (e2) => {\n            var d = e2[\"data\"];\n            var cmd = d[\"cmd\"];\n            if (worker.pthread)\n              PThread.currentProxiedOperationCallerThread = worker.pthread.threadInfoStruct;\n            if (d[\"targetThread\"] && d[\"targetThread\"] != _pthread_self()) {\n              var thread = PThread.pthreads[d.targetThread];\n              if (thread) {\n                thread.worker.postMessage(d, d[\"transferList\"]);\n              } else {\n                err('Internal error! Worker sent a message \"' + cmd + '\" to target pthread ' + d[\"targetThread\"] + \", but that thread no longer exists!\");\n              }\n              PThread.currentProxiedOperationCallerThread = void 0;\n              return;\n            }\n            if (cmd === \"processQueuedMainThreadWork\") {\n              _emscripten_main_thread_process_queued_calls();\n            } else if (cmd === \"spawnThread\") {\n              spawnThread(d);\n            } else if (cmd === \"cleanupThread\") {\n              cleanupThread(d[\"thread\"]);\n            } else if (cmd === \"killThread\") {\n              killThread(d[\"thread\"]);\n            } else if (cmd === \"cancelThread\") {\n              cancelThread(d[\"thread\"]);\n            } else if (cmd === \"loaded\") {\n              worker.loaded = true;\n              if (onFinishedLoading)\n                onFinishedLoading(worker);\n              if (worker.runPthread) {\n                worker.runPthread();\n                delete worker.runPthread;\n              }\n            } else if (cmd === \"print\") {\n              out(\"Thread \" + d[\"threadId\"] + \": \" + d[\"text\"]);\n            } else if (cmd === \"printErr\") {\n              err(\"Thread \" + d[\"threadId\"] + \": \" + d[\"text\"]);\n            } else if (cmd === \"alert\") {\n              alert(\"Thread \" + d[\"threadId\"] + \": \" + d[\"text\"]);\n            } else if (d.target === \"setimmediate\") {\n              worker.postMessage(d);\n            } else if (cmd === \"onAbort\") {\n              if (Module[\"onAbort\"]) {\n                Module[\"onAbort\"](d[\"arg\"]);\n              }\n            } else {\n              err(\"worker sent an unknown command \" + cmd);\n            }\n            PThread.currentProxiedOperationCallerThread = void 0;\n          };\n          worker.onerror = (e2) => {\n            var message = \"worker sent an error!\";\n            err(message + \" \" + e2.filename + \":\" + e2.lineno + \": \" + e2.message);\n            throw e2;\n          };\n          if (ENVIRONMENT_IS_NODE) {\n            worker.on(\"message\", function(data) {\n              worker.onmessage({ data });\n            });\n            worker.on(\"error\", function(e2) {\n              worker.onerror(e2);\n            });\n            worker.on(\"detachedExit\", function() {\n            });\n          }\n          worker.postMessage({ \"cmd\": \"load\", \"urlOrBlob\": Module[\"mainScriptUrlOrBlob\"] || _scriptDir, \"wasmMemory\": wasmMemory, \"wasmModule\": wasmModule });\n        }, allocateUnusedWorker: function() {\n          var pthreadMainJs = locateFile(\"tfjs-backend-wasm-threaded-simd.worker.js\");\n          PThread.unusedWorkers.push(new Worker(pthreadMainJs));\n        }, getNewWorker: function() {\n          if (PThread.unusedWorkers.length == 0) {\n            PThread.allocateUnusedWorker();\n            PThread.loadWasmModuleToWorker(PThread.unusedWorkers[0]);\n          }\n          return PThread.unusedWorkers.pop();\n        } };\n        function establishStackSpace() {\n          var pthread_ptr = _pthread_self();\n          var stackTop = GROWABLE_HEAP_I32()[pthread_ptr + 44 >> 2];\n          var stackSize = GROWABLE_HEAP_I32()[pthread_ptr + 48 >> 2];\n          var stackMax = stackTop - stackSize;\n          _emscripten_stack_set_limits(stackTop, stackMax);\n          stackRestore(stackTop);\n        }\n        Module[\"establishStackSpace\"] = establishStackSpace;\n        function exitOnMainThread(returnCode) {\n          if (ENVIRONMENT_IS_PTHREAD)\n            return _emscripten_proxy_to_main_thread_js(1, 0, returnCode);\n          try {\n            _exit(returnCode);\n          } catch (e2) {\n            handleException(e2);\n          }\n        }\n        var wasmTableMirror = [];\n        function getWasmTableEntry(funcPtr) {\n          var func2 = wasmTableMirror[funcPtr];\n          if (!func2) {\n            if (funcPtr >= wasmTableMirror.length)\n              wasmTableMirror.length = funcPtr + 1;\n            wasmTableMirror[funcPtr] = func2 = wasmTable.get(funcPtr);\n          }\n          return func2;\n        }\n        function invokeEntryPoint(ptr, arg) {\n          return getWasmTableEntry(ptr)(arg);\n        }\n        Module[\"invokeEntryPoint\"] = invokeEntryPoint;\n        function jsStackTrace() {\n          var error = new Error();\n          if (!error.stack) {\n            try {\n              throw new Error();\n            } catch (e2) {\n              error = e2;\n            }\n            if (!error.stack) {\n              return \"(no stack trace available)\";\n            }\n          }\n          return error.stack.toString();\n        }\n        function registerTlsInit(tlsInitFunc, moduleExports, metadata) {\n          PThread.tlsInitFunctions.push(tlsInitFunc);\n        }\n        function setWasmTableEntry(idx, func2) {\n          wasmTable.set(idx, func2);\n          wasmTableMirror[idx] = func2;\n        }\n        var _emscripten_get_now;\n        if (ENVIRONMENT_IS_NODE) {\n          _emscripten_get_now = () => {\n            var t2 = process[\"hrtime\"]();\n            return t2[0] * 1e3 + t2[1] / 1e6;\n          };\n        } else if (ENVIRONMENT_IS_PTHREAD) {\n          _emscripten_get_now = () => performance.now() - Module[\"__performance_now_clock_drift\"];\n        } else\n          _emscripten_get_now = () => performance.now();\n        var _emscripten_get_now_is_monotonic = true;\n        function setErrNo(value) {\n          GROWABLE_HEAP_I32()[___errno_location() >> 2] = value;\n          return value;\n        }\n        function _clock_gettime(clk_id, tp) {\n          var now2;\n          if (clk_id === 0) {\n            now2 = Date.now();\n          } else if ((clk_id === 1 || clk_id === 4) && _emscripten_get_now_is_monotonic) {\n            now2 = _emscripten_get_now();\n          } else {\n            setErrNo(28);\n            return -1;\n          }\n          GROWABLE_HEAP_I32()[tp >> 2] = now2 / 1e3 | 0;\n          GROWABLE_HEAP_I32()[tp + 4 >> 2] = now2 % 1e3 * 1e3 * 1e3 | 0;\n          return 0;\n        }\n        function ___clock_gettime(a0, a12) {\n          return _clock_gettime(a0, a12);\n        }\n        function ___emscripten_init_main_thread_js(tb) {\n          __emscripten_thread_init(tb, !ENVIRONMENT_IS_WORKER, 1, !ENVIRONMENT_IS_WEB);\n          PThread.threadInit();\n        }\n        function ___emscripten_thread_cleanup(thread) {\n          if (!ENVIRONMENT_IS_PTHREAD)\n            cleanupThread(thread);\n          else\n            postMessage({ \"cmd\": \"cleanupThread\", \"thread\": thread });\n        }\n        function spawnThread(threadParams) {\n          var worker = PThread.getNewWorker();\n          if (!worker) {\n            return 6;\n          }\n          PThread.runningWorkers.push(worker);\n          var pthread = PThread.pthreads[threadParams.pthread_ptr] = { worker, threadInfoStruct: threadParams.pthread_ptr };\n          worker.pthread = pthread;\n          var msg = { \"cmd\": \"run\", \"start_routine\": threadParams.startRoutine, \"arg\": threadParams.arg, \"threadInfoStruct\": threadParams.pthread_ptr };\n          worker.runPthread = () => {\n            msg.time = performance.now();\n            worker.postMessage(msg, threadParams.transferList);\n          };\n          if (worker.loaded) {\n            worker.runPthread();\n            delete worker.runPthread;\n          }\n          return 0;\n        }\n        function ___pthread_create_js(pthread_ptr, attr, start_routine, arg) {\n          if (typeof SharedArrayBuffer === \"undefined\") {\n            err(\"Current environment does not support SharedArrayBuffer, pthreads are not available!\");\n            return 6;\n          }\n          var transferList = [];\n          var error = 0;\n          if (ENVIRONMENT_IS_PTHREAD && (transferList.length === 0 || error)) {\n            return _emscripten_sync_run_in_main_thread_4(687865856, pthread_ptr, attr, start_routine, arg);\n          }\n          if (error)\n            return error;\n          var threadParams = { startRoutine: start_routine, pthread_ptr, arg, transferList };\n          if (ENVIRONMENT_IS_PTHREAD) {\n            threadParams.cmd = \"spawnThread\";\n            postMessage(threadParams, transferList);\n            return 0;\n          }\n          return spawnThread(threadParams);\n        }\n        function __emscripten_default_pthread_stack_size() {\n          return 2097152;\n        }\n        function __emscripten_notify_thread_queue(targetThreadId, mainThreadId) {\n          if (targetThreadId == mainThreadId) {\n            postMessage({ \"cmd\": \"processQueuedMainThreadWork\" });\n          } else if (ENVIRONMENT_IS_PTHREAD) {\n            postMessage({ \"targetThread\": targetThreadId, \"cmd\": \"processThreadQueue\" });\n          } else {\n            var pthread = PThread.pthreads[targetThreadId];\n            var worker = pthread && pthread.worker;\n            if (!worker) {\n              return;\n            }\n            worker.postMessage({ \"cmd\": \"processThreadQueue\" });\n          }\n          return 1;\n        }\n        function _abort() {\n          abort(\"\");\n        }\n        function _emscripten_check_blocking_allowed() {\n          if (ENVIRONMENT_IS_NODE)\n            return;\n          if (ENVIRONMENT_IS_WORKER)\n            return;\n          warnOnce(\"Blocking on the main thread is very dangerous, see https://emscripten.org/docs/porting/pthreads.html#blocking-on-the-main-browser-thread\");\n        }\n        function _emscripten_get_heap_max() {\n          return 2147483648;\n        }\n        function _emscripten_memcpy_big(dest, src, num) {\n          GROWABLE_HEAP_U8().copyWithin(dest, src, src + num);\n        }\n        function _emscripten_num_logical_cores() {\n          if (ENVIRONMENT_IS_NODE)\n            return require_os().cpus().length;\n          return navigator[\"hardwareConcurrency\"];\n        }\n        function _emscripten_proxy_to_main_thread_js(index, sync) {\n          var numCallArgs = arguments.length - 2;\n          var outerArgs = arguments;\n          return withStackSave(function() {\n            var serializedNumCallArgs = numCallArgs;\n            var args = stackAlloc(serializedNumCallArgs * 8);\n            var b = args >> 3;\n            for (var i2 = 0; i2 < numCallArgs; i2++) {\n              var arg = outerArgs[2 + i2];\n              GROWABLE_HEAP_F64()[b + i2] = arg;\n            }\n            return _emscripten_run_in_main_runtime_thread_js(index, serializedNumCallArgs, args, sync);\n          });\n        }\n        var _emscripten_receive_on_main_thread_js_callArgs = [];\n        function _emscripten_receive_on_main_thread_js(index, numCallArgs, args) {\n          _emscripten_receive_on_main_thread_js_callArgs.length = numCallArgs;\n          var b = args >> 3;\n          for (var i2 = 0; i2 < numCallArgs; i2++) {\n            _emscripten_receive_on_main_thread_js_callArgs[i2] = GROWABLE_HEAP_F64()[b + i2];\n          }\n          var isEmAsmConst = index < 0;\n          var func2 = !isEmAsmConst ? proxiedFunctionTable[index] : ASM_CONSTS[-index - 1];\n          return func2.apply(null, _emscripten_receive_on_main_thread_js_callArgs);\n        }\n        function emscripten_realloc_buffer(size) {\n          try {\n            wasmMemory.grow(size - buffer2.byteLength + 65535 >>> 16);\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n            return 1;\n          } catch (e2) {\n          }\n        }\n        function _emscripten_resize_heap(requestedSize) {\n          var oldSize = GROWABLE_HEAP_U8().length;\n          requestedSize = requestedSize >>> 0;\n          if (requestedSize <= oldSize) {\n            return false;\n          }\n          var maxHeapSize = _emscripten_get_heap_max();\n          if (requestedSize > maxHeapSize) {\n            return false;\n          }\n          for (var cutDown = 1; cutDown <= 4; cutDown *= 2) {\n            var overGrownHeapSize = oldSize * (1 + 0.2 / cutDown);\n            overGrownHeapSize = Math.min(overGrownHeapSize, requestedSize + 100663296);\n            var newSize = Math.min(maxHeapSize, alignUp(Math.max(requestedSize, overGrownHeapSize), 65536));\n            var replacement = emscripten_realloc_buffer(newSize);\n            if (replacement) {\n              return true;\n            }\n          }\n          return false;\n        }\n        var JSEvents = { inEventHandler: 0, removeAllEventListeners: function() {\n          for (var i2 = JSEvents.eventHandlers.length - 1; i2 >= 0; --i2) {\n            JSEvents._removeHandler(i2);\n          }\n          JSEvents.eventHandlers = [];\n          JSEvents.deferredCalls = [];\n        }, registerRemoveEventListeners: function() {\n          if (!JSEvents.removeEventListenersRegistered) {\n            __ATEXIT__.push(JSEvents.removeAllEventListeners);\n            JSEvents.removeEventListenersRegistered = true;\n          }\n        }, deferredCalls: [], deferCall: function(targetFunction, precedence, argsList) {\n          function arraysHaveEqualContent(arrA, arrB) {\n            if (arrA.length != arrB.length)\n              return false;\n            for (var i3 in arrA) {\n              if (arrA[i3] != arrB[i3])\n                return false;\n            }\n            return true;\n          }\n          for (var i2 in JSEvents.deferredCalls) {\n            var call = JSEvents.deferredCalls[i2];\n            if (call.targetFunction == targetFunction && arraysHaveEqualContent(call.argsList, argsList)) {\n              return;\n            }\n          }\n          JSEvents.deferredCalls.push({ targetFunction, precedence, argsList });\n          JSEvents.deferredCalls.sort(function(x, y) {\n            return x.precedence < y.precedence;\n          });\n        }, removeDeferredCalls: function(targetFunction) {\n          for (var i2 = 0; i2 < JSEvents.deferredCalls.length; ++i2) {\n            if (JSEvents.deferredCalls[i2].targetFunction == targetFunction) {\n              JSEvents.deferredCalls.splice(i2, 1);\n              --i2;\n            }\n          }\n        }, canPerformEventHandlerRequests: function() {\n          return JSEvents.inEventHandler && JSEvents.currentEventHandler.allowsDeferredCalls;\n        }, runDeferredCalls: function() {\n          if (!JSEvents.canPerformEventHandlerRequests()) {\n            return;\n          }\n          for (var i2 = 0; i2 < JSEvents.deferredCalls.length; ++i2) {\n            var call = JSEvents.deferredCalls[i2];\n            JSEvents.deferredCalls.splice(i2, 1);\n            --i2;\n            call.targetFunction.apply(null, call.argsList);\n          }\n        }, eventHandlers: [], removeAllHandlersOnTarget: function(target, eventTypeString) {\n          for (var i2 = 0; i2 < JSEvents.eventHandlers.length; ++i2) {\n            if (JSEvents.eventHandlers[i2].target == target && (!eventTypeString || eventTypeString == JSEvents.eventHandlers[i2].eventTypeString)) {\n              JSEvents._removeHandler(i2--);\n            }\n          }\n        }, _removeHandler: function(i2) {\n          var h = JSEvents.eventHandlers[i2];\n          h.target.removeEventListener(h.eventTypeString, h.eventListenerFunc, h.useCapture);\n          JSEvents.eventHandlers.splice(i2, 1);\n        }, registerOrRemoveHandler: function(eventHandler) {\n          var jsEventHandler = function jsEventHandler2(event) {\n            ++JSEvents.inEventHandler;\n            JSEvents.currentEventHandler = eventHandler;\n            JSEvents.runDeferredCalls();\n            eventHandler.handlerFunc(event);\n            JSEvents.runDeferredCalls();\n            --JSEvents.inEventHandler;\n          };\n          if (eventHandler.callbackfunc) {\n            eventHandler.eventListenerFunc = jsEventHandler;\n            eventHandler.target.addEventListener(eventHandler.eventTypeString, jsEventHandler, eventHandler.useCapture);\n            JSEvents.eventHandlers.push(eventHandler);\n            JSEvents.registerRemoveEventListeners();\n          } else {\n            for (var i2 = 0; i2 < JSEvents.eventHandlers.length; ++i2) {\n              if (JSEvents.eventHandlers[i2].target == eventHandler.target && JSEvents.eventHandlers[i2].eventTypeString == eventHandler.eventTypeString) {\n                JSEvents._removeHandler(i2--);\n              }\n            }\n          }\n        }, queueEventHandlerOnThread_iiii: function(targetThread, eventHandlerFunc, eventTypeId, eventData, userData) {\n          withStackSave(function() {\n            var varargs = stackAlloc(12);\n            GROWABLE_HEAP_I32()[varargs >> 2] = eventTypeId;\n            GROWABLE_HEAP_I32()[varargs + 4 >> 2] = eventData;\n            GROWABLE_HEAP_I32()[varargs + 8 >> 2] = userData;\n            _emscripten_dispatch_to_thread_(targetThread, 637534208, eventHandlerFunc, eventData, varargs);\n          });\n        }, getTargetThreadForEventCallback: function(targetThread) {\n          switch (targetThread) {\n            case 1:\n              return 0;\n            case 2:\n              return PThread.currentProxiedOperationCallerThread;\n            default:\n              return targetThread;\n          }\n        }, getNodeNameForTarget: function(target) {\n          if (!target)\n            return \"\";\n          if (target == window)\n            return \"#window\";\n          if (target == screen)\n            return \"#screen\";\n          return target && target.nodeName ? target.nodeName : \"\";\n        }, fullscreenEnabled: function() {\n          return document.fullscreenEnabled || document.webkitFullscreenEnabled;\n        } };\n        function stringToNewUTF8(jsString) {\n          var length = lengthBytesUTF8(jsString) + 1;\n          var cString = _malloc(length);\n          stringToUTF8(jsString, cString, length);\n          return cString;\n        }\n        function _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread, targetCanvas, width, height) {\n          withStackSave(function() {\n            var varargs = stackAlloc(12);\n            var targetCanvasPtr = 0;\n            if (targetCanvas) {\n              targetCanvasPtr = stringToNewUTF8(targetCanvas);\n            }\n            GROWABLE_HEAP_I32()[varargs >> 2] = targetCanvasPtr;\n            GROWABLE_HEAP_I32()[varargs + 4 >> 2] = width;\n            GROWABLE_HEAP_I32()[varargs + 8 >> 2] = height;\n            _emscripten_dispatch_to_thread_(targetThread, 657457152, 0, targetCanvasPtr, varargs);\n          });\n        }\n        function _emscripten_set_offscreencanvas_size_on_target_thread(targetThread, targetCanvas, width, height) {\n          targetCanvas = targetCanvas ? UTF8ToString(targetCanvas) : \"\";\n          _emscripten_set_offscreencanvas_size_on_target_thread_js(targetThread, targetCanvas, width, height);\n        }\n        function maybeCStringToJsString(cString) {\n          return cString > 2 ? UTF8ToString(cString) : cString;\n        }\n        var specialHTMLTargets = [0, typeof document !== \"undefined\" ? document : 0, typeof window !== \"undefined\" ? window : 0];\n        function findEventTarget(target) {\n          target = maybeCStringToJsString(target);\n          var domElement = specialHTMLTargets[target] || (typeof document !== \"undefined\" ? document.querySelector(target) : void 0);\n          return domElement;\n        }\n        function findCanvasEventTarget(target) {\n          return findEventTarget(target);\n        }\n        function _emscripten_set_canvas_element_size_calling_thread(target, width, height) {\n          var canvas = findCanvasEventTarget(target);\n          if (!canvas)\n            return -4;\n          if (canvas.canvasSharedPtr) {\n            GROWABLE_HEAP_I32()[canvas.canvasSharedPtr >> 2] = width;\n            GROWABLE_HEAP_I32()[canvas.canvasSharedPtr + 4 >> 2] = height;\n          }\n          if (canvas.offscreenCanvas || !canvas.controlTransferredOffscreen) {\n            if (canvas.offscreenCanvas)\n              canvas = canvas.offscreenCanvas;\n            var autoResizeViewport = false;\n            if (canvas.GLctxObject && canvas.GLctxObject.GLctx) {\n              var prevViewport = canvas.GLctxObject.GLctx.getParameter(2978);\n              autoResizeViewport = prevViewport[0] === 0 && prevViewport[1] === 0 && prevViewport[2] === canvas.width && prevViewport[3] === canvas.height;\n            }\n            canvas.width = width;\n            canvas.height = height;\n            if (autoResizeViewport) {\n              canvas.GLctxObject.GLctx.viewport(0, 0, width, height);\n            }\n          } else if (canvas.canvasSharedPtr) {\n            var targetThread = GROWABLE_HEAP_I32()[canvas.canvasSharedPtr + 8 >> 2];\n            _emscripten_set_offscreencanvas_size_on_target_thread(targetThread, target, width, height);\n            return 1;\n          } else {\n            return -4;\n          }\n          return 0;\n        }\n        function _emscripten_set_canvas_element_size_main_thread(target, width, height) {\n          if (ENVIRONMENT_IS_PTHREAD)\n            return _emscripten_proxy_to_main_thread_js(2, 1, target, width, height);\n          return _emscripten_set_canvas_element_size_calling_thread(target, width, height);\n        }\n        function _emscripten_set_canvas_element_size(target, width, height) {\n          var canvas = findCanvasEventTarget(target);\n          if (canvas) {\n            return _emscripten_set_canvas_element_size_calling_thread(target, width, height);\n          } else {\n            return _emscripten_set_canvas_element_size_main_thread(target, width, height);\n          }\n        }\n        function _emscripten_unwind_to_js_event_loop() {\n          throw \"unwind\";\n        }\n        function __webgl_enable_ANGLE_instanced_arrays(ctx) {\n          var ext = ctx.getExtension(\"ANGLE_instanced_arrays\");\n          if (ext) {\n            ctx[\"vertexAttribDivisor\"] = function(index, divisor) {\n              ext[\"vertexAttribDivisorANGLE\"](index, divisor);\n            };\n            ctx[\"drawArraysInstanced\"] = function(mode, first, count2, primcount) {\n              ext[\"drawArraysInstancedANGLE\"](mode, first, count2, primcount);\n            };\n            ctx[\"drawElementsInstanced\"] = function(mode, count2, type, indices, primcount) {\n              ext[\"drawElementsInstancedANGLE\"](mode, count2, type, indices, primcount);\n            };\n            return 1;\n          }\n        }\n        function __webgl_enable_OES_vertex_array_object(ctx) {\n          var ext = ctx.getExtension(\"OES_vertex_array_object\");\n          if (ext) {\n            ctx[\"createVertexArray\"] = function() {\n              return ext[\"createVertexArrayOES\"]();\n            };\n            ctx[\"deleteVertexArray\"] = function(vao) {\n              ext[\"deleteVertexArrayOES\"](vao);\n            };\n            ctx[\"bindVertexArray\"] = function(vao) {\n              ext[\"bindVertexArrayOES\"](vao);\n            };\n            ctx[\"isVertexArray\"] = function(vao) {\n              return ext[\"isVertexArrayOES\"](vao);\n            };\n            return 1;\n          }\n        }\n        function __webgl_enable_WEBGL_draw_buffers(ctx) {\n          var ext = ctx.getExtension(\"WEBGL_draw_buffers\");\n          if (ext) {\n            ctx[\"drawBuffers\"] = function(n2, bufs) {\n              ext[\"drawBuffersWEBGL\"](n2, bufs);\n            };\n            return 1;\n          }\n        }\n        function __webgl_enable_WEBGL_multi_draw(ctx) {\n          return !!(ctx.multiDrawWebgl = ctx.getExtension(\"WEBGL_multi_draw\"));\n        }\n        var GL = { counter: 1, buffers: [], programs: [], framebuffers: [], renderbuffers: [], textures: [], shaders: [], vaos: [], contexts: {}, offscreenCanvases: {}, queries: [], stringCache: {}, unpackAlignment: 4, recordError: function recordError(errorCode) {\n          if (!GL.lastError) {\n            GL.lastError = errorCode;\n          }\n        }, getNewId: function(table) {\n          var ret = GL.counter++;\n          for (var i2 = table.length; i2 < ret; i2++) {\n            table[i2] = null;\n          }\n          return ret;\n        }, getSource: function(shader, count2, string2, length) {\n          var source = \"\";\n          for (var i2 = 0; i2 < count2; ++i2) {\n            var len = length ? GROWABLE_HEAP_I32()[length + i2 * 4 >> 2] : -1;\n            source += UTF8ToString(GROWABLE_HEAP_I32()[string2 + i2 * 4 >> 2], len < 0 ? void 0 : len);\n          }\n          return source;\n        }, createContext: function(canvas, webGLContextAttributes) {\n          if (!canvas.getContextSafariWebGL2Fixed) {\n            canvas.getContextSafariWebGL2Fixed = canvas.getContext;\n            canvas.getContext = function(ver, attrs) {\n              var gl = canvas.getContextSafariWebGL2Fixed(ver, attrs);\n              return ver == \"webgl\" == gl instanceof WebGLRenderingContext ? gl : null;\n            };\n          }\n          var ctx = canvas.getContext(\"webgl\", webGLContextAttributes);\n          if (!ctx)\n            return 0;\n          var handle = GL.registerContext(ctx, webGLContextAttributes);\n          return handle;\n        }, registerContext: function(ctx, webGLContextAttributes) {\n          var handle = _malloc(8);\n          GROWABLE_HEAP_I32()[handle + 4 >> 2] = _pthread_self();\n          var context = { handle, attributes: webGLContextAttributes, version: webGLContextAttributes.majorVersion, GLctx: ctx };\n          if (ctx.canvas)\n            ctx.canvas.GLctxObject = context;\n          GL.contexts[handle] = context;\n          if (typeof webGLContextAttributes.enableExtensionsByDefault === \"undefined\" || webGLContextAttributes.enableExtensionsByDefault) {\n            GL.initExtensions(context);\n          }\n          return handle;\n        }, makeContextCurrent: function(contextHandle) {\n          GL.currentContext = GL.contexts[contextHandle];\n          Module.ctx = GLctx = GL.currentContext && GL.currentContext.GLctx;\n          return !(contextHandle && !GLctx);\n        }, getContext: function(contextHandle) {\n          return GL.contexts[contextHandle];\n        }, deleteContext: function(contextHandle) {\n          if (GL.currentContext === GL.contexts[contextHandle])\n            GL.currentContext = null;\n          if (typeof JSEvents === \"object\")\n            JSEvents.removeAllHandlersOnTarget(GL.contexts[contextHandle].GLctx.canvas);\n          if (GL.contexts[contextHandle] && GL.contexts[contextHandle].GLctx.canvas)\n            GL.contexts[contextHandle].GLctx.canvas.GLctxObject = void 0;\n          _free(GL.contexts[contextHandle].handle);\n          GL.contexts[contextHandle] = null;\n        }, initExtensions: function(context) {\n          if (!context)\n            context = GL.currentContext;\n          if (context.initExtensionsDone)\n            return;\n          context.initExtensionsDone = true;\n          var GLctx2 = context.GLctx;\n          __webgl_enable_ANGLE_instanced_arrays(GLctx2);\n          __webgl_enable_OES_vertex_array_object(GLctx2);\n          __webgl_enable_WEBGL_draw_buffers(GLctx2);\n          {\n            GLctx2.disjointTimerQueryExt = GLctx2.getExtension(\"EXT_disjoint_timer_query\");\n          }\n          __webgl_enable_WEBGL_multi_draw(GLctx2);\n          var exts = GLctx2.getSupportedExtensions() || [];\n          exts.forEach(function(ext) {\n            if (!ext.includes(\"lose_context\") && !ext.includes(\"debug\")) {\n              GLctx2.getExtension(ext);\n            }\n          });\n        } };\n        var __emscripten_webgl_power_preferences = [\"default\", \"low-power\", \"high-performance\"];\n        function _emscripten_webgl_do_create_context(target, attributes) {\n          var a = attributes >> 2;\n          var powerPreference = GROWABLE_HEAP_I32()[a + (24 >> 2)];\n          var contextAttributes = { \"alpha\": !!GROWABLE_HEAP_I32()[a + (0 >> 2)], \"depth\": !!GROWABLE_HEAP_I32()[a + (4 >> 2)], \"stencil\": !!GROWABLE_HEAP_I32()[a + (8 >> 2)], \"antialias\": !!GROWABLE_HEAP_I32()[a + (12 >> 2)], \"premultipliedAlpha\": !!GROWABLE_HEAP_I32()[a + (16 >> 2)], \"preserveDrawingBuffer\": !!GROWABLE_HEAP_I32()[a + (20 >> 2)], \"powerPreference\": __emscripten_webgl_power_preferences[powerPreference], \"failIfMajorPerformanceCaveat\": !!GROWABLE_HEAP_I32()[a + (28 >> 2)], majorVersion: GROWABLE_HEAP_I32()[a + (32 >> 2)], minorVersion: GROWABLE_HEAP_I32()[a + (36 >> 2)], enableExtensionsByDefault: GROWABLE_HEAP_I32()[a + (40 >> 2)], explicitSwapControl: GROWABLE_HEAP_I32()[a + (44 >> 2)], proxyContextToMainThread: GROWABLE_HEAP_I32()[a + (48 >> 2)], renderViaOffscreenBackBuffer: GROWABLE_HEAP_I32()[a + (52 >> 2)] };\n          var canvas = findCanvasEventTarget(target);\n          if (!canvas) {\n            return 0;\n          }\n          if (contextAttributes.explicitSwapControl) {\n            return 0;\n          }\n          var contextHandle = GL.createContext(canvas, contextAttributes);\n          return contextHandle;\n        }\n        function _emscripten_webgl_create_context(a0, a12) {\n          return _emscripten_webgl_do_create_context(a0, a12);\n        }\n        var SYSCALLS = { mappings: {}, buffers: [null, [], []], printChar: function(stream, curr) {\n          var buffer3 = SYSCALLS.buffers[stream];\n          if (curr === 0 || curr === 10) {\n            (stream === 1 ? out : err)(UTF8ArrayToString(buffer3, 0));\n            buffer3.length = 0;\n          } else {\n            buffer3.push(curr);\n          }\n        }, varargs: void 0, get: function() {\n          SYSCALLS.varargs += 4;\n          var ret = GROWABLE_HEAP_I32()[SYSCALLS.varargs - 4 >> 2];\n          return ret;\n        }, getStr: function(ptr) {\n          var ret = UTF8ToString(ptr);\n          return ret;\n        }, get64: function(low, high) {\n          return low;\n        } };\n        function _fd_close(fd) {\n          if (ENVIRONMENT_IS_PTHREAD)\n            return _emscripten_proxy_to_main_thread_js(3, 1, fd);\n          return 0;\n        }\n        function _fd_seek(fd, offset_low, offset_high, whence, newOffset) {\n          if (ENVIRONMENT_IS_PTHREAD)\n            return _emscripten_proxy_to_main_thread_js(4, 1, fd, offset_low, offset_high, whence, newOffset);\n        }\n        function _fd_write(fd, iov, iovcnt, pnum) {\n          if (ENVIRONMENT_IS_PTHREAD)\n            return _emscripten_proxy_to_main_thread_js(5, 1, fd, iov, iovcnt, pnum);\n          var num = 0;\n          for (var i2 = 0; i2 < iovcnt; i2++) {\n            var ptr = GROWABLE_HEAP_I32()[iov >> 2];\n            var len = GROWABLE_HEAP_I32()[iov + 4 >> 2];\n            iov += 8;\n            for (var j = 0; j < len; j++) {\n              SYSCALLS.printChar(fd, GROWABLE_HEAP_U8()[ptr + j]);\n            }\n            num += len;\n          }\n          GROWABLE_HEAP_I32()[pnum >> 2] = num;\n          return 0;\n        }\n        function _setTempRet0(val) {\n          setTempRet0(val);\n        }\n        PThread.init();\n        var GLctx;\n        var proxiedFunctionTable = [null, exitOnMainThread, _emscripten_set_canvas_element_size_main_thread, _fd_close, _fd_seek, _fd_write];\n        var ASSERTIONS = false;\n        var asmLibraryArg = { \"__clock_gettime\": ___clock_gettime, \"__emscripten_init_main_thread_js\": ___emscripten_init_main_thread_js, \"__emscripten_thread_cleanup\": ___emscripten_thread_cleanup, \"__pthread_create_js\": ___pthread_create_js, \"_emscripten_default_pthread_stack_size\": __emscripten_default_pthread_stack_size, \"_emscripten_notify_thread_queue\": __emscripten_notify_thread_queue, \"abort\": _abort, \"emscripten_check_blocking_allowed\": _emscripten_check_blocking_allowed, \"emscripten_get_heap_max\": _emscripten_get_heap_max, \"emscripten_get_now\": _emscripten_get_now, \"emscripten_memcpy_big\": _emscripten_memcpy_big, \"emscripten_num_logical_cores\": _emscripten_num_logical_cores, \"emscripten_receive_on_main_thread_js\": _emscripten_receive_on_main_thread_js, \"emscripten_resize_heap\": _emscripten_resize_heap, \"emscripten_set_canvas_element_size\": _emscripten_set_canvas_element_size, \"emscripten_unwind_to_js_event_loop\": _emscripten_unwind_to_js_event_loop, \"emscripten_webgl_create_context\": _emscripten_webgl_create_context, \"exit\": _exit, \"fd_close\": _fd_close, \"fd_seek\": _fd_seek, \"fd_write\": _fd_write, \"memory\": wasmMemory || Module[\"wasmMemory\"], \"setTempRet0\": _setTempRet0 };\n        var asm = createWasm();\n        var ___wasm_call_ctors = Module[\"___wasm_call_ctors\"] = function() {\n          return (___wasm_call_ctors = Module[\"___wasm_call_ctors\"] = Module[\"asm\"][\"__wasm_call_ctors\"]).apply(null, arguments);\n        };\n        var _init = Module[\"_init\"] = function() {\n          return (_init = Module[\"_init\"] = Module[\"asm\"][\"init\"]).apply(null, arguments);\n        };\n        var _init_with_threads_count = Module[\"_init_with_threads_count\"] = function() {\n          return (_init_with_threads_count = Module[\"_init_with_threads_count\"] = Module[\"asm\"][\"init_with_threads_count\"]).apply(null, arguments);\n        };\n        var _get_threads_count = Module[\"_get_threads_count\"] = function() {\n          return (_get_threads_count = Module[\"_get_threads_count\"] = Module[\"asm\"][\"get_threads_count\"]).apply(null, arguments);\n        };\n        var _register_tensor = Module[\"_register_tensor\"] = function() {\n          return (_register_tensor = Module[\"_register_tensor\"] = Module[\"asm\"][\"register_tensor\"]).apply(null, arguments);\n        };\n        var _dispose_data = Module[\"_dispose_data\"] = function() {\n          return (_dispose_data = Module[\"_dispose_data\"] = Module[\"asm\"][\"dispose_data\"]).apply(null, arguments);\n        };\n        var _dispose = Module[\"_dispose\"] = function() {\n          return (_dispose = Module[\"_dispose\"] = Module[\"asm\"][\"dispose\"]).apply(null, arguments);\n        };\n        var _Abs = Module[\"_Abs\"] = function() {\n          return (_Abs = Module[\"_Abs\"] = Module[\"asm\"][\"Abs\"]).apply(null, arguments);\n        };\n        var _Add = Module[\"_Add\"] = function() {\n          return (_Add = Module[\"_Add\"] = Module[\"asm\"][\"Add\"]).apply(null, arguments);\n        };\n        var _AddN = Module[\"_AddN\"] = function() {\n          return (_AddN = Module[\"_AddN\"] = Module[\"asm\"][\"AddN\"]).apply(null, arguments);\n        };\n        var _All = Module[\"_All\"] = function() {\n          return (_All = Module[\"_All\"] = Module[\"asm\"][\"All\"]).apply(null, arguments);\n        };\n        var _Any = Module[\"_Any\"] = function() {\n          return (_Any = Module[\"_Any\"] = Module[\"asm\"][\"Any\"]).apply(null, arguments);\n        };\n        var _ArgMax = Module[\"_ArgMax\"] = function() {\n          return (_ArgMax = Module[\"_ArgMax\"] = Module[\"asm\"][\"ArgMax\"]).apply(null, arguments);\n        };\n        var _AvgPool = Module[\"_AvgPool\"] = function() {\n          return (_AvgPool = Module[\"_AvgPool\"] = Module[\"asm\"][\"AvgPool\"]).apply(null, arguments);\n        };\n        var _BatchMatMul = Module[\"_BatchMatMul\"] = function() {\n          return (_BatchMatMul = Module[\"_BatchMatMul\"] = Module[\"asm\"][\"BatchMatMul\"]).apply(null, arguments);\n        };\n        var _Ceil = Module[\"_Ceil\"] = function() {\n          return (_Ceil = Module[\"_Ceil\"] = Module[\"asm\"][\"Ceil\"]).apply(null, arguments);\n        };\n        var _ClipByValue = Module[\"_ClipByValue\"] = function() {\n          return (_ClipByValue = Module[\"_ClipByValue\"] = Module[\"asm\"][\"ClipByValue\"]).apply(null, arguments);\n        };\n        var _Conv2D = Module[\"_Conv2D\"] = function() {\n          return (_Conv2D = Module[\"_Conv2D\"] = Module[\"asm\"][\"Conv2D\"]).apply(null, arguments);\n        };\n        var _Conv2DBackpropInput = Module[\"_Conv2DBackpropInput\"] = function() {\n          return (_Conv2DBackpropInput = Module[\"_Conv2DBackpropInput\"] = Module[\"asm\"][\"Conv2DBackpropInput\"]).apply(null, arguments);\n        };\n        var _Cos = Module[\"_Cos\"] = function() {\n          return (_Cos = Module[\"_Cos\"] = Module[\"asm\"][\"Cos\"]).apply(null, arguments);\n        };\n        var _Cosh = Module[\"_Cosh\"] = function() {\n          return (_Cosh = Module[\"_Cosh\"] = Module[\"asm\"][\"Cosh\"]).apply(null, arguments);\n        };\n        var _CropAndResize = Module[\"_CropAndResize\"] = function() {\n          return (_CropAndResize = Module[\"_CropAndResize\"] = Module[\"asm\"][\"CropAndResize\"]).apply(null, arguments);\n        };\n        var _Cumprod = Module[\"_Cumprod\"] = function() {\n          return (_Cumprod = Module[\"_Cumprod\"] = Module[\"asm\"][\"Cumprod\"]).apply(null, arguments);\n        };\n        var _Cumsum = Module[\"_Cumsum\"] = function() {\n          return (_Cumsum = Module[\"_Cumsum\"] = Module[\"asm\"][\"Cumsum\"]).apply(null, arguments);\n        };\n        var _DepthToSpace = Module[\"_DepthToSpace\"] = function() {\n          return (_DepthToSpace = Module[\"_DepthToSpace\"] = Module[\"asm\"][\"DepthToSpace\"]).apply(null, arguments);\n        };\n        var _DepthwiseConv2dNative = Module[\"_DepthwiseConv2dNative\"] = function() {\n          return (_DepthwiseConv2dNative = Module[\"_DepthwiseConv2dNative\"] = Module[\"asm\"][\"DepthwiseConv2dNative\"]).apply(null, arguments);\n        };\n        var _Elu = Module[\"_Elu\"] = function() {\n          return (_Elu = Module[\"_Elu\"] = Module[\"asm\"][\"Elu\"]).apply(null, arguments);\n        };\n        var _Equal = Module[\"_Equal\"] = function() {\n          return (_Equal = Module[\"_Equal\"] = Module[\"asm\"][\"Equal\"]).apply(null, arguments);\n        };\n        var _Exp = Module[\"_Exp\"] = function() {\n          return (_Exp = Module[\"_Exp\"] = Module[\"asm\"][\"Exp\"]).apply(null, arguments);\n        };\n        var _FlipLeftRight = Module[\"_FlipLeftRight\"] = function() {\n          return (_FlipLeftRight = Module[\"_FlipLeftRight\"] = Module[\"asm\"][\"FlipLeftRight\"]).apply(null, arguments);\n        };\n        var _Floor = Module[\"_Floor\"] = function() {\n          return (_Floor = Module[\"_Floor\"] = Module[\"asm\"][\"Floor\"]).apply(null, arguments);\n        };\n        var _FloorDiv = Module[\"_FloorDiv\"] = function() {\n          return (_FloorDiv = Module[\"_FloorDiv\"] = Module[\"asm\"][\"FloorDiv\"]).apply(null, arguments);\n        };\n        var _FusedBatchNorm = Module[\"_FusedBatchNorm\"] = function() {\n          return (_FusedBatchNorm = Module[\"_FusedBatchNorm\"] = Module[\"asm\"][\"FusedBatchNorm\"]).apply(null, arguments);\n        };\n        var _FusedConv2D = Module[\"_FusedConv2D\"] = function() {\n          return (_FusedConv2D = Module[\"_FusedConv2D\"] = Module[\"asm\"][\"FusedConv2D\"]).apply(null, arguments);\n        };\n        var _FusedDepthwiseConv2D = Module[\"_FusedDepthwiseConv2D\"] = function() {\n          return (_FusedDepthwiseConv2D = Module[\"_FusedDepthwiseConv2D\"] = Module[\"asm\"][\"FusedDepthwiseConv2D\"]).apply(null, arguments);\n        };\n        var _Gather = Module[\"_Gather\"] = function() {\n          return (_Gather = Module[\"_Gather\"] = Module[\"asm\"][\"Gather\"]).apply(null, arguments);\n        };\n        var _GatherNd = Module[\"_GatherNd\"] = function() {\n          return (_GatherNd = Module[\"_GatherNd\"] = Module[\"asm\"][\"GatherNd\"]).apply(null, arguments);\n        };\n        var _Greater = Module[\"_Greater\"] = function() {\n          return (_Greater = Module[\"_Greater\"] = Module[\"asm\"][\"Greater\"]).apply(null, arguments);\n        };\n        var _GreaterEqual = Module[\"_GreaterEqual\"] = function() {\n          return (_GreaterEqual = Module[\"_GreaterEqual\"] = Module[\"asm\"][\"GreaterEqual\"]).apply(null, arguments);\n        };\n        var _LeakyRelu = Module[\"_LeakyRelu\"] = function() {\n          return (_LeakyRelu = Module[\"_LeakyRelu\"] = Module[\"asm\"][\"LeakyRelu\"]).apply(null, arguments);\n        };\n        var _Less = Module[\"_Less\"] = function() {\n          return (_Less = Module[\"_Less\"] = Module[\"asm\"][\"Less\"]).apply(null, arguments);\n        };\n        var _LessEqual = Module[\"_LessEqual\"] = function() {\n          return (_LessEqual = Module[\"_LessEqual\"] = Module[\"asm\"][\"LessEqual\"]).apply(null, arguments);\n        };\n        var _Log = Module[\"_Log\"] = function() {\n          return (_Log = Module[\"_Log\"] = Module[\"asm\"][\"Log\"]).apply(null, arguments);\n        };\n        var _LogicalAnd = Module[\"_LogicalAnd\"] = function() {\n          return (_LogicalAnd = Module[\"_LogicalAnd\"] = Module[\"asm\"][\"LogicalAnd\"]).apply(null, arguments);\n        };\n        var _LogicalNot = Module[\"_LogicalNot\"] = function() {\n          return (_LogicalNot = Module[\"_LogicalNot\"] = Module[\"asm\"][\"LogicalNot\"]).apply(null, arguments);\n        };\n        var _LogicalOr = Module[\"_LogicalOr\"] = function() {\n          return (_LogicalOr = Module[\"_LogicalOr\"] = Module[\"asm\"][\"LogicalOr\"]).apply(null, arguments);\n        };\n        var _LogicalXor = Module[\"_LogicalXor\"] = function() {\n          return (_LogicalXor = Module[\"_LogicalXor\"] = Module[\"asm\"][\"LogicalXor\"]).apply(null, arguments);\n        };\n        var _Max = Module[\"_Max\"] = function() {\n          return (_Max = Module[\"_Max\"] = Module[\"asm\"][\"Max\"]).apply(null, arguments);\n        };\n        var _MaxPool = Module[\"_MaxPool\"] = function() {\n          return (_MaxPool = Module[\"_MaxPool\"] = Module[\"asm\"][\"MaxPool\"]).apply(null, arguments);\n        };\n        var _Maximum = Module[\"_Maximum\"] = function() {\n          return (_Maximum = Module[\"_Maximum\"] = Module[\"asm\"][\"Maximum\"]).apply(null, arguments);\n        };\n        var _Mean = Module[\"_Mean\"] = function() {\n          return (_Mean = Module[\"_Mean\"] = Module[\"asm\"][\"Mean\"]).apply(null, arguments);\n        };\n        var _Min = Module[\"_Min\"] = function() {\n          return (_Min = Module[\"_Min\"] = Module[\"asm\"][\"Min\"]).apply(null, arguments);\n        };\n        var _Minimum = Module[\"_Minimum\"] = function() {\n          return (_Minimum = Module[\"_Minimum\"] = Module[\"asm\"][\"Minimum\"]).apply(null, arguments);\n        };\n        var _MirrorPad = Module[\"_MirrorPad\"] = function() {\n          return (_MirrorPad = Module[\"_MirrorPad\"] = Module[\"asm\"][\"MirrorPad\"]).apply(null, arguments);\n        };\n        var _Multiply = Module[\"_Multiply\"] = function() {\n          return (_Multiply = Module[\"_Multiply\"] = Module[\"asm\"][\"Multiply\"]).apply(null, arguments);\n        };\n        var _Neg = Module[\"_Neg\"] = function() {\n          return (_Neg = Module[\"_Neg\"] = Module[\"asm\"][\"Neg\"]).apply(null, arguments);\n        };\n        var _NonMaxSuppressionV3 = Module[\"_NonMaxSuppressionV3\"] = function() {\n          return (_NonMaxSuppressionV3 = Module[\"_NonMaxSuppressionV3\"] = Module[\"asm\"][\"NonMaxSuppressionV3\"]).apply(null, arguments);\n        };\n        var _NonMaxSuppressionV4 = Module[\"_NonMaxSuppressionV4\"] = function() {\n          return (_NonMaxSuppressionV4 = Module[\"_NonMaxSuppressionV4\"] = Module[\"asm\"][\"NonMaxSuppressionV4\"]).apply(null, arguments);\n        };\n        var _NonMaxSuppressionV5 = Module[\"_NonMaxSuppressionV5\"] = function() {\n          return (_NonMaxSuppressionV5 = Module[\"_NonMaxSuppressionV5\"] = Module[\"asm\"][\"NonMaxSuppressionV5\"]).apply(null, arguments);\n        };\n        var _NotEqual = Module[\"_NotEqual\"] = function() {\n          return (_NotEqual = Module[\"_NotEqual\"] = Module[\"asm\"][\"NotEqual\"]).apply(null, arguments);\n        };\n        var _OneHot = Module[\"_OneHot\"] = function() {\n          return (_OneHot = Module[\"_OneHot\"] = Module[\"asm\"][\"OneHot\"]).apply(null, arguments);\n        };\n        var _PadV2 = Module[\"_PadV2\"] = function() {\n          return (_PadV2 = Module[\"_PadV2\"] = Module[\"asm\"][\"PadV2\"]).apply(null, arguments);\n        };\n        var _Pow = Module[\"_Pow\"] = function() {\n          return (_Pow = Module[\"_Pow\"] = Module[\"asm\"][\"Pow\"]).apply(null, arguments);\n        };\n        var _Prelu = Module[\"_Prelu\"] = function() {\n          return (_Prelu = Module[\"_Prelu\"] = Module[\"asm\"][\"Prelu\"]).apply(null, arguments);\n        };\n        var _Prod = Module[\"_Prod\"] = function() {\n          return (_Prod = Module[\"_Prod\"] = Module[\"asm\"][\"Prod\"]).apply(null, arguments);\n        };\n        var _RealDiv = Module[\"_RealDiv\"] = function() {\n          return (_RealDiv = Module[\"_RealDiv\"] = Module[\"asm\"][\"RealDiv\"]).apply(null, arguments);\n        };\n        var _Relu = Module[\"_Relu\"] = function() {\n          return (_Relu = Module[\"_Relu\"] = Module[\"asm\"][\"Relu\"]).apply(null, arguments);\n        };\n        var _Relu6 = Module[\"_Relu6\"] = function() {\n          return (_Relu6 = Module[\"_Relu6\"] = Module[\"asm\"][\"Relu6\"]).apply(null, arguments);\n        };\n        var _ResizeBilinear = Module[\"_ResizeBilinear\"] = function() {\n          return (_ResizeBilinear = Module[\"_ResizeBilinear\"] = Module[\"asm\"][\"ResizeBilinear\"]).apply(null, arguments);\n        };\n        var _ResizeNearestNeighbor = Module[\"_ResizeNearestNeighbor\"] = function() {\n          return (_ResizeNearestNeighbor = Module[\"_ResizeNearestNeighbor\"] = Module[\"asm\"][\"ResizeNearestNeighbor\"]).apply(null, arguments);\n        };\n        var _Reverse = Module[\"_Reverse\"] = function() {\n          return (_Reverse = Module[\"_Reverse\"] = Module[\"asm\"][\"Reverse\"]).apply(null, arguments);\n        };\n        var _RotateWithOffset = Module[\"_RotateWithOffset\"] = function() {\n          return (_RotateWithOffset = Module[\"_RotateWithOffset\"] = Module[\"asm\"][\"RotateWithOffset\"]).apply(null, arguments);\n        };\n        var _Round = Module[\"_Round\"] = function() {\n          return (_Round = Module[\"_Round\"] = Module[\"asm\"][\"Round\"]).apply(null, arguments);\n        };\n        var _Rsqrt = Module[\"_Rsqrt\"] = function() {\n          return (_Rsqrt = Module[\"_Rsqrt\"] = Module[\"asm\"][\"Rsqrt\"]).apply(null, arguments);\n        };\n        var _ScatterNd = Module[\"_ScatterNd\"] = function() {\n          return (_ScatterNd = Module[\"_ScatterNd\"] = Module[\"asm\"][\"ScatterNd\"]).apply(null, arguments);\n        };\n        var _SelectV2 = Module[\"_SelectV2\"] = function() {\n          return (_SelectV2 = Module[\"_SelectV2\"] = Module[\"asm\"][\"SelectV2\"]).apply(null, arguments);\n        };\n        var _Sigmoid = Module[\"_Sigmoid\"] = function() {\n          return (_Sigmoid = Module[\"_Sigmoid\"] = Module[\"asm\"][\"Sigmoid\"]).apply(null, arguments);\n        };\n        var _Sin = Module[\"_Sin\"] = function() {\n          return (_Sin = Module[\"_Sin\"] = Module[\"asm\"][\"Sin\"]).apply(null, arguments);\n        };\n        var _Softmax = Module[\"_Softmax\"] = function() {\n          return (_Softmax = Module[\"_Softmax\"] = Module[\"asm\"][\"Softmax\"]).apply(null, arguments);\n        };\n        var _SparseFillEmptyRows = Module[\"_SparseFillEmptyRows\"] = function() {\n          return (_SparseFillEmptyRows = Module[\"_SparseFillEmptyRows\"] = Module[\"asm\"][\"SparseFillEmptyRows\"]).apply(null, arguments);\n        };\n        var _SparseReshape = Module[\"_SparseReshape\"] = function() {\n          return (_SparseReshape = Module[\"_SparseReshape\"] = Module[\"asm\"][\"SparseReshape\"]).apply(null, arguments);\n        };\n        var _SparseSegmentReduction = Module[\"_SparseSegmentReduction\"] = function() {\n          return (_SparseSegmentReduction = Module[\"_SparseSegmentReduction\"] = Module[\"asm\"][\"SparseSegmentReduction\"]).apply(null, arguments);\n        };\n        var _Sqrt = Module[\"_Sqrt\"] = function() {\n          return (_Sqrt = Module[\"_Sqrt\"] = Module[\"asm\"][\"Sqrt\"]).apply(null, arguments);\n        };\n        var _Square = Module[\"_Square\"] = function() {\n          return (_Square = Module[\"_Square\"] = Module[\"asm\"][\"Square\"]).apply(null, arguments);\n        };\n        var _SquaredDifference = Module[\"_SquaredDifference\"] = function() {\n          return (_SquaredDifference = Module[\"_SquaredDifference\"] = Module[\"asm\"][\"SquaredDifference\"]).apply(null, arguments);\n        };\n        var _Step = Module[\"_Step\"] = function() {\n          return (_Step = Module[\"_Step\"] = Module[\"asm\"][\"Step\"]).apply(null, arguments);\n        };\n        var _StridedSlice = Module[\"_StridedSlice\"] = function() {\n          return (_StridedSlice = Module[\"_StridedSlice\"] = Module[\"asm\"][\"StridedSlice\"]).apply(null, arguments);\n        };\n        var _Sub = Module[\"_Sub\"] = function() {\n          return (_Sub = Module[\"_Sub\"] = Module[\"asm\"][\"Sub\"]).apply(null, arguments);\n        };\n        var _Sum = Module[\"_Sum\"] = function() {\n          return (_Sum = Module[\"_Sum\"] = Module[\"asm\"][\"Sum\"]).apply(null, arguments);\n        };\n        var _Tan = Module[\"_Tan\"] = function() {\n          return (_Tan = Module[\"_Tan\"] = Module[\"asm\"][\"Tan\"]).apply(null, arguments);\n        };\n        var _Tanh = Module[\"_Tanh\"] = function() {\n          return (_Tanh = Module[\"_Tanh\"] = Module[\"asm\"][\"Tanh\"]).apply(null, arguments);\n        };\n        var _Tile = Module[\"_Tile\"] = function() {\n          return (_Tile = Module[\"_Tile\"] = Module[\"asm\"][\"Tile\"]).apply(null, arguments);\n        };\n        var _TopK = Module[\"_TopK\"] = function() {\n          return (_TopK = Module[\"_TopK\"] = Module[\"asm\"][\"TopK\"]).apply(null, arguments);\n        };\n        var _Transform = Module[\"_Transform\"] = function() {\n          return (_Transform = Module[\"_Transform\"] = Module[\"asm\"][\"Transform\"]).apply(null, arguments);\n        };\n        var _Transpose = Module[\"_Transpose\"] = function() {\n          return (_Transpose = Module[\"_Transpose\"] = Module[\"asm\"][\"Transpose\"]).apply(null, arguments);\n        };\n        var __FusedMatMul = Module[\"__FusedMatMul\"] = function() {\n          return (__FusedMatMul = Module[\"__FusedMatMul\"] = Module[\"asm\"][\"_FusedMatMul\"]).apply(null, arguments);\n        };\n        var _malloc = Module[\"_malloc\"] = function() {\n          return (_malloc = Module[\"_malloc\"] = Module[\"asm\"][\"malloc\"]).apply(null, arguments);\n        };\n        var _free = Module[\"_free\"] = function() {\n          return (_free = Module[\"_free\"] = Module[\"asm\"][\"free\"]).apply(null, arguments);\n        };\n        var _emscripten_tls_init = Module[\"_emscripten_tls_init\"] = function() {\n          return (_emscripten_tls_init = Module[\"_emscripten_tls_init\"] = Module[\"asm\"][\"emscripten_tls_init\"]).apply(null, arguments);\n        };\n        var ___errno_location = Module[\"___errno_location\"] = function() {\n          return (___errno_location = Module[\"___errno_location\"] = Module[\"asm\"][\"__errno_location\"]).apply(null, arguments);\n        };\n        var _pthread_self = Module[\"_pthread_self\"] = function() {\n          return (_pthread_self = Module[\"_pthread_self\"] = Module[\"asm\"][\"pthread_self\"]).apply(null, arguments);\n        };\n        var _emscripten_main_thread_process_queued_calls = Module[\"_emscripten_main_thread_process_queued_calls\"] = function() {\n          return (_emscripten_main_thread_process_queued_calls = Module[\"_emscripten_main_thread_process_queued_calls\"] = Module[\"asm\"][\"emscripten_main_thread_process_queued_calls\"]).apply(null, arguments);\n        };\n        var __emscripten_thread_crashed = Module[\"__emscripten_thread_crashed\"] = function() {\n          return (__emscripten_thread_crashed = Module[\"__emscripten_thread_crashed\"] = Module[\"asm\"][\"_emscripten_thread_crashed\"]).apply(null, arguments);\n        };\n        var __emscripten_thread_init = Module[\"__emscripten_thread_init\"] = function() {\n          return (__emscripten_thread_init = Module[\"__emscripten_thread_init\"] = Module[\"asm\"][\"_emscripten_thread_init\"]).apply(null, arguments);\n        };\n        var _emscripten_current_thread_process_queued_calls = Module[\"_emscripten_current_thread_process_queued_calls\"] = function() {\n          return (_emscripten_current_thread_process_queued_calls = Module[\"_emscripten_current_thread_process_queued_calls\"] = Module[\"asm\"][\"emscripten_current_thread_process_queued_calls\"]).apply(null, arguments);\n        };\n        var _emscripten_main_browser_thread_id = Module[\"_emscripten_main_browser_thread_id\"] = function() {\n          return (_emscripten_main_browser_thread_id = Module[\"_emscripten_main_browser_thread_id\"] = Module[\"asm\"][\"emscripten_main_browser_thread_id\"]).apply(null, arguments);\n        };\n        var _emscripten_sync_run_in_main_thread_2 = Module[\"_emscripten_sync_run_in_main_thread_2\"] = function() {\n          return (_emscripten_sync_run_in_main_thread_2 = Module[\"_emscripten_sync_run_in_main_thread_2\"] = Module[\"asm\"][\"emscripten_sync_run_in_main_thread_2\"]).apply(null, arguments);\n        };\n        var _emscripten_sync_run_in_main_thread_4 = Module[\"_emscripten_sync_run_in_main_thread_4\"] = function() {\n          return (_emscripten_sync_run_in_main_thread_4 = Module[\"_emscripten_sync_run_in_main_thread_4\"] = Module[\"asm\"][\"emscripten_sync_run_in_main_thread_4\"]).apply(null, arguments);\n        };\n        var _emscripten_run_in_main_runtime_thread_js = Module[\"_emscripten_run_in_main_runtime_thread_js\"] = function() {\n          return (_emscripten_run_in_main_runtime_thread_js = Module[\"_emscripten_run_in_main_runtime_thread_js\"] = Module[\"asm\"][\"emscripten_run_in_main_runtime_thread_js\"]).apply(null, arguments);\n        };\n        var _emscripten_dispatch_to_thread_ = Module[\"_emscripten_dispatch_to_thread_\"] = function() {\n          return (_emscripten_dispatch_to_thread_ = Module[\"_emscripten_dispatch_to_thread_\"] = Module[\"asm\"][\"emscripten_dispatch_to_thread_\"]).apply(null, arguments);\n        };\n        var __emscripten_thread_free_data = Module[\"__emscripten_thread_free_data\"] = function() {\n          return (__emscripten_thread_free_data = Module[\"__emscripten_thread_free_data\"] = Module[\"asm\"][\"_emscripten_thread_free_data\"]).apply(null, arguments);\n        };\n        var __emscripten_thread_exit = Module[\"__emscripten_thread_exit\"] = function() {\n          return (__emscripten_thread_exit = Module[\"__emscripten_thread_exit\"] = Module[\"asm\"][\"_emscripten_thread_exit\"]).apply(null, arguments);\n        };\n        var _memalign = Module[\"_memalign\"] = function() {\n          return (_memalign = Module[\"_memalign\"] = Module[\"asm\"][\"memalign\"]).apply(null, arguments);\n        };\n        var _emscripten_stack_set_limits = Module[\"_emscripten_stack_set_limits\"] = function() {\n          return (_emscripten_stack_set_limits = Module[\"_emscripten_stack_set_limits\"] = Module[\"asm\"][\"emscripten_stack_set_limits\"]).apply(null, arguments);\n        };\n        var stackSave = Module[\"stackSave\"] = function() {\n          return (stackSave = Module[\"stackSave\"] = Module[\"asm\"][\"stackSave\"]).apply(null, arguments);\n        };\n        var stackRestore = Module[\"stackRestore\"] = function() {\n          return (stackRestore = Module[\"stackRestore\"] = Module[\"asm\"][\"stackRestore\"]).apply(null, arguments);\n        };\n        var stackAlloc = Module[\"stackAlloc\"] = function() {\n          return (stackAlloc = Module[\"stackAlloc\"] = Module[\"asm\"][\"stackAlloc\"]).apply(null, arguments);\n        };\n        var dynCall_iijjiiii = Module[\"dynCall_iijjiiii\"] = function() {\n          return (dynCall_iijjiiii = Module[\"dynCall_iijjiiii\"] = Module[\"asm\"][\"dynCall_iijjiiii\"]).apply(null, arguments);\n        };\n        var dynCall_jiji = Module[\"dynCall_jiji\"] = function() {\n          return (dynCall_jiji = Module[\"dynCall_jiji\"] = Module[\"asm\"][\"dynCall_jiji\"]).apply(null, arguments);\n        };\n        var __emscripten_allow_main_runtime_queued_calls = Module[\"__emscripten_allow_main_runtime_queued_calls\"] = 21672;\n        Module[\"cwrap\"] = cwrap;\n        Module[\"keepRuntimeAlive\"] = keepRuntimeAlive;\n        Module[\"PThread\"] = PThread;\n        Module[\"PThread\"] = PThread;\n        Module[\"wasmMemory\"] = wasmMemory;\n        Module[\"ExitStatus\"] = ExitStatus;\n        var calledRun;\n        function ExitStatus(status) {\n          this.name = \"ExitStatus\";\n          this.message = \"Program terminated with exit(\" + status + \")\";\n          this.status = status;\n        }\n        dependenciesFulfilled = function runCaller() {\n          if (!calledRun)\n            run();\n          if (!calledRun)\n            dependenciesFulfilled = runCaller;\n        };\n        function run(args) {\n          args = args || arguments_;\n          if (runDependencies > 0) {\n            return;\n          }\n          if (ENVIRONMENT_IS_PTHREAD) {\n            readyPromiseResolve(Module);\n            initRuntime();\n            postMessage({ \"cmd\": \"loaded\" });\n            return;\n          }\n          preRun();\n          if (runDependencies > 0) {\n            return;\n          }\n          function doRun() {\n            if (calledRun)\n              return;\n            calledRun = true;\n            Module[\"calledRun\"] = true;\n            if (ABORT)\n              return;\n            initRuntime();\n            readyPromiseResolve(Module);\n            if (Module[\"onRuntimeInitialized\"])\n              Module[\"onRuntimeInitialized\"]();\n            postRun();\n          }\n          if (Module[\"setStatus\"]) {\n            Module[\"setStatus\"](\"Running...\");\n            setTimeout(function() {\n              setTimeout(function() {\n                Module[\"setStatus\"](\"\");\n              }, 1);\n              doRun();\n            }, 1);\n          } else {\n            doRun();\n          }\n        }\n        Module[\"run\"] = run;\n        function exit(status, implicit) {\n          EXITSTATUS = status;\n          if (!implicit) {\n            if (ENVIRONMENT_IS_PTHREAD) {\n              exitOnMainThread(status);\n              throw \"unwind\";\n            } else {\n            }\n          }\n          if (keepRuntimeAlive()) {\n          } else {\n            exitRuntime();\n          }\n          procExit(status);\n        }\n        function procExit(code) {\n          EXITSTATUS = code;\n          if (!keepRuntimeAlive()) {\n            PThread.terminateAllThreads();\n            if (Module[\"onExit\"])\n              Module[\"onExit\"](code);\n            ABORT = true;\n          }\n          quit_(code, new ExitStatus(code));\n        }\n        if (Module[\"preInit\"]) {\n          if (typeof Module[\"preInit\"] == \"function\")\n            Module[\"preInit\"] = [Module[\"preInit\"]];\n          while (Module[\"preInit\"].length > 0) {\n            Module[\"preInit\"].pop()();\n          }\n        }\n        run();\n        var listenersAdded;\n        if (beforeListeners) {\n          listenersAdded = { uncaughtException: process.listeners(\"uncaughtException\").filter(function(listener) {\n            return !beforeListeners.uncaughtException.indexOf(listener) > -1;\n          }), unhandledRejection: process.listeners(\"unhandledRejection\").filter(function(listener) {\n            return !beforeListeners.unhandledRejection.indexOf(listener) > -1;\n          }) };\n        }\n        var actualModule;\n        if (typeof WasmBackendModule !== \"undefined\") {\n          actualModule = WasmBackendModule;\n        } else if (typeof WasmBackendModuleThreadedSimd3 !== \"undefined\") {\n          actualModule = WasmBackendModuleThreadedSimd3;\n        } else {\n          throw new Error(\"Could not find wasm module in post.js\");\n        }\n        if (listenersAdded) {\n          var tmpDispose = actualModule[\"_dispose\"];\n          actualModule[\"_dispose\"] = function() {\n            tmpDispose();\n            listenersAdded.uncaughtException.forEach(function(listener) {\n              process.removeListener(\"uncaughtException\", listener);\n            });\n            listenersAdded.unhandledRejection.forEach(function(listener) {\n              process.removeListener(\"unhandledRejection\", listener);\n            });\n          };\n        }\n        return WasmBackendModuleThreadedSimd3.ready;\n      };\n    })();\n    if (typeof exports === \"object\" && typeof module === \"object\")\n      module.exports = WasmBackendModuleThreadedSimd2;\n    else if (typeof define === \"function\" && define[\"amd\"])\n      define([], function() {\n        return WasmBackendModuleThreadedSimd2;\n      });\n    else if (typeof exports === \"object\")\n      exports[\"WasmBackendModuleThreadedSimd\"] = WasmBackendModuleThreadedSimd2;\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.worker.js\nvar require_tfjs_backend_wasm_threaded_simd_worker = __commonJS({\n  \"node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.worker.js\"(exports, module) {\n    module.exports.wasmWorkerContents = `\"use strict\";var Module={};var ENVIRONMENT_IS_NODE=typeof process===\"object\"&&typeof process.versions===\"object\"&&typeof process.versions.node===\"string\";if(ENVIRONMENT_IS_NODE){var nodeWorkerThreads=require(\"worker_threads\");var parentPort=nodeWorkerThreads.parentPort;parentPort.on(\"message\",function(data){onmessage({data:data})});var fs=require(\"fs\");Object.assign(global,{self:global,require:require,Module:Module,location:{href:__filename},Worker:nodeWorkerThreads.Worker,importScripts:function(f){(0,eval)(fs.readFileSync(f,\"utf8\"))},postMessage:function(msg){parentPort.postMessage(msg)},performance:global.performance||{now:function(){return Date.now()}}})}function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(\" \");if(ENVIRONMENT_IS_NODE){fs.writeSync(2,text+\"\n\");return}console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(\" \");postMessage({cmd:\"alert\",text:text,threadId:Module[\"_pthread_self\"]()})}var err=threadPrintErr;self.alert=threadAlert;Module[\"instantiateWasm\"]=((info,receiveInstance)=>{var instance=new WebAssembly.Instance(Module[\"wasmModule\"],info);receiveInstance(instance);Module[\"wasmModule\"]=null;return instance.exports});self.onmessage=(e=>{try{if(e.data.cmd===\"load\"){Module[\"wasmModule\"]=e.data.wasmModule;Module[\"wasmMemory\"]=e.data.wasmMemory;Module[\"buffer\"]=Module[\"wasmMemory\"].buffer;Module[\"ENVIRONMENT_IS_PTHREAD\"]=true;if(typeof e.data.urlOrBlob===\"string\"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module).then(function(instance){Module=instance})}else if(e.data.cmd===\"run\"){Module[\"__performance_now_clock_drift\"]=performance.now()-e.data.time;Module[\"__emscripten_thread_init\"](e.data.threadInfoStruct,0,0,1);Module[\"establishStackSpace\"]();Module[\"PThread\"].receiveObjectTransfer(e.data);Module[\"PThread\"].threadInit();try{var result=Module[\"invokeEntryPoint\"](e.data.start_routine,e.data.arg);if(Module[\"keepRuntimeAlive\"]()){Module[\"PThread\"].setExitStatus(result)}else{Module[\"__emscripten_thread_exit\"](result)}}catch(ex){if(ex!=\"unwind\"){if(ex instanceof Module[\"ExitStatus\"]){if(Module[\"keepRuntimeAlive\"]()){}else{Module[\"__emscripten_thread_exit\"](ex.status)}}else{throw ex}}}}else if(e.data.cmd===\"cancel\"){if(Module[\"_pthread_self\"]()){Module[\"__emscripten_thread_exit\"](-1)}}else if(e.data.target===\"setimmediate\"){}else if(e.data.cmd===\"processThreadQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_current_thread_process_queued_calls\"]()}}else if(e.data.cmd===\"processProxyingQueue\"){if(Module[\"_pthread_self\"]()){Module[\"_emscripten_proxy_execute_queue\"](e.data.queue)}}else{err(\"worker.js received unknown command \"+e.data.cmd);err(e.data)}}catch(ex){err(\"worker.js onmessage() captured an uncaught exception: \"+ex);if(ex&&ex.stack)err(ex.stack);if(Module[\"__emscripten_thread_crashed\"]){Module[\"__emscripten_thread_crashed\"]()}throw ex}});`;\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm.js\nvar require_tfjs_backend_wasm = __commonJS({\n  \"node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm.js\"(exports, module) {\n    var WasmBackendModule2 = (() => {\n      var _scriptDir = typeof document !== \"undefined\" && document.currentScript ? document.currentScript.src : void 0;\n      if (typeof __filename !== \"undefined\")\n        _scriptDir = _scriptDir || __filename;\n      return function(WasmBackendModule3) {\n        WasmBackendModule3 = WasmBackendModule3 || {};\n        var Module = typeof WasmBackendModule3 !== \"undefined\" ? WasmBackendModule3 : {};\n        var readyPromiseResolve, readyPromiseReject;\n        Module[\"ready\"] = new Promise(function(resolve, reject) {\n          readyPromiseResolve = resolve;\n          readyPromiseReject = reject;\n        });\n        var beforeListeners;\n        if (typeof process !== \"undefined\" && process.listeners) {\n          beforeListeners = { uncaughtException: process.listeners(\"uncaughtException\"), unhandledRejection: process.listeners(\"unhandledRejection\") };\n        }\n        var moduleOverrides = Object.assign({}, Module);\n        var arguments_ = [];\n        var thisProgram = \"./this.program\";\n        var quit_ = (status, toThrow) => {\n          throw toThrow;\n        };\n        var ENVIRONMENT_IS_WEB = typeof window === \"object\";\n        var ENVIRONMENT_IS_WORKER = typeof importScripts === \"function\";\n        var ENVIRONMENT_IS_NODE = typeof process === \"object\" && typeof process.versions === \"object\" && typeof process.versions.node === \"string\";\n        var scriptDirectory = \"\";\n        function locateFile(path) {\n          if (Module[\"locateFile\"]) {\n            return Module[\"locateFile\"](path, scriptDirectory);\n          }\n          return scriptDirectory + path;\n        }\n        var read_, readAsync, readBinary, setWindowTitle;\n        function logExceptionOnExit(e2) {\n          if (e2 instanceof ExitStatus)\n            return;\n          let toLog = e2;\n          err(\"exiting due to exception: \" + toLog);\n        }\n        var fs;\n        var nodePath;\n        var requireNodeFS;\n        if (ENVIRONMENT_IS_NODE) {\n          if (ENVIRONMENT_IS_WORKER) {\n            scriptDirectory = require_path().dirname(scriptDirectory) + \"/\";\n          } else {\n            scriptDirectory = __dirname + \"/\";\n          }\n          requireNodeFS = () => {\n            if (!nodePath) {\n              fs = require_fs();\n              nodePath = require_path();\n            }\n          };\n          read_ = function shell_read(filename, binary) {\n            requireNodeFS();\n            filename = nodePath[\"normalize\"](filename);\n            return fs.readFileSync(filename, binary ? void 0 : \"utf8\");\n          };\n          readBinary = (filename) => {\n            var ret = read_(filename, true);\n            if (!ret.buffer) {\n              ret = new Uint8Array(ret);\n            }\n            return ret;\n          };\n          readAsync = (filename, onload, onerror) => {\n            requireNodeFS();\n            filename = nodePath[\"normalize\"](filename);\n            fs.readFile(filename, function(err2, data) {\n              if (err2)\n                onerror(err2);\n              else\n                onload(data.buffer);\n            });\n          };\n          if (process[\"argv\"].length > 1) {\n            thisProgram = process[\"argv\"][1].replace(/\\\\/g, \"/\");\n          }\n          arguments_ = process[\"argv\"].slice(2);\n          process[\"on\"](\"uncaughtException\", function(ex) {\n            if (!(ex instanceof ExitStatus)) {\n              throw ex;\n            }\n          });\n          process[\"on\"](\"unhandledRejection\", function(reason) {\n            throw reason;\n          });\n          quit_ = (status, toThrow) => {\n            if (keepRuntimeAlive()) {\n              process[\"exitCode\"] = status;\n              throw toThrow;\n            }\n            logExceptionOnExit(toThrow);\n            process[\"exit\"](status);\n          };\n          Module[\"inspect\"] = function() {\n            return \"[Emscripten Module object]\";\n          };\n        } else if (ENVIRONMENT_IS_WEB || ENVIRONMENT_IS_WORKER) {\n          if (ENVIRONMENT_IS_WORKER) {\n            scriptDirectory = self.location.href;\n          } else if (typeof document !== \"undefined\" && document.currentScript) {\n            scriptDirectory = document.currentScript.src;\n          }\n          if (_scriptDir) {\n            scriptDirectory = _scriptDir;\n          }\n          if (scriptDirectory.indexOf(\"blob:\") !== 0) {\n            scriptDirectory = scriptDirectory.substr(0, scriptDirectory.replace(/[?#].*/, \"\").lastIndexOf(\"/\") + 1);\n          } else {\n            scriptDirectory = \"\";\n          }\n          {\n            read_ = (url) => {\n              var xhr = new XMLHttpRequest();\n              xhr.open(\"GET\", url, false);\n              xhr.send(null);\n              return xhr.responseText;\n            };\n            if (ENVIRONMENT_IS_WORKER) {\n              readBinary = (url) => {\n                var xhr = new XMLHttpRequest();\n                xhr.open(\"GET\", url, false);\n                xhr.responseType = \"arraybuffer\";\n                xhr.send(null);\n                return new Uint8Array(xhr.response);\n              };\n            }\n            readAsync = (url, onload, onerror) => {\n              var xhr = new XMLHttpRequest();\n              xhr.open(\"GET\", url, true);\n              xhr.responseType = \"arraybuffer\";\n              xhr.onload = () => {\n                if (xhr.status == 200 || xhr.status == 0 && xhr.response) {\n                  onload(xhr.response);\n                  return;\n                }\n                onerror();\n              };\n              xhr.onerror = onerror;\n              xhr.send(null);\n            };\n          }\n          setWindowTitle = (title) => document.title = title;\n        } else {\n        }\n        var out = Module[\"print\"] || console.log.bind(console);\n        var err = Module[\"printErr\"] || console.warn.bind(console);\n        Object.assign(Module, moduleOverrides);\n        moduleOverrides = null;\n        if (Module[\"arguments\"])\n          arguments_ = Module[\"arguments\"];\n        if (Module[\"thisProgram\"])\n          thisProgram = Module[\"thisProgram\"];\n        if (Module[\"quit\"])\n          quit_ = Module[\"quit\"];\n        var POINTER_SIZE = 4;\n        function warnOnce(text) {\n          if (!warnOnce.shown)\n            warnOnce.shown = {};\n          if (!warnOnce.shown[text]) {\n            warnOnce.shown[text] = 1;\n            err(text);\n          }\n        }\n        function convertJsFunctionToWasm(func2, sig) {\n          if (typeof WebAssembly.Function === \"function\") {\n            var typeNames = { \"i\": \"i32\", \"j\": \"i64\", \"f\": \"f32\", \"d\": \"f64\" };\n            var type = { parameters: [], results: sig[0] == \"v\" ? [] : [typeNames[sig[0]]] };\n            for (var i2 = 1; i2 < sig.length; ++i2) {\n              type.parameters.push(typeNames[sig[i2]]);\n            }\n            return new WebAssembly.Function(type, func2);\n          }\n          var typeSection = [1, 0, 1, 96];\n          var sigRet = sig.slice(0, 1);\n          var sigParam = sig.slice(1);\n          var typeCodes = { \"i\": 127, \"j\": 126, \"f\": 125, \"d\": 124 };\n          typeSection.push(sigParam.length);\n          for (var i2 = 0; i2 < sigParam.length; ++i2) {\n            typeSection.push(typeCodes[sigParam[i2]]);\n          }\n          if (sigRet == \"v\") {\n            typeSection.push(0);\n          } else {\n            typeSection = typeSection.concat([1, typeCodes[sigRet]]);\n          }\n          typeSection[1] = typeSection.length - 2;\n          var bytes = new Uint8Array([0, 97, 115, 109, 1, 0, 0, 0].concat(typeSection, [2, 7, 1, 1, 101, 1, 102, 0, 0, 7, 5, 1, 1, 102, 0, 0]));\n          var module2 = new WebAssembly.Module(bytes);\n          var instance = new WebAssembly.Instance(module2, { \"e\": { \"f\": func2 } });\n          var wrappedFunc = instance.exports[\"f\"];\n          return wrappedFunc;\n        }\n        var freeTableIndexes = [];\n        var functionsInTableMap;\n        function getEmptyTableSlot() {\n          if (freeTableIndexes.length) {\n            return freeTableIndexes.pop();\n          }\n          try {\n            wasmTable.grow(1);\n          } catch (err2) {\n            if (!(err2 instanceof RangeError)) {\n              throw err2;\n            }\n            throw \"Unable to grow wasm table. Set ALLOW_TABLE_GROWTH.\";\n          }\n          return wasmTable.length - 1;\n        }\n        function updateTableMap(offset, count2) {\n          for (var i2 = offset; i2 < offset + count2; i2++) {\n            var item = getWasmTableEntry(i2);\n            if (item) {\n              functionsInTableMap.set(item, i2);\n            }\n          }\n        }\n        var tempRet0 = 0;\n        var setTempRet0 = (value) => {\n          tempRet0 = value;\n        };\n        var wasmBinary;\n        if (Module[\"wasmBinary\"])\n          wasmBinary = Module[\"wasmBinary\"];\n        var noExitRuntime = Module[\"noExitRuntime\"] || true;\n        if (typeof WebAssembly !== \"object\") {\n          abort(\"no native wasm support detected\");\n        }\n        var wasmMemory;\n        var ABORT = false;\n        var EXITSTATUS;\n        function assert3(condition, text) {\n          if (!condition) {\n            abort(text);\n          }\n        }\n        function getCFunc(ident) {\n          var func2 = Module[\"_\" + ident];\n          return func2;\n        }\n        function ccall(ident, returnType, argTypes, args, opts) {\n          var toC = { \"string\": function(str) {\n            var ret2 = 0;\n            if (str !== null && str !== void 0 && str !== 0) {\n              var len = (str.length << 2) + 1;\n              ret2 = stackAlloc(len);\n              stringToUTF8(str, ret2, len);\n            }\n            return ret2;\n          }, \"array\": function(arr) {\n            var ret2 = stackAlloc(arr.length);\n            writeArrayToMemory(arr, ret2);\n            return ret2;\n          } };\n          function convertReturnValue(ret2) {\n            if (returnType === \"string\")\n              return UTF8ToString(ret2);\n            if (returnType === \"boolean\")\n              return Boolean(ret2);\n            return ret2;\n          }\n          var func2 = getCFunc(ident);\n          var cArgs = [];\n          var stack2 = 0;\n          if (args) {\n            for (var i2 = 0; i2 < args.length; i2++) {\n              var converter = toC[argTypes[i2]];\n              if (converter) {\n                if (stack2 === 0)\n                  stack2 = stackSave();\n                cArgs[i2] = converter(args[i2]);\n              } else {\n                cArgs[i2] = args[i2];\n              }\n            }\n          }\n          var ret = func2.apply(null, cArgs);\n          function onDone(ret2) {\n            if (stack2 !== 0)\n              stackRestore(stack2);\n            return convertReturnValue(ret2);\n          }\n          ret = onDone(ret);\n          return ret;\n        }\n        function cwrap(ident, returnType, argTypes, opts) {\n          argTypes = argTypes || [];\n          var numericArgs = argTypes.every(function(type) {\n            return type === \"number\";\n          });\n          var numericRet = returnType !== \"string\";\n          if (numericRet && numericArgs && !opts) {\n            return getCFunc(ident);\n          }\n          return function() {\n            return ccall(ident, returnType, argTypes, arguments, opts);\n          };\n        }\n        var ALLOC_STACK = 1;\n        var UTF8Decoder = typeof TextDecoder !== \"undefined\" ? new TextDecoder(\"utf8\") : void 0;\n        function UTF8ArrayToString(heap, idx, maxBytesToRead) {\n          var endIdx = idx + maxBytesToRead;\n          var endPtr = idx;\n          while (heap[endPtr] && !(endPtr >= endIdx))\n            ++endPtr;\n          if (endPtr - idx > 16 && heap.subarray && UTF8Decoder) {\n            return UTF8Decoder.decode(heap.subarray(idx, endPtr));\n          } else {\n            var str = \"\";\n            while (idx < endPtr) {\n              var u0 = heap[idx++];\n              if (!(u0 & 128)) {\n                str += String.fromCharCode(u0);\n                continue;\n              }\n              var u1 = heap[idx++] & 63;\n              if ((u0 & 224) == 192) {\n                str += String.fromCharCode((u0 & 31) << 6 | u1);\n                continue;\n              }\n              var u2 = heap[idx++] & 63;\n              if ((u0 & 240) == 224) {\n                u0 = (u0 & 15) << 12 | u1 << 6 | u2;\n              } else {\n                u0 = (u0 & 7) << 18 | u1 << 12 | u2 << 6 | heap[idx++] & 63;\n              }\n              if (u0 < 65536) {\n                str += String.fromCharCode(u0);\n              } else {\n                var ch = u0 - 65536;\n                str += String.fromCharCode(55296 | ch >> 10, 56320 | ch & 1023);\n              }\n            }\n          }\n          return str;\n        }\n        function UTF8ToString(ptr, maxBytesToRead) {\n          return ptr ? UTF8ArrayToString(HEAPU8, ptr, maxBytesToRead) : \"\";\n        }\n        function stringToUTF8Array(str, heap, outIdx, maxBytesToWrite) {\n          if (!(maxBytesToWrite > 0))\n            return 0;\n          var startIdx = outIdx;\n          var endIdx = outIdx + maxBytesToWrite - 1;\n          for (var i2 = 0; i2 < str.length; ++i2) {\n            var u = str.charCodeAt(i2);\n            if (u >= 55296 && u <= 57343) {\n              var u1 = str.charCodeAt(++i2);\n              u = 65536 + ((u & 1023) << 10) | u1 & 1023;\n            }\n            if (u <= 127) {\n              if (outIdx >= endIdx)\n                break;\n              heap[outIdx++] = u;\n            } else if (u <= 2047) {\n              if (outIdx + 1 >= endIdx)\n                break;\n              heap[outIdx++] = 192 | u >> 6;\n              heap[outIdx++] = 128 | u & 63;\n            } else if (u <= 65535) {\n              if (outIdx + 2 >= endIdx)\n                break;\n              heap[outIdx++] = 224 | u >> 12;\n              heap[outIdx++] = 128 | u >> 6 & 63;\n              heap[outIdx++] = 128 | u & 63;\n            } else {\n              if (outIdx + 3 >= endIdx)\n                break;\n              heap[outIdx++] = 240 | u >> 18;\n              heap[outIdx++] = 128 | u >> 12 & 63;\n              heap[outIdx++] = 128 | u >> 6 & 63;\n              heap[outIdx++] = 128 | u & 63;\n            }\n          }\n          heap[outIdx] = 0;\n          return outIdx - startIdx;\n        }\n        function stringToUTF8(str, outPtr, maxBytesToWrite) {\n          return stringToUTF8Array(str, HEAPU8, outPtr, maxBytesToWrite);\n        }\n        function lengthBytesUTF8(str) {\n          var len = 0;\n          for (var i2 = 0; i2 < str.length; ++i2) {\n            var u = str.charCodeAt(i2);\n            if (u >= 55296 && u <= 57343)\n              u = 65536 + ((u & 1023) << 10) | str.charCodeAt(++i2) & 1023;\n            if (u <= 127)\n              ++len;\n            else if (u <= 2047)\n              len += 2;\n            else if (u <= 65535)\n              len += 3;\n            else\n              len += 4;\n          }\n          return len;\n        }\n        var UTF16Decoder = typeof TextDecoder !== \"undefined\" ? new TextDecoder(\"utf-16le\") : void 0;\n        function writeArrayToMemory(array2, buffer3) {\n          HEAP8.set(array2, buffer3);\n        }\n        function writeAsciiToMemory(str, buffer3, dontAddNull) {\n          for (var i2 = 0; i2 < str.length; ++i2) {\n            HEAP8[buffer3++ >> 0] = str.charCodeAt(i2);\n          }\n          if (!dontAddNull)\n            HEAP8[buffer3 >> 0] = 0;\n        }\n        function alignUp(x, multiple) {\n          if (x % multiple > 0) {\n            x += multiple - x % multiple;\n          }\n          return x;\n        }\n        var buffer2, HEAP8, HEAPU8, HEAP16, HEAPU16, HEAP32, HEAPU32, HEAPF32, HEAPF64;\n        function updateGlobalBufferAndViews(buf) {\n          buffer2 = buf;\n          Module[\"HEAP8\"] = HEAP8 = new Int8Array(buf);\n          Module[\"HEAP16\"] = HEAP16 = new Int16Array(buf);\n          Module[\"HEAP32\"] = HEAP32 = new Int32Array(buf);\n          Module[\"HEAPU8\"] = HEAPU8 = new Uint8Array(buf);\n          Module[\"HEAPU16\"] = HEAPU16 = new Uint16Array(buf);\n          Module[\"HEAPU32\"] = HEAPU32 = new Uint32Array(buf);\n          Module[\"HEAPF32\"] = HEAPF32 = new Float32Array(buf);\n          Module[\"HEAPF64\"] = HEAPF64 = new Float64Array(buf);\n        }\n        var INITIAL_MEMORY = Module[\"INITIAL_MEMORY\"] || 16777216;\n        var wasmTable;\n        var __ATPRERUN__ = [];\n        var __ATINIT__ = [];\n        var __ATPOSTRUN__ = [];\n        var runtimeInitialized = false;\n        var runtimeExited = false;\n        var runtimeKeepaliveCounter = 0;\n        function keepRuntimeAlive() {\n          return noExitRuntime || runtimeKeepaliveCounter > 0;\n        }\n        function preRun() {\n          if (Module[\"preRun\"]) {\n            if (typeof Module[\"preRun\"] == \"function\")\n              Module[\"preRun\"] = [Module[\"preRun\"]];\n            while (Module[\"preRun\"].length) {\n              addOnPreRun(Module[\"preRun\"].shift());\n            }\n          }\n          callRuntimeCallbacks(__ATPRERUN__);\n        }\n        function initRuntime() {\n          runtimeInitialized = true;\n          callRuntimeCallbacks(__ATINIT__);\n        }\n        function exitRuntime() {\n          runtimeExited = true;\n        }\n        function postRun() {\n          if (Module[\"postRun\"]) {\n            if (typeof Module[\"postRun\"] == \"function\")\n              Module[\"postRun\"] = [Module[\"postRun\"]];\n            while (Module[\"postRun\"].length) {\n              addOnPostRun(Module[\"postRun\"].shift());\n            }\n          }\n          callRuntimeCallbacks(__ATPOSTRUN__);\n        }\n        function addOnPreRun(cb) {\n          __ATPRERUN__.unshift(cb);\n        }\n        function addOnInit(cb) {\n          __ATINIT__.unshift(cb);\n        }\n        function addOnPostRun(cb) {\n          __ATPOSTRUN__.unshift(cb);\n        }\n        var runDependencies = 0;\n        var runDependencyWatcher = null;\n        var dependenciesFulfilled = null;\n        function addRunDependency(id) {\n          runDependencies++;\n          if (Module[\"monitorRunDependencies\"]) {\n            Module[\"monitorRunDependencies\"](runDependencies);\n          }\n        }\n        function removeRunDependency(id) {\n          runDependencies--;\n          if (Module[\"monitorRunDependencies\"]) {\n            Module[\"monitorRunDependencies\"](runDependencies);\n          }\n          if (runDependencies == 0) {\n            if (runDependencyWatcher !== null) {\n              clearInterval(runDependencyWatcher);\n              runDependencyWatcher = null;\n            }\n            if (dependenciesFulfilled) {\n              var callback = dependenciesFulfilled;\n              dependenciesFulfilled = null;\n              callback();\n            }\n          }\n        }\n        Module[\"preloadedImages\"] = {};\n        Module[\"preloadedAudios\"] = {};\n        function abort(what) {\n          {\n            if (Module[\"onAbort\"]) {\n              Module[\"onAbort\"](what);\n            }\n          }\n          what = \"Aborted(\" + what + \")\";\n          err(what);\n          ABORT = true;\n          EXITSTATUS = 1;\n          what += \". Build with -s ASSERTIONS=1 for more info.\";\n          var e2 = new WebAssembly.RuntimeError(what);\n          readyPromiseReject(e2);\n          throw e2;\n        }\n        var dataURIPrefix = \"data:application/octet-stream;base64,\";\n        function isDataURI(filename) {\n          return filename.startsWith(dataURIPrefix);\n        }\n        function isFileURI(filename) {\n          return filename.startsWith(\"file://\");\n        }\n        var wasmBinaryFile;\n        wasmBinaryFile = \"tfjs-backend-wasm.wasm\";\n        if (!isDataURI(wasmBinaryFile)) {\n          wasmBinaryFile = locateFile(wasmBinaryFile);\n        }\n        function getBinary(file) {\n          try {\n            if (file == wasmBinaryFile && wasmBinary) {\n              return new Uint8Array(wasmBinary);\n            }\n            if (readBinary) {\n              return readBinary(file);\n            } else {\n              throw \"both async and sync fetching of the wasm failed\";\n            }\n          } catch (err2) {\n            abort(err2);\n          }\n        }\n        function getBinaryPromise() {\n          if (!wasmBinary && (ENVIRONMENT_IS_WEB || ENVIRONMENT_IS_WORKER)) {\n            if (typeof fetch === \"function\" && !isFileURI(wasmBinaryFile)) {\n              return fetch(wasmBinaryFile, { credentials: \"same-origin\" }).then(function(response) {\n                if (!response[\"ok\"]) {\n                  throw \"failed to load wasm binary file at '\" + wasmBinaryFile + \"'\";\n                }\n                return response[\"arrayBuffer\"]();\n              }).catch(function() {\n                return getBinary(wasmBinaryFile);\n              });\n            } else {\n              if (readAsync) {\n                return new Promise(function(resolve, reject) {\n                  readAsync(wasmBinaryFile, function(response) {\n                    resolve(new Uint8Array(response));\n                  }, reject);\n                });\n              }\n            }\n          }\n          return Promise.resolve().then(function() {\n            return getBinary(wasmBinaryFile);\n          });\n        }\n        function createWasm() {\n          var info = { \"env\": asmLibraryArg, \"wasi_snapshot_preview1\": asmLibraryArg };\n          function receiveInstance(instance, module2) {\n            var exports3 = instance.exports;\n            Module[\"asm\"] = exports3;\n            wasmMemory = Module[\"asm\"][\"memory\"];\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n            wasmTable = Module[\"asm\"][\"__indirect_function_table\"];\n            addOnInit(Module[\"asm\"][\"__wasm_call_ctors\"]);\n            removeRunDependency(\"wasm-instantiate\");\n          }\n          addRunDependency(\"wasm-instantiate\");\n          function receiveInstantiationResult(result) {\n            receiveInstance(result[\"instance\"]);\n          }\n          function instantiateArrayBuffer(receiver) {\n            return getBinaryPromise().then(function(binary) {\n              return WebAssembly.instantiate(binary, info);\n            }).then(function(instance) {\n              return instance;\n            }).then(receiver, function(reason) {\n              err(\"failed to asynchronously prepare wasm: \" + reason);\n              abort(reason);\n            });\n          }\n          function instantiateAsync() {\n            if (!wasmBinary && typeof WebAssembly.instantiateStreaming === \"function\" && !isDataURI(wasmBinaryFile) && !isFileURI(wasmBinaryFile) && typeof fetch === \"function\") {\n              return fetch(wasmBinaryFile, { credentials: \"same-origin\" }).then(function(response) {\n                var result = WebAssembly.instantiateStreaming(response, info);\n                return result.then(receiveInstantiationResult, function(reason) {\n                  err(\"wasm streaming compile failed: \" + reason);\n                  err(\"falling back to ArrayBuffer instantiation\");\n                  return instantiateArrayBuffer(receiveInstantiationResult);\n                });\n              });\n            } else {\n              return instantiateArrayBuffer(receiveInstantiationResult);\n            }\n          }\n          if (Module[\"instantiateWasm\"]) {\n            try {\n              var exports2 = Module[\"instantiateWasm\"](info, receiveInstance);\n              return exports2;\n            } catch (e2) {\n              err(\"Module.instantiateWasm callback failed with error: \" + e2);\n              return false;\n            }\n          }\n          instantiateAsync().catch(readyPromiseReject);\n          return {};\n        }\n        var tempDouble;\n        var tempI64;\n        function callRuntimeCallbacks(callbacks2) {\n          while (callbacks2.length > 0) {\n            var callback = callbacks2.shift();\n            if (typeof callback == \"function\") {\n              callback(Module);\n              continue;\n            }\n            var func2 = callback.func;\n            if (typeof func2 === \"number\") {\n              if (callback.arg === void 0) {\n                getWasmTableEntry(func2)();\n              } else {\n                getWasmTableEntry(func2)(callback.arg);\n              }\n            } else {\n              func2(callback.arg === void 0 ? null : callback.arg);\n            }\n          }\n        }\n        function demangle(func2) {\n          return func2;\n        }\n        function demangleAll(text) {\n          var regex = /\\b_Z[\\w\\d_]+/g;\n          return text.replace(regex, function(x) {\n            var y = demangle(x);\n            return x === y ? x : y + \" [\" + x + \"]\";\n          });\n        }\n        var wasmTableMirror = [];\n        function getWasmTableEntry(funcPtr) {\n          var func2 = wasmTableMirror[funcPtr];\n          if (!func2) {\n            if (funcPtr >= wasmTableMirror.length)\n              wasmTableMirror.length = funcPtr + 1;\n            wasmTableMirror[funcPtr] = func2 = wasmTable.get(funcPtr);\n          }\n          return func2;\n        }\n        function jsStackTrace() {\n          var error = new Error();\n          if (!error.stack) {\n            try {\n              throw new Error();\n            } catch (e2) {\n              error = e2;\n            }\n            if (!error.stack) {\n              return \"(no stack trace available)\";\n            }\n          }\n          return error.stack.toString();\n        }\n        function setWasmTableEntry(idx, func2) {\n          wasmTable.set(idx, func2);\n          wasmTableMirror[idx] = func2;\n        }\n        function _abort() {\n          abort(\"\");\n        }\n        function _emscripten_get_heap_max() {\n          return 2147483648;\n        }\n        function _emscripten_memcpy_big(dest, src, num) {\n          HEAPU8.copyWithin(dest, src, src + num);\n        }\n        function emscripten_realloc_buffer(size) {\n          try {\n            wasmMemory.grow(size - buffer2.byteLength + 65535 >>> 16);\n            updateGlobalBufferAndViews(wasmMemory.buffer);\n            return 1;\n          } catch (e2) {\n          }\n        }\n        function _emscripten_resize_heap(requestedSize) {\n          var oldSize = HEAPU8.length;\n          requestedSize = requestedSize >>> 0;\n          var maxHeapSize = _emscripten_get_heap_max();\n          if (requestedSize > maxHeapSize) {\n            return false;\n          }\n          for (var cutDown = 1; cutDown <= 4; cutDown *= 2) {\n            var overGrownHeapSize = oldSize * (1 + 0.2 / cutDown);\n            overGrownHeapSize = Math.min(overGrownHeapSize, requestedSize + 100663296);\n            var newSize = Math.min(maxHeapSize, alignUp(Math.max(requestedSize, overGrownHeapSize), 65536));\n            var replacement = emscripten_realloc_buffer(newSize);\n            if (replacement) {\n              return true;\n            }\n          }\n          return false;\n        }\n        var SYSCALLS = { mappings: {}, buffers: [null, [], []], printChar: function(stream, curr) {\n          var buffer3 = SYSCALLS.buffers[stream];\n          if (curr === 0 || curr === 10) {\n            (stream === 1 ? out : err)(UTF8ArrayToString(buffer3, 0));\n            buffer3.length = 0;\n          } else {\n            buffer3.push(curr);\n          }\n        }, varargs: void 0, get: function() {\n          SYSCALLS.varargs += 4;\n          var ret = HEAP32[SYSCALLS.varargs - 4 >> 2];\n          return ret;\n        }, getStr: function(ptr) {\n          var ret = UTF8ToString(ptr);\n          return ret;\n        }, get64: function(low, high) {\n          return low;\n        } };\n        function _fd_close(fd) {\n          return 0;\n        }\n        function _fd_seek(fd, offset_low, offset_high, whence, newOffset) {\n        }\n        function _fd_write(fd, iov, iovcnt, pnum) {\n          var num = 0;\n          for (var i2 = 0; i2 < iovcnt; i2++) {\n            var ptr = HEAP32[iov >> 2];\n            var len = HEAP32[iov + 4 >> 2];\n            iov += 8;\n            for (var j = 0; j < len; j++) {\n              SYSCALLS.printChar(fd, HEAPU8[ptr + j]);\n            }\n            num += len;\n          }\n          HEAP32[pnum >> 2] = num;\n          return 0;\n        }\n        function _setTempRet0(val) {\n          setTempRet0(val);\n        }\n        var ASSERTIONS = false;\n        var asmLibraryArg = { \"abort\": _abort, \"emscripten_get_heap_max\": _emscripten_get_heap_max, \"emscripten_memcpy_big\": _emscripten_memcpy_big, \"emscripten_resize_heap\": _emscripten_resize_heap, \"fd_close\": _fd_close, \"fd_seek\": _fd_seek, \"fd_write\": _fd_write, \"setTempRet0\": _setTempRet0 };\n        var asm = createWasm();\n        var ___wasm_call_ctors = Module[\"___wasm_call_ctors\"] = function() {\n          return (___wasm_call_ctors = Module[\"___wasm_call_ctors\"] = Module[\"asm\"][\"__wasm_call_ctors\"]).apply(null, arguments);\n        };\n        var _init = Module[\"_init\"] = function() {\n          return (_init = Module[\"_init\"] = Module[\"asm\"][\"init\"]).apply(null, arguments);\n        };\n        var _init_with_threads_count = Module[\"_init_with_threads_count\"] = function() {\n          return (_init_with_threads_count = Module[\"_init_with_threads_count\"] = Module[\"asm\"][\"init_with_threads_count\"]).apply(null, arguments);\n        };\n        var _get_threads_count = Module[\"_get_threads_count\"] = function() {\n          return (_get_threads_count = Module[\"_get_threads_count\"] = Module[\"asm\"][\"get_threads_count\"]).apply(null, arguments);\n        };\n        var _register_tensor = Module[\"_register_tensor\"] = function() {\n          return (_register_tensor = Module[\"_register_tensor\"] = Module[\"asm\"][\"register_tensor\"]).apply(null, arguments);\n        };\n        var _dispose_data = Module[\"_dispose_data\"] = function() {\n          return (_dispose_data = Module[\"_dispose_data\"] = Module[\"asm\"][\"dispose_data\"]).apply(null, arguments);\n        };\n        var _dispose = Module[\"_dispose\"] = function() {\n          return (_dispose = Module[\"_dispose\"] = Module[\"asm\"][\"dispose\"]).apply(null, arguments);\n        };\n        var _Abs = Module[\"_Abs\"] = function() {\n          return (_Abs = Module[\"_Abs\"] = Module[\"asm\"][\"Abs\"]).apply(null, arguments);\n        };\n        var _Add = Module[\"_Add\"] = function() {\n          return (_Add = Module[\"_Add\"] = Module[\"asm\"][\"Add\"]).apply(null, arguments);\n        };\n        var _AddN = Module[\"_AddN\"] = function() {\n          return (_AddN = Module[\"_AddN\"] = Module[\"asm\"][\"AddN\"]).apply(null, arguments);\n        };\n        var _All = Module[\"_All\"] = function() {\n          return (_All = Module[\"_All\"] = Module[\"asm\"][\"All\"]).apply(null, arguments);\n        };\n        var _Any = Module[\"_Any\"] = function() {\n          return (_Any = Module[\"_Any\"] = Module[\"asm\"][\"Any\"]).apply(null, arguments);\n        };\n        var _ArgMax = Module[\"_ArgMax\"] = function() {\n          return (_ArgMax = Module[\"_ArgMax\"] = Module[\"asm\"][\"ArgMax\"]).apply(null, arguments);\n        };\n        var _AvgPool = Module[\"_AvgPool\"] = function() {\n          return (_AvgPool = Module[\"_AvgPool\"] = Module[\"asm\"][\"AvgPool\"]).apply(null, arguments);\n        };\n        var _BatchMatMul = Module[\"_BatchMatMul\"] = function() {\n          return (_BatchMatMul = Module[\"_BatchMatMul\"] = Module[\"asm\"][\"BatchMatMul\"]).apply(null, arguments);\n        };\n        var _Ceil = Module[\"_Ceil\"] = function() {\n          return (_Ceil = Module[\"_Ceil\"] = Module[\"asm\"][\"Ceil\"]).apply(null, arguments);\n        };\n        var _ClipByValue = Module[\"_ClipByValue\"] = function() {\n          return (_ClipByValue = Module[\"_ClipByValue\"] = Module[\"asm\"][\"ClipByValue\"]).apply(null, arguments);\n        };\n        var _Conv2D = Module[\"_Conv2D\"] = function() {\n          return (_Conv2D = Module[\"_Conv2D\"] = Module[\"asm\"][\"Conv2D\"]).apply(null, arguments);\n        };\n        var _Conv2DBackpropInput = Module[\"_Conv2DBackpropInput\"] = function() {\n          return (_Conv2DBackpropInput = Module[\"_Conv2DBackpropInput\"] = Module[\"asm\"][\"Conv2DBackpropInput\"]).apply(null, arguments);\n        };\n        var _Cos = Module[\"_Cos\"] = function() {\n          return (_Cos = Module[\"_Cos\"] = Module[\"asm\"][\"Cos\"]).apply(null, arguments);\n        };\n        var _Cosh = Module[\"_Cosh\"] = function() {\n          return (_Cosh = Module[\"_Cosh\"] = Module[\"asm\"][\"Cosh\"]).apply(null, arguments);\n        };\n        var _CropAndResize = Module[\"_CropAndResize\"] = function() {\n          return (_CropAndResize = Module[\"_CropAndResize\"] = Module[\"asm\"][\"CropAndResize\"]).apply(null, arguments);\n        };\n        var _Cumprod = Module[\"_Cumprod\"] = function() {\n          return (_Cumprod = Module[\"_Cumprod\"] = Module[\"asm\"][\"Cumprod\"]).apply(null, arguments);\n        };\n        var _Cumsum = Module[\"_Cumsum\"] = function() {\n          return (_Cumsum = Module[\"_Cumsum\"] = Module[\"asm\"][\"Cumsum\"]).apply(null, arguments);\n        };\n        var _DepthToSpace = Module[\"_DepthToSpace\"] = function() {\n          return (_DepthToSpace = Module[\"_DepthToSpace\"] = Module[\"asm\"][\"DepthToSpace\"]).apply(null, arguments);\n        };\n        var _DepthwiseConv2dNative = Module[\"_DepthwiseConv2dNative\"] = function() {\n          return (_DepthwiseConv2dNative = Module[\"_DepthwiseConv2dNative\"] = Module[\"asm\"][\"DepthwiseConv2dNative\"]).apply(null, arguments);\n        };\n        var _Elu = Module[\"_Elu\"] = function() {\n          return (_Elu = Module[\"_Elu\"] = Module[\"asm\"][\"Elu\"]).apply(null, arguments);\n        };\n        var _Equal = Module[\"_Equal\"] = function() {\n          return (_Equal = Module[\"_Equal\"] = Module[\"asm\"][\"Equal\"]).apply(null, arguments);\n        };\n        var _Exp = Module[\"_Exp\"] = function() {\n          return (_Exp = Module[\"_Exp\"] = Module[\"asm\"][\"Exp\"]).apply(null, arguments);\n        };\n        var _FlipLeftRight = Module[\"_FlipLeftRight\"] = function() {\n          return (_FlipLeftRight = Module[\"_FlipLeftRight\"] = Module[\"asm\"][\"FlipLeftRight\"]).apply(null, arguments);\n        };\n        var _Floor = Module[\"_Floor\"] = function() {\n          return (_Floor = Module[\"_Floor\"] = Module[\"asm\"][\"Floor\"]).apply(null, arguments);\n        };\n        var _FloorDiv = Module[\"_FloorDiv\"] = function() {\n          return (_FloorDiv = Module[\"_FloorDiv\"] = Module[\"asm\"][\"FloorDiv\"]).apply(null, arguments);\n        };\n        var _FusedBatchNorm = Module[\"_FusedBatchNorm\"] = function() {\n          return (_FusedBatchNorm = Module[\"_FusedBatchNorm\"] = Module[\"asm\"][\"FusedBatchNorm\"]).apply(null, arguments);\n        };\n        var _FusedConv2D = Module[\"_FusedConv2D\"] = function() {\n          return (_FusedConv2D = Module[\"_FusedConv2D\"] = Module[\"asm\"][\"FusedConv2D\"]).apply(null, arguments);\n        };\n        var _FusedDepthwiseConv2D = Module[\"_FusedDepthwiseConv2D\"] = function() {\n          return (_FusedDepthwiseConv2D = Module[\"_FusedDepthwiseConv2D\"] = Module[\"asm\"][\"FusedDepthwiseConv2D\"]).apply(null, arguments);\n        };\n        var _Gather = Module[\"_Gather\"] = function() {\n          return (_Gather = Module[\"_Gather\"] = Module[\"asm\"][\"Gather\"]).apply(null, arguments);\n        };\n        var _GatherNd = Module[\"_GatherNd\"] = function() {\n          return (_GatherNd = Module[\"_GatherNd\"] = Module[\"asm\"][\"GatherNd\"]).apply(null, arguments);\n        };\n        var _Greater = Module[\"_Greater\"] = function() {\n          return (_Greater = Module[\"_Greater\"] = Module[\"asm\"][\"Greater\"]).apply(null, arguments);\n        };\n        var _GreaterEqual = Module[\"_GreaterEqual\"] = function() {\n          return (_GreaterEqual = Module[\"_GreaterEqual\"] = Module[\"asm\"][\"GreaterEqual\"]).apply(null, arguments);\n        };\n        var _LeakyRelu = Module[\"_LeakyRelu\"] = function() {\n          return (_LeakyRelu = Module[\"_LeakyRelu\"] = Module[\"asm\"][\"LeakyRelu\"]).apply(null, arguments);\n        };\n        var _Less = Module[\"_Less\"] = function() {\n          return (_Less = Module[\"_Less\"] = Module[\"asm\"][\"Less\"]).apply(null, arguments);\n        };\n        var _LessEqual = Module[\"_LessEqual\"] = function() {\n          return (_LessEqual = Module[\"_LessEqual\"] = Module[\"asm\"][\"LessEqual\"]).apply(null, arguments);\n        };\n        var _Log = Module[\"_Log\"] = function() {\n          return (_Log = Module[\"_Log\"] = Module[\"asm\"][\"Log\"]).apply(null, arguments);\n        };\n        var _LogicalAnd = Module[\"_LogicalAnd\"] = function() {\n          return (_LogicalAnd = Module[\"_LogicalAnd\"] = Module[\"asm\"][\"LogicalAnd\"]).apply(null, arguments);\n        };\n        var _LogicalNot = Module[\"_LogicalNot\"] = function() {\n          return (_LogicalNot = Module[\"_LogicalNot\"] = Module[\"asm\"][\"LogicalNot\"]).apply(null, arguments);\n        };\n        var _LogicalOr = Module[\"_LogicalOr\"] = function() {\n          return (_LogicalOr = Module[\"_LogicalOr\"] = Module[\"asm\"][\"LogicalOr\"]).apply(null, arguments);\n        };\n        var _LogicalXor = Module[\"_LogicalXor\"] = function() {\n          return (_LogicalXor = Module[\"_LogicalXor\"] = Module[\"asm\"][\"LogicalXor\"]).apply(null, arguments);\n        };\n        var _Max = Module[\"_Max\"] = function() {\n          return (_Max = Module[\"_Max\"] = Module[\"asm\"][\"Max\"]).apply(null, arguments);\n        };\n        var _MaxPool = Module[\"_MaxPool\"] = function() {\n          return (_MaxPool = Module[\"_MaxPool\"] = Module[\"asm\"][\"MaxPool\"]).apply(null, arguments);\n        };\n        var _Maximum = Module[\"_Maximum\"] = function() {\n          return (_Maximum = Module[\"_Maximum\"] = Module[\"asm\"][\"Maximum\"]).apply(null, arguments);\n        };\n        var _Mean = Module[\"_Mean\"] = function() {\n          return (_Mean = Module[\"_Mean\"] = Module[\"asm\"][\"Mean\"]).apply(null, arguments);\n        };\n        var _Min = Module[\"_Min\"] = function() {\n          return (_Min = Module[\"_Min\"] = Module[\"asm\"][\"Min\"]).apply(null, arguments);\n        };\n        var _Minimum = Module[\"_Minimum\"] = function() {\n          return (_Minimum = Module[\"_Minimum\"] = Module[\"asm\"][\"Minimum\"]).apply(null, arguments);\n        };\n        var _MirrorPad = Module[\"_MirrorPad\"] = function() {\n          return (_MirrorPad = Module[\"_MirrorPad\"] = Module[\"asm\"][\"MirrorPad\"]).apply(null, arguments);\n        };\n        var _Multiply = Module[\"_Multiply\"] = function() {\n          return (_Multiply = Module[\"_Multiply\"] = Module[\"asm\"][\"Multiply\"]).apply(null, arguments);\n        };\n        var _Neg = Module[\"_Neg\"] = function() {\n          return (_Neg = Module[\"_Neg\"] = Module[\"asm\"][\"Neg\"]).apply(null, arguments);\n        };\n        var _NonMaxSuppressionV3 = Module[\"_NonMaxSuppressionV3\"] = function() {\n          return (_NonMaxSuppressionV3 = Module[\"_NonMaxSuppressionV3\"] = Module[\"asm\"][\"NonMaxSuppressionV3\"]).apply(null, arguments);\n        };\n        var _NonMaxSuppressionV4 = Module[\"_NonMaxSuppressionV4\"] = function() {\n          return (_NonMaxSuppressionV4 = Module[\"_NonMaxSuppressionV4\"] = Module[\"asm\"][\"NonMaxSuppressionV4\"]).apply(null, arguments);\n        };\n        var _NonMaxSuppressionV5 = Module[\"_NonMaxSuppressionV5\"] = function() {\n          return (_NonMaxSuppressionV5 = Module[\"_NonMaxSuppressionV5\"] = Module[\"asm\"][\"NonMaxSuppressionV5\"]).apply(null, arguments);\n        };\n        var _NotEqual = Module[\"_NotEqual\"] = function() {\n          return (_NotEqual = Module[\"_NotEqual\"] = Module[\"asm\"][\"NotEqual\"]).apply(null, arguments);\n        };\n        var _OneHot = Module[\"_OneHot\"] = function() {\n          return (_OneHot = Module[\"_OneHot\"] = Module[\"asm\"][\"OneHot\"]).apply(null, arguments);\n        };\n        var _PadV2 = Module[\"_PadV2\"] = function() {\n          return (_PadV2 = Module[\"_PadV2\"] = Module[\"asm\"][\"PadV2\"]).apply(null, arguments);\n        };\n        var _Pow = Module[\"_Pow\"] = function() {\n          return (_Pow = Module[\"_Pow\"] = Module[\"asm\"][\"Pow\"]).apply(null, arguments);\n        };\n        var _Prelu = Module[\"_Prelu\"] = function() {\n          return (_Prelu = Module[\"_Prelu\"] = Module[\"asm\"][\"Prelu\"]).apply(null, arguments);\n        };\n        var _Prod = Module[\"_Prod\"] = function() {\n          return (_Prod = Module[\"_Prod\"] = Module[\"asm\"][\"Prod\"]).apply(null, arguments);\n        };\n        var _RealDiv = Module[\"_RealDiv\"] = function() {\n          return (_RealDiv = Module[\"_RealDiv\"] = Module[\"asm\"][\"RealDiv\"]).apply(null, arguments);\n        };\n        var _Relu = Module[\"_Relu\"] = function() {\n          return (_Relu = Module[\"_Relu\"] = Module[\"asm\"][\"Relu\"]).apply(null, arguments);\n        };\n        var _Relu6 = Module[\"_Relu6\"] = function() {\n          return (_Relu6 = Module[\"_Relu6\"] = Module[\"asm\"][\"Relu6\"]).apply(null, arguments);\n        };\n        var _ResizeBilinear = Module[\"_ResizeBilinear\"] = function() {\n          return (_ResizeBilinear = Module[\"_ResizeBilinear\"] = Module[\"asm\"][\"ResizeBilinear\"]).apply(null, arguments);\n        };\n        var _ResizeNearestNeighbor = Module[\"_ResizeNearestNeighbor\"] = function() {\n          return (_ResizeNearestNeighbor = Module[\"_ResizeNearestNeighbor\"] = Module[\"asm\"][\"ResizeNearestNeighbor\"]).apply(null, arguments);\n        };\n        var _Reverse = Module[\"_Reverse\"] = function() {\n          return (_Reverse = Module[\"_Reverse\"] = Module[\"asm\"][\"Reverse\"]).apply(null, arguments);\n        };\n        var _RotateWithOffset = Module[\"_RotateWithOffset\"] = function() {\n          return (_RotateWithOffset = Module[\"_RotateWithOffset\"] = Module[\"asm\"][\"RotateWithOffset\"]).apply(null, arguments);\n        };\n        var _Round = Module[\"_Round\"] = function() {\n          return (_Round = Module[\"_Round\"] = Module[\"asm\"][\"Round\"]).apply(null, arguments);\n        };\n        var _Rsqrt = Module[\"_Rsqrt\"] = function() {\n          return (_Rsqrt = Module[\"_Rsqrt\"] = Module[\"asm\"][\"Rsqrt\"]).apply(null, arguments);\n        };\n        var _ScatterNd = Module[\"_ScatterNd\"] = function() {\n          return (_ScatterNd = Module[\"_ScatterNd\"] = Module[\"asm\"][\"ScatterNd\"]).apply(null, arguments);\n        };\n        var _SelectV2 = Module[\"_SelectV2\"] = function() {\n          return (_SelectV2 = Module[\"_SelectV2\"] = Module[\"asm\"][\"SelectV2\"]).apply(null, arguments);\n        };\n        var _Sigmoid = Module[\"_Sigmoid\"] = function() {\n          return (_Sigmoid = Module[\"_Sigmoid\"] = Module[\"asm\"][\"Sigmoid\"]).apply(null, arguments);\n        };\n        var _Sin = Module[\"_Sin\"] = function() {\n          return (_Sin = Module[\"_Sin\"] = Module[\"asm\"][\"Sin\"]).apply(null, arguments);\n        };\n        var _Softmax = Module[\"_Softmax\"] = function() {\n          return (_Softmax = Module[\"_Softmax\"] = Module[\"asm\"][\"Softmax\"]).apply(null, arguments);\n        };\n        var _SparseFillEmptyRows = Module[\"_SparseFillEmptyRows\"] = function() {\n          return (_SparseFillEmptyRows = Module[\"_SparseFillEmptyRows\"] = Module[\"asm\"][\"SparseFillEmptyRows\"]).apply(null, arguments);\n        };\n        var _SparseReshape = Module[\"_SparseReshape\"] = function() {\n          return (_SparseReshape = Module[\"_SparseReshape\"] = Module[\"asm\"][\"SparseReshape\"]).apply(null, arguments);\n        };\n        var _SparseSegmentReduction = Module[\"_SparseSegmentReduction\"] = function() {\n          return (_SparseSegmentReduction = Module[\"_SparseSegmentReduction\"] = Module[\"asm\"][\"SparseSegmentReduction\"]).apply(null, arguments);\n        };\n        var _Sqrt = Module[\"_Sqrt\"] = function() {\n          return (_Sqrt = Module[\"_Sqrt\"] = Module[\"asm\"][\"Sqrt\"]).apply(null, arguments);\n        };\n        var _Square = Module[\"_Square\"] = function() {\n          return (_Square = Module[\"_Square\"] = Module[\"asm\"][\"Square\"]).apply(null, arguments);\n        };\n        var _SquaredDifference = Module[\"_SquaredDifference\"] = function() {\n          return (_SquaredDifference = Module[\"_SquaredDifference\"] = Module[\"asm\"][\"SquaredDifference\"]).apply(null, arguments);\n        };\n        var _Step = Module[\"_Step\"] = function() {\n          return (_Step = Module[\"_Step\"] = Module[\"asm\"][\"Step\"]).apply(null, arguments);\n        };\n        var _StridedSlice = Module[\"_StridedSlice\"] = function() {\n          return (_StridedSlice = Module[\"_StridedSlice\"] = Module[\"asm\"][\"StridedSlice\"]).apply(null, arguments);\n        };\n        var _Sub = Module[\"_Sub\"] = function() {\n          return (_Sub = Module[\"_Sub\"] = Module[\"asm\"][\"Sub\"]).apply(null, arguments);\n        };\n        var _Sum = Module[\"_Sum\"] = function() {\n          return (_Sum = Module[\"_Sum\"] = Module[\"asm\"][\"Sum\"]).apply(null, arguments);\n        };\n        var _Tan = Module[\"_Tan\"] = function() {\n          return (_Tan = Module[\"_Tan\"] = Module[\"asm\"][\"Tan\"]).apply(null, arguments);\n        };\n        var _Tanh = Module[\"_Tanh\"] = function() {\n          return (_Tanh = Module[\"_Tanh\"] = Module[\"asm\"][\"Tanh\"]).apply(null, arguments);\n        };\n        var _Tile = Module[\"_Tile\"] = function() {\n          return (_Tile = Module[\"_Tile\"] = Module[\"asm\"][\"Tile\"]).apply(null, arguments);\n        };\n        var _TopK = Module[\"_TopK\"] = function() {\n          return (_TopK = Module[\"_TopK\"] = Module[\"asm\"][\"TopK\"]).apply(null, arguments);\n        };\n        var _Transform = Module[\"_Transform\"] = function() {\n          return (_Transform = Module[\"_Transform\"] = Module[\"asm\"][\"Transform\"]).apply(null, arguments);\n        };\n        var _Transpose = Module[\"_Transpose\"] = function() {\n          return (_Transpose = Module[\"_Transpose\"] = Module[\"asm\"][\"Transpose\"]).apply(null, arguments);\n        };\n        var __FusedMatMul = Module[\"__FusedMatMul\"] = function() {\n          return (__FusedMatMul = Module[\"__FusedMatMul\"] = Module[\"asm\"][\"_FusedMatMul\"]).apply(null, arguments);\n        };\n        var _malloc = Module[\"_malloc\"] = function() {\n          return (_malloc = Module[\"_malloc\"] = Module[\"asm\"][\"malloc\"]).apply(null, arguments);\n        };\n        var _free = Module[\"_free\"] = function() {\n          return (_free = Module[\"_free\"] = Module[\"asm\"][\"free\"]).apply(null, arguments);\n        };\n        var ___errno_location = Module[\"___errno_location\"] = function() {\n          return (___errno_location = Module[\"___errno_location\"] = Module[\"asm\"][\"__errno_location\"]).apply(null, arguments);\n        };\n        var _emscripten_main_thread_process_queued_calls = Module[\"_emscripten_main_thread_process_queued_calls\"] = function() {\n          return (_emscripten_main_thread_process_queued_calls = Module[\"_emscripten_main_thread_process_queued_calls\"] = Module[\"asm\"][\"emscripten_main_thread_process_queued_calls\"]).apply(null, arguments);\n        };\n        var stackSave = Module[\"stackSave\"] = function() {\n          return (stackSave = Module[\"stackSave\"] = Module[\"asm\"][\"stackSave\"]).apply(null, arguments);\n        };\n        var stackRestore = Module[\"stackRestore\"] = function() {\n          return (stackRestore = Module[\"stackRestore\"] = Module[\"asm\"][\"stackRestore\"]).apply(null, arguments);\n        };\n        var stackAlloc = Module[\"stackAlloc\"] = function() {\n          return (stackAlloc = Module[\"stackAlloc\"] = Module[\"asm\"][\"stackAlloc\"]).apply(null, arguments);\n        };\n        var dynCall_iijjiiii = Module[\"dynCall_iijjiiii\"] = function() {\n          return (dynCall_iijjiiii = Module[\"dynCall_iijjiiii\"] = Module[\"asm\"][\"dynCall_iijjiiii\"]).apply(null, arguments);\n        };\n        var dynCall_jiji = Module[\"dynCall_jiji\"] = function() {\n          return (dynCall_jiji = Module[\"dynCall_jiji\"] = Module[\"asm\"][\"dynCall_jiji\"]).apply(null, arguments);\n        };\n        Module[\"cwrap\"] = cwrap;\n        var calledRun;\n        function ExitStatus(status) {\n          this.name = \"ExitStatus\";\n          this.message = \"Program terminated with exit(\" + status + \")\";\n          this.status = status;\n        }\n        dependenciesFulfilled = function runCaller() {\n          if (!calledRun)\n            run();\n          if (!calledRun)\n            dependenciesFulfilled = runCaller;\n        };\n        function run(args) {\n          args = args || arguments_;\n          if (runDependencies > 0) {\n            return;\n          }\n          preRun();\n          if (runDependencies > 0) {\n            return;\n          }\n          function doRun() {\n            if (calledRun)\n              return;\n            calledRun = true;\n            Module[\"calledRun\"] = true;\n            if (ABORT)\n              return;\n            initRuntime();\n            readyPromiseResolve(Module);\n            if (Module[\"onRuntimeInitialized\"])\n              Module[\"onRuntimeInitialized\"]();\n            postRun();\n          }\n          if (Module[\"setStatus\"]) {\n            Module[\"setStatus\"](\"Running...\");\n            setTimeout(function() {\n              setTimeout(function() {\n                Module[\"setStatus\"](\"\");\n              }, 1);\n              doRun();\n            }, 1);\n          } else {\n            doRun();\n          }\n        }\n        Module[\"run\"] = run;\n        function procExit(code) {\n          EXITSTATUS = code;\n          if (!keepRuntimeAlive()) {\n            if (Module[\"onExit\"])\n              Module[\"onExit\"](code);\n            ABORT = true;\n          }\n          quit_(code, new ExitStatus(code));\n        }\n        if (Module[\"preInit\"]) {\n          if (typeof Module[\"preInit\"] == \"function\")\n            Module[\"preInit\"] = [Module[\"preInit\"]];\n          while (Module[\"preInit\"].length > 0) {\n            Module[\"preInit\"].pop()();\n          }\n        }\n        run();\n        var listenersAdded;\n        if (beforeListeners) {\n          listenersAdded = { uncaughtException: process.listeners(\"uncaughtException\").filter(function(listener) {\n            return !beforeListeners.uncaughtException.indexOf(listener) > -1;\n          }), unhandledRejection: process.listeners(\"unhandledRejection\").filter(function(listener) {\n            return !beforeListeners.unhandledRejection.indexOf(listener) > -1;\n          }) };\n        }\n        var actualModule;\n        if (typeof WasmBackendModule3 !== \"undefined\") {\n          actualModule = WasmBackendModule3;\n        } else if (typeof WasmBackendModuleThreadedSimd !== \"undefined\") {\n          actualModule = WasmBackendModuleThreadedSimd;\n        } else {\n          throw new Error(\"Could not find wasm module in post.js\");\n        }\n        if (listenersAdded) {\n          var tmpDispose = actualModule[\"_dispose\"];\n          actualModule[\"_dispose\"] = function() {\n            tmpDispose();\n            listenersAdded.uncaughtException.forEach(function(listener) {\n              process.removeListener(\"uncaughtException\", listener);\n            });\n            listenersAdded.unhandledRejection.forEach(function(listener) {\n              process.removeListener(\"unhandledRejection\", listener);\n            });\n          };\n        }\n        return WasmBackendModule3.ready;\n      };\n    })();\n    if (typeof exports === \"object\" && typeof module === \"object\")\n      module.exports = WasmBackendModule2;\n    else if (typeof define === \"function\" && define[\"amd\"])\n      define([], function() {\n        return WasmBackendModule2;\n      });\n    else if (typeof exports === \"object\")\n      exports[\"WasmBackendModule\"] = WasmBackendModule2;\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/backend.js\nvar EPSILON_FLOAT32 = 1e-7;\nvar EPSILON_FLOAT16 = 1e-4;\nvar DataStorage = class {\n  constructor(backend2, dataMover) {\n    this.backend = backend2;\n    this.dataMover = dataMover;\n    this.data = /* @__PURE__ */ new WeakMap();\n    this.dataIdsCount = 0;\n  }\n  get(dataId) {\n    if (!this.data.has(dataId)) {\n      this.dataMover.moveData(this.backend, dataId);\n    }\n    return this.data.get(dataId);\n  }\n  set(dataId, value) {\n    this.dataIdsCount++;\n    this.data.set(dataId, value);\n  }\n  has(dataId) {\n    return this.data.has(dataId);\n  }\n  delete(dataId) {\n    this.dataIdsCount--;\n    return this.data.delete(dataId);\n  }\n  numDataIds() {\n    return this.dataIdsCount;\n  }\n};\nvar KernelBackend = class {\n  refCount(dataId) {\n    return notYetImplemented(\"refCount\");\n  }\n  incRef(dataId) {\n    return notYetImplemented(\"incRef\");\n  }\n  timerAvailable() {\n    return true;\n  }\n  time(f) {\n    return notYetImplemented(\"time\");\n  }\n  read(dataId) {\n    return notYetImplemented(\"read\");\n  }\n  readSync(dataId) {\n    return notYetImplemented(\"readSync\");\n  }\n  readToGPU(dataId, options) {\n    return notYetImplemented(\"readToGPU\");\n  }\n  numDataIds() {\n    return notYetImplemented(\"numDataIds\");\n  }\n  disposeData(dataId, force) {\n    return notYetImplemented(\"disposeData\");\n  }\n  write(values, shape, dtype) {\n    return notYetImplemented(\"write\");\n  }\n  move(dataId, values, shape, dtype, refCount) {\n    return notYetImplemented(\"move\");\n  }\n  memory() {\n    return notYetImplemented(\"memory\");\n  }\n  floatPrecision() {\n    return notYetImplemented(\"floatPrecision\");\n  }\n  epsilon() {\n    return this.floatPrecision() === 32 ? EPSILON_FLOAT32 : EPSILON_FLOAT16;\n  }\n  dispose() {\n    return notYetImplemented(\"dispose\");\n  }\n};\nfunction notYetImplemented(kernelName) {\n  throw new Error(`'${kernelName}' not yet implemented or not found in the registry. This kernel may not be supported by the tfjs backend you have chosen`);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/util_base.js\nfunction shuffle(array2) {\n  let counter = array2.length;\n  let index = 0;\n  while (counter > 0) {\n    index = Math.random() * counter | 0;\n    counter--;\n    swap(array2, counter, index);\n  }\n}\nfunction shuffleCombo(array2, array22) {\n  if (array2.length !== array22.length) {\n    throw new Error(`Array sizes must match to be shuffled together First array length was ${array2.length}Second array length was ${array22.length}`);\n  }\n  let counter = array2.length;\n  let index = 0;\n  while (counter > 0) {\n    index = Math.random() * counter | 0;\n    counter--;\n    swap(array2, counter, index);\n    swap(array22, counter, index);\n  }\n}\nfunction clamp(min7, x, max7) {\n  return Math.max(min7, Math.min(x, max7));\n}\nfunction nearestLargerEven(val) {\n  return val % 2 === 0 ? val : val + 1;\n}\nfunction swap(object, left, right) {\n  const temp = object[left];\n  object[left] = object[right];\n  object[right] = temp;\n}\nfunction sum(arr) {\n  let sum7 = 0;\n  for (let i2 = 0; i2 < arr.length; i2++) {\n    sum7 += arr[i2];\n  }\n  return sum7;\n}\nfunction randUniform(a, b) {\n  const r2 = Math.random();\n  return b * r2 + (1 - r2) * a;\n}\nfunction distSquared(a, b) {\n  let result = 0;\n  for (let i2 = 0; i2 < a.length; i2++) {\n    const diff = Number(a[i2]) - Number(b[i2]);\n    result += diff * diff;\n  }\n  return result;\n}\nfunction assert(expr, msg) {\n  if (!expr) {\n    throw new Error(typeof msg === \"string\" ? msg : msg());\n  }\n}\nfunction assertShapesMatch(shapeA, shapeB, errorMessagePrefix = \"\") {\n  assert(arraysEqual(shapeA, shapeB), () => errorMessagePrefix + ` Shapes ${shapeA} and ${shapeB} must match`);\n}\nfunction assertNonNull(a) {\n  assert(a != null, () => `The input to the tensor constructor must be a non-null value.`);\n}\nfunction flatten(arr, result = [], skipTypedArray = false) {\n  if (result == null) {\n    result = [];\n  }\n  if (Array.isArray(arr) || isTypedArray(arr) && !skipTypedArray) {\n    for (let i2 = 0; i2 < arr.length; ++i2) {\n      flatten(arr[i2], result, skipTypedArray);\n    }\n  } else {\n    result.push(arr);\n  }\n  return result;\n}\nfunction sizeFromShape(shape) {\n  if (shape.length === 0) {\n    return 1;\n  }\n  let size = shape[0];\n  for (let i2 = 1; i2 < shape.length; i2++) {\n    size *= shape[i2];\n  }\n  return size;\n}\nfunction isScalarShape(shape) {\n  return shape.length === 0;\n}\nfunction arraysEqual(n1, n2) {\n  if (n1 === n2) {\n    return true;\n  }\n  if (n1 == null || n2 == null) {\n    return false;\n  }\n  if (n1.length !== n2.length) {\n    return false;\n  }\n  for (let i2 = 0; i2 < n1.length; i2++) {\n    if (n1[i2] !== n2[i2]) {\n      return false;\n    }\n  }\n  return true;\n}\nfunction isInt(a) {\n  return a % 1 === 0;\n}\nfunction tanh(x) {\n  if (Math.tanh != null) {\n    return Math.tanh(x);\n  }\n  if (x === Infinity) {\n    return 1;\n  } else if (x === -Infinity) {\n    return -1;\n  } else {\n    const e2x = Math.exp(2 * x);\n    return (e2x - 1) / (e2x + 1);\n  }\n}\nfunction sizeToSquarishShape(size) {\n  const width = Math.ceil(Math.sqrt(size));\n  return [width, Math.ceil(size / width)];\n}\nfunction createShuffledIndices(n2) {\n  const shuffledIndices = new Uint32Array(n2);\n  for (let i2 = 0; i2 < n2; ++i2) {\n    shuffledIndices[i2] = i2;\n  }\n  shuffle(shuffledIndices);\n  return shuffledIndices;\n}\nfunction rightPad(a, size) {\n  if (size <= a.length) {\n    return a;\n  }\n  return a + \" \".repeat(size - a.length);\n}\nfunction repeatedTry(checkFn, delayFn = (counter) => 0, maxCounter) {\n  return new Promise((resolve, reject) => {\n    let tryCount = 0;\n    const tryFn = () => {\n      if (checkFn()) {\n        resolve();\n        return;\n      }\n      tryCount++;\n      const nextBackoff = delayFn(tryCount);\n      if (maxCounter != null && tryCount >= maxCounter) {\n        reject();\n        return;\n      }\n      setTimeout(tryFn, nextBackoff);\n    };\n    tryFn();\n  });\n}\nfunction inferFromImplicitShape(shape, size) {\n  let shapeProd = 1;\n  let implicitIdx = -1;\n  for (let i2 = 0; i2 < shape.length; ++i2) {\n    if (shape[i2] >= 0) {\n      shapeProd *= shape[i2];\n    } else if (shape[i2] === -1) {\n      if (implicitIdx !== -1) {\n        throw Error(`Shapes can only have 1 implicit size. Found -1 at dim ${implicitIdx} and dim ${i2}`);\n      }\n      implicitIdx = i2;\n    } else if (shape[i2] < 0) {\n      throw Error(`Shapes can not be < 0. Found ${shape[i2]} at dim ${i2}`);\n    }\n  }\n  if (implicitIdx === -1) {\n    if (size > 0 && size !== shapeProd) {\n      throw Error(`Size(${size}) must match the product of shape ${shape}`);\n    }\n    return shape;\n  }\n  if (shapeProd === 0) {\n    throw Error(`Cannot infer the missing size in [${shape}] when there are 0 elements`);\n  }\n  if (size % shapeProd !== 0) {\n    throw Error(`The implicit shape can't be a fractional number. Got ${size} / ${shapeProd}`);\n  }\n  const newShape = shape.slice();\n  newShape[implicitIdx] = size / shapeProd;\n  return newShape;\n}\nfunction parseAxisParam(axis, shape) {\n  const rank = shape.length;\n  axis = axis == null ? shape.map((s2, i2) => i2) : [].concat(axis);\n  assert(axis.every((ax) => ax >= -rank && ax < rank), () => `All values in axis param must be in range [-${rank}, ${rank}) but got axis ${axis}`);\n  assert(axis.every((ax) => isInt(ax)), () => `All values in axis param must be integers but got axis ${axis}`);\n  return axis.map((a) => a < 0 ? rank + a : a);\n}\nfunction squeezeShape(shape, axis) {\n  const newShape = [];\n  const keptDims = [];\n  const isEmptyArray = axis != null && Array.isArray(axis) && axis.length === 0;\n  const axes = axis == null || isEmptyArray ? null : parseAxisParam(axis, shape).sort();\n  let j = 0;\n  for (let i2 = 0; i2 < shape.length; ++i2) {\n    if (axes != null) {\n      if (axes[j] === i2 && shape[i2] !== 1) {\n        throw new Error(`Can't squeeze axis ${i2} since its dim '${shape[i2]}' is not 1`);\n      }\n      if ((axes[j] == null || axes[j] > i2) && shape[i2] === 1) {\n        newShape.push(shape[i2]);\n        keptDims.push(i2);\n      }\n      if (axes[j] <= i2) {\n        j++;\n      }\n    }\n    if (shape[i2] !== 1) {\n      newShape.push(shape[i2]);\n      keptDims.push(i2);\n    }\n  }\n  return { newShape, keptDims };\n}\nfunction getTypedArrayFromDType(dtype, size) {\n  let values = null;\n  if (dtype == null || dtype === \"float32\") {\n    values = new Float32Array(size);\n  } else if (dtype === \"int32\") {\n    values = new Int32Array(size);\n  } else if (dtype === \"bool\") {\n    values = new Uint8Array(size);\n  } else {\n    throw new Error(`Unknown data type ${dtype}`);\n  }\n  return values;\n}\nfunction getArrayFromDType(dtype, size) {\n  let values = null;\n  if (dtype == null || dtype === \"float32\") {\n    values = new Float32Array(size);\n  } else if (dtype === \"int32\") {\n    values = new Int32Array(size);\n  } else if (dtype === \"bool\") {\n    values = new Uint8Array(size);\n  } else if (dtype === \"string\") {\n    values = new Array(size);\n  } else {\n    throw new Error(`Unknown data type ${dtype}`);\n  }\n  return values;\n}\nfunction checkConversionForErrors(vals, dtype) {\n  for (let i2 = 0; i2 < vals.length; i2++) {\n    const num = vals[i2];\n    if (isNaN(num) || !isFinite(num)) {\n      throw Error(`A tensor of type ${dtype} being uploaded contains ${num}.`);\n    }\n  }\n}\nfunction isValidDtype(dtype) {\n  return dtype === \"bool\" || dtype === \"complex64\" || dtype === \"float32\" || dtype === \"int32\" || dtype === \"string\";\n}\nfunction hasEncodingLoss(oldType, newType) {\n  if (newType === \"complex64\") {\n    return false;\n  }\n  if (newType === \"float32\" && oldType !== \"complex64\") {\n    return false;\n  }\n  if (newType === \"int32\" && oldType !== \"float32\" && oldType !== \"complex64\") {\n    return false;\n  }\n  if (newType === \"bool\" && oldType === \"bool\") {\n    return false;\n  }\n  return true;\n}\nfunction isTypedArray(a) {\n  return a instanceof Float32Array || a instanceof Int32Array || a instanceof Uint8Array || a instanceof Uint8ClampedArray;\n}\nfunction bytesPerElement(dtype) {\n  if (dtype === \"float32\" || dtype === \"int32\") {\n    return 4;\n  } else if (dtype === \"complex64\") {\n    return 8;\n  } else if (dtype === \"bool\") {\n    return 1;\n  } else {\n    throw new Error(`Unknown dtype ${dtype}`);\n  }\n}\nfunction bytesFromStringArray(arr) {\n  if (arr == null) {\n    return 0;\n  }\n  let bytes = 0;\n  arr.forEach((x) => bytes += x.length);\n  return bytes;\n}\nfunction isString(value) {\n  return typeof value === \"string\" || value instanceof String;\n}\nfunction isBoolean(value) {\n  return typeof value === \"boolean\";\n}\nfunction isNumber(value) {\n  return typeof value === \"number\";\n}\nfunction inferDtype(values) {\n  if (Array.isArray(values)) {\n    return inferDtype(values[0]);\n  }\n  if (values instanceof Float32Array) {\n    return \"float32\";\n  } else if (values instanceof Int32Array || values instanceof Uint8Array || values instanceof Uint8ClampedArray) {\n    return \"int32\";\n  } else if (isNumber(values)) {\n    return \"float32\";\n  } else if (isString(values)) {\n    return \"string\";\n  } else if (isBoolean(values)) {\n    return \"bool\";\n  }\n  return \"float32\";\n}\nfunction isFunction(f) {\n  return !!(f && f.constructor && f.call && f.apply);\n}\nfunction nearestDivisor(size, start) {\n  for (let i2 = start; i2 < size; ++i2) {\n    if (size % i2 === 0) {\n      return i2;\n    }\n  }\n  return size;\n}\nfunction computeStrides(shape) {\n  const rank = shape.length;\n  if (rank < 2) {\n    return [];\n  }\n  const strides = new Array(rank - 1);\n  strides[rank - 2] = shape[rank - 1];\n  for (let i2 = rank - 3; i2 >= 0; --i2) {\n    strides[i2] = strides[i2 + 1] * shape[i2 + 1];\n  }\n  return strides;\n}\nfunction createNestedArray(offset, shape, a, isComplex = false) {\n  const ret = new Array();\n  if (shape.length === 1) {\n    const d = shape[0] * (isComplex ? 2 : 1);\n    for (let i2 = 0; i2 < d; i2++) {\n      ret[i2] = a[offset + i2];\n    }\n  } else {\n    const d = shape[0];\n    const rest = shape.slice(1);\n    const len = rest.reduce((acc, c) => acc * c) * (isComplex ? 2 : 1);\n    for (let i2 = 0; i2 < d; i2++) {\n      ret[i2] = createNestedArray(offset + i2 * len, rest, a, isComplex);\n    }\n  }\n  return ret;\n}\nfunction toNestedArray(shape, a, isComplex = false) {\n  if (shape.length === 0) {\n    return a[0];\n  }\n  const size = shape.reduce((acc, c) => acc * c) * (isComplex ? 2 : 1);\n  if (size === 0) {\n    return [];\n  }\n  if (size !== a.length) {\n    throw new Error(`[${shape}] does not match the input size ${a.length}${isComplex ? \" for a complex tensor\" : \"\"}.`);\n  }\n  return createNestedArray(0, shape, a, isComplex);\n}\nfunction makeOnesTypedArray(size, dtype) {\n  const array2 = makeZerosTypedArray(size, dtype);\n  for (let i2 = 0; i2 < array2.length; i2++) {\n    array2[i2] = 1;\n  }\n  return array2;\n}\nfunction makeZerosTypedArray(size, dtype) {\n  if (dtype == null || dtype === \"float32\" || dtype === \"complex64\") {\n    return new Float32Array(size);\n  } else if (dtype === \"int32\") {\n    return new Int32Array(size);\n  } else if (dtype === \"bool\") {\n    return new Uint8Array(size);\n  } else {\n    throw new Error(`Unknown data type ${dtype}`);\n  }\n}\nfunction makeZerosNestedTypedArray(shape, dtype) {\n  const size = shape.reduce((prev, curr) => prev * curr, 1);\n  if (dtype == null || dtype === \"float32\") {\n    return toNestedArray(shape, new Float32Array(size));\n  } else if (dtype === \"int32\") {\n    return toNestedArray(shape, new Int32Array(size));\n  } else if (dtype === \"bool\") {\n    return toNestedArray(shape, new Uint8Array(size));\n  } else {\n    throw new Error(`Unknown data type ${dtype}`);\n  }\n}\nfunction assertNonNegativeIntegerDimensions(shape) {\n  shape.forEach((dimSize) => {\n    assert(Number.isInteger(dimSize) && dimSize >= 0, () => `Tensor must have a shape comprised of positive integers but got shape [${shape}].`);\n  });\n}\nfunction locToIndex(locs, rank, strides) {\n  if (rank === 0) {\n    return 0;\n  } else if (rank === 1) {\n    return locs[0];\n  }\n  let index = locs[locs.length - 1];\n  for (let i2 = 0; i2 < locs.length - 1; ++i2) {\n    index += strides[i2] * locs[i2];\n  }\n  return index;\n}\nfunction indexToLoc(index, rank, strides) {\n  if (rank === 0) {\n    return [];\n  } else if (rank === 1) {\n    return [index];\n  }\n  const locs = new Array(rank);\n  for (let i2 = 0; i2 < locs.length - 1; ++i2) {\n    locs[i2] = Math.floor(index / strides[i2]);\n    index -= locs[i2] * strides[i2];\n  }\n  locs[locs.length - 1] = index;\n  return locs;\n}\nfunction isPromise(object) {\n  return object && object.then && typeof object.then === \"function\";\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/environment.js\nvar TENSORFLOWJS_FLAGS_PREFIX = \"tfjsflags\";\nvar Environment = class {\n  constructor(global2) {\n    this.global = global2;\n    this.flags = {};\n    this.flagRegistry = {};\n    this.urlFlags = {};\n    this.getQueryParams = getQueryParams;\n    this.populateURLFlags();\n  }\n  setPlatform(platformName, platform) {\n    if (this.platform != null) {\n      if (!(env().getBool(\"IS_TEST\") || env().getBool(\"PROD\"))) {\n        console.warn(`Platform ${this.platformName} has already been set. Overwriting the platform with ${platformName}.`);\n      }\n    }\n    this.platformName = platformName;\n    this.platform = platform;\n  }\n  registerFlag(flagName, evaluationFn, setHook) {\n    this.flagRegistry[flagName] = { evaluationFn, setHook };\n    if (this.urlFlags[flagName] != null) {\n      const flagValue = this.urlFlags[flagName];\n      if (!(env().getBool(\"IS_TEST\") || env().getBool(\"PROD\"))) {\n        console.warn(`Setting feature override from URL ${flagName}: ${flagValue}.`);\n      }\n      this.set(flagName, flagValue);\n    }\n  }\n  async getAsync(flagName) {\n    if (flagName in this.flags) {\n      return this.flags[flagName];\n    }\n    this.flags[flagName] = await this.evaluateFlag(flagName);\n    return this.flags[flagName];\n  }\n  get(flagName) {\n    if (flagName in this.flags) {\n      return this.flags[flagName];\n    }\n    const flagValue = this.evaluateFlag(flagName);\n    if (isPromise(flagValue)) {\n      throw new Error(`Flag ${flagName} cannot be synchronously evaluated. Please use getAsync() instead.`);\n    }\n    this.flags[flagName] = flagValue;\n    return this.flags[flagName];\n  }\n  getNumber(flagName) {\n    return this.get(flagName);\n  }\n  getBool(flagName) {\n    return this.get(flagName);\n  }\n  getFlags() {\n    return this.flags;\n  }\n  get features() {\n    return this.flags;\n  }\n  set(flagName, value) {\n    if (this.flagRegistry[flagName] == null) {\n      throw new Error(`Cannot set flag ${flagName} as it has not been registered.`);\n    }\n    this.flags[flagName] = value;\n    if (this.flagRegistry[flagName].setHook != null) {\n      this.flagRegistry[flagName].setHook(value);\n    }\n  }\n  evaluateFlag(flagName) {\n    if (this.flagRegistry[flagName] == null) {\n      throw new Error(`Cannot evaluate flag '${flagName}': no evaluation function found.`);\n    }\n    return this.flagRegistry[flagName].evaluationFn();\n  }\n  setFlags(flags) {\n    this.flags = Object.assign({}, flags);\n  }\n  reset() {\n    this.flags = {};\n    this.urlFlags = {};\n    this.populateURLFlags();\n  }\n  populateURLFlags() {\n    if (typeof this.global === \"undefined\" || typeof this.global.location === \"undefined\" || typeof this.global.location.search === \"undefined\") {\n      return;\n    }\n    const urlParams = this.getQueryParams(this.global.location.search);\n    if (TENSORFLOWJS_FLAGS_PREFIX in urlParams) {\n      const keyValues = urlParams[TENSORFLOWJS_FLAGS_PREFIX].split(\",\");\n      keyValues.forEach((keyValue) => {\n        const [key, value] = keyValue.split(\":\");\n        this.urlFlags[key] = parseValue(key, value);\n      });\n    }\n  }\n};\nfunction getQueryParams(queryString) {\n  const params = {};\n  queryString.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g, (s2, ...t2) => {\n    decodeParam(params, t2[0], t2[1]);\n    return t2.join(\"=\");\n  });\n  return params;\n}\nfunction decodeParam(params, name, value) {\n  params[decodeURIComponent(name)] = decodeURIComponent(value || \"\");\n}\nfunction parseValue(flagName, value) {\n  value = value.toLowerCase();\n  if (value === \"true\" || value === \"false\") {\n    return value === \"true\";\n  } else if (`${+value}` === value) {\n    return +value;\n  }\n  throw new Error(`Could not parse value flag value ${value} for flag ${flagName}.`);\n}\nfunction env() {\n  return ENV;\n}\nvar ENV = null;\nfunction setEnvironmentGlobal(environment) {\n  ENV = environment;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/global_util.js\nvar globalNameSpace;\nfunction getGlobalNamespace() {\n  if (globalNameSpace == null) {\n    let ns;\n    if (typeof window !== \"undefined\") {\n      ns = window;\n    } else if (typeof global !== \"undefined\") {\n      ns = global;\n    } else if (typeof process !== \"undefined\") {\n      ns = process;\n    } else if (typeof self !== \"undefined\") {\n      ns = self;\n    } else {\n      throw new Error(\"Could not find a global object\");\n    }\n    globalNameSpace = ns;\n  }\n  return globalNameSpace;\n}\nfunction getGlobalMap() {\n  const ns = getGlobalNamespace();\n  if (ns._tfGlobals == null) {\n    ns._tfGlobals = /* @__PURE__ */ new Map();\n  }\n  return ns._tfGlobals;\n}\nfunction getGlobal(key, init2) {\n  const globalMap = getGlobalMap();\n  if (globalMap.has(key)) {\n    return globalMap.get(key);\n  } else {\n    const singleton = init2();\n    globalMap.set(key, singleton);\n    return globalMap.get(key);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/kernel_names.js\nvar Abs = \"Abs\";\nvar Acos = \"Acos\";\nvar Acosh = \"Acosh\";\nvar Add = \"Add\";\nvar AddN = \"AddN\";\nvar All = \"All\";\nvar Any = \"Any\";\nvar ArgMax = \"ArgMax\";\nvar ArgMin = \"ArgMin\";\nvar Asin = \"Asin\";\nvar Asinh = \"Asinh\";\nvar Atan = \"Atan\";\nvar Atanh = \"Atanh\";\nvar Atan2 = \"Atan2\";\nvar AvgPool = \"AvgPool\";\nvar AvgPoolGrad = \"AvgPoolGrad\";\nvar AvgPool3D = \"AvgPool3D\";\nvar AvgPool3DGrad = \"AvgPool3DGrad\";\nvar BatchMatMul = \"BatchMatMul\";\nvar BatchToSpaceND = \"BatchToSpaceND\";\nvar Bincount = \"Bincount\";\nvar BroadcastTo = \"BroadcastTo\";\nvar BroadcastArgs = \"BroadcastArgs\";\nvar Cast = \"Cast\";\nvar Ceil = \"Ceil\";\nvar ClipByValue = \"ClipByValue\";\nvar Complex = \"Complex\";\nvar ComplexAbs = \"ComplexAbs\";\nvar Concat = \"Concat\";\nvar Conv2D = \"Conv2D\";\nvar Conv2DBackpropFilter = \"Conv2DBackpropFilter\";\nvar Conv2DBackpropInput = \"Conv2DBackpropInput\";\nvar Conv3D = \"Conv3D\";\nvar Conv3DBackpropFilterV2 = \"Conv3DBackpropFilterV2\";\nvar Conv3DBackpropInputV2 = \"Conv3DBackpropInputV2\";\nvar Cos = \"Cos\";\nvar Cosh = \"Cosh\";\nvar Cumprod = \"Cumprod\";\nvar Cumsum = \"Cumsum\";\nvar CropAndResize = \"CropAndResize\";\nvar DenseBincount = \"DenseBincount\";\nvar DepthToSpace = \"DepthToSpace\";\nvar DepthwiseConv2dNative = \"DepthwiseConv2dNative\";\nvar DepthwiseConv2dNativeBackpropFilter = \"DepthwiseConv2dNativeBackpropFilter\";\nvar DepthwiseConv2dNativeBackpropInput = \"DepthwiseConv2dNativeBackpropInput\";\nvar Diag = \"Diag\";\nvar Dilation2D = \"Dilation2D\";\nvar Dilation2DBackpropInput = \"Dilation2DBackpropInput\";\nvar Dilation2DBackpropFilter = \"Dilation2DBackpropFilter\";\nvar RealDiv = \"RealDiv\";\nvar Einsum = \"Einsum\";\nvar Elu = \"Elu\";\nvar EluGrad = \"EluGrad\";\nvar Erf = \"Erf\";\nvar Equal = \"Equal\";\nvar Exp = \"Exp\";\nvar ExpandDims = \"ExpandDims\";\nvar Expm1 = \"Expm1\";\nvar FFT = \"FFT\";\nvar Fill = \"Fill\";\nvar FlipLeftRight = \"FlipLeftRight\";\nvar Floor = \"Floor\";\nvar FloorDiv = \"FloorDiv\";\nvar FusedBatchNorm = \"FusedBatchNorm\";\nvar GatherV2 = \"GatherV2\";\nvar GatherNd = \"GatherNd\";\nvar Greater = \"Greater\";\nvar GreaterEqual = \"GreaterEqual\";\nvar Identity = \"Identity\";\nvar IFFT = \"IFFT\";\nvar Imag = \"Imag\";\nvar IsFinite = \"IsFinite\";\nvar IsInf = \"IsInf\";\nvar IsNan = \"IsNan\";\nvar LeakyRelu = \"LeakyRelu\";\nvar Less = \"Less\";\nvar LessEqual = \"LessEqual\";\nvar LinSpace = \"LinSpace\";\nvar Log = \"Log\";\nvar Log1p = \"Log1p\";\nvar LogicalAnd = \"LogicalAnd\";\nvar LogicalNot = \"LogicalNot\";\nvar LogicalOr = \"LogicalOr\";\nvar LogicalXor = \"LogicalXor\";\nvar LogSoftmax = \"LogSoftmax\";\nvar LowerBound = \"LowerBound\";\nvar LRN = \"LRN\";\nvar LRNGrad = \"LRNGrad\";\nvar Max = \"Max\";\nvar Maximum = \"Maximum\";\nvar MaxPool = \"MaxPool\";\nvar MaxPoolGrad = \"MaxPoolGrad\";\nvar MaxPool3D = \"MaxPool3D\";\nvar MaxPool3DGrad = \"MaxPool3DGrad\";\nvar MaxPoolWithArgmax = \"MaxPoolWithArgmax\";\nvar Mean = \"Mean\";\nvar Min = \"Min\";\nvar Minimum = \"Minimum\";\nvar MirrorPad = \"MirrorPad\";\nvar Mod = \"Mod\";\nvar Multinomial = \"Multinomial\";\nvar Multiply = \"Multiply\";\nvar Neg = \"Neg\";\nvar NotEqual = \"NotEqual\";\nvar NonMaxSuppressionV3 = \"NonMaxSuppressionV3\";\nvar NonMaxSuppressionV4 = \"NonMaxSuppressionV4\";\nvar NonMaxSuppressionV5 = \"NonMaxSuppressionV5\";\nvar OnesLike = \"OnesLike\";\nvar OneHot = \"OneHot\";\nvar Pack = \"Pack\";\nvar PadV2 = \"PadV2\";\nvar Pool = \"Pool\";\nvar Pow = \"Pow\";\nvar Prelu = \"Prelu\";\nvar Prod = \"Prod\";\nvar Range = \"Range\";\nvar Real = \"Real\";\nvar Reciprocal = \"Reciprocal\";\nvar Relu = \"Relu\";\nvar Reshape = \"Reshape\";\nvar ResizeNearestNeighbor = \"ResizeNearestNeighbor\";\nvar ResizeNearestNeighborGrad = \"ResizeNearestNeighborGrad\";\nvar ResizeBilinear = \"ResizeBilinear\";\nvar ResizeBilinearGrad = \"ResizeBilinearGrad\";\nvar Relu6 = \"Relu6\";\nvar Reverse = \"Reverse\";\nvar Round = \"Round\";\nvar Rsqrt = \"Rsqrt\";\nvar ScatterNd = \"ScatterNd\";\nvar SearchSorted = \"SearchSorted\";\nvar Select = \"Select\";\nvar Selu = \"Selu\";\nvar Slice = \"Slice\";\nvar Sin = \"Sin\";\nvar Sinh = \"Sinh\";\nvar Sign = \"Sign\";\nvar Sigmoid = \"Sigmoid\";\nvar Softplus = \"Softplus\";\nvar Sqrt = \"Sqrt\";\nvar Sum = \"Sum\";\nvar SpaceToBatchND = \"SpaceToBatchND\";\nvar SplitV = \"SplitV\";\nvar Softmax = \"Softmax\";\nvar SparseFillEmptyRows = \"SparseFillEmptyRows\";\nvar SparseReshape = \"SparseReshape\";\nvar SparseSegmentMean = \"SparseSegmentMean\";\nvar SparseSegmentSum = \"SparseSegmentSum\";\nvar SparseToDense = \"SparseToDense\";\nvar SquaredDifference = \"SquaredDifference\";\nvar Square = \"Square\";\nvar StridedSlice = \"StridedSlice\";\nvar StringNGrams = \"StringNGrams\";\nvar StringSplit = \"StringSplit\";\nvar StringToHashBucketFast = \"StringToHashBucketFast\";\nvar Sub = \"Sub\";\nvar Tan = \"Tan\";\nvar Tanh = \"Tanh\";\nvar Tile = \"Tile\";\nvar TopK = \"TopK\";\nvar Transform = \"Transform\";\nvar Transpose = \"Transpose\";\nvar Unique = \"Unique\";\nvar Unpack = \"Unpack\";\nvar UnsortedSegmentSum = \"UnsortedSegmentSum\";\nvar UpperBound = \"UpperBound\";\nvar ZerosLike = \"ZerosLike\";\nvar Step = \"Step\";\nvar FromPixels = \"FromPixels\";\nvar RotateWithOffset = \"RotateWithOffset\";\nvar _FusedMatMul = \"_FusedMatMul\";\nvar FusedConv2D = \"FusedConv2D\";\nvar FusedDepthwiseConv2D = \"FusedDepthwiseConv2D\";\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/log.js\nfunction warn(...msg) {\n  if (!(env().getBool(\"IS_TEST\") || env().getBool(\"PROD\"))) {\n    console.warn(...msg);\n  }\n}\nfunction log(...msg) {\n  if (!(env().getBool(\"IS_TEST\") || env().getBool(\"PROD\"))) {\n    console.log(...msg);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/kernel_registry.js\nvar kernelRegistry = getGlobal(\"kernelRegistry\", () => /* @__PURE__ */ new Map());\nvar gradRegistry = getGlobal(\"gradRegistry\", () => /* @__PURE__ */ new Map());\nfunction getKernel(kernelName, backendName) {\n  const key = makeKey(kernelName, backendName);\n  return kernelRegistry.get(key);\n}\nfunction getGradient(kernelName) {\n  return gradRegistry.get(kernelName);\n}\nfunction getKernelsForBackend(backendName) {\n  const it = kernelRegistry.entries();\n  const result = [];\n  while (true) {\n    const { done, value } = it.next();\n    if (done) {\n      break;\n    }\n    const [key, config] = value;\n    const [backend2] = key.split(\"_\");\n    if (backend2 === backendName) {\n      result.push(config);\n    }\n  }\n  return result;\n}\nfunction registerKernel(config) {\n  const { kernelName, backendName } = config;\n  const key = makeKey(kernelName, backendName);\n  if (kernelRegistry.has(key)) {\n    warn(`The kernel '${kernelName}' for backend '${backendName}' is already registered`);\n  }\n  kernelRegistry.set(key, config);\n}\nfunction registerGradient(config) {\n  const { kernelName } = config;\n  if (gradRegistry.has(kernelName)) {\n    if (env().getBool(\"DEBUG\")) {\n      warn(`Overriding the gradient for '${kernelName}'`);\n    }\n  }\n  gradRegistry.set(kernelName, config);\n}\nfunction unregisterKernel(kernelName, backendName) {\n  const key = makeKey(kernelName, backendName);\n  if (!kernelRegistry.has(key)) {\n    throw new Error(`The kernel '${kernelName}' for backend '${backendName}' is not registered`);\n  }\n  kernelRegistry.delete(key);\n}\nfunction unregisterGradient(kernelName) {\n  if (!gradRegistry.has(kernelName)) {\n    throw new Error(`The gradient '${kernelName}' for backend is not registered`);\n  }\n  gradRegistry.delete(kernelName);\n}\nfunction copyRegisteredKernels(registeredBackendName, newBackendName) {\n  const kernels = getKernelsForBackend(registeredBackendName);\n  kernels.forEach((kernelConfig) => {\n    const newKernelConfig = Object.assign({}, kernelConfig, { backendName: newBackendName });\n    registerKernel(newKernelConfig);\n  });\n}\nfunction makeKey(kernelName, backendName) {\n  return `${backendName}_${kernelName}`;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/util.js\nvar util_exports = {};\n__export(util_exports, {\n  arraysEqual: () => arraysEqual,\n  assert: () => assert,\n  assertNonNegativeIntegerDimensions: () => assertNonNegativeIntegerDimensions,\n  assertNonNull: () => assertNonNull,\n  assertShapesMatch: () => assertShapesMatch,\n  bytesFromStringArray: () => bytesFromStringArray,\n  bytesPerElement: () => bytesPerElement,\n  checkConversionForErrors: () => checkConversionForErrors,\n  clamp: () => clamp,\n  computeStrides: () => computeStrides,\n  createScalarValue: () => createScalarValue,\n  createShuffledIndices: () => createShuffledIndices,\n  decodeString: () => decodeString,\n  distSquared: () => distSquared,\n  encodeString: () => encodeString,\n  fetch: () => fetch3,\n  fingerPrint64: () => fingerPrint64,\n  flatten: () => flatten,\n  getArrayFromDType: () => getArrayFromDType,\n  getTypedArrayFromDType: () => getTypedArrayFromDType,\n  hasEncodingLoss: () => hasEncodingLoss,\n  hexToLong: () => hexToLong,\n  indexToLoc: () => indexToLoc,\n  inferDtype: () => inferDtype,\n  inferFromImplicitShape: () => inferFromImplicitShape,\n  isBoolean: () => isBoolean,\n  isFunction: () => isFunction,\n  isInt: () => isInt,\n  isNumber: () => isNumber,\n  isPromise: () => isPromise,\n  isScalarShape: () => isScalarShape,\n  isString: () => isString,\n  isTypedArray: () => isTypedArray,\n  isValidDtype: () => isValidDtype,\n  locToIndex: () => locToIndex,\n  makeOnesTypedArray: () => makeOnesTypedArray,\n  makeZerosNestedTypedArray: () => makeZerosNestedTypedArray,\n  makeZerosTypedArray: () => makeZerosTypedArray,\n  nearestDivisor: () => nearestDivisor,\n  nearestLargerEven: () => nearestLargerEven,\n  now: () => now,\n  parseAxisParam: () => parseAxisParam,\n  randUniform: () => randUniform,\n  repeatedTry: () => repeatedTry,\n  rightPad: () => rightPad,\n  shuffle: () => shuffle,\n  shuffleCombo: () => shuffleCombo,\n  sizeFromShape: () => sizeFromShape,\n  sizeToSquarishShape: () => sizeToSquarishShape,\n  squeezeShape: () => squeezeShape,\n  sum: () => sum,\n  swap: () => swap,\n  tanh: () => tanh,\n  toNestedArray: () => toNestedArray,\n  toTypedArray: () => toTypedArray\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/hash_util.js\nvar LongExports = __toESM(require_long());\nvar Long = LongExports.default || LongExports;\nfunction hexToLong(hex) {\n  return Long.fromString(hex, true, 16);\n}\nvar k0 = hexToLong(\"c3a5c85c97cb3127\");\nvar k1 = hexToLong(\"b492b66fbe98f273\");\nvar k2 = hexToLong(\"9ae16a3b2f90404f\");\nfunction shiftMix(val) {\n  return val.xor(val.shru(47));\n}\nfunction fetch2(s2, offset, numBytes) {\n  const bytes = s2.slice(offset, offset + numBytes);\n  return Long.fromBytes(Array.from(bytes), true, true);\n}\nfunction fetch64(s2, offset) {\n  return fetch2(s2, offset, 8);\n}\nfunction fetch32(s2, offset) {\n  return fetch2(s2, offset, 4);\n}\nfunction rotate64(val, shift) {\n  return shift === 0 ? val : val.shru(shift).or(val.shl(64 - shift));\n}\nfunction hashLen16(u, v, mul2 = hexToLong(\"9ddfea08eb382d69\")) {\n  let a = u.xor(v).mul(mul2);\n  a = a.xor(a.shru(47));\n  let b = v.xor(a).mul(mul2);\n  b = b.xor(b.shru(47));\n  b = b.mul(mul2);\n  return b;\n}\nfunction weakHashLen32WithSeeds(w, x, y, z, a, b) {\n  a = a.add(w);\n  b = rotate64(b.add(a).add(z), 21);\n  const c = a;\n  a = a.add(x);\n  a = a.add(y);\n  b = b.add(rotate64(a, 44));\n  return [a.add(z), b.add(c)];\n}\nfunction weakHashLen32WithSeedsStr(s2, offset, a, b) {\n  return weakHashLen32WithSeeds(fetch64(s2, offset), fetch64(s2, offset + 8), fetch64(s2, offset + 16), fetch64(s2, offset + 24), a, b);\n}\nfunction hashLen0to16(s2, len = s2.length) {\n  if (len >= 8) {\n    const mul2 = k2.add(len * 2);\n    const a = fetch64(s2, 0).add(k2);\n    const b = fetch64(s2, len - 8);\n    const c = rotate64(b, 37).mul(mul2).add(a);\n    const d = rotate64(a, 25).add(b).mul(mul2);\n    return hashLen16(c, d, mul2);\n  }\n  if (len >= 4) {\n    const mul2 = k2.add(len * 2);\n    const a = fetch32(s2, 0);\n    return hashLen16(a.shl(3).add(len), fetch32(s2, len - 4), mul2);\n  }\n  if (len > 0) {\n    const a = s2[0];\n    const b = s2[len >> 1];\n    const c = s2[len - 1];\n    const y = a + (b << 8);\n    const z = len + (c << 2);\n    return shiftMix(k2.mul(y).xor(k0.mul(z))).mul(k2);\n  }\n  return k2;\n}\nfunction hashLen17to32(s2, len = s2.length) {\n  const mul2 = k2.add(len * 2);\n  const a = fetch64(s2, 0).mul(k1);\n  const b = fetch64(s2, 8);\n  const c = fetch64(s2, len - 8).mul(mul2);\n  const d = fetch64(s2, len - 16).mul(k2);\n  return hashLen16(rotate64(a.add(b), 43).add(rotate64(c, 30)).add(d), a.add(rotate64(b.add(k2), 18)).add(c), mul2);\n}\nfunction hashLen33to64(s2, len = s2.length) {\n  const mul2 = k2.add(len * 2);\n  const a = fetch64(s2, 0).mul(k2);\n  const b = fetch64(s2, 8);\n  const c = fetch64(s2, len - 8).mul(mul2);\n  const d = fetch64(s2, len - 16).mul(k2);\n  const y = rotate64(a.add(b), 43).add(rotate64(c, 30)).add(d);\n  const z = hashLen16(y, a.add(rotate64(b.add(k2), 18)).add(c), mul2);\n  const e2 = fetch64(s2, 16).mul(mul2);\n  const f = fetch64(s2, 24);\n  const g = y.add(fetch64(s2, len - 32)).mul(mul2);\n  const h = z.add(fetch64(s2, len - 24)).mul(mul2);\n  return hashLen16(rotate64(e2.add(f), 43).add(rotate64(g, 30)).add(h), e2.add(rotate64(f.add(a), 18)).add(g), mul2);\n}\nfunction fingerPrint64(s2, len = s2.length) {\n  const seed = Long.fromNumber(81, true);\n  if (len <= 32) {\n    if (len <= 16) {\n      return hashLen0to16(s2, len);\n    } else {\n      return hashLen17to32(s2, len);\n    }\n  } else if (len <= 64) {\n    return hashLen33to64(s2, len);\n  }\n  let x = seed;\n  let y = seed.mul(k1).add(113);\n  let z = shiftMix(y.mul(k2).add(113)).mul(k2);\n  let v = [Long.UZERO, Long.UZERO];\n  let w = [Long.UZERO, Long.UZERO];\n  x = x.mul(k2).add(fetch64(s2, 0));\n  let offset = 0;\n  const end = (len - 1 >> 6) * 64;\n  const last64 = end + (len - 1 & 63) - 63;\n  do {\n    x = rotate64(x.add(y).add(v[0]).add(fetch64(s2, offset + 8)), 37).mul(k1);\n    y = rotate64(y.add(v[1]).add(fetch64(s2, offset + 48)), 42).mul(k1);\n    x = x.xor(w[1]);\n    y = y.add(v[0]).add(fetch64(s2, offset + 40));\n    z = rotate64(z.add(w[0]), 33).mul(k1);\n    v = weakHashLen32WithSeedsStr(s2, offset, v[1].mul(k1), x.add(w[0]));\n    w = weakHashLen32WithSeedsStr(s2, offset + 32, z.add(w[1]), y.add(fetch64(s2, offset + 16)));\n    [z, x] = [x, z];\n    offset += 64;\n  } while (offset !== end);\n  const mul2 = k1.add(z.and(255).shl(1));\n  offset = last64;\n  w[0] = w[0].add(len - 1 & 63);\n  v[0] = v[0].add(w[0]);\n  w[0] = w[0].add(v[0]);\n  x = rotate64(x.add(y).add(v[0]).add(fetch64(s2, offset + 8)), 37).mul(mul2);\n  y = rotate64(y.add(v[1]).add(fetch64(s2, offset + 48)), 42).mul(mul2);\n  x = x.xor(w[1].mul(9));\n  y = y.add(v[0].mul(9).add(fetch64(s2, offset + 40)));\n  z = rotate64(z.add(w[0]), 33).mul(mul2);\n  v = weakHashLen32WithSeedsStr(s2, offset, v[1].mul(mul2), x.add(w[0]));\n  w = weakHashLen32WithSeedsStr(s2, offset + 32, z.add(w[1]), y.add(fetch64(s2, offset + 16)));\n  [z, x] = [x, z];\n  return hashLen16(hashLen16(v[0], w[0], mul2).add(shiftMix(y).mul(k0)).add(z), hashLen16(v[1], w[1], mul2).add(x), mul2);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/util.js\nfunction createScalarValue(value, dtype) {\n  if (dtype === \"string\") {\n    return encodeString(value);\n  }\n  return toTypedArray([value], dtype);\n}\nfunction noConversionNeeded(a, dtype) {\n  return a instanceof Float32Array && dtype === \"float32\" || a instanceof Int32Array && dtype === \"int32\" || a instanceof Uint8Array && dtype === \"bool\";\n}\nfunction toTypedArray(a, dtype) {\n  if (dtype === \"string\") {\n    throw new Error(\"Cannot convert a string[] to a TypedArray\");\n  }\n  if (Array.isArray(a)) {\n    a = flatten(a);\n  }\n  if (env().getBool(\"DEBUG\")) {\n    checkConversionForErrors(a, dtype);\n  }\n  if (noConversionNeeded(a, dtype)) {\n    return a;\n  }\n  if (dtype == null || dtype === \"float32\" || dtype === \"complex64\") {\n    return new Float32Array(a);\n  } else if (dtype === \"int32\") {\n    return new Int32Array(a);\n  } else if (dtype === \"bool\") {\n    const bool = new Uint8Array(a.length);\n    for (let i2 = 0; i2 < bool.length; ++i2) {\n      if (Math.round(a[i2]) !== 0) {\n        bool[i2] = 1;\n      }\n    }\n    return bool;\n  } else {\n    throw new Error(`Unknown data type ${dtype}`);\n  }\n}\nfunction now() {\n  return env().platform.now();\n}\nfunction fetch3(path, requestInits) {\n  return env().platform.fetch(path, requestInits);\n}\nfunction encodeString(s2, encoding = \"utf-8\") {\n  encoding = encoding || \"utf-8\";\n  return env().platform.encode(s2, encoding);\n}\nfunction decodeString(bytes, encoding = \"utf-8\") {\n  encoding = encoding || \"utf-8\";\n  return env().platform.decode(bytes, encoding);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/profiler.js\nvar Profiler = class {\n  constructor(backendTimer, logger) {\n    this.backendTimer = backendTimer;\n    this.logger = logger;\n    if (logger == null) {\n      this.logger = new Logger();\n    }\n  }\n  profileKernel(kernelName, inputs, f) {\n    let outputs;\n    const holdResultWrapperFn = () => {\n      outputs = f();\n    };\n    let timer;\n    const start = now();\n    if (this.backendTimer.timerAvailable()) {\n      timer = this.backendTimer.time(holdResultWrapperFn);\n    } else {\n      holdResultWrapperFn();\n      for (const output of outputs) {\n        output.dataSync();\n      }\n      timer = Promise.resolve({ kernelMs: now() - start });\n    }\n    if (env().getBool(\"CHECK_COMPUTATION_FOR_ERRORS\")) {\n      for (let i2 = 0; i2 < outputs.length; i2++) {\n        const output = outputs[i2];\n        output.data().then((tensorVals) => {\n          checkComputationForErrors(tensorVals, output.dtype, kernelName);\n        });\n      }\n    }\n    const kernelProfile = {\n      kernelName,\n      outputs,\n      inputs,\n      timeMs: timer.then((timing) => timing.kernelMs),\n      extraInfo: timer.then((timing) => timing.getExtraProfileInfo != null ? timing.getExtraProfileInfo() : \"\")\n    };\n    return kernelProfile;\n  }\n  logKernelProfile(kernelProfile) {\n    const { kernelName, outputs, timeMs, inputs, extraInfo } = kernelProfile;\n    outputs.forEach((result) => {\n      Promise.all([result.data(), timeMs, extraInfo]).then((valueContainer) => {\n        this.logger.logKernelProfile(kernelName, result, valueContainer[0], valueContainer[1], inputs, valueContainer[2]);\n      });\n    });\n  }\n};\nfunction checkComputationForErrors(vals, dtype, kernelName) {\n  if (dtype !== \"float32\") {\n    return false;\n  }\n  for (let i2 = 0; i2 < vals.length; i2++) {\n    const num = vals[i2];\n    if (isNaN(num) || !isFinite(num)) {\n      console.warn(`Found ${num} in the result of '${kernelName}'`);\n      return true;\n    }\n  }\n  return false;\n}\nvar Logger = class {\n  logKernelProfile(name, result, vals, timeMs, inputs, extraInfo) {\n    const time2 = typeof timeMs === \"number\" ? rightPad(`${timeMs}ms`, 9) : timeMs[\"error\"];\n    const paddedName = rightPad(name, 25);\n    const rank = result.rank;\n    const size = result.size;\n    const shape = rightPad(result.shape.toString(), 14);\n    let inputShapesDescription = \"\";\n    for (const name2 in inputs) {\n      const input2 = inputs[name2];\n      if (input2 != null) {\n        const inputShape = input2.shape || result.shape;\n        const inputRank = inputShape.length;\n        inputShapesDescription += `${name2}: ${inputRank}D ${inputRank > 0 ? inputShape : \"\"} `;\n      }\n    }\n    console.log(`%c${paddedName}\t%c${time2}\t%c${rank}D ${shape}\t%c${size}\t%c${inputShapesDescription}\t%c${extraInfo}`, \"font-weight:bold\", \"color:red\", \"color:blue\", \"color: orange\", \"color: green\", \"color: steelblue\");\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/tape.js\nfunction getFilteredNodesXToY(tape, xs, y) {\n  const tensorsFromX = {};\n  const nodesFromX = {};\n  for (let i2 = 0; i2 < xs.length; i2++) {\n    tensorsFromX[xs[i2].id] = true;\n  }\n  for (let i2 = 0; i2 < tape.length; i2++) {\n    const node = tape[i2];\n    const nodeInputs = node.inputs;\n    for (const inputName in nodeInputs) {\n      const input2 = nodeInputs[inputName];\n      let anyInputFromX = false;\n      for (let j = 0; j < xs.length; j++) {\n        if (tensorsFromX[input2.id]) {\n          node.outputs.forEach((output) => tensorsFromX[output.id] = true);\n          anyInputFromX = true;\n          nodesFromX[node.id] = true;\n          break;\n        }\n      }\n      if (anyInputFromX) {\n        break;\n      }\n    }\n  }\n  const tensorsLeadToY = {};\n  tensorsLeadToY[y.id] = true;\n  const nodesToY = {};\n  for (let i2 = tape.length - 1; i2 >= 0; i2--) {\n    const node = tape[i2];\n    const nodeInputs = node.inputs;\n    for (let j = 0; j < node.outputs.length; j++) {\n      if (tensorsLeadToY[node.outputs[j].id]) {\n        for (const inputName in nodeInputs) {\n          tensorsLeadToY[nodeInputs[inputName].id] = true;\n          nodesToY[node.id] = true;\n        }\n        break;\n      }\n    }\n  }\n  const filteredTape = [];\n  for (let i2 = 0; i2 < tape.length; i2++) {\n    const node = tape[i2];\n    if (nodesFromX[node.id] && nodesToY[node.id]) {\n      const prunedInputs = {};\n      for (const inputName in node.inputs) {\n        const nodeInput = node.inputs[inputName];\n        if (tensorsFromX[nodeInput.id]) {\n          prunedInputs[inputName] = nodeInput;\n        }\n      }\n      const prunedNode = Object.assign({}, node);\n      prunedNode.inputs = prunedInputs;\n      prunedNode.outputs = node.outputs;\n      filteredTape.push(prunedNode);\n    }\n  }\n  return filteredTape;\n}\nfunction backpropagateGradients(tensorAccumulatedGradientMap, filteredTape, tidy2, add5) {\n  for (let i2 = filteredTape.length - 1; i2 >= 0; i2--) {\n    const node = filteredTape[i2];\n    const dys = [];\n    node.outputs.forEach((o) => {\n      const gradTensor = tensorAccumulatedGradientMap[o.id];\n      if (gradTensor != null) {\n        dys.push(gradTensor);\n      } else {\n        dys.push(null);\n      }\n    });\n    if (node.gradient == null) {\n      throw new Error(`Cannot compute gradient: gradient function not found for ${node.kernelName}.`);\n    }\n    const inputGradients = node.gradient(dys);\n    for (const inputName in node.inputs) {\n      if (!(inputName in inputGradients)) {\n        throw new Error(`Cannot backprop through input ${inputName}. Available gradients found: ${Object.keys(inputGradients)}.`);\n      }\n      const dx = tidy2(() => inputGradients[inputName]());\n      if (dx.dtype !== \"float32\") {\n        throw new Error(`Error in gradient for op ${node.kernelName}. The gradient of input ${inputName} must have 'float32' dtype, but has '${dx.dtype}'`);\n      }\n      const x = node.inputs[inputName];\n      if (!arraysEqual(dx.shape, x.shape)) {\n        throw new Error(`Error in gradient for op ${node.kernelName}. The gradient of input '${inputName}' has shape '${dx.shape}', which does not match the shape of the input '${x.shape}'`);\n      }\n      if (tensorAccumulatedGradientMap[x.id] == null) {\n        tensorAccumulatedGradientMap[x.id] = dx;\n      } else {\n        const curGradient = tensorAccumulatedGradientMap[x.id];\n        tensorAccumulatedGradientMap[x.id] = add5(curGradient, dx);\n        curGradient.dispose();\n      }\n    }\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/tensor_format.js\nvar FORMAT_LIMIT_NUM_VALS = 20;\nvar FORMAT_NUM_FIRST_LAST_VALS = 3;\nvar FORMAT_NUM_SIG_DIGITS = 7;\nfunction tensorToString(vals, shape, dtype, verbose) {\n  const strides = computeStrides(shape);\n  const padPerCol = computeMaxSizePerColumn(vals, shape, dtype, strides);\n  const rank = shape.length;\n  const valsLines = subTensorToString(vals, shape, dtype, strides, padPerCol);\n  const lines = [\"Tensor\"];\n  if (verbose) {\n    lines.push(`  dtype: ${dtype}`);\n    lines.push(`  rank: ${rank}`);\n    lines.push(`  shape: [${shape}]`);\n    lines.push(`  values:`);\n  }\n  lines.push(valsLines.map((l3) => \"    \" + l3).join(\"\\n\"));\n  return lines.join(\"\\n\");\n}\nfunction computeMaxSizePerColumn(vals, shape, dtype, strides) {\n  const n2 = sizeFromShape(shape);\n  const numCols = strides[strides.length - 1];\n  const padPerCol = new Array(numCols).fill(0);\n  const rank = shape.length;\n  const valuesOrTuples = dtype === \"complex64\" ? createComplexTuples(vals) : vals;\n  if (rank > 1) {\n    for (let row = 0; row < n2 / numCols; row++) {\n      const offset = row * numCols;\n      for (let j = 0; j < numCols; j++) {\n        padPerCol[j] = Math.max(padPerCol[j], valToString(valuesOrTuples[offset + j], 0, dtype).length);\n      }\n    }\n  }\n  return padPerCol;\n}\nfunction valToString(val, pad3, dtype) {\n  let valStr;\n  if (Array.isArray(val)) {\n    valStr = `${parseFloat(val[0].toFixed(FORMAT_NUM_SIG_DIGITS))} + ${parseFloat(val[1].toFixed(FORMAT_NUM_SIG_DIGITS))}j`;\n  } else if (isString(val)) {\n    valStr = `'${val}'`;\n  } else if (dtype === \"bool\") {\n    valStr = boolNumToString(val);\n  } else {\n    valStr = parseFloat(val.toFixed(FORMAT_NUM_SIG_DIGITS)).toString();\n  }\n  return rightPad(valStr, pad3);\n}\nfunction boolNumToString(v) {\n  return v === 0 ? \"false\" : \"true\";\n}\nfunction subTensorToString(vals, shape, dtype, strides, padPerCol, isLast = true) {\n  const storagePerElement = dtype === \"complex64\" ? 2 : 1;\n  const size = shape[0];\n  const rank = shape.length;\n  if (rank === 0) {\n    if (dtype === \"complex64\") {\n      const complexTuple = createComplexTuples(vals);\n      return [valToString(complexTuple[0], 0, dtype)];\n    }\n    if (dtype === \"bool\") {\n      return [boolNumToString(vals[0])];\n    }\n    return [vals[0].toString()];\n  }\n  if (rank === 1) {\n    if (size > FORMAT_LIMIT_NUM_VALS) {\n      const firstValsSize = FORMAT_NUM_FIRST_LAST_VALS * storagePerElement;\n      let firstVals = Array.from(vals.slice(0, firstValsSize));\n      let lastVals = Array.from(vals.slice((size - FORMAT_NUM_FIRST_LAST_VALS) * storagePerElement, size * storagePerElement));\n      if (dtype === \"complex64\") {\n        firstVals = createComplexTuples(firstVals);\n        lastVals = createComplexTuples(lastVals);\n      }\n      return [\n        \"[\" + firstVals.map((x, i2) => valToString(x, padPerCol[i2], dtype)).join(\", \") + \", ..., \" + lastVals.map((x, i2) => valToString(x, padPerCol[size - FORMAT_NUM_FIRST_LAST_VALS + i2], dtype)).join(\", \") + \"]\"\n      ];\n    }\n    const displayVals = dtype === \"complex64\" ? createComplexTuples(vals) : Array.from(vals);\n    return [\n      \"[\" + displayVals.map((x, i2) => valToString(x, padPerCol[i2], dtype)).join(\", \") + \"]\"\n    ];\n  }\n  const subshape = shape.slice(1);\n  const substrides = strides.slice(1);\n  const stride = strides[0] * storagePerElement;\n  const lines = [];\n  if (size > FORMAT_LIMIT_NUM_VALS) {\n    for (let i2 = 0; i2 < FORMAT_NUM_FIRST_LAST_VALS; i2++) {\n      const start = i2 * stride;\n      const end = start + stride;\n      lines.push(...subTensorToString(vals.slice(start, end), subshape, dtype, substrides, padPerCol, false));\n    }\n    lines.push(\"...\");\n    for (let i2 = size - FORMAT_NUM_FIRST_LAST_VALS; i2 < size; i2++) {\n      const start = i2 * stride;\n      const end = start + stride;\n      lines.push(...subTensorToString(vals.slice(start, end), subshape, dtype, substrides, padPerCol, i2 === size - 1));\n    }\n  } else {\n    for (let i2 = 0; i2 < size; i2++) {\n      const start = i2 * stride;\n      const end = start + stride;\n      lines.push(...subTensorToString(vals.slice(start, end), subshape, dtype, substrides, padPerCol, i2 === size - 1));\n    }\n  }\n  const sep = rank === 2 ? \",\" : \"\";\n  lines[0] = \"[\" + lines[0] + sep;\n  for (let i2 = 1; i2 < lines.length - 1; i2++) {\n    lines[i2] = \" \" + lines[i2] + sep;\n  }\n  let newLineSep = \",\\n\";\n  for (let i2 = 2; i2 < rank; i2++) {\n    newLineSep += \"\\n\";\n  }\n  lines[lines.length - 1] = \" \" + lines[lines.length - 1] + \"]\" + (isLast ? \"\" : newLineSep);\n  return lines;\n}\nfunction createComplexTuples(vals) {\n  const complexTuples = [];\n  for (let i2 = 0; i2 < vals.length; i2 += 2) {\n    complexTuples.push([vals[i2], vals[i2 + 1]]);\n  }\n  return complexTuples;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/tensor.js\nvar TensorBuffer = class {\n  constructor(shape, dtype, values) {\n    this.dtype = dtype;\n    this.shape = shape.slice();\n    this.size = sizeFromShape(shape);\n    if (values != null) {\n      const n2 = values.length;\n      assert(n2 === this.size, () => `Length of values '${n2}' does not match the size inferred by the shape '${this.size}'.`);\n    }\n    if (dtype === \"complex64\") {\n      throw new Error(`complex64 dtype TensorBuffers are not supported. Please create a TensorBuffer for the real and imaginary parts separately and call tf.complex(real, imag).`);\n    }\n    this.values = values || getArrayFromDType(dtype, this.size);\n    this.strides = computeStrides(shape);\n  }\n  set(value, ...locs) {\n    if (locs.length === 0) {\n      locs = [0];\n    }\n    assert(locs.length === this.rank, () => `The number of provided coordinates (${locs.length}) must match the rank (${this.rank})`);\n    const index = this.locToIndex(locs);\n    this.values[index] = value;\n  }\n  get(...locs) {\n    if (locs.length === 0) {\n      locs = [0];\n    }\n    let i2 = 0;\n    for (const loc of locs) {\n      if (loc < 0 || loc >= this.shape[i2]) {\n        const msg = `Requested out of range element at ${locs}.   Buffer shape=${this.shape}`;\n        throw new Error(msg);\n      }\n      i2++;\n    }\n    let index = locs[locs.length - 1];\n    for (let i3 = 0; i3 < locs.length - 1; ++i3) {\n      index += this.strides[i3] * locs[i3];\n    }\n    return this.values[index];\n  }\n  locToIndex(locs) {\n    if (this.rank === 0) {\n      return 0;\n    } else if (this.rank === 1) {\n      return locs[0];\n    }\n    let index = locs[locs.length - 1];\n    for (let i2 = 0; i2 < locs.length - 1; ++i2) {\n      index += this.strides[i2] * locs[i2];\n    }\n    return index;\n  }\n  indexToLoc(index) {\n    if (this.rank === 0) {\n      return [];\n    } else if (this.rank === 1) {\n      return [index];\n    }\n    const locs = new Array(this.shape.length);\n    for (let i2 = 0; i2 < locs.length - 1; ++i2) {\n      locs[i2] = Math.floor(index / this.strides[i2]);\n      index -= locs[i2] * this.strides[i2];\n    }\n    locs[locs.length - 1] = index;\n    return locs;\n  }\n  get rank() {\n    return this.shape.length;\n  }\n  toTensor() {\n    return trackerFn().makeTensor(this.values, this.shape, this.dtype);\n  }\n};\nvar trackerFn = null;\nvar opHandler = null;\nvar deprecationWarningFn = null;\nfunction setTensorTracker(fn) {\n  trackerFn = fn;\n}\nfunction setOpHandler(handler) {\n  opHandler = handler;\n}\nfunction setDeprecationWarningFn(fn) {\n  deprecationWarningFn = fn;\n}\nvar Tensor = class {\n  constructor(shape, dtype, dataId, id) {\n    this.kept = false;\n    this.isDisposedInternal = false;\n    this.shape = shape.slice();\n    this.dtype = dtype || \"float32\";\n    this.size = sizeFromShape(shape);\n    this.strides = computeStrides(shape);\n    this.dataId = dataId;\n    this.id = id;\n    this.rankType = this.rank < 5 ? this.rank.toString() : \"higher\";\n  }\n  get rank() {\n    return this.shape.length;\n  }\n  async buffer() {\n    const vals = await this.data();\n    return opHandler.buffer(this.shape, this.dtype, vals);\n  }\n  bufferSync() {\n    return opHandler.buffer(this.shape, this.dtype, this.dataSync());\n  }\n  async array() {\n    const vals = await this.data();\n    return toNestedArray(this.shape, vals, this.dtype === \"complex64\");\n  }\n  arraySync() {\n    return toNestedArray(this.shape, this.dataSync(), this.dtype === \"complex64\");\n  }\n  async data() {\n    this.throwIfDisposed();\n    const data = trackerFn().read(this.dataId);\n    if (this.dtype === \"string\") {\n      const bytes = await data;\n      try {\n        return bytes.map((b) => decodeString(b));\n      } catch (_a) {\n        throw new Error(\"Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().\");\n      }\n    }\n    return data;\n  }\n  dataToGPU(options) {\n    this.throwIfDisposed();\n    return trackerFn().readToGPU(this.dataId, options);\n  }\n  dataSync() {\n    this.throwIfDisposed();\n    const data = trackerFn().readSync(this.dataId);\n    if (this.dtype === \"string\") {\n      try {\n        return data.map((b) => decodeString(b));\n      } catch (_a) {\n        throw new Error(\"Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().\");\n      }\n    }\n    return data;\n  }\n  async bytes() {\n    this.throwIfDisposed();\n    const data = await trackerFn().read(this.dataId);\n    if (this.dtype === \"string\") {\n      return data;\n    } else {\n      return new Uint8Array(data.buffer);\n    }\n  }\n  dispose() {\n    if (this.isDisposed) {\n      return;\n    }\n    trackerFn().disposeTensor(this);\n    this.isDisposedInternal = true;\n  }\n  get isDisposed() {\n    return this.isDisposedInternal;\n  }\n  throwIfDisposed() {\n    if (this.isDisposed) {\n      throw new Error(`Tensor is disposed.`);\n    }\n  }\n  print(verbose = false) {\n    return opHandler.print(this, verbose);\n  }\n  clone() {\n    this.throwIfDisposed();\n    return opHandler.clone(this);\n  }\n  toString(verbose = false) {\n    const vals = this.dataSync();\n    return tensorToString(vals, this.shape, this.dtype, verbose);\n  }\n  cast(dtype) {\n    this.throwIfDisposed();\n    return opHandler.cast(this, dtype);\n  }\n  variable(trainable = true, name, dtype) {\n    this.throwIfDisposed();\n    return trackerFn().makeVariable(this, trainable, name, dtype);\n  }\n};\nObject.defineProperty(Tensor, Symbol.hasInstance, {\n  value: (instance) => {\n    return !!instance && instance.data != null && instance.dataSync != null && instance.throwIfDisposed != null;\n  }\n});\nfunction getGlobalTensorClass() {\n  return getGlobal(\"Tensor\", () => {\n    return Tensor;\n  });\n}\ngetGlobalTensorClass();\nvar Variable = class extends Tensor {\n  constructor(initialValue, trainable, name, tensorId) {\n    super(initialValue.shape, initialValue.dtype, initialValue.dataId, tensorId);\n    this.trainable = trainable;\n    this.name = name;\n  }\n  assign(newValue) {\n    if (newValue.dtype !== this.dtype) {\n      throw new Error(`dtype of the new value (${newValue.dtype}) and previous value (${this.dtype}) must match`);\n    }\n    if (!arraysEqual(newValue.shape, this.shape)) {\n      throw new Error(`shape of the new value (${newValue.shape}) and previous value (${this.shape}) must match`);\n    }\n    trackerFn().disposeTensor(this);\n    this.dataId = newValue.dataId;\n    trackerFn().incRef(this, null);\n  }\n  dispose() {\n    trackerFn().disposeVariable(this);\n    this.isDisposedInternal = true;\n  }\n};\nObject.defineProperty(Variable, Symbol.hasInstance, {\n  value: (instance) => {\n    return instance instanceof Tensor && instance.assign != null && instance.assign instanceof Function;\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/tensor_util.js\nvar tensor_util_exports = {};\n__export(tensor_util_exports, {\n  assertTypesMatch: () => assertTypesMatch,\n  getTensorsInContainer: () => getTensorsInContainer,\n  isTensorInList: () => isTensorInList,\n  makeTypesMatch: () => makeTypesMatch\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/types.js\nvar Rank;\n(function(Rank2) {\n  Rank2[\"R0\"] = \"R0\";\n  Rank2[\"R1\"] = \"R1\";\n  Rank2[\"R2\"] = \"R2\";\n  Rank2[\"R3\"] = \"R3\";\n  Rank2[\"R4\"] = \"R4\";\n  Rank2[\"R5\"] = \"R5\";\n  Rank2[\"R6\"] = \"R6\";\n})(Rank || (Rank = {}));\nvar UpcastInt32AndMap;\n(function(UpcastInt32AndMap2) {\n  UpcastInt32AndMap2[\"float32\"] = \"float32\";\n  UpcastInt32AndMap2[\"int32\"] = \"int32\";\n  UpcastInt32AndMap2[\"bool\"] = \"int32\";\n  UpcastInt32AndMap2[\"complex64\"] = \"complex64\";\n})(UpcastInt32AndMap || (UpcastInt32AndMap = {}));\nvar UpcastBoolAndMap;\n(function(UpcastBoolAndMap2) {\n  UpcastBoolAndMap2[\"float32\"] = \"float32\";\n  UpcastBoolAndMap2[\"int32\"] = \"int32\";\n  UpcastBoolAndMap2[\"bool\"] = \"bool\";\n  UpcastBoolAndMap2[\"complex64\"] = \"complex64\";\n})(UpcastBoolAndMap || (UpcastBoolAndMap = {}));\nvar UpcastFloat32AndMap;\n(function(UpcastFloat32AndMap2) {\n  UpcastFloat32AndMap2[\"float32\"] = \"float32\";\n  UpcastFloat32AndMap2[\"int32\"] = \"float32\";\n  UpcastFloat32AndMap2[\"bool\"] = \"float32\";\n  UpcastFloat32AndMap2[\"complex64\"] = \"complex64\";\n})(UpcastFloat32AndMap || (UpcastFloat32AndMap = {}));\nvar UpcastComplex64AndMap;\n(function(UpcastComplex64AndMap2) {\n  UpcastComplex64AndMap2[\"float32\"] = \"complex64\";\n  UpcastComplex64AndMap2[\"int32\"] = \"complex64\";\n  UpcastComplex64AndMap2[\"bool\"] = \"complex64\";\n  UpcastComplex64AndMap2[\"complex64\"] = \"complex64\";\n})(UpcastComplex64AndMap || (UpcastComplex64AndMap = {}));\nvar upcastTypeMap = {\n  \"float32\": UpcastFloat32AndMap,\n  \"int32\": UpcastInt32AndMap,\n  \"bool\": UpcastBoolAndMap,\n  \"complex64\": UpcastComplex64AndMap\n};\nfunction upcastType(typeA, typeB) {\n  if (typeA === \"string\" || typeB === \"string\") {\n    if (typeA === \"string\" && typeB === \"string\") {\n      return \"string\";\n    }\n    throw new Error(`Can not upcast ${typeA} with ${typeB}`);\n  }\n  return upcastTypeMap[typeA][typeB];\n}\nfunction sumOutType(type) {\n  return upcastType(type, \"int32\");\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/tensor_util.js\nfunction makeTypesMatch(a, b) {\n  if (a.dtype === b.dtype) {\n    return [a, b];\n  }\n  const dtype = upcastType(a.dtype, b.dtype);\n  return [a.cast(dtype), b.cast(dtype)];\n}\nfunction assertTypesMatch(a, b) {\n  assert(a.dtype === b.dtype, () => `The dtypes of the first(${a.dtype}) and second(${b.dtype}) input must match`);\n}\nfunction isTensorInList(tensor2, tensorList) {\n  return tensorList.some((x) => x.id === tensor2.id);\n}\nfunction getTensorsInContainer(result) {\n  const list = [];\n  const seen = /* @__PURE__ */ new Set();\n  walkTensorContainer(result, list, seen);\n  return list;\n}\nfunction walkTensorContainer(container, list, seen) {\n  if (container == null) {\n    return;\n  }\n  if (container instanceof Tensor) {\n    list.push(container);\n    return;\n  }\n  if (!isIterable(container)) {\n    return;\n  }\n  const iterable = container;\n  for (const k in iterable) {\n    const val = iterable[k];\n    if (!seen.has(val)) {\n      seen.add(val);\n      walkTensorContainer(val, list, seen);\n    }\n  }\n}\nfunction isIterable(obj) {\n  return Array.isArray(obj) || typeof obj === \"object\";\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/engine.js\nfunction isRegisteredKernelInvocation(kernelInvocation) {\n  return kernelInvocation.kernelName != null;\n}\nvar EngineState = class {\n  constructor() {\n    this.registeredVariables = {};\n    this.nextTapeNodeId = 0;\n    this.numBytes = 0;\n    this.numTensors = 0;\n    this.numStringTensors = 0;\n    this.numDataBuffers = 0;\n    this.gradientDepth = 0;\n    this.kernelDepth = 0;\n    this.scopeStack = [];\n    this.numDataMovesStack = [];\n    this.nextScopeId = 0;\n    this.tensorInfo = /* @__PURE__ */ new WeakMap();\n    this.profiling = false;\n    this.activeProfile = {\n      newBytes: 0,\n      newTensors: 0,\n      peakBytes: 0,\n      kernels: [],\n      result: null,\n      get kernelNames() {\n        return Array.from(new Set(this.kernels.map((k) => k.name)));\n      }\n    };\n  }\n  dispose() {\n    for (const variableName in this.registeredVariables) {\n      this.registeredVariables[variableName].dispose();\n    }\n  }\n};\nvar Engine = class {\n  constructor(ENV8) {\n    this.ENV = ENV8;\n    this.registry = {};\n    this.registryFactory = {};\n    this.pendingBackendInitId = 0;\n    this.state = new EngineState();\n  }\n  async ready() {\n    if (this.pendingBackendInit != null) {\n      return this.pendingBackendInit.then(() => {\n      });\n    }\n    if (this.backendInstance != null) {\n      return;\n    }\n    const sortedBackends = this.getSortedBackends();\n    for (let i2 = 0; i2 < sortedBackends.length; i2++) {\n      const backendName = sortedBackends[i2];\n      const success = await this.initializeBackend(backendName).success;\n      if (success) {\n        await this.setBackend(backendName);\n        return;\n      }\n    }\n    throw new Error(`Could not initialize any backends, all backend initializations failed.`);\n  }\n  get backend() {\n    if (this.pendingBackendInit != null) {\n      throw new Error(`Backend '${this.backendName}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);\n    }\n    if (this.backendInstance == null) {\n      const { name, asyncInit } = this.initializeBackendsAndReturnBest();\n      if (asyncInit) {\n        throw new Error(`The highest priority backend '${name}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);\n      }\n      this.setBackend(name);\n    }\n    return this.backendInstance;\n  }\n  backendNames() {\n    return Object.keys(this.registryFactory);\n  }\n  findBackend(backendName) {\n    if (!(backendName in this.registry)) {\n      if (backendName in this.registryFactory) {\n        const { asyncInit } = this.initializeBackend(backendName);\n        if (asyncInit) {\n          return null;\n        }\n      } else {\n        return null;\n      }\n    }\n    return this.registry[backendName];\n  }\n  findBackendFactory(backendName) {\n    if (!(backendName in this.registryFactory)) {\n      return null;\n    }\n    return this.registryFactory[backendName].factory;\n  }\n  registerBackend(backendName, factory, priority = 1) {\n    if (backendName in this.registryFactory) {\n      warn(`${backendName} backend was already registered. Reusing existing backend factory.`);\n      return false;\n    }\n    this.registryFactory[backendName] = { factory, priority };\n    return true;\n  }\n  async setBackend(backendName) {\n    if (this.registryFactory[backendName] == null) {\n      throw new Error(`Backend name '${backendName}' not found in registry`);\n    }\n    this.backendName = backendName;\n    if (this.registry[backendName] == null) {\n      this.backendInstance = null;\n      const { success, asyncInit } = this.initializeBackend(backendName);\n      const result = asyncInit ? await success : success;\n      if (!result) {\n        return false;\n      }\n    }\n    this.backendInstance = this.registry[backendName];\n    this.setupRegisteredKernels();\n    this.profiler = new Profiler(this.backendInstance);\n    return true;\n  }\n  setupRegisteredKernels() {\n    const kernels = getKernelsForBackend(this.backendName);\n    kernels.forEach((kernel) => {\n      if (kernel.setupFunc != null) {\n        kernel.setupFunc(this.backendInstance);\n      }\n    });\n  }\n  disposeRegisteredKernels(backendName) {\n    const kernels = getKernelsForBackend(backendName);\n    kernels.forEach((kernel) => {\n      if (kernel.disposeFunc != null) {\n        kernel.disposeFunc(this.registry[backendName]);\n      }\n    });\n  }\n  initializeBackend(backendName) {\n    const registryFactoryEntry = this.registryFactory[backendName];\n    if (registryFactoryEntry == null) {\n      throw new Error(`Cannot initialize backend ${backendName}, no registration found.`);\n    }\n    try {\n      const backend2 = registryFactoryEntry.factory();\n      if (backend2 && !(backend2 instanceof KernelBackend) && typeof backend2.then === \"function\") {\n        const promiseId = ++this.pendingBackendInitId;\n        const success = backend2.then((backendInstance) => {\n          if (promiseId < this.pendingBackendInitId) {\n            return false;\n          }\n          this.registry[backendName] = backendInstance;\n          this.pendingBackendInit = null;\n          return true;\n        }).catch((err) => {\n          if (promiseId < this.pendingBackendInitId) {\n            return false;\n          }\n          this.pendingBackendInit = null;\n          warn(`Initialization of backend ${backendName} failed`);\n          warn(err.stack || err.message);\n          return false;\n        });\n        this.pendingBackendInit = success;\n        return { success, asyncInit: true };\n      } else {\n        this.registry[backendName] = backend2;\n        return { success: true, asyncInit: false };\n      }\n    } catch (err) {\n      warn(`Initialization of backend ${backendName} failed`);\n      warn(err.stack || err.message);\n      return { success: false, asyncInit: false };\n    }\n  }\n  removeBackend(backendName) {\n    if (!(backendName in this.registryFactory)) {\n      throw new Error(`${backendName} backend not found in registry`);\n    }\n    if (this.backendName === backendName && this.pendingBackendInit != null) {\n      this.pendingBackendInitId++;\n    }\n    if (backendName in this.registry) {\n      this.disposeRegisteredKernels(backendName);\n      this.registry[backendName].dispose();\n      delete this.registry[backendName];\n    }\n    delete this.registryFactory[backendName];\n    if (this.backendName === backendName) {\n      this.pendingBackendInit = null;\n      this.backendName = null;\n      this.backendInstance = null;\n    }\n  }\n  getSortedBackends() {\n    if (Object.keys(this.registryFactory).length === 0) {\n      throw new Error(\"No backend found in registry.\");\n    }\n    return Object.keys(this.registryFactory).sort((a, b) => {\n      return this.registryFactory[b].priority - this.registryFactory[a].priority;\n    });\n  }\n  initializeBackendsAndReturnBest() {\n    const sortedBackends = this.getSortedBackends();\n    for (let i2 = 0; i2 < sortedBackends.length; i2++) {\n      const backendName = sortedBackends[i2];\n      const { success, asyncInit } = this.initializeBackend(backendName);\n      if (asyncInit || success) {\n        return { name: backendName, asyncInit };\n      }\n    }\n    throw new Error(`Could not initialize any backends, all backend initializations failed.`);\n  }\n  moveData(backend2, dataId) {\n    const info = this.state.tensorInfo.get(dataId);\n    const srcBackend = info.backend;\n    const values = this.readSync(dataId);\n    const refCount = srcBackend.refCount(dataId);\n    srcBackend.disposeData(dataId, true);\n    info.backend = backend2;\n    backend2.move(dataId, values, info.shape, info.dtype, refCount);\n    if (this.shouldCheckForMemLeaks()) {\n      this.state.numDataMovesStack[this.state.numDataMovesStack.length - 1]++;\n    }\n  }\n  tidy(nameOrFn, fn) {\n    let name = null;\n    if (fn == null) {\n      if (typeof nameOrFn !== \"function\") {\n        throw new Error(\"Please provide a function to tidy()\");\n      }\n      fn = nameOrFn;\n    } else {\n      if (typeof nameOrFn !== \"string\" && !(nameOrFn instanceof String)) {\n        throw new Error(\"When calling with two arguments, the first argument to tidy() must be a string\");\n      }\n      if (typeof fn !== \"function\") {\n        throw new Error(\"When calling with two arguments, the 2nd argument to tidy() must be a function\");\n      }\n      name = nameOrFn;\n    }\n    let result;\n    return this.scopedRun(() => this.startScope(name), () => this.endScope(result), () => {\n      result = fn();\n      if (result instanceof Promise) {\n        console.error(\"Cannot return a Promise inside of tidy.\");\n      }\n      return result;\n    });\n  }\n  scopedRun(start, end, f) {\n    start();\n    try {\n      const res = f();\n      end();\n      return res;\n    } catch (ex) {\n      end();\n      throw ex;\n    }\n  }\n  nextTensorId() {\n    return Engine.nextTensorId++;\n  }\n  nextVariableId() {\n    return Engine.nextVariableId++;\n  }\n  clone(x) {\n    const y = ENGINE.runKernel(Identity, { x });\n    const inputs = { x };\n    const grad2 = (dy) => ({\n      x: () => {\n        const dtype = \"float32\";\n        const gradInputs = { x: dy };\n        const attrs = { dtype };\n        return ENGINE.runKernel(\n          Cast,\n          gradInputs,\n          attrs\n        );\n      }\n    });\n    const saved = [];\n    this.addTapeNode(this.state.activeScope.name, inputs, [y], grad2, saved, {});\n    return y;\n  }\n  runKernel(kernelName, inputs, attrs) {\n    if (this.backendName == null) {\n      this.backend;\n    }\n    const hasKernel = getKernel(kernelName, this.backendName) != null;\n    if (!hasKernel) {\n      throw new Error(`Kernel '${kernelName}' not registered for backend '${this.backendName}'`);\n    }\n    return this.runKernelFunc({ kernelName, inputs, attrs });\n  }\n  shouldCheckForMemLeaks() {\n    return this.ENV.getBool(\"IS_TEST\");\n  }\n  checkKernelForMemLeak(kernelName, numDataIdsBefore, outInfos) {\n    const numDataIdsAfter = this.backend.numDataIds();\n    let numOutputDataIds = 0;\n    outInfos.forEach((info) => {\n      numOutputDataIds += info.dtype === \"complex64\" ? 3 : 1;\n    });\n    const numMoves = this.state.numDataMovesStack[this.state.numDataMovesStack.length - 1];\n    const dataIdsLeaked = numDataIdsAfter - numDataIdsBefore - numOutputDataIds - numMoves;\n    if (dataIdsLeaked > 0) {\n      throw new Error(`Backend '${this.backendName}' has an internal memory leak (${dataIdsLeaked} data ids) after running '${kernelName}'`);\n    }\n  }\n  runKernelFunc(kernelParams) {\n    let outputs;\n    let saved = [];\n    const isTapeOn = this.isTapeOn();\n    const startingBytecount = this.state.numBytes;\n    const startingNumTensors = this.state.numTensors;\n    if (this.shouldCheckForMemLeaks()) {\n      this.state.numDataMovesStack.push(0);\n    }\n    let kernelFunc3;\n    if (this.backendName == null) {\n      this.backend;\n    }\n    let out;\n    const kernelOrScopeName = isRegisteredKernelInvocation(kernelParams) ? kernelParams.kernelName : this.state.activeScope != null ? this.state.activeScope.name : \"\";\n    if (isRegisteredKernelInvocation(kernelParams)) {\n      const { kernelName, inputs: inputs2, attrs: attrs2 } = kernelParams;\n      if (this.backendName == null) {\n        this.backend;\n      }\n      const kernel = getKernel(kernelName, this.backendName);\n      assert(kernel != null, () => `Cannot find registered kernel '${kernelName}' for backend '${this.backendName}'`);\n      kernelFunc3 = () => {\n        const numDataIdsBefore = this.backend.numDataIds();\n        out = kernel.kernelFunc({ inputs: inputs2, attrs: attrs2, backend: this.backend });\n        const outInfos = Array.isArray(out) ? out : [out];\n        if (this.shouldCheckForMemLeaks()) {\n          this.checkKernelForMemLeak(kernelName, numDataIdsBefore, outInfos);\n        }\n        const outTensors = outInfos.map((outInfo) => {\n          if (outInfo.rank != null) {\n            return outInfo;\n          }\n          return this.makeTensorFromTensorInfo(outInfo);\n        });\n        if (isTapeOn) {\n          const tensorsToSave = this.getTensorsForGradient(kernelName, inputs2, outTensors);\n          saved = this.saveTensorsForBackwardMode(tensorsToSave);\n        }\n        return outTensors;\n      };\n    } else {\n      const { forwardFunc } = kernelParams;\n      const saveFunc = (tensors) => {\n        if (!isTapeOn) {\n          return;\n        }\n        saved = tensors.map((tensor2) => this.keep(this.clone(tensor2)));\n      };\n      kernelFunc3 = () => {\n        const numDataIdsBefore = this.backend.numDataIds();\n        out = this.tidy(() => forwardFunc(this.backend, saveFunc));\n        const outs = Array.isArray(out) ? out : [out];\n        if (this.shouldCheckForMemLeaks()) {\n          this.checkKernelForMemLeak(kernelOrScopeName, numDataIdsBefore, outs);\n        }\n        return outs;\n      };\n    }\n    const { inputs, attrs } = kernelParams;\n    const backwardsFunc = isRegisteredKernelInvocation(kernelParams) ? null : kernelParams.backwardsFunc;\n    let kernelProfile;\n    this.scopedRun(\n      () => this.state.kernelDepth++,\n      () => this.state.kernelDepth--,\n      () => {\n        if (!this.ENV.getBool(\"DEBUG\") && !this.state.profiling) {\n          outputs = kernelFunc3();\n        } else {\n          kernelProfile = this.profiler.profileKernel(kernelOrScopeName, inputs, () => kernelFunc3());\n          if (this.ENV.getBool(\"DEBUG\")) {\n            this.profiler.logKernelProfile(kernelProfile);\n          }\n          outputs = kernelProfile.outputs;\n        }\n      }\n    );\n    if (isTapeOn) {\n      this.addTapeNode(kernelOrScopeName, inputs, outputs, backwardsFunc, saved, attrs);\n    }\n    if (this.state.profiling) {\n      this.state.activeProfile.kernels.push({\n        name: kernelOrScopeName,\n        bytesAdded: this.state.numBytes - startingBytecount,\n        totalBytesSnapshot: this.state.numBytes,\n        tensorsAdded: this.state.numTensors - startingNumTensors,\n        totalTensorsSnapshot: this.state.numTensors,\n        inputShapes: Object.keys(inputs).map((key) => inputs[key] != null ? inputs[key].shape : null),\n        outputShapes: outputs.map((item) => item.shape),\n        kernelTimeMs: kernelProfile.timeMs,\n        extraInfo: kernelProfile.extraInfo\n      });\n    }\n    return Array.isArray(out) ? outputs : outputs[0];\n  }\n  saveTensorsForBackwardMode(tensors) {\n    const saved = tensors.map((tensor2) => this.keep(this.clone(tensor2)));\n    return saved;\n  }\n  getTensorsForGradient(kernelName, inputs, outputs) {\n    const gradConfig = getGradient(kernelName);\n    if (gradConfig != null) {\n      const inputsToSave = gradConfig.inputsToSave || [];\n      const outputsToSave = gradConfig.outputsToSave || [];\n      let inputTensorsToSave;\n      if (gradConfig.saveAllInputs) {\n        assert(Array.isArray(inputs), () => \"saveAllInputs is true, expected inputs to be an array.\");\n        inputTensorsToSave = Object.keys(inputs).map((key) => inputs[key]);\n      } else {\n        inputTensorsToSave = inputsToSave.map((inputName) => inputs[inputName]);\n      }\n      const outputTensorsToSave = outputs.filter((_, i2) => outputsToSave[i2]);\n      return inputTensorsToSave.concat(outputTensorsToSave);\n    }\n    return [];\n  }\n  makeTensor(values, shape, dtype, backend2) {\n    if (values == null) {\n      throw new Error(\"Values passed to engine.makeTensor() are null\");\n    }\n    dtype = dtype || \"float32\";\n    backend2 = backend2 || this.backend;\n    let backendVals = values;\n    if (dtype === \"string\" && isString(values[0])) {\n      backendVals = values.map((d) => encodeString(d));\n    }\n    const dataId = backend2.write(backendVals, shape, dtype);\n    const t2 = new Tensor(shape, dtype, dataId, this.nextTensorId());\n    this.trackTensor(t2, backend2);\n    if (dtype === \"string\") {\n      const info = this.state.tensorInfo.get(dataId);\n      const newBytes = bytesFromStringArray(backendVals);\n      this.state.numBytes += newBytes - info.bytes;\n      info.bytes = newBytes;\n    }\n    return t2;\n  }\n  makeTensorFromDataId(dataId, shape, dtype, backend2) {\n    dtype = dtype || \"float32\";\n    const tensorInfo = { dataId, shape, dtype };\n    return this.makeTensorFromTensorInfo(tensorInfo, backend2);\n  }\n  makeTensorFromTensorInfo(tensorInfo, backend2) {\n    const { dataId, shape, dtype } = tensorInfo;\n    const t2 = new Tensor(shape, dtype, dataId, this.nextTensorId());\n    this.trackTensor(t2, backend2);\n    return t2;\n  }\n  makeVariable(initialValue, trainable = true, name, dtype) {\n    name = name || this.nextVariableId().toString();\n    if (dtype != null && dtype !== initialValue.dtype) {\n      initialValue = initialValue.cast(dtype);\n    }\n    const v = new Variable(initialValue, trainable, name, this.nextTensorId());\n    if (this.state.registeredVariables[v.name] != null) {\n      throw new Error(`Variable with name ${v.name} was already registered`);\n    }\n    this.state.registeredVariables[v.name] = v;\n    this.incRef(v, this.backend);\n    return v;\n  }\n  trackTensor(a, backend2) {\n    this.state.numTensors++;\n    if (a.dtype === \"string\") {\n      this.state.numStringTensors++;\n    }\n    let bytes = 0;\n    if (a.dtype !== \"complex64\" && a.dtype !== \"string\") {\n      bytes = a.size * bytesPerElement(a.dtype);\n    }\n    this.state.numBytes += bytes;\n    if (!this.state.tensorInfo.has(a.dataId)) {\n      this.state.numDataBuffers++;\n      this.state.tensorInfo.set(a.dataId, {\n        backend: backend2 || this.backend,\n        dtype: a.dtype,\n        shape: a.shape,\n        bytes\n      });\n    }\n    if (!(a instanceof Variable)) {\n      this.track(a);\n    }\n  }\n  incRef(a, backend2) {\n    this.trackTensor(a, backend2);\n    this.backend.incRef(a.dataId);\n  }\n  removeDataId(dataId, backend2) {\n    if (this.state.tensorInfo.has(dataId) && this.state.tensorInfo.get(dataId).backend === backend2) {\n      this.state.tensorInfo.delete(dataId);\n      this.state.numDataBuffers--;\n    }\n  }\n  disposeTensor(a) {\n    if (!this.state.tensorInfo.has(a.dataId)) {\n      return;\n    }\n    const info = this.state.tensorInfo.get(a.dataId);\n    this.state.numTensors--;\n    if (a.dtype === \"string\") {\n      this.state.numStringTensors--;\n      this.state.numBytes -= info.bytes;\n    }\n    if (a.dtype !== \"complex64\" && a.dtype !== \"string\") {\n      const bytes = a.size * bytesPerElement(a.dtype);\n      this.state.numBytes -= bytes;\n    }\n    if (info.backend.disposeData(a.dataId)) {\n      this.removeDataId(a.dataId, info.backend);\n    }\n  }\n  disposeVariables() {\n    for (const varName in this.state.registeredVariables) {\n      const v = this.state.registeredVariables[varName];\n      this.disposeVariable(v);\n    }\n  }\n  disposeVariable(v) {\n    this.disposeTensor(v);\n    if (this.state.registeredVariables[v.name] != null) {\n      delete this.state.registeredVariables[v.name];\n    }\n  }\n  memory() {\n    const info = this.backend.memory();\n    info.numTensors = this.state.numTensors;\n    info.numDataBuffers = this.state.numDataBuffers;\n    info.numBytes = this.state.numBytes;\n    if (this.state.numStringTensors > 0) {\n      info.unreliable = true;\n      if (info.reasons == null) {\n        info.reasons = [];\n      }\n      info.reasons.push(\"Memory usage by string tensors is approximate (2 bytes per character)\");\n    }\n    return info;\n  }\n  async profile(query) {\n    this.state.profiling = true;\n    const startBytes = this.state.numBytes;\n    const startNumTensors = this.state.numTensors;\n    this.state.activeProfile.kernels = [];\n    this.state.activeProfile.result = await query();\n    this.state.profiling = false;\n    this.state.activeProfile.peakBytes = Math.max(...this.state.activeProfile.kernels.map((d) => d.totalBytesSnapshot));\n    this.state.activeProfile.newBytes = this.state.numBytes - startBytes;\n    this.state.activeProfile.newTensors = this.state.numTensors - startNumTensors;\n    for (const kernel of this.state.activeProfile.kernels) {\n      kernel.kernelTimeMs = await kernel.kernelTimeMs;\n      kernel.extraInfo = await kernel.extraInfo;\n    }\n    return this.state.activeProfile;\n  }\n  isTapeOn() {\n    return this.state.gradientDepth > 0 && this.state.kernelDepth === 0;\n  }\n  addTapeNode(kernelName, inputs, outputs, gradientsFunc, saved, attrs) {\n    const tapeNode = { id: this.state.nextTapeNodeId++, kernelName, inputs, outputs, saved };\n    const gradConfig = getGradient(kernelName);\n    if (gradConfig != null) {\n      gradientsFunc = gradConfig.gradFunc;\n    }\n    if (gradientsFunc != null) {\n      tapeNode.gradient = (dys) => {\n        dys = dys.map((dy, i2) => {\n          if (dy == null) {\n            const output = outputs[i2];\n            const vals = makeZerosTypedArray(output.size, output.dtype);\n            return this.makeTensor(vals, output.shape, output.dtype);\n          }\n          return dy;\n        });\n        return gradientsFunc(dys.length > 1 ? dys : dys[0], saved, attrs);\n      };\n    }\n    this.state.activeTape.push(tapeNode);\n  }\n  keep(result) {\n    result.kept = true;\n    return result;\n  }\n  startTape() {\n    if (this.state.gradientDepth === 0) {\n      this.state.activeTape = [];\n    }\n    this.state.gradientDepth++;\n  }\n  endTape() {\n    this.state.gradientDepth--;\n  }\n  startScope(name) {\n    const scopeInfo = {\n      track: [],\n      name: \"unnamed scope\",\n      id: this.state.nextScopeId++\n    };\n    if (name) {\n      scopeInfo.name = name;\n    }\n    this.state.scopeStack.push(scopeInfo);\n    this.state.activeScope = scopeInfo;\n  }\n  endScope(result) {\n    const tensorsToTrackInParent = getTensorsInContainer(result);\n    const tensorsToTrackInParentSet = new Set(tensorsToTrackInParent.map((t2) => t2.id));\n    for (let i2 = 0; i2 < this.state.activeScope.track.length; i2++) {\n      const tensor2 = this.state.activeScope.track[i2];\n      if (!tensor2.kept && !tensorsToTrackInParentSet.has(tensor2.id)) {\n        tensor2.dispose();\n      }\n    }\n    const oldScope = this.state.scopeStack.pop();\n    this.state.activeScope = this.state.scopeStack.length === 0 ? null : this.state.scopeStack[this.state.scopeStack.length - 1];\n    tensorsToTrackInParent.forEach((tensor2) => {\n      if (!tensor2.kept && tensor2.scopeId === oldScope.id) {\n        this.track(tensor2);\n      }\n    });\n  }\n  gradients(f, xs, dy, allowNoGradients = false) {\n    assert(xs.length > 0, () => \"gradients() received an empty list of xs.\");\n    if (dy != null && dy.dtype !== \"float32\") {\n      throw new Error(`dy must have 'float32' dtype, but has '${dy.dtype}'`);\n    }\n    const y = this.scopedRun(() => this.startTape(), () => this.endTape(), () => this.tidy(\"forward\", f));\n    assert(y instanceof Tensor, () => \"The result y returned by f() must be a tensor.\");\n    const filteredTape = getFilteredNodesXToY(this.state.activeTape, xs, y);\n    if (!allowNoGradients && filteredTape.length === 0 && xs.length > 0) {\n      throw new Error(\"Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.\");\n    }\n    return this.tidy(\"backward\", () => {\n      const accumulatedGradientMap = {};\n      accumulatedGradientMap[y.id] = dy == null ? ones(y.shape) : dy;\n      backpropagateGradients(\n        accumulatedGradientMap,\n        filteredTape,\n        (f2) => this.tidy(f2),\n        add\n      );\n      const grads2 = xs.map((x) => accumulatedGradientMap[x.id]);\n      if (this.state.gradientDepth === 0) {\n        this.state.activeTape.forEach((node) => {\n          for (const tensor2 of node.saved) {\n            tensor2.dispose();\n          }\n        });\n        this.state.activeTape = null;\n      }\n      return { value: y, grads: grads2 };\n    });\n  }\n  customGrad(f) {\n    assert(isFunction(f), () => \"The f passed in customGrad(f) must be a function.\");\n    return (...inputs) => {\n      assert(inputs.every((t2) => t2 instanceof Tensor), () => \"The args passed in customGrad(f)(x1, x2,...) must all be tensors\");\n      let res;\n      const inputMap = {};\n      inputs.forEach((input2, i2) => {\n        inputMap[i2] = input2;\n      });\n      const forwardFunc = (_, save) => {\n        res = f(...[...inputs, save]);\n        assert(res.value instanceof Tensor, () => \"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor\");\n        assert(isFunction(res.gradFunc), () => \"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function.\");\n        return res.value;\n      };\n      const backwardsFunc = (dy, saved) => {\n        const gradRes = res.gradFunc(dy, saved);\n        const grads2 = Array.isArray(gradRes) ? gradRes : [gradRes];\n        assert(grads2.length === inputs.length, () => \"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...).\");\n        assert(grads2.every((t2) => t2 instanceof Tensor), () => \"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors.\");\n        const gradMap = {};\n        grads2.forEach((grad2, i2) => {\n          gradMap[i2] = () => grad2;\n        });\n        return gradMap;\n      };\n      return this.runKernelFunc({\n        forwardFunc,\n        backwardsFunc,\n        inputs: inputMap\n      });\n    };\n  }\n  readSync(dataId) {\n    const info = this.state.tensorInfo.get(dataId);\n    return info.backend.readSync(dataId);\n  }\n  read(dataId) {\n    const info = this.state.tensorInfo.get(dataId);\n    return info.backend.read(dataId);\n  }\n  readToGPU(dataId, options) {\n    const info = this.state.tensorInfo.get(dataId);\n    return info.backend.readToGPU(dataId, options);\n  }\n  async time(query) {\n    const start = now();\n    const timingInfo = await this.backend.time(query);\n    timingInfo.wallMs = now() - start;\n    return timingInfo;\n  }\n  track(result) {\n    if (this.state.activeScope != null) {\n      result.scopeId = this.state.activeScope.id;\n      this.state.activeScope.track.push(result);\n    }\n    return result;\n  }\n  get registeredVariables() {\n    return this.state.registeredVariables;\n  }\n  reset() {\n    this.pendingBackendInitId++;\n    this.state.dispose();\n    this.ENV.reset();\n    this.state = new EngineState();\n    for (const backendName in this.registry) {\n      this.disposeRegisteredKernels(backendName);\n      this.registry[backendName].dispose();\n      delete this.registry[backendName];\n    }\n    this.backendName = null;\n    this.backendInstance = null;\n    this.pendingBackendInit = null;\n  }\n};\nEngine.nextTensorId = 0;\nEngine.nextVariableId = 0;\nfunction ones(shape) {\n  const values = makeOnesTypedArray(sizeFromShape(shape), \"float32\");\n  return ENGINE.makeTensor(values, shape, \"float32\");\n}\nfunction getOrMakeEngine() {\n  const ns = getGlobalNamespace();\n  if (ns._tfengine == null) {\n    const environment = new Environment(ns);\n    ns._tfengine = new Engine(environment);\n  }\n  setEnvironmentGlobal(ns._tfengine.ENV);\n  setTensorTracker(() => ns._tfengine);\n  return ns._tfengine;\n}\nvar ENGINE = getOrMakeEngine();\nfunction add(a, b) {\n  const inputs = { a, b };\n  return ENGINE.runKernel(Add, inputs);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/device_util.js\nvar device_util_exports = {};\n__export(device_util_exports, {\n  isBrowser: () => isBrowser,\n  isMobile: () => isMobile,\n  mockIsMobile: () => mockIsMobile\n});\nfunction _isNavigatorDefined() {\n  return typeof navigator !== \"undefined\" && navigator != null;\n}\nvar isMobileMockValue;\nfunction mockIsMobile(value) {\n  isMobileMockValue = value;\n}\nfunction isMobile(nav) {\n  if (isMobileMockValue !== void 0) {\n    return isMobileMockValue;\n  }\n  if (nav || _isNavigatorDefined()) {\n    if (!nav) {\n      nav = navigator;\n    }\n    if (nav.product === \"ReactNative\") {\n      return true;\n    }\n    const a = nav.userAgent || nav.vendor || (typeof window !== \"undefined\" ? window.opera : \"\");\n    if (!a) {\n      const navAny = nav;\n      return navAny.userAgentData && navAny.userAgentData.mobile;\n    }\n    return /(android|bb\\d+|meego).+mobile|avantgo|bada\\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i.test(a) || /1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\\-(n|u)|c55\\/|capi|ccwa|cdm\\-|cell|chtm|cldc|cmd\\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\\-s|devi|dica|dmob|do(c|p)o|ds(12|\\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\\-|_)|g1 u|g560|gene|gf\\-5|g\\-mo|go(\\.w|od)|gr(ad|un)|haie|hcit|hd\\-(m|p|t)|hei\\-|hi(pt|ta)|hp( i|ip)|hs\\-c|ht(c(\\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\\-(20|go|ma)|i230|iac( |\\-|\\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\\/)|klon|kpt |kwc\\-|kyo(c|k)|le(no|xi)|lg( g|\\/(k|l|u)|50|54|\\-[a-w])|libw|lynx|m1\\-w|m3ga|m50\\/|ma(te|ui|xo)|mc(01|21|ca)|m\\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\\-2|po(ck|rt|se)|prox|psio|pt\\-g|qa\\-a|qc(07|12|21|32|60|\\-[2-7]|i\\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\\-|oo|p\\-)|sdk\\/|se(c(\\-|0|1)|47|mc|nd|ri)|sgh\\-|shar|sie(\\-|m)|sk\\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\\-|v\\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\\-|tdg\\-|tel(i|m)|tim\\-|t\\-mo|to(pl|sh)|ts(70|m\\-|m3|m5)|tx\\-9|up(\\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\\-|your|zeto|zte\\-/i.test(a.substr(0, 4));\n  }\n  return false;\n}\nfunction isBrowser() {\n  return typeof window !== \"undefined\" && window.document != null || typeof WorkerGlobalScope !== \"undefined\";\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/flags.js\nvar ENV2 = env();\nENV2.registerFlag(\"DEBUG\", () => false, (debugValue) => {\n  if (debugValue) {\n    console.warn(\"Debugging mode is ON. The output of every math call will be downloaded to CPU and checked for NaNs. This significantly impacts performance.\");\n  }\n});\nENV2.registerFlag(\"IS_BROWSER\", () => isBrowser());\nENV2.registerFlag(\"IS_NODE\", () => typeof process !== \"undefined\" && typeof process.versions !== \"undefined\" && typeof process.versions.node !== \"undefined\");\nENV2.registerFlag(\"IS_CHROME\", () => typeof navigator !== \"undefined\" && navigator != null && navigator.userAgent != null && /Chrome/.test(navigator.userAgent) && /Google Inc/.test(navigator.vendor));\nENV2.registerFlag(\"PROD\", () => false);\nENV2.registerFlag(\"TENSORLIKE_CHECK_SHAPE_CONSISTENCY\", () => ENV2.getBool(\"DEBUG\"));\nENV2.registerFlag(\"DEPRECATION_WARNINGS_ENABLED\", () => true);\nENV2.registerFlag(\"IS_TEST\", () => false);\nENV2.registerFlag(\"CHECK_COMPUTATION_FOR_ERRORS\", () => true);\nENV2.registerFlag(\"WRAP_TO_IMAGEBITMAP\", () => false);\nENV2.registerFlag(\"ENGINE_COMPILE_ONLY\", () => false);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/tensor_util_env.js\nfunction inferShape(val, dtype) {\n  let firstElem = val;\n  if (isTypedArray(val)) {\n    return dtype === \"string\" ? [] : [val.length];\n  }\n  if (!Array.isArray(val)) {\n    return [];\n  }\n  const shape = [];\n  while (Array.isArray(firstElem) || isTypedArray(firstElem) && dtype !== \"string\") {\n    shape.push(firstElem.length);\n    firstElem = firstElem[0];\n  }\n  if (Array.isArray(val) && env().getBool(\"TENSORLIKE_CHECK_SHAPE_CONSISTENCY\")) {\n    deepAssertShapeConsistency(val, shape, []);\n  }\n  return shape;\n}\nfunction deepAssertShapeConsistency(val, shape, indices) {\n  indices = indices || [];\n  if (!Array.isArray(val) && !isTypedArray(val)) {\n    assert(shape.length === 0, () => `Element arr[${indices.join(\"][\")}] is a primitive, but should be an array/TypedArray of ${shape[0]} elements`);\n    return;\n  }\n  assert(shape.length > 0, () => `Element arr[${indices.join(\"][\")}] should be a primitive, but is an array of ${val.length} elements`);\n  assert(val.length === shape[0], () => `Element arr[${indices.join(\"][\")}] should have ${shape[0]} elements, but has ${val.length} elements`);\n  const subShape = shape.slice(1);\n  for (let i2 = 0; i2 < val.length; ++i2) {\n    deepAssertShapeConsistency(val[i2], subShape, indices.concat(i2));\n  }\n}\nfunction assertDtype(expectedDtype, actualDType, argName, functionName) {\n  if (expectedDtype === \"string_or_numeric\") {\n    return;\n  }\n  if (expectedDtype == null) {\n    throw new Error(`Expected dtype cannot be null.`);\n  }\n  if (expectedDtype !== \"numeric\" && expectedDtype !== actualDType || expectedDtype === \"numeric\" && actualDType === \"string\") {\n    throw new Error(`Argument '${argName}' passed to '${functionName}' must be ${expectedDtype} tensor, but got ${actualDType} tensor`);\n  }\n}\nfunction convertToTensor(x, argName, functionName, parseAsDtype = \"numeric\") {\n  if (x instanceof Tensor) {\n    assertDtype(parseAsDtype, x.dtype, argName, functionName);\n    return x;\n  }\n  let inferredDtype = inferDtype(x);\n  if (inferredDtype !== \"string\" && [\"bool\", \"int32\", \"float32\"].indexOf(parseAsDtype) >= 0) {\n    inferredDtype = parseAsDtype;\n  }\n  assertDtype(parseAsDtype, inferredDtype, argName, functionName);\n  if (x == null || !isTypedArray(x) && !Array.isArray(x) && typeof x !== \"number\" && typeof x !== \"boolean\" && typeof x !== \"string\") {\n    const type = x == null ? \"null\" : x.constructor.name;\n    throw new Error(`Argument '${argName}' passed to '${functionName}' must be a Tensor or TensorLike, but got '${type}'`);\n  }\n  const inferredShape = inferShape(x, inferredDtype);\n  if (!isTypedArray(x) && !Array.isArray(x)) {\n    x = [x];\n  }\n  const skipTypedArray = true;\n  const values = inferredDtype !== \"string\" ? toTypedArray(x, inferredDtype) : flatten(x, [], skipTypedArray);\n  return ENGINE.makeTensor(values, inferredShape, inferredDtype);\n}\nfunction convertToTensorArray(arg, argName, functionName, parseAsDtype = \"numeric\") {\n  if (!Array.isArray(arg)) {\n    throw new Error(`Argument ${argName} passed to ${functionName} must be a \\`Tensor[]\\` or \\`TensorLike[]\\``);\n  }\n  const tensors = arg;\n  return tensors.map((t2, i2) => convertToTensor(t2, `${argName}[${i2}]`, functionName, parseAsDtype));\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/operation.js\nvar OP_SCOPE_SUFFIX = \"__op\";\nfunction op(f) {\n  const keys = Object.keys(f);\n  if (keys.length !== 1) {\n    throw new Error(`Please provide an object with a single key (operation name) mapping to a function. Got an object with ${keys.length} keys.`);\n  }\n  let opName = keys[0];\n  const fn = f[opName];\n  if (opName.endsWith(\"_\")) {\n    opName = opName.substring(0, opName.length - 1);\n  }\n  opName = opName + OP_SCOPE_SUFFIX;\n  const f2 = (...args) => {\n    ENGINE.startScope(opName);\n    try {\n      const result = fn(...args);\n      if (isPromise(result)) {\n        console.error(\"Cannot return a Promise inside of tidy.\");\n      }\n      ENGINE.endScope(result);\n      return result;\n    } catch (ex) {\n      ENGINE.endScope(null);\n      throw ex;\n    }\n  };\n  Object.defineProperty(f2, \"name\", { value: opName, configurable: true });\n  return f2;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/complex.js\nfunction complex_(real5, imag5) {\n  const $real = convertToTensor(real5, \"real\", \"complex\");\n  const $imag = convertToTensor(imag5, \"imag\", \"complex\");\n  assertShapesMatch($real.shape, $imag.shape, `real and imag shapes, ${$real.shape} and ${$imag.shape}, must match in call to tf.complex().`);\n  const inputs = { real: $real, imag: $imag };\n  return ENGINE.runKernel(Complex, inputs);\n}\nvar complex = op({ complex_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor_ops_util.js\nfunction makeTensor(values, shape, inferredShape, dtype) {\n  if (dtype == null) {\n    dtype = inferDtype(values);\n  }\n  if (dtype === \"complex64\") {\n    throw new Error(`Cannot construct a complex64 tensor directly. Please use tf.complex(real, imag).`);\n  }\n  if (!isTypedArray(values) && !Array.isArray(values) && typeof values !== \"number\" && typeof values !== \"boolean\" && typeof values !== \"string\") {\n    throw new Error(\"values passed to tensor(values) must be a number/boolean/string or an array of numbers/booleans/strings, or a TypedArray\");\n  }\n  if (shape != null) {\n    assertNonNegativeIntegerDimensions(shape);\n    const providedSize = sizeFromShape(shape);\n    const inferredSize = sizeFromShape(inferredShape);\n    assert(providedSize === inferredSize, () => `Based on the provided shape, [${shape}], the tensor should have ${providedSize} values but has ${inferredSize}`);\n    for (let i2 = 0; i2 < inferredShape.length; ++i2) {\n      const inferred = inferredShape[i2];\n      const flatDimsDontMatch = i2 === inferredShape.length - 1 ? inferred !== sizeFromShape(shape.slice(i2)) : true;\n      assert(inferredShape[i2] === shape[i2] || !flatDimsDontMatch, () => `Error creating a new Tensor. Inferred shape (${inferredShape}) does not match the provided shape (${shape}). `);\n    }\n  }\n  if (!isTypedArray(values) && !Array.isArray(values)) {\n    values = [values];\n  }\n  shape = shape || inferredShape;\n  values = dtype !== \"string\" ? toTypedArray(values, dtype) : flatten(values, [], true);\n  return ENGINE.makeTensor(values, shape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor.js\nfunction tensor(values, shape, dtype) {\n  const inferredShape = inferShape(values, dtype);\n  return makeTensor(values, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/types.js\nvar DTYPE_VALUE_SIZE_MAP = {\n  \"float32\": 4,\n  \"float16\": 2,\n  \"int32\": 4,\n  \"uint16\": 2,\n  \"uint8\": 1,\n  \"bool\": 1,\n  \"complex64\": 8\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/io_utils.js\nvar NUM_BYTES_STRING_LENGTH = 4;\nasync function encodeWeights(tensors, group) {\n  const specs = [];\n  const dataPromises = [];\n  const names = Array.isArray(tensors) ? tensors.map((tensor2) => tensor2.name) : Object.keys(tensors);\n  for (let i2 = 0; i2 < names.length; ++i2) {\n    const name = names[i2];\n    const t2 = Array.isArray(tensors) ? tensors[i2].tensor : tensors[name];\n    if (t2.dtype !== \"float32\" && t2.dtype !== \"int32\" && t2.dtype !== \"bool\" && t2.dtype !== \"string\" && t2.dtype !== \"complex64\") {\n      throw new Error(`Unsupported dtype in weight '${name}': ${t2.dtype}`);\n    }\n    const spec = { name, shape: t2.shape, dtype: t2.dtype };\n    if (t2.dtype === \"string\") {\n      const utf8bytes = new Promise(async (resolve) => {\n        const vals = await t2.bytes();\n        const totalNumBytes = vals.reduce((p2, c) => p2 + c.length, 0) + NUM_BYTES_STRING_LENGTH * vals.length;\n        const bytes = new Uint8Array(totalNumBytes);\n        let offset = 0;\n        for (let i3 = 0; i3 < vals.length; i3++) {\n          const val = vals[i3];\n          const bytesOfLength = new Uint8Array(new Uint32Array([val.length]).buffer);\n          bytes.set(bytesOfLength, offset);\n          offset += NUM_BYTES_STRING_LENGTH;\n          bytes.set(val, offset);\n          offset += val.length;\n        }\n        resolve(bytes);\n      });\n      dataPromises.push(utf8bytes);\n    } else {\n      dataPromises.push(t2.data());\n    }\n    if (group != null) {\n      spec.group = group;\n    }\n    specs.push(spec);\n  }\n  const tensorValues = await Promise.all(dataPromises);\n  return { data: concatenateTypedArrays(tensorValues), specs };\n}\nfunction decodeWeights(buffer2, specs) {\n  const out = {};\n  let float16Decode;\n  let offset = 0;\n  for (const spec of specs) {\n    const name = spec.name;\n    const dtype = spec.dtype;\n    const shape = spec.shape;\n    const size = sizeFromShape(shape);\n    let values;\n    if (\"quantization\" in spec) {\n      const quantization = spec.quantization;\n      if (quantization.dtype === \"uint8\" || quantization.dtype === \"uint16\") {\n        if (!(\"min\" in quantization && \"scale\" in quantization)) {\n          throw new Error(`Weight ${spec.name} with quantization ${quantization.dtype} doesn't have corresponding metadata min and scale.`);\n        }\n      } else if (quantization.dtype === \"float16\") {\n        if (dtype !== \"float32\") {\n          throw new Error(`Weight ${spec.name} is quantized with ${quantization.dtype} which only supports weights of type float32 not ${dtype}.`);\n        }\n      } else {\n        throw new Error(`Weight ${spec.name} has unknown quantization dtype ${quantization.dtype}. Supported quantization dtypes are: 'uint8', 'uint16', and 'float16'.`);\n      }\n      const quantizationSizeFactor = DTYPE_VALUE_SIZE_MAP[quantization.dtype];\n      const byteBuffer = buffer2.slice(offset, offset + size * quantizationSizeFactor);\n      const quantizedArray = quantization.dtype === \"uint8\" ? new Uint8Array(byteBuffer) : new Uint16Array(byteBuffer);\n      if (dtype === \"float32\") {\n        if (quantization.dtype === \"uint8\" || quantization.dtype === \"uint16\") {\n          values = new Float32Array(quantizedArray.length);\n          for (let i2 = 0; i2 < quantizedArray.length; i2++) {\n            const v = quantizedArray[i2];\n            values[i2] = v * quantization.scale + quantization.min;\n          }\n        } else if (quantization.dtype === \"float16\") {\n          if (float16Decode === void 0) {\n            float16Decode = getFloat16Decoder();\n          }\n          values = float16Decode(quantizedArray);\n        } else {\n          throw new Error(`Unsupported quantization type ${quantization.dtype} for weight type float32.`);\n        }\n      } else if (dtype === \"int32\") {\n        if (quantization.dtype !== \"uint8\" && quantization.dtype !== \"uint16\") {\n          throw new Error(`Unsupported quantization type ${quantization.dtype} for weight type int32.`);\n        }\n        values = new Int32Array(quantizedArray.length);\n        for (let i2 = 0; i2 < quantizedArray.length; i2++) {\n          const v = quantizedArray[i2];\n          values[i2] = Math.round(v * quantization.scale + quantization.min);\n        }\n      } else {\n        throw new Error(`Unsupported dtype in weight '${name}': ${dtype}`);\n      }\n      offset += size * quantizationSizeFactor;\n    } else if (dtype === \"string\") {\n      const size2 = sizeFromShape(spec.shape);\n      values = [];\n      for (let i2 = 0; i2 < size2; i2++) {\n        const byteLength = new Uint32Array(buffer2.slice(offset, offset + NUM_BYTES_STRING_LENGTH))[0];\n        offset += NUM_BYTES_STRING_LENGTH;\n        const bytes = new Uint8Array(buffer2.slice(offset, offset + byteLength));\n        values.push(bytes);\n        offset += byteLength;\n      }\n    } else {\n      const dtypeFactor = DTYPE_VALUE_SIZE_MAP[dtype];\n      const byteBuffer = buffer2.slice(offset, offset + size * dtypeFactor);\n      if (dtype === \"float32\") {\n        values = new Float32Array(byteBuffer);\n      } else if (dtype === \"int32\") {\n        values = new Int32Array(byteBuffer);\n      } else if (dtype === \"bool\") {\n        values = new Uint8Array(byteBuffer);\n      } else if (dtype === \"complex64\") {\n        values = new Float32Array(byteBuffer);\n        const real5 = new Float32Array(values.length / 2);\n        const image2 = new Float32Array(values.length / 2);\n        for (let i2 = 0; i2 < real5.length; i2++) {\n          real5[i2] = values[i2 * 2];\n          image2[i2] = values[i2 * 2 + 1];\n        }\n        const realTensor = tensor(real5, shape, \"float32\");\n        const imageTensor = tensor(image2, shape, \"float32\");\n        out[name] = complex(realTensor, imageTensor);\n        realTensor.dispose();\n        imageTensor.dispose();\n      } else {\n        throw new Error(`Unsupported dtype in weight '${name}': ${dtype}`);\n      }\n      offset += size * dtypeFactor;\n    }\n    if (dtype !== \"complex64\") {\n      out[name] = tensor(values, shape, dtype);\n    }\n  }\n  return out;\n}\nfunction concatenateTypedArrays(xs) {\n  if (xs === null) {\n    throw new Error(`Invalid input value: ${JSON.stringify(xs)}`);\n  }\n  let totalByteLength = 0;\n  const normalizedXs = [];\n  xs.forEach((x) => {\n    totalByteLength += x.byteLength;\n    normalizedXs.push(x.byteLength === x.buffer.byteLength ? x : new x.constructor(x));\n    if (!(x instanceof Float32Array || x instanceof Int32Array || x instanceof Uint8Array)) {\n      throw new Error(`Unsupported TypedArray subtype: ${x.constructor.name}`);\n    }\n  });\n  const y = new Uint8Array(totalByteLength);\n  let offset = 0;\n  normalizedXs.forEach((x) => {\n    y.set(new Uint8Array(x.buffer), offset);\n    offset += x.byteLength;\n  });\n  return y.buffer;\n}\nvar useNodeBuffer = typeof Buffer !== \"undefined\" && (typeof Blob === \"undefined\" || typeof atob === \"undefined\" || typeof btoa === \"undefined\");\nfunction stringByteLength(str) {\n  if (useNodeBuffer) {\n    return Buffer.byteLength(str);\n  }\n  return new Blob([str]).size;\n}\nfunction arrayBufferToBase64String(buffer2) {\n  if (useNodeBuffer) {\n    return Buffer.from(buffer2).toString(\"base64\");\n  }\n  const buf = new Uint8Array(buffer2);\n  let s2 = \"\";\n  for (let i2 = 0, l3 = buf.length; i2 < l3; i2++) {\n    s2 += String.fromCharCode(buf[i2]);\n  }\n  return btoa(s2);\n}\nfunction base64StringToArrayBuffer(str) {\n  if (useNodeBuffer) {\n    const buf = Buffer.from(str, \"base64\");\n    return buf.buffer.slice(buf.byteOffset, buf.byteOffset + buf.byteLength);\n  }\n  const s2 = atob(str);\n  const buffer2 = new Uint8Array(s2.length);\n  for (let i2 = 0; i2 < s2.length; ++i2) {\n    buffer2.set([s2.charCodeAt(i2)], i2);\n  }\n  return buffer2.buffer;\n}\nfunction concatenateArrayBuffers(buffers) {\n  if (buffers.length === 1) {\n    return buffers[0];\n  }\n  let totalByteLength = 0;\n  buffers.forEach((buffer2) => {\n    totalByteLength += buffer2.byteLength;\n  });\n  const temp = new Uint8Array(totalByteLength);\n  let offset = 0;\n  buffers.forEach((buffer2) => {\n    temp.set(new Uint8Array(buffer2), offset);\n    offset += buffer2.byteLength;\n  });\n  return temp.buffer;\n}\nfunction basename(path) {\n  const SEPARATOR = \"/\";\n  path = path.trim();\n  while (path.endsWith(SEPARATOR)) {\n    path = path.slice(0, path.length - 1);\n  }\n  const items = path.split(SEPARATOR);\n  return items[items.length - 1];\n}\nfunction getModelJSONForModelArtifacts(artifacts, manifest) {\n  const result = {\n    modelTopology: artifacts.modelTopology,\n    format: artifacts.format,\n    generatedBy: artifacts.generatedBy,\n    convertedBy: artifacts.convertedBy,\n    weightsManifest: manifest\n  };\n  if (artifacts.signature != null) {\n    result.signature = artifacts.signature;\n  }\n  if (artifacts.userDefinedMetadata != null) {\n    result.userDefinedMetadata = artifacts.userDefinedMetadata;\n  }\n  if (artifacts.modelInitializer != null) {\n    result.modelInitializer = artifacts.modelInitializer;\n  }\n  if (artifacts.trainingConfig != null) {\n    result.trainingConfig = artifacts.trainingConfig;\n  }\n  return result;\n}\nasync function getModelArtifactsForJSON(modelJSON, loadWeights2) {\n  const modelArtifacts = {\n    modelTopology: modelJSON.modelTopology,\n    format: modelJSON.format,\n    generatedBy: modelJSON.generatedBy,\n    convertedBy: modelJSON.convertedBy\n  };\n  if (modelJSON.trainingConfig != null) {\n    modelArtifacts.trainingConfig = modelJSON.trainingConfig;\n  }\n  if (modelJSON.weightsManifest != null) {\n    const [weightSpecs, weightData] = await loadWeights2(modelJSON.weightsManifest);\n    modelArtifacts.weightSpecs = weightSpecs;\n    modelArtifacts.weightData = weightData;\n  }\n  if (modelJSON.signature != null) {\n    modelArtifacts.signature = modelJSON.signature;\n  }\n  if (modelJSON.userDefinedMetadata != null) {\n    modelArtifacts.userDefinedMetadata = modelJSON.userDefinedMetadata;\n  }\n  if (modelJSON.modelInitializer != null) {\n    modelArtifacts.modelInitializer = modelJSON.modelInitializer;\n  }\n  return modelArtifacts;\n}\nfunction getModelArtifactsInfoForJSON(modelArtifacts) {\n  if (modelArtifacts.modelTopology instanceof ArrayBuffer) {\n    throw new Error(\"Expected JSON model topology, received ArrayBuffer.\");\n  }\n  return {\n    dateSaved: new Date(),\n    modelTopologyType: \"JSON\",\n    modelTopologyBytes: modelArtifacts.modelTopology == null ? 0 : stringByteLength(JSON.stringify(modelArtifacts.modelTopology)),\n    weightSpecsBytes: modelArtifacts.weightSpecs == null ? 0 : stringByteLength(JSON.stringify(modelArtifacts.weightSpecs)),\n    weightDataBytes: modelArtifacts.weightData == null ? 0 : modelArtifacts.weightData.byteLength\n  };\n}\nfunction computeFloat16MantisaTable() {\n  const convertMantissa = (i2) => {\n    let m = i2 << 13;\n    let e2 = 0;\n    while ((m & 8388608) === 0) {\n      e2 -= 8388608;\n      m <<= 1;\n    }\n    m &= ~8388608;\n    e2 += 947912704;\n    return m | e2;\n  };\n  const mantisaTable = new Uint32Array(2048);\n  mantisaTable[0] = 0;\n  for (let i2 = 1; i2 < 1024; i2++) {\n    mantisaTable[i2] = convertMantissa(i2);\n  }\n  for (let i2 = 1024; i2 < 2048; i2++) {\n    mantisaTable[i2] = 939524096 + (i2 - 1024 << 13);\n  }\n  return mantisaTable;\n}\nfunction computeFloat16ExponentTable() {\n  const exponentTable = new Uint32Array(64);\n  exponentTable[0] = 0;\n  exponentTable[31] = 1199570944;\n  exponentTable[32] = 2147483648;\n  exponentTable[63] = 3347054592;\n  for (let i2 = 1; i2 < 31; i2++) {\n    exponentTable[i2] = i2 << 23;\n  }\n  for (let i2 = 33; i2 < 63; i2++) {\n    exponentTable[i2] = 2147483648 + (i2 - 32 << 23);\n  }\n  return exponentTable;\n}\nfunction computeFloat16OffsetTable() {\n  const offsetTable = new Uint32Array(64);\n  for (let i2 = 0; i2 < 64; i2++) {\n    offsetTable[i2] = 1024;\n  }\n  offsetTable[0] = offsetTable[32] = 0;\n  return offsetTable;\n}\nfunction getFloat16Decoder() {\n  const mantisaTable = computeFloat16MantisaTable();\n  const exponentTable = computeFloat16ExponentTable();\n  const offsetTable = computeFloat16OffsetTable();\n  return (quantizedArray) => {\n    const buffer2 = new ArrayBuffer(4 * quantizedArray.length);\n    const bufferUint32View = new Uint32Array(buffer2);\n    for (let index = 0; index < quantizedArray.length; index++) {\n      const float16Bits = quantizedArray[index];\n      const float32Bits = mantisaTable[offsetTable[float16Bits >> 10] + (float16Bits & 1023)] + exponentTable[float16Bits >> 10];\n      bufferUint32View[index] = float32Bits;\n    }\n    return new Float32Array(buffer2);\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/router_registry.js\nvar IORouterRegistry = class {\n  constructor() {\n    this.saveRouters = [];\n    this.loadRouters = [];\n  }\n  static getInstance() {\n    if (IORouterRegistry.instance == null) {\n      IORouterRegistry.instance = new IORouterRegistry();\n    }\n    return IORouterRegistry.instance;\n  }\n  static registerSaveRouter(saveRouter) {\n    IORouterRegistry.getInstance().saveRouters.push(saveRouter);\n  }\n  static registerLoadRouter(loadRouter) {\n    IORouterRegistry.getInstance().loadRouters.push(loadRouter);\n  }\n  static getSaveHandlers(url) {\n    return IORouterRegistry.getHandlers(url, \"save\");\n  }\n  static getLoadHandlers(url, loadOptions) {\n    return IORouterRegistry.getHandlers(url, \"load\", loadOptions);\n  }\n  static getHandlers(url, handlerType, loadOptions) {\n    const validHandlers = [];\n    const routers = handlerType === \"load\" ? IORouterRegistry.getInstance().loadRouters : IORouterRegistry.getInstance().saveRouters;\n    routers.forEach((router) => {\n      const handler = router(url, loadOptions);\n      if (handler !== null) {\n        validHandlers.push(handler);\n      }\n    });\n    return validHandlers;\n  }\n};\nvar registerSaveRouter = (loudRouter) => IORouterRegistry.registerSaveRouter(loudRouter);\nvar registerLoadRouter = (loudRouter) => IORouterRegistry.registerLoadRouter(loudRouter);\nvar getSaveHandlers = (url) => IORouterRegistry.getSaveHandlers(url);\nvar getLoadHandlers = (url, loadOptions) => IORouterRegistry.getLoadHandlers(url, loadOptions);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/indexed_db.js\nvar DATABASE_NAME = \"tensorflowjs\";\nvar DATABASE_VERSION = 1;\nvar MODEL_STORE_NAME = \"models_store\";\nvar INFO_STORE_NAME = \"model_info_store\";\nfunction getIndexedDBFactory() {\n  if (!env().getBool(\"IS_BROWSER\")) {\n    throw new Error(\"Failed to obtain IndexedDB factory because the current environmentis not a web browser.\");\n  }\n  const theWindow = typeof window === \"undefined\" ? self : window;\n  const factory = theWindow.indexedDB || theWindow.mozIndexedDB || theWindow.webkitIndexedDB || theWindow.msIndexedDB || theWindow.shimIndexedDB;\n  if (factory == null) {\n    throw new Error(\"The current browser does not appear to support IndexedDB.\");\n  }\n  return factory;\n}\nfunction setUpDatabase(openRequest) {\n  const db = openRequest.result;\n  db.createObjectStore(MODEL_STORE_NAME, { keyPath: \"modelPath\" });\n  db.createObjectStore(INFO_STORE_NAME, { keyPath: \"modelPath\" });\n}\nvar BrowserIndexedDB = class {\n  constructor(modelPath) {\n    this.indexedDB = getIndexedDBFactory();\n    if (modelPath == null || !modelPath) {\n      throw new Error(\"For IndexedDB, modelPath must not be null, undefined or empty.\");\n    }\n    this.modelPath = modelPath;\n  }\n  async save(modelArtifacts) {\n    if (modelArtifacts.modelTopology instanceof ArrayBuffer) {\n      throw new Error(\"BrowserLocalStorage.save() does not support saving model topology in binary formats yet.\");\n    }\n    return this.databaseAction(this.modelPath, modelArtifacts);\n  }\n  async load() {\n    return this.databaseAction(this.modelPath);\n  }\n  databaseAction(modelPath, modelArtifacts) {\n    return new Promise((resolve, reject) => {\n      const openRequest = this.indexedDB.open(DATABASE_NAME, DATABASE_VERSION);\n      openRequest.onupgradeneeded = () => setUpDatabase(openRequest);\n      openRequest.onsuccess = () => {\n        const db = openRequest.result;\n        if (modelArtifacts == null) {\n          const modelTx = db.transaction(MODEL_STORE_NAME, \"readonly\");\n          const modelStore = modelTx.objectStore(MODEL_STORE_NAME);\n          const getRequest = modelStore.get(this.modelPath);\n          getRequest.onsuccess = () => {\n            if (getRequest.result == null) {\n              db.close();\n              return reject(new Error(`Cannot find model with path '${this.modelPath}' in IndexedDB.`));\n            } else {\n              resolve(getRequest.result.modelArtifacts);\n            }\n          };\n          getRequest.onerror = (error) => {\n            db.close();\n            return reject(getRequest.error);\n          };\n          modelTx.oncomplete = () => db.close();\n        } else {\n          const modelArtifactsInfo = getModelArtifactsInfoForJSON(modelArtifacts);\n          const infoTx = db.transaction(INFO_STORE_NAME, \"readwrite\");\n          let infoStore = infoTx.objectStore(INFO_STORE_NAME);\n          const putInfoRequest = infoStore.put({ modelPath: this.modelPath, modelArtifactsInfo });\n          let modelTx;\n          putInfoRequest.onsuccess = () => {\n            modelTx = db.transaction(MODEL_STORE_NAME, \"readwrite\");\n            const modelStore = modelTx.objectStore(MODEL_STORE_NAME);\n            const putModelRequest = modelStore.put({\n              modelPath: this.modelPath,\n              modelArtifacts,\n              modelArtifactsInfo\n            });\n            putModelRequest.onsuccess = () => resolve({ modelArtifactsInfo });\n            putModelRequest.onerror = (error) => {\n              infoStore = infoTx.objectStore(INFO_STORE_NAME);\n              const deleteInfoRequest = infoStore.delete(this.modelPath);\n              deleteInfoRequest.onsuccess = () => {\n                db.close();\n                return reject(putModelRequest.error);\n              };\n              deleteInfoRequest.onerror = (error2) => {\n                db.close();\n                return reject(putModelRequest.error);\n              };\n            };\n          };\n          putInfoRequest.onerror = (error) => {\n            db.close();\n            return reject(putInfoRequest.error);\n          };\n          infoTx.oncomplete = () => {\n            if (modelTx == null) {\n              db.close();\n            } else {\n              modelTx.oncomplete = () => db.close();\n            }\n          };\n        }\n      };\n      openRequest.onerror = (error) => reject(openRequest.error);\n    });\n  }\n};\nBrowserIndexedDB.URL_SCHEME = \"indexeddb://\";\nvar indexedDBRouter = (url) => {\n  if (!env().getBool(\"IS_BROWSER\")) {\n    return null;\n  } else {\n    if (!Array.isArray(url) && url.startsWith(BrowserIndexedDB.URL_SCHEME)) {\n      return browserIndexedDB(url.slice(BrowserIndexedDB.URL_SCHEME.length));\n    } else {\n      return null;\n    }\n  }\n};\nIORouterRegistry.registerSaveRouter(indexedDBRouter);\nIORouterRegistry.registerLoadRouter(indexedDBRouter);\nfunction browserIndexedDB(modelPath) {\n  return new BrowserIndexedDB(modelPath);\n}\nfunction maybeStripScheme(key) {\n  return key.startsWith(BrowserIndexedDB.URL_SCHEME) ? key.slice(BrowserIndexedDB.URL_SCHEME.length) : key;\n}\nvar BrowserIndexedDBManager = class {\n  constructor() {\n    this.indexedDB = getIndexedDBFactory();\n  }\n  async listModels() {\n    return new Promise((resolve, reject) => {\n      const openRequest = this.indexedDB.open(DATABASE_NAME, DATABASE_VERSION);\n      openRequest.onupgradeneeded = () => setUpDatabase(openRequest);\n      openRequest.onsuccess = () => {\n        const db = openRequest.result;\n        const tx = db.transaction(INFO_STORE_NAME, \"readonly\");\n        const store = tx.objectStore(INFO_STORE_NAME);\n        const getAllInfoRequest = store.getAll();\n        getAllInfoRequest.onsuccess = () => {\n          const out = {};\n          for (const item of getAllInfoRequest.result) {\n            out[item.modelPath] = item.modelArtifactsInfo;\n          }\n          resolve(out);\n        };\n        getAllInfoRequest.onerror = (error) => {\n          db.close();\n          return reject(getAllInfoRequest.error);\n        };\n        tx.oncomplete = () => db.close();\n      };\n      openRequest.onerror = (error) => reject(openRequest.error);\n    });\n  }\n  async removeModel(path) {\n    path = maybeStripScheme(path);\n    return new Promise((resolve, reject) => {\n      const openRequest = this.indexedDB.open(DATABASE_NAME, DATABASE_VERSION);\n      openRequest.onupgradeneeded = () => setUpDatabase(openRequest);\n      openRequest.onsuccess = () => {\n        const db = openRequest.result;\n        const infoTx = db.transaction(INFO_STORE_NAME, \"readwrite\");\n        const infoStore = infoTx.objectStore(INFO_STORE_NAME);\n        const getInfoRequest = infoStore.get(path);\n        let modelTx;\n        getInfoRequest.onsuccess = () => {\n          if (getInfoRequest.result == null) {\n            db.close();\n            return reject(new Error(`Cannot find model with path '${path}' in IndexedDB.`));\n          } else {\n            const deleteInfoRequest = infoStore.delete(path);\n            const deleteModelData = () => {\n              modelTx = db.transaction(MODEL_STORE_NAME, \"readwrite\");\n              const modelStore = modelTx.objectStore(MODEL_STORE_NAME);\n              const deleteModelRequest = modelStore.delete(path);\n              deleteModelRequest.onsuccess = () => resolve(getInfoRequest.result.modelArtifactsInfo);\n              deleteModelRequest.onerror = (error) => reject(getInfoRequest.error);\n            };\n            deleteInfoRequest.onsuccess = deleteModelData;\n            deleteInfoRequest.onerror = (error) => {\n              deleteModelData();\n              db.close();\n              return reject(getInfoRequest.error);\n            };\n          }\n        };\n        getInfoRequest.onerror = (error) => {\n          db.close();\n          return reject(getInfoRequest.error);\n        };\n        infoTx.oncomplete = () => {\n          if (modelTx == null) {\n            db.close();\n          } else {\n            modelTx.oncomplete = () => db.close();\n          }\n        };\n      };\n      openRequest.onerror = (error) => reject(openRequest.error);\n    });\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/local_storage.js\nvar PATH_SEPARATOR = \"/\";\nvar PATH_PREFIX = \"tensorflowjs_models\";\nvar INFO_SUFFIX = \"info\";\nvar MODEL_TOPOLOGY_SUFFIX = \"model_topology\";\nvar WEIGHT_SPECS_SUFFIX = \"weight_specs\";\nvar WEIGHT_DATA_SUFFIX = \"weight_data\";\nvar MODEL_METADATA_SUFFIX = \"model_metadata\";\nfunction getModelKeys(path) {\n  return {\n    info: [PATH_PREFIX, path, INFO_SUFFIX].join(PATH_SEPARATOR),\n    topology: [PATH_PREFIX, path, MODEL_TOPOLOGY_SUFFIX].join(PATH_SEPARATOR),\n    weightSpecs: [PATH_PREFIX, path, WEIGHT_SPECS_SUFFIX].join(PATH_SEPARATOR),\n    weightData: [PATH_PREFIX, path, WEIGHT_DATA_SUFFIX].join(PATH_SEPARATOR),\n    modelMetadata: [PATH_PREFIX, path, MODEL_METADATA_SUFFIX].join(PATH_SEPARATOR)\n  };\n}\nfunction removeItems(keys) {\n  for (const key of Object.values(keys)) {\n    window.localStorage.removeItem(key);\n  }\n}\nfunction getModelPathFromKey(key) {\n  const items = key.split(PATH_SEPARATOR);\n  if (items.length < 3) {\n    throw new Error(`Invalid key format: ${key}`);\n  }\n  return items.slice(1, items.length - 1).join(PATH_SEPARATOR);\n}\nfunction maybeStripScheme2(key) {\n  return key.startsWith(BrowserLocalStorage.URL_SCHEME) ? key.slice(BrowserLocalStorage.URL_SCHEME.length) : key;\n}\nvar BrowserLocalStorage = class {\n  constructor(modelPath) {\n    if (!env().getBool(\"IS_BROWSER\") || typeof window === \"undefined\" || typeof window.localStorage === \"undefined\") {\n      throw new Error(\"The current environment does not support local storage.\");\n    }\n    this.LS = window.localStorage;\n    if (modelPath == null || !modelPath) {\n      throw new Error(\"For local storage, modelPath must not be null, undefined or empty.\");\n    }\n    this.modelPath = modelPath;\n    this.keys = getModelKeys(this.modelPath);\n  }\n  async save(modelArtifacts) {\n    if (modelArtifacts.modelTopology instanceof ArrayBuffer) {\n      throw new Error(\"BrowserLocalStorage.save() does not support saving model topology in binary formats yet.\");\n    } else {\n      const topology = JSON.stringify(modelArtifacts.modelTopology);\n      const weightSpecs = JSON.stringify(modelArtifacts.weightSpecs);\n      const modelArtifactsInfo = getModelArtifactsInfoForJSON(modelArtifacts);\n      try {\n        this.LS.setItem(this.keys.info, JSON.stringify(modelArtifactsInfo));\n        this.LS.setItem(this.keys.topology, topology);\n        this.LS.setItem(this.keys.weightSpecs, weightSpecs);\n        this.LS.setItem(this.keys.weightData, arrayBufferToBase64String(modelArtifacts.weightData));\n        const metadata = {\n          format: modelArtifacts.format,\n          generatedBy: modelArtifacts.generatedBy,\n          convertedBy: modelArtifacts.convertedBy,\n          signature: modelArtifacts.signature != null ? modelArtifacts.signature : void 0,\n          userDefinedMetadata: modelArtifacts.userDefinedMetadata != null ? modelArtifacts.userDefinedMetadata : void 0,\n          modelInitializer: modelArtifacts.modelInitializer != null ? modelArtifacts.modelInitializer : void 0,\n          trainingConfig: modelArtifacts.trainingConfig != null ? modelArtifacts.trainingConfig : void 0\n        };\n        this.LS.setItem(this.keys.modelMetadata, JSON.stringify(metadata));\n        return { modelArtifactsInfo };\n      } catch (err) {\n        removeItems(this.keys);\n        throw new Error(`Failed to save model '${this.modelPath}' to local storage: size quota being exceeded is a possible cause of this failure: modelTopologyBytes=${modelArtifactsInfo.modelTopologyBytes}, weightSpecsBytes=${modelArtifactsInfo.weightSpecsBytes}, weightDataBytes=${modelArtifactsInfo.weightDataBytes}.`);\n      }\n    }\n  }\n  async load() {\n    const info = JSON.parse(this.LS.getItem(this.keys.info));\n    if (info == null) {\n      throw new Error(`In local storage, there is no model with name '${this.modelPath}'`);\n    }\n    if (info.modelTopologyType !== \"JSON\") {\n      throw new Error(\"BrowserLocalStorage does not support loading non-JSON model topology yet.\");\n    }\n    const out = {};\n    const topology = JSON.parse(this.LS.getItem(this.keys.topology));\n    if (topology == null) {\n      throw new Error(`In local storage, the topology of model '${this.modelPath}' is missing.`);\n    }\n    out.modelTopology = topology;\n    const weightSpecs = JSON.parse(this.LS.getItem(this.keys.weightSpecs));\n    if (weightSpecs == null) {\n      throw new Error(`In local storage, the weight specs of model '${this.modelPath}' are missing.`);\n    }\n    out.weightSpecs = weightSpecs;\n    const metadataString = this.LS.getItem(this.keys.modelMetadata);\n    if (metadataString != null) {\n      const metadata = JSON.parse(metadataString);\n      out.format = metadata.format;\n      out.generatedBy = metadata.generatedBy;\n      out.convertedBy = metadata.convertedBy;\n      if (metadata.signature != null) {\n        out.signature = metadata.signature;\n      }\n      if (metadata.userDefinedMetadata != null) {\n        out.userDefinedMetadata = metadata.userDefinedMetadata;\n      }\n      if (metadata.modelInitializer != null) {\n        out.modelInitializer = metadata.modelInitializer;\n      }\n      if (metadata.trainingConfig != null) {\n        out.trainingConfig = metadata.trainingConfig;\n      }\n    }\n    const weightDataBase64 = this.LS.getItem(this.keys.weightData);\n    if (weightDataBase64 == null) {\n      throw new Error(`In local storage, the binary weight values of model '${this.modelPath}' are missing.`);\n    }\n    out.weightData = base64StringToArrayBuffer(weightDataBase64);\n    return out;\n  }\n};\nBrowserLocalStorage.URL_SCHEME = \"localstorage://\";\nvar localStorageRouter = (url) => {\n  if (!env().getBool(\"IS_BROWSER\")) {\n    return null;\n  } else {\n    if (!Array.isArray(url) && url.startsWith(BrowserLocalStorage.URL_SCHEME)) {\n      return browserLocalStorage(url.slice(BrowserLocalStorage.URL_SCHEME.length));\n    } else {\n      return null;\n    }\n  }\n};\nIORouterRegistry.registerSaveRouter(localStorageRouter);\nIORouterRegistry.registerLoadRouter(localStorageRouter);\nfunction browserLocalStorage(modelPath) {\n  return new BrowserLocalStorage(modelPath);\n}\nvar BrowserLocalStorageManager = class {\n  constructor() {\n    assert(env().getBool(\"IS_BROWSER\"), () => \"Current environment is not a web browser\");\n    assert(typeof window === \"undefined\" || typeof window.localStorage !== \"undefined\", () => \"Current browser does not appear to support localStorage\");\n    this.LS = window.localStorage;\n  }\n  async listModels() {\n    const out = {};\n    const prefix = PATH_PREFIX + PATH_SEPARATOR;\n    const suffix = PATH_SEPARATOR + INFO_SUFFIX;\n    for (let i2 = 0; i2 < this.LS.length; ++i2) {\n      const key = this.LS.key(i2);\n      if (key.startsWith(prefix) && key.endsWith(suffix)) {\n        const modelPath = getModelPathFromKey(key);\n        out[modelPath] = JSON.parse(this.LS.getItem(key));\n      }\n    }\n    return out;\n  }\n  async removeModel(path) {\n    path = maybeStripScheme2(path);\n    const keys = getModelKeys(path);\n    if (this.LS.getItem(keys.info) == null) {\n      throw new Error(`Cannot find model at path '${path}'`);\n    }\n    const info = JSON.parse(this.LS.getItem(keys.info));\n    removeItems(keys);\n    return info;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/model_management.js\nvar URL_SCHEME_SUFFIX = \"://\";\nvar ModelStoreManagerRegistry = class {\n  constructor() {\n    this.managers = {};\n  }\n  static getInstance() {\n    if (ModelStoreManagerRegistry.instance == null) {\n      ModelStoreManagerRegistry.instance = new ModelStoreManagerRegistry();\n    }\n    return ModelStoreManagerRegistry.instance;\n  }\n  static registerManager(scheme, manager) {\n    assert(scheme != null, () => \"scheme must not be undefined or null.\");\n    if (scheme.endsWith(URL_SCHEME_SUFFIX)) {\n      scheme = scheme.slice(0, scheme.indexOf(URL_SCHEME_SUFFIX));\n    }\n    assert(scheme.length > 0, () => \"scheme must not be an empty string.\");\n    const registry = ModelStoreManagerRegistry.getInstance();\n    assert(registry.managers[scheme] == null, () => `A model store manager is already registered for scheme '${scheme}'.`);\n    registry.managers[scheme] = manager;\n  }\n  static getManager(scheme) {\n    const manager = ModelStoreManagerRegistry.getInstance().managers[scheme];\n    if (manager == null) {\n      throw new Error(`Cannot find model manager for scheme '${scheme}'`);\n    }\n    return manager;\n  }\n  static getSchemes() {\n    return Object.keys(ModelStoreManagerRegistry.getInstance().managers);\n  }\n};\nfunction parseURL(url) {\n  if (url.indexOf(URL_SCHEME_SUFFIX) === -1) {\n    throw new Error(`The url string provided does not contain a scheme. Supported schemes are: ${ModelStoreManagerRegistry.getSchemes().join(\",\")}`);\n  }\n  return {\n    scheme: url.split(URL_SCHEME_SUFFIX)[0],\n    path: url.split(URL_SCHEME_SUFFIX)[1]\n  };\n}\nasync function cloneModelInternal(sourceURL, destURL, deleteSource = false) {\n  assert(sourceURL !== destURL, () => `Old path and new path are the same: '${sourceURL}'`);\n  const loadHandlers = IORouterRegistry.getLoadHandlers(sourceURL);\n  assert(loadHandlers.length > 0, () => `Copying failed because no load handler is found for source URL ${sourceURL}.`);\n  assert(loadHandlers.length < 2, () => `Copying failed because more than one (${loadHandlers.length}) load handlers for source URL ${sourceURL}.`);\n  const loadHandler = loadHandlers[0];\n  const saveHandlers = IORouterRegistry.getSaveHandlers(destURL);\n  assert(saveHandlers.length > 0, () => `Copying failed because no save handler is found for destination URL ${destURL}.`);\n  assert(saveHandlers.length < 2, () => `Copying failed because more than one (${loadHandlers.length}) save handlers for destination URL ${destURL}.`);\n  const saveHandler = saveHandlers[0];\n  const sourceScheme = parseURL(sourceURL).scheme;\n  const sourcePath = parseURL(sourceURL).path;\n  const sameMedium = sourceScheme === parseURL(sourceURL).scheme;\n  const modelArtifacts = await loadHandler.load();\n  if (deleteSource && sameMedium) {\n    await ModelStoreManagerRegistry.getManager(sourceScheme).removeModel(sourcePath);\n  }\n  const saveResult = await saveHandler.save(modelArtifacts);\n  if (deleteSource && !sameMedium) {\n    await ModelStoreManagerRegistry.getManager(sourceScheme).removeModel(sourcePath);\n  }\n  return saveResult.modelArtifactsInfo;\n}\nasync function listModels() {\n  const schemes = ModelStoreManagerRegistry.getSchemes();\n  const out = {};\n  for (const scheme of schemes) {\n    const schemeOut = await ModelStoreManagerRegistry.getManager(scheme).listModels();\n    for (const path in schemeOut) {\n      const url = scheme + URL_SCHEME_SUFFIX + path;\n      out[url] = schemeOut[path];\n    }\n  }\n  return out;\n}\nasync function removeModel(url) {\n  const schemeAndPath = parseURL(url);\n  const manager = ModelStoreManagerRegistry.getManager(schemeAndPath.scheme);\n  return manager.removeModel(schemeAndPath.path);\n}\nasync function copyModel(sourceURL, destURL) {\n  const deleteSource = false;\n  return cloneModelInternal(sourceURL, destURL, deleteSource);\n}\nasync function moveModel(sourceURL, destURL) {\n  const deleteSource = true;\n  return cloneModelInternal(sourceURL, destURL, deleteSource);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/platforms/platform_browser.js\nvar PlatformBrowser = class {\n  fetch(path, init2) {\n    return fetch(path, init2);\n  }\n  now() {\n    return performance.now();\n  }\n  encode(text, encoding) {\n    if (encoding !== \"utf-8\" && encoding !== \"utf8\") {\n      throw new Error(`Browser's encoder only supports utf-8, but got ${encoding}`);\n    }\n    if (this.textEncoder == null) {\n      this.textEncoder = new TextEncoder();\n    }\n    return this.textEncoder.encode(text);\n  }\n  decode(bytes, encoding) {\n    return new TextDecoder(encoding).decode(bytes);\n  }\n};\nif (env().get(\"IS_BROWSER\")) {\n  env().setPlatform(\"browser\", new PlatformBrowser());\n  try {\n    ModelStoreManagerRegistry.registerManager(BrowserLocalStorage.URL_SCHEME, new BrowserLocalStorageManager());\n  } catch (err) {\n  }\n  try {\n    ModelStoreManagerRegistry.registerManager(BrowserIndexedDB.URL_SCHEME, new BrowserIndexedDBManager());\n  } catch (err) {\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/platforms/platform_node.js\nvar getNodeFetch = {\n  importFetch: () => require_browser()\n};\nvar systemFetch;\nvar PlatformNode = class {\n  constructor() {\n    this.util = require_util();\n    this.textEncoder = new this.util.TextEncoder();\n  }\n  fetch(path, requestInits) {\n    if (env().global.fetch != null) {\n      return env().global.fetch(path, requestInits);\n    }\n    if (systemFetch == null) {\n      systemFetch = getNodeFetch.importFetch();\n    }\n    return systemFetch(path, requestInits);\n  }\n  now() {\n    const time2 = process.hrtime();\n    return time2[0] * 1e3 + time2[1] / 1e6;\n  }\n  encode(text, encoding) {\n    if (encoding !== \"utf-8\" && encoding !== \"utf8\") {\n      throw new Error(`Node built-in encoder only supports utf-8, but got ${encoding}`);\n    }\n    return this.textEncoder.encode(text);\n  }\n  decode(bytes, encoding) {\n    if (bytes.length === 0) {\n      return \"\";\n    }\n    return new this.util.TextDecoder(encoding).decode(bytes);\n  }\n};\nif (env().get(\"IS_NODE\") && !env().get(\"IS_BROWSER\")) {\n  env().setPlatform(\"node\", new PlatformNode());\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/buffer.js\nfunction buffer(shape, dtype = \"float32\", values) {\n  dtype = dtype || \"float32\";\n  assertNonNegativeIntegerDimensions(shape);\n  return new TensorBuffer(shape, dtype, values);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/cast.js\nfunction cast_(x, dtype) {\n  const $x = convertToTensor(x, \"x\", \"cast\");\n  if (!isValidDtype(dtype)) {\n    throw new Error(`Failed to cast to unknown dtype ${dtype}`);\n  }\n  if (dtype === \"string\" && $x.dtype !== \"string\" || dtype !== \"string\" && $x.dtype === \"string\") {\n    throw new Error(\"Only strings can be casted to strings\");\n  }\n  const inputs = { x: $x };\n  const attrs = { dtype };\n  return ENGINE.runKernel(Cast, inputs, attrs);\n}\nvar cast = op({ cast_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/clone.js\nfunction clone_(x) {\n  const $x = convertToTensor(x, \"x\", \"clone\", \"string_or_numeric\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Identity, inputs);\n}\nvar clone = op({ clone_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/print.js\nfunction print(x, verbose = false) {\n  console.log(x.toString(verbose));\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/base_side_effects.js\ngetOrMakeEngine();\nvar opHandler2 = {\n  buffer,\n  cast,\n  clone,\n  print\n};\nsetOpHandler(opHandler2);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/io.js\nvar io_exports = {};\n__export(io_exports, {\n  browserFiles: () => browserFiles,\n  browserHTTPRequest: () => browserHTTPRequest,\n  concatenateArrayBuffers: () => concatenateArrayBuffers,\n  copyModel: () => copyModel,\n  decodeWeights: () => decodeWeights,\n  encodeWeights: () => encodeWeights,\n  fromMemory: () => fromMemory,\n  fromMemorySync: () => fromMemorySync,\n  getLoadHandlers: () => getLoadHandlers,\n  getModelArtifactsForJSON: () => getModelArtifactsForJSON,\n  getModelArtifactsInfoForJSON: () => getModelArtifactsInfoForJSON,\n  getSaveHandlers: () => getSaveHandlers,\n  http: () => http,\n  isHTTPScheme: () => isHTTPScheme,\n  listModels: () => listModels,\n  loadWeights: () => loadWeights,\n  moveModel: () => moveModel,\n  registerLoadRouter: () => registerLoadRouter,\n  registerSaveRouter: () => registerSaveRouter,\n  removeModel: () => removeModel,\n  weightsLoaderFactory: () => weightsLoaderFactory,\n  withSaveHandler: () => withSaveHandler,\n  withSaveHandlerSync: () => withSaveHandlerSync\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/browser_files.js\nvar DEFAULT_FILE_NAME_PREFIX = \"model\";\nvar DEFAULT_JSON_EXTENSION_NAME = \".json\";\nvar DEFAULT_WEIGHT_DATA_EXTENSION_NAME = \".weights.bin\";\nfunction defer(f) {\n  return new Promise((resolve) => setTimeout(resolve)).then(f);\n}\nvar BrowserDownloads = class {\n  constructor(fileNamePrefix) {\n    if (!env().getBool(\"IS_BROWSER\")) {\n      throw new Error(\"browserDownloads() cannot proceed because the current environment is not a browser.\");\n    }\n    if (fileNamePrefix.startsWith(BrowserDownloads.URL_SCHEME)) {\n      fileNamePrefix = fileNamePrefix.slice(BrowserDownloads.URL_SCHEME.length);\n    }\n    if (fileNamePrefix == null || fileNamePrefix.length === 0) {\n      fileNamePrefix = DEFAULT_FILE_NAME_PREFIX;\n    }\n    this.modelJsonFileName = fileNamePrefix + DEFAULT_JSON_EXTENSION_NAME;\n    this.weightDataFileName = fileNamePrefix + DEFAULT_WEIGHT_DATA_EXTENSION_NAME;\n  }\n  async save(modelArtifacts) {\n    if (typeof document === \"undefined\") {\n      throw new Error(\"Browser downloads are not supported in this environment since `document` is not present\");\n    }\n    const weightsURL = window.URL.createObjectURL(new Blob([modelArtifacts.weightData], { type: \"application/octet-stream\" }));\n    if (modelArtifacts.modelTopology instanceof ArrayBuffer) {\n      throw new Error(\"BrowserDownloads.save() does not support saving model topology in binary formats yet.\");\n    } else {\n      const weightsManifest = [{\n        paths: [\"./\" + this.weightDataFileName],\n        weights: modelArtifacts.weightSpecs\n      }];\n      const modelJSON = getModelJSONForModelArtifacts(modelArtifacts, weightsManifest);\n      const modelJsonURL = window.URL.createObjectURL(new Blob([JSON.stringify(modelJSON)], { type: \"application/json\" }));\n      const jsonAnchor = this.modelJsonAnchor == null ? document.createElement(\"a\") : this.modelJsonAnchor;\n      jsonAnchor.download = this.modelJsonFileName;\n      jsonAnchor.href = modelJsonURL;\n      await defer(() => jsonAnchor.dispatchEvent(new MouseEvent(\"click\")));\n      if (modelArtifacts.weightData != null) {\n        const weightDataAnchor = this.weightDataAnchor == null ? document.createElement(\"a\") : this.weightDataAnchor;\n        weightDataAnchor.download = this.weightDataFileName;\n        weightDataAnchor.href = weightsURL;\n        await defer(() => weightDataAnchor.dispatchEvent(new MouseEvent(\"click\")));\n      }\n      return { modelArtifactsInfo: getModelArtifactsInfoForJSON(modelArtifacts) };\n    }\n  }\n};\nBrowserDownloads.URL_SCHEME = \"downloads://\";\nvar BrowserFiles = class {\n  constructor(files) {\n    if (files == null || files.length < 1) {\n      throw new Error(`When calling browserFiles, at least 1 file is required, but received ${files}`);\n    }\n    this.jsonFile = files[0];\n    this.weightsFiles = files.slice(1);\n  }\n  async load() {\n    return new Promise((resolve, reject) => {\n      const jsonReader = new FileReader();\n      jsonReader.onload = (event) => {\n        const modelJSON = JSON.parse(event.target.result);\n        const modelTopology = modelJSON.modelTopology;\n        if (modelTopology == null) {\n          reject(new Error(`modelTopology field is missing from file ${this.jsonFile.name}`));\n          return;\n        }\n        const weightsManifest = modelJSON.weightsManifest;\n        if (weightsManifest == null) {\n          reject(new Error(`weightManifest field is missing from file ${this.jsonFile.name}`));\n          return;\n        }\n        if (this.weightsFiles.length === 0) {\n          resolve({ modelTopology });\n          return;\n        }\n        const modelArtifactsPromise = getModelArtifactsForJSON(modelJSON, (weightsManifest2) => this.loadWeights(weightsManifest2));\n        resolve(modelArtifactsPromise);\n      };\n      jsonReader.onerror = (error) => reject(`Failed to read model topology and weights manifest JSON from file '${this.jsonFile.name}'. BrowserFiles supports loading Keras-style tf.Model artifacts only.`);\n      jsonReader.readAsText(this.jsonFile);\n    });\n  }\n  loadWeights(weightsManifest) {\n    const weightSpecs = [];\n    const paths = [];\n    for (const entry of weightsManifest) {\n      weightSpecs.push(...entry.weights);\n      paths.push(...entry.paths);\n    }\n    const pathToFile = this.checkManifestAndWeightFiles(weightsManifest);\n    const promises = paths.map((path) => this.loadWeightsFile(path, pathToFile[path]));\n    return Promise.all(promises).then((buffers) => [weightSpecs, concatenateArrayBuffers(buffers)]);\n  }\n  loadWeightsFile(path, file) {\n    return new Promise((resolve, reject) => {\n      const weightFileReader = new FileReader();\n      weightFileReader.onload = (event) => {\n        const weightData = event.target.result;\n        resolve(weightData);\n      };\n      weightFileReader.onerror = (error) => reject(`Failed to weights data from file of path '${path}'.`);\n      weightFileReader.readAsArrayBuffer(file);\n    });\n  }\n  checkManifestAndWeightFiles(manifest) {\n    const basenames = [];\n    const fileNames = this.weightsFiles.map((file) => basename(file.name));\n    const pathToFile = {};\n    for (const group of manifest) {\n      group.paths.forEach((path) => {\n        const pathBasename = basename(path);\n        if (basenames.indexOf(pathBasename) !== -1) {\n          throw new Error(`Duplicate file basename found in weights manifest: '${pathBasename}'`);\n        }\n        basenames.push(pathBasename);\n        if (fileNames.indexOf(pathBasename) === -1) {\n          throw new Error(`Weight file with basename '${pathBasename}' is not provided.`);\n        } else {\n          pathToFile[path] = this.weightsFiles[fileNames.indexOf(pathBasename)];\n        }\n      });\n    }\n    if (basenames.length !== this.weightsFiles.length) {\n      throw new Error(`Mismatch in the number of files in weights manifest (${basenames.length}) and the number of weight files provided (${this.weightsFiles.length}).`);\n    }\n    return pathToFile;\n  }\n};\nvar browserDownloadsRouter = (url) => {\n  if (!env().getBool(\"IS_BROWSER\")) {\n    return null;\n  } else {\n    if (!Array.isArray(url) && url.startsWith(BrowserDownloads.URL_SCHEME)) {\n      return browserDownloads(url.slice(BrowserDownloads.URL_SCHEME.length));\n    } else {\n      return null;\n    }\n  }\n};\nIORouterRegistry.registerSaveRouter(browserDownloadsRouter);\nfunction browserDownloads(fileNamePrefix = \"model\") {\n  return new BrowserDownloads(fileNamePrefix);\n}\nfunction browserFiles(files) {\n  return new BrowserFiles(files);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/progress.js\nfunction monitorPromisesProgress(promises, onProgress, startFraction, endFraction) {\n  checkPromises(promises);\n  startFraction = startFraction == null ? 0 : startFraction;\n  endFraction = endFraction == null ? 1 : endFraction;\n  checkFraction(startFraction, endFraction);\n  let resolvedPromise = 0;\n  const registerMonitor = (promise) => {\n    promise.then((value) => {\n      const fraction = startFraction + ++resolvedPromise / promises.length * (endFraction - startFraction);\n      onProgress(fraction);\n      return value;\n    });\n    return promise;\n  };\n  function checkPromises(promises2) {\n    assert(promises2 != null && Array.isArray(promises2) && promises2.length > 0, () => \"promises must be a none empty array\");\n  }\n  function checkFraction(startFraction2, endFraction2) {\n    assert(startFraction2 >= 0 && startFraction2 <= 1, () => `Progress fraction must be in range [0, 1], but got startFraction ${startFraction2}`);\n    assert(endFraction2 >= 0 && endFraction2 <= 1, () => `Progress fraction must be in range [0, 1], but got endFraction ${endFraction2}`);\n    assert(endFraction2 >= startFraction2, () => `startFraction must be no more than endFraction, but got startFraction ${startFraction2} and endFraction ${endFraction2}`);\n  }\n  return Promise.all(promises.map(registerMonitor));\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/weights_loader.js\nasync function loadWeightsAsArrayBuffer(fetchURLs, loadOptions) {\n  if (loadOptions == null) {\n    loadOptions = {};\n  }\n  const fetchFunc = loadOptions.fetchFunc == null ? env().platform.fetch : loadOptions.fetchFunc;\n  const requests = fetchURLs.map((fetchURL) => fetchFunc(fetchURL, loadOptions.requestInit, { isBinary: true }));\n  const fetchStartFraction = 0;\n  const fetchEndFraction = 0.5;\n  const responses = loadOptions.onProgress == null ? await Promise.all(requests) : await monitorPromisesProgress(requests, loadOptions.onProgress, fetchStartFraction, fetchEndFraction);\n  const bufferPromises = responses.map((response) => response.arrayBuffer());\n  const bufferStartFraction = 0.5;\n  const bufferEndFraction = 1;\n  const buffers = loadOptions.onProgress == null ? await Promise.all(bufferPromises) : await monitorPromisesProgress(bufferPromises, loadOptions.onProgress, bufferStartFraction, bufferEndFraction);\n  return buffers;\n}\nasync function loadWeights(manifest, filePathPrefix = \"\", weightNames, requestInit) {\n  const fetchWeights = (fetchUrls) => loadWeightsAsArrayBuffer(fetchUrls, { requestInit });\n  const loadWeights2 = weightsLoaderFactory(fetchWeights);\n  return loadWeights2(manifest, filePathPrefix, weightNames);\n}\nfunction weightsLoaderFactory(fetchWeightsFunction) {\n  return async (manifest, filePathPrefix = \"\", weightNames) => {\n    const groupIndicesToFetchMap = manifest.map(() => false);\n    const groupWeightsToFetch = {};\n    const weightsFound = weightNames != null ? weightNames.map(() => false) : [];\n    const allManifestWeightNames = [];\n    manifest.forEach((manifestGroupConfig, groupIndex) => {\n      let groupOffset = 0;\n      manifestGroupConfig.weights.forEach((weightsEntry) => {\n        const rawDtype = \"quantization\" in weightsEntry ? weightsEntry.quantization.dtype : weightsEntry.dtype;\n        const weightsBytes = DTYPE_VALUE_SIZE_MAP[rawDtype] * sizeFromShape(weightsEntry.shape);\n        const enqueueWeightsForFetchingFn = () => {\n          groupIndicesToFetchMap[groupIndex] = true;\n          if (groupWeightsToFetch[groupIndex] == null) {\n            groupWeightsToFetch[groupIndex] = [];\n          }\n          groupWeightsToFetch[groupIndex].push({\n            manifestEntry: weightsEntry,\n            groupOffset,\n            sizeBytes: weightsBytes\n          });\n        };\n        if (weightNames != null) {\n          weightNames.forEach((weightName, weightIndex) => {\n            if (weightName === weightsEntry.name) {\n              enqueueWeightsForFetchingFn();\n              weightsFound[weightIndex] = true;\n            }\n          });\n        } else {\n          enqueueWeightsForFetchingFn();\n        }\n        allManifestWeightNames.push(weightsEntry.name);\n        groupOffset += weightsBytes;\n      });\n    });\n    if (!weightsFound.every((found) => found)) {\n      const weightsNotFound = weightNames.filter((_, i2) => !weightsFound[i2]);\n      throw new Error(`Could not find weights in manifest with names: ${weightsNotFound.join(\", \")}. \nManifest JSON has weights with names: ${allManifestWeightNames.join(\", \")}.`);\n    }\n    const groupIndicesToFetch = groupIndicesToFetchMap.reduce((accumulator, shouldFetch, i2) => {\n      if (shouldFetch) {\n        accumulator.push(i2);\n      }\n      return accumulator;\n    }, []);\n    const fetchUrls = [];\n    groupIndicesToFetch.forEach((i2) => {\n      manifest[i2].paths.forEach((filepath) => {\n        const fetchUrl = filePathPrefix + (!filePathPrefix.endsWith(\"/\") ? \"/\" : \"\") + filepath;\n        fetchUrls.push(fetchUrl);\n      });\n    });\n    const buffers = await fetchWeightsFunction(fetchUrls);\n    const weightsTensorMap = {};\n    let bufferIndexOffset = 0;\n    groupIndicesToFetch.forEach((i2) => {\n      const numBuffers = manifest[i2].paths.length;\n      let groupBytes = 0;\n      for (let i3 = 0; i3 < numBuffers; i3++) {\n        groupBytes += buffers[bufferIndexOffset + i3].byteLength;\n      }\n      const groupBuffer = new ArrayBuffer(groupBytes);\n      const groupByteBuffer = new Uint8Array(groupBuffer);\n      let groupBufferOffset = 0;\n      for (let i3 = 0; i3 < numBuffers; i3++) {\n        const buffer2 = new Uint8Array(buffers[bufferIndexOffset + i3]);\n        groupByteBuffer.set(buffer2, groupBufferOffset);\n        groupBufferOffset += buffer2.byteLength;\n      }\n      const weightsEntries = groupWeightsToFetch[i2];\n      weightsEntries.forEach((weightsEntry) => {\n        const byteBuffer = groupBuffer.slice(weightsEntry.groupOffset, weightsEntry.groupOffset + weightsEntry.sizeBytes);\n        const nameToTensorMap = decodeWeights(byteBuffer, [weightsEntry.manifestEntry]);\n        for (const name in nameToTensorMap) {\n          weightsTensorMap[name] = nameToTensorMap[name];\n        }\n      });\n      bufferIndexOffset += numBuffers;\n    });\n    return weightsTensorMap;\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/http.js\nvar OCTET_STREAM_MIME_TYPE = \"application/octet-stream\";\nvar JSON_TYPE = \"application/json\";\nvar HTTPRequest = class {\n  constructor(path, loadOptions) {\n    this.DEFAULT_METHOD = \"POST\";\n    if (loadOptions == null) {\n      loadOptions = {};\n    }\n    this.weightPathPrefix = loadOptions.weightPathPrefix;\n    this.onProgress = loadOptions.onProgress;\n    this.weightUrlConverter = loadOptions.weightUrlConverter;\n    if (loadOptions.fetchFunc != null) {\n      assert(typeof loadOptions.fetchFunc === \"function\", () => \"Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)\");\n      this.fetch = loadOptions.fetchFunc;\n    } else {\n      this.fetch = env().platform.fetch;\n    }\n    assert(path != null && path.length > 0, () => \"URL path for http must not be null, undefined or empty.\");\n    if (Array.isArray(path)) {\n      assert(path.length === 2, () => `URL paths for http must have a length of 2, (actual length is ${path.length}).`);\n    }\n    this.path = path;\n    if (loadOptions.requestInit != null && loadOptions.requestInit.body != null) {\n      throw new Error(\"requestInit is expected to have no pre-existing body, but has one.\");\n    }\n    this.requestInit = loadOptions.requestInit || {};\n  }\n  async save(modelArtifacts) {\n    if (modelArtifacts.modelTopology instanceof ArrayBuffer) {\n      throw new Error(\"BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.\");\n    }\n    const init2 = Object.assign({ method: this.DEFAULT_METHOD }, this.requestInit);\n    init2.body = new FormData();\n    const weightsManifest = [{\n      paths: [\"./model.weights.bin\"],\n      weights: modelArtifacts.weightSpecs\n    }];\n    const modelTopologyAndWeightManifest = getModelJSONForModelArtifacts(modelArtifacts, weightsManifest);\n    init2.body.append(\"model.json\", new Blob([JSON.stringify(modelTopologyAndWeightManifest)], { type: JSON_TYPE }), \"model.json\");\n    if (modelArtifacts.weightData != null) {\n      init2.body.append(\"model.weights.bin\", new Blob([modelArtifacts.weightData], { type: OCTET_STREAM_MIME_TYPE }), \"model.weights.bin\");\n    }\n    const response = await this.fetch(this.path, init2);\n    if (response.ok) {\n      return {\n        modelArtifactsInfo: getModelArtifactsInfoForJSON(modelArtifacts),\n        responses: [response]\n      };\n    } else {\n      throw new Error(`BrowserHTTPRequest.save() failed due to HTTP response status ${response.status}.`);\n    }\n  }\n  async load() {\n    const modelConfigRequest = await this.fetch(this.path, this.requestInit);\n    if (!modelConfigRequest.ok) {\n      throw new Error(`Request to ${this.path} failed with status code ${modelConfigRequest.status}. Please verify this URL points to the model JSON of the model to load.`);\n    }\n    let modelJSON;\n    try {\n      modelJSON = await modelConfigRequest.json();\n    } catch (e2) {\n      let message = `Failed to parse model JSON of response from ${this.path}.`;\n      if (this.path.endsWith(\".pb\")) {\n        message += \" Your path contains a .pb file extension. Support for .pb models have been removed in TensorFlow.js 1.0 in favor of .json models. You can re-convert your Python TensorFlow model using the TensorFlow.js 1.0 conversion scripts or you can convert your.pb models with the 'pb2json'NPM script in the tensorflow/tfjs-converter repository.\";\n      } else {\n        message += \" Please make sure the server is serving valid JSON for this request.\";\n      }\n      throw new Error(message);\n    }\n    const modelTopology = modelJSON.modelTopology;\n    const weightsManifest = modelJSON.weightsManifest;\n    if (modelTopology == null && weightsManifest == null) {\n      throw new Error(`The JSON from HTTP path ${this.path} contains neither model topology or manifest for weights.`);\n    }\n    return getModelArtifactsForJSON(modelJSON, (weightsManifest2) => this.loadWeights(weightsManifest2));\n  }\n  async loadWeights(weightsManifest) {\n    const weightPath = Array.isArray(this.path) ? this.path[1] : this.path;\n    const [prefix, suffix] = parseUrl(weightPath);\n    const pathPrefix = this.weightPathPrefix || prefix;\n    const weightSpecs = [];\n    for (const entry of weightsManifest) {\n      weightSpecs.push(...entry.weights);\n    }\n    const fetchURLs = [];\n    const urlPromises = [];\n    for (const weightsGroup of weightsManifest) {\n      for (const path of weightsGroup.paths) {\n        if (this.weightUrlConverter != null) {\n          urlPromises.push(this.weightUrlConverter(path));\n        } else {\n          fetchURLs.push(pathPrefix + path + suffix);\n        }\n      }\n    }\n    if (this.weightUrlConverter) {\n      fetchURLs.push(...await Promise.all(urlPromises));\n    }\n    const buffers = await loadWeightsAsArrayBuffer(fetchURLs, {\n      requestInit: this.requestInit,\n      fetchFunc: this.fetch,\n      onProgress: this.onProgress\n    });\n    return [weightSpecs, concatenateArrayBuffers(buffers)];\n  }\n};\nHTTPRequest.URL_SCHEME_REGEX = /^https?:\\/\\//;\nfunction parseUrl(url) {\n  const lastSlash = url.lastIndexOf(\"/\");\n  const lastSearchParam = url.lastIndexOf(\"?\");\n  const prefix = url.substring(0, lastSlash);\n  const suffix = lastSearchParam > lastSlash ? url.substring(lastSearchParam) : \"\";\n  return [prefix + \"/\", suffix];\n}\nfunction isHTTPScheme(url) {\n  return url.match(HTTPRequest.URL_SCHEME_REGEX) != null;\n}\nvar httpRouter = (url, loadOptions) => {\n  if (typeof fetch === \"undefined\" && (loadOptions == null || loadOptions.fetchFunc == null)) {\n    return null;\n  } else {\n    let isHTTP = true;\n    if (Array.isArray(url)) {\n      isHTTP = url.every((urlItem) => isHTTPScheme(urlItem));\n    } else {\n      isHTTP = isHTTPScheme(url);\n    }\n    if (isHTTP) {\n      return http(url, loadOptions);\n    }\n  }\n  return null;\n};\nIORouterRegistry.registerSaveRouter(httpRouter);\nIORouterRegistry.registerLoadRouter(httpRouter);\nfunction http(path, loadOptions) {\n  return new HTTPRequest(path, loadOptions);\n}\nfunction browserHTTPRequest(path, loadOptions) {\n  return http(path, loadOptions);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/io/passthrough.js\nvar PassthroughLoader = class {\n  constructor(modelArtifacts) {\n    this.modelArtifacts = modelArtifacts;\n  }\n  load() {\n    return this.modelArtifacts;\n  }\n};\nvar PassthroughSaver = class {\n  constructor(saveHandler) {\n    this.saveHandler = saveHandler;\n  }\n  save(modelArtifacts) {\n    return this.saveHandler(modelArtifacts);\n  }\n};\nvar PassthroughAsync = class {\n  constructor(handler) {\n    if (handler.load) {\n      this.load = () => Promise.resolve(handler.load());\n    }\n    if (handler.save) {\n      this.save = (modelArtifacts) => Promise.resolve(handler.save(modelArtifacts));\n    }\n  }\n};\nfunction fromMemory(modelArtifacts, weightSpecs, weightData, trainingConfig) {\n  const args = arguments;\n  return new PassthroughAsync(fromMemorySync(...args));\n}\nfunction fromMemorySync(modelArtifacts, weightSpecs, weightData, trainingConfig) {\n  if (arguments.length === 1) {\n    const isModelArtifacts = modelArtifacts.modelTopology != null || modelArtifacts.weightSpecs != null;\n    if (isModelArtifacts) {\n      return new PassthroughLoader(modelArtifacts);\n    } else {\n      console.warn(\"Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release.\");\n      return new PassthroughLoader({ modelTopology: modelArtifacts });\n    }\n  } else {\n    console.warn(\"Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release.\");\n    return new PassthroughLoader({\n      modelTopology: modelArtifacts,\n      weightSpecs,\n      weightData,\n      trainingConfig\n    });\n  }\n}\nfunction withSaveHandler(saveHandler) {\n  return new PassthroughSaver(saveHandler);\n}\nfunction withSaveHandlerSync(saveHandler) {\n  return new PassthroughSaver(saveHandler);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/math.js\nvar math_exports = {};\n__export(math_exports, {\n  confusionMatrix: () => confusionMatrix\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/mat_mul.js\nfunction matMul_(a, b, transposeA = false, transposeB = false) {\n  let $a = convertToTensor(a, \"a\", \"matMul\");\n  let $b = convertToTensor(b, \"b\", \"matMul\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const inputs = { a: $a, b: $b };\n  const attrs = { transposeA, transposeB };\n  return ENGINE.runKernel(BatchMatMul, inputs, attrs);\n}\nvar matMul = op({ matMul_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/one_hot.js\nfunction oneHot_(indices, depth, onValue = 1, offValue = 0) {\n  if (depth < 2) {\n    throw new Error(`Error in oneHot: depth must be >=2, but it is ${depth}`);\n  }\n  const $indices = convertToTensor(indices, \"indices\", \"oneHot\", \"int32\");\n  const inputs = { indices: $indices };\n  const attrs = { depth, onValue, offValue };\n  return ENGINE.runKernel(OneHot, inputs, attrs);\n}\nvar oneHot = op({ oneHot_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/globals.js\nfunction enableProdMode() {\n  env().set(\"PROD\", true);\n}\nfunction enableDebugMode() {\n  env().set(\"DEBUG\", true);\n}\nfunction disableDeprecationWarnings() {\n  env().set(\"DEPRECATION_WARNINGS_ENABLED\", false);\n  console.warn(`TensorFlow.js deprecation warnings have been disabled.`);\n}\nfunction deprecationWarn(msg) {\n  if (env().getBool(\"DEPRECATION_WARNINGS_ENABLED\")) {\n    console.warn(msg + \" You can disable deprecation warnings with tf.disableDeprecationWarnings().\");\n  }\n}\nsetDeprecationWarningFn(deprecationWarn);\nfunction disposeVariables() {\n  ENGINE.disposeVariables();\n}\nfunction engine() {\n  return ENGINE;\n}\nfunction memory() {\n  return ENGINE.memory();\n}\nfunction profile(f) {\n  return ENGINE.profile(f);\n}\nfunction tidy(nameOrFn, fn) {\n  return ENGINE.tidy(nameOrFn, fn);\n}\nfunction dispose(container) {\n  const tensors = getTensorsInContainer(container);\n  tensors.forEach((tensor2) => tensor2.dispose());\n}\nfunction keep(result) {\n  return ENGINE.keep(result);\n}\nfunction time(f) {\n  return ENGINE.time(f);\n}\nfunction setBackend(backendName) {\n  return ENGINE.setBackend(backendName);\n}\nfunction ready() {\n  return ENGINE.ready();\n}\nfunction getBackend() {\n  return ENGINE.backendName;\n}\nfunction removeBackend(name) {\n  ENGINE.removeBackend(name);\n}\nfunction findBackend(name) {\n  return ENGINE.findBackend(name);\n}\nfunction findBackendFactory(name) {\n  return ENGINE.findBackendFactory(name);\n}\nfunction registerBackend(name, factory, priority = 1) {\n  return ENGINE.registerBackend(name, factory, priority);\n}\nfunction backend() {\n  return ENGINE.backend;\n}\nfunction setPlatform(platformName, platform) {\n  env().setPlatform(platformName, platform);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/imag.js\nfunction imag_(input2) {\n  const $input = convertToTensor(input2, \"input\", \"imag\");\n  const inputs = { input: $input };\n  return ENGINE.runKernel(Imag, inputs);\n}\nvar imag = op({ imag_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/neg.js\nfunction neg_(x) {\n  const $x = convertToTensor(x, \"x\", \"neg\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Neg, inputs);\n}\nvar neg = op({ neg_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/real.js\nfunction real_(input2) {\n  const $input = convertToTensor(input2, \"input\", \"real\");\n  const inputs = { input: $input };\n  return ENGINE.runKernel(Real, inputs);\n}\nvar real = op({ real_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/transpose.js\nfunction transpose_(x, perm, conjugate) {\n  const $x = convertToTensor(x, \"x\", \"transpose\");\n  if (perm == null) {\n    perm = $x.shape.map((s2, i2) => i2).reverse();\n  }\n  assert($x.rank === perm.length, () => `Error in transpose: rank of input ${$x.rank} must match length of perm ${perm}.`);\n  perm.forEach((axis) => {\n    assert(axis >= 0 && axis < $x.rank, () => `All entries in 'perm' must be between 0 and ${$x.rank - 1} but got ${perm}`);\n  });\n  if ($x.rank <= 1) {\n    return $x.clone();\n  }\n  const inputs = { x: $x };\n  const attrs = { perm };\n  if ($x.dtype === \"complex64\") {\n    return tidy(() => {\n      let $real = real($x);\n      let $imag = imag($x);\n      $real = ENGINE.runKernel(Transpose, { x: $real }, attrs);\n      $imag = ENGINE.runKernel(Transpose, { x: $imag }, attrs);\n      if (conjugate) {\n        $imag = neg($imag);\n      }\n      return complex($real, $imag);\n    });\n  }\n  return ENGINE.runKernel(Transpose, inputs, attrs);\n}\nvar transpose = op({ transpose_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/confusion_matrix.js\nfunction confusionMatrix_(labels, predictions, numClasses) {\n  const $labels = convertToTensor(labels, \"labels\", \"confusionMatrix\");\n  const $predictions = convertToTensor(predictions, \"predictions\", \"confusionMatrix\");\n  assert(numClasses == null || numClasses > 0 && Number.isInteger(numClasses), () => `If provided, numClasses must be a positive integer, but got ${numClasses}`);\n  assert($labels.rank === 1, () => `Expected the rank of labels to be 1, but got ${$labels.rank}`);\n  assert($predictions.rank === 1, () => `Expected the rank of predictions to be 1, but got ${$predictions.rank}`);\n  assert($labels.shape[0] === $predictions.shape[0], () => `Mismatch in the number of examples: ${$labels.shape[0]} vs. ${$predictions.shape[0]}. Labels and predictions should have the same number of elements.`);\n  assert(numClasses > 0 && Number.isInteger(numClasses), () => `numClasses is required to be a positive integer, but got ${numClasses}`);\n  const oneHotLabels = oneHot(cast($labels, \"int32\"), numClasses);\n  const oneHotPredictions = oneHot(cast($predictions, \"int32\"), numClasses);\n  const oneHotLabelsT = transpose(oneHotLabels);\n  const product = matMul(oneHotLabelsT, oneHotPredictions);\n  return cast(product, \"int32\");\n}\nvar confusionMatrix = op({ confusionMatrix_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/broadcast_util.js\nvar broadcast_util_exports = {};\n__export(broadcast_util_exports, {\n  assertAndGetBroadcastShape: () => assertAndGetBroadcastShape,\n  getBroadcastDims: () => getBroadcastDims,\n  getReductionAxes: () => getReductionAxes\n});\nfunction getBroadcastDims(inShape, outShape) {\n  const inRank = inShape.length;\n  const dims = [];\n  for (let i2 = 0; i2 < inRank; i2++) {\n    const dim = inRank - 1 - i2;\n    const a = inShape[dim] || 1;\n    const b = outShape[outShape.length - 1 - i2] || 1;\n    if (b > 1 && a === 1) {\n      dims.unshift(dim);\n    }\n  }\n  return dims;\n}\nfunction getReductionAxes(inShape, outShape) {\n  const result = [];\n  for (let i2 = 0; i2 < outShape.length; i2++) {\n    const inDim = inShape[inShape.length - i2 - 1];\n    const outAxis = outShape.length - i2 - 1;\n    const outDim = outShape[outAxis];\n    if (inDim == null || inDim === 1 && outDim > 1) {\n      result.unshift(outAxis);\n    }\n  }\n  return result;\n}\nfunction assertAndGetBroadcastShape(shapeA, shapeB) {\n  const result = [];\n  const l3 = Math.max(shapeA.length, shapeB.length);\n  for (let i2 = 0; i2 < l3; i2++) {\n    let a = shapeA[shapeA.length - i2 - 1];\n    if (a == null) {\n      a = 1;\n    }\n    let b = shapeB[shapeB.length - i2 - 1];\n    if (b == null) {\n      b = 1;\n    }\n    if (a === 1) {\n      result.unshift(b);\n    } else if (b === 1) {\n      result.unshift(a);\n    } else if (a !== b) {\n      const errMsg = `Operands could not be broadcast together with shapes ${shapeA} and ${shapeB}.`;\n      throw Error(errMsg);\n    } else {\n      result.unshift(a);\n    }\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/browser.js\nvar browser_exports = {};\n__export(browser_exports, {\n  fromPixels: () => fromPixels,\n  fromPixelsAsync: () => fromPixelsAsync,\n  toPixels: () => toPixels\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor3d.js\nfunction tensor3d(values, shape, dtype) {\n  assertNonNull(values);\n  if (shape != null && shape.length !== 3) {\n    throw new Error(\"tensor3d() requires shape to have three numbers\");\n  }\n  const inferredShape = inferShape(values, dtype);\n  if (inferredShape.length !== 3 && inferredShape.length !== 1) {\n    throw new Error(\"tensor3d() requires values to be number[][][] or flat/TypedArray\");\n  }\n  if (inferredShape.length === 1 && shape == null) {\n    throw new Error(\"tensor3d() requires shape to be provided when `values` are a flat array\");\n  }\n  return makeTensor(values, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/browser.js\nvar fromPixels2DContext;\nfunction fromPixels_(pixels, numChannels = 3) {\n  if (numChannels > 4) {\n    throw new Error(\"Cannot construct Tensor with more than 4 channels from pixels.\");\n  }\n  if (pixels == null) {\n    throw new Error(\"pixels passed to tf.browser.fromPixels() can not be null\");\n  }\n  let isPixelData2 = false;\n  let isImageData = false;\n  let isVideo = false;\n  let isImage = false;\n  let isCanvasLike = false;\n  let isImageBitmap = false;\n  if (pixels.data instanceof Uint8Array) {\n    isPixelData2 = true;\n  } else if (typeof ImageData !== \"undefined\" && pixels instanceof ImageData) {\n    isImageData = true;\n  } else if (typeof HTMLVideoElement !== \"undefined\" && pixels instanceof HTMLVideoElement) {\n    isVideo = true;\n  } else if (typeof HTMLImageElement !== \"undefined\" && pixels instanceof HTMLImageElement) {\n    isImage = true;\n  } else if (pixels.getContext != null) {\n    isCanvasLike = true;\n  } else if (typeof ImageBitmap !== \"undefined\" && pixels instanceof ImageBitmap) {\n    isImageBitmap = true;\n  } else {\n    throw new Error(`pixels passed to tf.browser.fromPixels() must be either an HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData in browser, or OffscreenCanvas, ImageData in webworker or {data: Uint32Array, width: number, height: number}, but was ${pixels.constructor.name}`);\n  }\n  if (isVideo) {\n    const HAVE_CURRENT_DATA_READY_STATE = 2;\n    if (isVideo && pixels.readyState < HAVE_CURRENT_DATA_READY_STATE) {\n      throw new Error(\"The video element has not loaded data yet. Please wait for `loadeddata` event on the <video> element.\");\n    }\n  }\n  const kernel = getKernel(FromPixels, ENGINE.backendName);\n  if (kernel != null) {\n    const inputs = { pixels };\n    const attrs = { numChannels };\n    return ENGINE.runKernel(FromPixels, inputs, attrs);\n  }\n  const [width, height] = isVideo ? [\n    pixels.videoWidth,\n    pixels.videoHeight\n  ] : [pixels.width, pixels.height];\n  let vals;\n  if (isCanvasLike) {\n    vals = pixels.getContext(\"2d\").getImageData(0, 0, width, height).data;\n  } else if (isImageData || isPixelData2) {\n    vals = pixels.data;\n  } else if (isImage || isVideo || isImageBitmap) {\n    if (fromPixels2DContext == null) {\n      if (typeof document === \"undefined\") {\n        if (typeof OffscreenCanvas !== \"undefined\" && typeof OffscreenCanvasRenderingContext2D !== \"undefined\") {\n          fromPixels2DContext = new OffscreenCanvas(1, 1).getContext(\"2d\");\n        } else {\n          throw new Error(\"Cannot parse input in current context. Reason: OffscreenCanvas Context2D rendering is not supported.\");\n        }\n      } else {\n        fromPixels2DContext = document.createElement(\"canvas\").getContext(\"2d\", { willReadFrequently: true });\n      }\n    }\n    fromPixels2DContext.canvas.width = width;\n    fromPixels2DContext.canvas.height = height;\n    fromPixels2DContext.drawImage(pixels, 0, 0, width, height);\n    vals = fromPixels2DContext.getImageData(0, 0, width, height).data;\n  }\n  let values;\n  if (numChannels === 4) {\n    values = new Int32Array(vals);\n  } else {\n    const numPixels = width * height;\n    values = new Int32Array(numPixels * numChannels);\n    for (let i2 = 0; i2 < numPixels; i2++) {\n      for (let channel = 0; channel < numChannels; ++channel) {\n        values[i2 * numChannels + channel] = vals[i2 * 4 + channel];\n      }\n    }\n  }\n  const outShape = [height, width, numChannels];\n  return tensor3d(values, outShape, \"int32\");\n}\nfunction isPixelData(pixels) {\n  return pixels != null && pixels.data instanceof Uint8Array;\n}\nfunction isImageBitmapFullySupported() {\n  return typeof window !== \"undefined\" && typeof ImageBitmap !== \"undefined\" && window.hasOwnProperty(\"createImageBitmap\");\n}\nfunction isNonEmptyPixels(pixels) {\n  return pixels != null && pixels.width !== 0 && pixels.height !== 0;\n}\nfunction canWrapPixelsToImageBitmap(pixels) {\n  return isImageBitmapFullySupported() && !(pixels instanceof ImageBitmap) && isNonEmptyPixels(pixels) && !isPixelData(pixels);\n}\nasync function fromPixelsAsync(pixels, numChannels = 3) {\n  let inputs = null;\n  if (env().getBool(\"WRAP_TO_IMAGEBITMAP\") && canWrapPixelsToImageBitmap(pixels)) {\n    let imageBitmap;\n    try {\n      imageBitmap = await createImageBitmap(pixels, { premultiplyAlpha: \"none\" });\n    } catch (e2) {\n      imageBitmap = null;\n    }\n    if (imageBitmap != null && imageBitmap.width === pixels.width && imageBitmap.height === pixels.height) {\n      inputs = imageBitmap;\n    } else {\n      inputs = pixels;\n    }\n  } else {\n    inputs = pixels;\n  }\n  return fromPixels_(inputs, numChannels);\n}\nasync function toPixels(img, canvas) {\n  let $img = convertToTensor(img, \"img\", \"toPixels\");\n  if (!(img instanceof Tensor)) {\n    const originalImgTensor = $img;\n    $img = cast(originalImgTensor, \"int32\");\n    originalImgTensor.dispose();\n  }\n  if ($img.rank !== 2 && $img.rank !== 3) {\n    throw new Error(`toPixels only supports rank 2 or 3 tensors, got rank ${$img.rank}.`);\n  }\n  const [height, width] = $img.shape.slice(0, 2);\n  const depth = $img.rank === 2 ? 1 : $img.shape[2];\n  if (depth > 4 || depth === 2) {\n    throw new Error(`toPixels only supports depth of size 1, 3 or 4 but got ${depth}`);\n  }\n  if ($img.dtype !== \"float32\" && $img.dtype !== \"int32\") {\n    throw new Error(`Unsupported type for toPixels: ${$img.dtype}. Please use float32 or int32 tensors.`);\n  }\n  const data = await $img.data();\n  const multiplier = $img.dtype === \"float32\" ? 255 : 1;\n  const bytes = new Uint8ClampedArray(width * height * 4);\n  for (let i2 = 0; i2 < height * width; ++i2) {\n    const rgba = [0, 0, 0, 255];\n    for (let d = 0; d < depth; d++) {\n      const value = data[i2 * depth + d];\n      if ($img.dtype === \"float32\") {\n        if (value < 0 || value > 1) {\n          throw new Error(`Tensor values for a float32 Tensor must be in the range [0 - 1] but encountered ${value}.`);\n        }\n      } else if ($img.dtype === \"int32\") {\n        if (value < 0 || value > 255) {\n          throw new Error(`Tensor values for a int32 Tensor must be in the range [0 - 255] but encountered ${value}.`);\n        }\n      }\n      if (depth === 1) {\n        rgba[0] = value * multiplier;\n        rgba[1] = value * multiplier;\n        rgba[2] = value * multiplier;\n      } else {\n        rgba[d] = value * multiplier;\n      }\n    }\n    const j = i2 * 4;\n    bytes[j + 0] = Math.round(rgba[0]);\n    bytes[j + 1] = Math.round(rgba[1]);\n    bytes[j + 2] = Math.round(rgba[2]);\n    bytes[j + 3] = Math.round(rgba[3]);\n  }\n  if (canvas != null) {\n    canvas.width = width;\n    canvas.height = height;\n    const ctx = canvas.getContext(\"2d\");\n    const imageData = new ImageData(bytes, width, height);\n    ctx.putImageData(imageData, 0, 0);\n  }\n  if ($img !== img) {\n    $img.dispose();\n  }\n  return bytes;\n}\nvar fromPixels = op({ fromPixels_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/gather_nd_util.js\nvar gather_nd_util_exports = {};\n__export(gather_nd_util_exports, {\n  prepareAndValidate: () => prepareAndValidate\n});\nfunction prepareAndValidate(tensor2, indices) {\n  const tensorRank = tensor2.shape.length;\n  const indicesRank = indices.shape.length;\n  if (tensorRank < 1) {\n    throw new Error(`tf.gatherND() expects the input to be rank 1 or higher, but the rank was ${tensorRank}.`);\n  }\n  if (indicesRank < 1) {\n    throw new Error(`tf.gatherND() expects the indices to be rank 1 or higher, but the rank was ${indicesRank}.`);\n  }\n  if (indices.dtype !== \"int32\") {\n    throw new Error(`tf.gatherND() expects the indices to be int32 type, but the dtype was ${indices.dtype}.`);\n  }\n  if (indices.shape[indicesRank - 1] > tensorRank) {\n    throw new Error(`index innermost dimension length must be <= tensor rank; saw: ${indices.shape[indicesRank - 1]} vs. ${tensorRank}`);\n  }\n  if (sizeFromShape(tensor2.shape) === 0) {\n    throw new Error(`Requested more than 0 entries, but input is empty. Input shape: ${tensor2.shape}.`);\n  }\n  const indicesShape = indices.shape;\n  const sliceRank = indicesShape[indicesShape.length - 1];\n  let nResult = 1;\n  for (let i2 = 0; i2 < indicesShape.length - 1; ++i2) {\n    nResult *= indicesShape[i2];\n  }\n  const inputShape = tensor2.shape;\n  const resultShape = indicesShape.slice();\n  resultShape.pop();\n  let sliceSize = 1;\n  for (let i2 = sliceRank; i2 < tensorRank; ++i2) {\n    sliceSize *= inputShape[i2];\n    resultShape.push(inputShape[i2]);\n  }\n  const strides = [\n    ...computeStrides(tensor2.shape).map((stride) => stride / sliceSize),\n    1\n  ].slice(0, sliceRank);\n  return [resultShape, nResult, sliceSize, strides];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/scatter_nd_util.js\nvar scatter_nd_util_exports = {};\n__export(scatter_nd_util_exports, {\n  calculateShapes: () => calculateShapes,\n  validateInput: () => validateInput,\n  validateUpdateShape: () => validateUpdateShape\n});\nfunction validateUpdateShape(shape, indices, updates) {\n  const sliceDim = indices.rank > 1 ? indices.shape[indices.rank - 1] : 1;\n  const batchDim = indices.rank > 1 ? indices.rank - 1 : 1;\n  const shapeError = `Must have updates.shape = indices.shape[:batchDim] + shape[sliceDim:], got updates.shape: ${updates.shape}, indices.shape: ${indices.shape}, shape: ${shape}, sliceDim: ${sliceDim}, and batchDim: ${batchDim}.`;\n  if (updates.rank < batchDim) {\n    throw new Error(shapeError + ` update.rank < ${batchDim}. `);\n  }\n  if (shape.length < sliceDim + (updates.rank - batchDim)) {\n    throw new Error(shapeError + ` Output shape length < ${sliceDim + (updates.rank - batchDim)}`);\n  }\n  if (updates.rank !== batchDim + shape.length - sliceDim) {\n    throw new Error(shapeError + ` update.rank != ${batchDim + shape.length - sliceDim}`);\n  }\n  for (let d = 0; d < batchDim; ++d) {\n    if (updates.shape[d] !== indices.shape[d]) {\n      throw new Error(shapeError + ` updates.shape[${d}] (${updates.shape[d]}) != indices.shape[${d}] (${indices.shape[d]}).`);\n    }\n  }\n  for (let d = 0; d < updates.rank - batchDim; ++d) {\n    if (updates.shape[d + batchDim] !== shape[d + sliceDim]) {\n      throw new Error(shapeError + ` updates.shape[${d + batchDim}] (${updates.shape[d + batchDim]}) != shape[${d + batchDim}] (${shape[d + batchDim]})`);\n    }\n  }\n}\nfunction validateInput(updates, indices, shape) {\n  if (indices.rank < 1) {\n    throw new Error(`tf.scatterND() expects the indices to be rank 1 or higher, but the rank was ${indices.rank}.`);\n  }\n  if (updates.rank < 1) {\n    throw new Error(`tf.scatterND() expects the updates to be rank 1 or higher, but the rank was ${updates.rank}.`);\n  }\n  if (indices.dtype !== \"int32\") {\n    throw new Error(`The dtype of 'indices' should be int32, but got dtype: ${indices.dtype}`);\n  }\n  if (shape.length < 1) {\n    throw new Error(`Output rank must be greater or equal to 1, but got shape: ${shape}`);\n  }\n  if (shape.length === 0) {\n    if (indices.size === 0) {\n      throw new Error(`Indices specified for empty output. indices shape: ${indices.shape}`);\n    }\n    if (updates.size === 0) {\n      throw new Error(`Updates specified for empty output. updates shape: ${updates.shape}`);\n    }\n  }\n  validateUpdateShape(shape, indices, updates);\n}\nfunction calculateShapes(updates, indices, shape) {\n  const indicesRank = indices.shape.length;\n  const sliceRank = indicesRank > 1 ? indices.shape[indicesRank - 1] : 1;\n  const totalNd = shape.length;\n  let sliceSize = 1;\n  for (let i2 = sliceRank; i2 < totalNd; ++i2) {\n    sliceSize *= shape[i2];\n  }\n  const safeSliceDim = sliceRank < 1 ? 1 : sliceRank;\n  const numUpdates = sizeFromShape(indices.shape) / safeSliceDim;\n  const strides = [...computeStrides(shape.slice(0, sliceRank)), 1];\n  const outputSize = sizeFromShape(shape);\n  return { sliceRank, numUpdates, sliceSize, strides, outputSize };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/slice_util.js\nvar slice_util_exports = {};\n__export(slice_util_exports, {\n  assertParamsValid: () => assertParamsValid,\n  computeFlatOffset: () => computeFlatOffset,\n  computeOutShape: () => computeOutShape,\n  getNormalizedAxes: () => getNormalizedAxes,\n  isSliceContinous: () => isSliceContinous,\n  maskToAxes: () => maskToAxes,\n  parseSliceParams: () => parseSliceParams,\n  sliceInfo: () => sliceInfo,\n  startForAxis: () => startForAxis,\n  startIndicesWithElidedDims: () => startIndicesWithElidedDims,\n  stopForAxis: () => stopForAxis,\n  stopIndicesWithElidedDims: () => stopIndicesWithElidedDims,\n  stridesForAxis: () => stridesForAxis,\n  stridesWithElidedDims: () => stridesWithElidedDims\n});\nvar NEW_AXIS = -2;\nvar SHRINK_AXIS = -1;\nfunction assertParamsValid(input2, begin, size) {\n  const inputRank = input2.shape.length;\n  assert(inputRank === begin.length, () => `Error in slice${inputRank}D: Length of begin ${begin} must match the rank of the array (${inputRank}).`);\n  assert(inputRank === size.length, () => `Error in slice${inputRank}D: Length of size ${size} must match the rank of the array (${inputRank}).`);\n  for (let i2 = 0; i2 < inputRank; ++i2) {\n    assert(begin[i2] + size[i2] <= input2.shape[i2], () => `Error in slice${inputRank}D: begin[${i2}] + size[${i2}] (${begin[i2] + size[i2]}) would overflow input.shape[${i2}] (${input2.shape[i2]})`);\n  }\n}\nfunction maskToAxes(mask) {\n  const axes = [];\n  let axis = 0;\n  while (mask > 0) {\n    if (mask & 1) {\n      axes.push(axis);\n    }\n    mask /= 2;\n    axis++;\n  }\n  return axes;\n}\nfunction computeOutShape(begin, end, strides) {\n  const size = [];\n  for (let axis = 0; axis < begin.length; axis++) {\n    size[axis] = Math.ceil((end[axis] - begin[axis]) / strides[axis]);\n  }\n  return size;\n}\nfunction stridesWithElidedDims(strides, ellipsisInsertionIndex, numElidedAxes, inputShape) {\n  const newStrides = [...strides];\n  for (let i2 = newStrides.length; i2 < inputShape.length; i2++) {\n    newStrides.push(1);\n  }\n  for (let i2 = 0; i2 < numElidedAxes; i2++) {\n    if (i2 === 0) {\n      newStrides[ellipsisInsertionIndex] = 1;\n    } else {\n      newStrides.splice(ellipsisInsertionIndex, 0, 1);\n      newStrides.pop();\n    }\n  }\n  return newStrides;\n}\nfunction unnormalizeAxis(ellipsisInsertionIndex, numElidedAxes, normalizedAxis) {\n  if (normalizedAxis <= ellipsisInsertionIndex) {\n    return normalizedAxis;\n  }\n  return normalizedAxis - (numElidedAxes - 1);\n}\nfunction getElidedAxes(numElidedAxes, ellipsisInsertionIndex) {\n  const elidedAxes = [];\n  for (let i2 = 0; i2 < numElidedAxes; i2++) {\n    elidedAxes.push(ellipsisInsertionIndex + i2);\n  }\n  return elidedAxes;\n}\nfunction getNormalizedAxes(inputShape, ellipsisAxes, numInterpolatedAxes, begin, end, strides, beginMask, endMask, ellipsisMask) {\n  const inputRank = inputShape.length;\n  let normalizedBegin = new Array(inputRank), normalizedEnd = new Array(inputRank), normalizedStrides = new Array(inputRank);\n  if (ellipsisAxes.length && numInterpolatedAxes > 0) {\n    const fullIndex = ellipsisAxes[0];\n    const numElidedAxes = numInterpolatedAxes + 1;\n    normalizedBegin = startIndicesWithElidedDims(beginMask, fullIndex, numElidedAxes, begin, inputShape);\n    normalizedEnd = stopIndicesWithElidedDims(endMask, fullIndex, numElidedAxes, end, inputShape);\n    normalizedStrides = stridesWithElidedDims(strides, fullIndex, numElidedAxes, inputShape);\n  } else {\n    for (let axis = 0; axis < inputRank; axis++) {\n      normalizedBegin[axis] = startForAxis(beginMask, begin, strides, inputShape, axis, ellipsisMask);\n      normalizedEnd[axis] = stopForAxis(endMask, end, strides, inputShape, axis, ellipsisMask);\n      normalizedStrides[axis] = stridesForAxis(strides, axis, ellipsisMask);\n    }\n  }\n  return {\n    begin: normalizedBegin,\n    end: normalizedEnd,\n    strides: normalizedStrides\n  };\n}\nfunction startIndicesWithElidedDims(beginMask, ellipsisInsertionIndex, numElidedAxes, originalBegin, inputShape) {\n  const newIndices = [...inputShape];\n  const elidedAxes = getElidedAxes(numElidedAxes, ellipsisInsertionIndex);\n  for (let axis = 0; axis < newIndices.length; axis++) {\n    if (elidedAxes.indexOf(axis) > -1) {\n      newIndices[axis] = 0;\n    } else {\n      const originalAxis = unnormalizeAxis(ellipsisInsertionIndex, numElidedAxes, axis);\n      let originalValue = originalBegin[originalAxis];\n      if (beginMask & 1 << originalAxis) {\n        originalValue = 0;\n      }\n      newIndices[axis] = originalValue;\n    }\n  }\n  return newIndices;\n}\nfunction stopIndicesWithElidedDims(endMask, ellipsisInsertionIndex, numElidedAxes, originalEnd, inputShape) {\n  const newIndices = [...inputShape];\n  const elidedAxes = getElidedAxes(numElidedAxes, ellipsisInsertionIndex);\n  for (let axis = 0; axis < newIndices.length; axis++) {\n    if (elidedAxes.indexOf(axis) > -1) {\n      newIndices[axis] = Number.MAX_SAFE_INTEGER;\n    } else {\n      const originalAxis = unnormalizeAxis(ellipsisInsertionIndex, numElidedAxes, axis);\n      let originalValue = originalEnd[originalAxis];\n      if (endMask & 1 << originalAxis) {\n        originalValue = Number.MAX_SAFE_INTEGER;\n      }\n      newIndices[axis] = originalValue;\n    }\n  }\n  for (let i2 = 0; i2 < newIndices.length; i2++) {\n    const axisSize = inputShape[i2];\n    if (newIndices[i2] < 0) {\n      newIndices[i2] += axisSize;\n    }\n    newIndices[i2] = clamp(0, newIndices[i2], inputShape[i2]);\n  }\n  return newIndices;\n}\nfunction stridesForAxis(strides, axis, ellipsisMask) {\n  let stride = strides[axis];\n  if (ellipsisMask & 1 << axis || stride == null) {\n    stride = 1;\n  }\n  return stride;\n}\nfunction startForAxis(beginMask, startIndices, strides, inputShape, axis, ellipsisMask) {\n  let start = startIndices[axis];\n  const stride = strides[axis] || 1;\n  if (beginMask & 1 << axis || ellipsisMask & 1 << axis || start == null) {\n    if (stride > 0) {\n      start = Number.MIN_SAFE_INTEGER;\n    } else {\n      start = Number.MAX_SAFE_INTEGER;\n    }\n  }\n  const axisSize = inputShape[axis];\n  if (start < 0) {\n    start += axisSize;\n  }\n  start = clamp(0, start, axisSize - 1);\n  return start;\n}\nfunction stopForAxis(endMask, stopIndices, strides, inputShape, axis, ellipsisMask) {\n  let stop = stopIndices[axis];\n  const stride = strides[axis] || 1;\n  if (endMask & 1 << axis || ellipsisMask & 1 << axis || stop == null) {\n    if (stride > 0) {\n      stop = Number.MAX_SAFE_INTEGER;\n    } else {\n      stop = Number.MIN_SAFE_INTEGER;\n    }\n  }\n  const axisSize = inputShape[axis];\n  if (stop < 0) {\n    stop += axisSize;\n  }\n  if (stride > 0) {\n    stop = clamp(0, stop, axisSize);\n  } else {\n    stop = clamp(-1, stop, axisSize - 1);\n  }\n  return stop;\n}\nfunction isSliceContinous(shape, begin, size) {\n  let firstNonOneAxis = size.length;\n  for (let i2 = 0; i2 < size.length; i2++) {\n    if (size[i2] > 1) {\n      firstNonOneAxis = i2;\n      break;\n    }\n  }\n  for (let i2 = firstNonOneAxis + 1; i2 < size.length; i2++) {\n    if (begin[i2] > 0 || size[i2] !== shape[i2]) {\n      return false;\n    }\n  }\n  return true;\n}\nfunction computeFlatOffset(begin, strides) {\n  let flatOffset = begin.length > 0 ? begin[begin.length - 1] : 1;\n  for (let i2 = 0; i2 < begin.length - 1; i2++) {\n    flatOffset += begin[i2] * strides[i2];\n  }\n  return flatOffset;\n}\nfunction parseSliceParams(x, begin, size) {\n  let begin_;\n  const xRank = x.shape.length;\n  if (typeof begin === \"number\") {\n    begin_ = [begin, ...new Array(xRank - 1).fill(0)];\n  } else if (begin.length < xRank) {\n    begin_ = begin.concat(new Array(xRank - begin.length).fill(0));\n  } else {\n    begin_ = begin.slice();\n  }\n  begin_.forEach((d) => {\n    assert(d !== -1, () => \"slice() does not support negative begin indexing.\");\n  });\n  let size_;\n  if (size == null) {\n    size_ = new Array(xRank).fill(-1);\n  } else if (typeof size === \"number\") {\n    size_ = [size, ...new Array(xRank - 1).fill(-1)];\n  } else if (size.length < xRank) {\n    size_ = size.concat(new Array(xRank - size.length).fill(-1));\n  } else {\n    size_ = size;\n  }\n  size_ = size_.map((d, i2) => {\n    if (d >= 0) {\n      return d;\n    } else {\n      assert(d === -1, () => `Negative size values should be exactly -1 but got ${d} for the slice() size at index ${i2}.`);\n      return x.shape[i2] - begin_[i2];\n    }\n  });\n  return [begin_, size_];\n}\nfunction sliceInfo(xShape, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask) {\n  let stridesNonNull;\n  if (strides == null) {\n    stridesNonNull = new Array(begin.length);\n    stridesNonNull.fill(1);\n  } else {\n    stridesNonNull = strides;\n  }\n  if (ellipsisMask != null && (ellipsisMask & ellipsisMask - 1) !== 0) {\n    throw new Error(\"Multiple ellipses in slice is not allowed.\");\n  }\n  let ellipsisSeen = false;\n  const sparseSpec = {\n    dims: stridesNonNull.length,\n    numAddAxisAfterEllipsis: 0,\n    begin: begin.slice(),\n    end: end.slice(),\n    strides: stridesNonNull.slice(),\n    beginMask,\n    endMask,\n    ellipsisMask,\n    newAxisMask,\n    shrinkAxisMask\n  };\n  for (let i2 = 0; i2 < sparseSpec.dims; i2++) {\n    if (ellipsisSeen && (1 << i2 & newAxisMask) !== 0) {\n      sparseSpec.numAddAxisAfterEllipsis++;\n    }\n    if (1 << i2 & ellipsisMask) {\n      ellipsisSeen = true;\n    }\n  }\n  if (!ellipsisSeen) {\n    sparseSpec.ellipsisMask |= 1 << sparseSpec.dims;\n    sparseSpec.dims++;\n  }\n  const denseSpec = {\n    dims: xShape.length,\n    beginMask: 0,\n    endMask: 0,\n    beginValid: false,\n    endValid: false\n  };\n  buildDenseSpec(sparseSpec, denseSpec);\n  let isIdentity = true;\n  let sliceDim0 = true;\n  let isSimpleSlice = true;\n  const processingShape = [];\n  const finalShape = [];\n  for (let i2 = 0; i2 < xShape.length; ++i2) {\n    if (denseSpec.strides[i2] === 0) {\n      throw Error(`strides[${i2}] must be non-zero`);\n    }\n    const shrinkI = !!(denseSpec.shrinkAxisMask & 1 << i2);\n    const dimI = xShape[i2];\n    if (dimI === -1) {\n      processingShape.push(shrinkI ? 1 : -1);\n      continue;\n    }\n    const masks = [denseSpec.beginMask & 1 << i2, denseSpec.endMask & 1 << i2];\n    const validRange = [\n      denseSpec.strides[i2] > 0 ? 0 : -1,\n      denseSpec.strides[i2] > 0 ? dimI : dimI - 1\n    ];\n    if (shrinkI && denseSpec.strides[i2] <= 0) {\n      throw Error(\"only stride 1 allowed on non-range indexing.\");\n    }\n    isSimpleSlice = isSimpleSlice && denseSpec.strides[i2] === 1;\n    const beginAndEndMasked = !!(denseSpec.beginMask & 1 << i2 && denseSpec.endMask & 1 << i2);\n    if (denseSpec.beginValid && denseSpec.endValid) {\n      if (shrinkI) {\n        const xFwd = denseSpec.begin[i2] < 0 ? dimI + denseSpec.begin[i2] : denseSpec.begin[i2];\n        denseSpec.begin[i2] = xFwd;\n        denseSpec.end[i2] = denseSpec.begin[i2] + 1;\n        if (xFwd < 0 || xFwd >= dimI) {\n          throw Error(`slice index ${denseSpec.begin[i2]} of dimension ${i2} out of bounds.`);\n        }\n      } else {\n        denseSpec.begin[i2] = canonical(denseSpec.begin[i2], 0, denseSpec.strides[i2], dimI, masks, validRange);\n        denseSpec.end[i2] = canonical(denseSpec.end[i2], 1, denseSpec.strides[i2], dimI, masks, validRange);\n      }\n      const takeAllInDimension = denseSpec.strides[i2] === 1 && denseSpec.begin[i2] === 0 && denseSpec.end[i2] === dimI;\n      isIdentity = isIdentity && takeAllInDimension;\n      sliceDim0 = sliceDim0 && (i2 === 0 && denseSpec.strides[i2] === 1 || takeAllInDimension);\n    } else {\n      isIdentity = isIdentity && (denseSpec.strides[i2] === 1 && beginAndEndMasked);\n      sliceDim0 = sliceDim0 && (i2 === 0 && denseSpec.strides[i2] === 1 || beginAndEndMasked);\n    }\n    let intervalLength;\n    let knownInterval = false;\n    if (denseSpec.beginValid && denseSpec.endValid) {\n      intervalLength = denseSpec.end[i2] - denseSpec.begin[i2];\n      knownInterval = true;\n    } else if (shrinkI) {\n      intervalLength = 1;\n      knownInterval = true;\n    } else if (beginAndEndMasked) {\n      if (dimI >= 0) {\n        if (denseSpec.strides[i2] < 0) {\n          intervalLength = -dimI;\n        } else {\n          intervalLength = dimI;\n        }\n        knownInterval = true;\n      }\n    }\n    if (knownInterval) {\n      let sizeI;\n      if (intervalLength === 0 || intervalLength < 0 !== denseSpec.strides[i2] < 0) {\n        sizeI = 0;\n      } else {\n        sizeI = Math.trunc(intervalLength / denseSpec.strides[i2]) + (intervalLength % denseSpec.strides[i2] !== 0 ? 1 : 0);\n      }\n      processingShape.push(sizeI);\n    } else {\n      processingShape.push(-1);\n    }\n  }\n  for (let denseDim = 0; denseDim < denseSpec.finalShapeGatherIndices.length; ++denseDim) {\n    const gatherIndex = denseSpec.finalShapeGatherIndices[denseDim];\n    if (gatherIndex >= 0) {\n      finalShape.push(processingShape[gatherIndex]);\n    } else if (gatherIndex === NEW_AXIS) {\n      finalShape.push(1);\n    }\n  }\n  const finalShapeSparse = finalShape.filter((dim, i2) => denseSpec.finalShapeGatherIndices[i2] !== NEW_AXIS);\n  return {\n    finalShapeSparse,\n    finalShape,\n    isIdentity,\n    sliceDim0,\n    isSimpleSlice,\n    begin: denseSpec.begin,\n    end: denseSpec.end,\n    strides: denseSpec.strides\n  };\n}\nfunction buildDenseSpec(sparse2, dense2) {\n  dense2.beginMask = 0;\n  dense2.endMask = 0;\n  dense2.shrinkAxisMask = 0;\n  let fullIndex = 0;\n  dense2.beginValid = sparse2.begin != null;\n  dense2.endValid = sparse2.end != null;\n  dense2.begin = new Array(dense2.dims);\n  dense2.end = new Array(dense2.dims);\n  dense2.strides = new Array(dense2.dims);\n  dense2.finalShapeGatherIndices = [];\n  dense2.finalShapeGatherIndicesSparse = [];\n  dense2.inputShapeGatherIndicesSparse = new Array(dense2.dims);\n  for (let i2 = 0; i2 < sparse2.dims; i2++) {\n    if (1 << i2 & sparse2.ellipsisMask) {\n      const nextIndex = Math.min(dense2.dims - (sparse2.dims - i2) + 1 + sparse2.numAddAxisAfterEllipsis, dense2.dims);\n      for (; fullIndex < nextIndex; fullIndex++) {\n        dense2.begin[fullIndex] = 0;\n        dense2.end[fullIndex] = 0;\n        dense2.strides[fullIndex] = 1;\n        dense2.beginMask |= 1 << fullIndex;\n        dense2.endMask |= 1 << fullIndex;\n        dense2.finalShapeGatherIndices.push(fullIndex);\n        dense2.finalShapeGatherIndicesSparse.push(-1);\n        dense2.inputShapeGatherIndicesSparse[fullIndex] = i2;\n      }\n    } else if (1 << i2 & sparse2.newAxisMask) {\n      dense2.finalShapeGatherIndices.push(NEW_AXIS);\n      dense2.finalShapeGatherIndicesSparse.push(-1);\n    } else {\n      if (fullIndex === dense2.begin.length) {\n        throw Error(`Index out of range using input dim ${fullIndex}; input has only ${dense2.dims} dims, ${dense2.begin.length}.`);\n      }\n      if (sparse2.begin != null) {\n        dense2.begin[fullIndex] = sparse2.begin[i2];\n      }\n      if (sparse2.end != null) {\n        dense2.end[fullIndex] = sparse2.end[i2];\n      }\n      dense2.strides[fullIndex] = sparse2.strides[i2];\n      if (sparse2.beginMask & 1 << i2) {\n        dense2.beginMask |= 1 << fullIndex;\n      }\n      if (sparse2.endMask & 1 << i2) {\n        dense2.endMask |= 1 << fullIndex;\n      }\n      if (sparse2.shrinkAxisMask & 1 << i2) {\n        dense2.finalShapeGatherIndices.push(SHRINK_AXIS);\n        dense2.finalShapeGatherIndicesSparse.push(-1);\n        dense2.shrinkAxisMask |= 1 << fullIndex;\n      } else {\n        dense2.finalShapeGatherIndices.push(fullIndex);\n        dense2.finalShapeGatherIndicesSparse.push(i2);\n      }\n      dense2.inputShapeGatherIndicesSparse[fullIndex] = i2;\n      fullIndex++;\n    }\n  }\n}\nfunction canonical(x, c, strideI, dimI, masks, validRange) {\n  if (masks[c]) {\n    return strideI > 0 ? validRange[c] : validRange[c + 1 & 1];\n  } else {\n    const xFwd = x < 0 ? dimI + x : x;\n    return xFwd < validRange[0] ? validRange[0] : xFwd > validRange[1] ? validRange[1] : xFwd;\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/serialization.js\nvar serialization_exports = {};\n__export(serialization_exports, {\n  Serializable: () => Serializable,\n  SerializationMap: () => SerializationMap,\n  registerClass: () => registerClass\n});\nvar Serializable = class {\n  getClassName() {\n    return this.constructor.className;\n  }\n  static fromConfig(cls, config) {\n    return new cls(config);\n  }\n};\nvar SerializationMap = class {\n  constructor() {\n    this.classNameMap = {};\n  }\n  static getMap() {\n    if (SerializationMap.instance == null) {\n      SerializationMap.instance = new SerializationMap();\n    }\n    return SerializationMap.instance;\n  }\n  static register(cls) {\n    SerializationMap.getMap().classNameMap[cls.className] = [cls, cls.fromConfig];\n  }\n};\nfunction registerClass(cls) {\n  assert(cls.className != null, () => `Class being registered does not have the static className property defined.`);\n  assert(typeof cls.className === \"string\", () => `className is required to be a string, but got type ` + typeof cls.className);\n  assert(cls.className.length > 0, () => `Class being registered has an empty-string as its className, which is disallowed.`);\n  SerializationMap.register(cls);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/test_util.js\nvar test_util_exports = {};\n__export(test_util_exports, {\n  TEST_EPSILON_FLOAT16: () => TEST_EPSILON_FLOAT16,\n  encodeStrings: () => encodeStrings,\n  expectArrayBuffersEqual: () => expectArrayBuffersEqual,\n  expectArraysClose: () => expectArraysClose,\n  expectArraysEqual: () => expectArraysEqual,\n  expectNumbersClose: () => expectNumbersClose,\n  expectPromiseToFail: () => expectPromiseToFail,\n  expectValuesInRange: () => expectValuesInRange,\n  testEpsilon: () => testEpsilon\n});\nvar TEST_EPSILON_FLOAT32 = 1e-3;\nvar TEST_EPSILON_FLOAT16 = 0.1;\nfunction expectArraysClose(actual, expected, epsilon3) {\n  if (epsilon3 == null) {\n    epsilon3 = testEpsilon();\n  }\n  return expectArraysPredicate(actual, expected, (a, b) => areClose(a, b, epsilon3));\n}\nfunction testEpsilon() {\n  return ENGINE.backend.floatPrecision() === 32 ? TEST_EPSILON_FLOAT32 : TEST_EPSILON_FLOAT16;\n}\nfunction expectArraysPredicate(actual, expected, predicate) {\n  let checkClassType = true;\n  if (isTypedArray(actual) || isTypedArray(expected)) {\n    checkClassType = false;\n  }\n  if (isTypedArray(actual) && isTypedArray(expected)) {\n    checkClassType = true;\n  }\n  if (checkClassType) {\n    const aType = actual.constructor.name;\n    const bType = expected.constructor.name;\n    if (aType !== bType) {\n      throw new Error(`Arrays are of different type. Actual: ${aType}. Expected: ${bType}`);\n    }\n  }\n  if (Array.isArray(actual) && Array.isArray(expected)) {\n    const actualShape = inferShape(actual);\n    const expectedShape = inferShape(expected);\n    if (!arraysEqual(actualShape, expectedShape)) {\n      throw new Error(`Arrays have different shapes. Actual: [${actualShape}]. Expected: [${expectedShape}]`);\n    }\n  }\n  const actualFlat = isTypedArray(actual) ? actual : flatten(actual);\n  const expectedFlat = isTypedArray(expected) ? expected : flatten(expected);\n  if (actualFlat.length !== expectedFlat.length) {\n    throw new Error(`Arrays have different lengths actual: ${actualFlat.length} vs expected: ${expectedFlat.length}.\nActual:   ${actualFlat}.\nExpected: ${expectedFlat}.`);\n  }\n  for (let i2 = 0; i2 < expectedFlat.length; ++i2) {\n    const a = actualFlat[i2];\n    const e2 = expectedFlat[i2];\n    if (!predicate(a, e2)) {\n      throw new Error(`Arrays differ: actual[${i2}] = ${a}, expected[${i2}] = ${e2}.\nActual:   ${actualFlat}.\nExpected: ${expectedFlat}.`);\n    }\n  }\n}\nfunction expectPromiseToFail(fn, done) {\n  fn().then(() => done.fail(), () => done());\n}\nfunction expectArraysEqual(actual, expected) {\n  const exp5 = typeof expected === \"string\" || typeof expected === \"number\" || typeof expected === \"boolean\" ? [expected] : expected;\n  if (isString(actual) || isString(actual[0]) || isString(expected) || isString(expected[0])) {\n    return expectArraysPredicate(actual, exp5, (a, b) => a == b);\n  }\n  return expectArraysPredicate(actual, expected, (a, b) => areClose(a, b, 0));\n}\nfunction expectNumbersClose(a, e2, epsilon3) {\n  if (epsilon3 == null) {\n    epsilon3 = testEpsilon();\n  }\n  if (!areClose(a, e2, epsilon3)) {\n    throw new Error(`Numbers differ: actual === ${a}, expected === ${e2}`);\n  }\n}\nfunction areClose(a, e2, epsilon3) {\n  if (!isFinite(a) && !isFinite(e2)) {\n    return true;\n  }\n  if (isNaN(a) || isNaN(e2) || Math.abs(a - e2) > epsilon3) {\n    return false;\n  }\n  return true;\n}\nfunction expectValuesInRange(actual, low, high) {\n  for (let i2 = 0; i2 < actual.length; i2++) {\n    if (actual[i2] < low || actual[i2] > high) {\n      throw new Error(`Value out of range:${actual[i2]} low: ${low}, high: ${high}`);\n    }\n  }\n}\nfunction expectArrayBuffersEqual(actual, expected) {\n  const actualArray = new Float32Array(actual);\n  const expectedArray = new Float32Array(expected);\n  if (actualArray.length !== expectedArray.length) {\n    throw new Error(`Expected ArrayBuffer to be of length ${expectedArray.length}, but it was ${actualArray.length}`);\n  }\n  for (let i2 = 0; i2 < expectedArray.length; i2++) {\n    if (actualArray[i2] !== expectedArray[i2]) {\n      throw new Error(`Expected ArrayBuffer value at ${i2} to be ${expectedArray[i2]} but got ${actualArray[i2]} instead`);\n    }\n  }\n}\nfunction encodeStrings(a) {\n  for (let i2 = 0; i2 < a.length; i2++) {\n    const val = a[i2];\n    if (Array.isArray(val)) {\n      encodeStrings(val);\n    } else {\n      a[i2] = encodeString(val);\n    }\n  }\n  return a;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/version.js\nvar version = \"3.19.0\";\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/add.js\nfunction add_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"add\");\n  let $b = convertToTensor(b, \"b\", \"add\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Add, inputs);\n}\nvar add2 = op({ add_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/floorDiv.js\nfunction floorDiv_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"floorDiv\");\n  let $b = convertToTensor(b, \"b\", \"floorDiv\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(FloorDiv, inputs);\n}\nvar floorDiv = op({ floorDiv_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/div.js\nfunction div_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"div\");\n  let $b = convertToTensor(b, \"b\", \"div\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  if ($a.dtype === \"int32\" && $b.dtype === \"int32\") {\n    return floorDiv($a, $b);\n  }\n  const inputs = { a: $a, b: $b };\n  const attrs = {};\n  return ENGINE.runKernel(RealDiv, inputs, attrs);\n}\nvar div = op({ div_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/mul.js\nfunction mul_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"mul\");\n  let $b = convertToTensor(b, \"b\", \"mul\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Multiply, inputs);\n}\nvar mul = op({ mul_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/abs.js\nfunction abs_(x) {\n  const $x = convertToTensor(x, \"x\", \"abs\");\n  if ($x.dtype === \"complex64\") {\n    const inputs = { x: $x };\n    return ENGINE.runKernel(ComplexAbs, inputs);\n  } else {\n    const inputs = { x: $x };\n    return ENGINE.runKernel(Abs, inputs);\n  }\n}\nvar abs = op({ abs_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/acos.js\nfunction acos_(x) {\n  const $x = convertToTensor(x, \"x\", \"acos\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Acos, inputs);\n}\nvar acos = op({ acos_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/acosh.js\nfunction acosh_(x) {\n  const $x = convertToTensor(x, \"x\", \"acosh\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Acosh, inputs);\n}\nvar acosh = op({ acosh_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/add_n.js\nfunction addN_(tensors) {\n  assert(Array.isArray(tensors), () => \"The argument passed to tf.addN() must be a list of tensors\");\n  assert(tensors.length >= 1, () => `Must pass at least one tensor to tf.addN(), but got ${tensors.length}`);\n  const $tensors = tensors.map((t2, i2) => convertToTensor(t2, `tensors${i2}`, \"addN\"));\n  const firstTensor = $tensors[0];\n  $tensors.forEach((t2) => {\n    if (t2.dtype !== firstTensor.dtype) {\n      throw new Error(\"All tensors passed to tf.addN() must have the same dtype\");\n    }\n  });\n  $tensors.forEach((t2) => {\n    if (!arraysEqual(t2.shape, firstTensor.shape)) {\n      throw new Error(\"All tensors passed to tf.addN() must have the same shape\");\n    }\n  });\n  const inputs = $tensors;\n  return ENGINE.runKernel(AddN, inputs);\n}\nvar addN = op({ addN_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/all.js\nfunction all_(x, axis = null, keepDims = false) {\n  const $x = convertToTensor(x, \"x\", \"all\", \"bool\");\n  const inputs = { x: $x };\n  const attrs = { axis, keepDims };\n  return ENGINE.runKernel(All, inputs, attrs);\n}\nvar all = op({ all_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/any.js\nfunction any_(x, axis = null, keepDims = false) {\n  const $x = convertToTensor(x, \"x\", \"any\", \"bool\");\n  const inputs = { x: $x };\n  const attrs = { axis, keepDims };\n  return ENGINE.runKernel(Any, inputs, attrs);\n}\nvar any = op({ any_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/arg_max.js\nfunction argMax_(x, axis = 0) {\n  const $x = convertToTensor(x, \"x\", \"argMax\");\n  const inputs = { x: $x };\n  const attrs = { axis };\n  return ENGINE.runKernel(ArgMax, inputs, attrs);\n}\nvar argMax = op({ argMax_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/arg_min.js\nfunction argMin_(x, axis = 0) {\n  const $x = convertToTensor(x, \"x\", \"argMin\");\n  const inputs = { x: $x };\n  const attrs = { axis };\n  return ENGINE.runKernel(ArgMin, inputs, attrs);\n}\nvar argMin = op({ argMin_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/asin.js\nfunction asin_(x) {\n  const $x = convertToTensor(x, \"x\", \"asin\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Asin, inputs);\n}\nvar asin = op({ asin_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/asinh.js\nfunction asinh_(x) {\n  const $x = convertToTensor(x, \"x\", \"asinh\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Asinh, inputs);\n}\nvar asinh = op({ asinh_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/atan.js\nfunction atan_(x) {\n  const $x = convertToTensor(x, \"x\", \"atan\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Atan, inputs);\n}\nvar atan = op({ atan_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/atan2.js\nfunction atan2_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"atan2\");\n  let $b = convertToTensor(b, \"b\", \"atan2\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Atan2, inputs);\n}\nvar atan2 = op({ atan2_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/atanh.js\nfunction atanh_(x) {\n  const $x = convertToTensor(x, \"x\", \"atanh\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Atanh, inputs);\n}\nvar atanh = op({ atanh_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv_util.js\nfunction computeDilation2DInfo(inputShape, filterShape, strides, pad3, dataFormat = \"NHWC\", dilations) {\n  const inputChannels = inputShape[3];\n  const $filterShape = [...filterShape, inputChannels];\n  const $dataFormat = convertConv2DDataFormat(dataFormat);\n  return computeConv2DInfo(inputShape, $filterShape, strides, dilations, pad3, null, null, $dataFormat);\n}\nfunction computePool2DInfo(inShape, filterSize, strides, dilations, pad3, roundingMode, dataFormat = \"channelsLast\") {\n  const [filterHeight, filterWidth] = parseTupleParam(filterSize);\n  let filterShape;\n  if (dataFormat === \"channelsLast\") {\n    filterShape = [filterHeight, filterWidth, inShape[3], inShape[3]];\n  } else if (dataFormat === \"channelsFirst\") {\n    filterShape = [filterHeight, filterWidth, inShape[1], inShape[1]];\n  } else {\n    throw new Error(`Unknown dataFormat ${dataFormat}`);\n  }\n  return computeConv2DInfo(inShape, filterShape, strides, dilations, pad3, roundingMode, false, dataFormat);\n}\nfunction computePool3DInfo(inShape, filterSize, strides, dilations, pad3, roundingMode, dataFormat = \"NDHWC\") {\n  const [filterDepth, filterHeight, filterWidth] = parse3TupleParam(filterSize);\n  let filterShape;\n  let $dataFormat;\n  if (dataFormat === \"NDHWC\") {\n    $dataFormat = \"channelsLast\";\n    filterShape = [filterDepth, filterHeight, filterWidth, inShape[4], inShape[4]];\n  } else if (dataFormat === \"NCDHW\") {\n    $dataFormat = \"channelsFirst\";\n    filterShape = [filterDepth, filterHeight, filterWidth, inShape[1], inShape[1]];\n  } else {\n    throw new Error(`Unknown dataFormat ${dataFormat}`);\n  }\n  return computeConv3DInfo(inShape, filterShape, strides, dilations, pad3, false, $dataFormat, roundingMode);\n}\nfunction computeConv2DInfo(inShape, filterShape, strides, dilations, pad3, roundingMode, depthwise = false, dataFormat = \"channelsLast\") {\n  let [batchSize, inHeight, inWidth, inChannels] = [-1, -1, -1, -1];\n  if (dataFormat === \"channelsLast\") {\n    [batchSize, inHeight, inWidth, inChannels] = inShape;\n  } else if (dataFormat === \"channelsFirst\") {\n    [batchSize, inChannels, inHeight, inWidth] = inShape;\n  } else {\n    throw new Error(`Unknown dataFormat ${dataFormat}`);\n  }\n  const [filterHeight, filterWidth, , filterChannels] = filterShape;\n  const [strideHeight, strideWidth] = parseTupleParam(strides);\n  const [dilationHeight, dilationWidth] = parseTupleParam(dilations);\n  const effectiveFilterHeight = getEffectiveFilterSize(filterHeight, dilationHeight);\n  const effectiveFilterWidth = getEffectiveFilterSize(filterWidth, dilationWidth);\n  const { padInfo, outHeight, outWidth } = getPadAndOutInfo(pad3, inHeight, inWidth, strideHeight, strideWidth, effectiveFilterHeight, effectiveFilterWidth, roundingMode, dataFormat);\n  const outChannels = depthwise ? filterChannels * inChannels : filterChannels;\n  let outShape;\n  if (dataFormat === \"channelsFirst\") {\n    outShape = [batchSize, outChannels, outHeight, outWidth];\n  } else if (dataFormat === \"channelsLast\") {\n    outShape = [batchSize, outHeight, outWidth, outChannels];\n  }\n  return {\n    batchSize,\n    dataFormat,\n    inHeight,\n    inWidth,\n    inChannels,\n    outHeight,\n    outWidth,\n    outChannels,\n    padInfo,\n    strideHeight,\n    strideWidth,\n    filterHeight,\n    filterWidth,\n    effectiveFilterHeight,\n    effectiveFilterWidth,\n    dilationHeight,\n    dilationWidth,\n    inShape,\n    outShape,\n    filterShape\n  };\n}\nfunction computeConv3DInfo(inShape, filterShape, strides, dilations, pad3, depthwise = false, dataFormat = \"channelsLast\", roundingMode) {\n  let [batchSize, inDepth, inHeight, inWidth, inChannels] = [-1, -1, -1, -1, -1];\n  if (dataFormat === \"channelsLast\") {\n    [batchSize, inDepth, inHeight, inWidth, inChannels] = inShape;\n  } else if (dataFormat === \"channelsFirst\") {\n    [batchSize, inChannels, inDepth, inHeight, inWidth] = inShape;\n  } else {\n    throw new Error(`Unknown dataFormat ${dataFormat}`);\n  }\n  const [filterDepth, filterHeight, filterWidth, , filterChannels] = filterShape;\n  const [strideDepth, strideHeight, strideWidth] = parse3TupleParam(strides);\n  const [dilationDepth, dilationHeight, dilationWidth] = parse3TupleParam(dilations);\n  const effectiveFilterDepth = getEffectiveFilterSize(filterDepth, dilationDepth);\n  const effectiveFilterHeight = getEffectiveFilterSize(filterHeight, dilationHeight);\n  const effectiveFilterWidth = getEffectiveFilterSize(filterWidth, dilationWidth);\n  const { padInfo, outDepth, outHeight, outWidth } = get3DPadAndOutInfo(pad3, inDepth, inHeight, inWidth, strideDepth, strideHeight, strideWidth, effectiveFilterDepth, effectiveFilterHeight, effectiveFilterWidth, roundingMode);\n  const outChannels = depthwise ? filterChannels * inChannels : filterChannels;\n  let outShape;\n  if (dataFormat === \"channelsFirst\") {\n    outShape = [batchSize, outChannels, outDepth, outHeight, outWidth];\n  } else if (dataFormat === \"channelsLast\") {\n    outShape = [batchSize, outDepth, outHeight, outWidth, outChannels];\n  }\n  return {\n    batchSize,\n    dataFormat,\n    inDepth,\n    inHeight,\n    inWidth,\n    inChannels,\n    outDepth,\n    outHeight,\n    outWidth,\n    outChannels,\n    padInfo,\n    strideDepth,\n    strideHeight,\n    strideWidth,\n    filterDepth,\n    filterHeight,\n    filterWidth,\n    effectiveFilterDepth,\n    effectiveFilterHeight,\n    effectiveFilterWidth,\n    dilationDepth,\n    dilationHeight,\n    dilationWidth,\n    inShape,\n    outShape,\n    filterShape\n  };\n}\nfunction computeOutputShape2D(inShape, fieldSize, stride, zeroPad, roundingMode) {\n  if (zeroPad == null) {\n    zeroPad = computeDefaultPad(inShape, fieldSize, stride);\n  }\n  const inputRows = inShape[0];\n  const inputCols = inShape[1];\n  const outputRows = round((inputRows - fieldSize + 2 * zeroPad) / stride + 1, roundingMode);\n  const outputCols = round((inputCols - fieldSize + 2 * zeroPad) / stride + 1, roundingMode);\n  return [outputRows, outputCols];\n}\nfunction computeOutputShape4D(inShape, fieldSize, outChannels, stride, zeroPad, roundingMode) {\n  if (zeroPad == null) {\n    zeroPad = computeDefaultPad(inShape, fieldSize, stride);\n  }\n  const inputDepth = inShape[0];\n  const inputRows = inShape[1];\n  const inputCols = inShape[2];\n  const outputDepths = round((inputDepth - fieldSize + 2 * zeroPad) / stride + 1, roundingMode);\n  const outputRows = round((inputRows - fieldSize + 2 * zeroPad) / stride + 1, roundingMode);\n  const outputCols = round((inputCols - fieldSize + 2 * zeroPad) / stride + 1, roundingMode);\n  return [outputDepths, outputRows, outputCols, outChannels];\n}\nfunction computeDefaultPad(inputShape, fieldSize, stride, dilation = 1) {\n  const effectiveFieldSize = getEffectiveFilterSize(fieldSize, dilation);\n  return Math.floor((inputShape[0] * (stride - 1) - stride + effectiveFieldSize) / 2);\n}\nfunction parseTupleParam(param) {\n  if (typeof param === \"number\") {\n    return [param, param, param];\n  }\n  if (param.length === 2) {\n    return [param[0], param[1], 1];\n  }\n  return param;\n}\nfunction parse3TupleParam(param) {\n  return typeof param === \"number\" ? [param, param, param] : param;\n}\nfunction getEffectiveFilterSize(filterSize, dilation) {\n  if (dilation <= 1) {\n    return filterSize;\n  }\n  return filterSize + (filterSize - 1) * (dilation - 1);\n}\nfunction getPadAndOutInfo(pad3, inHeight, inWidth, strideHeight, strideWidth, filterHeight, filterWidth, roundingMode, dataFormat) {\n  let padInfo;\n  let outHeight;\n  let outWidth;\n  if (typeof pad3 === \"number\") {\n    const padType = pad3 === 0 ? \"VALID\" : \"NUMBER\";\n    padInfo = { top: pad3, bottom: pad3, left: pad3, right: pad3, type: padType };\n    const outShape = computeOutputShape2D([inHeight, inWidth], filterHeight, strideHeight, pad3, roundingMode);\n    outHeight = outShape[0];\n    outWidth = outShape[1];\n  } else if (pad3 === \"same\") {\n    outHeight = Math.ceil(inHeight / strideHeight);\n    outWidth = Math.ceil(inWidth / strideWidth);\n    const padAlongHeight = Math.max(0, (outHeight - 1) * strideHeight + filterHeight - inHeight);\n    const padAlongWidth = Math.max(0, (outWidth - 1) * strideWidth + filterWidth - inWidth);\n    const top = Math.floor(padAlongHeight / 2);\n    const bottom = padAlongHeight - top;\n    const left = Math.floor(padAlongWidth / 2);\n    const right = padAlongWidth - left;\n    padInfo = { top, bottom, left, right, type: \"SAME\" };\n  } else if (pad3 === \"valid\") {\n    padInfo = { top: 0, bottom: 0, left: 0, right: 0, type: \"VALID\" };\n    outHeight = Math.ceil((inHeight - filterHeight + 1) / strideHeight);\n    outWidth = Math.ceil((inWidth - filterWidth + 1) / strideWidth);\n  } else if (typeof pad3 === \"object\") {\n    const top = dataFormat === \"channelsLast\" ? pad3[1][0] : pad3[2][0];\n    const bottom = dataFormat === \"channelsLast\" ? pad3[1][1] : pad3[2][1];\n    const left = dataFormat === \"channelsLast\" ? pad3[2][0] : pad3[3][0];\n    const right = dataFormat === \"channelsLast\" ? pad3[2][1] : pad3[3][1];\n    const padType = top === 0 && bottom === 0 && left === 0 && right === 0 ? \"VALID\" : \"EXPLICIT\";\n    padInfo = { top, bottom, left, right, type: padType };\n    outHeight = round((inHeight - filterHeight + top + bottom) / strideHeight + 1, roundingMode);\n    outWidth = round((inWidth - filterWidth + left + right) / strideWidth + 1, roundingMode);\n  } else {\n    throw Error(`Unknown padding parameter: ${pad3}`);\n  }\n  return { padInfo, outHeight, outWidth };\n}\nfunction get3DPadAndOutInfo(pad3, inDepth, inHeight, inWidth, strideDepth, strideHeight, strideWidth, filterDepth, filterHeight, filterWidth, roundingMode) {\n  let padInfo;\n  let outDepth;\n  let outHeight;\n  let outWidth;\n  if (typeof pad3 === \"number\") {\n    const padType = pad3 === 0 ? \"VALID\" : \"NUMBER\";\n    padInfo = {\n      top: pad3,\n      bottom: pad3,\n      left: pad3,\n      right: pad3,\n      front: pad3,\n      back: pad3,\n      type: padType\n    };\n    const outShape = computeOutputShape4D([inDepth, inHeight, inWidth, 1], filterDepth, 1, strideDepth, pad3, roundingMode);\n    outDepth = outShape[0];\n    outHeight = outShape[1];\n    outWidth = outShape[2];\n  } else if (pad3 === \"same\") {\n    outDepth = Math.ceil(inDepth / strideDepth);\n    outHeight = Math.ceil(inHeight / strideHeight);\n    outWidth = Math.ceil(inWidth / strideWidth);\n    const padAlongDepth = (outDepth - 1) * strideDepth + filterDepth - inDepth;\n    const padAlongHeight = (outHeight - 1) * strideHeight + filterHeight - inHeight;\n    const padAlongWidth = (outWidth - 1) * strideWidth + filterWidth - inWidth;\n    const front = Math.floor(padAlongDepth / 2);\n    const back = padAlongDepth - front;\n    const top = Math.floor(padAlongHeight / 2);\n    const bottom = padAlongHeight - top;\n    const left = Math.floor(padAlongWidth / 2);\n    const right = padAlongWidth - left;\n    padInfo = { top, bottom, left, right, front, back, type: \"SAME\" };\n  } else if (pad3 === \"valid\") {\n    padInfo = {\n      top: 0,\n      bottom: 0,\n      left: 0,\n      right: 0,\n      front: 0,\n      back: 0,\n      type: \"VALID\"\n    };\n    outDepth = Math.ceil((inDepth - filterDepth + 1) / strideDepth);\n    outHeight = Math.ceil((inHeight - filterHeight + 1) / strideHeight);\n    outWidth = Math.ceil((inWidth - filterWidth + 1) / strideWidth);\n  } else {\n    throw Error(`Unknown padding parameter: ${pad3}`);\n  }\n  return { padInfo, outDepth, outHeight, outWidth };\n}\nfunction round(value, roundingMode) {\n  if (!roundingMode) {\n    return Math.trunc(value);\n  }\n  switch (roundingMode) {\n    case \"round\":\n      return Math.round(value);\n    case \"ceil\":\n      return Math.ceil(value);\n    case \"floor\":\n      return Math.floor(value);\n    default:\n      throw new Error(`Unknown roundingMode ${roundingMode}`);\n  }\n}\nfunction tupleValuesAreOne(param) {\n  const [dimA, dimB, dimC] = parseTupleParam(param);\n  return dimA === 1 && dimB === 1 && dimC === 1;\n}\nfunction eitherStridesOrDilationsAreOne(strides, dilations) {\n  return tupleValuesAreOne(strides) || tupleValuesAreOne(dilations);\n}\nfunction convertConv2DDataFormat(dataFormat) {\n  if (dataFormat === \"NHWC\") {\n    return \"channelsLast\";\n  } else if (dataFormat === \"NCHW\") {\n    return \"channelsFirst\";\n  } else {\n    throw new Error(`Unknown dataFormat ${dataFormat}`);\n  }\n}\nfunction checkPadOnDimRoundingMode(opDesc, pad3, dimRoundingMode) {\n  if (dimRoundingMode != null) {\n    if (typeof pad3 === \"string\") {\n      throw Error(`Error in ${opDesc}: pad must be an integer when using dimRoundingMode ${dimRoundingMode} but got pad ${pad3}.`);\n    } else if (typeof pad3 === \"number\") {\n      assert(isInt(pad3), () => `Error in ${opDesc}: pad must be an integer when using dimRoundingMode ${dimRoundingMode} but got pad ${pad3}.`);\n    } else if (typeof pad3 === \"object\") {\n      pad3.forEach((p2) => {\n        p2.forEach((v) => {\n          assert(isInt(v), () => `Error in ${opDesc}: pad must be an integer when using dimRoundingMode ${dimRoundingMode} but got pad ${v}.`);\n        });\n      });\n    } else {\n      throw Error(`Error in ${opDesc}: Unknown padding parameter: ${pad3}`);\n    }\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reshape.js\nfunction reshape_(x, shape) {\n  const $x = convertToTensor(x, \"x\", \"reshape\", \"string_or_numeric\");\n  const inputs = { x: $x };\n  const attrs = { shape };\n  return ENGINE.runKernel(Reshape, inputs, attrs);\n}\nvar reshape = op({ reshape_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool.js\nfunction avgPool_(x, filterSize, strides, pad3, dimRoundingMode) {\n  const $x = convertToTensor(x, \"x\", \"avgPool\", \"float32\");\n  const dilations = 1;\n  assert(eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in avgPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  assert(x4D.rank === 4, () => `Error in avgPool: x must be rank 4 but got rank ${x4D.rank}.`);\n  checkPadOnDimRoundingMode(\"avgPool\", pad3, dimRoundingMode);\n  const inputs = { x: x4D };\n  const attrs = { filterSize, strides, pad: pad3, dimRoundingMode };\n  let res = ENGINE.runKernel(AvgPool, inputs, attrs);\n  res = cast(res, $x.dtype);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar avgPool = op({ avgPool_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool_3d.js\nfunction avgPool3d_(x, filterSize, strides, pad3, dimRoundingMode, dataFormat = \"NDHWC\") {\n  const $x = convertToTensor(x, \"x\", \"avgPool3d\", \"float32\");\n  let x5D = $x;\n  let reshapedTo5D = false;\n  if ($x.rank === 4) {\n    reshapedTo5D = true;\n    x5D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]]);\n  }\n  assert(x5D.rank === 5, () => `Error in avgPool3d: x must be rank 5 but got rank ${x5D.rank}.`);\n  assert(dataFormat === \"NDHWC\", () => `Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of ${dataFormat}`);\n  checkPadOnDimRoundingMode(\"avgPool3d\", pad3, dimRoundingMode);\n  const inputs = { x: x5D };\n  const attrs = { filterSize, strides, pad: pad3, dimRoundingMode, dataFormat };\n  let res = ENGINE.runKernel(AvgPool3D, inputs, attrs);\n  res = cast(res, x5D.dtype);\n  if (reshapedTo5D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);\n  }\n  return res;\n}\nvar avgPool3d = op({ avgPool3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/concat.js\nfunction concat_(tensors, axis = 0) {\n  assert(tensors.length >= 1, () => \"Pass at least one tensor to concat\");\n  const $tensors = convertToTensorArray(tensors, \"tensors\", \"concat\", \"string_or_numeric\");\n  if ($tensors[0].dtype === \"complex64\") {\n    $tensors.forEach((tensor2) => {\n      if (tensor2.dtype !== \"complex64\") {\n        throw new Error(`Cannot concatenate complex64 tensors with a tensor\n          with dtype ${tensor2.dtype}. `);\n      }\n    });\n  }\n  if ($tensors.length === 1) {\n    return clone($tensors[0]);\n  }\n  const inputs = $tensors;\n  const attr = { axis };\n  return ENGINE.runKernel(Concat, inputs, attr);\n}\nvar concat = op({ concat_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sigmoid.js\nfunction sigmoid_(x) {\n  const $x = convertToTensor(x, \"x\", \"sigmoid\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Sigmoid, inputs);\n}\nvar sigmoid = op({ sigmoid_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/slice.js\nfunction slice_(x, begin, size) {\n  const $x = convertToTensor(x, \"x\", \"slice\", \"string_or_numeric\");\n  if ($x.rank === 0) {\n    throw new Error(\"Slicing scalar is not possible\");\n  }\n  const inputs = { x: $x };\n  const attrs = { begin, size };\n  return ENGINE.runKernel(Slice, inputs, attrs);\n}\nvar slice = op({ slice_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tanh.js\nfunction tanh_(x) {\n  const $x = convertToTensor(x, \"x\", \"tanh\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Tanh, inputs);\n}\nvar tanh2 = op({ tanh_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/basic_lstm_cell.js\nfunction basicLSTMCell_(forgetBias, lstmKernel, lstmBias, data, c, h) {\n  const $forgetBias = convertToTensor(forgetBias, \"forgetBias\", \"basicLSTMCell\");\n  const $lstmKernel = convertToTensor(lstmKernel, \"lstmKernel\", \"basicLSTMCell\");\n  const $lstmBias = convertToTensor(lstmBias, \"lstmBias\", \"basicLSTMCell\");\n  const $data = convertToTensor(data, \"data\", \"basicLSTMCell\");\n  const $c = convertToTensor(c, \"c\", \"basicLSTMCell\");\n  const $h = convertToTensor(h, \"h\", \"basicLSTMCell\");\n  const combined = concat([$data, $h], 1);\n  const weighted = matMul(combined, $lstmKernel);\n  const res = add2(weighted, $lstmBias);\n  const batchSize = res.shape[0];\n  const sliceCols = res.shape[1] / 4;\n  const sliceSize = [batchSize, sliceCols];\n  const i2 = slice(res, [0, 0], sliceSize);\n  const j = slice(res, [0, sliceCols], sliceSize);\n  const f = slice(res, [0, sliceCols * 2], sliceSize);\n  const o = slice(res, [0, sliceCols * 3], sliceSize);\n  const newC = add2(mul(sigmoid(i2), tanh2(j)), mul($c, sigmoid(add2($forgetBias, f))));\n  const newH = mul(tanh2(newC), sigmoid(o));\n  return [newC, newH];\n}\nvar basicLSTMCell = op({ basicLSTMCell_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/batch_to_space_nd.js\nfunction batchToSpaceND_(x, blockShape, crops) {\n  const $x = convertToTensor(x, \"x\", \"batchToSpaceND\");\n  const prod6 = blockShape.reduce((a, b) => a * b);\n  assert($x.rank >= 1 + blockShape.length, () => `input rank is ${$x.rank} but should be > than blockShape.length ${blockShape.length}`);\n  assert(crops.length === blockShape.length, () => `crops.length is ${crops.length} but should be equal to blockShape.length  ${blockShape.length}`);\n  assert($x.shape[0] % prod6 === 0, () => `input tensor batch is ${$x.shape[0]} but is not divisible by the product of the elements of blockShape ${blockShape.join(\" * \")} === ${prod6}`);\n  const inputs = { x: $x };\n  const attrs = { blockShape, crops };\n  return ENGINE.runKernel(BatchToSpaceND, inputs, attrs);\n}\nvar batchToSpaceND = op({ batchToSpaceND_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm_util.js\nfunction xAs4D(x) {\n  let x4D;\n  if (x.rank === 0 || x.rank === 1) {\n    x4D = reshape(x, [1, 1, 1, x.size]);\n  } else if (x.rank === 2) {\n    x4D = reshape(x, [1, 1, x.shape[0], x.shape[1]]);\n  } else if (x.rank === 3) {\n    x4D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2]]);\n  } else {\n    x4D = x;\n  }\n  return x4D;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm.js\nfunction batchNorm_(x, mean5, variance, offset, scale2, varianceEpsilon) {\n  if (varianceEpsilon == null) {\n    varianceEpsilon = 1e-3;\n  }\n  const $x = convertToTensor(x, \"x\", \"batchNorm\");\n  const $mean = convertToTensor(mean5, \"mean\", \"batchNorm\");\n  const $variance = convertToTensor(variance, \"variance\", \"batchNorm\");\n  let $scale;\n  if (scale2 != null) {\n    $scale = convertToTensor(scale2, \"scale\", \"batchNorm\");\n  }\n  let $offset;\n  if (offset != null) {\n    $offset = convertToTensor(offset, \"offset\", \"batchNorm\");\n  }\n  assert($mean.rank === $variance.rank, () => \"Batch normalization gradient requires mean and variance to have equal ranks.\");\n  assert($offset == null || $mean.rank === $offset.rank, () => \"Batch normalization gradient requires mean and offset to have equal ranks.\");\n  assert($scale == null || $mean.rank === $scale.rank, () => \"Batch normalization gradient requires mean and scale to have equal ranks.\");\n  const x4D = xAs4D($x);\n  const inputs = {\n    x: x4D,\n    scale: $scale,\n    offset: $offset,\n    mean: $mean,\n    variance: $variance\n  };\n  const attrs = { varianceEpsilon };\n  const res = ENGINE.runKernel(FusedBatchNorm, inputs, attrs);\n  return reshape(res, $x.shape);\n}\nvar batchNorm = op({ batchNorm_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm2d.js\nfunction batchNorm2d_(x, mean5, variance, offset, scale2, varianceEpsilon) {\n  const $x = convertToTensor(x, \"x\", \"batchNorm\");\n  const $mean = convertToTensor(mean5, \"mean\", \"batchNorm\");\n  const $variance = convertToTensor(variance, \"variance\", \"batchNorm\");\n  let $scale;\n  if (scale2 != null) {\n    $scale = convertToTensor(scale2, \"scale\", \"batchNorm\");\n  }\n  let $offset;\n  if (offset != null) {\n    $offset = convertToTensor(offset, \"offset\", \"batchNorm\");\n  }\n  assert($x.rank === 2, () => `Error in batchNorm2D: x must be rank 2 but got rank ${$x.rank}.`);\n  assert($mean.rank === 2 || $mean.rank === 1, () => `Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank ${$mean.rank}.`);\n  assert($variance.rank === 2 || $variance.rank === 1, () => `Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank ${$variance.rank}.`);\n  if ($scale != null) {\n    assert($scale.rank === 2 || $scale.rank === 1, () => `Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank ${$scale.rank}.`);\n  }\n  if ($offset != null) {\n    assert($offset.rank === 2 || $offset.rank === 1, () => `Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${$offset.rank}.`);\n  }\n  return batchNorm($x, $mean, $variance, $offset, $scale, varianceEpsilon);\n}\nvar batchNorm2d = op({ batchNorm2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm3d.js\nfunction batchNorm3d_(x, mean5, variance, offset, scale2, varianceEpsilon) {\n  const $x = convertToTensor(x, \"x\", \"batchNorm\");\n  const $mean = convertToTensor(mean5, \"mean\", \"batchNorm\");\n  const $variance = convertToTensor(variance, \"variance\", \"batchNorm\");\n  let $scale;\n  if (scale2 != null) {\n    $scale = convertToTensor(scale2, \"scale\", \"batchNorm\");\n  }\n  let $offset;\n  if (offset != null) {\n    $offset = convertToTensor(offset, \"offset\", \"batchNorm\");\n  }\n  assert($x.rank === 3, () => `Error in batchNorm3D: x must be rank 3 but got rank ${$x.rank}.`);\n  assert($mean.rank === 3 || $mean.rank === 1, () => `Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${$mean.rank}.`);\n  assert($variance.rank === 3 || $variance.rank === 1, () => `Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${$variance.rank}.`);\n  if ($scale != null) {\n    assert($scale.rank === 3 || $scale.rank === 1, () => `Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${$scale.rank}.`);\n  }\n  if ($offset != null) {\n    assert($offset.rank === 3 || $offset.rank === 1, () => `Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${$offset.rank}.`);\n  }\n  return batchNorm($x, $mean, $variance, $offset, $scale, varianceEpsilon);\n}\nvar batchNorm3d = op({ batchNorm3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/batchnorm4d.js\nfunction batchNorm4d_(x, mean5, variance, offset, scale2, varianceEpsilon) {\n  const $x = convertToTensor(x, \"x\", \"batchNorm\");\n  const $mean = convertToTensor(mean5, \"mean\", \"batchNorm\");\n  const $variance = convertToTensor(variance, \"variance\", \"batchNorm\");\n  let $scale;\n  if (scale2 != null) {\n    $scale = convertToTensor(scale2, \"scale\", \"batchNorm\");\n  }\n  let $offset;\n  if (offset != null) {\n    $offset = convertToTensor(offset, \"offset\", \"batchNorm\");\n  }\n  assert($x.rank === 4, () => `Error in batchNorm4D: x must be rank 4 but got rank ${$x.rank}.`);\n  assert($mean.rank === 4 || $mean.rank === 1, () => `Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${$mean.rank}.`);\n  assert($variance.rank === 4 || $variance.rank === 1, () => `Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${$variance.rank}.`);\n  if ($scale != null) {\n    assert($scale.rank === 4 || $scale.rank === 1, () => `Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${$scale.rank}.`);\n  }\n  if ($offset != null) {\n    assert($offset.rank === 4 || $offset.rank === 1, () => `Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${$offset.rank}.`);\n  }\n  return batchNorm($x, $mean, $variance, $offset, $scale, varianceEpsilon);\n}\nvar batchNorm4d = op({ batchNorm4d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/bincount.js\nfunction bincount_(x, weights, size) {\n  const $x = convertToTensor(x, \"x\", \"bincount\");\n  const $weights = convertToTensor(weights, \"weights\", \"bincount\");\n  assert($x.dtype === \"int32\", () => `Error in bincount: input dtype must be int32, but got ${$x.dtype}`);\n  assert(size >= 0, () => `size must be non-negative, but got ${size}.`);\n  assert($weights.size === $x.size || $weights.size === 0, () => `Error in bincount: weights must have the same size as input or0-length, but got input shape: ${$x.shape}, weights shape: ${$weights.shape}.`);\n  const inputs = { x: $x, weights: $weights };\n  const attrs = { size };\n  return ENGINE.runKernel(Bincount, inputs, attrs);\n}\nvar bincount = op({ bincount_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/broadcast_args.js\nfunction broadcastArgs_(s0, s1) {\n  const shape1Input = convertToTensor(s0, \"s0\", \"broadcastArgs\", \"int32\");\n  const shape2Input = convertToTensor(s1, \"s1\", \"broadcastArgs\", \"int32\");\n  if (shape1Input.rank !== 1) {\n    throw new Error(`broadcastArgs(): first input must be a vector (rank=1). Has rank ${shape1Input.rank}`);\n  }\n  if (shape2Input.rank !== 1) {\n    throw new Error(`broadcastArgs(): second input must be a vector (rank=1). Has rank ${shape2Input.rank}`);\n  }\n  const inputs = { s0: shape1Input, s1: shape2Input };\n  return ENGINE.runKernel(BroadcastArgs, inputs);\n}\nvar broadcastArgs = op({ broadcastArgs_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/broadcast_to.js\nfunction broadcastTo_(x, shape) {\n  let input2 = convertToTensor(x, \"broadcastTo\", \"x\");\n  const xShape = input2.shape;\n  if (shape.some((d) => !(d > 0) || d % 1 !== 0)) {\n    throw new Error(`broadcastTo(): Invalid broadcast shape [${shape}].`);\n  }\n  if (shape.length < input2.rank) {\n    throw new Error(`broadcastTo(): shape.length=${shape.length} < input.rank=${input2.rank}.`);\n  }\n  if (shape.length > input2.rank) {\n    const newShape = input2.shape.slice();\n    while (newShape.length < shape.length) {\n      newShape.unshift(1);\n    }\n    input2 = reshape(input2, newShape);\n  }\n  const inputShape = input2.shape;\n  const reps = Array.from(shape);\n  for (let i2 = shape.length - 1; i2 >= 0; i2--) {\n    if (inputShape[i2] === shape[i2]) {\n      reps[i2] = 1;\n    } else if (input2.shape[i2] !== 1) {\n      throw new Error(`broadcastTo(): [${xShape}] cannot be broadcast to [${shape}].`);\n    }\n  }\n  const axes = reps.map((n2, i2) => n2 > 1 ? i2 : -1).filter((i2) => i2 >= 0);\n  if (axes.length === 0) {\n    return clone(input2);\n  }\n  const inputs = { x: input2 };\n  const attrs = { reps };\n  return ENGINE.runKernel(Tile, inputs, attrs);\n}\nvar broadcastTo = op({ broadcastTo_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/ceil.js\nfunction ceil_(x) {\n  const $x = convertToTensor(x, \"x\", \"ceil\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Ceil, inputs);\n}\nvar ceil = op({ ceil_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/clip_by_value.js\nfunction clipByValue_(x, clipValueMin, clipValueMax) {\n  const $x = convertToTensor(x, \"x\", \"clipByValue\");\n  assert(clipValueMin <= clipValueMax, () => `Error in clip: min (${clipValueMin}) must be less than or equal to max (${clipValueMax}).`);\n  const inputs = { x: $x };\n  const attrs = { clipValueMin, clipValueMax };\n  return ENGINE.runKernel(ClipByValue, inputs, attrs);\n}\nvar clipByValue = op({ clipByValue_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/concat_1d.js\nfunction concat1d_(tensors) {\n  return concat(tensors, 0);\n}\nvar concat1d = op({ concat1d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/concat_2d.js\nfunction concat2d_(tensors, axis) {\n  return concat(tensors, axis);\n}\nvar concat2d = op({ concat2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/concat_3d.js\nfunction concat3d_(tensors, axis) {\n  return concat(tensors, axis);\n}\nvar concat3d = op({ concat3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/concat_4d.js\nfunction concat4d_(tensors, axis) {\n  return concat(tensors, axis);\n}\nvar concat4d = op({ concat4d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv2d.js\nfunction conv2d_(x, filter, strides, pad3, dataFormat = \"NHWC\", dilations = [1, 1], dimRoundingMode) {\n  const $x = convertToTensor(x, \"x\", \"conv2d\", \"float32\");\n  const $filter = convertToTensor(filter, \"filter\", \"conv2d\", \"float32\");\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  assert(x4D.rank === 4, () => `Error in conv2d: input must be rank 4, but got rank ${x4D.rank}.`);\n  assert($filter.rank === 4, () => `Error in conv2d: filter must be rank 4, but got rank ${$filter.rank}.`);\n  checkPadOnDimRoundingMode(\"conv2d\", pad3, dimRoundingMode);\n  const inDepth = dataFormat === \"NHWC\" ? x4D.shape[3] : x4D.shape[1];\n  assert(inDepth === $filter.shape[2], () => `Error in conv2d: depth of input (${inDepth}) must match input depth for filter ${$filter.shape[2]}.`);\n  assert(eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in conv2D: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  const inputs = { x: x4D, filter: $filter };\n  const attrs = { strides, pad: pad3, dataFormat, dilations, dimRoundingMode };\n  const res = ENGINE.runKernel(Conv2D, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar conv2d = op({ conv2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv1d.js\nfunction conv1d_(x, filter, stride, pad3, dataFormat = \"NWC\", dilation = 1, dimRoundingMode) {\n  const $x = convertToTensor(x, \"x\", \"conv1d\");\n  const $filter = convertToTensor(filter, \"filter\", \"conv1d\");\n  let x3D = $x;\n  let reshapedTo3D = false;\n  if ($x.rank === 2) {\n    reshapedTo3D = true;\n    x3D = reshape($x, [1, $x.shape[0], $x.shape[1]]);\n  }\n  assert(x3D.rank === 3, () => `Error in conv1d: input must be rank 3, but got rank ${x3D.rank}.`);\n  assert($filter.rank === 3, () => `Error in conv1d: filter must be rank 3, but got rank ${$filter.rank}.`);\n  checkPadOnDimRoundingMode(\"conv1d\", pad3, dimRoundingMode);\n  assert(x3D.shape[2] === $filter.shape[1], () => `Error in conv1d: depth of input (${x3D.shape[2]}) must match input depth for filter ${$filter.shape[1]}.`);\n  assert(eitherStridesOrDilationsAreOne(stride, dilation), () => `Error in conv1D: Either stride or dilation must be 1. Got stride ${stride} and dilation '${dilation}'`);\n  assert(dataFormat === \"NWC\", () => `Error in conv1d: got dataFormat of ${dataFormat} but only NWC is currently supported.`);\n  const filter4D = reshape($filter, [1, $filter.shape[0], $filter.shape[1], $filter.shape[2]]);\n  const input4D = reshape(x3D, [x3D.shape[0], 1, x3D.shape[1], x3D.shape[2]]);\n  const strides = [1, stride];\n  const dilations = [1, dilation];\n  const conv2dDataFormat = \"NHWC\";\n  const res = conv2d(input4D, filter4D, strides, pad3, conv2dDataFormat, dilations, dimRoundingMode);\n  if (reshapedTo3D) {\n    return reshape(res, [res.shape[2], res.shape[3]]);\n  }\n  return reshape(res, [res.shape[0], res.shape[2], res.shape[3]]);\n}\nvar conv1d = op({ conv1d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv2d_backprop_input.js\nfunction conv2DBackpropInput_(xShape, dy, filter, strides, pad3, dataFormat = \"NHWC\", dimRoundingMode) {\n  assert(xShape.length === dy.rank, () => `Length of inShape (${xShape.length}) and rank of dy (${dy.rank}) must match`);\n  let xShape4D = xShape;\n  let dy4D = dy;\n  let reshapedTo4D = false;\n  if (dy.rank === 3) {\n    reshapedTo4D = true;\n    dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);\n    xShape4D = [1, xShape[0], xShape[1], xShape[2]];\n  }\n  assert(xShape4D.length === 4, () => `Error in conv2dDerInput: inShape must be length 4, but got length ${xShape4D.length}.`);\n  assert(dy4D.rank === 4, () => `Error in conv2dDerInput: dy must be rank 4, but got rank ${dy4D.rank}`);\n  assert(filter.rank === 4, () => `Error in conv2dDerInput: filter must be rank 4, but got rank ${filter.rank}`);\n  const inDepth = dataFormat === \"NHWC\" ? xShape4D[3] : xShape4D[1];\n  const outDepth = dataFormat === \"NHWC\" ? dy4D.shape[3] : dy4D.shape[1];\n  assert(inDepth === filter.shape[2], () => `Error in conv2dDerInput: depth of input (${inDepth}) must match input depth for filter ${filter.shape[2]}.`);\n  assert(outDepth === filter.shape[3], () => `Error in conv2dDerInput: depth of output (${outDepth}) must match output depth for filter ${filter.shape[3]}.`);\n  checkPadOnDimRoundingMode(\"conv2dDerInput\", pad3, dimRoundingMode);\n  const inputs = { dy: dy4D, filter };\n  const attrs = { strides, pad: pad3, dataFormat, dimRoundingMode, inputShape: xShape4D };\n  const res = ENGINE.runKernel(Conv2DBackpropInput, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar conv2DBackpropInput = op({ conv2DBackpropInput_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv2d_transpose.js\nfunction conv2dTranspose_(x, filter, outputShape, strides, pad3, dimRoundingMode) {\n  const $x = convertToTensor(x, \"x\", \"conv2dTranspose\");\n  const $filter = convertToTensor(filter, \"filter\", \"conv2dTranspose\");\n  return conv2DBackpropInput(outputShape, $x, $filter, strides, pad3, \"NHWC\", dimRoundingMode);\n}\nvar conv2dTranspose = op({ conv2dTranspose_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv3d.js\nfunction conv3d_(x, filter, strides, pad3, dataFormat = \"NDHWC\", dilations = [1, 1, 1]) {\n  const $x = convertToTensor(x, \"x\", \"conv3d\");\n  const $filter = convertToTensor(filter, \"filter\", \"conv3d\");\n  let x5D = $x;\n  let reshapedTo5D = false;\n  if ($x.rank === 4) {\n    reshapedTo5D = true;\n    x5D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]]);\n  }\n  assert(x5D.rank === 5, () => `Error in conv3d: input must be rank 5, but got rank ${x5D.rank}.`);\n  assert($filter.rank === 5, () => `Error in conv3d: filter must be rank 5, but got rank ${$filter.rank}.`);\n  assert(x5D.shape[4] === $filter.shape[3], () => `Error in conv3d: depth of input (${x5D.shape[4]}) must match input depth for filter ${$filter.shape[3]}.`);\n  assert(eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in conv3D: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  assert(dataFormat === \"NDHWC\", () => `Error in conv3d: got dataFormat of ${dataFormat} but only NDHWC is currently supported.`);\n  const inputs = { x: x5D, filter: $filter };\n  const attrs = { strides, pad: pad3, dataFormat, dilations };\n  const res = ENGINE.runKernel(Conv3D, inputs, attrs);\n  if (reshapedTo5D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);\n  }\n  return res;\n}\nvar conv3d = op({ conv3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv3d_backprop_input.js\nfunction conv3DBackpropInput_(xShape, dy, filter, strides, pad3) {\n  assert(xShape.length === dy.rank, () => `Length of inShape (${xShape.length}) and rank of dy (${dy.rank}) must match`);\n  let xShape5D = xShape;\n  let dy5D = dy;\n  let reshapedTo5D = false;\n  if (dy.rank === 4) {\n    reshapedTo5D = true;\n    dy5D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2], dy.shape[3]]);\n    xShape5D = [1, xShape[0], xShape[1], xShape[2], xShape[3]];\n  }\n  const inDepth = xShape5D[4];\n  const outDepth = dy5D.shape[4];\n  assert(xShape5D.length === 5, () => `Error in conv3dDerInput: inShape must be length 5, but got length ${xShape5D.length}.`);\n  assert(dy5D.rank === 5, () => `Error in conv3dDerInput: dy must be rank 5, but got rank ${dy5D.rank}`);\n  assert(filter.rank === 5, () => `Error in conv3dDerInput: filter must be rank 5, but got rank ${filter.rank}`);\n  assert(inDepth === filter.shape[3], () => `Error in conv3dDerInput: depth of input (${inDepth}) must match input depth for filter ${filter.shape[3]}.`);\n  assert(outDepth === filter.shape[4], () => `Error in conv3dDerInput: depth of output (${outDepth}) must match output depth for filter ${filter.shape[4]}.`);\n  const inputs = { dy: dy5D, filter };\n  const attrs = { pad: pad3, strides, inputShape: xShape5D };\n  const res = ENGINE.runKernel(Conv3DBackpropInputV2, inputs, attrs);\n  if (reshapedTo5D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);\n  }\n  return res;\n}\nvar conv3DBackpropInput = op({ conv3DBackpropInput_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv3d_transpose.js\nfunction conv3dTranspose_(x, filter, outputShape, strides, pad3) {\n  const $x = convertToTensor(x, \"x\", \"conv3dTranspose\");\n  const $filter = convertToTensor(filter, \"filter\", \"conv3dTranspose\");\n  return conv3DBackpropInput(outputShape, $x, $filter, strides, pad3);\n}\nvar conv3dTranspose = op({ conv3dTranspose_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/cos.js\nfunction cos_(x) {\n  const $x = convertToTensor(x, \"x\", \"cos\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Cos, inputs);\n}\nvar cos = op({ cos_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/cosh.js\nfunction cosh_(x) {\n  const $x = convertToTensor(x, \"x\", \"cosh\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Cosh, inputs);\n}\nvar cosh = op({ cosh_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/cumprod.js\nfunction cumprod_(x, axis = 0, exclusive = false, reverse5 = false) {\n  const $x = convertToTensor(x, \"x\", \"cumprod\");\n  const inputs = { x: $x };\n  const attrs = { axis, exclusive, reverse: reverse5 };\n  return ENGINE.runKernel(Cumprod, inputs, attrs);\n}\nvar cumprod = op({ cumprod_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/cumsum.js\nfunction cumsum_(x, axis = 0, exclusive = false, reverse5 = false) {\n  const $x = convertToTensor(x, \"x\", \"cumsum\");\n  const inputs = { x: $x };\n  const attrs = { axis, exclusive, reverse: reverse5 };\n  return ENGINE.runKernel(Cumsum, inputs, attrs);\n}\nvar cumsum = op({ cumsum_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/dense_bincount.js\nfunction denseBincount_(x, weights, size, binaryOutput = false) {\n  const $x = convertToTensor(x, \"x\", \"denseBincount\");\n  const $weights = convertToTensor(weights, \"weights\", \"denseBincount\");\n  assert($x.dtype === \"int32\", () => `Error in denseBincount: input dtype must be int32, but got ${$x.dtype}`);\n  assert($x.rank <= 2, () => `Error in denseBincount: input must be at most rank 2, but got rank ${$x.rank}.`);\n  assert(size >= 0, () => `size must be non-negative, but got ${size}.`);\n  assert($weights.size === $x.size || $weights.size === 0, () => `Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${$x.shape}, weights shape: ${$weights.shape}.`);\n  const inputs = { x: $x, weights: $weights };\n  const attrs = { size, binaryOutput };\n  return ENGINE.runKernel(DenseBincount, inputs, attrs);\n}\nvar denseBincount = op({ denseBincount_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/depth_to_space.js\nfunction depthToSpace_(x, blockSize, dataFormat = \"NHWC\") {\n  const $x = convertToTensor(x, \"x\", \"depthToSpace\", \"float32\");\n  const inputHeight = dataFormat === \"NHWC\" ? $x.shape[1] : $x.shape[2];\n  const inputWidth = dataFormat === \"NHWC\" ? $x.shape[2] : $x.shape[3];\n  const inputDepth = dataFormat === \"NHWC\" ? $x.shape[3] : $x.shape[1];\n  assert(blockSize > 1, () => `blockSize should be > 1 for depthToSpace, but was: ${blockSize}`);\n  assert(inputHeight * blockSize >= 0, () => `Negative dimension size caused by overflow when multiplying\n    ${inputHeight} and ${blockSize}  for depthToSpace with input shape\n    ${$x.shape}`);\n  assert(inputWidth * blockSize >= 0, () => `Negative dimension size caused by overflow when multiplying\n    ${inputWidth} and ${blockSize} for depthToSpace with input shape\n        ${$x.shape}`);\n  assert(inputDepth % (blockSize * blockSize) === 0, () => `Dimension size must be evenly divisible by ${blockSize * blockSize} but is ${inputDepth} for depthToSpace with input shape ${$x.shape}`);\n  const inputs = { x: $x };\n  const attrs = { blockSize, dataFormat };\n  return ENGINE.runKernel(DepthToSpace, inputs, attrs);\n}\nvar depthToSpace = op({ depthToSpace_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/depthwise_conv2d.js\nfunction depthwiseConv2d_(x, filter, strides, pad3, dataFormat = \"NHWC\", dilations = [1, 1], dimRoundingMode) {\n  const $x = convertToTensor(x, \"x\", \"depthwiseConv2d\", \"float32\");\n  const $filter = convertToTensor(filter, \"filter\", \"depthwiseConv2d\", \"float32\");\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  assert(x4D.rank === 4, () => `Error in depthwiseConv2d: input must be rank 4, but got rank ${x4D.rank}.`);\n  assert($filter.rank === 4, () => `Error in depthwiseConv2d: filter must be rank 4, but got rank ${$filter.rank}.`);\n  const inChannels = dataFormat === \"NHWC\" ? x4D.shape[3] : x4D.shape[1];\n  assert(inChannels === $filter.shape[2], () => `Error in depthwiseConv2d: number of input channels (${inChannels}) must match the inChannels dimension in filter ${$filter.shape[2]}.`);\n  checkPadOnDimRoundingMode(\"depthwiseConv2d\", pad3, dimRoundingMode);\n  const inputs = { x: x4D, filter: $filter };\n  const attrs = { strides, pad: pad3, dataFormat, dilations, dimRoundingMode };\n  const res = ENGINE.runKernel(DepthwiseConv2dNative, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar depthwiseConv2d = op({ depthwiseConv2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/diag.js\nfunction diag_(x) {\n  const $x = convertToTensor(x, \"x\", \"diag\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Diag, inputs);\n}\nvar diag = op({ diag_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/dilation2d.js\nfunction dilation2d_(x, filter, strides, pad3, dilations = [1, 1], dataFormat = \"NHWC\") {\n  const $x = convertToTensor(x, \"x\", \"dilation2d\");\n  const $filter = convertToTensor(filter, \"filter\", \"dilation2d\");\n  assert($x.rank === 3 || $x.rank === 4, () => `Error in dilation2d: input must be rank 3 or 4, but got rank ${$x.rank}.`);\n  assert($filter.rank === 3, () => `Error in dilation2d: filter must be rank 3, but got rank ${$filter.rank}.`);\n  assert(dataFormat === \"NHWC\", () => `Error in dilation2d: Only NHWC is currently supported, but got dataFormat of ${dataFormat}`);\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n    reshapedTo4D = true;\n  }\n  const inputs = { x: x4D, filter: $filter };\n  const attrs = { strides, pad: pad3, dilations };\n  const res = ENGINE.runKernel(Dilation2D, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar dilation2d = op({ dilation2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/equal.js\nfunction equal_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"equal\", \"string_or_numeric\");\n  let $b = convertToTensor(b, \"b\", \"equal\", \"string_or_numeric\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Equal, inputs);\n}\nvar equal = op({ equal_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/where.js\nfunction where_(condition, a, b) {\n  const $a = convertToTensor(a, \"a\", \"where\");\n  const $b = convertToTensor(b, \"b\", \"where\");\n  const $condition = convertToTensor(condition, \"condition\", \"where\", \"bool\");\n  const broadcastShape = assertAndGetBroadcastShape(assertAndGetBroadcastShape($condition.shape, $a.shape), $b.shape);\n  const $broadcastedCondition = broadcastTo($condition, broadcastShape);\n  const $broadcastedA = broadcastTo($a, broadcastShape);\n  const $broadcastedB = broadcastTo($b, broadcastShape);\n  const inputs = {\n    condition: $broadcastedCondition,\n    t: $broadcastedA,\n    e: $broadcastedB\n  };\n  return ENGINE.runKernel(Select, inputs);\n}\nvar where = op({ where_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/zeros_like.js\nfunction zerosLike_(x) {\n  const $x = convertToTensor(x, \"x\", \"zerosLike\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(ZerosLike, inputs);\n}\nvar zerosLike = op({ zerosLike_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/div_no_nan.js\nfunction divNoNan_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"div\");\n  let $b = convertToTensor(b, \"b\", \"div\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const divResult = div($a, $b);\n  const zeros4 = zerosLike(divResult);\n  const bEqualsZero = equal($b, zeros4);\n  return where(bEqualsZero, zeros4, divResult);\n}\nvar divNoNan = op({ divNoNan_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/dot.js\nfunction dot_(t1, t2) {\n  const $t1 = convertToTensor(t1, \"t1\", \"dot\");\n  const $t2 = convertToTensor(t2, \"t2\", \"dot\");\n  assert(($t1.rank === 1 || $t1.rank === 2) && ($t2.rank === 1 || $t2.rank === 2), () => `Error in dot: inputs must all be rank 1 or 2, but got ranks ${$t1.rank} and ${$t2.rank}.`);\n  const t1Inner = $t1.rank === 1 ? $t1.size : $t1.shape[1];\n  const t2Inner = $t2.rank === 1 ? $t2.size : $t2.shape[0];\n  assert(t1Inner === t2Inner, () => `Error in dot: inner dimensions of inputs must match, but got ${t1Inner} and ${t2Inner}.`);\n  if ($t1.rank === 1 && $t2.rank === 1) {\n    const t12D = reshape($t1, [1, -1]);\n    const t22D = reshape($t2, [-1, 1]);\n    const t1t2 = matMul(t12D, t22D);\n    return reshape(t1t2, []);\n  } else if ($t1.rank === 1 && $t2.rank === 2) {\n    const t12D = reshape($t1, [1, -1]);\n    const t22D = reshape($t2, [$t2.shape[0], $t2.shape[1]]);\n    const t1t2 = matMul(t12D, t22D);\n    return reshape(t1t2, [t1t2.size]);\n  } else if ($t1.rank === 2 && $t2.rank === 1) {\n    const t22D = reshape($t2, [-1, 1]);\n    const t1t2 = matMul($t1, t22D);\n    return reshape(t1t2, [t1t2.size]);\n  } else {\n    const t22D = reshape($t2, [$t2.shape[0], $t2.shape[1]]);\n    const t1t2 = matMul($t1, t22D);\n    return t1t2;\n  }\n}\nvar dot = op({ dot_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/einsum.js\nfunction einsum_(equation, ...tensors) {\n  const $tensors = tensors.map((t2, i2) => convertToTensor(t2, `tensors${i2}`, \"einsum\"));\n  const attrs = { equation };\n  return ENGINE.runKernel(Einsum, $tensors, attrs);\n}\nvar einsum = op({ einsum_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/elu.js\nfunction elu_(x) {\n  const $x = convertToTensor(x, \"x\", \"elu\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Elu, inputs);\n}\nvar elu = op({ elu_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/erf.js\nfunction erf_(x) {\n  let $x = convertToTensor(x, \"x\", \"erf\");\n  assert($x.dtype === \"int32\" || $x.dtype === \"float32\", () => \"Input dtype must be `int32` or `float32`.\");\n  if ($x.dtype === \"int32\") {\n    $x = cast($x, \"float32\");\n  }\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Erf, inputs);\n}\nvar erf = op({ erf_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/axis_util.js\nfunction axesAreInnerMostDims(axes, rank) {\n  for (let i2 = 0; i2 < axes.length; ++i2) {\n    if (axes[axes.length - i2 - 1] !== rank - 1 - i2) {\n      return false;\n    }\n  }\n  return true;\n}\nfunction combineLocations(outputLoc, reduceLoc, axes) {\n  const rank = outputLoc.length + reduceLoc.length;\n  const loc = [];\n  let outIdx = 0;\n  let reduceIdx = 0;\n  for (let dim = 0; dim < rank; dim++) {\n    if (axes.indexOf(dim) === -1) {\n      loc.push(outputLoc[outIdx++]);\n    } else {\n      loc.push(reduceLoc[reduceIdx++]);\n    }\n  }\n  return loc;\n}\nfunction computeOutAndReduceShapes(aShape, axes) {\n  const outShape = [];\n  const rank = aShape.length;\n  for (let dim = 0; dim < rank; dim++) {\n    if (axes.indexOf(dim) === -1) {\n      outShape.push(aShape[dim]);\n    }\n  }\n  const reduceShape = axes.map((dim) => aShape[dim]);\n  return [outShape, reduceShape];\n}\nfunction expandShapeToKeepDim(shape, axes) {\n  const reduceSubShape = axes.map((x) => 1);\n  return combineLocations(shape, reduceSubShape, axes);\n}\nfunction assertAxesAreInnerMostDims(msg, axes, rank) {\n  assert(axesAreInnerMostDims(axes, rank), () => `${msg} supports only inner-most axes for now. Got axes ${axes} and rank-${rank} input.`);\n}\nfunction getAxesPermutation(axes, rank) {\n  if (axesAreInnerMostDims(axes, rank)) {\n    return null;\n  }\n  const result = [];\n  for (let i2 = 0; i2 < rank; ++i2) {\n    if (axes.indexOf(i2) === -1) {\n      result.push(i2);\n    }\n  }\n  axes.forEach((axis) => result.push(axis));\n  return result;\n}\nfunction getUndoAxesPermutation(axes) {\n  return axes.map((axis, i2) => [i2, axis]).sort((a, b) => a[1] - b[1]).map((x) => x[0]);\n}\nfunction getInnerMostAxes(numAxes, rank) {\n  const res = [];\n  for (let i2 = rank - numAxes; i2 < rank; ++i2) {\n    res.push(i2);\n  }\n  return res;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/max.js\nfunction max_(x, axis = null, keepDims = false) {\n  const $x = convertToTensor(x, \"x\", \"max\");\n  const inputs = { x: $x };\n  const attrs = { reductionIndices: axis, keepDims };\n  return ENGINE.runKernel(Max, inputs, attrs);\n}\nvar max = op({ max_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/min.js\nfunction min_(x, axis = null, keepDims = false) {\n  const $x = convertToTensor(x, \"x\", \"min\");\n  const inputs = { x: $x };\n  const attrs = { axis, keepDims };\n  return ENGINE.runKernel(Min, inputs, attrs);\n}\nvar min = op({ min_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/pow.js\nfunction pow_(base, exp5) {\n  let $base = convertToTensor(base, \"base\", \"pow\");\n  let $exp = convertToTensor(exp5, \"exp\", \"pow\");\n  [$base, $exp] = makeTypesMatch($base, $exp);\n  const inputs = { a: $base, b: $exp };\n  return ENGINE.runKernel(Pow, inputs);\n}\nvar pow = op({ pow_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/scalar.js\nfunction scalar(value, dtype) {\n  if ((isTypedArray(value) && dtype !== \"string\" || Array.isArray(value)) && dtype !== \"complex64\") {\n    throw new Error(\"Error creating a new Scalar: value must be a primitive (number|boolean|string)\");\n  }\n  if (dtype === \"string\" && isTypedArray(value) && !(value instanceof Uint8Array)) {\n    throw new Error(\"When making a scalar from encoded string, the value must be `Uint8Array`.\");\n  }\n  const shape = [];\n  const inferredShape = [];\n  return makeTensor(value, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sqrt.js\nfunction sqrt_(x) {\n  const $x = convertToTensor(x, \"x\", \"sqrt\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Sqrt, inputs);\n}\nvar sqrt = op({ sqrt_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/square.js\nfunction square_(x) {\n  const $x = convertToTensor(x, \"x\", \"square\");\n  const attrs = {};\n  return ENGINE.runKernel(\"Square\", { x: $x }, attrs);\n}\nvar square = op({ square_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sum.js\nfunction sum_(x, axis = null, keepDims = false) {\n  let $x = convertToTensor(x, \"x\", \"sum\");\n  if ($x.dtype === \"bool\") {\n    $x = cast($x, \"int32\");\n  }\n  const inputs = { x: $x };\n  const attrs = { axis, keepDims };\n  return ENGINE.runKernel(Sum, inputs, attrs);\n}\nvar sum2 = op({ sum_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/norm.js\nfunction norm_(x, ord = \"euclidean\", axis = null, keepDims = false) {\n  x = convertToTensor(x, \"x\", \"norm\");\n  const norm2 = normImpl(x, ord, axis);\n  let keepDimsShape = norm2.shape;\n  if (keepDims) {\n    const axes = parseAxisParam(axis, x.shape);\n    keepDimsShape = expandShapeToKeepDim(norm2.shape, axes);\n  }\n  return reshape(norm2, keepDimsShape);\n}\nfunction normImpl(x, p2, axis = null) {\n  if (x.rank === 0) {\n    return abs(x);\n  }\n  if (x.rank !== 1 && axis === null) {\n    return normImpl(reshape(x, [-1]), p2, axis);\n  }\n  if (x.rank === 1 || typeof axis === \"number\" || Array.isArray(axis) && axis.length === 1) {\n    if (p2 === 1) {\n      return sum2(abs(x), axis);\n    }\n    if (p2 === Infinity) {\n      return max(abs(x), axis);\n    }\n    if (p2 === -Infinity) {\n      return min(abs(x), axis);\n    }\n    if (p2 === \"euclidean\" || p2 === 2) {\n      return sqrt(sum2(pow(abs(x), scalar(2, \"int32\")), axis));\n    }\n    throw new Error(`Error in norm: invalid ord value: ${p2}`);\n  }\n  if (Array.isArray(axis) && axis.length === 2) {\n    if (p2 === 1) {\n      return max(sum2(abs(x), axis[0]), axis[1] - 1);\n    }\n    if (p2 === Infinity) {\n      return max(sum2(abs(x), axis[1]), axis[0]);\n    }\n    if (p2 === -Infinity) {\n      return min(sum2(abs(x), axis[1]), axis[0]);\n    }\n    if (p2 === \"fro\" || p2 === \"euclidean\") {\n      return sqrt(sum2(square(x), axis));\n    }\n    throw new Error(`Error in norm: invalid ord value: ${p2}`);\n  }\n  throw new Error(`Error in norm: invalid axis: ${axis}`);\n}\nvar norm = op({ norm_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/euclidean_norm.js\nfunction euclideanNorm_(x, axis = null, keepDims = false) {\n  return norm(x, \"euclidean\", axis, keepDims);\n}\nvar euclideanNorm = op({ euclideanNorm_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/exp.js\nfunction exp_(x) {\n  const $x = convertToTensor(x, \"x\", \"exp\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Exp, inputs);\n}\nvar exp = op({ exp_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/expand_dims.js\nfunction expandDims_(x, axis = 0) {\n  const $x = convertToTensor(x, \"x\", \"expandDims\", \"string_or_numeric\");\n  assert(axis <= $x.rank, () => \"Axis must be <= rank of the tensor\");\n  const inputs = { input: $x };\n  const attrs = { dim: axis };\n  return ENGINE.runKernel(ExpandDims, inputs, attrs);\n}\nvar expandDims = op({ expandDims_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/expm1.js\nfunction expm1_(x) {\n  const $x = convertToTensor(x, \"x\", \"expm1\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Expm1, inputs);\n}\nvar expm1 = op({ expm1_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tile.js\nfunction tile_(x, reps) {\n  const $x = convertToTensor(x, \"x\", \"tile\", \"string_or_numeric\");\n  assert($x.rank === reps.length, () => `Error in transpose: rank of input ${$x.rank} must match length of reps ${reps}.`);\n  const inputs = { x: $x };\n  const attrs = { reps };\n  return ENGINE.runKernel(Tile, inputs, attrs);\n}\nvar tile = op({ tile_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/eye.js\nfunction eye_(numRows, numColumns, batchShape, dtype = \"float32\") {\n  if (numColumns == null) {\n    numColumns = numRows;\n  }\n  const buff = buffer([numRows, numColumns], dtype);\n  const n2 = numRows <= numColumns ? numRows : numColumns;\n  for (let i2 = 0; i2 < n2; ++i2) {\n    buff.set(1, i2, i2);\n  }\n  const out = reshape(buff.toTensor(), [numRows, numColumns]);\n  if (batchShape == null) {\n    return out;\n  } else {\n    if (batchShape.length === 1) {\n      return tile(expandDims(out, 0), [batchShape[0], 1, 1]);\n    } else if (batchShape.length === 2) {\n      return tile(expandDims(expandDims(out, 0), 0), [batchShape[0], batchShape[1], 1, 1]);\n    } else if (batchShape.length === 3) {\n      return tile(expandDims(expandDims(expandDims(out, 0), 0), 0), [\n        batchShape[0],\n        batchShape[1],\n        batchShape[2],\n        1,\n        1\n      ]);\n    } else {\n      throw new Error(`eye() currently supports only 1D and 2D batchShapes, but received ${batchShape.length}D.`);\n    }\n  }\n}\nvar eye = op({ eye_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/fill.js\nfunction fill(shape, value, dtype) {\n  const attrs = { shape, value, dtype };\n  return ENGINE.runKernel(Fill, {}, attrs);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/floor.js\nfunction floor_(x) {\n  const $x = convertToTensor(x, \"x\", \"floor\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Floor, inputs);\n}\nvar floor = op({ floor_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/gather.js\nfunction gather_(x, indices, axis = 0, batchDims = 0) {\n  const $x = convertToTensor(x, \"x\", \"gather\");\n  const $indices = convertToTensor(indices, \"indices\", \"gather\", \"int32\");\n  const inputs = { x: $x, indices: $indices };\n  const attrs = { axis, batchDims };\n  return ENGINE.runKernel(GatherV2, inputs, attrs);\n}\nvar gather = op({ gather_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/greater.js\nfunction greater_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"greater\", \"string_or_numeric\");\n  let $b = convertToTensor(b, \"b\", \"greater\", \"string_or_numeric\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Greater, inputs);\n}\nvar greater = op({ greater_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/greater_equal.js\nfunction greaterEqual_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"greaterEqual\", \"string_or_numeric\");\n  let $b = convertToTensor(b, \"b\", \"greaterEqual\", \"string_or_numeric\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(GreaterEqual, inputs);\n}\nvar greaterEqual = op({ greaterEqual_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/is_finite.js\nfunction isFinite_(x) {\n  const $x = convertToTensor(x, \"x\", \"isFinite\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(IsFinite, inputs);\n}\nvar isFinite2 = op({ isFinite_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/is_inf.js\nfunction isInf_(x) {\n  const $x = convertToTensor(x, \"x\", \"isInf\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(IsInf, inputs);\n}\nvar isInf = op({ isInf_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/is_nan.js\nfunction isNaN_(x) {\n  const $x = convertToTensor(x, \"x\", \"isNaN\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(IsNan, inputs);\n}\nvar isNaN2 = op({ isNaN_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/leaky_relu.js\nfunction leakyRelu_(x, alpha = 0.2) {\n  const $x = convertToTensor(x, \"x\", \"leakyRelu\");\n  const inputs = { x: $x };\n  const attrs = { alpha };\n  return ENGINE.runKernel(LeakyRelu, inputs, attrs);\n}\nvar leakyRelu = op({ leakyRelu_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/less.js\nfunction less_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"less\", \"string_or_numeric\");\n  let $b = convertToTensor(b, \"b\", \"less\", \"string_or_numeric\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Less, inputs);\n}\nvar less = op({ less_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/less_equal.js\nfunction lessEqual_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"lessEqual\", \"string_or_numeric\");\n  let $b = convertToTensor(b, \"b\", \"lessEqual\", \"string_or_numeric\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(LessEqual, inputs);\n}\nvar lessEqual = op({ lessEqual_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/linspace.js\nfunction linspace(start, stop, num) {\n  if (num <= 0) {\n    throw new Error(\"The number of values should be positive.\");\n  }\n  const attrs = { start, stop, num };\n  return ENGINE.runKernel(LinSpace, {}, attrs);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/local_response_normalization.js\nfunction localResponseNormalization_(x, depthRadius = 5, bias = 1, alpha = 1, beta = 0.5) {\n  const $x = convertToTensor(x, \"x\", \"localResponseNormalization\");\n  assert($x.rank === 4 || $x.rank === 3, () => `Error in localResponseNormalization: x must be rank 3 or 4 but got\n               rank ${$x.rank}.`);\n  assert(isInt(depthRadius), () => `Error in localResponseNormalization: depthRadius must be an integer but got depthRadius ${depthRadius}.`);\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  const inputs = { x: x4D };\n  const attrs = { depthRadius, bias, alpha, beta };\n  const res = ENGINE.runKernel(LRN, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  } else {\n    return res;\n  }\n}\nvar localResponseNormalization = op({ localResponseNormalization_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/log.js\nfunction log_(x) {\n  const $x = convertToTensor(x, \"x\", \"log\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Log, inputs);\n}\nvar log2 = op({ log_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/log1p.js\nfunction log1p_(x) {\n  const $x = convertToTensor(x, \"x\", \"log1p\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Log1p, inputs);\n}\nvar log1p = op({ log1p_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients.js\nfunction grad(f) {\n  assert(isFunction(f), () => \"The f passed in grad(f) must be a function\");\n  return (x, dy) => {\n    const $x = convertToTensor(x, \"x\", \"tf.grad\", \"string_or_numeric\");\n    const $dy = dy != null ? convertToTensor(dy, \"dy\", \"tf.grad\") : null;\n    return ENGINE.tidy(() => {\n      const { value, grads: grads2 } = ENGINE.gradients(() => f($x), [$x], $dy);\n      if ($dy != null) {\n        assertShapesMatch(value.shape, $dy.shape, \"The shape of dy passed in grad(f)(x, dy) must match the shape returned by f(x)\");\n      }\n      checkGrads(grads2);\n      return grads2[0];\n    });\n  };\n}\nfunction grads(f) {\n  assert(isFunction(f), () => \"The f passed in grads(f) must be a function\");\n  return (args, dy) => {\n    assert(Array.isArray(args), () => \"The args passed in grads(f)(args) must be an array of `Tensor`s or `TensorLike`s\");\n    const $args = convertToTensorArray(args, \"args\", \"tf.grads\", \"string_or_numeric\");\n    const $dy = dy != null ? convertToTensor(dy, \"dy\", \"tf.grads\") : null;\n    return ENGINE.tidy(() => {\n      const { value, grads: grads2 } = ENGINE.gradients(() => f(...$args), $args, $dy);\n      if ($dy != null) {\n        assertShapesMatch(value.shape, $dy.shape, \"The shape of dy passed in grads(f)([x1,...], dy) must match the shape returned by f([x1,...])\");\n      }\n      checkGrads(grads2);\n      return grads2;\n    });\n  };\n}\nfunction valueAndGrad(f) {\n  assert(isFunction(f), () => \"The f passed in valueAndGrad(f) must be a function\");\n  return (x, dy) => {\n    assert(x instanceof Tensor, () => \"The x passed in valueAndGrad(f)(x) must be a tensor\");\n    assert(dy == null || dy instanceof Tensor, () => \"The dy passed in valueAndGrad(f)(x, dy) must be a tensor\");\n    const { grads: grads2, value } = ENGINE.gradients(() => f(x), [x], dy);\n    checkGrads(grads2);\n    return { grad: grads2[0], value };\n  };\n}\nfunction valueAndGrads(f) {\n  assert(isFunction(f), () => \"The f passed in valueAndGrads(f) must be a function\");\n  return (args, dy) => {\n    assert(Array.isArray(args) && args.every((arg) => arg instanceof Tensor), () => \"The args passed in valueAndGrads(f)(args) must be array of tensors\");\n    assert(dy == null || dy instanceof Tensor, () => \"The dy passed in valueAndGrads(f)(args, dy) must be a tensor\");\n    const res = ENGINE.gradients(() => f(...args), args, dy);\n    if (dy != null) {\n      assertShapesMatch(res.value.shape, dy.shape, \"The shape of dy passed in valueAndGrads(f)([x1,...], dy) must match the shape returned by f([x1,...])\");\n    }\n    checkGrads(res.grads);\n    return res;\n  };\n}\nfunction variableGrads(f, varList) {\n  assert(isFunction(f), () => \"The f passed in variableGrads(f) must be a function\");\n  assert(varList == null || Array.isArray(varList) && varList.every((v) => v instanceof Variable), () => \"The varList passed in variableGrads(f, varList) must be an array of variables\");\n  const specifiedVarList = varList != null;\n  if (!specifiedVarList) {\n    varList = [];\n    for (const varName in ENGINE.registeredVariables) {\n      varList.push(ENGINE.registeredVariables[varName]);\n    }\n  }\n  const specifiedNonTrainable = specifiedVarList ? varList.filter((variable2) => !variable2.trainable) : null;\n  const originalVarCount = varList.length;\n  varList = varList.filter((variable2) => variable2.trainable);\n  assert(varList.length > 0, () => `variableGrads() expects at least one of the input variables to be trainable, but none of the ${originalVarCount} variables is trainable.`);\n  const allowNoGradients = true;\n  const { value, grads: grads2 } = ENGINE.gradients(f, varList, null, allowNoGradients);\n  assert(grads2.some((g) => g != null), () => \"Cannot find a connection between any variable and the result of the loss function y=f(x). Please make sure the operations that use variables are inside the function f passed to minimize().\");\n  assert(value.rank === 0, () => `The f passed in variableGrads(f) must return a scalar, but it returned a rank-${value.rank} tensor`);\n  const namedGrads = {};\n  varList.forEach((v, i2) => {\n    if (grads2[i2] != null) {\n      namedGrads[v.name] = grads2[i2];\n    }\n  });\n  if (specifiedNonTrainable != null) {\n    specifiedNonTrainable.forEach((v) => namedGrads[v.name] = null);\n  }\n  return { value, grads: namedGrads };\n}\nfunction customGrad(f) {\n  return ENGINE.customGrad(f);\n}\nfunction checkGrads(grads2) {\n  const numNullGradients = grads2.filter((g) => g == null).length;\n  if (numNullGradients > 0) {\n    throw new Error(`Cannot compute gradient of y=f(x) with respect to x. Make sure that\n    the f you passed encloses all operations that lead from x to y.`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/softplus.js\nfunction softplus_(x) {\n  const $x = convertToTensor(x, \"x\", \"softplus\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Softplus, inputs);\n}\nvar softplus = op({ softplus_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/log_sigmoid.js\nfunction logSigmoid_(x) {\n  const $x = convertToTensor(x, \"x\", \"logSigmoid\");\n  const customOp = customGrad((x2) => {\n    const value = neg(softplus(neg(x2)));\n    const gradFunc = (dy) => {\n      const derX = mul(dy, sigmoid(neg(x2)));\n      return derX;\n    };\n    return { value, gradFunc };\n  });\n  return customOp($x);\n}\nvar logSigmoid = op({ logSigmoid_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sub.js\nfunction sub_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"sub\");\n  let $b = convertToTensor(b, \"b\", \"sub\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Sub, inputs);\n}\nvar sub = op({ sub_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/log_softmax.js\nfunction logSoftmax_(logits, axis = -1) {\n  const $logits = convertToTensor(logits, \"logits\", \"logSoftmax\");\n  if (axis === -1) {\n    axis = $logits.rank - 1;\n  }\n  if (axis !== $logits.rank - 1) {\n    throw Error(`Log Softmax along a non-last dimension is not yet supported. Logits was rank ${$logits.rank} and axis was ${axis}`);\n  }\n  const customOp = customGrad((logits2, save) => {\n    const keepDims = true;\n    const xMax = max(logits2, axis, true);\n    const shifted = sub(logits2, xMax);\n    const value = sub(cast(shifted, \"float32\"), log2(sum2(exp(shifted), axis, keepDims)));\n    save([value]);\n    const gradFunc = (dy, saved) => {\n      const [value2] = saved;\n      const keepDims2 = true;\n      const softmax7 = exp(value2);\n      return sub(dy, mul(sum2(dy, axis, keepDims2), softmax7));\n    };\n    return { value, gradFunc };\n  });\n  return customOp($logits);\n}\nvar logSoftmax = op({ logSoftmax_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/log_sum_exp.js\nfunction logSumExp_(x, axis = null, keepDims = false) {\n  const $x = convertToTensor(x, \"x\", \"logSumExp\");\n  const axes = parseAxisParam(axis, $x.shape);\n  const xMax = max($x, axes, true);\n  const a = sub($x, xMax);\n  const b = exp(a);\n  const c = sum2(b, axes);\n  const d = log2(c);\n  const res = add2(reshape(xMax, d.shape), d);\n  if (keepDims) {\n    const newShape = expandShapeToKeepDim(res.shape, axes);\n    return reshape(res, newShape);\n  }\n  return res;\n}\nvar logSumExp = op({ logSumExp_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/logical_and.js\nfunction logicalAnd_(a, b) {\n  const $a = convertToTensor(a, \"a\", \"logicalAnd\", \"bool\");\n  const $b = convertToTensor(b, \"b\", \"logicalAnd\", \"bool\");\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(LogicalAnd, inputs);\n}\nvar logicalAnd = op({ logicalAnd_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/logical_not.js\nfunction logicalNot_(x) {\n  const $x = convertToTensor(x, \"x\", \"logicalNot\", \"bool\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(LogicalNot, inputs);\n}\nvar logicalNot = op({ logicalNot_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/logical_or.js\nfunction logicalOr_(a, b) {\n  const $a = convertToTensor(a, \"a\", \"logicalOr\", \"bool\");\n  const $b = convertToTensor(b, \"b\", \"logicalOr\", \"bool\");\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(LogicalOr, inputs);\n}\nvar logicalOr = op({ logicalOr_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/logical_xor.js\nfunction logicalXor_(a, b) {\n  const $a = convertToTensor(a, \"a\", \"logicalXor\", \"bool\");\n  const $b = convertToTensor(b, \"b\", \"logicalXor\", \"bool\");\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  return logicalAnd(logicalOr(a, b), logicalNot(logicalAnd(a, b)));\n}\nvar logicalXor = op({ logicalXor_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/search_sorted.js\nvar INT32_MAX = 2147483648;\nfunction searchSorted_(sortedSequence, values, side = \"left\") {\n  const $sortedSequence = convertToTensor(sortedSequence, \"sortedSequence\", \"searchSorted\");\n  const $values = convertToTensor(values, \"values\", \"searchSorted\");\n  const sequenceSize = $sortedSequence.shape[$sortedSequence.shape.length - 1];\n  const valuesSize = $values.shape[$values.shape.length - 1];\n  const $sortedSequence2D = reshape($sortedSequence, [-1, sequenceSize]);\n  const $values2D = reshape($values, [-1, valuesSize]);\n  if ($sortedSequence2D.rank < 2) {\n    throw new Error(`Sorted input argument must be at least 2-dimensional`);\n  }\n  if ($sortedSequence2D.shape[0] !== $values2D.shape[0]) {\n    throw new Error(`Leading dimension of 'sortedSequence' and 'values' must match.`);\n  }\n  if (sizeFromShape($values2D.shape) >= INT32_MAX) {\n    throw new Error(`values tensor size must less than ${INT32_MAX}`);\n  }\n  if ($sortedSequence2D.shape[1] >= INT32_MAX) {\n    throw new Error(`trailing dim_size must less than ${INT32_MAX} for int32 output type, was ${$sortedSequence2D.shape[1]}`);\n  }\n  const inputs = {\n    sortedSequence: $sortedSequence2D,\n    values: $values2D\n  };\n  const attrs = { side };\n  return ENGINE.runKernel(SearchSorted, inputs, attrs);\n}\nvar searchSorted = op({ searchSorted_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/lower_bound.js\nfunction lowerBound(sortedSequence, values) {\n  return searchSorted(sortedSequence, values, \"left\");\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/max_pool.js\nfunction maxPool_(x, filterSize, strides, pad3, dimRoundingMode) {\n  const $x = convertToTensor(x, \"x\", \"maxPool\");\n  const dilations = 1;\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  assert(x4D.rank === 4, () => `Error in maxPool: input must be rank 4 but got rank ${x4D.rank}.`);\n  assert(eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in maxPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  checkPadOnDimRoundingMode(\"maxPool\", pad3, dimRoundingMode);\n  const inputs = { x: x4D };\n  const attrs = { filterSize, strides, pad: pad3, dimRoundingMode };\n  const res = ENGINE.runKernel(MaxPool, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar maxPool = op({ maxPool_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_3d.js\nfunction maxPool3d_(x, filterSize = [1, 1, 1], strides, pad3, dimRoundingMode, dataFormat = \"NDHWC\") {\n  const $x = convertToTensor(x, \"x\", \"maxPool3d\");\n  let x5D = $x;\n  let reshapedTo5D = false;\n  if ($x.rank === 4) {\n    reshapedTo5D = true;\n    x5D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2], $x.shape[3]]);\n  }\n  assert(x5D.rank === 5, () => `Error in maxPool3d: x must be rank 5 but got rank ${x5D.rank}.`);\n  assert(dataFormat === \"NDHWC\", () => `Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of ${dataFormat}`);\n  checkPadOnDimRoundingMode(\"maxPool3d\", pad3, dimRoundingMode);\n  const inputs = { x: x5D };\n  const attrs = { filterSize, strides, pad: pad3, dimRoundingMode, dataFormat };\n  const res = ENGINE.runKernel(MaxPool3D, inputs, attrs);\n  if (reshapedTo5D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);\n  }\n  return res;\n}\nvar maxPool3d = op({ maxPool3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_with_argmax.js\nfunction maxPoolWithArgmax_(x, filterSize, strides, pad3, includeBatchInIndex = false) {\n  const $x = convertToTensor(x, \"x\", \"maxPoolWithArgmax\");\n  const inputs = { x: $x };\n  const attrs = { filterSize, strides, pad: pad3, includeBatchInIndex };\n  const result = ENGINE.runKernel(MaxPoolWithArgmax, inputs, attrs);\n  return { result: result[0], indexes: result[1] };\n}\nvar maxPoolWithArgmax = op({ maxPoolWithArgmax_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/maximum.js\nfunction maximum_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"maximum\");\n  let $b = convertToTensor(b, \"b\", \"maximum\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  if ($a.dtype === \"bool\") {\n    $a = cast($a, \"int32\");\n    $b = cast($b, \"int32\");\n  }\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Maximum, inputs);\n}\nvar maximum = op({ maximum_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/mean.js\nfunction mean_(x, axis = null, keepDims = false) {\n  const $x = convertToTensor(x, \"x\", \"mean\");\n  const inputs = { x: $x };\n  const attrs = { axis, keepDims };\n  return ENGINE.runKernel(Mean, inputs, attrs);\n}\nvar mean = op({ mean_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/zeros.js\nfunction zeros(shape, dtype = \"float32\") {\n  if (dtype === \"complex64\") {\n    const real5 = zeros(shape, \"float32\");\n    const imag5 = zeros(shape, \"float32\");\n    return complex(real5, imag5);\n  }\n  const values = makeZerosTypedArray(sizeFromShape(shape), dtype);\n  return ENGINE.makeTensor(values, shape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/ones.js\nfunction ones2(shape, dtype = \"float32\") {\n  if (dtype === \"complex64\") {\n    const real5 = ones2(shape, \"float32\");\n    const imag5 = zeros(shape, \"float32\");\n    return complex(real5, imag5);\n  }\n  const values = makeOnesTypedArray(sizeFromShape(shape), dtype);\n  return ENGINE.makeTensor(values, shape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/meshgrid.js\nfunction meshgrid(x, y, { indexing = \"xy\" } = {}) {\n  if (indexing !== \"xy\" && indexing !== \"ij\") {\n    throw new TypeError(`${indexing} is not a valid third argument to meshgrid`);\n  }\n  if (x === void 0) {\n    return [];\n  }\n  let $x = convertToTensor(x, \"x\", \"meshgrid\", x instanceof Tensor ? x.dtype : \"float32\");\n  if (y === void 0) {\n    return [$x];\n  }\n  let $y = convertToTensor(y, \"y\", \"meshgrid\", y instanceof Tensor ? y.dtype : \"float32\");\n  const w = sizeFromShape($x.shape);\n  const h = sizeFromShape($y.shape);\n  if (indexing === \"xy\") {\n    $x = reshape($x, [1, -1]);\n    $y = reshape($y, [-1, 1]);\n    return [\n      matMul(ones2([h, 1], $x.dtype), $x),\n      matMul($y, ones2([1, w], $y.dtype))\n    ];\n  }\n  $x = reshape($x, [-1, 1]);\n  $y = reshape($y, [1, -1]);\n  return [\n    matMul($x, ones2([1, h], $x.dtype)),\n    matMul(ones2([w, 1], $y.dtype), $y)\n  ];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/minimum.js\nfunction minimum_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"minimum\");\n  let $b = convertToTensor(b, \"b\", \"minimum\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  if ($a.dtype === \"bool\") {\n    $a = cast($a, \"int32\");\n    $b = cast($b, \"int32\");\n  }\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Minimum, inputs);\n}\nvar minimum = op({ minimum_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/mirror_pad.js\nfunction mirrorPad_(x, paddings, mode) {\n  assert(mode === \"reflect\" || mode === \"symmetric\", () => `Invalid mode. Mode must be either reflect or symmetric. Got ${mode}.`);\n  const $x = convertToTensor(x, \"x\", \"mirrorPad\");\n  if ($x.rank === 0) {\n    throw new Error(\"mirrorPad(scalar) is not defined. Pass non-scalar to mirrorPad\");\n  }\n  assert(paddings.length === $x.rank, () => `Padding doesn't match input. Must be ${$x.rank}. Got ${paddings.length}.`);\n  const shapeOffset = mode === \"reflect\" ? 1 : 0;\n  for (let i2 = 0; i2 < $x.rank; i2++) {\n    assert(paddings[i2].length === 2, () => `Invalid number of paddings. Must be length of 2 each.`);\n    assert(paddings[i2][0] >= 0 && paddings[i2][0] <= $x.shape[i2] - shapeOffset && paddings[i2][1] >= 0 && paddings[i2][1] <= $x.shape[i2] - shapeOffset, () => `Padding in dimension ${i2} cannot be greater than or equal to ${$x.shape[i2] - shapeOffset} or less than 0 for input of shape ${$x.shape}`);\n  }\n  const attrs = { paddings, mode };\n  const inputs = { x: $x };\n  return ENGINE.runKernel(MirrorPad, inputs, attrs);\n}\nvar mirrorPad = op({ mirrorPad_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/mod.js\nfunction mod_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"mod\");\n  let $b = convertToTensor(b, \"b\", \"mod\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(Mod, inputs);\n}\nvar mod = op({ mod_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/moments.js\nfunction moments_(x, axis = null, keepDims = false) {\n  x = convertToTensor(x, \"x\", \"moments\");\n  const axes = parseAxisParam(axis, x.shape);\n  const xMean = mean(x, axes, keepDims);\n  let keepDimsShape = xMean.shape;\n  if (!keepDims) {\n    keepDimsShape = expandShapeToKeepDim(xMean.shape, axes);\n  }\n  const devSquared = square(sub(cast(x, \"float32\"), reshape(xMean, keepDimsShape)));\n  const variance = mean(devSquared, axes, keepDims);\n  return { mean: xMean, variance };\n}\nvar moments = op({ moments_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/multi_rnn_cell.js\nfunction multiRNNCell_(lstmCells, data, c, h) {\n  const $data = convertToTensor(data, \"data\", \"multiRNNCell\");\n  const $c = convertToTensorArray(c, \"c\", \"multiRNNCell\");\n  const $h = convertToTensorArray(h, \"h\", \"multiRNNCell\");\n  let input2 = $data;\n  const newStates = [];\n  for (let i2 = 0; i2 < lstmCells.length; i2++) {\n    const output = lstmCells[i2](input2, $c[i2], $h[i2]);\n    newStates.push(output[0]);\n    newStates.push(output[1]);\n    input2 = output[1];\n  }\n  const newC = [];\n  const newH = [];\n  for (let i2 = 0; i2 < newStates.length; i2 += 2) {\n    newC.push(newStates[i2]);\n    newH.push(newStates[i2 + 1]);\n  }\n  return [newC, newH];\n}\nvar multiRNNCell = op({ multiRNNCell_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/multinomial.js\nfunction multinomial_(logits, numSamples, seed, normalized = false) {\n  const $logits = convertToTensor(logits, \"logits\", \"multinomial\");\n  const numOutcomes = $logits.size;\n  const origRank = $logits.rank;\n  if (numOutcomes < 2) {\n    throw new Error(`Error in multinomial: you need at least 2 outcomes, but got ${numOutcomes}.`);\n  }\n  if (origRank > 2) {\n    throw new Error(`Rank of probabilities must be 1 or 2, but is ${origRank}`);\n  }\n  seed = seed || Math.random();\n  const logits2D = origRank === 1 ? reshape($logits, [1, -1]) : $logits;\n  const inputs = { logits: logits2D };\n  const attrs = { numSamples, seed, normalized };\n  const res = ENGINE.runKernel(Multinomial, inputs, attrs);\n  return origRank === 1 ? reshape(res, [res.size]) : res;\n}\nvar multinomial = op({ multinomial_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/not_equal.js\nfunction notEqual_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"notEqual\", \"string_or_numeric\");\n  let $b = convertToTensor(b, \"b\", \"notEqual\", \"string_or_numeric\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  return ENGINE.runKernel(NotEqual, inputs);\n}\nvar notEqual = op({ notEqual_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/ones_like.js\nfunction onesLike_(x) {\n  const $x = convertToTensor(x, \"x\", \"onesLike\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(OnesLike, inputs);\n}\nvar onesLike = op({ onesLike_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/outer_product.js\nfunction outerProduct_(v1, v2) {\n  const $v1 = convertToTensor(v1, \"v1\", \"outerProduct\");\n  const $v2 = convertToTensor(v2, \"v2\", \"outerProduct\");\n  assert($v1.rank === 1 && $v2.rank === 1, () => `Error in outerProduct: inputs must be rank 1, but got ranks ${$v1.rank} and ${$v2.rank}.`);\n  const v12D = reshape($v1, [-1, 1]);\n  const v22D = reshape($v2, [1, -1]);\n  return matMul(v12D, v22D);\n}\nvar outerProduct = op({ outerProduct_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/pad.js\nfunction pad_(x, paddings, constantValue = 0) {\n  const $x = convertToTensor(x, \"x\", \"pad\");\n  if ($x.rank === 0) {\n    throw new Error(\"pad(scalar) is not defined. Pass non-scalar to pad\");\n  }\n  const attrs = { paddings, constantValue };\n  const inputs = { x: $x };\n  return ENGINE.runKernel(PadV2, inputs, attrs);\n}\nvar pad = op({ pad_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/pad1d.js\nfunction pad1d_(x, paddings, constantValue = 0) {\n  assert(paddings.length === 2, () => \"Invalid number of paddings. Must be length of 2.\");\n  return pad(x, [paddings], constantValue);\n}\nvar pad1d = op({ pad1d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/pad2d.js\nfunction pad2d_(x, paddings, constantValue = 0) {\n  assert(paddings.length === 2 && paddings[0].length === 2 && paddings[1].length === 2, () => \"Invalid number of paddings. Must be length of 2 each.\");\n  return pad(x, paddings, constantValue);\n}\nvar pad2d = op({ pad2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/pad3d.js\nfunction pad3d_(x, paddings, constantValue = 0) {\n  assert(paddings.length === 3 && paddings[0].length === 2 && paddings[1].length === 2 && paddings[2].length === 2, () => \"Invalid number of paddings. Must be length of 2 each.\");\n  return pad(x, paddings, constantValue);\n}\nvar pad3d = op({ pad3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/pad4d.js\nfunction pad4d_(x, paddings, constantValue = 0) {\n  assert(paddings.length === 4 && paddings[0].length === 2 && paddings[1].length === 2 && paddings[2].length === 2 && paddings[3].length === 2, () => \"Invalid number of paddings. Must be length of 2 each.\");\n  return pad(x, paddings, constantValue);\n}\nvar pad4d = op({ pad4d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/space_to_batch_nd.js\nfunction spaceToBatchND_(x, blockShape, paddings) {\n  const $x = convertToTensor(x, \"x\", \"spaceToBatchND\");\n  assert($x.rank >= 1 + blockShape.length, () => `input rank ${$x.rank} should be > than [blockShape] ${blockShape.length}`);\n  assert(paddings.length === blockShape.length, () => `paddings.shape[0] ${paddings.length} must be equal to [blockShape] ${blockShape.length}`);\n  assert($x.shape.reduce((a, b, i2) => {\n    if (i2 > 0 && i2 <= blockShape.length) {\n      return a && (b + paddings[i2 - 1][0] + paddings[i2 - 1][1]) % blockShape[i2 - 1] === 0;\n    }\n    return a;\n  }, true), () => `input spatial dimensions ${$x.shape.slice(1)} with paddings ${paddings.toString()} must be divisible by blockShapes ${blockShape.toString()}`);\n  const inputs = { x: $x };\n  const attrs = { blockShape, paddings };\n  return ENGINE.runKernel(SpaceToBatchND, inputs, attrs);\n}\nvar spaceToBatchND = op({ spaceToBatchND_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/pool.js\nfunction pool_(input2, windowShape, poolingType, pad3, dilations, strides, dimRoundingMode) {\n  if (dilations == null) {\n    dilations = [1, 1];\n  }\n  if (strides == null) {\n    strides = 1;\n  }\n  if (pad3 === 0) {\n    pad3 = \"valid\";\n  }\n  const $x = convertToTensor(input2, \"x\", \"maxPool\");\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  assert(eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in pool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  const convInfo = computePool2DInfo(x4D.shape, windowShape, strides, dilations, pad3);\n  const dilation = [convInfo.dilationHeight, convInfo.dilationWidth];\n  let basePadding;\n  if (pad3 === \"same\") {\n    basePadding = withSpaceToBatchBasePaddings([convInfo.filterHeight, convInfo.filterWidth], dilation);\n  } else {\n    basePadding = [[0, 0], [0, 0]];\n  }\n  const isDilationOne = dilation[0] === 1 && dilation[1] === 1;\n  const [adjustedPadding, adjustedCrops] = requiredSpaceToBatchPaddings([convInfo.inHeight, convInfo.inWidth], dilation, basePadding);\n  const convertedPad = isDilationOne ? pad3 : \"valid\";\n  const convertedX = isDilationOne ? x4D : spaceToBatchND(x4D, dilation, adjustedPadding);\n  const forwardOp = poolingType === \"avg\" ? () => avgPool(convertedX, windowShape, strides, convertedPad, dimRoundingMode) : () => maxPool(convertedX, windowShape, strides, convertedPad, dimRoundingMode);\n  const y = forwardOp();\n  const res = isDilationOne ? y : batchToSpaceND(y, dilation, adjustedCrops);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nfunction requiredSpaceToBatchPaddings(inputShape, blockShape, basePadding) {\n  const padStart = basePadding.map((b) => b[0]);\n  const origPadEnd = basePadding.map((b) => b[1]);\n  const fullInputShape = inputShape.concat(padStart, origPadEnd);\n  const padEndExtra = blockShape.map((b, i2) => (b - fullInputShape[i2] % b) % b);\n  const padEnd = origPadEnd.map((s2, i2) => s2 + padEndExtra[i2]);\n  const paddings = blockShape.map((_, i2) => [padStart[i2], padEnd[i2]]);\n  const crops = blockShape.map((_, i2) => [0, padEndExtra[i2]]);\n  return [paddings, crops];\n}\nfunction withSpaceToBatchBasePaddings(filterShape, dilation) {\n  const dilatedFilterShape = filterShape.map((s2, i2) => {\n    return s2 + (s2 - 1) * (dilation[i2] - 1);\n  });\n  const padExtraShape = dilatedFilterShape.map((s2) => s2 - 1);\n  const padExtraStart = padExtraShape.map((s2) => Math.floor(s2 / 2));\n  const padExtraEnd = padExtraShape.map((s2, i2) => s2 - padExtraStart[i2]);\n  return padExtraShape.map((_, i2) => {\n    return [padExtraStart[i2], padExtraEnd[i2]];\n  });\n}\nvar pool = op({ pool_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/prelu.js\nfunction prelu_(x, alpha) {\n  const $x = convertToTensor(x, \"x\", \"prelu\");\n  const $alpha = convertToTensor(alpha, \"alpha\", \"prelu\");\n  const inputs = { x: $x, alpha: $alpha };\n  return ENGINE.runKernel(Prelu, inputs);\n}\nvar prelu = op({ prelu_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/prod.js\nfunction prod_(x, axis = null, keepDims = false) {\n  let $x = convertToTensor(x, \"x\", \"prod\");\n  if ($x.dtype === \"bool\") {\n    $x = cast($x, \"int32\");\n  }\n  const inputs = { x: $x };\n  const attrs = { axis, keepDims };\n  return ENGINE.runKernel(Prod, inputs, attrs);\n}\nvar prod = op({ prod_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/rand.js\nfunction rand_(shape, randFunction, dtype) {\n  const size = sizeFromShape(shape);\n  let values = null;\n  if (dtype == null || dtype === \"float32\") {\n    values = new Float32Array(size);\n  } else if (dtype === \"int32\") {\n    values = new Int32Array(size);\n  } else if (dtype === \"bool\") {\n    values = new Uint8Array(size);\n  } else {\n    throw new Error(`Unknown data type ${dtype}`);\n  }\n  for (let i2 = 0; i2 < size; i2++) {\n    values[i2] = randFunction();\n  }\n  return ENGINE.makeTensor(values, shape, dtype);\n}\nvar rand = op({ rand_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/rand_util.js\nvar seedrandom = __toESM(require_seedrandom2());\nvar MPRandGauss = class {\n  constructor(mean5, stdDeviation, dtype, truncated, seed) {\n    this.mean = mean5;\n    this.stdDev = stdDeviation;\n    this.dtype = dtype;\n    this.nextVal = NaN;\n    this.truncated = truncated;\n    if (this.truncated) {\n      this.upper = this.mean + this.stdDev * 2;\n      this.lower = this.mean - this.stdDev * 2;\n    }\n    const seedValue = seed ? seed : Math.random();\n    this.random = seedrandom.alea(seedValue.toString());\n  }\n  nextValue() {\n    if (!isNaN(this.nextVal)) {\n      const value = this.nextVal;\n      this.nextVal = NaN;\n      return value;\n    }\n    let resultX, resultY;\n    let isValid = false;\n    while (!isValid) {\n      let v1, v2, s2;\n      do {\n        v1 = 2 * this.random() - 1;\n        v2 = 2 * this.random() - 1;\n        s2 = v1 * v1 + v2 * v2;\n      } while (s2 >= 1 || s2 === 0);\n      const mul2 = Math.sqrt(-2 * Math.log(s2) / s2);\n      resultX = this.mean + this.stdDev * v1 * mul2;\n      resultY = this.mean + this.stdDev * v2 * mul2;\n      if (!this.truncated || this.isValidTruncated(resultX)) {\n        isValid = true;\n      }\n    }\n    if (!this.truncated || this.isValidTruncated(resultY)) {\n      this.nextVal = this.convertValue(resultY);\n    }\n    return this.convertValue(resultX);\n  }\n  convertValue(value) {\n    if (this.dtype == null || this.dtype === \"float32\") {\n      return value;\n    }\n    return Math.round(value);\n  }\n  isValidTruncated(value) {\n    return value <= this.upper && value >= this.lower;\n  }\n};\nvar RandGamma = class {\n  constructor(alpha, beta, dtype, seed) {\n    this.alpha = alpha;\n    this.beta = 1 / beta;\n    this.dtype = dtype;\n    const seedValue = seed ? seed : Math.random();\n    this.randu = seedrandom.alea(seedValue.toString());\n    this.randn = new MPRandGauss(0, 1, dtype, false, this.randu());\n    if (alpha < 1) {\n      this.d = alpha + 2 / 3;\n    } else {\n      this.d = alpha - 1 / 3;\n    }\n    this.c = 1 / Math.sqrt(9 * this.d);\n  }\n  nextValue() {\n    let x2, v0, v1, x, u, v;\n    while (true) {\n      do {\n        x = this.randn.nextValue();\n        v = 1 + this.c * x;\n      } while (v <= 0);\n      v *= v * v;\n      x2 = x * x;\n      v0 = 1 - 0.331 * x2 * x2;\n      v1 = 0.5 * x2 + this.d * (1 - v + Math.log(v));\n      u = this.randu();\n      if (u < v0 || Math.log(u) < v1) {\n        break;\n      }\n    }\n    v = 1 / this.beta * this.d * v;\n    if (this.alpha < 1) {\n      v *= Math.pow(this.randu(), 1 / this.alpha);\n    }\n    return this.convertValue(v);\n  }\n  convertValue(value) {\n    if (this.dtype === \"float32\") {\n      return value;\n    }\n    return Math.round(value);\n  }\n};\nvar UniformRandom = class {\n  constructor(min7 = 0, max7 = 1, dtype, seed) {\n    this.canReturnFloat = () => this.dtype == null || this.dtype === \"float32\";\n    this.min = min7;\n    this.range = max7 - min7;\n    this.dtype = dtype;\n    if (seed == null) {\n      seed = Math.random();\n    }\n    if (typeof seed === \"number\") {\n      seed = seed.toString();\n    }\n    if (!this.canReturnFloat() && this.range <= 1) {\n      throw new Error(`The difference between ${min7} - ${max7} <= 1 and dtype is not float`);\n    }\n    this.random = seedrandom.alea(seed);\n  }\n  convertValue(value) {\n    if (this.canReturnFloat()) {\n      return value;\n    }\n    return Math.round(value);\n  }\n  nextValue() {\n    return this.convertValue(this.min + this.range * this.random());\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/random_gamma.js\nfunction randomGamma_(shape, alpha, beta = 1, dtype = \"float32\", seed) {\n  if (beta == null) {\n    beta = 1;\n  }\n  if (dtype == null) {\n    dtype = \"float32\";\n  }\n  if (dtype !== \"float32\" && dtype !== \"int32\") {\n    throw new Error(`Unsupported data type ${dtype}`);\n  }\n  const rgamma = new RandGamma(alpha, beta, dtype, seed);\n  const res = buffer(shape, dtype);\n  for (let i2 = 0; i2 < res.values.length; i2++) {\n    res.values[i2] = rgamma.nextValue();\n  }\n  return res.toTensor();\n}\nvar randomGamma = op({ randomGamma_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/random_normal.js\nfunction randomNormal_(shape, mean5 = 0, stdDev = 1, dtype, seed) {\n  if (dtype != null && dtype === \"bool\") {\n    throw new Error(`Unsupported data type ${dtype}`);\n  }\n  const randGauss = new MPRandGauss(mean5, stdDev, dtype, false, seed);\n  const res = buffer(shape, dtype);\n  for (let i2 = 0; i2 < res.values.length; i2++) {\n    res.values[i2] = randGauss.nextValue();\n  }\n  return res.toTensor();\n}\nvar randomNormal = op({ randomNormal_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/random_standard_normal.js\nfunction randomStandardNormal_(shape, dtype, seed) {\n  if (dtype != null && dtype === \"bool\") {\n    throw new Error(`Unsupported data type ${dtype}`);\n  }\n  return randomNormal(shape, 0, 1, dtype, seed);\n}\nvar randomStandardNormal = op({ randomStandardNormal_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/random_uniform.js\nfunction randomUniform_(shape, minval = 0, maxval = 1, dtype = \"float32\", seed) {\n  const res = buffer(shape, dtype);\n  const random = new UniformRandom(minval, maxval, null, seed);\n  for (let i2 = 0; i2 < res.values.length; i2++) {\n    res.values[i2] = random.nextValue();\n  }\n  return res.toTensor();\n}\nvar randomUniform = op({ randomUniform_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/range.js\nfunction range(start, stop, step5 = 1, dtype = \"float32\") {\n  if (step5 === 0) {\n    throw new Error(\"Cannot have a step of zero\");\n  }\n  const attrs = { start, stop, step: step5, dtype };\n  return ENGINE.runKernel(Range, {}, attrs);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reciprocal.js\nfunction reciprocal_(x) {\n  const $x = convertToTensor(x, \"x\", \"reciprocal\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Reciprocal, inputs);\n}\nvar reciprocal = op({ reciprocal_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/relu.js\nfunction relu_(x) {\n  const $x = convertToTensor(x, \"x\", \"relu\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Relu, inputs);\n}\nvar relu = op({ relu_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/relu6.js\nfunction relu6_(x) {\n  const $x = convertToTensor(x, \"x\", \"relu6\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Relu6, inputs);\n}\nvar relu6 = op({ relu6_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reverse.js\nfunction reverse_(x, axis) {\n  const $x = convertToTensor(x, \"x\", \"reverse\");\n  const inputs = { x: $x };\n  const attrs = { dims: axis };\n  return ENGINE.runKernel(Reverse, inputs, attrs);\n}\nvar reverse = op({ reverse_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reverse_1d.js\nfunction reverse1d_(x) {\n  const $x = convertToTensor(x, \"x\", \"reverse\");\n  assert($x.rank === 1, () => `Error in reverse1D: x must be rank 1 but got rank ${$x.rank}.`);\n  return reverse($x, 0);\n}\nvar reverse1d = op({ reverse1d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reverse_2d.js\nfunction reverse2d_(x, axis) {\n  const $x = convertToTensor(x, \"x\", \"reverse\");\n  assert($x.rank === 2, () => `Error in reverse2D: x must be rank 2 but got rank ${$x.rank}.`);\n  return reverse($x, axis);\n}\nvar reverse2d = op({ reverse2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reverse_3d.js\nfunction reverse3d_(x, axis) {\n  const $x = convertToTensor(x, \"x\", \"reverse\");\n  assert($x.rank === 3, () => `Error in reverse3D: x must be rank 3 but got rank ${$x.rank}.`);\n  return reverse($x, axis);\n}\nvar reverse3d = op({ reverse3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reverse_4d.js\nfunction reverse4d_(x, axis) {\n  const $x = convertToTensor(x, \"x\", \"reverse\");\n  assert($x.rank === 4, () => `Error in reverse4D: x must be rank 4 but got rank ${$x.rank}.`);\n  return reverse($x, axis);\n}\nvar reverse4d = op({ reverse4d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/round.js\nfunction round_(x) {\n  const $x = convertToTensor(x, \"x\", \"round\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Round, inputs);\n}\nvar round2 = op({ round_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/rsqrt.js\nfunction rsqrt_(x) {\n  const $x = convertToTensor(x, \"x\", \"rsqrt\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Rsqrt, inputs);\n}\nvar rsqrt = op({ rsqrt_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/selu.js\nfunction selu_(x) {\n  const $x = convertToTensor(x, \"x\", \"selu\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Selu, inputs);\n}\nvar selu = op({ selu_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/separable_conv2d.js\nfunction separableConv2d_(x, depthwiseFilter, pointwiseFilter, strides, pad3, dilation = [1, 1], dataFormat = \"NHWC\") {\n  const $x = convertToTensor(x, \"x\", \"separableConv2d\");\n  const $depthwiseFilter = convertToTensor(depthwiseFilter, \"depthwiseFilter\", \"separableConv2d\");\n  const $pointwiseFilter = convertToTensor(pointwiseFilter, \"pointwiseFilter\", \"separableConv2d\");\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  if (dataFormat === \"NCHW\") {\n    throw new Error(\"separableConv2d currently does not support dataFormat NCHW; only NHWC is supported\");\n  }\n  assert(x4D.rank === 4, () => `Error in separableConv2d: input must be rank 4, but got rank ${x4D.rank}.`);\n  assert($depthwiseFilter.rank === 4, () => `Error in separableConv2d: depthwise filter must be rank 4, but got rank ${$depthwiseFilter.rank}.`);\n  assert($pointwiseFilter.rank === 4, () => `Error in separableConv2d: pointwise filter must be rank 4, but got rank ${$depthwiseFilter.rank}.`);\n  assert($pointwiseFilter.shape[0] === 1, () => `Error in separableConv2d: the first dimension of pointwise filter  must be 1, but got ${$pointwiseFilter.shape[0]}.`);\n  assert($pointwiseFilter.shape[1] === 1, () => `Error in separableConv2d: the second dimension of pointwise filter must be 1, but got ${$pointwiseFilter.shape[1]}.`);\n  const inChannels = $depthwiseFilter.shape[2];\n  const channelMultiplier = $depthwiseFilter.shape[3];\n  assert($pointwiseFilter.shape[2] === inChannels * channelMultiplier, () => `Error in separableConv2d: the third dimension of pointwise filter must be ${inChannels * channelMultiplier}, but got ${$pointwiseFilter.shape[2]}.`);\n  const depthwise = depthwiseConv2d(x4D, $depthwiseFilter, strides, pad3, dataFormat, dilation);\n  const pointwiseStride = 1;\n  const res = conv2d(depthwise, $pointwiseFilter, pointwiseStride, \"valid\", dataFormat);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar separableConv2d = op({ separableConv2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/setdiff1d_async.js\nasync function setdiff1dAsync_(x, y) {\n  const $x = convertToTensor(x, \"x\", \"setdiff1d\");\n  const $y = convertToTensor(y, \"y\", \"setdiff1d\");\n  assert($x.dtype === $y.dtype, () => `x and y should have the same dtype, but got x (${$x.dtype}) and y (${$y.dtype}).`);\n  assert($x.rank === 1, () => `x should be 1D tensor, but got x (${$x.shape}).`);\n  assert($y.rank === 1, () => `y should be 1D tensor, but got y (${$y.shape}).`);\n  const xVals = await $x.data();\n  const yVals = await $y.data();\n  const ySet = new Set(yVals);\n  let outputSize = 0;\n  for (let i2 = 0; i2 < xVals.length; i2++) {\n    if (!ySet.has(xVals[i2])) {\n      outputSize++;\n    }\n  }\n  const buffer2 = new TensorBuffer([outputSize], $x.dtype);\n  const indices = new TensorBuffer([outputSize], \"int32\");\n  for (let i2 = 0, p2 = 0; i2 < xVals.length; i2++) {\n    if (!ySet.has(xVals[i2])) {\n      buffer2.values[p2] = xVals[i2];\n      indices.values[p2] = i2;\n      p2++;\n    }\n  }\n  return [buffer2.toTensor(), indices.toTensor()];\n}\nvar setdiff1dAsync = setdiff1dAsync_;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sign.js\nfunction sign_(x) {\n  const $x = convertToTensor(x, \"x\", \"sign\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Sign, inputs);\n}\nvar sign = op({ sign_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sin.js\nfunction sin_(x) {\n  const $x = convertToTensor(x, \"x\", \"sin\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Sin, inputs);\n}\nvar sin = op({ sin_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sinh.js\nfunction sinh_(x) {\n  const $x = convertToTensor(x, \"x\", \"sinh\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Sinh, inputs);\n}\nvar sinh = op({ sinh_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/slice1d.js\nfunction slice1d_(x, begin, size) {\n  const $x = convertToTensor(x, \"x\", \"slice1d\");\n  assert($x.rank === 1, () => `slice1d expects a rank-1 tensor, but got a rank-${$x.rank} tensor`);\n  return slice($x, [begin], [size]);\n}\nvar slice1d = op({ slice1d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/slice2d.js\nfunction slice2d_(x, begin, size) {\n  const $x = convertToTensor(x, \"x\", \"slice2d\");\n  assert($x.rank === 2, () => `slice2d expects a rank-2 tensor, but got a rank-${$x.rank} tensor`);\n  return slice($x, begin, size);\n}\nvar slice2d = op({ slice2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/slice3d.js\nfunction slice3d_(x, begin, size) {\n  const $x = convertToTensor(x, \"x\", \"slice3d\");\n  assert($x.rank === 3, () => `slice3d expects a rank-3 tensor, but got a rank-${$x.rank} tensor`);\n  return slice($x, begin, size);\n}\nvar slice3d = op({ slice3d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/slice4d.js\nfunction slice4d_(x, begin, size) {\n  const $x = convertToTensor(x, \"x\", \"slice4d\");\n  assert($x.rank === 4, () => `slice4d expects a rank-4 tensor, but got a rank-${$x.rank} tensor`);\n  return slice($x, begin, size);\n}\nvar slice4d = op({ slice4d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/softmax.js\nfunction softmax_(logits, dim = -1) {\n  const $logits = convertToTensor(logits, \"logits\", \"softmax\", \"float32\");\n  if (dim === -1) {\n    dim = $logits.rank - 1;\n  }\n  if (dim !== $logits.rank - 1) {\n    throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${$logits.rank} and dim was ${dim}`);\n  }\n  const inputs = { logits: $logits };\n  const attrs = { dim };\n  return ENGINE.runKernel(Softmax, inputs, attrs);\n}\nvar softmax = op({ softmax_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/spectral/fft.js\nfunction fft_(input2) {\n  assert(input2.dtype === \"complex64\", () => `The dtype for tf.spectral.fft() must be complex64 but got ${input2.dtype}.`);\n  const inputs = { input: input2 };\n  return ENGINE.runKernel(FFT, inputs);\n}\nvar fft = op({ fft_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/spectral/ifft.js\nfunction ifft_(input2) {\n  assert(input2.dtype === \"complex64\", () => `The dtype for tf.spectral.ifft() must be complex64 but got ${input2.dtype}.`);\n  const inputs = { input: input2 };\n  return ENGINE.runKernel(IFFT, inputs);\n}\nvar ifft = op({ ifft_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/spectral/irfft.js\nfunction irfft_(input2) {\n  const innerDimensionSize = input2.shape[input2.shape.length - 1];\n  const batch = input2.size / innerDimensionSize;\n  let ret;\n  if (innerDimensionSize <= 2) {\n    const complexInput = reshape(input2, [batch, innerDimensionSize]);\n    ret = ifft(complexInput);\n  } else {\n    const outputShape = [batch, 2 * (innerDimensionSize - 1)];\n    const realInput = reshape(real(input2), [batch, innerDimensionSize]);\n    const imagInput = reshape(imag(input2), [batch, innerDimensionSize]);\n    const realConjugate = reverse(slice(realInput, [0, 1], [batch, innerDimensionSize - 2]), 1);\n    const imagConjugate = mul(reverse(slice(imagInput, [0, 1], [batch, innerDimensionSize - 2]), 1), scalar(-1));\n    const r2 = concat([realInput, realConjugate], 1);\n    const i2 = concat([imagInput, imagConjugate], 1);\n    const complexInput = reshape(complex(r2, i2), [outputShape[0], outputShape[1]]);\n    ret = ifft(complexInput);\n  }\n  ret = real(ret);\n  if (input2.rank === 3 && input2.shape[0] !== 0) {\n    const temp = ret;\n    const batch2 = input2.shape[0];\n    ret = reshape(ret, [batch2, ret.shape[0] / batch2, ret.shape[1]]);\n    temp.dispose();\n  }\n  return ret;\n}\nvar irfft = op({ irfft_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/split.js\nfunction split_(x, numOrSizeSplits, axis = 0) {\n  const $x = convertToTensor(x, \"x\", \"split\");\n  const inputs = { x: $x };\n  const attr = { numOrSizeSplits, axis };\n  return ENGINE.runKernel(SplitV, inputs, attr);\n}\nvar split = op({ split_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/spectral/rfft.js\nfunction rfft_(input2, fftLength) {\n  assert(input2.dtype === \"float32\", () => `The dtype for rfft() must be real value but got ${input2.dtype}`);\n  let innerDimensionSize = input2.shape[input2.shape.length - 1];\n  const batch = input2.size / innerDimensionSize;\n  let adjustedInput;\n  if (fftLength != null && fftLength < innerDimensionSize) {\n    const begin = input2.shape.map((v) => 0);\n    const size = input2.shape.map((v) => v);\n    size[input2.shape.length - 1] = fftLength;\n    adjustedInput = slice(input2, begin, size);\n    innerDimensionSize = fftLength;\n  } else if (fftLength != null && fftLength > innerDimensionSize) {\n    const zerosShape = input2.shape.map((v) => v);\n    zerosShape[input2.shape.length - 1] = fftLength - innerDimensionSize;\n    adjustedInput = concat([input2, zeros(zerosShape)], input2.shape.length - 1);\n    innerDimensionSize = fftLength;\n  } else {\n    adjustedInput = input2;\n  }\n  const zerosInput = zerosLike(adjustedInput);\n  const complexInput = reshape(complex(adjustedInput, zerosInput), [batch, innerDimensionSize]);\n  const ret = fft(complexInput);\n  const half = Math.floor(innerDimensionSize / 2) + 1;\n  const realValues = real(ret);\n  const imagValues = imag(ret);\n  const realComplexConjugate = split(realValues, [half, innerDimensionSize - half], realValues.shape.length - 1);\n  const imagComplexConjugate = split(imagValues, [half, innerDimensionSize - half], imagValues.shape.length - 1);\n  const outputShape = adjustedInput.shape.slice();\n  outputShape[adjustedInput.shape.length - 1] = half;\n  return reshape(complex(realComplexConjugate[0], imagComplexConjugate[0]), outputShape);\n}\nvar rfft = op({ rfft_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/squared_difference.js\nfunction squaredDifference_(a, b) {\n  let $a = convertToTensor(a, \"a\", \"squaredDifference\");\n  let $b = convertToTensor(b, \"b\", \"squaredDifference\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  assertAndGetBroadcastShape($a.shape, $b.shape);\n  const inputs = { a: $a, b: $b };\n  const attrs = {};\n  return ENGINE.runKernel(SquaredDifference, inputs, attrs);\n}\nvar squaredDifference = op({ squaredDifference_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/squeeze.js\nfunction squeeze_(x, axis) {\n  const $x = convertToTensor(x, \"x\", \"squeeze\", \"string_or_numeric\");\n  return reshape($x, squeezeShape($x.shape, axis).newShape);\n}\nvar squeeze = op({ squeeze_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/stack.js\nfunction stack_(tensors, axis = 0) {\n  const $tensors = convertToTensorArray(tensors, \"tensors\", \"stack\", \"string_or_numeric\");\n  assert($tensors.length >= 1, () => \"Pass at least one tensor to tf.stack\");\n  if ($tensors.length > 0) {\n    assert(axis <= $tensors[0].rank, () => \"Axis must be <= rank of the tensor\");\n  }\n  const inputs = $tensors;\n  const attrs = { axis };\n  return ENGINE.runKernel(Pack, inputs, attrs);\n}\nvar stack = op({ stack_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/step.js\nfunction step_(x, alpha = 0) {\n  const $x = convertToTensor(x, \"x\", \"step\");\n  const inputs = { x: $x };\n  const attrs = { alpha };\n  return ENGINE.runKernel(Step, inputs, attrs);\n}\nvar step = op({ step_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/strided_slice.js\nfunction stridedSlice_(x, begin, end, strides, beginMask = 0, endMask = 0, ellipsisMask = 0, newAxisMask = 0, shrinkAxisMask = 0) {\n  const $x = convertToTensor(x, \"x\", \"stridedSlice\", \"string_or_numeric\");\n  const inputs = { x: $x };\n  const attrs = {\n    begin,\n    end,\n    strides,\n    beginMask,\n    endMask,\n    ellipsisMask,\n    newAxisMask,\n    shrinkAxisMask\n  };\n  return ENGINE.runKernel(StridedSlice, inputs, attrs);\n}\nvar stridedSlice = op({ stridedSlice_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tan.js\nfunction tan_(x) {\n  const $x = convertToTensor(x, \"x\", \"tan\", \"float32\");\n  const inputs = { x: $x };\n  return ENGINE.runKernel(Tan, inputs);\n}\nvar tan = op({ tan_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor1d.js\nfunction tensor1d(values, dtype) {\n  assertNonNull(values);\n  const inferredShape = inferShape(values, dtype);\n  if (inferredShape.length !== 1) {\n    throw new Error(\"tensor1d() requires values to be a flat/TypedArray\");\n  }\n  const shape = null;\n  return makeTensor(values, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor2d.js\nfunction tensor2d(values, shape, dtype) {\n  assertNonNull(values);\n  if (shape != null && shape.length !== 2) {\n    throw new Error(\"tensor2d() requires shape to have two numbers\");\n  }\n  const inferredShape = inferShape(values, dtype);\n  if (inferredShape.length !== 2 && inferredShape.length !== 1) {\n    throw new Error(\"tensor2d() requires values to be number[][] or flat/TypedArray\");\n  }\n  if (inferredShape.length === 1 && shape == null) {\n    throw new Error(\"tensor2d() requires shape to be provided when `values` are a flat/TypedArray\");\n  }\n  return makeTensor(values, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor4d.js\nfunction tensor4d(values, shape, dtype) {\n  assertNonNull(values);\n  if (shape != null && shape.length !== 4) {\n    throw new Error(\"tensor4d() requires shape to have four numbers\");\n  }\n  const inferredShape = inferShape(values, dtype);\n  if (inferredShape.length !== 4 && inferredShape.length !== 1) {\n    throw new Error(\"tensor4d() requires values to be number[][][][] or flat/TypedArray\");\n  }\n  if (inferredShape.length === 1 && shape == null) {\n    throw new Error(\"tensor4d() requires shape to be provided when `values` are a flat array\");\n  }\n  return makeTensor(values, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor5d.js\nfunction tensor5d(values, shape, dtype) {\n  assertNonNull(values);\n  if (shape != null && shape.length !== 5) {\n    throw new Error(\"tensor5d() requires shape to have five numbers\");\n  }\n  const inferredShape = inferShape(values, dtype);\n  if (inferredShape.length !== 5 && inferredShape.length !== 1) {\n    throw new Error(\"tensor5d() requires values to be number[][][][][] or flat/TypedArray\");\n  }\n  if (inferredShape.length === 1 && shape == null) {\n    throw new Error(\"tensor5d() requires shape to be provided when `values` are a flat array\");\n  }\n  return makeTensor(values, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/tensor6d.js\nfunction tensor6d(values, shape, dtype) {\n  assertNonNull(values);\n  if (shape != null && shape.length !== 6) {\n    throw new Error(\"tensor6d() requires shape to have six numbers\");\n  }\n  const inferredShape = inferShape(values, dtype);\n  if (inferredShape.length !== 6 && inferredShape.length !== 1) {\n    throw new Error(\"tensor6d() requires values to be number[][][][][][] or flat/TypedArray\");\n  }\n  if (inferredShape.length === 1 && shape == null) {\n    throw new Error(\"tensor6d() requires shape to be provided when `values` are a flat array\");\n  }\n  shape = shape || inferredShape;\n  return makeTensor(values, shape, inferredShape, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/topk.js\nfunction topk_(x, k = 1, sorted = true) {\n  const $x = convertToTensor(x, \"x\", \"topk\");\n  if ($x.rank === 0) {\n    throw new Error(\"topk() expects the input to be of rank 1 or higher\");\n  }\n  const lastDim = $x.shape[$x.shape.length - 1];\n  if (k < 0) {\n    throw new Error(`'k' passed to topk() must be >= 0 but got ${k}`);\n  }\n  if (k > lastDim) {\n    throw new Error(`'k' passed to topk() must be <= the last dimension (${lastDim}) but got ${k}`);\n  }\n  const inputs = { x: $x };\n  const attrs = { k, sorted };\n  const [values, indices] = ENGINE.runKernel(TopK, inputs, attrs);\n  return { values, indices };\n}\nvar topk = op({ topk_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/truncated_normal.js\nfunction truncatedNormal_(shape, mean5 = 0, stdDev = 1, dtype, seed) {\n  if (dtype != null && dtype === \"bool\") {\n    throw new Error(`Unsupported data type $ { dtype }`);\n  }\n  const randGauss = new MPRandGauss(mean5, stdDev, dtype, true, seed);\n  const res = buffer(shape, dtype);\n  for (let i2 = 0; i2 < res.values.length; i2++) {\n    res.values[i2] = randGauss.nextValue();\n  }\n  return res.toTensor();\n}\nvar truncatedNormal = op({ truncatedNormal_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/unique.js\nfunction unique_(x, axis = 0) {\n  const $x = convertToTensor(x, \"x\", \"unique\", \"string_or_numeric\");\n  assert($x.rank > 0, () => \"The input tensor must be at least 1D\");\n  const inputs = { x: $x };\n  const attrs = { axis };\n  const [values, indices] = ENGINE.runKernel(Unique, inputs, attrs);\n  return { values, indices };\n}\nvar unique = op({ unique_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/unsorted_segment_sum.js\nfunction unsortedSegmentSum_(x, segmentIds, numSegments) {\n  const $x = convertToTensor(x, \"x\", \"unsortedSegmentSum\");\n  const $segmentIds = convertToTensor(segmentIds, \"segmentIds\", \"unsortedSegmentSum\", \"int32\");\n  assert(isInt(numSegments), () => \"numSegments must be of dtype int\");\n  const inputs = { x: $x, segmentIds: $segmentIds };\n  const attrs = { numSegments };\n  return ENGINE.runKernel(UnsortedSegmentSum, inputs, attrs);\n}\nvar unsortedSegmentSum = op({ unsortedSegmentSum_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/unstack.js\nfunction unstack_(x, axis = 0) {\n  const $x = convertToTensor(x, \"x\", \"unstack\", \"string_or_numeric\");\n  assert(axis >= -$x.shape.length && axis < $x.shape.length, () => `Axis = ${axis} is not in [-${$x.shape.length}, ${$x.shape.length})`);\n  const inputs = { value: $x };\n  const attrs = { axis };\n  return ENGINE.runKernel(Unpack, inputs, attrs);\n}\nvar unstack = op({ unstack_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/upper_bound.js\nfunction upperBound(sortedSequence, values) {\n  return searchSorted(sortedSequence, values, \"right\");\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/variable.js\nfunction variable(initialValue, trainable = true, name, dtype) {\n  return ENGINE.makeVariable(initialValue, trainable, name, dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/where_impl.js\nfunction whereImpl(condShape, condVals) {\n  const indices = [];\n  for (let i2 = 0; i2 < condVals.length; i2++) {\n    if (condVals[i2]) {\n      indices.push(i2);\n    }\n  }\n  const inBuffer = buffer(condShape, \"int32\");\n  const out = buffer([indices.length, condShape.length], \"int32\");\n  for (let i2 = 0; i2 < indices.length; i2++) {\n    const loc = inBuffer.indexToLoc(indices[i2]);\n    const offset = i2 * condShape.length;\n    out.values.set(loc, offset);\n  }\n  return out.toTensor();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/where_async.js\nasync function whereAsync_(condition) {\n  const $condition = convertToTensor(condition, \"condition\", \"whereAsync\", \"bool\");\n  const vals = await $condition.data();\n  const res = whereImpl($condition.shape, vals);\n  if (condition !== $condition) {\n    $condition.dispose();\n  }\n  return res;\n}\nvar whereAsync = whereAsync_;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/boolean_mask.js\nasync function booleanMaskAsync_(tensor2, mask, axis) {\n  const $tensor = convertToTensor(tensor2, \"tensor\", \"boolMask\");\n  const $mask = convertToTensor(mask, \"mask\", \"boolMask\", \"bool\");\n  const axisFrom = axis == null ? 0 : axis;\n  const maskDim = $mask.rank;\n  const tensorShape = $tensor.shape;\n  assert(maskDim > 0, () => \"mask cannot be scalar\");\n  assertShapesMatch(tensorShape.slice(axisFrom, axisFrom + maskDim), $mask.shape, `mask's shape must match the first K dimensions of tensor's shape,`);\n  let leadingSize = 1;\n  for (let i2 = axisFrom; i2 < axisFrom + maskDim; i2++) {\n    leadingSize *= tensorShape[i2];\n  }\n  const targetTensorShape = tensorShape.slice(0, axisFrom).concat([leadingSize], tensorShape.slice(axisFrom + maskDim));\n  const reshapedTensor = reshape($tensor, targetTensorShape);\n  const reshapedMask = reshape($mask, [-1]);\n  const positivePositions = await whereAsync(reshapedMask);\n  const indices = squeeze(positivePositions, [1]);\n  const res = gather(reshapedTensor, indices, axisFrom);\n  if (tensor2 !== $tensor) {\n    $tensor.dispose();\n  }\n  if (mask !== $mask) {\n    $mask.dispose();\n  }\n  indices.dispose();\n  reshapedTensor.dispose();\n  reshapedMask.dispose();\n  positivePositions.dispose();\n  return res;\n}\nvar booleanMaskAsync = booleanMaskAsync_;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/moving_average.js\nfunction movingAverage_(v, x, decay, step5, zeroDebias = true) {\n  const $v = convertToTensor(v, \"v\", \"movingAverage\");\n  const $x = convertToTensor(x, \"x\", \"movingAverage\");\n  const $decay = convertToTensor(decay, \"decay\", \"movingAverage\");\n  assertTypesMatch($v, $x);\n  assert(arraysEqual($v.shape, $x.shape), () => \"Shape mismatch in v and x\");\n  const one = scalar(1);\n  const oneMinusDecay = sub(one, $decay);\n  let update = mul(sub($x, $v), oneMinusDecay);\n  if (zeroDebias) {\n    assert(step5 != null, () => \"When using zeroDebias: true, step is required.\");\n    const $step = convertToTensor(step5, \"step\", \"movingAverage\");\n    update = div(update, sub(one, pow($decay, $step)));\n  }\n  return add2($v, update);\n}\nvar movingAverage = op({ movingAverage_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/scatter_nd.js\nfunction scatterND_(indices, updates, shape) {\n  const $indices = convertToTensor(indices, \"indices\", \"scatterND\", \"int32\");\n  const $updates = convertToTensor(updates, \"updates\", \"scatterND\");\n  validateInput($updates, $indices, shape);\n  const inputs = { indices: $indices, updates: $updates };\n  const attrs = { shape };\n  return ENGINE.runKernel(ScatterNd, inputs, attrs);\n}\nvar scatterND = op({ scatterND_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse_to_dense_util.js\nfunction validateInput2(sparseIndices, sparseValues, outputShape, defaultValues) {\n  if (sparseIndices.dtype !== \"int32\") {\n    throw new Error(`tf.sparseToDense() expects the indices to be int32 type, but the dtype was ${sparseIndices.dtype}.`);\n  }\n  if (sparseIndices.rank > 2) {\n    throw new Error(`sparseIndices should be a scalar, vector, or matrix, but got shape ${sparseIndices.shape}.`);\n  }\n  const numElems = sparseIndices.rank > 0 ? sparseIndices.shape[0] : 1;\n  const numDims = sparseIndices.rank > 1 ? sparseIndices.shape[1] : 1;\n  if (outputShape.length !== numDims) {\n    throw new Error(`outputShape has incorrect number of elements:, ${outputShape.length}, should be: ${numDims}.`);\n  }\n  const numValues = sparseValues.size;\n  if (!(sparseValues.rank === 0 || sparseValues.rank === 1 && numValues === numElems)) {\n    throw new Error(`sparseValues has incorrect shape ${sparseValues.shape}, should be [] or [${numElems}]`);\n  }\n  if (sparseValues.dtype !== defaultValues.dtype) {\n    throw new Error(\"sparseValues.dtype must match defaultValues.dtype\");\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse_to_dense.js\nfunction sparseToDense_(sparseIndices, sparseValues, outputShape, defaultValue = 0) {\n  const $sparseIndices = convertToTensor(sparseIndices, \"sparseIndices\", \"sparseToDense\", \"int32\");\n  const $sparseValues = convertToTensor(sparseValues, \"sparseValues\", \"sparseToDense\", \"string_or_numeric\");\n  const $defaultValue = convertToTensor(defaultValue, \"defaultValue\", \"sparseToDense\", $sparseValues.dtype);\n  validateInput2($sparseIndices, $sparseValues, outputShape, $defaultValue);\n  const inputs = {\n    sparseIndices: $sparseIndices,\n    sparseValues: $sparseValues,\n    defaultValue: $defaultValue\n  };\n  const attrs = { outputShape };\n  return ENGINE.runKernel(SparseToDense, inputs, attrs);\n}\nvar sparseToDense = op({ sparseToDense_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/gather_nd.js\nfunction gatherND_(x, indices) {\n  const $indices = convertToTensor(indices, \"indices\", \"gatherND\", \"int32\");\n  const $x = convertToTensor(x, \"x\", \"gatherND\", \"string_or_numeric\");\n  const inputs = { params: $x, indices: $indices };\n  return ENGINE.runKernel(GatherNd, inputs);\n}\nvar gatherND = op({ gatherND_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/dropout_util.js\nfunction getNoiseShape(x, noiseShape) {\n  if (noiseShape == null) {\n    return x.shape.slice();\n  }\n  if (arraysEqual(x.shape, noiseShape)) {\n    return noiseShape;\n  }\n  if (x.shape.length === noiseShape.length) {\n    const newDimension = [];\n    for (let i2 = 0; i2 < x.shape.length; i2++) {\n      if (noiseShape[i2] == null && x.shape[i2] != null) {\n        newDimension.push(x.shape[i2]);\n      } else {\n        newDimension.push(noiseShape[i2]);\n      }\n    }\n    return newDimension;\n  }\n  return noiseShape;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/dropout.js\nfunction dropout_(x, rate, noiseShape, seed) {\n  const $x = convertToTensor(x, \"x\", \"dropout\");\n  assert($x.dtype === \"float32\", () => `x has to be a floating point tensor since it's going to be scaled, but got a ${$x.dtype} tensor instead.`);\n  assert(rate >= 0 && rate < 1, () => `rate must be a float in the range [0, 1), but got ${rate}.`);\n  if (rate === 0) {\n    return x instanceof Tensor ? $x.clone() : $x;\n  }\n  const $noiseShape = getNoiseShape($x, noiseShape);\n  const keepProb = 1 - rate;\n  const multiplier = div(floor(add2(randomUniform($noiseShape, 0, 1, \"float32\", seed), keepProb)), keepProb);\n  return mul($x, multiplier);\n}\nvar dropout = op({ dropout_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/signal_ops_util.js\nfunction enclosingPowerOfTwo(value) {\n  return Math.floor(Math.pow(2, Math.ceil(Math.log(value) / Math.log(2))));\n}\nfunction cosineWindow(windowLength, a, b) {\n  const even = 1 - windowLength % 2;\n  const newValues = new Float32Array(windowLength);\n  for (let i2 = 0; i2 < windowLength; ++i2) {\n    const cosArg = 2 * Math.PI * i2 / (windowLength + even - 1);\n    newValues[i2] = a - b * Math.cos(cosArg);\n  }\n  return tensor1d(newValues, \"float32\");\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/in_top_k.js\nasync function inTopKAsync_(predictions, targets, k = 1) {\n  const $predictions = convertToTensor(predictions, \"predictions\", \"inTopK\");\n  const $targets = convertToTensor(targets, \"targets\", \"inTopK\");\n  assert($predictions.rank > 1, () => `inTopK() expects the predictions to be of rank 2 or higher, but got ${$predictions.rank}`);\n  assert($predictions.rank - 1 === $targets.rank, () => `predictions rank should be 1 larger than targets rank, but got predictions rank ${$predictions.rank} and targets rank ${$targets.rank}`);\n  assertShapesMatch($predictions.shape.slice(0, $predictions.shape.length - 1), $targets.shape, `predictions's shape should be align with the targets' shape, except the last dimension.`);\n  const lastDim = $predictions.shape[$predictions.shape.length - 1];\n  assert(k > 0 && k <= lastDim, () => `'k' passed to inTopK() must be > 0 && <= the predictions last dimension (${lastDim}), but got ${k}`);\n  const predictionsVals = await $predictions.data();\n  const targetsVals = await $targets.data();\n  const [batch, size] = [predictionsVals.length / lastDim, lastDim];\n  const precision3 = getTypedArrayFromDType(\"bool\", batch);\n  for (let b = 0; b < batch; b++) {\n    const offset = b * size;\n    const vals = predictionsVals.subarray(offset, offset + size);\n    const valAndInd = [];\n    for (let i2 = 0; i2 < vals.length; i2++) {\n      valAndInd.push({ value: vals[i2], index: i2 });\n    }\n    valAndInd.sort((a, b2) => b2.value - a.value);\n    precision3[b] = 0;\n    for (let i2 = 0; i2 < k; i2++) {\n      if (valAndInd[i2].index === targetsVals[b]) {\n        precision3[b] = 1;\n        break;\n      }\n    }\n  }\n  if (predictions !== $predictions) {\n    $predictions.dispose();\n  }\n  if (targets !== $targets) {\n    $targets.dispose();\n  }\n  return tensor(precision3, $targets.shape, \"bool\");\n}\nvar inTopKAsync = inTopKAsync_;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/fused_ops.js\nvar fused_ops_exports = {};\n__export(fused_ops_exports, {\n  conv2d: () => conv2d2,\n  depthwiseConv2d: () => depthwiseConv2d2,\n  matMul: () => matMul2\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv2d_backprop_filter.js\nfunction conv2DBackpropFilter_(x, dy, filterShape, strides, pad3, dataFormat = \"NHWC\", dimRoundingMode) {\n  let x4D = x;\n  if (x.rank === 3) {\n    x4D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2]]);\n  }\n  let dy4D = dy;\n  if (dy4D.rank === 3) {\n    dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);\n  }\n  assert(x4D.rank === 4, () => `Error in conv2dDerFilter: input must be rank 4, but got shape ${x4D.shape}.`);\n  assert(dy4D.rank === 4, () => `Error in conv2dDerFilter: dy must be rank 4, but got shape ${dy4D.shape}.`);\n  assert(filterShape.length === 4, () => `Error in conv2dDerFilter: filterShape must be length 4, but got ${filterShape}.`);\n  const inDepth = dataFormat === \"NHWC\" ? x4D.shape[3] : x4D.shape[1];\n  const outDepth = dataFormat === \"NHWC\" ? dy4D.shape[3] : dy4D.shape[1];\n  assert(inDepth === filterShape[2], () => `Error in conv2dDerFilter: depth of input ${inDepth}) must match input depth in filter (${filterShape[2]}.`);\n  assert(outDepth === filterShape[3], () => `Error in conv2dDerFilter: depth of dy (${outDepth}) must match output depth for filter (${filterShape[3]}).`);\n  checkPadOnDimRoundingMode(\"conv2dDerFilter\", pad3, dimRoundingMode);\n  const inputs = { x: x4D, dy: dy4D };\n  const attrs = { strides, pad: pad3, dataFormat, dimRoundingMode, filterShape };\n  return ENGINE.runKernel(Conv2DBackpropFilter, inputs, attrs);\n}\nvar conv2DBackpropFilter = op({ conv2DBackpropFilter_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/fused_util.js\nfunction getFusedDyActivation(dy, y, activation2) {\n  if (activation2 == null || activation2 === \"linear\") {\n    return dy;\n  }\n  if (activation2 === \"relu\") {\n    return mul(dy, step(y));\n  }\n  throw new Error(`Cannot compute gradient for fused activation ${activation2}.`);\n}\nfunction getFusedBiasGradient(bias, dyActivation) {\n  let res = dyActivation;\n  const reduceAxes = getReductionAxes(bias.shape, dyActivation.shape);\n  if (reduceAxes.length > 0) {\n    res = sum2(res, reduceAxes);\n  }\n  return reshape(res, bias.shape);\n}\nfunction applyActivation(x, activation2, preluActivationWeights, leakyreluAlpha) {\n  if (activation2 === \"linear\") {\n    return x;\n  } else if (activation2 === \"relu\") {\n    return relu(x);\n  } else if (activation2 === \"elu\") {\n    return elu(x);\n  } else if (activation2 === \"relu6\") {\n    return relu6(x);\n  } else if (activation2 === \"prelu\") {\n    return prelu(x, preluActivationWeights);\n  } else if (activation2 === \"leakyrelu\") {\n    return leakyRelu(x, leakyreluAlpha);\n  } else if (activation2 === \"sigmoid\") {\n    return sigmoid(x);\n  }\n  throw new Error(`Unknown fused activation ${activation2}.`);\n}\nvar shouldFuse = (gradientDepth, activation2) => {\n  const gradientMode = gradientDepth > 0;\n  return !gradientMode || activation2 === \"linear\";\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/fused/conv2d.js\nfunction fusedConv2d_({ x, filter, strides, pad: pad3, dataFormat = \"NHWC\", dilations = [1, 1], dimRoundingMode, bias, activation: activation2 = \"linear\", preluActivationWeights, leakyreluAlpha }) {\n  activation2 = activation2 || \"linear\";\n  if (shouldFuse(ENGINE.state.gradientDepth, activation2) === false) {\n    assert(dataFormat === \"NHWC\", () => `Error in fused conv2d: got dataFormat of ${dataFormat} but only NHWC is currently supported for the case of gradient depth is 0 and the activation is not linear.`);\n    let result = conv2d(x, filter, strides, pad3, dataFormat, dilations, dimRoundingMode);\n    if (bias != null) {\n      result = add2(result, bias);\n    }\n    return applyActivation(result, activation2, preluActivationWeights, leakyreluAlpha);\n  }\n  const $x = convertToTensor(x, \"x\", \"conv2d\", \"float32\");\n  const $filter = convertToTensor(filter, \"filter\", \"conv2d\", \"float32\");\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  assert(x4D.rank === 4, () => `Error in fused conv2d: input must be rank 4, but got rank ${x4D.rank}.`);\n  assert($filter.rank === 4, () => `Error in fused conv2d: filter must be rank 4, but got rank ${$filter.rank}.`);\n  checkPadOnDimRoundingMode(\"fused conv2d\", pad3, dimRoundingMode);\n  const inputChannels = dataFormat === \"NHWC\" ? x4D.shape[3] : x4D.shape[1];\n  assert($filter.shape[2] === inputChannels, () => `Error in conv2d: depth of input (${inputChannels}) must match input depth for filter ${$filter.shape[2]}.`);\n  assert(eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in conv2D: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  const convInfo = computeConv2DInfo(x4D.shape, $filter.shape, strides, dilations, pad3, dimRoundingMode);\n  let $bias;\n  if (bias != null) {\n    $bias = convertToTensor(bias, \"bias\", \"fused conv2d\");\n    [$bias] = makeTypesMatch($bias, $x);\n    if (dataFormat === \"NHWC\") {\n      assertAndGetBroadcastShape(convInfo.outShape, $bias.shape);\n    } else {\n      assert($bias.shape.length <= 1, () => `Error in fused conv2d: only supports scalar or 1-D Tensor bias for NCHW format but got the bias of rank-${$bias.shape.length}.`);\n      assert($bias.shape.length === 0 || $bias.shape[0] === convInfo.outChannels || $bias.shape[0] === 1, () => `Error in fused conv2d: bias shape (${$bias.shape}) is not compatible with the number of output channels (${convInfo.outChannels})`);\n    }\n  }\n  let $preluActivationWeights;\n  if (preluActivationWeights != null) {\n    const alphaShape = preluActivationWeights.shape;\n    assert(alphaShape.length <= 1 || alphaShape.length === 3, () => `Error in fused conv2d: only supports scalar, 1-D Tensor or 3-D Tensor PReLU activation weights but got a tensor of rank-${alphaShape.length}.`);\n    if (alphaShape.length === 1) {\n      assert(alphaShape[0] === 1 || alphaShape[0] === convInfo.outChannels, () => `Error in fused conv2d: PReLU activation weights (${alphaShape}) is not compatible with the number of output channels (${convInfo.outChannels}).`);\n    } else if (alphaShape.length === 3) {\n      try {\n        assertAndGetBroadcastShape(alphaShape, convInfo.outShape);\n      } catch (e2) {\n        const errMsg = `Error in fused conv2d: PReLU activation weights (${alphaShape}) is not compatible with the output shape of the conv2d (${convInfo.outShape}).`;\n        throw Error(errMsg);\n      }\n    }\n    $preluActivationWeights = convertToTensor(preluActivationWeights, \"prelu weights\", \"fused conv2d\");\n  }\n  const grad2 = (dy, saved) => {\n    assert(dataFormat === \"NHWC\", () => `Error in gradient of fused conv2D: got dataFormat of ${dataFormat} but only NHWC is currently supported.`);\n    const [$filter2, x4D2, y, $bias2] = saved;\n    const dyActivation = getFusedDyActivation(dy, y, activation2);\n    assert(tupleValuesAreOne(dilations), () => `Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${dilations}'`);\n    const xDer = conv2DBackpropInput(x4D2.shape, dyActivation, $filter2, strides, pad3);\n    const filterDer = conv2DBackpropFilter(x4D2, dyActivation, $filter2.shape, strides, pad3);\n    const der = [xDer, filterDer];\n    if ($bias2 != null) {\n      const biasDer = getFusedBiasGradient($bias2, dyActivation);\n      der.push(biasDer);\n    }\n    return der;\n  };\n  const inputs = {\n    x: x4D,\n    filter: $filter,\n    bias: $bias,\n    preluActivationWeights: $preluActivationWeights\n  };\n  const attrs = {\n    strides,\n    pad: pad3,\n    dataFormat,\n    dilations,\n    dimRoundingMode,\n    activation: activation2,\n    leakyreluAlpha\n  };\n  if (bias == null) {\n    const customOp = customGrad((x4D2, filter2, save) => {\n      let res = ENGINE.runKernel(FusedConv2D, inputs, attrs);\n      save([filter2, x4D2, res]);\n      if (reshapedTo4D) {\n        res = reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n      }\n      return { value: res, gradFunc: grad2 };\n    });\n    return customOp(x4D, $filter);\n  } else {\n    const customOpWithBias = customGrad((x4D2, filter2, bias2, save) => {\n      let res = ENGINE.runKernel(FusedConv2D, inputs, attrs);\n      save([filter2, x4D2, res, bias2]);\n      if (reshapedTo4D) {\n        res = reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n      }\n      return { value: res, gradFunc: grad2 };\n    });\n    return customOpWithBias(x4D, $filter, $bias);\n  }\n}\nvar conv2d2 = op({ fusedConv2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/depthwise_conv2d_native_backprop_filter.js\nfunction depthwiseConv2dNativeBackpropFilter_(x, dy, filterShape, strides, pad3, dilations = [1, 1], dimRoundingMode) {\n  let x4D = x;\n  if (x.rank === 3) {\n    x4D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2]]);\n  }\n  let dy4D = dy;\n  if (dy4D.rank === 3) {\n    dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);\n  }\n  const inputs = { x: x4D, dy: dy4D };\n  const attrs = { strides, pad: pad3, dimRoundingMode, dilations, filterShape };\n  return ENGINE.runKernel(DepthwiseConv2dNativeBackpropFilter, inputs, attrs);\n}\nvar depthwiseConv2dNativeBackpropFilter = op({ depthwiseConv2dNativeBackpropFilter_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/depthwise_conv2d_native_backprop_input.js\nfunction depthwiseConv2dNativeBackpropInput_(xShape, dy, filter, strides, pad3, dilations = [1, 1], dimRoundingMode) {\n  let dy4D = dy;\n  let reshapedTo4D = false;\n  if (dy.rank === 3) {\n    reshapedTo4D = true;\n    dy4D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2]]);\n  }\n  const inputs = { dy: dy4D, filter };\n  const attrs = { strides, pad: pad3, dimRoundingMode, dilations, inputShape: xShape };\n  const res = ENGINE.runKernel(DepthwiseConv2dNativeBackpropInput, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar depthwiseConv2dNativeBackpropInput = op({ depthwiseConv2dNativeBackpropInput_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/fused/depthwise_conv2d.js\nfunction fusedDepthwiseConv2d_({ x, filter, strides, pad: pad3, dataFormat = \"NHWC\", dilations = [1, 1], dimRoundingMode, bias, activation: activation2 = \"linear\", preluActivationWeights, leakyreluAlpha }) {\n  if (shouldFuse(ENGINE.state.gradientDepth, activation2) === false) {\n    let result = depthwiseConv2d(x, filter, strides, pad3, dataFormat, dilations, dimRoundingMode);\n    if (bias != null) {\n      result = add2(result, bias);\n    }\n    return applyActivation(result, activation2, preluActivationWeights, leakyreluAlpha);\n  }\n  const $x = convertToTensor(x, \"x\", \"depthwiseConv2d\", \"float32\");\n  const $filter = convertToTensor(filter, \"filter\", \"depthwiseConv2d\", \"float32\");\n  let x4D = $x;\n  let reshapedTo4D = false;\n  if ($x.rank === 3) {\n    reshapedTo4D = true;\n    x4D = reshape($x, [1, $x.shape[0], $x.shape[1], $x.shape[2]]);\n  }\n  assert(x4D.rank === 4, () => `Error in fused depthwiseConv2d: input must be rank 4, but got rank ${x4D.rank}.`);\n  assert($filter.rank === 4, () => `Error in fused depthwiseConv2d: filter must be rank 4, but got rank ${$filter.rank}.`);\n  assert(x4D.shape[3] === $filter.shape[2], () => `Error in fused depthwiseConv2d: number of input channels (${x4D.shape[3]}) must match the inChannels dimension in filter ${$filter.shape[2]}.`);\n  if (dilations == null) {\n    dilations = [1, 1];\n  }\n  assert(eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in fused depthwiseConv2d: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  checkPadOnDimRoundingMode(\"fused depthwiseConv2d\", pad3, dimRoundingMode);\n  const convInfo = computeConv2DInfo(x4D.shape, $filter.shape, strides, dilations, pad3, dimRoundingMode, true);\n  let $bias;\n  if (bias != null) {\n    $bias = convertToTensor(bias, \"bias\", \"fused conv2d\");\n    [$bias] = makeTypesMatch($bias, $x);\n    assertAndGetBroadcastShape(convInfo.outShape, $bias.shape);\n  }\n  let $preluActivationWeights;\n  if (preluActivationWeights != null) {\n    $preluActivationWeights = convertToTensor(preluActivationWeights, \"prelu weights\", \"fused depthwiseConv2d\");\n  }\n  const grad2 = (dy, saved) => {\n    assert(tupleValuesAreOne(dilations), () => `Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '${dilations}'`);\n    const [$filter2, x4D2, y, bias2] = saved;\n    const dyActivation = getFusedDyActivation(dy, y, activation2);\n    const xDer = depthwiseConv2dNativeBackpropInput(x4D2.shape, dyActivation, $filter2, strides, pad3, dilations, dimRoundingMode);\n    const filterDer = depthwiseConv2dNativeBackpropFilter(x4D2, dyActivation, $filter2.shape, strides, pad3, dilations, dimRoundingMode);\n    if (bias2 != null) {\n      const biasDer = getFusedBiasGradient($bias, dyActivation);\n      return [xDer, filterDer, biasDer];\n    }\n    return [xDer, filterDer];\n  };\n  const inputs = {\n    x: x4D,\n    filter: $filter,\n    bias: $bias,\n    preluActivationWeights: $preluActivationWeights\n  };\n  const attrs = {\n    strides,\n    pad: pad3,\n    dataFormat,\n    dilations,\n    dimRoundingMode,\n    activation: activation2,\n    leakyreluAlpha\n  };\n  if (bias == null) {\n    const customOp = customGrad((x4D2, filter2, save) => {\n      let res = ENGINE.runKernel(FusedDepthwiseConv2D, inputs, attrs);\n      save([filter2, x4D2, res]);\n      if (reshapedTo4D) {\n        res = reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n      }\n      return { value: res, gradFunc: grad2 };\n    });\n    return customOp(x4D, $filter);\n  } else {\n    const customOpWithBias = customGrad((x4D2, filter2, bias2, save) => {\n      let res = ENGINE.runKernel(FusedDepthwiseConv2D, inputs, attrs);\n      save([filter2, x4D2, res, bias2]);\n      if (reshapedTo4D) {\n        res = reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n      }\n      return { value: res, gradFunc: grad2 };\n    });\n    return customOpWithBias(x4D, $filter, $bias);\n  }\n}\nvar depthwiseConv2d2 = op({ fusedDepthwiseConv2d_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/fused/mat_mul.js\nfunction fusedMatMul_({ a, b, transposeA = false, transposeB = false, bias, activation: activation2 = \"linear\", preluActivationWeights, leakyreluAlpha = 0.2 }) {\n  if (shouldFuse(ENGINE.state.gradientDepth, activation2) === false) {\n    let result = matMul(a, b, transposeA, transposeB);\n    if (bias != null) {\n      result = add2(result, bias);\n    }\n    return applyActivation(result, activation2, preluActivationWeights, leakyreluAlpha);\n  }\n  let $a = convertToTensor(a, \"a\", \"fused matMul\");\n  let $b = convertToTensor(b, \"b\", \"fused matMul\");\n  [$a, $b] = makeTypesMatch($a, $b);\n  const innerShapeA = transposeA ? $a.shape[$a.rank - 2] : $a.shape[$a.rank - 1];\n  const innerShapeB = transposeB ? $b.shape[$b.rank - 1] : $b.shape[$b.rank - 2];\n  const outerShapeA = transposeA ? $a.shape[$a.rank - 1] : $a.shape[$a.rank - 2];\n  const outerShapeB = transposeB ? $b.shape[$b.rank - 2] : $b.shape[$b.rank - 1];\n  const outerDimsA = $a.shape.slice(0, -2);\n  const outerDimsB = $b.shape.slice(0, -2);\n  const batchDimA = sizeFromShape(outerDimsA);\n  const batchDimB = sizeFromShape(outerDimsB);\n  assert(innerShapeA === innerShapeB, () => `Error in fused matMul: inner shapes (${innerShapeA}) and (${innerShapeB}) of Tensors with shapes ${$a.shape} and ${$b.shape} and transposeA=${transposeA} and transposeB=${transposeB} must match.`);\n  const outShapeOuterDims = assertAndGetBroadcastShape($a.shape.slice(0, -2), $b.shape.slice(0, -2));\n  const outShape = outShapeOuterDims.concat([outerShapeA, outerShapeB]);\n  const a3D = transposeA ? reshape($a, [batchDimA, innerShapeA, outerShapeA]) : reshape($a, [batchDimA, outerShapeA, innerShapeA]);\n  const b3D = transposeB ? reshape($b, [batchDimB, outerShapeB, innerShapeB]) : reshape($b, [batchDimB, innerShapeB, outerShapeB]);\n  let $bias;\n  if (bias != null) {\n    $bias = convertToTensor(bias, \"bias\", \"fused matMul\");\n    [$bias] = makeTypesMatch($bias, $a);\n    assertAndGetBroadcastShape(outShape, $bias.shape);\n  }\n  let $preluActivationWeights;\n  if (preluActivationWeights != null) {\n    $preluActivationWeights = convertToTensor(preluActivationWeights, \"prelu weights\", \"fused matMul\");\n  }\n  const grad2 = (dy, saved) => {\n    const [a3D2, b3D2, y, $bias2] = saved;\n    const dyActivation = getFusedDyActivation(reshape(dy, y.shape), y, activation2);\n    let aDer;\n    let bDer;\n    if (!transposeA && !transposeB) {\n      aDer = matMul(dyActivation, b3D2, false, true);\n      bDer = matMul(a3D2, dyActivation, true, false);\n    } else if (!transposeA && transposeB) {\n      aDer = matMul(dyActivation, b3D2, false, false);\n      bDer = matMul(dyActivation, a3D2, true, false);\n    } else if (transposeA && !transposeB) {\n      aDer = matMul(b3D2, dyActivation, false, true);\n      bDer = matMul(a3D2, dyActivation, false, false);\n    } else {\n      aDer = matMul(b3D2, dyActivation, true, true);\n      bDer = matMul(dyActivation, a3D2, true, true);\n    }\n    if (bias != null) {\n      const biasDer = getFusedBiasGradient($bias2, dyActivation);\n      return [aDer, bDer, biasDer];\n    } else {\n      return [aDer, bDer];\n    }\n  };\n  const inputs = {\n    a: a3D,\n    b: b3D,\n    bias: $bias,\n    preluActivationWeights: $preluActivationWeights\n  };\n  const attrs = { transposeA, transposeB, activation: activation2, leakyreluAlpha };\n  if (bias == null) {\n    const customOp = customGrad((a3D2, b3D2, save) => {\n      const res = ENGINE.runKernel(_FusedMatMul, inputs, attrs);\n      save([a3D2, b3D2, res]);\n      return { value: reshape(res, outShape), gradFunc: grad2 };\n    });\n    return customOp(a3D, b3D);\n  } else {\n    const customOpWithBias = customGrad((a3D2, b3D2, $bias2, save) => {\n      const res = ENGINE.runKernel(_FusedMatMul, inputs, attrs);\n      save([a3D2, b3D2, res, $bias2]);\n      return { value: reshape(res, outShape), gradFunc: grad2 };\n    });\n    return customOpWithBias(a3D, b3D, $bias);\n  }\n}\nvar matMul2 = op({ fusedMatMul_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/signal/hamming_window.js\nfunction hammingWindow_(windowLength) {\n  return cosineWindow(windowLength, 0.54, 0.46);\n}\nvar hammingWindow = op({ hammingWindow_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/signal/hann_window.js\nfunction hannWindow_(windowLength) {\n  return cosineWindow(windowLength, 0.5, 0.5);\n}\nvar hannWindow = op({ hannWindow_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/signal/frame.js\nfunction frame_(signal2, frameLength, frameStep, padEnd = false, padValue = 0) {\n  let start = 0;\n  const output = [];\n  while (start + frameLength <= signal2.size) {\n    output.push(slice(signal2, start, frameLength));\n    start += frameStep;\n  }\n  if (padEnd) {\n    while (start < signal2.size) {\n      const padLen = start + frameLength - signal2.size;\n      const pad3 = concat([\n        slice(signal2, start, frameLength - padLen),\n        fill([padLen], padValue)\n      ]);\n      output.push(pad3);\n      start += frameStep;\n    }\n  }\n  if (output.length === 0) {\n    return tensor2d([], [0, frameLength]);\n  }\n  return reshape(concat(output), [output.length, frameLength]);\n}\nvar frame = op({ frame_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/signal/stft.js\nfunction stft_(signal2, frameLength, frameStep, fftLength, windowFn = hannWindow) {\n  if (fftLength == null) {\n    fftLength = enclosingPowerOfTwo(frameLength);\n  }\n  const framedSignal = frame(signal2, frameLength, frameStep);\n  const windowedSignal = mul(framedSignal, windowFn(frameLength));\n  return rfft(windowedSignal, fftLength);\n}\nvar stft = op({ stft_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/crop_and_resize.js\nfunction cropAndResize_(image2, boxes, boxInd, cropSize, method = \"bilinear\", extrapolationValue = 0) {\n  const $image = convertToTensor(image2, \"image\", \"cropAndResize\");\n  const $boxes = convertToTensor(boxes, \"boxes\", \"cropAndResize\", \"float32\");\n  const $boxInd = convertToTensor(boxInd, \"boxInd\", \"cropAndResize\", \"int32\");\n  const numBoxes = $boxes.shape[0];\n  assert($image.rank === 4, () => `Error in cropAndResize: image must be rank 4,but got rank ${$image.rank}.`);\n  assert($boxes.rank === 2 && $boxes.shape[1] === 4, () => `Error in cropAndResize: boxes must be have size [${numBoxes},4] but had shape ${$boxes.shape}.`);\n  assert($boxInd.rank === 1 && $boxInd.shape[0] === numBoxes, () => `Error in cropAndResize: boxInd must be have size [${numBoxes}] but had shape ${$boxes.shape}.`);\n  assert(cropSize.length === 2, () => `Error in cropAndResize: cropSize must be of length 2, but got length ${cropSize.length}.`);\n  assert(cropSize[0] >= 1 && cropSize[1] >= 1, () => `cropSize must be atleast [1,1], but was ${cropSize}`);\n  assert(method === \"bilinear\" || method === \"nearest\", () => `method must be bilinear or nearest, but was ${method}`);\n  const inputs = { image: $image, boxes: $boxes, boxInd: $boxInd };\n  const attrs = { method, extrapolationValue, cropSize };\n  const res = ENGINE.runKernel(CropAndResize, inputs, attrs);\n  return res;\n}\nvar cropAndResize = op({ cropAndResize_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/flip_left_right.js\nfunction flipLeftRight_(image2) {\n  const $image = convertToTensor(image2, \"image\", \"flipLeftRight\", \"float32\");\n  assert($image.rank === 4, () => `Error in flipLeftRight: image must be rank 4,but got rank ${$image.rank}.`);\n  const inputs = { image: $image };\n  const res = ENGINE.runKernel(FlipLeftRight, inputs, {});\n  return res;\n}\nvar flipLeftRight = op({ flipLeftRight_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/grayscale_to_rgb.js\nfunction grayscaleToRGB_(image2) {\n  const $image = convertToTensor(image2, \"image\", \"grayscaleToRGB\");\n  const lastDimsIdx = $image.rank - 1;\n  const lastDims = $image.shape[lastDimsIdx];\n  assert($image.rank >= 2, () => `Error in grayscaleToRGB: images must be at least rank 2, but got rank ${$image.rank}.`);\n  assert(lastDims === 1, () => `Error in grayscaleToRGB: last dimension of a grayscale image should be size 1, but got size ${lastDims}.`);\n  const reps = new Array($image.rank);\n  reps.fill(1, 0, lastDimsIdx);\n  reps[lastDimsIdx] = 3;\n  return tile($image, reps);\n}\nvar grayscaleToRGB = op({ grayscaleToRGB_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/rotate_with_offset.js\nfunction rotateWithOffset_(image2, radians, fillValue = 0, center = 0.5) {\n  const $image = convertToTensor(image2, \"image\", \"rotateWithOffset\", \"float32\");\n  assert($image.rank === 4, () => `Error in rotateWithOffset: image must be rank 4,but got rank ${$image.rank}.`);\n  const inputs = { image: $image };\n  const attrs = { radians, fillValue, center };\n  const res = ENGINE.runKernel(RotateWithOffset, inputs, attrs);\n  return res;\n}\nvar rotateWithOffset = op({ rotateWithOffset_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/nonmax_util.js\nfunction nonMaxSuppSanityCheck(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma) {\n  if (iouThreshold == null) {\n    iouThreshold = 0.5;\n  }\n  if (scoreThreshold == null) {\n    scoreThreshold = Number.NEGATIVE_INFINITY;\n  }\n  if (softNmsSigma == null) {\n    softNmsSigma = 0;\n  }\n  const numBoxes = boxes.shape[0];\n  maxOutputSize = Math.min(maxOutputSize, numBoxes);\n  assert(0 <= iouThreshold && iouThreshold <= 1, () => `iouThreshold must be in [0, 1], but was '${iouThreshold}'`);\n  assert(boxes.rank === 2, () => `boxes must be a 2D tensor, but was of rank '${boxes.rank}'`);\n  assert(boxes.shape[1] === 4, () => `boxes must have 4 columns, but 2nd dimension was ${boxes.shape[1]}`);\n  assert(scores.rank === 1, () => \"scores must be a 1D tensor\");\n  assert(scores.shape[0] === numBoxes, () => `scores has incompatible shape with boxes. Expected ${numBoxes}, but was ${scores.shape[0]}`);\n  assert(0 <= softNmsSigma && softNmsSigma <= 1, () => `softNmsSigma must be in [0, 1], but was '${softNmsSigma}'`);\n  return { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/non_max_suppression.js\nfunction nonMaxSuppression_(boxes, scores, maxOutputSize, iouThreshold = 0.5, scoreThreshold = Number.NEGATIVE_INFINITY) {\n  const $boxes = convertToTensor(boxes, \"boxes\", \"nonMaxSuppression\", \"float32\");\n  const $scores = convertToTensor(scores, \"scores\", \"nonMaxSuppression\", \"float32\");\n  const inputs = nonMaxSuppSanityCheck($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold);\n  maxOutputSize = inputs.maxOutputSize;\n  iouThreshold = inputs.iouThreshold;\n  scoreThreshold = inputs.scoreThreshold;\n  const attrs = { maxOutputSize, iouThreshold, scoreThreshold };\n  return ENGINE.runKernel(NonMaxSuppressionV3, { boxes: $boxes, scores: $scores }, attrs);\n}\nvar nonMaxSuppression = op({ nonMaxSuppression_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/non_max_suppression_util.js\nfunction binaryInsert(arr, element, comparator) {\n  const index = binarySearch(arr, element, comparator);\n  const insertionPoint = index < 0 ? -(index + 1) : index;\n  arr.splice(insertionPoint, 0, element);\n}\nfunction binarySearch(arr, target, comparator) {\n  return binarySearch_(arr, target, comparator || defaultComparator);\n}\nfunction defaultComparator(a, b) {\n  return a > b ? 1 : a < b ? -1 : 0;\n}\nfunction binarySearch_(arr, target, comparator) {\n  let left = 0;\n  let right = arr.length;\n  let middle = 0;\n  let found = false;\n  while (left < right) {\n    middle = left + (right - left >>> 1);\n    const compareResult = comparator(target, arr[middle]);\n    if (compareResult > 0) {\n      left = middle + 1;\n    } else {\n      right = middle;\n      found = !compareResult;\n    }\n  }\n  return found ? left : -left - 1;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/non_max_suppression_impl.js\nfunction nonMaxSuppressionV3Impl(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold) {\n  return nonMaxSuppressionImpl_(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, 0);\n}\nfunction nonMaxSuppressionV4Impl(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize) {\n  return nonMaxSuppressionImpl_(\n    boxes,\n    scores,\n    maxOutputSize,\n    iouThreshold,\n    scoreThreshold,\n    0,\n    false,\n    padToMaxOutputSize,\n    true\n  );\n}\nfunction nonMaxSuppressionV5Impl(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma) {\n  return nonMaxSuppressionImpl_(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma, true);\n}\nfunction nonMaxSuppressionImpl_(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma, returnScoresTensor = false, padToMaxOutputSize = false, returnValidOutputs = false) {\n  const candidates = [];\n  for (let i2 = 0; i2 < scores.length; i2++) {\n    if (scores[i2] > scoreThreshold) {\n      candidates.push({ score: scores[i2], boxIndex: i2, suppressBeginIndex: 0 });\n    }\n  }\n  candidates.sort(ascendingComparator);\n  const scale2 = softNmsSigma > 0 ? -0.5 / softNmsSigma : 0;\n  const selectedIndices = [];\n  const selectedScores = [];\n  while (selectedIndices.length < maxOutputSize && candidates.length > 0) {\n    const candidate = candidates.pop();\n    const { score: originalScore, boxIndex, suppressBeginIndex } = candidate;\n    if (originalScore < scoreThreshold) {\n      break;\n    }\n    let ignoreCandidate = false;\n    for (let j = selectedIndices.length - 1; j >= suppressBeginIndex; --j) {\n      const iou = intersectionOverUnion(boxes, boxIndex, selectedIndices[j]);\n      if (iou >= iouThreshold) {\n        ignoreCandidate = true;\n        break;\n      }\n      candidate.score = candidate.score * suppressWeight(iouThreshold, scale2, iou);\n      if (candidate.score <= scoreThreshold) {\n        break;\n      }\n    }\n    candidate.suppressBeginIndex = selectedIndices.length;\n    if (!ignoreCandidate) {\n      if (candidate.score === originalScore) {\n        selectedIndices.push(boxIndex);\n        selectedScores.push(candidate.score);\n      } else if (candidate.score > scoreThreshold) {\n        binaryInsert(candidates, candidate, ascendingComparator);\n      }\n    }\n  }\n  const validOutputs = selectedIndices.length;\n  const elemsToPad = maxOutputSize - validOutputs;\n  if (padToMaxOutputSize && elemsToPad > 0) {\n    selectedIndices.push(...new Array(elemsToPad).fill(0));\n    selectedScores.push(...new Array(elemsToPad).fill(0));\n  }\n  const result = { selectedIndices };\n  if (returnScoresTensor) {\n    result[\"selectedScores\"] = selectedScores;\n  }\n  if (returnValidOutputs) {\n    result[\"validOutputs\"] = validOutputs;\n  }\n  return result;\n}\nfunction intersectionOverUnion(boxes, i2, j) {\n  const iCoord = boxes.subarray(i2 * 4, i2 * 4 + 4);\n  const jCoord = boxes.subarray(j * 4, j * 4 + 4);\n  const yminI = Math.min(iCoord[0], iCoord[2]);\n  const xminI = Math.min(iCoord[1], iCoord[3]);\n  const ymaxI = Math.max(iCoord[0], iCoord[2]);\n  const xmaxI = Math.max(iCoord[1], iCoord[3]);\n  const yminJ = Math.min(jCoord[0], jCoord[2]);\n  const xminJ = Math.min(jCoord[1], jCoord[3]);\n  const ymaxJ = Math.max(jCoord[0], jCoord[2]);\n  const xmaxJ = Math.max(jCoord[1], jCoord[3]);\n  const areaI = (ymaxI - yminI) * (xmaxI - xminI);\n  const areaJ = (ymaxJ - yminJ) * (xmaxJ - xminJ);\n  if (areaI <= 0 || areaJ <= 0) {\n    return 0;\n  }\n  const intersectionYmin = Math.max(yminI, yminJ);\n  const intersectionXmin = Math.max(xminI, xminJ);\n  const intersectionYmax = Math.min(ymaxI, ymaxJ);\n  const intersectionXmax = Math.min(xmaxI, xmaxJ);\n  const intersectionArea = Math.max(intersectionYmax - intersectionYmin, 0) * Math.max(intersectionXmax - intersectionXmin, 0);\n  return intersectionArea / (areaI + areaJ - intersectionArea);\n}\nfunction suppressWeight(iouThreshold, scale2, iou) {\n  const weight = Math.exp(scale2 * iou * iou);\n  return iou <= iouThreshold ? weight : 0;\n}\nfunction ascendingComparator(c1, c2) {\n  return c1.score - c2.score || c1.score === c2.score && c2.boxIndex - c1.boxIndex;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/non_max_suppression_async.js\nasync function nonMaxSuppressionAsync_(boxes, scores, maxOutputSize, iouThreshold = 0.5, scoreThreshold = Number.NEGATIVE_INFINITY) {\n  const $boxes = convertToTensor(boxes, \"boxes\", \"nonMaxSuppressionAsync\");\n  const $scores = convertToTensor(scores, \"scores\", \"nonMaxSuppressionAsync\");\n  const inputs = nonMaxSuppSanityCheck($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold);\n  maxOutputSize = inputs.maxOutputSize;\n  iouThreshold = inputs.iouThreshold;\n  scoreThreshold = inputs.scoreThreshold;\n  const boxesAndScores = await Promise.all([$boxes.data(), $scores.data()]);\n  const boxesVals = boxesAndScores[0];\n  const scoresVals = boxesAndScores[1];\n  const { selectedIndices } = nonMaxSuppressionV3Impl(boxesVals, scoresVals, maxOutputSize, iouThreshold, scoreThreshold);\n  if ($boxes !== boxes) {\n    $boxes.dispose();\n  }\n  if ($scores !== scores) {\n    $scores.dispose();\n  }\n  return tensor1d(selectedIndices, \"int32\");\n}\nvar nonMaxSuppressionAsync = nonMaxSuppressionAsync_;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/non_max_suppression_with_score.js\nfunction nonMaxSuppressionWithScore_(boxes, scores, maxOutputSize, iouThreshold = 0.5, scoreThreshold = Number.NEGATIVE_INFINITY, softNmsSigma = 0) {\n  const $boxes = convertToTensor(boxes, \"boxes\", \"nonMaxSuppression\");\n  const $scores = convertToTensor(scores, \"scores\", \"nonMaxSuppression\");\n  const params = nonMaxSuppSanityCheck($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma);\n  maxOutputSize = params.maxOutputSize;\n  iouThreshold = params.iouThreshold;\n  scoreThreshold = params.scoreThreshold;\n  softNmsSigma = params.softNmsSigma;\n  const inputs = { boxes: $boxes, scores: $scores };\n  const attrs = { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma };\n  const result = ENGINE.runKernel(NonMaxSuppressionV5, inputs, attrs);\n  return { selectedIndices: result[0], selectedScores: result[1] };\n}\nvar nonMaxSuppressionWithScore = op({ nonMaxSuppressionWithScore_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/non_max_suppression_with_score_async.js\nasync function nonMaxSuppressionWithScoreAsync_(boxes, scores, maxOutputSize, iouThreshold = 0.5, scoreThreshold = Number.NEGATIVE_INFINITY, softNmsSigma = 0) {\n  const $boxes = convertToTensor(boxes, \"boxes\", \"nonMaxSuppressionAsync\");\n  const $scores = convertToTensor(scores, \"scores\", \"nonMaxSuppressionAsync\");\n  const params = nonMaxSuppSanityCheck($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma);\n  maxOutputSize = params.maxOutputSize;\n  iouThreshold = params.iouThreshold;\n  scoreThreshold = params.scoreThreshold;\n  softNmsSigma = params.softNmsSigma;\n  const boxesAndScores = await Promise.all([$boxes.data(), $scores.data()]);\n  const boxesVals = boxesAndScores[0];\n  const scoresVals = boxesAndScores[1];\n  const { selectedIndices, selectedScores } = nonMaxSuppressionV5Impl(boxesVals, scoresVals, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma);\n  if ($boxes !== boxes) {\n    $boxes.dispose();\n  }\n  if ($scores !== scores) {\n    $scores.dispose();\n  }\n  return {\n    selectedIndices: tensor1d(selectedIndices, \"int32\"),\n    selectedScores: tensor1d(selectedScores)\n  };\n}\nvar nonMaxSuppressionWithScoreAsync = nonMaxSuppressionWithScoreAsync_;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/non_max_suppression_padded.js\nfunction nonMaxSuppressionPadded_(boxes, scores, maxOutputSize, iouThreshold = 0.5, scoreThreshold = Number.NEGATIVE_INFINITY, padToMaxOutputSize = false) {\n  const $boxes = convertToTensor(boxes, \"boxes\", \"nonMaxSuppression\");\n  const $scores = convertToTensor(scores, \"scores\", \"nonMaxSuppression\");\n  const params = nonMaxSuppSanityCheck($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold, null);\n  const $maxOutputSize = params.maxOutputSize;\n  const $iouThreshold = params.iouThreshold;\n  const $scoreThreshold = params.scoreThreshold;\n  const inputs = { boxes: $boxes, scores: $scores };\n  const attrs = {\n    maxOutputSize: $maxOutputSize,\n    iouThreshold: $iouThreshold,\n    scoreThreshold: $scoreThreshold,\n    padToMaxOutputSize\n  };\n  const result = ENGINE.runKernel(NonMaxSuppressionV4, inputs, attrs);\n  return { selectedIndices: result[0], validOutputs: result[1] };\n}\nvar nonMaxSuppressionPadded = op({ nonMaxSuppressionPadded_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/non_max_suppression_padded_async.js\nasync function nonMaxSuppressionPaddedAsync_(boxes, scores, maxOutputSize, iouThreshold = 0.5, scoreThreshold = Number.NEGATIVE_INFINITY, padToMaxOutputSize = false) {\n  const $boxes = convertToTensor(boxes, \"boxes\", \"nonMaxSuppressionAsync\");\n  const $scores = convertToTensor(scores, \"scores\", \"nonMaxSuppressionAsync\");\n  const params = nonMaxSuppSanityCheck($boxes, $scores, maxOutputSize, iouThreshold, scoreThreshold, null);\n  const $maxOutputSize = params.maxOutputSize;\n  const $iouThreshold = params.iouThreshold;\n  const $scoreThreshold = params.scoreThreshold;\n  const [boxesVals, scoresVals] = await Promise.all([$boxes.data(), $scores.data()]);\n  const { selectedIndices, validOutputs } = nonMaxSuppressionV4Impl(boxesVals, scoresVals, $maxOutputSize, $iouThreshold, $scoreThreshold, padToMaxOutputSize);\n  if ($boxes !== boxes) {\n    $boxes.dispose();\n  }\n  if ($scores !== scores) {\n    $scores.dispose();\n  }\n  return {\n    selectedIndices: tensor1d(selectedIndices, \"int32\"),\n    validOutputs: scalar(validOutputs, \"int32\")\n  };\n}\nvar nonMaxSuppressionPaddedAsync = nonMaxSuppressionPaddedAsync_;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/resize_bilinear.js\nfunction resizeBilinear_(images, size, alignCorners = false, halfPixelCenters = false) {\n  const $images = convertToTensor(images, \"images\", \"resizeBilinear\");\n  assert($images.rank === 3 || $images.rank === 4, () => `Error in resizeBilinear: x must be rank 3 or 4, but got rank ${$images.rank}.`);\n  assert(size.length === 2, () => `Error in resizeBilinear: new shape must 2D, but got shape ${size}.`);\n  assert(halfPixelCenters === false || alignCorners === false, () => `Error in resizeBilinear: If halfPixelCenters is true, alignCorners must be false.`);\n  let batchImages = $images;\n  let reshapedTo4D = false;\n  if ($images.rank === 3) {\n    reshapedTo4D = true;\n    batchImages = reshape($images, [1, $images.shape[0], $images.shape[1], $images.shape[2]]);\n  }\n  const [] = size;\n  const inputs = { images: batchImages };\n  const attrs = { alignCorners, halfPixelCenters, size };\n  const res = ENGINE.runKernel(ResizeBilinear, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar resizeBilinear = op({ resizeBilinear_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/resize_nearest_neighbor.js\nfunction resizeNearestNeighbor_(images, size, alignCorners = false, halfPixelCenters = false) {\n  const $images = convertToTensor(images, \"images\", \"resizeNearestNeighbor\");\n  assert($images.rank === 3 || $images.rank === 4, () => `Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank ${$images.rank}.`);\n  assert(size.length === 2, () => `Error in resizeNearestNeighbor: new shape must 2D, but got shape ${size}.`);\n  assert($images.dtype === \"float32\" || $images.dtype === \"int32\", () => \"`images` must have `int32` or `float32` as dtype\");\n  assert(halfPixelCenters === false || alignCorners === false, () => `Error in resizeNearestNeighbor: If halfPixelCenters is true, alignCorners must be false.`);\n  let batchImages = $images;\n  let reshapedTo4D = false;\n  if ($images.rank === 3) {\n    reshapedTo4D = true;\n    batchImages = reshape($images, [1, $images.shape[0], $images.shape[1], $images.shape[2]]);\n  }\n  const [] = size;\n  const inputs = { images: batchImages };\n  const attrs = { alignCorners, halfPixelCenters, size };\n  const res = ENGINE.runKernel(ResizeNearestNeighbor, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar resizeNearestNeighbor = op({ resizeNearestNeighbor_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/threshold.js\nfunction threshold_(image2, method = \"binary\", inverted = false, threshValue = 0.5) {\n  const $image = convertToTensor(image2, \"image\", \"threshold\");\n  const RED_INTENCITY_COEF = 0.2989;\n  const GREEN_INTENCITY_COEF = 0.587;\n  const BLUE_INTENCITY_COEF = 0.114;\n  const totalPixelsInImage = $image.shape[0] * $image.shape[1];\n  let $threshold = mul(tensor1d([threshValue]), 255);\n  let r2, g, b, grayscale;\n  assert($image.rank === 3, () => `Error in threshold: image must be rank 3,but got rank ${$image.rank}.`);\n  assert($image.shape[2] === 3 || $image.shape[2] === 1, () => `Error in threshold: image color channel must be equal to 3 or 1but got ${$image.shape[2]}.`);\n  assert($image.dtype === \"int32\" || $image.dtype === \"float32\", () => `Error in dtype: image dtype must be int32 or float32,but got dtype ${$image.dtype}.`);\n  assert(method === \"otsu\" || method === \"binary\", () => `Method must be binary or otsu, but was ${method}`);\n  if ($image.shape[2] === 3) {\n    [r2, g, b] = split($image, [1, 1, 1], -1);\n    const $r = mul(r2, RED_INTENCITY_COEF);\n    const $g = mul(g, GREEN_INTENCITY_COEF);\n    const $b = mul(b, BLUE_INTENCITY_COEF);\n    grayscale = add2(add2($r, $g), $b);\n  } else {\n    grayscale = image2;\n  }\n  if (method === \"otsu\") {\n    const $histogram = bincount(cast(round2(grayscale), \"int32\"), tensor([]), 256);\n    $threshold = otsu($histogram, totalPixelsInImage);\n  }\n  const invCondition = inverted ? lessEqual(grayscale, $threshold) : greater(grayscale, $threshold);\n  const result = cast(mul(invCondition, 255), \"int32\");\n  return result;\n}\nfunction otsu(histogram, total) {\n  let bestThresh = tensor1d([-1]);\n  let bestInBetVar = tensor1d([0]);\n  let cInBetVar = tensor1d([0]);\n  let classFirst, classSecond, meanFirst, meanSec, weightForeground, weightBack;\n  for (let index = 0; index < histogram.size - 1; index++) {\n    classFirst = slice(histogram, 0, index + 1);\n    classSecond = slice(histogram, index + 1);\n    weightForeground = div(sum2(classFirst), total);\n    weightBack = div(sum2(classSecond), total);\n    const meanFirstDivA = sum2(mul(classFirst, range(0, classFirst.size)));\n    meanFirst = div(meanFirstDivA, sum2(classFirst));\n    const meanSecFill = fill(classSecond.shape, classFirst.size);\n    const meanSecAdd = add2(range(0, classSecond.size), meanSecFill);\n    const meanSecMul = mul(classSecond, meanSecAdd);\n    meanSec = div(sum2(meanSecMul), sum2(classSecond));\n    const cInBetVarSubA = sub(meanFirst, meanSec);\n    const cInBetVarSubB = sub(meanFirst, meanSec);\n    const cInBetVarMul = mul(weightForeground, weightBack);\n    cInBetVar = mul(mul(cInBetVarMul, cInBetVarSubA), cInBetVarSubB);\n    const condition = greater(cInBetVar, bestInBetVar);\n    bestInBetVar = where(condition, cInBetVar, bestInBetVar);\n    bestThresh = where(condition, tensor1d([index]), bestThresh);\n  }\n  return bestThresh;\n}\nvar threshold = op({ threshold_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/image/transform.js\nfunction transform_(image2, transforms, interpolation = \"nearest\", fillMode = \"constant\", fillValue = 0, outputShape) {\n  const $image = convertToTensor(image2, \"image\", \"transform\", \"float32\");\n  const $transforms = convertToTensor(transforms, \"transforms\", \"transform\", \"float32\");\n  assert($image.rank === 4, () => `Error in transform: image must be rank 4,but got rank ${$image.rank}.`);\n  assert($transforms.rank === 2 && ($transforms.shape[0] === $image.shape[0] || $transforms.shape[0] === 1) && $transforms.shape[1] === 8, () => `Error in transform: Input transform should be batch x 8 or 1 x 8`);\n  assert(outputShape == null || outputShape.length === 2, () => `Error in transform: outputShape must be [height, width] or null, but got ${outputShape}.`);\n  const inputs = { image: $image, transforms: $transforms };\n  const attrs = { interpolation, fillMode, fillValue, outputShape };\n  return ENGINE.runKernel(Transform, inputs, attrs);\n}\nvar transform = op({ transform_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/linalg/band_part.js\nfunction bandPart_(a, numLower, numUpper) {\n  assert(numLower % 1 === 0, () => `bandPart(): numLower must be an integer, got ${numLower}.`);\n  assert(numUpper % 1 === 0, () => `bandPart(): numUpper must be an integer, got ${numUpper}.`);\n  const $a = convertToTensor(a, \"a\", \"bandPart\");\n  assert($a.rank >= 2, () => `bandPart(): Rank must be at least 2, got ${$a.rank}.`);\n  const shape = $a.shape;\n  const [M, N] = $a.shape.slice(-2);\n  if (!(numLower <= M)) {\n    throw new Error(`bandPart(): numLower (${numLower}) must not be greater than the number of rows (${M}).`);\n  }\n  if (!(numUpper <= N)) {\n    throw new Error(`bandPart(): numUpper (${numUpper}) must not be greater than the number of columns (${N}).`);\n  }\n  if (numLower < 0) {\n    numLower = M;\n  }\n  if (numUpper < 0) {\n    numUpper = N;\n  }\n  const i2 = reshape(range(0, M, 1, \"int32\"), [-1, 1]);\n  const j = range(0, N, 1, \"int32\");\n  const ij = sub(i2, j);\n  const inBand = logicalAnd(lessEqual(ij, scalar(+numLower, \"int32\")), greaterEqual(ij, scalar(-numUpper, \"int32\")));\n  const zero = zeros([M, N], $a.dtype);\n  return reshape(stack(unstack(reshape($a, [-1, M, N])).map((mat) => where(inBand, mat, zero))), shape);\n}\nvar bandPart = op({ bandPart_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/linalg/gram_schmidt.js\nfunction gramSchmidt_(xs) {\n  let inputIsTensor2D;\n  if (Array.isArray(xs)) {\n    inputIsTensor2D = false;\n    assert(xs != null && xs.length > 0, () => \"Gram-Schmidt process: input must not be null, undefined, or empty\");\n    const dim = xs[0].shape[0];\n    for (let i2 = 1; i2 < xs.length; ++i2) {\n      assert(xs[i2].shape[0] === dim, () => `Gram-Schmidt: Non-unique lengths found in the input vectors: (${xs[i2].shape[0]} vs. ${dim})`);\n    }\n  } else {\n    inputIsTensor2D = true;\n    xs = split(xs, xs.shape[0], 0).map((x) => squeeze(x, [0]));\n  }\n  assert(xs.length <= xs[0].shape[0], () => `Gram-Schmidt: Number of vectors (${xs.length}) exceeds number of dimensions (${xs[0].shape[0]}).`);\n  const ys = [];\n  const xs1d = xs;\n  for (let i2 = 0; i2 < xs.length; ++i2) {\n    ys.push(ENGINE.tidy(() => {\n      let x = xs1d[i2];\n      if (i2 > 0) {\n        for (let j = 0; j < i2; ++j) {\n          const proj = mul(sum2(mul(ys[j], x)), ys[j]);\n          x = sub(x, proj);\n        }\n      }\n      return div(x, norm(x, \"euclidean\"));\n    }));\n  }\n  if (inputIsTensor2D) {\n    return stack(ys, 0);\n  } else {\n    return ys;\n  }\n}\nvar gramSchmidt = op({ gramSchmidt_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/linalg/qr.js\nfunction qr_(x, fullMatrices = false) {\n  assert(x.rank >= 2, () => `qr() requires input tensor to have a rank >= 2, but got rank ${x.rank}`);\n  if (x.rank === 2) {\n    return qr2d(x, fullMatrices);\n  } else {\n    const outerDimsProd = x.shape.slice(0, x.shape.length - 2).reduce((value, prev) => value * prev);\n    const x2ds = unstack(reshape(x, [\n      outerDimsProd,\n      x.shape[x.shape.length - 2],\n      x.shape[x.shape.length - 1]\n    ]), 0);\n    const q2ds = [];\n    const r2ds = [];\n    x2ds.forEach((x2d) => {\n      const [q2d, r2d] = qr2d(x2d, fullMatrices);\n      q2ds.push(q2d);\n      r2ds.push(r2d);\n    });\n    const q = reshape(stack(q2ds, 0), x.shape);\n    const r2 = reshape(stack(r2ds, 0), x.shape);\n    return [q, r2];\n  }\n}\nfunction qr2d(x, fullMatrices = false) {\n  return ENGINE.tidy(() => {\n    assert(x.shape.length === 2, () => `qr2d() requires a 2D Tensor, but got a ${x.shape.length}D Tensor.`);\n    const m = x.shape[0];\n    const n2 = x.shape[1];\n    let q = eye(m);\n    let r2 = clone(x);\n    const one2D = tensor2d([[1]], [1, 1]);\n    let w = clone(one2D);\n    const iters = m >= n2 ? n2 : m;\n    for (let j = 0; j < iters; ++j) {\n      const rTemp = r2;\n      const wTemp = w;\n      const qTemp = q;\n      [w, r2, q] = ENGINE.tidy(() => {\n        const rjEnd1 = slice(r2, [j, j], [m - j, 1]);\n        const normX = norm(rjEnd1);\n        const rjj = slice(r2, [j, j], [1, 1]);\n        const s2 = where(greater(rjj, 0), tensor2d([[-1]]), tensor2d([[1]]));\n        const u1 = sub(rjj, mul(s2, normX));\n        const wPre = div(rjEnd1, u1);\n        if (wPre.shape[0] === 1) {\n          w = clone(one2D);\n        } else {\n          w = concat([\n            one2D,\n            slice(wPre, [1, 0], [wPre.shape[0] - 1, wPre.shape[1]])\n          ], 0);\n        }\n        const tau = neg(div(matMul(s2, u1), normX));\n        const rjEndAll = slice(r2, [j, 0], [m - j, n2]);\n        const tauTimesW = mul(tau, w);\n        const wT = transpose(w);\n        if (j === 0) {\n          r2 = sub(rjEndAll, matMul(tauTimesW, matMul(wT, rjEndAll)));\n        } else {\n          const rTimesTau = sub(rjEndAll, matMul(tauTimesW, matMul(wT, rjEndAll)));\n          r2 = concat([slice(r2, [0, 0], [j, n2]), rTimesTau], 0);\n        }\n        const tawTimesWT = transpose(tauTimesW);\n        const qAllJEnd = slice(q, [0, j], [m, q.shape[1] - j]);\n        if (j === 0) {\n          q = sub(qAllJEnd, matMul(matMul(qAllJEnd, w), tawTimesWT));\n        } else {\n          const qTimesTau = sub(qAllJEnd, matMul(matMul(qAllJEnd, w), tawTimesWT));\n          q = concat([slice(q, [0, 0], [m, j]), qTimesTau], 1);\n        }\n        return [w, r2, q];\n      });\n      dispose([rTemp, wTemp, qTemp]);\n    }\n    if (!fullMatrices && m > n2) {\n      q = slice(q, [0, 0], [m, n2]);\n      r2 = slice(r2, [0, 0], [n2, n2]);\n    }\n    return [q, r2];\n  });\n}\nvar qr = op({ qr_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/loss_ops_utils.js\nvar Reduction;\n(function(Reduction2) {\n  Reduction2[Reduction2[\"NONE\"] = 0] = \"NONE\";\n  Reduction2[Reduction2[\"MEAN\"] = 1] = \"MEAN\";\n  Reduction2[Reduction2[\"SUM\"] = 2] = \"SUM\";\n  Reduction2[Reduction2[\"SUM_BY_NONZERO_WEIGHTS\"] = 3] = \"SUM_BY_NONZERO_WEIGHTS\";\n})(Reduction || (Reduction = {}));\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/compute_weighted_loss.js\nfunction computeWeightedLoss_(losses2, weights, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  const $losses = convertToTensor(losses2, \"losses\", \"computeWeightedLoss\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"computeWeightedLoss\");\n  }\n  const weightedLoss = $weights == null ? $losses : mul($losses, $weights);\n  if (reduction === Reduction.NONE) {\n    return weightedLoss;\n  }\n  if (reduction === Reduction.SUM) {\n    return sum2(weightedLoss);\n  }\n  if (reduction === Reduction.MEAN) {\n    if ($weights == null) {\n      return mean(weightedLoss);\n    } else {\n      const broadcastFactor = $losses.size / $weights.size;\n      const result = div(sum2(weightedLoss), sum2($weights));\n      return broadcastFactor > 1 ? div(result, scalar(broadcastFactor)) : result;\n    }\n  }\n  if (reduction === Reduction.SUM_BY_NONZERO_WEIGHTS) {\n    if ($weights == null) {\n      return div(sum2(weightedLoss), scalar($losses.size));\n    } else {\n      const broadcastedWeights = mul($weights, ones2($losses.shape));\n      const numNonZeros = cast(sum2(notEqual(broadcastedWeights, scalar(0))), \"float32\");\n      return div(sum2(weightedLoss), numNonZeros);\n    }\n  }\n  throw Error(`Unknown reduction: ${reduction}`);\n}\nvar computeWeightedLoss = op({ computeWeightedLoss_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/absolute_difference.js\nfunction absoluteDifference_(labels, predictions, weights, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  const $labels = convertToTensor(labels, \"labels\", \"absoluteDifference\");\n  const $predictions = convertToTensor(predictions, \"predictions\", \"absoluteDifference\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"absoluteDifference\");\n  }\n  assertShapesMatch($labels.shape, $predictions.shape, \"Error in absoluteDifference: \");\n  const losses2 = abs(sub($labels, $predictions));\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar absoluteDifference = op({ absoluteDifference_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/cosine_distance.js\nfunction cosineDistance_(labels, predictions, axis, weights, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  const $labels = convertToTensor(labels, \"labels\", \"cosineDistance\");\n  const $predictions = convertToTensor(predictions, \"predictions\", \"cosineDistance\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"cosineDistance\");\n  }\n  assertShapesMatch($labels.shape, $predictions.shape, \"Error in cosineDistance: \");\n  const one = scalar(1);\n  const losses2 = sub(one, sum2(mul($labels, $predictions), axis, true));\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar cosineDistance = op({ cosineDistance_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/hinge_loss.js\nfunction hingeLoss_(labels, predictions, weights, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  let $labels = convertToTensor(labels, \"labels\", \"hingeLoss\");\n  const $predictions = convertToTensor(predictions, \"predictions\", \"hingeLoss\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"hingeLoss\");\n  }\n  assertShapesMatch($labels.shape, $predictions.shape, \"Error in hingeLoss: \");\n  const one = scalar(1);\n  $labels = sub(mul(scalar(2), $labels), one);\n  const losses2 = relu(sub(one, mul($labels, $predictions)));\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar hingeLoss = op({ hingeLoss_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/huber_loss.js\nfunction huberLoss_(labels, predictions, weights, delta = 1, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  const $labels = convertToTensor(labels, \"labels\", \"huberLoss\");\n  const $predictions = convertToTensor(predictions, \"predictions\", \"huberLoss\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"huberLoss\");\n  }\n  assertShapesMatch($labels.shape, $predictions.shape, \"Error in huberLoss: \");\n  const deltaScalar = scalar(delta);\n  const error = abs(sub($predictions, $labels));\n  const quadratic = minimum(error, deltaScalar);\n  const linear = sub(error, quadratic);\n  const losses2 = add2(mul(scalar(0.5), square(quadratic)), mul(deltaScalar, linear));\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar huberLoss = op({ huberLoss_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/log_loss.js\nfunction logLoss_(labels, predictions, weights, epsilon3 = 1e-7, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  const $labels = convertToTensor(labels, \"labels\", \"logLoss\");\n  const $predictions = convertToTensor(predictions, \"predictions\", \"logLoss\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"logLoss\");\n  }\n  assertShapesMatch($labels.shape, $predictions.shape, \"Error in logLoss: \");\n  const one = scalar(1);\n  const epsilonScalar = scalar(epsilon3);\n  const l13 = neg(mul($labels, log2(add2($predictions, epsilonScalar))));\n  const l23 = mul(sub(one, $labels), log2(add2(sub(one, $predictions), epsilonScalar)));\n  const losses2 = sub(l13, l23);\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar logLoss = op({ logLoss_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/mean_squared_error.js\nfunction meanSquaredError_(labels, predictions, weights, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  const $labels = convertToTensor(labels, \"labels\", \"meanSquaredError\");\n  const $predictions = convertToTensor(predictions, \"predictions\", \"meanSquaredError\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"meanSquaredError\");\n  }\n  assertShapesMatch($labels.shape, $predictions.shape, \"Error in meanSquaredError: \");\n  const losses2 = squaredDifference($labels, $predictions);\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar meanSquaredError = op({ meanSquaredError_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/sigmoid_cross_entropy.js\nfunction sigmoidCrossEntropyWithLogits_(labels, logits) {\n  const $labels = convertToTensor(labels, \"labels\", \"sigmoidCrossEntropyWithLogits\");\n  const $logits = convertToTensor(logits, \"logits\", \"sigmoidCrossEntropyWithLogits\");\n  assertShapesMatch($labels.shape, $logits.shape, \"Error in sigmoidCrossEntropyWithLogits: \");\n  const maxOutput = relu($logits);\n  const outputXTarget = mul($logits, $labels);\n  const sigmoidOutput = log1p(exp(neg(abs($logits))));\n  return add2(sub(maxOutput, outputXTarget), sigmoidOutput);\n}\nfunction sigmoidCrossEntropy_(multiClassLabels, logits, weights, labelSmoothing = 0, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  let $multiClassLabels = convertToTensor(multiClassLabels, \"multiClassLabels\", \"sigmoidCrossEntropy\");\n  const $logits = convertToTensor(logits, \"logits\", \"sigmoidCrossEntropy\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"sigmoidCrossEntropy\");\n  }\n  assertShapesMatch($multiClassLabels.shape, $logits.shape, \"Error in sigmoidCrossEntropy: \");\n  if (labelSmoothing > 0) {\n    const labelSmoothingScalar = scalar(labelSmoothing);\n    const one = scalar(1);\n    const half = scalar(0.5);\n    $multiClassLabels = add2(mul($multiClassLabels, sub(one, labelSmoothingScalar)), mul(half, labelSmoothingScalar));\n  }\n  const losses2 = sigmoidCrossEntropyWithLogits_($multiClassLabels, $logits);\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar sigmoidCrossEntropy = op({ sigmoidCrossEntropy_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/losses/softmax_cross_entropy.js\nfunction softmaxCrossEntropyWithLogits_(labels, logits, dim = -1) {\n  if (dim === -1) {\n    dim = logits.rank - 1;\n  }\n  if (dim !== logits.rank - 1) {\n    throw Error(`Softmax cross entropy along a non-last dimension is not yet supported. Labels / logits was rank ${logits.rank} and dim was ${dim}`);\n  }\n  const customOp = customGrad((labels2, logits2, save) => {\n    const keepDims = true;\n    const lse = logSumExp(logits2, [dim], keepDims);\n    const logResult = sub(cast(logits2, \"float32\"), lse);\n    save([labels2, logResult]);\n    const costVector = neg(mul(logResult, labels2));\n    const value = sum2(costVector, [dim]);\n    const gradFunc = (dy, saved) => {\n      const [labels3, logResult2] = saved;\n      const dyShape = expandShapeToKeepDim(dy.shape, [dim]);\n      return [\n        mul(reshape(dy, dyShape), sub(cast(labels3, \"float32\"), exp(logResult2))),\n        mul(reshape(dy, dyShape), sub(exp(logResult2), cast(labels3, \"float32\")))\n      ];\n    };\n    return { value, gradFunc };\n  });\n  return customOp(labels, logits);\n}\nfunction softmaxCrossEntropy_(onehotLabels, logits, weights, labelSmoothing = 0, reduction = Reduction.SUM_BY_NONZERO_WEIGHTS) {\n  let $onehotLabels = convertToTensor(onehotLabels, \"onehotLabels\", \"softmaxCrossEntropy\");\n  const $logits = convertToTensor(logits, \"logits\", \"softmaxCrossEntropy\");\n  let $weights = null;\n  if (weights != null) {\n    $weights = convertToTensor(weights, \"weights\", \"softmaxCrossEntropy\");\n  }\n  assertShapesMatch($onehotLabels.shape, $logits.shape, \"Error in softmaxCrossEntropy: \");\n  if (labelSmoothing > 0) {\n    const labelSmoothingScalar = scalar(labelSmoothing);\n    const one = scalar(1);\n    const numClasses = scalar($onehotLabels.shape[1]);\n    $onehotLabels = add2(mul($onehotLabels, sub(one, labelSmoothingScalar)), div(labelSmoothingScalar, numClasses));\n  }\n  const losses2 = softmaxCrossEntropyWithLogits_($onehotLabels, $logits);\n  return computeWeightedLoss(losses2, $weights, reduction);\n}\nvar softmaxCrossEntropy = op({ softmaxCrossEntropy_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse/sparse_fill_empty_rows.js\nfunction sparseFillEmptyRows_(indices, values, denseShape, defaultValue) {\n  const $indices = convertToTensor(indices, \"indices\", \"sparseFillEmptyRows\", \"int32\");\n  const $values = convertToTensor(values, \"values\", \"sparseFillEmptyRows\");\n  const $denseShape = convertToTensor(denseShape, \"denseShape\", \"sparseFillEmptyRows\", \"int32\");\n  const $defaultValue = convertToTensor(defaultValue, \"defaultValue\", \"sparseFillEmptyRows\", $values.dtype);\n  if ($indices.rank !== 2) {\n    throw new Error(`Indices should be Tensor2D but received shape\n        ${$indices.shape}`);\n  }\n  if ($values.rank !== 1) {\n    throw new Error(`Values should be Tensor1D but received shape ${$values.shape}`);\n  }\n  if ($denseShape.rank !== 1) {\n    throw new Error(`Dense shape should be Tensor1D but received shape ${$denseShape.shape}`);\n  }\n  if ($defaultValue.rank !== 0) {\n    throw new Error(`Default value should be a scalar but received shape ${$defaultValue.shape}`);\n  }\n  const inputs = {\n    indices: $indices,\n    values: $values,\n    denseShape: $denseShape,\n    defaultValue: $defaultValue\n  };\n  const result = ENGINE.runKernel(SparseFillEmptyRows, inputs);\n  return {\n    outputIndices: result[0],\n    outputValues: result[1],\n    emptyRowIndicator: result[2],\n    reverseIndexMap: result[3]\n  };\n}\nvar sparseFillEmptyRows = op({ sparseFillEmptyRows_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse/sparse_reshape.js\nfunction sparseReshape_(inputIndices, inputShape, newShape) {\n  const $inputIndices = convertToTensor(inputIndices, \"inputIndices\", \"sparseReshape\", \"int32\");\n  const $inputShape = convertToTensor(inputShape, \"inputShape\", \"sparseReshape\", \"int32\");\n  const $newShape = convertToTensor(newShape, \"newShape\", \"sparseReshape\", \"int32\");\n  if ($inputIndices.rank !== 2) {\n    throw new Error(`Input indices should be Tensor2D but received shape\n        ${$inputIndices.shape}`);\n  }\n  if ($inputShape.rank !== 1) {\n    throw new Error(`Input shape should be Tensor1D but received shape ${$inputShape.shape}`);\n  }\n  if ($newShape.rank !== 1) {\n    throw new Error(`New shape should be Tensor1D but received shape ${$newShape.shape}`);\n  }\n  const inputs = {\n    inputIndices: $inputIndices,\n    inputShape: $inputShape,\n    newShape: $newShape\n  };\n  const result = ENGINE.runKernel(SparseReshape, inputs);\n  return { outputIndices: result[0], outputShape: result[1] };\n}\nvar sparseReshape = op({ sparseReshape_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse/sparse_segment_mean.js\nfunction sparseSegmentMean_(data, indices, segmentIds) {\n  const $data = convertToTensor(data, \"data\", \"sparseSegmentMean\");\n  const $indices = convertToTensor(indices, \"indices\", \"sparseSegmentMean\", \"int32\");\n  const $segmentIds = convertToTensor(segmentIds, \"segmentIds\", \"sparseSegmentMean\", \"int32\");\n  if ($data.rank < 1) {\n    throw new Error(`Data should be at least 1 dimensional but received scalar`);\n  }\n  if ($indices.rank !== 1) {\n    throw new Error(`Indices should be Tensor1D but received shape\n          ${$indices.shape}`);\n  }\n  if ($segmentIds.rank !== 1) {\n    throw new Error(`Segment ids should be Tensor1D but received shape\n          ${$segmentIds.shape}`);\n  }\n  const inputs = {\n    data: $data,\n    indices: $indices,\n    segmentIds: $segmentIds\n  };\n  return ENGINE.runKernel(SparseSegmentMean, inputs);\n}\nvar sparseSegmentMean = op({ sparseSegmentMean_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse/sparse_segment_sum.js\nfunction sparseSegmentSum_(data, indices, segmentIds) {\n  const $data = convertToTensor(data, \"data\", \"sparseSegmentSum\");\n  const $indices = convertToTensor(indices, \"indices\", \"sparseSegmentSum\", \"int32\");\n  const $segmentIds = convertToTensor(segmentIds, \"segmentIds\", \"sparseSegmentSum\", \"int32\");\n  if ($data.rank < 1) {\n    throw new Error(`Data should be at least 1 dimensional but received scalar`);\n  }\n  if ($indices.rank !== 1) {\n    throw new Error(`Indices should be Tensor1D but received shape\n         ${$indices.shape}`);\n  }\n  if ($segmentIds.rank !== 1) {\n    throw new Error(`Segment ids should be Tensor1D but received shape\n         ${$segmentIds.shape}`);\n  }\n  const inputs = {\n    data: $data,\n    indices: $indices,\n    segmentIds: $segmentIds\n  };\n  return ENGINE.runKernel(SparseSegmentSum, inputs);\n}\nvar sparseSegmentSum = op({ sparseSegmentSum_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/string/string_n_grams.js\nfunction stringNGrams_(data, dataSplits, separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences) {\n  const $data = convertToTensor(data, \"data\", \"stringNGrams\", \"string\");\n  if ($data.dtype !== \"string\") {\n    throw new Error(\"Data must be of datatype string\");\n  }\n  if ($data.shape.length !== 1) {\n    throw new Error(`Data must be a vector, saw: ${$data.shape}`);\n  }\n  const $dataSplits = convertToTensor(dataSplits, \"dataSplits\", \"stringNGrams\");\n  if ($dataSplits.dtype !== \"int32\") {\n    throw new Error(\"Data splits must be of datatype int32\");\n  }\n  const attrs = {\n    separator,\n    nGramWidths,\n    leftPad,\n    rightPad: rightPad2,\n    padWidth,\n    preserveShortSequences\n  };\n  const inputs = { data: $data, dataSplits: $dataSplits };\n  const result = ENGINE.runKernel(StringNGrams, inputs, attrs);\n  return { nGrams: result[0], nGramsSplits: result[1] };\n}\nvar stringNGrams = op({ stringNGrams_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/string/string_split.js\nfunction stringSplit_(input2, delimiter, skipEmpty = true) {\n  const $input = convertToTensor(input2, \"input\", \"stringSplit\", \"string\");\n  const $delimiter = convertToTensor(delimiter, \"delimiter\", \"stringSplit\", \"string\");\n  if ($input.rank !== 1) {\n    throw new Error(`Input should be Tensor1D but received shape ${$input.shape}`);\n  }\n  if ($delimiter.rank !== 0) {\n    throw new Error(`Delimiter should be a scalar but received shape ${$delimiter.shape}`);\n  }\n  const attrs = { skipEmpty };\n  const inputs = { input: $input, delimiter: $delimiter };\n  const result = ENGINE.runKernel(StringSplit, inputs, attrs);\n  return { indices: result[0], values: result[1], shape: result[2] };\n}\nvar stringSplit = op({ stringSplit_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/string/string_to_hash_bucket_fast.js\nfunction stringToHashBucketFast_(input2, numBuckets) {\n  const $input = convertToTensor(input2, \"input\", \"stringToHashBucketFast\", \"string\");\n  const attrs = { numBuckets };\n  if (numBuckets <= 0) {\n    throw new Error(`Number of buckets must be at least 1`);\n  }\n  const inputs = { input: $input };\n  return ENGINE.runKernel(StringToHashBucketFast, inputs, attrs);\n}\nvar stringToHashBucketFast = op({ stringToHashBucketFast_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/ops.js\nvar spectral = {\n  fft,\n  ifft,\n  rfft,\n  irfft\n};\nvar signal = {\n  hammingWindow,\n  hannWindow,\n  frame,\n  stft\n};\nvar image = {\n  flipLeftRight,\n  grayscaleToRGB,\n  resizeNearestNeighbor,\n  resizeBilinear,\n  rotateWithOffset,\n  cropAndResize,\n  nonMaxSuppression,\n  nonMaxSuppressionAsync,\n  nonMaxSuppressionWithScore,\n  nonMaxSuppressionWithScoreAsync,\n  nonMaxSuppressionPadded,\n  nonMaxSuppressionPaddedAsync,\n  threshold,\n  transform\n};\nvar linalg = {\n  bandPart,\n  gramSchmidt,\n  qr\n};\nvar losses = {\n  absoluteDifference,\n  computeWeightedLoss,\n  cosineDistance,\n  hingeLoss,\n  huberLoss,\n  logLoss,\n  meanSquaredError,\n  sigmoidCrossEntropy,\n  softmaxCrossEntropy\n};\nvar sparse = {\n  sparseFillEmptyRows,\n  sparseReshape,\n  sparseSegmentMean,\n  sparseSegmentSum\n};\nvar string = {\n  stringNGrams,\n  stringSplit,\n  stringToHashBucketFast\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/optimizer.js\nvar Optimizer = class extends Serializable {\n  minimize(f, returnCost = false, varList) {\n    const { value, grads: grads2 } = this.computeGradients(f, varList);\n    if (varList != null) {\n      const gradArray = varList.map((v) => ({ name: v.name, tensor: grads2[v.name] }));\n      this.applyGradients(gradArray);\n    } else {\n      this.applyGradients(grads2);\n    }\n    dispose(grads2);\n    if (returnCost) {\n      return value;\n    } else {\n      value.dispose();\n      return null;\n    }\n  }\n  get iterations() {\n    if (this.iterations_ == null) {\n      this.iterations_ = 0;\n    }\n    return this.iterations_;\n  }\n  incrementIterations() {\n    this.iterations_ = this.iterations + 1;\n  }\n  computeGradients(f, varList) {\n    return variableGrads(f, varList);\n  }\n  dispose() {\n    if (this.iterations_ != null) {\n      dispose(this.iterations_);\n    }\n  }\n  async saveIterations() {\n    if (this.iterations_ == null) {\n      this.iterations_ = 0;\n    }\n    return {\n      name: \"iter\",\n      tensor: scalar(this.iterations_, \"int32\")\n    };\n  }\n  async getWeights() {\n    throw new Error(\"getWeights() is not implemented for this optimizer yet.\");\n  }\n  async setWeights(weightValues) {\n    throw new Error(`setWeights() is not implemented for this optimizer class ${this.getClassName()}`);\n  }\n  async extractIterations(weightValues) {\n    this.iterations_ = (await weightValues[0].tensor.data())[0];\n    return weightValues.slice(1);\n  }\n};\nObject.defineProperty(Optimizer, Symbol.hasInstance, {\n  value: (instance) => {\n    return instance.minimize != null && instance.computeGradients != null && instance.applyGradients != null;\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/adadelta_optimizer.js\nvar AdadeltaOptimizer = class extends Optimizer {\n  constructor(learningRate, rho, epsilon3 = null) {\n    super();\n    this.learningRate = learningRate;\n    this.rho = rho;\n    this.epsilon = epsilon3;\n    this.accumulatedGrads = [];\n    this.accumulatedUpdates = [];\n    if (epsilon3 == null) {\n      this.epsilon = ENGINE.backend.epsilon();\n    }\n  }\n  applyGradients(variableGradients) {\n    const variableNames = Array.isArray(variableGradients) ? variableGradients.map((item) => item.name) : Object.keys(variableGradients);\n    variableNames.forEach((name, i2) => {\n      const value = ENGINE.registeredVariables[name];\n      const trainable = false;\n      if (this.accumulatedGrads[i2] == null) {\n        this.accumulatedGrads[i2] = {\n          originalName: `${name}/accum_grad`,\n          variable: tidy(() => zerosLike(value).variable(trainable))\n        };\n      }\n      if (this.accumulatedUpdates[i2] == null) {\n        this.accumulatedUpdates[i2] = {\n          originalName: `${name}/accum_var`,\n          variable: tidy(() => zerosLike(value).variable(trainable))\n        };\n      }\n      const gradient = Array.isArray(variableGradients) ? variableGradients[i2].tensor : variableGradients[name];\n      if (gradient == null) {\n        return;\n      }\n      const accumulatedGrad = this.accumulatedGrads[i2].variable;\n      const accumulatedUpdate = this.accumulatedUpdates[i2].variable;\n      tidy(() => {\n        const newAccumulatedGrad = add2(mul(accumulatedGrad, this.rho), mul(square(gradient), 1 - this.rho));\n        const updates = mul(div(sqrt(add2(accumulatedUpdate, this.epsilon)), sqrt(add2(accumulatedGrad, this.epsilon))), gradient);\n        const newAccumulatedUpdate = add2(mul(accumulatedUpdate, this.rho), mul(square(updates), 1 - this.rho));\n        accumulatedGrad.assign(newAccumulatedGrad);\n        accumulatedUpdate.assign(newAccumulatedUpdate);\n        const newValue = add2(mul(updates, -this.learningRate), value);\n        value.assign(newValue);\n      });\n    });\n    this.incrementIterations();\n  }\n  dispose() {\n    if (this.accumulatedUpdates != null) {\n      dispose(this.accumulatedGrads.map((v) => v.variable));\n      dispose(this.accumulatedUpdates.map((v) => v.variable));\n    }\n  }\n  async getWeights() {\n    const variables = [...this.accumulatedGrads, ...this.accumulatedUpdates];\n    return [await this.saveIterations()].concat(variables.map((v) => ({ name: v.originalName, tensor: v.variable })));\n  }\n  async setWeights(weightValues) {\n    weightValues = await this.extractIterations(weightValues);\n    const variableCount = weightValues.length / 2;\n    const trainable = false;\n    this.accumulatedGrads = weightValues.slice(0, variableCount).map((v) => ({\n      originalName: v.name,\n      variable: v.tensor.variable(trainable)\n    }));\n    this.accumulatedUpdates = weightValues.slice(variableCount, variableCount * 2).map((v) => ({\n      originalName: v.name,\n      variable: v.tensor.variable(trainable)\n    }));\n  }\n  getConfig() {\n    return {\n      \"learningRate\": this.learningRate,\n      \"rho\": this.rho,\n      \"epsilon\": this.epsilon\n    };\n  }\n  static fromConfig(cls, config) {\n    return new cls(config[\"learningRate\"], config[\"rho\"], config[\"epsilon\"]);\n  }\n};\nAdadeltaOptimizer.className = \"Adadelta\";\nregisterClass(AdadeltaOptimizer);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/adagrad_optimizer.js\nvar AdagradOptimizer = class extends Optimizer {\n  constructor(learningRate, initialAccumulatorValue = 0.1) {\n    super();\n    this.learningRate = learningRate;\n    this.initialAccumulatorValue = initialAccumulatorValue;\n    this.accumulatedGrads = [];\n  }\n  applyGradients(variableGradients) {\n    const variableNames = Array.isArray(variableGradients) ? variableGradients.map((item) => item.name) : Object.keys(variableGradients);\n    variableNames.forEach((name, i2) => {\n      const value = ENGINE.registeredVariables[name];\n      if (this.accumulatedGrads[i2] == null) {\n        const trainable = false;\n        this.accumulatedGrads[i2] = {\n          originalName: `${name}/accumulator`,\n          variable: tidy(() => fill(value.shape, this.initialAccumulatorValue).variable(trainable))\n        };\n      }\n      const gradient = Array.isArray(variableGradients) ? variableGradients[i2].tensor : variableGradients[name];\n      if (gradient == null) {\n        return;\n      }\n      const accumulatedGrad = this.accumulatedGrads[i2].variable;\n      tidy(() => {\n        const newAccumulatedGrad = add2(accumulatedGrad, square(gradient));\n        accumulatedGrad.assign(newAccumulatedGrad);\n        const newValue = add2(mul(div(gradient, sqrt(add2(newAccumulatedGrad, ENGINE.backend.epsilon()))), -this.learningRate), value);\n        value.assign(newValue);\n      });\n    });\n    this.incrementIterations();\n  }\n  dispose() {\n    if (this.accumulatedGrads != null) {\n      dispose(this.accumulatedGrads.map((v) => v.variable));\n    }\n  }\n  async getWeights() {\n    return [await this.saveIterations()].concat(this.accumulatedGrads.map((v) => ({ name: v.originalName, tensor: v.variable })));\n  }\n  async setWeights(weightValues) {\n    weightValues = await this.extractIterations(weightValues);\n    const trainable = false;\n    this.accumulatedGrads = weightValues.map((v) => ({ originalName: v.name, variable: v.tensor.variable(trainable) }));\n  }\n  getConfig() {\n    return {\n      \"learningRate\": this.learningRate,\n      \"initialAccumulatorValue\": this.initialAccumulatorValue\n    };\n  }\n  static fromConfig(cls, config) {\n    return new cls(config[\"learningRate\"], config[\"initialAccumulatorValue\"]);\n  }\n};\nAdagradOptimizer.className = \"Adagrad\";\nregisterClass(AdagradOptimizer);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/adam_optimizer.js\nvar AdamOptimizer = class extends Optimizer {\n  constructor(learningRate, beta1, beta2, epsilon3 = null) {\n    super();\n    this.learningRate = learningRate;\n    this.beta1 = beta1;\n    this.beta2 = beta2;\n    this.epsilon = epsilon3;\n    this.accumulatedFirstMoment = [];\n    this.accumulatedSecondMoment = [];\n    tidy(() => {\n      this.accBeta1 = scalar(beta1).variable();\n      this.accBeta2 = scalar(beta2).variable();\n    });\n    if (epsilon3 == null) {\n      this.epsilon = ENGINE.backend.epsilon();\n    }\n  }\n  applyGradients(variableGradients) {\n    const varNames = Array.isArray(variableGradients) ? variableGradients.map((v) => v.name) : Object.keys(variableGradients);\n    tidy(() => {\n      const oneMinusAccBeta1 = sub(1, this.accBeta1);\n      const oneMinusAccBeta2 = sub(1, this.accBeta2);\n      varNames.forEach((name, i2) => {\n        const value = ENGINE.registeredVariables[name];\n        const trainable = false;\n        if (this.accumulatedFirstMoment[i2] == null) {\n          this.accumulatedFirstMoment[i2] = {\n            originalName: `${name}/m`,\n            variable: tidy(() => zerosLike(value).variable(trainable))\n          };\n        }\n        if (this.accumulatedSecondMoment[i2] == null) {\n          this.accumulatedSecondMoment[i2] = {\n            originalName: `${name}/v`,\n            variable: tidy(() => zerosLike(value).variable(trainable))\n          };\n        }\n        const gradient = Array.isArray(variableGradients) ? variableGradients[i2].tensor : variableGradients[name];\n        if (gradient == null) {\n          return;\n        }\n        const firstMoment = this.accumulatedFirstMoment[i2].variable;\n        const secondMoment = this.accumulatedSecondMoment[i2].variable;\n        const newFirstMoment = add2(mul(firstMoment, this.beta1), mul(gradient, 1 - this.beta1));\n        const newSecondMoment = add2(mul(secondMoment, this.beta2), mul(square(gradient), 1 - this.beta2));\n        const biasCorrectedFirstMoment = div(newFirstMoment, oneMinusAccBeta1);\n        const biasCorrectedSecondMoment = div(newSecondMoment, oneMinusAccBeta2);\n        firstMoment.assign(newFirstMoment);\n        secondMoment.assign(newSecondMoment);\n        const newValue = add2(mul(div(biasCorrectedFirstMoment, add2(sqrt(biasCorrectedSecondMoment), this.epsilon)), -this.learningRate), value);\n        value.assign(newValue);\n      });\n      this.accBeta1.assign(mul(this.accBeta1, this.beta1));\n      this.accBeta2.assign(mul(this.accBeta2, this.beta2));\n    });\n    this.incrementIterations();\n  }\n  dispose() {\n    this.accBeta1.dispose();\n    this.accBeta2.dispose();\n    if (this.accumulatedFirstMoment != null) {\n      dispose(this.accumulatedFirstMoment.map((v) => v.variable));\n    }\n    if (this.accumulatedSecondMoment != null) {\n      dispose(this.accumulatedSecondMoment.map((v) => v.variable));\n    }\n  }\n  async getWeights() {\n    const variables = [...this.accumulatedFirstMoment, ...this.accumulatedSecondMoment];\n    return [await this.saveIterations()].concat(variables.map((v) => ({ name: v.originalName, tensor: v.variable })));\n  }\n  async setWeights(weightValues) {\n    weightValues = await this.extractIterations(weightValues);\n    tidy(() => {\n      this.accBeta1.assign(pow(this.beta1, this.iterations_ + 1));\n      this.accBeta2.assign(pow(this.beta2, this.iterations_ + 1));\n    });\n    const variableCount = weightValues.length / 2;\n    const trainable = false;\n    this.accumulatedFirstMoment = weightValues.slice(0, variableCount).map((v) => ({\n      originalName: v.name,\n      variable: v.tensor.variable(trainable)\n    }));\n    this.accumulatedSecondMoment = weightValues.slice(variableCount, variableCount * 2).map((v) => ({\n      originalName: v.name,\n      variable: v.tensor.variable(trainable)\n    }));\n  }\n  getConfig() {\n    return {\n      \"learningRate\": this.learningRate,\n      \"beta1\": this.beta1,\n      \"beta2\": this.beta2,\n      \"epsilon\": this.epsilon\n    };\n  }\n  static fromConfig(cls, config) {\n    return new cls(config[\"learningRate\"], config[\"beta1\"], config[\"beta2\"], config[\"epsilon\"]);\n  }\n};\nAdamOptimizer.className = \"Adam\";\nregisterClass(AdamOptimizer);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/adamax_optimizer.js\nvar AdamaxOptimizer = class extends Optimizer {\n  constructor(learningRate, beta1, beta2, epsilon3 = null, decay = 0) {\n    super();\n    this.learningRate = learningRate;\n    this.beta1 = beta1;\n    this.beta2 = beta2;\n    this.epsilon = epsilon3;\n    this.decay = decay;\n    this.accumulatedFirstMoment = [];\n    this.accumulatedWeightedInfNorm = [];\n    tidy(() => {\n      this.iteration = scalar(0).variable();\n      this.accBeta1 = scalar(beta1).variable();\n    });\n    if (epsilon3 == null) {\n      this.epsilon = ENGINE.backend.epsilon();\n    }\n  }\n  applyGradients(variableGradients) {\n    const variableNames = Array.isArray(variableGradients) ? variableGradients.map((item) => item.name) : Object.keys(variableGradients);\n    tidy(() => {\n      const oneMinusAccBeta1 = sub(1, this.accBeta1);\n      const lr = div(-this.learningRate, add2(mul(this.iteration, this.decay), 1));\n      variableNames.forEach((name, i2) => {\n        const value = ENGINE.registeredVariables[name];\n        const trainable = false;\n        if (this.accumulatedFirstMoment[i2] == null) {\n          this.accumulatedFirstMoment[i2] = {\n            originalName: `${name}/m`,\n            variable: zerosLike(value).variable(trainable)\n          };\n        }\n        if (this.accumulatedWeightedInfNorm[i2] == null) {\n          this.accumulatedWeightedInfNorm[i2] = {\n            originalName: `${name}/v`,\n            variable: zerosLike(value).variable(trainable)\n          };\n        }\n        const gradient = Array.isArray(variableGradients) ? variableGradients[i2].tensor : variableGradients[name];\n        if (gradient == null) {\n          return;\n        }\n        const firstMoment = this.accumulatedFirstMoment[i2].variable;\n        const weightedInfNorm = this.accumulatedWeightedInfNorm[i2].variable;\n        const newFirstMoment = add2(mul(firstMoment, this.beta1), mul(gradient, 1 - this.beta1));\n        const ut0 = mul(weightedInfNorm, this.beta2);\n        const ut1 = abs(gradient);\n        const newWeightedInfNorm = maximum(ut0, ut1);\n        firstMoment.assign(newFirstMoment);\n        weightedInfNorm.assign(newWeightedInfNorm);\n        const newValue = add2(mul(div(lr, oneMinusAccBeta1), div(newFirstMoment, add2(newWeightedInfNorm, this.epsilon))), value);\n        value.assign(newValue);\n      });\n      this.iteration.assign(add2(this.iteration, 1));\n      this.accBeta1.assign(mul(this.accBeta1, this.beta1));\n    });\n    this.incrementIterations();\n  }\n  dispose() {\n    this.accBeta1.dispose();\n    this.iteration.dispose();\n    if (this.accumulatedFirstMoment != null) {\n      dispose(this.accumulatedFirstMoment.map((v) => v.variable));\n    }\n    if (this.accumulatedWeightedInfNorm != null) {\n      dispose(this.accumulatedWeightedInfNorm.map((v) => v.variable));\n    }\n  }\n  async getWeights() {\n    throw new Error(\"getWeights() is not implemented for Adamax yet.\");\n  }\n  async setWeights(weightValues) {\n    throw new Error(\"setWeights() is not implemented for Adamax yet.\");\n  }\n  getConfig() {\n    return {\n      \"learningRate\": this.learningRate,\n      \"beta1\": this.beta1,\n      \"beta2\": this.beta2,\n      \"epsilon\": this.epsilon,\n      \"decay\": this.decay\n    };\n  }\n  static fromConfig(cls, config) {\n    return new cls(config[\"learningRate\"], config[\"beta1\"], config[\"beta2\"], config[\"epsilon\"], config[\"decay\"]);\n  }\n};\nAdamaxOptimizer.className = \"Adamax\";\nregisterClass(AdamaxOptimizer);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/sgd_optimizer.js\nvar SGDOptimizer = class extends Optimizer {\n  constructor(learningRate) {\n    super();\n    this.learningRate = learningRate;\n    this.setLearningRate(learningRate);\n  }\n  applyGradients(variableGradients) {\n    const varNames = Array.isArray(variableGradients) ? variableGradients.map((v) => v.name) : Object.keys(variableGradients);\n    varNames.forEach((name, i2) => {\n      const gradient = Array.isArray(variableGradients) ? variableGradients[i2].tensor : variableGradients[name];\n      if (gradient == null) {\n        return;\n      }\n      const value = ENGINE.registeredVariables[name];\n      tidy(() => {\n        const newValue = add2(mul(this.c, gradient), value);\n        value.assign(newValue);\n      });\n    });\n    this.incrementIterations();\n  }\n  setLearningRate(learningRate) {\n    this.learningRate = learningRate;\n    if (this.c != null) {\n      this.c.dispose();\n    }\n    this.c = keep(scalar(-learningRate));\n  }\n  dispose() {\n    this.c.dispose();\n  }\n  async getWeights() {\n    return [await this.saveIterations()];\n  }\n  async setWeights(weightValues) {\n    weightValues = await this.extractIterations(weightValues);\n    if (weightValues.length !== 0) {\n      throw new Error(\"SGD optimizer does not have settable weights.\");\n    }\n  }\n  getConfig() {\n    return { \"learningRate\": this.learningRate };\n  }\n  static fromConfig(cls, config) {\n    return new cls(config[\"learningRate\"]);\n  }\n};\nSGDOptimizer.className = \"SGD\";\nregisterClass(SGDOptimizer);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/momentum_optimizer.js\nvar MomentumOptimizer = class extends SGDOptimizer {\n  constructor(learningRate, momentum, useNesterov = false) {\n    super(learningRate);\n    this.learningRate = learningRate;\n    this.momentum = momentum;\n    this.useNesterov = useNesterov;\n    this.accumulations = [];\n    this.m = scalar(this.momentum);\n  }\n  applyGradients(variableGradients) {\n    const variableNames = Array.isArray(variableGradients) ? variableGradients.map((item) => item.name) : Object.keys(variableGradients);\n    variableNames.forEach((name, i2) => {\n      const value = ENGINE.registeredVariables[name];\n      if (this.accumulations[i2] == null) {\n        const trainable = false;\n        this.accumulations[i2] = {\n          originalName: `${name}/momentum`,\n          variable: tidy(() => zerosLike(value).variable(trainable))\n        };\n      }\n      const accumulation = this.accumulations[i2].variable;\n      const gradient = Array.isArray(variableGradients) ? variableGradients[i2].tensor : variableGradients[name];\n      if (gradient == null) {\n        return;\n      }\n      tidy(() => {\n        let newValue;\n        const newAccumulation = add2(mul(this.m, accumulation), gradient);\n        if (this.useNesterov) {\n          newValue = add2(mul(this.c, add2(gradient, mul(newAccumulation, this.m))), value);\n        } else {\n          newValue = add2(mul(this.c, newAccumulation), value);\n        }\n        accumulation.assign(newAccumulation);\n        value.assign(newValue);\n      });\n    });\n    this.incrementIterations();\n  }\n  dispose() {\n    this.m.dispose();\n    if (this.accumulations != null) {\n      dispose(this.accumulations.map((v) => v.variable));\n    }\n  }\n  setMomentum(momentum) {\n    this.momentum = momentum;\n  }\n  async getWeights() {\n    return [await this.saveIterations()].concat(this.accumulations.map((v) => ({ name: v.originalName, tensor: v.variable })));\n  }\n  async setWeights(weightValues) {\n    weightValues = await this.extractIterations(weightValues);\n    const trainable = false;\n    this.accumulations = weightValues.map((v) => ({ originalName: v.name, variable: v.tensor.variable(trainable) }));\n  }\n  getConfig() {\n    return {\n      \"learningRate\": this.learningRate,\n      \"momentum\": this.momentum,\n      \"useNesterov\": this.useNesterov\n    };\n  }\n  static fromConfig(cls, config) {\n    return new cls(config[\"learningRate\"], config[\"momentum\"], config[\"useNesterov\"]);\n  }\n};\nMomentumOptimizer.className = \"Momentum\";\nregisterClass(MomentumOptimizer);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/rmsprop_optimizer.js\nvar RMSPropOptimizer = class extends Optimizer {\n  constructor(learningRate, decay = 0.9, momentum = 0, epsilon3 = null, centered = false) {\n    super();\n    this.learningRate = learningRate;\n    this.decay = decay;\n    this.momentum = momentum;\n    this.epsilon = epsilon3;\n    this.accumulatedMeanSquares = [];\n    this.accumulatedMoments = [];\n    this.accumulatedMeanGrads = [];\n    this.centered = centered;\n    if (epsilon3 == null) {\n      this.epsilon = ENGINE.backend.epsilon();\n    }\n    if (learningRate == null) {\n      throw new Error(`learningRate for RMSPropOptimizer must be defined.`);\n    }\n  }\n  applyGradients(variableGradients) {\n    const variableNames = Array.isArray(variableGradients) ? variableGradients.map((item) => item.name) : Object.keys(variableGradients);\n    variableNames.forEach((name, i2) => {\n      const value = ENGINE.registeredVariables[name];\n      const trainable = false;\n      if (this.accumulatedMeanSquares[i2] == null) {\n        this.accumulatedMeanSquares[i2] = {\n          originalName: `${name}/rms`,\n          variable: tidy(() => zerosLike(value).variable(trainable))\n        };\n      }\n      if (this.accumulatedMoments[i2] == null) {\n        this.accumulatedMoments[i2] = {\n          originalName: `${name}/momentum`,\n          variable: tidy(() => zerosLike(value).variable(trainable))\n        };\n      }\n      if (this.accumulatedMeanGrads[i2] == null && this.centered) {\n        this.accumulatedMeanGrads[i2] = {\n          originalName: `${name}/mg`,\n          variable: tidy(() => zerosLike(value).variable(trainable))\n        };\n      }\n      const gradient = Array.isArray(variableGradients) ? variableGradients[i2].tensor : variableGradients[name];\n      if (gradient == null) {\n        return;\n      }\n      const accumulatedMeanSquare = this.accumulatedMeanSquares[i2].variable;\n      const accumulatedMoments = this.accumulatedMoments[i2].variable;\n      tidy(() => {\n        const newAccumulatedMeanSquare = add2(mul(accumulatedMeanSquare, this.decay), mul(square(gradient), 1 - this.decay));\n        if (this.centered) {\n          const accumulatedMeanGrad = this.accumulatedMeanGrads[i2].variable;\n          const newAccumulatedMeanGrad = add2(mul(accumulatedMeanGrad, this.decay), mul(gradient, 1 - this.decay));\n          const gradContribution = div(mul(gradient, this.learningRate), sqrt(sub(newAccumulatedMeanSquare, add2(square(newAccumulatedMeanGrad), this.epsilon))));\n          const newAccumulatedMoments = add2(mul(accumulatedMoments, this.momentum), gradContribution);\n          accumulatedMeanSquare.assign(newAccumulatedMeanSquare);\n          accumulatedMeanGrad.assign(newAccumulatedMeanGrad);\n          accumulatedMoments.assign(newAccumulatedMoments);\n          const newValue = sub(value, newAccumulatedMoments);\n          value.assign(newValue);\n        } else {\n          const newAccumulatedMeanSquare2 = add2(mul(accumulatedMeanSquare, this.decay), mul(square(gradient), 1 - this.decay));\n          const newAccumulatedMoments = add2(mul(accumulatedMoments, this.momentum), div(mul(gradient, this.learningRate), sqrt(add2(newAccumulatedMeanSquare2, this.epsilon))));\n          accumulatedMeanSquare.assign(newAccumulatedMeanSquare2);\n          accumulatedMoments.assign(newAccumulatedMoments);\n          const newValue = sub(value, newAccumulatedMoments);\n          value.assign(newValue);\n        }\n      });\n    });\n    this.incrementIterations();\n  }\n  dispose() {\n    if (this.accumulatedMeanSquares != null) {\n      dispose(this.accumulatedMeanSquares.map((v) => v.variable));\n    }\n    if (this.accumulatedMeanGrads != null && this.centered) {\n      dispose(this.accumulatedMeanGrads.map((v) => v.variable));\n    }\n    if (this.accumulatedMoments != null) {\n      dispose(this.accumulatedMoments.map((v) => v.variable));\n    }\n  }\n  async getWeights() {\n    const variables = [...this.accumulatedMeanSquares, ...this.accumulatedMoments];\n    if (this.centered) {\n      variables.push(...this.accumulatedMeanGrads);\n    }\n    return [await this.saveIterations()].concat(variables.map((v) => ({ name: v.originalName, tensor: v.variable })));\n  }\n  async setWeights(weightValues) {\n    weightValues = await this.extractIterations(weightValues);\n    const variableCount = this.centered ? weightValues.length / 3 : weightValues.length / 2;\n    const trainable = false;\n    this.accumulatedMeanSquares = weightValues.slice(0, variableCount).map((v) => ({\n      originalName: v.name,\n      variable: v.tensor.variable(trainable)\n    }));\n    this.accumulatedMoments = weightValues.slice(variableCount, variableCount * 2).map((v) => ({\n      originalName: v.name,\n      variable: v.tensor.variable(trainable)\n    }));\n    if (this.centered) {\n      this.accumulatedMeanGrads = weightValues.slice(variableCount * 2, variableCount * 3).map((v) => ({\n        originalName: v.name,\n        variable: v.tensor.variable(trainable)\n      }));\n    }\n  }\n  getConfig() {\n    return {\n      \"learningRate\": this.learningRate,\n      \"decay\": this.decay,\n      \"momentum\": this.momentum,\n      \"epsilon\": this.epsilon,\n      \"centered\": this.centered\n    };\n  }\n  static fromConfig(cls, config) {\n    return new cls(config[\"learningRate\"], config[\"decay\"], config[\"momentum\"], config[\"epsilon\"], config[\"centered\"]);\n  }\n};\nRMSPropOptimizer.className = \"RMSProp\";\nregisterClass(RMSPropOptimizer);\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/optimizers/optimizer_constructors.js\nvar OptimizerConstructors = class {\n  static sgd(learningRate) {\n    return new SGDOptimizer(learningRate);\n  }\n  static momentum(learningRate, momentum, useNesterov = false) {\n    return new MomentumOptimizer(learningRate, momentum, useNesterov);\n  }\n  static rmsprop(learningRate, decay = 0.9, momentum = 0, epsilon3 = null, centered = false) {\n    return new RMSPropOptimizer(learningRate, decay, momentum, epsilon3, centered);\n  }\n  static adam(learningRate = 1e-3, beta1 = 0.9, beta2 = 0.999, epsilon3 = null) {\n    return new AdamOptimizer(learningRate, beta1, beta2, epsilon3);\n  }\n  static adadelta(learningRate = 1e-3, rho = 0.95, epsilon3 = null) {\n    return new AdadeltaOptimizer(learningRate, rho, epsilon3);\n  }\n  static adamax(learningRate = 2e-3, beta1 = 0.9, beta2 = 0.999, epsilon3 = null, decay = 0) {\n    return new AdamaxOptimizer(learningRate, beta1, beta2, epsilon3, decay);\n  }\n  static adagrad(learningRate, initialAccumulatorValue = 0.1) {\n    return new AdagradOptimizer(learningRate, initialAccumulatorValue);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/train.js\nvar train = {\n  sgd: OptimizerConstructors.sgd,\n  momentum: OptimizerConstructors.momentum,\n  adadelta: OptimizerConstructors.adadelta,\n  adagrad: OptimizerConstructors.adagrad,\n  rmsprop: OptimizerConstructors.rmsprop,\n  adamax: OptimizerConstructors.adamax,\n  adam: OptimizerConstructors.adam\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/browser_util.js\nvar delayCallback = (() => {\n  if (typeof requestAnimationFrame !== \"undefined\") {\n    return requestAnimationFrame;\n  } else if (typeof setImmediate !== \"undefined\") {\n    return setImmediate;\n  }\n  return (f) => f();\n})();\nfunction nextFrame() {\n  return new Promise((resolve) => delayCallback(() => resolve()));\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/backend_util.js\nvar backend_util_exports = {};\n__export(backend_util_exports, {\n  ERF_A1: () => ERF_A1,\n  ERF_A2: () => ERF_A2,\n  ERF_A3: () => ERF_A3,\n  ERF_A4: () => ERF_A4,\n  ERF_A5: () => ERF_A5,\n  ERF_P: () => ERF_P,\n  PARALLELIZE_THRESHOLD: () => PARALLELIZE_THRESHOLD,\n  SELU_SCALE: () => SELU_SCALE,\n  SELU_SCALEALPHA: () => SELU_SCALEALPHA,\n  applyActivation: () => applyActivation,\n  assertAndGetBroadcastShape: () => assertAndGetBroadcastShape,\n  assertAxesAreInnerMostDims: () => assertAxesAreInnerMostDims,\n  assertParamsConsistent: () => assertParamsConsistent,\n  assignToTypedArray: () => assignToTypedArray,\n  axesAreInnerMostDims: () => axesAreInnerMostDims,\n  calculateShapes: () => calculateShapes,\n  checkEinsumDimSizes: () => checkEinsumDimSizes,\n  checkPadOnDimRoundingMode: () => checkPadOnDimRoundingMode,\n  combineLocations: () => combineLocations,\n  complexWithEvenIndex: () => complexWithEvenIndex,\n  complexWithOddIndex: () => complexWithOddIndex,\n  computeConv2DInfo: () => computeConv2DInfo,\n  computeConv3DInfo: () => computeConv3DInfo,\n  computeDefaultPad: () => computeDefaultPad,\n  computeDilation2DInfo: () => computeDilation2DInfo,\n  computeOptimalWindowSize: () => computeOptimalWindowSize,\n  computeOutAndReduceShapes: () => computeOutAndReduceShapes,\n  computeOutShape: () => computeOutShape2,\n  computePool2DInfo: () => computePool2DInfo,\n  computePool3DInfo: () => computePool3DInfo,\n  convertConv2DDataFormat: () => convertConv2DDataFormat,\n  decodeEinsumEquation: () => decodeEinsumEquation,\n  eitherStridesOrDilationsAreOne: () => eitherStridesOrDilationsAreOne,\n  expandShapeToKeepDim: () => expandShapeToKeepDim,\n  exponent: () => exponent,\n  exponents: () => exponents,\n  fromStringArrayToUint8: () => fromStringArrayToUint8,\n  fromUint8ToStringArray: () => fromUint8ToStringArray,\n  getAxesPermutation: () => getAxesPermutation,\n  getBroadcastDims: () => getBroadcastDims,\n  getComplexWithIndex: () => getComplexWithIndex,\n  getEinsumComputePath: () => getEinsumComputePath,\n  getEinsumPermutation: () => getEinsumPermutation,\n  getFusedBiasGradient: () => getFusedBiasGradient,\n  getFusedDyActivation: () => getFusedDyActivation,\n  getImageCenter: () => getImageCenter,\n  getInnerMostAxes: () => getInnerMostAxes,\n  getPermuted: () => getPermuted,\n  getReductionAxes: () => getReductionAxes,\n  getReshaped: () => getReshaped,\n  getReshapedPermuted: () => getReshapedPermuted,\n  getSliceBeginCoords: () => getSliceBeginCoords,\n  getSliceSize: () => getSliceSize,\n  getSparseFillEmptyRowsIndicesDenseShapeMismatch: () => getSparseFillEmptyRowsIndicesDenseShapeMismatch,\n  getSparseFillEmptyRowsNegativeIndexErrorMessage: () => getSparseFillEmptyRowsNegativeIndexErrorMessage,\n  getSparseFillEmptyRowsOutOfRangeIndexErrorMessage: () => getSparseFillEmptyRowsOutOfRangeIndexErrorMessage,\n  getSparseReshapeEmptyTensorZeroOutputDimErrorMessage: () => getSparseReshapeEmptyTensorZeroOutputDimErrorMessage,\n  getSparseReshapeInputOutputMismatchErrorMessage: () => getSparseReshapeInputOutputMismatchErrorMessage,\n  getSparseReshapeInputOutputMultipleErrorMessage: () => getSparseReshapeInputOutputMultipleErrorMessage,\n  getSparseReshapeMultipleNegativeOneOutputDimErrorMessage: () => getSparseReshapeMultipleNegativeOneOutputDimErrorMessage,\n  getSparseReshapeNegativeOutputDimErrorMessage: () => getSparseReshapeNegativeOutputDimErrorMessage,\n  getSparseSegmentReductionIndicesOutOfRangeErrorMessage: () => getSparseSegmentReductionIndicesOutOfRangeErrorMessage,\n  getSparseSegmentReductionNegativeSegmentIdsErrorMessage: () => getSparseSegmentReductionNegativeSegmentIdsErrorMessage,\n  getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage: () => getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage,\n  getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage: () => getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage,\n  getUndoAxesPermutation: () => getUndoAxesPermutation,\n  isIdentityPermutation: () => isIdentityPermutation,\n  log: () => log,\n  mergeRealAndImagArrays: () => mergeRealAndImagArrays,\n  prepareAndValidate: () => prepareAndValidate,\n  prepareSplitSize: () => prepareSplitSize,\n  segment_util: () => segment_util_exports,\n  shouldFuse: () => shouldFuse,\n  slice_util: () => slice_util_exports,\n  splitRealAndImagArrays: () => splitRealAndImagArrays,\n  tupleValuesAreOne: () => tupleValuesAreOne,\n  upcastType: () => upcastType,\n  validateInput: () => validateInput,\n  validateUpdateShape: () => validateUpdateShape,\n  warn: () => warn\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/concat_util.js\nfunction assertParamsConsistent(shapes, axis) {\n  const rank = shapes[0].length;\n  shapes.forEach((shape, i2) => {\n    assert(shape.length === rank, () => `Error in concat${rank}D: rank of tensors[${i2}] must be the same as the rank of the rest (${rank})`);\n  });\n  assert(axis >= 0 && axis < rank, () => `Error in concat${rank}D: axis must be between 0 and ${rank - 1}.`);\n  const firstShape = shapes[0];\n  shapes.forEach((shape, i2) => {\n    for (let r2 = 0; r2 < rank; r2++) {\n      assert(r2 === axis || shape[r2] === firstShape[r2], () => `Error in concat${rank}D: Shape of tensors[${i2}] (${shape}) does not match the shape of the rest (${firstShape}) along the non-concatenated axis ${i2}.`);\n    }\n  });\n}\nfunction computeOutShape2(shapes, axis) {\n  const outputShape = shapes[0].slice();\n  for (let i2 = 1; i2 < shapes.length; i2++) {\n    outputShape[axis] += shapes[i2][axis];\n  }\n  return outputShape;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/reduce_util.js\nvar PARALLELIZE_THRESHOLD = 30;\nfunction computeOptimalWindowSize(inSize) {\n  if (inSize <= PARALLELIZE_THRESHOLD) {\n    return inSize;\n  }\n  return nearestDivisor(inSize, Math.floor(Math.sqrt(inSize)));\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/rotate_util.js\nfunction getImageCenter(center, imageHeight, imageWidth) {\n  const centerX = imageWidth * (typeof center === \"number\" ? center : center[0]);\n  const centerY = imageHeight * (typeof center === \"number\" ? center : center[1]);\n  return [centerX, centerY];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/array_ops_util.js\nfunction getReshaped(inputShape, blockShape, prod6, batchToSpace = true) {\n  let reshaped = [];\n  if (batchToSpace) {\n    reshaped = reshaped.concat(blockShape.slice(0));\n    reshaped.push(inputShape[0] / prod6);\n    reshaped = reshaped.concat(inputShape.slice(1));\n  } else {\n    reshaped = reshaped.concat(inputShape[0]);\n    const spatialLength = blockShape.length;\n    for (let i2 = 0; i2 < spatialLength; ++i2) {\n      reshaped = reshaped.concat([inputShape[i2 + 1] / blockShape[i2], blockShape[i2]]);\n    }\n    reshaped = reshaped.concat(inputShape.slice(spatialLength + 1));\n  }\n  return reshaped;\n}\nfunction getPermuted(reshapedRank, blockShapeRank, batchToSpace = true) {\n  const permuted = [];\n  if (batchToSpace) {\n    permuted.push(blockShapeRank);\n    for (let i2 = blockShapeRank + 1; i2 < reshapedRank; ++i2) {\n      if (i2 <= 2 * blockShapeRank) {\n        permuted.push(i2);\n        permuted.push(i2 - (blockShapeRank + 1));\n      } else {\n        permuted.push(i2);\n      }\n    }\n  } else {\n    const permutedBeforeBatch = [];\n    const permutedAfterBatch = [];\n    for (let i2 = 1; i2 < reshapedRank; ++i2) {\n      if (i2 >= blockShapeRank * 2 + 1 || i2 % 2 === 1) {\n        permutedAfterBatch.push(i2);\n      } else {\n        permutedBeforeBatch.push(i2);\n      }\n    }\n    permuted.push(...permutedBeforeBatch);\n    permuted.push(0);\n    permuted.push(...permutedAfterBatch);\n  }\n  return permuted;\n}\nfunction getReshapedPermuted(inputShape, blockShape, prod6, batchToSpace = true) {\n  const reshapedPermuted = [];\n  if (batchToSpace) {\n    reshapedPermuted.push(inputShape[0] / prod6);\n  } else {\n    reshapedPermuted.push(inputShape[0] * prod6);\n  }\n  for (let i2 = 1; i2 < inputShape.length; ++i2) {\n    if (i2 <= blockShape.length) {\n      if (batchToSpace) {\n        reshapedPermuted.push(blockShape[i2 - 1] * inputShape[i2]);\n      } else {\n        reshapedPermuted.push(inputShape[i2] / blockShape[i2 - 1]);\n      }\n    } else {\n      reshapedPermuted.push(inputShape[i2]);\n    }\n  }\n  return reshapedPermuted;\n}\nfunction getSliceBeginCoords(crops, blockShape) {\n  const sliceBeginCoords = [0];\n  for (let i2 = 0; i2 < blockShape; ++i2) {\n    sliceBeginCoords.push(crops[i2][0]);\n  }\n  return sliceBeginCoords;\n}\nfunction getSliceSize(uncroppedShape, crops, blockShape) {\n  const sliceSize = uncroppedShape.slice(0, 1);\n  for (let i2 = 0; i2 < blockShape; ++i2) {\n    sliceSize.push(uncroppedShape[i2 + 1] - crops[i2][0] - crops[i2][1]);\n  }\n  return sliceSize;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/selu_util.js\nvar SELU_SCALEALPHA = 1.7580993408473768;\nvar SELU_SCALE = 1.0507009873554805;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/erf_util.js\nvar ERF_P = 0.3275911;\nvar ERF_A1 = 0.254829592;\nvar ERF_A2 = -0.284496736;\nvar ERF_A3 = 1.421413741;\nvar ERF_A4 = -1.453152027;\nvar ERF_A5 = 1.061405429;\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/complex_util.js\nfunction mergeRealAndImagArrays(real5, imag5) {\n  if (real5.length !== imag5.length) {\n    throw new Error(`Cannot merge real and imag arrays of different lengths. real:${real5.length}, imag: ${imag5.length}.`);\n  }\n  const result = new Float32Array(real5.length * 2);\n  for (let i2 = 0; i2 < result.length; i2 += 2) {\n    result[i2] = real5[i2 / 2];\n    result[i2 + 1] = imag5[i2 / 2];\n  }\n  return result;\n}\nfunction splitRealAndImagArrays(complex5) {\n  const real5 = new Float32Array(complex5.length / 2);\n  const imag5 = new Float32Array(complex5.length / 2);\n  for (let i2 = 0; i2 < complex5.length; i2 += 2) {\n    real5[i2 / 2] = complex5[i2];\n    imag5[i2 / 2] = complex5[i2 + 1];\n  }\n  return { real: real5, imag: imag5 };\n}\nfunction complexWithEvenIndex(complex5) {\n  const len = Math.ceil(complex5.length / 4);\n  const real5 = new Float32Array(len);\n  const imag5 = new Float32Array(len);\n  for (let i2 = 0; i2 < complex5.length; i2 += 4) {\n    real5[Math.floor(i2 / 4)] = complex5[i2];\n    imag5[Math.floor(i2 / 4)] = complex5[i2 + 1];\n  }\n  return { real: real5, imag: imag5 };\n}\nfunction complexWithOddIndex(complex5) {\n  const len = Math.floor(complex5.length / 4);\n  const real5 = new Float32Array(len);\n  const imag5 = new Float32Array(len);\n  for (let i2 = 2; i2 < complex5.length; i2 += 4) {\n    real5[Math.floor(i2 / 4)] = complex5[i2];\n    imag5[Math.floor(i2 / 4)] = complex5[i2 + 1];\n  }\n  return { real: real5, imag: imag5 };\n}\nfunction getComplexWithIndex(complex5, index) {\n  const real5 = complex5[index * 2];\n  const imag5 = complex5[index * 2 + 1];\n  return { real: real5, imag: imag5 };\n}\nfunction assignToTypedArray(data, real5, imag5, index) {\n  data[index * 2] = real5;\n  data[index * 2 + 1] = imag5;\n}\nfunction exponents(n2, inverse) {\n  const real5 = new Float32Array(n2 / 2);\n  const imag5 = new Float32Array(n2 / 2);\n  for (let i2 = 0; i2 < Math.ceil(n2 / 2); i2++) {\n    const x = (inverse ? 2 : -2) * Math.PI * (i2 / n2);\n    real5[i2] = Math.cos(x);\n    imag5[i2] = Math.sin(x);\n  }\n  return { real: real5, imag: imag5 };\n}\nfunction exponent(k, n2, inverse) {\n  const x = (inverse ? 2 : -2) * Math.PI * (k / n2);\n  const real5 = Math.cos(x);\n  const imag5 = Math.sin(x);\n  return { real: real5, imag: imag5 };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/einsum_util.js\nvar ARROW = \"->\";\nvar ARROW_REGEX = /->/g;\nvar COMMA = \",\";\nvar ELLIPSIS = \"...\";\nfunction decodeEinsumEquation(equation, numTensors) {\n  equation = equation.replace(/\\s/g, \"\");\n  const numArrows = (equation.length - equation.replace(ARROW_REGEX, \"\").length) / ARROW.length;\n  if (numArrows < 1) {\n    throw new Error(\"Equations without an arrow are not supported.\");\n  } else if (numArrows > 1) {\n    throw new Error(`Equation must contain exactly one arrow (\"${ARROW}\").`);\n  }\n  const [inputString, outputString] = equation.split(ARROW);\n  assert(inputString.indexOf(ELLIPSIS) === -1, () => `The ellipsis notation (\"${ELLIPSIS}\") is not supported yet.`);\n  const inputTerms = inputString.split(COMMA);\n  const numInputs = inputTerms.length;\n  if (numTensors !== numInputs) {\n    throw new Error(`Expected ${numInputs} input tensors, received ${numTensors}`);\n  }\n  if (numInputs > 2) {\n    throw new Error(\"Support for more than 2 input tensors is not implemented yet.\");\n  }\n  const allDims = [];\n  for (let i2 = 0; i2 < outputString.length; ++i2) {\n    const dimName = outputString[i2];\n    if (!inputTerms.some((inputTerm) => inputTerm.indexOf(dimName) !== -1)) {\n      throw new Error(`Output subscripts contain the label ${dimName} not present in the input subscripts.`);\n    }\n    if (allDims.indexOf(dimName) === -1) {\n      allDims.push(dimName);\n    }\n  }\n  for (let i2 = 0; i2 < inputString.length; ++i2) {\n    const dimName = inputString[i2];\n    if (allDims.indexOf(dimName) === -1 && dimName !== COMMA) {\n      allDims.push(dimName);\n    }\n  }\n  const idDims = new Array(inputTerms.length);\n  for (let i2 = 0; i2 < numInputs; ++i2) {\n    if (new Set(inputTerms[i2].split(\"\")).size !== inputTerms[i2].length) {\n      throw new Error(`Found duplicate axes in input component ${inputTerms[i2]}. Support for duplicate axes in input is not implemented yet.`);\n    }\n    idDims[i2] = [];\n    for (let j = 0; j < inputTerms[i2].length; ++j) {\n      idDims[i2].push(allDims.indexOf(inputTerms[i2][j]));\n    }\n  }\n  const numDims = allDims.length;\n  const numOutDims = outputString.length;\n  const summedDims = [];\n  for (let i2 = numOutDims; i2 < numDims; ++i2) {\n    summedDims.push(i2);\n  }\n  return { allDims, summedDims, idDims };\n}\nfunction getEinsumPermutation(nDims, idDims) {\n  let permutationIndices = new Array(nDims);\n  permutationIndices.fill(-1);\n  for (let i2 = 0; i2 < idDims.length; ++i2) {\n    permutationIndices[idDims[i2]] = i2;\n  }\n  const expandDims7 = [];\n  for (let i2 = 0; i2 < nDims; ++i2) {\n    if (permutationIndices[i2] === -1) {\n      expandDims7.push(i2);\n    }\n  }\n  permutationIndices = permutationIndices.filter((d) => d !== -1);\n  return { permutationIndices, expandDims: expandDims7 };\n}\nfunction checkEinsumDimSizes(nDims, idDims, tensors) {\n  const dimSizes = new Array(nDims);\n  for (let i2 = 0; i2 < tensors.length; ++i2) {\n    const shape = tensors[i2].shape;\n    for (let j = 0; j < idDims[i2].length; ++j) {\n      if (dimSizes[idDims[i2][j]] === void 0) {\n        dimSizes[idDims[i2][j]] = shape[j];\n      } else {\n        assert(dimSizes[idDims[i2][j]] === shape[j], () => `Expected dimension ${dimSizes[idDims[i2][j]]} at axis ${j} of input shaped ${JSON.stringify(shape)}, but got dimension ${shape[j]}`);\n      }\n    }\n  }\n}\nfunction getEinsumComputePath(summedDims, idDims) {\n  const path = summedDims;\n  const steps = [];\n  let nSteps = 0;\n  if (summedDims.length === 0) {\n    path.push(-1);\n  }\n  nSteps = summedDims.length + 1;\n  for (let i2 = 0; i2 < nSteps; ++i2) {\n    steps.push([]);\n  }\n  const computedTermIndices = [];\n  for (let i2 = 0; i2 < path.length; ++i2) {\n    const summedDim = path[i2];\n    const termIndices = findTermsWithDim(idDims, summedDim);\n    for (const termIndex of termIndices) {\n      if (computedTermIndices.indexOf(termIndex) === -1) {\n        steps[i2].push(termIndex);\n        computedTermIndices.push(termIndex);\n      }\n    }\n  }\n  return { path, steps };\n}\nfunction isIdentityPermutation(perm) {\n  return perm.every((dim, index) => dim === index);\n}\nfunction findTermsWithDim(idDims, dim) {\n  const termIndices = [];\n  for (let i2 = 0; i2 < idDims.length; ++i2) {\n    if (idDims[i2].length === 0 || idDims[i2].indexOf(dim) !== -1 || dim === -1) {\n      termIndices.push(i2);\n    }\n  }\n  return termIndices;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/split_util.js\nfunction prepareSplitSize(x, numOrSizeSplits, axis = 0) {\n  let splitSizes = [];\n  if (typeof numOrSizeSplits === \"number\") {\n    assert(x.shape[axis] % numOrSizeSplits === 0, () => \"Number of splits must evenly divide the axis.\");\n    splitSizes = new Array(numOrSizeSplits).fill(x.shape[axis] / numOrSizeSplits);\n  } else {\n    const numOfNegs = numOrSizeSplits.reduce((count2, value) => {\n      if (value === -1) {\n        count2 += 1;\n      }\n      return count2;\n    }, 0);\n    assert(numOfNegs <= 1, () => \"There should be only one negative value in split array.\");\n    const negIndex = numOrSizeSplits.indexOf(-1);\n    if (negIndex !== -1) {\n      const total = numOrSizeSplits.reduce((a, b) => b > 0 ? a + b : a);\n      numOrSizeSplits[negIndex] = x.shape[axis] - total;\n    }\n    assert(x.shape[axis] === numOrSizeSplits.reduce((a, b) => a + b), () => \"The sum of sizes must match the size of the axis dimension.\");\n    splitSizes = numOrSizeSplits;\n  }\n  return splitSizes;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse/sparse_fill_empty_rows_util.js\nfunction getSparseFillEmptyRowsIndicesDenseShapeMismatch(indicesLength) {\n  return `Received SparseTensor with denseShape[0] = 0 but\n  indices.shape[0] = ${indicesLength}`;\n}\nfunction getSparseFillEmptyRowsNegativeIndexErrorMessage(index, value) {\n  return `indices(${index}, 0) is invalid: ${value} < 0`;\n}\nfunction getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(index, value, limit) {\n  return `indices(${index}, 0) is invalid: ${value} >= ${limit}`;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse/sparse_reshape_util.js\nfunction getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(dim1, dim2) {\n  return `only one output dimension may be -1, not both ${dim1} and ${dim2}`;\n}\nfunction getSparseReshapeNegativeOutputDimErrorMessage(dim, value) {\n  return `size ${dim} must be non-negative, not ${value}`;\n}\nfunction getSparseReshapeEmptyTensorZeroOutputDimErrorMessage() {\n  return \"reshape cannot infer the missing input size for an empty tensor unless all specified input sizes are non-zero\";\n}\nfunction getSparseReshapeInputOutputMultipleErrorMessage(inputShape, outputShape) {\n  const inputSize = sizeFromShape(inputShape);\n  const outputSize = sizeFromShape(outputShape);\n  return `Input to reshape is a SparseTensor with ${inputSize}\n  dense values, but the requested shape requires a multiple of ${outputSize}. inputShape=${inputShape} outputShape= ${outputShape}`;\n}\nfunction getSparseReshapeInputOutputMismatchErrorMessage(inputShape, outputShape) {\n  const inputSize = sizeFromShape(inputShape);\n  const outputSize = sizeFromShape(outputShape);\n  return `Input to reshape is a tensor with ${inputSize} dense values, but the requested shape has ${outputSize}. inputShape=${inputShape} outputShape=${outputShape}`;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/sparse/sparse_segment_reduction_util.js\nfunction getSparseSegmentReductionNegativeSegmentIdsErrorMessage() {\n  return `segment ids must be >= 0`;\n}\nfunction getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage() {\n  return `segment ids are not increasing`;\n}\nfunction getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(segmentId, outputRows) {\n  return `Segment id ${segmentId} out of range [0, ${outputRows}), possibly because segmentIds input is not sorted.`;\n}\nfunction getSparseSegmentReductionIndicesOutOfRangeErrorMessage(index, indexValue, inputRows) {\n  return `Bad: indices[${index}] == ${indexValue} out of range [0, ${inputRows})`;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/segment_util.js\nvar segment_util_exports = {};\n__export(segment_util_exports, {\n  collectGatherOpShapeInfo: () => collectGatherOpShapeInfo,\n  computeOutShape: () => computeOutShape3,\n  segOpComputeOptimalWindowSize: () => segOpComputeOptimalWindowSize\n});\nfunction segOpComputeOptimalWindowSize(inSize, numSegments) {\n  let done = false;\n  let res;\n  if (inSize <= PARALLELIZE_THRESHOLD) {\n    res = inSize;\n    done = true;\n  } else {\n    res = nearestDivisor(inSize, Math.floor(Math.sqrt(inSize)));\n  }\n  while (!done) {\n    if (res > numSegments || res === inSize) {\n      done = true;\n    } else {\n      res = nearestDivisor(inSize, res + 1);\n    }\n  }\n  return res;\n}\nfunction computeOutShape3(aShape, axis, numSegments) {\n  const outShape = [];\n  const rank = aShape.length;\n  for (let dim = 0; dim < rank; dim++) {\n    if (dim !== axis) {\n      outShape.push(aShape[dim]);\n    } else {\n      outShape.push(numSegments);\n    }\n  }\n  return outShape;\n}\nfunction collectGatherOpShapeInfo(x, indices, axis, batchDims) {\n  const indicesRank = indices.shape.length;\n  const xRank = x.shape.length;\n  if (batchDims !== 0) {\n    if (batchDims < -indicesRank || batchDims > indicesRank) {\n      throw new Error(`Expect batchDims in the range of [-${indicesRank}, ${indicesRank}], but got ${batchDims}`);\n    }\n  }\n  if (batchDims < 0) {\n    batchDims += indicesRank;\n  }\n  if (batchDims > xRank) {\n    throw new Error(`batchDims (${batchDims}) must be less than rank(x) (\n    ${xRank}).`);\n  }\n  if (axis < batchDims) {\n    throw new Error(`batchDims (${batchDims}) must be less than or equal to axis (${axis}).`);\n  }\n  for (let i2 = 0; i2 < batchDims; ++i2) {\n    if (x.shape[i2] !== indices.shape[i2]) {\n      throw new Error(`x.shape[${i2}]: ${x.shape[i2]} should be equal to indices.shape[${i2}]: ${indices.shape[i2]}.`);\n    }\n  }\n  const dimSize = x.shape[axis];\n  const outputShape = [];\n  let batchSize = 1;\n  let outerSize = 1;\n  let sliceSize = 1;\n  for (let i2 = 0; i2 < batchDims; ++i2) {\n    outputShape.push(x.shape[i2]);\n    batchSize *= x.shape[i2];\n  }\n  for (let i2 = batchDims; i2 < axis; i2++) {\n    outputShape.push(x.shape[i2]);\n    outerSize *= x.shape[i2];\n  }\n  for (let i2 = batchDims; i2 < indicesRank; i2++) {\n    outputShape.push(indices.shape[i2]);\n  }\n  for (let i2 = axis + 1; i2 < xRank; i2++) {\n    outputShape.push(x.shape[i2]);\n    sliceSize *= x.shape[i2];\n  }\n  return { batchSize, sliceSize, outerSize, dimSize, outputShape };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/backend_util.js\nfunction fromUint8ToStringArray(vals) {\n  try {\n    return vals.map((val) => decodeString(val));\n  } catch (err) {\n    throw new Error(`Failed to decode encoded string bytes into utf-8, error: ${err}`);\n  }\n}\nfunction fromStringArrayToUint8(strings) {\n  return strings.map((s2) => encodeString(s2));\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/backends/kernel_impls.js\nvar kernel_impls_exports = {};\n__export(kernel_impls_exports, {\n  nonMaxSuppressionV3Impl: () => nonMaxSuppressionV3Impl,\n  nonMaxSuppressionV4Impl: () => nonMaxSuppressionV4Impl,\n  nonMaxSuppressionV5Impl: () => nonMaxSuppressionV5Impl,\n  whereImpl: () => whereImpl\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Abs_grad.js\nvar absGradConfig = {\n  kernelName: Abs,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(dy, step(cast(x, \"float32\"), -1)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Acos_grad.js\nvar acosGradConfig = {\n  kernelName: Acos,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return {\n      x: () => {\n        const a = square(cast(x, \"float32\"));\n        const b = sqrt(sub(scalar(1), a));\n        return neg(div(dy, b));\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Acosh_grad.js\nvar acoshGradConfig = {\n  kernelName: Acosh,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return {\n      x: () => {\n        const a = sqrt(sub(square(cast(x, \"float32\")), 1));\n        return div(dy, a);\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Add_grad.js\nvar addGradConfig = {\n  kernelName: Add,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const outShape = assertAndGetBroadcastShape(a.shape, b.shape);\n    const derA = () => {\n      let res = dy;\n      const reduceAxes = getReductionAxes(a.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(res, a.shape);\n    };\n    const derB = () => {\n      let res = dy;\n      const reduceAxes = getReductionAxes(b.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(res, b.shape);\n    };\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/AddN_grad.js\nvar addNGradConfig = {\n  kernelName: AddN,\n  saveAllInputs: true,\n  gradFunc: (dy, saved) => {\n    const ders = {};\n    saved.forEach((_, i2) => {\n      ders[i2] = () => dy.clone();\n    });\n    return ders;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ArgMax_grad.js\nvar argMaxGradConfig = {\n  kernelName: ArgMax,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => zerosLike(x) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ArgMin_grad.js\nvar argMinGradConfig = {\n  kernelName: ArgMin,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => zerosLike(x) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Asin_grad.js\nvar asinGradConfig = {\n  kernelName: Asin,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, sqrt(sub(scalar(1), square(cast(x, \"float32\"))))) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Asinh_grad.js\nvar asinhGradConfig = {\n  kernelName: Asinh,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return {\n      x: () => {\n        const a = sqrt(add2(scalar(1), square(cast(x, \"float32\"))));\n        return div(dy, a);\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Atan2_grad.js\nvar atan2GradConfig = {\n  kernelName: Atan2,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const outShape = assertAndGetBroadcastShape(a.shape, b.shape);\n    const derA = () => {\n      const d = add2(square(a), square(b));\n      let res = mul(dy, div(b, d));\n      const reduceAxes = getReductionAxes(a.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(res, a.shape);\n    };\n    const derB = () => {\n      const d = add2(square(a), square(b));\n      let res = neg(mul(dy, div(a, d)));\n      const reduceAxes = getReductionAxes(b.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(res, b.shape);\n    };\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Atan_grad.js\nvar atanGradConfig = {\n  kernelName: Atan,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, add2(square(cast(x, \"float32\")), 1)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Atanh_grad.js\nvar atanhGradConfig = {\n  kernelName: Atanh,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, sub(scalar(1), square(cast(x, \"float32\")))) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool_3d_grad.js\nfunction avgPool3dGrad_(dy, input2, filterSize, strides, pad3, dimRoundingMode) {\n  const $dy = convertToTensor(dy, \"dy\", \"avgPool3dGrad\");\n  const $input = convertToTensor(input2, \"input\", \"avgPool3dGrad\");\n  let dy5D = $dy;\n  let input5D = $input;\n  let reshapedTo5D = false;\n  if ($input.rank === 4) {\n    reshapedTo5D = true;\n    dy5D = reshape($dy, [1, $dy.shape[0], $dy.shape[1], $dy.shape[2], $dy.shape[3]]);\n    input5D = reshape($input, [\n      1,\n      $input.shape[0],\n      $input.shape[1],\n      $input.shape[2],\n      $input.shape[3]\n    ]);\n  }\n  assert(dy5D.rank === 5, () => `Error in avgPool3dGrad: dy must be rank 5 but got rank ${dy5D.rank}.`);\n  assert(input5D.rank === 5, () => `Error in avgPool3dGrad: input must be rank 5 but got rank ${input5D.rank}.`);\n  checkPadOnDimRoundingMode(\"avgPool3dGrad\", pad3, dimRoundingMode);\n  const inputs = { dy: dy5D, input: input5D };\n  const attrs = { filterSize, strides, pad: pad3, dimRoundingMode };\n  const res = ENGINE.runKernel(AvgPool3DGrad, inputs, attrs);\n  if (reshapedTo5D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);\n  }\n  return res;\n}\nvar avgPool3dGrad = op({ avgPool3dGrad_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/AvgPool3D_grad.js\nvar avgPool3DGradConfig = {\n  kernelName: AvgPool3D,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n    return {\n      x: () => avgPool3dGrad(dy, x, filterSize, strides, pad3, dimRoundingMode)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/avg_pool_grad.js\nfunction avgPoolGrad_(dy, input2, filterSize, strides, pad3) {\n  const $dy = convertToTensor(dy, \"dy\", \"avgPoolGrad\");\n  const $input = convertToTensor(input2, \"input\", \"avgPoolGrad\");\n  assert($input.rank === $dy.rank, () => `Rank of input (${$input.rank}) does not match rank of dy (${$dy.rank})`);\n  let input4D = $input;\n  let dy4D = $dy;\n  let reshapedTo4D = false;\n  if ($input.rank === 3) {\n    reshapedTo4D = true;\n    input4D = reshape($input, [1, $input.shape[0], $input.shape[1], $input.shape[2]]);\n    dy4D = reshape($dy, [1, $dy.shape[0], $dy.shape[1], $dy.shape[2]]);\n  }\n  assert(dy4D.rank === 4, () => `Error in avgPoolGrad: dy must be rank 4 but got rank ${dy4D.rank}.`);\n  assert(input4D.rank === 4, () => `Error in avgPoolGrad: input must be rank 4 but got rank ${input4D.rank}.`);\n  const inputs = { dy: dy4D, input: input4D };\n  const attrs = { filterSize, strides, pad: pad3 };\n  const res = ENGINE.runKernel(AvgPoolGrad, inputs, attrs);\n  if (reshapedTo4D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3]]);\n  }\n  return res;\n}\nvar avgPoolGrad = op({ avgPoolGrad_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/AvgPool_grad.js\nvar avgPoolGradConfig = {\n  kernelName: AvgPool,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { filterSize, strides, pad: pad3 } = attrs;\n    return { x: () => avgPoolGrad(dy, x, filterSize, strides, pad3) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/BatchMatMul_grad.js\nvar batchMatMulGradConfig = {\n  kernelName: BatchMatMul,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [a, b] = saved;\n    const { transposeA, transposeB } = attrs;\n    if (!transposeA && !transposeB) {\n      return {\n        a: () => matMul(dy, b, false, true),\n        b: () => matMul(a, dy, true, false)\n      };\n    } else if (!transposeA && transposeB) {\n      return {\n        a: () => matMul(dy, b, false, false),\n        b: () => matMul(dy, a, true, false)\n      };\n    } else if (transposeA && !transposeB) {\n      return {\n        a: () => matMul(b, dy, false, true),\n        b: () => matMul(a, dy, false, false)\n      };\n    } else {\n      return {\n        a: () => matMul(b, dy, true, true),\n        b: () => matMul(dy, a, true, true)\n      };\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/BatchToSpaceND_grad.js\nvar batchToSpaceNDGradConfig = {\n  kernelName: BatchToSpaceND,\n  gradFunc: (dy, saved, attrs) => {\n    const { blockShape, crops } = attrs;\n    return { x: () => spaceToBatchND(dy, blockShape, crops) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/BroadcastTo_grad.js\nvar broadcastToGradConfig = {\n  kernelName: BroadcastTo,\n  gradFunc: (dy, saved, attrs) => {\n    const broadCastToAttrs = attrs;\n    const inputShape = broadCastToAttrs.inputShape;\n    const outputShape = broadCastToAttrs.shape;\n    const reps = Array.from(outputShape);\n    for (let i2 = inputShape.length - 1; i2 >= 0; i2--) {\n      if (inputShape[i2] === outputShape[i2]) {\n        reps[i2] = 1;\n      } else if (inputShape[i2] !== 1) {\n        throw new Error(`broadcastTo(): [${inputShape}] cannot be broadcast to [${outputShape}].`);\n      }\n    }\n    const axes = [];\n    for (let i2 = 0; i2 < reps.length; i2++) {\n      if (reps[i2] > 1) {\n        axes.push(i2);\n      }\n    }\n    return { x: () => sum2(dy, axes, true) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Cast_grad.js\nvar castGradConfig = {\n  kernelName: Cast,\n  gradFunc: (dy) => {\n    return { x: () => dy.clone() };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Ceil_grad.js\nvar ceilGradConfig = {\n  kernelName: Ceil,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ClipByValue_grad.js\nvar clipByValueGradConfig = {\n  kernelName: ClipByValue,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { clipValueMin, clipValueMax } = attrs;\n    return {\n      x: () => where(logicalAnd(greaterEqual(x, clipValueMin), lessEqual(x, clipValueMax)), dy, zerosLike(dy))\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ComplexAbs_grad.js\nvar complexAbsGradConfig = {\n  kernelName: ComplexAbs,\n  inputsToSave: [\"x\"],\n  gradFunc: absGradConfig.gradFunc\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Concat_grad.js\nvar concatGradConfig = {\n  kernelName: Concat,\n  saveAllInputs: true,\n  gradFunc: (dy, saved, attrs) => {\n    const shapes = saved.map((t2) => t2.shape);\n    const { axis } = attrs;\n    const $axis = parseAxisParam(axis, saved[0].shape)[0];\n    const sizeSplits = shapes.map((s2) => s2[$axis]);\n    const derTensors = split(dy, sizeSplits, $axis);\n    return derTensors.map((t2) => () => t2);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Conv2D_grad.js\nvar conv2DGradConfig = {\n  kernelName: Conv2D,\n  inputsToSave: [\"x\", \"filter\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x4D, $filter] = saved;\n    const { dilations, strides, pad: pad3, dataFormat } = attrs;\n    assert(tupleValuesAreOne(dilations), () => `Error in gradient of conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${dilations}'`);\n    return {\n      x: () => conv2DBackpropInput(x4D.shape, dy, $filter, strides, pad3, dataFormat),\n      filter: () => conv2DBackpropFilter(x4D, dy, $filter.shape, strides, pad3, dataFormat)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Conv2DBackpropInput_grad.js\nvar conv2DBackpropInputGradConfig = {\n  kernelName: Conv2DBackpropInput,\n  inputsToSave: [\"dy\", \"filter\"],\n  gradFunc: (ddx, saved, attrs) => {\n    const [dy, filter] = saved;\n    const { strides, pad: pad3, dataFormat, dimRoundingMode } = attrs;\n    return {\n      dy: () => conv2d(ddx, filter, strides, pad3, dataFormat, 1, dimRoundingMode),\n      filter: () => conv2DBackpropFilter(ddx, dy, filter.shape, strides, pad3, dataFormat, dimRoundingMode)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/conv3d_backprop_filter.js\nfunction conv3DBackpropFilter_(x, dy, filterShape, strides, pad3) {\n  let x5D = x;\n  if (x.rank === 4) {\n    x5D = reshape(x, [1, x.shape[0], x.shape[1], x.shape[2], x.shape[3]]);\n  }\n  let dy5D = dy;\n  if (dy5D.rank === 4) {\n    dy5D = reshape(dy, [1, dy.shape[0], dy.shape[1], dy.shape[2], dy.shape[3]]);\n  }\n  assert(x5D.rank === 5, () => `Error in conv3dDerFilter: input must be rank 5, but got shape ${x5D.shape}.`);\n  assert(dy5D.rank === 5, () => `Error in conv3dDerFilter: dy must be rank 5, but got shape ${dy5D.shape}.`);\n  assert(filterShape.length === 5, () => `Error in conv3dDerFilter: filterShape must be length 5, but got ${filterShape}.`);\n  assert(x5D.shape[4] === filterShape[3], () => `Error in conv3dDerFilter: depth of input ${x5D.shape[4]}) must match input depth in filter (${filterShape[3]}.`);\n  assert(dy5D.shape[4] === filterShape[4], () => `Error in conv3dDerFilter: depth of dy (${dy5D.shape[4]}) must match output depth for filter (${filterShape[4]}).`);\n  const inputs = { x: x5D, dy: dy5D };\n  const attrs = { strides, pad: pad3, filterShape };\n  return ENGINE.runKernel(Conv3DBackpropFilterV2, inputs, attrs);\n}\nvar conv3DBackpropFilter = op({ conv3DBackpropFilter_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Conv3D_grad.js\nvar conv3DGradConfig = {\n  kernelName: Conv3D,\n  inputsToSave: [\"x\", \"filter\"],\n  gradFunc: (dy, saved, attrs) => {\n    const { dilations, strides, pad: pad3 } = attrs;\n    assert(tupleValuesAreOne(dilations), () => `Error in gradient of conv3D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${dilations}'`);\n    const [x5D, $filter] = saved;\n    return {\n      x: () => conv3DBackpropInput(x5D.shape, dy, $filter, strides, pad3),\n      filter: () => conv3DBackpropFilter(x5D, dy, $filter.shape, strides, pad3)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Cos_grad.js\nvar cosGradConfig = {\n  kernelName: Cos,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(neg(sin(cast(x, \"float32\"))), dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Cosh_grad.js\nvar coshGradConfig = {\n  kernelName: Cosh,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(sinh(cast(x, \"float32\")), dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Cumsum_grad.js\nvar cumsumGradConfig = {\n  kernelName: Cumsum,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { axis, exclusive, reverse: reverse5 } = attrs;\n    return {\n      x: () => {\n        const permutation = getAxesPermutation([axis], x.rank);\n        let out = cumsum(dy, axis, exclusive, !reverse5);\n        if (permutation != null) {\n          out = transpose(out, permutation);\n        }\n        return out;\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/DepthwiseConv2dNative_grad.js\nvar depthwiseConv2dNativeGradConfig = {\n  kernelName: DepthwiseConv2dNative,\n  inputsToSave: [\"x\", \"filter\"],\n  gradFunc: (dy, saved, attrs) => {\n    const { dilations, strides, pad: pad3, dimRoundingMode } = attrs;\n    const $dilations = dilations == null ? [1, 1] : dilations;\n    assert(tupleValuesAreOne($dilations), () => `Error in gradient of depthwiseConv2dNative: dilation rates greater than 1 are not yet supported. Got dilations '${$dilations}'`);\n    const [x, filter] = saved;\n    assert(x.rank === 4, () => `Error in gradient of depthwiseConv2dNative: input must be rank 4, but got rank ${x.rank}.`);\n    assert(filter.rank === 4, () => `Error in gradient of depthwiseConv2dNative: filter must be rank 4, but got rank ${filter.rank}.`);\n    assert(x.shape[3] === filter.shape[2], () => `Error in gradient of depthwiseConv2d: number of input channels (${x.shape[3]}) must match the inChannels dimension in filter ${filter.shape[2]}.`);\n    assert(eitherStridesOrDilationsAreOne(strides, $dilations), () => `Error in gradient of depthwiseConv2d: Either strides or dilations must be  1. Got strides ${strides} and dilations '${$dilations}'.`);\n    checkPadOnDimRoundingMode(\"depthwiseConv2d\", pad3, dimRoundingMode);\n    return {\n      x: () => depthwiseConv2dNativeBackpropInput(x.shape, dy, filter, strides, pad3, $dilations, dimRoundingMode),\n      filter: () => depthwiseConv2dNativeBackpropFilter(x, dy, filter.shape, strides, pad3, $dilations, dimRoundingMode)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Dilation2D_grad.js\nvar dilation2dGradConfig = {\n  kernelName: Dilation2D,\n  inputsToSave: [\"x\", \"filter\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x, filter] = saved;\n    const inputInputs = { x, filter, dy };\n    const filterInputs = { x, filter, dy };\n    return {\n      x: () => ENGINE.runKernel(Dilation2DBackpropInput, inputInputs, attrs),\n      filter: () => ENGINE.runKernel(Dilation2DBackpropFilter, filterInputs, attrs)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Elu_grad.js\nvar eluGradConfig = {\n  kernelName: Elu,\n  outputsToSave: [true],\n  gradFunc: (dy, saved) => {\n    const [y] = saved;\n    const inputs = { dy, y };\n    return { x: () => ENGINE.runKernel(EluGrad, inputs) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Erf_grad.js\nvar erfGradConfig = {\n  kernelName: Erf,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    const a = mul(exp(neg(square(x))), 2 / Math.sqrt(Math.PI));\n    return { x: () => mul(dy, a) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Exp_grad.js\nvar expGradConfig = {\n  kernelName: Exp,\n  outputsToSave: [true],\n  gradFunc: (dy, saved) => {\n    const [y] = saved;\n    return { x: () => mul(dy, y) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ExpandDims_grad.js\nvar expandDimsGradConfig = {\n  kernelName: ExpandDims,\n  inputsToSave: [\"input\"],\n  gradFunc: (dy, saved) => {\n    const [input2] = saved;\n    return { input: () => reshape(dy, input2.shape) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Expm1_grad.js\nvar expm1GradConfig = {\n  kernelName: Expm1,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(dy, exp(x)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Floor_grad.js\nvar floorGradConfig = {\n  kernelName: Floor,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/FloorDiv_grad.js\nvar floorDivGradConfig = {\n  kernelName: FloorDiv,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const outShape = assertAndGetBroadcastShape(a.shape, b.shape);\n    const derA = () => {\n      const res = div(dy, cast(b, \"float32\"));\n      const reduceAxes = getReductionAxes(a.shape, outShape);\n      if (reduceAxes.length > 0) {\n        return reshape(sum2(res, reduceAxes), a.shape);\n      }\n      return res;\n    };\n    const derB = () => {\n      let res = mul(dy, cast(a, \"float32\"));\n      const reduceAxes = getReductionAxes(b.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = reshape(sum2(res, reduceAxes), b.shape);\n      }\n      const tmp = square(b);\n      return neg(div(res, cast(tmp, \"float32\")));\n    };\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/FusedBatchNorm_grad.js\nvar fusedBatchNormGradConfig = {\n  kernelName: FusedBatchNorm,\n  inputsToSave: [\"x\", \"mean\", \"variance\", \"scale\"],\n  gradFunc: (dy, saved, attrs) => {\n    const { varianceEpsilon } = attrs;\n    const [x, mean5, variance, scale2] = saved;\n    const scaleValue = scale2 == null ? scalar(1) : scale2;\n    const reductionAxes = getReductionAxes(mean5.shape, x.shape);\n    const tileShape = [];\n    if (mean5.rank === 1) {\n      for (let i2 = 0; i2 < x.shape.length - 1; ++i2) {\n        tileShape.push(x.shape[i2]);\n      }\n      tileShape.push(1);\n    }\n    const xMinusMean = sub(x, mean5);\n    const dyTimesScaleValue = mul(dy, scaleValue);\n    const oneOverSqrtVariance = rsqrt(add2(variance, scalar(varianceEpsilon)));\n    const minusHalfRCube = mul(mul(mul(oneOverSqrtVariance, oneOverSqrtVariance), oneOverSqrtVariance), scalar(-0.5));\n    const derX = () => {\n      if (mean5.rank === 1) {\n        return reshape(mul(mul(dy, tile(reshape(oneOverSqrtVariance, [1, 1, 1, mean5.shape[0]]), tileShape)), scaleValue), x.shape);\n      } else {\n        return reshape(mul(mul(dy, oneOverSqrtVariance), scaleValue), x.shape);\n      }\n    };\n    const derMean = () => {\n      let meanDer = mul(mul(oneOverSqrtVariance, scalar(-1)), dyTimesScaleValue);\n      if (mean5.rank === 1) {\n        meanDer = sum2(meanDer, reductionAxes);\n      }\n      return reshape(meanDer, mean5.shape);\n    };\n    const derVariance = () => {\n      let varianceDer = mul(mul(minusHalfRCube, xMinusMean), dyTimesScaleValue);\n      if (mean5.rank === 1) {\n        varianceDer = sum2(varianceDer, reductionAxes);\n      }\n      return reshape(varianceDer, mean5.shape);\n    };\n    const derScale = () => {\n      const xMinusMean2TimesRsqrt = mul(xMinusMean, oneOverSqrtVariance);\n      let scaleDer = mul(dy, xMinusMean2TimesRsqrt);\n      if (mean5.rank === 1) {\n        scaleDer = sum2(scaleDer, reductionAxes);\n      }\n      return reshape(scaleDer, mean5.shape);\n    };\n    const derOffset = () => {\n      let offsetDer = dy;\n      if (mean5.rank === 1) {\n        offsetDer = sum2(offsetDer, reductionAxes);\n      }\n      return reshape(offsetDer, mean5.shape);\n    };\n    return {\n      x: derX,\n      mean: derMean,\n      variance: derVariance,\n      scale: derScale,\n      offset: derOffset\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/GatherV2_grad.js\nvar gatherGradConfig = {\n  kernelName: GatherV2,\n  inputsToSave: [\"x\", \"indices\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x, indices] = saved;\n    const { axis } = attrs;\n    const parsedAxis = parseAxisParam(axis, x.shape)[0];\n    const derX = () => {\n      const paramsShape = x.shape;\n      const indicesSize = indices.size;\n      const outerShape = paramsShape.slice(0, parsedAxis);\n      const outerDims = outerShape.length;\n      const innerShape = paramsShape.slice(axis, paramsShape.length).slice(1);\n      const innerDims = innerShape.length;\n      const outerAxesIndices = arrayRange(0, outerDims);\n      const innerAxesIndices = arrayRange(outerDims + 1, outerDims + 1 + innerDims);\n      const valuesShape = arrayConcat([outerShape, [indicesSize], innerShape]);\n      const values = reshape(dy, valuesShape);\n      const reshapedIndices = reshape(indices, [indicesSize]);\n      const transposeDims = arrayConcat([[outerDims], outerAxesIndices, innerAxesIndices]);\n      const valuesTranspose = transpose(values, transposeDims);\n      let paramsGrad = unsortedSegmentSum(valuesTranspose, reshapedIndices, x.shape[parsedAxis]);\n      const invertTransposeDims = getUndoAxesPermutation(transposeDims);\n      paramsGrad = transpose(paramsGrad, invertTransposeDims);\n      return paramsGrad;\n    };\n    return { x: derX, indices: () => indices };\n  }\n};\nfunction arrayRange(start, stop) {\n  const result = [];\n  for (let i2 = start; i2 < stop; ++i2) {\n    result.push(i2);\n  }\n  return result;\n}\nfunction arrayConcat(arrays) {\n  const result = [];\n  for (let i2 = 0; i2 < arrays.length; ++i2) {\n    for (let j = 0; j < arrays[i2].length; ++j) {\n      result.push(arrays[i2][j]);\n    }\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/GreaterEqual_grad.js\nvar greaterEqualGradConfig = {\n  kernelName: GreaterEqual,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    return { a: () => zerosLike(a), b: () => zerosLike(b) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Identity_grad.js\nvar identityGradConfig = {\n  kernelName: Identity,\n  gradFunc: (dy) => {\n    return { x: () => cast(dy, \"float32\") };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/IsFinite_grad.js\nvar isFiniteGradConfig = {\n  kernelName: IsFinite,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/IsInf_grad.js\nvar isInfGradConfig = {\n  kernelName: IsInf,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/IsNan_grad.js\nvar isNanGradConfig = {\n  kernelName: IsNan,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/LeakyRelu_grad.js\nvar leakyReluGradConfig = {\n  kernelName: LeakyRelu,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { alpha } = attrs;\n    const mask = greater(x, 0);\n    return { x: () => where(mask, dy, mul(dy, alpha)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Log1p_grad.js\nvar log1pGradConfig = {\n  kernelName: Log1p,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, add2(x, 1)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Log_grad.js\nvar logGradConfig = {\n  kernelName: Log,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, cast(x, \"float32\")) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/LogSoftmax_grad.js\nvar logSoftmaxGradConfig = {\n  kernelName: LogSoftmax,\n  inputsToSave: [],\n  outputsToSave: [true],\n  gradFunc: (dy, saved, attrs) => {\n    const [value] = saved;\n    const { axis } = attrs;\n    return {\n      logits: () => {\n        const keepDims = true;\n        const softmax7 = exp(value);\n        return sub(dy, mul(sum2(dy, axis, keepDims), softmax7));\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/local_response_normalization_backprop.js\nfunction localResponseNormalizationBackprop_(x, y, dy, depthRadius = 5, bias = 1, alpha = 1, beta = 0.5) {\n  const inputs = { x, y, dy };\n  const attrs = { depthRadius, bias, alpha, beta };\n  return ENGINE.runKernel(LRNGrad, inputs, attrs);\n}\nvar localResponseNormalizationBackprop = op({ localResponseNormalizationBackprop_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/LRN_grad.js\nvar lrnGradConfig = {\n  kernelName: LRN,\n  inputsToSave: [\"x\"],\n  outputsToSave: [true],\n  gradFunc: (dy, saved, attrs) => {\n    const [x, y] = saved;\n    const { depthRadius, bias, alpha, beta } = attrs;\n    return {\n      x: () => localResponseNormalizationBackprop(x, y, dy, depthRadius, bias, alpha, beta)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/min_max_grad_util.js\nfunction gradForMinAndMax(dy, y, xOrig, origAxes) {\n  if (y.rank < xOrig.rank) {\n    y = reshape(y, expandShapeToKeepDim(y.shape, origAxes));\n  }\n  if (dy.rank < xOrig.rank) {\n    dy = reshape(dy, expandShapeToKeepDim(dy.shape, origAxes));\n  }\n  return {\n    x: () => {\n      const dx = mul(dy, cast(equal(xOrig, y), dy.dtype));\n      return dx;\n    }\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Max_grad.js\nvar maxGradConfig = {\n  kernelName: Max,\n  inputsToSave: [\"x\"],\n  outputsToSave: [true],\n  gradFunc: (dy, saved, attrs) => {\n    const maxAttrs = attrs;\n    const { reductionIndices } = maxAttrs;\n    const x = saved[0];\n    const y = saved[1];\n    const origAxes = parseAxisParam(reductionIndices, x.shape);\n    const maxGrad = gradForMinAndMax(dy, y, x, origAxes);\n    return {\n      x: () => {\n        return maxGrad[\"x\"]();\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Maximum_grad.js\nvar maximumGradConfig = {\n  kernelName: Maximum,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const derA = () => mul(dy, cast(greaterEqual(a, b), \"float32\"));\n    const derB = () => mul(dy, cast(less(a, b), \"float32\"));\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_3d_grad.js\nfunction maxPool3dGrad_(dy, input2, output, filterSize, strides, pad3, dimRoundingMode) {\n  const $dy = convertToTensor(dy, \"dy\", \"maxPool3dGrad\");\n  const $input = convertToTensor(input2, \"input\", \"maxPool3dGrad\");\n  const $output = convertToTensor(output, \"output\", \"maxPool3dGrad\");\n  let dy5D = $dy;\n  let input5D = $input;\n  let output5D = $output;\n  let reshapedTo5D = false;\n  if ($input.rank === 4) {\n    reshapedTo5D = true;\n    dy5D = reshape($dy, [1, $dy.shape[0], $dy.shape[1], $dy.shape[2], $dy.shape[3]]);\n    input5D = reshape($input, [\n      1,\n      $input.shape[0],\n      $input.shape[1],\n      $input.shape[2],\n      $input.shape[3]\n    ]);\n    output5D = reshape($output, [\n      1,\n      $output.shape[0],\n      $output.shape[1],\n      $output.shape[2],\n      $output.shape[3]\n    ]);\n  }\n  assert(dy5D.rank === 5, () => `Error in maxPool3dGrad: dy must be rank 5 but got rank ${dy5D.rank}.`);\n  assert(input5D.rank === 5, () => `Error in maxPool3dGrad: input must be rank 5 but got rank ${input5D.rank}.`);\n  assert(output5D.rank === 5, () => `Error in maxPool3dGrad: output must be rank 5 but got rank ${output5D.rank}.`);\n  checkPadOnDimRoundingMode(\"maxPool3dGrad\", pad3, dimRoundingMode);\n  const inputs = { dy: dy5D, input: input5D, output: output5D };\n  const attrs = { filterSize, strides, pad: pad3, dimRoundingMode };\n  const res = ENGINE.runKernel(MaxPool3DGrad, inputs, attrs);\n  if (reshapedTo5D) {\n    return reshape(res, [res.shape[1], res.shape[2], res.shape[3], res.shape[4]]);\n  }\n  return res;\n}\nvar maxPool3dGrad = op({ maxPool3dGrad_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/MaxPool3D_grad.js\nvar maxPool3DGradConfig = {\n  kernelName: MaxPool3D,\n  inputsToSave: [\"x\"],\n  outputsToSave: [true],\n  gradFunc: (dy, saved, attrs) => {\n    const [x, y] = saved;\n    const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n    return {\n      x: () => maxPool3dGrad(dy, x, y, filterSize, strides, pad3, dimRoundingMode)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/max_pool_grad.js\nfunction maxPoolGrad_(dy, input2, output, filterSize, strides, pad3, dimRoundingMode) {\n  const $dy = convertToTensor(dy, \"dy\", \"maxPoolGrad\");\n  const $input = convertToTensor(input2, \"input\", \"maxPoolGrad\");\n  const $output = convertToTensor(output, \"output\", \"maxPoolGrad\");\n  assert($input.rank === $dy.rank, () => `Rank of input (${$input.rank}) does not match rank of dy (${$dy.rank})`);\n  assert($dy.rank === 4, () => `Error in maxPoolGrad: dy must be rank 4 but got rank ${$dy.rank}.`);\n  assert($input.rank === 4, () => `Error in maxPoolGrad: input must be rank 4 but got rank ${$input.rank}.`);\n  checkPadOnDimRoundingMode(\"maxPoolGrad\", pad3, dimRoundingMode);\n  const inputs = { dy: $dy, input: $input, output: $output };\n  const attrs = { filterSize, strides, pad: pad3, dimRoundingMode };\n  return ENGINE.runKernel(MaxPoolGrad, inputs, attrs);\n}\nvar maxPoolGrad = op({ maxPoolGrad_ });\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/MaxPool_grad.js\nvar maxPoolGradConfig = {\n  kernelName: MaxPool,\n  inputsToSave: [\"x\"],\n  outputsToSave: [true],\n  gradFunc: (dy, saved, attrs) => {\n    const [x, y] = saved;\n    const { filterSize, strides, pad: pad3 } = attrs;\n    return {\n      x: () => maxPoolGrad(dy, x, y, filterSize, strides, pad3)\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Mean_grad.js\nvar meanGradConfig = {\n  kernelName: Mean,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { axis } = attrs;\n    const axes = parseAxisParam(axis, x.shape);\n    const shapes = computeOutAndReduceShapes(x.shape, axes);\n    const reduceShape = shapes[1];\n    const reduceSize = sizeFromShape(reduceShape);\n    const derX = () => {\n      const expandedDyShape = x.shape.slice();\n      axes.forEach((axis2) => {\n        expandedDyShape[axis2] = 1;\n      });\n      const expandedDy = reshape(dy, expandedDyShape);\n      const res = div(mul(expandedDy, ones2(x.shape, \"float32\")), reduceSize);\n      return res;\n    };\n    return { x: derX };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Min_grad.js\nvar minGradConfig = {\n  kernelName: Min,\n  inputsToSave: [\"x\"],\n  outputsToSave: [true],\n  gradFunc: (dy, saved, attrs) => {\n    const minAttrs = attrs;\n    const { axis } = minAttrs;\n    const [x, y] = saved;\n    const origAxes = parseAxisParam(axis, x.shape);\n    const minGrad = gradForMinAndMax(dy, y, x, origAxes);\n    return {\n      x: () => {\n        return minGrad[\"x\"]();\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Minimum_grad.js\nvar minimumGradConfig = {\n  kernelName: Minimum,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const derA = () => mul(dy, cast(lessEqual(a, b), \"float32\"));\n    const derB = () => mul(dy, cast(greater(a, b), \"float32\"));\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/MirrorPad_grad.js\nvar mirrorPadGradConfig = {\n  kernelName: MirrorPad,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const x = saved[0];\n    const { paddings } = attrs;\n    const begin = paddings.map((p2) => p2[0]);\n    return { x: () => slice(dy, begin, x.shape) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Mod_grad.js\nvar modGradConfig = {\n  kernelName: Mod,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const outShape = assertAndGetBroadcastShape(a.shape, b.shape);\n    const derA = () => {\n      const reduceAxes = getReductionAxes(a.shape, outShape);\n      if (reduceAxes.length > 0) {\n        return reshape(sum2(dy, reduceAxes), a.shape);\n      }\n      return dy;\n    };\n    const derB = () => {\n      const res = mul(dy, neg(floor(div(a, b))));\n      const reduceAxes = getReductionAxes(b.shape, outShape);\n      if (reduceAxes.length > 0) {\n        return reshape(sum2(res, reduceAxes), b.shape);\n      }\n      return res;\n    };\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Multiply_grad.js\nvar multiplyGradConfig = {\n  kernelName: Multiply,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const outShape = assertAndGetBroadcastShape(a.shape, b.shape);\n    const derA = () => {\n      const res = mul(dy, cast(b, \"float32\"));\n      const reduceAxes = getReductionAxes(a.shape, outShape);\n      if (reduceAxes.length > 0) {\n        return reshape(sum2(res, reduceAxes), a.shape);\n      }\n      return res;\n    };\n    const derB = () => {\n      const res = mul(dy, cast(a, \"float32\"));\n      const reduceAxes = getReductionAxes(b.shape, outShape);\n      if (reduceAxes.length > 0) {\n        return reshape(sum2(res, reduceAxes), b.shape);\n      }\n      return res;\n    };\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Neg_grad.js\nvar negGradConfig = {\n  kernelName: Neg,\n  gradFunc: (dy) => {\n    return { x: () => neg(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/OneHot_grad.js\nvar oneHotGradConfig = {\n  kernelName: OneHot,\n  inputsToSave: [\"indices\"],\n  gradFunc: (dy, saved) => {\n    const indices = saved[0];\n    return { indices: () => zeros(indices.shape, \"float32\") };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/OnesLike_grad.js\nvar onesLikeGradConfig = {\n  kernelName: OnesLike,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Pack_grad.js\nvar packGradConfig = {\n  kernelName: Pack,\n  saveAllInputs: true,\n  gradFunc: (dy, saved, attrs) => {\n    const { axis } = attrs;\n    const derTensors = unstack(dy, axis);\n    return derTensors.map((t2) => () => t2);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/PadV2_grad.js\nvar padV2GradConfig = {\n  kernelName: PadV2,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const x = saved[0];\n    const { paddings } = attrs;\n    const begin = paddings.map((p2) => p2[0]);\n    return { x: () => slice(dy, begin, x.shape) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Pow_grad.js\nvar powGradConfig = {\n  kernelName: Pow,\n  inputsToSave: [\"a\", \"b\"],\n  outputsToSave: [true],\n  gradFunc: (dy, saved) => {\n    const [a, b, y] = saved;\n    const base = a;\n    const exp5 = b;\n    const outShape = assertAndGetBroadcastShape(base.shape, exp5.shape);\n    const derBase = () => {\n      const expFloat = cast(exp5, \"float32\");\n      let res = mul(dy, mul(expFloat, pow(base, sub(expFloat, scalar(1)))));\n      const reduceAxes = getReductionAxes(base.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(res, base.shape);\n    };\n    const derExp = () => {\n      const condition = greater(base, 0);\n      const logBase = where(condition, log2(base), zerosLike(base));\n      let res = mul(dy, mul(y, logBase));\n      const reduceAxes = getReductionAxes(exp5.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(res, exp5.shape);\n    };\n    return { a: derBase, b: derExp };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Prelu_grad.js\nvar preluGradConfig = {\n  kernelName: Prelu,\n  inputsToSave: [\"x\", \"alpha\"],\n  gradFunc: (dy, saved) => {\n    const [x, alpha] = saved;\n    const mask = greater(x, 0);\n    return {\n      x: () => where(mask, dy, mul(dy, alpha)),\n      alpha: () => {\n        let res = where(mask, zerosLike(dy), mul(dy, x));\n        const reduceAxes = getReductionAxes(alpha.shape, dy.shape);\n        if (reduceAxes.length > 0) {\n          res = sum2(res, reduceAxes);\n        }\n        return reshape(res, alpha.shape);\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Prod_grad.js\nfunction prodGradFn_(x, dy, axis) {\n  const expandedYShape = x.shape.slice();\n  expandedYShape[axis] = 1;\n  const expandedDy = reshape(dy, expandedYShape);\n  const xCumProd = cumprod(x, axis, true, false);\n  const xCumRevProd = cumprod(x, axis, true, true);\n  const dx = mul(xCumProd, xCumRevProd);\n  return mul(expandedDy, dx);\n}\nfunction prodsGradFn_(x, dy, axis) {\n  const xRank = x.shape.length;\n  const finalProdAxis = xRank - axis.length;\n  const xPermutation = backend_util_exports.getAxesPermutation(axis, xRank);\n  let permutedX = x;\n  if (xPermutation != null) {\n    permutedX = transpose(x, xPermutation);\n  }\n  const newShape = permutedX.shape.slice();\n  const removedShape = newShape.splice(xRank - axis.length, axis.length);\n  const endPartShape = removedShape.reduce((p2, c) => p2 * c, 1);\n  newShape.push(endPartShape);\n  const reshapedPermutedX = permutedX.reshape(newShape);\n  let prodGrad = prodGradFn_(reshapedPermutedX, dy, finalProdAxis);\n  prodGrad = prodGrad.reshape(permutedX.shape);\n  if (xPermutation != null) {\n    const undoPermutation = backend_util_exports.getUndoAxesPermutation(xPermutation);\n    prodGrad = transpose(prodGrad, undoPermutation);\n  }\n  return prodGrad;\n}\nvar prodGradConfig = {\n  kernelName: Prod,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { axis } = attrs;\n    let axisArr = [];\n    if (axis === void 0 || axis === null) {\n      axisArr = x.shape.map((_, i2) => i2);\n    } else if (typeof axis === \"number\") {\n      axisArr = [axis];\n    } else {\n      axisArr = axis;\n    }\n    return { x: () => prodsGradFn_(x, dy, axisArr) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/RealDiv_grad.js\nvar divGradConfig = {\n  kernelName: RealDiv,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const outShape = assertAndGetBroadcastShape(a.shape, b.shape);\n    const derA = () => {\n      const res = div(dy, cast(b, \"float32\"));\n      const reduceAxes = getReductionAxes(a.shape, outShape);\n      if (reduceAxes.length > 0) {\n        return reshape(sum2(res, reduceAxes), a.shape);\n      }\n      return res;\n    };\n    const derB = () => {\n      let res = mul(dy, cast(a, \"float32\"));\n      const reduceAxes = getReductionAxes(b.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = reshape(sum2(res, reduceAxes), b.shape);\n      }\n      const tmp = square(b);\n      return neg(div(res, cast(tmp, \"float32\")));\n    };\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Reciprocal_grad.js\nvar reciprocalGradConfig = {\n  kernelName: Reciprocal,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, neg(square(x))) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Relu6_grad.js\nvar relu6GradConfig = {\n  kernelName: Relu6,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    const mask = mul(lessEqual(x, 6), step(x));\n    return { x: () => mul(dy, cast(mask, \"float32\")) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Relu_grad.js\nvar reluGradConfig = {\n  kernelName: Relu,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(dy, cast(step(x), \"float32\")) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Reshape_grad.js\nvar reshapeGradConfig = {\n  kernelName: Reshape,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => reshape(dy, x.shape) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ResizeBilinear_grad.js\nvar resizeBilinearGradConfig = {\n  kernelName: ResizeBilinear,\n  inputsToSave: [\"images\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [images] = saved;\n    const inputs = { dy, images };\n    const imagesDer = () => ENGINE.runKernel(ResizeBilinearGrad, inputs, attrs);\n    return { images: imagesDer };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ResizeNearestNeighbor_grad.js\nvar resizeNearestNeighborGradConfig = {\n  kernelName: ResizeNearestNeighbor,\n  inputsToSave: [\"images\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [images] = saved;\n    const inputs = { dy, images };\n    const imagesDer = () => ENGINE.runKernel(ResizeNearestNeighborGrad, inputs, attrs);\n    return { images: imagesDer };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Reverse_grad.js\nvar reverseGradConfig = {\n  kernelName: Reverse,\n  gradFunc: (dy, saved, attrs) => {\n    const { dims } = attrs;\n    const axes = parseAxisParam(dims, dy.shape);\n    return { x: () => reverse(dy, axes) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Round_grad.js\nvar roundGradConfig = {\n  kernelName: Round,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Rsqrt_grad.js\nvar rsqrtGradConfig = {\n  kernelName: Rsqrt,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => neg(div(dy, mul(pow(x, 1.5), 2))) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Select_grad.js\nvar selectGradConfig = {\n  kernelName: Select,\n  inputsToSave: [\"condition\"],\n  gradFunc: (dy, saved) => {\n    const [condition] = saved;\n    return {\n      condition: () => cast(zerosLike(condition), \"float32\"),\n      t: () => mul(dy, cast(condition, dy.dtype)),\n      e: () => mul(dy, cast(logicalNot(condition), dy.dtype))\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Selu_grad.js\nvar seluGradConfig = {\n  kernelName: Selu,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return {\n      x: () => {\n        const mask = greater(x, scalar(0));\n        const scaleAlpha2 = scalar(SELU_SCALEALPHA);\n        const scale2 = scalar(SELU_SCALE);\n        const greaterThanZeroDer = mul(dy, scale2);\n        const lessEqualZeroDer = mul(mul(dy, scaleAlpha2), exp(cast(x, \"float32\")));\n        return where(mask, greaterThanZeroDer, lessEqualZeroDer);\n      }\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Sigmoid_grad.js\nvar sigmoidGradConfig = {\n  kernelName: Sigmoid,\n  outputsToSave: [true],\n  gradFunc: (dy, saved) => {\n    const [y] = saved;\n    return { x: () => mul(dy, mul(y, sub(scalar(1), y))) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Sign_grad.js\nvar signGradConfig = {\n  kernelName: Sign,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Sin_grad.js\nvar sinGradConfig = {\n  kernelName: Sin,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(cos(cast(x, \"float32\")), dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Sinh_grad.js\nvar sinhGradConfig = {\n  kernelName: Sinh,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(cosh(cast(x, \"float32\")), dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Slice_grad.js\nvar sliceGradConfig = {\n  kernelName: Slice,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { begin, size } = attrs;\n    const inputShape = x.shape;\n    const [begin_, size_] = parseSliceParams(x, begin, size);\n    const paddings = [];\n    for (let i2 = 0; i2 < dy.rank; i2++) {\n      paddings.push([begin_[i2], inputShape[i2] - begin_[i2] - size_[i2]]);\n    }\n    return { x: () => pad(dy, paddings) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Softmax_grad.js\nvar softmaxGradConfig = {\n  kernelName: Softmax,\n  outputsToSave: [true],\n  gradFunc: (dy, saved, attrs) => {\n    const [y] = saved;\n    const { dim } = attrs;\n    const keepDims = true;\n    const dyTimesY = mul(dy, y);\n    return {\n      logits: () => sub(dyTimesY, mul(sum2(dyTimesY, [dim], keepDims), y))\n    };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Softplus_grad.js\nvar softplusGradConfig = {\n  kernelName: Softplus,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(dy, sigmoid(x)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/SpaceToBatchND_grad.js\nvar spaceToBatchNDGradConfig = {\n  kernelName: SpaceToBatchND,\n  gradFunc: (dy, saved, attrs) => {\n    const { blockShape, paddings } = attrs;\n    return { x: () => batchToSpaceND(dy, blockShape, paddings) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/SplitV_grad.js\nvar splitVGradConfig = {\n  kernelName: SplitV,\n  gradFunc: (dy, saved, attrs) => {\n    const { axis } = attrs;\n    return { x: () => concat(dy, axis) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Sqrt_grad.js\nvar sqrtGradConfig = {\n  kernelName: Sqrt,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, mul(sqrt(cast(x, \"float32\")), 2)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Square_grad.js\nvar squareGradConfig = {\n  kernelName: Square,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => mul(dy, mul(cast(x, \"float32\"), 2)) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/SquaredDifference_grad.js\nvar squaredDifferenceGradConfig = {\n  kernelName: SquaredDifference,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const two = scalar(2);\n    const derA = () => mul(dy, mul(two, sub(a, b)));\n    const derB = () => mul(dy, mul(two, sub(b, a)));\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Step_grad.js\nvar stepGradConfig = {\n  kernelName: Step,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Sub_grad.js\nvar subGradConfig = {\n  kernelName: Sub,\n  inputsToSave: [\"a\", \"b\"],\n  gradFunc: (dy, saved) => {\n    const [a, b] = saved;\n    const outShape = assertAndGetBroadcastShape(a.shape, b.shape);\n    const derA = () => {\n      let res = dy;\n      const reduceAxes = getReductionAxes(a.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(res, a.shape);\n    };\n    const derB = () => {\n      let res = dy;\n      const reduceAxes = getReductionAxes(b.shape, outShape);\n      if (reduceAxes.length > 0) {\n        res = sum2(res, reduceAxes);\n      }\n      return reshape(neg(res), b.shape);\n    };\n    return { a: derA, b: derB };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Sum_grad.js\nvar sumGradConfig = {\n  kernelName: Sum,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const expandedDyShape = x.shape.slice();\n    const { axis } = attrs;\n    const axes = parseAxisParam(axis, x.shape);\n    axes.forEach((axis2) => {\n      expandedDyShape[axis2] = 1;\n    });\n    const expandedDy = reshape(dy, expandedDyShape);\n    const derX = mul(expandedDy, ones2(x.shape, \"float32\"));\n    return { x: () => derX };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Tan_grad.js\nvar tanGradConfig = {\n  kernelName: Tan,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved) => {\n    const [x] = saved;\n    return { x: () => div(dy, square(cos(x))) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Tanh_grad.js\nvar tanhGradConfig = {\n  kernelName: Tanh,\n  outputsToSave: [true],\n  gradFunc: (dy, saved) => {\n    const [y] = saved;\n    return { x: () => mul(sub(scalar(1), square(y)), dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Tile_grad.js\nvar tileGradConfig = {\n  kernelName: Tile,\n  inputsToSave: [\"x\"],\n  gradFunc: (dy, saved, attrs) => {\n    const [x] = saved;\n    const { reps } = attrs;\n    const derX = () => {\n      let xGrad = zerosLike(x);\n      if (x.rank === 1) {\n        for (let i2 = 0; i2 < reps[0]; ++i2) {\n          xGrad = add2(xGrad, slice(dy, [i2 * x.shape[0]], [x.shape[0]]));\n        }\n      } else if (x.rank === 2) {\n        for (let i2 = 0; i2 < reps[0]; ++i2) {\n          for (let j = 0; j < reps[1]; ++j) {\n            xGrad = add2(xGrad, slice(dy, [i2 * x.shape[0], j * x.shape[1]], [\n              x.shape[0],\n              x.shape[1]\n            ]));\n          }\n        }\n      } else if (x.rank === 3) {\n        for (let i2 = 0; i2 < reps[0]; ++i2) {\n          for (let j = 0; j < reps[1]; ++j) {\n            for (let k = 0; k < reps[2]; ++k) {\n              xGrad = add2(xGrad, slice(dy, [i2 * x.shape[0], j * x.shape[1], k * x.shape[2]], [x.shape[0], x.shape[1], x.shape[2]]));\n            }\n          }\n        }\n      } else if (x.rank === 4) {\n        for (let i2 = 0; i2 < reps[0]; ++i2) {\n          for (let j = 0; j < reps[1]; ++j) {\n            for (let k = 0; k < reps[2]; ++k) {\n              for (let l3 = 0; l3 < reps[3]; ++l3) {\n                xGrad = add2(xGrad, slice(dy, [\n                  i2 * x.shape[0],\n                  j * x.shape[1],\n                  k * x.shape[2],\n                  l3 * x.shape[3]\n                ], [x.shape[0], x.shape[1], x.shape[2], x.shape[3]]));\n              }\n            }\n          }\n        }\n      } else {\n        throw new Error(`Gradient for tile operation is not implemented for rank-${x.rank} tensors yet.`);\n      }\n      return xGrad;\n    };\n    return { x: derX };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Transpose_grad.js\nvar transposeGradConfig = {\n  kernelName: Transpose,\n  gradFunc: (dy, saved, attrs) => {\n    const transposeAttrs = attrs;\n    const { perm } = transposeAttrs;\n    const undoPerm = getUndoAxesPermutation(perm);\n    return { x: () => transpose(dy, undoPerm) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/Unpack_grad.js\nvar unpackGradConfig = {\n  kernelName: Unpack,\n  gradFunc: (dy, saved, attrs) => {\n    const unpackAttrs = attrs;\n    const { axis } = unpackAttrs;\n    return { value: () => stack(dy, axis) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/UnsortedSegmentSum_grad.js\nvar unsortedSegmentSumGradConfig = {\n  kernelName: UnsortedSegmentSum,\n  inputsToSave: [\"segmentIds\"],\n  gradFunc: (dy, saved) => {\n    const [segmentIds] = saved;\n    const derX = () => {\n      return gatherDropNegatives(dy, segmentIds);\n    };\n    return { x: derX };\n  }\n};\nfunction gatherDropNegatives(x, indices) {\n  const zeroClippedIndices = maximum(indices, zerosLike(indices));\n  const gathered = gather(x, zeroClippedIndices);\n  let isPositive = greaterEqual(indices, scalar(0, \"int32\"));\n  const numIters = gathered.rank - isPositive.rank;\n  for (let i2 = 0; i2 < numIters; ++i2) {\n    isPositive = expandDims(isPositive, i2 + 1);\n  }\n  isPositive = logicalAnd(isPositive, ones2(gathered.shape, \"bool\"));\n  const zeroSlice = zerosLike(gathered);\n  return where(isPositive, gathered, zeroSlice);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/gradients/ZerosLike_grad.js\nvar zerosLikeGradConfig = {\n  kernelName: ZerosLike,\n  gradFunc: (dy) => {\n    return { x: () => zerosLike(dy) };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/register_all_gradients.js\nvar gradConfigs = [\n  absGradConfig,\n  acosGradConfig,\n  acoshGradConfig,\n  addGradConfig,\n  addNGradConfig,\n  argMaxGradConfig,\n  argMinGradConfig,\n  asinGradConfig,\n  asinhGradConfig,\n  atan2GradConfig,\n  atanGradConfig,\n  atanhGradConfig,\n  avgPool3DGradConfig,\n  avgPoolGradConfig,\n  batchMatMulGradConfig,\n  batchToSpaceNDGradConfig,\n  broadcastToGradConfig,\n  castGradConfig,\n  ceilGradConfig,\n  clipByValueGradConfig,\n  complexAbsGradConfig,\n  concatGradConfig,\n  conv2DBackpropInputGradConfig,\n  conv2DGradConfig,\n  conv3DGradConfig,\n  cosGradConfig,\n  coshGradConfig,\n  cumsumGradConfig,\n  depthwiseConv2dNativeGradConfig,\n  dilation2dGradConfig,\n  divGradConfig,\n  eluGradConfig,\n  erfGradConfig,\n  expGradConfig,\n  expandDimsGradConfig,\n  expm1GradConfig,\n  floorDivGradConfig,\n  floorGradConfig,\n  fusedBatchNormGradConfig,\n  gatherGradConfig,\n  greaterEqualGradConfig,\n  identityGradConfig,\n  isFiniteGradConfig,\n  isInfGradConfig,\n  isNanGradConfig,\n  leakyReluGradConfig,\n  log1pGradConfig,\n  logGradConfig,\n  logSoftmaxGradConfig,\n  lrnGradConfig,\n  maxGradConfig,\n  maxGradConfig,\n  maximumGradConfig,\n  maxPool3DGradConfig,\n  maxPoolGradConfig,\n  meanGradConfig,\n  minGradConfig,\n  minimumGradConfig,\n  mirrorPadGradConfig,\n  modGradConfig,\n  multiplyGradConfig,\n  negGradConfig,\n  oneHotGradConfig,\n  onesLikeGradConfig,\n  packGradConfig,\n  padV2GradConfig,\n  padV2GradConfig,\n  powGradConfig,\n  preluGradConfig,\n  prodGradConfig,\n  reciprocalGradConfig,\n  relu6GradConfig,\n  reluGradConfig,\n  reshapeGradConfig,\n  resizeBilinearGradConfig,\n  resizeNearestNeighborGradConfig,\n  reverseGradConfig,\n  roundGradConfig,\n  rsqrtGradConfig,\n  selectGradConfig,\n  seluGradConfig,\n  sigmoidGradConfig,\n  signGradConfig,\n  sinGradConfig,\n  sinhGradConfig,\n  sliceGradConfig,\n  softmaxGradConfig,\n  softplusGradConfig,\n  spaceToBatchNDGradConfig,\n  spaceToBatchNDGradConfig,\n  splitVGradConfig,\n  splitVGradConfig,\n  sqrtGradConfig,\n  squaredDifferenceGradConfig,\n  squareGradConfig,\n  stepGradConfig,\n  subGradConfig,\n  sumGradConfig,\n  tanGradConfig,\n  tanhGradConfig,\n  tileGradConfig,\n  transposeGradConfig,\n  unpackGradConfig,\n  unsortedSegmentSumGradConfig,\n  zerosLikeGradConfig\n];\nfor (const gradientConfig of gradConfigs) {\n  registerGradient(gradientConfig);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/abs.js\ngetGlobalTensorClass().prototype.abs = function() {\n  this.throwIfDisposed();\n  return abs(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/acos.js\ngetGlobalTensorClass().prototype.acos = function() {\n  this.throwIfDisposed();\n  return acos(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/acosh.js\ngetGlobalTensorClass().prototype.acosh = function() {\n  this.throwIfDisposed();\n  return acosh(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/add.js\ngetGlobalTensorClass().prototype.add = function(b) {\n  this.throwIfDisposed();\n  return add2(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/all.js\ngetGlobalTensorClass().prototype.all = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return all(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/any.js\ngetGlobalTensorClass().prototype.any = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return any(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/arg_max.js\ngetGlobalTensorClass().prototype.argMax = function(axis) {\n  this.throwIfDisposed();\n  return argMax(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/arg_min.js\ngetGlobalTensorClass().prototype.argMin = function(axis) {\n  this.throwIfDisposed();\n  return argMin(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/as_scalar.js\ngetGlobalTensorClass().prototype.asScalar = function() {\n  this.throwIfDisposed();\n  assert(this.size === 1, () => \"The array must have only 1 element.\");\n  return reshape(this, []);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/as_type.js\ngetGlobalTensorClass().prototype.asType = function(dtype) {\n  this.throwIfDisposed();\n  return cast(this, dtype);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/as1d.js\ngetGlobalTensorClass().prototype.as1D = function() {\n  this.throwIfDisposed();\n  return reshape(this, [this.size]);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/as2d.js\ngetGlobalTensorClass().prototype.as2D = function(rows, columns) {\n  this.throwIfDisposed();\n  return reshape(this, [rows, columns]);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/as3d.js\ngetGlobalTensorClass().prototype.as3D = function(rows, columns, depth) {\n  this.throwIfDisposed();\n  return reshape(this, [rows, columns, depth]);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/as4d.js\ngetGlobalTensorClass().prototype.as4D = function(rows, columns, depth, depth2) {\n  this.throwIfDisposed();\n  return reshape(this, [rows, columns, depth, depth2]);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/as5d.js\ngetGlobalTensorClass().prototype.as5D = function(rows, columns, depth, depth2, depth3) {\n  this.throwIfDisposed();\n  return reshape(this, [rows, columns, depth, depth2, depth3]);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/asin.js\ngetGlobalTensorClass().prototype.asin = function() {\n  this.throwIfDisposed();\n  return asin(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/asinh.js\ngetGlobalTensorClass().prototype.asinh = function() {\n  this.throwIfDisposed();\n  return asinh(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/atan.js\ngetGlobalTensorClass().prototype.atan = function() {\n  this.throwIfDisposed();\n  return atan(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/atan2.js\ngetGlobalTensorClass().prototype.atan2 = function(b) {\n  this.throwIfDisposed();\n  return atan2(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/atanh.js\ngetGlobalTensorClass().prototype.atanh = function() {\n  this.throwIfDisposed();\n  return atanh(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/avg_pool.js\ngetGlobalTensorClass().prototype.avgPool = function(filterSize, strides, pad3, dimRoundingMode) {\n  this.throwIfDisposed();\n  return avgPool(this, filterSize, strides, pad3, dimRoundingMode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/batch_to_space_nd.js\ngetGlobalTensorClass().prototype.batchToSpaceND = function(blockShape, crops) {\n  this.throwIfDisposed();\n  return batchToSpaceND(this, blockShape, crops);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/batchnorm.js\ngetGlobalTensorClass().prototype.batchNorm = function(mean5, variance, offset, scale2, varianceEpsilon) {\n  this.throwIfDisposed();\n  return batchNorm(this, mean5, variance, offset, scale2, varianceEpsilon);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/broadcast_to.js\ngetGlobalTensorClass().prototype.broadcastTo = function(shape) {\n  this.throwIfDisposed();\n  return broadcastTo(this, shape);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/cast.js\ngetGlobalTensorClass().prototype.cast = function(dtype) {\n  this.throwIfDisposed();\n  return cast(this, dtype);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/ceil.js\ngetGlobalTensorClass().prototype.ceil = function() {\n  this.throwIfDisposed();\n  return ceil(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/clip_by_value.js\ngetGlobalTensorClass().prototype.clipByValue = function(min7, max7) {\n  this.throwIfDisposed();\n  return clipByValue(this, min7, max7);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/concat.js\ngetGlobalTensorClass().prototype.concat = function(x, axis) {\n  this.throwIfDisposed();\n  if (x instanceof Tensor) {\n    x = [x];\n  }\n  return concat([this, ...x], axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/conv1d.js\ngetGlobalTensorClass().prototype.conv1d = function(filter, stride, pad3, dataFormat, dilation, dimRoundingMode) {\n  this.throwIfDisposed();\n  return conv1d(this, filter, stride, pad3, dataFormat, dilation, dimRoundingMode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/conv2d_transpose.js\ngetGlobalTensorClass().prototype.conv2dTranspose = function(filter, outputShape, strides, pad3, dimRoundingMode) {\n  this.throwIfDisposed();\n  return conv2dTranspose(this, filter, outputShape, strides, pad3, dimRoundingMode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/conv2d.js\ngetGlobalTensorClass().prototype.conv2d = function(filter, strides, pad3, dataFormat, dilations, dimRoundingMode) {\n  this.throwIfDisposed();\n  return conv2d(this, filter, strides, pad3, dataFormat, dilations, dimRoundingMode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/cos.js\ngetGlobalTensorClass().prototype.cos = function() {\n  this.throwIfDisposed();\n  return cos(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/cosh.js\ngetGlobalTensorClass().prototype.cosh = function() {\n  this.throwIfDisposed();\n  return cosh(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/cumprod.js\ngetGlobalTensorClass().prototype.cumprod = function(axis, exclusive, reverse5) {\n  this.throwIfDisposed();\n  return cumprod(this, axis, exclusive, reverse5);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/cumsum.js\ngetGlobalTensorClass().prototype.cumsum = function(axis, exclusive, reverse5) {\n  this.throwIfDisposed();\n  return cumsum(this, axis, exclusive, reverse5);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/depth_to_space.js\ngetGlobalTensorClass().prototype.depthToSpace = function(blockSize, dataFormat) {\n  this.throwIfDisposed();\n  return depthToSpace(this, blockSize, dataFormat);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/depthwise_conv2d.js\ngetGlobalTensorClass().prototype.depthwiseConv2d = function(filter, strides, pad3, dataFormat, dilations, dimRoundingMode) {\n  this.throwIfDisposed();\n  return depthwiseConv2d(this, filter, strides, pad3, dataFormat, dilations, dimRoundingMode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/dilation2d.js\ngetGlobalTensorClass().prototype.dilation2d = function(filter, strides, pad3, dilations, dataFormat) {\n  this.throwIfDisposed();\n  return dilation2d(this, filter, strides, pad3, dilations, dataFormat);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/div_no_nan.js\ngetGlobalTensorClass().prototype.divNoNan = function(b) {\n  this.throwIfDisposed();\n  return divNoNan(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/div.js\ngetGlobalTensorClass().prototype.div = function(b) {\n  this.throwIfDisposed();\n  return div(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/dot.js\ngetGlobalTensorClass().prototype.dot = function(b) {\n  this.throwIfDisposed();\n  return dot(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/elu.js\ngetGlobalTensorClass().prototype.elu = function() {\n  this.throwIfDisposed();\n  return elu(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/equal.js\ngetGlobalTensorClass().prototype.equal = function(b) {\n  this.throwIfDisposed();\n  return equal(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/erf.js\ngetGlobalTensorClass().prototype.erf = function() {\n  this.throwIfDisposed();\n  return erf(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/euclidean_norm.js\ngetGlobalTensorClass().prototype.euclideanNorm = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return euclideanNorm(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/exp.js\ngetGlobalTensorClass().prototype.exp = function() {\n  this.throwIfDisposed();\n  return exp(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/expand_dims.js\ngetGlobalTensorClass().prototype.expandDims = function(axis) {\n  this.throwIfDisposed();\n  return expandDims(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/expm1.js\ngetGlobalTensorClass().prototype.expm1 = function() {\n  this.throwIfDisposed();\n  return expm1(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/fft.js\ngetGlobalTensorClass().prototype.fft = function() {\n  this.throwIfDisposed();\n  return fft(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/flatten.js\ngetGlobalTensorClass().prototype.flatten = function() {\n  this.throwIfDisposed();\n  return reshape(this, [this.size]);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/floor.js\ngetGlobalTensorClass().prototype.floor = function() {\n  this.throwIfDisposed();\n  return floor(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/floorDiv.js\ngetGlobalTensorClass().prototype.floorDiv = function(b) {\n  this.throwIfDisposed();\n  return floorDiv(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/gather.js\ngetGlobalTensorClass().prototype.gather = function(indices, axis) {\n  this.throwIfDisposed();\n  return gather(this, indices, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/greater_equal.js\ngetGlobalTensorClass().prototype.greaterEqual = function(b) {\n  this.throwIfDisposed();\n  return greaterEqual(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/greater.js\ngetGlobalTensorClass().prototype.greater = function(b) {\n  this.throwIfDisposed();\n  return greater(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/ifft.js\ngetGlobalTensorClass().prototype.ifft = function() {\n  this.throwIfDisposed();\n  return ifft(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/irfft.js\ngetGlobalTensorClass().prototype.irfft = function() {\n  this.throwIfDisposed();\n  return irfft(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/is_finite.js\ngetGlobalTensorClass().prototype.isFinite = function() {\n  this.throwIfDisposed();\n  return isFinite2(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/is_inf.js\ngetGlobalTensorClass().prototype.isInf = function() {\n  this.throwIfDisposed();\n  return isInf(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/is_nan.js\ngetGlobalTensorClass().prototype.isNaN = function() {\n  this.throwIfDisposed();\n  return isNaN2(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/leaky_relu.js\ngetGlobalTensorClass().prototype.leakyRelu = function(alpha) {\n  this.throwIfDisposed();\n  return leakyRelu(this, alpha);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/less_equal.js\ngetGlobalTensorClass().prototype.lessEqual = function(b) {\n  this.throwIfDisposed();\n  return lessEqual(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/less.js\ngetGlobalTensorClass().prototype.less = function(b) {\n  this.throwIfDisposed();\n  return less(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/local_response_normalization.js\ngetGlobalTensorClass().prototype.localResponseNormalization = function(depthRadius, bias, alpha, beta) {\n  this.throwIfDisposed();\n  return localResponseNormalization(this, depthRadius, bias, alpha, beta);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/log_sigmoid.js\ngetGlobalTensorClass().prototype.logSigmoid = function() {\n  this.throwIfDisposed();\n  return logSigmoid(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/log_softmax.js\ngetGlobalTensorClass().prototype.logSoftmax = function(axis) {\n  this.throwIfDisposed();\n  return logSoftmax(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/log_sum_exp.js\ngetGlobalTensorClass().prototype.logSumExp = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return logSumExp(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/log.js\ngetGlobalTensorClass().prototype.log = function() {\n  this.throwIfDisposed();\n  return log2(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/log1p.js\ngetGlobalTensorClass().prototype.log1p = function() {\n  this.throwIfDisposed();\n  return log1p(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/logical_and.js\ngetGlobalTensorClass().prototype.logicalAnd = function(b) {\n  this.throwIfDisposed();\n  return logicalAnd(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/logical_not.js\ngetGlobalTensorClass().prototype.logicalNot = function() {\n  this.throwIfDisposed();\n  return logicalNot(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/logical_or.js\ngetGlobalTensorClass().prototype.logicalOr = function(b) {\n  this.throwIfDisposed();\n  return logicalOr(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/logical_xor.js\ngetGlobalTensorClass().prototype.logicalXor = function(b) {\n  this.throwIfDisposed();\n  return logicalXor(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mat_mul.js\ngetGlobalTensorClass().prototype.matMul = function(b, transposeA, transposeB) {\n  this.throwIfDisposed();\n  return matMul(this, b, transposeA, transposeB);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/max_pool.js\ngetGlobalTensorClass().prototype.maxPool = function(filterSize, strides, pad3, dimRoundingMode) {\n  this.throwIfDisposed();\n  return maxPool(this, filterSize, strides, pad3, dimRoundingMode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/max.js\ngetGlobalTensorClass().prototype.max = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return max(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/maximum.js\ngetGlobalTensorClass().prototype.maximum = function(b) {\n  this.throwIfDisposed();\n  return maximum(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mean.js\ngetGlobalTensorClass().prototype.mean = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return mean(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/min.js\ngetGlobalTensorClass().prototype.min = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return min(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/minimum.js\ngetGlobalTensorClass().prototype.minimum = function(b) {\n  this.throwIfDisposed();\n  return minimum(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mirror_pad.js\ngetGlobalTensorClass().prototype.mirrorPad = function(paddings, mode) {\n  this.throwIfDisposed();\n  return mirrorPad(this, paddings, mode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mod.js\ngetGlobalTensorClass().prototype.mod = function(b) {\n  this.throwIfDisposed();\n  return mod(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/mul.js\ngetGlobalTensorClass().prototype.mul = function(b) {\n  this.throwIfDisposed();\n  return mul(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/neg.js\ngetGlobalTensorClass().prototype.neg = function() {\n  this.throwIfDisposed();\n  return neg(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/norm.js\ngetGlobalTensorClass().prototype.norm = function(ord, axis, keepDims) {\n  this.throwIfDisposed();\n  return norm(this, ord, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/not_equal.js\ngetGlobalTensorClass().prototype.notEqual = function(b) {\n  this.throwIfDisposed();\n  return notEqual(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/one_hot.js\ngetGlobalTensorClass().prototype.oneHot = function(depth, onValue = 1, offValue = 0) {\n  this.throwIfDisposed();\n  return oneHot(this, depth, onValue, offValue);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/ones_like.js\ngetGlobalTensorClass().prototype.onesLike = function() {\n  this.throwIfDisposed();\n  return onesLike(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/pad.js\ngetGlobalTensorClass().prototype.pad = function(paddings, constantValue) {\n  this.throwIfDisposed();\n  return pad(this, paddings, constantValue);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/pool.js\ngetGlobalTensorClass().prototype.pool = function(windowShape, poolingType, padding, dilationRate, strides, dimRoundingMode) {\n  this.throwIfDisposed();\n  return pool(this, windowShape, poolingType, padding, dilationRate, strides, dimRoundingMode);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/pow.js\ngetGlobalTensorClass().prototype.pow = function(exp5) {\n  this.throwIfDisposed();\n  return pow(this, exp5);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/prelu.js\ngetGlobalTensorClass().prototype.prelu = function(alpha) {\n  this.throwIfDisposed();\n  return prelu(this, alpha);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/prod.js\ngetGlobalTensorClass().prototype.prod = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return prod(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/reciprocal.js\ngetGlobalTensorClass().prototype.reciprocal = function() {\n  this.throwIfDisposed();\n  return reciprocal(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/relu.js\ngetGlobalTensorClass().prototype.relu = function() {\n  this.throwIfDisposed();\n  return relu(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/relu6.js\ngetGlobalTensorClass().prototype.relu6 = function() {\n  this.throwIfDisposed();\n  return relu6(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/reshape_as.js\ngetGlobalTensorClass().prototype.reshapeAs = function(x) {\n  this.throwIfDisposed();\n  return reshape(this, x.shape);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/reshape.js\ngetGlobalTensorClass().prototype.reshape = function(shape) {\n  this.throwIfDisposed();\n  return reshape(this, shape);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/resize_bilinear.js\ngetGlobalTensorClass().prototype.resizeBilinear = function(newShape2D, alignCorners, halfPixelCenters) {\n  this.throwIfDisposed();\n  return resizeBilinear(this, newShape2D, alignCorners, halfPixelCenters);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/resize_nearest_neighbor.js\ngetGlobalTensorClass().prototype.resizeNearestNeighbor = function(newShape2D, alignCorners, halfFloatCenters) {\n  this.throwIfDisposed();\n  return resizeNearestNeighbor(this, newShape2D, alignCorners, halfFloatCenters);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/reverse.js\ngetGlobalTensorClass().prototype.reverse = function(axis) {\n  this.throwIfDisposed();\n  return reverse(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/rfft.js\ngetGlobalTensorClass().prototype.rfft = function() {\n  this.throwIfDisposed();\n  return rfft(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/round.js\ngetGlobalTensorClass().prototype.round = function() {\n  this.throwIfDisposed();\n  return round2(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/rsqrt.js\ngetGlobalTensorClass().prototype.rsqrt = function() {\n  this.throwIfDisposed();\n  return rsqrt(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/selu.js\ngetGlobalTensorClass().prototype.selu = function() {\n  this.throwIfDisposed();\n  return selu(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/separable_conv2d.js\ngetGlobalTensorClass().prototype.separableConv2d = function(depthwiseFilter, pointwiseFilter, strides, pad3, dilation, dataFormat) {\n  this.throwIfDisposed();\n  return separableConv2d(this, depthwiseFilter, pointwiseFilter, strides, pad3, dilation, dataFormat);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sigmoid.js\ngetGlobalTensorClass().prototype.sigmoid = function() {\n  this.throwIfDisposed();\n  return sigmoid(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sign.js\ngetGlobalTensorClass().prototype.sign = function() {\n  this.throwIfDisposed();\n  return sign(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sin.js\ngetGlobalTensorClass().prototype.sin = function() {\n  this.throwIfDisposed();\n  return sin(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sinh.js\ngetGlobalTensorClass().prototype.sinh = function() {\n  this.throwIfDisposed();\n  return sinh(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/slice.js\ngetGlobalTensorClass().prototype.slice = function(begin, size) {\n  this.throwIfDisposed();\n  return slice(this, begin, size);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/softmax.js\ngetGlobalTensorClass().prototype.softmax = function(dim) {\n  this.throwIfDisposed();\n  return softmax(this, dim);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/softplus.js\ngetGlobalTensorClass().prototype.softplus = function() {\n  this.throwIfDisposed();\n  return softplus(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/space_to_batch_nd.js\ngetGlobalTensorClass().prototype.spaceToBatchND = function(blockShape, paddings) {\n  this.throwIfDisposed();\n  return spaceToBatchND(this, blockShape, paddings);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/split.js\ngetGlobalTensorClass().prototype.split = function(numOrSizeSplits, axis) {\n  this.throwIfDisposed();\n  return split(this, numOrSizeSplits, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sqrt.js\ngetGlobalTensorClass().prototype.sqrt = function() {\n  this.throwIfDisposed();\n  return sqrt(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/square.js\ngetGlobalTensorClass().prototype.square = function() {\n  this.throwIfDisposed();\n  return square(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/squared_difference.js\ngetGlobalTensorClass().prototype.squaredDifference = function(b) {\n  this.throwIfDisposed();\n  return squaredDifference(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/squeeze.js\ngetGlobalTensorClass().prototype.squeeze = function(axis) {\n  this.throwIfDisposed();\n  return squeeze(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/stack.js\ngetGlobalTensorClass().prototype.stack = function(x, axis) {\n  this.throwIfDisposed();\n  const tensorsToBeStacked = x instanceof Tensor ? [this, x] : [this, ...x];\n  return stack(tensorsToBeStacked, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/step.js\ngetGlobalTensorClass().prototype.step = function(alpha) {\n  this.throwIfDisposed();\n  return step(this, alpha);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/strided_slice.js\ngetGlobalTensorClass().prototype.stridedSlice = function(begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask) {\n  this.throwIfDisposed();\n  return stridedSlice(this, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sub.js\ngetGlobalTensorClass().prototype.sub = function(b) {\n  this.throwIfDisposed();\n  return sub(this, b);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/sum.js\ngetGlobalTensorClass().prototype.sum = function(axis, keepDims) {\n  this.throwIfDisposed();\n  return sum2(this, axis, keepDims);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/tan.js\ngetGlobalTensorClass().prototype.tan = function() {\n  this.throwIfDisposed();\n  return tan(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/tanh.js\ngetGlobalTensorClass().prototype.tanh = function() {\n  this.throwIfDisposed();\n  return tanh2(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/tile.js\ngetGlobalTensorClass().prototype.tile = function(reps) {\n  this.throwIfDisposed();\n  return tile(this, reps);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/to_bool.js\ngetGlobalTensorClass().prototype.toBool = function() {\n  this.throwIfDisposed();\n  return cast(this, \"bool\");\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/to_float.js\ngetGlobalTensorClass().prototype.toFloat = function() {\n  this.throwIfDisposed();\n  return cast(this, \"float32\");\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/to_int.js\ngetGlobalTensorClass().prototype.toInt = function() {\n  this.throwIfDisposed();\n  return cast(this, \"int32\");\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/topk.js\ngetGlobalTensorClass().prototype.topk = function(k, sorted) {\n  this.throwIfDisposed();\n  return topk(this, k, sorted);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/transpose.js\ngetGlobalTensorClass().prototype.transpose = function(perm) {\n  this.throwIfDisposed();\n  return transpose(this, perm);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/unique.js\ngetGlobalTensorClass().prototype.unique = function(axis) {\n  this.throwIfDisposed();\n  return unique(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/unsorted_segment_sum.js\ngetGlobalTensorClass().prototype.unsortedSegmentSum = function(segmentIds, numSegments) {\n  this.throwIfDisposed();\n  return unsortedSegmentSum(this, segmentIds, numSegments);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/unstack.js\ngetGlobalTensorClass().prototype.unstack = function(axis) {\n  this.throwIfDisposed();\n  return unstack(this, axis);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/where.js\ngetGlobalTensorClass().prototype.where = function(condition, x) {\n  this.throwIfDisposed();\n  return where(condition, this, x);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/public/chained_ops/zeros_like.js\ngetGlobalTensorClass().prototype.zerosLike = function() {\n  this.throwIfDisposed();\n  return zerosLike(this);\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/errors.js\nvar AttributeError = class extends Error {\n  constructor(message) {\n    super(message);\n    Object.setPrototypeOf(this, AttributeError.prototype);\n  }\n};\nvar RuntimeError = class extends Error {\n  constructor(message) {\n    super(message);\n    Object.setPrototypeOf(this, RuntimeError.prototype);\n  }\n};\nvar ValueError = class extends Error {\n  constructor(message) {\n    super(message);\n    Object.setPrototypeOf(this, ValueError.prototype);\n  }\n};\nvar NotImplementedError = class extends Error {\n  constructor(message) {\n    super(message);\n    Object.setPrototypeOf(this, NotImplementedError.prototype);\n  }\n};\nvar AssertionError = class extends Error {\n  constructor(message) {\n    super(message);\n    Object.setPrototypeOf(this, AssertionError.prototype);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/executor_utils.js\nvar LruCache = class {\n  constructor(maxEntries) {\n    this.maxEntries = maxEntries || 100;\n    this.cache = /* @__PURE__ */ new Map();\n  }\n  get(key) {\n    let entry;\n    if (this.cache.has(key)) {\n      entry = this.cache.get(key);\n      this.cache.delete(key);\n      this.cache.set(key, entry);\n    }\n    return entry;\n  }\n  put(key, value) {\n    if (this.cache.has(key)) {\n      this.cache.delete(key);\n    } else if (this.cache.size >= this.maxEntries) {\n      const keyToDelete = this.cache.keys().next().value;\n      this.cache.delete(keyToDelete);\n    }\n    this.cache.set(key, value);\n  }\n  getMaxEntries() {\n    return this.maxEntries;\n  }\n  setMaxEntries(maxEntries) {\n    if (maxEntries < 0) {\n      throw new Error(`The maxEntries of LRU caches must be at least 0, but got ${maxEntries}.`);\n    }\n    if (this.maxEntries > maxEntries) {\n      for (let i2 = 0; i2 < this.maxEntries - maxEntries; i2++) {\n        const keyToDelete = this.cache.keys().next().value;\n        this.cache.delete(keyToDelete);\n      }\n    }\n    this.maxEntries = maxEntries;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/generic_utils.js\nfunction pyListRepeat(value, numValues) {\n  if (Array.isArray(value)) {\n    let newArray = [];\n    for (let i2 = 0; i2 < numValues; i2++) {\n      newArray = newArray.concat(value);\n    }\n    return newArray;\n  } else {\n    const newArray = new Array(numValues);\n    newArray.fill(value);\n    return newArray;\n  }\n}\nfunction assert2(val, message) {\n  if (!val) {\n    throw new AssertionError(message);\n  }\n}\nfunction count(array2, refernce) {\n  let counter = 0;\n  for (const item of array2) {\n    if (item === refernce) {\n      counter++;\n    }\n  }\n  return counter;\n}\nfunction singletonOrArray(xs) {\n  if (xs.length === 1) {\n    return xs[0];\n  }\n  return xs;\n}\nfunction toList(x) {\n  if (Array.isArray(x)) {\n    return x;\n  }\n  return [x];\n}\nfunction toSnakeCase(name) {\n  const intermediate = name.replace(/(.)([A-Z][a-z0-9]+)/g, \"$1_$2\");\n  const insecure = intermediate.replace(/([a-z])([A-Z])/g, \"$1_$2\").toLowerCase();\n  if (insecure[0] !== \"_\") {\n    return insecure;\n  }\n  return \"private\" + insecure;\n}\nfunction toCamelCase(identifier) {\n  if (identifier.length <= 1) {\n    return identifier;\n  }\n  if (identifier.indexOf(\"_\") === -1) {\n    return identifier;\n  }\n  return identifier.replace(/[_]+(\\w|$)/g, (m, p1) => p1.toUpperCase());\n}\nvar _GLOBAL_CUSTOM_OBJECTS = {};\nfunction serializeKerasObject(instance) {\n  if (instance === null || instance === void 0) {\n    return null;\n  }\n  const dict = {};\n  dict[\"className\"] = instance.getClassName();\n  dict[\"config\"] = instance.getConfig();\n  return dict;\n}\nfunction convertNDArrayScalarsInConfig(config) {\n  if (config == null || typeof config !== \"object\") {\n    return;\n  } else if (Array.isArray(config)) {\n    config.forEach((configItem) => convertNDArrayScalarsInConfig(configItem));\n  } else {\n    const fields = Object.keys(config);\n    for (const field of fields) {\n      const value = config[field];\n      if (value != null && typeof value === \"object\") {\n        if (!Array.isArray(value) && value[\"type\"] === \"ndarray\" && typeof value[\"value\"] === \"number\") {\n          config[field] = value[\"value\"];\n        } else {\n          convertNDArrayScalarsInConfig(value);\n        }\n      }\n    }\n  }\n}\nfunction deserializeKerasObject(identifier, moduleObjects = {}, customObjects = {}, printableModuleName = \"object\", fastWeightInit = false) {\n  if (typeof identifier === \"string\") {\n    const functionName = identifier;\n    let fn;\n    if (functionName in customObjects) {\n      fn = customObjects[functionName];\n    } else if (functionName in _GLOBAL_CUSTOM_OBJECTS) {\n      fn = _GLOBAL_CUSTOM_OBJECTS[functionName];\n    } else {\n      fn = moduleObjects[functionName];\n      if (fn == null) {\n        throw new ValueError(`Unknown ${printableModuleName}: ${identifier}. This may be due to one of the following reasons:\n1. The ${printableModuleName} is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.\n2. The custom ${printableModuleName} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);\n      }\n    }\n    return fn;\n  } else {\n    const config = identifier;\n    if (config[\"className\"] == null || config[\"config\"] == null) {\n      throw new ValueError(`${printableModuleName}: Improper config format: ${JSON.stringify(config)}.\n'className' and 'config' must set.`);\n    }\n    const className = config[\"className\"];\n    let cls, fromConfig;\n    if (className in customObjects) {\n      [cls, fromConfig] = customObjects[className];\n    } else if (className in _GLOBAL_CUSTOM_OBJECTS) {\n      [cls, fromConfig] = _GLOBAL_CUSTOM_OBJECTS[\"className\"];\n    } else if (className in moduleObjects) {\n      [cls, fromConfig] = moduleObjects[className];\n    }\n    if (cls == null) {\n      throw new ValueError(`Unknown ${printableModuleName}: ${className}. This may be due to one of the following reasons:\n1. The ${printableModuleName} is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.\n2. The custom ${printableModuleName} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);\n    }\n    if (fromConfig != null) {\n      const customObjectsCombined = {};\n      for (const key of Object.keys(_GLOBAL_CUSTOM_OBJECTS)) {\n        customObjectsCombined[key] = _GLOBAL_CUSTOM_OBJECTS[key];\n      }\n      for (const key of Object.keys(customObjects)) {\n        customObjectsCombined[key] = customObjects[key];\n      }\n      const nestedConfig = config[\"config\"];\n      nestedConfig[\"customObjects\"] = customObjectsCombined;\n      const backupCustomObjects = Object.assign({}, _GLOBAL_CUSTOM_OBJECTS);\n      for (const key of Object.keys(customObjects)) {\n        _GLOBAL_CUSTOM_OBJECTS[key] = customObjects[key];\n      }\n      convertNDArrayScalarsInConfig(config[\"config\"]);\n      const returnObj = fromConfig(cls, config[\"config\"], customObjects, fastWeightInit);\n      _GLOBAL_CUSTOM_OBJECTS = Object.assign({}, backupCustomObjects);\n      return returnObj;\n    } else {\n      const backupCustomObjects = Object.assign({}, _GLOBAL_CUSTOM_OBJECTS);\n      for (const key of Object.keys(customObjects)) {\n        _GLOBAL_CUSTOM_OBJECTS[key] = customObjects[key];\n      }\n      const returnObj = new cls(config[\"config\"]);\n      _GLOBAL_CUSTOM_OBJECTS = Object.assign({}, backupCustomObjects);\n      return returnObj;\n    }\n  }\n}\nfunction numberCompare(a, b) {\n  return a < b ? -1 : a > b ? 1 : 0;\n}\nfunction reverseNumberCompare(a, b) {\n  return -1 * numberCompare(a, b);\n}\nfunction unique2(xs) {\n  if (xs == null) {\n    return xs;\n  }\n  const out = [];\n  for (const x of xs) {\n    if (out.indexOf(x) === -1) {\n      out.push(x);\n    }\n  }\n  return out;\n}\nfunction isObjectEmpty(obj) {\n  if (obj == null) {\n    throw new ValueError(`Invalid value in obj: ${JSON.stringify(obj)}`);\n  }\n  for (const key in obj) {\n    if (obj.hasOwnProperty(key)) {\n      return false;\n    }\n  }\n  return true;\n}\nfunction checkStringTypeUnionValue(values, label, value) {\n  if (value == null) {\n    return;\n  }\n  if (values.indexOf(value) < 0) {\n    throw new ValueError(`${value} is not a valid ${label}.  Valid values are ${values} or null/undefined.`);\n  }\n}\nfunction checkArrayTypeAndLength(x, expectedType, minLength = 0, maxLength = Infinity) {\n  assert2(minLength >= 0);\n  assert2(maxLength >= minLength);\n  return Array.isArray(x) && x.length >= minLength && x.length <= maxLength && x.every((e2) => typeof e2 === expectedType);\n}\nfunction assertPositiveInteger(value, name) {\n  if (Array.isArray(value)) {\n    util_exports.assert(value.length > 0, () => `${name} is unexpectedly an empty array.`);\n    value.forEach((v, i2) => assertPositiveInteger(v, `element ${i2 + 1} of ${name}`));\n  } else {\n    util_exports.assert(Number.isInteger(value) && value > 0, () => `Expected ${name} to be a positive integer, but got ${formatAsFriendlyString(value)}.`);\n  }\n}\nfunction formatAsFriendlyString(value) {\n  if (value === null) {\n    return \"null\";\n  } else if (Array.isArray(value)) {\n    return \"[\" + value.map((v) => formatAsFriendlyString(v)).join(\",\") + \"]\";\n  } else if (typeof value === \"string\") {\n    return `\"${value}\"`;\n  } else {\n    return `${value}`;\n  }\n}\nfunction debounce(f, waitMs, nowFunc) {\n  let lastTime = nowFunc != null ? nowFunc() : util_exports.now();\n  let lastResult;\n  const f2 = (...args) => {\n    const now2 = nowFunc != null ? nowFunc() : util_exports.now();\n    if (now2 - lastTime < waitMs) {\n      return lastResult;\n    }\n    lastTime = now2;\n    lastResult = f(...args);\n    return lastResult;\n  };\n  return f2;\n}\nfunction mapActivationToFusedKernel(activationName) {\n  if (activationName === \"relu\") {\n    return \"relu\";\n  }\n  if (activationName === \"linear\") {\n    return \"linear\";\n  }\n  if (activationName === \"elu\") {\n    return \"elu\";\n  }\n  return null;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/backend/state.js\nvar _nextUniqueTensorId = 0;\nfunction getNextUniqueTensorId() {\n  return _nextUniqueTensorId++;\n}\nvar _uidPrefixes = {};\nfunction getUid(prefix = \"\") {\n  if (!(prefix in _uidPrefixes)) {\n    _uidPrefixes[prefix] = 0;\n  }\n  _uidPrefixes[prefix] += 1;\n  return prefix + _uidPrefixes[prefix].toString();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/keras_format/common.js\nvar VALID_DATA_FORMAT_VALUES = [\"channelsFirst\", \"channelsLast\"];\nvar VALID_INTERPOLATION_FORMAT_VALUES = [\"nearest\", \"bilinear\"];\nvar VALID_PADDING_MODE_VALUES = [\"valid\", \"same\", \"causal\"];\nvar VALID_POOL_MODE_VALUES = [\"max\", \"avg\"];\nvar VALID_BIDIRECTIONAL_MERGE_MODES = [\"sum\", \"mul\", \"concat\", \"ave\"];\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/common.js\nvar nameMap = /* @__PURE__ */ new Map();\nfunction checkDataFormat(value) {\n  checkStringTypeUnionValue(VALID_DATA_FORMAT_VALUES, \"DataFormat\", value);\n}\nfunction checkInterpolationFormat(value) {\n  checkStringTypeUnionValue(VALID_INTERPOLATION_FORMAT_VALUES, \"InterpolationFormat\", value);\n}\nfunction checkPaddingMode(value) {\n  checkStringTypeUnionValue(VALID_PADDING_MODE_VALUES, \"PaddingMode\", value);\n}\nfunction checkPoolMode(value) {\n  checkStringTypeUnionValue(VALID_POOL_MODE_VALUES, \"PoolMode\", value);\n}\nvar _nameScopeStack = [];\nvar _nameScopeDivider = \"/\";\nfunction nameScope(name, fn) {\n  _nameScopeStack.push(name);\n  try {\n    const val = fn();\n    _nameScopeStack.pop();\n    return val;\n  } catch (e2) {\n    _nameScopeStack.pop();\n    throw e2;\n  }\n}\nfunction currentNameScopePrefix() {\n  if (_nameScopeStack.length === 0) {\n    return \"\";\n  } else {\n    return _nameScopeStack.join(_nameScopeDivider) + _nameScopeDivider;\n  }\n}\nfunction getScopedTensorName(tensorName) {\n  if (!isValidTensorName(tensorName)) {\n    throw new Error(\"Not a valid tensor name: '\" + tensorName + \"'\");\n  }\n  return currentNameScopePrefix() + tensorName;\n}\nfunction getUniqueTensorName(scopedName) {\n  if (!isValidTensorName(scopedName)) {\n    throw new Error(\"Not a valid tensor name: '\" + scopedName + \"'\");\n  }\n  if (!nameMap.has(scopedName)) {\n    nameMap.set(scopedName, 0);\n  }\n  const index = nameMap.get(scopedName);\n  nameMap.set(scopedName, nameMap.get(scopedName) + 1);\n  if (index > 0) {\n    const result = `${scopedName}_${index}`;\n    nameMap.set(result, 1);\n    return result;\n  } else {\n    return scopedName;\n  }\n}\nvar tensorNameRegex = new RegExp(/^[A-Za-z0-9][-A-Za-z0-9\\._\\/]*$/);\nfunction isValidTensorName(name) {\n  return !!name.match(tensorNameRegex);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/math_utils.js\nfunction isInteger(x) {\n  return x === parseInt(x.toString(), 10);\n}\nfunction arrayProd(array2, begin, end) {\n  if (begin == null) {\n    begin = 0;\n  }\n  if (end == null) {\n    end = array2.length;\n  }\n  let prod6 = 1;\n  for (let i2 = begin; i2 < end; ++i2) {\n    prod6 *= array2[i2];\n  }\n  return prod6;\n}\nfunction min2(array2) {\n  if (array2.length === 0) {\n    return Number.NaN;\n  }\n  let min7 = Number.POSITIVE_INFINITY;\n  for (let i2 = 0; i2 < array2.length; i2++) {\n    const value = array2[i2];\n    if (value < min7) {\n      min7 = value;\n    }\n  }\n  return min7;\n}\nfunction max2(array2) {\n  if (array2.length === 0) {\n    return Number.NaN;\n  }\n  let max7 = Number.NEGATIVE_INFINITY;\n  for (let i2 = 0; i2 < array2.length; i2++) {\n    const value = array2[i2];\n    if (value > max7) {\n      max7 = value;\n    }\n  }\n  return max7;\n}\nfunction range2(begin, end) {\n  if (end < begin) {\n    throw new ValueError(`end (${end}) < begin (${begin}) is forbidden.`);\n  }\n  const out = [];\n  for (let i2 = begin; i2 < end; ++i2) {\n    out.push(i2);\n  }\n  return out;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/backend/common.js\nvar _epsilon;\nfunction epsilon() {\n  if (_epsilon == null) {\n    _epsilon = backend().epsilon();\n  }\n  return _epsilon;\n}\nfunction imageDataFormat() {\n  return \"channelsLast\";\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/backend/tfjs_backend.js\nfunction cast2(x, dtype) {\n  return cast(x, dtype);\n}\nfunction expandDims2(x, axis = -1) {\n  const outShape = x.shape.slice();\n  if (axis < 0) {\n    axis = outShape.length + axis + 1;\n  }\n  outShape.splice(axis, 0, 1);\n  return reshape(x, outShape);\n}\nfunction repeat(x, n2) {\n  return tidy(() => {\n    if (x.shape.length !== 2) {\n      throw new ValueError(`repeat() expects a rank-2 tensor, but received a rank-${x.shape.length} tensor.`);\n    }\n    const y = expandDims2(x, 1);\n    return tile2(y, [1, n2, 1]);\n  });\n}\nfunction flatten2(x) {\n  const newShape = [arrayProd(x.shape)];\n  return reshape(x, newShape);\n}\nfunction batchFlatten(x) {\n  if (x.rank <= 1) {\n    throw new ValueError(`batchFlatten requires a minimum rank of 2. Got rank: ${x.rank}.`);\n  }\n  const newShape = [x.shape[0], arrayProd(x.shape, 1)];\n  return reshape(x, newShape);\n}\nfunction sliceAlongFirstAxis(array2, start, size) {\n  return tidy(() => {\n    switch (array2.rank) {\n      case 1:\n        return slice1d(array2, start, size);\n      case 2:\n        return slice2d(array2, [start, 0], [size, array2.shape[1]]);\n      case 3:\n        return slice3d(array2, [start, 0, 0], [size, array2.shape[1], array2.shape[2]]);\n      case 4:\n        return slice4d(array2, [start, 0, 0, 0], [size, array2.shape[1], array2.shape[2], array2.shape[3]]);\n      case 5:\n        return slice(array2, [start, 0, 0, 0, 0], [\n          size,\n          array2.shape[1],\n          array2.shape[2],\n          array2.shape[3],\n          array2.shape[4]\n        ]);\n      case 6:\n        return slice(array2, [start, 0, 0, 0, 0, 0], [\n          size,\n          array2.shape[1],\n          array2.shape[2],\n          array2.shape[3],\n          array2.shape[4],\n          array2.shape[5]\n        ]);\n      default:\n        throw new ValueError(`sliceAlongFirstAxis() received an unsupported tensor rank: ${array2.rank}`);\n    }\n  });\n}\nfunction sliceAlongLastAxis(array2, start, size) {\n  return tidy(() => {\n    switch (array2.rank) {\n      case 1:\n        return slice1d(array2, start, size);\n      case 2:\n        return slice2d(array2, [0, start], [array2.shape[0], size]);\n      case 3:\n        return slice3d(array2, [0, 0, start], [array2.shape[0], array2.shape[1], size]);\n      case 4:\n        return slice4d(array2, [0, 0, 0, start], [array2.shape[0], array2.shape[1], array2.shape[2], size]);\n      default:\n        throw new ValueError(`sliceAlongLastAxis() received an unsupported tensor rank: ${array2.rank}`);\n    }\n  });\n}\nfunction sliceAlongAxis(array2, start, size, axis) {\n  return tidy(() => {\n    switch (array2.rank) {\n      case 1:\n        return slice1d(array2, start, size);\n      case 2:\n        switch (axis) {\n          case 1:\n            return sliceAlongFirstAxis(array2, start, size);\n          case 2:\n            return sliceAlongLastAxis(array2, start, size);\n          default:\n            throw new ValueError(`The axis is not within the rank of the tensor ${axis}`);\n        }\n      case 3:\n        switch (axis) {\n          case 1:\n            return sliceAlongFirstAxis(array2, start, size);\n          case 2:\n            return slice3d(array2, [0, start, 0], [array2.shape[0], size, array2.shape[2]]);\n          case 3:\n            return sliceAlongLastAxis(array2, start, size);\n          default:\n            throw new ValueError(`The axis is not within the rank of the tensor ${axis}`);\n        }\n      case 4:\n        switch (axis) {\n          case 1:\n            return sliceAlongFirstAxis(array2, start, size);\n          case 2:\n            return slice4d(array2, [0, start, 0, 0], [array2.shape[0], size, array2.shape[2], array2.shape[3]]);\n          case 3:\n            return slice4d(array2, [0, 0, start, 0], [array2.shape[0], array2.shape[1], size, array2.shape[3]]);\n          case 4:\n            return sliceAlongLastAxis(array2, start, size);\n          default:\n            throw new ValueError(`The axis is not within the rank of the tensor ${axis}`);\n        }\n      default:\n        throw new ValueError(`sliceAlongLastAxis() received an unsupported tensor rank: ${array2.rank}`);\n    }\n  });\n}\nfunction concatenate(tensors, axis = -1) {\n  let rank;\n  if (axis < 0) {\n    rank = tensors[0].rank;\n    if (rank !== 0) {\n      axis = rank;\n    } else {\n      axis = 0;\n    }\n  }\n  if (axis === tensors[0].rank) {\n    axis = -1;\n  }\n  return concat(tensors, axis);\n}\nfunction concatAlongFirstAxis(a, b) {\n  switch (a.rank) {\n    case 1:\n      return concat1d([a, b]);\n    case 2:\n      return concat2d([a, b], 0);\n    case 3:\n      return concat3d([a, b], 0);\n    case 4:\n      return concat4d([a, b], 0);\n    default:\n      throw new ValueError(`concatAlongFirstAxis() received an unsupported tensor rank: ${a.rank}`);\n  }\n}\nfunction tile2(x, n2) {\n  if (!Array.isArray(n2)) {\n    n2 = [n2];\n  }\n  if (x.rank !== n2.length) {\n    throw new ValueError(`The length of input n (${n2.length}) does not match the number of dimensions in input x (${x.rank})`);\n  }\n  return tile(x, n2);\n}\nfunction randomNormal2(shape, mean5 = 0, stddev = 1, dtype, seed) {\n  return randomNormal(shape, mean5, stddev, dtype, seed);\n}\nfunction dot2(a, b, activation2, bias) {\n  if (a.rank < 2 || b.rank < 2) {\n    throw new NotImplementedError(`dot requires both inputs to be rank >= 2 but got x shape = ${a.shape} and y shape = ${b.shape}`);\n  }\n  if (b.rank >= 3) {\n    const xLastDim = a.shape.slice(-1)[0];\n    const ySecondLastDim = b.shape.slice(-2)[0];\n    if (xLastDim !== ySecondLastDim) {\n      throw new NotImplementedError(`If rank y >= 3, then the second last dim of y must equal the last dim of x but got x shape = ${a.shape} and  y shape = ${b.shape}`);\n    }\n  }\n  if (a.rank === 2 && b.rank === 2) {\n    const transposeA = false;\n    const transposeB = false;\n    return fused_ops_exports.matMul({\n      a,\n      b,\n      transposeA,\n      transposeB,\n      bias: bias ? reshapeBias(a.rank, bias, imageDataFormat()) : null,\n      activation: activation2\n    });\n  } else {\n    const aFirstDims = a.shape.slice();\n    const aLastDim = aFirstDims.pop();\n    a = reshape(a, [-1, aLastDim]);\n    const bShape = b.shape.slice();\n    const bLastDim = bShape.pop();\n    const ySecondLastDim = bShape.pop();\n    const yOtherDims = [...bShape, bLastDim];\n    const perm = Array.from({ length: b.rank }, (_, i2) => {\n      if (i2 === 0) {\n        return b.rank - 2;\n      } else if (i2 <= b.rank - 2) {\n        return i2 - 1;\n      }\n      return i2;\n    });\n    b = reshape(transpose(b, perm), [ySecondLastDim, -1]);\n    const outputShape = [...aFirstDims, ...yOtherDims];\n    const transposeA = false;\n    const transposeB = false;\n    return reshape(fused_ops_exports.matMul({\n      a,\n      b,\n      transposeA,\n      transposeB,\n      bias: bias ? reshapeBias(a.rank, bias, imageDataFormat()) : null,\n      activation: activation2\n    }), outputShape);\n  }\n}\nfunction gather2(reference, indices, axis) {\n  return tidy(() => {\n    if (Array.isArray(indices)) {\n      indices = tensor1d(indices, \"int32\");\n    } else {\n      indices = cast(indices, \"int32\");\n    }\n    return gather(reference, indices, axis);\n  });\n}\nfunction square2(x) {\n  return mul(x, x);\n}\nfunction reshapeBias(xRank, bias, dataFormat) {\n  const biasShape = bias.shape;\n  if (bias.rank !== 1 && bias.rank !== xRank) {\n    throw new ValueError(`Unexpected bias dimensions: ${bias.rank}; expected it to be 1 or ${xRank}`);\n  }\n  if (xRank === 5) {\n    if (dataFormat === \"channelsFirst\") {\n      if (biasShape.length === 1) {\n        return reshape(bias, [1, biasShape[0], 1, 1, 1]);\n      } else {\n        return reshape(bias, [1, biasShape[3], biasShape[0], biasShape[1], biasShape[2]]);\n      }\n    } else if (dataFormat === \"channelsLast\") {\n      if (biasShape.length === 1) {\n        return reshape(bias, [1, 1, 1, 1, biasShape[0]]);\n      } else {\n        return reshape(bias, [1].concat(biasShape));\n      }\n    }\n  } else if (xRank === 4) {\n    if (dataFormat === \"channelsFirst\") {\n      if (biasShape.length === 1) {\n        return reshape(bias, [1, biasShape[0], 1, 1]);\n      } else {\n        return reshape(bias, [1, biasShape[2], biasShape[0], biasShape[1]]);\n      }\n    } else if (dataFormat === \"channelsLast\") {\n      if (biasShape.length === 1) {\n        return reshape(bias, [1, 1, 1, biasShape[0]]);\n      } else {\n        return reshape(bias, [1].concat(biasShape));\n      }\n    }\n  } else if (xRank === 3) {\n    if (dataFormat === \"channelsFirst\") {\n      if (biasShape.length === 1) {\n        return reshape(bias, [1, biasShape[0], 1]);\n      } else {\n        return reshape(bias, [1, biasShape[1], biasShape[0]]);\n      }\n    } else if (dataFormat === \"channelsLast\") {\n      if (biasShape.length === 1) {\n        return reshape(bias, [1, 1, biasShape[0]]);\n      } else {\n        return reshape(bias, [1].concat(biasShape));\n      }\n    }\n  } else if (xRank < 3) {\n    return bias;\n  }\n  throw new ValueError(`Unsupported input rank by biasAdd: ${bias.rank}`);\n}\nfunction biasAdd(x, bias, dataFormat) {\n  return tidy(() => {\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    checkDataFormat(dataFormat);\n    return add2(x, reshapeBias(x.rank, bias, dataFormat));\n  });\n}\nfunction elu2(x, alpha = 1) {\n  if (alpha !== 1) {\n    throw new NotImplementedError(`Support for alpha values other than 1 (${alpha}) is not implemented yet.`);\n  }\n  return elu(x);\n}\nfunction softsign(x) {\n  return tidy(() => div(x, add2(abs(x), 1)));\n}\nfunction dropout2(x, level, noiseShape, seed) {\n  return tidy(() => dropout(x, level, noiseShape, seed));\n}\nfunction hardSigmoid(x) {\n  return tidy(() => {\n    const y = add2(0.5, mul(0.2, x));\n    return clipByValue(y, 0, 1);\n  });\n}\nfunction inTrainPhase(x, alt, training = false) {\n  return training ? x() : alt();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/keras_format/initializer_config.js\nvar VALID_FAN_MODE_VALUES = [\"fanIn\", \"fanOut\", \"fanAvg\"];\nvar VALID_DISTRIBUTION_VALUES = [\"normal\", \"uniform\", \"truncatedNormal\"];\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/initializers.js\nfunction checkFanMode(value) {\n  checkStringTypeUnionValue(VALID_FAN_MODE_VALUES, \"FanMode\", value);\n}\nfunction checkDistribution(value) {\n  checkStringTypeUnionValue(VALID_DISTRIBUTION_VALUES, \"Distribution\", value);\n}\nvar Initializer = class extends serialization_exports.Serializable {\n  fromConfigUsesCustomObjects() {\n    return false;\n  }\n  getConfig() {\n    return {};\n  }\n};\nvar Zeros = class extends Initializer {\n  apply(shape, dtype) {\n    return zeros(shape, dtype);\n  }\n};\nZeros.className = \"Zeros\";\nserialization_exports.registerClass(Zeros);\nvar Ones = class extends Initializer {\n  apply(shape, dtype) {\n    return ones2(shape, dtype);\n  }\n};\nOnes.className = \"Ones\";\nserialization_exports.registerClass(Ones);\nvar Constant = class extends Initializer {\n  constructor(args) {\n    super();\n    if (typeof args !== \"object\") {\n      throw new ValueError(`Expected argument of type ConstantConfig but got ${args}`);\n    }\n    if (args.value === void 0) {\n      throw new ValueError(`config must have value set but got ${args}`);\n    }\n    this.value = args.value;\n  }\n  apply(shape, dtype) {\n    return tidy(() => mul(scalar(this.value), ones2(shape, dtype)));\n  }\n  getConfig() {\n    return {\n      value: this.value\n    };\n  }\n};\nConstant.className = \"Constant\";\nserialization_exports.registerClass(Constant);\nvar RandomUniform = class extends Initializer {\n  constructor(args) {\n    super();\n    this.DEFAULT_MINVAL = -0.05;\n    this.DEFAULT_MAXVAL = 0.05;\n    this.minval = args.minval || this.DEFAULT_MINVAL;\n    this.maxval = args.maxval || this.DEFAULT_MAXVAL;\n    this.seed = args.seed;\n  }\n  apply(shape, dtype) {\n    return randomUniform(shape, this.minval, this.maxval, dtype);\n  }\n  getConfig() {\n    return { minval: this.minval, maxval: this.maxval, seed: this.seed };\n  }\n};\nRandomUniform.className = \"RandomUniform\";\nserialization_exports.registerClass(RandomUniform);\nvar RandomNormal = class extends Initializer {\n  constructor(args) {\n    super();\n    this.DEFAULT_MEAN = 0;\n    this.DEFAULT_STDDEV = 0.05;\n    this.mean = args.mean || this.DEFAULT_MEAN;\n    this.stddev = args.stddev || this.DEFAULT_STDDEV;\n    this.seed = args.seed;\n  }\n  apply(shape, dtype) {\n    dtype = dtype || \"float32\";\n    if (dtype !== \"float32\" && dtype !== \"int32\") {\n      throw new NotImplementedError(`randomNormal does not support dType ${dtype}.`);\n    }\n    return randomNormal2(shape, this.mean, this.stddev, dtype, this.seed);\n  }\n  getConfig() {\n    return { mean: this.mean, stddev: this.stddev, seed: this.seed };\n  }\n};\nRandomNormal.className = \"RandomNormal\";\nserialization_exports.registerClass(RandomNormal);\nvar TruncatedNormal = class extends Initializer {\n  constructor(args) {\n    super();\n    this.DEFAULT_MEAN = 0;\n    this.DEFAULT_STDDEV = 0.05;\n    this.mean = args.mean || this.DEFAULT_MEAN;\n    this.stddev = args.stddev || this.DEFAULT_STDDEV;\n    this.seed = args.seed;\n  }\n  apply(shape, dtype) {\n    dtype = dtype || \"float32\";\n    if (dtype !== \"float32\" && dtype !== \"int32\") {\n      throw new NotImplementedError(`truncatedNormal does not support dType ${dtype}.`);\n    }\n    return truncatedNormal(shape, this.mean, this.stddev, dtype, this.seed);\n  }\n  getConfig() {\n    return { mean: this.mean, stddev: this.stddev, seed: this.seed };\n  }\n};\nTruncatedNormal.className = \"TruncatedNormal\";\nserialization_exports.registerClass(TruncatedNormal);\nvar Identity2 = class extends Initializer {\n  constructor(args) {\n    super();\n    this.gain = args.gain != null ? args.gain : 1;\n  }\n  apply(shape, dtype) {\n    return tidy(() => {\n      if (shape.length !== 2 || shape[0] !== shape[1]) {\n        throw new ValueError(\"Identity matrix initializer can only be used for 2D square matrices.\");\n      } else {\n        return mul(this.gain, eye(shape[0]));\n      }\n    });\n  }\n  getConfig() {\n    return { gain: this.gain };\n  }\n};\nIdentity2.className = \"Identity\";\nserialization_exports.registerClass(Identity2);\nfunction computeFans(shape, dataFormat = \"channelsLast\") {\n  let fanIn;\n  let fanOut;\n  checkDataFormat(dataFormat);\n  if (shape.length === 2) {\n    fanIn = shape[0];\n    fanOut = shape[1];\n  } else if ([3, 4, 5].indexOf(shape.length) !== -1) {\n    if (dataFormat === \"channelsFirst\") {\n      const receptiveFieldSize = arrayProd(shape, 2);\n      fanIn = shape[1] * receptiveFieldSize;\n      fanOut = shape[0] * receptiveFieldSize;\n    } else if (dataFormat === \"channelsLast\") {\n      const receptiveFieldSize = arrayProd(shape, 0, shape.length - 2);\n      fanIn = shape[shape.length - 2] * receptiveFieldSize;\n      fanOut = shape[shape.length - 1] * receptiveFieldSize;\n    }\n  } else {\n    const shapeProd = arrayProd(shape);\n    fanIn = Math.sqrt(shapeProd);\n    fanOut = Math.sqrt(shapeProd);\n  }\n  return [fanIn, fanOut];\n}\nvar VarianceScaling = class extends Initializer {\n  constructor(args) {\n    super();\n    if (args.scale < 0) {\n      throw new ValueError(`scale must be a positive float. Got: ${args.scale}`);\n    }\n    this.scale = args.scale == null ? 1 : args.scale;\n    this.mode = args.mode == null ? \"fanIn\" : args.mode;\n    checkFanMode(this.mode);\n    this.distribution = args.distribution == null ? \"normal\" : args.distribution;\n    checkDistribution(this.distribution);\n    this.seed = args.seed;\n  }\n  apply(shape, dtype) {\n    const fans = computeFans(shape);\n    const fanIn = fans[0];\n    const fanOut = fans[1];\n    let scale2 = this.scale;\n    if (this.mode === \"fanIn\") {\n      scale2 /= Math.max(1, fanIn);\n    } else if (this.mode === \"fanOut\") {\n      scale2 /= Math.max(1, fanOut);\n    } else {\n      scale2 /= Math.max(1, (fanIn + fanOut) / 2);\n    }\n    if (this.distribution === \"normal\") {\n      const stddev = Math.sqrt(scale2);\n      dtype = dtype || \"float32\";\n      if (dtype !== \"float32\" && dtype !== \"int32\") {\n        throw new NotImplementedError(`${this.getClassName()} does not support dType ${dtype}.`);\n      }\n      return truncatedNormal(shape, 0, stddev, dtype, this.seed);\n    } else {\n      const limit = Math.sqrt(3 * scale2);\n      return randomUniform(shape, -limit, limit, dtype);\n    }\n  }\n  getConfig() {\n    return {\n      scale: this.scale,\n      mode: this.mode,\n      distribution: this.distribution,\n      seed: this.seed\n    };\n  }\n};\nVarianceScaling.className = \"VarianceScaling\";\nserialization_exports.registerClass(VarianceScaling);\nvar GlorotUniform = class extends VarianceScaling {\n  constructor(args) {\n    super({\n      scale: 1,\n      mode: \"fanAvg\",\n      distribution: \"uniform\",\n      seed: args == null ? null : args.seed\n    });\n  }\n  getClassName() {\n    return VarianceScaling.className;\n  }\n};\nGlorotUniform.className = \"GlorotUniform\";\nserialization_exports.registerClass(GlorotUniform);\nvar GlorotNormal = class extends VarianceScaling {\n  constructor(args) {\n    super({\n      scale: 1,\n      mode: \"fanAvg\",\n      distribution: \"normal\",\n      seed: args == null ? null : args.seed\n    });\n  }\n  getClassName() {\n    return VarianceScaling.className;\n  }\n};\nGlorotNormal.className = \"GlorotNormal\";\nserialization_exports.registerClass(GlorotNormal);\nvar HeNormal = class extends VarianceScaling {\n  constructor(args) {\n    super({\n      scale: 2,\n      mode: \"fanIn\",\n      distribution: \"normal\",\n      seed: args == null ? null : args.seed\n    });\n  }\n  getClassName() {\n    return VarianceScaling.className;\n  }\n};\nHeNormal.className = \"HeNormal\";\nserialization_exports.registerClass(HeNormal);\nvar HeUniform = class extends VarianceScaling {\n  constructor(args) {\n    super({\n      scale: 2,\n      mode: \"fanIn\",\n      distribution: \"uniform\",\n      seed: args == null ? null : args.seed\n    });\n  }\n  getClassName() {\n    return VarianceScaling.className;\n  }\n};\nHeUniform.className = \"HeUniform\";\nserialization_exports.registerClass(HeUniform);\nvar LeCunNormal = class extends VarianceScaling {\n  constructor(args) {\n    super({\n      scale: 1,\n      mode: \"fanIn\",\n      distribution: \"normal\",\n      seed: args == null ? null : args.seed\n    });\n  }\n  getClassName() {\n    return VarianceScaling.className;\n  }\n};\nLeCunNormal.className = \"LeCunNormal\";\nserialization_exports.registerClass(LeCunNormal);\nvar LeCunUniform = class extends VarianceScaling {\n  constructor(args) {\n    super({\n      scale: 1,\n      mode: \"fanIn\",\n      distribution: \"uniform\",\n      seed: args == null ? null : args.seed\n    });\n  }\n  getClassName() {\n    return VarianceScaling.className;\n  }\n};\nLeCunUniform.className = \"LeCunNormal\";\nserialization_exports.registerClass(LeCunUniform);\nvar Orthogonal = class extends Initializer {\n  constructor(args) {\n    super();\n    this.DEFAULT_GAIN = 1;\n    this.gain = args.gain == null ? this.DEFAULT_GAIN : args.gain;\n    this.seed = args.seed;\n    if (this.seed != null) {\n      throw new NotImplementedError(\"Random seed is not implemented for Orthogonal Initializer yet.\");\n    }\n  }\n  apply(shape, dtype) {\n    return tidy(() => {\n      if (shape.length < 2) {\n        throw new NotImplementedError(\"Shape must be at least 2D.\");\n      }\n      if (shape[0] * shape[1] > 2e3) {\n        console.warn(`Orthogonal initializer is being called on a matrix with more than 2000 (${shape[0] * shape[1]}) elements: Slowness may result.`);\n      }\n      const normalizedShape = shape[0] > shape[1] ? [shape[1], shape[0]] : shape;\n      const a = randomNormal2(normalizedShape, 0, 1, \"float32\");\n      let q = linalg.gramSchmidt(a);\n      if (shape[0] > shape[1]) {\n        q = transpose(q);\n      }\n      return mul(this.gain, q);\n    });\n  }\n  getConfig() {\n    return {\n      gain: this.gain,\n      seed: this.seed\n    };\n  }\n};\nOrthogonal.className = \"Orthogonal\";\nserialization_exports.registerClass(Orthogonal);\nvar INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP = {\n  \"constant\": \"Constant\",\n  \"glorotNormal\": \"GlorotNormal\",\n  \"glorotUniform\": \"GlorotUniform\",\n  \"heNormal\": \"HeNormal\",\n  \"heUniform\": \"HeUniform\",\n  \"identity\": \"Identity\",\n  \"leCunNormal\": \"LeCunNormal\",\n  \"leCunUniform\": \"LeCunUniform\",\n  \"ones\": \"Ones\",\n  \"orthogonal\": \"Orthogonal\",\n  \"randomNormal\": \"RandomNormal\",\n  \"randomUniform\": \"RandomUniform\",\n  \"truncatedNormal\": \"TruncatedNormal\",\n  \"varianceScaling\": \"VarianceScaling\",\n  \"zeros\": \"Zeros\"\n};\nfunction deserializeInitializer(config, customObjects = {}) {\n  return deserializeKerasObject(config, serialization_exports.SerializationMap.getMap().classNameMap, customObjects, \"initializer\");\n}\nfunction serializeInitializer(initializer) {\n  return serializeKerasObject(initializer);\n}\nfunction getInitializer(identifier) {\n  if (typeof identifier === \"string\") {\n    const className = identifier in INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP ? INITIALIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP[identifier] : identifier;\n    if (className === \"GlorotNormal\") {\n      return new GlorotNormal();\n    } else if (className === \"GlorotUniform\") {\n      return new GlorotUniform();\n    } else if (className === \"HeNormal\") {\n      return new HeNormal();\n    } else if (className === \"HeUniform\") {\n      return new HeUniform();\n    } else if (className === \"LeCunNormal\") {\n      return new LeCunNormal();\n    } else if (className === \"LeCunUniform\") {\n      return new LeCunUniform();\n    } else {\n      const config = {};\n      config[\"className\"] = className;\n      config[\"config\"] = {};\n      return deserializeInitializer(config);\n    }\n  } else if (identifier instanceof Initializer) {\n    return identifier;\n  } else {\n    return deserializeInitializer(identifier);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/types_utils.js\nfunction isArrayOfShapes(x) {\n  return Array.isArray(x) && Array.isArray(x[0]);\n}\nfunction normalizeShapeList(x) {\n  if (x.length === 0) {\n    return [];\n  }\n  if (!Array.isArray(x[0])) {\n    return [x];\n  }\n  return x;\n}\nfunction getExactlyOneTensor(xs) {\n  let x;\n  if (Array.isArray(xs)) {\n    if (xs.length !== 1) {\n      throw new ValueError(`Expected Tensor length to be 1; got ${xs.length}`);\n    }\n    x = xs[0];\n  } else {\n    x = xs;\n  }\n  return x;\n}\nfunction getExactlyOneShape(shapes) {\n  if (Array.isArray(shapes) && Array.isArray(shapes[0])) {\n    if (shapes.length === 1) {\n      shapes = shapes;\n      return shapes[0];\n    } else {\n      throw new ValueError(`Expected exactly 1 Shape; got ${shapes.length}`);\n    }\n  } else {\n    return shapes;\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/variable_utils.js\nfunction countParamsInWeights(weights) {\n  let count2 = 0;\n  for (const weight of weights) {\n    if (weight.shape.length === 0) {\n      count2 += 1;\n    } else {\n      count2 += weight.shape.reduce((a, b) => a * b);\n    }\n  }\n  return count2;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/variables.js\nvar DEFAULT_VARIABLE_NAME_PREFIX = \"Variable\";\nvar LayerVariable = class {\n  constructor(val, dtype = \"float32\", name = DEFAULT_VARIABLE_NAME_PREFIX, trainable = true, constraint = null) {\n    this.dtype = dtype == null ? \"float32\" : dtype;\n    this.shape = val.shape;\n    this.id = getNextUniqueTensorId();\n    name = name == null ? DEFAULT_VARIABLE_NAME_PREFIX : name;\n    this.originalName = getScopedTensorName(name);\n    this.name = getUniqueTensorName(this.originalName);\n    this.trainable_ = trainable;\n    this.constraint = constraint;\n    this.val = variable(val, this.trainable_, this.name, this.dtype);\n  }\n  read() {\n    this.assertNotDisposed();\n    return this.val;\n  }\n  write(newVal) {\n    this.assertNotDisposed();\n    checkShapesMatch(this.val, newVal);\n    if (this.val.id !== newVal.id) {\n      this.val.assign(newVal);\n      if (this.constraint != null) {\n        this.val.assign(this.constraint.apply(this.val));\n      }\n    }\n    return this;\n  }\n  dispose() {\n    this.assertNotDisposed();\n    this.val.dispose();\n  }\n  assertNotDisposed() {\n    if (this.val.isDisposed) {\n      throw new Error(`LayersVariable ${this.name} is already disposed.`);\n    }\n  }\n  get trainable() {\n    return this.trainable_;\n  }\n  set trainable(trainable) {\n    this.trainable_ = trainable;\n    this.val.trainable = trainable;\n  }\n};\nfunction checkShapesMatch(x, y) {\n  if (x.shape.toString() !== y.shape.toString()) {\n    throw new Error(\"Shape mismatch: \" + JSON.stringify(x.shape) + \" vs. \" + JSON.stringify(y.shape));\n  }\n}\nfunction batchGetValue(xs) {\n  return xs.map((x) => x.read());\n}\nfunction batchSetValue(variablesAndValues) {\n  variablesAndValues.forEach((variableAndValue) => {\n    const variable2 = variableAndValue[0];\n    variable2.write(variableAndValue[1]);\n  });\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/topology.js\nvar InputSpec = class {\n  constructor(args) {\n    this.dtype = args.dtype;\n    this.shape = args.shape;\n    if (args.shape != null) {\n      this.ndim = args.shape.length;\n    } else {\n      this.ndim = args.ndim;\n    }\n    this.maxNDim = args.maxNDim;\n    this.minNDim = args.minNDim;\n    this.axes = args.axes || {};\n  }\n};\nvar SymbolicTensor = class {\n  constructor(dtype, shape, sourceLayer, inputs, callArgs, name, outputTensorIndex) {\n    this.dtype = dtype;\n    this.shape = shape;\n    this.sourceLayer = sourceLayer;\n    this.inputs = inputs;\n    this.callArgs = callArgs;\n    this.outputTensorIndex = outputTensorIndex;\n    this.id = getNextUniqueTensorId();\n    if (name != null) {\n      this.originalName = getScopedTensorName(name);\n      this.name = getUniqueTensorName(this.originalName);\n    }\n    this.rank = shape.length;\n  }\n};\nvar _nextNodeID = 0;\nvar Node = class {\n  constructor(args, callArgs) {\n    this.callArgs = callArgs;\n    this.id = _nextNodeID++;\n    this.outboundLayer = args.outboundLayer;\n    this.inboundLayers = args.inboundLayers;\n    this.nodeIndices = args.nodeIndices;\n    this.tensorIndices = args.tensorIndices;\n    this.inputTensors = args.inputTensors;\n    this.outputTensors = args.outputTensors;\n    this.inputMasks = args.inputMasks;\n    this.outputMasks = args.outputMasks;\n    this.inputShapes = args.inputShapes;\n    this.outputShapes = args.outputShapes;\n    for (const layer of args.inboundLayers) {\n      if (layer != null) {\n        layer.outboundNodes.push(this);\n      }\n    }\n    args.outboundLayer.inboundNodes.push(this);\n  }\n  getConfig() {\n    const inboundNames = [];\n    for (const layer of this.inboundLayers) {\n      if (layer != null) {\n        inboundNames.push(layer.name);\n      } else {\n        inboundNames.push(null);\n      }\n    }\n    return {\n      outboundLayer: this.outboundLayer ? this.outboundLayer.name : null,\n      inboundLayers: inboundNames,\n      nodeIndices: this.nodeIndices,\n      tensorIndices: this.tensorIndices\n    };\n  }\n};\nvar _nextLayerID = 0;\nvar Layer = class extends serialization_exports.Serializable {\n  constructor(args = {}) {\n    super();\n    this._callHook = null;\n    this._addedWeightNames = [];\n    this._stateful = false;\n    this.id = _nextLayerID++;\n    this.activityRegularizer = null;\n    this.inputSpec = null;\n    this.supportsMasking = false;\n    this._trainableWeights = [];\n    this._nonTrainableWeights = [];\n    this._losses = [];\n    this._updates = [];\n    this._built = false;\n    this.inboundNodes = [];\n    this.outboundNodes = [];\n    let name = args.name;\n    if (!name) {\n      const prefix = this.getClassName();\n      name = toSnakeCase(prefix) + \"_\" + getUid(prefix);\n    }\n    this.name = name;\n    this.trainable_ = args.trainable == null ? true : args.trainable;\n    if (args.inputShape != null || args.batchInputShape != null) {\n      let batchInputShape;\n      if (args.batchInputShape != null) {\n        batchInputShape = args.batchInputShape;\n      } else if (args.inputShape != null) {\n        let batchSize = null;\n        if (args.batchSize != null) {\n          batchSize = args.batchSize;\n        }\n        batchInputShape = [batchSize].concat(args.inputShape);\n      }\n      this.batchInputShape = batchInputShape;\n      let dtype = args.dtype;\n      if (dtype == null) {\n        dtype = args.inputDType;\n      }\n      if (dtype == null) {\n        dtype = \"float32\";\n      }\n      this.dtype = dtype;\n    }\n    if (args.weights != null) {\n      this.initialWeights = args.weights;\n    } else {\n      this.initialWeights = null;\n    }\n    this._refCount = null;\n    this.fastWeightInitDuringBuild = false;\n  }\n  static nodeKey(layer, nodeIndex) {\n    return layer.name + \"_ib-\" + nodeIndex.toString();\n  }\n  getNodeAtIndex(nodeIndex, attrName) {\n    if (this.inboundNodes.length === 0) {\n      throw new RuntimeError(`The layer has never been called and thus has no defined ${attrName}.`);\n    }\n    if (this.inboundNodes.length <= nodeIndex) {\n      throw new ValueError(`Asked to get ${attrName} at node ${nodeIndex}, but the layer has only ${this.inboundNodes.length} inbound nodes.`);\n    }\n    return this.inboundNodes[nodeIndex];\n  }\n  getInputAt(nodeIndex) {\n    return singletonOrArray(this.getNodeAtIndex(nodeIndex, \"input\").inputTensors);\n  }\n  getOutputAt(nodeIndex) {\n    return singletonOrArray(this.getNodeAtIndex(nodeIndex, \"output\").outputTensors);\n  }\n  get input() {\n    if (this.inboundNodes.length > 1) {\n      throw new AttributeError(`Layer ${this.name} has multiple inbound nodes, hence the notion of \"layer input\" is ill-defined. Use \\`getInputAt(nodeIndex)\\` instead.`);\n    } else if (this.inboundNodes.length === 0) {\n      throw new AttributeError(`Layer ${this.name} is not connected, no input to return.`);\n    }\n    return singletonOrArray(this.getNodeAtIndex(0, \"input\").inputTensors);\n  }\n  get output() {\n    if (this.inboundNodes.length === 0) {\n      throw new AttributeError(`Layer ${this.name} has no inbound nodes.`);\n    }\n    if (this.inboundNodes.length > 1) {\n      throw new AttributeError(`Layer ${this.name} has multiple inbound nodes, hence the notion of \"layer output\" is ill-defined. Use \\`getOutputAt(nodeIndex)\\` instead.`);\n    }\n    return singletonOrArray(this.getNodeAtIndex(0, \"output\").outputTensors);\n  }\n  get losses() {\n    return this._losses;\n  }\n  calculateLosses() {\n    return this.losses.map((lossFn) => lossFn());\n  }\n  get updates() {\n    return this._updates;\n  }\n  get built() {\n    return this._built;\n  }\n  set built(built) {\n    this._built = built;\n  }\n  get trainable() {\n    return this.trainable_;\n  }\n  set trainable(trainable) {\n    this._trainableWeights.forEach((w) => w.trainable = trainable);\n    this.trainable_ = trainable;\n  }\n  get trainableWeights() {\n    if (this.trainable_) {\n      return this._trainableWeights.filter((w) => w.trainable);\n    } else {\n      return [];\n    }\n  }\n  set trainableWeights(weights) {\n    this._trainableWeights = weights;\n  }\n  get nonTrainableWeights() {\n    if (this.trainable) {\n      return this._trainableWeights.filter((w) => !w.trainable).concat(this._nonTrainableWeights);\n    } else {\n      return this._trainableWeights.concat(this._nonTrainableWeights);\n    }\n  }\n  set nonTrainableWeights(weights) {\n    this._nonTrainableWeights = weights;\n  }\n  get weights() {\n    return this.trainableWeights.concat(this.nonTrainableWeights);\n  }\n  get stateful() {\n    return this._stateful;\n  }\n  resetStates() {\n    if (!this.stateful) {\n      throw new Error(\"Cannot call the resetStates() method of a non-stateful Layer object.\");\n    }\n  }\n  assertInputCompatibility(inputs) {\n    inputs = toList(inputs);\n    if (this.inputSpec == null || this.inputSpec.length === 0) {\n      return;\n    }\n    const inputSpec = toList(this.inputSpec);\n    if (inputs.length !== inputSpec.length) {\n      throw new ValueError(`Layer ${this.name} expects ${inputSpec.length} inputs, but it received ${inputs.length} input tensors. Input received: ${inputs}`);\n    }\n    for (let inputIndex = 0; inputIndex < inputs.length; inputIndex++) {\n      const x = inputs[inputIndex];\n      const spec = inputSpec[inputIndex];\n      if (spec == null) {\n        continue;\n      }\n      const ndim = x.rank;\n      if (spec.ndim != null) {\n        if (ndim !== spec.ndim) {\n          throw new ValueError(`Input ${inputIndex} is incompatible with layer ${this.name}: expected ndim=${spec.ndim}, found ndim=${ndim}`);\n        }\n      }\n      if (spec.maxNDim != null) {\n        if (ndim > spec.maxNDim) {\n          throw new ValueError(`Input ${inputIndex} is incompatible with layer ${this.name}: expected max_ndim=${spec.maxNDim}, found ndim=${ndim}`);\n        }\n      }\n      if (spec.minNDim != null) {\n        if (ndim < spec.minNDim) {\n          throw new ValueError(`Input ${inputIndex} is incompatible with layer ${this.name}: expected min_ndim=${spec.minNDim}, found ndim=${ndim}.`);\n        }\n      }\n      if (spec.dtype != null) {\n        if (x.dtype !== spec.dtype) {\n          throw new ValueError(`Input ${inputIndex} is incompatible with layer ${this.name} : expected dtype=${spec.dtype}, found dtype=${x.dtype}.`);\n        }\n      }\n      if (spec.axes) {\n        const xShape = x.shape;\n        for (const key in spec.axes) {\n          const axis = Number(key);\n          const value = spec.axes[key];\n          const xShapeAtAxis = axis >= 0 ? xShape[axis] : xShape[xShape.length + axis];\n          if (value != null && [value, null].indexOf(xShapeAtAxis) === -1) {\n            throw new ValueError(`Input ${inputIndex} is incompatible with layer ${this.name}: expected axis ${axis} of input shape to have value ${value} but got shape ${xShape}.`);\n          }\n        }\n      }\n      if (spec.shape != null) {\n        for (let i2 = 0; i2 < spec.shape.length; ++i2) {\n          const specDim = spec.shape[i2];\n          const dim = x.shape[i2];\n          if (specDim != null && dim != null) {\n            if (specDim !== dim) {\n              throw new ValueError(`Input ${inputIndex} is incompatible with layer ${this.name}: expected shape=${spec.shape}, found shape=${x.shape}.`);\n            }\n          }\n        }\n      }\n    }\n  }\n  call(inputs, kwargs) {\n    return inputs;\n  }\n  invokeCallHook(inputs, kwargs) {\n    if (this._callHook != null) {\n      this._callHook(inputs, kwargs);\n    }\n  }\n  setCallHook(callHook) {\n    this._callHook = callHook;\n  }\n  clearCallHook() {\n    this._callHook = null;\n  }\n  apply(inputs, kwargs) {\n    kwargs = kwargs || {};\n    this.assertNotDisposed();\n    const inputsList = toList(inputs);\n    let allAreSymbolic = true;\n    for (const input2 of inputsList) {\n      if (!(input2 instanceof SymbolicTensor)) {\n        allAreSymbolic = false;\n        break;\n      }\n    }\n    let noneAreSymbolic = true;\n    for (const input2 of inputsList) {\n      if (input2 instanceof SymbolicTensor) {\n        noneAreSymbolic = false;\n        break;\n      }\n    }\n    if (allAreSymbolic === noneAreSymbolic) {\n      throw new ValueError(\"Arguments to apply() must be all SymbolicTensors or all Tensors\");\n    }\n    return nameScope(this.name, () => {\n      if (!this.built) {\n        this.assertInputCompatibility(inputs);\n        const inputShapes = [];\n        for (const xElem of toList(inputs)) {\n          inputShapes.push(xElem.shape);\n        }\n        this.build(singletonOrArray(inputShapes));\n        this.built = true;\n        if (this.initialWeights) {\n          this.setWeights(this.initialWeights);\n        }\n        if (this._refCount === null && noneAreSymbolic) {\n          this._refCount = 1;\n        }\n      }\n      this.assertInputCompatibility(inputs);\n      if (noneAreSymbolic) {\n        let output = this.call(inputs, kwargs);\n        const outputList = toList(output);\n        const outputListCopy = [];\n        for (let x of outputList) {\n          if (inputsList.indexOf(x) !== -1) {\n            x = x.clone();\n          }\n          outputListCopy.push(x);\n        }\n        output = singletonOrArray(outputListCopy);\n        if (this.activityRegularizer != null) {\n          throw new NotImplementedError(\"Layer invocation in the presence of activity regularizer(s) is not supported yet.\");\n        }\n        return output;\n      } else {\n        const inputShape = collectInputShape(inputs);\n        const outputShape = this.computeOutputShape(inputShape);\n        let output;\n        const outputDType = guessOutputDType(inputs);\n        this.warnOnIncompatibleInputShape(Array.isArray(inputs) ? inputShape[0] : inputShape);\n        if (outputShape != null && outputShape.length > 0 && Array.isArray(outputShape[0])) {\n          output = outputShape.map((shape, index) => new SymbolicTensor(outputDType, shape, this, toList(inputs), kwargs, this.name, index));\n        } else {\n          output = new SymbolicTensor(outputDType, outputShape, this, toList(inputs), kwargs, this.name);\n        }\n        this.addInboundNode(inputs, output, null, null, inputShape, outputShape, kwargs);\n        this._refCount++;\n        if (this.activityRegularizer != null) {\n          throw new NotImplementedError(\"Layer invocation in the presence of activity regularizer(s) is not supported yet.\");\n        }\n        return output;\n      }\n    });\n  }\n  warnOnIncompatibleInputShape(inputShape) {\n    if (this.batchInputShape == null) {\n      return;\n    } else if (inputShape.length !== this.batchInputShape.length) {\n      console.warn(`The rank of the input tensor provided (shape: ${JSON.stringify(inputShape)}) does not match that of the batchInputShape (${JSON.stringify(this.batchInputShape)}) of the layer ${this.name}`);\n    } else {\n      let dimMismatch = false;\n      this.batchInputShape.forEach((dimension, i2) => {\n        if (dimension != null && inputShape[i2] != null && inputShape[i2] !== dimension) {\n          dimMismatch = true;\n        }\n      });\n      if (dimMismatch) {\n        console.warn(`The shape of the input tensor (${JSON.stringify(inputShape)}) does not match the expectation of layer ${this.name}: ${JSON.stringify(this.batchInputShape)}`);\n      }\n    }\n  }\n  get outputShape() {\n    if (this.inboundNodes == null || this.inboundNodes.length === 0) {\n      throw new AttributeError(`The layer ${this.name} has never been called and thus has no defined output shape.`);\n    }\n    const allOutputShapes = [];\n    for (const node of this.inboundNodes) {\n      const shapeString = JSON.stringify(node.outputShapes);\n      if (allOutputShapes.indexOf(shapeString) === -1) {\n        allOutputShapes.push(shapeString);\n      }\n    }\n    if (allOutputShapes.length === 1) {\n      const outputShapes = this.inboundNodes[0].outputShapes;\n      if (Array.isArray(outputShapes) && Array.isArray(outputShapes[0]) && outputShapes.length === 1) {\n        return outputShapes[0];\n      } else {\n        return outputShapes;\n      }\n    } else {\n      throw new AttributeError(`The layer ${this.name} has multiple inbound nodes with different output shapes. Hence the notion of \"output shape\" is ill-defined for the layer.`);\n    }\n  }\n  countParams() {\n    if (!this.built) {\n      throw new RuntimeError(`You tried to call countParams() on ${this.name}, but the layer is not built yet. Build it first by calling build(batchInputShape).`);\n    }\n    return countParamsInWeights(this.weights);\n  }\n  build(inputShape) {\n    this.built = true;\n  }\n  getWeights(trainableOnly = false) {\n    return batchGetValue(trainableOnly ? this.trainableWeights : this.weights);\n  }\n  setWeights(weights) {\n    tidy(() => {\n      const params = this.weights;\n      if (params.length !== weights.length) {\n        throw new ValueError(`You called setWeights(weights) on layer \"${this.name}\" with a weight list of length ${weights.length}, but the layer was expecting ${params.length} weights. Provided weights: ${weights}...`);\n      }\n      if (params.length === 0) {\n        return;\n      }\n      const weightValueTuples = [];\n      const paramValues = batchGetValue(params);\n      for (let i2 = 0; i2 < paramValues.length; ++i2) {\n        const pv = paramValues[i2];\n        const p2 = params[i2];\n        const w = weights[i2];\n        if (!util_exports.arraysEqual(pv.shape, w.shape)) {\n          throw new ValueError(`Layer weight shape ${pv.shape} not compatible with provided weight shape ${w.shape}`);\n        }\n        weightValueTuples.push([p2, w]);\n      }\n      batchSetValue(weightValueTuples);\n    });\n  }\n  addWeight(name, shape, dtype, initializer, regularizer, trainable, constraint, getInitializerFunc) {\n    if (this._addedWeightNames.indexOf(name) !== -1) {\n      throw new ValueError(`Duplicate weight name ${name} for layer ${this.name}`);\n    }\n    this._addedWeightNames.push(name);\n    if (dtype == null) {\n      dtype = \"float32\";\n    }\n    if (this.fastWeightInitDuringBuild) {\n      initializer = getInitializerFunc != null ? getInitializerFunc() : getInitializer(\"zeros\");\n    }\n    const initValue = initializer.apply(shape, dtype);\n    const weight = new LayerVariable(initValue, dtype, name, trainable, constraint);\n    initValue.dispose();\n    if (regularizer != null) {\n      this.addLoss(() => regularizer.apply(weight.read()));\n    }\n    if (trainable == null) {\n      trainable = true;\n    }\n    if (trainable) {\n      this._trainableWeights.push(weight);\n    } else {\n      this._nonTrainableWeights.push(weight);\n    }\n    return weight;\n  }\n  setFastWeightInitDuringBuild(value) {\n    this.fastWeightInitDuringBuild = value;\n  }\n  addLoss(losses2) {\n    if (losses2 == null || Array.isArray(losses2) && losses2.length === 0) {\n      return;\n    }\n    losses2 = toList(losses2);\n    if (this._losses !== void 0 && this._losses !== null) {\n      this.losses.push(...losses2);\n    }\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  computeMask(inputs, mask) {\n    if (!this.supportsMasking) {\n      if (mask != null) {\n        if (Array.isArray(mask)) {\n          mask.forEach((maskElement) => {\n            if (maskElement != null) {\n              throw new TypeError(`Layer ${this.name} does not support masking, but was passed an inputMask.`);\n            }\n          });\n        } else {\n          throw new TypeError(`Layer ${this.name} does not support masking, but was passed an inputMask.`);\n        }\n      }\n      return null;\n    }\n    return mask;\n  }\n  addInboundNode(inputTensors, outputTensors, inputMasks, outputMasks, inputShapes, outputShapes, kwargs = null) {\n    const inputTensorList = toList(inputTensors);\n    outputTensors = toList(outputTensors);\n    inputMasks = toList(inputMasks);\n    outputMasks = toList(outputMasks);\n    inputShapes = normalizeShapeList(inputShapes);\n    outputShapes = normalizeShapeList(outputShapes);\n    const inboundLayers = [];\n    const nodeIndices = [];\n    const tensorIndices = [];\n    for (const x of inputTensorList) {\n      inboundLayers.push(x.sourceLayer);\n      nodeIndices.push(x.nodeIndex);\n      tensorIndices.push(x.tensorIndex);\n    }\n    new Node({\n      outboundLayer: this,\n      inboundLayers,\n      nodeIndices,\n      tensorIndices,\n      inputTensors: inputTensorList,\n      outputTensors,\n      inputMasks,\n      outputMasks,\n      inputShapes,\n      outputShapes\n    }, kwargs);\n    for (let i2 = 0; i2 < outputTensors.length; i2++) {\n      outputTensors[i2].sourceLayer = this;\n      outputTensors[i2].nodeIndex = this.inboundNodes.length - 1;\n      outputTensors[i2].tensorIndex = i2;\n    }\n  }\n  getConfig() {\n    const config = { name: this.name, trainable: this.trainable };\n    if (this.batchInputShape != null) {\n      config[\"batchInputShape\"] = this.batchInputShape;\n    }\n    if (this.dtype != null) {\n      config[\"dtype\"] = this.dtype;\n    }\n    return config;\n  }\n  disposeWeights() {\n    this.weights.forEach((weight) => weight.dispose());\n    return this.weights.length;\n  }\n  assertNotDisposed() {\n    if (this._refCount === 0) {\n      throw new Error(`Layer '${this.name}' is already disposed.`);\n    }\n  }\n  dispose() {\n    if (!this.built) {\n      throw new Error(`Cannot dispose Layer ${this.name} because it has not been built yet.`);\n    }\n    if (this._refCount === null) {\n      throw new Error(`Cannot dispose Layer ${this.name} because it has not been used yet.`);\n    }\n    this.assertNotDisposed();\n    let numDisposedVariables = 0;\n    if (--this._refCount === 0) {\n      numDisposedVariables = this.disposeWeights();\n    }\n    return { refCountAfterDispose: this._refCount, numDisposedVariables };\n  }\n};\nfunction collectInputShape(inputTensors) {\n  inputTensors = toList(inputTensors);\n  const shapes = [];\n  for (const x of inputTensors) {\n    shapes.push(x.shape);\n  }\n  return singletonOrArray(shapes);\n}\nfunction guessOutputDType(inputTensors) {\n  return \"float32\";\n}\nfunction getSourceInputs(tensor2, layer, nodeIndex) {\n  if (layer == null || nodeIndex != null && nodeIndex > 0) {\n    layer = tensor2.sourceLayer;\n    nodeIndex = tensor2.nodeIndex;\n  }\n  if (layer.inboundNodes.length === 0) {\n    return [tensor2];\n  } else {\n    const node = layer.inboundNodes[nodeIndex];\n    if (node.inboundLayers.length === 0) {\n      return node.inputTensors;\n    } else {\n      const sourceTensors = [];\n      for (let i2 = 0; i2 < node.inboundLayers.length; i2++) {\n        const x = node.inputTensors[i2];\n        const layer2 = node.inboundLayers[i2];\n        const nodeIndex2 = node.nodeIndices[i2];\n        const previousSources = getSourceInputs(x, layer2, nodeIndex2);\n        for (const x2 of previousSources) {\n          if (sourceTensors.indexOf(x2) === -1) {\n            sourceTensors.push(x2);\n          }\n        }\n      }\n      return sourceTensors;\n    }\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/input_layer.js\nvar InputLayer = class extends Layer {\n  constructor(args) {\n    super({\n      dtype: args.dtype,\n      name: args.name != null ? args.name : getUid(\"input\").toString()\n    });\n    if (args.batchSize == null) {\n      args.batchSize = null;\n    }\n    if (args.sparse == null) {\n      args.sparse = false;\n    }\n    this.trainable = false;\n    this.built = true;\n    this.sparse = args.sparse;\n    if (args.inputShape != null && args.batchInputShape != null) {\n      throw new ValueError(\"Only provide the inputShape OR batchInputShape argument to inputLayer, not both at the same time.\");\n    }\n    let batchInputShape = args.batchInputShape;\n    if (batchInputShape == null) {\n      if (args.inputShape == null) {\n        throw new ValueError(\"An InputLayer should be passed either a `batchInputShape` or an `inputShape`.\");\n      } else {\n        batchInputShape = [args.batchSize].concat(args.inputShape);\n      }\n    } else {\n      if (args.batchSize != null) {\n        throw new ValueError(\"Cannot specify batchSize if batchInputShape is specified when creating an InputLayer.\");\n      }\n    }\n    const dtype = args.dtype || \"float32\";\n    this.batchInputShape = batchInputShape;\n    this.dtype = dtype;\n    this.inputSpec = [{ shape: batchInputShape }];\n    const inputTensor = new SymbolicTensor(this.dtype, this.batchInputShape, this, [], {}, this.name);\n    inputTensor.nodeIndex = 0;\n    inputTensor.tensorIndex = 0;\n    new Node({\n      outboundLayer: this,\n      inboundLayers: [],\n      nodeIndices: [],\n      tensorIndices: [],\n      inputTensors: [inputTensor],\n      outputTensors: [inputTensor],\n      inputMasks: [null],\n      outputMasks: [null],\n      inputShapes: [batchInputShape],\n      outputShapes: [batchInputShape]\n    });\n  }\n  apply(inputs, kwargs) {\n    throw new ValueError(`Cannot pass any input to an InputLayer's apply() method. InputLayer name: ${this.name}`);\n  }\n  dispose() {\n    return { refCountAfterDispose: this._refCount, numDisposedVariables: 0 };\n  }\n  getConfig() {\n    return {\n      batchInputShape: this.batchInputShape,\n      dtype: this.dtype,\n      sparse: this.sparse,\n      name: this.name\n    };\n  }\n};\nInputLayer.className = \"InputLayer\";\nserialization_exports.registerClass(InputLayer);\nfunction Input(config) {\n  if (config.batchShape == null && config.shape == null) {\n    throw new Error(\"Please provide to Input either a `shape` or a `batchShape` argument. Note that `shape` does not include the batch dimension.\");\n  }\n  if (config.batchShape != null && config.shape != null) {\n    throw new ValueError(\"Please provide either a `shape` or `batchShape` argument to Input, but not both.\");\n  }\n  let batchShape = config.batchShape;\n  if (config.shape != null && batchShape == null) {\n    batchShape = [null].concat(config.shape);\n  }\n  let dtype = config.dtype;\n  if (dtype == null) {\n    dtype = \"float32\";\n  }\n  const inputLayer2 = new InputLayer({\n    batchInputShape: batchShape,\n    name: config.name,\n    dtype,\n    sparse: config.sparse\n  });\n  const outputs = inputLayer2.inboundNodes[0].outputTensors;\n  return outputs[0];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/executor.js\nfunction assertFeedCompatibility(key, val) {\n  if (key.dtype == null || key.dtype === val.dtype) {\n    return val;\n  }\n  try {\n    return cast(val, key.dtype);\n  } catch (err) {\n    throw new ValueError(`The dtype of the feed (${val.dtype}) can not be cast to the dtype of the key '${key.name}' (${key.dtype}).`);\n  }\n}\nvar FeedDict = class {\n  constructor(feeds) {\n    this.id2Value = {};\n    this.id2Mask = {};\n    this.name2Id = {};\n    if (feeds instanceof FeedDict) {\n      for (const id in feeds.id2Value) {\n        this.id2Value[id] = feeds.id2Value[id];\n        if (id in feeds.id2Mask) {\n          this.id2Mask[id] = feeds.id2Mask[id];\n        }\n      }\n    } else {\n      if (feeds == null) {\n        return;\n      }\n      for (const feed of feeds) {\n        this.add(feed.key, feed.value);\n      }\n    }\n  }\n  add(key, value, mask) {\n    if (this.id2Value[key.id] == null) {\n      this.id2Value[key.id] = assertFeedCompatibility(key, value);\n      this.name2Id[key.name] = key.id;\n      if (mask != null) {\n        this.id2Mask[key.id] = mask;\n      }\n    } else {\n      throw new ValueError(`Duplicate key: name=${key.name}, id=${key.id}`);\n    }\n    return this;\n  }\n  addFeed(feed) {\n    this.add(feed.key, feed.value);\n  }\n  hasKey(key) {\n    return this.id2Value[key.id] != null;\n  }\n  names() {\n    return Object.keys(this.name2Id);\n  }\n  getValue(key) {\n    if (key instanceof SymbolicTensor) {\n      if (this.id2Value[key.id] == null) {\n        throw new ValueError(`Nonexistent key: ${key.name}`);\n      } else {\n        return this.id2Value[key.id];\n      }\n    } else {\n      const id = this.name2Id[key];\n      if (id == null) {\n        throw new ValueError(`Feed dict has no SymbolicTensor name: ${key}`);\n      }\n      return this.id2Value[id];\n    }\n  }\n  getMask(key) {\n    if (key instanceof SymbolicTensor) {\n      if (this.id2Value[key.id] == null) {\n        throw new ValueError(`Nonexistent key: ${key.name}`);\n      } else {\n        return this.id2Mask[key.id];\n      }\n    } else {\n      const id = this.name2Id[key];\n      if (id == null) {\n        throw new ValueError(`Feed dict has no SymbolicTensor name: ${key}`);\n      }\n      return this.id2Mask[id];\n    }\n  }\n  disposeMasks() {\n    if (this.id2Mask != null) {\n      dispose(this.id2Mask);\n    }\n  }\n};\nvar cachedSorted = new LruCache();\nvar cachedRecipientCounts = new LruCache();\nfunction updateCacheMaxEntries(maxEntries) {\n  if (cachedSorted != null) {\n    cachedSorted.setMaxEntries(maxEntries);\n  }\n  if (cachedRecipientCounts != null) {\n    cachedRecipientCounts.setMaxEntries(maxEntries);\n  }\n}\nfunction execute(fetches, feedDict, kwargs, probe) {\n  const training = kwargs == null ? false : kwargs[\"training\"];\n  const arrayFetches = Array.isArray(fetches);\n  const fetchArray = arrayFetches ? fetches : [fetches];\n  const outputNames = fetchArray.map((t2) => t2.name);\n  const finalOutputs = [];\n  const feedNames = feedDict.names();\n  for (const outputName of outputNames) {\n    if (feedNames.indexOf(outputName) !== -1) {\n      finalOutputs.push(feedDict.getValue(outputName));\n    } else {\n      finalOutputs.push(null);\n    }\n  }\n  if (probe != null) {\n    probe.maxNumTensors = -Infinity;\n    probe.minNumTensors = Infinity;\n  }\n  const fetchAndFeedKey = outputNames.join(\",\") + \"|\" + feedDict.names().sort().join(\",\");\n  let sorted = cachedSorted.get(fetchAndFeedKey);\n  let recipientCounts;\n  if (sorted == null) {\n    const out = getTopologicalSortAndRecipientCounts(fetchArray, feedDict);\n    sorted = out.sorted;\n    recipientCounts = out.recipientCounts;\n    cachedSorted.put(fetchAndFeedKey, sorted);\n    cachedRecipientCounts.put(fetchAndFeedKey, recipientCounts);\n  }\n  recipientCounts = {};\n  if (!training) {\n    Object.assign(recipientCounts, cachedRecipientCounts.get(fetchAndFeedKey));\n  }\n  const internalFeedDict = new FeedDict(feedDict);\n  for (let i2 = 0; i2 < sorted.length; ++i2) {\n    if (probe != null) {\n      const numTensors = memory().numTensors;\n      if (numTensors > probe.maxNumTensors) {\n        probe.maxNumTensors = numTensors;\n      }\n      if (numTensors < probe.minNumTensors) {\n        probe.minNumTensors = numTensors;\n      }\n    }\n    const symbolic = sorted[i2];\n    const srcLayer = symbolic.sourceLayer;\n    if (srcLayer instanceof InputLayer) {\n      continue;\n    }\n    const inputValues = [];\n    const inputMasks = [];\n    const tensorsToDispose = [];\n    let maskExists = false;\n    for (const input2 of symbolic.inputs) {\n      const value = internalFeedDict.getValue(input2);\n      const mask = internalFeedDict.getMask(input2);\n      inputValues.push(value);\n      inputMasks.push(mask);\n      if (mask != null) {\n        maskExists = true;\n      }\n      if (!training) {\n        recipientCounts[input2.name]--;\n        if (recipientCounts[input2.name] === 0 && !feedDict.hasKey(input2) && outputNames.indexOf(input2.name) === -1 && !value.isDisposed && input2.sourceLayer.stateful !== true) {\n          tensorsToDispose.push(value);\n        }\n      }\n    }\n    if (maskExists) {\n      kwargs = kwargs || {};\n      kwargs[\"mask\"] = inputMasks[0];\n    }\n    const outputTensors = toList(srcLayer.apply(inputValues, kwargs));\n    let outputMask = null;\n    if (srcLayer.supportsMasking) {\n      outputMask = srcLayer.computeMask(inputValues, inputMasks);\n    }\n    const layerOutputs = getNodeOutputs(symbolic);\n    const outputSymbolicTensors = Array.isArray(layerOutputs) ? layerOutputs : [layerOutputs];\n    for (let i3 = 0; i3 < outputSymbolicTensors.length; ++i3) {\n      if (!internalFeedDict.hasKey(outputSymbolicTensors[i3])) {\n        internalFeedDict.add(outputSymbolicTensors[i3], outputTensors[i3], Array.isArray(outputMask) ? outputMask[0] : outputMask);\n      }\n      const index = outputNames.indexOf(outputSymbolicTensors[i3].name);\n      if (index !== -1) {\n        finalOutputs[index] = outputTensors[i3];\n      }\n    }\n    if (!training) {\n      dispose(tensorsToDispose);\n    }\n  }\n  internalFeedDict.disposeMasks();\n  return arrayFetches ? finalOutputs : finalOutputs[0];\n}\nfunction getTopologicalSortAndRecipientCounts(fetches, feedDict) {\n  util_exports.assert(fetches != null && fetches.length > 0, () => `Expected at least one fetch, got none`);\n  let finalSorted = [];\n  let finalRecipientMap = {};\n  if (fetches.length === 1) {\n    const out = getTopologicalSortAndRecipientCountsForOneFetch(fetches[0], feedDict);\n    finalSorted = out.sorted;\n    finalRecipientMap = out.recipientMap;\n  } else {\n    const visited = /* @__PURE__ */ new Set();\n    for (const fetch4 of fetches) {\n      const { sorted, recipientMap } = getTopologicalSortAndRecipientCountsForOneFetch(fetch4, feedDict);\n      for (const symbolicTensor of sorted) {\n        if (!visited.has(symbolicTensor.name)) {\n          finalSorted.push(symbolicTensor);\n          visited.add(symbolicTensor.name);\n        }\n      }\n      for (const name in recipientMap) {\n        if (finalRecipientMap[name] == null) {\n          finalRecipientMap[name] = /* @__PURE__ */ new Set();\n        }\n        recipientMap[name].forEach((recipient) => finalRecipientMap[name].add(recipient));\n      }\n    }\n  }\n  return {\n    sorted: finalSorted,\n    recipientCounts: recipientMap2Counts(finalRecipientMap)\n  };\n}\nfunction recipientMap2Counts(recipientMap) {\n  const recipientCounts = {};\n  for (const name in recipientMap) {\n    recipientCounts[name] = recipientMap[name].size;\n  }\n  return recipientCounts;\n}\nfunction getTopologicalSortAndRecipientCountsForOneFetch(fetch4, feedDict) {\n  const visited = /* @__PURE__ */ new Set();\n  const sorted = [];\n  const recipientMap = {};\n  for (const key of feedDict.names()) {\n    visited.add(key);\n  }\n  const stack2 = [];\n  const marks = [];\n  stack2.push(fetch4);\n  while (stack2.length > 0) {\n    const top = stack2[stack2.length - 1];\n    if (visited.has(top.name)) {\n      stack2.pop();\n      continue;\n    }\n    const topIsMarked = marks[marks.length - 1] === stack2.length - 1;\n    if (top.inputs.length === 0 || topIsMarked) {\n      stack2.pop();\n      sorted.push(top);\n      visited.add(top.name);\n      if (topIsMarked) {\n        marks.pop();\n      }\n    } else {\n      marks.push(stack2.length - 1);\n      for (const input2 of top.inputs) {\n        if (recipientMap[input2.name] == null) {\n          recipientMap[input2.name] = /* @__PURE__ */ new Set();\n        }\n        recipientMap[input2.name].add(top.name);\n        if (visited.has(input2.name)) {\n          continue;\n        }\n        stack2.push(input2);\n      }\n    }\n  }\n  return { sorted, recipientMap };\n}\nfunction getNodeOutputs(fetch4) {\n  let layerOutputs;\n  if (fetch4.sourceLayer.inboundNodes.length === 1) {\n    layerOutputs = fetch4.sourceLayer.output;\n  } else {\n    let nodeIndex = null;\n    for (let i2 = 0; i2 < fetch4.sourceLayer.inboundNodes.length; ++i2) {\n      for (const outputTensor of fetch4.sourceLayer.inboundNodes[i2].outputTensors) {\n        if (outputTensor.id === fetch4.id) {\n          nodeIndex = i2;\n          break;\n        }\n      }\n    }\n    layerOutputs = fetch4.sourceLayer.getOutputAt(nodeIndex);\n  }\n  return layerOutputs;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/flags_layers.js\nvar ENV3 = env();\nENV3.registerFlag(\"TOPOLOGICAL_SORT_CACHE_MAX_ENTRIES\", () => 100, updateCacheMaxEntries);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_constraints.js\nvar exports_constraints_exports = {};\n__export(exports_constraints_exports, {\n  maxNorm: () => maxNorm,\n  minMaxNorm: () => minMaxNorm,\n  nonNeg: () => nonNeg,\n  unitNorm: () => unitNorm\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/constraints.js\nfunction calcL2Norms(w, axis) {\n  return tidy(() => sqrt(sum2(mul(w, w), axis, true)));\n}\nvar Constraint = class extends serialization_exports.Serializable {\n  getConfig() {\n    return {};\n  }\n};\nvar MaxNorm = class extends Constraint {\n  constructor(args) {\n    super();\n    this.defaultMaxValue = 2;\n    this.defaultAxis = 0;\n    this.maxValue = args.maxValue != null ? args.maxValue : this.defaultMaxValue;\n    this.axis = args.axis != null ? args.axis : this.defaultAxis;\n  }\n  apply(w) {\n    return tidy(() => {\n      const norms = calcL2Norms(w, this.axis);\n      const desired = clipByValue(norms, 0, this.maxValue);\n      return mul(w, div(desired, add2(epsilon(), norms)));\n    });\n  }\n  getConfig() {\n    return { maxValue: this.maxValue, axis: this.axis };\n  }\n};\nMaxNorm.className = \"MaxNorm\";\nserialization_exports.registerClass(MaxNorm);\nvar UnitNorm = class extends Constraint {\n  constructor(args) {\n    super();\n    this.defaultAxis = 0;\n    this.axis = args.axis != null ? args.axis : this.defaultAxis;\n  }\n  apply(w) {\n    return tidy(() => div(w, add2(epsilon(), calcL2Norms(w, this.axis))));\n  }\n  getConfig() {\n    return { axis: this.axis };\n  }\n};\nUnitNorm.className = \"UnitNorm\";\nserialization_exports.registerClass(UnitNorm);\nvar NonNeg = class extends Constraint {\n  apply(w) {\n    return relu(w);\n  }\n};\nNonNeg.className = \"NonNeg\";\nserialization_exports.registerClass(NonNeg);\nvar MinMaxNorm = class extends Constraint {\n  constructor(args) {\n    super();\n    this.defaultMinValue = 0;\n    this.defaultMaxValue = 1;\n    this.defaultRate = 1;\n    this.defaultAxis = 0;\n    this.minValue = args.minValue != null ? args.minValue : this.defaultMinValue;\n    this.maxValue = args.maxValue != null ? args.maxValue : this.defaultMaxValue;\n    this.rate = args.rate != null ? args.rate : this.defaultRate;\n    this.axis = args.axis != null ? args.axis : this.defaultAxis;\n  }\n  apply(w) {\n    return tidy(() => {\n      const norms = calcL2Norms(w, this.axis);\n      const desired = add2(mul(this.rate, clipByValue(norms, this.minValue, this.maxValue)), mul(1 - this.rate, norms));\n      return mul(w, div(desired, add2(epsilon(), norms)));\n    });\n  }\n  getConfig() {\n    return {\n      minValue: this.minValue,\n      maxValue: this.maxValue,\n      rate: this.rate,\n      axis: this.axis\n    };\n  }\n};\nMinMaxNorm.className = \"MinMaxNorm\";\nserialization_exports.registerClass(MinMaxNorm);\nvar CONSTRAINT_IDENTIFIER_REGISTRY_SYMBOL_MAP = {\n  \"maxNorm\": \"MaxNorm\",\n  \"minMaxNorm\": \"MinMaxNorm\",\n  \"nonNeg\": \"NonNeg\",\n  \"unitNorm\": \"UnitNorm\"\n};\nfunction serializeConstraint(constraint) {\n  return serializeKerasObject(constraint);\n}\nfunction deserializeConstraint(config, customObjects = {}) {\n  return deserializeKerasObject(config, serialization_exports.SerializationMap.getMap().classNameMap, customObjects, \"constraint\");\n}\nfunction getConstraint(identifier) {\n  if (identifier == null) {\n    return null;\n  }\n  if (typeof identifier === \"string\") {\n    const className = identifier in CONSTRAINT_IDENTIFIER_REGISTRY_SYMBOL_MAP ? CONSTRAINT_IDENTIFIER_REGISTRY_SYMBOL_MAP[identifier] : identifier;\n    const config = { className, config: {} };\n    return deserializeConstraint(config);\n  } else if (identifier instanceof Constraint) {\n    return identifier;\n  } else {\n    return deserializeConstraint(identifier);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_constraints.js\nfunction maxNorm(args) {\n  return new MaxNorm(args);\n}\nfunction unitNorm(args) {\n  return new UnitNorm(args);\n}\nfunction nonNeg() {\n  return new NonNeg();\n}\nfunction minMaxNorm(config) {\n  return new MinMaxNorm(config);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_initializers.js\nvar exports_initializers_exports = {};\n__export(exports_initializers_exports, {\n  constant: () => constant,\n  glorotNormal: () => glorotNormal,\n  glorotUniform: () => glorotUniform,\n  heNormal: () => heNormal,\n  heUniform: () => heUniform,\n  identity: () => identity,\n  leCunNormal: () => leCunNormal,\n  leCunUniform: () => leCunUniform,\n  ones: () => ones3,\n  orthogonal: () => orthogonal,\n  randomNormal: () => randomNormal3,\n  randomUniform: () => randomUniform2,\n  truncatedNormal: () => truncatedNormal2,\n  varianceScaling: () => varianceScaling,\n  zeros: () => zeros2\n});\nfunction zeros2() {\n  return new Zeros();\n}\nfunction ones3() {\n  return new Ones();\n}\nfunction constant(args) {\n  return new Constant(args);\n}\nfunction randomUniform2(args) {\n  return new RandomUniform(args);\n}\nfunction randomNormal3(args) {\n  return new RandomNormal(args);\n}\nfunction truncatedNormal2(args) {\n  return new TruncatedNormal(args);\n}\nfunction identity(args) {\n  return new Identity2(args);\n}\nfunction varianceScaling(config) {\n  return new VarianceScaling(config);\n}\nfunction glorotUniform(args) {\n  return new GlorotUniform(args);\n}\nfunction glorotNormal(args) {\n  return new GlorotNormal(args);\n}\nfunction heNormal(args) {\n  return new HeNormal(args);\n}\nfunction heUniform(args) {\n  return new HeUniform(args);\n}\nfunction leCunNormal(args) {\n  return new LeCunNormal(args);\n}\nfunction leCunUniform(args) {\n  return new LeCunUniform(args);\n}\nfunction orthogonal(args) {\n  return new Orthogonal(args);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_layers.js\nvar exports_layers_exports = {};\n__export(exports_layers_exports, {\n  Layer: () => Layer,\n  RNN: () => RNN,\n  RNNCell: () => RNNCell,\n  activation: () => activation,\n  add: () => add3,\n  alphaDropout: () => alphaDropout,\n  average: () => average,\n  averagePooling1d: () => averagePooling1d,\n  averagePooling2d: () => averagePooling2d,\n  averagePooling3d: () => averagePooling3d,\n  avgPool1d: () => avgPool1d,\n  avgPool2d: () => avgPool2d,\n  avgPool3d: () => avgPool3d2,\n  avgPooling1d: () => avgPooling1d,\n  avgPooling2d: () => avgPooling2d,\n  avgPooling3d: () => avgPooling3d,\n  batchNormalization: () => batchNormalization2,\n  bidirectional: () => bidirectional,\n  concatenate: () => concatenate2,\n  conv1d: () => conv1d2,\n  conv2d: () => conv2d3,\n  conv2dTranspose: () => conv2dTranspose2,\n  conv3d: () => conv3d2,\n  conv3dTranspose: () => conv3dTranspose2,\n  convLstm2d: () => convLstm2d,\n  convLstm2dCell: () => convLstm2dCell,\n  cropping2D: () => cropping2D,\n  dense: () => dense,\n  depthwiseConv2d: () => depthwiseConv2d4,\n  dot: () => dot3,\n  dropout: () => dropout3,\n  elu: () => elu3,\n  embedding: () => embedding,\n  flatten: () => flatten3,\n  gaussianDropout: () => gaussianDropout,\n  gaussianNoise: () => gaussianNoise,\n  globalAveragePooling1d: () => globalAveragePooling1d,\n  globalAveragePooling2d: () => globalAveragePooling2d,\n  globalMaxPool1d: () => globalMaxPool1d,\n  globalMaxPool2d: () => globalMaxPool2d,\n  globalMaxPooling1d: () => globalMaxPooling1d,\n  globalMaxPooling2d: () => globalMaxPooling2d,\n  gru: () => gru,\n  gruCell: () => gruCell,\n  input: () => input,\n  inputLayer: () => inputLayer,\n  layerNormalization: () => layerNormalization,\n  leakyReLU: () => leakyReLU,\n  lstm: () => lstm,\n  lstmCell: () => lstmCell,\n  masking: () => masking,\n  maxPool1d: () => maxPool1d,\n  maxPool2d: () => maxPool2d,\n  maxPooling1d: () => maxPooling1d,\n  maxPooling2d: () => maxPooling2d,\n  maxPooling3d: () => maxPooling3d,\n  maximum: () => maximum2,\n  minimum: () => minimum2,\n  multiply: () => multiply,\n  permute: () => permute,\n  prelu: () => prelu2,\n  reLU: () => reLU,\n  repeatVector: () => repeatVector,\n  reshape: () => reshape2,\n  rnn: () => rnn2,\n  separableConv2d: () => separableConv2d2,\n  simpleRNN: () => simpleRNN,\n  simpleRNNCell: () => simpleRNNCell,\n  softmax: () => softmax2,\n  spatialDropout1d: () => spatialDropout1d,\n  stackedRNNCells: () => stackedRNNCells,\n  thresholdedReLU: () => thresholdedReLU,\n  timeDistributed: () => timeDistributed,\n  upSampling2d: () => upSampling2d,\n  zeroPadding2d: () => zeroPadding2d\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/logs.js\nasync function resolveScalarsInLogs(logs) {\n  if (logs == null) {\n    return;\n  }\n  const promises = [];\n  const keys = [];\n  const scalarsToDispose = [];\n  for (const key in logs) {\n    const value = logs[key];\n    if (typeof value !== \"number\") {\n      const valueScalar = value;\n      promises.push(valueScalar.data());\n      keys.push(key);\n      scalarsToDispose.push(valueScalar);\n    }\n  }\n  if (promises.length > 0) {\n    const values = await Promise.all(promises);\n    for (let i2 = 0; i2 < values.length; ++i2) {\n      logs[keys[i2]] = values[i2][0];\n    }\n    dispose(scalarsToDispose);\n  }\n}\nfunction disposeTensorsInLogs(logs) {\n  if (logs == null) {\n    return;\n  }\n  for (const key in logs) {\n    const value = logs[key];\n    if (typeof value !== \"number\") {\n      value.dispose();\n    }\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/base_callbacks.js\nvar ModelLoggingVerbosity;\n(function(ModelLoggingVerbosity2) {\n  ModelLoggingVerbosity2[ModelLoggingVerbosity2[\"SILENT\"] = 0] = \"SILENT\";\n  ModelLoggingVerbosity2[ModelLoggingVerbosity2[\"VERBOSE\"] = 1] = \"VERBOSE\";\n})(ModelLoggingVerbosity || (ModelLoggingVerbosity = {}));\nvar DEFAULT_YIELD_EVERY_MS = 125;\nvar BaseCallback = class {\n  constructor() {\n    this.validationData = null;\n  }\n  setParams(params) {\n    this.params = params;\n  }\n  async onEpochBegin(epoch, logs) {\n  }\n  async onEpochEnd(epoch, logs) {\n  }\n  async onBatchBegin(batch, logs) {\n  }\n  async onBatchEnd(batch, logs) {\n  }\n  async onTrainBegin(logs) {\n  }\n  async onTrainEnd(logs) {\n  }\n  setModel(model2) {\n  }\n};\nvar CallbackList = class {\n  constructor(callbacks2, queueLength = 10) {\n    if (callbacks2 == null) {\n      callbacks2 = [];\n    }\n    this.callbacks = callbacks2;\n    this.queueLength = queueLength;\n  }\n  append(callback) {\n    this.callbacks.push(callback);\n  }\n  setParams(params) {\n    for (const callback of this.callbacks) {\n      callback.setParams(params);\n    }\n  }\n  setModel(model2) {\n    for (const callback of this.callbacks) {\n      callback.setModel(model2);\n    }\n  }\n  async onEpochBegin(epoch, logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    for (const callback of this.callbacks) {\n      await callback.onEpochBegin(epoch, logs);\n    }\n  }\n  async onEpochEnd(epoch, logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    for (const callback of this.callbacks) {\n      await callback.onEpochEnd(epoch, logs);\n    }\n  }\n  async onBatchBegin(batch, logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    for (const callback of this.callbacks) {\n      await callback.onBatchBegin(batch, logs);\n    }\n  }\n  async onBatchEnd(batch, logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    for (const callback of this.callbacks) {\n      await callback.onBatchEnd(batch, logs);\n    }\n  }\n  async onTrainBegin(logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    for (const callback of this.callbacks) {\n      await callback.onTrainBegin(logs);\n    }\n  }\n  async onTrainEnd(logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    for (const callback of this.callbacks) {\n      await callback.onTrainEnd(logs);\n    }\n  }\n};\nvar BaseLogger = class extends BaseCallback {\n  constructor() {\n    super();\n  }\n  async onEpochBegin(epoch) {\n    this.seen = 0;\n    this.totals = {};\n  }\n  async onBatchEnd(batch, logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    const batchSize = logs[\"size\"] == null ? 0 : logs[\"size\"];\n    this.seen += batchSize;\n    for (const key in logs) {\n      const value = logs[key];\n      if (typeof value === \"number\") {\n        if (!this.totals.hasOwnProperty(key)) {\n          this.totals[key] = 0;\n        }\n        this.totals[key] = this.totals[key] + value * batchSize;\n      } else {\n        let oldTotalsToDispose;\n        if (key in this.totals) {\n          oldTotalsToDispose = this.totals[key];\n        } else {\n          this.totals[key] = 0;\n        }\n        const total = tidy(() => add2(this.totals[key], mul(value, batchSize)));\n        this.totals[key] = total;\n        if (oldTotalsToDispose != null) {\n          oldTotalsToDispose.dispose();\n        }\n      }\n    }\n  }\n  async onEpochEnd(epoch, logs) {\n    if (logs != null) {\n      for (const key of this.params[\"metrics\"]) {\n        if (this.totals[key] == null) {\n          continue;\n        }\n        if (typeof this.totals[key] === \"number\") {\n          logs[key] = this.totals[key] / this.seen;\n        } else {\n          tidy(() => {\n            const log6 = mul(div(1, this.seen), this.totals[key]);\n            logs[key] = log6;\n            this.totals[key].dispose();\n            keep(logs[key]);\n          });\n        }\n      }\n    }\n  }\n};\nvar History = class extends BaseCallback {\n  async onTrainBegin(logs) {\n    this.epoch = [];\n    this.history = {};\n  }\n  async onEpochEnd(epoch, logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    this.epoch.push(epoch);\n    for (const key in logs) {\n      if (this.history[key] == null) {\n        this.history[key] = [];\n      }\n      this.history[key].push(logs[key]);\n    }\n  }\n  async syncData() {\n    const promises = [];\n    const keys = [];\n    const indices = [];\n    for (const key in this.history) {\n      const valueArray = this.history[key];\n      for (let i2 = 0; i2 < valueArray.length; ++i2) {\n        if (typeof valueArray[i2] !== \"number\") {\n          const valueScalar = valueArray[i2];\n          promises.push(valueScalar.data());\n          keys.push(key);\n          indices.push(i2);\n        }\n      }\n    }\n    const values = await Promise.all(promises);\n    for (let n2 = 0; n2 < values.length; ++n2) {\n      const tensorToDispose = this.history[keys[n2]][indices[n2]];\n      tensorToDispose.dispose();\n      this.history[keys[n2]][indices[n2]] = values[n2][0];\n    }\n  }\n};\nvar CustomCallback = class extends BaseCallback {\n  constructor(args, yieldEvery) {\n    super();\n    this.currentEpoch = 0;\n    this.nowFunc = args.nowFunc;\n    this.nextFrameFunc = args.nextFrameFunc || nextFrame;\n    this.yieldEvery = yieldEvery || \"auto\";\n    if (this.yieldEvery === \"auto\") {\n      this.yieldEvery = DEFAULT_YIELD_EVERY_MS;\n    }\n    if (this.yieldEvery === \"never\" && args.onYield != null) {\n      throw new Error(\"yieldEvery is `never` but you provided an `onYield` callback. Either change `yieldEvery` or remove the callback\");\n    }\n    if (util_exports.isNumber(this.yieldEvery)) {\n      this.maybeWait = debounce(this.maybeWait.bind(this), this.yieldEvery, this.nowFunc);\n    }\n    this.trainBegin = args.onTrainBegin;\n    this.trainEnd = args.onTrainEnd;\n    this.epochBegin = args.onEpochBegin;\n    this.epochEnd = args.onEpochEnd;\n    this.batchBegin = args.onBatchBegin;\n    this.batchEnd = args.onBatchEnd;\n    this.yield = args.onYield;\n  }\n  async maybeWait(epoch, batch, logs) {\n    const ps = [];\n    if (this.yield != null) {\n      await resolveScalarsInLogs(logs);\n      ps.push(this.yield(epoch, batch, logs));\n    }\n    ps.push(this.nextFrameFunc());\n    await Promise.all(ps);\n  }\n  async onEpochBegin(epoch, logs) {\n    this.currentEpoch = epoch;\n    if (this.epochBegin != null) {\n      await resolveScalarsInLogs(logs);\n      await this.epochBegin(epoch, logs);\n    }\n  }\n  async onEpochEnd(epoch, logs) {\n    const ps = [];\n    if (this.epochEnd != null) {\n      await resolveScalarsInLogs(logs);\n      ps.push(this.epochEnd(epoch, logs));\n    }\n    if (this.yieldEvery === \"epoch\") {\n      ps.push(this.nextFrameFunc());\n    }\n    await Promise.all(ps);\n  }\n  async onBatchBegin(batch, logs) {\n    if (this.batchBegin != null) {\n      await resolveScalarsInLogs(logs);\n      await this.batchBegin(batch, logs);\n    }\n  }\n  async onBatchEnd(batch, logs) {\n    const ps = [];\n    if (this.batchEnd != null) {\n      await resolveScalarsInLogs(logs);\n      ps.push(this.batchEnd(batch, logs));\n    }\n    if (this.yieldEvery === \"batch\") {\n      ps.push(this.nextFrameFunc());\n    } else if (util_exports.isNumber(this.yieldEvery)) {\n      ps.push(this.maybeWait(this.currentEpoch, batch, logs));\n    }\n    await Promise.all(ps);\n  }\n  async onTrainBegin(logs) {\n    if (this.trainBegin != null) {\n      await resolveScalarsInLogs(logs);\n      await this.trainBegin(logs);\n    }\n  }\n  async onTrainEnd(logs) {\n    if (this.trainEnd != null) {\n      await resolveScalarsInLogs(logs);\n      await this.trainEnd(logs);\n    }\n  }\n};\nfunction standardizeCallbacks(callbacks2, yieldEvery) {\n  if (callbacks2 == null) {\n    callbacks2 = {};\n  }\n  if (callbacks2 instanceof BaseCallback) {\n    return [callbacks2];\n  }\n  if (Array.isArray(callbacks2) && callbacks2[0] instanceof BaseCallback) {\n    return callbacks2;\n  }\n  const callbackConfigs = toList(callbacks2);\n  return callbackConfigs.map((callbackConfig) => new CustomCallback(callbackConfig, yieldEvery));\n}\nvar CallbackConstructorRegistry = class {\n  constructor() {\n  }\n  static registerCallbackConstructor(verbosityLevel, callbackConstructor) {\n    util_exports.assert(verbosityLevel >= 0 && Number.isInteger(verbosityLevel), () => `Verbosity level is expected to be an integer >= 0, but got ${verbosityLevel}`);\n    CallbackConstructorRegistry.checkForDuplicate(callbackConstructor);\n    if (CallbackConstructorRegistry.constructors[verbosityLevel] == null) {\n      CallbackConstructorRegistry.constructors[verbosityLevel] = [];\n    }\n    CallbackConstructorRegistry.constructors[verbosityLevel].push(callbackConstructor);\n  }\n  static checkForDuplicate(callbackConstructor) {\n    for (const levelName in CallbackConstructorRegistry.constructors) {\n      const constructors = CallbackConstructorRegistry.constructors[+levelName];\n      constructors.forEach((ctor) => {\n        if (ctor === callbackConstructor) {\n          throw new ValueError(\"Duplicate callback constructor.\");\n        }\n      });\n    }\n  }\n  static clear() {\n    CallbackConstructorRegistry.constructors = {};\n  }\n  static createCallbacks(verbosityLevel) {\n    const constructors = [];\n    for (const levelName in CallbackConstructorRegistry.constructors) {\n      const level = +levelName;\n      if (verbosityLevel >= level) {\n        constructors.push(...CallbackConstructorRegistry.constructors[level]);\n      }\n    }\n    return constructors.map((ctor) => new ctor());\n  }\n};\nCallbackConstructorRegistry.constructors = {};\nfunction configureCallbacks(callbacks2, verbose, epochs, initialEpoch, numTrainSamples, stepsPerEpoch, batchSize, doValidation, callbackMetrics) {\n  const history = new History();\n  const actualCallbacks = [\n    new BaseLogger(),\n    ...CallbackConstructorRegistry.createCallbacks(verbose)\n  ];\n  if (callbacks2 != null) {\n    actualCallbacks.push(...callbacks2);\n  }\n  actualCallbacks.push(history);\n  const callbackList = new CallbackList(actualCallbacks);\n  callbackList.setParams({\n    epochs,\n    initialEpoch,\n    samples: numTrainSamples,\n    steps: stepsPerEpoch,\n    batchSize,\n    verbose,\n    doValidation,\n    metrics: callbackMetrics\n  });\n  return { callbackList, history };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/serialization.js\nfunction deserialize(config, customObjects = {}, fastWeightInit = false) {\n  return deserializeKerasObject(config, serialization_exports.SerializationMap.getMap().classNameMap, customObjects, \"layer\", fastWeightInit);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/losses.js\nfunction l2Normalize(x, axis) {\n  return tidy(() => {\n    if (x.dtype !== \"float32\") {\n      x = cast(x, \"float32\");\n    }\n    const squareSum = sum2(square2(x), axis, true);\n    const epsilonTensor = fill(squareSum.shape, epsilon());\n    const norm2 = sqrt(maximum(squareSum, epsilonTensor));\n    return div(x, norm2);\n  });\n}\nfunction meanSquaredError2(yTrue, yPred) {\n  return tidy(() => mean(square2(sub(yPred, yTrue)), -1));\n}\nfunction meanAbsoluteError(yTrue, yPred) {\n  return tidy(() => mean(abs(sub(yPred, yTrue)), -1));\n}\nfunction meanAbsolutePercentageError(yTrue, yPred) {\n  return tidy(() => {\n    const diff = sub(yTrue, yPred);\n    const clippedTrue = clipByValue(abs(yTrue), epsilon(), Number.MAX_VALUE);\n    const absResult = abs(div(diff, clippedTrue));\n    return mul(100, mean(absResult, -1));\n  });\n}\nfunction meanSquaredLogarithmicError(yTrue, yPred) {\n  return tidy(() => {\n    const clippedPred = clipByValue(yPred, epsilon(), Number.MAX_VALUE);\n    const firstLog = log2(add2(1, clippedPred));\n    const clippedTrue = clipByValue(yTrue, epsilon(), Number.MAX_VALUE);\n    const secondLog = log2(add2(1, clippedTrue));\n    return mean(square2(sub(firstLog, secondLog)), -1);\n  });\n}\nfunction squaredHinge(yTrue, yPred) {\n  return tidy(() => {\n    const maxResult = maximum(0, sub(1, mul(yTrue, yPred)));\n    return mean(square2(maxResult), -1);\n  });\n}\nfunction hinge(yTrue, yPred) {\n  return tidy(() => {\n    const maxResult = maximum(0, sub(1, mul(yTrue, yPred)));\n    return mean(maxResult, -1);\n  });\n}\nfunction categoricalHinge(yTrue, yPred) {\n  return tidy(() => {\n    const pos = sum2(mul(yTrue, yPred), -1);\n    const neg5 = max(mul(sub(1, yTrue), yPred), -1);\n    return maximum(0, add2(1, sub(neg5, pos)));\n  });\n}\nfunction logcosh(yTrue, yPred) {\n  return tidy(() => {\n    const log22 = Math.log(2);\n    const predictionDiff = sub(yPred, yTrue);\n    const logcoshResult = sub(add2(predictionDiff, softplus(mul(-2, predictionDiff))), log22);\n    return mean(logcoshResult, -1);\n  });\n}\nfunction categoricalCrossentropy(target, output, fromLogits = false) {\n  return tidy(() => {\n    if (fromLogits) {\n      output = softmax(output);\n    } else {\n      const outputSum = sum2(output, output.shape.length - 1, true);\n      output = div(output, outputSum);\n    }\n    output = clipByValue(output, epsilon(), 1 - epsilon());\n    return neg(sum2(mul(cast(target, \"float32\"), log2(output)), output.shape.length - 1));\n  });\n}\nfunction sparseCategoricalCrossentropy(target, output, fromLogits = false) {\n  return tidy(() => {\n    const flatTarget = cast(floor(flatten2(target)), \"int32\");\n    output = clipByValue(output, epsilon(), 1 - epsilon());\n    const outputShape = output.shape;\n    const oneHotTarget = reshape(oneHot(flatTarget, outputShape[outputShape.length - 1]), outputShape);\n    return categoricalCrossentropy(oneHotTarget, output, fromLogits);\n  });\n}\nfunction sigmoidCrossEntropyWithLogits(labels, logits) {\n  if (!util_exports.arraysEqual(labels.shape, logits.shape)) {\n    throw new ValueError(`logits and labels must have the same shape, but got shapes ${JSON.stringify(labels.shape)} and ${JSON.stringify(logits.shape)}`);\n  }\n  return tidy(() => {\n    const reluLogits = relu(logits);\n    const negAbsLogits = neg(abs(logits));\n    return add2(sub(reluLogits, mul(logits, labels)), log1p(exp(negAbsLogits)));\n  });\n}\nfunction binaryCrossentropy(yTrue, yPred) {\n  return tidy(() => {\n    let y;\n    y = clipByValue(yPred, epsilon(), 1 - epsilon());\n    y = log2(div(y, sub(1, y)));\n    return mean(sigmoidCrossEntropyWithLogits(yTrue, y), -1);\n  });\n}\nfunction kullbackLeiblerDivergence(yTrue, yPred) {\n  return tidy(() => {\n    const clippedTrue = clipByValue(yTrue, epsilon(), 1);\n    const clippedPred = clipByValue(yPred, epsilon(), 1);\n    return sum2(mul(yTrue, log2(div(clippedTrue, clippedPred))), -1);\n  });\n}\nfunction poisson(yTrue, yPred) {\n  return tidy(() => {\n    const logPred = log2(add2(epsilon(), yPred));\n    return mean(sub(yPred, mul(yTrue, logPred)), -1);\n  });\n}\nfunction cosineProximity(yTrue, yPred) {\n  return tidy(() => {\n    const trueNormalized = l2Normalize(yTrue, -1);\n    const predNormalized = l2Normalize(yPred, -1);\n    const trueXPred = mul(trueNormalized, predNormalized);\n    return neg(sum2(trueXPred, -1));\n  });\n}\nvar lossesMap = {\n  meanSquaredError: meanSquaredError2,\n  meanAbsoluteError,\n  meanAbsolutePercentageError,\n  meanSquaredLogarithmicError,\n  squaredHinge,\n  hinge,\n  categoricalHinge,\n  logcosh,\n  categoricalCrossentropy,\n  sparseCategoricalCrossentropy,\n  binaryCrossentropy,\n  kullbackLeiblerDivergence,\n  poisson,\n  cosineProximity\n};\nfunction get(identifierOrFn) {\n  if (typeof identifierOrFn === \"string\") {\n    if (identifierOrFn in lossesMap) {\n      return lossesMap[identifierOrFn];\n    }\n    let errMsg = `Unknown loss ${identifierOrFn}`;\n    if (identifierOrFn.toLowerCase().includes(\"softmaxcrossentropy\")) {\n      errMsg = `Unknown loss ${identifierOrFn}. Use \"categoricalCrossentropy\" as the string name for tf.losses.softmaxCrossEntropy`;\n    }\n    throw new ValueError(errMsg);\n  } else {\n    return identifierOrFn;\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/metrics.js\nfunction binaryAccuracy(yTrue, yPred) {\n  return tidy(() => {\n    const threshold3 = mul(0.5, onesLike(yPred));\n    const yPredThresholded = cast2(greater(yPred, threshold3), yTrue.dtype);\n    return mean(equal(yTrue, yPredThresholded), -1);\n  });\n}\nfunction categoricalAccuracy(yTrue, yPred) {\n  return tidy(() => cast2(equal(argMax(yTrue, -1), argMax(yPred, -1)), \"float32\"));\n}\nfunction truePositives(yTrue, yPred) {\n  return tidy(() => {\n    return cast(sum2(logicalAnd(equal(yTrue, 1), equal(yPred, 1))), \"float32\");\n  });\n}\nfunction falseNegatives(yTrue, yPred) {\n  return tidy(() => {\n    return cast(sum2(logicalAnd(equal(yTrue, 1), equal(yPred, 0))), \"float32\");\n  });\n}\nfunction falsePositives(yTrue, yPred) {\n  return tidy(() => {\n    return cast(sum2(logicalAnd(equal(yTrue, 0), equal(yPred, 1))), \"float32\");\n  });\n}\nfunction precision(yTrue, yPred) {\n  return tidy(() => {\n    const tp = truePositives(yTrue, yPred);\n    const fp = falsePositives(yTrue, yPred);\n    const denominator = add2(tp, fp);\n    return cast(where(greater(denominator, 0), div(tp, denominator), 0), \"float32\");\n  });\n}\nfunction recall(yTrue, yPred) {\n  return tidy(() => {\n    const tp = truePositives(yTrue, yPred);\n    const fn = falseNegatives(yTrue, yPred);\n    const denominator = add2(tp, fn);\n    return cast(where(greater(denominator, 0), div(tp, denominator), 0), \"float32\");\n  });\n}\nfunction binaryCrossentropy2(yTrue, yPred) {\n  return binaryCrossentropy(yTrue, yPred);\n}\nfunction sparseCategoricalAccuracy(yTrue, yPred) {\n  if (yTrue.rank === yPred.rank) {\n    yTrue = squeeze(yTrue, [yTrue.rank - 1]);\n  }\n  yPred = argMax(yPred, -1);\n  if (yPred.dtype !== yTrue.dtype) {\n    yPred = cast(yPred, yTrue.dtype);\n  }\n  return cast(equal(yTrue, yPred), \"float32\");\n}\nvar mse = meanSquaredError2;\nvar MSE = meanSquaredError2;\nvar mae = meanAbsoluteError;\nvar MAE = meanAbsoluteError;\nvar mape = meanAbsolutePercentageError;\nvar MAPE = meanAbsolutePercentageError;\nvar categoricalCrossentropy2 = categoricalCrossentropy;\nvar cosine = cosineProximity;\nvar sparseCategoricalCrossentropy2 = sparseCategoricalCrossentropy;\nvar metricsMap = {\n  binaryAccuracy,\n  categoricalAccuracy,\n  precision,\n  categoricalCrossentropy: categoricalCrossentropy2,\n  sparseCategoricalCrossentropy: sparseCategoricalCrossentropy2,\n  mse,\n  MSE,\n  mae,\n  MAE,\n  mape,\n  MAPE,\n  cosine\n};\nfunction get2(identifier) {\n  if (typeof identifier === \"string\" && identifier in metricsMap) {\n    return metricsMap[identifier];\n  } else if (typeof identifier !== \"string\" && identifier != null) {\n    return identifier;\n  } else {\n    throw new ValueError(`Unknown metric ${identifier}`);\n  }\n}\nfunction getLossOrMetricName(fn) {\n  assert2(fn !== null, `Unknown LossOrMetricFn ${fn}`);\n  if (typeof fn === \"string\") {\n    return fn;\n  } else {\n    let fnName;\n    for (const key of Object.keys(lossesMap)) {\n      if (lossesMap[key] === fn) {\n        fnName = key;\n        break;\n      }\n    }\n    if (fnName !== void 0) {\n      return fnName;\n    }\n    for (const key of Object.keys(metricsMap)) {\n      if (metricsMap[key] === fn) {\n        fnName = key;\n        break;\n      }\n    }\n    if (fnName !== void 0) {\n      return fnName;\n    }\n    return fn.name;\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/optimizers.js\nfunction getOptimizer(identifier) {\n  const optimizerMap = {\n    \"Adagrad\": () => train.adagrad(0.01),\n    \"Adadelta\": () => train.adadelta(1, 0.95, epsilon()),\n    \"Adam\": () => train.adam(1e-3, 0.9, 0.999, epsilon()),\n    \"Adamax\": () => train.adamax(2e-3, 0.9, 0.999, epsilon(), 0),\n    \"RMSProp\": () => train.rmsprop(1e-3, 0.9, 0, epsilon()),\n    \"SGD\": () => train.sgd(0.01)\n  };\n  optimizerMap[\"adagrad\"] = optimizerMap[\"Adagrad\"];\n  optimizerMap[\"adadelta\"] = optimizerMap[\"Adadelta\"];\n  optimizerMap[\"adam\"] = optimizerMap[\"Adam\"];\n  optimizerMap[\"adamax\"] = optimizerMap[\"Adamax\"];\n  optimizerMap[\"rmsprop\"] = optimizerMap[\"RMSProp\"];\n  optimizerMap[\"sgd\"] = optimizerMap[\"SGD\"];\n  if (identifier in optimizerMap) {\n    return optimizerMap[identifier]();\n  }\n  throw new ValueError(`Unknown Optimizer ${identifier}`);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/user_defined_metadata.js\nvar MAX_USER_DEFINED_METADATA_SERIALIZED_LENGTH = 1 * 1024 * 1024;\nfunction checkUserDefinedMetadata(userDefinedMetadata, modelName, checkSize = false) {\n  if (userDefinedMetadata == null || typeof userDefinedMetadata !== \"object\" || Object.getPrototypeOf(userDefinedMetadata) !== Object.prototype || !plainObjectCheck(userDefinedMetadata)) {\n    throw new Error(\"User-defined metadata is expected to be a JSON object, but is not.\");\n  }\n  if (checkSize) {\n    const out = JSON.stringify(userDefinedMetadata);\n    if (out.length > MAX_USER_DEFINED_METADATA_SERIALIZED_LENGTH) {\n      console.warn(`User-defined metadata of model \"${modelName}\" is too large in size (length=${out.length} when serialized). It is not recommended to store such large objects in user-defined metadata. Please make sure its serialized length is <= ${MAX_USER_DEFINED_METADATA_SERIALIZED_LENGTH}.`);\n    }\n  }\n}\nfunction plainObjectCheck(x) {\n  if (x === null) {\n    return true;\n  } else if (typeof x === \"object\") {\n    if (Object.getPrototypeOf(x) === Object.prototype) {\n      const keys = Object.keys(x);\n      for (const key of keys) {\n        if (typeof key !== \"string\") {\n          return false;\n        }\n        if (!plainObjectCheck(x[key])) {\n          return false;\n        }\n      }\n      return true;\n    } else {\n      if (Array.isArray(x)) {\n        for (const item of x) {\n          if (!plainObjectCheck(item)) {\n            return false;\n          }\n        }\n        return true;\n      } else {\n        return false;\n      }\n    }\n  } else {\n    const xType = typeof x;\n    return xType === \"string\" || xType === \"number\" || xType === \"boolean\";\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/layer_utils.js\nfunction printSummary(model2, lineLength, positions, printFn = console.log) {\n  const sequentialLike = isModelSequentialLike(model2);\n  const toDisplay = [\"Layer (type)\", \"Input Shape\", \"Output shape\", \"Param #\"];\n  if (sequentialLike) {\n    lineLength = lineLength || 90;\n    positions = positions || [0.32, 0.61, 0.89, 1];\n  } else {\n    lineLength = lineLength || 115;\n    positions = positions || [0.24, 0.48, 0.7, 0.8, 1];\n  }\n  if (positions[positions.length - 1] <= 1) {\n    positions = positions.map((p2) => Math.floor(lineLength * p2));\n  }\n  let relevantNodes;\n  if (!sequentialLike) {\n    toDisplay.push(\"Receives inputs\");\n    relevantNodes = [];\n    for (const depth in model2.nodesByDepth) {\n      relevantNodes.push(...model2.nodesByDepth[depth]);\n    }\n  }\n  printFn(\"_\".repeat(lineLength));\n  printRow(toDisplay, positions, printFn);\n  printFn(\"=\".repeat(lineLength));\n  const layers = model2.layers;\n  for (let i2 = 0; i2 < layers.length; ++i2) {\n    if (sequentialLike) {\n      printLayerSummary(layers[i2], positions, printFn);\n    } else {\n      printLayerSummaryWithConnections(layers[i2], positions, relevantNodes, printFn);\n    }\n    printFn((i2 === layers.length - 1 ? \"=\" : \"_\").repeat(lineLength));\n  }\n  model2.checkTrainableWeightsConsistency();\n  const trainableCount = countTrainableParams(model2);\n  const nonTrainableCount = countParamsInWeights(model2.nonTrainableWeights);\n  printFn(`Total params: ${trainableCount + nonTrainableCount}`);\n  printFn(`Trainable params: ${trainableCount}`);\n  printFn(`Non-trainable params: ${nonTrainableCount}`);\n  printFn(\"_\".repeat(lineLength));\n}\nfunction countTrainableParams(model2) {\n  let trainableCount;\n  if (model2.collectedTrainableWeights != null) {\n    trainableCount = countParamsInWeights(model2.collectedTrainableWeights);\n  } else {\n    trainableCount = countParamsInWeights(model2.trainableWeights);\n  }\n  return trainableCount;\n}\nfunction isModelSequentialLike(model2) {\n  let sequentialLike = true;\n  const nodesByDepth = [];\n  const nodes = [];\n  for (const depth in model2.nodesByDepth) {\n    nodesByDepth.push(model2.nodesByDepth[depth]);\n  }\n  for (const depthNodes of nodesByDepth) {\n    if (depthNodes.length > 1 || depthNodes.length === 1 && depthNodes[0].inboundLayers.length > 1) {\n      sequentialLike = false;\n      break;\n    }\n    nodes.push(...depthNodes);\n  }\n  if (sequentialLike) {\n    for (const layer of model2.layers) {\n      let flag = false;\n      for (const node of layer.inboundNodes) {\n        if (nodes.indexOf(node) !== -1) {\n          if (flag) {\n            sequentialLike = false;\n            break;\n          } else {\n            flag = true;\n          }\n        }\n      }\n      if (!sequentialLike) {\n        break;\n      }\n    }\n  }\n  return sequentialLike;\n}\nfunction printRow(fields, positions, printFn = console.log) {\n  let line = \"\";\n  for (let i2 = 0; i2 < fields.length; ++i2) {\n    if (i2 > 0) {\n      line = line.slice(0, line.length - 1) + \" \";\n    }\n    line += fields[i2];\n    line = line.slice(0, positions[i2]);\n    line += \" \".repeat(positions[i2] - line.length);\n  }\n  printFn(line);\n}\nfunction printLayerSummary(layer, positions, printFn) {\n  let outputShape;\n  let inputShape;\n  try {\n    inputShape = layer.inboundNodes.map((x) => JSON.stringify(x.inputShapes)).join(\",\");\n  } catch (err) {\n    inputShape = \"multiple\";\n  }\n  try {\n    outputShape = JSON.stringify(layer.outputShape);\n  } catch (err) {\n    outputShape = \"multiple\";\n  }\n  const name = layer.name;\n  const className = layer.getClassName();\n  const fields = [\n    `${name} (${className})`,\n    inputShape,\n    outputShape,\n    layer.countParams().toString()\n  ];\n  printRow(fields, positions, printFn);\n}\nfunction printLayerSummaryWithConnections(layer, positions, relevantNodes, printFn) {\n  let outputShape;\n  let inputShape;\n  try {\n    inputShape = layer.inboundNodes.map((x) => JSON.stringify(x.inputShapes)).join(\",\");\n  } catch (err) {\n    inputShape = \"multiple\";\n  }\n  try {\n    outputShape = JSON.stringify(layer.outputShape);\n  } catch (err) {\n    outputShape = \"multiple\";\n  }\n  const connections = [];\n  for (const node of layer.inboundNodes) {\n    if (relevantNodes != null && relevantNodes.length > 0 && relevantNodes.indexOf(node) === -1) {\n      continue;\n    }\n    for (let i2 = 0; i2 < node.inboundLayers.length; ++i2) {\n      const inboundLayer = node.inboundLayers[i2].name;\n      const inboundLayerIndex = node.nodeIndices[i2];\n      const inboundTensorIndex = node.tensorIndices[i2];\n      connections.push(`${inboundLayer}[${inboundLayerIndex}][${inboundTensorIndex}]`);\n    }\n  }\n  const name = layer.name;\n  const className = layer.getClassName();\n  const firstConnection = connections.length === 0 ? \"\" : connections[0];\n  const fields = [\n    `${name} (${className})`,\n    inputShape,\n    outputShape,\n    layer.countParams().toString(),\n    firstConnection\n  ];\n  printRow(fields, positions, printFn);\n  for (let i2 = 1; i2 < connections.length; ++i2) {\n    printRow([\"\", \"\", \"\", \"\", connections[i2]], positions, printFn);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/serialization_utils.js\nfunction isArrayItemInputOrOutputName(key, index, value) {\n  return (key === \"inboundNodes\" || key === \"outputLayers\" || key === \"inputLayers\") && index === 0 && typeof value === \"string\";\n}\nfunction convertPythonicToTs(pythonicConfig, key) {\n  if (pythonicConfig === null) {\n    return null;\n  } else if (typeof pythonicConfig === \"string\") {\n    return toCamelCase(pythonicConfig);\n  } else if (typeof pythonicConfig === \"number\" || typeof pythonicConfig === \"boolean\") {\n    return pythonicConfig;\n  } else if (pythonicConfig instanceof Array) {\n    const tsArray = [];\n    const arrayLength = pythonicConfig.length;\n    for (let i2 = 0; i2 < arrayLength; ++i2) {\n      const item = pythonicConfig[i2];\n      if (isArrayItemInputOrOutputName(key, i2, item)) {\n        tsArray.push(item);\n      } else {\n        tsArray.push(convertPythonicToTs(item, key));\n      }\n    }\n    return tsArray;\n  } else {\n    const tsDict = {};\n    for (const pythonicKey of Object.keys(pythonicConfig)) {\n      const pythonicValue = pythonicConfig[pythonicKey];\n      if (pythonicKey === \"name\" && typeof pythonicValue === \"string\") {\n        tsDict[pythonicKey] = pythonicValue;\n      } else {\n        const tsKey = toCamelCase(pythonicKey);\n        tsDict[tsKey] = convertPythonicToTs(pythonicValue, tsKey);\n      }\n    }\n    return tsDict;\n  }\n}\nfunction convertTsToPythonic(tsConfig, key) {\n  if (tsConfig === null || tsConfig === void 0) {\n    return null;\n  } else if (typeof tsConfig === \"string\") {\n    return toSnakeCase(tsConfig);\n  } else if (typeof tsConfig === \"number\" || typeof tsConfig === \"boolean\") {\n    return tsConfig;\n  } else if (tsConfig instanceof Array) {\n    const pyArray = [];\n    const arrayLength = tsConfig.length;\n    for (let i2 = 0; i2 < arrayLength; ++i2) {\n      const item = tsConfig[i2];\n      if (isArrayItemInputOrOutputName(key, i2, item)) {\n        pyArray.push(item);\n      } else {\n        pyArray.push(convertTsToPythonic(item, key));\n      }\n    }\n    return pyArray;\n  } else {\n    const pyDict = {};\n    for (const tsKey of Object.keys(tsConfig)) {\n      const tsValue = tsConfig[tsKey];\n      const pyKey = toSnakeCase(tsKey);\n      if ((tsKey === \"name\" || tsKey === \"className\") && typeof tsValue === \"string\") {\n        pyDict[pyKey] = tsValue;\n      } else {\n        pyDict[pyKey] = convertTsToPythonic(tsValue, tsKey);\n      }\n    }\n    return pyDict;\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/version.js\nvar version2 = \"3.19.0\";\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/container.js\nvar Container = class extends Layer {\n  constructor(args) {\n    super({});\n    this.containerNodes = /* @__PURE__ */ new Set();\n    this.name = args.name;\n    if (this.name == null) {\n      const prefix = this.getClassName().toLowerCase();\n      this.name = getUid(prefix);\n    }\n    this.supportsMasking = false;\n    this.trainable_ = true;\n    if (Array.isArray(args.inputs)) {\n      this.inputs = args.inputs.slice();\n    } else {\n      this.inputs = [args.inputs];\n    }\n    if (Array.isArray(args.outputs)) {\n      this.outputs = args.outputs.slice();\n    } else {\n      this.outputs = [args.outputs];\n    }\n    if (unique2(this.inputs).length !== this.inputs.length) {\n      throw new ValueError(`The list of inputs passed to the model is redundant. All inputs should only appear once. Found: ${this.inputs.map((x) => x.name)}`);\n    }\n    if (unique2(this.outputs).length !== this.outputs.length) {\n      console.warn(`The list of outputs passed to the model is redundant. All outputs should only appear once. Found: ${this.outputs.map((x) => x.name)}`);\n    }\n    this.inputLayers = [];\n    this.inputLayersNodeIndices = [];\n    this.inputLayersTensorIndices = [];\n    this.outputLayers = [];\n    this.outputLayersNodeIndices = [];\n    this.outputLayersTensorIndices = [];\n    this.layers = [];\n    this.internalContainerRefs = [];\n    for (const x of this.outputs) {\n      const layer = x.sourceLayer;\n      const nodeIndex = x.nodeIndex;\n      const tensorIndex = x.tensorIndex;\n      this.outputLayers.push(layer);\n      this.outputLayersNodeIndices.push(nodeIndex);\n      this.outputLayersTensorIndices.push(tensorIndex);\n    }\n    for (const x of this.inputs) {\n      const layer = x.sourceLayer;\n      const nodeIndex = x.nodeIndex;\n      const tensorIndex = x.tensorIndex;\n      assert2(nodeIndex === 0, \"input layer has >1 nodes\");\n      assert2(tensorIndex === 0, \"input layer has >1 tensors\");\n      this.inputLayers.push(layer);\n      this.inputLayersNodeIndices.push(nodeIndex);\n      this.inputLayersTensorIndices.push(tensorIndex);\n    }\n    this.inputNames = [];\n    this.outputNames = [];\n    this.feedInputShapes = [];\n    this.feedInputNames = [];\n    this.feedOutputNames = [];\n    for (let i2 = 0; i2 < this.inputLayers.length; i2++) {\n      const layer = this.inputLayers[i2];\n      if (!(layer instanceof InputLayer)) {\n        throw new TypeError(`Input layers to a LayersModel must be InputLayer objects. Received inputs: ${args.inputs}. Input ${i2} (0-based) originates from layer type ${layer.getClassName()}.`);\n      }\n      this.inputNames.push(layer.name);\n      this.feedInputShapes.push(layer.batchInputShape);\n      this.feedInputNames.push(layer.name);\n    }\n    for (const layer of this.outputLayers) {\n      this.outputNames.push(layer.name);\n    }\n    this.internalInputShapes = this.inputs.map((x) => x.shape);\n    this.internalOutputShapes = this.outputs.map((x) => x.shape);\n    const nodesDepths = {};\n    const nodeIDToNode = {};\n    const layersDepths = {};\n    const layerIDToLayer = {};\n    const layerIndices = {};\n    const nodesInDecreasingDepth = [];\n    const buildMapOfGraph = (tensor2, finishedNodes2, nodesInProgress2, layer, nodeIndex, tensorIndex) => {\n      if (layer == null || nodeIndex == null || tensorIndex == null) {\n        layer = tensor2.sourceLayer;\n        nodeIndex = tensor2.nodeIndex;\n        tensorIndex = tensor2.tensorIndex;\n      }\n      const node = layer.inboundNodes[nodeIndex];\n      if (nodesInProgress2.indexOf(node) !== -1) {\n        throw new RuntimeError(`The tensor ${tensor2.name} at layer \"${layer.name}\" is part of a cycle.`);\n      }\n      if (finishedNodes2.indexOf(node) !== -1) {\n        return;\n      }\n      this.containerNodes.add(Container.nodeKey(layer, nodeIndex));\n      if (!(layer.id in layerIndices)) {\n        layerIndices[layer.id] = Object.keys(layerIndices).length;\n      }\n      if (nodesInProgress2.indexOf(node) === -1) {\n        nodesInProgress2.push(node);\n      }\n      const numInboundLayers = node.inboundLayers.length;\n      for (let i2 = 0; i2 < numInboundLayers; i2++) {\n        const x = node.inputTensors[i2];\n        const layer2 = node.inboundLayers[i2];\n        const nodeIndex2 = node.nodeIndices[i2];\n        const tensorIndex2 = node.tensorIndices[i2];\n        buildMapOfGraph(x, finishedNodes2, nodesInProgress2, layer2, nodeIndex2, tensorIndex2);\n      }\n      finishedNodes2.push(node);\n      while (nodesInProgress2.indexOf(node) >= 0) {\n        nodesInProgress2.splice(nodesInProgress2.indexOf(node), 1);\n      }\n      nodesInDecreasingDepth.push(node);\n    };\n    const finishedNodes = [];\n    const nodesInProgress = [];\n    for (const x of this.outputs) {\n      buildMapOfGraph(x, finishedNodes, nodesInProgress);\n    }\n    const reversedNodesInDecreasingDepth = nodesInDecreasingDepth.slice().reverse();\n    for (const node of reversedNodesInDecreasingDepth) {\n      nodeIDToNode[node.id] = node;\n      if (!(node.id in nodesDepths)) {\n        nodesDepths[node.id] = 0;\n      }\n      let depth = nodesDepths[node.id];\n      const previousDepth = layersDepths[node.outboundLayer.id] == null ? 0 : layersDepths[node.outboundLayer.id];\n      depth = Math.max(depth, previousDepth);\n      layersDepths[node.outboundLayer.id] = depth;\n      layerIDToLayer[node.outboundLayer.id] = node.outboundLayer;\n      nodesDepths[node.id] = depth;\n      for (let i2 = 0; i2 < node.inboundLayers.length; i2++) {\n        const inboundLayer = node.inboundLayers[i2];\n        const nodeIndex = node.nodeIndices[i2];\n        const inboundNode = inboundLayer.inboundNodes[nodeIndex];\n        const previousDepth2 = nodesDepths[inboundNode.id] == null ? 0 : nodesDepths[inboundNode.id];\n        nodesDepths[inboundNode.id] = Math.max(depth + 1, previousDepth2);\n        nodeIDToNode[inboundNode.id] = inboundNode;\n      }\n    }\n    const nodesByDepth = {};\n    for (const nodeID in nodesDepths) {\n      const depth = nodesDepths[nodeID];\n      if (!(depth in nodesByDepth)) {\n        nodesByDepth[depth] = [];\n      }\n      nodesByDepth[depth].push(nodeIDToNode[nodeID]);\n    }\n    const layersByDepth = {};\n    for (const layerID in layersDepths) {\n      const depth = layersDepths[layerID];\n      if (!(depth in layersByDepth)) {\n        layersByDepth[depth] = [];\n      }\n      layersByDepth[depth].push(layerIDToLayer[layerID]);\n    }\n    let depthKeys = Object.keys(layersByDepth).map((x) => parseInt(x, 10)).sort(reverseNumberCompare);\n    this.layers = [];\n    for (const depth of depthKeys) {\n      const layersForDepth = layersByDepth[depth];\n      layersForDepth.sort((a, b) => {\n        const aIndex = layerIndices[a.id];\n        const bIndex = layerIndices[b.id];\n        if (aIndex < bIndex) {\n          return -1;\n        }\n        if (aIndex > bIndex) {\n          return 1;\n        }\n        return 0;\n      });\n      for (const layer of layersForDepth) {\n        if (layer instanceof Container) {\n          this.internalContainerRefs.push(layer);\n        }\n        this.layers.push(layer);\n      }\n    }\n    this.layersByDepth = layersByDepth;\n    depthKeys = Object.keys(nodesByDepth).map((x) => parseInt(x, 10)).sort(reverseNumberCompare);\n    const computableTensors = this.inputs.slice();\n    const layersWithCompleteInput = [];\n    for (const depth of depthKeys) {\n      for (const node of nodesByDepth[depth]) {\n        const layer = node.outboundLayer;\n        if (layer != null) {\n          for (const x of node.inputTensors) {\n            if (computableTensors.indexOf(x) === -1) {\n              throw new RuntimeError(`Graph disconnected: cannot obtain value for tensor ${x} at layer \"${layer.name}\". The following previous layers were accessed without issue: ${layersWithCompleteInput}`);\n            }\n          }\n          for (const x of node.outputTensors) {\n            computableTensors.push(x);\n          }\n          layersWithCompleteInput.push(layer.name);\n        }\n      }\n    }\n    this.nodesByDepth = nodesByDepth;\n    const allNames = this.layers.map((x) => x.name);\n    for (const name of allNames) {\n      const numOccurrences = allNames.filter((x) => x === name).length;\n      if (numOccurrences !== 1) {\n        throw new RuntimeError(`The name \"${name}\" is used ${numOccurrences} times in the model. All layer names should be unique. Layer names: ` + JSON.stringify(allNames));\n      }\n    }\n    this.outboundNodes = [];\n    this.inboundNodes = [];\n    new Node({\n      outboundLayer: this,\n      inboundLayers: [],\n      nodeIndices: [],\n      tensorIndices: [],\n      inputTensors: this.inputs,\n      outputTensors: this.outputs,\n      inputMasks: this.inputs.map((x) => null),\n      outputMasks: this.outputs.map((x) => null),\n      inputShapes: this.inputs.map((x) => x.shape),\n      outputShapes: this.outputs.map((x) => x.shape)\n    });\n    this.built = true;\n    this._refCount = 1;\n  }\n  assertNotDisposed() {\n    if (this._refCount === 0) {\n      throw new Error(`Container '${this.name}' is already disposed.`);\n    }\n  }\n  dispose() {\n    this.assertNotDisposed();\n    const result = { refCountAfterDispose: null, numDisposedVariables: 0 };\n    if (--this._refCount === 0) {\n      for (const layer of this.layers) {\n        result.numDisposedVariables += layer.dispose().numDisposedVariables;\n      }\n      for (const container of this.internalContainerRefs) {\n        result.numDisposedVariables += container.dispose().numDisposedVariables;\n      }\n    }\n    result.refCountAfterDispose = this._refCount;\n    return result;\n  }\n  get trainable() {\n    return this.trainable_;\n  }\n  set trainable(trainable) {\n    this.layers.forEach((layer) => {\n      layer._trainableWeights.forEach((w) => w.trainable = trainable);\n    });\n    this.trainable_ = trainable;\n  }\n  get trainableWeights() {\n    if (this._trainableWeights.length > 0) {\n      throw new ValueError(\"Container instance unexpectedly contains _trainableWeights.The trainable weights of a Container are a union of the trainable weights of its consituent Layers. Its own _trainableWeights must remain an empty Array.\");\n    }\n    if (!this.trainable) {\n      return [];\n    }\n    let weights = [];\n    for (const layer of this.layers) {\n      weights = weights.concat(layer.trainableWeights);\n    }\n    return weights;\n  }\n  get nonTrainableWeights() {\n    const weights = [];\n    for (const layer of this.layers) {\n      weights.push(...layer.nonTrainableWeights);\n    }\n    if (!this.trainable) {\n      const trainableWeights = [];\n      for (const layer of this.layers) {\n        trainableWeights.push(...layer.trainableWeights);\n      }\n      return trainableWeights.concat(weights);\n    }\n    return weights;\n  }\n  get weights() {\n    return this.trainableWeights.concat(this.nonTrainableWeights);\n  }\n  loadWeights(weights, strict = true) {\n    const nameToWeight = {};\n    let totalWeightsCount = 0;\n    for (const layer of this.layers) {\n      for (const weight of layer.weights) {\n        if (nameToWeight[weight.originalName] != null) {\n          throw new ValueError(`Duplicate weight name: ${weight.originalName}`);\n        }\n        nameToWeight[weight.originalName] = weight;\n        totalWeightsCount++;\n      }\n    }\n    const weightValueTuples = [];\n    for (const name in weights) {\n      let validatedName = name;\n      if (nameToWeight[name] == null) {\n        const tokens = name.split(\"/\");\n        const shortenNameArray = tokens.slice(0, -2).concat([tokens[tokens.length - 1]]);\n        validatedName = shortenNameArray.join(\"/\");\n      }\n      if (nameToWeight[validatedName] != null) {\n        weightValueTuples.push([nameToWeight[validatedName], weights[name]]);\n      } else if (strict) {\n        throw new ValueError(`Provided weight data has no target variable: ${name}`);\n      }\n      delete nameToWeight[validatedName];\n    }\n    if (strict) {\n      const unsetNames = [];\n      for (const name in nameToWeight) {\n        unsetNames.push(name);\n      }\n      if (unsetNames.length > 0) {\n        throw new ValueError(`${unsetNames.length} of ${totalWeightsCount} weights are not set: ${unsetNames}`);\n      }\n    }\n    batchSetValue(weightValueTuples);\n  }\n  updatedConfig() {\n    const theConfig = this.getConfig();\n    const modelConfig = {};\n    modelConfig[\"className\"] = this.getClassName();\n    modelConfig[\"config\"] = theConfig;\n    modelConfig[\"kerasVersion\"] = `tfjs-layers ${version2}`;\n    modelConfig[\"backend\"] = \"TensorFlow.js\";\n    return modelConfig;\n  }\n  toJSON(unused, returnString = true) {\n    const modelConfig = convertTsToPythonic(this.updatedConfig());\n    return returnString ? JSON.stringify(modelConfig) : modelConfig;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = toList(inputs);\n      const feedDict = new FeedDict();\n      for (let i2 = 0; i2 < this.inputs.length; ++i2) {\n        feedDict.add(this.inputs[i2], inputs[i2]);\n      }\n      return execute(this.outputs, feedDict, kwargs);\n    });\n  }\n  computeMask(inputs, mask) {\n    return tidy(() => {\n      inputs = toList(inputs);\n      let masks;\n      if (mask == null) {\n        masks = pyListRepeat(null, inputs.length);\n      } else {\n        masks = toList(mask);\n      }\n      return this.runInternalGraph(inputs, masks)[1];\n    });\n  }\n  computeOutputShape(inputShape) {\n    const inputShapes = normalizeShapeList(inputShape);\n    if (inputShapes.length !== this.inputLayers.length) {\n      throw new ValueError(`Invalid inputShape argument ${inputShape}: model has ${this.inputLayers.length} tensor inputs.`);\n    }\n    const layersToOutputShapes = {};\n    for (let i2 = 0; i2 < inputShapes.length; i2++) {\n      const layer = this.inputLayers[i2];\n      const inputShape2 = inputShapes[i2];\n      const shapeKey = layer.name + \"_0_0\";\n      layersToOutputShapes[shapeKey] = inputShape2;\n    }\n    const depthKeys = Object.keys(this.nodesByDepth).map((x) => parseInt(x, 10)).sort(reverseNumberCompare);\n    if (depthKeys.length > 1) {\n      for (const depth of depthKeys) {\n        const nodes = this.nodesByDepth[depth];\n        for (const node of nodes) {\n          const layer = node.outboundLayer;\n          if (this.inputLayers.map((x) => x.id).indexOf(layer.id) !== -1) {\n            continue;\n          }\n          const inputShapes2 = [];\n          for (let j = 0; j < node.inboundLayers.length; j++) {\n            const inboundLayer = node.inboundLayers[j];\n            const nodeIndex2 = node.nodeIndices[j];\n            const tensorIndex = node.tensorIndices[j];\n            const shapeKey = `${inboundLayer.name}_${nodeIndex2}_${tensorIndex}`;\n            const inputShape2 = layersToOutputShapes[shapeKey];\n            inputShapes2.push(inputShape2);\n          }\n          const outputShape = layer.computeOutputShape(singletonOrArray(inputShapes2));\n          const outputShapes2 = normalizeShapeList(outputShape);\n          const nodeIndex = layer.inboundNodes.indexOf(node);\n          for (let j = 0; j < outputShapes2.length; j++) {\n            const shapeKey = `${layer.name}_${nodeIndex}_${j}`;\n            layersToOutputShapes[shapeKey] = outputShapes2[j];\n          }\n        }\n      }\n    }\n    const outputShapes = [];\n    const outputShapeKeys = [];\n    for (let i2 = 0; i2 < this.outputLayers.length; i2++) {\n      const layer = this.outputLayers[i2];\n      const nodeIndex = this.outputLayersNodeIndices[i2];\n      const tensorIndex = this.outputLayersTensorIndices[i2];\n      const shapeKey = `${layer.name}_${nodeIndex}_${tensorIndex}`;\n      outputShapeKeys.push(shapeKey);\n    }\n    for (let i2 = 0; i2 < outputShapeKeys.length; i2++) {\n      const key = outputShapeKeys[i2];\n      assert2(key in layersToOutputShapes);\n      outputShapes.push(layersToOutputShapes[key]);\n    }\n    return singletonOrArray(outputShapes);\n  }\n  runInternalGraph(inputs, masks) {\n    if (masks == null) {\n      masks = pyListRepeat(null, inputs.length);\n    }\n    const tensorMap = {};\n    for (let i2 = 0; i2 < this.inputs.length; ++i2) {\n      const x = this.inputs[i2];\n      const y = inputs[i2];\n      const mask = masks[i2];\n      tensorMap[x.id] = [y, mask];\n    }\n    const depthKeys = Object.keys(this.nodesByDepth).map((x) => parseInt(x, 10)).sort(reverseNumberCompare);\n    for (const depth of depthKeys) {\n      const nodes = this.nodesByDepth[depth];\n      for (const node of nodes) {\n        const layer = node.outboundLayer;\n        const referenceInputTensors = node.inputTensors;\n        const referenceOutputTensors = node.outputTensors;\n        const computedData = new Array();\n        for (const x of referenceInputTensors) {\n          if (x.id in tensorMap) {\n            computedData.push(tensorMap[x.id]);\n          }\n        }\n        if (computedData.length === referenceInputTensors.length) {\n          let kwargs = {};\n          let computedTensors;\n          let computedMasks;\n          let outputTensors2;\n          let outputMasks2;\n          if (node.callArgs != null) {\n            kwargs = node.callArgs;\n          }\n          if (computedData.length === 1) {\n            const [computedTensor, computedMask] = computedData[0];\n            if (kwargs[\"mask\"] == null) {\n              kwargs[\"mask\"] = computedMask;\n            }\n            outputTensors2 = toList(layer.call(computedTensor, kwargs));\n            outputMasks2 = toList(layer.computeMask(computedTensor, computedMask));\n            computedTensors = [computedTensor];\n            computedMasks = [computedMask];\n          } else {\n            computedTensors = computedData.map((x) => x[0]);\n            computedMasks = computedData.map((x) => x[1]);\n            if (kwargs[\"mask\"] == null) {\n              kwargs[\"mask\"] = computedMasks;\n            }\n            outputTensors2 = toList(layer.call(computedTensors, kwargs));\n            outputMasks2 = toList(layer.computeMask(computedTensors, computedMasks));\n          }\n          if (layer.activityRegularizer) {\n            throw new NotImplementedError(\"LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.\");\n          }\n          for (let i2 = 0; i2 < referenceOutputTensors.length; ++i2) {\n            const x = referenceOutputTensors[i2];\n            const y = outputTensors2[i2];\n            const mask = outputMasks2[i2];\n            tensorMap[x.id] = [y, mask];\n          }\n        }\n      }\n    }\n    const outputTensors = [];\n    const outputMasks = [];\n    const outputShapes = [];\n    for (const x of this.outputs) {\n      assert2(x.id in tensorMap, `Could not compute output ${x.name} : ${x.id}`);\n      const [tensor2, mask] = tensorMap[x.id];\n      outputShapes.push(tensor2.shape);\n      outputTensors.push(tensor2);\n      outputMasks.push(mask);\n    }\n    return [outputTensors, outputMasks, outputShapes];\n  }\n  buildNodeConversionMap(layers) {\n    const nodeConversionMap = {};\n    let keptNodes;\n    for (const layer of this.layers) {\n      keptNodes = layer instanceof Container ? 1 : 0;\n      for (let originalNodeIndex = 0; originalNodeIndex < layer.inboundNodes.length; originalNodeIndex++) {\n        const nodeKey = Container.nodeKey(layer, originalNodeIndex);\n        if (this.containerNodes.has(nodeKey)) {\n          nodeConversionMap[nodeKey] = keptNodes;\n          keptNodes += 1;\n        }\n      }\n    }\n    return nodeConversionMap;\n  }\n  getLayer(name, index) {\n    if (index != null) {\n      if (this.layers.length <= index) {\n        throw new ValueError(`Was asked to retrieve layer at index ${index}, but model only has ${this.layers.length} layer(s).`);\n      } else {\n        return this.layers[index];\n      }\n    } else {\n      if (name == null) {\n        throw new ValueError(\"Provide either a layer name or layer index\");\n      }\n    }\n    for (const layer of this.layers) {\n      if (layer.name === name) {\n        return layer;\n      }\n    }\n    throw new ValueError(`No such layer: ${name}`);\n  }\n  calculateLosses() {\n    return tidy(() => {\n      const losses2 = [];\n      for (const layer of this.layers) {\n        for (let nodeIndex = 0; nodeIndex < layer.inboundNodes.length; ++nodeIndex) {\n          const nodeKey = Container.nodeKey(layer, nodeIndex);\n          if (this.containerNodes.has(nodeKey)) {\n            losses2.push(...layer.calculateLosses());\n          }\n        }\n      }\n      return losses2;\n    });\n  }\n  getConfig() {\n    const config = { name: this.name };\n    const nodeConversionMap = this.buildNodeConversionMap(this.layers);\n    const layerConfigs = [];\n    for (const layer of this.layers) {\n      const layerClassName = layer.getClassName();\n      const layerConfig = layer.getConfig();\n      const filteredInboundNodes = [];\n      for (let originalNodeIndex = 0; originalNodeIndex < layer.inboundNodes.length; originalNodeIndex++) {\n        const node = layer.inboundNodes[originalNodeIndex];\n        const nodeKey = Container.nodeKey(layer, originalNodeIndex);\n        let kwargs = {};\n        if (this.containerNodes.has(nodeKey)) {\n          if (node.callArgs) {\n            try {\n              JSON.stringify(node.callArgs);\n              kwargs = node.callArgs;\n            } catch (err) {\n              console.warn(`Layer ${layer.name} was passed non-serializable keyword arguments: ${node.callArgs}. They will not be included in the serialized model (and thus will be missing at deserialization time).`);\n              kwargs = {};\n            }\n          }\n          if (node.inboundLayers.length > 0) {\n            const nodeData = [];\n            for (let i2 = 0; i2 < node.inboundLayers.length; i2++) {\n              const inboundLayer = node.inboundLayers[i2];\n              const nodeIndex = node.nodeIndices[i2];\n              const tensorIndex = node.tensorIndices[i2];\n              const nodeKey2 = Container.nodeKey(inboundLayer, nodeIndex);\n              let newNodeIndex = nodeConversionMap[nodeKey2];\n              if (newNodeIndex == null) {\n                newNodeIndex = 0;\n              }\n              nodeData.push([inboundLayer.name, newNodeIndex, tensorIndex, kwargs]);\n            }\n            filteredInboundNodes.push(nodeData);\n          }\n        }\n      }\n      const dict = {};\n      dict[\"name\"] = layer.name;\n      dict[\"className\"] = layerClassName;\n      dict[\"config\"] = layerConfig;\n      dict[\"inboundNodes\"] = filteredInboundNodes;\n      layerConfigs.push(dict);\n    }\n    config[\"layers\"] = layerConfigs;\n    const modelInputs = [];\n    for (let i2 = 0; i2 < this.inputLayers.length; i2++) {\n      const layer = this.inputLayers[i2];\n      const nodeIndex = this.inputLayersNodeIndices[i2];\n      const nodeKey = Container.nodeKey(layer, nodeIndex);\n      if (!this.containerNodes.has(nodeKey)) {\n        continue;\n      }\n      let newNodeIndex = nodeConversionMap[nodeKey];\n      if (newNodeIndex === null || newNodeIndex === void 0) {\n        newNodeIndex = 0;\n      }\n      const tensorIndex = this.inputLayersTensorIndices[i2];\n      modelInputs.push([layer.name, newNodeIndex, tensorIndex]);\n    }\n    config[\"inputLayers\"] = modelInputs;\n    const modelOutputs = [];\n    for (let i2 = 0; i2 < this.outputLayers.length; i2++) {\n      const layer = this.outputLayers[i2];\n      const nodeIndex = this.outputLayersNodeIndices[i2];\n      const nodeKey = Container.nodeKey(layer, nodeIndex);\n      if (!this.containerNodes.has(nodeKey)) {\n        continue;\n      }\n      let newNodeIndex = nodeConversionMap[nodeKey];\n      if (newNodeIndex === null || newNodeIndex === void 0) {\n        newNodeIndex = 0;\n      }\n      const tensorIndex = this.outputLayersTensorIndices[i2];\n      modelOutputs.push([layer.name, newNodeIndex, tensorIndex]);\n    }\n    config[\"outputLayers\"] = modelOutputs;\n    return config;\n  }\n  static fromConfig(cls, config, customObjects = {}, fastWeightInit = false) {\n    const createdLayers = {};\n    const unprocessedNodes = {};\n    function addUnprocessedNode(layer, nodeData) {\n      if (!(layer.name in unprocessedNodes)) {\n        unprocessedNodes[layer.name] = [nodeData];\n      } else {\n        unprocessedNodes[layer.name].push(nodeData);\n      }\n    }\n    function processNode(layer, nodeData) {\n      const inputTensors2 = [];\n      let kwargs;\n      for (const inputData of nodeData) {\n        const inboundLayerName = inputData[0];\n        const inboundNodeIndex = inputData[1];\n        const inboundTensorIndex = inputData[2];\n        kwargs = inputData[3] == null ? {} : inputData[3];\n        if (!(inboundLayerName in createdLayers)) {\n          addUnprocessedNode(layer, nodeData);\n          return;\n        }\n        const inboundLayer = createdLayers[inboundLayerName];\n        if (inboundLayer.inboundNodes.length <= inboundNodeIndex) {\n          addUnprocessedNode(layer, nodeData);\n          return;\n        }\n        const inboundNode = inboundLayer.inboundNodes[inboundNodeIndex];\n        inputTensors2.push(inboundNode.outputTensors[inboundTensorIndex]);\n      }\n      if (inputTensors2.length > 0) {\n        layer.apply(singletonOrArray(inputTensors2), kwargs);\n      }\n    }\n    function processLayer(layerData) {\n      const layerName = layerData[\"name\"];\n      const layer = deserialize(layerData, config[\"customObjects\"] != null ? config[\"customObjects\"] : {});\n      layer.setFastWeightInitDuringBuild(fastWeightInit);\n      createdLayers[layerName] = layer;\n      const inboundNodesData = layerData[\"inboundNodes\"];\n      inboundNodesData.forEach((nodeData) => {\n        if (!(nodeData instanceof Array)) {\n          throw new ValueError(`Corrupted configuration, expected array for nodeData: ${nodeData}`);\n        }\n        addUnprocessedNode(layer, nodeData);\n      });\n    }\n    const name = config[\"name\"];\n    const layersFromConfig = config[\"layers\"];\n    for (const layerData of layersFromConfig) {\n      processLayer(layerData);\n    }\n    while (!isObjectEmpty(unprocessedNodes)) {\n      for (const layerData of layersFromConfig) {\n        const layer = createdLayers[layerData[\"name\"]];\n        if (layer.name in unprocessedNodes) {\n          const currentUnprocessedNodesForLayer = unprocessedNodes[layer.name];\n          delete unprocessedNodes[layer.name];\n          for (const nodeData of currentUnprocessedNodesForLayer) {\n            processNode(layer, nodeData);\n          }\n        }\n      }\n    }\n    const inputTensors = [];\n    const outputTensors = [];\n    const inputLayersFromConfig = config[\"inputLayers\"];\n    for (const layerData of inputLayersFromConfig) {\n      const layerName = layerData[0];\n      const nodeIndex = layerData[1];\n      const tensorIndex = layerData[2];\n      assert2(layerName in createdLayers);\n      const layer = createdLayers[layerName];\n      const layerOutputTensors = layer.inboundNodes[nodeIndex].outputTensors;\n      inputTensors.push(layerOutputTensors[tensorIndex]);\n    }\n    const outputLayersFromConfig = config[\"outputLayers\"];\n    for (const layerData of outputLayersFromConfig) {\n      const layerName = layerData[0];\n      const nodeIndex = layerData[1];\n      const tensorIndex = layerData[2];\n      assert2(layerName in createdLayers);\n      const layer = createdLayers[layerName];\n      const layerOutputTensors = layer.inboundNodes[nodeIndex].outputTensors;\n      outputTensors.push(layerOutputTensors[tensorIndex]);\n    }\n    return new cls({ inputs: inputTensors, outputs: outputTensors, name });\n  }\n  get stateful() {\n    if (this._stateful) {\n      throw new ValueError(\"Container instance unexpectedly has _stateful = true. The statefulness of a Container is determined by the Layers it contains. Its _stateful property must remain the default false.\");\n    }\n    for (const layer of this.layers) {\n      if (layer.stateful) {\n        return true;\n      }\n    }\n    return false;\n  }\n  resetStates() {\n    tidy(() => {\n      this.layers.forEach((layer) => {\n        if (layer.stateful) {\n          layer.resetStates();\n        }\n      });\n    });\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/training_utils.js\nfunction standardizeSampleOrClassWeights(xWeight, outputNames, weightType) {\n  const numOutputs = outputNames.length;\n  if (xWeight == null || Array.isArray(xWeight) && xWeight.length === 0) {\n    return outputNames.map((name) => null);\n  }\n  if (numOutputs === 1) {\n    if (Array.isArray(xWeight) && xWeight.length === 1) {\n      return xWeight;\n    } else if (typeof xWeight === \"object\" && outputNames[0] in xWeight) {\n      return [xWeight[outputNames[0]]];\n    } else {\n      return [xWeight];\n    }\n  }\n  if (Array.isArray(xWeight)) {\n    if (xWeight.length !== numOutputs) {\n      throw new Error(`Provided ${weightType} is an array of ${xWeight.length} element(s), but the model has ${numOutputs} outputs. Make sure a set of weights is provided for each model output.`);\n    }\n    return xWeight;\n  } else if (typeof xWeight === \"object\" && Object.keys(xWeight).length > 0 && typeof xWeight[Object.keys(xWeight)[0]] === \"object\") {\n    const output = [];\n    outputNames.forEach((outputName) => {\n      if (outputName in xWeight) {\n        output.push(xWeight[outputName]);\n      } else {\n        output.push(null);\n      }\n    });\n    return output;\n  } else {\n    throw new Error(`The model has multiple (${numOutputs}) outputs, so ${weightType} must be either an array with ${numOutputs} elements or an object with ${outputNames} keys. Provided ${weightType} not understood: ${JSON.stringify(xWeight)}`);\n  }\n}\nfunction standardizeClassWeights(classWeight, outputNames) {\n  return standardizeSampleOrClassWeights(classWeight, outputNames, \"classWeight\");\n}\nasync function standardizeWeights(y, sampleWeight, classWeight, sampleWeightMode) {\n  if (sampleWeight != null || sampleWeightMode != null) {\n    throw new Error(\"Support sampleWeight is not implemented yet\");\n  }\n  if (classWeight != null) {\n    const yClasses = tidy(() => {\n      if (y.shape.length === 1) {\n        return clone(y);\n      } else if (y.shape.length === 2) {\n        if (y.shape[1] > 1) {\n          const axis = 1;\n          return argMax(y, axis);\n        } else if (y.shape[1] === 1) {\n          return reshape(y, [y.shape[0]]);\n        } else {\n          throw new Error(`Encountered unexpected last-dimension size (${y.shape[1]}) during handling of class weights. The size is expected to be >= 1.`);\n        }\n      } else {\n        throw new Error(`Unexpected rank of target (y) tensor (${y.rank}) during handling of class weights. The rank is expected to be 1 or 2.`);\n      }\n    });\n    const yClassIndices = Array.from(await yClasses.data());\n    dispose(yClasses);\n    const classSampleWeight = [];\n    yClassIndices.forEach((classIndex) => {\n      if (classWeight[classIndex] == null) {\n        throw new Error(`classWeight must contain all classes in the training data. The class ${classIndex} exists in the data but not in classWeight`);\n      } else {\n        classSampleWeight.push(classWeight[classIndex]);\n      }\n    });\n    return tensor1d(classSampleWeight, \"float32\");\n  } else {\n    return null;\n  }\n}\nfunction computeWeightedLoss2(losses2, sampleWeights) {\n  return mul(losses2, sampleWeights);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/training_dataset.js\nvar DEFAULT_VALIDATION_BATCH_SIZE = 32;\nfunction standardizeDataIteratorOutput(model2, iteratorOut) {\n  let xs;\n  let ys;\n  const iteratorOutObj = iteratorOut;\n  xs = iteratorOutObj[\"xs\"];\n  ys = iteratorOutObj[\"ys\"];\n  util_exports.assert(xs != null && ys != null, () => `A Dataset iterator for fitDataset() is expected to generate objects of the form \\`{xs: xVal, ys: yVal}\\`, where the two values may be \\`tf.Tensor\\`, an array of Tensors, or a map of string to Tensor.  The provided Dataset instead generates ${iteratorOut}`);\n  const flattenedXs = flattenTensorOrArrayOrMap(\"input\", model2.inputNames, xs);\n  const flattenedYs = flattenTensorOrArrayOrMap(\"output\", model2.outputNames, ys);\n  const batchSize = flattenedXs[0].shape[0];\n  util_exports.assert(flattenedXs.length === model2.inputs.length, () => `LayersModel has ${model2.inputs.length} inputs, but the dataset provides ${flattenedXs.length} inputs.  (Expected input keys: ${JSON.stringify(model2.inputNames)})`);\n  util_exports.assert(flattenedYs.length === model2.outputs.length, () => `LayersModel has ${model2.outputs.length} outputs, but the dataset provides ${flattenedYs.length} outputs.  (Expected output keys: ${JSON.stringify(model2.outputNames)})`);\n  for (let xIndex = 0; xIndex < flattenedXs.length; xIndex++) {\n    util_exports.assert(flattenedXs[xIndex].shape[0] === batchSize, () => `Batch size mismatch: input ${model2.inputNames[xIndex]} has ${flattenedXs[xIndex].shape[0]}; expected  ${batchSize} based on input ${model2.inputNames[0]}.`);\n  }\n  for (let yIndex = 0; yIndex < flattenedYs.length; yIndex++) {\n    util_exports.assert(flattenedYs[yIndex].shape[0] === batchSize, () => `Batch size mismatch: output ${model2.outputNames[yIndex]} has ${flattenedYs[yIndex].shape[0]}; expected  ${batchSize} based on input ${model2.inputNames[0]}.`);\n  }\n  return { xs: flattenedXs, ys: flattenedYs };\n}\nfunction flattenTensorOrArrayOrMap(inputOrOutput, names, values) {\n  if (values instanceof Tensor) {\n    return [values];\n  } else if (Array.isArray(values)) {\n    util_exports.assert(values.length === names.length, () => `Received an array of ${values.length} Tensors, but expected ${names.length} to match the ${inputOrOutput} keys ${names}.`);\n    return values;\n  } else {\n    const result = [];\n    for (const name of names) {\n      if (values[name] == null) {\n        throw new ValueError(`The feature data generated by the dataset lacks the required ${inputOrOutput} key '${name}'.`);\n      }\n      result.push(values[name]);\n    }\n    return result;\n  }\n}\nfunction standardizeTensorValidationData(data) {\n  if (data.length === 3) {\n    throw new NotImplementedError(\"Validation with sample weights is not implemented yet.\");\n  }\n  return { xs: data[0], ys: data[1] };\n}\nasync function fitDataset(model2, dataset, args) {\n  const hasBatchesPerEpoch = args.batchesPerEpoch != null;\n  util_exports.assert(model2.optimizer != null, () => \"You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig).\");\n  util_exports.assert(args != null, () => `For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call.`);\n  util_exports.assert(args.epochs != null && args.epochs > 0 && Number.isInteger(args.epochs), () => `For fitDataset(), config.epochs is expected to be a positive integer, but got ${args.epochs}`);\n  util_exports.assert(!hasBatchesPerEpoch || args.batchesPerEpoch > 0 && Number.isInteger(args.batchesPerEpoch), () => `For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${args.batchesPerEpoch}`);\n  util_exports.assert(\n    args[\"validationSplit\"] == null,\n    () => \"`validationSplit` is not supported by `fitDataset()`. Use validationData instead.\"\n  );\n  if (model2.isTraining) {\n    throw new Error(\"Cannot start training because another fit() call is ongoing.\");\n  }\n  model2.isTraining = true;\n  try {\n    const doValidation = args.validationData != null;\n    let valXs;\n    let valYs;\n    if (doValidation) {\n      if (isDatasetObject(args.validationData)) {\n        util_exports.assert(args.validationBatches == null || args.validationBatches > 0 && Number.isInteger(args.validationBatches), () => `For fitDataset() with dataset-based validation, config.validationBatches is expected not to be provided, or to be a positive integer, but got ${args.validationBatches}`);\n      } else {\n        const validationData = standardizeTensorValidationData(args.validationData);\n        valXs = validationData.xs;\n        valYs = validationData.ys;\n      }\n    }\n    const trainFunction = model2.makeTrainFunction();\n    const outLabels = model2.getDedupedMetricsNames();\n    let callbackMetrics;\n    if (doValidation) {\n      callbackMetrics = outLabels.slice().concat(outLabels.map((n2) => \"val_\" + n2));\n    } else {\n      callbackMetrics = outLabels.slice();\n    }\n    const callbacks2 = standardizeCallbacks(args.callbacks, args.yieldEvery);\n    const verbose = args.verbose == null ? 1 : args.verbose;\n    const { callbackList, history } = configureCallbacks(\n      callbacks2,\n      verbose,\n      args.epochs,\n      null,\n      null,\n      getStepsPerEpoch(dataset, args),\n      null,\n      doValidation,\n      callbackMetrics\n    );\n    callbackList.setModel(model2);\n    model2.history = history;\n    await callbackList.onTrainBegin();\n    model2.stopTraining_ = false;\n    let epoch = args.initialEpoch == null ? 0 : args.initialEpoch;\n    let dataIterator = await dataset.iterator();\n    while (epoch < args.epochs) {\n      const epochLogs = {};\n      await callbackList.onEpochBegin(epoch);\n      let stepsDone = 0;\n      let batchIndex = 0;\n      if (!hasBatchesPerEpoch) {\n        dataIterator = await dataset.iterator();\n      }\n      while (hasBatchesPerEpoch ? stepsDone < args.batchesPerEpoch : true) {\n        const iteratorOut = await dataIterator.next();\n        if (hasBatchesPerEpoch && iteratorOut.done) {\n          console.warn(`You provided \\`batchesPerEpoch\\` as ${args.batchesPerEpoch}, but your dataset iterator ran out of data after ${stepsDone} batches; interrupting training. Make sure that your dataset can generate at least \\`batchesPerEpoch * epochs\\` batches (in this case, ${args.batchesPerEpoch * args.epochs} batches). You may need to use the repeat() function when building your dataset.`);\n          break;\n        }\n        if (iteratorOut.value != null) {\n          const { xs, ys } = standardizeDataIteratorOutput(model2, iteratorOut.value);\n          const batchLogs = {};\n          batchLogs[\"batch\"] = batchIndex;\n          batchLogs[\"size\"] = xs[0].shape[0];\n          await callbackList.onBatchBegin(batchIndex, batchLogs);\n          const sampleWeights = [];\n          if (args.classWeight != null) {\n            const standardClassWeights = standardizeClassWeights(args.classWeight, model2.outputNames);\n            for (let i2 = 0; i2 < standardClassWeights.length; ++i2) {\n              sampleWeights.push(await standardizeWeights(ys[i2], null, standardClassWeights[i2]));\n            }\n          }\n          const ins = xs.concat(ys).concat(sampleWeights);\n          const outs = trainFunction(ins);\n          dispose(ins);\n          for (let i2 = 0; i2 < outLabels.length; ++i2) {\n            const label = outLabels[i2];\n            const out = outs[i2];\n            batchLogs[label] = out;\n            keep(out);\n          }\n          await callbackList.onBatchEnd(batchIndex, batchLogs);\n          disposeTensorsInLogs(batchLogs);\n          batchIndex++;\n          stepsDone++;\n        }\n        if (hasBatchesPerEpoch ? stepsDone >= args.batchesPerEpoch : iteratorOut.done) {\n          if (doValidation) {\n            let valOuts;\n            if (isDatasetObject(args.validationData)) {\n              valOuts = toList(await model2.evaluateDataset(args.validationData, { batches: args.validationBatches }));\n            } else {\n              valOuts = toList(model2.evaluate(valXs, valYs, {\n                batchSize: args.validationBatchSize == null ? DEFAULT_VALIDATION_BATCH_SIZE : args.validationBatchSize,\n                verbose: 0\n              }));\n            }\n            for (let i2 = 0; i2 < model2.metricsNames.length; ++i2) {\n              epochLogs[`val_${model2.metricsNames[i2]}`] = valOuts[i2];\n            }\n          }\n          break;\n        }\n        if (model2.stopTraining_) {\n          break;\n        }\n      }\n      await callbackList.onEpochEnd(epoch, epochLogs);\n      epoch++;\n      if (model2.stopTraining_) {\n        break;\n      }\n    }\n    await callbackList.onTrainEnd();\n    await model2.history.syncData();\n    return model2.history;\n  } finally {\n    model2.isTraining = false;\n  }\n}\nfunction getStepsPerEpoch(dataset, args) {\n  let stepsPerEpoch = null;\n  if (args.batchesPerEpoch != null) {\n    stepsPerEpoch = args.batchesPerEpoch;\n  } else if (Number.isFinite(dataset.size)) {\n    stepsPerEpoch = dataset.size;\n  }\n  return stepsPerEpoch;\n}\nfunction isDatasetObject(dataset) {\n  return typeof dataset.iterator === \"function\";\n}\nfunction isLazyIteratorObject(iterator) {\n  return typeof iterator.next === \"function\";\n}\nasync function evaluateDataset(model2, dataset, args) {\n  args = args || {};\n  const hasBatches = args.batches != null;\n  const f = model2.testFunction;\n  let outs = [];\n  if (args.verbose > 0) {\n    throw new NotImplementedError(\"Verbose mode is not implemented yet.\");\n  }\n  util_exports.assert(!hasBatches || args.batches > 0 && Number.isInteger(args.batches), () => `Test loop expects \\`batches\\` to be a positive integer, but received ${JSON.stringify(args.batches)}`);\n  const dataIterator = isLazyIteratorObject(dataset) ? dataset : await dataset.iterator();\n  let numExamples = 0;\n  let batch = 0;\n  while (hasBatches ? batch < args.batches : true) {\n    const iteratorOut = await dataIterator.next();\n    outs = tidy(() => {\n      if (iteratorOut.value) {\n        const { xs, ys } = standardizeDataIteratorOutput(model2, iteratorOut.value);\n        const xsAndYs = xs.concat(ys);\n        const batchOuts = tidy(() => f(xsAndYs));\n        dispose(xsAndYs);\n        if (batch === 0) {\n          for (let i2 = 0; i2 < batchOuts.length; ++i2) {\n            outs.push(scalar(0));\n          }\n        }\n        const batchSize = xsAndYs[0].shape[0];\n        for (let i2 = 0; i2 < batchOuts.length; ++i2) {\n          const batchOut = batchOuts[i2];\n          const oldScalar = outs[i2];\n          outs[i2] = tidy(() => add2(outs[i2], mul(batchSize, batchOut)));\n          if (batch > 0) {\n            dispose(oldScalar);\n          }\n        }\n        dispose(batchOuts);\n        numExamples += batchSize;\n        ++batch;\n      }\n      return outs;\n    });\n    if (iteratorOut.done) {\n      if (hasBatches) {\n        console.warn(`Your dataset iterator ran out of data during evaluateDataset(). Interrupting evalution. Make sure that your dataset can generate at least \\`batches\\` batches (in this case, ${args.batches} batches). You may need to use the repeat() function when building your dataset.`);\n      }\n      break;\n    }\n  }\n  for (let i2 = 0; i2 < outs.length; ++i2) {\n    const oldScalar = outs[i2];\n    outs[i2] = div(outs[i2], numExamples);\n    dispose(oldScalar);\n  }\n  return singletonOrArray(outs);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/training_tensors.js\nfunction checkBatchSize(batchSize) {\n  util_exports.assert(batchSize > 0 && Number.isInteger(batchSize), () => `batchSize is required to be a positive integer, but got ${batchSize}`);\n}\nfunction sliceArrays(arrays, start, stop) {\n  if (arrays == null) {\n    return [null];\n  } else if (Array.isArray(arrays)) {\n    return arrays.map((array2) => sliceAlongFirstAxis(array2, start, stop - start));\n  } else {\n    return sliceAlongFirstAxis(arrays, start, stop - start);\n  }\n}\nfunction sliceArraysByIndices(arrays, indices) {\n  return tidy(() => {\n    if (arrays == null) {\n      return null;\n    } else if (Array.isArray(arrays)) {\n      return arrays.map((array2) => sliceArraysByIndices(array2, indices));\n    } else {\n      return gather2(arrays, indices.dtype === \"int32\" ? indices : cast(indices, \"int32\"));\n    }\n  });\n}\nfunction makeBatches(size, batchSize) {\n  const output = [];\n  let batchStart = 0;\n  let batchEnd = null;\n  while (batchStart < size) {\n    batchEnd = batchStart + batchSize;\n    if (batchEnd >= size) {\n      batchEnd = size;\n    }\n    output.push([batchStart, batchEnd]);\n    batchStart = batchEnd;\n  }\n  return output;\n}\nasync function fitLoop(model2, f, ins, outLabels, batchSize, epochs, verbose, callbacks2, valF, valIns, shuffle2, callbackMetrics, initialEpoch, stepsPerEpoch, validationSteps) {\n  if (batchSize == null) {\n    batchSize = 32;\n  }\n  if (epochs == null) {\n    epochs = 1;\n  }\n  if (shuffle2 == null) {\n    shuffle2 = true;\n  }\n  if (initialEpoch == null) {\n    initialEpoch = 0;\n  }\n  let doValidation = false;\n  if (valF != null && valIns != null) {\n    doValidation = true;\n  }\n  if (validationSteps != null) {\n    doValidation = true;\n    if (stepsPerEpoch == null) {\n      throw new ValueError(\"Can only use `validationSteps` when doing step-wise training, i.e., `stepsPerEpoch` must be set.\");\n    }\n  }\n  const numTrainSamples = model2.checkNumSamples(ins, batchSize, stepsPerEpoch, \"steps_per_epoch\");\n  let indexArray;\n  if (numTrainSamples != null) {\n    indexArray = range2(0, numTrainSamples);\n  }\n  if (verbose == null) {\n    verbose = 1;\n  }\n  const { callbackList, history } = configureCallbacks(callbacks2, verbose, epochs, initialEpoch, numTrainSamples, stepsPerEpoch, batchSize, doValidation, callbackMetrics);\n  callbackList.setModel(model2);\n  model2.history = history;\n  await callbackList.onTrainBegin();\n  model2.stopTraining_ = false;\n  for (let epoch = initialEpoch; epoch < epochs; ++epoch) {\n    await callbackList.onEpochBegin(epoch);\n    const epochLogs = {};\n    if (stepsPerEpoch != null) {\n      throw new NotImplementedError(\"stepsPerEpoch mode is not implemented yet.\");\n    } else {\n      if (shuffle2 === \"batch\") {\n        throw new NotImplementedError(\"batch shuffling is not implemneted yet\");\n      } else if (shuffle2) {\n        util_exports.shuffle(indexArray);\n      }\n      const epochIndexArray1D = tensor1d(indexArray);\n      const batches = makeBatches(numTrainSamples, batchSize);\n      for (let batchIndex = 0; batchIndex < batches.length; ++batchIndex) {\n        const batchLogs = {};\n        await callbackList.onBatchBegin(batchIndex, batchLogs);\n        tidy(() => {\n          const batchStart = batches[batchIndex][0];\n          const batchEnd = batches[batchIndex][1];\n          const batchIds = sliceAlongFirstAxis(epochIndexArray1D, batchStart, batchEnd - batchStart);\n          batchLogs[\"batch\"] = batchIndex;\n          batchLogs[\"size\"] = batchEnd - batchStart;\n          const insBatch = sliceArraysByIndices(ins, batchIds);\n          const outs = f(insBatch);\n          for (let i2 = 0; i2 < outLabels.length; ++i2) {\n            const label = outLabels[i2];\n            const out = outs[i2];\n            batchLogs[label] = out;\n            keep(out);\n          }\n          if (batchIndex === batches.length - 1) {\n            if (doValidation) {\n              const valOuts = model2.testLoop(valF, valIns, batchSize);\n              for (let i2 = 0; i2 < outLabels.length; ++i2) {\n                const label = outLabels[i2];\n                const out = valOuts[i2];\n                keep(out);\n                epochLogs[\"val_\" + label] = out;\n              }\n            }\n          }\n        });\n        await callbackList.onBatchEnd(batchIndex, batchLogs);\n        disposeTensorsInLogs(batchLogs);\n        if (model2.stopTraining_) {\n          break;\n        }\n      }\n      epochIndexArray1D.dispose();\n    }\n    await callbackList.onEpochEnd(epoch, epochLogs);\n    if (model2.stopTraining_) {\n      break;\n    }\n  }\n  await callbackList.onTrainEnd();\n  await model2.history.syncData();\n  return model2.history;\n}\nasync function fitTensors(model2, x, y, args = {}) {\n  if (model2.isTraining) {\n    throw new Error(\"Cannot start training because another fit() call is ongoing.\");\n  }\n  model2.isTraining = true;\n  let inputs;\n  let targets;\n  let originalInputs;\n  let originalTargets;\n  let inputValX;\n  let inputValY;\n  let valX;\n  let valY;\n  let sampleWeights;\n  try {\n    const batchSize = args.batchSize == null ? 32 : args.batchSize;\n    checkBatchSize(batchSize);\n    const checkBatchAxis = false;\n    const standardizedOuts = await model2.standardizeUserData(x, y, args.sampleWeight, args.classWeight, checkBatchAxis, batchSize);\n    inputs = standardizedOuts[0];\n    targets = standardizedOuts[1];\n    sampleWeights = standardizedOuts[2];\n    let doValidation = false;\n    let valIns;\n    if (args.validationData != null && args.validationData.length > 0) {\n      doValidation = true;\n      if (args.validationData.length === 2) {\n        inputValX = args.validationData[0];\n        inputValY = args.validationData[1];\n      } else if (args.validationData.length === 3) {\n        throw new NotImplementedError(\"validationData including sample weights is not supported yet.\");\n      } else {\n        throw new ValueError(`When passing validation data, it must contain 2 (valX, valY) or 3 (valX, valY, valSampleWeight) items; ${args.validationData} is invalid.`);\n      }\n      const checkBatchAxis2 = true;\n      const valStandardized = await model2.standardizeUserData(inputValX, inputValY, null, null, checkBatchAxis2, batchSize);\n      valX = valStandardized[0];\n      valY = valStandardized[1];\n      valIns = valX.concat(valY);\n    } else if (args.validationSplit != null && args.validationSplit > 0 && args.validationSplit < 1) {\n      doValidation = true;\n      const splitAt = Math.floor(inputs[0].shape[0] * (1 - args.validationSplit));\n      const originalBatchSize = inputs[0].shape[0];\n      valX = sliceArrays(inputs, splitAt, originalBatchSize);\n      originalInputs = inputs;\n      inputs = sliceArrays(inputs, 0, splitAt);\n      valY = sliceArrays(targets, splitAt, originalBatchSize);\n      originalTargets = targets;\n      targets = sliceArrays(targets, 0, splitAt);\n      valIns = valX.concat(valY);\n    } else if (args.validationSteps != null) {\n      doValidation = true;\n    }\n    const ins = inputs.concat(targets).concat(sampleWeights);\n    model2.checkTrainableWeightsConsistency();\n    const trainFunction = model2.makeTrainFunction();\n    const outLabels = model2.getDedupedMetricsNames();\n    let valFunction;\n    let callbackMetrics;\n    if (doValidation) {\n      model2.makeTestFunction();\n      valFunction = model2.testFunction;\n      callbackMetrics = outLabels.slice().concat(outLabels.map((n2) => \"val_\" + n2));\n    } else {\n      valFunction = null;\n      valIns = [];\n      callbackMetrics = outLabels.slice();\n    }\n    const callbacks2 = standardizeCallbacks(args.callbacks, args.yieldEvery);\n    const out = await fitLoop(model2, trainFunction, ins, outLabels, batchSize, args.epochs, args.verbose, callbacks2, valFunction, valIns, args.shuffle, callbackMetrics, args.initialEpoch, null, null);\n    return out;\n  } finally {\n    model2.isTraining = false;\n    disposeNewTensors(inputs, x);\n    disposeNewTensors(targets, y);\n    disposeNewTensors(originalInputs, x);\n    disposeNewTensors(originalTargets, y);\n    disposeNewTensors(valX, inputValX);\n    disposeNewTensors(valY, inputValY);\n    if (sampleWeights != null) {\n      dispose(sampleWeights);\n    }\n  }\n}\nfunction ensureTensorsRank2OrHigher(tensors) {\n  const outs = [];\n  if (tensors instanceof Tensor) {\n    tensors = [tensors];\n  }\n  for (let i2 = 0; i2 < tensors.length; ++i2) {\n    const tensor2 = tensors[i2];\n    if (tensor2.rank === 1) {\n      outs.push(expandDims2(tensor2, 1));\n    } else if (tensor2.rank === 0) {\n      throw new Error(\"Expected tensor to be at least 1D, but received a 0D tensor (scalar).\");\n    } else {\n      outs.push(tensor2);\n    }\n  }\n  return outs;\n}\nfunction disposeNewTensors(tensors, refTensors) {\n  if (tensors == null) {\n    return;\n  }\n  const oldTensorIds = [];\n  if (refTensors instanceof Tensor) {\n    oldTensorIds.push(refTensors.id);\n  } else if (Array.isArray(refTensors)) {\n    refTensors.forEach((t2) => oldTensorIds.push(t2.id));\n  } else if (refTensors != null) {\n    for (const name in refTensors) {\n      const oldTensor = refTensors[name];\n      oldTensorIds.push(oldTensor.id);\n    }\n  }\n  const tensorsToDispose = [];\n  if (tensors instanceof Tensor) {\n    if (oldTensorIds.indexOf(tensors.id) === -1) {\n      tensorsToDispose.push(tensors);\n    }\n  } else if (Array.isArray(tensors)) {\n    tensors.forEach((t2) => {\n      if (oldTensorIds.indexOf(t2.id) === -1) {\n        tensorsToDispose.push(t2);\n      }\n    });\n  } else if (tensors != null) {\n    for (const name in tensors) {\n      const tensor2 = tensors[name];\n      if (oldTensorIds.indexOf(tensor2.id) === -1) {\n        tensorsToDispose.push(tensor2);\n      }\n    }\n  }\n  tensorsToDispose.forEach((t2) => {\n    if (!t2.isDisposed) {\n      t2.dispose();\n    }\n  });\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/engine/training.js\nfunction isDataTensor(x) {\n  return x instanceof Tensor;\n}\nfunction isDataArray(x) {\n  return Array.isArray(x);\n}\nfunction isDataDict(x) {\n  return !isDataTensor(x) && !isDataArray(x);\n}\nfunction standardizeInputData(data, names, shapes, checkBatchAxis = true, exceptionPrefix = \"\") {\n  if (names == null || names.length === 0) {\n    if (data != null) {\n      let gotUnexpectedData = false;\n      if (isDataArray(data) && data.length > 0) {\n        gotUnexpectedData = true;\n      } else if (isDataDict(data)) {\n        for (const key in data) {\n          if (data.hasOwnProperty(key)) {\n            gotUnexpectedData = true;\n            break;\n          }\n        }\n      } else {\n        gotUnexpectedData = true;\n      }\n      if (gotUnexpectedData) {\n        throw new ValueError(`Error when checking model ${exceptionPrefix} expected no data, but got ${data}`);\n      }\n    }\n    return [];\n  }\n  if (data == null) {\n    return names.map((name) => null);\n  }\n  let arrays;\n  if (isDataDict(data)) {\n    data = data;\n    arrays = [];\n    for (const name of names) {\n      if (data[name] == null) {\n        throw new ValueError(`No data provided for \"${name}\". Need data for each key in: ${names}`);\n      }\n      arrays.push(data[name]);\n    }\n  } else if (isDataArray(data)) {\n    data = data;\n    if (data.length !== names.length) {\n      throw new ValueError(`Error when checking model ${exceptionPrefix}: the Array of Tensors that you are passing to your model is not the size the model expected. Expected to see ${names.length} Tensor(s), but instead got the following list of Tensor(s): ${data}`);\n    }\n    arrays = data;\n  } else {\n    data = data;\n    if (names.length > 1) {\n      throw new ValueError(`The model ${exceptionPrefix} expects ${names.length} Tensor(s), but only received one Tensor. Found: Tensor with shape ${data.shape}`);\n    }\n    arrays = [data];\n  }\n  arrays = ensureTensorsRank2OrHigher(arrays);\n  if (shapes != null) {\n    for (let i2 = 0; i2 < names.length; ++i2) {\n      if (shapes[i2] == null) {\n        continue;\n      }\n      const array2 = arrays[i2];\n      if (array2.shape.length !== shapes[i2].length) {\n        throw new ValueError(`Error when checking ${exceptionPrefix}: expected ${names[i2]} to have ${shapes[i2].length} dimension(s). but got array with shape ${array2.shape}`);\n      }\n      for (let j = 0; j < shapes[i2].length; ++j) {\n        if (j === 0 && !checkBatchAxis) {\n          continue;\n        }\n        const dim = array2.shape[j];\n        const refDim = shapes[i2][j];\n        if (refDim != null && refDim >= 0 && dim !== refDim) {\n          throw new ValueError(`${exceptionPrefix} expected a batch of elements where each example has shape [${shapes[i2].slice(1, shapes[i2].length)}] (i.e.,tensor shape [*,${shapes[i2].slice(1, shapes[i2].length)}]) but the ${exceptionPrefix} received an input with ${array2.shape[0]} examples, each with shape [${array2.shape.slice(1, array2.shape.length)}] (tensor shape [${array2.shape}])`);\n        }\n      }\n    }\n  }\n  return arrays;\n}\nfunction checkArrayLengths(inputs, targets, weights) {\n  const setX = unique2(inputs.map((input2) => input2.shape[0]));\n  setX.sort();\n  const setY = unique2(targets.map((target) => target.shape[0]));\n  setY.sort();\n  if (setX.length > 1) {\n    throw new ValueError(`All input Tensors (x) should have the same number of samples. Got array shapes: ${JSON.stringify(inputs.map((input2) => input2.shape))}`);\n  }\n  if (setY.length > 1) {\n    throw new ValueError(`All target Tensors (y) should have the same number of samples. Got array shapes: ${JSON.stringify(targets.map((target) => target.shape))}`);\n  }\n  if (setX.length > 0 && setY.length > 0 && !util_exports.arraysEqual(setX, setY)) {\n    throw new ValueError(`Input Tensors should have the same number of samples as target Tensors. Found ${setX[0]} input sample(s) and ${setY[0]} target sample(s).`);\n  }\n}\nfunction checkLossAndTargetCompatibility(targets, lossFns, outputShapes) {\n  const keyLosses = [\n    meanSquaredError2,\n    binaryCrossentropy,\n    categoricalCrossentropy\n  ];\n  for (let i2 = 0; i2 < targets.length; ++i2) {\n    const y = targets[i2];\n    const loss = lossFns[i2];\n    const shape = outputShapes[i2];\n    if (loss == null) {\n      continue;\n    }\n    if (loss === categoricalCrossentropy) {\n      if (y.shape[y.shape.length - 1] === 1) {\n        throw new ValueError(`You are passing a target array of shape ${y.shape} while using a loss 'categorical_crossentropy'. 'categorical_crossentropy'expects targets to be binary matrices (1s and 0s) of shape [samples, classes].`);\n      }\n    }\n    if (keyLosses.indexOf(loss) !== -1) {\n      const slicedYShape = y.shape.slice(1);\n      const slicedShape = shape.slice(1);\n      for (let j = 0; j < slicedYShape.length; ++j) {\n        const targetDim = slicedYShape[j];\n        const outDim = slicedShape[j];\n        if (outDim != null && targetDim !== outDim) {\n          throw new ValueError(`A target Tensor with shape ${y.shape} was passed for an output of shape ${shape}, while using a loss function that expects targets to have the same shape as the output.`);\n        }\n      }\n    }\n  }\n}\nfunction checkInputData(data, names, shapes, checkBatchAxis = true, exceptionPrefix = \"\") {\n  let arrays;\n  if (Array.isArray(data)) {\n    if (data.length !== names.length) {\n      throw new ValueError(`Error when checking model ${exceptionPrefix}: the Array of Tensors that you are passing to your model is not the size the the model expected. Expected to see ${names.length} Tensor(s), but instead got ${data.length} Tensors(s).`);\n    }\n    arrays = data;\n  } else {\n    if (names.length > 1) {\n      throw new ValueError(`The model expects ${names.length} ${exceptionPrefix} Tensors, but only received one Tensor. Found: array with shape ${JSON.stringify(data.shape)}.`);\n    }\n    arrays = [data];\n  }\n  if (shapes != null) {\n    for (let i2 = 0; i2 < names.length; ++i2) {\n      if (shapes[i2] == null) {\n        continue;\n      }\n      const array2 = arrays[i2];\n      if (array2.shape.length !== shapes[i2].length) {\n        throw new ValueError(`Error when checking ${exceptionPrefix}: expected ${names[i2]} to have ${shapes[i2].length} dimension(s), but got array with shape ${JSON.stringify(array2.shape)}`);\n      }\n      for (let j = 0; j < shapes[i2].length; ++j) {\n        if (j === 0 && !checkBatchAxis) {\n          continue;\n        }\n        const dim = array2.shape[j];\n        const refDim = shapes[i2][j];\n        if (refDim != null) {\n          if (refDim !== dim) {\n            throw new ValueError(`Error when checking ${exceptionPrefix}: expected ${names[i2]} to have shape ${JSON.stringify(shapes[i2])} but got array with shape ${JSON.stringify(array2.shape)}.`);\n          }\n        }\n      }\n    }\n  }\n}\nfunction collectMetrics(metrics, outputNames) {\n  if (metrics == null || Array.isArray(metrics) && metrics.length === 0) {\n    return outputNames.map((name) => []);\n  }\n  let wrappedMetrics;\n  if (typeof metrics === \"string\" || typeof metrics === \"function\") {\n    wrappedMetrics = [metrics];\n  } else if (Array.isArray(metrics) || typeof metrics === \"object\") {\n    wrappedMetrics = metrics;\n  } else {\n    throw new TypeError(`Type of metrics argument not understood. Expected an string,function, Array, or Object, found: ${metrics}`);\n  }\n  if (Array.isArray(wrappedMetrics)) {\n    return outputNames.map((name) => wrappedMetrics);\n  } else {\n    const nestedMetrics = [];\n    for (const name of outputNames) {\n      let outputMetrics = wrappedMetrics.hasOwnProperty(name) ? wrappedMetrics[name] : [];\n      if (!Array.isArray(outputMetrics)) {\n        outputMetrics = [outputMetrics];\n      }\n      nestedMetrics.push(outputMetrics);\n    }\n    return nestedMetrics;\n  }\n}\nvar LAYERS_MODEL_FORMAT_NAME = \"layers-model\";\nvar LayersModel = class extends Container {\n  constructor(args) {\n    super(args);\n    this.isTraining = false;\n  }\n  summary(lineLength, positions, printFn = console.log) {\n    if (!this.built) {\n      throw new ValueError(`This model has never been called, thus its weights have not been created yet. So no summary can be displayed. Build the model first (e.g., by calling it on some test data).`);\n    }\n    printSummary(this, lineLength, positions, printFn);\n  }\n  compile(args) {\n    if (args.loss == null) {\n      args.loss = [];\n    }\n    this.loss = args.loss;\n    if (typeof args.optimizer === \"string\") {\n      this.optimizer_ = getOptimizer(args.optimizer);\n      this.isOptimizerOwned = true;\n    } else {\n      if (!(args.optimizer instanceof Optimizer)) {\n        throw new ValueError(`User-defined optimizer must be an instance of tf.Optimizer.`);\n      }\n      this.optimizer_ = args.optimizer;\n      this.isOptimizerOwned = false;\n    }\n    let lossFunctions = [];\n    if (!Array.isArray(args.loss) && typeof args.loss !== \"string\" && typeof args.loss !== \"function\") {\n      args.loss = args.loss;\n      for (const name in args.loss) {\n        if (this.outputNames.indexOf(name) === -1) {\n          throw new ValueError(`Unknown entry in loss dictionary: \"${name}\". Only expected the following keys: ${this.outputNames}`);\n        }\n      }\n      for (const name of this.outputNames) {\n        if (args.loss[name] == null) {\n          console.warn(`Output \"${name}\" is missing from loss dictionary. We assume this was done on purpose, and we will not be expecting data to be passed to ${name} during training`);\n        }\n        lossFunctions.push(get(args.loss[name]));\n      }\n    } else if (Array.isArray(args.loss)) {\n      if (args.loss.length !== this.outputs.length) {\n        throw new ValueError(`When passing an Array as loss, it should have one entry per model output. The model has ${this.outputs.length} output(s), but you passed loss=${args.loss}.`);\n      }\n      const theLosses = args.loss;\n      lossFunctions = theLosses.map((l3) => get(l3));\n    } else {\n      const lossFunction = get(args.loss);\n      this.outputs.forEach((_) => {\n        lossFunctions.push(lossFunction);\n      });\n    }\n    this.lossFunctions = lossFunctions;\n    this.feedOutputNames = [];\n    this.feedOutputShapes = [];\n    this.feedLossFns = [];\n    for (let i2 = 0; i2 < this.outputs.length; ++i2) {\n      const shape = this.internalOutputShapes[i2];\n      const name = this.outputNames[i2];\n      this.feedOutputNames.push(name);\n      this.feedOutputShapes.push(shape);\n      this.feedLossFns.push(this.lossFunctions[i2]);\n    }\n    const skipTargetIndices = [];\n    this.metrics = args.metrics;\n    this.metricsNames = [\"loss\"];\n    this.metricsTensors = [];\n    nameScope(\"loss\", () => {\n      for (let i2 = 0; i2 < this.outputs.length; ++i2) {\n        if (skipTargetIndices.indexOf(i2) !== -1) {\n          continue;\n        }\n        const weightedLoss = this.lossFunctions[i2];\n        if (this.outputs.length > 1) {\n          this.metricsTensors.push([weightedLoss, i2]);\n          this.metricsNames.push(this.outputNames[i2] + \"_loss\");\n        }\n      }\n    });\n    const nestedMetrics = collectMetrics(args.metrics, this.outputNames);\n    const appendMetric = (outputIndex, metricName, metricTensor) => {\n      if (this.outputNames.length > 1) {\n        metricName = this.outputNames[outputIndex] + \"_\" + metricName;\n      }\n      this.metricsNames.push(metricName);\n      this.metricsTensors.push([metricTensor, outputIndex]);\n    };\n    nameScope(\"metric\", () => {\n      for (let i2 = 0; i2 < this.outputs.length; ++i2) {\n        if (skipTargetIndices.indexOf(i2) !== -1) {\n          continue;\n        }\n        const outputMetrics = nestedMetrics[i2];\n        const handleMetrics = (metrics) => {\n          const metricNamePrefix = \"\";\n          let metricName;\n          let accFn;\n          let weightedMetricFn;\n          for (const metric of metrics) {\n            if (typeof metric === \"string\" && [\"accuracy\", \"acc\", \"crossentropy\", \"ce\"].indexOf(metric) !== -1) {\n              const outputShape = this.internalOutputShapes[i2];\n              if (outputShape[outputShape.length - 1] === 1 || this.lossFunctions[i2] === binaryCrossentropy) {\n                if ([\"accuracy\", \"acc\"].indexOf(metric) !== -1) {\n                  accFn = binaryAccuracy;\n                } else if ([\"crossentropy\", \"ce\"].indexOf(metric) !== -1) {\n                  accFn = binaryCrossentropy2;\n                }\n              } else if (this.lossFunctions[i2] === sparseCategoricalCrossentropy) {\n                if ([\"accuracy\", \"acc\"].indexOf(metric) !== -1) {\n                  accFn = sparseCategoricalAccuracy;\n                } else if ([\"crossentropy\", \"ce\"].indexOf(metric) !== -1) {\n                  accFn = sparseCategoricalCrossentropy2;\n                }\n              } else {\n                if ([\"accuracy\", \"acc\"].indexOf(metric) !== -1) {\n                  accFn = categoricalAccuracy;\n                } else if ([\"crossentropy\", \"ce\"].indexOf(metric) !== -1) {\n                  accFn = categoricalCrossentropy2;\n                }\n              }\n              let suffix;\n              if ([\"accuracy\", \"acc\"].indexOf(metric) !== -1) {\n                suffix = \"acc\";\n              } else if ([\"crossentropy\", \"ce\"].indexOf(metric) !== -1) {\n                suffix = \"ce\";\n              }\n              weightedMetricFn = accFn;\n              metricName = metricNamePrefix + suffix;\n            } else {\n              const metricFn = get2(metric);\n              weightedMetricFn = metricFn;\n              metricName = metricNamePrefix + getLossOrMetricName(metric);\n            }\n            let metricResult;\n            nameScope(metricName, () => {\n              metricResult = weightedMetricFn;\n            });\n            appendMetric(i2, metricName, metricResult);\n          }\n        };\n        handleMetrics(outputMetrics);\n      }\n    });\n    this.collectedTrainableWeights = this.trainableWeights;\n  }\n  checkTrainableWeightsConsistency() {\n    if (this.collectedTrainableWeights == null) {\n      return;\n    }\n    if (this.trainableWeights.length !== this.collectedTrainableWeights.length) {\n      console.warn(\"Discrepancy between trainableweights and collected trainable weights. Did you set `model.trainable` without calling `model.compile()` afterwards?\");\n    }\n  }\n  evaluate(x, y, args = {}) {\n    const batchSize = args.batchSize == null ? 32 : args.batchSize;\n    checkBatchSize(batchSize);\n    const checkBatchAxis = true;\n    const standardizedOuts = this.standardizeUserDataXY(x, y, checkBatchAxis, batchSize);\n    try {\n      const ins = standardizedOuts[0].concat(standardizedOuts[1]);\n      this.makeTestFunction();\n      const f = this.testFunction;\n      const testOuts = this.testLoop(f, ins, batchSize, args.verbose, args.steps);\n      return singletonOrArray(testOuts);\n    } finally {\n      disposeNewTensors(standardizedOuts[0], x);\n      disposeNewTensors(standardizedOuts[1], y);\n    }\n  }\n  async evaluateDataset(dataset, args) {\n    this.makeTestFunction();\n    return evaluateDataset(this, dataset, args);\n  }\n  checkNumSamples(ins, batchSize, steps, stepsName = \"steps\") {\n    let numSamples;\n    if (steps != null) {\n      numSamples = null;\n      if (batchSize != null) {\n        throw new ValueError(`If ${stepsName} is set, batchSize must be null or undefined.Got batchSize = ${batchSize}`);\n      }\n    } else if (ins != null) {\n      if (Array.isArray(ins)) {\n        numSamples = ins[0].shape[0];\n      } else {\n        numSamples = ins.shape[0];\n      }\n    } else {\n      throw new ValueError(`Either the input data should have a defined shape, or ${stepsName} shoud be specified.`);\n    }\n    return numSamples;\n  }\n  execute(inputs, outputs) {\n    if (Array.isArray(outputs) && outputs.length === 0) {\n      throw new ValueError(\"`outputs` is an empty Array, which is not allowed.\");\n    }\n    const outputsIsArray = Array.isArray(outputs);\n    const outputNames = outputsIsArray ? outputs : [outputs];\n    const outputSymbolicTensors = this.retrieveSymbolicTensors(outputNames);\n    const feedDict = new FeedDict();\n    if (inputs instanceof Tensor) {\n      inputs = [inputs];\n    }\n    if (Array.isArray(inputs)) {\n      if (inputs.length !== this.inputs.length) {\n        throw new ValueError(`The number of inputs provided (${inputs.length}) does not match the number of inputs of this model (${this.inputs.length}).`);\n      }\n      for (let i2 = 0; i2 < this.inputs.length; ++i2) {\n        feedDict.add(this.inputs[i2], inputs[i2]);\n      }\n    } else {\n      for (const input2 of this.inputs) {\n        const tensorValue = inputs[input2.name];\n        if (tensorValue == null) {\n          throw new ValueError(`No value is provided for the model's input ${input2.name}`);\n        }\n        feedDict.add(input2, tensorValue);\n      }\n    }\n    const executeOutputs = execute(outputSymbolicTensors, feedDict);\n    return outputsIsArray ? executeOutputs : executeOutputs[0];\n  }\n  retrieveSymbolicTensors(symbolicTensorNames) {\n    const outputSymbolicTensors = pyListRepeat(null, symbolicTensorNames.length);\n    let outputsRemaining = symbolicTensorNames.length;\n    for (const layer of this.layers) {\n      const layerOutputs = Array.isArray(layer.output) ? layer.output : [layer.output];\n      const layerOutputNames = layerOutputs.map((output) => output.name);\n      for (let i2 = 0; i2 < symbolicTensorNames.length; ++i2) {\n        const index = layerOutputNames.indexOf(symbolicTensorNames[i2]);\n        if (index !== -1) {\n          outputSymbolicTensors[i2] = layerOutputs[index];\n          outputsRemaining--;\n        }\n        if (outputsRemaining === 0) {\n          break;\n        }\n      }\n      if (outputsRemaining === 0) {\n        break;\n      }\n    }\n    if (outputsRemaining > 0) {\n      const remainingNames = [];\n      outputSymbolicTensors.forEach((tensor2, i2) => {\n        if (tensor2 == null) {\n          remainingNames.push(symbolicTensorNames[i2]);\n        }\n      });\n      throw new ValueError(`Cannot find SymbolicTensors for output name(s): ${JSON.stringify(remainingNames)}`);\n    }\n    return outputSymbolicTensors;\n  }\n  predictLoop(ins, batchSize = 32, verbose = false) {\n    return tidy(() => {\n      const numSamples = this.checkNumSamples(ins);\n      if (verbose) {\n        throw new NotImplementedError(\"Verbose predictLoop() is not implemented yet.\");\n      }\n      const batches = makeBatches(numSamples, batchSize);\n      const outsBatches = this.outputs.map((output) => []);\n      for (let batchIndex = 0; batchIndex < batches.length; ++batchIndex) {\n        const batchOuts = tidy(() => {\n          const batchStart = batches[batchIndex][0];\n          const batchEnd = batches[batchIndex][1];\n          const insBatch = sliceArrays(ins, batchStart, batchEnd);\n          const feeds = [];\n          if (Array.isArray(insBatch)) {\n            for (let i2 = 0; i2 < insBatch.length; ++i2) {\n              feeds.push({ key: this.inputs[i2], value: insBatch[i2] });\n            }\n          } else {\n            feeds.push({ key: this.inputs[0], value: insBatch });\n          }\n          const feedDict = new FeedDict(feeds);\n          return execute(this.outputs, feedDict);\n        });\n        batchOuts.forEach((batchOut, i2) => outsBatches[i2].push(batchOut));\n      }\n      return singletonOrArray(outsBatches.map((batches2) => concat(batches2, 0)));\n    });\n  }\n  predict(x, args = {}) {\n    const xsRank2OrHigher = ensureTensorsRank2OrHigher(x);\n    checkInputData(xsRank2OrHigher, this.inputNames, this.feedInputShapes, false);\n    try {\n      const batchSize = args.batchSize == null ? 32 : args.batchSize;\n      checkBatchSize(batchSize);\n      return this.predictLoop(xsRank2OrHigher, batchSize);\n    } finally {\n      disposeNewTensors(xsRank2OrHigher, x);\n    }\n  }\n  predictOnBatch(x) {\n    checkInputData(x, this.inputNames, this.feedInputShapes, true);\n    const batchSize = (Array.isArray(x) ? x[0] : x).shape[0];\n    return this.predictLoop(x, batchSize);\n  }\n  standardizeUserDataXY(x, y, checkBatchAxis = true, batchSize) {\n    if (this.optimizer_ == null) {\n      throw new RuntimeError(\"You must compile a model before training/testing. Use LayersModel.compile(modelCompileArgs).\");\n    }\n    const outputShapes = [];\n    for (let i2 = 0; i2 < this.feedOutputShapes.length; ++i2) {\n      const outputShape = this.feedOutputShapes[i2];\n      const lossFn = this.feedLossFns[i2];\n      if (lossFn === sparseCategoricalCrossentropy) {\n        outputShapes.push(outputShape.slice(0, outputShape.length - 1).concat([1]));\n      } else {\n        outputShapes.push(outputShape);\n      }\n    }\n    x = standardizeInputData(x, this.feedInputNames, this.feedInputShapes, false, \"input\");\n    y = standardizeInputData(y, this.feedOutputNames, outputShapes, false, \"target\");\n    checkArrayLengths(x, y, null);\n    checkLossAndTargetCompatibility(y, this.feedLossFns, this.feedOutputShapes);\n    if (this.stateful && batchSize != null && batchSize > 0) {\n      if (x[0].shape[0] % batchSize !== 0) {\n        throw new ValueError(`In a stateful network, you should only pass inputs with a number of samples that is divisible by the batch size ${batchSize}. Found: ${x[0].shape[0]} sample(s).`);\n      }\n    }\n    return [x, y];\n  }\n  async standardizeUserData(x, y, sampleWeight, classWeight, checkBatchAxis = true, batchSize) {\n    const [standardXs, standardYs] = this.standardizeUserDataXY(x, y, checkBatchAxis, batchSize);\n    if (sampleWeight != null) {\n      throw new Error(\"sample weight is not supported yet.\");\n    }\n    let standardSampleWeights = null;\n    if (classWeight != null) {\n      const classWeights = standardizeClassWeights(classWeight, this.outputNames);\n      standardSampleWeights = [];\n      for (let i2 = 0; i2 < classWeights.length; ++i2) {\n        standardSampleWeights.push(await standardizeWeights(standardYs[i2], null, classWeights[i2]));\n      }\n    }\n    return [standardXs, standardYs, standardSampleWeights];\n  }\n  testLoop(f, ins, batchSize, verbose = 0, steps) {\n    return tidy(() => {\n      const numSamples = this.checkNumSamples(ins, batchSize, steps, \"steps\");\n      const outs = [];\n      if (verbose > 0) {\n        throw new NotImplementedError(\"Verbose mode is not implemented yet.\");\n      }\n      if (steps != null) {\n        throw new NotImplementedError(\"steps mode in testLoop() is not implemented yet\");\n      } else {\n        const batches = makeBatches(numSamples, batchSize);\n        const indexArray = tensor1d(range2(0, numSamples));\n        for (let batchIndex = 0; batchIndex < batches.length; ++batchIndex) {\n          const batchStart = batches[batchIndex][0];\n          const batchEnd = batches[batchIndex][1];\n          const batchIds = sliceAlongFirstAxis(indexArray, batchStart, batchEnd - batchStart);\n          const insBatch = sliceArraysByIndices(ins, batchIds);\n          const batchOuts = f(insBatch);\n          if (batchIndex === 0) {\n            for (let i2 = 0; i2 < batchOuts.length; ++i2) {\n              outs.push(scalar(0));\n            }\n          }\n          for (let i2 = 0; i2 < batchOuts.length; ++i2) {\n            const batchOut = batchOuts[i2];\n            outs[i2] = add2(outs[i2], mul(batchEnd - batchStart, batchOut));\n          }\n        }\n        for (let i2 = 0; i2 < outs.length; ++i2) {\n          outs[i2] = div(outs[i2], numSamples);\n        }\n      }\n      return outs;\n    });\n  }\n  getDedupedMetricsNames() {\n    const outLabels = this.metricsNames;\n    const dedupedOutLabels = [];\n    for (let i2 = 0; i2 < outLabels.length; ++i2) {\n      const label = outLabels[i2];\n      let newLabel = label;\n      if (count(outLabels, label) > 1) {\n        const dupIndex = count(outLabels.slice(0, i2), label);\n        newLabel += `_${dupIndex}`;\n      }\n      dedupedOutLabels.push(newLabel);\n    }\n    return dedupedOutLabels;\n  }\n  makeTrainFunction() {\n    return (data) => {\n      const lossValues = [];\n      const inputs = data.slice(0, this.inputs.length);\n      const targets = data.slice(this.inputs.length, this.inputs.length + this.outputs.length);\n      const sampleWeights = data.slice(this.inputs.length + this.outputs.length, this.inputs.length + this.outputs.length * 2);\n      const metricsValues = [];\n      const totalLossFunction = () => {\n        const feeds = [];\n        for (let i2 = 0; i2 < this.inputs.length; ++i2) {\n          feeds.push({ key: this.inputs[i2], value: inputs[i2] });\n        }\n        const feedDict = new FeedDict(feeds);\n        const outputs = execute(this.outputs, feedDict, { \"training\": true });\n        let totalLoss;\n        for (let i2 = 0; i2 < this.lossFunctions.length; ++i2) {\n          const lossFunction = this.lossFunctions[i2];\n          let loss = lossFunction(targets[i2], outputs[i2]);\n          if (sampleWeights[i2] != null) {\n            loss = computeWeightedLoss2(loss, sampleWeights[i2]);\n          }\n          const meanLoss = mean(loss);\n          lossValues.push(meanLoss);\n          if (i2 === 0) {\n            totalLoss = loss;\n          } else {\n            totalLoss = add2(totalLoss, loss);\n          }\n        }\n        for (let i2 = 0; i2 < this.metricsTensors.length; ++i2) {\n          let weightedMetric;\n          if (this.outputs.length > 1 && i2 < this.outputs.length) {\n            weightedMetric = lossValues[i2];\n          } else {\n            const metric = this.metricsTensors[i2][0];\n            const outputIndex = this.metricsTensors[i2][1];\n            weightedMetric = mean(metric(targets[outputIndex], outputs[outputIndex]));\n          }\n          keep(weightedMetric);\n          metricsValues.push(weightedMetric);\n        }\n        totalLoss = mean(totalLoss);\n        this.calculateLosses().forEach((regularizerLoss) => {\n          totalLoss = add2(totalLoss, regularizerLoss);\n        });\n        return totalLoss;\n      };\n      const variables = this.collectedTrainableWeights.map((param) => param.read());\n      const returnCost = true;\n      const totalLossValue = this.optimizer_.minimize(totalLossFunction, returnCost, variables);\n      return [totalLossValue].concat(metricsValues);\n    };\n  }\n  makeTestFunction() {\n    this.testFunction = (data) => {\n      return tidy(() => {\n        const valOutputs = [];\n        let totalLoss;\n        const inputs = data.slice(0, this.inputs.length);\n        const targets = data.slice(this.inputs.length, this.inputs.length + this.outputs.length);\n        const feeds = [];\n        for (let i2 = 0; i2 < this.inputs.length; ++i2) {\n          feeds.push({ key: this.inputs[i2], value: inputs[i2] });\n        }\n        const feedDict = new FeedDict(feeds);\n        const outputs = execute(this.outputs, feedDict);\n        for (let i2 = 0; i2 < this.lossFunctions.length; ++i2) {\n          const lossFunction = this.lossFunctions[i2];\n          const loss = mean(lossFunction(targets[i2], outputs[i2]));\n          if (i2 === 0) {\n            totalLoss = loss;\n          } else {\n            totalLoss = add2(totalLoss, loss);\n          }\n          valOutputs.push(totalLoss);\n        }\n        for (let i2 = 0; i2 < this.metricsTensors.length; ++i2) {\n          const metric = this.metricsTensors[i2][0];\n          const outputIndex = this.metricsTensors[i2][1];\n          const meanMetric = mean(metric(targets[outputIndex], outputs[outputIndex]));\n          valOutputs.push(meanMetric);\n        }\n        return valOutputs;\n      });\n    };\n  }\n  async fit(x, y, args = {}) {\n    return fitTensors(this, x, y, args);\n  }\n  async fitDataset(dataset, args) {\n    return fitDataset(this, dataset, args);\n  }\n  async trainOnBatch(x, y) {\n    const standardizeOut = await this.standardizeUserData(x, y);\n    const inputs = standardizeOut[0];\n    const targets = standardizeOut[1];\n    const trainFunction = this.makeTrainFunction();\n    const losses2 = trainFunction(inputs.concat(targets));\n    const lossValues = [];\n    for (const loss of losses2) {\n      const v = await loss.data();\n      lossValues.push(v[0]);\n    }\n    dispose(losses2);\n    disposeNewTensors(standardizeOut[0], x);\n    disposeNewTensors(standardizeOut[1], y);\n    return singletonOrArray(lossValues);\n  }\n  getNamedWeights(config) {\n    const namedWeights = [];\n    const trainableOnly = config != null && config.trainableOnly;\n    const weights = trainableOnly ? this.trainableWeights : this.weights;\n    const weightValues = this.getWeights(trainableOnly);\n    for (let i2 = 0; i2 < weights.length; ++i2) {\n      if (trainableOnly && !weights[i2].trainable) {\n        continue;\n      }\n      namedWeights.push({ name: weights[i2].originalName, tensor: weightValues[i2] });\n    }\n    return namedWeights;\n  }\n  set stopTraining(stop) {\n    this.stopTraining_ = stop;\n  }\n  get stopTraining() {\n    return this.stopTraining_;\n  }\n  get optimizer() {\n    return this.optimizer_;\n  }\n  set optimizer(optimizer) {\n    if (this.optimizer_ !== optimizer) {\n      this.optimizer_ = optimizer;\n      this.isOptimizerOwned = false;\n    }\n  }\n  dispose() {\n    const result = super.dispose();\n    if (result.refCountAfterDispose === 0 && this.optimizer != null && this.isOptimizerOwned) {\n      const numTensorsBeforeOptmizerDisposal = memory().numTensors;\n      this.optimizer_.dispose();\n      result.numDisposedVariables += numTensorsBeforeOptmizerDisposal - memory().numTensors;\n    }\n    return result;\n  }\n  getLossIdentifiers() {\n    let lossNames;\n    if (typeof this.loss === \"string\") {\n      lossNames = toSnakeCase(this.loss);\n    } else if (Array.isArray(this.loss)) {\n      for (const loss of this.loss) {\n        if (typeof loss !== \"string\") {\n          throw new Error(\"Serialization of non-string loss is not supported.\");\n        }\n      }\n      lossNames = this.loss.map((name) => toSnakeCase(name));\n    } else {\n      const outputNames = Object.keys(this.loss);\n      lossNames = {};\n      const losses2 = this.loss;\n      for (const outputName of outputNames) {\n        if (typeof losses2[outputName] === \"string\") {\n          lossNames[outputName] = toSnakeCase(losses2[outputName]);\n        } else {\n          throw new Error(\"Serialization of non-string loss is not supported.\");\n        }\n      }\n    }\n    return lossNames;\n  }\n  getMetricIdentifiers() {\n    if (typeof this.metrics === \"string\" || typeof this.metrics === \"function\") {\n      return [toSnakeCase(getLossOrMetricName(this.metrics))];\n    } else if (Array.isArray(this.metrics)) {\n      return this.metrics.map((metric) => toSnakeCase(getLossOrMetricName(metric)));\n    } else {\n      const metricsIdentifiers = {};\n      for (const key in this.metrics) {\n        metricsIdentifiers[key] = toSnakeCase(getLossOrMetricName(this.metrics[key]));\n      }\n      return metricsIdentifiers;\n    }\n  }\n  getTrainingConfig() {\n    return {\n      loss: this.getLossIdentifiers(),\n      metrics: this.getMetricIdentifiers(),\n      optimizer_config: {\n        class_name: this.optimizer.getClassName(),\n        config: this.optimizer.getConfig()\n      }\n    };\n  }\n  loadTrainingConfig(trainingConfig) {\n    if (trainingConfig.weighted_metrics != null) {\n      throw new Error(\"Loading weight_metrics is not supported yet.\");\n    }\n    if (trainingConfig.loss_weights != null) {\n      throw new Error(\"Loading loss_weights is not supported yet.\");\n    }\n    if (trainingConfig.sample_weight_mode != null) {\n      throw new Error(\"Loading sample_weight_mode is not supported yet.\");\n    }\n    const tsConfig = convertPythonicToTs(trainingConfig.optimizer_config);\n    const optimizer = deserialize(tsConfig);\n    let loss;\n    if (typeof trainingConfig.loss === \"string\") {\n      loss = toCamelCase(trainingConfig.loss);\n    } else if (Array.isArray(trainingConfig.loss)) {\n      loss = trainingConfig.loss.map((lossEntry) => toCamelCase(lossEntry));\n    } else if (trainingConfig.loss != null) {\n      loss = {};\n      for (const key in trainingConfig.loss) {\n        loss[key] = toCamelCase(trainingConfig.loss[key]);\n      }\n    }\n    let metrics;\n    if (Array.isArray(trainingConfig.metrics)) {\n      metrics = trainingConfig.metrics.map((metric) => toCamelCase(metric));\n    } else if (trainingConfig.metrics != null) {\n      metrics = {};\n      for (const key in trainingConfig.metrics) {\n        metrics[key] = toCamelCase(trainingConfig.metrics[key]);\n      }\n    }\n    this.compile({ loss, metrics, optimizer });\n  }\n  async save(handlerOrURL, config) {\n    if (typeof handlerOrURL === \"string\") {\n      const handlers = io_exports.getSaveHandlers(handlerOrURL);\n      if (handlers.length === 0) {\n        throw new ValueError(`Cannot find any save handlers for URL '${handlerOrURL}'`);\n      } else if (handlers.length > 1) {\n        throw new ValueError(`Found more than one (${handlers.length}) save handlers for URL '${handlerOrURL}'`);\n      }\n      handlerOrURL = handlers[0];\n    }\n    if (handlerOrURL.save == null) {\n      throw new ValueError(\"LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.\");\n    }\n    const weightDataAndSpecs = await io_exports.encodeWeights(this.getNamedWeights(config));\n    const returnString = false;\n    const unusedArg = null;\n    const modelConfig = this.toJSON(unusedArg, returnString);\n    const modelArtifacts = {\n      modelTopology: modelConfig,\n      format: LAYERS_MODEL_FORMAT_NAME,\n      generatedBy: `TensorFlow.js tfjs-layers v${version2}`,\n      convertedBy: null\n    };\n    const includeOptimizer = config == null ? false : config.includeOptimizer;\n    if (includeOptimizer && this.optimizer != null) {\n      modelArtifacts.trainingConfig = this.getTrainingConfig();\n      const weightType = \"optimizer\";\n      const { data: optimizerWeightData, specs: optimizerWeightSpecs } = await io_exports.encodeWeights(await this.optimizer.getWeights(), weightType);\n      weightDataAndSpecs.specs.push(...optimizerWeightSpecs);\n      weightDataAndSpecs.data = io_exports.concatenateArrayBuffers([weightDataAndSpecs.data, optimizerWeightData]);\n    }\n    if (this.userDefinedMetadata != null) {\n      const checkSize = true;\n      checkUserDefinedMetadata(this.userDefinedMetadata, this.name, checkSize);\n      modelArtifacts.userDefinedMetadata = this.userDefinedMetadata;\n    }\n    modelArtifacts.weightData = weightDataAndSpecs.data;\n    modelArtifacts.weightSpecs = weightDataAndSpecs.specs;\n    return handlerOrURL.save(modelArtifacts);\n  }\n  setUserDefinedMetadata(userDefinedMetadata) {\n    checkUserDefinedMetadata(userDefinedMetadata, this.name);\n    this.userDefinedMetadata = userDefinedMetadata;\n  }\n  getUserDefinedMetadata() {\n    return this.userDefinedMetadata;\n  }\n};\nLayersModel.className = \"Model\";\nserialization_exports.registerClass(LayersModel);\nvar Functional = class extends LayersModel {\n};\nFunctional.className = \"Functional\";\nserialization_exports.registerClass(Functional);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/models.js\nasync function modelFromJSON(modelAndWeightsConfig, customObjects) {\n  if (!(\"modelTopology\" in modelAndWeightsConfig)) {\n    modelAndWeightsConfig = { modelTopology: modelAndWeightsConfig };\n  }\n  modelAndWeightsConfig = modelAndWeightsConfig;\n  let modelTopology = modelAndWeightsConfig.modelTopology;\n  if (modelTopology[\"model_config\"] != null) {\n    modelTopology = modelTopology[\"model_config\"];\n  }\n  const tsConfig = convertPythonicToTs(modelTopology);\n  const model2 = deserialize(tsConfig, customObjects);\n  if (modelAndWeightsConfig.weightsManifest != null) {\n    const weightValues = await io_exports.loadWeights(modelAndWeightsConfig.weightsManifest, modelAndWeightsConfig.pathPrefix, model2.weights.map((weight) => weight.originalName));\n    const uniqueWeightValues = {};\n    for (const weight of model2.weights) {\n      uniqueWeightValues[weight.originalName] = weightValues[weight.originalName];\n    }\n    model2.loadWeights(uniqueWeightValues);\n    dispose(weightValues);\n  }\n  return model2;\n}\nasync function loadLayersModelInternal(pathOrIOHandler, options) {\n  if (options == null) {\n    options = {};\n  }\n  if (typeof pathOrIOHandler === \"string\") {\n    const handlers = io_exports.getLoadHandlers(pathOrIOHandler, options);\n    if (handlers.length === 0) {\n      handlers.push(io_exports.browserHTTPRequest(pathOrIOHandler, options));\n    } else if (handlers.length > 1) {\n      throw new ValueError(`Found more than one (${handlers.length}) load handlers for URL '${pathOrIOHandler}'`);\n    }\n    pathOrIOHandler = handlers[0];\n  }\n  return loadLayersModelFromIOHandler(pathOrIOHandler, void 0, options);\n}\nasync function loadLayersModelFromIOHandler(handler, customObjects, options) {\n  if (options == null) {\n    options = {};\n  }\n  if (handler.load == null) {\n    throw new ValueError(\"Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.\");\n  }\n  const artifacts = await handler.load();\n  let modelTopology = artifacts.modelTopology;\n  if (modelTopology[\"model_config\"] != null) {\n    modelTopology = modelTopology[\"model_config\"];\n  }\n  const strict = options.strict == null ? true : options.strict;\n  const fastWeightInit = artifacts.weightData != null && artifacts.weightSpecs != null && strict;\n  const model2 = deserialize(convertPythonicToTs(modelTopology), customObjects, fastWeightInit);\n  const trainingConfig = artifacts.trainingConfig;\n  if (trainingConfig != null) {\n    model2.loadTrainingConfig(trainingConfig);\n  }\n  if (artifacts.userDefinedMetadata != null) {\n    model2.setUserDefinedMetadata(artifacts.userDefinedMetadata);\n  }\n  if (artifacts.weightData != null) {\n    if (artifacts.weightSpecs == null) {\n      throw new ValueError(\"LayersModel artifacts contains weight data, but not weight specs. Therefore loading of weights cannot proceed.\");\n    }\n    const { modelWeights, optimizerWeights } = decodeModelAndOptimizerWeights(artifacts.weightData, artifacts.weightSpecs);\n    model2.loadWeights(modelWeights, strict);\n    if (model2.optimizer != null && optimizerWeights.length > 0) {\n      await model2.optimizer.setWeights(optimizerWeights);\n    }\n    dispose(modelWeights);\n    dispose(optimizerWeights.map((w) => w.tensor));\n  }\n  return model2;\n}\nfunction decodeModelAndOptimizerWeights(buffer2, specs) {\n  const name2Tensor = io_exports.decodeWeights(buffer2, specs);\n  const modelWeights = {};\n  const optimizerWeights = [];\n  specs.forEach((spec) => {\n    if (spec.group === \"optimizer\") {\n      optimizerWeights.push({ name: spec.name, tensor: name2Tensor[spec.name] });\n    } else {\n      modelWeights[spec.name] = name2Tensor[spec.name];\n    }\n  });\n  return { modelWeights, optimizerWeights };\n}\nvar Sequential = class extends LayersModel {\n  constructor(args) {\n    super({ inputs: [], outputs: [] });\n    args = args || {};\n    this.trainable = true;\n    this.built = false;\n    this.name = args.name != null ? args.name : getUid(\"sequential_\");\n    if (args.layers != null) {\n      for (const layer of args.layers) {\n        this.add(layer);\n      }\n    }\n  }\n  checkShape(layer) {\n    const shape = layer.inboundNodes[0].outputTensors[0].shape;\n    if (shape.some((x) => x < 0)) {\n      throw new ValueError(`Negative dimension size caused by adding layer ${layer.name} with input shape [${layer.inboundNodes[0].inputTensors[0].shape}]`);\n    }\n  }\n  add(layer) {\n    const isLayerModelInstance = layer instanceof Sequential || layer instanceof LayersModel;\n    let modelLayer;\n    if (isLayerModelInstance) {\n      modelLayer = layer;\n      if (modelLayer.outputs.length !== 1) {\n        throw new ValueError(\"All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.\");\n      }\n      if (modelLayer.inputs.length !== 1) {\n        throw new ValueError(\"All layers in a Sequential model should have a single input tensor. For multi-input layers, use the functional API.\");\n      }\n    }\n    if (this.outputs.length === 0) {\n      if (layer.inboundNodes.length === 0) {\n        if (layer.batchInputShape == null) {\n          throw new ValueError(\"The first layer in a Sequential model must get an `inputShape` or `batchInputShape` argument.\");\n        }\n        const x = Input({\n          batchShape: layer.batchInputShape,\n          dtype: layer.dtype,\n          name: layer.name + \"_input\"\n        });\n        layer.apply(x);\n      }\n      if (isLayerModelInstance) {\n        this.outputs = modelLayer.outputs;\n        this.inputs = modelLayer.inputs;\n      } else {\n        if (layer.inboundNodes.length !== 1) {\n          throw new ValueError(`A layer added to a Sequential model must not already be connected somewhere else. LayersModel received layer ${layer.name} which has ${layer.inboundNodes.length} pre-existing inbound connections.`);\n        }\n        if (layer.inboundNodes[0].outputTensors.length !== 1) {\n          throw new ValueError(\"All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.\");\n        }\n        this.checkShape(layer);\n        this.outputs = [layer.inboundNodes[0].outputTensors[0]];\n        this.inputs = getSourceInputs(this.outputs[0]);\n      }\n      this.inboundNodes = [];\n      new Node({\n        outboundLayer: this,\n        inboundLayers: [],\n        nodeIndices: [],\n        tensorIndices: [],\n        inputTensors: this.inputs,\n        outputTensors: this.outputs,\n        inputMasks: pyListRepeat(null, this.inputs.length),\n        outputMasks: [null],\n        inputShapes: this.inputs.map((x) => x.shape),\n        outputShapes: this.outputs[0].shape\n      });\n    } else {\n      const outputTensor = layer.apply(this.outputs[0]);\n      if (Array.isArray(outputTensor)) {\n        throw new TypeError(\"All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.\");\n      }\n      this.checkShape(layer);\n      this.outputs = [outputTensor];\n      this.inboundNodes[0].outputTensors = this.outputs;\n      this.inboundNodes[0].outputShapes = [this.outputs[0].shape];\n    }\n    this.layers.push(layer);\n    this.built = false;\n  }\n  pop() {\n    if (this.layers.length === 0) {\n      throw new TypeError(\"There are no layers in the model.\");\n    }\n    this.layers.pop();\n    if (this.layers.length === 0) {\n      this.outputs = [];\n      this.inboundNodes = [];\n      this.outboundNodes = [];\n    } else {\n      const lastLayerIndex = this.layers.length - 1;\n      this.layers[lastLayerIndex].outboundNodes = [];\n      this.outputs = [this.layers[lastLayerIndex].output];\n      this.inboundNodes[0].outputTensors = this.outputs;\n      this.inboundNodes[0].outputShapes = [this.outputs[0].shape];\n    }\n  }\n  call(inputs, kwargs) {\n    if (this.model == null) {\n      this.build();\n    }\n    return this.model.call(inputs, kwargs);\n  }\n  build(inputShape) {\n    getExactlyOneShape(inputShape);\n    if (this.inputs.length === 0 || this.outputs.length === 0) {\n      throw new TypeError(\"Sequential model cannot be built: model is empty. Add some layers first.\");\n    }\n    this.model = new LayersModel({\n      inputs: this.inputs,\n      outputs: this.outputs[0],\n      name: this.name + \"_model\"\n    });\n    this.model.trainable = this.trainable;\n    this.supportsMasking = this.model.supportsMasking;\n    this.inputLayers = this.model.inputLayers;\n    this.inputLayersNodeIndices = this.model.inputLayersNodeIndices;\n    this.inputLayersTensorIndices = this.model.inputLayersTensorIndices;\n    this.outputLayers = this.model.outputLayers;\n    this.outputLayersNodeIndices = this.model.outputLayersNodeIndices;\n    this.outputLayersTensorIndices = this.model.outputLayersTensorIndices;\n    this.nodesByDepth = this.model.nodesByDepth;\n    this.containerNodes = this.model.containerNodes;\n    this.outputNames = this.model.outputNames;\n    this.inputNames = this.model.inputNames;\n    this.built = true;\n  }\n  countParams() {\n    if (!this.built) {\n      this.build();\n    }\n    return super.countParams();\n  }\n  summary(lineLength, positions, printFn = console.log) {\n    if (!this.built) {\n      this.build();\n    }\n    super.summary(lineLength, positions, printFn);\n  }\n  setWeights(weights) {\n    if (this.model == null) {\n      this.build();\n    }\n    this.model.setWeights(weights);\n  }\n  evaluate(x, y, args = {}) {\n    if (!this.built) {\n      throw new RuntimeError(\"The model needs to be compiled before being used.\");\n    }\n    return this.model.evaluate(x, y, args);\n  }\n  async evaluateDataset(dataset, args) {\n    if (!this.built) {\n      throw new RuntimeError(\"The model needs to be compiled before being used.\");\n    }\n    return this.model.evaluateDataset(dataset, args);\n  }\n  predict(x, args = {}) {\n    if (this.model == null) {\n      this.build();\n    }\n    return this.model.predict(x, args);\n  }\n  predictOnBatch(x) {\n    if (this.model == null) {\n      this.build();\n    }\n    return this.model.predictOnBatch(x);\n  }\n  compile(args) {\n    this.build();\n    this.model.compile(args);\n    this.optimizer_ = this.model.optimizer;\n    this.isOptimizerOwned = this.model.isOptimizerOwned;\n    this.loss = this.model.loss;\n    this.metrics = this.model.metrics;\n    this.metricsTensors = this.model.metricsTensors;\n    this.metricsNames = this.model.metricsNames;\n  }\n  get optimizer() {\n    return this.model == null ? void 0 : this.model.optimizer;\n  }\n  set optimizer(optimizer) {\n    this.model.optimizer = optimizer;\n  }\n  async fit(x, y, args = {}) {\n    if (!this.built) {\n      throw new RuntimeError(\"The model needs to be compiled before being used.\");\n    }\n    return this.model.fit(x, y, args);\n  }\n  async fitDataset(dataset, args) {\n    if (!this.built) {\n      throw new RuntimeError(\"The model needs to be compiled before being used.\");\n    }\n    return this.model.fitDataset(dataset, args);\n  }\n  async trainOnBatch(x, y) {\n    return this.model.trainOnBatch(x, y);\n  }\n  static fromConfig(cls, config, customObjects = {}, fastWeightInit = false) {\n    let configArray;\n    let extraModelConfig = {};\n    if (config instanceof Array) {\n      if (!(config[0].className != null) || config[0][\"className\"] === \"Merge\") {\n        throw new ValueError(\"Legacy serialization format not supported yet.\");\n      }\n      configArray = config;\n    } else {\n      util_exports.assert(config[\"layers\"] != null, () => `When the config data for a Sequential model is not an Array, it must be an Object that contains the 'layers' field.`);\n      configArray = config[\"layers\"];\n      delete config[\"layers\"];\n      extraModelConfig = config;\n    }\n    const model2 = new cls(extraModelConfig);\n    if (!(model2 instanceof Sequential)) {\n      throw new NotImplementedError(`Sequential.fromConfig called on non-Sequential input: ${model2}`);\n    }\n    for (const conf of configArray) {\n      const customObjects2 = void 0;\n      const layer = deserialize(conf, customObjects2, fastWeightInit);\n      if (fastWeightInit) {\n        layer.setFastWeightInitDuringBuild(true);\n      }\n      model2.add(layer);\n    }\n    return model2;\n  }\n  set stopTraining(stop) {\n    if (this.model == null) {\n      throw new ValueError(\"Cannot set the stopTraining property of a sequential model before it is compiled.\");\n    }\n    this.model.stopTraining = stop;\n  }\n  get stopTraining() {\n    if (this.model == null) {\n      throw new ValueError(\"Cannot get the stopTraining property of a sequential model before it is compiled.\");\n    }\n    return this.model.stopTraining;\n  }\n  getConfig() {\n    const layers = [];\n    for (const layer of this.layers) {\n      const dict = {};\n      dict[\"className\"] = layer.getClassName();\n      dict[\"config\"] = layer.getConfig();\n      layers.push(dict);\n    }\n    return { name: this.name, layers };\n  }\n};\nSequential.className = \"Sequential\";\nserialization_exports.registerClass(Sequential);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports.js\nfunction model(args) {\n  return new LayersModel(args);\n}\nfunction sequential(config) {\n  return new Sequential(config);\n}\nfunction loadLayersModel(pathOrIOHandler, options) {\n  if (options == null) {\n    options = {};\n  }\n  return loadLayersModelInternal(pathOrIOHandler, options);\n}\nfunction input(config) {\n  return Input(config);\n}\nfunction registerCallbackConstructor(verbosityLevel, callbackConstructor) {\n  CallbackConstructorRegistry.registerCallbackConstructor(verbosityLevel, callbackConstructor);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/activations.js\nvar Activation = class extends serialization_exports.Serializable {\n  getConfig() {\n    return {};\n  }\n};\nvar Elu2 = class extends Activation {\n  apply(x, alpha = 1) {\n    return elu2(x, alpha);\n  }\n};\nElu2.className = \"elu\";\nserialization_exports.registerClass(Elu2);\nvar Selu2 = class extends Activation {\n  apply(x) {\n    return selu(x);\n  }\n};\nSelu2.className = \"selu\";\nserialization_exports.registerClass(Selu2);\nvar Relu2 = class extends Activation {\n  apply(x) {\n    return relu(x);\n  }\n};\nRelu2.className = \"relu\";\nserialization_exports.registerClass(Relu2);\nvar Relu62 = class extends Activation {\n  apply(x) {\n    return tidy(() => minimum(6, relu(x)));\n  }\n};\nRelu62.className = \"relu6\";\nserialization_exports.registerClass(Relu62);\nvar Linear = class extends Activation {\n  apply(x) {\n    return x;\n  }\n};\nLinear.className = \"linear\";\nserialization_exports.registerClass(Linear);\nvar Sigmoid2 = class extends Activation {\n  apply(x) {\n    return sigmoid(x);\n  }\n};\nSigmoid2.className = \"sigmoid\";\nserialization_exports.registerClass(Sigmoid2);\nvar HardSigmoid = class extends Activation {\n  apply(x) {\n    return hardSigmoid(x);\n  }\n};\nHardSigmoid.className = \"hardSigmoid\";\nserialization_exports.registerClass(HardSigmoid);\nvar Softplus2 = class extends Activation {\n  apply(x) {\n    return softplus(x);\n  }\n};\nSoftplus2.className = \"softplus\";\nserialization_exports.registerClass(Softplus2);\nvar Softsign = class extends Activation {\n  apply(x) {\n    return softsign(x);\n  }\n};\nSoftsign.className = \"softsign\";\nserialization_exports.registerClass(Softsign);\nvar Tanh2 = class extends Activation {\n  apply(x) {\n    return tanh2(x);\n  }\n};\nTanh2.className = \"tanh\";\nserialization_exports.registerClass(Tanh2);\nvar Softmax2 = class extends Activation {\n  apply(x, axis = -1) {\n    return softmax(x, axis);\n  }\n};\nSoftmax2.className = \"softmax\";\nserialization_exports.registerClass(Softmax2);\nvar LogSoftmax2 = class extends Activation {\n  apply(x, axis = -1) {\n    return logSoftmax(x, axis);\n  }\n};\nLogSoftmax2.className = \"logSoftmax\";\nserialization_exports.registerClass(LogSoftmax2);\nvar Swish = class extends Activation {\n  apply(x, alpha = 1) {\n    return tidy(() => mul(sigmoid(mul(x, alpha)), x));\n  }\n};\nSwish.className = \"swish\";\nserialization_exports.registerClass(Swish);\nvar Mish = class extends Activation {\n  apply(x) {\n    return tidy(() => mul(x, tanh2(softplus(x))));\n  }\n};\nMish.className = \"mish\";\nserialization_exports.registerClass(Mish);\nfunction serializeActivation(activation2) {\n  return activation2.getClassName();\n}\nfunction deserializeActivation(config, customObjects = {}) {\n  return deserializeKerasObject(config, serialization_exports.SerializationMap.getMap().classNameMap, customObjects, \"activation\");\n}\nfunction getActivation(identifier) {\n  if (identifier == null) {\n    const config = {};\n    config[\"className\"] = \"linear\";\n    config[\"config\"] = {};\n    return deserializeActivation(config);\n  }\n  if (typeof identifier === \"string\") {\n    const config = {};\n    config[\"className\"] = identifier;\n    config[\"config\"] = {};\n    return deserializeActivation(config);\n  } else if (identifier instanceof Activation) {\n    return identifier;\n  } else {\n    return deserializeActivation(identifier);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/regularizers.js\nfunction assertObjectArgs(args) {\n  if (args != null && typeof args !== \"object\") {\n    throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${args}`);\n  }\n}\nvar Regularizer = class extends serialization_exports.Serializable {\n};\nvar L1L2 = class extends Regularizer {\n  constructor(args) {\n    super();\n    assertObjectArgs(args);\n    this.l1 = args == null || args.l1 == null ? 0.01 : args.l1;\n    this.l2 = args == null || args.l2 == null ? 0.01 : args.l2;\n    this.hasL1 = this.l1 !== 0;\n    this.hasL2 = this.l2 !== 0;\n  }\n  apply(x) {\n    return tidy(() => {\n      let regularization = zeros([1]);\n      if (this.hasL1) {\n        regularization = add2(regularization, sum2(mul(this.l1, abs(x))));\n      }\n      if (this.hasL2) {\n        regularization = add2(regularization, sum2(mul(this.l2, square2(x))));\n      }\n      return reshape(regularization, []);\n    });\n  }\n  getConfig() {\n    return { \"l1\": this.l1, \"l2\": this.l2 };\n  }\n  static fromConfig(cls, config) {\n    return new cls({ l1: config[\"l1\"], l2: config[\"l2\"] });\n  }\n};\nL1L2.className = \"L1L2\";\nserialization_exports.registerClass(L1L2);\nfunction l1(args) {\n  assertObjectArgs(args);\n  return new L1L2({ l1: args != null ? args.l1 : null, l2: 0 });\n}\nfunction l2(args) {\n  assertObjectArgs(args);\n  return new L1L2({ l2: args != null ? args.l2 : null, l1: 0 });\n}\nvar REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP = {\n  \"l1l2\": \"L1L2\"\n};\nfunction serializeRegularizer(constraint) {\n  return serializeKerasObject(constraint);\n}\nfunction deserializeRegularizer(config, customObjects = {}) {\n  return deserializeKerasObject(config, serialization_exports.SerializationMap.getMap().classNameMap, customObjects, \"regularizer\");\n}\nfunction getRegularizer(identifier) {\n  if (identifier == null) {\n    return null;\n  }\n  if (typeof identifier === \"string\") {\n    const className = identifier in REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP ? REGULARIZER_IDENTIFIER_REGISTRY_SYMBOL_MAP[identifier] : identifier;\n    const config = { className, config: {} };\n    return deserializeRegularizer(config);\n  } else if (identifier instanceof Regularizer) {\n    return identifier;\n  } else {\n    return deserializeRegularizer(identifier);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/advanced_activations.js\nvar ReLU = class extends Layer {\n  constructor(args) {\n    super(args == null ? {} : args);\n    this.supportsMasking = true;\n    if (args != null) {\n      this.maxValue = args.maxValue;\n    }\n  }\n  call(inputs, kwargs) {\n    inputs = getExactlyOneTensor(inputs);\n    let output = relu(inputs);\n    if (this.maxValue != null) {\n      output = clipByValue(output, 0, this.maxValue);\n    }\n    return output;\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const config = { maxValue: this.maxValue };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nReLU.className = \"ReLU\";\nserialization_exports.registerClass(ReLU);\nvar LeakyReLU = class extends Layer {\n  constructor(args) {\n    super(args == null ? {} : args);\n    this.DEFAULT_ALPHA = 0.3;\n    if (args == null) {\n      args = {};\n    }\n    this.alpha = args.alpha == null ? this.DEFAULT_ALPHA : args.alpha;\n  }\n  call(inputs, kwargs) {\n    const x = getExactlyOneTensor(inputs);\n    return leakyRelu(x, this.alpha);\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const config = { alpha: this.alpha };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nLeakyReLU.className = \"LeakyReLU\";\nserialization_exports.registerClass(LeakyReLU);\nvar PReLU = class extends Layer {\n  constructor(args) {\n    super(args == null ? {} : args);\n    this.DEFAULT_ALPHA_INITIALIZER = \"zeros\";\n    if (args == null) {\n      args = {};\n    }\n    this.supportsMasking = true;\n    this.alphaInitializer = getInitializer(args.alphaInitializer || this.DEFAULT_ALPHA_INITIALIZER);\n    this.alphaRegularizer = getRegularizer(args.alphaRegularizer);\n    this.alphaConstraint = getConstraint(args.alphaConstraint);\n    if (args.sharedAxes == null) {\n      this.sharedAxes = null;\n    } else if (Array.isArray(args.sharedAxes)) {\n      this.sharedAxes = args.sharedAxes;\n    } else if (typeof args.sharedAxes === \"number\") {\n      this.sharedAxes = [args.sharedAxes];\n    } else {\n      throw new ValueError(`Expected sharedAxes to be a number or an array of numbers, but got ${args.sharedAxes}`);\n    }\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const paramShape = inputShape.slice(1);\n    if (this.sharedAxes != null) {\n      for (const i2 of this.sharedAxes) {\n        paramShape[i2 - 1] = 1;\n      }\n    }\n    this.alpha = this.addWeight(\"alpha\", paramShape, \"float32\", this.alphaInitializer, this.alphaRegularizer, true, this.alphaConstraint);\n    const axes = {};\n    if (this.sharedAxes != null) {\n      for (let i2 = 1; i2 < inputShape.length; ++i2) {\n        axes[i2] = inputShape[i2];\n      }\n    }\n    this.inputSpec = [new InputSpec({\n      ndim: inputShape.length,\n      axes\n    })];\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    inputs = getExactlyOneTensor(inputs);\n    return prelu(inputs, this.alpha.read());\n  }\n  getConfig() {\n    const config = {\n      alphaInitializer: serializeInitializer(this.alphaInitializer),\n      alphaRegularizer: serializeRegularizer(this.alphaRegularizer),\n      alphaConstraint: serializeConstraint(this.alphaConstraint),\n      sharedAxes: this.sharedAxes\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nPReLU.className = \"PReLU\";\nserialization_exports.registerClass(PReLU);\nvar ELU = class extends Layer {\n  constructor(args) {\n    super(args == null ? {} : args);\n    this.DEFAULT_ALPHA = 1;\n    if (args == null) {\n      args = {};\n    }\n    if (args.alpha != null && args.alpha !== this.DEFAULT_ALPHA) {\n      throw new NotImplementedError(`Non-default alpha value (${args.alpha}) is not supported by the ELU layer yet.`);\n    }\n    this.alpha = args.alpha == null ? this.DEFAULT_ALPHA : args.alpha;\n  }\n  call(inputs, kwargs) {\n    const x = getExactlyOneTensor(inputs);\n    return elu(x);\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const config = { alpha: this.alpha };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nELU.className = \"ELU\";\nserialization_exports.registerClass(ELU);\nvar ThresholdedReLU = class extends Layer {\n  constructor(args) {\n    super(args == null ? {} : args);\n    this.DEFAULT_THETA = 1;\n    if (args == null) {\n      args = {};\n    }\n    this.theta = args.theta == null ? this.DEFAULT_THETA : args.theta;\n  }\n  call(inputs, kwargs) {\n    const x = getExactlyOneTensor(inputs);\n    return mul(x, cast(greater(x, this.theta), \"float32\"));\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const config = { theta: this.theta };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nThresholdedReLU.className = \"ThresholdedReLU\";\nserialization_exports.registerClass(ThresholdedReLU);\nvar Softmax3 = class extends Layer {\n  constructor(args) {\n    super(args == null ? {} : args);\n    this.DEFAULT_AXIS = 1;\n    if (args == null) {\n      args = {};\n    }\n    this.softmax = new Softmax2().apply;\n    this.axis = args.axis == null ? this.DEFAULT_AXIS : args.axis;\n  }\n  call(inputs, kwargs) {\n    const x = getExactlyOneTensor(inputs);\n    return this.softmax(x, this.axis);\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const config = { axis: this.axis };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nSoftmax3.className = \"Softmax\";\nserialization_exports.registerClass(Softmax3);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/utils/conv_utils.js\nfunction normalizeArray(value, n2, name) {\n  if (typeof value === \"number\") {\n    return pyListRepeat(value, n2);\n  } else {\n    if (value.length !== n2) {\n      throw new ValueError(`The ${name} argument must be an integer or tuple of ${n2} integers. Received: ${value.length} elements.`);\n    }\n    for (let i2 = 0; i2 < n2; ++i2) {\n      const singleValue = value[i2];\n      if (!isInteger(singleValue)) {\n        throw new ValueError(`The ${name} argument must be an integer or tuple of ${n2} integers. Received: ${JSON.stringify(value)} including a non-integer number ${singleValue}`);\n      }\n    }\n    return value;\n  }\n}\nfunction convOutputLength(inputLength, filterSize, padding, stride, dilation = 1) {\n  if (inputLength == null) {\n    return inputLength;\n  }\n  const dilatedFilterSize = filterSize + (filterSize - 1) * (dilation - 1);\n  let outputLength;\n  if (padding === \"same\") {\n    outputLength = inputLength;\n  } else {\n    outputLength = inputLength - dilatedFilterSize + 1;\n  }\n  return Math.floor((outputLength + stride - 1) / stride);\n}\nfunction deconvLength(dimSize, strideSize, kernelSize, padding) {\n  if (dimSize == null) {\n    return null;\n  }\n  if (padding === \"valid\") {\n    dimSize = dimSize * strideSize + max2([kernelSize - strideSize, 0]);\n  } else if (padding === \"same\") {\n    dimSize = dimSize * strideSize;\n  } else {\n    throw new ValueError(`Unsupport padding mode: ${padding}.`);\n  }\n  return dimSize;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/convolutional.js\nfunction preprocessConv2DInput(x, dataFormat) {\n  return tidy(() => {\n    checkDataFormat(dataFormat);\n    if (dataFormat === \"channelsFirst\") {\n      return transpose(x, [0, 2, 3, 1]);\n    } else {\n      return x;\n    }\n  });\n}\nfunction preprocessConv3DInput(x, dataFormat) {\n  return tidy(() => {\n    checkDataFormat(dataFormat);\n    if (dataFormat === \"channelsFirst\") {\n      return transpose(x, [0, 2, 3, 4, 1]);\n    } else {\n      return x;\n    }\n  });\n}\nfunction conv1dWithBias(x, kernel, bias, strides = 1, padding = \"valid\", dataFormat, dilationRate = 1) {\n  return tidy(() => {\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    checkDataFormat(dataFormat);\n    if (x.shape.length !== 3) {\n      throw new ValueError(`The input of a conv1dWithBias operation should be 3, but is ${x.shape.length} instead.`);\n    }\n    if (kernel.shape.length !== 3) {\n      throw new ValueError(`The kernel for a conv1dWithBias operation should be 3, but is ${kernel.shape.length} instead`);\n    }\n    if (bias != null && bias.shape.length !== 1) {\n      throw new ValueError(`The bias for a conv1dWithBias operation should be 1, but is ${kernel.shape.length} instead`);\n    }\n    if (dataFormat === \"channelsFirst\") {\n      x = transpose(x, [0, 2, 1]);\n    }\n    if (padding === \"causal\") {\n      throw new NotImplementedError(\"The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.\");\n    }\n    let y = conv1d(x, kernel, strides, padding === \"same\" ? \"same\" : \"valid\", \"NWC\", dilationRate);\n    if (bias != null) {\n      y = biasAdd(y, bias);\n    }\n    return y;\n  });\n}\nfunction conv2dWithBiasActivation(x, kernel, bias, strides = [1, 1], padding = \"valid\", dataFormat, dilationRate, activation2 = null) {\n  return tidy(() => {\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    checkDataFormat(dataFormat);\n    if (x.rank !== 3 && x.rank !== 4) {\n      throw new ValueError(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${x.rank}.`);\n    }\n    if (kernel.rank !== 3 && kernel.rank !== 4) {\n      throw new ValueError(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${x.rank}.`);\n    }\n    let y = preprocessConv2DInput(x, dataFormat);\n    if (padding === \"causal\") {\n      throw new NotImplementedError(\"The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.\");\n    }\n    y = fused_ops_exports.conv2d({\n      x: y,\n      filter: kernel,\n      strides,\n      pad: padding === \"same\" ? \"same\" : \"valid\",\n      dilations: dilationRate,\n      dataFormat: \"NHWC\",\n      bias,\n      activation: activation2\n    });\n    if (dataFormat === \"channelsFirst\") {\n      y = transpose(y, [0, 3, 1, 2]);\n    }\n    return y;\n  });\n}\nfunction conv3dWithBias(x, kernel, bias, strides = [1, 1, 1], padding = \"valid\", dataFormat, dilationRate) {\n  return tidy(() => {\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    checkDataFormat(dataFormat);\n    if (x.rank !== 4 && x.rank !== 5) {\n      throw new ValueError(`conv3dWithBias expects input to be of rank 4 or 5, but received ${x.rank}.`);\n    }\n    if (kernel.rank !== 4 && kernel.rank !== 5) {\n      throw new ValueError(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${x.rank}.`);\n    }\n    let y = preprocessConv3DInput(x, dataFormat);\n    if (padding === \"causal\") {\n      throw new NotImplementedError(\"The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.\");\n    }\n    y = conv3d(y, kernel, strides, padding === \"same\" ? \"same\" : \"valid\", \"NDHWC\", dilationRate);\n    if (bias != null) {\n      y = biasAdd(y, bias);\n    }\n    if (dataFormat === \"channelsFirst\") {\n      y = transpose(y, [0, 4, 1, 2, 3]);\n    }\n    return y;\n  });\n}\nvar BaseConv = class extends Layer {\n  constructor(rank, args) {\n    super(args);\n    this.bias = null;\n    this.DEFAULT_KERNEL_INITIALIZER = \"glorotNormal\";\n    this.DEFAULT_BIAS_INITIALIZER = \"zeros\";\n    BaseConv.verifyArgs(args);\n    this.rank = rank;\n    assertPositiveInteger(this.rank, \"rank\");\n    if (this.rank !== 1 && this.rank !== 2 && this.rank !== 3) {\n      throw new NotImplementedError(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);\n    }\n    this.kernelSize = normalizeArray(args.kernelSize, rank, \"kernelSize\");\n    this.strides = normalizeArray(args.strides == null ? 1 : args.strides, rank, \"strides\");\n    this.padding = args.padding == null ? \"valid\" : args.padding;\n    checkPaddingMode(this.padding);\n    this.dataFormat = args.dataFormat == null ? \"channelsLast\" : args.dataFormat;\n    checkDataFormat(this.dataFormat);\n    this.activation = getActivation(args.activation);\n    this.useBias = args.useBias == null ? true : args.useBias;\n    this.biasInitializer = getInitializer(args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER);\n    this.biasConstraint = getConstraint(args.biasConstraint);\n    this.biasRegularizer = getRegularizer(args.biasRegularizer);\n    this.activityRegularizer = getRegularizer(args.activityRegularizer);\n    this.dilationRate = normalizeArray(args.dilationRate == null ? 1 : args.dilationRate, rank, \"dilationRate\");\n    if (this.rank === 1 && (Array.isArray(this.dilationRate) && this.dilationRate.length !== 1)) {\n      throw new ValueError(`dilationRate must be a number or an array of a single number for 1D convolution, but received ${JSON.stringify(this.dilationRate)}`);\n    } else if (this.rank === 2) {\n      if (typeof this.dilationRate === \"number\") {\n        this.dilationRate = [this.dilationRate, this.dilationRate];\n      } else if (this.dilationRate.length !== 2) {\n        throw new ValueError(`dilationRate must be a number or array of two numbers for 2D convolution, but received ${JSON.stringify(this.dilationRate)}`);\n      }\n    } else if (this.rank === 3) {\n      if (typeof this.dilationRate === \"number\") {\n        this.dilationRate = [this.dilationRate, this.dilationRate, this.dilationRate];\n      } else if (this.dilationRate.length !== 3) {\n        throw new ValueError(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`);\n      }\n    }\n  }\n  static verifyArgs(args) {\n    assert2(\"kernelSize\" in args, `required key 'kernelSize' not in config`);\n    if (typeof args.kernelSize !== \"number\" && !checkArrayTypeAndLength(args.kernelSize, \"number\", 1, 3)) {\n      throw new ValueError(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(args.kernelSize)}.`);\n    }\n  }\n  getConfig() {\n    const config = {\n      kernelSize: this.kernelSize,\n      strides: this.strides,\n      padding: this.padding,\n      dataFormat: this.dataFormat,\n      dilationRate: this.dilationRate,\n      activation: serializeActivation(this.activation),\n      useBias: this.useBias,\n      biasInitializer: serializeInitializer(this.biasInitializer),\n      biasRegularizer: serializeRegularizer(this.biasRegularizer),\n      activityRegularizer: serializeRegularizer(this.activityRegularizer),\n      biasConstraint: serializeConstraint(this.biasConstraint)\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nvar Conv = class extends BaseConv {\n  constructor(rank, args) {\n    super(rank, args);\n    this.kernel = null;\n    Conv.verifyArgs(args);\n    this.filters = args.filters;\n    assertPositiveInteger(this.filters, \"filters\");\n    this.kernelInitializer = getInitializer(args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER);\n    this.kernelConstraint = getConstraint(args.kernelConstraint);\n    this.kernelRegularizer = getRegularizer(args.kernelRegularizer);\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const channelAxis = this.dataFormat === \"channelsFirst\" ? 1 : inputShape.length - 1;\n    if (inputShape[channelAxis] == null) {\n      throw new ValueError(`The channel dimension of the input should be defined. Found ${inputShape[channelAxis]}`);\n    }\n    const inputDim = inputShape[channelAxis];\n    const kernelShape = this.kernelSize.concat([inputDim, this.filters]);\n    this.kernel = this.addWeight(\"kernel\", kernelShape, null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n    if (this.useBias) {\n      this.bias = this.addWeight(\"bias\", [this.filters], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    }\n    this.inputSpec = [{ ndim: this.rank + 2, axes: { [channelAxis]: inputDim } }];\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = getExactlyOneTensor(inputs);\n      let outputs;\n      const biasValue = this.bias == null ? null : this.bias.read();\n      const fusedActivationName = mapActivationToFusedKernel(this.activation.getClassName());\n      if (fusedActivationName != null && this.rank === 2) {\n        outputs = conv2dWithBiasActivation(inputs, this.kernel.read(), biasValue, this.strides, this.padding, this.dataFormat, this.dilationRate, fusedActivationName);\n      } else {\n        if (this.rank === 1) {\n          outputs = conv1dWithBias(inputs, this.kernel.read(), biasValue, this.strides[0], this.padding, this.dataFormat, this.dilationRate[0]);\n        } else if (this.rank === 2) {\n          outputs = conv2dWithBiasActivation(inputs, this.kernel.read(), biasValue, this.strides, this.padding, this.dataFormat, this.dilationRate);\n        } else if (this.rank === 3) {\n          outputs = conv3dWithBias(inputs, this.kernel.read(), biasValue, this.strides, this.padding, this.dataFormat, this.dilationRate);\n        } else {\n          throw new NotImplementedError(\"convolutions greater than 3D are not implemented yet.\");\n        }\n        if (this.activation != null) {\n          outputs = this.activation.apply(outputs);\n        }\n      }\n      return outputs;\n    });\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const newSpace = [];\n    const space = this.dataFormat === \"channelsLast\" ? inputShape.slice(1, inputShape.length - 1) : inputShape.slice(2);\n    for (let i2 = 0; i2 < space.length; ++i2) {\n      const newDim = convOutputLength(space[i2], this.kernelSize[i2], this.padding, this.strides[i2], typeof this.dilationRate === \"number\" ? this.dilationRate : this.dilationRate[i2]);\n      newSpace.push(newDim);\n    }\n    let outputShape = [inputShape[0]];\n    if (this.dataFormat === \"channelsLast\") {\n      outputShape = outputShape.concat(newSpace);\n      outputShape.push(this.filters);\n    } else {\n      outputShape.push(this.filters);\n      outputShape = outputShape.concat(newSpace);\n    }\n    return outputShape;\n  }\n  getConfig() {\n    const config = {\n      filters: this.filters,\n      kernelInitializer: serializeInitializer(this.kernelInitializer),\n      kernelRegularizer: serializeRegularizer(this.kernelRegularizer),\n      kernelConstraint: serializeConstraint(this.kernelConstraint)\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  static verifyArgs(args) {\n    if (!(\"filters\" in args) || typeof args.filters !== \"number\" || args.filters < 1) {\n      throw new ValueError(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(args.filters)}`);\n    }\n  }\n};\nvar Conv2D2 = class extends Conv {\n  constructor(args) {\n    super(2, args);\n    Conv2D2.verifyArgs(args);\n  }\n  getConfig() {\n    const config = super.getConfig();\n    delete config[\"rank\"];\n    return config;\n  }\n  static verifyArgs(args) {\n    if (typeof args.kernelSize !== \"number\" && !checkArrayTypeAndLength(args.kernelSize, \"number\", 1, 2)) {\n      throw new ValueError(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(args.kernelSize)}.`);\n    }\n  }\n};\nConv2D2.className = \"Conv2D\";\nserialization_exports.registerClass(Conv2D2);\nvar Conv3D2 = class extends Conv {\n  constructor(args) {\n    super(3, args);\n    Conv3D2.verifyArgs(args);\n  }\n  getConfig() {\n    const config = super.getConfig();\n    delete config[\"rank\"];\n    return config;\n  }\n  static verifyArgs(args) {\n    if (typeof args.kernelSize !== \"number\") {\n      if (!(Array.isArray(args.kernelSize) && (args.kernelSize.length === 1 || args.kernelSize.length === 3))) {\n        throw new ValueError(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(args.kernelSize)}.`);\n      }\n    }\n  }\n};\nConv3D2.className = \"Conv3D\";\nserialization_exports.registerClass(Conv3D2);\nvar Conv2DTranspose = class extends Conv2D2 {\n  constructor(args) {\n    super(args);\n    this.inputSpec = [new InputSpec({ ndim: 4 })];\n    if (this.padding !== \"same\" && this.padding !== \"valid\") {\n      throw new ValueError(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`);\n    }\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    if (inputShape.length !== 4) {\n      throw new ValueError(\"Input should have rank 4; Received input shape: \" + JSON.stringify(inputShape));\n    }\n    const channelAxis = this.dataFormat === \"channelsFirst\" ? 1 : inputShape.length - 1;\n    if (inputShape[channelAxis] == null) {\n      throw new ValueError(\"The channel dimension of the inputs should be defined. Found `None`.\");\n    }\n    const inputDim = inputShape[channelAxis];\n    const kernelShape = this.kernelSize.concat([this.filters, inputDim]);\n    this.kernel = this.addWeight(\"kernel\", kernelShape, \"float32\", this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n    if (this.useBias) {\n      this.bias = this.addWeight(\"bias\", [this.filters], \"float32\", this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    }\n    this.inputSpec = [new InputSpec({ ndim: 4, axes: { [channelAxis]: inputDim } })];\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      let input2 = getExactlyOneTensor(inputs);\n      if (input2.shape.length !== 4) {\n        throw new ValueError(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${input2.shape.length}`);\n      }\n      const inputShape = input2.shape;\n      const batchSize = inputShape[0];\n      let hAxis;\n      let wAxis;\n      if (this.dataFormat === \"channelsFirst\") {\n        hAxis = 2;\n        wAxis = 3;\n      } else {\n        hAxis = 1;\n        wAxis = 2;\n      }\n      const height = inputShape[hAxis];\n      const width = inputShape[wAxis];\n      const kernelH = this.kernelSize[0];\n      const kernelW = this.kernelSize[1];\n      const strideH = this.strides[0];\n      const strideW = this.strides[1];\n      const outHeight = deconvLength(height, strideH, kernelH, this.padding);\n      const outWidth = deconvLength(width, strideW, kernelW, this.padding);\n      const outputShape = [batchSize, outHeight, outWidth, this.filters];\n      if (this.dataFormat !== \"channelsLast\") {\n        input2 = transpose(input2, [0, 2, 3, 1]);\n      }\n      let outputs = conv2dTranspose(input2, this.kernel.read(), outputShape, this.strides, this.padding);\n      if (this.dataFormat !== \"channelsLast\") {\n        outputs = transpose(outputs, [0, 3, 1, 2]);\n      }\n      if (this.bias != null) {\n        outputs = biasAdd(outputs, this.bias.read(), this.dataFormat);\n      }\n      if (this.activation != null) {\n        outputs = this.activation.apply(outputs);\n      }\n      return outputs;\n    });\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const outputShape = inputShape.slice();\n    let channelAxis;\n    let heightAxis;\n    let widthAxis;\n    if (this.dataFormat === \"channelsFirst\") {\n      channelAxis = 1;\n      heightAxis = 2;\n      widthAxis = 3;\n    } else {\n      channelAxis = 3;\n      heightAxis = 1;\n      widthAxis = 2;\n    }\n    const kernelH = this.kernelSize[0];\n    const kernelW = this.kernelSize[1];\n    const strideH = this.strides[0];\n    const strideW = this.strides[1];\n    outputShape[channelAxis] = this.filters;\n    outputShape[heightAxis] = deconvLength(outputShape[heightAxis], strideH, kernelH, this.padding);\n    outputShape[widthAxis] = deconvLength(outputShape[widthAxis], strideW, kernelW, this.padding);\n    return outputShape;\n  }\n  getConfig() {\n    const config = super.getConfig();\n    delete config[\"dilationRate\"];\n    return config;\n  }\n};\nConv2DTranspose.className = \"Conv2DTranspose\";\nserialization_exports.registerClass(Conv2DTranspose);\nvar Conv3DTranspose = class extends Conv3D2 {\n  constructor(args) {\n    super(args);\n    this.inputSpec = [new InputSpec({ ndim: 5 })];\n    if (this.padding !== \"same\" && this.padding !== \"valid\") {\n      throw new ValueError(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`);\n    }\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    if (inputShape.length !== 5) {\n      throw new ValueError(\"Input should have rank 5; Received input shape: \" + JSON.stringify(inputShape));\n    }\n    const channelAxis = this.dataFormat === \"channelsFirst\" ? 1 : inputShape.length - 1;\n    if (inputShape[channelAxis] == null) {\n      throw new ValueError(\"The channel dimension of the inputs should be defined. Found `None`.\");\n    }\n    const inputDim = inputShape[channelAxis];\n    const kernelShape = this.kernelSize.concat([this.filters, inputDim]);\n    this.kernel = this.addWeight(\"kernel\", kernelShape, \"float32\", this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n    if (this.useBias) {\n      this.bias = this.addWeight(\"bias\", [this.filters], \"float32\", this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    }\n    this.inputSpec = [new InputSpec({ ndim: 5, axes: { [channelAxis]: inputDim } })];\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      let input2 = getExactlyOneTensor(inputs);\n      if (input2.shape.length !== 5) {\n        throw new ValueError(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${input2.shape.length}`);\n      }\n      const inputShape = input2.shape;\n      const batchSize = inputShape[0];\n      let hAxis;\n      let wAxis;\n      let dAxis;\n      if (this.dataFormat === \"channelsFirst\") {\n        dAxis = 2;\n        hAxis = 3;\n        wAxis = 4;\n      } else {\n        dAxis = 1;\n        hAxis = 2;\n        wAxis = 3;\n      }\n      const depth = inputShape[dAxis];\n      const height = inputShape[hAxis];\n      const width = inputShape[wAxis];\n      const kernelD = this.kernelSize[0];\n      const kernelH = this.kernelSize[1];\n      const kernelW = this.kernelSize[2];\n      const strideD = this.strides[0];\n      const strideH = this.strides[1];\n      const strideW = this.strides[2];\n      const outDepth = deconvLength(depth, strideD, kernelD, this.padding);\n      const outHeight = deconvLength(height, strideH, kernelH, this.padding);\n      const outWidth = deconvLength(width, strideW, kernelW, this.padding);\n      const outputShape = [batchSize, outDepth, outHeight, outWidth, this.filters];\n      if (this.dataFormat !== \"channelsLast\") {\n        input2 = transpose(input2, [0, 2, 3, 4, 1]);\n      }\n      let outputs = conv3dTranspose(input2, this.kernel.read(), outputShape, this.strides, this.padding);\n      if (this.dataFormat !== \"channelsLast\") {\n        outputs = transpose(outputs, [0, 4, 1, 2, 3]);\n      }\n      if (this.bias !== null) {\n        outputs = biasAdd(outputs, this.bias.read(), this.dataFormat);\n      }\n      if (this.activation !== null) {\n        outputs = this.activation.apply(outputs);\n      }\n      return outputs;\n    });\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const outputShape = inputShape.slice();\n    let channelAxis;\n    let depthAxis;\n    let heightAxis;\n    let widthAxis;\n    if (this.dataFormat === \"channelsFirst\") {\n      channelAxis = 1;\n      depthAxis = 2;\n      heightAxis = 3;\n      widthAxis = 4;\n    } else {\n      channelAxis = 4;\n      depthAxis = 1;\n      heightAxis = 2;\n      widthAxis = 3;\n    }\n    const kernelD = this.kernelSize[0];\n    const kernelH = this.kernelSize[1];\n    const kernelW = this.kernelSize[2];\n    const strideD = this.strides[0];\n    const strideH = this.strides[1];\n    const strideW = this.strides[2];\n    outputShape[channelAxis] = this.filters;\n    outputShape[depthAxis] = deconvLength(outputShape[depthAxis], strideD, kernelD, this.padding);\n    outputShape[heightAxis] = deconvLength(outputShape[heightAxis], strideH, kernelH, this.padding);\n    outputShape[widthAxis] = deconvLength(outputShape[widthAxis], strideW, kernelW, this.padding);\n    return outputShape;\n  }\n  getConfig() {\n    const config = super.getConfig();\n    delete config[\"dilationRate\"];\n    return config;\n  }\n};\nConv3DTranspose.className = \"Conv3DTranspose\";\nserialization_exports.registerClass(Conv3DTranspose);\nvar SeparableConv = class extends Conv {\n  constructor(rank, config) {\n    super(rank, config);\n    this.DEFAULT_DEPTHWISE_INITIALIZER = \"glorotUniform\";\n    this.DEFAULT_POINTWISE_INITIALIZER = \"glorotUniform\";\n    this.depthwiseKernel = null;\n    this.pointwiseKernel = null;\n    if (config.filters == null) {\n      throw new ValueError(\"The `filters` configuration field is required by SeparableConv, but is unspecified.\");\n    }\n    if (config.kernelInitializer != null || config.kernelRegularizer != null || config.kernelConstraint != null) {\n      throw new ValueError(\"Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.\");\n    }\n    if (config.padding != null && config.padding !== \"same\" && config.padding !== \"valid\") {\n      throw new ValueError(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(config.padding)}`);\n    }\n    this.depthMultiplier = config.depthMultiplier == null ? 1 : config.depthMultiplier;\n    this.depthwiseInitializer = getInitializer(config.depthwiseInitializer || this.DEFAULT_DEPTHWISE_INITIALIZER);\n    this.depthwiseRegularizer = getRegularizer(config.depthwiseRegularizer);\n    this.depthwiseConstraint = getConstraint(config.depthwiseConstraint);\n    this.pointwiseInitializer = getInitializer(config.depthwiseInitializer || this.DEFAULT_POINTWISE_INITIALIZER);\n    this.pointwiseRegularizer = getRegularizer(config.pointwiseRegularizer);\n    this.pointwiseConstraint = getConstraint(config.pointwiseConstraint);\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    if (inputShape.length < this.rank + 2) {\n      throw new ValueError(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank + 2}, but received input shape: ${JSON.stringify(inputShape)}`);\n    }\n    const channelAxis = this.dataFormat === \"channelsFirst\" ? 1 : inputShape.length - 1;\n    if (inputShape[channelAxis] == null || inputShape[channelAxis] < 0) {\n      throw new ValueError(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(inputShape[channelAxis])}`);\n    }\n    const inputDim = inputShape[channelAxis];\n    const depthwiseKernelShape = this.kernelSize.concat([inputDim, this.depthMultiplier]);\n    const pointwiseKernelShape = [];\n    for (let i2 = 0; i2 < this.rank; ++i2) {\n      pointwiseKernelShape.push(1);\n    }\n    pointwiseKernelShape.push(inputDim * this.depthMultiplier, this.filters);\n    const trainable = true;\n    this.depthwiseKernel = this.addWeight(\"depthwise_kernel\", depthwiseKernelShape, \"float32\", this.depthwiseInitializer, this.depthwiseRegularizer, trainable, this.depthwiseConstraint);\n    this.pointwiseKernel = this.addWeight(\"pointwise_kernel\", pointwiseKernelShape, \"float32\", this.pointwiseInitializer, this.pointwiseRegularizer, trainable, this.pointwiseConstraint);\n    if (this.useBias) {\n      this.bias = this.addWeight(\"bias\", [this.filters], \"float32\", this.biasInitializer, this.biasRegularizer, trainable, this.biasConstraint);\n    } else {\n      this.bias = null;\n    }\n    this.inputSpec = [new InputSpec({ ndim: this.rank + 2, axes: { [channelAxis]: inputDim } })];\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = getExactlyOneTensor(inputs);\n      let output;\n      if (this.rank === 1) {\n        throw new NotImplementedError(\"1D separable convolution is not implemented yet.\");\n      } else if (this.rank === 2) {\n        if (this.dataFormat === \"channelsFirst\") {\n          inputs = transpose(inputs, [0, 2, 3, 1]);\n        }\n        output = separableConv2d(inputs, this.depthwiseKernel.read(), this.pointwiseKernel.read(), this.strides, this.padding, this.dilationRate, \"NHWC\");\n      }\n      if (this.useBias) {\n        output = biasAdd(output, this.bias.read(), this.dataFormat);\n      }\n      if (this.activation != null) {\n        output = this.activation.apply(output);\n      }\n      if (this.dataFormat === \"channelsFirst\") {\n        output = transpose(output, [0, 3, 1, 2]);\n      }\n      return output;\n    });\n  }\n  getConfig() {\n    const config = super.getConfig();\n    delete config[\"rank\"];\n    delete config[\"kernelInitializer\"];\n    delete config[\"kernelRegularizer\"];\n    delete config[\"kernelConstraint\"];\n    config[\"depthwiseInitializer\"] = serializeInitializer(this.depthwiseInitializer);\n    config[\"pointwiseInitializer\"] = serializeInitializer(this.pointwiseInitializer);\n    config[\"depthwiseRegularizer\"] = serializeRegularizer(this.depthwiseRegularizer);\n    config[\"pointwiseRegularizer\"] = serializeRegularizer(this.pointwiseRegularizer);\n    config[\"depthwiseConstraint\"] = serializeConstraint(this.depthwiseConstraint);\n    config[\"pointwiseConstraint\"] = serializeConstraint(this.pointwiseConstraint);\n    return config;\n  }\n};\nSeparableConv.className = \"SeparableConv\";\nvar SeparableConv2D = class extends SeparableConv {\n  constructor(args) {\n    super(2, args);\n  }\n};\nSeparableConv2D.className = \"SeparableConv2D\";\nserialization_exports.registerClass(SeparableConv2D);\nvar Conv1D = class extends Conv {\n  constructor(args) {\n    super(1, args);\n    Conv1D.verifyArgs(args);\n    this.inputSpec = [{ ndim: 3 }];\n  }\n  getConfig() {\n    const config = super.getConfig();\n    delete config[\"rank\"];\n    delete config[\"dataFormat\"];\n    return config;\n  }\n  static verifyArgs(args) {\n    if (typeof args.kernelSize !== \"number\" && !checkArrayTypeAndLength(args.kernelSize, \"number\", 1, 1)) {\n      throw new ValueError(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(args.kernelSize)}.`);\n    }\n  }\n};\nConv1D.className = \"Conv1D\";\nserialization_exports.registerClass(Conv1D);\nvar Cropping2D = class extends Layer {\n  constructor(args) {\n    super(args);\n    if (typeof args.cropping === \"number\") {\n      this.cropping = [[args.cropping, args.cropping], [args.cropping, args.cropping]];\n    } else if (typeof args.cropping[0] === \"number\") {\n      this.cropping = [\n        [args.cropping[0], args.cropping[0]],\n        [args.cropping[1], args.cropping[1]]\n      ];\n    } else {\n      this.cropping = args.cropping;\n    }\n    this.dataFormat = args.dataFormat === void 0 ? \"channelsLast\" : args.dataFormat;\n    this.inputSpec = [{ ndim: 4 }];\n  }\n  computeOutputShape(inputShape) {\n    if (this.dataFormat === \"channelsFirst\") {\n      return [\n        inputShape[0],\n        inputShape[1],\n        inputShape[2] - this.cropping[0][0] - this.cropping[0][1],\n        inputShape[3] - this.cropping[1][0] - this.cropping[1][1]\n      ];\n    } else {\n      return [\n        inputShape[0],\n        inputShape[1] - this.cropping[0][0] - this.cropping[0][1],\n        inputShape[2] - this.cropping[1][0] - this.cropping[1][1],\n        inputShape[3]\n      ];\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = getExactlyOneTensor(inputs);\n      if (this.dataFormat === \"channelsLast\") {\n        const hSliced = sliceAlongAxis(inputs, this.cropping[0][0], inputs.shape[1] - this.cropping[0][0] - this.cropping[0][1], 2);\n        return sliceAlongAxis(hSliced, this.cropping[1][0], inputs.shape[2] - this.cropping[1][1] - this.cropping[1][0], 3);\n      } else {\n        const hSliced = sliceAlongAxis(inputs, this.cropping[0][0], inputs.shape[2] - this.cropping[0][0] - this.cropping[0][1], 3);\n        return sliceAlongAxis(hSliced, this.cropping[1][0], inputs.shape[3] - this.cropping[1][1] - this.cropping[1][0], 4);\n      }\n    });\n  }\n  getConfig() {\n    const config = { cropping: this.cropping, dataFormat: this.dataFormat };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nCropping2D.className = \"Cropping2D\";\nserialization_exports.registerClass(Cropping2D);\nvar UpSampling2D = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.DEFAULT_SIZE = [2, 2];\n    this.inputSpec = [{ ndim: 4 }];\n    this.size = args.size == null ? this.DEFAULT_SIZE : args.size;\n    this.dataFormat = args.dataFormat == null ? \"channelsLast\" : args.dataFormat;\n    checkDataFormat(this.dataFormat);\n    this.interpolation = args.interpolation == null ? \"nearest\" : args.interpolation;\n    checkInterpolationFormat(this.interpolation);\n  }\n  computeOutputShape(inputShape) {\n    if (this.dataFormat === \"channelsFirst\") {\n      const height = inputShape[2] == null ? null : this.size[0] * inputShape[2];\n      const width = inputShape[3] == null ? null : this.size[1] * inputShape[3];\n      return [inputShape[0], inputShape[1], height, width];\n    } else {\n      const height = inputShape[1] == null ? null : this.size[0] * inputShape[1];\n      const width = inputShape[2] == null ? null : this.size[1] * inputShape[2];\n      return [inputShape[0], height, width, inputShape[3]];\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      let input2 = getExactlyOneTensor(inputs);\n      const inputShape = input2.shape;\n      if (this.dataFormat === \"channelsFirst\") {\n        input2 = transpose(input2, [0, 2, 3, 1]);\n        const height = this.size[0] * inputShape[2];\n        const width = this.size[1] * inputShape[3];\n        const resized = this.interpolation === \"nearest\" ? image.resizeNearestNeighbor(input2, [height, width]) : image.resizeBilinear(input2, [height, width]);\n        return transpose(resized, [0, 3, 1, 2]);\n      } else {\n        const height = this.size[0] * inputShape[1];\n        const width = this.size[1] * inputShape[2];\n        return this.interpolation === \"nearest\" ? image.resizeNearestNeighbor(input2, [height, width]) : image.resizeBilinear(input2, [height, width]);\n      }\n    });\n  }\n  getConfig() {\n    const config = {\n      size: this.size,\n      dataFormat: this.dataFormat,\n      interpolation: this.interpolation\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nUpSampling2D.className = \"UpSampling2D\";\nserialization_exports.registerClass(UpSampling2D);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/convolutional_depthwise.js\nfunction depthwiseConv2d3(x, depthwiseKernel, strides = [1, 1], padding = \"valid\", dataFormat, dilationRate) {\n  return tidy(() => {\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    checkDataFormat(dataFormat);\n    let y = preprocessConv2DInput(x, dataFormat);\n    if (x.rank !== 4) {\n      throw new ValueError(`Input for depthwiseConv2d is required to be 4-D, but is instead ${x.rank}-D`);\n    }\n    if (depthwiseKernel.rank !== 4) {\n      throw new ValueError(`depthwiseKernel is required to be 4-D, but is instead ${depthwiseKernel.rank}-D`);\n    }\n    y = depthwiseConv2d(y, depthwiseKernel, strides, padding === \"same\" ? \"same\" : \"valid\", \"NHWC\", dilationRate);\n    if (dataFormat === \"channelsFirst\") {\n      y = transpose(y, [0, 3, 1, 2]);\n    }\n    return y;\n  });\n}\nvar DepthwiseConv2D = class extends BaseConv {\n  constructor(args) {\n    super(2, args);\n    this.depthwiseKernel = null;\n    this.depthMultiplier = args.depthMultiplier == null ? 1 : args.depthMultiplier;\n    this.depthwiseInitializer = getInitializer(args.depthwiseInitializer || this.DEFAULT_KERNEL_INITIALIZER);\n    this.depthwiseConstraint = getConstraint(args.depthwiseConstraint);\n    this.depthwiseRegularizer = getRegularizer(args.depthwiseRegularizer);\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    if (inputShape.length < 4) {\n      throw new ValueError(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(inputShape)}.`);\n    }\n    const channelAxis = this.dataFormat === \"channelsFirst\" ? 1 : 3;\n    if (inputShape[channelAxis] == null || inputShape[channelAxis] < 0) {\n      throw new ValueError(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${inputShape[channelAxis]}).`);\n    }\n    const inputDim = inputShape[channelAxis];\n    const depthwiseKernelShape = [\n      this.kernelSize[0],\n      this.kernelSize[1],\n      inputDim,\n      this.depthMultiplier\n    ];\n    this.depthwiseKernel = this.addWeight(\"depthwise_kernel\", depthwiseKernelShape, null, this.depthwiseInitializer, this.depthwiseRegularizer, true, this.depthwiseConstraint);\n    if (this.useBias) {\n      this.bias = this.addWeight(\"bias\", [inputDim * this.depthMultiplier], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    } else {\n      this.bias = null;\n    }\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = getExactlyOneTensor(inputs);\n      let outputs = depthwiseConv2d3(inputs, this.depthwiseKernel.read(), this.strides, this.padding, this.dataFormat, null);\n      if (this.useBias) {\n        outputs = biasAdd(outputs, this.bias.read(), this.dataFormat);\n      }\n      if (this.activation != null) {\n        outputs = this.activation.apply(outputs);\n      }\n      return outputs;\n    });\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const rows = this.dataFormat === \"channelsFirst\" ? inputShape[2] : inputShape[1];\n    const cols = this.dataFormat === \"channelsFirst\" ? inputShape[3] : inputShape[2];\n    const outFilters = this.dataFormat === \"channelsFirst\" ? inputShape[1] * this.depthMultiplier : inputShape[3] * this.depthMultiplier;\n    const outRows = convOutputLength(rows, this.kernelSize[0], this.padding, this.strides[0]);\n    const outCols = convOutputLength(cols, this.kernelSize[1], this.padding, this.strides[1]);\n    if (this.dataFormat === \"channelsFirst\") {\n      return [inputShape[0], outFilters, outRows, outCols];\n    } else {\n      return [inputShape[0], outRows, outCols, outFilters];\n    }\n  }\n  getConfig() {\n    const config = super.getConfig();\n    config[\"depthMultiplier\"] = this.depthMultiplier;\n    config[\"depthwiseInitializer\"] = serializeInitializer(this.depthwiseInitializer);\n    config[\"depthwiseRegularizer\"] = serializeRegularizer(this.depthwiseRegularizer);\n    config[\"depthwiseConstraint\"] = serializeConstraint(this.depthwiseRegularizer);\n    return config;\n  }\n};\nDepthwiseConv2D.className = \"DepthwiseConv2D\";\nserialization_exports.registerClass(DepthwiseConv2D);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/recurrent.js\nfunction standardizeArgs(inputs, initialState, constants, numConstants) {\n  if (Array.isArray(inputs)) {\n    if (initialState != null || constants != null) {\n      throw new ValueError(\"When inputs is an array, neither initialState or constants should be provided\");\n    }\n    if (numConstants != null) {\n      constants = inputs.slice(inputs.length - numConstants, inputs.length);\n      inputs = inputs.slice(0, inputs.length - numConstants);\n    }\n    if (inputs.length > 1) {\n      initialState = inputs.slice(1, inputs.length);\n    }\n    inputs = inputs[0];\n  }\n  function toListOrNull(x) {\n    if (x == null || Array.isArray(x)) {\n      return x;\n    } else {\n      return [x];\n    }\n  }\n  initialState = toListOrNull(initialState);\n  constants = toListOrNull(constants);\n  return { inputs, initialState, constants };\n}\nfunction rnn(stepFunction, inputs, initialStates, goBackwards = false, mask, constants, unroll = false, needPerStepOutputs = false) {\n  return tidy(() => {\n    const ndim = inputs.shape.length;\n    if (ndim < 3) {\n      throw new ValueError(`Input should be at least 3D, but is ${ndim}D.`);\n    }\n    const axes = [1, 0].concat(range2(2, ndim));\n    inputs = transpose(inputs, axes);\n    if (constants != null) {\n      throw new NotImplementedError(\"The rnn() functoin of the deeplearn.js backend does not support constants yet.\");\n    }\n    if (unroll) {\n      console.warn(\"Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend.\");\n    }\n    if (mask != null) {\n      mask = cast(cast(mask, \"bool\"), \"float32\");\n      if (mask.rank === ndim - 1) {\n        mask = expandDims(mask, -1);\n      }\n      mask = transpose(mask, axes);\n    }\n    if (goBackwards) {\n      inputs = reverse(inputs, 0);\n      if (mask != null) {\n        mask = reverse(mask, 0);\n      }\n    }\n    const perStepOutputs = [];\n    let lastOutput;\n    let states = initialStates;\n    const timeSteps = inputs.shape[0];\n    const perStepInputs = unstack(inputs);\n    let perStepMasks;\n    if (mask != null) {\n      perStepMasks = unstack(mask);\n    }\n    for (let t2 = 0; t2 < timeSteps; ++t2) {\n      const currentInput = perStepInputs[t2];\n      const stepOutputs = tidy(() => stepFunction(currentInput, states));\n      if (mask == null) {\n        lastOutput = stepOutputs[0];\n        states = stepOutputs[1];\n      } else {\n        const maskedOutputs = tidy(() => {\n          const stepMask = perStepMasks[t2];\n          const negStepMask = sub(onesLike(stepMask), stepMask);\n          const output = add2(mul(stepOutputs[0], stepMask), mul(states[0], negStepMask));\n          const newStates = states.map((state, i2) => {\n            return add2(mul(stepOutputs[1][i2], stepMask), mul(state, negStepMask));\n          });\n          return { output, newStates };\n        });\n        lastOutput = maskedOutputs.output;\n        states = maskedOutputs.newStates;\n      }\n      if (needPerStepOutputs) {\n        perStepOutputs.push(lastOutput);\n      }\n    }\n    let outputs;\n    if (needPerStepOutputs) {\n      const axis = 1;\n      outputs = stack(perStepOutputs, axis);\n    }\n    return [lastOutput, outputs, states];\n  });\n}\nvar RNN = class extends Layer {\n  constructor(args) {\n    super(args);\n    let cell;\n    if (args.cell == null) {\n      throw new ValueError(\"cell property is missing for the constructor of RNN.\");\n    } else if (Array.isArray(args.cell)) {\n      cell = new StackedRNNCells({ cells: args.cell });\n    } else {\n      cell = args.cell;\n    }\n    if (cell.stateSize == null) {\n      throw new ValueError(\"The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).\");\n    }\n    this.cell = cell;\n    this.returnSequences = args.returnSequences == null ? false : args.returnSequences;\n    this.returnState = args.returnState == null ? false : args.returnState;\n    this.goBackwards = args.goBackwards == null ? false : args.goBackwards;\n    this._stateful = args.stateful == null ? false : args.stateful;\n    this.unroll = args.unroll == null ? false : args.unroll;\n    this.supportsMasking = true;\n    this.inputSpec = [new InputSpec({ ndim: 3 })];\n    this.stateSpec = null;\n    this.states_ = null;\n    this.numConstants = null;\n    this.keptStates = [];\n  }\n  getStates() {\n    if (this.states_ == null) {\n      const numStates = Array.isArray(this.cell.stateSize) ? this.cell.stateSize.length : 1;\n      return range2(0, numStates).map((x) => null);\n    } else {\n      return this.states_;\n    }\n  }\n  setStates(states) {\n    this.states_ = states;\n  }\n  computeOutputShape(inputShape) {\n    if (isArrayOfShapes(inputShape)) {\n      inputShape = inputShape[0];\n    }\n    inputShape = inputShape;\n    let stateSize = this.cell.stateSize;\n    if (!Array.isArray(stateSize)) {\n      stateSize = [stateSize];\n    }\n    const outputDim = stateSize[0];\n    let outputShape;\n    if (this.returnSequences) {\n      outputShape = [inputShape[0], inputShape[1], outputDim];\n    } else {\n      outputShape = [inputShape[0], outputDim];\n    }\n    if (this.returnState) {\n      const stateShape = [];\n      for (const dim of stateSize) {\n        stateShape.push([inputShape[0], dim]);\n      }\n      return [outputShape].concat(stateShape);\n    } else {\n      return outputShape;\n    }\n  }\n  computeMask(inputs, mask) {\n    return tidy(() => {\n      if (Array.isArray(mask)) {\n        mask = mask[0];\n      }\n      const outputMask = this.returnSequences ? mask : null;\n      if (this.returnState) {\n        const stateMask = this.states.map((s2) => null);\n        return [outputMask].concat(stateMask);\n      } else {\n        return outputMask;\n      }\n    });\n  }\n  get states() {\n    if (this.states_ == null) {\n      const numStates = Array.isArray(this.cell.stateSize) ? this.cell.stateSize.length : 1;\n      const output = [];\n      for (let i2 = 0; i2 < numStates; ++i2) {\n        output.push(null);\n      }\n      return output;\n    } else {\n      return this.states_;\n    }\n  }\n  set states(s2) {\n    this.states_ = s2;\n  }\n  build(inputShape) {\n    const constantShape = null;\n    if (this.numConstants != null) {\n      throw new NotImplementedError(\"Constants support is not implemented in RNN yet.\");\n    }\n    if (isArrayOfShapes(inputShape)) {\n      inputShape = inputShape[0];\n    }\n    inputShape = inputShape;\n    const batchSize = this.stateful ? inputShape[0] : null;\n    const inputDim = inputShape.slice(2);\n    this.inputSpec[0] = new InputSpec({ shape: [batchSize, null, ...inputDim] });\n    const stepInputShape = [inputShape[0]].concat(inputShape.slice(2));\n    if (constantShape != null) {\n      throw new NotImplementedError(\"Constants support is not implemented in RNN yet.\");\n    } else {\n      this.cell.build(stepInputShape);\n    }\n    let stateSize;\n    if (Array.isArray(this.cell.stateSize)) {\n      stateSize = this.cell.stateSize;\n    } else {\n      stateSize = [this.cell.stateSize];\n    }\n    if (this.stateSpec != null) {\n      if (!util_exports.arraysEqual(this.stateSpec.map((spec) => spec.shape[spec.shape.length - 1]), stateSize)) {\n        throw new ValueError(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`);\n      }\n    } else {\n      this.stateSpec = stateSize.map((dim) => new InputSpec({ shape: [null, dim] }));\n    }\n    if (this.stateful) {\n      this.resetStates();\n    }\n  }\n  resetStates(states, training = false) {\n    tidy(() => {\n      if (!this.stateful) {\n        throw new AttributeError(\"Cannot call resetStates() on an RNN Layer that is not stateful.\");\n      }\n      const batchSize = this.inputSpec[0].shape[0];\n      if (batchSize == null) {\n        throw new ValueError(\"If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \\n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.\");\n      }\n      if (this.states_ == null) {\n        if (Array.isArray(this.cell.stateSize)) {\n          this.states_ = this.cell.stateSize.map((dim) => zeros([batchSize, dim]));\n        } else {\n          this.states_ = [zeros([batchSize, this.cell.stateSize])];\n        }\n      } else if (states == null) {\n        dispose(this.states_);\n        if (this.keptStates != null) {\n          dispose(this.keptStates);\n          this.keptStates = [];\n        }\n        if (Array.isArray(this.cell.stateSize)) {\n          this.states_ = this.cell.stateSize.map((dim) => zeros([batchSize, dim]));\n        } else {\n          this.states_[0] = zeros([batchSize, this.cell.stateSize]);\n        }\n      } else {\n        if (!Array.isArray(states)) {\n          states = [states];\n        }\n        if (states.length !== this.states_.length) {\n          throw new ValueError(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${states.length} state value(s). Input received: ${states}`);\n        }\n        if (training === true) {\n          this.keptStates.push(this.states_.slice());\n        } else {\n          dispose(this.states_);\n        }\n        for (let index = 0; index < this.states_.length; ++index) {\n          const value = states[index];\n          const dim = Array.isArray(this.cell.stateSize) ? this.cell.stateSize[index] : this.cell.stateSize;\n          const expectedShape = [batchSize, dim];\n          if (!util_exports.arraysEqual(value.shape, expectedShape)) {\n            throw new ValueError(`State ${index} is incompatible with layer ${this.name}: expected shape=${expectedShape}, received shape=${value.shape}`);\n          }\n          this.states_[index] = value;\n        }\n      }\n      this.states_ = this.states_.map((state) => keep(state.clone()));\n    });\n  }\n  apply(inputs, kwargs) {\n    let initialState = kwargs == null ? null : kwargs[\"initialState\"];\n    let constants = kwargs == null ? null : kwargs[\"constants\"];\n    if (kwargs == null) {\n      kwargs = {};\n    }\n    const standardized = standardizeArgs(inputs, initialState, constants, this.numConstants);\n    inputs = standardized.inputs;\n    initialState = standardized.initialState;\n    constants = standardized.constants;\n    let additionalInputs = [];\n    let additionalSpecs = [];\n    if (initialState != null) {\n      kwargs[\"initialState\"] = initialState;\n      additionalInputs = additionalInputs.concat(initialState);\n      this.stateSpec = [];\n      for (const state of initialState) {\n        this.stateSpec.push(new InputSpec({ shape: state.shape }));\n      }\n      additionalSpecs = additionalSpecs.concat(this.stateSpec);\n    }\n    if (constants != null) {\n      kwargs[\"constants\"] = constants;\n      additionalInputs = additionalInputs.concat(constants);\n      this.numConstants = constants.length;\n    }\n    const isTensor = additionalInputs[0] instanceof SymbolicTensor;\n    if (isTensor) {\n      const fullInput = [inputs].concat(additionalInputs);\n      const fullInputSpec = this.inputSpec.concat(additionalSpecs);\n      const originalInputSpec = this.inputSpec;\n      this.inputSpec = fullInputSpec;\n      const output = super.apply(fullInput, kwargs);\n      this.inputSpec = originalInputSpec;\n      return output;\n    } else {\n      return super.apply(inputs, kwargs);\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const mask = kwargs == null ? null : kwargs[\"mask\"];\n      const training = kwargs == null ? null : kwargs[\"training\"];\n      let initialState = kwargs == null ? null : kwargs[\"initialState\"];\n      inputs = getExactlyOneTensor(inputs);\n      if (initialState == null) {\n        if (this.stateful) {\n          initialState = this.states_;\n        } else {\n          initialState = this.getInitialState(inputs);\n        }\n      }\n      const numStates = Array.isArray(this.cell.stateSize) ? this.cell.stateSize.length : 1;\n      if (initialState.length !== numStates) {\n        throw new ValueError(`RNN Layer has ${numStates} state(s) but was passed ${initialState.length} initial state(s).`);\n      }\n      if (this.unroll) {\n        console.warn(\"Ignoring unroll = true for RNN layer, due to imperative backend.\");\n      }\n      const cellCallKwargs = { training };\n      const step5 = (inputs2, states2) => {\n        const outputs2 = this.cell.call([inputs2].concat(states2), cellCallKwargs);\n        return [outputs2[0], outputs2.slice(1)];\n      };\n      const rnnOutputs = rnn(step5, inputs, initialState, this.goBackwards, mask, null, this.unroll, this.returnSequences);\n      const lastOutput = rnnOutputs[0];\n      const outputs = rnnOutputs[1];\n      const states = rnnOutputs[2];\n      if (this.stateful) {\n        this.resetStates(states, training);\n      }\n      const output = this.returnSequences ? outputs : lastOutput;\n      if (this.returnState) {\n        return [output].concat(states);\n      } else {\n        return output;\n      }\n    });\n  }\n  getInitialState(inputs) {\n    return tidy(() => {\n      let initialState = zeros(inputs.shape);\n      initialState = sum2(initialState, [1, 2]);\n      initialState = expandDims2(initialState);\n      if (Array.isArray(this.cell.stateSize)) {\n        return this.cell.stateSize.map((dim) => dim > 1 ? tile2(initialState, [1, dim]) : initialState);\n      } else {\n        return this.cell.stateSize > 1 ? [tile2(initialState, [1, this.cell.stateSize])] : [initialState];\n      }\n    });\n  }\n  get trainableWeights() {\n    if (!this.trainable) {\n      return [];\n    }\n    return this.cell.trainableWeights;\n  }\n  get nonTrainableWeights() {\n    if (!this.trainable) {\n      return this.cell.weights;\n    }\n    return this.cell.nonTrainableWeights;\n  }\n  setFastWeightInitDuringBuild(value) {\n    super.setFastWeightInitDuringBuild(value);\n    if (this.cell != null) {\n      this.cell.setFastWeightInitDuringBuild(value);\n    }\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = {\n      returnSequences: this.returnSequences,\n      returnState: this.returnState,\n      goBackwards: this.goBackwards,\n      stateful: this.stateful,\n      unroll: this.unroll\n    };\n    if (this.numConstants != null) {\n      config[\"numConstants\"] = this.numConstants;\n    }\n    const cellConfig = this.cell.getConfig();\n    if (this.getClassName() === RNN.className) {\n      config[\"cell\"] = {\n        \"className\": this.cell.getClassName(),\n        \"config\": cellConfig\n      };\n    }\n    return Object.assign({}, cellConfig, baseConfig, config);\n  }\n  static fromConfig(cls, config, customObjects = {}) {\n    const cellConfig = config[\"cell\"];\n    const cell = deserialize(cellConfig, customObjects);\n    return new cls(Object.assign(config, { cell }));\n  }\n};\nRNN.className = \"RNN\";\nserialization_exports.registerClass(RNN);\nvar RNNCell = class extends Layer {\n};\nvar SimpleRNNCell = class extends RNNCell {\n  constructor(args) {\n    super(args);\n    this.DEFAULT_ACTIVATION = \"tanh\";\n    this.DEFAULT_KERNEL_INITIALIZER = \"glorotNormal\";\n    this.DEFAULT_RECURRENT_INITIALIZER = \"orthogonal\";\n    this.DEFAULT_BIAS_INITIALIZER = \"zeros\";\n    this.units = args.units;\n    assertPositiveInteger(this.units, `units`);\n    this.activation = getActivation(args.activation == null ? this.DEFAULT_ACTIVATION : args.activation);\n    this.useBias = args.useBias == null ? true : args.useBias;\n    this.kernelInitializer = getInitializer(args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER);\n    this.recurrentInitializer = getInitializer(args.recurrentInitializer || this.DEFAULT_RECURRENT_INITIALIZER);\n    this.biasInitializer = getInitializer(args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER);\n    this.kernelRegularizer = getRegularizer(args.kernelRegularizer);\n    this.recurrentRegularizer = getRegularizer(args.recurrentRegularizer);\n    this.biasRegularizer = getRegularizer(args.biasRegularizer);\n    this.kernelConstraint = getConstraint(args.kernelConstraint);\n    this.recurrentConstraint = getConstraint(args.recurrentConstraint);\n    this.biasConstraint = getConstraint(args.biasConstraint);\n    this.dropout = min2([1, max2([0, args.dropout == null ? 0 : args.dropout])]);\n    this.recurrentDropout = min2([\n      1,\n      max2([0, args.recurrentDropout == null ? 0 : args.recurrentDropout])\n    ]);\n    this.dropoutFunc = args.dropoutFunc;\n    this.stateSize = this.units;\n    this.dropoutMask = null;\n    this.recurrentDropoutMask = null;\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    this.kernel = this.addWeight(\"kernel\", [inputShape[inputShape.length - 1], this.units], null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n    this.recurrentKernel = this.addWeight(\"recurrent_kernel\", [this.units, this.units], null, this.recurrentInitializer, this.recurrentRegularizer, true, this.recurrentConstraint);\n    if (this.useBias) {\n      this.bias = this.addWeight(\"bias\", [this.units], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    } else {\n      this.bias = null;\n    }\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = inputs;\n      if (inputs.length !== 2) {\n        throw new ValueError(`SimpleRNNCell expects 2 input Tensors, got ${inputs.length}.`);\n      }\n      let prevOutput = inputs[1];\n      inputs = inputs[0];\n      const training = kwargs[\"training\"] == null ? false : kwargs[\"training\"];\n      if (0 < this.dropout && this.dropout < 1 && this.dropoutMask == null) {\n        this.dropoutMask = generateDropoutMask({\n          ones: () => onesLike(inputs),\n          rate: this.dropout,\n          training,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      if (0 < this.recurrentDropout && this.recurrentDropout < 1 && this.recurrentDropoutMask == null) {\n        this.recurrentDropoutMask = generateDropoutMask({\n          ones: () => onesLike(prevOutput),\n          rate: this.recurrentDropout,\n          training,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      let h;\n      const dpMask = this.dropoutMask;\n      const recDpMask = this.recurrentDropoutMask;\n      if (dpMask != null) {\n        h = dot2(mul(inputs, dpMask), this.kernel.read());\n      } else {\n        h = dot2(inputs, this.kernel.read());\n      }\n      if (this.bias != null) {\n        h = biasAdd(h, this.bias.read());\n      }\n      if (recDpMask != null) {\n        prevOutput = mul(prevOutput, recDpMask);\n      }\n      let output = add2(h, dot2(prevOutput, this.recurrentKernel.read()));\n      if (this.activation != null) {\n        output = this.activation.apply(output);\n      }\n      return [output, output];\n    });\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = {\n      units: this.units,\n      activation: serializeActivation(this.activation),\n      useBias: this.useBias,\n      kernelInitializer: serializeInitializer(this.kernelInitializer),\n      recurrentInitializer: serializeInitializer(this.recurrentInitializer),\n      biasInitializer: serializeInitializer(this.biasInitializer),\n      kernelRegularizer: serializeRegularizer(this.kernelRegularizer),\n      recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),\n      biasRegularizer: serializeRegularizer(this.biasRegularizer),\n      activityRegularizer: serializeRegularizer(this.activityRegularizer),\n      kernelConstraint: serializeConstraint(this.kernelConstraint),\n      recurrentConstraint: serializeConstraint(this.recurrentConstraint),\n      biasConstraint: serializeConstraint(this.biasConstraint),\n      dropout: this.dropout,\n      recurrentDropout: this.recurrentDropout\n    };\n    return Object.assign({}, baseConfig, config);\n  }\n};\nSimpleRNNCell.className = \"SimpleRNNCell\";\nserialization_exports.registerClass(SimpleRNNCell);\nvar SimpleRNN = class extends RNN {\n  constructor(args) {\n    args.cell = new SimpleRNNCell(args);\n    super(args);\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      if (this.cell.dropoutMask != null) {\n        dispose(this.cell.dropoutMask);\n        this.cell.dropoutMask = null;\n      }\n      if (this.cell.recurrentDropoutMask != null) {\n        dispose(this.cell.recurrentDropoutMask);\n        this.cell.recurrentDropoutMask = null;\n      }\n      const mask = kwargs == null ? null : kwargs[\"mask\"];\n      const training = kwargs == null ? null : kwargs[\"training\"];\n      const initialState = kwargs == null ? null : kwargs[\"initialState\"];\n      return super.call(inputs, { mask, training, initialState });\n    });\n  }\n  static fromConfig(cls, config) {\n    return new cls(config);\n  }\n};\nSimpleRNN.className = \"SimpleRNN\";\nserialization_exports.registerClass(SimpleRNN);\nvar GRUCell = class extends RNNCell {\n  constructor(args) {\n    super(args);\n    this.DEFAULT_ACTIVATION = \"tanh\";\n    this.DEFAULT_RECURRENT_ACTIVATION = \"hardSigmoid\";\n    this.DEFAULT_KERNEL_INITIALIZER = \"glorotNormal\";\n    this.DEFAULT_RECURRENT_INITIALIZER = \"orthogonal\";\n    this.DEFAULT_BIAS_INITIALIZER = \"zeros\";\n    if (args.resetAfter) {\n      throw new ValueError(`GRUCell does not support reset_after parameter set to true.`);\n    }\n    this.units = args.units;\n    assertPositiveInteger(this.units, \"units\");\n    this.activation = getActivation(args.activation === void 0 ? this.DEFAULT_ACTIVATION : args.activation);\n    this.recurrentActivation = getActivation(args.recurrentActivation === void 0 ? this.DEFAULT_RECURRENT_ACTIVATION : args.recurrentActivation);\n    this.useBias = args.useBias == null ? true : args.useBias;\n    this.kernelInitializer = getInitializer(args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER);\n    this.recurrentInitializer = getInitializer(args.recurrentInitializer || this.DEFAULT_RECURRENT_INITIALIZER);\n    this.biasInitializer = getInitializer(args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER);\n    this.kernelRegularizer = getRegularizer(args.kernelRegularizer);\n    this.recurrentRegularizer = getRegularizer(args.recurrentRegularizer);\n    this.biasRegularizer = getRegularizer(args.biasRegularizer);\n    this.kernelConstraint = getConstraint(args.kernelConstraint);\n    this.recurrentConstraint = getConstraint(args.recurrentConstraint);\n    this.biasConstraint = getConstraint(args.biasConstraint);\n    this.dropout = min2([1, max2([0, args.dropout == null ? 0 : args.dropout])]);\n    this.recurrentDropout = min2([\n      1,\n      max2([0, args.recurrentDropout == null ? 0 : args.recurrentDropout])\n    ]);\n    this.dropoutFunc = args.dropoutFunc;\n    this.implementation = args.implementation;\n    this.stateSize = this.units;\n    this.dropoutMask = null;\n    this.recurrentDropoutMask = null;\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const inputDim = inputShape[inputShape.length - 1];\n    this.kernel = this.addWeight(\"kernel\", [inputDim, this.units * 3], null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n    this.recurrentKernel = this.addWeight(\"recurrent_kernel\", [this.units, this.units * 3], null, this.recurrentInitializer, this.recurrentRegularizer, true, this.recurrentConstraint);\n    if (this.useBias) {\n      this.bias = this.addWeight(\"bias\", [this.units * 3], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    } else {\n      this.bias = null;\n    }\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = inputs;\n      if (inputs.length !== 2) {\n        throw new ValueError(`GRUCell expects 2 input Tensors (inputs, h, c), got ${inputs.length}.`);\n      }\n      const training = kwargs[\"training\"] == null ? false : kwargs[\"training\"];\n      let hTMinus1 = inputs[1];\n      inputs = inputs[0];\n      if (0 < this.dropout && this.dropout < 1 && this.dropoutMask == null) {\n        this.dropoutMask = generateDropoutMask({\n          ones: () => onesLike(inputs),\n          rate: this.dropout,\n          training,\n          count: 3,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      if (0 < this.recurrentDropout && this.recurrentDropout < 1 && this.recurrentDropoutMask == null) {\n        this.recurrentDropoutMask = generateDropoutMask({\n          ones: () => onesLike(hTMinus1),\n          rate: this.recurrentDropout,\n          training,\n          count: 3,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      const dpMask = this.dropoutMask;\n      const recDpMask = this.recurrentDropoutMask;\n      let z;\n      let r2;\n      let hh;\n      if (0 < this.dropout && this.dropout < 1) {\n        inputs = mul(inputs, dpMask[0]);\n      }\n      let matrixX = dot2(inputs, this.kernel.read());\n      if (this.useBias) {\n        matrixX = biasAdd(matrixX, this.bias.read());\n      }\n      if (0 < this.recurrentDropout && this.recurrentDropout < 1) {\n        hTMinus1 = mul(hTMinus1, recDpMask[0]);\n      }\n      const recurrentKernelValue = this.recurrentKernel.read();\n      const [rk1, rk2] = split(recurrentKernelValue, [2 * this.units, this.units], recurrentKernelValue.rank - 1);\n      const matrixInner = dot2(hTMinus1, rk1);\n      const [xZ, xR, xH] = split(matrixX, 3, matrixX.rank - 1);\n      const [recurrentZ, recurrentR] = split(matrixInner, 2, matrixInner.rank - 1);\n      z = this.recurrentActivation.apply(add2(xZ, recurrentZ));\n      r2 = this.recurrentActivation.apply(add2(xR, recurrentR));\n      const recurrentH = dot2(mul(r2, hTMinus1), rk2);\n      hh = this.activation.apply(add2(xH, recurrentH));\n      const h = add2(mul(z, hTMinus1), mul(add2(1, neg(z)), hh));\n      return [h, h];\n    });\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = {\n      units: this.units,\n      activation: serializeActivation(this.activation),\n      recurrentActivation: serializeActivation(this.recurrentActivation),\n      useBias: this.useBias,\n      kernelInitializer: serializeInitializer(this.kernelInitializer),\n      recurrentInitializer: serializeInitializer(this.recurrentInitializer),\n      biasInitializer: serializeInitializer(this.biasInitializer),\n      kernelRegularizer: serializeRegularizer(this.kernelRegularizer),\n      recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),\n      biasRegularizer: serializeRegularizer(this.biasRegularizer),\n      activityRegularizer: serializeRegularizer(this.activityRegularizer),\n      kernelConstraint: serializeConstraint(this.kernelConstraint),\n      recurrentConstraint: serializeConstraint(this.recurrentConstraint),\n      biasConstraint: serializeConstraint(this.biasConstraint),\n      dropout: this.dropout,\n      recurrentDropout: this.recurrentDropout,\n      implementation: this.implementation,\n      resetAfter: false\n    };\n    return Object.assign({}, baseConfig, config);\n  }\n};\nGRUCell.className = \"GRUCell\";\nserialization_exports.registerClass(GRUCell);\nvar GRU = class extends RNN {\n  constructor(args) {\n    if (args.implementation === 0) {\n      console.warn(\"`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call.\");\n    }\n    args.cell = new GRUCell(args);\n    super(args);\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      if (this.cell.dropoutMask != null) {\n        dispose(this.cell.dropoutMask);\n        this.cell.dropoutMask = null;\n      }\n      if (this.cell.recurrentDropoutMask != null) {\n        dispose(this.cell.recurrentDropoutMask);\n        this.cell.recurrentDropoutMask = null;\n      }\n      const mask = kwargs == null ? null : kwargs[\"mask\"];\n      const training = kwargs == null ? null : kwargs[\"training\"];\n      const initialState = kwargs == null ? null : kwargs[\"initialState\"];\n      return super.call(inputs, { mask, training, initialState });\n    });\n  }\n  static fromConfig(cls, config) {\n    if (config[\"implmentation\"] === 0) {\n      config[\"implementation\"] = 1;\n    }\n    return new cls(config);\n  }\n};\nGRU.className = \"GRU\";\nserialization_exports.registerClass(GRU);\nvar LSTMCell = class extends RNNCell {\n  constructor(args) {\n    super(args);\n    this.DEFAULT_ACTIVATION = \"tanh\";\n    this.DEFAULT_RECURRENT_ACTIVATION = \"hardSigmoid\";\n    this.DEFAULT_KERNEL_INITIALIZER = \"glorotNormal\";\n    this.DEFAULT_RECURRENT_INITIALIZER = \"orthogonal\";\n    this.DEFAULT_BIAS_INITIALIZER = \"zeros\";\n    this.units = args.units;\n    assertPositiveInteger(this.units, \"units\");\n    this.activation = getActivation(args.activation === void 0 ? this.DEFAULT_ACTIVATION : args.activation);\n    this.recurrentActivation = getActivation(args.recurrentActivation === void 0 ? this.DEFAULT_RECURRENT_ACTIVATION : args.recurrentActivation);\n    this.useBias = args.useBias == null ? true : args.useBias;\n    this.kernelInitializer = getInitializer(args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER);\n    this.recurrentInitializer = getInitializer(args.recurrentInitializer || this.DEFAULT_RECURRENT_INITIALIZER);\n    this.biasInitializer = getInitializer(args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER);\n    this.unitForgetBias = args.unitForgetBias;\n    this.kernelRegularizer = getRegularizer(args.kernelRegularizer);\n    this.recurrentRegularizer = getRegularizer(args.recurrentRegularizer);\n    this.biasRegularizer = getRegularizer(args.biasRegularizer);\n    this.kernelConstraint = getConstraint(args.kernelConstraint);\n    this.recurrentConstraint = getConstraint(args.recurrentConstraint);\n    this.biasConstraint = getConstraint(args.biasConstraint);\n    this.dropout = min2([1, max2([0, args.dropout == null ? 0 : args.dropout])]);\n    this.recurrentDropout = min2([\n      1,\n      max2([0, args.recurrentDropout == null ? 0 : args.recurrentDropout])\n    ]);\n    this.dropoutFunc = args.dropoutFunc;\n    this.implementation = args.implementation;\n    this.stateSize = [this.units, this.units];\n    this.dropoutMask = null;\n    this.recurrentDropoutMask = null;\n  }\n  build(inputShape) {\n    var _a;\n    inputShape = getExactlyOneShape(inputShape);\n    const inputDim = inputShape[inputShape.length - 1];\n    this.kernel = this.addWeight(\"kernel\", [inputDim, this.units * 4], null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n    this.recurrentKernel = this.addWeight(\"recurrent_kernel\", [this.units, this.units * 4], null, this.recurrentInitializer, this.recurrentRegularizer, true, this.recurrentConstraint);\n    let biasInitializer;\n    if (this.useBias) {\n      if (this.unitForgetBias) {\n        const capturedBiasInit = this.biasInitializer;\n        const capturedUnits = this.units;\n        biasInitializer = new (_a = class CustomInit extends Initializer {\n          apply(shape, dtype) {\n            const bI = capturedBiasInit.apply([capturedUnits]);\n            const bF = new Ones().apply([capturedUnits]);\n            const bCAndH = capturedBiasInit.apply([capturedUnits * 2]);\n            return concatAlongFirstAxis(concatAlongFirstAxis(bI, bF), bCAndH);\n          }\n        }, _a.className = \"CustomInit\", _a)();\n      } else {\n        biasInitializer = this.biasInitializer;\n      }\n      this.bias = this.addWeight(\"bias\", [this.units * 4], null, biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    } else {\n      this.bias = null;\n    }\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const training = kwargs[\"training\"] == null ? false : kwargs[\"training\"];\n      inputs = inputs;\n      if (inputs.length !== 3) {\n        throw new ValueError(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${inputs.length}.`);\n      }\n      let hTMinus1 = inputs[1];\n      const cTMinus1 = inputs[2];\n      inputs = inputs[0];\n      if (0 < this.dropout && this.dropout < 1 && this.dropoutMask == null) {\n        this.dropoutMask = generateDropoutMask({\n          ones: () => onesLike(inputs),\n          rate: this.dropout,\n          training,\n          count: 4,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      if (0 < this.recurrentDropout && this.recurrentDropout < 1 && this.recurrentDropoutMask == null) {\n        this.recurrentDropoutMask = generateDropoutMask({\n          ones: () => onesLike(hTMinus1),\n          rate: this.recurrentDropout,\n          training,\n          count: 4,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      const dpMask = this.dropoutMask;\n      const recDpMask = this.recurrentDropoutMask;\n      let i2;\n      let f;\n      let c;\n      let o;\n      if (0 < this.dropout && this.dropout < 1) {\n        inputs = mul(inputs, dpMask[0]);\n      }\n      let z = dot2(inputs, this.kernel.read());\n      if (0 < this.recurrentDropout && this.recurrentDropout < 1) {\n        hTMinus1 = mul(hTMinus1, recDpMask[0]);\n      }\n      z = add2(z, dot2(hTMinus1, this.recurrentKernel.read()));\n      if (this.useBias) {\n        z = biasAdd(z, this.bias.read());\n      }\n      const [z0, z1, z2, z3] = split(z, 4, z.rank - 1);\n      i2 = this.recurrentActivation.apply(z0);\n      f = this.recurrentActivation.apply(z1);\n      c = add2(mul(f, cTMinus1), mul(i2, this.activation.apply(z2)));\n      o = this.recurrentActivation.apply(z3);\n      const h = mul(o, this.activation.apply(c));\n      return [h, h, c];\n    });\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = {\n      units: this.units,\n      activation: serializeActivation(this.activation),\n      recurrentActivation: serializeActivation(this.recurrentActivation),\n      useBias: this.useBias,\n      kernelInitializer: serializeInitializer(this.kernelInitializer),\n      recurrentInitializer: serializeInitializer(this.recurrentInitializer),\n      biasInitializer: serializeInitializer(this.biasInitializer),\n      unitForgetBias: this.unitForgetBias,\n      kernelRegularizer: serializeRegularizer(this.kernelRegularizer),\n      recurrentRegularizer: serializeRegularizer(this.recurrentRegularizer),\n      biasRegularizer: serializeRegularizer(this.biasRegularizer),\n      activityRegularizer: serializeRegularizer(this.activityRegularizer),\n      kernelConstraint: serializeConstraint(this.kernelConstraint),\n      recurrentConstraint: serializeConstraint(this.recurrentConstraint),\n      biasConstraint: serializeConstraint(this.biasConstraint),\n      dropout: this.dropout,\n      recurrentDropout: this.recurrentDropout,\n      implementation: this.implementation\n    };\n    return Object.assign({}, baseConfig, config);\n  }\n};\nLSTMCell.className = \"LSTMCell\";\nserialization_exports.registerClass(LSTMCell);\nvar LSTM = class extends RNN {\n  constructor(args) {\n    if (args.implementation === 0) {\n      console.warn(\"`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call.\");\n    }\n    args.cell = new LSTMCell(args);\n    super(args);\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      if (this.cell.dropoutMask != null) {\n        dispose(this.cell.dropoutMask);\n        this.cell.dropoutMask = null;\n      }\n      if (this.cell.recurrentDropoutMask != null) {\n        dispose(this.cell.recurrentDropoutMask);\n        this.cell.recurrentDropoutMask = null;\n      }\n      const mask = kwargs == null ? null : kwargs[\"mask\"];\n      const training = kwargs == null ? null : kwargs[\"training\"];\n      const initialState = kwargs == null ? null : kwargs[\"initialState\"];\n      return super.call(inputs, { mask, training, initialState });\n    });\n  }\n  static fromConfig(cls, config) {\n    if (config[\"implmentation\"] === 0) {\n      config[\"implementation\"] = 1;\n    }\n    return new cls(config);\n  }\n};\nLSTM.className = \"LSTM\";\nserialization_exports.registerClass(LSTM);\nvar StackedRNNCells = class extends RNNCell {\n  constructor(args) {\n    super(args);\n    this.cells = args.cells;\n  }\n  get stateSize() {\n    const stateSize = [];\n    for (const cell of this.cells.slice().reverse()) {\n      if (Array.isArray(cell.stateSize)) {\n        stateSize.push(...cell.stateSize);\n      } else {\n        stateSize.push(cell.stateSize);\n      }\n    }\n    return stateSize;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = inputs;\n      let states = inputs.slice(1);\n      const nestedStates = [];\n      for (const cell of this.cells.slice().reverse()) {\n        if (Array.isArray(cell.stateSize)) {\n          nestedStates.push(states.splice(0, cell.stateSize.length));\n        } else {\n          nestedStates.push(states.splice(0, 1));\n        }\n      }\n      nestedStates.reverse();\n      const newNestedStates = [];\n      let callInputs;\n      for (let i2 = 0; i2 < this.cells.length; ++i2) {\n        const cell = this.cells[i2];\n        states = nestedStates[i2];\n        if (i2 === 0) {\n          callInputs = [inputs[0]].concat(states);\n        } else {\n          callInputs = [callInputs[0]].concat(states);\n        }\n        callInputs = cell.call(callInputs, kwargs);\n        newNestedStates.push(callInputs.slice(1));\n      }\n      states = [];\n      for (const cellStates of newNestedStates.slice().reverse()) {\n        states.push(...cellStates);\n      }\n      return [callInputs[0]].concat(states);\n    });\n  }\n  build(inputShape) {\n    if (isArrayOfShapes(inputShape)) {\n      inputShape = inputShape[0];\n    }\n    inputShape = inputShape;\n    let outputDim;\n    this.cells.forEach((cell, i2) => {\n      nameScope(`RNNCell_${i2}`, () => {\n        cell.build(inputShape);\n        if (Array.isArray(cell.stateSize)) {\n          outputDim = cell.stateSize[0];\n        } else {\n          outputDim = cell.stateSize;\n        }\n        inputShape = [inputShape[0], outputDim];\n      });\n    });\n    this.built = true;\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const getCellConfig = (cell) => {\n      return {\n        \"className\": cell.getClassName(),\n        \"config\": cell.getConfig()\n      };\n    };\n    const cellConfigs = this.cells.map(getCellConfig);\n    const config = { \"cells\": cellConfigs };\n    return Object.assign({}, baseConfig, config);\n  }\n  static fromConfig(cls, config, customObjects = {}) {\n    const cells = [];\n    for (const cellConfig of config[\"cells\"]) {\n      cells.push(deserialize(cellConfig, customObjects));\n    }\n    return new cls({ cells });\n  }\n  get trainableWeights() {\n    if (!this.trainable) {\n      return [];\n    }\n    const weights = [];\n    for (const cell of this.cells) {\n      weights.push(...cell.trainableWeights);\n    }\n    return weights;\n  }\n  get nonTrainableWeights() {\n    const weights = [];\n    for (const cell of this.cells) {\n      weights.push(...cell.nonTrainableWeights);\n    }\n    if (!this.trainable) {\n      const trainableWeights = [];\n      for (const cell of this.cells) {\n        trainableWeights.push(...cell.trainableWeights);\n      }\n      return trainableWeights.concat(weights);\n    }\n    return weights;\n  }\n  getWeights() {\n    const weights = [];\n    for (const cell of this.cells) {\n      weights.push(...cell.weights);\n    }\n    return batchGetValue(weights);\n  }\n  setWeights(weights) {\n    const tuples = [];\n    for (const cell of this.cells) {\n      const numParams = cell.weights.length;\n      const inputWeights = weights.splice(numParams);\n      for (let i2 = 0; i2 < cell.weights.length; ++i2) {\n        tuples.push([cell.weights[i2], inputWeights[i2]]);\n      }\n    }\n    batchSetValue(tuples);\n  }\n};\nStackedRNNCells.className = \"StackedRNNCells\";\nserialization_exports.registerClass(StackedRNNCells);\nfunction generateDropoutMask(args) {\n  const { ones: ones4, rate, training = false, count: count2 = 1, dropoutFunc } = args;\n  const droppedInputs = () => dropoutFunc != null ? dropoutFunc(ones4(), rate) : dropout2(ones4(), rate);\n  const createMask = () => inTrainPhase(droppedInputs, ones4, training);\n  if (!count2 || count2 <= 1) {\n    return keep(createMask().clone());\n  }\n  const masks = Array(count2).fill(void 0).map(createMask);\n  return masks.map((m) => keep(m.clone()));\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/convolutional_recurrent.js\nvar __rest = function(s2, e2) {\n  var t2 = {};\n  for (var p2 in s2)\n    if (Object.prototype.hasOwnProperty.call(s2, p2) && e2.indexOf(p2) < 0)\n      t2[p2] = s2[p2];\n  if (s2 != null && typeof Object.getOwnPropertySymbols === \"function\")\n    for (var i2 = 0, p2 = Object.getOwnPropertySymbols(s2); i2 < p2.length; i2++) {\n      if (e2.indexOf(p2[i2]) < 0 && Object.prototype.propertyIsEnumerable.call(s2, p2[i2]))\n        t2[p2[i2]] = s2[p2[i2]];\n    }\n  return t2;\n};\nvar ConvRNN2D = class extends RNN {\n  constructor(args) {\n    if (args.unroll) {\n      throw new NotImplementedError(\"Unrolling is not possible with convolutional RNNs.\");\n    }\n    if (Array.isArray(args.cell)) {\n      throw new NotImplementedError(\"It is not possible at the moment to stack convolutional cells.\");\n    }\n    super(args);\n    this.inputSpec = [new InputSpec({ ndim: 5 })];\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      if (this.cell.dropoutMask != null) {\n        dispose(this.cell.dropoutMask);\n        this.cell.dropoutMask = null;\n      }\n      if (this.cell.recurrentDropoutMask != null) {\n        dispose(this.cell.recurrentDropoutMask);\n        this.cell.recurrentDropoutMask = null;\n      }\n      if (kwargs && kwargs[\"constants\"]) {\n        throw new ValueError(\"ConvRNN2D cell does not support constants\");\n      }\n      const mask = kwargs == null ? null : kwargs[\"mask\"];\n      const training = kwargs == null ? null : kwargs[\"training\"];\n      const initialState = kwargs == null ? null : kwargs[\"initialState\"];\n      return super.call(inputs, { mask, training, initialState });\n    });\n  }\n  computeOutputShape(inputShape) {\n    let outShape = this.computeSingleOutputShape(inputShape);\n    if (!this.returnSequences) {\n      outShape = [outShape[0], ...outShape.slice(2)];\n    }\n    if (this.returnState) {\n      outShape = [outShape, ...Array(2).fill([inputShape[0], ...outShape.slice(-3)])];\n    }\n    return outShape;\n  }\n  getInitialState(inputs) {\n    return tidy(() => {\n      const { stateSize } = this.cell;\n      const inputShape = inputs.shape;\n      const outputShape = this.computeSingleOutputShape(inputShape);\n      const stateShape = [outputShape[0], ...outputShape.slice(2)];\n      const initialState = zeros(stateShape);\n      if (Array.isArray(stateSize)) {\n        return Array(stateSize.length).fill(initialState);\n      }\n      return [initialState];\n    });\n  }\n  resetStates(states, training = false) {\n    tidy(() => {\n      if (!this.stateful) {\n        throw new AttributeError(\"Cannot call resetStates() on an RNN Layer that is not stateful.\");\n      }\n      const inputShape = this.inputSpec[0].shape;\n      const outputShape = this.computeSingleOutputShape(inputShape);\n      const stateShape = [outputShape[0], ...outputShape.slice(2)];\n      const batchSize = inputShape[0];\n      if (batchSize == null) {\n        throw new ValueError(\"If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \\n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.\");\n      }\n      if (this.getStates() == null) {\n        if (Array.isArray(this.cell.stateSize)) {\n          this.states_ = this.cell.stateSize.map(() => zeros(stateShape));\n        } else {\n          this.states_ = [zeros(stateShape)];\n        }\n      } else if (states == null) {\n        dispose(this.states_);\n        if (this.keptStates != null) {\n          dispose(this.keptStates);\n          this.keptStates = [];\n        }\n        if (Array.isArray(this.cell.stateSize)) {\n          this.states_ = this.cell.stateSize.map(() => zeros(stateShape));\n        } else {\n          this.states_[0] = zeros(stateShape);\n        }\n      } else {\n        if (!Array.isArray(states)) {\n          states = [states];\n        }\n        if (states.length !== this.states_.length) {\n          throw new ValueError(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${states.length} state value(s). Input received: ${states}`);\n        }\n        if (training) {\n          this.keptStates.push(this.states_.slice());\n        } else {\n          dispose(this.states_);\n        }\n        for (let index = 0; index < this.states_.length; ++index) {\n          const value = states[index];\n          const expectedShape = stateShape;\n          if (!util_exports.arraysEqual(value.shape, expectedShape)) {\n            throw new ValueError(`State ${index} is incompatible with layer ${this.name}: expected shape=${expectedShape}, received shape=${value.shape}`);\n          }\n          this.states_[index] = value;\n        }\n      }\n      this.states_ = this.states_.map((state) => keep(state.clone()));\n    });\n  }\n  computeSingleOutputShape(inputShape) {\n    const { dataFormat, filters, kernelSize, padding, strides, dilationRate } = this.cell;\n    const isChannelsFirst = dataFormat === \"channelsFirst\";\n    const h = inputShape[isChannelsFirst ? 3 : 2];\n    const w = inputShape[isChannelsFirst ? 4 : 3];\n    const hOut = convOutputLength(h, kernelSize[0], padding, strides[0], dilationRate[0]);\n    const wOut = convOutputLength(w, kernelSize[1], padding, strides[1], dilationRate[1]);\n    const outShape = [\n      ...inputShape.slice(0, 2),\n      ...isChannelsFirst ? [filters, hOut, wOut] : [hOut, wOut, filters]\n    ];\n    return outShape;\n  }\n};\nConvRNN2D.className = \"ConvRNN2D\";\nvar ConvLSTM2DCell = class extends LSTMCell {\n  constructor(args) {\n    const { filters, kernelSize, strides, padding, dataFormat, dilationRate } = args;\n    super(Object.assign({}, args, { units: filters }));\n    this.filters = filters;\n    assertPositiveInteger(this.filters, \"filters\");\n    this.kernelSize = normalizeArray(kernelSize, 2, \"kernelSize\");\n    this.kernelSize.forEach((size) => assertPositiveInteger(size, \"kernelSize\"));\n    this.strides = normalizeArray(strides || 1, 2, \"strides\");\n    this.strides.forEach((stride) => assertPositiveInteger(stride, \"strides\"));\n    this.padding = padding || \"valid\";\n    checkPaddingMode(this.padding);\n    this.dataFormat = dataFormat || \"channelsLast\";\n    checkDataFormat(this.dataFormat);\n    this.dilationRate = normalizeArray(dilationRate || 1, 2, \"dilationRate\");\n    this.dilationRate.forEach((rate) => assertPositiveInteger(rate, \"dilationRate\"));\n  }\n  build(inputShape) {\n    var _a;\n    inputShape = getExactlyOneShape(inputShape);\n    const channelAxis = this.dataFormat === \"channelsFirst\" ? 1 : inputShape.length - 1;\n    if (inputShape[channelAxis] == null) {\n      throw new ValueError(`The channel dimension of the input should be defined. Found ${inputShape[channelAxis]}`);\n    }\n    const inputDim = inputShape[channelAxis];\n    const numOfKernels = 4;\n    const kernelShape = this.kernelSize.concat([inputDim, this.filters * numOfKernels]);\n    this.kernel = this.addWeight(\"kernel\", kernelShape, null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n    const recurrentKernelShape = this.kernelSize.concat([this.filters, this.filters * numOfKernels]);\n    this.recurrentKernel = this.addWeight(\"recurrent_kernel\", recurrentKernelShape, null, this.recurrentInitializer, this.recurrentRegularizer, true, this.recurrentConstraint);\n    if (this.useBias) {\n      let biasInitializer;\n      if (this.unitForgetBias) {\n        const init2 = this.biasInitializer;\n        const filters = this.filters;\n        biasInitializer = new (_a = class CustomInit extends Initializer {\n          apply(shape, dtype) {\n            const biasI = init2.apply([filters]);\n            const biasF = ones2([filters]);\n            const biasCAndO = init2.apply([filters * 2]);\n            return concatenate([biasI, biasF, biasCAndO]);\n          }\n        }, _a.className = \"CustomInit\", _a)();\n      } else {\n        biasInitializer = this.biasInitializer;\n      }\n      this.bias = this.addWeight(\"bias\", [this.filters * numOfKernels], null, biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n    }\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      if (inputs.length !== 3) {\n        throw new ValueError(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${inputs.length}.`);\n      }\n      const training = kwargs[\"training\"] || false;\n      const x = inputs[0];\n      const hTMinus1 = inputs[1];\n      const cTMinus1 = inputs[2];\n      const numOfKernels = 4;\n      if (0 < this.dropout && this.dropout < 1 && this.dropoutMask == null) {\n        this.dropoutMask = generateDropoutMask({\n          ones: () => onesLike(x),\n          rate: this.dropout,\n          training,\n          count: numOfKernels,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      const dropoutMask = this.dropoutMask;\n      const applyDropout = (x2, mask, index) => {\n        if (!mask || !mask[index]) {\n          return x2;\n        }\n        return mul(mask[index], x2);\n      };\n      let xI = applyDropout(x, dropoutMask, 0);\n      let xF = applyDropout(x, dropoutMask, 1);\n      let xC = applyDropout(x, dropoutMask, 2);\n      let xO = applyDropout(x, dropoutMask, 3);\n      if (0 < this.recurrentDropout && this.recurrentDropout < 1 && this.recurrentDropoutMask == null) {\n        this.recurrentDropoutMask = generateDropoutMask({\n          ones: () => onesLike(hTMinus1),\n          rate: this.recurrentDropout,\n          training,\n          count: numOfKernels,\n          dropoutFunc: this.dropoutFunc\n        });\n      }\n      const recDropoutMask = this.recurrentDropoutMask;\n      let hI = applyDropout(hTMinus1, recDropoutMask, 0);\n      let hF = applyDropout(hTMinus1, recDropoutMask, 1);\n      let hC = applyDropout(hTMinus1, recDropoutMask, 2);\n      let hO = applyDropout(hTMinus1, recDropoutMask, 3);\n      const kernelChannelAxis = 3;\n      const [kernelI, kernelF, kernelC, kernelO] = split(this.kernel.read(), numOfKernels, kernelChannelAxis);\n      const [biasI, biasF, biasC, biasO] = this.useBias ? split(this.bias.read(), numOfKernels) : [null, null, null, null];\n      xI = this.inputConv(xI, kernelI, biasI, this.padding);\n      xF = this.inputConv(xF, kernelF, biasF, this.padding);\n      xC = this.inputConv(xC, kernelC, biasC, this.padding);\n      xO = this.inputConv(xO, kernelO, biasO, this.padding);\n      const [recKernelI, recKernelF, recKernelC, recKernelO] = split(this.recurrentKernel.read(), numOfKernels, kernelChannelAxis);\n      hI = this.recurrentConv(hI, recKernelI);\n      hF = this.recurrentConv(hF, recKernelF);\n      hC = this.recurrentConv(hC, recKernelC);\n      hO = this.recurrentConv(hO, recKernelO);\n      const i2 = this.recurrentActivation.apply(add2(xI, hI));\n      const f = this.recurrentActivation.apply(add2(xF, hF));\n      const c = add2(mul(f, cTMinus1), mul(i2, this.activation.apply(add2(xC, hC))));\n      const h = mul(this.recurrentActivation.apply(add2(xO, hO)), this.activation.apply(c));\n      return [h, h, c];\n    });\n  }\n  getConfig() {\n    const _a = super.getConfig(), { \"units\": _ } = _a, baseConfig = __rest(_a, [\"units\"]);\n    const config = {\n      filters: this.filters,\n      kernelSize: this.kernelSize,\n      padding: this.padding,\n      dataFormat: this.dataFormat,\n      dilationRate: this.dilationRate,\n      strides: this.strides\n    };\n    return Object.assign({}, baseConfig, config);\n  }\n  inputConv(x, w, b, padding) {\n    const out = conv2d(x, w, this.strides, padding || \"valid\", this.dataFormat === \"channelsFirst\" ? \"NCHW\" : \"NHWC\", this.dilationRate);\n    if (b) {\n      return biasAdd(out, b, this.dataFormat);\n    }\n    return out;\n  }\n  recurrentConv(x, w) {\n    const strides = 1;\n    return conv2d(x, w, strides, \"same\", this.dataFormat === \"channelsFirst\" ? \"NCHW\" : \"NHWC\");\n  }\n};\nConvLSTM2DCell.className = \"ConvLSTM2DCell\";\nserialization_exports.registerClass(ConvLSTM2DCell);\nvar ConvLSTM2D = class extends ConvRNN2D {\n  constructor(args) {\n    const cell = new ConvLSTM2DCell(args);\n    super(Object.assign({}, args, { cell }));\n  }\n  static fromConfig(cls, config) {\n    return new cls(config);\n  }\n};\nConvLSTM2D.className = \"ConvLSTM2D\";\nserialization_exports.registerClass(ConvLSTM2D);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/core.js\nvar Dropout = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.rate = Math.max(Math.min(args.rate, 1), 0);\n    this.noiseShape = args.noiseShape;\n    this.seed = args.seed;\n    this.supportsMasking = true;\n  }\n  getNoiseShape(input2) {\n    if (this.noiseShape == null) {\n      return this.noiseShape;\n    }\n    const inputShape = input2.shape;\n    const noiseShape = [];\n    for (let i2 = 0; i2 < this.noiseShape.length; ++i2) {\n      noiseShape.push(this.noiseShape[i2] == null ? inputShape[i2] : this.noiseShape[i2]);\n    }\n    return noiseShape;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      const input2 = getExactlyOneTensor(inputs);\n      if (0 < this.rate && this.rate < 1) {\n        const training = kwargs[\"training\"] == null ? false : kwargs[\"training\"];\n        const noiseShape = this.getNoiseShape(input2);\n        const output = inTrainPhase(() => dropout2(input2, this.rate, noiseShape, this.seed), () => input2, training);\n        return output;\n      }\n      return inputs;\n    });\n  }\n  getConfig() {\n    const config = {\n      rate: this.rate,\n      noiseShape: this.noiseShape,\n      seed: this.seed\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  dispose() {\n    return super.dispose();\n  }\n};\nDropout.className = \"Dropout\";\nserialization_exports.registerClass(Dropout);\nvar SpatialDropout1D = class extends Dropout {\n  constructor(args) {\n    super(args);\n    this.inputSpec = [{ ndim: 3 }];\n  }\n  getNoiseShape(input2) {\n    const inputShape = input2.shape;\n    return [inputShape[0], 1, inputShape[2]];\n  }\n};\nSpatialDropout1D.className = \"SpatialDropout1D\";\nserialization_exports.registerClass(SpatialDropout1D);\nvar Dense = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.activation = null;\n    this.useBias = true;\n    this.kernel = null;\n    this.bias = null;\n    this.DEFAULT_KERNEL_INITIALIZER = \"glorotNormal\";\n    this.DEFAULT_BIAS_INITIALIZER = \"zeros\";\n    if (args.batchInputShape == null && args.inputShape == null && args.inputDim != null) {\n      let batchSize = null;\n      if (args.batchSize != null) {\n        batchSize = args.batchSize;\n      }\n      this.batchInputShape = [batchSize, args.inputDim];\n    }\n    this.units = args.units;\n    assertPositiveInteger(this.units, \"units\");\n    this.activation = getActivation(args.activation);\n    if (args.useBias != null) {\n      this.useBias = args.useBias;\n    }\n    this.kernelInitializer = getInitializer(args.kernelInitializer || this.DEFAULT_KERNEL_INITIALIZER);\n    this.biasInitializer = getInitializer(args.biasInitializer || this.DEFAULT_BIAS_INITIALIZER);\n    this.kernelConstraint = getConstraint(args.kernelConstraint);\n    this.biasConstraint = getConstraint(args.biasConstraint);\n    this.kernelRegularizer = getRegularizer(args.kernelRegularizer);\n    this.biasRegularizer = getRegularizer(args.biasRegularizer);\n    this.activityRegularizer = getRegularizer(args.activityRegularizer);\n    this.supportsMasking = true;\n    this.inputSpec = [{ minNDim: 2 }];\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const inputLastDim = inputShape[inputShape.length - 1];\n    if (this.kernel == null) {\n      this.kernel = this.addWeight(\"kernel\", [inputLastDim, this.units], null, this.kernelInitializer, this.kernelRegularizer, true, this.kernelConstraint);\n      if (this.useBias) {\n        this.bias = this.addWeight(\"bias\", [this.units], null, this.biasInitializer, this.biasRegularizer, true, this.biasConstraint);\n      }\n    }\n    this.inputSpec = [{ minNDim: 2, axes: { [-1]: inputLastDim } }];\n    this.built = true;\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const outputShape = inputShape.slice();\n    outputShape[outputShape.length - 1] = this.units;\n    return outputShape;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      const input2 = getExactlyOneTensor(inputs);\n      const fusedActivationName = mapActivationToFusedKernel(this.activation.getClassName());\n      let output;\n      if (fusedActivationName != null) {\n        output = dot2(input2, this.kernel.read(), fusedActivationName, this.bias ? this.bias.read() : null);\n      } else {\n        output = dot2(input2, this.kernel.read());\n        if (this.bias != null) {\n          output = biasAdd(output, this.bias.read());\n        }\n        if (this.activation != null) {\n          output = this.activation.apply(output);\n        }\n      }\n      return output;\n    });\n  }\n  getConfig() {\n    const config = {\n      units: this.units,\n      activation: serializeActivation(this.activation),\n      useBias: this.useBias,\n      kernelInitializer: serializeInitializer(this.kernelInitializer),\n      biasInitializer: serializeInitializer(this.biasInitializer),\n      kernelRegularizer: serializeRegularizer(this.kernelRegularizer),\n      biasRegularizer: serializeRegularizer(this.biasRegularizer),\n      activityRegularizer: serializeRegularizer(this.activityRegularizer),\n      kernelConstraint: serializeConstraint(this.kernelConstraint),\n      biasConstraint: serializeConstraint(this.biasConstraint)\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nDense.className = \"Dense\";\nserialization_exports.registerClass(Dense);\nvar Flatten = class extends Layer {\n  constructor(args) {\n    args = args || {};\n    super(args);\n    this.inputSpec = [{ minNDim: 3 }];\n    this.dataFormat = args.dataFormat;\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    for (const dim of inputShape.slice(1)) {\n      if (dim == null) {\n        throw new ValueError(`The shape of the input to \"Flatten\" is not fully defined (got ${inputShape.slice(1)}). Make sure to pass a complete \"input_shape\" or \"batch_input_shape\" argument to the first layer in your model.`);\n      }\n    }\n    return [inputShape[0], arrayProd(inputShape, 1)];\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      let input2 = getExactlyOneTensor(inputs);\n      if (this.dataFormat === \"channelsFirst\" && input2.rank > 1) {\n        const permutation = [0];\n        for (let i2 = 2; i2 < input2.rank; ++i2) {\n          permutation.push(i2);\n        }\n        permutation.push(1);\n        input2 = transpose(input2, permutation);\n      }\n      return batchFlatten(input2);\n    });\n  }\n  getConfig() {\n    const config = {};\n    if (this.dataFormat != null) {\n      config[\"dataFormat\"] = this.dataFormat;\n    }\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nFlatten.className = \"Flatten\";\nserialization_exports.registerClass(Flatten);\nvar Activation2 = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.supportsMasking = true;\n    this.activation = getActivation(args.activation);\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      const input2 = getExactlyOneTensor(inputs);\n      return this.activation.apply(input2);\n    });\n  }\n  getConfig() {\n    const config = { activation: serializeActivation(this.activation) };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nActivation2.className = \"Activation\";\nserialization_exports.registerClass(Activation2);\nvar RepeatVector = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.n = args.n;\n    this.inputSpec = [{ ndim: 2 }];\n  }\n  computeOutputShape(inputShape) {\n    return [inputShape[0], this.n, inputShape[1]];\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = getExactlyOneTensor(inputs);\n      return repeat(inputs, this.n);\n    });\n  }\n  getConfig() {\n    const config = {\n      n: this.n\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nRepeatVector.className = \"RepeatVector\";\nserialization_exports.registerClass(RepeatVector);\nvar Reshape2 = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.targetShape = args.targetShape;\n    for (let i2 = 0; i2 < this.targetShape.length; ++i2) {\n      if (this.isUnknown(this.targetShape[i2])) {\n        this.targetShape[i2] = null;\n      }\n    }\n  }\n  isUnknown(dim) {\n    return dim < 0 || dim == null;\n  }\n  fixUnknownDimension(inputShape, outputShape) {\n    const errorMsg = \"Total size of new array must be unchanged.\";\n    const finalShape = outputShape.slice();\n    let known = 1;\n    let unknown = null;\n    for (let i2 = 0; i2 < finalShape.length; ++i2) {\n      const dim = finalShape[i2];\n      if (this.isUnknown(dim)) {\n        if (unknown === null) {\n          unknown = i2;\n        } else {\n          throw new ValueError(\"Can only specifiy one unknown dimension.\");\n        }\n      } else {\n        known *= dim;\n      }\n    }\n    const originalSize = arrayProd(inputShape);\n    if (unknown !== null) {\n      if (known === 0 || originalSize % known !== 0) {\n        throw new ValueError(errorMsg);\n      }\n      finalShape[unknown] = originalSize / known;\n    } else if (originalSize !== known) {\n      throw new ValueError(errorMsg);\n    }\n    return finalShape;\n  }\n  computeOutputShape(inputShape) {\n    let anyUnknownDims = false;\n    for (let i2 = 0; i2 < inputShape.length; ++i2) {\n      if (this.isUnknown(inputShape[i2])) {\n        anyUnknownDims = true;\n        break;\n      }\n    }\n    if (anyUnknownDims) {\n      return inputShape.slice(0, 1).concat(this.targetShape);\n    } else {\n      return inputShape.slice(0, 1).concat(this.fixUnknownDimension(inputShape.slice(1), this.targetShape));\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      const input2 = getExactlyOneTensor(inputs);\n      const inputShape = input2.shape;\n      const outputShape = inputShape.slice(0, 1).concat(this.fixUnknownDimension(inputShape.slice(1), this.targetShape));\n      return reshape(input2, outputShape);\n    });\n  }\n  getConfig() {\n    const config = {\n      targetShape: this.targetShape\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nReshape2.className = \"Reshape\";\nserialization_exports.registerClass(Reshape2);\nvar Permute = class extends Layer {\n  constructor(args) {\n    super(args);\n    if (args.dims == null) {\n      throw new Error(\"Required configuration field `dims` is missing during Permute constructor call.\");\n    }\n    if (!Array.isArray(args.dims)) {\n      throw new Error(`Permute constructor requires \\`dims\\` to be an Array, but received ${args.dims} instead.`);\n    }\n    const expectedSortedIndices = range2(1, args.dims.length + 1);\n    if (!util_exports.arraysEqual(args.dims.slice().sort(), expectedSortedIndices)) {\n      throw new Error(\"Invalid permutation `dims`: \" + JSON.stringify(args.dims) + \" `dims` must contain consecutive integers starting from 1.\");\n    }\n    this.dims = args.dims;\n    this.dimsIncludingBatch = [0].concat(this.dims);\n    this.inputSpec = [new InputSpec({ ndim: this.dims.length + 1 })];\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const outputShape = inputShape.slice();\n    this.dims.forEach((dim, i2) => {\n      outputShape[i2 + 1] = inputShape[dim];\n    });\n    return outputShape;\n  }\n  call(inputs, kwargs) {\n    return transpose(getExactlyOneTensor(inputs), this.dimsIncludingBatch);\n  }\n  getConfig() {\n    const config = {\n      dims: this.dims\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nPermute.className = \"Permute\";\nserialization_exports.registerClass(Permute);\nvar Masking = class extends Layer {\n  constructor(args) {\n    super(args == null ? {} : args);\n    this.supportsMasking = true;\n    if (args != null) {\n      this.maskValue = args.maskValue == null ? 0 : args.maskValue;\n    } else {\n      this.maskValue = 0;\n    }\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = { maskValue: this.maskValue };\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  computeMask(inputs, mask) {\n    const input2 = getExactlyOneTensor(inputs);\n    const axis = -1;\n    return any(notEqual(input2, this.maskValue), axis);\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      const input2 = getExactlyOneTensor(inputs);\n      const axis = -1;\n      const keepDims = true;\n      const booleanMask = any(notEqual(input2, this.maskValue), axis, keepDims);\n      const output = mul(input2, cast(booleanMask, input2.dtype));\n      return output;\n    });\n  }\n};\nMasking.className = \"Masking\";\nserialization_exports.registerClass(Masking);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/embeddings.js\nvar Embedding = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.embeddings = null;\n    this.DEFAULT_EMBEDDINGS_INITIALIZER = \"randomUniform\";\n    if (args.batchInputShape == null && args.inputShape == null) {\n      let batchSize = null;\n      if (args.batchSize != null) {\n        batchSize = args.batchSize;\n      }\n      if (args.inputLength == null) {\n        this.batchInputShape = [batchSize, null];\n      } else {\n        this.batchInputShape = [batchSize].concat(toList(args.inputLength));\n      }\n    }\n    this.inputDim = args.inputDim;\n    assertPositiveInteger(this.inputDim, \"inputDim\");\n    this.outputDim = args.outputDim;\n    assertPositiveInteger(this.outputDim, \"outputDim\");\n    this.embeddingsInitializer = getInitializer(args.embeddingsInitializer || this.DEFAULT_EMBEDDINGS_INITIALIZER);\n    this.embeddingsRegularizer = getRegularizer(args.embeddingsRegularizer);\n    this.activityRegularizer = getRegularizer(args.activityRegularizer);\n    this.embeddingsConstraint = getConstraint(args.embeddingsConstraint);\n    this.maskZero = args.maskZero;\n    this.supportsMasking = args.maskZero;\n    this.inputLength = args.inputLength;\n  }\n  build(inputShape) {\n    this.embeddings = this.addWeight(\"embeddings\", [this.inputDim, this.outputDim], this.dtype, this.embeddingsInitializer, this.embeddingsRegularizer, true, this.embeddingsConstraint);\n    this.built = true;\n  }\n  warnOnIncompatibleInputShape(inputShape) {\n  }\n  computeMask(inputs, mask) {\n    return tidy(() => {\n      if (!this.maskZero) {\n        return null;\n      } else {\n        inputs = getExactlyOneTensor(inputs);\n        return notEqual(inputs, zerosLike(inputs));\n      }\n    });\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    if (this.inputLength == null) {\n      return [...inputShape, this.outputDim];\n    }\n    const inLens = toList(this.inputLength);\n    if (inLens.length !== inputShape.length - 1) {\n      throw new ValueError(`\"inputLength\" is ${this.inputLength}, but received input shape has shape ${inputShape}`);\n    } else {\n      let i2 = 0;\n      for (let k = 0; k < inLens.length; ++k) {\n        const s1 = inLens[k];\n        const s2 = inputShape[k + 1];\n        if (s1 != null && s2 != null && s1 !== s2) {\n          throw new ValueError(`\"inputLength\" is ${this.inputLength}, but received input shape has shape ${inputShape}`);\n        } else if (s1 == null) {\n          inLens[i2] = s2;\n        }\n        i2++;\n      }\n    }\n    return [inputShape[0], ...inLens, this.outputDim];\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      let input2 = getExactlyOneTensor(inputs);\n      if (input2.dtype !== \"int32\") {\n        input2 = cast2(input2, \"int32\");\n      }\n      const output = gather2(this.embeddings.read(), reshape(input2, [input2.size]));\n      return reshape(output, getExactlyOneShape(this.computeOutputShape(input2.shape)));\n    });\n  }\n  getConfig() {\n    const config = {\n      inputDim: this.inputDim,\n      outputDim: this.outputDim,\n      embeddingsInitializer: serializeInitializer(this.embeddingsInitializer),\n      embeddingsRegularizer: serializeRegularizer(this.embeddingsRegularizer),\n      activityRegularizer: serializeRegularizer(this.activityRegularizer),\n      embeddingsConstraint: serializeConstraint(this.embeddingsConstraint),\n      maskZero: this.maskZero,\n      inputLength: this.inputLength\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nEmbedding.className = \"Embedding\";\nserialization_exports.registerClass(Embedding);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/merge.js\nvar Merge = class extends Layer {\n  constructor(args) {\n    super(args || {});\n    this.supportsMasking = true;\n  }\n  mergeFunction(inputs) {\n    throw new NotImplementedError();\n  }\n  computeElementwiseOpOutputShape(shape1, shape2) {\n    if (shape1 == null || shape2 == null) {\n      return null;\n    } else if (shape1.length < shape2.length) {\n      return this.computeElementwiseOpOutputShape(shape2, shape1);\n    } else if (shape2.length === 0) {\n      return shape1;\n    }\n    const outputShape = shape1.slice(0, shape1.length - shape2.length);\n    for (let k = 0; k < shape2.length; ++k) {\n      const i2 = shape1[shape1.length - shape2.length + k];\n      const j = shape2[k];\n      if (i2 == null || j == null || i2 < 0 || j < 0) {\n        outputShape.push(null);\n      } else if (i2 === 1) {\n        outputShape.push(j);\n      } else if (j === 1) {\n        outputShape.push(i2);\n      } else {\n        if (i2 !== j) {\n          throw new ValueError(\"Operands could not be broadcast together with shapes \" + JSON.stringify(shape1) + \" \" + JSON.stringify(shape2));\n        }\n        outputShape.push(i2);\n      }\n    }\n    return outputShape;\n  }\n  build(inputShape) {\n    if (Array.isArray(inputShape) && !Array.isArray(inputShape[0])) {\n      inputShape = [getExactlyOneShape(inputShape)];\n    }\n    inputShape = inputShape;\n    if (inputShape.length < 2) {\n      throw new ValueError(`A merge layer should be called on an Array of at least 2 inputs. Got ${inputShape.length} input(s).`);\n    }\n    let batchSizes = [];\n    for (const shape of inputShape) {\n      if (shape != null && shape[0] !== null) {\n        batchSizes.push(shape[0]);\n      }\n    }\n    batchSizes = unique2(batchSizes);\n    if (batchSizes.length > 1) {\n      throw new ValueError(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(inputShape)}.`);\n    }\n    let outputShape = inputShape[0] == null ? null : inputShape[0].slice(1);\n    for (let i2 = 1; i2 < inputShape.length; ++i2) {\n      const shape = inputShape[i2] == null ? null : inputShape[i2].slice(1);\n      outputShape = this.computeElementwiseOpOutputShape(outputShape, shape);\n    }\n    const allRanks = inputShape.map((shape) => shape.length);\n    if (inputShape.indexOf(null) === -1 && unique2(allRanks).length === 1) {\n      this.reshapeRequired = false;\n    } else {\n      this.reshapeRequired = true;\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = inputs;\n      if (this.reshapeRequired) {\n        const reshapedInputs = [];\n        const inputDims = inputs.map((input2) => input2.rank);\n        if (inputDims.indexOf(null) === -1) {\n          const maxNDim = max2(inputDims);\n          for (let x of inputs) {\n            const xNDim = x.rank;\n            for (let k = 0; k < maxNDim - xNDim; ++k) {\n              x = expandDims2(x, 1);\n            }\n            reshapedInputs.push(x);\n          }\n          return this.mergeFunction(reshapedInputs);\n        } else {\n          let transposed = false;\n          for (const x of inputs) {\n            const xNDim = x.rank;\n            if (xNDim == null) {\n              const xShape = x.shape;\n              const batchSize = xShape[0];\n              const newShape = xShape.slice(1).concat([batchSize]);\n              let xTransposed = reshape(x, [batchSize].concat(arrayProd(xShape.slice(1))));\n              xTransposed = transpose(xTransposed, [1, 0]);\n              xTransposed = reshape(xTransposed, newShape);\n              reshapedInputs.push(xTransposed);\n              transposed = true;\n            } else if (xNDim > 1) {\n              const dims = range2(1, xNDim).concat([0]);\n              reshapedInputs.push(transpose(x, dims));\n              transposed = true;\n            } else {\n              reshapedInputs.push(x);\n            }\n          }\n          let y = this.mergeFunction(reshapedInputs);\n          const yNDim = y.rank;\n          if (transposed) {\n            if (yNDim == null) {\n              const yShape = y.shape;\n              const yNDim2 = yShape.length;\n              const batchSize = yShape[yNDim2 - 1];\n              const newShape = [batchSize].concat(yShape.slice(0, yShape.length - 1));\n              y = reshape(transpose(reshape(y, [-1, batchSize]), [1, 0]), newShape);\n            } else if (yNDim > 1) {\n              const dims = [yNDim - 1].concat(range2(0, yNDim - 1));\n              y = transpose(y, dims);\n            }\n          }\n          return y;\n        }\n      } else {\n        return this.mergeFunction(inputs);\n      }\n    });\n  }\n  computeOutputShape(inputShape) {\n    inputShape = inputShape;\n    let outputShape;\n    if (inputShape[0] == null) {\n      outputShape = null;\n    } else {\n      outputShape = inputShape[0].slice(1);\n    }\n    for (let i2 = 1; i2 < inputShape.length; ++i2) {\n      const shape = inputShape[i2] == null ? null : inputShape[i2].slice(1);\n      outputShape = this.computeElementwiseOpOutputShape(outputShape, shape);\n    }\n    let batchSizes = [];\n    for (const shape of inputShape) {\n      if (shape != null && shape[0] !== null) {\n        batchSizes.push(shape[0]);\n      }\n    }\n    batchSizes = unique2(batchSizes);\n    if (batchSizes.length === 1) {\n      outputShape = batchSizes.concat(outputShape);\n    } else {\n      outputShape = [null].concat(outputShape);\n    }\n    return outputShape;\n  }\n  computeMask(inputs, mask) {\n    return tidy(() => {\n      if (mask == null) {\n        return null;\n      }\n      if (!Array.isArray(mask)) {\n        throw new ValueError(\"`mask` should be an Array\");\n      }\n      if (!Array.isArray(inputs)) {\n        throw new ValueError(\"`inputs` should be an Array\");\n      }\n      if (mask.length !== inputs.length) {\n        throw new ValueError(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${inputs.length} vs ${mask.length})`);\n      }\n      if (mask.every((m) => m == null)) {\n        return null;\n      }\n      mask = mask.map((m) => m == null ? m : expandDims(m, 0));\n      let output = mask[0];\n      for (let i2 = 1; i2 < mask.length - 1; ++i2) {\n        output = logicalAnd(output, mask[i2]);\n      }\n      return output;\n    });\n  }\n};\nvar Add2 = class extends Merge {\n  constructor(args) {\n    super(args);\n  }\n  mergeFunction(inputs) {\n    return tidy(() => {\n      let output = inputs[0].clone();\n      for (let i2 = 1; i2 < inputs.length; ++i2) {\n        output = add2(output, inputs[i2]);\n      }\n      return output;\n    });\n  }\n};\nAdd2.className = \"Add\";\nserialization_exports.registerClass(Add2);\nvar Multiply2 = class extends Merge {\n  constructor(args) {\n    super(args);\n  }\n  mergeFunction(inputs) {\n    return tidy(() => {\n      let output = inputs[0].clone();\n      for (let i2 = 1; i2 < inputs.length; ++i2) {\n        output = mul(output, inputs[i2]);\n      }\n      return output;\n    });\n  }\n};\nMultiply2.className = \"Multiply\";\nserialization_exports.registerClass(Multiply2);\nvar Average = class extends Merge {\n  constructor(args) {\n    super(args);\n  }\n  mergeFunction(inputs) {\n    return tidy(() => {\n      let output = inputs[0].clone();\n      for (let i2 = 1; i2 < inputs.length; ++i2) {\n        output = add2(output, inputs[i2]);\n      }\n      return mul(1 / inputs.length, output);\n    });\n  }\n};\nAverage.className = \"Average\";\nserialization_exports.registerClass(Average);\nvar Maximum2 = class extends Merge {\n  constructor(args) {\n    super(args);\n  }\n  mergeFunction(inputs) {\n    return tidy(() => {\n      let output = inputs[0];\n      for (let i2 = 1; i2 < inputs.length; ++i2) {\n        output = maximum(output, inputs[i2]);\n      }\n      return output;\n    });\n  }\n};\nMaximum2.className = \"Maximum\";\nserialization_exports.registerClass(Maximum2);\nvar Minimum2 = class extends Merge {\n  constructor(args) {\n    super(args);\n  }\n  mergeFunction(inputs) {\n    return tidy(() => {\n      let output = inputs[0];\n      for (let i2 = 1; i2 < inputs.length; ++i2) {\n        output = minimum(output, inputs[i2]);\n      }\n      return output;\n    });\n  }\n};\nMinimum2.className = \"Minimum\";\nserialization_exports.registerClass(Minimum2);\nvar Concatenate = class extends Merge {\n  constructor(args) {\n    super(args);\n    this.DEFAULT_AXIS = -1;\n    if (args == null) {\n      args = {};\n    }\n    this.axis = args.axis == null ? this.DEFAULT_AXIS : args.axis;\n    this.supportsMasking = true;\n    this.reshapeRequired = false;\n  }\n  build(inputShape) {\n    if (!(Array.isArray(inputShape) && Array.isArray(inputShape[0])) || inputShape.length === 1) {\n      throw new ValueError(\"A `Concatenate` layer should be called on a list of at least 2 inputs\");\n    }\n    inputShape = inputShape;\n    let allNoneShape = true;\n    for (const shape of inputShape) {\n      if (shape != null) {\n        allNoneShape = false;\n        break;\n      }\n    }\n    if (allNoneShape) {\n      return;\n    }\n    const shapeSet = [];\n    for (let i2 = 0; i2 < inputShape.length; ++i2) {\n      const shapeWithoutConcatAxis = inputShape[i2].slice();\n      shapeWithoutConcatAxis.splice(this.axis, 1);\n      let exists = false;\n      for (const shape of shapeSet) {\n        if (util_exports.arraysEqual(shape, shapeWithoutConcatAxis)) {\n          exists = true;\n          break;\n        }\n      }\n      if (!exists) {\n        shapeSet.push(shapeWithoutConcatAxis);\n      }\n    }\n    if (shapeSet.length > 1) {\n      throw new ValueError(\"A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: \" + JSON.stringify(inputShape));\n    }\n  }\n  mergeFunction(inputs) {\n    return tidy(() => {\n      return concatenate(inputs, this.axis);\n    });\n  }\n  computeOutputShape(inputShape) {\n    if (!(Array.isArray(inputShape) && Array.isArray(inputShape[0]))) {\n      throw new ValueError(\"A `Concatenate` layer should be called on a list of inputs.\");\n    }\n    const inputShapes = inputShape;\n    const outputShape = inputShapes[0].slice();\n    const axis = this.axis < 0 ? outputShape.length + this.axis : this.axis;\n    for (const shape of inputShapes.slice(1)) {\n      if (outputShape[axis] == null || shape[axis] == null) {\n        outputShape[axis] = null;\n        break;\n      }\n      outputShape[axis] += shape[axis];\n    }\n    return outputShape;\n  }\n  computeMask(inputs, mask) {\n    if (mask == null) {\n      return null;\n    }\n    if (!Array.isArray(mask)) {\n      throw new ValueError(\"`mask` should be an array for Concatenate\");\n    }\n    if (!Array.isArray(inputs)) {\n      throw new ValueError(\"`inputs` should be an array for Concatenate\");\n    }\n    if (mask.length !== inputs.length) {\n      throw new ValueError(`Mismatch in the length of mask (${mask.length}) and the legnth of inputs (${inputs.length})`);\n    }\n    return tidy(() => {\n      let allNullMasks = true;\n      mask.forEach((m) => {\n        if (m != null) {\n          allNullMasks = false;\n          return;\n        }\n      });\n      if (allNullMasks) {\n        return null;\n      }\n      const outputMasks = [];\n      for (let i2 = 0; i2 < inputs.length; ++i2) {\n        if (mask[i2] == null) {\n          outputMasks.push(cast(onesLike(inputs[i2]), \"bool\"));\n        } else if (mask[i2].rank < inputs[i2].rank) {\n          outputMasks.push(expandDims(mask[i2], -1));\n        } else {\n          outputMasks.push(mask[i2]);\n        }\n      }\n      const concatenatedMasks = concat(outputMasks, this.axis);\n      return all(concatenatedMasks, -1, false);\n    });\n  }\n  getConfig() {\n    const config = {\n      \"axis\": this.axis\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nConcatenate.className = \"Concatenate\";\nserialization_exports.registerClass(Concatenate);\nfunction interpretAxis(axis, dim) {\n  while (axis < 0) {\n    axis += dim;\n  }\n  return axis;\n}\nfunction batchDot(x, y, axes) {\n  if (x.shape.length > 3 || y.shape.length > 3) {\n    throw new NotImplementedError(\"batchDot is not implemented for tensors of 4D or higher rank yet\");\n  }\n  util_exports.assert(x.shape.length >= 2, () => `batchDot requires the rank of x to be >= 2, but got ${x.shape.length}`);\n  util_exports.assert(x.shape.length >= 2, () => `batchDot requires the rank of y to be >= 2, but got ${y.shape.length}`);\n  if (typeof axes === \"number\") {\n    axes = [axes, axes];\n  }\n  if (x.dtype === \"complex64\" || y.dtype === \"complex64\") {\n    throw new NotImplementedError(\"batchDot is not implemented for complex64-type Tensors yet.\");\n  }\n  const xNDim = x.shape.length;\n  const yNDim = y.shape.length;\n  if (axes == null) {\n    axes = [xNDim - 1, yNDim - 2];\n  }\n  const axesArray = axes;\n  return tidy(() => {\n    let diff;\n    if (xNDim > yNDim) {\n      diff = xNDim - yNDim;\n      const diffShape = [];\n      for (let i2 = 0; i2 < diff; ++i2) {\n        diffShape.push(1);\n      }\n      y = reshape(y, y.shape.concat(diffShape));\n    } else if (yNDim > xNDim) {\n      diff = yNDim - xNDim;\n      const diffShape = [];\n      for (let i2 = 0; i2 < diff; ++i2) {\n        diffShape.push(1);\n      }\n      x = reshape(x, x.shape.concat(diffShape));\n    } else {\n      diff = 0;\n    }\n    let out;\n    if (x.shape.length === 2 && y.shape.length === 2) {\n      if (axesArray[0] === axesArray[1]) {\n        out = sum2(mul(x, y), axesArray[0]);\n      } else {\n        out = sum2(mul(transpose(x, [1, 0]), y), axesArray[1]);\n      }\n    } else {\n      const adjX = axesArray[0] !== x.shape.length - 1;\n      const adjY = axesArray[1] === y.shape.length - 1;\n      out = matMul(x, y, adjX, adjY);\n    }\n    if (diff > 0) {\n      let idx;\n      if (xNDim > yNDim) {\n        idx = xNDim + yNDim - 3;\n      } else {\n        idx = xNDim - 1;\n      }\n      const squeezeAxes = [];\n      for (let i2 = idx; i2 < idx + diff; ++i2) {\n        squeezeAxes.push(i2);\n      }\n      out = squeeze(out, squeezeAxes);\n    }\n    if (out.shape.length === 1) {\n      out = expandDims(out, 1);\n    }\n    return out;\n  });\n}\nvar Dot = class extends Merge {\n  constructor(args) {\n    super(args);\n    this.axes = args.axes;\n    this.normalize = args.normalize == null ? false : args.normalize;\n    this.supportsMasking = true;\n    this.reshapeRequired = false;\n  }\n  build(inputShape) {\n    util_exports.assert(Array.isArray(inputShape) && inputShape.length === 2 && Array.isArray(inputShape[0]) && Array.isArray(inputShape[1]), () => \"A `Dot` layer should be called on a list of exactly 2 inputs.\");\n    const shape1 = inputShape[0];\n    const shape2 = inputShape[1];\n    if (shape1.length > 3 || shape2.length > 3) {\n      throw new NotImplementedError(\"Dot layer does not support tensors of 4D or higher rank yet.\");\n    }\n    const axes = this.interpretAxes(shape1, shape2);\n    if (shape1[axes[0]] !== shape2[axes[1]]) {\n      throw new ValueError(`Dimension incompatibility: ${shape1[axes[0]]} !== ${shape2[axes[1]]}`);\n    }\n  }\n  mergeFunction(inputs) {\n    if (inputs.length !== 2) {\n      throw new ValueError(`A \\`Dot\\` layer must be called on exactly 2 inputs, but received ${inputs.length} input(s).`);\n    }\n    let x1 = inputs[0];\n    let x2 = inputs[1];\n    let axes;\n    if (!Array.isArray(this.axes)) {\n      axes = [\n        interpretAxis(this.axes, x1.shape.length),\n        interpretAxis(this.axes, x2.shape.length)\n      ];\n    } else {\n      axes = this.axes.map((axis, i2) => interpretAxis(axis, inputs[i2].shape.length));\n    }\n    if (this.normalize) {\n      x1 = l2Normalize(x1, axes[0]);\n      x2 = l2Normalize(x2, axes[1]);\n    }\n    return batchDot(x1, x2, axes);\n  }\n  interpretAxes(shape1, shape2) {\n    let axes;\n    if (!Array.isArray(this.axes)) {\n      axes = [\n        interpretAxis(this.axes, shape1.length),\n        interpretAxis(this.axes, shape2.length)\n      ];\n    } else {\n      axes = this.axes;\n    }\n    return axes;\n  }\n  computeOutputShape(inputShape) {\n    util_exports.assert(Array.isArray(inputShape) && inputShape.length === 2 && Array.isArray(inputShape[0]) && Array.isArray(inputShape[1]), () => \"A `Dot` layer should be called on a list of exactly 2 inputs.\");\n    const shape1 = inputShape[0].slice();\n    const shape2 = inputShape[1].slice();\n    if (shape1.length > 3 || shape2.length > 3) {\n      throw new NotImplementedError(\"Dot layer does not support tensors of 4D or higher rank yet.\");\n    }\n    const axes = this.interpretAxes(shape1, shape2);\n    shape1.splice(axes[0], 1);\n    shape2.splice(axes[1], 1);\n    shape2.splice(0, 1);\n    const outputShape = shape1.concat(shape2);\n    if (outputShape.length === 1) {\n      outputShape.push(1);\n    }\n    return outputShape;\n  }\n  computeMask(inputs, mask) {\n    return null;\n  }\n  getConfig() {\n    const config = {\n      \"axes\": this.axes,\n      \"normalize\": this.normalize\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nDot.className = \"Dot\";\nserialization_exports.registerClass(Dot);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/noise.js\nvar GaussianNoise = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.supportsMasking = true;\n    this.stddev = args.stddev;\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = { stddev: this.stddev };\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      const input2 = getExactlyOneTensor(inputs);\n      const noised = () => add2(randomNormal2(input2.shape, 0, this.stddev), input2);\n      const output = inTrainPhase(noised, () => input2, kwargs[\"training\"] || false);\n      return output;\n    });\n  }\n};\nGaussianNoise.className = \"GaussianNoise\";\nserialization_exports.registerClass(GaussianNoise);\nvar GaussianDropout = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.supportsMasking = true;\n    this.rate = args.rate;\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = { rate: this.rate };\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      const input2 = getExactlyOneTensor(inputs);\n      if (this.rate > 0 && this.rate < 1) {\n        const noised = () => {\n          const stddev = Math.sqrt(this.rate / (1 - this.rate));\n          return mul(input2, randomNormal2(input2.shape, 1, stddev));\n        };\n        return inTrainPhase(noised, () => input2, kwargs[\"training\"] || false);\n      }\n      return input2;\n    });\n  }\n};\nGaussianDropout.className = \"GaussianDropout\";\nserialization_exports.registerClass(GaussianDropout);\nvar AlphaDropout = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.supportsMasking = true;\n    this.rate = args.rate;\n    this.noiseShape = args.noiseShape;\n  }\n  _getNoiseShape(inputs) {\n    return this.noiseShape || getExactlyOneTensor(inputs).shape;\n  }\n  computeOutputShape(inputShape) {\n    return inputShape;\n  }\n  getConfig() {\n    const baseConfig = super.getConfig();\n    const config = { rate: this.rate };\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      if (this.rate < 1 && this.rate > 0) {\n        const noiseShape = this._getNoiseShape(inputs);\n        const droppedInputs = () => {\n          const input2 = getExactlyOneTensor(inputs);\n          const alpha = 1.6732632423543772;\n          const scale2 = 1.0507009873554805;\n          const alphaP = -alpha * scale2;\n          let keptIdx = greaterEqual(randomUniform(noiseShape), this.rate);\n          keptIdx = cast2(keptIdx, \"float32\");\n          const a = ((1 - this.rate) * (1 + this.rate * alphaP ** 2)) ** -0.5;\n          const b = -a * alphaP * this.rate;\n          const x = add2(mul(input2, keptIdx), mul(add2(keptIdx, -1), alphaP));\n          return add2(mul(x, a), b);\n        };\n        return inTrainPhase(droppedInputs, () => getExactlyOneTensor(inputs), kwargs[\"training\"] || false);\n      }\n      return inputs;\n    });\n  }\n};\nAlphaDropout.className = \"AlphaDropout\";\nserialization_exports.registerClass(AlphaDropout);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/normalization.js\nfunction batchNormalization(x, mean5, variance, beta, gamma, epsilon3 = 1e-3) {\n  let out;\n  if (x.rank === 2) {\n    out = batchNorm2d(x, mean5, variance, beta, gamma, epsilon3);\n  } else if (x.rank === 3) {\n    out = batchNorm3d(x, mean5, variance, beta, gamma, epsilon3);\n  } else if (x.rank === 4) {\n    out = batchNorm4d(x, mean5, variance, beta, gamma, epsilon3);\n  } else {\n    throw new NotImplementedError(`batchNormalization is not implemented for array of rank ${x.rank} yet`);\n  }\n  return out;\n}\nfunction regularNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon3 = 1e-3) {\n  return tidy(() => {\n    const meanAndVariance = moments(x, reductionAxes);\n    const mean5 = meanAndVariance.mean;\n    const variance = meanAndVariance.variance;\n    const normed = batchNormalization(x, mean5, variance, beta, gamma, epsilon3);\n    return [normed, mean5, variance];\n  });\n}\nfunction broadcastNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon3 = 1e-3) {\n  return tidy(() => {\n    const meanAndVariance = moments(x, reductionAxes);\n    const mean5 = meanAndVariance.mean;\n    const variance = meanAndVariance.variance;\n    const targetShape = [];\n    for (const axis of range2(0, x.rank)) {\n      if (reductionAxes.indexOf(axis) !== -1) {\n        targetShape.push(1);\n      } else {\n        targetShape.push(x.shape[axis]);\n      }\n    }\n    const broadcastMean = reshape(mean5, targetShape);\n    const broadcastVariance = reshape(variance, targetShape);\n    const broadcastGamma = gamma == null ? null : reshape(gamma, targetShape);\n    const broadcastBeta = beta == null ? null : reshape(beta, targetShape);\n    const normed = batchNormalization(x, broadcastMean, broadcastVariance, broadcastBeta, broadcastGamma, epsilon3);\n    return [normed, mean5, variance];\n  });\n}\nfunction normalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon3 = 1e-3) {\n  if (util_exports.arraysEqual(reductionAxes.slice().sort(), range2(0, x.rank - 1))) {\n    return regularNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon3);\n  } else {\n    return broadcastNormalizeBatchInTraining(x, gamma, beta, reductionAxes, epsilon3);\n  }\n}\nvar BatchNormalization = class extends Layer {\n  constructor(args) {\n    if (args == null) {\n      args = {};\n    }\n    super(args);\n    this.supportsMasking = true;\n    this.axis = args.axis == null ? -1 : args.axis;\n    this.momentum = args.momentum == null ? 0.99 : args.momentum;\n    this.epsilon = args.epsilon == null ? 1e-3 : args.epsilon;\n    this.center = args.center == null ? true : args.center;\n    this.scale = args.scale == null ? true : args.scale;\n    this.betaInitializer = getInitializer(args.betaInitializer || \"zeros\");\n    this.gammaInitializer = getInitializer(args.gammaInitializer || \"ones\");\n    this.movingMeanInitializer = getInitializer(args.movingMeanInitializer || \"zeros\");\n    this.movingVarianceInitializer = getInitializer(args.movingVarianceInitializer || \"ones\");\n    this.betaConstraint = getConstraint(args.betaConstraint);\n    this.gammaConstraint = getConstraint(args.gammaConstraint);\n    this.betaRegularizer = getRegularizer(args.betaRegularizer);\n    this.gammaRegularizer = getRegularizer(args.gammaRegularizer);\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const axis = this.axis >= 0 ? this.axis : this.axis + inputShape.length;\n    const dim = inputShape[axis];\n    if (dim == null) {\n      throw new ValueError(`Axis ${axis} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(inputShape)}.`);\n    }\n    this.inputSpec = [new InputSpec({ ndim: inputShape.length, axes: { [axis]: dim } })];\n    const shape = [dim];\n    if (this.scale) {\n      this.gamma = this.addWeight(\"gamma\", shape, null, this.gammaInitializer, this.gammaRegularizer, true, this.gammaConstraint);\n    }\n    if (this.center) {\n      this.beta = this.addWeight(\"beta\", shape, null, this.betaInitializer, this.betaRegularizer, true, this.betaConstraint);\n    }\n    this.movingMean = this.addWeight(\"moving_mean\", shape, null, this.movingMeanInitializer, null, false);\n    this.movingVariance = this.addWeight(\"moving_variance\", shape, null, this.movingVarianceInitializer, null, false);\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const training = kwargs[\"training\"] == null ? false : kwargs[\"training\"];\n      const input2 = getExactlyOneTensor(inputs);\n      const inputShape = input2.shape;\n      const ndim = inputShape.length;\n      const reductionAxes = range2(0, ndim);\n      const axis = this.axis >= 0 ? this.axis : this.axis + ndim;\n      reductionAxes.splice(axis, 1);\n      const broadcastShape = pyListRepeat(1, ndim);\n      broadcastShape[axis] = inputShape[axis];\n      const sortedReductionAxes = reductionAxes.slice();\n      sortedReductionAxes.sort();\n      const needsBroadcasting = !util_exports.arraysEqual(sortedReductionAxes, range2(0, ndim).slice(0, ndim - 1));\n      const normalizeInference = () => {\n        if (needsBroadcasting) {\n          const broadcastMovingMean = reshape(this.movingMean.read(), broadcastShape);\n          const broadcastMovingVariance = reshape(this.movingVariance.read(), broadcastShape);\n          const broadcastBeta = this.center ? reshape(this.beta.read(), broadcastShape) : null;\n          const broadcastGamma = this.scale ? reshape(this.gamma.read(), broadcastShape) : null;\n          return batchNormalization(input2, broadcastMovingMean, broadcastMovingVariance, broadcastBeta, broadcastGamma, this.epsilon);\n        } else {\n          return batchNormalization(input2, this.movingMean.read(), this.movingVariance.read(), this.beta == null ? null : this.beta.read(), this.gamma == null ? null : this.gamma.read(), this.epsilon);\n        }\n      };\n      if (!training) {\n        return normalizeInference();\n      }\n      const [normedTraining, mean5, variance] = normalizeBatchInTraining(input2, this.gamma.read(), this.beta.read(), reductionAxes, this.epsilon);\n      const doMovingAverage = (variable2, value, momentum) => {\n        tidy(() => {\n          const decay = 1 - momentum;\n          const origValue = variable2.read();\n          const updateDelta = mul(sub(origValue, value), decay);\n          variable2.write(sub(origValue, updateDelta));\n        });\n      };\n      const updateMovingMeanAndVariance = () => {\n        doMovingAverage(this.movingMean, mean5, this.momentum);\n        doMovingAverage(this.movingVariance, variance, this.momentum);\n      };\n      updateMovingMeanAndVariance();\n      return normedTraining;\n    });\n  }\n  getConfig() {\n    const config = {\n      axis: this.axis,\n      momentum: this.momentum,\n      epsilon: this.epsilon,\n      center: this.center,\n      scale: this.scale,\n      betaInitializer: serializeInitializer(this.betaInitializer),\n      gammaInitializer: serializeInitializer(this.gammaInitializer),\n      movingMeanInitializer: serializeInitializer(this.movingMeanInitializer),\n      movingVarianceInitializer: serializeInitializer(this.movingVarianceInitializer),\n      betaRegularizer: serializeRegularizer(this.betaRegularizer),\n      gammaRegularizer: serializeRegularizer(this.gammaRegularizer),\n      betaConstraint: serializeConstraint(this.betaConstraint),\n      gammaConstraint: serializeConstraint(this.gammaConstraint)\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nBatchNormalization.className = \"BatchNormalization\";\nserialization_exports.registerClass(BatchNormalization);\nvar LayerNormalization = class extends Layer {\n  constructor(args) {\n    if (args == null) {\n      args = {};\n    }\n    super(args);\n    this.axis = args.axis == null ? -1 : args.axis;\n    if (typeof this.axis === \"number\") {\n      if (!Number.isInteger(this.axis)) {\n        throw new Error(`Expected axis to be an integer, but received ${this.axis}`);\n      }\n    } else if (Array.isArray(this.axis)) {\n      for (const axis of this.axis) {\n        if (!Number.isInteger(axis)) {\n          throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`);\n        }\n      }\n    } else {\n      throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);\n    }\n    this.epsilon = args.epsilon == null ? 1e-3 : args.epsilon;\n    this.center = args.center == null ? true : args.center;\n    this.scale = args.scale == null ? true : args.scale;\n    this.betaInitializer = getInitializer(args.betaInitializer || \"zeros\");\n    this.gammaInitializer = getInitializer(args.gammaInitializer || \"ones\");\n    this.betaRegularizer = getRegularizer(args.betaRegularizer);\n    this.gammaRegularizer = getRegularizer(args.gammaRegularizer);\n    this.supportsMasking = true;\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const nDims = inputShape.length;\n    if (typeof this.axis === \"number\") {\n      this.axis = [this.axis];\n    }\n    for (let i2 = 0; i2 < this.axis.length; ++i2) {\n      if (this.axis[i2] < 0) {\n        this.axis[i2] += nDims;\n      }\n    }\n    for (const axis of this.axis) {\n      if (axis < 0 || axis >= nDims) {\n        throw new Error(`Invalid axis: ${axis}`);\n      }\n    }\n    if (this.axis.length !== unique2(this.axis).length) {\n      throw new Error(`Found duplicate axes in: ${this.axis}`);\n    }\n    const paramShape = this.axis.map((axis) => inputShape[axis]);\n    const trainable = true;\n    if (this.scale) {\n      this.gamma = this.addWeight(\"gamma\", paramShape, \"float32\", this.gammaInitializer, this.gammaRegularizer, trainable);\n    } else {\n      this.gamma = null;\n    }\n    if (this.center) {\n      this.beta = this.addWeight(\"beta\", paramShape, \"float32\", this.betaInitializer, this.betaRegularizer, trainable);\n    } else {\n      this.beta = null;\n    }\n    this.built = true;\n  }\n  call(inputs, kwargs) {\n    const input2 = getExactlyOneTensor(inputs);\n    const inputShape = input2.shape;\n    const nDims = inputShape.length;\n    return tidy(() => {\n      const keepDims = true;\n      let { mean: mean5, variance } = moments(input2, this.axis, keepDims);\n      const broadcastShape = pyListRepeat(1, nDims);\n      for (const dim of this.axis) {\n        broadcastShape[dim] = inputShape[dim];\n      }\n      const broadcast = (v) => {\n        if (v != null && v.shape.length !== nDims) {\n          return reshape(v, broadcastShape);\n        } else {\n          return v;\n        }\n      };\n      let scale2 = this.scale ? broadcast(this.gamma.read()) : null;\n      let offset = this.center ? broadcast(this.beta.read()) : null;\n      const momentsTiling = [];\n      const scaleOffsetTiling = [];\n      for (let i2 = 0; i2 < nDims; ++i2) {\n        if (this.axis.indexOf(i2) !== -1) {\n          momentsTiling.push(inputShape[i2]);\n          scaleOffsetTiling.push(1);\n        } else {\n          momentsTiling.push(1);\n          scaleOffsetTiling.push(inputShape[i2]);\n        }\n      }\n      mean5 = tile(mean5, momentsTiling);\n      variance = tile(variance, momentsTiling);\n      if (scale2 != null) {\n        scale2 = tile(scale2, scaleOffsetTiling);\n      }\n      if (offset != null) {\n        offset = tile(offset, scaleOffsetTiling);\n      }\n      return batchNormalization(input2, mean5, variance, offset, scale2, this.epsilon);\n    });\n  }\n  getConfig() {\n    const config = {\n      axis: this.axis,\n      epsilon: this.epsilon,\n      center: this.center,\n      scale: this.scale,\n      betaInitializer: serializeInitializer(this.betaInitializer),\n      gammaInitializer: serializeInitializer(this.gammaInitializer),\n      betaRegularizer: serializeRegularizer(this.betaRegularizer),\n      gammaRegularizer: serializeRegularizer(this.gammaRegularizer)\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nLayerNormalization.className = \"LayerNormalization\";\nserialization_exports.registerClass(LayerNormalization);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/padding.js\nfunction spatial2dPadding(x, padding, dataFormat) {\n  return tidy(() => {\n    if (x.rank !== 4) {\n      throw new ValueError(`temporalPadding expects input tensor to be 4-D, but received a ${x.rank}-D tensor.`);\n    }\n    if (padding == null) {\n      padding = [[1, 1], [1, 1]];\n    }\n    if (padding.length !== 2 || padding[0].length !== 2 || padding[1].length !== 2) {\n      throw new ValueError(\"spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.\");\n    }\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    if (dataFormat !== \"channelsLast\" && dataFormat !== \"channelsFirst\") {\n      throw new ValueError(`Unknown data format: ${dataFormat}. Supported data formats are 'channelsLast' and 'channelsFirst.`);\n    }\n    let pattern;\n    if (dataFormat === \"channelsFirst\") {\n      pattern = [[0, 0], [0, 0], padding[0], padding[1]];\n    } else {\n      pattern = [[0, 0], padding[0], padding[1], [0, 0]];\n    }\n    return pad(x, pattern);\n  });\n}\nvar ZeroPadding2D = class extends Layer {\n  constructor(args) {\n    if (args == null) {\n      args = {};\n    }\n    super(args);\n    this.dataFormat = args.dataFormat == null ? imageDataFormat() : args.dataFormat;\n    if (args.padding == null) {\n      this.padding = [[1, 1], [1, 1]];\n    } else if (typeof args.padding === \"number\") {\n      this.padding = [[args.padding, args.padding], [args.padding, args.padding]];\n    } else {\n      args.padding = args.padding;\n      if (args.padding.length !== 2) {\n        throw new ValueError(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${args.padding.length} array.`);\n      }\n      let heightPadding;\n      let widthPadding;\n      if (typeof args.padding[0] === \"number\") {\n        heightPadding = [args.padding[0], args.padding[0]];\n        widthPadding = [args.padding[1], args.padding[1]];\n      } else {\n        args.padding = args.padding;\n        if (args.padding[0].length !== 2) {\n          throw new ValueError(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${args.padding[0].length} array.`);\n        }\n        heightPadding = args.padding[0];\n        if (args.padding[1].length !== 2) {\n          throw new ValueError(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${args.padding[1].length} array.`);\n        }\n        widthPadding = args.padding[1];\n      }\n      this.padding = [heightPadding, widthPadding];\n    }\n    this.inputSpec = [new InputSpec({ ndim: 4 })];\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    let rows;\n    let cols;\n    if (this.dataFormat === \"channelsFirst\") {\n      if (inputShape[2] != null && inputShape[2] >= 0) {\n        rows = inputShape[2] + this.padding[0][0] + this.padding[0][1];\n      } else {\n        rows = null;\n      }\n      if (inputShape[3] != null && inputShape[3] >= 0) {\n        cols = inputShape[3] + this.padding[1][0] + this.padding[1][1];\n      } else {\n        cols = null;\n      }\n      return [inputShape[0], inputShape[1], rows, cols];\n    } else {\n      if (inputShape[1] != null && inputShape[1] >= 0) {\n        rows = inputShape[1] + this.padding[0][0] + this.padding[0][1];\n      } else {\n        rows = null;\n      }\n      if (inputShape[2] != null && inputShape[2] >= 0) {\n        cols = inputShape[2] + this.padding[1][0] + this.padding[1][1];\n      } else {\n        cols = null;\n      }\n      return [inputShape[0], rows, cols, inputShape[3]];\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => spatial2dPadding(getExactlyOneTensor(inputs), this.padding, this.dataFormat));\n  }\n  getConfig() {\n    const config = {\n      padding: this.padding,\n      dataFormat: this.dataFormat\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nZeroPadding2D.className = \"ZeroPadding2D\";\nserialization_exports.registerClass(ZeroPadding2D);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/pooling.js\nfunction pool2d(x, poolSize, strides, padding, dataFormat, poolMode) {\n  return tidy(() => {\n    checkDataFormat(dataFormat);\n    checkPoolMode(poolMode);\n    checkPaddingMode(padding);\n    if (strides == null) {\n      strides = [1, 1];\n    }\n    if (padding == null) {\n      padding = \"valid\";\n    }\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    if (poolMode == null) {\n      poolMode = \"max\";\n    }\n    x = preprocessConv2DInput(x, dataFormat);\n    let y;\n    const paddingString = padding === \"same\" ? \"same\" : \"valid\";\n    if (poolMode === \"max\") {\n      y = maxPool(x, poolSize, strides, paddingString);\n    } else {\n      y = avgPool(\n        x,\n        poolSize,\n        strides,\n        paddingString\n      );\n    }\n    if (dataFormat === \"channelsFirst\") {\n      y = transpose(y, [0, 3, 1, 2]);\n    }\n    return y;\n  });\n}\nfunction pool3d(x, poolSize, strides, padding, dataFormat, poolMode) {\n  return tidy(() => {\n    checkDataFormat(dataFormat);\n    checkPoolMode(poolMode);\n    checkPaddingMode(padding);\n    if (strides == null) {\n      strides = [1, 1, 1];\n    }\n    if (padding == null) {\n      padding = \"valid\";\n    }\n    if (dataFormat == null) {\n      dataFormat = imageDataFormat();\n    }\n    if (poolMode == null) {\n      poolMode = \"max\";\n    }\n    x = preprocessConv3DInput(x, dataFormat);\n    let y;\n    const paddingString = padding === \"same\" ? \"same\" : \"valid\";\n    if (poolMode === \"max\") {\n      y = maxPool3d(x, poolSize, strides, paddingString);\n    } else {\n      y = avgPool3d(x, poolSize, strides, paddingString);\n    }\n    if (dataFormat === \"channelsFirst\") {\n      y = transpose(y, [0, 4, 1, 2, 3]);\n    }\n    return y;\n  });\n}\nvar Pooling1D = class extends Layer {\n  constructor(args) {\n    if (args.poolSize == null) {\n      args.poolSize = 2;\n    }\n    super(args);\n    if (typeof args.poolSize === \"number\") {\n      this.poolSize = [args.poolSize];\n    } else if (Array.isArray(args.poolSize) && args.poolSize.length === 1 && typeof args.poolSize[0] === \"number\") {\n      this.poolSize = args.poolSize;\n    } else {\n      throw new ValueError(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(args.poolSize)}`);\n    }\n    assertPositiveInteger(this.poolSize, \"poolSize\");\n    if (args.strides == null) {\n      this.strides = this.poolSize;\n    } else {\n      if (typeof args.strides === \"number\") {\n        this.strides = [args.strides];\n      } else if (Array.isArray(args.strides) && args.strides.length === 1 && typeof args.strides[0] === \"number\") {\n        this.strides = args.strides;\n      } else {\n        throw new ValueError(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(args.strides)}`);\n      }\n    }\n    assertPositiveInteger(this.strides, \"strides\");\n    this.padding = args.padding == null ? \"valid\" : args.padding;\n    checkPaddingMode(this.padding);\n    this.inputSpec = [new InputSpec({ ndim: 3 })];\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const length = convOutputLength(inputShape[1], this.poolSize[0], this.padding, this.strides[0]);\n    return [inputShape[0], length, inputShape[2]];\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      inputs = expandDims2(getExactlyOneTensor(inputs), 2);\n      const output = this.poolingFunction(getExactlyOneTensor(inputs), [this.poolSize[0], 1], [this.strides[0], 1], this.padding, \"channelsLast\");\n      return squeeze(output, [2]);\n    });\n  }\n  getConfig() {\n    const config = {\n      poolSize: this.poolSize,\n      padding: this.padding,\n      strides: this.strides\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nvar MaxPooling1D = class extends Pooling1D {\n  constructor(args) {\n    super(args);\n  }\n  poolingFunction(inputs, poolSize, strides, padding, dataFormat) {\n    checkDataFormat(dataFormat);\n    checkPaddingMode(padding);\n    return pool2d(inputs, poolSize, strides, padding, dataFormat, \"max\");\n  }\n};\nMaxPooling1D.className = \"MaxPooling1D\";\nserialization_exports.registerClass(MaxPooling1D);\nvar AveragePooling1D = class extends Pooling1D {\n  constructor(args) {\n    super(args);\n  }\n  poolingFunction(inputs, poolSize, strides, padding, dataFormat) {\n    checkDataFormat(dataFormat);\n    checkPaddingMode(padding);\n    return pool2d(inputs, poolSize, strides, padding, dataFormat, \"avg\");\n  }\n};\nAveragePooling1D.className = \"AveragePooling1D\";\nserialization_exports.registerClass(AveragePooling1D);\nvar Pooling2D = class extends Layer {\n  constructor(args) {\n    if (args.poolSize == null) {\n      args.poolSize = [2, 2];\n    }\n    super(args);\n    this.poolSize = Array.isArray(args.poolSize) ? args.poolSize : [args.poolSize, args.poolSize];\n    if (args.strides == null) {\n      this.strides = this.poolSize;\n    } else if (Array.isArray(args.strides)) {\n      if (args.strides.length !== 2) {\n        throw new ValueError(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${args.strides.length}.`);\n      }\n      this.strides = args.strides;\n    } else {\n      this.strides = [args.strides, args.strides];\n    }\n    assertPositiveInteger(this.poolSize, \"poolSize\");\n    assertPositiveInteger(this.strides, \"strides\");\n    this.padding = args.padding == null ? \"valid\" : args.padding;\n    this.dataFormat = args.dataFormat == null ? \"channelsLast\" : args.dataFormat;\n    checkDataFormat(this.dataFormat);\n    checkPaddingMode(this.padding);\n    this.inputSpec = [new InputSpec({ ndim: 4 })];\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    let rows = this.dataFormat === \"channelsFirst\" ? inputShape[2] : inputShape[1];\n    let cols = this.dataFormat === \"channelsFirst\" ? inputShape[3] : inputShape[2];\n    rows = convOutputLength(rows, this.poolSize[0], this.padding, this.strides[0]);\n    cols = convOutputLength(cols, this.poolSize[1], this.padding, this.strides[1]);\n    if (this.dataFormat === \"channelsFirst\") {\n      return [inputShape[0], inputShape[1], rows, cols];\n    } else {\n      return [inputShape[0], rows, cols, inputShape[3]];\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      return this.poolingFunction(getExactlyOneTensor(inputs), this.poolSize, this.strides, this.padding, this.dataFormat);\n    });\n  }\n  getConfig() {\n    const config = {\n      poolSize: this.poolSize,\n      padding: this.padding,\n      strides: this.strides,\n      dataFormat: this.dataFormat\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nvar MaxPooling2D = class extends Pooling2D {\n  constructor(args) {\n    super(args);\n  }\n  poolingFunction(inputs, poolSize, strides, padding, dataFormat) {\n    checkDataFormat(dataFormat);\n    checkPaddingMode(padding);\n    return pool2d(inputs, poolSize, strides, padding, dataFormat, \"max\");\n  }\n};\nMaxPooling2D.className = \"MaxPooling2D\";\nserialization_exports.registerClass(MaxPooling2D);\nvar AveragePooling2D = class extends Pooling2D {\n  constructor(args) {\n    super(args);\n  }\n  poolingFunction(inputs, poolSize, strides, padding, dataFormat) {\n    checkDataFormat(dataFormat);\n    checkPaddingMode(padding);\n    return pool2d(inputs, poolSize, strides, padding, dataFormat, \"avg\");\n  }\n};\nAveragePooling2D.className = \"AveragePooling2D\";\nserialization_exports.registerClass(AveragePooling2D);\nvar Pooling3D = class extends Layer {\n  constructor(args) {\n    if (args.poolSize == null) {\n      args.poolSize = [2, 2, 2];\n    }\n    super(args);\n    this.poolSize = Array.isArray(args.poolSize) ? args.poolSize : [args.poolSize, args.poolSize, args.poolSize];\n    if (args.strides == null) {\n      this.strides = this.poolSize;\n    } else if (Array.isArray(args.strides)) {\n      if (args.strides.length !== 3) {\n        throw new ValueError(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${args.strides.length}.`);\n      }\n      this.strides = args.strides;\n    } else {\n      this.strides = [args.strides, args.strides, args.strides];\n    }\n    assertPositiveInteger(this.poolSize, \"poolSize\");\n    assertPositiveInteger(this.strides, \"strides\");\n    this.padding = args.padding == null ? \"valid\" : args.padding;\n    this.dataFormat = args.dataFormat == null ? \"channelsLast\" : args.dataFormat;\n    checkDataFormat(this.dataFormat);\n    checkPaddingMode(this.padding);\n    this.inputSpec = [new InputSpec({ ndim: 5 })];\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    let depths = this.dataFormat === \"channelsFirst\" ? inputShape[2] : inputShape[1];\n    let rows = this.dataFormat === \"channelsFirst\" ? inputShape[3] : inputShape[2];\n    let cols = this.dataFormat === \"channelsFirst\" ? inputShape[4] : inputShape[3];\n    depths = convOutputLength(depths, this.poolSize[0], this.padding, this.strides[0]);\n    rows = convOutputLength(rows, this.poolSize[1], this.padding, this.strides[1]);\n    cols = convOutputLength(cols, this.poolSize[2], this.padding, this.strides[2]);\n    if (this.dataFormat === \"channelsFirst\") {\n      return [inputShape[0], inputShape[1], depths, rows, cols];\n    } else {\n      return [inputShape[0], depths, rows, cols, inputShape[4]];\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      this.invokeCallHook(inputs, kwargs);\n      return this.poolingFunction(getExactlyOneTensor(inputs), this.poolSize, this.strides, this.padding, this.dataFormat);\n    });\n  }\n  getConfig() {\n    const config = {\n      poolSize: this.poolSize,\n      padding: this.padding,\n      strides: this.strides,\n      dataFormat: this.dataFormat\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nvar MaxPooling3D = class extends Pooling3D {\n  constructor(args) {\n    super(args);\n  }\n  poolingFunction(inputs, poolSize, strides, padding, dataFormat) {\n    checkDataFormat(dataFormat);\n    checkPaddingMode(padding);\n    return pool3d(inputs, poolSize, strides, padding, dataFormat, \"max\");\n  }\n};\nMaxPooling3D.className = \"MaxPooling3D\";\nserialization_exports.registerClass(MaxPooling3D);\nvar AveragePooling3D = class extends Pooling3D {\n  constructor(args) {\n    super(args);\n  }\n  poolingFunction(inputs, poolSize, strides, padding, dataFormat) {\n    checkDataFormat(dataFormat);\n    checkPaddingMode(padding);\n    return pool3d(inputs, poolSize, strides, padding, dataFormat, \"avg\");\n  }\n};\nAveragePooling3D.className = \"AveragePooling3D\";\nserialization_exports.registerClass(AveragePooling3D);\nvar GlobalPooling1D = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.inputSpec = [new InputSpec({ ndim: 3 })];\n  }\n  computeOutputShape(inputShape) {\n    return [inputShape[0], inputShape[2]];\n  }\n  call(inputs, kwargs) {\n    throw new NotImplementedError();\n  }\n};\nvar GlobalAveragePooling1D = class extends GlobalPooling1D {\n  constructor(args) {\n    super(args || {});\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const input2 = getExactlyOneTensor(inputs);\n      return mean(input2, 1);\n    });\n  }\n};\nGlobalAveragePooling1D.className = \"GlobalAveragePooling1D\";\nserialization_exports.registerClass(GlobalAveragePooling1D);\nvar GlobalMaxPooling1D = class extends GlobalPooling1D {\n  constructor(args) {\n    super(args || {});\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const input2 = getExactlyOneTensor(inputs);\n      return max(input2, 1);\n    });\n  }\n};\nGlobalMaxPooling1D.className = \"GlobalMaxPooling1D\";\nserialization_exports.registerClass(GlobalMaxPooling1D);\nvar GlobalPooling2D = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.dataFormat = args.dataFormat == null ? \"channelsLast\" : args.dataFormat;\n    checkDataFormat(this.dataFormat);\n    this.inputSpec = [new InputSpec({ ndim: 4 })];\n  }\n  computeOutputShape(inputShape) {\n    inputShape = inputShape;\n    if (this.dataFormat === \"channelsLast\") {\n      return [inputShape[0], inputShape[3]];\n    } else {\n      return [inputShape[0], inputShape[1]];\n    }\n  }\n  call(inputs, kwargs) {\n    throw new NotImplementedError();\n  }\n  getConfig() {\n    const config = { dataFormat: this.dataFormat };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n};\nvar GlobalAveragePooling2D = class extends GlobalPooling2D {\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const input2 = getExactlyOneTensor(inputs);\n      if (this.dataFormat === \"channelsLast\") {\n        return mean(input2, [1, 2]);\n      } else {\n        return mean(input2, [2, 3]);\n      }\n    });\n  }\n};\nGlobalAveragePooling2D.className = \"GlobalAveragePooling2D\";\nserialization_exports.registerClass(GlobalAveragePooling2D);\nvar GlobalMaxPooling2D = class extends GlobalPooling2D {\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const input2 = getExactlyOneTensor(inputs);\n      if (this.dataFormat === \"channelsLast\") {\n        return max(input2, [1, 2]);\n      } else {\n        return max(input2, [2, 3]);\n      }\n    });\n  }\n};\nGlobalMaxPooling2D.className = \"GlobalMaxPooling2D\";\nserialization_exports.registerClass(GlobalMaxPooling2D);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/layers/wrappers.js\nvar Wrapper = class extends Layer {\n  constructor(args) {\n    super(args);\n    this.layer = args.layer;\n  }\n  build(inputShape) {\n    this.built = true;\n  }\n  get trainable() {\n    if (this.layer != null) {\n      return this.layer.trainable;\n    } else {\n      return false;\n    }\n  }\n  set trainable(value) {\n    if (this.layer != null) {\n      this.layer.trainable = value;\n    }\n  }\n  get trainableWeights() {\n    return this.layer.trainableWeights;\n  }\n  get nonTrainableWeights() {\n    return this.layer.nonTrainableWeights;\n  }\n  get updates() {\n    return this.layer._updates;\n  }\n  get losses() {\n    return this.layer.losses;\n  }\n  getWeights() {\n    return this.layer.getWeights();\n  }\n  setWeights(weights) {\n    this.layer.setWeights(weights);\n  }\n  getConfig() {\n    const config = {\n      \"layer\": {\n        \"className\": this.layer.getClassName(),\n        \"config\": this.layer.getConfig()\n      }\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  setFastWeightInitDuringBuild(value) {\n    super.setFastWeightInitDuringBuild(value);\n    if (this.layer != null) {\n      this.layer.setFastWeightInitDuringBuild(value);\n    }\n  }\n  static fromConfig(cls, config, customObjects = {}) {\n    const layerConfig = config[\"layer\"];\n    const layer = deserialize(layerConfig, customObjects);\n    delete config[\"layer\"];\n    const newConfig = { layer };\n    Object.assign(newConfig, config);\n    return new cls(newConfig);\n  }\n};\nvar TimeDistributed = class extends Wrapper {\n  constructor(args) {\n    super(args);\n    this.supportsMasking = true;\n  }\n  build(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    if (inputShape.length < 3) {\n      throw new ValueError(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(inputShape)}`);\n    }\n    this.inputSpec = [{ shape: inputShape }];\n    const childInputShape = [inputShape[0]].concat(inputShape.slice(2));\n    if (!this.layer.built) {\n      this.layer.build(childInputShape);\n      this.layer.built = true;\n    }\n    super.build(inputShape);\n  }\n  computeOutputShape(inputShape) {\n    inputShape = getExactlyOneShape(inputShape);\n    const childInputShape = [inputShape[0]].concat(inputShape.slice(2));\n    const childOutputShape = this.layer.computeOutputShape(childInputShape);\n    const timesteps = inputShape[1];\n    return [childOutputShape[0], timesteps].concat(childOutputShape.slice(1));\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      inputs = getExactlyOneTensor(inputs);\n      const step5 = (inputs2, states) => {\n        const output = getExactlyOneTensor(this.layer.call(inputs2, kwargs));\n        return [output, []];\n      };\n      const rnnOutputs = rnn(step5, inputs, [], false, null, null, false, true);\n      const y = rnnOutputs[1];\n      return y;\n    });\n  }\n};\nTimeDistributed.className = \"TimeDistributed\";\nserialization_exports.registerClass(TimeDistributed);\nfunction checkBidirectionalMergeMode(value) {\n  checkStringTypeUnionValue(VALID_BIDIRECTIONAL_MERGE_MODES, \"BidirectionalMergeMode\", value);\n}\nvar DEFAULT_BIDIRECTIONAL_MERGE_MODE = \"concat\";\nvar Bidirectional = class extends Wrapper {\n  constructor(args) {\n    super(args);\n    const layerConfig = args.layer.getConfig();\n    const forwDict = {};\n    forwDict[\"className\"] = args.layer.getClassName();\n    forwDict[\"config\"] = layerConfig;\n    this.forwardLayer = deserialize(forwDict);\n    layerConfig[\"goBackwards\"] = layerConfig[\"goBackwards\"] === true ? false : true;\n    const backDict = {};\n    backDict[\"className\"] = args.layer.getClassName();\n    backDict[\"config\"] = layerConfig;\n    this.backwardLayer = deserialize(backDict);\n    this.forwardLayer.name = \"forward_\" + this.forwardLayer.name;\n    this.backwardLayer.name = \"backward_\" + this.backwardLayer.name;\n    this.mergeMode = args.mergeMode === void 0 ? DEFAULT_BIDIRECTIONAL_MERGE_MODE : args.mergeMode;\n    checkBidirectionalMergeMode(this.mergeMode);\n    if (args.weights) {\n      throw new NotImplementedError(\"weights support is not implemented for Bidirectional layer yet.\");\n    }\n    this._stateful = args.layer.stateful;\n    this.returnSequences = args.layer.returnSequences;\n    this.returnState = args.layer.returnState;\n    this.supportsMasking = true;\n    this._trainable = true;\n    this.inputSpec = args.layer.inputSpec;\n    this.numConstants = null;\n  }\n  get trainable() {\n    return this._trainable;\n  }\n  set trainable(value) {\n    this._trainable = value;\n    if (this.forwardLayer != null) {\n      this.forwardLayer.trainable = value;\n    }\n    if (this.backwardLayer != null) {\n      this.backwardLayer.trainable = value;\n    }\n  }\n  getWeights() {\n    return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights());\n  }\n  setWeights(weights) {\n    const numWeights = weights.length;\n    const numeightsOver2 = Math.floor(numWeights / 2);\n    this.forwardLayer.setWeights(weights.slice(0, numeightsOver2));\n    this.backwardLayer.setWeights(weights.slice(numeightsOver2));\n  }\n  computeOutputShape(inputShape) {\n    let layerShapes = this.forwardLayer.computeOutputShape(inputShape);\n    if (!(Array.isArray(layerShapes) && Array.isArray(layerShapes[0]))) {\n      layerShapes = [layerShapes];\n    }\n    layerShapes = layerShapes;\n    let outputShape;\n    let outputShapes;\n    let stateShape;\n    if (this.returnState) {\n      stateShape = layerShapes.slice(1);\n      outputShape = layerShapes[0];\n    } else {\n      outputShape = layerShapes[0];\n    }\n    outputShape = outputShape;\n    if (this.mergeMode === \"concat\") {\n      outputShape[outputShape.length - 1] *= 2;\n      outputShapes = [outputShape];\n    } else if (this.mergeMode == null) {\n      outputShapes = [outputShape, outputShape.slice()];\n    } else {\n      outputShapes = [outputShape];\n    }\n    if (this.returnState) {\n      if (this.mergeMode == null) {\n        return outputShapes.concat(stateShape).concat(stateShape.slice());\n      }\n      return [outputShape].concat(stateShape).concat(stateShape.slice());\n    }\n    return singletonOrArray(outputShapes);\n  }\n  apply(inputs, kwargs) {\n    let initialState = kwargs == null ? null : kwargs[\"initialState\"];\n    let constants = kwargs == null ? null : kwargs[\"constants\"];\n    if (kwargs == null) {\n      kwargs = {};\n    }\n    const standardized = standardizeArgs(inputs, initialState, constants, this.numConstants);\n    inputs = standardized.inputs;\n    initialState = standardized.initialState;\n    constants = standardized.constants;\n    if (Array.isArray(inputs)) {\n      initialState = inputs.slice(1);\n      inputs = inputs[0];\n    }\n    if ((initialState == null || initialState.length === 0) && constants == null) {\n      return super.apply(inputs, kwargs);\n    }\n    const additionalInputs = [];\n    const additionalSpecs = [];\n    if (initialState != null) {\n      const numStates = initialState.length;\n      if (numStates % 2 > 0) {\n        throw new ValueError(\"When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.\");\n      }\n      kwargs[\"initialState\"] = initialState;\n      additionalInputs.push(...initialState);\n      const stateSpecs = initialState.map((state) => new InputSpec({ shape: state.shape }));\n      this.forwardLayer.stateSpec = stateSpecs.slice(0, numStates / 2);\n      this.backwardLayer.stateSpec = stateSpecs.slice(numStates / 2);\n      additionalSpecs.push(...stateSpecs);\n    }\n    if (constants != null) {\n      throw new NotImplementedError(\"Support for constants in Bidirectional layers is not implemented yet.\");\n    }\n    const isSymbolicTensor = additionalInputs[0] instanceof SymbolicTensor;\n    for (const tensor2 of additionalInputs) {\n      if (tensor2 instanceof SymbolicTensor !== isSymbolicTensor) {\n        throw new ValueError(\"The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors\");\n      }\n    }\n    if (isSymbolicTensor) {\n      const fullInput = [inputs].concat(additionalInputs);\n      const fullInputSpec = this.inputSpec.concat(additionalSpecs);\n      const originalInputSpec = this.inputSpec;\n      this.inputSpec = fullInputSpec;\n      const output = super.apply(fullInput, kwargs);\n      this.inputSpec = originalInputSpec;\n      return output;\n    } else {\n      return super.apply(inputs, kwargs);\n    }\n  }\n  call(inputs, kwargs) {\n    return tidy(() => {\n      const initialState = kwargs[\"initialState\"];\n      let y;\n      let yRev;\n      if (initialState == null) {\n        y = this.forwardLayer.call(inputs, kwargs);\n        yRev = this.backwardLayer.call(inputs, kwargs);\n      } else {\n        const forwardState = initialState.slice(0, initialState.length / 2);\n        const backwardState = initialState.slice(initialState.length / 2);\n        y = this.forwardLayer.call(inputs, Object.assign(kwargs, { initialState: forwardState }));\n        yRev = this.backwardLayer.call(inputs, Object.assign(kwargs, { initialState: backwardState }));\n      }\n      let states;\n      if (this.returnState) {\n        if (Array.isArray(y)) {\n          states = y.slice(1).concat(yRev.slice(1));\n        } else {\n        }\n        y = y[0];\n        yRev = yRev[0];\n      }\n      if (this.returnSequences) {\n        yRev = reverse(yRev, 1);\n      }\n      let output;\n      if (this.mergeMode === \"concat\") {\n        output = concatenate([y, yRev]);\n      } else if (this.mergeMode === \"sum\") {\n        output = add2(y, yRev);\n      } else if (this.mergeMode === \"ave\") {\n        output = mul(0.5, add2(y, yRev));\n      } else if (this.mergeMode === \"mul\") {\n        output = mul(y, yRev);\n      } else if (this.mergeMode == null) {\n        output = [y, yRev];\n      }\n      if (this.returnState) {\n        if (this.mergeMode == null) {\n          return output.concat(states);\n        }\n        return [output].concat(states);\n      }\n      return output;\n    });\n  }\n  resetStates(states) {\n    this.forwardLayer.resetStates();\n    this.backwardLayer.resetStates();\n  }\n  build(inputShape) {\n    nameScope(this.forwardLayer.name, () => {\n      this.forwardLayer.build(inputShape);\n    });\n    nameScope(this.backwardLayer.name, () => {\n      this.backwardLayer.build(inputShape);\n    });\n    this.built = true;\n  }\n  computeMask(inputs, mask) {\n    if (Array.isArray(mask)) {\n      mask = mask[0];\n    }\n    let outputMask;\n    if (this.returnSequences) {\n      if (this.mergeMode == null) {\n        outputMask = [mask, mask];\n      } else {\n        outputMask = mask;\n      }\n    } else {\n      if (this.mergeMode == null) {\n        outputMask = [null, null];\n      } else {\n        outputMask = null;\n      }\n    }\n    if (this.returnState) {\n      const states = this.forwardLayer.states;\n      const stateMask = states.map((state) => null);\n      if (Array.isArray(outputMask)) {\n        return outputMask.concat(stateMask).concat(stateMask);\n      } else {\n        return [outputMask].concat(stateMask).concat(stateMask);\n      }\n    } else {\n      return outputMask;\n    }\n  }\n  get trainableWeights() {\n    return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights);\n  }\n  get nonTrainableWeights() {\n    return this.forwardLayer.nonTrainableWeights.concat(this.backwardLayer.nonTrainableWeights);\n  }\n  setFastWeightInitDuringBuild(value) {\n    super.setFastWeightInitDuringBuild(value);\n    if (this.forwardLayer != null) {\n      this.forwardLayer.setFastWeightInitDuringBuild(value);\n    }\n    if (this.backwardLayer != null) {\n      this.backwardLayer.setFastWeightInitDuringBuild(value);\n    }\n  }\n  getConfig() {\n    const config = {\n      \"mergeMode\": this.mergeMode\n    };\n    const baseConfig = super.getConfig();\n    Object.assign(config, baseConfig);\n    return config;\n  }\n  static fromConfig(cls, config) {\n    const rnnLayer = deserialize(config[\"layer\"]);\n    delete config[\"layer\"];\n    if (config[\"numConstants\"] != null) {\n      throw new NotImplementedError(`Deserialization of a Bidirectional layer with numConstants present is not supported yet.`);\n    }\n    const newConfig = config;\n    newConfig[\"layer\"] = rnnLayer;\n    return new cls(newConfig);\n  }\n};\nBidirectional.className = \"Bidirectional\";\nserialization_exports.registerClass(Bidirectional);\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_layers.js\nfunction inputLayer(args) {\n  return new InputLayer(args);\n}\nfunction elu3(args) {\n  return new ELU(args);\n}\nfunction reLU(args) {\n  return new ReLU(args);\n}\nfunction leakyReLU(args) {\n  return new LeakyReLU(args);\n}\nfunction prelu2(args) {\n  return new PReLU(args);\n}\nfunction softmax2(args) {\n  return new Softmax3(args);\n}\nfunction thresholdedReLU(args) {\n  return new ThresholdedReLU(args);\n}\nfunction conv1d2(args) {\n  return new Conv1D(args);\n}\nfunction conv2d3(args) {\n  return new Conv2D2(args);\n}\nfunction conv2dTranspose2(args) {\n  return new Conv2DTranspose(args);\n}\nfunction conv3d2(args) {\n  return new Conv3D2(args);\n}\nfunction conv3dTranspose2(args) {\n  return new Conv3DTranspose(args);\n}\nfunction separableConv2d2(args) {\n  return new SeparableConv2D(args);\n}\nfunction cropping2D(args) {\n  return new Cropping2D(args);\n}\nfunction upSampling2d(args) {\n  return new UpSampling2D(args);\n}\nfunction depthwiseConv2d4(args) {\n  return new DepthwiseConv2D(args);\n}\nfunction activation(args) {\n  return new Activation2(args);\n}\nfunction dense(args) {\n  return new Dense(args);\n}\nfunction dropout3(args) {\n  return new Dropout(args);\n}\nfunction spatialDropout1d(args) {\n  return new SpatialDropout1D(args);\n}\nfunction flatten3(args) {\n  return new Flatten(args);\n}\nfunction repeatVector(args) {\n  return new RepeatVector(args);\n}\nfunction reshape2(args) {\n  return new Reshape2(args);\n}\nfunction permute(args) {\n  return new Permute(args);\n}\nfunction embedding(args) {\n  return new Embedding(args);\n}\nfunction add3(args) {\n  return new Add2(args);\n}\nfunction average(args) {\n  return new Average(args);\n}\nfunction concatenate2(args) {\n  return new Concatenate(args);\n}\nfunction maximum2(args) {\n  return new Maximum2(args);\n}\nfunction minimum2(args) {\n  return new Minimum2(args);\n}\nfunction multiply(args) {\n  return new Multiply2(args);\n}\nfunction dot3(args) {\n  return new Dot(args);\n}\nfunction batchNormalization2(args) {\n  return new BatchNormalization(args);\n}\nfunction layerNormalization(args) {\n  return new LayerNormalization(args);\n}\nfunction zeroPadding2d(args) {\n  return new ZeroPadding2D(args);\n}\nfunction averagePooling1d(args) {\n  return new AveragePooling1D(args);\n}\nfunction avgPool1d(args) {\n  return averagePooling1d(args);\n}\nfunction avgPooling1d(args) {\n  return averagePooling1d(args);\n}\nfunction averagePooling2d(args) {\n  return new AveragePooling2D(args);\n}\nfunction avgPool2d(args) {\n  return averagePooling2d(args);\n}\nfunction avgPooling2d(args) {\n  return averagePooling2d(args);\n}\nfunction averagePooling3d(args) {\n  return new AveragePooling3D(args);\n}\nfunction avgPool3d2(args) {\n  return averagePooling3d(args);\n}\nfunction avgPooling3d(args) {\n  return averagePooling3d(args);\n}\nfunction globalAveragePooling1d(args) {\n  return new GlobalAveragePooling1D(args);\n}\nfunction globalAveragePooling2d(args) {\n  return new GlobalAveragePooling2D(args);\n}\nfunction globalMaxPooling1d(args) {\n  return new GlobalMaxPooling1D(args);\n}\nfunction globalMaxPooling2d(args) {\n  return new GlobalMaxPooling2D(args);\n}\nfunction maxPooling1d(args) {\n  return new MaxPooling1D(args);\n}\nfunction maxPooling2d(args) {\n  return new MaxPooling2D(args);\n}\nfunction maxPooling3d(args) {\n  return new MaxPooling3D(args);\n}\nfunction gru(args) {\n  return new GRU(args);\n}\nfunction gruCell(args) {\n  return new GRUCell(args);\n}\nfunction lstm(args) {\n  return new LSTM(args);\n}\nfunction lstmCell(args) {\n  return new LSTMCell(args);\n}\nfunction simpleRNN(args) {\n  return new SimpleRNN(args);\n}\nfunction simpleRNNCell(args) {\n  return new SimpleRNNCell(args);\n}\nfunction convLstm2d(args) {\n  return new ConvLSTM2D(args);\n}\nfunction convLstm2dCell(args) {\n  return new ConvLSTM2DCell(args);\n}\nfunction rnn2(args) {\n  return new RNN(args);\n}\nfunction stackedRNNCells(args) {\n  return new StackedRNNCells(args);\n}\nfunction bidirectional(args) {\n  return new Bidirectional(args);\n}\nfunction timeDistributed(args) {\n  return new TimeDistributed(args);\n}\nvar globalMaxPool1d = globalMaxPooling1d;\nvar globalMaxPool2d = globalMaxPooling2d;\nvar maxPool1d = maxPooling1d;\nvar maxPool2d = maxPooling2d;\nfunction gaussianNoise(args) {\n  return new GaussianNoise(args);\n}\nfunction gaussianDropout(args) {\n  return new GaussianDropout(args);\n}\nfunction alphaDropout(args) {\n  return new AlphaDropout(args);\n}\nfunction masking(args) {\n  return new Masking(args);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_metrics.js\nvar exports_metrics_exports = {};\n__export(exports_metrics_exports, {\n  MAPE: () => MAPE2,\n  MSE: () => MSE2,\n  binaryAccuracy: () => binaryAccuracy2,\n  binaryCrossentropy: () => binaryCrossentropy3,\n  categoricalAccuracy: () => categoricalAccuracy2,\n  categoricalCrossentropy: () => categoricalCrossentropy3,\n  cosineProximity: () => cosineProximity2,\n  mape: () => mape2,\n  meanAbsoluteError: () => meanAbsoluteError2,\n  meanAbsolutePercentageError: () => meanAbsolutePercentageError2,\n  meanSquaredError: () => meanSquaredError3,\n  mse: () => mse2,\n  precision: () => precision2,\n  recall: () => recall2,\n  sparseCategoricalAccuracy: () => sparseCategoricalAccuracy2\n});\nfunction binaryAccuracy2(yTrue, yPred) {\n  return binaryAccuracy(yTrue, yPred);\n}\nfunction binaryCrossentropy3(yTrue, yPred) {\n  return binaryCrossentropy2(yTrue, yPred);\n}\nfunction sparseCategoricalAccuracy2(yTrue, yPred) {\n  return sparseCategoricalAccuracy(yTrue, yPred);\n}\nfunction categoricalAccuracy2(yTrue, yPred) {\n  return categoricalAccuracy(yTrue, yPred);\n}\nfunction categoricalCrossentropy3(yTrue, yPred) {\n  return categoricalCrossentropy2(yTrue, yPred);\n}\nfunction precision2(yTrue, yPred) {\n  return precision(yTrue, yPred);\n}\nfunction recall2(yTrue, yPred) {\n  return recall(yTrue, yPred);\n}\nfunction cosineProximity2(yTrue, yPred) {\n  return cosineProximity(yTrue, yPred);\n}\nfunction meanAbsoluteError2(yTrue, yPred) {\n  return meanAbsoluteError(yTrue, yPred);\n}\nfunction meanAbsolutePercentageError2(yTrue, yPred) {\n  return meanAbsolutePercentageError(yTrue, yPred);\n}\nfunction MAPE2(yTrue, yPred) {\n  return meanAbsolutePercentageError(yTrue, yPred);\n}\nfunction mape2(yTrue, yPred) {\n  return meanAbsolutePercentageError(yTrue, yPred);\n}\nfunction meanSquaredError3(yTrue, yPred) {\n  return meanSquaredError2(yTrue, yPred);\n}\nfunction MSE2(yTrue, yPred) {\n  return meanSquaredError2(yTrue, yPred);\n}\nfunction mse2(yTrue, yPred) {\n  return meanSquaredError2(yTrue, yPred);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_models.js\nvar exports_models_exports = {};\n__export(exports_models_exports, {\n  modelFromJSON: () => modelFromJSON\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/exports_regularizers.js\nvar exports_regularizers_exports = {};\n__export(exports_regularizers_exports, {\n  l1: () => l12,\n  l1l2: () => l1l2,\n  l2: () => l22\n});\nfunction l1l2(config) {\n  return new L1L2(config);\n}\nfunction l12(config) {\n  return l1(config);\n}\nfunction l22(config) {\n  return l2(config);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-layers@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-layers/dist/callbacks.js\nvar Callback = class extends BaseCallback {\n  constructor() {\n    super(...arguments);\n    this.model = null;\n  }\n  setModel(model2) {\n    if (!(model2 instanceof LayersModel)) {\n      throw new Error(\"model must be a LayersModel, not some other Container\");\n    }\n    this.model = model2;\n  }\n};\nfunction less2(currVal, prevVal) {\n  return currVal < prevVal;\n}\nfunction greater2(currVal, prevVal) {\n  return currVal > prevVal;\n}\nvar EarlyStopping = class extends Callback {\n  constructor(args) {\n    super();\n    if (args == null) {\n      args = {};\n    }\n    if (args.restoreBestWeights) {\n      throw new NotImplementedError(\"restoreBestWeights = True is not implemented in EarlyStopping yet.\");\n    }\n    this.monitor = args.monitor || \"val_loss\";\n    this.minDelta = Math.abs(args.minDelta || 0);\n    this.patience = args.patience || 0;\n    this.verbose = args.verbose || 0;\n    this.mode = args.mode || \"auto\";\n    this.baseline = args.baseline;\n    if ([\"auto\", \"min\", \"max\"].indexOf(this.mode) === -1) {\n      console.warn(`EarlyStopping mode '${this.mode}' is invalid. Falling back to mode 'auto'.`);\n      this.mode = \"auto\";\n    }\n    if (this.mode === \"min\") {\n      this.monitorFunc = less2;\n    } else if (this.mode === \"max\") {\n      this.monitorFunc = greater2;\n    } else {\n      if (this.monitor.indexOf(\"acc\") !== -1) {\n        this.monitorFunc = greater2;\n      } else {\n        this.monitorFunc = less2;\n      }\n    }\n    if (this.monitorFunc === less2) {\n      this.minDelta *= -1;\n    }\n  }\n  async onTrainBegin(logs) {\n    this.wait = 0;\n    this.stoppedEpoch = 0;\n    if (this.baseline != null) {\n      this.best = this.baseline;\n    } else {\n      this.best = this.monitorFunc === less2 ? Infinity : -Infinity;\n    }\n  }\n  async onEpochEnd(epoch, logs) {\n    await resolveScalarsInLogs(logs);\n    const current = this.getMonitorValue(logs);\n    if (current == null) {\n      return;\n    }\n    if (this.monitorFunc(current - this.minDelta, this.best)) {\n      this.best = current;\n      this.wait = 0;\n    } else {\n      this.wait++;\n      if (this.wait >= this.patience) {\n        this.stoppedEpoch = epoch;\n        this.model.stopTraining = true;\n      }\n    }\n  }\n  async onTrainEnd(logs) {\n    if (this.stoppedEpoch > 0 && this.verbose) {\n      console.log(`Epoch ${this.stoppedEpoch}: early stopping.`);\n    }\n  }\n  getMonitorValue(logs) {\n    if (logs == null) {\n      logs = {};\n    }\n    const monitorValue = logs[this.monitor];\n    if (monitorValue == null) {\n      console.warn(`Metric for EarlyStopping ${this.monitor} is not available. Available metrics are: ${Object.keys(logs)}`);\n    }\n    return monitorValue;\n  }\n};\nfunction earlyStopping(args) {\n  return new EarlyStopping(args);\n}\nvar callbacks = { earlyStopping };\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/flags.js\nvar ENV4 = env();\nENV4.registerFlag(\"KEEP_INTERMEDIATE_TENSORS\", () => false, (debugValue) => {\n  if (debugValue) {\n    console.warn(\"Keep intermediate tensors is ON. This will print the values of all intermediate tensors during model inference. Not all models support this mode. For details, check e2e/benchmarks/ model_config.js. This significantly impacts performance.\");\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/data/compiled_api.js\nvar DataType;\n(function(DataType2) {\n  DataType2[DataType2[\"DT_INVALID\"] = 0] = \"DT_INVALID\";\n  DataType2[DataType2[\"DT_FLOAT\"] = 1] = \"DT_FLOAT\";\n  DataType2[DataType2[\"DT_DOUBLE\"] = 2] = \"DT_DOUBLE\";\n  DataType2[DataType2[\"DT_INT32\"] = 3] = \"DT_INT32\";\n  DataType2[DataType2[\"DT_UINT8\"] = 4] = \"DT_UINT8\";\n  DataType2[DataType2[\"DT_INT16\"] = 5] = \"DT_INT16\";\n  DataType2[DataType2[\"DT_INT8\"] = 6] = \"DT_INT8\";\n  DataType2[DataType2[\"DT_STRING\"] = 7] = \"DT_STRING\";\n  DataType2[DataType2[\"DT_COMPLEX64\"] = 8] = \"DT_COMPLEX64\";\n  DataType2[DataType2[\"DT_INT64\"] = 9] = \"DT_INT64\";\n  DataType2[DataType2[\"DT_BOOL\"] = 10] = \"DT_BOOL\";\n  DataType2[DataType2[\"DT_QINT8\"] = 11] = \"DT_QINT8\";\n  DataType2[DataType2[\"DT_QUINT8\"] = 12] = \"DT_QUINT8\";\n  DataType2[DataType2[\"DT_QINT32\"] = 13] = \"DT_QINT32\";\n  DataType2[DataType2[\"DT_BFLOAT16\"] = 14] = \"DT_BFLOAT16\";\n  DataType2[DataType2[\"DT_QINT16\"] = 15] = \"DT_QINT16\";\n  DataType2[DataType2[\"DT_QUINT16\"] = 16] = \"DT_QUINT16\";\n  DataType2[DataType2[\"DT_UINT16\"] = 17] = \"DT_UINT16\";\n  DataType2[DataType2[\"DT_COMPLEX128\"] = 18] = \"DT_COMPLEX128\";\n  DataType2[DataType2[\"DT_HALF\"] = 19] = \"DT_HALF\";\n  DataType2[DataType2[\"DT_RESOURCE\"] = 20] = \"DT_RESOURCE\";\n  DataType2[DataType2[\"DT_VARIANT\"] = 21] = \"DT_VARIANT\";\n  DataType2[DataType2[\"DT_UINT32\"] = 22] = \"DT_UINT32\";\n  DataType2[DataType2[\"DT_UINT64\"] = 23] = \"DT_UINT64\";\n  DataType2[DataType2[\"DT_FLOAT_REF\"] = 101] = \"DT_FLOAT_REF\";\n  DataType2[DataType2[\"DT_DOUBLE_REF\"] = 102] = \"DT_DOUBLE_REF\";\n  DataType2[DataType2[\"DT_INT32_REF\"] = 103] = \"DT_INT32_REF\";\n  DataType2[DataType2[\"DT_UINT8_REF\"] = 104] = \"DT_UINT8_REF\";\n  DataType2[DataType2[\"DT_INT16_REF\"] = 105] = \"DT_INT16_REF\";\n  DataType2[DataType2[\"DT_INT8_REF\"] = 106] = \"DT_INT8_REF\";\n  DataType2[DataType2[\"DT_STRING_REF\"] = 107] = \"DT_STRING_REF\";\n  DataType2[DataType2[\"DT_COMPLEX64_REF\"] = 108] = \"DT_COMPLEX64_REF\";\n  DataType2[DataType2[\"DT_INT64_REF\"] = 109] = \"DT_INT64_REF\";\n  DataType2[DataType2[\"DT_BOOL_REF\"] = 110] = \"DT_BOOL_REF\";\n  DataType2[DataType2[\"DT_QINT8_REF\"] = 111] = \"DT_QINT8_REF\";\n  DataType2[DataType2[\"DT_QUINT8_REF\"] = 112] = \"DT_QUINT8_REF\";\n  DataType2[DataType2[\"DT_QINT32_REF\"] = 113] = \"DT_QINT32_REF\";\n  DataType2[DataType2[\"DT_BFLOAT16_REF\"] = 114] = \"DT_BFLOAT16_REF\";\n  DataType2[DataType2[\"DT_QINT16_REF\"] = 115] = \"DT_QINT16_REF\";\n  DataType2[DataType2[\"DT_QUINT16_REF\"] = 116] = \"DT_QUINT16_REF\";\n  DataType2[DataType2[\"DT_UINT16_REF\"] = 117] = \"DT_UINT16_REF\";\n  DataType2[DataType2[\"DT_COMPLEX128_REF\"] = 118] = \"DT_COMPLEX128_REF\";\n  DataType2[DataType2[\"DT_HALF_REF\"] = 119] = \"DT_HALF_REF\";\n  DataType2[DataType2[\"DT_RESOURCE_REF\"] = 120] = \"DT_RESOURCE_REF\";\n  DataType2[DataType2[\"DT_VARIANT_REF\"] = 121] = \"DT_VARIANT_REF\";\n  DataType2[DataType2[\"DT_UINT32_REF\"] = 122] = \"DT_UINT32_REF\";\n  DataType2[DataType2[\"DT_UINT64_REF\"] = 123] = \"DT_UINT64_REF\";\n})(DataType || (DataType = {}));\nvar SaverDef;\n(function(SaverDef2) {\n  let CheckpointFormatVersion;\n  (function(CheckpointFormatVersion2) {\n    CheckpointFormatVersion2[CheckpointFormatVersion2[\"LEGACY\"] = 0] = \"LEGACY\";\n    CheckpointFormatVersion2[CheckpointFormatVersion2[\"V1\"] = 1] = \"V1\";\n    CheckpointFormatVersion2[CheckpointFormatVersion2[\"V2\"] = 2] = \"V2\";\n  })(CheckpointFormatVersion = SaverDef2.CheckpointFormatVersion || (SaverDef2.CheckpointFormatVersion = {}));\n})(SaverDef || (SaverDef = {}));\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/custom_op/register.js\nvar CUSTOM_OPS = {};\nfunction registerOp(name, opFunc) {\n  const opMapper = {\n    tfOpName: name,\n    category: \"custom\",\n    inputs: [],\n    attrs: [],\n    customExecutor: opFunc\n  };\n  CUSTOM_OPS[name] = opMapper;\n}\nfunction getRegisteredOp(name) {\n  return CUSTOM_OPS[name];\n}\nfunction deregisterOp(name) {\n  delete CUSTOM_OPS[name];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/utils.js\nfunction getParamValue(paramName, node, tensorMap, context, resourceManager) {\n  const inputParam = node.inputParams[paramName];\n  if (inputParam && inputParam.inputIndexStart !== void 0) {\n    const start = inputParam.inputIndexStart;\n    const end = inputParam.inputIndexEnd === 0 ? void 0 : inputParam.inputIndexEnd === void 0 ? start + 1 : inputParam.inputIndexEnd;\n    if (inputParam.type === \"tensor\") {\n      return getTensor(node.inputNames[inputParam.inputIndexStart], tensorMap, context, resourceManager);\n    }\n    if (inputParam.type === \"tensors\") {\n      const inputs = node.inputNames.slice(start, end);\n      return inputs.map((name) => getTensor(name, tensorMap, context, resourceManager));\n    }\n    const tensor2 = getTensor(node.inputNames.slice(start)[0], tensorMap, context, resourceManager);\n    const data = tensor2.dataSync();\n    return inputParam.type === \"number\" ? data[0] : util_exports.toNestedArray(tensor2.shape, data);\n  }\n  const attrParam = node.attrParams[paramName];\n  return attrParam && attrParam.value;\n}\nfunction getTensor(name, tensorsMap, context, resourceManager) {\n  const [nodeName, index] = parseNodeName(name);\n  if (resourceManager != null) {\n    const tensor2 = resourceManager.getHashTableHandleByName(nodeName);\n    if (tensor2 != null) {\n      return tensor2;\n    }\n  }\n  const contextId = context.currentContextIds.find((contextId2) => {\n    return !!tensorsMap[getNodeNameWithContextId(nodeName, contextId2)];\n  });\n  return contextId !== void 0 ? tensorsMap[getNodeNameWithContextId(nodeName, contextId)][index] : void 0;\n}\nfunction getTensorsForCurrentContenxt(name, tensorsMap, context) {\n  return tensorsMap[getNodeNameWithContextId(name, context.currentContextId)];\n}\nfunction getNodeNameAndIndex(inputName, context) {\n  const [nodeName, index, outputName] = parseNodeName(inputName);\n  return [\n    getNodeNameWithContextId(nodeName, context && context.currentContextId),\n    index,\n    outputName\n  ];\n}\nfunction getNodeNameWithContextId(name, contextId) {\n  return !!contextId ? `${name}-${contextId}` : name;\n}\nfunction parseNodeName(name) {\n  const parts = name.split(\":\");\n  if (parts.length === 1) {\n    return [name, 0, void 0];\n  }\n  const nodeName = parts[0];\n  const outputName = parts.length === 3 ? parts[1] : void 0;\n  const index = Number(parts[parts.length - 1]);\n  return [nodeName, index, outputName];\n}\nfunction getPadding(node, tensorMap, context) {\n  let pad3 = getParamValue(\"pad\", node, tensorMap, context);\n  if (pad3 === \"explicit\") {\n    pad3 = getParamValue(\"explicitPaddings\", node, tensorMap, context);\n    const explicitPadding = [[0, 0], [0, 0], [0, 0], [0, 0]];\n    for (let i2 = 0; i2 < 4; i2++) {\n      explicitPadding[i2][0] = pad3[i2 * 2];\n      explicitPadding[i2][1] = pad3[i2 * 2 + 1];\n    }\n    return explicitPadding;\n  }\n  return pad3;\n}\nfunction cloneTensor(tensor2) {\n  return tensor2.kept ? tensor2 : clone(tensor2);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/arithmetic.js\nvar arithmetic_exports = {};\n__export(arithmetic_exports, {\n  json: () => json\n});\nvar json = [\n  {\n    \"tfOpName\": \"Add\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"AddV2\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"AddN\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"tensors\",\n        \"type\": \"tensors\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"BiasAdd\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Sub\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"RealDiv\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Div\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"DivNoNan\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"FloorDiv\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Mul\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Maximum\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Minimum\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Pow\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SquaredDifference\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Mod\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"FloorMod\",\n    \"category\": \"arithmetic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/basic_math.js\nvar basic_math_exports = {};\n__export(basic_math_exports, {\n  json: () => json2\n});\nvar json2 = [\n  {\n    \"tfOpName\": \"Abs\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Acos\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Asin\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Atan\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Atan2\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"y\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Ceil\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ClipByValue\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"clipValueMin\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"clipValueMax\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Complex\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"real\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"imag\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ComplexAbs\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Cos\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Cosh\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Elu\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Exp\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Floor\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Log\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Imag\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"Tout\",\n        \"name\": \"outputType\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Neg\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Real\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"Tout\",\n        \"name\": \"outputType\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Prelu\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"alpha\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Relu\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Relu6\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Selu\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Sigmoid\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Sin\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Sinh\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Sqrt\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Rsqrt\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Square\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Tan\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Tanh\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Sign\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Round\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Expm1\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Log1p\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Reciprocal\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Softplus\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Asinh\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Acosh\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Atanh\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Erf\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Prod\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axes\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LeakyRelu\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"alpha\",\n        \"name\": \"alpha\",\n        \"type\": \"number\",\n        \"defaultValue\": 0.2\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"IsNan\",\n    \"category\": \"basic_math\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/control.js\nvar control_exports = {};\n__export(control_exports, {\n  json: () => json3\n});\nvar json3 = [\n  {\n    \"tfOpName\": \"EmptyTensorList\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"maxNumElements\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LoopCond\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"pred\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Switch\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"data\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"pred\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Merge\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"tensors\",\n        \"type\": \"tensors\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Enter\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"frame_name\",\n        \"name\": \"frameName\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"is_constant\",\n        \"name\": \"isConstant\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Exit\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"NextIteration\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArrayV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"size\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"element_shape\",\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"tfName\": \"dynamic_size\",\n        \"name\": \"dynamicSize\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"clear_after_read\",\n        \"name\": \"clearAfterRead\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"identical_element_shapes\",\n        \"name\": \"identicalElementShapes\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"tensor_array_name\",\n        \"name\": \"name\",\n        \"type\": \"string\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArrayWriteV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"index\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"flowIn\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArrayReadV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"index\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"flowIn\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArrayGatherV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"flowIn\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"element_shape\",\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArrayScatterV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"flowIn\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArrayConcatV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"flowIn\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"element_shape_except0\",\n        \"name\": \"elementShapeExcept0\",\n        \"type\": \"shape\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArraySplitV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"lengths\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"flowIn\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArraySizeV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"flowIn\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorArrayCloseV3\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorArrayId\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"StatelessIf\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"cond\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"end\": 0,\n        \"name\": \"args\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"then_branch\",\n        \"name\": \"thenBranch\",\n        \"type\": \"func\"\n      },\n      {\n        \"tfName\": \"else_branch\",\n        \"name\": \"elseBranch\",\n        \"type\": \"func\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"If\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"cond\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"end\": 0,\n        \"name\": \"args\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"then_branch\",\n        \"name\": \"thenBranch\",\n        \"type\": \"func\"\n      },\n      {\n        \"tfName\": \"else_branch\",\n        \"name\": \"elseBranch\",\n        \"type\": \"func\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"StatelessWhile\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"args\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"cond\",\n        \"name\": \"cond\",\n        \"type\": \"func\"\n      },\n      {\n        \"tfName\": \"body\",\n        \"name\": \"body\",\n        \"type\": \"func\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"While\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"args\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"cond\",\n        \"name\": \"cond\",\n        \"type\": \"func\"\n      },\n      {\n        \"tfName\": \"body\",\n        \"name\": \"body\",\n        \"type\": \"func\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListScatter\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListScatterV2\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"numElements\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListGather\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListGetItem\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"index\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListSetItem\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"index\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListReserve\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"numElements\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListFromTensor\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListStack\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"num_elements\",\n        \"name\": \"numElements\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListSplit\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"lengths\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListConcat\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_shape\",\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListConcatV2\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_shape\",\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListPopBack\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"elementShape\",\n        \"type\": \"shape\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListPushBack\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"element_dtype\",\n        \"name\": \"elementDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListLength\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TensorListResize\",\n    \"category\": \"control\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensorListId\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"size\",\n        \"type\": \"number\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/convolution.js\nvar convolution_exports = {};\n__export(convolution_exports, {\n  json: () => json4\n});\nvar json4 = [\n  {\n    \"tfOpName\": \"AvgPool\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"ksize\",\n        \"name\": \"kernelSize\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"MaxPool\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"ksize\",\n        \"name\": \"kernelSize\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"explicit_paddings\",\n        \"name\": \"explicitPaddings\",\n        \"type\": \"number[]\",\n        \"defaultValue\": [],\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"MaxPoolWithArgmax\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"ksize\",\n        \"name\": \"kernelSize\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"include_batch_in_index\",\n        \"name\": \"includeBatchInIndex\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"AvgPool3D\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"ksize\",\n        \"name\": \"kernelSize\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"MaxPool3D\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"ksize\",\n        \"name\": \"kernelSize\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Conv1D\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"stride\",\n        \"name\": \"stride\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"defaultValue\": \"NWC\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"dilation\",\n        \"name\": \"dilation\",\n        \"type\": \"number\",\n        \"defaultValue\": 1\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Conv2D\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"useCudnnOnGpu\",\n        \"name\": \"useCudnnOnGpu\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"defaultValue\": \"NHWC\"\n      },\n      {\n        \"tfName\": \"explicit_paddings\",\n        \"name\": \"explicitPaddings\",\n        \"type\": \"number[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"dilations\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"_FusedConv2D\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"end\": 0,\n        \"name\": \"args\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"num_args\",\n        \"name\": \"numArgs\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"explicit_paddings\",\n        \"name\": \"explicitPaddings\",\n        \"type\": \"number[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"use_cudnn_on_gpu\",\n        \"name\": \"useCudnnOnGpu\",\n        \"type\": \"bool\",\n        \"defaultValue\": true\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"defaultValue\": \"NHWC\"\n      },\n      {\n        \"tfName\": \"dilations\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\",\n        \"defaultValue\": [\n          1,\n          1,\n          1,\n          1\n        ]\n      },\n      {\n        \"tfName\": \"fused_ops\",\n        \"name\": \"fusedOps\",\n        \"type\": \"string[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"epsilon\",\n        \"name\": \"epsilon\",\n        \"type\": \"number\",\n        \"defaultValue\": 1e-4\n      },\n      {\n        \"tfName\": \"leakyrelu_alpha\",\n        \"name\": \"leakyreluAlpha\",\n        \"type\": \"number\",\n        \"defaultValue\": 0.2\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Conv2DBackpropInput\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 2,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 0,\n        \"name\": \"outputShape\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"explicit_paddings\",\n        \"name\": \"explicitPaddings\",\n        \"type\": \"number[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"dilations\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"DepthwiseConv2d\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"input\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"defaultValue\": \"NHWC\"\n      },\n      {\n        \"tfName\": \"explicit_paddings\",\n        \"name\": \"explicitPaddings\",\n        \"type\": \"number[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"dilations\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"DepthwiseConv2dNative\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"input\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"defaultValue\": \"NHWC\"\n      },\n      {\n        \"tfName\": \"explicit_paddings\",\n        \"name\": \"explicitPaddings\",\n        \"type\": \"number[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"dilations\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"FusedDepthwiseConv2dNative\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"end\": 0,\n        \"name\": \"args\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"num_args\",\n        \"name\": \"numArgs\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"defaultValue\": \"NHWC\"\n      },\n      {\n        \"tfName\": \"dilations\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\",\n        \"defaultValue\": [\n          1,\n          1,\n          1,\n          1\n        ]\n      },\n      {\n        \"tfName\": \"fused_ops\",\n        \"name\": \"fusedOps\",\n        \"type\": \"string[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"explicit_paddings\",\n        \"name\": \"explicitPaddings\",\n        \"type\": \"number[]\",\n        \"defaultValue\": []\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Conv3D\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"defaultValue\": \"NHWC\"\n      },\n      {\n        \"tfName\": \"dilations\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Dilation2D\",\n    \"category\": \"convolution\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"filter\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"strides\",\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"rates\",\n        \"name\": \"dilations\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"padding\",\n        \"name\": \"pad\",\n        \"type\": \"string\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/creation.js\nvar creation_exports = {};\n__export(creation_exports, {\n  json: () => json5\n});\nvar json5 = [\n  {\n    \"tfOpName\": \"Fill\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"value\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LinSpace\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"start\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"stop\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"num\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"OneHot\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"depth\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"onValue\",\n        \"type\": \"number\",\n        \"defaultValue\": 1\n      },\n      {\n        \"start\": 3,\n        \"name\": \"offValue\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"axis\",\n        \"name\": \"axis\",\n        \"type\": \"number\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Ones\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"OnesLike\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"RandomStandardNormal\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"seed\",\n        \"name\": \"seed\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"seed2\",\n        \"name\": \"seed2\",\n        \"type\": \"number\",\n        \"defaultValue\": 0,\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"T\",\n        \"type\": \"number\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"RandomUniform\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"minval\",\n        \"name\": \"minval\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"maxval\",\n        \"name\": \"maxval\",\n        \"type\": \"number\",\n        \"defaultValue\": 1\n      },\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"seed\",\n        \"name\": \"seed\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"seed2\",\n        \"name\": \"seed2\",\n        \"type\": \"number\",\n        \"defaultValue\": 0,\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"T\",\n        \"type\": \"number\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Range\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"start\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"stop\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"step\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"Tidx\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TruncatedNormal\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"means\",\n        \"name\": \"mean\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"stddev\",\n        \"name\": \"stdDev\",\n        \"type\": \"number\",\n        \"defaultValue\": 1\n      },\n      {\n        \"tfName\": \"seed\",\n        \"name\": \"seed\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"seed2\",\n        \"name\": \"seed2\",\n        \"type\": \"number\",\n        \"defaultValue\": 0,\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"T\",\n        \"type\": \"number\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Zeros\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ZerosLike\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Multinomial\",\n    \"category\": \"creation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"logits\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"numSamples\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"seed\",\n        \"name\": \"seed\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"seed2\",\n        \"name\": \"seed2\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"output_dtype\",\n        \"name\": \"output_dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/dynamic.js\nvar dynamic_exports = {};\n__export(dynamic_exports, {\n  json: () => json6\n});\nvar json6 = [\n  {\n    \"tfOpName\": \"NonMaxSuppressionV2\",\n    \"category\": \"dynamic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"boxes\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"scores\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"maxOutputSize\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"iouThreshold\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"NonMaxSuppressionV3\",\n    \"category\": \"dynamic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"boxes\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"scores\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"maxOutputSize\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"iouThreshold\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 4,\n        \"name\": \"scoreThreshold\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"NonMaxSuppressionV4\",\n    \"category\": \"dynamic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"boxes\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"scores\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"maxOutputSize\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"iouThreshold\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 4,\n        \"name\": \"scoreThreshold\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"T_threshold\",\n        \"name\": \"threshold\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"pad_to_max_output_size\",\n        \"name\": \"padToMaxOutputSize\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"NonMaxSuppressionV5\",\n    \"category\": \"dynamic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"boxes\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"scores\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"maxOutputSize\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"iouThreshold\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 4,\n        \"name\": \"scoreThreshold\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 5,\n        \"name\": \"softNmsSigma\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Where\",\n    \"category\": \"dynamic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"condition\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ListDiff\",\n    \"category\": \"dynamic\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"y\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/evaluation.js\nvar evaluation_exports = {};\n__export(evaluation_exports, {\n  json: () => json7\n});\nvar json7 = [\n  {\n    \"tfOpName\": \"LowerBound\",\n    \"category\": \"evaluation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"sortedSequence\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"values\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"TopKV2\",\n    \"category\": \"evaluation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"k\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"sorted\",\n        \"name\": \"sorted\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"UpperBound\",\n    \"category\": \"evaluation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"sortedSequence\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"values\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Unique\",\n    \"category\": \"evaluation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"UniqueV2\",\n    \"category\": \"evaluation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/graph.js\nvar graph_exports = {};\n__export(graph_exports, {\n  json: () => json8\n});\nvar json8 = [\n  {\n    \"tfOpName\": \"PlaceholderWithDefault\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"default\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"shape\",\n        \"name\": \"shape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Placeholder\",\n    \"category\": \"graph\",\n    \"attrs\": [\n      {\n        \"tfName\": \"shape\",\n        \"name\": \"shape\",\n        \"type\": \"shape\"\n      },\n      {\n        \"tfName\": \"dtype\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Const\",\n    \"category\": \"graph\"\n  },\n  {\n    \"tfOpName\": \"Identity\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"IdentityN\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensors\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Snapshot\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Rank\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Size\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Shape\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ShapeN\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensors\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Print\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"data\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"message\",\n        \"name\": \"message\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"first_n\",\n        \"name\": \"firstN\",\n        \"type\": \"number\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"summarize\",\n        \"name\": \"summarize\",\n        \"type\": \"number\",\n        \"defaultValue\": 3\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"NoOp\",\n    \"category\": \"graph\",\n    \"inputs\": []\n  },\n  {\n    \"tfOpName\": \"StopGradient\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"FakeQuantWithMinMaxVars\",\n    \"category\": \"graph\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"min\",\n        \"name\": \"min\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"max\",\n        \"name\": \"max\",\n        \"type\": \"number\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/hash_table.js\nvar hash_table_exports = {};\n__export(hash_table_exports, {\n  json: () => json9\n});\nvar json9 = [\n  {\n    \"tfOpName\": \"HashTable\",\n    \"category\": \"hash_table\",\n    \"inputs\": [],\n    \"attrs\": [\n      {\n        \"tfName\": \"shared_name\",\n        \"name\": \"sharedName\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"use_node_name_sharing\",\n        \"name\": \"useNodeNameSharing\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"key_dtype\",\n        \"name\": \"keyDType\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"value_dtype\",\n        \"name\": \"valueDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"HashTableV2\",\n    \"category\": \"hash_table\",\n    \"inputs\": [],\n    \"attrs\": [\n      {\n        \"tfName\": \"shared_name\",\n        \"name\": \"sharedName\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"use_node_name_sharing\",\n        \"name\": \"useNodeNameSharing\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"key_dtype\",\n        \"name\": \"keyDType\",\n        \"type\": \"dtype\"\n      },\n      {\n        \"tfName\": \"value_dtype\",\n        \"name\": \"valueDType\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LookupTableImport\",\n    \"category\": \"hash_table\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tableHandle\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"keys\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"values\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"Tin\",\n        \"name\": \"tIn\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"Tout\",\n        \"name\": \"tOut\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LookupTableImportV2\",\n    \"category\": \"hash_table\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tableHandle\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"keys\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"values\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"Tin\",\n        \"name\": \"tIn\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"Tout\",\n        \"name\": \"tOut\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LookupTableFind\",\n    \"category\": \"hash_table\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tableHandle\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"keys\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"defaultValue\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"Tin\",\n        \"name\": \"tIn\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"Tout\",\n        \"name\": \"tOut\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LookupTableFindV2\",\n    \"category\": \"hash_table\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tableHandle\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"keys\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"defaultValue\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"Tin\",\n        \"name\": \"tIn\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"Tout\",\n        \"name\": \"tOut\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LookupTableSize\",\n    \"category\": \"hash_table\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tableHandle\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LookupTableSizeV2\",\n    \"category\": \"hash_table\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tableHandle\",\n        \"type\": \"tensor\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/image.js\nvar image_exports = {};\n__export(image_exports, {\n  json: () => json10\n});\nvar json10 = [\n  {\n    \"tfOpName\": \"ResizeBilinear\",\n    \"category\": \"image\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"images\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"size\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"align_corners\",\n        \"name\": \"alignCorners\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"half_pixel_centers\",\n        \"name\": \"halfPixelCenters\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ResizeNearestNeighbor\",\n    \"category\": \"image\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"images\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"size\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"align_corners\",\n        \"name\": \"alignCorners\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"half_pixel_centers\",\n        \"name\": \"halfPixelCenters\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"CropAndResize\",\n    \"category\": \"image\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"image\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"boxes\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"boxInd\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"cropSize\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"method\",\n        \"name\": \"method\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"extrapolation_value\",\n        \"name\": \"extrapolationValue\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ImageProjectiveTransformV3\",\n    \"category\": \"image\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"images\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"transforms\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"outputShape\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"fillValue\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"interpolation\",\n        \"name\": \"interpolation\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"fill_mode\",\n        \"name\": \"fillMode\",\n        \"type\": \"string\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/logical.js\nvar logical_exports = {};\n__export(logical_exports, {\n  json: () => json11\n});\nvar json11 = [\n  {\n    \"tfOpName\": \"Equal\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"NotEqual\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Greater\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"GreaterEqual\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Less\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LessEqual\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LogicalAnd\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LogicalNot\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LogicalOr\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Select\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"condition\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SelectV2\",\n    \"category\": \"logical\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"condition\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/matrices.js\nvar matrices_exports = {};\n__export(matrices_exports, {\n  json: () => json12\n});\nvar json12 = [\n  {\n    \"tfOpName\": \"_FusedMatMul\",\n    \"category\": \"matrices\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"end\": 0,\n        \"name\": \"args\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"num_args\",\n        \"name\": \"numArgs\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"fused_ops\",\n        \"name\": \"fusedOps\",\n        \"type\": \"string[]\",\n        \"defaultValue\": []\n      },\n      {\n        \"tfName\": \"epsilon\",\n        \"name\": \"epsilon\",\n        \"type\": \"number\",\n        \"defaultValue\": 1e-4\n      },\n      {\n        \"tfName\": \"transpose_a\",\n        \"name\": \"transposeA\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"transpose_b\",\n        \"name\": \"transposeB\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"leakyrelu_alpha\",\n        \"name\": \"leakyreluAlpha\",\n        \"type\": \"number\",\n        \"defaultValue\": 0.2\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"MatMul\",\n    \"category\": \"matrices\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"transpose_a\",\n        \"name\": \"transposeA\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"transpose_b\",\n        \"name\": \"transposeB\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"BatchMatMul\",\n    \"category\": \"matrices\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"adj_x\",\n        \"name\": \"transposeA\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"adj_y\",\n        \"name\": \"transposeB\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"BatchMatMulV2\",\n    \"category\": \"matrices\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"a\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"b\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"adj_x\",\n        \"name\": \"transposeA\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"adj_y\",\n        \"name\": \"transposeB\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Transpose\",\n    \"category\": \"matrices\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"perm\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Einsum\",\n    \"category\": \"matrices\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"tensors\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"equation\",\n        \"name\": \"equation\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"N\",\n        \"name\": \"n\",\n        \"type\": \"number\",\n        \"defaultValue\": 2\n      },\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/normalization.js\nvar normalization_exports = {};\n__export(normalization_exports, {\n  json: () => json13\n});\nvar json13 = [\n  {\n    \"tfOpName\": \"EuclideanNorm\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\",\n        \"defaultValue\": false\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"FusedBatchNorm\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"scale\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"offset\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"mean\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 4,\n        \"name\": \"variance\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"epsilon\",\n        \"name\": \"epsilon\",\n        \"type\": \"number\",\n        \"defaultValue\": 1e-3\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"FusedBatchNormV2\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"scale\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"offset\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"mean\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 4,\n        \"name\": \"variance\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"epsilon\",\n        \"name\": \"epsilon\",\n        \"type\": \"number\",\n        \"defaultValue\": 1e-3\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"FusedBatchNormV3\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"scale\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"offset\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"mean\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 4,\n        \"name\": \"variance\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"epsilon\",\n        \"name\": \"epsilon\",\n        \"type\": \"number\",\n        \"defaultValue\": 1e-3\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LRN\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"depth_radius\",\n        \"name\": \"radius\",\n        \"type\": \"number\",\n        \"defaultValue\": 5\n      },\n      {\n        \"tfName\": \"bias\",\n        \"name\": \"bias\",\n        \"type\": \"number\",\n        \"defaultValue\": 1\n      },\n      {\n        \"tfName\": \"alpha\",\n        \"name\": \"alpha\",\n        \"type\": \"number\",\n        \"defaultValue\": 1\n      },\n      {\n        \"tfName\": \"beta\",\n        \"name\": \"beta\",\n        \"type\": \"number\",\n        \"defaultValue\": 0.5\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Softmax\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"LogSoftmax\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SparseToDense\",\n    \"category\": \"normalization\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"sparseIndices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"outputShape\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"sparseValues\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"defaultValue\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"validate_indices\",\n        \"name\": \"validateIndices\",\n        \"type\": \"bool\",\n        \"defaultValue\": true,\n        \"notSupported\": true\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/reduction.js\nvar reduction_exports = {};\n__export(reduction_exports, {\n  json: () => json14\n});\nvar json14 = [\n  {\n    \"tfOpName\": \"Bincount\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"size\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"weights\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"DenseBincount\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"size\",\n        \"type\": \"number\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"weights\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"binary_output\",\n        \"name\": \"binaryOutput\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Max\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Mean\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Min\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Sum\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"All\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Any\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ArgMax\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ArgMin\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Prod\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"keep_dims\",\n        \"name\": \"keepDims\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Cumprod\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"exclusive\",\n        \"name\": \"exclusive\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"reverse\",\n        \"name\": \"reverse\",\n        \"type\": \"bool\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Cumsum\",\n    \"category\": \"reduction\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"exclusive\",\n        \"name\": \"exclusive\",\n        \"type\": \"bool\"\n      },\n      {\n        \"tfName\": \"reverse\",\n        \"name\": \"reverse\",\n        \"type\": \"bool\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/slice_join.js\nvar slice_join_exports = {};\n__export(slice_join_exports, {\n  json: () => json15\n});\nvar json15 = [\n  {\n    \"tfOpName\": \"ConcatV2\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": -1,\n        \"name\": \"tensors\",\n        \"type\": \"tensors\"\n      },\n      {\n        \"start\": -1,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"N\",\n        \"name\": \"n\",\n        \"type\": \"number\",\n        \"defaultValue\": 2\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Concat\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 1,\n        \"end\": 0,\n        \"name\": \"tensors\",\n        \"type\": \"tensors\"\n      },\n      {\n        \"start\": 0,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"N\",\n        \"name\": \"n\",\n        \"type\": \"number\",\n        \"defaultValue\": 2\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"GatherV2\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"axis\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"batch_dims\",\n        \"name\": \"batchDims\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Gather\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"validate_indices\",\n        \"name\": \"validateIndices\",\n        \"type\": \"bool\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Reverse\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"dims\",\n        \"type\": \"bool[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ReverseV2\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Slice\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"begin\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"size\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"StridedSlice\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"begin\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"end\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"strides\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"begin_mask\",\n        \"name\": \"beginMask\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"end_mask\",\n        \"name\": \"endMask\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"new_axis_mask\",\n        \"name\": \"newAxisMask\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"ellipsis_mask\",\n        \"name\": \"ellipsisMask\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"shrink_axis_mask\",\n        \"name\": \"shrinkAxisMask\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Pack\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"end\": 0,\n        \"name\": \"tensors\",\n        \"type\": \"tensors\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"axis\",\n        \"name\": \"axis\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Unpack\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"tensor\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"axis\",\n        \"name\": \"axis\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"tfName\": \"num\",\n        \"name\": \"num\",\n        \"type\": \"number\",\n        \"defaultValue\": 0,\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Tile\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"reps\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Split\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"axis\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      },\n      {\n        \"start\": 1,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"num_split\",\n        \"name\": \"numOrSizeSplits\",\n        \"type\": \"number\",\n        \"defaultValue\": 1\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SplitV\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"numOrSizeSplits\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"axis\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ScatterNd\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"values\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"GatherNd\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SparseToDense\",\n    \"category\": \"slice_join\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"sparseIndices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"outputShape\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"sparseValues\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"defaultValue\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"validate_indices\",\n        \"name\": \"validateIndices\",\n        \"type\": \"bool\",\n        \"defaultValue\": false,\n        \"notSupported\": true\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/sparse.js\nvar sparse_exports = {};\n__export(sparse_exports, {\n  json: () => json16\n});\nvar json16 = [\n  {\n    \"tfOpName\": \"SparseFillEmptyRows\",\n    \"category\": \"sparse\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"values\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"denseShape\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 3,\n        \"name\": \"defaultValue\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SparseReshape\",\n    \"category\": \"sparse\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"inputIndices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"inputShape\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"newShape\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"T\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SparseSegmentMean\",\n    \"category\": \"sparse\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"data\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"segmentIds\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SparseSegmentSum\",\n    \"category\": \"sparse\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"data\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"indices\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"segmentIds\",\n        \"type\": \"tensor\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/spectral.js\nvar spectral_exports = {};\n__export(spectral_exports, {\n  json: () => json17\n});\nvar json17 = [\n  {\n    \"tfOpName\": \"FFT\",\n    \"category\": \"spectral\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"IFFT\",\n    \"category\": \"spectral\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"RFFT\",\n    \"category\": \"spectral\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"fft_length\",\n        \"type\": \"number\",\n        \"notSupported\": true\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"IRFFT\",\n    \"category\": \"spectral\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"fft_length\",\n        \"type\": \"number\",\n        \"notSupported\": true\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/string.js\nvar string_exports = {};\n__export(string_exports, {\n  json: () => json18\n});\nvar json18 = [\n  {\n    \"tfOpName\": \"StringNGrams\",\n    \"category\": \"string\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"data\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"dataSplits\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"separator\",\n        \"name\": \"separator\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"ngram_widths\",\n        \"name\": \"nGramWidths\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"tfName\": \"left_pad\",\n        \"name\": \"leftPad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"right_pad\",\n        \"name\": \"rightPad\",\n        \"type\": \"string\"\n      },\n      {\n        \"tfName\": \"pad_width\",\n        \"name\": \"padWidth\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"preserve_short_sequences\",\n        \"name\": \"preserveShortSequences\",\n        \"type\": \"bool\"\n      }\n    ],\n    \"outputs\": [\n      \"ngrams\",\n      \"ngrams_splits\"\n    ]\n  },\n  {\n    \"tfOpName\": \"StringSplit\",\n    \"category\": \"string\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"input\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"delimiter\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"skip_empty\",\n        \"name\": \"skipEmpty\",\n        \"type\": \"bool\"\n      }\n    ],\n    \"outputs\": [\n      \"indices\",\n      \"values\",\n      \"shape\"\n    ]\n  },\n  {\n    \"tfOpName\": \"StringToHashBucketFast\",\n    \"category\": \"string\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"input\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"num_buckets\",\n        \"name\": \"numBuckets\",\n        \"type\": \"number\"\n      }\n    ]\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/op_list/transformation.js\nvar transformation_exports = {};\n__export(transformation_exports, {\n  json: () => json19\n});\nvar json19 = [\n  {\n    \"tfOpName\": \"Cast\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"SrcT\",\n        \"name\": \"sdtype\",\n        \"type\": \"dtype\",\n        \"notSupported\": true\n      },\n      {\n        \"tfName\": \"DstT\",\n        \"name\": \"dtype\",\n        \"type\": \"dtype\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"ExpandDims\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"axis\",\n        \"type\": \"number\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"MirrorPad\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"padding\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"mode\",\n        \"name\": \"mode\",\n        \"type\": \"string\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Pad\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"padding\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"constant_value\",\n        \"name\": \"constantValue\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"PadV2\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"padding\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"constantValue\",\n        \"type\": \"number\",\n        \"defaultValue\": 0\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Reshape\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"Squeeze\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"axis\",\n        \"tfDeprecatedName\": \"squeeze_dims\",\n        \"name\": \"axis\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"SpaceToBatchND\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"blockShape\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"paddings\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"BatchToSpaceND\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"blockShape\",\n        \"type\": \"number[]\"\n      },\n      {\n        \"start\": 2,\n        \"name\": \"crops\",\n        \"type\": \"number[]\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"DepthToSpace\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": [\n      {\n        \"tfName\": \"block_size\",\n        \"name\": \"blockSize\",\n        \"type\": \"number\"\n      },\n      {\n        \"tfName\": \"data_format\",\n        \"name\": \"dataFormat\",\n        \"type\": \"string\"\n      }\n    ]\n  },\n  {\n    \"tfOpName\": \"BroadcastTo\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"x\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"shape\",\n        \"type\": \"number[]\"\n      }\n    ],\n    \"attrs\": []\n  },\n  {\n    \"tfOpName\": \"BroadcastArgs\",\n    \"category\": \"transformation\",\n    \"inputs\": [\n      {\n        \"start\": 0,\n        \"name\": \"s0\",\n        \"type\": \"tensor\"\n      },\n      {\n        \"start\": 1,\n        \"name\": \"s1\",\n        \"type\": \"tensor\"\n      }\n    ],\n    \"attrs\": []\n  }\n];\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/operation_mapper.js\nvar OperationMapper = class {\n  static get Instance() {\n    return this._instance || (this._instance = new this());\n  }\n  constructor() {\n    const ops = [\n      arithmetic_exports,\n      basic_math_exports,\n      control_exports,\n      convolution_exports,\n      creation_exports,\n      dynamic_exports,\n      evaluation_exports,\n      graph_exports,\n      hash_table_exports,\n      image_exports,\n      logical_exports,\n      matrices_exports,\n      normalization_exports,\n      reduction_exports,\n      slice_join_exports,\n      sparse_exports,\n      spectral_exports,\n      string_exports,\n      transformation_exports\n    ];\n    const mappersJson = [].concat(...ops.map((op2) => op2.json));\n    this.opMappers = mappersJson.reduce((map, mapper) => {\n      map[mapper.tfOpName] = mapper;\n      return map;\n    }, {});\n  }\n  transformGraph(graph, signature = {}) {\n    const tfNodes = graph.node;\n    const placeholders = [];\n    const weights = [];\n    const initNodes = [];\n    const nodes = tfNodes.reduce((map, node) => {\n      map[node.name] = this.mapNode(node);\n      if (node.op.startsWith(\"Placeholder\")) {\n        placeholders.push(map[node.name]);\n      } else if (node.op === \"Const\") {\n        weights.push(map[node.name]);\n      } else if (node.input == null || node.input.length === 0) {\n        initNodes.push(map[node.name]);\n      }\n      return map;\n    }, {});\n    let inputs = [];\n    const outputs = [];\n    let inputNodeNameToKey = {};\n    let outputNodeNameToKey = {};\n    if (signature != null) {\n      inputNodeNameToKey = this.mapSignatureEntries(signature.inputs);\n      outputNodeNameToKey = this.mapSignatureEntries(signature.outputs);\n    }\n    const allNodes = Object.keys(nodes);\n    allNodes.forEach((key) => {\n      const node = nodes[key];\n      node.inputNames.forEach((name, index) => {\n        const [nodeName, , outputName] = getNodeNameAndIndex(name);\n        const inputNode = nodes[nodeName];\n        if (inputNode.outputs != null) {\n          const outputIndex = inputNode.outputs.indexOf(outputName);\n          if (outputIndex !== -1) {\n            const inputName = `${nodeName}:${outputIndex}`;\n            node.inputNames[index] = inputName;\n          }\n        }\n        node.inputs.push(inputNode);\n        inputNode.children.push(node);\n      });\n    });\n    if (Object.keys(outputNodeNameToKey).length === 0) {\n      allNodes.forEach((key) => {\n        const node = nodes[key];\n        if (node.children.length === 0) {\n          outputs.push(node);\n        }\n      });\n    } else {\n      Object.keys(outputNodeNameToKey).forEach((name) => {\n        const [nodeName] = getNodeNameAndIndex(name);\n        const node = nodes[nodeName];\n        if (node != null) {\n          node.signatureKey = outputNodeNameToKey[name];\n          outputs.push(node);\n        }\n      });\n    }\n    if (Object.keys(inputNodeNameToKey).length > 0) {\n      Object.keys(inputNodeNameToKey).forEach((name) => {\n        const [nodeName] = getNodeNameAndIndex(name);\n        const node = nodes[nodeName];\n        if (node) {\n          node.signatureKey = inputNodeNameToKey[name];\n          inputs.push(node);\n        }\n      });\n    } else {\n      inputs = placeholders;\n    }\n    let functions = {};\n    if (graph.library != null && graph.library.function != null) {\n      functions = graph.library.function.reduce((functions2, func2) => {\n        functions2[func2.signature.name] = this.mapFunction(func2);\n        return functions2;\n      }, {});\n    }\n    const result = { nodes, inputs, outputs, weights, placeholders, signature, functions };\n    if (initNodes.length > 0) {\n      result.initNodes = initNodes;\n    }\n    return result;\n  }\n  mapSignatureEntries(entries) {\n    return Object.keys(entries || {}).reduce((prev, curr) => {\n      prev[entries[curr].name] = curr;\n      return prev;\n    }, {});\n  }\n  mapNode(node) {\n    const mapper = getRegisteredOp(node.op) || this.opMappers[node.op] || {};\n    if (node.attr == null) {\n      node.attr = {};\n    }\n    const newNode = {\n      name: node.name,\n      op: node.op,\n      category: mapper.category,\n      inputNames: (node.input || []).map((input2) => input2.startsWith(\"^\") ? input2.slice(1) : input2),\n      inputs: [],\n      children: [],\n      inputParams: {},\n      attrParams: {},\n      rawAttrs: node.attr,\n      outputs: mapper.outputs\n    };\n    if (mapper.inputs != null) {\n      newNode.inputParams = mapper.inputs.reduce((map, param) => {\n        map[param.name] = {\n          type: param.type,\n          inputIndexStart: param.start,\n          inputIndexEnd: param.end\n        };\n        return map;\n      }, {});\n    }\n    if (mapper.attrs != null) {\n      newNode.attrParams = mapper.attrs.reduce((map, param) => {\n        const type = param.type;\n        let value = void 0;\n        switch (param.type) {\n          case \"string\":\n            value = getStringParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getStringParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"string[]\":\n            value = getStringArrayParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getStringArrayParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"number\":\n            value = getNumberParam(node.attr, param.tfName, param.defaultValue || 0);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getNumberParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"number[]\":\n            value = getNumericArrayParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getNumericArrayParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"bool\":\n            value = getBoolParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getBoolParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"bool[]\":\n            value = getBoolArrayParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getBoolArrayParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"shape\":\n            value = getTensorShapeParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getTensorShapeParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"shape[]\":\n            value = getTensorShapeArrayParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getTensorShapeArrayParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"dtype\":\n            value = getDtypeParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getDtypeParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"dtype[]\":\n            value = getDtypeArrayParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getDtypeArrayParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"func\":\n            value = getFuncParam(node.attr, param.tfName, param.defaultValue);\n            if (value === void 0 && !!param.tfDeprecatedName) {\n              value = getFuncParam(node.attr, param.tfDeprecatedName, param.defaultValue);\n            }\n            break;\n          case \"tensor\":\n          case \"tensors\":\n            break;\n          default:\n            throw new Error(`Unsupported param type: ${param.type} for op: ${node.op}`);\n        }\n        map[param.name] = { value, type };\n        return map;\n      }, {});\n    }\n    return newNode;\n  }\n  mapFunction(functionDef) {\n    const tfNodes = functionDef.nodeDef;\n    const placeholders = [];\n    const weights = [];\n    let nodes = {};\n    if (tfNodes != null) {\n      nodes = tfNodes.reduce((map, node) => {\n        map[node.name] = this.mapNode(node);\n        if (node.op === \"Const\") {\n          weights.push(map[node.name]);\n        }\n        return map;\n      }, {});\n    }\n    const inputs = [];\n    const outputs = [];\n    functionDef.signature.inputArg.forEach((arg) => {\n      const [nodeName] = getNodeNameAndIndex(arg.name);\n      const node = {\n        name: nodeName,\n        op: \"Placeholder\",\n        inputs: [],\n        inputNames: [],\n        category: \"graph\",\n        inputParams: {},\n        attrParams: { dtype: { value: parseDtypeParam(arg.type), type: \"dtype\" } },\n        children: []\n      };\n      node.signatureKey = arg.name;\n      inputs.push(node);\n      nodes[nodeName] = node;\n    });\n    const allNodes = Object.keys(nodes);\n    allNodes.forEach((key) => {\n      const node = nodes[key];\n      node.inputNames.forEach((name, index) => {\n        const [nodeName, , outputName] = getNodeNameAndIndex(name);\n        const inputNode = nodes[nodeName];\n        if (inputNode.outputs != null) {\n          const outputIndex = inputNode.outputs.indexOf(outputName);\n          if (outputIndex !== -1) {\n            const inputName = `${nodeName}:${outputIndex}`;\n            node.inputNames[index] = inputName;\n          }\n        }\n        node.inputs.push(inputNode);\n        inputNode.children.push(node);\n      });\n    });\n    const returnNodeMap = functionDef.ret;\n    functionDef.signature.outputArg.forEach((output) => {\n      const [nodeName, index] = getNodeNameAndIndex(returnNodeMap[output.name]);\n      const node = nodes[nodeName];\n      if (node != null) {\n        node.defaultOutput = index;\n        outputs.push(node);\n      }\n    });\n    const signature = this.mapArgsToSignature(functionDef);\n    return { nodes, inputs, outputs, weights, placeholders, signature };\n  }\n  mapArgsToSignature(functionDef) {\n    return {\n      methodName: functionDef.signature.name,\n      inputs: functionDef.signature.inputArg.reduce((map, arg) => {\n        map[arg.name] = this.mapArgToTensorInfo(arg);\n        return map;\n      }, {}),\n      outputs: functionDef.signature.outputArg.reduce((map, arg) => {\n        map[arg.name] = this.mapArgToTensorInfo(arg, functionDef.ret);\n        return map;\n      }, {})\n    };\n  }\n  mapArgToTensorInfo(arg, nameMap2) {\n    let name = arg.name;\n    if (nameMap2 != null) {\n      name = nameMap2[name];\n    }\n    return { name, dtype: arg.type };\n  }\n};\nfunction decodeBase64(text) {\n  const global2 = env().global;\n  if (typeof global2.atob !== \"undefined\") {\n    return global2.atob(text);\n  } else if (typeof Buffer !== \"undefined\") {\n    return new Buffer(text, \"base64\").toString();\n  } else {\n    throw new Error(\"Unable to decode base64 in this environment. Missing built-in atob() or Buffer()\");\n  }\n}\nfunction parseStringParam(s2, keepCase) {\n  const value = Array.isArray(s2) ? String.fromCharCode.apply(null, s2) : decodeBase64(s2);\n  return keepCase ? value : value.toLowerCase();\n}\nfunction getStringParam(attrs, name, def, keepCase = false) {\n  const param = attrs[name];\n  if (param != null) {\n    return parseStringParam(param.s, keepCase);\n  }\n  return def;\n}\nfunction getBoolParam(attrs, name, def) {\n  const param = attrs[name];\n  return param ? param.b : def;\n}\nfunction getNumberParam(attrs, name, def) {\n  const param = attrs[name] || {};\n  const value = param[\"i\"] != null ? param[\"i\"] : param[\"f\"] != null ? param[\"f\"] : def;\n  return typeof value === \"number\" ? value : parseInt(value, 10);\n}\nfunction parseDtypeParam(value) {\n  if (typeof value === \"string\") {\n    value = DataType[value];\n  }\n  switch (value) {\n    case DataType.DT_FLOAT:\n    case DataType.DT_HALF:\n      return \"float32\";\n    case DataType.DT_INT32:\n    case DataType.DT_INT64:\n    case DataType.DT_INT8:\n    case DataType.DT_UINT8:\n      return \"int32\";\n    case DataType.DT_BOOL:\n      return \"bool\";\n    case DataType.DT_DOUBLE:\n      return \"float32\";\n    case DataType.DT_STRING:\n      return \"string\";\n    default:\n      return null;\n  }\n}\nfunction getFuncParam(attrs, name, def) {\n  const param = attrs[name];\n  if (param && param.func) {\n    return param.func.name;\n  }\n  return def;\n}\nfunction getDtypeParam(attrs, name, def) {\n  const param = attrs[name];\n  if (param && param.type) {\n    return parseDtypeParam(param.type);\n  }\n  return def;\n}\nfunction getDtypeArrayParam(attrs, name, def) {\n  const param = attrs[name];\n  if (param && param.list && param.list.type) {\n    return param.list.type.map((v) => parseDtypeParam(v));\n  }\n  return def;\n}\nfunction parseTensorShapeParam(shape) {\n  if (shape.unknownRank) {\n    return void 0;\n  }\n  if (shape.dim != null) {\n    return shape.dim.map((dim) => typeof dim.size === \"number\" ? dim.size : parseInt(dim.size, 10));\n  }\n  return [];\n}\nfunction getTensorShapeParam(attrs, name, def) {\n  const param = attrs[name];\n  if (param && param.shape) {\n    return parseTensorShapeParam(param.shape);\n  }\n  return def;\n}\nfunction getNumericArrayParam(attrs, name, def) {\n  const param = attrs[name];\n  if (param) {\n    return ((param.list.f && param.list.f.length ? param.list.f : param.list.i) || []).map((v) => typeof v === \"number\" ? v : parseInt(v, 10));\n  }\n  return def;\n}\nfunction getStringArrayParam(attrs, name, def, keepCase = false) {\n  const param = attrs[name];\n  if (param && param.list && param.list.s) {\n    return param.list.s.map((v) => {\n      return parseStringParam(v, keepCase);\n    });\n  }\n  return def;\n}\nfunction getTensorShapeArrayParam(attrs, name, def) {\n  const param = attrs[name];\n  if (param && param.list && param.list.shape) {\n    return param.list.shape.map((v) => {\n      return parseTensorShapeParam(v);\n    });\n  }\n  return def;\n}\nfunction getBoolArrayParam(attrs, name, def) {\n  const param = attrs[name];\n  if (param && param.list && param.list.b) {\n    return param.list.b;\n  }\n  return def;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/custom_op/node_value_impl.js\nvar NodeValueImpl = class {\n  constructor(node, tensorMap, context) {\n    this.node = node;\n    this.tensorMap = tensorMap;\n    this.context = context;\n    this.inputs = [];\n    this.attrs = {};\n    this.inputs = node.inputNames.map((name) => this.getInput(name));\n    if (node.rawAttrs != null) {\n      this.attrs = Object.keys(node.rawAttrs).reduce((attrs, key) => {\n        attrs[key] = this.getAttr(key);\n        return attrs;\n      }, {});\n    }\n  }\n  getInput(name) {\n    return getTensor(name, this.tensorMap, this.context);\n  }\n  getAttr(name, defaultValue) {\n    const value = this.node.rawAttrs[name];\n    if (value.tensor != null) {\n      return getTensor(name, this.tensorMap, this.context);\n    }\n    if (value.i != null || value.f != null) {\n      return getNumberParam(this.node.rawAttrs, name, defaultValue);\n    }\n    if (value.s != null) {\n      return getStringParam(this.node.rawAttrs, name, defaultValue);\n    }\n    if (value.b != null) {\n      return getBoolParam(this.node.rawAttrs, name, defaultValue);\n    }\n    if (value.shape != null) {\n      return getTensorShapeParam(this.node.rawAttrs, name, defaultValue);\n    }\n    if (value.type != null) {\n      return getDtypeParam(this.node.rawAttrs, name, defaultValue);\n    }\n    if (value.list != null) {\n      if (value.list.i != null || value.list.f != null) {\n        return getNumericArrayParam(this.node.rawAttrs, name, defaultValue);\n      }\n      if (value.list.s != null) {\n        return getStringArrayParam(this.node.rawAttrs, name, defaultValue);\n      }\n      if (value.list.shape != null) {\n        return getTensorShapeArrayParam(this.node.rawAttrs, name, defaultValue);\n      }\n      if (value.list.b != null) {\n        return getBoolArrayParam(this.node.rawAttrs, name, defaultValue);\n      }\n      if (value.list.type != null) {\n        return getDtypeArrayParam(this.node.rawAttrs, name, defaultValue);\n      }\n    }\n    return defaultValue;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-core@3.19.0/node_modules/@tensorflow/tfjs-core/dist/ops/ops_for_converter.js\nvar ops_for_converter_exports = {};\n__export(ops_for_converter_exports, {\n  OP_SCOPE_SUFFIX: () => OP_SCOPE_SUFFIX,\n  abs: () => abs,\n  acos: () => acos,\n  acosh: () => acosh,\n  add: () => add2,\n  addN: () => addN,\n  all: () => all,\n  any: () => any,\n  argMax: () => argMax,\n  argMin: () => argMin,\n  asin: () => asin,\n  asinh: () => asinh,\n  atan: () => atan,\n  atan2: () => atan2,\n  atanh: () => atanh,\n  avgPool: () => avgPool,\n  avgPool3d: () => avgPool3d,\n  basicLSTMCell: () => basicLSTMCell,\n  batchNorm: () => batchNorm,\n  batchNorm2d: () => batchNorm2d,\n  batchNorm3d: () => batchNorm3d,\n  batchNorm4d: () => batchNorm4d,\n  batchToSpaceND: () => batchToSpaceND,\n  bincount: () => bincount,\n  booleanMaskAsync: () => booleanMaskAsync,\n  broadcastArgs: () => broadcastArgs,\n  broadcastTo: () => broadcastTo,\n  buffer: () => buffer,\n  cast: () => cast,\n  ceil: () => ceil,\n  clipByValue: () => clipByValue,\n  clone: () => clone,\n  complex: () => complex,\n  concat: () => concat,\n  concat1d: () => concat1d,\n  concat2d: () => concat2d,\n  concat3d: () => concat3d,\n  concat4d: () => concat4d,\n  conv1d: () => conv1d,\n  conv2d: () => conv2d,\n  conv2dTranspose: () => conv2dTranspose,\n  conv3d: () => conv3d,\n  conv3dTranspose: () => conv3dTranspose,\n  cos: () => cos,\n  cosh: () => cosh,\n  cosineWindow: () => cosineWindow,\n  cumprod: () => cumprod,\n  cumsum: () => cumsum,\n  denseBincount: () => denseBincount,\n  depthToSpace: () => depthToSpace,\n  depthwiseConv2d: () => depthwiseConv2d,\n  diag: () => diag,\n  dilation2d: () => dilation2d,\n  div: () => div,\n  divNoNan: () => divNoNan,\n  dot: () => dot,\n  dropout: () => dropout,\n  einsum: () => einsum,\n  elu: () => elu,\n  enclosingPowerOfTwo: () => enclosingPowerOfTwo,\n  equal: () => equal,\n  erf: () => erf,\n  euclideanNorm: () => euclideanNorm,\n  exp: () => exp,\n  expandDims: () => expandDims,\n  expm1: () => expm1,\n  eye: () => eye,\n  fft: () => fft,\n  fill: () => fill,\n  floor: () => floor,\n  floorDiv: () => floorDiv,\n  fused: () => fused_ops_exports,\n  gather: () => gather,\n  gatherND: () => gatherND,\n  greater: () => greater,\n  greaterEqual: () => greaterEqual,\n  ifft: () => ifft,\n  imag: () => imag,\n  image: () => image,\n  inTopKAsync: () => inTopKAsync,\n  irfft: () => irfft,\n  isFinite: () => isFinite2,\n  isInf: () => isInf,\n  isNaN: () => isNaN2,\n  leakyRelu: () => leakyRelu,\n  less: () => less,\n  lessEqual: () => lessEqual,\n  linalg: () => linalg,\n  linspace: () => linspace,\n  localResponseNormalization: () => localResponseNormalization,\n  log: () => log2,\n  log1p: () => log1p,\n  logSigmoid: () => logSigmoid,\n  logSoftmax: () => logSoftmax,\n  logSumExp: () => logSumExp,\n  logicalAnd: () => logicalAnd,\n  logicalNot: () => logicalNot,\n  logicalOr: () => logicalOr,\n  logicalXor: () => logicalXor,\n  losses: () => losses,\n  lowerBound: () => lowerBound,\n  matMul: () => matMul,\n  max: () => max,\n  maxPool: () => maxPool,\n  maxPool3d: () => maxPool3d,\n  maxPoolWithArgmax: () => maxPoolWithArgmax,\n  maximum: () => maximum,\n  mean: () => mean,\n  meshgrid: () => meshgrid,\n  min: () => min,\n  minimum: () => minimum,\n  mirrorPad: () => mirrorPad,\n  mod: () => mod,\n  moments: () => moments,\n  movingAverage: () => movingAverage,\n  mul: () => mul,\n  multiRNNCell: () => multiRNNCell,\n  multinomial: () => multinomial,\n  neg: () => neg,\n  norm: () => norm,\n  notEqual: () => notEqual,\n  oneHot: () => oneHot,\n  ones: () => ones2,\n  onesLike: () => onesLike,\n  op: () => op,\n  outerProduct: () => outerProduct,\n  pad: () => pad,\n  pad1d: () => pad1d,\n  pad2d: () => pad2d,\n  pad3d: () => pad3d,\n  pad4d: () => pad4d,\n  pool: () => pool,\n  pow: () => pow,\n  prelu: () => prelu,\n  print: () => print,\n  prod: () => prod,\n  rand: () => rand,\n  randomGamma: () => randomGamma,\n  randomNormal: () => randomNormal,\n  randomStandardNormal: () => randomStandardNormal,\n  randomUniform: () => randomUniform,\n  range: () => range,\n  real: () => real,\n  reciprocal: () => reciprocal,\n  relu: () => relu,\n  relu6: () => relu6,\n  reshape: () => reshape,\n  reverse: () => reverse,\n  reverse1d: () => reverse1d,\n  reverse2d: () => reverse2d,\n  reverse3d: () => reverse3d,\n  reverse4d: () => reverse4d,\n  rfft: () => rfft,\n  round: () => round2,\n  rsqrt: () => rsqrt,\n  scalar: () => scalar,\n  scatterND: () => scatterND,\n  searchSorted: () => searchSorted,\n  selu: () => selu,\n  separableConv2d: () => separableConv2d,\n  setdiff1dAsync: () => setdiff1dAsync,\n  sigmoid: () => sigmoid,\n  sign: () => sign,\n  signal: () => signal,\n  sin: () => sin,\n  sinh: () => sinh,\n  slice: () => slice,\n  slice1d: () => slice1d,\n  slice2d: () => slice2d,\n  slice3d: () => slice3d,\n  slice4d: () => slice4d,\n  softmax: () => softmax,\n  softplus: () => softplus,\n  spaceToBatchND: () => spaceToBatchND,\n  sparse: () => sparse,\n  sparseToDense: () => sparseToDense,\n  spectral: () => spectral,\n  split: () => split,\n  sqrt: () => sqrt,\n  square: () => square,\n  squaredDifference: () => squaredDifference,\n  squeeze: () => squeeze,\n  stack: () => stack,\n  step: () => step,\n  stridedSlice: () => stridedSlice,\n  string: () => string,\n  sub: () => sub,\n  sum: () => sum2,\n  tan: () => tan,\n  tanh: () => tanh2,\n  tensor: () => tensor,\n  tensor1d: () => tensor1d,\n  tensor2d: () => tensor2d,\n  tensor3d: () => tensor3d,\n  tensor4d: () => tensor4d,\n  tensor5d: () => tensor5d,\n  tensor6d: () => tensor6d,\n  tile: () => tile,\n  topk: () => topk,\n  transpose: () => transpose,\n  truncatedNormal: () => truncatedNormal,\n  unique: () => unique,\n  unsortedSegmentSum: () => unsortedSegmentSum,\n  unstack: () => unstack,\n  upperBound: () => upperBound,\n  variable: () => variable,\n  where: () => where,\n  whereAsync: () => whereAsync,\n  zeros: () => zeros,\n  zerosLike: () => zerosLike\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/arithmetic_executor.js\nvar executeOp = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"BiasAdd\":\n    case \"AddV2\":\n    case \"Add\": {\n      return [ops.add(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"AddN\": {\n      return [ops.addN(getParamValue(\"tensors\", node, tensorMap, context))];\n    }\n    case \"FloorMod\":\n    case \"Mod\":\n      return [ops.mod(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    case \"Mul\":\n      return [ops.mul(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    case \"RealDiv\":\n    case \"Div\": {\n      return [ops.div(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"DivNoNan\": {\n      return [ops.divNoNan(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"FloorDiv\": {\n      return [ops.floorDiv(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"Sub\": {\n      return [ops.sub(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"Minimum\": {\n      return [ops.minimum(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"Maximum\": {\n      return [ops.maximum(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"Pow\": {\n      return [ops.pow(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"SquaredDifference\": {\n      return [ops.squaredDifference(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/basic_math_executor.js\nvar executeOp2 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"Abs\":\n    case \"ComplexAbs\":\n      return [ops.abs(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Acos\":\n      return [ops.acos(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Acosh\":\n      return [ops.acosh(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Asin\":\n      return [ops.asin(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Asinh\":\n      return [ops.asinh(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Atan\":\n      return [ops.atan(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Atan2\":\n      return [ops.atan2(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"y\", node, tensorMap, context))];\n    case \"Atanh\":\n      return [ops.atanh(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Ceil\":\n      return [ops.ceil(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Complex\":\n      return [ops.complex(getParamValue(\"real\", node, tensorMap, context), getParamValue(\"imag\", node, tensorMap, context))];\n    case \"Cos\":\n      return [ops.cos(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Cosh\":\n      return [ops.cosh(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Elu\":\n      return [ops.elu(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Erf\":\n      return [ops.erf(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Exp\":\n      return [ops.exp(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Expm1\": {\n      return [ops.expm1(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Floor\":\n      return [ops.floor(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Log\":\n      return [ops.log(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Log1p\": {\n      return [ops.log1p(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Imag\":\n      return [ops.imag(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Neg\":\n      return [ops.neg(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Reciprocal\": {\n      return [ops.reciprocal(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Real\":\n      return [ops.real(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Relu\":\n      return [ops.relu(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Round\": {\n      return [ops.round(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Selu\":\n      return [ops.selu(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Sigmoid\":\n      return [ops.sigmoid(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Sin\":\n      return [ops.sin(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Sign\": {\n      return [ops.sign(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Sinh\": {\n      return [ops.sinh(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Softplus\": {\n      return [ops.softplus(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Sqrt\": {\n      return [ops.sqrt(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Square\": {\n      return [ops.square(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Tanh\": {\n      return [ops.tanh(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"Tan\":\n      return [ops.tan(getParamValue(\"x\", node, tensorMap, context))];\n    case \"ClipByValue\":\n      return [ops.clipByValue(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"clipValueMin\", node, tensorMap, context), getParamValue(\"clipValueMax\", node, tensorMap, context))];\n    case \"Relu6\":\n      return [ops.relu6(getParamValue(\"x\", node, tensorMap, context))];\n    case \"Rsqrt\":\n      return [ops.rsqrt(getTensor(node.inputNames[0], tensorMap, context))];\n    case \"Prod\":\n      return [ops.prod(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"axes\", node, tensorMap, context))];\n    case \"LeakyRelu\":\n      return [ops.leakyRelu(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"alpha\", node, tensorMap, context))];\n    case \"Prelu\":\n      return [ops.prelu(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"alpha\", node, tensorMap, context))];\n    case \"IsNan\":\n      return [ops.isNaN(getTensor(node.inputNames[0], tensorMap, context))];\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/tensor_utils.js\nfunction assertShapesMatchAllowUndefinedSize(shapeA, shapeB, errorMessagePrefix = \"\") {\n  if (typeof shapeA === \"number\" || typeof shapeB === \"number\") {\n    return;\n  }\n  util_exports.assert(shapeA.length === shapeB.length, () => errorMessagePrefix + ` Shapes ${shapeA} and ${shapeB} must match`);\n  for (let i2 = 0; i2 < shapeA.length; i2++) {\n    const dim0 = shapeA[i2];\n    const dim1 = shapeB[i2];\n    util_exports.assert(dim0 < 0 || dim1 < 0 || dim0 === dim1, () => errorMessagePrefix + ` Shapes ${shapeA} and ${shapeB} must match`);\n  }\n}\nfunction fullDefinedShape(elementShape) {\n  if (typeof elementShape === \"number\" || elementShape.some((dim) => dim < 0)) {\n    return false;\n  }\n  return true;\n}\nfunction inferElementShape(listElementShape, tensors, elementShape) {\n  let partialShape = mergeElementShape(listElementShape, elementShape);\n  const notfullDefinedShape = !fullDefinedShape(partialShape);\n  if (notfullDefinedShape && tensors.length === 0) {\n    throw new Error(`Tried to calculate elements of an empty list with non-fully-defined elementShape: ${partialShape}`);\n  }\n  if (notfullDefinedShape) {\n    tensors.forEach((tensor2) => {\n      partialShape = mergeElementShape(tensor2.shape, partialShape);\n    });\n  }\n  if (!fullDefinedShape(partialShape)) {\n    throw new Error(`Non-fully-defined elementShape: ${partialShape}`);\n  }\n  return partialShape;\n}\nfunction mergeElementShape(elementShapeA, elementShapeB) {\n  if (typeof elementShapeA === \"number\") {\n    return elementShapeB;\n  }\n  if (typeof elementShapeB === \"number\") {\n    return elementShapeA;\n  }\n  if (elementShapeA.length !== elementShapeB.length) {\n    throw new Error(`Incompatible ranks during merge: ${elementShapeA} vs. ${elementShapeB}`);\n  }\n  const result = [];\n  for (let i2 = 0; i2 < elementShapeA.length; ++i2) {\n    const dim0 = elementShapeA[i2];\n    const dim1 = elementShapeB[i2];\n    if (dim0 >= 0 && dim1 >= 0 && dim0 !== dim1) {\n      throw new Error(`Incompatible shape during merge: ${elementShapeA} vs. ${elementShapeB}`);\n    }\n    result[i2] = dim0 >= 0 ? dim0 : dim1;\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/tensor_array.js\nvar TensorArray = class {\n  constructor(name, dtype, maxSize, elementShape, identicalElementShapes, dynamicSize, clearAfterRead) {\n    this.name = name;\n    this.dtype = dtype;\n    this.maxSize = maxSize;\n    this.elementShape = elementShape;\n    this.identicalElementShapes = identicalElementShapes;\n    this.dynamicSize = dynamicSize;\n    this.clearAfterRead = clearAfterRead;\n    this.tensors = [];\n    this.closed_ = false;\n    this.idTensor = scalar(0);\n    keep(this.idTensor);\n  }\n  get id() {\n    return this.idTensor.id;\n  }\n  get closed() {\n    return this.closed_;\n  }\n  clearAndClose(keepIds) {\n    this.tensors.forEach((tensor2) => {\n      if (keepIds == null || !keepIds.has(tensor2.tensor.id)) {\n        tensor2.tensor.dispose();\n      }\n    });\n    this.tensors = [];\n    this.closed_ = true;\n    this.idTensor.dispose();\n  }\n  size() {\n    return this.tensors.length;\n  }\n  read(index) {\n    if (this.closed_) {\n      throw new Error(`TensorArray ${this.name} has already been closed.`);\n    }\n    if (index < 0 || index >= this.size()) {\n      throw new Error(`Tried to read from index ${index}, but array size is: ${this.size()}`);\n    }\n    const tensorWithState = this.tensors[index];\n    if (tensorWithState.cleared) {\n      throw new Error(`TensorArray ${this.name}: Could not read index ${index} twice because it was cleared after a previous read (perhaps try setting clear_after_read = false?).`);\n    }\n    if (this.clearAfterRead) {\n      tensorWithState.cleared = true;\n    }\n    tensorWithState.read = true;\n    return tensorWithState.tensor;\n  }\n  readMany(indices) {\n    return indices.map((index) => this.read(index));\n  }\n  write(index, tensor2) {\n    if (this.closed_) {\n      throw new Error(`TensorArray ${this.name} has already been closed.`);\n    }\n    if (index < 0 || !this.dynamicSize && index >= this.maxSize) {\n      throw new Error(`Tried to write to index ${index}, but array is not resizeable and size is: ${this.maxSize}`);\n    }\n    const t2 = this.tensors[index] || {};\n    if (tensor2.dtype !== this.dtype) {\n      throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${index},\n          because the value dtype is ${tensor2.dtype}, but TensorArray dtype is ${this.dtype}.`);\n    }\n    if (this.size() === 0 && (this.elementShape == null || this.elementShape.length === 0)) {\n      this.elementShape = tensor2.shape;\n    }\n    assertShapesMatchAllowUndefinedSize(this.elementShape, tensor2.shape, `TensorArray ${this.name}: Could not write to TensorArray index ${index}.`);\n    if (t2.read) {\n      throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${index}, because it has already been read.`);\n    }\n    if (t2.written) {\n      throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${index}, because it has already been written.`);\n    }\n    t2.tensor = tensor2;\n    keep(tensor2);\n    t2.written = true;\n    this.tensors[index] = t2;\n  }\n  writeMany(indices, tensors) {\n    if (indices.length !== tensors.length) {\n      throw new Error(`TensorArray ${this.name}: could not write multiple tensors,because the index size: ${indices.length} is not the same as tensors size: ${tensors.length}.`);\n    }\n    indices.forEach((i2, index) => this.write(i2, tensors[index]));\n  }\n  gather(indices, dtype) {\n    if (!!dtype && dtype !== this.dtype) {\n      throw new Error(`TensorArray dtype is ${this.dtype} but gather requested dtype ${dtype}`);\n    }\n    if (!indices) {\n      indices = [];\n      for (let i2 = 0; i2 < this.size(); i2++) {\n        indices.push(i2);\n      }\n    } else {\n      indices = indices.slice(0, this.size());\n    }\n    if (indices.length === 0) {\n      return tensor([], [0].concat(this.elementShape));\n    }\n    const tensors = this.readMany(indices);\n    assertShapesMatchAllowUndefinedSize(this.elementShape, tensors[0].shape, \"TensorArray shape mismatch: \");\n    return stack(tensors, 0);\n  }\n  concat(dtype) {\n    if (!!dtype && dtype !== this.dtype) {\n      throw new Error(`TensorArray dtype is ${this.dtype} but concat requested dtype ${dtype}`);\n    }\n    if (this.size() === 0) {\n      return tensor([], [0].concat(this.elementShape));\n    }\n    const indices = [];\n    for (let i2 = 0; i2 < this.size(); i2++) {\n      indices.push(i2);\n    }\n    const tensors = this.readMany(indices);\n    assertShapesMatchAllowUndefinedSize(this.elementShape, tensors[0].shape, `TensorArray shape mismatch: tensor array shape (${this.elementShape}) vs first tensor shape (${tensors[0].shape})`);\n    return concat(tensors, 0);\n  }\n  scatter(indices, tensor2) {\n    if (tensor2.dtype !== this.dtype) {\n      throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${tensor2.dtype}`);\n    }\n    if (indices.length !== tensor2.shape[0]) {\n      throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${indices.length} vs. ${tensor2.shape[0]}`);\n    }\n    const maxIndex = Math.max(...indices);\n    if (!this.dynamicSize && maxIndex >= this.maxSize) {\n      throw new Error(`Max index must be < array size (${maxIndex}  vs. ${this.maxSize})`);\n    }\n    this.writeMany(indices, unstack(tensor2, 0));\n  }\n  split(length, tensor2) {\n    if (tensor2.dtype !== this.dtype) {\n      throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${tensor2.dtype}`);\n    }\n    let totalLength = 0;\n    const cumulativeLengths = length.map((len) => {\n      totalLength += len;\n      return totalLength;\n    });\n    if (totalLength !== tensor2.shape[0]) {\n      throw new Error(`Expected sum of lengths to be equal to\n          tensor.shape[0], but sum of lengths is\n        ${totalLength}, and tensor's shape is: ${tensor2.shape}`);\n    }\n    if (!this.dynamicSize && length.length !== this.maxSize) {\n      throw new Error(`TensorArray's size is not equal to the size of lengths (${this.maxSize} vs. ${length.length}), and the TensorArray is not marked as dynamically resizeable`);\n    }\n    const elementPerRow = totalLength === 0 ? 0 : tensor2.size / totalLength;\n    const tensors = [];\n    tidy(() => {\n      tensor2 = reshape(tensor2, [1, totalLength, elementPerRow]);\n      for (let i2 = 0; i2 < length.length; ++i2) {\n        const previousLength = i2 === 0 ? 0 : cumulativeLengths[i2 - 1];\n        const indices2 = [0, previousLength, 0];\n        const sizes = [1, length[i2], elementPerRow];\n        tensors[i2] = reshape(slice(tensor2, indices2, sizes), this.elementShape);\n      }\n      return tensors;\n    });\n    const indices = [];\n    for (let i2 = 0; i2 < length.length; i2++) {\n      indices[i2] = i2;\n    }\n    this.writeMany(indices, tensors);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/tensor_list.js\nvar TensorList = class {\n  constructor(tensors, elementShape, elementDtype, maxNumElements = -1) {\n    this.tensors = tensors;\n    this.elementShape = elementShape;\n    this.elementDtype = elementDtype;\n    if (tensors != null) {\n      tensors.forEach((tensor2) => {\n        if (elementDtype !== tensor2.dtype) {\n          throw new Error(`Invalid data types; op elements ${elementDtype}, but list elements ${tensor2.dtype}`);\n        }\n        assertShapesMatchAllowUndefinedSize(elementShape, tensor2.shape, \"TensorList shape mismatch: \");\n        keep(tensor2);\n      });\n    }\n    this.idTensor = scalar(0);\n    this.maxNumElements = maxNumElements;\n    keep(this.idTensor);\n  }\n  get id() {\n    return this.idTensor.id;\n  }\n  copy() {\n    return new TensorList([...this.tensors], this.elementShape, this.elementDtype);\n  }\n  clearAndClose(keepIds) {\n    this.tensors.forEach((tensor2) => {\n      if (keepIds == null || !keepIds.has(tensor2.id)) {\n        tensor2.dispose();\n      }\n    });\n    this.tensors.length = 0;\n    this.idTensor.dispose();\n  }\n  size() {\n    return this.tensors.length;\n  }\n  stack(elementShape, elementDtype, numElements = -1) {\n    if (elementDtype !== this.elementDtype) {\n      throw new Error(`Invalid data types; op elements ${elementDtype}, but list elements ${this.elementDtype}`);\n    }\n    if (numElements !== -1 && this.tensors.length !== numElements) {\n      throw new Error(`Operation expected a list with ${numElements} elements but got a list with ${this.tensors.length} elements.`);\n    }\n    assertShapesMatchAllowUndefinedSize(elementShape, this.elementShape, \"TensorList shape mismatch: \");\n    const outputElementShape = inferElementShape(this.elementShape, this.tensors, elementShape);\n    return tidy(() => {\n      const reshapedTensors = this.tensors.map((tensor2) => reshape(tensor2, outputElementShape));\n      return stack(reshapedTensors, 0);\n    });\n  }\n  popBack(elementShape, elementDtype) {\n    if (elementDtype !== this.elementDtype) {\n      throw new Error(`Invalid data types; op elements ${elementDtype}, but list elements ${this.elementDtype}`);\n    }\n    if (this.size() === 0) {\n      throw new Error(\"Trying to pop from an empty list.\");\n    }\n    const outputElementShape = inferElementShape(this.elementShape, this.tensors, elementShape);\n    const tensor2 = this.tensors.pop();\n    assertShapesMatchAllowUndefinedSize(tensor2.shape, elementShape, \"TensorList shape mismatch: \");\n    return reshape(tensor2, outputElementShape);\n  }\n  pushBack(tensor2) {\n    if (tensor2.dtype !== this.elementDtype) {\n      throw new Error(`Invalid data types; op elements ${tensor2.dtype}, but list elements ${this.elementDtype}`);\n    }\n    assertShapesMatchAllowUndefinedSize(tensor2.shape, this.elementShape, \"TensorList shape mismatch: \");\n    if (this.maxNumElements === this.size()) {\n      throw new Error(`Trying to push element into a full list.`);\n    }\n    keep(tensor2);\n    this.tensors.push(tensor2);\n  }\n  resize(size) {\n    if (size < 0) {\n      throw new Error(`TensorListResize expects size to be non-negative. Got: ${size}`);\n    }\n    if (this.maxNumElements !== -1 && size > this.maxNumElements) {\n      throw new Error(`TensorListResize input size ${size} is greater maxNumElement ${this.maxNumElements}.`);\n    }\n    const destTensorList = new TensorList([], this.elementShape, this.elementDtype, this.maxNumElements);\n    destTensorList.tensors.length = size;\n    for (let i2 = 0; i2 < Math.min(this.tensors.length, size); ++i2) {\n      destTensorList.tensors[i2] = this.tensors[i2];\n    }\n    return destTensorList;\n  }\n  getItem(elementIndex, elementShape, elementDtype) {\n    if (elementDtype !== this.elementDtype) {\n      throw new Error(`Invalid data types; op elements ${elementDtype}, but list elements ${this.elementDtype}`);\n    }\n    if (elementIndex < 0 || elementIndex > this.tensors.length) {\n      throw new Error(`Trying to access element ${elementIndex} in a list with ${this.tensors.length} elements.`);\n    }\n    if (this.tensors[elementIndex] == null) {\n      throw new Error(`element at index ${elementIndex} is null.`);\n    }\n    assertShapesMatchAllowUndefinedSize(this.tensors[elementIndex].shape, elementShape, \"TensorList shape mismatch: \");\n    const outputElementShape = inferElementShape(this.elementShape, this.tensors, elementShape);\n    return reshape(this.tensors[elementIndex], outputElementShape);\n  }\n  setItem(elementIndex, tensor2) {\n    if (tensor2.dtype !== this.elementDtype) {\n      throw new Error(`Invalid data types; op elements ${tensor2.dtype}, but list elements ${this.elementDtype}`);\n    }\n    if (elementIndex < 0 || this.maxNumElements !== -1 && elementIndex >= this.maxNumElements) {\n      throw new Error(`Trying to set element ${elementIndex} in a list with max ${this.maxNumElements} elements.`);\n    }\n    assertShapesMatchAllowUndefinedSize(this.elementShape, tensor2.shape, \"TensorList shape mismatch: \");\n    keep(tensor2);\n    this.tensors[elementIndex] = tensor2;\n  }\n  gather(indices, elementDtype, elementShape) {\n    if (elementDtype !== this.elementDtype) {\n      throw new Error(`Invalid data types; op elements ${elementDtype}, but list elements ${this.elementDtype}`);\n    }\n    assertShapesMatchAllowUndefinedSize(this.elementShape, elementShape, \"TensorList shape mismatch: \");\n    indices = indices.slice(0, this.size());\n    const outputElementShape = inferElementShape(this.elementShape, this.tensors, elementShape);\n    if (indices.length === 0) {\n      return tensor([], [0].concat(outputElementShape));\n    }\n    return tidy(() => {\n      const tensors = indices.map((i2) => reshape(this.tensors[i2], outputElementShape));\n      return stack(tensors, 0);\n    });\n  }\n  concat(elementDtype, elementShape) {\n    if (!!elementDtype && elementDtype !== this.elementDtype) {\n      throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${elementDtype}`);\n    }\n    assertShapesMatchAllowUndefinedSize(this.elementShape, elementShape, \"TensorList shape mismatch: \");\n    const outputElementShape = inferElementShape(this.elementShape, this.tensors, elementShape);\n    if (this.size() === 0) {\n      return tensor([], [0].concat(outputElementShape));\n    }\n    return tidy(() => {\n      const tensors = this.tensors.map((t2) => reshape(t2, outputElementShape));\n      return concat(tensors, 0);\n    });\n  }\n};\nfunction fromTensor(tensor2, elementShape, elementDtype) {\n  const dtype = tensor2.dtype;\n  if (tensor2.shape.length < 1) {\n    throw new Error(`Tensor must be at least a vector, but saw shape: ${tensor2.shape}`);\n  }\n  if (tensor2.dtype !== elementDtype) {\n    throw new Error(`Invalid data types; op elements ${tensor2.dtype}, but list elements ${elementDtype}`);\n  }\n  const tensorElementShape = tensor2.shape.slice(1);\n  assertShapesMatchAllowUndefinedSize(tensorElementShape, elementShape, \"TensorList shape mismatch: \");\n  const tensorList = unstack(tensor2);\n  return new TensorList(tensorList, elementShape, dtype);\n}\nfunction reserve(elementShape, elementDtype, numElements, maxNumElements) {\n  return new TensorList([], elementShape, elementDtype, maxNumElements);\n}\nfunction scatter(tensor2, indices, elementShape, numElements) {\n  if (indices.length !== tensor2.shape[0]) {\n    throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${indices.length} vs. ${tensor2.shape[0]}`);\n  }\n  const maxIndex = Math.max(...indices);\n  if (numElements != null && numElements !== -1 && maxIndex >= numElements) {\n    throw new Error(`Max index must be < array size (${maxIndex}  vs. ${numElements})`);\n  }\n  const list = new TensorList([], elementShape, tensor2.dtype, numElements);\n  const tensors = unstack(tensor2, 0);\n  indices.forEach((value, index) => {\n    list.setItem(value, tensors[index]);\n  });\n  return list;\n}\nfunction split2(tensor2, length, elementShape) {\n  let totalLength = 0;\n  const cumulativeLengths = length.map((len) => {\n    totalLength += len;\n    return totalLength;\n  });\n  if (totalLength !== tensor2.shape[0]) {\n    throw new Error(`Expected sum of lengths to be equal to\n          tensor.shape[0], but sum of lengths is\n        ${totalLength}, and tensor's shape is: ${tensor2.shape}`);\n  }\n  const shapeWithoutFirstDim = tensor2.shape.slice(1);\n  const outputElementShape = mergeElementShape(shapeWithoutFirstDim, elementShape);\n  const elementPerRow = totalLength === 0 ? 0 : tensor2.size / totalLength;\n  const tensors = tidy(() => {\n    const tensors2 = [];\n    tensor2 = reshape(tensor2, [1, totalLength, elementPerRow]);\n    for (let i2 = 0; i2 < length.length; ++i2) {\n      const previousLength = i2 === 0 ? 0 : cumulativeLengths[i2 - 1];\n      const indices = [0, previousLength, 0];\n      const sizes = [1, length[i2], elementPerRow];\n      tensors2[i2] = reshape(slice(tensor2, indices, sizes), outputElementShape);\n    }\n    tensor2.dispose();\n    return tensors2;\n  });\n  const list = new TensorList([], elementShape, tensor2.dtype, length.length);\n  for (let i2 = 0; i2 < tensors.length; i2++) {\n    list.setItem(i2, tensors[i2]);\n  }\n  return list;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/control_executor.js\nvar executeOp3 = async (node, tensorMap, context) => {\n  switch (node.op) {\n    case \"If\":\n    case \"StatelessIf\": {\n      const thenFunc = getParamValue(\"thenBranch\", node, tensorMap, context);\n      const elseFunc = getParamValue(\"elseBranch\", node, tensorMap, context);\n      const cond = getParamValue(\"cond\", node, tensorMap, context);\n      const args = getParamValue(\"args\", node, tensorMap, context);\n      const condValue = await cond.data();\n      if (condValue[0]) {\n        return context.functionMap[thenFunc].executeFunctionAsync(args, context.tensorArrayMap, context.tensorListMap);\n      } else {\n        return context.functionMap[elseFunc].executeFunctionAsync(args, context.tensorArrayMap, context.tensorListMap);\n      }\n    }\n    case \"While\":\n    case \"StatelessWhile\": {\n      const bodyFunc = getParamValue(\"body\", node, tensorMap, context);\n      const condFunc = getParamValue(\"cond\", node, tensorMap, context);\n      const args = getParamValue(\"args\", node, tensorMap, context);\n      const condResult = await context.functionMap[condFunc].executeFunctionAsync(args, context.tensorArrayMap, context.tensorListMap);\n      const argIds = args.map((tensor2) => tensor2.id);\n      let condValue = await condResult[0].data();\n      condResult.forEach((tensor2) => {\n        if (!tensor2.kept && argIds.indexOf(tensor2.id) === -1) {\n          tensor2.dispose();\n        }\n      });\n      let result = args;\n      while (condValue[0]) {\n        const origResult = result;\n        result = await context.functionMap[bodyFunc].executeFunctionAsync(result, context.tensorArrayMap, context.tensorListMap);\n        const resultIds = result.map((tensor2) => tensor2.id);\n        origResult.forEach((tensor2) => {\n          if (!tensor2.kept && argIds.indexOf(tensor2.id) === -1 && resultIds.indexOf(tensor2.id) === -1) {\n            tensor2.dispose();\n          }\n        });\n        const condResult2 = await context.functionMap[condFunc].executeFunctionAsync(result, context.tensorArrayMap, context.tensorListMap);\n        condValue = await condResult2[0].data();\n        condResult2.forEach((tensor2) => {\n          if (!tensor2.kept && argIds.indexOf(tensor2.id) === -1 && resultIds.indexOf(tensor2.id) === -1) {\n            tensor2.dispose();\n          }\n        });\n      }\n      return result;\n    }\n    case \"LoopCond\": {\n      const pred = getParamValue(\"pred\", node, tensorMap, context);\n      return [cloneTensor(pred)];\n    }\n    case \"Switch\": {\n      const pred = getParamValue(\"pred\", node, tensorMap, context);\n      let data = getParamValue(\"data\", node, tensorMap, context);\n      if (!data.kept) {\n        data = cloneTensor(data);\n      }\n      return (await pred.data())[0] ? [void 0, data] : [data, void 0];\n    }\n    case \"Merge\": {\n      const inputName = node.inputNames.find((name) => getTensor(name, tensorMap, context) !== void 0);\n      if (inputName) {\n        const data = getTensor(inputName, tensorMap, context);\n        return [cloneTensor(data)];\n      }\n      return void 0;\n    }\n    case \"Enter\": {\n      const frameId = getParamValue(\"frameName\", node, tensorMap, context);\n      const data = getParamValue(\"tensor\", node, tensorMap, context);\n      context.enterFrame(frameId);\n      return [cloneTensor(data)];\n    }\n    case \"Exit\": {\n      const data = getParamValue(\"tensor\", node, tensorMap, context);\n      context.exitFrame();\n      return [cloneTensor(data)];\n    }\n    case \"NextIteration\": {\n      const data = getParamValue(\"tensor\", node, tensorMap, context);\n      context.nextIteration();\n      return [cloneTensor(data)];\n    }\n    case \"TensorArrayV3\": {\n      const size = getParamValue(\"size\", node, tensorMap, context);\n      const dtype = getParamValue(\"dtype\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const dynamicSize = getParamValue(\"dynamicSize\", node, tensorMap, context);\n      const clearAfterRead = getParamValue(\"clearAfterRead\", node, tensorMap, context);\n      const identicalElementShapes = getParamValue(\"identicalElementShapes\", node, tensorMap, context);\n      const name = getParamValue(\"name\", node, tensorMap, context);\n      const tensorArray = new TensorArray(name, dtype, size, elementShape, identicalElementShapes, dynamicSize, clearAfterRead);\n      context.addTensorArray(tensorArray);\n      return [tensorArray.idTensor, scalar(1)];\n    }\n    case \"TensorArrayWriteV3\": {\n      const id = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const index = getParamValue(\"index\", node, tensorMap, context);\n      const writeTensor = getParamValue(\"tensor\", node, tensorMap, context);\n      const writeTensorArray = context.getTensorArray(id.id);\n      writeTensorArray.write(index, writeTensor);\n      return [writeTensorArray.idTensor];\n    }\n    case \"TensorArrayReadV3\": {\n      const readId = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const readIndex = getParamValue(\"index\", node, tensorMap, context);\n      const readTensorArray = context.getTensorArray(readId.id);\n      return [readTensorArray.read(readIndex)];\n    }\n    case \"TensorArrayGatherV3\": {\n      const gatherId = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const gatherIndices = getParamValue(\"indices\", node, tensorMap, context);\n      const gatherDtype = getParamValue(\"dtype\", node, tensorMap, context);\n      const gatherTensorArray = context.getTensorArray(gatherId.id);\n      return [gatherTensorArray.gather(gatherIndices, gatherDtype)];\n    }\n    case \"TensorArrayScatterV3\": {\n      const scatterId = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const scatterIndices = getParamValue(\"indices\", node, tensorMap, context);\n      const scatterTensor = getParamValue(\"tensor\", node, tensorMap, context);\n      const scatterTensorArray = context.getTensorArray(scatterId.id);\n      scatterTensorArray.scatter(scatterIndices, scatterTensor);\n      return [scatterTensorArray.idTensor];\n    }\n    case \"TensorArrayConcatV3\": {\n      const concatId = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const concatTensorArray = context.getTensorArray(concatId.id);\n      const concatDtype = getParamValue(\"dtype\", node, tensorMap, context);\n      return [concatTensorArray.concat(concatDtype)];\n    }\n    case \"TensorArraySplitV3\": {\n      const splitId = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const splitTensor = getParamValue(\"tensor\", node, tensorMap, context);\n      const lengths = getParamValue(\"lengths\", node, tensorMap, context);\n      const splitTensorArray = context.getTensorArray(splitId.id);\n      splitTensorArray.split(lengths, splitTensor);\n      return [splitTensorArray.idTensor];\n    }\n    case \"TensorArraySizeV3\": {\n      const sizeId = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const sizeTensorArray = context.getTensorArray(sizeId.id);\n      return [scalar(sizeTensorArray.size(), \"int32\")];\n    }\n    case \"TensorArrayCloseV3\": {\n      const closeId = getParamValue(\"tensorArrayId\", node, tensorMap, context);\n      const closeTensorArray = context.getTensorArray(closeId.id);\n      closeTensorArray.clearAndClose();\n      return [closeTensorArray.idTensor];\n    }\n    case \"TensorListSetItem\": {\n      const idTensor = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const index = getParamValue(\"index\", node, tensorMap, context);\n      const writeTensor = getParamValue(\"tensor\", node, tensorMap, context);\n      const tensorList = context.getTensorList(idTensor.id);\n      tensorList.setItem(index, writeTensor);\n      return [tensorList.idTensor];\n    }\n    case \"TensorListGetItem\": {\n      const idTensor = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const readIndex = getParamValue(\"index\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const elementDType = getParamValue(\"elementDType\", node, tensorMap, context);\n      const tensorList = context.getTensorList(idTensor.id);\n      return [tensorList.getItem(readIndex, elementShape, elementDType)];\n    }\n    case \"TensorListScatterV2\":\n    case \"TensorListScatter\": {\n      const scatterIndices = getParamValue(\"indices\", node, tensorMap, context);\n      const scatterTensor = getParamValue(\"tensor\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const numElements = getParamValue(\"numElements\", node, tensorMap, context);\n      const tensorList = scatter(scatterTensor, scatterIndices, elementShape, numElements);\n      context.addTensorList(tensorList);\n      return [tensorList.idTensor];\n    }\n    case \"TensorListReserve\":\n    case \"EmptyTensorList\": {\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const elementDtype = getParamValue(\"elementDType\", node, tensorMap, context);\n      let numElementsParam;\n      if (node.op === \"TensorListReserve\") {\n        numElementsParam = \"numElements\";\n      } else {\n        numElementsParam = \"maxNumElements\";\n      }\n      const numElements = getParamValue(numElementsParam, node, tensorMap, context);\n      const maxNumElements = node.op === \"TensorListReserve\" ? -1 : numElements;\n      const tensorList = reserve(elementShape, elementDtype, numElements, maxNumElements);\n      context.addTensorList(tensorList);\n      return [tensorList.idTensor];\n    }\n    case \"TensorListGather\": {\n      const gatherId = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const gatherIndices = getParamValue(\"indices\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const elementDtype = getParamValue(\"elementDType\", node, tensorMap, context);\n      const tensorList = context.getTensorList(gatherId.id);\n      return [tensorList.gather(gatherIndices, elementDtype, elementShape)];\n    }\n    case \"TensorListStack\": {\n      const idTensor = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const elementDtype = getParamValue(\"elementDType\", node, tensorMap, context);\n      const numElements = getParamValue(\"numElements\", node, tensorMap, context);\n      const tensorList = context.getTensorList(idTensor.id);\n      return [tensorList.stack(elementShape, elementDtype, numElements)];\n    }\n    case \"TensorListFromTensor\": {\n      const tensor2 = getParamValue(\"tensor\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const elementDtype = getParamValue(\"elementDType\", node, tensorMap, context);\n      const tensorList = fromTensor(tensor2, elementShape, elementDtype);\n      context.addTensorList(tensorList);\n      return [tensorList.idTensor];\n    }\n    case \"TensorListConcat\":\n    case \"TensorListConcatV2\": {\n      const concatId = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const tensorList = context.getTensorList(concatId.id);\n      const concatDtype = getParamValue(\"dtype\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      return [tensorList.concat(concatDtype, elementShape)];\n    }\n    case \"TensorListPushBack\": {\n      const idTensor = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const writeTensor = getParamValue(\"tensor\", node, tensorMap, context);\n      const tensorList = context.getTensorList(idTensor.id);\n      tensorList.pushBack(writeTensor);\n      return [tensorList.idTensor];\n    }\n    case \"TensorListPopBack\": {\n      const idTensor = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const elementDType = getParamValue(\"elementDType\", node, tensorMap, context);\n      const tensorList = context.getTensorList(idTensor.id);\n      return [tensorList.popBack(elementShape, elementDType)];\n    }\n    case \"TensorListSplit\": {\n      const splitTensor = getParamValue(\"tensor\", node, tensorMap, context);\n      const elementShape = getParamValue(\"elementShape\", node, tensorMap, context);\n      const lengths = getParamValue(\"lengths\", node, tensorMap, context);\n      const tensorList = split2(splitTensor, lengths, elementShape);\n      context.addTensorList(tensorList);\n      return [tensorList.idTensor];\n    }\n    case \"TensorListLength\": {\n      const idTensor = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const tensorList = context.getTensorList(idTensor.id);\n      return [scalar(tensorList.size(), \"int32\")];\n    }\n    case \"TensorListResize\": {\n      const idTensor = getParamValue(\"tensorListId\", node, tensorMap, context);\n      const size = getParamValue(\"size\", node, tensorMap, context);\n      const srcTensorList = context.getTensorList(idTensor.id);\n      const destTensorList = srcTensorList.resize(size);\n      context.addTensorList(destTensorList);\n      return [destTensorList.idTensor];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/convolution_executor.js\nfunction fusedConvAndDepthWiseParams(node, tensorMap, context) {\n  const [extraOp, activationFunc] = getParamValue(\"fusedOps\", node, tensorMap, context);\n  const isBiasAdd = extraOp === \"biasadd\";\n  const noBiasAdd = !isBiasAdd;\n  const isPrelu = activationFunc === \"prelu\";\n  const isBatchNorm = extraOp === \"fusedbatchnorm\";\n  const numArgs = getParamValue(\"numArgs\", node, tensorMap, context);\n  if (isBiasAdd) {\n    if (isPrelu && numArgs !== 2) {\n      throw new Error(\"FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.\");\n    }\n    if (!isPrelu && isBiasAdd && numArgs !== 1) {\n      throw new Error(\"FusedConv2d and DepthwiseConv2d with BiasAdd must have one extra argument: bias.\");\n    }\n  }\n  if (isBatchNorm) {\n    throw new Error(\"FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported\");\n  }\n  const stride = getParamValue(\"strides\", node, tensorMap, context);\n  const pad3 = getPadding(node, tensorMap, context);\n  const dataFormat = getParamValue(\"dataFormat\", node, tensorMap, context).toUpperCase();\n  const dilations = getParamValue(\"dilations\", node, tensorMap, context);\n  let [biasArg, preluArg] = getParamValue(\"args\", node, tensorMap, context);\n  if (noBiasAdd) {\n    preluArg = biasArg;\n    biasArg = void 0;\n  }\n  const leakyreluAlpha = getParamValue(\"leakyreluAlpha\", node, tensorMap, context);\n  return {\n    stride,\n    pad: pad3,\n    dataFormat,\n    dilations,\n    biasArg,\n    preluArg,\n    activationFunc,\n    leakyreluAlpha\n  };\n}\nvar executeOp4 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"Conv1D\": {\n      const stride = getParamValue(\"stride\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const dataFormat = getParamValue(\"dataFormat\", node, tensorMap, context).toUpperCase();\n      const dilation = getParamValue(\"dilation\", node, tensorMap, context);\n      return [ops.conv1d(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"filter\", node, tensorMap, context), stride, pad3, dataFormat, dilation)];\n    }\n    case \"Conv2D\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getPadding(node, tensorMap, context);\n      const dataFormat = getParamValue(\"dataFormat\", node, tensorMap, context).toUpperCase();\n      const dilations = getParamValue(\"dilations\", node, tensorMap, context);\n      return [ops.conv2d(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"filter\", node, tensorMap, context), [stride[1], stride[2]], pad3, dataFormat, [dilations[1], dilations[2]])];\n    }\n    case \"_FusedConv2D\": {\n      const { stride, pad: pad3, dataFormat, dilations, biasArg, preluArg, activationFunc, leakyreluAlpha } = fusedConvAndDepthWiseParams(node, tensorMap, context);\n      return [ops.fused.conv2d({\n        x: getParamValue(\"x\", node, tensorMap, context),\n        filter: getParamValue(\"filter\", node, tensorMap, context),\n        strides: [stride[1], stride[2]],\n        pad: pad3,\n        dataFormat,\n        dilations: [dilations[1], dilations[2]],\n        bias: biasArg,\n        activation: activationFunc,\n        preluActivationWeights: preluArg,\n        leakyreluAlpha\n      })];\n    }\n    case \"FusedDepthwiseConv2dNative\": {\n      const { stride, pad: pad3, dataFormat, dilations, biasArg, preluArg, activationFunc, leakyreluAlpha } = fusedConvAndDepthWiseParams(node, tensorMap, context);\n      return [ops.fused.depthwiseConv2d({\n        x: getParamValue(\"x\", node, tensorMap, context),\n        filter: getParamValue(\"filter\", node, tensorMap, context),\n        strides: [stride[1], stride[2]],\n        pad: pad3,\n        dataFormat,\n        dilations: [dilations[1], dilations[2]],\n        bias: biasArg,\n        activation: activationFunc,\n        preluActivationWeights: preluArg,\n        leakyreluAlpha\n      })];\n    }\n    case \"Conv2DBackpropInput\":\n    case \"Conv2dTranspose\": {\n      const shape = getParamValue(\"outputShape\", node, tensorMap, context);\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getPadding(node, tensorMap, context);\n      return [ops.conv2dTranspose(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"filter\", node, tensorMap, context), shape, [stride[1], stride[2]], pad3)];\n    }\n    case \"DepthwiseConv2dNative\":\n    case \"DepthwiseConv2d\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getPadding(node, tensorMap, context);\n      const dilations = getParamValue(\"dilations\", node, tensorMap, context);\n      const dataFormat = getParamValue(\"dataFormat\", node, tensorMap, context).toUpperCase();\n      return [ops.depthwiseConv2d(getParamValue(\"input\", node, tensorMap, context), getParamValue(\"filter\", node, tensorMap, context), [stride[1], stride[2]], pad3, dataFormat, [dilations[1], dilations[2]])];\n    }\n    case \"Conv3D\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const dataFormat = getParamValue(\"dataFormat\", node, tensorMap, context).toUpperCase();\n      const dilations = getParamValue(\"dilations\", node, tensorMap, context);\n      return [ops.conv3d(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"filter\", node, tensorMap, context), [stride[1], stride[2], stride[3]], pad3, dataFormat, [dilations[1], dilations[2], dilations[3]])];\n    }\n    case \"AvgPool\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const kernelSize = getParamValue(\"kernelSize\", node, tensorMap, context);\n      return [ops.avgPool(getParamValue(\"x\", node, tensorMap, context), [kernelSize[1], kernelSize[2]], [stride[1], stride[2]], pad3)];\n    }\n    case \"MaxPool\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const kernelSize = getParamValue(\"kernelSize\", node, tensorMap, context);\n      return [ops.maxPool(getParamValue(\"x\", node, tensorMap, context), [kernelSize[1], kernelSize[2]], [stride[1], stride[2]], pad3)];\n    }\n    case \"MaxPoolWithArgmax\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const kernelSize = getParamValue(\"kernelSize\", node, tensorMap, context);\n      const includeBatchInIndex = getParamValue(\"includeBatchInIndex\", node, tensorMap, context);\n      const { result, indexes } = ops.maxPoolWithArgmax(getParamValue(\"x\", node, tensorMap, context), [kernelSize[1], kernelSize[2]], [stride[1], stride[2]], pad3, includeBatchInIndex);\n      return [result, indexes];\n    }\n    case \"AvgPool3D\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const kernelSize = getParamValue(\"kernelSize\", node, tensorMap, context);\n      return [ops.avgPool3d(getParamValue(\"x\", node, tensorMap, context), [kernelSize[1], kernelSize[2], kernelSize[3]], [stride[1], stride[2], stride[3]], pad3)];\n    }\n    case \"MaxPool3D\": {\n      const stride = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const kernelSize = getParamValue(\"kernelSize\", node, tensorMap, context);\n      return [ops.maxPool3d(getParamValue(\"x\", node, tensorMap, context), [kernelSize[1], kernelSize[2], kernelSize[3]], [stride[1], stride[2], stride[3]], pad3)];\n    }\n    case \"Dilation2D\": {\n      const strides = getParamValue(\"strides\", node, tensorMap, context);\n      const pad3 = getParamValue(\"pad\", node, tensorMap, context);\n      const dilations = getParamValue(\"dilations\", node, tensorMap, context);\n      const strideHeight = strides[1];\n      const strideWidth = strides[2];\n      const dilationHeight = dilations[1];\n      const dilationWidth = dilations[2];\n      return [ops.dilation2d(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"filter\", node, tensorMap, context), [strideHeight, strideWidth], pad3, [dilationHeight, dilationWidth], \"NHWC\")];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/creation_executor.js\nvar executeOp5 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"Fill\": {\n      const shape = getParamValue(\"shape\", node, tensorMap, context);\n      const dtype = getParamValue(\"dtype\", node, tensorMap, context);\n      const value = getParamValue(\"value\", node, tensorMap, context);\n      return [ops.fill(shape, value, dtype)];\n    }\n    case \"LinSpace\": {\n      const start = getParamValue(\"start\", node, tensorMap, context);\n      const stop = getParamValue(\"stop\", node, tensorMap, context);\n      const num = getParamValue(\"num\", node, tensorMap, context);\n      return [ops.linspace(start, stop, num)];\n    }\n    case \"Multinomial\": {\n      const logits = getParamValue(\"logits\", node, tensorMap, context);\n      const numSamples = getParamValue(\"numSamples\", node, tensorMap, context);\n      const seed = getParamValue(\"seed\", node, tensorMap, context);\n      return [ops.multinomial(logits, numSamples, seed)];\n    }\n    case \"OneHot\": {\n      const indices = getParamValue(\"indices\", node, tensorMap, context);\n      const depth = getParamValue(\"depth\", node, tensorMap, context);\n      const onValue = getParamValue(\"onValue\", node, tensorMap, context);\n      const offValue = getParamValue(\"offValue\", node, tensorMap, context);\n      return [ops.oneHot(indices, depth, onValue, offValue)];\n    }\n    case \"Ones\": {\n      return [ops.ones(getParamValue(\"shape\", node, tensorMap, context), getParamValue(\"dtype\", node, tensorMap, context))];\n    }\n    case \"OnesLike\": {\n      return [ops.onesLike(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"RandomStandardNormal\": {\n      return [ops.randomStandardNormal(getParamValue(\"shape\", node, tensorMap, context), getParamValue(\"dtype\", node, tensorMap, context), getParamValue(\"seed\", node, tensorMap, context))];\n    }\n    case \"RandomUniform\": {\n      return [ops.randomUniform(\n        getParamValue(\"shape\", node, tensorMap, context),\n        getParamValue(\"minval\", node, tensorMap, context),\n        getParamValue(\"maxval\", node, tensorMap, context),\n        getParamValue(\"dtype\", node, tensorMap, context)\n      )];\n    }\n    case \"Range\": {\n      const start = getParamValue(\"start\", node, tensorMap, context);\n      const stop = getParamValue(\"stop\", node, tensorMap, context);\n      const step5 = getParamValue(\"step\", node, tensorMap, context);\n      return [ops.range(start, stop, step5, getParamValue(\"dtype\", node, tensorMap, context))];\n    }\n    case \"TruncatedNormal\": {\n      const shape = getParamValue(\"shape\", node, tensorMap, context);\n      const mean5 = getParamValue(\"mean\", node, tensorMap, context);\n      const stdDev = getParamValue(\"stdDev\", node, tensorMap, context);\n      const seed = getParamValue(\"seed\", node, tensorMap, context);\n      return [ops.truncatedNormal(shape, mean5, stdDev, getParamValue(\"dtype\", node, tensorMap, context), seed)];\n    }\n    case \"Zeros\": {\n      return [ops.zeros(getParamValue(\"shape\", node, tensorMap, context), getParamValue(\"dtype\", node, tensorMap, context))];\n    }\n    case \"ZerosLike\": {\n      return [ops.zerosLike(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/dynamic_executor.js\nfunction nmsParams(node, tensorMap, context) {\n  const boxes = getParamValue(\"boxes\", node, tensorMap, context);\n  const scores = getParamValue(\"scores\", node, tensorMap, context);\n  const maxOutputSize = getParamValue(\"maxOutputSize\", node, tensorMap, context);\n  const iouThreshold = getParamValue(\"iouThreshold\", node, tensorMap, context);\n  const scoreThreshold = getParamValue(\"scoreThreshold\", node, tensorMap, context);\n  const softNmsSigma = getParamValue(\"softNmsSigma\", node, tensorMap, context);\n  return {\n    boxes,\n    scores,\n    maxOutputSize,\n    iouThreshold,\n    scoreThreshold,\n    softNmsSigma\n  };\n}\nvar executeOp6 = async (node, tensorMap, context, resourceManager, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"NonMaxSuppressionV5\": {\n      const { boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma } = nmsParams(node, tensorMap, context);\n      const result = await ops.image.nonMaxSuppressionWithScoreAsync(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma);\n      return [result.selectedIndices, result.selectedScores];\n    }\n    case \"NonMaxSuppressionV4\": {\n      const { boxes, scores, maxOutputSize, iouThreshold, scoreThreshold } = nmsParams(node, tensorMap, context);\n      const padToMaxOutputSize = getParamValue(\"padToMaxOutputSize\", node, tensorMap, context);\n      const result = await ops.image.nonMaxSuppressionPaddedAsync(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize);\n      return [result.selectedIndices, result.validOutputs];\n    }\n    case \"NonMaxSuppressionV3\":\n    case \"NonMaxSuppressionV2\": {\n      const { boxes, scores, maxOutputSize, iouThreshold, scoreThreshold } = nmsParams(node, tensorMap, context);\n      return [await ops.image.nonMaxSuppressionAsync(boxes, scores, maxOutputSize, iouThreshold, scoreThreshold)];\n    }\n    case \"Where\": {\n      const condition = ops.cast(getParamValue(\"condition\", node, tensorMap, context), \"bool\");\n      const result = [await ops.whereAsync(condition)];\n      condition.dispose();\n      return result;\n    }\n    case \"ListDiff\": {\n      return ops.setdiff1dAsync(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"y\", node, tensorMap, context));\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/evaluation_executor.js\nvar executeOp7 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"LowerBound\": {\n      const sortedSequence = getParamValue(\"sortedSequence\", node, tensorMap, context);\n      const values = getParamValue(\"values\", node, tensorMap, context);\n      return [ops.lowerBound(sortedSequence, values)];\n    }\n    case \"TopKV2\": {\n      const x = getParamValue(\"x\", node, tensorMap, context);\n      const k = getParamValue(\"k\", node, tensorMap, context);\n      const sorted = getParamValue(\"sorted\", node, tensorMap, context);\n      const result = ops.topk(x, k, sorted);\n      return [result.values, result.indices];\n    }\n    case \"UpperBound\": {\n      const sortedSequence = getParamValue(\"sortedSequence\", node, tensorMap, context);\n      const values = getParamValue(\"values\", node, tensorMap, context);\n      return [ops.upperBound(sortedSequence, values)];\n    }\n    case \"Unique\": {\n      const x = getParamValue(\"x\", node, tensorMap, context);\n      const result = ops.unique(x);\n      return [result.values, result.indices];\n    }\n    case \"UniqueV2\": {\n      const x = getParamValue(\"x\", node, tensorMap, context);\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const result = ops.unique(x, axis);\n      return [result.values, result.indices];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/graph_executor.js\nvar executeOp8 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"Const\": {\n      return tensorMap[node.name];\n    }\n    case \"PlaceholderWithDefault\":\n      const def = getParamValue(\"default\", node, tensorMap, context);\n      return [getTensor(node.name, tensorMap, context) || def];\n    case \"Placeholder\":\n      return [getTensor(node.name, tensorMap, context)];\n    case \"Identity\":\n    case \"StopGradient\":\n    case \"FakeQuantWithMinMaxVars\": {\n      const data2 = getParamValue(\"x\", node, tensorMap, context);\n      return [cloneTensor(data2)];\n    }\n    case \"IdentityN\":\n      return getParamValue(\"x\", node, tensorMap, context).map((t2) => cloneTensor(t2));\n    case \"Snapshot\":\n      const snapshot = getParamValue(\"x\", node, tensorMap, context);\n      return [cloneTensor(snapshot)];\n    case \"Shape\":\n      return [ops.tensor1d(getParamValue(\"x\", node, tensorMap, context).shape, \"int32\")];\n    case \"ShapeN\":\n      return getParamValue(\"x\", node, tensorMap, context).map((t2) => ops.tensor1d(t2.shape));\n    case \"Size\":\n      return [ops.scalar(getParamValue(\"x\", node, tensorMap, context).size, \"int32\")];\n    case \"Rank\":\n      return [ops.scalar(getParamValue(\"x\", node, tensorMap, context).rank, \"int32\")];\n    case \"NoOp\":\n      return [ops.scalar(1)];\n    case \"Print\":\n      const input2 = getParamValue(\"x\", node, tensorMap, context);\n      const data = getParamValue(\"data\", node, tensorMap, context);\n      const message = getParamValue(\"message\", node, tensorMap, context);\n      const summarize = getParamValue(\"summarize\", node, tensorMap, context);\n      console.warn(\"The graph has a tf.print() operation,usually used for debugging, which slows down performance.\");\n      console.log(message);\n      for (let i2 = 0; i2 < data.length; i2++) {\n        console.log(Array.prototype.slice.call(data[i2].dataSync()).slice(0, summarize));\n      }\n      return [input2];\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/hash_table.js\nvar HashTable = class {\n  constructor(keyDType, valueDType) {\n    this.keyDType = keyDType;\n    this.valueDType = valueDType;\n    this.handle = scalar(0);\n    this.tensorMap = /* @__PURE__ */ new Map();\n    keep(this.handle);\n  }\n  get id() {\n    return this.handle.id;\n  }\n  clearAndClose() {\n    this.tensorMap.forEach((value) => value.dispose());\n    this.tensorMap.clear();\n    this.handle.dispose();\n  }\n  size() {\n    return this.tensorMap.size;\n  }\n  tensorSize() {\n    return scalar(this.size(), \"int32\");\n  }\n  async import(keys, values) {\n    this.checkKeyAndValueTensor(keys, values);\n    const $keys = await keys.data();\n    this.tensorMap.forEach((value) => value.dispose());\n    this.tensorMap.clear();\n    return tidy(() => {\n      const $values = unstack(values);\n      const keysLength = $keys.length;\n      const valuesLength = $values.length;\n      util_exports.assert(keysLength === valuesLength, () => `The number of elements doesn't match, keys has ${keysLength} elements, the values has ${valuesLength} elements.`);\n      for (let i2 = 0; i2 < keysLength; i2++) {\n        const key = $keys[i2];\n        const value = $values[i2];\n        keep(value);\n        this.tensorMap.set(key, value);\n      }\n      return this.handle;\n    });\n  }\n  async find(keys, defaultValue) {\n    this.checkKeyAndValueTensor(keys, defaultValue);\n    const $keys = await keys.data();\n    return tidy(() => {\n      const result = [];\n      for (let i2 = 0; i2 < $keys.length; i2++) {\n        const key = $keys[i2];\n        const value = this.findWithDefault(key, defaultValue);\n        result.push(value);\n      }\n      return stack(result);\n    });\n  }\n  findWithDefault(key, defaultValue) {\n    const result = this.tensorMap.get(key);\n    return result != null ? result : defaultValue;\n  }\n  checkKeyAndValueTensor(key, value) {\n    if (key.dtype !== this.keyDType) {\n      throw new Error(`Expect key dtype ${this.keyDType}, but got ${key.dtype}`);\n    }\n    if (value.dtype !== this.valueDType) {\n      throw new Error(`Expect value dtype ${this.valueDType}, but got ${value.dtype}`);\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/hash_table_executor.js\nvar executeOp9 = async (node, tensorMap, context, resourceManager) => {\n  switch (node.op) {\n    case \"HashTable\":\n    case \"HashTableV2\": {\n      const keyDType = getParamValue(\"keyDType\", node, tensorMap, context);\n      const valueDType = getParamValue(\"valueDType\", node, tensorMap, context);\n      const hashTable = new HashTable(keyDType, valueDType);\n      resourceManager.addHashTable(node.name, hashTable);\n      return [hashTable.handle];\n    }\n    case \"LookupTableImport\":\n    case \"LookupTableImportV2\": {\n      const handle = getParamValue(\"tableHandle\", node, tensorMap, context, resourceManager);\n      const keys = getParamValue(\"keys\", node, tensorMap, context);\n      const values = getParamValue(\"values\", node, tensorMap, context);\n      const hashTable = resourceManager.getHashTableById(handle.id);\n      return [await hashTable.import(keys, values)];\n    }\n    case \"LookupTableFind\":\n    case \"LookupTableFindV2\": {\n      const handle = getParamValue(\"tableHandle\", node, tensorMap, context, resourceManager);\n      const keys = getParamValue(\"keys\", node, tensorMap, context);\n      const defaultValue = getParamValue(\"defaultValue\", node, tensorMap, context);\n      const hashTable = resourceManager.getHashTableById(handle.id);\n      return [await hashTable.find(keys, defaultValue)];\n    }\n    case \"LookupTableSize\":\n    case \"LookupTableSizeV2\": {\n      const handle = getParamValue(\"tableHandle\", node, tensorMap, context, resourceManager);\n      const hashTable = resourceManager.getHashTableById(handle.id);\n      return [hashTable.tensorSize()];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/image_executor.js\nvar executeOp10 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"ResizeBilinear\": {\n      const images = getParamValue(\"images\", node, tensorMap, context);\n      const size = getParamValue(\"size\", node, tensorMap, context);\n      const alignCorners = getParamValue(\"alignCorners\", node, tensorMap, context);\n      const halfPixelCenters = getParamValue(\"halfPixelCenters\", node, tensorMap, context);\n      return [ops.image.resizeBilinear(images, [size[0], size[1]], alignCorners, halfPixelCenters)];\n    }\n    case \"ResizeNearestNeighbor\": {\n      const images = getParamValue(\"images\", node, tensorMap, context);\n      const size = getParamValue(\"size\", node, tensorMap, context);\n      const alignCorners = getParamValue(\"alignCorners\", node, tensorMap, context);\n      const halfPixelCenters = getParamValue(\"halfPixelCenters\", node, tensorMap, context);\n      return [ops.image.resizeNearestNeighbor(images, [size[0], size[1]], alignCorners, halfPixelCenters)];\n    }\n    case \"CropAndResize\": {\n      const image2 = getParamValue(\"image\", node, tensorMap, context);\n      const boxes = getParamValue(\"boxes\", node, tensorMap, context);\n      const boxInd = getParamValue(\"boxInd\", node, tensorMap, context);\n      const cropSize = getParamValue(\"cropSize\", node, tensorMap, context);\n      const method = getParamValue(\"method\", node, tensorMap, context);\n      const extrapolationValue = getParamValue(\"extrapolationValue\", node, tensorMap, context);\n      return [ops.image.cropAndResize(image2, boxes, boxInd, cropSize, method, extrapolationValue)];\n    }\n    case \"ImageProjectiveTransformV3\": {\n      const images = getParamValue(\"images\", node, tensorMap, context);\n      const transforms = getParamValue(\"transforms\", node, tensorMap, context);\n      const outputShape = getParamValue(\"outputShape\", node, tensorMap, context);\n      const fillValue = getParamValue(\"fillValue\", node, tensorMap, context);\n      const interpolation = getParamValue(\"interpolation\", node, tensorMap, context);\n      const fillMode = getParamValue(\"fillMode\", node, tensorMap, context);\n      return [ops.image.transform(images, transforms, interpolation.toLowerCase(), fillMode.toLowerCase(), fillValue, outputShape)];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/logical_executor.js\nvar executeOp11 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"Equal\": {\n      return [ops.equal(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"NotEqual\": {\n      return [ops.notEqual(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"Greater\": {\n      return [ops.greater(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"GreaterEqual\": {\n      return [ops.greaterEqual(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"Less\": {\n      return [ops.less(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"LessEqual\": {\n      return [ops.lessEqual(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"LogicalAnd\": {\n      return [ops.logicalAnd(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"LogicalNot\": {\n      return [ops.logicalNot(getParamValue(\"a\", node, tensorMap, context))];\n    }\n    case \"LogicalOr\": {\n      return [ops.logicalOr(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    case \"Select\":\n    case \"SelectV2\": {\n      return [ops.where(getParamValue(\"condition\", node, tensorMap, context), getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context))];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/matrices_executor.js\nvar executeOp12 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"BatchMatMul\":\n    case \"BatchMatMulV2\":\n    case \"MatMul\":\n      return [ops.matMul(getParamValue(\"a\", node, tensorMap, context), getParamValue(\"b\", node, tensorMap, context), getParamValue(\"transposeA\", node, tensorMap, context), getParamValue(\"transposeB\", node, tensorMap, context))];\n    case \"Einsum\":\n      return [ops.einsum(getParamValue(\"equation\", node, tensorMap, context), ...getParamValue(\"tensors\", node, tensorMap, context))];\n    case \"Transpose\":\n      return [ops.transpose(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"perm\", node, tensorMap, context))];\n    case \"_FusedMatMul\":\n      const [extraOp, activationFunc] = getParamValue(\"fusedOps\", node, tensorMap, context);\n      const isBiasAdd = extraOp === \"biasadd\";\n      const isPrelu = activationFunc === \"prelu\";\n      const numArgs = getParamValue(\"numArgs\", node, tensorMap, context);\n      const leakyreluAlpha = getParamValue(\"leakyreluAlpha\", node, tensorMap, context);\n      if (isBiasAdd) {\n        if (isPrelu && numArgs !== 2) {\n          throw new Error(\"Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.\");\n        }\n        if (!isPrelu && numArgs !== 1) {\n          throw new Error(\"Fused MatMul with BiasAdd must have one extra argument: bias.\");\n        }\n      }\n      const [biasArg, preluArg] = getParamValue(\"args\", node, tensorMap, context);\n      return [ops.fused.matMul({\n        a: getParamValue(\"a\", node, tensorMap, context),\n        b: getParamValue(\"b\", node, tensorMap, context),\n        transposeA: getParamValue(\"transposeA\", node, tensorMap, context),\n        transposeB: getParamValue(\"transposeB\", node, tensorMap, context),\n        bias: biasArg,\n        activation: activationFunc,\n        preluActivationWeights: preluArg,\n        leakyreluAlpha\n      })];\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/normalization_executor.js\nvar executeOp13 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"EuclideanNorm\":\n      return [ops.euclideanNorm(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"axis\", node, tensorMap, context), getParamValue(\"keepDims\", node, tensorMap, context))];\n    case \"FusedBatchNorm\":\n    case \"FusedBatchNormV2\": {\n      return [ops.batchNorm(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"mean\", node, tensorMap, context), getParamValue(\"variance\", node, tensorMap, context), getParamValue(\"offset\", node, tensorMap, context), getParamValue(\"scale\", node, tensorMap, context), getParamValue(\"epsilon\", node, tensorMap, context))];\n    }\n    case \"FusedBatchNormV3\": {\n      return [ops.batchNorm(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"mean\", node, tensorMap, context), getParamValue(\"variance\", node, tensorMap, context), getParamValue(\"offset\", node, tensorMap, context), getParamValue(\"scale\", node, tensorMap, context), getParamValue(\"epsilon\", node, tensorMap, context))];\n    }\n    case \"LRN\": {\n      return [ops.localResponseNormalization(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"radius\", node, tensorMap, context), getParamValue(\"bias\", node, tensorMap, context), getParamValue(\"alpha\", node, tensorMap, context), getParamValue(\"beta\", node, tensorMap, context))];\n    }\n    case \"Softmax\": {\n      return [ops.softmax(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"LogSoftmax\": {\n      return [ops.logSoftmax(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"SparseToDense\": {\n      return [ops.sparseToDense(getParamValue(\"sparseIndices\", node, tensorMap, context), getParamValue(\"outputShape\", node, tensorMap, context), getParamValue(\"sparseValues\", node, tensorMap, context), getParamValue(\"defaultValue\", node, tensorMap, context))];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/reduction_executor.js\nvar executeOp14 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"Max\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const keepDims = getParamValue(\"keepDims\", node, tensorMap, context);\n      return [ops.max(getParamValue(\"x\", node, tensorMap, context), axis, keepDims)];\n    }\n    case \"Mean\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const keepDims = getParamValue(\"keepDims\", node, tensorMap, context);\n      return [ops.mean(getParamValue(\"x\", node, tensorMap, context), axis, keepDims)];\n    }\n    case \"Min\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const keepDims = getParamValue(\"keepDims\", node, tensorMap, context);\n      return [ops.min(getParamValue(\"x\", node, tensorMap, context), axis, keepDims)];\n    }\n    case \"Sum\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const keepDims = getParamValue(\"keepDims\", node, tensorMap, context);\n      return [ops.sum(getParamValue(\"x\", node, tensorMap, context), axis, keepDims)];\n    }\n    case \"All\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const keepDims = getParamValue(\"keepDims\", node, tensorMap, context);\n      return [ops.all(getParamValue(\"x\", node, tensorMap, context), axis, keepDims)];\n    }\n    case \"Any\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const keepDims = getParamValue(\"keepDims\", node, tensorMap, context);\n      return [ops.any(getParamValue(\"x\", node, tensorMap, context), axis, keepDims)];\n    }\n    case \"ArgMax\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      return [ops.argMax(getParamValue(\"x\", node, tensorMap, context), axis)];\n    }\n    case \"ArgMin\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      return [ops.argMin(getParamValue(\"x\", node, tensorMap, context), axis)];\n    }\n    case \"Prod\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const keepDims = getParamValue(\"keepDims\", node, tensorMap, context);\n      return [ops.prod(getParamValue(\"x\", node, tensorMap, context), axis, keepDims)];\n    }\n    case \"Cumprod\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const exclusive = getParamValue(\"exclusive\", node, tensorMap, context);\n      const reverse5 = getParamValue(\"reverse\", node, tensorMap, context);\n      return [ops.cumprod(getParamValue(\"x\", node, tensorMap, context), axis, exclusive, reverse5)];\n    }\n    case \"Cumsum\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const exclusive = getParamValue(\"exclusive\", node, tensorMap, context);\n      const reverse5 = getParamValue(\"reverse\", node, tensorMap, context);\n      return [ops.cumsum(getParamValue(\"x\", node, tensorMap, context), axis, exclusive, reverse5)];\n    }\n    case \"Bincount\":\n      const x = getParamValue(\"x\", node, tensorMap, context);\n      const weights = getParamValue(\"weights\", node, tensorMap, context);\n      const size = getParamValue(\"size\", node, tensorMap, context);\n      return [ops.bincount(x, weights, size)];\n    case \"DenseBincount\": {\n      const x2 = getParamValue(\"x\", node, tensorMap, context);\n      const weights2 = getParamValue(\"weights\", node, tensorMap, context);\n      const size2 = getParamValue(\"size\", node, tensorMap, context);\n      const binaryOutput = getParamValue(\"binaryOutput\", node, tensorMap, context);\n      return [ops.denseBincount(x2, weights2, size2, binaryOutput)];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/slice_join_executor.js\nvar executeOp15 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"ConcatV2\":\n    case \"Concat\": {\n      const n2 = getParamValue(\"n\", node, tensorMap, context);\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      let inputs = getParamValue(\"tensors\", node, tensorMap, context);\n      inputs = inputs.slice(0, n2);\n      return [ops.concat(inputs, axis)];\n    }\n    case \"Gather\": {\n      const input2 = getParamValue(\"x\", node, tensorMap, context);\n      const indices = getParamValue(\"indices\", node, tensorMap, context);\n      return [ops.gather(input2, ops.cast(indices, \"int32\"), 0)];\n    }\n    case \"GatherV2\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const batchDims = getParamValue(\"batchDims\", node, tensorMap, context);\n      const input2 = getParamValue(\"x\", node, tensorMap, context);\n      const indices = getParamValue(\"indices\", node, tensorMap, context);\n      return [ops.gather(input2, ops.cast(indices, \"int32\"), axis, batchDims)];\n    }\n    case \"Reverse\": {\n      const dims = getParamValue(\"dims\", node, tensorMap, context);\n      const axis = [];\n      for (let i2 = 0; i2 < dims.length; i2++) {\n        if (dims[i2]) {\n          axis.push(i2);\n        }\n      }\n      const input2 = getParamValue(\"x\", node, tensorMap, context);\n      return [ops.reverse(input2, axis)];\n    }\n    case \"ReverseV2\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const input2 = getParamValue(\"x\", node, tensorMap, context);\n      return [ops.reverse(input2, axis)];\n    }\n    case \"Slice\": {\n      const begin = getParamValue(\"begin\", node, tensorMap, context);\n      const size = getParamValue(\"size\", node, tensorMap, context);\n      return [ops.slice(getParamValue(\"x\", node, tensorMap, context), begin, size)];\n    }\n    case \"StridedSlice\": {\n      const begin = getParamValue(\"begin\", node, tensorMap, context);\n      const end = getParamValue(\"end\", node, tensorMap, context);\n      const strides = getParamValue(\"strides\", node, tensorMap, context);\n      const beginMask = getParamValue(\"beginMask\", node, tensorMap, context);\n      const endMask = getParamValue(\"endMask\", node, tensorMap, context);\n      const ellipsisMask = getParamValue(\"ellipsisMask\", node, tensorMap, context);\n      const newAxisMask = getParamValue(\"newAxisMask\", node, tensorMap, context);\n      const shrinkAxisMask = getParamValue(\"shrinkAxisMask\", node, tensorMap, context);\n      const tensor2 = getParamValue(\"x\", node, tensorMap, context);\n      return [ops.stridedSlice(tensor2, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask)];\n    }\n    case \"Pack\": {\n      return tidy(() => {\n        const axis = getParamValue(\"axis\", node, tensorMap, context);\n        const tensors = getParamValue(\"tensors\", node, tensorMap, context);\n        const shape = tensors[0].shape;\n        const squeezedShape = ops.squeeze(tensors[0]).shape;\n        const mapped = tensors.map((tensor2) => {\n          const sameShape = util_exports.arraysEqual(tensor2.shape, shape);\n          if (!sameShape && !util_exports.arraysEqual(ops.squeeze(tensor2).shape, squeezedShape)) {\n            throw new Error(\"the input tensors shape does not match\");\n          }\n          return sameShape ? tensor2 : ops.reshape(tensor2, shape);\n        });\n        return [ops.stack(mapped, axis)];\n      });\n    }\n    case \"Unpack\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const tensor2 = getParamValue(\"tensor\", node, tensorMap, context);\n      return ops.unstack(tensor2, axis);\n    }\n    case \"Tile\": {\n      const reps = getParamValue(\"reps\", node, tensorMap, context);\n      return [ops.tile(getParamValue(\"x\", node, tensorMap, context), reps)];\n    }\n    case \"Split\":\n    case \"SplitV\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      const numOrSizeSplits = getParamValue(\"numOrSizeSplits\", node, tensorMap, context);\n      const tensor2 = getParamValue(\"x\", node, tensorMap, context);\n      return ops.split(tensor2, numOrSizeSplits, axis);\n    }\n    case \"ScatterNd\": {\n      const indices = getParamValue(\"indices\", node, tensorMap, context);\n      const values = getParamValue(\"values\", node, tensorMap, context);\n      const shape = getParamValue(\"shape\", node, tensorMap, context);\n      return [ops.scatterND(indices, values, shape)];\n    }\n    case \"GatherNd\": {\n      const x = getParamValue(\"x\", node, tensorMap, context);\n      const indices = getParamValue(\"indices\", node, tensorMap, context);\n      return [ops.gatherND(x, indices)];\n    }\n    case \"SparseToDense\": {\n      const indices = getParamValue(\"sparseIndices\", node, tensorMap, context);\n      const shape = getParamValue(\"outputShape\", node, tensorMap, context);\n      const sparseValues = getParamValue(\"sparseValues\", node, tensorMap, context);\n      const defaultValue = getParamValue(\"defaultValue\", node, tensorMap, context);\n      return [ops.sparseToDense(indices, sparseValues, shape, sparseValues.dtype === defaultValue.dtype ? defaultValue : ops.cast(defaultValue, sparseValues.dtype))];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/sparse_executor.js\nvar executeOp16 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"SparseFillEmptyRows\": {\n      const { outputIndices, outputValues, emptyRowIndicator, reverseIndexMap } = ops.sparse.sparseFillEmptyRows(getParamValue(\"indices\", node, tensorMap, context), getParamValue(\"values\", node, tensorMap, context), getParamValue(\"denseShape\", node, tensorMap, context), getParamValue(\"defaultValue\", node, tensorMap, context));\n      return [\n        outputIndices,\n        outputValues,\n        emptyRowIndicator,\n        reverseIndexMap\n      ];\n    }\n    case \"SparseReshape\": {\n      const { outputIndices, outputShape } = ops.sparse.sparseReshape(getParamValue(\"inputIndices\", node, tensorMap, context), getParamValue(\"inputShape\", node, tensorMap, context), getParamValue(\"newShape\", node, tensorMap, context));\n      return [outputIndices, outputShape];\n    }\n    case \"SparseSegmentMean\": {\n      const outputData = ops.sparse.sparseSegmentMean(getParamValue(\"data\", node, tensorMap, context), getParamValue(\"indices\", node, tensorMap, context), getParamValue(\"segmentIds\", node, tensorMap, context));\n      return [outputData];\n    }\n    case \"SparseSegmentSum\": {\n      const outputData = ops.sparse.sparseSegmentSum(getParamValue(\"data\", node, tensorMap, context), getParamValue(\"indices\", node, tensorMap, context), getParamValue(\"segmentIds\", node, tensorMap, context));\n      return [outputData];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/spectral_executor.js\nvar executeOp17 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"FFT\": {\n      return [ops.fft(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"IFFT\": {\n      return [ops.ifft(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"RFFT\": {\n      return [ops.rfft(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    case \"IRFFT\": {\n      return [ops.irfft(getParamValue(\"x\", node, tensorMap, context))];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/string_executor.js\nvar executeOp18 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"StringNGrams\": {\n      const { nGrams, nGramsSplits } = ops.string.stringNGrams(getParamValue(\"data\", node, tensorMap, context), getParamValue(\"dataSplits\", node, tensorMap, context), getParamValue(\"separator\", node, tensorMap, context), getParamValue(\"nGramWidths\", node, tensorMap, context), getParamValue(\"leftPad\", node, tensorMap, context), getParamValue(\"rightPad\", node, tensorMap, context), getParamValue(\"padWidth\", node, tensorMap, context), getParamValue(\"preserveShortSequences\", node, tensorMap, context));\n      return [nGrams, nGramsSplits];\n    }\n    case \"StringSplit\": {\n      const { indices, values, shape } = ops.string.stringSplit(getParamValue(\"input\", node, tensorMap, context), getParamValue(\"delimiter\", node, tensorMap, context), getParamValue(\"skipEmpty\", node, tensorMap, context));\n      return [indices, values, shape];\n    }\n    case \"StringToHashBucketFast\": {\n      const output = ops.string.stringToHashBucketFast(getParamValue(\"input\", node, tensorMap, context), getParamValue(\"numBuckets\", node, tensorMap, context));\n      return [output];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/executors/transformation_executor.js\nvar executeOp19 = (node, tensorMap, context, ops = ops_for_converter_exports) => {\n  switch (node.op) {\n    case \"Cast\": {\n      return [ops.cast(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"dtype\", node, tensorMap, context))];\n    }\n    case \"ExpandDims\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      return [ops.expandDims(getParamValue(\"x\", node, tensorMap, context), axis)];\n    }\n    case \"Squeeze\": {\n      const axis = getParamValue(\"axis\", node, tensorMap, context);\n      return [ops.squeeze(getParamValue(\"x\", node, tensorMap, context), axis)];\n    }\n    case \"Reshape\": {\n      return [ops.reshape(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"shape\", node, tensorMap, context))];\n    }\n    case \"MirrorPad\": {\n      return [ops.mirrorPad(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"padding\", node, tensorMap, context), getParamValue(\"mode\", node, tensorMap, context))];\n    }\n    case \"PadV2\":\n    case \"Pad\": {\n      return [ops.pad(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"padding\", node, tensorMap, context), getParamValue(\"constantValue\", node, tensorMap, context))];\n    }\n    case \"SpaceToBatchND\": {\n      const blockShape = getParamValue(\"blockShape\", node, tensorMap, context);\n      const paddings = getParamValue(\"paddings\", node, tensorMap, context);\n      return [ops.spaceToBatchND(getParamValue(\"x\", node, tensorMap, context), blockShape, paddings)];\n    }\n    case \"BatchToSpaceND\": {\n      const blockShape = getParamValue(\"blockShape\", node, tensorMap, context);\n      const crops = getParamValue(\"crops\", node, tensorMap, context);\n      return [ops.batchToSpaceND(getParamValue(\"x\", node, tensorMap, context), blockShape, crops)];\n    }\n    case \"DepthToSpace\": {\n      const blockSize = getParamValue(\"blockSize\", node, tensorMap, context);\n      const dataFormat = getParamValue(\"dataFormat\", node, tensorMap, context).toUpperCase();\n      return [ops.depthToSpace(getParamValue(\"x\", node, tensorMap, context), blockSize, dataFormat)];\n    }\n    case \"BroadcastTo\": {\n      return [ops.broadcastTo(getParamValue(\"x\", node, tensorMap, context), getParamValue(\"shape\", node, tensorMap, context))];\n    }\n    case \"BroadcastArgs\": {\n      return [ops.broadcastArgs(getParamValue(\"s0\", node, tensorMap, context), getParamValue(\"s1\", node, tensorMap, context))];\n    }\n    default:\n      throw TypeError(`Node type ${node.op} is not implemented`);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/operations/operation_executor.js\nfunction executeOp20(node, tensorMap, context, resourceManager, tidy2 = tidy) {\n  const value = ((node2, tensorMap2, context2) => {\n    switch (node2.category) {\n      case \"arithmetic\":\n        return tidy2(() => executeOp(node2, tensorMap2, context2));\n      case \"basic_math\":\n        return tidy2(() => executeOp2(node2, tensorMap2, context2));\n      case \"control\":\n        return executeOp3(node2, tensorMap2, context2);\n      case \"convolution\":\n        return tidy2(() => executeOp4(node2, tensorMap2, context2));\n      case \"creation\":\n        return tidy2(() => executeOp5(node2, tensorMap2, context2));\n      case \"dynamic\":\n        return executeOp6(node2, tensorMap2, context2);\n      case \"evaluation\":\n        return tidy2(() => executeOp7(node2, tensorMap2, context2));\n      case \"image\":\n        return tidy2(() => executeOp10(node2, tensorMap2, context2));\n      case \"graph\":\n        return tidy2(() => executeOp8(node2, tensorMap2, context2));\n      case \"logical\":\n        return tidy2(() => executeOp11(node2, tensorMap2, context2));\n      case \"matrices\":\n        return tidy2(() => executeOp12(node2, tensorMap2, context2));\n      case \"normalization\":\n        return tidy2(() => executeOp13(node2, tensorMap2, context2));\n      case \"reduction\":\n        return tidy2(() => executeOp14(node2, tensorMap2, context2));\n      case \"slice_join\":\n        return tidy2(() => executeOp15(node2, tensorMap2, context2));\n      case \"sparse\":\n        return tidy2(() => executeOp16(node2, tensorMap2, context2));\n      case \"spectral\":\n        return tidy2(() => executeOp17(node2, tensorMap2, context2));\n      case \"string\":\n        return tidy2(() => executeOp18(node2, tensorMap2, context2));\n      case \"transformation\":\n        return tidy2(() => executeOp19(node2, tensorMap2, context2));\n      case \"hash_table\":\n        return executeOp9(node2, tensorMap2, context2, resourceManager);\n      case \"custom\":\n        const opMapper = getRegisteredOp(node2.op);\n        if (opMapper && opMapper.customExecutor) {\n          return opMapper.customExecutor(new NodeValueImpl(node2, tensorMap2, context2));\n        } else {\n          throw TypeError(`Custom op ${node2.op} is not registered.`);\n        }\n      default:\n        throw TypeError(`Unknown op '${node2.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`);\n    }\n  })(node, tensorMap, context);\n  if (util_exports.isPromise(value)) {\n    return value.then((data) => [].concat(data));\n  }\n  return [].concat(value);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/execution_context.js\nvar ExecutionContext = class {\n  constructor(weightMap = {}, tensorArrayMap = {}, tensorListMap = {}, functionMap = {}) {\n    this.weightMap = weightMap;\n    this.tensorArrayMap = tensorArrayMap;\n    this.tensorListMap = tensorListMap;\n    this.functionMap = functionMap;\n    this.rootContext = { id: 0, frameName: \"\", iterationId: 0 };\n    this.contexts = [this.rootContext];\n    this.lastId = 0;\n    this.generateCurrentContextIds();\n  }\n  newFrame(id, frameName) {\n    return { id, frameName, iterationId: 0 };\n  }\n  set currentContext(contexts2) {\n    if (this.contexts !== contexts2) {\n      this.contexts = contexts2;\n      this.generateCurrentContextIds();\n    }\n  }\n  get currentContext() {\n    return this.contexts;\n  }\n  get currentContextId() {\n    return this._currentContextIds[0];\n  }\n  get currentContextIds() {\n    return this._currentContextIds;\n  }\n  generateCurrentContextIds() {\n    const names = [];\n    for (let i2 = 0; i2 < this.contexts.length - 1; i2++) {\n      const contexts2 = this.contexts.slice(0, this.contexts.length - i2);\n      names.push(this.contextIdforContexts(contexts2));\n    }\n    names.push(\"\");\n    this._currentContextIds = names;\n  }\n  contextIdforContexts(contexts2) {\n    return contexts2 ? contexts2.map((context) => context.id === 0 && context.iterationId === 0 ? \"\" : `${context.frameName}-${context.iterationId}`).join(\"/\") : \"\";\n  }\n  enterFrame(frameId) {\n    if (this.contexts) {\n      this.lastId++;\n      this.contexts = this.contexts.slice();\n      this.contexts.push(this.newFrame(this.lastId, frameId));\n      this._currentContextIds.unshift(this.contextIdforContexts(this.contexts));\n    }\n  }\n  exitFrame() {\n    if (this.contexts && this.contexts.length > 1) {\n      this.contexts = this.contexts.slice();\n      this.contexts.splice(-1);\n      this.currentContextIds.shift();\n    } else {\n      throw new Error(\"Cannot exit frame, the context is empty\");\n    }\n  }\n  nextIteration() {\n    if (this.contexts && this.contexts.length > 0) {\n      this.contexts = this.contexts.slice();\n      this.lastId++;\n      const context = Object.assign({}, this.contexts[this.contexts.length - 1]);\n      context.iterationId += 1;\n      context.id = this.lastId;\n      this.contexts.splice(-1, 1, context);\n      this._currentContextIds.splice(0, 1, this.contextIdforContexts(this.contexts));\n    } else {\n      throw new Error(\"Cannot increase frame iteration, the context is empty\");\n    }\n  }\n  getWeight(name) {\n    return this.weightMap[name];\n  }\n  addTensorArray(tensorArray) {\n    this.tensorArrayMap[tensorArray.id] = tensorArray;\n  }\n  getTensorArray(id) {\n    return this.tensorArrayMap[id];\n  }\n  addTensorList(tensorList) {\n    this.tensorListMap[tensorList.id] = tensorList;\n  }\n  getTensorList(id) {\n    return this.tensorListMap[id];\n  }\n  dispose(keepIds) {\n    for (const key in this.tensorArrayMap) {\n      this.tensorArrayMap[key].clearAndClose(keepIds);\n    }\n    for (const key in this.tensorListMap) {\n      this.tensorListMap[key].clearAndClose(keepIds);\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/model_analysis.js\nfunction getExecutionSubgraph(inputs, outputs, weightMap, initNodes) {\n  const usedNodes = /* @__PURE__ */ new Set();\n  const missingInputs = [];\n  let dynamicNode = null;\n  let syncInputs = null;\n  const seen = /* @__PURE__ */ new Set();\n  const inputNodeNames = Object.keys(inputs).map((name) => parseNodeName(name)[0]);\n  let initNodeNames = [];\n  if (initNodes != null) {\n    initNodeNames = initNodes.map((node) => parseNodeName(node.name)[0]);\n  }\n  const frontier = [...outputs];\n  while (frontier.length > 0) {\n    const node = frontier.pop();\n    if (isControlFlow(node) || isDynamicShape(node) || isHashTable(node)) {\n      if (dynamicNode == null) {\n        dynamicNode = node;\n        syncInputs = dynamicNode.children.map((child) => child.name).filter((name) => usedNodes.has(name));\n      }\n    }\n    usedNodes.add(node.name);\n    if (weightMap[node.name] != null) {\n      continue;\n    }\n    if (inputNodeNames.indexOf(node.name) !== -1) {\n      continue;\n    }\n    if (initNodeNames.indexOf(node.name) !== -1) {\n      continue;\n    }\n    if (node.inputs.length === 0) {\n      missingInputs.push(node.name);\n      continue;\n    }\n    node.inputs.forEach((input2) => {\n      if (seen.has(input2.name)) {\n        return;\n      }\n      seen.add(input2.name);\n      frontier.push(input2);\n    });\n  }\n  return { inputs, outputs, usedNodes, missingInputs, dynamicNode, syncInputs };\n}\nfunction getNodesInTopologicalOrder(graph, weightMap, executionInfo) {\n  const { usedNodes, inputs } = executionInfo;\n  const frontier = [];\n  const inputNodes = Object.keys(inputs).map((name) => parseNodeName(name)[0]).map((name) => graph.nodes[name]);\n  const initNodes = graph.initNodes;\n  inputNodes.forEach((input2) => {\n    if (usedNodes.has(input2.name)) {\n      frontier.push(input2);\n    }\n  });\n  graph.weights.forEach((weight) => {\n    if (usedNodes.has(weight.name)) {\n      frontier.push(weight);\n    }\n  });\n  if (initNodes != null) {\n    initNodes.forEach((node) => {\n      if (usedNodes.has(node.name)) {\n        frontier.push(node);\n      }\n    });\n  }\n  const seen = /* @__PURE__ */ new Set();\n  const orderedNodes = [];\n  while (frontier.length > 0) {\n    const node = frontier.pop();\n    seen.add(node.name);\n    if (!weightMap[node.name]) {\n      orderedNodes.push(node);\n    }\n    node.children.forEach((child) => {\n      if (!seen.has(child.name) && usedNodes.has(child.name) && child.inputs.every((input2) => seen.has(input2.name))) {\n        frontier.push(child);\n      }\n    });\n  }\n  return orderedNodes;\n}\nvar CONTROL_FLOW_OPS = [\n  \"Switch\",\n  \"Merge\",\n  \"Enter\",\n  \"Exit\",\n  \"NextIteration\",\n  \"StatelessIf\",\n  \"StatelessWhile\",\n  \"if\",\n  \"While\"\n];\nvar DYNAMIC_SHAPE_OPS = [\n  \"NonMaxSuppressionV2\",\n  \"NonMaxSuppressionV3\",\n  \"NonMaxSuppressionV5\",\n  \"Where\"\n];\nvar HASH_TABLE_OPS = [\n  \"HashTable\",\n  \"HashTableV2\",\n  \"LookupTableImport\",\n  \"LookupTableImportV2\",\n  \"LookupTableFind\",\n  \"LookupTableFindV2\",\n  \"LookupTableSize\",\n  \"LookupTableSizeV2\"\n];\nfunction isControlFlow(node) {\n  return CONTROL_FLOW_OPS.indexOf(node.op) >= 0;\n}\nfunction isDynamicShape(node) {\n  return DYNAMIC_SHAPE_OPS.indexOf(node.op) >= 0;\n}\nfunction isHashTable(node) {\n  return HASH_TABLE_OPS.indexOf(node.op) >= 0;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/graph_executor.js\nvar GraphExecutor = class {\n  constructor(graph, parent) {\n    this.graph = graph;\n    this.parent = parent;\n    this.compiledMap = /* @__PURE__ */ new Map();\n    this._weightMap = {};\n    this.SEPERATOR = \",\";\n    this._functions = {};\n    this._functionExecutorMap = {};\n    this.intermediateTensors = {};\n    this.keepTensorForDebug = false;\n    this._outputs = graph.outputs;\n    this._inputs = graph.inputs;\n    this._initNodes = graph.initNodes;\n    this._signature = graph.signature;\n    this._functions = graph.functions;\n    if (graph.functions != null) {\n      Object.keys(graph.functions).forEach((name) => {\n        this._functionExecutorMap[name] = new GraphExecutor(graph.functions[name], this);\n      });\n    }\n  }\n  get weightIds() {\n    return this.parent ? this.parent.weightIds : this._weightIds;\n  }\n  get functionExecutorMap() {\n    return this.parent ? this.parent.functionExecutorMap : this._functionExecutorMap;\n  }\n  get weightMap() {\n    return this.parent ? this.parent.weightMap : this._weightMap;\n  }\n  set weightMap(weightMap) {\n    const weightIds = Object.keys(weightMap).map((key) => weightMap[key].map((tensor2) => tensor2.id));\n    this._weightIds = [].concat(...weightIds);\n    this._weightMap = weightMap;\n  }\n  set resourceManager(resourceManager) {\n    this._resourceManager = resourceManager;\n  }\n  get inputs() {\n    return this._inputs.map((node) => {\n      return {\n        name: node.name,\n        shape: node.attrParams[\"shape\"] ? node.attrParams[\"shape\"].value : void 0,\n        dtype: node.attrParams[\"dtype\"] ? node.attrParams[\"dtype\"].value : void 0\n      };\n    });\n  }\n  get outputs() {\n    return this._outputs.map((node) => {\n      return {\n        name: node.name,\n        shape: node.attrParams[\"shape\"] ? node.attrParams[\"shape\"].value : void 0,\n        dtype: node.attrParams[\"dtype\"] ? node.attrParams[\"dtype\"].value : void 0\n      };\n    });\n  }\n  get inputNodes() {\n    return this._inputs.map((node) => node.signatureKey || node.name);\n  }\n  get outputNodes() {\n    return this._outputs.map((node) => {\n      const name = node.signatureKey || node.name;\n      return node.defaultOutput ? `${name}:${node.defaultOutput}` : name;\n    });\n  }\n  get functions() {\n    return Object.keys(this._functions).reduce((map, key) => {\n      map[key] = this._functions[key].signature;\n      return map;\n    }, {});\n  }\n  getCompilationKey(inputs, outputs) {\n    const sortedInputs = inputs.map((node) => node.name).sort();\n    const sortedOutputs = outputs.map((node) => node.name).sort();\n    return sortedInputs.join(this.SEPERATOR) + \"--\" + sortedOutputs.join(this.SEPERATOR);\n  }\n  compile(inputs, outputs) {\n    const executionInfo = getExecutionSubgraph(inputs, outputs, this.weightMap, this._initNodes);\n    const { missingInputs, dynamicNode, syncInputs } = executionInfo;\n    if (dynamicNode != null) {\n      throw new Error(`This execution contains the node '${dynamicNode.name}', which has the dynamic op '${dynamicNode.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${syncInputs}]`);\n    }\n    if (missingInputs.length > 0) {\n      const outNames = outputs.map((n2) => n2.name);\n      const inNames = Object.keys(inputs);\n      throw new Error(`Cannot compute the outputs [${outNames}] from the provided inputs [${inNames}]. Missing the following inputs: [${missingInputs}]`);\n    }\n    return getNodesInTopologicalOrder(this.graph, this.weightMap, executionInfo);\n  }\n  execute(inputs, outputs) {\n    inputs = this.mapInputs(inputs);\n    const names = Object.keys(inputs).sort();\n    this.checkInputs(inputs);\n    this.checkInputShapeAndType(inputs);\n    outputs = this.mapOutputs(outputs);\n    this.checkOutputs(outputs);\n    const inputNodes = names.map((name) => this.graph.nodes[parseNodeName(name)[0]]);\n    const outputNodeNames = outputs.map((name) => parseNodeName(name)[0]);\n    let outputNodes = outputNodeNames.map((name) => this.graph.nodes[name]);\n    this.resetIntermediateTensors();\n    if (outputNodes.length === 0) {\n      outputNodes = this._outputs;\n    }\n    const compilationKey = this.getCompilationKey(inputNodes, outputNodes);\n    let orderedNodes = this.compiledMap.get(compilationKey);\n    if (orderedNodes == null) {\n      orderedNodes = this.compile(inputs, outputNodes);\n      this.compiledMap.set(compilationKey, orderedNodes);\n    }\n    const tensorArrayMap = {};\n    const tensorListMap = {};\n    return tidy(() => {\n      const context = new ExecutionContext(this.weightMap, tensorArrayMap, tensorListMap, this.functionExecutorMap);\n      const tensorsMap = Object.assign({}, this.weightMap);\n      Object.keys(inputs).forEach((name) => {\n        const [nodeName, index] = parseNodeName(name);\n        const tensors = [];\n        tensors[index] = inputs[name];\n        tensorsMap[nodeName] = tensors;\n      });\n      const tensorsToKeep = this.getFrozenTensorIds(tensorsMap);\n      const intermediateTensorConsumerCount = {};\n      for (let i2 = 0; i2 < orderedNodes.length; i2++) {\n        const node = orderedNodes[i2];\n        if (!tensorsMap[node.name]) {\n          const tensors = executeOp20(node, tensorsMap, context, this._resourceManager);\n          if (util_exports.isPromise(tensors)) {\n            throw new Error(`The execution of the op '${node.op}' returned a promise. Please use model.executeAsync() instead.`);\n          }\n          tensorsMap[node.name] = tensors;\n          this.checkTensorForDisposal(node.name, node, tensorsMap, context, tensorsToKeep, outputNodeNames, intermediateTensorConsumerCount);\n        }\n      }\n      if (this.parent == null) {\n        context.dispose(tensorsToKeep);\n      }\n      return outputs.map((name) => getTensor(name, tensorsMap, context));\n    });\n  }\n  getFrozenTensorIds(tensorMap) {\n    const ids = [].concat.apply([], Object.keys(tensorMap).map((key) => tensorMap[key]).map((tensors) => tensors.map((tensor2) => tensor2.id)));\n    return new Set(ids);\n  }\n  checkTensorForDisposal(nodeName, node, tensorMap, context, tensorsToKeep, outputNames, intermediateTensorConsumerCount) {\n    if (node.category === \"control\" || outputNames.indexOf(nodeName) !== -1) {\n      return;\n    }\n    tensorMap[nodeName].forEach((tensor2) => {\n      if (tensor2 != null) {\n        intermediateTensorConsumerCount[tensor2.id] = (intermediateTensorConsumerCount[tensor2.id] || 0) + node.children.length;\n      }\n    });\n    node.inputs.forEach((input2) => {\n      if (input2.category !== \"control\") {\n        const tensors = getTensorsForCurrentContenxt(input2.name, tensorMap, context);\n        if (tensors != null) {\n          tensors.forEach((tensor2) => {\n            if (tensor2 && !tensor2.kept && !tensorsToKeep.has(tensor2.id)) {\n              const count2 = intermediateTensorConsumerCount[tensor2.id];\n              if (count2 === 1) {\n                if (!this.keepTensorForDebug) {\n                  tensor2.dispose();\n                } else {\n                  const [nodeName2, index] = getNodeNameAndIndex(node.name, context);\n                  if (this.intermediateTensors[nodeName2]) {\n                    this.intermediateTensors[nodeName2][index] = tensor2;\n                  } else {\n                    this.intermediateTensors[nodeName2] = [];\n                    this.intermediateTensors[nodeName2][index] = tensor2;\n                  }\n                }\n                delete intermediateTensorConsumerCount[tensor2.id];\n              } else if (count2 != null) {\n                intermediateTensorConsumerCount[tensor2.id]--;\n              }\n            }\n          });\n        }\n      }\n    });\n  }\n  async executeAsync(inputs, outputs) {\n    return this._executeAsync(inputs, outputs);\n  }\n  disposeIntermediateTensors() {\n    if (!this.intermediateTensors) {\n      return;\n    }\n    Object.keys(this.intermediateTensors).forEach((key) => this.intermediateTensors[key].forEach((tensor2) => tensor2.dispose()));\n    this.disposeTensorsMap();\n  }\n  disposeTensorsMap() {\n    if (!this.tensorsMap) {\n      return;\n    }\n    Object.keys(this.tensorsMap).forEach((key) => {\n      const tensorArray = this.tensorsMap[key];\n      tensorArray.forEach((tensor2) => {\n        if (tensor2 && !tensor2.kept && !tensor2.isDisposed && !this.keepIds.has(tensor2.id)) {\n          tensor2.dispose();\n        }\n      });\n    });\n  }\n  getIntermediateTensors() {\n    return this.tensorsMap;\n  }\n  resetIntermediateTensors() {\n    for (const key in this.intermediateTensors) {\n      this.intermediateTensors[key].forEach((tensor2) => tensor2.dispose());\n      delete this.intermediateTensors[key];\n    }\n  }\n  async _executeAsync(inputs, outputs, isFunctionExecution = false, tensorArrayMap = {}, tensorListMap = {}) {\n    if (!isFunctionExecution) {\n      inputs = this.mapInputs(inputs);\n      this.checkInputs(inputs);\n      this.checkInputShapeAndType(inputs);\n      outputs = this.mapOutputs(outputs);\n      this.checkOutputs(outputs);\n    }\n    try {\n      this.keepTensorForDebug = env().getBool(\"KEEP_INTERMEDIATE_TENSORS\");\n    } catch (e2) {\n      console.warn(e2.message);\n    }\n    this.resetIntermediateTensors();\n    const context = new ExecutionContext(this.weightMap, tensorArrayMap, tensorListMap, this.functionExecutorMap);\n    this.tensorsMap = await this.executeWithControlFlow(inputs, context, outputs, isFunctionExecution);\n    const results = outputs.map((name) => getTensor(name, this.tensorsMap, context));\n    const outputIds = results.map((t2) => t2.id);\n    const inputIds = Object.keys(inputs).map((name) => inputs[name].id);\n    this.keepIds = /* @__PURE__ */ new Set([...outputIds, ...inputIds, ...this.weightIds]);\n    if (!this.keepTensorForDebug) {\n      this.disposeTensorsMap();\n    }\n    if (this.parent == null) {\n      context.dispose(this.keepIds);\n    }\n    return results;\n  }\n  async executeFunctionAsync(inputs, tensorArrayMap, tensorListMap) {\n    const mappedInputs = inputs.reduce((map, tensor2, index) => {\n      map[this.inputs[index].name] = tensor2;\n      return map;\n    }, {});\n    return this._executeAsync(mappedInputs, this.outputNodes, true, tensorArrayMap, tensorListMap);\n  }\n  async executeWithControlFlow(inputs, context, outputNames, isFunctionExecution) {\n    const names = Object.keys(inputs);\n    const inputNodes = names.map((name) => this.graph.nodes[parseNodeName(name)[0]]);\n    const outputNodeNames = outputNames.map((name) => parseNodeName(name)[0]);\n    let outputNodes = outputNodeNames.map((name) => this.graph.nodes[name]);\n    if (outputNodes.length === 0) {\n      outputNodes = this._outputs;\n    }\n    const { usedNodes, missingInputs, dynamicNode, syncInputs } = getExecutionSubgraph(inputs, outputNodes, this.weightMap, this._initNodes);\n    const stack2 = [\n      ...inputNodes,\n      ...this.graph.weights,\n      ...this._initNodes || []\n    ].map((node) => {\n      return { node, contexts: context.currentContext };\n    });\n    const tensorsMap = Object.assign({}, this.weightMap);\n    Object.keys(inputs).forEach((name) => {\n      const [nodeName, index] = parseNodeName(name);\n      const tensors = [];\n      tensors[index] = inputs[name];\n      tensorsMap[nodeName] = tensors;\n    });\n    const intermediateTensorConsumerCount = {};\n    const tensorsToKeep = this.getFrozenTensorIds(tensorsMap);\n    const added = {};\n    while (stack2.length > 0) {\n      const promises = this.processStack(inputNodes, stack2, context, tensorsMap, added, tensorsToKeep, outputNodeNames, intermediateTensorConsumerCount, usedNodes);\n      await Promise.all(promises);\n    }\n    if (dynamicNode == null && !isFunctionExecution) {\n      console.warn(`This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.`);\n    }\n    const missingOutputs = outputNodes.filter((node) => !isControlFlow(node) && !getTensor(node.name, tensorsMap, context)).map((node) => node.name);\n    if (missingOutputs.length > 0) {\n      let alternativeMsg = \"\";\n      if (dynamicNode != null) {\n        alternativeMsg = `Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${syncInputs}]`;\n      }\n      throw new Error(`Cannot compute the outputs [${missingOutputs}] from the provided inputs [${names}]. Consider providing the following inputs: [${missingInputs}]. ${alternativeMsg}`);\n    }\n    return tensorsMap;\n  }\n  processStack(inputNodes, stack2, context, tensorMap, added, tensorsToKeep, outputNames, intermediateTensorConsumerCount, usedNodes) {\n    const promises = [];\n    while (stack2.length > 0) {\n      const item = stack2.pop();\n      context.currentContext = item.contexts;\n      let nodeName = \"\";\n      if (item.node.op === \"Enter\" && getParamValue(\"isConstant\", item.node, tensorMap, context)) {\n        [nodeName] = getNodeNameAndIndex(item.node.name, context);\n      }\n      if (tensorMap[item.node.name] == null) {\n        const tensors = executeOp20(item.node, tensorMap, context, this._resourceManager);\n        if (!nodeName) {\n          [nodeName] = getNodeNameAndIndex(item.node.name, context);\n        }\n        const currentContext = context.currentContext;\n        if (util_exports.isPromise(tensors)) {\n          promises.push(tensors.then((t2) => {\n            tensorMap[nodeName] = t2;\n            context.currentContext = currentContext;\n            this.checkTensorForDisposal(nodeName, item.node, tensorMap, context, tensorsToKeep, outputNames, intermediateTensorConsumerCount);\n            this.processChildNodes(item.node, stack2, context, tensorMap, added, usedNodes);\n            return t2;\n          }));\n        } else {\n          tensorMap[nodeName] = tensors;\n          this.checkTensorForDisposal(nodeName, item.node, tensorMap, context, tensorsToKeep, outputNames, intermediateTensorConsumerCount);\n          this.processChildNodes(item.node, stack2, context, tensorMap, added, usedNodes);\n        }\n      } else {\n        this.processChildNodes(item.node, stack2, context, tensorMap, added, usedNodes);\n      }\n    }\n    return promises;\n  }\n  processChildNodes(node, stack2, context, tensorMap, added, usedNodes) {\n    node.children.forEach((childNode) => {\n      const [nodeName] = getNodeNameAndIndex(childNode.name, context);\n      if (added[nodeName] || !usedNodes.has(childNode.name)) {\n        return;\n      }\n      if (childNode.op === \"Merge\") {\n        if (childNode.inputNames.some((name) => {\n          return !!getTensor(name, tensorMap, context);\n        })) {\n          added[nodeName] = true;\n          stack2.push({ contexts: context.currentContext, node: childNode });\n        }\n      } else if (childNode.inputNames.every((name) => {\n        return !!getTensor(name, tensorMap, context);\n      })) {\n        added[nodeName] = true;\n        stack2.push({ contexts: context.currentContext, node: childNode });\n      }\n    });\n  }\n  dispose() {\n    Object.keys(this.weightMap).forEach((key) => this.weightMap[key].forEach((tensor2) => tensor2.dispose()));\n  }\n  checkInputShapeAndType(inputs) {\n    Object.keys(inputs).forEach((name) => {\n      const input2 = inputs[name];\n      const [nodeName] = parseNodeName(name);\n      const node = this.graph.nodes[nodeName];\n      if (node.attrParams[\"shape\"] && node.attrParams[\"shape\"].value) {\n        const shape = node.attrParams[\"shape\"].value;\n        const match = shape.length === input2.shape.length && input2.shape.every((dim, index) => shape[index] === -1 || shape[index] === dim);\n        util_exports.assert(match, () => `The shape of dict['${node.name}'] provided in model.execute(dict) must be [${shape}], but was [${input2.shape}]`);\n      }\n      if (node.attrParams[\"dtype\"] && node.attrParams[\"dtype\"].value) {\n        util_exports.assert(input2.dtype === node.attrParams[\"dtype\"].value, () => `The dtype of dict['${node.name}'] provided in model.execute(dict) must be ${node.attrParams[\"dtype\"].value}, but was ${input2.dtype}`);\n      }\n    });\n  }\n  mapInputs(inputs) {\n    const result = {};\n    for (const inputName in inputs) {\n      if (this._signature != null && this._signature.inputs != null && this._signature.inputs[inputName] != null) {\n        const tensor2 = this._signature.inputs[inputName];\n        result[tensor2.name] = inputs[inputName];\n      } else {\n        result[inputName] = inputs[inputName];\n      }\n    }\n    return result;\n  }\n  checkInputs(inputs) {\n    const notInGraph = Object.keys(inputs).filter((name) => {\n      const [nodeName] = parseNodeName(name);\n      return this.graph.nodes[nodeName] == null;\n    });\n    if (notInGraph.length > 0) {\n      throw new Error(`The dict provided in model.execute(dict) has keys: [${notInGraph}] that are not part of graph`);\n    }\n  }\n  mapOutputs(outputs) {\n    return outputs.map((name) => {\n      if (this._signature != null && this._signature.outputs != null && this._signature.outputs[name] != null) {\n        const tensor2 = this._signature.outputs[name];\n        return tensor2.name;\n      }\n      return name;\n    }, {});\n  }\n  checkOutputs(outputs) {\n    outputs.forEach((name) => {\n      const [normalizedName] = parseNodeName(name);\n      if (!this.graph.nodes[normalizedName]) {\n        throw new Error(`The output '${name}' is not found in the graph`);\n      }\n    });\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/resource_manager.js\nvar ResourceManager = class {\n  constructor(hashTableNameToHandle = {}, hashTableMap = {}) {\n    this.hashTableNameToHandle = hashTableNameToHandle;\n    this.hashTableMap = hashTableMap;\n  }\n  addHashTable(name, hashTable) {\n    this.hashTableNameToHandle[name] = hashTable.handle;\n    this.hashTableMap[hashTable.id] = hashTable;\n  }\n  getHashTableHandleByName(name) {\n    return this.hashTableNameToHandle[name];\n  }\n  getHashTableById(id) {\n    return this.hashTableMap[id];\n  }\n  dispose() {\n    for (const key in this.hashTableMap) {\n      this.hashTableMap[key].clearAndClose();\n      delete this.hashTableMap[key];\n    }\n    for (const name in this.hashTableNameToHandle) {\n      this.hashTableNameToHandle[name].dispose();\n      delete this.hashTableNameToHandle[name];\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/executor/graph_model.js\nvar TFHUB_SEARCH_PARAM = \"?tfjs-format=file\";\nvar DEFAULT_MODEL_NAME = \"model.json\";\nvar GraphModel = class {\n  constructor(modelUrl, loadOptions = {}, tfio = io_exports) {\n    this.modelUrl = modelUrl;\n    this.loadOptions = loadOptions;\n    this.version = \"n/a\";\n    this.io = tfio;\n    if (loadOptions == null) {\n      this.loadOptions = {};\n    }\n    this.resourceManager = new ResourceManager();\n  }\n  get modelVersion() {\n    return this.version;\n  }\n  get inputNodes() {\n    return this.executor.inputNodes;\n  }\n  get outputNodes() {\n    return this.executor.outputNodes;\n  }\n  get inputs() {\n    return this.executor.inputs;\n  }\n  get outputs() {\n    return this.executor.outputs;\n  }\n  get weights() {\n    return this.executor.weightMap;\n  }\n  get metadata() {\n    return this.artifacts.userDefinedMetadata;\n  }\n  get modelSignature() {\n    return this.signature;\n  }\n  get modelStructuredOutputKeys() {\n    return this.structuredOutputKeys;\n  }\n  findIOHandler() {\n    const path = this.modelUrl;\n    if (path.load != null) {\n      this.handler = path;\n    } else if (this.loadOptions.requestInit != null) {\n      this.handler = this.io.browserHTTPRequest(path, this.loadOptions);\n    } else {\n      const handlers = this.io.getLoadHandlers(path, this.loadOptions);\n      if (handlers.length === 0) {\n        handlers.push(this.io.browserHTTPRequest(path, this.loadOptions));\n      } else if (handlers.length > 1) {\n        throw new Error(`Found more than one (${handlers.length}) load handlers for URL '${[path]}'`);\n      }\n      this.handler = handlers[0];\n    }\n  }\n  load() {\n    this.findIOHandler();\n    if (this.handler.load == null) {\n      throw new Error(\"Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.\");\n    }\n    const loadResult = this.handler.load();\n    if (util_exports.isPromise(loadResult)) {\n      return loadResult.then((artifacts) => this.loadSync(artifacts));\n    }\n    return this.loadSync(loadResult);\n  }\n  loadSync(artifacts) {\n    this.artifacts = artifacts;\n    const graph = this.artifacts.modelTopology;\n    let signature = this.artifacts.signature;\n    if (this.artifacts.userDefinedMetadata != null) {\n      const metadata = this.artifacts.userDefinedMetadata;\n      if (metadata.signature != null) {\n        signature = metadata.signature;\n      }\n      if (metadata.structuredOutputKeys != null) {\n        this.structuredOutputKeys = metadata.structuredOutputKeys;\n      }\n    }\n    this.signature = signature;\n    this.version = `${graph.versions.producer}.${graph.versions.minConsumer}`;\n    const weightMap = this.io.decodeWeights(this.artifacts.weightData, this.artifacts.weightSpecs);\n    this.executor = new GraphExecutor(OperationMapper.Instance.transformGraph(graph, this.signature));\n    this.executor.weightMap = this.convertTensorMapToTensorsMap(weightMap);\n    this.executor.resourceManager = this.resourceManager;\n    if (artifacts.modelInitializer != null && artifacts.modelInitializer.node != null) {\n      const initializer = OperationMapper.Instance.transformGraph(artifacts.modelInitializer);\n      this.initializer = new GraphExecutor(initializer);\n      this.initializer.weightMap = this.executor.weightMap;\n      this.initializer.resourceManager = this.resourceManager;\n      this.initializer.executeAsync({}, []);\n    }\n    return true;\n  }\n  async save(handlerOrURL, config) {\n    if (typeof handlerOrURL === \"string\") {\n      const handlers = this.io.getSaveHandlers(handlerOrURL);\n      if (handlers.length === 0) {\n        throw new Error(`Cannot find any save handlers for URL '${handlerOrURL}'`);\n      } else if (handlers.length > 1) {\n        throw new Error(`Found more than one (${handlers.length}) save handlers for URL '${handlerOrURL}'`);\n      }\n      handlerOrURL = handlers[0];\n    }\n    if (handlerOrURL.save == null) {\n      throw new Error(\"GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.\");\n    }\n    return handlerOrURL.save(this.artifacts);\n  }\n  predict(inputs, config) {\n    const outputTensors = this.execute(inputs, this.outputNodes);\n    if (this.structuredOutputKeys) {\n      const outputTensorsArray = outputTensors instanceof Tensor ? [outputTensors] : outputTensors;\n      const outputTensorMap = {};\n      outputTensorsArray.forEach((outputTensor, i2) => outputTensorMap[this.structuredOutputKeys[i2]] = outputTensor);\n      return outputTensorMap;\n    }\n    return outputTensors;\n  }\n  normalizeInputs(inputs) {\n    if (!(inputs instanceof Tensor) && !Array.isArray(inputs)) {\n      return inputs;\n    }\n    inputs = Array.isArray(inputs) ? inputs : [inputs];\n    if (inputs.length !== this.inputNodes.length) {\n      throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${inputs.length} input tensors.`);\n    }\n    return this.inputNodes.reduce((map, inputName, i2) => {\n      map[inputName] = inputs[i2];\n      return map;\n    }, {});\n  }\n  normalizeOutputs(outputs) {\n    outputs = outputs || this.outputNodes;\n    return !Array.isArray(outputs) ? [outputs] : outputs;\n  }\n  execute(inputs, outputs) {\n    inputs = this.normalizeInputs(inputs);\n    outputs = this.normalizeOutputs(outputs);\n    const result = this.executor.execute(inputs, outputs);\n    return result.length > 1 ? result : result[0];\n  }\n  async executeAsync(inputs, outputs) {\n    inputs = this.normalizeInputs(inputs);\n    outputs = this.normalizeOutputs(outputs);\n    const result = await this.executor.executeAsync(inputs, outputs);\n    return result.length > 1 ? result : result[0];\n  }\n  getIntermediateTensors() {\n    return this.executor.getIntermediateTensors();\n  }\n  disposeIntermediateTensors() {\n    this.executor.disposeIntermediateTensors();\n  }\n  convertTensorMapToTensorsMap(map) {\n    return Object.keys(map).reduce((newMap, key) => {\n      newMap[key] = [map[key]];\n      return newMap;\n    }, {});\n  }\n  dispose() {\n    this.executor.dispose();\n    if (this.initializer) {\n      this.initializer.dispose();\n    }\n    this.resourceManager.dispose();\n  }\n};\nasync function loadGraphModel(modelUrl, options = {}, tfio = io_exports) {\n  if (modelUrl == null) {\n    throw new Error(\"modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model\");\n  }\n  if (options == null) {\n    options = {};\n  }\n  if (options.fromTFHub && typeof modelUrl === \"string\") {\n    modelUrl = getTFHubUrl(modelUrl);\n  }\n  const model2 = new GraphModel(modelUrl, options, tfio);\n  await model2.load();\n  return model2;\n}\nfunction loadGraphModelSync(modelSource) {\n  if (modelSource == null) {\n    throw new Error(\"modelUrl in loadGraphModelSync() cannot be null. Please provide a url or an IOHandler that loads the model\");\n  }\n  if (!modelSource.load) {\n    throw new Error(`modelUrl IO Handler ${modelSource} has no load function`);\n  }\n  const model2 = new GraphModel(modelSource);\n  model2.load();\n  return model2;\n}\nfunction getTFHubUrl(modelUrl) {\n  if (!modelUrl.endsWith(\"/\")) {\n    modelUrl = modelUrl + \"/\";\n  }\n  return `${modelUrl}${DEFAULT_MODEL_NAME}${TFHUB_SEARCH_PARAM}`;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-converter@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-converter/dist/version.js\nvar version3 = \"3.19.0\";\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/index.js\nvar dist_exports2 = {};\n__export(dist_exports2, {\n  CSVDataset: () => CSVDataset,\n  Dataset: () => Dataset,\n  FileDataSource: () => FileDataSource,\n  TextLineDataset: () => TextLineDataset,\n  URLDataSource: () => URLDataSource,\n  array: () => array,\n  csv: () => csv,\n  func: () => func,\n  generator: () => generator,\n  microphone: () => microphone,\n  version_data: () => version4,\n  webcam: () => webcam,\n  zip: () => zip\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/dataset.js\nvar seedrandom3 = __toESM(require_seedrandom2());\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/lazy_iterator.js\nvar seedrandom2 = __toESM(require_seedrandom2());\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/util/deep_map.js\nfunction deepMap(input2, mapFn) {\n  return deepMapInternal(input2, mapFn);\n}\nfunction deepMapInternal(input2, mapFn, seen = /* @__PURE__ */ new Map(), containedIn = /* @__PURE__ */ new Set()) {\n  if (input2 == null) {\n    return null;\n  }\n  if (typeof Blob === \"function\" && input2 instanceof Blob) {\n    return input2.slice();\n  }\n  if (containedIn.has(input2)) {\n    throw new Error(\"Circular references are not supported.\");\n  }\n  if (seen.has(input2)) {\n    return seen.get(input2);\n  }\n  const result = mapFn(input2);\n  if (result.recurse && result.value !== null) {\n    throw new Error(\"A deep map function may not return both a value and recurse=true.\");\n  }\n  if (!result.recurse) {\n    seen.set(input2, result.value);\n    return result.value;\n  } else if (isIterable2(input2)) {\n    const mappedIterable = Array.isArray(input2) ? [] : {};\n    containedIn.add(input2);\n    for (const k in input2) {\n      const child = input2[k];\n      const childResult = deepMapInternal(child, mapFn, seen, containedIn);\n      mappedIterable[k] = childResult;\n    }\n    containedIn.delete(input2);\n    if (input2.__proto__) {\n      mappedIterable.__proto__ = input2.__proto__;\n    }\n    return mappedIterable;\n  } else {\n    throw new Error(`Can't recurse into non-iterable type: ${input2}`);\n  }\n}\nfunction deepZip(inputs, zipFn = zipToList) {\n  return deepZipInternal(inputs, zipFn);\n}\nfunction deepZipInternal(inputs, zipFn, containedIn = /* @__PURE__ */ new Set()) {\n  const input2 = inputs[0];\n  if (containedIn.has(input2)) {\n    throw new Error(\"Circular references are not supported.\");\n  }\n  const result = zipFn(inputs);\n  if (result.recurse && result.value !== null) {\n    throw new Error(\"A deep zip function may not return both a value and recurse=true.\");\n  }\n  if (!result.recurse) {\n    return result.value;\n  } else if (isIterable2(input2)) {\n    const mappedIterable = Array.isArray(input2) ? [] : {};\n    containedIn.add(input2);\n    for (const k in input2) {\n      const children = inputs.map((x) => x[k]);\n      const childResult = deepZipInternal(children, zipFn, containedIn);\n      mappedIterable[k] = childResult;\n    }\n    containedIn.delete(input2);\n    return mappedIterable;\n  } else {\n    throw new Error(`Can't recurse into non-iterable type: ${input2}`);\n  }\n}\nfunction zipToList(x) {\n  if (x === null) {\n    return null;\n  }\n  if (isIterable2(x[0])) {\n    return { value: null, recurse: true };\n  } else {\n    return { value: x, recurse: false };\n  }\n}\nasync function deepMapAndAwaitAll(input2, mapFn) {\n  const seen = /* @__PURE__ */ new Map();\n  deepMapInternal(input2, mapFn, seen);\n  for (const key of Array.from(seen.keys())) {\n    const value = seen.get(key);\n    if (util_exports.isPromise(value)) {\n      const mappedValue = await value;\n      seen.set(key, mappedValue);\n    }\n  }\n  const result = deepMapInternal(input2, mapFn, seen);\n  return result;\n}\nfunction isIterable2(obj) {\n  let isTextDecoder = false;\n  if (env().get(\"IS_BROWSER\")) {\n    isTextDecoder = obj instanceof TextDecoder;\n  } else {\n    const { StringDecoder } = require_string_decoder();\n    isTextDecoder = obj instanceof StringDecoder;\n  }\n  return obj != null && !ArrayBuffer.isView(obj) && (Array.isArray(obj) || typeof obj === \"object\" && !(obj instanceof Tensor) && !(obj instanceof Promise) && !isTextDecoder);\n}\nfunction canTensorify(obj) {\n  return obj == null || isPrimitive(obj) || Array.isArray(obj) || typeof obj === \"object\" && obj instanceof Tensor || util_exports.isTypedArray(obj);\n}\nfunction isPrimitive(value) {\n  return value === null || typeof value !== \"object\" && typeof value !== \"function\";\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/util/deep_clone.js\nfunction deepClone(container) {\n  return deepMap(container, cloneIfTensor);\n}\nfunction cloneIfTensor(item) {\n  if (item instanceof Tensor) {\n    return { value: item.clone(), recurse: false };\n  } else if (isIterable2(item)) {\n    return { value: null, recurse: true };\n  } else {\n    return { value: item, recurse: false };\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/util/ring_buffer.js\nvar RingBuffer = class {\n  constructor(capacity) {\n    this.capacity = capacity;\n    this.begin = 0;\n    this.end = 0;\n    if (capacity == null) {\n      throw new RangeError(\"Can't create a ring buffer of unknown capacity.\");\n    }\n    if (capacity < 1) {\n      throw new RangeError(\"Can't create ring buffer of capacity < 1.\");\n    }\n    this.data = new Array(capacity);\n    this.doubledCapacity = 2 * capacity;\n  }\n  wrap(index) {\n    while (index < 0) {\n      index += this.doubledCapacity;\n    }\n    return index % this.doubledCapacity;\n  }\n  get(index) {\n    if (index < 0) {\n      throw new RangeError(\"Can't get item at a negative index.\");\n    }\n    return this.data[index % this.capacity];\n  }\n  set(index, value) {\n    if (index < 0) {\n      throw new RangeError(\"Can't set item at a negative index.\");\n    }\n    this.data[index % this.capacity] = value;\n  }\n  length() {\n    let length = this.end - this.begin;\n    if (length < 0) {\n      length = this.doubledCapacity + length;\n    }\n    return length;\n  }\n  isFull() {\n    return this.length() === this.capacity;\n  }\n  isEmpty() {\n    return this.length() === 0;\n  }\n  push(value) {\n    if (this.isFull()) {\n      throw new RangeError(\"Ring buffer is full.\");\n    }\n    this.set(this.end, value);\n    this.end = this.wrap(this.end + 1);\n  }\n  pushAll(values) {\n    for (const value of values) {\n      this.push(value);\n    }\n  }\n  pop() {\n    if (this.isEmpty()) {\n      throw new RangeError(\"Ring buffer is empty.\");\n    }\n    this.end = this.wrap(this.end - 1);\n    const result = this.get(this.end);\n    this.set(this.end, void 0);\n    return result;\n  }\n  unshift(value) {\n    if (this.isFull()) {\n      throw new RangeError(\"Ring buffer is full.\");\n    }\n    this.begin = this.wrap(this.begin - 1);\n    this.set(this.begin, value);\n  }\n  shift() {\n    if (this.isEmpty()) {\n      throw new RangeError(\"Ring buffer is empty.\");\n    }\n    const result = this.get(this.begin);\n    this.set(this.begin, void 0);\n    this.begin = this.wrap(this.begin + 1);\n    return result;\n  }\n  shuffleExcise(relativeIndex) {\n    if (this.isEmpty()) {\n      throw new RangeError(\"Ring buffer is empty.\");\n    }\n    const index = this.wrap(this.begin + relativeIndex);\n    const result = this.get(index);\n    this.set(index, this.pop());\n    return result;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/util/growing_ring_buffer.js\nvar GrowingRingBuffer = class extends RingBuffer {\n  constructor() {\n    super(GrowingRingBuffer.INITIAL_CAPACITY);\n  }\n  isFull() {\n    return false;\n  }\n  push(value) {\n    if (super.isFull()) {\n      this.expand();\n    }\n    super.push(value);\n  }\n  unshift(value) {\n    if (super.isFull()) {\n      this.expand();\n    }\n    super.unshift(value);\n  }\n  expand() {\n    const newCapacity = this.capacity * 2;\n    const newData = new Array(newCapacity);\n    const len = this.length();\n    for (let i2 = 0; i2 < len; i2++) {\n      newData[i2] = this.get(this.wrap(this.begin + i2));\n    }\n    this.data = newData;\n    this.capacity = newCapacity;\n    this.doubledCapacity = 2 * this.capacity;\n    this.begin = 0;\n    this.end = len;\n  }\n};\nGrowingRingBuffer.INITIAL_CAPACITY = 32;\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/lazy_iterator.js\nfunction iteratorFromItems(items) {\n  return new ArrayIterator(items);\n}\nfunction iteratorFromFunction(func2) {\n  return new FunctionCallIterator(func2);\n}\nfunction iteratorFromConcatenated(baseIterators, baseErrorHandler) {\n  return new ChainedIterator(baseIterators, baseErrorHandler);\n}\nfunction iteratorFromZipped(iterators, mismatchMode = ZipMismatchMode.FAIL) {\n  return new ZipIterator(iterators, mismatchMode);\n}\nvar LazyIterator = class {\n  async toArray() {\n    const result = [];\n    let x = await this.next();\n    while (!x.done) {\n      result.push(x.value);\n      x = await this.next();\n    }\n    return result;\n  }\n  async toArrayForTest() {\n    const stream = this.prefetch(100);\n    const result = [];\n    let x = await stream.next();\n    while (!x.done) {\n      result.push(x.value);\n      x = await stream.next();\n    }\n    return result;\n  }\n  async resolveFully() {\n    let x = await this.next();\n    while (!x.done) {\n      x = await this.next();\n    }\n  }\n  async resolveWhile(predicate) {\n    let x = await this.next();\n    let shouldContinue = predicate(x.value);\n    while (!x.done && shouldContinue) {\n      x = await this.next();\n      shouldContinue = predicate(x.value);\n    }\n  }\n  handleErrors(handler) {\n    return new ErrorHandlingLazyIterator(this, handler);\n  }\n  filter(predicate) {\n    return new FilterIterator(this, predicate);\n  }\n  map(transform6) {\n    return new MapIterator(this, transform6);\n  }\n  mapAsync(transform6) {\n    return new AsyncMapIterator(this, transform6);\n  }\n  serialMapAsync(transform6) {\n    return new AsyncMapIterator(this, transform6).serial();\n  }\n  flatmap(transform6) {\n    return new FlatmapIterator(this, transform6);\n  }\n  async forEachAsync(f) {\n    return this.map(f).resolveFully();\n  }\n  async serialForEach(f) {\n    return this.serialMapAsync(f).resolveWhile((x) => x === true);\n  }\n  rowMajorBatch(batchSize, smallLastBatch = true) {\n    return new RowMajorBatchIterator(this, batchSize, smallLastBatch);\n  }\n  columnMajorBatch(batchSize, smallLastBatch = true, zipFn = zipToList) {\n    const rowBatches = this.rowMajorBatch(batchSize, smallLastBatch);\n    return rowBatches.map((x) => deepZip(x, zipFn));\n  }\n  concatenate(iterator, baseErrorHandler) {\n    return new ChainedIterator(iteratorFromItems([this, iterator]), baseErrorHandler);\n  }\n  take(count2) {\n    if (count2 < 0 || count2 == null) {\n      return this;\n    }\n    return new TakeIterator(this, count2);\n  }\n  skip(count2) {\n    if (count2 < 0 || count2 == null) {\n      return this;\n    }\n    return new SkipIterator(this, count2);\n  }\n  prefetch(bufferSize) {\n    return new PrefetchIterator(this, bufferSize);\n  }\n  shuffle(windowSize, seed) {\n    return new ShuffleIterator(this, windowSize, seed);\n  }\n  serial() {\n    return new SerialIterator(this);\n  }\n};\nvar ArrayIterator = class extends LazyIterator {\n  constructor(items) {\n    super();\n    this.items = items;\n    this.trav = 0;\n  }\n  summary() {\n    return `Array of ${this.items.length} items`;\n  }\n  async next() {\n    if (this.trav >= this.items.length) {\n      return { value: null, done: true };\n    }\n    const item = this.items[this.trav];\n    this.trav++;\n    return { value: deepClone(item), done: false };\n  }\n};\nvar FunctionCallIterator = class extends LazyIterator {\n  constructor(nextFn) {\n    super();\n    this.nextFn = nextFn;\n  }\n  summary() {\n    return `Function call`;\n  }\n  async next() {\n    try {\n      return this.nextFn();\n    } catch (e2) {\n      e2.message = `Error thrown while iterating through a dataset: ${e2.message}`;\n      throw e2;\n    }\n  }\n};\nvar SerialIterator = class extends LazyIterator {\n  constructor(upstream) {\n    super();\n    this.upstream = upstream;\n    this.lastRead = Promise.resolve({ value: null, done: false });\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Serial`;\n  }\n  async next() {\n    this.lastRead = this.lastRead.then(() => this.serialNext());\n    return this.lastRead;\n  }\n  async serialNext() {\n    return this.upstream.next();\n  }\n};\nvar SkipIterator = class extends LazyIterator {\n  constructor(upstream, maxCount) {\n    super();\n    this.upstream = upstream;\n    this.maxCount = maxCount;\n    this.count = 0;\n    this.lastRead = Promise.resolve({ value: null, done: false });\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Skip`;\n  }\n  async next() {\n    this.lastRead = this.lastRead.then(() => this.serialNext());\n    return this.lastRead;\n  }\n  async serialNext() {\n    while (this.count++ < this.maxCount) {\n      const skipped = await this.upstream.next();\n      if (skipped.done) {\n        return skipped;\n      }\n      dispose(skipped.value);\n    }\n    return this.upstream.next();\n  }\n};\nvar TakeIterator = class extends LazyIterator {\n  constructor(upstream, maxCount) {\n    super();\n    this.upstream = upstream;\n    this.maxCount = maxCount;\n    this.count = 0;\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Take`;\n  }\n  async next() {\n    if (this.count++ >= this.maxCount) {\n      return { value: null, done: true };\n    }\n    return this.upstream.next();\n  }\n};\nvar RowMajorBatchIterator = class extends LazyIterator {\n  constructor(upstream, batchSize, enableSmallLastBatch = true) {\n    super();\n    this.upstream = upstream;\n    this.batchSize = batchSize;\n    this.enableSmallLastBatch = enableSmallLastBatch;\n    this.lastRead = Promise.resolve({ value: null, done: false });\n  }\n  summary() {\n    return `${this.upstream.summary()} -> RowMajorBatch`;\n  }\n  async next() {\n    this.lastRead = this.lastRead.then(() => this.serialNext());\n    return this.lastRead;\n  }\n  async serialNext() {\n    const batch = [];\n    while (batch.length < this.batchSize) {\n      const item = await this.upstream.next();\n      if (item.done) {\n        if (this.enableSmallLastBatch && batch.length > 0) {\n          return { value: batch, done: false };\n        }\n        return { value: null, done: true };\n      }\n      batch.push(item.value);\n    }\n    return { value: batch, done: false };\n  }\n};\nvar FilterIterator = class extends LazyIterator {\n  constructor(upstream, predicate) {\n    super();\n    this.upstream = upstream;\n    this.predicate = predicate;\n    this.lastRead = Promise.resolve({ value: null, done: false });\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Filter`;\n  }\n  async next() {\n    this.lastRead = this.lastRead.then(() => this.serialNext());\n    return this.lastRead;\n  }\n  async serialNext() {\n    while (true) {\n      const item = await this.upstream.next();\n      if (item.done || this.predicate(item.value)) {\n        return item;\n      }\n      dispose(item.value);\n    }\n  }\n};\nvar MapIterator = class extends LazyIterator {\n  constructor(upstream, transform6) {\n    super();\n    this.upstream = upstream;\n    this.transform = transform6;\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Map`;\n  }\n  async next() {\n    const item = await this.upstream.next();\n    if (item.done) {\n      return { value: null, done: true };\n    }\n    const inputTensors = tensor_util_exports.getTensorsInContainer(item.value);\n    const mapped = this.transform(item.value);\n    const outputTensors = tensor_util_exports.getTensorsInContainer(mapped);\n    for (const t2 of inputTensors) {\n      if (!tensor_util_exports.isTensorInList(t2, outputTensors)) {\n        t2.dispose();\n      }\n    }\n    return { value: mapped, done: false };\n  }\n};\nvar ErrorHandlingLazyIterator = class extends LazyIterator {\n  constructor(upstream, handler) {\n    super();\n    this.upstream = upstream;\n    this.handler = handler;\n    this.count = 0;\n    this.lastRead = Promise.resolve({ value: null, done: false });\n  }\n  summary() {\n    return `${this.upstream.summary()} -> handleErrors`;\n  }\n  async next() {\n    this.lastRead = this.lastRead.then(() => this.serialNext());\n    return this.lastRead;\n  }\n  async serialNext() {\n    while (true) {\n      try {\n        return await this.upstream.next();\n      } catch (e2) {\n        if (!this.handler(e2)) {\n          return { value: null, done: true };\n        }\n      }\n    }\n  }\n};\nvar AsyncMapIterator = class extends LazyIterator {\n  constructor(upstream, transform6) {\n    super();\n    this.upstream = upstream;\n    this.transform = transform6;\n  }\n  summary() {\n    return `${this.upstream.summary()} -> AsyncMap`;\n  }\n  async next() {\n    const item = await this.upstream.next();\n    if (item.done) {\n      return { value: null, done: true };\n    }\n    const inputTensors = tensor_util_exports.getTensorsInContainer(item.value);\n    const mapped = await this.transform(item.value);\n    const outputTensors = tensor_util_exports.getTensorsInContainer(mapped);\n    for (const t2 of inputTensors) {\n      if (!tensor_util_exports.isTensorInList(t2, outputTensors)) {\n        t2.dispose();\n      }\n    }\n    return { value: mapped, done: false };\n  }\n};\nvar OneToManyIterator = class extends LazyIterator {\n  constructor() {\n    super();\n    this.outputQueue = new GrowingRingBuffer();\n    this.lastRead = Promise.resolve({ value: null, done: false });\n  }\n  async next() {\n    this.lastRead = this.lastRead.then(() => this.serialNext());\n    return this.lastRead;\n  }\n  async serialNext() {\n    while (this.outputQueue.length() === 0) {\n      if (!await this.pump()) {\n        return { value: null, done: true };\n      }\n    }\n    return { value: this.outputQueue.shift(), done: false };\n  }\n};\nvar FlatmapIterator = class extends OneToManyIterator {\n  constructor(upstream, transform6) {\n    super();\n    this.upstream = upstream;\n    this.transform = transform6;\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Flatmap`;\n  }\n  async pump() {\n    const item = await this.upstream.next();\n    if (item.done) {\n      return false;\n    }\n    const inputTensors = tensor_util_exports.getTensorsInContainer(item.value);\n    const mappedArray = this.transform(item.value);\n    const outputTensors = tensor_util_exports.getTensorsInContainer(mappedArray);\n    this.outputQueue.pushAll(mappedArray);\n    for (const t2 of inputTensors) {\n      if (!tensor_util_exports.isTensorInList(t2, outputTensors)) {\n        t2.dispose();\n      }\n    }\n    return true;\n  }\n};\nvar ChainedIterator = class extends LazyIterator {\n  constructor(iterators, baseErrorHandler) {\n    super();\n    this.baseErrorHandler = baseErrorHandler;\n    this.lastRead = null;\n    this.iterator = null;\n    this.moreIterators = iterators;\n  }\n  summary() {\n    const upstreamSummaries = \"TODO: fill in upstream of chained summaries\";\n    return `${upstreamSummaries} -> Chained`;\n  }\n  async next() {\n    this.lastRead = this.readFromChain(this.lastRead);\n    return this.lastRead;\n  }\n  async readFromChain(lastRead) {\n    await lastRead;\n    if (this.iterator == null) {\n      const iteratorResult = await this.moreIterators.next();\n      if (iteratorResult.done) {\n        return { value: null, done: true };\n      }\n      this.iterator = iteratorResult.value;\n      if (this.baseErrorHandler != null) {\n        this.iterator = this.iterator.handleErrors(this.baseErrorHandler);\n      }\n    }\n    const itemResult = await this.iterator.next();\n    if (itemResult.done) {\n      this.iterator = null;\n      return this.readFromChain(lastRead);\n    }\n    return itemResult;\n  }\n};\nvar ZipMismatchMode;\n(function(ZipMismatchMode2) {\n  ZipMismatchMode2[ZipMismatchMode2[\"FAIL\"] = 0] = \"FAIL\";\n  ZipMismatchMode2[ZipMismatchMode2[\"SHORTEST\"] = 1] = \"SHORTEST\";\n  ZipMismatchMode2[ZipMismatchMode2[\"LONGEST\"] = 2] = \"LONGEST\";\n})(ZipMismatchMode || (ZipMismatchMode = {}));\nvar ZipIterator = class extends LazyIterator {\n  constructor(iterators, mismatchMode = ZipMismatchMode.FAIL) {\n    super();\n    this.iterators = iterators;\n    this.mismatchMode = mismatchMode;\n    this.count = 0;\n    this.currentPromise = null;\n  }\n  summary() {\n    const upstreamSummaries = \"TODO: fill in upstream of zip summaries\";\n    return `{${upstreamSummaries}} -> Zip`;\n  }\n  async nextState(afterState) {\n    await afterState;\n    let numIterators = 0;\n    let iteratorsDone = 0;\n    function getNext(container) {\n      if (container instanceof LazyIterator) {\n        const result = container.next();\n        return {\n          value: result.then((x) => {\n            numIterators++;\n            if (x.done) {\n              iteratorsDone++;\n            }\n            return x.value;\n          }),\n          recurse: false\n        };\n      } else {\n        return { value: null, recurse: true };\n      }\n    }\n    const mapped = await deepMapAndAwaitAll(this.iterators, getNext);\n    if (numIterators === iteratorsDone) {\n      return { value: null, done: true };\n    }\n    if (iteratorsDone > 0) {\n      switch (this.mismatchMode) {\n        case ZipMismatchMode.FAIL:\n          throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);\n        case ZipMismatchMode.SHORTEST:\n          return { value: null, done: true };\n        case ZipMismatchMode.LONGEST:\n        default:\n      }\n    }\n    this.count++;\n    return { value: mapped, done: false };\n  }\n  async next() {\n    this.currentPromise = this.nextState(this.currentPromise);\n    return this.currentPromise;\n  }\n};\nvar PrefetchIterator = class extends LazyIterator {\n  constructor(upstream, bufferSize) {\n    super();\n    this.upstream = upstream;\n    this.bufferSize = bufferSize;\n    this.buffer = new RingBuffer(bufferSize);\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Prefetch`;\n  }\n  refill() {\n    while (!this.buffer.isFull()) {\n      const v = this.upstream.next();\n      this.buffer.push(v);\n    }\n  }\n  next() {\n    this.refill();\n    return this.buffer.shift();\n  }\n};\nvar ShuffleIterator = class extends PrefetchIterator {\n  constructor(upstream, windowSize, seed) {\n    super(upstream, windowSize);\n    this.upstream = upstream;\n    this.windowSize = windowSize;\n    this.upstreamExhausted = false;\n    this.random = seedrandom2.alea(seed || util_exports.now().toString());\n    this.lastRead = Promise.resolve({ value: null, done: false });\n  }\n  async next() {\n    this.lastRead = this.lastRead.then(() => this.serialNext());\n    return this.lastRead;\n  }\n  randomInt(max7) {\n    return Math.floor(this.random() * max7);\n  }\n  chooseIndex() {\n    return this.randomInt(this.buffer.length());\n  }\n  async serialNext() {\n    if (!this.upstreamExhausted) {\n      this.refill();\n    }\n    while (!this.buffer.isEmpty()) {\n      const chosenIndex = this.chooseIndex();\n      const result = await this.buffer.shuffleExcise(chosenIndex);\n      if (result.done) {\n        this.upstreamExhausted = true;\n      } else {\n        this.refill();\n        return result;\n      }\n    }\n    return { value: null, done: true };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/dataset.js\nvar Dataset = class {\n  constructor() {\n    this.size = null;\n  }\n  batch(batchSize, smallLastBatch = true) {\n    const base = this;\n    util_exports.assert(batchSize > 0, () => `batchSize needs to be positive, but it is\n      ${batchSize}`);\n    let size;\n    if (this.size === Infinity || this.size == null) {\n      size = this.size;\n    } else if (smallLastBatch) {\n      size = Math.ceil(this.size / batchSize);\n    } else {\n      size = Math.floor(this.size / batchSize);\n    }\n    return datasetFromIteratorFn(async () => {\n      return (await base.iterator()).columnMajorBatch(batchSize, smallLastBatch, deepBatchConcat);\n    }, size);\n  }\n  concatenate(dataset) {\n    const base = this;\n    let size;\n    if (this.size === Infinity || dataset.size === Infinity) {\n      size = Infinity;\n    } else if (this.size != null && dataset.size != null) {\n      size = this.size + dataset.size;\n    } else {\n      size = null;\n    }\n    return datasetFromIteratorFn(async () => (await base.iterator()).concatenate(await dataset.iterator()), size);\n  }\n  filter(predicate) {\n    const base = this;\n    let size;\n    if (this.size === Infinity) {\n      size = Infinity;\n    } else {\n      size = null;\n    }\n    return datasetFromIteratorFn(async () => {\n      return (await base.iterator()).filter((x) => tidy(() => predicate(x)));\n    }, size);\n  }\n  async forEachAsync(f) {\n    return (await this.iterator()).forEachAsync(f);\n  }\n  map(transform6) {\n    const base = this;\n    return datasetFromIteratorFn(async () => {\n      return (await base.iterator()).map((x) => tidy(() => transform6(x)));\n    }, this.size);\n  }\n  mapAsync(transform6) {\n    const base = this;\n    return datasetFromIteratorFn(async () => {\n      return (await base.iterator()).mapAsync(transform6);\n    }, this.size);\n  }\n  prefetch(bufferSize) {\n    if (bufferSize == null) {\n      throw new RangeError(\"`Dataset.prefetch()` requires bufferSize to be specified.\");\n    }\n    const base = this;\n    return datasetFromIteratorFn(async () => (await base.iterator()).prefetch(bufferSize), this.size);\n  }\n  repeat(count2) {\n    const base = this;\n    let size;\n    if (this.size != null && count2 > 0) {\n      size = this.size * count2;\n    } else if (count2 === 0) {\n      size = 0;\n    } else if (this.size != null && (count2 === void 0 || count2 < 0)) {\n      size = Infinity;\n    } else {\n      size = null;\n    }\n    return datasetFromIteratorFn(async () => {\n      const iteratorIterator = iteratorFromFunction(async () => ({ value: await base.iterator(), done: false }));\n      return iteratorFromConcatenated(iteratorIterator.take(count2));\n    }, size);\n  }\n  skip(count2) {\n    const base = this;\n    let size;\n    if (this.size != null && count2 >= 0 && this.size >= count2) {\n      size = this.size - count2;\n    } else if (this.size != null && (this.size < count2 || count2 === void 0 || count2 < 0)) {\n      size = 0;\n    } else {\n      size = null;\n    }\n    return datasetFromIteratorFn(async () => (await base.iterator()).skip(count2), size);\n  }\n  shuffle(bufferSize, seed, reshuffleEachIteration = true) {\n    if (bufferSize == null || bufferSize < 0) {\n      if (this.size == null) {\n        throw new RangeError(\"`Dataset.shuffle()` requires bufferSize to be specified.\");\n      } else {\n        throw new RangeError(`\\`Dataset.shuffle()\\` requires bufferSize to be specified.  If your data fits in main memory (for regular JS objects), and/or GPU memory (for \\`tf.Tensor\\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);\n      }\n    }\n    const base = this;\n    const random = seedrandom3.alea(seed || util_exports.now().toString());\n    return datasetFromIteratorFn(async () => {\n      let seed2 = random.int32();\n      if (reshuffleEachIteration) {\n        seed2 += random.int32();\n      }\n      return (await base.iterator()).shuffle(bufferSize, seed2.toString());\n    }, this.size);\n  }\n  take(count2) {\n    const base = this;\n    let size;\n    if (this.size != null && this.size > count2) {\n      size = count2;\n    } else if (this.size != null && this.size <= count2) {\n      size = this.size;\n    } else {\n      size = null;\n    }\n    return datasetFromIteratorFn(async () => (await base.iterator()).take(count2), size);\n  }\n  async toArray() {\n    if (this.size === Infinity) {\n      throw new Error(\"Can not convert infinite data stream to array.\");\n    }\n    return (await this.iterator()).toArray();\n  }\n  async toArrayForTest() {\n    if (this.size === Infinity) {\n      throw new Error(\"Can not convert infinite data stream to array.\");\n    }\n    return (await this.iterator()).toArrayForTest();\n  }\n};\nDataset.MAX_BUFFER_SIZE = 1e4;\nfunction datasetFromIteratorFn(iteratorFn, size = null) {\n  return new class extends Dataset {\n    constructor() {\n      super(...arguments);\n      this.size = size;\n    }\n    async iterator() {\n      return iteratorFn();\n    }\n  }();\n}\nfunction array(items) {\n  return datasetFromIteratorFn(async () => iteratorFromItems(items), items.length);\n}\nfunction zip(datasets) {\n  if (!isIterable2(datasets)) {\n    throw new Error(\"The argument to zip() must be an object or array.\");\n  }\n  let size;\n  if (Array.isArray(datasets)) {\n    for (let i2 = 0; i2 < datasets.length; i2++) {\n      size = size == null ? datasets[i2].size : Math.min(size, datasets[i2].size);\n    }\n  } else if (datasets instanceof Object) {\n    for (const ds in datasets) {\n      size = size == null ? datasets[ds].size : Math.min(size, datasets[ds].size);\n    }\n  }\n  return datasetFromIteratorFn(async () => {\n    const streams = await deepMapAndAwaitAll(datasets, (d) => {\n      if (d instanceof Dataset) {\n        return { value: d.iterator(), recurse: false };\n      } else if (isIterable2(d)) {\n        return { value: null, recurse: true };\n      } else {\n        throw new Error(\"Leaves of the structure passed to zip() must be Datasets, not primitives.\");\n      }\n    });\n    return iteratorFromZipped(streams, ZipMismatchMode.SHORTEST);\n  }, size);\n}\nfunction deepBatchConcat(rows) {\n  if (rows === null) {\n    return null;\n  }\n  const exampleRow = rows[0];\n  if (canTensorify(exampleRow)) {\n    const value = batchConcat(rows);\n    return { value, recurse: false };\n  }\n  return { value: null, recurse: true };\n}\nfunction batchConcat(arrays) {\n  if (arrays.length === 0) {\n    throw new Error(\"Can't make a batch of zero elements.\");\n  }\n  if (arrays[0] instanceof Tensor) {\n    return stack(arrays);\n  } else {\n    return tensor(arrays);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/datasets/text_line_dataset.js\nvar TextLineDataset = class extends Dataset {\n  constructor(input2) {\n    super();\n    this.input = input2;\n  }\n  async iterator() {\n    const inputIterator = await this.input.iterator();\n    const utf8Iterator = inputIterator.decodeUTF8();\n    const lineIterator = utf8Iterator.split(\"\\n\").map((line) => {\n      if (line.endsWith(\"\\r\")) {\n        line = line.slice(0, -1);\n      }\n      return line;\n    });\n    return lineIterator;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/datasets/csv_dataset.js\nvar CODE_QUOTE = '\"';\nvar STATE_OUT = Symbol(\"out\");\nvar STATE_FIELD = Symbol(\"field\");\nvar STATE_QUOTE = Symbol(\"quote\");\nvar STATE_QUOTE_AFTER_QUOTE = Symbol(\"quoteafterquote\");\nvar STATE_WITHIN_QUOTE_IN_QUOTE = Symbol(\"quoteinquote\");\nvar CSVDataset = class extends Dataset {\n  constructor(input2, csvConfig) {\n    super();\n    this.input = input2;\n    this.hasHeader = true;\n    this.fullColumnNames = null;\n    this.columnNamesValidated = false;\n    this.columnConfigs = null;\n    this.configuredColumnsOnly = false;\n    this.delimiter = \",\";\n    this.delimWhitespace = false;\n    this.base = new TextLineDataset(input2);\n    if (!csvConfig) {\n      csvConfig = {};\n    }\n    this.hasHeader = csvConfig.hasHeader === false ? false : true;\n    this.fullColumnNames = csvConfig.columnNames;\n    this.columnConfigs = csvConfig.columnConfigs;\n    this.configuredColumnsOnly = csvConfig.configuredColumnsOnly;\n    if (csvConfig.delimWhitespace) {\n      util_exports.assert(csvConfig.delimiter == null, () => \"Delimiter should not be provided when delimWhitespace is true.\");\n      this.delimWhitespace = true;\n      this.delimiter = \" \";\n    } else {\n      this.delimiter = csvConfig.delimiter ? csvConfig.delimiter : \",\";\n    }\n  }\n  async columnNames() {\n    if (!this.columnNamesValidated) {\n      await this.setColumnNames();\n    }\n    return this.configuredColumnsOnly ? Object.keys(this.columnConfigs) : this.fullColumnNames;\n  }\n  async setColumnNames() {\n    const columnNamesFromFile = await this.maybeReadHeaderLine();\n    if (!this.fullColumnNames && !columnNamesFromFile) {\n      throw new Error(\"Column names must be provided if there is no header line.\");\n    } else if (this.fullColumnNames && columnNamesFromFile) {\n      util_exports.assert(columnNamesFromFile.length === this.fullColumnNames.length, () => \"The length of provided columnNames (\" + this.fullColumnNames.length.toString() + \") does not match the length of the header line read from file (\" + columnNamesFromFile.length.toString() + \").\");\n    }\n    if (!this.fullColumnNames) {\n      this.fullColumnNames = columnNamesFromFile;\n    }\n    const counts = this.fullColumnNames.reduce((countAcc, name) => {\n      countAcc[name] = countAcc[name] + 1 || 1;\n      return countAcc;\n    }, {});\n    const duplicateNames = Object.keys(counts).filter((name) => counts[name] > 1);\n    util_exports.assert(duplicateNames.length === 0, () => \"Duplicate column names found: \" + duplicateNames.toString());\n    if (this.columnConfigs) {\n      for (const key of Object.keys(this.columnConfigs)) {\n        const index = this.fullColumnNames.indexOf(key);\n        if (index === -1) {\n          throw new Error('The key \"' + key + '\" provided in columnConfigs does not match any of the column names (' + this.fullColumnNames.toString() + \").\");\n        }\n      }\n    }\n    this.columnNamesValidated = true;\n  }\n  async maybeReadHeaderLine() {\n    if (this.hasHeader) {\n      const iter = await this.base.iterator();\n      const firstElement = await iter.next();\n      if (firstElement.done) {\n        throw new Error(\"No data was found for CSV parsing.\");\n      }\n      const firstLine = firstElement.value;\n      const headers = this.parseRow(firstLine, false);\n      return headers;\n    } else {\n      return null;\n    }\n  }\n  async iterator() {\n    if (!this.columnNamesValidated) {\n      await this.setColumnNames();\n    }\n    let lines = await this.base.iterator();\n    if (this.hasHeader) {\n      lines = lines.skip(1);\n    }\n    return lines.map((x) => this.makeDataElement(x));\n  }\n  makeDataElement(line) {\n    const values = this.parseRow(line);\n    const features = {};\n    const labels = {};\n    for (let i2 = 0; i2 < this.fullColumnNames.length; i2++) {\n      const key = this.fullColumnNames[i2];\n      const config = this.columnConfigs ? this.columnConfigs[key] : null;\n      if (this.configuredColumnsOnly && !config) {\n        continue;\n      } else {\n        const value = values[i2];\n        let parsedValue = null;\n        if (value === \"\") {\n          if (config && config.default !== void 0) {\n            parsedValue = config.default;\n          } else if (config && (config.required || config.isLabel)) {\n            throw new Error(`Required column ${key} is empty in this line: ${line}`);\n          } else {\n            parsedValue = void 0;\n          }\n        } else {\n          const valueAsNum = Number(value);\n          if (isNaN(valueAsNum)) {\n            if (config && config.dtype === \"bool\") {\n              parsedValue = this.getBoolean(value);\n            } else {\n              parsedValue = value;\n            }\n          } else if (!config || !config.dtype) {\n            parsedValue = valueAsNum;\n          } else {\n            switch (config.dtype) {\n              case \"float32\":\n                parsedValue = valueAsNum;\n                break;\n              case \"int32\":\n                parsedValue = Math.floor(valueAsNum);\n                break;\n              case \"bool\":\n                parsedValue = this.getBoolean(value);\n                break;\n              default:\n                parsedValue = valueAsNum;\n            }\n          }\n        }\n        config && config.isLabel ? labels[key] = parsedValue : features[key] = parsedValue;\n      }\n    }\n    if (Object.keys(labels).length === 0) {\n      return features;\n    } else {\n      return { xs: features, ys: labels };\n    }\n  }\n  getBoolean(value) {\n    if (value === \"1\" || value.toLowerCase() === \"true\") {\n      return 1;\n    } else {\n      return 0;\n    }\n  }\n  parseRow(line, validateElementCount = true) {\n    const result = [];\n    let readOffset = 0;\n    const readLength = line.length;\n    let currentState = STATE_OUT;\n    for (let i2 = 0; i2 < readLength; i2++) {\n      switch (currentState) {\n        case STATE_OUT:\n          switch (line.charAt(i2)) {\n            case CODE_QUOTE:\n              readOffset = i2 + 1;\n              currentState = STATE_QUOTE;\n              break;\n            case this.delimiter:\n              readOffset = i2 + 1;\n              if (this.delimiter === \" \" && this.delimWhitespace) {\n                break;\n              }\n              result.push(\"\");\n              currentState = STATE_OUT;\n              break;\n            default:\n              currentState = STATE_FIELD;\n              readOffset = i2;\n              break;\n          }\n          break;\n        case STATE_FIELD:\n          switch (line.charAt(i2)) {\n            case this.delimiter:\n              result.push(line.substring(readOffset, i2));\n              currentState = STATE_OUT;\n              readOffset = i2 + 1;\n              break;\n            default:\n          }\n          break;\n        case STATE_QUOTE:\n          switch (line.charAt(i2)) {\n            case CODE_QUOTE:\n              currentState = STATE_QUOTE_AFTER_QUOTE;\n              break;\n            default:\n          }\n          break;\n        case STATE_QUOTE_AFTER_QUOTE:\n          switch (line.charAt(i2)) {\n            case this.delimiter:\n              result.push(line.substring(readOffset, i2 - 1));\n              currentState = STATE_OUT;\n              readOffset = i2 + 1;\n              break;\n            case CODE_QUOTE:\n              currentState = STATE_QUOTE;\n              break;\n            default:\n              currentState = STATE_WITHIN_QUOTE_IN_QUOTE;\n              break;\n          }\n          break;\n        case STATE_WITHIN_QUOTE_IN_QUOTE:\n          switch (line.charAt(i2)) {\n            case CODE_QUOTE:\n              currentState = STATE_QUOTE;\n              break;\n            default:\n          }\n          break;\n        default:\n      }\n    }\n    if (currentState === STATE_QUOTE_AFTER_QUOTE) {\n      result.push(line.substring(readOffset, readLength - 1));\n    } else {\n      result.push(line.substring(readOffset));\n    }\n    if (validateElementCount && result.length !== this.fullColumnNames.length) {\n      throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${result}`);\n    }\n    return result;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/microphone_iterator.js\nvar MicrophoneIterator = class extends LazyIterator {\n  constructor(microphoneConfig) {\n    super();\n    this.microphoneConfig = microphoneConfig;\n    this.isClosed = false;\n    this.fftSize = microphoneConfig.fftSize || 1024;\n    const fftSizeLog2 = Math.log2(this.fftSize);\n    if (this.fftSize < 0 || fftSizeLog2 < 4 || fftSizeLog2 > 14 || !Number.isInteger(fftSizeLog2)) {\n      throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);\n    }\n    this.numFrames = microphoneConfig.numFramesPerSpectrogram || 43;\n    this.sampleRateHz = microphoneConfig.sampleRateHz;\n    this.columnTruncateLength = microphoneConfig.columnTruncateLength || this.fftSize;\n    this.audioTrackConstraints = microphoneConfig.audioTrackConstraints;\n    this.smoothingTimeConstant = microphoneConfig.smoothingTimeConstant || 0;\n    this.includeSpectrogram = microphoneConfig.includeSpectrogram === false ? false : true;\n    this.includeWaveform = microphoneConfig.includeWaveform === true ? true : false;\n    if (!this.includeSpectrogram && !this.includeWaveform) {\n      throw new Error(\"Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.\");\n    }\n  }\n  summary() {\n    return `microphone`;\n  }\n  static async create(microphoneConfig = {}) {\n    if (!env().get(\"IS_BROWSER\")) {\n      throw new Error(\"microphone API is only supported in browser environment.\");\n    }\n    const microphoneIterator = new MicrophoneIterator(microphoneConfig);\n    await microphoneIterator.start();\n    return microphoneIterator;\n  }\n  async start() {\n    try {\n      this.stream = await navigator.mediaDevices.getUserMedia({\n        audio: this.audioTrackConstraints == null ? true : this.audioTrackConstraints,\n        video: false\n      });\n    } catch (e2) {\n      throw new Error(`Error thrown while initializing video stream: ${e2.message}`);\n    }\n    if (!this.stream) {\n      throw new Error(\"Could not obtain audio from microphone.\");\n    }\n    const ctxConstructor = window.AudioContext || window.webkitAudioContext;\n    this.audioContext = new ctxConstructor();\n    if (!this.sampleRateHz) {\n      this.sampleRateHz = this.audioContext.sampleRate;\n    } else if (this.audioContext.sampleRate !== this.sampleRateHz) {\n      throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);\n    }\n    const streamSource = this.audioContext.createMediaStreamSource(this.stream);\n    this.analyser = this.audioContext.createAnalyser();\n    this.analyser.fftSize = this.fftSize * 2;\n    this.analyser.smoothingTimeConstant = this.smoothingTimeConstant;\n    streamSource.connect(this.analyser);\n    this.freqData = new Float32Array(this.fftSize);\n    this.timeData = new Float32Array(this.fftSize);\n    return;\n  }\n  async next() {\n    if (this.isClosed) {\n      return { value: null, done: true };\n    }\n    let spectrogramTensor;\n    let waveformTensor;\n    const audioDataQueue = await this.getAudioData();\n    if (this.includeSpectrogram) {\n      const freqData = this.flattenQueue(audioDataQueue.freqDataQueue);\n      spectrogramTensor = this.getTensorFromAudioDataArray(freqData, [this.numFrames, this.columnTruncateLength, 1]);\n    }\n    if (this.includeWaveform) {\n      const timeData = this.flattenQueue(audioDataQueue.timeDataQueue);\n      waveformTensor = this.getTensorFromAudioDataArray(timeData, [this.numFrames * this.fftSize, 1]);\n    }\n    return {\n      value: { \"spectrogram\": spectrogramTensor, \"waveform\": waveformTensor },\n      done: false\n    };\n  }\n  async capture() {\n    return (await this.next()).value;\n  }\n  async getAudioData() {\n    const freqDataQueue = [];\n    const timeDataQueue = [];\n    let currentFrames = 0;\n    return new Promise((resolve) => {\n      const intervalID = setInterval(() => {\n        if (this.includeSpectrogram) {\n          this.analyser.getFloatFrequencyData(this.freqData);\n          if (this.freqData[0] === -Infinity) {\n            resolve({ freqDataQueue, timeDataQueue });\n          }\n          freqDataQueue.push(this.freqData.slice(0, this.columnTruncateLength));\n        }\n        if (this.includeWaveform) {\n          this.analyser.getFloatTimeDomainData(this.timeData);\n          timeDataQueue.push(this.timeData.slice());\n        }\n        if (++currentFrames === this.numFrames) {\n          clearInterval(intervalID);\n          resolve({ freqDataQueue, timeDataQueue });\n        }\n      }, this.fftSize / this.sampleRateHz * 1e3);\n    });\n  }\n  stop() {\n    if (!this.isClosed) {\n      this.isClosed = true;\n      this.analyser.disconnect();\n      this.audioContext.close();\n      if (this.stream != null && this.stream.getTracks().length > 0) {\n        this.stream.getTracks()[0].stop();\n      }\n    }\n  }\n  toArray() {\n    throw new Error(\"Can not convert infinite audio stream to array.\");\n  }\n  getSampleRate() {\n    return this.sampleRateHz;\n  }\n  flattenQueue(queue) {\n    const frameSize = queue[0].length;\n    const freqData = new Float32Array(queue.length * frameSize);\n    queue.forEach((data, i2) => freqData.set(data, i2 * frameSize));\n    return freqData;\n  }\n  getTensorFromAudioDataArray(freqData, shape) {\n    const vals = new Float32Array(util_exports.sizeFromShape(shape));\n    vals.set(freqData, vals.length - freqData.length);\n    return tensor(vals, shape);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/webcam_iterator.js\nvar WebcamIterator = class extends LazyIterator {\n  constructor(webcamVideoElement, webcamConfig) {\n    super();\n    this.webcamVideoElement = webcamVideoElement;\n    this.webcamConfig = webcamConfig;\n    this.isClosed = true;\n    this.resize = false;\n    if (this.needToResize()) {\n      this.resize = true;\n      this.cropSize = [this.webcamConfig.resizeHeight, this.webcamConfig.resizeWidth];\n      this.cropBoxInd = tensor1d([0], \"int32\");\n      if (this.webcamConfig.centerCrop) {\n        const widthCroppingRatio = this.webcamConfig.resizeWidth * 1 / this.webcamVideoElement.width;\n        const heightCroppingRatio = this.webcamConfig.resizeHeight * 1 / this.webcamVideoElement.height;\n        const widthCropStart = (1 - widthCroppingRatio) / 2;\n        const heightCropStart = (1 - heightCroppingRatio) / 2;\n        const widthCropEnd = widthCropStart + widthCroppingRatio;\n        const heightCropEnd = heightCroppingRatio + heightCropStart;\n        this.cropBox = tensor2d([heightCropStart, widthCropStart, heightCropEnd, widthCropEnd], [1, 4]);\n      } else {\n        this.cropBox = tensor2d([0, 0, 1, 1], [1, 4]);\n      }\n    }\n  }\n  summary() {\n    return `webcam`;\n  }\n  static async create(webcamVideoElement, webcamConfig = {}) {\n    if (!env().get(\"IS_BROWSER\")) {\n      throw new Error(\"tf.data.webcam is only supported in browser environment.\");\n    }\n    if (!webcamVideoElement) {\n      webcamVideoElement = document.createElement(\"video\");\n      if (!webcamConfig.resizeWidth || !webcamConfig.resizeHeight) {\n        throw new Error(\"Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.\");\n      }\n      webcamVideoElement.width = webcamConfig.resizeWidth;\n      webcamVideoElement.height = webcamConfig.resizeHeight;\n    }\n    const webcamIterator = new WebcamIterator(webcamVideoElement, webcamConfig);\n    await webcamIterator.start();\n    return webcamIterator;\n  }\n  async start() {\n    if (this.webcamConfig.facingMode) {\n      util_exports.assert(this.webcamConfig.facingMode === \"user\" || this.webcamConfig.facingMode === \"environment\", () => `Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);\n    }\n    try {\n      this.stream = await navigator.mediaDevices.getUserMedia({\n        video: {\n          deviceId: this.webcamConfig.deviceId,\n          facingMode: this.webcamConfig.facingMode ? this.webcamConfig.facingMode : \"user\",\n          width: this.webcamVideoElement.width,\n          height: this.webcamVideoElement.height\n        }\n      });\n    } catch (e2) {\n      e2.message = `Error thrown while initializing video stream: ${e2.message}`;\n      throw e2;\n    }\n    if (!this.stream) {\n      throw new Error(\"Could not obtain video from webcam.\");\n    }\n    try {\n      this.webcamVideoElement.srcObject = this.stream;\n    } catch (error) {\n      console.log(error);\n      this.webcamVideoElement.src = window.URL.createObjectURL(this.stream);\n    }\n    this.webcamVideoElement.play();\n    this.isClosed = false;\n    return new Promise((resolve) => {\n      this.webcamVideoElement.onloadedmetadata = () => {\n        resolve();\n      };\n    });\n  }\n  async next() {\n    if (this.isClosed) {\n      return { value: null, done: true };\n    }\n    let img;\n    try {\n      img = browser_exports.fromPixels(this.webcamVideoElement);\n    } catch (e2) {\n      throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(e2)}`);\n    }\n    if (this.resize) {\n      try {\n        return { value: this.cropAndResizeFrame(img), done: false };\n      } catch (e2) {\n        throw new Error(`Error thrown cropping the video: ${e2.message}`);\n      } finally {\n        img.dispose();\n      }\n    } else {\n      return { value: img, done: false };\n    }\n  }\n  needToResize() {\n    if (this.webcamConfig.resizeWidth && this.webcamConfig.resizeHeight && (this.webcamVideoElement.width !== this.webcamConfig.resizeWidth || this.webcamVideoElement.height !== this.webcamConfig.resizeHeight)) {\n      return true;\n    }\n    return false;\n  }\n  cropAndResizeFrame(img) {\n    return tidy(() => {\n      const expandedImage = expandDims(cast(img, \"float32\"), 0);\n      let resizedImage;\n      resizedImage = image.cropAndResize(expandedImage, this.cropBox, this.cropBoxInd, this.cropSize, \"bilinear\");\n      const shape = resizedImage.shape;\n      return reshape(resizedImage, shape.slice(1));\n    });\n  }\n  async capture() {\n    return (await this.next()).value;\n  }\n  stop() {\n    const tracks = this.stream.getTracks();\n    tracks.forEach((track) => track.stop());\n    try {\n      this.webcamVideoElement.srcObject = null;\n    } catch (error) {\n      console.log(error);\n      this.webcamVideoElement.src = null;\n    }\n    this.isClosed = true;\n  }\n  toArray() {\n    throw new Error(\"Can not convert infinite video stream to array.\");\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/datasource.js\nvar DataSource = class {\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/string_iterator.js\nvar StringIterator = class extends LazyIterator {\n  split(separator) {\n    return new SplitIterator(this, separator);\n  }\n};\nvar SplitIterator = class extends StringIterator {\n  constructor(upstream, separator) {\n    super();\n    this.upstream = upstream;\n    this.impl = new SplitIteratorImpl(upstream, separator);\n  }\n  summary() {\n    return this.impl.summary();\n  }\n  async next() {\n    return this.impl.next();\n  }\n};\nvar SplitIteratorImpl = class extends OneToManyIterator {\n  constructor(upstream, separator) {\n    super();\n    this.upstream = upstream;\n    this.separator = separator;\n    this.carryover = \"\";\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Split('${this.separator}')`;\n  }\n  async pump() {\n    const chunkResult = await this.upstream.next();\n    if (chunkResult.done) {\n      if (this.carryover === \"\") {\n        return false;\n      }\n      this.outputQueue.push(this.carryover);\n      this.carryover = \"\";\n      return true;\n    }\n    const lines = chunkResult.value.split(this.separator);\n    lines[0] = this.carryover + lines[0];\n    for (const line of lines.slice(0, -1)) {\n      this.outputQueue.push(line);\n    }\n    this.carryover = lines[lines.length - 1];\n    return true;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/byte_chunk_iterator.js\nvar ByteChunkIterator = class extends LazyIterator {\n  decodeUTF8() {\n    return new Utf8Iterator(this);\n  }\n};\nvar Utf8Iterator = class extends StringIterator {\n  constructor(upstream) {\n    super();\n    this.upstream = upstream;\n    this.impl = new Utf8IteratorImpl(upstream);\n  }\n  summary() {\n    return this.impl.summary();\n  }\n  async next() {\n    return this.impl.next();\n  }\n};\nvar Utf8IteratorImpl = class extends OneToManyIterator {\n  constructor(upstream) {\n    super();\n    this.upstream = upstream;\n    if (env().get(\"IS_BROWSER\")) {\n      this.decoder = new TextDecoder(\"utf-8\");\n    } else {\n      const { StringDecoder } = require_string_decoder();\n      this.decoder = new StringDecoder(\"utf8\");\n    }\n  }\n  summary() {\n    return `${this.upstream.summary()} -> Utf8`;\n  }\n  async pump() {\n    const chunkResult = await this.upstream.next();\n    let chunk;\n    if (chunkResult.done) {\n      return false;\n    } else {\n      chunk = chunkResult.value;\n    }\n    let text;\n    if (env().get(\"IS_BROWSER\")) {\n      text = this.decoder.decode(chunk, { stream: true });\n    } else {\n      text = this.decoder.write(Buffer.from(chunk.buffer));\n    }\n    this.outputQueue.push(text);\n    return true;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/file_chunk_iterator.js\nvar FileChunkIterator = class extends ByteChunkIterator {\n  constructor(file, options = {}) {\n    super();\n    this.file = file;\n    this.options = options;\n    util_exports.assert(file instanceof Uint8Array || (env().get(\"IS_BROWSER\") ? file instanceof File || file instanceof Blob : false), () => \"FileChunkIterator only supports File, Blob and Uint8Array right now.\");\n    this.offset = options.offset || 0;\n    this.chunkSize = options.chunkSize || 1024 * 1024;\n  }\n  summary() {\n    return `FileChunks ${this.file}`;\n  }\n  async next() {\n    if (this.offset >= (this.file instanceof Uint8Array ? this.file.byteLength : this.file.size)) {\n      return { value: null, done: true };\n    }\n    const chunk = new Promise((resolve, reject) => {\n      const end = this.offset + this.chunkSize;\n      if (this.file instanceof Uint8Array) {\n        resolve(new Uint8Array(this.file.slice(this.offset, end)));\n      } else {\n        const fileReader = new FileReader();\n        fileReader.onload = (event) => {\n          let data = fileReader.result;\n          if (data instanceof ArrayBuffer) {\n            data = new Uint8Array(data);\n          }\n          if (!(data instanceof Uint8Array)) {\n            return reject(new TypeError(\"FileReader returned unknown type.\"));\n          }\n          resolve(data);\n        };\n        fileReader.onabort = (event) => {\n          return reject(new Error(\"Aborted\"));\n        };\n        fileReader.onerror = (event) => {\n          return reject(new Error(event.type));\n        };\n        const slice6 = this.file.slice(this.offset, end);\n        fileReader.readAsArrayBuffer(slice6);\n      }\n      this.offset = end;\n    });\n    return { value: await chunk, done: false };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/iterators/url_chunk_iterator.js\nasync function urlChunkIterator(url, options = {}, fetchFunc) {\n  let urlString;\n  let requestInit;\n  if (typeof url === \"string\") {\n    urlString = url;\n  } else {\n    urlString = url.url;\n    requestInit = getRequestInitFromRequest(url);\n  }\n  const response = await (fetchFunc || util_exports.fetch)(urlString, requestInit);\n  if (response.ok) {\n    const uint8Array = new Uint8Array(await response.arrayBuffer());\n    return new FileChunkIterator(uint8Array, options);\n  } else {\n    throw new Error(response.statusText);\n  }\n}\nvar getRequestInitFromRequest = (request) => {\n  const init2 = {\n    method: request.method,\n    headers: request.headers,\n    body: request.body,\n    mode: request.mode,\n    credentials: request.credentials,\n    cache: request.cache,\n    redirect: request.redirect,\n    referrer: request.referrer,\n    integrity: request.integrity\n  };\n  return init2;\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/util/source_util.js\nfunction isLocalPath(source) {\n  return typeof source === \"string\" && source.slice(0, 7) === \"file://\";\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/sources/file_data_source.js\nvar FileDataSource = class extends DataSource {\n  constructor(input2, options = {}) {\n    super();\n    this.input = input2;\n    this.options = options;\n  }\n  async iterator() {\n    if (isLocalPath(this.input) && env().get(\"IS_NODE\")) {\n      const fs = require_fs();\n      this.input = fs.readFileSync(this.input.slice(7));\n    }\n    return new FileChunkIterator(this.input, this.options);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/sources/url_data_source.js\nvar URLDataSource = class extends DataSource {\n  constructor(url, fileOptions = {}) {\n    super();\n    this.url = url;\n    this.fileOptions = fileOptions;\n  }\n  async iterator() {\n    if (isLocalPath(this.url)) {\n      return new FileDataSource(this.url, this.fileOptions).iterator();\n    } else {\n      return urlChunkIterator(this.url, this.fileOptions);\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/readers.js\nfunction csv(source, csvConfig = {}) {\n  return new CSVDataset(new URLDataSource(source), csvConfig);\n}\nfunction func(f) {\n  const iter = iteratorFromFunction(f);\n  return datasetFromIteratorFn(async () => iter);\n}\nfunction generator(generator2) {\n  return datasetFromIteratorFn(async () => {\n    const gen = await generator2();\n    return iteratorFromFunction(() => gen.next());\n  });\n}\nasync function webcam(webcamVideoElement, webcamConfig) {\n  return WebcamIterator.create(webcamVideoElement, webcamConfig);\n}\nasync function microphone(microphoneConfig) {\n  return MicrophoneIterator.create(microphoneConfig);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-data@3.19.0_umkohei6j4f2ojerldjngreig4/node_modules/@tensorflow/tfjs-data/dist/version.js\nvar version4 = \"3.19.0\";\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/cpu_util.js\nfunction assertNotComplex(tensor2, opName) {\n  if (!Array.isArray(tensor2)) {\n    tensor2 = [tensor2];\n  }\n  tensor2.forEach((t2) => {\n    if (t2 != null) {\n      util_exports.assert(t2.dtype !== \"complex64\", () => `${opName} does not support complex64 tensors in the CPU backend.`);\n    }\n  });\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/backend_cpu.js\nvar whereImpl2 = kernel_impls_exports.whereImpl;\nvar MathBackendCPU = class extends KernelBackend {\n  constructor() {\n    super();\n    this.blockSize = 48;\n    this.firstUse = true;\n    this.data = new DataStorage(this, engine());\n  }\n  nextDataId() {\n    return MathBackendCPU.nextDataId++;\n  }\n  write(values, shape, dtype) {\n    if (this.firstUse) {\n      this.firstUse = false;\n      if (env().get(\"IS_NODE\")) {\n        backend_util_exports.warn(\"\\n============================\\nHi, looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, visit https://github.com/tensorflow/tfjs-node for more details. \\n============================\");\n      }\n    }\n    const dataId = { id: this.nextDataId() };\n    this.data.set(dataId, { values, dtype, refCount: 1 });\n    return dataId;\n  }\n  makeTensorInfo(shape, dtype, values) {\n    let outId;\n    if (dtype === \"string\" && values != null && values.length > 0 && util_exports.isString(values[0])) {\n      const encodedValues = values.map((d) => util_exports.encodeString(d));\n      outId = this.write(encodedValues, shape, dtype);\n    } else {\n      outId = this.write(values, shape, dtype);\n    }\n    return { dataId: outId, shape, dtype };\n  }\n  refCount(dataId) {\n    if (this.data.has(dataId)) {\n      const tensorData = this.data.get(dataId);\n      return tensorData.refCount;\n    }\n    return 0;\n  }\n  incRef(dataId) {\n    const tensorData = this.data.get(dataId);\n    tensorData.refCount++;\n  }\n  decRef(dataId) {\n    if (this.data.has(dataId)) {\n      const tensorData = this.data.get(dataId);\n      tensorData.refCount--;\n    }\n  }\n  move(dataId, values, shape, dtype, refCount) {\n    this.data.set(dataId, { values, dtype, refCount });\n  }\n  numDataIds() {\n    return this.data.numDataIds();\n  }\n  async read(dataId) {\n    return this.readSync(dataId);\n  }\n  readSync(dataId) {\n    const { dtype, complexTensorInfos } = this.data.get(dataId);\n    if (dtype === \"complex64\") {\n      const realValues = this.readSync(complexTensorInfos.real.dataId);\n      const imagValues = this.readSync(complexTensorInfos.imag.dataId);\n      return backend_util_exports.mergeRealAndImagArrays(realValues, imagValues);\n    }\n    return this.data.get(dataId).values;\n  }\n  bufferSync(t2) {\n    const data = this.readSync(t2.dataId);\n    if (t2.dtype === \"string\") {\n      try {\n        const strings = data.map((d) => util_exports.decodeString(d));\n        return buffer(t2.shape, t2.dtype, strings);\n      } catch (_a) {\n        throw new Error(\"Failed to decode encoded string bytes into utf-8\");\n      }\n    }\n    return buffer(t2.shape, t2.dtype, data);\n  }\n  makeOutput(values, shape, dtype) {\n    return engine().makeTensorFromTensorInfo(this.makeTensorInfo(shape, dtype, values), this);\n  }\n  disposeData(dataId, force = false) {\n    if (this.data.has(dataId)) {\n      this.data.get(dataId).refCount--;\n      if (!force && this.data.get(dataId).refCount > 0) {\n        return false;\n      }\n      const { complexTensorInfos } = this.data.get(dataId);\n      if (complexTensorInfos != null) {\n        this.disposeData(complexTensorInfos.real.dataId, true);\n        this.disposeData(complexTensorInfos.imag.dataId, true);\n      }\n      this.data.delete(dataId);\n    }\n    return true;\n  }\n  disposeIntermediateTensorInfo(tensorInfo) {\n    this.disposeData(tensorInfo.dataId);\n  }\n  async time(f) {\n    const start = util_exports.now();\n    f();\n    const kernelMs = util_exports.now() - start;\n    return { kernelMs };\n  }\n  memory() {\n    return {\n      unreliable: true,\n      reasons: [\"The reported memory is an upper bound. Due to automatic garbage collection, the true allocated memory may be less.\"]\n    };\n  }\n  where(condition) {\n    assertNotComplex([condition], \"where\");\n    const condVals = this.readSync(condition.dataId);\n    return whereImpl2(condition.shape, condVals);\n  }\n  dispose() {\n  }\n  floatPrecision() {\n    return 32;\n  }\n  epsilon() {\n    return super.epsilon();\n  }\n};\nMathBackendCPU.nextDataId = 0;\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/shared.js\nvar shared_exports = {};\n__export(shared_exports, {\n  addImpl: () => addImpl,\n  bincountImpl: () => bincountImpl,\n  bincountReduceImpl: () => bincountReduceImpl,\n  ceilImpl: () => ceilImpl,\n  concatImpl: () => concatImpl,\n  equalImpl: () => equalImpl,\n  expImpl: () => expImpl,\n  expm1Impl: () => expm1Impl,\n  floorImpl: () => floorImpl,\n  gatherNdImpl: () => gatherNdImpl,\n  gatherV2Impl: () => gatherV2Impl,\n  greaterEqualImpl: () => greaterEqualImpl,\n  greaterImpl: () => greaterImpl,\n  lessEqualImpl: () => lessEqualImpl,\n  lessImpl: () => lessImpl,\n  linSpaceImpl: () => linSpaceImpl,\n  logImpl: () => logImpl,\n  maxImpl: () => maxImpl,\n  maximumImpl: () => maximumImpl,\n  minimumImpl: () => minimumImpl,\n  multiplyImpl: () => multiplyImpl,\n  negImpl: () => negImpl,\n  notEqualImpl: () => notEqualImpl,\n  prodImpl: () => prodImpl,\n  rangeImpl: () => rangeImpl,\n  rsqrtImpl: () => rsqrtImpl,\n  scatterImpl: () => scatterImpl,\n  sigmoidImpl: () => sigmoidImpl,\n  simpleAbsImpl: () => simpleAbsImpl,\n  sliceImpl: () => sliceImpl,\n  sparseFillEmptyRowsImpl: () => sparseFillEmptyRowsImpl,\n  sparseReshapeImpl: () => sparseReshapeImpl,\n  sparseSegmentReductionImpl: () => sparseSegmentReductionImpl,\n  sqrtImpl: () => sqrtImpl,\n  squaredDifferenceImpl: () => squaredDifferenceImpl,\n  stridedSliceImpl: () => stridedSliceImpl,\n  stringNGramsImpl: () => stringNGramsImpl,\n  stringSplitImpl: () => stringSplitImpl,\n  stringToHashBucketFastImpl: () => stringToHashBucketFastImpl,\n  subImpl: () => subImpl,\n  tileImpl: () => tileImpl,\n  topKImpl: () => topKImpl,\n  transposeImpl: () => transposeImpl,\n  uniqueImpl: () => uniqueImpl\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Abs.js\nfunction simpleAbsImpl(vals) {\n  const resultValues = new Float32Array(vals.length);\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    resultValues[i2] = Math.abs(vals[i2]);\n  }\n  return resultValues;\n}\nvar abs2 = (args) => {\n  const { x } = args.inputs;\n  const cpuBackend = args.backend;\n  assertNotComplex(x, \"abs\");\n  let resultValues = new Float32Array(util_exports.sizeFromShape(x.shape));\n  const values = cpuBackend.data.get(x.dataId).values;\n  resultValues = simpleAbsImpl(values);\n  return cpuBackend.makeOutput(resultValues, x.shape, x.dtype);\n};\nvar absConfig = {\n  kernelName: Abs,\n  backendName: \"cpu\",\n  kernelFunc: abs2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/binary_impl.js\nfunction createSimpleBinaryKernelImpl(op2) {\n  return (aShape, bShape, aVals, bVals, dtype) => {\n    const newShape = backend_util_exports.assertAndGetBroadcastShape(aShape, bShape);\n    const resultRank = newShape.length;\n    const resultStrides = util_exports.computeStrides(newShape);\n    const resultSize = util_exports.sizeFromShape(newShape);\n    const result = util_exports.getTypedArrayFromDType(dtype, resultSize);\n    const aRank = aShape.length;\n    const bRank = bShape.length;\n    const aStrides = util_exports.computeStrides(aShape);\n    const bStrides = util_exports.computeStrides(bShape);\n    const aBroadcastDims = backend_util_exports.getBroadcastDims(aShape, newShape);\n    const bBroadcastDims = backend_util_exports.getBroadcastDims(bShape, newShape);\n    if (aBroadcastDims.length + bBroadcastDims.length === 0) {\n      for (let i2 = 0; i2 < result.length; ++i2) {\n        result[i2] = op2(aVals[i2 % aVals.length], bVals[i2 % bVals.length]);\n      }\n    } else {\n      for (let i2 = 0; i2 < result.length; ++i2) {\n        const loc = util_exports.indexToLoc(i2, resultRank, resultStrides);\n        const aLoc = loc.slice(-aRank);\n        aBroadcastDims.forEach((d) => aLoc[d] = 0);\n        const aIndex = util_exports.locToIndex(aLoc, aRank, aStrides);\n        const bLoc = loc.slice(-bRank);\n        bBroadcastDims.forEach((d) => bLoc[d] = 0);\n        const bIndex = util_exports.locToIndex(bLoc, bRank, bStrides);\n        result[i2] = op2(aVals[aIndex], bVals[bIndex]);\n      }\n    }\n    return [result, newShape];\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Complex.js\nfunction complex2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { real: real5, imag: imag5 } = inputs;\n  const realVals = backend2.data.get(real5.dataId).values;\n  const imagVals = backend2.data.get(imag5.dataId).values;\n  const complexInfo = backend2.makeTensorInfo(real5.shape, \"complex64\");\n  const complex5 = backend2.data.get(complexInfo.dataId);\n  complex5.complexTensorInfos = {\n    real: backend2.makeTensorInfo(real5.shape, \"float32\", realVals),\n    imag: backend2.makeTensorInfo(imag5.shape, \"float32\", imagVals)\n  };\n  return complexInfo;\n}\nvar complexConfig = {\n  kernelName: Complex,\n  backendName: \"cpu\",\n  kernelFunc: complex2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/zeros_impl.js\nfunction zeros3(backend2, shape, dtype = \"float32\") {\n  if (dtype === \"complex64\") {\n    const real5 = zeros3(backend2, shape, \"float32\");\n    const imag5 = zeros3(backend2, shape, \"float32\");\n    return complex2({ inputs: { real: real5, imag: imag5 }, backend: backend2 });\n  }\n  const values = util_exports.makeZerosTypedArray(util_exports.sizeFromShape(shape), dtype);\n  return backend2.makeTensorInfo(shape, dtype, values);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Identity.js\nfunction identity2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  backend2.incRef(x.dataId);\n  return { dataId: x.dataId, shape: x.shape, dtype: x.dtype };\n}\nvar identityConfig = {\n  kernelName: Identity,\n  backendName: \"cpu\",\n  kernelFunc: identity2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Real.js\nfunction real2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const real5 = backend2.data.get(input2.dataId).complexTensorInfos.real;\n  const realVal = backend2.data.get(real5.dataId).values;\n  return backend2.makeTensorInfo(real5.shape, real5.dtype, realVal);\n}\nvar realConfig = {\n  kernelName: Real,\n  backendName: \"cpu\",\n  kernelFunc: real2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Cast.js\nfunction cast3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { dtype } = attrs;\n  if (dtype === \"complex64\") {\n    if (x.dtype === \"complex64\") {\n      return identity2({ inputs: { x }, backend: backend2 });\n    }\n    const zerosTensorInfo = zeros3(backend2, x.shape, x.dtype);\n    const floatX = cast3({ inputs: { x }, backend: backend2, attrs: { dtype: \"float32\" } });\n    const result = complex2({ inputs: { real: floatX, imag: zerosTensorInfo }, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(zerosTensorInfo);\n    backend2.disposeIntermediateTensorInfo(floatX);\n    return result;\n  }\n  if (x.dtype === \"complex64\") {\n    const realPart = real2({ inputs: { input: x }, backend: backend2 });\n    const result = cast3({ inputs: { x: realPart }, backend: backend2, attrs: { dtype } });\n    backend2.disposeIntermediateTensorInfo(realPart);\n    return result;\n  }\n  if (!util_exports.hasEncodingLoss(x.dtype, dtype)) {\n    const result = identity2({ inputs: { x }, backend: backend2 });\n    return { dataId: result.dataId, shape: result.shape, dtype };\n  }\n  if (dtype === \"int32\") {\n    const values = backend2.data.get(x.dataId).values;\n    const resultValues = Int32Array.from(values);\n    return backend2.makeTensorInfo(x.shape, \"int32\", resultValues);\n  }\n  if (dtype === \"bool\") {\n    const xVals = backend2.data.get(x.dataId).values;\n    const zero = util_exports.toTypedArray([0], x.dtype);\n    const [resultData, resultShape] = createSimpleBinaryKernelImpl((a, b) => a !== b ? 1 : 0)(x.shape, [], xVals, zero, \"bool\");\n    return backend2.makeTensorInfo(resultShape, \"bool\", resultData);\n  }\n  throw new Error(`Error in Cast: failed to cast ${x.dtype} to ${dtype}`);\n}\nvar castConfig = {\n  kernelName: Cast,\n  backendName: \"cpu\",\n  kernelFunc: cast3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/binary_utils.js\nfunction binaryKernelFunc(name, simpleImpl, complexImpl, dtype) {\n  if (complexImpl == null) {\n    return ({ inputs, backend: backend2 }) => {\n      const { a, b } = inputs;\n      const cpuBackend = backend2;\n      assertNotComplex([a, b], name);\n      const aVals = cpuBackend.data.get(a.dataId).values;\n      const bVals = cpuBackend.data.get(b.dataId).values;\n      const decodedAVals = a.dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(aVals) : aVals;\n      const decodedBVals = a.dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(bVals) : bVals;\n      const $dtype = dtype || a.dtype;\n      const [resultData, resultShape] = simpleImpl(a.shape, b.shape, decodedAVals, decodedBVals, $dtype);\n      return cpuBackend.makeTensorInfo(resultShape, $dtype, resultData);\n    };\n  }\n  return ({ inputs, backend: backend2 }) => {\n    const { a, b } = inputs;\n    const cpuBackend = backend2;\n    if (a.dtype === \"complex64\" || b.dtype === \"complex64\") {\n      const $aComplex = cast3({ inputs: { x: a }, backend: cpuBackend, attrs: { dtype: \"complex64\" } });\n      const $aComplexVals = cpuBackend.data.get($aComplex.dataId);\n      const aReal = $aComplexVals.complexTensorInfos.real;\n      const aImag = $aComplexVals.complexTensorInfos.imag;\n      const aRealVals = cpuBackend.data.get(aReal.dataId).values;\n      const aImagVals = cpuBackend.data.get(aImag.dataId).values;\n      const $bComplex = cast3({ inputs: { x: b }, backend: cpuBackend, attrs: { dtype: \"complex64\" } });\n      const $bComplexVals = cpuBackend.data.get($bComplex.dataId);\n      const bReal = $bComplexVals.complexTensorInfos.real;\n      const bImag = $bComplexVals.complexTensorInfos.imag;\n      const bRealVals = cpuBackend.data.get(bReal.dataId).values;\n      const bImagVals = cpuBackend.data.get(bImag.dataId).values;\n      const [resultRealData, resultImagData, resultShape] = complexImpl(a.shape, b.shape, aRealVals, aImagVals, bRealVals, bImagVals);\n      const resultReal = cpuBackend.makeTensorInfo(resultShape, \"float32\", resultRealData);\n      const resultImag = cpuBackend.makeTensorInfo(resultShape, \"float32\", resultImagData);\n      const result = complex2({ inputs: { real: resultReal, imag: resultImag }, backend: cpuBackend });\n      cpuBackend.disposeIntermediateTensorInfo($aComplex);\n      cpuBackend.disposeIntermediateTensorInfo($bComplex);\n      cpuBackend.disposeIntermediateTensorInfo(resultReal);\n      cpuBackend.disposeIntermediateTensorInfo(resultImag);\n      return result;\n    } else {\n      const aVals = cpuBackend.data.get(a.dataId).values;\n      const bVals = cpuBackend.data.get(b.dataId).values;\n      const $dtype = dtype || a.dtype;\n      const [resultData, resultShape] = simpleImpl(a.shape, b.shape, aVals, bVals, $dtype);\n      return cpuBackend.makeTensorInfo(resultShape, $dtype, resultData);\n    }\n  };\n}\nfunction createComplexBinaryKernelImpl(op2) {\n  return (aShape, bShape, aRealVals, aImagVals, bRealVals, bImagVals) => {\n    const resultShape = backend_util_exports.assertAndGetBroadcastShape(aShape, bShape);\n    const resultSize = util_exports.sizeFromShape(resultShape);\n    const resultRank = resultShape.length;\n    const resultStrides = util_exports.computeStrides(resultShape);\n    const resultRealVals = util_exports.getTypedArrayFromDType(\"float32\", resultSize);\n    const resultImagVals = util_exports.getTypedArrayFromDType(\"float32\", resultSize);\n    const aBroadcastDims = backend_util_exports.getBroadcastDims(aShape, resultShape);\n    const bBroadcastDims = backend_util_exports.getBroadcastDims(bShape, resultShape);\n    const aVals = backend_util_exports.mergeRealAndImagArrays(aRealVals, aImagVals);\n    const bVals = backend_util_exports.mergeRealAndImagArrays(bRealVals, bImagVals);\n    const aRank = aShape.length;\n    const aStrides = util_exports.computeStrides(aShape);\n    const bRank = bShape.length;\n    const bStrides = util_exports.computeStrides(bShape);\n    if (aBroadcastDims.length + bBroadcastDims.length === 0) {\n      for (let i2 = 0; i2 < resultRealVals.length; i2++) {\n        const aIdx = i2 % aVals.length;\n        const bIdx = i2 % bVals.length;\n        const result = op2(aVals[aIdx * 2], aVals[aIdx * 2 + 1], bVals[bIdx * 2], bVals[bIdx * 2 + 1]);\n        resultRealVals[i2] = result.real;\n        resultImagVals[i2] = result.imag;\n      }\n    } else {\n      for (let i2 = 0; i2 < resultRealVals.length; i2++) {\n        const loc = util_exports.indexToLoc(i2, resultRank, resultStrides);\n        const aLoc = loc.slice(-aRank);\n        aBroadcastDims.forEach((d) => aLoc[d] = 0);\n        const aIndex = util_exports.locToIndex(aLoc, aRank, aStrides);\n        const bLoc = loc.slice(-bRank);\n        bBroadcastDims.forEach((d) => bLoc[d] = 0);\n        const bIndex = util_exports.locToIndex(bLoc, bRank, bStrides);\n        const opResult = op2(aVals[aIndex * 2], aVals[aIndex * 2 + 1], bVals[bIndex * 2], bVals[bIndex * 2 + 1]);\n        resultRealVals[i2] = opResult.real;\n        resultImagVals[i2] = opResult.imag;\n      }\n    }\n    return [resultRealVals, resultImagVals, resultShape];\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Add.js\nvar addImpl = createSimpleBinaryKernelImpl((a, b) => a + b);\nvar addComplexImpl = createComplexBinaryKernelImpl((aReal, aImag, bReal, bImag) => {\n  return { real: aReal + bReal, imag: aImag + bImag };\n});\nvar add4 = binaryKernelFunc(Add, addImpl, addComplexImpl);\nvar addConfig = {\n  kernelName: Add,\n  backendName: \"cpu\",\n  kernelFunc: add4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Bincount_impl.js\nfunction bincountImpl(xVals, weightsVals, weightsDtype, weightsShape, size) {\n  const weightsSize = util_exports.sizeFromShape(weightsShape);\n  const outVals = util_exports.makeZerosTypedArray(size, weightsDtype);\n  for (let i2 = 0; i2 < xVals.length; i2++) {\n    const value = xVals[i2];\n    if (value < 0) {\n      throw new Error(\"Input x must be non-negative!\");\n    }\n    if (value >= size) {\n      continue;\n    }\n    if (weightsSize > 0) {\n      outVals[value] += weightsVals[i2];\n    } else {\n      outVals[value] += 1;\n    }\n  }\n  return outVals;\n}\nfunction bincountReduceImpl(xBuf, weightsBuf, size, binaryOutput = false) {\n  const numRows = xBuf.shape[0];\n  const numCols = xBuf.shape[1];\n  const outBuf = buffer([numRows, size], weightsBuf.dtype);\n  for (let i2 = 0; i2 < numRows; i2++) {\n    for (let j = 0; j < numCols; j++) {\n      const value = xBuf.get(i2, j);\n      if (value < 0) {\n        throw new Error(\"Input x must be non-negative!\");\n      }\n      if (value >= size) {\n        continue;\n      }\n      if (binaryOutput) {\n        outBuf.set(1, i2, value);\n      } else {\n        if (weightsBuf.size > 0) {\n          outBuf.set(outBuf.get(i2, value) + weightsBuf.get(i2, j), i2, value);\n        } else {\n          outBuf.set(outBuf.get(i2, value) + 1, i2, value);\n        }\n      }\n    }\n  }\n  return outBuf;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/unary_impl.js\nfunction createSimpleUnaryImpl(op2) {\n  return (values, dtype, attrs) => {\n    const newValues = util_exports.getTypedArrayFromDType(dtype, values.length);\n    for (let i2 = 0; i2 < values.length; ++i2) {\n      newValues[i2] = op2(values[i2], attrs);\n    }\n    return newValues;\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/unary_utils.js\nfunction unaryKernelFunc(name, op2, dtype) {\n  return ({ inputs, attrs, backend: backend2 }) => {\n    const { x } = inputs;\n    assertNotComplex(x, name);\n    if (x.dtype === \"string\" || dtype === \"string\") {\n      throw new Error(\"unaryKernelFunc does not support string input/output\");\n    }\n    const cpuBackend = backend2;\n    const values = cpuBackend.data.get(x.dataId).values;\n    const xSize = util_exports.sizeFromShape(x.shape);\n    const $dtype = dtype || x.dtype;\n    const newValues = util_exports.getArrayFromDType($dtype, xSize);\n    for (let i2 = 0; i2 < xSize; ++i2) {\n      newValues[i2] = op2(values[i2], attrs);\n    }\n    return cpuBackend.makeTensorInfo(x.shape, $dtype, newValues);\n  };\n}\nfunction unaryKernelFuncFromImpl(name, unaryImpl, dtype) {\n  return ({ inputs, attrs, backend: backend2 }) => {\n    const { x } = inputs;\n    assertNotComplex(x, name);\n    if (x.dtype === \"string\" || dtype === \"string\") {\n      throw new Error(\"unaryKernelFunc does not support string input/output\");\n    }\n    const cpuBackend = backend2;\n    const values = cpuBackend.data.get(x.dataId).values;\n    const $dtype = dtype || x.dtype;\n    const newValues = unaryImpl(values, $dtype, attrs);\n    return cpuBackend.makeTensorInfo(x.shape, $dtype, newValues);\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Ceil.js\nvar ceilImpl = createSimpleUnaryImpl((xi) => Math.ceil(xi));\nvar ceil2 = unaryKernelFuncFromImpl(Ceil, ceilImpl);\nvar ceilConfig = {\n  kernelName: Ceil,\n  backendName: \"cpu\",\n  kernelFunc: ceil2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Concat_impl.js\nfunction concatImpl(inputs, outShape, dtype, simplyConcat) {\n  const outVals = util_exports.getArrayFromDType(dtype, util_exports.sizeFromShape(outShape));\n  if (simplyConcat && dtype !== \"string\") {\n    let offset = 0;\n    inputs.forEach((input2) => {\n      const size = util_exports.sizeFromShape(input2.shape);\n      outVals.set(input2.vals, offset);\n      offset += size;\n    });\n  } else {\n    let colOffset = 0;\n    inputs.forEach((input2) => {\n      const decodedData = dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(input2.vals) : input2.vals;\n      let tIdx = 0;\n      for (let row = 0; row < input2.shape[0]; ++row) {\n        const resIdx = row * outShape[1] + colOffset;\n        for (let col = 0; col < input2.shape[1]; ++col) {\n          outVals[resIdx + col] = decodedData[tIdx++];\n        }\n      }\n      colOffset += input2.shape[1];\n    });\n  }\n  return outVals;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Equal.js\nvar equalImpl = createSimpleBinaryKernelImpl((a, b) => a === b ? 1 : 0);\nvar equal2 = binaryKernelFunc(Equal, equalImpl, null, \"bool\");\nvar equalConfig = {\n  kernelName: Equal,\n  backendName: \"cpu\",\n  kernelFunc: equal2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Exp.js\nvar expImpl = createSimpleUnaryImpl((xi) => Math.exp(xi));\nvar exp2 = unaryKernelFuncFromImpl(Exp, expImpl, \"float32\");\nvar expConfig = {\n  kernelName: Exp,\n  backendName: \"cpu\",\n  kernelFunc: exp2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Expm1.js\nvar expm1Impl = createSimpleUnaryImpl((xi) => Math.expm1(xi));\nvar expm12 = unaryKernelFuncFromImpl(Expm1, expm1Impl);\nvar expm1Config = {\n  kernelName: Expm1,\n  backendName: \"cpu\",\n  kernelFunc: expm12\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Floor.js\nvar floorImpl = createSimpleUnaryImpl((xi) => Math.floor(xi));\nvar floor2 = unaryKernelFuncFromImpl(Floor, floorImpl);\nvar floorConfig = {\n  kernelName: Floor,\n  backendName: \"cpu\",\n  kernelFunc: floor2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/GatherNd_Impl.js\nfunction gatherNdImpl(indicesData, paramsBuf, dtype, numSlices, sliceRank, sliceSize, strides, paramsShape, paramsSize) {\n  const outBuf = buffer([numSlices, sliceSize], dtype);\n  for (let i2 = 0; i2 < numSlices; i2++) {\n    const index = [];\n    let flattenIndex = 0;\n    for (let j = 0; j < sliceRank; j++) {\n      const dim = indicesData[i2 * sliceRank + j];\n      flattenIndex += dim * strides[j];\n      index.push(dim);\n    }\n    if (flattenIndex < 0 || flattenIndex >= paramsSize / sliceSize) {\n      throw new Error(`Invalid indices: ${index} does not index into ${paramsShape}`);\n    }\n    for (let k = 0; k < sliceSize; k++) {\n      outBuf.values[i2 * sliceSize + k] = paramsBuf.get(...paramsBuf.indexToLoc(flattenIndex * sliceSize + k));\n    }\n  }\n  return outBuf;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/GatherV2_impl.js\nfunction gatherV2Impl(xBuf, indicesBuf, flattenOutputShape) {\n  const outBuf = buffer(flattenOutputShape, xBuf.dtype);\n  for (let i2 = 0; i2 < outBuf.size; ++i2) {\n    const newLoc = outBuf.indexToLoc(i2);\n    const originalLoc = newLoc.slice();\n    const batchIdx = originalLoc[0];\n    const indicesIdx = originalLoc[2];\n    const indicesIndex = indicesBuf.locToIndex([batchIdx, indicesIdx]);\n    originalLoc[2] = indicesBuf.values[indicesIndex];\n    const originalIndex = xBuf.locToIndex(originalLoc);\n    if (0 <= originalIndex && originalIndex < xBuf.values.length) {\n      outBuf.values[i2] = xBuf.values[originalIndex];\n    }\n  }\n  return outBuf;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Greater.js\nvar greaterImpl = createSimpleBinaryKernelImpl((a, b) => a > b ? 1 : 0);\nvar greater3 = binaryKernelFunc(Greater, greaterImpl, null, \"bool\");\nvar greaterConfig = {\n  kernelName: Greater,\n  backendName: \"cpu\",\n  kernelFunc: greater3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/GreaterEqual.js\nvar greaterEqualImpl = createSimpleBinaryKernelImpl((a, b) => a >= b ? 1 : 0);\nvar greaterEqual2 = binaryKernelFunc(GreaterEqual, greaterEqualImpl, null, \"bool\");\nvar greaterEqualConfig = {\n  kernelName: GreaterEqual,\n  backendName: \"cpu\",\n  kernelFunc: greaterEqual2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Less.js\nvar lessImpl = createSimpleBinaryKernelImpl((a, b) => a < b ? 1 : 0);\nvar less3 = binaryKernelFunc(Less, lessImpl, null, \"bool\");\nvar lessConfig = {\n  kernelName: Less,\n  backendName: \"cpu\",\n  kernelFunc: less3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LessEqual.js\nvar lessEqualImpl = createSimpleBinaryKernelImpl((a, b) => a <= b ? 1 : 0);\nvar lessEqual2 = binaryKernelFunc(LessEqual, lessEqualImpl, null, \"bool\");\nvar lessEqualConfig = {\n  kernelName: LessEqual,\n  backendName: \"cpu\",\n  kernelFunc: lessEqual2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LinSpace_impl.js\nfunction linSpaceImpl(start, stop, num) {\n  const step5 = (stop - start) / (num - 1);\n  const values = util_exports.makeZerosTypedArray(num, \"float32\");\n  values[0] = start;\n  for (let i2 = 1; i2 < values.length; i2++) {\n    values[i2] = values[i2 - 1] + step5;\n  }\n  return values;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Log.js\nvar logImpl = createSimpleUnaryImpl((xi) => Math.log(xi));\nvar log3 = unaryKernelFuncFromImpl(Log, logImpl);\nvar logConfig = {\n  kernelName: Log,\n  backendName: \"cpu\",\n  kernelFunc: log3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Max_impl.js\nfunction maxImpl(aVals, reduceSize, outShape, dtype) {\n  const vals = util_exports.getTypedArrayFromDType(dtype, util_exports.sizeFromShape(outShape));\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let max7 = aVals[offset];\n    for (let j = 0; j < reduceSize; ++j) {\n      const value = aVals[offset + j];\n      if (Number.isNaN(value) || value > max7) {\n        max7 = value;\n      }\n    }\n    vals[i2] = max7;\n  }\n  return vals;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Maximum.js\nvar maximumImpl = createSimpleBinaryKernelImpl((aValue, bValue) => Math.max(aValue, bValue));\nvar maximum3 = binaryKernelFunc(Maximum, maximumImpl);\nvar maximumConfig = {\n  kernelName: Maximum,\n  backendName: \"cpu\",\n  kernelFunc: maximum3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Minimum.js\nvar minimumImpl = createSimpleBinaryKernelImpl((aValue, bValue) => Math.min(aValue, bValue));\nvar minimum3 = binaryKernelFunc(Minimum, minimumImpl);\nvar minimumConfig = {\n  kernelName: Minimum,\n  backendName: \"cpu\",\n  kernelFunc: minimum3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Multiply.js\nvar multiplyImpl = createSimpleBinaryKernelImpl((aValue, bValue) => aValue * bValue);\nvar multiplyComplexImpl = createComplexBinaryKernelImpl((aReal, aImag, bReal, bImag) => {\n  return {\n    real: aReal * bReal - aImag * bImag,\n    imag: aReal * bImag + aImag * bReal\n  };\n});\nvar multiply2 = binaryKernelFunc(Multiply, multiplyImpl, multiplyComplexImpl);\nvar multiplyConfig = {\n  kernelName: Multiply,\n  backendName: \"cpu\",\n  kernelFunc: multiply2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Neg.js\nfunction negImpl(xVals, xShape, xDtype) {\n  const minusOne = util_exports.createScalarValue(-1, xDtype);\n  return multiplyImpl([], xShape, minusOne, xVals, xDtype);\n}\nfunction neg2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  assertNotComplex(x, \"neg\");\n  const xVals = backend2.data.get(x.dataId).values;\n  const [res, newShape] = negImpl(xVals, x.shape, x.dtype);\n  return backend2.makeTensorInfo(newShape, x.dtype, res);\n}\nvar negConfig = {\n  kernelName: Neg,\n  backendName: \"cpu\",\n  kernelFunc: neg2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/NotEqual.js\nvar notEqualImpl = createSimpleBinaryKernelImpl((a, b) => a !== b ? 1 : 0);\nvar notEqual2 = binaryKernelFunc(NotEqual, notEqualImpl, null, \"bool\");\nvar notEqualConfig = {\n  kernelName: NotEqual,\n  backendName: \"cpu\",\n  kernelFunc: notEqual2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Transpose_impl.js\nfunction transposeImpl(xVals, xShape, dtype, perm, newShape) {\n  const xRank = xShape.length;\n  const xSize = util_exports.sizeFromShape(xShape);\n  const xStrides = util_exports.computeStrides(xShape);\n  const newStrides = util_exports.computeStrides(newShape);\n  const result = util_exports.getTypedArrayFromDType(dtype, util_exports.sizeFromShape(newShape));\n  for (let i2 = 0; i2 < xSize; ++i2) {\n    const loc = util_exports.indexToLoc(i2, xRank, xStrides);\n    const newLoc = new Array(loc.length);\n    for (let i3 = 0; i3 < newLoc.length; i3++) {\n      newLoc[i3] = loc[perm[i3]];\n    }\n    const newIndex = util_exports.locToIndex(newLoc, xRank, newStrides);\n    result[newIndex] = xVals[i2];\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Transpose.js\nfunction transpose2(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { x } = inputs;\n  const { perm } = attrs;\n  assertNotComplex(x, \"transpose\");\n  const xRank = x.shape.length;\n  const newShape = new Array(xRank);\n  for (let i2 = 0; i2 < newShape.length; i2++) {\n    newShape[i2] = x.shape[perm[i2]];\n  }\n  const values = backend2.data.get(x.dataId).values;\n  const result = transposeImpl(values, x.shape, x.dtype, perm, newShape);\n  const dataId = backend2.write(result, newShape, x.dtype);\n  return { dataId, shape: newShape, dtype: x.dtype };\n}\nvar transposeConfig = {\n  kernelName: Transpose,\n  backendName: \"cpu\",\n  kernelFunc: transpose2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Prod.js\nfunction prodImpl(xShape, xDtype, xVals, reductionAxes) {\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(xShape, reductionAxes);\n  const outDtype = upcastType(xDtype, \"int32\");\n  const outVals = util_exports.makeZerosTypedArray(util_exports.sizeFromShape(outShape), outDtype);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  for (let i2 = 0; i2 < outVals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let prod6 = 1;\n    for (let j = 0; j < reduceSize; ++j) {\n      prod6 *= xVals[offset + j];\n    }\n    outVals[i2] = prod6;\n  }\n  return { outVals, outShape, outDtype };\n}\nfunction prod2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  assertNotComplex(x, \"prod\");\n  const xRank = x.shape.length;\n  const axes = util_exports.parseAxisParam(axis, x.shape);\n  const permutation = backend_util_exports.getAxesPermutation(axes, xRank);\n  let reductionAxes = axes;\n  let permutedX = x;\n  const intermediateTensorInfos = [];\n  if (permutation != null) {\n    permutedX = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutation } });\n    intermediateTensorInfos.push(permutedX);\n    reductionAxes = backend_util_exports.getInnerMostAxes(reductionAxes.length, xRank);\n  }\n  const xVals = backend2.data.get(permutedX.dataId).values;\n  const { outVals, outShape, outDtype } = prodImpl(permutedX.shape, permutedX.dtype, xVals, reductionAxes);\n  let resultShape = outShape;\n  if (keepDims) {\n    resultShape = backend_util_exports.expandShapeToKeepDim(outShape, axes);\n  }\n  intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return backend2.makeTensorInfo(resultShape, outDtype, outVals);\n}\nvar prodConfig = {\n  kernelName: Prod,\n  backendName: \"cpu\",\n  kernelFunc: prod2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Range_impl.js\nfunction rangeImpl(start, stop, step5, dtype) {\n  const sameStartStop = start === stop;\n  const increasingRangeNegativeStep = start < stop && step5 < 0;\n  const decreasingRangePositiveStep = stop < start && step5 > 1;\n  if (sameStartStop || increasingRangeNegativeStep || decreasingRangePositiveStep) {\n    return util_exports.makeZerosTypedArray(0, dtype);\n  }\n  const numElements = Math.abs(Math.ceil((stop - start) / step5));\n  const values = util_exports.makeZerosTypedArray(numElements, dtype);\n  if (stop < start && step5 === 1) {\n    step5 = -1;\n  }\n  values[0] = start;\n  for (let i2 = 1; i2 < values.length; i2++) {\n    values[i2] = values[i2 - 1] + step5;\n  }\n  return values;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Rsqrt.js\nvar rsqrtImpl = createSimpleUnaryImpl((xi) => 1 / Math.sqrt(xi));\nvar rsqrt2 = unaryKernelFuncFromImpl(Rsqrt, rsqrtImpl);\nvar rsqrtConfig = {\n  kernelName: Rsqrt,\n  backendName: \"cpu\",\n  kernelFunc: rsqrt2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Scatter_impl.js\nfunction scatterImpl(indices, updates, shape, outputSize, sliceSize, numUpdates, sliceRank, strides, defaultValue, sumDupeIndices) {\n  const flattenShape = [outputSize / sliceSize, sliceSize];\n  const indicesData = indices.values;\n  const updatesData = updates.values;\n  if (outputSize === 0) {\n    return buffer(shape, updates.dtype);\n  }\n  const outBuf = buffer(flattenShape, updates.dtype);\n  if (typeof defaultValue === \"string\") {\n    outBuf.values.fill(defaultValue);\n  } else if (typeof defaultValue === \"number\") {\n    outBuf.values.fill(defaultValue);\n  } else if (typeof defaultValue === \"boolean\") {\n    outBuf.values.fill(+defaultValue);\n  }\n  for (let i2 = 0; i2 < numUpdates; i2++) {\n    const index = [];\n    let flattenIndex = 0;\n    for (let j = 0; j < sliceRank; j++) {\n      const dim = indicesData[i2 * sliceRank + j];\n      index.push(dim);\n      flattenIndex += dim * strides[j];\n    }\n    if (flattenIndex < 0 || flattenIndex >= outputSize / sliceSize) {\n      throw new Error(`Invalid indices: ${index} does not index into ${shape}`);\n    }\n    for (let k = 0; k < sliceSize; k++) {\n      if (sumDupeIndices) {\n        outBuf.values[flattenIndex * sliceSize + k] += updatesData[i2 * sliceSize + k];\n      } else {\n        outBuf.values[flattenIndex * sliceSize + k] = updates.rank === 0 ? updatesData[0] : updatesData[i2 * sliceSize + k];\n      }\n    }\n  }\n  return outBuf;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Sigmoid.js\nvar sigmoidImpl = createSimpleUnaryImpl((xi) => 1 / (1 + Math.exp(-xi)));\nvar sigmoid2 = unaryKernelFunc(Sigmoid, (xi) => 1 / (1 + Math.exp(-xi)));\nvar sigmoidConfig = {\n  kernelName: Sigmoid,\n  backendName: \"cpu\",\n  kernelFunc: sigmoid2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Slice.js\nfunction sliceImpl(vals, begin, size, shape, dtype) {\n  const isContinous = slice_util_exports.isSliceContinous(shape, begin, size);\n  const length = util_exports.sizeFromShape(size);\n  const xStrides = util_exports.computeStrides(shape);\n  if (isContinous) {\n    const flatOffset = slice_util_exports.computeFlatOffset(begin, xStrides);\n    if (dtype === \"string\") {\n      return vals.slice(flatOffset, flatOffset + length);\n    }\n    return vals.subarray(flatOffset, flatOffset + length);\n  }\n  const decodedData = dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(vals) : vals;\n  const inBuf = buffer(shape, dtype, decodedData);\n  const outBuf = buffer(size, dtype);\n  for (let i2 = 0; i2 < outBuf.size; ++i2) {\n    const outLoc = outBuf.indexToLoc(i2);\n    const inLoc = outLoc.map((idx, j) => idx + begin[j]);\n    outBuf.set(inBuf.get(...inLoc), ...outLoc);\n  }\n  if (dtype === \"string\") {\n    return backend_util_exports.fromStringArrayToUint8(outBuf.values);\n  }\n  return outBuf.values;\n}\nfunction slice2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { begin, size } = attrs;\n  assertNotComplex(x, \"slice\");\n  const [$begin, $size] = slice_util_exports.parseSliceParams(x, begin, size);\n  slice_util_exports.assertParamsValid(x, $begin, $size);\n  const vals = backend2.data.get(x.dataId).values;\n  const outVals = sliceImpl(vals, $begin, $size, x.shape, x.dtype);\n  return backend2.makeTensorInfo($size, x.dtype, outVals);\n}\nvar sliceConfig = {\n  kernelName: Slice,\n  backendName: \"cpu\",\n  kernelFunc: slice2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseFillEmptyRows_impl.js\nfunction sparseFillEmptyRowsImpl(indices, indicesShape, indicesDType, values, valuesDType, denseShape, defaultValue) {\n  const indicesCount = indicesShape[0];\n  const denseRows = denseShape[0];\n  const emptyRowIndicator = new Array(denseRows);\n  const reverseIndexMap = new Array(indicesCount);\n  const rank = indicesShape[1];\n  if (denseRows === 0) {\n    if (indicesCount !== 0) {\n      throw new Error(backend_util_exports.getSparseFillEmptyRowsIndicesDenseShapeMismatch(indicesCount));\n    }\n    const outputIndices = util_exports.getArrayFromDType(indicesDType, 0);\n    const outputValues = util_exports.getArrayFromDType(valuesDType, 0);\n    return [\n      outputIndices,\n      [0, rank],\n      outputValues,\n      emptyRowIndicator,\n      reverseIndexMap\n    ];\n  }\n  let rowsAreOrdered = true;\n  let lastIndicesRow = 0;\n  const csrOffset = new Array(denseRows).fill(0);\n  for (let i2 = 0; i2 < indicesCount; ++i2) {\n    const row = indices[i2 * rank];\n    if (row < 0) {\n      throw new Error(backend_util_exports.getSparseFillEmptyRowsNegativeIndexErrorMessage(i2, row));\n    }\n    if (row >= denseRows) {\n      throw new Error(backend_util_exports.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(i2, row, denseRows));\n    }\n    ++csrOffset[row];\n    rowsAreOrdered = rowsAreOrdered && row >= lastIndicesRow;\n    lastIndicesRow = row;\n  }\n  let allRowsFull = true;\n  for (let row = 0; row < denseRows; ++row) {\n    const rowEmpty = csrOffset[row] === 0;\n    emptyRowIndicator[row] = rowEmpty;\n    allRowsFull = allRowsFull && !rowEmpty;\n    csrOffset[row] = Math.max(csrOffset[row], 1);\n    if (row > 0) {\n      csrOffset[row] += csrOffset[row - 1];\n    }\n  }\n  if (allRowsFull && rowsAreOrdered) {\n    const outputIndices = indices;\n    const outputValues = values;\n    for (let i2 = 0; i2 < indicesCount; ++i2) {\n      reverseIndexMap[i2] = i2;\n    }\n    return [\n      outputIndices,\n      [indicesCount, rank],\n      outputValues,\n      emptyRowIndicator,\n      reverseIndexMap\n    ];\n  } else {\n    const fullIndicesCount = csrOffset[denseRows - 1];\n    const outputIndices = util_exports.getArrayFromDType(indicesDType, fullIndicesCount * rank);\n    const outputValues = util_exports.getArrayFromDType(valuesDType, fullIndicesCount);\n    const filledCount = new Array(denseRows).fill(0);\n    for (let i2 = 0; i2 < indicesCount; ++i2) {\n      const row = indices[i2 * rank];\n      const offset = filledCount[row];\n      const outputI = (row === 0 ? 0 : csrOffset[row - 1]) + offset;\n      filledCount[row]++;\n      for (let j = 0; j < rank; ++j) {\n        outputIndices[outputI * rank + j] = indices[i2 * rank + j];\n      }\n      outputValues[outputI] = values[i2];\n      reverseIndexMap[i2] = outputI;\n    }\n    for (let row = 0; row < denseRows; ++row) {\n      const rowCount = filledCount[row];\n      if (rowCount === 0) {\n        const startingIndex = row === 0 ? 0 : csrOffset[row - 1];\n        outputIndices[startingIndex * rank + 0] = row;\n        for (let col = 1; col < rank; ++col) {\n          outputIndices[startingIndex * rank + col] = 0;\n        }\n        outputValues[startingIndex] = defaultValue;\n      }\n    }\n    return [\n      outputIndices,\n      [fullIndicesCount, rank],\n      outputValues,\n      emptyRowIndicator,\n      reverseIndexMap\n    ];\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseReshape_impl.js\nfunction sparseReshapeImpl(inputIndices, inputIndicesShape, inputDType, inputShape, targetShape) {\n  const denseSize = util_exports.sizeFromShape(inputShape);\n  const nnz = inputIndicesShape[0];\n  const outputRank = targetShape.length;\n  const outputShape = [];\n  let product = 1;\n  let unknownIndex = -1;\n  for (let d = 0; d < outputRank; ++d) {\n    const size = targetShape[d];\n    if (size === -1) {\n      if (unknownIndex !== -1) {\n        throw new Error(backend_util_exports.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(unknownIndex, d));\n      }\n      unknownIndex = d;\n      outputShape.push(1);\n    } else {\n      if (size < 0) {\n        throw new Error(backend_util_exports.getSparseReshapeNegativeOutputDimErrorMessage(d, size));\n      }\n      product *= size;\n      outputShape.push(size);\n    }\n  }\n  if (unknownIndex !== -1) {\n    if (product <= 0) {\n      throw new Error(backend_util_exports.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage());\n    }\n    const missing = Math.trunc(denseSize / product);\n    if (product * missing !== denseSize) {\n      throw new Error(backend_util_exports.getSparseReshapeInputOutputMultipleErrorMessage(inputShape, outputShape));\n    }\n    outputShape[unknownIndex] = missing;\n  }\n  const outputSize = util_exports.sizeFromShape(outputShape);\n  if (outputSize !== denseSize) {\n    throw new Error(backend_util_exports.getSparseReshapeInputOutputMismatchErrorMessage(inputShape, outputShape));\n  }\n  const inputRank = inputShape.length;\n  const inputStrides = [];\n  if (inputRank > 0) {\n    inputStrides[inputRank - 1] = 1;\n    for (let d = inputRank - 2; d >= 0; --d) {\n      inputStrides[d] = inputStrides[d + 1] * inputShape[d + 1];\n    }\n  }\n  const outputStrides = [];\n  if (outputRank > 0) {\n    outputStrides[outputRank - 1] = 1;\n    for (let d = outputRank - 2; d >= 0; --d) {\n      outputStrides[d] = outputStrides[d + 1] * outputShape[d + 1];\n    }\n  }\n  const newIndices = util_exports.getArrayFromDType(inputDType, nnz * outputRank);\n  for (let i2 = 0; i2 < nnz; ++i2) {\n    let id = 0;\n    for (let j = 0; j < inputRank; ++j) {\n      id += inputIndices[i2 * inputRank + j] * inputStrides[j];\n    }\n    for (let j = 0; j < outputRank; ++j) {\n      newIndices[i2 * outputRank + j] = Math.trunc(id / outputStrides[j]);\n      id %= outputStrides[j];\n    }\n  }\n  return [newIndices, [nnz, outputRank], outputShape];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseSegmentReduction_impl.js\nfunction sparseSegmentReductionImpl(input2, inputShape, inputDType, indices, segmentIds, isMean = false, defaultValue = 0) {\n  const numIndices = indices.length;\n  const inputFlat = [inputShape[0], input2.length / inputShape[0]];\n  const numCol = inputFlat[1];\n  const lastSegmentIdPlusOne = numIndices > 0 ? segmentIds[numIndices - 1] + 1 : 0;\n  const outputRows = lastSegmentIdPlusOne;\n  if (outputRows < 0) {\n    throw new Error(backend_util_exports.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());\n  }\n  const outputShape = inputShape.slice();\n  outputShape[0] = outputRows;\n  const outputLength = outputShape.reduce((product, value) => product * value, 1);\n  const output = util_exports.getArrayFromDType(inputDType, outputLength);\n  if (numIndices === 0) {\n    if (outputRows > 0) {\n      output.fill(defaultValue);\n    }\n    return [output, outputShape];\n  }\n  if (outputRows <= 0) {\n    throw new Error(backend_util_exports.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());\n  }\n  let start = 0, end = 1;\n  let uninitializedIndex = 0;\n  let outIndex = segmentIds[start];\n  while (true) {\n    let nextIndex = 0;\n    if (end < numIndices) {\n      nextIndex = segmentIds[end];\n      if (outIndex === nextIndex) {\n        ++end;\n        continue;\n      }\n      if (outIndex >= nextIndex) {\n        throw new Error(backend_util_exports.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage());\n      }\n    }\n    if (outIndex < 0 || outIndex >= outputRows) {\n      throw new Error(backend_util_exports.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(outIndex, outputRows));\n    }\n    if (outIndex > uninitializedIndex) {\n      output.fill(defaultValue, uninitializedIndex * numCol, outIndex * numCol);\n    }\n    for (let i2 = start; i2 < end; ++i2) {\n      const index = indices[i2];\n      if (index < 0 || index >= inputFlat[0]) {\n        throw new Error(backend_util_exports.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(i2, indices[i2], inputFlat[0]));\n      }\n      for (let j = 0; j < numCol; j++) {\n        output[outIndex * numCol + j] += input2[index * numCol + j];\n      }\n    }\n    if (isMean) {\n      for (let j = 0; j < numCol; j++) {\n        output[outIndex * numCol + j] /= end - start;\n      }\n    }\n    start = end;\n    ++end;\n    uninitializedIndex = outIndex + 1;\n    outIndex = nextIndex;\n    if (end > numIndices) {\n      break;\n    }\n  }\n  if (uninitializedIndex < outputRows) {\n    output.fill(defaultValue, uninitializedIndex * numCol, outputRows * numCol);\n  }\n  return [output, outputShape];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Sqrt.js\nvar sqrtImpl = createSimpleUnaryImpl((xi) => Math.sqrt(xi));\nvar sqrt2 = unaryKernelFunc(Sqrt, (xi) => Math.sqrt(xi));\nvar sqrtConfig = {\n  kernelName: Sqrt,\n  backendName: \"cpu\",\n  kernelFunc: sqrt2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SquaredDifference.js\nvar squaredDifferenceImpl = createSimpleBinaryKernelImpl((a, b) => {\n  const diff = a - b;\n  return diff * diff;\n});\nvar squaredDifference2 = binaryKernelFunc(SquaredDifference, squaredDifferenceImpl);\nvar squaredDifferenceConfig = {\n  kernelName: SquaredDifference,\n  backendName: \"cpu\",\n  kernelFunc: squaredDifference2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StridedSlice_impl.js\nfunction stridedSliceImpl(outShape, xBuf, strides, begin) {\n  const outBuf = buffer(outShape, xBuf.dtype);\n  for (let i2 = 0; i2 < outBuf.size; i2++) {\n    const loc = outBuf.indexToLoc(i2);\n    const newLoc = new Array(loc.length);\n    for (let j = 0; j < newLoc.length; j++) {\n      newLoc[j] = loc[j] * strides[j] + begin[j];\n    }\n    outBuf.set(xBuf.get(...newLoc), ...loc);\n  }\n  return outBuf;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StringNGrams_impl.js\nvar StringNGramsOp = class {\n  constructor(separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences) {\n    this.separator = util_exports.encodeString(separator);\n    this.nGramWidths = nGramWidths;\n    this.leftPad = util_exports.encodeString(leftPad);\n    this.rightPad = util_exports.encodeString(rightPad2);\n    this.padWidth = padWidth;\n    this.preserveShort = preserveShortSequences;\n  }\n  getPadWidth(nGramWidth) {\n    return Math.min(this.padWidth < 0 ? nGramWidth - 1 : this.padWidth, nGramWidth - 1);\n  }\n  getNumNGrams(length, nGramWidth) {\n    const padWidth = this.getPadWidth(nGramWidth);\n    return Math.max(0, length + 2 * padWidth - nGramWidth + 1);\n  }\n  createNGrams(data, splitIndex, output, outputStartIndex, numNGrams, nGramWidth) {\n    for (let nGramIndex = 0; nGramIndex < numNGrams; ++nGramIndex) {\n      const padWidth = this.getPadWidth(nGramWidth);\n      const leftPadding = Math.max(0, padWidth - nGramIndex);\n      const rightPadding = Math.max(0, padWidth - (numNGrams - (nGramIndex + 1)));\n      const numTokens = nGramWidth - (leftPadding + rightPadding);\n      const dataStartIndex = splitIndex + (leftPadding > 0 ? 0 : nGramIndex - padWidth);\n      let nGramSize = 0;\n      nGramSize += leftPadding * this.leftPad.length;\n      for (let n2 = 0; n2 < numTokens; ++n2) {\n        nGramSize += data[dataStartIndex + n2].length;\n      }\n      nGramSize += rightPadding * this.rightPad.length;\n      const numSeparators = leftPadding + rightPadding + numTokens - 1;\n      nGramSize += numSeparators * this.separator.length;\n      output[outputStartIndex + nGramIndex] = new Uint8Array(nGramSize);\n      const nGram = output[outputStartIndex + nGramIndex];\n      let nextNGramIndex = 0;\n      const appendToNGram = (str) => str.forEach((value) => nGram[nextNGramIndex++] = value);\n      for (let n2 = 0; n2 < leftPadding; ++n2) {\n        appendToNGram(this.leftPad);\n        appendToNGram(this.separator);\n      }\n      for (let n2 = 0; n2 < numTokens - 1; ++n2) {\n        appendToNGram(data[dataStartIndex + n2]);\n        appendToNGram(this.separator);\n      }\n      if (numTokens > 0) {\n        appendToNGram(data[dataStartIndex + numTokens - 1]);\n        for (let n2 = 0; n2 < rightPadding; ++n2) {\n          appendToNGram(this.separator);\n          appendToNGram(this.rightPad);\n        }\n      } else {\n        for (let n2 = 0; n2 < rightPadding - 1; ++n2) {\n          appendToNGram(this.rightPad);\n          appendToNGram(this.separator);\n        }\n        appendToNGram(this.rightPad);\n      }\n    }\n  }\n  compute(data, splits) {\n    const inputDataSize = data.length;\n    const splitsSize = splits.length;\n    if (splitsSize > 0) {\n      let prevSplit = splits[0];\n      if (prevSplit !== 0) {\n        throw new Error(`First split value must be 0, got ${prevSplit}`);\n      }\n      for (let i2 = 1; i2 < splitsSize; ++i2) {\n        let validSplits = splits[i2] >= prevSplit;\n        validSplits = validSplits && splits[i2] <= inputDataSize;\n        if (!validSplits) {\n          throw new Error(`Invalid split value ${splits[i2]}, must be in [${prevSplit}, ${inputDataSize}]`);\n        }\n        prevSplit = splits[i2];\n      }\n      if (prevSplit !== inputDataSize) {\n        throw new Error(`Last split value must be data size. Expected ${inputDataSize}, got ${prevSplit}`);\n      }\n    }\n    const numBatchItems = splitsSize - 1;\n    const nGramsSplits = util_exports.getArrayFromDType(\"int32\", splitsSize);\n    if (inputDataSize === 0 || splitsSize === 0) {\n      const empty = new Array(inputDataSize);\n      for (let i2 = 0; i2 <= numBatchItems; ++i2) {\n        nGramsSplits[i2] = 0;\n      }\n      return [empty, nGramsSplits];\n    }\n    nGramsSplits[0] = 0;\n    for (let i2 = 1; i2 <= numBatchItems; ++i2) {\n      const length = splits[i2] - splits[i2 - 1];\n      let numNGrams = 0;\n      this.nGramWidths.forEach((nGramWidth) => {\n        numNGrams += this.getNumNGrams(length, nGramWidth);\n      });\n      if (this.preserveShort && length > 0 && numNGrams === 0) {\n        numNGrams = 1;\n      }\n      nGramsSplits[i2] = nGramsSplits[i2 - 1] + numNGrams;\n    }\n    const nGrams = new Array(nGramsSplits[numBatchItems]);\n    for (let i2 = 0; i2 < numBatchItems; ++i2) {\n      const splitIndex = splits[i2];\n      let outputStartIdx = nGramsSplits[i2];\n      this.nGramWidths.forEach((nGramWidth) => {\n        const length = splits[i2 + 1] - splits[i2];\n        const numNGrams = this.getNumNGrams(length, nGramWidth);\n        this.createNGrams(data, splitIndex, nGrams, outputStartIdx, numNGrams, nGramWidth);\n        outputStartIdx += numNGrams;\n      });\n      if (this.preserveShort && outputStartIdx === nGramsSplits[i2]) {\n        const dataLength = splits[i2 + 1] - splits[i2];\n        if (dataLength === 0) {\n          continue;\n        }\n        const nGramWidth = dataLength + 2 * this.padWidth;\n        const numNGrams = 1;\n        this.createNGrams(data, splitIndex, nGrams, outputStartIdx, numNGrams, nGramWidth);\n      }\n    }\n    return [nGrams, nGramsSplits];\n  }\n};\nfunction stringNGramsImpl(data, dataSplits, separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences) {\n  return new StringNGramsOp(separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences).compute(data, dataSplits);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StringSplit_impl.js\nfunction split3(str, delimiters, skipEmpty, result) {\n  if (!str.length) {\n    return;\n  }\n  if (delimiters.length === 0) {\n    for (let i2 = 0; i2 < str.length; ++i2) {\n      result.push(str.subarray(i2, i2 + 1));\n    }\n    return;\n  }\n  if (delimiters.length === 1) {\n    const delimiter = delimiters[0];\n    let f = str.indexOf(delimiter);\n    while (f !== -1) {\n      const token = str.subarray(0, f);\n      if (!skipEmpty || token.length !== 0) {\n        result.push(token);\n      }\n      str = str.subarray(f + 1);\n      f = str.indexOf(delimiter);\n    }\n    if (!skipEmpty || str.length !== 0) {\n      result.push(str);\n    }\n    return;\n  }\n  let tokenStart = 0;\n  for (let i2 = 0; i2 < str.length + 1; i2++) {\n    if (i2 === str.length || delimiters.indexOf(str[i2]) !== -1) {\n      const token = str.subarray(tokenStart, i2);\n      if (!skipEmpty || token.length !== 0) {\n        result.push(token);\n      }\n      tokenStart = i2 + 1;\n    }\n  }\n}\nfunction stringSplitImpl(input2, delimiter, skipEmpty) {\n  const batchSize = input2.length;\n  const tokens = [];\n  let outputSize = 0;\n  let maxNumEntries = 0;\n  const numIndices = new Array(batchSize);\n  for (let i2 = 0; i2 < batchSize; ++i2) {\n    const prevTokensLength = tokens.length;\n    split3(input2[i2], delimiter, skipEmpty, tokens);\n    const nEntries = tokens.length - prevTokensLength;\n    numIndices[i2] = nEntries;\n    outputSize += nEntries;\n    maxNumEntries = Math.max(maxNumEntries, nEntries);\n  }\n  const indices = util_exports.getArrayFromDType(\"int32\", outputSize * 2);\n  const values = new Array(outputSize);\n  const shape = [batchSize, maxNumEntries];\n  let c = 0;\n  for (let i2 = 0; i2 < batchSize; ++i2) {\n    for (let j = 0; j < numIndices[i2]; ++j) {\n      indices[c * 2] = i2;\n      indices[c * 2 + 1] = j;\n      values[c] = tokens[c];\n      ++c;\n    }\n  }\n  return [indices, values, shape];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StringToHashBucketFast_impl.js\nfunction stringToHashBucketFastImpl(input2, numBuckets) {\n  const output = util_exports.getArrayFromDType(\"int32\", input2.length);\n  for (let i2 = 0; i2 < input2.length; ++i2) {\n    output[i2] = util_exports.fingerPrint64(input2[i2]).modulo(numBuckets).getLowBitsUnsigned();\n  }\n  return output;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Sub.js\nvar subImpl = createSimpleBinaryKernelImpl((aValue, bValue) => aValue - bValue);\nvar subComplexImpl = createComplexBinaryKernelImpl((aReal, aImag, bReal, bImag) => {\n  return { real: aReal - bReal, imag: aImag - bImag };\n});\nvar sub2 = binaryKernelFunc(Sub, subImpl, subComplexImpl);\nvar subConfig = {\n  kernelName: Sub,\n  backendName: \"cpu\",\n  kernelFunc: sub2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Tile_impl.js\nfunction tileImpl(xBuf, reps) {\n  const newShape = new Array(xBuf.rank);\n  for (let i2 = 0; i2 < newShape.length; i2++) {\n    newShape[i2] = xBuf.shape[i2] * reps[i2];\n  }\n  const result = buffer(newShape, xBuf.dtype);\n  for (let i2 = 0; i2 < result.values.length; ++i2) {\n    const newLoc = result.indexToLoc(i2);\n    const originalLoc = new Array(xBuf.rank);\n    for (let j = 0; j < originalLoc.length; j++) {\n      originalLoc[j] = newLoc[j] % xBuf.shape[j];\n    }\n    const originalIndex = xBuf.locToIndex(originalLoc);\n    result.values[i2] = xBuf.values[originalIndex];\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/TopK_impl.js\nvar comparePair = (a, b) => {\n  const valueDiff = b.value - a.value;\n  return valueDiff === 0 ? a.index - b.index : valueDiff;\n};\nfunction select(array2, k, left = 0, right = array2.length - 1) {\n  while (right > left) {\n    if (right - left > 600) {\n      const n2 = right - left + 1;\n      const i3 = k - left + 1;\n      const z = Math.log(n2);\n      const s2 = 0.5 * Math.exp(2 * z / 3);\n      const sd = 0.5 * Math.sqrt(z * s2 * (n2 - s2) / n2) * Math.sign(i3 - n2 / 2);\n      const newLeft = Math.max(left, Math.floor(k - i3 * s2 / n2 + sd));\n      const newRight = Math.min(right, Math.floor(k + (n2 - i3) * s2 / n2 + sd));\n      select(array2, k, newLeft, newRight);\n    }\n    const t2 = array2[k];\n    let i2 = left;\n    let j = right;\n    util_exports.swap(array2, left, k);\n    if (comparePair(array2[right], t2) > 0) {\n      util_exports.swap(array2, left, right);\n    }\n    while (i2 < j) {\n      util_exports.swap(array2, i2, j);\n      i2++;\n      j--;\n      while (comparePair(array2[i2], t2) < 0) {\n        i2 = i2 + 1;\n      }\n      while (comparePair(array2[j], t2) > 0) {\n        j = j - 1;\n      }\n    }\n    if (comparePair(array2[left], t2) === 0) {\n      util_exports.swap(array2, left, j);\n    } else {\n      j = j + 1;\n      util_exports.swap(array2, j, right);\n    }\n    if (j <= k) {\n      left = j + 1;\n    }\n    if (k <= j) {\n      right = j - 1;\n    }\n  }\n}\nfunction topKImpl(x, xShape, xDtype, k, sorted) {\n  const lastDim = xShape[xShape.length - 1];\n  const [batch, size] = [x.length / lastDim, lastDim];\n  const allTopKVals = util_exports.getTypedArrayFromDType(xDtype, batch * k);\n  const allTopKIndices = util_exports.getTypedArrayFromDType(\"int32\", batch * k);\n  for (let b = 0; b < batch; b++) {\n    const offset = b * size;\n    const vals = x.subarray(offset, offset + size);\n    let valAndInd = new Array(vals.length);\n    vals.forEach((value, index) => valAndInd[index] = { value, index });\n    if (k < valAndInd.length) {\n      select(valAndInd, k);\n      valAndInd = valAndInd.slice(0, k);\n    }\n    if (sorted) {\n      valAndInd.sort(comparePair);\n    }\n    const outOffset = b * k;\n    const topKVals = allTopKVals.subarray(outOffset, outOffset + k);\n    const topKIndices = allTopKIndices.subarray(outOffset, outOffset + k);\n    for (let i2 = 0; i2 < k; i2++) {\n      topKVals[i2] = valAndInd[i2].value;\n      topKIndices[i2] = valAndInd[i2].index;\n    }\n  }\n  const outputShape = xShape.slice();\n  outputShape[outputShape.length - 1] = k;\n  return [\n    buffer(outputShape, xDtype, allTopKVals),\n    buffer(outputShape, \"int32\", allTopKIndices)\n  ];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Unique_impl.js\nfunction uniqueImpl(values, axis, shape, dtype) {\n  const $axis = util_exports.parseAxisParam(axis, shape)[0];\n  const newShape = [1, shape[0], 1];\n  for (let i2 = 0; i2 < $axis; i2++) {\n    newShape[0] *= shape[i2];\n  }\n  newShape[1] = shape[$axis];\n  for (let i2 = $axis + 1; i2 < shape.length; i2++) {\n    newShape[2] *= shape[i2];\n  }\n  const uniqueElements = {};\n  const indices = new Int32Array(shape[$axis]);\n  const inputBuffer = new TensorBuffer(newShape, dtype, values);\n  const uniqueIndices = [];\n  const is1DTensor = newShape[0] === 1 && newShape[2] === 1;\n  for (let i2 = 0; i2 < shape[$axis]; i2++) {\n    let element;\n    if (is1DTensor) {\n      element = values[i2].toString();\n    } else {\n      const axisValues = [];\n      for (let m = 0; m < newShape[0]; m++) {\n        for (let n2 = 0; n2 < newShape[2]; n2++) {\n          axisValues.push(inputBuffer.get(m, i2, n2));\n        }\n      }\n      element = axisValues.join(\",\");\n    }\n    if (uniqueElements[element] !== void 0) {\n      indices[i2] = uniqueElements[element];\n    } else {\n      const uniqueIndex = Object.keys(uniqueElements).length;\n      uniqueElements[element] = uniqueIndex;\n      indices[i2] = uniqueIndex;\n      uniqueIndices.push(i2);\n    }\n  }\n  const outputTmpShape = newShape.slice();\n  outputTmpShape[1] = Object.keys(uniqueElements).length;\n  const outputBuffer = new TensorBuffer(outputTmpShape, dtype);\n  uniqueIndices.forEach((uniqueElementIndex, i2) => {\n    for (let m = 0; m < newShape[0]; m++) {\n      for (let n2 = 0; n2 < newShape[2]; n2++) {\n        outputBuffer.set(inputBuffer.get(m, uniqueElementIndex, n2), m, i2, n2);\n      }\n    }\n  });\n  const outputShape = shape.slice();\n  outputShape[$axis] = outputTmpShape[1];\n  return {\n    outputValues: outputBuffer.values,\n    outputShape,\n    indices\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/base.js\nregisterBackend(\"cpu\", () => new MathBackendCPU(), 1);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Elu.js\nvar elu4 = unaryKernelFunc(Elu, (xi) => xi >= 0 ? xi : Math.exp(xi) - 1);\nvar eluConfig = {\n  kernelName: Elu,\n  backendName: \"cpu\",\n  kernelFunc: elu4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LeakyRelu.js\nfunction leakyRelu2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { alpha } = attrs;\n  assertNotComplex([x], \"leakyRelu\");\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const xVals = backend2.data.get(x.dataId).values;\n  const outVals = util_exports.getTypedArrayFromDType(\"float32\", xSize);\n  for (let i2 = 0; i2 < xVals.length; i2++) {\n    outVals[i2] = xVals[i2] < 0 ? alpha * xVals[i2] : xVals[i2];\n  }\n  return backend2.makeTensorInfo(x.shape, \"float32\", outVals);\n}\nvar leakyReluConfig = {\n  kernelName: LeakyRelu,\n  backendName: \"cpu\",\n  kernelFunc: leakyRelu2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Prelu.js\nvar preluImpl = createSimpleBinaryKernelImpl((xValue, aValue) => xValue < 0 ? aValue * xValue : xValue);\nfunction prelu3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x, alpha } = inputs;\n  assertNotComplex([x, alpha], \"prelu\");\n  const aVals = backend2.data.get(x.dataId).values;\n  const bVals = backend2.data.get(alpha.dataId).values;\n  const [resultData, resultShape] = preluImpl(x.shape, alpha.shape, aVals, bVals, \"float32\");\n  return backend2.makeTensorInfo(resultShape, \"float32\", resultData);\n}\nvar preluConfig = {\n  kernelName: Prelu,\n  backendName: \"cpu\",\n  kernelFunc: prelu3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Relu.js\nvar relu2 = unaryKernelFunc(Relu, (xi) => Math.max(0, xi));\nvar reluConfig = {\n  kernelName: Relu,\n  backendName: \"cpu\",\n  kernelFunc: relu2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Relu6.js\nvar relu62 = unaryKernelFunc(Relu6, (xi) => Math.min(Math.max(0, xi), 6));\nvar relu6Config = {\n  kernelName: Relu6,\n  backendName: \"cpu\",\n  kernelFunc: relu62\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/fused_utils.js\nfunction applyActivation2(backend2, x, activation2, preluActivationWeights, leakyreluAlpha) {\n  if (activation2 === \"linear\") {\n    return identity2({ inputs: { x }, backend: backend2 });\n  } else if (activation2 === \"relu\") {\n    return relu2({ inputs: { x }, backend: backend2 });\n  } else if (activation2 === \"elu\") {\n    return elu4({ inputs: { x }, backend: backend2 });\n  } else if (activation2 === \"relu6\") {\n    return relu62({ inputs: { x }, backend: backend2 });\n  } else if (activation2 === \"prelu\") {\n    return prelu3({ inputs: { x, alpha: preluActivationWeights }, backend: backend2 });\n  } else if (activation2 === \"leakyrelu\") {\n    return leakyRelu2({ inputs: { x }, backend: backend2, attrs: { alpha: leakyreluAlpha } });\n  } else if (activation2 === \"sigmoid\") {\n    return sigmoid2({ inputs: { x }, backend: backend2 });\n  }\n  throw new Error(`Activation ${activation2} has not been implemented for the CPU backend.`);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Reshape.js\nfunction reshape3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { shape } = attrs;\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const $shape = util_exports.inferFromImplicitShape(shape, xSize);\n  const $xSize = util_exports.sizeFromShape($shape);\n  util_exports.assert(xSize === $xSize, () => `The new shape (${$shape}) has ${$xSize} elements and the old shape (${x.shape}) has ${xSize} elements. The new shape and old shape must have the same number of elements.`);\n  backend2.incRef(x.dataId);\n  const xData = backend2.data.get(x.dataId);\n  if (xData.complexTensorInfos != null) {\n    const real5 = xData.complexTensorInfos.real;\n    const imag5 = xData.complexTensorInfos.imag;\n    real5.shape = $shape;\n    imag5.shape = $shape;\n  }\n  return { dataId: x.dataId, shape: $shape, dtype: x.dtype };\n}\nvar reshapeConfig = {\n  kernelName: Reshape,\n  backendName: \"cpu\",\n  kernelFunc: reshape3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/BatchMatMul.js\nfunction batchMatMul(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b } = inputs;\n  const { transposeA, transposeB } = attrs;\n  assertNotComplex([a, b], \"matMul\");\n  const aRank = a.shape.length;\n  const bRank = b.shape.length;\n  const innerShapeA = transposeA ? a.shape[aRank - 2] : a.shape[aRank - 1];\n  const innerShapeB = transposeB ? b.shape[bRank - 1] : b.shape[bRank - 2];\n  const outerShapeA = transposeA ? a.shape[aRank - 1] : a.shape[aRank - 2];\n  const outerShapeB = transposeB ? b.shape[bRank - 2] : b.shape[bRank - 1];\n  const outerDimsA = a.shape.slice(0, -2);\n  const outerDimsB = b.shape.slice(0, -2);\n  const batchDimA = util_exports.sizeFromShape(outerDimsA);\n  const batchDimB = util_exports.sizeFromShape(outerDimsB);\n  const outShapeOuterDims = broadcast_util_exports.assertAndGetBroadcastShape(a.shape.slice(0, -2), b.shape.slice(0, -2));\n  const outShape = outShapeOuterDims.concat([outerShapeA, outerShapeB]);\n  util_exports.assert(innerShapeA === innerShapeB, () => `Error in matMul: inner shapes (${innerShapeA}) and (${innerShapeB}) of Tensors with shapes ${a.shape} and ${b.shape} and transposeA=${transposeA} and transposeB=${transposeB} must match.`);\n  const a3dShape = transposeA ? [batchDimA, innerShapeA, outerShapeA] : [batchDimA, outerShapeA, innerShapeA];\n  const b3dShape = transposeB ? [batchDimB, outerShapeB, innerShapeB] : [batchDimB, innerShapeB, outerShapeB];\n  const a3d = reshape3({ inputs: { x: a }, backend: backend2, attrs: { shape: a3dShape } });\n  const b3d = reshape3({ inputs: { x: b }, backend: backend2, attrs: { shape: b3dShape } });\n  const sharedDim = transposeA ? a3d.shape[1] : a3d.shape[2];\n  const leftDim = transposeA ? a3d.shape[2] : a3d.shape[1];\n  const rightDim = transposeB ? b3d.shape[1] : b3d.shape[2];\n  const batchDim = Math.max(batchDimA, batchDimB);\n  const a3dValues = backend2.data.get(a3d.dataId).values;\n  const b3dValues = backend2.data.get(b3d.dataId).values;\n  const a3dStrides = util_exports.computeStrides(a3d.shape);\n  const b3dStrides = util_exports.computeStrides(b3d.shape);\n  const [aBatch, aOuterStep, aInnerStep] = transposeA ? [a3dStrides[0], 1, a3dStrides[1]] : [a3dStrides[0], a3dStrides[1], 1];\n  const [bInnerStep, bOuterStep, bBatch] = transposeB ? [1, b3dStrides[1], b3dStrides[0]] : [b3dStrides[1], 1, b3dStrides[0]];\n  const size = leftDim * rightDim;\n  const result = buffer([batchDim, leftDim, rightDim], a3d.dtype);\n  const resVals = result.values;\n  const blockSize = backend2.blockSize;\n  for (let bi = 0; bi < batchDim; bi++) {\n    for (let i0 = 0; i0 < leftDim; i0 += blockSize) {\n      for (let j0 = 0; j0 < rightDim; j0 += blockSize) {\n        for (let k02 = 0; k02 < sharedDim; k02 += blockSize) {\n          const iBlock = Math.min(i0 + blockSize, leftDim);\n          const jBlock = Math.min(j0 + blockSize, rightDim);\n          const kBlock = Math.min(k02 + blockSize, sharedDim);\n          for (let i2 = i0; i2 < iBlock; i2++) {\n            for (let j = j0; j < jBlock; j++) {\n              let sum7 = 0;\n              for (let k = k02; k < kBlock; k++) {\n                const batchOffsetA = Math.min(bi, batchDimA - 1) * aBatch;\n                const batchOffsetB = Math.min(bi, batchDimB - 1) * bBatch;\n                const aVal = a3dValues[batchOffsetA + i2 * aOuterStep + k * aInnerStep];\n                const bVal = b3dValues[k * bInnerStep + j * bOuterStep + batchOffsetB];\n                sum7 += aVal * bVal;\n              }\n              resVals[bi * size + (i2 * rightDim + j)] += sum7;\n            }\n          }\n        }\n      }\n    }\n  }\n  backend2.disposeIntermediateTensorInfo(a3d);\n  backend2.disposeIntermediateTensorInfo(b3d);\n  return backend2.makeTensorInfo(outShape, result.dtype, result.values);\n}\nvar batchMatMulConfig = {\n  kernelName: BatchMatMul,\n  backendName: \"cpu\",\n  kernelFunc: batchMatMul\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/_FusedMatMul.js\nfunction _fusedMatMul(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b, bias, preluActivationWeights } = inputs;\n  const { transposeA, transposeB, activation: activation2, leakyreluAlpha } = attrs;\n  let current;\n  let addRes;\n  let activationRes;\n  const intermediates = [];\n  const matMulRes = batchMatMul({ inputs: { a, b }, attrs: { transposeA, transposeB }, backend: backend2 });\n  current = matMulRes;\n  if (bias) {\n    addRes = add4({ inputs: { a: current, b: bias }, backend: backend2 });\n    intermediates.push(current);\n    current = addRes;\n  }\n  if (activation2) {\n    activationRes = applyActivation2(backend2, current, activation2, preluActivationWeights, leakyreluAlpha);\n    intermediates.push(current);\n    current = activationRes;\n  }\n  for (const i2 of intermediates) {\n    backend2.disposeIntermediateTensorInfo(i2);\n  }\n  return current;\n}\nvar _fusedMatMulConfig = {\n  kernelName: _FusedMatMul,\n  backendName: \"cpu\",\n  kernelFunc: _fusedMatMul\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Acos.js\nvar acos2 = unaryKernelFunc(Acos, (xi) => Math.acos(xi));\nvar acosConfig = {\n  kernelName: Acos,\n  backendName: \"cpu\",\n  kernelFunc: acos2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Acosh.js\nvar acosh2 = unaryKernelFunc(Acosh, (xi) => Math.acosh(xi));\nvar acoshConfig = {\n  kernelName: Acosh,\n  backendName: \"cpu\",\n  kernelFunc: acosh2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/AddN.js\nfunction addN2(args) {\n  const { inputs, backend: backend2 } = args;\n  const tensors = inputs;\n  assertNotComplex(inputs, \"addN\");\n  const vals = tensors.map((t2) => backend2.data.get(t2.dataId).values);\n  const outBuf = buffer(tensors[0].shape, tensors[0].dtype);\n  const outVals = outBuf.values;\n  for (let i2 = 0; i2 < tensors.length; i2++) {\n    const currVals = vals[i2];\n    for (let j = 0; j < outVals.length; j++) {\n      outVals[j] += currVals[j];\n    }\n  }\n  return backend2.makeTensorInfo(outBuf.shape, outBuf.dtype, outBuf.values);\n}\nvar addNConfig = {\n  kernelName: AddN,\n  backendName: \"cpu\",\n  kernelFunc: addN2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/All.js\nfunction all2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  assertNotComplex(x, \"all\");\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  if (permutedAxes != null) {\n    $x = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"all\", axes, $x.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes($x.shape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const vals = util_exports.makeZerosTypedArray(util_exports.sizeFromShape(outShape), $x.dtype);\n  const aVals = backend2.data.get($x.dataId).values;\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let all5 = aVals[offset];\n    for (let j = 0; j < reduceSize; ++j) {\n      const value = aVals[offset + j];\n      all5 = all5 && value;\n    }\n    vals[i2] = all5;\n  }\n  if (permutedAxes != null) {\n    backend2.disposeIntermediateTensorInfo($x);\n  }\n  const result = backend2.makeTensorInfo(outShape, $x.dtype, vals);\n  if (keepDims) {\n    const expandedShape = backend_util_exports.expandShapeToKeepDim(outShape, origAxes);\n    const reshapedResult = reshape3({ inputs: { x: result }, backend: backend2, attrs: { shape: expandedShape } });\n    backend2.disposeIntermediateTensorInfo(result);\n    return reshapedResult;\n  }\n  return result;\n}\nvar allConfig = {\n  kernelName: All,\n  backendName: \"cpu\",\n  kernelFunc: all2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Any.js\nfunction any2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  assertNotComplex(x, \"any\");\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  if (permutedAxes != null) {\n    $x = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"any\", axes, $x.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes($x.shape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const vals = util_exports.makeZerosTypedArray(util_exports.sizeFromShape(outShape), $x.dtype);\n  const aVals = backend2.data.get($x.dataId).values;\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let anyVal = aVals[offset];\n    for (let j = 0; j < reduceSize; ++j) {\n      const value = aVals[offset + j];\n      anyVal = anyVal || value;\n    }\n    vals[i2] = anyVal;\n  }\n  if (permutedAxes != null) {\n    backend2.disposeIntermediateTensorInfo($x);\n  }\n  const result = backend2.makeTensorInfo(outShape, $x.dtype, vals);\n  if (keepDims) {\n    const expandedShape = backend_util_exports.expandShapeToKeepDim(outShape, origAxes);\n    const reshapedResult = reshape3({ inputs: { x: result }, backend: backend2, attrs: { shape: expandedShape } });\n    backend2.disposeIntermediateTensorInfo(result);\n    return reshapedResult;\n  }\n  return result;\n}\nvar anyConfig = {\n  kernelName: Any,\n  backendName: \"cpu\",\n  kernelFunc: any2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ArgMax.js\nfunction argMax2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis } = attrs;\n  assertNotComplex(x, \"argMax\");\n  let axes = util_exports.parseAxisParam(axis, x.shape);\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  const intermediateTensorInfos = [];\n  if (permutedAxes != null) {\n    $x = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    intermediateTensorInfos.push($x);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, $x.shape.length);\n  }\n  axes = [axes[0]];\n  backend_util_exports.assertAxesAreInnerMostDims(\"argMax\", axes, $x.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes($x.shape, axes);\n  const outSize = util_exports.sizeFromShape(outShape);\n  const vals = util_exports.makeZerosTypedArray(outSize, \"int32\");\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const aVals = backend2.data.get($x.dataId).values;\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let max7 = aVals[offset];\n    let maxIndex = 0;\n    for (let j = 0; j < reduceSize; ++j) {\n      const value = aVals[offset + j];\n      if (value > max7) {\n        max7 = value;\n        maxIndex = j;\n      }\n    }\n    vals[i2] = maxIndex;\n  }\n  intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return backend2.makeTensorInfo(outShape, \"int32\", vals);\n}\nvar argMaxConfig = {\n  kernelName: ArgMax,\n  backendName: \"cpu\",\n  kernelFunc: argMax2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ArgMin.js\nfunction argMin2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis } = attrs;\n  assertNotComplex(x, \"argMin\");\n  let axes = util_exports.parseAxisParam(axis, x.shape);\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  const intermediateTensorInfos = [];\n  if (permutedAxes != null) {\n    $x = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    intermediateTensorInfos.push($x);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, $x.shape.length);\n  }\n  axes = [axes[0]];\n  backend_util_exports.assertAxesAreInnerMostDims(\"argMin\", axes, $x.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes($x.shape, axes);\n  const outSize = util_exports.sizeFromShape(outShape);\n  const vals = util_exports.makeZerosTypedArray(outSize, \"int32\");\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const aVals = backend2.data.get($x.dataId).values;\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let min7 = aVals[offset];\n    let minIndex = 0;\n    for (let j = 0; j < reduceSize; ++j) {\n      const value = aVals[offset + j];\n      if (value < min7) {\n        min7 = value;\n        minIndex = j;\n      }\n    }\n    vals[i2] = minIndex;\n  }\n  intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return backend2.makeTensorInfo(outShape, \"int32\", vals);\n}\nvar argMinConfig = {\n  kernelName: ArgMin,\n  backendName: \"cpu\",\n  kernelFunc: argMin2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Asin.js\nvar asin2 = unaryKernelFunc(Asin, (xi) => Math.asin(xi));\nvar asinConfig = {\n  kernelName: Asin,\n  backendName: \"cpu\",\n  kernelFunc: asin2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Asinh.js\nvar asinh2 = unaryKernelFunc(Asinh, (xi) => Math.asinh(xi));\nvar asinhConfig = {\n  kernelName: Asinh,\n  backendName: \"cpu\",\n  kernelFunc: asinh2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Atan.js\nvar atan3 = unaryKernelFunc(Atan, (xi) => Math.atan(xi));\nvar atanConfig = {\n  kernelName: Atan,\n  backendName: \"cpu\",\n  kernelFunc: atan3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Atan2.js\nvar atan2Impl = createSimpleBinaryKernelImpl((aValue, bValue) => Math.atan2(aValue, bValue));\nvar atan22 = binaryKernelFunc(Atan2, atan2Impl);\nvar atan2Config = {\n  kernelName: Atan2,\n  backendName: \"cpu\",\n  kernelFunc: atan22\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Atanh.js\nvar atanh2 = unaryKernelFunc(Atanh, (xi) => Math.atanh(xi));\nvar atanhConfig = {\n  kernelName: Atanh,\n  backendName: \"cpu\",\n  kernelFunc: atanh2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/pool_utils.js\nfunction pool2(xValues, xShape, dtype, strides, convInfo, poolType) {\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padLeft = convInfo.padInfo.left;\n  const initialValue = poolType === \"max\" ? Number.NEGATIVE_INFINITY : Number.POSITIVE_INFINITY;\n  const output = buffer(convInfo.outShape, dtype);\n  const outputVals = output.values;\n  const outputBatchStrides = convInfo.outShape[1] * convInfo.outShape[2] * convInfo.outShape[3];\n  const outputRowStrides = convInfo.outShape[2] * convInfo.outShape[3];\n  const outputColStrides = convInfo.outShape[3];\n  for (let b = 0; b < convInfo.batchSize; ++b) {\n    const outputBatchOffset = b * outputBatchStrides;\n    const inputBatchOffset = b * strides[0];\n    for (let d = 0; d < convInfo.inChannels; ++d) {\n      for (let yR = 0; yR < convInfo.outHeight; ++yR) {\n        const xRCorner = yR * strideHeight - padTop;\n        const xRMin = Math.max(0, xRCorner);\n        const xRMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRCorner);\n        const outputRowOffset = outputBatchOffset + yR * outputRowStrides;\n        for (let yC = 0; yC < convInfo.outWidth; ++yC) {\n          const xCCorner = yC * strideWidth - padLeft;\n          const xCMin = Math.max(0, xCCorner);\n          const xCMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xCCorner);\n          let minMaxValue = initialValue;\n          let avgValue = 0;\n          let count2 = 0;\n          for (let xR = xRMin; xR < xRMax; xR += dilationHeight) {\n            const xROffset = inputBatchOffset + xR * strides[1];\n            for (let xC = xCMin; xC < xCMax; xC += dilationWidth) {\n              const xCOffset = xROffset + xC * strides[2];\n              const pixel = xValues[xCOffset + d];\n              if (poolType === \"max\" && pixel > minMaxValue) {\n                minMaxValue = pixel;\n              } else if (poolType === \"avg\") {\n                avgValue += pixel;\n                count2++;\n              }\n            }\n            if (isNaN(minMaxValue)) {\n              break;\n            }\n          }\n          const outputOffset = outputRowOffset + yC * outputColStrides + d;\n          outputVals[outputOffset] = poolType === \"avg\" ? avgValue / count2 : minMaxValue;\n        }\n      }\n    }\n  }\n  return output;\n}\nfunction maxPoolPositions(xValues, xShape, dtype, convInfo, flattenPositions = false, includeBatchInIndex = false) {\n  const maxPositions = buffer(convInfo.outShape, \"int32\");\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padLeft = convInfo.padInfo.left;\n  const xBuf = buffer(xShape, dtype, xValues);\n  for (let b = 0; b < convInfo.batchSize; ++b) {\n    for (let d = 0; d < convInfo.inChannels; ++d) {\n      for (let yR = 0; yR < convInfo.outHeight; ++yR) {\n        const xRCorner = yR * strideHeight - padTop;\n        let xRMin = xRCorner;\n        while (xRMin < 0) {\n          xRMin += dilationHeight;\n        }\n        const xRMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRCorner);\n        for (let yC = 0; yC < convInfo.outWidth; ++yC) {\n          const xCCorner = yC * strideWidth - padLeft;\n          let xCMin = xCCorner;\n          while (xCMin < 0) {\n            xCMin += dilationWidth;\n          }\n          const xCMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xCCorner);\n          let maxValue = Number.NEGATIVE_INFINITY;\n          let maxPosition = -1;\n          for (let xR = xRMin; xR < xRMax; xR += dilationHeight) {\n            const wR = xR - xRCorner;\n            for (let xC = xCMin; xC < xCMax; xC += dilationWidth) {\n              const wC = xC - xCCorner;\n              const pixel = xBuf.get(b, xR, xC, d);\n              if (pixel > maxValue) {\n                maxValue = pixel;\n                if (flattenPositions) {\n                  maxPosition = includeBatchInIndex ? ((b * convInfo.inHeight + xR) * convInfo.inWidth + xC) * convInfo.inChannels + d : (xR * convInfo.inWidth + xC) * convInfo.inChannels + d;\n                } else {\n                  maxPosition = wR * effectiveFilterWidth + wC;\n                }\n              }\n            }\n          }\n          maxPositions.set(maxPosition, b, yR, yC, d);\n        }\n      }\n    }\n  }\n  return maxPositions;\n}\nfunction pool3d2(xValues, xShape, dtype, strides, convInfo, poolType) {\n  const strideDepth = convInfo.strideDepth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const dilationDepth = convInfo.dilationDepth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterDepth = convInfo.effectiveFilterDepth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padFront = convInfo.padInfo.front;\n  const padTop = convInfo.padInfo.top;\n  const padLeft = convInfo.padInfo.left;\n  const initialValue = poolType === \"max\" ? Number.NEGATIVE_INFINITY : Number.POSITIVE_INFINITY;\n  const output = buffer(convInfo.outShape, dtype);\n  const outputVals = output.values;\n  const outputBatchStrides = convInfo.outShape[1] * convInfo.outShape[2] * convInfo.outShape[3] * convInfo.outShape[4];\n  const outputDepthStrides = convInfo.outShape[2] * convInfo.outShape[3] * convInfo.outShape[4];\n  const outputRowStrides = convInfo.outShape[3] * convInfo.outShape[4];\n  const outputColStrides = convInfo.outShape[4];\n  for (let batch = 0; batch < convInfo.batchSize; ++batch) {\n    const outputBatchOffset = batch * outputBatchStrides;\n    const inputBatchOffset = batch * strides[0];\n    for (let channel = 0; channel < convInfo.inChannels; ++channel) {\n      for (let yDepth = 0; yDepth < convInfo.outDepth; ++yDepth) {\n        const xDepthCorner = yDepth * strideDepth - padFront;\n        let xDepthMin = xDepthCorner;\n        while (xDepthMin < 0) {\n          xDepthMin += dilationDepth;\n        }\n        const xDepthMax = Math.min(convInfo.inDepth, effectiveFilterDepth + xDepthCorner);\n        const outputDepthOffset = outputBatchOffset + yDepth * outputDepthStrides;\n        for (let yRow = 0; yRow < convInfo.outHeight; ++yRow) {\n          const xRowCorner = yRow * strideHeight - padTop;\n          let xRowMin = xRowCorner;\n          while (xRowMin < 0) {\n            xRowMin += dilationHeight;\n          }\n          const xRowMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRowCorner);\n          const outputRowOffset = outputDepthOffset + yRow * outputRowStrides;\n          for (let yCol = 0; yCol < convInfo.outWidth; ++yCol) {\n            const xColCorner = yCol * strideWidth - padLeft;\n            let xColMin = xColCorner;\n            while (xColMin < 0) {\n              xColMin += dilationWidth;\n            }\n            const xColMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xColCorner);\n            const outputColOffset = outputRowOffset + yCol * outputColStrides;\n            let minMaxValue = initialValue;\n            let avgValue = 0;\n            let count2 = 0;\n            for (let xDepth = xDepthMin; xDepth < xDepthMax; xDepth += dilationDepth) {\n              const xDepthOffset = inputBatchOffset + xDepth * strides[1];\n              for (let xRow = xRowMin; xRow < xRowMax; xRow += dilationHeight) {\n                const xRowOffset = xDepthOffset + xRow * strides[2];\n                for (let xCol = xColMin; xCol < xColMax; xCol += dilationWidth) {\n                  const xColOffset = xRowOffset + xCol * strides[3];\n                  const pixel = xValues[xColOffset + channel];\n                  if (poolType === \"max\" && pixel > minMaxValue) {\n                    minMaxValue = pixel;\n                  } else if (poolType === \"avg\") {\n                    avgValue += pixel;\n                    count2++;\n                  }\n                  if (isNaN(minMaxValue)) {\n                    break;\n                  }\n                }\n                if (isNaN(minMaxValue)) {\n                  break;\n                }\n              }\n              if (isNaN(minMaxValue)) {\n                break;\n              }\n            }\n            const outputOffset = outputColOffset + channel;\n            outputVals[outputOffset] = poolType === \"avg\" ? avgValue / count2 : minMaxValue;\n          }\n        }\n      }\n    }\n  }\n  return output;\n}\nfunction maxPool3dPositions(xBuf, convInfo) {\n  const maxPositions = buffer(convInfo.outShape, \"int32\");\n  const strideDepth = convInfo.strideDepth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const dilationDepth = convInfo.dilationDepth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterDepth = convInfo.effectiveFilterDepth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padFront = convInfo.padInfo.front;\n  const padTop = convInfo.padInfo.top;\n  const padLeft = convInfo.padInfo.left;\n  for (let batch = 0; batch < convInfo.batchSize; ++batch) {\n    for (let channel = 0; channel < convInfo.inChannels; ++channel) {\n      for (let yDepth = 0; yDepth < convInfo.outDepth; ++yDepth) {\n        const xDepthCorner = yDepth * strideDepth - padFront;\n        let xDepthMin = xDepthCorner;\n        while (xDepthMin < 0) {\n          xDepthMin += dilationDepth;\n        }\n        const xDepthMax = Math.min(convInfo.inDepth, effectiveFilterDepth + xDepthCorner);\n        for (let yRow = 0; yRow < convInfo.outHeight; ++yRow) {\n          const xRowCorner = yRow * strideHeight - padTop;\n          let xRowMin = xRowCorner;\n          while (xRowMin < 0) {\n            xRowMin += dilationHeight;\n          }\n          const xRowMax = Math.min(convInfo.inHeight, effectiveFilterHeight + xRowCorner);\n          for (let yCol = 0; yCol < convInfo.outWidth; ++yCol) {\n            const xColCorner = yCol * strideWidth - padLeft;\n            let xColMin = xColCorner;\n            while (xColMin < 0) {\n              xColMin += dilationWidth;\n            }\n            const xColMax = Math.min(convInfo.inWidth, effectiveFilterWidth + xColCorner);\n            let maxValue = Number.NEGATIVE_INFINITY;\n            let maxPosition = -1;\n            for (let xDepth = xDepthMin; xDepth < xDepthMax; xDepth += dilationDepth) {\n              const wDepth = xDepth - xDepthCorner;\n              for (let xRow = xRowMin; xRow < xRowMax; xRow += dilationHeight) {\n                const wRow = xRow - xRowCorner;\n                for (let xCol = xColMin; xCol < xColMax; xCol += dilationWidth) {\n                  const wCol = xCol - xColCorner;\n                  const pixel = xBuf.get(batch, xDepth, xRow, xCol, channel);\n                  if (pixel >= maxValue) {\n                    maxValue = pixel;\n                    maxPosition = wDepth * effectiveFilterHeight * effectiveFilterWidth + wRow * effectiveFilterHeight + wCol;\n                  }\n                }\n              }\n            }\n            maxPositions.set(maxPosition, batch, yDepth, yRow, yCol, channel);\n          }\n        }\n      }\n    }\n  }\n  return maxPositions;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/AvgPool.js\nfunction avgPool2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  assertNotComplex(x, \"avgPool\");\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = 1;\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in avgPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  let res;\n  if (convInfo.filterWidth === 1 && convInfo.filterHeight === 1 && util_exports.arraysEqual(convInfo.inShape, convInfo.outShape)) {\n    res = identity2({ inputs: { x }, backend: backend2 });\n  } else {\n    const xValues = backend2.data.get(x.dataId).values;\n    const strides2 = util_exports.computeStrides(x.shape);\n    const buffer2 = pool2(xValues, x.shape, x.dtype, strides2, convInfo, \"avg\");\n    res = backend2.makeTensorInfo(convInfo.outShape, x.dtype, buffer2.values);\n  }\n  return res;\n}\nvar avgPoolConfig = {\n  kernelName: AvgPool,\n  backendName: \"cpu\",\n  kernelFunc: avgPool2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/AvgPool3D.js\nfunction avgPool3D(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { filterSize, strides, pad: pad3, dimRoundingMode, dataFormat } = attrs;\n  assertNotComplex(x, \"avgPool3d\");\n  const convInfo = backend_util_exports.computePool3DInfo(x.shape, filterSize, strides, 1, pad3, dimRoundingMode, dataFormat);\n  const xValues = backend2.data.get(x.dataId).values;\n  const outBuf = pool3d2(xValues, x.shape, x.dtype, util_exports.computeStrides(x.shape), convInfo, \"avg\");\n  return backend2.makeTensorInfo(outBuf.shape, \"float32\", outBuf.values);\n}\nvar avgPool3DConfig = {\n  kernelName: AvgPool3D,\n  backendName: \"cpu\",\n  kernelFunc: avgPool3D\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/AvgPool3DGrad.js\nfunction avgPool3DGrad(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2 } = inputs;\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  assertNotComplex([dy, input2], \"avgPool3DGrad\");\n  const convInfo = backend_util_exports.computePool3DInfo(input2.shape, filterSize, strides, 1, pad3, dimRoundingMode);\n  const strideDepth = convInfo.strideDepth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const filterDepth = convInfo.filterDepth;\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const dilationDepth = convInfo.dilationDepth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterDepth = convInfo.effectiveFilterDepth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;\n  const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n  const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n  const dx = buffer(input2.shape, \"float32\");\n  const avgMultiplier = 1 / (filterDepth * filterHeight * filterWidth);\n  const dyBuf = backend2.bufferSync(dy);\n  for (let batch = 0; batch < convInfo.batchSize; ++batch) {\n    for (let channel = 0; channel < convInfo.inChannels; ++channel) {\n      for (let dxDepth = 0; dxDepth < convInfo.inDepth; ++dxDepth) {\n        for (let dxRow = 0; dxRow < convInfo.inHeight; ++dxRow) {\n          for (let dxCol = 0; dxCol < convInfo.inWidth; ++dxCol) {\n            const dyDepthCorner = dxDepth - padFront;\n            const dyRowCorner = dxRow - padTop;\n            const dyColCorner = dxCol - padLeft;\n            let dotProd = 0;\n            for (let wDepth = 0; wDepth < effectiveFilterDepth; wDepth += dilationDepth) {\n              const dyDepth = (dyDepthCorner + wDepth) / strideDepth;\n              if (dyDepth < 0 || dyDepth >= convInfo.outDepth || Math.floor(dyDepth) !== dyDepth) {\n                continue;\n              }\n              for (let wRow = 0; wRow < effectiveFilterHeight; wRow += dilationHeight) {\n                const dyRow = (dyRowCorner + wRow) / strideHeight;\n                if (dyRow < 0 || dyRow >= convInfo.outHeight || Math.floor(dyRow) !== dyRow) {\n                  continue;\n                }\n                for (let wCol = 0; wCol < effectiveFilterWidth; wCol += dilationWidth) {\n                  const dyCol = (dyColCorner + wCol) / strideWidth;\n                  if (dyCol < 0 || dyCol >= convInfo.outWidth || Math.floor(dyCol) !== dyCol) {\n                    continue;\n                  }\n                  const pixel = dyBuf.get(batch, dyDepth, dyRow, dyCol, channel);\n                  dotProd += pixel;\n                }\n              }\n            }\n            dx.set(dotProd * avgMultiplier, batch, dxDepth, dxRow, dxCol, channel);\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dx.shape, dx.dtype, dx.values);\n}\nvar avgPool3DGradConfig2 = {\n  kernelName: AvgPool3DGrad,\n  backendName: \"cpu\",\n  kernelFunc: avgPool3DGrad\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/AvgPoolGrad.js\nfunction avgPoolGrad2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2 } = inputs;\n  const x = input2;\n  assertNotComplex([dy, input2], \"avgPoolGrad\");\n  const { filterSize, strides, pad: pad3 } = attrs;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, 1, pad3);\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n  const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n  const dx = buffer(x.shape, \"float32\");\n  const avgMultiplier = 1 / (filterHeight * filterWidth);\n  const dyData = backend2.data.get(dy.dataId).values;\n  const dyBuf = buffer(dy.shape, \"float32\", dyData);\n  for (let b = 0; b < convInfo.batchSize; ++b) {\n    for (let d = 0; d < convInfo.inChannels; ++d) {\n      for (let dxR = 0; dxR < convInfo.inHeight; ++dxR) {\n        for (let dxC = 0; dxC < convInfo.inWidth; ++dxC) {\n          const dyRCorner = dxR - padTop;\n          const dyCCorner = dxC - padLeft;\n          let dotProd = 0;\n          for (let wR = 0; wR < effectiveFilterHeight; wR += dilationHeight) {\n            const dyR = (dyRCorner + wR) / strideHeight;\n            if (dyR < 0 || dyR >= convInfo.outHeight || Math.floor(dyR) !== dyR) {\n              continue;\n            }\n            for (let wC = 0; wC < effectiveFilterWidth; wC += dilationWidth) {\n              const dyC = (dyCCorner + wC) / strideWidth;\n              if (dyC < 0 || dyC >= convInfo.outWidth || Math.floor(dyC) !== dyC) {\n                continue;\n              }\n              const pixel = dyBuf.get(b, dyR, dyC, d);\n              dotProd += pixel;\n            }\n          }\n          dx.set(dotProd * avgMultiplier, b, dxR, dxC, d);\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dx.shape, dx.dtype, dx.values);\n}\nvar avgPoolGradConfig2 = {\n  kernelName: AvgPoolGrad,\n  backendName: \"cpu\",\n  kernelFunc: avgPoolGrad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/BatchNorm.js\nfunction batchNorm2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, scale: scale2, offset, mean: mean5, variance } = inputs;\n  util_exports.assert(mean5.shape.length === variance.shape.length, () => \"Batch normalization gradient requires mean and variance to have equal ranks.\");\n  util_exports.assert(offset == null || mean5.shape.length === offset.shape.length, () => \"Batch normalization gradient requires mean and offset to have equal ranks.\");\n  util_exports.assert(scale2 == null || mean5.shape.length === scale2.shape.length, () => \"Batch normalization gradient requires mean and scale to have equal ranks.\");\n  assertNotComplex([x, mean5, variance, scale2, offset], \"batchNorm\");\n  let { varianceEpsilon } = attrs;\n  if (varianceEpsilon == null) {\n    varianceEpsilon = 1e-3;\n  }\n  const xVals = backend2.data.get(x.dataId).values;\n  const mVals = backend2.data.get(mean5.dataId).values;\n  const varVals = backend2.data.get(variance.dataId).values;\n  const sVals = scale2 ? backend2.data.get(scale2.dataId).values : new Float32Array([1]);\n  const offVals = offset ? backend2.data.get(offset.dataId).values : new Float32Array([0]);\n  const outVals = new Float32Array(xVals.length);\n  const offValsLength = offVals.length;\n  const sValsLength = sVals.length;\n  const varValsLength = varVals.length;\n  const mValsLength = mVals.length;\n  let offi = 0;\n  let mi = 0;\n  let si = 0;\n  let vi = 0;\n  for (let i2 = 0; i2 < xVals.length; ++i2) {\n    outVals[i2] = offVals[offi++] + (xVals[i2] - mVals[mi++]) * sVals[si++] / Math.sqrt(varVals[vi++] + varianceEpsilon);\n    if (offi >= offValsLength) {\n      offi = 0;\n    }\n    if (mi >= mValsLength) {\n      mi = 0;\n    }\n    if (si >= sValsLength) {\n      si = 0;\n    }\n    if (vi >= varValsLength) {\n      vi = 0;\n    }\n  }\n  return backend2.makeTensorInfo(x.shape, x.dtype, outVals);\n}\nvar batchNormConfig = {\n  kernelName: FusedBatchNorm,\n  backendName: \"cpu\",\n  kernelFunc: batchNorm2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/BatchToSpaceND.js\nfunction batchToSpaceND2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, crops } = attrs;\n  assertNotComplex([x], \"batchToSpaceND\");\n  const prod6 = blockShape.reduce((a, b) => a * b);\n  const reshaped = backend_util_exports.getReshaped(x.shape, blockShape, prod6);\n  const permuted = backend_util_exports.getPermuted(reshaped.length, blockShape.length);\n  const reshapedPermuted = backend_util_exports.getReshapedPermuted(x.shape, blockShape, prod6);\n  const sliceBeginCoords = backend_util_exports.getSliceBeginCoords(crops, blockShape.length);\n  const sliceSize = backend_util_exports.getSliceSize(reshapedPermuted, crops, blockShape.length);\n  const xReshaped = reshape3({ inputs: { x }, backend: backend2, attrs: { shape: reshaped } });\n  const xTransposed = transpose2({ inputs: { x: xReshaped }, backend: backend2, attrs: { perm: permuted } });\n  const xTransposedReshaped = reshape3({ inputs: { x: xTransposed }, backend: backend2, attrs: { shape: reshapedPermuted } });\n  const result = slice2({\n    inputs: { x: xTransposedReshaped },\n    backend: backend2,\n    attrs: { begin: sliceBeginCoords, size: sliceSize }\n  });\n  backend2.disposeIntermediateTensorInfo(xReshaped);\n  backend2.disposeIntermediateTensorInfo(xTransposed);\n  backend2.disposeIntermediateTensorInfo(xTransposedReshaped);\n  return result;\n}\nvar batchToSpaceNDConfig = {\n  kernelName: BatchToSpaceND,\n  backendName: \"cpu\",\n  kernelFunc: batchToSpaceND2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Bincount.js\nfunction bincount2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, weights } = inputs;\n  const { size } = attrs;\n  const xVals = backend2.data.get(x.dataId).values;\n  const weightsVals = backend2.data.get(weights.dataId).values;\n  const outVals = bincountImpl(xVals, weightsVals, weights.dtype, weights.shape, size);\n  return backend2.makeTensorInfo([size], weights.dtype, outVals);\n}\nvar bincountConfig = {\n  kernelName: Bincount,\n  backendName: \"cpu\",\n  kernelFunc: bincount2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/BroadcastArgs.js\nfunction broadcastArgs2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { s0, s1 } = inputs;\n  const s0Vals = backend2.data.get(s0.dataId).values;\n  const s1Vals = backend2.data.get(s1.dataId).values;\n  const broadcastShape = backend_util_exports.assertAndGetBroadcastShape(Array.from(s0Vals), Array.from(s1Vals));\n  return backend2.makeTensorInfo([broadcastShape.length], \"int32\", Int32Array.from(broadcastShape));\n}\nvar broadcastArgsConfig = {\n  kernelName: BroadcastArgs,\n  backendName: \"cpu\",\n  kernelFunc: broadcastArgs2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ClipByValue.js\nvar clipByValue2 = unaryKernelFunc(ClipByValue, (xi, attrs) => {\n  const clipAttrs = attrs;\n  if (xi > clipAttrs.clipValueMax) {\n    return clipAttrs.clipValueMax;\n  }\n  return xi < clipAttrs.clipValueMin ? clipAttrs.clipValueMin : xi;\n});\nvar clipByValueConfig = {\n  kernelName: ClipByValue,\n  backendName: \"cpu\",\n  kernelFunc: clipByValue2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ComplexAbs.js\nvar complexAbs = (args) => {\n  const { x } = args.inputs;\n  const cpuBackend = args.backend;\n  const resultValues = new Float32Array(util_exports.sizeFromShape(x.shape));\n  const complexVals = cpuBackend.data.get(x.dataId);\n  const real5 = complexVals.complexTensorInfos.real;\n  const imag5 = complexVals.complexTensorInfos.imag;\n  const realVals = cpuBackend.data.get(real5.dataId).values;\n  const imagVals = cpuBackend.data.get(imag5.dataId).values;\n  for (let i2 = 0; i2 < realVals.length; i2++) {\n    const real6 = realVals[i2];\n    const imag6 = imagVals[i2];\n    resultValues[i2] = Math.hypot(real6, imag6);\n  }\n  return cpuBackend.makeOutput(resultValues, x.shape, \"float32\");\n};\nvar complexAbsConfig = {\n  kernelName: ComplexAbs,\n  backendName: \"cpu\",\n  kernelFunc: complexAbs\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Imag.js\nfunction imag2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const imag5 = backend2.data.get(input2.dataId).complexTensorInfos.imag;\n  const imagVal = backend2.data.get(imag5.dataId).values;\n  return backend2.makeTensorInfo(imag5.shape, imag5.dtype, imagVal);\n}\nvar imagConfig = {\n  kernelName: Imag,\n  backendName: \"cpu\",\n  kernelFunc: imag2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Concat.js\nfunction concat2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { axis } = attrs;\n  const $axis = util_exports.parseAxisParam(axis, inputs[0].shape)[0];\n  let outShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), $axis);\n  if (util_exports.sizeFromShape(outShape) === 0) {\n    return backend2.makeTensorInfo(outShape, inputs[0].dtype, []);\n  }\n  const $inputs = inputs.filter((t2) => util_exports.sizeFromShape(t2.shape) > 0);\n  if ($inputs.length === 1) {\n    return identity2({ inputs: { x: $inputs[0] }, backend: backend2 });\n  }\n  const shapes = $inputs.map((t2) => t2.shape);\n  backend_util_exports.assertParamsConsistent(shapes, $axis);\n  if ($inputs[0].dtype === \"complex64\") {\n    const reals = $inputs.map((t2) => real2({ inputs: { input: t2 }, backend: backend2 }));\n    const imags = $inputs.map((t2) => imag2({ inputs: { input: t2 }, backend: backend2 }));\n    const realConcated = concat2({ inputs: reals, backend: backend2, attrs: { axis: $axis } });\n    const imagConcated = concat2({ inputs: imags, backend: backend2, attrs: { axis: $axis } });\n    const result = complex2({ inputs: { real: realConcated, imag: imagConcated }, backend: backend2 });\n    reals.forEach((r2) => backend2.disposeIntermediateTensorInfo(r2));\n    imags.forEach((i2) => backend2.disposeIntermediateTensorInfo(i2));\n    backend2.disposeIntermediateTensorInfo(realConcated);\n    backend2.disposeIntermediateTensorInfo(imagConcated);\n    return result;\n  }\n  const inputs2D = $inputs.map((t2) => {\n    const innerSize = util_exports.sizeFromShape(t2.shape.slice($axis));\n    const shape = [-1, innerSize];\n    return reshape3({ inputs: { x: t2 }, backend: backend2, attrs: { shape } });\n  });\n  const inputsValShapes = inputs2D.map((t2) => {\n    return { vals: backend2.data.get(t2.dataId).values, shape: t2.shape };\n  });\n  outShape = backend_util_exports.computeOutShape(inputs2D.map((t2) => t2.shape), 1);\n  const simplyConcat = inputs2D[0].shape[0] === 1;\n  const outVals = concatImpl(inputsValShapes, outShape, inputs[0].dtype, simplyConcat);\n  const finalOutShape = backend_util_exports.computeOutShape($inputs.map((t2) => t2.shape), $axis);\n  const outInfo = backend2.makeTensorInfo(finalOutShape, inputs[0].dtype, outVals);\n  inputs2D.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return outInfo;\n}\nvar concatConfig = {\n  kernelName: Concat,\n  backendName: \"cpu\",\n  kernelFunc: concat2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Conv2D.js\nfunction conv2D(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode } = attrs;\n  assertNotComplex([x, filter], \"conv2d\");\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode, false, $dataFormat);\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const padLeft = convInfo.padInfo.left;\n  const padTop = convInfo.padInfo.top;\n  const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n  const y = new TensorBuffer(convInfo.outShape, x.dtype);\n  const xStrides = util_exports.computeStrides(x.shape);\n  const filterStrides = util_exports.computeStrides(filter.shape);\n  const xBatchStride = xStrides[0];\n  const xRowStride = isChannelsLast ? xStrides[1] : xStrides[2];\n  const xColStride = isChannelsLast ? xStrides[2] : 1;\n  const xChannelStride = isChannelsLast ? 1 : xStrides[1];\n  const yBatchStride = y.strides[0];\n  const yRowStride = isChannelsLast ? y.strides[1] : y.strides[2];\n  const yColStride = isChannelsLast ? y.strides[2] : 1;\n  const yChannelStride = isChannelsLast ? 1 : y.strides[1];\n  const xVals = backend2.data.get(x.dataId).values;\n  const wVals = backend2.data.get(filter.dataId).values;\n  const yVals = y.values;\n  for (let b = 0; b < convInfo.batchSize; ++b) {\n    const xOffset1 = b * xBatchStride;\n    const yOffset1 = b * yBatchStride;\n    for (let yR = 0; yR < convInfo.outHeight; ++yR) {\n      const yOffset2 = yOffset1 + yR * yRowStride;\n      const xRCorner = yR * convInfo.strideHeight - padTop;\n      for (let wR = 0; wR < filterHeight; ++wR) {\n        const xR = xRCorner + wR * dilationHeight;\n        if (xR < 0 || xR >= convInfo.inHeight) {\n          continue;\n        }\n        const wOffset1 = wR * filterStrides[0];\n        const xOffset2 = xOffset1 + xR * xRowStride;\n        for (let yC = 0; yC < convInfo.outWidth; ++yC) {\n          const yOffset3 = yOffset2 + yC * yColStride;\n          const xCCorner = yC * convInfo.strideWidth - padLeft;\n          for (let wC = 0; wC < filterWidth; ++wC) {\n            const xC = xCCorner + wC * dilationWidth;\n            if (xC < 0 || xC >= convInfo.inWidth) {\n              continue;\n            }\n            const wOffset2 = wOffset1 + wC * filterStrides[1];\n            const xOffset3 = xOffset2 + xC * xColStride;\n            let wOffset3 = wOffset2;\n            for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {\n              const xVal = xVals[xOffset3 + d1 * xChannelStride];\n              for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {\n                yVals[yOffset3 + d2 * yChannelStride] += xVal * wVals[wOffset3 + d2];\n              }\n              wOffset3 += convInfo.outChannels;\n            }\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(y.shape, y.dtype, yVals);\n}\nvar conv2DConfig = {\n  kernelName: Conv2D,\n  backendName: \"cpu\",\n  kernelFunc: conv2D\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Conv2DBackpropFilter.js\nfunction conv2DBackpropFilter2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, dy } = inputs;\n  const { strides, pad: pad3, dataFormat, dimRoundingMode, filterShape } = attrs;\n  assertNotComplex([x, dy], \"conv2dBackpropFilter\");\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filterShape, strides, 1, pad3, dimRoundingMode, false, $dataFormat);\n  const { strideHeight, strideWidth, filterHeight, filterWidth } = convInfo;\n  const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n  const dW = new TensorBuffer(convInfo.filterShape, \"float32\");\n  const leftPad = convInfo.padInfo.left;\n  const topPad = convInfo.padInfo.top;\n  const xVals = backend2.data.get(x.dataId).values;\n  const dyVals = backend2.data.get(dy.dataId).values;\n  const xBuf = new TensorBuffer(x.shape, x.dtype, xVals);\n  const dyBuf = new TensorBuffer(dy.shape, dy.dtype, dyVals);\n  for (let wR = 0; wR < filterHeight; ++wR) {\n    const yRMin = Math.max(0, Math.ceil((topPad - wR) / strideHeight));\n    const yRMax = Math.min(convInfo.outHeight, (convInfo.inHeight + topPad - wR) / strideHeight);\n    for (let wC = 0; wC < filterWidth; ++wC) {\n      const yCMin = Math.max(0, Math.ceil((leftPad - wC) / strideWidth));\n      const yCMax = Math.min(convInfo.outWidth, (convInfo.inWidth + leftPad - wC) / strideWidth);\n      for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {\n        for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {\n          let dotProd = 0;\n          for (let b = 0; b < convInfo.batchSize; ++b) {\n            for (let yR = yRMin; yR < yRMax; ++yR) {\n              const xR = wR + yR * strideHeight - topPad;\n              for (let yC = yCMin; yC < yCMax; ++yC) {\n                const xC = wC + yC * strideWidth - leftPad;\n                if (isChannelsLast) {\n                  dotProd += xBuf.get(b, xR, xC, d1) * dyBuf.get(b, yR, yC, d2);\n                } else {\n                  dotProd += xBuf.get(b, d1, xR, xC) * dyBuf.get(b, d2, yR, yC);\n                }\n              }\n            }\n          }\n          dW.set(dotProd, wR, wC, d1, d2);\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dW.shape, dW.dtype, dW.values);\n}\nvar conv2DBackpropFilterConfig = {\n  kernelName: Conv2DBackpropFilter,\n  backendName: \"cpu\",\n  kernelFunc: conv2DBackpropFilter2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Conv2DBackpropInput.js\nfunction conv2DBackpropInput2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, filter } = inputs;\n  const { inputShape, strides, pad: pad3, dataFormat, dimRoundingMode } = attrs;\n  assertNotComplex([dy, filter], \"conv2dBackpropInput\");\n  const filterStrides = util_exports.computeStrides(filter.shape);\n  const dyStrides = util_exports.computeStrides(dy.shape);\n  let $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(inputShape, filter.shape, strides, 1, pad3, dimRoundingMode, false, $dataFormat);\n  const dx = new TensorBuffer(convInfo.inShape, \"float32\");\n  const dxValues = dx.values;\n  const dyValues = backend2.data.get(dy.dataId).values;\n  const fltValues = backend2.data.get(filter.dataId).values;\n  const [fltS0, fltS1, fltS2] = filterStrides;\n  const { batchSize, filterHeight, filterWidth, inChannels, inHeight, inWidth, outChannels, outHeight, outWidth, strideHeight, strideWidth } = convInfo;\n  $dataFormat = convInfo.dataFormat;\n  const topPad = filterHeight - 1 - convInfo.padInfo.top;\n  const leftPad = filterWidth - 1 - convInfo.padInfo.left;\n  const isChannelsLast = $dataFormat === \"channelsLast\";\n  const xBatchStride = dx.strides[0];\n  const xRowStride = isChannelsLast ? dx.strides[1] : dx.strides[2];\n  const xColStride = isChannelsLast ? dx.strides[2] : 1;\n  const xChannelStride = isChannelsLast ? 1 : dx.strides[1];\n  const yBatchStride = dyStrides[0];\n  const yRowStride = isChannelsLast ? dyStrides[1] : dyStrides[2];\n  const yColStride = isChannelsLast ? dyStrides[2] : 1;\n  const yChannelStride = isChannelsLast ? 1 : dyStrides[1];\n  for (let b = 0; b < batchSize; ++b) {\n    for (let d1 = 0; d1 < inChannels; ++d1) {\n      for (let xR = 0; xR < inHeight; ++xR) {\n        const xRCorner = xR - topPad;\n        const xRMin = Math.max(0, Math.ceil(xRCorner / strideHeight));\n        const yRMax = Math.min(outHeight, (filterHeight + xRCorner) / strideHeight);\n        for (let xC = 0; xC < inWidth; ++xC) {\n          const xCCorner = xC - leftPad;\n          const xCMin = Math.max(0, Math.ceil(xCCorner / strideWidth));\n          const yCMax = Math.min(outWidth, (filterWidth + xCCorner) / strideWidth);\n          let dotProd = 0;\n          for (let yR = xRMin; yR < yRMax; ++yR) {\n            const wR = yR * strideHeight - xRCorner;\n            for (let yC = xCMin; yC < yCMax; ++yC) {\n              const wC = yC * strideWidth - xCCorner;\n              const dyOffset = yBatchStride * b + yRowStride * yR + yColStride * yC;\n              const fltOffset = fltS0 * (filterHeight - 1 - wR) + fltS1 * (filterWidth - 1 - wC) + fltS2 * d1;\n              for (let d2 = 0; d2 < outChannels; ++d2) {\n                const pixel = dyValues[dyOffset + yChannelStride * d2];\n                const weight = fltValues[fltOffset + d2];\n                dotProd += pixel * weight;\n              }\n            }\n          }\n          const dxOffset = xBatchStride * b + xRowStride * xR + xColStride * xC + xChannelStride * d1;\n          dxValues[dxOffset] = dotProd;\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dx.shape, dx.dtype, dx.values);\n}\nvar conv2DBackpropInputConfig = {\n  kernelName: Conv2DBackpropInput,\n  backendName: \"cpu\",\n  kernelFunc: conv2DBackpropInput2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Conv3D.js\nfunction conv3D(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dilations } = attrs;\n  assertNotComplex([x, filter], \"conv3d\");\n  const convInfo = backend_util_exports.computeConv3DInfo(x.shape, filter.shape, strides, dilations, pad3);\n  const { filterDepth, filterHeight, filterWidth, dilationDepth, dilationHeight, dilationWidth, padInfo } = convInfo;\n  const padFront = padInfo.front;\n  const padLeft = padInfo.left;\n  const padTop = padInfo.top;\n  const y = new TensorBuffer(convInfo.outShape, x.dtype);\n  const xVals = backend2.data.get(x.dataId).values;\n  const wVals = backend2.data.get(filter.dataId).values;\n  const yVals = y.values;\n  const xStrides = util_exports.computeStrides(x.shape);\n  const filterStrides = util_exports.computeStrides(filter.shape);\n  for (let b = 0; b < convInfo.batchSize; ++b) {\n    const xOffset1 = b * xStrides[0];\n    const yOffset1 = b * y.strides[0];\n    for (let yF = 0; yF < convInfo.outDepth; ++yF) {\n      const yOffset2 = yOffset1 + yF * y.strides[1];\n      const xFCorner = yF * convInfo.strideDepth - padFront;\n      for (let wF = 0; wF < filterDepth; ++wF) {\n        const xF = xFCorner + wF * dilationDepth;\n        if (xF < 0 || xF >= convInfo.inDepth) {\n          continue;\n        }\n        const wOffset1 = wF * filterStrides[0];\n        const xOffset2 = xOffset1 + xF * xStrides[1];\n        for (let yR = 0; yR < convInfo.outHeight; ++yR) {\n          const yOffset3 = yOffset2 + yR * y.strides[2];\n          const xRCorner = yR * convInfo.strideHeight - padTop;\n          for (let wR = 0; wR < filterHeight; ++wR) {\n            const xR = xRCorner + wR * dilationHeight;\n            if (xR < 0 || xR >= convInfo.inHeight) {\n              continue;\n            }\n            const wOffset2 = wOffset1 + wR * filterStrides[1];\n            const xOffset3 = xOffset2 + xR * xStrides[2];\n            for (let yC = 0; yC < convInfo.outWidth; ++yC) {\n              const yOffset4 = yOffset3 + yC * convInfo.outChannels;\n              const xCCorner = yC * convInfo.strideWidth - padLeft;\n              for (let wC = 0; wC < filterWidth; ++wC) {\n                const xC = xCCorner + wC * dilationWidth;\n                if (xC < 0 || xC >= convInfo.inWidth) {\n                  continue;\n                }\n                const wOffset3 = wOffset2 + wC * filterStrides[2];\n                const xOffset4 = xOffset3 + xC * convInfo.inChannels;\n                let wOffset4 = wOffset3;\n                for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {\n                  const xVal = xVals[xOffset4 + d1];\n                  for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {\n                    yVals[yOffset4 + d2] += xVal * wVals[wOffset4 + d2];\n                  }\n                  wOffset4 += convInfo.outChannels;\n                }\n              }\n            }\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(y.shape, y.dtype, y.values);\n}\nvar conv3DConfig = {\n  kernelName: Conv3D,\n  backendName: \"cpu\",\n  kernelFunc: conv3D\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Conv3DBackpropFilterV2.js\nfunction conv3DBackpropFilterV2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, dy } = inputs;\n  const { strides, pad: pad3, filterShape } = attrs;\n  assertNotComplex([x, dy], \"conv3dBackpropFilterV2\");\n  const xStrides = util_exports.computeStrides(x.shape);\n  const dyStrides = util_exports.computeStrides(dy.shape);\n  const convInfo = backend_util_exports.computeConv3DInfo(x.shape, filterShape, strides, 1, pad3);\n  const strideDepth = convInfo.strideDepth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const filterDepth = convInfo.filterDepth;\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const dw = new TensorBuffer(convInfo.filterShape, \"float32\");\n  const dwValues = dw.values;\n  const [dwS0, dwS1, dwS2, dwS3] = dw.strides;\n  const dyValues = backend2.data.get(dy.dataId).values;\n  const [dyS0, dyS1, dyS2, dyS3] = dyStrides;\n  const xValues = backend2.data.get(x.dataId).values;\n  const [xS0, xS1, xS2, xS3] = xStrides;\n  const frontPad = convInfo.padInfo.front;\n  const leftPad = convInfo.padInfo.left;\n  const topPad = convInfo.padInfo.top;\n  for (let wF = 0; wF < filterDepth; ++wF) {\n    const yFMin = Math.max(0, Math.ceil((frontPad - wF) / strideDepth));\n    const yFMax = Math.min(convInfo.outDepth, (convInfo.inDepth + frontPad - wF) / strideDepth);\n    const wOffset1 = wF * dwS0;\n    for (let wR = 0; wR < filterHeight; ++wR) {\n      const yRMin = Math.max(0, Math.ceil((topPad - wR) / strideHeight));\n      const yRMax = Math.min(convInfo.outHeight, (convInfo.inHeight + topPad - wR) / strideHeight);\n      const wOffset2 = wR * dwS1 + wOffset1;\n      for (let wC = 0; wC < filterWidth; ++wC) {\n        const yCMin = Math.max(0, Math.ceil((leftPad - wC) / strideWidth));\n        const yCMax = Math.min(convInfo.outWidth, (convInfo.inWidth + leftPad - wC) / strideWidth);\n        const wOffset3 = wC * dwS2 + wOffset2;\n        for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {\n          const wOffset4 = d1 * dwS3 + wOffset3;\n          for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {\n            let dotProd = 0;\n            for (let b = 0; b < convInfo.batchSize; ++b) {\n              const xOffset1 = b * xS0;\n              const yOffset1 = b * dyS0;\n              for (let yF = yFMin; yF < yFMax; ++yF) {\n                const xF = wF + yF * strideDepth - frontPad;\n                const xOffset2 = xF * xS1 + xOffset1;\n                const yOffset2 = yF * dyS1 + yOffset1;\n                for (let yR = yRMin; yR < yRMax; ++yR) {\n                  const xR = wR + yR * strideHeight - topPad;\n                  const xOffset3 = xR * xS2 + xOffset2;\n                  const yOffset3 = yR * dyS2 + yOffset2;\n                  for (let yC = yCMin; yC < yCMax; ++yC) {\n                    const xC = wC + yC * strideWidth - leftPad;\n                    const xOffset4 = xC * xS3 + xOffset3;\n                    const yOffset4 = yC * dyS3 + yOffset3;\n                    dotProd += xValues[xOffset4 + d1] * dyValues[yOffset4 + d2];\n                  }\n                }\n              }\n            }\n            dwValues[wOffset4 + d2] = dotProd;\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dw.shape, dw.dtype, dw.values);\n}\nvar conv3DBackpropFilterV2Config = {\n  kernelName: Conv3DBackpropFilterV2,\n  backendName: \"cpu\",\n  kernelFunc: conv3DBackpropFilterV2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Conv3DBackpropInputV2.js\nfunction conv3DBackpropInputV2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, filter } = inputs;\n  const { pad: pad3, strides, inputShape } = attrs;\n  assertNotComplex([dy], \"conv3dBackpropInputV2\");\n  const dyStrides = util_exports.computeStrides(dy.shape);\n  const filterStrides = util_exports.computeStrides(filter.shape);\n  const convInfo = backend_util_exports.computeConv3DInfo(inputShape, filter.shape, strides, 1, pad3);\n  const dx = new TensorBuffer(convInfo.inShape, \"float32\");\n  const dxValues = dx.values;\n  const [dxS0, dxS1, dxS2, dxS3] = dx.strides;\n  const dyValues = backend2.data.get(dy.dataId).values;\n  const [dyS0, dyS1, dyS2, dyS3] = dyStrides;\n  const fltValues = backend2.data.get(filter.dataId).values;\n  const [fltS0, fltS1, fltS2, fltS3] = filterStrides;\n  const { batchSize, filterDepth, filterHeight, filterWidth, inChannels, inDepth, inHeight, inWidth, outChannels, outDepth, outHeight, outWidth, strideDepth, strideHeight, strideWidth } = convInfo;\n  const frontPad = filterDepth - 1 - convInfo.padInfo.front;\n  const topPad = filterHeight - 1 - convInfo.padInfo.top;\n  const leftPad = filterWidth - 1 - convInfo.padInfo.left;\n  for (let b = 0; b < batchSize; ++b) {\n    for (let d1 = 0; d1 < inChannels; ++d1) {\n      for (let xF = 0; xF < inDepth; ++xF) {\n        const xFCorner = xF - frontPad;\n        const xFMin = Math.max(0, Math.ceil(xFCorner / strideDepth));\n        const yFMax = Math.min(outDepth, (filterDepth + xFCorner) / strideDepth);\n        for (let xR = 0; xR < inHeight; ++xR) {\n          const xRCorner = xR - topPad;\n          const xRMin = Math.max(0, Math.ceil(xRCorner / strideHeight));\n          const yRMax = Math.min(outHeight, (filterHeight + xRCorner) / strideHeight);\n          for (let xC = 0; xC < inWidth; ++xC) {\n            const xCCorner = xC - leftPad;\n            const xCMin = Math.max(0, Math.ceil(xCCorner / strideWidth));\n            const yCMax = Math.min(outWidth, (filterWidth + xCCorner) / strideWidth);\n            let dotProd = 0;\n            for (let yF = xFMin; yF < yFMax; ++yF) {\n              const wF = yF * strideDepth - xFCorner;\n              for (let yR = xRMin; yR < yRMax; ++yR) {\n                const wR = yR * strideHeight - xRCorner;\n                for (let yC = xCMin; yC < yCMax; ++yC) {\n                  const wC = yC * strideWidth - xCCorner;\n                  const dyOffset = dyS0 * b + dyS1 * yF + dyS2 * yR + dyS3 * yC;\n                  const fltOffset = fltS0 * (filterDepth - 1 - wF) + fltS1 * (filterHeight - 1 - wR) + fltS2 * (filterWidth - 1 - wC) + fltS3 * d1;\n                  for (let d2 = 0; d2 < outChannels; ++d2) {\n                    const pixel = dyValues[dyOffset + d2];\n                    const weight = fltValues[fltOffset + d2];\n                    dotProd += pixel * weight;\n                  }\n                }\n              }\n            }\n            dxValues[dxS0 * b + dxS1 * xF + dxS2 * xR + dxS3 * xC + d1] = dotProd;\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dx.shape, dx.dtype, dx.values);\n}\nvar conv3DBackpropInputV2Config = {\n  kernelName: Conv3DBackpropInputV2,\n  backendName: \"cpu\",\n  kernelFunc: conv3DBackpropInputV2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Cos.js\nvar cos2 = unaryKernelFunc(Cos, (xi) => Math.cos(xi));\nvar cosConfig = {\n  kernelName: Cos,\n  backendName: \"cpu\",\n  kernelFunc: cos2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Cosh.js\nvar cosh2 = unaryKernelFunc(Cosh, (xi) => Math.cosh(xi));\nvar coshConfig = {\n  kernelName: Cosh,\n  backendName: \"cpu\",\n  kernelFunc: cosh2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/CropAndResize.js\nfunction cropAndResize2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { image: image2, boxes, boxInd } = inputs;\n  const { cropSize, method, extrapolationValue } = attrs;\n  const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n  const numBoxes = boxes.shape[0];\n  const [cropHeight, cropWidth] = cropSize;\n  const output = buffer([numBoxes, cropHeight, cropWidth, numChannels], \"float32\");\n  const boxVals = backend2.data.get(boxes.dataId).values;\n  const boxIndVals = backend2.data.get(boxInd.dataId).values;\n  const imageVals = backend2.data.get(image2.dataId).values;\n  const inStride = util_exports.computeStrides(image2.shape);\n  const outStride = util_exports.computeStrides(output.shape);\n  for (let b = 0; b < numBoxes; b++) {\n    const startInd = b * 4;\n    const y1 = boxVals[startInd];\n    const x1 = boxVals[startInd + 1];\n    const y2 = boxVals[startInd + 2];\n    const x2 = boxVals[startInd + 3];\n    const bInd = boxIndVals[b];\n    if (bInd >= batch) {\n      continue;\n    }\n    const heightScale = cropHeight > 1 ? (y2 - y1) * (imageHeight - 1) / (cropHeight - 1) : 0;\n    const widthScale = cropWidth > 1 ? (x2 - x1) * (imageWidth - 1) / (cropWidth - 1) : 0;\n    for (let y = 0; y < cropHeight; y++) {\n      const yInd = cropHeight > 1 ? y1 * (imageHeight - 1) + y * heightScale : 0.5 * (y1 + y2) * (imageHeight - 1);\n      if (yInd < 0 || yInd > imageHeight - 1) {\n        for (let x = 0; x < cropWidth; x++) {\n          for (let c = 0; c < numChannels; c++) {\n            const ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];\n            output.values[ind] = extrapolationValue;\n          }\n        }\n        continue;\n      }\n      if (method === \"bilinear\") {\n        const topInd = Math.floor(yInd);\n        const bottomInd = Math.ceil(yInd);\n        const yLerp = yInd - topInd;\n        for (let x = 0; x < cropWidth; x++) {\n          const xInd = cropWidth > 1 ? x1 * (imageWidth - 1) + x * widthScale : 0.5 * (x1 + x2) * (imageWidth - 1);\n          if (xInd < 0 || xInd > imageWidth - 1) {\n            for (let c = 0; c < numChannels; c++) {\n              const ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];\n              output.values[ind] = extrapolationValue;\n            }\n            continue;\n          }\n          const leftInd = Math.floor(xInd);\n          const rightInd = Math.ceil(xInd);\n          const xLerp = xInd - leftInd;\n          for (let c = 0; c < numChannels; c++) {\n            let ind = c + leftInd * inStride[2] + topInd * inStride[1] + bInd * inStride[0];\n            const topLeft = imageVals[ind];\n            ind = c + rightInd * inStride[2] + topInd * inStride[1] + bInd * inStride[0];\n            const topRight = imageVals[ind];\n            ind = c + leftInd * inStride[2] + bottomInd * inStride[1] + bInd * inStride[0];\n            const bottomLeft = imageVals[ind];\n            ind = c + rightInd * inStride[2] + bottomInd * inStride[1] + bInd * inStride[0];\n            const bottomRight = imageVals[ind];\n            const top = topLeft + (topRight - topLeft) * xLerp;\n            const bottom = bottomLeft + (bottomRight - bottomLeft) * xLerp;\n            ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];\n            output.values[ind] = top + (bottom - top) * yLerp;\n          }\n        }\n      } else {\n        for (let x = 0; x < cropWidth; ++x) {\n          const xInd = cropWidth > 1 ? x1 * (imageWidth - 1) + x * widthScale : 0.5 * (x1 + x2) * (imageWidth - 1);\n          if (xInd < 0 || xInd > imageWidth - 1) {\n            for (let c = 0; c < numChannels; c++) {\n              const ind = c + x * outStride[2] + y * outStride[1] + b * outStride[0];\n              output.values[ind] = extrapolationValue;\n            }\n            continue;\n          }\n          const closestX = Math.round(xInd);\n          const closestY = Math.round(yInd);\n          for (let c = 0; c < numChannels; c++) {\n            const inInd = c + closestX * inStride[2] + closestY * inStride[1] + bInd * inStride[0];\n            const outInd = c + x * outStride[2] + y * outStride[1] + b * outStride[0];\n            output.values[outInd] = imageVals[inInd];\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(output.shape, output.dtype, output.values);\n}\nvar cropAndResizeConfig = {\n  kernelName: CropAndResize,\n  backendName: \"cpu\",\n  kernelFunc: cropAndResize2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Cumprod.js\nfunction cumprod2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  assertNotComplex(x, \"cumprod\");\n  const permutation = backend_util_exports.getAxesPermutation([axis], x.shape.length);\n  let $x = x;\n  if (permutation != null) {\n    $x = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutation } });\n  }\n  const permutedAxis = backend_util_exports.getInnerMostAxes(1, x.shape.length)[0];\n  if (permutedAxis !== $x.shape.length - 1) {\n    throw new Error(`backend.cumprod in CPU expects an inner-most axis=${$x.shape.length - 1} but got axis=${permutedAxis}`);\n  }\n  const resultDtype = upcastType($x.dtype, \"int32\");\n  const vals = util_exports.makeOnesTypedArray(util_exports.sizeFromShape($x.shape), resultDtype);\n  const aVals = backend2.data.get($x.dataId).values;\n  const finalDim = $x.shape[$x.shape.length - 1];\n  const indexAdjuster = reverse5 ? (i2, j) => i2 + finalDim - j - 1 : (i2, j) => i2 + j;\n  for (let i2 = 0; i2 < aVals.length; i2 += finalDim) {\n    for (let j = 0; j < finalDim; j++) {\n      const idx = indexAdjuster(i2, j);\n      if (j === 0) {\n        vals[idx] = exclusive ? 1 : aVals[idx];\n      } else {\n        const prevIdx = indexAdjuster(i2, j - 1);\n        vals[idx] = exclusive ? aVals[prevIdx] * vals[prevIdx] : aVals[idx] * vals[prevIdx];\n      }\n    }\n  }\n  const result = backend2.makeTensorInfo($x.shape, resultDtype, vals);\n  if (permutation != null) {\n    const reversePermutation = backend_util_exports.getUndoAxesPermutation(permutation);\n    const reverseTransposedResult = transpose2({ inputs: { x: result }, backend: backend2, attrs: { perm: reversePermutation } });\n    backend2.disposeIntermediateTensorInfo(result);\n    backend2.disposeIntermediateTensorInfo($x);\n    return reverseTransposedResult;\n  }\n  return result;\n}\nvar cumprodConfig = {\n  kernelName: Cumprod,\n  backendName: \"cpu\",\n  kernelFunc: cumprod2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Cumsum.js\nfunction cumsum2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  assertNotComplex(x, \"cumsum\");\n  const permutation = backend_util_exports.getAxesPermutation([axis], x.shape.length);\n  let $x = x;\n  if (permutation != null) {\n    $x = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutation } });\n  }\n  const permutedAxis = backend_util_exports.getInnerMostAxes(1, x.shape.length)[0];\n  if (permutedAxis !== $x.shape.length - 1) {\n    throw new Error(`backend.cumsum in CPU expects an inner-most axis=${$x.shape.length - 1} but got axis=${permutedAxis}`);\n  }\n  const resultDtype = upcastType($x.dtype, \"int32\");\n  const vals = util_exports.makeZerosTypedArray(util_exports.sizeFromShape($x.shape), resultDtype);\n  const aVals = backend2.data.get($x.dataId).values;\n  const finalDim = $x.shape[$x.shape.length - 1];\n  const indexAdjuster = reverse5 ? (i2, j) => i2 + finalDim - j - 1 : (i2, j) => i2 + j;\n  for (let i2 = 0; i2 < aVals.length; i2 += finalDim) {\n    for (let j = 0; j < finalDim; j++) {\n      const idx = indexAdjuster(i2, j);\n      if (j === 0) {\n        vals[idx] = exclusive ? 0 : aVals[idx];\n      } else {\n        const prevIdx = indexAdjuster(i2, j - 1);\n        vals[idx] = exclusive ? aVals[prevIdx] + vals[prevIdx] : aVals[idx] + vals[prevIdx];\n      }\n    }\n  }\n  const result = backend2.makeTensorInfo($x.shape, resultDtype, vals);\n  if (permutation != null) {\n    const reversePermutation = backend_util_exports.getUndoAxesPermutation(permutation);\n    const reverseTransposedResult = transpose2({ inputs: { x: result }, backend: backend2, attrs: { perm: reversePermutation } });\n    backend2.disposeIntermediateTensorInfo(result);\n    backend2.disposeIntermediateTensorInfo($x);\n    return reverseTransposedResult;\n  }\n  return result;\n}\nvar cumsumConfig = {\n  kernelName: Cumsum,\n  backendName: \"cpu\",\n  kernelFunc: cumsum2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/DenseBincount.js\nfunction denseBincount2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, weights } = inputs;\n  const { size, binaryOutput } = attrs;\n  if (x.shape.length === 1) {\n    const xVals = backend2.data.get(x.dataId).values;\n    const weightsVals = backend2.data.get(weights.dataId).values;\n    const outVals = bincountImpl(xVals, weightsVals, weights.dtype, weights.shape, size);\n    return backend2.makeTensorInfo([size], weights.dtype, outVals);\n  } else if (x.shape.length === 2) {\n    const xBuf = backend2.bufferSync(x);\n    const weightsBuf = backend2.bufferSync(weights);\n    const outBuf = bincountReduceImpl(xBuf, weightsBuf, size, binaryOutput);\n    return backend2.makeTensorInfo(outBuf.shape, weights.dtype, outBuf.values);\n  }\n  throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${x.shape.length}.`);\n}\nvar denseBincountConfig = {\n  kernelName: DenseBincount,\n  backendName: \"cpu\",\n  kernelFunc: denseBincount2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/DepthToSpace.js\nfunction depthToSpace2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockSize, dataFormat } = attrs;\n  util_exports.assert(dataFormat === \"NHWC\", () => `Only NHWC dataFormat supported on CPU for depthToSpace. Got ${dataFormat}`);\n  const batchSize = x.shape[0];\n  const inputHeight = x.shape[1];\n  const inputWidth = x.shape[2];\n  const inputDepth = x.shape[3];\n  const outputHeight = inputHeight * blockSize;\n  const outputWidth = inputWidth * blockSize;\n  const outputDepth = inputDepth / (blockSize * blockSize);\n  const xValues = backend2.data.get(x.dataId).values;\n  const result = new Float32Array(batchSize * outputHeight * outputWidth * outputDepth);\n  let outputIdx = 0;\n  for (let b = 0; b < batchSize; ++b) {\n    for (let h = 0; h < outputHeight; ++h) {\n      const inH = Math.floor(h / blockSize);\n      const offsetH = h % blockSize;\n      for (let w = 0; w < outputWidth; ++w) {\n        const inW = Math.floor(w / blockSize);\n        const offsetW = w % blockSize;\n        const offsetD = (offsetH * blockSize + offsetW) * outputDepth;\n        for (let d = 0; d < outputDepth; ++d) {\n          const inD = d + offsetD;\n          const inputIdx = inD + inputDepth * (inW + inputWidth * (inH + inputHeight * b));\n          result[outputIdx++] = xValues[inputIdx];\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo([batchSize, outputHeight, outputWidth, outputDepth], x.dtype, result);\n}\nvar depthToSpaceConfig = {\n  kernelName: DepthToSpace,\n  backendName: \"cpu\",\n  kernelFunc: depthToSpace2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/DepthwiseConv2dNative.js\nfunction depthwiseConv2dNative(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dilations, dimRoundingMode } = attrs;\n  assertNotComplex([x, filter], \"depthwiseConv2DNative\");\n  const xStrides = util_exports.computeStrides(x.shape);\n  const filterStrides = util_exports.computeStrides(filter.shape);\n  let $dilations = dilations;\n  if ($dilations == null) {\n    $dilations = [1, 1];\n  }\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, $dilations), () => `Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${strides} and dilations '${$dilations}'`);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad3, dimRoundingMode, true);\n  const { filterHeight, filterWidth, dilationHeight, dilationWidth, padInfo } = convInfo;\n  const padLeft = padInfo.left;\n  const padTop = padInfo.top;\n  const chMul = convInfo.outChannels / convInfo.inChannels;\n  const y = new TensorBuffer(convInfo.outShape, x.dtype);\n  const xVals = backend2.data.get(x.dataId).values;\n  const wVals = backend2.data.get(filter.dataId).values;\n  const yVals = y.values;\n  for (let b = 0; b < convInfo.batchSize; ++b) {\n    const xOffset1 = b * xStrides[0];\n    const yOffset1 = b * y.strides[0];\n    for (let yR = 0; yR < convInfo.outHeight; ++yR) {\n      const yOffset2 = yOffset1 + yR * y.strides[1];\n      const xRCorner = yR * convInfo.strideHeight - padTop;\n      for (let wR = 0; wR < filterHeight; ++wR) {\n        const xR = xRCorner + wR * dilationHeight;\n        if (xR < 0 || xR >= convInfo.inHeight) {\n          continue;\n        }\n        const wOffset1 = wR * filterStrides[0];\n        const xOffset2 = xOffset1 + xR * xStrides[1];\n        for (let yC = 0; yC < convInfo.outWidth; ++yC) {\n          const yOffset3 = yOffset2 + yC * y.strides[2];\n          const xCCorner = yC * convInfo.strideWidth - padLeft;\n          for (let wC = 0; wC < filterWidth; ++wC) {\n            const xC = xCCorner + wC * dilationWidth;\n            if (xC < 0 || xC >= convInfo.inWidth) {\n              continue;\n            }\n            const wOffset2 = wOffset1 + wC * filterStrides[1];\n            const xOffset3 = xOffset2 + xC * convInfo.inChannels;\n            let yOffset4 = yOffset3;\n            let wOffset3 = wOffset2;\n            for (let d1 = 0; d1 < convInfo.inChannels; ++d1) {\n              const xVal = xVals[xOffset3 + d1];\n              for (let q = 0; q < chMul; ++q) {\n                yVals[yOffset4 + q] += xVal * wVals[wOffset3 + q];\n              }\n              yOffset4 += chMul;\n              wOffset3 += chMul;\n            }\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(y.shape, y.dtype, y.values);\n}\nvar depthwiseConv2dNativeConfig = {\n  kernelName: DepthwiseConv2dNative,\n  backendName: \"cpu\",\n  kernelFunc: depthwiseConv2dNative\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/DepthwiseConv2dNativeBackpropFilter.js\nfunction depthwiseConv2dNativeBackpropFilter2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, dy } = inputs;\n  const { strides, dilations, pad: pad3, dimRoundingMode, filterShape } = attrs;\n  assertNotComplex([x, dy], \"depthwiseConv2dNativeBackpropFilter\");\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filterShape, strides, dilations, pad3, dimRoundingMode, true);\n  const { strideHeight, strideWidth, filterHeight, filterWidth } = convInfo;\n  const dW = new TensorBuffer(convInfo.filterShape, \"float32\");\n  const leftPad = convInfo.padInfo.left;\n  const topPad = convInfo.padInfo.top;\n  const chMul = convInfo.outChannels / convInfo.inChannels;\n  const xVals = backend2.data.get(x.dataId).values;\n  const xBuf = new TensorBuffer(x.shape, x.dtype, xVals);\n  const dyVals = backend2.data.get(dy.dataId).values;\n  const dyBuf = new TensorBuffer(dy.shape, dy.dtype, dyVals);\n  for (let wR = 0; wR < filterHeight; ++wR) {\n    const yRMin = Math.max(0, Math.ceil((topPad - wR) / strideHeight));\n    const yRMax = Math.min(convInfo.outHeight, (convInfo.inHeight + topPad - wR) / strideHeight);\n    for (let wC = 0; wC < filterWidth; ++wC) {\n      const yCMin = Math.max(0, Math.ceil((leftPad - wC) / strideWidth));\n      const yCMax = Math.min(convInfo.outWidth, (convInfo.inWidth + leftPad - wC) / strideWidth);\n      for (let d2 = 0; d2 < convInfo.outChannels; ++d2) {\n        const d1 = Math.trunc(d2 / chMul);\n        const dm = d2 % chMul;\n        let dotProd = 0;\n        for (let b = 0; b < convInfo.batchSize; ++b) {\n          for (let yR = yRMin; yR < yRMax; ++yR) {\n            const xR = wR + yR * strideHeight - topPad;\n            for (let yC = yCMin; yC < yCMax; ++yC) {\n              const xC = wC + yC * strideWidth - leftPad;\n              dotProd += xBuf.get(b, xR, xC, d1) * dyBuf.get(b, yR, yC, d2);\n            }\n          }\n        }\n        dW.set(dotProd, wR, wC, d1, dm);\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dW.shape, dW.dtype, dW.values);\n}\nvar depthwiseConv2dNativeBackpropFilterConfig = {\n  kernelName: DepthwiseConv2dNativeBackpropFilter,\n  backendName: \"cpu\",\n  kernelFunc: depthwiseConv2dNativeBackpropFilter2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/DepthwiseConv2dNativeBackpropInput.js\nfunction depthwiseConv2dNativeBackpropInput2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, filter } = inputs;\n  const { strides, dilations, pad: pad3, dimRoundingMode, inputShape } = attrs;\n  assertNotComplex([dy, filter], \"depthwiseConv2DNativeBackpropInput\");\n  const dyStrides = util_exports.computeStrides(dy.shape);\n  const filterStrides = util_exports.computeStrides(filter.shape);\n  const convInfo = backend_util_exports.computeConv2DInfo(inputShape, filter.shape, strides, dilations, pad3, dimRoundingMode, true);\n  const dx = new TensorBuffer(convInfo.inShape, \"float32\");\n  const dxValues = dx.values;\n  const [dxS0, dxS1, dxS2] = dx.strides;\n  const dyValues = backend2.data.get(dy.dataId).values;\n  const [dyS0, dyS1, dyS2] = dyStrides;\n  const fltValues = backend2.data.get(filter.dataId).values;\n  const [fltS0, fltS1, fltS2] = filterStrides;\n  const { batchSize, filterHeight, filterWidth, inChannels, inHeight, inWidth, outChannels, outHeight, outWidth, strideHeight, strideWidth } = convInfo;\n  const topPad = filterHeight - 1 - convInfo.padInfo.top;\n  const leftPad = filterWidth - 1 - convInfo.padInfo.left;\n  const chMul = outChannels / inChannels;\n  for (let b = 0; b < batchSize; ++b) {\n    for (let d1 = 0; d1 < inChannels; ++d1) {\n      for (let xR = 0; xR < inHeight; ++xR) {\n        const xRCorner = xR - topPad;\n        const xRMin = Math.max(0, Math.ceil(xRCorner / strideHeight));\n        const yRMax = Math.min(outHeight, (filterHeight + xRCorner) / strideHeight);\n        for (let xC = 0; xC < inWidth; ++xC) {\n          const xCCorner = xC - leftPad;\n          const xCMin = Math.max(0, Math.ceil(xCCorner / strideWidth));\n          const yCMax = Math.min(outWidth, (filterWidth + xCCorner) / strideWidth);\n          let dotProd = 0;\n          for (let yR = xRMin; yR < yRMax; ++yR) {\n            const wR = yR * strideHeight - xRCorner;\n            for (let yC = xCMin; yC < yCMax; ++yC) {\n              const wC = yC * strideWidth - xCCorner;\n              const dyOffset = dyS0 * b + dyS1 * yR + dyS2 * yC;\n              const fltOffset = fltS0 * (filterHeight - 1 - wR) + fltS1 * (filterWidth - 1 - wC) + fltS2 * d1;\n              for (let dm = 0; dm < chMul; ++dm) {\n                const d2 = d1 * chMul + dm;\n                const pixel = dyValues[dyOffset + d2];\n                const weight = fltValues[fltOffset + dm];\n                dotProd += pixel * weight;\n              }\n            }\n          }\n          dxValues[dxS0 * b + dxS1 * xR + dxS2 * xC + d1] = dotProd;\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dx.shape, dx.dtype, dx.values);\n}\nvar depthwiseConv2dNativeBackpropInputConfig = {\n  kernelName: DepthwiseConv2dNativeBackpropInput,\n  backendName: \"cpu\",\n  kernelFunc: depthwiseConv2dNativeBackpropInput2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Diag.js\nfunction diag2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const xVals = backend2.data.get(x.dataId).values;\n  const outBuf = buffer([xSize, xSize], x.dtype);\n  const vals = outBuf.values;\n  for (let i2 = 0; i2 < xVals.length; i2++) {\n    vals[i2 * xSize + i2] = xVals[i2];\n  }\n  const outShape = [...x.shape, ...x.shape];\n  return backend2.makeTensorInfo(outShape, outBuf.dtype, outBuf.values);\n}\nvar diagConfig = {\n  kernelName: Diag,\n  backendName: \"cpu\",\n  kernelFunc: diag2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Dilation2D.js\nvar dilation2DConfig = {\n  kernelName: Dilation2D,\n  backendName: \"cpu\",\n  kernelFunc: ({ inputs, backend: backend2, attrs }) => {\n    const { x, filter } = inputs;\n    const { strides, pad: pad3, dilations } = attrs;\n    const cpuBackend = backend2;\n    const xVals = cpuBackend.data.get(x.dataId).values;\n    const xRank = x.shape.length;\n    const filterVals = cpuBackend.data.get(filter.dataId).values;\n    const filterRank = filter.shape.length;\n    const { batchSize, inHeight, inWidth, inChannels, outHeight, outWidth, padInfo, strideHeight, strideWidth, filterHeight, filterWidth, dilationHeight, dilationWidth, outShape } = backend_util_exports.computeDilation2DInfo(x.shape, filter.shape, strides, pad3, \"NHWC\", dilations);\n    const outSize = util_exports.sizeFromShape(outShape);\n    const outRank = outShape.length;\n    const outputVals = util_exports.getArrayFromDType(x.dtype, outSize);\n    for (let b = 0; b < batchSize; ++b) {\n      for (let hOut = 0; hOut < outHeight; ++hOut) {\n        const hBeg = hOut * strideHeight - padInfo.top;\n        for (let wOut = 0; wOut < outWidth; ++wOut) {\n          const wBeg = wOut * strideWidth - padInfo.left;\n          for (let d = 0; d < inChannels; ++d) {\n            let curVal = Number.MIN_SAFE_INTEGER;\n            for (let h = 0; h < filterHeight; ++h) {\n              const hIn = hBeg + h * dilationHeight;\n              if (hIn >= 0 && hIn < inHeight) {\n                for (let w = 0; w < filterWidth; ++w) {\n                  const wIn = wBeg + w * dilationWidth;\n                  if (wIn >= 0 && wIn < inWidth) {\n                    const xIndex = util_exports.locToIndex([b, hIn, wIn, d], xRank, util_exports.computeStrides(x.shape));\n                    const filterIndex = util_exports.locToIndex([h, w, d], filterRank, util_exports.computeStrides(filter.shape));\n                    const val = xVals[xIndex] + filterVals[filterIndex];\n                    if (val > curVal) {\n                      curVal = val;\n                    }\n                  }\n                }\n              }\n            }\n            const outputIndex = util_exports.locToIndex([b, hOut, wOut, d], outRank, util_exports.computeStrides(outShape));\n            outputVals[outputIndex] = curVal;\n          }\n        }\n      }\n    }\n    const dataId = cpuBackend.write(util_exports.toTypedArray(outputVals, x.dtype), outShape, x.dtype);\n    return { dataId, shape: outShape, dtype: x.dtype };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Dilation2DBackpropFilter.js\nvar dilation2DBackpropFilterConfig = {\n  kernelName: Dilation2DBackpropFilter,\n  backendName: \"cpu\",\n  kernelFunc: ({ inputs, backend: backend2, attrs }) => {\n    const { x, filter, dy } = inputs;\n    const { strides, pad: pad3, dilations } = attrs;\n    const cpuBackend = backend2;\n    const $x = util_exports.toNestedArray(x.shape, cpuBackend.data.get(x.dataId).values);\n    const $filter = util_exports.toNestedArray(filter.shape, cpuBackend.data.get(filter.dataId).values);\n    const { batchSize, inHeight, inWidth, inChannels, outHeight, outWidth, padInfo, strideHeight, strideWidth, filterHeight, filterWidth, dilationHeight, dilationWidth, outShape } = backend_util_exports.computeDilation2DInfo(x.shape, filter.shape, strides, pad3, \"NHWC\", dilations);\n    util_exports.assert(dy.rank === outShape.length, () => `Error in ${Dilation2DBackpropFilter}, dy must have the same rank as output ${outShape.length}, but got ${dy.rank}`);\n    const $dy = util_exports.toNestedArray(outShape, cpuBackend.data.get(dy.dataId).values);\n    const gradients = util_exports.makeZerosNestedTypedArray(filter.shape, filter.dtype);\n    for (let b = 0; b < batchSize; ++b) {\n      for (let hOut = 0; hOut < outHeight; ++hOut) {\n        const hBeg = hOut * strideHeight - padInfo.top;\n        for (let wOut = 0; wOut < outWidth; ++wOut) {\n          const wBeg = wOut * strideWidth - padInfo.left;\n          for (let d = 0; d < inChannels; ++d) {\n            let curVal = Number.MIN_SAFE_INTEGER;\n            let hMax = 0;\n            let wMax = 0;\n            for (let h = 0; h < filterHeight; ++h) {\n              const hIn = hBeg + h * dilationHeight;\n              if (hIn >= 0 && hIn < inHeight) {\n                for (let w = 0; w < filterWidth; ++w) {\n                  const wIn = wBeg + w * dilationWidth;\n                  if (wIn >= 0 && wIn < inWidth) {\n                    const val = $x[b][hIn][wIn][d] + $filter[h][w][d];\n                    if (val > curVal) {\n                      curVal = val;\n                      hMax = h;\n                      wMax = w;\n                    }\n                  }\n                }\n              }\n            }\n            gradients[hMax][wMax][d] += $dy[b][hOut][wOut][d];\n          }\n        }\n      }\n    }\n    const dataId = cpuBackend.write(util_exports.toTypedArray(gradients, x.dtype), filter.shape, filter.dtype);\n    return { dataId, shape: filter.shape, dtype: filter.dtype };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Dilation2DBackpropInput.js\nvar dilation2DBackpropInputConfig = {\n  kernelName: Dilation2DBackpropInput,\n  backendName: \"cpu\",\n  kernelFunc: ({ inputs, backend: backend2, attrs }) => {\n    const { x, filter, dy } = inputs;\n    const { strides, pad: pad3, dilations } = attrs;\n    const cpuBackend = backend2;\n    const $x = util_exports.toNestedArray(x.shape, cpuBackend.data.get(x.dataId).values);\n    const $filter = util_exports.toNestedArray(filter.shape, cpuBackend.data.get(filter.dataId).values);\n    const { batchSize, inHeight, inWidth, inChannels, outHeight, outWidth, padInfo, strideHeight, strideWidth, filterHeight, filterWidth, dilationHeight, dilationWidth, outShape } = backend_util_exports.computeDilation2DInfo(x.shape, filter.shape, strides, pad3, \"NHWC\", dilations);\n    util_exports.assert(dy.rank === outShape.length, () => `Error in ${Dilation2DBackpropInput}, dy must have the same rank as output ${outShape.length}, but got ${dy.rank}`);\n    const $dy = util_exports.toNestedArray(outShape, cpuBackend.data.get(dy.dataId).values);\n    const gradients = util_exports.makeZerosNestedTypedArray(x.shape, x.dtype);\n    for (let b = 0; b < batchSize; ++b) {\n      for (let hOut = 0; hOut < outHeight; ++hOut) {\n        const hBeg = hOut * strideHeight - padInfo.top;\n        for (let wOut = 0; wOut < outWidth; ++wOut) {\n          const wBeg = wOut * strideWidth - padInfo.left;\n          for (let d = 0; d < inChannels; ++d) {\n            let curVal = Number.MIN_SAFE_INTEGER;\n            let hInMax = hBeg < 0 ? 0 : hBeg;\n            let wInMax = wBeg < 0 ? 0 : wBeg;\n            for (let h = 0; h < filterHeight; ++h) {\n              const hIn = hBeg + h * dilationHeight;\n              if (hIn >= 0 && hIn < inHeight) {\n                for (let w = 0; w < filterWidth; ++w) {\n                  const wIn = wBeg + w * dilationWidth;\n                  if (wIn >= 0 && wIn < inWidth) {\n                    const val = $x[b][hIn][wIn][d] + $filter[h][w][d];\n                    if (val > curVal) {\n                      curVal = val;\n                      hInMax = hIn;\n                      wInMax = wIn;\n                    }\n                  }\n                }\n              }\n            }\n            gradients[b][hInMax][wInMax][d] += $dy[b][hOut][wOut][d];\n          }\n        }\n      }\n    }\n    const dataId = cpuBackend.write(util_exports.toTypedArray(gradients, x.dtype), x.shape, x.dtype);\n    return { dataId, shape: x.shape, dtype: x.dtype };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Sum.js\nfunction sum3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  assertNotComplex(x, \"sum\");\n  let $x;\n  if (x.dtype === \"bool\") {\n    $x = cast3({ inputs: { x }, backend: backend2, attrs: { dtype: \"int32\" } });\n  } else {\n    $x = identity2({ inputs: { x }, backend: backend2 });\n  }\n  const xRank = $x.shape.length;\n  const axes = util_exports.parseAxisParam(axis, $x.shape);\n  const permutation = backend_util_exports.getAxesPermutation(axes, xRank);\n  let reductionAxes = axes;\n  let permutedX = $x;\n  if (permutation != null) {\n    permutedX = transpose2({ inputs: { x: $x }, backend: backend2, attrs: { perm: permutation } });\n    reductionAxes = backend_util_exports.getInnerMostAxes(reductionAxes.length, xRank);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"sum\", reductionAxes, permutedX.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(permutedX.shape, reductionAxes);\n  const resultDtype = backend_util_exports.upcastType(permutedX.dtype, \"int32\");\n  let result = zeros3(backend2, outShape, resultDtype);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const vals = backend2.data.get(result.dataId).values;\n  const aVals = backend2.data.get(permutedX.dataId).values;\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let sum7 = 0;\n    for (let j = 0; j < reduceSize; ++j) {\n      sum7 += aVals[offset + j];\n    }\n    vals[i2] = sum7;\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(result.shape, axes);\n    const oldResult = result;\n    result = reshape3({ inputs: { x: result }, backend: backend2, attrs: { shape: newShape } });\n    backend2.disposeIntermediateTensorInfo(oldResult);\n  }\n  backend2.disposeIntermediateTensorInfo($x);\n  if (permutation != null) {\n    backend2.disposeIntermediateTensorInfo(permutedX);\n  }\n  return result;\n}\nvar sumConfig = {\n  kernelName: Sum,\n  backendName: \"cpu\",\n  kernelFunc: sum3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Einsum.js\nfunction einsum2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { equation } = attrs;\n  const tensors = inputs;\n  const { allDims, summedDims, idDims } = backend_util_exports.decodeEinsumEquation(equation, tensors.length);\n  backend_util_exports.checkEinsumDimSizes(allDims.length, idDims, tensors);\n  const { path, steps } = backend_util_exports.getEinsumComputePath(summedDims, idDims);\n  const nSteps = steps.length;\n  let out = null;\n  let numDimsRemaining = allDims.length;\n  const tensorsToDispose = [];\n  for (let i2 = 0; i2 < nSteps; ++i2) {\n    for (const idTerm of steps[i2]) {\n      const { permutationIndices: perm, expandDims: dimsToExpand } = backend_util_exports.getEinsumPermutation(numDimsRemaining, idDims[idTerm]);\n      let x;\n      if (backend_util_exports.isIdentityPermutation(perm)) {\n        x = tensors[idTerm];\n      } else {\n        x = transpose2({ inputs: { x: tensors[idTerm] }, backend: backend2, attrs: { perm } });\n        tensorsToDispose.push(x);\n      }\n      const targetShape = x.shape.slice();\n      for (let k = 0; k < dimsToExpand.length; ++k) {\n        targetShape.splice(dimsToExpand[k], 0, 1);\n      }\n      if (!util_exports.arraysEqual(x.shape, targetShape)) {\n        x = reshape3({ inputs: { x }, backend: backend2, attrs: { shape: targetShape } });\n        tensorsToDispose.push(x);\n      }\n      if (out === null) {\n        out = x;\n      } else {\n        out = multiply2({ inputs: { a: x, b: out }, backend: backend2 });\n        tensorsToDispose.push(out);\n      }\n    }\n    if (i2 < nSteps - 1) {\n      if (path[i2] >= 0) {\n        out = sum3({\n          inputs: { x: out },\n          backend: backend2,\n          attrs: {\n            axis: path[i2] - (allDims.length - numDimsRemaining),\n            keepDims: false\n          }\n        });\n        tensorsToDispose.push(out);\n      }\n      numDimsRemaining--;\n    }\n  }\n  for (const tensorInfo of tensorsToDispose) {\n    if (tensorInfo === out) {\n      continue;\n    }\n    backend2.disposeIntermediateTensorInfo(tensorInfo);\n  }\n  return out;\n}\nvar einsumConfig = {\n  kernelName: Einsum,\n  backendName: \"cpu\",\n  kernelFunc: einsum2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/EluGrad.js\nfunction eluGrad(args) {\n  const { inputs, backend: backend2 } = args;\n  const { dy, y } = inputs;\n  assertNotComplex([dy, y], \"eluGrad\");\n  const resultValues = new Float32Array(util_exports.sizeFromShape(y.shape));\n  const values = backend2.data.get(y.dataId).values;\n  const dyValues = backend2.data.get(dy.dataId).values;\n  for (let i2 = 0; i2 < values.length; ++i2) {\n    const v = values[i2];\n    if (v >= 1) {\n      resultValues[i2] = dyValues[i2];\n    } else {\n      resultValues[i2] = dyValues[i2] * (v + 1);\n    }\n  }\n  return backend2.makeTensorInfo(y.shape, \"float32\", resultValues);\n}\nvar eluGradConfig2 = {\n  kernelName: EluGrad,\n  backendName: \"cpu\",\n  kernelFunc: eluGrad\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Erf.js\nvar p = backend_util_exports.ERF_P;\nvar a1 = backend_util_exports.ERF_A1;\nvar a2 = backend_util_exports.ERF_A2;\nvar a3 = backend_util_exports.ERF_A3;\nvar a4 = backend_util_exports.ERF_A4;\nvar a5 = backend_util_exports.ERF_A5;\nvar erf2 = unaryKernelFunc(Erf, (xi) => {\n  const sign4 = Math.sign(xi);\n  const v = Math.abs(xi);\n  const t2 = 1 / (1 + p * v);\n  return sign4 * (1 - ((((a5 * t2 + a4) * t2 + a3) * t2 + a2) * t2 + a1) * t2 * Math.exp(-v * v));\n});\nvar erfConfig = {\n  kernelName: Erf,\n  backendName: \"cpu\",\n  kernelFunc: erf2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ExpandDims.js\nfunction expandDims3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { input: input2 } = inputs;\n  const { dim } = attrs;\n  const inputRank = input2.shape.length;\n  const newShape = input2.shape.slice();\n  let $dim = dim;\n  if (dim < 0) {\n    util_exports.assert(-(inputRank + 1) <= dim, () => `Axis must be in the interval [${-(inputRank + 1)}, ${inputRank}]`);\n    $dim = inputRank + dim + 1;\n  }\n  newShape.splice($dim, 0, 1);\n  return reshape3({ inputs: { x: input2 }, backend: backend2, attrs: { shape: newShape } });\n}\nvar expandDimsConfig = {\n  kernelName: ExpandDims,\n  backendName: \"cpu\",\n  kernelFunc: expandDims3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/RealDiv.js\nvar realDivImpl = createSimpleBinaryKernelImpl((a, b) => a / b);\nvar div2 = binaryKernelFunc(RealDiv, realDivImpl);\nvar realDivConfig = {\n  kernelName: RealDiv,\n  backendName: \"cpu\",\n  kernelFunc: div2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/utils/fft_utils.js\nfunction fftBatch(input2, inverse, cpuBackend) {\n  const inputShape = input2.shape;\n  const batch = inputShape[0];\n  const innerDim = inputShape[1];\n  const inputVals = cpuBackend.data.get(input2.dataId);\n  const real2D = inputVals.complexTensorInfos.real;\n  const imag2D = inputVals.complexTensorInfos.imag;\n  const resultShape = [batch, innerDim];\n  const resultSize = util_exports.sizeFromShape(resultShape);\n  const resultReal = util_exports.getTypedArrayFromDType(\"float32\", resultSize);\n  const resultImag = util_exports.getTypedArrayFromDType(\"float32\", resultSize);\n  for (let b = 0; b < batch; b++) {\n    const r2 = slice2({\n      inputs: { x: real2D },\n      backend: cpuBackend,\n      attrs: { begin: [b, 0], size: [1, innerDim] }\n    });\n    const i2 = slice2({\n      inputs: { x: imag2D },\n      backend: cpuBackend,\n      attrs: { begin: [b, 0], size: [1, innerDim] }\n    });\n    const input3 = complex2({ inputs: { real: r2, imag: i2 }, backend: cpuBackend });\n    const { real: real5, imag: imag5 } = fftImpl(input3, inverse, cpuBackend);\n    const res = backend_util_exports.mergeRealAndImagArrays(real5, imag5);\n    for (let d = 0; d < innerDim; d++) {\n      const c = backend_util_exports.getComplexWithIndex(res, d);\n      resultReal[b * innerDim + d] = c.real;\n      resultImag[b * innerDim + d] = c.imag;\n    }\n    cpuBackend.disposeIntermediateTensorInfo(r2);\n    cpuBackend.disposeIntermediateTensorInfo(i2);\n    cpuBackend.disposeIntermediateTensorInfo(input3);\n  }\n  const $realInfo = cpuBackend.makeTensorInfo(resultShape, \"float32\", resultReal);\n  const $imagInfo = cpuBackend.makeTensorInfo(resultShape, \"float32\", resultImag);\n  const result = complex2({ inputs: { real: $realInfo, imag: $imagInfo }, backend: cpuBackend });\n  cpuBackend.disposeIntermediateTensorInfo($realInfo);\n  cpuBackend.disposeIntermediateTensorInfo($imagInfo);\n  return result;\n}\nfunction fftImpl(input2, inverse, cpuBackend) {\n  const inputSize = util_exports.sizeFromShape(input2.shape);\n  const inputVals = cpuBackend.data.get(input2.dataId);\n  const realVals = cpuBackend.data.get(inputVals.complexTensorInfos.real.dataId).values;\n  const imagVals = cpuBackend.data.get(inputVals.complexTensorInfos.imag.dataId).values;\n  if (isExponentOf2(inputSize)) {\n    const result = fftRadix2(realVals, imagVals, inputSize, inverse, cpuBackend);\n    const resultShape = [input2.shape[0], input2.shape[1]];\n    if (inverse) {\n      const realInfo = cpuBackend.makeTensorInfo(resultShape, \"float32\", result.real);\n      const imagInfo = cpuBackend.makeTensorInfo(resultShape, \"float32\", result.imag);\n      const sizeInfo = cpuBackend.makeTensorInfo([], \"float32\", util_exports.createScalarValue(inputSize, \"float32\"));\n      const sizeInfoCopy = identity2({ inputs: { x: sizeInfo }, backend: cpuBackend });\n      const divRealInfo = realDivConfig.kernelFunc({ inputs: { a: realInfo, b: sizeInfo }, backend: cpuBackend });\n      const divImagInfo = realDivConfig.kernelFunc({ inputs: { a: imagInfo, b: sizeInfoCopy }, backend: cpuBackend });\n      const divRealVals = cpuBackend.data.get(divRealInfo.dataId).values;\n      const divImagVals = cpuBackend.data.get(divImagInfo.dataId).values;\n      cpuBackend.disposeIntermediateTensorInfo(realInfo);\n      cpuBackend.disposeIntermediateTensorInfo(imagInfo);\n      cpuBackend.disposeIntermediateTensorInfo(sizeInfo);\n      cpuBackend.disposeIntermediateTensorInfo(sizeInfoCopy);\n      cpuBackend.disposeIntermediateTensorInfo(divRealInfo);\n      cpuBackend.disposeIntermediateTensorInfo(divImagInfo);\n      return { real: divRealVals, imag: divImagVals };\n    }\n    return result;\n  } else {\n    const data = backend_util_exports.mergeRealAndImagArrays(realVals, imagVals);\n    const rawOutput = fourierTransformByMatmul(data, inputSize, inverse);\n    return backend_util_exports.splitRealAndImagArrays(rawOutput);\n  }\n}\nfunction isExponentOf2(size) {\n  return (size & size - 1) === 0;\n}\nfunction fftRadix2(realVals, imagVals, size, inverse, cpuBackend) {\n  if (size === 1) {\n    return { real: realVals, imag: imagVals };\n  }\n  const data = backend_util_exports.mergeRealAndImagArrays(realVals, imagVals);\n  const half = size / 2;\n  const evenComplex = backend_util_exports.complexWithEvenIndex(data);\n  const evenRealVals = evenComplex.real;\n  const evenImagVals = evenComplex.imag;\n  const evenShape = [evenRealVals.length];\n  const evenRealInfo = cpuBackend.makeTensorInfo(evenShape, \"float32\", evenRealVals);\n  const evenImagInfo = cpuBackend.makeTensorInfo(evenShape, \"float32\", evenImagVals);\n  const evenTensorInfo = complex2({ inputs: { real: evenRealInfo, imag: evenImagInfo }, backend: cpuBackend });\n  const oddComplex = backend_util_exports.complexWithOddIndex(data);\n  const oddRealVals = oddComplex.real;\n  const oddImagVals = oddComplex.imag;\n  const oddShape = [oddRealVals.length];\n  const oddRealInfo = cpuBackend.makeTensorInfo(oddShape, \"float32\", oddRealVals);\n  const oddImagInfo = cpuBackend.makeTensorInfo(oddShape, \"float32\", oddImagVals);\n  const oddTensorInfo = complex2({ inputs: { real: oddRealInfo, imag: oddImagInfo }, backend: cpuBackend });\n  const $evenComplex = fftRadix2(evenRealVals, evenImagVals, half, inverse, cpuBackend);\n  const $evenRealVals = $evenComplex.real;\n  const $evenImagVals = $evenComplex.imag;\n  const $evenShape = [$evenRealVals.length];\n  const $evenRealInfo = cpuBackend.makeTensorInfo($evenShape, \"float32\", $evenRealVals);\n  const $evenImagInfo = cpuBackend.makeTensorInfo($evenShape, \"float32\", $evenImagVals);\n  const $evenTensorInfo = complex2({\n    inputs: { real: $evenRealInfo, imag: $evenImagInfo },\n    backend: cpuBackend\n  });\n  const $oddComplex = fftRadix2(oddRealVals, oddImagVals, half, inverse, cpuBackend);\n  const $oddRealVals = $oddComplex.real;\n  const $oddImagVals = $oddComplex.imag;\n  const $oddShape = [$oddRealVals.length];\n  const $oddRealInfo = cpuBackend.makeTensorInfo($oddShape, \"float32\", $oddRealVals);\n  const $oddImagInfo = cpuBackend.makeTensorInfo($oddShape, \"float32\", $oddImagVals);\n  const $oddTensorInfo = complex2({ inputs: { real: $oddRealInfo, imag: $oddImagInfo }, backend: cpuBackend });\n  const e2 = backend_util_exports.exponents(size, inverse);\n  const eShape = [e2.real.length];\n  const eRealInfo = cpuBackend.makeTensorInfo(eShape, \"float32\", e2.real);\n  const eImagInfo = cpuBackend.makeTensorInfo(eShape, \"float32\", e2.imag);\n  const complexInfo = complex2({ inputs: { real: eRealInfo, imag: eImagInfo }, backend: cpuBackend });\n  const exponentInfo = multiply2({ inputs: { a: complexInfo, b: $oddTensorInfo }, backend: cpuBackend });\n  const addPart = add4({\n    inputs: { a: $evenTensorInfo, b: exponentInfo },\n    backend: cpuBackend\n  });\n  const subPart = sub2({\n    inputs: { a: $evenTensorInfo, b: exponentInfo },\n    backend: cpuBackend\n  });\n  const addPartReal = real2({ inputs: { input: addPart }, backend: cpuBackend });\n  const subPartReal = real2({ inputs: { input: subPart }, backend: cpuBackend });\n  const addPartImag = imag2({ inputs: { input: addPart }, backend: cpuBackend });\n  const subPartImag = imag2({ inputs: { input: subPart }, backend: cpuBackend });\n  const $real = concat2({\n    inputs: [addPartReal, subPartReal],\n    backend: cpuBackend,\n    attrs: { axis: 0 }\n  });\n  const $imag = concat2({\n    inputs: [addPartImag, subPartImag],\n    backend: cpuBackend,\n    attrs: { axis: 0 }\n  });\n  const $realVals = cpuBackend.data.get($real.dataId).values;\n  const $imagVals = cpuBackend.data.get($imag.dataId).values;\n  cpuBackend.disposeIntermediateTensorInfo(evenRealInfo);\n  cpuBackend.disposeIntermediateTensorInfo(evenImagInfo);\n  cpuBackend.disposeIntermediateTensorInfo(evenTensorInfo);\n  cpuBackend.disposeIntermediateTensorInfo(oddRealInfo);\n  cpuBackend.disposeIntermediateTensorInfo(oddImagInfo);\n  cpuBackend.disposeIntermediateTensorInfo(oddTensorInfo);\n  cpuBackend.disposeIntermediateTensorInfo($evenRealInfo);\n  cpuBackend.disposeIntermediateTensorInfo($evenImagInfo);\n  cpuBackend.disposeIntermediateTensorInfo($evenTensorInfo);\n  cpuBackend.disposeIntermediateTensorInfo($oddRealInfo);\n  cpuBackend.disposeIntermediateTensorInfo($oddImagInfo);\n  cpuBackend.disposeIntermediateTensorInfo($oddTensorInfo);\n  cpuBackend.disposeIntermediateTensorInfo(eRealInfo);\n  cpuBackend.disposeIntermediateTensorInfo(eImagInfo);\n  cpuBackend.disposeIntermediateTensorInfo(complexInfo);\n  cpuBackend.disposeIntermediateTensorInfo(exponentInfo);\n  cpuBackend.disposeIntermediateTensorInfo(addPart);\n  cpuBackend.disposeIntermediateTensorInfo(subPart);\n  cpuBackend.disposeIntermediateTensorInfo(addPartReal);\n  cpuBackend.disposeIntermediateTensorInfo(addPartImag);\n  cpuBackend.disposeIntermediateTensorInfo(subPartReal);\n  cpuBackend.disposeIntermediateTensorInfo(subPartImag);\n  cpuBackend.disposeIntermediateTensorInfo($real);\n  cpuBackend.disposeIntermediateTensorInfo($imag);\n  return { real: $realVals, imag: $imagVals };\n}\nfunction fourierTransformByMatmul(data, size, inverse) {\n  const ret = new Float32Array(size * 2);\n  for (let r2 = 0; r2 < size; r2++) {\n    let real5 = 0;\n    let imag5 = 0;\n    for (let c = 0; c < size; c++) {\n      const e2 = backend_util_exports.exponent(r2 * c, size, inverse);\n      const term = backend_util_exports.getComplexWithIndex(data, c);\n      real5 += term.real * e2.real - term.imag * e2.imag;\n      imag5 += term.real * e2.imag + term.imag * e2.real;\n    }\n    if (inverse) {\n      real5 /= size;\n      imag5 /= size;\n    }\n    backend_util_exports.assignToTypedArray(ret, real5, imag5, r2);\n  }\n  return ret;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/FFT.js\nfunction fft2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const inputSize = util_exports.sizeFromShape(input2.shape);\n  const innerDimensionSize = input2.shape[input2.shape.length - 1];\n  const batch = inputSize / innerDimensionSize;\n  const input2D = reshape3({\n    inputs: { x: input2 },\n    backend: backend2,\n    attrs: { shape: [batch, innerDimensionSize] }\n  });\n  const result = fftBatch(input2D, false, backend2);\n  const resultReshaped = reshape3({ inputs: { x: result }, backend: backend2, attrs: { shape: input2.shape } });\n  backend2.disposeIntermediateTensorInfo(input2D);\n  backend2.disposeIntermediateTensorInfo(result);\n  return resultReshaped;\n}\nvar fftConfig = {\n  kernelName: FFT,\n  backendName: \"cpu\",\n  kernelFunc: fft2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Fill.js\nfunction fill2(args) {\n  const { backend: backend2, attrs } = args;\n  const { shape, value, dtype } = attrs;\n  const $dtype = dtype || util_exports.inferDtype(value);\n  const values = util_exports.getArrayFromDType($dtype, util_exports.sizeFromShape(shape));\n  fillValues(values, value, $dtype);\n  return backend2.makeTensorInfo(shape, $dtype, values);\n}\nvar fillConfig = {\n  kernelName: Fill,\n  backendName: \"cpu\",\n  kernelFunc: fill2\n};\nfunction fillValues(values, value, dtype) {\n  if (dtype === \"string\") {\n    values.fill(value);\n  } else {\n    values.fill(value);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/FlipLeftRight.js\nvar flipLeftRightConfig = {\n  kernelName: FlipLeftRight,\n  backendName: \"cpu\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { image: image2 } = inputs;\n    const cpuBackend = backend2;\n    const output = util_exports.getTypedArrayFromDType(image2.dtype, util_exports.sizeFromShape(image2.shape));\n    const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n    const imageVals = cpuBackend.data.get(image2.dataId).values;\n    for (let batchIdx = 0; batchIdx < batch; batchIdx++) {\n      const batchOffset = batchIdx * imageWidth * imageHeight * numChannels;\n      for (let row = 0; row < imageHeight; row++) {\n        const rowOffset = row * (imageWidth * numChannels);\n        for (let col = 0; col < imageWidth; col++) {\n          const colOffset = col * numChannels;\n          for (let channel = 0; channel < numChannels; channel++) {\n            const coordX = Math.round(imageWidth - col - 1);\n            const outIdx = batchOffset + rowOffset + colOffset + channel;\n            let outputValue = imageVals[outIdx];\n            if (coordX >= 0 && coordX < imageWidth) {\n              const rotatedColOffset = coordX * numChannels;\n              const imageIdx = batchOffset + rowOffset + rotatedColOffset + channel;\n              outputValue = imageVals[imageIdx];\n            }\n            output[outIdx] = outputValue;\n          }\n        }\n      }\n    }\n    const dataId = cpuBackend.write(output, image2.shape, image2.dtype);\n    return { dataId, shape: image2.shape, dtype: image2.dtype };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/FloorDiv.js\nvar floorDivImpl = createSimpleBinaryKernelImpl((a, b) => Math.floor(a / b));\nvar floorDiv2 = binaryKernelFunc(FloorDiv, floorDivImpl, null, \"int32\");\nvar floorDivConfig = {\n  kernelName: FloorDiv,\n  backendName: \"cpu\",\n  kernelFunc: floorDiv2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/FusedConv2D.js\nfunction fusedConv2D(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  let result = conv2D({\n    inputs: { x, filter },\n    backend: backend2,\n    attrs: { strides, pad: pad3, dataFormat, dilations, dimRoundingMode }\n  });\n  if (bias) {\n    const resultOld = result;\n    if (dataFormat === \"NCHW\" && bias.shape.length === 1 && bias.shape[0] !== 1) {\n      const reshapedBias = reshape3({ inputs: { x: bias }, backend: backend2, attrs: { shape: [bias.shape[0], 1, 1] } });\n      result = add4({ inputs: { a: result, b: reshapedBias }, backend: backend2 });\n      backend2.disposeIntermediateTensorInfo(reshapedBias);\n    } else {\n      result = add4({ inputs: { a: result, b: bias }, backend: backend2 });\n    }\n    backend2.disposeIntermediateTensorInfo(resultOld);\n  }\n  if (activation2) {\n    const resultOld = result;\n    if (dataFormat === \"NCHW\" && activation2 === \"prelu\" && preluActivationWeights.shape.length === 1 && preluActivationWeights.shape[0] !== 1) {\n      const reshapedAlpha = reshape3({\n        inputs: { x: preluActivationWeights },\n        backend: backend2,\n        attrs: { shape: [preluActivationWeights.shape[0], 1, 1] }\n      });\n      result = applyActivation2(backend2, result, activation2, reshapedAlpha, leakyreluAlpha);\n      backend2.disposeIntermediateTensorInfo(reshapedAlpha);\n    } else {\n      result = applyActivation2(backend2, result, activation2, preluActivationWeights, leakyreluAlpha);\n    }\n    backend2.disposeIntermediateTensorInfo(resultOld);\n  }\n  return result;\n}\nvar fusedConv2DConfig = {\n  kernelName: FusedConv2D,\n  backendName: \"cpu\",\n  kernelFunc: fusedConv2D\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/FusedDepthwiseConv2D.js\nfunction fusedDepthwiseConv2D(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  let result = depthwiseConv2dNative({\n    inputs: { x, filter },\n    backend: backend2,\n    attrs: { strides, pad: pad3, dataFormat, dilations, dimRoundingMode }\n  });\n  if (bias) {\n    const oldResult = result;\n    result = add4({ inputs: { a: result, b: bias }, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(oldResult);\n  }\n  if (activation2) {\n    const oldResult = result;\n    result = applyActivation2(backend2, result, activation2, preluActivationWeights, leakyreluAlpha);\n    backend2.disposeIntermediateTensorInfo(oldResult);\n  }\n  return result;\n}\nvar fusedDepthwiseConv2DConfig = {\n  kernelName: FusedDepthwiseConv2D,\n  backendName: \"cpu\",\n  kernelFunc: fusedDepthwiseConv2D\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/GatherNd.js\nfunction gatherNd(args) {\n  const { inputs, backend: backend2 } = args;\n  const { params, indices } = inputs;\n  const paramsSize = util_exports.sizeFromShape(params.shape);\n  const indicesShape = indices.shape;\n  const sliceRank = indicesShape[indicesShape.length - 1];\n  const [resultShape, numSlices, sliceSize, strides] = backend_util_exports.prepareAndValidate(params, indices);\n  if (numSlices === 0) {\n    return backend2.makeTensorInfo(resultShape, params.dtype, []);\n  }\n  const indicesData = backend2.data.get(indices.dataId).values;\n  const paramsBuf = backend2.bufferSync(params);\n  const outBuf = gatherNdImpl(indicesData, paramsBuf, params.dtype, numSlices, sliceRank, sliceSize, strides, params.shape, paramsSize);\n  return backend2.makeTensorInfo(resultShape, params.dtype, outBuf.values);\n}\nvar gatherNdConfig = {\n  kernelName: GatherNd,\n  backendName: \"cpu\",\n  kernelFunc: gatherNd\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/GatherV2.js\nfunction gatherV2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, indices } = inputs;\n  const { axis, batchDims } = attrs;\n  assertNotComplex([x, indices], \"gatherV2\");\n  const parsedAxis = util_exports.parseAxisParam(axis, x.shape)[0];\n  const indicesVals = backend2.data.get(indices.dataId).values;\n  const axisDim = x.shape[parsedAxis];\n  for (let i2 = 0; i2 < indicesVals.length; ++i2) {\n    const index = indicesVals[i2];\n    util_exports.assert(index <= axisDim - 1 && index >= 0, () => `GatherV2: the index value ${index} is not in [0, ${axisDim - 1}]`);\n  }\n  let $batchDims = batchDims;\n  if (batchDims == null) {\n    $batchDims = 0;\n  }\n  const indicesSize = util_exports.sizeFromShape(indices.shape);\n  const shapeInfo = backend_util_exports.segment_util.collectGatherOpShapeInfo(x, indices, parsedAxis, $batchDims);\n  const flattenX = reshape3({\n    inputs: { x },\n    backend: backend2,\n    attrs: {\n      shape: [\n        shapeInfo.batchSize,\n        shapeInfo.outerSize,\n        shapeInfo.dimSize,\n        shapeInfo.sliceSize\n      ]\n    }\n  });\n  const flattenIndex = reshape3({\n    inputs: { x: indices },\n    backend: backend2,\n    attrs: { shape: [shapeInfo.batchSize, indicesSize / shapeInfo.batchSize] }\n  });\n  const flattenOutputShape = [\n    shapeInfo.batchSize,\n    shapeInfo.outerSize,\n    indicesSize / shapeInfo.batchSize,\n    shapeInfo.sliceSize\n  ];\n  const indicesBuf = backend2.bufferSync(flattenIndex);\n  const xBuf = backend2.bufferSync(flattenX);\n  const outBuf = gatherV2Impl(xBuf, indicesBuf, flattenOutputShape);\n  backend2.disposeIntermediateTensorInfo(flattenX);\n  backend2.disposeIntermediateTensorInfo(flattenIndex);\n  return backend2.makeTensorInfo(shapeInfo.outputShape, outBuf.dtype, outBuf.values);\n}\nvar gatherV2Config = {\n  kernelName: GatherV2,\n  backendName: \"cpu\",\n  kernelFunc: gatherV2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/IFFT.js\nfunction ifft2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const inputSize = util_exports.sizeFromShape(input2.shape);\n  const innerDimensionSize = input2.shape[input2.shape.length - 1];\n  const batch = inputSize / innerDimensionSize;\n  const input2D = reshape3({\n    inputs: { x: input2 },\n    backend: backend2,\n    attrs: { shape: [batch, innerDimensionSize] }\n  });\n  const result = fftBatch(input2D, true, backend2);\n  const resultReshaped = reshape3({ inputs: { x: result }, backend: backend2, attrs: { shape: input2.shape } });\n  backend2.disposeIntermediateTensorInfo(input2D);\n  backend2.disposeIntermediateTensorInfo(result);\n  return resultReshaped;\n}\nvar ifftConfig = {\n  kernelName: IFFT,\n  backendName: \"cpu\",\n  kernelFunc: ifft2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/IsFinite.js\nvar isFinite3 = unaryKernelFunc(IsFinite, (xi) => Number.isFinite(xi) ? 1 : 0, \"bool\");\nvar isFiniteConfig = {\n  kernelName: IsFinite,\n  backendName: \"cpu\",\n  kernelFunc: isFinite3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/IsInf.js\nvar isInf2 = unaryKernelFunc(IsInf, (xi) => Math.abs(xi) === Infinity ? 1 : 0, \"bool\");\nvar isInfConfig = {\n  kernelName: IsInf,\n  backendName: \"cpu\",\n  kernelFunc: isInf2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/IsNaN.js\nvar isNaN3 = unaryKernelFunc(IsNan, (xi) => Number.isNaN(xi) ? 1 : 0, \"bool\");\nvar isNaNConfig = {\n  kernelName: IsNan,\n  backendName: \"cpu\",\n  kernelFunc: isNaN3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LinSpace.js\nfunction linSpace(args) {\n  const { backend: backend2, attrs } = args;\n  const { start, stop, num } = attrs;\n  const outVals = linSpaceImpl(start, stop, num);\n  return backend2.makeTensorInfo([outVals.length], \"float32\", outVals);\n}\nvar linSpaceConfig = {\n  kernelName: LinSpace,\n  backendName: \"cpu\",\n  kernelFunc: linSpace\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Log1p.js\nvar log1p2 = unaryKernelFunc(Log1p, (xi) => Math.log1p(xi));\nvar log1pConfig = {\n  kernelName: Log1p,\n  backendName: \"cpu\",\n  kernelFunc: log1p2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LogicalAnd.js\nvar logicalAndImpl = createSimpleBinaryKernelImpl((a, b) => a && b);\nvar logicalAnd2 = binaryKernelFunc(LogicalAnd, logicalAndImpl, null, \"bool\");\nvar logicalAndConfig = {\n  kernelName: LogicalAnd,\n  backendName: \"cpu\",\n  kernelFunc: logicalAnd2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LogicalNot.js\nvar logicalNot2 = unaryKernelFunc(LogicalNot, (xi) => xi ? 0 : 1, \"bool\");\nvar logicalNotConfig = {\n  kernelName: LogicalNot,\n  backendName: \"cpu\",\n  kernelFunc: logicalNot2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LogicalOr.js\nvar logicalOrImpl = createSimpleBinaryKernelImpl((a, b) => a || b);\nvar logicalOr2 = binaryKernelFunc(LogicalOr, logicalOrImpl, null, \"bool\");\nvar logicalOrConfig = {\n  kernelName: LogicalOr,\n  backendName: \"cpu\",\n  kernelFunc: logicalOr2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LRN.js\nfunction lRN(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { depthRadius, bias, alpha, beta } = attrs;\n  assertNotComplex(x, \"LRN\");\n  const channels = x.shape[3];\n  const maxD = channels - 1;\n  const xValues = backend2.data.get(x.dataId).values;\n  const size = util_exports.sizeFromShape(x.shape);\n  const result = new Float32Array(size);\n  function sumAcrossChannels(offset) {\n    const currentChannel = offset % channels;\n    let beginSumOffset = offset - currentChannel + Math.max(0, currentChannel - depthRadius);\n    const endSumOffset = offset - currentChannel + Math.min(currentChannel + depthRadius, maxD);\n    let sum7 = 0;\n    for (; beginSumOffset <= endSumOffset; beginSumOffset++) {\n      const z = xValues[beginSumOffset];\n      sum7 += z * z;\n    }\n    return sum7;\n  }\n  for (let offset = 0; offset < size; offset++) {\n    const sum7 = sumAcrossChannels(offset);\n    const val = xValues[offset] * Math.pow(bias + alpha * sum7, -beta);\n    result[offset] = val;\n  }\n  return backend2.makeTensorInfo(x.shape, x.dtype, result);\n}\nvar LRNConfig = {\n  kernelName: LRN,\n  backendName: \"cpu\",\n  kernelFunc: lRN\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/LRNGrad.js\nfunction lRNGrad(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, y, dy } = inputs;\n  const { depthRadius, bias, alpha, beta } = attrs;\n  assertNotComplex(dy, \"LRNGrad\");\n  const dySize = util_exports.sizeFromShape(dy.shape);\n  const channels = dy.shape[3];\n  const dyValues = backend2.data.get(dy.dataId).values;\n  const xValues = backend2.data.get(x.dataId).values;\n  const yValues = backend2.data.get(y.dataId).values;\n  const result = new Float32Array(dySize);\n  const size = dySize;\n  for (let offset = 0; offset < size; offset++) {\n    const currentChannel = offset % channels;\n    const depthBegin = offset - currentChannel + Math.max(0, currentChannel - depthRadius);\n    const depthEnd = offset - currentChannel + Math.min(channels, currentChannel + depthRadius + 1);\n    let norm2 = 0;\n    for (let k = depthBegin; k < depthEnd; k++) {\n      norm2 += Math.pow(xValues[k], 2);\n    }\n    norm2 = alpha * norm2 + bias;\n    for (let k = depthBegin; k < depthEnd; k++) {\n      let dyi = -2 * alpha * beta * xValues[k] * yValues[offset] / norm2;\n      if (offset === k) {\n        dyi += Math.pow(norm2, -beta);\n      }\n      dyi *= dyValues[offset];\n      result[k] += dyi;\n    }\n  }\n  return backend2.makeTensorInfo(dy.shape, x.dtype, result);\n}\nvar LRNGradConfig = {\n  kernelName: LRNGrad,\n  backendName: \"cpu\",\n  kernelFunc: lRNGrad\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Max.js\nfunction max3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { reductionIndices, keepDims } = attrs;\n  const cpuBackend = backend2;\n  let xShape = x.shape;\n  const xRank = xShape.length;\n  const origAxes = util_exports.parseAxisParam(reductionIndices, xShape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  let xVals = cpuBackend.data.get(x.dataId).values;\n  if (permutedAxes != null) {\n    const newShape = new Array(xRank);\n    for (let i2 = 0; i2 < newShape.length; i2++) {\n      newShape[i2] = xShape[permutedAxes[i2]];\n    }\n    xVals = transposeImpl(xVals, xShape, x.dtype, permutedAxes, newShape);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n    xShape = newShape;\n  }\n  assertNotComplex(x, \"max\");\n  backend_util_exports.assertAxesAreInnerMostDims(\"max\", axes, xRank);\n  const [maxOutShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(xShape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const result = maxImpl(xVals, reduceSize, maxOutShape, x.dtype);\n  const dataId = cpuBackend.write(result, maxOutShape, x.dtype);\n  let outShape = maxOutShape;\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(maxOutShape, origAxes);\n    outShape = newShape;\n  }\n  return { dataId, shape: outShape, dtype: x.dtype };\n}\nvar maxConfig = {\n  kernelName: Max,\n  backendName: \"cpu\",\n  kernelFunc: max3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPool.js\nfunction maxPool2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  assertNotComplex(x, \"maxPool\");\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = 1;\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in maxPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  let res;\n  if (convInfo.filterWidth === 1 && convInfo.filterHeight === 1 && util_exports.arraysEqual(convInfo.inShape, convInfo.outShape)) {\n    res = identity2({ inputs: { x }, backend: backend2 });\n  } else {\n    const xValues = backend2.data.get(x.dataId).values;\n    const strides2 = util_exports.computeStrides(x.shape);\n    const buffer2 = pool2(xValues, x.shape, x.dtype, strides2, convInfo, \"max\");\n    res = backend2.makeTensorInfo(convInfo.outShape, x.dtype, buffer2.values);\n  }\n  return res;\n}\nvar maxPoolConfig = {\n  kernelName: MaxPool,\n  backendName: \"cpu\",\n  kernelFunc: maxPool2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPool3D.js\nfunction maxPool3D(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { filterSize, strides, pad: pad3, dimRoundingMode, dataFormat } = attrs;\n  assertNotComplex(x, \"maxPool3d\");\n  const convInfo = backend_util_exports.computePool3DInfo(x.shape, filterSize, strides, 1, pad3, dimRoundingMode, dataFormat);\n  const xValues = backend2.data.get(x.dataId).values;\n  const outBuf = pool3d2(xValues, x.shape, x.dtype, util_exports.computeStrides(x.shape), convInfo, \"max\");\n  return backend2.makeTensorInfo(outBuf.shape, \"float32\", outBuf.values);\n}\nvar maxPool3DConfig = {\n  kernelName: MaxPool3D,\n  backendName: \"cpu\",\n  kernelFunc: maxPool3D\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPool3DGrad.js\nfunction maxPool3DGrad(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2 } = inputs;\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  assertNotComplex([dy, input2], \"maxPool3DGrad\");\n  const convInfo = backend_util_exports.computePool3DInfo(input2.shape, filterSize, strides, 1, pad3, dimRoundingMode);\n  const inputBuf = backend2.bufferSync(input2);\n  const maxPosBuf = maxPool3dPositions(inputBuf, convInfo);\n  const strideDepth = convInfo.strideDepth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const dilationDepth = convInfo.dilationDepth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterDepth = convInfo.effectiveFilterDepth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;\n  const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n  const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n  const dx = buffer(input2.shape, \"float32\");\n  const dyBuf = backend2.bufferSync(dy);\n  for (let batch = 0; batch < convInfo.batchSize; ++batch) {\n    for (let channel = 0; channel < convInfo.inChannels; ++channel) {\n      for (let dxDepth = 0; dxDepth < convInfo.inDepth; ++dxDepth) {\n        for (let dxRow = 0; dxRow < convInfo.inHeight; ++dxRow) {\n          for (let dxCol = 0; dxCol < convInfo.inWidth; ++dxCol) {\n            const dyDepthCorner = dxDepth - padFront;\n            const dyRowCorner = dxRow - padTop;\n            const dyColCorner = dxCol - padLeft;\n            let dotProd = 0;\n            for (let wDepth = 0; wDepth < effectiveFilterDepth; wDepth += dilationDepth) {\n              const dyDepth = (dyDepthCorner + wDepth) / strideDepth;\n              if (dyDepth < 0 || dyDepth >= convInfo.outDepth || Math.floor(dyDepth) !== dyDepth) {\n                continue;\n              }\n              for (let wRow = 0; wRow < effectiveFilterHeight; wRow += dilationHeight) {\n                const dyRow = (dyRowCorner + wRow) / strideHeight;\n                if (dyRow < 0 || dyRow >= convInfo.outHeight || Math.floor(dyRow) !== dyRow) {\n                  continue;\n                }\n                for (let wCol = 0; wCol < effectiveFilterWidth; wCol += dilationWidth) {\n                  const dyCol = (dyColCorner + wCol) / strideWidth;\n                  if (dyCol < 0 || dyCol >= convInfo.outWidth || Math.floor(dyCol) !== dyCol) {\n                    continue;\n                  }\n                  const maxPos = effectiveFilterDepth * effectiveFilterHeight * effectiveFilterWidth - 1 - maxPosBuf.get(batch, dyDepth, dyRow, dyCol, channel);\n                  const curPos = wDepth * effectiveFilterHeight * effectiveFilterWidth + wRow * effectiveFilterWidth + wCol;\n                  const mask = maxPos === curPos ? 1 : 0;\n                  if (mask === 0) {\n                    continue;\n                  }\n                  const pixel = dyBuf.get(batch, dyDepth, dyRow, dyCol, channel);\n                  dotProd += pixel * mask;\n                }\n              }\n            }\n            dx.set(dotProd, batch, dxDepth, dxRow, dxCol, channel);\n          }\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dx.shape, dx.dtype, dx.values);\n}\nvar maxPool3DGradConfig2 = {\n  kernelName: MaxPool3DGrad,\n  backendName: \"cpu\",\n  kernelFunc: maxPool3DGrad\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPoolGrad.js\nfunction maxPoolGrad2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2, output } = inputs;\n  const x = input2;\n  assertNotComplex([input2, output], \"maxPoolGrad\");\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, 1, pad3, dimRoundingMode);\n  const xValues = backend2.data.get(x.dataId).values;\n  const maxPosBuf = buffer(convInfo.outShape, x.dtype, maxPoolPositions(xValues, x.shape, x.dtype, convInfo).values);\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n  const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n  const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n  const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n  const dx = buffer(x.shape, \"float32\");\n  const dyData = backend2.data.get(dy.dataId).values;\n  const dyBuf = buffer(dy.shape, \"float32\", dyData);\n  for (let b = 0; b < convInfo.batchSize; ++b) {\n    for (let d = 0; d < convInfo.inChannels; ++d) {\n      for (let dxR = 0; dxR < convInfo.inHeight; ++dxR) {\n        for (let dxC = 0; dxC < convInfo.inWidth; ++dxC) {\n          const dyRCorner = dxR - padTop;\n          const dyCCorner = dxC - padLeft;\n          let dotProd = 0;\n          for (let wR = 0; wR < effectiveFilterHeight; wR += dilationHeight) {\n            const dyR = (dyRCorner + wR) / strideHeight;\n            if (dyR < 0 || dyR >= convInfo.outHeight || Math.floor(dyR) !== dyR) {\n              continue;\n            }\n            for (let wC = 0; wC < effectiveFilterWidth; wC += dilationWidth) {\n              const dyC = (dyCCorner + wC) / strideWidth;\n              if (dyC < 0 || dyC >= convInfo.outWidth || Math.floor(dyC) !== dyC) {\n                continue;\n              }\n              const maxPos = effectiveFilterHeight * effectiveFilterWidth - 1 - maxPosBuf.get(b, dyR, dyC, d);\n              const curPos = wR * effectiveFilterWidth + wC;\n              const mask = maxPos === curPos ? 1 : 0;\n              if (mask === 0) {\n                continue;\n              }\n              const pixel = dyBuf.get(b, dyR, dyC, d);\n              dotProd += pixel * mask;\n            }\n          }\n          dx.set(dotProd, b, dxR, dxC, d);\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(dx.shape, dx.dtype, dx.values);\n}\nvar maxPoolGradConfig2 = {\n  kernelName: MaxPoolGrad,\n  backendName: \"cpu\",\n  kernelFunc: maxPoolGrad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPoolWithArgmax_impl.js\nfunction maxPoolWithArgmaxImpl(xValues, xShape, dtype, includeBatchInIndex, convInfo) {\n  const strides = util_exports.computeStrides(xShape);\n  const maxPools = pool2(xValues, xShape, dtype, strides, convInfo, \"max\");\n  const maxPositions = maxPoolPositions(xValues, xShape, dtype, convInfo, true, includeBatchInIndex);\n  return [maxPools.values, maxPositions.values];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MaxPoolWithArgmax.js\nvar maxPoolWithArgmaxConfig = {\n  kernelName: MaxPoolWithArgmax,\n  backendName: \"cpu\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { x } = inputs;\n    const { filterSize, strides, pad: pad3, includeBatchInIndex } = attrs;\n    const cpuBackend = backend2;\n    assertNotComplex(x, \"MaxPoolWithArgmax\");\n    const values = cpuBackend.data.get(x.dataId).values;\n    const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, [1, 1], pad3);\n    const [pooled, indexes] = maxPoolWithArgmaxImpl(values, x.shape, x.dtype, includeBatchInIndex, convInfo);\n    const pooledDataId = cpuBackend.write(pooled, convInfo.outShape, x.dtype);\n    const indexesDataId = cpuBackend.write(indexes, convInfo.outShape, x.dtype);\n    return [\n      { dataId: pooledDataId, shape: convInfo.outShape, dtype: x.dtype },\n      { dataId: indexesDataId, shape: convInfo.outShape, dtype: \"int32\" }\n    ];\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Mean.js\nfunction mean2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  const axes = util_exports.parseAxisParam(axis, x.shape);\n  const shapes = backend_util_exports.computeOutAndReduceShapes(x.shape, axes);\n  const reduceShape = shapes[1];\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const toDispose = [];\n  const reduceSizeScalar = backend2.makeTensorInfo([], \"float32\", new Float32Array([reduceSize]));\n  toDispose.push(reduceSizeScalar);\n  const $x = cast3({ inputs: { x }, backend: backend2, attrs: { dtype: \"float32\" } });\n  toDispose.push($x);\n  const res = div2({ inputs: { a: $x, b: reduceSizeScalar }, backend: backend2 });\n  toDispose.push(res);\n  const result = sum3({ inputs: { x: res }, backend: backend2, attrs: { axis, keepDims } });\n  toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return result;\n}\nvar meanConfig = {\n  kernelName: Mean,\n  backendName: \"cpu\",\n  kernelFunc: mean2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Min.js\nfunction min3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  assertNotComplex(x, \"min\");\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  if (permutedAxes != null) {\n    $x = transpose2({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"min\", axes, $x.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes($x.shape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const vals = util_exports.makeZerosTypedArray(util_exports.sizeFromShape(outShape), $x.dtype);\n  const aVals = backend2.data.get($x.dataId).values;\n  for (let i2 = 0; i2 < vals.length; ++i2) {\n    const offset = i2 * reduceSize;\n    let min7 = aVals[offset];\n    for (let j = 0; j < reduceSize; ++j) {\n      const value = aVals[offset + j];\n      if (Number.isNaN(value) || value < min7) {\n        min7 = value;\n      }\n    }\n    vals[i2] = min7;\n  }\n  if (permutedAxes != null) {\n    backend2.disposeIntermediateTensorInfo($x);\n  }\n  const result = backend2.makeTensorInfo(outShape, $x.dtype, vals);\n  if (keepDims) {\n    const expandedShape = backend_util_exports.expandShapeToKeepDim(outShape, origAxes);\n    const reshapedResult = reshape3({ inputs: { x: result }, backend: backend2, attrs: { shape: expandedShape } });\n    backend2.disposeIntermediateTensorInfo(result);\n    return reshapedResult;\n  }\n  return result;\n}\nvar minConfig = {\n  kernelName: Min,\n  backendName: \"cpu\",\n  kernelFunc: min3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/MirrorPad.js\nfunction mirrorPad2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { paddings, mode } = attrs;\n  assertNotComplex(x, \"mirrorPad\");\n  const outShape = paddings.map((p2, i2) => p2[0] + x.shape[i2] + p2[1]);\n  const start = paddings.map((p2) => p2[0]);\n  const end = paddings.map((p2, i2) => p2[0] + x.shape[i2]);\n  const offset = mode === \"reflect\" ? 0 : 1;\n  const xVals = backend2.data.get(x.dataId).values;\n  const xRank = x.shape.length;\n  const xStrides = util_exports.computeStrides(x.shape);\n  const resultSize = util_exports.sizeFromShape(outShape);\n  const resultRank = outShape.length;\n  const resultStrides = util_exports.computeStrides(outShape);\n  const resVals = util_exports.getTypedArrayFromDType(x.dtype, resultSize);\n  for (let i2 = 0; i2 < resultSize; i2++) {\n    let coords3 = util_exports.indexToLoc(i2, resultRank, resultStrides);\n    for (let i3 = 0; i3 < resultRank; i3++) {\n      if (coords3[i3] < start[i3]) {\n        coords3[i3] = start[i3] * 2 - coords3[i3] - offset;\n      } else if (coords3[i3] >= end[i3]) {\n        coords3[i3] = (end[i3] - 1) * 2 - coords3[i3] + offset;\n      }\n    }\n    coords3 = coords3.map((c, i3) => c - start[i3]);\n    const inIndex = util_exports.locToIndex(coords3, xRank, xStrides);\n    resVals[i2] = xVals[inIndex];\n  }\n  const outId = backend2.write(resVals, outShape, x.dtype);\n  return { dataId: outId, shape: outShape, dtype: x.dtype };\n}\nvar mirrorPadConfig = {\n  kernelName: MirrorPad,\n  backendName: \"cpu\",\n  kernelFunc: mirrorPad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Mod.js\nvar modImpl = createSimpleBinaryKernelImpl((aValue, bValue) => {\n  const rem = aValue % bValue;\n  if (aValue < 0 && bValue < 0 || aValue >= 0 && bValue >= 0) {\n    return rem;\n  } else {\n    return (rem + bValue) % bValue;\n  }\n});\nvar mod2 = binaryKernelFunc(Mod, modImpl);\nvar modConfig = {\n  kernelName: Mod,\n  backendName: \"cpu\",\n  kernelFunc: mod2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Multinomial.js\nvar seedrandom4 = __toESM(require_seedrandom2());\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Softmax.js\nfunction softmax3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { logits } = inputs;\n  const { dim } = attrs;\n  const logitsRank = logits.shape.length;\n  let $dim = dim;\n  if ($dim === -1) {\n    $dim = logitsRank - 1;\n  }\n  if ($dim !== logitsRank - 1) {\n    throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${logitsRank} and dim was ${$dim}`);\n  }\n  const axes = util_exports.parseAxisParam([$dim], logits.shape);\n  const maxLogit = max3({\n    inputs: { x: logits },\n    backend: backend2,\n    attrs: { reductionIndices: axes, keepDims: false }\n  });\n  const expandedShape = backend_util_exports.expandShapeToKeepDim(maxLogit.shape, axes);\n  const maxLogitReshaped = reshape3({ inputs: { x: maxLogit }, backend: backend2, attrs: { shape: expandedShape } });\n  const a = sub2({ inputs: { a: logits, b: maxLogitReshaped }, backend: backend2 });\n  const b = exp2({ inputs: { x: a }, backend: backend2 });\n  const sumExp = sum3({ inputs: { x: b }, backend: backend2, attrs: { axis: axes, keepDims: false } });\n  const sumReshaped = reshape3({ inputs: { x: sumExp }, backend: backend2, attrs: { shape: expandedShape } });\n  const result = div2({ inputs: { a: b, b: sumReshaped }, backend: backend2 });\n  backend2.disposeIntermediateTensorInfo(maxLogit);\n  backend2.disposeIntermediateTensorInfo(maxLogitReshaped);\n  backend2.disposeIntermediateTensorInfo(a);\n  backend2.disposeIntermediateTensorInfo(b);\n  backend2.disposeIntermediateTensorInfo(sumExp);\n  backend2.disposeIntermediateTensorInfo(sumReshaped);\n  return result;\n}\nvar softmaxConfig = {\n  kernelName: Softmax,\n  backendName: \"cpu\",\n  kernelFunc: softmax3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Multinomial.js\nfunction multinomial2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { logits } = inputs;\n  const { numSamples, seed, normalized } = attrs;\n  assertNotComplex(logits, \"multinomial\");\n  const probabilities = normalized ? logits : softmax3({ inputs: { logits }, backend: backend2, attrs: { dim: -1 } });\n  const batchSize = probabilities.shape[0];\n  const numEvents = probabilities.shape[1];\n  const probVals = backend2.data.get(probabilities.dataId).values;\n  const resShape = [batchSize, numSamples];\n  const resVals = util_exports.makeZerosTypedArray(util_exports.sizeFromShape(resShape), \"int32\");\n  for (let b = 0; b < batchSize; ++b) {\n    const offset = b * numEvents;\n    const cdf = new Float32Array(numEvents - 1);\n    cdf[0] = probVals[offset];\n    for (let event = 1; event < cdf.length; ++event) {\n      cdf[event] = cdf[event - 1] + probVals[offset + event];\n    }\n    const random = seedrandom4.alea(seed.toString());\n    const outOffset = b * numSamples;\n    for (let sampleId = 0; sampleId < numSamples; ++sampleId) {\n      const r2 = random();\n      resVals[outOffset + sampleId] = cdf.length;\n      for (let event = 0; event < cdf.length; event++) {\n        if (r2 < cdf[event]) {\n          resVals[outOffset + sampleId] = event;\n          break;\n        }\n      }\n    }\n  }\n  if (!normalized) {\n    backend2.disposeIntermediateTensorInfo(probabilities);\n  }\n  return backend2.makeTensorInfo(resShape, \"int32\", resVals);\n}\nvar multinomialConfig = {\n  kernelName: Multinomial,\n  backendName: \"cpu\",\n  kernelFunc: multinomial2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/NonMaxSuppressionV3.js\nvar nonMaxSuppressionV3Impl2 = kernel_impls_exports.nonMaxSuppressionV3Impl;\nfunction nonMaxSuppressionV3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold } = attrs;\n  assertNotComplex(boxes, \"NonMaxSuppression\");\n  const boxesVals = backend2.data.get(boxes.dataId).values;\n  const scoresVals = backend2.data.get(scores.dataId).values;\n  const { selectedIndices } = nonMaxSuppressionV3Impl2(boxesVals, scoresVals, maxOutputSize, iouThreshold, scoreThreshold);\n  return backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices));\n}\nvar nonMaxSuppressionV3Config = {\n  kernelName: NonMaxSuppressionV3,\n  backendName: \"cpu\",\n  kernelFunc: nonMaxSuppressionV3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/NonMaxSuppressionV4.js\nvar nonMaxSuppressionV4Impl2 = kernel_impls_exports.nonMaxSuppressionV4Impl;\nfunction nonMaxSuppressionV4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize } = attrs;\n  assertNotComplex(boxes, \"NonMaxSuppressionPadded\");\n  const boxesVals = backend2.data.get(boxes.dataId).values;\n  const scoresVals = backend2.data.get(scores.dataId).values;\n  const { selectedIndices, validOutputs } = nonMaxSuppressionV4Impl2(boxesVals, scoresVals, maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize);\n  return [\n    backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices)),\n    backend2.makeTensorInfo([], \"int32\", new Int32Array([validOutputs]))\n  ];\n}\nvar nonMaxSuppressionV4Config = {\n  kernelName: NonMaxSuppressionV4,\n  backendName: \"cpu\",\n  kernelFunc: nonMaxSuppressionV4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/NonMaxSuppressionV5.js\nvar nonMaxSuppressionV5Impl2 = kernel_impls_exports.nonMaxSuppressionV5Impl;\nfunction nonMaxSuppressionV5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma } = attrs;\n  assertNotComplex(boxes, \"NonMaxSuppressionWithScore\");\n  const boxesVals = backend2.data.get(boxes.dataId).values;\n  const scoresVals = backend2.data.get(scores.dataId).values;\n  const maxOutputSizeVal = maxOutputSize;\n  const iouThresholdVal = iouThreshold;\n  const scoreThresholdVal = scoreThreshold;\n  const softNmsSigmaVal = softNmsSigma;\n  const { selectedIndices, selectedScores } = nonMaxSuppressionV5Impl2(boxesVals, scoresVals, maxOutputSizeVal, iouThresholdVal, scoreThresholdVal, softNmsSigmaVal);\n  return [\n    backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices)),\n    backend2.makeTensorInfo([selectedScores.length], \"float32\", new Float32Array(selectedScores))\n  ];\n}\nvar nonMaxSuppressionV5Config = {\n  kernelName: NonMaxSuppressionV5,\n  backendName: \"cpu\",\n  kernelFunc: nonMaxSuppressionV5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/OneHot.js\nfunction oneHot2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { indices } = inputs;\n  const { depth, onValue, offValue } = attrs;\n  assertNotComplex(indices, \"oneHot\");\n  const indicesSize = util_exports.sizeFromShape(indices.shape);\n  const res = new Float32Array(indicesSize * depth);\n  res.fill(offValue);\n  const indicesVal = backend2.data.get(indices.dataId).values;\n  for (let event = 0; event < indicesSize; ++event) {\n    if (indicesVal[event] >= 0 && indicesVal[event] < depth) {\n      res[event * depth + indicesVal[event]] = onValue;\n    }\n  }\n  return backend2.makeTensorInfo([...indices.shape, depth], \"int32\", res);\n}\nvar oneHotConfig = {\n  kernelName: OneHot,\n  backendName: \"cpu\",\n  kernelFunc: oneHot2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ZerosLike.js\nfunction zerosLike2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (x.dtype === \"string\") {\n    throw new Error(\"zerosLike is not supported for string tensors\");\n  } else if (x.dtype === \"complex64\") {\n    const realPart = real2({ inputs: { input: x }, backend: backend2 });\n    const r2 = zerosLike2({ inputs: { x: realPart }, backend: backend2 });\n    const imagPart = imag2({ inputs: { input: x }, backend: backend2 });\n    const i2 = zerosLike2({ inputs: { x: imagPart }, backend: backend2 });\n    const result = complex2({ inputs: { real: r2, imag: i2 }, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(realPart);\n    backend2.disposeIntermediateTensorInfo(r2);\n    backend2.disposeIntermediateTensorInfo(imagPart);\n    backend2.disposeIntermediateTensorInfo(i2);\n    return result;\n  } else {\n    return fill2({ backend: backend2, attrs: { shape: x.shape, value: 0, dtype: x.dtype } });\n  }\n}\nvar zerosLikeConfig = {\n  kernelName: ZerosLike,\n  backendName: \"cpu\",\n  kernelFunc: zerosLike2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/OnesLike.js\nfunction onesLike2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (x.dtype === \"string\") {\n    throw new Error(\"onesLike is not supported for string tensors\");\n  } else if (x.dtype === \"complex64\") {\n    const realPart = real2({ inputs: { input: x }, backend: backend2 });\n    const r2 = onesLike2({ inputs: { x: realPart }, backend: backend2 });\n    const imagPart = imag2({ inputs: { input: x }, backend: backend2 });\n    const i2 = zerosLike2({ inputs: { x: imagPart }, backend: backend2 });\n    const result = complex2({ inputs: { real: r2, imag: i2 }, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(realPart);\n    backend2.disposeIntermediateTensorInfo(r2);\n    backend2.disposeIntermediateTensorInfo(imagPart);\n    backend2.disposeIntermediateTensorInfo(i2);\n    return result;\n  } else {\n    return fill2({ backend: backend2, attrs: { shape: x.shape, value: 1, dtype: x.dtype } });\n  }\n}\nvar onesLikeConfig = {\n  kernelName: OnesLike,\n  backendName: \"cpu\",\n  kernelFunc: onesLike2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Pack.js\nfunction pack(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { axis } = attrs;\n  if (inputs.length === 1) {\n    return expandDims3({ inputs: { input: inputs[0] }, backend: backend2, attrs: { dim: axis } });\n  }\n  const shape = inputs[0].shape;\n  const dtype = inputs[0].dtype;\n  inputs.forEach((t2) => {\n    util_exports.assertShapesMatch(shape, t2.shape, \"All tensors passed to stack must have matching shapes\");\n    util_exports.assert(dtype === t2.dtype, () => \"All tensors passed to stack must have matching dtypes\");\n  });\n  const intermediateTensorInfos = [];\n  const expandedTensors = inputs.map((t2) => {\n    const expandedT = expandDims3({ inputs: { input: t2 }, backend: backend2, attrs: { dim: axis } });\n    intermediateTensorInfos.push(expandedT);\n    return expandedT;\n  });\n  const result = concat2({ inputs: expandedTensors, backend: backend2, attrs: { axis } });\n  intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return result;\n}\nvar packConfig = {\n  kernelName: Pack,\n  backendName: \"cpu\",\n  kernelFunc: pack\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/PadV2.js\nfunction padV2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { paddings, constantValue } = attrs;\n  assertNotComplex(x, \"pad\");\n  const outShape = paddings.map((p2, i2) => p2[0] + x.shape[i2] + p2[1]);\n  const start = paddings.map((p2) => p2[0]);\n  const xVals = backend2.data.get(x.dataId).values;\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const xRank = x.shape.length;\n  const xStrides = util_exports.computeStrides(x.shape);\n  const resultSize = util_exports.sizeFromShape(outShape);\n  const resultRank = outShape.length;\n  const resultStrides = util_exports.computeStrides(outShape);\n  const resVals = util_exports.getTypedArrayFromDType(x.dtype, resultSize);\n  if (constantValue !== 0) {\n    resVals.fill(constantValue);\n  }\n  for (let i2 = 0; i2 < xSize; i2++) {\n    const coords3 = util_exports.indexToLoc(i2, xRank, xStrides);\n    const outCoords = coords3.map((c, i3) => c + start[i3]);\n    const outIndex = util_exports.locToIndex(outCoords, resultRank, resultStrides);\n    resVals[outIndex] = xVals[i2];\n  }\n  const outId = backend2.write(resVals, outShape, x.dtype);\n  return { dataId: outId, shape: outShape, dtype: x.dtype };\n}\nvar padV2Config = {\n  kernelName: PadV2,\n  backendName: \"cpu\",\n  kernelFunc: padV2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Pow.js\nvar powImpl = createSimpleBinaryKernelImpl((a, b) => Math.pow(a, b));\nvar pow2 = binaryKernelFunc(Pow, powImpl);\nvar powConfig = {\n  kernelName: Pow,\n  backendName: \"cpu\",\n  kernelFunc: pow2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Range.js\nfunction range3(args) {\n  const { backend: backend2, attrs } = args;\n  const { start, stop, dtype, step: step5 } = attrs;\n  const values = rangeImpl(start, stop, step5, dtype);\n  return backend2.makeTensorInfo([values.length], dtype, values);\n}\nvar rangeConfig = {\n  kernelName: Range,\n  backendName: \"cpu\",\n  kernelFunc: range3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Reciprocal.js\nvar reciprocal2 = unaryKernelFunc(Reciprocal, (xi) => 1 / xi);\nvar reciprocalConfig = {\n  kernelName: Reciprocal,\n  backendName: \"cpu\",\n  kernelFunc: reciprocal2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ResizeBilinear.js\nfunction resizeBilinear2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, halfPixelCenters, size } = attrs;\n  assertNotComplex(images, \"resizeBilinear\");\n  const imagesStrides = util_exports.computeStrides(images.shape);\n  const [newHeight, newWidth] = size;\n  const [batch, oldHeight, oldWidth, numChannels] = images.shape;\n  const xValues = backend2.data.get(images.dataId).values;\n  const result = new Float32Array(util_exports.sizeFromShape([batch, newHeight, newWidth, numChannels]));\n  const effectiveInputSize = [\n    alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,\n    alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth\n  ];\n  const effectiveOutputSize = [\n    alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,\n    alignCorners && newWidth > 1 ? newWidth - 1 : newWidth\n  ];\n  let outputIdx = 0;\n  const effectiveRowSizeRatio = effectiveInputSize[0] / effectiveOutputSize[0];\n  const effectiveColSizeRatio = effectiveInputSize[1] / effectiveOutputSize[1];\n  for (let b = 0; b < batch; b++) {\n    for (let r2 = 0; r2 < newHeight; r2++) {\n      let sourceFracRow;\n      if (halfPixelCenters) {\n        sourceFracRow = effectiveRowSizeRatio * (r2 + 0.5) - 0.5;\n      } else {\n        sourceFracRow = effectiveRowSizeRatio * r2;\n      }\n      const sourceRowFloor = Math.max(0, Math.floor(sourceFracRow));\n      const rowFrac = sourceFracRow - sourceRowFloor;\n      const sourceRowCeil = Math.min(oldHeight - 1, Math.ceil(sourceFracRow));\n      const topRowOffset = b * imagesStrides[0] + sourceRowFloor * imagesStrides[1];\n      const botRowOffset = b * imagesStrides[0] + sourceRowCeil * imagesStrides[1];\n      for (let c = 0; c < newWidth; c++) {\n        let sourceFracCol;\n        if (halfPixelCenters) {\n          sourceFracCol = effectiveColSizeRatio * (c + 0.5) - 0.5;\n        } else {\n          sourceFracCol = effectiveColSizeRatio * c;\n        }\n        const sourceColFloor = Math.max(0, Math.floor(sourceFracCol));\n        const colFrac = sourceFracCol - sourceColFloor;\n        const sourceColCeil = Math.min(oldWidth - 1, Math.ceil(sourceFracCol));\n        const topLeftOffest = topRowOffset + sourceColFloor * imagesStrides[2];\n        const botLeftOffset = botRowOffset + sourceColFloor * imagesStrides[2];\n        const topRightOffset = topRowOffset + sourceColCeil * imagesStrides[2];\n        const botRightOffest = botRowOffset + sourceColCeil * imagesStrides[2];\n        for (let d = 0; d < numChannels; d++) {\n          const topLeft = xValues[topLeftOffest + d];\n          const bottomLeft = xValues[botLeftOffset + d];\n          const topRight = xValues[topRightOffset + d];\n          const bottomRight = xValues[botRightOffest + d];\n          const top = topLeft + (topRight - topLeft) * colFrac;\n          const bottom = bottomLeft + (bottomRight - bottomLeft) * colFrac;\n          const newValue = top + (bottom - top) * rowFrac;\n          result[outputIdx++] = newValue;\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo([batch, newHeight, newWidth, numChannels], \"float32\", result);\n}\nvar resizeBilinearConfig = {\n  kernelName: ResizeBilinear,\n  backendName: \"cpu\",\n  kernelFunc: resizeBilinear2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ResizeBilinearGrad.js\nfunction resizeBilinearGrad(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images, dy } = inputs;\n  const { alignCorners } = attrs;\n  assertNotComplex([dy, images], \"resizeBilinearGrad\");\n  const imagesStrides = util_exports.computeStrides(images.shape);\n  const [batch, xHeight, xWidth, depth] = images.shape;\n  const [, yHeight, yWidth] = dy.shape;\n  const output = new Float32Array(batch * xHeight * xWidth * depth);\n  const effectiveXSize = [\n    alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,\n    alignCorners && yWidth > 1 ? xWidth - 1 : xWidth\n  ];\n  const effectiveYSize = [\n    alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,\n    alignCorners && yWidth > 1 ? yWidth - 1 : yWidth\n  ];\n  const heightScale = effectiveXSize[0] / effectiveYSize[0];\n  const widthScale = effectiveXSize[1] / effectiveYSize[1];\n  const dyValues = backend2.data.get(dy.dataId).values;\n  let offset = 0;\n  for (let b = 0; b < batch; b++) {\n    const bOffset = b * imagesStrides[0];\n    for (let r2 = 0; r2 < yHeight; r2++) {\n      const dxR = r2 * heightScale;\n      const topDxRIndex = Math.floor(dxR);\n      const bottomDxRIndex = Math.min(Math.ceil(dxR), xHeight - 1);\n      const topDxROffset = bOffset + topDxRIndex * imagesStrides[1];\n      const bottomDxROffset = bOffset + bottomDxRIndex * imagesStrides[1];\n      const dxRLerp = dxR - topDxRIndex;\n      const inverseDxRLerp = 1 - dxRLerp;\n      for (let c = 0; c < yWidth; c++) {\n        const dxC = c * widthScale;\n        const leftDxCIndex = Math.floor(dxC);\n        const rightDxCIndex = Math.min(Math.ceil(dxC), xWidth - 1);\n        const dxCLerp = dxC - leftDxCIndex;\n        const inverseDxCLerp = 1 - dxCLerp;\n        const topLeftRCOffset = topDxROffset + leftDxCIndex * imagesStrides[2];\n        const topRightRCOffset = topDxROffset + rightDxCIndex * imagesStrides[2];\n        const bottomLeftRCOffset = bottomDxROffset + leftDxCIndex * imagesStrides[2];\n        const bottomRightRCOffset = bottomDxROffset + rightDxCIndex * imagesStrides[2];\n        const inverseDxRLerpTimesInverseDxCLerp = inverseDxRLerp * inverseDxCLerp;\n        const inverseDxRLerpTimesDxCLerp = inverseDxRLerp * dxCLerp;\n        const dxRLerpTimesInverseDxCLerp = dxRLerp * inverseDxCLerp;\n        const dxRLerpTimesDxCLerp = dxRLerp * dxCLerp;\n        for (let d = 0; d < depth; d++) {\n          const dyVal = dyValues[offset++];\n          output[topLeftRCOffset + d] += dyVal * inverseDxRLerpTimesInverseDxCLerp;\n          output[topRightRCOffset + d] += dyVal * inverseDxRLerpTimesDxCLerp;\n          output[bottomLeftRCOffset + d] += dyVal * dxRLerpTimesInverseDxCLerp;\n          output[bottomRightRCOffset + d] += dyVal * dxRLerpTimesDxCLerp;\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo([batch, xWidth, xHeight, depth], \"float32\", output);\n}\nvar resizeBilinearGradConfig2 = {\n  kernelName: ResizeBilinearGrad,\n  backendName: \"cpu\",\n  kernelFunc: resizeBilinearGrad\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ResizeNearestNeighbor.js\nfunction resizeNearestNeighbor2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, halfPixelCenters, size } = attrs;\n  assertNotComplex(images, \"resizeNearestNeighbor\");\n  const imagesStrides = util_exports.computeStrides(images.shape);\n  const [newHeight, newWidth] = size;\n  const [batch, oldHeight, oldWidth, numChannels] = images.shape;\n  const xValues = backend2.data.get(images.dataId).values;\n  const output = new Float32Array(batch * newHeight * newWidth * numChannels);\n  const effectiveInputSize = [\n    alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,\n    alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth\n  ];\n  const effectiveOutputSize = [\n    alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,\n    alignCorners && newWidth > 1 ? newWidth - 1 : newWidth\n  ];\n  const effectiveRowSizeRatio = effectiveInputSize[0] / effectiveOutputSize[0];\n  const effectiveColSizeRatio = effectiveInputSize[1] / effectiveOutputSize[1];\n  let outputOffset = 0;\n  for (let b = 0; b < batch; b++) {\n    const batchOffset = b * imagesStrides[0];\n    for (let r2 = 0; r2 < newHeight; r2++) {\n      const sourceFracRow = halfPixelCenters ? effectiveRowSizeRatio * (r2 + 0.5) : effectiveRowSizeRatio * r2;\n      let sourceNearestRow = Math.min(oldHeight - 1, alignCorners ? Math.round(sourceFracRow) : Math.floor(sourceFracRow));\n      if (halfPixelCenters) {\n        sourceNearestRow = Math.max(0, sourceNearestRow);\n      }\n      const rowOffset = batchOffset + sourceNearestRow * imagesStrides[1];\n      for (let c = 0; c < newWidth; c++) {\n        const sourceFracCol = halfPixelCenters ? effectiveColSizeRatio * (c + 0.5) : effectiveColSizeRatio * c;\n        let sourceNearestCol = Math.min(oldWidth - 1, alignCorners ? Math.round(sourceFracCol) : Math.floor(sourceFracCol));\n        if (halfPixelCenters) {\n          sourceNearestCol = Math.max(0, sourceNearestCol);\n        }\n        const colOffset = rowOffset + sourceNearestCol * imagesStrides[2];\n        for (let d = 0; d < numChannels; d++) {\n          const newVal = xValues[colOffset + d];\n          output[outputOffset++] = newVal;\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo([batch, newHeight, newWidth, numChannels], images.dtype, output);\n}\nvar resizeNearestNeighborConfig = {\n  kernelName: ResizeNearestNeighbor,\n  backendName: \"cpu\",\n  kernelFunc: resizeNearestNeighbor2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ResizeNearestNeighborGrad.js\nfunction resizeNearestNeighborGrad(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images, dy } = inputs;\n  const { alignCorners } = attrs;\n  assertNotComplex([dy, images], \"resizeNearestNeighborGrad\");\n  const imagesStrides = util_exports.computeStrides(images.shape);\n  const dyStrides = util_exports.computeStrides(dy.shape);\n  const [batch, xHeight, xWidth, depth] = images.shape;\n  const [, yHeight, yWidth] = dy.shape;\n  const output = new Float32Array(batch * xHeight * xWidth * depth);\n  const dyValues = backend2.data.get(dy.dataId).values;\n  const effectiveXSize = [\n    alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,\n    alignCorners && yWidth > 1 ? xWidth - 1 : xWidth\n  ];\n  const effectiveYSize = [\n    alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,\n    alignCorners && yWidth > 1 ? yWidth - 1 : yWidth\n  ];\n  const heightScale = effectiveXSize[0] / effectiveYSize[0];\n  const widthScale = effectiveXSize[1] / effectiveYSize[1];\n  const invHeightScale = 1 / heightScale;\n  const invWidthScale = 1 / widthScale;\n  const winHeight = Math.ceil(invHeightScale) * 2 + 2;\n  const winWidth = Math.ceil(invWidthScale) * 2 + 2;\n  for (let b = 0; b < batch; b++) {\n    const batchOffset = b * imagesStrides[0];\n    for (let r2 = 0; r2 < xHeight; r2++) {\n      const rowOffset = batchOffset + r2 * imagesStrides[1];\n      const startRLerp = Math.floor(r2 * invHeightScale);\n      const startDyR = Math.floor(startRLerp - winHeight / 2);\n      for (let c = 0; c < xWidth; c++) {\n        const colOffset = rowOffset + c * imagesStrides[2];\n        const startCLerp = Math.floor(c * invWidthScale);\n        const startDyC = Math.floor(startCLerp - winWidth / 2);\n        for (let d = 0; d < depth; d++) {\n          let accum = 0;\n          for (let dyRIndex = 0; dyRIndex < winHeight; dyRIndex++) {\n            const dyR = dyRIndex + startDyR;\n            if (dyR < 0 || dyR >= yHeight) {\n              continue;\n            }\n            const dyROffset = batchOffset + dyR * dyStrides[1];\n            const sourceFracRow = dyR * heightScale;\n            const sourceNearestRow = Math.min(xHeight - 1, alignCorners ? Math.round(sourceFracRow) : Math.floor(sourceFracRow));\n            if (r2 !== sourceNearestRow) {\n              continue;\n            }\n            for (let dyCIndex = 0; dyCIndex < winWidth; dyCIndex++) {\n              const dyC = dyCIndex + startDyC;\n              if (dyC < 0 || dyC >= yWidth) {\n                continue;\n              }\n              const dyCOffset = dyROffset + dyC * dyStrides[2];\n              const sourceFracCol = dyC * widthScale;\n              const sourceNearestCol = Math.min(xWidth - 1, alignCorners ? Math.round(sourceFracCol) : Math.floor(sourceFracCol));\n              if (c === sourceNearestCol) {\n                accum += dyValues[dyCOffset + d];\n              }\n            }\n          }\n          output[colOffset + d] = accum;\n        }\n      }\n    }\n  }\n  return backend2.makeTensorInfo(images.shape, images.dtype, output);\n}\nvar resizeNearestNeighborGradConfig2 = {\n  kernelName: ResizeNearestNeighborGrad,\n  backendName: \"cpu\",\n  kernelFunc: resizeNearestNeighborGrad\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Reverse.js\nfunction reverse2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { dims } = attrs;\n  assertNotComplex(x, \"reverse\");\n  const xRank = x.shape.length;\n  const $dims = util_exports.parseAxisParam(dims, x.shape);\n  if (xRank === 0) {\n    return identity2({ inputs: { x }, backend: backend2 });\n  }\n  const outBuf = new TensorBuffer(x.shape, x.dtype);\n  const xBuf = backend2.bufferSync(x);\n  for (let i2 = 0; i2 < outBuf.size; i2++) {\n    const outLoc = outBuf.indexToLoc(i2);\n    const inLoc = outLoc.slice();\n    $dims.forEach((d) => inLoc[d] = x.shape[d] - 1 - inLoc[d]);\n    outBuf.set(xBuf.get(...inLoc), ...outLoc);\n  }\n  return backend2.makeTensorInfo(outBuf.shape, outBuf.dtype, outBuf.values);\n}\nvar reverseConfig = {\n  kernelName: Reverse,\n  backendName: \"cpu\",\n  kernelFunc: reverse2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/RotateWithOffset.js\nvar rotateWithOffsetConfig = {\n  kernelName: RotateWithOffset,\n  backendName: \"cpu\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { image: image2 } = inputs;\n    const { radians, fillValue, center } = attrs;\n    const cpuBackend = backend2;\n    const output = util_exports.getTypedArrayFromDType(image2.dtype, util_exports.sizeFromShape(image2.shape));\n    const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n    const [centerX, centerY] = backend_util_exports.getImageCenter(center, imageHeight, imageWidth);\n    const fullOpacityValue = 255;\n    const sinFactor = Math.sin(radians);\n    const cosFactor = Math.cos(radians);\n    const imageVals = cpuBackend.data.get(image2.dataId).values;\n    for (let batchIdx = 0; batchIdx < batch; batchIdx++) {\n      const batchOffset = batchIdx * imageWidth * imageHeight * numChannels;\n      for (let row = 0; row < imageHeight; row++) {\n        const rowOffset = row * (imageWidth * numChannels);\n        for (let col = 0; col < imageWidth; col++) {\n          const colOffset = col * numChannels;\n          for (let channel = 0; channel < numChannels; channel++) {\n            const coords3 = [batch, row, col, channel];\n            const x = coords3[2];\n            const y = coords3[1];\n            let coordX = (x - centerX) * cosFactor - (y - centerY) * sinFactor;\n            let coordY = (x - centerX) * sinFactor + (y - centerY) * cosFactor;\n            coordX = Math.round(coordX + centerX);\n            coordY = Math.round(coordY + centerY);\n            let outputValue = fillValue;\n            if (typeof fillValue !== \"number\") {\n              if (channel === 3) {\n                outputValue = fullOpacityValue;\n              } else {\n                outputValue = fillValue[channel];\n              }\n            }\n            if (coordX >= 0 && coordX < imageWidth && coordY >= 0 && coordY < imageHeight) {\n              const rotatedRowOffset = coordY * (imageWidth * numChannels);\n              const rotatedColOffset = coordX * numChannels;\n              const imageIdx = batchOffset + rotatedRowOffset + rotatedColOffset + channel;\n              outputValue = imageVals[imageIdx];\n            }\n            const outIdx = batchOffset + rowOffset + colOffset + channel;\n            output[outIdx] = outputValue;\n          }\n        }\n      }\n    }\n    const dataId = cpuBackend.write(output, image2.shape, image2.dtype);\n    return { dataId, shape: image2.shape, dtype: image2.dtype };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Round.js\nvar round3 = unaryKernelFunc(Round, (xi) => {\n  const base = Math.floor(xi);\n  if (xi - base < 0.5) {\n    return Math.floor(xi);\n  } else if (xi - base > 0.5) {\n    return Math.ceil(xi);\n  } else {\n    if (base % 2 === 0) {\n      return base;\n    } else {\n      return base + 1;\n    }\n  }\n});\nvar roundConfig = {\n  kernelName: Round,\n  backendName: \"cpu\",\n  kernelFunc: round3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/ScatterNd.js\nfunction scatterNd(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { indices, updates } = inputs;\n  const { shape } = attrs;\n  const { sliceRank, numUpdates, sliceSize, strides, outputSize } = backend_util_exports.calculateShapes(updates, indices, shape);\n  const sumDupeIndices = true;\n  const indicesBuf = backend2.bufferSync(indices);\n  const updatesBuf = backend2.bufferSync(updates);\n  const outBuf = scatterImpl(indicesBuf, updatesBuf, shape, outputSize, sliceSize, numUpdates, sliceRank, strides, 0, sumDupeIndices);\n  return backend2.makeTensorInfo(shape, outBuf.dtype, outBuf.values);\n}\nvar scatterNdConfig = {\n  kernelName: ScatterNd,\n  backendName: \"cpu\",\n  kernelFunc: scatterNd\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SearchSorted_impl.js\nfunction lowerBound2(array2, value) {\n  let left = 0;\n  let right = array2.length;\n  let mid = 0;\n  while (left < right) {\n    mid = Math.floor((left + right) / 2);\n    if (array2[mid] < value) {\n      left = mid + 1;\n    } else {\n      right = mid;\n    }\n  }\n  return right;\n}\nfunction upperBound2(array2, value) {\n  let left = 0;\n  let right = array2.length;\n  let mid = 0;\n  while (left < right) {\n    mid = Math.floor((left + right) / 2);\n    if (array2[mid] <= value) {\n      left = mid + 1;\n    } else {\n      right = mid;\n    }\n  }\n  return right;\n}\nfunction searchSortedImpl(sortedInputs, values, batchSize, numInputs, numValues, side) {\n  const output = util_exports.getArrayFromDType(\"int32\", batchSize * numValues);\n  for (let b = 0; b < batchSize; ++b) {\n    const sortedInputsSlice = sortedInputs.slice(b * numInputs, (b + 1) * numInputs);\n    const outputOffset = b * numValues;\n    for (let i2 = 0; i2 < numValues; ++i2) {\n      output[outputOffset + i2] = side === \"left\" ? lowerBound2(sortedInputsSlice, values[i2 + outputOffset]) : upperBound2(sortedInputsSlice, values[i2 + outputOffset]);\n    }\n  }\n  return output;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SearchSorted.js\nfunction searchSorted2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { sortedSequence, values } = inputs;\n  const { side } = attrs;\n  const $sortedSequence = backend2.data.get(sortedSequence.dataId).values;\n  const $values = backend2.data.get(values.dataId).values;\n  const output = searchSortedImpl($sortedSequence, $values, sortedSequence.shape[0], sortedSequence.shape[1], values.shape[1], side);\n  return backend2.makeTensorInfo(values.shape, \"int32\", output);\n}\nvar searchSortedConfig = {\n  kernelName: SearchSorted,\n  backendName: \"cpu\",\n  kernelFunc: searchSorted2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Select.js\nfunction select2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { condition, t: t2, e: e2 } = inputs;\n  assertNotComplex([condition, t2, e2], \"select\");\n  const conditionRank = condition.shape.length;\n  const values = backend2.data.get(condition.dataId).values;\n  const tValues = backend2.data.get(t2.dataId).values;\n  const eValues = backend2.data.get(e2.dataId).values;\n  const resultDtype = upcastType(t2.dtype, e2.dtype);\n  const newValues = util_exports.makeZerosTypedArray(util_exports.sizeFromShape(t2.shape), resultDtype);\n  let index = 0;\n  const offset = conditionRank === 0 || conditionRank > 1 || t2.shape.length === 1 ? 1 : util_exports.sizeFromShape(t2.shape.slice(1));\n  for (let i2 = 0; i2 < values.length; i2++) {\n    for (let j = 0; j < offset; j++) {\n      if (values[i2] === 1) {\n        newValues[index++] = tValues[i2];\n      } else {\n        newValues[index++] = eValues[i2];\n      }\n    }\n  }\n  return backend2.makeTensorInfo(t2.shape, resultDtype, newValues);\n}\nvar selectConfig = {\n  kernelName: Select,\n  backendName: \"cpu\",\n  kernelFunc: select2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Selu.js\nvar scaleAlpha = backend_util_exports.SELU_SCALEALPHA;\nvar scale = backend_util_exports.SELU_SCALE;\nvar selu2 = unaryKernelFunc(Selu, (xi) => {\n  if (xi >= 0) {\n    return scale * xi;\n  } else {\n    return scaleAlpha * (Math.exp(xi) - 1);\n  }\n});\nvar seluConfig = {\n  kernelName: Selu,\n  backendName: \"cpu\",\n  kernelFunc: selu2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Sign.js\nvar sign2 = unaryKernelFunc(Sign, (xi) => {\n  if (xi < 0) {\n    return -1;\n  } else if (xi > 0) {\n    return 1;\n  } else {\n    return 0;\n  }\n});\nvar signConfig = {\n  kernelName: Sign,\n  backendName: \"cpu\",\n  kernelFunc: sign2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Sin.js\nvar sin2 = unaryKernelFunc(Sin, (xi) => Math.sin(xi));\nvar sinConfig = {\n  kernelName: Sin,\n  backendName: \"cpu\",\n  kernelFunc: sin2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Sinh.js\nvar sinh2 = unaryKernelFunc(Sinh, (xi) => Math.sinh(xi));\nvar sinhConfig = {\n  kernelName: Sinh,\n  backendName: \"cpu\",\n  kernelFunc: sinh2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Softplus.js\nvar epsilon2 = 11920928955078125e-23;\nvar threshold2 = Math.log(epsilon2) + 2;\nvar softplus2 = unaryKernelFunc(Softplus, (xi) => {\n  const tooLarge = xi > -threshold2;\n  const tooSmall = xi < threshold2;\n  const expX = Math.exp(xi);\n  let result;\n  if (tooSmall) {\n    result = expX;\n  } else if (tooLarge) {\n    result = xi;\n  } else {\n    result = Math.log(1 + expX);\n  }\n  return result;\n});\nvar softplusConfig = {\n  kernelName: Softplus,\n  backendName: \"cpu\",\n  kernelFunc: softplus2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SpaceToBatchND.js\nfunction spaceToBatchND2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, paddings } = attrs;\n  assertNotComplex([x], \"spaceToBatchND\");\n  const prod6 = util_exports.sizeFromShape(blockShape);\n  const completePaddings = [[0, 0]];\n  completePaddings.push(...paddings);\n  for (let i2 = 1 + blockShape.length; i2 < x.shape.length; ++i2) {\n    completePaddings.push([0, 0]);\n  }\n  const paddedX = padV2Config.kernelFunc({\n    inputs: { x },\n    backend: backend2,\n    attrs: { paddings: completePaddings, constantValue: 0 }\n  });\n  const reshapedPaddedShape = backend_util_exports.getReshaped(paddedX.shape, blockShape, prod6, false);\n  const permutedReshapedPaddedPermutation = backend_util_exports.getPermuted(reshapedPaddedShape.length, blockShape.length, false);\n  const flattenShape = backend_util_exports.getReshapedPermuted(paddedX.shape, blockShape, prod6, false);\n  const reshapeInputs = { x: paddedX };\n  const reshapeAttrs = { shape: reshapedPaddedShape };\n  const paddedXReshaped = reshape3({ inputs: reshapeInputs, backend: backend2, attrs: reshapeAttrs });\n  const transposeInputs = { x: paddedXReshaped };\n  const transposeAttrs = { perm: permutedReshapedPaddedPermutation };\n  const paddedXT = transpose2({ inputs: transposeInputs, backend: backend2, attrs: transposeAttrs });\n  const resultReshapeInputs = { x: paddedXT };\n  const resultReshapeAttrs = { shape: flattenShape };\n  const result = reshape3({ inputs: resultReshapeInputs, backend: backend2, attrs: resultReshapeAttrs });\n  backend2.disposeIntermediateTensorInfo(paddedX);\n  backend2.disposeIntermediateTensorInfo(paddedXReshaped);\n  backend2.disposeIntermediateTensorInfo(paddedXT);\n  return result;\n}\nvar spaceToBatchNDConfig = {\n  kernelName: SpaceToBatchND,\n  backendName: \"cpu\",\n  kernelFunc: spaceToBatchND2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseFillEmptyRows.js\nfunction sparseFillEmptyRows2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { indices, values, denseShape, defaultValue } = inputs;\n  if (denseShape.shape.length !== 1) {\n    throw new Error(`Dense shape must be a vector, saw:\n        ${denseShape.shape}`);\n  }\n  if (indices.shape.length !== 2) {\n    throw new Error(`Indices must be a matrix, saw:\n        ${indices.shape}`);\n  }\n  if (values.shape.length !== 1) {\n    throw new Error(`Values must be a vector, saw:\n        ${values.shape}`);\n  }\n  if (defaultValue.shape.length !== 0) {\n    throw new Error(`Default value must be a scalar, saw:\n        ${defaultValue.shape}`);\n  }\n  const $indices = backend2.data.get(indices.dataId).values;\n  const $values = backend2.data.get(values.dataId).values;\n  const $denseShape = backend2.data.get(denseShape.dataId).values;\n  const $defaultValue = backend2.data.get(defaultValue.dataId).values[0];\n  const [outputIndices, outputIndicesShape, outputValues, emptyRowIndicator, reverseIndexMap] = sparseFillEmptyRowsImpl($indices, indices.shape, indices.dtype, $values, values.dtype, $denseShape, $defaultValue);\n  return [\n    backend2.makeTensorInfo(outputIndicesShape, indices.dtype, outputIndices),\n    backend2.makeTensorInfo([outputIndicesShape[0]], values.dtype, outputValues),\n    backend2.makeTensorInfo([emptyRowIndicator.length], \"bool\", new Uint8Array(emptyRowIndicator.map((value) => Number(value)))),\n    backend2.makeTensorInfo([reverseIndexMap.length], indices.dtype, new Int32Array(reverseIndexMap))\n  ];\n}\nvar sparseFillEmptyRowsConfig = {\n  kernelName: SparseFillEmptyRows,\n  backendName: \"cpu\",\n  kernelFunc: sparseFillEmptyRows2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseReshape.js\nfunction sparseReshape2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { inputIndices, inputShape, newShape } = inputs;\n  if (inputIndices.shape.length !== 2) {\n    throw new Error(`Input indices should be a matrix but received shape\n        ${inputIndices.shape}`);\n  }\n  if (inputShape.shape.length !== 1) {\n    throw new Error(`Input shape should be a vector but received shape\n        ${inputShape.shape}`);\n  }\n  if (newShape.shape.length !== 1) {\n    throw new Error(`Target shape should be a vector but received shape ${newShape.shape}`);\n  }\n  const $inputShape = Array.from(backend2.data.get(inputShape.dataId).values);\n  const $inputIndices = backend2.data.get(inputIndices.dataId).values;\n  const targetShape = Array.from(backend2.data.get(newShape.dataId).values);\n  const [newIndices, indicesShape, outputShape] = sparseReshapeImpl($inputIndices, inputIndices.shape, inputIndices.dtype, $inputShape, targetShape);\n  return [\n    backend2.makeTensorInfo(indicesShape, inputIndices.dtype, newIndices),\n    backend2.makeTensorInfo([outputShape.length], newShape.dtype, new Int32Array(outputShape))\n  ];\n}\nvar sparseReshapeConfig = {\n  kernelName: SparseReshape,\n  backendName: \"cpu\",\n  kernelFunc: sparseReshape2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseSegmentMean.js\nfunction sparseSegmentMean2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { data, indices, segmentIds } = inputs;\n  if (data.shape.length < 1) {\n    throw new Error(`Data should be at least 1 dimensional but received scalar`);\n  }\n  if (indices.shape.length !== 1) {\n    throw new Error(`Indices should be a vector but received shape\n          ${indices.shape}`);\n  }\n  if (segmentIds.shape.length !== 1) {\n    throw new Error(`Segment ids should be a vector but received shape\n          ${segmentIds.shape}`);\n  }\n  if (indices.shape[0] !== segmentIds.shape[0]) {\n    throw new Error(`segmentIds and indices should have same size.`);\n  }\n  const $data = backend2.data.get(data.dataId).values;\n  const $indices = backend2.data.get(indices.dataId).values;\n  const $segmentIds = backend2.data.get(segmentIds.dataId).values;\n  const [outputData, outputDataShape] = sparseSegmentReductionImpl($data, data.shape, data.dtype, $indices, $segmentIds, true);\n  return backend2.makeTensorInfo(outputDataShape, data.dtype, outputData);\n}\nvar sparseSegmentMeanConfig = {\n  kernelName: SparseSegmentMean,\n  backendName: \"cpu\",\n  kernelFunc: sparseSegmentMean2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseSegmentSum.js\nfunction sparseSegmentSum2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { data, indices, segmentIds } = inputs;\n  if (data.shape.length < 1) {\n    throw new Error(`Data should be at least 1 dimensional but received scalar`);\n  }\n  if (indices.shape.length !== 1) {\n    throw new Error(`Indices should be a vector but received shape\n         ${indices.shape}`);\n  }\n  if (segmentIds.shape.length !== 1) {\n    throw new Error(`Segment ids should be a vector but received shape\n         ${segmentIds.shape}`);\n  }\n  if (indices.shape[0] !== segmentIds.shape[0]) {\n    throw new Error(`segmentIds and indices should have same size.`);\n  }\n  const $data = backend2.data.get(data.dataId).values;\n  const $indices = backend2.data.get(indices.dataId).values;\n  const $segmentIds = backend2.data.get(segmentIds.dataId).values;\n  const [outputData, outputDataShape] = sparseSegmentReductionImpl($data, data.shape, data.dtype, $indices, $segmentIds);\n  return backend2.makeTensorInfo(outputDataShape, data.dtype, outputData);\n}\nvar sparseSegmentSumConfig = {\n  kernelName: SparseSegmentSum,\n  backendName: \"cpu\",\n  kernelFunc: sparseSegmentSum2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SparseToDense.js\nfunction sparseToDense2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { sparseIndices, sparseValues, defaultValue } = inputs;\n  const { outputShape } = attrs;\n  const { sliceRank, numUpdates, sliceSize, strides, outputSize } = backend_util_exports.calculateShapes(sparseValues, sparseIndices, outputShape);\n  const sumDupeIndices = false;\n  const indicesBuf = backend2.bufferSync(sparseIndices);\n  let outBuf;\n  switch (sparseValues.dtype) {\n    case \"bool\": {\n      const updatesBuf = backend2.bufferSync(sparseValues);\n      const $defaultValue = Boolean(backend2.data.get(defaultValue.dataId).values[0]);\n      outBuf = scatterImpl(indicesBuf, updatesBuf, outputShape, outputSize, sliceSize, numUpdates, sliceRank, strides, $defaultValue, sumDupeIndices);\n      break;\n    }\n    case \"float32\": {\n      const updatesBuf = backend2.bufferSync(sparseValues);\n      const $defaultValue = backend2.data.get(defaultValue.dataId).values[0];\n      outBuf = scatterImpl(indicesBuf, updatesBuf, outputShape, outputSize, sliceSize, numUpdates, sliceRank, strides, $defaultValue, sumDupeIndices);\n      break;\n    }\n    case \"int32\": {\n      const updatesBuf = backend2.bufferSync(sparseValues);\n      const $defaultValue = backend2.data.get(defaultValue.dataId).values[0];\n      outBuf = scatterImpl(indicesBuf, updatesBuf, outputShape, outputSize, sliceSize, numUpdates, sliceRank, strides, $defaultValue, sumDupeIndices);\n      break;\n    }\n    case \"string\": {\n      const updatesBuf = backend2.bufferSync(sparseValues);\n      const $defaultValue = util_exports.decodeString(backend2.data.get(defaultValue.dataId).values[0]);\n      outBuf = scatterImpl(indicesBuf, updatesBuf, outputShape, outputSize, sliceSize, numUpdates, sliceRank, strides, $defaultValue, sumDupeIndices);\n      break;\n    }\n    default:\n      throw new Error(`Unsupported type ${sparseValues.dtype}`);\n  }\n  return backend2.makeTensorInfo(outputShape, outBuf.dtype, outBuf.values);\n}\nvar sparseToDenseConfig = {\n  kernelName: SparseToDense,\n  backendName: \"cpu\",\n  kernelFunc: sparseToDense2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/SplitV.js\nfunction splitV(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { numOrSizeSplits, axis } = attrs;\n  const $axis = util_exports.parseAxisParam(axis, x.shape)[0];\n  const splitSizes = backend_util_exports.prepareSplitSize(x, numOrSizeSplits, $axis);\n  const begin = new Array(x.shape.length).fill(0);\n  const size = x.shape.slice();\n  return splitSizes.map((s2) => {\n    const sliceSize = [...size];\n    sliceSize[$axis] = s2;\n    const sliceT = slice2({ inputs: { x }, backend: backend2, attrs: { begin, size: sliceSize } });\n    begin[$axis] += s2;\n    return sliceT;\n  });\n}\nvar splitVConfig = {\n  kernelName: SplitV,\n  backendName: \"cpu\",\n  kernelFunc: splitV\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Square.js\nvar squareConfig = {\n  kernelName: Square,\n  backendName: \"cpu\",\n  kernelFunc: ({ inputs, backend: backend2 }) => {\n    const { x } = inputs;\n    const cpuBackend = backend2;\n    assertNotComplex(x, \"square\");\n    const values = cpuBackend.data.get(x.dataId).values;\n    const newValues = new Float32Array(values.length);\n    for (let i2 = 0; i2 < values.length; ++i2) {\n      const value = values[i2];\n      newValues[i2] = value * value;\n    }\n    const dataId = cpuBackend.write(newValues, x.shape, x.dtype);\n    return { dataId, shape: x.shape, dtype: x.dtype };\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Step.js\nvar step2 = unaryKernelFunc(Step, (xi, attrs) => {\n  const stepAttrs = attrs;\n  if (isNaN(xi)) {\n    return NaN;\n  } else {\n    return xi > 0 ? 1 : stepAttrs.alpha;\n  }\n});\nvar stepConfig = {\n  kernelName: Step,\n  backendName: \"cpu\",\n  kernelFunc: step2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StridedSlice.js\nfunction stridedSlice2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask } = attrs;\n  assertNotComplex(x, \"stridedSlice\");\n  const { finalShapeSparse, finalShape, isIdentity, sliceDim0, isSimpleSlice, begin: $begin, end: $end, strides: $strides } = slice_util_exports.sliceInfo(x.shape, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask);\n  let result;\n  if (isIdentity) {\n    result = reshape3({ inputs: { x }, backend: backend2, attrs: { shape: finalShape } });\n  } else if (sliceDim0 || isSimpleSlice) {\n    util_exports.assert(x.shape.length >= 1, () => `Input must have rank at least 1, got: ${x.shape.length}`);\n    const size = slice_util_exports.computeOutShape($begin, $end, $strides);\n    const sliced = slice2({ inputs: { x }, backend: backend2, attrs: { begin: $begin, size } });\n    result = reshape3({ inputs: { x: sliced }, backend: backend2, attrs: { shape: finalShape } });\n    backend2.disposeIntermediateTensorInfo(sliced);\n  } else {\n    const xBuf = backend2.bufferSync(x);\n    const outBuf = stridedSliceImpl(finalShapeSparse, xBuf, $strides, $begin);\n    result = backend2.makeTensorInfo(finalShape, outBuf.dtype, outBuf.values);\n  }\n  return result;\n}\nvar stridedSliceConfig = {\n  kernelName: StridedSlice,\n  backendName: \"cpu\",\n  kernelFunc: stridedSlice2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StringNGrams.js\nfunction stringNGrams2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { separator, nGramWidths, leftPad, rightPad: rightPad2, padWidth, preserveShortSequences } = attrs;\n  const { data, dataSplits } = inputs;\n  const $data = backend2.data.get(data.dataId).values;\n  const $dataSplits = backend2.data.get(dataSplits.dataId).values;\n  const [nGrams, nGramsSplits] = stringNGramsImpl($data, $dataSplits, separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences);\n  return [\n    backend2.makeTensorInfo([nGrams.length], \"string\", nGrams),\n    backend2.makeTensorInfo(dataSplits.shape, \"int32\", nGramsSplits)\n  ];\n}\nvar stringNGramsConfig = {\n  kernelName: StringNGrams,\n  backendName: \"cpu\",\n  kernelFunc: stringNGrams2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StringSplit.js\nfunction stringSplit2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { skipEmpty } = attrs;\n  const { input: input2, delimiter } = inputs;\n  if (input2.dtype !== \"string\") {\n    throw new Error(\"Input must be of datatype string\");\n  }\n  if (input2.shape.length !== 1) {\n    throw new Error(`Input must be a vector, got shape: ${input2.shape}`);\n  }\n  if (delimiter.shape.length !== 0) {\n    throw new Error(`Delimiter must be a scalar, got shape: ${delimiter.shape}`);\n  }\n  const $input = backend2.data.get(input2.dataId).values;\n  const $delimiter = backend2.data.get(delimiter.dataId).values[0];\n  const [indices, values, shape] = stringSplitImpl($input, $delimiter, skipEmpty);\n  const outputSize = values.length;\n  return [\n    backend2.makeTensorInfo([outputSize, 2], \"int32\", indices),\n    backend2.makeTensorInfo([outputSize], \"string\", values),\n    backend2.makeTensorInfo([2], \"int32\", new Int32Array(shape))\n  ];\n}\nvar stringSplitConfig = {\n  kernelName: StringSplit,\n  backendName: \"cpu\",\n  kernelFunc: stringSplit2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/StringToHashBucketFast.js\nfunction stringToHashBucketFast2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { numBuckets } = attrs;\n  const { input: input2 } = inputs;\n  if (input2.dtype !== \"string\") {\n    throw new Error(\"Input must be of datatype string\");\n  }\n  if (numBuckets <= 0) {\n    throw new Error(`Number of buckets must be at least 1`);\n  }\n  const $input = backend2.data.get(input2.dataId).values;\n  const output = stringToHashBucketFastImpl($input, numBuckets);\n  return backend2.makeTensorInfo(input2.shape, \"int32\", output);\n}\nvar stringToHashBucketFastConfig = {\n  kernelName: StringToHashBucketFast,\n  backendName: \"cpu\",\n  kernelFunc: stringToHashBucketFast2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Tan.js\nvar tan2 = unaryKernelFunc(Tan, (xi) => Math.tan(xi));\nvar tanConfig = {\n  kernelName: Tan,\n  backendName: \"cpu\",\n  kernelFunc: tan2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Tanh.js\nvar tanh3 = unaryKernelFunc(Tanh, (xi) => Math.tanh(xi));\nvar tanhConfig = {\n  kernelName: Tanh,\n  backendName: \"cpu\",\n  kernelFunc: tanh3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Tile.js\nfunction tile3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { reps } = attrs;\n  assertNotComplex(x, \"tile\");\n  const outBuf = tileImpl(backend2.bufferSync(x), reps);\n  return backend2.makeTensorInfo(outBuf.shape, outBuf.dtype, outBuf.values);\n}\nvar tileConfig = {\n  kernelName: Tile,\n  backendName: \"cpu\",\n  kernelFunc: tile3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/TopK.js\nfunction topK(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { k, sorted } = attrs;\n  assertNotComplex(x, \"topk\");\n  const xVals = backend2.data.get(x.dataId).values;\n  const [allTopKVals, allTopKIndices] = topKImpl(xVals, x.shape, x.dtype, k, sorted);\n  return [\n    backend2.makeTensorInfo(allTopKVals.shape, allTopKVals.dtype, allTopKVals.values),\n    backend2.makeTensorInfo(allTopKIndices.shape, allTopKIndices.dtype, allTopKIndices.values)\n  ];\n}\nvar topKConfig = {\n  kernelName: TopK,\n  backendName: \"cpu\",\n  kernelFunc: topK\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Transform.js\nfunction transform2(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { image: image2, transforms } = inputs;\n  const { interpolation, fillMode, fillValue, outputShape } = attrs;\n  const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n  const [outHeight, outWidth] = outputShape != null ? outputShape : [imageHeight, imageWidth];\n  const outShape = [batch, outHeight, outWidth, numChannels];\n  const strides = util_exports.computeStrides(image2.shape);\n  const batchStride = strides[0];\n  const rowStride = strides[1];\n  const colStride = strides[2];\n  const outVals = util_exports.getTypedArrayFromDType(image2.dtype, util_exports.sizeFromShape(outShape));\n  outVals.fill(fillValue);\n  const imageVals = backend2.data.get(image2.dataId).values;\n  const transformVals = backend2.data.get(transforms.dataId).values;\n  for (let b = 0; b < batch; ++b) {\n    const transform6 = transforms.shape[0] === 1 ? transformVals : transformVals.subarray(b * 8, b * 8 + 8);\n    for (let outY = 0; outY < outHeight; ++outY) {\n      for (let outX = 0; outX < outWidth; ++outX) {\n        for (let channel = 0; channel < numChannels; ++channel) {\n          let val;\n          const projection = transform6[6] * outX + transform6[7] * outY + 1;\n          if (projection === 0) {\n            continue;\n          }\n          const inX = (transform6[0] * outX + transform6[1] * outY + transform6[2]) / projection;\n          const inY = (transform6[3] * outX + transform6[4] * outY + transform6[5]) / projection;\n          const x = mapCoord(inX, imageWidth, fillMode);\n          const y = mapCoord(inY, imageHeight, fillMode);\n          switch (interpolation) {\n            case \"nearest\":\n              val = nearestInterpolation(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, b, y, x, channel, fillValue);\n              break;\n            case \"bilinear\":\n              val = bilinearInterpolation(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, b, y, x, channel, fillValue);\n              break;\n            default:\n              throw new Error(`Error in Transform: Expect 'nearest' or 'bilinear', but got ${interpolation}`);\n          }\n          const ind = b * batchStride + outY * rowStride + outX * colStride + channel;\n          outVals[ind] = val;\n        }\n      }\n    }\n    return backend2.makeTensorInfo(outShape, image2.dtype, outVals);\n  }\n  const dataId = backend2.write(outVals, outShape, image2.dtype);\n  return { dataId, shape: image2.shape, dtype: image2.dtype };\n}\nvar transformConfig = {\n  kernelName: Transform,\n  backendName: \"cpu\",\n  kernelFunc: transform2\n};\nfunction mapCoord(outCoord, len, mode) {\n  switch (mode) {\n    case \"reflect\":\n      return mapCoordReflect(outCoord, len);\n    case \"wrap\":\n      return mapCoordWrap(outCoord, len);\n    case \"nearest\":\n      return mapCoordNearest(outCoord, len);\n    case \"constant\":\n    default:\n      return mapCoordConstant(outCoord, len);\n  }\n}\nfunction mapCoordReflect(outCoord, len) {\n  let inCoord = outCoord;\n  if (inCoord < 0) {\n    if (len <= 1) {\n      inCoord = 0;\n    } else {\n      const sz2 = 2 * len;\n      if (inCoord < sz2) {\n        inCoord = sz2 * Math.trunc(-inCoord / sz2) + inCoord;\n      }\n      inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1;\n    }\n  } else if (inCoord > len - 1) {\n    if (len <= 1) {\n      inCoord = 0;\n    } else {\n      const sz2 = 2 * len;\n      inCoord -= sz2 * Math.trunc(inCoord / sz2);\n      if (inCoord >= len) {\n        inCoord = sz2 - inCoord - 1;\n      }\n    }\n  }\n  return util_exports.clamp(0, inCoord, len - 1);\n}\nfunction mapCoordWrap(outCoord, len) {\n  let inCoord = outCoord;\n  if (inCoord < 0) {\n    if (len <= 1) {\n      inCoord = 0;\n    } else {\n      const sz = len - 1;\n      inCoord += len * (Math.trunc(-inCoord / sz) + 1);\n    }\n  } else if (inCoord > len - 1) {\n    if (len <= 1) {\n      inCoord = 0;\n    } else {\n      const sz = len - 1;\n      inCoord -= len * Math.trunc(inCoord / sz);\n    }\n  }\n  return util_exports.clamp(0, inCoord, len - 1);\n}\nfunction mapCoordConstant(outCoord, len) {\n  return outCoord;\n}\nfunction mapCoordNearest(outCoord, len) {\n  return util_exports.clamp(0, outCoord, len - 1);\n}\nfunction readWithFillValue(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, y, x, channel, fillValue) {\n  const ind = batch * batchStride + y * rowStride + x * colStride + channel;\n  if (0 <= y && y < imageHeight && 0 <= x && x < imageWidth) {\n    return imageVals[ind];\n  } else {\n    return fillValue;\n  }\n}\nfunction nearestInterpolation(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, y, x, channel, fillValue) {\n  const $y = Math.round(y);\n  const $x = Math.round(x);\n  return readWithFillValue(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, $y, $x, channel, fillValue);\n}\nfunction bilinearInterpolation(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, y, x, channel, fillValue) {\n  const yFloor = Math.floor(y);\n  const xFloor = Math.floor(x);\n  const yCeil = yFloor + 1;\n  const xCeil = xFloor + 1;\n  const valueYFloor = (xCeil - x) * readWithFillValue(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, yFloor, xFloor, channel, fillValue) + (x - xFloor) * readWithFillValue(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, yFloor, xCeil, channel, fillValue);\n  const valueYCeil = (xCeil - x) * readWithFillValue(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, yCeil, xFloor, channel, fillValue) + (x - xFloor) * readWithFillValue(imageVals, imageHeight, imageWidth, batchStride, rowStride, colStride, batch, yCeil, xCeil, channel, fillValue);\n  return (yCeil - y) * valueYFloor + (y - yFloor) * valueYCeil;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Unique.js\nfunction unique3(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { axis } = attrs;\n  const { x } = inputs;\n  assertNotComplex(x, \"unique\");\n  const values = backend2.data.get(x.dataId).values;\n  const { outputValues, outputShape, indices } = uniqueImpl(values, axis, x.shape, x.dtype);\n  return [\n    backend2.makeTensorInfo(outputShape, x.dtype, outputValues),\n    backend2.makeTensorInfo([indices.length], \"int32\", indices)\n  ];\n}\nvar uniqueConfig = {\n  kernelName: Unique,\n  backendName: \"cpu\",\n  kernelFunc: unique3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/Unpack.js\nfunction unpack(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { value } = inputs;\n  let { axis } = attrs;\n  if (axis < 0) {\n    axis += value.shape.length;\n  }\n  const valueRank = value.shape.length;\n  const num = value.shape[axis];\n  const outShape = new Array(valueRank - 1);\n  let outIndex = 0;\n  for (let i2 = 0; i2 < valueRank; i2++) {\n    if (i2 !== axis) {\n      outShape[outIndex++] = value.shape[i2];\n    }\n  }\n  const begin = new Array(valueRank).fill(0);\n  const size = value.shape.slice();\n  size[axis] = 1;\n  const res = new Array(num);\n  for (let i2 = 0; i2 < res.length; i2++) {\n    begin[axis] = i2;\n    const tempRes = slice2({ inputs: { x: value }, backend: backend2, attrs: { begin, size } });\n    res[i2] = reshape3({ inputs: { x: tempRes }, backend: backend2, attrs: { shape: outShape } });\n    backend2.disposeIntermediateTensorInfo(tempRes);\n  }\n  return res;\n}\nvar unpackConfig = {\n  kernelName: Unpack,\n  backendName: \"cpu\",\n  kernelFunc: unpack\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/kernels/UnsortedSegmentSum.js\nfunction unsortedSegmentSum2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, segmentIds } = inputs;\n  const { numSegments } = attrs;\n  assertNotComplex(x, \"unsortedSegmentSum\");\n  const xRank = x.shape.length;\n  const segmentIdsRank = segmentIds.shape.length;\n  const res = [];\n  const intermediates = [];\n  const numIters = xRank - segmentIdsRank;\n  let $segmentIds = segmentIds;\n  for (let i2 = 0; i2 < numIters; ++i2) {\n    const expanded = expandDims3({ inputs: { input: $segmentIds }, backend: backend2, attrs: { dim: i2 + 1 } });\n    $segmentIds = expanded;\n    intermediates.push(expanded);\n  }\n  for (let i2 = 0; i2 < numSegments; ++i2) {\n    const scalarValue = util_exports.createScalarValue(i2, \"int32\");\n    const segmentId = backend2.makeTensorInfo([], \"int32\", scalarValue);\n    const mask = equal2({ inputs: { a: segmentId, b: $segmentIds }, backend: backend2 });\n    const maskCasted = cast3({ inputs: { x: mask }, backend: backend2, attrs: { dtype: \"float32\" } });\n    const mul2 = multiply2({ inputs: { a: maskCasted, b: x }, backend: backend2 });\n    const sumTensorInfo = sum3({ inputs: { x: mul2 }, backend: backend2, attrs: { axis: 0, keepDims: false } });\n    res.push(sumTensorInfo);\n    intermediates.push(segmentId);\n    intermediates.push(mask);\n    intermediates.push(maskCasted);\n    intermediates.push(mul2);\n    intermediates.push(sumTensorInfo);\n  }\n  const result = pack({ inputs: res, backend: backend2, attrs: { axis: 0 } });\n  intermediates.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return result;\n}\nvar unsortedSegmentSumConfig = {\n  kernelName: UnsortedSegmentSum,\n  backendName: \"cpu\",\n  kernelFunc: unsortedSegmentSum2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-cpu@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-cpu/dist/register_all_kernels.js\nvar kernelConfigs = [\n  _fusedMatMulConfig,\n  absConfig,\n  acosConfig,\n  acoshConfig,\n  addConfig,\n  addNConfig,\n  allConfig,\n  anyConfig,\n  argMaxConfig,\n  argMinConfig,\n  asinConfig,\n  asinhConfig,\n  atanConfig,\n  atan2Config,\n  atanhConfig,\n  avgPoolConfig,\n  avgPool3DConfig,\n  avgPool3DGradConfig2,\n  avgPoolGradConfig2,\n  batchMatMulConfig,\n  batchNormConfig,\n  batchToSpaceNDConfig,\n  bincountConfig,\n  broadcastArgsConfig,\n  castConfig,\n  ceilConfig,\n  clipByValueConfig,\n  complexConfig,\n  complexAbsConfig,\n  concatConfig,\n  conv2DConfig,\n  conv2DBackpropFilterConfig,\n  conv2DBackpropInputConfig,\n  conv3DConfig,\n  conv3DBackpropFilterV2Config,\n  conv3DBackpropInputV2Config,\n  cosConfig,\n  coshConfig,\n  cropAndResizeConfig,\n  cumprodConfig,\n  cumsumConfig,\n  denseBincountConfig,\n  depthToSpaceConfig,\n  depthwiseConv2dNativeConfig,\n  depthwiseConv2dNativeBackpropFilterConfig,\n  depthwiseConv2dNativeBackpropInputConfig,\n  diagConfig,\n  dilation2DConfig,\n  dilation2DBackpropFilterConfig,\n  dilation2DBackpropInputConfig,\n  einsumConfig,\n  eluConfig,\n  eluGradConfig2,\n  equalConfig,\n  erfConfig,\n  expConfig,\n  expandDimsConfig,\n  expm1Config,\n  fftConfig,\n  fillConfig,\n  flipLeftRightConfig,\n  floorConfig,\n  floorDivConfig,\n  fusedConv2DConfig,\n  fusedDepthwiseConv2DConfig,\n  gatherNdConfig,\n  gatherV2Config,\n  greaterConfig,\n  greaterEqualConfig,\n  identityConfig,\n  ifftConfig,\n  imagConfig,\n  isFiniteConfig,\n  isInfConfig,\n  isNaNConfig,\n  leakyReluConfig,\n  lessConfig,\n  lessEqualConfig,\n  linSpaceConfig,\n  logConfig,\n  log1pConfig,\n  logicalAndConfig,\n  logicalNotConfig,\n  logicalOrConfig,\n  LRNConfig,\n  LRNGradConfig,\n  maxConfig,\n  maximumConfig,\n  maxPoolConfig,\n  maxPool3DConfig,\n  maxPool3DGradConfig2,\n  maxPoolGradConfig2,\n  maxPoolWithArgmaxConfig,\n  meanConfig,\n  minConfig,\n  minimumConfig,\n  mirrorPadConfig,\n  modConfig,\n  multinomialConfig,\n  multiplyConfig,\n  negConfig,\n  nonMaxSuppressionV3Config,\n  nonMaxSuppressionV4Config,\n  nonMaxSuppressionV5Config,\n  notEqualConfig,\n  oneHotConfig,\n  onesLikeConfig,\n  packConfig,\n  padV2Config,\n  powConfig,\n  preluConfig,\n  prodConfig,\n  rangeConfig,\n  realConfig,\n  realDivConfig,\n  reciprocalConfig,\n  reluConfig,\n  relu6Config,\n  reshapeConfig,\n  resizeBilinearConfig,\n  resizeBilinearGradConfig2,\n  resizeNearestNeighborConfig,\n  resizeNearestNeighborGradConfig2,\n  reverseConfig,\n  rotateWithOffsetConfig,\n  roundConfig,\n  rsqrtConfig,\n  scatterNdConfig,\n  searchSortedConfig,\n  selectConfig,\n  seluConfig,\n  sigmoidConfig,\n  signConfig,\n  sinConfig,\n  sinhConfig,\n  sliceConfig,\n  softmaxConfig,\n  softplusConfig,\n  spaceToBatchNDConfig,\n  sparseFillEmptyRowsConfig,\n  sparseReshapeConfig,\n  sparseSegmentMeanConfig,\n  sparseSegmentSumConfig,\n  sparseToDenseConfig,\n  splitVConfig,\n  sqrtConfig,\n  squareConfig,\n  squaredDifferenceConfig,\n  stepConfig,\n  stridedSliceConfig,\n  stringNGramsConfig,\n  stringSplitConfig,\n  stringToHashBucketFastConfig,\n  subConfig,\n  sumConfig,\n  tanConfig,\n  tanhConfig,\n  tileConfig,\n  topKConfig,\n  transformConfig,\n  transposeConfig,\n  uniqueConfig,\n  unpackConfig,\n  unsortedSegmentSumConfig,\n  zerosLikeConfig\n];\nfor (const kernelConfig of kernelConfigs) {\n  registerKernel(kernelConfig);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/webgl_util.js\nvar webgl_util_exports = {};\n__export(webgl_util_exports, {\n  assertNotComplex: () => assertNotComplex2,\n  bindCanvasToFramebuffer: () => bindCanvasToFramebuffer,\n  bindColorTextureToFramebuffer: () => bindColorTextureToFramebuffer,\n  bindTextureToProgramUniformSampler: () => bindTextureToProgramUniformSampler,\n  bindTextureUnit: () => bindTextureUnit,\n  bindVertexBufferToProgramAttribute: () => bindVertexBufferToProgramAttribute,\n  callAndCheck: () => callAndCheck,\n  canBeRepresented: () => canBeRepresented,\n  createFragmentShader: () => createFragmentShader,\n  createFramebuffer: () => createFramebuffer,\n  createProgram: () => createProgram,\n  createStaticIndexBuffer: () => createStaticIndexBuffer,\n  createStaticVertexBuffer: () => createStaticVertexBuffer,\n  createTexture: () => createTexture,\n  createVertexShader: () => createVertexShader,\n  getBatchDim: () => getBatchDim,\n  getExtensionOrThrow: () => getExtensionOrThrow,\n  getFramebufferErrorMessage: () => getFramebufferErrorMessage,\n  getMaxTexturesInShader: () => getMaxTexturesInShader,\n  getNumChannels: () => getNumChannels,\n  getProgramUniformLocation: () => getProgramUniformLocation,\n  getProgramUniformLocationOrThrow: () => getProgramUniformLocationOrThrow,\n  getRowsCols: () => getRowsCols,\n  getShapeAs3D: () => getShapeAs3D,\n  getTextureShapeFromLogicalShape: () => getTextureShapeFromLogicalShape,\n  getWebGLDisjointQueryTimerVersion: () => getWebGLDisjointQueryTimerVersion,\n  getWebGLErrorMessage: () => getWebGLErrorMessage,\n  getWebGLMaxTextureSize: () => getWebGLMaxTextureSize,\n  hasExtension: () => hasExtension,\n  isCapableOfRenderingToFloatTexture: () => isCapableOfRenderingToFloatTexture,\n  isDownloadFloatTextureEnabled: () => isDownloadFloatTextureEnabled,\n  isReshapeFree: () => isReshapeFree,\n  isWebGLFenceEnabled: () => isWebGLFenceEnabled,\n  isWebGLVersionEnabled: () => isWebGLVersionEnabled,\n  linkProgram: () => linkProgram,\n  logShaderSourceAndInfoLog: () => logShaderSourceAndInfoLog,\n  resetMaxTextureSize: () => resetMaxTextureSize,\n  resetMaxTexturesInShader: () => resetMaxTexturesInShader,\n  unbindColorTextureFromFramebuffer: () => unbindColorTextureFromFramebuffer,\n  unbindTextureUnit: () => unbindTextureUnit,\n  validateFramebuffer: () => validateFramebuffer,\n  validateProgram: () => validateProgram,\n  validateTextureSize: () => validateTextureSize\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/canvas_util.js\nvar contexts = {};\nvar WEBGL_ATTRIBUTES = {\n  alpha: false,\n  antialias: false,\n  premultipliedAlpha: false,\n  preserveDrawingBuffer: false,\n  depth: false,\n  stencil: false,\n  failIfMajorPerformanceCaveat: true\n};\nfunction setWebGLContext(webGLVersion, gl) {\n  contexts[webGLVersion] = gl;\n}\nfunction getWebGLContext(webGLVersion, customCanvas) {\n  if (!(webGLVersion in contexts) || customCanvas != null) {\n    const newCtx = getWebGLRenderingContext(webGLVersion, customCanvas);\n    if (newCtx !== null) {\n      contexts[webGLVersion] = newCtx;\n    } else {\n      console.log(\"Could not get context for WebGL version\", webGLVersion);\n      return null;\n    }\n  }\n  const gl = contexts[webGLVersion];\n  if (gl == null || gl.isContextLost()) {\n    delete contexts[webGLVersion];\n    return getWebGLContext(webGLVersion);\n  }\n  gl.disable(gl.DEPTH_TEST);\n  gl.disable(gl.STENCIL_TEST);\n  gl.disable(gl.BLEND);\n  gl.disable(gl.DITHER);\n  gl.disable(gl.POLYGON_OFFSET_FILL);\n  gl.disable(gl.SAMPLE_COVERAGE);\n  gl.enable(gl.SCISSOR_TEST);\n  gl.enable(gl.CULL_FACE);\n  gl.cullFace(gl.BACK);\n  return contexts[webGLVersion];\n}\nfunction createCanvas(webGLVersion) {\n  if (typeof OffscreenCanvas !== \"undefined\" && webGLVersion === 2) {\n    return new OffscreenCanvas(300, 150);\n  } else if (typeof document !== \"undefined\") {\n    return document.createElement(\"canvas\");\n  } else {\n    throw new Error(\"Cannot create a canvas in this context\");\n  }\n}\nfunction getWebGLRenderingContext(webGLVersion, customCanvas) {\n  if (webGLVersion !== 1 && webGLVersion !== 2) {\n    throw new Error(\"Cannot get WebGL rendering context, WebGL is disabled.\");\n  }\n  const canvas = customCanvas == null ? createCanvas(webGLVersion) : customCanvas;\n  canvas.addEventListener(\"webglcontextlost\", (ev) => {\n    ev.preventDefault();\n    delete contexts[webGLVersion];\n  }, false);\n  if (webGLVersion === 1) {\n    return canvas.getContext(\"webgl\", WEBGL_ATTRIBUTES) || canvas.getContext(\"experimental-webgl\", WEBGL_ATTRIBUTES);\n  }\n  return canvas.getContext(\"webgl2\", WEBGL_ATTRIBUTES);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/tex_util.js\nvar PackingScheme;\n(function(PackingScheme2) {\n  PackingScheme2[PackingScheme2[\"DENSE\"] = 0] = \"DENSE\";\n  PackingScheme2[PackingScheme2[\"SHARED_BATCH\"] = 1] = \"SHARED_BATCH\";\n})(PackingScheme || (PackingScheme = {}));\nvar TextureUsage;\n(function(TextureUsage2) {\n  TextureUsage2[TextureUsage2[\"RENDER\"] = 0] = \"RENDER\";\n  TextureUsage2[TextureUsage2[\"UPLOAD\"] = 1] = \"UPLOAD\";\n  TextureUsage2[TextureUsage2[\"PIXELS\"] = 2] = \"PIXELS\";\n  TextureUsage2[TextureUsage2[\"DOWNLOAD\"] = 3] = \"DOWNLOAD\";\n})(TextureUsage || (TextureUsage = {}));\nvar PhysicalTextureType;\n(function(PhysicalTextureType2) {\n  PhysicalTextureType2[PhysicalTextureType2[\"UNPACKED_FLOAT16\"] = 0] = \"UNPACKED_FLOAT16\";\n  PhysicalTextureType2[PhysicalTextureType2[\"UNPACKED_FLOAT32\"] = 1] = \"UNPACKED_FLOAT32\";\n  PhysicalTextureType2[PhysicalTextureType2[\"PACKED_4X1_UNSIGNED_BYTE\"] = 2] = \"PACKED_4X1_UNSIGNED_BYTE\";\n  PhysicalTextureType2[PhysicalTextureType2[\"PACKED_2X2_FLOAT32\"] = 3] = \"PACKED_2X2_FLOAT32\";\n  PhysicalTextureType2[PhysicalTextureType2[\"PACKED_2X2_FLOAT16\"] = 4] = \"PACKED_2X2_FLOAT16\";\n})(PhysicalTextureType || (PhysicalTextureType = {}));\nfunction getUnpackedMatrixTextureShapeWidthHeight(rows, columns) {\n  return [columns, rows];\n}\nfunction getUnpackedArraySizeFromMatrixSize(matrixSize, channelsPerTexture) {\n  return matrixSize * channelsPerTexture;\n}\nfunction getDenseTexShape(shape) {\n  const size = util_exports.sizeFromShape(shape);\n  const texelsNeeded = Math.ceil(size / 4);\n  return util_exports.sizeToSquarishShape(texelsNeeded);\n}\nfunction getPackedMatrixTextureShapeWidthHeight(rows, columns) {\n  return [\n    Math.max(1, Math.ceil(columns / 2)),\n    Math.max(1, Math.ceil(rows / 2))\n  ];\n}\nfunction getPackedRGBAArraySizeFromMatrixShape(rows, columns) {\n  const [w, h] = getPackedMatrixTextureShapeWidthHeight(rows, columns);\n  return w * h * 4;\n}\nfunction getTextureConfig(gl, textureHalfFloatExtension) {\n  const glany = gl;\n  let internalFormatFloat;\n  let internalFormatHalfFloat;\n  let internalFormatPackedHalfFloat;\n  let internalFormatPackedFloat;\n  let textureFormatFloat;\n  let downloadTextureFormat;\n  let downloadUnpackNumChannels;\n  let defaultNumChannels;\n  let textureTypeHalfFloat;\n  let textureTypeFloat;\n  if (env().getNumber(\"WEBGL_VERSION\") === 2) {\n    internalFormatFloat = glany.R32F;\n    internalFormatHalfFloat = glany.R16F;\n    internalFormatPackedHalfFloat = glany.RGBA16F;\n    internalFormatPackedFloat = glany.RGBA32F;\n    textureFormatFloat = glany.RED;\n    downloadUnpackNumChannels = 4;\n    defaultNumChannels = 1;\n    textureTypeHalfFloat = glany.HALF_FLOAT;\n    textureTypeFloat = glany.FLOAT;\n    downloadTextureFormat = glany.RGBA8;\n  } else {\n    internalFormatFloat = gl.RGBA;\n    internalFormatHalfFloat = gl.RGBA;\n    internalFormatPackedHalfFloat = gl.RGBA;\n    internalFormatPackedFloat = glany.RGBA;\n    textureFormatFloat = gl.RGBA;\n    downloadUnpackNumChannels = 4;\n    defaultNumChannels = 4;\n    textureTypeHalfFloat = textureHalfFloatExtension != null ? textureHalfFloatExtension.HALF_FLOAT_OES : null;\n    textureTypeFloat = gl.FLOAT;\n    downloadTextureFormat = gl.RGBA;\n  }\n  return {\n    internalFormatFloat,\n    internalFormatHalfFloat,\n    internalFormatPackedHalfFloat,\n    internalFormatPackedFloat,\n    textureFormatFloat,\n    downloadTextureFormat,\n    downloadUnpackNumChannels,\n    defaultNumChannels,\n    textureTypeHalfFloat,\n    textureTypeFloat\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/webgl_util.js\nfunction callAndCheck(gl, func2) {\n  const returnValue = func2();\n  if (env().getBool(\"DEBUG\")) {\n    checkWebGLError(gl);\n  }\n  return returnValue;\n}\nfunction checkWebGLError(gl) {\n  const error = gl.getError();\n  if (error !== gl.NO_ERROR) {\n    throw new Error(\"WebGL Error: \" + getWebGLErrorMessage(gl, error));\n  }\n}\nvar MIN_FLOAT16 = 596e-10;\nvar MAX_FLOAT16 = 65504;\nfunction canBeRepresented(num) {\n  if (env().getBool(\"WEBGL_RENDER_FLOAT32_ENABLED\") || num === 0 || MIN_FLOAT16 < Math.abs(num) && Math.abs(num) < MAX_FLOAT16) {\n    return true;\n  }\n  return false;\n}\nfunction getWebGLErrorMessage(gl, status) {\n  switch (status) {\n    case gl.NO_ERROR:\n      return \"NO_ERROR\";\n    case gl.INVALID_ENUM:\n      return \"INVALID_ENUM\";\n    case gl.INVALID_VALUE:\n      return \"INVALID_VALUE\";\n    case gl.INVALID_OPERATION:\n      return \"INVALID_OPERATION\";\n    case gl.INVALID_FRAMEBUFFER_OPERATION:\n      return \"INVALID_FRAMEBUFFER_OPERATION\";\n    case gl.OUT_OF_MEMORY:\n      return \"OUT_OF_MEMORY\";\n    case gl.CONTEXT_LOST_WEBGL:\n      return \"CONTEXT_LOST_WEBGL\";\n    default:\n      return `Unknown error code ${status}`;\n  }\n}\nfunction getExtensionOrThrow(gl, extensionName) {\n  return throwIfNull(gl, () => gl.getExtension(extensionName), 'Extension \"' + extensionName + '\" not supported on this browser.');\n}\nfunction createVertexShader(gl, vertexShaderSource) {\n  const vertexShader = throwIfNull(gl, () => gl.createShader(gl.VERTEX_SHADER), \"Unable to create vertex WebGLShader.\");\n  callAndCheck(gl, () => gl.shaderSource(vertexShader, vertexShaderSource));\n  callAndCheck(gl, () => gl.compileShader(vertexShader));\n  if (gl.getShaderParameter(vertexShader, gl.COMPILE_STATUS) === false) {\n    console.log(gl.getShaderInfoLog(vertexShader));\n    throw new Error(\"Failed to compile vertex shader.\");\n  }\n  return vertexShader;\n}\nfunction createFragmentShader(gl, fragmentShaderSource) {\n  const fragmentShader = throwIfNull(gl, () => gl.createShader(gl.FRAGMENT_SHADER), \"Unable to create fragment WebGLShader.\");\n  callAndCheck(gl, () => gl.shaderSource(fragmentShader, fragmentShaderSource));\n  callAndCheck(gl, () => gl.compileShader(fragmentShader));\n  if (env().get(\"ENGINE_COMPILE_ONLY\")) {\n    return fragmentShader;\n  }\n  if (gl.getShaderParameter(fragmentShader, gl.COMPILE_STATUS) === false) {\n    logShaderSourceAndInfoLog(fragmentShaderSource, gl.getShaderInfoLog(fragmentShader));\n    throw new Error(\"Failed to compile fragment shader.\");\n  }\n  return fragmentShader;\n}\nvar lineNumberRegex = /ERROR: [0-9]+:([0-9]+):/g;\nfunction logShaderSourceAndInfoLog(shaderSource, shaderInfoLog) {\n  const lineNumberRegexResult = lineNumberRegex.exec(shaderInfoLog);\n  if (lineNumberRegexResult == null) {\n    console.log(`Couldn't parse line number in error: ${shaderInfoLog}`);\n    console.log(shaderSource);\n    return;\n  }\n  const lineNumber = +lineNumberRegexResult[1];\n  const shaderLines = shaderSource.split(\"\\n\");\n  const pad3 = shaderLines.length.toString().length + 2;\n  const linesWithLineNumbers = shaderLines.map((line, lineNumber2) => util_exports.rightPad((lineNumber2 + 1).toString(), pad3) + line);\n  let maxLineLength = 0;\n  for (let i2 = 0; i2 < linesWithLineNumbers.length; i2++) {\n    maxLineLength = Math.max(linesWithLineNumbers[i2].length, maxLineLength);\n  }\n  const beforeErrorLines = linesWithLineNumbers.slice(0, lineNumber - 1);\n  const errorLine = linesWithLineNumbers.slice(lineNumber - 1, lineNumber);\n  const afterErrorLines = linesWithLineNumbers.slice(lineNumber);\n  console.log(beforeErrorLines.join(\"\\n\"));\n  console.log(shaderInfoLog.split(\"\\n\")[0]);\n  console.log(`%c ${util_exports.rightPad(errorLine[0], maxLineLength)}`, \"border:1px solid red; background-color:#e3d2d2; color:#a61717\");\n  console.log(afterErrorLines.join(\"\\n\"));\n}\nfunction createProgram(gl) {\n  return throwIfNull(gl, () => gl.createProgram(), \"Unable to create WebGLProgram.\");\n}\nfunction linkProgram(gl, program) {\n  callAndCheck(gl, () => gl.linkProgram(program));\n  if (env().get(\"ENGINE_COMPILE_ONLY\")) {\n    return;\n  }\n  if (gl.getProgramParameter(program, gl.LINK_STATUS) === false) {\n    console.log(gl.getProgramInfoLog(program));\n    throw new Error(\"Failed to link vertex and fragment shaders.\");\n  }\n}\nfunction validateProgram(gl, program) {\n  callAndCheck(gl, () => gl.validateProgram(program));\n  if (gl.getProgramParameter(program, gl.VALIDATE_STATUS) === false) {\n    console.log(gl.getProgramInfoLog(program));\n    throw new Error(\"Shader program validation failed.\");\n  }\n}\nfunction createStaticVertexBuffer(gl, data) {\n  const buffer2 = throwIfNull(gl, () => gl.createBuffer(), \"Unable to create WebGLBuffer\");\n  callAndCheck(gl, () => gl.bindBuffer(gl.ARRAY_BUFFER, buffer2));\n  callAndCheck(gl, () => gl.bufferData(gl.ARRAY_BUFFER, data, gl.STATIC_DRAW));\n  return buffer2;\n}\nfunction createStaticIndexBuffer(gl, data) {\n  const buffer2 = throwIfNull(gl, () => gl.createBuffer(), \"Unable to create WebGLBuffer\");\n  callAndCheck(gl, () => gl.bindBuffer(gl.ELEMENT_ARRAY_BUFFER, buffer2));\n  callAndCheck(gl, () => gl.bufferData(gl.ELEMENT_ARRAY_BUFFER, data, gl.STATIC_DRAW));\n  return buffer2;\n}\nfunction getNumChannels() {\n  if (env().getNumber(\"WEBGL_VERSION\") === 2) {\n    return 1;\n  }\n  return 4;\n}\nfunction createTexture(gl) {\n  return throwIfNull(gl, () => gl.createTexture(), \"Unable to create WebGLTexture.\");\n}\nfunction validateTextureSize(width, height) {\n  const maxTextureSize = env().getNumber(\"WEBGL_MAX_TEXTURE_SIZE\");\n  if (width <= 0 || height <= 0) {\n    const requested = `[${width}x${height}]`;\n    throw new Error(\"Requested texture size \" + requested + \" is invalid.\");\n  }\n  if (width > maxTextureSize || height > maxTextureSize) {\n    const requested = `[${width}x${height}]`;\n    const max7 = `[${maxTextureSize}x${maxTextureSize}]`;\n    throw new Error(\"Requested texture size \" + requested + \" greater than WebGL maximum on this browser / GPU \" + max7 + \".\");\n  }\n}\nfunction createFramebuffer(gl) {\n  return throwIfNull(gl, () => gl.createFramebuffer(), \"Unable to create WebGLFramebuffer.\");\n}\nfunction bindVertexBufferToProgramAttribute(gl, program, attribute, buffer2, arrayEntriesPerItem, itemStrideInBytes, itemOffsetInBytes) {\n  const loc = gl.getAttribLocation(program, attribute);\n  if (loc === -1) {\n    return false;\n  }\n  callAndCheck(gl, () => gl.bindBuffer(gl.ARRAY_BUFFER, buffer2));\n  callAndCheck(gl, () => gl.vertexAttribPointer(loc, arrayEntriesPerItem, gl.FLOAT, false, itemStrideInBytes, itemOffsetInBytes));\n  callAndCheck(gl, () => gl.enableVertexAttribArray(loc));\n  return true;\n}\nfunction bindTextureUnit(gl, texture, textureUnit) {\n  validateTextureUnit(gl, textureUnit);\n  callAndCheck(gl, () => gl.activeTexture(gl.TEXTURE0 + textureUnit));\n  callAndCheck(gl, () => gl.bindTexture(gl.TEXTURE_2D, texture));\n}\nfunction unbindTextureUnit(gl, textureUnit) {\n  validateTextureUnit(gl, textureUnit);\n  callAndCheck(gl, () => gl.activeTexture(gl.TEXTURE0 + textureUnit));\n  callAndCheck(gl, () => gl.bindTexture(gl.TEXTURE_2D, null));\n}\nfunction getProgramUniformLocationOrThrow(gl, program, uniformName) {\n  return throwIfNull(gl, () => gl.getUniformLocation(program, uniformName), 'uniform \"' + uniformName + '\" not present in program.');\n}\nfunction getProgramUniformLocation(gl, program, uniformName) {\n  return gl.getUniformLocation(program, uniformName);\n}\nfunction bindTextureToProgramUniformSampler(gl, texture, uniformSamplerLocation, textureUnit) {\n  callAndCheck(gl, () => bindTextureUnit(gl, texture, textureUnit));\n  callAndCheck(gl, () => gl.uniform1i(uniformSamplerLocation, textureUnit));\n}\nfunction bindCanvasToFramebuffer(gl) {\n  callAndCheck(gl, () => gl.bindFramebuffer(gl.FRAMEBUFFER, null));\n  callAndCheck(gl, () => gl.viewport(0, 0, gl.canvas.width, gl.canvas.height));\n  callAndCheck(gl, () => gl.scissor(0, 0, gl.canvas.width, gl.canvas.height));\n}\nfunction bindColorTextureToFramebuffer(gl, texture, framebuffer) {\n  callAndCheck(gl, () => gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffer));\n  callAndCheck(gl, () => gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0));\n}\nfunction unbindColorTextureFromFramebuffer(gl, framebuffer) {\n  callAndCheck(gl, () => gl.bindFramebuffer(gl.FRAMEBUFFER, framebuffer));\n  callAndCheck(gl, () => gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, null, 0));\n}\nfunction validateFramebuffer(gl) {\n  const status = gl.checkFramebufferStatus(gl.FRAMEBUFFER);\n  if (status !== gl.FRAMEBUFFER_COMPLETE) {\n    throw new Error(\"Error binding framebuffer: \" + getFramebufferErrorMessage(gl, status));\n  }\n}\nfunction getFramebufferErrorMessage(gl, status) {\n  switch (status) {\n    case gl.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:\n      return \"FRAMEBUFFER_INCOMPLETE_ATTACHMENT\";\n    case gl.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:\n      return \"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT\";\n    case gl.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:\n      return \"FRAMEBUFFER_INCOMPLETE_DIMENSIONS\";\n    case gl.FRAMEBUFFER_UNSUPPORTED:\n      return \"FRAMEBUFFER_UNSUPPORTED\";\n    default:\n      return `unknown error ${status}`;\n  }\n}\nfunction throwIfNull(gl, returnTOrNull, failureMessage) {\n  const tOrNull = callAndCheck(gl, () => returnTOrNull());\n  if (tOrNull == null) {\n    throw new Error(failureMessage);\n  }\n  return tOrNull;\n}\nfunction validateTextureUnit(gl, textureUnit) {\n  const maxTextureUnit = gl.MAX_COMBINED_TEXTURE_IMAGE_UNITS - 1;\n  const glTextureUnit = textureUnit + gl.TEXTURE0;\n  if (glTextureUnit < gl.TEXTURE0 || glTextureUnit > maxTextureUnit) {\n    const textureUnitRange = `[gl.TEXTURE0, gl.TEXTURE${maxTextureUnit}]`;\n    throw new Error(`textureUnit must be in ${textureUnitRange}.`);\n  }\n}\nfunction getBatchDim(shape, dimsToSkip = 2) {\n  return util_exports.sizeFromShape(shape.slice(0, shape.length - dimsToSkip));\n}\nfunction getRowsCols(shape) {\n  if (shape.length === 0) {\n    throw Error(\"Cannot get rows and columns of an empty shape array.\");\n  }\n  return [\n    shape.length > 1 ? shape[shape.length - 2] : 1,\n    shape[shape.length - 1]\n  ];\n}\nfunction getShapeAs3D(shape) {\n  let shapeAs3D = [1, 1, 1];\n  const isScalar = shape.length === 0 || shape.length === 1 && shape[0] === 1;\n  if (!isScalar) {\n    shapeAs3D = [getBatchDim(shape), ...getRowsCols(shape)];\n  }\n  return shapeAs3D;\n}\nfunction getTextureShapeFromLogicalShape(logShape, isPacked = false) {\n  let maxTexSize = env().getNumber(\"WEBGL_MAX_TEXTURE_SIZE\");\n  if (isPacked) {\n    maxTexSize = maxTexSize * 2;\n    logShape = logShape.map((d, i2) => i2 >= logShape.length - 2 ? util_exports.nearestLargerEven(logShape[i2]) : logShape[i2]);\n    if (logShape.length === 1) {\n      logShape = [2, logShape[0]];\n    }\n  }\n  if (logShape.length !== 2) {\n    const squeezeResult = util_exports.squeezeShape(logShape);\n    logShape = squeezeResult.newShape;\n  }\n  let size = util_exports.sizeFromShape(logShape);\n  if (logShape.length <= 1 && size <= maxTexSize) {\n    return [1, size];\n  } else if (logShape.length === 2 && logShape[0] <= maxTexSize && logShape[1] <= maxTexSize) {\n    return logShape;\n  } else if (logShape.length === 3 && logShape[0] * logShape[1] <= maxTexSize && logShape[2] <= maxTexSize) {\n    return [logShape[0] * logShape[1], logShape[2]];\n  } else if (logShape.length === 3 && logShape[0] <= maxTexSize && logShape[1] * logShape[2] <= maxTexSize) {\n    return [logShape[0], logShape[1] * logShape[2]];\n  } else if (logShape.length === 4 && logShape[0] * logShape[1] * logShape[2] <= maxTexSize && logShape[3] <= maxTexSize) {\n    return [logShape[0] * logShape[1] * logShape[2], logShape[3]];\n  } else if (logShape.length === 4 && logShape[0] <= maxTexSize && logShape[1] * logShape[2] * logShape[3] <= maxTexSize) {\n    return [logShape[0], logShape[1] * logShape[2] * logShape[3]];\n  } else {\n    if (isPacked) {\n      const batchDim = getBatchDim(logShape);\n      let rows = 2, cols = 2;\n      if (logShape.length) {\n        [rows, cols] = getRowsCols(logShape);\n      }\n      size = batchDim * (rows / 2) * (cols / 2);\n      return util_exports.sizeToSquarishShape(size).map((d) => d * 2);\n    }\n    return util_exports.sizeToSquarishShape(size);\n  }\n}\nfunction isEven(n2) {\n  return n2 % 2 === 0;\n}\nfunction isReshapeFree(shape1, shape2) {\n  shape1 = shape1.slice(-2);\n  shape2 = shape2.slice(-2);\n  if (util_exports.arraysEqual(shape1, shape2)) {\n    return true;\n  }\n  if (!shape1.length || !shape2.length) {\n    return true;\n  }\n  if (shape1[0] === 0 || shape1[1] === 0 || shape2[0] === 0 || shape2[1] === 0) {\n    return true;\n  }\n  if (shape1.length !== shape2.length) {\n    const shape1Cols = shape1.slice(-1)[0];\n    const shape2Cols = shape2.slice(-1)[0];\n    if (shape1Cols === shape2Cols) {\n      return true;\n    }\n    if (isEven(shape1Cols) && isEven(shape2Cols) && (shape1[0] === 1 || shape2[0] === 1)) {\n      return true;\n    }\n  }\n  return shape1[1] === shape2[1] && isEven(shape1[0]) && isEven(shape2[0]);\n}\nvar MAX_TEXTURE_SIZE;\nvar MAX_TEXTURES_IN_SHADER;\nfunction getWebGLMaxTextureSize(webGLVersion) {\n  if (MAX_TEXTURE_SIZE == null) {\n    const gl = getWebGLContext(webGLVersion);\n    MAX_TEXTURE_SIZE = gl.getParameter(gl.MAX_TEXTURE_SIZE);\n  }\n  return MAX_TEXTURE_SIZE;\n}\nfunction resetMaxTextureSize() {\n  MAX_TEXTURE_SIZE = null;\n}\nfunction resetMaxTexturesInShader() {\n  MAX_TEXTURES_IN_SHADER = null;\n}\nfunction getMaxTexturesInShader(webGLVersion) {\n  if (MAX_TEXTURES_IN_SHADER == null) {\n    const gl = getWebGLContext(webGLVersion);\n    MAX_TEXTURES_IN_SHADER = gl.getParameter(gl.MAX_TEXTURE_IMAGE_UNITS);\n  }\n  return Math.min(16, MAX_TEXTURES_IN_SHADER);\n}\nfunction getWebGLDisjointQueryTimerVersion(webGLVersion) {\n  if (webGLVersion === 0) {\n    return 0;\n  }\n  let queryTimerVersion;\n  const gl = getWebGLContext(webGLVersion);\n  if (hasExtension(gl, \"EXT_disjoint_timer_query_webgl2\") && webGLVersion === 2) {\n    queryTimerVersion = 2;\n  } else if (hasExtension(gl, \"EXT_disjoint_timer_query\")) {\n    queryTimerVersion = 1;\n  } else {\n    queryTimerVersion = 0;\n  }\n  return queryTimerVersion;\n}\nfunction hasExtension(gl, extensionName) {\n  const ext = gl.getExtension(extensionName);\n  return ext != null;\n}\nfunction isWebGLVersionEnabled(webGLVersion) {\n  try {\n    const gl = getWebGLContext(webGLVersion);\n    if (gl != null) {\n      return true;\n    }\n  } catch (e2) {\n    console.log(\"Error when getting WebGL context: \", e2);\n    return false;\n  }\n  return false;\n}\nfunction isCapableOfRenderingToFloatTexture(webGLVersion) {\n  if (webGLVersion === 0) {\n    return false;\n  }\n  const gl = getWebGLContext(webGLVersion);\n  if (webGLVersion === 1) {\n    if (!hasExtension(gl, \"OES_texture_float\")) {\n      return false;\n    }\n  } else {\n    if (!hasExtension(gl, \"EXT_color_buffer_float\")) {\n      return false;\n    }\n  }\n  const isFrameBufferComplete = createFloatTextureAndBindToFramebuffer(gl);\n  return isFrameBufferComplete;\n}\nfunction isDownloadFloatTextureEnabled(webGLVersion) {\n  if (webGLVersion === 0) {\n    return false;\n  }\n  const gl = getWebGLContext(webGLVersion);\n  if (webGLVersion === 1) {\n    if (!hasExtension(gl, \"OES_texture_float\")) {\n      return false;\n    }\n    if (!hasExtension(gl, \"WEBGL_color_buffer_float\")) {\n      return false;\n    }\n  } else {\n    if (hasExtension(gl, \"EXT_color_buffer_float\")) {\n      return createFloatTextureAndBindToFramebuffer(gl);\n    }\n    const COLOR_BUFFER_HALF_FLOAT = \"EXT_color_buffer_half_float\";\n    if (hasExtension(gl, COLOR_BUFFER_HALF_FLOAT)) {\n      const textureHalfFloatExtension = gl.getExtension(COLOR_BUFFER_HALF_FLOAT);\n      return createHalfFloatTextureAndBindToFramebuffer(gl, textureHalfFloatExtension);\n    }\n    return false;\n  }\n  const isFrameBufferComplete = createFloatTextureAndBindToFramebuffer(gl);\n  return isFrameBufferComplete;\n}\nfunction createFloatTextureAndBindToFramebuffer(gl) {\n  const texConfig = getTextureConfig(gl);\n  const texture = gl.createTexture();\n  gl.bindTexture(gl.TEXTURE_2D, texture);\n  const width = 1;\n  const height = 1;\n  gl.texImage2D(gl.TEXTURE_2D, 0, texConfig.internalFormatFloat, width, height, 0, texConfig.textureFormatFloat, texConfig.textureTypeFloat, null);\n  const frameBuffer = gl.createFramebuffer();\n  gl.bindFramebuffer(gl.FRAMEBUFFER, frameBuffer);\n  gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n  const isFrameBufferComplete = gl.checkFramebufferStatus(gl.FRAMEBUFFER) === gl.FRAMEBUFFER_COMPLETE;\n  gl.bindTexture(gl.TEXTURE_2D, null);\n  gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n  gl.deleteTexture(texture);\n  gl.deleteFramebuffer(frameBuffer);\n  return isFrameBufferComplete;\n}\nfunction createHalfFloatTextureAndBindToFramebuffer(gl, textureHalfFloatExtension) {\n  const texConfig = getTextureConfig(gl, textureHalfFloatExtension);\n  const texture = gl.createTexture();\n  gl.bindTexture(gl.TEXTURE_2D, texture);\n  const width = 1;\n  const height = 1;\n  gl.texImage2D(gl.TEXTURE_2D, 0, texConfig.internalFormatHalfFloat, width, height, 0, texConfig.textureFormatFloat, texConfig.textureTypeHalfFloat, null);\n  const frameBuffer = gl.createFramebuffer();\n  gl.bindFramebuffer(gl.FRAMEBUFFER, frameBuffer);\n  gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n  const isFrameBufferComplete = gl.checkFramebufferStatus(gl.FRAMEBUFFER) === gl.FRAMEBUFFER_COMPLETE;\n  gl.bindTexture(gl.TEXTURE_2D, null);\n  gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n  gl.deleteTexture(texture);\n  gl.deleteFramebuffer(frameBuffer);\n  return isFrameBufferComplete;\n}\nfunction isWebGLFenceEnabled(webGLVersion) {\n  if (webGLVersion !== 2) {\n    return false;\n  }\n  const gl = getWebGLContext(webGLVersion);\n  const isEnabled = gl.fenceSync != null;\n  return isEnabled;\n}\nfunction assertNotComplex2(tensor2, opName) {\n  if (!Array.isArray(tensor2)) {\n    tensor2 = [tensor2];\n  }\n  tensor2.forEach((t2) => {\n    if (t2 != null) {\n      util_exports.assert(t2.dtype !== \"complex64\", () => `${opName} does not support complex64 tensors in the WebGL backend.`);\n    }\n  });\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/flags_webgl.js\nvar ENV5 = env();\nENV5.registerFlag(\"HAS_WEBGL\", () => ENV5.getNumber(\"WEBGL_VERSION\") > 0);\nENV5.registerFlag(\"WEBGL_VERSION\", () => {\n  if (isWebGLVersionEnabled(2)) {\n    return 2;\n  } else if (isWebGLVersionEnabled(1)) {\n    return 1;\n  }\n  return 0;\n});\nENV5.registerFlag(\"WEBGL_CHECK_NUMERICAL_PROBLEMS\", () => false);\nENV5.registerFlag(\"WEBGL_BUFFER_SUPPORTED\", () => ENV5.get(\"WEBGL_VERSION\") === 2);\nENV5.registerFlag(\"WEBGL_CPU_FORWARD\", () => true);\nENV5.registerFlag(\"WEBGL_FORCE_F16_TEXTURES\", () => false);\nENV5.registerFlag(\"WEBGL_PACK\", () => ENV5.getBool(\"HAS_WEBGL\"));\nENV5.registerFlag(\"WEBGL_PACK_NORMALIZATION\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_PACK_CLIP\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_PACK_DEPTHWISECONV\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_PACK_BINARY_OPERATIONS\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_PACK_UNARY_OPERATIONS\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_PACK_ARRAY_OPERATIONS\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_PACK_IMAGE_OPERATIONS\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_PACK_REDUCE\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_LAZILY_UNPACK\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_CONV_IM2COL\", () => ENV5.getBool(\"WEBGL_PACK\"));\nENV5.registerFlag(\"WEBGL_MAX_TEXTURE_SIZE\", () => getWebGLMaxTextureSize(ENV5.getNumber(\"WEBGL_VERSION\")));\nENV5.registerFlag(\"WEBGL_MAX_TEXTURES_IN_SHADER\", () => getMaxTexturesInShader(ENV5.getNumber(\"WEBGL_VERSION\")));\nENV5.registerFlag(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\", () => {\n  const webGLVersion = ENV5.getNumber(\"WEBGL_VERSION\");\n  if (webGLVersion === 0) {\n    return 0;\n  }\n  return getWebGLDisjointQueryTimerVersion(webGLVersion);\n});\nENV5.registerFlag(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\", () => ENV5.getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\") > 0 && !device_util_exports.isMobile());\nENV5.registerFlag(\"WEBGL_RENDER_FLOAT32_CAPABLE\", () => isCapableOfRenderingToFloatTexture(ENV5.getNumber(\"WEBGL_VERSION\")));\nENV5.registerFlag(\"WEBGL_RENDER_FLOAT32_ENABLED\", () => {\n  return ENV5.getBool(\"WEBGL_FORCE_F16_TEXTURES\") ? false : ENV5.getBool(\"WEBGL_RENDER_FLOAT32_CAPABLE\");\n});\nENV5.registerFlag(\"WEBGL_DOWNLOAD_FLOAT_ENABLED\", () => isDownloadFloatTextureEnabled(ENV5.getNumber(\"WEBGL_VERSION\")));\nENV5.registerFlag(\"WEBGL_FENCE_API_ENABLED\", () => isWebGLFenceEnabled(ENV5.getNumber(\"WEBGL_VERSION\")));\nENV5.registerFlag(\"WEBGL_SIZE_UPLOAD_UNIFORM\", () => {\n  const useUniforms = ENV5.getBool(\"WEBGL_RENDER_FLOAT32_ENABLED\");\n  return useUniforms ? 4 : 0;\n});\nENV5.registerFlag(\"WEBGL_DELETE_TEXTURE_THRESHOLD\", () => {\n  return -1;\n}, (threshold3) => {\n  if (threshold3 < 0 && threshold3 !== -1) {\n    throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${threshold3}.`);\n  }\n});\nENV5.registerFlag(\"WEBGL_FLUSH_THRESHOLD\", () => {\n  return device_util_exports.isMobile() ? 1 : -1;\n}, (threshold3) => {\n  if (threshold3 < 0 && threshold3 !== -1) {\n    throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${threshold3}.`);\n  }\n});\nENV5.registerFlag(\"CPU_HANDOFF_SIZE_THRESHOLD\", () => 128);\nENV5.registerFlag(\"WEBGL_USE_SHAPES_UNIFORMS\", () => false);\nENV5.registerFlag(\"TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD\", () => 1e5);\nENV5.registerFlag(\"TOPK_K_CPU_HANDOFF_THRESHOLD\", () => 128);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/glsl_version.js\nfunction getGlslDifferences() {\n  let version9;\n  let attribute;\n  let varyingVs;\n  let varyingFs;\n  let texture2D;\n  let output;\n  let defineOutput;\n  let defineSpecialNaN;\n  let defineSpecialInf;\n  let defineRound;\n  if (env().getNumber(\"WEBGL_VERSION\") === 2) {\n    version9 = \"#version 300 es\";\n    attribute = \"in\";\n    varyingVs = \"out\";\n    varyingFs = \"in\";\n    texture2D = \"texture\";\n    output = \"outputColor\";\n    defineOutput = \"out vec4 outputColor;\";\n    defineSpecialNaN = `\n      bool isnan_custom(float val) {\n        uint floatToUint = floatBitsToUint(val);\n        return (floatToUint & 0x7fffffffu) > 0x7f800000u;\n      }\n\n      bvec4 isnan_custom(vec4 val) {\n        return bvec4(isnan_custom(val.x),\n          isnan_custom(val.y), isnan_custom(val.z), isnan_custom(val.w));\n      }\n\n      #define isnan(value) isnan_custom(value)\n    `;\n    defineSpecialInf = ``;\n    defineRound = `\n      #define round(value) newRound(value)\n      int newRound(float value) {\n        return int(floor(value + 0.5));\n      }\n\n      ivec4 newRound(vec4 value) {\n        return ivec4(floor(value + vec4(0.5)));\n      }\n    `;\n  } else {\n    version9 = \"\";\n    attribute = \"attribute\";\n    varyingVs = \"varying\";\n    varyingFs = \"varying\";\n    texture2D = \"texture2D\";\n    output = \"gl_FragColor\";\n    defineOutput = \"\";\n    defineSpecialNaN = `\n      #define isnan(value) isnan_custom(value)\n      bool isnan_custom(float val) {\n        return (val > 0. || val < 1. || val == 0.) ? false : true;\n      }\n      bvec4 isnan_custom(vec4 val) {\n        return bvec4(isnan(val.x), isnan(val.y), isnan(val.z), isnan(val.w));\n      }\n    `;\n    defineSpecialInf = `\n      uniform float INFINITY;\n\n      bool isinf(float val) {\n        return abs(val) == INFINITY;\n      }\n      bvec4 isinf(vec4 val) {\n        return equal(abs(val), vec4(INFINITY));\n      }\n    `;\n    defineRound = `\n      int round(float value) {\n        return int(floor(value + 0.5));\n      }\n\n      ivec4 round(vec4 value) {\n        return ivec4(floor(value + vec4(0.5)));\n      }\n    `;\n  }\n  return {\n    version: version9,\n    attribute,\n    varyingVs,\n    varyingFs,\n    texture2D,\n    output,\n    defineOutput,\n    defineSpecialNaN,\n    defineSpecialInf,\n    defineRound\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/shader_compiler_util.js\nfunction getLogicalCoordinatesFromFlatIndex(coords3, shape, index = \"index\") {\n  const strides = util_exports.computeStrides(shape);\n  return strides.map((stride, i2) => {\n    const line1 = `int ${coords3[i2]} = ${index} / ${stride}`;\n    const line2 = i2 === strides.length - 1 ? `int ${coords3[i2 + 1]} = ${index} - ${coords3[i2]} * ${stride}` : `index -= ${coords3[i2]} * ${stride}`;\n    return `${line1}; ${line2};`;\n  }).join(\"\");\n}\nfunction getOutputLogicalCoordinatesFromFlatIndexByUniform(coords3, shape, index = \"index\") {\n  const strides = util_exports.computeStrides(shape);\n  return strides.map((_, i2) => {\n    const line1 = `int ${coords3[i2]} = ${index} / outShapeStrides[${i2}]`;\n    const line2 = i2 === strides.length - 1 ? `int ${coords3[i2 + 1]} = ${index} - ${coords3[i2]} * outShapeStrides[${i2}]` : `index -= ${coords3[i2]} * outShapeStrides[${i2}]`;\n    return `${line1}; ${line2};`;\n  }).join(\"\");\n}\nfunction symbolicallyComputeStrides(indicesArr, variableName) {\n  const numCoords = indicesArr.length;\n  const shape = indicesArr.map((d) => `${variableName}[${d}]`);\n  const strides = new Array(numCoords - 1);\n  strides[numCoords - 2] = shape[numCoords - 1];\n  for (let i2 = numCoords - 3; i2 >= 0; --i2) {\n    strides[i2] = `(${strides[i2 + 1]} * ${shape[i2 + 1]})`;\n  }\n  return strides;\n}\nfunction getLogicalCoordinatesFromFlatIndexByUniform(coords3, variableName, index = \"index\") {\n  const indicesArray = coords3.map((_, i2) => i2);\n  const strides = symbolicallyComputeStrides(indicesArray, variableName);\n  return strides.map((_, i2) => {\n    const line1 = `int ${coords3[i2]} = ${index} / ${strides[i2]}`;\n    const line2 = i2 === strides.length - 1 ? `int ${coords3[i2 + 1]} = ${index} - ${coords3[i2]} * ${strides[i2]}` : `index -= ${coords3[i2]} * ${strides[i2]}`;\n    return `${line1}; ${line2};`;\n  }).join(\"\");\n}\nfunction getFlatIndexFrom3D(shape) {\n  const strides = util_exports.computeStrides(shape).map((d) => d.toString());\n  return `\n  int getFlatIndex(ivec3 coords) {\n    return coords.x * ${strides[0]} + coords.y * ${strides[1]} + coords.z;\n  }\n`;\n}\nfunction getFlatIndexFrom3DOutput() {\n  return `\n  int getFlatIndex(ivec3 coords) {\n    return coords.x * outShapeStrides[0] + coords.y * outShapeStrides[1] + coords.z;\n  }\n`;\n}\nvar ENCODE_FLOAT_SNIPPET = `\n  const float FLOAT_MAX = 1.70141184e38;\n  const float FLOAT_MIN = 1.17549435e-38;\n\n  lowp vec4 encode_float(highp float v) {\n    if (isnan(v)) {\n      return vec4(255, 255, 255, 255);\n    }\n\n    highp float av = abs(v);\n\n    if(av < FLOAT_MIN) {\n      return vec4(0.0, 0.0, 0.0, 0.0);\n    } else if(v > FLOAT_MAX) {\n      return vec4(0.0, 0.0, 128.0, 127.0) / 255.0;\n    } else if(v < -FLOAT_MAX) {\n      return vec4(0.0, 0.0,  128.0, 255.0) / 255.0;\n    }\n\n    highp vec4 c = vec4(0,0,0,0);\n\n    highp float e = floor(log2(av));\n    highp float m = exp2(fract(log2(av))) - 1.0;\n\n    c[2] = floor(128.0 * m);\n    m -= c[2] / 128.0;\n    c[1] = floor(32768.0 * m);\n    m -= c[1] / 32768.0;\n    c[0] = floor(8388608.0 * m);\n\n    highp float ebias = e + 127.0;\n    c[3] = floor(ebias / 2.0);\n    ebias -= c[3] * 2.0;\n    c[2] += floor(ebias) * 128.0;\n\n    c[3] += 128.0 * step(0.0, -v);\n\n    return c / 255.0;\n  }\n`;\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/shader_compiler.js\nvar { getBroadcastDims: getBroadcastDims2 } = backend_util_exports;\nfunction makeShader(inputsInfo, outputShape, program) {\n  const prefixSnippets = [];\n  inputsInfo.forEach((x) => {\n    const size = util_exports.sizeFromShape(x.shapeInfo.logicalShape);\n    if (x.shapeInfo.isUniform) {\n      prefixSnippets.push(`uniform float ${x.name}${size > 1 ? `[${size}]` : \"\"};`);\n    } else {\n      prefixSnippets.push(`uniform sampler2D ${x.name};`);\n      prefixSnippets.push(`uniform int offset${x.name};`);\n    }\n    if (program.enableShapeUniforms) {\n      const { uniformShape } = getUniformInfoFromShape(program.packedInputs, x.shapeInfo.logicalShape, x.shapeInfo.texShape);\n      switch (uniformShape.length) {\n        case 1:\n          prefixSnippets.push(`uniform int ${x.name}Shape;`);\n          break;\n        case 2:\n          prefixSnippets.push(`uniform ivec2 ${x.name}Shape;`);\n          break;\n        case 3:\n          prefixSnippets.push(`uniform ivec3 ${x.name}Shape;`);\n          break;\n        case 4:\n          prefixSnippets.push(`uniform ivec4 ${x.name}Shape;`);\n          break;\n        default:\n          break;\n      }\n      prefixSnippets.push(`uniform ivec2 ${x.name}TexShape;`);\n    }\n  });\n  if (program.enableShapeUniforms) {\n    switch (outputShape.logicalShape.length) {\n      case 1:\n        prefixSnippets.push(`uniform int outShape;`);\n        break;\n      case 2:\n        prefixSnippets.push(`uniform ivec2 outShape;`);\n        prefixSnippets.push(`uniform int outShapeStrides;`);\n        break;\n      case 3:\n        prefixSnippets.push(`uniform ivec3 outShape;`);\n        prefixSnippets.push(`uniform ivec2 outShapeStrides;`);\n        break;\n      case 4:\n        prefixSnippets.push(`uniform ivec4 outShape;`);\n        prefixSnippets.push(`uniform ivec3 outShapeStrides;`);\n        break;\n      default:\n        break;\n    }\n    prefixSnippets.push(`uniform ivec2 outTexShape;`);\n  }\n  if (program.customUniforms) {\n    program.customUniforms.forEach((d) => {\n      prefixSnippets.push(`uniform ${d.type} ${d.name}${d.arrayIndex ? `[${d.arrayIndex}]` : \"\"};`);\n    });\n  }\n  const inputPrefixSnippet = prefixSnippets.join(\"\\n\");\n  const inputSamplingSnippet = inputsInfo.map((x) => getInputSamplingSnippet(x, outputShape, program.packedInputs, program.enableShapeUniforms)).join(\"\\n\");\n  const outTexShape = outputShape.texShape;\n  const glsl = getGlslDifferences();\n  const floatTextureSampleSnippet = getFloatTextureSampleSnippet(glsl);\n  let outputSamplingSnippet;\n  let floatTextureSetOutputSnippet;\n  let shaderPrefix = getShaderPrefix(glsl);\n  if (outputShape.isPacked) {\n    outputSamplingSnippet = getPackedOutputSamplingSnippet(outputShape.logicalShape, outTexShape, program.enableShapeUniforms);\n    floatTextureSetOutputSnippet = getFloatTextureSetRGBASnippet(glsl);\n  } else {\n    outputSamplingSnippet = getOutputSamplingSnippet(outputShape.logicalShape, outTexShape, program.enableShapeUniforms);\n    floatTextureSetOutputSnippet = getFloatTextureSetRSnippet(glsl);\n  }\n  if (program.packedInputs) {\n    shaderPrefix += SHADER_PACKED_PREFIX;\n  }\n  const source = [\n    shaderPrefix,\n    floatTextureSampleSnippet,\n    floatTextureSetOutputSnippet,\n    inputPrefixSnippet,\n    outputSamplingSnippet,\n    inputSamplingSnippet,\n    program.userCode\n  ].join(\"\\n\");\n  return source;\n}\nfunction getSamplerFromInInfo(inInfo, enableShapeUniforms = false) {\n  const shape = inInfo.shapeInfo.logicalShape;\n  switch (shape.length) {\n    case 0:\n      return getSamplerScalar(inInfo, enableShapeUniforms);\n    case 1:\n      return getSampler1D(inInfo, enableShapeUniforms);\n    case 2:\n      return getSampler2D(inInfo, enableShapeUniforms);\n    case 3:\n      return getSampler3D(inInfo, enableShapeUniforms);\n    case 4:\n      return getSampler4D(inInfo, enableShapeUniforms);\n    case 5:\n      return getSampler5D(inInfo);\n    case 6:\n      return getSampler6D(inInfo);\n    default:\n      throw new Error(`${shape.length}-D input sampling is not yet supported`);\n  }\n}\nfunction getPackedSamplerFromInInfo(inInfo, enableShapeUniforms) {\n  const shape = inInfo.shapeInfo.logicalShape;\n  switch (shape.length) {\n    case 0:\n      return getPackedSamplerScalar(inInfo);\n    case 1:\n      return getPackedSampler1D(inInfo, enableShapeUniforms);\n    case 2:\n      return getPackedSampler2D(inInfo, enableShapeUniforms);\n    case 3:\n      return getPackedSampler3D(inInfo, enableShapeUniforms);\n    default:\n      return getPackedSamplerND(inInfo, enableShapeUniforms);\n  }\n}\nfunction getInputSamplingSnippet(inInfo, outShapeInfo, usesPackedTextures = false, enableShapeUniforms) {\n  let res = \"\";\n  if (usesPackedTextures) {\n    res += getPackedSamplerFromInInfo(inInfo, enableShapeUniforms);\n  } else {\n    res += getSamplerFromInInfo(inInfo, enableShapeUniforms);\n  }\n  const inShape = inInfo.shapeInfo.logicalShape;\n  const outShape = outShapeInfo.logicalShape;\n  if (inShape.length <= outShape.length) {\n    if (usesPackedTextures) {\n      res += getPackedSamplerAtOutputCoords(inInfo, outShapeInfo);\n    } else {\n      res += getSamplerAtOutputCoords(inInfo, outShapeInfo);\n    }\n  }\n  return res;\n}\nfunction getPackedOutputSamplingSnippet(outShape, outTexShape, enableShapeUniforms) {\n  switch (outShape.length) {\n    case 0:\n      return getOutputScalarCoords();\n    case 1:\n      return getOutputPacked1DCoords(outShape, outTexShape, enableShapeUniforms);\n    case 2:\n      return getOutputPacked2DCoords(outShape, outTexShape, enableShapeUniforms);\n    case 3:\n      return getOutputPacked3DCoords(outShape, outTexShape, enableShapeUniforms);\n    default:\n      return getOutputPackedNDCoords(outShape, outTexShape, enableShapeUniforms);\n  }\n}\nfunction getOutputSamplingSnippet(outShape, outTexShape, enableShapeUniforms) {\n  switch (outShape.length) {\n    case 0:\n      return getOutputScalarCoords();\n    case 1:\n      return getOutput1DCoords(outShape, outTexShape, enableShapeUniforms);\n    case 2:\n      return getOutput2DCoords(outShape, outTexShape, enableShapeUniforms);\n    case 3:\n      return getOutput3DCoords(outShape, outTexShape, enableShapeUniforms);\n    case 4:\n      return getOutput4DCoords(outShape, outTexShape, enableShapeUniforms);\n    case 5:\n      return getOutput5DCoords(outShape, outTexShape);\n    case 6:\n      return getOutput6DCoords(outShape, outTexShape);\n    default:\n      throw new Error(`${outShape.length}-D output sampling is not yet supported`);\n  }\n}\nfunction getFloatTextureSampleSnippet(glsl) {\n  return `\n    float sampleTexture(sampler2D textureSampler, vec2 uv) {\n      return ${glsl.texture2D}(textureSampler, uv).r;\n    }\n  `;\n}\nfunction getFloatTextureSetRSnippet(glsl) {\n  return `\n    void setOutput(float val) {\n      ${glsl.output} = vec4(val, 0, 0, 0);\n    }\n  `;\n}\nfunction getFloatTextureSetRGBASnippet(glsl) {\n  return `\n    void setOutput(vec4 val) {\n      ${glsl.output} = val;\n    }\n  `;\n}\nfunction getShaderPrefix(glsl) {\n  const SHADER_PREFIX = `${glsl.version}\n    precision highp float;\n    precision highp int;\n    precision highp sampler2D;\n    ${glsl.varyingFs} vec2 resultUV;\n    ${glsl.defineOutput}\n    const vec2 halfCR = vec2(0.5, 0.5);\n\n    struct ivec5\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n    };\n\n    struct ivec6\n    {\n      int x;\n      int y;\n      int z;\n      int w;\n      int u;\n      int v;\n    };\n\n    uniform float NAN;\n    ${glsl.defineSpecialNaN}\n    ${glsl.defineSpecialInf}\n    ${glsl.defineRound}\n\n    int imod(int x, int y) {\n      return x - y * (x / y);\n    }\n\n    int idiv(int a, int b, float sign) {\n      int res = a / b;\n      int mod = imod(a, b);\n      if (sign < 0. && mod != 0) {\n        res -= 1;\n      }\n      return res;\n    }\n\n    //Based on the work of Dave Hoskins\n    //https://www.shadertoy.com/view/4djSRW\n    #define HASHSCALE1 443.8975\n    float random(float seed){\n      vec2 p = resultUV * seed;\n      vec3 p3  = fract(vec3(p.xyx) * HASHSCALE1);\n      p3 += dot(p3, p3.yzx + 19.19);\n      return fract((p3.x + p3.y) * p3.z);\n    }\n\n    ${SAMPLE_1D_SNIPPET}\n    ${SAMPLE_2D_SNIPPET}\n    ${SAMPLE_3D_SNIPPET}\n  `;\n  return SHADER_PREFIX;\n}\nvar SAMPLE_1D_SNIPPET = `\nvec2 uvFromFlat(int texNumR, int texNumC, int index) {\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\nvec2 packedUVfrom1D(int texNumR, int texNumC, int index) {\n  int texelIndex = index / 2;\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n`;\nvar SAMPLE_2D_SNIPPET = `\nvec2 packedUVfrom2D(int texelsInLogicalRow, int texNumR,\n  int texNumC, int row, int col) {\n  int texelIndex = (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = texelIndex / texNumC;\n  int texC = texelIndex - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n`;\nvar SAMPLE_3D_SNIPPET = `\nvec2 packedUVfrom3D(int texNumR, int texNumC,\n    int texelsInBatch, int texelsInLogicalRow, int b,\n    int row, int col) {\n  int index = b * texelsInBatch + (row / 2) * texelsInLogicalRow + (col / 2);\n  int texR = index / texNumC;\n  int texC = index - texR * texNumC;\n  return (vec2(texC, texR) + halfCR) / vec2(texNumC, texNumR);\n}\n`;\nvar SHADER_PACKED_PREFIX = `\n  float getChannel(vec4 frag, vec2 innerDims) {\n    vec2 modCoord = mod(innerDims, 2.);\n    return modCoord.x == 0. ?\n      (modCoord.y == 0. ? frag.r : frag.g) :\n      (modCoord.y == 0. ? frag.b : frag.a);\n  }\n  float getChannel(vec4 frag, int dim) {\n    float modCoord = mod(float(dim), 2.);\n    return modCoord == 0. ? frag.r : frag.g;\n  }\n`;\nfunction getOutputScalarCoords() {\n  return `\n    int getOutputCoords() {\n      return 0;\n    }\n  `;\n}\nfunction getOutputPacked1DCoords(shape, texShape, enableShapeUniforms) {\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  if (packedTexShape[0] === 1) {\n    if (enableShapeUniforms) {\n      return `\n      int getOutputCoords() {\n        return 2 * int(resultUV.x * ceil(float(outTexShape[1]) / 2.0));\n      }\n    `;\n    }\n    return `\n      int getOutputCoords() {\n        return 2 * int(resultUV.x * ${packedTexShape[1]}.0);\n      }\n    `;\n  }\n  if (packedTexShape[1] === 1) {\n    if (enableShapeUniforms) {\n      return `\n      int getOutputCoords() {\n        return 2 * int(resultUV.y * ceil(float(outTexShape[0]) / 2.0));\n      }\n    `;\n    }\n    return `\n      int getOutputCoords() {\n        return 2 * int(resultUV.y * ${packedTexShape[0]}.0);\n      }\n    `;\n  }\n  if (enableShapeUniforms) {\n    return `\n    int getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n      return 2 * (resTexRC.x * packedTexShape[1] + resTexRC.y);\n    }\n  `;\n  }\n  return `\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));\n      return 2 * (resTexRC.x * ${packedTexShape[1]} + resTexRC.y);\n    }\n  `;\n}\nfunction getOutput1DCoords(shape, texShape, enableShapeUniforms) {\n  if (texShape[0] === 1) {\n    if (enableShapeUniforms) {\n      return `\n      int getOutputCoords() {\n        return int(resultUV.x * float(outTexShape[1]));\n      }\n    `;\n    }\n    return `\n      int getOutputCoords() {\n        return int(resultUV.x * ${texShape[1]}.0);\n      }\n    `;\n  }\n  if (texShape[1] === 1) {\n    if (enableShapeUniforms) {\n      return `\n      int getOutputCoords() {\n        return int(resultUV.y * float(outTexShape[0]));\n      }\n    `;\n    }\n    return `\n      int getOutputCoords() {\n        return int(resultUV.y * ${texShape[0]}.0);\n      }\n    `;\n  }\n  if (enableShapeUniforms) {\n    return `\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(outTexShape[0], outTexShape[1]));\n      return resTexRC.x * outTexShape[1] + resTexRC.y;\n    }\n  `;\n  }\n  return `\n    int getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${texShape[0]}, ${texShape[1]}));\n      return resTexRC.x * ${texShape[1]} + resTexRC.y;\n    }\n  `;\n}\nfunction getOutputPacked3DCoords(shape, texShape, enableShapeUniforms) {\n  if (enableShapeUniforms) {\n    return `\n    ivec3 getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      int texelsInLogicalRow = int(ceil(float(outShape[2]) / 2.0));\n      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n\n      int b = index / texelsInBatch;\n      index -= b * texelsInBatch;\n\n      int r = 2 * (index / texelsInLogicalRow);\n      int c = imod(index, texelsInLogicalRow) * 2;\n\n      return ivec3(b, r, c);\n    }\n  `;\n  }\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  const texelsInLogicalRow = Math.ceil(shape[2] / 2);\n  const texelsInBatch = texelsInLogicalRow * Math.ceil(shape[1] / 2);\n  return `\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));\n      int index = resTexRC.x * ${packedTexShape[1]} + resTexRC.y;\n\n      int b = index / ${texelsInBatch};\n      index -= b * ${texelsInBatch};\n\n      int r = 2 * (index / ${texelsInLogicalRow});\n      int c = imod(index, ${texelsInLogicalRow}) * 2;\n\n      return ivec3(b, r, c);\n    }\n  `;\n}\nfunction getOutput3DCoords(shape, texShape, enableShapeUniforms) {\n  if (enableShapeUniforms) {\n    const coordsFromIndexSnippet2 = getOutputLogicalCoordinatesFromFlatIndexByUniform([\"r\", \"c\", \"d\"], shape);\n    return `\n  ivec3 getOutputCoords() {\n    ivec2 resTexRC = ivec2(resultUV.yx *\n                           vec2(outTexShape[0], outTexShape[1]));\n    int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n    ${coordsFromIndexSnippet2}\n    return ivec3(r, c, d);\n  }\n`;\n  }\n  const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex([\"r\", \"c\", \"d\"], shape);\n  return `\n    ivec3 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${texShape[0]}, ${texShape[1]}));\n      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;\n      ${coordsFromIndexSnippet}\n      return ivec3(r, c, d);\n    }\n  `;\n}\nfunction getOutputPackedNDCoords(shape, texShape, enableShapeUniforms) {\n  if (enableShapeUniforms) {\n    return `\n    ivec4 getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n\n      int texelsInLogicalRow = int(ceil(float(outShape[3]) / 2.0));\n      int texelsInBatch = texelsInLogicalRow * int(ceil(float(outShape[2]) / 2.0));\n      int texelsInBatchN = texelsInBatch * outShape[1];\n\n      int b2 = index / texelsInBatchN;\n      index -= b2 * texelsInBatchN;\n\n      int b = index / texelsInBatch;\n      index -= b * texelsInBatch;\n\n      int r = 2 * (index / texelsInLogicalRow);\n      int c = imod(index, texelsInLogicalRow) * 2;\n\n      return ivec4(b2, b, r, c);\n    }\n  `;\n  }\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  const texelsInLogicalRow = Math.ceil(shape[shape.length - 1] / 2);\n  const texelsInBatch = texelsInLogicalRow * Math.ceil(shape[shape.length - 2] / 2);\n  let texelsInBatchN = texelsInBatch;\n  let batches = ``;\n  let coords3 = \"b, r, c\";\n  for (let b = 2; b < shape.length - 1; b++) {\n    texelsInBatchN *= shape[shape.length - b - 1];\n    batches = `\n      int b${b} = index / ${texelsInBatchN};\n      index -= b${b} * ${texelsInBatchN};\n    ` + batches;\n    coords3 = `b${b}, ` + coords3;\n  }\n  return `\n    ivec${shape.length} getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));\n      int index = resTexRC.x * ${packedTexShape[1]} + resTexRC.y;\n\n      ${batches}\n\n      int b = index / ${texelsInBatch};\n      index -= b * ${texelsInBatch};\n\n      int r = 2 * (index / ${texelsInLogicalRow});\n      int c = imod(index, ${texelsInLogicalRow}) * 2;\n\n      return ivec${shape.length}(${coords3});\n    }\n  `;\n}\nfunction getOutput4DCoords(shape, texShape, enableShapeUniforms) {\n  if (enableShapeUniforms) {\n    const coordsFromIndexSnippet2 = getOutputLogicalCoordinatesFromFlatIndexByUniform([\"r\", \"c\", \"d\", \"d2\"], shape);\n    return `\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2(outTexShape[0], outTexShape[1]));\n      int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n      ${coordsFromIndexSnippet2}\n      return ivec4(r, c, d, d2);\n    }\n  `;\n  }\n  const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex([\"r\", \"c\", \"d\", \"d2\"], shape);\n  return `\n    ivec4 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2(${texShape[0]}, ${texShape[1]}));\n      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;\n      ${coordsFromIndexSnippet}\n      return ivec4(r, c, d, d2);\n    }\n  `;\n}\nfunction getOutput5DCoords(shape, texShape) {\n  const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex([\"r\", \"c\", \"d\", \"d2\", \"d3\"], shape);\n  return `\n    ivec5 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx * vec2(${texShape[0]},\n                             ${texShape[1]}));\n\n      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;\n\n      ${coordsFromIndexSnippet}\n\n      ivec5 outShape = ivec5(r, c, d, d2, d3);\n      return outShape;\n    }\n  `;\n}\nfunction getOutput6DCoords(shape, texShape) {\n  const coordsFromIndexSnippet = getLogicalCoordinatesFromFlatIndex([\"r\", \"c\", \"d\", \"d2\", \"d3\", \"d4\"], shape);\n  return `\n    ivec6 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n        vec2(${texShape[0]}, ${texShape[1]}));\n      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;\n\n      ${coordsFromIndexSnippet}\n\n      ivec6 result = ivec6(r, c, d, d2, d3, d4);\n      return result;\n    }\n  `;\n}\nfunction getOutputPacked2DCoords(shape, texShape, enableShapeUniforms) {\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  if (util_exports.arraysEqual(shape, texShape)) {\n    if (enableShapeUniforms) {\n      return `\n      ivec2 getOutputCoords() {\n        ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n        return 2 * ivec2(resultUV.yx * vec2(packedTexShape[0], packedTexShape[1]));\n      }\n    `;\n    }\n    return `\n      ivec2 getOutputCoords() {\n        return 2 * ivec2(resultUV.yx * vec2(${packedTexShape[0]}, ${packedTexShape[1]}));\n      }\n    `;\n  }\n  const texelsInLogicalRow = Math.ceil(shape[1] / 2);\n  if (enableShapeUniforms) {\n    return `\n    ivec2 getOutputCoords() {\n      ivec2 packedTexShape = ivec2(ceil(float(outTexShape[0]) / 2.0), ceil(float(outTexShape[1]) / 2.0));\n      int texelsInLogicalRow = int(ceil(float(outShape[1]) / 2.0));\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(packedTexShape[0], packedTexShape[1]));\n\n      int index = resTexRC.x * packedTexShape[1] + resTexRC.y;\n      int r = 2 * (index / texelsInLogicalRow);\n      int c = imod(index, texelsInLogicalRow) * 2;\n\n      return ivec2(r, c);\n    }\n  `;\n  }\n  return `\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${packedTexShape[0]}, ${packedTexShape[1]}));\n\n      int index = resTexRC.x * ${packedTexShape[1]} + resTexRC.y;\n      int r = 2 * (index / ${texelsInLogicalRow});\n      int c = imod(index, ${texelsInLogicalRow}) * 2;\n\n      return ivec2(r, c);\n    }\n  `;\n}\nfunction getOutput2DCoords(shape, texShape, enableShapeUniforms) {\n  if (util_exports.arraysEqual(shape, texShape)) {\n    if (enableShapeUniforms) {\n      return `\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2(outTexShape[0], outTexShape[1]));\n      }\n    `;\n    }\n    return `\n      ivec2 getOutputCoords() {\n        return ivec2(resultUV.yx * vec2(${texShape[0]}, ${texShape[1]}));\n      }\n    `;\n  }\n  if (shape[1] === 1) {\n    if (enableShapeUniforms) {\n      return `\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(outTexShape[0], outTexShape[1]));\n        int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    `;\n    }\n    return `\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(${texShape[0]}, ${texShape[1]}));\n        int index = resTexRC.x * ${texShape[1]} + resTexRC.y;\n        return ivec2(index, 0);\n      }\n    `;\n  }\n  if (shape[0] === 1) {\n    if (enableShapeUniforms) {\n      return `\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(outTexShape[0], outTexShape[1]));\n        int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n        return ivec2(0, index);\n      }\n    `;\n    }\n    return `\n      ivec2 getOutputCoords() {\n        ivec2 resTexRC = ivec2(resultUV.yx *\n                               vec2(${texShape[0]}, ${texShape[1]}));\n        int index = resTexRC.x * ${texShape[1]} + resTexRC.y;\n        return ivec2(0, index);\n      }\n    `;\n  }\n  if (enableShapeUniforms) {\n    return `\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(outTexShape[0], outTexShape[1]));\n      int index = resTexRC.x * outTexShape[1] + resTexRC.y;\n      int r = index / outShape[1];\n      int c = index - r * outShape[1];\n      return ivec2(r, c);\n    }\n  `;\n  }\n  return `\n    ivec2 getOutputCoords() {\n      ivec2 resTexRC = ivec2(resultUV.yx *\n                             vec2(${texShape[0]}, ${texShape[1]}));\n      int index = resTexRC.x * ${texShape[1]} + resTexRC.y;\n      int r = index / ${shape[1]};\n      int c = index - r * ${shape[1]};\n      return ivec2(r, c);\n    }\n  `;\n}\nfunction getFlatOffsetUniformName(texName) {\n  return `offset${texName}`;\n}\nfunction getPackedSamplerScalar(inputInfo) {\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const glsl = getGlslDifferences();\n  return `\n    vec4 ${funcName}() {\n      return ${glsl.texture2D}(${texName}, halfCR);\n    }\n  `;\n}\nfunction getSamplerScalar(inputInfo, enableShapeUniforms) {\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  if (inputInfo.shapeInfo.isUniform) {\n    return `float ${funcName}() {return ${texName};}`;\n  }\n  const [texNumR, texNumC] = inputInfo.shapeInfo.texShape;\n  if (texNumR === 1 && texNumC === 1) {\n    return `\n      float ${funcName}() {\n        return sampleTexture(${texName}, halfCR);\n      }\n    `;\n  }\n  const offset = getFlatOffsetUniformName(texName);\n  if (enableShapeUniforms) {\n    return `\n    float ${funcName}() {\n      vec2 uv = uvFromFlat(${texName}TexShape[0], ${texName}TexShape[1], ${offset});\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n  }\n  const [tNumR, tNumC] = inputInfo.shapeInfo.texShape;\n  return `\n    float ${funcName}() {\n      vec2 uv = uvFromFlat(${tNumR}, ${tNumC}, ${offset});\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n}\nfunction getPackedSampler1D(inputInfo, enableShapeUniforms) {\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const texShape = inputInfo.shapeInfo.texShape;\n  const glsl = getGlslDifferences();\n  if (enableShapeUniforms) {\n    return `\n    vec4 ${funcName}(int index) {\n      ivec2 packedTexShape = ivec2(ceil(float(${texName}TexShape[0]) / 2.0), ceil(float(${texName}TexShape[1]) / 2.0));\n      vec2 uv = packedUVfrom1D(\n        packedTexShape[0], packedTexShape[1], index);\n      return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n  }\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  return `\n    vec4 ${funcName}(int index) {\n      vec2 uv = packedUVfrom1D(\n        ${packedTexShape[0]}, ${packedTexShape[1]}, index);\n      return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n}\nfunction getSampler1D(inputInfo, enableShapeUniforms) {\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  if (inputInfo.shapeInfo.isUniform) {\n    return `\n      float ${funcName}(int index) {\n        ${getUniformSampler(inputInfo)}\n      }\n    `;\n  }\n  const texShape = inputInfo.shapeInfo.texShape;\n  const tNumR = texShape[0];\n  const tNumC = texShape[1];\n  if (tNumC === 1 && tNumR === 1) {\n    return `\n      float ${funcName}(int index) {\n        return sampleTexture(${texName}, halfCR);\n      }\n    `;\n  }\n  const offset = getFlatOffsetUniformName(texName);\n  if (tNumC === 1) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int index) {\n        vec2 uv = vec2(0.5, (float(index + ${offset}) + 0.5) / float(${texName}TexShape[0]));\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n      float ${funcName}(int index) {\n        vec2 uv = vec2(0.5, (float(index + ${offset}) + 0.5) / ${tNumR}.0);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  if (tNumR === 1) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int index) {\n        vec2 uv = vec2((float(index + ${offset}) + 0.5) / float(${texName}TexShape[1]), 0.5);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n      float ${funcName}(int index) {\n        vec2 uv = vec2((float(index + ${offset}) + 0.5) / ${tNumC}.0, 0.5);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  if (enableShapeUniforms) {\n    return `\n    float ${funcName}(int index) {\n      vec2 uv = uvFromFlat(${texName}TexShape[0], ${texName}TexShape[1], index + ${offset});\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n  }\n  return `\n    float ${funcName}(int index) {\n      vec2 uv = uvFromFlat(${tNumR}, ${tNumC}, index + ${offset});\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n}\nfunction getPackedSampler2D(inputInfo, enableShapeUniforms) {\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const texShape = inputInfo.shapeInfo.texShape;\n  const texNumR = texShape[0];\n  const texNumC = texShape[1];\n  const glsl = getGlslDifferences();\n  if (texShape != null && util_exports.arraysEqual(shape, texShape)) {\n    if (enableShapeUniforms) {\n      return `\n      vec4 ${funcName}(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(${texName}TexShape[1], ${texName}TexShape[0]);\n\n        return ${glsl.texture2D}(${texName}, uv);\n      }\n    `;\n    }\n    return `\n      vec4 ${funcName}(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(${texNumC}.0, ${texNumR}.0);\n\n        return ${glsl.texture2D}(${texName}, uv);\n      }\n    `;\n  }\n  if (enableShapeUniforms) {\n    return `\n    vec4 ${funcName}(int row, int col) {\n      ivec2 packedTexShape = ivec2(ceil(float(${texName}TexShape[0]) / 2.0), ceil(float(${texName}TexShape[1]) / 2.0));\n      int valuesPerRow = int(ceil(float(${texName}Shape[1]) / 2.0));\n      vec2 uv = packedUVfrom2D(valuesPerRow, packedTexShape[0], packedTexShape[1], row, col);\n      return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n  }\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  const valuesPerRow = Math.ceil(shape[1] / 2);\n  return `\n    vec4 ${funcName}(int row, int col) {\n      vec2 uv = packedUVfrom2D(${valuesPerRow}, ${packedTexShape[0]}, ${packedTexShape[1]}, row, col);\n      return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n}\nfunction getSampler2D(inputInfo, enableShapeUniforms) {\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const texShape = inputInfo.shapeInfo.texShape;\n  if (texShape != null && util_exports.arraysEqual(shape, texShape)) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int row, int col) {\n        vec2 uv = (vec2(col, row) + halfCR) / vec2(${texName}TexShape[1], ${texName}TexShape[0]);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    const texNumR2 = texShape[0];\n    const texNumC2 = texShape[1];\n    return `\n    float ${funcName}(int row, int col) {\n      vec2 uv = (vec2(col, row) + halfCR) / vec2(${texNumC2}.0, ${texNumR2}.0);\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n  }\n  const { newShape, keptDims } = util_exports.squeezeShape(shape);\n  const squeezedShape = newShape;\n  if (squeezedShape.length < shape.length) {\n    const newInputInfo = squeezeInputInfo(inputInfo, squeezedShape);\n    const params = [\"row\", \"col\"];\n    return `\n      ${getSamplerFromInInfo(newInputInfo, enableShapeUniforms)}\n      float ${funcName}(int row, int col) {\n        return ${funcName}(${getSqueezedParams(params, keptDims)});\n      }\n    `;\n  }\n  if (inputInfo.shapeInfo.isUniform) {\n    return `\n      float ${funcName}(int row, int col) {\n        int index = round(dot(vec2(row, col), vec2(${shape[1]}, 1)));\n        ${getUniformSampler(inputInfo)}\n      }\n    `;\n  }\n  const texNumR = texShape[0];\n  const texNumC = texShape[1];\n  const offset = getFlatOffsetUniformName(texName);\n  if (texNumC === 1) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int row, int col) {\n        float index = dot(vec3(row, col, ${offset}), vec3(${texName}Shape[1], 1, 1));\n        vec2 uv = vec2(0.5, (index + 0.5) / float(${texName}TexShape[0]));\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n    float ${funcName}(int row, int col) {\n      float index = dot(vec3(row, col, ${offset}), vec3(${shape[1]}, 1, 1));\n      vec2 uv = vec2(0.5, (index + 0.5) / ${texNumR}.0);\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n  }\n  if (texNumR === 1) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int row, int col) {\n        float index = dot(vec3(row, col, ${offset}), vec3(${texName}Shape[1], 1, 1));\n        vec2 uv = vec2((index + 0.5) / float(${texName}TexShape[1]), 0.5);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n    float ${funcName}(int row, int col) {\n      float index = dot(vec3(row, col, ${offset}), vec3(${shape[1]}, 1, 1));\n      vec2 uv = vec2((index + 0.5) / ${texNumC}.0, 0.5);\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n  }\n  if (enableShapeUniforms) {\n    return `\n      float ${funcName}(int row, int col) {\n        // Explicitly use integer operations as dot() only works on floats.\n        int index = row * ${texName}Shape[1] + col + ${offset};\n        vec2 uv = uvFromFlat(${texName}TexShape[0], ${texName}TexShape[1], index);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  return `\n  float ${funcName}(int row, int col) {\n    // Explicitly use integer operations as dot() only works on floats.\n    int index = row * ${shape[1]} + col + ${offset};\n    vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);\n    return sampleTexture(${texName}, uv);\n  }\n`;\n}\nfunction getPackedSampler3D(inputInfo, enableShapeUniforms) {\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const texShape = inputInfo.shapeInfo.texShape;\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  if (shape[0] === 1) {\n    const squeezedShape = shape.slice(1);\n    const keptDims = [1, 2];\n    const newInputInfo = squeezeInputInfo(inputInfo, squeezedShape);\n    const params = [\"b\", \"row\", \"col\"];\n    return `\n        ${getPackedSamplerFromInInfo(newInputInfo, enableShapeUniforms)}\n        vec4 ${funcName}(int b, int row, int col) {\n          return ${funcName}(${getSqueezedParams(params, keptDims)});\n        }\n      `;\n  }\n  const glsl = getGlslDifferences();\n  if (enableShapeUniforms) {\n    return `\n    vec4 ${funcName}(int b, int row, int col) {\n      ivec2 packedTexShape = ivec2(ceil(float(${texName}TexShape[0]) / 2.0), ceil(float(${texName}TexShape[1]) / 2.0));\n      int valuesPerRow = int(ceil(float(${texName}Shape[2]) / 2.0));\n      int texelsInBatch = valuesPerRow * int(ceil(float(${texName}Shape[1]) / 2.0));\n      vec2 uv = packedUVfrom3D(\n        packedTexShape[0], packedTexShape[1], texelsInBatch, valuesPerRow, b, row, col);\n      return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n  }\n  const texNumR = packedTexShape[0];\n  const texNumC = packedTexShape[1];\n  const valuesPerRow = Math.ceil(shape[2] / 2);\n  const texelsInBatch = valuesPerRow * Math.ceil(shape[1] / 2);\n  return `\n    vec4 ${funcName}(int b, int row, int col) {\n      vec2 uv = packedUVfrom3D(\n        ${texNumR}, ${texNumC}, ${texelsInBatch}, ${valuesPerRow}, b, row, col);\n      return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n}\nfunction getSampler3D(inputInfo, enableShapeUniforms) {\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const stride0 = shape[1] * shape[2];\n  const stride1 = shape[2];\n  const { newShape, keptDims } = util_exports.squeezeShape(shape);\n  const squeezedShape = newShape;\n  if (squeezedShape.length < shape.length) {\n    const newInputInfo = squeezeInputInfo(inputInfo, squeezedShape);\n    const params = [\"row\", \"col\", \"depth\"];\n    return `\n        ${getSamplerFromInInfo(newInputInfo, enableShapeUniforms)}\n        float ${funcName}(int row, int col, int depth) {\n          return ${funcName}(${getSqueezedParams(params, keptDims)});\n        }\n      `;\n  }\n  if (inputInfo.shapeInfo.isUniform) {\n    return `\n      float ${funcName}(int row, int col, int depth) {\n        int index = round(dot(vec3(row, col, depth),\n                          vec3(${stride0}, ${stride1}, 1)));\n        ${getUniformSampler(inputInfo)}\n      }\n    `;\n  }\n  const texShape = inputInfo.shapeInfo.texShape;\n  const texNumR = texShape[0];\n  const texNumC = texShape[1];\n  const flatOffset = inputInfo.shapeInfo.flatOffset;\n  if (texNumC === stride0 && flatOffset == null) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int row, int col, int depth) {\n        int stride1 = ${texName}Shape[2];\n        float texR = float(row);\n        float texC = dot(vec2(col, depth), vec2(stride1, 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${texName}TexShape[1], ${texName}TexShape[0]);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n        float ${funcName}(int row, int col, int depth) {\n          float texR = float(row);\n          float texC = dot(vec2(col, depth), vec2(${stride1}, 1));\n          vec2 uv = (vec2(texC, texR) + halfCR) /\n                     vec2(${texNumC}.0, ${texNumR}.0);\n          return sampleTexture(${texName}, uv);\n        }\n      `;\n  }\n  if (texNumC === stride1 && flatOffset == null) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int row, int col, int depth) {\n        float texR = dot(vec2(row, col), vec2(${texName}Shape[1], 1));\n        float texC = float(depth);\n        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${texName}TexShape[1], ${texName}TexShape[0]);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n    float ${funcName}(int row, int col, int depth) {\n      float texR = dot(vec2(row, col), vec2(${shape[1]}, 1));\n      float texC = float(depth);\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${texNumC}.0, ${texNumR}.0);\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n  }\n  const offset = getFlatOffsetUniformName(texName);\n  if (enableShapeUniforms) {\n    return `\n    float ${funcName}(int row, int col, int depth) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int stride0 = ${texName}Shape[1] * ${texName}Shape[2];\n      int stride1 = ${texName}Shape[2];\n      int index = row * ${stride0} + col * ${stride1} + depth + ${offset};\n      vec2 uv = uvFromFlat(${texName}TexShape[0], ${texName}TexShape[1], index);\n      return sampleTexture(${texName}, uv);\n    }\n    `;\n  }\n  return `\n      float ${funcName}(int row, int col, int depth) {\n        // Explicitly use integer operations as dot() only works on floats.\n        int index = row * ${stride0} + col * ${stride1} + depth + ${offset};\n        vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);\n        return sampleTexture(${texName}, uv);\n      }\n  `;\n}\nfunction getPackedSamplerND(inputInfo, enableShapeUniforms) {\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const glsl = getGlslDifferences();\n  if (enableShapeUniforms) {\n    return `\n    vec4 ${funcName}(int b2, int b, int row, int col) {\n      int valuesPerRow = int(ceil(float(${texName}Shape[3]) / 2.0));\n      int texelsInBatch = valuesPerRow * int(ceil(float(${texName}Shape[2]) / 2.0));\n      int index = b * texelsInBatch + (row / 2) * valuesPerRow + (col / 2);\n      texelsInBatch *= ${texName}Shape[1];\n      index = b2 * texelsInBatch + index;\n      ivec2 packedTexShape = ivec2(ceil(float(${texName}TexShape[0]) / 2.0), ceil(float(${texName}TexShape[1]) / 2.0));\n      int texR = index / packedTexShape[1];\n      int texC = index - texR * packedTexShape[1];\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(packedTexShape[1], packedTexShape[0]); return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n  }\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const rank = shape.length;\n  const texShape = inputInfo.shapeInfo.texShape;\n  const packedTexShape = [Math.ceil(texShape[0] / 2), Math.ceil(texShape[1] / 2)];\n  const texNumR = packedTexShape[0];\n  const texNumC = packedTexShape[1];\n  const valuesPerRow = Math.ceil(shape[rank - 1] / 2);\n  let texelsInBatch = valuesPerRow * Math.ceil(shape[rank - 2] / 2);\n  let params = `int b, int row, int col`;\n  let index = `b * ${texelsInBatch} + (row / 2) * ${valuesPerRow} + (col / 2)`;\n  for (let b = 2; b < rank - 1; b++) {\n    params = `int b${b}, ` + params;\n    texelsInBatch *= shape[rank - b - 1];\n    index = `b${b} * ${texelsInBatch} + ` + index;\n  }\n  return `\n    vec4 ${funcName}(${params}) {\n      int index = ${index};\n      int texR = index / ${texNumC};\n      int texC = index - texR * ${texNumC};\n      vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${texNumC}, ${texNumR});\n      return ${glsl.texture2D}(${texName}, uv);\n    }\n  `;\n}\nfunction getSampler4D(inputInfo, enableShapeUniforms) {\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const stride2 = shape[3];\n  const stride1 = shape[2] * stride2;\n  const stride0 = shape[1] * stride1;\n  const { newShape, keptDims } = util_exports.squeezeShape(shape);\n  if (newShape.length < shape.length) {\n    const newInputInfo = squeezeInputInfo(inputInfo, newShape);\n    const params = [\"row\", \"col\", \"depth\", \"depth2\"];\n    return `\n      ${getSamplerFromInInfo(newInputInfo, enableShapeUniforms)}\n      float ${funcName}(int row, int col, int depth, int depth2) {\n        return ${funcName}(${getSqueezedParams(params, keptDims)});\n      }\n    `;\n  }\n  if (inputInfo.shapeInfo.isUniform) {\n    return `\n      float ${funcName}(int row, int col, int depth, int depth2) {\n        int index = round(dot(vec4(row, col, depth, depth2),\n                          vec4(${stride0}, ${stride1}, ${stride2}, 1)));\n        ${getUniformSampler(inputInfo)}\n      }\n    `;\n  }\n  const flatOffset = inputInfo.shapeInfo.flatOffset;\n  const texShape = inputInfo.shapeInfo.texShape;\n  const texNumR = texShape[0];\n  const texNumC = texShape[1];\n  const stride2Str = `int stride2 = ${texName}Shape[3];`;\n  const stride1Str = `int stride1 = ${texName}Shape[2] * stride2;`;\n  const stride0Str = `int stride0 = ${texName}Shape[1] * stride1;`;\n  if (texNumC === stride0 && flatOffset == null) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int row, int col, int depth, int depth2) {\n        ${stride2Str}\n        ${stride1Str}\n        float texR = float(row);\n        float texC =\n            dot(vec3(col, depth, depth2),\n                vec3(stride1, stride2, 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${texName}TexShape[1], ${texName}TexShape[0]);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n      float ${funcName}(int row, int col, int depth, int depth2) {\n        float texR = float(row);\n        float texC =\n            dot(vec3(col, depth, depth2),\n                vec3(${stride1}, ${stride2}, 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${texNumC}.0, ${texNumR}.0);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  if (texNumC === stride2 && flatOffset == null) {\n    if (enableShapeUniforms) {\n      return `\n      float ${funcName}(int row, int col, int depth, int depth2) {\n        float texR = dot(vec3(row, col, depth),\n                         vec3(${texName}Shape[1] * ${texName}Shape[2], ${texName}Shape[2], 1));\n        float texC = float(depth2);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(${texName}TexShape[1], ${texName}TexShape[0]);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n    }\n    return `\n      float ${funcName}(int row, int col, int depth, int depth2) {\n        float texR = dot(vec3(row, col, depth),\n                         vec3(${shape[1] * shape[2]}, ${shape[2]}, 1));\n        float texC = float(depth2);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(${texNumC}.0, ${texNumR}.0);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  const offset = getFlatOffsetUniformName(texName);\n  if (enableShapeUniforms) {\n    return `\n    float ${funcName}(int row, int col, int depth, int depth2) {\n      // Explicitly use integer operations as dot() only works on floats.\n      ${stride2Str}\n      ${stride1Str}\n      ${stride0Str}\n      int index = row * stride0 + col * stride1 +\n          depth * stride2 + depth2;\n      vec2 uv = uvFromFlat(${texName}TexShape[0], ${texName}TexShape[1], index + ${offset});\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n  }\n  return `\n    float ${funcName}(int row, int col, int depth, int depth2) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * ${stride0} + col * ${stride1} +\n          depth * ${stride2} + depth2;\n      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index + ${offset});\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n}\nfunction getSampler5D(inputInfo) {\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const stride3 = shape[4];\n  const stride2 = shape[3] * stride3;\n  const stride1 = shape[2] * stride2;\n  const stride0 = shape[1] * stride1;\n  const { newShape, keptDims } = util_exports.squeezeShape(shape);\n  if (newShape.length < shape.length) {\n    const newInputInfo = squeezeInputInfo(inputInfo, newShape);\n    const params = [\"row\", \"col\", \"depth\", \"depth2\", \"depth3\"];\n    return `\n      ${getSamplerFromInInfo(newInputInfo)}\n      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {\n        return ${funcName}(${getSqueezedParams(params, keptDims)});\n      }\n    `;\n  }\n  if (inputInfo.shapeInfo.isUniform) {\n    return `\n      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {\n        float index = dot(\n          vec4(row, col, depth, depth2),\n          vec4(${stride0}, ${stride1}, ${stride2}, ${stride3})) +\n          depth3;\n        ${getUniformSampler(inputInfo)}\n      }\n    `;\n  }\n  const flatOffset = inputInfo.shapeInfo.flatOffset;\n  const texShape = inputInfo.shapeInfo.texShape;\n  const texNumR = texShape[0];\n  const texNumC = texShape[1];\n  if (texNumC === stride0 && flatOffset == null) {\n    return `\n      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n                         vec4(${stride1}, ${stride2}, ${stride3}, 1));\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${texNumC}.0, ${texNumR}.0);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  if (texNumC === stride3 && flatOffset == null) {\n    return `\n      float ${funcName}(int row, int col, int depth, int depth2, int depth3) {\n        float texR = dot(\n          vec4(row, col, depth, depth2),\n          vec4(${shape[1] * shape[2] * shape[3]},\n               ${shape[2] * shape[3]}, ${shape[3]}, 1));\n        int texC = depth3;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(${texNumC}.0, ${texNumR}.0);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  const offset = getFlatOffsetUniformName(texName);\n  return `\n    float ${funcName}(int row, int col, int depth, int depth2, int depth3) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * ${stride0} + col * ${stride1} + depth * ${stride2} +\n          depth2 * ${stride3} + depth3 + ${offset};\n      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n}\nfunction getSampler6D(inputInfo) {\n  const shape = inputInfo.shapeInfo.logicalShape;\n  const texName = inputInfo.name;\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const { newShape, keptDims } = util_exports.squeezeShape(shape);\n  if (newShape.length < shape.length) {\n    const newInputInfo = squeezeInputInfo(inputInfo, newShape);\n    const params = [\"row\", \"col\", \"depth\", \"depth2\", \"depth3\", \"depth4\"];\n    return `\n      ${getSamplerFromInInfo(newInputInfo)}\n      float ${funcName}(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        return ${funcName}(${getSqueezedParams(params, keptDims)});\n      }\n    `;\n  }\n  const stride4 = shape[5];\n  const stride3 = shape[4] * stride4;\n  const stride2 = shape[3] * stride3;\n  const stride1 = shape[2] * stride2;\n  const stride0 = shape[1] * stride1;\n  if (inputInfo.shapeInfo.isUniform) {\n    return `\n      float ${funcName}(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n        int index = round(dot(\n          vec4(row, col, depth, depth2),\n          vec4(${stride0}, ${stride1}, ${stride2}, ${stride3})) +\n          dot(\n            vec2(depth3, depth4),\n            vec2(${stride4}, 1)));\n        ${getUniformSampler(inputInfo)}\n      }\n    `;\n  }\n  const flatOffset = inputInfo.shapeInfo.flatOffset;\n  const texShape = inputInfo.shapeInfo.texShape;\n  const texNumR = texShape[0];\n  const texNumC = texShape[1];\n  if (texNumC === stride0 && flatOffset == null) {\n    return `\n      float ${funcName}(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        int texR = row;\n        float texC = dot(vec4(col, depth, depth2, depth3),\n          vec4(${stride1}, ${stride2}, ${stride3}, ${stride4})) +\n               float(depth4);\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                   vec2(${texNumC}.0, ${texNumR}.0);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  if (texNumC === stride4 && flatOffset == null) {\n    return `\n      float ${funcName}(int row, int col, int depth,\n                    int depth2, int depth3, int depth4) {\n        float texR = dot(vec4(row, col, depth, depth2),\n          vec4(${shape[1] * shape[2] * shape[3] * shape[4]},\n               ${shape[2] * shape[3] * shape[4]},\n               ${shape[3] * shape[4]},\n               ${shape[4]})) + float(depth3);\n        int texC = depth4;\n        vec2 uv = (vec2(texC, texR) + halfCR) /\n                  vec2(${texNumC}.0, ${texNumR}.0);\n        return sampleTexture(${texName}, uv);\n      }\n    `;\n  }\n  const offset = getFlatOffsetUniformName(texName);\n  return `\n    float ${funcName}(int row, int col, int depth,\n                  int depth2, int depth3, int depth4) {\n      // Explicitly use integer operations as dot() only works on floats.\n      int index = row * ${stride0} + col * ${stride1} + depth * ${stride2} +\n          depth2 * ${stride3} + depth3 * ${stride4} + depth4 + ${offset};\n      vec2 uv = uvFromFlat(${texNumR}, ${texNumC}, index);\n      return sampleTexture(${texName}, uv);\n    }\n  `;\n}\nfunction getUniformSampler(inputInfo) {\n  const texName = inputInfo.name;\n  const inSize = util_exports.sizeFromShape(inputInfo.shapeInfo.logicalShape);\n  if (inSize < 2) {\n    return `return ${texName};`;\n  }\n  return `\n    for (int i = 0; i < ${inSize}; i++) {\n      if (i == index) {\n        return ${texName}[i];\n      }\n    }\n  `;\n}\nfunction getPackedSamplerAtOutputCoords(inputInfo, outShapeInfo) {\n  const texName = inputInfo.name;\n  const texFuncSnippet = texName.charAt(0).toUpperCase() + texName.slice(1);\n  const funcName = \"get\" + texFuncSnippet + \"AtOutCoords\";\n  const inRank = inputInfo.shapeInfo.logicalShape.length;\n  const outRank = outShapeInfo.logicalShape.length;\n  const broadcastDims = getBroadcastDims2(inputInfo.shapeInfo.logicalShape, outShapeInfo.logicalShape);\n  const type = getCoordsDataType(outRank);\n  const rankDiff = outRank - inRank;\n  let coordsSnippet;\n  const fields = [\"x\", \"y\", \"z\", \"w\", \"u\", \"v\"];\n  if (inRank === 0) {\n    coordsSnippet = \"\";\n  } else if (outRank < 2 && broadcastDims.length >= 1) {\n    coordsSnippet = \"coords = 0;\";\n  } else {\n    coordsSnippet = broadcastDims.map((d) => `coords.${fields[d + rankDiff]} = 0;`).join(\"\\n\");\n  }\n  let unpackedCoordsSnippet = \"\";\n  if (outRank < 2 && inRank > 0) {\n    unpackedCoordsSnippet = \"coords\";\n  } else {\n    unpackedCoordsSnippet = inputInfo.shapeInfo.logicalShape.map((s2, i2) => `coords.${fields[i2 + rankDiff]}`).join(\", \");\n  }\n  let output = `return outputValue;`;\n  const inSize = util_exports.sizeFromShape(inputInfo.shapeInfo.logicalShape);\n  const isInputScalar = inSize === 1;\n  const outSize = util_exports.sizeFromShape(outShapeInfo.logicalShape);\n  const isOutputScalar = outSize === 1;\n  if (inRank === 1 && !isInputScalar && !isOutputScalar) {\n    output = `\n      return vec4(outputValue.xy, outputValue.xy);\n    `;\n  } else if (isInputScalar && !isOutputScalar) {\n    if (outRank === 1) {\n      output = `\n        return vec4(outputValue.x, outputValue.x, 0., 0.);\n      `;\n    } else {\n      output = `\n        return vec4(outputValue.x);\n      `;\n    }\n  } else if (broadcastDims.length) {\n    const rows = inRank - 2;\n    const cols = inRank - 1;\n    if (broadcastDims.indexOf(rows) > -1 && broadcastDims.indexOf(cols) > -1) {\n      output = `return vec4(outputValue.x);`;\n    } else if (broadcastDims.indexOf(rows) > -1) {\n      output = `return vec4(outputValue.x, outputValue.y, outputValue.x, outputValue.y);`;\n    } else if (broadcastDims.indexOf(cols) > -1) {\n      output = `return vec4(outputValue.xx, outputValue.zz);`;\n    }\n  }\n  return `\n    vec4 ${funcName}() {\n      ${type} coords = getOutputCoords();\n      ${coordsSnippet}\n      vec4 outputValue = get${texFuncSnippet}(${unpackedCoordsSnippet});\n      ${output}\n    }\n  `;\n}\nfunction getSamplerAtOutputCoords(inputInfo, outShapeInfo) {\n  const texName = inputInfo.name;\n  const texFuncSnippet = texName.charAt(0).toUpperCase() + texName.slice(1);\n  const funcName = \"get\" + texFuncSnippet + \"AtOutCoords\";\n  const outTexShape = outShapeInfo.texShape;\n  const inTexShape = inputInfo.shapeInfo.texShape;\n  const inRank = inputInfo.shapeInfo.logicalShape.length;\n  const outRank = outShapeInfo.logicalShape.length;\n  if (!inputInfo.shapeInfo.isUniform && inRank === outRank && inputInfo.shapeInfo.flatOffset == null && util_exports.arraysEqual(inTexShape, outTexShape)) {\n    return `\n      float ${funcName}() {\n        return sampleTexture(${texName}, resultUV);\n      }\n    `;\n  }\n  const type = getCoordsDataType(outRank);\n  const broadcastDims = getBroadcastDims2(inputInfo.shapeInfo.logicalShape, outShapeInfo.logicalShape);\n  const rankDiff = outRank - inRank;\n  let coordsSnippet;\n  const fields = [\"x\", \"y\", \"z\", \"w\", \"u\", \"v\"];\n  if (inRank === 0) {\n    coordsSnippet = \"\";\n  } else if (outRank < 2 && broadcastDims.length >= 1) {\n    coordsSnippet = \"coords = 0;\";\n  } else {\n    coordsSnippet = broadcastDims.map((d) => `coords.${fields[d + rankDiff]} = 0;`).join(\"\\n\");\n  }\n  let unpackedCoordsSnippet = \"\";\n  if (outRank < 2 && inRank > 0) {\n    unpackedCoordsSnippet = \"coords\";\n  } else {\n    unpackedCoordsSnippet = inputInfo.shapeInfo.logicalShape.map((s2, i2) => `coords.${fields[i2 + rankDiff]}`).join(\", \");\n  }\n  return `\n    float ${funcName}() {\n      ${type} coords = getOutputCoords();\n      ${coordsSnippet}\n      return get${texFuncSnippet}(${unpackedCoordsSnippet});\n    }\n  `;\n}\nfunction getCoordsDataType(rank) {\n  if (rank <= 1) {\n    return \"int\";\n  } else if (rank === 2) {\n    return \"ivec2\";\n  } else if (rank === 3) {\n    return \"ivec3\";\n  } else if (rank === 4) {\n    return \"ivec4\";\n  } else if (rank === 5) {\n    return \"ivec5\";\n  } else if (rank === 6) {\n    return \"ivec6\";\n  } else {\n    throw Error(`GPU for rank ${rank} is not yet supported`);\n  }\n}\nfunction getUniformInfoFromShape(isPacked, shape, texShape) {\n  const { newShape, keptDims } = util_exports.squeezeShape(shape);\n  const rank = shape.length;\n  const useSqueezePackedShape = isPacked && rank === 3 && shape[0] === 1;\n  const squeezeShape2 = useSqueezePackedShape ? shape.slice(1) : newShape;\n  const useSqueezeShape = !isPacked && rank > 1 && !util_exports.arraysEqual(shape, texShape) && newShape.length < rank || useSqueezePackedShape;\n  const uniformShape = useSqueezeShape ? squeezeShape2 : shape;\n  return { useSqueezeShape, uniformShape, keptDims };\n}\nfunction squeezeInputInfo(inInfo, squeezedShape) {\n  const newInputInfo = JSON.parse(JSON.stringify(inInfo));\n  newInputInfo.shapeInfo.logicalShape = squeezedShape;\n  return newInputInfo;\n}\nfunction getSqueezedParams(params, keptDims) {\n  return keptDims.map((d) => params[d]).join(\", \");\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/gpgpu_math.js\nfunction compileProgram(gpgpu, program, inputs, output) {\n  const inputInfos = inputs.map((input2, i2) => {\n    const shapeInfo = {\n      logicalShape: input2.shape,\n      texShape: input2.isUniform ? null : input2.texData.texShape,\n      isUniform: input2.isUniform,\n      isPacked: input2.isUniform ? false : input2.texData.isPacked,\n      flatOffset: null\n    };\n    if (input2.texData != null && input2.texData.slice != null && input2.texData.slice.flatOffset > 0) {\n      shapeInfo.flatOffset = input2.texData.slice.flatOffset;\n    }\n    return { name: program.variableNames[i2], shapeInfo };\n  });\n  const inShapeInfos = inputInfos.map((x) => x.shapeInfo);\n  const outShapeInfo = {\n    logicalShape: output.shape,\n    texShape: output.texData.texShape,\n    isUniform: false,\n    isPacked: output.texData.isPacked,\n    flatOffset: null\n  };\n  const source = makeShader(inputInfos, outShapeInfo, program);\n  const fragmentShader = createFragmentShader(gpgpu.gl, source);\n  const webGLProgram = gpgpu.createProgram(fragmentShader);\n  if (!env().get(\"ENGINE_COMPILE_ONLY\")) {\n    return Object.assign({\n      program,\n      fragmentShader,\n      source,\n      webGLProgram,\n      inShapeInfos,\n      outShapeInfo\n    }, getUniformLocations(gpgpu, program, webGLProgram));\n  } else {\n    return {\n      program,\n      fragmentShader,\n      source,\n      webGLProgram,\n      inShapeInfos,\n      outShapeInfo,\n      uniformLocations: null,\n      customUniformLocations: null,\n      infLoc: null,\n      nanLoc: null,\n      inShapesLocations: null,\n      inTexShapesLocations: null,\n      outShapeLocation: null,\n      outShapeStridesLocation: null,\n      outTexShapeLocation: null\n    };\n  }\n}\nfunction getUniformLocations(gpgpu, program, webGLProgram) {\n  const uniformLocations = {};\n  const inShapesLocations = {};\n  const inTexShapesLocations = {};\n  const customUniformLocations = [];\n  let outShapeLocation;\n  let outTexShapeLocation;\n  let outShapeStridesLocation;\n  let infLoc = null;\n  let nanLoc = null;\n  nanLoc = gpgpu.getUniformLocation(webGLProgram, \"NAN\", false);\n  if (env().getNumber(\"WEBGL_VERSION\") === 1) {\n    infLoc = gpgpu.getUniformLocation(webGLProgram, \"INFINITY\", false);\n  }\n  const shouldThrow = false;\n  for (let i2 = 0; i2 < program.variableNames.length; i2++) {\n    const varName = program.variableNames[i2];\n    uniformLocations[varName] = gpgpu.getUniformLocation(webGLProgram, varName, shouldThrow);\n    uniformLocations[`offset${varName}`] = gpgpu.getUniformLocation(webGLProgram, `offset${varName}`, shouldThrow);\n    if (program.enableShapeUniforms) {\n      inShapesLocations[`${varName}Shape`] = gpgpu.getUniformLocation(webGLProgram, `${varName}Shape`, shouldThrow);\n      inTexShapesLocations[`${varName}TexShape`] = gpgpu.getUniformLocation(webGLProgram, `${varName}TexShape`, shouldThrow);\n    }\n  }\n  if (program.enableShapeUniforms) {\n    outShapeLocation = gpgpu.getUniformLocation(webGLProgram, \"outShape\", shouldThrow);\n    outShapeStridesLocation = gpgpu.getUniformLocation(webGLProgram, \"outShapeStrides\", shouldThrow);\n    outTexShapeLocation = gpgpu.getUniformLocation(webGLProgram, \"outTexShape\", shouldThrow);\n  }\n  if (program.customUniforms) {\n    program.customUniforms.forEach((d, i2) => {\n      customUniformLocations[i2] = gpgpu.getUniformLocation(webGLProgram, d.name, shouldThrow);\n    });\n  }\n  return {\n    uniformLocations,\n    customUniformLocations,\n    infLoc,\n    nanLoc,\n    inShapesLocations,\n    inTexShapesLocations,\n    outShapeLocation,\n    outShapeStridesLocation,\n    outTexShapeLocation\n  };\n}\nfunction validateBinaryAndProgram(shapeInfos, inputs) {\n  if (shapeInfos.length !== inputs.length) {\n    throw Error(`Binary was compiled with ${shapeInfos.length} inputs, but was executed with ${inputs.length} inputs`);\n  }\n  shapeInfos.forEach((s2, i2) => {\n    const shapeA = s2.logicalShape;\n    const input2 = inputs[i2];\n    const shapeB = input2.shape;\n    if (!util_exports.arraysEqual(shapeA, shapeB)) {\n      throw Error(`Binary was compiled with different shapes than the current args. Shapes ${shapeA} and ${shapeB} must match`);\n    }\n    if (s2.isUniform && input2.isUniform) {\n      return;\n    }\n    const texShapeA = s2.texShape;\n    const texShapeB = input2.isUniform ? null : input2.texData.texShape;\n    if (!util_exports.arraysEqual(texShapeA, texShapeB)) {\n      throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${texShapeA} and ${texShapeB} must match`);\n    }\n  });\n}\nfunction runProgram(gpgpu, binary, inputs, output, customUniformValues) {\n  if (!binary.program.enableShapeUniforms) {\n    validateBinaryAndProgram(binary.inShapeInfos, inputs);\n    validateBinaryAndProgram([binary.outShapeInfo], [output]);\n  }\n  const outTex = output.texData.texture;\n  const outTexShape = output.texData.texShape;\n  if (output.texData.isPacked) {\n    gpgpu.setOutputPackedMatrixTexture(outTex.texture, outTexShape[0], outTexShape[1]);\n  } else {\n    gpgpu.setOutputMatrixTexture(outTex.texture, outTexShape[0], outTexShape[1]);\n  }\n  gpgpu.setProgram(binary.webGLProgram);\n  if (env().getNumber(\"WEBGL_VERSION\") === 1) {\n    if (binary.infLoc !== null) {\n      gpgpu.gl.uniform1f(binary.infLoc, Infinity);\n    }\n  }\n  if (binary.nanLoc !== null) {\n    gpgpu.gl.uniform1f(binary.nanLoc, NaN);\n  }\n  inputs.forEach((input2, i2) => {\n    const varName = binary.program.variableNames[i2];\n    const varLoc = binary.uniformLocations[varName];\n    const varOffsetLoc = binary.uniformLocations[`offset${varName}`];\n    const varShapeLoc = binary.inShapesLocations[`${varName}Shape`];\n    const varTexShapeLoc = binary.inTexShapesLocations[`${varName}TexShape`];\n    if (varShapeLoc) {\n      const { uniformShape } = getUniformInfoFromShape(binary.program.packedInputs, input2.shape, input2.texData.texShape);\n      switch (uniformShape.length) {\n        case 1:\n          gpgpu.gl.uniform1iv(varShapeLoc, new Int32Array(uniformShape));\n          break;\n        case 2:\n          gpgpu.gl.uniform2iv(varShapeLoc, new Int32Array(uniformShape));\n          break;\n        case 3:\n          gpgpu.gl.uniform3iv(varShapeLoc, new Int32Array(uniformShape));\n          break;\n        case 4:\n          gpgpu.gl.uniform4iv(varShapeLoc, new Int32Array(uniformShape));\n          break;\n        default:\n          break;\n      }\n    }\n    if (varTexShapeLoc) {\n      gpgpu.gl.uniform2i(varTexShapeLoc, input2.texData.texShape[0], input2.texData.texShape[1]);\n    }\n    if (varLoc == null) {\n      return;\n    }\n    if (input2.isUniform) {\n      if (util_exports.sizeFromShape(input2.shape) < 2) {\n        gpgpu.gl.uniform1f(varLoc, input2.uniformValues[0]);\n      } else {\n        let vals = input2.uniformValues;\n        if (!(vals instanceof Float32Array)) {\n          vals = new Float32Array(vals);\n        }\n        gpgpu.gl.uniform1fv(varLoc, vals);\n      }\n      return;\n    }\n    if (input2.texData.slice != null && varOffsetLoc != null) {\n      gpgpu.gl.uniform1i(varOffsetLoc, input2.texData.slice.flatOffset);\n    }\n    gpgpu.setInputMatrixTexture(input2.texData.texture.texture, varLoc, i2);\n  });\n  const outShapeLoc = binary.outShapeLocation;\n  if (outShapeLoc) {\n    switch (output.shape.length) {\n      case 1:\n        gpgpu.gl.uniform1iv(outShapeLoc, new Int32Array(output.shape));\n        break;\n      case 2:\n        gpgpu.gl.uniform2iv(outShapeLoc, new Int32Array(output.shape));\n        break;\n      case 3:\n        gpgpu.gl.uniform3iv(outShapeLoc, new Int32Array(output.shape));\n        break;\n      case 4:\n        gpgpu.gl.uniform4iv(outShapeLoc, new Int32Array(output.shape));\n        break;\n      default:\n        break;\n    }\n  }\n  if (binary.outShapeStridesLocation) {\n    const strides = util_exports.computeStrides(output.shape);\n    switch (output.shape.length) {\n      case 2:\n        gpgpu.gl.uniform1iv(binary.outShapeStridesLocation, new Int32Array(strides));\n        break;\n      case 3:\n        gpgpu.gl.uniform2iv(binary.outShapeStridesLocation, new Int32Array(strides));\n        break;\n      case 4:\n        gpgpu.gl.uniform3iv(binary.outShapeStridesLocation, new Int32Array(strides));\n        break;\n      default:\n        break;\n    }\n  }\n  if (binary.outTexShapeLocation) {\n    gpgpu.gl.uniform2i(binary.outTexShapeLocation, output.texData.texShape[0], output.texData.texShape[1]);\n  }\n  if (binary.program.customUniforms && customUniformValues) {\n    binary.program.customUniforms.forEach((d, i2) => {\n      const customLoc = binary.customUniformLocations[i2];\n      const customValue = customUniformValues[i2];\n      if (d.type === \"float\") {\n        gpgpu.gl.uniform1fv(customLoc, customValue);\n      } else if (d.type === \"vec2\") {\n        gpgpu.gl.uniform2fv(customLoc, customValue);\n      } else if (d.type === \"vec3\") {\n        gpgpu.gl.uniform3fv(customLoc, customValue);\n      } else if (d.type === \"vec4\") {\n        gpgpu.gl.uniform4fv(customLoc, customValue);\n      } else if (d.type === \"int\") {\n        gpgpu.gl.uniform1iv(customLoc, customValue);\n      } else if (d.type === \"ivec2\") {\n        gpgpu.gl.uniform2iv(customLoc, customValue);\n      } else if (d.type === \"ivec3\") {\n        gpgpu.gl.uniform3iv(customLoc, customValue);\n      } else if (d.type === \"ivec4\") {\n        gpgpu.gl.uniform4iv(customLoc, customValue);\n      } else {\n        throw Error(`uniform type ${d.type} is not supported yet.`);\n      }\n    });\n  }\n  gpgpu.executeProgram();\n}\nfunction makeShaderKey(program, inputs, output) {\n  let keyInputs = \"\";\n  inputs.concat(output).forEach((x) => {\n    const hasOffset = x.texData != null && x.texData.slice != null && x.texData.slice.flatOffset > 0;\n    if (program.enableShapeUniforms && !x.isUniform) {\n      const xTexShape = x.texData.texShape;\n      const { useSqueezeShape, uniformShape, keptDims } = getUniformInfoFromShape(program.packedInputs, x.shape, xTexShape);\n      let rank1 = \"\", rank2 = \"\", rank34 = \"\";\n      if (uniformShape.length === 1 && program.packedInputs) {\n        const packedTexShape = [Math.ceil(xTexShape[0] / 2), Math.ceil(xTexShape[1] / 2)];\n        rank1 = `${packedTexShape[0] > 1}_${packedTexShape[1] > 1}`;\n      } else if (uniformShape.length === 2 && !program.packedInputs) {\n        rank2 = `${uniformShape[0] > 1}_${uniformShape[1] > 1}`;\n      } else if (uniformShape.length > 2 && !program.packedInputs) {\n        const strides = util_exports.computeStrides(uniformShape);\n        rank34 = `${strides[0] === xTexShape[1]}_${strides[strides.length - 1] === xTexShape[1]}`;\n      }\n      const xRank = x.shape.length;\n      const isLogicalShapTexShapeEqual = uniformShape.length === 2 && util_exports.arraysEqual(x.shape, xTexShape);\n      const isScalar = util_exports.sizeFromShape(x.shape) === 1;\n      const broadcastDims = backend_util_exports.getBroadcastDims(x.shape, output.shape);\n      const isInOutTexShapeEqual = !program.packedInputs && xRank === output.shape.length && util_exports.arraysEqual(xTexShape, output.texData.texShape);\n      const isTexShapeGreaterThanOne = program.packedInputs || uniformShape.length > 2 ? \"\" : `${xTexShape[0] > 1}_${xTexShape[1] > 1}`;\n      keyInputs += `${xRank}_${isInOutTexShapeEqual}_${useSqueezeShape ? keptDims : \"\"}_${uniformShape.length}_${isScalar}_${broadcastDims}_${isLogicalShapTexShapeEqual}_${rank1}_${rank2}_${rank34}_${isTexShapeGreaterThanOne}_${hasOffset}`;\n    } else {\n      const texShape = x.isUniform ? \"uniform\" : x.texData.texShape;\n      keyInputs += `${x.shape}_${texShape}_${hasOffset}`;\n    }\n  });\n  const keyUserCode = program.userCode;\n  let key = program.constructor.name;\n  key += \"_\" + keyInputs + \"_\" + keyUserCode + `${env().getNumber(\"WEBGL_VERSION\")}`;\n  return key;\n}\nfunction useShapeUniforms(rank) {\n  return env().getBool(\"WEBGL_USE_SHAPES_UNIFORMS\") && rank <= 4;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/decode_matrix_gpu.js\nvar DecodeMatrixProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = false;\n    this.packedOutput = true;\n    this.outPackingScheme = PackingScheme.DENSE;\n    this.customUniforms = [{ name: \"texShape\", type: \"ivec2\" }];\n    const glsl = getGlslDifferences();\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    this.userCode = `\n      ivec3 outCoordsFromFlatIndex(int index) {\n        ${this.enableShapeUniforms ? getOutputLogicalCoordinatesFromFlatIndexByUniform([\"r\", \"c\", \"d\"], outputShape) : getLogicalCoordinatesFromFlatIndex([\"r\", \"c\", \"d\"], outputShape)}\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));\n        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getA(rc.x, rc.y, rc.z);\n        }\n\n        ${glsl.output} = result;\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/decode_matrix_packed_gpu.js\nvar DecodeMatrixPackedProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outPackingScheme = PackingScheme.DENSE;\n    this.customUniforms = [{ name: \"texShape\", type: \"ivec2\" }];\n    const glsl = getGlslDifferences();\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    this.userCode = `\n      ivec3 outCoordsFromFlatIndex(int index) {\n        ${this.enableShapeUniforms ? getOutputLogicalCoordinatesFromFlatIndexByUniform([\"r\", \"c\", \"d\"], outputShape) : getLogicalCoordinatesFromFlatIndex([\"r\", \"c\", \"d\"], outputShape)}\n        return ivec3(r, c, d);\n      }\n\n      void main() {\n        ivec2 resTexRC = ivec2(resultUV.yx * vec2(texShape[0], texShape[1]));\n        int index = 4 * (resTexRC.x * texShape[1] + resTexRC.y);\n\n        vec4 result = vec4(0.);\n\n        for (int i=0; i<4; i++) {\n          int flatIndex = index + i;\n          ivec3 rc = outCoordsFromFlatIndex(flatIndex);\n          result[i] = getChannel(getA(rc.x, rc.y, rc.z), vec2(rc.y, rc.z));\n        }\n\n        ${glsl.output} = result;\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_float_gpu.js\nvar EncodeFloatProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.outTexUsage = TextureUsage.DOWNLOAD;\n    const glsl = getGlslDifferences();\n    this.outputShape = outputShape;\n    this.userCode = `\n      ${ENCODE_FLOAT_SNIPPET}\n\n      void main() {\n        float x = getAAtOutCoords();\n        ${glsl.output} = encode_float(x);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_float_packed_gpu.js\nvar EncodeFloatPackedProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = false;\n    this.outTexUsage = TextureUsage.DOWNLOAD;\n    const glsl = getGlslDifferences();\n    this.outputShape = outputShape;\n    this.userCode = `\n      ${ENCODE_FLOAT_SNIPPET}\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n        float x = getChannel(getAAtOutCoords(), vec2(coords.y, coords.z));\n        ${glsl.output} = encode_float(x);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_matrix_gpu.js\nvar EncodeMatrixProgram = class {\n  constructor(outputShape, inputIsUnsignedByte = false) {\n    this.variableNames = [\"A\"];\n    this.customUniforms = [{ name: \"texShape\", type: \"ivec2\" }];\n    const glsl = getGlslDifferences();\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    let output = `result`;\n    if (inputIsUnsignedByte) {\n      output = `floor(result * 255. + 0.5)`;\n    }\n    this.userCode = `\n      ${this.enableShapeUniforms ? getFlatIndexFrom3DOutput() : getFlatIndexFrom3D(outputShape)}\n\n      void main() {\n        ivec3 coords = getOutputCoords();\n\n        int flatIndex = getFlatIndex(coords);\n        int offset = imod(flatIndex, 4);\n\n        flatIndex = idiv(flatIndex, 4, 1.);\n\n        int r = flatIndex / texShape[1];\n        int c = imod(flatIndex, texShape[1]);\n        vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);\n        vec4 values = ${glsl.texture2D}(A, uv);\n\n        float result;\n\n        if(offset == 0) {\n          result = values[0];\n        } else if(offset == 1) {\n          result = values[1];\n        } else if(offset == 2) {\n          result = values[2];\n        } else {\n          result = values[3];\n        }\n\n        ${glsl.output} = vec4(${output}, 0., 0., 0.);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/encode_matrix_packed_gpu.js\nvar EncodeMatrixPackedProgram = class {\n  constructor(outputShape, inputIsUnsignedByte = false) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = false;\n    this.packedOutput = true;\n    this.customUniforms = [{ name: \"texShape\", type: \"ivec2\" }];\n    const glsl = getGlslDifferences();\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    let mainLoop = \"\";\n    let output = \"result\";\n    if (inputIsUnsignedByte) {\n      output = \"floor(result * 255. + 0.5)\";\n    }\n    for (let row = 0; row <= 1; row++) {\n      for (let col = 0; col <= 1; col++) {\n        const channel = row * 2 + col;\n        mainLoop += `\n          localCoords = coords;\n          if(localCoords[2] + ${col} < ${this.enableShapeUniforms ? \"outShape[2]\" : `${outputShape[2]}`}) {\n          localCoords[2] += ${col};\n          if (localCoords[1] + ${row} < ${this.enableShapeUniforms ? \"outShape[1]\" : `${outputShape[1]}`}) {\n            localCoords[1] += ${row};\n\n            flatIndex = getFlatIndex(localCoords);\n            offset = imod(flatIndex, 4);\n\n            flatIndex = idiv(flatIndex, 4, 1.);\n\n            int r = flatIndex / texShape[1];\n            int c = imod(flatIndex, texShape[1]);\n            vec2 uv = (vec2(c, r) + halfCR) / vec2(texShape[1], texShape[0]);\n            values = ${glsl.texture2D}(A, uv);\n\n            if (offset == 0) {\n              result[${channel}] = values[0];\n            } else if (offset == 1) {\n              result[${channel}] = values[1];\n            } else if (offset == 2) {\n              result[${channel}] = values[2];\n            } else {\n              result[${channel}] = values[3];\n            }\n          }\n        }\n        `;\n      }\n    }\n    this.userCode = `\n        ${this.enableShapeUniforms ? getFlatIndexFrom3DOutput() : getFlatIndexFrom3D(outputShape)}\n\n        void main() {\n          ivec3 coords = getOutputCoords();\n\n          vec4 result = vec4(0.);\n          int flatIndex, r, c, offset;\n          ivec3 localCoords;\n          vec2 uv;\n          vec4 values;\n\n          ${mainLoop}\n\n          ${glsl.output} = ${output};\n        }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/gpgpu_util.js\nvar gpgpu_util_exports = {};\n__export(gpgpu_util_exports, {\n  bindVertexProgramAttributeStreams: () => bindVertexProgramAttributeStreams,\n  createBufferFromOutputTexture: () => createBufferFromOutputTexture,\n  createFloat16MatrixTexture: () => createFloat16MatrixTexture,\n  createFloat16PackedMatrixTexture: () => createFloat16PackedMatrixTexture,\n  createFloat32MatrixTexture: () => createFloat32MatrixTexture,\n  createIndexBuffer: () => createIndexBuffer,\n  createPackedMatrixTexture: () => createPackedMatrixTexture,\n  createUnsignedBytesMatrixTexture: () => createUnsignedBytesMatrixTexture,\n  createVertexBuffer: () => createVertexBuffer,\n  createVertexShader: () => createVertexShader2,\n  downloadByteEncodedFloatMatrixFromOutputTexture: () => downloadByteEncodedFloatMatrixFromOutputTexture,\n  downloadFloat32MatrixFromBuffer: () => downloadFloat32MatrixFromBuffer,\n  downloadMatrixFromPackedOutputTexture: () => downloadMatrixFromPackedOutputTexture,\n  downloadPackedMatrixFromBuffer: () => downloadPackedMatrixFromBuffer,\n  getInternalFormatForFloat16MatrixTexture: () => getInternalFormatForFloat16MatrixTexture,\n  getInternalFormatForFloat16PackedMatrixTexture: () => getInternalFormatForFloat16PackedMatrixTexture,\n  getInternalFormatForFloat32MatrixTexture: () => getInternalFormatForFloat32MatrixTexture,\n  getInternalFormatForPackedMatrixTexture: () => getInternalFormatForPackedMatrixTexture,\n  getInternalFormatForUnsignedBytesMatrixTexture: () => getInternalFormatForUnsignedBytesMatrixTexture,\n  uploadDenseMatrixToTexture: () => uploadDenseMatrixToTexture,\n  uploadPixelDataToTexture: () => uploadPixelDataToTexture\n});\nfunction createVertexShader2(gl) {\n  const glsl = getGlslDifferences();\n  const vertexShaderSource = `${glsl.version}\n    precision highp float;\n    ${glsl.attribute} vec3 clipSpacePos;\n    ${glsl.attribute} vec2 uv;\n    ${glsl.varyingVs} vec2 resultUV;\n\n    void main() {\n      gl_Position = vec4(clipSpacePos, 1);\n      resultUV = uv;\n    }`;\n  return createVertexShader(gl, vertexShaderSource);\n}\nfunction createVertexBuffer(gl) {\n  const vertexArray = new Float32Array([-1, 1, 0, 0, 1, -1, -1, 0, 0, 0, 1, 1, 0, 1, 1, 1, -1, 0, 1, 0]);\n  return createStaticVertexBuffer(gl, vertexArray);\n}\nfunction createIndexBuffer(gl) {\n  const triangleVertexIndices = new Uint16Array([0, 1, 2, 2, 1, 3]);\n  return createStaticIndexBuffer(gl, triangleVertexIndices);\n}\nfunction createAndConfigureTexture(gl, width, height, internalFormat, textureFormat, textureType) {\n  validateTextureSize(width, height);\n  const texture = createTexture(gl);\n  const tex2d = gl.TEXTURE_2D;\n  callAndCheck(gl, () => gl.bindTexture(tex2d, texture));\n  callAndCheck(gl, () => gl.texParameteri(tex2d, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE));\n  callAndCheck(gl, () => gl.texParameteri(tex2d, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE));\n  callAndCheck(gl, () => gl.texParameteri(tex2d, gl.TEXTURE_MIN_FILTER, gl.NEAREST));\n  callAndCheck(gl, () => gl.texParameteri(tex2d, gl.TEXTURE_MAG_FILTER, gl.NEAREST));\n  if (env().getNumber(\"WEBGL_VERSION\") === 1) {\n    callAndCheck(gl, () => gl.texImage2D(tex2d, 0, internalFormat, width, height, 0, textureFormat, textureType, null));\n  } else {\n    callAndCheck(gl, () => gl.texStorage2D(tex2d, 1, internalFormat, width, height));\n  }\n  callAndCheck(gl, () => gl.bindTexture(gl.TEXTURE_2D, null));\n  return { texture, texShape: [height, width] };\n}\nfunction getInternalFormatForFloat32MatrixTexture(textureConfig) {\n  return textureConfig.internalFormatFloat;\n}\nfunction createFloat32MatrixTexture(gl, rows, columns, textureConfig) {\n  const [width, height] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);\n  return createAndConfigureTexture(gl, width, height, getInternalFormatForFloat32MatrixTexture(textureConfig), textureConfig.textureFormatFloat, gl.FLOAT);\n}\nfunction getInternalFormatForFloat16MatrixTexture(textureConfig) {\n  return textureConfig.internalFormatHalfFloat;\n}\nfunction createFloat16MatrixTexture(gl, rows, columns, textureConfig) {\n  const [width, height] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);\n  return createAndConfigureTexture(gl, width, height, getInternalFormatForFloat16MatrixTexture(textureConfig), textureConfig.textureFormatFloat, textureConfig.textureTypeHalfFloat);\n}\nfunction getInternalFormatForUnsignedBytesMatrixTexture(textureConfig) {\n  return textureConfig.downloadTextureFormat;\n}\nfunction createUnsignedBytesMatrixTexture(gl, rows, columns, textureConfig) {\n  const [width, height] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);\n  return createAndConfigureTexture(gl, width, height, getInternalFormatForUnsignedBytesMatrixTexture(textureConfig), gl.RGBA, gl.UNSIGNED_BYTE);\n}\nfunction getInternalFormatForPackedMatrixTexture(textureConfig) {\n  return textureConfig.internalFormatPackedFloat;\n}\nfunction createPackedMatrixTexture(gl, rows, columns, textureConfig) {\n  const [width, height] = getPackedMatrixTextureShapeWidthHeight(rows, columns);\n  return createAndConfigureTexture(gl, width, height, getInternalFormatForPackedMatrixTexture(textureConfig), gl.RGBA, gl.FLOAT);\n}\nfunction getInternalFormatForFloat16PackedMatrixTexture(textureConfig) {\n  return textureConfig.internalFormatPackedHalfFloat;\n}\nfunction createFloat16PackedMatrixTexture(gl, rows, columns, textureConfig) {\n  const [width, height] = getPackedMatrixTextureShapeWidthHeight(rows, columns);\n  return createAndConfigureTexture(gl, width, height, getInternalFormatForFloat16PackedMatrixTexture(textureConfig), gl.RGBA, textureConfig.textureTypeHalfFloat);\n}\nfunction bindVertexProgramAttributeStreams(gl, program, vertexBuffer) {\n  const posOffset = 0;\n  const uvOffset = 3 * 4;\n  const stride = 3 * 4 + 2 * 4;\n  callAndCheck(gl, () => gl.bindBuffer(gl.ARRAY_BUFFER, vertexBuffer));\n  const success = bindVertexBufferToProgramAttribute(gl, program, \"clipSpacePos\", vertexBuffer, 3, stride, posOffset);\n  return success && bindVertexBufferToProgramAttribute(gl, program, \"uv\", vertexBuffer, 2, stride, uvOffset);\n}\nfunction uploadDenseMatrixToTexture(gl, texture, width, height, data, textureConfig) {\n  callAndCheck(gl, () => gl.bindTexture(gl.TEXTURE_2D, texture));\n  let dataForUpload, texelDataType, internalFormat;\n  if (data instanceof Uint8Array) {\n    dataForUpload = new Uint8Array(width * height * 4);\n    texelDataType = gl.UNSIGNED_BYTE;\n    internalFormat = gl.RGBA;\n  } else {\n    dataForUpload = new Float32Array(width * height * 4);\n    texelDataType = gl.FLOAT;\n    internalFormat = textureConfig.internalFormatPackedFloat;\n  }\n  dataForUpload.set(data);\n  if (env().getNumber(\"WEBGL_VERSION\") === 2) {\n    callAndCheck(gl, () => gl.texSubImage2D(gl.TEXTURE_2D, 0, 0, 0, width, height, gl.RGBA, texelDataType, dataForUpload));\n  } else {\n    callAndCheck(gl, () => gl.texImage2D(gl.TEXTURE_2D, 0, internalFormat, width, height, 0, gl.RGBA, texelDataType, dataForUpload));\n  }\n  callAndCheck(gl, () => gl.bindTexture(gl.TEXTURE_2D, null));\n}\nfunction uploadPixelDataToTexture(gl, texture, pixels) {\n  callAndCheck(gl, () => gl.bindTexture(gl.TEXTURE_2D, texture));\n  if (pixels.data instanceof Uint8Array) {\n    if (env().getNumber(\"WEBGL_VERSION\") === 2) {\n      callAndCheck(gl, () => gl.texSubImage2D(gl.TEXTURE_2D, 0, 0, 0, pixels.width, pixels.height, gl.RGBA, gl.UNSIGNED_BYTE, pixels.data));\n    } else {\n      callAndCheck(gl, () => gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, pixels.width, pixels.height, 0, gl.RGBA, gl.UNSIGNED_BYTE, pixels.data));\n    }\n  } else {\n    if (env().getNumber(\"WEBGL_VERSION\") === 2) {\n      callAndCheck(gl, () => gl.texSubImage2D(gl.TEXTURE_2D, 0, 0, 0, gl.RGBA, gl.UNSIGNED_BYTE, pixels));\n    } else {\n      callAndCheck(gl, () => gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, pixels));\n    }\n  }\n  callAndCheck(gl, () => gl.bindTexture(gl.TEXTURE_2D, null));\n}\nfunction createBufferFromOutputTexture(gl2, rows, columns, textureConfig) {\n  const buffer2 = gl2.createBuffer();\n  callAndCheck(gl2, () => gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, buffer2));\n  const bytesPerFloat = 4;\n  const valuesPerTexel = 4;\n  const bufferSizeBytes = bytesPerFloat * valuesPerTexel * rows * columns;\n  callAndCheck(gl2, () => gl2.bufferData(gl2.PIXEL_PACK_BUFFER, bufferSizeBytes, gl2.STREAM_READ));\n  callAndCheck(gl2, () => gl2.readPixels(0, 0, columns, rows, gl2.RGBA, gl2.FLOAT, 0));\n  callAndCheck(gl2, () => gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, null));\n  return buffer2;\n}\nfunction downloadFloat32MatrixFromBuffer(gl, buffer2, size) {\n  const gl2 = gl;\n  const downloadTarget = new Float32Array(size);\n  gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, buffer2);\n  gl2.getBufferSubData(gl2.PIXEL_PACK_BUFFER, 0, downloadTarget);\n  gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, null);\n  return downloadTarget;\n}\nfunction downloadByteEncodedFloatMatrixFromOutputTexture(gl, rows, columns, textureConfig) {\n  const [w, h] = getUnpackedMatrixTextureShapeWidthHeight(rows, columns);\n  const numChannels = 4;\n  const downloadTarget = new Uint8Array(getUnpackedArraySizeFromMatrixSize(rows * columns, numChannels));\n  callAndCheck(gl, () => gl.readPixels(0, 0, w, h, textureConfig.downloadTextureFormat, gl.UNSIGNED_BYTE, downloadTarget));\n  return new Float32Array(downloadTarget.buffer);\n}\nfunction downloadPackedMatrixFromBuffer(gl, buffer2, batch, rows, cols, physicalRows, physicalCols, textureConfig) {\n  const gl2 = gl;\n  const downloadTarget = new Float32Array(getPackedRGBAArraySizeFromMatrixShape(physicalRows, physicalCols));\n  gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, buffer2);\n  gl2.getBufferSubData(gl2.PIXEL_PACK_BUFFER, 0, downloadTarget);\n  gl2.bindBuffer(gl2.PIXEL_PACK_BUFFER, null);\n  return downloadTarget;\n}\nfunction downloadMatrixFromPackedOutputTexture(gl, physicalRows, physicalCols) {\n  const packedRGBA = new Float32Array(physicalRows * physicalCols * 4);\n  callAndCheck(gl, () => gl.readPixels(0, 0, physicalCols, physicalRows, gl.RGBA, gl.FLOAT, packedRGBA));\n  return packedRGBA;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/gpgpu_context.js\nvar GPGPUContext = class {\n  constructor(gl) {\n    this.outputTexture = null;\n    this.program = null;\n    this.disposed = false;\n    this.vertexAttrsAreBound = false;\n    this.itemsToPoll = [];\n    const glVersion = env().getNumber(\"WEBGL_VERSION\");\n    if (gl != null) {\n      this.gl = gl;\n      setWebGLContext(glVersion, gl);\n    } else {\n      this.gl = getWebGLContext(glVersion);\n    }\n    let COLOR_BUFFER_FLOAT = \"WEBGL_color_buffer_float\";\n    const COLOR_BUFFER_HALF_FLOAT = \"EXT_color_buffer_half_float\";\n    this.parallelCompilationExtension = this.gl.getExtension(\"KHR_parallel_shader_compile\");\n    if (env().getNumber(\"WEBGL_VERSION\") === 1) {\n      const TEXTURE_FLOAT = \"OES_texture_float\";\n      const TEXTURE_HALF_FLOAT = \"OES_texture_half_float\";\n      this.textureFloatExtension = getExtensionOrThrow(this.gl, TEXTURE_FLOAT);\n      if (hasExtension(this.gl, TEXTURE_HALF_FLOAT)) {\n        this.textureHalfFloatExtension = getExtensionOrThrow(this.gl, TEXTURE_HALF_FLOAT);\n      } else if (env().get(\"WEBGL_FORCE_F16_TEXTURES\")) {\n        throw new Error(\"GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.\");\n      }\n      this.colorBufferFloatExtension = this.gl.getExtension(COLOR_BUFFER_FLOAT);\n      if (hasExtension(this.gl, COLOR_BUFFER_HALF_FLOAT)) {\n        this.colorBufferHalfFloatExtension = getExtensionOrThrow(this.gl, COLOR_BUFFER_HALF_FLOAT);\n      } else if (env().get(\"WEBGL_FORCE_F16_TEXTURES\")) {\n        throw new Error(\"GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.\");\n      }\n    } else {\n      COLOR_BUFFER_FLOAT = \"EXT_color_buffer_float\";\n      if (hasExtension(this.gl, COLOR_BUFFER_FLOAT)) {\n        this.colorBufferFloatExtension = this.gl.getExtension(COLOR_BUFFER_FLOAT);\n      } else if (hasExtension(this.gl, COLOR_BUFFER_HALF_FLOAT)) {\n        this.colorBufferHalfFloatExtension = this.gl.getExtension(COLOR_BUFFER_HALF_FLOAT);\n      } else {\n        throw new Error(\"GL context does not support color renderable floats\");\n      }\n    }\n    this.vertexBuffer = createVertexBuffer(this.gl);\n    this.indexBuffer = createIndexBuffer(this.gl);\n    this.framebuffer = createFramebuffer(this.gl);\n    this.textureConfig = getTextureConfig(this.gl, this.textureHalfFloatExtension);\n  }\n  get debug() {\n    return env().getBool(\"DEBUG\");\n  }\n  dispose() {\n    if (this.disposed) {\n      return;\n    }\n    if (this.program != null) {\n      console.warn(\"Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing.\");\n    }\n    if (this.outputTexture != null) {\n      console.warn(\"Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.\");\n    }\n    const gl = this.gl;\n    callAndCheck(gl, () => gl.finish());\n    callAndCheck(gl, () => gl.bindFramebuffer(gl.FRAMEBUFFER, null));\n    callAndCheck(gl, () => gl.deleteFramebuffer(this.framebuffer));\n    callAndCheck(gl, () => gl.bindBuffer(gl.ARRAY_BUFFER, null));\n    callAndCheck(gl, () => gl.bindBuffer(gl.ELEMENT_ARRAY_BUFFER, null));\n    callAndCheck(gl, () => gl.deleteBuffer(this.indexBuffer));\n    this.disposed = true;\n  }\n  createFloat32MatrixTexture(rows, columns) {\n    this.throwIfDisposed();\n    return createFloat32MatrixTexture(this.gl, rows, columns, this.textureConfig);\n  }\n  createFloat16MatrixTexture(rows, columns) {\n    this.throwIfDisposed();\n    return createFloat16MatrixTexture(this.gl, rows, columns, this.textureConfig);\n  }\n  createUnsignedBytesMatrixTexture(rows, columns) {\n    this.throwIfDisposed();\n    return createUnsignedBytesMatrixTexture(this.gl, rows, columns, this.textureConfig);\n  }\n  uploadPixelDataToTexture(texture, pixels) {\n    this.throwIfDisposed();\n    uploadPixelDataToTexture(this.gl, texture, pixels);\n  }\n  uploadDenseMatrixToTexture(texture, width, height, data) {\n    this.throwIfDisposed();\n    uploadDenseMatrixToTexture(this.gl, texture, width, height, data, this.textureConfig);\n  }\n  createFloat16PackedMatrixTexture(rows, columns) {\n    this.throwIfDisposed();\n    return createFloat16PackedMatrixTexture(this.gl, rows, columns, this.textureConfig);\n  }\n  createPackedMatrixTexture(rows, columns) {\n    this.throwIfDisposed();\n    return createPackedMatrixTexture(this.gl, rows, columns, this.textureConfig);\n  }\n  deleteMatrixTexture(texture) {\n    this.throwIfDisposed();\n    if (this.outputTexture === texture) {\n      unbindColorTextureFromFramebuffer(this.gl, this.framebuffer);\n      this.outputTexture = null;\n    }\n    callAndCheck(this.gl, () => this.gl.deleteTexture(texture));\n  }\n  downloadByteEncodedFloatMatrixFromOutputTexture(texture, rows, columns) {\n    return this.downloadMatrixDriver(texture, () => downloadByteEncodedFloatMatrixFromOutputTexture(this.gl, rows, columns, this.textureConfig));\n  }\n  downloadPackedMatrixFromBuffer(buffer2, batch, rows, columns, physicalRows, physicalCols) {\n    return downloadPackedMatrixFromBuffer(this.gl, buffer2, batch, rows, columns, physicalRows, physicalCols, this.textureConfig);\n  }\n  downloadFloat32MatrixFromBuffer(buffer2, size) {\n    return downloadFloat32MatrixFromBuffer(this.gl, buffer2, size);\n  }\n  createBufferFromTexture(texture, rows, columns) {\n    this.bindTextureToFrameBuffer(texture);\n    const result = createBufferFromOutputTexture(this.gl, rows, columns, this.textureConfig);\n    this.unbindTextureToFrameBuffer();\n    return result;\n  }\n  createAndWaitForFence() {\n    const fenceContext = this.createFence(this.gl);\n    return this.pollFence(fenceContext);\n  }\n  createFence(gl) {\n    let query;\n    let isFencePassed;\n    if (env().getBool(\"WEBGL_FENCE_API_ENABLED\")) {\n      const gl2 = gl;\n      const sync = gl2.fenceSync(gl2.SYNC_GPU_COMMANDS_COMPLETE, 0);\n      gl.flush();\n      isFencePassed = () => {\n        const status = gl2.clientWaitSync(sync, 0, 0);\n        return status === gl2.ALREADY_SIGNALED || status === gl2.CONDITION_SATISFIED;\n      };\n      query = sync;\n    } else if (env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\") > 0) {\n      query = this.beginQuery();\n      this.endQuery();\n      isFencePassed = () => this.isQueryAvailable(query, env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\"));\n    } else {\n      isFencePassed = () => true;\n    }\n    return { query, isFencePassed };\n  }\n  downloadMatrixFromPackedTexture(texture, physicalRows, physicalCols) {\n    return this.downloadMatrixDriver(texture, () => downloadMatrixFromPackedOutputTexture(this.gl, physicalRows, physicalCols));\n  }\n  createProgram(fragmentShader) {\n    this.throwIfDisposed();\n    const gl = this.gl;\n    if (this.vertexShader == null) {\n      this.vertexShader = createVertexShader2(gl);\n    }\n    const program = createProgram(gl);\n    callAndCheck(gl, () => gl.attachShader(program, this.vertexShader));\n    callAndCheck(gl, () => gl.attachShader(program, fragmentShader));\n    linkProgram(gl, program);\n    if (this.debug) {\n      validateProgram(gl, program);\n    }\n    if (!this.vertexAttrsAreBound) {\n      this.setProgram(program);\n      this.vertexAttrsAreBound = bindVertexProgramAttributeStreams(gl, this.program, this.vertexBuffer);\n    }\n    return program;\n  }\n  deleteProgram(program) {\n    this.throwIfDisposed();\n    if (program === this.program) {\n      this.program = null;\n    }\n    if (program != null) {\n      callAndCheck(this.gl, () => this.gl.deleteProgram(program));\n    }\n  }\n  setProgram(program) {\n    this.throwIfDisposed();\n    this.program = program;\n    if (this.program != null && this.debug) {\n      validateProgram(this.gl, this.program);\n    }\n    callAndCheck(this.gl, () => this.gl.useProgram(program));\n  }\n  getUniformLocation(program, uniformName, shouldThrow = true) {\n    this.throwIfDisposed();\n    if (shouldThrow) {\n      return getProgramUniformLocationOrThrow(this.gl, program, uniformName);\n    } else {\n      return getProgramUniformLocation(this.gl, program, uniformName);\n    }\n  }\n  getAttributeLocation(program, attribute) {\n    this.throwIfDisposed();\n    return callAndCheck(this.gl, () => this.gl.getAttribLocation(program, attribute));\n  }\n  getUniformLocationNoThrow(program, uniformName) {\n    this.throwIfDisposed();\n    return this.gl.getUniformLocation(program, uniformName);\n  }\n  setInputMatrixTexture(inputMatrixTexture, uniformLocation, textureUnit) {\n    this.throwIfDisposed();\n    this.throwIfNoProgram();\n    bindTextureToProgramUniformSampler(this.gl, inputMatrixTexture, uniformLocation, textureUnit);\n  }\n  setOutputMatrixTexture(outputMatrixTexture, rows, columns) {\n    this.setOutputMatrixTextureDriver(outputMatrixTexture, columns, rows);\n  }\n  setOutputPackedMatrixTexture(outputPackedMatrixTexture, rows, columns) {\n    this.throwIfDisposed();\n    const [width, height] = getPackedMatrixTextureShapeWidthHeight(rows, columns);\n    this.setOutputMatrixTextureDriver(outputPackedMatrixTexture, width, height);\n  }\n  setOutputMatrixWriteRegion(startRow, numRows, startColumn, numColumns) {\n    this.setOutputMatrixWriteRegionDriver(startColumn, startRow, numColumns, numRows);\n  }\n  setOutputPackedMatrixWriteRegion(startRow, numRows, startColumn, numColumns) {\n    throw new Error(\"setOutputPackedMatrixWriteRegion not implemented.\");\n  }\n  debugValidate() {\n    if (this.program != null) {\n      validateProgram(this.gl, this.program);\n    }\n    validateFramebuffer(this.gl);\n  }\n  executeProgram() {\n    this.throwIfDisposed();\n    this.throwIfNoProgram();\n    const gl = this.gl;\n    if (this.debug) {\n      this.debugValidate();\n    }\n    callAndCheck(gl, () => gl.drawElements(gl.TRIANGLES, 6, gl.UNSIGNED_SHORT, 0));\n  }\n  blockUntilAllProgramsCompleted() {\n    this.throwIfDisposed();\n    callAndCheck(this.gl, () => this.gl.finish());\n  }\n  getQueryTimerExtension() {\n    if (this.disjointQueryTimerExtension == null) {\n      this.disjointQueryTimerExtension = getExtensionOrThrow(this.gl, env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\") === 2 ? \"EXT_disjoint_timer_query_webgl2\" : \"EXT_disjoint_timer_query\");\n    }\n    return this.disjointQueryTimerExtension;\n  }\n  getQueryTimerExtensionWebGL2() {\n    return this.getQueryTimerExtension();\n  }\n  getQueryTimerExtensionWebGL1() {\n    return this.getQueryTimerExtension();\n  }\n  beginQuery() {\n    if (env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\") === 2) {\n      const gl2 = this.gl;\n      const ext2 = this.getQueryTimerExtensionWebGL2();\n      const query2 = gl2.createQuery();\n      gl2.beginQuery(ext2.TIME_ELAPSED_EXT, query2);\n      return query2;\n    }\n    const ext = this.getQueryTimerExtensionWebGL1();\n    const query = ext.createQueryEXT();\n    ext.beginQueryEXT(ext.TIME_ELAPSED_EXT, query);\n    return query;\n  }\n  endQuery() {\n    if (env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\") === 2) {\n      const gl2 = this.gl;\n      const ext2 = this.getQueryTimerExtensionWebGL2();\n      gl2.endQuery(ext2.TIME_ELAPSED_EXT);\n      return;\n    }\n    const ext = this.getQueryTimerExtensionWebGL1();\n    ext.endQueryEXT(ext.TIME_ELAPSED_EXT);\n  }\n  async waitForQueryAndGetTime(query) {\n    await util_exports.repeatedTry(() => this.disposed || this.isQueryAvailable(query, env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\")));\n    return this.getQueryTime(query, env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION\"));\n  }\n  getQueryTime(query, queryTimerVersion) {\n    if (queryTimerVersion === 0) {\n      return null;\n    }\n    if (queryTimerVersion === 2) {\n      const gl2 = this.gl;\n      const timeElapsedNanos = gl2.getQueryParameter(query, gl2.QUERY_RESULT);\n      return timeElapsedNanos / 1e6;\n    } else {\n      const ext = this.getQueryTimerExtensionWebGL1();\n      const timeElapsedNanos = ext.getQueryObjectEXT(query, ext.QUERY_RESULT_EXT);\n      return timeElapsedNanos / 1e6;\n    }\n  }\n  isQueryAvailable(query, queryTimerVersion) {\n    if (queryTimerVersion === 0) {\n      return true;\n    }\n    if (queryTimerVersion === 2) {\n      const gl2 = this.gl;\n      const ext = this.getQueryTimerExtensionWebGL2();\n      const available = gl2.getQueryParameter(query, gl2.QUERY_RESULT_AVAILABLE);\n      if (this.disjoint == null) {\n        this.disjoint = this.gl.getParameter(ext.GPU_DISJOINT_EXT);\n      }\n      return available && !this.disjoint;\n    } else {\n      const ext = this.getQueryTimerExtensionWebGL1();\n      const available = ext.getQueryObjectEXT(query, ext.QUERY_RESULT_AVAILABLE_EXT);\n      if (this.disjoint == null) {\n        this.disjoint = this.gl.getParameter(ext.GPU_DISJOINT_EXT);\n      }\n      return available && !this.disjoint;\n    }\n  }\n  pollFence(fenceContext) {\n    return new Promise((resolve) => {\n      this.addItemToPoll(() => fenceContext.isFencePassed(), () => resolve());\n    });\n  }\n  pollItems() {\n    const index = linearSearchLastTrue(this.itemsToPoll.map((x) => x.isDoneFn));\n    for (let i2 = 0; i2 <= index; ++i2) {\n      const { resolveFn } = this.itemsToPoll[i2];\n      resolveFn();\n    }\n    this.itemsToPoll = this.itemsToPoll.slice(index + 1);\n  }\n  addItemToPoll(isDoneFn, resolveFn) {\n    this.itemsToPoll.push({ isDoneFn, resolveFn });\n    if (this.itemsToPoll.length > 1) {\n      return;\n    }\n    util_exports.repeatedTry(() => {\n      this.pollItems();\n      return this.itemsToPoll.length === 0;\n    });\n  }\n  bindTextureToFrameBuffer(texture) {\n    this.throwIfDisposed();\n    bindColorTextureToFramebuffer(this.gl, texture, this.framebuffer);\n    if (this.debug) {\n      validateFramebuffer(this.gl);\n    }\n  }\n  unbindTextureToFrameBuffer() {\n    if (this.outputTexture != null) {\n      bindColorTextureToFramebuffer(this.gl, this.outputTexture, this.framebuffer);\n      if (this.debug) {\n        validateFramebuffer(this.gl);\n      }\n    } else {\n      unbindColorTextureFromFramebuffer(this.gl, this.framebuffer);\n    }\n  }\n  downloadMatrixDriver(texture, downloadAndDecode) {\n    this.bindTextureToFrameBuffer(texture);\n    const result = downloadAndDecode();\n    this.unbindTextureToFrameBuffer();\n    return result;\n  }\n  setOutputMatrixTextureDriver(outputMatrixTextureMaybePacked, width, height) {\n    this.throwIfDisposed();\n    const gl = this.gl;\n    bindColorTextureToFramebuffer(gl, outputMatrixTextureMaybePacked, this.framebuffer);\n    if (this.debug) {\n      validateFramebuffer(gl);\n    }\n    this.outputTexture = outputMatrixTextureMaybePacked;\n    callAndCheck(gl, () => gl.viewport(0, 0, width, height));\n    callAndCheck(gl, () => gl.scissor(0, 0, width, height));\n  }\n  setOutputMatrixWriteRegionDriver(x, y, width, height) {\n    this.throwIfDisposed();\n    callAndCheck(this.gl, () => this.gl.scissor(x, y, width, height));\n  }\n  throwIfDisposed() {\n    if (this.disposed) {\n      throw new Error(\"Attempted to use disposed GPGPUContext.\");\n    }\n  }\n  throwIfNoProgram() {\n    if (this.program == null) {\n      throw new Error(\"No GPU program is currently set.\");\n    }\n  }\n};\nfunction linearSearchLastTrue(arr) {\n  let i2 = 0;\n  for (; i2 < arr.length; ++i2) {\n    const isDone = arr[i2]();\n    if (!isDone) {\n      break;\n    }\n  }\n  return i2 - 1;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/shared.js\nvar { addImpl: addImplCPU, bincountImpl: bincountImplCPU, bincountReduceImpl: bincountReduceImplCPU, ceilImpl: ceilImplCPU, concatImpl: concatImplCPU, equalImpl: equalImplCPU, expImpl: expImplCPU, expm1Impl: expm1ImplCPU, floorImpl: floorImplCPU, gatherNdImpl: gatherNdImplCPU, gatherV2Impl: gatherV2ImplCPU, greaterImpl: greaterImplCPU, greaterEqualImpl: greaterEqualImplCPU, lessImpl: lessImplCPU, lessEqualImpl: lessEqualImplCPU, linSpaceImpl: linSpaceImplCPU, logImpl: logImplCPU, maxImpl: maxImplCPU, maximumImpl: maximumImplCPU, minimumImpl: minimumImplCPU, multiplyImpl: multiplyImplCPU, negImpl: negImplCPU, notEqualImpl: notEqualImplCPU, prodImpl: prodImplCPU, rangeImpl: rangeImplCPU, rsqrtImpl: rsqrtImplCPU, scatterImpl: scatterImplCPU, sigmoidImpl: sigmoidImplCPU, simpleAbsImpl: simpleAbsImplCPU, sliceImpl: sliceImplCPU, sparseFillEmptyRowsImpl: sparseFillEmptyRowsImplCPU, sparseReshapeImpl: sparseReshapeImplCPU, sparseSegmentReductionImpl: sparseSegmentReductionImplCPU, sqrtImpl: sqrtImplCPU, stridedSliceImpl: stridedSliceImplCPU, stringNGramsImpl: stringNGramsImplCPU, stringSplitImpl: stringSplitImplCPU, stringToHashBucketFastImpl: stringToHashBucketFastImplCPU, subImpl: subImplCPU, tileImpl: tileImplCPU, topKImpl: topKImplCPU, transposeImpl: transposeImplCPU, uniqueImpl: uniqueImplCPU } = shared_exports;\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/packing_util.js\nfunction getVecChannels(name, rank) {\n  return [\"x\", \"y\", \"z\", \"w\", \"u\", \"v\"].slice(0, rank).map((d) => `${name}.${d}`);\n}\nfunction getChannels(name, rank) {\n  if (rank === 1) {\n    return [name];\n  }\n  return getVecChannels(name, rank);\n}\nfunction getSourceCoords(rank, dims) {\n  if (rank === 1) {\n    return \"rc\";\n  }\n  let coords3 = \"\";\n  for (let i2 = 0; i2 < rank; i2++) {\n    coords3 += dims[i2];\n    if (i2 < rank - 1) {\n      coords3 += \",\";\n    }\n  }\n  return coords3;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/pack_gpu.js\nvar PackProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = false;\n    this.packedOutput = true;\n    this.outputShape = outputShape;\n    this.rank = outputShape.length;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    if (this.rank === 0) {\n      this.userCode = `\n        void main() {\n          setOutput(vec4(getA(), 0., 0., 0.));\n        }\n      `;\n    } else {\n      const channels = getChannels(\"rc\", this.rank);\n      const dtype = getCoordsDataType(this.rank);\n      const outOfBoundsCondition = this.getOutOfBoundsCondition(channels);\n      const setup51 = this.getSetup(channels);\n      const output = this.getOutput(channels);\n      this.userCode = `\n        void main() {\n          ${dtype} rc = getOutputCoords();\n\n          if(${outOfBoundsCondition}) {\n            setOutput(vec4(0));\n          } else {\n            ${setup51}\n\n            setOutput(vec4(${output}));\n          }\n        }\n      `;\n    }\n  }\n  getSourceCoordsArr(dims) {\n    const coords3 = [];\n    for (let row = 0; row <= 1; row++) {\n      for (let col = 0; col <= 1; col++) {\n        let coord = `${row === 0 ? \"r\" : \"rp1\"}, ${col === 0 ? \"c\" : \"cp1\"}`;\n        for (let d = 2; d < this.rank; d++) {\n          coord = `${dims[dims.length - 1 - d]},` + coord;\n        }\n        coords3.push(coord);\n      }\n    }\n    return coords3;\n  }\n  getOutOfBoundsCondition(dims) {\n    if (this.rank === 1) {\n      return `rc > ${this.enableShapeUniforms ? \"outShape\" : this.outputShape[0]}`;\n    }\n    let cond = \"\";\n    for (let i2 = this.rank - 2; i2 < this.rank; i2++) {\n      cond += `${dims[i2]} >= ${this.enableShapeUniforms ? `outShape[${i2}]` : this.outputShape[i2]}`;\n      if (i2 < this.rank - 1) {\n        cond += \"||\";\n      }\n    }\n    return cond;\n  }\n  getSetup(dims) {\n    if (this.rank === 1) {\n      return \"\";\n    }\n    const innerDims = dims.slice(-2);\n    const col = this.enableShapeUniforms ? `outShape[${this.rank} - 1]` : this.outputShape[this.rank - 1];\n    const row = this.enableShapeUniforms ? `outShape[${this.rank} - 2]` : this.outputShape[this.rank - 2];\n    return `\n      int r = ${innerDims[0]};\n      int c = ${innerDims[1]};\n      int rp1 = r + 1;\n      int cp1 = c + 1;\n\n      bool cEdge = cp1 >= ${col};\n      bool rEdge = rp1 >= ${row};\n    `;\n  }\n  getOutput(dims) {\n    const sourceCoords = this.getSourceCoordsArr(dims);\n    if (this.rank === 1) {\n      const outShape = this.enableShapeUniforms ? \"outShape\" : this.outputShape[0];\n      return `getA(rc), (rc + 1 >= ${outShape} ? 0. : getA(rc + 1)), 0, 0`;\n    }\n    return `getA(${sourceCoords[0]}),\n            cEdge ? 0. : getA(${sourceCoords[1]}),\n            rEdge ? 0. : getA(${sourceCoords[2]}),\n            rEdge || cEdge ? 0. : getA(${sourceCoords[3]})`;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/reshape_packed_gpu.js\nvar ReshapePackedProgram = class {\n  constructor(outputShape, inputShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.customUniforms = [{ name: \"inputShape\", type: \"ivec3\" }];\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    let mainLoop = ``;\n    for (let i2 = 0; i2 < 4; i2++) {\n      let thisRC = `thisRC = rc;`;\n      if (i2 % 2 === 1) {\n        thisRC += `thisRC.z += 1;`;\n      }\n      if (i2 > 1) {\n        thisRC += `thisRC.y += 1;`;\n      }\n      mainLoop += `\n        ${thisRC}\n        ${i2 > 0 ? `if(thisRC.y < rows && thisRC.z < cols){` : \"\"}\n          int flatIndex = getFlatIndex(thisRC);\n\n          ivec3 inputRC = inputCoordsFromReshapedOutCoords(flatIndex);\n          vec2 inputRCInnerDims = vec2(float(inputRC.y),float(inputRC.z));\n\n          result[${i2}] =\n            getChannel(getA(inputRC.x, inputRC.y, inputRC.z), inputRCInnerDims);\n        ${i2 > 0 ? \"}\" : \"\"}\n      `;\n    }\n    this.userCode = `\n      ${getReshapedInputCoords(inputShape, this.enableShapeUniforms)}\n      ${this.enableShapeUniforms ? getFlatIndexFrom3DOutput() : getFlatIndexFrom3D(outputShape)}\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n\n        vec4 result = vec4(0.);\n\n        ivec3 thisRC;\n        int rows = ${this.enableShapeUniforms ? \"outShape[1]\" : outputShape[1]};\n        int cols = ${this.enableShapeUniforms ? \"outShape[2]\" : outputShape[2]};\n\n        ${mainLoop}\n\n        setOutput(result);\n      }\n    `;\n  }\n};\nfunction getReshapedInputCoords(shape, enableShapeUniforms) {\n  const coordsFromIndexSnippet = enableShapeUniforms ? getLogicalCoordinatesFromFlatIndexByUniform([\"r\", \"c\", \"d\"], \"inputShape\") : getLogicalCoordinatesFromFlatIndex([\"r\", \"c\", \"d\"], shape);\n  return `\n    ivec3 inputCoordsFromReshapedOutCoords(int index) {\n      ${coordsFromIndexSnippet}\n      return ivec3(r, c, d);\n    }\n  `;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/texture_manager.js\nvar TextureManager = class {\n  constructor(gpgpu) {\n    this.gpgpu = gpgpu;\n    this.numUsedTextures = 0;\n    this.numFreeTextures = 0;\n    this._numBytesAllocated = 0;\n    this._numBytesFree = 0;\n    this.freeTextures = {};\n    this.logEnabled = false;\n    this.usedTextures = {};\n  }\n  acquireTexture(shapeRC, usage, isPacked) {\n    const physicalTexType = getPhysicalFromLogicalTextureType(usage, isPacked);\n    const shapeKey = getKeyFromTextureShape(shapeRC, physicalTexType, isPacked);\n    if (!(shapeKey in this.freeTextures)) {\n      this.freeTextures[shapeKey] = [];\n    }\n    if (!(shapeKey in this.usedTextures)) {\n      this.usedTextures[shapeKey] = [];\n    }\n    const texBytes = computeBytes(shapeRC, physicalTexType, this.gpgpu.gl, this.gpgpu.textureConfig, isPacked);\n    if (this.freeTextures[shapeKey].length > 0) {\n      this.numFreeTextures--;\n      this.numUsedTextures++;\n      this._numBytesFree -= texBytes;\n      this.log();\n      const newTexture2 = this.freeTextures[shapeKey].shift();\n      this.usedTextures[shapeKey].push(newTexture2);\n      return newTexture2;\n    }\n    let newTexture;\n    if (physicalTexType === PhysicalTextureType.PACKED_2X2_FLOAT32) {\n      newTexture = this.gpgpu.createPackedMatrixTexture(shapeRC[0], shapeRC[1]);\n    } else if (physicalTexType === PhysicalTextureType.PACKED_2X2_FLOAT16) {\n      newTexture = this.gpgpu.createFloat16PackedMatrixTexture(shapeRC[0], shapeRC[1]);\n    } else if (physicalTexType === PhysicalTextureType.UNPACKED_FLOAT32) {\n      newTexture = this.gpgpu.createFloat32MatrixTexture(shapeRC[0], shapeRC[1]);\n    } else if (physicalTexType === PhysicalTextureType.UNPACKED_FLOAT16) {\n      newTexture = this.gpgpu.createFloat16MatrixTexture(shapeRC[0], shapeRC[1]);\n    } else if (physicalTexType === PhysicalTextureType.PACKED_4X1_UNSIGNED_BYTE) {\n      newTexture = this.gpgpu.createUnsignedBytesMatrixTexture(shapeRC[0], shapeRC[1]);\n    }\n    this.usedTextures[shapeKey].push(newTexture);\n    this.numUsedTextures++;\n    this._numBytesAllocated += texBytes;\n    this.log();\n    return newTexture;\n  }\n  releaseTexture(texture, shape, logicalTexType, isPacked) {\n    if (this.freeTextures == null) {\n      return;\n    }\n    const physicalTexType = getPhysicalFromLogicalTextureType(logicalTexType, isPacked);\n    const shapeKey = getKeyFromTextureShape(shape, physicalTexType, isPacked);\n    if (!(shapeKey in this.freeTextures)) {\n      this.freeTextures[shapeKey] = [];\n    }\n    const texBytes = computeBytes(shape, physicalTexType, this.gpgpu.gl, this.gpgpu.textureConfig, isPacked);\n    const deleteTexThreshold = env().get(\"WEBGL_DELETE_TEXTURE_THRESHOLD\");\n    if (deleteTexThreshold !== -1 && this._numBytesAllocated > deleteTexThreshold) {\n      this.gpgpu.deleteMatrixTexture(texture.texture);\n      this._numBytesAllocated -= texBytes;\n    } else {\n      this.freeTextures[shapeKey].push(texture);\n      this.numFreeTextures++;\n      this._numBytesFree += texBytes;\n    }\n    this.numUsedTextures--;\n    const texList = this.usedTextures[shapeKey];\n    const texIndex = texList.indexOf(texture);\n    if (texIndex < 0) {\n      throw new Error(\"Cannot release a texture that was never provided by this texture manager\");\n    }\n    texList.splice(texIndex, 1);\n    this.log();\n  }\n  log() {\n    if (!this.logEnabled) {\n      return;\n    }\n    const total = this.numFreeTextures + this.numUsedTextures;\n    console.log(\"Free/Used\", `${this.numFreeTextures} / ${this.numUsedTextures}`, `(${total})`);\n    const freeRatio = this._numBytesFree / this._numBytesAllocated;\n    console.log(`Bytes allocated: ${this._numBytesAllocated}`);\n    console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100 * freeRatio)}%)`);\n  }\n  get numBytesAllocated() {\n    return this._numBytesAllocated;\n  }\n  get numBytesFree() {\n    return this._numBytesFree;\n  }\n  getNumUsedTextures() {\n    return this.numUsedTextures;\n  }\n  getNumFreeTextures() {\n    return this.numFreeTextures;\n  }\n  dispose() {\n    if (this.freeTextures == null) {\n      return;\n    }\n    for (const texShape in this.freeTextures) {\n      this.freeTextures[texShape].forEach((tex) => {\n        this.gpgpu.deleteMatrixTexture(tex.texture);\n      });\n    }\n    for (const texShape in this.usedTextures) {\n      this.usedTextures[texShape].forEach((tex) => {\n        this.gpgpu.deleteMatrixTexture(tex.texture);\n      });\n    }\n    this.freeTextures = null;\n    this.usedTextures = null;\n    this.numUsedTextures = 0;\n    this.numFreeTextures = 0;\n    this._numBytesAllocated = 0;\n    this._numBytesFree = 0;\n  }\n};\nfunction numBytesForInternalFormat(gl, internalFormat) {\n  const glany = gl;\n  if (internalFormat === glany.R32F) {\n    return 4;\n  } else if (internalFormat === glany.R16F) {\n    return 2;\n  } else if (internalFormat === glany.RGBA32F) {\n    return 16;\n  } else if (internalFormat === gl.RGBA) {\n    return 16;\n  } else if (internalFormat === glany.RGBA16F) {\n    return 8;\n  } else if (internalFormat === glany.RGBA8) {\n    return 4;\n  }\n  throw new Error(`Unknown internal format ${internalFormat}`);\n}\nfunction computeBytes(shape, physicalTexType, gl, textureConfig, isPacked) {\n  const internalFormat = internalFormatForPhysicalTexType(physicalTexType, textureConfig);\n  let numElements;\n  if (isPacked) {\n    const [packedWidth, packedHeight] = getPackedMatrixTextureShapeWidthHeight(shape[0], shape[1]);\n    numElements = packedWidth * packedHeight;\n  } else {\n    const [width, height] = getUnpackedMatrixTextureShapeWidthHeight(shape[0], shape[1]);\n    numElements = width * height;\n  }\n  const bytesPerElement2 = numBytesForInternalFormat(gl, internalFormat);\n  return numElements * bytesPerElement2;\n}\nfunction internalFormatForPhysicalTexType(physicalTexType, textureConfig) {\n  switch (physicalTexType) {\n    case PhysicalTextureType.PACKED_2X2_FLOAT32:\n      return getInternalFormatForPackedMatrixTexture(textureConfig);\n    case PhysicalTextureType.PACKED_2X2_FLOAT16:\n      return getInternalFormatForFloat16PackedMatrixTexture(textureConfig);\n    case PhysicalTextureType.UNPACKED_FLOAT32:\n      return getInternalFormatForFloat32MatrixTexture(textureConfig);\n    case PhysicalTextureType.UNPACKED_FLOAT16:\n      return getInternalFormatForFloat16MatrixTexture(textureConfig);\n    case PhysicalTextureType.PACKED_4X1_UNSIGNED_BYTE:\n      return getInternalFormatForUnsignedBytesMatrixTexture(textureConfig);\n    default:\n      throw new Error(`Unknown physical texture type ${physicalTexType}`);\n  }\n}\nfunction getPhysicalTextureForRendering(isPacked) {\n  if (env().getBool(\"WEBGL_RENDER_FLOAT32_ENABLED\")) {\n    if (isPacked) {\n      return PhysicalTextureType.PACKED_2X2_FLOAT32;\n    }\n    return PhysicalTextureType.UNPACKED_FLOAT32;\n  }\n  if (isPacked) {\n    return PhysicalTextureType.PACKED_2X2_FLOAT16;\n  }\n  return PhysicalTextureType.UNPACKED_FLOAT16;\n}\nfunction getPhysicalFromLogicalTextureType(logicalTexType, isPacked) {\n  if (logicalTexType === TextureUsage.UPLOAD) {\n    return PhysicalTextureType.PACKED_2X2_FLOAT32;\n  } else if (logicalTexType === TextureUsage.RENDER || logicalTexType == null) {\n    return getPhysicalTextureForRendering(isPacked);\n  } else if (logicalTexType === TextureUsage.DOWNLOAD || logicalTexType === TextureUsage.PIXELS) {\n    return PhysicalTextureType.PACKED_4X1_UNSIGNED_BYTE;\n  }\n  throw new Error(`Unknown logical texture type ${logicalTexType}`);\n}\nfunction getKeyFromTextureShape(shapeRowsCol, physicalTexType, isPacked) {\n  return `${shapeRowsCol[0]}_${shapeRowsCol[1]}_${physicalTexType}_${isPacked}`;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/unaryop_gpu.js\nvar UnaryOpProgram = class {\n  constructor(aShape, opSnippet) {\n    this.variableNames = [\"A\"];\n    this.outputShape = aShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    this.userCode = `\n      float unaryOperation(float x) {\n        ${opSnippet}\n      }\n\n      void main() {\n        float x = getAAtOutCoords();\n        float y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    `;\n  }\n};\nvar CHECK_NAN_SNIPPET = `if (isnan(x)) return x;`;\nvar LINEAR = `return x;`;\nvar ABS = `return abs(x);`;\nvar ELU2 = `return (x >= 0.0) ? x : (exp(x) - 1.0);`;\nvar RELU = CHECK_NAN_SNIPPET + `\n  return (x < 0.0) ? 0.0 : x;\n`;\nvar RELU6 = CHECK_NAN_SNIPPET + `\n  return (x < 0.0) ? 0.0 : min(6.0, x);\n`;\nvar CLONE = \"return x;\";\nvar SIGMOID = `return 1.0 / (1.0 + exp(-1.0 * x));`;\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/unaryop_packed_gpu.js\nvar LINEAR2 = `return x;`;\nvar ELU3 = `\n  vec4 result;\n\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\n\n  return result;\n`;\nvar RELU2 = `\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n`;\nvar RELU62 = `\n  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n`;\nvar SIGMOID2 = `return 1.0 / (1.0 + exp(-1.0 * x));`;\nvar UnaryOpPackedProgram = class {\n  constructor(aShape, opSnippet) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = aShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    this.userCode = `\n      vec4 unaryOperation(vec4 x) {\n        ${opSnippet}\n      }\n\n      void main() {\n        vec4 x = getAAtOutCoords();\n        vec4 y = unaryOperation(x);\n\n        setOutput(y);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/unpack_gpu.js\nvar UnpackProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = false;\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    const rank = outputShape.length;\n    const channels = getChannels(\"rc\", rank);\n    const dtype = getCoordsDataType(rank);\n    const sourceCoords = getSourceCoords(rank, channels);\n    const innerDims = channels.slice(-2);\n    const coords3 = rank <= 1 ? \"rc\" : `vec2(${innerDims.join(\",\")})`;\n    this.userCode = `\n      void main() {\n        ${dtype} rc = getOutputCoords();\n        vec4 packedInput = getA(${sourceCoords});\n\n        setOutput(getChannel(packedInput, ${coords3}));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/backend_webgl.js\nvar whereImpl3 = kernel_impls_exports.whereImpl;\nvar EPSILON_FLOAT322 = 1e-7;\nvar EPSILON_FLOAT162 = 1e-4;\nvar binaryCaches = {};\nfunction getBinaryCache(webGLVersion) {\n  if (webGLVersion in binaryCaches) {\n    return binaryCaches[webGLVersion];\n  }\n  binaryCaches[webGLVersion] = {};\n  return binaryCaches[webGLVersion];\n}\nvar CPU_HANDOFF_SIZE_THRESHOLD = env().getNumber(\"CPU_HANDOFF_SIZE_THRESHOLD\");\nvar BEFORE_PAGING_CONSTANT = 600;\nfunction numMBBeforeWarning() {\n  if (env().global.screen == null) {\n    return 1024;\n  }\n  return env().global.screen.height * env().global.screen.width * window.devicePixelRatio * BEFORE_PAGING_CONSTANT / 1024 / 1024;\n}\nvar MathBackendWebGL = class extends KernelBackend {\n  constructor(gpuResource) {\n    super();\n    this.pendingRead = /* @__PURE__ */ new WeakMap();\n    this.pendingDisposal = /* @__PURE__ */ new WeakSet();\n    this.dataRefCount = /* @__PURE__ */ new WeakMap();\n    this.numBytesInGPU = 0;\n    this.uploadWaitMs = 0;\n    this.downloadWaitMs = 0;\n    this.lastGlFlushTime = 0;\n    this.warnedAboutMemory = false;\n    this.pendingDeletes = 0;\n    this.disposed = false;\n    if (!env().getBool(\"HAS_WEBGL\")) {\n      throw new Error(\"WebGL is not supported on this device\");\n    }\n    let newGPGPU;\n    if (gpuResource != null) {\n      if (gpuResource instanceof GPGPUContext) {\n        newGPGPU = gpuResource;\n      } else {\n        const gl = getWebGLContext(env().getNumber(\"WEBGL_VERSION\"), gpuResource);\n        newGPGPU = new GPGPUContext(gl);\n      }\n      this.binaryCache = {};\n      this.gpgpuCreatedLocally = false;\n    } else {\n      const gl = getWebGLContext(env().getNumber(\"WEBGL_VERSION\"));\n      newGPGPU = new GPGPUContext(gl);\n      this.binaryCache = getBinaryCache(env().getNumber(\"WEBGL_VERSION\"));\n      this.gpgpuCreatedLocally = true;\n    }\n    this.gpgpu = newGPGPU;\n    this.canvas = this.gpgpu.gl.canvas;\n    this.textureManager = new TextureManager(this.gpgpu);\n    this.numMBBeforeWarning = numMBBeforeWarning();\n    this.texData = new DataStorage(this, engine());\n  }\n  nextDataId() {\n    return MathBackendWebGL.nextDataId++;\n  }\n  numDataIds() {\n    return this.texData.numDataIds() - this.pendingDeletes;\n  }\n  write(values, shape, dtype) {\n    if (env().getBool(\"WEBGL_CHECK_NUMERICAL_PROBLEMS\") || env().getBool(\"DEBUG\")) {\n      this.checkNumericalProblems(values);\n    }\n    if (dtype === \"complex64\" && values != null) {\n      throw new Error(`Cannot write to a complex64 dtype. Please use tf.complex(real, imag).`);\n    }\n    const dataId = { id: this.nextDataId() };\n    this.texData.set(dataId, { shape, dtype, values, usage: TextureUsage.UPLOAD, refCount: 1 });\n    return dataId;\n  }\n  refCount(dataId) {\n    if (this.texData.has(dataId)) {\n      const tensorData = this.texData.get(dataId);\n      return tensorData.refCount;\n    }\n    return 0;\n  }\n  incRef(dataId) {\n    const texData = this.texData.get(dataId);\n    texData.refCount++;\n  }\n  decRef(dataId) {\n    if (this.texData.has(dataId)) {\n      const texData = this.texData.get(dataId);\n      texData.refCount--;\n    }\n  }\n  move(dataId, values, shape, dtype, refCount) {\n    if (env().getBool(\"DEBUG\")) {\n      this.checkNumericalProblems(values);\n    }\n    if (dtype === \"complex64\") {\n      throw new Error(`Cannot write to a complex64 dtype. Please use tf.complex(real, imag).`);\n    }\n    this.texData.set(dataId, { shape, dtype, values, usage: TextureUsage.UPLOAD, refCount });\n  }\n  disposeIntermediateTensorInfo(tensorInfo) {\n    this.disposeData(tensorInfo.dataId);\n  }\n  readSync(dataId) {\n    const texData = this.texData.get(dataId);\n    const { values, dtype, complexTensorInfos, slice: slice6, shape, isPacked } = texData;\n    if (slice6 != null) {\n      let program;\n      if (isPacked) {\n        program = new UnaryOpPackedProgram(shape, CLONE);\n      } else {\n        program = new UnaryOpProgram(shape, CLONE);\n      }\n      const res = this.runWebGLProgram(program, [{ dataId, shape, dtype }], dtype);\n      const data = this.readSync(res.dataId);\n      this.disposeIntermediateTensorInfo(res);\n      return data;\n    }\n    if (values != null) {\n      return this.convertAndCacheOnCPU(dataId);\n    }\n    if (dtype === \"string\") {\n      return values;\n    }\n    const shouldTimeProgram = this.activeTimers != null;\n    let start;\n    if (shouldTimeProgram) {\n      start = util_exports.now();\n    }\n    let result;\n    if (dtype === \"complex64\") {\n      const realValues = this.readSync(complexTensorInfos.real.dataId);\n      const imagValues = this.readSync(complexTensorInfos.imag.dataId);\n      result = backend_util_exports.mergeRealAndImagArrays(realValues, imagValues);\n    } else {\n      result = this.getValuesFromTexture(dataId);\n    }\n    if (shouldTimeProgram) {\n      this.downloadWaitMs += util_exports.now() - start;\n    }\n    return this.convertAndCacheOnCPU(dataId, result);\n  }\n  async read(dataId) {\n    if (this.pendingRead.has(dataId)) {\n      const subscribers2 = this.pendingRead.get(dataId);\n      return new Promise((resolve) => subscribers2.push(resolve));\n    }\n    const texData = this.texData.get(dataId);\n    const { values, shape, slice: slice6, dtype, complexTensorInfos, isPacked } = texData;\n    if (slice6 != null) {\n      let program;\n      if (isPacked) {\n        program = new UnaryOpPackedProgram(shape, CLONE);\n      } else {\n        program = new UnaryOpProgram(shape, CLONE);\n      }\n      const res = this.runWebGLProgram(program, [{ dataId, shape, dtype }], dtype);\n      const data = this.read(res.dataId);\n      this.disposeIntermediateTensorInfo(res);\n      return data;\n    }\n    if (values != null) {\n      return this.convertAndCacheOnCPU(dataId);\n    }\n    if (env().getBool(\"DEBUG\")) {\n      if (!env().getBool(\"WEBGL_DOWNLOAD_FLOAT_ENABLED\") && env().getNumber(\"WEBGL_VERSION\") === 2) {\n        throw new Error(`tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.`);\n      }\n    }\n    let buffer2 = null;\n    let tmpDownloadTarget;\n    if (dtype !== \"complex64\" && env().get(\"WEBGL_BUFFER_SUPPORTED\")) {\n      tmpDownloadTarget = this.decode(dataId);\n      const tmpData = this.texData.get(tmpDownloadTarget.dataId);\n      buffer2 = this.gpgpu.createBufferFromTexture(tmpData.texture.texture, ...getDenseTexShape(shape));\n    }\n    this.pendingRead.set(dataId, []);\n    if (dtype !== \"complex64\") {\n      await this.gpgpu.createAndWaitForFence();\n    }\n    let vals;\n    if (dtype === \"complex64\") {\n      const ps = await Promise.all([\n        this.read(complexTensorInfos.real.dataId),\n        this.read(complexTensorInfos.imag.dataId)\n      ]);\n      const realValues = ps[0];\n      const imagValues = ps[1];\n      vals = backend_util_exports.mergeRealAndImagArrays(realValues, imagValues);\n    } else if (buffer2 == null) {\n      vals = this.getValuesFromTexture(dataId);\n    } else {\n      const size = util_exports.sizeFromShape(shape);\n      vals = this.gpgpu.downloadFloat32MatrixFromBuffer(buffer2, size);\n    }\n    if (tmpDownloadTarget != null) {\n      this.disposeIntermediateTensorInfo(tmpDownloadTarget);\n    }\n    if (buffer2 != null) {\n      const gl = this.gpgpu.gl;\n      callAndCheck(gl, () => gl.deleteBuffer(buffer2));\n    }\n    const dTypeVals = this.convertAndCacheOnCPU(dataId, vals);\n    const subscribers = this.pendingRead.get(dataId);\n    this.pendingRead.delete(dataId);\n    subscribers.forEach((resolve) => resolve(dTypeVals));\n    if (this.pendingDisposal.has(dataId)) {\n      this.pendingDisposal.delete(dataId);\n      if (this.disposeData(dataId)) {\n        engine().removeDataId(dataId, this);\n      }\n      this.pendingDeletes--;\n    }\n    return dTypeVals;\n  }\n  readToGPU(dataId, options = {}) {\n    const texData = this.texData.get(dataId);\n    const { values, shape, slice: slice6, dtype, isPacked, texture } = texData;\n    if (dtype === \"complex64\") {\n      throw new Error(\"Does not support reading texture for complex64 dtype.\");\n    }\n    if (slice6 != null) {\n      let program;\n      if (isPacked) {\n        program = new UnaryOpPackedProgram(shape, CLONE);\n      } else {\n        program = new UnaryOpProgram(shape, CLONE);\n      }\n      const res = this.runWebGLProgram(program, [{ dataId, shape, dtype }], dtype);\n      const gpuResouorce = this.readToGPU(res, options);\n      this.disposeIntermediateTensorInfo(res);\n      return gpuResouorce;\n    }\n    if (texture == null) {\n      if (values != null) {\n        throw new Error(\"Data is not on GPU but on CPU.\");\n      } else {\n        throw new Error(\"There is no data on GPU or CPU.\");\n      }\n    }\n    const tmpTarget = this.decode(dataId, options.customTexShape);\n    const tensorRef = engine().makeTensorFromTensorInfo(tmpTarget);\n    const tmpData = this.texData.get(tmpTarget.dataId);\n    return Object.assign({ tensorRef }, tmpData.texture);\n  }\n  bufferSync(t2) {\n    const data = this.readSync(t2.dataId);\n    if (t2.dtype === \"string\") {\n      try {\n        const strings = data.map((d) => util_exports.decodeString(d));\n        return buffer(t2.shape, t2.dtype, strings);\n      } catch (_a) {\n        throw new Error(\"Failed to decode encoded string bytes into utf-8\");\n      }\n    }\n    return buffer(t2.shape, t2.dtype, data);\n  }\n  checkNumericalProblems(values) {\n    if (values == null) {\n      return;\n    }\n    for (let i2 = 0; i2 < values.length; i2++) {\n      const num = values[i2];\n      if (!canBeRepresented(num)) {\n        if (env().getBool(\"WEBGL_RENDER_FLOAT32_CAPABLE\")) {\n          throw Error(`The value ${num} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`);\n        }\n        throw Error(`The value ${num} cannot be represented on this device.`);\n      }\n    }\n  }\n  getValuesFromTexture(dataId) {\n    const { shape, dtype, isPacked } = this.texData.get(dataId);\n    const size = util_exports.sizeFromShape(shape);\n    if (env().getBool(\"WEBGL_DOWNLOAD_FLOAT_ENABLED\")) {\n      const tmpTarget = this.decode(dataId);\n      const tmpData2 = this.texData.get(tmpTarget.dataId);\n      const vals2 = this.gpgpu.downloadMatrixFromPackedTexture(tmpData2.texture.texture, ...getDenseTexShape(shape)).subarray(0, size);\n      this.disposeIntermediateTensorInfo(tmpTarget);\n      return vals2;\n    }\n    const shouldUsePackedProgram = env().getBool(\"WEBGL_PACK\") && isPacked === true;\n    const outputShape = shouldUsePackedProgram ? getShapeAs3D(shape) : shape;\n    const program = shouldUsePackedProgram ? new EncodeFloatPackedProgram(outputShape) : new EncodeFloatProgram(outputShape);\n    const output = this.runWebGLProgram(program, [{ shape: outputShape, dtype, dataId }], \"float32\");\n    const tmpData = this.texData.get(output.dataId);\n    const vals = this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(tmpData.texture.texture, tmpData.texShape[0], tmpData.texShape[1]).subarray(0, size);\n    this.disposeIntermediateTensorInfo(output);\n    return vals;\n  }\n  timerAvailable() {\n    return env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\") > 0;\n  }\n  time(f) {\n    const oldActiveTimers = this.activeTimers;\n    const newActiveTimers = [];\n    let outerMostTime = false;\n    if (this.programTimersStack == null) {\n      this.programTimersStack = newActiveTimers;\n      outerMostTime = true;\n    } else {\n      this.activeTimers.push(newActiveTimers);\n    }\n    this.activeTimers = newActiveTimers;\n    f();\n    const flattenedActiveTimerQueries = util_exports.flatten(this.activeTimers.map((d) => d.query)).filter((d) => d != null);\n    const flattenedActiveTimerNames = util_exports.flatten(this.activeTimers.map((d) => d.name)).filter((d) => d != null);\n    this.activeTimers = oldActiveTimers;\n    if (outerMostTime) {\n      this.programTimersStack = null;\n    }\n    const res = {\n      uploadWaitMs: this.uploadWaitMs,\n      downloadWaitMs: this.downloadWaitMs,\n      kernelMs: null,\n      wallMs: null\n    };\n    return (async () => {\n      if (env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\") > 0) {\n        const kernelMs = await Promise.all(flattenedActiveTimerQueries);\n        res[\"kernelMs\"] = util_exports.sum(kernelMs);\n        res[\"getExtraProfileInfo\"] = () => kernelMs.map((d, i2) => ({ name: flattenedActiveTimerNames[i2], ms: d })).map((d) => `${d.name}: ${d.ms}`).join(\", \");\n      } else {\n        res[\"kernelMs\"] = {\n          error: \"WebGL query timers are not supported in this environment.\"\n        };\n      }\n      this.uploadWaitMs = 0;\n      this.downloadWaitMs = 0;\n      return res;\n    })();\n  }\n  memory() {\n    return {\n      unreliable: false,\n      numBytesInGPU: this.numBytesInGPU,\n      numBytesInGPUAllocated: this.textureManager.numBytesAllocated,\n      numBytesInGPUFree: this.textureManager.numBytesFree\n    };\n  }\n  startTimer() {\n    if (env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\") > 0) {\n      return this.gpgpu.beginQuery();\n    }\n    return { startMs: util_exports.now(), endMs: null };\n  }\n  endTimer(query) {\n    if (env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\") > 0) {\n      this.gpgpu.endQuery();\n      return query;\n    }\n    query.endMs = util_exports.now();\n    return query;\n  }\n  async getQueryTime(query) {\n    if (env().getNumber(\"WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE\") > 0) {\n      return this.gpgpu.waitForQueryAndGetTime(query);\n    }\n    const timerQuery = query;\n    return timerQuery.endMs - timerQuery.startMs;\n  }\n  disposeData(dataId, force = false) {\n    if (this.pendingDisposal.has(dataId)) {\n      return false;\n    }\n    if (!this.texData.has(dataId)) {\n      return true;\n    }\n    if (force) {\n      this.texData.get(dataId).refCount = 0;\n    } else {\n      this.texData.get(dataId).refCount--;\n    }\n    if (!force && this.texData.get(dataId).refCount > 0) {\n      return false;\n    }\n    if (this.pendingRead.has(dataId)) {\n      this.pendingDisposal.add(dataId);\n      this.pendingDeletes++;\n      return false;\n    }\n    this.releaseGPUData(dataId);\n    const { complexTensorInfos } = this.texData.get(dataId);\n    if (complexTensorInfos != null) {\n      this.disposeData(complexTensorInfos.real.dataId, force);\n      this.disposeData(complexTensorInfos.imag.dataId, force);\n    }\n    this.texData.delete(dataId);\n    return true;\n  }\n  releaseGPUData(dataId) {\n    const { texture, dtype, texShape, usage, isPacked, slice: slice6 } = this.texData.get(dataId);\n    const key = slice6 && slice6.origDataId || dataId;\n    const refCount = this.dataRefCount.get(key);\n    if (refCount > 1) {\n      this.dataRefCount.set(key, refCount - 1);\n    } else {\n      this.dataRefCount.delete(key);\n      if (texture != null) {\n        this.numBytesInGPU -= this.computeBytes(texShape, dtype);\n        this.textureManager.releaseTexture(texture, texShape, usage, isPacked);\n      }\n    }\n    const texData = this.texData.get(dataId);\n    texData.texture = null;\n    texData.texShape = null;\n    texData.isPacked = false;\n    texData.slice = null;\n  }\n  getTexture(dataId) {\n    this.uploadToGPU(dataId);\n    return this.texData.get(dataId).texture.texture;\n  }\n  getDataInfo(dataId) {\n    return this.texData.get(dataId);\n  }\n  shouldExecuteOnCPU(inputs, sizeThreshold = CPU_HANDOFF_SIZE_THRESHOLD) {\n    return env().getBool(\"WEBGL_CPU_FORWARD\") && inputs.every((input2) => this.texData.get(input2.dataId).texture == null && util_exports.sizeFromShape(input2.shape) < sizeThreshold);\n  }\n  getGPGPUContext() {\n    return this.gpgpu;\n  }\n  where(condition) {\n    backend_util_exports.warn(\"tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead\");\n    const condVals = condition.dataSync();\n    return whereImpl3(condition.shape, condVals);\n  }\n  packedUnaryOp(x, op2, dtype) {\n    const program = new UnaryOpPackedProgram(x.shape, op2);\n    const outInfo = this.compileAndRun(program, [x], dtype);\n    return engine().makeTensorFromTensorInfo(outInfo);\n  }\n  abs(x) {\n    if (this.shouldExecuteOnCPU([x]) && x.dtype !== \"complex64\") {\n      const outValues = simpleAbsImplCPU(this.texData.get(x.dataId).values);\n      return this.makeOutput(x.shape, x.dtype, outValues);\n    }\n    if (env().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\")) {\n      return this.packedUnaryOp(x, ABS, x.dtype);\n    }\n    const program = new UnaryOpProgram(x.shape, ABS);\n    const outInfo = this.compileAndRun(program, [x]);\n    return engine().makeTensorFromTensorInfo(outInfo);\n  }\n  makeTensorInfo(shape, dtype, values) {\n    let dataId;\n    if (dtype === \"string\" && values != null && values.length > 0 && util_exports.isString(values[0])) {\n      const encodedValues = values.map((d) => util_exports.encodeString(d));\n      dataId = this.write(encodedValues, shape, dtype);\n    } else {\n      dataId = this.write(values, shape, dtype);\n    }\n    this.texData.get(dataId).usage = null;\n    return { dataId, shape, dtype };\n  }\n  makeOutput(shape, dtype, values) {\n    return engine().makeTensorFromTensorInfo(this.makeTensorInfo(shape, dtype, values), this);\n  }\n  unpackTensor(input2) {\n    const program = new UnpackProgram(input2.shape);\n    return this.runWebGLProgram(program, [input2], input2.dtype);\n  }\n  packTensor(input2) {\n    const program = new PackProgram(input2.shape);\n    const preventEagerUnpackingOutput = true;\n    return this.runWebGLProgram(program, [input2], input2.dtype, null, preventEagerUnpackingOutput);\n  }\n  packedReshape(input2, afterShape) {\n    const input3DShape = [\n      getBatchDim(input2.shape),\n      ...getRowsCols(input2.shape)\n    ];\n    const input3D = {\n      dtype: input2.dtype,\n      shape: input3DShape,\n      dataId: input2.dataId\n    };\n    const afterShapeAs3D = [\n      getBatchDim(afterShape),\n      ...getRowsCols(afterShape)\n    ];\n    const program = new ReshapePackedProgram(afterShapeAs3D, input3DShape);\n    const preventEagerUnpackingOfOutput = true;\n    const customValues = [input3DShape];\n    const output = this.runWebGLProgram(program, [input3D], input2.dtype, customValues, preventEagerUnpackingOfOutput);\n    return { dataId: output.dataId, shape: afterShape, dtype: output.dtype };\n  }\n  decode(dataId, customTexShape) {\n    const texData = this.texData.get(dataId);\n    const { isPacked, shape, dtype } = texData;\n    if (customTexShape != null) {\n      const size = util_exports.sizeFromShape(shape);\n      const texSize = customTexShape[0] * customTexShape[1] * 4;\n      util_exports.assert(size <= texSize, () => \"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.\");\n    }\n    const shapeAs3D = getShapeAs3D(shape);\n    let program;\n    if (isPacked) {\n      program = new DecodeMatrixPackedProgram(shapeAs3D);\n    } else {\n      program = new DecodeMatrixProgram(shapeAs3D);\n    }\n    const preventEagerUnpackingOfOutput = true;\n    const customValues = [customTexShape != null ? customTexShape : getDenseTexShape(shapeAs3D)];\n    const out = this.runWebGLProgram(program, [{ shape: shapeAs3D, dtype, dataId }], dtype, customValues, preventEagerUnpackingOfOutput, customTexShape);\n    return { dtype, shape, dataId: out.dataId };\n  }\n  runWebGLProgram(program, inputs, outputDtype, customUniformValues, preventEagerUnpackingOfOutput = false, customTexShape) {\n    const output = this.makeTensorInfo(program.outputShape, outputDtype);\n    const outData = this.texData.get(output.dataId);\n    if (program.packedOutput) {\n      outData.isPacked = true;\n    }\n    if (program.outPackingScheme === PackingScheme.DENSE) {\n      const texelShape = customTexShape != null ? customTexShape : getDenseTexShape(program.outputShape);\n      outData.texShape = texelShape.map((d) => d * 2);\n    }\n    if (program.outTexUsage != null) {\n      outData.usage = program.outTexUsage;\n    }\n    if (util_exports.sizeFromShape(output.shape) === 0) {\n      outData.values = util_exports.getTypedArrayFromDType(output.dtype, 0);\n      return output;\n    }\n    const dataToDispose = [];\n    const inputsData = inputs.map((input2) => {\n      if (input2.dtype === \"complex64\") {\n        throw new Error(`GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.`);\n      }\n      let texData = this.texData.get(input2.dataId);\n      if (texData.texture == null) {\n        if (!program.packedInputs && util_exports.sizeFromShape(input2.shape) <= env().getNumber(\"WEBGL_SIZE_UPLOAD_UNIFORM\")) {\n          return {\n            shape: input2.shape,\n            texData: null,\n            isUniform: true,\n            uniformValues: texData.values\n          };\n        }\n        if (program.packedInputs) {\n          texData.isPacked = true;\n          texData.shape = input2.shape;\n        }\n      }\n      this.uploadToGPU(input2.dataId);\n      if (!!texData.isPacked !== !!program.packedInputs) {\n        input2 = texData.isPacked ? this.unpackTensor(input2) : this.packTensor(input2);\n        dataToDispose.push(input2);\n        texData = this.texData.get(input2.dataId);\n      } else if (texData.isPacked && !isReshapeFree(texData.shape, input2.shape)) {\n        const savedInput = input2;\n        const targetShape = input2.shape;\n        input2.shape = texData.shape;\n        input2 = this.packedReshape(input2, targetShape);\n        dataToDispose.push(input2);\n        texData = this.texData.get(input2.dataId);\n        savedInput.shape = targetShape;\n      }\n      return { shape: input2.shape, texData, isUniform: false };\n    });\n    this.uploadToGPU(output.dataId);\n    const outputData = { shape: output.shape, texData: outData, isUniform: false };\n    const key = makeShaderKey(program, inputsData, outputData);\n    const binary = this.getAndSaveBinary(key, () => {\n      return compileProgram(this.gpgpu, program, inputsData, outputData);\n    });\n    const shouldTimeProgram = this.activeTimers != null;\n    let query;\n    if (shouldTimeProgram) {\n      query = this.startTimer();\n    }\n    if (!env().get(\"ENGINE_COMPILE_ONLY\")) {\n      runProgram(this.gpgpu, binary, inputsData, outputData, customUniformValues);\n    }\n    dataToDispose.forEach((info) => this.disposeIntermediateTensorInfo(info));\n    if (shouldTimeProgram) {\n      query = this.endTimer(query);\n      this.activeTimers.push({ name: program.constructor.name, query: this.getQueryTime(query) });\n    }\n    const glFlushThreshold = env().get(\"WEBGL_FLUSH_THRESHOLD\");\n    if (glFlushThreshold > 0) {\n      const time2 = util_exports.now();\n      if (time2 - this.lastGlFlushTime > glFlushThreshold) {\n        this.gpgpu.gl.flush();\n        this.lastGlFlushTime = time2;\n      }\n    }\n    if (!env().getBool(\"WEBGL_LAZILY_UNPACK\") && outData.isPacked && preventEagerUnpackingOfOutput === false) {\n      const unpacked = this.unpackTensor(output);\n      this.disposeIntermediateTensorInfo(output);\n      return unpacked;\n    }\n    return output;\n  }\n  compileAndRun(program, inputs, outputDtype, customUniformValues, preventEagerUnpackingOfOutput = false) {\n    outputDtype = outputDtype || inputs[0].dtype;\n    const outInfo = this.runWebGLProgram(program, inputs, outputDtype, customUniformValues, preventEagerUnpackingOfOutput);\n    return outInfo;\n  }\n  getAndSaveBinary(key, getBinary) {\n    if (!(key in this.binaryCache)) {\n      this.binaryCache[key] = getBinary();\n    }\n    return this.binaryCache[key];\n  }\n  getTextureManager() {\n    return this.textureManager;\n  }\n  dispose() {\n    if (this.disposed) {\n      return;\n    }\n    if (!env().getBool(\"IS_TEST\")) {\n      const allKeys = Object.keys(this.binaryCache);\n      allKeys.forEach((key) => {\n        this.gpgpu.deleteProgram(this.binaryCache[key].webGLProgram);\n        delete this.binaryCache[key];\n      });\n    }\n    this.textureManager.dispose();\n    if (this.canvas != null && (typeof HTMLCanvasElement !== \"undefined\" && this.canvas instanceof HTMLCanvasElement)) {\n      this.canvas.remove();\n    } else {\n      this.canvas = null;\n    }\n    if (this.gpgpuCreatedLocally) {\n      this.gpgpu.program = null;\n      this.gpgpu.dispose();\n    }\n    this.disposed = true;\n  }\n  floatPrecision() {\n    if (this.floatPrecisionValue == null) {\n      this.floatPrecisionValue = tidy(() => {\n        if (!env().get(\"WEBGL_RENDER_FLOAT32_ENABLED\")) {\n          const debugFlag = env().getBool(\"DEBUG\");\n          env().set(\"DEBUG\", false);\n          const underflowCheckValue = this.abs(scalar(1e-8)).dataSync()[0];\n          env().set(\"DEBUG\", debugFlag);\n          if (underflowCheckValue > 0) {\n            return 32;\n          }\n        }\n        return 16;\n      });\n    }\n    return this.floatPrecisionValue;\n  }\n  epsilon() {\n    return this.floatPrecision() === 32 ? EPSILON_FLOAT322 : EPSILON_FLOAT162;\n  }\n  uploadToGPU(dataId) {\n    const texData = this.texData.get(dataId);\n    const { shape, dtype, values, texture, usage, isPacked } = texData;\n    if (texture != null) {\n      return;\n    }\n    const shouldTimeProgram = this.activeTimers != null;\n    let start;\n    if (shouldTimeProgram) {\n      start = util_exports.now();\n    }\n    let texShape = texData.texShape;\n    if (texShape == null) {\n      texShape = getTextureShapeFromLogicalShape(shape, isPacked);\n      texData.texShape = texShape;\n    }\n    if (values != null) {\n      const shapeAs3D = getShapeAs3D(shape);\n      let program;\n      let width = texShape[1], height = texShape[0];\n      const isByteArray = values instanceof Uint8Array || values instanceof Uint8ClampedArray;\n      if (isPacked || !isByteArray) {\n        [width, height] = getPackedMatrixTextureShapeWidthHeight(texShape[0], texShape[1]);\n      }\n      if (isPacked) {\n        program = new EncodeMatrixPackedProgram(shapeAs3D, isByteArray);\n      } else {\n        program = new EncodeMatrixProgram(shapeAs3D, isByteArray);\n      }\n      const tempDenseInputTexShape = isByteArray ? [height, width] : texShape;\n      const tempDenseInputHandle = this.makeTensorInfo(tempDenseInputTexShape, dtype);\n      const tempDenseInputTexData = this.texData.get(tempDenseInputHandle.dataId);\n      if (isByteArray) {\n        tempDenseInputTexData.usage = TextureUsage.PIXELS;\n      } else {\n        tempDenseInputTexData.usage = TextureUsage.UPLOAD;\n      }\n      tempDenseInputTexData.texShape = tempDenseInputTexShape;\n      this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(tempDenseInputHandle.dataId), width, height, values);\n      const customValues = [[height, width]];\n      const preventEagerUnpacking = true;\n      const encodedOutputTarget = this.runWebGLProgram(program, [tempDenseInputHandle], dtype, customValues, preventEagerUnpacking);\n      const outputTexData = this.texData.get(encodedOutputTarget.dataId);\n      texData.texShape = outputTexData.texShape;\n      texData.isPacked = outputTexData.isPacked;\n      texData.usage = outputTexData.usage;\n      if (!env().get(\"ENGINE_COMPILE_ONLY\")) {\n        texData.texture = outputTexData.texture;\n        texData.values = null;\n        this.texData.delete(encodedOutputTarget.dataId);\n      } else {\n        this.disposeData(encodedOutputTarget.dataId);\n      }\n      this.disposeIntermediateTensorInfo(tempDenseInputHandle);\n      if (shouldTimeProgram) {\n        this.uploadWaitMs += util_exports.now() - start;\n      }\n    } else {\n      const newTexture = this.acquireTexture(texShape, usage, dtype, isPacked);\n      texData.texture = newTexture;\n    }\n  }\n  convertAndCacheOnCPU(dataId, float32Values) {\n    const texData = this.texData.get(dataId);\n    const { dtype } = texData;\n    this.releaseGPUData(dataId);\n    if (float32Values != null) {\n      texData.values = float32ToTypedArray(float32Values, dtype);\n    }\n    return texData.values;\n  }\n  acquireTexture(texShape, texType, dtype, isPacked) {\n    this.numBytesInGPU += this.computeBytes(texShape, dtype);\n    if (!this.warnedAboutMemory && this.numBytesInGPU > this.numMBBeforeWarning * 1024 * 1024) {\n      const mb = (this.numBytesInGPU / 1024 / 1024).toFixed(2);\n      this.warnedAboutMemory = true;\n      console.warn(`High memory usage in GPU: ${mb} MB, most likely due to a memory leak`);\n    }\n    return this.textureManager.acquireTexture(texShape, texType, isPacked);\n  }\n  computeBytes(shape, dtype) {\n    return shape[0] * shape[1] * util_exports.bytesPerElement(dtype);\n  }\n  checkCompileCompletion() {\n    for (const [, binary] of Object.entries(this.binaryCache)) {\n      this.checkCompletion_(binary);\n    }\n  }\n  async checkCompileCompletionAsync() {\n    const ps = [];\n    if (this.gpgpu.parallelCompilationExtension) {\n      for (const [, binary] of Object.entries(this.binaryCache)) {\n        ps.push(this.checkCompletionAsync_(binary));\n      }\n      return Promise.all(ps);\n    } else {\n      for (const [, binary] of Object.entries(this.binaryCache)) {\n        const p2 = new Promise((resolve) => {\n          try {\n            this.checkCompletion_(binary);\n            resolve(true);\n          } catch (error) {\n            throw error;\n          }\n        });\n        ps.push(p2);\n      }\n      return Promise.all(ps);\n    }\n  }\n  async checkCompletionAsync_(binary) {\n    if (this.gpgpu.gl.getProgramParameter(binary.webGLProgram, this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)) {\n      return this.checkCompletion_(binary);\n    } else {\n      await nextFrame();\n      return this.checkCompletionAsync_(binary);\n    }\n  }\n  checkCompletion_(binary) {\n    if (this.gpgpu.gl.getProgramParameter(binary.webGLProgram, this.gpgpu.gl.LINK_STATUS) === false) {\n      console.log(this.gpgpu.gl.getProgramInfoLog(binary.webGLProgram));\n      if (this.gpgpu.gl.getShaderParameter(binary.fragmentShader, this.gpgpu.gl.COMPILE_STATUS) === false) {\n        logShaderSourceAndInfoLog(binary.source, this.gpgpu.gl.getShaderInfoLog(binary.fragmentShader));\n        throw new Error(\"Failed to compile fragment shader.\");\n      }\n      throw new Error(\"Failed to link vertex and fragment shaders.\");\n    }\n    return true;\n  }\n  getUniformLocations() {\n    for (const [, binary] of Object.entries(this.binaryCache)) {\n      const { uniformLocations, customUniformLocations, infLoc, nanLoc, inShapesLocations, inTexShapesLocations, outShapeLocation, outShapeStridesLocation, outTexShapeLocation } = getUniformLocations(this.gpgpu, binary.program, binary.webGLProgram);\n      binary.uniformLocations = uniformLocations;\n      binary.customUniformLocations = customUniformLocations;\n      binary.infLoc = infLoc;\n      binary.nanLoc = nanLoc;\n      binary.inShapesLocations = inShapesLocations;\n      binary.inTexShapesLocations = inTexShapesLocations;\n      binary.outShapeLocation = outShapeLocation;\n      binary.outShapeStridesLocation = outShapeStridesLocation;\n      binary.outTexShapeLocation = outTexShapeLocation;\n    }\n  }\n};\nMathBackendWebGL.nextDataId = 0;\nfunction float32ToTypedArray(a, dtype) {\n  if (dtype === \"float32\" || dtype === \"complex64\") {\n    return a;\n  } else if (dtype === \"int32\" || dtype === \"bool\") {\n    const result = dtype === \"int32\" ? new Int32Array(a.length) : new Uint8Array(a.length);\n    for (let i2 = 0; i2 < result.length; ++i2) {\n      result[i2] = Math.round(a[i2]);\n    }\n    return result;\n  } else {\n    throw new Error(`Unknown dtype ${dtype}`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/version.js\nvar version6 = \"3.19.0\";\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/webgl.js\nfunction forceHalfFloat() {\n  env().set(\"WEBGL_FORCE_F16_TEXTURES\", true);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/base.js\nif (device_util_exports.isBrowser()) {\n  registerBackend(\"webgl\", () => new MathBackendWebGL(), 2);\n}\nvar webgl = { forceHalfFloat };\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/binaryop_gpu.js\nvar CHECK_NAN_SNIPPET2 = `\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n`;\nvar BinaryOpProgram = class {\n  constructor(op2, aShape, bShape) {\n    this.variableNames = [\"A\", \"B\"];\n    this.outputShape = backend_util_exports.assertAndGetBroadcastShape(aShape, bShape);\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    this.userCode = `\n      float binaryOperation(float a, float b) {\n        ${op2}\n      }\n\n      void main() {\n        float a = getAAtOutCoords();\n        float b = getBAtOutCoords();\n        setOutput(binaryOperation(a, b));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/binaryop_packed_gpu.js\nvar CHECK_NAN_SNIPPET3 = `\n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n`;\nvar BinaryOpPackedProgram = class {\n  constructor(op2, aShape, bShape, checkOutOfBounds = false) {\n    this.variableNames = [\"A\", \"B\"];\n    this.supportsBroadcasting = true;\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = backend_util_exports.assertAndGetBroadcastShape(aShape, bShape);\n    const rank = this.outputShape.length;\n    this.enableShapeUniforms = useShapeUniforms(rank);\n    let checkOutOfBoundsString = \"\";\n    if (checkOutOfBounds) {\n      if (rank === 0 || util_exports.sizeFromShape(this.outputShape) === 1) {\n        checkOutOfBoundsString = `\n          result.y = 0.;\n          result.z = 0.;\n          result.w = 0.;\n        `;\n      } else {\n        const dtype = getCoordsDataType(rank);\n        checkOutOfBoundsString = `\n          ${dtype} coords = getOutputCoords();\n        `;\n        if (rank === 1) {\n          if (this.enableShapeUniforms) {\n            checkOutOfBoundsString += `\n            result.y = (coords + 1) >= outShape ? 0. : result.y;\n            result.z = 0.;\n            result.w = 0.;\n          `;\n          } else {\n            checkOutOfBoundsString += `\n            result.y = (coords + 1) >= ${this.outputShape[0]} ? 0. : result.y;\n            result.z = 0.;\n            result.w = 0.;\n          `;\n          }\n        } else {\n          const channels = getChannels(\"coords\", rank);\n          if (this.enableShapeUniforms) {\n            checkOutOfBoundsString += `\n            bool nextRowOutOfBounds =\n              (${channels[rank - 2]} + 1) >= outShape[${rank} - 2];\n            bool nextColOutOfBounds =\n              (${channels[rank - 1]} + 1) >= outShape[${rank} - 1];\n            result.y = nextColOutOfBounds ? 0. : result.y;\n            result.z = nextRowOutOfBounds ? 0. : result.z;\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n          `;\n          } else {\n            checkOutOfBoundsString += `\n            bool nextRowOutOfBounds =\n              (${channels[rank - 2]} + 1) >= ${this.outputShape[rank - 2]};\n            bool nextColOutOfBounds =\n              (${channels[rank - 1]} + 1) >= ${this.outputShape[rank - 1]};\n            result.y = nextColOutOfBounds ? 0. : result.y;\n            result.z = nextRowOutOfBounds ? 0. : result.z;\n            result.w = nextColOutOfBounds || nextRowOutOfBounds ? 0. : result.w;\n          `;\n          }\n        }\n      }\n    }\n    this.userCode = `\n      vec4 binaryOperation(vec4 a, vec4 b) {\n        ${op2}\n      }\n\n      void main() {\n        vec4 a = getAAtOutCoords();\n        vec4 b = getBAtOutCoords();\n\n        vec4 result = binaryOperation(a, b);\n        ${checkOutOfBoundsString}\n\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Identity.js\nfunction identity3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  backend2.incRef(x.dataId);\n  return { dataId: x.dataId, shape: x.shape, dtype: x.dtype };\n}\nvar identityConfig2 = {\n  kernelName: Identity,\n  backendName: \"webgl\",\n  kernelFunc: identity3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Complex.js\nfunction complex3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { real: real5, imag: imag5 } = inputs;\n  const complexInfo = backend2.makeTensorInfo(real5.shape, \"complex64\");\n  const complex5 = backend2.texData.get(complexInfo.dataId);\n  const realTensorInfo = identity3({ inputs: { x: real5 }, backend: backend2 });\n  const imagTensorInfo = identity3({ inputs: { x: imag5 }, backend: backend2 });\n  complex5.complexTensorInfos = { real: realTensorInfo, imag: imagTensorInfo };\n  return complexInfo;\n}\nvar complexConfig2 = {\n  kernelName: Complex,\n  backendName: \"webgl\",\n  kernelFunc: complex3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LeakyRelu.js\nvar LEAKYRELU = `return (a < 0.) ? b * a : a;`;\nvar LEAKYRELU_PACKED = `\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n`;\nfunction leakyRelu3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { alpha } = attrs;\n  const $alpha = backend2.makeTensorInfo([], \"float32\", util_exports.createScalarValue(alpha, \"float32\"));\n  const program = env().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\") ? new BinaryOpPackedProgram(LEAKYRELU_PACKED, x.shape, $alpha.shape) : new BinaryOpProgram(LEAKYRELU, x.shape, $alpha.shape);\n  const result = backend2.runWebGLProgram(program, [x, $alpha], \"float32\");\n  backend2.disposeIntermediateTensorInfo($alpha);\n  return result;\n}\nvar leakyReluConfig2 = {\n  kernelName: LeakyRelu,\n  backendName: \"webgl\",\n  kernelFunc: leakyRelu3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Prelu.js\nvar PRELU = `return (a < 0.) ? b * a : a;`;\nvar PRELU_PACKED = `\n  vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));\n  return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);\n`;\nfunction prelu4(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x, alpha } = inputs;\n  const program = env().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\") ? new BinaryOpPackedProgram(PRELU_PACKED, x.shape, alpha.shape) : new BinaryOpProgram(PRELU, x.shape, alpha.shape);\n  return backend2.runWebGLProgram(program, [x, alpha], \"float32\");\n}\nvar preluConfig2 = {\n  kernelName: Prelu,\n  backendName: \"webgl\",\n  kernelFunc: prelu4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/kernel_funcs_utils.js\nvar CHECK_NAN_SNIPPET_UNARY = `if (isnan(x)) return x;`;\nvar CHECK_NAN_SNIPPET_BINARY = `\n  if (isnan(a)) return a;\n  if (isnan(b)) return b;\n`;\nvar CHECK_NAN_SNIPPET_BINARY_PACKED = `\n  result.r = isNaN.r > 0. ? NAN : result.r;\n  result.g = isNaN.g > 0. ? NAN : result.g;\n  result.b = isNaN.b > 0. ? NAN : result.b;\n  result.a = isNaN.a > 0. ? NAN : result.a;\n`;\nfunction unaryKernelFunc2({ opSnippet, packedOpSnippet, cpuKernelImpl, dtype }) {\n  return ({ inputs, backend: backend2 }) => {\n    const { x } = inputs;\n    const webglBackend = backend2;\n    const $dtype = dtype || x.dtype;\n    if (webglBackend.shouldExecuteOnCPU([x]) && cpuKernelImpl != null) {\n      const xData = webglBackend.texData.get(x.dataId);\n      const outValues = cpuKernelImpl(xData.values, $dtype);\n      return webglBackend.makeTensorInfo(x.shape, $dtype, outValues);\n    }\n    const shouldUsePackedProgram = env().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\") && packedOpSnippet != null;\n    let program;\n    if (shouldUsePackedProgram) {\n      program = new UnaryOpPackedProgram(x.shape, packedOpSnippet);\n    } else {\n      program = new UnaryOpProgram(x.shape, opSnippet);\n    }\n    return webglBackend.runWebGLProgram(program, [x], $dtype);\n  };\n}\nfunction binaryKernelFunc2({ opSnippet, packedOpSnippet, checkOutOfBounds = false, supportsComplex = false, cpuKernelImpl, dtype }) {\n  return ({ inputs, backend: backend2 }) => {\n    const { a, b } = inputs;\n    const webglBackend = backend2;\n    if (supportsComplex && a.dtype === \"complex64\") {\n      const aData = webglBackend.texData.get(a.dataId);\n      const bData = webglBackend.texData.get(b.dataId);\n      const [real5, imag5] = [\n        [aData.complexTensorInfos.real, bData.complexTensorInfos.real],\n        [aData.complexTensorInfos.imag, bData.complexTensorInfos.imag]\n      ].map((complexParts) => {\n        const [aPart, bPart] = complexParts;\n        const aHandle = {\n          dataId: aPart.dataId,\n          dtype: aPart.dtype,\n          shape: a.shape\n        };\n        const bHandle = {\n          dataId: bPart.dataId,\n          dtype: bPart.dtype,\n          shape: b.shape\n        };\n        const program2 = new BinaryOpProgram(opSnippet, a.shape, b.shape);\n        return webglBackend.runWebGLProgram(program2, [aHandle, bHandle], upcastType(aPart.dtype, bPart.dtype));\n      });\n      const complexOutput = complex3({ inputs: { real: real5, imag: imag5 }, backend: webglBackend });\n      webglBackend.disposeIntermediateTensorInfo(real5);\n      webglBackend.disposeIntermediateTensorInfo(imag5);\n      return complexOutput;\n    }\n    const $dtype = dtype || upcastType(a.dtype, b.dtype);\n    if ((a.dtype === \"string\" || b.dtype === \"string\" || webglBackend.shouldExecuteOnCPU([a, b])) && cpuKernelImpl != null) {\n      const aVals = webglBackend.texData.get(a.dataId).values;\n      const bVals = webglBackend.texData.get(b.dataId).values;\n      const decodedAVals = a.dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(aVals) : aVals;\n      const decodedBVals = a.dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(bVals) : bVals;\n      const [outValues, outShape] = cpuKernelImpl(a.shape, b.shape, decodedAVals, decodedBVals, $dtype);\n      const out = webglBackend.makeTensorInfo(outShape, $dtype);\n      const outData = webglBackend.texData.get(out.dataId);\n      outData.values = outValues;\n      return out;\n    }\n    const shouldUsePackedProgram = env().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\") && packedOpSnippet != null;\n    let program;\n    if (shouldUsePackedProgram) {\n      program = new BinaryOpPackedProgram(packedOpSnippet, a.shape, b.shape, checkOutOfBounds);\n    } else {\n      program = new BinaryOpProgram(opSnippet, a.shape, b.shape);\n    }\n    return webglBackend.runWebGLProgram(program, [a, b], $dtype);\n  };\n}\nfunction mapActivationToShaderProgram(activation2, packed = false) {\n  if (activation2 === \"linear\") {\n    if (packed) {\n      return LINEAR2;\n    }\n    return LINEAR;\n  } else if (activation2 === \"relu\") {\n    if (packed) {\n      return RELU2;\n    }\n    return RELU;\n  } else if (activation2 === \"elu\") {\n    if (packed) {\n      return ELU3;\n    }\n    return ELU2;\n  } else if (activation2 === \"relu6\") {\n    if (packed) {\n      return RELU62;\n    }\n    return RELU6;\n  } else if (activation2 === \"prelu\") {\n    if (packed) {\n      return PRELU_PACKED;\n    }\n    return PRELU;\n  } else if (activation2 === \"leakyrelu\") {\n    if (packed) {\n      return LEAKYRELU_PACKED;\n    }\n    return LEAKYRELU;\n  } else if (activation2 === \"sigmoid\") {\n    if (packed) {\n      return SIGMOID2;\n    }\n    return SIGMOID;\n  }\n  throw new Error(`Activation ${activation2} has not been implemented for the WebGL backend.`);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/mulmat_packed_gpu.js\nvar MatMulPackedProgram = class {\n  constructor(aShape, bShape, outputShape, transposeA = false, transposeB = false, addBias = false, activation2 = null, hasPreluActivation = false, hasLeakyreluActivation = false) {\n    this.variableNames = [\"matrixA\", \"matrixB\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    const sharedDim = transposeA ? aShape[1] : aShape[2];\n    const sharedDimensionPacked = Math.ceil(sharedDim / 2);\n    const aSample = transposeA ? \"i * 2, rc.y\" : \"rc.y, i * 2\";\n    const bSample = transposeB ? \"rc.z, i * 2\" : \"i * 2, rc.z\";\n    const aSwizzle = transposeA ? [\"a.xxyy\", \"a.zzww\"] : [\"a.xxzz\", \"a.yyww\"];\n    const bSwizzle = transposeB ? [\"b.xzxz\", \"b.ywyw\"] : [\"b.xyxy\", \"b.zwzw\"];\n    let activationSnippet = \"\", applyActivationSnippet = \"\";\n    if (activation2) {\n      if (hasPreluActivation) {\n        activationSnippet = `vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          ${activation2}\n        }`;\n      } else if (hasLeakyreluActivation) {\n        activationSnippet = `vec4 activation(vec4 a) {\n          vec4 b = getLeakyreluAlphaAtOutCoords();\n          ${activation2}\n        }`;\n      } else {\n        activationSnippet = `vec4 activation(vec4 x) {\n          ${activation2}\n        }`;\n      }\n      applyActivationSnippet = `result = activation(result);`;\n    }\n    const addBiasSnippet = addBias ? \"result += getBiasAtOutCoords();\" : \"\";\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivation) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    if (hasLeakyreluActivation) {\n      this.variableNames.push(\"leakyreluAlpha\");\n    }\n    let batchASnippet = \"rc.x\";\n    let batchBSnippet = \"rc.x\";\n    if (aShape[0] < bShape[0]) {\n      batchASnippet = `int(min(float(rc.x), ${aShape[0] - 1}.))`;\n    } else if (bShape[0] < aShape[0]) {\n      batchBSnippet = `int(min(float(rc.x), ${bShape[0] - 1}.))`;\n    }\n    this.userCode = `\n      ${activationSnippet}\n      // Don't use uniform for sharedDimensionPacked for performance.\n      const float sharedDimension = ${sharedDimensionPacked}.0;\n\n      vec4 dot2x2ARowBCol(ivec3 rc) {\n        vec4 result = vec4(0);\n        for (int i = 0; i < ${sharedDimensionPacked}; i++) {\n          int batchA = ${batchASnippet};\n          int batchB = ${batchBSnippet};\n          vec4 a = getMatrixA(batchA, ${aSample});\n          vec4 b = getMatrixB(batchB, ${bSample});\n\n          // These swizzled products need to be separately added.\n          // See: https://github.com/tensorflow/tfjs/issues/1735\n          result += (${aSwizzle[0]} * ${bSwizzle[0]});\n          result += (${aSwizzle[1]} * ${bSwizzle[1]});\n        }\n        return result;\n      }\n\n      void main() {\n        ivec3 rc = getOutputCoords();\n        vec4 result = dot2x2ARowBCol(rc);\n\n        ${addBiasSnippet}\n\n        ${applyActivationSnippet}\n\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/binaryop_complex_gpu.js\nvar COMPLEX_MULTIPLY = {\n  REAL: \"return areal * breal - aimag * bimag;\",\n  IMAG: \"return areal * bimag + aimag * breal;\"\n};\nvar BinaryOpComplexProgram = class {\n  constructor(op2, aShape, bShape) {\n    this.variableNames = [\"AReal\", \"AImag\", \"BReal\", \"BImag\"];\n    this.outputShape = backend_util_exports.assertAndGetBroadcastShape(aShape, bShape);\n    this.userCode = `\n      float binaryOpComplex(\n          float areal, float aimag, float breal, float bimag) {\n        ${op2}\n      }\n\n      void main() {\n        float areal = getARealAtOutCoords();\n        float aimag = getAImagAtOutCoords();\n        float breal = getBRealAtOutCoords();\n        float bimag = getBImagAtOutCoords();\n        setOutput(binaryOpComplex(areal, aimag, breal, bimag));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Multiply.js\nvar MUL = \"return a * b;\";\nfunction multiply3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { a, b } = inputs;\n  const dtype = backend_util_exports.upcastType(a.dtype, b.dtype);\n  if (a.dtype === \"complex64\") {\n    const aData = backend2.texData.get(a.dataId);\n    const bData = backend2.texData.get(b.dataId);\n    const realProgram = new BinaryOpComplexProgram(COMPLEX_MULTIPLY.REAL, a.shape, b.shape);\n    const imagProgram = new BinaryOpComplexProgram(COMPLEX_MULTIPLY.IMAG, a.shape, b.shape);\n    const inputs2 = [\n      {\n        dataId: aData.complexTensorInfos.real.dataId,\n        dtype: aData.complexTensorInfos.real.dtype,\n        shape: a.shape\n      },\n      {\n        dataId: aData.complexTensorInfos.imag.dataId,\n        dtype: aData.complexTensorInfos.imag.dtype,\n        shape: a.shape\n      },\n      {\n        dataId: bData.complexTensorInfos.real.dataId,\n        dtype: bData.complexTensorInfos.real.dtype,\n        shape: b.shape\n      },\n      {\n        dataId: bData.complexTensorInfos.imag.dataId,\n        dtype: bData.complexTensorInfos.imag.dtype,\n        shape: b.shape\n      }\n    ];\n    const realPart = backend2.runWebGLProgram(realProgram, inputs2, \"float32\");\n    const imagPart = backend2.runWebGLProgram(imagProgram, inputs2, \"float32\");\n    const complexOutput = complex3({ inputs: { real: realPart, imag: imagPart }, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(realPart);\n    backend2.disposeIntermediateTensorInfo(imagPart);\n    return complexOutput;\n  }\n  if (backend2.shouldExecuteOnCPU([a, b])) {\n    const aData = backend2.texData.get(a.dataId);\n    const bData = backend2.texData.get(b.dataId);\n    const [outValues, outShape] = multiplyImplCPU(a.shape, b.shape, aData.values, bData.values, dtype);\n    const out = backend2.makeTensorInfo(outShape, dtype);\n    const outData = backend2.texData.get(out.dataId);\n    outData.values = outValues;\n    return out;\n  }\n  let program;\n  if (env().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\")) {\n    program = new BinaryOpPackedProgram(MUL, a.shape, b.shape);\n  } else {\n    program = new BinaryOpProgram(MUL, a.shape, b.shape);\n  }\n  return backend2.runWebGLProgram(program, [a, b], dtype);\n}\nvar multiplyConfig2 = {\n  kernelName: Multiply,\n  backendName: \"webgl\",\n  kernelFunc: multiply3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/reshape.js\nfunction packedReshape(input2, afterShape, backend2) {\n  const input3DShape = [\n    getBatchDim(input2.shape),\n    ...getRowsCols(input2.shape)\n  ];\n  const input3D = {\n    dtype: input2.dtype,\n    shape: input3DShape,\n    dataId: input2.dataId\n  };\n  const afterShapeAs3D = [\n    getBatchDim(afterShape),\n    ...getRowsCols(afterShape)\n  ];\n  const program = new ReshapePackedProgram(afterShapeAs3D, input3DShape);\n  const preventEagerUnpackingOfOutput = true;\n  const customValues = [input3DShape];\n  const output = backend2.runWebGLProgram(program, [input3D], input2.dtype, customValues, preventEagerUnpackingOfOutput);\n  return { dataId: output.dataId, shape: afterShape, dtype: output.dtype };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Reshape.js\nfunction reshape4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { shape } = attrs;\n  const webglBackend = backend2;\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const $shape = util_exports.inferFromImplicitShape(shape, xSize);\n  const $xSize = util_exports.sizeFromShape($shape);\n  util_exports.assert(xSize === $xSize, () => `The new shape (${$shape}) has ${$xSize} elements and the old shape (${x.shape}) has ${xSize} elements. The new shape and old shape must have the same number of elements.`);\n  const xTexData = webglBackend.texData.get(x.dataId);\n  if (xTexData.isPacked && !isReshapeFree(x.shape, $shape) && !(xTexData.texture !== null && isReshapeFree(xTexData.shape, $shape))) {\n    return packedReshape(x, $shape, webglBackend);\n  }\n  webglBackend.incRef(x.dataId);\n  return { dataId: x.dataId, shape: $shape, dtype: x.dtype };\n}\nvar reshapeConfig2 = {\n  kernelName: Reshape,\n  backendName: \"webgl\",\n  kernelFunc: reshape4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/mean_gpu.js\nvar MeanProgram = class {\n  constructor(reduceInfo, divisor) {\n    this.variableNames = [\"x\"];\n    const { windowSize, batchSize, inSize, outSize } = reduceInfo;\n    this.outputShape = [batchSize, outSize];\n    const windowSizeNearestVec4 = Math.floor(windowSize / 4) * 4;\n    const windowSizeVec4Remainder = windowSize % 4;\n    let updateSnippet = `sumValue += dot(values, ones);`;\n    if (divisor != null) {\n      const denominator = 1 / divisor;\n      updateSnippet = `sumValue += dot(values * ${util_exports.isInt(denominator) ? denominator.toPrecision(2) : denominator}, ones);`;\n    }\n    let checkOutOfBounds = \"\";\n    if (inSize % windowSize > 0) {\n      checkOutOfBounds = `\n        if (inIdx < 0 || inIdx >= ${inSize}) {\n          return 0.0;\n        }\n      `;\n    }\n    this.userCode = `\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        ${checkOutOfBounds}\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * ${windowSize};\n\n        float sumValue = 0.0;\n\n        for (int i = 0; i < ${windowSizeNearestVec4}; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          ${updateSnippet}\n        }\n\n        int inIdx = inOffset + ${windowSizeNearestVec4};\n        if (${windowSizeVec4Remainder === 1}) {\n          vec4 values = vec4(getValue(batch, inIdx), 0.0, 0.0, 0.0);\n\n          ${updateSnippet}\n        } else if (${windowSizeVec4Remainder === 2}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1), 0.0, 0.0);\n\n          ${updateSnippet}\n        } else if (${windowSizeVec4Remainder === 3}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2), 0.0);\n\n          ${updateSnippet}\n        }\n        setOutput(sumValue);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/reduce_gpu.js\nvar ReduceProgram = class {\n  constructor(reduceInfo, reduceType) {\n    this.variableNames = [\"x\"];\n    const { windowSize, batchSize, inSize, outSize } = reduceInfo;\n    this.outputShape = [batchSize, outSize];\n    let initializationValue = \"0.0\";\n    let compareOp = ``;\n    if (reduceType === \"prod\") {\n      initializationValue = \"1.0\";\n    } else if (reduceType === \"min\") {\n      initializationValue = \"1.0 / 1e-20\";\n      compareOp = `min`;\n    } else if (reduceType === \"max\") {\n      initializationValue = \"-1.0 / 1e-20\";\n      compareOp = `max`;\n    }\n    let returnValue = `${reduceType}(${reduceType}(${reduceType}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;\n    if (reduceType === \"sum\") {\n      returnValue = `sumValue`;\n    } else if (reduceType === \"prod\") {\n      returnValue = `prodValue`;\n    } else if (reduceType === \"all\") {\n      returnValue = `allValue`;\n    } else if (reduceType === \"any\") {\n      returnValue = `anyValue`;\n    }\n    const windowSizeNearestVec4 = Math.floor(windowSize / 4) * 4;\n    const windowSizeVec4Remainder = windowSize % 4;\n    let updateSnippet = `\n      if (${reduceType === \"sum\"}) {\n        sumValue += dot(values, ones);\n      } else if (${reduceType === \"prod\"}) {\n        vec2 tmp = vec2(values[0], values[1]) * vec2(values[2], values[3]);\n        prodValue *= tmp[0] * tmp[1];\n      } else {\n        minMaxValue = ${compareOp}(values, minMaxValue);\n        if (${reduceType === \"min\"} || ${reduceType === \"max\"}) {\n          minMaxValue = ${compareOp}(values, minMaxValue);\n          bvec4 isNaN = isnan(values);\n          if (isNaN.r || isNaN.g || isNaN.b || isNaN.a) {\n            minMaxValue = vec4(NAN);\n          }\n        }\n      }\n    `;\n    let vecType = `vec4`;\n    if (reduceType === \"all\") {\n      initializationValue = \"1.0\";\n      updateSnippet = `\n        bool reducedAllValue = all(values);\n        float floatedReducedAllValue = float(reducedAllValue);\n        allValue = float(allValue >= 1.0 && floatedReducedAllValue >= 1.0);\n      `;\n      vecType = `bvec4`;\n    } else if (reduceType === \"any\") {\n      initializationValue = \"0.0\";\n      updateSnippet = `\n        bool reducedAnyValue = any(values);\n        float floatedReducedAnyValue = float(reducedAnyValue);\n        anyValue = float(anyValue >= 1.0 || floatedReducedAnyValue >= 1.0);\n      `;\n      vecType = `bvec4`;\n    }\n    let checkOutOfBounds = \"\";\n    if (inSize % windowSize > 0) {\n      checkOutOfBounds = `\n        if (inIdx < 0 || inIdx >= ${inSize}) {\n          return initializationValue;\n        }\n      `;\n    }\n    this.userCode = `\n      const float initializationValue = ${initializationValue};\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float getValue(int batch, int inIdx) {\n        ${checkOutOfBounds}\n        return getX(batch, inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * ${windowSize};\n\n        vec4 minMaxValue = vec4(${initializationValue});\n        float prodValue = 1.0;\n        float sumValue = 0.0;\n        float allValue = 1.0;\n        float anyValue = 0.0;\n\n        for (int i = 0; i < ${windowSizeNearestVec4}; i += 4) {\n          int inIdx = inOffset + i;\n          ${vecType} values = ${vecType}(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          ${updateSnippet}\n        }\n\n        int inIdx = inOffset + ${windowSizeNearestVec4};\n        if (${windowSizeVec4Remainder === 1}) {\n          ${vecType} values = ${vecType}(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          ${updateSnippet}\n        } else if (${windowSizeVec4Remainder === 2}) {\n          ${vecType} values = ${vecType}(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          ${updateSnippet}\n        } else if (${windowSizeVec4Remainder === 3}) {\n          ${vecType} values = ${vecType}(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          ${updateSnippet}\n        }\n        setOutput(${returnValue});\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/reduce.js\nfunction getReductionStages(inShape) {\n  const stages = [];\n  while (stages.length === 0 || stages[stages.length - 1].outSize !== 1) {\n    const outSize = stages.length ? stages[stages.length - 1].outSize : inShape[1];\n    const windowSize = backend_util_exports.computeOptimalWindowSize(outSize);\n    stages.push({\n      inSize: outSize,\n      windowSize,\n      outSize: Math.ceil(outSize / windowSize)\n    });\n  }\n  return stages;\n}\nfunction reduce(x, dtype, reductionType, backend2) {\n  const reductionStages = getReductionStages(x.shape);\n  let result = x;\n  for (let i2 = 0; i2 < reductionStages.length; i2++) {\n    const { inSize, windowSize, outSize } = reductionStages[i2];\n    let program;\n    let previousResult;\n    if (reductionType === \"mean\") {\n      program = i2 === 0 ? new MeanProgram({ windowSize, inSize, batchSize: x.shape[0], outSize }, inSize) : new MeanProgram({ windowSize, inSize, batchSize: x.shape[0], outSize });\n    } else {\n      program = new ReduceProgram({ windowSize, inSize, batchSize: x.shape[0], outSize }, reductionType);\n    }\n    previousResult = result;\n    result = backend2.runWebGLProgram(program, [result], dtype);\n    if (previousResult.dataId !== x.dataId) {\n      backend2.disposeIntermediateTensorInfo(previousResult);\n    }\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/transpose_gpu.js\nvar TransposeProgram = class {\n  constructor(aShape, newDim) {\n    this.variableNames = [\"A\"];\n    const outputShape = new Array(aShape.length);\n    for (let i2 = 0; i2 < outputShape.length; i2++) {\n      outputShape[i2] = aShape[newDim[i2]];\n    }\n    this.outputShape = outputShape;\n    this.rank = outputShape.length;\n    const dtype = getCoordsDataType(this.rank);\n    const switched = getSwitchedCoords(newDim);\n    this.userCode = `\n    void main() {\n      ${dtype} resRC = getOutputCoords();\n      setOutput(getA(${switched}));\n    }\n    `;\n  }\n};\nfunction getSwitchedCoords(newDim) {\n  const rank = newDim.length;\n  if (rank > 6) {\n    throw Error(`Transpose for rank ${rank} is not yet supported`);\n  }\n  const originalOrder = [\"resRC.x\", \"resRC.y\", \"resRC.z\", \"resRC.w\", \"resRC.u\", \"resRC.v\"];\n  const switchedCoords = new Array(rank);\n  for (let i2 = 0; i2 < newDim.length; i2++) {\n    switchedCoords[newDim[i2]] = originalOrder[i2];\n  }\n  return switchedCoords.join();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/transpose_packed_gpu.js\nvar TransposePackedProgram = class {\n  constructor(aShape, newDim) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    const outputShape = new Array(aShape.length);\n    for (let i2 = 0; i2 < outputShape.length; i2++) {\n      outputShape[i2] = aShape[newDim[i2]];\n    }\n    this.outputShape = outputShape;\n    this.rank = outputShape.length;\n    if (this.rank > 6) {\n      throw Error(`Packed transpose for rank ${this.rank} is not yet supported.`);\n    }\n    const dtype = getCoordsDataType(this.rank);\n    const outputOrder = getVecChannels(\"rc\", this.rank);\n    const switchedOrder = new Array(this.rank);\n    for (let i2 = 0; i2 < newDim.length; i2++) {\n      switchedOrder[newDim[i2]] = outputOrder[i2];\n    }\n    const innerDims = `vec2(${switchedOrder.slice(-2).join()})`;\n    const nextColumn = `++${outputOrder[this.rank - 1]} < ${outputShape[this.rank - 1]}`;\n    const getc = `getChannel(getA(${switchedOrder.join()}), ${innerDims})`;\n    this.userCode = `\n    void main() {\n      ${dtype} rc = getOutputCoords();\n      vec4 result = vec4(0.);\n      result[0] = ${getc};\n      if(${nextColumn}) {\n        result[1] = ${getc};\n      }\n      --${outputOrder[this.rank - 1]};\n      if(++${outputOrder[this.rank - 2]} < ${outputShape[this.rank - 2]}) {\n        result[2] = ${getc};\n        if(${nextColumn}) {\n          result[3] = ${getc};\n        }\n      }\n      setOutput(result);\n    }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Transpose_impl.js\nfunction transposeImpl2(x, perm, backend2) {\n  const program = env().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\") ? new TransposePackedProgram(x.shape, perm) : new TransposeProgram(x.shape, perm);\n  return backend2.runWebGLProgram(program, [x], x.dtype);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sum_impl.js\nfunction sumImpl(x, axis, keepDims, backend2) {\n  const reductionIndices = axis;\n  const xRank = x.shape.length;\n  const origAxes = util_exports.parseAxisParam(reductionIndices, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  const sumInputIsTransposed = permutedAxes != null;\n  let sumInput = x;\n  if (sumInputIsTransposed) {\n    sumInput = transposeImpl2(x, permutedAxes, backend2);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"sum\", axes, xRank);\n  const [sumOutShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(sumInput.shape, axes);\n  let outShape = sumOutShape;\n  if (keepDims) {\n    outShape = backend_util_exports.expandShapeToKeepDim(sumOutShape, origAxes);\n  }\n  const inSize = util_exports.sizeFromShape(reduceShape);\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const batchSize = xSize / inSize;\n  const reshapedInput = reshape4({ inputs: { x: sumInput }, attrs: { shape: [batchSize, inSize] }, backend: backend2 });\n  const outType = sumOutType(x.dtype);\n  const reduced = reduce(reshapedInput, outType, \"sum\", backend2);\n  const out = reshape4({ inputs: { x: reduced }, attrs: { shape: outShape }, backend: backend2 });\n  backend2.disposeIntermediateTensorInfo(reshapedInput);\n  backend2.disposeIntermediateTensorInfo(reduced);\n  if (sumInputIsTransposed) {\n    backend2.disposeIntermediateTensorInfo(sumInput);\n  }\n  return out;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sum.js\nfunction sum4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  return sumImpl(x, axis, keepDims, backend2);\n}\nvar sumConfig2 = {\n  kernelName: Sum,\n  backendName: \"webgl\",\n  kernelFunc: sum4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Transpose.js\nfunction transpose3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { perm } = attrs;\n  const webglBackend = backend2;\n  const xRank = x.shape.length;\n  const newShape = new Array(xRank);\n  for (let i2 = 0; i2 < newShape.length; i2++) {\n    newShape[i2] = x.shape[perm[i2]];\n  }\n  let out;\n  if (webglBackend.shouldExecuteOnCPU([x])) {\n    const xTexData = webglBackend.texData.get(x.dataId);\n    const values = xTexData.values;\n    const outValues = transposeImplCPU(values, x.shape, x.dtype, perm, newShape);\n    out = webglBackend.makeTensorInfo(newShape, x.dtype);\n    const outData = webglBackend.texData.get(out.dataId);\n    outData.values = outValues;\n  } else {\n    out = transposeImpl2(x, perm, webglBackend);\n  }\n  return out;\n}\nvar transposeConfig2 = {\n  kernelName: Transpose,\n  backendName: \"webgl\",\n  kernelFunc: transpose3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/BatchMatMul_impl.js\nvar MATMUL_SHARED_DIM_THRESHOLD = 1e3;\nfunction batchMatMulImpl({ a, b, transposeA, transposeB, backend: backend2, bias = null, preluActivationWeights = null, leakyreluAlpha = 0, activation: activation2 = null }) {\n  const aRank = a.shape.length;\n  const bRank = b.shape.length;\n  const innerShapeA = transposeA ? a.shape[aRank - 2] : a.shape[aRank - 1];\n  const innerShapeB = transposeB ? b.shape[bRank - 1] : b.shape[bRank - 2];\n  const outerShapeA = transposeA ? a.shape[aRank - 1] : a.shape[aRank - 2];\n  const outerShapeB = transposeB ? b.shape[bRank - 2] : b.shape[bRank - 1];\n  const outerDimsA = a.shape.slice(0, -2);\n  const outerDimsB = b.shape.slice(0, -2);\n  const batchDimA = util_exports.sizeFromShape(outerDimsA);\n  const batchDimB = util_exports.sizeFromShape(outerDimsB);\n  const outShapeOuterDims = broadcast_util_exports.assertAndGetBroadcastShape(a.shape.slice(0, -2), b.shape.slice(0, -2));\n  const outShape = outShapeOuterDims.concat([outerShapeA, outerShapeB]);\n  util_exports.assert(innerShapeA === innerShapeB, () => `Error in matMul: inner shapes (${innerShapeA}) and (${innerShapeB}) of Tensors with shapes ${a.shape} and ${b.shape} and transposeA=${transposeA} and transposeB=${transposeB} must match.`);\n  const a3dShape = transposeA ? [batchDimA, innerShapeA, outerShapeA] : [batchDimA, outerShapeA, innerShapeA];\n  const b3dShape = transposeB ? [batchDimB, outerShapeB, innerShapeB] : [batchDimB, innerShapeB, outerShapeB];\n  const a3d = reshape4({ inputs: { x: a }, backend: backend2, attrs: { shape: a3dShape } });\n  const b3d = reshape4({ inputs: { x: b }, backend: backend2, attrs: { shape: b3dShape } });\n  const intermediates = [a3d, b3d];\n  const batchDim = Math.max(batchDimA, batchDimB);\n  const sharedDim = transposeA ? a3d.shape[1] : a3d.shape[2];\n  const hasBias = bias != null;\n  const hasPreluActivationWeights = preluActivationWeights != null;\n  const hasLeakyreluAlpha = activation2 === \"leakyrelu\";\n  const fusedActivation = activation2 != null ? mapActivationToShaderProgram(activation2, true) : null;\n  const containsFusedOps = hasBias || hasPreluActivationWeights || hasLeakyreluAlpha || fusedActivation != null;\n  let out;\n  if ((outerShapeA === 1 || outerShapeB === 1) && sharedDim > MATMUL_SHARED_DIM_THRESHOLD && containsFusedOps === false) {\n    let aVec = a3d;\n    let bVec = b3d;\n    if (transposeA) {\n      aVec = transpose3({ inputs: { x: a3d }, backend: backend2, attrs: { perm: [0, 2, 1] } });\n      intermediates.push(aVec);\n    }\n    if (transposeB) {\n      bVec = transpose3({ inputs: { x: b3d }, backend: backend2, attrs: { perm: [0, 2, 1] } });\n      intermediates.push(bVec);\n    }\n    const shouldReshapeA = outerShapeB !== 1;\n    const shouldReshapeB = outerShapeB === 1;\n    let aVec3d = aVec;\n    if (shouldReshapeA) {\n      aVec3d = reshape4({\n        inputs: { x: aVec },\n        backend: backend2,\n        attrs: { shape: [batchDim, sharedDim, 1] }\n      });\n      intermediates.push(aVec3d);\n    }\n    const axis = outerShapeB === 1 ? 2 : 1;\n    let bVec3d = bVec;\n    if (shouldReshapeB) {\n      bVec3d = reshape4({\n        inputs: { x: bVec },\n        backend: backend2,\n        attrs: { shape: [batchDim, 1, sharedDim] }\n      });\n      intermediates.push(bVec3d);\n    }\n    const product = multiply3({ inputs: { a: aVec3d, b: bVec3d }, backend: backend2 });\n    out = sum4({ inputs: { x: product }, backend: backend2, attrs: { axis, keepDims: true } });\n    intermediates.push(product);\n  } else {\n    const dtype = upcastType(a.dtype, b.dtype);\n    const program = new MatMulPackedProgram(a3dShape, b3dShape, [batchDim, outerShapeA, outerShapeB], transposeA, transposeB, hasBias, fusedActivation, hasPreluActivationWeights, hasLeakyreluAlpha);\n    const inputs = [a3d, b3d];\n    if (bias != null) {\n      inputs.push(bias);\n    }\n    if (hasPreluActivationWeights) {\n      inputs.push(preluActivationWeights);\n    }\n    if (hasLeakyreluAlpha) {\n      const $leakyreluAlpha = backend2.makeTensorInfo([], \"float32\", util_exports.createScalarValue(leakyreluAlpha, \"float32\"));\n      inputs.push($leakyreluAlpha);\n      intermediates.push($leakyreluAlpha);\n    }\n    out = backend2.runWebGLProgram(program, inputs, dtype);\n  }\n  const outReshaped = reshape4({ inputs: { x: out }, backend: backend2, attrs: { shape: outShape } });\n  intermediates.push(out);\n  for (const i2 of intermediates) {\n    backend2.disposeIntermediateTensorInfo(i2);\n  }\n  return outReshaped;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/_FusedMatMul.js\nfunction _fusedMatMul2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b, bias, preluActivationWeights } = inputs;\n  const { transposeA, transposeB, activation: activation2, leakyreluAlpha } = attrs;\n  return batchMatMulImpl({\n    a,\n    b,\n    transposeA,\n    transposeB,\n    backend: backend2,\n    bias,\n    preluActivationWeights,\n    leakyreluAlpha,\n    activation: activation2\n  });\n}\nvar _fusedMatMulConfig2 = {\n  kernelName: _FusedMatMul,\n  backendName: \"webgl\",\n  kernelFunc: _fusedMatMul2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Abs.js\nvar ABS2 = `return abs(x);`;\nfunction abs3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (backend2.shouldExecuteOnCPU([x]) && x.dtype !== \"complex64\") {\n    const xData = backend2.texData.get(x.dataId);\n    const outValues = simpleAbsImplCPU(xData.values);\n    return backend2.makeTensorInfo(x.shape, x.dtype, outValues);\n  }\n  let program;\n  if (env().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\")) {\n    program = new UnaryOpPackedProgram(x.shape, ABS2);\n  } else {\n    program = new UnaryOpProgram(x.shape, ABS2);\n  }\n  return backend2.runWebGLProgram(program, [x], x.dtype);\n}\nvar absConfig2 = {\n  kernelName: Abs,\n  backendName: \"webgl\",\n  kernelFunc: abs3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Acos.js\nvar ACOS = CHECK_NAN_SNIPPET + `\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return acos(x);\n`;\nvar acos3 = unaryKernelFunc2({ opSnippet: ACOS });\nvar acosConfig2 = {\n  kernelName: Acos,\n  backendName: \"webgl\",\n  kernelFunc: acos3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Acosh.js\nvar ACOSH = CHECK_NAN_SNIPPET + `\n  if (x < 1.0) return NAN;\nreturn log(x + sqrt(x * x - 1.0));`;\nvar acosh3 = unaryKernelFunc2({ opSnippet: ACOSH });\nvar acoshConfig2 = {\n  kernelName: Acosh,\n  backendName: \"webgl\",\n  kernelFunc: acosh3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Add.js\nvar ADD = \"return a + b;\";\nvar addKernelFunc = binaryKernelFunc2({\n  opSnippet: ADD,\n  packedOpSnippet: ADD,\n  supportsComplex: true,\n  cpuKernelImpl: addImplCPU\n});\nvar addConfig2 = {\n  kernelName: Add,\n  backendName: \"webgl\",\n  kernelFunc: addKernelFunc\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/addn_gpu.js\nvar AddNProgram = class {\n  constructor(outputShape, shapes) {\n    this.outputShape = [];\n    this.outputShape = outputShape;\n    this.variableNames = shapes.map((_, i2) => `T${i2}`);\n    const snippets = [];\n    this.variableNames.forEach((variable2) => {\n      snippets.push(`float v${variable2} = get${variable2}AtOutCoords();`);\n    });\n    const operation = this.variableNames.map((variable2) => {\n      return `v${variable2}`;\n    }).join(\" + \");\n    this.userCode = `\n      void main() {\n        ${snippets.join(\"\\n        \")}\n\n        float result = ${operation};\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/addn_packed_gpu.js\nvar AddNPackedProgram = class {\n  constructor(outputShape, shapes) {\n    this.outputShape = [];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = outputShape;\n    this.variableNames = shapes.map((_, i2) => `T${i2}`);\n    const snippets = [];\n    this.variableNames.forEach((variable2) => {\n      snippets.push(`vec4 v${variable2} = get${variable2}AtOutCoords();`);\n    });\n    const operation = this.variableNames.map((variable2) => {\n      return `v${variable2}`;\n    }).join(\" + \");\n    this.userCode = `\n      void main() {\n        ${snippets.join(\"\\n        \")}\n\n        vec4 result = ${operation};\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/AddN.js\nfunction addN3(args) {\n  const { inputs, backend: backend2 } = args;\n  const tensors = inputs;\n  if (tensors.length === 1) {\n    return identity3({ inputs: { x: tensors[0] }, backend: backend2 });\n  }\n  if (tensors.length > env().get(\"WEBGL_MAX_TEXTURES_IN_SHADER\")) {\n    const midIndex = Math.floor(tensors.length / 2);\n    const leftSide = addN3({ inputs: tensors.slice(0, midIndex), backend: backend2 });\n    const rightSide = addN3({ inputs: tensors.slice(midIndex), backend: backend2 });\n    return addN3({ inputs: [leftSide, rightSide], backend: backend2 });\n  }\n  const dtype = tensors.map((t2) => t2.dtype).reduce((d1, d2) => upcastType(d1, d2));\n  const shapes = tensors.map((t2) => t2.shape);\n  const usePackedOp = env().getBool(\"WEBGL_PACK\");\n  const program = usePackedOp ? new AddNPackedProgram(tensors[0].shape, shapes) : new AddNProgram(tensors[0].shape, shapes);\n  return backend2.runWebGLProgram(program, tensors, dtype);\n}\nvar addNConfig2 = {\n  kernelName: AddN,\n  backendName: \"webgl\",\n  kernelFunc: addN3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/All.js\nfunction all3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  const xRank = x.shape.length;\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  let permutedX = x;\n  if (permutedAxes != null) {\n    permutedX = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"all\", axes, xRank);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(permutedX.shape, axes);\n  const inSize = util_exports.sizeFromShape(reduceShape);\n  const a2D = reshape4({ inputs: { x: permutedX }, backend: backend2, attrs: { shape: [-1, inSize] } });\n  const reduced = reduce(a2D, a2D.dtype, \"all\", backend2);\n  let res;\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(outShape, origAxes);\n    res = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: newShape } });\n  } else {\n    res = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: outShape } });\n  }\n  backend2.disposeIntermediateTensorInfo(a2D);\n  backend2.disposeIntermediateTensorInfo(reduced);\n  if (permutedAxes != null) {\n    backend2.disposeIntermediateTensorInfo(permutedX);\n  }\n  return res;\n}\nvar allConfig2 = {\n  kernelName: All,\n  backendName: \"webgl\",\n  kernelFunc: all3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Any.js\nfunction any3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  const xRank = x.shape.length;\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  let permutedX = x;\n  if (permutedAxes != null) {\n    permutedX = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"any\", axes, xRank);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(permutedX.shape, axes);\n  const inSize = util_exports.sizeFromShape(reduceShape);\n  const a2D = reshape4({ inputs: { x: permutedX }, backend: backend2, attrs: { shape: [-1, inSize] } });\n  const reduced = reduce(a2D, a2D.dtype, \"any\", backend2);\n  let res;\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(outShape, origAxes);\n    res = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: newShape } });\n  } else {\n    res = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: outShape } });\n  }\n  backend2.disposeIntermediateTensorInfo(a2D);\n  backend2.disposeIntermediateTensorInfo(reduced);\n  if (permutedAxes != null) {\n    backend2.disposeIntermediateTensorInfo(permutedX);\n  }\n  return res;\n}\nvar anyConfig2 = {\n  kernelName: Any,\n  backendName: \"webgl\",\n  kernelFunc: any3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/argminmax_gpu.js\nvar ArgMinMaxProgram = class {\n  constructor(reduceInfo, op2, firstPass) {\n    this.variableNames = [\"A\"];\n    const { windowSize, batchSize, outSize } = reduceInfo;\n    if (!firstPass) {\n      this.variableNames.push(\"bestIndicesA\");\n    }\n    this.outputShape = [batchSize, outSize];\n    const compOp = op2 === \"max\" ? \">\" : \"<\";\n    const indexSnippet = firstPass ? \"inOffset + i;\" : \"round(getBestIndicesA(batch, inOffset + i));\";\n    this.userCode = `\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = outIdx * ${windowSize};\n\n        int bestIndex = inOffset;\n        float bestValue = getA(batch, bestIndex);\n\n        for (int i = 0; i < ${windowSize}; i++) {\n          int inIdx = ${indexSnippet};\n          float candidate = getA(batch, inIdx);\n          if (candidate ${compOp} bestValue) {\n            bestValue = candidate;\n            bestIndex = inIdx;\n          }\n        }\n        setOutput(float(bestIndex));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/argminmax_packed_gpu.js\nvar ArgMinMaxPackedProgram = class {\n  constructor(shape, windowSize, op2, firstPass) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    util_exports.assert(shape.length > 2, () => `Packed arg${op2.charAt(0).toUpperCase() + op2.slice(1)} supports only inputs with rank above 2.`);\n    const inSize = shape[shape.length - 1];\n    const outSize = Math.ceil(inSize / windowSize);\n    this.outputShape = shape.slice(0, -1);\n    if (outSize > 1) {\n      this.outputShape.push(outSize);\n    }\n    if (!firstPass) {\n      this.variableNames.push(\"bestIndicesA\");\n    }\n    const outShape = this.outputShape;\n    const rank = outShape.length;\n    const dtype = getCoordsDataType(rank);\n    const coords3 = getChannels(\"coords\", rank);\n    let sourceLocSetup;\n    let sourceRank;\n    if (outSize === 1) {\n      sourceRank = rank + 1;\n      const sourceLocDType = getCoordsDataType(sourceRank);\n      sourceLocSetup = `\n        ${sourceLocDType} sourceLocR = ${sourceLocDType}(${coords3.join()}, 0);\n        ++${coords3[rank - 1]};\n        ${sourceLocDType} sourceLocG = ${sourceLocDType}(${coords3.join()}, 0);\n        ++${coords3[rank - 2]};\n        ${sourceLocDType} sourceLocA = ${sourceLocDType}(${coords3.join()}, 0);\n        --${coords3[rank - 1]};\n        ${sourceLocDType} sourceLocB = ${sourceLocDType}(${coords3.join()}, 0);\n        --${coords3[rank - 2]};`;\n    } else {\n      sourceRank = rank;\n      sourceLocSetup = `\n        ${dtype} sourceLocR = coords;\n        ++${coords3[rank - 1]};\n        ${dtype} sourceLocG = coords;\n        ++${coords3[rank - 2]};\n        ${dtype} sourceLocA = coords;\n        --${coords3[rank - 1]};\n        ${dtype} sourceLocB = coords;\n        --${coords3[rank - 2]};`;\n    }\n    const channels = [\"x\", \"y\", \"z\", \"w\", \"u\", \"v\"].slice(0, sourceRank);\n    const inChannel = \".\" + channels[sourceRank - 1];\n    const intChannels = channels.map((x) => \"int \" + x);\n    const srcRCoords = getChannels(\"sourceLocR\", sourceRank - 1).concat(\"inIdx.r\");\n    const srcGCoords = getChannels(\"sourceLocG\", sourceRank - 1).concat(\"inIdx.g\");\n    const srcBCoords = getChannels(\"sourceLocB\", sourceRank - 1).concat(\"inIdx.b\");\n    const srcACoords = getChannels(\"sourceLocA\", sourceRank - 1).concat(\"inIdx.a\");\n    const compOp = op2 === \"max\" ? \"greaterThan\" : \"lessThan\";\n    const fetchCandidateIdx = firstPass ? \"\" : `\n          inIdx = round(vec4(getBestIndicesAChannel(${srcRCoords.join()}),\n                             getBestIndicesAChannel(${srcGCoords.join()}),\n                             getBestIndicesAChannel(${srcBCoords.join()}),\n                             getBestIndicesAChannel(${srcACoords.join()})));`;\n    const fetchValue = `vec4(\n            getAChannel(${srcRCoords.join()}),\n            hasNextCol ? getAChannel(${srcGCoords.join()}) : 0.,\n            hasNextRow ? getAChannel(${srcBCoords.join()}) : 0.,\n            hasNextRow && hasNextCol ? getAChannel(${srcACoords.join()}) : 0.)`;\n    const getBestIndicesAChannelSnippet = firstPass ? \"\" : `\n      float getBestIndicesAChannel(${intChannels.join()}) {\n        return getChannel(getBestIndicesA(${channels.join()}),\n                                          vec2(${channels.slice(-2).join()}));\n      }`;\n    this.userCode = `\n      float getAChannel(${intChannels.join()}) {\n        return getChannel(getA(${channels.join()}),\n                               vec2(${channels.slice(-2).join()}));\n      }\n      ${getBestIndicesAChannelSnippet}\n      void main() {\n        ${dtype} coords = getOutputCoords();\n        bool hasNextCol = ${coords3[rank - 1]} < ${outShape[rank - 1] - 1};\n        bool hasNextRow = ${coords3[rank - 2]} < ${outShape[rank - 2] - 1};\n        ${sourceLocSetup}\n        ivec4 srcIdx = ivec4(sourceLocR${inChannel}, sourceLocG${inChannel},\n          sourceLocB${inChannel}, sourceLocA${inChannel}) * ${windowSize};\n        ivec4 inIdx = srcIdx;\n        vec4 bestIndex = vec4(inIdx);\n        vec4 bestValue = ${fetchValue};\n\n        for (int i = 0; i < ${windowSize}; i++) {\n          inIdx = srcIdx;\n          ${fetchCandidateIdx}\n          vec4 candidate = ${fetchValue};\n          bvec4 nan = isnan(candidate);\n          bvec4 replace = bvec4(\n            vec4(${compOp}(candidate, bestValue)) * (vec4(1.0) - vec4(nan)));\n\n          bestValue = vec4(replace.x  ? candidate.x : bestValue.x,\n                           replace.y  ? candidate.y : bestValue.y,\n                           replace.z  ? candidate.z : bestValue.z,\n                           replace.w  ? candidate.w : bestValue.w);\n          bestIndex = mix(bestIndex, vec4(inIdx), vec4(replace));\n          srcIdx++;\n        }\n        setOutput(bestIndex);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/arg_min_max.js\nfunction argReduce(backend2, x, reduceType, bestIndicesA = null) {\n  let batchSize = x.shape[0];\n  let inSize = x.shape[1];\n  if (bestIndicesA != null) {\n    batchSize = bestIndicesA.shape[0];\n    inSize = bestIndicesA.shape[1];\n  }\n  const windowSize = backend_util_exports.computeOptimalWindowSize(inSize);\n  const reduceInfo = { windowSize, inSize, batchSize, outSize: Math.ceil(inSize / windowSize) };\n  const program = new ArgMinMaxProgram(reduceInfo, reduceType, bestIndicesA == null);\n  const inputs = [x];\n  if (bestIndicesA != null) {\n    inputs.push(bestIndicesA);\n  }\n  const output = backend2.runWebGLProgram(program, inputs, \"int32\");\n  if (output.shape[1] === 1) {\n    return output;\n  }\n  const result = argReduce(backend2, x, reduceType, output);\n  backend2.disposeIntermediateTensorInfo(output);\n  return result;\n}\nfunction argReducePacked(backend2, x, reduceType, bestIndicesA = null) {\n  const inShape = bestIndicesA != null ? bestIndicesA.shape : x.shape;\n  const inSize = inShape[inShape.length - 1];\n  const windowSize = backend_util_exports.computeOptimalWindowSize(inSize);\n  const program = new ArgMinMaxPackedProgram(inShape, windowSize, reduceType, bestIndicesA == null);\n  const inputs = bestIndicesA == null ? [x] : [x, bestIndicesA];\n  const output = backend2.runWebGLProgram(program, inputs, \"int32\");\n  if (output.shape.length === x.shape.length) {\n    const result = argReducePacked(backend2, x, reduceType, output);\n    backend2.disposeIntermediateTensorInfo(output);\n    return result;\n  }\n  return output;\n}\nfunction argMinMaxReduce(backend2, x, axis, reduceType) {\n  const axes = [axis];\n  backend_util_exports.assertAxesAreInnerMostDims(\"arg\" + reduceType.charAt(0).toUpperCase() + reduceType.slice(1), axes, x.shape.length);\n  if (!env().getBool(\"WEBGL_PACK_REDUCE\") || x.shape.length <= 2) {\n    const intermediateTensorInfos = [];\n    const xtexData = backend2.texData.get(x.dataId);\n    const xIsPacked = xtexData !== null && xtexData.isPacked;\n    let xUnPacked = x;\n    if (xIsPacked) {\n      xUnPacked = backend2.unpackTensor(x);\n      intermediateTensorInfos.push(xUnPacked);\n    }\n    const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(xUnPacked.shape, axes);\n    const inSize = util_exports.sizeFromShape(reduceShape);\n    const a2D = reshape4({ inputs: { x: xUnPacked }, backend: backend2, attrs: { shape: [-1, inSize] } });\n    intermediateTensorInfos.push(a2D);\n    const reduced = argReduce(backend2, a2D, reduceType);\n    intermediateTensorInfos.push(reduced);\n    const reshaped = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: outShape } });\n    intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n    return reshaped;\n  }\n  return argReducePacked(backend2, x, reduceType);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ArgMax.js\nfunction argMax3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis } = attrs;\n  let axes = util_exports.parseAxisParam(axis, x.shape);\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  const intermediateTensorInfos = [];\n  if (permutedAxes != null) {\n    $x = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    intermediateTensorInfos.push($x);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, $x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"argMax\", [axes[0]], $x.shape.length);\n  const out = argMinMaxReduce(backend2, $x, axes[0], \"max\");\n  intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return out;\n}\nvar argMaxConfig2 = {\n  kernelName: ArgMax,\n  backendName: \"webgl\",\n  kernelFunc: argMax3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ArgMin.js\nfunction argMin3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis } = attrs;\n  let axes = util_exports.parseAxisParam(axis, x.shape);\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  const intermediateTensorInfos = [];\n  if (permutedAxes != null) {\n    $x = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    intermediateTensorInfos.push($x);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, $x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"argMin\", [axes[0]], $x.shape.length);\n  const out = argMinMaxReduce(backend2, $x, axes[0], \"min\");\n  intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return out;\n}\nvar argMinConfig2 = {\n  kernelName: ArgMin,\n  backendName: \"webgl\",\n  kernelFunc: argMin3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Asin.js\nvar ASIN = CHECK_NAN_SNIPPET + `\n  if (abs(x) > 1.) {\n    return NAN;\n  }\n  return asin(x);\n`;\nvar asin3 = unaryKernelFunc2({ opSnippet: ASIN });\nvar asinConfig2 = {\n  kernelName: Asin,\n  backendName: \"webgl\",\n  kernelFunc: asin3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Asinh.js\nvar ASINH = CHECK_NAN_SNIPPET + `return log(x + sqrt(x * x + 1.0));`;\nvar asinh3 = unaryKernelFunc2({ opSnippet: ASINH });\nvar asinhConfig2 = {\n  kernelName: Asinh,\n  backendName: \"webgl\",\n  kernelFunc: asinh3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Atan.js\nvar ATAN = CHECK_NAN_SNIPPET + `\n  return atan(x);\n`;\nvar atan4 = unaryKernelFunc2({ opSnippet: ATAN });\nvar atanConfig2 = {\n  kernelName: Atan,\n  backendName: \"webgl\",\n  kernelFunc: atan4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Atan2.js\nvar ATAN2 = CHECK_NAN_SNIPPET_BINARY + `\n  return atan(a, b);\n`;\nvar ATAN2_PACKED = `\n  vec4 result = atan(a, b);\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  ` + CHECK_NAN_SNIPPET_BINARY_PACKED + `\n  return result;\n`;\nvar atan23 = binaryKernelFunc2({ opSnippet: ATAN2, packedOpSnippet: ATAN2_PACKED });\nvar atan2Config2 = {\n  kernelName: Atan2,\n  backendName: \"webgl\",\n  kernelFunc: atan23\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Atanh.js\nvar ATANH = CHECK_NAN_SNIPPET + `\n  if ((x < -1.0) || (x > 1.0)) return NAN;\nreturn (log(1.0 + x) - log(1.0 - x)) / 2.0;`;\nvar atanh3 = unaryKernelFunc2({ opSnippet: ATANH });\nvar atanhConfig2 = {\n  kernelName: Atanh,\n  backendName: \"webgl\",\n  kernelFunc: atanh3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/pool_gpu.js\nvar Pool2DProgram = class {\n  constructor(convInfo, poolType, computePositions, flattenPositions = false, includeBatchInIndex = false) {\n    this.variableNames = [\"x\"];\n    if (poolType === \"avg\" && computePositions) {\n      throw new Error(\"Cannot compute positions for average pool.\");\n    }\n    const filterWidth = convInfo.filterWidth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationHeight = convInfo.dilationHeight;\n    const dilationWidth = convInfo.dilationWidth;\n    const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n    const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n    const padTop = convInfo.padInfo.top;\n    const padLeft = convInfo.padInfo.left;\n    this.outputShape = convInfo.outShape;\n    const isAvgPool = poolType === \"avg\";\n    const batchFlattenPositionStr = `((batch  * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + d`;\n    const flattenPositionStr = `(xR * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + d`;\n    let initializationValue = \"0.0\";\n    if (!isAvgPool) {\n      initializationValue = \"-1.0 / 1e-20\";\n    }\n    if (computePositions) {\n      const compareOp2 = \">=\";\n      this.userCode = `\n        const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});\n        const ivec2 pads = ivec2(${padTop}, ${padLeft});\n\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int batch = coords[0];\n          int d = coords[3];\n\n          ivec2 xRCCorner = coords.yz * strides - pads;\n          int xRCorner = xRCCorner.x;\n          int xCCorner = xRCCorner.y;\n\n          // max/min x(?, ?, d) to get y(yR, yC, d).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n          float avgValue = 0.0;\n\n          for (int wR = 0; wR < ${effectiveFilterHeight};\n              wR += ${dilationHeight}) {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= ${convInfo.inHeight}) {\n              continue;\n            }\n\n            for (int wC = 0; wC < ${effectiveFilterWidth};\n                wC += ${dilationWidth}) {\n              int xC = xCCorner + wC;\n\n              if (xC < 0 || xC >= ${convInfo.inWidth}) {\n                continue;\n              }\n\n              float value = getX(batch, xR, xC, d);\n\n              // If a min / max value has already been found, use it. If not,\n              // use the current value.\n              float currMinMaxValue = mix(\n                  value, minMaxValue, minMaxValueFound);\n              if (value ${compareOp2} currMinMaxValue) {\n                minMaxValue = value;\n                minMaxValueFound = 1.0;\n                minMaxPosition = ${flattenPositions ? includeBatchInIndex ? batchFlattenPositionStr : flattenPositionStr : `wR * ${effectiveFilterWidth} + wC`};\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      `;\n      return;\n    }\n    const compareOp = \"max\";\n    let returnValue = `${poolType}(${poolType}(${poolType}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;\n    if (poolType === \"avg\") {\n      returnValue = `avgValue / count`;\n    }\n    const filterWidthNearestVec4 = Math.floor(filterWidth / 4) * 4;\n    const filterWidthVec4Remainder = filterWidth % 4;\n    const updateSnippet = `\n      if (${isAvgPool}) {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = ${compareOp}(values, minMaxValue);\n      }\n    `;\n    this.userCode = `\n      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});\n      const ivec2 pads = ivec2(${padTop}, ${padLeft});\n      const float initializationValue = ${initializationValue};\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xR, int xC, int d) {\n        if (xC < 0 || xC >= ${convInfo.inWidth}) {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xR, xC, d);\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d = coords[3];\n\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // max/min x(?, ?, d) to get y(yR, yC, d).\n        // ? = to be determined\n        vec4 minMaxValue = vec4(${initializationValue});\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wR = 0; wR < ${effectiveFilterHeight};\n            wR += ${dilationHeight}) {\n          int xR = xRCorner + wR;\n\n          if (xR < 0 || xR >= ${convInfo.inHeight}) {\n            continue;\n          }\n\n          for (int wC = 0; wC < ${filterWidthNearestVec4}; wC += 4) {\n            int xC = xCCorner + wC * ${dilationWidth};\n\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + ${dilationWidth}, d),\n              getValue(batch, xR, xC + 2 * ${dilationWidth}, d),\n              getValue(batch, xR, xC + 3 * ${dilationWidth}, d)\n            );\n\n            ${updateSnippet}\n          }\n\n          int xC = xCCorner + ${filterWidthNearestVec4};\n          if (${filterWidthVec4Remainder === 1}) {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              initializationValue,\n              initializationValue,\n              initializationValue\n            );\n\n            ${updateSnippet}\n          } else if (${filterWidthVec4Remainder === 2}) {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + ${dilationWidth}, d),\n              initializationValue,\n              initializationValue\n            );\n\n            ${updateSnippet}\n          } else if (${filterWidthVec4Remainder === 3}) {\n            vec4 values = vec4(\n              getValue(batch, xR, xC, d),\n              getValue(batch, xR, xC + ${dilationWidth}, d),\n              getValue(batch, xR, xC + 2 * ${dilationWidth}, d),\n              initializationValue\n            );\n\n            ${updateSnippet}\n          }\n        }\n        setOutput(${returnValue});\n      }\n    `;\n  }\n};\nvar Pool3DProgram = class {\n  constructor(convInfo, poolType, computePositions, flattenPositions = false, includeBatchInIndex = false) {\n    this.variableNames = [\"x\"];\n    if (poolType === \"avg\" && computePositions) {\n      throw new Error(\"Cannot compute positions for average pool.\");\n    }\n    const filterWidth = convInfo.filterWidth;\n    const strideDepth = convInfo.strideDepth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationDepth = convInfo.dilationDepth;\n    const dilationHeight = convInfo.dilationHeight;\n    const dilationWidth = convInfo.dilationWidth;\n    const effectiveFilterDepth = convInfo.effectiveFilterDepth;\n    const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n    const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n    const padFront = convInfo.padInfo.front;\n    const padTop = convInfo.padInfo.top;\n    const padLeft = convInfo.padInfo.left;\n    this.outputShape = convInfo.outShape;\n    const isAvgPool = poolType === \"avg\";\n    let initializationValue = \"0.0\";\n    if (!isAvgPool) {\n      initializationValue = \"-1.0 / 1e-20\";\n    }\n    if (computePositions) {\n      const compareOp2 = \">=\";\n      this.userCode = `\n        const ivec3 strides =\n            ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});\n        const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});\n\n        void main() {\n          ivec5 coords = getOutputCoords();\n          int batch = coords.x;\n          int ch = coords.u;\n\n          ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n          int xDCorner = xCorner.x;\n          int xRCorner = xCorner.y;\n          int xCCorner = xCorner.z;\n\n          // max/min x(?, ?, ?, ch) to get y(yD, yR, yC, ch).\n          // ? = to be determined\n          float minMaxValue = 0.0;\n          float minMaxValueFound = 0.0;\n          int minMaxPosition = 0;\n\n          for (int wD = 0; wD < ${effectiveFilterDepth};\n              wD += ${dilationDepth}) {\n            int xD = xDCorner + wD;\n\n            if (xD < 0 || xD >= ${convInfo.inDepth}) {\n              continue;\n            }\n\n            for (int wR = 0; wR < ${effectiveFilterHeight};\n                wR += ${dilationHeight}) {\n              int xR = xRCorner + wR;\n\n              if (xR < 0 || xR >= ${convInfo.inHeight}) {\n                continue;\n              }\n\n              for (int wC = 0; wC < ${effectiveFilterWidth};\n                  wC += ${dilationWidth}) {\n                int xC = xCCorner + wC;\n\n                if (xC < 0 || xC >= ${convInfo.inWidth}) {\n                  continue;\n                }\n\n                float value = getX(batch, xD, xR, xC, ch);\n\n                // If a min / max value has already been found, use it. If not,\n                // use the current value.\n                float currMinMaxValue = mix(\n                    value, minMaxValue, minMaxValueFound);\n                if (value ${compareOp2} currMinMaxValue) {\n                  minMaxValue = value;\n                  minMaxValueFound = 1.0;\n                  minMaxPosition = ${flattenPositions ? includeBatchInIndex ? `(((batch * ${convInfo.inDepth} + xD) * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + ch` : `((xD * ${convInfo.inHeight} + xR) * ${convInfo.inWidth} + xC) * ${convInfo.inChannels} + ch` : `wD * ${effectiveFilterHeight} * ${effectiveFilterWidth} +\n                      wR * ${effectiveFilterWidth} + wC`};\n                }\n              }\n            }\n          }\n          setOutput(float(minMaxPosition));\n        }\n      `;\n      return;\n    }\n    const compareOp = \"max\";\n    let returnValue = `${poolType}(${poolType}(${poolType}(minMaxValue[0], minMaxValue[1]), minMaxValue[2]), minMaxValue[3])`;\n    if (poolType === \"avg\") {\n      returnValue = `avgValue / count`;\n    }\n    const filterWidthNearestVec4 = Math.floor(filterWidth / 4) * 4;\n    const filterWidthVec4Remainder = filterWidth % 4;\n    const updateSnippet = `\n      if (${isAvgPool}) {\n        avgValue += dot(values, ones);\n      } else {\n        minMaxValue = ${compareOp}(values, minMaxValue);\n      }\n    `;\n    this.userCode = `\n      const ivec3 strides =\n        ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});\n      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});\n      const float initializationValue = ${initializationValue};\n      const vec4 ones = vec4(1.0, 1.0, 1.0, 1.0);\n\n      float count = 0.0;\n\n      float getValue(int batch, int xD, int xR, int xC, int ch) {\n        if (xC < 0 || xC >= ${convInfo.inWidth}) {\n          return initializationValue;\n        }\n        count += 1.0;\n        return getX(batch, xD, xR, xC, ch);\n      }\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 xCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xDCorner = xCorner.x;\n        int xRCorner = xCorner.y;\n        int xCCorner = xCorner.z;\n\n        // max/min x(?, ?, ?, d) to get y(yD, yR, yC, ch).\n        // ? = to be determined\n        vec4 minMaxValue = vec4(${initializationValue});\n        float avgValue = 0.0;\n        count = 0.0;\n\n        for (int wD = 0; wD < ${effectiveFilterDepth};\n            wD += ${dilationDepth}) {\n          int xD = xDCorner + wD;\n\n          if (xD < 0 || xD >= ${convInfo.inDepth}) {\n            continue;\n          }\n\n          for (int wR = 0; wR < ${effectiveFilterHeight};\n            wR += ${dilationHeight}) {\n            int xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= ${convInfo.inHeight}) {\n              continue;\n            }\n\n            for (int wC = 0; wC < ${filterWidthNearestVec4}; wC += 4) {\n              int xC = xCCorner + wC * ${dilationWidth};\n\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + ${dilationWidth}, ch),\n                getValue(batch, xD, xR, xC + 2 * ${dilationWidth}, ch),\n                getValue(batch, xD, xR, xC + 3 * ${dilationWidth}, ch)\n              );\n\n              ${updateSnippet}\n            }\n\n            int xC = xCCorner + ${filterWidthNearestVec4};\n            if (${filterWidthVec4Remainder === 1}) {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                initializationValue,\n                initializationValue,\n                initializationValue\n              );\n\n              ${updateSnippet}\n            } else if (${filterWidthVec4Remainder === 2}) {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + ${dilationWidth}, ch),\n                initializationValue,\n                initializationValue\n              );\n\n              ${updateSnippet}\n            } else if (${filterWidthVec4Remainder === 3}) {\n              vec4 values = vec4(\n                getValue(batch, xD, xR, xC, ch),\n                getValue(batch, xD, xR, xC + ${dilationWidth}, ch),\n                getValue(batch, xD, xR, xC + 2 * ${dilationWidth}, ch),\n                initializationValue\n              );\n\n              ${updateSnippet}\n            }\n          }\n          setOutput(${returnValue});\n        }\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/AvgPool.js\nfunction avgPool3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  assertNotComplex2(x, \"avgPool\");\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = 1;\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in avgPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  if (convInfo.filterWidth === 1 && convInfo.filterHeight === 1 && util_exports.arraysEqual(convInfo.inShape, convInfo.outShape)) {\n    return identity3({ inputs: { x }, backend: backend2 });\n  }\n  const avgPoolProgram = new Pool2DProgram(convInfo, \"avg\", false);\n  return backend2.runWebGLProgram(avgPoolProgram, [x], \"float32\");\n}\nvar avgPoolConfig2 = {\n  kernelName: AvgPool,\n  backendName: \"webgl\",\n  kernelFunc: avgPool3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/AvgPool3D.js\nfunction avgPool3D2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { filterSize, strides, pad: pad3, dimRoundingMode, dataFormat } = attrs;\n  const dilations = [1, 1, 1];\n  const convInfo = backend_util_exports.computePool3DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode, dataFormat);\n  const avgPoolProgram = new Pool3DProgram(convInfo, \"avg\", false);\n  return backend2.runWebGLProgram(avgPoolProgram, [x], \"float32\");\n}\nvar avgPool3DConfig2 = {\n  kernelName: AvgPool3D,\n  backendName: \"webgl\",\n  kernelFunc: avgPool3D2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/avg_pool_backprop_gpu.js\nvar AvgPool2DBackpropProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\"];\n    this.outputShape = convInfo.inShape;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationHeight = convInfo.dilationHeight;\n    const dilationWidth = convInfo.dilationWidth;\n    const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n    const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n    const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n    const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n    const avgMultiplier = 1 / (filterHeight * filterWidth);\n    this.userCode = `\n      const ivec2 pads = ivec2(${padTop}, ${padLeft});\n      const float avgMultiplier = float(${avgMultiplier});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ${effectiveFilterHeight};\n            wR += ${dilationHeight}) {\n          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;\n\n          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < ${effectiveFilterWidth};\n            wC+= ${dilationWidth}) {\n            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;\n\n            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n\n            dotProd += dyValue * avgMultiplier;\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\nvar AvgPool3DBackpropProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\"];\n    this.outputShape = convInfo.inShape;\n    const filterDepth = convInfo.filterDepth;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const strideDepth = convInfo.strideDepth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationDepth = convInfo.dilationDepth;\n    const dilationHeight = convInfo.dilationHeight;\n    const dilationWidth = convInfo.dilationWidth;\n    const effectiveFilterDepth = convInfo.effectiveFilterDepth;\n    const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n    const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n    const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;\n    const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n    const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n    const avgMultiplier = 1 / (filterDepth * filterHeight * filterWidth);\n    this.userCode = `\n      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});\n      const float avgMultiplier = float(${avgMultiplier});\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, d) with pos mask(:, :, :, ch) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < ${effectiveFilterDepth};\n            wD += ${dilationDepth}) {\n          float dyD = float(dyDCorner + wD) / ${strideDepth}.0;\n\n          if (dyD < 0.0 || dyD >= ${convInfo.outDepth}.0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < ${effectiveFilterHeight};\n              wR += ${dilationHeight}) {\n            float dyR = float(dyRCorner + wR) / ${strideHeight}.0;\n\n            if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < ${effectiveFilterWidth};\n                wC += ${dilationWidth}) {\n              float dyC = float(dyCCorner + wC) / ${strideWidth}.0;\n\n              if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n\n              dotProd += dyValue * avgMultiplier;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/AvgPool3DGrad.js\nfunction avgPool3DGrad2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2 } = inputs;\n  const x = input2;\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = [1, 1, 1];\n  const convInfo = backend_util_exports.computePool3DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  const avgPoolBackpropProgram = new AvgPool3DBackpropProgram(convInfo);\n  return backend2.runWebGLProgram(avgPoolBackpropProgram, [dy], x.dtype);\n}\nvar avgPool3DGradConfig3 = {\n  kernelName: AvgPool3DGrad,\n  backendName: \"webgl\",\n  kernelFunc: avgPool3DGrad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/AvgPoolGrad.js\nfunction avgPoolGrad3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2 } = inputs;\n  const x = input2;\n  assertNotComplex2([dy, input2], \"avgPoolGrad\");\n  const { filterSize, strides, pad: pad3 } = attrs;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, 1, pad3);\n  const avgPoolBackpropProgram = new AvgPool2DBackpropProgram(convInfo);\n  return backend2.runWebGLProgram(avgPoolBackpropProgram, [dy], x.dtype);\n}\nvar avgPoolGradConfig3 = {\n  kernelName: AvgPoolGrad,\n  backendName: \"webgl\",\n  kernelFunc: avgPoolGrad3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/BatchMatMul.js\nfunction batchMatMul2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b } = inputs;\n  const { transposeA, transposeB } = attrs;\n  return batchMatMulImpl({ a, b, transposeA, transposeB, backend: backend2 });\n}\nvar batchMatMulConfig2 = {\n  kernelName: BatchMatMul,\n  backendName: \"webgl\",\n  kernelFunc: batchMatMul2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/batchnorm_gpu.js\nvar BatchNormProgram = class {\n  constructor(xShape, meanShape, varianceShape, offsetShape, scaleShape, varianceEpsilon) {\n    this.outputShape = [];\n    this.variableNames = [\"x\", \"mean\", \"variance\"];\n    backend_util_exports.assertAndGetBroadcastShape(xShape, meanShape);\n    backend_util_exports.assertAndGetBroadcastShape(xShape, varianceShape);\n    let offsetSnippet = \"0.0\";\n    if (offsetShape != null) {\n      backend_util_exports.assertAndGetBroadcastShape(xShape, offsetShape);\n      this.variableNames.push(\"offset\");\n      offsetSnippet = \"getOffsetAtOutCoords()\";\n    }\n    let scaleSnippet = \"1.0\";\n    if (scaleShape != null) {\n      backend_util_exports.assertAndGetBroadcastShape(xShape, scaleShape);\n      this.variableNames.push(\"scale\");\n      scaleSnippet = \"getScaleAtOutCoords()\";\n    }\n    this.outputShape = xShape;\n    this.userCode = `\n      void main() {\n        float x = getXAtOutCoords();\n        float mean = getMeanAtOutCoords();\n        float variance = getVarianceAtOutCoords();\n        float offset = ${offsetSnippet};\n        float scale = ${scaleSnippet};\n        float inv = scale * inversesqrt(variance + float(${varianceEpsilon}));\n        setOutput(dot(vec3(x, -mean, offset), vec3(inv, inv, 1)));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/batchnorm_packed_gpu.js\nvar BatchNormPackedProgram = class {\n  constructor(xShape, meanShape, varianceShape, offsetShape, scaleShape, varianceEpsilon) {\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.variableNames = [\"x\", \"mean\", \"variance\"];\n    backend_util_exports.assertAndGetBroadcastShape(xShape, meanShape);\n    backend_util_exports.assertAndGetBroadcastShape(xShape, varianceShape);\n    let offsetSnippet = \"vec4(0.0)\";\n    if (offsetShape != null) {\n      backend_util_exports.assertAndGetBroadcastShape(xShape, offsetShape);\n      this.variableNames.push(\"offset\");\n      offsetSnippet = \"getOffsetAtOutCoords()\";\n    }\n    let scaleSnippet = \"vec4(1.0)\";\n    if (scaleShape != null) {\n      backend_util_exports.assertAndGetBroadcastShape(xShape, scaleShape);\n      this.variableNames.push(\"scale\");\n      scaleSnippet = \"getScaleAtOutCoords()\";\n    }\n    this.outputShape = xShape;\n    this.userCode = `\n      void main() {\n        vec4 offset = ${offsetSnippet};\n        vec4 scale = ${scaleSnippet};\n\n        vec4 x = getXAtOutCoords();\n        vec4 mean = getMeanAtOutCoords();\n        vec4 variance = getVarianceAtOutCoords();\n\n        vec4 inv = scale * inversesqrt(variance + vec4(${varianceEpsilon}));\n\n        setOutput((x - mean) * inv + offset);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/BatchNorm.js\nvar batchNorm3 = ({ inputs, backend: backend2, attrs }) => {\n  const { x, mean: mean5, variance, offset, scale: scale2 } = inputs;\n  util_exports.assert(mean5.shape.length === variance.shape.length, () => \"Batch normalization gradient requires mean and variance to have equal ranks.\");\n  util_exports.assert(offset == null || mean5.shape.length === offset.shape.length, () => \"Batch normalization gradient requires mean and offset to have equal ranks.\");\n  util_exports.assert(scale2 == null || mean5.shape.length === scale2.shape.length, () => \"Batch normalization gradient requires mean and scale to have equal ranks.\");\n  let { varianceEpsilon } = attrs;\n  if (varianceEpsilon == null) {\n    varianceEpsilon = 1e-3;\n  }\n  const finalInputs = [x, mean5, variance];\n  let offsetShape = null;\n  if (offset != null) {\n    offsetShape = offset.shape;\n    finalInputs.push(offset);\n  }\n  let scaleShape = null;\n  if (scale2 != null) {\n    scaleShape = scale2.shape;\n    finalInputs.push(scale2);\n  }\n  const program = env().getBool(\"WEBGL_PACK_NORMALIZATION\") ? new BatchNormPackedProgram(x.shape, mean5.shape, variance.shape, offsetShape, scaleShape, varianceEpsilon) : new BatchNormProgram(x.shape, mean5.shape, variance.shape, offsetShape, scaleShape, varianceEpsilon);\n  const output = backend2.runWebGLProgram(program, finalInputs, finalInputs[0].dtype);\n  return output;\n};\nvar batchNormConfig2 = {\n  kernelName: FusedBatchNorm,\n  backendName: \"webgl\",\n  kernelFunc: batchNorm3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/slice_gpu.js\nvar SliceProgram = class {\n  constructor(destSize) {\n    this.variableNames = [\"source\"];\n    this.outputShape = destSize;\n    this.rank = destSize.length;\n    const dtype = getCoordsDataType(this.rank);\n    this.customUniforms = [{ name: \"start\", arrayIndex: this.rank, type: \"int\" }];\n    const sourceCoords = getCoords(this.rank);\n    let body;\n    const coordSum = destSize.map((_, i2) => {\n      return `sourceLoc.${coords[i2]} = start[${i2}] + coords.${coords[i2]};`;\n    });\n    body = `\n        ${dtype} sourceLoc;\n        ${dtype} coords = getOutputCoords();\n        ${coordSum.join(\"\\n\")}\n      `;\n    this.userCode = `\n      void main() {\n        ${body}\n        setOutput(getSource(${sourceCoords}));\n      }\n    `;\n  }\n};\nvar coords = [\"x\", \"y\", \"z\", \"w\", \"u\", \"v\"];\nfunction getCoords(rank) {\n  if (rank === 1) {\n    return \"sourceLoc\";\n  } else if (rank <= 6) {\n    return coords.slice(0, rank).map((x) => \"sourceLoc.\" + x).join(\",\");\n  } else {\n    throw Error(`Slicing for rank ${rank} is not yet supported`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/slice_packed_gpu.js\nvar SlicePackedProgram = class {\n  constructor(destSize) {\n    this.variableNames = [\"source\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = destSize;\n    this.rank = destSize.length;\n    this.customUniforms = [{ name: \"start\", arrayIndex: this.rank, type: \"int\" }];\n    const dtype = getCoordsDataType(this.rank);\n    const coords3 = getChannels(\"coords\", this.rank);\n    const sourceLoc = getChannels(\"sourceLoc\", this.rank);\n    const innerDims = this.rank === 1 ? \"sourceLoc\" : `vec2(${sourceLoc.slice(-2).join()})`;\n    const getChannel = `getChannel(getSource(${sourceLoc.join()}), ${innerDims})`;\n    const upperRow = `\n      result.x = ${getChannel};\n      if (++${coords3[this.rank - 1]} < ${destSize[this.rank - 1]}) {\n        ++${sourceLoc[this.rank - 1]};\n        result.y = ${getChannel};\n        --${sourceLoc[this.rank - 1]};\n      }\n    `;\n    const lowerRow = this.rank === 1 ? \"\" : `\n      --${coords3[this.rank - 1]};\n      if (++${coords3[this.rank - 2]} < ${destSize[this.rank - 2]}) {\n        ++${sourceLoc[this.rank - 2]};\n        result.z = ${getChannel};\n        if (++${coords3[this.rank - 1]} < ${destSize[this.rank - 1]}) {\n          ++${sourceLoc[this.rank - 1]};\n          result.w = ${getChannel};\n        }\n      }\n    `;\n    const sourceLocSetup = this.rank <= 4 ? `sourceLoc = coords +\n            ${dtype}(${destSize.map((_, i2) => `start[${i2}]`).join()});` : destSize.map((_, i2) => `${sourceLoc[i2]} = ${coords3[i2]} + start[${i2}];`).join(\"\\n\");\n    this.userCode = `\n      void main() {\n        ${dtype} coords = getOutputCoords();\n        ${dtype} sourceLoc;\n        ${sourceLocSetup}\n        vec4 result = vec4(0.);\n        ${upperRow}\n        ${lowerRow}\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Slice.js\nfunction shallowSlice(x, begin, size, backend2) {\n  const xTexData = backend2.texData.get(x.dataId);\n  const t2 = backend2.makeTensorInfo(size, x.dtype);\n  const newTexData = backend2.texData.get(t2.dataId);\n  Object.assign(newTexData, xTexData);\n  newTexData.refCount = 1;\n  newTexData.shape = size;\n  newTexData.dtype = x.dtype;\n  let flatOffset = slice_util_exports.computeFlatOffset(begin, util_exports.computeStrides(x.shape));\n  if (xTexData.slice) {\n    flatOffset += xTexData.slice.flatOffset;\n  }\n  newTexData.slice = {\n    flatOffset,\n    origDataId: xTexData.slice && xTexData.slice.origDataId || x.dataId\n  };\n  const refCount = backend2.dataRefCount.get(newTexData.slice.origDataId) || 1;\n  backend2.dataRefCount.set(newTexData.slice.origDataId, refCount + 1);\n  return t2;\n}\nfunction slice3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { begin, size } = attrs;\n  const [$begin, $size] = slice_util_exports.parseSliceParams(x, begin, size);\n  slice_util_exports.assertParamsValid(x, $begin, $size);\n  if (util_exports.sizeFromShape($size) === 0) {\n    return backend2.makeTensorInfo($size, x.dtype, []);\n  }\n  if (backend2.shouldExecuteOnCPU([x]) || x.dtype === \"string\") {\n    const xTexData = backend2.texData.get(x.dataId);\n    const outValues = sliceImplCPU(xTexData.values, $begin, $size, x.shape, x.dtype);\n    return backend2.makeTensorInfo($size, x.dtype, outValues);\n  }\n  const { isPacked } = backend2.texData.get(x.dataId);\n  const isContinous = slice_util_exports.isSliceContinous(x.shape, $begin, $size);\n  if (isPacked || !isContinous) {\n    const program = env().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\") ? new SlicePackedProgram($size) : new SliceProgram($size);\n    const customValues = [$begin];\n    return backend2.runWebGLProgram(program, [x], x.dtype, customValues);\n  }\n  backend2.uploadToGPU(x.dataId);\n  return shallowSlice(x, $begin, $size, backend2);\n}\nvar sliceConfig2 = {\n  kernelName: Slice,\n  backendName: \"webgl\",\n  kernelFunc: slice3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/BatchToSpaceND.js\nvar batchToSpaceND3 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, crops } = attrs;\n  util_exports.assert(x.shape.length <= 4, () => \"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet\");\n  const prod6 = blockShape.reduce((a, b) => a * b);\n  const reshaped = backend_util_exports.getReshaped(x.shape, blockShape, prod6);\n  const permuted = backend_util_exports.getPermuted(reshaped.length, blockShape.length);\n  const reshapedPermuted = backend_util_exports.getReshapedPermuted(x.shape, blockShape, prod6);\n  const sliceBeginCoords = backend_util_exports.getSliceBeginCoords(crops, blockShape.length);\n  const sliceSize = backend_util_exports.getSliceSize(reshapedPermuted, crops, blockShape.length);\n  const toDispose = [];\n  const reshapedIntermediate = reshape4({ inputs: { x }, backend: backend2, attrs: { shape: reshaped } });\n  const transposedIntermediate = transpose3({ inputs: { x: reshapedIntermediate }, backend: backend2, attrs: { perm: permuted } });\n  const reshapedIntermediate2 = reshape4({\n    inputs: { x: transposedIntermediate },\n    backend: backend2,\n    attrs: { shape: reshapedPermuted }\n  });\n  const sliced = slice3({\n    inputs: { x: reshapedIntermediate2 },\n    backend: backend2,\n    attrs: { begin: sliceBeginCoords, size: sliceSize }\n  });\n  toDispose.push(reshapedIntermediate);\n  toDispose.push(transposedIntermediate);\n  toDispose.push(reshapedIntermediate2);\n  toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return sliced;\n};\nvar batchToSpaceNDConfig2 = {\n  kernelName: BatchToSpaceND,\n  backendName: \"webgl\",\n  kernelFunc: batchToSpaceND3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Bincount.js\nfunction bincount3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, weights } = inputs;\n  const { size } = attrs;\n  const xVals = backend2.readSync(x.dataId);\n  const weightsVals = backend2.readSync(weights.dataId);\n  const outVals = bincountImplCPU(xVals, weightsVals, weights.dtype, weights.shape, size);\n  return backend2.makeTensorInfo([size], weights.dtype, outVals);\n}\nvar bincountConfig2 = {\n  kernelName: Bincount,\n  backendName: \"webgl\",\n  kernelFunc: bincount3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/BroadcastArgs.js\nfunction broadcastArgs3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { s0, s1 } = inputs;\n  const s0Vals = backend2.readSync(s0.dataId);\n  const s1Vals = backend2.readSync(s1.dataId);\n  const broadcastShape = backend_util_exports.assertAndGetBroadcastShape(Array.from(s0Vals), Array.from(s1Vals));\n  return backend2.makeTensorInfo([broadcastShape.length], \"int32\", Int32Array.from(broadcastShape));\n}\nvar broadcastArgsConfig2 = {\n  kernelName: BroadcastArgs,\n  backendName: \"webgl\",\n  kernelFunc: broadcastArgs3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/NotEqual.js\nvar NOT_EQUAL = `return float(a != b);`;\nvar notEqual3 = binaryKernelFunc2({ opSnippet: NOT_EQUAL, cpuKernelImpl: notEqualImplCPU, dtype: \"bool\" });\nvar notEqualConfig2 = {\n  kernelName: NotEqual,\n  backendName: \"webgl\",\n  kernelFunc: notEqual3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Real.js\nfunction real3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const inputData = backend2.texData.get(input2.dataId);\n  return identity3({ inputs: { x: inputData.complexTensorInfos.real }, backend: backend2 });\n}\nvar realConfig2 = {\n  kernelName: Real,\n  backendName: \"webgl\",\n  kernelFunc: real3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernel_utils/int.js\nvar TO_INT = `return float(int(x));`;\nfunction int(input2, backend2) {\n  const program = new UnaryOpProgram(input2.shape, TO_INT);\n  const output = backend2.runWebGLProgram(program, [input2], \"int32\");\n  return { dataId: output.dataId, shape: output.shape, dtype: output.dtype };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Cast.js\nfunction cast4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { dtype } = attrs;\n  if (dtype === \"complex64\") {\n    if (x.dtype === \"complex64\") {\n      return identity3({ inputs: { x }, backend: backend2 });\n    }\n    const zerosTensor = zeros(x.shape);\n    const floatX = cast4({ inputs: { x }, backend: backend2, attrs: { dtype: \"float32\" } });\n    const result = complex3({ inputs: { real: floatX, imag: zerosTensor }, backend: backend2 });\n    zerosTensor.dispose();\n    backend2.disposeIntermediateTensorInfo(floatX);\n    return result;\n  }\n  if (x.dtype === \"complex64\") {\n    const realPart = real3({ inputs: { input: x }, backend: backend2 });\n    const result = cast4({ inputs: { x: realPart }, backend: backend2, attrs: { dtype } });\n    backend2.disposeIntermediateTensorInfo(realPart);\n    return result;\n  }\n  if (!util_exports.hasEncodingLoss(x.dtype, dtype)) {\n    const result = identity3({ inputs: { x }, backend: backend2 });\n    return { dataId: result.dataId, shape: result.shape, dtype };\n  }\n  if (dtype === \"int32\") {\n    return int(x, backend2);\n  }\n  if (dtype === \"bool\") {\n    const zerosTensorInfo = backend2.makeTensorInfo([], \"bool\", util_exports.getTypedArrayFromDType(\"bool\", 1));\n    const binaryInputs = { a: x, b: zerosTensorInfo };\n    const result = notEqual3({ inputs: binaryInputs, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(zerosTensorInfo);\n    return result;\n  }\n  throw new Error(`Error in Cast: failed to cast ${x.dtype} to ${dtype}`);\n}\nvar castConfig2 = {\n  kernelName: Cast,\n  backendName: \"webgl\",\n  kernelFunc: cast4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Ceil.js\nvar CEIL = `return ceil(x);`;\nvar ceil3 = unaryKernelFunc2({ opSnippet: CEIL, packedOpSnippet: CEIL, cpuKernelImpl: ceilImplCPU });\nvar ceilConfig2 = {\n  kernelName: Ceil,\n  backendName: \"webgl\",\n  kernelFunc: ceil3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/clip_gpu.js\nvar ClipProgram = class {\n  constructor(aShape) {\n    this.variableNames = [\"A\"];\n    this.customUniforms = [\n      { name: \"minVal\", type: \"float\" },\n      { name: \"maxVal\", type: \"float\" }\n    ];\n    this.outputShape = aShape;\n    this.userCode = `\n\n      void main() {\n        float value = getAAtOutCoords();\n        if (isnan(value)) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, minVal, maxVal));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/clip_packed_gpu.js\nvar ClipPackedProgram = class {\n  constructor(aShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.customUniforms = [\n      { name: \"minVal\", type: \"float\" },\n      { name: \"maxVal\", type: \"float\" }\n    ];\n    this.outputShape = aShape;\n    this.userCode = `\n      void main() {\n        vec4 value = getAAtOutCoords();\n\n        if (any(isnan(value))) {\n          setOutput(value);\n          return;\n        }\n\n        setOutput(clamp(value, vec4(minVal), vec4(maxVal)));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ClipByValue.js\nfunction clipByValue3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { clipValueMin, clipValueMax } = attrs;\n  let program;\n  if (env().getBool(\"WEBGL_PACK_CLIP\")) {\n    program = new ClipPackedProgram(x.shape);\n  } else {\n    program = new ClipProgram(x.shape);\n  }\n  const customValues = [[clipValueMin], [clipValueMax]];\n  return backend2.runWebGLProgram(program, [x], x.dtype, customValues);\n}\nvar clipByValueConfig2 = {\n  kernelName: ClipByValue,\n  backendName: \"webgl\",\n  kernelFunc: clipByValue3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/complex_abs_gpu.js\nvar ComplexAbsProgram = class {\n  constructor(shape) {\n    this.variableNames = [\"real\", \"imag\"];\n    this.outputShape = shape;\n    this.userCode = `\n      void main() {\n        float re = abs(getRealAtOutCoords());\n        float im = abs(getImagAtOutCoords());\n        float mx = max(re, im);\n\n        // sadly the length function in glsl is not underflow-safe\n        // (at least not on Intel GPUs). So the safe solution is\n        // to ensure underflow-safety in all cases.\n        setOutput(\n          mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))\n        );\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ComplexAbs.js\nfunction makeComplexComponentTensorInfo(complexTensor, complexPart) {\n  return {\n    dataId: complexPart.dataId,\n    dtype: complexPart.dtype,\n    shape: complexTensor.shape\n  };\n}\nfunction complexAbs2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  const xData = backend2.texData.get(x.dataId);\n  const program = new ComplexAbsProgram(x.shape);\n  const programInputs = [\n    makeComplexComponentTensorInfo(x, xData.complexTensorInfos.real),\n    makeComplexComponentTensorInfo(x, xData.complexTensorInfos.imag)\n  ];\n  return backend2.runWebGLProgram(program, programInputs, programInputs[0].dtype);\n}\nvar complexAbsConfig2 = {\n  kernelName: ComplexAbs,\n  backendName: \"webgl\",\n  kernelFunc: complexAbs2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/concat_gpu.js\nvar ConcatProgram = class {\n  constructor(shapes) {\n    this.outputShape = [];\n    this.outputShape = backend_util_exports.computeOutShape(shapes, 1);\n    this.variableNames = shapes.map((_, i2) => `T${i2}`);\n    const offsets = new Array(shapes.length - 1);\n    offsets[0] = shapes[0][1];\n    for (let i2 = 1; i2 < offsets.length; i2++) {\n      offsets[i2] = offsets[i2 - 1] + shapes[i2][1];\n    }\n    const snippets = [`if (yC < ${offsets[0]}) setOutput(getT0(yR, yC));`];\n    for (let i2 = 1; i2 < offsets.length; i2++) {\n      const shift = offsets[i2 - 1];\n      snippets.push(`else if (yC < ${offsets[i2]}) setOutput(getT${i2}(yR, yC-${shift}));`);\n    }\n    const lastIndex = offsets.length;\n    const lastShift = offsets[offsets.length - 1];\n    snippets.push(`else setOutput(getT${lastIndex}(yR, yC-${lastShift}));`);\n    this.userCode = `\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int yR = coords.x;\n        int yC = coords.y;\n\n        ${snippets.join(\"\\n        \")}\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/concat_packed_gpu.js\nvar ConcatPackedProgram = class {\n  constructor(shapes, axis) {\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = [];\n    this.outputShape = backend_util_exports.computeOutShape(shapes, axis);\n    const shape = this.outputShape;\n    const rank = shape.length;\n    const dtype = getCoordsDataType(rank);\n    const coords3 = getChannels(\"coords\", rank);\n    const channels = [\"x\", \"y\", \"z\", \"w\", \"u\", \"v\"].slice(0, rank);\n    this.variableNames = shapes.map((_, i2) => `T${i2}`);\n    const offsets = new Array(shapes.length - 1);\n    offsets[0] = shapes[0][axis];\n    for (let i2 = 1; i2 < offsets.length; i2++) {\n      offsets[i2] = offsets[i2 - 1] + shapes[i2][axis];\n    }\n    const channel = channels[axis];\n    const lastChannels = channels.slice(-2);\n    const allChannels = channels.join();\n    let getValueSnippet = `if (${channel} < ${offsets[0]}) {\n        return getChannel(\n            getT0(${allChannels}), vec2(${lastChannels.join()}));\n        }`;\n    for (let i2 = 1; i2 < offsets.length; i2++) {\n      const shift2 = offsets[i2 - 1];\n      getValueSnippet += `\n        if (${channel} < ${offsets[i2]}  && ${channel} >= ${offsets[i2 - 1]}) {\n          return getChannel(\n            getT${i2}(${shiftedChannels(channels, channel, shift2)}),\n            vec2(${shiftedChannels(lastChannels, channel, shift2)}));\n        }`;\n    }\n    const lastIndex = offsets.length;\n    const shift = offsets[offsets.length - 1];\n    getValueSnippet += `\n        return getChannel(\n          getT${lastIndex}(${shiftedChannels(channels, channel, shift)}),\n          vec2(${shiftedChannels(lastChannels, channel, shift)}));`;\n    this.userCode = `\n      float getValue(${channels.map((x) => \"int \" + x)}) {\n        ${getValueSnippet}\n      }\n\n      void main() {\n        ${dtype} coords = getOutputCoords();\n        vec4 result = vec4(getValue(${coords3}), 0., 0., 0.);\n\n        ${coords3[rank - 1]} = ${coords3[rank - 1]} + 1;\n        if (${coords3[rank - 1]} < ${shape[rank - 1]}) {\n          result.g = getValue(${coords3});\n        }\n\n        ${coords3[rank - 2]} = ${coords3[rank - 2]} + 1;\n        if (${coords3[rank - 2]} < ${shape[rank - 2]}) {\n          result.a = getValue(${coords3});\n        }\n\n        ${coords3[rank - 1]} = ${coords3[rank - 1]} - 1;\n        if (${coords3[rank - 2]} < ${shape[rank - 2]} &&\n            ${coords3[rank - 1]} < ${shape[rank - 1]}) {\n          result.b = getValue(${coords3});\n        }\n        setOutput(result);\n      }\n    `;\n  }\n};\nfunction shiftedChannels(channels, channel, shift) {\n  const channelIdx = channels.indexOf(channel);\n  const res = channels.map((c, idx) => {\n    if (idx === channelIdx) {\n      return `${c} - ${shift}`;\n    } else {\n      return c;\n    }\n  });\n  return res.join();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Imag.js\nfunction imag3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const inputData = backend2.texData.get(input2.dataId);\n  return identity3({ inputs: { x: inputData.complexTensorInfos.imag }, backend: backend2 });\n}\nvar imagConfig2 = {\n  kernelName: Imag,\n  backendName: \"webgl\",\n  kernelFunc: imag3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Concat_impl.js\nfunction concatImpl2(inputs, axis, backend2) {\n  const dtype = inputs[0].dtype;\n  if (dtype === \"complex64\") {\n    const reals = inputs.map((t2) => real3({ inputs: { input: t2 }, backend: backend2 }));\n    const imags = inputs.map((t2) => imag3({ inputs: { input: t2 }, backend: backend2 }));\n    const realConcated = concatImpl2(reals, axis, backend2);\n    const imagConcated = concatImpl2(imags, axis, backend2);\n    const result2 = complex3({ inputs: { real: realConcated, imag: imagConcated }, backend: backend2 });\n    reals.forEach((r2) => backend2.disposeIntermediateTensorInfo(r2));\n    imags.forEach((i2) => backend2.disposeIntermediateTensorInfo(i2));\n    backend2.disposeIntermediateTensorInfo(realConcated);\n    backend2.disposeIntermediateTensorInfo(imagConcated);\n    return result2;\n  }\n  let runOnCpu = backend2.shouldExecuteOnCPU(inputs);\n  if (dtype === \"string\") {\n    runOnCpu = true;\n  }\n  if (runOnCpu) {\n    const tensors2D2 = inputs.map((t2) => {\n      const innerSize = util_exports.sizeFromShape(t2.shape.slice(axis));\n      const shape = [-1, innerSize];\n      return reshape4({ inputs: { x: t2 }, backend: backend2, attrs: { shape } });\n    });\n    const inputsValShapes = tensors2D2.map((t2) => {\n      return { vals: backend2.readSync(t2.dataId), shape: t2.shape };\n    });\n    const outShape2 = backend_util_exports.computeOutShape(tensors2D2.map((t2) => t2.shape), 1);\n    const simplyConcat = tensors2D2[0].shape[0] === 1;\n    const outVals = concatImplCPU(inputsValShapes, outShape2, dtype, simplyConcat);\n    const finalOutShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), axis);\n    const outInfo = backend2.makeTensorInfo(finalOutShape, dtype, outVals);\n    tensors2D2.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n    return outInfo;\n  }\n  const maxTexturesInShader = env().getNumber(\"WEBGL_MAX_TEXTURES_IN_SHADER\");\n  if (inputs.length > maxTexturesInShader) {\n    const reducedInputs = [];\n    for (let i2 = 0; i2 < inputs.length; i2 += maxTexturesInShader) {\n      const subArray = inputs.slice(i2, i2 + maxTexturesInShader);\n      reducedInputs.push(concatImpl2(subArray, axis, backend2));\n    }\n    const result2 = concatImpl2(reducedInputs, axis, backend2);\n    for (const i2 of reducedInputs) {\n      backend2.disposeIntermediateTensorInfo(i2);\n    }\n    return result2;\n  }\n  if (env().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\") && inputs[0].shape.length > 1) {\n    const program2 = new ConcatPackedProgram(inputs.map((t2) => t2.shape), axis);\n    return backend2.runWebGLProgram(program2, inputs, dtype);\n  }\n  const { tensors2D, outShape } = computeTensors2D(inputs, axis, backend2);\n  const program = new ConcatProgram(tensors2D.map((t2) => t2.shape));\n  const result = backend2.runWebGLProgram(program, tensors2D, dtype);\n  tensors2D.forEach((r2) => backend2.disposeIntermediateTensorInfo(r2));\n  const reshapedResult = reshape4({ inputs: { x: result }, attrs: { shape: outShape }, backend: backend2 });\n  backend2.disposeIntermediateTensorInfo(result);\n  return reshapedResult;\n}\nfunction computeTensors2D(inputs, axis, backend2) {\n  const outShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), axis);\n  const tensors2D = inputs.map((x) => reshape4({\n    inputs: { x },\n    attrs: { shape: [-1, util_exports.sizeFromShape(x.shape.slice(axis))] },\n    backend: backend2\n  }));\n  return { tensors2D, outShape };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Concat.js\nfunction concat3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { axis } = attrs;\n  const $axis = util_exports.parseAxisParam(axis, inputs[0].shape)[0];\n  const outShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), $axis);\n  if (util_exports.sizeFromShape(outShape) === 0) {\n    return backend2.makeTensorInfo(outShape, inputs[0].dtype, []);\n  }\n  const $inputs = inputs.filter((t2) => util_exports.sizeFromShape(t2.shape) > 0);\n  if ($inputs.length === 1) {\n    return identity3({ inputs: { x: $inputs[0] }, backend: backend2 });\n  }\n  const shapes = $inputs.map((t2) => t2.shape);\n  backend_util_exports.assertParamsConsistent(shapes, $axis);\n  return concatImpl2($inputs, $axis, backend2);\n}\nvar concatConfig2 = {\n  kernelName: Concat,\n  backendName: \"webgl\",\n  kernelFunc: concat3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_gpu.js\nvar Conv2DProgram = class {\n  constructor(convInfo, addBias = false, activation2 = null, hasPreluActivationWeights = false, hasLeakyreluAlpha = false) {\n    this.variableNames = [\"x\", \"W\"];\n    this.outputShape = convInfo.outShape;\n    const padTop = convInfo.padInfo.top;\n    const padLeft = convInfo.padInfo.left;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationHeight = convInfo.dilationHeight;\n    const dilationWidth = convInfo.dilationWidth;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const inputDepthNearestVec4 = Math.floor(convInfo.inChannels / 4) * 4;\n    const inputDepthVec4Remainder = convInfo.inChannels % 4;\n    const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n    const rowDim = isChannelsLast ? 1 : 2;\n    const colDim = isChannelsLast ? 2 : 3;\n    const channelDim = isChannelsLast ? 3 : 1;\n    let activationSnippet = \"\", applyActivationSnippet = \"\";\n    if (activation2) {\n      if (hasPreluActivationWeights) {\n        activationSnippet = `float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          ${activation2}\n        }`;\n      } else if (hasLeakyreluAlpha) {\n        activationSnippet = `float activation(float a) {\n          float b = getLeakyreluAlphaAtOutCoords();\n          ${activation2}\n        }`;\n      } else {\n        activationSnippet = `\n          float activation(float x) {\n            ${activation2}\n          }\n        `;\n      }\n      applyActivationSnippet = `result = activation(result);`;\n    }\n    const addBiasSnippet = addBias ? \"result += getBiasAtOutCoords();\" : \"\";\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivationWeights) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    if (hasLeakyreluAlpha) {\n      this.variableNames.push(\"leakyreluAlpha\");\n    }\n    this.userCode = `\n      ${activationSnippet}\n\n      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});\n      const ivec2 pads = ivec2(${padTop}, ${padLeft});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d2 = coords[${channelDim}];\n\n        ivec2 xRCCorner =\n            ivec2(coords[${rowDim}], coords[${colDim}]) * strides - pads;\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, d2) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ${filterHeight}; wR++) {\n          int xR = xRCorner + wR * ${dilationHeight};\n\n          if (xR < 0 || xR >= ${convInfo.inHeight}) {\n            continue;\n          }\n\n          for (int wC = 0; wC < ${filterWidth}; wC++) {\n            int xC = xCCorner + wC * ${dilationWidth};\n\n            if (xC < 0 || xC >= ${convInfo.inWidth}) {\n              continue;\n            }\n\n            for (int d1 = 0; d1 < ${inputDepthNearestVec4}; d1 += 4) {\n              vec4 wValues = vec4(\n                getW(wR, wC, d1, d2),\n                getW(wR, wC, d1 + 1, d2),\n                getW(wR, wC, d1 + 2, d2),\n                getW(wR, wC, d1 + 3, d2)\n              );\n\n              if (${isChannelsLast}) {\n                vec4 xValues = vec4(\n                  getX(batch, xR, xC, d1),\n                  getX(batch, xR, xC, d1 + 1),\n                  getX(batch, xR, xC, d1 + 2),\n                  getX(batch, xR, xC, d1 + 3)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec4 xValues = vec4(\n                  getX(batch, d1, xR, xC),\n                  getX(batch, d1 + 1, xR, xC),\n                  getX(batch, d1 + 2, xR, xC),\n                  getX(batch, d1 + 3, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n\n            if (${inputDepthVec4Remainder === 1}) {\n\n              if (${isChannelsLast}) {\n                dotProd +=\n                    getX(batch, xR, xC, ${inputDepthNearestVec4}) *\n                    getW(wR, wC, ${inputDepthNearestVec4}, d2);\n              } else {\n                dotProd +=\n                    getX(batch, ${inputDepthNearestVec4}, xR, xC) *\n                    getW(wR, wC, ${inputDepthNearestVec4}, d2);\n              }\n\n            } else if (${inputDepthVec4Remainder === 2}) {\n              vec2 wValues = vec2(\n                getW(wR, wC, ${inputDepthNearestVec4}, d2),\n                getW(wR, wC, ${inputDepthNearestVec4} + 1, d2)\n              );\n\n              if (${isChannelsLast}) {\n                vec2 xValues = vec2(\n                  getX(batch, xR, xC, ${inputDepthNearestVec4}),\n                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 1)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec2 xValues = vec2(\n                  getX(batch, ${inputDepthNearestVec4}, xR, xC),\n                  getX(batch, ${inputDepthNearestVec4} + 1, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            } else if (${inputDepthVec4Remainder === 3}) {\n              vec3 wValues = vec3(\n                getW(wR, wC, ${inputDepthNearestVec4}, d2),\n                getW(wR, wC, ${inputDepthNearestVec4} + 1, d2),\n                getW(wR, wC, ${inputDepthNearestVec4} + 2, d2)\n              );\n\n              if (${isChannelsLast}) {\n                vec3 xValues = vec3(\n                  getX(batch, xR, xC, ${inputDepthNearestVec4}),\n                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 1),\n                  getX(batch, xR, xC, ${inputDepthNearestVec4} + 2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else {\n                vec3 xValues = vec3(\n                  getX(batch, ${inputDepthNearestVec4}, xR, xC),\n                  getX(batch, ${inputDepthNearestVec4} + 1, xR, xC),\n                  getX(batch, ${inputDepthNearestVec4} + 2, xR, xC)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n\n            }\n          }\n        }\n\n        float result = dotProd;\n        ${addBiasSnippet}\n        ${applyActivationSnippet}\n        setOutput(result);\n      }\n    `;\n  }\n};\nvar Conv3DProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"x\", \"W\"];\n    this.outputShape = convInfo.outShape;\n    const padFront = convInfo.padInfo.front;\n    const padTop = convInfo.padInfo.top;\n    const padLeft = convInfo.padInfo.left;\n    const strideDepth = convInfo.strideDepth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationDepth = convInfo.dilationDepth;\n    const dilationHeight = convInfo.dilationHeight;\n    const dilationWidth = convInfo.dilationWidth;\n    const filterDepth = convInfo.filterDepth;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const inputDepthNearestVec4 = Math.floor(convInfo.inChannels / 4) * 4;\n    const inputDepthVec4Remainder = convInfo.inChannels % 4;\n    this.userCode = `\n      const ivec3 strides = ivec3(${strideDepth}, ${strideHeight}, ${strideWidth});\n      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d2 = coords.u;\n\n        ivec3 xFRCCorner = ivec3(coords.y, coords.z, coords.w) * strides - pads;\n        int xFCorner = xFRCCorner.x;\n        int xRCorner = xFRCCorner.y;\n        int xCCorner = xFRCCorner.z;\n\n        // Convolve x(?, ?, ?, d1) with w(:, :, :, d1, d2) to get\n        // y(yF, yR, yC, d2). ? = to be determined. : = across all\n        // values in that axis.\n        float dotProd = 0.0;\n        for (int wF = 0; wF < ${filterDepth}; wF++) {\n          int xF = xFCorner + wF * ${dilationDepth};\n\n          if (xF < 0 || xF >= ${convInfo.inDepth}) {\n            continue;\n          }\n\n          for (int wR = 0; wR < ${filterHeight}; wR++) {\n            int xR = xRCorner + wR * ${dilationHeight};\n\n            if (xR < 0 || xR >= ${convInfo.inHeight}) {\n              continue;\n            }\n\n            for (int wC = 0; wC < ${filterWidth}; wC++) {\n              int xC = xCCorner + wC * ${dilationWidth};\n\n              if (xC < 0 || xC >= ${convInfo.inWidth}) {\n                continue;\n              }\n\n              for (int d1 = 0; d1 < ${inputDepthNearestVec4}; d1 += 4) {\n                vec4 xValues = vec4(\n                  getX(batch, xF, xR, xC, d1),\n                  getX(batch, xF, xR, xC, d1 + 1),\n                  getX(batch, xF, xR, xC, d1 + 2),\n                  getX(batch, xF, xR, xC, d1 + 3)\n                );\n                vec4 wValues = vec4(\n                  getW(wF, wR, wC, d1, d2),\n                  getW(wF, wR, wC, d1 + 1, d2),\n                  getW(wF, wR, wC, d1 + 2, d2),\n                  getW(wF, wR, wC, d1 + 3, d2)\n                );\n\n                dotProd += dot(xValues, wValues);\n              }\n\n              if (${inputDepthVec4Remainder === 1}) {\n                dotProd +=\n                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}) *\n                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2);\n              } else if (${inputDepthVec4Remainder === 2}) {\n                vec2 xValues = vec2(\n                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}),\n                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 1)\n                );\n                vec2 wValues = vec2(\n                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2),\n                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 1, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              } else if (${inputDepthVec4Remainder === 3}) {\n                vec3 xValues = vec3(\n                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4}),\n                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 1),\n                  getX(batch, xF, xR, xC, ${inputDepthNearestVec4} + 2)\n                );\n                vec3 wValues = vec3(\n                  getW(wF, wR, wC, ${inputDepthNearestVec4}, d2),\n                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 1, d2),\n                  getW(wF, wR, wC, ${inputDepthNearestVec4} + 2, d2)\n                );\n                dotProd += dot(xValues, wValues);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/im2col_packed_gpu.js\nvar Im2ColPackedProgram = class {\n  constructor(outputShape, convInfo) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.customUniforms = [\n      { name: \"inputShape\", type: \"ivec4\" },\n      { name: \"pad\", type: \"ivec2\" },\n      { name: \"stride\", type: \"ivec2\" },\n      { name: \"dilation\", type: \"ivec2\" },\n      { name: \"inChannels\", type: \"int\" },\n      { name: \"itemsPerBlockRow\", type: \"int\" },\n      { name: \"outWidth\", type: \"int\" }\n    ];\n    this.outputShape = outputShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    const { dataFormat } = convInfo;\n    const glsl = getGlslDifferences();\n    const isChannelsLast = dataFormat === \"channelsLast\";\n    const rowDim = isChannelsLast ? 1 : 2;\n    const colDim = isChannelsLast ? 2 : 3;\n    const boundsCheckingSnippet = this.enableShapeUniforms ? \"if(blockIndex < outShape[2] && pos < outShape[1]) {\" : `if(blockIndex < ${outputShape[2]} && pos < ${outputShape[1]}) {`;\n    let unrolled = ``;\n    for (let row = 0; row <= 1; row++) {\n      for (let col = 0; col <= 1; col++) {\n        unrolled += `\n          blockIndex = rc.z + ${col};\n          pos = rc.y + ${row};\n\n          ${boundsCheckingSnippet}\n            offsetY = int(blockIndex / outWidth) * stride[0] - pad[0];\n            d0 = offsetY + dilation[0] * (pos / itemsPerBlockRow);\n\n            if(d0 < inputShape[${rowDim}] && d0 >= 0) {\n              // Use custom imod instead mod. On Intel GPU, mod may generate\n              // unexpected value.\n              // https://github.com/tensorflow/tfjs/issues/5447\n              offsetX = imod(blockIndex, outWidth) * stride[1] - pad[1];\n              d1 = offsetX + dilation[1] * (imod(pos, itemsPerBlockRow) /\n                  inChannels);\n\n              if(d1 < inputShape[${colDim}] && d1 >= 0) {\n\n                ch = imod(pos, inChannels);\n\n                if (${isChannelsLast}) {\n                  innerDims = vec2(d1, ch);\n                  result[${row * 2 + col}] = getChannel(\n                    getA(rc.x, d0, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                } else {\n                  innerDims = vec2(d0, d1);\n                  result[${row * 2 + col}] = getChannel(\n                    getA(rc.x, ch, int(innerDims.x),\n                    int(innerDims.y)), innerDims);\n                }\n              }\n            }\n          }\n        `;\n      }\n    }\n    this.userCode = `\n      void main() {\n        ivec3 rc = getOutputCoords();\n\n        vec4 result = vec4(0);\n\n        int blockIndex, pos, offsetY, d0, offsetX, d1, ch;\n        vec2 innerDims;\n\n        ${unrolled}\n\n        ${glsl.output} = result;\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Conv2D_impl.js\nfunction getShapeForBatchMatMul(shape, isChannelsLast) {\n  const length = shape.length;\n  if (length >= 3) {\n    return isChannelsLast ? [\n      ...shape.slice(0, -3),\n      shape[length - 3] * shape[length - 2],\n      shape[length - 1]\n    ] : [\n      ...shape.slice(0, -3),\n      shape[length - 3],\n      shape[length - 2] * shape[length - 1]\n    ];\n  } else if (!isChannelsLast && length === 1 && shape[0] > 1) {\n    return [shape[0], 1];\n  } else {\n    return null;\n  }\n}\nfunction conv2dByMatMul({ x, filter, convInfo, backend: backend2, bias = null, preluActivationWeights = null, leakyreluAlpha = 0, activation: activation2 = null }) {\n  const xShape = x.shape;\n  const xTexData = backend2.texData.get(x.dataId);\n  const sharedMatMulDim = convInfo.inChannels;\n  const outerShapeX = xShape[0] * xShape[1] * xShape[2];\n  const outerShapeFilter = convInfo.outChannels;\n  const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n  const transposeA = false;\n  const transposeB = false;\n  let out;\n  const intermediates = [];\n  if (preluActivationWeights != null) {\n    const targetShape = getShapeForBatchMatMul(preluActivationWeights.shape, isChannelsLast);\n    if (targetShape != null) {\n      preluActivationWeights = reshape4({\n        inputs: { x: preluActivationWeights },\n        backend: backend2,\n        attrs: { shape: targetShape }\n      });\n      intermediates.push(preluActivationWeights);\n    }\n  }\n  if (bias != null) {\n    const targetShape = getShapeForBatchMatMul(bias.shape, isChannelsLast);\n    if (targetShape != null) {\n      bias = reshape4({ inputs: { x: bias }, backend: backend2, attrs: { shape: targetShape } });\n      intermediates.push(bias);\n    }\n  }\n  const batchMatMulWillBeUnpacked = (outerShapeX === 1 || outerShapeFilter === 1) && sharedMatMulDim > MATMUL_SHARED_DIM_THRESHOLD;\n  const canOptimize = !batchMatMulWillBeUnpacked && xTexData.isPacked && isChannelsLast && xTexData.texture != null && xShape[2] % 2 !== 0 && util_exports.arraysEqual(xTexData.shape.slice(-3), xShape.slice(-3));\n  if (canOptimize) {\n    const targetShape = xShape[0] * xShape[1] * (xShape[2] + 1);\n    const xReshaped = {\n      dataId: x.dataId,\n      shape: [1, targetShape, convInfo.inChannels],\n      dtype: x.dtype\n    };\n    const originalXTexDataShape = xTexData.shape;\n    xTexData.shape = xTexData.shape.slice();\n    xTexData.shape[xTexData.shape.length - 2]++;\n    util_exports.assert(isReshapeFree(xTexData.shape, xReshaped.shape), () => `packed reshape ${xTexData.shape} to ${xReshaped.shape} isn't free`);\n    const filterReshaped = reshape4({\n      inputs: { x: filter },\n      backend: backend2,\n      attrs: { shape: [1, convInfo.inChannels, convInfo.outChannels] }\n    });\n    intermediates.push(filterReshaped);\n    const pointwiseConv = batchMatMulImpl({\n      a: xReshaped,\n      b: filterReshaped,\n      backend: backend2,\n      transposeA,\n      transposeB,\n      bias,\n      activation: activation2,\n      preluActivationWeights,\n      leakyreluAlpha\n    });\n    const pointwiseConvTexData = backend2.texData.get(pointwiseConv.dataId);\n    util_exports.assert(pointwiseConvTexData.isPacked, () => \"batchMatMul result is expected to be packed\");\n    xTexData.shape = originalXTexDataShape;\n    pointwiseConvTexData.shape = convInfo.outShape;\n    out = identity3({ inputs: { x: pointwiseConv }, backend: backend2 });\n    out.shape = convInfo.outShape;\n    intermediates.push(pointwiseConv);\n  } else {\n    const numCols = convInfo.outHeight * convInfo.outWidth;\n    const xReshaped = reshape4({\n      inputs: { x },\n      backend: backend2,\n      attrs: {\n        shape: isChannelsLast ? [convInfo.batchSize, numCols, convInfo.inChannels] : [convInfo.batchSize, convInfo.inChannels, numCols]\n      }\n    });\n    const filterReshaped = reshape4({\n      inputs: { x: filter },\n      backend: backend2,\n      attrs: { shape: [1, convInfo.inChannels, convInfo.outChannels] }\n    });\n    const result = batchMatMulImpl({\n      a: isChannelsLast ? xReshaped : filterReshaped,\n      b: isChannelsLast ? filterReshaped : xReshaped,\n      transposeA: !isChannelsLast,\n      transposeB,\n      backend: backend2,\n      bias,\n      activation: activation2,\n      preluActivationWeights,\n      leakyreluAlpha\n    });\n    out = reshape4({ inputs: { x: result }, backend: backend2, attrs: { shape: convInfo.outShape } });\n    intermediates.push(xReshaped);\n    intermediates.push(filterReshaped);\n    intermediates.push(result);\n  }\n  for (const i2 of intermediates) {\n    backend2.disposeIntermediateTensorInfo(i2);\n  }\n  return out;\n}\nfunction conv2dWithIm2Row({ x, filter, convInfo, backend: backend2, bias = null, preluActivationWeights = null, leakyreluAlpha = 0, activation: activation2 = null }) {\n  const { filterWidth, filterHeight, inChannels, outWidth, outHeight, dataFormat } = convInfo;\n  const isChannelsLast = dataFormat === \"channelsLast\";\n  const sharedDim = filterWidth * filterHeight * inChannels;\n  const numCols = outHeight * outWidth;\n  const x2ColShape = [convInfo.batchSize, sharedDim, numCols];\n  const transposeA = true;\n  const transposeB = false;\n  const intermediates = [];\n  if (preluActivationWeights != null) {\n    const targetShape = getShapeForBatchMatMul(preluActivationWeights.shape, isChannelsLast);\n    if (targetShape != null) {\n      preluActivationWeights = reshape4({\n        inputs: { x: preluActivationWeights },\n        backend: backend2,\n        attrs: { shape: targetShape }\n      });\n      intermediates.push(preluActivationWeights);\n    }\n  }\n  if (bias != null) {\n    const targetShape = getShapeForBatchMatMul(bias.shape, isChannelsLast);\n    if (targetShape != null) {\n      bias = reshape4({ inputs: { x: bias }, backend: backend2, attrs: { shape: targetShape } });\n      intermediates.push(bias);\n    }\n  }\n  const w2Row = reshape4({\n    inputs: { x: filter },\n    backend: backend2,\n    attrs: { shape: [1, sharedDim, util_exports.sizeFromShape(filter.shape) / sharedDim] }\n  });\n  intermediates.push(w2Row);\n  const im2ColProgram = new Im2ColPackedProgram(x2ColShape, convInfo);\n  const customValues = [\n    x.shape,\n    [convInfo.padInfo.top, convInfo.padInfo.left],\n    [convInfo.strideHeight, convInfo.strideWidth],\n    [convInfo.dilationHeight, convInfo.dilationWidth],\n    [convInfo.inChannels],\n    [convInfo.filterWidth * convInfo.inChannels],\n    [convInfo.outWidth]\n  ];\n  const im2Col = backend2.runWebGLProgram(im2ColProgram, [x], \"float32\", customValues);\n  const im2ColReshaped = reshape4({ inputs: { x: im2Col }, backend: backend2, attrs: { shape: x2ColShape } });\n  intermediates.push(im2Col);\n  intermediates.push(im2ColReshaped);\n  const hasBias = bias != null;\n  const hasPreluActivationWeights = preluActivationWeights != null;\n  const hasLeakyreluAlpha = activation2 === \"leakyrelu\";\n  const fusedActivation = activation2 ? mapActivationToShaderProgram(activation2, true) : null;\n  const matmulProgram = new MatMulPackedProgram(isChannelsLast ? im2ColReshaped.shape : w2Row.shape, isChannelsLast ? w2Row.shape : im2ColReshaped.shape, isChannelsLast ? [convInfo.batchSize, numCols, convInfo.outChannels] : [convInfo.batchSize, convInfo.outChannels, numCols], transposeA, transposeB, hasBias, fusedActivation, hasPreluActivationWeights, hasLeakyreluAlpha);\n  const inputs = isChannelsLast ? [im2ColReshaped, w2Row] : [w2Row, im2ColReshaped];\n  if (bias) {\n    inputs.push(bias);\n  }\n  if (hasPreluActivationWeights) {\n    inputs.push(preluActivationWeights);\n  }\n  if (hasLeakyreluAlpha) {\n    const $leakyreluAlpha = backend2.makeTensorInfo([], \"float32\", util_exports.createScalarValue(leakyreluAlpha, \"float32\"));\n    inputs.push($leakyreluAlpha);\n    intermediates.push($leakyreluAlpha);\n  }\n  const product = backend2.runWebGLProgram(matmulProgram, inputs, \"float32\");\n  const out = reshape4({ inputs: { x: product }, backend: backend2, attrs: { shape: convInfo.outShape } });\n  intermediates.push(product);\n  for (const i2 of intermediates) {\n    backend2.disposeIntermediateTensorInfo(i2);\n  }\n  return out;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Conv2D.js\nfunction conv2d4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode, false, $dataFormat);\n  let out;\n  if (convInfo.filterHeight === 1 && convInfo.filterWidth === 1 && convInfo.dilationHeight === 1 && convInfo.dilationWidth === 1 && convInfo.strideHeight === 1 && convInfo.strideWidth === 1 && (convInfo.padInfo.type === \"SAME\" || convInfo.padInfo.type === \"VALID\")) {\n    out = conv2dByMatMul({ x, filter, convInfo, backend: backend2 });\n  } else if (env().getBool(\"WEBGL_CONV_IM2COL\")) {\n    out = conv2dWithIm2Row({ x, filter, convInfo, backend: backend2 });\n  } else {\n    const program = new Conv2DProgram(convInfo);\n    out = backend2.runWebGLProgram(program, [x, filter], \"float32\");\n  }\n  const outReshaped = reshape4({ inputs: { x: out }, backend: backend2, attrs: { shape: convInfo.outShape } });\n  backend2.disposeIntermediateTensorInfo(out);\n  return outReshaped;\n}\nvar conv2DConfig2 = {\n  kernelName: Conv2D,\n  backendName: \"webgl\",\n  kernelFunc: conv2d4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_backprop_gpu.js\nvar Conv2DDerFilterProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"x\", \"dy\"];\n    this.outputShape = convInfo.filterShape;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const padTop = convInfo.padInfo.top;\n    const padLeft = convInfo.padInfo.left;\n    const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n    this.userCode = `\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int d2 = coords.w;\n\n        // Convolve x(?, ?, d1) with dy(:, :, d2) to get dw(wR, wC, d1, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int b = 0; b < ${convInfo.batchSize}; b++) {\n          for (int yR = 0; yR < ${convInfo.outHeight}; yR++) {\n            int xR = wR + yR * ${strideHeight} - ${padTop};\n\n            if (xR < 0 || xR >= ${convInfo.inHeight}) {\n              continue;\n            }\n\n            for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {\n              int xC = wC + yC * ${strideWidth} - ${padLeft};\n\n              if (xC < 0 || xC >= ${convInfo.inWidth}) {\n                continue;\n              }\n\n              if (${isChannelsLast}) {\n                float dyValue = getDy(b, yR, yC, d2);\n                float xValue = getX(b, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              } else {\n                float dyValue = getDy(b, d2, yR, yC);\n                float xValue = getX(b, d1, xR, xC);\n                dotProd += (xValue * dyValue);\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\nvar Conv2DDerInputProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\", \"W\"];\n    this.outputShape = convInfo.inShape;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n    const padTop = filterHeight - 1 - convInfo.padInfo.top;\n    const padLeft = filterWidth - 1 - convInfo.padInfo.left;\n    const rowDim = isChannelsLast ? 1 : 2;\n    const colDim = isChannelsLast ? 2 : 3;\n    const channelDim = isChannelsLast ? 3 : 1;\n    this.userCode = `\n      const ivec2 pads = ivec2(${padTop}, ${padLeft});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[${channelDim}];\n\n        ivec2 dyCorner = ivec2(coords[${rowDim}], coords[${colDim}]) - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ${filterHeight}; wR++) {\n          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;\n\n          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = ${filterHeight} - 1 - wR;\n\n          for (int wC = 0; wC < ${filterWidth}; wC++) {\n            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;\n\n            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = ${filterWidth} - 1 - wC;\n\n            for (int d2 = 0; d2 < ${convInfo.outChannels}; d2++) {\n\n              if (${isChannelsLast}) {\n                float xValue = getDy(batch, idyR, idyC, d2);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              } else {\n                float xValue = getDy(batch, d2, idyR, idyC);\n                float wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\nvar Conv3DDerFilterProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"x\", \"dy\"];\n    this.outputShape = convInfo.filterShape;\n    const strideDepth = convInfo.strideDepth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const padFront = convInfo.padInfo.front;\n    const padTop = convInfo.padInfo.top;\n    const padLeft = convInfo.padInfo.left;\n    this.userCode = `\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int wF = coords.x;\n        int wR = coords.y;\n        int wC = coords.z;\n        int d1 = coords.w;\n        int d2 = coords.u;\n\n        float dotProd = 0.0;\n\n        for (int b = 0; b < ${convInfo.batchSize}; b++) {\n          for (int yF = 0; yF < ${convInfo.outDepth}; yF++) {\n            int xF = wF + yF * ${strideDepth} - ${padFront};\n\n            if (xF < 0 || xF >= ${convInfo.inDepth}) {\n              continue;\n            }\n\n            for (int yR = 0; yR < ${convInfo.outHeight}; yR++) {\n              int xR = wR + yR * ${strideHeight} - ${padTop};\n\n              if (xR < 0 || xR >= ${convInfo.inHeight}) {\n                continue;\n              }\n\n              for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {\n                int xC = wC + yC * ${strideWidth} - ${padLeft};\n\n                if (xC < 0 || xC >= ${convInfo.inWidth}) {\n                  continue;\n                }\n\n                float dyValue = getDy(b, yF, yR, yC, d2);\n                float xValue = getX(b, xF, xR, xC, d1);\n                dotProd += (xValue * dyValue);\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\nvar Conv3DDerInputProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\", \"W\"];\n    this.outputShape = convInfo.inShape;\n    const filterDepth = convInfo.filterDepth;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const strideDepth = convInfo.strideDepth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const padFront = filterDepth - 1 - convInfo.padInfo.front;\n    const padTop = filterHeight - 1 - convInfo.padInfo.top;\n    const padLeft = filterWidth - 1 - convInfo.padInfo.left;\n    this.userCode = `\n      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int d1 = coords.u;\n\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyFCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        float dotProd = 0.0;\n        for (int wF = 0; wF < ${filterDepth}; wF++) {\n          float dyF = float(dyFCorner + wF) / ${strideDepth}.0;\n\n          if (dyF < 0.0 || dyF >= ${convInfo.outDepth}.0 || fract(dyF) > 0.0) {\n            continue;\n          }\n          int idyF = int(dyF);\n\n          int wFPerm = ${filterDepth} - 1 - wF;\n\n          for (int wR = 0; wR < ${filterHeight}; wR++) {\n            float dyR = float(dyRCorner + wR) / ${strideHeight}.0;\n\n            if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 ||\n              fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            int wRPerm = ${filterHeight} - 1 - wR;\n\n            for (int wC = 0; wC < ${filterWidth}; wC++) {\n              float dyC = float(dyCCorner + wC) / ${strideWidth}.0;\n\n              if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              int wCPerm = ${filterWidth} - 1 - wC;\n\n              for (int d2 = 0; d2 < ${convInfo.outChannels}; d2++) {\n                float xValue = getDy(batch, idyF, idyR, idyC, d2);\n                float wValue = getW(wFPerm, wRPerm, wCPerm, d1, d2);\n                dotProd += xValue * wValue;\n              }\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Conv2DBackpropFilter.js\nfunction conv2DBackpropFilter3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, dy } = inputs;\n  const { strides, pad: pad3, dataFormat, dimRoundingMode, filterShape } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filterShape, strides, 1, pad3, dimRoundingMode, false, $dataFormat);\n  const program = new Conv2DDerFilterProgram(convInfo);\n  return backend2.runWebGLProgram(program, [x, dy], \"float32\");\n}\nvar conv2DBackpropFilterConfig2 = {\n  kernelName: Conv2DBackpropFilter,\n  backendName: \"webgl\",\n  kernelFunc: conv2DBackpropFilter3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Conv2DBackpropInput.js\nfunction conv2DBackpropInput3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, filter } = inputs;\n  const { inputShape, strides, pad: pad3, dataFormat, dimRoundingMode } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(inputShape, filter.shape, strides, 1, pad3, dimRoundingMode, false, $dataFormat);\n  const program = new Conv2DDerInputProgram(convInfo);\n  return backend2.runWebGLProgram(program, [dy, filter], \"float32\");\n}\nvar conv2DBackpropInputConfig2 = {\n  kernelName: Conv2DBackpropInput,\n  backendName: \"webgl\",\n  kernelFunc: conv2DBackpropInput3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Conv3D.js\nfunction conv3D2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dilations } = attrs;\n  const convInfo = backend_util_exports.computeConv3DInfo(x.shape, filter.shape, strides, dilations, pad3);\n  const program = new Conv3DProgram(convInfo);\n  return backend2.runWebGLProgram(program, [x, filter], \"float32\");\n}\nvar conv3DConfig2 = {\n  kernelName: Conv3D,\n  backendName: \"webgl\",\n  kernelFunc: conv3D2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Conv3DBackpropFilterV2.js\nfunction conv3DBackpropFilterV22(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, dy } = inputs;\n  const { strides, pad: pad3, filterShape } = attrs;\n  const convInfo = backend_util_exports.computeConv3DInfo(x.shape, filterShape, strides, 1, pad3);\n  const program = new Conv3DDerFilterProgram(convInfo);\n  return backend2.runWebGLProgram(program, [x, dy], \"float32\");\n}\nvar conv3DBackpropFilterV2Config2 = {\n  kernelName: Conv3DBackpropFilterV2,\n  backendName: \"webgl\",\n  kernelFunc: conv3DBackpropFilterV22\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Conv3DBackpropInputV2.js\nfunction conv3DBackpropInput2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, filter } = inputs;\n  const { pad: pad3, strides, inputShape } = attrs;\n  const convInfo = backend_util_exports.computeConv3DInfo(inputShape, filter.shape, strides, 1, pad3);\n  const program = new Conv3DDerInputProgram(convInfo);\n  return backend2.runWebGLProgram(program, [dy, filter], \"float32\");\n}\nvar conv3DBackpropInputConfig = {\n  kernelName: Conv3DBackpropInputV2,\n  backendName: \"webgl\",\n  kernelFunc: conv3DBackpropInput2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Cos.js\nvar COS = CHECK_NAN_SNIPPET_UNARY + `\n  return cos(x);\n`;\nvar cos3 = unaryKernelFunc2({ opSnippet: COS });\nvar cosConfig2 = {\n  kernelName: Cos,\n  backendName: \"webgl\",\n  kernelFunc: cos3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Cosh.js\nvar COSH = `\n  float e2x = exp(-x);\n  return (e2x + 1.0 / e2x) / 2.0;\n`;\nvar cosh3 = unaryKernelFunc2({ opSnippet: COSH });\nvar coshConfig2 = {\n  kernelName: Cosh,\n  backendName: \"webgl\",\n  kernelFunc: cosh3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/crop_and_resize_gpu.js\nvar CropAndResizeProgram = class {\n  constructor(imageShape, boxShape, cropSize, method, extrapolationValue) {\n    this.variableNames = [\"Image\", \"Boxes\", \"BoxInd\"];\n    this.outputShape = [];\n    const [batch, imageHeight, imageWidth, depth] = imageShape;\n    const [numBoxes] = boxShape;\n    const [cropHeight, cropWidth] = cropSize;\n    this.outputShape = [numBoxes, cropHeight, cropWidth, depth];\n    const methodId = method === \"bilinear\" ? 1 : 0;\n    const [inputHeightFloat, inputWidthFloat] = [`${imageHeight - 1}.0`, `${imageWidth - 1}.0`];\n    const [heightRatio, heightScale, inY] = cropHeight > 1 ? [\n      `${(imageHeight - 1) / (cropHeight - 1)}`,\n      \"(y2-y1) * height_ratio\",\n      `y1*${inputHeightFloat} + float(y)*(height_scale)`\n    ] : [\n      \"0.0\",\n      \"0.0\",\n      `0.5 * (y1+y2) * ${inputHeightFloat}`\n    ];\n    const [widthRatio, widthScale, inX] = cropWidth > 1 ? [\n      `${(imageWidth - 1) / (cropWidth - 1)}`,\n      \"(x2-x1) * width_ratio\",\n      `x1*${inputWidthFloat} + float(x)*(width_scale)`\n    ] : [\n      \"0.0\",\n      \"0.0\",\n      `0.5 * (x1+x2) * ${inputWidthFloat}`\n    ];\n    this.userCode = `\n      const float height_ratio = float(${heightRatio});\n      const float width_ratio = float(${widthRatio});\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int y = coords[1];\n        int x = coords[2];\n        int d = coords[3];\n\n        // get box vals\n        float y1 = getBoxes(b,0);\n        float x1 = getBoxes(b,1);\n        float y2 = getBoxes(b,2);\n        float x2 = getBoxes(b,3);\n\n        // get image in batch index\n        int bInd = round(getBoxInd(b));\n        if(bInd < 0 || bInd >= ${batch}) {\n          return;\n        }\n\n        float height_scale = ${heightScale};\n        float width_scale = ${widthScale};\n\n        float in_y = ${inY};\n        if( in_y < 0.0 || in_y > ${inputHeightFloat} ) {\n          setOutput(float(${extrapolationValue}));\n          return;\n        }\n        float in_x = ${inX};\n        if( in_x < 0.0 || in_x > ${inputWidthFloat} ) {\n          setOutput(float(${extrapolationValue}));\n          return;\n        }\n\n        vec2 sourceFracIndexCR = vec2(in_x,in_y);\n        if(${methodId} == 1) {\n          // Compute the four integer indices.\n          ivec2 sourceFloorCR = ivec2(sourceFracIndexCR);\n          ivec2 sourceCeilCR = ivec2(ceil(sourceFracIndexCR));\n\n          float topLeft = getImage(b, sourceFloorCR.y, sourceFloorCR.x, d);\n          float bottomLeft = getImage(b, sourceCeilCR.y, sourceFloorCR.x, d);\n          float topRight = getImage(b, sourceFloorCR.y, sourceCeilCR.x, d);\n          float bottomRight = getImage(b, sourceCeilCR.y, sourceCeilCR.x, d);\n\n          vec2 fracCR = sourceFracIndexCR - vec2(sourceFloorCR);\n\n          float top = topLeft + (topRight - topLeft) * fracCR.x;\n          float bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;\n          float newValue = top + (bottom - top) * fracCR.y;\n          setOutput(newValue);\n        } else {\n          // Compute the coordinators of nearest neighbor point.\n          ivec2 sourceNearestCR = ivec2(floor(\n            sourceFracIndexCR + vec2(0.5,0.5)));\n          float newValue = getImage(b, sourceNearestCR.y, sourceNearestCR.x, d);\n          setOutput(newValue);\n        }\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/CropAndResize.js\nvar cropAndResize3 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { image: image2, boxes, boxInd } = inputs;\n  const { cropSize, method, extrapolationValue } = attrs;\n  const program = new CropAndResizeProgram(image2.shape, boxes.shape, cropSize, method, extrapolationValue);\n  return backend2.runWebGLProgram(program, [image2, boxes, boxInd], \"float32\");\n};\nvar cropAndResizeConfig2 = {\n  kernelName: CropAndResize,\n  backendName: \"webgl\",\n  kernelFunc: cropAndResize3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/cum_gpu.js\nvar CumOpType;\n(function(CumOpType3) {\n  CumOpType3[\"Prod\"] = \"*\";\n  CumOpType3[\"Sum\"] = \"+\";\n})(CumOpType || (CumOpType = {}));\nvar CumProgram = class {\n  constructor(op2, outputShape, exclusive, reverse5) {\n    this.op = op2;\n    this.outputShape = outputShape;\n    this.variableNames = [\"x\"];\n    this.customUniforms = [{ name: \"index\", type: \"float\" }];\n    const rank = this.outputShape.length;\n    const initVal = this.op === CumOpType.Prod ? \"1.0\" : \"0.0\";\n    const val = exclusive ? initVal : `getX(${getCoords2(rank, \"coords\", this.op)})`;\n    const length = this.outputShape[this.outputShape.length - 1];\n    let condition = \"\";\n    let idxString = \"\";\n    if (exclusive) {\n      condition = reverse5 ? `end != ${length - 1}` : \"end != 0\";\n      idxString = reverse5 ? \"end + 1\" : \"end - 1\";\n    } else {\n      condition = reverse5 ? `end + pow2 < ${length}` : \"end >= pow2\";\n      idxString = reverse5 ? \"end + pow2\" : \"end - pow2\";\n    }\n    this.userCode = `\n      void main() {\n        ${getCoordsDataType(rank)} coords = getOutputCoords();\n        int end = ${getFinalCoord(rank, \"coords\", this.op)};\n        float val = ${val};\n        int pow2 = int(pow(2.0, index));\n        if (${condition}) {\n          int idx = ${idxString};\n          ${getFinalCoord(rank, \"coords\", this.op)} = idx;\n          val ${this.op}= getX(${getCoords2(rank, \"coords\", this.op)});\n        }\n        setOutput(val);\n      }\n    `;\n  }\n};\nfunction getCoords2(rank, name, op2) {\n  if (rank === 1) {\n    return `${name}`;\n  } else if (rank === 2) {\n    return `${name}.x, ${name}.y`;\n  } else if (rank === 3) {\n    return `${name}.x, ${name}.y, ${name}.z`;\n  } else if (rank === 4) {\n    return `${name}.x, ${name}.y, ${name}.z, ${name}.w`;\n  } else {\n    throw new Error(`Cumulative ${op2} for rank ${rank} is not yet supported`);\n  }\n}\nfunction getFinalCoord(rank, name, op2) {\n  if (rank === 1) {\n    return `${name}`;\n  } else if (rank === 2) {\n    return `${name}.y`;\n  } else if (rank === 3) {\n    return `${name}.z`;\n  } else if (rank === 4) {\n    return `${name}.w`;\n  } else {\n    throw new Error(`Cumulative ${op2} for rank ${rank} is not yet supported`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Cum_impl.js\nfunction cumImpl(op2, x, backend2, axis, exclusive, reverse5) {\n  const xRank = x.shape.length;\n  const permutation = backend_util_exports.getAxesPermutation([axis], xRank);\n  let permutedX = x;\n  if (permutation != null) {\n    permutedX = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutation } });\n  }\n  const permutedAxis = backend_util_exports.getInnerMostAxes(1, xRank)[0];\n  if (permutedAxis !== xRank - 1) {\n    throw new Error(`WebGL cumprod shader expects an inner-most axis=${x.shape.length - 1} but got axis=${axis}`);\n  }\n  const size = permutedX.shape[permutedAxis];\n  let result = identity3({ inputs: { x: permutedX }, backend: backend2 });\n  for (let i2 = 0; i2 <= Math.ceil(Math.log2(size)) - 1; i2++) {\n    const program = new CumProgram(op2, permutedX.shape, false, reverse5);\n    const customValues = [[i2]];\n    const prevResult = result;\n    result = backend2.runWebGLProgram(program, [result], result.dtype, customValues);\n    backend2.disposeIntermediateTensorInfo(prevResult);\n  }\n  if (exclusive) {\n    const program = new CumProgram(op2, permutedX.shape, exclusive, reverse5);\n    const prevResult = result;\n    result = backend2.runWebGLProgram(program, [result], result.dtype);\n    backend2.disposeIntermediateTensorInfo(prevResult);\n  }\n  if (permutation != null) {\n    const reversePermutation = backend_util_exports.getUndoAxesPermutation(permutation);\n    const reverseTransposedResult = transpose3({ inputs: { x: result }, backend: backend2, attrs: { perm: reversePermutation } });\n    backend2.disposeIntermediateTensorInfo(result);\n    backend2.disposeIntermediateTensorInfo(permutedX);\n    return reverseTransposedResult;\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Cumprod.js\nfunction cumprod3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  return cumImpl(CumOpType.Prod, x, backend2, axis, exclusive, reverse5);\n}\nvar cumprodConfig2 = {\n  kernelName: Cumprod,\n  backendName: \"webgl\",\n  kernelFunc: cumprod3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Cumsum.js\nfunction cumsum3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  return cumImpl(CumOpType.Sum, x, backend2, axis, exclusive, reverse5);\n}\nvar cumsumConfig2 = {\n  kernelName: Cumsum,\n  backendName: \"webgl\",\n  kernelFunc: cumsum3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/DenseBincount.js\nfunction denseBincount3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, weights } = inputs;\n  const { size, binaryOutput } = attrs;\n  if (x.shape.length === 1) {\n    const xVals = backend2.readSync(x.dataId);\n    const weightsVals = backend2.readSync(weights.dataId);\n    const outVals = bincountImplCPU(xVals, weightsVals, weights.dtype, weights.shape, size);\n    return backend2.makeTensorInfo([size], weights.dtype, outVals);\n  } else if (x.shape.length === 2) {\n    const xBuf = backend2.bufferSync(x);\n    const weightsBuf = backend2.bufferSync(weights);\n    const outBuf = bincountReduceImplCPU(xBuf, weightsBuf, size, binaryOutput);\n    return backend2.makeTensorInfo(outBuf.shape, weights.dtype, outBuf.values);\n  }\n  throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${x.shape.length}.`);\n}\nvar denseBincountConfig2 = {\n  kernelName: DenseBincount,\n  backendName: \"webgl\",\n  kernelFunc: denseBincount3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/depth_to_space_gpu.js\nvar DepthToSpaceProgram = class {\n  constructor(outputShape, blockSize, dataFormat) {\n    this.variableNames = [\"x\"];\n    this.outputShape = [];\n    this.outputShape = outputShape;\n    this.blockSize = blockSize;\n    this.dataFormat = dataFormat;\n    this.userCode = `\n    void main() {\n      ivec4 coords = getOutputCoords();\n      int b = coords[0];\n      int h = ${this.getHeightCoordString()};\n      int w = ${this.getWidthCoordString()};\n      int d = ${this.getDepthCoordString()};\n\n      int in_h = h / ${blockSize};\n      int offset_h = imod(h, ${blockSize});\n      int in_w = w / ${blockSize};\n      int offset_w = imod(w, ${blockSize});\n      int offset_d = (offset_h * ${blockSize} + offset_w) *\n        ${this.getOutputDepthSize()};\n      int in_d = d + offset_d;\n\n      float result = ${this.getInputSamplingString()};\n      setOutput(result);\n    }\n  `;\n  }\n  getHeightCoordString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `coords[1]`;\n    } else {\n      return `coords[2]`;\n    }\n  }\n  getWidthCoordString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `coords[2]`;\n    } else {\n      return `coords[3]`;\n    }\n  }\n  getDepthCoordString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `coords[3]`;\n    } else {\n      return `coords[1]`;\n    }\n  }\n  getOutputDepthSize() {\n    if (this.dataFormat === \"NHWC\") {\n      return this.outputShape[3];\n    } else {\n      return this.outputShape[1];\n    }\n  }\n  getInputSamplingString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `getX(b, in_h, in_w, in_d)`;\n    } else {\n      return `getX(b, in_d, in_h, in_w)`;\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/DepthToSpace.js\nfunction depthToSpace3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockSize, dataFormat } = attrs;\n  const batchSize = x.shape[0];\n  const inputHeight = dataFormat === \"NHWC\" ? x.shape[1] : x.shape[2];\n  const inputWidth = dataFormat === \"NHWC\" ? x.shape[2] : x.shape[3];\n  const inputDepth = dataFormat === \"NHWC\" ? x.shape[3] : x.shape[1];\n  const outputHeight = inputHeight * blockSize;\n  const outputWidth = inputWidth * blockSize;\n  const outputDepth = inputDepth / (blockSize * blockSize);\n  const outputShape = dataFormat === \"NHWC\" ? [batchSize, outputHeight, outputWidth, outputDepth] : [batchSize, outputDepth, outputHeight, outputWidth];\n  const program = new DepthToSpaceProgram(outputShape, blockSize, dataFormat);\n  return backend2.runWebGLProgram(program, [x], x.dtype);\n}\nvar depthToSpaceConfig2 = {\n  kernelName: DepthToSpace,\n  backendName: \"webgl\",\n  kernelFunc: depthToSpace3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_gpu_depthwise.js\nvar DepthwiseConv2DProgram = class {\n  constructor(convInfo, addBias = false, activation2 = null, hasPreluActivation = false, hasLeakyReluAlpha = false) {\n    this.variableNames = [\"x\", \"W\"];\n    this.customUniforms = [\n      { name: \"pads\", type: \"ivec2\" },\n      { name: \"strides\", type: \"ivec2\" },\n      { name: \"dilations\", type: \"ivec2\" },\n      { name: \"inDims\", type: \"ivec2\" }\n    ];\n    this.outputShape = convInfo.outShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const channelMul = convInfo.outChannels / convInfo.inChannels;\n    let activationSnippet = \"\", applyActivationSnippet = \"\";\n    if (activation2) {\n      if (hasPreluActivation) {\n        activationSnippet = `float activation(float a) {\n          float b = getPreluActivationWeightsAtOutCoords();\n          ${activation2}\n        }`;\n      } else if (hasLeakyReluAlpha) {\n        activationSnippet = `float activation(float a) {\n          float b = getLeakyreluAlphaAtOutCoords();\n          ${activation2}\n        }`;\n      } else {\n        activationSnippet = `\n          float activation(float x) {\n            ${activation2}\n          }\n        `;\n      }\n      applyActivationSnippet = `result = activation(result);`;\n    }\n    const addBiasSnippet = addBias ? \"result += getBiasAtOutCoords();\" : \"\";\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivation) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    if (hasLeakyReluAlpha) {\n      this.variableNames.push(\"leakyreluAlpha\");\n    }\n    this.userCode = `\n      ${activationSnippet}\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / ${channelMul};\n        int q = d2 - d1 * ${channelMul};\n\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        // Convolve x(?, ?, d1) with w(:, :, d1, q) to get y(yR, yC, d2).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        // TO DO(dsmilkov): Flatten the two for loops and vec4 the operations.\n        for (int wR = 0; wR < ${filterHeight}; wR++) {\n          int xR = xRCorner + wR * dilations[0];\n\n          if (xR < 0 || xR >= inDims[0]) {\n            continue;\n          }\n\n          for (int wC = 0; wC < ${filterWidth}; wC++) {\n            int xC = xCCorner + wC * dilations[1];\n\n            if (xC < 0 || xC >= inDims[1]) {\n              continue;\n            }\n\n            float xVal = getX(batch, xR, xC, d1);\n            float wVal = getW(wR, wC, d1, q);\n            dotProd += xVal * wVal;\n          }\n        }\n\n        float result = dotProd;\n        ${addBiasSnippet}\n        ${applyActivationSnippet}\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_packed_gpu_depthwise.js\nvar DepthwiseConvPacked2DProgram = class {\n  constructor(convInfo, addBias = false, activation2 = null, hasPreluActivation = false, hasLeakyReluAlpha = false) {\n    this.variableNames = [\"x\", \"W\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.customUniforms = [\n      { name: \"pads\", type: \"ivec2\" },\n      { name: \"strides\", type: \"ivec2\" },\n      { name: \"dilations\", type: \"ivec2\" },\n      { name: \"inDims\", type: \"ivec2\" }\n    ];\n    this.outputShape = convInfo.outShape;\n    this.enableShapeUniforms = useShapeUniforms(this.outputShape.length);\n    const channelMul = convInfo.outChannels / convInfo.inChannels;\n    const padLeft = convInfo.padInfo.left;\n    const strideWidth = convInfo.strideWidth;\n    const dilationWidth = convInfo.dilationWidth;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const texelsAcross = filterWidth;\n    let mainLoop = `\n      int xR; int xC; int xCOffset;\n      vec4 wTexel; vec4 previous; vec4 final;`;\n    for (let c = 0; c < filterWidth; c++) {\n      mainLoop += `\n          vec4 xTexelC${c * 2};\n          int xTexelC${c * 2}Ready;\n          vec4 xTexelC${c * 2 + 1};\n          int xTexelC${c * 2 + 1}Ready;\n          vec4 xC${c};`;\n    }\n    mainLoop += `\n    for (int r = 0; r < ${filterHeight}; r++) {\n      `;\n    for (let c = 0; c < filterWidth; c++) {\n      mainLoop += `\n          xTexelC${c * 2} = vec4(0.0);\n          xTexelC${c * 2}Ready = 0;\n          xTexelC${c * 2 + 1} = vec4(0.0);\n          xTexelC${c * 2 + 1}Ready = 0;\n          xC${c} = vec4(0.0);`;\n    }\n    mainLoop += `\n        xR = xRCorner + r * dilations[0];\n        if (xR >=0 && xR < inDims[0]) {\n      `;\n    for (let texelC = 0; texelC < (texelsAcross + 1) / 2; texelC++) {\n      const colIndex = texelC * 2;\n      mainLoop += `\n          xC = xCCorner + ${colIndex * dilationWidth};\n          `;\n      if (strideWidth === 1) {\n        if (colIndex < filterWidth) {\n          if (padLeft % 2 === 1) {\n            mainLoop += `\n                xCOffset = xC + 1;\n                if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${colIndex}Ready == 0) {\n                  xTexelC${colIndex} = getX(batch, xR, xCOffset, d1);\n\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if (xCOffset + 1 >= inDims[1]) {\n                    xTexelC${colIndex}.zw = vec2(0.0);\n                  }\n                  xTexelC${colIndex}Ready = 1;\n                }\n              `;\n            if (dilationWidth === 1 && colIndex > 0) {\n              mainLoop += `\n                xC${colIndex} = vec4(xTexelC${colIndex - 2}.zw, xTexelC${colIndex}.xy);\n                `;\n            } else {\n              mainLoop += `\n                  xCOffset = xC + 1 - 2;\n\n                  if (xCOffset >= 0 && xCOffset < inDims[1]) {\n                    previous = getX(batch, xR, xCOffset, d1);\n\n                    // Need to manually clear unused channels in case\n                    // we're reading from recycled texture.\n                    if (xCOffset + 1 >= inDims[1]) {\n                      previous.zw = vec2(0.0);\n                    }\n\n                    xC${colIndex} = vec4(previous.zw, xTexelC${colIndex}.xy);\n                  } else {\n                    xC${colIndex} = vec4(0.0, 0.0, xTexelC${colIndex}.xy);\n                  }\n                  `;\n            }\n          } else {\n            mainLoop += `\n                if (xC >= 0 && xC < inDims[1] && xTexelC${colIndex}Ready == 0) {\n                  xTexelC${colIndex} = getX(batch, xR, xC, d1);\n                  if (xC + 1 >= inDims[1]) {\n                    xTexelC${colIndex}.zw = vec2(0.0);\n                  }\n                  xTexelC${colIndex}Ready = 1;\n                }\n\n                xC${colIndex} = xTexelC${colIndex};\n                `;\n          }\n          if (colIndex + 1 < filterWidth) {\n            const nextTexelOffset = padLeft % 2 === 0 ? util_exports.nearestLargerEven(dilationWidth) : dilationWidth;\n            if (dilationWidth % 2 === 0 && padLeft % 2 === 1 || dilationWidth % 2 !== 0 && padLeft % 2 !== 1) {\n              mainLoop += `\n                  xCOffset = xC + imod(pads[1], 2) + ${nextTexelOffset};\n\n                  if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${colIndex + 1}Ready == 0) {\n                    xTexelC${colIndex + 1} = getX(batch, xR, xCOffset, d1);\n\n                    // Need to manually clear unused channels in case\n                    // we're reading from recycled texture.\n                    if (xCOffset + 1 >= inDims[1]) {\n                      xTexelC${colIndex + 1}.zw = vec2(0.0);\n                    }\n                    xTexelC${colIndex + 1}Ready = 1;\n                  }\n                  `;\n              if (dilationWidth > 1) {\n                mainLoop += `\n                    xCOffset -= 2;\n                    if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${colIndex}Ready == 0) {\n                      xTexelC${colIndex} = getX(batch, xR, xCOffset, d1);\n                      xTexelC${colIndex}Ready = 1;\n                    }\n                    `;\n              }\n              mainLoop += `\n                  xC${colIndex + 1} = vec4(xTexelC${colIndex}.zw, xTexelC${colIndex + 1}.xy);\n                  `;\n            } else {\n              if (nextTexelOffset === 1) {\n                mainLoop += `\n                    xC${colIndex + 1} = xTexelC${colIndex};\n                    `;\n              } else {\n                mainLoop += `\n                    xCOffset = xC + ${nextTexelOffset};\n\n                    if (xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${colIndex + 1}Ready == 0) {\n                      xTexelC${colIndex + 1} = getX(batch, xR, xCOffset, d1);\n                      if (xCOffset + 1 >= inDims[1]) {\n                        xTexelC${colIndex + 1}.zw = vec2(0.0);\n                      }\n                      xTexelC${colIndex + 1}Ready = 1;\n                    }\n\n                    xC${colIndex + 1} = xTexelC${colIndex + 1};\n                    `;\n              }\n            }\n          }\n        }\n      } else {\n        if (colIndex < filterWidth) {\n          if (padLeft % 2 === 1) {\n            mainLoop += `\n                xCOffset = xC + 1 - strides[1];\n                if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${colIndex}Ready == 0) {\n                  xTexelC${colIndex} = getX(batch, xR, xCOffset, d1);\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if (xCOffset + 1 >= inDims[1]) {\n                    xTexelC${colIndex}.zw = vec2(0.0);\n                  }\n                  xTexelC${colIndex}Ready = 1;\n                }\n\n                if(xC + 1 >= 0 && xC + 1 < inDims[1] && xTexelC${colIndex + 1}Ready == 0) {\n                  xTexelC${colIndex + 1} = getX(batch, xR, xC + 1, d1);\n                  // Need to manually clear unused channels in case\n                  // we're reading from recycled texture.\n                  if (xC + 2 >= inDims[1]) {\n                    xTexelC${colIndex + 1}.zw = vec2(0.0);\n                  }\n                  xTexelC${colIndex + 1}Ready = 1;\n                }\n\n                xC${colIndex} = vec4(xTexelC${colIndex}.zw, xTexelC${colIndex + 1}.zw);\n              `;\n            if (colIndex + 1 < filterWidth) {\n              mainLoop += `\n                  final = vec4(0.0);\n                  xCOffset = xC + 1 + strides[1];\n                  if(xCOffset >= 0 && xCOffset < inDims[1]) {\n                    final = getX(batch, xR, xCOffset, d1);\n                  }\n                  xC${colIndex + 1} = vec4(xTexelC${colIndex + 1}.xy, final.xy);\n                `;\n            }\n          } else {\n            mainLoop += `\n                if(xC >= 0 && xC < inDims[1] && xTexelC${colIndex}Ready == 0) {\n                  xTexelC${colIndex} = getX(batch, xR, xC, d1);\n                  if (xC + 1 >= inDims[1]) {\n                    xTexelC${colIndex}.zw = vec2(0.0);\n                  }\n                  xTexelC${colIndex}Ready = 1;\n                }\n\n                xCOffset = xC + strides[1];\n                if(xCOffset >= 0 && xCOffset < inDims[1] && xTexelC${colIndex + 1}Ready == 0) {\n                  xTexelC${colIndex + 1} = getX(batch, xR, xCOffset, d1);\n                  if (xCOffset + 1 >= inDims[1]) {\n                    xTexelC${colIndex + 1}.zw = vec2(0.);\n                  }\n                  xTexelC${colIndex + 1}Ready = 1;\n                }\n\n                xC${colIndex} = vec4(\n                  xTexelC${colIndex}.xy, xTexelC${colIndex + 1}.xy);\n              `;\n            if (colIndex + 1 < filterWidth) {\n              mainLoop += `\n                  xC${colIndex + 1} = vec4(xTexelC${colIndex}.zw, xTexelC${colIndex + 1}.zw);\n                `;\n            }\n          }\n        }\n      }\n      if (colIndex < filterWidth) {\n        mainLoop += `\n            wTexel = getW(r, ${colIndex}, d1, q);\n            dotProd += xC${colIndex} * vec4(wTexel.xz, wTexel.xz);\n          `;\n        if (colIndex + 1 < filterWidth) {\n          mainLoop += `\n              wTexel = getW(r, ${colIndex + 1}, d1, q);\n              dotProd += xC${colIndex + 1} * vec4(wTexel.xz, wTexel.xz);\n            `;\n        }\n      }\n    }\n    mainLoop += `\n    }\n  `;\n    mainLoop += `\n      }\n    `;\n    let activationSnippet = \"\", applyActivationSnippet = \"\";\n    if (activation2) {\n      if (hasPreluActivation) {\n        activationSnippet = `vec4 activation(vec4 a) {\n          vec4 b = getPreluActivationWeightsAtOutCoords();\n          ${activation2}\n        }`;\n      } else if (hasLeakyReluAlpha) {\n        activationSnippet = `vec4 activation(vec4 a) {\n          vec4 b = getLeakyreluAlphaAtOutCoords();\n          ${activation2}\n        }`;\n      } else {\n        activationSnippet = `vec4 activation(vec4 x) {\n          ${activation2}\n        }`;\n      }\n      applyActivationSnippet = `result = activation(result);`;\n    }\n    const addBiasSnippet = addBias ? \"result += getBiasAtOutCoords();\" : \"\";\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivation) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    if (hasLeakyReluAlpha) {\n      this.variableNames.push(\"leakyreluAlpha\");\n    }\n    this.userCode = `\n      ${activationSnippet}\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        ivec2 xRCCorner = coords.yz * strides - pads;\n        int d2 = coords.w;\n        int d1 = d2 / ${channelMul};\n        int q = d2 - d1 * ${channelMul};\n        int xRCorner = xRCCorner.x;\n        int xCCorner = xRCCorner.y;\n\n        //intialize dotProd with a small epsilon seems to reduce GPU accuracy loss.\n        vec4 dotProd = vec4(0.000000000000001);\n\n        ${mainLoop}\n\n        vec4 result = dotProd - vec4(0.000000000000001);\n        ${addBiasSnippet}\n        ${applyActivationSnippet}\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/DepthwiseConv2dNative.js\nfunction depthwiseConv2dNative2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dilations, dimRoundingMode } = attrs;\n  let $dilations = dilations;\n  if ($dilations == null) {\n    $dilations = [1, 1];\n  }\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, $dilations), () => `Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${strides} and dilations '${$dilations}'`);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad3, dimRoundingMode, true);\n  let program;\n  if (env().getBool(\"WEBGL_PACK_DEPTHWISECONV\") && convInfo.strideWidth <= 2 && convInfo.outChannels / convInfo.inChannels === 1) {\n    program = new DepthwiseConvPacked2DProgram(convInfo);\n  } else {\n    program = new DepthwiseConv2DProgram(convInfo);\n  }\n  const customValues = [\n    [convInfo.padInfo.top, convInfo.padInfo.left],\n    [convInfo.strideHeight, convInfo.strideWidth],\n    [convInfo.dilationHeight, convInfo.dilationWidth],\n    [convInfo.inHeight, convInfo.inWidth]\n  ];\n  return backend2.runWebGLProgram(program, [x, filter], \"float32\", customValues);\n}\nvar depthwiseConv2dNativeConfig2 = {\n  kernelName: DepthwiseConv2dNative,\n  backendName: \"webgl\",\n  kernelFunc: depthwiseConv2dNative2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/conv_backprop_gpu_depthwise.js\nvar DepthwiseConv2DDerFilterProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"x\", \"dy\"];\n    this.outputShape = convInfo.filterShape;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const padTop = convInfo.padInfo.top;\n    const padLeft = convInfo.padInfo.left;\n    const channelMul = convInfo.outChannels / convInfo.inChannels;\n    this.userCode = `\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int wR = coords.x;\n        int wC = coords.y;\n        int d1 = coords.z;\n        int dm = coords.w;\n        int d2 = d1 * ${channelMul} + dm;\n\n        float dotProd = 0.0;\n\n        // TO DO: Vec4 over the batch size\n        for (int b = 0; b < ${convInfo.batchSize}; b++) {\n          for (int yR = 0; yR < ${convInfo.outHeight}; yR++) {\n            int xR = wR + yR * ${strideHeight} - ${padTop};\n\n            if (xR < 0 || xR >= ${convInfo.inHeight}) {\n              continue;\n            }\n\n            for (int yC = 0; yC < ${convInfo.outWidth}; yC++) {\n              int xC = wC + yC * ${strideWidth} - ${padLeft};\n\n              if (xC < 0 || xC >= ${convInfo.inWidth}) {\n                continue;\n              }\n\n              float dyValue = getDy(b, yR, yC, d2);\n              float xValue = getX(b, xR, xC, d1);\n              dotProd += (xValue * dyValue);\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\nvar DepthwiseConv2DDerInputProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\", \"W\"];\n    this.outputShape = convInfo.inShape;\n    const filterHeight = convInfo.filterHeight;\n    const filterWidth = convInfo.filterWidth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const padTop = filterHeight - 1 - convInfo.padInfo.top;\n    const padLeft = filterWidth - 1 - convInfo.padInfo.left;\n    const channelMul = convInfo.outChannels / convInfo.inChannels;\n    this.userCode = `\n      const ivec2 pads = ivec2(${padTop}, ${padLeft});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords[0];\n        int d1 = coords[3];\n        ivec2 dyCorner = coords.yz - pads;\n        int dyRCorner = dyCorner.x;\n        int dyCCorner = dyCorner.y;\n\n        float dotProd = 0.0;\n\n        for (int wR = 0; wR < ${filterHeight}; wR++) {\n          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;\n\n          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          int wRPerm = ${filterHeight} - 1 - wR;\n\n          for (int wC = 0; wC < ${filterWidth}; wC++) {\n            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;\n\n            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            int wCPerm = ${filterWidth} - 1 - wC;\n\n            // TO DO: Vec4 over the channelMul\n            for (int dm = 0; dm < ${channelMul}; dm++) {\n              int d2 = d1 * ${channelMul} + dm;\n              float xValue = getDy(batch, idyR, idyC, d2);\n              float wValue = getW(wRPerm, wCPerm, d1, dm);\n              dotProd += xValue * wValue;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/DepthwiseConv2dNativeBackpropFilter.js\nfunction depthwiseConv2dNativeBackpropFilter3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, dy } = inputs;\n  const { strides, dilations, pad: pad3, dimRoundingMode, filterShape } = attrs;\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filterShape, strides, dilations, pad3, dimRoundingMode, true);\n  const program = new DepthwiseConv2DDerFilterProgram(convInfo);\n  return backend2.runWebGLProgram(program, [x, dy], \"float32\");\n}\nvar depthwiseConv2dNativeBackpropFilterConfig2 = {\n  kernelName: DepthwiseConv2dNativeBackpropFilter,\n  backendName: \"webgl\",\n  kernelFunc: depthwiseConv2dNativeBackpropFilter3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/DepthwiseConv2dNativeBackpropInput.js\nfunction depthwiseConv2dNativeBackpropInput3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, filter } = inputs;\n  const { strides, dilations, pad: pad3, dimRoundingMode, inputShape } = attrs;\n  const convInfo = backend_util_exports.computeConv2DInfo(inputShape, filter.shape, strides, dilations, pad3, dimRoundingMode, true);\n  const program = new DepthwiseConv2DDerInputProgram(convInfo);\n  return backend2.runWebGLProgram(program, [dy, filter], \"float32\");\n}\nvar depthwiseConv2dNativeBackpropInputConfig2 = {\n  kernelName: DepthwiseConv2dNativeBackpropInput,\n  backendName: \"webgl\",\n  kernelFunc: depthwiseConv2dNativeBackpropInput3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/diag_gpu.js\nvar DiagProgram = class {\n  constructor(size) {\n    this.variableNames = [\"X\"];\n    this.outputShape = [size, size];\n    this.userCode = `\n      void main() {\n          ivec2 coords = getOutputCoords();\n          float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;\n          setOutput(val);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Diag.js\nfunction diag3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  const outShape = [...x.shape, ...x.shape];\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const flat = reshape4({ inputs: { x }, backend: backend2, attrs: { shape: [xSize] } });\n  const program = new DiagProgram(xSize);\n  const res = backend2.runWebGLProgram(program, [flat], flat.dtype);\n  const out = reshape4({ inputs: { x: res }, backend: backend2, attrs: { shape: outShape } });\n  backend2.disposeIntermediateTensorInfo(flat);\n  backend2.disposeIntermediateTensorInfo(res);\n  return out;\n}\nvar diagConfig2 = {\n  kernelName: Diag,\n  backendName: \"webgl\",\n  kernelFunc: diag3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/dilation_gpu.js\nvar Dilation2DProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"x\", \"W\"];\n    this.outputShape = convInfo.outShape;\n    const { inHeight, inWidth, padInfo, strideHeight, strideWidth, filterHeight, filterWidth, dilationHeight, dilationWidth } = convInfo;\n    const { top: padTop, left: padLeft } = padInfo;\n    this.userCode = `\n      const ivec2 strides = ivec2(${strideHeight}, ${strideWidth});\n      const ivec2 pads = ivec2(${padTop}, ${padLeft});\n      const float neg_infinity = -3.4e38;\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int batch = coords.x;\n        int d1 = coords.w;\n        ivec2 outTopLeftCorner =\n            coords.yz * strides - pads;\n        int hBeg = outTopLeftCorner.x;\n        int wBeg = outTopLeftCorner.y;\n\n        float curVal = neg_infinity;\n        for (int h = 0; h < ${filterHeight}; h++) {\n          int hIn = hBeg + h * ${dilationHeight};\n\n          if (hIn >= 0 && hIn < ${inHeight}) {\n            for (int w = 0; w < ${filterWidth}; w++) {\n              int wIn = wBeg + w * ${dilationWidth};\n\n              if (wIn >= 0 && wIn < ${inWidth}) {\n                float xVal = getX(batch, hIn, wIn, d1);\n                float wVal = getW(h, w, d1);\n\n                float val = xVal + wVal;\n                if (val > curVal) {\n                  curVal = val;\n                }\n              }\n            }\n          }\n        }\n\n        float result = curVal;\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Dilation2D.js\nfunction dilation2D(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dilations } = attrs;\n  const convInfo = backend_util_exports.computeDilation2DInfo(x.shape, filter.shape, strides, pad3, \"NHWC\", dilations);\n  let out;\n  const program = new Dilation2DProgram(convInfo);\n  out = backend2.runWebGLProgram(program, [x, filter], \"float32\");\n  const outReshaped = reshape4({ inputs: { x: out }, backend: backend2, attrs: { shape: convInfo.outShape } });\n  backend2.disposeIntermediateTensorInfo(out);\n  return outReshaped;\n}\nvar dilation2DConfig2 = {\n  kernelName: Dilation2D,\n  backendName: \"webgl\",\n  kernelFunc: dilation2D\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Einsum.js\nfunction einsum3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { equation } = attrs;\n  const tensors = inputs;\n  const { allDims, summedDims, idDims } = backend_util_exports.decodeEinsumEquation(equation, tensors.length);\n  backend_util_exports.checkEinsumDimSizes(allDims.length, idDims, tensors);\n  const { path, steps } = backend_util_exports.getEinsumComputePath(summedDims, idDims);\n  const nSteps = steps.length;\n  let out = null;\n  let numDimsRemaining = allDims.length;\n  const tensorsToDispose = [];\n  for (let i2 = 0; i2 < nSteps; ++i2) {\n    for (const idTerm of steps[i2]) {\n      const { permutationIndices: perm, expandDims: dimsToExpand } = backend_util_exports.getEinsumPermutation(numDimsRemaining, idDims[idTerm]);\n      let x;\n      if (backend_util_exports.isIdentityPermutation(perm)) {\n        x = tensors[idTerm];\n      } else {\n        x = transpose3({ inputs: { x: tensors[idTerm] }, backend: backend2, attrs: { perm } });\n        tensorsToDispose.push(x);\n      }\n      const targetShape = x.shape.slice();\n      for (let k = 0; k < dimsToExpand.length; ++k) {\n        targetShape.splice(dimsToExpand[k], 0, 1);\n      }\n      if (!util_exports.arraysEqual(x.shape, targetShape)) {\n        x = reshape4({ inputs: { x }, backend: backend2, attrs: { shape: targetShape } });\n        tensorsToDispose.push(x);\n      }\n      if (out === null) {\n        out = x;\n      } else {\n        out = multiply3({ inputs: { a: x, b: out }, backend: backend2 });\n        tensorsToDispose.push(out);\n      }\n    }\n    if (i2 < nSteps - 1) {\n      if (path[i2] >= 0) {\n        out = sum4({\n          inputs: { x: out },\n          backend: backend2,\n          attrs: {\n            axis: path[i2] - (allDims.length - numDimsRemaining),\n            keepDims: false\n          }\n        });\n        tensorsToDispose.push(out);\n      }\n      numDimsRemaining--;\n    }\n  }\n  for (const tensorInfo of tensorsToDispose) {\n    if (tensorInfo === out) {\n      continue;\n    }\n    backend2.disposeIntermediateTensorInfo(tensorInfo);\n  }\n  return out;\n}\nvar einsumConfig2 = {\n  kernelName: Einsum,\n  backendName: \"webgl\",\n  kernelFunc: einsum3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Elu.js\nvar ELU4 = `return (x >= 0.0) ? x : (exp(x) - 1.0);`;\nvar ELU_PACKED = `\n  vec4 result;\n\n  result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);\n  result.g = (x.g >= 0.0) ? x.g : (exp(x.g) - 1.0);\n  result.b = (x.b >= 0.0) ? x.b : (exp(x.b) - 1.0);\n  result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);\n\n  return result;\n`;\nvar elu5 = unaryKernelFunc2({ opSnippet: ELU4, packedOpSnippet: ELU_PACKED });\nvar eluConfig2 = {\n  kernelName: Elu,\n  backendName: \"webgl\",\n  kernelFunc: elu5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/EluGrad.js\nvar ELU_DER = `return (b >= 1.0) ? a : a * (b + 1.0);`;\nvar ELU_DER_PACKED = `\n  vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));\n  return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));\n`;\nvar eluGrad2 = (args) => {\n  const { inputs, backend: backend2 } = args;\n  const { dy, y } = inputs;\n  const program = env().getBool(\"WEBGL_PACK_BINARY_OPERATIONS\") ? new BinaryOpPackedProgram(ELU_DER_PACKED, dy.shape, y.shape) : new BinaryOpProgram(ELU_DER, dy.shape, y.shape);\n  return backend2.runWebGLProgram(program, [dy, y], dy.dtype);\n};\nvar eluGradConfig3 = {\n  kernelName: EluGrad,\n  backendName: \"webgl\",\n  kernelFunc: eluGrad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Equal.js\nvar PACKED_EQUAL = `\n  return vec4(equal(a, b));\n`;\nvar EQUAL = `return float(a == b);`;\nvar equal3 = binaryKernelFunc2({\n  opSnippet: EQUAL,\n  packedOpSnippet: PACKED_EQUAL,\n  dtype: \"bool\",\n  cpuKernelImpl: equalImplCPU\n});\nvar equalConfig2 = {\n  kernelName: Equal,\n  backendName: \"webgl\",\n  kernelFunc: equal3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Erf.js\nvar ERF = `\n  // Error function is calculated approximately with elementary function.\n  // See \"Handbook of Mathematical Functions with Formulas,\n  // Graphs, and Mathematical Tables\", Abramowitz and Stegun.\n  float p = ${backend_util_exports.ERF_P};\n  float a1 = ${backend_util_exports.ERF_A1};\n  float a2 = ${backend_util_exports.ERF_A2};\n  float a3 = ${backend_util_exports.ERF_A3};\n  float a4 = ${backend_util_exports.ERF_A4};\n  float a5 = ${backend_util_exports.ERF_A5};\n\n  float sign = sign(x);\n  x = abs(x);\n  float t = 1.0 / (1.0 + p * x);\n  return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));\n`;\nvar erf3 = unaryKernelFunc2({ opSnippet: ERF });\nvar erfConfig2 = {\n  kernelName: Erf,\n  backendName: \"webgl\",\n  kernelFunc: erf3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Exp.js\nvar EXP = CHECK_NAN_SNIPPET_UNARY + `\n  return exp(x);\n`;\nvar EXP_PACKED = `\n  vec4 result = exp(x);\n  bvec4 isNaN = isnan(x);\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n`;\nvar exp3 = unaryKernelFunc2({\n  opSnippet: EXP,\n  packedOpSnippet: EXP_PACKED,\n  cpuKernelImpl: expImplCPU,\n  dtype: \"float32\"\n});\nvar expConfig2 = {\n  kernelName: Exp,\n  backendName: \"webgl\",\n  kernelFunc: exp3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ExpandDims.js\nfunction expandDims4(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { dim } = attrs;\n  const { input: input2 } = inputs;\n  const inputRank = input2.shape.length;\n  const newShape = input2.shape.slice();\n  let $dim = dim;\n  if (dim < 0) {\n    util_exports.assert(-(inputRank + 1) <= dim, () => `Axis must be in the interval [${-(inputRank + 1)}, ${inputRank}]`);\n    $dim = inputRank + dim + 1;\n  }\n  newShape.splice($dim, 0, 1);\n  return reshape4({ inputs: { x: input2 }, backend: backend2, attrs: { shape: newShape } });\n}\nvar expandDimsConfig2 = {\n  kernelName: ExpandDims,\n  backendName: \"webgl\",\n  kernelFunc: expandDims4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Expm1.js\nvar EXPM1 = `return exp(x) - 1.0;`;\nvar expm13 = unaryKernelFunc2({ opSnippet: EXPM1, packedOpSnippet: EXPM1, cpuKernelImpl: expm1ImplCPU });\nvar expm1Config2 = {\n  kernelName: Expm1,\n  backendName: \"webgl\",\n  kernelFunc: expm13\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/fft_gpu.js\nvar FFTProgram = class {\n  constructor(component, inputShape, inverse) {\n    this.variableNames = [\"real\", \"imag\"];\n    const innerDim = inputShape[1];\n    this.outputShape = inputShape;\n    const exponentMultiplierSnippet = inverse ? `2.0 * ${Math.PI}` : `-2.0 * ${Math.PI}`;\n    const resultDenominator = inverse ? `${innerDim}.0` : \"1.0\";\n    let opString;\n    if (component === \"real\") {\n      opString = \"return real * expR - imag * expI;\";\n    } else if (component === \"imag\") {\n      opString = \"return real * expI + imag * expR;\";\n    } else {\n      throw new Error(`FFT component must be either \"real\" or \"imag\", got ${component}.`);\n    }\n    this.userCode = `\n      const float exponentMultiplier = ${exponentMultiplierSnippet};\n\n      float unaryOpComplex(float real, float expR, float imag, float expI) {\n        ${opString}\n      }\n\n      float mulMatDFT(int batch, int index) {\n        float indexRatio = float(index) / float(${innerDim});\n        float exponentMultiplierTimesIndexRatio =\n            exponentMultiplier * indexRatio;\n\n        float result = 0.0;\n\n        for (int i = 0; i < ${innerDim}; i++) {\n          // x = (-2|2 * PI / N) * index * i;\n          float x = exponentMultiplierTimesIndexRatio * float(i);\n          float expR = cos(x);\n          float expI = sin(x);\n          float real = getReal(batch, i);\n          float imag = getImag(batch, i);\n\n          result +=\n              unaryOpComplex(real, expR, imag, expI) / ${resultDenominator};\n        }\n\n        return result;\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        setOutput(mulMatDFT(coords[0], coords[1]));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FFT_impl.js\nfunction fftImpl2(x, inverse, backend2) {\n  const xData = backend2.texData.get(x.dataId);\n  const inputSize = util_exports.sizeFromShape(x.shape);\n  const innerDimensionSize = x.shape[x.shape.length - 1];\n  const batch = inputSize / innerDimensionSize;\n  const input2D = reshape4({ inputs: { x }, backend: backend2, attrs: { shape: [batch, innerDimensionSize] } });\n  const xShape = input2D.shape;\n  const realProgram = new FFTProgram(\"real\", xShape, inverse);\n  const imagProgram = new FFTProgram(\"imag\", xShape, inverse);\n  const inputs = [\n    {\n      dataId: xData.complexTensorInfos.real.dataId,\n      dtype: xData.complexTensorInfos.real.dtype,\n      shape: xShape\n    },\n    {\n      dataId: xData.complexTensorInfos.imag.dataId,\n      dtype: xData.complexTensorInfos.imag.dtype,\n      shape: xShape\n    }\n  ];\n  const realPart = backend2.runWebGLProgram(realProgram, inputs, \"float32\");\n  const imagPart = backend2.runWebGLProgram(imagProgram, inputs, \"float32\");\n  const complexOutput = complex3({ inputs: { real: realPart, imag: imagPart }, backend: backend2 });\n  backend2.disposeIntermediateTensorInfo(realPart);\n  backend2.disposeIntermediateTensorInfo(imagPart);\n  const complexOutputReshaped = reshape4({ inputs: { x: complexOutput }, backend: backend2, attrs: { shape: x.shape } });\n  backend2.disposeIntermediateTensorInfo(input2D);\n  backend2.disposeIntermediateTensorInfo(complexOutput);\n  return complexOutputReshaped;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FFT.js\nfunction fft3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  return fftImpl2(input2, false, backend2);\n}\nvar fftConfig2 = {\n  kernelName: FFT,\n  backendName: \"webgl\",\n  kernelFunc: fft3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/fill_gpu.js\nvar FillProgram = class {\n  constructor(shape, value) {\n    this.outputShape = [];\n    this.customUniforms = [{ name: \"value\", type: \"float\" }];\n    this.variableNames = [\"x\"];\n    this.outputShape = shape;\n    this.userCode = `\n      void main() {\n        // Input can be obtained from uniform value.\n        setOutput(value);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Fill.js\nfunction fill3(args) {\n  const { backend: backend2, attrs } = args;\n  const { shape, value } = attrs;\n  let { dtype } = attrs;\n  dtype = dtype || util_exports.inferDtype(value);\n  if (dtype === \"string\") {\n    const values = util_exports.getArrayFromDType(dtype, util_exports.sizeFromShape(shape));\n    values.fill(value);\n    return backend2.makeTensorInfo(shape, dtype, values);\n  } else {\n    const program = new FillProgram(shape, value);\n    const customValues = [[value]];\n    return backend2.runWebGLProgram(program, [], dtype, customValues);\n  }\n}\nvar fillConfig2 = {\n  kernelName: Fill,\n  backendName: \"webgl\",\n  kernelFunc: fill3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/flip_left_right_gpu.js\nvar FlipLeftRightProgram = class {\n  constructor(imageShape) {\n    this.variableNames = [\"Image\"];\n    this.outputShape = [];\n    const imageWidth = imageShape[2];\n    this.outputShape = imageShape;\n    this.userCode = `\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int x = coords[2];\n\n          int coordX = ${imageWidth} - x - 1;\n          float outputValue;\n          if(coordX >= 0 && coordX < ${imageWidth}) {\n            outputValue = getImage(coords[0], coords[1], coordX, coords[3]);\n          } else {\n            outputValue = getImage(coords[0], coords[1], coords[2], coords[3]);\n          }\n          setOutput(outputValue);\n        }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FlipLeftRight.js\nvar flipLeftRightConfig2 = {\n  kernelName: FlipLeftRight,\n  backendName: \"webgl\",\n  kernelFunc: ({ inputs, backend: backend2 }) => {\n    const { image: image2 } = inputs;\n    const webglBackend = backend2;\n    const program = new FlipLeftRightProgram(image2.shape);\n    const output = webglBackend.runWebGLProgram(program, [image2], image2.dtype);\n    return output;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Floor.js\nvar FLOOR = `return floor(x);`;\nvar floor3 = unaryKernelFunc2({ opSnippet: FLOOR, packedOpSnippet: FLOOR, cpuKernelImpl: floorImplCPU });\nvar floorConfig2 = {\n  kernelName: Floor,\n  backendName: \"webgl\",\n  kernelFunc: floor3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FloorDiv.js\nvar INT_DIV = `\n  float s = sign(a) * sign(b);\n  int ia = round(a);\n  int ib = round(b);\n  if (ib != 0) {\n    // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n    return float(idiv(ia, ib, s));\n  } else {\n    return NAN;\n  }\n`;\nvar INT_DIV_PACKED = `\n  ivec4 ia = round(a);\n  ivec4 ib = round(b);\n  bvec4 cond = notEqual(ib, ivec4(0));\n  ivec4 result = ivec4(0);\n  vec4 s = sign(a) * sign(b);\n\n  // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n  if (cond[0]) {\n    result[0] = idiv(ia[0], ib[0], s[0]);\n  }\n  if (cond[1]) {\n    result[1] = idiv(ia[1], ib[1], s[1]);\n  }\n  if (cond[2]) {\n    result[2] = idiv(ia[2], ib[2], s[2]);\n  }\n  if (cond[3]) {\n    result[3] = idiv(ia[3], ib[3], s[3]);\n  }\n  return vec4(result);\n`;\nvar floorDiv3 = binaryKernelFunc2({ opSnippet: INT_DIV, packedOpSnippet: INT_DIV_PACKED, dtype: \"int32\" });\nvar floorDivConfig2 = {\n  kernelName: FloorDiv,\n  backendName: \"webgl\",\n  kernelFunc: floorDiv3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FromPixels_utils/from_pixels_gpu.js\nvar FromPixelsProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    const glsl = getGlslDifferences();\n    const [height, width] = outputShape;\n    this.outputShape = outputShape;\n    this.userCode = `\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n        vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${width}.0, ${height}.0);\n\n        vec4 values = ${glsl.texture2D}(A, uv);\n        float value;\n        if (depth == 0) {\n          value = values.r;\n        } else if (depth == 1) {\n          value = values.g;\n        } else if (depth == 2) {\n          value = values.b;\n        } else if (depth == 3) {\n          value = values.a;\n        }\n\n        setOutput(floor(value * 255.0 + 0.5));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FromPixels_utils/from_pixels_packed_gpu.js\nvar FromPixelsPackedProgram = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = false;\n    this.packedOutput = true;\n    const glsl = getGlslDifferences();\n    const [height, width] = outputShape;\n    this.outputShape = outputShape;\n    this.userCode = `\n      void main() {\n        ivec3 coords = getOutputCoords();\n        int texR = coords[0];\n        int texC = coords[1];\n        int depth = coords[2];\n\n        vec4 result = vec4(0.);\n\n        for(int row=0; row<=1; row++) {\n          for(int col=0; col<=1; col++) {\n            texC = coords[1] + row;\n            depth = coords[2] + col;\n\n            vec2 uv = (vec2(texC, texR) + halfCR) /\n                       vec2(${width}.0, ${height}.0);\n            vec4 values = ${glsl.texture2D}(A, uv);\n            float value;\n            if (depth == 0) {\n              value = values.r;\n            } else if (depth == 1) {\n              value = values.g;\n            } else if (depth == 2) {\n              value = values.b;\n            } else if (depth == 3) {\n              value = values.a;\n            }\n\n            result[row * 2 + col] = floor(value * 255.0 + 0.5);\n          }\n        }\n\n        ${glsl.output} = result;\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FromPixels.js\nvar fromPixelsConfig = {\n  kernelName: FromPixels,\n  backendName: \"webgl\",\n  kernelFunc: fromPixels2\n};\nvar fromPixels2DContext2;\nfunction fromPixels2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  let { pixels } = inputs;\n  const { numChannels } = attrs;\n  const isVideo = typeof HTMLVideoElement !== \"undefined\" && pixels instanceof HTMLVideoElement;\n  const isImage = typeof HTMLImageElement !== \"undefined\" && pixels instanceof HTMLImageElement;\n  const [width, height] = isVideo ? [\n    pixels.videoWidth,\n    pixels.videoHeight\n  ] : [pixels.width, pixels.height];\n  const texShape = [height, width];\n  const outShape = [height, width, numChannels];\n  if (isImage || isVideo) {\n    if (fromPixels2DContext2 == null) {\n      fromPixels2DContext2 = document.createElement(\"canvas\").getContext(\"2d\");\n    }\n    fromPixels2DContext2.canvas.width = width;\n    fromPixels2DContext2.canvas.height = height;\n    fromPixels2DContext2.drawImage(pixels, 0, 0, width, height);\n    pixels = fromPixels2DContext2.canvas;\n  }\n  const tempPixelHandle = backend2.makeTensorInfo(texShape, \"int32\");\n  backend2.texData.get(tempPixelHandle.dataId).usage = TextureUsage.PIXELS;\n  backend2.gpgpu.uploadPixelDataToTexture(backend2.getTexture(tempPixelHandle.dataId), pixels);\n  const program = env().getBool(\"WEBGL_PACK\") ? new FromPixelsPackedProgram(outShape) : new FromPixelsProgram(outShape);\n  const res = backend2.runWebGLProgram(program, [tempPixelHandle], \"int32\");\n  backend2.disposeData(tempPixelHandle.dataId);\n  return res;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FusedConv2D.js\nfunction fusedConv2d(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode, false, $dataFormat);\n  let out;\n  const intermediates = [];\n  if (convInfo.filterHeight === 1 && convInfo.filterWidth === 1 && convInfo.dilationHeight === 1 && convInfo.dilationWidth === 1 && convInfo.strideHeight === 1 && convInfo.strideWidth === 1 && (convInfo.padInfo.type === \"SAME\" || convInfo.padInfo.type === \"VALID\")) {\n    out = conv2dByMatMul({\n      x,\n      filter,\n      convInfo,\n      backend: backend2,\n      bias,\n      activation: activation2,\n      preluActivationWeights,\n      leakyreluAlpha\n    });\n  } else if (env().getBool(\"WEBGL_CONV_IM2COL\")) {\n    out = conv2dWithIm2Row({\n      x,\n      filter,\n      convInfo,\n      backend: backend2,\n      bias,\n      activation: activation2,\n      preluActivationWeights,\n      leakyreluAlpha\n    });\n  } else {\n    const hasBias = bias != null;\n    const hasPreluActivationWeights = preluActivationWeights != null;\n    const hasLeakyreluAlpha = activation2 === \"leakyrelu\";\n    const fusedActivation = activation2 ? mapActivationToShaderProgram(activation2, false) : null;\n    const program = new Conv2DProgram(convInfo, hasBias, fusedActivation, hasPreluActivationWeights, hasLeakyreluAlpha);\n    const inputs2 = [x, filter];\n    const alignInputWithDataFormat = (input2, dataFormat2) => {\n      if (dataFormat2 === \"NCHW\" && input2.shape.length === 1 && input2.shape[0] !== 1) {\n        const alignedInput = reshape4({\n          inputs: { x: input2 },\n          backend: backend2,\n          attrs: { shape: [input2.shape[0], 1, 1] }\n        });\n        intermediates.push(alignedInput);\n        return alignedInput;\n      }\n      return input2;\n    };\n    if (hasBias) {\n      inputs2.push(alignInputWithDataFormat(bias, dataFormat));\n    }\n    if (hasPreluActivationWeights) {\n      inputs2.push(alignInputWithDataFormat(preluActivationWeights, dataFormat));\n    }\n    if (hasLeakyreluAlpha) {\n      const $leakyreluAlpha = backend2.makeTensorInfo([], \"float32\", util_exports.createScalarValue(leakyreluAlpha, \"float32\"));\n      inputs2.push($leakyreluAlpha);\n      intermediates.push($leakyreluAlpha);\n    }\n    out = backend2.runWebGLProgram(program, inputs2, \"float32\");\n  }\n  const outReshaped = reshape4({ inputs: { x: out }, backend: backend2, attrs: { shape: convInfo.outShape } });\n  intermediates.push(out);\n  intermediates.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return outReshaped;\n}\nvar fusedConv2DConfig2 = {\n  kernelName: FusedConv2D,\n  backendName: \"webgl\",\n  kernelFunc: fusedConv2d\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/FusedDepthwiseConv2D.js\nfunction fusedDepthwiseConv2D2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dilations, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  const intermediates = [];\n  let $dilations = dilations;\n  if ($dilations == null) {\n    $dilations = [1, 1];\n  }\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, $dilations), () => `Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${strides} and dilations '${$dilations}'`);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad3, dimRoundingMode, true);\n  const shouldPackDepthwiseConv = env().getBool(\"WEBGL_PACK_DEPTHWISECONV\") && convInfo.strideWidth <= 2 && convInfo.outChannels / convInfo.inChannels === 1;\n  const fusedActivation = activation2 ? mapActivationToShaderProgram(activation2, shouldPackDepthwiseConv) : null;\n  const programInputs = [x, filter];\n  const hasBias = bias != null;\n  const hasPreluActivationWeights = preluActivationWeights != null;\n  const hasLeakyreluAlpha = activation2 === \"leakyrelu\";\n  if (hasBias) {\n    programInputs.push(bias);\n  }\n  if (hasPreluActivationWeights) {\n    programInputs.push(preluActivationWeights);\n  }\n  if (hasLeakyreluAlpha) {\n    const $leakyreluAlpha = backend2.makeTensorInfo([], \"float32\", util_exports.createScalarValue(leakyreluAlpha, \"float32\"));\n    programInputs.push($leakyreluAlpha);\n    intermediates.push($leakyreluAlpha);\n  }\n  let program;\n  if (shouldPackDepthwiseConv) {\n    program = new DepthwiseConvPacked2DProgram(convInfo, hasBias, fusedActivation, hasPreluActivationWeights, hasLeakyreluAlpha);\n  } else {\n    program = new DepthwiseConv2DProgram(convInfo, hasBias, fusedActivation, hasPreluActivationWeights, hasLeakyreluAlpha);\n  }\n  const customValues = [\n    [convInfo.padInfo.top, convInfo.padInfo.left],\n    [convInfo.strideHeight, convInfo.strideWidth],\n    [convInfo.dilationHeight, convInfo.dilationWidth],\n    [convInfo.inHeight, convInfo.inWidth]\n  ];\n  const result = backend2.runWebGLProgram(program, programInputs, \"float32\", customValues);\n  intermediates.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return result;\n}\nvar fusedDepthwiseConv2DConfig2 = {\n  kernelName: FusedDepthwiseConv2D,\n  backendName: \"webgl\",\n  kernelFunc: fusedDepthwiseConv2D2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/gather_nd_gpu.js\nvar GatherNDProgram = class {\n  constructor(sliceDim, strides, shape, paramsShape) {\n    this.sliceDim = sliceDim;\n    this.strides = strides;\n    this.paramsShape = paramsShape;\n    this.variableNames = [\"x\", \"indices\"];\n    this.outputShape = shape;\n    const stridesType = getCoordsDataType(strides.length);\n    const dtype = getCoordsDataType(shape.length);\n    const strideString = this.sliceDim > 1 ? \"strides[j]\" : \"strides\";\n    const paramsShapeType = getCoordsDataType(paramsShape.length);\n    const paramsShapeString = paramsShape.length > 1 ? \"paramsShape[j]\" : \"paramsShape\";\n    this.userCode = `\n        ${stridesType} strides = ${stridesType}(${this.strides});\n        ${paramsShapeType} paramsShape = ${paramsShapeType}(${this.paramsShape});\n         void main() {\n          ${dtype} coords = getOutputCoords();\n          int flattenIndex = 0;\n          bool out_of_bounds = false;\n          for (int j = 0; j < ${this.sliceDim}; j++) {\n            int index = round(getIndices(coords[0], j));\n            out_of_bounds = out_of_bounds || index < 0;\n            out_of_bounds = out_of_bounds || index >= ${paramsShapeString};\n            flattenIndex += index * ${strideString};\n          }\n          setOutput(out_of_bounds ? 0.0 : getX(flattenIndex, coords[1]));\n        }\n      `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/GatherNd.js\nfunction gatherNd2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { params, indices } = inputs;\n  const indicesShape = indices.shape;\n  const sliceRank = indicesShape[indicesShape.length - 1];\n  const paramsSize = util_exports.sizeFromShape(params.shape);\n  const [resultShape, numSlices, sliceSize, strides] = backend_util_exports.prepareAndValidate(params, indices);\n  const flattenIndices = reshape4({ inputs: { x: indices }, backend: backend2, attrs: { shape: [numSlices, sliceRank] } });\n  const flattenX = reshape4({\n    inputs: { x: params },\n    backend: backend2,\n    attrs: { shape: [util_exports.sizeFromShape(params.shape) / sliceSize, sliceSize] }\n  });\n  if (backend2.shouldExecuteOnCPU([params, indices]) || params.dtype === \"string\") {\n    const indicesData = backend2.readSync(indices.dataId);\n    const paramsBuf = backend2.bufferSync(params);\n    const outValue = gatherNdImplCPU(indicesData, paramsBuf, params.dtype, numSlices, sliceRank, sliceSize, strides, params.shape, paramsSize);\n    return backend2.makeTensorInfo(resultShape, params.dtype, outValue.values);\n  }\n  const program = new GatherNDProgram(sliceRank, strides, [numSlices, sliceSize], params.shape);\n  const res = backend2.runWebGLProgram(program, [flattenX, flattenIndices], flattenX.dtype);\n  const reshaped = reshape4({ inputs: { x: res }, backend: backend2, attrs: { shape: resultShape } });\n  backend2.disposeIntermediateTensorInfo(flattenIndices);\n  backend2.disposeIntermediateTensorInfo(flattenX);\n  backend2.disposeIntermediateTensorInfo(res);\n  return reshaped;\n}\nvar gatherNdConfig2 = {\n  kernelName: GatherNd,\n  backendName: \"webgl\",\n  kernelFunc: gatherNd2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/gather_gpu.js\nvar GatherProgram = class {\n  constructor(aShape, outputShape) {\n    this.variableNames = [\"A\", \"indices\"];\n    this.outputShape = outputShape;\n    this.rank = outputShape.length;\n    const dtype = getCoordsDataType(this.rank);\n    const sourceCoords = getSourceCoords2(aShape, 2);\n    this.userCode = `\n      void main() {\n        ${dtype} resRC = getOutputCoords();\n        int index = int(getIndices(resRC.x, resRC.z));\n        float inBounds = (index >= 0) && (index < ${aShape[2]}) ? 1.0 : 0.0;\n        setOutput(inBounds * getA(${sourceCoords}));\n      }\n    `;\n  }\n};\nfunction getSourceCoords2(aShape, axis) {\n  const currentCoords = [\"resRC.x\", \"resRC.y\", \"resRC.z\", \"resRC.w\"];\n  const sourceCoords = [];\n  for (let i2 = 0; i2 < aShape.length; i2++) {\n    if (i2 === 2) {\n      sourceCoords.push(\"index\");\n    } else {\n      sourceCoords.push(`${currentCoords[i2]}`);\n    }\n  }\n  return sourceCoords.join();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/GatherV2.js\nfunction gatherV22(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, indices } = inputs;\n  const { axis, batchDims } = attrs;\n  const parsedAxis = util_exports.parseAxisParam(axis, x.shape)[0];\n  if (env().get(\"DEBUG\")) {\n    const indicesVals = backend2.readSync(indices.dataId);\n    const axisDim = x.shape[parsedAxis];\n    for (let i2 = 0; i2 < indicesVals.length; ++i2) {\n      const index = indicesVals[i2];\n      util_exports.assert(index <= axisDim - 1 && index >= 0, () => `GatherV2: the index value ${index} is not in [0, ${axisDim - 1}]`);\n    }\n  }\n  const shapeInfo = backend_util_exports.segment_util.collectGatherOpShapeInfo(x, indices, parsedAxis, batchDims);\n  const indicesSize = util_exports.sizeFromShape(indices.shape);\n  const toDispose = [];\n  const flattenX = reshape4({\n    inputs: { x },\n    backend: backend2,\n    attrs: {\n      shape: [\n        shapeInfo.batchSize,\n        shapeInfo.outerSize,\n        shapeInfo.dimSize,\n        shapeInfo.sliceSize\n      ]\n    }\n  });\n  const flattenIndex = reshape4({\n    inputs: { x: indices },\n    backend: backend2,\n    attrs: { shape: [shapeInfo.batchSize, indicesSize / shapeInfo.batchSize] }\n  });\n  toDispose.push(flattenX);\n  toDispose.push(flattenIndex);\n  const flattenOutputShape = [\n    shapeInfo.batchSize,\n    shapeInfo.outerSize,\n    indicesSize / shapeInfo.batchSize,\n    shapeInfo.sliceSize\n  ];\n  if (backend2.shouldExecuteOnCPU([x, indices]) || x.dtype === \"string\") {\n    const indicesBuf = backend2.bufferSync(flattenIndex);\n    const xBuf = backend2.bufferSync(flattenX);\n    const outBuf = gatherV2ImplCPU(xBuf, indicesBuf, flattenOutputShape);\n    toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n    return backend2.makeTensorInfo(shapeInfo.outputShape, outBuf.dtype, outBuf.values);\n  }\n  const program = new GatherProgram(flattenX.shape, flattenOutputShape);\n  const res = backend2.runWebGLProgram(program, [flattenX, flattenIndex], flattenX.dtype);\n  toDispose.push(res);\n  const reshaped = reshape4({ inputs: { x: res }, backend: backend2, attrs: { shape: shapeInfo.outputShape } });\n  toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return reshaped;\n}\nvar gatherV2Config2 = {\n  kernelName: GatherV2,\n  backendName: \"webgl\",\n  kernelFunc: gatherV22\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Greater.js\nvar GREATER = `return float(a > b);`;\nvar GREATER_PACKED = `\n  return vec4(greaterThan(a, b));\n`;\nvar greater4 = binaryKernelFunc2({\n  opSnippet: GREATER,\n  packedOpSnippet: GREATER_PACKED,\n  cpuKernelImpl: greaterImplCPU,\n  dtype: \"bool\"\n});\nvar greaterConfig2 = {\n  kernelName: Greater,\n  backendName: \"webgl\",\n  kernelFunc: greater4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/GreaterEqual.js\nvar GREATER_EQUAL = `return float(a >= b);`;\nvar GREATER_EQUAL_PACKED = `\n  return vec4(greaterThanEqual(a, b));\n`;\nvar greaterEqual3 = binaryKernelFunc2({\n  opSnippet: GREATER_EQUAL,\n  packedOpSnippet: GREATER_EQUAL_PACKED,\n  dtype: \"bool\",\n  cpuKernelImpl: greaterEqualImplCPU\n});\nvar greaterEqualConfig2 = {\n  kernelName: GreaterEqual,\n  backendName: \"webgl\",\n  kernelFunc: greaterEqual3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/IFFT.js\nfunction ifft3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  return fftImpl2(input2, true, backend2);\n}\nvar ifftConfig2 = {\n  kernelName: IFFT,\n  backendName: \"webgl\",\n  kernelFunc: ifft3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/IsFinite.js\nvar IS_FINITE = `return float(!isnan(x) && !isinf(x));`;\nvar isFinite4 = unaryKernelFunc2({ opSnippet: IS_FINITE, dtype: \"bool\" });\nvar isFiniteConfig2 = {\n  kernelName: IsFinite,\n  backendName: \"webgl\",\n  kernelFunc: isFinite4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/IsInf.js\nvar IS_INF = `return float(isinf(x));`;\nvar isInf3 = unaryKernelFunc2({ opSnippet: IS_INF, dtype: \"bool\" });\nvar isInfConfig2 = {\n  kernelName: IsInf,\n  backendName: \"webgl\",\n  kernelFunc: isInf3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/IsNaN.js\nvar IS_NAN = `return float(isnan(x));`;\nvar isNaN4 = unaryKernelFunc2({ opSnippet: IS_NAN, dtype: \"bool\" });\nvar isNaNConfig2 = {\n  kernelName: IsNan,\n  backendName: \"webgl\",\n  kernelFunc: isNaN4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Less.js\nvar LESS = `return float(a < b);`;\nvar LESS_PACKED = `\n  return vec4(lessThan(a, b));\n`;\nvar less4 = binaryKernelFunc2({\n  opSnippet: LESS,\n  packedOpSnippet: LESS_PACKED,\n  cpuKernelImpl: lessImplCPU,\n  dtype: \"bool\"\n});\nvar lessConfig2 = {\n  kernelName: Less,\n  backendName: \"webgl\",\n  kernelFunc: less4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LessEqual.js\nvar LESS_EQUAL = `return float(a <= b);`;\nvar LESS_EQUAL_PACKED = `\n  return vec4(lessThanEqual(a, b));\n`;\nvar lessEqual3 = binaryKernelFunc2({\n  opSnippet: LESS_EQUAL,\n  packedOpSnippet: LESS_EQUAL_PACKED,\n  cpuKernelImpl: lessEqualImplCPU,\n  dtype: \"bool\"\n});\nvar lessEqualConfig2 = {\n  kernelName: LessEqual,\n  backendName: \"webgl\",\n  kernelFunc: lessEqual3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LinSpace.js\nfunction linSpace2(args) {\n  const { backend: backend2, attrs } = args;\n  const { start, stop, num } = attrs;\n  const outVals = linSpaceImplCPU(start, stop, num);\n  return backend2.makeTensorInfo([outVals.length], \"float32\", outVals);\n}\nvar linSpaceConfig2 = {\n  kernelName: LinSpace,\n  backendName: \"webgl\",\n  kernelFunc: linSpace2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Log.js\nvar LOG = CHECK_NAN_SNIPPET_UNARY + `\n  return x < 0.0 ? 0./0. : log(x);\n`;\nvar LOG_PACKED = `\n  vec4 result = log(x);\n  bvec4 isNaN = isnan(x);\n  result.r = isNaN.r ? x.r : (x.r < 0.0 ? 0./0. : result.r);\n  result.g = isNaN.g ? x.g : (x.g < 0.0 ? 0./0. : result.g);\n  result.b = isNaN.b ? x.b : (x.b < 0.0 ? 0./0. : result.b);\n  result.a = isNaN.a ? x.a : (x.a < 0.0 ? 0./0. : result.a);\n  return result;\n`;\nvar log4 = unaryKernelFunc2({ opSnippet: LOG, packedOpSnippet: LOG_PACKED, cpuKernelImpl: logImplCPU });\nvar logConfig2 = {\n  kernelName: Log,\n  backendName: \"webgl\",\n  kernelFunc: log4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Log1p.js\nvar LOG1P = CHECK_NAN_SNIPPET_UNARY + `\n  return log(1.0 + x);\n`;\nvar log1p3 = unaryKernelFunc2({ opSnippet: LOG1P });\nvar log1pConfig2 = {\n  kernelName: Log1p,\n  backendName: \"webgl\",\n  kernelFunc: log1p3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LogicalAnd.js\nvar LOGICAL_AND = `return float(a >= 1.0 && b >= 1.0);`;\nvar LOGICAL_AND_PACKED = `\n  return vec4(\n    vec4(greaterThanEqual(a, vec4(1.0))) *\n    vec4(greaterThanEqual(b, vec4(1.0))));\n`;\nvar logicalAnd3 = binaryKernelFunc2({\n  opSnippet: LOGICAL_AND,\n  packedOpSnippet: LOGICAL_AND_PACKED,\n  dtype: \"bool\"\n});\nvar logicalAndConfig2 = {\n  kernelName: LogicalAnd,\n  backendName: \"webgl\",\n  kernelFunc: logicalAnd3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LogicalNot.js\nvar LOGICAL_NOT = `return float(!(x >= 1.0));`;\nvar logicalNot3 = unaryKernelFunc2({ opSnippet: LOGICAL_NOT });\nvar logicalNotConfig2 = {\n  kernelName: LogicalNot,\n  backendName: \"webgl\",\n  kernelFunc: logicalNot3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LogicalOr.js\nvar LOGICAL_OR = `return float(a >= 1.0 || b >= 1.0);`;\nvar LOGICAL_OR_PACKED = `\n  return min(\n    vec4(greaterThanEqual(a, vec4(1.0))) +\n    vec4(greaterThanEqual(b, vec4(1.0))),\n    vec4(1.0));\n`;\nvar logicalOr3 = binaryKernelFunc2({ opSnippet: LOGICAL_OR, packedOpSnippet: LOGICAL_OR_PACKED, dtype: \"bool\" });\nvar logicalOrConfig2 = {\n  kernelName: LogicalOr,\n  backendName: \"webgl\",\n  kernelFunc: logicalOr3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/lrn_gpu.js\nvar LRNProgram = class {\n  constructor(xShape, radius, bias, alpha, beta) {\n    this.variableNames = [\"x\"];\n    this.outputShape = [];\n    const rad = radius;\n    const maxD = xShape[3] - 1;\n    this.outputShape = xShape;\n    let powOperator;\n    const basis = `float(${bias}) + float(${alpha}) * sum`;\n    if (beta === 0.5) {\n      powOperator = `inversesqrt(${basis})`;\n    } else if (beta === 1) {\n      powOperator = `1.0/(${basis})`;\n    } else {\n      powOperator = `exp(log(${basis}) * float(-${beta}));`;\n    }\n    this.userCode = `\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n        int d = coords[3];\n        float x = getX(b, r, c, d);\n        float sum = 0.0;\n        for (int j = -${rad}; j <= ${rad}; j++) {\n          int idx = d + j;\n          if (idx >= 0 && idx <=  ${maxD}) {\n            float z = getX(b, r, c, idx);\n            sum += z * z;\n          }\n        }\n        float val = x * ${powOperator};\n        setOutput(val);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/lrn_packed_gpu.js\nvar LRNPackedProgram = class {\n  constructor(xShape, radius, bias, alpha, beta) {\n    this.variableNames = [\"x\"];\n    this.outputShape = [];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    const rad = radius;\n    const maxD = xShape[3] - 1;\n    this.outputShape = xShape;\n    let powOperator;\n    const basis = `float(${bias}) + float(${alpha}) * sum`;\n    if (beta === 0.5) {\n      powOperator = `inversesqrt(${basis})`;\n    } else if (beta === 1) {\n      powOperator = `1.0/(${basis})`;\n    } else {\n      powOperator = `exp(log(${basis}) * float(-${beta}));`;\n    }\n    this.userCode = `\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords.x;\n        int r = coords.y;\n        int c = coords.z;\n        int d = coords.w;\n\n        bool hasNextCol = d < ${this.outputShape[3]};\n        bool hasNextRow = c < ${this.outputShape[2]};\n\n        vec4 sum = vec4(0.);\n        vec4 xFragAtOutputCoords = getX(b, r, c, d);\n\n        vec4 xAtOutputCoords = vec4(\n          getChannel(xFragAtOutputCoords, vec2(c, d)),\n          hasNextCol ?\n            getChannel(xFragAtOutputCoords, vec2(c, d + 1)) : 0.0,\n          hasNextRow ?\n            getChannel(xFragAtOutputCoords , vec2(c + 1, d)) : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getChannel(xFragAtOutputCoords, vec2(c + 1, d + 1)) : 0.0\n        );\n\n        int firstChannel = d - ${rad};\n        vec2 cache = vec2(0.);\n        if(firstChannel >= 0){\n          vec4 firstChannelFrag = getX(b, r, c, firstChannel);\n          cache.x = getChannel(firstChannelFrag, vec2(c, firstChannel));\n            if(hasNextRow){\n              cache.y = getChannel(firstChannelFrag, vec2(c + 1, firstChannel));\n            }\n        }\n\n        ivec2 depth = ivec2(d, d + 1);\n        for (int j = - ${rad}; j <= ${rad}; j++) {\n          ivec2 idx = depth + j;\n          bvec2 aboveLowerBound = greaterThanEqual(idx, ivec2(0));\n          bvec2 belowUpperBound = lessThanEqual(idx, ivec2(${maxD}));\n\n          bool depthInRange = aboveLowerBound.x && belowUpperBound.x;\n          bool depthPlusOneInRange = aboveLowerBound.y && belowUpperBound.y;\n\n          if(depthInRange || depthPlusOneInRange){\n            vec4 z = vec4(0.);\n            vec4 xFragAtCurrentDepth;\n            z.xz = cache.xy;\n            if(depthPlusOneInRange && hasNextCol){\n              xFragAtCurrentDepth = idx.y != d ?\n                getX(b, r, c, idx.y) : xFragAtOutputCoords;\n              z.y = getChannel(xFragAtCurrentDepth, vec2(c, idx.y));\n              if(hasNextRow){\n                z.w = getChannel(xFragAtCurrentDepth, vec2(c + 1, idx.y));\n              }\n            }\n            cache.xy = z.yw;\n            sum += z * z;\n          }\n        }\n        vec4 result = xAtOutputCoords * ${powOperator};\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LRN.js\nvar lrn = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { depthRadius, bias, alpha, beta } = attrs;\n  const program = env().getBool(\"WEBGL_PACK_NORMALIZATION\") ? new LRNPackedProgram(x.shape, depthRadius, bias, alpha, beta) : new LRNProgram(x.shape, depthRadius, bias, alpha, beta);\n  return backend2.runWebGLProgram(program, [x], x.dtype);\n};\nvar LRNConfig2 = {\n  kernelName: LRN,\n  backendName: \"webgl\",\n  kernelFunc: lrn\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/lrn_grad_gpu.js\nvar LRNGradProgram = class {\n  constructor(inputShape, depthRadius, bias, alpha, beta) {\n    this.variableNames = [\"inputImage\", \"outputImage\", \"dy\"];\n    this.outputShape = [];\n    this.outputShape = inputShape;\n    this.depth = inputShape[3];\n    this.depthRadius = depthRadius;\n    this.bias = bias;\n    this.alpha = alpha;\n    this.beta = beta;\n    this.userCode = `\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int r = coords[1];\n        int c = coords[2];\n\n        float result = 0.0;\n        for (int d = 0; d < ${this.depth}; ++d) {\n          int depthBegin = int(max(0.0, float(d - ${depthRadius})));\n          int depthEnd = int(min(float(${this.depth}),\n              float(d + ${depthRadius} + 1)));\n\n          const int MIN_DEPTH_BEGIN = 0;\n          const int MAX_DEPTH_END = ${this.depth};\n\n          float norm = 0.0;\n          for (int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k) {\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd) {\n              norm += getInputImage(b, r, c, k) * getInputImage(b, r, c, k);\n            }\n            else {\n              break;\n            }\n          }\n\n          norm = float(${alpha}) * norm + float(${bias});\n\n          for(int k = MIN_DEPTH_BEGIN; k < MAX_DEPTH_END; ++k){\n            if (k < depthBegin){\n              continue;\n            }\n            else if (k >= depthBegin && k < depthEnd){\n              float dyi = -2.0 * float(${alpha})\n                * float(${beta})\n                * getInputImage(b ,r ,c, k) * getOutputImage(b, r, c, d)\n                / norm;\n              if (k == d) {\n                dyi += pow(norm, -1.0 * ${beta});\n              }\n              if (k == coords[3]) {\n                dyi *= getDy(b, r, c, d);\n                result += dyi;\n              }\n            }\n            else {\n              break;\n            }\n          }\n      }\n      setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/LRNGrad.js\nvar lrnGrad = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, y, dy } = inputs;\n  const { depthRadius, bias, alpha, beta } = attrs;\n  const program = new LRNGradProgram(x.shape, depthRadius, bias, alpha, beta);\n  return backend2.runWebGLProgram(program, [x, y, dy], x.dtype);\n};\nvar LRNGradConfig2 = {\n  kernelName: LRNGrad,\n  backendName: \"webgl\",\n  kernelFunc: lrnGrad\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Max_impl.js\nfunction maxImpl2(x, reduceShape, outShape, backend2) {\n  const inSize = util_exports.sizeFromShape(reduceShape);\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const batchSize = xSize / inSize;\n  const reshapedInput = reshape4({ inputs: { x }, attrs: { shape: [batchSize, inSize] }, backend: backend2 });\n  const reduced = reduce(reshapedInput, x.dtype, \"max\", backend2);\n  const reshapedOutput = reshape4({ inputs: { x: reduced }, attrs: { shape: outShape }, backend: backend2 });\n  backend2.disposeIntermediateTensorInfo(reshapedInput);\n  backend2.disposeIntermediateTensorInfo(reduced);\n  return reshapedOutput;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Max.js\nfunction max4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { reductionIndices, keepDims } = attrs;\n  const xRank = x.shape.length;\n  const origAxes = util_exports.parseAxisParam(reductionIndices, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  const maxInputIsTransposed = permutedAxes != null;\n  const shouldExecuteOnCPU = backend2.shouldExecuteOnCPU([x]);\n  let maxInput = x;\n  if (maxInputIsTransposed) {\n    if (shouldExecuteOnCPU) {\n      const xTexData = backend2.texData.get(maxInput.dataId);\n      const values = xTexData.values;\n      const newShape = new Array(xRank);\n      for (let i2 = 0; i2 < newShape.length; i2++) {\n        newShape[i2] = x.shape[permutedAxes[i2]];\n      }\n      const maxInputValues = transposeImplCPU(values, x.shape, x.dtype, permutedAxes, newShape);\n      maxInput = backend2.makeTensorInfo(newShape, x.dtype);\n      const maxInputData = backend2.texData.get(maxInput.dataId);\n      maxInputData.values = maxInputValues;\n    } else {\n      maxInput = transposeImpl2(x, permutedAxes, backend2);\n    }\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"max\", axes, xRank);\n  const [maxOutShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(maxInput.shape, axes);\n  let outShape = maxOutShape;\n  if (keepDims) {\n    outShape = backend_util_exports.expandShapeToKeepDim(maxOutShape, origAxes);\n  }\n  let out;\n  if (shouldExecuteOnCPU) {\n    const xTexData = backend2.texData.get(maxInput.dataId);\n    const values = xTexData.values;\n    const outValues = maxImplCPU(values, util_exports.sizeFromShape(reduceShape), outShape, x.dtype);\n    out = backend2.makeTensorInfo(outShape, x.dtype);\n    const outData = backend2.texData.get(out.dataId);\n    outData.values = outValues;\n  } else {\n    out = maxImpl2(maxInput, reduceShape, outShape, backend2);\n  }\n  if (maxInputIsTransposed) {\n    backend2.disposeIntermediateTensorInfo(maxInput);\n  }\n  return out;\n}\nvar maxConfig2 = {\n  kernelName: Max,\n  backendName: \"webgl\",\n  kernelFunc: max4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Maximum.js\nvar MAXIMUM = CHECK_NAN_SNIPPET2 + `\n  return max(a, b);\n`;\nvar MAXIMUM_PACKED = `\n  vec4 result = vec4(max(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  ` + CHECK_NAN_SNIPPET3 + `\n  return result;\n`;\nvar maximum4 = binaryKernelFunc2({\n  opSnippet: MAXIMUM,\n  packedOpSnippet: MAXIMUM_PACKED,\n  cpuKernelImpl: maximumImplCPU\n});\nvar maximumConfig2 = {\n  kernelName: Maximum,\n  backendName: \"webgl\",\n  kernelFunc: maximum4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPool.js\nfunction maxPool3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  assertNotComplex2(x, \"maxPool\");\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = 1;\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in maxPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  if (convInfo.filterWidth === 1 && convInfo.filterHeight === 1 && util_exports.arraysEqual(convInfo.inShape, convInfo.outShape)) {\n    return identity3({ inputs: { x }, backend: backend2 });\n  }\n  const maxPoolProgram = new Pool2DProgram(convInfo, \"max\", false);\n  return backend2.runWebGLProgram(maxPoolProgram, [x], x.dtype);\n}\nvar maxPoolConfig2 = {\n  kernelName: MaxPool,\n  backendName: \"webgl\",\n  kernelFunc: maxPool3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPool3D.js\nfunction maxPool3d2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { filterSize, strides, pad: pad3, dataFormat, dimRoundingMode } = attrs;\n  const dilations = [1, 1, 1];\n  const convInfo = backend_util_exports.computePool3DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode, dataFormat);\n  const maxPoolProgram = new Pool3DProgram(convInfo, \"max\", false);\n  return backend2.runWebGLProgram(maxPoolProgram, [x], x.dtype);\n}\nvar maxPool3DConfig2 = {\n  kernelName: MaxPool3D,\n  backendName: \"webgl\",\n  kernelFunc: maxPool3d2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/max_pool_backprop_gpu.js\nvar MaxPool2DBackpropProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\", \"maxPos\"];\n    this.outputShape = convInfo.inShape;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationHeight = convInfo.dilationHeight;\n    const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n    const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n    const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n    const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n    const lastIndex = effectiveFilterHeight * effectiveFilterWidth - 1;\n    this.userCode = `\n      const ivec2 pads = ivec2(${padTop}, ${padLeft});\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n\n        ivec2 dyRCCorner = coords.yz - pads;\n        int dyRCorner = dyRCCorner.x;\n        int dyCCorner = dyRCCorner.y;\n\n        // Convolve dy(?, ?, d) with pos mask(:, :, d) to get dx(xR, xC, d).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n        for (int wR = 0; wR < ${effectiveFilterHeight};\n          wR += ${dilationHeight}) {\n          float dyR = float(dyRCorner + wR) / ${strideHeight}.0;\n\n          if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 || fract(dyR) > 0.0) {\n            continue;\n          }\n          int idyR = int(dyR);\n\n          for (int wC = 0; wC < ${effectiveFilterWidth}; wC++) {\n            float dyC = float(dyCCorner + wC) / ${strideWidth}.0;\n\n            if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||\n                fract(dyC) > 0.0) {\n              continue;\n            }\n            int idyC = int(dyC);\n\n            float dyValue = getDy(b, idyR, idyC, d);\n            int maxPosValue = ${lastIndex} - int(getMaxPos(b, idyR, idyC, d));\n\n            // Get the current value, check it against the value from the\n            // position matrix.\n            int curPosValue = wR * ${effectiveFilterWidth} + wC;\n            float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n            dotProd += dyValue * mask;\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\nvar MaxPool3DBackpropProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\", \"maxPos\"];\n    this.outputShape = convInfo.inShape;\n    const strideDepth = convInfo.strideDepth;\n    const strideHeight = convInfo.strideHeight;\n    const strideWidth = convInfo.strideWidth;\n    const dilationDepth = convInfo.dilationDepth;\n    const dilationHeight = convInfo.dilationHeight;\n    const dilationWidth = convInfo.dilationWidth;\n    const effectiveFilterDepth = convInfo.effectiveFilterDepth;\n    const effectiveFilterHeight = convInfo.effectiveFilterHeight;\n    const effectiveFilterWidth = convInfo.effectiveFilterWidth;\n    const padFront = effectiveFilterDepth - 1 - convInfo.padInfo.front;\n    const padTop = effectiveFilterHeight - 1 - convInfo.padInfo.top;\n    const padLeft = effectiveFilterWidth - 1 - convInfo.padInfo.left;\n    const lastIndex = effectiveFilterDepth * effectiveFilterHeight * effectiveFilterWidth - 1;\n    this.userCode = `\n      const ivec3 pads = ivec3(${padFront}, ${padTop}, ${padLeft});\n\n      void main() {\n        ivec5 coords = getOutputCoords();\n        int batch = coords.x;\n        int ch = coords.u;\n\n        ivec3 dyCorner = ivec3(coords.y, coords.z, coords.w) - pads;\n        int dyDCorner = dyCorner.x;\n        int dyRCorner = dyCorner.y;\n        int dyCCorner = dyCorner.z;\n\n        // Convolve dy(?, ?, ?, ch) with pos mask(:, :, :, d) to get\n        // dx(xD, xR, xC, ch).\n        // ? = to be determined. : = across all values in that axis.\n        float dotProd = 0.0;\n\n        for (int wD = 0; wD < ${effectiveFilterDepth};\n           wD += ${dilationDepth}) {\n          float dyD = float(dyDCorner + wD) / ${strideDepth}.0;\n\n          if (dyD < 0.0 || dyD >= ${convInfo.outDepth}.0 || fract(dyD) > 0.0) {\n            continue;\n          }\n          int idyD = int(dyD);\n\n          for (int wR = 0; wR < ${effectiveFilterHeight};\n              wR += ${dilationHeight}) {\n            float dyR = float(dyRCorner + wR) / ${strideHeight}.0;\n\n            if (dyR < 0.0 || dyR >= ${convInfo.outHeight}.0 ||\n                fract(dyR) > 0.0) {\n              continue;\n            }\n            int idyR = int(dyR);\n\n            for (int wC = 0; wC < ${effectiveFilterWidth};\n                wC += ${dilationWidth}) {\n              float dyC = float(dyCCorner + wC) / ${strideWidth}.0;\n\n              if (dyC < 0.0 || dyC >= ${convInfo.outWidth}.0 ||\n                  fract(dyC) > 0.0) {\n                continue;\n              }\n              int idyC = int(dyC);\n\n              float dyValue = getDy(batch, idyD, idyR, idyC, ch);\n              int maxPosValue = ${lastIndex} -\n                  int(getMaxPos(batch, idyD, idyR, idyC, ch));\n\n              // Get the current value, check it against the value from the\n              // position matrix.\n              int curPosValue =\n                  wD * ${effectiveFilterHeight} * ${effectiveFilterWidth} +\n                  wR * ${effectiveFilterWidth} + wC;\n              float mask = float(maxPosValue == curPosValue ? 1.0 : 0.0);\n\n              dotProd += dyValue * mask;\n            }\n          }\n        }\n        setOutput(dotProd);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPool3DGrad.js\nfunction maxPool3DGrad2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2 } = inputs;\n  const x = input2;\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = [1, 1, 1];\n  const convInfo = backend_util_exports.computePool3DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  const maxPool3dPositionsProgram = new Pool3DProgram(convInfo, \"max\", true);\n  const maxPool3dPositions2 = backend2.runWebGLProgram(maxPool3dPositionsProgram, [x], x.dtype);\n  const maxPoolBackpropProgram = new MaxPool3DBackpropProgram(convInfo);\n  const result = backend2.runWebGLProgram(maxPoolBackpropProgram, [dy, maxPool3dPositions2], x.dtype);\n  backend2.disposeIntermediateTensorInfo(maxPool3dPositions2);\n  return result;\n}\nvar maxPool3DGradConfig3 = {\n  kernelName: MaxPool3DGrad,\n  backendName: \"webgl\",\n  kernelFunc: maxPool3DGrad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPoolGrad.js\nfunction maxPoolGrad3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, input: input2, output } = inputs;\n  const x = input2;\n  assertNotComplex2([input2, output], \"maxPoolGrad\");\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, 1, pad3, dimRoundingMode);\n  const getPositions = true;\n  const maxPoolPositionsProgram = new Pool2DProgram(convInfo, \"max\", getPositions);\n  const maxPoolPositions2 = backend2.runWebGLProgram(maxPoolPositionsProgram, [x], x.dtype);\n  const maxPoolBackPropProgram = new MaxPool2DBackpropProgram(convInfo);\n  const result = backend2.runWebGLProgram(maxPoolBackPropProgram, [dy, maxPoolPositions2], x.dtype);\n  backend2.disposeIntermediateTensorInfo(maxPoolPositions2);\n  return result;\n}\nvar maxPoolGradConfig3 = {\n  kernelName: MaxPoolGrad,\n  backendName: \"webgl\",\n  kernelFunc: maxPoolGrad3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPoolWithArgmax_impl.js\nfunction maxPoolWithArgmaxImpl2(x, includeBatchInIndex, convInfo, backend2) {\n  let program = new Pool2DProgram(convInfo, \"max\", false);\n  const poolOutput = backend2.runWebGLProgram(program, [x], \"float32\");\n  program = new Pool2DProgram(convInfo, \"max\", true, true, includeBatchInIndex);\n  const indexOutput = backend2.runWebGLProgram(program, [x], \"float32\");\n  return [poolOutput, indexOutput];\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MaxPoolWithArgmax.js\nvar maxPoolWithArgmaxConfig2 = {\n  kernelName: MaxPoolWithArgmax,\n  backendName: \"webgl\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { x } = inputs;\n    const { filterSize, strides, pad: pad3, includeBatchInIndex } = attrs;\n    const webglBackend = backend2;\n    util_exports.assert(x.shape.length === 4, () => `Error in maxPool: input must be rank 4 but got rank ${x.shape.length}.`);\n    const dilations = [1, 1];\n    util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, dilations), () => `Error in maxPool: Either strides or dilations must be 1. Got strides ${strides} and dilations '${dilations}'`);\n    const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, dilations, pad3);\n    const [result, indexes] = maxPoolWithArgmaxImpl2(x, includeBatchInIndex, convInfo, webglBackend);\n    return [result, indexes];\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Mean_impl.js\nfunction meanImpl(x, reduceShape, outShape, backend2) {\n  const inSize = util_exports.sizeFromShape(reduceShape);\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const batchSize = xSize / inSize;\n  const reshapedInput = reshape4({ inputs: { x }, attrs: { shape: [batchSize, inSize] }, backend: backend2 });\n  const reduced = reduce(reshapedInput, \"float32\", \"mean\", backend2);\n  const reshapedOutput = reshape4({ inputs: { x: reduced }, attrs: { shape: outShape }, backend: backend2 });\n  backend2.disposeIntermediateTensorInfo(reshapedInput);\n  backend2.disposeIntermediateTensorInfo(reduced);\n  return reshapedOutput;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Mean.js\nvar meanConfig2 = {\n  kernelName: Mean,\n  backendName: \"webgl\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { x } = inputs;\n    const { keepDims, axis } = attrs;\n    const webglBackend = backend2;\n    const xRank = x.shape.length;\n    const origAxes = util_exports.parseAxisParam(axis, x.shape);\n    let axes = origAxes;\n    const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n    const meanInputIsTransposed = permutedAxes != null;\n    const shouldExecuteOnCPU = webglBackend.shouldExecuteOnCPU([x]);\n    const intermediates = [];\n    let meanInput = x;\n    if (meanInputIsTransposed) {\n      if (shouldExecuteOnCPU) {\n        const xTexData = webglBackend.texData.get(meanInput.dataId);\n        const values = xTexData.values;\n        const newShape = new Array(xRank);\n        for (let i2 = 0; i2 < newShape.length; i2++) {\n          newShape[i2] = x.shape[permutedAxes[i2]];\n        }\n        const meanInputValues = transposeImplCPU(values, x.shape, x.dtype, permutedAxes, newShape);\n        meanInput = webglBackend.makeTensorInfo(newShape, x.dtype);\n        const meanInputData = webglBackend.texData.get(meanInput.dataId);\n        meanInputData.values = meanInputValues;\n      } else {\n        meanInput = transposeImpl2(x, permutedAxes, webglBackend);\n      }\n      intermediates.push(meanInput);\n      axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n    }\n    backend_util_exports.assertAxesAreInnerMostDims(\"sum\", axes, xRank);\n    const [meanOutShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(meanInput.shape, axes);\n    let outShape = meanOutShape;\n    if (keepDims) {\n      outShape = backend_util_exports.expandShapeToKeepDim(meanOutShape, origAxes);\n    }\n    const out = meanImpl(meanInput, reduceShape, outShape, webglBackend);\n    for (const i2 of intermediates) {\n      webglBackend.disposeIntermediateTensorInfo(i2);\n    }\n    return out;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Min.js\nfunction min4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  const xRank = x.shape.length;\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  let permutedX = x;\n  if (permutedAxes != null) {\n    permutedX = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"min\", axes, xRank);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(permutedX.shape, axes);\n  const inSize = util_exports.sizeFromShape(reduceShape);\n  const a2D = reshape4({ inputs: { x: permutedX }, backend: backend2, attrs: { shape: [-1, inSize] } });\n  const reduced = reduce(a2D, a2D.dtype, \"min\", backend2);\n  let res;\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(outShape, origAxes);\n    res = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: newShape } });\n  } else {\n    res = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: outShape } });\n  }\n  backend2.disposeIntermediateTensorInfo(a2D);\n  backend2.disposeIntermediateTensorInfo(reduced);\n  if (permutedAxes != null) {\n    backend2.disposeIntermediateTensorInfo(permutedX);\n  }\n  return res;\n}\nvar minConfig2 = {\n  kernelName: Min,\n  backendName: \"webgl\",\n  kernelFunc: min4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Minimum.js\nvar MINIMUM = CHECK_NAN_SNIPPET2 + `\n  return min(a, b);\n`;\nvar MINIMUM_PACKED = `\n  vec4 result = vec4(min(a, b));\n  vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));\n  ` + CHECK_NAN_SNIPPET3 + `\n  return result;\n`;\nvar minimum4 = binaryKernelFunc2({\n  opSnippet: MINIMUM,\n  packedOpSnippet: MINIMUM_PACKED,\n  cpuKernelImpl: minimumImplCPU\n});\nvar minimumConfig2 = {\n  kernelName: Minimum,\n  backendName: \"webgl\",\n  kernelFunc: minimum4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/mirror_pad_gpu.js\nvar MirrorPadProgram = class {\n  constructor(xShape, paddings, mode) {\n    this.variableNames = [\"x\"];\n    this.outputShape = paddings.map((p2, i2) => p2[0] + xShape[i2] + p2[1]);\n    const rank = xShape.length;\n    const dtype = getCoordsDataType(rank);\n    const start = paddings.map((p2) => p2[0]).join(\",\");\n    const end = paddings.map((p2, i2) => p2[0] + xShape[i2]).join(\",\");\n    const unpackedCoords = [\"coords[0]\", \"coords[1]\", \"coords[2]\", \"coords[3]\"].slice(0, rank);\n    const offset = mode === \"reflect\" ? 0 : 1;\n    if (rank === 1) {\n      this.userCode = `\n        int start = ${start};\n        int end = ${end};\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start) {\n            outC = start * 2 - outC - ${offset};\n          } else if(outC >= end) {\n            outC = (end - 1) * 2 - outC + ${offset};\n          }\n          setOutput(getX(outC - start));\n        }\n      `;\n      return;\n    }\n    this.userCode = `\n      ${dtype} start = ${dtype}(${start});\n      ${dtype} end = ${dtype}(${end});\n\n      void main() {\n        ${dtype} outC = getOutputCoords();\n        for (int i = 0; i < ${rank}; i++) {\n          if (outC[i] < start[i]) {\n            outC[i] = start[i] * 2 - outC[i] - ${offset};\n          } else if(outC[i] >= end[i]) {\n            outC[i] = (end[i] - 1) * 2 - outC[i] + ${offset};\n          }\n        }\n        ${dtype} coords = outC - start;\n        setOutput(getX(${unpackedCoords}));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/mirror_pad_packed_gpu.js\nvar MirrorPadPackedProgram = class {\n  constructor(xShape, paddings, mode) {\n    this.variableNames = [\"x\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = paddings.map((p2, i2) => p2[0] + xShape[i2] + p2[1]);\n    const rank = xShape.length;\n    const dtype = getCoordsDataType(rank);\n    const start = paddings.map((p2) => p2[0]).join(\",\");\n    const end = paddings.map((p2, i2) => p2[0] + xShape[i2]).join(\",\");\n    const coords3 = getChannels(\"rc\", rank);\n    const source = getChannels(\"source\", rank);\n    const cLimit = `${coords3[rank - 1]} < ${this.outputShape[rank - 1]}`;\n    const innerDims = rank === 1 ? \"source\" : `vec2(${source.slice(-2).join()})`;\n    const offset = mode === \"reflect\" ? 0 : 1;\n    let mainLoop = \"\";\n    if (rank === 1) {\n      const padSetup = `\n        ${dtype} source = rc;\n        if (source < start) {\n          source = start * 2 - source - ${offset};\n        } else if (source >= end) {\n          source = (end - 1) * 2 - source + ${offset};\n        }\n        source -= start;\n      `;\n      mainLoop = `\n        ${dtype} rc = outputLoc;\n        ${padSetup}\n        result[0] = getChannel(getX(${source.join()}), ${innerDims});\n        ${coords3[rank - 1]} += 1;\n        if(${cLimit}) {\n          ${padSetup}\n          result[1] = getChannel(getX(${source.join()}), ${innerDims});\n        }\n      `;\n    } else {\n      const padSetup = `\n        ${dtype} source = rc;\n        ${dtype} lt = ${dtype}(lessThan(source, start));\n        ${dtype} gte = ${dtype}(greaterThanEqual(source, end));\n        ${dtype} orig = 1 - (lt + gte);\n        source = orig * source +\n                lt * (start * 2 - source - ${offset}) +\n                gte * ((end - 1) * 2 - source + ${offset});\n        source -= start;\n      `;\n      mainLoop = `\n        ${dtype} rc = outputLoc;\n        ${padSetup}\n        result[0] = getChannel(getX(${source.join()}), ${innerDims});\n        ${coords3[rank - 1]} += 1;\n        if(${cLimit}) {\n          ${padSetup}\n          result[1] = getChannel(getX(${source.join()}), ${innerDims});\n        }\n        rc = outputLoc;\n        ${coords3[rank - 2]} += 1;\n        if(${coords3[rank - 2]} < ${this.outputShape[rank - 2]}) {\n          ${padSetup}\n          result[2] = getChannel(getX(${source.join()}), ${innerDims});\n          ${coords3[rank - 1]} += 1;\n          if(${cLimit}) {\n            ${padSetup}\n            result[3] = getChannel(getX(${source.join()}), ${innerDims});\n          }\n        }\n      `;\n    }\n    this.userCode = `\n      const ${dtype} start = ${dtype}(${start});\n      const ${dtype} end = ${dtype}(${end});\n\n      void main() {\n        ${dtype} outputLoc = getOutputCoords();\n        vec4 result = vec4(0.);\n        ${mainLoop}\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/MirrorPad.js\nvar mirrorPadKernelFunc = ({ inputs, backend: backend2, attrs }) => {\n  const { x } = inputs;\n  const { paddings, mode } = attrs;\n  const program = env().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\") ? new MirrorPadPackedProgram(x.shape, paddings, mode) : new MirrorPadProgram(x.shape, paddings, mode);\n  const output = backend2.runWebGLProgram(program, [x], x.dtype);\n  return output;\n};\nvar mirrorPadConfig2 = {\n  kernelName: MirrorPad,\n  backendName: \"webgl\",\n  kernelFunc: mirrorPadKernelFunc\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Mod.js\nvar MOD = `if (b == 0.0) return NAN;\n  return mod(a, b);`;\nvar MOD_PACKED = `\n  vec4 result = mod(a, b);\n  vec4 isNaN = vec4(equal(b, vec4(0.0)));\n  ` + CHECK_NAN_SNIPPET3 + `\n  return result;\n`;\nvar mod3 = binaryKernelFunc2({\n  opSnippet: MOD,\n  packedOpSnippet: MOD_PACKED\n});\nvar modConfig2 = {\n  kernelName: Mod,\n  backendName: \"webgl\",\n  kernelFunc: mod3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/multinomial_gpu.js\nvar MultinomialProgram = class {\n  constructor(batchSize, numOutcomes, numSamples) {\n    this.variableNames = [\"probs\"];\n    this.customUniforms = [{ name: \"seed\", type: \"float\" }];\n    this.outputShape = [batchSize, numSamples];\n    this.userCode = `\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n\n        float r = random(seed);\n        float cdf = 0.0;\n\n        for (int i = 0; i < ${numOutcomes - 1}; i++) {\n          cdf += getProbs(batch, i);\n\n          if (r < cdf) {\n            setOutput(float(i));\n            return;\n          }\n        }\n\n        // If no other event happened, last event happened.\n        setOutput(float(${numOutcomes - 1}));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/RealDiv.js\nvar DIV = `\nif (a == b) {\n  return 1.0;\n};\nreturn a / b;`;\nvar DIV_PACKED = `\n  // vec4 one = vec4(equal(a, b));\n  // return one + (vec4(1.0) - one) * a / b;\n  vec4 result = a / b;\n  if(a.x == b.x) {\n    result.x = 1.;\n  }\n  if(a.y == b.y) {\n    result.y = 1.;\n  }\n  if(a.z == b.z) {\n    result.z = 1.;\n  }\n  if(a.w == b.w) {\n    result.w = 1.;\n  }\n\n  return result;\n`;\nvar realDiv = binaryKernelFunc2({ opSnippet: DIV, packedOpSnippet: DIV_PACKED, checkOutOfBounds: true });\nvar realDivConfig2 = {\n  kernelName: RealDiv,\n  backendName: \"webgl\",\n  kernelFunc: realDiv\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sub.js\nvar SUB = \"return a - b;\";\nvar sub3 = binaryKernelFunc2({\n  opSnippet: SUB,\n  packedOpSnippet: SUB,\n  supportsComplex: true,\n  cpuKernelImpl: subImplCPU\n});\nvar subConfig2 = {\n  kernelName: Sub,\n  backendName: \"webgl\",\n  kernelFunc: sub3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Softmax.js\nfunction softmax4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { logits } = inputs;\n  const { dim } = attrs;\n  const axes = util_exports.parseAxisParam([dim], logits.shape);\n  const maxLogit = max4({\n    inputs: { x: logits },\n    backend: backend2,\n    attrs: { reductionIndices: axes, keepDims: false }\n  });\n  const expandedShape = backend_util_exports.expandShapeToKeepDim(maxLogit.shape, axes);\n  const maxLogitsReshaped = reshape4({ inputs: { x: maxLogit }, backend: backend2, attrs: { shape: expandedShape } });\n  const a = sub3({ inputs: { a: logits, b: maxLogitsReshaped }, backend: backend2 });\n  const b = exp3({ inputs: { x: a }, backend: backend2 });\n  const sumExp = sum4({ inputs: { x: b }, backend: backend2, attrs: { axis: axes, keepDims: false } });\n  const sumExpReshaped = reshape4({ inputs: { x: sumExp }, backend: backend2, attrs: { shape: expandedShape } });\n  const res = realDiv({ inputs: { a: b, b: sumExpReshaped }, backend: backend2 });\n  backend2.disposeIntermediateTensorInfo(maxLogit);\n  backend2.disposeIntermediateTensorInfo(maxLogitsReshaped);\n  backend2.disposeIntermediateTensorInfo(a);\n  backend2.disposeIntermediateTensorInfo(b);\n  backend2.disposeIntermediateTensorInfo(sumExp);\n  backend2.disposeIntermediateTensorInfo(sumExpReshaped);\n  return res;\n}\nvar softmaxConfig2 = {\n  kernelName: Softmax,\n  backendName: \"webgl\",\n  kernelFunc: softmax4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Multinomial.js\nfunction multinomial3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { logits } = inputs;\n  const { numSamples, seed, normalized } = attrs;\n  const probs = normalized ? logits : softmax4({ inputs: { logits }, backend: backend2, attrs: { dim: logits.shape.length - 1 } });\n  const batchSize = probs.shape[0];\n  const numOutcomes = probs.shape[1];\n  const program = new MultinomialProgram(batchSize, numOutcomes, numSamples);\n  const customValues = [[seed]];\n  const res = backend2.runWebGLProgram(program, [probs], \"int32\", customValues);\n  if (!normalized) {\n    backend2.disposeIntermediateTensorInfo(probs);\n  }\n  return res;\n}\nvar multinomialConfig2 = {\n  kernelName: Multinomial,\n  backendName: \"webgl\",\n  kernelFunc: multinomial3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Neg.js\nvar NEG = CHECK_NAN_SNIPPET + `\n  return -x;\n`;\nvar NEG_PACKED = `\n  vec4 result = -x;\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n`;\nfunction neg3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (backend2.shouldExecuteOnCPU([x])) {\n    const xData = backend2.texData.get(x.dataId);\n    const [outValues, newShape] = negImplCPU(xData.values, x.shape, x.dtype);\n    return backend2.makeTensorInfo(newShape, x.dtype, outValues);\n  }\n  let program;\n  if (env().getBool(\"WEBGL_PACK_UNARY_OPERATIONS\")) {\n    program = new UnaryOpPackedProgram(x.shape, NEG_PACKED);\n  } else {\n    program = new UnaryOpProgram(x.shape, NEG);\n  }\n  return backend2.runWebGLProgram(program, [x], x.dtype);\n}\nvar negConfig2 = {\n  kernelName: Neg,\n  backendName: \"webgl\",\n  kernelFunc: neg3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/NonMaxSuppressionV3.js\nvar nonMaxSuppressionV3Impl3 = kernel_impls_exports.nonMaxSuppressionV3Impl;\nfunction nonMaxSuppressionV32(args) {\n  backend_util_exports.warn(\"tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead\");\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold } = attrs;\n  const boxesVals = backend2.readSync(boxes.dataId);\n  const scoresVals = backend2.readSync(scores.dataId);\n  const { selectedIndices } = nonMaxSuppressionV3Impl3(boxesVals, scoresVals, maxOutputSize, iouThreshold, scoreThreshold);\n  return backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices));\n}\nvar nonMaxSuppressionV3Config2 = {\n  kernelName: NonMaxSuppressionV3,\n  backendName: \"webgl\",\n  kernelFunc: nonMaxSuppressionV32\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/NonMaxSuppressionV4.js\nvar nonMaxSuppressionV4Impl3 = kernel_impls_exports.nonMaxSuppressionV4Impl;\nfunction nonMaxSuppressionV42(args) {\n  backend_util_exports.warn(\"tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead\");\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize } = attrs;\n  const boxesVals = backend2.readSync(boxes.dataId);\n  const scoresVals = backend2.readSync(scores.dataId);\n  const { selectedIndices, validOutputs } = nonMaxSuppressionV4Impl3(boxesVals, scoresVals, maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize);\n  return [\n    backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices)),\n    backend2.makeTensorInfo([], \"int32\", new Int32Array([validOutputs]))\n  ];\n}\nvar nonMaxSuppressionV4Config2 = {\n  kernelName: NonMaxSuppressionV4,\n  backendName: \"webgl\",\n  kernelFunc: nonMaxSuppressionV42\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/NonMaxSuppressionV5.js\nvar nonMaxSuppressionV5Impl3 = kernel_impls_exports.nonMaxSuppressionV5Impl;\nfunction nonMaxSuppressionV52(args) {\n  backend_util_exports.warn(\"tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead\");\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma } = attrs;\n  const boxesVals = backend2.readSync(boxes.dataId);\n  const scoresVals = backend2.readSync(scores.dataId);\n  const maxOutputSizeVal = maxOutputSize;\n  const iouThresholdVal = iouThreshold;\n  const scoreThresholdVal = scoreThreshold;\n  const softNmsSigmaVal = softNmsSigma;\n  const { selectedIndices, selectedScores } = nonMaxSuppressionV5Impl3(boxesVals, scoresVals, maxOutputSizeVal, iouThresholdVal, scoreThresholdVal, softNmsSigmaVal);\n  return [\n    backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices)),\n    backend2.makeTensorInfo([selectedScores.length], \"float32\", new Float32Array(selectedScores))\n  ];\n}\nvar nonMaxSuppressionV5Config2 = {\n  kernelName: NonMaxSuppressionV5,\n  backendName: \"webgl\",\n  kernelFunc: nonMaxSuppressionV52\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/onehot_gpu.js\nvar OneHotProgram = class {\n  constructor(numIndices, depth, onValue, offValue) {\n    this.variableNames = [\"indices\"];\n    this.outputShape = [numIndices, depth];\n    this.userCode = `\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int index = round(getIndices(coords.x));\n        setOutput(mix(float(${offValue}), float(${onValue}),\n                      float(index == coords.y)));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/OneHot.js\nvar oneHot3 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { indices } = inputs;\n  const { depth, onValue, offValue } = attrs;\n  const indicesSize = util_exports.sizeFromShape(indices.shape);\n  const program = new OneHotProgram(indicesSize, depth, onValue, offValue);\n  const reshaped = reshape4({ inputs: { x: indices }, backend: backend2, attrs: { shape: [indicesSize] } });\n  const result = backend2.runWebGLProgram(program, [reshaped], indices.dtype);\n  backend2.disposeIntermediateTensorInfo(reshaped);\n  const outShape = [...indices.shape, depth];\n  const out = reshape4({ inputs: { x: result }, backend: backend2, attrs: { shape: outShape } });\n  backend2.disposeIntermediateTensorInfo(result);\n  return out;\n};\nvar oneHotConfig2 = {\n  kernelName: OneHot,\n  backendName: \"webgl\",\n  kernelFunc: oneHot3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ZerosLike.js\nfunction zerosLike3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (x.dtype === \"complex64\") {\n    const realPart = real3({ inputs: { input: x }, backend: backend2 });\n    const r2 = zerosLike3({ inputs: { x: realPart }, backend: backend2 });\n    const imagPart = imag3({ inputs: { input: x }, backend: backend2 });\n    const i2 = zerosLike3({ inputs: { x: imagPart }, backend: backend2 });\n    const result = complex3({ inputs: { real: r2, imag: i2 }, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(realPart);\n    backend2.disposeIntermediateTensorInfo(r2);\n    backend2.disposeIntermediateTensorInfo(imagPart);\n    backend2.disposeIntermediateTensorInfo(i2);\n    return result;\n  } else {\n    return fill3({\n      attrs: {\n        shape: x.shape,\n        dtype: x.dtype,\n        value: x.dtype === \"string\" ? \"\" : 0\n      },\n      backend: backend2\n    });\n  }\n}\nvar zerosLikeConfig2 = {\n  kernelName: ZerosLike,\n  backendName: \"webgl\",\n  kernelFunc: zerosLike3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/OnesLike.js\nfunction onesLike3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (x.dtype === \"string\") {\n    throw new Error(\"onesLike is not supported under string dtype\");\n  } else if (x.dtype === \"complex64\") {\n    const realPart = real3({ inputs: { input: x }, backend: backend2 });\n    const r2 = onesLike3({ inputs: { x: realPart }, backend: backend2 });\n    const imagPart = imag3({ inputs: { input: x }, backend: backend2 });\n    const i2 = zerosLike3({ inputs: { x: imagPart }, backend: backend2 });\n    const result = complex3({ inputs: { real: r2, imag: i2 }, backend: backend2 });\n    backend2.disposeIntermediateTensorInfo(realPart);\n    backend2.disposeIntermediateTensorInfo(r2);\n    backend2.disposeIntermediateTensorInfo(imagPart);\n    backend2.disposeIntermediateTensorInfo(i2);\n    return result;\n  } else {\n    return fill3({ attrs: { shape: x.shape, dtype: x.dtype, value: 1 }, backend: backend2 });\n  }\n}\nvar onesLikeConfig2 = {\n  kernelName: OnesLike,\n  backendName: \"webgl\",\n  kernelFunc: onesLike3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Pack.js\nfunction pack2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { axis } = attrs;\n  if (inputs.length === 1) {\n    return expandDims4({ inputs: { input: inputs[0] }, backend: backend2, attrs: { dim: axis } });\n  }\n  const shape = inputs[0].shape;\n  const dtype = inputs[0].dtype;\n  inputs.forEach((t2) => {\n    util_exports.assertShapesMatch(shape, t2.shape, \"All tensors passed to stack must have matching shapes\");\n    util_exports.assert(dtype === t2.dtype, () => \"All tensors passed to stack must have matching dtypes\");\n  });\n  const intermediateTensorInfos = [];\n  const expandedTensors = inputs.map((t2) => {\n    const expandedT = expandDims4({ inputs: { input: t2 }, backend: backend2, attrs: { dim: axis } });\n    intermediateTensorInfos.push(expandedT);\n    return expandedT;\n  });\n  const result = concat3({ inputs: expandedTensors, backend: backend2, attrs: { axis } });\n  intermediateTensorInfos.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return result;\n}\nvar packConfig2 = {\n  kernelName: Pack,\n  backendName: \"webgl\",\n  kernelFunc: pack2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/pad_gpu.js\nvar PadProgram = class {\n  constructor(xShape, paddings, constantValue) {\n    this.variableNames = [\"x\"];\n    this.customUniforms = [{ name: \"value\", type: \"float\" }];\n    this.outputShape = paddings.map((p2, i2) => p2[0] + xShape[i2] + p2[1]);\n    const rank = xShape.length;\n    const type = getCoordsDataType(rank);\n    const start = paddings.map((p2) => p2[0]).join(\",\");\n    const end = paddings.map((p2, i2) => p2[0] + xShape[i2]).join(\",\");\n    const unpackedCoords = [\"coords[0]\", \"coords[1]\", \"coords[2]\", \"coords[3]\"].slice(0, rank);\n    if (rank === 1) {\n      this.userCode = `\n        int start = ${start};\n        int end = ${end};\n\n        void main() {\n          int outC = getOutputCoords();\n          if (outC < start || outC >= end) {\n            setOutput(value);\n          } else {\n            setOutput(getX(outC - start));\n          }\n        }\n      `;\n      return;\n    }\n    this.userCode = `\n      ${type} start = ${type}(${start});\n      ${type} end = ${type}(${end});\n\n      void main() {\n        ${type} outC = getOutputCoords();\n        if (any(lessThan(outC, start)) || any(greaterThanEqual(outC, end))) {\n          setOutput(value);\n        } else {\n          ${type} coords = outC - start;\n          setOutput(getX(${unpackedCoords}));\n        }\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/pad_packed_gpu.js\nvar PadPackedProgram = class {\n  constructor(xShape, paddings, constantValue) {\n    this.variableNames = [\"x\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.customUniforms = [{ name: \"value\", type: \"float\" }];\n    this.outputShape = paddings.map((p2, i2) => p2[0] + xShape[i2] + p2[1]);\n    const rank = xShape.length;\n    const dtype = getCoordsDataType(rank);\n    const start = paddings.map((p2) => p2[0]).join(\",\");\n    const end = paddings.map((p2, i2) => p2[0] + xShape[i2]).join(\",\");\n    const coords3 = getChannels(\"rc\", rank);\n    const source = getChannels(\"source\", rank);\n    const cLimit = `${coords3[rank - 1]} < ${this.outputShape[rank - 1]}`;\n    const innerDims = rank === 1 ? \"source\" : `vec2(${source.slice(-2).join()})`;\n    const componentSetup = [\n      `${dtype} rc = outputLoc;`,\n      `${coords3[rank - 1]} += 1;\n       if(${cLimit}) {\n      `,\n      rank === 1 ? \"\" : `}\n       rc = outputLoc;\n       ${coords3[rank - 2]} += 1;\n       if(${coords3[rank - 2]} < ${this.outputShape[rank - 2]}) {`,\n      rank === 1 ? \"\" : `  ${coords3[rank - 1]} += 1;\n         if(${cLimit}) {`\n    ];\n    const paddingArea = rank === 1 ? \"rc < start || rc >= end\" : \"any(lessThan(rc, start)) || any(greaterThanEqual(rc, end))\";\n    let mainLoop = \"\";\n    for (let i2 = 0, j = rank === 1 ? 2 : 4; i2 < j; i2++) {\n      mainLoop += `\n        ${componentSetup[i2]}\n        if (${paddingArea}) {\n          result[${i2}] = float(value);\n        } else {\n          ${dtype} source = rc - start;\n          result[${i2}] = getChannel(getX(${source.join()}), ${innerDims});\n        }\n      `;\n    }\n    mainLoop += rank === 1 ? `} ` : `}}`;\n    this.userCode = `\n      const ${dtype} start = ${dtype}(${start});\n      const ${dtype} end = ${dtype}(${end});\n\n      void main() {\n        ${dtype} outputLoc = getOutputCoords();\n        vec4 result = vec4(0.);\n        ${mainLoop}\n        setOutput(result);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/PadV2.js\nvar padV22 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { paddings, constantValue } = attrs;\n  if (util_exports.sizeFromShape(x.shape) === 0) {\n    const outputShape = paddings.map((p2, i2) => p2[0] + x.shape[i2] + p2[1]);\n    return fill3({\n      backend: backend2,\n      attrs: { shape: outputShape, value: constantValue, dtype: x.dtype }\n    });\n  }\n  const program = env().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\") ? new PadPackedProgram(x.shape, paddings, constantValue) : new PadProgram(x.shape, paddings, constantValue);\n  const customValues = [[constantValue]];\n  return backend2.runWebGLProgram(program, [x], x.dtype, customValues);\n};\nvar padV2Config2 = {\n  kernelName: PadV2,\n  backendName: \"webgl\",\n  kernelFunc: padV22\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Pow.js\nvar POW = `\n  if(a < 0.0 && floor(b) < b){\n    return NAN;\n  }\n  if (b == 0.0) {\n    return 1.0;\n  }\n  return (round(mod(b, 2.0)) != 1) ?\n      pow(abs(a), b) : sign(a) * pow(abs(a), b);\n`;\nvar POW_PACKED = `\n  // isModRound1 has 1 for components with round(mod(b, 2.0)) == 1, 0 otherwise.\n  vec4 isModRound1 = vec4(equal(round(mod(b, 2.0)), ivec4(1)));\n  vec4 multiplier = sign(a) * isModRound1 + (vec4(1.0) - isModRound1);\n  vec4 result = multiplier * pow(abs(a), b);\n\n  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\n  bvec4 isExpZero = equal(b, vec4(0.0));\n  result.r = isExpZero.r ? 1.0 : result.r;\n  result.g = isExpZero.g ? 1.0 : result.g;\n  result.b = isExpZero.b ? 1.0 : result.b;\n  result.a = isExpZero.a ? 1.0 : result.a;\n\n  vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));\n  ` + CHECK_NAN_SNIPPET3 + `\n  return result;\n`;\nvar pow3 = binaryKernelFunc2({ opSnippet: POW, packedOpSnippet: POW_PACKED });\nvar powConfig2 = {\n  kernelName: Pow,\n  backendName: \"webgl\",\n  kernelFunc: pow3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Prod.js\nfunction prod3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  const xRank = x.shape.length;\n  const toDispose = [];\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  let permutedX = x;\n  if (permutedAxes != null) {\n    permutedX = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n    toDispose.push(permutedX);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"prod\", axes, xRank);\n  let res;\n  if (backend2.shouldExecuteOnCPU([permutedX])) {\n    const xVals = backend2.texData.get(permutedX.dataId).values;\n    const { outVals, outShape, outDtype } = prodImplCPU(permutedX.shape, permutedX.dtype, xVals, axes);\n    res = backend2.makeTensorInfo(outShape, outDtype, outVals);\n  } else {\n    const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(permutedX.shape, axes);\n    const inSize = util_exports.sizeFromShape(reduceShape);\n    const a2D = reshape4({ inputs: { x: permutedX }, backend: backend2, attrs: { shape: [-1, inSize] } });\n    const outputDType = sumOutType(x.dtype);\n    const reduced = reduce(a2D, outputDType, \"prod\", backend2);\n    res = reshape4({ inputs: { x: reduced }, backend: backend2, attrs: { shape: outShape } });\n    toDispose.push(a2D);\n    toDispose.push(reduced);\n  }\n  if (keepDims) {\n    toDispose.push(res);\n    const newShape = backend_util_exports.expandShapeToKeepDim(res.shape, origAxes);\n    res = reshape4({ inputs: { x: res }, backend: backend2, attrs: { shape: newShape } });\n  }\n  toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return res;\n}\nvar prodConfig2 = {\n  kernelName: Prod,\n  backendName: \"webgl\",\n  kernelFunc: prod3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Range.js\nvar range4 = (args) => {\n  const { backend: backend2, attrs } = args;\n  const { start, stop, step: step5, dtype } = attrs;\n  const values = rangeImplCPU(start, stop, step5, dtype);\n  return backend2.makeTensorInfo([values.length], dtype, values);\n};\nvar rangeConfig2 = {\n  kernelName: Range,\n  backendName: \"webgl\",\n  kernelFunc: range4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Reciprocal.js\nvar RECIPROCAL = `return 1.0 / x;`;\nvar reciprocal3 = unaryKernelFunc2({ opSnippet: RECIPROCAL });\nvar reciprocalConfig2 = {\n  kernelName: Reciprocal,\n  backendName: \"webgl\",\n  kernelFunc: reciprocal3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Relu.js\nvar RELU3 = CHECK_NAN_SNIPPET + `\n  return (x < 0.0) ? 0.0 : x;\n`;\nvar RELU_PACKED = `\n  vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n`;\nvar relu3 = unaryKernelFunc2({ opSnippet: RELU3, packedOpSnippet: RELU_PACKED });\nvar reluConfig2 = {\n  kernelName: Relu,\n  backendName: \"webgl\",\n  kernelFunc: relu3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Relu6.js\nvar RELU63 = CHECK_NAN_SNIPPET + `\n  return (x < 0.0) ? 0.0 : min(6.0, x);\n`;\nvar RELU6_PACKED = `\n  vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n`;\nvar relu63 = unaryKernelFunc2({ opSnippet: RELU63, packedOpSnippet: RELU6_PACKED });\nvar relu6Config2 = {\n  kernelName: Relu6,\n  backendName: \"webgl\",\n  kernelFunc: relu63\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_bilinear_gpu.js\nvar ResizeBilinearProgram = class {\n  constructor(inputShape, newHeight, newWidth, alignCorners, halfPixelCenters) {\n    this.variableNames = [\"A\"];\n    this.outputShape = [];\n    const [batch, oldHeight, oldWidth, depth] = inputShape;\n    this.outputShape = [batch, newHeight, newWidth, depth];\n    const effectiveInSize = [\n      alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,\n      alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth\n    ];\n    const effectiveOutSize = [\n      alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,\n      alignCorners && newWidth > 1 ? newWidth - 1 : newWidth\n    ];\n    let sourceFracIndexRC;\n    if (halfPixelCenters) {\n      sourceFracIndexRC = `(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)`;\n    } else {\n      sourceFracIndexRC = `vec2(yRC) * effectiveInputOverOutputRatioRC`;\n    }\n    this.userCode = `\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          ${effectiveInSize[0] / effectiveOutSize[0]},\n          ${effectiveInSize[1] / effectiveOutSize[1]});\n      const vec2 inputShapeRC = vec2(${oldHeight}.0, ${oldWidth}.0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = ${sourceFracIndexRC};\n\n        // Compute the four integer indices.\n        ivec2 sourceFloorRC = ivec2(max(sourceFracIndexRC, vec2(0.0)));\n        ivec2 sourceCeilRC = ivec2(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        float topLeft = getA(b, sourceFloorRC.x, sourceFloorRC.y, d);\n        float bottomLeft = getA(b, sourceCeilRC.x, sourceFloorRC.y, d);\n        float topRight = getA(b, sourceFloorRC.x, sourceCeilRC.y, d);\n        float bottomRight = getA(b, sourceCeilRC.x, sourceCeilRC.y, d);\n\n        vec2 fracRC = sourceFracIndexRC - vec2(sourceFloorRC);\n\n        float top = topLeft + (topRight - topLeft) * fracRC.y;\n        float bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\n        float newValue = top + (bottom - top) * fracRC.x;\n\n        setOutput(newValue);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_bilinear_packed_gpu.js\nvar ResizeBilinearPackedProgram = class {\n  constructor(inputShape, newHeight, newWidth, alignCorners, halfPixelCenters) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = [];\n    const [batch, oldHeight, oldWidth, depth] = inputShape;\n    this.outputShape = [batch, newHeight, newWidth, depth];\n    const effectiveInSize = [\n      alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,\n      alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth\n    ];\n    const effectiveOutSize = [\n      alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,\n      alignCorners && newWidth > 1 ? newWidth - 1 : newWidth\n    ];\n    let sourceFracIndexRC;\n    if (halfPixelCenters) {\n      sourceFracIndexRC = `(vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC - vec3(0.5)`;\n    } else {\n      sourceFracIndexRC = `vec3(yRC) * effectiveInputOverOutputRatioRC`;\n    }\n    this.userCode = `\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\n          ${effectiveInSize[0] / effectiveOutSize[0]},\n          ${effectiveInSize[1] / effectiveOutSize[1]},\n          ${effectiveInSize[1] / effectiveOutSize[1]});\n      const vec3 inputShapeRC = vec3(${oldHeight}.0, ${oldWidth}.0,\n                                     ${oldWidth}.0);\n\n      float getAValue(int b, int r, int c, int d) {\n        return getChannel(getA(b, r, c, d), vec2(c, d));\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        // Calculate values for next column in yRC.z.\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n        // Fractional source index.\n        vec3 sourceFracIndexRC = ${sourceFracIndexRC};\n\n        // Compute the four integer indices.\n        ivec3 sourceFloorRC = ivec3(max(sourceFracIndexRC, vec3(0.0)));\n        ivec3 sourceCeilRC = ivec3(\n          min(inputShapeRC - 1.0, ceil(sourceFracIndexRC)));\n\n        // Should we calculate next column and row elements in 2x2 packed cell.\n        bool hasNextCol = d < ${depth - 1};\n        bool hasNextRow = coords.z < ${newWidth - 1};\n\n        // In parallel, construct four corners for all four components in\n        // packed 2x2 cell.\n        vec4 topLeft = vec4(\n          getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 bottomLeft = vec4(\n          getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceFloorRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceFloorRC.z, d + 1) : 0.0);\n\n        vec4 topRight = vec4(\n          getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceFloorRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceFloorRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec4 bottomRight = vec4(\n          getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d),\n          hasNextCol ? getAValue(b, sourceCeilRC.x, sourceCeilRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceCeilRC.x, sourceCeilRC.z, d + 1) : 0.0);\n\n        vec3 fracRC = sourceFracIndexRC - vec3(sourceFloorRC);\n\n        vec4 top = mix(topLeft, topRight, fracRC.yyzz);\n        vec4 bottom = mix(bottomLeft, bottomRight, fracRC.yyzz);\n        vec4 newValue = mix(top, bottom, fracRC.x);\n\n        setOutput(newValue);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ResizeBilinear.js\nfunction resizeBilinear3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, halfPixelCenters, size } = attrs;\n  const [newHeight, newWidth] = size;\n  const program = env().getBool(\"WEBGL_PACK_IMAGE_OPERATIONS\") ? new ResizeBilinearPackedProgram(images.shape, newHeight, newWidth, alignCorners, halfPixelCenters) : new ResizeBilinearProgram(images.shape, newHeight, newWidth, alignCorners, halfPixelCenters);\n  return backend2.runWebGLProgram(program, [images], \"float32\");\n}\nvar resizeBilinearConfig2 = {\n  kernelName: ResizeBilinear,\n  backendName: \"webgl\",\n  kernelFunc: resizeBilinear3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_bilinear_backprop_gpu.js\nvar ResizeBilinearBackpropProgram = class {\n  constructor(dyShape, inputShape, alignCorners) {\n    this.variableNames = [\"dy\"];\n    this.outputShape = [];\n    this.outputShape = inputShape;\n    const [, xHeight, xWidth] = inputShape;\n    const [, yHeight, yWidth] = dyShape;\n    const effectiveXSize = [\n      alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,\n      alignCorners && yWidth > 1 ? xWidth - 1 : xWidth\n    ];\n    const effectiveYSize = [\n      alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,\n      alignCorners && yWidth > 1 ? yWidth - 1 : yWidth\n    ];\n    const heightScale = effectiveXSize[0] / effectiveYSize[0];\n    const widthScale = effectiveXSize[1] / effectiveYSize[1];\n    const invHeightScale = 1 / heightScale;\n    const invWidthScale = 1 / widthScale;\n    const winHeight = Math.ceil(invHeightScale) * 2 + 2;\n    const winWidth = Math.ceil(invWidthScale) * 2 + 2;\n    this.userCode = `\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float(${heightScale});\n        const float widthScale = float(${widthScale});\n\n        const float invHeightScale = float(${invHeightScale});\n        const float invWidthScale = float(${invWidthScale});\n\n        const int winHeight = int(${winHeight});\n        const int winWidth = int(${winWidth});\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(startRLerp - float(winHeight / 2));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(startCLerp - float(winWidth / 2));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= ${yHeight}) {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= ${yWidth}) {\n              continue;\n            }\n\n            float dxR = float(dyR) * heightScale;\n            int topDxRIndex = int(floor(dxR));\n            int bottomDxRIndex = int(min(ceil(dxR), ${xHeight - 1}.0));\n            float dxRLerp = dxR - float(topDxRIndex);\n            float inverseDxRLerp = 1.0 - dxRLerp;\n\n            float dxC = float(dyC) * widthScale;\n            int leftDxCIndex = int(floor(dxC));\n            int rightDxCIndex = int(min(ceil(dxC), ${xWidth - 1}.0));\n            float dxCLerp = dxC - float(leftDxCIndex);\n            float inverseDxCLerp = 1.0 - dxCLerp;\n\n            if (r == topDxRIndex && c == leftDxCIndex) {\n              // topLeft\n              accumulator +=\n                getDy(b, dyR, dyC, d) * inverseDxRLerp * inverseDxCLerp;\n            }\n\n            if (r == topDxRIndex && c == rightDxCIndex) {\n              // topRight\n              accumulator += getDy(b, dyR, dyC, d) * inverseDxRLerp * dxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == leftDxCIndex) {\n              // bottomLeft\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * inverseDxCLerp;\n            }\n\n            if (r == bottomDxRIndex && c == rightDxCIndex) {\n              // bottomRight\n              accumulator += getDy(b, dyR, dyC, d) * dxRLerp * dxCLerp;\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ResizeBilinearGrad.js\nfunction resizeBilinearGrad2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images, dy } = inputs;\n  const { alignCorners } = attrs;\n  const program = new ResizeBilinearBackpropProgram(dy.shape, images.shape, alignCorners);\n  return backend2.runWebGLProgram(program, [dy], dy.dtype);\n}\nvar resizeBilinearGradConfig3 = {\n  kernelName: ResizeBilinearGrad,\n  backendName: \"webgl\",\n  kernelFunc: resizeBilinearGrad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_nearest_neighbor_gpu.js\nvar ResizeNearestNeighborProgram = class {\n  constructor(inputShape, newHeight, newWidth, alignCorners, halfPixelCenters) {\n    this.variableNames = [\"A\"];\n    this.outputShape = [];\n    const [batch, oldHeight, oldWidth, depth] = inputShape;\n    this.outputShape = [batch, newHeight, newWidth, depth];\n    const effectiveInSize = [\n      alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,\n      alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth\n    ];\n    const effectiveOutSize = [\n      alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,\n      alignCorners && newWidth > 1 ? newWidth - 1 : newWidth\n    ];\n    const roundBase = alignCorners ? \"0.5\" : \"0.0\";\n    let sourceFracIndexRC;\n    if (halfPixelCenters) {\n      sourceFracIndexRC = `max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))`;\n    } else {\n      sourceFracIndexRC = `vec2(yRC) * effectiveInputOverOutputRatioRC`;\n    }\n    this.userCode = `\n      const vec2 effectiveInputOverOutputRatioRC = vec2(\n          ${effectiveInSize[0] / effectiveOutSize[0]},\n          ${effectiveInSize[1] / effectiveOutSize[1]});\n      const vec2 inputShapeRC = vec2(${oldHeight}.0, ${oldWidth}.0);\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        ivec2 yRC = coords.yz;\n\n        // Fractional source index.\n        vec2 sourceFracIndexRC = ${sourceFracIndexRC};\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec2 sourceNearestRC = ivec2(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${roundBase})));\n        float newValue = getA(b, sourceNearestRC.x, sourceNearestRC.y, d);\n\n        setOutput(newValue);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_nearest_neighbor_packed_gpu.js\nvar ResizeNearestNeighborPackedProgram = class {\n  constructor(inputShape, newHeight, newWidth, alignCorners, halfPixelCenters) {\n    this.variableNames = [\"A\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    this.outputShape = [];\n    const [batch, oldHeight, oldWidth, depth] = inputShape;\n    this.outputShape = [batch, newHeight, newWidth, depth];\n    const effectiveInSize = [\n      alignCorners && newHeight > 1 ? oldHeight - 1 : oldHeight,\n      alignCorners && newWidth > 1 ? oldWidth - 1 : oldWidth\n    ];\n    const effectiveOutSize = [\n      alignCorners && newHeight > 1 ? newHeight - 1 : newHeight,\n      alignCorners && newWidth > 1 ? newWidth - 1 : newWidth\n    ];\n    const roundBase = alignCorners ? \"0.5\" : \"0.0\";\n    let sourceFracIndexRC;\n    if (halfPixelCenters) {\n      sourceFracIndexRC = `max((vec3(yRC) + vec3(0.5)) * effectiveInputOverOutputRatioRC, vec3(0.0))`;\n    } else {\n      sourceFracIndexRC = `vec3(yRC) * effectiveInputOverOutputRatioRC`;\n    }\n    this.userCode = `\n      const vec3 effectiveInputOverOutputRatioRC = vec3(\n          ${effectiveInSize[0] / effectiveOutSize[0]},\n          ${effectiveInSize[1] / effectiveOutSize[1]},\n          ${effectiveInSize[1] / effectiveOutSize[1]});\n      const vec3 inputShapeRC = vec3(${oldHeight}.0, ${oldWidth}.0,\n                                     ${oldWidth}.0);\n\n      float getAValue(int b, int r, int c, int d) {\n        return getChannel(getA(b, r, c, d), vec2(c, d));\n      }\n\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        // Calculate values for next column in yRC.z.\n        ivec3 yRC = coords.yzz + ivec3(0, 0, 1);\n\n        // Fractional source index.\n        vec3 sourceFracIndexRC = ${sourceFracIndexRC};\n\n        // Compute the coordinators of nearest neighbor point.\n        ivec3 sourceNearestRC = ivec3(\n          min(inputShapeRC - 1.0, floor(sourceFracIndexRC + ${roundBase})));\n\n        // Should we calculate next column and row elements in 2x2 packed cell.\n        bool hasNextCol = d < ${depth - 1};\n        bool hasNextRow = coords.z < ${newWidth - 1};\n\n        vec4 newValue = vec4(\n          getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d),\n          hasNextCol ? getAValue(b, sourceNearestRC.x, sourceNearestRC.y, d + 1)\n                     : 0.0,\n          hasNextRow ? getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d)\n                     : 0.0,\n          (hasNextRow && hasNextCol) ?\n            getAValue(b, sourceNearestRC.x, sourceNearestRC.z, d + 1) : 0.0);\n\n        setOutput(newValue);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ResizeNearestNeighbor.js\nfunction resizeNearestNeighbor3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, halfPixelCenters, size } = attrs;\n  const [newHeight, newWidth] = size;\n  const program = env().getBool(\"WEBGL_PACK_IMAGE_OPERATIONS\") ? new ResizeNearestNeighborPackedProgram(images.shape, newHeight, newWidth, alignCorners, halfPixelCenters) : new ResizeNearestNeighborProgram(images.shape, newHeight, newWidth, alignCorners, halfPixelCenters);\n  return backend2.runWebGLProgram(program, [images], images.dtype);\n}\nvar resizeNearestNeighborConfig2 = {\n  kernelName: ResizeNearestNeighbor,\n  backendName: \"webgl\",\n  kernelFunc: resizeNearestNeighbor3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/resize_nearest_neighbor_backprop_gpu.js\nvar ResizeNearestNeigborBackpropProgram = class {\n  constructor(dyShape, inputShape, alignCorners) {\n    this.variableNames = [\"dy\"];\n    this.outputShape = [];\n    this.outputShape = inputShape;\n    const [, xHeight, xWidth] = inputShape;\n    const [, yHeight, yWidth] = dyShape;\n    const effectiveXSize = [\n      alignCorners && yHeight > 1 ? xHeight - 1 : xHeight,\n      alignCorners && yWidth > 1 ? xWidth - 1 : xWidth\n    ];\n    const effectiveYSize = [\n      alignCorners && yHeight > 1 ? yHeight - 1 : yHeight,\n      alignCorners && yWidth > 1 ? yWidth - 1 : yWidth\n    ];\n    const heightScale = effectiveXSize[0] / effectiveYSize[0];\n    const widthScale = effectiveXSize[1] / effectiveYSize[1];\n    const invHeightScale = 1 / heightScale;\n    const invWidthScale = 1 / widthScale;\n    const winHeight = Math.ceil(invHeightScale) * 2 + 2;\n    const winWidth = Math.ceil(invWidthScale) * 2 + 2;\n    this.userCode = `\n      void main() {\n        ivec4 coords = getOutputCoords();\n        int b = coords[0];\n        int d = coords[3];\n        int r = coords[1];\n        int c = coords[2];\n\n        float accumulator = 0.0;\n\n        const float heightScale = float(${heightScale});\n        const float widthScale = float(${widthScale});\n\n        const float invHeightScale = float(${invHeightScale});\n        const float invWidthScale = float(${invWidthScale});\n\n        const int winHeight = int(${winHeight});\n        const int winWidth = int(${winWidth});\n\n        // Compute bounds for where in dy we will look\n        float startRLerp = floor(float(r) * invHeightScale);\n        int startDyR = int(floor(startRLerp - float(winHeight / 2)));\n\n        float startCLerp = floor(float(c) * invWidthScale);\n        int startDyC = int(floor(startCLerp - float(winWidth / 2)));\n\n        // Loop over dy\n        for (int dyROffset = 0; dyROffset < winHeight; dyROffset++) {\n          int dyR = dyROffset + startDyR;\n\n          // Guard against the window exceeding the bounds of dy\n          if (dyR < 0 || dyR >= ${yHeight}) {\n            continue;\n          }\n\n          for (int dyCOffset = 0; dyCOffset < winWidth; dyCOffset++) {\n            int dyC = dyCOffset + startDyC;\n\n            // Guard against the window exceeding the bounds of dy\n            if (dyC < 0 || dyC >= ${yWidth}) {\n              continue;\n            }\n\n            float sourceFracRow =\n              float(${effectiveXSize[0]}) *\n                (float(dyR) / float(${effectiveYSize[0]}));\n\n            float sourceFracCol =\n                float(${effectiveXSize[1]}) *\n                  (float(dyC) / float(${effectiveYSize[1]}));\n\n            int sourceNearestRow = int(min(\n                float(int(${xHeight}) - 1),\n                ${alignCorners} ? float(round(sourceFracRow)) :\n                                  float(floor(sourceFracRow))));\n\n            int sourceNearestCol = int(min(\n                float(int(${xWidth}) - 1),\n                ${alignCorners} ? float(round(sourceFracCol)) :\n                                  float(floor(sourceFracCol))));\n\n            if (r == sourceNearestRow && c == sourceNearestCol) {\n              accumulator += getDy(b, dyR, dyC, d);\n            }\n          }\n        }\n        // End loop over dy\n\n        setOutput(accumulator);\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ResizeNearestNeighborGrad.js\nfunction resizeNearestNeighborGrad2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images, dy } = inputs;\n  const { alignCorners } = attrs;\n  const program = new ResizeNearestNeigborBackpropProgram(dy.shape, images.shape, alignCorners);\n  return backend2.runWebGLProgram(program, [dy], dy.dtype);\n}\nvar resizeNearestNeighborGradConfig3 = {\n  kernelName: ResizeNearestNeighborGrad,\n  backendName: \"webgl\",\n  kernelFunc: resizeNearestNeighborGrad2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/reverse_gpu.js\nvar ReverseProgram = class {\n  constructor(xShape, axis) {\n    this.variableNames = [\"x\"];\n    const rank = xShape.length;\n    if (rank > 4) {\n      throw new Error(`WebGL backend: Reverse of rank-${rank} tensor is not yet supported`);\n    }\n    this.outputShape = xShape;\n    if (rank === 1) {\n      this.userCode = `\n        void main() {\n          int coord = getOutputCoords();\n          setOutput(getX(${xShape[0]} - coord - 1));\n        }\n      `;\n      return;\n    }\n    const getInCoord = (i2) => {\n      if (axis.indexOf(i2) !== -1 && xShape[i2] !== 1) {\n        return `${xShape[i2]} - coords[${i2}] - 1`;\n      }\n      return `coords[${i2}]`;\n    };\n    const inCoords = xShape.map((_, i2) => getInCoord(i2)).join(\",\");\n    const type = getCoordsDataType(rank);\n    this.userCode = `\n      void main() {\n        ${type} coords = getOutputCoords();\n        setOutput(getX(${inCoords}));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/reverse_packed_gpu.js\nvar ReversePackedProgram = class {\n  constructor(xShape, axis) {\n    this.variableNames = [\"x\"];\n    this.packedInputs = true;\n    this.packedOutput = true;\n    const rank = xShape.length;\n    if (rank > 4) {\n      throw new Error(`WebGL backend: Reverse of rank-${rank} tensor is not yet supported`);\n    }\n    this.outputShape = xShape;\n    const channels = getChannels(\"rc\", rank);\n    const nextColumn = `${channels[rank - 1]} + 1 < ${this.outputShape[rank - 1]}`;\n    const nextRow = `${channels[rank - 2]} + 1 < ${this.outputShape[rank - 2]}`;\n    const type = getCoordsDataType(rank);\n    if (rank === 1) {\n      this.userCode = `\n        void main(){\n          int rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = getChannel(getX(${xShape[0]} - rc - 1),\n            ${xShape[0]} - rc - 1);\n          if(${nextColumn}){\n              result.g = getChannel(getX(${xShape[0]} - (rc  + 1) - 1),\n                ${xShape[0]} - (rc  + 1) - 1);\n          }\n          setOutput(result);\n        }\n      `;\n    } else {\n      this.userCode = `\n        void main() {\n          ${type} rc = getOutputCoords();\n          vec4 result = vec4(0.);\n          result.r = ${getR(channels.slice())};\n          if(${nextColumn}){\n            result.g = ${getG(channels.slice())};\n          }\n          if(${nextRow}) {\n            result.b = ${getB(channels.slice())};\n            if(${nextColumn}) {\n              result.a = ${getA(channels.slice())};\n            }\n          }\n          setOutput(result);\n        }\n    `;\n    }\n    function getR(channels2) {\n      return getChannel(channels2);\n    }\n    function getG(channels2) {\n      channels2[rank - 1] = \"(\" + channels2[rank - 1] + ` + 1)`;\n      return getChannel(channels2);\n    }\n    function getB(channels2) {\n      channels2[rank - 2] = \"(\" + channels2[rank - 2] + ` + 1)`;\n      return getChannel(channels2);\n    }\n    function getA(channels2) {\n      channels2[rank - 1] = \"(\" + channels2[rank - 1] + ` + 1)`;\n      channels2[rank - 2] = \"(\" + channels2[rank - 2] + ` + 1)`;\n      return getChannel(channels2);\n    }\n    function getChannel(channels2) {\n      const inCoordsArray = xShape.map((_, i2) => getInCoord(i2, channels2));\n      const inCoords = inCoordsArray.join(\",\");\n      const innerDims = inCoordsArray.slice(-2).join(\",\");\n      return `getChannel(getX(${inCoords}), vec2(${innerDims}))`;\n    }\n    function getInCoord(i2, channels1) {\n      if (axis.indexOf(i2) !== -1 && xShape[i2] !== 1) {\n        return `${xShape[i2]} - ${channels1[i2]} - 1`;\n      } else {\n        return `${channels1[i2]}`;\n      }\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Reverse.js\nfunction reverse3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { dims } = attrs;\n  const xRank = x.shape.length;\n  const $dims = util_exports.parseAxisParam(dims, x.shape);\n  if (xRank === 0) {\n    return identity3({ inputs: { x }, backend: backend2 });\n  }\n  const program = env().getBool(\"WEBGL_PACK_ARRAY_OPERATIONS\") ? new ReversePackedProgram(x.shape, $dims) : new ReverseProgram(x.shape, $dims);\n  return backend2.runWebGLProgram(program, [x], x.dtype);\n}\nvar reverseConfig2 = {\n  kernelName: Reverse,\n  backendName: \"webgl\",\n  kernelFunc: reverse3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/rotate_gpu.js\nvar RotateProgram = class {\n  constructor(imageShape, fillValue) {\n    this.variableNames = [\"Image\"];\n    this.outputShape = [];\n    this.customUniforms = [{ name: \"params\", type: \"vec4\" }];\n    const imageHeight = imageShape[1];\n    const imageWidth = imageShape[2];\n    this.outputShape = imageShape;\n    let fillSnippet = \"\";\n    if (typeof fillValue === \"number\") {\n      fillSnippet = `float outputValue = ${fillValue.toFixed(2)};`;\n    } else {\n      fillSnippet = `\n        vec3 fill = vec3(${fillValue.join(\",\")});\n        float outputValue = fill[coords[3]];`;\n    }\n    this.userCode = `\n        void main() {\n          ivec4 coords = getOutputCoords();\n          int x = coords[2];\n          int y = coords[1];\n          float coordXFloat = (float(x) - params[0]) * params[3] -\n            (float(y) - params[1]) * params[2];\n          float coordYFloat = (float(x) - params[0]) * params[2] +\n            (float(y) - params[1]) * params[3];\n          int coordX = int(round(coordXFloat + params[0]));\n          int coordY = int(round(coordYFloat + params[1]));\n          ${fillSnippet}\n          if(coordX >= 0 && coordX < ${imageWidth} && coordY >= 0 && coordY < ${imageHeight}) {\n            outputValue = getImage(coords[0], coordY, coordX, coords[3]);\n          }\n          setOutput(outputValue);\n        }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/RotateWithOffset.js\nvar rotateWithOffsetConfig2 = {\n  kernelName: RotateWithOffset,\n  backendName: \"webgl\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { image: image2 } = inputs;\n    const { radians, fillValue, center } = attrs;\n    const webglBackend = backend2;\n    const program = new RotateProgram(image2.shape, fillValue);\n    const [centerX, centerY] = backend_util_exports.getImageCenter(center, image2.shape[1], image2.shape[2]);\n    const customValues = [[centerX, centerY, Math.sin(radians), Math.cos(radians)]];\n    const output = webglBackend.runWebGLProgram(program, [image2], image2.dtype, customValues);\n    return output;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Round.js\nvar ROUND = `\n  // OpenGL ES does not support round function.\n  // The algorithm is based on banker's rounding.\n  float base = floor(x);\n  if ((x - base) < 0.5) {\n    return floor(x);\n  } else if ((x - base) > 0.5) {\n    return ceil(x);\n  } else {\n    if (mod(base, 2.0) == 0.0) {\n      return base;\n    } else {\n      return base + 1.0;\n    }\n  }\n`;\nvar round4 = unaryKernelFunc2({ opSnippet: ROUND });\nvar roundConfig2 = {\n  kernelName: Round,\n  backendName: \"webgl\",\n  kernelFunc: round4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Rsqrt.js\nvar RSQRT = `return inversesqrt(x);`;\nvar rsqrt3 = unaryKernelFunc2({ opSnippet: RSQRT, cpuKernelImpl: rsqrtImplCPU });\nvar rsqrtConfig2 = {\n  kernelName: Rsqrt,\n  backendName: \"webgl\",\n  kernelFunc: rsqrt3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/scatter_gpu.js\nvar ScatterProgram = class {\n  constructor(updateSize, sliceDim, indicesRank, updatesRank, strides, shape, summingDupeIndex = true) {\n    this.variableNames = [\"updates\", \"indices\", \"defaultValue\"];\n    this.outputShape = shape;\n    const stridesType = getCoordsDataType(strides.length);\n    const dtype = getCoordsDataType(shape.length);\n    let indicesString = \"\";\n    if (indicesRank === 1) {\n      indicesString = \"i\";\n    } else if (indicesRank === 2) {\n      indicesString = \"i, j\";\n    }\n    const indicesSnippet = `getIndices(${indicesString})`;\n    let updatesString = \"\";\n    if (updatesRank === 1) {\n      updatesString = \"i\";\n    } else if (updatesRank === 2) {\n      updatesString = \"i, coords[1]\";\n    }\n    const updatesSnippet = `getUpdates(${updatesString})`;\n    const strideString = sliceDim > 1 ? \"strides[j]\" : \"strides\";\n    this.userCode = `\n        ${stridesType} strides = ${stridesType}(${strides});\n\n        void main() {\n          ${dtype} coords = getOutputCoords();\n          float sum = 0.0;\n          bool found = false;\n          for (int i = 0; i < ${updateSize}; i++) {\n            int flattenedIndex = 0;\n            for (int j = 0; j < ${sliceDim}; j++) {\n              int index = round(${indicesSnippet});\n              flattenedIndex += index * ${strideString};\n            }\n            if (flattenedIndex == coords[0]) {\n              sum += ${updatesSnippet};\n              found = true;\n            }\n          }\n          setOutput(mix(getDefaultValue(), sum, float(found)));\n        }\n      `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/ScatterNd.js\nfunction scatterNd2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { indices, updates } = inputs;\n  const { shape } = attrs;\n  const { sliceRank, numUpdates, sliceSize, strides, outputSize } = backend_util_exports.calculateShapes(updates, indices, shape);\n  const flattenShape = [outputSize / sliceSize, sliceSize];\n  if (outputSize === 0) {\n    return backend2.makeTensorInfo(shape, indices.dtype);\n  }\n  const flattenIndices = reshape4({ inputs: { x: indices }, backend: backend2, attrs: { shape: [numUpdates, sliceRank] } });\n  const flattenX = reshape4({ inputs: { x: updates }, backend: backend2, attrs: { shape: [numUpdates, sliceSize] } });\n  const defaultValue = backend2.makeTensorInfo([], \"float32\", new Float32Array([0]));\n  const program = new ScatterProgram(numUpdates, sliceRank, flattenIndices.shape.length, flattenX.shape.length, strides, flattenShape);\n  const res = backend2.runWebGLProgram(program, [flattenX, flattenIndices, defaultValue], flattenX.dtype);\n  const reshaped = reshape4({ inputs: { x: res }, backend: backend2, attrs: { shape } });\n  backend2.disposeIntermediateTensorInfo(flattenIndices);\n  backend2.disposeIntermediateTensorInfo(flattenX);\n  backend2.disposeIntermediateTensorInfo(res);\n  backend2.disposeIntermediateTensorInfo(defaultValue);\n  return reshaped;\n}\nvar scatterNdConfig2 = {\n  kernelName: ScatterNd,\n  backendName: \"webgl\",\n  kernelFunc: scatterNd2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/search_sorted_gpu.js\nvar SearchSortedProgram = class {\n  constructor(batchSize, numInputs, numValues, side) {\n    this.variableNames = [\"sortedSequence\", \"values\"];\n    this.customUniforms = [{ name: \"numInputs\", type: \"int\" }];\n    this.outputShape = [batchSize, numValues];\n    const webGL2LoopHead = \"while (left < right) {\";\n    const webGL1LoopHead = `for (int i = 0; i < ${Math.ceil(Math.log2(numInputs + 1))}; ++i) { if (left >= right) break;`;\n    const loopHead = env().getNumber(\"WEBGL_VERSION\") === 2 ? webGL2LoopHead : webGL1LoopHead;\n    const boundComparator = side === \"left\" ? \"<\" : \"<=\";\n    this.userCode = `\n       int findBound(int batch, float value) {\n         int left = 0;\n         int right = numInputs;\n         int mid;\n         ${loopHead}\n           mid = (left + right) / 2;\n           if (getSortedSequence(batch, mid) ${boundComparator} value) {\n             left = mid + 1;\n           } else {\n             right = mid;\n           }\n         }\n         return right;\n       }\n\n       void main() {\n         ivec2 coords = getOutputCoords();\n         int batch = coords[0];\n         int valueIndex = coords[1];\n\n         float value = getValues(batch, valueIndex);\n\n         setOutput(float(findBound(batch, value)));\n       }\n     `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SearchSorted.js\nfunction searchSorted3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { sortedSequence, values } = inputs;\n  const { side } = attrs;\n  const program = new SearchSortedProgram(sortedSequence.shape[0], sortedSequence.shape[1], values.shape[1], side);\n  const customValues = [[sortedSequence.shape[1]]];\n  return backend2.runWebGLProgram(program, [sortedSequence, values], \"int32\", customValues);\n}\nvar searchSortedConfig2 = {\n  kernelName: SearchSorted,\n  backendName: \"webgl\",\n  kernelFunc: searchSorted3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/select_gpu.js\nvar SelectProgram = class {\n  constructor(cRank, shape, rank) {\n    this.variableNames = [\"c\", \"a\", \"b\"];\n    this.outputShape = shape;\n    let cCoords;\n    let abCoords;\n    if (rank > 4) {\n      throw Error(`Where for rank ${rank} is not yet supported`);\n    }\n    if (rank === 1) {\n      abCoords = `resRC`;\n      cCoords = `resRC`;\n    } else {\n      const currentCoords = [\"resRC.x\", \"resRC.y\", \"resRC.z\", \"resRC.w\"];\n      const cCoordVars = [];\n      const abCoordVars = [];\n      for (let i2 = 0; i2 < shape.length; i2++) {\n        abCoordVars.push(`${currentCoords[i2]}`);\n        if (i2 < cRank) {\n          cCoordVars.push(`${currentCoords[i2]}`);\n        }\n      }\n      cCoords = cCoordVars.join();\n      abCoords = abCoordVars.join();\n    }\n    const dtype = getCoordsDataType(rank);\n    this.userCode = `\n      void main() {\n        ${dtype} resRC = getOutputCoords();\n        float cVal = getC(${cCoords});\n        if (cVal >= 1.0) {\n          setOutput(getA(${abCoords}));\n        } else {\n          setOutput(getB(${abCoords}));\n        }\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Select.js\nfunction select3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { condition, t: t2, e: e2 } = inputs;\n  const program = new SelectProgram(condition.shape.length, t2.shape, t2.shape.length);\n  return backend2.runWebGLProgram(program, [condition, t2, e2], upcastType(t2.dtype, e2.dtype));\n}\nvar selectConfig2 = {\n  kernelName: Select,\n  backendName: \"webgl\",\n  kernelFunc: select3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Selu.js\nvar SELU = `\n  // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.\n  // see: https://arxiv.org/abs/1706.02515\n  float scaleAlpha = ${backend_util_exports.SELU_SCALEALPHA};\n  float scale = ${backend_util_exports.SELU_SCALE};\n  return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);\n`;\nvar selu3 = unaryKernelFunc2({ opSnippet: SELU });\nvar seluConfig2 = {\n  kernelName: Selu,\n  backendName: \"webgl\",\n  kernelFunc: selu3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sigmoid.js\nvar SIGMOID3 = CHECK_NAN_SNIPPET_UNARY + `\n  return 1.0 / (1.0 + exp(-1.0 * x));\n`;\nvar SIGMOID_PACKED = `\n  vec4 result = 1.0 / (1.0 + exp(-1.0 * x));\n  bvec4 isNaN = isnan(x);\n\n  result.r = isNaN.r ? x.r : result.r;\n  result.g = isNaN.g ? x.g : result.g;\n  result.b = isNaN.b ? x.b : result.b;\n  result.a = isNaN.a ? x.a : result.a;\n\n  return result;\n`;\nvar sigmoid3 = unaryKernelFunc2({\n  opSnippet: SIGMOID3,\n  packedOpSnippet: SIGMOID_PACKED,\n  cpuKernelImpl: sigmoidImplCPU\n});\nvar sigmoidConfig2 = {\n  kernelName: Sigmoid,\n  backendName: \"webgl\",\n  kernelFunc: sigmoid3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sign.js\nvar SIGN = `\n  if (isnan(x)) { return 0.0; }\n  return sign(x);\n`;\nvar sign3 = unaryKernelFunc2({ opSnippet: SIGN });\nvar signConfig2 = {\n  kernelName: Sign,\n  backendName: \"webgl\",\n  kernelFunc: sign3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sin.js\nvar SIN = CHECK_NAN_SNIPPET_UNARY + `\n  return sin(x);\n`;\nvar sin3 = unaryKernelFunc2({ opSnippet: SIN });\nvar sinConfig2 = {\n  kernelName: Sin,\n  backendName: \"webgl\",\n  kernelFunc: sin3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sinh.js\nvar SINH = `\n  float e2x = exp(x);\n  return (e2x - 1.0 / e2x) / 2.0;\n`;\nvar sinh3 = unaryKernelFunc2({ opSnippet: SINH });\nvar sinhConfig2 = {\n  kernelName: Sinh,\n  backendName: \"webgl\",\n  kernelFunc: sinh3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Softplus.js\nvar SOFTPLUS = `\n  float epsilon = 1.1920928955078125e-7;\n  float threshold = log(epsilon) + 2.0;\n\n  bool too_large = x > -threshold;\n  bool too_small = x < threshold;\n\n  float result;\n  float exp_x = exp(x);\n\n  if (too_large){\n    result = x;\n  }\n  else if (too_small){\n    result = exp_x;\n  }\n  else{\n    result = log(exp_x + 1.0);\n  }\n  return result;\n`;\nvar softplus3 = unaryKernelFunc2({ opSnippet: SOFTPLUS });\nvar softplusConfig2 = {\n  kernelName: Softplus,\n  backendName: \"webgl\",\n  kernelFunc: softplus3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SpaceToBatchND.js\nvar spaceToBatchND3 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, paddings } = attrs;\n  util_exports.assert(x.shape.length <= 4, () => \"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet\");\n  const prod6 = blockShape.reduce((a, b) => a * b);\n  const completePaddings = [[0, 0]];\n  completePaddings.push(...paddings);\n  for (let i2 = 1 + blockShape.length; i2 < x.shape.length; ++i2) {\n    completePaddings.push([0, 0]);\n  }\n  const toDispose = [];\n  const paddedX = padV22({\n    inputs: { x },\n    backend: backend2,\n    attrs: { paddings: completePaddings, constantValue: 0 }\n  });\n  const reshapedPaddedShape = backend_util_exports.getReshaped(paddedX.shape, blockShape, prod6, false);\n  const permutedReshapedPaddedPermutation = backend_util_exports.getPermuted(reshapedPaddedShape.length, blockShape.length, false);\n  const flattenShape = backend_util_exports.getReshapedPermuted(paddedX.shape, blockShape, prod6, false);\n  const reshapedPaddedX = reshape4({ inputs: { x: paddedX }, backend: backend2, attrs: { shape: reshapedPaddedShape } });\n  const paddedXT = transpose3({\n    inputs: { x: reshapedPaddedX },\n    backend: backend2,\n    attrs: { perm: permutedReshapedPaddedPermutation }\n  });\n  const result = reshape4({ inputs: { x: paddedXT }, backend: backend2, attrs: { shape: flattenShape } });\n  toDispose.push(paddedX);\n  toDispose.push(reshapedPaddedX);\n  toDispose.push(paddedXT);\n  toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return result;\n};\nvar spaceToBatchNDConfig2 = {\n  kernelName: SpaceToBatchND,\n  backendName: \"webgl\",\n  kernelFunc: spaceToBatchND3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SparseFillEmptyRows.js\nfunction sparseFillEmptyRows3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { indices, values, denseShape, defaultValue } = inputs;\n  if (denseShape.shape.length !== 1) {\n    throw new Error(`Dense shape must be a vector, saw:\n         ${denseShape.shape}`);\n  }\n  if (indices.shape.length !== 2) {\n    throw new Error(`Indices must be a matrix, saw:\n         ${indices.shape}`);\n  }\n  if (values.shape.length !== 1) {\n    throw new Error(`Values must be a vector, saw:\n         ${values.shape}`);\n  }\n  if (defaultValue.shape.length !== 0) {\n    throw new Error(`Default value must be a scalar, saw:\n        ${defaultValue.shape}`);\n  }\n  const $indices = backend2.readSync(indices.dataId);\n  const $values = backend2.readSync(values.dataId);\n  const $denseShape = backend2.readSync(denseShape.dataId);\n  const $defaultValue = backend2.readSync(defaultValue.dataId)[0];\n  const [outputIndices, outputIndicesShape, outputValues, emptyRowIndicator, reverseIndexMap] = sparseFillEmptyRowsImplCPU($indices, indices.shape, indices.dtype, $values, values.dtype, $denseShape, $defaultValue);\n  return [\n    backend2.makeTensorInfo(outputIndicesShape, indices.dtype, outputIndices),\n    backend2.makeTensorInfo([outputIndicesShape[0]], values.dtype, outputValues),\n    backend2.makeTensorInfo([emptyRowIndicator.length], \"bool\", new Uint8Array(emptyRowIndicator.map((value) => Number(value)))),\n    backend2.makeTensorInfo([reverseIndexMap.length], indices.dtype, new Int32Array(reverseIndexMap))\n  ];\n}\nvar sparseFillEmptyRowsConfig2 = {\n  kernelName: SparseFillEmptyRows,\n  backendName: \"webgl\",\n  kernelFunc: sparseFillEmptyRows3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SparseReshape.js\nfunction sparseReshape3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { inputIndices, inputShape, newShape } = inputs;\n  if (inputIndices.shape.length !== 2) {\n    throw new Error(`Input indices should be a matrix but received shape ${inputIndices.shape}`);\n  }\n  if (inputShape.shape.length !== 1) {\n    throw new Error(`Input shape should be a vector but received shape ${inputShape.shape}`);\n  }\n  if (newShape.shape.length !== 1) {\n    throw new Error(`Target shape should be a vector but received shape ${newShape.shape}`);\n  }\n  const $inputShape = Array.from(backend2.readSync(inputShape.dataId));\n  const $inputIndices = backend2.readSync(inputIndices.dataId);\n  const targetShape = Array.from(backend2.readSync(newShape.dataId));\n  const [newIndices, indicesShape, outputShape] = sparseReshapeImplCPU($inputIndices, inputIndices.shape, inputIndices.dtype, $inputShape, targetShape);\n  return [\n    backend2.makeTensorInfo(indicesShape, inputIndices.dtype, newIndices),\n    backend2.makeTensorInfo([outputShape.length], newShape.dtype, new Int32Array(outputShape))\n  ];\n}\nvar sparseReshapeConfig2 = {\n  kernelName: SparseReshape,\n  backendName: \"webgl\",\n  kernelFunc: sparseReshape3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SparseSegmentMean.js\nfunction sparseSegmentMean3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { data, indices, segmentIds } = inputs;\n  if (data.shape.length < 1) {\n    throw new Error(`Data should be at least 1 dimensional but received scalar`);\n  }\n  if (indices.shape.length !== 1) {\n    throw new Error(`Indices should be a vector but received shape\n              ${indices.shape}`);\n  }\n  if (segmentIds.shape.length !== 1) {\n    throw new Error(`Segment ids should be a vector but received shape\n              ${segmentIds.shape}`);\n  }\n  const $data = backend2.readSync(data.dataId);\n  const $indices = backend2.readSync(indices.dataId);\n  const $segmentIds = backend2.readSync(segmentIds.dataId);\n  const [outputData, outputDataShape] = sparseSegmentReductionImplCPU($data, data.shape, data.dtype, $indices, $segmentIds, true);\n  return backend2.makeTensorInfo(outputDataShape, data.dtype, outputData);\n}\nvar sparseSegmentMeanConfig2 = {\n  kernelName: SparseSegmentMean,\n  backendName: \"webgl\",\n  kernelFunc: sparseSegmentMean3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SparseSegmentSum.js\nfunction sparseSegmentSum3(args) {\n  const { inputs, backend: backend2 } = args;\n  const { data, indices, segmentIds } = inputs;\n  if (data.shape.length < 1) {\n    throw new Error(`Data should be at least 1 dimensional but received scalar`);\n  }\n  if (indices.shape.length !== 1) {\n    throw new Error(`Indices should be a vector but received shape\n             ${indices.shape}`);\n  }\n  if (segmentIds.shape.length !== 1) {\n    throw new Error(`Segment ids should be a vector but received shape\n             ${segmentIds.shape}`);\n  }\n  const $data = backend2.readSync(data.dataId);\n  const $indices = backend2.readSync(indices.dataId);\n  const $segmentIds = backend2.readSync(segmentIds.dataId);\n  const [outputData, outputDataShape] = sparseSegmentReductionImplCPU($data, data.shape, data.dtype, $indices, $segmentIds);\n  return backend2.makeTensorInfo(outputDataShape, data.dtype, outputData);\n}\nvar sparseSegmentSumConfig2 = {\n  kernelName: SparseSegmentSum,\n  backendName: \"webgl\",\n  kernelFunc: sparseSegmentSum3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SparseToDense.js\nfunction sparseToDense3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { sparseIndices, sparseValues, defaultValue } = inputs;\n  const { outputShape } = attrs;\n  const { sliceRank, numUpdates, sliceSize, strides, outputSize } = backend_util_exports.calculateShapes(sparseValues, sparseIndices, outputShape);\n  const sumDupeIndices = false;\n  if (sparseValues.dtype === \"string\") {\n    const indicesBuf = backend2.bufferSync(sparseIndices);\n    const updatesBuf = backend2.bufferSync(sparseValues);\n    const $defaultValue = util_exports.decodeString(backend2.readSync(defaultValue.dataId)[0]);\n    const outBuf = scatterImplCPU(indicesBuf, updatesBuf, outputShape, outputSize, sliceSize, numUpdates, sliceRank, strides, $defaultValue, sumDupeIndices);\n    return backend2.makeTensorInfo(outputShape, outBuf.dtype, outBuf.values);\n  }\n  const program = new ScatterProgram(numUpdates, sliceRank, sparseIndices.shape.length, sparseValues.shape.length, strides, [outputSize, 1], sumDupeIndices);\n  const res = backend2.runWebGLProgram(program, [sparseValues, sparseIndices, defaultValue], sparseValues.dtype);\n  const reshaped = reshape4({ inputs: { x: res }, backend: backend2, attrs: { shape: outputShape } });\n  backend2.disposeIntermediateTensorInfo(res);\n  return reshaped;\n}\nvar sparseToDenseConfig2 = {\n  kernelName: SparseToDense,\n  backendName: \"webgl\",\n  kernelFunc: sparseToDense3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SplitV.js\nfunction splitV2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { numOrSizeSplits, axis } = attrs;\n  const $axis = util_exports.parseAxisParam(axis, x.shape)[0];\n  const splitSizes = backend_util_exports.prepareSplitSize(x, numOrSizeSplits, $axis);\n  const xRank = x.shape.length;\n  const begin = new Array(xRank).fill(0);\n  const size = x.shape.slice();\n  return splitSizes.map((s2) => {\n    const sliceSize = [...size];\n    sliceSize[$axis] = s2;\n    const sliceT = slice3({ inputs: { x }, backend: backend2, attrs: { begin, size: sliceSize } });\n    begin[$axis] += s2;\n    return sliceT;\n  });\n}\nvar splitVConfig2 = {\n  kernelName: SplitV,\n  backendName: \"webgl\",\n  kernelFunc: splitV2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Sqrt.js\nvar SQRT = `return sqrt(x);`;\nvar sqrt3 = unaryKernelFunc2({ opSnippet: SQRT, packedOpSnippet: SQRT, cpuKernelImpl: sqrtImplCPU });\nvar sqrtConfig2 = {\n  kernelName: Sqrt,\n  backendName: \"webgl\",\n  kernelFunc: sqrt3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Square.js\nvar SQUARE = `return x * x;`;\nvar square3 = unaryKernelFunc2({ opSnippet: SQUARE });\nvar squareConfig2 = {\n  kernelName: Square,\n  backendName: \"webgl\",\n  kernelFunc: square3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/SquaredDifference.js\nvar SQUARED_DIFFERENCE = \"return (a - b) * (a - b);\";\nvar squaredDifference3 = binaryKernelFunc2({ opSnippet: SQUARED_DIFFERENCE, packedOpSnippet: SQUARED_DIFFERENCE });\nvar squaredDifferenceConfig2 = {\n  kernelName: SquaredDifference,\n  backendName: \"webgl\",\n  kernelFunc: squaredDifference3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Step.js\nfunction step3({ inputs, attrs, backend: backend2 }) {\n  const { x } = inputs;\n  const opSnippet = CHECK_NAN_SNIPPET + `\n    return x > 0.0 ? 1.0 : float(${attrs.alpha});\n  `;\n  const program = new UnaryOpProgram(x.shape, opSnippet);\n  return backend2.runWebGLProgram(program, [x], x.dtype);\n}\nvar stepConfig2 = {\n  kernelName: Step,\n  backendName: \"webgl\",\n  kernelFunc: step3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/strided_slice_gpu.js\nvar StridedSliceProgram = class {\n  constructor(begin, strides, size) {\n    this.variableNames = [\"x\"];\n    this.outputShape = size;\n    const rank = size.length;\n    const inputDtype = getCoordsDataType(size.length);\n    const dtype = getCoordsDataType(size.length);\n    let newCoords = \"\";\n    if (rank === 1) {\n      newCoords = \"coords * strides + begin\";\n    } else {\n      let outputAxis = 0;\n      newCoords = size.map((_, i2) => {\n        outputAxis++;\n        return size.length === 1 ? `coords * strides[${i2}] + begin[${i2}]` : `coords[${outputAxis - 1}] * strides[${i2}] + begin[${i2}]`;\n      }).join(\",\");\n    }\n    this.userCode = `\n      ${inputDtype} begin = ${inputDtype}(${begin});\n      ${inputDtype} strides = ${inputDtype}(${strides});\n\n      void main() {\n        ${dtype} coords = getOutputCoords();\n        setOutput(getX(${newCoords}));\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/StridedSlice.js\nfunction stridedSlice3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask } = attrs;\n  const { finalShapeSparse, finalShape, isIdentity, sliceDim0, isSimpleSlice, begin: $begin, end: $end, strides: $strides } = slice_util_exports.sliceInfo(x.shape, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask);\n  let result;\n  if (isIdentity) {\n    result = reshape4({ inputs: { x }, backend: backend2, attrs: { shape: finalShape } });\n  } else if (sliceDim0 || isSimpleSlice) {\n    util_exports.assert(x.shape.length >= 1, () => `Input must have rank at least 1, got: ${x.shape.length}`);\n    const size = slice_util_exports.computeOutShape($begin, $end, $strides);\n    const sliced = slice3({ inputs: { x }, backend: backend2, attrs: { begin: $begin, size } });\n    result = reshape4({ inputs: { x: sliced }, backend: backend2, attrs: { shape: finalShape } });\n    backend2.disposeIntermediateTensorInfo(sliced);\n  } else {\n    const shouldExecuteOnCPU = backend2.shouldExecuteOnCPU([x]);\n    if (shouldExecuteOnCPU) {\n      const values = backend2.readSync(x.dataId);\n      const xBuf = buffer(x.shape, x.dtype, values);\n      const resultValues = stridedSliceImplCPU(finalShapeSparse, xBuf, $strides, $begin);\n      result = backend2.makeTensorInfo(finalShape, x.dtype, resultValues.values);\n    } else {\n      const program = new StridedSliceProgram($begin, $strides, finalShapeSparse);\n      result = backend2.runWebGLProgram(program, [x], x.dtype);\n    }\n  }\n  const resultReshaped = reshape4({ inputs: { x: result }, backend: backend2, attrs: { shape: finalShape } });\n  backend2.disposeIntermediateTensorInfo(result);\n  return resultReshaped;\n}\nvar stridedSliceConfig2 = {\n  kernelName: StridedSlice,\n  backendName: \"webgl\",\n  kernelFunc: stridedSlice3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/StringNGrams.js\nfunction stringNGrams3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { separator, nGramWidths, leftPad, rightPad: rightPad2, padWidth, preserveShortSequences } = attrs;\n  const { data, dataSplits } = inputs;\n  const $data = backend2.readSync(data.dataId);\n  const $dataSplits = backend2.readSync(dataSplits.dataId);\n  const [nGrams, nGramsSplits] = stringNGramsImplCPU($data, $dataSplits, separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences);\n  return [\n    backend2.makeTensorInfo([nGrams.length], \"string\", nGrams),\n    backend2.makeTensorInfo(dataSplits.shape, \"int32\", nGramsSplits)\n  ];\n}\nvar stringNGramsConfig2 = {\n  kernelName: StringNGrams,\n  backendName: \"webgl\",\n  kernelFunc: stringNGrams3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/StringSplit.js\nfunction stringSplit3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { skipEmpty } = attrs;\n  const { input: input2, delimiter } = inputs;\n  if (input2.dtype !== \"string\") {\n    throw new Error(\"Input must be of datatype string\");\n  }\n  if (input2.shape.length !== 1) {\n    throw new Error(`Input must be a vector, got shape: ${input2.shape}`);\n  }\n  if (delimiter.shape.length !== 0) {\n    throw new Error(`Delimiter must be a scalar, got shape: ${delimiter.shape}`);\n  }\n  const $input = backend2.readSync(input2.dataId);\n  const $delimiter = backend2.readSync(delimiter.dataId)[0];\n  const [indices, values, shape] = stringSplitImplCPU($input, $delimiter, skipEmpty);\n  const outputSize = values.length;\n  return [\n    backend2.makeTensorInfo([outputSize, 2], \"int32\", indices),\n    backend2.makeTensorInfo([outputSize], \"string\", values),\n    backend2.makeTensorInfo([2], \"int32\", new Int32Array(shape))\n  ];\n}\nvar stringSplitConfig2 = {\n  kernelName: StringSplit,\n  backendName: \"webgl\",\n  kernelFunc: stringSplit3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/StringToHashBucketFast.js\nfunction stringToHashBucketFast3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { numBuckets } = attrs;\n  const { input: input2 } = inputs;\n  if (input2.dtype !== \"string\") {\n    throw new Error(\"Input must be of datatype string\");\n  }\n  if (numBuckets <= 0) {\n    throw new Error(`Number of buckets must be at least 1`);\n  }\n  const $input = backend2.readSync(input2.dataId);\n  const output = stringToHashBucketFastImplCPU($input, numBuckets);\n  return backend2.makeTensorInfo(input2.shape, \"int32\", output);\n}\nvar stringToHashBucketFastConfig2 = {\n  kernelName: StringToHashBucketFast,\n  backendName: \"webgl\",\n  kernelFunc: stringToHashBucketFast3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Tan.js\nvar TAN = `return tan(x);`;\nvar tan3 = unaryKernelFunc2({ opSnippet: TAN });\nvar tanConfig2 = {\n  kernelName: Tan,\n  backendName: \"webgl\",\n  kernelFunc: tan3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Tanh.js\nvar TANH = `\n  float e2x = exp(-2.0 * abs(x));\n  return sign(x) * (1.0 - e2x) / (1.0 + e2x);\n`;\nvar tanh4 = unaryKernelFunc2({ opSnippet: TANH });\nvar tanhConfig2 = {\n  kernelName: Tanh,\n  backendName: \"webgl\",\n  kernelFunc: tanh4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/tile_gpu.js\nvar TileProgram = class {\n  constructor(aShape, reps) {\n    this.variableNames = [\"A\"];\n    const outputShape = new Array(aShape.length);\n    for (let i2 = 0; i2 < outputShape.length; i2++) {\n      outputShape[i2] = aShape[i2] * reps[i2];\n    }\n    this.outputShape = outputShape;\n    this.rank = outputShape.length;\n    const dtype = getCoordsDataType(this.rank);\n    const sourceCoords = getSourceCoords3(aShape);\n    this.userCode = `\n      void main() {\n        ${dtype} resRC = getOutputCoords();\n        setOutput(getA(${sourceCoords}));\n      }\n    `;\n  }\n};\nfunction getSourceCoords3(aShape) {\n  const rank = aShape.length;\n  if (rank > 5) {\n    throw Error(`Tile for rank ${rank} is not yet supported`);\n  }\n  if (rank === 1) {\n    return `imod(resRC, ${aShape[0]})`;\n  }\n  const currentCoords = [\"resRC.x\", \"resRC.y\", \"resRC.z\", \"resRC.w\", \"resRC.u\"];\n  const sourceCoords = [];\n  for (let i2 = 0; i2 < aShape.length; i2++) {\n    sourceCoords.push(`imod(${currentCoords[i2]}, ${aShape[i2]})`);\n  }\n  return sourceCoords.join();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Tile.js\nfunction tile4(params) {\n  const { inputs, backend: backend2, attrs } = params;\n  const { x } = inputs;\n  const { reps } = attrs;\n  if (x.dtype === \"string\" || x.shape.length > 5) {\n    const data = backend2.readSync(x.dataId);\n    const value = x.dtype === \"string\" ? data.map((d) => util_exports.decodeString(d)) : data;\n    const buf = buffer(x.shape, x.dtype, value);\n    const outBuf = tileImplCPU(buf, reps);\n    return backend2.makeTensorInfo(outBuf.shape, outBuf.dtype, outBuf.values);\n  }\n  const program = new TileProgram(x.shape, reps);\n  const output = backend2.runWebGLProgram(program, [x], x.dtype);\n  return output;\n}\nvar tileConfig2 = {\n  kernelName: Tile,\n  backendName: \"webgl\",\n  kernelFunc: tile4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/top_k_gpu.js\nvar SwapProgram = class {\n  constructor(shape) {\n    this.variableNames = [\"x\", \"indices\"];\n    this.customUniforms = [\n      { name: \"n\", type: \"int\" },\n      { name: \"firstPass\", type: \"int\" },\n      { name: \"negativeInf\", type: \"float\" },\n      { name: \"dir\", type: \"int\" },\n      { name: \"inc\", type: \"int\" }\n    ];\n    this.outputShape = shape;\n    this.userCode = `\n       void main() {\n         ivec2 coords = getOutputCoords();\n         int batch = coords[0];\n         int elemIdx = coords[1];\n\n         // We compare elements pair-wise within a group of size 2 * inc.\n         // The comparing rule for each group alternates between ascending\n         // and descending. Within each group, we compare each pair at\n         // positions i and i+inc. To decide whether an element at position i\n         // is x0 or x1, we mod it by 2 * inc, if the result is smaller than\n         // inc, it is in the first half of the group, we denote it as x0,\n         // otherwise we denote it as x1.\n         // For example, as shown in the Bitonic top K paper referenced above,\n         // Figure5(a) shows that element[1] is in the\n         // second half of the group when group size is 2, but it is in the\n         // first half of the group when group size is 4.\n\n         bool isFirstInPair = imod(elemIdx, 2 * inc) < inc;\n         int i = isFirstInPair ? elemIdx : elemIdx - inc;\n\n         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));\n         int i1 = firstPass == 1 ? i + inc : int(getIndices(batch, i + inc));\n         float x0 = i0 < n ? getX(batch, i0) : negativeInf;\n         float x1 = i1 < n ? getX(batch, i1) : negativeInf;\n\n         // Denotes which direction indices are in (ascending or descending).\n         bool reverse = imod(elemIdx, 2 * dir) >= dir;\n         bool isGreater = x0 > x1 || (x0 == x1 && i1 > i0);\n         if (reverse == isGreater) { // Elements in opposite order of direction\n           int iTemp = i0;\n           i0 = i1;\n           i1 = iTemp;\n         }\n         if (isFirstInPair) {\n            setOutput(float(i0));\n         } else {\n            setOutput(float(i1));\n         }\n       }\n     `;\n  }\n};\nvar MergeProgram = class {\n  constructor(shape) {\n    this.variableNames = [\"x\", \"indices\"];\n    this.customUniforms = [\n      { name: \"n\", type: \"int\" },\n      { name: \"firstPass\", type: \"int\" },\n      { name: \"k\", type: \"int\" }\n    ];\n    this.outputShape = shape;\n    this.userCode = `\n    void main() {\n         // Takes max of indices (0, k), (1, k + 1), (2, k + 2) ...\n         ivec2 coords = getOutputCoords();\n         int batch = coords[0];\n         int elemIdx = coords[1];\n\n         // The output size is half of the previous size.\n         // If the previous sequence is | | | | _ _ _ _  | | | |  _ _ _ _ (k=4),\n         // we only need to output the indices at positions |, the indices at\n         // positions _ can be thrown away, see Figure5(b) After Phase 2\n         // (Merge phase) in the Bitonic Top K paper referenced above.\n         // For example, the paper shows we only need to output the orange bars.\n         // The output sequence should look like this | | | | | | | |.\n         // Because the sequence is halved, to map the output index back\n         // to the previous sequence to find the corresponding value,\n         // we need to double the index. When we double the index,\n         // we basically interpolate a position, so 2i looks like\n         // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k position\n         // of each 2k positions by - elemIdx % k. E.g. for output at\n         // index 4,5,6,7, we want to get the corresponding element at\n         // original index 8,9,10,11, for output at index 8,9,10,11,\n         // we want to get the corresponding element at original index\n         // 16,17,18,19, so on and so forth.\n\n         int i = elemIdx < k ? elemIdx : (elemIdx * 2 - imod(elemIdx, k));\n         int i0 = firstPass == 1 ? i : int(getIndices(batch, i));\n         int i1 = firstPass == 1 ? i + k : int(getIndices(batch, i + k));\n\n         float x0 = getX(batch, i0);\n         float x1 = i1 < n ? getX(batch, i1) : x0;\n\n         setOutput(x0 >= x1 ? float(i0) : float(i1));\n       }\n     `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/TopK.js\nfunction disposeIntermediateTensorInfoOrNull(backend2, tensorInfo) {\n  if (tensorInfo !== null) {\n    backend2.disposeIntermediateTensorInfo(tensorInfo);\n  }\n}\nfunction roundUpToPow2(num) {\n  let pow22 = 1;\n  while (pow22 < num) {\n    pow22 *= 2;\n  }\n  return pow22;\n}\nfunction topK2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { k, sorted } = attrs;\n  const TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD = env().getNumber(\"TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD\");\n  const TOPK_K_CPU_HANDOFF_THRESHOLD = env().getNumber(\"TOPK_K_CPU_HANDOFF_THRESHOLD\");\n  const xShape = x.shape;\n  const lastDim = xShape[xShape.length - 1];\n  if (backend2.shouldExecuteOnCPU([x]) || lastDim < TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD || k > TOPK_K_CPU_HANDOFF_THRESHOLD) {\n    const xVals = backend2.readSync(x.dataId);\n    const [allTopKVals, allTopKIndices] = topKImplCPU(xVals, xShape, x.dtype, k, sorted);\n    return [\n      backend2.makeTensorInfo(allTopKVals.shape, allTopKVals.dtype, allTopKVals.values),\n      backend2.makeTensorInfo(allTopKIndices.shape, allTopKIndices.dtype, allTopKIndices.values)\n    ];\n  }\n  if (k === 0) {\n    xShape[xShape.length - 1] = 0;\n    return [\n      backend2.makeTensorInfo(xShape, x.dtype, []),\n      backend2.makeTensorInfo(xShape, \"int32\", [])\n    ];\n  }\n  if (lastDim === 1) {\n    return [\n      x,\n      fill3({ attrs: { shape: xShape, dtype: \"int32\", value: 0 }, backend: backend2 })\n    ];\n  }\n  const xtexData = backend2.texData.get(x.dataId);\n  const xIsPacked = xtexData !== null && xtexData.isPacked;\n  const xUnPacked = xIsPacked ? backend2.unpackTensor(x) : x;\n  const xSize = util_exports.sizeFromShape(xShape);\n  const batch = xSize / lastDim;\n  const x2D = reshape4({ inputs: { x: xUnPacked }, attrs: { shape: [batch, lastDim] }, backend: backend2 });\n  if (xIsPacked) {\n    disposeIntermediateTensorInfoOrNull(backend2, xUnPacked);\n  }\n  const kPow2 = roundUpToPow2(k);\n  const lastDimPow2 = roundUpToPow2(lastDim);\n  let indices = null;\n  const getInputs = () => indices === null ? [x2D, x2D] : [x2D, indices];\n  const runSwap = (dir, inc, shape) => {\n    const inputs2 = getInputs();\n    const program = new SwapProgram(shape);\n    const fistPass = indices === null ? 1 : 0;\n    const customValues = [[lastDim], [fistPass], [Number.NEGATIVE_INFINITY], [dir], [inc]];\n    const prevIndices2 = indices;\n    indices = backend2.runWebGLProgram(program, inputs2, \"int32\", customValues);\n    disposeIntermediateTensorInfoOrNull(backend2, prevIndices2);\n  };\n  for (let len = 1; len < kPow2; len *= 2) {\n    const dir = len * 2;\n    for (let inc = len; inc >= 1; inc /= 2) {\n      runSwap(dir, inc, [batch, lastDimPow2]);\n    }\n  }\n  for (let indicesSize = lastDimPow2; indicesSize > kPow2; indicesSize /= 2) {\n    const inputs2 = getInputs();\n    const mergeProgram = new MergeProgram([batch, indicesSize / 2]);\n    const firstPass = indices === null ? 1 : 0;\n    const customValues = [[lastDim], [firstPass], [kPow2]];\n    const prevIndices2 = indices;\n    indices = backend2.runWebGLProgram(mergeProgram, inputs2, \"int32\", customValues);\n    disposeIntermediateTensorInfoOrNull(backend2, prevIndices2);\n    const len = kPow2 / 2;\n    const dir = len * 2;\n    for (let inc = len; inc >= 1; inc /= 2) {\n      runSwap(dir, inc, indices.shape);\n    }\n  }\n  let prevIndices = indices;\n  indices = slice3({ inputs: { x: indices }, backend: backend2, attrs: { begin: 0, size: [batch, k] } });\n  disposeIntermediateTensorInfoOrNull(backend2, prevIndices);\n  let values = gatherV22({ inputs: { x: x2D, indices }, backend: backend2, attrs: { axis: 1, batchDims: 1 } });\n  disposeIntermediateTensorInfoOrNull(backend2, x2D);\n  const newShape = xShape.slice(0, -1);\n  newShape.push(k);\n  prevIndices = indices;\n  indices = reshape4({ inputs: { x: indices }, attrs: { shape: newShape }, backend: backend2 });\n  disposeIntermediateTensorInfoOrNull(backend2, prevIndices);\n  const prevValues = values;\n  values = reshape4({ inputs: { x: values }, attrs: { shape: newShape }, backend: backend2 });\n  disposeIntermediateTensorInfoOrNull(backend2, prevValues);\n  return [values, indices];\n}\nvar topKConfig2 = {\n  kernelName: TopK,\n  backendName: \"webgl\",\n  kernelFunc: topK2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/transform_gpu.js\nvar TransformProgram = class {\n  constructor(imageHeight, imageWidth, interpolation, fillMode, fillValue, outShape) {\n    this.variableNames = [\"Image\", \"Transforms\"];\n    this.outputShape = outShape;\n    const interpolationModeId = interpolation === \"nearest\" ? 1 : 2;\n    let fillModeId;\n    switch (fillMode) {\n      case \"constant\":\n        fillModeId = 1;\n        break;\n      case \"reflect\":\n        fillModeId = 2;\n        break;\n      case \"wrap\":\n        fillModeId = 3;\n        break;\n      case \"nearest\":\n        fillModeId = 4;\n        break;\n      default:\n        fillModeId = 1;\n        break;\n    }\n    this.userCode = `\n            float mapCoord(float outCoord, float len) {\n              float inCoord = outCoord;\n              if(${fillModeId} == 2) {\n                if (inCoord < 0.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz2 = 2.0 * len;\n                    if (inCoord < sz2) {\n                      inCoord = sz2 * float(int(float(-inCoord / sz2))) +\n                      inCoord;\n                    }\n                    inCoord = inCoord < -len ? inCoord + sz2 : -inCoord - 1.0;\n                  }\n                } else if (inCoord > len - 1.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz2 = 2.0 * len;\n                    inCoord -= sz2 * float(int(float(inCoord / sz2)));\n                    if (inCoord >= len) {\n                      inCoord = sz2 - inCoord - 1.0;\n                    }\n                  }\n                }\n                return clamp(inCoord, 0.0, len - 1.0);\n              } else if (${fillModeId} == 3) {\n                if (inCoord < 0.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz = len - 1.0;\n                    inCoord += len * (float(int(float(-inCoord / sz))) + 1.0);\n                  }\n                } else if (inCoord > len - 1.0) {\n                  if (len <= 1.0) {\n                    inCoord = 0.0;\n                  } else {\n                    float sz = len - 1.0;\n                    inCoord -= len * float(int(float(inCoord / sz)));\n                  }\n                }\n                return clamp(inCoord, 0.0, len - 1.0);\n              } else if (${fillModeId} == 4) {\n                return clamp(outCoord, 0.0, len - 1.0);\n              } else {\n                return outCoord;\n              }\n            }\n\n            float readWithFillValue(int batch, int coordY, int coordX,\n              int channel) {\n              float outputValue;\n              if (0 <= coordY && coordY < ${imageHeight} && 0 <= coordX && coordX < ${imageWidth}) {\n                  outputValue = getImage(batch, coordY, coordX, channel);\n              } else {\n                outputValue = float(${fillValue});\n              }\n              return outputValue;\n            }\n\n            void main() {\n              ivec4 coords = getOutputCoords();\n              float outputValue;\n              int batch = coords[0];\n              int x = coords[2];\n              int y = coords[1];\n              int channel = coords[3];\n              float xf = float(x);\n              float yf = float(y);\n              float a1 = getTransforms(batch, 0);\n              float a2 = getTransforms(batch, 1);\n              float a3 = getTransforms(batch, 2);\n              float b1 = getTransforms(batch, 3);\n              float b2 = getTransforms(batch, 4);\n              float b3 = getTransforms(batch, 5);\n              float c1 = getTransforms(batch, 6);\n              float c2 = getTransforms(batch, 7);\n              float projection = c1 * xf + c2 * yf + 1.0;\n              if (projection == 0.0) {\n                outputValue = float(${fillValue});\n              } else {\n                float inX = (a1 * xf + a2 * yf + a3) / projection;\n                float inY = (b1 * xf + b2 * yf + b3) / projection;\n                float mapX = mapCoord(inX, float(${imageWidth}));\n                float mapY = mapCoord(inY, float(${imageHeight}));\n\n                if (${interpolationModeId} == 1) {\n                  int coordY = int(round(mapY));\n                  int coordX = int(round(mapX));\n                  outputValue = readWithFillValue(batch, coordY, coordX,\n                    channel);\n                } else {\n                  float yFloor = floor(mapY);\n                  float xFloor = floor(mapX);\n                  float yCeil = yFloor + 1.0;\n                  float xCeil = xFloor + 1.0;\n                  float valueYFloor = (xCeil - mapX) *\n                  readWithFillValue(batch, int(yFloor), int(xFloor), channel) +\n                  (mapX - xFloor) *\n                  readWithFillValue(batch, int(yFloor), int(xCeil), channel);\n                  float valueYCeil = (xCeil - mapX) *\n                  readWithFillValue(batch, int(yCeil), int(xFloor), channel) +\n                  (mapX - xFloor) *\n                  readWithFillValue(batch, int(yCeil), int(xCeil), channel);\n                  outputValue = (yCeil - mapY) * valueYFloor +\n                  (mapY - yFloor) * valueYCeil;\n                }\n              }\n              setOutput(outputValue);\n            }\n        `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Transform.js\nfunction transform3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { image: image2, transforms } = inputs;\n  const { interpolation, fillMode, fillValue, outputShape } = attrs;\n  const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n  const [outHeight, outWidth] = outputShape != null ? outputShape : [imageHeight, imageWidth];\n  const outShape = [\n    batch,\n    outHeight,\n    outWidth,\n    numChannels\n  ];\n  const program = new TransformProgram(imageHeight, imageWidth, interpolation, fillMode, fillValue, outShape);\n  return backend2.runWebGLProgram(program, [image2, transforms], \"float32\");\n}\nvar transformConfig2 = {\n  kernelName: Transform,\n  backendName: \"webgl\",\n  kernelFunc: transform3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Unique.js\nfunction unique4(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { axis } = attrs;\n  const { x } = inputs;\n  assertNotComplex2(x, \"unique\");\n  console.warn(\"WARNING: \", \"UI might be locked temporarily as data is being downloaded\");\n  const values = backend2.readSync(x.dataId);\n  const { outputValues, outputShape, indices } = uniqueImplCPU(values, axis, x.shape, x.dtype);\n  return [\n    backend2.makeTensorInfo(outputShape, x.dtype, outputValues),\n    backend2.makeTensorInfo([indices.length], \"int32\", indices)\n  ];\n}\nvar uniqueConfig2 = {\n  kernelName: Unique,\n  backendName: \"webgl\",\n  kernelFunc: unique4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/Unpack.js\nfunction unpack2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { value } = inputs;\n  let { axis } = attrs;\n  if (axis < 0) {\n    axis += value.shape.length;\n  }\n  const x = value;\n  const xRank = x.shape.length;\n  const num = value.shape[axis];\n  const outShape = new Array(xRank - 1);\n  let outIndex = 0;\n  for (let i2 = 0; i2 < xRank; i2++) {\n    if (i2 !== axis) {\n      outShape[outIndex++] = x.shape[i2];\n    }\n  }\n  const toDispose = [];\n  const begin = new Array(xRank).fill(0);\n  const size = x.shape.slice();\n  size[axis] = 1;\n  const res = new Array(num);\n  for (let i2 = 0; i2 < res.length; i2++) {\n    begin[axis] = i2;\n    const sliced = slice3({ inputs: { x }, backend: backend2, attrs: { begin, size } });\n    const reshaped = reshape4({ inputs: { x: sliced }, backend: backend2, attrs: { shape: outShape } });\n    res[i2] = reshaped;\n    toDispose.push(sliced);\n  }\n  toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return res;\n}\nvar unpackConfig2 = {\n  kernelName: Unpack,\n  backendName: \"webgl\",\n  kernelFunc: unpack2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/segment_gpu.js\nvar SegmentOpProgram = class {\n  constructor(segOpInfo, segOpType) {\n    this.variableNames = [\"x\", \"segmentIds\"];\n    const windowSize = segOpInfo.windowSize;\n    const batchSize = segOpInfo.batchSize;\n    const inSize = segOpInfo.inSize;\n    const numSegments = segOpInfo.numSegments;\n    const outSize = numSegments * Math.ceil(inSize / windowSize);\n    this.outputShape = [batchSize, outSize];\n    const initializationValue = \"0.0\";\n    const returnValue = `sumValue`;\n    const windowSizeNearestVec4 = Math.floor(windowSize / 4) * 4;\n    const windowSizeVec4Remainder = windowSize % 4;\n    const updateSnippet = `\n        sumValue += dot(values, segFilter);\n    `;\n    let checkValueOutOfBounds = \"\";\n    if (inSize % windowSize > 0) {\n      checkValueOutOfBounds = `\n        if (inIdx < 0 || inIdx >= ${inSize}) {\n          return initializationValue;\n        }\n      `;\n    }\n    let checkSegmentIdOutOfBounds = \"\";\n    if (inSize % windowSize > 0) {\n      checkSegmentIdOutOfBounds = `\n        if (inIdx < 0 || inIdx >= ${inSize}) {\n          return -1.0;\n        }\n      `;\n    }\n    this.userCode = `\n      const float initializationValue = ${initializationValue};\n\n      float getValue(int batch, int inIdx) {\n        ${checkValueOutOfBounds}\n        return getX(batch, inIdx);\n      }\n\n      float getSegmentIdAtIndex(int inIdx) {\n        ${checkSegmentIdOutOfBounds}\n        return getSegmentIds(inIdx);\n      }\n\n      void main() {\n        ivec2 coords = getOutputCoords();\n        int batch = coords[0];\n        int outIdx = coords[1];\n        int inOffset = int(floor(float(outIdx) / float(\n          ${numSegments})) * float(${windowSize}));\n        int currentSeg = int(mod(float(outIdx), float(${numSegments})));\n\n        float sumValue = 0.0;\n\n        for (int i = 0; i < ${windowSizeNearestVec4}; i += 4) {\n          int inIdx = inOffset + i;\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            getValue(batch, inIdx + 3)\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 3)) == currentSeg ? 1 : 0\n          );\n\n          ${updateSnippet}\n        }\n\n        int inIdx = inOffset + ${windowSizeNearestVec4};\n        if (${windowSizeVec4Remainder === 1}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            initializationValue,\n            initializationValue,\n            initializationValue\n          );\n\n          int inIdxSeg = int(getSegmentIdAtIndex(inIdx));\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            0,\n            0,\n            0\n          );\n\n          ${updateSnippet}\n        } else if (${windowSizeVec4Remainder === 2}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            initializationValue,\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n              0,\n              0\n          );\n\n          ${updateSnippet}\n        } else if (${windowSizeVec4Remainder === 3}) {\n          vec4 values = vec4(\n            getValue(batch, inIdx),\n            getValue(batch, inIdx + 1),\n            getValue(batch, inIdx + 2),\n            initializationValue\n          );\n\n          vec4 segFilter = vec4(\n            int(getSegmentIdAtIndex(inIdx)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 1)) == currentSeg ? 1 : 0,\n            int(getSegmentIdAtIndex(inIdx + 2)) == currentSeg ? 1 : 0,\n            0\n          );\n\n          ${updateSnippet}\n        }\n        setOutput(${returnValue});\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/kernels/UnsortedSegmentSum.js\nfunction unsortedSegmentSum3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, segmentIds } = inputs;\n  const { numSegments } = attrs;\n  const xRank = x.shape.length;\n  const toDispose = [];\n  let axis = 0;\n  const permutation = backend_util_exports.getAxesPermutation([axis], xRank);\n  let permutedX = x;\n  if (permutation != null) {\n    permutedX = transpose3({ inputs: { x }, backend: backend2, attrs: { perm: permutation } });\n    toDispose.push(permutedX);\n    axis = backend_util_exports.getInnerMostAxes(1, xRank)[0];\n  }\n  const outShape = backend_util_exports.segment_util.computeOutShape(permutedX.shape, axis, numSegments);\n  const inSize = util_exports.sizeFromShape([permutedX.shape[axis]]);\n  const a2D = reshape4({ inputs: { x: permutedX }, backend: backend2, attrs: { shape: [-1, inSize] } });\n  toDispose.push(a2D);\n  const outputDType = sumOutType(x.dtype);\n  const segOpCompute = (x2, segOpType, segmentIds2, dtype, numSegments2) => {\n    const batchSize = x2.shape[0];\n    const inSize2 = x2.shape[1];\n    const windowSize = backend_util_exports.segment_util.segOpComputeOptimalWindowSize(inSize2, numSegments2);\n    const segOpInfo = { windowSize, inSize: inSize2, batchSize, numSegments: numSegments2 };\n    const program = new SegmentOpProgram(segOpInfo, segOpType);\n    const output = backend2.compileAndRun(program, [x2, segmentIds2], dtype);\n    toDispose.push(output);\n    if (output.shape[1] === numSegments2) {\n      return output;\n    }\n    const rangeInfo = range4({\n      backend: backend2,\n      attrs: { start: 0, stop: numSegments2, step: 1, dtype: \"float32\" }\n    });\n    const tileInfo = tile4({\n      inputs: { x: rangeInfo },\n      backend: backend2,\n      attrs: { reps: [inSize2 / windowSize] }\n    });\n    toDispose.push(rangeInfo);\n    toDispose.push(tileInfo);\n    const result2 = segOpCompute(output, segOpType, tileInfo, dtype, numSegments2);\n    return result2;\n  };\n  const segOpResult = segOpCompute(a2D, \"unsortedSegmentSum\", segmentIds, outputDType, numSegments);\n  const reshaped = reshape4({ inputs: { x: segOpResult }, backend: backend2, attrs: { shape: outShape } });\n  let result = reshaped;\n  if (permutation != null) {\n    toDispose.push(reshaped);\n    const perm = backend_util_exports.getUndoAxesPermutation(permutation);\n    result = transpose3({ inputs: { x: result }, backend: backend2, attrs: { perm } });\n  }\n  toDispose.forEach((t2) => backend2.disposeIntermediateTensorInfo(t2));\n  return result;\n}\nvar unsortedSegmentSumConfig2 = {\n  kernelName: UnsortedSegmentSum,\n  backendName: \"webgl\",\n  kernelFunc: unsortedSegmentSum3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgl@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgl/dist/register_all_kernels.js\nvar kernelConfigs2 = [\n  _fusedMatMulConfig2,\n  absConfig2,\n  acosConfig2,\n  acoshConfig2,\n  addConfig2,\n  addNConfig2,\n  allConfig2,\n  anyConfig2,\n  argMaxConfig2,\n  argMinConfig2,\n  asinConfig2,\n  asinhConfig2,\n  atanConfig2,\n  atan2Config2,\n  atanhConfig2,\n  avgPoolConfig2,\n  avgPool3DConfig2,\n  avgPool3DGradConfig3,\n  avgPoolGradConfig3,\n  batchMatMulConfig2,\n  batchNormConfig2,\n  batchToSpaceNDConfig2,\n  bincountConfig2,\n  broadcastArgsConfig2,\n  castConfig2,\n  ceilConfig2,\n  clipByValueConfig2,\n  complexConfig2,\n  complexAbsConfig2,\n  concatConfig2,\n  conv2DConfig2,\n  conv2DBackpropFilterConfig2,\n  conv2DBackpropInputConfig2,\n  conv3DConfig2,\n  conv3DBackpropFilterV2Config2,\n  conv3DBackpropInputConfig,\n  cosConfig2,\n  coshConfig2,\n  cropAndResizeConfig2,\n  cumprodConfig2,\n  cumsumConfig2,\n  denseBincountConfig2,\n  depthToSpaceConfig2,\n  depthwiseConv2dNativeConfig2,\n  depthwiseConv2dNativeBackpropFilterConfig2,\n  depthwiseConv2dNativeBackpropInputConfig2,\n  diagConfig2,\n  dilation2DConfig2,\n  einsumConfig2,\n  eluConfig2,\n  eluGradConfig3,\n  equalConfig2,\n  erfConfig2,\n  expConfig2,\n  expandDimsConfig2,\n  expm1Config2,\n  fftConfig2,\n  fillConfig2,\n  flipLeftRightConfig2,\n  floorConfig2,\n  floorDivConfig2,\n  fromPixelsConfig,\n  fusedConv2DConfig2,\n  fusedDepthwiseConv2DConfig2,\n  gatherNdConfig2,\n  gatherV2Config2,\n  greaterConfig2,\n  greaterEqualConfig2,\n  identityConfig2,\n  ifftConfig2,\n  imagConfig2,\n  isFiniteConfig2,\n  isInfConfig2,\n  isNaNConfig2,\n  leakyReluConfig2,\n  lessConfig2,\n  lessEqualConfig2,\n  linSpaceConfig2,\n  logConfig2,\n  log1pConfig2,\n  logicalAndConfig2,\n  logicalNotConfig2,\n  logicalOrConfig2,\n  LRNConfig2,\n  LRNGradConfig2,\n  maxConfig2,\n  maximumConfig2,\n  maxPoolConfig2,\n  maxPool3DConfig2,\n  maxPool3DGradConfig3,\n  maxPoolGradConfig3,\n  maxPoolWithArgmaxConfig2,\n  meanConfig2,\n  minConfig2,\n  minimumConfig2,\n  mirrorPadConfig2,\n  modConfig2,\n  multinomialConfig2,\n  multiplyConfig2,\n  negConfig2,\n  nonMaxSuppressionV3Config2,\n  nonMaxSuppressionV4Config2,\n  nonMaxSuppressionV5Config2,\n  notEqualConfig2,\n  oneHotConfig2,\n  onesLikeConfig2,\n  packConfig2,\n  padV2Config2,\n  powConfig2,\n  preluConfig2,\n  prodConfig2,\n  rangeConfig2,\n  realConfig2,\n  realDivConfig2,\n  reciprocalConfig2,\n  reluConfig2,\n  relu6Config2,\n  reshapeConfig2,\n  resizeBilinearConfig2,\n  resizeBilinearGradConfig3,\n  resizeNearestNeighborConfig2,\n  resizeNearestNeighborGradConfig3,\n  reverseConfig2,\n  rotateWithOffsetConfig2,\n  roundConfig2,\n  rsqrtConfig2,\n  scatterNdConfig2,\n  searchSortedConfig2,\n  selectConfig2,\n  seluConfig2,\n  sigmoidConfig2,\n  signConfig2,\n  sinConfig2,\n  sinhConfig2,\n  sliceConfig2,\n  softmaxConfig2,\n  softplusConfig2,\n  spaceToBatchNDConfig2,\n  sparseFillEmptyRowsConfig2,\n  sparseReshapeConfig2,\n  sparseSegmentMeanConfig2,\n  sparseSegmentSumConfig2,\n  sparseToDenseConfig2,\n  splitVConfig2,\n  sqrtConfig2,\n  squareConfig2,\n  squaredDifferenceConfig2,\n  stepConfig2,\n  stridedSliceConfig2,\n  stringNGramsConfig2,\n  stringSplitConfig2,\n  stringToHashBucketFastConfig2,\n  subConfig2,\n  sumConfig2,\n  tanConfig2,\n  tanhConfig2,\n  tileConfig2,\n  topKConfig2,\n  transformConfig2,\n  transposeConfig2,\n  uniqueConfig2,\n  unpackConfig2,\n  unsortedSegmentSumConfig2,\n  zerosLikeConfig2\n];\nfor (const kernelConfig of kernelConfigs2) {\n  registerKernel(kernelConfig);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/types.js\nvar CppDType;\n(function(CppDType2) {\n  CppDType2[CppDType2[\"float32\"] = 0] = \"float32\";\n  CppDType2[CppDType2[\"int32\"] = 1] = \"int32\";\n  CppDType2[CppDType2[\"bool\"] = 2] = \"bool\";\n  CppDType2[CppDType2[\"string\"] = 3] = \"string\";\n  CppDType2[CppDType2[\"complex64\"] = 4] = \"complex64\";\n})(CppDType || (CppDType = {}));\nvar FusableActivation;\n(function(FusableActivation2) {\n  FusableActivation2[FusableActivation2[\"linear\"] = 0] = \"linear\";\n  FusableActivation2[FusableActivation2[\"relu\"] = 1] = \"relu\";\n  FusableActivation2[FusableActivation2[\"relu6\"] = 2] = \"relu6\";\n  FusableActivation2[FusableActivation2[\"prelu\"] = 3] = \"prelu\";\n  FusableActivation2[FusableActivation2[\"leakyrelu\"] = 4] = \"leakyrelu\";\n  FusableActivation2[FusableActivation2[\"sigmoid\"] = 5] = \"sigmoid\";\n  FusableActivation2[FusableActivation2[\"elu\"] = 6] = \"elu\";\n})(FusableActivation || (FusableActivation = {}));\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/_FusedMatMul.js\nvar wasmFusedMatMul;\nfunction setup(backend2) {\n  wasmFusedMatMul = backend2.wasm.cwrap(_FusedMatMul, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction fusedBatchMatMul(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b, bias, preluActivationWeights } = inputs;\n  if (a.dtype !== \"float32\" || b.dtype !== \"float32\") {\n    throw new Error(`_FusedMatMul for non non-float32 tensors not yet supported.`);\n  }\n  const { transposeA, transposeB, activation: activation2, leakyreluAlpha } = attrs;\n  const aId = backend2.dataIdMap.get(a.dataId).id;\n  const bId = backend2.dataIdMap.get(b.dataId).id;\n  let biasId = 0;\n  if (bias != null) {\n    const biasData = backend2.dataIdMap.get(bias.dataId);\n    if (biasData.shape.length !== 1) {\n      throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${biasData.shape.length}.`);\n    }\n    biasId = biasData.id;\n  }\n  const preluActivationWeightsId = preluActivationWeights == null ? 0 : backend2.dataIdMap.get(preluActivationWeights.dataId).id;\n  const fusedActivation = FusableActivation[activation2];\n  if (fusedActivation == null) {\n    throw new Error(`${activation2} activation not yet supported for FusedConv2D in the wasm backend.`);\n  }\n  const leftDim = transposeA ? a.shape[2] : a.shape[1];\n  const rightDim = transposeB ? b.shape[1] : b.shape[2];\n  const batchDims = broadcast_util_exports.assertAndGetBroadcastShape(a.shape.slice(0, -2), b.shape.slice(0, -2));\n  const out = backend2.makeOutput([...batchDims, leftDim, rightDim], a.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const aShapeBytes = new Uint8Array(new Int32Array(a.shape).buffer);\n  const bShapeBytes = new Uint8Array(new Int32Array(b.shape).buffer);\n  wasmFusedMatMul(aId, aShapeBytes, a.shape.length, bId, bShapeBytes, b.shape.length, transposeA, transposeB, fusedActivation, biasId, preluActivationWeightsId, leakyreluAlpha || 0, outId);\n  return out;\n}\nvar _fusedMatMulConfig3 = {\n  kernelName: _FusedMatMul,\n  backendName: \"wasm\",\n  setupFunc: setup,\n  kernelFunc: fusedBatchMatMul\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/unary_kernel.js\nfunction createUnaryKernelConfig(kernelName, outType) {\n  let wasmFunc9;\n  function setupFunc3(backend2) {\n    wasmFunc9 = backend2.wasm.cwrap(kernelName, null, [\n      \"number\",\n      \"number\",\n      \"number\"\n    ]);\n  }\n  function kernelFunc3(args) {\n    const { backend: backend2, inputs: { x } } = args;\n    const xId = backend2.dataIdMap.get(x.dataId).id;\n    const out = backend2.makeOutput(x.shape, outType || x.dtype);\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    if (util_exports.sizeFromShape(out.shape) === 0) {\n      return out;\n    }\n    wasmFunc9(xId, CppDType[x.dtype], outId);\n    return out;\n  }\n  return { kernelName, backendName: \"wasm\", setupFunc: setupFunc3, kernelFunc: kernelFunc3 };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Abs.js\nvar absConfig3 = createUnaryKernelConfig(Abs);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/binary_kernel.js\nfunction createBinaryKernelConfig(kernelName, supportsFullBroadcast19, dtype) {\n  let wasmFunc9;\n  function setupFunc3(backend2) {\n    wasmFunc9 = backend2.wasm.cwrap(kernelName, null, [\n      \"number\",\n      \"array\",\n      \"number\",\n      \"number\",\n      \"array\",\n      \"number\",\n      \"number\",\n      \"number\"\n    ]);\n  }\n  function kernelFunc3(args) {\n    const { backend: backend2, inputs } = args;\n    const { a, b } = inputs;\n    const aId = backend2.dataIdMap.get(a.dataId).id;\n    const bId = backend2.dataIdMap.get(b.dataId).id;\n    const outputType = dtype != null ? dtype : a.dtype;\n    const newShape = backend_util_exports.assertAndGetBroadcastShape(a.shape, b.shape);\n    const out = backend2.makeOutput(newShape, outputType);\n    if (util_exports.sizeFromShape(newShape) === 0) {\n      return out;\n    }\n    const aShapeBytes = new Uint8Array(new Int32Array(a.shape).buffer);\n    const bShapeBytes = new Uint8Array(new Int32Array(b.shape).buffer);\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    const kernelFunc4 = () => wasmFunc9(aId, aShapeBytes, a.shape.length, bId, bShapeBytes, b.shape.length, CppDType[a.dtype], outId);\n    kernelFunc4();\n    return out;\n  }\n  return { kernelName, backendName: \"wasm\", setupFunc: setupFunc3, kernelFunc: kernelFunc3 };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Add.js\nvar supportsFullBroadcast = true;\nvar addConfig3 = createBinaryKernelConfig(Add, supportsFullBroadcast);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/AddN.js\nvar wasmFunc;\nfunction setupFunc(backend2) {\n  wasmFunc = backend2.wasm.cwrap(AddN, null, [\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction addn(args) {\n  const { inputs, backend: backend2 } = args;\n  const out = backend2.makeOutput(inputs[0].shape, inputs[0].dtype);\n  if (util_exports.sizeFromShape(out.shape) === 0) {\n    return out;\n  }\n  const inputIds = inputs.map((x) => backend2.dataIdMap.get(x.dataId).id);\n  const inputIdsBytes = new Uint8Array(new Int32Array(inputIds).buffer);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmFunc(inputIdsBytes, inputIds.length, CppDType[out.dtype], outId);\n  return out;\n}\nvar addNConfig3 = {\n  kernelName: AddN,\n  backendName: \"wasm\",\n  setupFunc,\n  kernelFunc: addn\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Identity.js\nfunction identity4(args) {\n  const { inputs: { x }, backend: backend2 } = args;\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  const inVals = backend2.typedArrayFromHeap(x);\n  const outVals = backend2.typedArrayFromHeap(out);\n  outVals.set(inVals);\n  return out;\n}\nvar identityConfig3 = {\n  kernelName: Identity,\n  backendName: \"wasm\",\n  kernelFunc: identity4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Transpose.js\nvar wasmTranspose;\nfunction setup2(backend2) {\n  wasmTranspose = backend2.wasm.cwrap(Transpose, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\"\n  ]);\n}\nfunction transpose4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const [reducedShape, perm] = removeOneSizeDims(inputs.x.shape, attrs.perm);\n  let permIsNoOp = true;\n  for (let i2 = 0; i2 < perm.length; i2++) {\n    if (perm[i2] !== i2) {\n      permIsNoOp = false;\n    }\n  }\n  const outShape = computeOutShape4(inputs.x.shape, attrs.perm);\n  const x = {\n    dataId: inputs.x.dataId,\n    shape: reducedShape,\n    dtype: inputs.x.dtype\n  };\n  if (permIsNoOp) {\n    const cloned = identity4({ inputs, backend: backend2 });\n    cloned.shape = outShape;\n    return cloned;\n  }\n  const out = backend2.makeOutput(outShape, x.dtype);\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const permBytes = new Uint8Array(new Int32Array(perm).buffer);\n  const xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);\n  wasmTranspose(xId, xShapeBytes, x.shape.length, CppDType[x.dtype], outId, permBytes, perm.length);\n  return out;\n}\nfunction computeOutShape4(inShape, perm) {\n  const outShape = new Array(inShape.length);\n  for (let i2 = 0; i2 < outShape.length; i2++) {\n    outShape[i2] = inShape[perm[i2]];\n  }\n  return outShape;\n}\nfunction removeOneSizeDims(shape, perm) {\n  const newShape = [];\n  const newPerm = [];\n  for (let i2 = 0; i2 < shape.length; ++i2) {\n    if (shape[i2] !== 1) {\n      newShape.push(shape[i2]);\n    }\n    if (shape[perm[i2]] !== 1) {\n      newPerm.push(perm[i2]);\n    }\n  }\n  for (let i2 = 0; i2 < newPerm.length; ++i2) {\n    let minValIdx = -1;\n    for (let j = 0; j < newPerm.length; ++j) {\n      if (newPerm[j] >= i2 && (minValIdx === -1 || newPerm[minValIdx] > newPerm[j])) {\n        minValIdx = j;\n      }\n    }\n    newPerm[minValIdx] = i2;\n  }\n  return [newShape, newPerm];\n}\nvar transposeConfig3 = {\n  kernelName: Transpose,\n  backendName: \"wasm\",\n  kernelFunc: transpose4,\n  setupFunc: setup2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/kernel_utils.js\nfunction permuteAxesAndTranspose(x, axis, backend2) {\n  const xShape = x.shape;\n  const xRank = x.shape.length;\n  const originalAxes = util_exports.parseAxisParam(axis, xShape);\n  let axes = originalAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  let xTransposed = null;\n  let inputWasTransposed = false;\n  if (permutedAxes != null) {\n    const newShape = new Array(xRank);\n    for (let i2 = 0; i2 < newShape.length; i2++) {\n      newShape[i2] = xShape[permutedAxes[i2]];\n    }\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n    xTransposed = transpose4({ inputs: { x }, attrs: { perm: permutedAxes }, backend: backend2 });\n    const xId = backend2.dataIdMap.get(x.dataId).id;\n    const transposedId = backend2.dataIdMap.get(xTransposed.dataId).id;\n    if (transposedId !== xId) {\n      inputWasTransposed = true;\n    }\n  }\n  return { transposed: xTransposed, originalAxes, axes, inputWasTransposed };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/All.js\nvar wasmAll;\nfunction setup3(backend2) {\n  wasmAll = backend2.wasm.cwrap(All, null, [\"number, number, number\"]);\n}\nfunction all4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { axis, keepDims } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    input2 = transposed;\n    inputId = transposedId;\n  }\n  const inputRank = input2.shape.length;\n  backend_util_exports.assertAxesAreInnerMostDims(\"all\", axes, inputRank);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const out = backend2.makeOutput(outShape, x.dtype);\n  if (util_exports.sizeFromShape(input2.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmAll(inputId, reduceSize, outId);\n  }\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(out.shape, originalAxes);\n    out.shape = newShape;\n  }\n  return out;\n}\nvar allConfig3 = {\n  kernelName: All,\n  backendName: \"wasm\",\n  setupFunc: setup3,\n  kernelFunc: all4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Any.js\nvar wasmAny;\nfunction setup4(backend2) {\n  wasmAny = backend2.wasm.cwrap(Any, null, [\"number, number, number\"]);\n}\nfunction any4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { axis, keepDims } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    input2 = transposed;\n    inputId = transposedId;\n  }\n  const inputRank = input2.shape.length;\n  backend_util_exports.assertAxesAreInnerMostDims(\"any\", axes, inputRank);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const out = backend2.makeOutput(outShape, x.dtype);\n  if (util_exports.sizeFromShape(input2.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmAny(inputId, reduceSize, outId);\n  }\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(out.shape, originalAxes);\n    out.shape = newShape;\n  }\n  return out;\n}\nvar anyConfig3 = {\n  kernelName: Any,\n  backendName: \"wasm\",\n  setupFunc: setup4,\n  kernelFunc: any4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/ArgMax.js\nvar wasmFunc2;\nfunction setup5(backend2) {\n  wasmFunc2 = backend2.wasm.cwrap(ArgMax, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction argmax(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { axis } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    if (transposedId !== xId) {\n      input2 = transposed;\n      inputId = transposedId;\n    }\n  }\n  const outShape = input2.shape.slice(0, -1);\n  const out = backend2.makeOutput(outShape, \"int32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const outerSize = util_exports.sizeFromShape(out.shape);\n  const innerSize = input2.shape[axes[0]];\n  wasmFunc2(inputId, CppDType[input2.dtype], outerSize, innerSize, outId);\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  return out;\n}\nvar argMaxConfig3 = {\n  kernelName: ArgMax,\n  backendName: \"wasm\",\n  kernelFunc: argmax,\n  setupFunc: setup5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/AvgPool.js\nvar wasmAvgPool;\nfunction setup6(backend2) {\n  wasmAvgPool = backend2.wasm.cwrap(AvgPool, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction avgPool4(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const x = inputs.x;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, 1, pad3, dimRoundingMode);\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padRight = convInfo.padInfo.right;\n  const padBottom = convInfo.padInfo.bottom;\n  const padLeft = convInfo.padInfo.left;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const channels = convInfo.inChannels;\n  if (convInfo.dataFormat !== \"channelsLast\") {\n    throw new Error(`wasm backend does not support dataFormat:'${convInfo.dataFormat}'. Please use 'channelsLast'.`);\n  }\n  if (convInfo.dilationWidth !== 1 || convInfo.dilationHeight !== 1) {\n    throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${convInfo.dilationHeight}, ${convInfo.dilationWidth}].`);\n  }\n  const out = backend2.makeOutput(convInfo.outShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmAvgPool(xId, x.shape[0], x.shape[1], x.shape[2], filterHeight, filterWidth, padTop, padRight, padBottom, padLeft, strideHeight, strideWidth, channels, outId);\n  return out;\n}\nvar avgPoolConfig3 = {\n  kernelName: AvgPool,\n  backendName: \"wasm\",\n  setupFunc: setup6,\n  kernelFunc: avgPool4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Reshape.js\nfunction reshape5(args) {\n  const { inputs, attrs } = args;\n  const { x } = inputs;\n  const { shape } = attrs;\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const $shape = util_exports.inferFromImplicitShape(shape, xSize);\n  util_exports.assert(xSize === util_exports.sizeFromShape($shape), () => `new shape: ${$shape}, old shape: ${x.shape}. New shape and old shape must have the same number of elements.`);\n  args.backend.incRef(x.dataId);\n  return { dataId: x.dataId, shape: $shape, dtype: x.dtype };\n}\nvar reshapeConfig3 = {\n  kernelName: Reshape,\n  backendName: \"wasm\",\n  kernelFunc: reshape5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/BatchMatMul.js\nvar wasmBatchMatMul;\nfunction setup7(backend2) {\n  wasmBatchMatMul = backend2.wasm.cwrap(BatchMatMul, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction batchMatMul3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b } = inputs;\n  const { transposeA, transposeB } = attrs;\n  if (a.dtype !== \"float32\" || b.dtype !== \"float32\") {\n    throw new Error(`BatchMatMul for non non-float32 tensors not yet supported.`);\n  }\n  const aRank = a.shape.length;\n  const bRank = b.shape.length;\n  const innerShapeA = transposeA ? a.shape[aRank - 2] : a.shape[aRank - 1];\n  const innerShapeB = transposeB ? b.shape[bRank - 1] : b.shape[bRank - 2];\n  const outerShapeA = transposeA ? a.shape[aRank - 1] : a.shape[aRank - 2];\n  const outerShapeB = transposeB ? b.shape[bRank - 2] : b.shape[bRank - 1];\n  const outerDimsA = a.shape.slice(0, -2);\n  const outerDimsB = b.shape.slice(0, -2);\n  const batchDimA = util_exports.sizeFromShape(outerDimsA);\n  const batchDimB = util_exports.sizeFromShape(outerDimsB);\n  const outShapeOuterDims = broadcast_util_exports.assertAndGetBroadcastShape(a.shape.slice(0, -2), b.shape.slice(0, -2));\n  const outShape = outShapeOuterDims.concat([outerShapeA, outerShapeB]);\n  util_exports.assert(innerShapeA === innerShapeB, () => `Error in matMul: inner shapes (${innerShapeA}) and (${innerShapeB}) of Tensors with shapes ${a.shape} and ${b.shape} and transposeA=${transposeA} and transposeB=${transposeB} must match.`);\n  const a3dShape = transposeA ? [batchDimA, innerShapeA, outerShapeA] : [batchDimA, outerShapeA, innerShapeA];\n  const b3dShape = transposeB ? [batchDimB, outerShapeB, innerShapeB] : [batchDimB, innerShapeB, outerShapeB];\n  const a3d = reshape5({ inputs: { x: a }, backend: backend2, attrs: { shape: a3dShape } });\n  const b3d = reshape5({ inputs: { x: b }, backend: backend2, attrs: { shape: b3dShape } });\n  const a3dId = backend2.dataIdMap.get(a3d.dataId).id;\n  const b3dId = backend2.dataIdMap.get(b3d.dataId).id;\n  const leftDim = transposeA ? a3d.shape[2] : a3d.shape[1];\n  const rightDim = transposeB ? b3d.shape[1] : b3d.shape[2];\n  const batchDim = Math.max(batchDimA, batchDimB);\n  const out = backend2.makeOutput([batchDim, leftDim, rightDim], a3d.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const aShapeBytes = new Uint8Array(new Int32Array(a3d.shape).buffer);\n  const bShapeBytes = new Uint8Array(new Int32Array(b3d.shape).buffer);\n  wasmBatchMatMul(a3dId, aShapeBytes, a3d.shape.length, b3dId, bShapeBytes, b3d.shape.length, transposeA, transposeB, outId);\n  backend2.disposeData(a3d.dataId);\n  backend2.disposeData(b3d.dataId);\n  out.shape = outShape;\n  return out;\n}\nvar batchMatMulConfig3 = {\n  kernelName: BatchMatMul,\n  backendName: \"wasm\",\n  setupFunc: setup7,\n  kernelFunc: batchMatMul3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Slice.js\nfunction slice4(args) {\n  const { inputs: { x }, attrs: { begin, size }, backend: backend2 } = args;\n  const [begin_, size_] = slice_util_exports.parseSliceParams(x, begin, size);\n  const isContinous = slice_util_exports.isSliceContinous(x.shape, begin_, size_);\n  const xVals = backend2.readSync(x.dataId);\n  const out = backend2.makeOutput(size_, x.dtype);\n  const xStrides = util_exports.computeStrides(x.shape);\n  const outData = backend2.dataIdMap.get(out.dataId);\n  if (isContinous) {\n    const flatOffset = slice_util_exports.computeFlatOffset(begin_, xStrides);\n    if (x.dtype === \"string\") {\n      outData.stringBytes = xVals.slice(flatOffset, flatOffset + util_exports.sizeFromShape(size_));\n    } else {\n      const outVals2 = backend2.typedArrayFromHeap(out);\n      outVals2.set(xVals.subarray(flatOffset, flatOffset + util_exports.sizeFromShape(size_)));\n    }\n    return out;\n  }\n  if (x.dtype === \"string\") {\n    const res = sliceImpl(xVals, begin_, size_, x.shape, x.dtype);\n    outData.stringBytes = res;\n    return out;\n  }\n  const outVals = backend2.typedArrayFromHeap(out);\n  const rank = x.shape.length;\n  if (rank === 2) {\n    slice2d2(xVals, xStrides[0], outVals, begin_, size_);\n  } else if (rank === 3) {\n    slice3d2(xVals, xStrides[0], xStrides[1], outVals, begin_, size_);\n  } else if (rank === 4) {\n    slice4d2(xVals, xStrides[0], xStrides[1], xStrides[2], outVals, begin_, size_);\n  } else {\n    const res = sliceImpl(xVals, begin_, size_, x.shape, x.dtype);\n    outVals.set(res);\n  }\n  return out;\n}\nfunction slice2d2(xVals, xStride, outVals, begin, size) {\n  let outOffset = 0;\n  const beginI = begin[0];\n  const beginJ = begin[1];\n  const endI = beginI + size[0];\n  for (let i2 = beginI; i2 < endI; i2++) {\n    const xOffset = i2 * xStride + beginJ;\n    outVals.set(xVals.subarray(xOffset, xOffset + size[1]), outOffset);\n    outOffset += size[1];\n  }\n}\nfunction slice3d2(xVals, xStride1, xStride2, outVals, begin, size) {\n  let outOffset = 0;\n  const beginI = begin[0];\n  const beginJ = begin[1];\n  const beginK = begin[2];\n  const endI = beginI + size[0];\n  const endJ = beginJ + size[1];\n  for (let i2 = beginI; i2 < endI; i2++) {\n    for (let j = beginJ; j < endJ; j++) {\n      const xOffset = i2 * xStride1 + j * xStride2 + beginK;\n      outVals.set(xVals.subarray(xOffset, xOffset + size[2]), outOffset);\n      outOffset += size[2];\n    }\n  }\n}\nfunction slice4d2(xVals, xStride1, xStride2, xStride3, outVals, begin, size) {\n  let outOffset = 0;\n  const beginI = begin[0];\n  const beginJ = begin[1];\n  const beginK = begin[2];\n  const endI = beginI + size[0];\n  const endJ = beginJ + size[1];\n  const endK = beginK + size[2];\n  const beginL = begin[3];\n  for (let i2 = beginI; i2 < endI; i2++) {\n    for (let j = beginJ; j < endJ; j++) {\n      for (let k = beginK; k < endK; k++) {\n        const xOffset = i2 * xStride1 + j * xStride2 + k * xStride3 + beginL;\n        outVals.set(xVals.subarray(xOffset, xOffset + size[3]), outOffset);\n        outOffset += size[3];\n      }\n    }\n  }\n}\nvar sliceConfig3 = {\n  kernelName: Slice,\n  backendName: \"wasm\",\n  kernelFunc: slice4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/BatchToSpaceND.js\nfunction batchToSpaceND4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, crops } = attrs;\n  const prod6 = blockShape.reduce((a, b) => a * b);\n  const reshaped = backend_util_exports.getReshaped(x.shape, blockShape, prod6);\n  const permuted = backend_util_exports.getPermuted(reshaped.length, blockShape.length);\n  const reshapedPermuted = backend_util_exports.getReshapedPermuted(x.shape, blockShape, prod6);\n  const sliceBeginCoords = backend_util_exports.getSliceBeginCoords(crops, blockShape.length);\n  const sliceSize = backend_util_exports.getSliceSize(reshapedPermuted, crops, blockShape.length);\n  const xReshaped = reshape5({ inputs: { x }, backend: backend2, attrs: { shape: reshaped } });\n  const xTransposed = transpose4({ inputs: { x: xReshaped }, backend: backend2, attrs: { perm: permuted } });\n  const xTransposedReshaped = reshape5({ inputs: { x: xTransposed }, backend: backend2, attrs: { shape: reshapedPermuted } });\n  const result = slice4({\n    inputs: { x: xTransposedReshaped },\n    backend: backend2,\n    attrs: { begin: sliceBeginCoords, size: sliceSize }\n  });\n  backend2.disposeData(xReshaped.dataId);\n  backend2.disposeData(xTransposed.dataId);\n  backend2.disposeData(xReshaped.dataId);\n  return result;\n}\nvar batchToSpaceNDConfig3 = {\n  kernelName: BatchToSpaceND,\n  backendName: \"wasm\",\n  kernelFunc: batchToSpaceND4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Cast.js\nfunction cast5(args) {\n  const { inputs: { x }, attrs: { dtype }, backend: backend2 } = args;\n  const out = backend2.makeOutput(x.shape, dtype);\n  const inVals = backend2.typedArrayFromHeap(x);\n  const outVals = backend2.typedArrayFromHeap(out);\n  outVals.set(inVals);\n  return out;\n}\nvar castConfig3 = {\n  kernelName: Cast,\n  backendName: \"wasm\",\n  kernelFunc: cast5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Ceil.js\nvar ceilConfig3 = createUnaryKernelConfig(Ceil);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/ClipByValue.js\nvar wasmClip;\nfunction setup8(backend2) {\n  wasmClip = backend2.wasm.cwrap(ClipByValue, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction clip(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { clipValueMin, clipValueMax } = attrs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmClip(xId, clipValueMin, clipValueMax, outId);\n  return out;\n}\nvar clipByValueConfig3 = {\n  kernelName: ClipByValue,\n  backendName: \"wasm\",\n  setupFunc: setup8,\n  kernelFunc: clip\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Concat.js\nfunction concat4(args) {\n  const { inputs, backend: backend2 } = args;\n  const axis = util_exports.parseAxisParam(args.attrs.axis, inputs[0].shape)[0];\n  let outShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), axis);\n  const $inputs = inputs.filter((t2) => util_exports.sizeFromShape(t2.shape) > 0);\n  if ($inputs.length === 1) {\n    return identity4({ inputs: { x: $inputs[0] }, backend: backend2 });\n  }\n  const out = backend2.makeOutput(outShape, inputs[0].dtype);\n  if (util_exports.sizeFromShape(outShape) === 0) {\n    return out;\n  }\n  const shapes = $inputs.map((t2) => t2.shape);\n  backend_util_exports.assertParamsConsistent(shapes, axis);\n  if ($inputs[0].dtype === \"string\") {\n    const inputs2D = $inputs.map((t2) => {\n      const innerSize = util_exports.sizeFromShape(t2.shape.slice(axis));\n      const shape = [-1, innerSize];\n      return reshape5({ inputs: { x: t2 }, backend: backend2, attrs: { shape } });\n    });\n    const inputsValShapes = inputs2D.map((t2) => {\n      return { vals: backend2.readSync(t2.dataId), shape: t2.shape };\n    });\n    outShape = backend_util_exports.computeOutShape(inputs2D.map((t2) => t2.shape), 1);\n    const simplyConcat = inputs2D[0].shape[0] === 1;\n    const outVals2 = concatImpl(inputsValShapes, outShape, inputs[0].dtype, simplyConcat);\n    const finalOutShape = backend_util_exports.computeOutShape($inputs.map((t2) => t2.shape), axis);\n    out.shape = finalOutShape;\n    const outData = backend2.dataIdMap.get(out.dataId);\n    outData.stringBytes = backend_util_exports.fromStringArrayToUint8(outVals2);\n    inputs2D.forEach((t2) => backend2.disposeData(t2.dataId));\n    return out;\n  }\n  const batchDim = util_exports.sizeFromShape($inputs[0].shape.slice(0, axis));\n  let sumInnerDims = 0;\n  const innerDims = $inputs.map((input2) => {\n    const innerDim = util_exports.sizeFromShape(input2.shape.slice(axis));\n    sumInnerDims += innerDim;\n    return innerDim;\n  });\n  const inVals = $inputs.map((input2) => backend2.typedArrayFromHeap(input2));\n  const outVals = backend2.typedArrayFromHeap(out);\n  for (let b = 0; b < batchDim; b++) {\n    let outOffset = b * sumInnerDims;\n    for (let i2 = 0; i2 < inVals.length; i2++) {\n      const innerDim = innerDims[i2];\n      const inOffset = b * innerDim;\n      const vals = inVals[i2].subarray(inOffset, inOffset + innerDim);\n      outVals.set(vals, outOffset);\n      outOffset += innerDim;\n    }\n  }\n  return out;\n}\nvar concatConfig3 = {\n  kernelName: Concat,\n  backendName: \"wasm\",\n  kernelFunc: concat4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Conv2D.js\nvar wasmConv2d;\nfunction setup9(backend2) {\n  wasmConv2d = backend2.wasm.cwrap(Conv2D, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction conv2d5(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { x, filter } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const filterId = backend2.dataIdMap.get(filter.dataId).id;\n  const { strides, dilations, pad: pad3, dimRoundingMode, dataFormat } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode, false, $dataFormat);\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padRight = convInfo.padInfo.right;\n  const padBottom = convInfo.padInfo.bottom;\n  const padLeft = convInfo.padInfo.left;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const inputChannels = convInfo.inChannels;\n  const outputChannels = convInfo.outChannels;\n  const isSamePad = convInfo.padInfo.type === \"SAME\" ? 1 : 0;\n  if (convInfo.dataFormat !== \"channelsLast\") {\n    throw new Error(`wasm backend Conv2D does not support dataFormat:'${convInfo.dataFormat}'. Please use 'channelsLast'.`);\n  }\n  const out = backend2.makeOutput(convInfo.outShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmConv2d(xId, x.shape[0], x.shape[1], x.shape[2], filterId, filterHeight, filterWidth, padTop, padRight, padBottom, padLeft, isSamePad, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, outId);\n  return out;\n}\nvar conv2DConfig3 = {\n  kernelName: Conv2D,\n  backendName: \"wasm\",\n  setupFunc: setup9,\n  kernelFunc: conv2d5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Conv2DBackpropInput.js\nvar wasmConv2DBackpropInput;\nfunction setup10(backend2) {\n  wasmConv2DBackpropInput = backend2.wasm.cwrap(Conv2DBackpropInput, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction conv2DBackpropInput4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { dy, filter } = inputs;\n  const { strides, pad: pad3, dataFormat, dimRoundingMode, inputShape } = attrs;\n  const dilations = 1;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(inputShape, filter.shape, strides, dilations, pad3, dimRoundingMode, false, $dataFormat);\n  const { batchSize, filterHeight, filterWidth, inChannels, inHeight, inWidth, outChannels, outHeight, outWidth, strideHeight, strideWidth } = convInfo;\n  const topPad = filterHeight - 1 - convInfo.padInfo.top;\n  const leftPad = filterWidth - 1 - convInfo.padInfo.left;\n  const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n  const dxStrides = util_exports.computeStrides(convInfo.inShape);\n  const dyStrides = util_exports.computeStrides(dy.shape);\n  const [fltS0, fltS1, fltS2] = util_exports.computeStrides(filter.shape);\n  const xBatchStride = dxStrides[0];\n  const xRowStride = isChannelsLast ? dxStrides[1] : dxStrides[2];\n  const xColStride = isChannelsLast ? dxStrides[2] : 1;\n  const xChannelStride = isChannelsLast ? 1 : dxStrides[1];\n  const yBatchStride = dyStrides[0];\n  const yRowStride = isChannelsLast ? dyStrides[1] : dyStrides[2];\n  const yColStride = isChannelsLast ? dyStrides[2] : 1;\n  const yChannelStride = isChannelsLast ? 1 : dyStrides[1];\n  const out = backend2.makeOutput(convInfo.inShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const dyId = backend2.dataIdMap.get(dy.dataId).id;\n  const filterId = backend2.dataIdMap.get(filter.dataId).id;\n  wasmConv2DBackpropInput(dyId, filterId, batchSize, filterHeight, filterWidth, inHeight, inWidth, inChannels, outHeight, outWidth, outChannels, strideHeight, strideWidth, topPad, leftPad, fltS0, fltS1, fltS2, xBatchStride, xRowStride, xColStride, xChannelStride, yBatchStride, yRowStride, yColStride, yChannelStride, outId);\n  return out;\n}\nvar conv2DBackpropInputConfig3 = {\n  kernelName: Conv2DBackpropInput,\n  backendName: \"wasm\",\n  setupFunc: setup10,\n  kernelFunc: conv2DBackpropInput4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Cos.js\nvar cosConfig3 = createUnaryKernelConfig(Cos);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Cosh.js\nvar coshConfig3 = createUnaryKernelConfig(Cosh);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/CropAndResize.js\nvar InterpolationMethod;\n(function(InterpolationMethod2) {\n  InterpolationMethod2[InterpolationMethod2[\"bilinear\"] = 0] = \"bilinear\";\n  InterpolationMethod2[InterpolationMethod2[\"nearest\"] = 1] = \"nearest\";\n})(InterpolationMethod || (InterpolationMethod = {}));\nvar wasmCropAndResize;\nfunction setup11(backend2) {\n  wasmCropAndResize = backend2.wasm.cwrap(CropAndResize, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction cropAndResize4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { method, extrapolationValue, cropSize } = attrs;\n  const { image: image2, boxes, boxInd } = inputs;\n  const numBoxes = boxes.shape[0];\n  const [cropHeight, cropWidth] = cropSize;\n  const outShape = [numBoxes, cropHeight, cropWidth, image2.shape[3]];\n  let imagesData = backend2.dataIdMap.get(image2.dataId);\n  let castedData;\n  if (image2.dtype !== \"float32\") {\n    castedData = cast5({ backend: backend2, inputs: { x: image2 }, attrs: { dtype: \"float32\" } });\n    imagesData = backend2.dataIdMap.get(castedData.dataId);\n  }\n  const imagesId = imagesData.id;\n  const boxesId = backend2.dataIdMap.get(boxes.dataId).id;\n  const boxIndId = backend2.dataIdMap.get(boxInd.dataId).id;\n  const out = backend2.makeOutput(outShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const imagesShapeBytes = new Uint8Array(new Int32Array(image2.shape).buffer);\n  wasmCropAndResize(imagesId, boxesId, boxIndId, numBoxes, imagesShapeBytes, cropHeight, cropWidth, InterpolationMethod[method], extrapolationValue, outId);\n  if (castedData != null) {\n    backend2.disposeData(castedData.dataId);\n  }\n  return out;\n}\nvar cropAndResizeConfig3 = {\n  kernelName: CropAndResize,\n  backendName: \"wasm\",\n  setupFunc: setup11,\n  kernelFunc: cropAndResize4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Cumprod.js\nvar wasmCumprod;\nfunction setup12(backend2) {\n  wasmCumprod = backend2.wasm.cwrap(Cumprod, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction cumprod4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  const xRank = x.shape.length;\n  util_exports.assert(x.dtype === \"float32\" || x.dtype === \"int32\", () => `cumprod does not support ${x.dtype} tensors in the WASM backend`);\n  const permutation = backend_util_exports.getAxesPermutation([axis], xRank);\n  let permutedX = x;\n  if (permutation !== null) {\n    permutedX = transpose4({ inputs: { x }, attrs: { perm: permutation }, backend: backend2 });\n  }\n  const permutedAxis = backend_util_exports.getInnerMostAxes(1, xRank)[0];\n  backend_util_exports.assertAxesAreInnerMostDims(\"cumprod\", [permutedAxis], xRank);\n  const permutedOut = backend2.makeOutput(permutedX.shape, permutedX.dtype);\n  const finalDim = permutedX.shape[permutedAxis];\n  const permutedXId = backend2.dataIdMap.get(permutedX.dataId).id;\n  const permutedOutId = backend2.dataIdMap.get(permutedOut.dataId).id;\n  wasmCumprod(permutedXId, exclusive ? 1 : 0, reverse5 ? 1 : 0, finalDim, permutedOutId, CppDType[x.dtype]);\n  let out = permutedOut;\n  if (permutation !== null) {\n    const undoPermutation = backend_util_exports.getUndoAxesPermutation(permutation);\n    out = transpose4({ inputs: { x: permutedOut }, attrs: { perm: undoPermutation }, backend: backend2 });\n    backend2.disposeData(permutedX.dataId);\n    backend2.disposeData(permutedOut.dataId);\n  }\n  return out;\n}\nvar cumprodConfig3 = {\n  kernelName: Cumprod,\n  backendName: \"wasm\",\n  setupFunc: setup12,\n  kernelFunc: cumprod4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Cumsum.js\nvar wasmCumsum;\nfunction setup13(backend2) {\n  wasmCumsum = backend2.wasm.cwrap(Cumsum, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction cumsum4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  const xRank = x.shape.length;\n  util_exports.assert(x.dtype === \"float32\" || x.dtype === \"int32\", () => `cumsum does not support ${x.dtype} tensors in the WASM backend`);\n  const permutation = backend_util_exports.getAxesPermutation([axis], xRank);\n  let permutedX = x;\n  if (permutation !== null) {\n    permutedX = transpose4({ inputs: { x }, attrs: { perm: permutation }, backend: backend2 });\n  }\n  const permutedAxis = backend_util_exports.getInnerMostAxes(1, xRank)[0];\n  backend_util_exports.assertAxesAreInnerMostDims(\"cumsum\", [permutedAxis], xRank);\n  const permutedOut = backend2.makeOutput(permutedX.shape, permutedX.dtype);\n  const finalDim = permutedX.shape[permutedAxis];\n  const permutedXId = backend2.dataIdMap.get(permutedX.dataId).id;\n  const permutedOutId = backend2.dataIdMap.get(permutedOut.dataId).id;\n  wasmCumsum(permutedXId, exclusive ? 1 : 0, reverse5 ? 1 : 0, finalDim, permutedOutId, CppDType[x.dtype]);\n  let out = permutedOut;\n  if (permutation !== null) {\n    const undoPermutation = backend_util_exports.getUndoAxesPermutation(permutation);\n    out = transpose4({ inputs: { x: permutedOut }, attrs: { perm: undoPermutation }, backend: backend2 });\n    backend2.disposeData(permutedX.dataId);\n    backend2.disposeData(permutedOut.dataId);\n  }\n  return out;\n}\nvar cumsumConfig3 = {\n  kernelName: Cumsum,\n  backendName: \"wasm\",\n  setupFunc: setup13,\n  kernelFunc: cumsum4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/DepthToSpace.js\nvar wasmDepthToSpace;\nfunction setup14(backend2) {\n  wasmDepthToSpace = backend2.wasm.cwrap(DepthToSpace, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"array\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction depthToSpace4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { x } = inputs;\n  const { blockSize, dataFormat } = attrs;\n  const batchSize = x.shape[0];\n  const inputHeight = dataFormat === \"NHWC\" ? x.shape[1] : x.shape[2];\n  const inputWidth = dataFormat === \"NHWC\" ? x.shape[2] : x.shape[3];\n  const inputDepth = dataFormat === \"NHWC\" ? x.shape[3] : x.shape[1];\n  const outputHeight = inputHeight * blockSize;\n  const outputWidth = inputWidth * blockSize;\n  const outputDepth = inputDepth / (blockSize * blockSize);\n  const outputShape = dataFormat === \"NHWC\" ? [batchSize, outputHeight, outputWidth, outputDepth] : [batchSize, outputDepth, outputHeight, outputWidth];\n  const out = backend2.makeOutput(outputShape, \"float32\");\n  const xData = backend2.dataIdMap.get(x.dataId);\n  const xId = xData.id;\n  const xStridesBytes = new Uint8Array(new Int32Array(util_exports.computeStrides(x.shape)).buffer);\n  const outputShapeBytes = new Uint8Array(new Int32Array(outputShape).buffer);\n  const outStridesBytes = new Uint8Array(new Int32Array(util_exports.computeStrides(outputShape)).buffer);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const channelsLast = dataFormat === \"NHWC\" ? 1 : 0;\n  wasmDepthToSpace(xId, blockSize, channelsLast, xStridesBytes, x.shape.length - 1, outputShapeBytes, outStridesBytes, outputShape.length, outId);\n  return out;\n}\nvar depthToSpaceConfig3 = {\n  kernelName: DepthToSpace,\n  backendName: \"wasm\",\n  setupFunc: setup14,\n  kernelFunc: depthToSpace4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/DepthwiseConv2dNative.js\nvar wasmDepthwiseConv2d;\nfunction setup15(backend2) {\n  wasmDepthwiseConv2d = backend2.wasm.cwrap(DepthwiseConv2dNative, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction depthwiseConv2d5(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { x, filter } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const filterId = backend2.dataIdMap.get(filter.dataId).id;\n  const { strides, dilations, pad: pad3, dimRoundingMode } = attrs;\n  const $dilations = dilations == null ? [1, 1] : dilations;\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad3, dimRoundingMode, true);\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padRight = convInfo.padInfo.right;\n  const padBottom = convInfo.padInfo.bottom;\n  const padLeft = convInfo.padInfo.left;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const inputChannels = convInfo.inChannels;\n  const outputChannels = convInfo.outChannels;\n  const isSamePad = convInfo.padInfo.type === \"SAME\" ? 1 : 0;\n  if (convInfo.dataFormat !== \"channelsLast\") {\n    throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${convInfo.dataFormat}'. Please use 'channelsLast'.`);\n  }\n  const out = backend2.makeOutput(convInfo.outShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmDepthwiseConv2d(xId, x.shape[0], x.shape[1], x.shape[2], filterId, filterHeight, filterWidth, padTop, padRight, padBottom, padLeft, isSamePad, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, outId);\n  return out;\n}\nvar depthwiseConv2dNativeConfig3 = {\n  kernelName: DepthwiseConv2dNative,\n  backendName: \"wasm\",\n  setupFunc: setup15,\n  kernelFunc: depthwiseConv2d5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Elu.js\nvar eluConfig3 = createUnaryKernelConfig(Elu);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Equal.js\nvar supportsFullBroadcast2 = false;\nvar equalConfig3 = createBinaryKernelConfig(Equal, supportsFullBroadcast2, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Exp.js\nvar expConfig3 = createUnaryKernelConfig(Exp, \"float32\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/ExpandDims.js\nfunction expandDims5(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const { dim } = attrs;\n  const inputRank = input2.shape.length;\n  const newShape = input2.shape.slice();\n  let $dim = dim;\n  if (dim < 0) {\n    util_exports.assert(-(inputRank + 1) <= dim, () => `Axis must be in the interval [${-(inputRank + 1)}, ${inputRank}]`);\n    $dim = inputRank + dim + 1;\n  }\n  newShape.splice($dim, 0, 1);\n  return reshape5({ inputs: { x: input2 }, backend: backend2, attrs: { shape: newShape } });\n}\nvar expandDimsConfig3 = {\n  kernelName: ExpandDims,\n  backendName: \"wasm\",\n  kernelFunc: expandDims5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Fill.js\nfunction fill4(args) {\n  const { attrs: { shape, value, dtype }, backend: backend2 } = args;\n  const out = backend2.makeOutput(shape, dtype);\n  const outVals = backend2.typedArrayFromHeap(out);\n  outVals.fill(value);\n  return out;\n}\nvar fillConfig3 = {\n  kernelName: Fill,\n  backendName: \"wasm\",\n  kernelFunc: fill4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/FlipLeftRight.js\nvar wasmFlipLeftRight;\nfunction setup16(backend2) {\n  wasmFlipLeftRight = backend2.wasm.cwrap(FlipLeftRight, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction flipLeftRight2(args) {\n  const { inputs, backend: backend2 } = args;\n  const { image: image2 } = inputs;\n  const out = backend2.makeOutput(image2.shape, image2.dtype);\n  const imageId = backend2.dataIdMap.get(image2.dataId).id;\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n  wasmFlipLeftRight(imageId, batch, imageHeight, imageWidth, numChannels, outId);\n  return out;\n}\nvar flipLeftRightConfig3 = {\n  kernelName: FlipLeftRight,\n  backendName: \"wasm\",\n  kernelFunc: flipLeftRight2,\n  setupFunc: setup16\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Floor.js\nvar floorConfig3 = createUnaryKernelConfig(Floor);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/FloorDiv.js\nvar supportsFullBroadcast3 = false;\nvar floorDivConfig3 = createBinaryKernelConfig(FloorDiv, supportsFullBroadcast3);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/FusedBatchNorm.js\nvar wasmBatchNorm;\nfunction setup17(backend2) {\n  wasmBatchNorm = backend2.wasm.cwrap(FusedBatchNorm, null, [\"number\", \"number\", \"number\", \"number\", \"number\", \"number\", \"number\"]);\n}\nfunction fusedBatchNorm(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { varianceEpsilon } = attrs;\n  const { x, mean: mean5, variance, offset, scale: scale2 } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const meanId = backend2.dataIdMap.get(mean5.dataId).id;\n  const varianceId = backend2.dataIdMap.get(variance.dataId).id;\n  const offsetId = offset != null ? backend2.dataIdMap.get(offset.dataId).id : 0;\n  const scaleId = scale2 != null ? backend2.dataIdMap.get(scale2.dataId).id : 0;\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  if (util_exports.sizeFromShape(x.shape) === 0) {\n    return out;\n  }\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmBatchNorm(xId, meanId, varianceId, offsetId, scaleId, varianceEpsilon, outId);\n  return out;\n}\nvar fusedBatchNormConfig = {\n  kernelName: FusedBatchNorm,\n  backendName: \"wasm\",\n  setupFunc: setup17,\n  kernelFunc: fusedBatchNorm\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/FusedConv2D.js\nvar wasmFusedConv2d;\nfunction setup18(backend2) {\n  wasmFusedConv2d = backend2.wasm.cwrap(FusedConv2D, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction fusedConv2d2(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dilations, dataFormat, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode);\n  const fusedActivation = FusableActivation[activation2];\n  if (fusedActivation == null) {\n    throw new Error(`${activation2} activation not yet supported for FusedConv2D in the wasm backend.`);\n  }\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const filterId = backend2.dataIdMap.get(filter.dataId).id;\n  const outputChannels = convInfo.outChannels;\n  let biasId = 0;\n  if (bias != null) {\n    const biasData = backend2.dataIdMap.get(bias.dataId);\n    if (biasData.shape.length !== 1) {\n      throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${biasData.shape.length}.`);\n    }\n    if (biasData.shape[0] !== outputChannels) {\n      throw new Error(`FusedConv2D bias shape (${biasData.shape}) does not match the number of output channels (${outputChannels})`);\n    }\n    biasId = biasData.id;\n  }\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padRight = convInfo.padInfo.right;\n  const padBottom = convInfo.padInfo.bottom;\n  const padLeft = convInfo.padInfo.left;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const inputChannels = convInfo.inChannels;\n  const isSamePad = convInfo.padInfo.type === \"SAME\" ? 1 : 0;\n  const batchSize = convInfo.batchSize;\n  const inHeight = convInfo.inHeight;\n  const inWidth = convInfo.inWidth;\n  if (dataFormat !== \"NHWC\") {\n    throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${dataFormat}'. Please use 'NHWC'.`);\n  }\n  const out = backend2.makeOutput(convInfo.outShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const preluActivationWeightsId = preluActivationWeights == null ? 0 : backend2.dataIdMap.get(preluActivationWeights.dataId).id;\n  wasmFusedConv2d(xId, batchSize, inHeight, inWidth, filterId, filterHeight, filterWidth, biasId, padTop, padRight, padBottom, padLeft, isSamePad, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, fusedActivation, preluActivationWeightsId, leakyreluAlpha || 0, outId);\n  return out;\n}\nvar fusedConv2DConfig3 = {\n  kernelName: FusedConv2D,\n  backendName: \"wasm\",\n  setupFunc: setup18,\n  kernelFunc: fusedConv2d2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/FusedDepthwiseConv2D.js\nvar wasmFusedDepthwiseConv2d;\nfunction setup19(backend2) {\n  wasmFusedDepthwiseConv2d = backend2.wasm.cwrap(FusedDepthwiseConv2D, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction fusedDepthwiseConv2d(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dilations, dataFormat, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode, true);\n  const fusedActivation = FusableActivation[activation2];\n  if (fusedActivation == null) {\n    throw new Error(`${activation2} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);\n  }\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const filterId = backend2.dataIdMap.get(filter.dataId).id;\n  const outputChannels = convInfo.outChannels;\n  let biasId = 0;\n  if (bias != null) {\n    const biasData = backend2.dataIdMap.get(bias.dataId);\n    if (biasData.shape.length !== 1) {\n      throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${biasData.shape.length}.`);\n    }\n    if (biasData.shape[0] !== outputChannels) {\n      throw new Error(`FusedDepthwiseConv2D bias shape (${biasData.shape}) does not match the number of output channels (${outputChannels})`);\n    }\n    biasId = biasData.id;\n  }\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padRight = convInfo.padInfo.right;\n  const padBottom = convInfo.padInfo.bottom;\n  const padLeft = convInfo.padInfo.left;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const inputChannels = convInfo.inChannels;\n  const isSamePad = convInfo.padInfo.type === \"SAME\" ? 1 : 0;\n  const batchSize = convInfo.batchSize;\n  const inHeight = convInfo.inHeight;\n  const inWidth = convInfo.inWidth;\n  if (dataFormat !== \"NHWC\") {\n    throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${dataFormat}'. Please use 'NHWC'.`);\n  }\n  const out = backend2.makeOutput(convInfo.outShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const preluActivationWeightsId = preluActivationWeights == null ? 0 : backend2.dataIdMap.get(preluActivationWeights.dataId).id;\n  wasmFusedDepthwiseConv2d(xId, batchSize, inHeight, inWidth, filterId, filterHeight, filterWidth, biasId, padTop, padRight, padBottom, padLeft, isSamePad, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, fusedActivation, preluActivationWeightsId, leakyreluAlpha || 0, outId);\n  return out;\n}\nvar fusedDepthwiseConv2DConfig3 = {\n  kernelName: FusedDepthwiseConv2D,\n  backendName: \"wasm\",\n  setupFunc: setup19,\n  kernelFunc: fusedDepthwiseConv2d\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/GatherNd.js\nvar wasmGatherNd;\nfunction setup20(backend2) {\n  wasmGatherNd = backend2.wasm.cwrap(GatherNd, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\"\n  ]);\n}\nfunction gatherNd3(args) {\n  const { backend: backend2, inputs } = args;\n  const { params, indices } = inputs;\n  const [resultShape, numSlices, sliceSize, strides] = gather_nd_util_exports.prepareAndValidate(params, indices);\n  const out = backend2.makeOutput(resultShape, params.dtype);\n  if (numSlices === 0) {\n    return out;\n  }\n  const indicesShape = indices.shape;\n  const sliceRank = indicesShape[indicesShape.length - 1];\n  const xData = backend2.dataIdMap.get(params.dataId);\n  const xId = xData.id;\n  const indicesData = backend2.dataIdMap.get(indices.dataId);\n  const indicesId = indicesData.id;\n  const stridesBytes = new Uint8Array(new Int32Array(strides).buffer);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmGatherNd(xId, CppDType[params.dtype], indicesId, numSlices, sliceRank, sliceSize, stridesBytes, outId);\n  return out;\n}\nvar gatherNdConfig3 = {\n  kernelName: GatherNd,\n  backendName: \"wasm\",\n  setupFunc: setup20,\n  kernelFunc: gatherNd3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/GatherV2.js\nvar wasmGather;\nfunction setup21(backend2) {\n  wasmGather = backend2.wasm.cwrap(\"Gather\", null, [\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\"\n  ]);\n}\nfunction gatherV23(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { x, indices } = inputs;\n  const { axis, batchDims } = attrs;\n  const parsedAxis = util_exports.parseAxisParam(axis, x.shape)[0];\n  const indicesVals = backend2.readSync(indices.dataId);\n  const axisDim = x.shape[parsedAxis];\n  for (let i2 = 0; i2 < indicesVals.length; ++i2) {\n    const index = indicesVals[i2];\n    util_exports.assert(index <= axisDim - 1 && index >= 0, () => `GatherV2: the index value ${index} is not in [0, ${axisDim - 1}]`);\n  }\n  const shapeInfo = backend_util_exports.segment_util.collectGatherOpShapeInfo(x, indices, parsedAxis, batchDims);\n  const flattenX = reshape5({\n    inputs: { x },\n    attrs: {\n      shape: [\n        shapeInfo.batchSize,\n        shapeInfo.outerSize,\n        shapeInfo.dimSize,\n        shapeInfo.sliceSize\n      ]\n    },\n    backend: backend2\n  });\n  const indicesSize = util_exports.sizeFromShape(indices.shape);\n  const flattenIndex = reshape5({\n    inputs: { x: indices },\n    attrs: { shape: [shapeInfo.batchSize, indicesSize / shapeInfo.batchSize] },\n    backend: backend2\n  });\n  const flattenOutputShape = [\n    shapeInfo.batchSize,\n    shapeInfo.outerSize,\n    indicesSize / shapeInfo.batchSize,\n    shapeInfo.sliceSize\n  ];\n  const out = backend2.makeOutput(flattenOutputShape, x.dtype);\n  if (util_exports.sizeFromShape(x.shape) === 0) {\n    return out;\n  }\n  const stridesSize = flattenX.shape.length - 1;\n  const xData = backend2.dataIdMap.get(flattenX.dataId);\n  const xId = xData.id;\n  const indicesData = backend2.dataIdMap.get(flattenIndex.dataId);\n  const indicesId = indicesData.id;\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const xStridesBytes = new Uint8Array(new Int32Array(util_exports.computeStrides(flattenX.shape)).buffer);\n  const outStridesBytes = new Uint8Array(new Int32Array(util_exports.computeStrides(flattenOutputShape)).buffer);\n  wasmGather(xId, CppDType[x.dtype], xStridesBytes, stridesSize, indicesId, shapeInfo.batchSize, outStridesBytes, outId);\n  backend2.disposeData(flattenX.dataId);\n  backend2.disposeData(flattenIndex.dataId);\n  out.shape = shapeInfo.outputShape;\n  return out;\n}\nvar gatherV2Config3 = {\n  kernelName: GatherV2,\n  backendName: \"wasm\",\n  setupFunc: setup21,\n  kernelFunc: gatherV23\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Greater.js\nvar supportsFullBroadcast4 = false;\nvar greaterConfig3 = createBinaryKernelConfig(Greater, supportsFullBroadcast4, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/GreaterEqual.js\nvar supportsFullBroadcast5 = false;\nvar greaterEqualConfig3 = createBinaryKernelConfig(GreaterEqual, supportsFullBroadcast5, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/LeakyRelu.js\nvar wasmFunc3;\nfunction setupFunc2(backend2) {\n  wasmFunc3 = backend2.wasm.cwrap(LeakyRelu, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction leakyRelu4(args) {\n  const { inputs: { x }, attrs: { alpha }, backend: backend2 } = args;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const out = backend2.makeOutput(x.shape, \"float32\");\n  if (util_exports.sizeFromShape(x.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmFunc3(xId, CppDType[x.dtype], alpha, outId);\n  }\n  return out;\n}\nvar leakyReluConfig3 = {\n  kernelName: LeakyRelu,\n  backendName: \"wasm\",\n  setupFunc: setupFunc2,\n  kernelFunc: leakyRelu4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Less.js\nvar supportsFullBroadcast6 = false;\nvar lessConfig3 = createBinaryKernelConfig(Less, supportsFullBroadcast6, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/LessEqual.js\nvar supportsFullBroadcast7 = false;\nvar lessEqualConfig3 = createBinaryKernelConfig(LessEqual, supportsFullBroadcast7, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Log.js\nvar logConfig3 = createUnaryKernelConfig(Log);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/LogicalAnd.js\nvar supportsFullBroadcast8 = false;\nvar logicalAndConfig3 = createBinaryKernelConfig(LogicalAnd, supportsFullBroadcast8, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/LogicalNot.js\nvar logicalNotConfig3 = createUnaryKernelConfig(LogicalNot);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/LogicalOr.js\nvar supportsFullBroadcast9 = false;\nvar logicalOrConfig3 = createBinaryKernelConfig(LogicalOr, supportsFullBroadcast9, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/LogicalXor.js\nvar supportsFullBroadcast10 = false;\nvar logicalXorConfig = createBinaryKernelConfig(LogicalXor, supportsFullBroadcast10, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Max.js\nvar wasmMax;\nfunction setup22(backend2) {\n  wasmMax = backend2.wasm.cwrap(Max, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction max5(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { reductionIndices: axis, keepDims } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    input2 = transposed;\n    inputId = transposedId;\n  }\n  const inputRank = input2.shape.length;\n  backend_util_exports.assertAxesAreInnerMostDims(\"max\", axes, inputRank);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const out = backend2.makeOutput(outShape, x.dtype);\n  if (util_exports.sizeFromShape(input2.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmMax(inputId, CppDType[x.dtype], reduceSize, outId);\n  }\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(out.shape, originalAxes);\n    out.shape = newShape;\n  }\n  return out;\n}\nvar maxConfig3 = {\n  kernelName: Max,\n  backendName: \"wasm\",\n  setupFunc: setup22,\n  kernelFunc: max5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Maximum.js\nvar supportsFullBroadcast11 = false;\nvar maximumConfig3 = createBinaryKernelConfig(Maximum, supportsFullBroadcast11);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/MaxPool.js\nvar wasmMaxPool;\nfunction setup23(backend2) {\n  wasmMaxPool = backend2.wasm.cwrap(MaxPool, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction maxPool4(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const x = inputs.x;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  util_exports.assert(x.dtype === \"float32\", () => `Error in MaxPool: only float32 input is supported. Got ${x.dtype}.`);\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, 1, pad3, dimRoundingMode);\n  const filterHeight = convInfo.filterHeight;\n  const filterWidth = convInfo.filterWidth;\n  const padTop = convInfo.padInfo.top;\n  const padRight = convInfo.padInfo.right;\n  const padBottom = convInfo.padInfo.bottom;\n  const padLeft = convInfo.padInfo.left;\n  const dilationHeight = convInfo.dilationHeight;\n  const dilationWidth = convInfo.dilationWidth;\n  const strideHeight = convInfo.strideHeight;\n  const strideWidth = convInfo.strideWidth;\n  const inputChannels = convInfo.inChannels;\n  const outputChannels = convInfo.outChannels;\n  if (convInfo.dataFormat !== \"channelsLast\") {\n    throw new Error(`wasm backend does not support dataFormat:'${convInfo.dataFormat}'. Please use 'channelsLast'.`);\n  }\n  const out = backend2.makeOutput(convInfo.outShape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmMaxPool(xId, x.shape[0], x.shape[1], x.shape[2], filterHeight, filterWidth, padTop, padRight, padBottom, padLeft, dilationHeight, dilationWidth, strideHeight, strideWidth, inputChannels, outputChannels, outId);\n  return out;\n}\nvar maxPoolConfig3 = {\n  kernelName: MaxPool,\n  backendName: \"wasm\",\n  setupFunc: setup23,\n  kernelFunc: maxPool4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Mean.js\nvar wasmMean;\nfunction setup24(backend2) {\n  wasmMean = backend2.wasm.cwrap(Mean, null, [\"number, number, number\"]);\n}\nfunction mean3(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { axis, keepDims } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  let reductionAxes = axes;\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    if (transposedId !== xId) {\n      input2 = transposed;\n      inputId = transposedId;\n      reductionAxes = backend_util_exports.getInnerMostAxes(reductionAxes.length, input2.shape.length);\n    }\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"mean\", reductionAxes, input2.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, reductionAxes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  let castedInput = input2;\n  if (input2.dtype !== \"float32\") {\n    castedInput = cast5({ backend: backend2, inputs: { x: input2 }, attrs: { dtype: \"float32\" } });\n    inputId = backend2.dataIdMap.get(castedInput.dataId).id;\n  }\n  const out = backend2.makeOutput(outShape, \"float32\");\n  if (util_exports.sizeFromShape(input2.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmMean(inputId, reduceSize, outId);\n  }\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(out.shape, originalAxes);\n    out.shape = newShape;\n  }\n  if (input2.dtype !== \"float32\") {\n    backend2.disposeData(castedInput.dataId);\n  }\n  return out;\n}\nvar meanConfig3 = {\n  kernelName: Mean,\n  backendName: \"wasm\",\n  setupFunc: setup24,\n  kernelFunc: mean3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Min.js\nvar wasmMin;\nfunction setup25(backend2) {\n  wasmMin = backend2.wasm.cwrap(Min, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction min5(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { axis, keepDims } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    if (transposedId !== xId) {\n      input2 = transposed;\n      inputId = transposedId;\n    }\n  }\n  const inputRank = input2.shape.length;\n  backend_util_exports.assertAxesAreInnerMostDims(\"min\", axes, inputRank);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, axes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const out = backend2.makeOutput(outShape, input2.dtype);\n  if (util_exports.sizeFromShape(input2.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmMin(inputId, CppDType[x.dtype], reduceSize, outId);\n  }\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(out.shape, originalAxes);\n    out.shape = newShape;\n  }\n  return out;\n}\nvar minConfig3 = {\n  kernelName: Min,\n  backendName: \"wasm\",\n  setupFunc: setup25,\n  kernelFunc: min5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Minimum.js\nvar supportsFullBroadcast12 = false;\nvar minimumConfig3 = createBinaryKernelConfig(Minimum, supportsFullBroadcast12);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/MirrorPad.js\nvar MirrorPaddingMode;\n(function(MirrorPaddingMode2) {\n  MirrorPaddingMode2[MirrorPaddingMode2[\"reflect\"] = 0] = \"reflect\";\n  MirrorPaddingMode2[MirrorPaddingMode2[\"symmetric\"] = 1] = \"symmetric\";\n})(MirrorPaddingMode || (MirrorPaddingMode = {}));\nvar wasmMirrorPad;\nfunction setup26(backend2) {\n  wasmMirrorPad = backend2.wasm.cwrap(MirrorPad, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction mirrorPad3(args) {\n  const { inputs: { x }, backend: backend2, attrs: { paddings, mode } } = args;\n  const outShape = paddings.map((p2, i2) => p2[0] + x.shape[i2] + p2[1]);\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const out = backend2.makeOutput(outShape, x.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);\n  const prePaddingsFlat = paddings.map((padTuple) => padTuple[0]);\n  const postPaddingsFlat = paddings.map((padTuple) => padTuple[1]);\n  const prePaddingsBytes = new Uint8Array(new Int32Array(prePaddingsFlat).buffer);\n  const postPaddingsBytes = new Uint8Array(new Int32Array(postPaddingsFlat).buffer);\n  wasmMirrorPad(xId, xShapeBytes, x.shape.length, CppDType[x.dtype], prePaddingsBytes, postPaddingsBytes, MirrorPaddingMode[mode], outId);\n  return out;\n}\nvar mirrorPadConfig3 = {\n  kernelName: MirrorPad,\n  backendName: \"wasm\",\n  kernelFunc: mirrorPad3,\n  setupFunc: setup26\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Multiply.js\nvar supportsFullBroadcast13 = true;\nvar multiplyConfig3 = createBinaryKernelConfig(Multiply, supportsFullBroadcast13);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Neg.js\nvar negConfig3 = createUnaryKernelConfig(Neg);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/NonMaxSuppression_util.js\nfunction parseResultStruct(backend2, resOffset) {\n  const result = new Int32Array(backend2.wasm.HEAPU8.buffer, resOffset, 4);\n  const pSelectedIndices = result[0];\n  const selectedSize = result[1];\n  const pSelectedScores = result[2];\n  const pValidOutputs = result[3];\n  backend2.wasm._free(resOffset);\n  return { pSelectedIndices, selectedSize, pSelectedScores, pValidOutputs };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/NonMaxSuppressionV3.js\nvar wasmFunc4;\nfunction setup27(backend2) {\n  wasmFunc4 = backend2.wasm.cwrap(\n    NonMaxSuppressionV3,\n    \"number\",\n    [\n      \"number\",\n      \"number\",\n      \"number\",\n      \"number\",\n      \"number\"\n    ]\n  );\n}\nfunction kernelFunc(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { iouThreshold, maxOutputSize, scoreThreshold } = attrs;\n  const { boxes, scores } = inputs;\n  const boxesId = backend2.dataIdMap.get(boxes.dataId).id;\n  const scoresId = backend2.dataIdMap.get(scores.dataId).id;\n  const resOffset = wasmFunc4(boxesId, scoresId, maxOutputSize, iouThreshold, scoreThreshold);\n  const { pSelectedIndices, selectedSize, pSelectedScores, pValidOutputs } = parseResultStruct(backend2, resOffset);\n  backend2.wasm._free(pSelectedScores);\n  backend2.wasm._free(pValidOutputs);\n  const selectedIndicesTensor = backend2.makeOutput([selectedSize], \"int32\", pSelectedIndices);\n  return selectedIndicesTensor;\n}\nvar nonMaxSuppressionV3Config3 = {\n  kernelName: NonMaxSuppressionV3,\n  backendName: \"wasm\",\n  setupFunc: setup27,\n  kernelFunc\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/NonMaxSuppressionV4.js\nvar wasmFunc5;\nfunction setup28(backend2) {\n  wasmFunc5 = backend2.wasm.cwrap(\n    NonMaxSuppressionV4,\n    \"number\",\n    [\n      \"number\",\n      \"number\",\n      \"number\",\n      \"number\",\n      \"number\",\n      \"bool\"\n    ]\n  );\n}\nfunction nonMaxSuppressionV43(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { iouThreshold, maxOutputSize, scoreThreshold, padToMaxOutputSize } = attrs;\n  const { boxes, scores } = inputs;\n  const boxesId = backend2.dataIdMap.get(boxes.dataId).id;\n  const scoresId = backend2.dataIdMap.get(scores.dataId).id;\n  const resOffset = wasmFunc5(boxesId, scoresId, maxOutputSize, iouThreshold, scoreThreshold, padToMaxOutputSize);\n  const { pSelectedIndices, selectedSize, pSelectedScores, pValidOutputs } = parseResultStruct(backend2, resOffset);\n  backend2.wasm._free(pSelectedScores);\n  const selectedIndicesTensor = backend2.makeOutput([selectedSize], \"int32\", pSelectedIndices);\n  const validOutputsTensor = backend2.makeOutput([], \"int32\", pValidOutputs);\n  return [selectedIndicesTensor, validOutputsTensor];\n}\nvar nonMaxSuppressionV4Config3 = {\n  kernelName: NonMaxSuppressionV4,\n  backendName: \"wasm\",\n  setupFunc: setup28,\n  kernelFunc: nonMaxSuppressionV43\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/NonMaxSuppressionV5.js\nvar wasmFunc6;\nfunction setup29(backend2) {\n  wasmFunc6 = backend2.wasm.cwrap(\n    NonMaxSuppressionV5,\n    \"number\",\n    [\n      \"number\",\n      \"number\",\n      \"number\",\n      \"number\",\n      \"number\",\n      \"number\"\n    ]\n  );\n}\nfunction kernelFunc2(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { iouThreshold, maxOutputSize, scoreThreshold, softNmsSigma } = attrs;\n  const { boxes, scores } = inputs;\n  const boxesId = backend2.dataIdMap.get(boxes.dataId).id;\n  const scoresId = backend2.dataIdMap.get(scores.dataId).id;\n  const resOffset = wasmFunc6(boxesId, scoresId, maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma);\n  const { pSelectedIndices, selectedSize, pSelectedScores, pValidOutputs } = parseResultStruct(backend2, resOffset);\n  backend2.wasm._free(pValidOutputs);\n  const selectedIndicesTensor = backend2.makeOutput([selectedSize], \"int32\", pSelectedIndices);\n  const selectedScoresTensor = backend2.makeOutput([selectedSize], \"float32\", pSelectedScores);\n  return [selectedIndicesTensor, selectedScoresTensor];\n}\nvar nonMaxSuppressionV5Config3 = {\n  kernelName: NonMaxSuppressionV5,\n  backendName: \"wasm\",\n  setupFunc: setup29,\n  kernelFunc: kernelFunc2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/NotEqual.js\nvar supportsFullBroadcast14 = false;\nvar notEqualConfig3 = createBinaryKernelConfig(NotEqual, supportsFullBroadcast14, \"bool\");\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/OneHot.js\nvar wasmOneHot;\nfunction setup30(backend2) {\n  wasmOneHot = backend2.wasm.cwrap(OneHot, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction oneHot4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { indices } = inputs;\n  const { depth, onValue, offValue } = attrs;\n  const out = backend2.makeOutput([...indices.shape, depth], \"int32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const indicesData = backend2.dataIdMap.get(indices.dataId);\n  const indicesId = indicesData.id;\n  wasmOneHot(indicesId, depth, onValue, offValue, outId);\n  return out;\n}\nvar oneHotConfig3 = {\n  kernelName: OneHot,\n  backendName: \"wasm\",\n  setupFunc: setup30,\n  kernelFunc: oneHot4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/OnesLike.js\nfunction onesLike4(args) {\n  const { inputs: { x }, backend: backend2 } = args;\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  const outVals = backend2.typedArrayFromHeap(out);\n  outVals.fill(1);\n  return out;\n}\nvar onesLikeConfig3 = {\n  kernelName: OnesLike,\n  backendName: \"wasm\",\n  kernelFunc: onesLike4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Pack.js\nfunction pack3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { axis } = attrs;\n  if (inputs.length === 1) {\n    return expandDims5({ inputs: { input: inputs[0] }, backend: backend2, attrs: { dim: axis } });\n  }\n  const shape = inputs[0].shape;\n  const dtype = inputs[0].dtype;\n  inputs.forEach((t2) => {\n    util_exports.assertShapesMatch(shape, t2.shape, \"All tensors passed to stack must have matching shapes\");\n    util_exports.assert(dtype === t2.dtype, () => \"All tensors passed to stack must have matching dtypes\");\n  });\n  const intermediateTensorInfos = [];\n  const expandedTensors = inputs.map((t2) => {\n    const expandedT = expandDims5({ inputs: { input: t2 }, backend: backend2, attrs: { dim: axis } });\n    intermediateTensorInfos.push(expandedT);\n    return expandedT;\n  });\n  const result = concat4({ inputs: expandedTensors, backend: backend2, attrs: { axis } });\n  intermediateTensorInfos.forEach((t2) => backend2.disposeData(t2.dataId));\n  return result;\n}\nvar packConfig3 = {\n  kernelName: Pack,\n  backendName: \"wasm\",\n  kernelFunc: pack3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/PadV2.js\nvar wasmPadV2;\nfunction setup31(backend2) {\n  wasmPadV2 = backend2.wasm.cwrap(PadV2, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction pad2(args) {\n  const { inputs: { x }, backend: backend2, attrs: { paddings, constantValue } } = args;\n  const outShape = paddings.map((p2, i2) => p2[0] + x.shape[i2] + p2[1]);\n  if (util_exports.sizeFromShape(x.shape) === 0) {\n    return fill4({\n      backend: backend2,\n      attrs: { shape: outShape, value: constantValue, dtype: x.dtype }\n    });\n  }\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const out = backend2.makeOutput(outShape, x.dtype);\n  const outTensorData = backend2.dataIdMap.get(out.dataId);\n  const outId = outTensorData.id;\n  const xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);\n  const prePaddingsFlat = paddings.map((padTuple) => padTuple[0]);\n  const postPaddingsFlat = paddings.map((padTuple) => padTuple[1]);\n  const prePaddingsBytes = new Uint8Array(new Int32Array(prePaddingsFlat).buffer);\n  const postPaddingsBytes = new Uint8Array(new Int32Array(postPaddingsFlat).buffer);\n  wasmPadV2(xId, xShapeBytes, x.shape.length, CppDType[x.dtype], prePaddingsBytes, postPaddingsBytes, constantValue, outId);\n  return out;\n}\nvar padV2Config3 = {\n  kernelName: PadV2,\n  backendName: \"wasm\",\n  kernelFunc: pad2,\n  setupFunc: setup31\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Pow.js\nvar supportsFullBroadcast15 = false;\nvar powConfig3 = createBinaryKernelConfig(Pow, supportsFullBroadcast15);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Prelu.js\nvar wasmPrelu;\nfunction setup32(backend2) {\n  wasmPrelu = backend2.wasm.cwrap(Prelu, null, [\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction prelu5(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x, alpha } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const weightsId = backend2.dataIdMap.get(alpha.dataId).id;\n  let inputId = xId;\n  const input2 = x;\n  let castedInput = input2;\n  if (input2.dtype !== \"float32\") {\n    castedInput = cast5({ backend: backend2, inputs: { x }, attrs: { dtype: \"float32\" } });\n    inputId = backend2.dataIdMap.get(castedInput.dataId).id;\n  }\n  const out = backend2.makeOutput(x.shape, \"float32\");\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmPrelu(inputId, weightsId, outId);\n  if (input2.dtype !== \"float32\") {\n    backend2.disposeData(castedInput.dataId);\n  }\n  return out;\n}\nvar preluConfig3 = {\n  kernelName: Prelu,\n  backendName: \"wasm\",\n  setupFunc: setup32,\n  kernelFunc: prelu5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Prod.js\nvar wasmProd;\nfunction setup33(backend2) {\n  wasmProd = backend2.wasm.cwrap(Prod, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction prod4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { axis, keepDims } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  let reductionAxes = axes;\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    if (transposedId !== xId) {\n      input2 = transposed;\n      inputId = transposedId;\n      reductionAxes = backend_util_exports.getInnerMostAxes(reductionAxes.length, input2.shape.length);\n    }\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"prod\", reductionAxes, input2.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, reductionAxes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const out = backend2.makeOutput(outShape, input2.dtype);\n  if (util_exports.sizeFromShape(input2.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmProd(inputId, reduceSize, CppDType[out.dtype], outId);\n  }\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(out.shape, originalAxes);\n    out.shape = newShape;\n  }\n  return out;\n}\nvar prodConfig3 = {\n  kernelName: Prod,\n  backendName: \"wasm\",\n  setupFunc: setup33,\n  kernelFunc: prod4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Range.js\nvar range5 = (args) => {\n  const { backend: backend2, attrs } = args;\n  const { start, stop, step: step5, dtype } = attrs;\n  const values = rangeImpl(start, stop, step5, dtype);\n  const out = backend2.makeOutput([values.length], dtype);\n  const outVals = backend2.typedArrayFromHeap(out);\n  outVals.set(values);\n  return out;\n};\nvar rangeConfig3 = {\n  kernelName: Range,\n  backendName: \"wasm\",\n  kernelFunc: range5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/RealDiv.js\nvar supportsFullBroadcast16 = true;\nvar realDivConfig3 = createBinaryKernelConfig(RealDiv, supportsFullBroadcast16);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Relu.js\nvar reluConfig3 = createUnaryKernelConfig(Relu);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Relu6.js\nvar relu6Config3 = createUnaryKernelConfig(Relu6);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/ResizeBilinear.js\nvar wasmResizeBilinear;\nfunction setup34(backend2) {\n  wasmResizeBilinear = backend2.wasm.cwrap(ResizeBilinear, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction resizeBilinear4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, halfPixelCenters, size } = attrs;\n  const [newHeight, newWidth] = size;\n  const [batch, oldHeight, oldWidth, numChannels] = images.shape;\n  const outShape = [batch, newHeight, newWidth, numChannels];\n  let xData = backend2.dataIdMap.get(images.dataId);\n  let castedData;\n  if (xData.dtype !== \"float32\") {\n    castedData = cast5({ backend: backend2, inputs: { x: images }, attrs: { dtype: \"float32\" } });\n    xData = backend2.dataIdMap.get(castedData.dataId);\n  }\n  const xId = xData.id;\n  const out = backend2.makeOutput(outShape, \"float32\");\n  if (util_exports.sizeFromShape(images.shape) === 0) {\n    return out;\n  }\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmResizeBilinear(xId, batch, oldHeight, oldWidth, numChannels, newHeight, newWidth, alignCorners ? 1 : 0, halfPixelCenters ? 1 : 0, outId);\n  if (castedData != null) {\n    backend2.disposeData(castedData.dataId);\n  }\n  return out;\n}\nvar resizeBilinearConfig3 = {\n  kernelName: ResizeBilinear,\n  backendName: \"wasm\",\n  setupFunc: setup34,\n  kernelFunc: resizeBilinear4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/ResizeNearestNeighbor.js\nvar wasmResizeNearestNeighbor;\nfunction setup35(backend2) {\n  wasmResizeNearestNeighbor = backend2.wasm.cwrap(ResizeNearestNeighbor, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction resizeNearestNeighbor4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, halfPixelCenters, size } = attrs;\n  const [newHeight, newWidth] = size;\n  const [batch, oldHeight, oldWidth, numChannels] = images.shape;\n  const outShape = [batch, newHeight, newWidth, numChannels];\n  const out = backend2.makeOutput(outShape, \"float32\");\n  if (util_exports.sizeFromShape(images.shape) === 0) {\n    return out;\n  }\n  let xData = backend2.dataIdMap.get(images.dataId);\n  let castedData;\n  if (xData.dtype !== \"float32\") {\n    castedData = cast5({\n      backend: backend2,\n      inputs: { x: images },\n      attrs: { dtype: \"float32\" }\n    });\n    xData = backend2.dataIdMap.get(castedData.dataId);\n  }\n  const xId = xData.id;\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmResizeNearestNeighbor(xId, batch, oldHeight, oldWidth, numChannels, newHeight, newWidth, alignCorners ? 1 : 0, halfPixelCenters ? 1 : 0, outId);\n  if (castedData != null) {\n    backend2.disposeData(castedData.dataId);\n  }\n  return out;\n}\nvar resizeNearestNeighborConfig3 = {\n  kernelName: ResizeNearestNeighbor,\n  backendName: \"wasm\",\n  setupFunc: setup35,\n  kernelFunc: resizeNearestNeighbor4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Reverse.js\nvar wasmReverse;\nfunction setup36(backend2) {\n  wasmReverse = backend2.wasm.cwrap(Reverse, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction reverse4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { dims } = attrs;\n  const axes = util_exports.parseAxisParam(dims, x.shape);\n  if (x.shape.length === 0) {\n    return identity4({ inputs: { x }, backend: backend2 });\n  }\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const axesBytes = new Uint8Array(new Int32Array(axes).buffer);\n  const outShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);\n  wasmReverse(xId, axesBytes, axes.length, outShapeBytes, x.shape.length, outId);\n  const reshaped = reshape5({ inputs: { x: out }, attrs: { shape: x.shape }, backend: backend2 });\n  backend2.disposeData(out.dataId);\n  return reshaped;\n}\nvar reverseConfig3 = {\n  kernelName: Reverse,\n  backendName: \"wasm\",\n  kernelFunc: reverse4,\n  setupFunc: setup36\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/RotateWithOffset.js\nvar wasmRotate;\nfunction setup37(backend2) {\n  wasmRotate = backend2.wasm.cwrap(RotateWithOffset, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction rotateWithOffset2(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { image: image2 } = inputs;\n  const { radians, fillValue, center } = attrs;\n  const out = backend2.makeOutput(image2.shape, image2.dtype);\n  const imageId = backend2.dataIdMap.get(image2.dataId).id;\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n  const [centerX, centerY] = backend_util_exports.getImageCenter(center, imageHeight, imageWidth);\n  const fillIsBlack = fillValue === 0;\n  const fullOpacityValue = 255;\n  const fillValues2 = typeof fillValue === \"number\" ? [fillValue, fillValue, fillValue, fillIsBlack ? 0 : fullOpacityValue] : [...fillValue, fullOpacityValue];\n  const fillBytes = new Uint8Array(new Int32Array(fillValues2).buffer);\n  wasmRotate(imageId, batch, imageHeight, imageWidth, numChannels, radians, centerX, centerY, fillBytes, fillValues2.length, outId);\n  return out;\n}\nvar rotateWithOffsetConfig3 = {\n  kernelName: RotateWithOffset,\n  backendName: \"wasm\",\n  kernelFunc: rotateWithOffset2,\n  setupFunc: setup37\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Round.js\nvar roundConfig3 = createUnaryKernelConfig(Round);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Rsqrt.js\nvar rsqrtConfig3 = createUnaryKernelConfig(Rsqrt);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/ScatterNd.js\nvar wasmScatterNd;\nfunction setup38(backend2) {\n  wasmScatterNd = backend2.wasm.cwrap(ScatterNd, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction scatterNd3(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { indices, updates } = inputs;\n  const { shape } = attrs;\n  const out = backend2.makeOutput(shape, updates.dtype);\n  if (util_exports.sizeFromShape(shape) === 0) {\n    return out;\n  }\n  const { sliceRank, numUpdates, sliceSize, strides, outputSize } = scatter_nd_util_exports.calculateShapes(updates, indices, shape);\n  const indicesData = backend2.dataIdMap.get(indices.dataId);\n  const indicesId = indicesData.id;\n  const updatesData = backend2.dataIdMap.get(updates.dataId);\n  const updatesId = updatesData.id;\n  const stridesBytes = new Uint8Array(new Int32Array(strides).buffer);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmScatterNd(indicesId, updatesId, CppDType[updates.dtype], sliceRank, numUpdates, sliceSize, stridesBytes, outputSize, outId);\n  return out;\n}\nvar scatterNdConfig3 = {\n  kernelName: ScatterNd,\n  backendName: \"wasm\",\n  setupFunc: setup38,\n  kernelFunc: scatterNd3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Select.js\nvar wasmSelect;\nfunction setup39(backend2) {\n  wasmSelect = backend2.wasm.cwrap(\"SelectV2\", null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction select4(args) {\n  const { inputs, backend: backend2 } = args;\n  const { condition, t: t2, e: e2 } = inputs;\n  const conditionId = backend2.dataIdMap.get(condition.dataId).id;\n  const tId = backend2.dataIdMap.get(t2.dataId).id;\n  const eId = backend2.dataIdMap.get(e2.dataId).id;\n  const out = backend2.makeOutput(t2.shape, t2.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const cRank = condition.shape.length;\n  const tRank = t2.shape.length;\n  const offset = cRank === 0 || cRank > 1 || tRank === 1 ? 1 : util_exports.sizeFromShape(t2.shape.slice(1));\n  wasmSelect(conditionId, tId, eId, offset, outId);\n  return out;\n}\nvar selectConfig3 = {\n  kernelName: Select,\n  backendName: \"wasm\",\n  kernelFunc: select4,\n  setupFunc: setup39\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Sigmoid.js\nvar wasmFunc7;\nfunction setup40(backend2) {\n  wasmFunc7 = backend2.wasm.cwrap(Sigmoid, null, [\"number\", \"number\"]);\n}\nfunction sigmoid4(args) {\n  const { backend: backend2, inputs: { x } } = args;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  if (util_exports.sizeFromShape(out.shape) === 0) {\n    return out;\n  }\n  wasmFunc7(xId, outId);\n  return out;\n}\nvar sigmoidConfig3 = {\n  kernelName: \"Sigmoid\",\n  backendName: \"wasm\",\n  setupFunc: setup40,\n  kernelFunc: sigmoid4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Sin.js\nvar sinConfig3 = createUnaryKernelConfig(Sin);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Softmax.js\nvar wasmFunc8;\nfunction setup41(backend2) {\n  wasmFunc8 = backend2.wasm.cwrap(Softmax, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction softmax5(args) {\n  const { backend: backend2, inputs: { logits }, attrs: { dim } } = args;\n  const xId = backend2.dataIdMap.get(logits.dataId).id;\n  const out = backend2.makeOutput(logits.shape, logits.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const channels = logits.shape[dim];\n  const batch = util_exports.sizeFromShape(logits.shape) / channels;\n  if (util_exports.sizeFromShape(out.shape) === 0) {\n    return out;\n  }\n  wasmFunc8(xId, outId, channels, batch);\n  return out;\n}\nvar softmaxConfig3 = {\n  kernelName: Softmax,\n  backendName: \"wasm\",\n  setupFunc: setup41,\n  kernelFunc: softmax5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SpaceToBatchND.js\nfunction spaceToBatchND4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, paddings } = attrs;\n  const prod6 = util_exports.sizeFromShape(blockShape);\n  const completePaddings = [[0, 0]];\n  completePaddings.push(...paddings);\n  for (let i2 = 1 + blockShape.length; i2 < x.shape.length; ++i2) {\n    completePaddings.push([0, 0]);\n  }\n  const paddedX = padV2Config3.kernelFunc({\n    inputs: { x },\n    backend: backend2,\n    attrs: { paddings: completePaddings, constantValue: 0 }\n  });\n  const reshapedPaddedShape = backend_util_exports.getReshaped(paddedX.shape, blockShape, prod6, false);\n  const permutedReshapedPaddedPermutation = backend_util_exports.getPermuted(reshapedPaddedShape.length, blockShape.length, false);\n  const flattenShape = backend_util_exports.getReshapedPermuted(paddedX.shape, blockShape, prod6, false);\n  const reshapeInputs = { x: paddedX };\n  const reshapeAttrs = { shape: reshapedPaddedShape };\n  const paddedXReshaped = reshape5({ inputs: reshapeInputs, backend: backend2, attrs: reshapeAttrs });\n  const transposeInputs = { x: paddedXReshaped };\n  const transposeAttrs = { perm: permutedReshapedPaddedPermutation };\n  const paddedXT = transpose4({ inputs: transposeInputs, backend: backend2, attrs: transposeAttrs });\n  const resultReshapeInputs = { x: paddedXT };\n  const resultReshapeAttrs = { shape: flattenShape };\n  const result = reshape5({ inputs: resultReshapeInputs, backend: backend2, attrs: resultReshapeAttrs });\n  backend2.disposeData(paddedX.dataId);\n  backend2.disposeData(paddedXReshaped.dataId);\n  backend2.disposeData(paddedXT.dataId);\n  return result;\n}\nvar spaceToBatchNDConfig3 = {\n  kernelName: SpaceToBatchND,\n  backendName: \"wasm\",\n  kernelFunc: spaceToBatchND4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SparseFillEmptyRows.js\nvar wasmSparseFillEmptyRows;\nfunction setup42(backend2) {\n  wasmSparseFillEmptyRows = backend2.wasm.cwrap(\"SparseFillEmptyRows\", \"number\", [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction sparseFillEmptyRows4(args) {\n  const { backend: backend2, inputs } = args;\n  const { indices, values, denseShape, defaultValue } = inputs;\n  const indicesCount = indices.shape[0];\n  const rank = indices.shape[1];\n  const denseRows = backend2.readSync(denseShape.dataId)[0];\n  const maxOutputIndicesShape = [indicesCount + denseRows, rank];\n  const indicesId = backend2.dataIdMap.get(indices.dataId).id;\n  const valuesId = backend2.dataIdMap.get(values.dataId).id;\n  const defaultValueId = backend2.dataIdMap.get(defaultValue.dataId).id;\n  const outputIndices = backend2.makeOutput(maxOutputIndicesShape, indices.dtype);\n  const outputIndicesId = backend2.dataIdMap.get(outputIndices.dataId).id;\n  const outputValues = backend2.makeOutput(maxOutputIndicesShape.slice(0, 1), values.dtype);\n  const outputValuesId = backend2.dataIdMap.get(outputValues.dataId).id;\n  const emptyRowIndicator = backend2.makeOutput([denseRows], \"bool\");\n  const emptyRowIndicatorId = backend2.dataIdMap.get(emptyRowIndicator.dataId).id;\n  const reverseIndexMap = backend2.makeOutput([indicesCount], indices.dtype);\n  const reverseIndexMapId = backend2.dataIdMap.get(reverseIndexMap.dataId).id;\n  const exceptionValues = backend2.makeOutput([4], \"int32\");\n  const exceptionValuesId = backend2.dataIdMap.get(exceptionValues.dataId).id;\n  const outputRows = wasmSparseFillEmptyRows(indicesId, valuesId, CppDType[values.dtype], indicesCount, denseRows, rank, defaultValueId, outputIndicesId, outputValuesId, emptyRowIndicatorId, reverseIndexMapId, exceptionValuesId);\n  const exceptionValuesArray = backend2.readSync(exceptionValues.dataId);\n  let exceptionMessage;\n  switch (exceptionValuesArray[0]) {\n    case 1: {\n      exceptionMessage = backend_util_exports.getSparseFillEmptyRowsIndicesDenseShapeMismatch(exceptionValuesArray[1]);\n      break;\n    }\n    case 2: {\n      exceptionMessage = backend_util_exports.getSparseFillEmptyRowsNegativeIndexErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2]);\n      break;\n    }\n    case 3:\n      exceptionMessage = backend_util_exports.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2], exceptionValuesArray[3]);\n      break;\n    default:\n      exceptionMessage = \"\";\n  }\n  backend2.disposeData(exceptionValues.dataId);\n  if (exceptionMessage) {\n    backend2.disposeData(outputIndices.dataId);\n    backend2.disposeData(outputValues.dataId);\n    backend2.disposeData(emptyRowIndicator.dataId);\n    backend2.disposeData(reverseIndexMap.dataId);\n    throw new Error(exceptionMessage);\n  }\n  let resizedIndices = outputIndices;\n  let resizedValues = outputValues;\n  if (outputRows !== maxOutputIndicesShape[0]) {\n    resizedIndices = slice4({\n      inputs: { x: outputIndices },\n      attrs: { begin: 0, size: [outputRows, rank] },\n      backend: backend2\n    });\n    resizedValues = slice4({\n      inputs: { x: outputValues },\n      attrs: { begin: 0, size: outputRows },\n      backend: backend2\n    });\n    backend2.disposeData(outputIndices.dataId);\n    backend2.disposeData(outputValues.dataId);\n  }\n  return [resizedIndices, resizedValues, emptyRowIndicator, reverseIndexMap];\n}\nvar sparseFillEmptyRowsConfig3 = {\n  kernelName: SparseFillEmptyRows,\n  backendName: \"wasm\",\n  setupFunc: setup42,\n  kernelFunc: sparseFillEmptyRows4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SparseReshape.js\nvar wasmSparseReshape;\nfunction setup43(backend2) {\n  wasmSparseReshape = backend2.wasm.cwrap(SparseReshape, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction sparseReshape4(args) {\n  const { backend: backend2, inputs } = args;\n  const { inputIndices, inputShape, newShape } = inputs;\n  if (inputIndices.shape.length !== 2) {\n    throw new Error(`Input indices should be a matrix but received shape\n        ${inputIndices.shape}`);\n  }\n  if (inputShape.shape.length !== 1) {\n    throw new Error(`Input shape should be a vector but received shape\n        ${inputShape.shape}`);\n  }\n  if (newShape.shape.length !== 1) {\n    throw new Error(`Target shape should be a vector but received shape ${newShape.shape}`);\n  }\n  const inputIndicesId = backend2.dataIdMap.get(inputIndices.dataId).id;\n  const inputShapeId = backend2.dataIdMap.get(inputShape.dataId).id;\n  const newShapeId = backend2.dataIdMap.get(newShape.dataId).id;\n  const nnz = inputIndices.shape[0];\n  const outputRank = util_exports.sizeFromShape(newShape.shape);\n  const newIndices = backend2.makeOutput([nnz, outputRank], inputIndices.dtype);\n  const newIndicesId = backend2.dataIdMap.get(newIndices.dataId).id;\n  const outputShape = backend2.makeOutput([outputRank], newShape.dtype);\n  const outputShapeId = backend2.dataIdMap.get(outputShape.dataId).id;\n  const exceptionValues = backend2.makeOutput([3], \"int32\");\n  const exceptionValuesId = backend2.dataIdMap.get(exceptionValues.dataId).id;\n  wasmSparseReshape(inputIndicesId, inputShapeId, newShapeId, nnz, newIndicesId, outputShapeId, exceptionValuesId);\n  const exceptionValuesArray = backend2.readSync(exceptionValues.dataId);\n  let exceptionMessage;\n  switch (exceptionValuesArray[0]) {\n    case 0: {\n      exceptionMessage = backend_util_exports.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2]);\n      break;\n    }\n    case 1: {\n      exceptionMessage = backend_util_exports.getSparseReshapeNegativeOutputDimErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2]);\n      break;\n    }\n    case 2:\n      exceptionMessage = backend_util_exports.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage();\n      break;\n    case 3: {\n      const inputShapeValues = Array.from(backend2.readSync(inputShape.dataId)), outputShapeValues = Array.from(backend2.readSync(outputShape.dataId));\n      exceptionMessage = backend_util_exports.getSparseReshapeInputOutputMultipleErrorMessage(inputShapeValues, outputShapeValues);\n      break;\n    }\n    case 4: {\n      const inputShapeValues = Array.from(backend2.readSync(inputShape.dataId)), outputShapeValues = Array.from(backend2.readSync(outputShape.dataId));\n      exceptionMessage = backend_util_exports.getSparseReshapeInputOutputMismatchErrorMessage(inputShapeValues, outputShapeValues);\n      break;\n    }\n    default:\n      exceptionMessage = \"\";\n  }\n  backend2.disposeData(exceptionValues.dataId);\n  if (exceptionMessage) {\n    backend2.disposeData(newIndices.dataId);\n    backend2.disposeData(outputShape.dataId);\n    throw new Error(exceptionMessage);\n  }\n  return [newIndices, outputShape];\n}\nvar sparseReshapeConfig3 = {\n  kernelName: SparseReshape,\n  backendName: \"wasm\",\n  setupFunc: setup43,\n  kernelFunc: sparseReshape4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SparseSegmentReduction.js\nvar wasmSparseSegmentReduction;\nfunction setup44(backend2) {\n  wasmSparseSegmentReduction = backend2.wasm.cwrap(\"SparseSegmentReduction\", null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction sparseSegmentReduction(args, isMean) {\n  const { backend: backend2, inputs } = args;\n  const { data, indices, segmentIds } = inputs;\n  const numIndices = indices.shape[0];\n  const segmentIdsBack = backend2.readSync(segmentIds.dataId, numIndices - 1, numIndices)[0];\n  const lastSegmentIdPlusOne = numIndices > 0 ? segmentIdsBack + 1 : 0;\n  const outputRows = lastSegmentIdPlusOne;\n  if (outputRows < 0) {\n    throw new Error(backend_util_exports.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());\n  }\n  const outputShape = data.shape.slice();\n  outputShape[0] = outputRows;\n  const dataId = backend2.dataIdMap.get(data.dataId).id;\n  const indicesId = backend2.dataIdMap.get(indices.dataId).id;\n  const segmentIdsId = backend2.dataIdMap.get(segmentIds.dataId).id;\n  const output = backend2.makeOutput(outputShape, data.dtype);\n  const outputId = backend2.dataIdMap.get(output.dataId).id;\n  const exceptionValues = backend2.makeOutput([4], \"int32\");\n  const exceptionValuesId = backend2.dataIdMap.get(exceptionValues.dataId).id;\n  wasmSparseSegmentReduction(dataId, CppDType[data.dtype], data.shape[0], indicesId, segmentIdsId, outputId, exceptionValuesId, isMean, 0);\n  const exceptionValuesArray = backend2.readSync(exceptionValues.dataId);\n  let exceptionMessage;\n  switch (exceptionValuesArray[0]) {\n    case 0: {\n      exceptionMessage = backend_util_exports.getSparseSegmentReductionNegativeSegmentIdsErrorMessage();\n      break;\n    }\n    case 1: {\n      exceptionMessage = backend_util_exports.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage();\n      break;\n    }\n    case 2:\n      exceptionMessage = backend_util_exports.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2]);\n      break;\n    case 3:\n      exceptionMessage = backend_util_exports.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(exceptionValuesArray[1], exceptionValuesArray[2], exceptionValuesArray[3]);\n      break;\n    default:\n      exceptionMessage = \"\";\n  }\n  backend2.disposeData(exceptionValues.dataId);\n  if (exceptionMessage) {\n    backend2.disposeData(output.dataId);\n    throw new Error(exceptionMessage);\n  }\n  return output;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SparseSegmentMean.js\nfunction sparseSegmentMean4(args) {\n  return sparseSegmentReduction(args, true);\n}\nvar sparseSegmentMeanConfig3 = {\n  kernelName: SparseSegmentMean,\n  backendName: \"wasm\",\n  setupFunc: setup44,\n  kernelFunc: sparseSegmentMean4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SparseSegmentSum.js\nfunction sparseSegmentSum4(args) {\n  return sparseSegmentReduction(args, false);\n}\nvar sparseSegmentSumConfig3 = {\n  kernelName: SparseSegmentSum,\n  backendName: \"wasm\",\n  setupFunc: setup44,\n  kernelFunc: sparseSegmentSum4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SplitV.js\nfunction splitV3(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { x } = inputs;\n  const { numOrSizeSplits, axis } = attrs;\n  const $axis = util_exports.parseAxisParam(axis, x.shape)[0];\n  const splitSizes = backend_util_exports.prepareSplitSize(x, numOrSizeSplits, $axis);\n  const begin = new Array(x.shape.length).fill(0);\n  const size = x.shape.slice();\n  return splitSizes.map((s2) => {\n    const xSliceSize = [...size];\n    xSliceSize[$axis] = s2;\n    const xSlice = slice4({ inputs: { x }, attrs: { begin, size: xSliceSize }, backend: backend2 });\n    begin[$axis] += s2;\n    return xSlice;\n  });\n}\nvar splitVConfig3 = {\n  kernelName: SplitV,\n  backendName: \"wasm\",\n  kernelFunc: splitV3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Sqrt.js\nvar sqrtConfig3 = createUnaryKernelConfig(Sqrt);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Square.js\nvar squareConfig3 = createUnaryKernelConfig(Square);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/SquaredDifference.js\nvar supportsFullBroadcast17 = true;\nvar squaredDifferenceConfig3 = createBinaryKernelConfig(SquaredDifference, supportsFullBroadcast17);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Step.js\nvar wasmStep;\nfunction setup45(backend2) {\n  wasmStep = backend2.wasm.cwrap(Step, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction step4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { alpha } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmStep(xId, alpha, CppDType[x.dtype], outId);\n  return out;\n}\nvar stepConfig3 = {\n  kernelName: Step,\n  backendName: \"wasm\",\n  setupFunc: setup45,\n  kernelFunc: step4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/StridedSlice.js\nvar wasmStridedSlice;\nfunction setup46(backend2) {\n  wasmStridedSlice = backend2.wasm.cwrap(StridedSlice, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"array\",\n    \"array\",\n    \"array\",\n    \"array\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction stridedSlice4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { x } = inputs;\n  const { begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask } = attrs;\n  const { finalShapeSparse, finalShape, isIdentity, sliceDim0, isSimpleSlice, begin: $begin, end: $end, strides: $strides } = slice_util_exports.sliceInfo(x.shape, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask);\n  let result;\n  if (isIdentity) {\n    result = reshape5({ inputs: { x }, backend: backend2, attrs: { shape: finalShape } });\n  } else if (sliceDim0 || isSimpleSlice) {\n    util_exports.assert(x.shape.length >= 1, () => `Input must have rank at least 1, got: ${x.shape.length}`);\n    const size = slice_util_exports.computeOutShape($begin, $end, $strides);\n    const sliced = slice4({ inputs: { x }, backend: backend2, attrs: { begin: $begin, size } });\n    result = reshape5({ inputs: { x: sliced }, backend: backend2, attrs: { shape: finalShape } });\n    backend2.disposeData(sliced.dataId);\n  } else {\n    const out = backend2.makeOutput(finalShapeSparse, \"float32\");\n    const xId = backend2.dataIdMap.get(x.dataId).id;\n    const xStridesBytes = new Uint8Array(new Int32Array(util_exports.computeStrides(x.shape)).buffer);\n    const beginBytes = new Uint8Array(new Int32Array($begin).buffer);\n    const endBytes = new Uint8Array(new Int32Array($end).buffer);\n    const stridesBytes = new Uint8Array(new Int32Array($strides).buffer);\n    const outputShapeBytes = new Uint8Array(new Int32Array(finalShapeSparse).buffer);\n    const outStridesBytes = new Uint8Array(new Int32Array(util_exports.computeStrides(finalShapeSparse)).buffer);\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmStridedSlice(xId, xStridesBytes, x.shape.length, beginBytes, endBytes, stridesBytes, outputShapeBytes, outStridesBytes, finalShapeSparse.length, outId);\n    result = reshape5({ inputs: { x: out }, backend: backend2, attrs: { shape: finalShape } });\n    backend2.disposeData(out.dataId);\n  }\n  return result;\n}\nvar stridedSliceConfig3 = {\n  kernelName: StridedSlice,\n  backendName: \"wasm\",\n  setupFunc: setup46,\n  kernelFunc: stridedSlice4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/StringNGrams.js\nfunction stringNGrams4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { data, dataSplits } = inputs;\n  const { separator, nGramWidths, leftPad, rightPad: rightPad2, padWidth, preserveShortSequences } = attrs;\n  const $data = backend2.readSync(data.dataId);\n  const $dataSplits = backend2.readSync(dataSplits.dataId);\n  const [nGrams, nGramsSplits] = stringNGramsImpl($data, $dataSplits, separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences);\n  const nGramsOut = backend2.makeOutput([nGrams.length], \"string\");\n  const nGramsOutData = backend2.dataIdMap.get(nGramsOut.dataId);\n  nGramsOutData.stringBytes = nGrams;\n  const nGramsSplitsOut = backend2.makeOutput(dataSplits.shape, \"int32\");\n  const nGramsSplitsOutVals = backend2.typedArrayFromHeap(nGramsSplitsOut);\n  nGramsSplitsOutVals.set(nGramsSplits);\n  return [nGramsOut, nGramsSplitsOut];\n}\nvar stringNGramsConfig3 = {\n  kernelName: StringNGrams,\n  backendName: \"wasm\",\n  kernelFunc: stringNGrams4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/StringSplit.js\nfunction stringSplit4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { input: input2, delimiter } = inputs;\n  const { skipEmpty } = attrs;\n  const inputVals = backend2.readSync(input2.dataId);\n  const delimiterVals = backend2.readSync(delimiter.dataId);\n  const [indices, values, shape] = stringSplitImpl(inputVals, delimiterVals[0], skipEmpty);\n  const outputSize = values.length;\n  const indicesOut = backend2.makeOutput([outputSize, 2], \"int32\");\n  const indicesOutVals = backend2.typedArrayFromHeap(indicesOut);\n  indicesOutVals.set(indices);\n  const valuesOut = backend2.makeOutput([outputSize], \"string\");\n  const valuesOutData = backend2.dataIdMap.get(valuesOut.dataId);\n  valuesOutData.stringBytes = values;\n  const shapeOut = backend2.makeOutput([2], \"int32\");\n  const shapeOutVals = backend2.typedArrayFromHeap(shapeOut);\n  shapeOutVals.set(shape);\n  return [indicesOut, valuesOut, shapeOut];\n}\nvar stringSplitConfig3 = {\n  kernelName: StringSplit,\n  backendName: \"wasm\",\n  kernelFunc: stringSplit4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/StringToHashBucketFast.js\nfunction stringToHashBucketFast4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { input: input2 } = inputs;\n  const { numBuckets } = attrs;\n  const inputVals = backend2.readSync(input2.dataId);\n  const values = stringToHashBucketFastImpl(inputVals, numBuckets);\n  const out = backend2.makeOutput(input2.shape, \"int32\");\n  const outVals = backend2.typedArrayFromHeap(out);\n  outVals.set(values);\n  return out;\n}\nvar stringToHashBucketFastConfig3 = {\n  kernelName: StringToHashBucketFast,\n  backendName: \"wasm\",\n  kernelFunc: stringToHashBucketFast4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Sub.js\nvar supportsFullBroadcast18 = true;\nvar subConfig3 = createBinaryKernelConfig(Sub, supportsFullBroadcast18);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Sum.js\nvar wasmSum;\nfunction setup47(backend2) {\n  wasmSum = backend2.wasm.cwrap(Sum, null, [\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction sum5(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { axis, keepDims } = attrs;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  let inputId = xId;\n  let input2 = x;\n  const { transposed, axes, originalAxes, inputWasTransposed } = permuteAxesAndTranspose(x, axis, backend2);\n  let reductionAxes = axes;\n  if (inputWasTransposed) {\n    const transposedId = backend2.dataIdMap.get(transposed.dataId).id;\n    if (transposedId !== xId) {\n      input2 = transposed;\n      inputId = transposedId;\n      reductionAxes = backend_util_exports.getInnerMostAxes(reductionAxes.length, input2.shape.length);\n    }\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"sum\", reductionAxes, input2.shape.length);\n  const [outShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, reductionAxes);\n  const reduceSize = util_exports.sizeFromShape(reduceShape);\n  const out = backend2.makeOutput(outShape, input2.dtype);\n  if (util_exports.sizeFromShape(input2.shape) !== 0) {\n    const outId = backend2.dataIdMap.get(out.dataId).id;\n    wasmSum(inputId, reduceSize, CppDType[out.dtype], outId);\n  }\n  if (inputWasTransposed) {\n    backend2.disposeData(transposed.dataId);\n  }\n  if (keepDims) {\n    const newShape = backend_util_exports.expandShapeToKeepDim(out.shape, originalAxes);\n    out.shape = newShape;\n  }\n  return out;\n}\nvar sumConfig3 = {\n  kernelName: Sum,\n  backendName: \"wasm\",\n  setupFunc: setup47,\n  kernelFunc: sum5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Tan.js\nvar tanConfig3 = createUnaryKernelConfig(Tan);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Tanh.js\nvar tanhConfig3 = createUnaryKernelConfig(Tanh);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Tile.js\nvar wasmTile;\nfunction setup48(backend2) {\n  wasmTile = backend2.wasm.cwrap(Tile, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction tile5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const { reps } = attrs;\n  const newShape = new Array(x.shape.length);\n  for (let i2 = 0; i2 < newShape.length; i2++) {\n    newShape[i2] = x.shape[i2] * reps[i2];\n  }\n  const xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);\n  const newShapeBytes = new Uint8Array(new Int32Array(newShape).buffer);\n  const out = backend2.makeOutput(newShape, x.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  wasmTile(xId, xShapeBytes, x.shape.length, newShapeBytes, newShape.length, CppDType[out.dtype], outId);\n  return out;\n}\nvar tileConfig3 = {\n  kernelName: Tile,\n  backendName: \"wasm\",\n  setupFunc: setup48,\n  kernelFunc: tile5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/TopK.js\nvar wasmTopK;\nfunction setup49(backend2) {\n  wasmTopK = backend2.wasm.cwrap(TopK, null, [\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"bool\",\n    \"number\",\n    \"number\"\n  ]);\n}\nvar topk2 = ({ inputs, backend: backend2, attrs }) => {\n  const { x } = inputs;\n  const { k, sorted } = attrs;\n  const xId = backend2.dataIdMap.get(x.dataId).id;\n  const xShapeBytes = new Uint8Array(new Int32Array(x.shape).buffer);\n  const outputShape = x.shape.slice();\n  outputShape[outputShape.length - 1] = k;\n  const outValues = backend2.makeOutput(outputShape, x.dtype);\n  const outValuesId = backend2.dataIdMap.get(outValues.dataId).id;\n  const outIndices = backend2.makeOutput(outputShape, \"int32\");\n  const outIndicesId = backend2.dataIdMap.get(outIndices.dataId).id;\n  wasmTopK(xId, xShapeBytes, x.shape.length, CppDType[x.dtype], k, sorted, outValuesId, outIndicesId);\n  return [outValues, outIndices];\n};\nvar topKConfig3 = {\n  kernelName: TopK,\n  backendName: \"wasm\",\n  setupFunc: setup49,\n  kernelFunc: topk2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Transform.js\nvar wasmTransform;\nfunction setup50(backend2) {\n  wasmTransform = backend2.wasm.cwrap(Transform, null, [\n    \"number\",\n    \"number\",\n    \"bool\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"array\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\",\n    \"number\"\n  ]);\n}\nfunction transform4(args) {\n  const { backend: backend2, inputs, attrs } = args;\n  const { image: image2, transforms } = inputs;\n  const { interpolation, fillMode, fillValue, outputShape } = attrs;\n  const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n  const [outHeight, outWidth] = outputShape != null ? outputShape : [imageHeight, imageWidth];\n  const outShape = [\n    batch,\n    outHeight,\n    outWidth,\n    numChannels\n  ];\n  const strides = new Uint8Array(new Int32Array(util_exports.computeStrides(image2.shape)).buffer);\n  const out = backend2.makeOutput(outShape, image2.dtype);\n  const outId = backend2.dataIdMap.get(out.dataId).id;\n  const imageData = backend2.dataIdMap.get(image2.dataId);\n  const imageId = imageData.id;\n  const transformsData = backend2.dataIdMap.get(transforms.dataId);\n  const transformsId = transformsData.id;\n  const interpolationModeId = interpolation === \"nearest\" ? 1 : 2;\n  let fillModeId;\n  switch (fillMode) {\n    case \"constant\":\n      fillModeId = 1;\n      break;\n    case \"reflect\":\n      fillModeId = 2;\n      break;\n    case \"wrap\":\n      fillModeId = 3;\n      break;\n    case \"nearest\":\n      fillModeId = 4;\n      break;\n    default:\n      fillModeId = 1;\n      break;\n  }\n  wasmTransform(imageId, transformsId, transforms.shape[0] > 1, batch, outHeight, outWidth, numChannels, imageWidth, imageHeight, strides, image2.shape.length - 1, interpolationModeId, fillModeId, fillValue, outId);\n  return out;\n}\nvar transformConfig3 = {\n  kernelName: Transform,\n  backendName: \"wasm\",\n  setupFunc: setup50,\n  kernelFunc: transform4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/Unpack.js\nfunction unpack3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { value } = inputs;\n  let { axis } = attrs;\n  if (axis < 0) {\n    axis += value.shape.length;\n  }\n  const numOutputs = value.shape[axis];\n  const rank = value.shape.length;\n  const outShape = new Array(rank - 1);\n  let outIndex = 0;\n  for (let i2 = 0; i2 < rank; i2++) {\n    if (i2 !== axis) {\n      outShape[outIndex++] = value.shape[i2];\n    }\n  }\n  const outs = new Array(numOutputs);\n  const begin = new Array(rank).fill(0);\n  const size = value.shape.slice();\n  size[axis] = 1;\n  for (let i2 = 0; i2 < outs.length; i2++) {\n    begin[axis] = i2;\n    outs[i2] = slice4({ inputs: { x: value }, attrs: { begin, size }, backend: backend2 });\n  }\n  return outs.map(({ dataId, dtype }) => ({ dataId, dtype, shape: outShape }));\n}\nvar unpackConfig3 = {\n  kernelName: Unpack,\n  backendName: \"wasm\",\n  kernelFunc: unpack3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/kernels/ZerosLike.js\nfunction zerosLike4(args) {\n  const { inputs: { x }, backend: backend2 } = args;\n  const out = backend2.makeOutput(x.shape, x.dtype);\n  const outVals = backend2.typedArrayFromHeap(out);\n  outVals.fill(0);\n  return out;\n}\nvar zerosLikeConfig3 = {\n  kernelName: ZerosLike,\n  backendName: \"wasm\",\n  kernelFunc: zerosLike4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/register_all_kernels.js\nvar kernelConfigs3 = [\n  _fusedMatMulConfig3,\n  absConfig3,\n  addConfig3,\n  addNConfig3,\n  allConfig3,\n  anyConfig3,\n  argMaxConfig3,\n  avgPoolConfig3,\n  batchMatMulConfig3,\n  batchToSpaceNDConfig3,\n  castConfig3,\n  ceilConfig3,\n  clipByValueConfig3,\n  concatConfig3,\n  conv2DConfig3,\n  conv2DBackpropInputConfig3,\n  cosConfig3,\n  coshConfig3,\n  cropAndResizeConfig3,\n  cumprodConfig3,\n  cumsumConfig3,\n  depthToSpaceConfig3,\n  depthwiseConv2dNativeConfig3,\n  eluConfig3,\n  equalConfig3,\n  expConfig3,\n  expandDimsConfig3,\n  fillConfig3,\n  flipLeftRightConfig3,\n  floorConfig3,\n  floorDivConfig3,\n  fusedBatchNormConfig,\n  fusedConv2DConfig3,\n  fusedDepthwiseConv2DConfig3,\n  gatherNdConfig3,\n  gatherV2Config3,\n  greaterConfig3,\n  greaterEqualConfig3,\n  identityConfig3,\n  leakyReluConfig3,\n  lessConfig3,\n  lessEqualConfig3,\n  logConfig3,\n  logicalAndConfig3,\n  logicalNotConfig3,\n  logicalOrConfig3,\n  logicalXorConfig,\n  maxConfig3,\n  maximumConfig3,\n  maxPoolConfig3,\n  meanConfig3,\n  minConfig3,\n  minimumConfig3,\n  mirrorPadConfig3,\n  multiplyConfig3,\n  negConfig3,\n  nonMaxSuppressionV3Config3,\n  nonMaxSuppressionV4Config3,\n  nonMaxSuppressionV5Config3,\n  notEqualConfig3,\n  oneHotConfig3,\n  onesLikeConfig3,\n  packConfig3,\n  padV2Config3,\n  powConfig3,\n  preluConfig3,\n  prodConfig3,\n  rangeConfig3,\n  realDivConfig3,\n  reluConfig3,\n  relu6Config3,\n  reshapeConfig3,\n  resizeBilinearConfig3,\n  resizeNearestNeighborConfig3,\n  reverseConfig3,\n  rotateWithOffsetConfig3,\n  roundConfig3,\n  rsqrtConfig3,\n  scatterNdConfig3,\n  selectConfig3,\n  sigmoidConfig3,\n  sinConfig3,\n  sliceConfig3,\n  softmaxConfig3,\n  spaceToBatchNDConfig3,\n  sparseFillEmptyRowsConfig3,\n  sparseReshapeConfig3,\n  sparseSegmentMeanConfig3,\n  sparseSegmentSumConfig3,\n  splitVConfig3,\n  sqrtConfig3,\n  squareConfig3,\n  squaredDifferenceConfig3,\n  stepConfig3,\n  stridedSliceConfig3,\n  stringNGramsConfig3,\n  stringSplitConfig3,\n  stringToHashBucketFastConfig3,\n  subConfig3,\n  sumConfig3,\n  tanConfig3,\n  tanhConfig3,\n  tileConfig3,\n  topKConfig3,\n  transformConfig3,\n  transposeConfig3,\n  unpackConfig3,\n  zerosLikeConfig3\n];\nfor (const kernelConfig of kernelConfigs3) {\n  registerKernel(kernelConfig);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/flags_wasm.js\nvar ENV6 = env();\nENV6.registerFlag(\n  \"WASM_HAS_SIMD_SUPPORT\",\n  async () => WebAssembly.validate(new Uint8Array([\n    0,\n    97,\n    115,\n    109,\n    1,\n    0,\n    0,\n    0,\n    1,\n    4,\n    1,\n    96,\n    0,\n    0,\n    3,\n    2,\n    1,\n    0,\n    10,\n    9,\n    1,\n    7,\n    0,\n    65,\n    0,\n    253,\n    15,\n    26,\n    11\n  ]))\n);\nENV6.registerFlag(\"WASM_HAS_MULTITHREAD_SUPPORT\", async () => {\n  if (ENV6.get(\"IS_NODE\")) {\n    return false;\n  }\n  try {\n    new MessageChannel().port1.postMessage(new SharedArrayBuffer(1));\n    return WebAssembly.validate(new Uint8Array([\n      0,\n      97,\n      115,\n      109,\n      1,\n      0,\n      0,\n      0,\n      1,\n      4,\n      1,\n      96,\n      0,\n      0,\n      3,\n      2,\n      1,\n      0,\n      5,\n      4,\n      1,\n      3,\n      1,\n      1,\n      10,\n      11,\n      1,\n      9,\n      0,\n      65,\n      0,\n      254,\n      16,\n      2,\n      0,\n      26,\n      11\n    ]));\n  } catch (e2) {\n    return false;\n  }\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/backend_wasm.js\nvar wasmFactoryThreadedSimd_import = __toESM(require_tfjs_backend_wasm_threaded_simd());\nvar import_tfjs_backend_wasm_threaded_simd_worker = __toESM(require_tfjs_backend_wasm_threaded_simd_worker());\nvar wasmFactory_import = __toESM(require_tfjs_backend_wasm());\nvar wasmFactoryThreadedSimd = wasmFactoryThreadedSimd_import.default || wasmFactoryThreadedSimd_import;\nvar wasmFactory = wasmFactory_import.default || wasmFactory_import;\nvar BackendWasm = class extends KernelBackend {\n  constructor(wasm) {\n    super();\n    this.wasm = wasm;\n    this.dataIdNextNumber = 1;\n    this.wasm.tfjs.initWithThreadsCount(threadsCount);\n    actualThreadsCount = this.wasm.tfjs.getThreadsCount();\n    this.dataIdMap = new DataStorage(this, engine());\n  }\n  write(values, shape, dtype) {\n    const dataId = { id: this.dataIdNextNumber++ };\n    this.move(dataId, values, shape, dtype, 1);\n    return dataId;\n  }\n  numDataIds() {\n    return this.dataIdMap.numDataIds();\n  }\n  async time(f) {\n    const start = util_exports.now();\n    f();\n    const kernelMs = util_exports.now() - start;\n    return { kernelMs };\n  }\n  move(dataId, values, shape, dtype, refCount) {\n    const id = this.dataIdNextNumber++;\n    if (dtype === \"string\") {\n      const stringBytes = values;\n      this.dataIdMap.set(dataId, { id, stringBytes, shape, dtype, memoryOffset: null, refCount });\n      return;\n    }\n    const size = util_exports.sizeFromShape(shape);\n    const numBytes = size * util_exports.bytesPerElement(dtype);\n    const memoryOffset = this.wasm._malloc(numBytes);\n    this.dataIdMap.set(dataId, { id, memoryOffset, shape, dtype, refCount });\n    this.wasm.tfjs.registerTensor(id, size, memoryOffset);\n    if (values != null) {\n      this.wasm.HEAPU8.set(new Uint8Array(values.buffer, values.byteOffset, numBytes), memoryOffset);\n    }\n  }\n  async read(dataId) {\n    return this.readSync(dataId);\n  }\n  readSync(dataId, start, end) {\n    const { memoryOffset, dtype, shape, stringBytes } = this.dataIdMap.get(dataId);\n    if (dtype === \"string\") {\n      if ((start == null || start === 0) && (end == null || end >= stringBytes.length)) {\n        return stringBytes;\n      }\n      return stringBytes.slice(start, end);\n    }\n    start = start || 0;\n    end = end || util_exports.sizeFromShape(shape);\n    const bytesPerElement2 = util_exports.bytesPerElement(dtype);\n    const bytes = this.wasm.HEAPU8.slice(memoryOffset + start * bytesPerElement2, memoryOffset + end * bytesPerElement2);\n    return typedArrayFromBuffer(bytes.buffer, dtype);\n  }\n  disposeData(dataId, force = false) {\n    if (this.dataIdMap.has(dataId)) {\n      const data = this.dataIdMap.get(dataId);\n      data.refCount--;\n      if (!force && data.refCount > 0) {\n        return false;\n      }\n      this.wasm._free(data.memoryOffset);\n      this.wasm.tfjs.disposeData(data.id);\n      this.dataIdMap.delete(dataId);\n    }\n    return true;\n  }\n  refCount(dataId) {\n    if (this.dataIdMap.has(dataId)) {\n      const tensorData = this.dataIdMap.get(dataId);\n      return tensorData.refCount;\n    }\n    return 0;\n  }\n  incRef(dataId) {\n    const data = this.dataIdMap.get(dataId);\n    if (data != null) {\n      data.refCount++;\n    }\n  }\n  floatPrecision() {\n    return 32;\n  }\n  getMemoryOffset(dataId) {\n    return this.dataIdMap.get(dataId).memoryOffset;\n  }\n  dispose() {\n    this.wasm.tfjs.dispose();\n    if (\"PThread\" in this.wasm) {\n      this.wasm.PThread.terminateAllThreads();\n    }\n    this.wasm = null;\n  }\n  memory() {\n    return { unreliable: false };\n  }\n  makeOutput(shape, dtype, memoryOffset) {\n    let dataId;\n    if (memoryOffset == null) {\n      dataId = this.write(null, shape, dtype);\n    } else {\n      const id = this.dataIdNextNumber++;\n      dataId = { id };\n      this.dataIdMap.set(dataId, { id, memoryOffset, shape, dtype, refCount: 1 });\n      const size = util_exports.sizeFromShape(shape);\n      this.wasm.tfjs.registerTensor(id, size, memoryOffset);\n    }\n    return { dataId, shape, dtype };\n  }\n  typedArrayFromHeap({ shape, dtype, dataId }) {\n    const buffer2 = this.wasm.HEAPU8.buffer;\n    const { memoryOffset } = this.dataIdMap.get(dataId);\n    const size = util_exports.sizeFromShape(shape);\n    switch (dtype) {\n      case \"float32\":\n        return new Float32Array(buffer2, memoryOffset, size);\n      case \"int32\":\n        return new Int32Array(buffer2, memoryOffset, size);\n      case \"bool\":\n        return new Uint8Array(buffer2, memoryOffset, size);\n      default:\n        throw new Error(`Unknown dtype ${dtype}`);\n    }\n  }\n};\nfunction createInstantiateWasmFunc(path) {\n  return (imports, callback) => {\n    util_exports.fetch(path, { credentials: \"same-origin\" }).then((response) => {\n      if (!response[\"ok\"]) {\n        imports.env.a(`failed to load wasm binary file at '${path}'`);\n      }\n      response.arrayBuffer().then((binary) => {\n        WebAssembly.instantiate(binary, imports).then((output) => {\n          callback(output.instance, output.module);\n        });\n      });\n    });\n    return {};\n  };\n}\nfunction getPathToWasmBinary(simdSupported, threadsSupported, wasmModuleFolder) {\n  if (wasmPath != null) {\n    return wasmPath;\n  }\n  let path = \"tfjs-backend-wasm.wasm\";\n  if (simdSupported && threadsSupported) {\n    path = \"tfjs-backend-wasm-threaded-simd.wasm\";\n  } else if (simdSupported) {\n    path = \"tfjs-backend-wasm-simd.wasm\";\n  }\n  if (wasmFileMap != null) {\n    if (wasmFileMap[path] != null) {\n      return wasmFileMap[path];\n    }\n  }\n  return wasmModuleFolder + path;\n}\nasync function init() {\n  const [simdSupported, threadsSupported] = await Promise.all([\n    env().getAsync(\"WASM_HAS_SIMD_SUPPORT\"),\n    env().getAsync(\"WASM_HAS_MULTITHREAD_SUPPORT\")\n  ]);\n  return new Promise((resolve, reject) => {\n    const factoryConfig = {};\n    factoryConfig.locateFile = (path, prefix) => {\n      if (path.endsWith(\".worker.js\")) {\n        const response = import_tfjs_backend_wasm_threaded_simd_worker.wasmWorkerContents.replace(/\\n/g, \"\\\\n\");\n        const blob = new Blob([response], { type: \"application/javascript\" });\n        return URL.createObjectURL(blob);\n      }\n      if (path.endsWith(\".wasm\")) {\n        return getPathToWasmBinary(simdSupported, threadsSupported, wasmPathPrefix != null ? wasmPathPrefix : prefix);\n      }\n      return prefix + path;\n    };\n    if (customFetch) {\n      factoryConfig.instantiateWasm = createInstantiateWasmFunc(getPathToWasmBinary(simdSupported, threadsSupported, wasmPathPrefix != null ? wasmPathPrefix : \"\"));\n    }\n    let initialized = false;\n    factoryConfig.onAbort = () => {\n      if (initialized) {\n        return;\n      }\n      if (initAborted) {\n        return;\n      }\n      initAborted = true;\n      const rejectMsg = \"Make sure the server can serve the `.wasm` file relative to the bundled js file. For more details see https://github.com/tensorflow/tfjs/blob/master/tfjs-backend-wasm/README.md#using-bundlers\";\n      reject({ message: rejectMsg });\n    };\n    let wasm;\n    if (threadsSupported && simdSupported && wasmPath == null) {\n      factoryConfig.mainScriptUrlOrBlob = new Blob([`var WasmBackendModuleThreadedSimd = ` + wasmFactoryThreadedSimd.toString()], { type: \"text/javascript\" });\n      wasm = wasmFactoryThreadedSimd(factoryConfig);\n    } else {\n      wasm = wasmFactory(factoryConfig);\n    }\n    wasm.then((module) => {\n      initialized = true;\n      initAborted = false;\n      const voidReturnType = null;\n      module.tfjs = {\n        init: module.cwrap(\"init\", null, []),\n        initWithThreadsCount: module.cwrap(\"init_with_threads_count\", null, [\"number\"]),\n        getThreadsCount: module.cwrap(\"get_threads_count\", \"number\", []),\n        registerTensor: module.cwrap(\"register_tensor\", null, [\n          \"number\",\n          \"number\",\n          \"number\"\n        ]),\n        disposeData: module.cwrap(\"dispose_data\", voidReturnType, [\"number\"]),\n        dispose: module.cwrap(\"dispose\", voidReturnType, [])\n      };\n      resolve({ wasm: module });\n    }).catch(reject);\n  });\n}\nfunction typedArrayFromBuffer(buffer2, dtype) {\n  switch (dtype) {\n    case \"float32\":\n      return new Float32Array(buffer2);\n    case \"int32\":\n      return new Int32Array(buffer2);\n    case \"bool\":\n      return new Uint8Array(buffer2);\n    default:\n      throw new Error(`Unknown dtype ${dtype}`);\n  }\n}\nvar wasmBinaryNames = [\n  \"tfjs-backend-wasm.wasm\",\n  \"tfjs-backend-wasm-simd.wasm\",\n  \"tfjs-backend-wasm-threaded-simd.wasm\"\n];\nvar wasmPath = null;\nvar wasmPathPrefix = null;\nvar wasmFileMap = {};\nvar initAborted = false;\nvar customFetch = false;\nfunction setWasmPath(path, usePlatformFetch = false) {\n  deprecationWarn(\"setWasmPath has been deprecated in favor of setWasmPaths and will be removed in a future release.\");\n  if (initAborted) {\n    throw new Error(\"The WASM backend was already initialized. Make sure you call `setWasmPath()` before you call `tf.setBackend()` or `tf.ready()`\");\n  }\n  wasmPath = path;\n  customFetch = usePlatformFetch;\n}\nfunction setWasmPaths(prefixOrFileMap, usePlatformFetch = false) {\n  if (initAborted) {\n    throw new Error(\"The WASM backend was already initialized. Make sure you call `setWasmPaths()` before you call `tf.setBackend()` or `tf.ready()`\");\n  }\n  if (typeof prefixOrFileMap === \"string\") {\n    wasmPathPrefix = prefixOrFileMap;\n  } else {\n    wasmFileMap = prefixOrFileMap;\n    const missingPaths = wasmBinaryNames.filter((name) => wasmFileMap[name] == null);\n    if (missingPaths.length > 0) {\n      throw new Error(`There were no entries found for the following binaries: ${missingPaths.join(\",\")}. Please either call setWasmPaths with a map providing a path for each binary, or with a string indicating the directory where all the binaries can be found.`);\n    }\n  }\n  customFetch = usePlatformFetch;\n}\nvar threadsCount = -1;\nvar actualThreadsCount = -1;\nfunction setThreadsCount(numThreads) {\n  threadsCount = numThreads;\n}\nfunction getThreadsCount() {\n  if (actualThreadsCount === -1) {\n    throw new Error(`WASM backend not initialized.`);\n  }\n  return actualThreadsCount;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/version.js\nvar version8 = \"3.19.0\";\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/dist/base.js\nvar WASM_PRIORITY = 2;\nregisterBackend(\"wasm\", async () => {\n  const { wasm } = await init();\n  return new BackendWasm(wasm);\n}, WASM_PRIORITY);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/flags_webgpu.js\nvar ENV7 = env();\nENV7.registerFlag(\"WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE\", () => 15);\nENV7.registerFlag(\"WEBGPU_CPU_FORWARD\", () => true);\nENV7.registerFlag(\"WEBGPU_MATMUL_WORK_PER_THREAD\", () => 4);\nENV7.registerFlag(\"WEBGPU_MATMUL_PROGRAM_TYPE\", () => -1);\nENV7.registerFlag(\"WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE\", () => false);\nENV7.registerFlag(\"WEBGPU_USE_LOW_POWER_GPU\", () => false);\nENV7.registerFlag(\"WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD\", () => 1e3);\nENV7.registerFlag(\"WEBGPU_USE_PROFILE_TOOL\", () => false);\nENV7.registerFlag(\"WEBGPU_IMPORT_EXTERNAL_TEXTURE\", () => false);\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/binary_op_util.js\nvar BinaryOpType;\n(function(BinaryOpType2) {\n  BinaryOpType2[BinaryOpType2[\"MUL\"] = 0] = \"MUL\";\n  BinaryOpType2[BinaryOpType2[\"ADD\"] = 1] = \"ADD\";\n  BinaryOpType2[BinaryOpType2[\"SUB\"] = 2] = \"SUB\";\n  BinaryOpType2[BinaryOpType2[\"DIV\"] = 3] = \"DIV\";\n  BinaryOpType2[BinaryOpType2[\"EQUAL\"] = 4] = \"EQUAL\";\n  BinaryOpType2[BinaryOpType2[\"GREATER\"] = 5] = \"GREATER\";\n  BinaryOpType2[BinaryOpType2[\"GREATER_EQUAL\"] = 6] = \"GREATER_EQUAL\";\n  BinaryOpType2[BinaryOpType2[\"LESS\"] = 7] = \"LESS\";\n  BinaryOpType2[BinaryOpType2[\"LESS_EQUAL\"] = 8] = \"LESS_EQUAL\";\n  BinaryOpType2[BinaryOpType2[\"LOGICAL_AND\"] = 9] = \"LOGICAL_AND\";\n  BinaryOpType2[BinaryOpType2[\"NOT_EQUAL\"] = 10] = \"NOT_EQUAL\";\n  BinaryOpType2[BinaryOpType2[\"SQUARED_DIFFERENCE\"] = 11] = \"SQUARED_DIFFERENCE\";\n  BinaryOpType2[BinaryOpType2[\"INT_DIV\"] = 12] = \"INT_DIV\";\n  BinaryOpType2[BinaryOpType2[\"POW\"] = 13] = \"POW\";\n  BinaryOpType2[BinaryOpType2[\"PRELU\"] = 14] = \"PRELU\";\n  BinaryOpType2[BinaryOpType2[\"MAX\"] = 15] = \"MAX\";\n  BinaryOpType2[BinaryOpType2[\"MIN\"] = 16] = \"MIN\";\n  BinaryOpType2[BinaryOpType2[\"COMPLEX_MULTIPLY_REAL\"] = 17] = \"COMPLEX_MULTIPLY_REAL\";\n  BinaryOpType2[BinaryOpType2[\"COMPLEX_MULTIPLY_IMAG\"] = 18] = \"COMPLEX_MULTIPLY_IMAG\";\n})(BinaryOpType || (BinaryOpType = {}));\nvar ADD2 = \"return a + b;\";\nvar COMPLEX_MULTIPLY_REAL = \"return areal * breal - aimag * bimag;\";\nvar COMPLEX_MULTIPLY_IMAG = \"return areal * bimag + aimag * breal;\";\nvar DIV2 = \"return a / b;\";\nvar MUL2 = \"return a * b;\";\nvar SQUARED_DIFFERENCE2 = \"return (a - b) * (a - b);\";\nvar SUB2 = \"return a - b;\";\nvar EQUAL2 = \"return f32(a == b);\";\nvar EQUAL_VEC4 = \"return vec4<f32>(a == b);\";\nvar GREATER2 = \"return f32(a > b);\";\nvar GREATER_VEC4 = \"return vec4<f32>(a > b);\";\nvar GREATER_EQUAL2 = \"return f32(a >= b);\";\nvar GREATER_EQUAL_VEC4 = \"return vec4<f32>(a >= b);\";\nvar LESS2 = \"return f32(a < b);\";\nvar LESS_VEC4 = \"return vec4<f32>(a < b);\";\nvar LESS_EQUAL2 = \"return f32(a <= b);\";\nvar LESS_EQUAL_VEC4 = \"return vec4<f32>(a <= b);\";\nvar LOGICAL_AND2 = \"return f32(f32(a) >= 1.0 && f32(b) >= 1.0);\";\nvar LOGICAL_AND_VEC4 = `return (vec4<f32>(a >= vec4<f32>(1.0)) *\n  vec4<f32>(b >= vec4<f32>(1.0)));`;\nvar CHECK_NAN_SNIPPET4 = `\n  if (isnan(a)) { return a; }\n  if (isnan(b)) { return b; }\n  `;\nvar CHECK_NAN_SNIPPET_VEC4 = `\n  if (isNaN.r) {\n    resultTemp.r = uniforms.NAN;\n  }\n  if (isNaN.g) {\n    resultTemp.g = uniforms.NAN;\n  }\n  if (isNaN.b) {\n    resultTemp.b = uniforms.NAN;\n  }\n  if (isNaN.a) {\n    resultTemp.a = uniforms.NAN;\n  }\n  `;\nvar INT_DIV2 = `\n  let s = sign(a) * sign(b);\n  let ia = i32(round(a));\n  let ib = i32(round(b));\n  return f32(idiv(ia, ib, s));\n  `;\nvar INT_DIV_VEC4 = `\n  let ia = vec4<i32>(round(a));\n  let ib = vec4<i32>(round(b));\n  let cond = ib != vec4<i32>(0);\n  var resultTemp = vec4<i32>(0);\n  let s = sign(a) * sign(b);\n\n  // Windows (D3D) wants guaranteed non-zero int division at compile-time.\n  if (cond[0]) {\n    resultTemp[0] = idiv(ia[0], ib[0], s[0]);\n  }\n  if (cond[1]) {\n    resultTemp[1] = idiv(ia[1], ib[1], s[1]);\n  }\n  if (cond[2]) {\n    resultTemp[2] = idiv(ia[2], ib[2], s[2]);\n  }\n  if (cond[3]) {\n    resultTemp[3] = idiv(ia[3], ib[3], s[3]);\n  }\n  return vec4<f32>(resultTemp);\n  `;\nvar NOT_EQUAL2 = \"return f32(a != b);\";\nvar NOT_EQUAL_VEC4 = \"return vec4<f32>(a != b);\";\nvar POW2 = `\n  if(a < 0.0 && floor(b) < b) {\n    return uniforms.NAN;\n  }\n  if (b == 0.0) {\n    return 1.0;\n  }\n  if (round(abs(b) % 2.0) != 1.0) {\n    return pow(abs(a), b);\n  }\n  return sign(a) * pow(abs(a), b);\n  `;\nvar POW_VEC4 = `\n  let isModRound1Bool = vec4<i32>(round(abs(b) % vec4<f32>(2.0))) == vec4<i32>(1);\n  let isModRound1 = vec4<f32>(isModRound1Bool);\n  let multiplier = sign(a) * isModRound1 + (vec4<f32>(1.0) - isModRound1);\n  var resultTemp = multiplier * pow(abs(a), b);\n\n  // Ensure that a^0 = 1, including 0^0 = 1 as this correspond to TF and JS\n  let isExpZero = b == vec4<f32>(0.0);\n  if (isExpZero.r) {\n    resultTemp.r = 1.0;\n  }\n  if (isExpZero.g) {\n    resultTemp.g = 1.0;\n  }\n  if (isExpZero.b) {\n    resultTemp.b = 1.0;\n  }\n  if (isExpZero.a) {\n    resultTemp.a = 1.0;\n  }\n  let isNaN = a < vec4<f32>(0.0) & floor(b) < b;\n  ${CHECK_NAN_SNIPPET_VEC4}\n  return resultTemp;\n  `;\nvar PRELU2 = `if (a < 0.0) { return b * a; }  return a;`;\nvar PRELU_VEC4 = `\n  let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));\n  return (aLessThanZero * (b * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);\n  `;\nfunction getMinMaxString(op2, useVec4) {\n  const checkNanSnippet = useVec4 ? CHECK_NAN_SNIPPET_VEC4 : CHECK_NAN_SNIPPET4;\n  return useVec4 ? `\n    var resultTemp = vec4<f32>(${op2}(a, b));\n    let isNaN = isnanVec4(a) | isnanVec4(b);\n    ` + checkNanSnippet + `\n    return resultTemp;\n  ` : checkNanSnippet + `\n    return ${op2}(a, b);\n  `;\n}\nfunction getBinaryOpString(type, useVec4) {\n  switch (type) {\n    case BinaryOpType.MUL:\n      return MUL2;\n    case BinaryOpType.ADD:\n      return ADD2;\n    case BinaryOpType.SUB:\n      return SUB2;\n    case BinaryOpType.DIV:\n      return DIV2;\n    case BinaryOpType.EQUAL:\n      return useVec4 ? EQUAL_VEC4 : EQUAL2;\n    case BinaryOpType.GREATER:\n      return useVec4 ? GREATER_VEC4 : GREATER2;\n    case BinaryOpType.GREATER_EQUAL:\n      return useVec4 ? GREATER_EQUAL_VEC4 : GREATER_EQUAL2;\n    case BinaryOpType.LESS:\n      return useVec4 ? LESS_VEC4 : LESS2;\n    case BinaryOpType.LESS_EQUAL:\n      return useVec4 ? LESS_EQUAL_VEC4 : LESS_EQUAL2;\n    case BinaryOpType.LOGICAL_AND:\n      return useVec4 ? LOGICAL_AND_VEC4 : LOGICAL_AND2;\n    case BinaryOpType.NOT_EQUAL:\n      return useVec4 ? NOT_EQUAL_VEC4 : NOT_EQUAL2;\n    case BinaryOpType.SQUARED_DIFFERENCE:\n      return SQUARED_DIFFERENCE2;\n    case BinaryOpType.INT_DIV:\n      return useVec4 ? INT_DIV_VEC4 : INT_DIV2;\n    case BinaryOpType.PRELU:\n      return useVec4 ? PRELU_VEC4 : PRELU2;\n    case BinaryOpType.MAX:\n      return getMinMaxString(\"max\", useVec4);\n    case BinaryOpType.MIN:\n      return getMinMaxString(\"min\", useVec4);\n    case BinaryOpType.POW:\n      return useVec4 ? POW_VEC4 : POW2;\n    case BinaryOpType.COMPLEX_MULTIPLY_REAL:\n      return COMPLEX_MULTIPLY_REAL;\n    case BinaryOpType.COMPLEX_MULTIPLY_IMAG:\n      return COMPLEX_MULTIPLY_IMAG;\n    default:\n      throw new Error(`BinaryType ${type} is not implemented!`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/unary_op_util.js\nvar UnaryOpType;\n(function(UnaryOpType2) {\n  UnaryOpType2[UnaryOpType2[\"ABS\"] = 0] = \"ABS\";\n  UnaryOpType2[UnaryOpType2[\"CEIL\"] = 1] = \"CEIL\";\n  UnaryOpType2[UnaryOpType2[\"COS\"] = 2] = \"COS\";\n  UnaryOpType2[UnaryOpType2[\"COSH\"] = 3] = \"COSH\";\n  UnaryOpType2[UnaryOpType2[\"ELU\"] = 4] = \"ELU\";\n  UnaryOpType2[UnaryOpType2[\"EXP\"] = 5] = \"EXP\";\n  UnaryOpType2[UnaryOpType2[\"EXPM1\"] = 6] = \"EXPM1\";\n  UnaryOpType2[UnaryOpType2[\"FLOOR\"] = 7] = \"FLOOR\";\n  UnaryOpType2[UnaryOpType2[\"LINEAR\"] = 8] = \"LINEAR\";\n  UnaryOpType2[UnaryOpType2[\"LOG\"] = 9] = \"LOG\";\n  UnaryOpType2[UnaryOpType2[\"LOGICAL_NOT\"] = 10] = \"LOGICAL_NOT\";\n  UnaryOpType2[UnaryOpType2[\"NEG\"] = 11] = \"NEG\";\n  UnaryOpType2[UnaryOpType2[\"RELU\"] = 12] = \"RELU\";\n  UnaryOpType2[UnaryOpType2[\"RELU6\"] = 13] = \"RELU6\";\n  UnaryOpType2[UnaryOpType2[\"LEAKYRELU\"] = 14] = \"LEAKYRELU\";\n  UnaryOpType2[UnaryOpType2[\"RSQRT\"] = 15] = \"RSQRT\";\n  UnaryOpType2[UnaryOpType2[\"SIN\"] = 16] = \"SIN\";\n  UnaryOpType2[UnaryOpType2[\"SINH\"] = 17] = \"SINH\";\n  UnaryOpType2[UnaryOpType2[\"SIGMOID\"] = 18] = \"SIGMOID\";\n  UnaryOpType2[UnaryOpType2[\"SQRT\"] = 19] = \"SQRT\";\n  UnaryOpType2[UnaryOpType2[\"SQUARE\"] = 20] = \"SQUARE\";\n  UnaryOpType2[UnaryOpType2[\"TANH\"] = 21] = \"TANH\";\n  UnaryOpType2[UnaryOpType2[\"TO_INT\"] = 22] = \"TO_INT\";\n})(UnaryOpType || (UnaryOpType = {}));\nvar ABS3 = `return abs(a);`;\nvar CEIL2 = `return ceil(a);`;\nvar COS2 = `return cos(a);`;\nvar COSH2 = `\n  let e2x = exp(-a);\n  return (e2x + 1.0 / e2x) / 2.0;\n`;\nvar EXPM12 = `return exp(a) - 1.0;`;\nvar ELU5 = `if (a >= 0.0) { return a; }  return (exp(a) - 1.0);`;\nvar ELU_VEC4 = `\n  var resFloat = exp(a) - vec4<f32>(1.0);\n  if (a.r >= 0.0) {\n    resFloat.r = a.r;\n  }\n  if (a.g >= 0.0) {\n    resFloat.g = a.g;\n  }\n  if (a.b >= 0.0) {\n    resFloat.b = a.b;\n  }\n  if (a.a >= 0.0) {\n    resFloat.a = a.a;\n  }\n  return resFloat;\n`;\nvar EXP2 = `return exp(a);`;\nvar FLOOR2 = `return floor(a);`;\nvar LINEAR3 = `return a;`;\nvar LOG2 = `if (a < 0.0) { return 1.0/0.0; }\n  return log(a);`;\nvar LOGICAL_NOT2 = `return f32(!(a >= 1.0));`;\nvar NEG2 = `return -a;`;\nvar LEAKYRELU2 = `if (a < 0.0) { return uniforms.alpha * a; } return a;`;\nvar LEAKYRELU_VEC4 = `\n  let aLessThanZero = vec4<f32>(a < vec4<f32>(0.0));\n  return (aLessThanZero * (uniforms.alpha * a)) + ((vec4<f32>(1.0) - aLessThanZero) * a);\n`;\nvar RELU4 = `return select(a, 0.0, a < 0.0);`;\nvar RELU64 = \"return clamp(a, 0.0, 6.0);\";\nvar RELU6_VEC4 = \"return clamp(a, vec4<f32>(0.0, 0.0, 0.0, 0.0), vec4<f32>(6.0, 6.0, 6.0, 6.0));\";\nvar RELU_VEC4 = `\n  return select(a, vec4<f32>(0.0), a < vec4<f32>(0.0));\n`;\nvar RSQRT2 = `return 1.0/sqrt(a);`;\nvar SIGMOID4 = `return 1.0 / (1.0 + exp(-1.0 * a));`;\nvar SIN2 = `return sin(a);`;\nvar SINH2 = `\n  let e2x = exp(a);\n  return (e2x - 1.0 / e2x) / 2.0;\n`;\nvar SQRT2 = `return sqrt(a);`;\nvar SQUARE2 = `return a * a;`;\nvar TANH2 = `\n  let e2x = exp(-2.0 * abs(a));\n  return sign(a) * (1.0 - e2x) / (1.0 + e2x);\n`;\nvar TO_INT2 = `return f32(i32((a)));`;\nfunction getUnaryOpString(type, useVec4) {\n  switch (type) {\n    case UnaryOpType.ABS:\n      return ABS3;\n    case UnaryOpType.COS:\n      return COS2;\n    case UnaryOpType.COSH:\n      return COSH2;\n    case UnaryOpType.CEIL:\n      return CEIL2;\n    case UnaryOpType.ELU:\n      return useVec4 ? ELU_VEC4 : ELU5;\n    case UnaryOpType.EXP:\n      return EXP2;\n    case UnaryOpType.EXPM1:\n      return EXPM12;\n    case UnaryOpType.FLOOR:\n      return FLOOR2;\n    case UnaryOpType.LINEAR:\n      return LINEAR3;\n    case UnaryOpType.LOG:\n      return LOG2;\n    case UnaryOpType.LOGICAL_NOT:\n      return LOGICAL_NOT2;\n    case UnaryOpType.NEG:\n      return NEG2;\n    case UnaryOpType.LEAKYRELU:\n      return useVec4 ? LEAKYRELU_VEC4 : LEAKYRELU2;\n    case UnaryOpType.RELU:\n      return useVec4 ? RELU_VEC4 : RELU4;\n    case UnaryOpType.RELU6:\n      return useVec4 ? RELU6_VEC4 : RELU64;\n    case UnaryOpType.RSQRT:\n      return RSQRT2;\n    case UnaryOpType.SIGMOID:\n      return SIGMOID4;\n    case UnaryOpType.SIN:\n      return SIN2;\n    case UnaryOpType.SINH:\n      return SINH2;\n    case UnaryOpType.SQRT:\n      return SQRT2;\n    case UnaryOpType.SQUARE:\n      return SQUARE2;\n    case UnaryOpType.TANH:\n      return TANH2;\n    case UnaryOpType.TO_INT:\n      return TO_INT2;\n    default:\n      throw new Error(`BinaryType ${type} is not implemented!`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/activation_util.js\nvar typeSnippet = (component) => {\n  switch (component) {\n    case 1:\n      return \"f32\";\n    case 2:\n      return \"vec2<f32>\";\n    case 3:\n      return \"vec3<f32>\";\n    case 4:\n      return \"vec4<f32>\";\n    default:\n      throw new Error(`${component}-component is not supported.`);\n  }\n};\nfunction activationFnSnippet(activation2, hasPreluActivationWeights = false, packed = false, coordsLength = 3) {\n  if (activation2 === null) {\n    return \"\";\n  }\n  let activationOpSnippet = \"\";\n  if (activation2 === \"linear\") {\n    activationOpSnippet = getUnaryOpString(UnaryOpType.LINEAR);\n  } else if (activation2 === \"relu\") {\n    activationOpSnippet = getUnaryOpString(UnaryOpType.RELU, packed);\n  } else if (activation2 === \"elu\") {\n    activationOpSnippet = getUnaryOpString(UnaryOpType.ELU, packed);\n  } else if (activation2 === \"relu6\") {\n    activationOpSnippet = getUnaryOpString(UnaryOpType.RELU6, packed);\n  } else if (activation2 === \"prelu\") {\n    activationOpSnippet = getBinaryOpString(BinaryOpType.PRELU, packed);\n  } else if (activation2 === \"sigmoid\") {\n    activationOpSnippet = getUnaryOpString(UnaryOpType.SIGMOID, packed);\n  } else if (activation2 === \"leakyrelu\") {\n    activationOpSnippet = getUnaryOpString(UnaryOpType.LEAKYRELU, packed);\n  } else {\n    throw new Error(`Activation ${activation2} has not been implemented for the WebGPU backend.`);\n  }\n  const elementSize = packed ? 4 : 1;\n  const dataType = typeSnippet(elementSize);\n  let activationFnSnippet2 = \"\";\n  if (hasPreluActivationWeights) {\n    activationFnSnippet2 = `\n      fn activation(a : ${dataType}, coords : vec${coordsLength}<i32>) -> ${dataType} {\n        let b = getPreluActivationWeightsByOutputCoords(coords);\n        ${activationOpSnippet}\n      }`;\n  } else {\n    activationFnSnippet2 = `\n      fn activation(a : ${dataType}, coords : vec${coordsLength}<i32>) -> ${dataType} {\n        ${activationOpSnippet}\n      }`;\n  }\n  return activationFnSnippet2;\n}\nfunction biasActivationSnippet(hasBias, activation2) {\n  return `\n      ${hasBias ? \"value = value + getBiasByOutputCoords(coords);\" : \"\"}\n      ${activation2 ? \"value = activation(value, coords);\" : \"\"}\n      `;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/shader_util.js\nfunction symbolicallyComputeStrides2(indicesArr, variableName) {\n  if (Math.max(...indicesArr) > 3) {\n    throw new Error(\"Cannot symbolically compute strides for rank > 4 tensor.\");\n  }\n  const numCoords = indicesArr.length;\n  const shape = indicesArr.map((d) => `${variableName}[${d}]`);\n  const strides = new Array(numCoords - 1);\n  strides[numCoords - 2] = shape[numCoords - 1];\n  for (let i2 = numCoords - 3; i2 >= 0; --i2) {\n    strides[i2] = `(${strides[i2 + 1]} * ${shape[i2 + 1]})`;\n  }\n  return strides;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/webgpu_program.js\nvar compileProgram2 = (device, program, inputsData, output) => {\n  const outputData = { dtype: output.dtype, shape: output.shape };\n  const source = makeShader2(inputsData, outputData, program);\n  const module = device.createShaderModule({ code: source, label: program.constructor.name });\n  const pipeline = device.createComputePipeline({\n    compute: { module, entryPoint: \"main\" },\n    label: program.constructor.name,\n    layout: \"auto\"\n  });\n  return pipeline;\n};\nfunction getCoordsDataType2(rank) {\n  if (rank <= 1) {\n    return \"i32\";\n  } else if (rank === 2) {\n    return `vec2<i32>`;\n  } else if (rank === 3) {\n    return `vec3<i32>`;\n  } else if (rank === 4) {\n    return `vec4<i32>`;\n  } else if (rank === 5) {\n    return `vec5`;\n  } else if (rank === 6) {\n    return `vec6`;\n  } else {\n    throw Error(`GPU for rank ${rank} is not yet supported`);\n  }\n}\nfunction getCoordsXYZ(index) {\n  if (index === 0) {\n    return \"x\";\n  } else if (index === 1) {\n    return \"y\";\n  } else if (index === 2) {\n    return \"z\";\n  } else if (index === 3) {\n    return \"w\";\n  } else if (index === 4) {\n    return \"u\";\n  } else if (index === 5) {\n    return \"v\";\n  } else {\n    throw Error(`Index ${index} is not yet supported`);\n  }\n}\nfunction getMainHeaderAndGlobalIndexString() {\n  return `\n    ${getMainHeaderString()}\n      let index = getGlobalIndex();\n`;\n}\nfunction getMainHeaderString() {\n  return `\n  ${getWorkGroupSizeString()}\n  fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,\n          @builtin(global_invocation_id) GlobalId : vec3<u32>,\n          @builtin(num_workgroups) NumWorkgroups: vec3<u32>) {\n    localId = LocalId;\n    globalId = GlobalId;\n    numWorkgroups = NumWorkgroups;\n`;\n}\nfunction getWorkGroupSizeString() {\n  return `\n  @compute @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)\n`;\n}\nfunction makeShader2(inputInfo, outputData, program) {\n  const prefixSnippets = [];\n  prefixSnippets.push(`\n      const workGroupSizeX = ${program.workGroupSize[0]}u;\n      const workGroupSizeY = ${program.workGroupSize[1]}u;\n      const workGroupSizeZ = ${program.workGroupSize[2]}u;\n\n      var<private> localId: vec3<u32>;\n      var<private> globalId: vec3<u32>;\n      var<private> numWorkgroups: vec3<u32>;\n\n      // Only used when the y/z dimension of workgroup size is 1.\n      fn getGlobalIndex() -> i32 {\n        ${isFlatDispatch(program) ? `  return i32(globalId.x);` : `  let localInvocationIndex = localId.z * workGroupSizeX * workGroupSizeY +\n                   localId.y * workGroupSizeX + localId.x;\n               let workGroupID = (globalId - localId)/vec3<u32>(\n                   workGroupSizeX, workGroupSizeY, workGroupSizeZ);\n\n               return i32((workGroupID.z * numWorkgroups.x * numWorkgroups.y +\n                   workGroupID.y * numWorkgroups.x + workGroupID.x) *\n                   (workGroupSizeX * workGroupSizeY * workGroupSizeZ) +\n                   localInvocationIndex);\n        `}\n      }\n    `);\n  if (program.isFromPixels) {\n    prefixSnippets.push(`\n        struct Uniform {\n          size            : i32,\n          numChannels     : i32,\n          outShapeStrides : vec2<i32>,\n        };\n\n        @group(0) @binding(0) var<storage, read_write> result: array<${mapToWgslTypes(outputData.dtype, program.isVec4)}>;\n        @group(0) @binding(2) var<uniform> uniforms: Uniform;\n      `);\n    return [\n      commonSnippet,\n      prefixSnippets.join(\"\\n\"),\n      getCoordsFromIndexSnippet(outputData.shape),\n      program.getUserCode()\n    ].join(\"\\n\");\n  }\n  let preMemberIsStruct = false;\n  let currentMemberIsStruct = false;\n  let uniformDeclaration = \"struct Uniforms { NAN : f32, \";\n  program.variableNames.forEach((x, i2) => {\n    const perDataType = getCoordsDataType2(inputInfo[i2].shape.length);\n    if (perDataType === \"vec5\" || perDataType === \"vec6\") {\n      currentMemberIsStruct = true;\n    }\n    if (preMemberIsStruct || currentMemberIsStruct) {\n      uniformDeclaration += `@align(16) `;\n    }\n    preMemberIsStruct = currentMemberIsStruct;\n    uniformDeclaration += `${x.charAt(0).toLowerCase() + x.slice(1)}Shape : ${perDataType}, `;\n  });\n  const outputDataType = getCoordsDataType2(outputData.shape.length);\n  currentMemberIsStruct = outputDataType === \"vec5\" || outputDataType === \"vec6\";\n  if (preMemberIsStruct || currentMemberIsStruct) {\n    uniformDeclaration += `@align(16) `;\n  }\n  preMemberIsStruct = currentMemberIsStruct;\n  uniformDeclaration += `outShape : ${outputDataType}, `;\n  const stridesLength = outputData.shape.length - 1;\n  const stridesDataType = getCoordsDataType2(stridesLength);\n  currentMemberIsStruct = stridesDataType === \"vec5\" || stridesDataType === \"vec6\";\n  if (preMemberIsStruct || currentMemberIsStruct) {\n    uniformDeclaration += `@align(16) `;\n  }\n  preMemberIsStruct = currentMemberIsStruct;\n  uniformDeclaration += `\n         outShapeStrides: ${stridesDataType}, `;\n  if (program.size) {\n    if (preMemberIsStruct) {\n      uniformDeclaration += `@align(16) `;\n    }\n    preMemberIsStruct = false;\n    uniformDeclaration += \"size : i32, \";\n  }\n  if (program.uniforms) {\n    if (preMemberIsStruct) {\n      uniformDeclaration += `@align(16) `;\n    }\n    uniformDeclaration += program.uniforms;\n  }\n  uniformDeclaration += \"};\";\n  prefixSnippets.push(uniformDeclaration);\n  if (program.atomic) {\n    prefixSnippets.push(`\n      @group(0) @binding(0) var<storage, read_write> result: array<atomic<i32>>;\n    `);\n  } else {\n    prefixSnippets.push(`\n      @group(0) @binding(0) var<storage, read_write> result: array<${mapToWgslTypes(outputData.dtype, program.isVec4)}>;\n    `);\n  }\n  program.variableNames.forEach((x, i2) => {\n    prefixSnippets.push(`\n      @group(0) @binding(${1 + i2}) var<storage, read> ${x}: array<${program.variableTypes ? program.variableTypes[i2] : mapToWgslTypes(inputInfo[i2].dtype, program.isVec4)}>;\n        `);\n  });\n  if (uniformDeclaration !== \"\") {\n    prefixSnippets.push(`\n      @group(0) @binding(${1 + program.variableNames.length}) var<uniform> uniforms: Uniforms;\n      `);\n  }\n  const coordsSnippet = getOutputCoordsSnippet(outputData.shape, program.dispatchLayout);\n  const sources = [\n    commonSnippet,\n    prefixSnippets.join(\"\\n\"),\n    getCoordsFromIndexSnippet(outputData.shape),\n    coordsSnippet,\n    getOutputIndexFromCoordsSnippet(outputData.shape.length)\n  ];\n  if (!program.atomic) {\n    sources.push(setOutputSnippet(outputData.shape, outputData.dtype, program.isVec4));\n  }\n  const inputSnippet = inputInfo.map((x, i2) => getInputSnippet(x, outputData.shape, program.variableTypes ? program.variableTypes[i2] === \"vec4<f32>\" : program.isVec4, program.dispatchLayout.x.length === outputData.shape.length)).join(\"\\n\");\n  sources.push(inputSnippet);\n  sources.push(program.getUserCode());\n  const source = sources.join(\"\\n\");\n  return source;\n}\nfunction makeShaderKey2(program, shapes, inputsData, output) {\n  let key = program.shaderKey;\n  if (program.isFromPixels) {\n    return key;\n  }\n  const types = inputsData.map((d) => d.dtype).concat(output.dtype);\n  const broadcastDims = inputsData.map((d) => backend_util_exports.getBroadcastDims(d.shape, output.shape));\n  const inputShapesEqualsOutShape = inputsData.map((d) => util_exports.arraysEqual(d.shape, output.shape)).join(\"_\");\n  const broadcastDimsKey = broadcastDims.map((d) => d.join(\"_\")).join(\";\");\n  const flatDispatchString = isFlatDispatch(program) ? \"flatDispatch\" : \"\";\n  key += \"_\" + (program.workGroupSize ? program.workGroupSize.join(\",\") : \"\") + shapes.map((shape) => shape.length).join(\",\") + types.join(\",\") + program.variableNames.join(\",\") + broadcastDimsKey + inputShapesEqualsOutShape + flatDispatchString;\n  return key;\n}\nvar commonSnippet = `\n  struct vec5 {x: i32, y: i32, z: i32, w: i32, u: i32};\n  struct vec6 {x: i32, y: i32, z: i32, w: i32, u: i32, v: i32};\n\n  // Checks whether coordinates lie within the bounds of the shape.\n  fn coordsInBounds2D(coord : vec2<i32>, shape : vec2<i32>) -> bool {\n    return all(coord >= vec2<i32>(0)) && all(coord < shape);\n  }\n  fn coordsInBounds3D(coord : vec3<i32>, shape : vec3<i32>) -> bool {\n    return all(coord >= vec3<i32>(0)) && all(coord < shape);\n  }\n  fn coordsInBounds4D(coord : vec4<i32>, shape : vec4<i32>) -> bool {\n    return all(coord >= vec4<i32>(0)) && all(coord < shape);\n  }\n\n  fn getIndexFromCoords1D(coord : i32, shape : i32) -> i32 {\n    return coord;\n  }\n  fn getIndexFromCoords2D(coords : vec2<i32>, shape : vec2<i32>) -> i32 {\n    return dot(coords, vec2<i32>(shape.y, 1));\n  }\n  fn getIndexFromCoords3D(coords : vec3<i32>, shape : vec3<i32>) -> i32 {\n    return dot(coords, vec3<i32>(shape.y * shape.z, shape.z, 1));\n  }\n  fn getIndexFromCoords4D(coords : vec4<i32>, shape : vec4<i32>) -> i32 {\n    return dot(coords, vec4<i32>(\n        shape.y * shape.z * shape.w, shape.z * shape.w, shape.w, 1));\n  }\n  fn getIndexFromCoords5D(coords : vec5, shape : vec5) -> i32 {\n    let shapeStrides: vec5 = vec5(shape.y * shape.z * shape.w * shape.u, shape.z * shape.w * shape.u, shape.w * shape.u, shape.u, 1);\n    return coords.x*shapeStrides.x + coords.y*shapeStrides.y + coords.z*shapeStrides.z + coords.w*shapeStrides.w + coords.u*shapeStrides.u;\n  }\n  fn getIndexFromCoords6D(coords : vec6, shape : vec6) -> i32 {\n    let shapeStrides: vec6 = vec6(shape.y * shape.z * shape.w * shape.u * shape.v, shape.z * shape.w * shape.u * shape.v, shape.w * shape.u * shape.v, shape.u * shape.v, shape.v, 1);\n    return coords.x*shapeStrides.x + coords.y*shapeStrides.y + coords.z*shapeStrides.z + coords.w*shapeStrides.w + coords.u*shapeStrides.u + coords.v*shapeStrides.v;\n  }\n\n  fn idiv(a: i32, b: i32, sign: f32) -> i32 {\n    var res: i32 = a / b;\n    let mod: i32 = a % b;\n    if (sign < 0. && mod != 0) {\n      res = res - 1;\n    }\n    return res;\n  }\n\n  // NaN defination in IEEE 754-1985 is :\n  //   - sign = either 0 or 1.\n  //   - biased exponent = all 1 bits.\n  //   - fraction = anything except all 0 bits (since all 0 bits represents infinity).\n  // https://en.wikipedia.org/wiki/IEEE_754-1985#Representation_of_non-numbers\n  fn isnan(val: f32) -> bool {\n    let floatToUint: u32 = bitcast<u32>(val);\n    return (floatToUint & 0x7fffffffu) > 0x7f800000u;\n  }\n  fn isnanVec4(val : vec4<f32>) -> vec4<bool> {\n    return vec4<bool>(isnan(val[0]), isnan(val[1]), isnan(val[2]), isnan(val[3]));\n  }\n`;\nfunction getCoordsFromIndexSnippet(shape) {\n  const rank = shape.length;\n  if (rank <= 1) {\n    return `fn getCoordsFromIndex(index : i32) -> i32 { return index; }`;\n  }\n  const strides = util_exports.computeStrides(shape);\n  const dtype = getCoordsDataType2(rank);\n  const coords3 = [];\n  for (let i2 = 0; i2 < rank; i2++) {\n    coords3.push(`d${i2}`);\n  }\n  if (strides.length === 1) {\n    return `    fn getCoordsFromIndex(index : i32) -> vec2<i32> {\n      let d0 = index / uniforms.outShapeStrides; let d1 = index - d0 * uniforms.outShapeStrides;\n      return vec2<i32>(d0, d1);\n    }`;\n  }\n  let snippet;\n  snippet = \"var index2 = index;\" + strides.map((_, i2) => {\n    const line1 = `let ${coords3[i2]} = index2 / uniforms.outShapeStrides.${getCoordsXYZ(i2)}`;\n    const line2 = i2 === strides.length - 1 ? `let ${coords3[i2 + 1]} = index2 - ${coords3[i2]} * uniforms.outShapeStrides.${getCoordsXYZ(i2)}` : `index2 = index2 - ${coords3[i2]} * uniforms.outShapeStrides.${getCoordsXYZ(i2)}`;\n    return `${line1}; ${line2};`;\n  }).join(\"\");\n  return `\n    fn getCoordsFromIndex(index : i32) -> ${dtype} {\n      ${snippet}\n      return ${dtype}(${coords3.join(\",\")});\n    }\n  `;\n}\nfunction getInputAtCoordsSnippet(inputInfo, isVec4) {\n  const texName = inputInfo.name;\n  const rank = inputInfo.shape.length;\n  const type = getCoordsDataType2(rank);\n  const funcName = \"get\" + texName.charAt(0).toUpperCase() + texName.slice(1);\n  const dims = [\"d0\", \"d1\", \"d2\", \"d3\", \"d4\", \"d5\"].slice(0, rank);\n  const inputs = dims.map((d) => `${d} : i32`).join(\", \");\n  if (rank < 1) {\n    if (isVec4) {\n      return `\n        fn ${funcName}() -> vec4<f32> {\n          return vec4<f32>(${texName}[0]);\n        }\n      `;\n    }\n    return `\n      fn ${funcName}() ->f32 {\n        return f32(${texName}[0]);\n      }\n    `;\n  }\n  const shapeStr = `uniforms.${texName.charAt(0).toLowerCase() + texName.slice(1)}Shape`;\n  let rankStr = `${rank}D`;\n  if (rank === 0) {\n    rankStr = \"1D\";\n  }\n  if (isVec4) {\n    return `\n      fn ${funcName}(${inputs}) -> vec4<f32> {\n        return vec4<f32>(${texName}[getIndexFromCoords${rankStr}(${type}(${dims.join(\",\")}),\n          ${shapeStr}) / 4]);\n      }\n      `;\n  }\n  return `\n    fn ${funcName}(${inputs}) -> f32 {\n      return f32(${texName}[getIndexFromCoords${rankStr}(${type}(${dims.join(\",\")}),\n        ${shapeStr})]);\n    }\n   `;\n}\nfunction getInputByOutputSnippet(inputInfo, outShape, isVec4, isFlatDispatchLayout) {\n  const texName = inputInfo.name;\n  const texFuncSnippet = texName.charAt(0).toUpperCase() + texName.slice(1);\n  const funcName = \"get\" + texFuncSnippet + \"ByOutput\";\n  const inRank = inputInfo.shape.length;\n  const outRank = outShape.length;\n  const type = getCoordsDataType2(outRank);\n  if (util_exports.arraysEqual(inputInfo.shape, outShape) && isFlatDispatchLayout) {\n    if (isVec4) {\n      return `\n      fn ${funcName}Index(globalIndex : i32) -> vec4<f32> {\n        return vec4<f32>(${texName}[globalIndex]);\n      }\n\n      fn ${funcName}Coords(coords : ${type}) -> vec4<f32> {\n        return vec4<f32>(${texName}[${outRank > 1 ? \"getOutputIndexFromCoords(coords)\" : \"coords\"} / 4]);\n      }\n      `;\n    } else {\n      return `\n    fn ${funcName}Index(globalIndex : i32) -> f32 {\n      return f32(${texName}[globalIndex]);\n    }\n\n    fn ${funcName}Coords(coords : ${type}) -> f32 {\n      return f32(${texName}[${outRank > 1 ? \"getOutputIndexFromCoords(coords)\" : \"coords\"}]);\n    }\n    `;\n    }\n  }\n  const broadcastDims = backend_util_exports.getBroadcastDims(inputInfo.shape, outShape);\n  const rankDiff = outRank - inRank;\n  let coordsSnippet = \"\";\n  if (inRank === 0) {\n    if (isVec4) {\n      return `\n    fn ${funcName}Index(globalIndex : i32) -> vec4<f32> {\n      return get${texFuncSnippet}();\n    }\n\n    fn ${funcName}Coords(coords : ${type}) -> vec4<f32> {\n      return get${texFuncSnippet}();\n    }\n  `;\n    }\n    return `\n    fn ${funcName}Index(globalIndex : i32) -> f32{\n      return get${texFuncSnippet}();\n    }\n\n    fn ${funcName}Coords(coords : ${type}) -> f32{\n      return get${texFuncSnippet}();\n    }\n  `;\n  } else {\n    if (outRank < 2 && broadcastDims.length >= 1) {\n      coordsSnippet = \"coords = 0;\";\n    } else {\n      coordsSnippet = broadcastDims.map((d) => `coords.${getCoordsXYZ(d + rankDiff)} = 0;`).join(\"\\n\");\n    }\n  }\n  let unpackedCoordsSnippet = \"\";\n  if (outRank < 2 && inRank > 0) {\n    unpackedCoordsSnippet = \"coords\";\n  } else {\n    if (outRank > 1) {\n      const coordsType = getCoordsDataType2(inRank);\n      const coordsValues = inputInfo.shape.map((s2, i2) => `coords.${getCoordsXYZ(i2 + rankDiff)}`).join(\", \");\n      unpackedCoordsSnippet = `${coordsType}(${coordsValues})`;\n    } else {\n      unpackedCoordsSnippet = \"coords\";\n    }\n  }\n  const shapeStr = `uniforms.${texName.charAt(0).toLowerCase() + texName.slice(1)}Shape`;\n  const rankStr = `${inRank}D`;\n  if (isVec4) {\n    return `\n    fn ${funcName}Index(globalIndex : i32) -> vec4<f32> {\n      var coords = getCoordsFromIndex(globalIndex);\n      ${coordsSnippet}\n      return ${texName}[getIndexFromCoords${rankStr}(${unpackedCoordsSnippet}, ${shapeStr}) / 4];\n    }\n\n    fn ${funcName}Coords(coordsIn : ${type}) -> vec4<f32> {\n      var coords = coordsIn;\n      ${coordsSnippet}\n      return ${texName}[getIndexFromCoords${rankStr}(${unpackedCoordsSnippet}, ${shapeStr}) / 4];\n    }\n  `;\n  }\n  return `\n  fn ${funcName}Index(globalIndex : i32) -> f32 {\n    var coords = getCoordsFromIndex(globalIndex);\n    ${coordsSnippet}\n    return f32(${texName}[getIndexFromCoords${rankStr}(${unpackedCoordsSnippet}, ${shapeStr})]);\n  }\n\n  fn ${funcName}Coords(coordsIn : ${type}) -> f32 {\n    var coords = coordsIn;\n    ${coordsSnippet}\n    return f32(${texName}[getIndexFromCoords${rankStr}(${unpackedCoordsSnippet}, ${shapeStr})]);\n  }\n`;\n}\nfunction getInputSnippet(inputInfo, outShape, isVec4, isFlatDispatchLayout) {\n  let res = getInputAtCoordsSnippet(inputInfo, isVec4);\n  const inShape = inputInfo.shape;\n  if (inShape.length <= outShape.length) {\n    res += getInputByOutputSnippet(inputInfo, outShape, isVec4, isFlatDispatchLayout);\n  }\n  return res;\n}\nfunction getOutputCoordsSnippet(outShape, dispatchLayout) {\n  const { x, y = [], z = [] } = dispatchLayout;\n  const outRank = outShape.length;\n  if (x.length === outRank) {\n    const dtype2 = getCoordsDataType2(outRank);\n    const snippet2 = `fn getOutputCoords() -> ${dtype2}{\n    let globalIndex = getGlobalIndex();\n    return getCoordsFromIndex(globalIndex);\n  }\n  `;\n    return snippet2;\n  }\n  let gatherDimensionsStr = \"\";\n  const dims = [x, y, z];\n  let rank = 0;\n  for (let i2 = 0; i2 < dims.length; i2++) {\n    const arr = dims[i2];\n    if (arr.length === 0) {\n      continue;\n    }\n    rank += arr.length;\n    if (arr.length === 1) {\n      gatherDimensionsStr += `let d${arr[0]} = i32(globalId[${i2}]);`;\n    } else {\n      const strides = symbolicallyComputeStrides2(arr, \"uniforms.outShape\");\n      gatherDimensionsStr += `var index${i2} = i32(globalId[${i2}]);`;\n      for (let j = 0; j < strides.length; j++) {\n        gatherDimensionsStr += `let d${arr[j]} = index${i2} / ${strides[j]};`;\n        if (j === strides.length - 1) {\n          gatherDimensionsStr += `let d${arr[j + 1]} = index${i2} - d${arr[j]} * ${strides[j]};`;\n        } else {\n          gatherDimensionsStr += `index${i2} = index${i2} - d${arr[j]} * ${strides[j]};`;\n        }\n      }\n    }\n  }\n  const dimensions = [];\n  for (let i2 = 0; i2 < rank; i2++) {\n    dimensions.push(`d${i2}`);\n  }\n  const dtype = getCoordsDataType2(rank);\n  let snippet = `fn getOutputCoords() -> ${dtype} {\n  ${gatherDimensionsStr}\n`;\n  if (dimensions.length === 0) {\n    snippet += `return ${dtype}(0); }`;\n  } else {\n    snippet += `return ${dtype}(${dimensions.join(\",\")}); }`;\n  }\n  return snippet;\n}\nfunction getOutputIndexFromCoordsSnippet(outRank) {\n  let snippet = \"\";\n  switch (outRank) {\n    case 0:\n    case 1:\n      snippet += `\n        fn getOutputIndexFromCoords(coords : i32) -> i32 {\n          return coords;\n        }\n        `;\n      break;\n    case 2:\n      snippet += `\n        fn getOutputIndexFromCoords(coords : vec2<i32>) -> i32 {\n          return dot(coords, vec2<i32>(uniforms.outShapeStrides, 1));\n        }\n        `;\n      break;\n    case 3:\n      snippet += `\n        fn getOutputIndexFromCoords(coords : vec3<i32>) -> i32 {\n          return dot(coords, vec3<i32>(uniforms.outShapeStrides.x, uniforms.outShapeStrides.y, 1));\n        }\n        `;\n      break;\n    case 4:\n      snippet += `\n        fn getOutputIndexFromCoords(coords : vec4<i32>) -> i32 {\n          return dot(coords, vec4<i32>(\n            uniforms.outShapeStrides.x, uniforms.outShapeStrides.y, uniforms.outShapeStrides.z, 1));\n        }\n        `;\n      break;\n    case 5:\n      snippet += `\n        fn getOutputIndexFromCoords(coords : vec5) -> i32 {\n          return coords.x * uniforms.outShapeStrides.x +\n              coords.y * uniforms.outShapeStrides.y +\n              coords.z * uniforms.outShapeStrides.z +\n              coords.w * uniforms.outShapeStrides.w +\n              coords.u;\n        }\n        `;\n      break;\n    case 6:\n      snippet += `\n        fn getOutputIndexFromCoords(coords : vec6) -> i32 {\n          return coords.x * uniforms.outShapeStrides.x +\n              coords.y * uniforms.outShapeStrides.y +\n              coords.z * uniforms.outShapeStrides.z +\n              coords.w * uniforms.outShapeStrides.w +\n              coords.u * uniforms.outShapeStrides.u +\n              coords.v;\n        }\n        `;\n      break;\n    default:\n      util_exports.assert(false, () => `Unsupported ${outRank}D shape`);\n      break;\n  }\n  return snippet;\n}\nfunction isFlatDispatch(program) {\n  return program.dispatch[1] === 1 && program.dispatch[2] === 1;\n}\nfunction mapToWgslTypes(type, isVec4) {\n  if (type === \"float32\") {\n    return isVec4 ? \"vec4<f32>\" : \"f32\";\n  } else if (type === \"int32\") {\n    return isVec4 ? \"vec4<i32>\" : \"i32\";\n  } else if (type === \"bool\") {\n    return isVec4 ? \"vec4<i32>\" : \"i32\";\n  }\n  return type;\n}\nfunction setOutputSnippet(outShape, outBufferType, isVec4) {\n  const outRank = outShape.length;\n  const wgslType = mapToWgslTypes(outBufferType, isVec4);\n  let snippet;\n  if (isVec4) {\n    snippet = `fn setOutputAtIndex(flatIndex : i32, value : vec4<f32>) {\n      result[flatIndex] = ${wgslType}(value);\n    }\n    fn setOutputAtIndexI32(flatIndex : i32, value : vec4<i32>) {\n      result[flatIndex] = ${wgslType}(value);\n    }`;\n  } else {\n    snippet = `fn setOutputAtIndex(flatIndex : i32, value : f32) {\n      result[flatIndex] = ${wgslType}(value);\n    }\n    fn setOutputAtIndexI32(flatIndex : i32, value : i32) {\n      result[flatIndex] = ${wgslType}(value);\n    }`;\n  }\n  if (outRank >= 2) {\n    const dims = [\"d0\", \"d1\", \"d2\", \"d3\", \"d4\", \"d5\"].slice(0, outRank);\n    const type = getCoordsDataType2(outRank);\n    if (isVec4) {\n      snippet += `\n      fn setOutputAtCoords(${dims.map((d) => `${d} : i32`).join(\", \")}, value : vec4<f32>) {\n        let flatIndex = getOutputIndexFromCoords(${type}(${dims.join(\", \")}));\n        setOutputAtIndex(flatIndex / 4, value);\n      }\n      fn setOutputAtCoordsI32(${dims.map((d) => `${d} : i32`).join(\", \")}, value : vec4<i32>) {\n        let flatIndex = getOutputIndexFromCoords(${type}(${dims.join(\", \")}));\n        setOutputAtIndexI32(flatIndex / 4, value);\n      }\n    `;\n    } else {\n      snippet += `\n      fn setOutputAtCoords(${dims.map((d) => `${d} : i32`).join(\", \")}, value : f32) {\n        let flatIndex = getOutputIndexFromCoords(${type}(${dims.join(\", \")}));\n        setOutputAtIndex(flatIndex, value);\n      }\n      fn setOutputAtCoordsI32(${dims.map((d) => `${d} : i32`).join(\", \")}, value : i32) {\n        let flatIndex = getOutputIndexFromCoords(${type}(${dims.join(\", \")}));\n        setOutputAtIndexI32(flatIndex, value);\n      }\n    `;\n    }\n  }\n  return snippet;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/webgpu_util.js\nvar webgpu_util_exports = {};\n__export(webgpu_util_exports, {\n  ArrayBufferToTypedArray: () => ArrayBufferToTypedArray,\n  GPUBytesPerElement: () => GPUBytesPerElement,\n  MatMulProgramType: () => MatMulProgramType,\n  computeDispatch: () => computeDispatch,\n  computeWorkGroupSizeForConv2d: () => computeWorkGroupSizeForConv2d,\n  computeWorkGroupSizeForMatMul: () => computeWorkGroupSizeForMatMul,\n  computeWorkPerThreadForConv2d: () => computeWorkPerThreadForConv2d,\n  flatDispatchLayout: () => flatDispatchLayout,\n  isWebGPUSupported: () => isWebGPUSupported,\n  tilesFitEvenlyIntoShape: () => tilesFitEvenlyIntoShape\n});\nvar arrayProduct = (arr) => {\n  let product = 1;\n  for (let i2 = 0; i2 < arr.length; i2++) {\n    product *= arr[i2];\n  }\n  return product;\n};\nfunction tilesFitEvenlyIntoShape(tileSize, shape) {\n  if (tileSize.length !== shape.length) {\n    throw new Error(`Cannot compute whether rank ${tileSize.length} tiles fit evenly into rank ${shape.length} shape - ranks must match.`);\n  }\n  return shape.every((dim, dimIdx) => dim % tileSize[dimIdx] === 0);\n}\nfunction computeDispatch(layout, outputShape, workGroupSize = [1, 1, 1], elementsPerThread = [1, 1, 1]) {\n  const [dispatchX, dispatchY, dispatchZ] = [\n    Math.ceil(arrayProduct(layout.x.map((d) => outputShape[d])) / (workGroupSize[0] * elementsPerThread[0])),\n    layout.y ? Math.ceil(arrayProduct(layout.y.map((d) => outputShape[d])) / (workGroupSize[1] * elementsPerThread[1])) : 1,\n    layout.z ? Math.ceil(arrayProduct(layout.z.map((d) => outputShape[d])) / (workGroupSize[2] * elementsPerThread[2])) : 1\n  ];\n  return [dispatchX, dispatchY, dispatchZ];\n}\nfunction computeWorkGroupSizeForConv2d(layout, outputShape, isVec4 = false) {\n  if (isVec4) {\n    return [8, 8, 1];\n  }\n  const dim0 = arrayProduct(layout.x.map((d) => outputShape[d]));\n  const dim1 = arrayProduct(layout.y.map((d) => outputShape[d]));\n  if (dim0 <= 4) {\n    return [4, 16, 1];\n  }\n  if (dim1 <= 4) {\n    return [16, 4, 1];\n  }\n  return [16, 16, 1];\n}\nfunction computeWorkGroupSizeForMatMul(dimAOuter, dimInner, dimBOuter) {\n  if (dimAOuter === 1) {\n    return [32, 1, 1];\n  } else if (dimBOuter === 1) {\n    return [1, 32, 1];\n  }\n  return [8, 8, 1];\n}\nfunction computeWorkPerThreadForConv2d(layout, outputShape, isVec4 = false) {\n  if (isVec4) {\n    return [4, 4, 1];\n  }\n  const dim0 = arrayProduct(layout.x.map((d) => outputShape[d]));\n  const dim1 = arrayProduct(layout.y.map((d) => outputShape[d]));\n  if (dim0 <= 4) {\n    return [1, 2, 1];\n  }\n  if (dim1 <= 4) {\n    return [2, 1, 1];\n  }\n  return [2, 2, 1];\n}\nfunction flatDispatchLayout(shape) {\n  return { x: shape.map((d, i2) => i2) };\n}\nfunction GPUBytesPerElement(dtype) {\n  if (dtype === \"float32\" || dtype === \"int32\" || dtype === \"bool\" || dtype === \"string\") {\n    return 4;\n  } else if (dtype === \"complex64\") {\n    return 8;\n  } else {\n    throw new Error(`Unknown dtype ${dtype}`);\n  }\n}\nfunction ArrayBufferToTypedArray(data, dtype) {\n  if (dtype === \"float32\") {\n    return new Float32Array(data);\n  } else if (dtype === \"int32\") {\n    return new Int32Array(data);\n  } else if (dtype === \"bool\" || dtype === \"string\") {\n    return Uint8Array.from(new Int32Array(data));\n  } else {\n    throw new Error(`Unknown dtype ${dtype}`);\n  }\n}\nfunction isWebGPUSupported() {\n  return (typeof window !== \"undefined\" || typeof WorkerGlobalScope !== \"undefined\") && !!navigator.gpu;\n}\nvar MatMulProgramType;\n(function(MatMulProgramType2) {\n  MatMulProgramType2[MatMulProgramType2[\"MatMulPackedVec4Program\"] = 0] = \"MatMulPackedVec4Program\";\n  MatMulProgramType2[MatMulProgramType2[\"MatMulReduceProgram\"] = 1] = \"MatMulReduceProgram\";\n  MatMulProgramType2[MatMulProgramType2[\"MatMulSplitKProgram\"] = 2] = \"MatMulSplitKProgram\";\n  MatMulProgramType2[MatMulProgramType2[\"MatMulSmallOutputSizeProgram\"] = 3] = \"MatMulSmallOutputSizeProgram\";\n  MatMulProgramType2[MatMulProgramType2[\"MatMulPackedProgram\"] = 4] = \"MatMulPackedProgram\";\n  MatMulProgramType2[MatMulProgramType2[\"MatMulMax\"] = 5] = \"MatMulMax\";\n})(MatMulProgramType || (MatMulProgramType = {}));\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/matmul_packed_webgpu.js\nfunction matMulReadFnSource(batchAEqualOne, batchBEqualOne, transposeA, transposeB, fitAOuter = false, fitBOuter = false, fitInner = false, component = 1) {\n  util_exports.assert(transposeA && component === 1 || !transposeA, () => `transposeA ${transposeA} is not compatible with component size ${component}`);\n  const sampleA = `\n      let batch = ${batchAEqualOne ? \"0\" : \"batchIn\"};\n      let batchASize = uniforms.aShape[1] * uniforms.aShape[2];\n      ${transposeA ? `value = A[(batch * batchASize + col * uniforms.aShape[2] + row) / ${component}];` : `value = A[(batch * batchASize + row * uniforms.aShape[2] + col) / ${component}];`}\n\n    `;\n  let sampleB;\n  if (transposeB === false) {\n    sampleB = `value = B[(batch * batchBSize + row * uniforms.bShape[2] + col) / ${component}];`;\n  } else {\n    sampleB = `value = B[(batch * batchBSize + col * uniforms.bShape[2] + row) / ${component}];`;\n  }\n  return `\n  fn mm_readA(batchIn: i32, row: i32, colIn: i32) -> ${typeSnippet(component)} {\n    var value = ${typeSnippet(component)}(0.0);\n    let col = colIn * ${component};\n    ${fitAOuter && fitInner ? sampleA : `\n    ${transposeA ? `if(row < uniforms.dimAOuter && col < uniforms.dimInner)` : `if(row < uniforms.aShape[1] && col < uniforms.aShape[2])`}\n    {\n      ${sampleA}\n    }\n    `}\n    return value;\n  }\n\n  fn mm_readB(batchIn: i32, row: i32, colIn: i32) -> ${typeSnippet(component)} {\n    let col = colIn * ${component};\n    let batch = ${batchBEqualOne ? \"0\" : \"batchIn\"};\n    let batchBSize = uniforms.bShape[1] * uniforms.bShape[2];\n    var value = ${typeSnippet(component)}(0.0);\n    ${sampleB}\n    return value;\n  }\n  `;\n}\nfunction matMulReadWriteFnSource(hasBias, activation2, batchAEqualOne, batchBEqualOne, transposeA, transposeB, fitAOuter = false, fitBOuter = false, fitInner = false, component = 1) {\n  return `\n  ${matMulReadFnSource(batchAEqualOne, batchBEqualOne, transposeA, transposeB, fitAOuter, fitBOuter, fitInner, component)}\n  fn mm_write(batch: i32, row: i32, colIn: i32, valueIn: ${typeSnippet(component)}) {\n    let col = colIn * ${component};\n    ${fitAOuter && fitBOuter ? \"\" : \"if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)\"}\n    {\n      var value = valueIn;\n      let coords = vec3<i32>(batch, row, col);\n      ${biasActivationSnippet(hasBias, activation2)}\n      setOutputAtCoords(coords[0], coords[1], coords[2], value);\n    }\n  }\n  `;\n}\nvar writeDataToSubASnippet = (transpose6) => {\n  if (transpose6) {\n    return `\n        mm_Asub[inputRow][inputCol] = mm_readA(batch,\n          t * TileInner + inputRow,\n          globalRowStart + inputCol);\n        `;\n  } else {\n    return `\n        mm_Asub[inputRow][inputCol] = mm_readA(batch,\n          globalRowStart + inputRow,\n          t * TileInner + inputCol);\n        `;\n  }\n};\nvar readDataFromSubASnippet = (transposeA) => {\n  return transposeA ? \"let ACached = mm_Asub[k][tileRow + innerRow];\" : \"let ACached = mm_Asub[tileRow + innerRow][k];\";\n};\nfunction makeMatMulPackedSource(workPerThread, workGroupSize, transposeA = false, tileInner = 32) {\n  const tileAOuter = workPerThread[1] * workGroupSize[1];\n  const tileBOuter = workPerThread[0] * workGroupSize[0];\n  const tileAWidth = transposeA ? tileAOuter : tileInner;\n  const tileAHight = transposeA ? tileInner : tileAOuter;\n  util_exports.assert(tileAHight % workGroupSize[1] === 0 && tileAWidth % workGroupSize[0] === 0 && tileInner % workGroupSize[1] === 0, () => `tileAHight ${tileAHight} must be divisible by workGroupSize[1]${workGroupSize[1]}, tileAWidth ${tileAWidth} must be divisible by workGroupSize[0]${workGroupSize[0]}, tileInner ${tileInner} must be divisible by workGroupSize[1]${workGroupSize[1]}`);\n  const rowPerThreadA = tileAHight / workGroupSize[1];\n  const colPerThreadA = tileAWidth / workGroupSize[0];\n  const rowPerThreadB = tileInner / workGroupSize[1];\n  return `\n    var<workgroup> mm_Asub : array<array<f32, ${tileAWidth}>, ${tileAHight}>;\n    var<workgroup> mm_Bsub : array<array<f32, ${tileBOuter}>, ${tileInner}>;\n    const RowPerThread = ${workPerThread[1]};\n    const ColPerThread = ${workPerThread[0]};\n    const TileInner = ${tileInner};\n\n    @compute @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)\n    fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,\n            @builtin(global_invocation_id) GlobalId : vec3<u32>,\n            @builtin(num_workgroups) NumWorkgroups: vec3<u32>,\n            @builtin(workgroup_id) workgroupId: vec3<u32>) {\n      localId = LocalId;\n      globalId = GlobalId;\n      numWorkgroups = NumWorkgroups;\n\n      let tileRow = i32(localId.y) * RowPerThread;\n      let tileCol = i32(localId.x) * ColPerThread;\n\n      let globalRow = i32(globalId.y) * RowPerThread;\n      let globalCol = i32(globalId.x) * ColPerThread;\n      let batch = i32(globalId.z);\n      let globalRowStart = i32(workgroupId.y) * ${tileAOuter};\n\n      let numTiles = (uniforms.dimInner - 1) / TileInner + 1;\n\n      var acc : array<array<f32, ColPerThread>, RowPerThread>;\n\n      // Without this initialization strange values show up in acc.\n      for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {\n        for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {\n          acc[innerRow][innerCol] = 0.0;\n        }\n      }\n\n      let tileRowA = i32(localId.y) * ${rowPerThreadA};\n      let tileColA = i32(localId.x) * ${colPerThreadA};\n      let tileRowB = i32(localId.y) * ${rowPerThreadB};\n      // Loop over shared dimension.\n      for (var t = 0; t < numTiles; t = t + 1) {\n        // Load one tile of A into local memory.\n        for (var innerRow = 0; innerRow < ${rowPerThreadA}; innerRow = innerRow + 1) {\n          for (var innerCol = 0; innerCol < ${colPerThreadA}; innerCol = innerCol + 1) {\n            let inputRow = tileRowA + innerRow;\n            let inputCol = tileColA + innerCol;\n            ${writeDataToSubASnippet(transposeA)}\n          }\n        }\n\n        // Load one tile of B into local memory.\n        for (var innerRow = 0; innerRow < ${rowPerThreadB}; innerRow = innerRow + 1) {\n          for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {\n            let inputRow = tileRowB + innerRow;\n            let inputCol = tileCol + innerCol;\n            mm_Bsub[inputRow][inputCol] = mm_readB(batch,\n              t * TileInner + inputRow,\n              globalCol + innerCol);\n          }\n        }\n\n        workgroupBarrier();\n\n        // Compute acc values for a single thread.\n        var BCached : array<f32, ColPerThread>;\n        for (var k = 0; k < TileInner; k = k + 1) {\n          for (var inner = 0; inner < ColPerThread; inner = inner + 1) {\n            BCached[inner] = mm_Bsub[k][tileCol + inner];\n          }\n\n          for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {\n            ${readDataFromSubASnippet(transposeA)}\n            for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {\n              acc[innerRow][innerCol] = acc[innerRow][innerCol] + ACached * BCached[innerCol];\n            }\n          }\n        }\n\n        workgroupBarrier();\n      }\n\n      for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {\n        for (var innerCol = 0; innerCol < ColPerThread; innerCol = innerCol + 1) {\n          mm_write(batch, globalRow + innerRow, globalCol + innerCol,\n              acc[innerRow][innerCol]);\n        }\n      }\n    }\n  `;\n}\nvar readVectorASnippet = (transpose6) => {\n  return transpose6 ? `\n      mm_readA(batch, colA, globalRow),\n      mm_readA(batch, colA + 1, globalRow),\n      mm_readA(batch, colA + 2, globalRow),\n      mm_readA(batch, colA + 3, globalRow)\n  ` : `\n      mm_readA(batch, globalRow, colA),\n      mm_readA(batch, globalRow, colA + 1),\n      mm_readA(batch, globalRow, colA + 2),\n      mm_readA(batch, globalRow, colA + 3)\n  `;\n};\nfunction makeVectorMatrixProductSource(workGroupSize, transposeA = false) {\n  util_exports.assert(workGroupSize[1] === 1 && workGroupSize[2] === 1, () => `A linear work group size is required. But got ${workGroupSize}.`);\n  return `\n    const TileSize = ${workGroupSize[0] * 4};\n    var<workgroup> mm_Asub : array<vec4<f32>, ${workGroupSize[0]}>;\n\n    ${getMainHeaderString()}\n      let tileCol = i32(localId.x);\n      let globalCol = i32(globalId.x);\n      let globalRow = i32(globalId.y);\n\n      let numTiles = (uniforms.dimInner - 1) / TileSize + 1;\n      let batch = i32(globalId.z);\n      // Without this initialization strange values show up in acc.\n      var acc = 0.0;\n\n      // Loop over shared dimension.\n      for (var t = 0; t < numTiles; t = t + 1) {\n        // Load one tile of A into local memory.\n        let colA = t * TileSize + tileCol * 4;\n        mm_Asub[tileCol] = vec4<f32>(${readVectorASnippet(transposeA)});\n        workgroupBarrier();\n\n        // Compute acc values for a single thread.\n        for (var k = 0; k < TileSize / 4; k = k + 1) {\n          let rowB = t * TileSize + k * 4;\n          let BCached = vec4<f32>(mm_readB(batch, rowB, globalCol),\n                              mm_readB(batch, rowB + 1, globalCol),\n                              mm_readB(batch, rowB + 2, globalCol),\n                              mm_readB(batch, rowB + 3, globalCol));\n\n          let ACached = mm_Asub[k];\n          acc = acc + dot(ACached, BCached);\n        }\n\n        workgroupBarrier();\n      }\n\n      mm_write(batch, globalRow, globalCol, acc);\n    }\n  `;\n}\nvar MatMulPackedProgram2 = class {\n  constructor(aShape, outputShape, workPerThread, batchAEqualOne, batchBEqualOne, transposeA = false, transposeB = false, bias = null, activation2 = null, preluActivationWeights = null) {\n    this.variableNames = [\"A\", \"B\"];\n    this.uniforms = `dimAOuter : i32, dimBOuter : i32, dimInner : i32,`;\n    this.workGroupSize = [16, 16, 1];\n    this.outputShape = outputShape;\n    this.dispatchLayout = { x: [2], y: [1], z: [0] };\n    const dimInner = transposeA ? aShape[1] : aShape[2];\n    this.workGroupSize = computeWorkGroupSizeForMatMul(outputShape[1], dimInner, outputShape[2]);\n    if (outputShape[1] === 1 || outputShape[2] === 1) {\n      workPerThread = 1;\n    }\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [workPerThread, workPerThread, 1]);\n    if (util_exports.arraysEqual(this.dispatch, [1, 1, 1])) {\n      workPerThread = 1;\n      this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [workPerThread, workPerThread, 1]);\n    }\n    const addBias = bias != null;\n    const hasPreluActivationWeights = preluActivationWeights != null;\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivationWeights) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.workPerThread = workPerThread;\n    this.transposeA = transposeA;\n    this.transposeB = transposeB;\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivationWeights = hasPreluActivationWeights;\n    this.batchAEqualOne = batchAEqualOne;\n    this.batchBEqualOne = batchBEqualOne;\n    [this.fitAOuter, this.fitBOuter, this.fitInner] = this.getShapeFit(outputShape[1], outputShape[2], dimInner);\n    this.shaderKey = `matMulPacked_${this.workPerThread}_${transposeA}_${transposeB}_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.outputShape[1] > 1}_${this.batchAEqualOne}_${this.batchBEqualOne}`;\n  }\n  getShapeFit(dimAOuter, dimBOuter, dimInner) {\n    const tileAOuter = this.workGroupSize[1] * this.workPerThread;\n    const tileBOuter = this.workGroupSize[0] * this.workPerThread;\n    this.tileInner = 32;\n    if (this.outputShape[1] === 1) {\n      this.tileInner = this.workGroupSize[0] * 4;\n    }\n    const fitAOuter = dimAOuter % tileAOuter === 0;\n    const fitBOuter = dimBOuter % tileBOuter === 0;\n    const fitInner = dimInner % this.tileInner === 0;\n    return [fitAOuter, fitBOuter, fitInner];\n  }\n  getUserCode() {\n    const userCode = `\n      ${activationFnSnippet(this.activation, this.hasPreluActivationWeights)}\n      ${matMulReadWriteFnSource(this.addBias, this.activation, this.batchAEqualOne, this.batchBEqualOne, false, this.transposeB, this.fitAOuter, this.fitBOuter, this.fitInner)}\n      ${this.outputShape[1] > 1 ? makeMatMulPackedSource([this.workPerThread, this.workPerThread, 1], this.workGroupSize, this.transposeA, this.tileInner) : makeVectorMatrixProductSource(this.workGroupSize, this.transposeA)}\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/matmul_packed_vec4_webgpu.js\nvar writeDataToSubASnippet2 = (transpose6, innerAElementSize) => {\n  if (transpose6) {\n    return `\n        mm_Asub[inputRow][inputCol] = mm_readA(batch,\n          t * TileInner + inputRow,\n          globalRowStart / ${innerAElementSize} + inputCol);\n        `;\n  } else {\n    return `\n        mm_Asub[inputRow][inputCol] = mm_readA(batch,\n          globalRow + innerRow,\n          t * TileInner / ${innerAElementSize} + inputCol);\n        `;\n  }\n};\nvar calculateResultSnippet = (transposeA, innerElementSize) => {\n  if (transposeA) {\n    return `\n        let ACached0 = mm_Asub[k * InnerElementSize][localRow];\n        let ACached1 = mm_Asub[k * InnerElementSize + 1][localRow];\n        let ACached2 = mm_Asub[k * InnerElementSize + 2][localRow];\n        ${innerElementSize === 3 ? \"\" : \"let ACached3 = mm_Asub[k * InnerElementSize + 3][localRow];\"}\n        for (var i = 0; i < RowPerThread; i = i + 1) {\n          acc[i] = BCached[0] * ACached0[i] + acc[i];\n          acc[i] = BCached[1] * ACached1[i] + acc[i];\n          acc[i] = BCached[2] * ACached2[i] + acc[i];\n          ${innerElementSize === 3 ? \"\" : \"acc[i] = BCached[3] * ACached3[i] + acc[i];\"}\n        }`;\n  } else {\n    return `\n        for (var i = 0; i < RowPerThread; i = i + 1) {\n          let ACached = mm_Asub[tileRow + i][k];\n          acc[i] = BCached[0] * ACached.x + acc[i];\n          acc[i] = BCached[1] * ACached.y + acc[i];\n          acc[i] = BCached[2] * ACached.z + acc[i];\n          ${innerElementSize === 3 ? \"\" : \"acc[i] = BCached[3] * ACached.w + acc[i];\"}\n        }`;\n  }\n};\nfunction makeMatMulPackedVec4Source(workPerThread, tileAOuter, tileBOuter, tileInner, innerElementSize = 4, transposeA = false) {\n  const tileAWidth = transposeA ? tileAOuter : tileInner;\n  const tileAHight = transposeA ? tileInner : tileAOuter;\n  const innerAElementSize = transposeA ? workPerThread[1] : innerElementSize;\n  util_exports.assert((transposeA && tileAOuter === tileBOuter || (tileInner % 4 === 0 || tileInner % 3 === 0)) && workPerThread[0] === 4 && (innerElementSize === 3 || innerElementSize === 4), () => `tileInner ${tileInner} must be divisible by 4|3. ColPerThread ${workPerThread[0]} must be 4.\n           innerElementSize ${innerElementSize} must be 3|4.`);\n  return `\n  var<workgroup> mm_Asub : array<array<vec${innerAElementSize}<f32>, ${tileAWidth / innerAElementSize}>, ${tileAHight}>;\n  var<workgroup> mm_Bsub : array<array<vec4<f32>, ${tileBOuter / workPerThread[0]}>, ${tileInner}>;\n\n  const RowPerThread = ${workPerThread[1]};\n  const ColPerThread = ${workPerThread[0]};\n  const InnerElementSize = ${innerElementSize};\n  const TileInner = ${tileInner};\n\n  @compute @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)\n  fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,\n          @builtin(global_invocation_id) GlobalId : vec3<u32>,\n          @builtin(num_workgroups) NumWorkgroups: vec3<u32>,\n          @builtin(workgroup_id) workgroupId: vec3<u32>) {\n    localId = LocalId;\n    globalId = GlobalId;\n    numWorkgroups = NumWorkgroups;\n\n    let localRow = i32(localId.y);\n    let tileRow = ${tileAOuter === 1 ? \"0\" : \"localRow * RowPerThread\"};\n    let tileCol = i32(localId.x);\n\n    let globalRow = ${tileAOuter === 1 ? \"0\" : \"i32(globalId.y) * RowPerThread\"};\n    let globalCol = i32(globalId.x);\n    let batch = i32(globalId.z);\n    let globalRowStart = i32(workgroupId.y) * ${tileAOuter};\n\n    let numTiles = (uniforms.dimInner - 1) / TileInner + 1;\n\n    var acc: array<vec4<f32>, RowPerThread>;\n    var BCached : array<vec4<f32>, 4>;\n\n    // Loop over shared dimension.\n    let RowPerThreadB = TileInner / i32(workGroupSizeY);\n    let tileRowB = localRow * RowPerThreadB;\n    for (var t = 0; t < numTiles; t = t + 1) {\n        // Load one tile of A into local memory.\n        for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {\n            let inputRow = tileRow + innerRow;\n            let inputCol = tileCol;\n            ${writeDataToSubASnippet2(transposeA, innerAElementSize)}\n        }\n\n        // Load one tile of B into local memory.\n        for (var innerRow = 0; innerRow < RowPerThreadB; innerRow = innerRow + 1) {\n            let inputRow = tileRowB + innerRow;\n            let inputCol = tileCol;\n            mm_Bsub[inputRow][inputCol] = mm_readB(batch, t * TileInner + inputRow, globalCol);\n        }\n\n        workgroupBarrier();\n\n        // Compute acc values for a single thread.\n        for (var k = 0; k < TileInner / InnerElementSize; k = k + 1) {\n            BCached[0] = mm_Bsub[k * InnerElementSize][tileCol];\n            BCached[1] = mm_Bsub[k * InnerElementSize + 1][tileCol];\n            BCached[2] = mm_Bsub[k * InnerElementSize + 2][tileCol];\n            ${innerElementSize === 3 ? \"\" : \"BCached[3] = mm_Bsub[k * InnerElementSize + 3][tileCol];\"}\n\n            ${calculateResultSnippet(transposeA, innerElementSize)}\n        }\n\n        workgroupBarrier();\n    }\n\n    for (var innerRow = 0; innerRow < RowPerThread; innerRow = innerRow + 1) {\n        mm_write(batch, globalRow + innerRow, globalCol, acc[innerRow]);\n    }\n  }`;\n}\nvar MatMulPackedVec4Program = class {\n  constructor(aShape, outputShape, batchAEqualOne, batchBEqualOne, transposeA = false, bias = null, activation2 = null, preluActivationWeights = null) {\n    this.variableNames = [\"A\", \"B\"];\n    this.uniforms = `dimAOuter : i32, dimBOuter : i32, dimInner : i32,`;\n    this.workGroupSize = [8, 8, 1];\n    this.isVec4 = true;\n    this.outputShape = outputShape;\n    this.dispatchLayout = { x: [2], y: [1], z: [0] };\n    if (outputShape[1] === 1 && !transposeA) {\n      this.elementsPerThread = [4, 1, 1];\n    } else {\n      this.elementsPerThread = [4, 4, 1];\n    }\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, this.elementsPerThread);\n    const addBias = bias != null;\n    const hasPreluActivationWeights = preluActivationWeights != null;\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivationWeights) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.tileAOuter = outputShape[1] === 1 && !transposeA ? 1 : this.workGroupSize[1] * this.elementsPerThread[1];\n    this.tileBOuter = this.workGroupSize[0] * this.elementsPerThread[0];\n    this.tileInner = this.tileBOuter;\n    this.aShape = aShape;\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivationWeights = hasPreluActivationWeights;\n    this.batchAEqualOne = batchAEqualOne;\n    this.batchBEqualOne = batchBEqualOne;\n    this.transposeA = transposeA;\n    const dimInner = transposeA ? aShape[1] : aShape[2];\n    this.fitAOuter = outputShape[1] % this.tileAOuter === 0;\n    this.fitBOuter = outputShape[2] % this.tileBOuter === 0;\n    this.fitInner = dimInner % this.tileInner === 0;\n    this.shaderKey = `matMulPackedVec4_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.elementsPerThread}_${this.batchAEqualOne}_${this.batchBEqualOne}_${this.transposeA}`;\n  }\n  getUserCode() {\n    const userCode = `\n      ${activationFnSnippet(this.activation, this.hasPreluActivationWeights, true)}\n      ${matMulReadWriteFnSource(this.addBias, this.activation, this.batchAEqualOne, this.batchBEqualOne, false, false, this.fitAOuter, this.fitBOuter, this.fitInner, 4)}\n      ${makeMatMulPackedVec4Source(this.elementsPerThread, this.tileAOuter, this.tileBOuter, this.tileInner, 4, this.transposeA)}\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/matmul_reduce_webgpu.js\nfunction makeMatMulReduceSource() {\n  return `\n    var<workgroup> sumValues : array<f32, workGroupSizeX>;\n    ${getMainHeaderString()}\n      let coords = getOutputCoords();\n      let batch = coords[0];\n      let row = coords[1];\n      let col = coords[2];\n      var sum = 0.0;\n      let Length = uniforms.dimInner;\n      for (var k = i32(localId.x); k < Length; k = k + i32(workGroupSizeX)) {\n        let dataA = mm_readA(batch, row, k);\n        let dataB = mm_readB(batch, k, col);\n        sum = sum + dataA * dataB;\n      }\n      sumValues[localId.x] = sum;\n      workgroupBarrier();\n\n      for(var currentSize = workGroupSizeX / 2u; currentSize > 1u;\n          currentSize = currentSize / 2u) {\n        if (localId.x < currentSize)\n        {\n          sumValues[localId.x] = sumValues[localId.x] + sumValues[localId.x + currentSize];\n        }\n        workgroupBarrier();\n      }\n\n      if (localId.x == 0u) {\n        sum = sumValues[0] + sumValues[1];\n        mm_write(batch, row, col, sum);\n      }\n    }\n  `;\n}\nvar MatMulReduceProgram = class {\n  constructor(outputShape, batchAEqualOne, batchBEqualOne, transposeA = false, transposeB = false, bias = null, activation2 = null, preluActivationWeights = null) {\n    this.variableNames = [\"A\", \"B\"];\n    this.uniforms = `dimAOuter : i32, dimBOuter : i32, dimInner : i32,`;\n    this.workGroupSize = [256, 1, 1];\n    this.outputShape = outputShape;\n    this.dispatchLayout = { x: [], y: [1, 2], z: [0] };\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    const addBias = bias != null;\n    const hasPreluActivationWeights = preluActivationWeights != null;\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivationWeights) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.transposeA = transposeA;\n    this.transposeB = transposeB;\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivationWeights = hasPreluActivationWeights;\n    this.batchAEqualOne = batchAEqualOne;\n    this.batchBEqualOne = batchBEqualOne;\n    this.shaderKey = `matMulReduce_${this.activation}_${transposeA}_${transposeB}_${this.batchAEqualOne}_${this.batchBEqualOne}`;\n  }\n  getUserCode() {\n    const userCode = `\n      ${activationFnSnippet(this.activation, this.hasPreluActivationWeights)}\n      ${matMulReadWriteFnSource(this.addBias, this.activation, this.batchAEqualOne, this.batchBEqualOne, this.transposeA, this.transposeB)}\n      ${makeMatMulReduceSource()}\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/matmul_small_output_size_webgpu.js\nfunction makeMatMulSmallOutputSizeSource(workGroupSize) {\n  const tileAOuter = workGroupSize[1];\n  const tileBOuter = workGroupSize[0];\n  const tileInner = tileAOuter > tileBOuter ? tileAOuter : tileBOuter;\n  return `\n  var<workgroup> mm_Asub : array<array<f32, ${tileInner}>, ${tileAOuter}>;\n  var<workgroup> mm_Bsub : array<array<f32, ${tileBOuter}>, ${tileInner}>;\n\n  // If the output size is small for matrix multiplication, avoid to use vec4\n  // and handle some elements per thread to optimally utilize the ALU.\n  // Read data from global memory to registers firstly, then store them into\n  // shared memory, so it is instruction-Level parallelism for arithmetic\n  // operations and others handle IO operations between barrier api, makes ALU\n  // and load/store units work simultaneously, could improves the performance.\n  ${getMainHeaderString()}\n    let tileRow = i32(localId.y);\n    let tileCol = i32(localId.x);\n    let globalRow = i32(globalId.y);\n    let globalCol = i32(globalId.x);\n    let batch = i32(globalId.z);\n\n    // uniforms.dimInner should be greater than 0.\n    let numTiles = (uniforms.dimInner - 1) / ${tileInner} + 1;\n    var acc = 0.0;\n\n    var globalColA = tileCol;\n    var globalRowB = 0;\n    var regA = mm_readA(batch, globalRow, globalColA);\n    var regB0 = mm_readB(batch, globalRowB + 2 * tileRow, globalCol);\n    var regB1 = mm_readB(batch, globalRowB + 2 * tileRow + 1, globalCol);\n    globalColA = globalColA + ${tileInner};\n    globalRowB = globalRowB + ${tileInner};\n\n    for (var t = 0; t < numTiles; t = t + 1) {\n      mm_Asub[tileRow][tileCol] = regA;\n      mm_Bsub[2 * tileRow][tileCol] = regB0;\n      mm_Bsub[2 * tileRow + 1][tileCol] = regB1;\n\n      workgroupBarrier();\n\n      regA = mm_readA(batch, globalRow, globalColA);\n      regB0 = mm_readB(batch, globalRowB + 2 * tileRow, globalCol);\n      regB1 = mm_readB(batch, globalRowB + 2 * tileRow + 1, globalCol);\n      globalColA = globalColA + ${tileInner};\n      globalRowB = globalRowB + ${tileInner};\n\n      for (var k = 0; k < ${tileInner}; k = k + 1) {\n        acc = acc + mm_Asub[tileRow][k] * mm_Bsub[k][tileCol];\n      }\n      workgroupBarrier();\n    }\n\n    mm_write(batch, globalRow, globalCol, acc);\n  }\n  `;\n}\nvar MatMulSmallOutputSizeProgram = class {\n  constructor(aShape, bShape, outputShape, transposeA = false, transposeB = false, bias = null, activation2 = null, preluActivationWeights = null) {\n    this.variableNames = [\"A\", \"B\"];\n    this.uniforms = `dimAOuter : i32, dimBOuter : i32, dimInner : i32,`;\n    this.workGroupSize = [16, 8, 1];\n    this.outputShape = outputShape;\n    this.dispatchLayout = { x: [2], y: [1], z: [0] };\n    this.dispatch = [\n      Math.ceil(outputShape[2] / this.workGroupSize[0]),\n      Math.ceil(outputShape[1] / this.workGroupSize[1]),\n      outputShape[0]\n    ];\n    const addBias = bias != null;\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    const hasPreluActivationWeights = preluActivationWeights != null;\n    if (hasPreluActivationWeights) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.transposeA = transposeA;\n    this.transposeB = transposeB;\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivationWeights = hasPreluActivationWeights;\n    this.batchAEqualOne = aShape[0] === 1;\n    this.batchBEqualOne = bShape[0] === 1;\n    this.shaderKey = `matMulSmallOutputSize_${this.activation}_${transposeA}_${transposeB}_${this.batchAEqualOne}_${this.batchBEqualOne}`;\n  }\n  getUserCode() {\n    const userCode = `\n      ${activationFnSnippet(this.activation, this.hasPreluActivationWeights)}\n      ${matMulReadWriteFnSource(this.addBias, this.activation, this.batchAEqualOne, this.batchBEqualOne, this.transposeA, this.transposeB)}\n      ${makeMatMulSmallOutputSizeSource(this.workGroupSize)}\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/matmul_splitK_webgpu.js\nvar MatMulSplitKProgram = class {\n  constructor(outputShape, dimInner, batchAEqualOne, batchBEqualOne, transposeA = false, transposeB = false) {\n    this.variableNames = [\"A\", \"B\"];\n    this.uniforms = `dimAOuter : i32, dimBOuter : i32, dimInner : i32,`;\n    this.workGroupSize = [8, 8, 1];\n    this.atomic = true;\n    this.tileInner = 32;\n    util_exports.assert(outputShape[0] === 1, () => \"MatMulSplitKProgram only supports batch = 1.\");\n    this.outputShape = outputShape;\n    this.dispatchLayout = { x: [2], y: [1], z: [0, 3] };\n    this.elementsPerThread = [4, 4, this.tileInner];\n    if (this.outputShape[1] < 16) {\n      this.elementsPerThread[1] = 1;\n    }\n    if (this.outputShape[2] < 16) {\n      this.elementsPerThread[0] = 1;\n    }\n    this.dispatch = computeDispatch(this.dispatchLayout, [\n      this.outputShape[0],\n      this.outputShape[1],\n      this.outputShape[2],\n      dimInner\n    ], this.workGroupSize, this.elementsPerThread);\n    this.transposeA = transposeA;\n    this.transposeB = transposeB;\n    this.batchAEqualOne = batchAEqualOne;\n    this.batchBEqualOne = batchBEqualOne;\n    this.shaderKey = `matMulSplitK_${transposeA}_${transposeB}_${batchAEqualOne}_${batchBEqualOne}_${this.elementsPerThread}`;\n  }\n  getUserCode() {\n    const atomicAddSnippet = `\n     var oldValue = atomicLoad(&(result[flatIndex]));\n     var exchanged = false;\n     for (; !exchanged;) {\n       let newValueF32 = bitcast<f32>(oldValue) + value;\n       let newValue = bitcast<i32>(newValueF32);\n       let res = atomicCompareExchangeWeak(&(result[flatIndex]), oldValue, newValue);\n       oldValue = res.old_value;\n       exchanged = res.exchanged;\n     }\n     `;\n    const userCode = `\n      ${matMulReadFnSource(this.batchAEqualOne, this.batchBEqualOne, this.transposeA, this.transposeB)}\n      fn mm_write(batch: i32, row : i32, col : i32, valueIn : f32) {\n        if (row < uniforms.dimAOuter && col < uniforms.dimBOuter) {\n          let coords = vec3<i32>(batch, row, col);\n          let flatIndex = getOutputIndexFromCoords(coords);\n          var value = valueIn;\n          // The problem is that we should initialize output to zero before using.\n          // Otherwise, the original value will be added to the result.\n          ${atomicAddSnippet}\n        }\n      }\n\n      ${this.makeMatMulSplitKSource()}\n    `;\n    return userCode;\n  }\n  makeMatMulSplitKSource() {\n    const tileAOuter = this.workGroupSize[1] * this.elementsPerThread[1];\n    const tileBOuter = this.workGroupSize[0] * this.elementsPerThread[0];\n    const rowPerThread = this.elementsPerThread[1];\n    const colPerThread = this.elementsPerThread[0];\n    const colPerThreadA = this.tileInner / this.workGroupSize[0];\n    const rowPerThreadB = this.tileInner / this.workGroupSize[1];\n    util_exports.assert(this.tileInner % this.workGroupSize[0] === 0 && this.tileInner % this.workGroupSize[1] === 0, () => `tileInner ${this.tileInner} must be divisible by workGroupSize[0]${this.workGroupSize[0]} and workGroupSize[1]${this.workGroupSize[1]}`);\n    return `\n      var<workgroup> mm_Asub : array<array<f32, ${this.tileInner}>, ${tileAOuter}>;\n      var<workgroup> mm_Bsub : array<array<f32, ${tileBOuter}>, ${this.tileInner}>;\n      ${getMainHeaderString()}\n        let tileRow = i32(localId.y) * ${rowPerThread};\n        let tileCol = i32(localId.x) * ${colPerThread};\n\n        let globalRow = i32(globalId.y) * ${rowPerThread};\n        let globalCol = i32(globalId.x) * ${colPerThread};\n        let batch = 0;\n        let kStart = i32(globalId.z) * ${this.tileInner};\n\n        // Load one tile of A into local memory.\n        let tileColA = i32(localId.x) * ${colPerThreadA};\n        for (var innerRow = 0; innerRow < ${rowPerThread}; innerRow = innerRow + 1) {\n          for (var innerCol = 0; innerCol < ${colPerThreadA}; innerCol = innerCol + 1) {\n            let inputRow = tileRow + innerRow;\n            let inputCol = tileColA + innerCol;\n            mm_Asub[inputRow][inputCol] = mm_readA(${this.batchAEqualOne ? 0 : \"batch\"},\n                globalRow + innerRow,\n                kStart + inputCol);\n          }\n        }\n        // Load one tile of B into local memory.\n        let tileRowB = i32(localId.y) * ${rowPerThreadB};\n        for (var innerRow = 0; innerRow < ${rowPerThreadB}; innerRow = innerRow + 1) {\n          for (var innerCol = 0; innerCol < ${colPerThread}; innerCol = innerCol + 1) {\n            let inputRow = tileRowB + innerRow;\n            let inputCol = tileCol + innerCol;\n            mm_Bsub[inputRow][inputCol] = mm_readB(${this.batchBEqualOne ? 0 : \"batch\"},\n                kStart + inputRow,\n                globalCol + innerCol);\n          }\n        }\n\n        workgroupBarrier();\n\n        var acc : array<array<f32, ${colPerThread}>, ${rowPerThread}>;\n        // Loop over shared dimension. Compute acc values for a single thread.\n        for (var k = 0; k < ${this.tileInner}; k = k + 1) {\n          var BCached : array<f32, ${colPerThread}>;\n          for (var inner = 0; inner < ${colPerThread}; inner = inner + 1) {\n            BCached[inner] = mm_Bsub[k][tileCol + inner];\n          }\n\n          for (var innerRow = 0; innerRow < ${rowPerThread}; innerRow = innerRow + 1) {\n            let ACached = mm_Asub[tileRow + innerRow][k];\n            for (var innerCol = 0; innerCol < ${colPerThread}; innerCol = innerCol + 1) {\n              acc[innerRow][innerCol] = acc[innerRow][innerCol] + ACached * BCached[innerCol];\n            }\n          }\n        }\n\n        for (var innerRow = 0; innerRow < ${rowPerThread}; innerRow = innerRow + 1) {\n          for (var innerCol = 0; innerCol < ${colPerThread}; innerCol = innerCol + 1) {\n            mm_write(batch, globalRow + innerRow, globalCol + innerCol, acc[innerRow][innerCol]);\n          }\n        }\n      }\n    `;\n  }\n};\nvar BiasActivationProgram = class {\n  constructor(outputShape, bias = null, activation2 = null, preluActivationWeights = null) {\n    this.uniforms = \"\";\n    this.variableNames = [\"x\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.addBias = bias != null;\n    this.hasPreluActivationWeights = preluActivationWeights != null;\n    this.activation = activation2;\n    if (this.addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (this.hasPreluActivationWeights) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.shaderKey = `biasActivation_${activation2}`;\n  }\n  getUserCode() {\n    return `\n    ${activationFnSnippet(this.activation, this.hasPreluActivationWeights)}\n    ${getMainHeaderAndGlobalIndexString()}\n      if (index < uniforms.size) {\n        let coords = getCoordsFromIndex(index);\n        var value = getXByOutputIndex(index);\n        ${biasActivationSnippet(this.addBias, this.activation)}\n        setOutputAtIndex(index, value);\n      }\n    }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/fill_webgpu.js\nvar FillProgram2 = class {\n  constructor(shape) {\n    this.variableNames = [];\n    this.outputShape = [];\n    this.uniforms = \"value : f32,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = shape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = \"fill\";\n  }\n  getUserCode() {\n    const userCode = `\n    ${getMainHeaderAndGlobalIndexString()}\n      if (index < uniforms.size) {\n        setOutputAtIndex(index, uniforms.value);\n      }\n    }\n  `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Fill.js\nfunction fill5(args) {\n  const { backend: backend2, attrs } = args;\n  const { shape, value } = attrs;\n  let { dtype } = attrs;\n  dtype = dtype || util_exports.inferDtype(value);\n  if (dtype === \"string\") {\n    const values = util_exports.getArrayFromDType(dtype, util_exports.sizeFromShape(shape));\n    values.fill(value);\n    return backend2.makeTensorInfo(shape, dtype, values);\n  } else {\n    const program = new FillProgram2(shape);\n    const uniformData = [{ type: \"float32\", data: [value] }];\n    return backend2.runWebGPUProgram(program, [], dtype, uniformData);\n  }\n}\nvar fillConfig4 = {\n  kernelName: Fill,\n  backendName: \"webgpu\",\n  kernelFunc: fill5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Reshape.js\nfunction reshape6(args) {\n  const { inputs, attrs } = args;\n  const { x } = inputs;\n  const { shape } = attrs;\n  const xSize = util_exports.sizeFromShape(x.shape);\n  const $shape = util_exports.inferFromImplicitShape(shape, xSize);\n  const $xSize = util_exports.sizeFromShape($shape);\n  util_exports.assert(xSize === $xSize, () => `The new shape (${$shape}) has ${$xSize} elements and the old shape (${x.shape}) has ${xSize} elements. The new shape and old shape must have the same number of elements.`);\n  args.backend.incRef(x.dataId);\n  return { dataId: x.dataId, shape: $shape, dtype: x.dtype };\n}\nvar reshapeConfig4 = {\n  kernelName: Reshape,\n  backendName: \"webgpu\",\n  kernelFunc: reshape6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/BatchMatMul_impl.js\nfunction batchMatMulImpl2({ a, b, transposeA, transposeB, backend: backend2, bias = null, preluActivationWeights = null, leakyreluAlpha = 0, activation: activation2 = null }) {\n  const aRank = a.shape.length;\n  const bRank = b.shape.length;\n  const innerShapeA = transposeA ? a.shape[aRank - 2] : a.shape[aRank - 1];\n  const innerShapeB = transposeB ? b.shape[bRank - 1] : b.shape[bRank - 2];\n  const outerShapeA = transposeA ? a.shape[aRank - 1] : a.shape[aRank - 2];\n  const outerShapeB = transposeB ? b.shape[bRank - 2] : b.shape[bRank - 1];\n  const outerDimsA = a.shape.slice(0, -2);\n  const outerDimsB = b.shape.slice(0, -2);\n  const batchDimA = util_exports.sizeFromShape(outerDimsA);\n  const batchDimB = util_exports.sizeFromShape(outerDimsB);\n  const outShapeOuterDims = broadcast_util_exports.assertAndGetBroadcastShape(a.shape.slice(0, -2), b.shape.slice(0, -2));\n  const outShape = outShapeOuterDims.concat([outerShapeA, outerShapeB]);\n  util_exports.assert(innerShapeA === innerShapeB, () => `Error in matMul: inner shapes (${innerShapeA}) and (${innerShapeB}) of Tensors with shapes ${a.shape} and ${b.shape} and transposeA=${transposeA} and transposeB=${transposeB} must match.`);\n  const a3dShape = transposeA ? [batchDimA, innerShapeA, outerShapeA] : [batchDimA, outerShapeA, innerShapeA];\n  const b3dShape = transposeB ? [batchDimB, outerShapeB, innerShapeB] : [batchDimB, innerShapeB, outerShapeB];\n  const a3d = reshape6({ inputs: { x: a }, backend: backend2, attrs: { shape: a3dShape } });\n  const b3d = reshape6({ inputs: { x: b }, backend: backend2, attrs: { shape: b3dShape } });\n  const intermediates = [a3d, b3d];\n  const batchDim = Math.max(batchDimA, batchDimB);\n  const batchAEqualOne = batchDimA === 1;\n  const batchBEqualOne = batchDimB === 1;\n  const useVec4 = (innerShapeA % 4 === 0 && !transposeA || outerShapeA % 4 === 0 && transposeA) && outerShapeB % 4 === 0 && !transposeB;\n  const inputs = [a3d, b3d];\n  const dimensions = [\n    { type: \"int32\", data: [outerShapeA] },\n    { type: \"int32\", data: [outerShapeB] },\n    { type: \"int32\", data: [innerShapeA] }\n  ];\n  let program;\n  let out;\n  const outputShape = [batchDim, outerShapeA, outerShapeB];\n  let matmulProgramType = env().get(\"WEBGPU_MATMUL_PROGRAM_TYPE\");\n  if (matmulProgramType < 0) {\n    if (outerShapeA * outerShapeB <= 128) {\n      matmulProgramType = MatMulProgramType.MatMulReduceProgram;\n    } else if (batchDim === 1 && outerShapeA <= 128 && outerShapeB <= 48 && innerShapeB >= 2e3) {\n      matmulProgramType = MatMulProgramType.MatMulSplitKProgram;\n    } else if (outerShapeA <= 16 && (outerShapeB <= 512 || innerShapeB >= 2 * outerShapeB) || outerShapeB <= 16 && (outerShapeA <= 512 || innerShapeA >= 2 * outerShapeA)) {\n      matmulProgramType = MatMulProgramType.MatMulSmallOutputSizeProgram;\n    } else if (useVec4) {\n      matmulProgramType = MatMulProgramType.MatMulPackedVec4Program;\n    } else {\n      matmulProgramType = MatMulProgramType.MatMulPackedProgram;\n    }\n  }\n  switch (matmulProgramType) {\n    case MatMulProgramType.MatMulPackedVec4Program:\n      program = new MatMulPackedVec4Program(a3dShape, outputShape, batchAEqualOne, batchBEqualOne, transposeA, bias, activation2, preluActivationWeights);\n      break;\n    case MatMulProgramType.MatMulReduceProgram:\n      program = new MatMulReduceProgram(outputShape, batchAEqualOne, batchBEqualOne, transposeA, transposeB, bias, activation2, preluActivationWeights);\n      break;\n    case MatMulProgramType.MatMulSplitKProgram: {\n      out = fill5({ backend: backend2, attrs: { shape: outputShape, value: 0, dtype: a.dtype } });\n      program = new MatMulSplitKProgram(outputShape, innerShapeB, batchAEqualOne, batchBEqualOne, transposeA, transposeB);\n      if (bias || activation2) {\n        out = backend2.runWebGPUProgram(program, inputs, a.dtype, dimensions, out);\n        const biasActivationProgram = new BiasActivationProgram(out.shape, bias, activation2, preluActivationWeights);\n        let uniformData = null;\n        const activationInputs = [out];\n        if (bias) {\n          activationInputs.push(bias);\n        }\n        if (preluActivationWeights) {\n          activationInputs.push(preluActivationWeights);\n        }\n        if (activation2 === \"leakyrelu\") {\n          uniformData = [{ type: \"float32\", data: [leakyreluAlpha] }];\n          biasActivationProgram.uniforms += \" alpha : f32,\";\n        }\n        const outActivated = backend2.runWebGPUProgram(biasActivationProgram, activationInputs, out.dtype, uniformData);\n        intermediates.push(out);\n        const outReshaped2 = reshape6({ inputs: { x: outActivated }, backend: backend2, attrs: { shape: outShape } });\n        intermediates.push(outActivated);\n        for (const i2 of intermediates) {\n          backend2.disposeData(i2.dataId);\n        }\n        return outReshaped2;\n      }\n      break;\n    }\n    case MatMulProgramType.MatMulSmallOutputSizeProgram:\n      program = new MatMulSmallOutputSizeProgram(a3dShape, b3dShape, outputShape, transposeA, transposeB, bias, activation2, preluActivationWeights);\n      break;\n    case MatMulProgramType.MatMulPackedProgram:\n      program = new MatMulPackedProgram2(a3dShape, outputShape, env().get(\"WEBGPU_MATMUL_WORK_PER_THREAD\"), batchAEqualOne, batchBEqualOne, transposeA, transposeB, bias, activation2, preluActivationWeights);\n      break;\n    default:\n      throw new Error(`Unsupported MatMulProgramType ${matmulProgramType}.`);\n  }\n  if (bias) {\n    inputs.push(bias);\n  }\n  if (preluActivationWeights) {\n    inputs.push(preluActivationWeights);\n  }\n  if (activation2 === \"leakyrelu\") {\n    dimensions.push({ type: \"float32\", data: [leakyreluAlpha] });\n    program.uniforms += \" alpha : f32,\";\n  }\n  out = backend2.runWebGPUProgram(program, inputs, a.dtype, dimensions, out);\n  const outReshaped = reshape6({ inputs: { x: out }, backend: backend2, attrs: { shape: outShape } });\n  intermediates.push(out);\n  for (const i2 of intermediates) {\n    backend2.disposeData(i2.dataId);\n  }\n  return outReshaped;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/_FusedMatMul.js\nfunction _fusedMatMul3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b, bias, preluActivationWeights } = inputs;\n  const { transposeA, transposeB, activation: activation2, leakyreluAlpha } = attrs;\n  return batchMatMulImpl2({\n    a,\n    b,\n    transposeA,\n    transposeB,\n    backend: backend2,\n    bias,\n    preluActivationWeights,\n    leakyreluAlpha,\n    activation: activation2\n  });\n}\nvar _fusedMatMulConfig4 = {\n  kernelName: _FusedMatMul,\n  backendName: \"webgpu\",\n  kernelFunc: _fusedMatMul3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/binary_op_complex_webgpu.js\nvar BinaryOpComplexProgram2 = class {\n  constructor(op2, aShape, bShape) {\n    this.variableNames = [\"AReal\", \"AImag\", \"BReal\", \"BImag\"];\n    this.workGroupSize = [128, 1, 1];\n    this.size = true;\n    this.outputShape = backend_util_exports.assertAndGetBroadcastShape(aShape, bShape);\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = `binaryOpComplex_${op2}`;\n    this.op = op2;\n  }\n  getUserCode() {\n    const opStr = getBinaryOpString(this.op, false);\n    const userCode = `\n      fn binaryOpComplex(\n          areal : f32, aimag : f32, breal : f32, bimag : f32) -> f32 {\n        ${opStr}\n      }\n\n      ${getMainHeaderAndGlobalIndexString()}\n        if(index < uniforms.size) {\n          let areal = getARealByOutputIndex(index);\n          let aimag = getAImagByOutputIndex(index);\n          let breal = getBRealByOutputIndex(index);\n          let bimag = getBImagByOutputIndex(index);\n          setOutputAtIndex(index, binaryOpComplex(areal, aimag, breal, bimag));\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/binary_op_webgpu.js\nvar BinaryOpProgram2 = class {\n  constructor(op2, aShape, bShape) {\n    this.size = true;\n    this.variableNames = [\"A\", \"B\"];\n    this.outputShape = backend_util_exports.assertAndGetBroadcastShape(aShape, bShape);\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.op = op2;\n    this.useSharedMemoryWithA = aShape.length === 1 && bShape.length > 1 && aShape[0] < 1024;\n    this.useSharedMemoryWithB = bShape.length === 1 && aShape.length > 1 && bShape[0] < 1024;\n    if (this.useSharedMemoryWithA || this.useSharedMemoryWithB) {\n      this.isVec4 = false;\n      this.lastDimensionSize = this.useSharedMemoryWithB ? bShape[0] : aShape[0];\n      this.shaderKey = `binary_${this.type}_${op2}_${this.lastDimensionSize}_${this.useSharedMemoryWithB}`;\n      this.type = \"shared\";\n      this.workGroupSize = [256, 1, 1];\n      if (this.lastDimensionSize < 256) {\n        this.workPerThread = 1;\n      } else if (this.lastDimensionSize < 512) {\n        this.workPerThread = 2;\n      } else {\n        this.workPerThread = 4;\n      }\n    } else {\n      if (util_exports.arraysEqual(aShape, bShape) && util_exports.sizeFromShape(aShape) % 4 === 0) {\n        this.isVec4 = true;\n        this.type = \"vec4\";\n        this.workPerThread = 4;\n      } else {\n        this.isVec4 = false;\n        this.type = \"plain\";\n        this.workPerThread = 1;\n      }\n      this.shaderKey = `binary_${this.type}_${op2}`;\n      this.workGroupSize = [128, 1, 1];\n    }\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [this.workPerThread, 1, 1]);\n  }\n  getUserCode() {\n    let userCode;\n    if (this.type === \"shared\") {\n      const sharedIndexSnippet = this.lastDimensionSize > 1 ? `coords[${this.outputShape.length - 1}]` : \"0\";\n      const accessDataSnippet = this.useSharedMemoryWithB ? `let a = getAByOutputCoords(coords);\n          let b = sharedBuf[${sharedIndexSnippet}];` : `let a = sharedBuf[${sharedIndexSnippet}];\n          let b = getBByOutputCoords(coords);`;\n      const opStr = getBinaryOpString(this.op, this.isVec4);\n      userCode = `\n        fn binaryOperation(a : f32, b : f32) -> f32 {\n          ${opStr}\n        }\n        var<workgroup> sharedBuf : array<f32, ${this.lastDimensionSize}>;\n        ${getMainHeaderAndGlobalIndexString()}\n\n          // Fill in the shared memory buffer. Here we need a loop to make sure\n          // that all data in A|B are uploaded when |sharedMemorySize| is larger\n          // than work group size.\n          for(var localIndex = i32(localId.x); localIndex < ${this.lastDimensionSize}; localIndex = localIndex + ${this.workGroupSize[0]}) {\n            sharedBuf[localIndex] = f32(${this.useSharedMemoryWithB ? \"B\" : \"A\"}[localIndex]);\n          }\n          workgroupBarrier();\n\n          for(var i = 0; i < ${this.workPerThread}; i = i + 1) {\n            let flatIndex = index * ${this.workPerThread} + i;\n            if(flatIndex < uniforms.size) {\n              let coords = getCoordsFromIndex(flatIndex);\n\n              ${accessDataSnippet}\n              setOutputAtIndex(flatIndex, binaryOperation(a, b));\n            }\n          }\n        }\n        `;\n    } else {\n      const dType = this.type === \"vec4\" ? \"vec4<f32>\" : \"f32\";\n      const opStr = getBinaryOpString(this.op, this.isVec4);\n      userCode = `\n       fn binaryOperation(a : ${dType}, b : ${dType}) -> ${dType} {\n         ${opStr}\n       }\n       ${getMainHeaderAndGlobalIndexString()}\n         if (index < uniforms.size) {\n           let a = getAByOutputIndex(index);\n           let b = getBByOutputIndex(index);\n           setOutputAtIndex(index, binaryOperation(a, b));\n         }\n       }\n       `;\n    }\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Identity.js\nfunction identity5(args) {\n  const { inputs } = args;\n  const { x } = inputs;\n  args.backend.incRef(x.dataId);\n  return { dataId: x.dataId, shape: x.shape, dtype: x.dtype };\n}\nvar identityConfig4 = {\n  kernelName: Identity,\n  backendName: \"webgpu\",\n  kernelFunc: identity5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Complex.js\nfunction complex4(args) {\n  const { inputs, backend: backend2 } = args;\n  const { real: real5, imag: imag5 } = inputs;\n  const complexInfo = backend2.makeTensorInfo(real5.shape, \"complex64\");\n  const complex5 = backend2.tensorMap.get(complexInfo.dataId);\n  const realTensorInfo = identity5({ inputs: { x: real5 }, backend: backend2 });\n  const imagTensorInfo = identity5({ inputs: { x: imag5 }, backend: backend2 });\n  complex5.complexTensorInfos = { real: realTensorInfo, imag: imagTensorInfo };\n  return complexInfo;\n}\nvar complexConfig3 = {\n  kernelName: Complex,\n  backendName: \"webgpu\",\n  kernelFunc: complex4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/unary_op_webgpu.js\nvar UnaryOpProgram2 = class {\n  constructor(outputShape, op2) {\n    this.variableNames = [\"A\"];\n    this.size = true;\n    const workGroupSizeX = 128;\n    this.workGroupSize = [workGroupSizeX, 1, 1];\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.op = op2;\n    this.shaderKey = `unary_${op2}`;\n  }\n  getUserCode() {\n    return `\n      fn unaryOperation(a : f32) -> f32 {\n        ${getUnaryOpString(this.op, false)}\n      }\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let a = getAByOutputIndex(index);\n          setOutputAtIndex(index, unaryOperation(a));\n        }\n      }\n      `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernel_utils/kernel_funcs_utils.js\nfunction unaryKernelFunc3({ opType, cpuKernelImpl, dtype }) {\n  return ({ inputs, backend: backend2 }) => {\n    const { x } = inputs;\n    const webgpuBackend = backend2;\n    const $dtype = dtype || x.dtype;\n    if (webgpuBackend.shouldExecuteOnCPU([x]) && cpuKernelImpl != null) {\n      const xData = webgpuBackend.tensorMap.get(x.dataId);\n      const outValues = cpuKernelImpl(xData.values, $dtype);\n      return webgpuBackend.makeTensorInfo(x.shape, $dtype, outValues);\n    }\n    const program = new UnaryOpProgram2(x.shape, opType);\n    return webgpuBackend.runWebGPUProgram(program, [x], $dtype);\n  };\n}\nfunction binaryKernelFunc3({ opType, cpuKernelImpl, supportsComplex = false, dtype }) {\n  return ({ inputs, backend: backend2 }) => {\n    const { a, b } = inputs;\n    const webgpuBackend = backend2;\n    if (supportsComplex && a.dtype === \"complex64\") {\n      const aData = webgpuBackend.tensorMap.get(a.dataId);\n      const bData = webgpuBackend.tensorMap.get(b.dataId);\n      let real5, imag5;\n      if (opType !== BinaryOpType.MUL) {\n        [real5, imag5] = [\n          [aData.complexTensorInfos.real, bData.complexTensorInfos.real],\n          [aData.complexTensorInfos.imag, bData.complexTensorInfos.imag]\n        ].map((complexParts) => {\n          const [aPart, bPart] = complexParts;\n          const aHandle = {\n            dataId: aPart.dataId,\n            dtype: aPart.dtype,\n            shape: a.shape\n          };\n          const bHandle = {\n            dataId: bPart.dataId,\n            dtype: bPart.dtype,\n            shape: b.shape\n          };\n          const program2 = new BinaryOpProgram2(opType, a.shape, b.shape);\n          return webgpuBackend.runWebGPUProgram(program2, [aHandle, bHandle], upcastType(aPart.dtype, bPart.dtype));\n        });\n      } else {\n        const realProgram = new BinaryOpComplexProgram2(BinaryOpType.COMPLEX_MULTIPLY_REAL, a.shape, b.shape);\n        const imagProgram = new BinaryOpComplexProgram2(BinaryOpType.COMPLEX_MULTIPLY_IMAG, a.shape, b.shape);\n        const inputs2 = [\n          {\n            dataId: aData.complexTensorInfos.real.dataId,\n            dtype: aData.complexTensorInfos.real.dtype,\n            shape: a.shape\n          },\n          {\n            dataId: aData.complexTensorInfos.imag.dataId,\n            dtype: aData.complexTensorInfos.imag.dtype,\n            shape: a.shape\n          },\n          {\n            dataId: bData.complexTensorInfos.real.dataId,\n            dtype: bData.complexTensorInfos.real.dtype,\n            shape: b.shape\n          },\n          {\n            dataId: bData.complexTensorInfos.imag.dataId,\n            dtype: bData.complexTensorInfos.imag.dtype,\n            shape: b.shape\n          }\n        ];\n        real5 = webgpuBackend.runWebGPUProgram(realProgram, inputs2, \"float32\");\n        imag5 = webgpuBackend.runWebGPUProgram(imagProgram, inputs2, \"float32\");\n      }\n      const complexOutput = complex4({ inputs: { real: real5, imag: imag5 }, backend: webgpuBackend });\n      webgpuBackend.disposeData(real5.dataId);\n      webgpuBackend.disposeData(imag5.dataId);\n      return complexOutput;\n    }\n    const $dtype = dtype || upcastType(a.dtype, b.dtype);\n    if ((a.dtype === \"string\" || b.dtype === \"string\" || webgpuBackend.shouldExecuteOnCPU([a, b])) && cpuKernelImpl != null) {\n      const aData = webgpuBackend.tensorMap.get(a.dataId).values;\n      const bData = webgpuBackend.tensorMap.get(b.dataId).values;\n      const decodedAVals = a.dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(aData) : aData;\n      const decodedBVals = a.dtype === \"string\" ? backend_util_exports.fromUint8ToStringArray(bData) : bData;\n      const [outValues, outShape] = cpuKernelImpl(a.shape, b.shape, decodedAVals, decodedBVals, $dtype);\n      return webgpuBackend.makeTensorInfo(outShape, $dtype, outValues);\n    }\n    const program = new BinaryOpProgram2(opType, a.shape, b.shape);\n    return webgpuBackend.runWebGPUProgram(program, [a, b], $dtype);\n  };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernel_utils/shared.js\nvar { addImpl: addImplCPU2, ceilImpl: ceilImplCPU2, concatImpl: concatImplCPU2, equalImpl: equalImplCPU2, expImpl: expImplCPU2, expm1Impl: expm1ImplCPU2, floorImpl: floorImplCPU2, gatherNdImpl: gatherNdImplCPU2, gatherV2Impl: gatherV2ImplCPU2, greaterEqualImpl: greaterEqualImplCPU2, greaterImpl: greaterImplCPU2, lessEqualImpl: lessEqualImplCPU2, lessImpl: lessImplCPU2, logImpl: logImplCPU2, maxImpl: maxImplCPU2, maximumImpl: maximumImplCPU2, minimumImpl: minimumImplCPU2, multiplyImpl: multiplyImplCPU2, negImpl: negImplCPU2, notEqualImpl: notEqualImplCPU2, prodImpl: prodImplCPU2, rangeImpl: rangeImplCPU2, rsqrtImpl: rsqrtImplCPU2, scatterImpl: scatterImplCPU2, simpleAbsImpl: simpleAbsImplCPU2, sliceImpl: sliceImplCPU2, stridedSliceImpl: stridedSliceImplCPU2, stringNGramsImpl: stringNGramsImplCPU2, subImpl: subImplCPU2, tileImpl: tileImplCPU2, topKImpl: topKImplCPU2, transposeImpl: transposeImplCPU2, uniqueImpl: uniqueImplCPU2 } = shared_exports;\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Abs.js\nvar abs4 = unaryKernelFunc3({ opType: UnaryOpType.ABS, cpuKernelImpl: simpleAbsImplCPU2 });\nvar absConfig4 = {\n  kernelName: Abs,\n  backendName: \"webgpu\",\n  kernelFunc: abs4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Add.js\nvar addKernelFunc2 = binaryKernelFunc3({ opType: BinaryOpType.ADD, cpuKernelImpl: addImplCPU2, supportsComplex: true });\nvar addConfig4 = {\n  kernelName: Add,\n  backendName: \"webgpu\",\n  kernelFunc: addKernelFunc2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/addn_packed_webgpu.js\nvar AddNPackedProgram2 = class {\n  constructor(shapes) {\n    this.workPerThread = 4;\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = shapes[0];\n    this.variableNames = shapes.map((_, i2) => `T${i2}`);\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [this.workPerThread, 1, 1]);\n    this.shaderKey = \"addN\";\n  }\n  getUserCode() {\n    const snippets = [];\n    this.variableNames.forEach((variable2) => {\n      snippets.push(`let v${variable2} = get${variable2}ByOutputCoords(coords);`);\n    });\n    const operation = this.variableNames.map((variable2) => {\n      return `v${variable2}`;\n    }).join(\" + \");\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        for (var i = 0; i < ${this.workPerThread}; i = i + 1) {\n          let flatIndex = index * ${this.workPerThread} + i;\n          if (flatIndex < uniforms.size) {\n            let coords = getCoordsFromIndex(flatIndex);\n            ${snippets.join(\"\\n        \")}\n            setOutputAtIndex(flatIndex, ${operation});\n          }\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/AddN.js\nfunction addN4(args) {\n  const { inputs, backend: backend2 } = args;\n  const tensors = inputs;\n  if (tensors.length === 1) {\n    return identity5({ inputs: { x: tensors[0] }, backend: backend2 });\n  }\n  const dtype = tensors.map((t2) => t2.dtype).reduce((d1, d2) => upcastType(d1, d2));\n  const shapes = tensors.map((t2) => t2.shape);\n  const program = new AddNPackedProgram2(shapes);\n  return backend2.runWebGPUProgram(program, tensors, dtype);\n}\nvar addNConfig4 = {\n  kernelName: AddN,\n  backendName: \"webgpu\",\n  kernelFunc: addN4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/argminmax_webgpu.js\nvar ArgMinMaxProgram2 = class {\n  constructor(inputShape, axis, reduceType) {\n    this.workGroupSize = [64, 1, 1];\n    this.variableNames = [\"x\"];\n    this.uniforms = \"infinityValue : f32,\";\n    this.size = true;\n    const axes = [axis];\n    backend_util_exports.assertAxesAreInnerMostDims(\"arg\" + reduceType.charAt(0).toUpperCase() + reduceType.slice(1), axes, inputShape.length);\n    this.op = reduceType === \"min\" ? \"<\" : \">\";\n    const [outputShape] = backend_util_exports.computeOutAndReduceShapes(inputShape, axes);\n    this.outputShape = outputShape.length === 0 ? [1] : outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, [1, 1, 1]);\n    this.inputShape = inputShape;\n    this.shaderKey = `argMinMax${this.op}`;\n  }\n  getUserCode() {\n    const sharedMemorySnippet = `\n      var<workgroup> xBestIndices : array<i32, ${this.workGroupSize[0]}>;\n      var<workgroup> xBestValues : array<f32, ${this.workGroupSize[0]}>;\n    `;\n    const getInputShapeLastDim = () => {\n      if (this.inputShape.length === 1) {\n        return \"uniforms.xShape\";\n      } else {\n        return `uniforms.xShape.${getCoordsXYZ(this.inputShape.length - 1)}`;\n      }\n    };\n    const splitOutputCoords = () => {\n      let snippet = \"\";\n      if (this.outputShape.length === 1) {\n        if (this.inputShape.length !== 1) {\n          snippet += \"outputCoords,\";\n        }\n      } else {\n        for (let i2 = 0; i2 < this.outputShape.length; i2++) {\n          snippet += `outputCoords.${getCoordsXYZ(i2)},`;\n        }\n      }\n      return snippet;\n    };\n    const userCode = `\n      fn DIV_CEIL(a : u32, b : u32) -> u32 {\n        return ((a - 1u) / b + 1u);\n      }\n\n      ${sharedMemorySnippet}\n\n      ${getMainHeaderAndGlobalIndexString()}\n        let outputIndex = index / i32(workGroupSizeX);\n        let reduceLength = ${getInputShapeLastDim()};\n\n        var bestIndex = i32(localId.x);\n        var bestValue = uniforms.infinityValue;\n        let outputCoords = getCoordsFromIndex(outputIndex);\n        for (var k = i32(localId.x); k < reduceLength && outputIndex < uniforms.size;\n            k = k + i32(workGroupSizeX)) {\n          let candidate = getX(${splitOutputCoords()} k);\n          if (!isnan(candidate) && candidate ${this.op} bestValue) {\n            bestValue = candidate;\n            bestIndex = k;\n          }\n        }\n        xBestValues[localId.x] = bestValue;\n        xBestIndices[localId.x] = bestIndex;\n        workgroupBarrier();\n\n        var reduceSize = min(u32(reduceLength), workGroupSizeX);\n        for (var currentSize = reduceSize / 2u; reduceSize > 1u;\n            currentSize = reduceSize / 2u) {\n          let interval = DIV_CEIL(reduceSize, 2u);\n          if (localId.x < currentSize) {\n            let candidate = xBestValues[localId.x + interval];\n            if (candidate ${this.op} bestValue) {\n              bestValue = candidate;\n              xBestValues[localId.x] = bestValue;\n              xBestIndices[localId.x] = xBestIndices[localId.x + interval];\n            }\n          }\n          reduceSize = interval;\n          workgroupBarrier();\n        }\n\n        if (localId.x == 0u && outputIndex < uniforms.size) {\n          setOutputAtIndexI32(outputIndex, xBestIndices[localId.x]);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/transpose_shared_webgpu.js\nvar TransposeSharedProgram = class {\n  constructor(aShape, newDim) {\n    this.variableNames = [\"A\"];\n    this.workGroupSize = [16, 16, 1];\n    const outputShape = new Array(aShape.length);\n    for (let i2 = 0; i2 < outputShape.length; i2++) {\n      outputShape[i2] = aShape[newDim[i2]];\n    }\n    this.outputShape = outputShape;\n    this.dispatchLayout = { x: [0], y: [1] };\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [1, 1, 1]);\n    this.shaderKey = \"transposeShared\";\n  }\n  getUserCode() {\n    const userCode = `\n      const TILE_DIM = ${this.workGroupSize[0]};\n      var<workgroup> tile : array<array<f32, ${this.workGroupSize[0] + 1}>, ${this.workGroupSize[0]}>;\n      ${getWorkGroupSizeString()}\n      fn main(@builtin(local_invocation_id) localId : vec3<u32>,\n              @builtin(workgroup_id) workgroupId : vec3<u32>) {\n        var x = i32(workgroupId.x) * TILE_DIM + i32(localId.x);\n        var y = i32(workgroupId.y) * TILE_DIM + i32(localId.y);\n        let width = uniforms.outShape[0];\n        let height = uniforms.outShape[1];\n        if (x < width && y < height) {\n          tile[localId.y][localId.x] = A[y * width + x];\n        }\n        workgroupBarrier();\n\n        x = i32(workgroupId.y) * TILE_DIM + i32(localId.x);\n        y = i32(workgroupId.x) * TILE_DIM + i32(localId.y);\n        if (x < height && y < width) {\n          setOutputAtIndex((y * height + x), tile[localId.x]\n            [localId.y]);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/transpose_webgpu.js\nvar TransposeProgram2 = class {\n  constructor(aShape, newDim) {\n    this.variableNames = [\"A\"];\n    this.workPerThread = 4;\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    const outputShape = new Array(aShape.length);\n    for (let i2 = 0; i2 < outputShape.length; i2++) {\n      outputShape[i2] = aShape[newDim[i2]];\n    }\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [this.workPerThread, 1, 1]);\n    this.newDim = newDim;\n    this.shaderKey = `transpose_${newDim}`;\n  }\n  getUserCode() {\n    const dtype = getCoordsDataType2(this.outputShape.length);\n    const switched = getSwitchedCoords2(this.newDim);\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n\n        for(var i = 0; i < ${this.workPerThread}; i = i + 1) {\n          let flatIndex = index * ${this.workPerThread} + i;\n          if(flatIndex < uniforms.size) {\n            let resRC = getCoordsFromIndex(flatIndex);\n            setOutputAtIndex(flatIndex, A[getIndexFromCoords${this.outputShape.length}D(\n              ${dtype}(${switched}), uniforms.aShape)]);\n          }\n        }\n      }\n    `;\n    return userCode;\n  }\n};\nfunction getSwitchedCoords2(newDim) {\n  const rank = newDim.length;\n  if (rank > 6) {\n    throw Error(`Transpose for rank ${rank} is not yet supported`);\n  }\n  const switchedCoords = new Array(rank);\n  for (let i2 = 0; i2 < newDim.length; i2++) {\n    switchedCoords[newDim[i2]] = `resRC.${getCoordsXYZ(i2)}`;\n  }\n  return switchedCoords.join();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Transpose.js\nfunction transpose5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { perm } = attrs;\n  const webgpuBackend = backend2;\n  const xRank = x.shape.length;\n  const newShape = new Array(xRank);\n  for (let i2 = 0; i2 < newShape.length; i2++) {\n    newShape[i2] = x.shape[perm[i2]];\n  }\n  if (backend2.shouldExecuteOnCPU([x])) {\n    const xData = webgpuBackend.tensorMap.get(x.dataId);\n    const values = xData.values;\n    const outValues = transposeImplCPU2(values, x.shape, x.dtype, perm, newShape);\n    return backend2.makeTensorInfo(newShape, x.dtype, outValues);\n  }\n  if (x.shape.length === 2 && util_exports.arraysEqual(perm, [1, 0])) {\n    const program2 = new TransposeSharedProgram(x.shape, perm);\n    return webgpuBackend.runWebGPUProgram(program2, [x], x.dtype);\n  }\n  const program = new TransposeProgram2(x.shape, perm);\n  return webgpuBackend.runWebGPUProgram(program, [x], x.dtype);\n}\nvar transposeConfig4 = {\n  kernelName: Transpose,\n  backendName: \"webgpu\",\n  kernelFunc: transpose5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ArgMax.js\nfunction argMax4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis } = attrs;\n  let axes = util_exports.parseAxisParam(axis, x.shape);\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  const intermediateTensorInfos = [];\n  if (permutedAxes != null) {\n    $x = transpose5({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    intermediateTensorInfos.push($x);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, $x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"argMax\", [axes[0]], $x.shape.length);\n  const program = new ArgMinMaxProgram2($x.shape, axes[0], \"max\");\n  const uniformData = [{ type: \"float32\", data: [Number.NEGATIVE_INFINITY] }];\n  const out = backend2.runWebGPUProgram(program, [$x], \"int32\", uniformData);\n  intermediateTensorInfos.forEach((t2) => backend2.disposeData(t2.dataId));\n  return out;\n}\nvar argMaxConfig4 = {\n  kernelName: ArgMax,\n  backendName: \"webgpu\",\n  kernelFunc: argMax4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ArgMin.js\nfunction argMin4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis } = attrs;\n  let axes = util_exports.parseAxisParam(axis, x.shape);\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, x.shape.length);\n  let $x = x;\n  const intermediateTensorInfos = [];\n  if (permutedAxes != null) {\n    $x = transpose5({ inputs: { x }, backend: backend2, attrs: { perm: permutedAxes } });\n    intermediateTensorInfos.push($x);\n    axes = backend_util_exports.getInnerMostAxes(axes.length, $x.shape.length);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(\"argMin\", [axes[0]], $x.shape.length);\n  const program = new ArgMinMaxProgram2($x.shape, axes[0], \"min\");\n  const uniformData = [{ type: \"float32\", data: [Number.POSITIVE_INFINITY] }];\n  const out = backend2.runWebGPUProgram(program, [$x], \"int32\", uniformData);\n  intermediateTensorInfos.forEach((t2) => backend2.disposeData(t2.dataId));\n  return out;\n}\nvar argMinConfig3 = {\n  kernelName: ArgMin,\n  backendName: \"webgpu\",\n  kernelFunc: argMin4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/pool2d_webgpu.js\nvar Pool2DProgram2 = class {\n  constructor(convInfo, poolType) {\n    this.variableNames = [\"x\"];\n    this.uniforms = `stride : vec2<i32>, pad : vec2<i32>, dilation : vec2<i32>, convDims : vec2<i32>, filterDims : vec2<i32>,`;\n    this.workGroupSize = [128, 1, 1];\n    this.size = true;\n    this.outputShape = convInfo.outShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = `pool2D_${poolType}`;\n    this.poolType = poolType;\n  }\n  getUserCode() {\n    let updateSnippet = `resultValue = max(value, resultValue);`;\n    if (this.poolType === \"avg\") {\n      updateSnippet = `resultValue = resultValue + value; count = count + 1.0;`;\n    }\n    let returnValue = `resultValue`;\n    if (this.poolType === \"avg\") {\n      returnValue = `resultValue / count`;\n    }\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n      if (index < uniforms.size) {\n        let coords = getCoordsFromIndex(index);\n          let batch = coords[0];\n          let xRCCorner = vec2<i32>(coords.yz) * uniforms.stride - uniforms.pad;\n          let xRCorner = xRCCorner.x;\n          let xCCorner = xRCCorner.y;\n\n          var resultValue = ${this.poolType === \"avg\" ? \"0.0\" : \"-1.0 / pow(10.0, -20.0)\"};\n          var count = 0.0;\n\n          for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + uniforms.dilation.x) {\n            let xR = xRCorner + wR;\n\n            if (xR < 0 || xR >= uniforms.convDims.x) {\n              continue;\n            }\n\n            for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + uniforms.dilation.y) {\n              let xC = xCCorner + wC;\n              if (xC < 0 || xC >= uniforms.convDims.y) {\n                continue;\n              }\n\n              let value = getX(batch, xR, xC, coords[3]);\n              ${updateSnippet}\n            }\n          }\n\n          setOutputAtIndex(index, ${returnValue});\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/pool_filtersizeone_webgpu.js\nvar PoolWithFilterSizeEqualsOneProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"x\"];\n    this.uniforms = `stride : vec2<i32>,`;\n    this.workGroupSize = [256, 1, 1];\n    this.size = true;\n    this.outputShape = convInfo.outShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = \"poolWithFilterSizeEqualsOne\";\n  }\n  getUserCode() {\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let coords = getCoordsFromIndex(index);\n          let batch = coords[0];\n          let d = coords[3];\n\n          let xRCCorner = coords.yz * uniforms.stride;\n          let xRCorner = xRCCorner.x;\n          let xCCorner = xRCCorner.y;\n\n          let value = getX(batch, xRCorner, xCCorner, d);\n          setOutputAtIndex(index, value);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/AvgPool.js\nfunction avgPool5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = 1;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  if (convInfo.filterWidth === 1 && convInfo.filterHeight === 1 && util_exports.arraysEqual(convInfo.inShape, convInfo.outShape)) {\n    return identity5({ inputs: { x }, backend: backend2 });\n  }\n  let program;\n  const dimensions = [{ type: \"int32\", data: [convInfo.strideHeight, convInfo.strideWidth] }];\n  if (convInfo.filterHeight === 1 && convInfo.filterWidth === 1) {\n    program = new PoolWithFilterSizeEqualsOneProgram(convInfo);\n  } else {\n    program = new Pool2DProgram2(convInfo, \"avg\");\n    dimensions.push({ type: \"int32\", data: [convInfo.padInfo.top, convInfo.padInfo.left] }, {\n      type: \"int32\",\n      data: [convInfo.dilationHeight, convInfo.dilationWidth]\n    }, { type: \"int32\", data: [convInfo.inHeight, convInfo.inWidth] }, {\n      type: \"int32\",\n      data: [convInfo.effectiveFilterHeight, convInfo.effectiveFilterWidth]\n    });\n  }\n  return backend2.runWebGPUProgram(program, [x], x.dtype, dimensions);\n}\nvar avgPoolConfig4 = {\n  kernelName: AvgPool,\n  backendName: \"webgpu\",\n  kernelFunc: avgPool5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/BatchMatMul.js\nfunction batchMatMul4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { a, b } = inputs;\n  const { transposeA, transposeB } = attrs;\n  return batchMatMulImpl2({ a, b, transposeA, transposeB, backend: backend2 });\n}\nvar batchMatMulConfig4 = {\n  kernelName: BatchMatMul,\n  backendName: \"webgpu\",\n  kernelFunc: batchMatMul4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/slice_webgpu.js\nvar SliceProgram2 = class {\n  constructor(start, destSize) {\n    this.variableNames = [\"source\"];\n    this.workPerThread = 1;\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = destSize;\n    this.rank = destSize.length;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [this.workPerThread, 1, 1]);\n    this.start = start;\n    this.uniforms = `start : ${getCoordsDataType2(start.length)}, `;\n    this.shaderKey = \"slice\";\n  }\n  getUserCode() {\n    const dtype = getCoordsDataType2(this.rank);\n    const sourceCoords = getCoords3(this.rank);\n    let coordSum;\n    if (this.start.length === 1) {\n      coordSum = this.outputShape.map((_, i2) => {\n        return `sourceLoc = uniforms.start + coords;`;\n      });\n    } else {\n      coordSum = this.outputShape.map((_, i2) => {\n        return `sourceLoc.${coords2[i2]} = uniforms.start[${i2}] + coords.${coords2[i2]};`;\n      });\n    }\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          var sourceLoc : ${dtype};\n          let coords = getCoordsFromIndex(index);\n          ${coordSum.join(\"\\n\")}\n          setOutputAtIndex(index, getSource(${sourceCoords}));\n        }\n      }\n    `;\n    return userCode;\n  }\n};\nvar coords2 = [\"x\", \"y\", \"z\", \"w\", \"u\", \"v\"];\nfunction getCoords3(rank) {\n  if (rank === 1) {\n    return \"sourceLoc\";\n  } else if (rank <= 6) {\n    return coords2.slice(0, rank).map((coord) => `sourceLoc.${coord}`).join(\",\");\n  } else {\n    throw Error(`Slicing for rank ${rank} is not yet supported`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Slice.js\nfunction slice5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { begin, size } = attrs;\n  const [$begin, $size] = slice_util_exports.parseSliceParams(x, begin, size);\n  slice_util_exports.assertParamsValid(x, $begin, $size);\n  if (backend2.shouldExecuteOnCPU([x]) || x.dtype === \"string\") {\n    const xBufferInfo = backend2.tensorMap.get(x.dataId);\n    const outValues = sliceImplCPU2(xBufferInfo.values, $begin, $size, x.shape, x.dtype);\n    return backend2.makeTensorInfo($size, x.dtype, outValues);\n  }\n  if (util_exports.sizeFromShape($size) === 0) {\n    return backend2.makeTensorInfo($size, x.dtype, []);\n  }\n  const program = new SliceProgram2($begin, $size);\n  const uniformData = [{ type: \"int32\", data: $begin }];\n  return backend2.runWebGPUProgram(program, [x], x.dtype, uniformData);\n}\nvar sliceConfig4 = {\n  kernelName: Slice,\n  backendName: \"webgpu\",\n  kernelFunc: slice5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/BatchToSpaceND.js\nvar batchToSpaceND5 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, crops } = attrs;\n  util_exports.assert(x.shape.length <= 4, () => \"batchToSpaceND for rank > 4 with a WebGPU backend not implemented yet\");\n  const prod6 = blockShape.reduce((a, b) => a * b);\n  const reshaped = backend_util_exports.getReshaped(x.shape, blockShape, prod6);\n  const permuted = backend_util_exports.getPermuted(reshaped.length, blockShape.length);\n  const reshapedPermuted = backend_util_exports.getReshapedPermuted(x.shape, blockShape, prod6);\n  const sliceBeginCoords = backend_util_exports.getSliceBeginCoords(crops, blockShape.length);\n  const sliceSize = backend_util_exports.getSliceSize(reshapedPermuted, crops, blockShape.length);\n  const toDispose = [];\n  const reshapedIntermediate = reshape6({ inputs: { x }, backend: backend2, attrs: { shape: reshaped } });\n  const transposedIntermediate = transpose5({ inputs: { x: reshapedIntermediate }, backend: backend2, attrs: { perm: permuted } });\n  const reshapedIntermediate2 = reshape6({\n    inputs: { x: transposedIntermediate },\n    backend: backend2,\n    attrs: { shape: reshapedPermuted }\n  });\n  const sliced = slice5({\n    inputs: { x: reshapedIntermediate2 },\n    backend: backend2,\n    attrs: { begin: sliceBeginCoords, size: sliceSize }\n  });\n  toDispose.push(reshapedIntermediate);\n  toDispose.push(transposedIntermediate);\n  toDispose.push(reshapedIntermediate2);\n  toDispose.forEach((t2) => backend2.disposeData(t2.dataId));\n  return sliced;\n};\nvar batchToSpaceNDConfig4 = {\n  kernelName: BatchToSpaceND,\n  backendName: \"webgpu\",\n  kernelFunc: batchToSpaceND5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/NotEqual.js\nvar notEqual4 = binaryKernelFunc3({\n  opType: BinaryOpType.NOT_EQUAL,\n  dtype: \"bool\",\n  cpuKernelImpl: notEqualImplCPU2\n});\nvar notEqualConfig4 = {\n  kernelName: NotEqual,\n  backendName: \"webgpu\",\n  kernelFunc: notEqual4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Real.js\nfunction real4(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const inputData = backend2.tensorMap.get(input2.dataId);\n  return identity5({ inputs: { x: inputData.complexTensorInfos.real }, backend: backend2 });\n}\nvar realConfig3 = {\n  kernelName: Real,\n  backendName: \"webgpu\",\n  kernelFunc: real4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernel_utils/int.js\nfunction int2(input2, backend2) {\n  const program = new UnaryOpProgram2(input2.shape, UnaryOpType.TO_INT);\n  const output = backend2.runWebGPUProgram(program, [input2], \"int32\");\n  return { dataId: output.dataId, shape: output.shape, dtype: output.dtype };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Cast.js\nfunction cast6(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { dtype } = attrs;\n  if (dtype === \"complex64\") {\n    if (x.dtype === \"complex64\") {\n      return identity5({ inputs: { x }, backend: backend2 });\n    }\n    const zerosTensor = zeros(x.shape);\n    const floatX = cast6({ inputs: { x }, backend: backend2, attrs: { dtype: \"float32\" } });\n    const result = complex4({ inputs: { real: floatX, imag: zerosTensor }, backend: backend2 });\n    zerosTensor.dispose();\n    backend2.disposeData(floatX.dataId);\n    return result;\n  }\n  if (x.dtype === \"complex64\") {\n    const realPart = real4({ inputs: { input: x }, backend: backend2 });\n    const result = cast6({ inputs: { x: realPart }, backend: backend2, attrs: { dtype } });\n    backend2.disposeData(realPart.dataId);\n    return result;\n  }\n  if (!util_exports.hasEncodingLoss(x.dtype, dtype)) {\n    const result = identity5({ inputs: { x }, backend: backend2 });\n    return { dataId: result.dataId, shape: result.shape, dtype };\n  }\n  if (dtype === \"int32\") {\n    return int2(x, backend2);\n  }\n  if (dtype === \"bool\") {\n    const zerosTensorInfo = backend2.makeTensorInfo([], \"bool\", util_exports.getTypedArrayFromDType(\"bool\", 1));\n    const binaryInputs = { a: x, b: zerosTensorInfo };\n    const result = notEqual4({ inputs: binaryInputs, backend: backend2 });\n    backend2.disposeData(zerosTensorInfo.dataId);\n    return result;\n  }\n  throw new Error(`Error in Cast: failed to cast ${x.dtype} to ${dtype}`);\n}\nvar castConfig4 = {\n  kernelName: Cast,\n  backendName: \"webgpu\",\n  kernelFunc: cast6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Ceil.js\nvar ceil4 = unaryKernelFunc3({ opType: UnaryOpType.CEIL, cpuKernelImpl: ceilImplCPU2 });\nvar ceilConfig4 = {\n  kernelName: Ceil,\n  backendName: \"webgpu\",\n  kernelFunc: ceil4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/clip_vec4_webgpu.js\nvar ClipVec4Program = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.uniforms = \"minVal : f32, maxVal : f32,\";\n    this.workPerThread = 4;\n    this.workGroupSize = [64, 1, 1];\n    this.isVec4 = true;\n    this.size = true;\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [this.workPerThread, 1, 1]);\n    this.shaderKey = \"clipVec4\";\n  }\n  getUserCode() {\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if(index < uniforms.size) {\n          let value = getAByOutputIndex(index);\n          var clampedValue : vec4<f32>;\n          for (var i = 0; i < 4; i = i + 1) {\n            if (isnan(value[i])) {\n              clampedValue[i] = value[i];\n            } else {\n              clampedValue[i] = clamp(value[i], uniforms.minVal, uniforms.maxVal);\n            }\n          }\n\n          setOutputAtIndex(index, clampedValue);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/clip_webgpu.js\nvar ClipProgram2 = class {\n  constructor(outputShape) {\n    this.variableNames = [\"A\"];\n    this.uniforms = \"minVal : f32, maxVal : f32,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = \"clip\";\n  }\n  getUserCode() {\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if(index < uniforms.size) {\n          let value = getAByOutputIndex(index);\n          if (isnan(value)) {\n            setOutputAtIndex(index, value);\n            return;\n          }\n          setOutputAtIndex(index, clamp(value, uniforms.minVal, uniforms.maxVal));\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ClipByValue.js\nfunction clipByValue4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { clipValueMin, clipValueMax } = attrs;\n  let program;\n  const uniformData = [\n    { type: \"float32\", data: [clipValueMin] },\n    { type: \"float32\", data: [clipValueMax] }\n  ];\n  if (util_exports.sizeFromShape(x.shape) % 4 === 0) {\n    program = new ClipVec4Program(x.shape);\n  } else {\n    program = new ClipProgram2(x.shape);\n  }\n  return backend2.runWebGPUProgram(program, [x], x.dtype, uniformData);\n}\nvar clipByValueConfig4 = {\n  kernelName: ClipByValue,\n  backendName: \"webgpu\",\n  kernelFunc: clipByValue4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/concat_webgpu.js\nvar ConcatProgram2 = class {\n  constructor(shapes) {\n    this.uniforms = \"\";\n    this.workPerThread = 4;\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = backend_util_exports.computeOutShape(shapes, 1);\n    this.variableNames = shapes.map((_, i2) => `T${i2}`);\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [this.workPerThread, 1, 1]);\n    this.offsetLength = shapes.length - 1;\n    for (let i2 = 0; i2 < this.offsetLength; i2++) {\n      this.uniforms += `offset${i2} : i32,`;\n    }\n    this.shaderKey = \"concat\";\n  }\n  getUserCode() {\n    const snippets = [];\n    if (this.offsetLength > 0) {\n      snippets.push(`if (yC < uniforms.offset0){ setOutputAtCoords(coords.x, coords.y, getT0(yR, yC)); }`);\n      for (let i2 = 1; i2 < this.offsetLength; i2++) {\n        snippets.push(`else if (yC < uniforms.offset${[i2]}){ setOutputAtCoords(coords.x, coords.y, getT${i2}(yR, yC - uniforms.offset${i2 - 1})); }`);\n      }\n      const lastIndex = this.offsetLength;\n      const lastShiftIndex = this.offsetLength - 1;\n      snippets.push(`else { setOutputAtCoords(coords.x, coords.y, getT${lastIndex}(yR, yC - uniforms.offset${lastShiftIndex})); }`);\n    } else {\n      snippets.push(`setOutputAtCoords(coords.x, coords.y, getT0(yR, yC));`);\n    }\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        for(var i = 0; i < ${this.workPerThread}; i = i + 1) {\n          let flatIndex = index * ${this.workPerThread} + i;\n          if(flatIndex < uniforms.size) {\n            let coords = getCoordsFromIndex(flatIndex);\n            let yR = coords.x;\n            let yC = coords.y;\n\n            ${snippets.join(\"\\n        \")}\n          }\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Imag.js\nfunction imag4(args) {\n  const { inputs, backend: backend2 } = args;\n  const { input: input2 } = inputs;\n  const inputData = backend2.tensorMap.get(input2.dataId);\n  return identity5({ inputs: { x: inputData.complexTensorInfos.imag }, backend: backend2 });\n}\nvar imagConfig3 = {\n  kernelName: Imag,\n  backendName: \"webgpu\",\n  kernelFunc: imag4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Concat_impl.js\nfunction concatImpl3(inputs, axis, backend2) {\n  const dtype = inputs[0].dtype;\n  if (dtype === \"complex64\") {\n    const reals = inputs.map((t2) => real4({ inputs: { input: t2 }, backend: backend2 }));\n    const imags = inputs.map((t2) => imag4({ inputs: { input: t2 }, backend: backend2 }));\n    const realConcated = concatImpl3(reals, axis, backend2);\n    const imagConcated = concatImpl3(imags, axis, backend2);\n    const result = complex4({ inputs: { real: realConcated, imag: imagConcated }, backend: backend2 });\n    reals.forEach((r2) => backend2.disposeData(r2.dataId));\n    imags.forEach((i2) => backend2.disposeData(i2.dataId));\n    backend2.disposeData(realConcated.dataId);\n    backend2.disposeData(imagConcated.dataId);\n    return result;\n  }\n  let runOnCpu = backend2.shouldExecuteOnCPU(inputs);\n  if (dtype === \"string\") {\n    runOnCpu = true;\n  }\n  if (runOnCpu) {\n    const tensors2D2 = inputs.map((t2) => {\n      const innerSize = util_exports.sizeFromShape(t2.shape.slice(axis));\n      const shape = [-1, innerSize];\n      return reshape6({ inputs: { x: t2 }, backend: backend2, attrs: { shape } });\n    });\n    const inputsValShapes = tensors2D2.map((t2) => {\n      return { vals: backend2.readSync(t2.dataId), shape: t2.shape };\n    });\n    const outShape2 = backend_util_exports.computeOutShape(tensors2D2.map((t2) => t2.shape), 1);\n    const simplyConcat = tensors2D2[0].shape[0] === 1;\n    const outVals = concatImplCPU2(inputsValShapes, outShape2, dtype, simplyConcat);\n    const finalOutShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), axis);\n    const outInfo = backend2.makeTensorInfo(finalOutShape, dtype, outVals);\n    tensors2D2.forEach((t2) => backend2.disposeData(t2.dataId));\n    return outInfo;\n  }\n  const maxInputNum = backend2.device.limits.maxStorageBuffersPerShaderStage - 1;\n  if (inputs.length > maxInputNum) {\n    const reducedInputs = [];\n    for (let i2 = 0; i2 < inputs.length; i2 += maxInputNum) {\n      const subArray = inputs.slice(i2, i2 + maxInputNum);\n      reducedInputs.push(concatImpl3(subArray, axis, backend2));\n    }\n    const result = concatImpl3(reducedInputs, axis, backend2);\n    for (const i2 of reducedInputs) {\n      backend2.disposeData(i2.dataId);\n    }\n    return result;\n  }\n  const { tensors2D, outShape } = computeTensors2D2(inputs, axis, backend2);\n  const shapes = tensors2D.map((t2) => t2.shape);\n  const program = new ConcatProgram2(shapes);\n  const uniformData = [];\n  const offsets = new Array(shapes.length - 1);\n  if (offsets.length > 0) {\n    offsets[0] = shapes[0][1];\n    uniformData.push({ type: \"int32\", data: [offsets[0]] });\n    for (let i2 = 1; i2 < offsets.length; i2++) {\n      offsets[i2] = offsets[i2 - 1] + shapes[i2][1];\n      uniformData.push({ type: \"int32\", data: [offsets[i2]] });\n    }\n  }\n  const res = backend2.runWebGPUProgram(program, tensors2D, tensors2D[0].dtype, uniformData);\n  tensors2D.forEach((r2) => backend2.disposeData(r2.dataId));\n  const reshapedResult = reshape6({ inputs: { x: res }, backend: backend2, attrs: { shape: outShape } });\n  backend2.disposeData(res.dataId);\n  return reshapedResult;\n}\nfunction computeTensors2D2(inputs, axis, backend2) {\n  const outShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), axis);\n  const tensors2D = inputs.map((t2) => reshape6({\n    inputs: { x: t2 },\n    backend: backend2,\n    attrs: {\n      shape: [\n        util_exports.sizeFromShape(t2.shape.slice(0, axis)),\n        util_exports.sizeFromShape(t2.shape.slice(axis))\n      ]\n    }\n  }));\n  return { tensors2D, outShape };\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Concat.js\nfunction concat5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { axis } = attrs;\n  const $axis = util_exports.parseAxisParam(axis, inputs[0].shape)[0];\n  const outShape = backend_util_exports.computeOutShape(inputs.map((t2) => t2.shape), $axis);\n  if (util_exports.sizeFromShape(outShape) === 0) {\n    return backend2.makeTensorInfo(outShape, inputs[0].dtype, []);\n  }\n  const $inputs = inputs.filter((t2) => util_exports.sizeFromShape(t2.shape) > 0);\n  if ($inputs.length === 1) {\n    return identity5({ inputs: { x: $inputs[0] }, backend: backend2 });\n  }\n  const shapes = $inputs.map((t2) => t2.shape);\n  backend_util_exports.assertParamsConsistent(shapes, $axis);\n  return concatImpl3($inputs, $axis, backend2);\n}\nvar concatConfig4 = {\n  kernelName: Concat,\n  backendName: \"webgpu\",\n  kernelFunc: concat5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/conv2d_mm_webgpu.js\nfunction conv2dCommonSnippet(isChannelsLast, fitAOuter, fitBOuter, fitInner, addBias = false, activation2 = null, hasPreluActivationWeights = false, innerElementSizeX = 4, innerElementSizeW = 4, innerElementSize = 4) {\n  const getXSnippet = (innerElementSize2) => {\n    switch (innerElementSize2) {\n      case 1:\n        return \"resData = x[xIndex];\";\n      case 3:\n        return \"resData = vec3<f32>(x[xIndex], x[xIndex + 1], x[xIndex + 2]);\";\n      case 4:\n        return \"resData = x[xIndex / 4];\";\n      default:\n        throw new Error(`innerElementSize ${innerElementSize2} is not supported.`);\n    }\n  };\n  const getWSnippet = (innerElementSize2) => {\n    switch (innerElementSize2) {\n      case 1:\n        return \"return W[row * uniforms.wShape[3] + colIn];\";\n      case 4:\n        return \"return W[row * uniforms.wShape[3] / 4 + colIn];\";\n      default:\n        throw new Error(`innerElementSize ${innerElementSize2} is not supported.`);\n    }\n  };\n  const coordASnippet = isChannelsLast ? `\n      let coord = vec4<i32>(batch, xRow, xCol, xCh);\n      ` : `\n      let coord = vec4<i32>(batch, xCh, xRow, xCol);\n      `;\n  const coordResSnippet = isChannelsLast ? `\n      let coords = vec4<i32>(\n        batch,\n        row / outWidth,\n        row % outWidth,\n        col);\n      ` : `\n      let coords = vec4<i32>(\n        batch,\n        row,\n        col / outWidth,\n        col % outWidth);\n      `;\n  const xHight = isChannelsLast ? \"uniforms.xShape[1]\" : \"uniforms.xShape[2]\";\n  const xWidth = isChannelsLast ? \"uniforms.xShape[2]\" : \"uniforms.xShape[3]\";\n  const row = isChannelsLast ? \"row\" : \"col\";\n  const col = isChannelsLast ? \"col\" : \"row\";\n  const readXSnippet = `\n      let inChannels = uniforms.wShape[2];\n      let outWidth = ${isChannelsLast ? \"uniforms.outShape[2]\" : \"uniforms.outShape[3]\"};\n      let outRow = ${row} / outWidth;\n      let outCol = ${row} % outWidth;\n\n      let WRow = ${col} / (uniforms.filterDims[1] * inChannels);\n      let WCol = ${col} / inChannels % uniforms.filterDims[1];\n      let xRow = outRow * uniforms.stride[0] + uniforms.dilation[0] * WRow - uniforms.pad[0];\n      let xCol = outCol * uniforms.stride[1] + uniforms.dilation[1] * WCol - uniforms.pad[1];\n      let xCh = ${col} % inChannels;\n      var resData = ${typeSnippet(innerElementSizeX)}(0.0);\n      // The bounds checking is always needed since we use it to pad zero for\n      // the 'same' padding type.\n      if (xRow >= 0 && xRow < ${xHight} && xCol >= 0 && xCol < ${xWidth}) {\n        ${coordASnippet}\n        let xIndex = getIndexFromCoords4D(coord, uniforms.xShape);\n        ${getXSnippet(innerElementSizeX)}\n      }\n      return resData;`;\n  const sampleX = isChannelsLast ? fitAOuter && fitInner ? `\n      let col = colIn * ${innerElementSizeX};\n      ${readXSnippet}` : `\n      let col = colIn * ${innerElementSizeX};\n      if (row < uniforms.dimAOuter && col < uniforms.dimInner) {\n        ${readXSnippet}\n      }\n      return ${typeSnippet(innerElementSizeX)}(0.0);` : fitInner && fitBOuter ? `\n      let col = colIn * ${innerElementSizeX};\n      ${readXSnippet}` : `\n      let col = colIn * ${innerElementSizeX};\n      if (row < uniforms.dimInner && col < uniforms.dimBOuter) {\n        ${readXSnippet}\n      }\n      return ${typeSnippet(innerElementSizeX)}(0.0);`;\n  const sampleW = `${getWSnippet(innerElementSizeW)}`;\n  const resType = typeSnippet(innerElementSize);\n  const aType = isChannelsLast ? typeSnippet(innerElementSizeX) : typeSnippet(innerElementSizeW);\n  const bType = isChannelsLast ? typeSnippet(innerElementSizeW) : typeSnippet(innerElementSizeX);\n  const userCode = `\n      ${activationFnSnippet(activation2, hasPreluActivationWeights, innerElementSize === 4, 4)}\n      fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${aType} {\n        ${isChannelsLast ? sampleX : sampleW}\n      }\n\n      fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${bType} {\n        ${isChannelsLast ? sampleW : sampleX}\n      }\n\n      fn mm_write(batch: i32, row : i32, colIn : i32, valueIn : ${resType}) {\n        let col = colIn * ${innerElementSize};\n        if (row < uniforms.dimAOuter && col < uniforms.dimBOuter)\n        {\n        var value = valueIn;\n        let outWidth = ${isChannelsLast ? \"uniforms.outShape[2]\" : \"uniforms.outShape[3]\"};\n        ${coordResSnippet}\n        ${biasActivationSnippet(addBias, activation2)}\n        setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);\n        }\n      }`;\n  return userCode;\n}\nvar Conv2DMMProgram = class {\n  constructor(convInfo, dimAOuter, dimBOuter, dimInner, addBias = false, activation2 = null, hasPreluActivationWeights = false) {\n    this.variableNames = [\"x\", \"W\"];\n    this.uniforms = `filterDims : vec2<i32>, pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,`;\n    this.outputShape = convInfo.outShape;\n    this.isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n    this.isVec4 = ((convInfo.inChannels % 4 === 0 || convInfo.inChannels % 3 === 0) && this.isChannelsLast || convInfo.outWidth % 4 === 0 && !this.isChannelsLast) && convInfo.outChannels % 4 === 0;\n    this.dispatchLayout = this.isChannelsLast ? { x: [3], y: [1, 2], z: [0] } : { x: [2, 3], y: [1], z: [0] };\n    this.workGroupSize = computeWorkGroupSizeForConv2d(this.dispatchLayout, this.outputShape, this.isVec4);\n    this.elementsPerThread = computeWorkPerThreadForConv2d(this.dispatchLayout, this.outputShape, this.isVec4);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, this.elementsPerThread);\n    if (this.isVec4) {\n      if (this.isChannelsLast && convInfo.inChannels % 4 !== 0) {\n        this.innerElementSize = 3;\n        this.variableTypes = [\"f32\", \"vec4<f32>\"];\n      } else {\n        this.innerElementSize = 4;\n        this.variableTypes = [\"vec4<f32>\", \"vec4<f32>\"];\n      }\n      if (addBias) {\n        this.variableNames.push(\"bias\");\n        this.variableTypes.push(\"vec4<f32>\");\n      }\n      if (hasPreluActivationWeights) {\n        this.variableNames.push(\"preluActivationWeights\");\n        this.variableTypes.push(\"vec4<f32>\");\n      }\n    } else {\n      this.innerElementSize = this.elementsPerThread[0];\n      if (addBias) {\n        this.variableNames.push(\"bias\");\n      }\n      if (hasPreluActivationWeights) {\n        this.variableNames.push(\"preluActivationWeights\");\n      }\n    }\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivationWeights = hasPreluActivationWeights;\n    this.tileAOuter = this.workGroupSize[1] * this.elementsPerThread[1];\n    this.tileBOuter = this.workGroupSize[0] * this.elementsPerThread[0];\n    this.tileInner = Math.max(this.workGroupSize[0] * this.innerElementSize, this.workGroupSize[1]);\n    this.fitAOuter = dimAOuter % this.tileAOuter === 0;\n    this.fitBOuter = dimBOuter % this.tileBOuter === 0;\n    this.fitInner = dimInner % this.tileInner === 0;\n    this.shaderKey = `conv2DMM_${this.elementsPerThread}_${this.activation}}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.innerElementSize}_${this.isChannelsLast}`;\n  }\n  getUserCode() {\n    const matMulSource = this.isVec4 ? makeMatMulPackedVec4Source(this.elementsPerThread, this.tileAOuter, this.tileBOuter, this.tileInner, this.innerElementSize, !this.isChannelsLast) : makeMatMulPackedSource(this.elementsPerThread, this.workGroupSize, !this.isChannelsLast, this.tileInner);\n    const elementsSize = this.isVec4 ? [this.isChannelsLast ? this.innerElementSize : 4, 4, 4] : [1, 1, 1];\n    const userCode = `\n    ${conv2dCommonSnippet(this.isChannelsLast, this.fitAOuter, this.fitBOuter, this.fitInner, this.addBias, this.activation, this.hasPreluActivationWeights, elementsSize[0], elementsSize[1], elementsSize[2])}\n    ${matMulSource}\n  `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Conv2D_impl.js\nfunction getShapeForBatchMatMul2(shape, isChannelsLast) {\n  const length = shape.length;\n  if (length >= 3) {\n    return isChannelsLast ? [\n      ...shape.slice(0, -3),\n      shape[length - 3] * shape[length - 2],\n      shape[length - 1]\n    ] : [\n      ...shape.slice(0, -3),\n      shape[length - 3],\n      shape[length - 2] * shape[length - 1]\n    ];\n  } else if (!isChannelsLast && length === 1 && shape[0] > 1) {\n    return [shape[0], 1];\n  } else {\n    return null;\n  }\n}\nfunction conv2dByMatMul2({ x, filter, convInfo, backend: backend2, bias = null, preluActivationWeights = null, leakyreluAlpha = 0, activation: activation2 = null }) {\n  const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n  const transposeA = isChannelsLast ? false : true;\n  const transposeB = false;\n  const sameSize = isChannelsLast && convInfo.filterHeight === convInfo.inHeight && convInfo.filterWidth === convInfo.inWidth && convInfo.padInfo.type === \"VALID\";\n  const intermediates = [];\n  let xReshaped;\n  let filterReshaped;\n  if (sameSize) {\n    const sharedDim = convInfo.inHeight * convInfo.inWidth * convInfo.inChannels;\n    xReshaped = reshape6({\n      inputs: { x },\n      backend: backend2,\n      attrs: { shape: [1, convInfo.batchSize, sharedDim] }\n    });\n    filterReshaped = reshape6({\n      inputs: { x: filter },\n      backend: backend2,\n      attrs: { shape: [1, sharedDim, convInfo.outChannels] }\n    });\n  } else {\n    xReshaped = reshape6({\n      inputs: { x },\n      backend: backend2,\n      attrs: {\n        shape: isChannelsLast ? [\n          convInfo.batchSize,\n          convInfo.inHeight * convInfo.inWidth,\n          convInfo.inChannels\n        ] : [\n          convInfo.batchSize,\n          convInfo.inChannels,\n          convInfo.inHeight * convInfo.inWidth\n        ]\n      }\n    });\n    filterReshaped = reshape6({\n      inputs: { x: filter },\n      backend: backend2,\n      attrs: { shape: [1, convInfo.inChannels, convInfo.outChannels] }\n    });\n  }\n  intermediates.push(xReshaped);\n  intermediates.push(filterReshaped);\n  if (preluActivationWeights != null) {\n    const targetShape = getShapeForBatchMatMul2(preluActivationWeights.shape, isChannelsLast);\n    if (targetShape != null) {\n      preluActivationWeights = reshape6({\n        inputs: { x: preluActivationWeights },\n        backend: backend2,\n        attrs: { shape: targetShape }\n      });\n      intermediates.push(preluActivationWeights);\n    }\n  }\n  if (bias != null) {\n    const targetShape = getShapeForBatchMatMul2(bias.shape, isChannelsLast);\n    if (targetShape != null) {\n      bias = reshape6({ inputs: { x: bias }, backend: backend2, attrs: { shape: targetShape } });\n      intermediates.push(bias);\n    }\n  }\n  const result = batchMatMulImpl2({\n    a: isChannelsLast ? xReshaped : filterReshaped,\n    b: isChannelsLast ? filterReshaped : xReshaped,\n    transposeA,\n    transposeB,\n    backend: backend2,\n    bias,\n    activation: activation2,\n    preluActivationWeights,\n    leakyreluAlpha\n  });\n  const out = reshape6({ inputs: { x: result }, backend: backend2, attrs: { shape: convInfo.outShape } });\n  intermediates.push(result);\n  for (const i2 of intermediates) {\n    backend2.disposeData(i2.dataId);\n  }\n  return out;\n}\nfunction conv2DImpl({ x, filter, convInfo, backend: backend2, bias = null, preluActivationWeights = null, leakyreluAlpha = 0, activation: activation2 = null }) {\n  const hasBias = bias != null;\n  const hasPreluActivationWeights = preluActivationWeights != null;\n  const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n  const sameSize = isChannelsLast && convInfo.filterHeight === convInfo.inHeight && convInfo.filterWidth === convInfo.inWidth && convInfo.padInfo.type === \"VALID\";\n  if (sameSize || convInfo.filterHeight === 1 && convInfo.filterWidth === 1 && convInfo.dilationHeight === 1 && convInfo.dilationWidth === 1 && convInfo.strideHeight === 1 && convInfo.strideWidth === 1 && (convInfo.padInfo.type === \"SAME\" || convInfo.padInfo.type === \"VALID\")) {\n    return conv2dByMatMul2({\n      x,\n      filter,\n      convInfo,\n      backend: backend2,\n      bias,\n      activation: activation2,\n      preluActivationWeights,\n      leakyreluAlpha\n    });\n  }\n  const dimAOuter = isChannelsLast ? convInfo.outHeight * convInfo.outWidth : convInfo.outChannels;\n  const dimBOuter = isChannelsLast ? convInfo.outChannels : convInfo.outHeight * convInfo.outWidth;\n  const dimInner = convInfo.filterHeight * convInfo.filterWidth * convInfo.inChannels;\n  const padInfo = [convInfo.padInfo.top, convInfo.padInfo.left];\n  const dimensions = [\n    { type: \"int32\", data: [convInfo.filterHeight, convInfo.filterWidth] },\n    { type: \"int32\", data: [...padInfo] },\n    { type: \"int32\", data: [convInfo.strideHeight, convInfo.strideWidth] },\n    { type: \"int32\", data: [convInfo.dilationHeight, convInfo.dilationWidth] },\n    { type: \"int32\", data: [dimAOuter] },\n    { type: \"int32\", data: [dimBOuter] },\n    { type: \"int32\", data: [dimInner] }\n  ];\n  const program = new Conv2DMMProgram(convInfo, dimAOuter, dimBOuter, dimInner, hasBias, activation2, hasPreluActivationWeights);\n  const intermediates = [];\n  const inputVar = [x, filter];\n  if (hasBias) {\n    if (!isChannelsLast && bias.shape.length === 1) {\n      bias = reshape6({ inputs: { x: bias }, backend: backend2, attrs: { shape: [bias.shape[0], 1, 1] } });\n      intermediates.push(bias);\n    }\n    inputVar.push(bias);\n  }\n  if (hasPreluActivationWeights) {\n    if (!isChannelsLast && preluActivationWeights.shape.length === 1) {\n      preluActivationWeights = reshape6({\n        inputs: { x: preluActivationWeights },\n        backend: backend2,\n        attrs: { shape: [preluActivationWeights.shape[0], 1, 1] }\n      });\n      intermediates.push(preluActivationWeights);\n    }\n    inputVar.push(preluActivationWeights);\n  }\n  if (activation2 === \"leakyrelu\") {\n    dimensions.push({ type: \"float32\", data: [leakyreluAlpha] });\n    program.uniforms += \" alpha : f32,\";\n  }\n  const out = backend2.runWebGPUProgram(program, inputVar, x.dtype, dimensions);\n  for (const i2 of intermediates) {\n    backend2.disposeData(i2.dataId);\n  }\n  return out;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Conv2D.js\nfunction conv2d6(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode, false, $dataFormat);\n  return conv2DImpl({ x, filter, convInfo, backend: backend2 });\n}\nvar conv2DConfig4 = {\n  kernelName: Conv2D,\n  backendName: \"webgpu\",\n  kernelFunc: conv2d6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/conv_backprop_mm_webgpu.js\nfunction conv2dTransposeCommonSnippet(innerElementSize = 4) {\n  const getWSnippet = (innerElementSize2) => {\n    switch (innerElementSize2) {\n      case 1:\n        return \"return W[getIndexFromCoords4D(coord, uniforms.wShape)];\";\n      case 4:\n        return `\n            let coord1 = vec4<i32>(coordX, coordY, col + 1, rowInner);\n            let coord2 = vec4<i32>(coordX, coordY, col + 2, rowInner);\n            let coord3 = vec4<i32>(coordX, coordY, col + 3, rowInner);\n            let v0 = W[getIndexFromCoords4D(coord, uniforms.wShape)];\n            let v1 = W[getIndexFromCoords4D(coord1, uniforms.wShape)];\n            let v2 = W[getIndexFromCoords4D(coord2, uniforms.wShape)];\n            let v3 = W[getIndexFromCoords4D(coord3, uniforms.wShape)];\n            return vec4<f32>(v0, v1, v2, v3);\n            `;\n      default:\n        throw new Error(`innerElementSize ${innerElementSize2} is not supported.`);\n    }\n  };\n  const readASnippet = `\n      let outRow = row / uniforms.outShape[2];\n      let outCol = row % uniforms.outShape[2];\n\n      let WRow = col / (uniforms.filterDims[1] * uniforms.outBackprop[3]);\n      let WCol = col / uniforms.outBackprop[3] % uniforms.filterDims[1];\n      let xR = f32(outRow - uniforms.pads[0] + WRow) / f32(uniforms.stride[0]);\n      let xC = f32(outCol - uniforms.pads[1] + WCol) / f32(uniforms.stride[1]);\n      if (xR < 0.0 || xR >= f32(uniforms.outBackprop[1]) || fract(xR) > 0.0) {\n        return ${typeSnippet(innerElementSize)}(0.0);\n      }\n      if (xC < 0.0 || xC >= f32(uniforms.outBackprop[2]) || fract(xC) > 0.0) {\n        return ${typeSnippet(innerElementSize)}(0.0);\n      }\n      let coord = vec4<i32>(\n          batch,\n          i32(xR),\n          i32(xC),\n          col % uniforms.outBackprop[3]);\n      return x[getIndexFromCoords4D(coord, uniforms.xShape)/${innerElementSize}];`;\n  const sampleA = `if (row < uniforms.dimAOuter && col < uniforms.dimInner) {\n        ${readASnippet}\n      }\n      return ${typeSnippet(innerElementSize)}(0.0);`;\n  const userCode = `\n  fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${typeSnippet(innerElementSize)} {\n    let col = colIn * ${innerElementSize};\n    ${sampleA}\n  }\n\n  fn mm_readB(batch: i32, row : i32, colIn : i32) -> ${typeSnippet(innerElementSize)} {\n    let col = colIn * ${innerElementSize};\n    let coordX = uniforms.filterDims.x - 1 -\n        row / (uniforms.filterDims[1] * uniforms.outBackprop[3]);\n    let coordY = uniforms.filterDims.y - 1 -\n        (row / uniforms.outBackprop[3]) % uniforms.filterDims[1];\n    if (row < uniforms.dimInner && col < uniforms.dimBOuter &&\n        coordX >= 0 && coordY >= 0) {\n      let rowInner = row % uniforms.outBackprop[3];\n      let coord = vec4<i32>(coordX, coordY, col, rowInner);\n      ${getWSnippet(innerElementSize)}\n    }\n    return ${typeSnippet(innerElementSize)}(0.0);\n  }\n\n  fn mm_write(batch: i32, row : i32, colIn : i32, valueInput : ${typeSnippet(innerElementSize)}) {\n    let col = colIn * ${innerElementSize};\n    if (row < uniforms.dimAOuter && (col + ${innerElementSize - 1}) < uniforms.dimBOuter) {\n      var value = valueInput;\n      let outCoord = vec4<i32>(\n          batch,\n          row / uniforms.outShape[2],\n          row % uniforms.outShape[2],\n          col);\n      result[getIndexFromCoords4D(outCoord, uniforms.outShape)/${innerElementSize}] = value;\n    }\n  }`;\n  return userCode;\n}\nvar Conv2DDerInputMMProgram = class {\n  constructor(convInfo) {\n    this.variableNames = [\"x\", \"W\"];\n    this.uniforms = \"filterDims : vec2<i32>, pads : vec2<i32>, stride : vec2<i32>, outBackprop : vec4<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,\";\n    this.outputShape = convInfo.inShape;\n    util_exports.assert(convInfo.dataFormat === \"channelsLast\", () => \"TODO: NCHW is unimplemented\");\n    this.isVec4 = convInfo.inChannels % 4 === 0 && convInfo.outChannels % 4 === 0;\n    this.dispatchLayout = { x: [3], y: [1, 2], z: [0] };\n    this.workGroupSize = computeWorkGroupSizeForConv2d(this.dispatchLayout, this.outputShape, this.isVec4);\n    this.elementsPerThread = computeWorkPerThreadForConv2d(this.dispatchLayout, this.outputShape, this.isVec4);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, this.elementsPerThread);\n    if (this.isVec4) {\n      this.innerElementSize = 4;\n      this.variableTypes = [\"vec4<f32>\", \"f32\"];\n    } else {\n      this.innerElementSize = this.elementsPerThread[0];\n    }\n    this.tileAOuter = this.workGroupSize[1] * this.elementsPerThread[1];\n    this.tileBOuter = this.workGroupSize[0] * this.elementsPerThread[0];\n    this.tileInner = Math.max(this.workGroupSize[0] * this.innerElementSize, this.workGroupSize[1]);\n    this.shaderKey = `conv2DDerInputMM_${this.isVec4}_${this.elementsPerThread}_${this.innerElementSize}`;\n  }\n  getUserCode() {\n    const matMulSource = this.isVec4 ? makeMatMulPackedVec4Source(this.elementsPerThread, this.tileAOuter, this.tileBOuter, this.tileInner, this.innerElementSize) : makeMatMulPackedSource(this.elementsPerThread, this.workGroupSize);\n    const userCode = `\n    ${conv2dTransposeCommonSnippet(this.isVec4 ? 4 : 1)}\n    ${matMulSource}\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/conv_backprop_webgpu.js\nvar Conv2DDerInputProgram2 = class {\n  constructor(convInfo) {\n    this.variableNames = [\"dy\", \"W\"];\n    this.uniforms = \"filterDims : vec2<i32>, pads : vec2<i32>, stride : vec2<i32>, outBackprop : vec4<i32>,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = convInfo.inShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n    this.shaderKey = `conv2DDerInput_${this.isChannelsLast}`;\n  }\n  getUserCode() {\n    const rowDim = this.isChannelsLast ? 1 : 2;\n    const colDim = this.isChannelsLast ? 2 : 3;\n    const channelDim = this.isChannelsLast ? 3 : 1;\n    return `\n    ${getMainHeaderAndGlobalIndexString()} {\n      if(index < uniforms.size) {\n        let coords = getCoordsFromIndex(index);\n        let batch = coords[0];\n        let d1 = coords[${channelDim}];\n\n        let dyCorner = vec2<i32>(coords[${rowDim}]), coords[${colDim}]) - uniforms.pads;\n        let dyRCorner = dyCorner.x;\n        let dyCCorner = dyCorner.y;\n\n        // Convolve dy(?, ?, d2) with w(:, :, d1, d2) to compute dx(xR, xC, d1).\n        // ? = to be determined. : = across all values in that axis.\n        var dotProd = 0.0;\n        for (var wR = 0; wR < uniforms.filterDims.x; wR = wR + 1) {\n          let dyR = (f32(dyRCorner) + f32(wR)) / f32(uniforms.stride.x);\n          let wRPerm = uniforms.filterDims.x - 1 - wR;\n          if (dyR < 0.0 || dyR >= f32(uniforms.outBackprop[1]) || fract(dyR) > 0.0 ||\n              wRPerm < 0) {\n            continue;\n          }\n          let idyR = dyR;\n\n          for (var wC = 0; wC < uniforms.filterDims.y; wC = wC + 1) {\n            let dyC = (f32(dyCCorner) + f32(wC)) / f32(uniforms.stride.y);\n            let wCPerm = uniforms.filterDims.y - 1 - wC;\n            if (dyC < 0.0 || dyC >= f32(uniforms.outBackprop[2]) ||\n                fract(dyC) > 0.0 || wCPerm < 0) {\n              continue;\n            }\n            let idyC = dyC;\n\n            for (var d2 = 0; d2 < uniforms.outBackprop[3]; d2 = d2 + 1) {\n              if (${this.isChannelsLast}) {\n                let xValue = getDy(batch, idyR, idyC, d2);\n                let wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd = dotProd + xValue * wValue;\n              } else {\n                let xValue = getDy(batch, d2, idyR, idyC);\n                let wValue = getW(wRPerm, wCPerm, d1, d2);\n                dotProd = dotProd + xValue * wValue;\n              }\n\n            }\n          }\n        }\n        setOutputAtIndex(index, dotProd);\n      }\n    }\n  `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Conv2DBackpropInput.js\nfunction conv2DBackpropInput5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { dy, filter } = inputs;\n  const { inputShape, strides, pad: pad3, dataFormat, dimRoundingMode } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(inputShape, filter.shape, strides, 1, pad3, dimRoundingMode, false, $dataFormat);\n  const dimensions = [\n    { type: \"int32\", data: [convInfo.filterHeight, convInfo.filterWidth] },\n    {\n      type: \"int32\",\n      data: [\n        convInfo.filterHeight - 1 - convInfo.padInfo.top,\n        convInfo.filterWidth - 1 - convInfo.padInfo.left\n      ]\n    },\n    { type: \"int32\", data: [convInfo.strideHeight, convInfo.strideWidth] },\n    {\n      type: \"int32\",\n      data: [\n        convInfo.batchSize,\n        convInfo.outHeight,\n        convInfo.outWidth,\n        convInfo.outChannels\n      ]\n    }\n  ];\n  let program;\n  if (env().getBool(\"WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE\")) {\n    program = new Conv2DDerInputProgram2(convInfo);\n  } else {\n    program = new Conv2DDerInputMMProgram(convInfo);\n    const dimAOuter = convInfo.inShape[1] * convInfo.inShape[2];\n    const dimBOuter = convInfo.inShape[3];\n    const dimInner = convInfo.filterHeight * convInfo.filterWidth * convInfo.outChannels;\n    dimensions.push({ type: \"uint32\", data: [dimAOuter] }, { type: \"uint32\", data: [dimBOuter] }, { type: \"uint32\", data: [dimInner] });\n  }\n  return backend2.runWebGPUProgram(program, [dy, filter], \"float32\", dimensions);\n}\nvar conv2DBackpropInputConfig4 = {\n  kernelName: Conv2DBackpropInput,\n  backendName: \"webgpu\",\n  kernelFunc: conv2DBackpropInput5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Cos.js\nvar cos4 = unaryKernelFunc3({ opType: UnaryOpType.COS });\nvar cosConfig4 = {\n  kernelName: Cos,\n  backendName: \"webgpu\",\n  kernelFunc: cos4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Cosh.js\nvar cosh4 = unaryKernelFunc3({ opType: UnaryOpType.COSH });\nvar coshConfig4 = {\n  kernelName: Cosh,\n  backendName: \"webgpu\",\n  kernelFunc: cosh4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/crop_and_resize_webgpu.js\nvar CropAndResizeProgram2 = class {\n  constructor(channnel, boxShape, cropSize, method) {\n    this.variableNames = [\"Image\", \"Boxes\", \"BoxInd\"];\n    this.uniforms = \"extrapolationValue : f32,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    const [numBoxes] = boxShape;\n    this.outputShape = [numBoxes, cropSize[0], cropSize[1], channnel];\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.methodId = method === \"bilinear\" ? 1 : 0;\n    this.cropHeightBiggerThan1 = this.outputShape[1] > 1;\n    this.cropWidthBiggerThan1 = this.outputShape[2] > 1;\n    this.shaderKey = `cropAndResize_${this.methodId}_${this.cropHeightBiggerThan1}_${this.cropWidthBiggerThan1}`;\n  }\n  getUserCode() {\n    const [inputHeightFloat, inputWidthFloat] = [`f32(uniforms.imageShape[1] - 1)`, `f32(uniforms.imageShape[2] - 1)`];\n    const [heightRatio, heightScale, inY] = this.cropHeightBiggerThan1 ? [\n      `(${inputHeightFloat} / f32(uniforms.outShape[1] - 1))`,\n      \"(y2-y1) * height_ratio\",\n      `y1*${inputHeightFloat} + f32(y)*(height_scale)`\n    ] : [\n      \"0.0\",\n      \"0.0\",\n      `0.5 * (y1+y2) * ${inputHeightFloat}`\n    ];\n    const [widthRatio, widthScale, inX] = this.cropWidthBiggerThan1 ? [\n      `(${inputWidthFloat} / f32(uniforms.outShape[2] - 1))`,\n      \"(x2-x1) * width_ratio\",\n      `x1*${inputWidthFloat} + f32(x)*(width_scale)`\n    ] : [\n      \"0.0\",\n      \"0.0\",\n      `0.5 * (x1+x2) * ${inputWidthFloat}`\n    ];\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n      if (index < uniforms.size) {\n        let coords = getCoordsFromIndex(index);\n        let height_ratio = f32(${heightRatio});\n        let width_ratio = f32(${widthRatio});\n        let b = coords[0];\n        let y = coords[1];\n        let x = coords[2];\n        let d = coords[3];\n        // get box vals\n        let y1 = getBoxes(b, 0);\n        let x1 = getBoxes(b, 1);\n        let y2 = getBoxes(b, 2);\n        let x2 = getBoxes(b, 3);\n        // get image in batch index\n        let bInd = i32(round(getBoxInd(b)));\n        if(bInd < 0 || bInd >= uniforms.outShape[0]) {\n          return;\n        }\n        let height_scale = ${heightScale};\n        let width_scale = ${widthScale};\n        let in_y = ${inY};\n        if( in_y < 0.0 || in_y > ${inputHeightFloat} ) {\n          setOutputAtIndex(index, uniforms.extrapolationValue);\n          return;\n        }\n        let in_x = ${inX};\n        if( in_x < 0.0 || in_x > ${inputWidthFloat} ) {\n          setOutputAtIndex(index, uniforms.extrapolationValue);\n          return;\n        }\n        let sourceFracIndexCR = vec2<f32>(in_x,in_y);\n        if(${this.methodId} == 1) {\n          // Compute the four integer indices.\n          let sourceFloorCR = vec2<i32>(sourceFracIndexCR);\n          let sourceCeilCR = vec2<i32>(ceil(sourceFracIndexCR));\n          let topLeft = getImage(bInd, sourceFloorCR.y, sourceFloorCR.x, d);\n          let bottomLeft = getImage(bInd, sourceCeilCR.y, sourceFloorCR.x, d);\n          let topRight = getImage(bInd, sourceFloorCR.y, sourceCeilCR.x, d);\n          let bottomRight = getImage(bInd, sourceCeilCR.y, sourceCeilCR.x, d);\n          let fracCR = sourceFracIndexCR - vec2<f32>(sourceFloorCR);\n          let top = topLeft + (topRight - topLeft) * fracCR.x;\n          let bottom = bottomLeft + (bottomRight - bottomLeft) * fracCR.x;\n          let newValue = top + (bottom - top) * fracCR.y;\n          setOutputAtIndex(index, newValue);\n        } else {\n          // Compute the coordinators of nearest neighbor point.\n          let sourceNearestCR = vec2<i32>(floor(\n            sourceFracIndexCR + vec2<f32>(0.5,0.5)));\n          let newValue = getImage(\n            bInd, sourceNearestCR.y, sourceNearestCR.x, d);\n          setOutputAtIndex(index, newValue);\n        }\n      }\n    }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/CropAndResize.js\nvar cropAndResize5 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { image: image2, boxes, boxInd } = inputs;\n  const { cropSize, method, extrapolationValue } = attrs;\n  const program = new CropAndResizeProgram2(image2.shape[3], boxes.shape, cropSize, method);\n  const uniformData = [{ type: \"float32\", data: [extrapolationValue] }];\n  return backend2.runWebGPUProgram(program, [image2, boxes, boxInd], \"float32\", uniformData);\n};\nvar cropAndResizeConfig4 = {\n  kernelName: CropAndResize,\n  backendName: \"webgpu\",\n  kernelFunc: cropAndResize5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/cum_webgpu.js\nvar CumOpType2;\n(function(CumOpType3) {\n  CumOpType3[\"Prod\"] = \"*\";\n  CumOpType3[\"Sum\"] = \"+\";\n})(CumOpType2 || (CumOpType2 = {}));\nvar CumProgram2 = class {\n  constructor(op2, shape, exclusive, reverse5) {\n    this.variableNames = [\"x\"];\n    this.uniforms = \"index : f32,\";\n    this.size = true;\n    const workGroupSizeX = 128;\n    this.workGroupSize = [workGroupSizeX, 1, 1];\n    this.outputShape = shape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.exclusive = exclusive;\n    this.reverse = reverse5;\n    this.op = op2;\n    this.shaderKey = `cum_${this.op}_${this.exclusive}_${this.reverse}`;\n  }\n  getUserCode() {\n    const rank = this.outputShape.length;\n    const initVal = this.op === CumOpType2.Prod ? \"1.0\" : \"0.0\";\n    const val = this.exclusive ? initVal : `getX(${getCoords4(rank, \"coords\", this.op)})`;\n    const length = this.outputShape[this.outputShape.length - 1];\n    let condition = \"\";\n    let idxString = \"\";\n    if (this.exclusive) {\n      condition = this.reverse ? `end != ${length - 1}` : \"end != 0\";\n      idxString = this.reverse ? \"end + 1\" : \"end - 1\";\n    } else {\n      condition = this.reverse ? `end + pow2 < ${length}` : \"end >= pow2\";\n      idxString = this.reverse ? \"end + pow2\" : \"end - pow2\";\n    }\n    return `\n      ${getMainHeaderAndGlobalIndexString()}\n       if (index < uniforms.size) {\n         var coords = getCoordsFromIndex(index);\n\n         let end = ${getFinalCoord2(rank, \"coords\", this.op)};\n         var val = ${val};\n         let pow2 = i32(pow(2.0, uniforms.index));\n         if (${condition}) {\n           let idx = ${idxString};\n           ${getFinalCoord2(rank, \"coords\", this.op)} = idx;\n           val ${this.op}= getX(${getCoords4(rank, \"coords\", this.op)});\n         }\n         setOutputAtIndex(index, val);\n       }\n      }\n    `;\n  }\n};\nfunction getCoords4(rank, name, op2) {\n  if (rank === 1) {\n    return `${name}`;\n  } else if (rank === 2) {\n    return `${name}.x, ${name}.y`;\n  } else if (rank === 3) {\n    return `${name}.x, ${name}.y, ${name}.z`;\n  } else if (rank === 4) {\n    return `${name}.x, ${name}.y, ${name}.z, ${name}.w`;\n  } else {\n    throw Error(`Cumulative ${op2} for rank ${rank} is not yet supported`);\n  }\n}\nfunction getFinalCoord2(rank, name, op2) {\n  if (rank === 1) {\n    return `${name}`;\n  } else if (rank === 2) {\n    return `${name}.y`;\n  } else if (rank === 3) {\n    return `${name}.z`;\n  } else if (rank === 4) {\n    return `${name}.w`;\n  } else {\n    throw Error(`Cumulative ${op2} for rank ${rank} is not yet supported`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Cum_impl.js\nfunction cumImpl2(op2, x, backend2, axis, exclusive, reverse5) {\n  const xRank = x.shape.length;\n  const permutation = backend_util_exports.getAxesPermutation([axis], xRank);\n  let permutedX = x;\n  if (permutation != null) {\n    permutedX = transpose5({ inputs: { x }, backend: backend2, attrs: { perm: permutation } });\n  }\n  const permutedAxis = backend_util_exports.getInnerMostAxes(1, xRank)[0];\n  if (permutedAxis !== xRank - 1) {\n    throw new Error(`WebGPU cumprod shader expects an inner-most axis=${x.shape.length - 1} but got axis=${axis}`);\n  }\n  const size = permutedX.shape[permutedAxis];\n  let result = identity5({ inputs: { x: permutedX }, backend: backend2 });\n  for (let i2 = 0; i2 <= Math.ceil(Math.log2(size)) - 1; i2++) {\n    const program = new CumProgram2(op2, permutedX.shape, false, reverse5);\n    const prevResult = result;\n    const uniformData = [{ type: \"float32\", data: [i2] }];\n    result = backend2.runWebGPUProgram(program, [result], result.dtype, uniformData);\n    backend2.disposeData(prevResult.dataId);\n  }\n  if (exclusive) {\n    const program = new CumProgram2(op2, permutedX.shape, exclusive, reverse5);\n    const prevResult = result;\n    const uniformData = [{ type: \"float32\", data: [0] }];\n    result = backend2.runWebGPUProgram(program, [result], result.dtype, uniformData);\n    backend2.disposeData(prevResult.dataId);\n  }\n  if (permutation != null) {\n    const reversePermutation = backend_util_exports.getUndoAxesPermutation(permutation);\n    const reverseTransposedResult = transpose5({ inputs: { x: result }, backend: backend2, attrs: { perm: reversePermutation } });\n    backend2.disposeData(result.dataId);\n    backend2.disposeData(permutedX.dataId);\n    return reverseTransposedResult;\n  }\n  return result;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Cumprod.js\nfunction cumprod5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  return cumImpl2(CumOpType2.Prod, x, backend2, axis, exclusive, reverse5);\n}\nvar cumprodConfig4 = {\n  kernelName: Cumprod,\n  backendName: \"webgpu\",\n  kernelFunc: cumprod5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Cumsum.js\nfunction cumsum5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, exclusive, reverse: reverse5 } = attrs;\n  return cumImpl2(CumOpType2.Sum, x, backend2, axis, exclusive, reverse5);\n}\nvar cumsumConfig4 = {\n  kernelName: Cumsum,\n  backendName: \"webgpu\",\n  kernelFunc: cumsum5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/depth_to_space_webgpu.js\nvar DepthToSpaceProgram2 = class {\n  constructor(outputShape, dataFormat) {\n    this.variableNames = [\"x\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.uniforms = \"blockSize : i32,\";\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = `depthToSpace_${dataFormat}`;\n    this.dataFormat = dataFormat;\n  }\n  getUserCode() {\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let coords = getCoordsFromIndex(index);\n          let b = coords[0];\n          let h = ${this.getHeightCoordString()};\n          let w = ${this.getWidthCoordString()};\n          let d = ${this.getDepthCoordString()};\n\n          let in_h = h / uniforms.blockSize;\n          let offset_h = h % uniforms.blockSize;\n          let in_w = w / uniforms.blockSize;\n          let offset_w = w % uniforms.blockSize;\n          let offset_d = (offset_h * uniforms.blockSize + offset_w) *\n            ${this.getOutputDepthSize()};\n          let in_d = d + offset_d;\n\n          let rlt = ${this.getInputSamplingString()};\n          setOutputAtIndex(index, rlt);\n        }\n      }`;\n    return userCode;\n  }\n  getHeightCoordString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `coords[1]`;\n    } else {\n      return `coords[2]`;\n    }\n  }\n  getWidthCoordString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `coords[2]`;\n    } else {\n      return `coords[3]`;\n    }\n  }\n  getDepthCoordString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `coords[3]`;\n    } else {\n      return `coords[1]`;\n    }\n  }\n  getOutputDepthSize() {\n    if (this.dataFormat === \"NHWC\") {\n      return `uniforms.outShape[3]`;\n    } else {\n      return `uniforms.outShape[1]`;\n    }\n  }\n  getInputSamplingString() {\n    if (this.dataFormat === \"NHWC\") {\n      return `getX(b, in_h, in_w, in_d)`;\n    } else {\n      return `getX(b, in_d, in_h, in_w)`;\n    }\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/DepthToSpace.js\nfunction depthToSpace5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockSize, dataFormat } = attrs;\n  const batchSize = x.shape[0];\n  const inputHeight = dataFormat === \"NHWC\" ? x.shape[1] : x.shape[2];\n  const inputWidth = dataFormat === \"NHWC\" ? x.shape[2] : x.shape[3];\n  const inputDepth = dataFormat === \"NHWC\" ? x.shape[3] : x.shape[1];\n  const outputHeight = inputHeight * blockSize;\n  const outputWidth = inputWidth * blockSize;\n  const outputDepth = inputDepth / (blockSize * blockSize);\n  const outputShape = dataFormat === \"NHWC\" ? [batchSize, outputHeight, outputWidth, outputDepth] : [batchSize, outputDepth, outputHeight, outputWidth];\n  const uniformData = [\n    { type: \"int32\", data: [blockSize] }\n  ];\n  const program = new DepthToSpaceProgram2(outputShape, dataFormat);\n  return backend2.runWebGPUProgram(program, [x], x.dtype, uniformData);\n}\nvar depthToSpaceConfig4 = {\n  kernelName: DepthToSpace,\n  backendName: \"webgpu\",\n  kernelFunc: depthToSpace5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/depthwise_conv2d_nchw_shared_webgpu.js\nvar DepthwiseConv2DNCHWSharedProgram = class {\n  constructor(outputShape, filterHeight, filterWidth, addBias = false, activation2 = null, hasPreluActivation = false) {\n    this.variableNames = [\"x\", \"W\"];\n    this.uniforms = `pad : vec2<i32>, inDims : vec2<i32>,`;\n    this.workGroupSize = [16, 16, 1];\n    this.outputShape = outputShape;\n    this.dispatchLayout = { x: [3], y: [2], z: [0, 1] };\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivation) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivation = hasPreluActivation;\n    this.filterHeight = filterHeight;\n    this.filterWidth = filterWidth;\n    this.shaderKey = `depthwiseNCHW_${this.activation}_${this.filterHeight}_${this.filterWidth}`;\n  }\n  getUserCode() {\n    const filterSize = this.filterWidth * this.filterHeight;\n    const workGroupSize = this.workGroupSize[0] * this.workGroupSize[1] * this.workGroupSize[2];\n    const tileAHeight = this.workGroupSize[1] + this.filterHeight - 1;\n    const tileAWidth = this.workGroupSize[0] + this.filterWidth - 1;\n    const userCode = `\n      ${activationFnSnippet(this.activation, this.hasPreluActivation, false, 4)}\n\n      var<workgroup> mm_Asub : array<array<f32, ${tileAWidth}>, ${tileAHeight}>;\n      var<workgroup> mm_Bsub : array<array<f32, ${this.filterWidth}>, ${this.filterHeight}>;\n      fn readX(batch : i32, channel : i32, row : i32, col : i32) -> f32 {\n        var value = 0.0;\n        if (row >=0 && row < uniforms.inDims[0] && col >=0 && col < uniforms.inDims[1])\n        {\n          value = getX(batch, channel, row, col);\n        }\n        return value;\n      }\n\n      ${getWorkGroupSizeString()}\n      fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,\n              @builtin(global_invocation_id) GlobalId : vec3<u32>,\n              @builtin(local_invocation_index) LocalIndex: u32,\n              @builtin(num_workgroups) NumWorkgroups: vec3<u32>) {\n        localId = LocalId;\n        globalId = GlobalId;\n        let localIndex = i32(LocalIndex);\n        numWorkgroups = NumWorkgroups;\n        let coords = getOutputCoords();\n        let batch = coords[0];\n        let xRCCorner = vec2<i32>(coords.zw) - uniforms.pad;\n        let channelMul = uniforms.wShape[3];\n        let d1 = coords[1] / channelMul;\n        let q = coords[1] % channelMul;\n\n        let inputRowStart = xRCCorner.x;\n        let inputColStart = xRCCorner.y;\n\n        let localRow = i32(localId.y);\n        let localCol = i32(localId.x);\n\n        // Load one tile of X into local memory.\n        for (var inputRow = localRow; inputRow < ${tileAHeight}; inputRow = inputRow + ${this.workGroupSize[1]}) {\n          for (var inputCol = localCol; inputCol < ${tileAWidth}; inputCol = inputCol + ${this.workGroupSize[0]}) {\n            let rowOffset = inputRow - localRow;\n            let colOffset = inputCol - localCol;\n            mm_Asub[inputRow][inputCol] = readX(batch, d1, inputRowStart + rowOffset, inputColStart + colOffset);\n          }\n        }\n\n        // Load one tile of W into local memory.\n        var wIndex = localIndex;\n        ${filterSize < workGroupSize ? `if (wIndex < ${filterSize})` : `for(; wIndex < ${filterSize}; wIndex = wIndex + ${workGroupSize})`}\n\n        {\n          let wRow = wIndex / ${this.filterWidth};\n          let wCol = wIndex % ${this.filterWidth};\n          mm_Bsub[wRow][wCol] = getW(wRow, wCol, d1, q);\n        }\n\n        workgroupBarrier();\n\n        var value = 0.0;\n        for (var wR = 0; wR < ${this.filterHeight}; wR = wR + 1) {\n          for (var wC = 0; wC < ${this.filterWidth}; wC = wC + 1) {\n            let xVal = mm_Asub[localRow + wR][localCol + wC];\n            let wVal = mm_Bsub[wR][wC];\n            value = fma(xVal, wVal, value);\n          }\n        }\n        ${biasActivationSnippet(this.addBias, this.activation)}\n        if (coordsInBounds4D(coords, uniforms.outShape)) {\n          setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/depthwise_conv2d_vec4_webgpu.js\nvar DepthwiseConv2DVec4Program = class {\n  constructor(convInfo, addBias = false, activation2 = null, hasPreluActivation = false) {\n    this.variableNames = [\"x\", \"W\"];\n    this.uniforms = \"pad : vec2<i32>, inDims : vec2<i32>,\";\n    this.workGroupSize = [4, 4, 4];\n    this.isVec4 = true;\n    this.outputShape = convInfo.outShape;\n    this.dispatchLayout = { x: [3], y: [2], z: [0, 1] };\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [4, 4, 1]);\n    util_exports.assert(convInfo.dataFormat === \"channelsLast\", () => \"TODO: NCHW is unimplemented\");\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivation) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.convInfo = convInfo;\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivation = hasPreluActivation;\n    this.shaderKey = `depthwiseVec4_${activation2}_${this.convInfo.filterHeight}_${this.convInfo.filterWidth}`;\n  }\n  getUserCode() {\n    const xNumber = 4 + this.convInfo.filterWidth - 1;\n    const userCode = `\n      ${activationFnSnippet(this.activation, this.hasPreluActivation, true, 4)}\n      fn readX(batch : i32, row : i32, col : i32, channel : i32) -> vec4<f32> {\n        var value = vec4<f32>(0.0);\n        if (row >=0 && row < uniforms.inDims[0] && col >=0 && col < uniforms.inDims[1])\n        {\n          value = getX(batch, row, col, channel);\n        }\n        return value;\n      }\n      ${getWorkGroupSizeString()}\n      fn main(@builtin(global_invocation_id) globalId: vec3<u32>) {\n        let batch = i32(globalId.z) / uniforms.outShape[1];\n        let r = i32(globalId.z) % uniforms.outShape[1];\n        let c = i32(globalId.y) * 4;\n        let d1 = i32(globalId.x) * 4;\n        let xRCCorner = vec2<i32>(r, c) - uniforms.pad;\n\n        let xRCorner = xRCCorner.x;\n        let xCCorner = xRCCorner.y;\n        var xVals : array<vec4<f32>, ${xNumber}>;\n        var dotProd : array<vec4<f32>, 4>;\n        dotProd[0] = vec4<f32>(0.0);\n        dotProd[1] = vec4<f32>(0.0);\n        dotProd[2] = vec4<f32>(0.0);\n        dotProd[3] = vec4<f32>(0.0);\n\n        // Use constant instead of uniform can give better performance.\n        for (var wR = 0; wR < ${this.convInfo.filterHeight}; wR = wR + 1) {\n          let xR = xRCorner + wR;\n          for (var i = 0; i < ${xNumber}; i++)\n          {\n            xVals[i] = readX(batch, xR, xCCorner + i, d1);\n          }\n          for (var wC = 0; wC < ${this.convInfo.filterWidth}; wC = wC + 1) {\n            let wValue = getW(wR, wC, d1, 0);\n            dotProd[0] = dotProd[0] + xVals[0 + wC] * wValue;\n            dotProd[1] = dotProd[1] + xVals[1 + wC] * wValue;\n            dotProd[2] = dotProd[2] + xVals[2 + wC] * wValue;\n            dotProd[3] = dotProd[3] + xVals[3 + wC] * wValue;\n          }\n        }\n\n        for (var i = 0; i < 4; i = i + 1) {\n          let coords = vec4<i32>(batch, r, c + i, d1);\n          if (coordsInBounds4D(coords, uniforms.outShape)) {\n            var value = dotProd[i];\n            ${biasActivationSnippet(this.addBias, this.activation)}\n            setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);\n          }\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/depthwise_conv2d_webgpu.js\nvar DepthwiseConv2DProgram2 = class {\n  constructor(convInfo, addBias = false, activation2 = null, hasPreluActivation = false) {\n    this.variableNames = [\"x\", \"W\"];\n    this.uniforms = `pad : vec2<i32>, inDims : vec2<i32>, filterHeight : i32,\n      filterWidth : i32, stride : vec2<i32>, dilation : vec2<i32>,`;\n    this.workGroupSize = [256, 1, 1];\n    this.outputShape = convInfo.outShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n    if (addBias) {\n      this.variableNames.push(\"bias\");\n    }\n    if (hasPreluActivation) {\n      this.variableNames.push(\"preluActivationWeights\");\n    }\n    this.convInfo = convInfo;\n    this.addBias = addBias;\n    this.activation = activation2;\n    this.hasPreluActivation = hasPreluActivation;\n    this.shaderKey = `depthwise_${this.activation}_${this.isChannelsLast}`;\n  }\n  getUserCode() {\n    const getXSnippet = this.isChannelsLast ? \"getX(batch, xR, xC, d1);\" : \"getX(batch, d1, xR, xC);\";\n    const userCode = `\n      ${activationFnSnippet(this.activation, this.hasPreluActivation, false, 4)}\n\n      ${getMainHeaderString()}\n        let coords = getOutputCoords();\n        let batch = coords[0];\n        let xRCCorner = vec2<i32>(coords.${this.isChannelsLast ? \"yz\" : \"zw\"}) * uniforms.stride - uniforms.pad;\n        let d2 = coords[${this.isChannelsLast ? 3 : 1}];\n        let channelMul = uniforms.wShape[3];\n        let d1 = d2 / channelMul;\n        let q = d2 % channelMul;\n\n        let inputRowStart = xRCCorner.x;\n        let inputColStart = xRCCorner.y;\n        let inputRowEnd = inputRowStart + uniforms.filterHeight *\n            uniforms.dilation[0];\n        let inputColEnd = inputColStart + uniforms.filterWidth *\n            uniforms.dilation[1];\n\n        // Convolve x(?, ?, d1)|x(d1, ?, ?) with w(:, :, d1, q) to get\n        // y(yR, yC, d2)|y(d2, yR, yC). ? = to be determined. : = across all\n        // values in that axis. x(?, ?, d1) and y(yR, yC, d2) is for NHWC.\n        // x(d1, ?, ?) and y(d2, yR, yC) is for NCHW.\n        var value = 0.0;\n\n        // Extract if checking out of for loop for performance.\n        if (inputRowStart >= 0 && inputColStart >= 0 &&\n          inputRowEnd < uniforms.inDims[0] &&\n              inputColEnd < uniforms.inDims[1]) {\n            for (var wR = 0; wR < uniforms.filterHeight; wR = wR + 1) {\n              let xR = inputRowStart + wR * uniforms.dilation[0];\n\n              for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {\n                let xC = inputColStart + wC * uniforms.dilation[1];\n\n                let xVal = ${getXSnippet};\n                let wVal = getW(wR, wC, d1, q);\n                value = value + xVal * wVal;\n              }\n            }\n          } else {\n            for (var wR = 0; wR < uniforms.filterHeight; wR = wR + 1) {\n              let xR = inputRowStart + wR * uniforms.dilation[0];\n\n              if (xR < 0 || xR >= uniforms.inDims[0]) {\n                continue;\n              }\n\n              for (var wC = 0; wC < uniforms.filterWidth; wC = wC + 1) {\n                let xC = inputColStart + wC * uniforms.dilation[1];\n\n                if (xC < 0 || xC >= uniforms.inDims[1]) {\n                  continue;\n                }\n\n                let xVal = ${getXSnippet};\n                let wVal = getW(wR, wC, d1, q);\n                value = value + xVal * wVal;\n              }\n            }\n          }\n          ${biasActivationSnippet(this.addBias, this.activation)}\n        if (coordsInBounds4D(coords, uniforms.outShape)) {\n          setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/DepthwiseConv2dNative.js\nfunction depthwiseConv2dNative3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  let $dilations = dilations;\n  if ($dilations == null) {\n    $dilations = [1, 1];\n  }\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad3, dimRoundingMode, true, $dataFormat);\n  const dimensions = [\n    { type: \"int32\", data: [convInfo.padInfo.top, convInfo.padInfo.left] },\n    { type: \"int32\", data: [convInfo.inHeight, convInfo.inWidth] }\n  ];\n  const isChannelsLast = convInfo.dataFormat === \"channelsLast\";\n  let program;\n  if (!isChannelsLast && convInfo.inHeight > 16 && convInfo.inWidth > 16 && convInfo.strideHeight === 1 && convInfo.strideWidth === 1 && convInfo.dilationWidth === 1 && convInfo.dilationHeight === 1 && convInfo.inChannels === convInfo.outChannels) {\n    program = new DepthwiseConv2DNCHWSharedProgram(convInfo.outShape, convInfo.filterHeight, convInfo.filterWidth);\n  } else if (isChannelsLast && convInfo.inHeight > 4 && convInfo.inWidth > 4 && convInfo.strideHeight === 1 && convInfo.strideWidth === 1 && convInfo.inChannels === convInfo.outChannels && convInfo.dilationHeight === 1 && convInfo.dilationWidth === 1 && convInfo.inChannels % 4 === 0) {\n    program = new DepthwiseConv2DVec4Program(convInfo);\n  } else {\n    program = new DepthwiseConv2DProgram2(convInfo);\n    dimensions.push({ type: \"int32\", data: [convInfo.filterHeight] }, { type: \"int32\", data: [convInfo.filterWidth] }, { type: \"int32\", data: [convInfo.strideHeight, convInfo.strideWidth] }, {\n      type: \"int32\",\n      data: [convInfo.dilationHeight, convInfo.dilationWidth]\n    });\n  }\n  return backend2.runWebGPUProgram(program, [x, filter], x.dtype, dimensions);\n}\nvar depthwiseConv2dNativeConfig4 = {\n  kernelName: DepthwiseConv2dNative,\n  backendName: \"webgpu\",\n  kernelFunc: depthwiseConv2dNative3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Multiply.js\nvar multiplyKernelFunc = binaryKernelFunc3({\n  opType: BinaryOpType.MUL,\n  cpuKernelImpl: multiplyImplCPU2,\n  supportsComplex: true\n});\nvar multiplyConfig4 = {\n  kernelName: Multiply,\n  backendName: \"webgpu\",\n  kernelFunc: multiplyKernelFunc\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/reduce_webgpu.js\nvar ReduceProgram2 = class {\n  constructor(reduceInfo, reduceType) {\n    this.workGroupSize = [64, 1, 1];\n    this.variableNames = [\"x\"];\n    this.uniforms = \"reduceSize : i32,\";\n    this.size = true;\n    this.inputShape = [reduceInfo.batchSize, reduceInfo.inSize];\n    const [outputShape] = backend_util_exports.computeOutAndReduceShapes(this.inputShape, [1]);\n    this.outputShape = outputShape.length === 0 ? [1] : outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, [1, 1, 1]);\n    this.reduceType = reduceType;\n    this.shaderKey = `reduce_${reduceType}`;\n  }\n  getUserCode() {\n    let reduceOp = ``;\n    let initValue = \"0.0\";\n    if (this.reduceType === \"min\" || this.reduceType === \"max\") {\n      reduceOp = `\n         if (isnan(candidate)) {\n          bestValue = uniforms.NAN;\n         } else if (!isnan(bestValue) && candidate ${this.reduceType === \"min\" ? \"<\" : \">\"} bestValue)\n           {  bestValue = candidate; }`;\n      initValue = \"f32(x[offset])\";\n    } else if (this.reduceType === \"sum\" || this.reduceType === \"mean\") {\n      reduceOp = \" bestValue = bestValue + candidate; \";\n    } else if (this.reduceType === \"prod\") {\n      reduceOp = \" bestValue = bestValue * candidate; \";\n      initValue = \"1.0\";\n    }\n    const outputSnippet = this.reduceType === \"mean\" ? `setOutputAtIndex(outputIndex, bestValue / f32(uniforms.reduceSize));` : `setOutputAtIndex(outputIndex, bestValue);`;\n    const sharedMemorySnippet = `\n         var<workgroup> xBestValues : array<f32, ${this.workGroupSize[0]}>;\n       `;\n    const userCode = `\n       fn DIV_CEIL(a : u32, b : u32) -> u32 {\n        return ((a - 1u) / b + 1u);\n       }\n\n       ${sharedMemorySnippet}\n       fn getOffset(outputIndex : i32) -> i32 {\n         let outputCoords = getCoordsFromIndex(outputIndex);\n         let offset = ${this.outputShape.length === 1 ? \"outputCoords\" : \"outputCoords[0]\"} * uniforms.reduceSize;\n          return offset;\n       }\n       ${getMainHeaderAndGlobalIndexString()}\n         let outputIndex = index / i32(workGroupSizeX);\n         let offset = getOffset(outputIndex);\n         var bestValue = ${initValue};\n         let Length = uniforms.reduceSize;\n         let WorkPerThread = DIV_CEIL(u32(Length), workGroupSizeX);\n         for (var k = i32(localId.x); k < Length && outputIndex < uniforms.size;\n             k = k + i32(workGroupSizeX)) {\n           let candidate = f32(x[offset + k]);\n           ${reduceOp}\n         }\n         xBestValues[localId.x] = bestValue;\n         workgroupBarrier();\n\n         var reduceSize = min(u32(Length), workGroupSizeX);\n         for (var currentSize = reduceSize / 2u; reduceSize > 1u;\n             currentSize = reduceSize / 2u) {\n           let interval = DIV_CEIL(reduceSize, 2u);\n           if (localId.x < currentSize) {\n            let candidate = xBestValues[localId.x + interval];\n            ${reduceOp}\n            xBestValues[localId.x] = bestValue;\n           }\n           reduceSize = interval;\n           workgroupBarrier();\n         }\n\n         if (localId.x == 0u && outputIndex < uniforms.size) {\n          ${outputSnippet}\n        }\n       }\n     `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernel_utils/reduce.js\nfunction reduce2(x, axis, keepDims, reduceType, backend2) {\n  const xRank = x.shape.length;\n  const toDispose = [];\n  const origAxes = util_exports.parseAxisParam(axis, x.shape);\n  let axes = origAxes;\n  const permutedAxes = backend_util_exports.getAxesPermutation(axes, xRank);\n  let input2 = x;\n  if (permutedAxes != null) {\n    input2 = transpose5({ inputs: { x }, attrs: { perm: permutedAxes }, backend: backend2 });\n    axes = backend_util_exports.getInnerMostAxes(axes.length, xRank);\n    toDispose.push(input2);\n  }\n  backend_util_exports.assertAxesAreInnerMostDims(reduceType, axes, xRank);\n  const [reduceOutShape, reduceShape] = backend_util_exports.computeOutAndReduceShapes(input2.shape, axes);\n  let resOutShape = reduceOutShape;\n  if (keepDims) {\n    resOutShape = backend_util_exports.expandShapeToKeepDim(reduceOutShape, origAxes);\n  }\n  let res;\n  if ((reduceType === \"max\" || reduceType === \"prod\") && backend2.shouldExecuteOnCPU([input2])) {\n    const xVals = backend2.tensorMap.get(input2.dataId).values;\n    switch (reduceType) {\n      case \"max\":\n        const outValues = maxImplCPU2(xVals, util_exports.sizeFromShape(reduceShape), resOutShape, x.dtype);\n        res = backend2.makeTensorInfo(resOutShape, x.dtype, outValues);\n        break;\n      case \"prod\":\n        const { outVals, outShape, outDtype } = prodImplCPU2(input2.shape, input2.dtype, xVals, axes);\n        res = backend2.makeTensorInfo(outShape, outDtype, outVals);\n        break;\n      default:\n        throw new Error(`${reduceType} CPU implementation is not yet supported.`);\n    }\n  } else {\n    const inSize = util_exports.sizeFromShape(reduceShape);\n    const xSize = util_exports.sizeFromShape(input2.shape);\n    const batchSize = xSize / inSize;\n    const reduceInfo = { windowSize: inSize, inSize, batchSize, outSize: 1 };\n    const dtype = reduceType === \"mean\" ? \"float32\" : sumOutType(x.dtype);\n    const uniformData = [\n      { type: \"int32\", data: [inSize] }\n    ];\n    const program = new ReduceProgram2(reduceInfo, reduceType);\n    const reduced = backend2.runWebGPUProgram(program, [input2], dtype, uniformData);\n    toDispose.push(reduced);\n    res = reshape6({ inputs: { x: reduced }, attrs: { shape: resOutShape }, backend: backend2 });\n  }\n  toDispose.forEach((t2) => backend2.disposeData(t2.dataId));\n  return res;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Sum.js\nfunction sum6(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  return reduce2(x, axis, keepDims, \"sum\", backend2);\n}\nvar sumConfig4 = {\n  kernelName: Sum,\n  backendName: \"webgpu\",\n  kernelFunc: sum6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Einsum.js\nfunction einsum4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { equation } = attrs;\n  const tensors = inputs;\n  const { allDims, summedDims, idDims } = backend_util_exports.decodeEinsumEquation(equation, tensors.length);\n  backend_util_exports.checkEinsumDimSizes(allDims.length, idDims, tensors);\n  const { path, steps } = backend_util_exports.getEinsumComputePath(summedDims, idDims);\n  const nSteps = steps.length;\n  let out = null;\n  let numDimsRemaining = allDims.length;\n  const tensorsToDispose = [];\n  for (let i2 = 0; i2 < nSteps; ++i2) {\n    for (const idTerm of steps[i2]) {\n      const { permutationIndices: perm, expandDims: dimsToExpand } = backend_util_exports.getEinsumPermutation(numDimsRemaining, idDims[idTerm]);\n      let x;\n      if (backend_util_exports.isIdentityPermutation(perm)) {\n        x = tensors[idTerm];\n      } else {\n        x = transpose5({ inputs: { x: tensors[idTerm] }, backend: backend2, attrs: { perm } });\n        tensorsToDispose.push(x);\n      }\n      const targetShape = x.shape.slice();\n      for (let k = 0; k < dimsToExpand.length; ++k) {\n        targetShape.splice(dimsToExpand[k], 0, 1);\n      }\n      if (!util_exports.arraysEqual(x.shape, targetShape)) {\n        x = reshape6({ inputs: { x }, backend: backend2, attrs: { shape: targetShape } });\n        tensorsToDispose.push(x);\n      }\n      if (out === null) {\n        out = x;\n      } else {\n        out = multiplyKernelFunc({ inputs: { a: x, b: out }, backend: backend2 });\n        tensorsToDispose.push(out);\n      }\n    }\n    if (i2 < nSteps - 1) {\n      if (path[i2] >= 0) {\n        out = sum6({\n          inputs: { x: out },\n          backend: backend2,\n          attrs: {\n            axis: path[i2] - (allDims.length - numDimsRemaining),\n            keepDims: false\n          }\n        });\n        tensorsToDispose.push(out);\n      }\n      numDimsRemaining--;\n    }\n  }\n  for (const tensorInfo of tensorsToDispose) {\n    if (tensorInfo === out) {\n      continue;\n    }\n    backend2.disposeData(tensorInfo.dataId);\n  }\n  return out;\n}\nvar einsumConfig3 = {\n  kernelName: Einsum,\n  backendName: \"webgpu\",\n  kernelFunc: einsum4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Elu.js\nvar elu6 = unaryKernelFunc3({ opType: UnaryOpType.ELU });\nvar eluConfig4 = {\n  kernelName: Elu,\n  backendName: \"webgpu\",\n  kernelFunc: elu6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Equal.js\nvar equal4 = binaryKernelFunc3({ opType: BinaryOpType.EQUAL, dtype: \"bool\", cpuKernelImpl: equalImplCPU2 });\nvar equalConfig4 = {\n  kernelName: Equal,\n  backendName: \"webgpu\",\n  kernelFunc: equal4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Exp.js\nvar exp4 = unaryKernelFunc3({\n  opType: UnaryOpType.EXP,\n  cpuKernelImpl: expImplCPU2,\n  dtype: \"float32\"\n});\nvar expConfig4 = {\n  kernelName: Exp,\n  backendName: \"webgpu\",\n  kernelFunc: exp4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ExpandDims.js\nfunction expandDims6(args) {\n  const { inputs, attrs, backend: backend2 } = args;\n  const { dim } = attrs;\n  const { input: input2 } = inputs;\n  const inputRank = input2.shape.length;\n  const newShape = input2.shape.slice();\n  let $dim = dim;\n  if (dim < 0) {\n    util_exports.assert(-(inputRank + 1) <= dim, () => `Axis must be in the interval [${-(inputRank + 1)}, ${inputRank}]`);\n    $dim = inputRank + dim + 1;\n  }\n  newShape.splice($dim, 0, 1);\n  return reshape6({ inputs: { x: input2 }, backend: backend2, attrs: { shape: newShape } });\n}\nvar expandDimsConfig4 = {\n  kernelName: ExpandDims,\n  backendName: \"webgpu\",\n  kernelFunc: expandDims6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Expm1.js\nvar expm14 = unaryKernelFunc3({ opType: UnaryOpType.EXPM1, cpuKernelImpl: expm1ImplCPU2 });\nvar expm1Config3 = {\n  kernelName: Expm1,\n  backendName: \"webgpu\",\n  kernelFunc: expm14\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/flip_left_right_webgpu.js\nvar FlipLeftRightProgram2 = class {\n  constructor(imageShape) {\n    this.outputShape = [];\n    this.variableNames = [\"x\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = imageShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = \"flipLeftRight\";\n  }\n  getUserCode() {\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let coords = getCoordsFromIndex(index);\n          let coordX = uniforms.xShape[2] - coords[2] - 1;\n          let outputValue = getX(coords[0], coords[1], coordX, coords[3]);\n          setOutputAtIndex(index, outputValue);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/FlipLeftRight.js\nvar flipLeftRightConfig4 = {\n  kernelName: FlipLeftRight,\n  backendName: \"webgpu\",\n  kernelFunc: ({ inputs, backend: backend2 }) => {\n    const { image: image2 } = inputs;\n    const webgpuBackend = backend2;\n    const program = new FlipLeftRightProgram2(image2.shape);\n    const output = webgpuBackend.runWebGPUProgram(program, [image2], image2.dtype);\n    return output;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Floor.js\nvar floor4 = unaryKernelFunc3({ opType: UnaryOpType.FLOOR, cpuKernelImpl: floorImplCPU2 });\nvar floorConfig4 = {\n  kernelName: Floor,\n  backendName: \"webgpu\",\n  kernelFunc: floor4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/FloorDiv.js\nvar floorDiv4 = binaryKernelFunc3({ opType: BinaryOpType.INT_DIV, dtype: \"int32\" });\nvar floorDivConfig4 = {\n  kernelName: FloorDiv,\n  backendName: \"webgpu\",\n  kernelFunc: floorDiv4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/from_pixels_webgpu.js\nvar FromPixelsProgram2 = class {\n  constructor(outputShape, numChannels, importVideo = false) {\n    this.isFromPixels = true;\n    this.outputShape = [0];\n    this.variableNames = [];\n    this.workGroupSize = [256, 1, 1];\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [numChannels, 1, 1]);\n    this.importVideo = importVideo;\n    this.shaderKey = `fromPixels_${this.importVideo}`;\n  }\n  getUserCode() {\n    const textureLoad = this.importVideo ? \"textureLoad(src, vec2<i32>(coords.yx));\" : \"textureLoad(src, vec2<i32>(coords.yx), 0)\";\n    const textureType = this.importVideo ? \"texture_external\" : \"texture_2d<f32>\";\n    return `\n      @binding(1) @group(0) var src: ${textureType};\n      ${getMainHeaderAndGlobalIndexString()}\n        let flatIndex = index * uniforms.numChannels;\n        if (flatIndex < uniforms.size) {\n          let coords = getCoordsFromIndex(flatIndex);\n          let values = ${textureLoad};\n          for (var i = 0; i < uniforms.numChannels; i = i + 1) {\n            result[flatIndex + i] = i32(floor(255.0 * values[i]));\n          }\n        }\n      }\n  `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/FromPixels.js\nvar fromPixelsConfig2 = {\n  kernelName: FromPixels,\n  backendName: \"webgpu\",\n  kernelFunc: fromPixels3\n};\nvar fromPixels2DContext3;\nvar videoToTextureMap = /* @__PURE__ */ new Map();\nfunction fromPixels3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  let { pixels } = inputs;\n  const { numChannels } = attrs;\n  if (pixels == null) {\n    throw new Error(\"pixels passed to tf.browser.fromPixels() can not be null\");\n  }\n  const isVideo = typeof HTMLVideoElement !== \"undefined\" && pixels instanceof HTMLVideoElement;\n  const isImage = typeof HTMLImageElement !== \"undefined\" && pixels instanceof HTMLImageElement;\n  const isCanvas = typeof HTMLCanvasElement !== \"undefined\" && pixels instanceof HTMLCanvasElement || typeof OffscreenCanvas !== \"undefined\" && pixels instanceof OffscreenCanvas;\n  const isImageBitmap = typeof ImageBitmap !== \"undefined\" && pixels instanceof ImageBitmap;\n  const [width, height] = isVideo ? [\n    pixels.videoWidth,\n    pixels.videoHeight\n  ] : [pixels.width, pixels.height];\n  const outputShape = [height, width, numChannels];\n  const importVideo = env().getBool(\"WEBGPU_IMPORT_EXTERNAL_TEXTURE\") && isVideo;\n  const isVideoOrImage = isVideo || isImage;\n  if (isImageBitmap || isCanvas || isVideoOrImage) {\n    let textureInfo;\n    if (importVideo) {\n      const videoElement = pixels;\n      if (!videoToTextureMap.has(videoElement) || videoToTextureMap.get(videoElement).expired) {\n        const externalTextureDescriptor = { source: videoElement };\n        videoToTextureMap.set(videoElement, backend2.device.importExternalTexture(externalTextureDescriptor));\n      }\n      textureInfo = {\n        width,\n        height,\n        format: null,\n        usage: null,\n        texture: videoToTextureMap.get(videoElement)\n      };\n    } else {\n      if (isVideoOrImage) {\n        if (fromPixels2DContext3 == null) {\n          fromPixels2DContext3 = document.createElement(\"canvas\").getContext(\"2d\");\n        }\n        fromPixels2DContext3.canvas.width = width;\n        fromPixels2DContext3.canvas.height = height;\n        fromPixels2DContext3.drawImage(pixels, 0, 0, width, height);\n        pixels = fromPixels2DContext3.canvas;\n      }\n      const usage = GPUTextureUsage.COPY_DST | GPUTextureUsage.RENDER_ATTACHMENT | GPUTextureUsage.TEXTURE_BINDING;\n      const format = \"rgba8unorm\";\n      const texture = backend2.textureManager.acquireTexture(outputShape[1], outputShape[0], format, usage);\n      backend2.queue.copyExternalImageToTexture({ source: pixels }, { texture }, [outputShape[1], outputShape[0]]);\n      textureInfo = { width, height, format, usage, texture };\n    }\n    const size = util_exports.sizeFromShape(outputShape);\n    const strides = util_exports.computeStrides(outputShape);\n    const program = new FromPixelsProgram2(outputShape, numChannels, importVideo);\n    const uniformData = [\n      { type: \"uint32\", data: [size] },\n      { type: \"uint32\", data: [numChannels] },\n      { type: \"uint32\", data: [...strides] }\n    ];\n    const input2 = backend2.makeTensorInfo([height, width], \"int32\");\n    const info = backend2.tensorMap.get(input2.dataId);\n    info.resourceInfo = textureInfo;\n    const result = backend2.runWebGPUProgram(program, [input2], \"int32\", uniformData);\n    backend2.disposeData(input2.dataId);\n    return result;\n  }\n  const imageData = pixels.data;\n  let pixelArray = imageData;\n  if (numChannels != null && numChannels !== 4) {\n    pixelArray = new Uint8Array(pixels.width * pixels.height * numChannels);\n    const dataLength = imageData.length;\n    let j = 0;\n    for (let i2 = 0; i2 < dataLength; i2++) {\n      if (i2 % 4 < numChannels) {\n        pixelArray[j++] = imageData[i2];\n      }\n    }\n  }\n  const output = backend2.makeTensorInfo(outputShape, \"int32\", new Int32Array(pixelArray));\n  backend2.uploadToGPU(output.dataId);\n  return output;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/batchnorm_webgpu.js\nvar BatchNormProgram2 = class {\n  constructor(xShape, meanShape, varianceShape, offsetShape, scaleShape) {\n    this.uniforms = \"varianceEpsilon : f32,\";\n    this.workGroupSize = [128, 1, 1];\n    this.size = true;\n    this.variableNames = [\"x\", \"mean\", \"variance\"];\n    backend_util_exports.assertAndGetBroadcastShape(xShape, meanShape);\n    backend_util_exports.assertAndGetBroadcastShape(xShape, varianceShape);\n    this.outputShape = xShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    if (offsetShape != null) {\n      backend_util_exports.assertAndGetBroadcastShape(xShape, offsetShape);\n      this.variableNames.push(\"offset\");\n    }\n    if (scaleShape != null) {\n      backend_util_exports.assertAndGetBroadcastShape(xShape, scaleShape);\n      this.variableNames.push(\"scale\");\n    }\n    this.offsetShape = offsetShape;\n    this.scaleShape = scaleShape;\n    this.shaderKey = \"batchNorm\";\n  }\n  getUserCode() {\n    let offsetSnippet = \"0.0\";\n    if (this.offsetShape != null) {\n      offsetSnippet = \"getOffsetByOutputIndex(index)\";\n    }\n    let scaleSnippet = \"1.0\";\n    if (this.scaleShape != null) {\n      scaleSnippet = \"getScaleByOutputIndex(index)\";\n    }\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size)\n        {\n          let xValue = getXByOutputIndex(index);\n          let meanValue = getMeanByOutputIndex(index);\n          let varianValue = getVarianceByOutputIndex(index);\n          let offsetValue = ${offsetSnippet};\n          let scaleValue = ${scaleSnippet};\n          let inv = scaleValue * inverseSqrt(varianValue + f32(uniforms.varianceEpsilon));\n          setOutputAtIndex(index,dot(vec3<f32>(xValue, -meanValue, offsetValue), vec3<f32>(inv, inv, 1.0)));\n        }\n      }\n  `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/FusedBatchNorm.js\nvar fusedBatchNormConfig2 = {\n  kernelName: FusedBatchNorm,\n  backendName: \"webgpu\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { x, scale: scale2, offset, mean: mean5, variance } = inputs;\n    const { varianceEpsilon } = attrs;\n    const webGPUBackend = backend2;\n    const batchNormInputs = [x, mean5, variance];\n    let offsetShape = null;\n    if (offset != null) {\n      offsetShape = offset.shape;\n      batchNormInputs.push(offset);\n    }\n    let scaleShape = null;\n    if (scale2 != null) {\n      scaleShape = scale2.shape;\n      batchNormInputs.push(scale2);\n    }\n    const program = new BatchNormProgram2(x.shape, mean5.shape, variance.shape, offsetShape, scaleShape);\n    const uniformData = [{ type: \"float32\", data: [varianceEpsilon] }];\n    return webGPUBackend.runWebGPUProgram(program, batchNormInputs, x.dtype, uniformData);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/FusedConv2D.js\nfunction fusedConv2d3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dataFormat, dilations, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  const $dataFormat = backend_util_exports.convertConv2DDataFormat(dataFormat);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, dilations, pad3, dimRoundingMode, false, $dataFormat);\n  return conv2DImpl({\n    x,\n    filter,\n    convInfo,\n    backend: backend2,\n    bias,\n    preluActivationWeights,\n    leakyreluAlpha,\n    activation: activation2\n  });\n}\nvar fusedConv2DConfig4 = {\n  kernelName: FusedConv2D,\n  backendName: \"webgpu\",\n  kernelFunc: fusedConv2d3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/FusedDepthwiseConv2D.js\nfunction fusedDepthwiseConv2D3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, filter, bias, preluActivationWeights } = inputs;\n  const { strides, pad: pad3, dilations, dimRoundingMode, activation: activation2, leakyreluAlpha } = attrs;\n  let $dilations = dilations;\n  if ($dilations == null) {\n    $dilations = [1, 1];\n  }\n  util_exports.assert(backend_util_exports.eitherStridesOrDilationsAreOne(strides, $dilations), () => `Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${strides} and dilations '${$dilations}'`);\n  const convInfo = backend_util_exports.computeConv2DInfo(x.shape, filter.shape, strides, $dilations, pad3, dimRoundingMode, true);\n  const programInputs = [x, filter];\n  const hasBias = bias != null;\n  const hasPreluActivationWeights = preluActivationWeights != null;\n  if (hasBias) {\n    programInputs.push(bias);\n  }\n  if (hasPreluActivationWeights) {\n    programInputs.push(preluActivationWeights);\n  }\n  const dimensions = [\n    { type: \"int32\", data: [convInfo.padInfo.top, convInfo.padInfo.left] },\n    { type: \"int32\", data: [convInfo.inHeight, convInfo.inWidth] }\n  ];\n  let program;\n  if (convInfo.inHeight > 4 && convInfo.inWidth > 4 && convInfo.strideHeight === 1 && convInfo.strideWidth === 1 && convInfo.inChannels === convInfo.outChannels && convInfo.dilationHeight === 1 && convInfo.dilationWidth === 1 && convInfo.inChannels % 4 === 0) {\n    program = new DepthwiseConv2DVec4Program(convInfo, hasBias, activation2, hasPreluActivationWeights);\n  } else {\n    program = new DepthwiseConv2DProgram2(convInfo, hasBias, activation2, hasPreluActivationWeights);\n    dimensions.push({ type: \"int32\", data: [convInfo.filterHeight] }, { type: \"int32\", data: [convInfo.filterWidth] }, { type: \"int32\", data: [convInfo.strideHeight, convInfo.strideWidth] }, {\n      type: \"int32\",\n      data: [convInfo.dilationHeight, convInfo.dilationWidth]\n    });\n  }\n  if (activation2 === \"leakyrelu\") {\n    dimensions.push({ type: \"float32\", data: [leakyreluAlpha] });\n    program.uniforms += \" alpha : f32,\";\n  }\n  const result = backend2.runWebGPUProgram(program, programInputs, \"float32\", dimensions);\n  return result;\n}\nvar fusedDepthwiseConv2DConfig4 = {\n  kernelName: FusedDepthwiseConv2D,\n  backendName: \"webgpu\",\n  kernelFunc: fusedDepthwiseConv2D3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/gather_nd_webgpu.js\nvar GatherNDProgram2 = class {\n  constructor(sliceDim, shape) {\n    this.variableNames = [\"A\", \"indices\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = shape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = `gathernd_${sliceDim}`;\n    this.sliceDim = sliceDim;\n    this.uniforms = `sliceDim : i32, strides : ${getCoordsDataType2(sliceDim)},`;\n  }\n  getUserCode() {\n    let strideString;\n    if (this.sliceDim > 1) {\n      strideString = \"uniforms.strides[j]\";\n    } else {\n      strideString = \"uniforms.strides\";\n    }\n    const userCode = `\n        ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let coords = getCoordsFromIndex(index);\n          var flattenIndex = 0;\n          for (var j = 0; j < uniforms.sliceDim; j = j + 1) {\n            let indexTemp = i32(round(getIndices(coords[0], j)));\n            let strideNum = ${strideString};\n            flattenIndex = flattenIndex + indexTemp * strideNum;\n          }\n\n          setOutputAtIndex(index, getA(flattenIndex, coords[1]));\n        }\n      }\n      `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/GatherNd.js\nfunction gatherNd4(args) {\n  const { inputs, backend: backend2 } = args;\n  const { params, indices } = inputs;\n  const indicesShape = indices.shape;\n  const sliceRank = indicesShape[indicesShape.length - 1];\n  const paramsSize = util_exports.sizeFromShape(params.shape);\n  const [resultShape, numSlices, sliceSize, strides] = backend_util_exports.prepareAndValidate(params, indices);\n  const flattenIndices = reshape6({ inputs: { x: indices }, backend: backend2, attrs: { shape: [numSlices, sliceRank] } });\n  const flattenX = reshape6({\n    inputs: { x: params },\n    backend: backend2,\n    attrs: { shape: [util_exports.sizeFromShape(params.shape) / sliceSize, sliceSize] }\n  });\n  if (backend2.shouldExecuteOnCPU([params, indices]) || params.dtype === \"string\") {\n    const indicesData = backend2.readSync(indices.dataId);\n    const paramsBuf = backend2.bufferSync(params);\n    const outValue = gatherNdImplCPU2(indicesData, paramsBuf, params.dtype, numSlices, sliceRank, sliceSize, strides, params.shape, paramsSize);\n    return backend2.makeTensorInfo(resultShape, params.dtype, outValue.values);\n  }\n  const program = new GatherNDProgram2(sliceRank, [numSlices, sliceSize]);\n  const uniformData = [{ type: \"int32\", data: [sliceRank] }, { type: \"int32\", data: strides }];\n  const res = backend2.runWebGPUProgram(program, [flattenX, flattenIndices], flattenX.dtype, uniformData);\n  const reshaped = reshape6({ inputs: { x: res }, backend: backend2, attrs: { shape: resultShape } });\n  backend2.disposeData(flattenIndices.dataId);\n  backend2.disposeData(flattenX.dataId);\n  backend2.disposeData(res.dataId);\n  return reshaped;\n}\nvar gatherNdConfig4 = {\n  kernelName: GatherNd,\n  backendName: \"webgpu\",\n  kernelFunc: gatherNd4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/gather_webgpu.js\nvar GatherProgram2 = class {\n  constructor(aShape, outputShape) {\n    this.variableNames = [\"A\", \"indices\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = aShape.slice();\n    this.aShape = aShape;\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = `gather`;\n  }\n  getUserCode() {\n    const sourceCoords = getSourceCoords4(this.aShape);\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let resRC = getCoordsFromIndex(index);\n          let indexZ = i32(getIndices(resRC.x, resRC.z));\n          let inBounds = select(0.0, 1.0, indexZ >= 0 && indexZ < uniforms.aShape[2]);\n          setOutputAtIndex(index, inBounds * getA(${sourceCoords}));\n        }\n      }\n    `;\n    return userCode;\n  }\n};\nfunction getSourceCoords4(aShape) {\n  const currentCoords = [\"resRC.x\", \"resRC.y\", \"resRC.z\", \"resRC.w\"];\n  const sourceCoords = [];\n  for (let i2 = 0; i2 < aShape.length; i2++) {\n    if (i2 === 2) {\n      sourceCoords.push(\"indexZ\");\n    } else {\n      sourceCoords.push(`${currentCoords[i2]}`);\n    }\n  }\n  return sourceCoords.join();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/GatherV2.js\nfunction gatherV24(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x, indices } = inputs;\n  const { axis, batchDims } = attrs;\n  const parsedAxis = util_exports.parseAxisParam(axis, x.shape)[0];\n  const shapeInfo = backend_util_exports.segment_util.collectGatherOpShapeInfo(x, indices, parsedAxis, batchDims);\n  const indicesSize = util_exports.sizeFromShape(indices.shape);\n  const toDispose = [];\n  const flattenX = reshape6({\n    inputs: { x },\n    backend: backend2,\n    attrs: {\n      shape: [\n        shapeInfo.batchSize,\n        shapeInfo.outerSize,\n        shapeInfo.dimSize,\n        shapeInfo.sliceSize\n      ]\n    }\n  });\n  const flattenIndex = reshape6({\n    inputs: { x: indices },\n    backend: backend2,\n    attrs: { shape: [shapeInfo.batchSize, indicesSize / shapeInfo.batchSize] }\n  });\n  toDispose.push(flattenX);\n  toDispose.push(flattenIndex);\n  const flattenOutputShape = [\n    shapeInfo.batchSize,\n    shapeInfo.outerSize,\n    indicesSize / shapeInfo.batchSize,\n    shapeInfo.sliceSize\n  ];\n  if (backend2.shouldExecuteOnCPU([x, indices])) {\n    const indicesBufferInfo = backend2.tensorMap.get(flattenIndex.dataId);\n    const indicesValues = indicesBufferInfo.values;\n    const indicesBuf = buffer(flattenIndex.shape, flattenIndex.dtype, indicesValues);\n    const xBufferInfo = backend2.tensorMap.get(flattenX.dataId);\n    const xValues = xBufferInfo.values;\n    const xBuf = buffer(flattenX.shape, flattenX.dtype, xValues);\n    const outBuf = gatherV2ImplCPU2(xBuf, indicesBuf, flattenOutputShape);\n    toDispose.forEach((t2) => backend2.disposeData(t2.dataId));\n    return backend2.makeTensorInfo(shapeInfo.outputShape, outBuf.dtype, outBuf.values);\n  }\n  const program = new GatherProgram2(flattenX.shape, flattenOutputShape);\n  const res = backend2.runWebGPUProgram(program, [flattenX, flattenIndex], flattenX.dtype);\n  toDispose.push(res);\n  const reshaped = reshape6({ inputs: { x: res }, backend: backend2, attrs: { shape: shapeInfo.outputShape } });\n  toDispose.forEach((t2) => backend2.disposeData(t2.dataId));\n  return reshaped;\n}\nvar gatherV2Config4 = {\n  kernelName: GatherV2,\n  backendName: \"webgpu\",\n  kernelFunc: gatherV24\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Greater.js\nvar greater5 = binaryKernelFunc3({\n  opType: BinaryOpType.GREATER,\n  cpuKernelImpl: greaterImplCPU2,\n  dtype: \"bool\"\n});\nvar greaterConfig4 = {\n  kernelName: Greater,\n  backendName: \"webgpu\",\n  kernelFunc: greater5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/GreaterEqual.js\nvar greaterEqual4 = binaryKernelFunc3({\n  opType: BinaryOpType.GREATER_EQUAL,\n  dtype: \"bool\",\n  cpuKernelImpl: greaterEqualImplCPU2\n});\nvar greaterEqualConfig4 = {\n  kernelName: GreaterEqual,\n  backendName: \"webgpu\",\n  kernelFunc: greaterEqual4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/LeakyRelu.js\nfunction leakyRelu5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { alpha } = attrs;\n  const uniformData = [{ type: \"float32\", data: [alpha] }];\n  const program = new UnaryOpProgram2(x.shape, UnaryOpType.LEAKYRELU);\n  program.uniforms = \"alpha : f32,\";\n  return backend2.runWebGPUProgram(program, [x], \"float32\", uniformData);\n}\nvar leakyReluConfig4 = {\n  kernelName: LeakyRelu,\n  backendName: \"webgpu\",\n  kernelFunc: leakyRelu5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Less.js\nvar less5 = binaryKernelFunc3({ opType: BinaryOpType.LESS, dtype: \"bool\", cpuKernelImpl: lessImplCPU2 });\nvar lessConfig4 = {\n  kernelName: Less,\n  backendName: \"webgpu\",\n  kernelFunc: less5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/LessEqual.js\nvar lessEqual4 = binaryKernelFunc3({\n  opType: BinaryOpType.LESS_EQUAL,\n  dtype: \"bool\",\n  cpuKernelImpl: lessEqualImplCPU2\n});\nvar lessEqualConfig4 = {\n  kernelName: LessEqual,\n  backendName: \"webgpu\",\n  kernelFunc: lessEqual4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Log.js\nvar log5 = unaryKernelFunc3({ opType: UnaryOpType.LOG, cpuKernelImpl: logImplCPU2 });\nvar logConfig4 = {\n  kernelName: Log,\n  backendName: \"webgpu\",\n  kernelFunc: log5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/LogicalAnd.js\nvar logicalAnd4 = binaryKernelFunc3({ opType: BinaryOpType.LOGICAL_AND, dtype: \"bool\" });\nvar logicalAndConfig4 = {\n  kernelName: LogicalAnd,\n  backendName: \"webgpu\",\n  kernelFunc: logicalAnd4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/LogicalNot.js\nvar logicalNot4 = unaryKernelFunc3({ opType: UnaryOpType.LOGICAL_NOT });\nvar logicalNotConfig4 = {\n  kernelName: LogicalNot,\n  backendName: \"webgpu\",\n  kernelFunc: logicalNot4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Max.js\nfunction max6(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { reductionIndices, keepDims } = attrs;\n  return reduce2(x, reductionIndices, keepDims, \"max\", backend2);\n}\nvar maxConfig4 = {\n  kernelName: Max,\n  backendName: \"webgpu\",\n  kernelFunc: max6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Maximum.js\nvar maximum5 = binaryKernelFunc3({\n  opType: BinaryOpType.MAX,\n  cpuKernelImpl: maximumImplCPU2\n});\nvar maximumConfig4 = {\n  kernelName: Maximum,\n  backendName: \"webgpu\",\n  kernelFunc: maximum5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/MaxPool.js\nfunction maxPool5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { filterSize, strides, pad: pad3, dimRoundingMode } = attrs;\n  const dilations = 1;\n  const convInfo = backend_util_exports.computePool2DInfo(x.shape, filterSize, strides, dilations, pad3, dimRoundingMode);\n  let program;\n  const dimensions = [];\n  if (convInfo.filterHeight === 1 && convInfo.filterWidth === 1) {\n    if (util_exports.arraysEqual(convInfo.inShape, convInfo.outShape)) {\n      return identity5({ inputs: { x }, backend: backend2 });\n    }\n    program = new PoolWithFilterSizeEqualsOneProgram(convInfo);\n    dimensions.push({ type: \"int32\", data: [convInfo.strideHeight, convInfo.strideWidth] });\n  } else {\n    program = new Pool2DProgram2(convInfo, \"max\");\n    dimensions.push({ type: \"int32\", data: [convInfo.strideHeight, convInfo.strideWidth] }, { type: \"int32\", data: [convInfo.padInfo.top, convInfo.padInfo.left] }, {\n      type: \"int32\",\n      data: [convInfo.dilationHeight, convInfo.dilationWidth]\n    }, { type: \"int32\", data: [convInfo.inHeight, convInfo.inWidth] }, {\n      type: \"int32\",\n      data: [convInfo.effectiveFilterHeight, convInfo.effectiveFilterWidth]\n    });\n  }\n  return backend2.runWebGPUProgram(program, [x], x.dtype, dimensions);\n}\nvar maxPoolConfig4 = {\n  kernelName: MaxPool,\n  backendName: \"webgpu\",\n  kernelFunc: maxPool5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Mean.js\nfunction mean4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { keepDims, axis } = attrs;\n  return reduce2(x, axis, keepDims, \"mean\", backend2);\n}\nvar meanConfig4 = {\n  kernelName: Mean,\n  backendName: \"webgpu\",\n  kernelFunc: mean4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Min.js\nfunction min6(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  return reduce2(x, axis, keepDims, \"min\", backend2);\n}\nvar minConfig4 = {\n  kernelName: Min,\n  backendName: \"webgpu\",\n  kernelFunc: min6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Minimum.js\nvar minimum5 = binaryKernelFunc3({\n  opType: BinaryOpType.MIN,\n  cpuKernelImpl: minimumImplCPU2\n});\nvar minimumConfig4 = {\n  kernelName: Minimum,\n  backendName: \"webgpu\",\n  kernelFunc: minimum5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/mirror_pad_webgpu.js\nvar MirrorPadProgram2 = class {\n  constructor(xShape, paddings, mode) {\n    this.uniforms = \"\";\n    this.variableNames = [\"x\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = paddings.map((p2, i2) => p2[0] + xShape[i2] + p2[1]);\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.xShape = xShape;\n    paddings.map((_, i2) => {\n      this.uniforms += ` pad${i2} : vec2<i32>,`;\n    });\n    this.offset = mode === \"reflect\" ? 0 : 1;\n    this.shaderKey = `mirrorPad_${mode}`;\n  }\n  getUserCode() {\n    const rank = this.xShape.length;\n    const start = this.xShape.map((_, i2) => `uniforms.pad${i2}[0]`).join(\",\");\n    const end = this.xShape.map((_, i2) => `uniforms.pad${i2}[0] + uniforms.xShape${rank > 1 ? `[${i2}]` : \"\"}`).join(\",\");\n    const shaderStart = rank === 1 ? \"start\" : \"start[i]\";\n    const shaderEnd = rank === 1 ? \"end\" : \"end[i]\";\n    const shaderOutC = rank === 1 ? \"outC\" : \"outC[i]\";\n    const dtype = getCoordsDataType2(rank);\n    const unpackedCoords = rank > 1 ? [\"coords[0]\", \"coords[1]\", \"coords[2]\", \"coords[3]\"].slice(0, rank) : \"coords\";\n    return `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let start = ${dtype}(${start});\n          let end = ${dtype}(${end});\n          var outC = getCoordsFromIndex(index);\n          for (var i = 0; i < ${rank}; i = i + 1) {\n            if (${shaderOutC} < ${shaderStart}) {\n              ${shaderOutC} = ${shaderStart} * 2 - ${shaderOutC} - ${this.offset};\n            } else if(${shaderOutC} >= ${shaderEnd}) {\n              ${shaderOutC} = (${shaderEnd} - 1) * 2 - ${shaderOutC} + ${this.offset};\n            }\n          }\n          let coords = outC - start;\n          setOutputAtIndex(index, getX(${unpackedCoords}));\n        }\n      }\n    `;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/MirrorPad.js\nvar mirrorPadConfig4 = {\n  kernelName: MirrorPad,\n  backendName: \"webgpu\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { x } = inputs;\n    const { paddings, mode } = attrs;\n    const webGPUBackend = backend2;\n    const uniformData = paddings.map((p2) => {\n      return { type: \"int32\", data: [p2[0], p2[1]] };\n    });\n    const program = new MirrorPadProgram2(x.shape, paddings, mode);\n    const output = webGPUBackend.runWebGPUProgram(program, [x], x.dtype, uniformData);\n    return output;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Neg.js\nfunction neg4(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (backend2.shouldExecuteOnCPU([x])) {\n    const xData = backend2.tensorMap.get(x.dataId);\n    const [outValues, newShape] = negImplCPU2(xData.values, x.shape, x.dtype);\n    return backend2.makeTensorInfo(newShape, x.dtype, outValues);\n  }\n  const program = new UnaryOpProgram2(x.shape, UnaryOpType.NEG);\n  return backend2.runWebGPUProgram(program, [x], x.dtype);\n}\nvar negConfig4 = {\n  kernelName: Neg,\n  backendName: \"webgpu\",\n  kernelFunc: neg4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/NonMaxSuppressionV3.js\nfunction nonMaxSuppressionV33(args) {\n  console.warn(\"tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead\");\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold } = attrs;\n  const boxesVals = backend2.readSync(boxes.dataId);\n  const scoresVals = backend2.readSync(scores.dataId);\n  const { selectedIndices } = kernel_impls_exports.nonMaxSuppressionV3Impl(boxesVals, scoresVals, maxOutputSize, iouThreshold, scoreThreshold);\n  return backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices));\n}\nvar nonMaxSuppressionV3Config4 = {\n  kernelName: NonMaxSuppressionV3,\n  backendName: \"webgpu\",\n  kernelFunc: nonMaxSuppressionV33\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/NonMaxSuppressionV5.js\nfunction nonMaxSuppressionV53(args) {\n  console.warn(\"tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead\");\n  const { inputs, backend: backend2, attrs } = args;\n  const { boxes, scores } = inputs;\n  const { maxOutputSize, iouThreshold, scoreThreshold, softNmsSigma } = attrs;\n  const boxesVals = backend2.readSync(boxes.dataId);\n  const scoresVals = backend2.readSync(scores.dataId);\n  const maxOutputSizeVal = maxOutputSize;\n  const iouThresholdVal = iouThreshold;\n  const scoreThresholdVal = scoreThreshold;\n  const softNmsSigmaVal = softNmsSigma;\n  const { selectedIndices, selectedScores } = kernel_impls_exports.nonMaxSuppressionV5Impl(boxesVals, scoresVals, maxOutputSizeVal, iouThresholdVal, scoreThresholdVal, softNmsSigmaVal);\n  return [\n    backend2.makeTensorInfo([selectedIndices.length], \"int32\", new Int32Array(selectedIndices)),\n    backend2.makeTensorInfo([selectedScores.length], \"float32\", new Float32Array(selectedScores))\n  ];\n}\nvar nonMaxSuppressionV5Config4 = {\n  kernelName: NonMaxSuppressionV5,\n  backendName: \"webgpu\",\n  kernelFunc: nonMaxSuppressionV53\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ZerosLike.js\nfunction zerosLike5(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (x.dtype === \"complex64\") {\n    const realPart = real4({ inputs: { input: x }, backend: backend2 });\n    const r2 = zerosLike5({ inputs: { x: realPart }, backend: backend2 });\n    const imagPart = imag4({ inputs: { input: x }, backend: backend2 });\n    const i2 = zerosLike5({ inputs: { x: imagPart }, backend: backend2 });\n    const result = complex4({ inputs: { real: r2, imag: i2 }, backend: backend2 });\n    backend2.disposeData(realPart.dataId);\n    backend2.disposeData(r2.dataId);\n    backend2.disposeData(imagPart.dataId);\n    backend2.disposeData(i2.dataId);\n    return result;\n  } else {\n    return fill5({\n      attrs: {\n        shape: x.shape,\n        dtype: x.dtype,\n        value: x.dtype === \"string\" ? \"\" : 0\n      },\n      backend: backend2\n    });\n  }\n}\nvar zerosLikeConfig4 = {\n  kernelName: ZerosLike,\n  backendName: \"webgpu\",\n  kernelFunc: zerosLike5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/OnesLike.js\nfunction onesLike5(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x } = inputs;\n  if (x.dtype === \"string\") {\n    throw new Error(\"onesLike is not supported under string dtype\");\n  } else if (x.dtype === \"complex64\") {\n    const realPart = real4({ inputs: { input: x }, backend: backend2 });\n    const r2 = onesLike5({ inputs: { x: realPart }, backend: backend2 });\n    const imagPart = imag4({ inputs: { input: x }, backend: backend2 });\n    const i2 = zerosLike5({ inputs: { x: imagPart }, backend: backend2 });\n    const result = complex4({ inputs: { real: r2, imag: i2 }, backend: backend2 });\n    backend2.disposeData(realPart.dataId);\n    backend2.disposeData(r2.dataId);\n    backend2.disposeData(imagPart.dataId);\n    backend2.disposeData(i2.dataId);\n    return result;\n  } else {\n    return fill5({ attrs: { shape: x.shape, dtype: x.dtype, value: 1 }, backend: backend2 });\n  }\n}\nvar onesLikeConfig4 = {\n  kernelName: OnesLike,\n  backendName: \"webgpu\",\n  kernelFunc: onesLike5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Pack.js\nfunction pack4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { axis } = attrs;\n  if (inputs.length === 1) {\n    return expandDims6({ inputs: { input: inputs[0] }, backend: backend2, attrs: { dim: axis } });\n  }\n  const shape = inputs[0].shape;\n  const dtype = inputs[0].dtype;\n  inputs.forEach((t2) => {\n    util_exports.assertShapesMatch(shape, t2.shape, \"All tensors passed to stack must have matching shapes\");\n    util_exports.assert(dtype === t2.dtype, () => \"All tensors passed to stack must have matching dtypes\");\n  });\n  const intermediateTensorInfos = [];\n  const expandedTensors = inputs.map((t2) => {\n    const expandedT = expandDims6({ inputs: { input: t2 }, backend: backend2, attrs: { dim: axis } });\n    intermediateTensorInfos.push(expandedT);\n    return expandedT;\n  });\n  const result = concat5({ inputs: expandedTensors, backend: backend2, attrs: { axis } });\n  intermediateTensorInfos.forEach((t2) => backend2.disposeData(t2.dataId));\n  return result;\n}\nvar packConfig4 = {\n  kernelName: Pack,\n  backendName: \"webgpu\",\n  kernelFunc: pack4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/pad_webgpu.js\nvar PadProgram2 = class {\n  constructor(xShape, paddings) {\n    this.variableNames = [\"x\"];\n    this.uniforms = \"constantValue : f32,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = paddings.map((p2, i2) => p2[0] + xShape[i2] + p2[1]);\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    paddings.map((_, i2) => {\n      this.uniforms += ` pad${i2} : vec2<i32>,`;\n    });\n    this.xShape = xShape;\n    this.shaderKey = \"pad\";\n  }\n  getUserCode() {\n    const rank = this.xShape.length;\n    const type = getCoordsDataType2(rank);\n    const start = this.xShape.map((_, i2) => `uniforms.pad${i2}[0]`).join(\",\");\n    const end = this.xShape.map((_, i2) => `uniforms.pad${i2}[0] + uniforms.xShape${rank > 1 ? `[${i2}]` : \"\"}`).join(\",\");\n    const startValue = rank > 1 ? `${type}(${start})` : `${start}`;\n    const endValue = rank > 1 ? `${type}(${end})` : `${end}`;\n    const leftPadCondition = rank > 1 ? `any(outC < start)` : `outC < start`;\n    const rightPadCondition = rank > 1 ? `any(outC >= end)` : `outC >= end`;\n    const unpackedCoords = rank > 1 ? [\"coords[0]\", \"coords[1]\", \"coords[2]\", \"coords[3]\"].slice(0, rank) : \"coords\";\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let start = ${startValue};\n          let end = ${endValue};\n          let outC = getCoordsFromIndex(index);\n\n          if (${leftPadCondition} || ${rightPadCondition}) {\n            setOutputAtIndex(index, uniforms.constantValue);\n          } else {\n            let coords = outC - start;\n            setOutputAtIndex(index, getX(${unpackedCoords}));\n          }\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/PadV2.js\nvar padV23 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { paddings, constantValue } = attrs;\n  if (paddings.every((p2) => util_exports.arraysEqual(p2, [0, 0]))) {\n    return identity5({ inputs: { x }, backend: backend2 });\n  }\n  if (util_exports.sizeFromShape(x.shape) === 0) {\n    const outputShape = paddings.map((p2, i2) => p2[0] + x.shape[i2] + p2[1]);\n    return fill5({\n      backend: backend2,\n      attrs: { shape: outputShape, value: constantValue, dtype: x.dtype }\n    });\n  }\n  const uniformData = [{ type: \"float32\", data: [constantValue] }];\n  paddings.map((p2) => uniformData.push({ type: \"int32\", data: [p2[0], p2[1]] }));\n  const program = new PadProgram2(x.shape, paddings);\n  return backend2.runWebGPUProgram(program, [x], x.dtype, uniformData);\n};\nvar padV2Config4 = {\n  kernelName: PadV2,\n  backendName: \"webgpu\",\n  kernelFunc: padV23\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Pow.js\nvar pow4 = binaryKernelFunc3({\n  opType: BinaryOpType.POW\n});\nvar powConfig4 = {\n  kernelName: Pow,\n  backendName: \"webgpu\",\n  kernelFunc: pow4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Prelu.js\nfunction prelu6(args) {\n  const { inputs, backend: backend2 } = args;\n  const { x, alpha } = inputs;\n  const program = new BinaryOpProgram2(BinaryOpType.PRELU, x.shape, alpha.shape);\n  return backend2.runWebGPUProgram(program, [x, alpha], \"float32\");\n}\nvar preluConfig4 = {\n  kernelName: Prelu,\n  backendName: \"webgpu\",\n  kernelFunc: prelu6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Prod.js\nfunction prod5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { axis, keepDims } = attrs;\n  return reduce2(x, axis, keepDims, \"prod\", backend2);\n}\nvar prodConfig4 = {\n  kernelName: Prod,\n  backendName: \"webgpu\",\n  kernelFunc: prod5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Range.js\nvar range6 = (args) => {\n  const { backend: backend2, attrs } = args;\n  const { start, stop, step: step5, dtype } = attrs;\n  const values = rangeImplCPU2(start, stop, step5, dtype);\n  return backend2.makeTensorInfo([values.length], dtype, values);\n};\nvar rangeConfig4 = {\n  kernelName: Range,\n  backendName: \"webgpu\",\n  kernelFunc: range6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/RealDiv.js\nvar realDiv2 = binaryKernelFunc3({ opType: BinaryOpType.DIV });\nvar realDivConfig4 = {\n  kernelName: RealDiv,\n  backendName: \"webgpu\",\n  kernelFunc: realDiv2\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Relu.js\nvar relu4 = unaryKernelFunc3({ opType: UnaryOpType.RELU });\nvar reluConfig4 = {\n  kernelName: Relu,\n  backendName: \"webgpu\",\n  kernelFunc: relu4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Relu6.js\nvar relu64 = unaryKernelFunc3({ opType: UnaryOpType.RELU6 });\nvar relu6Config4 = {\n  kernelName: Relu6,\n  backendName: \"webgpu\",\n  kernelFunc: relu64\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/resize_bilinear_webgpu.js\nvar ResizeBilinearProgram2 = class {\n  constructor(inputShape, newHeight, newWidth) {\n    this.variableNames = [\"x\"];\n    this.uniforms = \"adjustHeightWidth : vec2<f32>, halfPixelCenters : f32,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = [inputShape[0], newHeight, newWidth, inputShape[3]];\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = `resizeBilinear`;\n  }\n  getUserCode() {\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n        let coords = getCoordsFromIndex(index);\n          let b = coords[0];\n          let d = coords[3];\n          let rc = coords.yz;\n\n          let effectiveInSize = vec2<f32>(\n            f32(uniforms.xShape.y) - uniforms.adjustHeightWidth[0],\n            f32(uniforms.xShape.z) - uniforms.adjustHeightWidth[1]);\n\n          let effectiveOutSize = vec2<f32>(\n            f32(uniforms.outShape.y) - uniforms.adjustHeightWidth[0],\n            f32(uniforms.outShape.z) - uniforms.adjustHeightWidth[1]);\n\n          let effectiveInputOverOutputRatioRC =\n              effectiveInSize / effectiveOutSize;\n\n          // Fractional source index\n          let sourceFracIndexRC =\n            (vec2<f32>(rc) + vec2<f32>(uniforms.halfPixelCenters)) *\n            effectiveInputOverOutputRatioRC - vec2<f32>(uniforms.halfPixelCenters);\n\n          // Compute the four integer indices.\n          let sourceFloorRC = vec2<i32>(sourceFracIndexRC);\n          let sourceCeilRC = vec2<i32>(\n            min(vec2<f32>(uniforms.xShape.yz) - vec2<f32>(1.0), ceil(sourceFracIndexRC)));\n\n          let topLeft = getX(b, sourceFloorRC.x, sourceFloorRC.y, d);\n          let bottomLeft = getX(b, sourceCeilRC.x, sourceFloorRC.y, d);\n          let topRight = getX(b, sourceFloorRC.x, sourceCeilRC.y, d);\n          let bottomRight = getX(b, sourceCeilRC.x, sourceCeilRC.y, d);\n\n          let fracRC = sourceFracIndexRC - vec2<f32>(sourceFloorRC);\n\n          let top = topLeft + (topRight - topLeft) * fracRC.y;\n          let bottom = bottomLeft + (bottomRight - bottomLeft) * fracRC.y;\n          let newValue = top + (bottom - top) * fracRC.x;\n\n          setOutputAtIndex(index, newValue);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ResizeBilinear.js\nfunction resizeBilinear5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, size, halfPixelCenters } = attrs;\n  const [newHeight, newWidth] = size;\n  const adjustHeight = alignCorners && newHeight > 1 ? 1 : 0;\n  const adjustWidth = alignCorners && newWidth > 1 ? 1 : 0;\n  const halfPixelCentersValue = halfPixelCenters ? 0.5 : 0;\n  const uniformData = [\n    { type: \"float32\", data: [adjustHeight, adjustWidth] },\n    { type: \"float32\", data: [halfPixelCentersValue] }\n  ];\n  const program = new ResizeBilinearProgram2(images.shape, newHeight, newWidth);\n  return backend2.runWebGPUProgram(program, [images], \"float32\", uniformData);\n}\nvar resizeBilinearConfig4 = {\n  kernelName: ResizeBilinear,\n  backendName: \"webgpu\",\n  kernelFunc: resizeBilinear5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/resize_nearest_neighbor_webgpu.js\nvar ResizeNearestNeighborProgram2 = class {\n  constructor(inputShape, newHeight, newWidth, halfPixelCenters) {\n    this.variableNames = [\"x\"];\n    this.uniforms = \"adjustHeightWidth : vec2<f32>, roundBase : f32,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = [inputShape[0], newHeight, newWidth, inputShape[3]];\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.halfPixelCenters = halfPixelCenters;\n    this.shaderKey = `resizeNearest_${halfPixelCenters}`;\n  }\n  getUserCode() {\n    let sourceFracIndexRC;\n    if (this.halfPixelCenters) {\n      sourceFracIndexRC = `max((vec2<f32>(rc) + vec2<f32>(0.5)) * effectiveInputOverOutputRatioRC, vec2<f32>(0.0))`;\n    } else {\n      sourceFracIndexRC = `vec2<f32>(rc) * effectiveInputOverOutputRatioRC`;\n    }\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let coords = getCoordsFromIndex(index);\n          let b = coords[0];\n          let d = coords[3];\n          let rc = coords.yz;\n\n          let effectiveInSize = vec2<f32>(\n            f32(uniforms.xShape.y) - uniforms.adjustHeightWidth[0],\n            f32(uniforms.xShape.z) - uniforms.adjustHeightWidth[1]);\n\n          let effectiveOutSize = vec2<f32>(\n            f32(uniforms.outShape.y) - uniforms.adjustHeightWidth[0],\n            f32(uniforms.outShape.z) - uniforms.adjustHeightWidth[1]);\n\n          let effectiveInputOverOutputRatioRC =\n              effectiveInSize / effectiveOutSize;\n\n          // Fractional source index\n          let sourceFracIndexRC = ${sourceFracIndexRC};\n\n          // Compute the coordinators of nearest neighbor point.\n          let inputShapeRC = vec2<f32>(f32(uniforms.xShape.y), f32(uniforms.xShape.z));\n          let sourceNearestRC = vec2<i32>(\n            min(inputShapeRC - 1.0, floor(sourceFracIndexRC + uniforms.roundBase)));\n          let newValue = getX(b, sourceNearestRC.x, sourceNearestRC.y, d);\n\n          setOutputAtIndex(index, newValue);\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ResizeNearestNeighbor.js\nfunction resizeNearestNeighbor5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { images } = inputs;\n  const { alignCorners, halfPixelCenters, size } = attrs;\n  const [newHeight, newWidth] = size;\n  const adjustHeight = alignCorners && newHeight > 1 ? 1 : 0;\n  const adjustWidth = alignCorners && newWidth > 1 ? 1 : 0;\n  const roundBase = alignCorners ? 0.5 : 0;\n  const uniformData = [\n    { type: \"float32\", data: [adjustHeight, adjustWidth] },\n    { type: \"float32\", data: [roundBase] }\n  ];\n  const program = new ResizeNearestNeighborProgram2(images.shape, newHeight, newWidth, halfPixelCenters);\n  return backend2.runWebGPUProgram(program, [images], images.dtype, uniformData);\n}\nvar resizeNearestNeighborConfig4 = {\n  kernelName: ResizeNearestNeighbor,\n  backendName: \"webgpu\",\n  kernelFunc: resizeNearestNeighbor5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/rotate_webgpu.js\nvar RotateProgram2 = class {\n  constructor(imageShape, fillValue) {\n    this.outputShape = [];\n    this.variableNames = [\"x\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = imageShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.uniforms = `centerX : f32, centerY : f32, sinRadians : f32,\n          cosRadians : f32,`;\n    this.shaderKey = \"rotate\";\n    this.outputShape = imageShape;\n    if (typeof fillValue === \"number\") {\n      this.uniforms += ` fillValue : f32,`;\n      this.fillSnippet = `var outputValue = uniforms.fillValue;`;\n      this.shaderKey += \"_float\";\n    } else {\n      this.uniforms += ` fillValue : vec3<f32>,`;\n      this.fillSnippet = `var outputValue = uniforms.fillValue[coords[3]];`;\n      this.shaderKey += \"_vec3\";\n    }\n  }\n  getUserCode() {\n    const userCode = `\n        ${getMainHeaderAndGlobalIndexString()}\n\n          if (index < uniforms.size) {\n            let coords = getCoordsFromIndex(index);\n            let coordXFloat = (f32(coords[2]) - uniforms.centerX) *\n                uniforms.cosRadians - (f32(coords[1]) - uniforms.centerY) *\n                uniforms.sinRadians;\n            let coordYFloat = (f32(coords[2]) - uniforms.centerX) *\n                uniforms.sinRadians + (f32(coords[1]) - uniforms.centerY) *\n                uniforms.cosRadians;\n            let coordX = i32(round(coordXFloat + uniforms.centerX));\n            let coordY = i32(round(coordYFloat + uniforms.centerY));\n            ${this.fillSnippet}\n            if(coordX >= 0 && coordX < uniforms.xShape[2] && coordY >= 0 &&\n                coordY < uniforms.xShape[1]) {\n              outputValue = getX(coords[0], coordY, coordX, coords[3]);\n            }\n            setOutputAtIndex(index, outputValue);\n          }\n        }\n      `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/RotateWithOffset.js\nvar rotateWithOffsetConfig4 = {\n  kernelName: RotateWithOffset,\n  backendName: \"webgpu\",\n  kernelFunc: ({ inputs, attrs, backend: backend2 }) => {\n    const { image: image2 } = inputs;\n    const { radians, fillValue, center } = attrs;\n    const webgpuBackend = backend2;\n    const program = new RotateProgram2(image2.shape, fillValue);\n    const [centerX, centerY] = backend_util_exports.getImageCenter(center, image2.shape[1], image2.shape[2]);\n    const uniformData = [\n      { type: \"float32\", data: [centerX] },\n      { type: \"float32\", data: [centerY] },\n      { type: \"float32\", data: [Math.sin(radians)] },\n      { type: \"float32\", data: [Math.cos(radians)] }\n    ];\n    if (typeof fillValue === \"number\") {\n      uniformData.push({ type: \"float32\", data: [Number.parseFloat(fillValue.toFixed(2))] });\n    } else {\n      uniformData.push({ type: \"float32\", data: fillValue });\n    }\n    const output = webgpuBackend.runWebGPUProgram(program, [image2], image2.dtype, uniformData);\n    return output;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Rsqrt.js\nvar rsqrt4 = unaryKernelFunc3({ opType: UnaryOpType.RSQRT, cpuKernelImpl: rsqrtImplCPU2 });\nvar rsqrtConfig4 = {\n  kernelName: Rsqrt,\n  backendName: \"webgpu\",\n  kernelFunc: rsqrt4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/scatter_optimized_webgpu.js\nvar ScatterOptimizedProgram = class {\n  constructor(flattenXShape, sliceDim, indicesRank, updatesRank, strides, shape, outputDtype, sumDupeIndices = true) {\n    this.variableNames = [\"updates\", \"indices\"];\n    this.workGroupSize = [64, 1, 1];\n    this.atomic = true;\n    this.outputShape = shape;\n    this.type = outputDtype;\n    this.sumDupeIndices = sumDupeIndices;\n    this.dispatchLayout = flatDispatchLayout(flattenXShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, flattenXShape, this.workGroupSize);\n    this.sliceDimGreaterThanOne = sliceDim > 1;\n    this.shaderKey = `scatter_${indicesRank}_${updatesRank}_${this.sliceDimGreaterThanOne}_${outputDtype}_${sumDupeIndices}`;\n    const stridesType = getCoordsDataType2(strides.length);\n    this.uniforms = `sliceDim : i32, strides: ${stridesType}, size: i32,`;\n    this.updatesRank = updatesRank;\n    this.indicesRank = indicesRank;\n  }\n  getUserCode() {\n    let indicesString = \"\";\n    if (this.indicesRank === 1) {\n      indicesString = \"coords[0]\";\n    } else if (this.indicesRank === 2) {\n      indicesString = \"coords[0], j\";\n    }\n    const indicesSnippet = `getIndices(${indicesString})`;\n    const strideString = this.sliceDimGreaterThanOne ? \"uniforms.strides[j]\" : \"uniforms.strides\";\n    let outCoordsString = \"\";\n    let getUpdatesCoordsFromFlatIndex = \"\";\n    if (this.dispatchLayout.x.length === 1) {\n      outCoordsString = \"flattenedIndex\";\n      getUpdatesCoordsFromFlatIndex = `\n      fn getUpdatesCoordsFromFlatIndex(index : i32) -> i32 {\n        return index;\n      }\n      `;\n    } else if (this.dispatchLayout.x.length === 2) {\n      outCoordsString = \"vec2<i32>(flattenedIndex, coords[1])\";\n      getUpdatesCoordsFromFlatIndex = `\n      fn getUpdatesCoordsFromFlatIndex(index : i32) -> vec2<i32> {\n        // N.B. |updates| could be a scalar tensor, conceptually representing a\n        // 2D tensor with all values equal to that. By design, its size must be\n        // the same as |outShape[1]| in one dimension, and |indicesShape[0]|\n        // gives the other.\n        let sliceSize = uniforms.outShape[1];\n        let d0 = index / sliceSize;\n        let d1 = index - d0 * sliceSize;\n        return vec2<i32>(d0, d1);\n      }\n      `;\n    }\n    const updatesString = Array.from({ length: this.updatesRank }, (_, idx) => `coords[${idx}]`);\n    const updatesSnippet = `getUpdates(${updatesString.join(\", \")})`;\n    const atomicRMW = (ptr, val) => {\n      let atomicAddSnippet = `atomicAdd(${ptr}, bitcast<i32>(${val}))`;\n      if (this.type === \"float32\") {\n        atomicAddSnippet = `\n          {\n            var oldBits = 0;\n            var newBits = bitcast<i32>(${val});\n            loop {\n              let info = atomicCompareExchangeWeak(${ptr}, oldBits, newBits);\n              if (info.exchanged) {\n                break;\n              }\n              oldBits = info.old_value;\n              let oldValue = bitcast<f32>(oldBits);\n              let newValue = oldValue + (${val});\n              newBits = bitcast<i32>(newValue);\n            }\n          }\n        `;\n      }\n      const atomicStoreSnippet = `atomicStore(${ptr}, bitcast<i32>(${val}));`;\n      return this.sumDupeIndices ? atomicAddSnippet : atomicStoreSnippet;\n    };\n    const userCode = `\n    ${getUpdatesCoordsFromFlatIndex}\n\n      ${getMainHeaderAndGlobalIndexString()}\n\n        if (index < uniforms.size) {\n          let coords = getUpdatesCoordsFromFlatIndex(index);\n          var flattenedIndex = 0;\n          for (var j = 0; j < uniforms.sliceDim; j = j + 1) {\n            let indexInside = i32(round(${indicesSnippet}));\n            flattenedIndex = flattenedIndex + indexInside * ${strideString};\n          }\n          let updateValue =\n              ${mapToWgslTypes(this.type, false)}(${updatesSnippet});\n          let flatIndex = getOutputIndexFromCoords(${outCoordsString});\n\n          ${atomicRMW(\"&result[flatIndex]\", \"updateValue\")};\n        }\n      }`;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/ScatterNd.js\nfunction scatterNd4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { indices, updates } = inputs;\n  const { shape } = attrs;\n  const { sliceRank, numUpdates, sliceSize, strides, outputSize } = backend_util_exports.calculateShapes(updates, indices, shape);\n  const flattenShape = [outputSize / sliceSize, sliceSize];\n  if (outputSize === 0) {\n    return backend2.makeTensorInfo(shape, indices.dtype);\n  }\n  const flattenIndices = reshape6({ inputs: { x: indices }, backend: backend2, attrs: { shape: [numUpdates, sliceRank] } });\n  const flattenX = reshape6({ inputs: { x: updates }, backend: backend2, attrs: { shape: [numUpdates, sliceSize] } });\n  const type = flattenX.dtype;\n  const output = fill5({ backend: backend2, attrs: { shape: flattenShape, value: 0, dtype: type } });\n  const size = util_exports.sizeFromShape(flattenX.shape);\n  const uniformData = [\n    { type: \"int32\", data: [sliceRank] },\n    { type: \"int32\", data: strides },\n    { type: \"int32\", data: [size] }\n  ];\n  const program = new ScatterOptimizedProgram(flattenX.shape, sliceRank, flattenIndices.shape.length, flattenX.shape.length, strides, flattenShape, type);\n  const res = backend2.runWebGPUProgram(program, [flattenX, flattenIndices], type, uniformData, output);\n  const reshaped = reshape6({ inputs: { x: res }, backend: backend2, attrs: { shape } });\n  backend2.disposeData(flattenIndices.dataId);\n  backend2.disposeData(flattenX.dataId);\n  backend2.disposeData(res.dataId);\n  return reshaped;\n}\nvar scatterNdConfig4 = {\n  kernelName: ScatterNd,\n  backendName: \"webgpu\",\n  kernelFunc: scatterNd4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/select_webgpu.js\nvar SelectProgram2 = class {\n  constructor(cRank, shape, rank) {\n    this.variableNames = [\"c\", \"a\", \"b\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = shape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.cRank = cRank;\n    this.rank = rank;\n    this.shaderKey = \"select\";\n  }\n  getUserCode() {\n    let cCoords;\n    let abCoords;\n    if (this.rank > 4) {\n      throw Error(`Where for rank ${this.rank} is not yet supported`);\n    }\n    if (this.rank === 1) {\n      abCoords = `resRC`;\n      cCoords = `resRC`;\n    } else {\n      const currentCoords = [\"resRC.x\", \"resRC.y\", \"resRC.z\", \"resRC.w\"];\n      const cCoordVars = [];\n      const abCoordVars = [];\n      for (let i2 = 0; i2 < this.outputShape.length; i2++) {\n        abCoordVars.push(`${currentCoords[i2]}`);\n        if (i2 < this.cRank) {\n          cCoordVars.push(`${currentCoords[i2]}`);\n        }\n      }\n      cCoords = cCoordVars.join();\n      abCoords = abCoordVars.join();\n    }\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let resRC = getCoordsFromIndex(index);\n          let cVal = getC(${cCoords});\n          if (cVal >= 1.0) {\n            setOutputAtIndex(index, getA(${abCoords}));\n          } else {\n            setOutputAtIndex(index, getB(${abCoords}));\n          }\n        }\n      }\n    `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Select.js\nfunction select5(args) {\n  const { inputs, backend: backend2 } = args;\n  const { condition, t: t2, e: e2 } = inputs;\n  const program = new SelectProgram2(condition.shape.length, t2.shape, t2.shape.length);\n  return backend2.runWebGPUProgram(program, [condition, t2, e2], upcastType(t2.dtype, e2.dtype));\n}\nvar selectConfig4 = {\n  kernelName: Select,\n  backendName: \"webgpu\",\n  kernelFunc: select5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Sigmoid.js\nvar sigmoid5 = unaryKernelFunc3({ opType: UnaryOpType.SIGMOID });\nvar sigmoidConfig4 = {\n  kernelName: Sigmoid,\n  backendName: \"webgpu\",\n  kernelFunc: sigmoid5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Sin.js\nvar sin4 = unaryKernelFunc3({ opType: UnaryOpType.SIN });\nvar sinConfig4 = {\n  kernelName: Sin,\n  backendName: \"webgpu\",\n  kernelFunc: sin4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Sinh.js\nvar sinh4 = unaryKernelFunc3({ opType: UnaryOpType.SINH });\nvar sinhConfig3 = {\n  kernelName: Sinh,\n  backendName: \"webgpu\",\n  kernelFunc: sinh4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Sub.js\nvar sub4 = binaryKernelFunc3({ opType: BinaryOpType.SUB, cpuKernelImpl: subImplCPU2, supportsComplex: true });\nvar subConfig4 = {\n  kernelName: Sub,\n  backendName: \"webgpu\",\n  kernelFunc: sub4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Softmax.js\nfunction softmax6(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { logits } = inputs;\n  const { dim } = attrs;\n  const axes = util_exports.parseAxisParam([dim], logits.shape);\n  const maxLogit = max6({\n    inputs: { x: logits },\n    backend: backend2,\n    attrs: { reductionIndices: axes, keepDims: false }\n  });\n  const expandedShape = backend_util_exports.expandShapeToKeepDim(maxLogit.shape, axes);\n  const maxLogitsReshaped = reshape6({ inputs: { x: maxLogit }, backend: backend2, attrs: { shape: expandedShape } });\n  const a = sub4({ inputs: { a: logits, b: maxLogitsReshaped }, backend: backend2 });\n  const b = exp4({ inputs: { x: a }, backend: backend2 });\n  const sumExp = sum6({ inputs: { x: b }, backend: backend2, attrs: { axis: axes, keepDims: false } });\n  const sumExpReshaped = reshape6({ inputs: { x: sumExp }, backend: backend2, attrs: { shape: expandedShape } });\n  const res = realDiv2({ inputs: { a: b, b: sumExpReshaped }, backend: backend2 });\n  backend2.disposeData(maxLogit.dataId);\n  backend2.disposeData(maxLogitsReshaped.dataId);\n  backend2.disposeData(a.dataId);\n  backend2.disposeData(b.dataId);\n  backend2.disposeData(sumExp.dataId);\n  backend2.disposeData(sumExpReshaped.dataId);\n  return res;\n}\nvar softmaxConfig4 = {\n  kernelName: Softmax,\n  backendName: \"webgpu\",\n  kernelFunc: softmax6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/SpaceToBatchND.js\nvar spaceToBatchND5 = (args) => {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { blockShape, paddings } = attrs;\n  util_exports.assert(x.shape.length <= 4, () => \"spaceToBatchND for rank > 4 with a WebGPU backend not implemented yet\");\n  const prod6 = blockShape.reduce((a, b) => a * b);\n  const completePaddings = [[0, 0]];\n  completePaddings.push(...paddings);\n  for (let i2 = 1 + blockShape.length; i2 < x.shape.length; ++i2) {\n    completePaddings.push([0, 0]);\n  }\n  const toDispose = [];\n  const paddedX = padV23({\n    inputs: { x },\n    backend: backend2,\n    attrs: { paddings: completePaddings, constantValue: 0 }\n  });\n  const reshapedPaddedShape = backend_util_exports.getReshaped(paddedX.shape, blockShape, prod6, false);\n  const permutedReshapedPaddedPermutation = backend_util_exports.getPermuted(reshapedPaddedShape.length, blockShape.length, false);\n  const flattenShape = backend_util_exports.getReshapedPermuted(paddedX.shape, blockShape, prod6, false);\n  const reshapedPaddedX = reshape6({ inputs: { x: paddedX }, backend: backend2, attrs: { shape: reshapedPaddedShape } });\n  const paddedXT = transpose5({\n    inputs: { x: reshapedPaddedX },\n    backend: backend2,\n    attrs: { perm: permutedReshapedPaddedPermutation }\n  });\n  const result = reshape6({ inputs: { x: paddedXT }, backend: backend2, attrs: { shape: flattenShape } });\n  toDispose.push(paddedX);\n  toDispose.push(reshapedPaddedX);\n  toDispose.push(paddedXT);\n  toDispose.forEach((t2) => backend2.disposeData(t2.dataId));\n  return result;\n};\nvar spaceToBatchNDConfig4 = {\n  kernelName: SpaceToBatchND,\n  backendName: \"webgpu\",\n  kernelFunc: spaceToBatchND5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/tile_webgpu.js\nvar TileProgram2 = class {\n  constructor(aShape, reps) {\n    this.variableNames = [\"A\"];\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    const outputShape = new Array(aShape.length);\n    for (let i2 = 0; i2 < outputShape.length; i2++) {\n      outputShape[i2] = aShape[i2] * reps[i2];\n    }\n    this.outputShape = outputShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.rank = this.outputShape.length;\n    this.shaderKey = \"tile\";\n  }\n  getUserCode() {\n    const sourceCoords = getSourceCoords5(this.rank, \"uniforms.\");\n    const userCode = `\n      ${getMainHeaderAndGlobalIndexString()}\n        if (index < uniforms.size) {\n          let resRC = getCoordsFromIndex(index);\n          setOutputAtIndex(index, getA(${sourceCoords}));\n        }\n      }\n    `;\n    return userCode;\n  }\n};\nfunction getSourceCoords5(rank, uniformPrefix = \"\") {\n  if (rank >= 5) {\n    throw Error(`Tile for rank ${rank} is not yet supported`);\n  }\n  if (rank === 1) {\n    return `(resRC % ${uniformPrefix}aShape)`;\n  }\n  const currentCoords = [\"resRC.x\", \"resRC.y\", \"resRC.z\", \"resRC.w\"];\n  const sourceCoords = [];\n  for (let i2 = 0; i2 < rank; i2++) {\n    sourceCoords.push(`(${currentCoords[i2]} % ${uniformPrefix}aShape[${i2}])`);\n  }\n  return sourceCoords.join();\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Tile.js\nfunction tile6(params) {\n  const { inputs, backend: backend2, attrs } = params;\n  const { x } = inputs;\n  const { reps } = attrs;\n  if (backend2.shouldExecuteOnCPU([x]) || x.dtype === \"string\" || x.shape.length >= 5) {\n    const data = backend2.readSync(x.dataId);\n    const value = x.dtype === \"string\" ? data.map((d) => util_exports.decodeString(d)) : data;\n    const buf = buffer(x.shape, x.dtype, value);\n    const outBuf = tileImplCPU2(buf, reps);\n    return backend2.makeTensorInfo(outBuf.shape, outBuf.dtype, outBuf.values);\n  }\n  const program = new TileProgram2(x.shape, reps);\n  const output = backend2.runWebGPUProgram(program, [x], x.dtype);\n  return output;\n}\nvar tileConfig4 = {\n  kernelName: Tile,\n  backendName: \"webgpu\",\n  kernelFunc: tile6\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/SparseToDense.js\nfunction sparseToDense4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { sparseIndices, sparseValues, defaultValue } = inputs;\n  const { outputShape } = attrs;\n  const { sliceRank, numUpdates, sliceSize, strides, outputSize } = backend_util_exports.calculateShapes(sparseValues, sparseIndices, outputShape);\n  const sumDupeIndices = false;\n  if (sparseValues.dtype === \"string\") {\n    const indicesBuf = backend2.bufferSync(sparseIndices);\n    const updatesBuf = backend2.bufferSync(sparseValues);\n    const $defaultValue2 = util_exports.decodeString(backend2.readSync(defaultValue.dataId)[0]);\n    const outBuf = scatterImplCPU2(indicesBuf, updatesBuf, outputShape, outputSize, sliceSize, numUpdates, sliceRank, strides, $defaultValue2, sumDupeIndices);\n    return backend2.makeTensorInfo(outputShape, outBuf.dtype, outBuf.values);\n  }\n  const flattenShape = [outputSize / sliceSize, sliceSize];\n  const $sparseIndices = reshape6({\n    inputs: { x: sparseIndices },\n    backend: backend2,\n    attrs: { shape: [numUpdates, sliceRank] }\n  });\n  const $sparseValues = sparseValues.shape.length ? reshape6({\n    inputs: { x: sparseValues },\n    backend: backend2,\n    attrs: { shape: [numUpdates, sliceSize] }\n  }) : identity5({ inputs: { x: sparseValues }, backend: backend2 });\n  const type = $sparseValues.dtype;\n  const zero = backend2.makeTensorInfo([], type, util_exports.makeZerosTypedArray(1, type));\n  const $defaultValue = reshape6({\n    inputs: { x: defaultValue },\n    backend: backend2,\n    attrs: { shape: Array(flattenShape.length).fill(1) }\n  });\n  const $denseValues = tile6({ inputs: { x: $defaultValue }, backend: backend2, attrs: { reps: flattenShape } });\n  const size = util_exports.sizeFromShape([numUpdates, sliceSize]);\n  const uniformData = [\n    { type: \"int32\", data: [sliceRank] },\n    { type: \"int32\", data: strides },\n    { type: \"int32\", data: [size] }\n  ];\n  switch (numUpdates) {\n    case 0:\n      break;\n    case 1:\n      if (true) {\n        const program = new ScatterOptimizedProgram([numUpdates, sliceSize], sliceRank, $sparseIndices.shape.length, $sparseValues.shape.length, strides, flattenShape, type, sumDupeIndices);\n        backend2.runWebGPUProgram(program, [$sparseValues, $sparseIndices], type, uniformData, $denseValues);\n      }\n      break;\n    default:\n      if (true) {\n        const program = new ScatterOptimizedProgram([numUpdates, sliceSize], sliceRank, $sparseIndices.shape.length, zero.shape.length, strides, flattenShape, type, sumDupeIndices);\n        backend2.runWebGPUProgram(program, [zero, $sparseIndices], type, uniformData, $denseValues);\n      }\n      {\n        const program = new ScatterOptimizedProgram([numUpdates, sliceSize], sliceRank, $sparseIndices.shape.length, $sparseValues.shape.length, strides, flattenShape, type);\n        backend2.runWebGPUProgram(program, [$sparseValues, $sparseIndices], type, uniformData, $denseValues);\n      }\n  }\n  const denseValues = reshape6({ inputs: { x: $denseValues }, backend: backend2, attrs: { shape: outputShape } });\n  backend2.disposeData($sparseIndices.dataId);\n  backend2.disposeData($sparseValues.dataId);\n  backend2.disposeData($defaultValue.dataId);\n  backend2.disposeData(zero.dataId);\n  backend2.disposeData($denseValues.dataId);\n  return denseValues;\n}\nvar sparseToDenseConfig3 = {\n  kernelName: SparseToDense,\n  backendName: \"webgpu\",\n  kernelFunc: sparseToDense4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/SplitV.js\nfunction splitV4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { numOrSizeSplits, axis } = attrs;\n  const $axis = util_exports.parseAxisParam(axis, x.shape)[0];\n  const splitSizes = backend_util_exports.prepareSplitSize(x, numOrSizeSplits, $axis);\n  const xRank = x.shape.length;\n  const begin = new Array(xRank).fill(0);\n  const size = x.shape.slice();\n  return splitSizes.map((s2) => {\n    const sliceSize = [...size];\n    sliceSize[$axis] = s2;\n    const sliceT = slice5({ inputs: { x }, backend: backend2, attrs: { begin, size: sliceSize } });\n    begin[$axis] += s2;\n    return sliceT;\n  });\n}\nvar splitVConfig4 = {\n  kernelName: SplitV,\n  backendName: \"webgpu\",\n  kernelFunc: splitV4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Sqrt.js\nvar sqrt4 = unaryKernelFunc3({ opType: UnaryOpType.SQRT });\nvar sqrtConfig4 = {\n  kernelName: Sqrt,\n  backendName: \"webgpu\",\n  kernelFunc: sqrt4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Square.js\nvar squareConfig4 = {\n  kernelName: Square,\n  backendName: \"webgpu\",\n  kernelFunc: ({ inputs, backend: backend2 }) => {\n    const { x } = inputs;\n    const webGPUBackend = backend2;\n    const program = new UnaryOpProgram2(x.shape, UnaryOpType.SQUARE);\n    return webGPUBackend.runWebGPUProgram(program, [x], x.dtype);\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/SquaredDifference.js\nvar squaredDifference4 = binaryKernelFunc3({\n  opType: BinaryOpType.SQUARED_DIFFERENCE\n});\nvar squaredDifferenceConfig4 = {\n  kernelName: SquaredDifference,\n  backendName: \"webgpu\",\n  kernelFunc: squaredDifference4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/strided_slice_webgpu.js\nvar StridedSliceProgram2 = class {\n  constructor(destSize) {\n    this.variableNames = [\"x\"];\n    this.workPerThread = 1;\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = destSize;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize, [this.workPerThread, 1, 1]);\n    const dtype = getCoordsDataType2(this.outputShape.length);\n    this.uniforms = `begin : ${dtype},  strides : ${dtype}, `;\n    this.shaderKey = \"stridedSlice\";\n  }\n  getUserCode() {\n    const rank = this.outputShape.length;\n    let newCoords = \"\";\n    if (rank === 1) {\n      newCoords = \"coords * uniforms.strides + uniforms.begin\";\n    } else {\n      let outputAxis = 0;\n      newCoords = this.outputShape.map((_, i2) => {\n        outputAxis++;\n        return this.outputShape.length === 1 ? `coords * uniforms.strides[${i2}] + uniforms.begin[${i2}]` : `coords[${outputAxis - 1}] * uniforms.strides[${i2}] + uniforms.begin[${i2}]`;\n      }).join(\",\");\n    }\n    const userCode = `\n       ${getMainHeaderAndGlobalIndexString()}\n         if (index < uniforms.size) {\n           let coords = getCoordsFromIndex(index);\n           setOutputAtIndex(index, getX(${newCoords}));\n         }\n       }\n     `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/StridedSlice.js\nfunction stridedSlice5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask } = attrs;\n  const { finalShapeSparse, finalShape, isIdentity, sliceDim0, isSimpleSlice, begin: $begin, end: $end, strides: $strides } = slice_util_exports.sliceInfo(x.shape, begin, end, strides, beginMask, endMask, ellipsisMask, newAxisMask, shrinkAxisMask);\n  let result;\n  if (isIdentity) {\n    result = reshape6({ inputs: { x }, backend: backend2, attrs: { shape: finalShape } });\n  } else if (sliceDim0 || isSimpleSlice) {\n    util_exports.assert(x.shape.length >= 1, () => `Input must have rank at least 1, got: ${x.shape.length}`);\n    const size = slice_util_exports.computeOutShape($begin, $end, $strides);\n    const sliced = slice5({ inputs: { x }, backend: backend2, attrs: { begin: $begin, size } });\n    result = reshape6({ inputs: { x: sliced }, backend: backend2, attrs: { shape: finalShape } });\n    backend2.disposeData(sliced.dataId);\n  } else {\n    const shouldExecuteOnCPU = backend2.shouldExecuteOnCPU([x]);\n    if (shouldExecuteOnCPU) {\n      const values = backend2.readSync(x.dataId);\n      const xBuf = buffer(x.shape, x.dtype, values);\n      const resultValues = stridedSliceImplCPU2(finalShapeSparse, xBuf, $strides, $begin);\n      result = backend2.makeTensorInfo(finalShape, x.dtype, resultValues.values);\n    } else {\n      const program = new StridedSliceProgram2(finalShapeSparse);\n      const uniformData = [{ type: \"int32\", data: $begin }, { type: \"int32\", data: $strides }];\n      const resultValues = backend2.runWebGPUProgram(program, [x], x.dtype, uniformData);\n      result = reshape6({ inputs: { x: resultValues }, backend: backend2, attrs: { shape: finalShape } });\n      backend2.disposeData(resultValues.dataId);\n    }\n  }\n  return result;\n}\nvar stridedSliceConfig4 = {\n  kernelName: StridedSlice,\n  backendName: \"webgpu\",\n  kernelFunc: stridedSlice5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/StringNGrams.js\nfunction stringNGrams5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { separator, nGramWidths, leftPad, rightPad: rightPad2, padWidth, preserveShortSequences } = attrs;\n  const { data, dataSplits } = inputs;\n  const $data = backend2.readSync(data.dataId);\n  const $dataSplits = backend2.readSync(dataSplits.dataId);\n  const [nGrams, nGramsSplits] = stringNGramsImplCPU2($data, $dataSplits, separator, nGramWidths, leftPad, rightPad2, padWidth, preserveShortSequences);\n  return [\n    backend2.makeTensorInfo([nGrams.length], \"string\", nGrams),\n    backend2.makeTensorInfo(dataSplits.shape, \"int32\", nGramsSplits)\n  ];\n}\nvar stringNGramsConfig4 = {\n  kernelName: StringNGrams,\n  backendName: \"webgpu\",\n  kernelFunc: stringNGrams5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Tanh.js\nvar tanh5 = unaryKernelFunc3({ opType: UnaryOpType.TANH });\nvar tanhConfig4 = {\n  kernelName: Tanh,\n  backendName: \"webgpu\",\n  kernelFunc: tanh5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/top_k_webgpu.js\nvar SwapProgram2 = class {\n  constructor(shape) {\n    this.variableNames = [\"x\", \"indices\"];\n    this.workGroupSize = [256, 1, 1];\n    this.size = true;\n    this.outputShape = shape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.uniforms = `inputSize : i32, firstPass : i32, negativeInf : f32,\n        dir : i32, inc : i32,`;\n    this.shaderKey = \"swap\";\n  }\n  getUserCode() {\n    const userCode = `\n        ${getMainHeaderAndGlobalIndexString()}\n          if (index < uniforms.size) {\n            let outC = getCoordsFromIndex(index);\n            let batch = outC[0];\n            let elemIdx = outC[1];\n            // We compare elements pair-wise within a group of size 2 * inc.\n            // The comparing rule for each group alternates between ascending\n            // and descending. Within each group, we compare each pair at\n            // positions i and i+inc. To decide whether an element at position i\n            // is x0 or x1, we mod it by 2 * inc, if the result is smaller than\n            // inc, it is in the first half of the group, we denote it as x0,\n            // otherwise we denote it as x1.\n            // For example, as shown in the Bitonic top K paper referenced\n            // above, Figure5(a) shows that element[1] is in the second half of\n            // the group when group size is 2, but it is in the first half of\n            // the group when group size is 4.\n            let isFirstInPair = elemIdx % (2 * uniforms.inc) < uniforms.inc;\n            var i = 0;\n            if (isFirstInPair) {\n              i = elemIdx;\n            } else {\n              i = elemIdx - uniforms.inc;\n            }\n\n            var i0 = 0;\n            if (uniforms.firstPass == 1) {\n              i0 = i;\n            } else {\n              i0 = i32(getIndices(batch, i));\n            }\n\n            var i1 = 0;\n            if (uniforms.firstPass == 1) {\n              i1 = i + uniforms.inc;\n            } else {\n              i1 = i32(getIndices(batch, i + uniforms.inc));\n            }\n\n            var x0 = f32(0.0);\n            var x1 = f32(0.0);\n            if (i0 < uniforms.inputSize) {\n              x0 = getX(batch, i0);\n            } else {\n              x0 = uniforms.negativeInf;\n            }\n            if (i1 < uniforms.inputSize) {\n              x1 = getX(batch, i1);\n            } else {\n              x1 = uniforms.negativeInf;\n            }\n\n            let reverse = elemIdx % (2 * uniforms.dir) >= uniforms.dir;\n            let isGreater = x0 > x1 || (x0 == x1 && i1 > i0);\n            if (reverse == isGreater) {\n              // Elements in opposite order of direction\n              let iTemp = i0;\n              i0 = i1;\n              i1 = iTemp;\n            }\n            if (isFirstInPair) {\n              setOutputAtIndex(index, f32(i0));\n            } else {\n              setOutputAtIndex(index, f32(i1));\n            }\n          }\n        }\n      `;\n    return userCode;\n  }\n};\nvar MergeProgram2 = class {\n  constructor(shape) {\n    this.variableNames = [\"x\", \"indices\"];\n    this.workGroupSize = [256, 1, 1];\n    this.size = true;\n    this.outputShape = shape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.uniforms = `inputSize : i32, firstPass : i32, k : i32,`;\n    this.shaderKey = \"merge\";\n  }\n  getUserCode() {\n    const userCode = `\n        ${getMainHeaderAndGlobalIndexString()}\n          if (index < uniforms.size) {\n            let outC = getCoordsFromIndex(index);\n            let batch = outC[0];\n            let elemIdx = outC[1];\n            // The output size is half of the previous size.\n            // If the previous sequence is | | | | _ _ _ _  | | | |  _ _ _ _\n            // (k=4), we only need to output the indices at positions |, the\n            // indices at positions _ can be thrown away, see Figure5(b) After\n            // Phase 2 (Merge phase) in the Bitonic Top K paper referenced\n            // above.\n            // For example, the paper shows we only need to output the orange\n            // bars. The output sequence should look like this | | | | | | | |.\n            // Because the sequence is halved, to map the output index back to\n            // the previous sequence to find the corresponding value, we need\n            // to double the index. When we double the index, we basically\n            // interpolate a position, so 2i looks like\n            // | _ | _ | _ | _ | _ | _ | _. We move the | to the first k\n            // position of each 2k positions by - elemIdx % k. E.g. for output\n            // at index 4,5,6,7, we want to get the corresponding element at\n            // original index 8,9,10,11, for output at index 8,9,10,11,\n            // we want to get the corresponding element at original index\n            // 16,17,18,19, so on and so forth.\n\n            var i = 0;\n            if (elemIdx < uniforms.k) {\n              i = elemIdx;\n            } else {\n              i = elemIdx * 2 - elemIdx % uniforms.k;\n            }\n            var i0 = 0;\n            if (uniforms.firstPass == 1) {\n              i0 = i;\n            } else {\n              i0 = i32(getIndices(batch, i));\n            }\n            var i1 = 0;\n            if (uniforms.firstPass == 1) {\n              i1 = i + uniforms.k;\n            } else {\n              i1 = i32(getIndices(batch, i + uniforms.k));\n            }\n\n            let x0 = getX(batch, i0);\n            var x1 = f32(0.0);\n            if (i1 < uniforms.inputSize) {\n              x1 = getX(batch, i1);\n            } else {\n              x1 = x0;\n            }\n\n            if (x0 >= x1) {\n              setOutputAtIndex(index, f32(i0));\n            } else {\n              setOutputAtIndex(index, f32(i1));\n            }\n          }\n        }\n      `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/TopK.js\nfunction disposeIntermediateTensorInfoOrNull2(backend2, tensorInfo) {\n  if (tensorInfo !== null) {\n    backend2.disposeData(tensorInfo.dataId);\n  }\n}\nfunction roundUpToPow22(num) {\n  let pow22 = 1;\n  while (pow22 < num) {\n    pow22 *= 2;\n  }\n  return pow22;\n}\nfunction topK3(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { x } = inputs;\n  const { k, sorted } = attrs;\n  const xShape = x.shape;\n  const lastDim = xShape[xShape.length - 1];\n  if (backend2.shouldExecuteOnCPU([x])) {\n    const xVals = backend2.readSync(x.dataId);\n    const [allTopKVals, allTopKIndices] = topKImplCPU2(xVals, xShape, x.dtype, k, sorted);\n    return [\n      backend2.makeTensorInfo(allTopKVals.shape, allTopKVals.dtype, allTopKVals.values),\n      backend2.makeTensorInfo(allTopKIndices.shape, allTopKIndices.dtype, allTopKIndices.values)\n    ];\n  }\n  if (k === 0) {\n    xShape[xShape.length - 1] = 0;\n    return [\n      backend2.makeTensorInfo(xShape, x.dtype, []),\n      backend2.makeTensorInfo(xShape, \"int32\", [])\n    ];\n  }\n  if (lastDim === 1) {\n    return [\n      x,\n      fill5({ attrs: { shape: xShape, dtype: \"int32\", value: 0 }, backend: backend2 })\n    ];\n  }\n  const xSize = util_exports.sizeFromShape(xShape);\n  const batch = xSize / lastDim;\n  const x2D = reshape6({ inputs: { x }, attrs: { shape: [batch, lastDim] }, backend: backend2 });\n  const kPow2 = roundUpToPow22(k);\n  const lastDimPow2 = roundUpToPow22(lastDim);\n  let indices = null;\n  const getInputs = () => indices === null ? [x2D, x2D] : [x2D, indices];\n  const runSwap = (dir, inc, shape) => {\n    const inputs2 = getInputs();\n    const program = new SwapProgram2(shape);\n    const firstPass = indices === null ? 1 : 0;\n    const uniformDataSwap = [\n      { type: \"int32\", data: [lastDim] },\n      { type: \"int32\", data: [firstPass] },\n      { type: \"float32\", data: [Number.NEGATIVE_INFINITY] },\n      { type: \"int32\", data: [dir] },\n      { type: \"int32\", data: [inc] }\n    ];\n    const prevIndices2 = indices;\n    indices = backend2.runWebGPUProgram(program, inputs2, \"int32\", uniformDataSwap);\n    disposeIntermediateTensorInfoOrNull2(backend2, prevIndices2);\n  };\n  for (let len = 1; len < kPow2; len *= 2) {\n    const dir = len * 2;\n    for (let inc = len; inc >= 1; inc /= 2) {\n      runSwap(dir, inc, [batch, lastDimPow2]);\n    }\n  }\n  for (let indicesSize = lastDimPow2; indicesSize > kPow2; indicesSize /= 2) {\n    const inputs2 = getInputs();\n    const mergeProgram = new MergeProgram2([batch, indicesSize / 2]);\n    const firstPass = indices === null ? 1 : 0;\n    const uniformDataMerge = [\n      { type: \"int32\", data: [lastDim] },\n      { type: \"int32\", data: [firstPass] },\n      { type: \"int32\", data: [kPow2] }\n    ];\n    const prevIndices2 = indices;\n    indices = backend2.runWebGPUProgram(mergeProgram, inputs2, \"int32\", uniformDataMerge);\n    disposeIntermediateTensorInfoOrNull2(backend2, prevIndices2);\n    const len = kPow2 / 2;\n    const dir = len * 2;\n    for (let inc = len; inc >= 1; inc /= 2) {\n      runSwap(dir, inc, indices.shape);\n    }\n  }\n  let prevIndices = indices;\n  indices = slice5({ inputs: { x: indices }, backend: backend2, attrs: { begin: 0, size: [batch, k] } });\n  disposeIntermediateTensorInfoOrNull2(backend2, prevIndices);\n  let values = gatherV24({ inputs: { x: x2D, indices }, backend: backend2, attrs: { axis: 1, batchDims: 1 } });\n  disposeIntermediateTensorInfoOrNull2(backend2, x2D);\n  const newShape = xShape.slice(0, -1);\n  newShape.push(k);\n  prevIndices = indices;\n  indices = reshape6({ inputs: { x: indices }, attrs: { shape: newShape }, backend: backend2 });\n  disposeIntermediateTensorInfoOrNull2(backend2, prevIndices);\n  const prevValues = values;\n  values = reshape6({ inputs: { x: values }, attrs: { shape: newShape }, backend: backend2 });\n  disposeIntermediateTensorInfoOrNull2(backend2, prevValues);\n  return [values, indices];\n}\nvar topKConfig4 = {\n  kernelName: TopK,\n  backendName: \"webgpu\",\n  kernelFunc: topK3\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/transform_webgpu.js\nvar TransformProgram2 = class {\n  constructor(outShape) {\n    this.variableNames = [\"Image\", \"Transforms\"];\n    this.uniforms = \"interpolationModeId : i32, fillModeId : i32, fillValue : f32,\";\n    this.workGroupSize = [64, 1, 1];\n    this.size = true;\n    this.outputShape = outShape;\n    this.dispatchLayout = flatDispatchLayout(this.outputShape);\n    this.dispatch = computeDispatch(this.dispatchLayout, this.outputShape, this.workGroupSize);\n    this.shaderKey = \"transform\";\n  }\n  getUserCode() {\n    const userCode = `\n          fn mapCoord(outCoord : f32, len : f32) -> f32{\n            var inCoord = outCoord;\n            if(uniforms.fillModeId == 2) {\n              if (inCoord < 0.0) {\n                if (len <= 1.0) {\n                  inCoord = 0.0;\n                } else {\n                  let sz2 = 2.0 * len;\n                  if (inCoord < sz2) {\n                    inCoord = sz2 * f32(i32(f32(-inCoord / sz2))) +\n                    inCoord;\n                  }\n                  if (inCoord < -len) {\n                    inCoord = inCoord + sz2;\n                  } else {\n                    inCoord = -inCoord - 1.0;\n                  }\n                }\n              } else if (inCoord > len - 1.0) {\n                if (len <= 1.0) {\n                  inCoord = 0.0;\n                } else {\n                  let sz2 = 2.0 * len;\n                  inCoord = inCoord - sz2 * f32(i32(f32(inCoord / sz2)));\n                  if (inCoord >= len) {\n                    inCoord = sz2 - inCoord - 1.0;\n                  }\n                }\n              }\n              return clamp(inCoord, 0.0, len - 1.0);\n            } else if (uniforms.fillModeId == 3) {\n              if (inCoord < 0.0) {\n                if (len <= 1.0) {\n                  inCoord = 0.0;\n                } else {\n                  let sz = len - 1.0;\n                  inCoord = inCoord + len * (f32(i32(f32(-inCoord / sz))) + 1.0);\n                }\n              } else if (inCoord > len - 1.0) {\n                if (len <= 1.0) {\n                  inCoord = 0.0;\n                } else {\n                  let sz = len - 1.0;\n                  inCoord = inCoord - len * f32(i32(f32(inCoord / sz)));\n                }\n              }\n              return clamp(inCoord, 0.0, len - 1.0);\n            } else if (uniforms.fillModeId == 4) {\n              return clamp(outCoord, 0.0, len - 1.0);\n            }\n            return outCoord;\n          }\n          fn readWithFillValue(batch : i32, coordY : i32, coordX : i32,\n            channel : i32) -> f32 {\n            var outputValue : f32;\n            if (0 <= coordY && coordY < uniforms.imageShape[1] && 0 <= coordX && coordX < uniforms.imageShape[2]) {\n                outputValue = getImage(batch, coordY, coordX, channel);\n            } else {\n              outputValue = uniforms.fillValue;\n            }\n            return outputValue;\n          }\n\n          ${getMainHeaderAndGlobalIndexString()}\n            if (index < uniforms.size) {\n              let coords = getCoordsFromIndex(index);\n              var outputValue : f32;\n              let batch = coords[0];\n              let x = coords[2];\n              let y = coords[1];\n              let channel = coords[3];\n              let xf = f32(x);\n              let yf = f32(y);\n              let a1 = getTransforms(batch, 0);\n              let a2 = getTransforms(batch, 1);\n              let a3 = getTransforms(batch, 2);\n              let b1 = getTransforms(batch, 3);\n              let b2 = getTransforms(batch, 4);\n              let b3 = getTransforms(batch, 5);\n              let c1 = getTransforms(batch, 6);\n              let c2 = getTransforms(batch, 7);\n              let projection = c1 * xf + c2 * yf + 1.0;\n              if (projection == 0.0) {\n                outputValue = uniforms.fillValue;\n              } else {\n                let inX = (a1 * xf + a2 * yf + a3) / projection;\n                let inY = (b1 * xf + b2 * yf + b3) / projection;\n                let mapX = mapCoord(inX, f32(uniforms.imageShape[2]));\n                let mapY = mapCoord(inY, f32(uniforms.imageShape[1]));\n\n                if (uniforms.interpolationModeId == 1) {\n                  let coordY = i32(round(mapY));\n                  let coordX = i32(round(mapX));\n                  outputValue = readWithFillValue(batch, coordY, coordX,\n                    channel);\n                } else {\n                  let yFloor = floor(mapY);\n                  let xFloor = floor(mapX);\n                  let yCeil = yFloor + 1.0;\n                  let xCeil = xFloor + 1.0;\n                  let valueYFloor = (xCeil - mapX) *\n                  readWithFillValue(batch, i32(yFloor), i32(xFloor), channel) +\n                  (mapX - xFloor) *\n                  readWithFillValue(batch, i32(yFloor), i32(xCeil), channel);\n                  let valueYCeil = (xCeil - mapX) *\n                  readWithFillValue(batch, i32(yCeil), i32(xFloor), channel) +\n                  (mapX - xFloor) *\n                  readWithFillValue(batch, i32(yCeil), i32(xCeil), channel);\n                  outputValue = (yCeil - mapY) * valueYFloor +\n                  (mapY - yFloor) * valueYCeil;\n                }\n              }\n              setOutputAtIndex(index, outputValue);\n            }\n          }\n        `;\n    return userCode;\n  }\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Transform.js\nfunction transform5(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { image: image2, transforms } = inputs;\n  const { interpolation, fillMode, fillValue, outputShape } = attrs;\n  const [batch, imageHeight, imageWidth, numChannels] = image2.shape;\n  const [outHeight, outWidth] = outputShape != null ? outputShape : [imageHeight, imageWidth];\n  const outShape = [\n    batch,\n    outHeight,\n    outWidth,\n    numChannels\n  ];\n  const program = new TransformProgram2(outShape);\n  const interpolationModeId = interpolation === \"nearest\" ? 1 : 2;\n  let fillModeId;\n  switch (fillMode) {\n    case \"constant\":\n      fillModeId = 1;\n      break;\n    case \"reflect\":\n      fillModeId = 2;\n      break;\n    case \"wrap\":\n      fillModeId = 3;\n      break;\n    case \"nearest\":\n      fillModeId = 4;\n      break;\n    default:\n      fillModeId = 1;\n      break;\n  }\n  const uniformData = [\n    { type: \"int32\", data: [interpolationModeId] },\n    { type: \"int32\", data: [fillModeId] },\n    { type: \"float32\", data: [fillValue] }\n  ];\n  return backend2.runWebGPUProgram(program, [image2, transforms], \"float32\", uniformData);\n}\nvar transformConfig4 = {\n  kernelName: Transform,\n  backendName: \"webgpu\",\n  kernelFunc: transform5\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/kernels/Unpack.js\nfunction unpack4(args) {\n  const { inputs, backend: backend2, attrs } = args;\n  const { value } = inputs;\n  let { axis } = attrs;\n  if (axis < 0) {\n    axis += value.shape.length;\n  }\n  const x = value;\n  const xRank = x.shape.length;\n  const num = value.shape[axis];\n  const outShape = new Array(xRank - 1);\n  let outIndex = 0;\n  for (let i2 = 0; i2 < xRank; i2++) {\n    if (i2 !== axis) {\n      outShape[outIndex++] = x.shape[i2];\n    }\n  }\n  const toDispose = [];\n  const begin = new Array(xRank).fill(0);\n  const size = x.shape.slice();\n  size[axis] = 1;\n  const res = new Array(num);\n  for (let i2 = 0; i2 < res.length; i2++) {\n    begin[axis] = i2;\n    const sliced = slice5({ inputs: { x }, backend: backend2, attrs: { begin, size } });\n    const reshaped = reshape6({ inputs: { x: sliced }, backend: backend2, attrs: { shape: outShape } });\n    res[i2] = reshaped;\n    toDispose.push(sliced);\n  }\n  toDispose.forEach((t2) => backend2.disposeData(t2.dataId));\n  return res;\n}\nvar unpackConfig4 = {\n  kernelName: Unpack,\n  backendName: \"webgpu\",\n  kernelFunc: unpack4\n};\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/register_all_kernels.js\nvar kernelConfigs4 = [\n  _fusedMatMulConfig4,\n  absConfig4,\n  addConfig4,\n  addNConfig4,\n  argMaxConfig4,\n  argMinConfig3,\n  avgPoolConfig4,\n  batchMatMulConfig4,\n  batchToSpaceNDConfig4,\n  castConfig4,\n  ceilConfig4,\n  clipByValueConfig4,\n  complexConfig3,\n  concatConfig4,\n  conv2DConfig4,\n  conv2DBackpropInputConfig4,\n  cosConfig4,\n  coshConfig4,\n  cropAndResizeConfig4,\n  cumprodConfig4,\n  cumsumConfig4,\n  depthToSpaceConfig4,\n  depthwiseConv2dNativeConfig4,\n  einsumConfig3,\n  eluConfig4,\n  equalConfig4,\n  expConfig4,\n  expandDimsConfig4,\n  expm1Config3,\n  fillConfig4,\n  flipLeftRightConfig4,\n  fromPixelsConfig2,\n  floorConfig4,\n  floorDivConfig4,\n  fusedBatchNormConfig2,\n  fusedConv2DConfig4,\n  fusedDepthwiseConv2DConfig4,\n  gatherNdConfig4,\n  gatherV2Config4,\n  greaterConfig4,\n  greaterEqualConfig4,\n  identityConfig4,\n  imagConfig3,\n  leakyReluConfig4,\n  lessConfig4,\n  lessEqualConfig4,\n  logConfig4,\n  logicalAndConfig4,\n  logicalNotConfig4,\n  maxConfig4,\n  maximumConfig4,\n  maxPoolConfig4,\n  meanConfig4,\n  minConfig4,\n  minimumConfig4,\n  mirrorPadConfig4,\n  multiplyConfig4,\n  negConfig4,\n  nonMaxSuppressionV3Config4,\n  nonMaxSuppressionV5Config4,\n  notEqualConfig4,\n  onesLikeConfig4,\n  packConfig4,\n  padV2Config4,\n  powConfig4,\n  preluConfig4,\n  prodConfig4,\n  rangeConfig4,\n  realConfig3,\n  realDivConfig4,\n  reluConfig4,\n  relu6Config4,\n  reshapeConfig4,\n  resizeBilinearConfig4,\n  resizeNearestNeighborConfig4,\n  rotateWithOffsetConfig4,\n  rsqrtConfig4,\n  scatterNdConfig4,\n  selectConfig4,\n  sigmoidConfig4,\n  sinConfig4,\n  sinhConfig3,\n  sliceConfig4,\n  stridedSliceConfig4,\n  stringNGramsConfig4,\n  softmaxConfig4,\n  spaceToBatchNDConfig4,\n  sparseToDenseConfig3,\n  splitVConfig4,\n  sqrtConfig4,\n  squareConfig4,\n  squaredDifferenceConfig4,\n  subConfig4,\n  sumConfig4,\n  tanhConfig4,\n  tileConfig4,\n  topKConfig4,\n  transformConfig4,\n  transposeConfig4,\n  unpackConfig4,\n  zerosLikeConfig4\n];\nfor (const kernelConfig of kernelConfigs4) {\n  registerKernel(kernelConfig);\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/buffer_manager.js\nvar BufferManager = class {\n  constructor(device) {\n    this.device = device;\n    this.numUsedBuffers = 0;\n    this.numFreeBuffers = 0;\n    this.freeBuffers = /* @__PURE__ */ new Map();\n    this.usedBuffers = /* @__PURE__ */ new Map();\n    this.numBytesUsed = 0;\n    this.numBytesAllocated = 0;\n  }\n  acquireUploadBuffer(size, usage) {\n    return this.acquireBuffer(size, usage, true);\n  }\n  acquireBuffer(size, usage, mappedAtCreation = false) {\n    const key = getBufferKey(size, usage);\n    if (!this.freeBuffers.has(key)) {\n      this.freeBuffers.set(key, []);\n    }\n    if (!this.usedBuffers.has(key)) {\n      this.usedBuffers.set(key, []);\n    }\n    this.numBytesUsed += size;\n    this.numUsedBuffers++;\n    if (this.freeBuffers.get(key).length > 0) {\n      this.numFreeBuffers--;\n      const newBuffer2 = this.freeBuffers.get(key).shift();\n      this.usedBuffers.get(key).push(newBuffer2);\n      return newBuffer2;\n    }\n    this.numBytesAllocated += size;\n    const newBuffer = this.device.createBuffer({ size, usage, mappedAtCreation });\n    this.usedBuffers.get(key).push(newBuffer);\n    return newBuffer;\n  }\n  releaseBuffer(buffer2, size, usage) {\n    if (this.freeBuffers.size === 0) {\n      return;\n    }\n    const key = getBufferKey(size, usage);\n    if (!this.freeBuffers.has(key)) {\n      this.freeBuffers.set(key, []);\n    }\n    this.freeBuffers.get(key).push(buffer2);\n    this.numFreeBuffers++;\n    this.numUsedBuffers--;\n    const bufferList = this.usedBuffers.get(key);\n    const bufferIndex = bufferList.indexOf(buffer2);\n    if (bufferIndex < 0) {\n      throw new Error(\"Cannot release a buffer that was never provided by this buffer manager\");\n    }\n    bufferList.splice(bufferIndex, 1);\n    this.numBytesUsed -= size;\n  }\n  releaseUploadBuffer(buffer2, size, usage) {\n    buffer2.mapAsync(GPUMapMode.WRITE).then(() => {\n      this.releaseBuffer(buffer2, size, usage);\n    }, (err) => {\n    });\n  }\n  getNumUsedBuffers() {\n    return this.numUsedBuffers;\n  }\n  getNumFreeBuffers() {\n    return this.numFreeBuffers;\n  }\n  dispose() {\n    this.freeBuffers.forEach((buffers, key) => {\n      buffers.forEach((buffer2) => {\n        buffer2.destroy();\n      });\n    });\n    this.usedBuffers.forEach((buffers, key) => {\n      buffers.forEach((buffer2) => {\n        buffer2.destroy();\n      });\n    });\n    this.freeBuffers = /* @__PURE__ */ new Map();\n    this.usedBuffers = /* @__PURE__ */ new Map();\n    this.numUsedBuffers = 0;\n    this.numFreeBuffers = 0;\n    this.numBytesUsed = 0;\n    this.numBytesAllocated = 0;\n  }\n};\nfunction getBufferKey(size, usage) {\n  return `${size}_${usage}`;\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/texture_manager.js\nvar TextureManager2 = class {\n  constructor(device) {\n    this.device = device;\n    this.numUsedTextures = 0;\n    this.numFreeTextures = 0;\n    this.freeTextures = /* @__PURE__ */ new Map();\n    this.usedTextures = /* @__PURE__ */ new Map();\n    this.numBytesUsed = 0;\n    this.numBytesAllocated = 0;\n  }\n  acquireTexture(width, height, format, usage) {\n    const bytesPerElement2 = getBytesPerElement(format);\n    const byteSize = width * height * bytesPerElement2;\n    const key = getTextureKey(width, height, format, usage);\n    if (!this.freeTextures.has(key)) {\n      this.freeTextures.set(key, []);\n    }\n    if (!this.usedTextures.has(key)) {\n      this.usedTextures.set(key, []);\n    }\n    this.numBytesUsed += byteSize;\n    this.numUsedTextures++;\n    if (this.freeTextures.get(key).length > 0) {\n      this.numFreeTextures--;\n      const newTexture2 = this.freeTextures.get(key).shift();\n      this.usedTextures.get(key).push(newTexture2);\n      return newTexture2;\n    }\n    this.numBytesAllocated += byteSize;\n    const newTexture = this.device.createTexture({\n      size: [width, height],\n      format,\n      usage\n    });\n    this.usedTextures.get(key).push(newTexture);\n    return newTexture;\n  }\n  releaseTexture(texture, width, height, format, usage) {\n    if (this.freeTextures.size === 0) {\n      return;\n    }\n    const key = getTextureKey(width, height, format, usage);\n    if (!this.freeTextures.has(key)) {\n      this.freeTextures.set(key, []);\n    }\n    this.freeTextures.get(key).push(texture);\n    this.numFreeTextures++;\n    this.numUsedTextures--;\n    const textureList = this.usedTextures.get(key);\n    const textureIndex = textureList.indexOf(texture);\n    if (textureIndex < 0) {\n      throw new Error(\"Cannot release a texture that was never provided by this texture manager\");\n    }\n    textureList.splice(textureIndex, 1);\n    const bytesPerElement2 = getBytesPerElement(format);\n    const byteSize = width * height * bytesPerElement2;\n    this.numBytesUsed -= byteSize;\n  }\n  getNumUsedTextures() {\n    return this.numUsedTextures;\n  }\n  getNumFreeTextures() {\n    return this.numFreeTextures;\n  }\n  dispose() {\n    this.freeTextures.forEach((textures, key) => {\n      textures.forEach((texture) => {\n        texture.destroy();\n      });\n    });\n    this.usedTextures.forEach((textures, key) => {\n      textures.forEach((texture) => {\n        texture.destroy();\n      });\n    });\n    this.freeTextures = /* @__PURE__ */ new Map();\n    this.usedTextures = /* @__PURE__ */ new Map();\n    this.numUsedTextures = 0;\n    this.numFreeTextures = 0;\n    this.numBytesUsed = 0;\n    this.numBytesAllocated = 0;\n  }\n};\nfunction getTextureKey(width, height, format, usage) {\n  return `${width}_${height}_${format}_${usage}`;\n}\nfunction getBytesPerElement(format) {\n  if (format === \"rgba8unorm\") {\n    return 16;\n  } else {\n    throw new Error(`${format} is not supported!`);\n  }\n}\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/backend_webgpu.js\nvar CPU_HANDOFF_SIZE_THRESHOLD2 = env().getNumber(\"WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD\");\nvar reshapeDispatch = (device, program) => {\n  const MAX_COMPUTE_PER_DIMENSION_DISPATCH_SIZE = device.limits.maxComputeWorkgroupsPerDimension;\n  const layout = program[\"dispatchLayout\"];\n  const dispatch = program[\"dispatch\"];\n  if (dispatch.every((d) => d <= MAX_COMPUTE_PER_DIMENSION_DISPATCH_SIZE)) {\n    return dispatch;\n  }\n  util_exports.assert(dispatch[0] > MAX_COMPUTE_PER_DIMENSION_DISPATCH_SIZE && layout.y === void 0 && layout.z === void 0, () => \"Dispatch size exceeds WebGPU limits in Y or Z dimension.\");\n  let dispatchAverage = Math.ceil(Math.sqrt(dispatch[0]));\n  if (dispatchAverage > MAX_COMPUTE_PER_DIMENSION_DISPATCH_SIZE) {\n    dispatchAverage = Math.ceil(Math.cbrt(dispatch[0]));\n    util_exports.assert(dispatchAverage <= MAX_COMPUTE_PER_DIMENSION_DISPATCH_SIZE, () => \"Total dispatch size exceeds WebGPU maximum.\");\n    return [dispatchAverage, dispatchAverage, dispatchAverage];\n  } else {\n    return [dispatchAverage, dispatchAverage, 1];\n  }\n};\nvar WebGPUBackend = class extends KernelBackend {\n  constructor(device, supportTimeQuery = false) {\n    super();\n    this.commandQueueOwnedIds = /* @__PURE__ */ new WeakSet();\n    this.dispatchNumberInEncoder = 0;\n    this.disposed = false;\n    this.downloadWaitMs = 0;\n    this.tensorDataPendingDisposal = [];\n    this.stagingPendingDisposal = [];\n    this.uniformPendingDisposal = [];\n    this.uploadWaitMs = 0;\n    if (!isWebGPUSupported()) {\n      throw new Error(\"WebGPU is not supported on this device\");\n    }\n    this.pipelineCache = {};\n    this.device = device;\n    this.queue = device.queue;\n    this.currentCommandEncoder = null;\n    this.currentComputePass = null;\n    this.supportTimeQuery = supportTimeQuery;\n    this.bufferManager = new BufferManager(this.device);\n    this.textureManager = new TextureManager2(this.device);\n    this.tensorMap = new DataStorage(this, engine());\n    if (this.supportTimeQuery) {\n      this.querySet = this.device.createQuerySet({\n        type: \"timestamp\",\n        count: 2\n      });\n    }\n    if (env().getBool(\"WEBGPU_USE_PROFILE_TOOL\")) {\n      this.dummyCanvas = document.createElement(\"canvas\");\n      this.dummyCanvas.width = 1;\n      this.dummyCanvas.height = 1;\n      this.dummyContext = this.dummyCanvas.getContext(\"webgpu\");\n      this.dummyContext.configure({\n        device,\n        format: \"bgra8unorm\"\n      });\n      document.body.appendChild(this.dummyCanvas);\n    }\n  }\n  nextDataId() {\n    return WebGPUBackend.nextDataId++;\n  }\n  floatPrecision() {\n    return 32;\n  }\n  defaultGpuBufferUsage() {\n    return GPUBufferUsage.STORAGE | GPUBufferUsage.COPY_SRC | GPUBufferUsage.COPY_DST;\n  }\n  disposeData(dataId, force = false) {\n    if (this.tensorDataPendingDisposal.indexOf(dataId) >= 0) {\n      return false;\n    }\n    if (!this.tensorMap.has(dataId)) {\n      return true;\n    }\n    const tensorData = this.tensorMap.get(dataId);\n    this.decRef(dataId);\n    if (!force && tensorData.refCount > 0) {\n      return false;\n    }\n    if (this.commandQueueOwnedIds.has(dataId)) {\n      this.tensorDataPendingDisposal.push(dataId);\n      return false;\n    }\n    const { complexTensorInfos } = this.tensorMap.get(dataId);\n    if (complexTensorInfos != null) {\n      this.disposeData(complexTensorInfos.real.dataId, force);\n      this.disposeData(complexTensorInfos.imag.dataId, force);\n    }\n    this.releaseResource(dataId);\n    this.tensorMap.delete(dataId);\n    return true;\n  }\n  memory() {\n    return {\n      numBytesInGPU: this.bufferManager.numBytesUsed,\n      numBytesAllocatedInGPU: this.bufferManager.numBytesAllocated,\n      unreliable: false\n    };\n  }\n  releaseResource(dataId) {\n    const tensorData = this.tensorMap.get(dataId);\n    if (!tensorData || !tensorData.resourceInfo) {\n      return;\n    }\n    if (\"texture\" in tensorData.resourceInfo) {\n      const textureInfo = tensorData.resourceInfo;\n      if (textureInfo.texture instanceof GPUTexture) {\n        this.textureManager.releaseTexture(textureInfo.texture, textureInfo.width, textureInfo.height, textureInfo.format, textureInfo.usage);\n      }\n      textureInfo.texture = null;\n    } else {\n      const bufferInfo = tensorData.resourceInfo;\n      this.bufferManager.releaseBuffer(bufferInfo.buffer, bufferInfo.size, bufferInfo.usage);\n      bufferInfo.buffer = null;\n    }\n    tensorData.resourceInfo = null;\n  }\n  refCount(dataId) {\n    if (this.tensorMap.has(dataId)) {\n      const tensorData = this.tensorMap.get(dataId);\n      return tensorData.refCount;\n    }\n    return 0;\n  }\n  incRef(dataId) {\n    const tensorData = this.tensorMap.get(dataId);\n    tensorData.refCount++;\n  }\n  decRef(dataId) {\n    if (this.tensorMap.has(dataId)) {\n      const tensorData = this.tensorMap.get(dataId);\n      tensorData.refCount--;\n    }\n  }\n  write(values, shape, dtype) {\n    if (dtype === \"complex64\" && values != null) {\n      throw new Error(`Cannot write to a complex64 dtype. Please use tf.complex(real, imag).`);\n    }\n    const dataId = { id: this.nextDataId() };\n    this.tensorMap.set(dataId, { dtype, shape, values, refCount: 1 });\n    return dataId;\n  }\n  move(dataId, values, shape, dtype, refCount) {\n    if (dtype === \"complex64\") {\n      throw new Error(`Cannot write to a complex64 dtype. Please use tf.complex(real, imag).`);\n    }\n    this.tensorMap.set(dataId, { dtype, shape, values, refCount });\n  }\n  submitQueue() {\n    this.ensureComputePassEnded();\n    this.queue.submit([this.currentCommandEncoder.finish()]);\n    this.currentCommandEncoder = null;\n    this.dispatchNumberInEncoder = 0;\n    this.commandQueueOwnedIds = /* @__PURE__ */ new WeakSet();\n    this.tensorDataPendingDisposal.forEach((d) => {\n      this.releaseResource(d);\n      this.tensorMap.delete(d);\n    });\n    this.uniformPendingDisposal.forEach((d) => this.bufferManager.releaseBuffer(d.buffer, d.size, d.usage));\n    this.stagingPendingDisposal.forEach((d) => this.bufferManager.releaseUploadBuffer(d.buffer, d.size, d.usage));\n    this.tensorDataPendingDisposal = [];\n    this.uniformPendingDisposal = [];\n    this.stagingPendingDisposal = [];\n  }\n  ensureCommandEncoderReady() {\n    if (!this.currentCommandEncoder) {\n      this.currentCommandEncoder = this.device.createCommandEncoder();\n    }\n  }\n  ensureComputePassEnded() {\n    if (this.currentComputePass) {\n      this.currentComputePass.end();\n      this.currentComputePass = null;\n    }\n  }\n  getComputePass() {\n    if (!this.currentComputePass) {\n      this.currentComputePass = this.currentCommandEncoder.beginComputePass();\n    }\n    return this.currentComputePass;\n  }\n  async getBufferData(buffer2, size) {\n    const staging = this.bufferManager.acquireBuffer(size, GPUBufferUsage.COPY_DST | GPUBufferUsage.MAP_READ);\n    this.ensureCommandEncoderReady();\n    this.ensureComputePassEnded();\n    this.currentCommandEncoder.copyBufferToBuffer(buffer2, 0, staging, 0, size);\n    this.submitQueue();\n    await staging.mapAsync(GPUMapMode.READ);\n    const values = staging.getMappedRange().slice(0);\n    staging.unmap();\n    if (staging != null) {\n      this.bufferManager.releaseBuffer(staging, size, GPUBufferUsage.COPY_DST | GPUBufferUsage.MAP_READ);\n    }\n    if (env().getBool(\"WEBGPU_USE_PROFILE_TOOL\")) {\n      util_exports.assert(this.dummyContext !== void 0, () => `Fail to get context for profiling tool`);\n      this.dummyContext.getCurrentTexture();\n    }\n    return values;\n  }\n  convertAndCacheOnCPU(dataId, data) {\n    const tensorData = this.tensorMap.get(dataId);\n    this.releaseResource(dataId);\n    tensorData.values = data;\n    return tensorData.values;\n  }\n  readSync(dataId) {\n    const tensorData = this.tensorMap.get(dataId);\n    const { values } = tensorData;\n    if (values == null) {\n      throw new Error(\"WebGPU readSync is only available for CPU-resident tensors.\");\n    }\n    return values;\n  }\n  async read(dataId) {\n    if (!this.tensorMap.has(dataId)) {\n      throw new Error(`Tensor ${dataId} was not registered!`);\n    }\n    const tensorData = this.tensorMap.get(dataId);\n    const { values } = tensorData;\n    if (values != null) {\n      return this.convertAndCacheOnCPU(dataId, values);\n    }\n    let vals;\n    if (tensorData.dtype === \"complex64\") {\n      const ps = await Promise.all([\n        this.read(tensorData.complexTensorInfos.real.dataId),\n        this.read(tensorData.complexTensorInfos.imag.dataId)\n      ]);\n      const realValues = ps[0];\n      const imagValues = ps[1];\n      vals = backend_util_exports.mergeRealAndImagArrays(realValues, imagValues);\n    } else {\n      const bufferInfo = tensorData.resourceInfo;\n      const data = await this.getBufferData(bufferInfo.buffer, bufferInfo.size);\n      vals = ArrayBufferToTypedArray(data, tensorData.dtype);\n    }\n    this.convertAndCacheOnCPU(dataId, vals);\n    return vals;\n  }\n  readToGPU(dataId) {\n    const srcTensorData = this.tensorMap.get(dataId);\n    const { values, dtype, shape, resourceInfo } = srcTensorData;\n    if (dtype === \"complex64\") {\n      throw new Error(\"Does not support reading buffer for complex64 dtype.\");\n    }\n    if (resourceInfo == null) {\n      if (values != null) {\n        throw new Error(\"Data is not on GPU but on CPU.\");\n      } else {\n        throw new Error(\"There is no data on GPU or CPU.\");\n      }\n    }\n    const size = resourceInfo.size;\n    const buffer2 = this.bufferManager.acquireBuffer(size, resourceInfo.usage);\n    this.ensureCommandEncoderReady();\n    this.ensureComputePassEnded();\n    this.currentCommandEncoder.copyBufferToBuffer(resourceInfo.buffer, 0, buffer2, 0, size);\n    this.submitQueue();\n    const tensorInfo = this.makeTensorInfo(shape, dtype);\n    const tensorRef = engine().makeTensorFromTensorInfo(tensorInfo);\n    const tensorData = this.tensorMap.get(tensorInfo.dataId);\n    tensorData.resourceInfo = { size, usage: this.defaultGpuBufferUsage(), buffer: buffer2 };\n    return { tensorRef, buffer: buffer2, bufSize: size };\n  }\n  bufferSync(t2) {\n    const data = this.readSync(t2.dataId);\n    if (t2.dtype === \"string\") {\n      try {\n        const strings = data.map((d) => util_exports.decodeString(d));\n        return buffer(t2.shape, t2.dtype, strings);\n      } catch (_a) {\n        throw new Error(\"Failed to decode encoded string bytes into utf-8\");\n      }\n    }\n    return buffer(t2.shape, t2.dtype, data);\n  }\n  async time(f) {\n    const oldActiveTimers = this.activeTimers;\n    const newActiveTimers = [];\n    let outerMostTime = false;\n    if (this.programTimersStack == null) {\n      this.programTimersStack = newActiveTimers;\n      outerMostTime = true;\n    } else {\n      this.activeTimers.push(newActiveTimers);\n    }\n    this.activeTimers = newActiveTimers;\n    f();\n    const flattenedActiveTimerQueries = util_exports.flatten(this.activeTimers.map((d) => d.query)).filter((d) => d != null);\n    const flattenedActiveTimerNames = util_exports.flatten(this.activeTimers.map((d) => d.name)).filter((d) => d != null);\n    this.activeTimers = oldActiveTimers;\n    if (outerMostTime) {\n      this.programTimersStack = null;\n    }\n    const res = {\n      uploadWaitMs: this.uploadWaitMs,\n      downloadWaitMs: this.downloadWaitMs,\n      kernelMs: null,\n      wallMs: null\n    };\n    const kernelMs = await Promise.all(flattenedActiveTimerQueries);\n    res[\"kernelMs\"] = util_exports.sum(kernelMs);\n    res[\"getExtraProfileInfo\"] = () => kernelMs.map((d, i2) => ({ name: flattenedActiveTimerNames[i2], ms: d })).map((d) => `${d.name}: ${d.ms}`).join(\", \");\n    this.uploadWaitMs = 0;\n    this.downloadWaitMs = 0;\n    return res;\n  }\n  makeTensorInfo(shape, dtype, values) {\n    if (dtype === \"string\" && values != null && values.length > 0 && util_exports.isString(values[0])) {\n      values = values.map((d) => util_exports.encodeString(d));\n    }\n    const dataId = this.write(values, shape, dtype);\n    return { dataId, shape, dtype };\n  }\n  tensorToBinding(tensor2) {\n    if (!tensor2) {\n      return null;\n    }\n    const tensorData = this.tensorMap.get(tensor2.dataId);\n    if (\"texture\" in tensorData.resourceInfo) {\n      const info = tensorData.resourceInfo;\n      if (info.texture instanceof GPUExternalTexture) {\n        return info.texture;\n      } else {\n        return info.texture.createView();\n      }\n    }\n    const bufferInfo = tensorData.resourceInfo;\n    return { offset: 0, size: bufferInfo.size, buffer: bufferInfo.buffer };\n  }\n  async getQueryTime(query) {\n    if (this.supportTimeQuery) {\n      return this.getTimeFromQuerySet(query);\n    } else {\n      return 0;\n    }\n  }\n  uploadToGPU(dataId) {\n    const tensorData = this.tensorMap.get(dataId);\n    if (tensorData.resourceInfo) {\n      return;\n    }\n    const size = GPUBytesPerElement(tensorData.dtype) * util_exports.sizeFromShape(tensorData.shape);\n    const buffer2 = this.bufferManager.acquireBuffer(size, this.defaultGpuBufferUsage());\n    tensorData.resourceInfo = { size, usage: this.defaultGpuBufferUsage(), buffer: buffer2 };\n    if (tensorData.values) {\n      const stagingBuffer = this.bufferManager.acquireUploadBuffer(size, GPUBufferUsage.MAP_WRITE | GPUBufferUsage.COPY_SRC);\n      const arrayBuffer = stagingBuffer.getMappedRange();\n      if (tensorData.dtype === \"int32\" || tensorData.dtype === \"bool\") {\n        new Int32Array(arrayBuffer).set(tensorData.values);\n      } else {\n        new Float32Array(arrayBuffer).set(tensorData.values);\n      }\n      stagingBuffer.unmap();\n      this.ensureCommandEncoderReady();\n      this.ensureComputePassEnded();\n      this.currentCommandEncoder.copyBufferToBuffer(stagingBuffer, 0, buffer2, 0, size);\n      const stagingInfo = {\n        size,\n        usage: GPUBufferUsage.MAP_WRITE | GPUBufferUsage.COPY_SRC,\n        buffer: stagingBuffer\n      };\n      this.stagingPendingDisposal.push(stagingInfo);\n    }\n  }\n  makeUniforms(programUniform) {\n    let currentOffset = 0;\n    let preLength = 0;\n    const offsets = [];\n    programUniform.forEach((d) => {\n      if (d.data.length === 0) {\n        d.data = [1];\n      }\n      let baseAlignment;\n      switch (d.data.length) {\n        case 1:\n          baseAlignment = 4;\n          break;\n        case 2:\n          baseAlignment = 8;\n          break;\n        case 3:\n          baseAlignment = 16;\n          break;\n        case 4:\n          baseAlignment = 16;\n          break;\n        case 5:\n          baseAlignment = 16;\n          break;\n        case 6:\n          baseAlignment = 16;\n          break;\n        default:\n          util_exports.assert(false, () => `Unsupported ${d.data.length}D shape`);\n      }\n      if (preLength === 5 || preLength === 6) {\n        baseAlignment = 16;\n      }\n      currentOffset = Math.ceil(currentOffset / baseAlignment) * baseAlignment;\n      preLength = d.data.length;\n      offsets.push(currentOffset);\n      currentOffset += d.data.length * 4;\n    });\n    const arrayBuffer = new ArrayBuffer(currentOffset);\n    programUniform.forEach((d, i2) => {\n      const offset = offsets[i2];\n      if (d.type === \"int32\") {\n        new Int32Array(arrayBuffer, offset, d.data.length).set(d.data);\n      } else if (d.type === \"uint32\") {\n        new Uint32Array(arrayBuffer, offset, d.data.length).set(d.data);\n      } else {\n        new Float32Array(arrayBuffer, offset, d.data.length).set(d.data);\n      }\n    });\n    const uniformBuffer = this.bufferManager.acquireBuffer(currentOffset, GPUBufferUsage.COPY_DST | GPUBufferUsage.UNIFORM);\n    this.queue.writeBuffer(uniformBuffer, 0, arrayBuffer, 0, currentOffset);\n    const uniformInfo = {\n      size: currentOffset,\n      usage: GPUBufferUsage.COPY_DST | GPUBufferUsage.UNIFORM,\n      buffer: uniformBuffer\n    };\n    this.uniformPendingDisposal.push(uniformInfo);\n    return { offset: 0, size: currentOffset, buffer: uniformBuffer };\n  }\n  runWebGPUProgram(program, inputs, outputDtype, programDefinedUniform, output) {\n    if (!output) {\n      output = this.makeTensorInfo(program.outputShape, outputDtype);\n    }\n    if (util_exports.sizeFromShape(output.shape) === 0) {\n      this.tensorMap.get(output.dataId).values = util_exports.getTypedArrayFromDType(output.dtype, 0);\n      return output;\n    }\n    this.uploadToGPU(output.dataId);\n    program.dispatch = reshapeDispatch(this.device, program);\n    let programUniform = [];\n    let bufferShapes = [];\n    if (!program.isFromPixels) {\n      programUniform.push({ type: \"float32\", data: [NaN] });\n      bufferShapes = inputs.concat(output).map((d) => d.shape);\n      const uniformsType = \"int32\";\n      bufferShapes.map((d) => {\n        programUniform.push({ type: uniformsType, data: d });\n      });\n      const strides = util_exports.computeStrides(output.shape);\n      programUniform.push({ type: uniformsType, data: strides });\n      if (program.size) {\n        const size = util_exports.sizeFromShape(program.outputShape);\n        programUniform.push({ type: uniformsType, data: [program.isVec4 ? size / 4 : size] });\n      }\n    }\n    const inputsData = inputs.map((input2, i2) => {\n      if (input2.dtype === \"complex64\") {\n        throw new Error(`GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.`);\n      }\n      this.uploadToGPU(input2.dataId);\n      return {\n        dtype: this.tensorMap.get(input2.dataId).dtype,\n        shape: input2.shape,\n        name: program.variableNames[i2]\n      };\n    });\n    const key = makeShaderKey2(program, bufferShapes, inputsData, output);\n    let pipeline;\n    if (key in this.pipelineCache) {\n      pipeline = this.pipelineCache[key];\n    } else {\n      pipeline = compileProgram2(this.device, program, inputsData, output);\n      this.pipelineCache[key] = pipeline;\n    }\n    if (programDefinedUniform) {\n      programUniform = [...programUniform, ...programDefinedUniform];\n    }\n    const bindings = [\n      this.tensorToBinding(output),\n      ...inputs.map((t2) => this.tensorToBinding(t2)),\n      this.makeUniforms(programUniform)\n    ];\n    const bindGroup = this.device.createBindGroup({\n      layout: pipeline.getBindGroupLayout(0),\n      entries: bindings.map((b, i2) => ({ binding: i2, resource: b }))\n    });\n    this.ensureCommandEncoderReady();\n    const pass = this.getComputePass();\n    const shouldTimeProgram = this.activeTimers != null;\n    if (shouldTimeProgram) {\n      if (this.supportTimeQuery) {\n        pass.writeTimestamp(this.querySet, 0);\n      }\n    }\n    pass.setPipeline(pipeline);\n    pass.setBindGroup(0, bindGroup);\n    pass.dispatchWorkgroups(program.dispatch[0], program.dispatch[1], program.dispatch[2]);\n    if (shouldTimeProgram) {\n      if (this.supportTimeQuery) {\n        pass.writeTimestamp(this.querySet, 1);\n      }\n    }\n    this.dispatchNumberInEncoder++;\n    inputs.forEach((input2) => {\n      this.commandQueueOwnedIds.add(input2.dataId);\n    });\n    this.commandQueueOwnedIds.add(output.dataId);\n    if (env().get(\"WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE\") <= this.dispatchNumberInEncoder) {\n      this.submitQueue();\n    }\n    if (shouldTimeProgram) {\n      this.activeTimers.push({\n        name: program.constructor.name,\n        query: this.getQueryTime(this.querySet)\n      });\n    }\n    return output;\n  }\n  async getTimeFromQuerySet(querySet) {\n    const queryBuffer = this.bufferManager.acquireBuffer(16, GPUBufferUsage.COPY_SRC | GPUBufferUsage.QUERY_RESOLVE);\n    const dst = this.bufferManager.acquireBuffer(16, GPUBufferUsage.MAP_READ | GPUBufferUsage.COPY_DST);\n    this.ensureCommandEncoderReady();\n    this.ensureComputePassEnded();\n    this.currentCommandEncoder.resolveQuerySet(querySet, 0, 2, queryBuffer, 0);\n    this.currentCommandEncoder.copyBufferToBuffer(queryBuffer, 0, dst, 0, 16);\n    this.submitQueue();\n    await dst.mapAsync(GPUMapMode.READ);\n    const arrayBuf = new BigUint64Array(dst.getMappedRange());\n    const timeElapsedNanos = Number(arrayBuf[1] - arrayBuf[0]);\n    dst.unmap();\n    this.bufferManager.releaseBuffer(dst, 16, GPUBufferUsage.MAP_READ | GPUBufferUsage.COPY_DST);\n    this.bufferManager.releaseBuffer(queryBuffer, 16, GPUBufferUsage.COPY_SRC | GPUBufferUsage.QUERY_RESOLVE);\n    return timeElapsedNanos / 1e6;\n  }\n  shouldExecuteOnCPU(inputs, sizeThreshold = CPU_HANDOFF_SIZE_THRESHOLD2) {\n    return env().getBool(\"WEBGPU_CPU_FORWARD\") && inputs.every((input2) => this.tensorMap.get(input2.dataId).resourceInfo == null && util_exports.sizeFromShape(input2.shape) < sizeThreshold);\n  }\n  numDataIds() {\n    return this.tensorMap.numDataIds() - this.tensorDataPendingDisposal.length;\n  }\n  dispose() {\n    if (this.disposed) {\n      return;\n    }\n    this.bufferManager.dispose();\n    this.textureManager.dispose();\n    this.disposed = true;\n  }\n};\nWebGPUBackend.nextDataId = 0;\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/webgpu.js\nvar webgpu_exports = {};\n__export(webgpu_exports, {\n  WebGPUBackend: () => WebGPUBackend,\n  webgpu_util: () => webgpu_util_exports\n});\n\n// node_modules/.pnpm/@tensorflow+tfjs-backend-webgpu@0.0.1-alpha.12_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-webgpu/dist/index.js\nif (isWebGPUSupported()) {\n  registerBackend(\"webgpu\", async () => {\n    env().set(\"CHECK_COMPUTATION_FOR_ERRORS\", false);\n    const gpuDescriptor = {\n      powerPreference: env().get(\"WEBGPU_USE_LOW_POWER_GPU\") ? \"low-power\" : \"high-performance\"\n    };\n    const adapter = await navigator.gpu.requestAdapter(gpuDescriptor);\n    const adapterLimits = adapter.limits;\n    const deviceDescriptor = {};\n    const supportTimeQuery = adapter.features.has(\"timestamp-query\");\n    deviceDescriptor.requiredLimits = {\n      \"maxComputeWorkgroupStorageSize\": adapterLimits.maxComputeWorkgroupStorageSize,\n      \"maxComputeWorkgroupsPerDimension\": adapterLimits.maxComputeWorkgroupsPerDimension,\n      \"maxStorageBufferBindingSize\": adapterLimits.maxStorageBufferBindingSize\n    };\n    if (supportTimeQuery) {\n      deviceDescriptor.requiredFeatures = [\"timestamp-query\"];\n    } else {\n      console.warn(`This device doesn't support timestamp-query extension. Start Chrome browser with flag --disable-dawn-features=disallow_unsafe_apis then try again. Or zero will shown for the kernel time when profiling mode isenabled. Using performance.now is not workable for webgpu sinceit doesn't support synchronously to read data from GPU.`);\n    }\n    const device = await adapter.requestDevice(deviceDescriptor);\n    return new WebGPUBackend(device, supportTimeQuery);\n  }, 3);\n}\n\n// dist/tfjs.version.js\nvar e = \"3.19.0\";\nvar s = \"3.19.0\";\nvar t = \"3.19.0\";\nvar i = \"3.19.0\";\nvar n = \"3.19.0\";\nvar r = \"3.19.0\";\nvar l = \"3.19.0\";\nvar V = { tfjs: e, \"tfjs-core\": s, \"tfjs-data\": t, \"tfjs-layers\": i, \"tfjs-converter\": n, \"tfjs-backend-webgl\": r, \"tfjs-backend-wasm\": l };\nexport {\n  Abs,\n  Acos,\n  Acosh,\n  AdadeltaOptimizer,\n  AdagradOptimizer,\n  AdamOptimizer,\n  AdamaxOptimizer,\n  Add,\n  AddN,\n  All,\n  Any,\n  ArgMax,\n  ArgMin,\n  Asin,\n  Asinh,\n  Atan,\n  Atan2,\n  Atanh,\n  AvgPool,\n  AvgPool3D,\n  AvgPool3DGrad,\n  AvgPoolGrad,\n  BackendWasm,\n  BatchMatMul,\n  BatchToSpaceND,\n  Bincount,\n  BroadcastArgs,\n  BroadcastTo,\n  Callback,\n  CallbackList,\n  Cast,\n  Ceil,\n  ClipByValue,\n  Complex,\n  ComplexAbs,\n  Concat,\n  Conv2D,\n  Conv2DBackpropFilter,\n  Conv2DBackpropInput,\n  Conv3D,\n  Conv3DBackpropFilterV2,\n  Conv3DBackpropInputV2,\n  Cos,\n  Cosh,\n  CropAndResize,\n  Cumprod,\n  Cumsum,\n  CustomCallback,\n  DataStorage,\n  DenseBincount,\n  DepthToSpace,\n  DepthwiseConv2dNative,\n  DepthwiseConv2dNativeBackpropFilter,\n  DepthwiseConv2dNativeBackpropInput,\n  Diag,\n  Dilation2D,\n  Dilation2DBackpropFilter,\n  Dilation2DBackpropInput,\n  ENV,\n  EarlyStopping,\n  Einsum,\n  Elu,\n  EluGrad,\n  Environment,\n  Equal,\n  Erf,\n  Exp,\n  ExpandDims,\n  Expm1,\n  FFT,\n  Fill,\n  FlipLeftRight,\n  Floor,\n  FloorDiv,\n  FromPixels,\n  FusedBatchNorm,\n  FusedConv2D,\n  FusedDepthwiseConv2D,\n  GPGPUContext,\n  GatherNd,\n  GatherV2,\n  GraphModel,\n  Greater,\n  GreaterEqual,\n  History,\n  IFFT,\n  Identity,\n  Imag,\n  InputSpec,\n  IsFinite,\n  IsInf,\n  IsNan,\n  KernelBackend,\n  LRN,\n  LRNGrad,\n  LayerVariable,\n  LayersModel,\n  LeakyRelu,\n  Less,\n  LessEqual,\n  LinSpace,\n  Log,\n  Log1p,\n  LogSoftmax,\n  LogicalAnd,\n  LogicalNot,\n  LogicalOr,\n  LogicalXor,\n  LowerBound,\n  MathBackendWebGL,\n  Max,\n  MaxPool,\n  MaxPool3D,\n  MaxPool3DGrad,\n  MaxPoolGrad,\n  MaxPoolWithArgmax,\n  Maximum,\n  Mean,\n  Min,\n  Minimum,\n  MirrorPad,\n  Mod,\n  MomentumOptimizer,\n  Multinomial,\n  Multiply,\n  Neg,\n  NonMaxSuppressionV3,\n  NonMaxSuppressionV4,\n  NonMaxSuppressionV5,\n  NotEqual,\n  OP_SCOPE_SUFFIX,\n  OneHot,\n  OnesLike,\n  Optimizer,\n  OptimizerConstructors,\n  Pack,\n  PadV2,\n  Pool,\n  Pow,\n  Prelu,\n  Prod,\n  RMSPropOptimizer,\n  RNN,\n  Range,\n  Rank,\n  Real,\n  RealDiv,\n  Reciprocal,\n  Reduction,\n  Relu,\n  Relu6,\n  Reshape,\n  ResizeBilinear,\n  ResizeBilinearGrad,\n  ResizeNearestNeighbor,\n  ResizeNearestNeighborGrad,\n  Reverse,\n  RotateWithOffset,\n  Round,\n  Rsqrt,\n  SGDOptimizer,\n  ScatterNd,\n  SearchSorted,\n  Select,\n  Selu,\n  Sequential,\n  Sigmoid,\n  Sign,\n  Sin,\n  Sinh,\n  Slice,\n  Softmax,\n  Softplus,\n  SpaceToBatchND,\n  SparseFillEmptyRows,\n  SparseReshape,\n  SparseSegmentMean,\n  SparseSegmentSum,\n  SparseToDense,\n  SplitV,\n  Sqrt,\n  Square,\n  SquaredDifference,\n  Step,\n  StridedSlice,\n  StringNGrams,\n  StringSplit,\n  StringToHashBucketFast,\n  Sub,\n  Sum,\n  SymbolicTensor,\n  Tan,\n  Tanh,\n  Tensor,\n  TensorBuffer,\n  Tile,\n  TopK,\n  Transform,\n  Transpose,\n  Unique,\n  Unpack,\n  UnsortedSegmentSum,\n  UpperBound,\n  Variable,\n  ZerosLike,\n  _FusedMatMul,\n  abs,\n  acos,\n  acosh,\n  add2 as add,\n  addN,\n  all,\n  any,\n  argMax,\n  argMin,\n  asin,\n  asinh,\n  atan,\n  atan2,\n  atanh,\n  avgPool,\n  avgPool3d,\n  backend,\n  backend_util_exports as backend_util,\n  basicLSTMCell,\n  batchNorm,\n  batchNorm2d,\n  batchNorm3d,\n  batchNorm4d,\n  batchToSpaceND,\n  bincount,\n  booleanMaskAsync,\n  broadcastArgs,\n  broadcastTo,\n  broadcast_util_exports as broadcast_util,\n  browser_exports as browser,\n  buffer,\n  callbacks,\n  cast,\n  ceil,\n  clipByValue,\n  clone,\n  complex,\n  concat,\n  concat1d,\n  concat2d,\n  concat3d,\n  concat4d,\n  exports_constraints_exports as constraints,\n  conv1d,\n  conv2d,\n  conv2dTranspose,\n  conv3d,\n  conv3dTranspose,\n  copyRegisteredKernels,\n  cos,\n  cosh,\n  cosineWindow,\n  cumprod,\n  cumsum,\n  customGrad,\n  dist_exports2 as data,\n  denseBincount,\n  deprecationWarn,\n  depthToSpace,\n  depthwiseConv2d,\n  deregisterOp,\n  device_util_exports as device_util,\n  diag,\n  dilation2d,\n  disableDeprecationWarnings,\n  dispose,\n  disposeVariables,\n  div,\n  divNoNan,\n  dot,\n  dropout,\n  einsum,\n  elu,\n  enableDebugMode,\n  enableProdMode,\n  enclosingPowerOfTwo,\n  engine,\n  env,\n  equal,\n  erf,\n  euclideanNorm,\n  exp,\n  expandDims,\n  expm1,\n  eye,\n  fft,\n  fill,\n  findBackend,\n  findBackendFactory,\n  floor,\n  floorDiv,\n  forceHalfFloat,\n  fused_ops_exports as fused,\n  gather,\n  gatherND,\n  gather_nd_util_exports as gather_util,\n  getBackend,\n  getGradient,\n  getKernel,\n  getKernelsForBackend,\n  getThreadsCount,\n  gpgpu_util_exports as gpgpu_util,\n  grad,\n  grads,\n  greater,\n  greaterEqual,\n  ifft,\n  imag,\n  image,\n  inTopKAsync,\n  exports_initializers_exports as initializers,\n  input,\n  io_exports as io,\n  irfft,\n  isFinite2 as isFinite,\n  isInf,\n  isNaN2 as isNaN,\n  keep,\n  kernel_impls_exports as kernel_impls,\n  exports_layers_exports as layers,\n  leakyRelu,\n  less,\n  lessEqual,\n  linalg,\n  linspace,\n  loadGraphModel,\n  loadGraphModelSync,\n  loadLayersModel,\n  localResponseNormalization,\n  log2 as log,\n  log1p,\n  logSigmoid,\n  logSoftmax,\n  logSumExp,\n  logicalAnd,\n  logicalNot,\n  logicalOr,\n  logicalXor,\n  losses,\n  lowerBound,\n  matMul,\n  math_exports as math,\n  max,\n  maxPool,\n  maxPool3d,\n  maxPoolWithArgmax,\n  maximum,\n  mean,\n  memory,\n  meshgrid,\n  exports_metrics_exports as metrics,\n  min,\n  minimum,\n  mirrorPad,\n  mod,\n  model,\n  exports_models_exports as models,\n  moments,\n  movingAverage,\n  mul,\n  multiRNNCell,\n  multinomial,\n  neg,\n  nextFrame,\n  norm,\n  notEqual,\n  oneHot,\n  ones2 as ones,\n  onesLike,\n  op,\n  outerProduct,\n  pad,\n  pad1d,\n  pad2d,\n  pad3d,\n  pad4d,\n  pool,\n  pow,\n  prelu,\n  print,\n  prod,\n  profile,\n  rand,\n  randomGamma,\n  randomNormal,\n  randomStandardNormal,\n  randomUniform,\n  range,\n  ready,\n  real,\n  reciprocal,\n  registerBackend,\n  registerCallbackConstructor,\n  registerGradient,\n  registerKernel,\n  registerOp,\n  exports_regularizers_exports as regularizers,\n  relu,\n  relu6,\n  removeBackend,\n  reshape,\n  reverse,\n  reverse1d,\n  reverse2d,\n  reverse3d,\n  reverse4d,\n  rfft,\n  round2 as round,\n  rsqrt,\n  scalar,\n  scatterND,\n  scatter_nd_util_exports as scatter_util,\n  searchSorted,\n  selu,\n  separableConv2d,\n  sequential,\n  serialization_exports as serialization,\n  setBackend,\n  setPlatform,\n  setThreadsCount,\n  setWasmPath,\n  setWasmPaths,\n  setWebGLContext,\n  setdiff1dAsync,\n  sigmoid,\n  sign,\n  signal,\n  sin,\n  sinh,\n  slice,\n  slice1d,\n  slice2d,\n  slice3d,\n  slice4d,\n  slice_util_exports as slice_util,\n  softmax,\n  softplus,\n  spaceToBatchND,\n  sparse,\n  sparseToDense,\n  spectral,\n  split,\n  sqrt,\n  square,\n  squaredDifference,\n  squeeze,\n  stack,\n  step,\n  stridedSlice,\n  string,\n  sub,\n  sum2 as sum,\n  sumOutType,\n  tan,\n  tanh2 as tanh,\n  tensor,\n  tensor1d,\n  tensor2d,\n  tensor3d,\n  tensor4d,\n  tensor5d,\n  tensor6d,\n  tensor_util_exports as tensor_util,\n  test_util_exports as test_util,\n  tidy,\n  tile,\n  time,\n  topk,\n  train,\n  transpose,\n  truncatedNormal,\n  unique,\n  unregisterGradient,\n  unregisterKernel,\n  unsortedSegmentSum,\n  unstack,\n  upcastType,\n  upperBound,\n  util_exports as util,\n  valueAndGrad,\n  valueAndGrads,\n  variable,\n  variableGrads,\n  V as version,\n  version3 as version_converter,\n  version as version_core,\n  version2 as version_layers,\n  version8 as version_wasm,\n  version6 as version_webgl,\n  webgl,\n  webgl_util_exports as webgl_util,\n  webgpu_exports as webgpu,\n  where,\n  whereAsync,\n  zeros,\n  zerosLike\n};\n", "export const vertexIdentity = `\n  precision highp float;\n  attribute vec2 pos;\n  attribute vec2 uv;\n  varying vec2 vUv;\n  uniform float flipY;\n  void main(void) {\n    vUv = uv;\n    gl_Position = vec4(pos.x, pos.y*flipY, 0.0, 1.);\n  }\n`;\n\nexport const fragmentIdentity = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  void main(void) {\n    gl_FragColor = texture2D(texture, vUv);\n  }\n`;\n\nexport const colorMatrixWithAlpha = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform float m[20];\n  void main(void) {\n    vec4 c = texture2D(texture, vUv);\n    gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[3] * c.a + m[4];\n    gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[8] * c.a + m[9];\n    gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[13] * c.a + m[14];\n    gl_FragColor.a = m[15] * c.r + m[16] * c.g + m[17] * c.b + m[18] * c.a + m[19];\n  }\n`;\n\nexport const colorMatrixWithoutAlpha = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform float m[20];\n  void main(void) {\n    vec4 c = texture2D(texture, vUv);\n    gl_FragColor.r = m[0] * c.r + m[1] * c.g + m[2] * c.b + m[4];\n    gl_FragColor.g = m[5] * c.r + m[6] * c.g + m[7] * c.b + m[9];\n    gl_FragColor.b = m[10] * c.r + m[11] * c.g + m[12] * c.b + m[14];\n    gl_FragColor.a = c.a;\n  }\n`;\n\nexport const pixelate = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform vec2 size;\n  uniform sampler2D texture;\n  vec2 pixelate(vec2 coord, vec2 size) {\n    return floor( coord / size ) * size;\n  }\n  void main(void) {\n    gl_FragColor = vec4(0.0);\n    vec2 coord = pixelate(vUv, size);\n    gl_FragColor += texture2D(texture, coord);\n  }\n`;\n\nexport const blur = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform vec2 px;\n  void main(void) {\n    gl_FragColor = vec4(0.0);\n    gl_FragColor += texture2D(texture, vUv + vec2(-7.0*px.x, -7.0*px.y))*0.0044299121055113265;\n    gl_FragColor += texture2D(texture, vUv + vec2(-6.0*px.x, -6.0*px.y))*0.00895781211794;\n    gl_FragColor += texture2D(texture, vUv + vec2(-5.0*px.x, -5.0*px.y))*0.0215963866053;\n    gl_FragColor += texture2D(texture, vUv + vec2(-4.0*px.x, -4.0*px.y))*0.0443683338718;\n    gl_FragColor += texture2D(texture, vUv + vec2(-3.0*px.x, -3.0*px.y))*0.0776744219933;\n    gl_FragColor += texture2D(texture, vUv + vec2(-2.0*px.x, -2.0*px.y))*0.115876621105;\n    gl_FragColor += texture2D(texture, vUv + vec2(-1.0*px.x, -1.0*px.y))*0.147308056121;\n    gl_FragColor += texture2D(texture, vUv                             )*0.159576912161;\n    gl_FragColor += texture2D(texture, vUv + vec2( 1.0*px.x,  1.0*px.y))*0.147308056121;\n    gl_FragColor += texture2D(texture, vUv + vec2( 2.0*px.x,  2.0*px.y))*0.115876621105;\n    gl_FragColor += texture2D(texture, vUv + vec2( 3.0*px.x,  3.0*px.y))*0.0776744219933;\n    gl_FragColor += texture2D(texture, vUv + vec2( 4.0*px.x,  4.0*px.y))*0.0443683338718;\n    gl_FragColor += texture2D(texture, vUv + vec2( 5.0*px.x,  5.0*px.y))*0.0215963866053;\n    gl_FragColor += texture2D(texture, vUv + vec2( 6.0*px.x,  6.0*px.y))*0.00895781211794;\n    gl_FragColor += texture2D(texture, vUv + vec2( 7.0*px.x,  7.0*px.y))*0.0044299121055113265;\n  }\n`;\n\nexport const convolution = `\n  precision highp float;\n  varying vec2 vUv;\n  uniform sampler2D texture;\n  uniform vec2 px;\n  uniform float m[9];\n  void main(void) {\n    vec4 c11 = texture2D(texture, vUv - px); // top left\n    vec4 c12 = texture2D(texture, vec2(vUv.x, vUv.y - px.y)); // top center\n    vec4 c13 = texture2D(texture, vec2(vUv.x + px.x, vUv.y - px.y)); // top right\n    vec4 c21 = texture2D(texture, vec2(vUv.x - px.x, vUv.y) ); // mid left\n    vec4 c22 = texture2D(texture, vUv); // mid center\n    vec4 c23 = texture2D(texture, vec2(vUv.x + px.x, vUv.y) ); // mid right\n    vec4 c31 = texture2D(texture, vec2(vUv.x - px.x, vUv.y + px.y) ); // bottom left\n    vec4 c32 = texture2D(texture, vec2(vUv.x, vUv.y + px.y) ); // bottom center\n    vec4 c33 = texture2D(texture, vUv + px ); // bottom right\n    gl_FragColor = \n    c11 * m[0] + c12 * m[1] + c22 * m[2] +\n    c21 * m[3] + c22 * m[4] + c23 * m[5] +\n    c31 * m[6] + c32 * m[7] + c33 * m[8];\n    gl_FragColor.a = c22.a;\n  }\n`;\n", "/**\n * Image Filters in WebGL algoritm implementation\n * Based on: [WebGLImageFilter](https://github.com/phoboslab/WebGLImageFilter)\n */\n\nimport * as shaders from './imagefxshaders';\nimport { canvas } from './image';\nimport { log } from '../util/util';\n\nconst collect = (source, prefix, collection) => {\n  const r = new RegExp('\\\\b' + prefix + ' \\\\w+ (\\\\w+)', 'ig');\n  source.replace(r, (match, name) => {\n    collection[name] = 0;\n    return match;\n  });\n};\n\nclass GLProgram {\n  uniform = {};\n  attribute = {};\n  gl: WebGLRenderingContext;\n  id: WebGLProgram;\n\n  constructor(gl, vertexSource, fragmentSource) {\n    this.gl = gl;\n    const vertexShader = this.compile(vertexSource, this.gl.VERTEX_SHADER);\n    const fragmentShader = this.compile(fragmentSource, this.gl.FRAGMENT_SHADER);\n    this.id = this.gl.createProgram() as WebGLProgram;\n    if (!vertexShader || !fragmentShader) return;\n    if (!this.id) {\n      log('filter: could not create webgl program');\n      return;\n    }\n    this.gl.attachShader(this.id, vertexShader);\n    this.gl.attachShader(this.id, fragmentShader);\n    this.gl.linkProgram(this.id);\n    if (!this.gl.getProgramParameter(this.id, this.gl.LINK_STATUS)) {\n      log(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);\n      return;\n    }\n    this.gl.useProgram(this.id);\n    collect(vertexSource, 'attribute', this.attribute); // Collect attributes\n    for (const a in this.attribute) this.attribute[a] = this.gl.getAttribLocation(this.id, a);\n    collect(vertexSource, 'uniform', this.uniform); // Collect uniforms\n    collect(fragmentSource, 'uniform', this.uniform);\n    for (const u in this.uniform) this.uniform[u] = this.gl.getUniformLocation(this.id, u);\n  }\n\n  compile = (source, type): WebGLShader | null => {\n    const shader = this.gl.createShader(type) as WebGLShader;\n    if (!shader) {\n      log('filter: could not create shader');\n      return null;\n    }\n    this.gl.shaderSource(shader, source);\n    this.gl.compileShader(shader);\n    if (!this.gl.getShaderParameter(shader, this.gl.COMPILE_STATUS)) {\n      log(`filter: gl compile failed: ${this.gl.getShaderInfoLog(shader)}`);\n      return null;\n    }\n    return shader;\n  };\n}\n\n// function that is instantiated as class so it has private this members\n/**\n * @class GLImageFilter\n * @property {function} reset reset current filter chain\n * @property {function} add add specified filter to filter chain\n * @property {function} apply execute filter chain and draw result\n * @property {function} draw just draw input to result\n */\n\nexport function GLImageFilter() {\n  let drawCount = 0;\n  let sourceTexture: WebGLTexture | null = null;\n  let lastInChain = false;\n  let currentFramebufferIndex = -1;\n  let tempFramebuffers: [null, null] | [{ fbo: WebGLFramebuffer | null, texture: WebGLTexture | null }] = [null, null];\n  let filterChain: Record<string, unknown>[] = [];\n  let vertexBuffer: WebGLBuffer | null = null;\n  let currentProgram: GLProgram | null = null;\n  const fxcanvas = canvas(100, 100);\n  const shaderProgramCache = { }; // key is the shader program source, value is the compiled program\n  const DRAW = { INTERMEDIATE: 1 };\n  const gl = fxcanvas.getContext('webgl') as WebGLRenderingContext;\n  if (!gl) {\n    log('filter: cannot get webgl context');\n    return;\n  }\n  // @ts-ignore used for sanity checks outside of imagefx\n  this.gl = gl;\n\n  function resize(width, height) {\n    if (width === fxcanvas.width && height === fxcanvas.height) return; // Same width/height? Nothing to do here\n    fxcanvas.width = width;\n    fxcanvas.height = height;\n    if (!vertexBuffer) { // Create the context if we don't have it yet\n      const vertices = new Float32Array([-1, -1, 0, 1, 1, -1, 1, 1, -1, 1, 0, 0, -1, 1, 0, 0, 1, -1, 1, 1, 1, 1, 1, 0]); // Create the vertex buffer for the two triangles [x, y, u, v] * 6\n      vertexBuffer = gl.createBuffer();\n      gl.bindBuffer(gl.ARRAY_BUFFER, vertexBuffer);\n      gl.bufferData(gl.ARRAY_BUFFER, vertices, gl.STATIC_DRAW);\n      gl.pixelStorei(gl.UNPACK_PREMULTIPLY_ALPHA_WEBGL, true);\n    }\n    gl.viewport(0, 0, fxcanvas.width, fxcanvas.height);\n    tempFramebuffers = [null, null]; // Delete old temp framebuffers\n  }\n\n  function createFramebufferTexture(width, height) {\n    const fbo = gl.createFramebuffer() as WebGLFramebuffer;\n    gl.bindFramebuffer(gl.FRAMEBUFFER, fbo);\n    const renderbuffer = gl.createRenderbuffer();\n    gl.bindRenderbuffer(gl.RENDERBUFFER, renderbuffer);\n    const texture = gl.createTexture() as WebGLTexture;\n    gl.bindTexture(gl.TEXTURE_2D, texture);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, width, height, 0, gl.RGBA, gl.UNSIGNED_BYTE, null);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.LINEAR);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.framebufferTexture2D(gl.FRAMEBUFFER, gl.COLOR_ATTACHMENT0, gl.TEXTURE_2D, texture, 0);\n    gl.bindTexture(gl.TEXTURE_2D, null);\n    gl.bindFramebuffer(gl.FRAMEBUFFER, null);\n    return { fbo, texture };\n  }\n\n  function getTempFramebuffer(index): { fbo: WebGLFramebuffer | null, texture: WebGLTexture | null } {\n    tempFramebuffers[index] = tempFramebuffers[index] || createFramebufferTexture(fxcanvas.width, fxcanvas.height);\n    return tempFramebuffers[index] as { fbo: WebGLFramebuffer, texture: WebGLTexture };\n  }\n\n  function draw(flags = 0) {\n    if (!currentProgram) return;\n    let source: WebGLTexture | null = null;\n    let target: WebGLFramebuffer | null = null;\n    let flipY = false;\n    if (drawCount === 0) source = sourceTexture; // First draw call - use the source texture\n    else source = getTempFramebuffer(currentFramebufferIndex).texture || null; // All following draw calls use the temp buffer last drawn to\n    drawCount++;\n    if (lastInChain && !(flags & DRAW.INTERMEDIATE)) { // Last filter in our chain - draw directly to the WebGL Canvas. We may also have to flip the image vertically now\n      target = null;\n      flipY = drawCount % 2 === 0;\n    } else {\n      currentFramebufferIndex = (currentFramebufferIndex + 1) % 2;\n      target = getTempFramebuffer(currentFramebufferIndex).fbo || null; // Intermediate draw call - get a temp buffer to draw to\n    }\n    gl.bindTexture(gl.TEXTURE_2D, source); // Bind the source and target and draw the two triangles\n    gl.bindFramebuffer(gl.FRAMEBUFFER, target);\n    gl.uniform1f(currentProgram.uniform['flipY'], (flipY ? -1 : 1));\n    gl.drawArrays(gl.TRIANGLES, 0, 6);\n  }\n\n  function compileShader(fragmentSource): GLProgram | null {\n    if (shaderProgramCache[fragmentSource]) {\n      currentProgram = shaderProgramCache[fragmentSource];\n      gl.useProgram((currentProgram ? currentProgram.id : null) || null);\n      return currentProgram as GLProgram;\n    }\n    currentProgram = new GLProgram(gl, shaders.vertexIdentity, fragmentSource);\n    if (!currentProgram) {\n      log('filter: could not get webgl program');\n      return null;\n    }\n    const floatSize = Float32Array.BYTES_PER_ELEMENT;\n    const vertSize = 4 * floatSize;\n    gl.enableVertexAttribArray(currentProgram.attribute['pos']);\n    gl.vertexAttribPointer(currentProgram.attribute['pos'], 2, gl.FLOAT, false, vertSize, 0 * floatSize);\n    gl.enableVertexAttribArray(currentProgram.attribute['uv']);\n    gl.vertexAttribPointer(currentProgram.attribute['uv'], 2, gl.FLOAT, false, vertSize, 2 * floatSize);\n    shaderProgramCache[fragmentSource] = currentProgram;\n    return currentProgram as GLProgram;\n  }\n\n  const filter = {\n    colorMatrix: (matrix) => { // general color matrix filter\n      const m = new Float32Array(matrix);\n      m[4] /= 255;\n      m[9] /= 255;\n      m[14] /= 255;\n      m[19] /= 255;\n      const shader = (m[18] === 1 && m[3] === 0 && m[8] === 0 && m[13] === 0 && m[15] === 0 && m[16] === 0 && m[17] === 0 && m[19] === 0) // Can we ignore the alpha value? Makes things a bit faster.\n        ? shaders.colorMatrixWithoutAlpha\n        : shaders.colorMatrixWithAlpha;\n      const program = compileShader(shader);\n      if (!program) return;\n      gl.uniform1fv(program.uniform['m'], m);\n      draw();\n    },\n\n    brightness: (brightness) => {\n      const b = (brightness || 0) + 1;\n      filter.colorMatrix([\n        b, 0, 0, 0, 0,\n        0, b, 0, 0, 0,\n        0, 0, b, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    saturation: (amount) => {\n      const x = (amount || 0) * 2 / 3 + 1;\n      const y = ((x - 1) * -0.5);\n      filter.colorMatrix([\n        x, y, y, 0, 0,\n        y, x, y, 0, 0,\n        y, y, x, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    desaturate: () => {\n      filter.saturation(-1);\n    },\n\n    contrast: (amount) => {\n      const v = (amount || 0) + 1;\n      const o = -128 * (v - 1);\n      filter.colorMatrix([\n        v, 0, 0, 0, o,\n        0, v, 0, 0, o,\n        0, 0, v, 0, o,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    negative: () => {\n      filter.contrast(-2);\n    },\n\n    hue: (rotation) => {\n      rotation = (rotation || 0) / 180 * Math.PI;\n      const cos = Math.cos(rotation);\n      const sin = Math.sin(rotation);\n      const lumR = 0.213;\n      const lumG = 0.715;\n      const lumB = 0.072;\n      filter.colorMatrix([\n        lumR + cos * (1 - lumR) + sin * (-lumR), lumG + cos * (-lumG) + sin * (-lumG), lumB + cos * (-lumB) + sin * (1 - lumB), 0, 0,\n        lumR + cos * (-lumR) + sin * (0.143), lumG + cos * (1 - lumG) + sin * (0.140), lumB + cos * (-lumB) + sin * (-0.283), 0, 0,\n        lumR + cos * (-lumR) + sin * (-(1 - lumR)), lumG + cos * (-lumG) + sin * (lumG), lumB + cos * (1 - lumB) + sin * (lumB), 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    desaturateLuminance: () => {\n      filter.colorMatrix([\n        0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n        0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n        0.2764723, 0.9297080, 0.0938197, 0, -37.1,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    sepia: () => {\n      filter.colorMatrix([\n        0.393, 0.7689999, 0.18899999, 0, 0,\n        0.349, 0.6859999, 0.16799999, 0, 0,\n        0.272, 0.5339999, 0.13099999, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    brownie: () => {\n      filter.colorMatrix([\n        0.5997023498159715, 0.34553243048391263, -0.2708298674538042, 0, 47.43192855600873,\n        -0.037703249837783157, 0.8609577587992641, 0.15059552388459913, 0, -36.96841498319127,\n        0.24113635128153335, -0.07441037908422492, 0.44972182064877153, 0, -7.562075277591283,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    vintagePinhole: () => {\n      filter.colorMatrix([\n        0.6279345635605994, 0.3202183420819367, -0.03965408211312453, 0, 9.651285835294123,\n        0.02578397704808868, 0.6441188644374771, 0.03259127616149294, 0, 7.462829176470591,\n        0.0466055556782719, -0.0851232987247891, 0.5241648018700465, 0, 5.159190588235296,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    kodachrome: () => {\n      filter.colorMatrix([\n        1.1285582396593525, -0.3967382283601348, -0.03992559172921793, 0, 63.72958762196502,\n        -0.16404339962244616, 1.0835251566291304, -0.05498805115633132, 0, 24.732407896706203,\n        -0.16786010706155763, -0.5603416277695248, 1.6014850761964943, 0, 35.62982807460946,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    technicolor: () => {\n      filter.colorMatrix([\n        1.9125277891456083, -0.8545344976951645, -0.09155508482755585, 0, 11.793603434377337,\n        -0.3087833385928097, 1.7658908555458428, -0.10601743074722245, 0, -70.35205161461398,\n        -0.231103377548616, -0.7501899197440212, 1.847597816108189, 0, 30.950940869491138,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    polaroid: () => {\n      filter.colorMatrix([\n        1.438, -0.062, -0.062, 0, 0,\n        -0.122, 1.378, -0.122, 0, 0,\n        -0.016, -0.016, 1.483, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    shiftToBGR: () => {\n      filter.colorMatrix([\n        0, 0, 1, 0, 0,\n        0, 1, 0, 0, 0,\n        1, 0, 0, 0, 0,\n        0, 0, 0, 1, 0,\n      ]);\n    },\n\n    convolution: (matrix) => { // general convolution Filter\n      const m = new Float32Array(matrix);\n      const pixelSizeX = 1 / fxcanvas.width;\n      const pixelSizeY = 1 / fxcanvas.height;\n      const program = compileShader(shaders.convolution);\n      if (!program) return;\n      gl.uniform1fv(program.uniform['m'], m);\n      gl.uniform2f(program.uniform['px'], pixelSizeX, pixelSizeY);\n      draw();\n    },\n\n    detectEdges: () => {\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        0, 1, 0,\n        1, -4, 1,\n        0, 1, 0,\n      ]);\n    },\n\n    sobelX: () => {\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        -1, 0, 1,\n        -2, 0, 2,\n        -1, 0, 1,\n      ]);\n    },\n\n    sobelY: () => {\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        -1, -2, -1,\n        0, 0, 0,\n        1, 2, 1,\n      ]);\n    },\n\n    sharpen: (amount) => {\n      const a = amount || 1;\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        0, -1 * a, 0,\n        -1 * a, 1 + 4 * a, -1 * a,\n        0, -1 * a, 0,\n      ]);\n    },\n\n    emboss: (size) => {\n      const s = size || 1;\n      // @ts-ignore this\n      filter.convolution.call(this, [\n        -2 * s, -1 * s, 0,\n        -1 * s, 1, 1 * s,\n        0, 1 * s, 2 * s,\n      ]);\n    },\n\n    blur: (size) => {\n      const blurSizeX = (size / 7) / fxcanvas.width;\n      const blurSizeY = (size / 7) / fxcanvas.height;\n      const program = compileShader(shaders.blur);\n      if (!program) return;\n      // Vertical\n      gl.uniform2f(program.uniform['px'], 0, blurSizeY);\n      draw(DRAW.INTERMEDIATE);\n      // Horizontal\n      gl.uniform2f(program.uniform['px'], blurSizeX, 0);\n      draw();\n    },\n\n    pixelate: (size) => {\n      const blurSizeX = (size) / fxcanvas.width;\n      const blurSizeY = (size) / fxcanvas.height;\n      const program = compileShader(shaders.pixelate);\n      if (!program) return;\n      gl.uniform2f(program.uniform['size'], blurSizeX, blurSizeY);\n      draw();\n    },\n  };\n\n  // @ts-ignore this\n  this.add = function (name) {\n    // eslint-disable-next-line prefer-rest-params\n    const args = Array.prototype.slice.call(arguments, 1);\n    const func = filter[name];\n    filterChain.push({ func, args });\n  };\n\n  // @ts-ignore this\n  this.reset = function () {\n    filterChain = [];\n  };\n\n  // @ts-ignore this\n  this.get = function () {\n    return filterChain;\n  };\n\n  // @ts-ignore this\n  this.apply = function (image) {\n    resize(image.width, image.height);\n    drawCount = 0;\n    if (!sourceTexture) sourceTexture = gl.createTexture(); // Create the texture for the input image if we haven't yet\n    gl.bindTexture(gl.TEXTURE_2D, sourceTexture);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_S, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_WRAP_T, gl.CLAMP_TO_EDGE);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MIN_FILTER, gl.NEAREST);\n    gl.texParameteri(gl.TEXTURE_2D, gl.TEXTURE_MAG_FILTER, gl.NEAREST);\n    gl.texImage2D(gl.TEXTURE_2D, 0, gl.RGBA, gl.RGBA, gl.UNSIGNED_BYTE, image);\n    for (let i = 0; i < filterChain.length; i++) {\n      lastInChain = (i === filterChain.length - 1);\n      const f = filterChain[i];\n      // @ts-ignore function assigment\n      f.func.apply(this, f.args || []);\n    }\n    return fxcanvas;\n  };\n\n  // @ts-ignore this\n  this.draw = function (image) {\n    this.add('brightness', 0);\n    return this.apply(image);\n  };\n}\n", "/**\n * Image enhancements\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from '../exports';\n\nexport async function histogramEqualization(inputImage: Tensor): Promise<Tensor> {\n  // const maxValue = 254; // using 255 results in values slightly larger than 1 due to math rounding errors\n  const squeeze = inputImage.shape.length === 4 ? tf.squeeze(inputImage) : inputImage;\n  const channels = tf.split(squeeze, 3, 2);\n  const min: Tensor[] = [tf.min(channels[0]), tf.min(channels[1]), tf.min(channels[2])];\n  const max: Tensor[] = [tf.max(channels[0]), tf.max(channels[1]), tf.max(channels[2])];\n  const absMax = await Promise.all(max.map((channel) => channel.data()));\n  const maxValue = 0.99 * Math.max(absMax[0][0], absMax[1][0], absMax[2][0]);\n  const sub = [tf.sub(channels[0], min[0]), tf.sub(channels[1], min[1]), tf.sub(channels[2], min[2])];\n  const range = [tf.sub(max[0], min[0]), tf.sub(max[1], min[1]), tf.sub(max[2], min[2])];\n  const fact = [tf.div(maxValue, range[0]), tf.div(maxValue, range[1]), tf.div(maxValue, range[2])];\n  const enh = [tf.mul(sub[0], fact[0]), tf.mul(sub[1], fact[1]), tf.mul(sub[2], fact[2])];\n  const rgb = tf.stack([enh[0], enh[1], enh[2]], 2);\n  const reshape = tf.reshape(rgb, [1, squeeze.shape[0], squeeze.shape[1], 3]);\n  tf.dispose([...channels, ...min, ...max, ...sub, ...range, ...fact, ...enh, rgb, squeeze]);\n  return reshape; // output shape is [1, height, width, 3]\n}\n", "/**\n * Image Processing algorithm implementation\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as fxImage from './imagefx';\nimport type { Input, AnyCanvas, Tensor, Config } from '../exports';\nimport { env } from '../util/env';\nimport { log } from '../util/util';\nimport * as enhance from './enhance';\n\nconst maxSize = 3840;\n// internal temp canvases\nlet inCanvas: AnyCanvas | null = null; // use global variable to avoid recreating canvas on each frame\nlet outCanvas: AnyCanvas | null = null; // use global variable to avoid recreating canvas on each frame\nlet tmpCanvas: AnyCanvas | null = null; // use global variable to avoid recreating canvas on each frame\n// @ts-ignore // imagefx is js module that should be converted to a class\nlet fx: fxImage.GLImageFilter | null; // instance of imagefx\n\nconst last: { inputSum: number, cacheDiff: number, sumMethod: number, inputTensor: undefined | Tensor } = {\n  inputSum: 0,\n  cacheDiff: 1,\n  sumMethod: 0,\n  inputTensor: undefined,\n};\n\nexport function canvas(width: number, height: number): AnyCanvas {\n  let c;\n  if (env.browser) { // browser defines canvas object\n    if (env.worker) { // if runing in web  worker use OffscreenCanvas\n      if (typeof OffscreenCanvas === 'undefined') throw new Error('canvas error: attempted to run in web worker but OffscreenCanvas is not supported');\n      c = new OffscreenCanvas(width, height);\n    } else { // otherwise use DOM canvas\n      if (typeof document === 'undefined') throw new Error('canvas error: attempted to run in browser but DOM is not defined');\n      c = document.createElement('canvas');\n      c.width = width;\n      c.height = height;\n    }\n  } else { // if not running in browser, there is no \"default\" canvas object, so we need monkey patch or fail\n    // @ts-ignore // env.canvas is an external monkey-patch\n    if (typeof env.Canvas !== 'undefined') c = new env.Canvas(width, height);\n    else if (typeof globalThis.Canvas !== 'undefined') c = new globalThis.Canvas(width, height);\n    // else throw new Error('canvas error: attempted to use canvas in nodejs without canvas support installed');\n  }\n  return c;\n}\n\n// helper function to copy canvas from input to output\nexport function copy(input: AnyCanvas, output?: AnyCanvas) {\n  const outputCanvas = output || canvas(input.width, input.height);\n  const ctx = outputCanvas.getContext('2d') as CanvasRenderingContext2D;\n  ctx.drawImage(input, 0, 0);\n  return outputCanvas;\n}\n\n// process input image and return tensor\n// input can be tensor, imagedata, htmlimageelement, htmlvideoelement\n// input is resized and run through imagefx filter\nexport async function process(input: Input, config: Config, getTensor: boolean = true): Promise<{ tensor: Tensor | null, canvas: AnyCanvas | null }> {\n  if (!input) {\n    // throw new Error('input is missing');\n    if (config.debug) log('input error: input is missing');\n    return { tensor: null, canvas: null }; // video may become temporarily unavailable due to onresize\n  }\n  // sanity checks since different browsers do not implement all dom elements\n  if (\n    !(input instanceof tf.Tensor)\n    && !(typeof Image !== 'undefined' && input instanceof Image)\n    && !(typeof env.Canvas !== 'undefined' && input instanceof env.Canvas)\n    && !(typeof globalThis.Canvas !== 'undefined' && input instanceof globalThis.Canvas)\n    && !(typeof ImageData !== 'undefined' && input instanceof ImageData)\n    && !(typeof ImageBitmap !== 'undefined' && input instanceof ImageBitmap)\n    && !(typeof HTMLImageElement !== 'undefined' && input instanceof HTMLImageElement)\n    && !(typeof HTMLMediaElement !== 'undefined' && input instanceof HTMLMediaElement)\n    && !(typeof HTMLVideoElement !== 'undefined' && input instanceof HTMLVideoElement)\n    && !(typeof HTMLCanvasElement !== 'undefined' && input instanceof HTMLCanvasElement)\n    && !(typeof OffscreenCanvas !== 'undefined' && input instanceof OffscreenCanvas)\n  ) {\n    throw new Error('input error: type is not recognized');\n  }\n  if (input instanceof tf.Tensor) { // if input is tensor use as-is without filters but correct shape as needed\n    let tensor: Tensor | null = null;\n    if ((input as Tensor)['isDisposedInternal']) throw new Error('input error: attempted to use tensor but it is disposed');\n    if (!(input as Tensor)['shape']) throw new Error('input error: attempted to use tensor without a shape');\n    if ((input as Tensor).shape.length === 3) { // [height, width, 3 || 4]\n      if ((input as Tensor).shape[2] === 3) { // [height, width, 3] so add batch\n        tensor = tf.expandDims(input, 0);\n      } else if ((input as Tensor).shape[2] === 4) { // [height, width, 4] so strip alpha and add batch\n        const rgb = tf.slice3d(input, [0, 0, 0], [-1, -1, 3]);\n        tensor = tf.expandDims(rgb, 0);\n        tf.dispose(rgb);\n      }\n    } else if ((input as Tensor).shape.length === 4) { // [1, width, height, 3 || 4]\n      if ((input as Tensor).shape[3] === 3) { // [1, width, height, 3] just clone\n        tensor = tf.clone(input);\n      } else if ((input as Tensor).shape[3] === 4) { // [1, width, height, 4] so strip alpha\n        tensor = tf.slice4d(input, [0, 0, 0, 0], [-1, -1, -1, 3]);\n      }\n    }\n    // at the end shape must be [1, height, width, 3]\n    if (tensor == null || tensor.shape.length !== 4 || tensor.shape[0] !== 1 || tensor.shape[3] !== 3) throw new Error(`input error: attempted to use tensor with unrecognized shape: ${input['shape']}`);\n    if ((tensor as Tensor).dtype === 'int32') {\n      const cast = tf.cast(tensor, 'float32');\n      tf.dispose(tensor);\n      tensor = cast;\n    }\n    return { tensor, canvas: (config.filter.return ? outCanvas : null) };\n  } else {\n    // check if resizing will be needed\n    if (typeof input['readyState'] !== 'undefined' && input['readyState'] <= 2) {\n      if (config.debug) log('input stream is not ready');\n      return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize\n    }\n    const originalWidth = input['naturalWidth'] || input['videoWidth'] || input['width'] || (input['shape'] && (input['shape'][1] > 0));\n    const originalHeight = input['naturalHeight'] || input['videoHeight'] || input['height'] || (input['shape'] && (input['shape'][2] > 0));\n    if (!originalWidth || !originalHeight) {\n      if (config.debug) log('cannot determine input dimensions');\n      return { tensor: null, canvas: inCanvas }; // video may become temporarily unavailable due to onresize\n    }\n    let targetWidth = originalWidth;\n    let targetHeight = originalHeight;\n    if (targetWidth > maxSize) {\n      targetWidth = maxSize;\n      targetHeight = Math.trunc(targetWidth * originalHeight / originalWidth);\n    }\n    if (targetHeight > maxSize) {\n      targetHeight = maxSize;\n      targetWidth = Math.trunc(targetHeight * originalWidth / originalHeight);\n    }\n\n    // create our canvas and resize it if needed\n    if ((config.filter.width || 0) > 0) targetWidth = config.filter.width;\n    else if ((config.filter.height || 0) > 0) targetWidth = originalWidth * ((config.filter.height || 0) / originalHeight);\n    if ((config.filter.height || 0) > 0) targetHeight = config.filter.height;\n    else if ((config.filter.width || 0) > 0) targetHeight = originalHeight * ((config.filter.width || 0) / originalWidth);\n    if (!targetWidth || !targetHeight) throw new Error('input error: cannot determine dimension');\n    if (!inCanvas || (inCanvas?.width !== targetWidth) || (inCanvas?.height !== targetHeight)) inCanvas = canvas(targetWidth, targetHeight);\n\n    // draw input to our canvas\n    const inCtx = inCanvas.getContext('2d') as CanvasRenderingContext2D;\n    if ((typeof ImageData !== 'undefined') && (input instanceof ImageData)) {\n      inCtx.putImageData(input, 0, 0);\n    } else {\n      if (config.filter.flip && typeof inCtx.translate !== 'undefined') {\n        inCtx.translate(originalWidth, 0);\n        inCtx.scale(-1, 1);\n        inCtx.drawImage(input as AnyCanvas, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas?.width, inCanvas?.height);\n        inCtx.setTransform(1, 0, 0, 1, 0, 0); // resets transforms to defaults\n      } else {\n        inCtx.drawImage(input as AnyCanvas, 0, 0, originalWidth, originalHeight, 0, 0, inCanvas?.width, inCanvas?.height);\n      }\n    }\n\n    if (!outCanvas || (inCanvas.width !== outCanvas.width) || (inCanvas?.height !== outCanvas?.height)) outCanvas = canvas(inCanvas.width, inCanvas.height); // init output canvas\n\n    // imagefx transforms using gl from input canvas to output canvas\n    if (config.filter.enabled && env.webgl.supported) {\n      if (!fx) fx = env.browser ? new fxImage.GLImageFilter() : null; // && (typeof document !== 'undefined')\n      env.filter = !!fx;\n      if (!fx || !fx.add) {\n        if (config.debug) log('input process error: cannot initialize filters');\n        env.webgl.supported = false;\n        config.filter.enabled = false;\n        copy(inCanvas, outCanvas); // filter failed to initialize\n        // return { tensor: null, canvas: inCanvas };\n      } else {\n        fx.reset();\n        if (config.filter.brightness !== 0) fx.add('brightness', config.filter.brightness);\n        if (config.filter.contrast !== 0) fx.add('contrast', config.filter.contrast);\n        if (config.filter.sharpness !== 0) fx.add('sharpen', config.filter.sharpness);\n        if (config.filter.blur !== 0) fx.add('blur', config.filter.blur);\n        if (config.filter.saturation !== 0) fx.add('saturation', config.filter.saturation);\n        if (config.filter.hue !== 0) fx.add('hue', config.filter.hue);\n        if (config.filter.negative) fx.add('negative');\n        if (config.filter.sepia) fx.add('sepia');\n        if (config.filter.vintage) fx.add('brownie');\n        if (config.filter.sepia) fx.add('sepia');\n        if (config.filter.kodachrome) fx.add('kodachrome');\n        if (config.filter.technicolor) fx.add('technicolor');\n        if (config.filter.polaroid) fx.add('polaroid');\n        if (config.filter.pixelate !== 0) fx.add('pixelate', config.filter.pixelate);\n        if (fx.get() > 0) outCanvas = fx.apply(inCanvas);\n        else outCanvas = fx.draw(inCanvas);\n      }\n    } else {\n      copy(inCanvas, outCanvas); // if no filters applied, output canvas is input canvas\n      if (fx) fx = null;\n      env.filter = !!fx;\n    }\n\n    if (!getTensor) return { tensor: null, canvas: outCanvas }; // just canvas was requested\n    if (!outCanvas) throw new Error('canvas error: cannot create output');\n\n    // create tensor from image unless input was a tensor already\n    let pixels;\n    let depth = 3;\n    if ((typeof ImageData !== 'undefined' && input instanceof ImageData) || (input['data'] && input['width'] && input['height'])) { // if input is imagedata, just use it\n      if (env.browser && tf.browser) {\n        pixels = tf.browser ? tf.browser.fromPixels(input) : null;\n      } else {\n        depth = input['data'].length / input['height'] / input['width'];\n        // const arr = Uint8Array.from(input['data']);\n        const arr = new Uint8Array(input['data']['buffer']);\n        pixels = tf.tensor(arr, [input['height'], input['width'], depth], 'int32');\n      }\n    } else {\n      if (!tmpCanvas || (outCanvas.width !== tmpCanvas.width) || (outCanvas.height !== tmpCanvas.height)) tmpCanvas = canvas(outCanvas.width, outCanvas.height); // init output canvas\n      if (tf.browser && env.browser) {\n        if (config.backend === 'webgl' || config.backend === 'humangl' || config.backend === 'webgpu') {\n          pixels = tf.browser.fromPixels(outCanvas); // safe to reuse since both backend and context are gl based\n        } else {\n          tmpCanvas = copy(outCanvas); // cannot use output canvas as it already has gl context so we do a silly one more canvas\n          pixels = tf.browser.fromPixels(tmpCanvas);\n        }\n      } else {\n        const tempCanvas = copy(outCanvas); // cannot use output canvas as it already has gl context so we do a silly one more canvas\n        const tempCtx = tempCanvas.getContext('2d') as CanvasRenderingContext2D;\n        const tempData = tempCtx.getImageData(0, 0, targetWidth, targetHeight);\n        depth = tempData.data.length / targetWidth / targetHeight;\n        const arr = new Uint8Array(tempData.data.buffer);\n        pixels = tf.tensor(arr, [targetWidth, targetHeight, depth]);\n      }\n    }\n    if (depth === 4) { // rgba to rgb\n      const rgb = tf.slice3d(pixels, [0, 0, 0], [-1, -1, 3]); // strip alpha channel\n      tf.dispose(pixels);\n      pixels = rgb;\n    }\n    if (!pixels) throw new Error('input error: cannot create tensor');\n    const casted = tf.cast(pixels, 'float32');\n    const tensor = config.filter.equalization ? await enhance.histogramEqualization(casted) : tf.expandDims(casted, 0);\n    tf.dispose([pixels, casted]);\n    return { tensor, canvas: (config.filter.return ? outCanvas : null) };\n  }\n}\n\n/*\nconst checksum = async (input: Tensor): Promise<number> => { // use tf sum or js based sum loop depending on which is faster\n  const resizeFact = 48;\n  const reduced: Tensor = tf.image.resizeBilinear(input, [Math.trunc((input.shape[1] || 1) / resizeFact), Math.trunc((input.shape[2] || 1) / resizeFact)]);\n  const tfSum = async (): Promise<number> => {\n    const sumT = tf.sum(reduced);\n    const sum0 = await sumT.data();\n    tf.dispose(sumT);\n    return sum0[0];\n  };\n  const jsSum = async (): Promise<number> => {\n    const reducedData = await reduced.data(); // raw image rgb array\n    let sum0 = 0;\n    for (let i = 0; i < reducedData.length / 3; i++) sum0 += reducedData[3 * i + 2]; // look only at green value of each pixel\n    return sum0;\n  };\n  if (last.sumMethod === 0) {\n    const t0 = now();\n    await jsSum();\n    const t1 = now();\n    await tfSum();\n    const t2 = now();\n    last.sumMethod = t1 - t0 < t2 - t1 ? 1 : 2;\n  }\n  const res = last.sumMethod === 1 ? await jsSum() : await tfSum();\n  tf.dispose(reduced);\n  return res;\n};\n*/\n\nexport async function skip(config: Partial<Config>, input: Tensor) {\n  let skipFrame = false;\n  if (config.cacheSensitivity === 0 || !input.shape || input.shape.length !== 4 || input.shape[1] > 2048 || input.shape[2] > 2048) return skipFrame; // cache disabled or input is invalid or too large for cache analysis\n\n  /*\n  const checkSum = await checksum(input);\n  const diff = 100 * (Math.max(checkSum, last.inputSum) / Math.min(checkSum, last.inputSum) - 1);\n  last.inputSum = checkSum;\n  // if previous frame was skipped, skip this frame if changed more than cacheSensitivity\n  // if previous frame was not skipped, then look for cacheSensitivity or difference larger than one in previous frame to avoid resetting cache in subsequent frames unnecessarily\n  let skipFrame = diff < Math.max(config.cacheSensitivity, last.cacheDiff);\n  // if difference is above 10x threshold, don't use last value to force reset cache for significant change of scenes or images\n  last.cacheDiff = diff > 10 * config.cacheSensitivity ? 0 : diff;\n  skipFrame = skipFrame && (last.cacheDiff > 0); // if no cached diff value then force no skip\n  */\n\n  if (!last.inputTensor) {\n    last.inputTensor = tf.clone(input);\n  } else if (last.inputTensor.shape[1] !== input.shape[1] || last.inputTensor.shape[2] !== input.shape[2]) { // input resolution changed\n    tf.dispose(last.inputTensor);\n    last.inputTensor = tf.clone(input);\n  } else {\n    const t: Record<string, Tensor> = {};\n    t.diff = tf.sub(input, last.inputTensor);\n    t.squared = tf.mul(t.diff, t.diff);\n    t.sum = tf.sum(t.squared);\n    const diffSum = await t.sum.data();\n    const diffRelative = diffSum[0] / (input.shape[1] || 1) / (input.shape[2] || 1) / 255 / 3; // squared difference relative to input resolution and averaged per channel\n    tf.dispose([last.inputTensor, t.diff, t.squared, t.sum]);\n    last.inputTensor = tf.clone(input);\n    skipFrame = diffRelative <= (config.cacheSensitivity || 0);\n  }\n  return skipFrame;\n}\n\nexport async function compare(config: Partial<Config>, input1: Tensor, input2: Tensor): Promise<number> {\n  const t: Record<string, Tensor> = {};\n  if (!input1 || !input2 || input1.shape.length !== 4 || input1.shape.length !== input2.shape.length) {\n    if (!config.debug) log('invalid input tensor or tensor shapes do not match:', input1.shape, input2.shape);\n    return 0;\n  }\n  if (input1.shape[0] !== 1 || input2.shape[0] !== 1 || input1.shape[3] !== 3 || input2.shape[3] !== 3) {\n    if (!config.debug) log('input tensors must be of shape [1, height, width, 3]:', input1.shape, input2.shape);\n    return 0;\n  }\n  t.input1 = tf.clone(input1);\n  t.input2 = (input1.shape[1] !== input2.shape[1] || input1.shape[2] !== input2.shape[2]) ? tf.image.resizeBilinear(input2, [input1.shape[1], input1.shape[2]]) : tf.clone(input2);\n  t.diff = tf.sub(t.input1, t.input2);\n  t.squared = tf.mul(t.diff, t.diff);\n  t.sum = tf.sum(t.squared);\n  const diffSum = await t.sum.data();\n  const diffRelative = diffSum[0] / (input1.shape[1] || 1) / (input1.shape[2] || 1) / 255 / 3;\n  tf.dispose([t.input1, t.input2, t.diff, t.squared, t.sum]);\n  return diffRelative;\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport * as image from '../image/image';\n\n/** Env class that holds detected capabilities */\nexport class Env {\n  /** Running in Browser */\n  browser: boolean;\n  /** Running in NodeJS */\n  node: boolean;\n  /** Running in WebWorker thread */\n  worker: boolean;\n  /** Detected platform */\n  platform: string = '';\n  /** Detected agent */\n  agent: string = '';\n  /** List of supported backends */\n  backends: string[] = [];\n  /** Has any work been performed so far */\n  initial: boolean;\n  /** Are image filters supported? */\n  filter: boolean | undefined;\n  /** TFJS instance details */\n  tfjs: {\n    version: undefined | string,\n  };\n  /** Is offscreenCanvas supported? */\n  offscreen: undefined | boolean;\n  /** Are performance counter instant values or additive */\n  perfadd: boolean = false;\n  /** WASM detected capabilities */\n  wasm: {\n    supported: undefined | boolean,\n    backend: undefined | boolean,\n    simd: undefined | boolean,\n    multithread: undefined | boolean,\n  } = {\n      supported: undefined,\n      backend: undefined,\n      simd: undefined,\n      multithread: undefined,\n    };\n  /** WebGL detected capabilities */\n  webgl: {\n    supported: undefined | boolean,\n    backend: undefined | boolean,\n    version: undefined | string,\n    renderer: undefined | string,\n  } = {\n      supported: undefined,\n      backend: undefined,\n      version: undefined,\n      renderer: undefined,\n    };\n  /** WebGPU detected capabilities */\n  webgpu: {\n    supported: undefined | boolean,\n    backend: undefined | boolean,\n    adapter: undefined | string,\n  } = {\n      supported: undefined,\n      backend: undefined,\n      adapter: undefined,\n    };\n  /** CPU info */\n  cpu: {\n    model: undefined | string,\n    flags: string[],\n  } = {\n      model: undefined,\n      flags: [],\n    };\n  /** List of supported kernels for current backend */\n  kernels: string[] = [];\n  /** MonkeyPatch for Canvas */\n  Canvas: undefined;\n  /** MonkeyPatch for Image */\n  Image: undefined;\n  /** MonkeyPatch for ImageData */\n  ImageData: undefined;\n\n  constructor() {\n    this.browser = typeof navigator !== 'undefined';\n    this.node = (typeof process !== 'undefined') && (typeof process.versions !== 'undefined') && (typeof process.versions.node !== 'undefined');\n    this.tfjs = { version: tf.version['tfjs-core'] };\n    this.offscreen = typeof OffscreenCanvas !== 'undefined';\n    this.initial = true;\n    // @ts-ignore WorkerGlobalScope evaluated in browser only\n    this.worker = this.browser && this.offscreen ? (typeof WorkerGlobalScope !== 'undefined') : undefined;\n    if (typeof navigator !== 'undefined') {\n      const raw = navigator.userAgent.match(/\\(([^()]+)\\)/g);\n      if (raw && raw[0]) {\n        const platformMatch = raw[0].match(/\\(([^()]+)\\)/g);\n        this.platform = (platformMatch && platformMatch[0]) ? platformMatch[0].replace(/\\(|\\)/g, '') : '';\n        this.agent = navigator.userAgent.replace(raw[0], '');\n        if (this.platform[1]) this.agent = this.agent.replace(raw[1], '');\n        this.agent = this.agent.replace(/  /g, ' ');\n        // chrome offscreencanvas gpu memory leak\n        /*\n        const isChrome = env.agent.match(/Chrome\\/.[0-9]/g);\n        const verChrome = isChrome && isChrome[0] ? isChrome[0].split('/')[1] : 0;\n        if (verChrome > 92 && verChrome < 96) {\n          log('disabling offscreenCanvas due to browser error:', isChrome ? isChrome[0] : 'unknown');\n          this.offscreen = false;\n        }\n        */\n      }\n    } else if (typeof process !== 'undefined') {\n      this.platform = `${process.platform} ${process.arch}`;\n      this.agent = `NodeJS ${process.version}`;\n    }\n  }\n\n  /** update backend information */\n  async updateBackend() {\n    // analyze backends\n    this.backends = Object.keys(tf.engine().registryFactory);\n    this.wasm.supported = typeof WebAssembly !== 'undefined';\n    this.wasm.backend = this.backends.includes('wasm');\n    if (this.wasm.supported && this.wasm.backend && tf.getBackend() === 'wasm') {\n      this.wasm.simd = await tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n      this.wasm.multithread = await tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n    }\n    const c = image.canvas(100, 100);\n    const ctx = c ? c.getContext('webgl2') : undefined; // causes too many gl contexts\n    // const ctx = typeof tf.backend().getGPGPUContext !== undefined ? tf.backend().getGPGPUContext : null;\n    this.webgl.supported = typeof ctx !== 'undefined';\n    this.webgl.backend = this.backends.includes('webgl');\n    if (this.webgl.supported && this.webgl.backend && (tf.getBackend() === 'webgl' || tf.getBackend() === 'humangl')) {\n      // @ts-ignore getGPGPUContext only exists on WebGL backend\n      const gl = tf.backend().gpgpu !== 'undefined' ? await tf.backend().getGPGPUContext().gl : null;\n      if (gl) {\n        this.webgl.version = gl.getParameter(gl.VERSION);\n        this.webgl.renderer = gl.getParameter(gl.RENDERER);\n      }\n    }\n    // @ts-ignore navigator.gpu is only defined when webgpu is available in browser\n    this.webgpu.supported = this.browser && typeof navigator['gpu'] !== 'undefined';\n    this.webgpu.backend = this.backends.includes('webgpu');\n    try {\n      // @ts-ignore navigator.gpu is only defined when webgpu is available in browser\n      if (this.webgpu.supported) this.webgpu.adapter = (await navigator['gpu'].requestAdapter()).name;\n    } catch {\n      this.webgpu.supported = false;\n    }\n    try {\n      this.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => kernel.kernelName.toLowerCase());\n    } catch { /**/ }\n  }\n\n  /** update cpu information */\n  async updateCPU() {\n    const cpu = { model: '', flags: [] };\n    if (this.node && this.platform.startsWith('linux')) {\n      /*\n      const fs = require('fs');\n      try {\n        const data = fs.readFileSync('/proc/cpuinfo').toString();\n        for (const line of data.split('\\n')) {\n          if (line.startsWith('model name')) cpu.model = line.match(/:(.*)/g)[0].replace(':', '').trim();\n          if (line.startsWith('flags')) cpu.flags = line.match(/:(.*)/g)[0].replace(':', '').trim().split(' ').sort();\n        }\n      } catch { }\n      */\n    }\n    if (!this['cpu']) Object.defineProperty(this, 'cpu', { value: cpu });\n    else this['cpu'] = cpu;\n  }\n}\n\nexport const env = new Env();\n", "import { log, join } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { GraphModel } from './types';\nimport type { Config } from '../config';\nimport * as modelsDefs from '../../models/models.json';\n\nconst options = {\n  cacheModels: true,\n  cacheSupported: true,\n  verbose: true,\n  debug: false,\n  modelBasePath: '',\n};\n\nexport type ModelInfo = {\n  name: string,\n  inCache: boolean,\n  sizeDesired: number,\n  sizeFromManifest: number,\n  sizeLoadedWeights: number,\n}\n\nexport const modelStats: Record<string, ModelInfo> = {};\n\nasync function httpHandler(url, init?): Promise<Response | null> {\n  if (options.debug) log('load model fetch:', url, init);\n  return fetch(url, init);\n}\n\nexport function setModelLoadOptions(config: Config) {\n  options.cacheModels = config.cacheModels;\n  options.verbose = config.debug;\n  options.modelBasePath = config.modelBasePath;\n}\n\nexport async function loadModel(modelPath: string | undefined): Promise<GraphModel> {\n  let modelUrl = join(options.modelBasePath, modelPath || '');\n  if (!modelUrl.toLowerCase().endsWith('.json')) modelUrl += '.json';\n  const modelPathSegments = modelUrl.includes('/') ? modelUrl.split('/') : modelUrl.split('\\\\');\n  const shortModelName = modelPathSegments[modelPathSegments.length - 1].replace('.json', '');\n  const cachedModelName = 'indexeddb://' + shortModelName; // generate short model name for cache\n  modelStats[shortModelName] = {\n    name: shortModelName,\n    sizeFromManifest: 0,\n    sizeLoadedWeights: 0,\n    sizeDesired: modelsDefs[shortModelName],\n    inCache: false,\n  };\n  options.cacheSupported = (typeof window !== 'undefined') && (typeof window.localStorage !== 'undefined') && (typeof window.indexedDB !== 'undefined'); // check if running in browser and if indexedb is available\n  let cachedModels = {};\n  try {\n    cachedModels = (options.cacheSupported && options.cacheModels) ? await tf.io.listModels() : {}; // list all models already in cache // this fails for webview although localStorage is defined\n  } catch {\n    options.cacheSupported = false;\n  }\n  modelStats[shortModelName].inCache = (options.cacheSupported && options.cacheModels) && Object.keys(cachedModels).includes(cachedModelName); // is model found in cache\n  const tfLoadOptions = typeof fetch === 'undefined' ? {} : { fetchFunc: (url, init?) => httpHandler(url, init) };\n  const model: GraphModel = new tf.GraphModel(modelStats[shortModelName].inCache ? cachedModelName : modelUrl, tfLoadOptions) as unknown as GraphModel; // create model prototype and decide if load from cache or from original modelurl\n  let loaded = false;\n  try {\n    // @ts-ignore private function\n    model.findIOHandler(); // decide how to actually load a model\n    if (options.debug) log('model load handler:', model['handler']);\n    // @ts-ignore private property\n    const artifacts = await model.handler.load(); // load manifest\n    modelStats[shortModelName].sizeFromManifest = artifacts?.weightData?.byteLength || 0;\n    model.loadSync(artifacts); // load weights\n    // @ts-ignore private property\n    modelStats[shortModelName].sizeLoadedWeights = model?.artifacts?.weightData?.byteLength || 0;\n    if (options.verbose) log('load model:', model['modelUrl'], { bytes: modelStats[shortModelName].sizeLoadedWeights }, options);\n    loaded = true;\n  } catch (err) {\n    log('error loading model:', modelUrl, err);\n  }\n  if (loaded && options.cacheModels && options.cacheSupported && !modelStats[shortModelName].inCache) { // save model to cache\n    try {\n      const saveResult = await model.save(cachedModelName);\n      log('model saved:', cachedModelName, saveResult);\n    } catch (err) {\n      log('error saving model:', modelUrl, err);\n    }\n  }\n  return model;\n}\n", "/**\n * Loader and Validator for all models used by Human\n */\n\nimport { env } from './util/env';\nimport { log } from './util/util';\nimport * as gear from './gear/gear';\nimport * as ssrnetAge from './gear/ssrnet-age';\nimport * as ssrnetGender from './gear/ssrnet-gender';\nimport * as antispoof from './face/antispoof';\nimport * as blazeface from './face/blazeface';\nimport * as blazepose from './body/blazepose';\nimport * as centernet from './object/centernet';\nimport * as efficientpose from './body/efficientpose';\nimport * as emotion from './gear/emotion';\nimport * as mobilefacenet from './face/mobilefacenet';\nimport * as facemesh from './face/facemesh';\nimport * as faceres from './face/faceres';\nimport * as handpose from './hand/handpose';\nimport * as handtrack from './hand/handtrack';\nimport * as iris from './face/iris';\nimport * as liveness from './face/liveness';\nimport * as movenet from './body/movenet';\nimport * as nanodet from './object/nanodet';\nimport * as posenet from './body/posenet';\nimport * as segmentation from './segmentation/segmentation';\nimport { modelStats, ModelInfo } from './tfjs/load';\nimport type { GraphModel } from './tfjs/types';\nimport type { Human } from './human';\n\n/** Instances of all possible TFJS Graph Models used by Human\n * - loaded as needed based on configuration\n * - initialized explictly with `human.load()` method\n * - initialized implicity on first call to `human.detect()`\n * - each model can be `null` if not loaded, instance of `GraphModel` if loaded or `Promise` if loading\n */\nexport class Models {\n  ssrnetage: null | GraphModel | Promise<GraphModel> = null;\n  gear: null | GraphModel | Promise<GraphModel> = null;\n  blazeposedetect: null | GraphModel | Promise<GraphModel> = null;\n  blazepose: null | GraphModel | Promise<GraphModel> = null;\n  centernet: null | GraphModel | Promise<GraphModel> = null;\n  efficientpose: null | GraphModel | Promise<GraphModel> = null;\n  mobilefacenet: null | GraphModel | Promise<GraphModel> = null;\n  emotion: null | GraphModel | Promise<GraphModel> = null;\n  facedetect: null | GraphModel | Promise<GraphModel> = null;\n  faceiris: null | GraphModel | Promise<GraphModel> = null;\n  facemesh: null | GraphModel | Promise<GraphModel> = null;\n  faceres: null | GraphModel | Promise<GraphModel> = null;\n  ssrnetgender: null | GraphModel | Promise<GraphModel> = null;\n  handpose: null | GraphModel | Promise<GraphModel> = null;\n  handskeleton: null | GraphModel | Promise<GraphModel> = null;\n  handtrack: null | GraphModel | Promise<GraphModel> = null;\n  liveness: null | GraphModel | Promise<GraphModel> = null;\n  movenet: null | GraphModel | Promise<GraphModel> = null;\n  nanodet: null | GraphModel | Promise<GraphModel> = null;\n  posenet: null | GraphModel | Promise<GraphModel> = null;\n  segmentation: null | GraphModel | Promise<GraphModel> = null;\n  antispoof: null | GraphModel | Promise<GraphModel> = null;\n}\n\nexport type ModelStats = {\n  numLoadedModels: number,\n  numEnabledModels: undefined,\n  numDefinedModels: number,\n  percentageLoaded: number,\n  totalSizeFromManifest: number,\n  totalSizeWeights: number,\n  totalSizeLoading: number,\n  totalSizeEnabled: undefined,\n  modelStats: ModelInfo[],\n}\n\nexport const getModelStats = (instance: Human): ModelStats => {\n  let totalSizeFromManifest = 0;\n  let totalSizeWeights = 0;\n  let totalSizeLoading = 0;\n  for (const m of Object.values(modelStats)) {\n    totalSizeFromManifest += m.sizeFromManifest;\n    totalSizeWeights += m.sizeLoadedWeights;\n    totalSizeLoading += m.sizeDesired;\n  }\n  const percentageLoaded = totalSizeLoading > 0 ? totalSizeWeights / totalSizeLoading : 0;\n  return {\n    numLoadedModels: Object.values(modelStats).length,\n    numEnabledModels: undefined,\n    numDefinedModels: Object.keys(instance.models).length,\n    percentageLoaded,\n    totalSizeFromManifest,\n    totalSizeWeights,\n    totalSizeLoading,\n    totalSizeEnabled: undefined,\n    modelStats: Object.values(modelStats),\n  };\n};\n\nexport function reset(instance: Human): void {\n  // if (instance.config.debug) log('resetting loaded models');\n  for (const model of Object.keys(instance.models)) instance.models[model as keyof Models] = null;\n}\n\n/** Load method preloads all instance.configured models on-demand */\nexport async function load(instance: Human): Promise<void> {\n  if (env.initial) reset(instance);\n  if (instance.config.hand.enabled) { // handpose model is a combo that must be loaded as a whole\n    if (!instance.models.handpose && instance.config.hand.detector?.modelPath?.includes('handdetect')) {\n      [instance.models.handpose, instance.models.handskeleton] = await handpose.load(instance.config);\n    }\n    if (!instance.models.handskeleton && instance.config.hand.landmarks && instance.config.hand.detector?.modelPath?.includes('handdetect')) {\n      [instance.models.handpose, instance.models.handskeleton] = await handpose.load(instance.config);\n    }\n  }\n  if (instance.config.body.enabled && !instance.models.blazepose && instance.config.body?.modelPath?.includes('blazepose')) instance.models.blazepose = blazepose.loadPose(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.body.enabled && !instance.models.blazeposedetect && instance.config.body['detector'] && instance.config.body['detector']['modelPath']) instance.models.blazeposedetect = blazepose.loadDetect(instance.config);\n  if (instance.config.body.enabled && !instance.models.efficientpose && instance.config.body?.modelPath?.includes('efficientpose')) instance.models.efficientpose = efficientpose.load(instance.config);\n  if (instance.config.body.enabled && !instance.models.movenet && instance.config.body?.modelPath?.includes('movenet')) instance.models.movenet = movenet.load(instance.config);\n  if (instance.config.body.enabled && !instance.models.posenet && instance.config.body?.modelPath?.includes('posenet')) instance.models.posenet = posenet.load(instance.config);\n  if (instance.config.face.enabled && !instance.models.facedetect) instance.models.facedetect = blazeface.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.antispoof?.enabled && !instance.models.antispoof) instance.models.antispoof = antispoof.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.liveness?.enabled && !instance.models.liveness) instance.models.liveness = liveness.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.description?.enabled && !instance.models.faceres) instance.models.faceres = faceres.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.emotion?.enabled && !instance.models.emotion) instance.models.emotion = emotion.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.iris?.enabled && !instance.config.face.attention?.enabled && !instance.models.faceiris) instance.models.faceiris = iris.load(instance.config);\n  if (instance.config.face.enabled && instance.config.face.mesh?.enabled && !instance.models.facemesh) instance.models.facemesh = facemesh.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['gear']?.enabled && !instance.models.gear) instance.models.gear = gear.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['ssrnet']?.enabled && !instance.models.ssrnetage) instance.models.ssrnetage = ssrnetAge.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['ssrnet']?.enabled && !instance.models.ssrnetgender) instance.models.ssrnetgender = ssrnetGender.load(instance.config);\n  // @ts-ignore optional model\n  if (instance.config.face.enabled && instance.config.face['mobilefacenet']?.enabled && !instance.models.mobilefacenet) instance.models.mobilefacenet = mobilefacenet.load(instance.config);\n  if (instance.config.hand.enabled && !instance.models.handtrack && instance.config.hand.detector?.modelPath?.includes('handtrack')) instance.models.handtrack = handtrack.loadDetect(instance.config);\n  if (instance.config.hand.enabled && instance.config.hand.landmarks && !instance.models.handskeleton && instance.config.hand.detector?.modelPath?.includes('handtrack')) instance.models.handskeleton = handtrack.loadSkeleton(instance.config);\n  if (instance.config.object.enabled && !instance.models.centernet && instance.config.object?.modelPath?.includes('centernet')) instance.models.centernet = centernet.load(instance.config);\n  if (instance.config.object.enabled && !instance.models.nanodet && instance.config.object?.modelPath?.includes('nanodet')) instance.models.nanodet = nanodet.load(instance.config);\n  if (instance.config.segmentation.enabled && !instance.models.segmentation) instance.models.segmentation = segmentation.load(instance.config);\n\n  // models are loaded in parallel asynchronously so lets wait until they are actually loaded\n  for await (const model of Object.keys(instance.models)) {\n    if (instance.models[model as keyof Models] && typeof instance.models[model as keyof Models] !== 'undefined') {\n      instance.models[model as keyof Models] = await instance.models[model as keyof Models];\n    }\n  }\n}\n\nexport async function validate(instance: Human): Promise<void> {\n  interface Op { name: string, category: string, op: string }\n  const simpleOps = ['const', 'placeholder', 'noop', 'pad', 'squeeze', 'add', 'sub', 'mul', 'div'];\n  for (const defined of Object.keys(instance.models)) {\n    const model: GraphModel | null = instance.models[defined as keyof Models] as GraphModel | null;\n    if (!model) continue;\n    const ops: string[] = [];\n    // @ts-ignore // executor is a private method\n    const executor = model?.executor;\n    if (executor && executor.graph.nodes) {\n      for (const kernel of Object.values(executor.graph.nodes)) {\n        const op = (kernel as Op).op.toLowerCase();\n        if (!ops.includes(op)) ops.push(op);\n      }\n    } else {\n      if (!executor && instance.config.debug) log('model signature not determined:', defined);\n    }\n    const missing: string[] = [];\n    for (const op of ops) {\n      if (!simpleOps.includes(op) // exclude simple ops\n        && !instance.env.kernels.includes(op) // check actual kernel ops\n        && !instance.env.kernels.includes(op.replace('_', '')) // check variation without _\n        && !instance.env.kernels.includes(op.replace('native', '')) // check standard variation\n        && !instance.env.kernels.includes(op.replace('v2', ''))) { // check non-versioned variation\n        missing.push(op);\n      }\n    }\n    // log('model validation ops:', defined, ops);\n    if (instance.config.debug && missing.length > 0) log('model validation failed:', defined, missing);\n  }\n}\n", "/**\n * GEAR [gender/emotion/age/race] model implementation\n *\n * Based on: [**GEAR Predictor**](https://github.com/Udolf15/GEAR-Predictor)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { Gender, Race } from '../result';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport { env } from '../util/env';\n\nexport type GearType = { age: number, gender: Gender, genderScore: number, race: Array<{ score: number, race: Race }> }\nlet model: GraphModel | null;\nconst last: Array<GearType> = [];\nconst raceNames = ['white', 'black', 'asian', 'indian', 'other'];\nconst ageWeights = [15, 23, 28, 35.5, 45.5, 55.5, 65];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function load(config: Config) {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['gear']?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<GearType> {\n  if (!model) return { age: 0, gender: 'unknown', genderScore: 0, race: [] };\n  const skipFrame = skipped < (config.face['gear']?.skipFrames || 0);\n  const skipTime = (config.face['gear']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && last[idx]) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    if (!model?.inputs[0].shape) return;\n    const t: Record<string, Tensor> = {};\n    // t.resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape[2], model?.inputs[0].shape[1]], false);\n    const box = [[0.0, 0.10, 0.90, 0.90]]; // empyrical values for top, left, bottom, right\n    t.resize = tf.image.cropAndResize(image, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n    const obj: GearType = { age: 0, gender: 'unknown', genderScore: 0, race: [] };\n    if (config.face['gear']?.enabled) [t.age, t.gender, t.race] = model.execute(t.resize, ['age_output', 'gender_output', 'race_output']) as Tensor[];\n    const gender = await t.gender.data();\n    obj.gender = gender[0] > gender[1] ? 'male' : 'female';\n    obj.genderScore = Math.round(100 * (gender[0] > gender[1] ? gender[0] : gender[1])) / 100;\n    const race = await t.race.data();\n    for (let i = 0; i < race.length; i++) {\n      if (race[i] > (config.face['gear']?.minConfidence || 0.2)) obj.race.push({ score: Math.round(100 * race[i]) / 100, race: raceNames[i] as Race });\n    }\n    obj.race.sort((a, b) => b.score - a.score);\n    // {0: 'Below20', 1: '21-25', 2: '26-30', 3: '31-40',4: '41-50', 5: '51-60', 6: 'Above60'}\n    const ageDistribution = Array.from(await t.age.data());\n    const ageSorted = ageDistribution.map((a, i) => [ageWeights[i], a]).sort((a, b) => b[1] - a[1]);\n    let age = ageSorted[0][0]; // pick best starting point\n    for (let i = 1; i < ageSorted.length; i++) age += ageSorted[i][1] * (ageSorted[i][0] - age); // adjust with each other choice by weight\n    obj.age = Math.round(10 * age) / 10;\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    last[idx] = obj;\n    lastCount = count;\n    lastTime = now();\n    resolve(obj);\n  });\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from './types';\n\nexport const constants: Record<string, Tensor | number | number[]> = {\n  tf255: 255,\n  tf1: 1,\n  tf2: 2,\n  tf05: 0.5,\n  tf127: 127.5,\n  rgb: [0.2989, 0.5870, 0.1140],\n};\n\nexport function init() {\n  constants.tf255 = tf.scalar(255, 'float32');\n  constants.tf1 = tf.scalar(1, 'float32');\n  constants.tf2 = tf.scalar(2, 'float32');\n  constants.tf05 = tf.scalar(0.5, 'float32');\n  constants.tf127 = tf.scalar(127.5, 'float32');\n  constants.rgb = tf.tensor1d([0.2989, 0.5870, 0.1140], 'float32'); // factors for red/green/blue colors when converting to grayscale\n}\n", "/**\n * Age model implementation\n *\n * Based on: [**SSR-Net**](https://github.com/shamangary/SSR-Net)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { env } from '../util/env';\nimport { constants } from '../tfjs/constants';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\n\nlet model: GraphModel | null;\nconst last: Array<{ age: number }> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function load(config: Config) {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['ssrnet'].modelPathAge);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<{ age: number }> {\n  if (!model) return { age: 0 };\n  const skipFrame = skipped < (config.face['ssrnet']?.skipFrames || 0);\n  const skipTime = (config.face['ssrnet']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipFrame && skipTime && (lastCount === count) && last[idx]?.age && (last[idx]?.age > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    if (!model?.inputs || !model.inputs[0] || !model.inputs[0].shape) return;\n    const t: Record<string, Tensor> = {};\n    t.resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    t.enhance = tf.mul(t.resize, constants.tf255);\n    const obj = { age: 0 };\n    if (config.face['ssrnet'].enabled) t.age = model.execute(t.enhance) as Tensor;\n    if (t.age) {\n      const data = await t.age.data();\n      obj.age = Math.trunc(10 * data[0]) / 10;\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    last[idx] = obj;\n    lastCount = count;\n    lastTime = now();\n    resolve(obj);\n  });\n}\n", "/**\n * Gender model implementation\n *\n * Based on: [**SSR-Net**](https://github.com/shamangary/SSR-Net)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport type { Gender } from '../result';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst last: Array<{ gender: Gender, genderScore: number }> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\n// tuning values\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function load(config: Config | any) {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['ssrnet'].modelPathGender);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// eslint-disable-next-line @typescript-eslint/no-explicit-any\nexport async function predict(image: Tensor, config: Config, idx, count): Promise<{ gender: Gender, genderScore: number }> {\n  if (!model) return { gender: 'unknown', genderScore: 0 };\n  const skipFrame = skipped < (config.face['ssrnet']?.skipFrames || 0);\n  const skipTime = (config.face['ssrnet']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipFrame && skipTime && (lastCount === count) && last[idx]?.gender && (last[idx]?.genderScore > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    if (!model?.inputs[0].shape) return;\n    const t: Record<string, Tensor> = {};\n    t.resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n    t.enhance = tf.tidy(() => {\n      const [red, green, blue] = tf.split(t.resize, 3, 3);\n      const redNorm = tf.mul(red, rgb[0]);\n      const greenNorm = tf.mul(green, rgb[1]);\n      const blueNorm = tf.mul(blue, rgb[2]);\n      const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n      const normalize = tf.mul(tf.sub(grayscale, constants.tf05), 2); // range grayscale:-1..1\n      return normalize;\n    });\n    const obj: { gender: Gender, genderScore: number } = { gender: 'unknown', genderScore: 0 };\n    if (config.face['ssrnet'].enabled) t.gender = model.execute(t.enhance) as Tensor;\n    const data = await t.gender.data();\n    obj.gender = data[0] > data[1] ? 'female' : 'male'; // returns two values 0..1, bigger one is prediction\n    obj.genderScore = data[0] > data[1] ? (Math.trunc(100 * data[0]) / 100) : (Math.trunc(100 * data[1]) / 100);\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    last[idx] = obj;\n    lastCount = count;\n    lastTime = now();\n    resolve(obj);\n  });\n}\n", "/**\n * Anti-spoofing model implementation\n */\n\nimport { log, now } from '../util/util';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst cached: Array<number> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet lastCount = 0;\nlet lastTime = 0;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.antispoof?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<number> {\n  if (!model) return 0;\n  const skipTime = (config.face.antispoof?.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.face.antispoof?.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && cached[idx]) {\n    skipped++;\n    return cached[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape ? model.inputs[0].shape[2] : 0, model?.inputs[0].shape ? model.inputs[0].shape[1] : 0], false);\n    const res = model?.execute(resize) as Tensor;\n    const num = (await res.data())[0];\n    cached[idx] = Math.round(100 * num) / 100;\n    lastCount = count;\n    lastTime = now();\n    tf.dispose([resize, res]);\n    resolve(cached[idx]);\n  });\n}\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n * See `facemesh.ts` for entry point\n */\n\nexport const meshAnnotations: Record<string, number[]> = {\n  silhouette: [\n    10, 338, 297, 332, 284, 251, 389, 356, 454, 323, 361, 288,\n    397, 365, 379, 378, 400, 377, 152, 148, 176, 149, 150, 136,\n    172, 58, 132, 93, 234, 127, 162, 21, 54, 103, 67, 109,\n  ],\n  // lipsUpperOuter: [61, 185, 40, 39, 37, 0, 267, 269, 270, 409, 291], // 11\n  // lipsLowerOuter: [146, 91, 181, 84, 17, 314, 405, 321, 375, 291], // 10\n  // lipsUpperInner: [78, 191, 80, 81, 82, 13, 312, 311, 310, 415, 308], // 11\n  // lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308], // 11\n  lipsUpperOuter: [185, 40, 39, 37, 0, 267, 269, 270, 409],\n  lipsLowerOuter: [61, 146, 91, 181, 84, 17, 314, 405, 321, 375, 291],\n  lipsUpperInner: [191, 80, 81, 82, 13, 312, 311, 310, 415],\n  lipsLowerInner: [78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308],\n  lipsLowerSemiOuter: [76, 77, 90, 180, 85, 16, 315, 404, 320, 307, 306],\n  lipsUpperSemiOuter: [184, 74, 73, 72, 11, 302, 303, 304, 408],\n  lipsLowerSemiInner: [62, 96, 89, 179, 86, 15, 316, 403, 319, 325, 292],\n  lipsUpperSemiInner: [183, 42, 41, 38, 12, 268, 271, 272, 407],\n  rightEyeUpper0: [246, 161, 160, 159, 158, 157, 173], // 7\n  rightEyeLower0: [33, 7, 163, 144, 145, 153, 154, 155, 133], // 9\n  rightEyeUpper1: [247, 30, 29, 27, 28, 56, 190], // 7\n  rightEyeLower1: [130, 25, 110, 24, 23, 22, 26, 112, 243], // 9\n  rightEyeUpper2: [113, 225, 224, 223, 222, 221, 189], // 7\n  rightEyeLower2: [226, 31, 228, 229, 230, 231, 232, 233, 244], // 9\n  rightEyeLower3: [143, 111, 117, 118, 119, 120, 121, 128, 245], // 9\n  rightEyebrowUpper: [156, 70, 63, 105, 66, 107, 55, 193], // 8\n  rightEyebrowLower: [35, 124, 46, 53, 52, 65], // 6\n  rightEyeIris: [473, 474, 475, 476, 477], // 5\n  leftEyeUpper0: [466, 388, 387, 386, 385, 384, 398],\n  leftEyeLower0: [263, 249, 390, 373, 374, 380, 381, 382, 362],\n  leftEyeUpper1: [467, 260, 259, 257, 258, 286, 414],\n  leftEyeLower1: [359, 255, 339, 254, 253, 252, 256, 341, 463],\n  leftEyeUpper2: [342, 445, 444, 443, 442, 441, 413],\n  leftEyeLower2: [446, 261, 448, 449, 450, 451, 452, 453, 464],\n  leftEyeLower3: [372, 340, 346, 347, 348, 349, 350, 357, 465],\n  leftEyebrowUpper: [383, 300, 293, 334, 296, 336, 285, 417],\n  leftEyebrowLower: [265, 353, 276, 283, 282, 295],\n  leftEyeIris: [468, 469, 470, 471, 472],\n  midwayBetweenEyes: [168],\n  noseTip: [1],\n  noseBottom: [2],\n  noseRightCorner: [98],\n  noseLeftCorner: [327],\n  rightCheek: [205],\n  leftCheek: [425],\n};\n\nexport const meshLandmarks: Record<string, number | number[]> = {\n  count: 468,\n  mouth: 13,\n  symmetryLine: [13, meshAnnotations['midwayBetweenEyes'][0]],\n};\n\nexport const blazeFaceLandmarks: Record<string, number | number[]> = {\n  leftEye: 0,\n  rightEye: 1,\n  nose: 2,\n  mouth: 3,\n  leftEar: 4,\n  rightEar: 5,\n  symmetryLine: [3, 2],\n};\n\nexport const irisIndices: Array<{ key: string, indices: number[] }> = [ // A mapping from facemesh model keypoints to iris model keypoints.\n  { key: 'EyeUpper0', indices: [9, 10, 11, 12, 13, 14, 15] }, // 7 x 3d\n  { key: 'EyeUpper1', indices: [25, 26, 27, 28, 29, 30, 31] }, // 7 x 3d\n  { key: 'EyeUpper2', indices: [41, 42, 43, 44, 45, 46, 47] }, // 7 x 3d\n  { key: 'EyeLower0', indices: [0, 1, 2, 3, 4, 5, 6, 7, 8] }, // 7 x 3d\n  { key: 'EyeLower1', indices: [16, 17, 18, 19, 20, 21, 22, 23, 24] }, // 9 x 3d\n  { key: 'EyeLower2', indices: [32, 33, 34, 35, 36, 37, 38, 39, 40] }, // 9 x 3d\n  { key: 'EyeLower3', indices: [54, 55, 56, 57, 58, 59, 60, 61, 62] }, // 9 x 3d\n  { key: 'EyebrowUpper', indices: [63, 64, 65, 66, 67, 68, 69, 70] }, // 8 x 3d\n  { key: 'EyebrowLower', indices: [48, 49, 50, 51, 52, 53] }, // 6 x 3d\n];\n\nexport const UV468: [number, number][] = [\n  [0.499976992607117, 0.652534008026123],\n  [0.500025987625122, 0.547487020492554],\n  [0.499974012374878, 0.602371990680695],\n  [0.482113003730774, 0.471979022026062],\n  [0.500150978565216, 0.527155995368958],\n  [0.499909996986389, 0.498252987861633],\n  [0.499523013830185, 0.40106201171875],\n  [0.289712011814117, 0.380764007568359],\n  [0.499954998493195, 0.312398016452789],\n  [0.499987006187439, 0.269918978214264],\n  [0.500023007392883, 0.107050001621246],\n  [0.500023007392883, 0.666234016418457],\n  [0.5000159740448, 0.679224014282227],\n  [0.500023007392883, 0.692348003387451],\n  [0.499976992607117, 0.695277988910675],\n  [0.499976992607117, 0.70593398809433],\n  [0.499976992607117, 0.719385027885437],\n  [0.499976992607117, 0.737019002437592],\n  [0.499967992305756, 0.781370997428894],\n  [0.499816000461578, 0.562981009483337],\n  [0.473773002624512, 0.573909997940063],\n  [0.104906998574734, 0.254140973091125],\n  [0.365929991006851, 0.409575998783112],\n  [0.338757991790771, 0.41302502155304],\n  [0.311120003461838, 0.409460008144379],\n  [0.274657994508743, 0.389131009578705],\n  [0.393361985683441, 0.403706014156342],\n  [0.345234006643295, 0.344011008739471],\n  [0.370094001293182, 0.346076011657715],\n  [0.319321990013123, 0.347265005111694],\n  [0.297903001308441, 0.353591024875641],\n  [0.24779200553894, 0.410809993743896],\n  [0.396889001131058, 0.842755019664764],\n  [0.280097991228104, 0.375599980354309],\n  [0.106310002505779, 0.399955987930298],\n  [0.2099249958992, 0.391353011131287],\n  [0.355807989835739, 0.534406006336212],\n  [0.471751004457474, 0.65040397644043],\n  [0.474155008792877, 0.680191993713379],\n  [0.439785003662109, 0.657229006290436],\n  [0.414617002010345, 0.66654098033905],\n  [0.450374007225037, 0.680860996246338],\n  [0.428770989179611, 0.682690978050232],\n  [0.374971002340317, 0.727805018424988],\n  [0.486716985702515, 0.547628998756409],\n  [0.485300987958908, 0.527395009994507],\n  [0.257764995098114, 0.314490020275116],\n  [0.401223003864288, 0.455172002315521],\n  [0.429818987846375, 0.548614978790283],\n  [0.421351999044418, 0.533740997314453],\n  [0.276895999908447, 0.532056987285614],\n  [0.483370006084442, 0.499586999416351],\n  [0.33721199631691, 0.282882988452911],\n  [0.296391993761063, 0.293242990970612],\n  [0.169294998049736, 0.193813979625702],\n  [0.447580009698868, 0.302609980106354],\n  [0.392390012741089, 0.353887975215912],\n  [0.354490011930466, 0.696784019470215],\n  [0.067304998636246, 0.730105042457581],\n  [0.442739009857178, 0.572826027870178],\n  [0.457098007202148, 0.584792017936707],\n  [0.381974011659622, 0.694710969924927],\n  [0.392388999462128, 0.694203019142151],\n  [0.277076005935669, 0.271932005882263],\n  [0.422551989555359, 0.563233017921448],\n  [0.385919004678726, 0.281364023685455],\n  [0.383103013038635, 0.255840003490448],\n  [0.331431001424789, 0.119714021682739],\n  [0.229923993349075, 0.232002973556519],\n  [0.364500999450684, 0.189113974571228],\n  [0.229622006416321, 0.299540996551514],\n  [0.173287004232407, 0.278747975826263],\n  [0.472878992557526, 0.666198015213013],\n  [0.446828007698059, 0.668527007102966],\n  [0.422762006521225, 0.673889994621277],\n  [0.445307999849319, 0.580065965652466],\n  [0.388103008270264, 0.693961024284363],\n  [0.403039008378983, 0.706539988517761],\n  [0.403629004955292, 0.693953037261963],\n  [0.460041999816895, 0.557139039039612],\n  [0.431158006191254, 0.692366003990173],\n  [0.452181994915009, 0.692366003990173],\n  [0.475387006998062, 0.692366003990173],\n  [0.465828001499176, 0.779190003871918],\n  [0.472328990697861, 0.736225962638855],\n  [0.473087012767792, 0.717857003211975],\n  [0.473122000694275, 0.704625964164734],\n  [0.473033010959625, 0.695277988910675],\n  [0.427942007780075, 0.695277988910675],\n  [0.426479011774063, 0.703539967536926],\n  [0.423162013292313, 0.711845993995667],\n  [0.4183090031147, 0.720062971115112],\n  [0.390094995498657, 0.639572978019714],\n  [0.013953999616206, 0.560034036636353],\n  [0.499913990497589, 0.58014702796936],\n  [0.413199990987778, 0.69539999961853],\n  [0.409626007080078, 0.701822996139526],\n  [0.468080013990402, 0.601534962654114],\n  [0.422728985548019, 0.585985004901886],\n  [0.463079988956451, 0.593783974647522],\n  [0.37211999297142, 0.47341400384903],\n  [0.334562003612518, 0.496073007583618],\n  [0.411671012639999, 0.546965003013611],\n  [0.242175996303558, 0.14767599105835],\n  [0.290776997804642, 0.201445996761322],\n  [0.327338010072708, 0.256527006626129],\n  [0.399509996175766, 0.748921036720276],\n  [0.441727995872498, 0.261676013469696],\n  [0.429764986038208, 0.187834024429321],\n  [0.412198007106781, 0.108901023864746],\n  [0.288955003023148, 0.398952007293701],\n  [0.218936994671822, 0.435410976409912],\n  [0.41278201341629, 0.398970007896423],\n  [0.257135003805161, 0.355440020561218],\n  [0.427684992551804, 0.437960982322693],\n  [0.448339998722076, 0.536936044692993],\n  [0.178560003638268, 0.45755398273468],\n  [0.247308000922203, 0.457193970680237],\n  [0.286267012357712, 0.467674970626831],\n  [0.332827985286713, 0.460712015628815],\n  [0.368755996227264, 0.447206974029541],\n  [0.398963987827301, 0.432654976844788],\n  [0.476410001516342, 0.405806005001068],\n  [0.189241006970406, 0.523923993110657],\n  [0.228962004184723, 0.348950982093811],\n  [0.490725994110107, 0.562400996685028],\n  [0.404670000076294, 0.485132992267609],\n  [0.019469000399113, 0.401564002037048],\n  [0.426243007183075, 0.420431017875671],\n  [0.396993011236191, 0.548797011375427],\n  [0.266469985246658, 0.376977026462555],\n  [0.439121007919312, 0.51895797252655],\n  [0.032313998788595, 0.644356966018677],\n  [0.419054001569748, 0.387154996395111],\n  [0.462783008813858, 0.505746960639954],\n  [0.238978996872902, 0.779744982719421],\n  [0.198220998048782, 0.831938028335571],\n  [0.107550002634525, 0.540755033493042],\n  [0.183610007166862, 0.740257024765015],\n  [0.134409993886948, 0.333683013916016],\n  [0.385764002799988, 0.883153975009918],\n  [0.490967005491257, 0.579378008842468],\n  [0.382384985685349, 0.508572995662689],\n  [0.174399003386497, 0.397670984268188],\n  [0.318785011768341, 0.39623498916626],\n  [0.343364000320435, 0.400596976280212],\n  [0.396100014448166, 0.710216999053955],\n  [0.187885001301765, 0.588537991046906],\n  [0.430987000465393, 0.944064974784851],\n  [0.318993002176285, 0.898285031318665],\n  [0.266247987747192, 0.869701027870178],\n  [0.500023007392883, 0.190576016902924],\n  [0.499976992607117, 0.954452991485596],\n  [0.366169989109039, 0.398822009563446],\n  [0.393207013607025, 0.39553701877594],\n  [0.410373002290726, 0.391080021858215],\n  [0.194993004202843, 0.342101991176605],\n  [0.388664990663528, 0.362284004688263],\n  [0.365961998701096, 0.355970978736877],\n  [0.343364000320435, 0.355356991291046],\n  [0.318785011768341, 0.35834002494812],\n  [0.301414996385574, 0.363156020641327],\n  [0.058132998645306, 0.319076001644135],\n  [0.301414996385574, 0.387449026107788],\n  [0.499987989664078, 0.618434011936188],\n  [0.415838003158569, 0.624195992946625],\n  [0.445681989192963, 0.566076993942261],\n  [0.465844005346298, 0.620640993118286],\n  [0.49992299079895, 0.351523995399475],\n  [0.288718998432159, 0.819945991039276],\n  [0.335278987884521, 0.852819979190826],\n  [0.440512001514435, 0.902418971061707],\n  [0.128294005990028, 0.791940987110138],\n  [0.408771991729736, 0.373893976211548],\n  [0.455606997013092, 0.451801002025604],\n  [0.499877005815506, 0.908990025520325],\n  [0.375436991453171, 0.924192011356354],\n  [0.11421000212431, 0.615022003650665],\n  [0.448662012815475, 0.695277988910675],\n  [0.4480200111866, 0.704632043838501],\n  [0.447111994028091, 0.715808033943176],\n  [0.444831997156143, 0.730794012546539],\n  [0.430011987686157, 0.766808986663818],\n  [0.406787008047104, 0.685672998428345],\n  [0.400738000869751, 0.681069016456604],\n  [0.392399996519089, 0.677703022956848],\n  [0.367855995893478, 0.663918972015381],\n  [0.247923001646996, 0.601333022117615],\n  [0.452769994735718, 0.420849978923798],\n  [0.43639200925827, 0.359887003898621],\n  [0.416164010763168, 0.368713974952698],\n  [0.413385987281799, 0.692366003990173],\n  [0.228018000721931, 0.683571994304657],\n  [0.468268007040024, 0.352671027183533],\n  [0.411361992359161, 0.804327011108398],\n  [0.499989002943039, 0.469825029373169],\n  [0.479153990745544, 0.442654013633728],\n  [0.499974012374878, 0.439637005329132],\n  [0.432112008333206, 0.493588984012604],\n  [0.499886006116867, 0.866917014122009],\n  [0.49991300702095, 0.821729004383087],\n  [0.456548988819122, 0.819200992584229],\n  [0.344549000263214, 0.745438992977142],\n  [0.37890899181366, 0.574010014533997],\n  [0.374292999505997, 0.780184984207153],\n  [0.319687992334366, 0.570737957954407],\n  [0.357154995203018, 0.604269981384277],\n  [0.295284003019333, 0.621580958366394],\n  [0.447750002145767, 0.862477004528046],\n  [0.410986006259918, 0.508723020553589],\n  [0.31395098567009, 0.775308012962341],\n  [0.354128003120422, 0.812552988529205],\n  [0.324548006057739, 0.703992962837219],\n  [0.189096003770828, 0.646299958229065],\n  [0.279776990413666, 0.71465802192688],\n  [0.1338230073452, 0.682700991630554],\n  [0.336768001317978, 0.644733011722565],\n  [0.429883986711502, 0.466521978378296],\n  [0.455527991056442, 0.548622965812683],\n  [0.437114000320435, 0.558896005153656],\n  [0.467287987470627, 0.529924988746643],\n  [0.414712011814117, 0.335219979286194],\n  [0.37704598903656, 0.322777986526489],\n  [0.344107985496521, 0.320150971412659],\n  [0.312875986099243, 0.32233202457428],\n  [0.283526003360748, 0.333190023899078],\n  [0.241245999932289, 0.382785975933075],\n  [0.102986000478268, 0.468762993812561],\n  [0.267612010240555, 0.424560010433197],\n  [0.297879010438919, 0.433175981044769],\n  [0.333433985710144, 0.433878004550934],\n  [0.366427004337311, 0.426115989685059],\n  [0.396012008190155, 0.416696012020111],\n  [0.420121014118195, 0.41022801399231],\n  [0.007561000064015, 0.480777025222778],\n  [0.432949006557465, 0.569517970085144],\n  [0.458638995885849, 0.479089021682739],\n  [0.473466008901596, 0.545744001865387],\n  [0.476087987422943, 0.563830018043518],\n  [0.468472003936768, 0.555056989192963],\n  [0.433990985155106, 0.582361996173859],\n  [0.483518004417419, 0.562983989715576],\n  [0.482482999563217, 0.57784903049469],\n  [0.42645001411438, 0.389798998832703],\n  [0.438998997211456, 0.39649498462677],\n  [0.450067013502121, 0.400434017181396],\n  [0.289712011814117, 0.368252992630005],\n  [0.276670008897781, 0.363372981548309],\n  [0.517862021923065, 0.471948027610779],\n  [0.710287988185883, 0.380764007568359],\n  [0.526226997375488, 0.573909997940063],\n  [0.895093023777008, 0.254140973091125],\n  [0.634069979190826, 0.409575998783112],\n  [0.661242008209229, 0.41302502155304],\n  [0.688880026340485, 0.409460008144379],\n  [0.725341975688934, 0.389131009578705],\n  [0.606630027294159, 0.40370500087738],\n  [0.654766023159027, 0.344011008739471],\n  [0.629905998706818, 0.346076011657715],\n  [0.680678009986877, 0.347265005111694],\n  [0.702096998691559, 0.353591024875641],\n  [0.75221198797226, 0.410804986953735],\n  [0.602918028831482, 0.842862963676453],\n  [0.719901978969574, 0.375599980354309],\n  [0.893692970275879, 0.399959981441498],\n  [0.790081977844238, 0.391354024410248],\n  [0.643998026847839, 0.534487962722778],\n  [0.528249025344849, 0.65040397644043],\n  [0.525849997997284, 0.680191040039062],\n  [0.560214996337891, 0.657229006290436],\n  [0.585384011268616, 0.66654098033905],\n  [0.549625992774963, 0.680860996246338],\n  [0.57122802734375, 0.682691991329193],\n  [0.624852001667023, 0.72809898853302],\n  [0.513050019741058, 0.547281980514526],\n  [0.51509702205658, 0.527251958847046],\n  [0.742246985435486, 0.314507007598877],\n  [0.598631024360657, 0.454979002475739],\n  [0.570338010787964, 0.548575043678284],\n  [0.578631997108459, 0.533622980117798],\n  [0.723087012767792, 0.532054007053375],\n  [0.516445994377136, 0.499638974666595],\n  [0.662801027297974, 0.282917976379395],\n  [0.70362401008606, 0.293271005153656],\n  [0.830704987049103, 0.193813979625702],\n  [0.552385985851288, 0.302568018436432],\n  [0.607609987258911, 0.353887975215912],\n  [0.645429015159607, 0.696707010269165],\n  [0.932694971561432, 0.730105042457581],\n  [0.557260990142822, 0.572826027870178],\n  [0.542901992797852, 0.584792017936707],\n  [0.6180260181427, 0.694710969924927],\n  [0.607590973377228, 0.694203019142151],\n  [0.722943007946014, 0.271963000297546],\n  [0.577413976192474, 0.563166975975037],\n  [0.614082992076874, 0.281386971473694],\n  [0.616907000541687, 0.255886018276215],\n  [0.668509006500244, 0.119913995265961],\n  [0.770092010498047, 0.232020974159241],\n  [0.635536015033722, 0.189248979091644],\n  [0.77039098739624, 0.299556016921997],\n  [0.826722025871277, 0.278755009174347],\n  [0.527121007442474, 0.666198015213013],\n  [0.553171992301941, 0.668527007102966],\n  [0.577238023281097, 0.673889994621277],\n  [0.554691970348358, 0.580065965652466],\n  [0.611896991729736, 0.693961024284363],\n  [0.59696102142334, 0.706539988517761],\n  [0.596370995044708, 0.693953037261963],\n  [0.539958000183105, 0.557139039039612],\n  [0.568841993808746, 0.692366003990173],\n  [0.547818005084991, 0.692366003990173],\n  [0.52461302280426, 0.692366003990173],\n  [0.534089982509613, 0.779141008853912],\n  [0.527670979499817, 0.736225962638855],\n  [0.526912987232208, 0.717857003211975],\n  [0.526877999305725, 0.704625964164734],\n  [0.526966989040375, 0.695277988910675],\n  [0.572058022022247, 0.695277988910675],\n  [0.573521018028259, 0.703539967536926],\n  [0.57683801651001, 0.711845993995667],\n  [0.581691026687622, 0.720062971115112],\n  [0.609944999217987, 0.639909982681274],\n  [0.986046016216278, 0.560034036636353],\n  [0.5867999792099, 0.69539999961853],\n  [0.590372025966644, 0.701822996139526],\n  [0.531915009021759, 0.601536989212036],\n  [0.577268004417419, 0.585934996604919],\n  [0.536915004253387, 0.593786001205444],\n  [0.627542972564697, 0.473352015018463],\n  [0.665585994720459, 0.495950996875763],\n  [0.588353991508484, 0.546862006187439],\n  [0.757824003696442, 0.14767599105835],\n  [0.709249973297119, 0.201507985591888],\n  [0.672684013843536, 0.256581008434296],\n  [0.600408971309662, 0.74900496006012],\n  [0.55826598405838, 0.261672019958496],\n  [0.570303976535797, 0.187870979309082],\n  [0.588165998458862, 0.109044015407562],\n  [0.711045026779175, 0.398952007293701],\n  [0.781069993972778, 0.435405015945435],\n  [0.587247014045715, 0.398931980133057],\n  [0.742869973182678, 0.355445981025696],\n  [0.572156012058258, 0.437651991844177],\n  [0.55186802148819, 0.536570012569427],\n  [0.821442008018494, 0.457556009292603],\n  [0.752701997756958, 0.457181990146637],\n  [0.71375697851181, 0.467626988887787],\n  [0.66711300611496, 0.460672974586487],\n  [0.631101012229919, 0.447153985500336],\n  [0.6008620262146, 0.432473003864288],\n  [0.523481011390686, 0.405627012252808],\n  [0.810747981071472, 0.523926019668579],\n  [0.771045982837677, 0.348959028720856],\n  [0.509127020835876, 0.562718033790588],\n  [0.595292985439301, 0.485023975372314],\n  [0.980530977249146, 0.401564002037048],\n  [0.573499977588654, 0.420000016689301],\n  [0.602994978427887, 0.548687994480133],\n  [0.733529984951019, 0.376977026462555],\n  [0.560611009597778, 0.519016981124878],\n  [0.967685997486115, 0.644356966018677],\n  [0.580985009670258, 0.387160003185272],\n  [0.537728011608124, 0.505385041236877],\n  [0.760966002941132, 0.779752969741821],\n  [0.801778972148895, 0.831938028335571],\n  [0.892440974712372, 0.54076099395752],\n  [0.816350996494293, 0.740260004997253],\n  [0.865594983100891, 0.333687007427216],\n  [0.614073991775513, 0.883246004581451],\n  [0.508952975273132, 0.579437971115112],\n  [0.617941975593567, 0.508316040039062],\n  [0.825608015060425, 0.397674977779388],\n  [0.681214988231659, 0.39623498916626],\n  [0.656635999679565, 0.400596976280212],\n  [0.603900015354156, 0.710216999053955],\n  [0.81208598613739, 0.588539004325867],\n  [0.56801301240921, 0.944564998149872],\n  [0.681007981300354, 0.898285031318665],\n  [0.733752012252808, 0.869701027870178],\n  [0.633830010890961, 0.398822009563446],\n  [0.606792986392975, 0.39553701877594],\n  [0.589659988880157, 0.391062021255493],\n  [0.805015981197357, 0.342108011245728],\n  [0.611334979534149, 0.362284004688263],\n  [0.634037971496582, 0.355970978736877],\n  [0.656635999679565, 0.355356991291046],\n  [0.681214988231659, 0.35834002494812],\n  [0.698584973812103, 0.363156020641327],\n  [0.941866993904114, 0.319076001644135],\n  [0.698584973812103, 0.387449026107788],\n  [0.584177017211914, 0.624107003211975],\n  [0.554318010807037, 0.566076993942261],\n  [0.534153997898102, 0.62064003944397],\n  [0.711217999458313, 0.819975018501282],\n  [0.664629995822906, 0.852871000766754],\n  [0.559099972248077, 0.902631998062134],\n  [0.871706008911133, 0.791940987110138],\n  [0.591234028339386, 0.373893976211548],\n  [0.544341027736664, 0.451583981513977],\n  [0.624562978744507, 0.924192011356354],\n  [0.88577002286911, 0.615028977394104],\n  [0.551338016986847, 0.695277988910675],\n  [0.551980018615723, 0.704632043838501],\n  [0.552887976169586, 0.715808033943176],\n  [0.555167973041534, 0.730794012546539],\n  [0.569944024085999, 0.767035007476807],\n  [0.593203008174896, 0.685675978660583],\n  [0.599261999130249, 0.681069016456604],\n  [0.607599973678589, 0.677703022956848],\n  [0.631937980651855, 0.663500010967255],\n  [0.752032995223999, 0.601315021514893],\n  [0.547226011753082, 0.420395016670227],\n  [0.563543975353241, 0.359827995300293],\n  [0.583841025829315, 0.368713974952698],\n  [0.586614012718201, 0.692366003990173],\n  [0.771915018558502, 0.683578014373779],\n  [0.531597018241882, 0.352482974529266],\n  [0.588370978832245, 0.804440975189209],\n  [0.52079701423645, 0.442565023899078],\n  [0.567984998226166, 0.493479013442993],\n  [0.543282985687256, 0.819254994392395],\n  [0.655317008495331, 0.745514988899231],\n  [0.621008992195129, 0.574018001556396],\n  [0.625559985637665, 0.78031200170517],\n  [0.680198013782501, 0.570719003677368],\n  [0.64276397228241, 0.604337990283966],\n  [0.704662978649139, 0.621529996395111],\n  [0.552012026309967, 0.862591981887817],\n  [0.589071989059448, 0.508637011051178],\n  [0.685944974422455, 0.775357007980347],\n  [0.645735025405884, 0.812640011310577],\n  [0.675342977046967, 0.703978002071381],\n  [0.810858011245728, 0.646304965019226],\n  [0.72012197971344, 0.714666962623596],\n  [0.866151988506317, 0.682704985141754],\n  [0.663187026977539, 0.644596993923187],\n  [0.570082008838654, 0.466325998306274],\n  [0.544561982154846, 0.548375964164734],\n  [0.562758982181549, 0.558784961700439],\n  [0.531987011432648, 0.530140042304993],\n  [0.585271000862122, 0.335177004337311],\n  [0.622952997684479, 0.32277899980545],\n  [0.655896008014679, 0.320163011550903],\n  [0.687132000923157, 0.322345972061157],\n  [0.716481983661652, 0.333200991153717],\n  [0.758756995201111, 0.382786989212036],\n  [0.897013008594513, 0.468769013881683],\n  [0.732392013072968, 0.424547016620636],\n  [0.70211398601532, 0.433162987232208],\n  [0.66652500629425, 0.433866024017334],\n  [0.633504986763, 0.426087975502014],\n  [0.603875994682312, 0.416586995124817],\n  [0.579657971858978, 0.409945011138916],\n  [0.992439985275269, 0.480777025222778],\n  [0.567192018032074, 0.569419980049133],\n  [0.54136598110199, 0.478899002075195],\n  [0.526564002037048, 0.546118021011353],\n  [0.523913025856018, 0.563830018043518],\n  [0.531529009342194, 0.555056989192963],\n  [0.566035985946655, 0.582329034805298],\n  [0.51631098985672, 0.563053965568542],\n  [0.5174720287323, 0.577877044677734],\n  [0.573594987392426, 0.389806985855103],\n  [0.560697972774506, 0.395331978797913],\n  [0.549755990505219, 0.399751007556915],\n  [0.710287988185883, 0.368252992630005],\n  [0.723330020904541, 0.363372981548309],\n];\n\nexport const TRI468: Array<number> = [\n  127, 34, 139, 11, 0, 37, 232, 231, 120, 72, 37, 39, 128, 121, 47, 232, 121, 128, 104, 69, 67, 175, 171, 148, 157, 154, 155, 118, 50, 101, 73, 39, 40, 9,\n  151, 108, 48, 115, 131, 194, 204, 211, 74, 40, 185, 80, 42, 183, 40, 92, 186, 230, 229, 118, 202, 212, 214, 83, 18, 17, 76, 61, 146, 160, 29, 30, 56,\n  157, 173, 106, 204, 194, 135, 214, 192, 203, 165, 98, 21, 71, 68, 51, 45, 4, 144, 24, 23, 77, 146, 91, 205, 50, 187, 201, 200, 18, 91, 106, 182, 90, 91,\n  181, 85, 84, 17, 206, 203, 36, 148, 171, 140, 92, 40, 39, 193, 189, 244, 159, 158, 28, 247, 246, 161, 236, 3, 196, 54, 68, 104, 193, 168, 8, 117,\n  228, 31, 189, 193, 55, 98, 97, 99, 126, 47, 100, 166, 79, 218, 155, 154, 26, 209, 49, 131, 135, 136, 150, 47, 126, 217, 223, 52, 53, 45, 51, 134, 211,\n  170, 140, 67, 69, 108, 43, 106, 91, 230, 119, 120, 226, 130, 247, 63, 53, 52, 238, 20, 242, 46, 70, 156, 78, 62, 96, 46, 53, 63, 143, 34, 227, 173,\n  155, 133, 123, 117, 111, 44, 125, 19, 236, 134, 51, 216, 206, 205, 154, 153, 22, 39, 37, 167, 200, 201, 208, 36, 142, 100, 57, 212, 202, 20, 60, 99, 28,\n  158, 157, 35, 226, 113, 160, 159, 27, 204, 202, 210, 113, 225, 46, 43, 202, 204, 62, 76, 77, 137, 123, 116, 41, 38, 72, 203, 129, 142, 64, 98, 240, 49,\n  102, 64, 41, 73, 74, 212, 216, 207, 42, 74, 184, 169, 170, 211, 170, 149, 176, 105, 66, 69, 122, 6, 168, 123, 147, 187, 96, 77, 90, 65, 55, 107, 89,\n  90, 180, 101, 100, 120, 63, 105, 104, 93, 137, 227, 15, 86, 85, 129, 102, 49, 14, 87, 86, 55, 8, 9, 100, 47, 121, 145, 23, 22, 88, 89, 179, 6, 122,\n  196, 88, 95, 96, 138, 172, 136, 215, 58, 172, 115, 48, 219, 42, 80, 81, 195, 3, 51, 43, 146, 61, 171, 175, 199, 81, 82, 38, 53, 46, 225, 144, 163, 110,\n  246, 33, 7, 52, 65, 66, 229, 228, 117, 34, 127, 234, 107, 108, 69, 109, 108, 151, 48, 64, 235, 62, 78, 191, 129, 209, 126, 111, 35, 143, 163, 161, 246,\n  117, 123, 50, 222, 65, 52, 19, 125, 141, 221, 55, 65, 3, 195, 197, 25, 7, 33, 220, 237, 44, 70, 71, 139, 122, 193, 245, 247, 130, 33, 71, 21, 162,\n  153, 158, 159, 170, 169, 150, 188, 174, 196, 216, 186, 92, 144, 160, 161, 2, 97, 167, 141, 125, 241, 164, 167, 37, 72, 38, 12, 145, 159, 160, 38, 82, 13,\n  63, 68, 71, 226, 35, 111, 158, 153, 154, 101, 50, 205, 206, 92, 165, 209, 198, 217, 165, 167, 97, 220, 115, 218, 133, 112, 243, 239, 238, 241, 214,\n  135, 169, 190, 173, 133, 171, 208, 32, 125, 44, 237, 86, 87, 178, 85, 86, 179, 84, 85, 180, 83, 84, 181, 201, 83, 182, 137, 93, 132, 76, 62, 183, 61,\n  76, 184, 57, 61, 185, 212, 57, 186, 214, 207, 187, 34, 143, 156, 79, 239, 237, 123, 137, 177, 44, 1, 4, 201, 194, 32, 64, 102, 129, 213, 215, 138, 59,\n  166, 219, 242, 99, 97, 2, 94, 141, 75, 59, 235, 24, 110, 228, 25, 130, 226, 23, 24, 229, 22, 23, 230, 26, 22, 231, 112, 26, 232, 189, 190, 243, 221, 56,\n  190, 28, 56, 221, 27, 28, 222, 29, 27, 223, 30, 29, 224, 247, 30, 225, 238, 79, 20, 166, 59, 75, 60, 75, 240, 147, 177, 215, 20, 79, 166, 187, 147, 213,\n  112, 233, 244, 233, 128, 245, 128, 114, 188, 114, 217, 174, 131, 115, 220, 217, 198, 236, 198, 131, 134, 177, 132, 58, 143, 35, 124, 110, 163, 7, 228,\n  110, 25, 356, 389, 368, 11, 302, 267, 452, 350, 349, 302, 303, 269, 357, 343, 277, 452, 453, 357, 333, 332, 297, 175, 152, 377, 384, 398, 382, 347,\n  348, 330, 303, 304, 270, 9, 336, 337, 278, 279, 360, 418, 262, 431, 304, 408, 409, 310, 415, 407, 270, 409, 410, 450, 348, 347, 422, 430, 434, 313,\n  314, 17, 306, 307, 375, 387, 388, 260, 286, 414, 398, 335, 406, 418, 364, 367, 416, 423, 358, 327, 251, 284, 298, 281, 5, 4, 373, 374, 253, 307, 320,\n  321, 425, 427, 411, 421, 313, 18, 321, 405, 406, 320, 404, 405, 315, 16, 17, 426, 425, 266, 377, 400, 369, 322, 391, 269, 417, 465, 464, 386, 257, 258,\n  466, 260, 388, 456, 399, 419, 284, 332, 333, 417, 285, 8, 346, 340, 261, 413, 441, 285, 327, 460, 328, 355, 371, 329, 392, 439, 438, 382, 341, 256,\n  429, 420, 360, 364, 394, 379, 277, 343, 437, 443, 444, 283, 275, 440, 363, 431, 262, 369, 297, 338, 337, 273, 375, 321, 450, 451, 349, 446, 342, 467,\n  293, 334, 282, 458, 461, 462, 276, 353, 383, 308, 324, 325, 276, 300, 293, 372, 345, 447, 382, 398, 362, 352, 345, 340, 274, 1, 19, 456, 248, 281, 436,\n  427, 425, 381, 256, 252, 269, 391, 393, 200, 199, 428, 266, 330, 329, 287, 273, 422, 250, 462, 328, 258, 286, 384, 265, 353, 342, 387, 259, 257, 424,\n  431, 430, 342, 353, 276, 273, 335, 424, 292, 325, 307, 366, 447, 345, 271, 303, 302, 423, 266, 371, 294, 455, 460, 279, 278, 294, 271, 272, 304, 432,\n  434, 427, 272, 407, 408, 394, 430, 431, 395, 369, 400, 334, 333, 299, 351, 417, 168, 352, 280, 411, 325, 319, 320, 295, 296, 336, 319, 403, 404, 330,\n  348, 349, 293, 298, 333, 323, 454, 447, 15, 16, 315, 358, 429, 279, 14, 15, 316, 285, 336, 9, 329, 349, 350, 374, 380, 252, 318, 402, 403, 6, 197, 419,\n  318, 319, 325, 367, 364, 365, 435, 367, 397, 344, 438, 439, 272, 271, 311, 195, 5, 281, 273, 287, 291, 396, 428, 199, 311, 271, 268, 283, 444, 445,\n  373, 254, 339, 263, 466, 249, 282, 334, 296, 449, 347, 346, 264, 447, 454, 336, 296, 299, 338, 10, 151, 278, 439, 455, 292, 407, 415, 358, 371, 355,\n  340, 345, 372, 390, 249, 466, 346, 347, 280, 442, 443, 282, 19, 94, 370, 441, 442, 295, 248, 419, 197, 263, 255, 359, 440, 275, 274, 300, 383, 368,\n  351, 412, 465, 263, 467, 466, 301, 368, 389, 380, 374, 386, 395, 378, 379, 412, 351, 419, 436, 426, 322, 373, 390, 388, 2, 164, 393, 370, 462, 461,\n  164, 0, 267, 302, 11, 12, 374, 373, 387, 268, 12, 13, 293, 300, 301, 446, 261, 340, 385, 384, 381, 330, 266, 425, 426, 423, 391, 429, 355, 437, 391,\n  327, 326, 440, 457, 438, 341, 382, 362, 459, 457, 461, 434, 430, 394, 414, 463, 362, 396, 369, 262, 354, 461, 457, 316, 403, 402, 315, 404, 403, 314,\n  405, 404, 313, 406, 405, 421, 418, 406, 366, 401, 361, 306, 408, 407, 291, 409, 408, 287, 410, 409, 432, 436, 410, 434, 416, 411, 264, 368, 383, 309,\n  438, 457, 352, 376, 401, 274, 275, 4, 421, 428, 262, 294, 327, 358, 433, 416, 367, 289, 455, 439, 462, 370, 326, 2, 326, 370, 305, 460, 455, 254,\n  449, 448, 255, 261, 446, 253, 450, 449, 252, 451, 450, 256, 452, 451, 341, 453, 452, 413, 464, 463, 441, 413, 414, 258, 442, 441, 257, 443, 442, 259,\n  444, 443, 260, 445, 444, 467, 342, 445, 459, 458, 250, 289, 392, 290, 290, 328, 460, 376, 433, 435, 250, 290, 392, 411, 416, 433, 341, 463, 464, 453,\n  464, 465, 357, 465, 412, 343, 412, 399, 360, 363, 440, 437, 399, 456, 420, 456, 363, 401, 435, 288, 372, 383, 353, 339, 255, 249, 448, 261, 255, 133,\n  243, 190, 133, 155, 112, 33, 246, 247, 33, 130, 25, 398, 384, 286, 362, 398, 414, 362, 463, 341, 263, 359, 467, 263, 249, 255, 466, 467, 260, 75, 60,\n  166, 238, 239, 79, 162, 127, 139, 72, 11, 37, 121, 232, 120, 73, 72, 39, 114, 128, 47, 233, 232, 128, 103, 104, 67, 152, 175, 148, 173, 157, 155,\n  119, 118, 101, 74, 73, 40, 107, 9, 108, 49, 48, 131, 32, 194, 211, 184, 74, 185, 191, 80, 183, 185, 40, 186, 119, 230, 118, 210, 202, 214, 84, 83, 17,\n  77, 76, 146, 161, 160, 30, 190, 56, 173, 182, 106, 194, 138, 135, 192, 129, 203, 98, 54, 21, 68, 5, 51, 4, 145, 144, 23, 90, 77, 91, 207, 205, 187, 83,\n  201, 18, 181, 91, 182, 180, 90, 181, 16, 85, 17, 205, 206, 36, 176, 148, 140, 165, 92, 39, 245, 193, 244, 27, 159, 28, 30, 247, 161, 174, 236, 196,\n  103, 54, 104, 55, 193, 8, 111, 117, 31, 221, 189, 55, 240, 98, 99, 142, 126, 100, 219, 166, 218, 112, 155, 26, 198, 209, 131, 169, 135, 150, 114, 47,\n  217, 224, 223, 53, 220, 45, 134, 32, 211, 140, 109, 67, 108, 146, 43, 91, 231, 230, 120, 113, 226, 247, 105, 63, 52, 241, 238, 242, 124, 46, 156, 95,\n  78, 96, 70, 46, 63, 116, 143, 227, 116, 123, 111, 1, 44, 19, 3, 236, 51, 207, 216, 205, 26, 154, 22, 165, 39, 167, 199, 200, 208, 101, 36, 100, 43,\n  57, 202, 242, 20, 99, 56, 28, 157, 124, 35, 113, 29, 160, 27, 211, 204, 210, 124, 113, 46, 106, 43, 204, 96, 62, 77, 227, 137, 116, 73, 41, 72, 36, 203,\n  142, 235, 64, 240, 48, 49, 64, 42, 41, 74, 214, 212, 207, 183, 42, 184, 210, 169, 211, 140, 170, 176, 104, 105, 69, 193, 122, 168, 50, 123, 187, 89, 96,\n  90, 66, 65, 107, 179, 89, 180, 119, 101, 120, 68, 63, 104, 234, 93, 227, 16, 15, 85, 209, 129, 49, 15, 14, 86, 107, 55, 9, 120, 100, 121, 153, 145, 22,\n  178, 88, 179, 197, 6, 196, 89, 88, 96, 135, 138, 136, 138, 215, 172, 218, 115, 219, 41, 42, 81, 5, 195, 51, 57, 43, 61, 208, 171, 199, 41, 81, 38,\n  224, 53, 225, 24, 144, 110, 105, 52, 66, 118, 229, 117, 227, 34, 234, 66, 107, 69, 10, 109, 151, 219, 48, 235, 183, 62, 191, 142, 129, 126, 116, 111,\n  143, 7, 163, 246, 118, 117, 50, 223, 222, 52, 94, 19, 141, 222, 221, 65, 196, 3, 197, 45, 220, 44, 156, 70, 139, 188, 122, 245, 139, 71, 162, 145,\n  153, 159, 149, 170, 150, 122, 188, 196, 206, 216, 92, 163, 144, 161, 164, 2, 167, 242, 141, 241, 0, 164, 37, 11, 72, 12, 144, 145, 160, 12, 38, 13, 70,\n  63, 71, 31, 226, 111, 157, 158, 154, 36, 101, 205, 203, 206, 165, 126, 209, 217, 98, 165, 97, 237, 220, 218, 237, 239, 241, 210, 214, 169, 140, 171, 32,\n  241, 125, 237, 179, 86, 178, 180, 85, 179, 181, 84, 180, 182, 83, 181, 194, 201, 182, 177, 137, 132, 184, 76, 183, 185, 61, 184, 186, 57, 185, 216, 212,\n  186, 192, 214, 187, 139, 34, 156, 218, 79, 237, 147, 123, 177, 45, 44, 4, 208, 201, 32, 98, 64, 129, 192, 213, 138, 235, 59, 219, 141, 242, 97, 97, 2,\n  141, 240, 75, 235, 229, 24, 228, 31, 25, 226, 230, 23, 229, 231, 22, 230, 232, 26, 231, 233, 112, 232, 244, 189, 243, 189, 221, 190, 222, 28, 221,\n  223, 27, 222, 224, 29, 223, 225, 30, 224, 113, 247, 225, 99, 60, 240, 213, 147, 215, 60, 20, 166, 192, 187, 213, 243, 112, 244, 244, 233, 245, 245,\n  128, 188, 188, 114, 174, 134, 131, 220, 174, 217, 236, 236, 198, 134, 215, 177, 58, 156, 143, 124, 25, 110, 7, 31, 228, 25, 264, 356, 368, 0, 11, 267,\n  451, 452, 349, 267, 302, 269, 350, 357, 277, 350, 452, 357, 299, 333, 297, 396, 175, 377, 381, 384, 382, 280, 347, 330, 269, 303, 270, 151, 9, 337,\n  344, 278, 360, 424, 418, 431, 270, 304, 409, 272, 310, 407, 322, 270, 410, 449, 450, 347, 432, 422, 434, 18, 313, 17, 291, 306, 375, 259, 387, 260,\n  424, 335, 418, 434, 364, 416, 391, 423, 327, 301, 251, 298, 275, 281, 4, 254, 373, 253, 375, 307, 321, 280, 425, 411, 200, 421, 18, 335, 321, 406,\n  321, 320, 405, 314, 315, 17, 423, 426, 266, 396, 377, 369, 270, 322, 269, 413, 417, 464, 385, 386, 258, 248, 456, 419, 298, 284, 333, 168, 417, 8,\n  448, 346, 261, 417, 413, 285, 326, 327, 328, 277, 355, 329, 309, 392, 438, 381, 382, 256, 279, 429, 360, 365, 364, 379, 355, 277, 437, 282, 443, 283,\n  281, 275, 363, 395, 431, 369, 299, 297, 337, 335, 273, 321, 348, 450, 349, 359, 446, 467, 283, 293, 282, 250, 458, 462, 300, 276, 383, 292, 308, 325,\n  283, 276, 293, 264, 372, 447, 346, 352, 340, 354, 274, 19, 363, 456, 281, 426, 436, 425, 380, 381, 252, 267, 269, 393, 421, 200, 428, 371, 266, 329,\n  432, 287, 422, 290, 250, 328, 385, 258, 384, 446, 265, 342, 386, 387, 257, 422, 424, 430, 445, 342, 276, 422, 273, 424, 306, 292, 307, 352, 366, 345,\n  268, 271, 302, 358, 423, 371, 327, 294, 460, 331, 279, 294, 303, 271, 304, 436, 432, 427, 304, 272, 408, 395, 394, 431, 378, 395, 400, 296, 334, 299,\n  6, 351, 168, 376, 352, 411, 307, 325, 320, 285, 295, 336, 320, 319, 404, 329, 330, 349, 334, 293, 333, 366, 323, 447, 316, 15, 315, 331, 358, 279,\n  317, 14, 316, 8, 285, 9, 277, 329, 350, 253, 374, 252, 319, 318, 403, 351, 6, 419, 324, 318, 325, 397, 367, 365, 288, 435, 397, 278, 344, 439, 310,\n  272, 311, 248, 195, 281, 375, 273, 291, 175, 396, 199, 312, 311, 268, 276, 283, 445, 390, 373, 339, 295, 282, 296, 448, 449, 346, 356, 264, 454, 337,\n  336, 299, 337, 338, 151, 294, 278, 455, 308, 292, 415, 429, 358, 355, 265, 340, 372, 388, 390, 466, 352, 346, 280, 295, 442, 282, 354, 19, 370, 285,\n  441, 295, 195, 248, 197, 457, 440, 274, 301, 300, 368, 417, 351, 465, 251, 301, 389, 385, 380, 386, 394, 395, 379, 399, 412, 419, 410, 436, 322, 387,\n  373, 388, 326, 2, 393, 354, 370, 461, 393, 164, 267, 268, 302, 12, 386, 374, 387, 312, 268, 13, 298, 293, 301, 265, 446, 340, 380, 385, 381, 280, 330,\n  425, 322, 426, 391, 420, 429, 437, 393, 391, 326, 344, 440, 438, 458, 459, 461, 364, 434, 394, 428, 396, 262, 274, 354, 457, 317, 316, 402, 316, 315,\n  403, 315, 314, 404, 314, 313, 405, 313, 421, 406, 323, 366, 361, 292, 306, 407, 306, 291, 408, 291, 287, 409, 287, 432, 410, 427, 434, 411, 372, 264,\n  383, 459, 309, 457, 366, 352, 401, 1, 274, 4, 418, 421, 262, 331, 294, 358, 435, 433, 367, 392, 289, 439, 328, 462, 326, 94, 2, 370, 289, 305, 455, 339,\n  254, 448, 359, 255, 446, 254, 253, 449, 253, 252, 450, 252, 256, 451, 256, 341, 452, 414, 413, 463, 286, 441, 414, 286, 258, 441, 258, 257, 442, 257,\n  259, 443, 259, 260, 444, 260, 467, 445, 309, 459, 250, 305, 289, 290, 305, 290, 460, 401, 376, 435, 309, 250, 392, 376, 411, 433, 453, 341, 464, 357,\n  453, 465, 343, 357, 412, 437, 343, 399, 344, 360, 440, 420, 437, 456, 360, 420, 363, 361, 401, 288, 265, 372, 353, 390, 339, 249, 339, 448, 255];\n\nexport const TRI68: Array<number> = [0, 1, 36, 0, 36, 17, 1, 2, 41, 1, 41, 36, 2, 3, 31, 2, 31, 41, 3, 4, 48, 3, 48, 31, 4, 5, 48, 5, 6, 48, 6, 7, 59, 6, 59, 48, 7, 8, 58, 7, 58, 59,\n  8, 9, 56, 8, 56, 57, 8, 57, 58, 9, 10, 55, 9, 55, 56, 10, 11, 54, 10, 54, 55, 11, 12, 54, 12, 13, 54, 13, 14, 35, 13, 35, 54, 14, 15, 46, 14, 46, 35, 15, 16,\n  45, 15, 45, 46, 16, 26, 45, 17, 36, 18, 18, 37, 19, 18, 36, 37, 19, 38, 20, 19, 37, 38, 20, 39, 21, 20, 38, 39, 21, 39, 27, 22, 42, 23, 22, 27, 42, 23, 43, 24,\n  23, 42, 43, 24, 44, 25, 24, 43, 44, 25, 45, 26, 25, 44, 45, 27, 39, 28, 27, 28, 42, 28, 39, 29, 28, 29, 42, 29, 31, 30, 29, 30, 35, 29, 40, 31, 29, 35, 47, 29,\n  39, 40, 29, 47, 42, 30, 31, 32, 30, 32, 33, 30, 33, 34, 30, 34, 35, 31, 50, 32, 31, 40, 41, 31, 48, 49, 31, 49, 50, 32, 51, 33, 32, 50, 51, 33, 51, 34, 34, 52,\n  35, 34, 51, 52, 35, 46, 47, 35, 52, 53, 35, 53, 54, 36, 41, 37, 37, 40, 38, 37, 41, 40, 38, 40, 39, 42, 47, 43, 43, 47, 44, 44, 46, 45, 44, 47, 46, 48, 60, 49,\n  48, 59, 60, 49, 61, 50, 49, 60, 61, 50, 62, 51, 50, 61, 62, 51, 62, 52, 52, 63, 53, 52, 62, 63, 53, 64, 54, 53, 63, 64, 54, 64, 55, 55, 65, 56, 55, 64, 65, 56,\n  66, 57, 56, 65, 66, 57, 66, 58, 58, 67, 59, 58, 66, 67, 59, 67, 60, 60, 67, 61, 61, 66, 62, 61, 67, 66, 62, 66, 63, 63, 65, 64, 63, 66, 65, 21, 27, 22];\n\nexport const TRI33: Array<number> = [\n  /*  eyes  */ 0, 8, 7, 7, 8, 1, 2, 10, 9, 9, 10, 3,\n  /*  brows */ 17, 0, 18, 18, 0, 7, 18, 7, 19, 19, 7, 1, 19, 1, 11, 19, 11, 20, 21, 3, 22, 21, 9, 3, 20, 9, 21, 20, 2, 9, 20, 11, 2,\n  /*  4head */ 23, 17, 18, 25, 21, 22, 24, 19, 20, 24, 18, 19, 24, 20, 21, 24, 23, 18, 24, 21, 25,\n  /*  nose  */ 11, 12, 4, 11, 4, 13, 1, 12, 11, 11, 13, 2, 12, 14, 4, 4, 14, 13,\n  /* up-lip */ 14, 5, 15, 14, 15, 6, 12, 5, 14, 14, 6, 13,\n  /* cheeks */ 8, 12, 1, 2, 13, 10, 8, 26, 12, 10, 13, 27, 26, 5, 12, 13, 6, 27, 0, 26, 8, 10, 27, 3,\n  /*  chin  */ 5, 32, 16, 16, 32, 6, 5, 30, 32, 6, 32, 31,\n  /*  cont  */ 26, 30, 5, 27, 6, 31, 0, 28, 26, 3, 27, 29, 17, 28, 0, 3, 29, 22, 23, 28, 17, 22, 29, 25, 28, 30, 26, 27, 31, 29,\n];\n\nexport const TRI7: Array<number> = [0, 4, 1, 2, 4, 3, 4, 5, 6];\n\nexport const VTX68: Array<number> = [\n  /* cont  */ 127, 234, 132, 58, 172, 150, 149, 148, 152, 377, 378, 379, 397, 288, 361, 454, 356,\n  /* brows */ 70, 63, 105, 66, 107, 336, 296, 334, 293, 300,\n  /* nose  */ 168, 6, 195, 4, 98, 97, 2, 326, 327,\n  /* eyes  */ 33, 160, 158, 133, 153, 144, 362, 385, 387, 263, 373, 380,\n  /* lip   */ 57, 40, 37, 0, 267, 270, 287, 321, 314, 17, 84, 91,\n  /* mouth */ 78, 81, 13, 311, 308, 402, 14, 178,\n];\n\nexport const VTX33: Array<number> = [33, 133, 362, 263, 1, 62, 308, 159, 145, 386, 374, 6, 102, 331, 2, 13, 14, 70, 105, 107, 336, 334, 300, 54, 10, 284, 50, 280, 234, 454, 58, 288, 152];\n\nexport const VTX7: Array<number> = [33, 133, 362, 263, 1, 78, 308];\n\nexport const UV68 = VTX68.map((x) => UV468[x]);\n\nexport const UV33 = VTX33.map((x) => UV468[x]);\n\nexport const UV7 = VTX7.map((x) => UV468[x]);\n\n// https://github.com/tensorflow/tfjs-models/blob/master/face-landmarks-detection/src/constants.ts\n// https://github.com/google/mediapipe/mediapipe/python/solutions/face_mesh_connections.py\n\ntype PairArray = Array<[number, number]>;\n\nfunction connectionsToIndices(connections: PairArray) {\n  const indices = connections.map((connection) => connection[0]);\n  indices.push(connections[connections.length - 1][1]);\n  return indices;\n}\n\nexport const pairsLips: PairArray = [\n  [61, 146], [146, 91], [91, 181], [181, 84], [84, 17], [17, 314], [314, 405], [405, 321], [321, 375], [375, 291], [61, 185], [185, 40], [40, 39], [39, 37], [37, 0], [0, 267], [267, 269], [269, 270], [270, 409], [409, 291],\n  [78, 95], [95, 88], [88, 178], [178, 87], [87, 14], [14, 317], [317, 402], [402, 318], [318, 324], [324, 308], [78, 191], [191, 80], [80, 81], [81, 82], [82, 13], [13, 312], [312, 311], [311, 310], [310, 415], [415, 308],\n];\n\nexport const pairsLeftEye: PairArray = [[263, 249], [249, 390], [390, 373], [373, 374], [374, 380], [380, 381], [381, 382], [382, 362], [263, 466], [466, 388], [388, 387], [387, 386], [386, 385], [385, 384], [384, 398], [398, 362]];\n\nexport const pairsLeftEyebrow: PairArray = [[276, 283], [283, 282], [282, 295], [295, 285], [300, 293], [293, 334], [334, 296], [296, 336]];\n\nexport const pairsLeftIris: PairArray = [[474, 475], [475, 476], [476, 477], [477, 474]];\n\nexport const pairsRightEye: PairArray = [[33, 7], [7, 163], [163, 144], [144, 145], [145, 153], [153, 154], [154, 155], [155, 133], [33, 246], [246, 161], [161, 160], [160, 159], [159, 158], [158, 157], [157, 173], [173, 133]];\n\nexport const pairsRightEyebrow: PairArray = [[46, 53], [53, 52], [52, 65], [65, 55], [70, 63], [63, 105], [105, 66], [66, 107]];\n\nexport const pairsRightIris: PairArray = [[469, 470], [470, 471], [471, 472], [472, 469]];\n\nexport const pairsFaceContour: PairArray = [\n  [10, 338], [338, 297], [297, 332], [332, 284], [284, 251], [251, 389],\n  [389, 356], [356, 454], [454, 323], [323, 361], [361, 288], [288, 397],\n  [397, 365], [365, 379], [379, 378], [378, 400], [400, 377], [377, 152],\n  [152, 148], [148, 176], [176, 149], [149, 150], [150, 136], [136, 172],\n  [172, 58], [58, 132], [132, 93], [93, 234], [234, 127], [127, 162],\n  [162, 21], [21, 54], [54, 103], [103, 67], [67, 109], [109, 10],\n];\n\nexport const contourKeypoints = {\n  lips: connectionsToIndices(pairsLips),\n  leftEye: connectionsToIndices(pairsLeftEye),\n  leftEyebrow: connectionsToIndices(pairsLeftEyebrow),\n  leftIris: connectionsToIndices(pairsLeftIris),\n  rightEye: connectionsToIndices(pairsRightEye),\n  rightEyebrow: connectionsToIndices(pairsRightEyebrow),\n  rightIris: connectionsToIndices(pairsRightIris),\n  faceOval: connectionsToIndices(pairsFaceContour),\n};\n\nexport const pairsFaceMesh: PairArray = [\n  [127, 34], [34, 139], [139, 127], [11, 0], [0, 37], [37, 11],\n  [232, 231], [231, 120], [120, 232], [72, 37], [37, 39], [39, 72],\n  [128, 121], [121, 47], [47, 128], [232, 121], [121, 128], [128, 232],\n  [104, 69], [69, 67], [67, 104], [175, 171], [171, 148], [148, 175],\n  [118, 50], [50, 101], [101, 118], [73, 39], [39, 40], [40, 73],\n  [9, 151], [151, 108], [108, 9], [48, 115], [115, 131], [131, 48],\n  [194, 204], [204, 211], [211, 194], [74, 40], [40, 185], [185, 74],\n  [80, 42], [42, 183], [183, 80], [40, 92], [92, 186], [186, 40],\n  [230, 229], [229, 118], [118, 230], [202, 212], [212, 214], [214, 202],\n  [83, 18], [18, 17], [17, 83], [76, 61], [61, 146], [146, 76],\n  [160, 29], [29, 30], [30, 160], [56, 157], [157, 173], [173, 56],\n  [106, 204], [204, 194], [194, 106], [135, 214], [214, 192], [192, 135],\n  [203, 165], [165, 98], [98, 203], [21, 71], [71, 68], [68, 21],\n  [51, 45], [45, 4], [4, 51], [144, 24], [24, 23], [23, 144],\n  [77, 146], [146, 91], [91, 77], [205, 50], [50, 187], [187, 205],\n  [201, 200], [200, 18], [18, 201], [91, 106], [106, 182], [182, 91],\n  [90, 91], [91, 181], [181, 90], [85, 84], [84, 17], [17, 85],\n  [206, 203], [203, 36], [36, 206], [148, 171], [171, 140], [140, 148],\n  [92, 40], [40, 39], [39, 92], [193, 189], [189, 244], [244, 193],\n  [159, 158], [158, 28], [28, 159], [247, 246], [246, 161], [161, 247],\n  [236, 3], [3, 196], [196, 236], [54, 68], [68, 104], [104, 54],\n  [193, 168], [168, 8], [8, 193], [117, 228], [228, 31], [31, 117],\n  [189, 193], [193, 55], [55, 189], [98, 97], [97, 99], [99, 98],\n  [126, 47], [47, 100], [100, 126], [166, 79], [79, 218], [218, 166],\n  [155, 154], [154, 26], [26, 155], [209, 49], [49, 131], [131, 209],\n  [135, 136], [136, 150], [150, 135], [47, 126], [126, 217], [217, 47],\n  [223, 52], [52, 53], [53, 223], [45, 51], [51, 134], [134, 45],\n  [211, 170], [170, 140], [140, 211], [67, 69], [69, 108], [108, 67],\n  [43, 106], [106, 91], [91, 43], [230, 119], [119, 120], [120, 230],\n  [226, 130], [130, 247], [247, 226], [63, 53], [53, 52], [52, 63],\n  [238, 20], [20, 242], [242, 238], [46, 70], [70, 156], [156, 46],\n  [78, 62], [62, 96], [96, 78], [46, 53], [53, 63], [63, 46],\n  [143, 34], [34, 227], [227, 143], [123, 117], [117, 111], [111, 123],\n  [44, 125], [125, 19], [19, 44], [236, 134], [134, 51], [51, 236],\n  [216, 206], [206, 205], [205, 216], [154, 153], [153, 22], [22, 154],\n  [39, 37], [37, 167], [167, 39], [200, 201], [201, 208], [208, 200],\n  [36, 142], [142, 100], [100, 36], [57, 212], [212, 202], [202, 57],\n  [20, 60], [60, 99], [99, 20], [28, 158], [158, 157], [157, 28],\n  [35, 226], [226, 113], [113, 35], [160, 159], [159, 27], [27, 160],\n  [204, 202], [202, 210], [210, 204], [113, 225], [225, 46], [46, 113],\n  [43, 202], [202, 204], [204, 43], [62, 76], [76, 77], [77, 62],\n  [137, 123], [123, 116], [116, 137], [41, 38], [38, 72], [72, 41],\n  [203, 129], [129, 142], [142, 203], [64, 98], [98, 240], [240, 64],\n  [49, 102], [102, 64], [64, 49], [41, 73], [73, 74], [74, 41],\n  [212, 216], [216, 207], [207, 212], [42, 74], [74, 184], [184, 42],\n  [169, 170], [170, 211], [211, 169], [170, 149], [149, 176], [176, 170],\n  [105, 66], [66, 69], [69, 105], [122, 6], [6, 168], [168, 122],\n  [123, 147], [147, 187], [187, 123], [96, 77], [77, 90], [90, 96],\n  [65, 55], [55, 107], [107, 65], [89, 90], [90, 180], [180, 89],\n  [101, 100], [100, 120], [120, 101], [63, 105], [105, 104], [104, 63],\n  [93, 137], [137, 227], [227, 93], [15, 86], [86, 85], [85, 15],\n  [129, 102], [102, 49], [49, 129], [14, 87], [87, 86], [86, 14],\n  [55, 8], [8, 9], [9, 55], [100, 47], [47, 121], [121, 100],\n  [145, 23], [23, 22], [22, 145], [88, 89], [89, 179], [179, 88],\n  [6, 122], [122, 196], [196, 6], [88, 95], [95, 96], [96, 88],\n  [138, 172], [172, 136], [136, 138], [215, 58], [58, 172], [172, 215],\n  [115, 48], [48, 219], [219, 115], [42, 80], [80, 81], [81, 42],\n  [195, 3], [3, 51], [51, 195], [43, 146], [146, 61], [61, 43],\n  [171, 175], [175, 199], [199, 171], [81, 82], [82, 38], [38, 81],\n  [53, 46], [46, 225], [225, 53], [144, 163], [163, 110], [110, 144],\n  [52, 65], [65, 66], [66, 52], [229, 228], [228, 117], [117, 229],\n  [34, 127], [127, 234], [234, 34], [107, 108], [108, 69], [69, 107],\n  [109, 108], [108, 151], [151, 109], [48, 64], [64, 235], [235, 48],\n  [62, 78], [78, 191], [191, 62], [129, 209], [209, 126], [126, 129],\n  [111, 35], [35, 143], [143, 111], [117, 123], [123, 50], [50, 117],\n  [222, 65], [65, 52], [52, 222], [19, 125], [125, 141], [141, 19],\n  [221, 55], [55, 65], [65, 221], [3, 195], [195, 197], [197, 3],\n  [25, 7], [7, 33], [33, 25], [220, 237], [237, 44], [44, 220],\n  [70, 71], [71, 139], [139, 70], [122, 193], [193, 245], [245, 122],\n  [247, 130], [130, 33], [33, 247], [71, 21], [21, 162], [162, 71],\n  [170, 169], [169, 150], [150, 170], [188, 174], [174, 196], [196, 188],\n  [216, 186], [186, 92], [92, 216], [2, 97], [97, 167], [167, 2],\n  [141, 125], [125, 241], [241, 141], [164, 167], [167, 37], [37, 164],\n  [72, 38], [38, 12], [12, 72], [38, 82], [82, 13], [13, 38],\n  [63, 68], [68, 71], [71, 63], [226, 35], [35, 111], [111, 226],\n  [101, 50], [50, 205], [205, 101], [206, 92], [92, 165], [165, 206],\n  [209, 198], [198, 217], [217, 209], [165, 167], [167, 97], [97, 165],\n  [220, 115], [115, 218], [218, 220], [133, 112], [112, 243], [243, 133],\n  [239, 238], [238, 241], [241, 239], [214, 135], [135, 169], [169, 214],\n  [190, 173], [173, 133], [133, 190], [171, 208], [208, 32], [32, 171],\n  [125, 44], [44, 237], [237, 125], [86, 87], [87, 178], [178, 86],\n  [85, 86], [86, 179], [179, 85], [84, 85], [85, 180], [180, 84],\n  [83, 84], [84, 181], [181, 83], [201, 83], [83, 182], [182, 201],\n  [137, 93], [93, 132], [132, 137], [76, 62], [62, 183], [183, 76],\n  [61, 76], [76, 184], [184, 61], [57, 61], [61, 185], [185, 57],\n  [212, 57], [57, 186], [186, 212], [214, 207], [207, 187], [187, 214],\n  [34, 143], [143, 156], [156, 34], [79, 239], [239, 237], [237, 79],\n  [123, 137], [137, 177], [177, 123], [44, 1], [1, 4], [4, 44],\n  [201, 194], [194, 32], [32, 201], [64, 102], [102, 129], [129, 64],\n  [213, 215], [215, 138], [138, 213], [59, 166], [166, 219], [219, 59],\n  [242, 99], [99, 97], [97, 242], [2, 94], [94, 141], [141, 2],\n  [75, 59], [59, 235], [235, 75], [24, 110], [110, 228], [228, 24],\n  [25, 130], [130, 226], [226, 25], [23, 24], [24, 229], [229, 23],\n  [22, 23], [23, 230], [230, 22], [26, 22], [22, 231], [231, 26],\n  [112, 26], [26, 232], [232, 112], [189, 190], [190, 243], [243, 189],\n  [221, 56], [56, 190], [190, 221], [28, 56], [56, 221], [221, 28],\n  [27, 28], [28, 222], [222, 27], [29, 27], [27, 223], [223, 29],\n  [30, 29], [29, 224], [224, 30], [247, 30], [30, 225], [225, 247],\n  [238, 79], [79, 20], [20, 238], [166, 59], [59, 75], [75, 166],\n  [60, 75], [75, 240], [240, 60], [147, 177], [177, 215], [215, 147],\n  [20, 79], [79, 166], [166, 20], [187, 147], [147, 213], [213, 187],\n  [112, 233], [233, 244], [244, 112], [233, 128], [128, 245], [245, 233],\n  [128, 114], [114, 188], [188, 128], [114, 217], [217, 174], [174, 114],\n  [131, 115], [115, 220], [220, 131], [217, 198], [198, 236], [236, 217],\n  [198, 131], [131, 134], [134, 198], [177, 132], [132, 58], [58, 177],\n  [143, 35], [35, 124], [124, 143], [110, 163], [163, 7], [7, 110],\n  [228, 110], [110, 25], [25, 228], [356, 389], [389, 368], [368, 356],\n  [11, 302], [302, 267], [267, 11], [452, 350], [350, 349], [349, 452],\n  [302, 303], [303, 269], [269, 302], [357, 343], [343, 277], [277, 357],\n  [452, 453], [453, 357], [357, 452], [333, 332], [332, 297], [297, 333],\n  [175, 152], [152, 377], [377, 175], [347, 348], [348, 330], [330, 347],\n  [303, 304], [304, 270], [270, 303], [9, 336], [336, 337], [337, 9],\n  [278, 279], [279, 360], [360, 278], [418, 262], [262, 431], [431, 418],\n  [304, 408], [408, 409], [409, 304], [310, 415], [415, 407], [407, 310],\n  [270, 409], [409, 410], [410, 270], [450, 348], [348, 347], [347, 450],\n  [422, 430], [430, 434], [434, 422], [313, 314], [314, 17], [17, 313],\n  [306, 307], [307, 375], [375, 306], [387, 388], [388, 260], [260, 387],\n  [286, 414], [414, 398], [398, 286], [335, 406], [406, 418], [418, 335],\n  [364, 367], [367, 416], [416, 364], [423, 358], [358, 327], [327, 423],\n  [251, 284], [284, 298], [298, 251], [281, 5], [5, 4], [4, 281],\n  [373, 374], [374, 253], [253, 373], [307, 320], [320, 321], [321, 307],\n  [425, 427], [427, 411], [411, 425], [421, 313], [313, 18], [18, 421],\n  [321, 405], [405, 406], [406, 321], [320, 404], [404, 405], [405, 320],\n  [315, 16], [16, 17], [17, 315], [426, 425], [425, 266], [266, 426],\n  [377, 400], [400, 369], [369, 377], [322, 391], [391, 269], [269, 322],\n  [417, 465], [465, 464], [464, 417], [386, 257], [257, 258], [258, 386],\n  [466, 260], [260, 388], [388, 466], [456, 399], [399, 419], [419, 456],\n  [284, 332], [332, 333], [333, 284], [417, 285], [285, 8], [8, 417],\n  [346, 340], [340, 261], [261, 346], [413, 441], [441, 285], [285, 413],\n  [327, 460], [460, 328], [328, 327], [355, 371], [371, 329], [329, 355],\n  [392, 439], [439, 438], [438, 392], [382, 341], [341, 256], [256, 382],\n  [429, 420], [420, 360], [360, 429], [364, 394], [394, 379], [379, 364],\n  [277, 343], [343, 437], [437, 277], [443, 444], [444, 283], [283, 443],\n  [275, 440], [440, 363], [363, 275], [431, 262], [262, 369], [369, 431],\n  [297, 338], [338, 337], [337, 297], [273, 375], [375, 321], [321, 273],\n  [450, 451], [451, 349], [349, 450], [446, 342], [342, 467], [467, 446],\n  [293, 334], [334, 282], [282, 293], [458, 461], [461, 462], [462, 458],\n  [276, 353], [353, 383], [383, 276], [308, 324], [324, 325], [325, 308],\n  [276, 300], [300, 293], [293, 276], [372, 345], [345, 447], [447, 372],\n  [352, 345], [345, 340], [340, 352], [274, 1], [1, 19], [19, 274],\n  [456, 248], [248, 281], [281, 456], [436, 427], [427, 425], [425, 436],\n  [381, 256], [256, 252], [252, 381], [269, 391], [391, 393], [393, 269],\n  [200, 199], [199, 428], [428, 200], [266, 330], [330, 329], [329, 266],\n  [287, 273], [273, 422], [422, 287], [250, 462], [462, 328], [328, 250],\n  [258, 286], [286, 384], [384, 258], [265, 353], [353, 342], [342, 265],\n  [387, 259], [259, 257], [257, 387], [424, 431], [431, 430], [430, 424],\n  [342, 353], [353, 276], [276, 342], [273, 335], [335, 424], [424, 273],\n  [292, 325], [325, 307], [307, 292], [366, 447], [447, 345], [345, 366],\n  [271, 303], [303, 302], [302, 271], [423, 266], [266, 371], [371, 423],\n  [294, 455], [455, 460], [460, 294], [279, 278], [278, 294], [294, 279],\n  [271, 272], [272, 304], [304, 271], [432, 434], [434, 427], [427, 432],\n  [272, 407], [407, 408], [408, 272], [394, 430], [430, 431], [431, 394],\n  [395, 369], [369, 400], [400, 395], [334, 333], [333, 299], [299, 334],\n  [351, 417], [417, 168], [168, 351], [352, 280], [280, 411], [411, 352],\n  [325, 319], [319, 320], [320, 325], [295, 296], [296, 336], [336, 295],\n  [319, 403], [403, 404], [404, 319], [330, 348], [348, 349], [349, 330],\n  [293, 298], [298, 333], [333, 293], [323, 454], [454, 447], [447, 323],\n  [15, 16], [16, 315], [315, 15], [358, 429], [429, 279], [279, 358],\n  [14, 15], [15, 316], [316, 14], [285, 336], [336, 9], [9, 285],\n  [329, 349], [349, 350], [350, 329], [374, 380], [380, 252], [252, 374],\n  [318, 402], [402, 403], [403, 318], [6, 197], [197, 419], [419, 6],\n  [318, 319], [319, 325], [325, 318], [367, 364], [364, 365], [365, 367],\n  [435, 367], [367, 397], [397, 435], [344, 438], [438, 439], [439, 344],\n  [272, 271], [271, 311], [311, 272], [195, 5], [5, 281], [281, 195],\n  [273, 287], [287, 291], [291, 273], [396, 428], [428, 199], [199, 396],\n  [311, 271], [271, 268], [268, 311], [283, 444], [444, 445], [445, 283],\n  [373, 254], [254, 339], [339, 373], [282, 334], [334, 296], [296, 282],\n  [449, 347], [347, 346], [346, 449], [264, 447], [447, 454], [454, 264],\n  [336, 296], [296, 299], [299, 336], [338, 10], [10, 151], [151, 338],\n  [278, 439], [439, 455], [455, 278], [292, 407], [407, 415], [415, 292],\n  [358, 371], [371, 355], [355, 358], [340, 345], [345, 372], [372, 340],\n  [346, 347], [347, 280], [280, 346], [442, 443], [443, 282], [282, 442],\n  [19, 94], [94, 370], [370, 19], [441, 442], [442, 295], [295, 441],\n  [248, 419], [419, 197], [197, 248], [263, 255], [255, 359], [359, 263],\n  [440, 275], [275, 274], [274, 440], [300, 383], [383, 368], [368, 300],\n  [351, 412], [412, 465], [465, 351], [263, 467], [467, 466], [466, 263],\n  [301, 368], [368, 389], [389, 301], [395, 378], [378, 379], [379, 395],\n  [412, 351], [351, 419], [419, 412], [436, 426], [426, 322], [322, 436],\n  [2, 164], [164, 393], [393, 2], [370, 462], [462, 461], [461, 370],\n  [164, 0], [0, 267], [267, 164], [302, 11], [11, 12], [12, 302],\n  [268, 12], [12, 13], [13, 268], [293, 300], [300, 301], [301, 293],\n  [446, 261], [261, 340], [340, 446], [330, 266], [266, 425], [425, 330],\n  [426, 423], [423, 391], [391, 426], [429, 355], [355, 437], [437, 429],\n  [391, 327], [327, 326], [326, 391], [440, 457], [457, 438], [438, 440],\n  [341, 382], [382, 362], [362, 341], [459, 457], [457, 461], [461, 459],\n  [434, 430], [430, 394], [394, 434], [414, 463], [463, 362], [362, 414],\n  [396, 369], [369, 262], [262, 396], [354, 461], [461, 457], [457, 354],\n  [316, 403], [403, 402], [402, 316], [315, 404], [404, 403], [403, 315],\n  [314, 405], [405, 404], [404, 314], [313, 406], [406, 405], [405, 313],\n  [421, 418], [418, 406], [406, 421], [366, 401], [401, 361], [361, 366],\n  [306, 408], [408, 407], [407, 306], [291, 409], [409, 408], [408, 291],\n  [287, 410], [410, 409], [409, 287], [432, 436], [436, 410], [410, 432],\n  [434, 416], [416, 411], [411, 434], [264, 368], [368, 383], [383, 264],\n  [309, 438], [438, 457], [457, 309], [352, 376], [376, 401], [401, 352],\n  [274, 275], [275, 4], [4, 274], [421, 428], [428, 262], [262, 421],\n  [294, 327], [327, 358], [358, 294], [433, 416], [416, 367], [367, 433],\n  [289, 455], [455, 439], [439, 289], [462, 370], [370, 326], [326, 462],\n  [2, 326], [326, 370], [370, 2], [305, 460], [460, 455], [455, 305],\n  [254, 449], [449, 448], [448, 254], [255, 261], [261, 446], [446, 255],\n  [253, 450], [450, 449], [449, 253], [252, 451], [451, 450], [450, 252],\n  [256, 452], [452, 451], [451, 256], [341, 453], [453, 452], [452, 341],\n  [413, 464], [464, 463], [463, 413], [441, 413], [413, 414], [414, 441],\n  [258, 442], [442, 441], [441, 258], [257, 443], [443, 442], [442, 257],\n  [259, 444], [444, 443], [443, 259], [260, 445], [445, 444], [444, 260],\n  [467, 342], [342, 445], [445, 467], [459, 458], [458, 250], [250, 459],\n  [289, 392], [392, 290], [290, 289], [290, 328], [328, 460], [460, 290],\n  [376, 433], [433, 435], [435, 376], [250, 290], [290, 392], [392, 250],\n  [411, 416], [416, 433], [433, 411], [341, 463], [463, 464], [464, 341],\n  [453, 464], [464, 465], [465, 453], [357, 465], [465, 412], [412, 357],\n  [343, 412], [412, 399], [399, 343], [360, 363], [363, 440], [440, 360],\n  [437, 399], [399, 456], [456, 437], [420, 456], [456, 363], [363, 420],\n  [401, 435], [435, 288], [288, 401], [372, 383], [383, 353], [353, 372],\n  [339, 255], [255, 249], [249, 339], [448, 261], [261, 255], [255, 448],\n  [133, 243], [243, 190], [190, 133], [133, 155], [155, 112], [112, 133],\n  [33, 246], [246, 247], [247, 33], [33, 130], [130, 25], [25, 33],\n  [398, 384], [384, 286], [286, 398], [362, 398], [398, 414], [414, 362],\n  [362, 463], [463, 341], [341, 362], [263, 359], [359, 467], [467, 263],\n  [263, 249], [249, 255], [255, 263], [466, 467], [467, 260], [260, 466],\n  [75, 60], [60, 166], [166, 75], [238, 239], [239, 79], [79, 238],\n  [162, 127], [127, 139], [139, 162], [72, 11], [11, 37], [37, 72],\n  [121, 232], [232, 120], [120, 121], [73, 72], [72, 39], [39, 73],\n  [114, 128], [128, 47], [47, 114], [233, 232], [232, 128], [128, 233],\n  [103, 104], [104, 67], [67, 103], [152, 175], [175, 148], [148, 152],\n  [119, 118], [118, 101], [101, 119], [74, 73], [73, 40], [40, 74],\n  [107, 9], [9, 108], [108, 107], [49, 48], [48, 131], [131, 49],\n  [32, 194], [194, 211], [211, 32], [184, 74], [74, 185], [185, 184],\n  [191, 80], [80, 183], [183, 191], [185, 40], [40, 186], [186, 185],\n  [119, 230], [230, 118], [118, 119], [210, 202], [202, 214], [214, 210],\n  [84, 83], [83, 17], [17, 84], [77, 76], [76, 146], [146, 77],\n  [161, 160], [160, 30], [30, 161], [190, 56], [56, 173], [173, 190],\n  [182, 106], [106, 194], [194, 182], [138, 135], [135, 192], [192, 138],\n  [129, 203], [203, 98], [98, 129], [54, 21], [21, 68], [68, 54],\n  [5, 51], [51, 4], [4, 5], [145, 144], [144, 23], [23, 145],\n  [90, 77], [77, 91], [91, 90], [207, 205], [205, 187], [187, 207],\n  [83, 201], [201, 18], [18, 83], [181, 91], [91, 182], [182, 181],\n  [180, 90], [90, 181], [181, 180], [16, 85], [85, 17], [17, 16],\n  [205, 206], [206, 36], [36, 205], [176, 148], [148, 140], [140, 176],\n  [165, 92], [92, 39], [39, 165], [245, 193], [193, 244], [244, 245],\n  [27, 159], [159, 28], [28, 27], [30, 247], [247, 161], [161, 30],\n  [174, 236], [236, 196], [196, 174], [103, 54], [54, 104], [104, 103],\n  [55, 193], [193, 8], [8, 55], [111, 117], [117, 31], [31, 111],\n  [221, 189], [189, 55], [55, 221], [240, 98], [98, 99], [99, 240],\n  [142, 126], [126, 100], [100, 142], [219, 166], [166, 218], [218, 219],\n  [112, 155], [155, 26], [26, 112], [198, 209], [209, 131], [131, 198],\n  [169, 135], [135, 150], [150, 169], [114, 47], [47, 217], [217, 114],\n  [224, 223], [223, 53], [53, 224], [220, 45], [45, 134], [134, 220],\n  [32, 211], [211, 140], [140, 32], [109, 67], [67, 108], [108, 109],\n  [146, 43], [43, 91], [91, 146], [231, 230], [230, 120], [120, 231],\n  [113, 226], [226, 247], [247, 113], [105, 63], [63, 52], [52, 105],\n  [241, 238], [238, 242], [242, 241], [124, 46], [46, 156], [156, 124],\n  [95, 78], [78, 96], [96, 95], [70, 46], [46, 63], [63, 70],\n  [116, 143], [143, 227], [227, 116], [116, 123], [123, 111], [111, 116],\n  [1, 44], [44, 19], [19, 1], [3, 236], [236, 51], [51, 3],\n  [207, 216], [216, 205], [205, 207], [26, 154], [154, 22], [22, 26],\n  [165, 39], [39, 167], [167, 165], [199, 200], [200, 208], [208, 199],\n  [101, 36], [36, 100], [100, 101], [43, 57], [57, 202], [202, 43],\n  [242, 20], [20, 99], [99, 242], [56, 28], [28, 157], [157, 56],\n  [124, 35], [35, 113], [113, 124], [29, 160], [160, 27], [27, 29],\n  [211, 204], [204, 210], [210, 211], [124, 113], [113, 46], [46, 124],\n  [106, 43], [43, 204], [204, 106], [96, 62], [62, 77], [77, 96],\n  [227, 137], [137, 116], [116, 227], [73, 41], [41, 72], [72, 73],\n  [36, 203], [203, 142], [142, 36], [235, 64], [64, 240], [240, 235],\n  [48, 49], [49, 64], [64, 48], [42, 41], [41, 74], [74, 42],\n  [214, 212], [212, 207], [207, 214], [183, 42], [42, 184], [184, 183],\n  [210, 169], [169, 211], [211, 210], [140, 170], [170, 176], [176, 140],\n  [104, 105], [105, 69], [69, 104], [193, 122], [122, 168], [168, 193],\n  [50, 123], [123, 187], [187, 50], [89, 96], [96, 90], [90, 89],\n  [66, 65], [65, 107], [107, 66], [179, 89], [89, 180], [180, 179],\n  [119, 101], [101, 120], [120, 119], [68, 63], [63, 104], [104, 68],\n  [234, 93], [93, 227], [227, 234], [16, 15], [15, 85], [85, 16],\n  [209, 129], [129, 49], [49, 209], [15, 14], [14, 86], [86, 15],\n  [107, 55], [55, 9], [9, 107], [120, 100], [100, 121], [121, 120],\n  [153, 145], [145, 22], [22, 153], [178, 88], [88, 179], [179, 178],\n  [197, 6], [6, 196], [196, 197], [89, 88], [88, 96], [96, 89],\n  [135, 138], [138, 136], [136, 135], [138, 215], [215, 172], [172, 138],\n  [218, 115], [115, 219], [219, 218], [41, 42], [42, 81], [81, 41],\n  [5, 195], [195, 51], [51, 5], [57, 43], [43, 61], [61, 57],\n  [208, 171], [171, 199], [199, 208], [41, 81], [81, 38], [38, 41],\n  [224, 53], [53, 225], [225, 224], [24, 144], [144, 110], [110, 24],\n  [105, 52], [52, 66], [66, 105], [118, 229], [229, 117], [117, 118],\n  [227, 34], [34, 234], [234, 227], [66, 107], [107, 69], [69, 66],\n  [10, 109], [109, 151], [151, 10], [219, 48], [48, 235], [235, 219],\n  [183, 62], [62, 191], [191, 183], [142, 129], [129, 126], [126, 142],\n  [116, 111], [111, 143], [143, 116], [118, 117], [117, 50], [50, 118],\n  [223, 222], [222, 52], [52, 223], [94, 19], [19, 141], [141, 94],\n  [222, 221], [221, 65], [65, 222], [196, 3], [3, 197], [197, 196],\n  [45, 220], [220, 44], [44, 45], [156, 70], [70, 139], [139, 156],\n  [188, 122], [122, 245], [245, 188], [139, 71], [71, 162], [162, 139],\n  [149, 170], [170, 150], [150, 149], [122, 188], [188, 196], [196, 122],\n  [206, 216], [216, 92], [92, 206], [164, 2], [2, 167], [167, 164],\n  [242, 141], [141, 241], [241, 242], [0, 164], [164, 37], [37, 0],\n  [11, 72], [72, 12], [12, 11], [12, 38], [38, 13], [13, 12],\n  [70, 63], [63, 71], [71, 70], [31, 226], [226, 111], [111, 31],\n  [36, 101], [101, 205], [205, 36], [203, 206], [206, 165], [165, 203],\n  [126, 209], [209, 217], [217, 126], [98, 165], [165, 97], [97, 98],\n  [237, 220], [220, 218], [218, 237], [237, 239], [239, 241], [241, 237],\n  [210, 214], [214, 169], [169, 210], [140, 171], [171, 32], [32, 140],\n  [241, 125], [125, 237], [237, 241], [179, 86], [86, 178], [178, 179],\n  [180, 85], [85, 179], [179, 180], [181, 84], [84, 180], [180, 181],\n  [182, 83], [83, 181], [181, 182], [194, 201], [201, 182], [182, 194],\n  [177, 137], [137, 132], [132, 177], [184, 76], [76, 183], [183, 184],\n  [185, 61], [61, 184], [184, 185], [186, 57], [57, 185], [185, 186],\n  [216, 212], [212, 186], [186, 216], [192, 214], [214, 187], [187, 192],\n  [139, 34], [34, 156], [156, 139], [218, 79], [79, 237], [237, 218],\n  [147, 123], [123, 177], [177, 147], [45, 44], [44, 4], [4, 45],\n  [208, 201], [201, 32], [32, 208], [98, 64], [64, 129], [129, 98],\n  [192, 213], [213, 138], [138, 192], [235, 59], [59, 219], [219, 235],\n  [141, 242], [242, 97], [97, 141], [97, 2], [2, 141], [141, 97],\n  [240, 75], [75, 235], [235, 240], [229, 24], [24, 228], [228, 229],\n  [31, 25], [25, 226], [226, 31], [230, 23], [23, 229], [229, 230],\n  [231, 22], [22, 230], [230, 231], [232, 26], [26, 231], [231, 232],\n  [233, 112], [112, 232], [232, 233], [244, 189], [189, 243], [243, 244],\n  [189, 221], [221, 190], [190, 189], [222, 28], [28, 221], [221, 222],\n  [223, 27], [27, 222], [222, 223], [224, 29], [29, 223], [223, 224],\n  [225, 30], [30, 224], [224, 225], [113, 247], [247, 225], [225, 113],\n  [99, 60], [60, 240], [240, 99], [213, 147], [147, 215], [215, 213],\n  [60, 20], [20, 166], [166, 60], [192, 187], [187, 213], [213, 192],\n  [243, 112], [112, 244], [244, 243], [244, 233], [233, 245], [245, 244],\n  [245, 128], [128, 188], [188, 245], [188, 114], [114, 174], [174, 188],\n  [134, 131], [131, 220], [220, 134], [174, 217], [217, 236], [236, 174],\n  [236, 198], [198, 134], [134, 236], [215, 177], [177, 58], [58, 215],\n  [156, 143], [143, 124], [124, 156], [25, 110], [110, 7], [7, 25],\n  [31, 228], [228, 25], [25, 31], [264, 356], [356, 368], [368, 264],\n  [0, 11], [11, 267], [267, 0], [451, 452], [452, 349], [349, 451],\n  [267, 302], [302, 269], [269, 267], [350, 357], [357, 277], [277, 350],\n  [350, 452], [452, 357], [357, 350], [299, 333], [333, 297], [297, 299],\n  [396, 175], [175, 377], [377, 396], [280, 347], [347, 330], [330, 280],\n  [269, 303], [303, 270], [270, 269], [151, 9], [9, 337], [337, 151],\n  [344, 278], [278, 360], [360, 344], [424, 418], [418, 431], [431, 424],\n  [270, 304], [304, 409], [409, 270], [272, 310], [310, 407], [407, 272],\n  [322, 270], [270, 410], [410, 322], [449, 450], [450, 347], [347, 449],\n  [432, 422], [422, 434], [434, 432], [18, 313], [313, 17], [17, 18],\n  [291, 306], [306, 375], [375, 291], [259, 387], [387, 260], [260, 259],\n  [424, 335], [335, 418], [418, 424], [434, 364], [364, 416], [416, 434],\n  [391, 423], [423, 327], [327, 391], [301, 251], [251, 298], [298, 301],\n  [275, 281], [281, 4], [4, 275], [254, 373], [373, 253], [253, 254],\n  [375, 307], [307, 321], [321, 375], [280, 425], [425, 411], [411, 280],\n  [200, 421], [421, 18], [18, 200], [335, 321], [321, 406], [406, 335],\n  [321, 320], [320, 405], [405, 321], [314, 315], [315, 17], [17, 314],\n  [423, 426], [426, 266], [266, 423], [396, 377], [377, 369], [369, 396],\n  [270, 322], [322, 269], [269, 270], [413, 417], [417, 464], [464, 413],\n  [385, 386], [386, 258], [258, 385], [248, 456], [456, 419], [419, 248],\n  [298, 284], [284, 333], [333, 298], [168, 417], [417, 8], [8, 168],\n  [448, 346], [346, 261], [261, 448], [417, 413], [413, 285], [285, 417],\n  [326, 327], [327, 328], [328, 326], [277, 355], [355, 329], [329, 277],\n  [309, 392], [392, 438], [438, 309], [381, 382], [382, 256], [256, 381],\n  [279, 429], [429, 360], [360, 279], [365, 364], [364, 379], [379, 365],\n  [355, 277], [277, 437], [437, 355], [282, 443], [443, 283], [283, 282],\n  [281, 275], [275, 363], [363, 281], [395, 431], [431, 369], [369, 395],\n  [299, 297], [297, 337], [337, 299], [335, 273], [273, 321], [321, 335],\n  [348, 450], [450, 349], [349, 348], [359, 446], [446, 467], [467, 359],\n  [283, 293], [293, 282], [282, 283], [250, 458], [458, 462], [462, 250],\n  [300, 276], [276, 383], [383, 300], [292, 308], [308, 325], [325, 292],\n  [283, 276], [276, 293], [293, 283], [264, 372], [372, 447], [447, 264],\n  [346, 352], [352, 340], [340, 346], [354, 274], [274, 19], [19, 354],\n  [363, 456], [456, 281], [281, 363], [426, 436], [436, 425], [425, 426],\n  [380, 381], [381, 252], [252, 380], [267, 269], [269, 393], [393, 267],\n  [421, 200], [200, 428], [428, 421], [371, 266], [266, 329], [329, 371],\n  [432, 287], [287, 422], [422, 432], [290, 250], [250, 328], [328, 290],\n  [385, 258], [258, 384], [384, 385], [446, 265], [265, 342], [342, 446],\n  [386, 387], [387, 257], [257, 386], [422, 424], [424, 430], [430, 422],\n  [445, 342], [342, 276], [276, 445], [422, 273], [273, 424], [424, 422],\n  [306, 292], [292, 307], [307, 306], [352, 366], [366, 345], [345, 352],\n  [268, 271], [271, 302], [302, 268], [358, 423], [423, 371], [371, 358],\n  [327, 294], [294, 460], [460, 327], [331, 279], [279, 294], [294, 331],\n  [303, 271], [271, 304], [304, 303], [436, 432], [432, 427], [427, 436],\n  [304, 272], [272, 408], [408, 304], [395, 394], [394, 431], [431, 395],\n  [378, 395], [395, 400], [400, 378], [296, 334], [334, 299], [299, 296],\n  [6, 351], [351, 168], [168, 6], [376, 352], [352, 411], [411, 376],\n  [307, 325], [325, 320], [320, 307], [285, 295], [295, 336], [336, 285],\n  [320, 319], [319, 404], [404, 320], [329, 330], [330, 349], [349, 329],\n  [334, 293], [293, 333], [333, 334], [366, 323], [323, 447], [447, 366],\n  [316, 15], [15, 315], [315, 316], [331, 358], [358, 279], [279, 331],\n  [317, 14], [14, 316], [316, 317], [8, 285], [285, 9], [9, 8],\n  [277, 329], [329, 350], [350, 277], [253, 374], [374, 252], [252, 253],\n  [319, 318], [318, 403], [403, 319], [351, 6], [6, 419], [419, 351],\n  [324, 318], [318, 325], [325, 324], [397, 367], [367, 365], [365, 397],\n  [288, 435], [435, 397], [397, 288], [278, 344], [344, 439], [439, 278],\n  [310, 272], [272, 311], [311, 310], [248, 195], [195, 281], [281, 248],\n  [375, 273], [273, 291], [291, 375], [175, 396], [396, 199], [199, 175],\n  [312, 311], [311, 268], [268, 312], [276, 283], [283, 445], [445, 276],\n  [390, 373], [373, 339], [339, 390], [295, 282], [282, 296], [296, 295],\n  [448, 449], [449, 346], [346, 448], [356, 264], [264, 454], [454, 356],\n  [337, 336], [336, 299], [299, 337], [337, 338], [338, 151], [151, 337],\n  [294, 278], [278, 455], [455, 294], [308, 292], [292, 415], [415, 308],\n  [429, 358], [358, 355], [355, 429], [265, 340], [340, 372], [372, 265],\n  [352, 346], [346, 280], [280, 352], [295, 442], [442, 282], [282, 295],\n  [354, 19], [19, 370], [370, 354], [285, 441], [441, 295], [295, 285],\n  [195, 248], [248, 197], [197, 195], [457, 440], [440, 274], [274, 457],\n  [301, 300], [300, 368], [368, 301], [417, 351], [351, 465], [465, 417],\n  [251, 301], [301, 389], [389, 251], [394, 395], [395, 379], [379, 394],\n  [399, 412], [412, 419], [419, 399], [410, 436], [436, 322], [322, 410],\n  [326, 2], [2, 393], [393, 326], [354, 370], [370, 461], [461, 354],\n  [393, 164], [164, 267], [267, 393], [268, 302], [302, 12], [12, 268],\n  [312, 268], [268, 13], [13, 312], [298, 293], [293, 301], [301, 298],\n  [265, 446], [446, 340], [340, 265], [280, 330], [330, 425], [425, 280],\n  [322, 426], [426, 391], [391, 322], [420, 429], [429, 437], [437, 420],\n  [393, 391], [391, 326], [326, 393], [344, 440], [440, 438], [438, 344],\n  [458, 459], [459, 461], [461, 458], [364, 434], [434, 394], [394, 364],\n  [428, 396], [396, 262], [262, 428], [274, 354], [354, 457], [457, 274],\n  [317, 316], [316, 402], [402, 317], [316, 315], [315, 403], [403, 316],\n  [315, 314], [314, 404], [404, 315], [314, 313], [313, 405], [405, 314],\n  [313, 421], [421, 406], [406, 313], [323, 366], [366, 361], [361, 323],\n  [292, 306], [306, 407], [407, 292], [306, 291], [291, 408], [408, 306],\n  [291, 287], [287, 409], [409, 291], [287, 432], [432, 410], [410, 287],\n  [427, 434], [434, 411], [411, 427], [372, 264], [264, 383], [383, 372],\n  [459, 309], [309, 457], [457, 459], [366, 352], [352, 401], [401, 366],\n  [1, 274], [274, 4], [4, 1], [418, 421], [421, 262], [262, 418],\n  [331, 294], [294, 358], [358, 331], [435, 433], [433, 367], [367, 435],\n  [392, 289], [289, 439], [439, 392], [328, 462], [462, 326], [326, 328],\n  [94, 2], [2, 370], [370, 94], [289, 305], [305, 455], [455, 289],\n  [339, 254], [254, 448], [448, 339], [359, 255], [255, 446], [446, 359],\n  [254, 253], [253, 449], [449, 254], [253, 252], [252, 450], [450, 253],\n  [252, 256], [256, 451], [451, 252], [256, 341], [341, 452], [452, 256],\n  [414, 413], [413, 463], [463, 414], [286, 441], [441, 414], [414, 286],\n  [286, 258], [258, 441], [441, 286], [258, 257], [257, 442], [442, 258],\n  [257, 259], [259, 443], [443, 257], [259, 260], [260, 444], [444, 259],\n  [260, 467], [467, 445], [445, 260], [309, 459], [459, 250], [250, 309],\n  [305, 289], [289, 290], [290, 305], [305, 290], [290, 460], [460, 305],\n  [401, 376], [376, 435], [435, 401], [309, 250], [250, 392], [392, 309],\n  [376, 411], [411, 433], [433, 376], [453, 341], [341, 464], [464, 453],\n  [357, 453], [453, 465], [465, 357], [343, 357], [357, 412], [412, 343],\n  [437, 343], [343, 399], [399, 437], [344, 360], [360, 440], [440, 344],\n  [420, 437], [437, 456], [456, 420], [360, 420], [420, 363], [363, 360],\n  [361, 401], [401, 288], [288, 361], [265, 372], [372, 353], [353, 265],\n  [390, 339], [339, 249], [249, 390], [339, 448], [448, 255], [255, 339],\n];\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n * See `facemesh.ts` for entry point\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as coords from './facemeshcoords';\nimport { constants } from '../tfjs/constants';\nimport type { Box, Point } from '../result';\nimport { env } from '../util/env';\n\nexport const createBox = (startEndTensor) => ({ startPoint: tf.slice(startEndTensor, [0, 0], [-1, 2]), endPoint: tf.slice(startEndTensor, [0, 2], [-1, 2]) });\n\nexport const disposeBox = (t) => tf.dispose([t.startPoint, t.endPoint]);\n\nexport const getBoxSize = (box): [number, number] => [Math.abs(box.endPoint[0] - box.startPoint[0]), Math.abs(box.endPoint[1] - box.startPoint[1])];\n\nexport const getBoxCenter = (box): [number, number, number] => [box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2, box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2, 1];\n\nexport const clampBox = (box, input): Box => (box ? [\n  Math.trunc(Math.max(0, box.startPoint[0])),\n  Math.trunc(Math.max(0, box.startPoint[1])),\n  Math.trunc(Math.min((input.shape[2] || 0), box.endPoint[0]) - Math.max(0, box.startPoint[0])),\n  Math.trunc(Math.min((input.shape[1] || 0), box.endPoint[1]) - Math.max(0, box.startPoint[1])),\n] : [0, 0, 0, 0]);\n\nexport const getRawBox = (box, input): Box => (box ? [\n  box.startPoint[0] / (input.shape[2] || 0),\n  box.startPoint[1] / (input.shape[1] || 0),\n  (box.endPoint[0] - box.startPoint[0]) / (input.shape[2] || 0),\n  (box.endPoint[1] - box.startPoint[1]) / (input.shape[1] || 0),\n] : [0, 0, 0, 0]);\n\nexport const scaleBoxCoordinates = (box, factor) => {\n  const startPoint: Point = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]];\n  const endPoint: Point = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]];\n  return { startPoint, endPoint, landmarks: box.landmarks, confidence: box.confidence };\n};\n\nexport const cutAndResize = (box, image, cropSize) => {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const cutBox = [box.startPoint[1] / h, box.startPoint[0] / w, box.endPoint[1] / h, box.endPoint[0] / w];\n  const crop = tf.image.cropAndResize(image, [cutBox], [0], cropSize);\n  const norm = tf.div(crop, constants.tf255);\n  tf.dispose(crop);\n  return norm;\n};\n\nexport const enlargeBox = (box, factor) => {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const halfSize: [number, number] = [factor * size[0] / 2, factor * size[1] / 2];\n  return { startPoint: [center[0] - halfSize[0], center[1] - halfSize[1]] as Point, endPoint: [center[0] + halfSize[0], center[1] + halfSize[1]] as Point, landmarks: box.landmarks, confidence: box.confidence };\n};\n\nexport const squarifyBox = (box) => {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const halfSize = Math.max(...size) / 2;\n  return { startPoint: [Math.round(centers[0] - halfSize), Math.round(centers[1] - halfSize)] as Point, endPoint: [Math.round(centers[0] + halfSize), Math.round(centers[1] + halfSize)] as Point, landmarks: box.landmarks, confidence: box.confidence };\n};\n\nexport const calculateLandmarksBoundingBox = (landmarks) => {\n  const x = landmarks.map((d) => d[0]);\n  const y = landmarks.map((d) => d[1]);\n  return { startPoint: [Math.min(...x), Math.min(...y)] as Point, endPoint: [Math.max(...x), Math.max(...y)] as Point, landmarks };\n};\n\nexport const fixedRotationMatrix = [[1, 0, 0], [0, 1, 0], [0, 0, 1]];\n\nexport const normalizeRadians = (angle) => angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n\nexport const computeRotation = (point1, point2) => normalizeRadians(Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]));\n\nexport const radToDegrees = (rad) => rad * 180 / Math.PI;\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport const dot = (v1: number[], v2: number[]) => {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) product += v1[i] * v2[i];\n  return product;\n};\n\nexport const getColumnFrom2DArr = (arr, columnIndex) => {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) column.push(arr[i][columnIndex]);\n  return column;\n};\n\nexport const multiplyTransformMatrices = (mat1, mat2) => {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n  }\n  return product;\n};\n\nexport const buildRotationMatrix = (rotation, center) => {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n};\n\nexport const invertTransformMatrix = (matrix) => {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [-dot(rotationComponent[0], translationComponent), -dot(rotationComponent[1], translationComponent)];\n  return [rotationComponent[0].concat(invertedTranslation[0]), rotationComponent[1].concat(invertedTranslation[1]), [0, 0, 1]];\n};\n\nexport const rotatePoint = (homogeneousCoordinate, rotationMatrix) => [dot(homogeneousCoordinate, rotationMatrix[0]), dot(homogeneousCoordinate, rotationMatrix[1])];\n\nexport const xyDistanceBetweenPoints = (a, b) => Math.sqrt(((a[0] - b[0]) ** 2) + ((a[1] - b[1]) ** 2));\n\nexport function generateAnchors(inputSize) {\n  const spec = inputSize === 192\n    ? { strides: [4], anchors: [1] } // facemesh-detector\n    : { strides: [inputSize / 16, inputSize / 8], anchors: [2, 6] }; // blazeface\n  const anchors: Array<[number, number]> = [];\n  for (let i = 0; i < spec.strides.length; i++) {\n    const stride = spec.strides[i];\n    const gridRows = Math.floor((inputSize + stride - 1) / stride);\n    const gridCols = Math.floor((inputSize + stride - 1) / stride);\n    const anchorsNum = spec.anchors[i];\n    for (let gridY = 0; gridY < gridRows; gridY++) {\n      const anchorY = stride * (gridY + 0.5);\n      for (let gridX = 0; gridX < gridCols; gridX++) {\n        const anchorX = stride * (gridX + 0.5);\n        for (let n = 0; n < anchorsNum; n++) anchors.push([anchorX, anchorY]);\n      }\n    }\n  }\n  return anchors;\n}\n\nexport function transformRawCoords(coordsRaw, box, angle, rotationMatrix, inputSize) {\n  const boxSize = getBoxSize(box);\n  const coordsScaled = coordsRaw.map((coord) => ([ // scaled around zero-point\n    (boxSize[0] / inputSize) * (coord[0] - (inputSize / 2)),\n    (boxSize[1] / inputSize) * (coord[1] - (inputSize / 2)),\n    (coord[2] || 0),\n  ]));\n  const largeAngle = angle && (angle !== 0) && (Math.abs(angle) > 0.2);\n  const coordsRotationMatrix = largeAngle ? buildRotationMatrix(angle, [0, 0]) : fixedRotationMatrix;\n  const coordsRotated = largeAngle ? coordsScaled.map((coord) => ([...rotatePoint(coord, coordsRotationMatrix), coord[2]])) : coordsScaled;\n  const inverseRotationMatrix = largeAngle ? invertTransformMatrix(rotationMatrix) : fixedRotationMatrix;\n  const boxCenter = getBoxCenter(box);\n  const offsets = [dot(boxCenter, inverseRotationMatrix[0]), dot(boxCenter, inverseRotationMatrix[1])];\n  return coordsRotated.map((coord) => ([\n    Math.trunc(coord[0] + offsets[0]),\n    Math.trunc(coord[1] + offsets[1]),\n    Math.trunc(coord[2] || 0),\n  ]));\n}\n\nexport function correctFaceRotation(rotate, box, input, inputSize) {\n  const symmetryLine = (box.landmarks.length >= coords.meshLandmarks.count)\n    ? coords.meshLandmarks.symmetryLine\n    : coords.blazeFaceLandmarks.symmetryLine;\n  let angle = 0; // default\n  let rotationMatrix = fixedRotationMatrix; // default\n  let face; // default\n\n  if (rotate && env.kernels.includes('rotatewithoffset')) { // rotateWithOffset is not defined for tfjs-node\n    angle = computeRotation(box.landmarks[symmetryLine[0]], box.landmarks[symmetryLine[1]]);\n    const largeAngle = angle && (angle !== 0) && (Math.abs(angle) > 0.2);\n    if (largeAngle) { // perform rotation only if angle is sufficiently high\n      const center: Point = getBoxCenter(box);\n      const centerRaw: Point = [center[0] / input.shape[2], center[1] / input.shape[1]];\n      const rotated = tf.image.rotateWithOffset(input, angle, 0, centerRaw);\n      rotationMatrix = buildRotationMatrix(-angle, center);\n      face = cutAndResize(box, rotated, [inputSize, inputSize]);\n      tf.dispose(rotated);\n    } else {\n      face = cutAndResize(box, input, [inputSize, inputSize]);\n    }\n  } else {\n    face = cutAndResize(box, input, [inputSize, inputSize]);\n  }\n  return [angle, rotationMatrix, face];\n}\n\nexport const findFaceCenter = (mesh) => {\n  const x = mesh.map((m) => m[0]);\n  const y = mesh.map((m) => m[1]);\n  // weighted center\n  /*\n  const sum = (arr: number[]) => arr.reduce((prev, curr) => prev + curr, 0);\n  return [sum(x) / mesh.length, sum(y) / mesh.length];\n  */\n  // absolute center\n  return [Math.min(...x) + (Math.max(...x) - Math.min(...x)) / 2, Math.min(...y) + (Math.max(...y) - Math.min(...y)) / 2];\n};\n\nexport const calculateFaceBox = (mesh, previousBox) => {\n  const center = findFaceCenter(mesh);\n  const boxSize = getBoxSize(previousBox);\n  const calculatedBox = {\n    startPoint: [center[0] - boxSize[0] / 2, center[1] - boxSize[1] / 2] as Point,\n    endPoint: [center[0] + boxSize[0] / 2, center[1] + boxSize[1] / 2] as Point,\n  };\n  return calculatedBox;\n};\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n * See `facemesh.ts` for entry point\n */\n\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as util from './facemeshutil';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport type { Config } from '../config';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport { env } from '../util/env';\nimport type { Point } from '../result';\n\nconst keypointsCount = 6;\nconst faceBoxScaleFactor = 1.4;\nlet model: GraphModel | null;\nlet anchors: Tensor | null = null;\nlet inputSize = 0;\nlet inputSizeT: Tensor | null = null;\n\ntype DetectBox = { startPoint: Point, endPoint: Point, landmarks: Array<Point>, confidence: number };\n\nexport const size = () => inputSize;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.detector?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  inputSizeT = tf.scalar(inputSize, 'int32') as Tensor;\n  anchors = tf.tensor2d(util.generateAnchors(inputSize)) as Tensor;\n  return model;\n}\n\nfunction decodeBoxes(boxOutputs: Tensor) {\n  const t: Record<string, Tensor> = {};\n  t.boxStarts = tf.slice(boxOutputs, [0, 1], [-1, 2]);\n  t.centers = tf.add(t.boxStarts, anchors);\n  t.boxSizes = tf.slice(boxOutputs, [0, 3], [-1, 2]);\n  t.boxSizesNormalized = tf.div(t.boxSizes, inputSizeT);\n  t.centersNormalized = tf.div(t.centers, inputSizeT);\n  t.halfBoxSize = tf.div(t.boxSizesNormalized, constants.tf2);\n  t.starts = tf.sub(t.centersNormalized, t.halfBoxSize);\n  t.ends = tf.add(t.centersNormalized, t.halfBoxSize);\n  t.startNormalized = tf.mul(t.starts, inputSizeT);\n  t.endNormalized = tf.mul(t.ends, inputSizeT);\n  const boxes = tf.concat2d([t.startNormalized, t.endNormalized], 1);\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return boxes;\n}\n\nexport async function getBoxes(inputImage: Tensor, config: Config) {\n  // sanity check on input\n  if ((!inputImage) || (inputImage['isDisposedInternal']) || (inputImage.shape.length !== 4) || (inputImage.shape[1] < 1) || (inputImage.shape[2] < 1)) return [];\n  const t: Record<string, Tensor> = {};\n  t.resized = tf.image.resizeBilinear(inputImage, [inputSize, inputSize]);\n  t.div = tf.div(t.resized, constants.tf127);\n  t.normalized = tf.sub(t.div, constants.tf05);\n  const res = model?.execute(t.normalized) as Tensor[];\n  if (Array.isArray(res) && res.length > 2) { // pinto converted model?\n    const sorted = res.sort((a, b) => a.size - b.size);\n    t.concat384 = tf.concat([sorted[0], sorted[2]], 2); // dim: 384, 1 + 16\n    t.concat512 = tf.concat([sorted[1], sorted[3]], 2); // dim: 512, 1 + 16\n    t.concat = tf.concat([t.concat512, t.concat384], 1);\n    t.batch = tf.squeeze(t.concat, 0);\n  } else if (Array.isArray(res)) { // new facemesh-detection tfhub model\n    t.batch = tf.squeeze(res[0]);\n  } else { // original blazeface tfhub model\n    t.batch = tf.squeeze(res);\n  }\n  tf.dispose(res);\n  t.boxes = decodeBoxes(t.batch);\n  t.logits = tf.slice(t.batch, [0, 0], [-1, 1]);\n  t.sigmoid = tf.sigmoid(t.logits);\n  t.scores = tf.squeeze(t.sigmoid);\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.scores, (config.face.detector?.maxDetected || 0), (config.face.detector?.iouThreshold || 0), (config.face.detector?.minConfidence || 0));\n  const nms = await t.nms.array() as number[];\n  const boxes: Array<DetectBox> = [];\n  const scores = await t.scores.data();\n  for (let i = 0; i < nms.length; i++) {\n    const confidence = scores[nms[i]];\n    if (confidence > (config.face.detector?.minConfidence || 0)) {\n      const b: Record<string, Tensor> = {};\n      b.bbox = tf.slice(t.boxes, [nms[i], 0], [1, -1]);\n      b.slice = tf.slice(t.batch, [nms[i], keypointsCount - 1], [1, -1]);\n      b.squeeze = tf.squeeze(b.slice);\n      b.landmarks = tf.reshape(b.squeeze, [keypointsCount, -1]);\n      const points = await b.bbox.data();\n      const rawBox = {\n        startPoint: [points[0], points[1]] as Point,\n        endPoint: [points[2], points[3]] as Point,\n        landmarks: (await b.landmarks.array()) as Point[],\n        confidence,\n      };\n      const scaledBox = util.scaleBoxCoordinates(rawBox, [(inputImage.shape[2] || 0) / inputSize, (inputImage.shape[1] || 0) / inputSize]);\n      const enlargedBox = util.enlargeBox(scaledBox, config.face['scale'] || faceBoxScaleFactor);\n      const squaredBox = util.squarifyBox(enlargedBox);\n      boxes.push(squaredBox);\n      Object.keys(b).forEach((tensor) => tf.dispose(b[tensor]));\n    }\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return boxes;\n}\n", "/* eslint-disable no-multi-spaces */\n\nexport const kpt: Array<string> = [\n  'nose',            //  0\n  'leftEyeInside',   //  1\n  'leftEye',         //  2\n  'leftEyeOutside',  //  3\n  'rightEyeInside',  //  4\n  'rightEye',        //  5\n  'rightEyeOutside', //  6\n  'leftEar',         //  7\n  'rightEar',        //  8\n  'leftMouth',       //  9\n  'rightMouth',      // 10\n  'leftShoulder',    // 11\n  'rightShoulder',   // 12\n  'leftElbow',       // 13\n  'rightElbow',      // 14\n  'leftWrist',       // 15\n  'rightWrist',      // 16\n  'leftPinky',       // 17\n  'rightPinky',      // 18\n  'leftIndex',       // 19\n  'rightIndex',      // 20\n  'leftThumb',       // 21\n  'rightThumb',      // 22\n  'leftHip',         // 23\n  'rightHip',        // 24\n  'leftKnee',        // 25\n  'rightKnee',       // 26\n  'leftAnkle',       // 27\n  'rightAnkle',      // 28\n  'leftHeel',        // 29\n  'rightHeel',       // 30\n  'leftFoot',        // 31\n  'rightFoot',       // 32\n  'bodyCenter',      // 33\n  'bodyTop',         // 34\n  'leftPalm',        // 35 // z-coord not ok\n  'leftHand',        // 36 // similar to wrist but z-coord not ok\n  'rightPalm',       // 37 // z-coord not ok\n  'rightHand',       // 38 // similar to wrist but z-coord not ok\n];\n\nexport const connected: Record<string, string[]> = {\n  shoulders: ['leftShoulder', 'rightShoulder'],\n  hips: ['rightHip', 'leftHip'],\n  mouth: ['leftMouth', 'rightMouth'],\n  leftLegUpper: ['leftHip', 'leftKnee'],\n  leftLegLower: ['leftKnee', 'leftAnkle'],\n  leftFoot: ['leftAnkle', 'leftHeel', 'leftFoot'],\n  leftTorso: ['leftShoulder', 'leftHip'],\n  leftArmUpper: ['leftShoulder', 'leftElbow'],\n  leftArmLower: ['leftElbow', 'leftWrist'],\n  leftHand: ['leftWrist', 'leftPalm'],\n  leftHandPinky: ['leftPalm', 'leftPinky'],\n  leftHandIndex: ['leftPalm', 'leftIndex'],\n  leftHandThumb: ['leftPalm', 'leftThumb'],\n  leftEyeOutline: ['leftEyeInside', 'leftEyeOutside'],\n  rightLegUpper: ['rightHip', 'rightKnee'],\n  rightLegLower: ['rightKnee', 'rightAnkle'],\n  rightFoot: ['rightAnkle', 'rightHeel', 'rightFoot'],\n  rightTorso: ['rightShoulder', 'rightHip'],\n  rightArmUpper: ['rightShoulder', 'rightElbow'],\n  rightArmLower: ['rightElbow', 'rightWrist'],\n  rightHand: ['rightWrist', 'rightPalm'],\n  rightHandPinky: ['rightPalm', 'rightPinky'],\n  rightHandIndex: ['rightPalm', 'rightIndex'],\n  rightHandThumb: ['rightPalm', 'rightThumb'],\n  rightEyeOutline: ['rightEyeInside', 'rightEyeOutside'],\n};\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from '../tfjs/types';\nimport type { Box } from '../result';\nimport type { Config } from '../config';\n\ninterface DetectedBox { box: Box, boxRaw: Box, score: number }\n\nconst inputSize = 224;\nlet anchorTensor: { x, y };\nconst numLayers = 5;\nconst strides = [8, 16, 32, 32, 32];\n\nexport async function createAnchors() {\n  const anchors: Array<{ x: number, y: number }> = [];\n  let layerId = 0;\n  while (layerId < numLayers) {\n    let anchorCount = 0;\n    let lastSameStrideLayer = layerId;\n    while (lastSameStrideLayer < strides.length && strides[lastSameStrideLayer] === strides[layerId]) {\n      anchorCount += 2;\n      lastSameStrideLayer++;\n    }\n    const stride = strides[layerId];\n    const featureMapHeight = Math.ceil(inputSize / stride);\n    const featureMapWidth = Math.ceil(inputSize / stride);\n    for (let y = 0; y < featureMapHeight; ++y) {\n      for (let x = 0; x < featureMapWidth; ++x) {\n        for (let anchorId = 0; anchorId < anchorCount; ++anchorId) {\n          anchors.push({ x: (x + 0.5) / featureMapWidth, y: (y + 0.5) / featureMapHeight });\n        }\n      }\n    }\n    layerId = lastSameStrideLayer;\n  }\n  anchorTensor = { x: tf.tensor1d(anchors.map((a) => a.x)), y: tf.tensor1d(anchors.map((a) => a.y)) };\n}\n\nconst cropFactor = [5.0, 5.0];\nfunction decodeBoxes(boxesTensor, anchor): Tensor {\n  return tf.tidy(() => {\n    const split = tf.split(boxesTensor, 12, 1); // first 4 are box data [x,y,w,h] and 4 are keypoints data [x,y] for total of 12\n    let xCenter = tf.squeeze(split[0]);\n    let yCenter = tf.squeeze(split[1]);\n    let width = tf.squeeze(split[2]);\n    let height = tf.squeeze(split[3]);\n    xCenter = tf.add(tf.div(xCenter, inputSize), anchor.x);\n    yCenter = tf.add(tf.div(yCenter, inputSize), anchor.y);\n    width = tf.mul(tf.div(width, inputSize), cropFactor[0]);\n    height = tf.mul(tf.div(height, inputSize), cropFactor[1]);\n    const xMin = tf.sub(xCenter, tf.div(width, 2));\n    const yMin = tf.sub(yCenter, tf.div(height, 2));\n    const boxes = tf.stack([xMin, yMin, width, height], 1);\n    return boxes;\n  });\n}\n\nexport async function decode(boxesTensor: Tensor, logitsTensor: Tensor, config: Config, outputSize: [number, number]): Promise<DetectedBox[]> {\n  const t: Record<string, Tensor> = {};\n  t.boxes = decodeBoxes(boxesTensor, anchorTensor);\n  t.scores = tf.sigmoid(logitsTensor);\n  t.argmax = tf.argMax(t.scores);\n  const i = (await t.argmax.data())[0] as number;\n  const scores = await t.scores.data();\n  const detected: Array<{ box: Box, boxRaw: Box, score: number }> = [];\n  const minScore = (config.body['detector'] && config.body['detector']['minConfidence']) ? config.body['detector']['minConfidence'] : 0;\n  if (scores[i] >= minScore) {\n    const boxes = await t.boxes.array();\n    const boxRaw: Box = boxes[i];\n    const box: Box = [boxRaw[0] * outputSize[0], boxRaw[1] * outputSize[1], boxRaw[2] * outputSize[0], boxRaw[3] * outputSize[1]];\n    // console.log(box);\n    detected.push({ box, boxRaw, score: scores[i] });\n  }\n  /*\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.scores, 1, config.body.detector?.minConfidence || 0.1, config.body.detector?.iouThreshold || 0.1);\n  const boxes = t.boxes.arraySync();\n  const scores = t.scores.dataSync();\n  const nms = t.nms.dataSync();\n  const detected: Array<DetectedBox> = [];\n  for (const i of Array.from(nms)) {\n    const boxRaw: Box = boxes[i];\n    const box: Box = [boxRaw[0] * outputSize[0], boxRaw[0] * outputSize[1], boxRaw[3] * outputSize[0], boxRaw[2] * outputSize[1]];\n    detected.push({ box, boxRaw, score: scores[i] });\n  }\n  */\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return detected;\n}\n", "import type { Point, Box } from '../result';\n\nexport function calc(keypoints: Array<Point>, outputSize: [number, number] = [1, 1]) {\n  const coords = [keypoints.map((pt) => pt[0]), keypoints.map((pt) => pt[1])]; // all x/y coords\n  const min = [Math.min(...coords[0]), Math.min(...coords[1])];\n  const max = [Math.max(...coords[0]), Math.max(...coords[1])];\n  const box: Box = [min[0], min[1], max[0] - min[0], max[1] - min[1]];\n  const boxRaw: Box = [box[0] / outputSize[0], box[1] / outputSize[1], box[2] / outputSize[0], box[3] / outputSize[1]];\n  return { box, boxRaw };\n}\n\nexport function square(keypoints: Array<Point>, outputSize: [number, number] = [1, 1]) {\n  const coords = [keypoints.map((pt) => pt[0]), keypoints.map((pt) => pt[1])]; // all x/y coords\n  const min = [Math.min(...coords[0]), Math.min(...coords[1])];\n  const max = [Math.max(...coords[0]), Math.max(...coords[1])];\n  const center = [(min[0] + max[0]) / 2, (min[1] + max[1]) / 2]; // find center x and y coord of all fingers\n  const dist = Math.max(center[0] - min[0], center[1] - min[1], -center[0] + max[0], -center[1] + max[1]); // largest distance from center in any direction\n  const box: Box = [Math.trunc(center[0] - dist), Math.trunc(center[1] - dist), Math.trunc(2 * dist), Math.trunc(2 * dist)];\n  const boxRaw: Box = [box[0] / outputSize[0], box[1] / outputSize[1], box[2] / outputSize[0], box[3] / outputSize[1]];\n  return { box, boxRaw };\n}\n\nexport function scale(box: Box, scaleFact: number) {\n  const dist = [box[2] * scaleFact, box[3] * scaleFact];\n  const newBox: Box = [\n    box[0] - (dist[0] - box[2]) / 2,\n    box[1] - (dist[1] - box[3]) / 2,\n    dist[0],\n    dist[1],\n  ];\n  return newBox;\n}\n\nexport function crop(box: Box) { // [y1, x1, y2, x2] clamped to 0..1\n  const yxBox: Box = [Math.max(0, box[1]), Math.max(0, box[0]), Math.min(1, box[3] + box[1]), Math.min(1, box[2] + box[0])];\n  return yxBox;\n}\n", "/**\n * BlazePose model implementation\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport { log, now } from '../util/util';\nimport type { BodyKeypoint, BodyResult, BodyLandmark, Box, Point, BodyAnnotation } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport * as coords from './blazeposecoords';\nimport * as detect from './blazeposedetector';\nimport * as box from '../util/box';\n\nconst env = { initial: true };\n// const models: [GraphModel | null, GraphModel | null] = [null, null];\nconst models: { detector: GraphModel | null, landmarks: GraphModel | null } = { detector: null, landmarks: null };\nconst inputSize: { detector: [number, number], landmarks: [number, number] } = { detector: [224, 224], landmarks: [256, 256] };\nlet skipped = Number.MAX_SAFE_INTEGER;\nconst outputNodes: { detector: string[], landmarks: string[] } = {\n  landmarks: ['ld_3d', 'activation_segmentation', 'activation_heatmap', 'world_3d', 'output_poseflag'],\n  detector: [],\n};\n\nlet cache: BodyResult | null = null;\nlet cropBox: Box | undefined;\nlet padding: [number, number][] = [[0, 0], [0, 0], [0, 0], [0, 0]];\nlet lastTime = 0;\n\nconst sigmoid = (x) => (1 - (1 / (1 + Math.exp(x))));\n\nexport async function loadDetect(config: Config): Promise<GraphModel> {\n  if (env.initial) models.detector = null;\n  if (!models.detector && config.body['detector'] && config.body['detector']['modelPath'] || '') {\n    models.detector = await loadModel(config.body['detector']['modelPath']);\n    const inputs = Object.values(models.detector.modelSignature['inputs']);\n    inputSize.detector[0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize.detector[1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug && models.detector) log('cached model:', models.detector['modelUrl']);\n  await detect.createAnchors();\n  return models.detector as GraphModel;\n}\n\nexport async function loadPose(config: Config): Promise<GraphModel> {\n  if (env.initial) models.landmarks = null;\n  if (!models.landmarks) {\n    models.landmarks = await loadModel(config.body.modelPath);\n    const inputs = Object.values(models.landmarks.modelSignature['inputs']);\n    inputSize.landmarks[0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize.landmarks[1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', models.landmarks['modelUrl']);\n  return models.landmarks;\n}\n\nexport async function load(config: Config): Promise<[GraphModel | null, GraphModel | null]> {\n  if (!models.detector) await loadDetect(config);\n  if (!models.landmarks) await loadPose(config);\n  return [models.detector, models.landmarks];\n}\n\nasync function prepareImage(input: Tensor, size: number): Promise<Tensor> {\n  const t: Record<string, Tensor> = {};\n  if (!input.shape || !input.shape[1] || !input.shape[2]) return input;\n  let final: Tensor;\n  if (cropBox) {\n    t.cropped = tf.image.cropAndResize(input, [cropBox], [0], [input.shape[1], input.shape[2]]); // if we have cached box use it to crop input\n  }\n  if (input.shape[1] !== input.shape[2]) { // only pad if width different than height\n    const height: [number, number] = [\n      input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0,\n      input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0,\n    ];\n    const width: [number, number] = [\n      input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0,\n      input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0,\n    ];\n    padding = [\n      [0, 0], // dont touch batch\n      height, // height before&after\n      width, // width before&after\n      [0, 0], // dont touch rbg\n    ];\n    t.pad = tf.pad(t.cropped || input, padding); // use cropped box if it exists\n    t.resize = tf.image.resizeBilinear(t.pad, [size, size]);\n    final = tf.div(t.resize, constants.tf255);\n  } else if (input.shape[1] !== size) { // if input needs resizing\n    t.resize = tf.image.resizeBilinear(t.cropped || input, [size, size]);\n    final = tf.div(t.resize, constants.tf255);\n  } else { // if input is already in a correct resolution just normalize it\n    final = tf.div(t.cropped || input, constants.tf255);\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return final;\n}\n\nfunction rescaleKeypoints(keypoints: Array<BodyKeypoint>, outputSize: [number, number]): Array<BodyKeypoint> {\n  for (const kpt of keypoints) { // first rescale due to padding\n    kpt.position = [\n      Math.trunc(kpt.position[0] * (outputSize[0] + padding[2][0] + padding[2][1]) / outputSize[0] - padding[2][0]),\n      Math.trunc(kpt.position[1] * (outputSize[1] + padding[1][0] + padding[1][1]) / outputSize[1] - padding[1][0]),\n      kpt.position[2] as number,\n    ];\n    kpt.positionRaw = [kpt.position[0] / outputSize[0], kpt.position[1] / outputSize[1], 2 * (kpt.position[2] as number) / (outputSize[0] + outputSize[1])];\n  }\n  if (cropBox) { // second rescale due to cropping\n    for (const kpt of keypoints) {\n      kpt.positionRaw = [\n        kpt.positionRaw[0] + cropBox[1], // correct offset due to crop\n        kpt.positionRaw[1] + cropBox[0], // correct offset due to crop\n        kpt.positionRaw[2] as number,\n      ];\n      kpt.position = [\n        Math.trunc(kpt.positionRaw[0] * outputSize[0]),\n        Math.trunc(kpt.positionRaw[1] * outputSize[1]),\n        kpt.positionRaw[2] as number,\n      ];\n    }\n  }\n  return keypoints;\n}\n\nasync function fixKeypoints(keypoints: Array<BodyKeypoint>) {\n  // palm z-coord is incorrect around near-zero so we approximate it\n  const leftPalm = keypoints.find((k) => k.part === 'leftPalm') as BodyKeypoint;\n  const leftWrist = keypoints.find((k) => k.part === 'leftWrist') as BodyKeypoint;\n  const leftIndex = keypoints.find((k) => k.part === 'leftIndex') as BodyKeypoint;\n  leftPalm.position[2] = ((leftWrist.position[2] || 0) + (leftIndex.position[2] || 0)) / 2;\n  const rightPalm = keypoints.find((k) => k.part === 'rightPalm') as BodyKeypoint;\n  const rightWrist = keypoints.find((k) => k.part === 'rightWrist') as BodyKeypoint;\n  const rightIndex = keypoints.find((k) => k.part === 'rightIndex') as BodyKeypoint;\n  rightPalm.position[2] = ((rightWrist.position[2] || 0) + (rightIndex.position[2] || 0)) / 2;\n}\n\nasync function detectLandmarks(input: Tensor, config: Config, outputSize: [number, number]): Promise<BodyResult | null> {\n  /**\n   * t.ld: 39 keypoints [x,y,z,score,presence] normalized to input size\n   * t.segmentation:\n   * t.heatmap:\n   * t.world: 39 keypoints [x,y,z] normalized to -1..1\n   * t.poseflag: body score\n  */\n  const t: Record<string, Tensor> = {};\n  [t.ld/* 1,195(39*5) */, t.segmentation/* 1,256,256,1 */, t.heatmap/* 1,64,64,39 */, t.world/* 1,117(39*3) */, t.poseflag/* 1,1 */] = models.landmarks?.execute(input, outputNodes.landmarks) as Tensor[]; // run model\n  const poseScore = (await t.poseflag.data())[0];\n  const points = await t.ld.data();\n  const distances = await t.world.data();\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor])); // dont need tensors after this\n  const keypointsRelative: Array<BodyKeypoint> = [];\n  const depth = 5; // each points has x,y,z,visibility,presence\n  for (let i = 0; i < points.length / depth; i++) {\n    const score = sigmoid(points[depth * i + 3]);\n    const presence = sigmoid(points[depth * i + 4]);\n    const adjScore = Math.trunc(100 * score * presence * poseScore) / 100;\n    const positionRaw: Point = [points[depth * i + 0] / inputSize.landmarks[0], points[depth * i + 1] / inputSize.landmarks[1], points[depth * i + 2] + 0];\n    const position: Point = [Math.trunc(outputSize[0] * positionRaw[0]), Math.trunc(outputSize[1] * positionRaw[1]), positionRaw[2] as number];\n    const distance: Point = [distances[depth * i + 0], distances[depth * i + 1], distances[depth * i + 2] + 0];\n    keypointsRelative.push({ part: coords.kpt[i] as BodyLandmark, positionRaw, position, distance, score: adjScore });\n  }\n  if (poseScore < (config.body.minConfidence || 0)) return null;\n  fixKeypoints(keypointsRelative);\n  const keypoints: Array<BodyKeypoint> = rescaleKeypoints(keypointsRelative, outputSize); // keypoints were relative to input image which is padded\n  const kpts = keypoints.map((k) => k.position);\n  const boxes = box.calc(kpts, [outputSize[0], outputSize[1]]); // now find boxes based on rescaled keypoints\n  const annotations: Record<BodyAnnotation, Point[][]> = {} as Record<BodyAnnotation, Point[][]>;\n  for (const [name, indexes] of Object.entries(coords.connected)) {\n    const pt: Array<Point[]> = [];\n    for (let i = 0; i < indexes.length - 1; i++) {\n      const pt0 = keypoints.find((kpt) => kpt.part === indexes[i]);\n      const pt1 = keypoints.find((kpt) => kpt.part === indexes[i + 1]);\n      if (pt0 && pt1) pt.push([pt0.position, pt1.position]);\n    }\n    annotations[name] = pt;\n  }\n  const body = { id: 0, score: Math.trunc(100 * poseScore) / 100, box: boxes.box, boxRaw: boxes.boxRaw, keypoints, annotations };\n  return body;\n}\n\n/*\ninterface DetectedBox { box: Box, boxRaw: Box, score: number }\n\nfunction rescaleBoxes(boxes: Array<DetectedBox>, outputSize: [number, number]): Array<DetectedBox> {\n  for (const b of boxes) {\n    b.box = [\n      Math.trunc(b.box[0] * (outputSize[0] + padding[2][0] + padding[2][1]) / outputSize[0]),\n      Math.trunc(b.box[1] * (outputSize[1] + padding[1][0] + padding[1][1]) / outputSize[1]),\n      Math.trunc(b.box[2] * (outputSize[0] + padding[2][0] + padding[2][1]) / outputSize[0]),\n      Math.trunc(b.box[3] * (outputSize[1] + padding[1][0] + padding[1][1]) / outputSize[1]),\n    ];\n    b.boxRaw = [b.box[0] / outputSize[0], b.box[1] / outputSize[1], b.box[2] / outputSize[0], b.box[3] / outputSize[1]];\n  }\n  return boxes;\n}\n\nasync function detectBoxes(input: Tensor, config: Config, outputSize: [number, number]) {\n  const t: Record<string, Tensor> = {};\n  t.res = models.detector?.execute(input, ['Identity']) as Tensor; //\n  t.logitsRaw = tf.slice(t.res, [0, 0, 0], [1, -1, 1]);\n  t.boxesRaw = tf.slice(t.res, [0, 0, 1], [1, -1, -1]);\n  t.logits = tf.squeeze(t.logitsRaw);\n  t.boxes = tf.squeeze(t.boxesRaw);\n  const boxes = await detect.decode(t.boxes, t.logits, config, outputSize);\n  rescaleBoxes(boxes, outputSize);\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return boxes;\n}\n*/\n\nexport async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {\n  const outputSize: [number, number] = [input.shape[2] || 0, input.shape[1] || 0];\n  const skipTime = (config.body.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.body.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && cache !== null) {\n    skipped++;\n  } else {\n    const t: Record<string, Tensor> = {};\n    /*\n    if (config.body['detector'] && config.body['detector']['enabled']) {\n      t.detector = await prepareImage(input, 224);\n      const boxes = await detectBoxes(t.detector, config, outputSize);\n    }\n    */\n    t.landmarks = await prepareImage(input, 256); // padded and resized\n    cache = await detectLandmarks(t.landmarks, config, outputSize);\n    /*\n    cropBox = [0, 0, 1, 1]; // reset crop coordinates\n    if (cache?.boxRaw && config.skipAllowed) {\n      const cx = (2.0 * cache.boxRaw[0] + cache.boxRaw[2]) / 2;\n      const cy = (2.0 * cache.boxRaw[1] + cache.boxRaw[3]) / 2;\n      let size = cache.boxRaw[2] > cache.boxRaw[3] ? cache.boxRaw[2] : cache.boxRaw[3];\n      size = (size * 1.0) / 2; // enlarge and half it\n      if (cx > 0.1 && cx < 0.9 && cy > 0.1 && cy < 0.9 && size > 0.1) { // only update if box is sane\n        const y = 0; // cy - size;\n        const x = cx - size;\n        cropBox = [y, x, y + 1, x + 1]; // [y0,x0,y1,x1] used for cropping but width/height are not yet implemented so we only reposition image to center of body\n      }\n    }\n    */\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    lastTime = now();\n    skipped = 0;\n  }\n  return cache ? [cache] : [];\n}\n", "/**\n * CoCo Labels used by object detection implementations\n */\nexport const labels = [\n  { class: 1, label: 'person' },\n  { class: 2, label: 'bicycle' },\n  { class: 3, label: 'car' },\n  { class: 4, label: 'motorcycle' },\n  { class: 5, label: 'airplane' },\n  { class: 6, label: 'bus' },\n  { class: 7, label: 'train' },\n  { class: 8, label: 'truck' },\n  { class: 9, label: 'boat' },\n  { class: 10, label: 'traffic light' },\n  { class: 11, label: 'fire hydrant' },\n  { class: 12, label: 'stop sign' },\n  { class: 13, label: 'parking meter' },\n  { class: 14, label: 'bench' },\n  { class: 15, label: 'bird' },\n  { class: 16, label: 'cat' },\n  { class: 17, label: 'dog' },\n  { class: 18, label: 'horse' },\n  { class: 19, label: 'sheep' },\n  { class: 20, label: 'cow' },\n  { class: 21, label: 'elephant' },\n  { class: 22, label: 'bear' },\n  { class: 23, label: 'zebra' },\n  { class: 24, label: 'giraffe' },\n  { class: 25, label: 'backpack' },\n  { class: 26, label: 'umbrella' },\n  { class: 27, label: 'handbag' },\n  { class: 28, label: 'tie' },\n  { class: 29, label: 'suitcase' },\n  { class: 30, label: 'frisbee' },\n  { class: 31, label: 'skis' },\n  { class: 32, label: 'snowboard' },\n  { class: 33, label: 'sports ball' },\n  { class: 34, label: 'kite' },\n  { class: 35, label: 'baseball bat' },\n  { class: 36, label: 'baseball glove' },\n  { class: 37, label: 'skateboard' },\n  { class: 38, label: 'surfboard' },\n  { class: 39, label: 'tennis racket' },\n  { class: 40, label: 'bottle' },\n  { class: 41, label: 'wine glass' },\n  { class: 42, label: 'cup' },\n  { class: 43, label: 'fork' },\n  { class: 44, label: 'knife' },\n  { class: 45, label: 'spoon' },\n  { class: 46, label: 'bowl' },\n  { class: 47, label: 'banana' },\n  { class: 48, label: 'apple' },\n  { class: 49, label: 'sandwich' },\n  { class: 50, label: 'orange' },\n  { class: 51, label: 'broccoli' },\n  { class: 52, label: 'carrot' },\n  { class: 53, label: 'hot dog' },\n  { class: 54, label: 'pizza' },\n  { class: 55, label: 'donut' },\n  { class: 56, label: 'cake' },\n  { class: 57, label: 'chair' },\n  { class: 58, label: 'couch' },\n  { class: 59, label: 'potted plant' },\n  { class: 60, label: 'bed' },\n  { class: 61, label: 'dining table' },\n  { class: 62, label: 'toilet' },\n  { class: 63, label: 'tv' },\n  { class: 64, label: 'laptop' },\n  { class: 65, label: 'mouse' },\n  { class: 66, label: 'remote' },\n  { class: 67, label: 'keyboard' },\n  { class: 68, label: 'cell phone' },\n  { class: 69, label: 'microwave' },\n  { class: 70, label: 'oven' },\n  { class: 71, label: 'toaster' },\n  { class: 72, label: 'sink' },\n  { class: 73, label: 'refrigerator' },\n  { class: 74, label: 'book' },\n  { class: 75, label: 'clock' },\n  { class: 76, label: 'vase' },\n  { class: 77, label: 'scissors' },\n  { class: 78, label: 'teddy bear' },\n  { class: 79, label: 'hair drier' },\n  { class: 80, label: 'toothbrush' },\n];\n", "/**\n * CenterNet object detection model implementation\n *\n * Based on: [**NanoDet**](https://github.com/RangiLyu/nanodet)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { labels } from './labels';\nimport type { ObjectResult, ObjectType, Box } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nlet inputSize = 0;\nlet last: ObjectResult[] = [];\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) {\n    // fakeOps(['floormod'], config);\n    model = await loadModel(config.object.modelPath);\n    const inputs = Object.values(model.modelSignature['inputs']);\n    inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nasync function process(res: Tensor | null, outputShape: [number, number], config: Config) {\n  if (!res) return [];\n  const t: Record<string, Tensor> = {};\n  const results: Array<ObjectResult> = [];\n  const detections = await res.array() as number[][][];\n  t.squeeze = tf.squeeze(res);\n  const arr = tf.split(t.squeeze, 6, 1) as Tensor[]; // x1, y1, x2, y2, score, class\n  t.stack = tf.stack([arr[1], arr[0], arr[3], arr[2]], 1); // reorder dims as tf.nms expects y, x\n  t.boxes = tf.squeeze(t.stack);\n  t.scores = tf.squeeze(arr[4]);\n  t.classes = tf.squeeze(arr[5]);\n  tf.dispose([res, ...arr]);\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.scores, config.object.maxDetected, config.object.iouThreshold, (config.object.minConfidence || 0));\n  const nms = await t.nms.data();\n  let i = 0;\n  for (const id of Array.from(nms)) {\n    const score = Math.trunc(100 * detections[0][id][4]) / 100;\n    const classVal = detections[0][id][5];\n    const label = labels[classVal].label as ObjectType;\n    const [x, y] = [\n      detections[0][id][0] / inputSize,\n      detections[0][id][1] / inputSize,\n    ];\n    const boxRaw: Box = [\n      x,\n      y,\n      detections[0][id][2] / inputSize - x,\n      detections[0][id][3] / inputSize - y,\n    ];\n    const box: Box = [\n      Math.trunc(boxRaw[0] * outputShape[0]),\n      Math.trunc(boxRaw[1] * outputShape[1]),\n      Math.trunc(boxRaw[2] * outputShape[0]),\n      Math.trunc(boxRaw[3] * outputShape[1]),\n    ];\n    results.push({ id: i++, score, class: classVal, label, box, boxRaw });\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return results;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<ObjectResult[]> {\n  const skipTime = (config.object.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.object.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const outputSize = [input.shape[2] || 0, input.shape[1] || 0] as [number, number];\n    const resize = tf.image.resizeBilinear(input, [inputSize, inputSize]);\n    const objectT = config.object.enabled ? model?.execute(resize, ['tower_0/detections']) as Tensor : null;\n    lastTime = now();\n    tf.dispose(resize);\n\n    const obj = await process(objectT, outputSize, config);\n    last = obj;\n\n    resolve(obj);\n  });\n}\n", "export const kpt: Array<string> = [\n  'head',\n  'neck',\n  'rightShoulder',\n  'rightElbow',\n  'rightWrist',\n  'chest',\n  'leftShoulder',\n  'leftElbow',\n  'leftWrist',\n  'bodyCenter',\n  'rightHip',\n  'rightKnee',\n  'rightAnkle',\n  'leftHip',\n  'leftKnee',\n  'leftAnkle',\n];\n\nexport const connected: Record<string, string[]> = {\n  leftLeg: ['leftHip', 'leftKnee', 'leftAnkle'],\n  rightLeg: ['rightHip', 'rightKnee', 'rightAnkle'],\n  torso: ['leftShoulder', 'rightShoulder', 'rightHip', 'leftHip', 'leftShoulder'],\n  leftArm: ['leftShoulder', 'leftElbow', 'leftWrist'],\n  rightArm: ['rightShoulder', 'rightElbow', 'rightWrist'],\n  head: [],\n};\n", "/**\n * EfficientPose model implementation\n *\n * Based on: [**EfficientPose**](https://github.com/daniegr/EfficientPose)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport * as coords from './efficientposecoords';\nimport { constants } from '../tfjs/constants';\nimport type { BodyResult, Point, BodyLandmark, BodyAnnotation } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nlet lastTime = 0;\nconst cache: BodyResult = { id: 0, keypoints: [], box: [0, 0, 0, 0], boxRaw: [0, 0, 0, 0], score: 0, annotations: {} as Record<BodyAnnotation, Point[][]> };\n\n// const keypoints: Array<BodyKeypoint> = [];\n// let box: Box = [0, 0, 0, 0];\n// let boxRaw: Box = [0, 0, 0, 0];\n// let score = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.body.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n// performs argmax and max functions on a 2d tensor\nasync function max2d(inputs, minScore) {\n  const [width, height] = inputs.shape;\n  const reshaped = tf.reshape(inputs, [height * width]); // combine all data\n  const max = tf.max(reshaped, 0);\n  const newScore = (await max.data())[0]; // get highest score\n  tf.dispose([reshaped, max]);\n  if (newScore > minScore) { // skip coordinate calculation is score is too low\n    const coordinates = tf.argMax(reshaped, 0);\n    const mod = tf.mod(coordinates, width);\n    const x = (await mod.data())[0];\n    const div = tf.div(coordinates, tf.scalar(width, 'int32'));\n    const y = (await div.data())[0];\n    tf.dispose([mod, div]);\n    return [x, y, newScore];\n  }\n  return [0, 0, newScore];\n}\n\nexport async function predict(image: Tensor, config: Config): Promise<BodyResult[]> {\n  const skipTime = (config.body.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.body.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && Object.keys(cache.keypoints).length > 0) {\n    skipped++;\n    return [cache];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const tensor = tf.tidy(() => {\n      if (!model?.inputs[0].shape) return null;\n      const resize = tf.image.resizeBilinear(image, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n      const enhance = tf.mul(resize, constants.tf2);\n      const norm = tf.sub(enhance, constants.tf1);\n      return norm;\n    });\n\n    let resT;\n    if (config.body.enabled) resT = model?.execute(tensor);\n    lastTime = now();\n    tf.dispose(tensor);\n\n    if (resT) {\n      cache.keypoints.length = 0;\n      const squeeze = resT.squeeze();\n      tf.dispose(resT);\n      // body parts are basically just a stack of 2d tensors\n      const stack = squeeze.unstack(2);\n      tf.dispose(squeeze);\n      // process each unstacked tensor as a separate body part\n      for (let id = 0; id < stack.length; id++) {\n        // actual processing to get coordinates and score\n        const [x, y, partScore] = await max2d(stack[id], config.body.minConfidence);\n        if (partScore > (config.body?.minConfidence || 0)) {\n          cache.keypoints.push({\n            score: Math.round(100 * partScore) / 100,\n            part: coords.kpt[id] as BodyLandmark,\n            positionRaw: [ // normalized to 0..1\n              // @ts-ignore model is not undefined here\n              x / model.inputs[0].shape[2], y / model.inputs[0].shape[1],\n            ],\n            position: [ // normalized to input image size\n              // @ts-ignore model is not undefined here\n              Math.round(image.shape[2] * x / model.inputs[0].shape[2]), Math.round(image.shape[1] * y / model.inputs[0].shape[1]),\n            ],\n          });\n        }\n      }\n      stack.forEach((s) => tf.dispose(s));\n    }\n    cache.score = cache.keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n    const x = cache.keypoints.map((a) => a.position[0]);\n    const y = cache.keypoints.map((a) => a.position[1]);\n    cache.box = [\n      Math.min(...x),\n      Math.min(...y),\n      Math.max(...x) - Math.min(...x),\n      Math.max(...y) - Math.min(...y),\n    ];\n    const xRaw = cache.keypoints.map((a) => a.positionRaw[0]);\n    const yRaw = cache.keypoints.map((a) => a.positionRaw[1]);\n    cache.boxRaw = [\n      Math.min(...xRaw),\n      Math.min(...yRaw),\n      Math.max(...xRaw) - Math.min(...xRaw),\n      Math.max(...yRaw) - Math.min(...yRaw),\n    ];\n    for (const [name, indexes] of Object.entries(coords.connected)) {\n      const pt: Array<Point[]> = [];\n      for (let i = 0; i < indexes.length - 1; i++) {\n        const pt0 = cache.keypoints.find((kpt) => kpt.part === indexes[i]);\n        const pt1 = cache.keypoints.find((kpt) => kpt.part === indexes[i + 1]);\n        if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n      }\n      cache.annotations[name] = pt;\n    }\n    resolve([cache]);\n  });\n}\n", "/**\n * Emotion model implementation\n *\n * [**Oarriaga**](https://github.com/oarriaga/face_classification)\n */\n\nimport type { Emotion } from '../result';\nimport { log, now } from '../util/util';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { env } from '../util/env';\nimport { constants } from '../tfjs/constants';\n\nconst annotations = ['angry', 'disgust', 'fear', 'happy', 'sad', 'surprise', 'neutral'];\nlet model: GraphModel | null;\nconst last: Array<Array<{ score: number, emotion: Emotion }>> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.emotion?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<Array<{ score: number, emotion: Emotion }>> {\n  if (!model) return [];\n  const skipFrame = skipped < (config.face.emotion?.skipFrames || 0);\n  const skipTime = (config.face.emotion?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && last[idx] && (last[idx].length > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const obj: Array<{ score: number, emotion: Emotion }> = [];\n    if (config.face.emotion?.enabled) {\n      const t: Record<string, Tensor> = {};\n      const inputSize = model?.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n      t.resize = tf.image.resizeBilinear(image, [inputSize, inputSize], false);\n      // const box = [[0.15, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n      // const resize = tf.image.cropAndResize(image, box, [0], [inputSize, inputSize]);\n      // [t.red, t.green, t.blue] = tf.split(t.resize, 3, 3);\n      // weighted rgb to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n      // t.redNorm = tf.mul(t.red, rgb[0]);\n      // t.greenNorm = tf.mul(t.green, rgb[1]);\n      // t.blueNorm = tf.mul(t.blue, rgb[2]);\n      // t.grayscale = tf.addN([t.redNorm, t.greenNorm, t.blueNorm]);\n      t.channels = tf.mul(t.resize, constants.rgb);\n      t.grayscale = tf.sum(t.channels, 3, true);\n      t.grayscaleSub = tf.sub(t.grayscale, constants.tf05);\n      t.grayscaleMul = tf.mul(t.grayscaleSub, constants.tf2);\n      t.emotion = model?.execute(t.grayscaleMul) as Tensor; // result is already in range 0..1, no need for additional activation\n      lastTime = now();\n      const data = await t.emotion.data();\n      for (let i = 0; i < data.length; i++) {\n        if (data[i] > (config.face.emotion?.minConfidence || 0)) obj.push({ score: Math.min(0.99, Math.trunc(100 * data[i]) / 100), emotion: annotations[i] as Emotion });\n      }\n      obj.sort((a, b) => b.score - a.score);\n      Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    }\n    last[idx] = obj;\n    lastCount = count;\n    resolve(obj);\n  });\n}\n", "/**\n * EfficientPose model implementation\n *\n * Based on: [**BecauseofAI MobileFace**](https://github.com/becauseofAI/MobileFace)\n *\n * Obsolete and replaced by `faceres` that performs age/gender/descriptor analysis\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst last: Array<number[]> = [];\nlet lastCount = 0;\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face['mobilefacenet'].modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\n/*\n// convert to black&white to avoid colorization impact\nconst rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\nconst [red, green, blue] = tf.split(crop, 3, 3);\nconst redNorm = tf.mul(red, rgb[0]);\nconst greenNorm = tf.mul(green, rgb[1]);\nconst blueNorm = tf.mul(blue, rgb[2]);\nconst grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\nconst merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n\n// optional increase image contrast\n// or do it per-channel so mean is done on each channel\n// or do it based on histogram\nconst mean = merge.mean();\nconst factor = 5;\nconst contrast = merge.sub(mean).mul(factor).add(mean);\n*/\n\nexport async function predict(input: Tensor, config: Config, idx, count): Promise<number[]> {\n  if (!model) return [];\n  const skipFrame = skipped < (config.face['embedding']?.skipFrames || 0);\n  const skipTime = (config.face['embedding']?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && last[idx]) {\n    skipped++;\n    return last[idx];\n  }\n  return new Promise(async (resolve) => {\n    let data: Array<number> = [];\n    if (config.face['embedding']?.enabled && model?.inputs[0].shape) {\n      const t: Record<string, Tensor> = {};\n      t.crop = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false); // just resize to fit the embedding model\n      // do a tight crop of image and resize it to fit the model\n      // const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n      // t.crop = tf.image.cropAndResize(input, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n      t.data = model?.execute(t.crop) as Tensor;\n      /*\n      // optional normalize outputs with l2 normalization\n      const scaled = tf.tidy(() => {\n        const l2 = res.norm('euclidean');\n        const scale = res.div(l2);\n        return scale;\n      });\n\n      // optional reduce feature vector complexity\n      const reshape = tf.reshape(res, [128, 2]); // split 256 vectors into 128 x 2\n      const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it\n      */\n      const output = await t.data.data();\n      data = Array.from(output); // convert typed array to simple array\n    }\n    last[idx] = data;\n    lastCount = count;\n    lastTime = now();\n    resolve(data);\n  });\n}\n", "import * as coords from './facemeshcoords';\nimport * as util from './facemeshutil';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport { env } from '../util/env';\nimport { log } from '../util/util';\nimport { loadModel } from '../tfjs/load';\nimport type { Config } from '../config';\nimport type { Point } from '../result';\n\nlet model: GraphModel | null;\nlet inputSize = 0;\n\nconst irisEnlarge = 2.3;\n\nconst leftOutline = coords.meshAnnotations['leftEyeLower0'];\nconst rightOutline = coords.meshAnnotations['rightEyeLower0'];\n\nconst eyeLandmarks = {\n  leftBounds: [leftOutline[0], leftOutline[leftOutline.length - 1]],\n  rightBounds: [rightOutline[0], rightOutline[rightOutline.length - 1]],\n};\n\nconst irisLandmarks = {\n  upperCenter: 3,\n  lowerCenter: 4,\n  index: 71,\n  numCoordinates: 76,\n};\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.iris?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  if (inputSize === -1) inputSize = 64;\n  return model;\n}\n\n// Replace the raw coordinates returned by facemesh with refined iris model coordinates and update the z coordinate to be an average of the original and the new.\nexport function replaceIrisCoords(rawCoords, newCoords, prefix, keys) {\n  for (let i = 0; i < coords.irisIndices.length; i++) {\n    const { key, indices } = coords.irisIndices[i];\n    const originalIndices = coords.meshAnnotations[`${prefix}${key}`];\n    if (!keys || keys.includes(key)) {\n      for (let j = 0; j < indices.length; j++) {\n        const index = indices[j];\n        rawCoords[originalIndices[j]] = [\n          newCoords[index][0],\n          newCoords[index][1],\n          (newCoords[index][2] + rawCoords[originalIndices[j]][2]) / 2,\n        ];\n      }\n    }\n  }\n}\n\nexport const getLeftToRightEyeDepthDifference = (rawCoords) => {\n  const leftEyeZ = rawCoords[eyeLandmarks.leftBounds[0]][2];\n  const rightEyeZ = rawCoords[eyeLandmarks.rightBounds[0]][2];\n  return leftEyeZ - rightEyeZ;\n};\n\n// Returns a box describing a cropped region around the eye fit for passing to the iris model.\nexport const getEyeBox = (rawCoords, face, eyeInnerCornerIndex, eyeOuterCornerIndex, meshSize, flip = false) => {\n  const box = util.squarifyBox(util.enlargeBox(util.calculateLandmarksBoundingBox([rawCoords[eyeInnerCornerIndex], rawCoords[eyeOuterCornerIndex]]), irisEnlarge));\n  const boxSize = util.getBoxSize(box);\n  let crop = tf.image.cropAndResize(face, [[\n    box.startPoint[1] / meshSize,\n    box.startPoint[0] / meshSize, box.endPoint[1] / meshSize,\n    box.endPoint[0] / meshSize,\n  ]], [0], [inputSize, inputSize]);\n  if (flip && env.kernels.includes('flipleftright')) {\n    const flipped = tf.image.flipLeftRight(crop); // flipLeftRight is not defined for tfjs-node\n    tf.dispose(crop);\n    crop = flipped;\n  }\n  return { box, boxSize, crop };\n};\n\n// Given a cropped image of an eye, returns the coordinates of the contours surrounding the eye and the iris.\nexport const getEyeCoords = (eyeData, eyeBox, eyeBoxSize, flip = false) => {\n  const eyeRawCoords: Array<Point> = [];\n  for (let i = 0; i < irisLandmarks.numCoordinates; i++) {\n    const x = eyeData[i * 3];\n    const y = eyeData[i * 3 + 1];\n    const z = eyeData[i * 3 + 2];\n    eyeRawCoords.push([\n      (flip ? (1 - (x / inputSize)) : (x / inputSize)) * eyeBoxSize[0] + eyeBox.startPoint[0],\n      (y / inputSize) * eyeBoxSize[1] + eyeBox.startPoint[1], z,\n    ]);\n  }\n  return { rawCoords: eyeRawCoords, iris: eyeRawCoords.slice(irisLandmarks.index) };\n};\n\n// The z-coordinates returned for the iris are unreliable, so we take the z values from the surrounding keypoints.\nexport const getAdjustedIrisCoords = (rawCoords, irisCoords, direction) => {\n  const upperCenterZ = rawCoords[coords.meshAnnotations[`${direction}EyeUpper0`][irisLandmarks.upperCenter]][2];\n  const lowerCenterZ = rawCoords[coords.meshAnnotations[`${direction}EyeLower0`][irisLandmarks.lowerCenter]][2];\n  const averageZ = (upperCenterZ + lowerCenterZ) / 2;\n  // Iris indices: 0: center | 1: right | 2: above | 3: left | 4: below\n  return irisCoords.map((coord, i) => {\n    let z = averageZ;\n    if (i === 2) {\n      z = upperCenterZ;\n    } else if (i === 4) {\n      z = lowerCenterZ;\n    }\n    return [coord[0], coord[1], z];\n  });\n};\n\nexport async function augmentIris(rawCoords, face, config, meshSize) {\n  if (!model) {\n    if (config.debug) log('face mesh iris detection requested, but model is not loaded');\n    return rawCoords;\n  }\n  const { box: leftEyeBox, boxSize: leftEyeBoxSize, crop: leftEyeCrop } = getEyeBox(rawCoords, face, eyeLandmarks.leftBounds[0], eyeLandmarks.leftBounds[1], meshSize, true);\n  const { box: rightEyeBox, boxSize: rightEyeBoxSize, crop: rightEyeCrop } = getEyeBox(rawCoords, face, eyeLandmarks.rightBounds[0], eyeLandmarks.rightBounds[1], meshSize, true);\n  const combined = tf.concat([leftEyeCrop, rightEyeCrop]);\n  tf.dispose(leftEyeCrop);\n  tf.dispose(rightEyeCrop);\n  const eyePredictions = model.execute(combined) as Tensor;\n  tf.dispose(combined);\n  const eyePredictionsData = await eyePredictions.data();\n  tf.dispose(eyePredictions);\n  const leftEyeData = eyePredictionsData.slice(0, irisLandmarks.numCoordinates * 3);\n  const { rawCoords: leftEyeRawCoords, iris: leftIrisRawCoords } = getEyeCoords(leftEyeData, leftEyeBox, leftEyeBoxSize, true);\n  const rightEyeData = eyePredictionsData.slice(irisLandmarks.numCoordinates * 3);\n  const { rawCoords: rightEyeRawCoords, iris: rightIrisRawCoords } = getEyeCoords(rightEyeData, rightEyeBox, rightEyeBoxSize, false);\n  const leftToRightEyeDepthDifference = getLeftToRightEyeDepthDifference(rawCoords);\n  if (Math.abs(leftToRightEyeDepthDifference) < 30) { // User is looking straight ahead.\n    replaceIrisCoords(rawCoords, leftEyeRawCoords, 'left', null);\n    replaceIrisCoords(rawCoords, rightEyeRawCoords, 'right', null);\n    // If the user is looking to the left or to the right, the iris coordinates tend to diverge too much from the mesh coordinates for them to be merged so we only update a single contour line above and below the eye.\n  } else if (leftToRightEyeDepthDifference < 1) { // User is looking towards the right.\n    replaceIrisCoords(rawCoords, leftEyeRawCoords, 'left', ['EyeUpper0', 'EyeLower0']);\n  } else { // User is looking towards the left.\n    replaceIrisCoords(rawCoords, rightEyeRawCoords, 'right', ['EyeUpper0', 'EyeLower0']);\n  }\n  const adjustedLeftIrisCoords = getAdjustedIrisCoords(rawCoords, leftIrisRawCoords, 'left');\n  const adjustedRightIrisCoords = getAdjustedIrisCoords(rawCoords, rightIrisRawCoords, 'right');\n  const newCoords = rawCoords.concat(adjustedLeftIrisCoords).concat(adjustedRightIrisCoords);\n  return newCoords;\n}\n", "// @tensorflow/tfjs-models/face-landmark-detection/src/constants.ts\n// https://github.com/google/mediapipe/mediapipe/python/solutions/face_mesh_connections.py\n\ntype PairArray = Array<[number, number]>;\n\nconst LIPS_CONNECTIONS: PairArray = [\n  [61, 146], [146, 91], [91, 181], [181, 84], [84, 17], [17, 314], [314, 405], [405, 321], [321, 375], [375, 291], [61, 185], [185, 40], [40, 39], [39, 37], [37, 0], [0, 267], [267, 269], [269, 270], [270, 409], [409, 291],\n  [78, 95], [95, 88], [88, 178], [178, 87], [87, 14], [14, 317], [317, 402], [402, 318], [318, 324], [324, 308], [78, 191], [191, 80], [80, 81], [81, 82], [82, 13], [13, 312], [312, 311], [311, 310], [310, 415], [415, 308],\n];\n\nconst LEFT_EYE_CONNECTIONS: PairArray = [[263, 249], [249, 390], [390, 373], [373, 374], [374, 380], [380, 381], [381, 382], [382, 362], [263, 466], [466, 388], [388, 387], [387, 386], [386, 385], [385, 384], [384, 398], [398, 362]];\n\nconst LEFT_EYEBROW_CONNECTIONS: PairArray = [[276, 283], [283, 282], [282, 295], [295, 285], [300, 293], [293, 334], [334, 296], [296, 336]];\n\nconst LEFT_IRIS_CONNECTIONS: PairArray = [[474, 475], [475, 476], [476, 477], [477, 474]];\n\nconst RIGHT_EYE_CONNECTIONS: PairArray = [[33, 7], [7, 163], [163, 144], [144, 145], [145, 153], [153, 154], [154, 155], [155, 133], [33, 246], [246, 161], [161, 160], [160, 159], [159, 158], [158, 157], [157, 173], [173, 133]];\n\nconst RIGHT_EYEBROW_CONNECTIONS: PairArray = [[46, 53], [53, 52], [52, 65], [65, 55], [70, 63], [63, 105], [105, 66], [66, 107]];\n\nconst RIGHT_IRIS_CONNECTIONS: PairArray = [[469, 470], [470, 471], [471, 472], [472, 469]];\n\nconst FACE_OVAL_CONNECTIONS: PairArray = [\n  [10, 338], [338, 297], [297, 332], [332, 284], [284, 251], [251, 389], [389, 356], [356, 454], [454, 323], [323, 361], [361, 288], [288, 397], [397, 365], [365, 379], [379, 378], [378, 400], [400, 377], [377, 152],\n  [152, 148], [148, 176], [176, 149], [149, 150], [150, 136], [136, 172], [172, 58], [58, 132], [132, 93], [93, 234], [234, 127], [127, 162], [162, 21], [21, 54], [54, 103], [103, 67], [67, 109], [109, 10],\n];\n\nexport const MEDIAPIPE_FACE_MESH_CONNECTED_KEYPOINTS_PAIRS: PairArray = [\n  [127, 34], [34, 139], [139, 127], [11, 0], [0, 37], [37, 11], [232, 231], [231, 120], [120, 232], [72, 37], [37, 39], [39, 72], [128, 121], [121, 47], [47, 128], [232, 121], [121, 128], [128, 232],\n  [104, 69], [69, 67], [67, 104], [175, 171], [171, 148], [148, 175], [118, 50], [50, 101], [101, 118], [73, 39], [39, 40], [40, 73], [9, 151], [151, 108], [108, 9], [48, 115], [115, 131], [131, 48],\n  [194, 204], [204, 211], [211, 194], [74, 40], [40, 185], [185, 74], [80, 42], [42, 183], [183, 80], [40, 92], [92, 186], [186, 40], [230, 229], [229, 118], [118, 230], [202, 212], [212, 214], [214, 202],\n  [83, 18], [18, 17], [17, 83], [76, 61], [61, 146], [146, 76], [160, 29], [29, 30], [30, 160], [56, 157], [157, 173], [173, 56], [106, 204], [204, 194], [194, 106], [135, 214], [214, 192], [192, 135],\n  [203, 165], [165, 98], [98, 203], [21, 71], [71, 68], [68, 21], [51, 45], [45, 4], [4, 51], [144, 24], [24, 23], [23, 144], [77, 146], [146, 91], [91, 77], [205, 50], [50, 187], [187, 205],\n  [201, 200], [200, 18], [18, 201], [91, 106], [106, 182], [182, 91], [90, 91], [91, 181], [181, 90], [85, 84], [84, 17], [17, 85], [206, 203], [203, 36], [36, 206], [148, 171], [171, 140], [140, 148],\n  [92, 40], [40, 39], [39, 92], [193, 189], [189, 244], [244, 193], [159, 158], [158, 28], [28, 159], [247, 246], [246, 161], [161, 247], [236, 3], [3, 196], [196, 236], [54, 68], [68, 104], [104, 54],\n  [193, 168], [168, 8], [8, 193], [117, 228], [228, 31], [31, 117], [189, 193], [193, 55], [55, 189], [98, 97], [97, 99], [99, 98], [126, 47], [47, 100], [100, 126], [166, 79], [79, 218], [218, 166],\n  [155, 154], [154, 26], [26, 155], [209, 49], [49, 131], [131, 209], [135, 136], [136, 150], [150, 135], [47, 126], [126, 217], [217, 47], [223, 52], [52, 53], [53, 223], [45, 51], [51, 134], [134, 45],\n  [211, 170], [170, 140], [140, 211], [67, 69], [69, 108], [108, 67], [43, 106], [106, 91], [91, 43], [230, 119], [119, 120], [120, 230], [226, 130], [130, 247], [247, 226], [63, 53], [53, 52], [52, 63],\n  [238, 20], [20, 242], [242, 238], [46, 70], [70, 156], [156, 46], [78, 62], [62, 96], [96, 78], [46, 53], [53, 63], [63, 46], [143, 34], [34, 227], [227, 143], [123, 117], [117, 111], [111, 123],\n  [44, 125], [125, 19], [19, 44], [236, 134], [134, 51], [51, 236], [216, 206], [206, 205], [205, 216], [154, 153], [153, 22], [22, 154], [39, 37], [37, 167], [167, 39], [200, 201], [201, 208], [208, 200],\n  [36, 142], [142, 100], [100, 36], [57, 212], [212, 202], [202, 57], [20, 60], [60, 99], [99, 20], [28, 158], [158, 157], [157, 28], [35, 226], [226, 113], [113, 35], [160, 159], [159, 27], [27, 160],\n  [204, 202], [202, 210], [210, 204], [113, 225], [225, 46], [46, 113], [43, 202], [202, 204], [204, 43], [62, 76], [76, 77], [77, 62], [137, 123], [123, 116], [116, 137], [41, 38], [38, 72], [72, 41],\n  [203, 129], [129, 142], [142, 203], [64, 98], [98, 240], [240, 64], [49, 102], [102, 64], [64, 49], [41, 73], [73, 74], [74, 41], [212, 216], [216, 207], [207, 212], [42, 74], [74, 184], [184, 42],\n  [169, 170], [170, 211], [211, 169], [170, 149], [149, 176], [176, 170], [105, 66], [66, 69], [69, 105], [122, 6], [6, 168], [168, 122], [123, 147], [147, 187], [187, 123], [96, 77], [77, 90], [90, 96],\n  [65, 55], [55, 107], [107, 65], [89, 90], [90, 180], [180, 89], [101, 100], [100, 120], [120, 101], [63, 105], [105, 104], [104, 63], [93, 137], [137, 227], [227, 93], [15, 86], [86, 85], [85, 15],\n  [129, 102], [102, 49], [49, 129], [14, 87], [87, 86], [86, 14], [55, 8], [8, 9], [9, 55], [100, 47], [47, 121], [121, 100], [145, 23], [23, 22], [22, 145], [88, 89], [89, 179], [179, 88],\n  [6, 122], [122, 196], [196, 6], [88, 95], [95, 96], [96, 88], [138, 172], [172, 136], [136, 138], [215, 58], [58, 172], [172, 215], [115, 48], [48, 219], [219, 115], [42, 80], [80, 81], [81, 42],\n  [195, 3], [3, 51], [51, 195], [43, 146], [146, 61], [61, 43], [171, 175], [175, 199], [199, 171], [81, 82], [82, 38], [38, 81], [53, 46], [46, 225], [225, 53], [144, 163], [163, 110], [110, 144],\n  [52, 65], [65, 66], [66, 52], [229, 228], [228, 117], [117, 229], [34, 127], [127, 234], [234, 34], [107, 108], [108, 69], [69, 107], [109, 108], [108, 151], [151, 109], [48, 64], [64, 235], [235, 48],\n  [62, 78], [78, 191], [191, 62], [129, 209], [209, 126], [126, 129], [111, 35], [35, 143], [143, 111], [117, 123], [123, 50], [50, 117], [222, 65], [65, 52], [52, 222], [19, 125], [125, 141], [141, 19],\n  [221, 55], [55, 65], [65, 221], [3, 195], [195, 197], [197, 3], [25, 7], [7, 33], [33, 25], [220, 237], [237, 44], [44, 220], [70, 71], [71, 139], [139, 70], [122, 193], [193, 245], [245, 122],\n  [247, 130], [130, 33], [33, 247], [71, 21], [21, 162], [162, 71], [170, 169], [169, 150], [150, 170], [188, 174], [174, 196], [196, 188], [216, 186], [186, 92], [92, 216], [2, 97], [97, 167], [167, 2],\n  [141, 125], [125, 241], [241, 141], [164, 167], [167, 37], [37, 164], [72, 38], [38, 12], [12, 72], [38, 82], [82, 13], [13, 38], [63, 68], [68, 71], [71, 63], [226, 35], [35, 111], [111, 226],\n  [101, 50], [50, 205], [205, 101], [206, 92], [92, 165], [165, 206], [209, 198], [198, 217], [217, 209], [165, 167], [167, 97], [97, 165], [220, 115], [115, 218], [218, 220], [133, 112], [112, 243], [243, 133],\n  [239, 238], [238, 241], [241, 239], [214, 135], [135, 169], [169, 214], [190, 173], [173, 133], [133, 190], [171, 208], [208, 32], [32, 171], [125, 44], [44, 237], [237, 125], [86, 87], [87, 178], [178, 86],\n  [85, 86], [86, 179], [179, 85], [84, 85], [85, 180], [180, 84], [83, 84], [84, 181], [181, 83], [201, 83], [83, 182], [182, 201], [137, 93], [93, 132], [132, 137], [76, 62], [62, 183], [183, 76],\n  [61, 76], [76, 184], [184, 61], [57, 61], [61, 185], [185, 57], [212, 57], [57, 186], [186, 212], [214, 207], [207, 187], [187, 214], [34, 143], [143, 156], [156, 34], [79, 239], [239, 237], [237, 79],\n  [123, 137], [137, 177], [177, 123], [44, 1], [1, 4], [4, 44], [201, 194], [194, 32], [32, 201], [64, 102], [102, 129], [129, 64], [213, 215], [215, 138], [138, 213], [59, 166], [166, 219], [219, 59],\n  [242, 99], [99, 97], [97, 242], [2, 94], [94, 141], [141, 2], [75, 59], [59, 235], [235, 75], [24, 110], [110, 228], [228, 24], [25, 130], [130, 226], [226, 25], [23, 24], [24, 229], [229, 23],\n  [22, 23], [23, 230], [230, 22], [26, 22], [22, 231], [231, 26], [112, 26], [26, 232], [232, 112], [189, 190], [190, 243], [243, 189], [221, 56], [56, 190], [190, 221], [28, 56], [56, 221], [221, 28],\n  [27, 28], [28, 222], [222, 27], [29, 27], [27, 223], [223, 29], [30, 29], [29, 224], [224, 30], [247, 30], [30, 225], [225, 247], [238, 79], [79, 20], [20, 238], [166, 59], [59, 75], [75, 166],\n  [60, 75], [75, 240], [240, 60], [147, 177], [177, 215], [215, 147], [20, 79], [79, 166], [166, 20], [187, 147], [147, 213], [213, 187], [112, 233], [233, 244], [244, 112], [233, 128], [128, 245], [245, 233],\n  [128, 114], [114, 188], [188, 128], [114, 217], [217, 174], [174, 114], [131, 115], [115, 220], [220, 131], [217, 198], [198, 236], [236, 217], [198, 131], [131, 134], [134, 198], [177, 132], [132, 58], [58, 177],\n  [143, 35], [35, 124], [124, 143], [110, 163], [163, 7], [7, 110], [228, 110], [110, 25], [25, 228], [356, 389], [389, 368], [368, 356], [11, 302], [302, 267], [267, 11], [452, 350], [350, 349], [349, 452],\n  [302, 303], [303, 269], [269, 302], [357, 343], [343, 277], [277, 357], [452, 453], [453, 357], [357, 452], [333, 332], [332, 297], [297, 333], [175, 152], [152, 377], [377, 175], [347, 348], [348, 330], [330, 347],\n  [303, 304], [304, 270], [270, 303], [9, 336], [336, 337], [337, 9], [278, 279], [279, 360], [360, 278], [418, 262], [262, 431], [431, 418], [304, 408], [408, 409], [409, 304], [310, 415], [415, 407], [407, 310],\n  [270, 409], [409, 410], [410, 270], [450, 348], [348, 347], [347, 450], [422, 430], [430, 434], [434, 422], [313, 314], [314, 17], [17, 313], [306, 307], [307, 375], [375, 306], [387, 388], [388, 260], [260, 387],\n  [286, 414], [414, 398], [398, 286], [335, 406], [406, 418], [418, 335], [364, 367], [367, 416], [416, 364], [423, 358], [358, 327], [327, 423], [251, 284], [284, 298], [298, 251], [281, 5], [5, 4], [4, 281],\n  [373, 374], [374, 253], [253, 373], [307, 320], [320, 321], [321, 307], [425, 427], [427, 411], [411, 425], [421, 313], [313, 18], [18, 421], [321, 405], [405, 406], [406, 321], [320, 404], [404, 405], [405, 320],\n  [315, 16], [16, 17], [17, 315], [426, 425], [425, 266], [266, 426], [377, 400], [400, 369], [369, 377], [322, 391], [391, 269], [269, 322], [417, 465], [465, 464], [464, 417], [386, 257], [257, 258], [258, 386],\n  [466, 260], [260, 388], [388, 466], [456, 399], [399, 419], [419, 456], [284, 332], [332, 333], [333, 284], [417, 285], [285, 8], [8, 417], [346, 340], [340, 261], [261, 346], [413, 441], [441, 285], [285, 413],\n  [327, 460], [460, 328], [328, 327], [355, 371], [371, 329], [329, 355], [392, 439], [439, 438], [438, 392], [382, 341], [341, 256], [256, 382], [429, 420], [420, 360], [360, 429], [364, 394], [394, 379], [379, 364],\n  [277, 343], [343, 437], [437, 277], [443, 444], [444, 283], [283, 443], [275, 440], [440, 363], [363, 275], [431, 262], [262, 369], [369, 431], [297, 338], [338, 337], [337, 297], [273, 375], [375, 321], [321, 273],\n  [450, 451], [451, 349], [349, 450], [446, 342], [342, 467], [467, 446], [293, 334], [334, 282], [282, 293], [458, 461], [461, 462], [462, 458], [276, 353], [353, 383], [383, 276], [308, 324], [324, 325], [325, 308],\n  [276, 300], [300, 293], [293, 276], [372, 345], [345, 447], [447, 372], [352, 345], [345, 340], [340, 352], [274, 1], [1, 19], [19, 274], [456, 248], [248, 281], [281, 456], [436, 427], [427, 425], [425, 436],\n  [381, 256], [256, 252], [252, 381], [269, 391], [391, 393], [393, 269], [200, 199], [199, 428], [428, 200], [266, 330], [330, 329], [329, 266], [287, 273], [273, 422], [422, 287], [250, 462], [462, 328], [328, 250],\n  [258, 286], [286, 384], [384, 258], [265, 353], [353, 342], [342, 265], [387, 259], [259, 257], [257, 387], [424, 431], [431, 430], [430, 424], [342, 353], [353, 276], [276, 342], [273, 335], [335, 424], [424, 273],\n  [292, 325], [325, 307], [307, 292], [366, 447], [447, 345], [345, 366], [271, 303], [303, 302], [302, 271], [423, 266], [266, 371], [371, 423], [294, 455], [455, 460], [460, 294], [279, 278], [278, 294], [294, 279],\n  [271, 272], [272, 304], [304, 271], [432, 434], [434, 427], [427, 432], [272, 407], [407, 408], [408, 272], [394, 430], [430, 431], [431, 394], [395, 369], [369, 400], [400, 395], [334, 333], [333, 299], [299, 334],\n  [351, 417], [417, 168], [168, 351], [352, 280], [280, 411], [411, 352], [325, 319], [319, 320], [320, 325], [295, 296], [296, 336], [336, 295], [319, 403], [403, 404], [404, 319], [330, 348], [348, 349], [349, 330],\n  [293, 298], [298, 333], [333, 293], [323, 454], [454, 447], [447, 323], [15, 16], [16, 315], [315, 15], [358, 429], [429, 279], [279, 358], [14, 15], [15, 316], [316, 14], [285, 336], [336, 9], [9, 285],\n  [329, 349], [349, 350], [350, 329], [374, 380], [380, 252], [252, 374], [318, 402], [402, 403], [403, 318], [6, 197], [197, 419], [419, 6], [318, 319], [319, 325], [325, 318], [367, 364], [364, 365], [365, 367],\n  [435, 367], [367, 397], [397, 435], [344, 438], [438, 439], [439, 344], [272, 271], [271, 311], [311, 272], [195, 5], [5, 281], [281, 195], [273, 287], [287, 291], [291, 273], [396, 428], [428, 199], [199, 396],\n  [311, 271], [271, 268], [268, 311], [283, 444], [444, 445], [445, 283], [373, 254], [254, 339], [339, 373], [282, 334], [334, 296], [296, 282], [449, 347], [347, 346], [346, 449], [264, 447], [447, 454], [454, 264],\n  [336, 296], [296, 299], [299, 336], [338, 10], [10, 151], [151, 338], [278, 439], [439, 455], [455, 278], [292, 407], [407, 415], [415, 292], [358, 371], [371, 355], [355, 358], [340, 345], [345, 372], [372, 340],\n  [346, 347], [347, 280], [280, 346], [442, 443], [443, 282], [282, 442], [19, 94], [94, 370], [370, 19], [441, 442], [442, 295], [295, 441], [248, 419], [419, 197], [197, 248], [263, 255], [255, 359], [359, 263],\n  [440, 275], [275, 274], [274, 440], [300, 383], [383, 368], [368, 300], [351, 412], [412, 465], [465, 351], [263, 467], [467, 466], [466, 263], [301, 368], [368, 389], [389, 301], [395, 378], [378, 379], [379, 395],\n  [412, 351], [351, 419], [419, 412], [436, 426], [426, 322], [322, 436], [2, 164], [164, 393], [393, 2], [370, 462], [462, 461], [461, 370], [164, 0], [0, 267], [267, 164], [302, 11], [11, 12], [12, 302],\n  [268, 12], [12, 13], [13, 268], [293, 300], [300, 301], [301, 293], [446, 261], [261, 340], [340, 446], [330, 266], [266, 425], [425, 330], [426, 423], [423, 391], [391, 426], [429, 355], [355, 437], [437, 429],\n  [391, 327], [327, 326], [326, 391], [440, 457], [457, 438], [438, 440], [341, 382], [382, 362], [362, 341], [459, 457], [457, 461], [461, 459], [434, 430], [430, 394], [394, 434], [414, 463], [463, 362], [362, 414],\n  [396, 369], [369, 262], [262, 396], [354, 461], [461, 457], [457, 354], [316, 403], [403, 402], [402, 316], [315, 404], [404, 403], [403, 315], [314, 405], [405, 404], [404, 314], [313, 406], [406, 405], [405, 313],\n  [421, 418], [418, 406], [406, 421], [366, 401], [401, 361], [361, 366], [306, 408], [408, 407], [407, 306], [291, 409], [409, 408], [408, 291], [287, 410], [410, 409], [409, 287], [432, 436], [436, 410], [410, 432],\n  [434, 416], [416, 411], [411, 434], [264, 368], [368, 383], [383, 264], [309, 438], [438, 457], [457, 309], [352, 376], [376, 401], [401, 352], [274, 275], [275, 4], [4, 274], [421, 428], [428, 262], [262, 421],\n  [294, 327], [327, 358], [358, 294], [433, 416], [416, 367], [367, 433], [289, 455], [455, 439], [439, 289], [462, 370], [370, 326], [326, 462], [2, 326], [326, 370], [370, 2], [305, 460], [460, 455], [455, 305],\n  [254, 449], [449, 448], [448, 254], [255, 261], [261, 446], [446, 255], [253, 450], [450, 449], [449, 253], [252, 451], [451, 450], [450, 252], [256, 452], [452, 451], [451, 256], [341, 453], [453, 452], [452, 341],\n  [413, 464], [464, 463], [463, 413], [441, 413], [413, 414], [414, 441], [258, 442], [442, 441], [441, 258], [257, 443], [443, 442], [442, 257], [259, 444], [444, 443], [443, 259], [260, 445], [445, 444], [444, 260],\n  [467, 342], [342, 445], [445, 467], [459, 458], [458, 250], [250, 459], [289, 392], [392, 290], [290, 289], [290, 328], [328, 460], [460, 290], [376, 433], [433, 435], [435, 376], [250, 290], [290, 392], [392, 250],\n  [411, 416], [416, 433], [433, 411], [341, 463], [463, 464], [464, 341], [453, 464], [464, 465], [465, 453], [357, 465], [465, 412], [412, 357], [343, 412], [412, 399], [399, 343], [360, 363], [363, 440], [440, 360],\n  [437, 399], [399, 456], [456, 437], [420, 456], [456, 363], [363, 420], [401, 435], [435, 288], [288, 401], [372, 383], [383, 353], [353, 372], [339, 255], [255, 249], [249, 339], [448, 261], [261, 255], [255, 448],\n  [133, 243], [243, 190], [190, 133], [133, 155], [155, 112], [112, 133], [33, 246], [246, 247], [247, 33], [33, 130], [130, 25], [25, 33], [398, 384], [384, 286], [286, 398], [362, 398], [398, 414], [414, 362],\n  [362, 463], [463, 341], [341, 362], [263, 359], [359, 467], [467, 263], [263, 249], [249, 255], [255, 263], [466, 467], [467, 260], [260, 466], [75, 60], [60, 166], [166, 75], [238, 239], [239, 79], [79, 238],\n  [162, 127], [127, 139], [139, 162], [72, 11], [11, 37], [37, 72], [121, 232], [232, 120], [120, 121], [73, 72], [72, 39], [39, 73], [114, 128], [128, 47], [47, 114], [233, 232], [232, 128], [128, 233],\n  [103, 104], [104, 67], [67, 103], [152, 175], [175, 148], [148, 152], [119, 118], [118, 101], [101, 119], [74, 73], [73, 40], [40, 74], [107, 9], [9, 108], [108, 107], [49, 48], [48, 131], [131, 49],\n  [32, 194], [194, 211], [211, 32], [184, 74], [74, 185], [185, 184], [191, 80], [80, 183], [183, 191], [185, 40], [40, 186], [186, 185], [119, 230], [230, 118], [118, 119], [210, 202], [202, 214], [214, 210],\n  [84, 83], [83, 17], [17, 84], [77, 76], [76, 146], [146, 77], [161, 160], [160, 30], [30, 161], [190, 56], [56, 173], [173, 190], [182, 106], [106, 194], [194, 182], [138, 135], [135, 192], [192, 138],\n  [129, 203], [203, 98], [98, 129], [54, 21], [21, 68], [68, 54], [5, 51], [51, 4], [4, 5], [145, 144], [144, 23], [23, 145], [90, 77], [77, 91], [91, 90], [207, 205], [205, 187], [187, 207],\n  [83, 201], [201, 18], [18, 83], [181, 91], [91, 182], [182, 181], [180, 90], [90, 181], [181, 180], [16, 85], [85, 17], [17, 16], [205, 206], [206, 36], [36, 205], [176, 148], [148, 140], [140, 176],\n  [165, 92], [92, 39], [39, 165], [245, 193], [193, 244], [244, 245], [27, 159], [159, 28], [28, 27], [30, 247], [247, 161], [161, 30], [174, 236], [236, 196], [196, 174], [103, 54], [54, 104], [104, 103],\n  [55, 193], [193, 8], [8, 55], [111, 117], [117, 31], [31, 111], [221, 189], [189, 55], [55, 221], [240, 98], [98, 99], [99, 240], [142, 126], [126, 100], [100, 142], [219, 166], [166, 218], [218, 219],\n  [112, 155], [155, 26], [26, 112], [198, 209], [209, 131], [131, 198], [169, 135], [135, 150], [150, 169], [114, 47], [47, 217], [217, 114], [224, 223], [223, 53], [53, 224], [220, 45], [45, 134], [134, 220],\n  [32, 211], [211, 140], [140, 32], [109, 67], [67, 108], [108, 109], [146, 43], [43, 91], [91, 146], [231, 230], [230, 120], [120, 231], [113, 226], [226, 247], [247, 113], [105, 63], [63, 52], [52, 105],\n  [241, 238], [238, 242], [242, 241], [124, 46], [46, 156], [156, 124], [95, 78], [78, 96], [96, 95], [70, 46], [46, 63], [63, 70], [116, 143], [143, 227], [227, 116], [116, 123], [123, 111], [111, 116],\n  [1, 44], [44, 19], [19, 1], [3, 236], [236, 51], [51, 3], [207, 216], [216, 205], [205, 207], [26, 154], [154, 22], [22, 26], [165, 39], [39, 167], [167, 165], [199, 200], [200, 208], [208, 199],\n  [101, 36], [36, 100], [100, 101], [43, 57], [57, 202], [202, 43], [242, 20], [20, 99], [99, 242], [56, 28], [28, 157], [157, 56], [124, 35], [35, 113], [113, 124], [29, 160], [160, 27], [27, 29],\n  [211, 204], [204, 210], [210, 211], [124, 113], [113, 46], [46, 124], [106, 43], [43, 204], [204, 106], [96, 62], [62, 77], [77, 96], [227, 137], [137, 116], [116, 227], [73, 41], [41, 72], [72, 73],\n  [36, 203], [203, 142], [142, 36], [235, 64], [64, 240], [240, 235], [48, 49], [49, 64], [64, 48], [42, 41], [41, 74], [74, 42], [214, 212], [212, 207], [207, 214], [183, 42], [42, 184], [184, 183],\n  [210, 169], [169, 211], [211, 210], [140, 170], [170, 176], [176, 140], [104, 105], [105, 69], [69, 104], [193, 122], [122, 168], [168, 193], [50, 123], [123, 187], [187, 50], [89, 96], [96, 90], [90, 89],\n  [66, 65], [65, 107], [107, 66], [179, 89], [89, 180], [180, 179], [119, 101], [101, 120], [120, 119], [68, 63], [63, 104], [104, 68], [234, 93], [93, 227], [227, 234], [16, 15], [15, 85], [85, 16],\n  [209, 129], [129, 49], [49, 209], [15, 14], [14, 86], [86, 15], [107, 55], [55, 9], [9, 107], [120, 100], [100, 121], [121, 120], [153, 145], [145, 22], [22, 153], [178, 88], [88, 179], [179, 178],\n  [197, 6], [6, 196], [196, 197], [89, 88], [88, 96], [96, 89], [135, 138], [138, 136], [136, 135], [138, 215], [215, 172], [172, 138], [218, 115], [115, 219], [219, 218], [41, 42], [42, 81], [81, 41],\n  [5, 195], [195, 51], [51, 5], [57, 43], [43, 61], [61, 57], [208, 171], [171, 199], [199, 208], [41, 81], [81, 38], [38, 41], [224, 53], [53, 225], [225, 224], [24, 144], [144, 110], [110, 24],\n  [105, 52], [52, 66], [66, 105], [118, 229], [229, 117], [117, 118], [227, 34], [34, 234], [234, 227], [66, 107], [107, 69], [69, 66], [10, 109], [109, 151], [151, 10], [219, 48], [48, 235], [235, 219],\n  [183, 62], [62, 191], [191, 183], [142, 129], [129, 126], [126, 142], [116, 111], [111, 143], [143, 116], [118, 117], [117, 50], [50, 118], [223, 222], [222, 52], [52, 223], [94, 19], [19, 141], [141, 94],\n  [222, 221], [221, 65], [65, 222], [196, 3], [3, 197], [197, 196], [45, 220], [220, 44], [44, 45], [156, 70], [70, 139], [139, 156], [188, 122], [122, 245], [245, 188], [139, 71], [71, 162], [162, 139],\n  [149, 170], [170, 150], [150, 149], [122, 188], [188, 196], [196, 122], [206, 216], [216, 92], [92, 206], [164, 2], [2, 167], [167, 164], [242, 141], [141, 241], [241, 242], [0, 164], [164, 37], [37, 0],\n  [11, 72], [72, 12], [12, 11], [12, 38], [38, 13], [13, 12], [70, 63], [63, 71], [71, 70], [31, 226], [226, 111], [111, 31], [36, 101], [101, 205], [205, 36], [203, 206], [206, 165], [165, 203],\n  [126, 209], [209, 217], [217, 126], [98, 165], [165, 97], [97, 98], [237, 220], [220, 218], [218, 237], [237, 239], [239, 241], [241, 237], [210, 214], [214, 169], [169, 210], [140, 171], [171, 32], [32, 140],\n  [241, 125], [125, 237], [237, 241], [179, 86], [86, 178], [178, 179], [180, 85], [85, 179], [179, 180], [181, 84], [84, 180], [180, 181], [182, 83], [83, 181], [181, 182], [194, 201], [201, 182], [182, 194],\n  [177, 137], [137, 132], [132, 177], [184, 76], [76, 183], [183, 184], [185, 61], [61, 184], [184, 185], [186, 57], [57, 185], [185, 186], [216, 212], [212, 186], [186, 216], [192, 214], [214, 187], [187, 192],\n  [139, 34], [34, 156], [156, 139], [218, 79], [79, 237], [237, 218], [147, 123], [123, 177], [177, 147], [45, 44], [44, 4], [4, 45], [208, 201], [201, 32], [32, 208], [98, 64], [64, 129], [129, 98],\n  [192, 213], [213, 138], [138, 192], [235, 59], [59, 219], [219, 235], [141, 242], [242, 97], [97, 141], [97, 2], [2, 141], [141, 97], [240, 75], [75, 235], [235, 240], [229, 24], [24, 228], [228, 229],\n  [31, 25], [25, 226], [226, 31], [230, 23], [23, 229], [229, 230], [231, 22], [22, 230], [230, 231], [232, 26], [26, 231], [231, 232], [233, 112], [112, 232], [232, 233], [244, 189], [189, 243], [243, 244],\n  [189, 221], [221, 190], [190, 189], [222, 28], [28, 221], [221, 222], [223, 27], [27, 222], [222, 223], [224, 29], [29, 223], [223, 224], [225, 30], [30, 224], [224, 225], [113, 247], [247, 225], [225, 113],\n  [99, 60], [60, 240], [240, 99], [213, 147], [147, 215], [215, 213], [60, 20], [20, 166], [166, 60], [192, 187], [187, 213], [213, 192], [243, 112], [112, 244], [244, 243], [244, 233], [233, 245], [245, 244],\n  [245, 128], [128, 188], [188, 245], [188, 114], [114, 174], [174, 188], [134, 131], [131, 220], [220, 134], [174, 217], [217, 236], [236, 174], [236, 198], [198, 134], [134, 236], [215, 177], [177, 58], [58, 215],\n  [156, 143], [143, 124], [124, 156], [25, 110], [110, 7], [7, 25], [31, 228], [228, 25], [25, 31], [264, 356], [356, 368], [368, 264], [0, 11], [11, 267], [267, 0], [451, 452], [452, 349], [349, 451],\n  [267, 302], [302, 269], [269, 267], [350, 357], [357, 277], [277, 350], [350, 452], [452, 357], [357, 350], [299, 333], [333, 297], [297, 299], [396, 175], [175, 377], [377, 396], [280, 347], [347, 330], [330, 280],\n  [269, 303], [303, 270], [270, 269], [151, 9], [9, 337], [337, 151], [344, 278], [278, 360], [360, 344], [424, 418], [418, 431], [431, 424], [270, 304], [304, 409], [409, 270], [272, 310], [310, 407], [407, 272],\n  [322, 270], [270, 410], [410, 322], [449, 450], [450, 347], [347, 449], [432, 422], [422, 434], [434, 432], [18, 313], [313, 17], [17, 18], [291, 306], [306, 375], [375, 291], [259, 387], [387, 260], [260, 259],\n  [424, 335], [335, 418], [418, 424], [434, 364], [364, 416], [416, 434], [391, 423], [423, 327], [327, 391], [301, 251], [251, 298], [298, 301], [275, 281], [281, 4], [4, 275], [254, 373], [373, 253], [253, 254],\n  [375, 307], [307, 321], [321, 375], [280, 425], [425, 411], [411, 280], [200, 421], [421, 18], [18, 200], [335, 321], [321, 406], [406, 335], [321, 320], [320, 405], [405, 321], [314, 315], [315, 17], [17, 314],\n  [423, 426], [426, 266], [266, 423], [396, 377], [377, 369], [369, 396], [270, 322], [322, 269], [269, 270], [413, 417], [417, 464], [464, 413], [385, 386], [386, 258], [258, 385], [248, 456], [456, 419], [419, 248],\n  [298, 284], [284, 333], [333, 298], [168, 417], [417, 8], [8, 168], [448, 346], [346, 261], [261, 448], [417, 413], [413, 285], [285, 417], [326, 327], [327, 328], [328, 326], [277, 355], [355, 329], [329, 277],\n  [309, 392], [392, 438], [438, 309], [381, 382], [382, 256], [256, 381], [279, 429], [429, 360], [360, 279], [365, 364], [364, 379], [379, 365], [355, 277], [277, 437], [437, 355], [282, 443], [443, 283], [283, 282],\n  [281, 275], [275, 363], [363, 281], [395, 431], [431, 369], [369, 395], [299, 297], [297, 337], [337, 299], [335, 273], [273, 321], [321, 335], [348, 450], [450, 349], [349, 348], [359, 446], [446, 467], [467, 359],\n  [283, 293], [293, 282], [282, 283], [250, 458], [458, 462], [462, 250], [300, 276], [276, 383], [383, 300], [292, 308], [308, 325], [325, 292], [283, 276], [276, 293], [293, 283], [264, 372], [372, 447], [447, 264],\n  [346, 352], [352, 340], [340, 346], [354, 274], [274, 19], [19, 354], [363, 456], [456, 281], [281, 363], [426, 436], [436, 425], [425, 426], [380, 381], [381, 252], [252, 380], [267, 269], [269, 393], [393, 267],\n  [421, 200], [200, 428], [428, 421], [371, 266], [266, 329], [329, 371], [432, 287], [287, 422], [422, 432], [290, 250], [250, 328], [328, 290], [385, 258], [258, 384], [384, 385], [446, 265], [265, 342], [342, 446],\n  [386, 387], [387, 257], [257, 386], [422, 424], [424, 430], [430, 422], [445, 342], [342, 276], [276, 445], [422, 273], [273, 424], [424, 422], [306, 292], [292, 307], [307, 306], [352, 366], [366, 345], [345, 352],\n  [268, 271], [271, 302], [302, 268], [358, 423], [423, 371], [371, 358], [327, 294], [294, 460], [460, 327], [331, 279], [279, 294], [294, 331], [303, 271], [271, 304], [304, 303], [436, 432], [432, 427], [427, 436],\n  [304, 272], [272, 408], [408, 304], [395, 394], [394, 431], [431, 395], [378, 395], [395, 400], [400, 378], [296, 334], [334, 299], [299, 296], [6, 351], [351, 168], [168, 6], [376, 352], [352, 411], [411, 376],\n  [307, 325], [325, 320], [320, 307], [285, 295], [295, 336], [336, 285], [320, 319], [319, 404], [404, 320], [329, 330], [330, 349], [349, 329], [334, 293], [293, 333], [333, 334], [366, 323], [323, 447], [447, 366],\n  [316, 15], [15, 315], [315, 316], [331, 358], [358, 279], [279, 331], [317, 14], [14, 316], [316, 317], [8, 285], [285, 9], [9, 8], [277, 329], [329, 350], [350, 277], [253, 374], [374, 252], [252, 253],\n  [319, 318], [318, 403], [403, 319], [351, 6], [6, 419], [419, 351], [324, 318], [318, 325], [325, 324], [397, 367], [367, 365], [365, 397], [288, 435], [435, 397], [397, 288], [278, 344], [344, 439], [439, 278],\n  [310, 272], [272, 311], [311, 310], [248, 195], [195, 281], [281, 248], [375, 273], [273, 291], [291, 375], [175, 396], [396, 199], [199, 175], [312, 311], [311, 268], [268, 312], [276, 283], [283, 445], [445, 276],\n  [390, 373], [373, 339], [339, 390], [295, 282], [282, 296], [296, 295], [448, 449], [449, 346], [346, 448], [356, 264], [264, 454], [454, 356], [337, 336], [336, 299], [299, 337], [337, 338], [338, 151], [151, 337],\n  [294, 278], [278, 455], [455, 294], [308, 292], [292, 415], [415, 308], [429, 358], [358, 355], [355, 429], [265, 340], [340, 372], [372, 265], [352, 346], [346, 280], [280, 352], [295, 442], [442, 282], [282, 295],\n  [354, 19], [19, 370], [370, 354], [285, 441], [441, 295], [295, 285], [195, 248], [248, 197], [197, 195], [457, 440], [440, 274], [274, 457], [301, 300], [300, 368], [368, 301], [417, 351], [351, 465], [465, 417],\n  [251, 301], [301, 389], [389, 251], [394, 395], [395, 379], [379, 394], [399, 412], [412, 419], [419, 399], [410, 436], [436, 322], [322, 410], [326, 2], [2, 393], [393, 326], [354, 370], [370, 461], [461, 354],\n  [393, 164], [164, 267], [267, 393], [268, 302], [302, 12], [12, 268], [312, 268], [268, 13], [13, 312], [298, 293], [293, 301], [301, 298], [265, 446], [446, 340], [340, 265], [280, 330], [330, 425], [425, 280],\n  [322, 426], [426, 391], [391, 322], [420, 429], [429, 437], [437, 420], [393, 391], [391, 326], [326, 393], [344, 440], [440, 438], [438, 344], [458, 459], [459, 461], [461, 458], [364, 434], [434, 394], [394, 364],\n  [428, 396], [396, 262], [262, 428], [274, 354], [354, 457], [457, 274], [317, 316], [316, 402], [402, 317], [316, 315], [315, 403], [403, 316], [315, 314], [314, 404], [404, 315], [314, 313], [313, 405], [405, 314],\n  [313, 421], [421, 406], [406, 313], [323, 366], [366, 361], [361, 323], [292, 306], [306, 407], [407, 292], [306, 291], [291, 408], [408, 306], [291, 287], [287, 409], [409, 291], [287, 432], [432, 410], [410, 287],\n  [427, 434], [434, 411], [411, 427], [372, 264], [264, 383], [383, 372], [459, 309], [309, 457], [457, 459], [366, 352], [352, 401], [401, 366], [1, 274], [274, 4], [4, 1], [418, 421], [421, 262], [262, 418],\n  [331, 294], [294, 358], [358, 331], [435, 433], [433, 367], [367, 435], [392, 289], [289, 439], [439, 392], [328, 462], [462, 326], [326, 328], [94, 2], [2, 370], [370, 94], [289, 305], [305, 455], [455, 289],\n  [339, 254], [254, 448], [448, 339], [359, 255], [255, 446], [446, 359], [254, 253], [253, 449], [449, 254], [253, 252], [252, 450], [450, 253], [252, 256], [256, 451], [451, 252], [256, 341], [341, 452], [452, 256],\n  [414, 413], [413, 463], [463, 414], [286, 441], [441, 414], [414, 286], [286, 258], [258, 441], [441, 286], [258, 257], [257, 442], [442, 258], [257, 259], [259, 443], [443, 257], [259, 260], [260, 444], [444, 259],\n  [260, 467], [467, 445], [445, 260], [309, 459], [459, 250], [250, 309], [305, 289], [289, 290], [290, 305], [305, 290], [290, 460], [460, 305], [401, 376], [376, 435], [435, 401], [309, 250], [250, 392], [392, 309],\n  [376, 411], [411, 433], [433, 376], [453, 341], [341, 464], [464, 453], [357, 453], [453, 465], [465, 357], [343, 357], [357, 412], [412, 343], [437, 343], [343, 399], [399, 437], [344, 360], [360, 440], [440, 344],\n  [420, 437], [437, 456], [456, 420], [360, 420], [420, 363], [363, 360], [361, 401], [401, 288], [288, 361], [265, 372], [372, 353], [353, 265], [390, 339], [339, 249], [249, 390], [339, 448], [448, 255], [255, 339],\n];\n\nfunction connectionsToIndices(connections: PairArray) {\n  const indices = connections.map((connection) => connection[0]);\n  indices.push(connections[connections.length - 1][1]);\n  return indices;\n}\n\nexport const MEDIAPIPE_FACE_MESH_KEYPOINTS_BY_CONTOUR = {\n  lips: connectionsToIndices(LIPS_CONNECTIONS),\n  leftEye: connectionsToIndices(LEFT_EYE_CONNECTIONS),\n  leftEyebrow: connectionsToIndices(LEFT_EYEBROW_CONNECTIONS),\n  leftIris: connectionsToIndices(LEFT_IRIS_CONNECTIONS),\n  rightEye: connectionsToIndices(RIGHT_EYE_CONNECTIONS),\n  rightEyebrow: connectionsToIndices(RIGHT_EYEBROW_CONNECTIONS),\n  rightIris: connectionsToIndices(RIGHT_IRIS_CONNECTIONS),\n  faceOval: connectionsToIndices(FACE_OVAL_CONNECTIONS),\n};\n\nconst indexLabelPairs: Array<[number, string]> = Object.entries(MEDIAPIPE_FACE_MESH_KEYPOINTS_BY_CONTOUR)\n  .map(([label, indices]) => indices.map((index) => [index, label] as [number, string]))\n  .flat();\n\nexport const MEDIAPIPE_FACE_MESH_KEYPOINTS = new Map(indexLabelPairs);\n\ntype AssignAverage = number[];\nexport interface LandmarksRefinementConfig {\n  indexesMapping: number[]; // Maps indexes of the given set of landmarks to indexes of the resulting set of landmarks. Should be non empty and contain the same amount of indexes as landmarks in the corresponding input\n  zRefinement: 'none'|'copy'|AssignAverage; // Z refinement instructions.\n}\n\nexport const LANDMARKS_REFINEMENT_LIPS_CONFIG = [\n  61, 146, 91, 181, 84, 17, 314, 405, 321, 375, 291, // Lower outer.\n  185, 40, 39, 37, 0, 267, 269, 270, 409, // Upper outer(excluding corners).\n  78, 95, 88, 178, 87, 14, 317, 402, 318, 324, 308, // Lower inner.\n  191, 80, 81, 82, 13, 312, 311, 310, 415, // Upper inner(excluding corners).\n  76, 77, 90, 180, 85, 16, 315, 404, 320, 307, 306, // Lower semi - outer.\n  184, 74, 73, 72, 11, 302, 303, 304, 408, // Upper semi - outer(excluding corners).\n  62, 96, 89, 179, 86, 15, 316, 403, 319, 325, 292, // Lower semi - inner.\n  183, 42, 41, 38, 12, 268, 271, 272, 407, // Upper semi - inner(excluding corners).\n];\n\nexport const LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG = [\n  33, 7, 163, 144, 145, 153, 154, 155, 133, // Lower contour.\n  246, 161, 160, 159, 158, 157, 173, // upper contour (excluding corners).\n  130, 25, 110, 24, 23, 22, 26, 112, 243, // Halo x2 lower contour.\n  247, 30, 29, 27, 28, 56, 190, // Halo x2 upper contour (excluding corners).\n  226, 31, 228, 229, 230, 231, 232, 233, 244, // Halo x3 lower contour.\n  113, 225, 224, 223, 222, 221, 189, // Halo x3 upper contour (excluding corners).\n  35, 124, 46, 53, 52, 65, // Halo x4 upper contour (no lower because of mesh structure) or eyebrow inner contour.\n  143, 111, 117, 118, 119, 120, 121, 128, 245, // Halo x5 lower contour.\n  156, 70, 63, 105, 66, 107, 55, 193, // Halo x5 upper contour (excluding corners) or eyebrow outer contour.\n];\n\nexport const LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG = [\n  263, 249, 390, 373, 374, 380, 381, 382, 362, // Lower contour.\n  466, 388, 387, 386, 385, 384, 398, // Upper contour (excluding corners).\n  359, 255, 339, 254, 253, 252, 256, 341, 463, // Halo x2 lower contour.\n  467, 260, 259, 257, 258, 286, 414, // Halo x2 upper contour (excluding corners).\n  446, 261, 448, 449, 450, 451, 452, 453, 464, // Halo x3 lower contour.\n  342, 445, 444, 443, 442, 441, 413, // Halo x3 upper contour (excluding corners).\n  265, 353, 276, 283, 282, 295, // Halo x4 upper contour (no lower because of mesh structure) or/ eyebrow inner contour.\n  372, 340, 346, 347, 348, 349, 350, 357, 465, // Halo x5 lower contour.\n  383, 300, 293, 334, 296, 336, 285, 417, // Halo x5 upper contour (excluding corners) or eyebrow outer contour.\n];\n\nexport const LANDMARKS_REFINEMENT_LEFT_IRIS_CONFIG = [\n  468, // Center.\n  469, // Iris right edge.\n  470, // Iris top edge.\n  471, // Iris left edge.\n  472, // Iris bottom edge.\n];\n/*\nzRefinement: [\n  33, 7, 163, 144, 145, 153, 154, 155, 133, // Lower contour.\n  246, 161, 160, 159, 158, 157, 173, // Upper contour (excluding corners).\n];\n*/\n\nexport const LANDMARKS_REFINEMENT_RIGHT_IRIS_CONFIG = [\n  473, // Center.\n  474, // Iris right edge.\n  475, // Iris top edge.\n  476, // Iris left edge.\n  477, // Iris bottom edge.\n];\n/*\nzRefinement: [\n  263, 249, 390, 373, 374, 380, 381, 382, 362, // Lower contour.\n  466, 388, 387, 386, 385, 384, 398, // Upper contour (excluding corners).\n];\n*/\n", "import * as constants from './constants';\nimport type { Tensor } from '../tfjs/types';\n\nexport async function augment(rawCoords, results: Tensor[]) {\n  const t: Record<string, Float32Array> = { // all attention models produce 2d results so it needs to be later augmented with correct z-coords\n    // mesh: results[0], // already have it in rawCoords // output_mesh_identity\n    // flag: results[1], // already processed in parent // conv_faceflag\n    lips: await results.filter((r) => r.size === 160)[0].data() as Float32Array, // 80 x 2d = 160 // output_lips\n    irisL: await results.filter((r) => r.size === 10)[0].data() as Float32Array, // 5 x 2d = 10 // output_right_iris\n    eyeL: await results.filter((r) => r.size === 142)[0].data() as Float32Array, // 71 x 2d = 142 // output_right_eye\n    irisR: await results.filter((r) => r.size === 10)[1].data() as Float32Array, // 5 x 2d = 10 // output_left_iris\n    eyeR: await results.filter((r) => r.size === 142)[1].data() as Float32Array, // 71 x 2d = 142// output_left_eye\n  };\n\n  // augment iris: adds additional 5 keypoints per eye\n  const irisLDepth = constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG.reduce((prev, curr) => prev += rawCoords[curr][2], 0) / constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG.length; // get average z-coord for iris\n  for (let i = 0; i < t.irisL.length / 2; i++) rawCoords.push([t.irisL[2 * i + 0], t.irisL[2 * i + 1], irisLDepth]);\n  const irisRDepth = constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG.reduce((prev, curr) => prev += rawCoords[curr][2], 0) / constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG.length; // get average z-coord for iris\n  for (let i = 0; i < t.irisR.length / 2; i++) rawCoords.push([t.irisR[2 * i + 0], t.irisR[2 * i + 1], irisRDepth]);\n\n  // augment eyes: replaces eye keypoints based on heuristic mapping\n  for (let i = 0; i < t.eyeL.length / 2; i++) rawCoords[constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG[i]] = [t.eyeL[2 * i + 0], t.eyeL[2 * i + 1], rawCoords[constants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG[i]][2]];\n  for (let i = 0; i < t.eyeR.length / 2; i++) rawCoords[constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG[i]] = [t.eyeR[2 * i + 0], t.eyeR[2 * i + 1], rawCoords[constants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG[i]][2]];\n\n  // augment lips: replaces eye keypoints based on heuristic mapping\n  for (let i = 0; i < t.lips.length / 2; i++) rawCoords[constants.LANDMARKS_REFINEMENT_LIPS_CONFIG[i]] = [t.lips[2 * i + 0], t.lips[2 * i + 1], rawCoords[constants.LANDMARKS_REFINEMENT_LIPS_CONFIG[i]][2]];\n\n  return rawCoords;\n}\n", "/**\n * BlazeFace, FaceMesh & Iris model implementation\n *\n * Based on:\n * - [**MediaPipe BlazeFace**](https://drive.google.com/file/d/1f39lSzU5Oq-j_OXgS67KfN5wNsoeAZ4V/view)\n * - Facial Spacial Geometry: [**MediaPipe FaceMesh**](https://drive.google.com/file/d/1VFC_wIpw4O7xBOiTgUldl79d9LA-LsnA/view)\n * - Eye Iris Details: [**MediaPipe Iris**](https://drive.google.com/file/d/1bsWbokp9AklH2ANjCfmjqEzzxO1CNbMu/view)\n */\n\nimport { log, now } from '../util/util';\nimport { loadModel } from '../tfjs/load';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as blazeface from './blazeface';\nimport * as util from './facemeshutil';\nimport * as coords from './facemeshcoords';\nimport * as iris from './iris';\nimport * as attention from './attention';\nimport { histogramEqualization } from '../image/enhance';\nimport { env } from '../util/env';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { FaceResult, FaceLandmark, Point } from '../result';\nimport type { Config } from '../config';\n\ntype DetectBox = { startPoint: Point, endPoint: Point, landmarks: Array<Point>, confidence: number };\n\nconst cache = {\n  boxes: [] as DetectBox[],\n  skipped: Number.MAX_SAFE_INTEGER,\n  timestamp: 0,\n};\n\nlet model: GraphModel | null = null;\nlet inputSize = 0;\n\nexport async function predict(input: Tensor, config: Config): Promise<FaceResult[]> {\n  // reset cached boxes\n  const skipTime = (config.face.detector?.skipTime || 0) > (now() - cache.timestamp);\n  const skipFrame = cache.skipped < (config.face.detector?.skipFrames || 0);\n  if (!config.skipAllowed || !skipTime || !skipFrame || cache.boxes.length === 0) {\n    cache.boxes = await blazeface.getBoxes(input, config); // get results from blazeface detector\n    cache.timestamp = now();\n    cache.skipped = 0;\n  } else {\n    cache.skipped++;\n  }\n  const faces: Array<FaceResult> = [];\n  const newCache: Array<DetectBox> = [];\n  let id = 0;\n  for (let i = 0; i < cache.boxes.length; i++) {\n    const box = cache.boxes[i];\n    let angle = 0;\n    let rotationMatrix;\n    const face: FaceResult = { // init face result\n      id: id++,\n      mesh: [],\n      meshRaw: [],\n      box: [0, 0, 0, 0],\n      boxRaw: [0, 0, 0, 0],\n      score: 0,\n      boxScore: 0,\n      faceScore: 0,\n      // contoursRaw: [],\n      // contours: [],\n      annotations: {} as Record<FaceLandmark, Point[]>,\n    };\n\n    // optional rotation correction based on detector data only if mesh is disabled otherwise perform it later when we have more accurate mesh data. if no rotation correction this function performs crop\n    [angle, rotationMatrix, face.tensor] = util.correctFaceRotation(config.face.detector?.rotation, box, input, config.face.mesh?.enabled ? inputSize : blazeface.size());\n    if (config?.filter?.equalization) {\n      const equilized = await histogramEqualization(face.tensor as Tensor);\n      tf.dispose(face.tensor);\n      face.tensor = equilized;\n    }\n    face.boxScore = Math.round(100 * box.confidence) / 100;\n    if (!config.face.mesh?.enabled) { // mesh not enabled, return resuts from detector only\n      face.box = util.clampBox(box, input);\n      face.boxRaw = util.getRawBox(box, input);\n      face.score = face.boxScore;\n      face.mesh = box.landmarks.map((pt) => [\n        ((box.startPoint[0] + box.endPoint[0])) / 2 + ((box.endPoint[0] + box.startPoint[0]) * pt[0] / blazeface.size()),\n        ((box.startPoint[1] + box.endPoint[1])) / 2 + ((box.endPoint[1] + box.startPoint[1]) * pt[1] / blazeface.size()),\n      ]);\n      face.meshRaw = face.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize]);\n      for (const key of Object.keys(coords.blazeFaceLandmarks)) {\n        face.annotations[key] = [face.mesh[coords.blazeFaceLandmarks[key] as number]]; // add annotations\n      }\n    } else if (!model) { // mesh enabled, but not loaded\n      if (config.debug) log('face mesh detection requested, but model is not loaded');\n    } else { // mesh enabled\n      const results = model.execute(face.tensor as Tensor) as Array<Tensor>;\n      const confidenceT = results.find((t) => t.shape[t.shape.length - 1] === 1) as Tensor;\n      const faceConfidence = await confidenceT.data();\n      face.faceScore = Math.round(100 * faceConfidence[0]) / 100;\n\n      if (face.faceScore < (config.face.detector?.minConfidence || 1)) { // low confidence in detected mesh\n        box.confidence = face.faceScore; // reset confidence of cached box\n        if (config.face.mesh?.keepInvalid) {\n          face.box = util.clampBox(box, input);\n          face.boxRaw = util.getRawBox(box, input);\n          face.score = face.boxScore;\n          face.mesh = box.landmarks.map((pt) => [\n            ((box.startPoint[0] + box.endPoint[0])) / 2 + ((box.endPoint[0] + box.startPoint[0]) * pt[0] / blazeface.size()),\n            ((box.startPoint[1] + box.endPoint[1])) / 2 + ((box.endPoint[1] + box.startPoint[1]) * pt[1] / blazeface.size()),\n          ]);\n          face.meshRaw = face.mesh.map((pt) => [pt[0] / (input.shape[2] || 1), pt[1] / (input.shape[1] || 1), (pt[2] || 0) / inputSize]);\n          for (const key of Object.keys(coords.blazeFaceLandmarks)) {\n            face.annotations[key] = [face.mesh[coords.blazeFaceLandmarks[key] as number]]; // add annotations\n          }\n        }\n      } else {\n        const meshT = results.find((t) => t.shape[t.shape.length - 1] === 1404) as Tensor;\n        const coordsReshaped = tf.reshape(meshT, [-1, 3]);\n        let rawCoords = await coordsReshaped.array();\n        tf.dispose(coordsReshaped);\n        if (config.face.attention?.enabled) {\n          rawCoords = await attention.augment(rawCoords, results); // augment iris results using attention model results\n        } else if (config.face.iris?.enabled) {\n          rawCoords = await iris.augmentIris(rawCoords, face.tensor, config, inputSize); // run iris model and augment results\n        }\n        face.mesh = util.transformRawCoords(rawCoords, box, angle, rotationMatrix, inputSize); // get processed mesh\n        face.meshRaw = face.mesh.map((pt) => [pt[0] / (input.shape[2] || 0), pt[1] / (input.shape[1] || 0), (pt[2] || 0) / inputSize]);\n        for (const key of Object.keys(coords.meshAnnotations)) face.annotations[key] = coords.meshAnnotations[key].map((index) => face.mesh[index]); // add annotations\n        face.score = face.faceScore;\n        const calculatedBox = { ...util.calculateFaceBox(face.mesh, box), confidence: box.confidence, landmarks: box.landmarks };\n        face.box = util.clampBox(calculatedBox, input);\n        face.boxRaw = util.getRawBox(calculatedBox, input);\n        /*\n        const contoursT = results.find((t) => t.shape[t.shape.length - 1] === 266) as Tensor;\n        const contoursData = contoursT && await contoursT.data(); // 133 x 2d points\n        face.contoursRaw = [];\n        for (let j = 0; j < contoursData.length / 2; j++) face.contoursRaw.push([contoursData[2 * j + 0] / inputSize, contoursData[2 * j + 1] / inputSize]);\n        face.contours = face.contoursRaw.map((c) => [Math.trunc((input.shape[2] || 1) * c[0]), Math.trunc((input.shape[1] || 1) * c[1])]);\n        */\n        newCache.push(calculatedBox);\n      }\n      tf.dispose(results);\n    }\n    if (face.score > (config.face.detector?.minConfidence || 1)) faces.push(face);\n    else tf.dispose(face.tensor);\n  }\n  cache.boxes = newCache; // reset cache\n  return faces;\n}\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  // @ts-ignore private property\n  if (config?.face?.attention?.enabled && model?.signature) {\n    // @ts-ignore private property\n    if (Object.keys(model?.signature?.outputs || {}).length < 6) model = null;\n  }\n  if (!model) {\n    if (config.face.attention?.enabled) model = await loadModel(config.face.attention?.modelPath);\n    else model = await loadModel(config.face.mesh?.modelPath);\n  } else if (config.debug) {\n    log('cached model:', model['modelUrl']);\n  }\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  return model;\n}\n\nexport const triangulation = coords.TRI468;\nexport const uvmap = coords.UV468;\n", "/**\n * FaceRes model implementation\n *\n * Returns Age, Gender, Descriptor\n * Implements Face simmilarity function\n *\n * Based on: [**HSE-FaceRes**](https://github.com/HSE-asavchenko/HSE_FaceRec_tf)\n */\n\nimport { log, now } from '../util/util';\nimport { env } from '../util/env';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport type { Gender, Race } from '../result';\n\nexport type FaceRes = { age: number, gender: Gender, genderScore: number, descriptor: number[], race?: { score: number, race: Race }[] };\n\nlet model: GraphModel | null;\nconst last: Array<{\n  age: number,\n  gender: Gender,\n  genderScore: number,\n  descriptor: number[],\n}> = [];\n\nlet lastTime = 0;\nlet lastCount = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.description?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport function enhance(input): Tensor {\n  const tensor = (input.image || input.tensor || input) as Tensor; // input received from detector is already normalized to 0..1, input is also assumed to be straightened\n  if (!model?.inputs[0].shape) return tensor; // model has no shape so no point continuing\n  const crop = tf.image.resizeBilinear(tensor, [model.inputs[0].shape[2], model.inputs[0].shape[1]], false);\n  const norm = tf.mul(crop, constants.tf255);\n  tf.dispose(crop);\n  return norm;\n  /*\n  // do a tight crop of image and resize it to fit the model\n  const box = [[0.05, 0.15, 0.85, 0.85]]; // empyrical values for top, left, bottom, right\n  const crop = (tensor.shape.length === 3)\n    ? tf.image.cropAndResize(tf.expandDims(tensor, 0), box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) // add batch dimension if missing\n    : tf.image.cropAndResize(tensor, box, [0], [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n  */\n  /*\n  // convert to black&white to avoid colorization impact\n  const rgb = [0.2989, 0.5870, 0.1140]; // factors for red/green/blue colors when converting to grayscale: https://www.mathworks.com/help/matlab/ref/rgb2gray.html\n  const [red, green, blue] = tf.split(crop, 3, 3);\n  const redNorm = tf.mul(red, rgb[0]);\n  const greenNorm = tf.mul(green, rgb[1]);\n  const blueNorm = tf.mul(blue, rgb[2]);\n  const grayscale = tf.addN([redNorm, greenNorm, blueNorm]);\n  const merge = tf.stack([grayscale, grayscale, grayscale], 3).squeeze(4);\n  */\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<FaceRes> {\n  if (!model) return { age: 0, gender: 'unknown', genderScore: 0, descriptor: [] };\n  const skipFrame = skipped < (config.face.description?.skipFrames || 0);\n  const skipTime = (config.face.description?.skipTime || 0) > (now() - lastTime);\n  if (config.skipAllowed && skipFrame && skipTime && (lastCount === count) && last[idx]?.age && (last[idx]?.age > 0)) {\n    skipped++;\n    return last[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const obj = {\n      age: <number>0,\n      gender: <Gender>'unknown',\n      genderScore: <number>0,\n      descriptor: <number[]>[],\n    };\n\n    if (config.face.description?.enabled) {\n      const enhanced = enhance(image);\n      const resT = model?.execute(enhanced) as Tensor[];\n      lastTime = now();\n      tf.dispose(enhanced);\n      const genderT = await resT.find((t) => t.shape[1] === 1) as Tensor;\n      const gender = await genderT.data();\n      const confidence = Math.trunc(200 * Math.abs((gender[0] - 0.5))) / 100;\n      if (confidence > (config.face.description?.minConfidence || 0)) {\n        obj.gender = gender[0] <= 0.5 ? 'female' : 'male';\n        obj.genderScore = Math.min(0.99, confidence);\n      }\n      const argmax = tf.argMax(resT.find((t) => t.shape[1] === 100), 1);\n      const age = (await argmax.data())[0];\n      tf.dispose(argmax);\n      const ageT = resT.find((t) => t.shape[1] === 100) as Tensor;\n      const all = await ageT.data();\n      obj.age = Math.round(all[age - 1] > all[age + 1] ? 10 * age - 100 * all[age - 1] : 10 * age + 100 * all[age + 1]) / 10;\n\n      const desc = resT.find((t) => t.shape[1] === 1024);\n      // const reshape = desc.reshape([128, 8]); // reshape large 1024-element descriptor to 128 x 8\n      // const reduce = reshape.logSumExp(1); // reduce 2nd dimension by calculating logSumExp on it which leaves us with 128-element descriptor\n      const descriptor = desc ? await desc.data() : <number[]>[];\n      obj.descriptor = Array.from(descriptor);\n      resT.forEach((t) => tf.dispose(t));\n    }\n    last[idx] = obj;\n    lastCount = count;\n    resolve(obj);\n  });\n}\n", "import * as tf from '../../dist/tfjs.esm.js';\nimport type { Point } from '../result';\n\nexport function getBoxSize(box) {\n  return [\n    Math.abs(box.endPoint[0] - box.startPoint[0]),\n    Math.abs(box.endPoint[1] - box.startPoint[1]),\n  ];\n}\n\nexport function getBoxCenter(box) {\n  return [\n    box.startPoint[0] + (box.endPoint[0] - box.startPoint[0]) / 2,\n    box.startPoint[1] + (box.endPoint[1] - box.startPoint[1]) / 2,\n  ];\n}\n\nexport function cutBoxFromImageAndResize(box, image, cropSize) {\n  const h = image.shape[1];\n  const w = image.shape[2];\n  const boxes = [[\n    box.startPoint[1] / h,\n    box.startPoint[0] / w,\n    box.endPoint[1] / h,\n    box.endPoint[0] / w,\n  ]];\n  return tf.image.cropAndResize(image, boxes, [0], cropSize);\n}\n\nexport function scaleBoxCoordinates(box, factor) {\n  const startPoint = [box.startPoint[0] * factor[0], box.startPoint[1] * factor[1]] as Point;\n  const endPoint = [box.endPoint[0] * factor[0], box.endPoint[1] * factor[1]] as Point;\n  const palmLandmarks = box.palmLandmarks.map((coord) => {\n    const scaledCoord = [coord[0] * factor[0], coord[1] * factor[1]];\n    return scaledCoord;\n  });\n  return { startPoint, endPoint, palmLandmarks, confidence: box.confidence };\n}\n\nexport function enlargeBox(box, factor = 1.5) {\n  const center = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const newHalfSize = [factor * size[0] / 2, factor * size[1] / 2];\n  const startPoint = [center[0] - newHalfSize[0], center[1] - newHalfSize[1]] as Point;\n  const endPoint = [center[0] + newHalfSize[0], center[1] + newHalfSize[1]] as Point;\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function squarifyBox(box) {\n  const centers = getBoxCenter(box);\n  const size = getBoxSize(box);\n  const maxEdge = Math.max(...size);\n  const halfSize = maxEdge / 2;\n  const startPoint = [centers[0] - halfSize, centers[1] - halfSize] as Point;\n  const endPoint = [centers[0] + halfSize, centers[1] + halfSize] as Point;\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function shiftBox(box, shiftFactor) {\n  const boxSize = [\n    box.endPoint[0] - box.startPoint[0],\n    box.endPoint[1] - box.startPoint[1],\n  ];\n  const shiftVector = [boxSize[0] * shiftFactor[0], boxSize[1] * shiftFactor[1]];\n  const startPoint = [box.startPoint[0] + shiftVector[0], box.startPoint[1] + shiftVector[1]] as Point;\n  const endPoint = [box.endPoint[0] + shiftVector[0], box.endPoint[1] + shiftVector[1]] as Point;\n  return { startPoint, endPoint, palmLandmarks: box.palmLandmarks };\n}\n\nexport function normalizeRadians(angle) {\n  return angle - 2 * Math.PI * Math.floor((angle + Math.PI) / (2 * Math.PI));\n}\n\nexport function computeRotation(point1, point2) {\n  const radians = Math.PI / 2 - Math.atan2(-(point2[1] - point1[1]), point2[0] - point1[0]);\n  return normalizeRadians(radians);\n}\n\nexport const buildTranslationMatrix = (x, y) => [[1, 0, x], [0, 1, y], [0, 0, 1]];\n\nexport function dot(v1, v2) {\n  let product = 0;\n  for (let i = 0; i < v1.length; i++) {\n    product += v1[i] * v2[i];\n  }\n  return product;\n}\n\nexport function getColumnFrom2DArr(arr, columnIndex) {\n  const column: Array<number> = [];\n  for (let i = 0; i < arr.length; i++) {\n    column.push(arr[i][columnIndex]);\n  }\n  return column;\n}\n\nexport function multiplyTransformMatrices(mat1, mat2) {\n  const product: Array<number[]> = [];\n  const size = mat1.length;\n  for (let row = 0; row < size; row++) {\n    product.push([]);\n    for (let col = 0; col < size; col++) {\n      product[row].push(dot(mat1[row], getColumnFrom2DArr(mat2, col)));\n    }\n  }\n  return product;\n}\n\nexport function buildRotationMatrix(rotation, center) {\n  const cosA = Math.cos(rotation);\n  const sinA = Math.sin(rotation);\n  const rotationMatrix = [[cosA, -sinA, 0], [sinA, cosA, 0], [0, 0, 1]];\n  const translationMatrix = buildTranslationMatrix(center[0], center[1]);\n  const translationTimesRotation = multiplyTransformMatrices(translationMatrix, rotationMatrix);\n  const negativeTranslationMatrix = buildTranslationMatrix(-center[0], -center[1]);\n  return multiplyTransformMatrices(translationTimesRotation, negativeTranslationMatrix);\n}\n\nexport function invertTransformMatrix(matrix) {\n  const rotationComponent = [[matrix[0][0], matrix[1][0]], [matrix[0][1], matrix[1][1]]];\n  const translationComponent = [matrix[0][2], matrix[1][2]];\n  const invertedTranslation = [\n    -dot(rotationComponent[0], translationComponent),\n    -dot(rotationComponent[1], translationComponent),\n  ];\n  return [\n    rotationComponent[0].concat(invertedTranslation[0]),\n    rotationComponent[1].concat(invertedTranslation[1]),\n    [0, 0, 1],\n  ];\n}\n\nexport function rotatePoint(homogeneousCoordinate, rotationMatrix) {\n  return [\n    dot(homogeneousCoordinate, rotationMatrix[0]),\n    dot(homogeneousCoordinate, rotationMatrix[1]),\n  ];\n}\n", "/**\n * HandPose model implementation constants\n * See `handpose.ts` for entry point\n */\n\nexport const anchors = [\n  { x: 0.015625, y: 0.015625 },\n  { x: 0.015625, y: 0.015625 },\n  { x: 0.046875, y: 0.015625 },\n  { x: 0.046875, y: 0.015625 },\n  { x: 0.078125, y: 0.015625 },\n  { x: 0.078125, y: 0.015625 },\n  { x: 0.109375, y: 0.015625 },\n  { x: 0.109375, y: 0.015625 },\n  { x: 0.140625, y: 0.015625 },\n  { x: 0.140625, y: 0.015625 },\n  { x: 0.171875, y: 0.015625 },\n  { x: 0.171875, y: 0.015625 },\n  { x: 0.203125, y: 0.015625 },\n  { x: 0.203125, y: 0.015625 },\n  { x: 0.234375, y: 0.015625 },\n  { x: 0.234375, y: 0.015625 },\n  { x: 0.265625, y: 0.015625 },\n  { x: 0.265625, y: 0.015625 },\n  { x: 0.296875, y: 0.015625 },\n  { x: 0.296875, y: 0.015625 },\n  { x: 0.328125, y: 0.015625 },\n  { x: 0.328125, y: 0.015625 },\n  { x: 0.359375, y: 0.015625 },\n  { x: 0.359375, y: 0.015625 },\n  { x: 0.390625, y: 0.015625 },\n  { x: 0.390625, y: 0.015625 },\n  { x: 0.421875, y: 0.015625 },\n  { x: 0.421875, y: 0.015625 },\n  { x: 0.453125, y: 0.015625 },\n  { x: 0.453125, y: 0.015625 },\n  { x: 0.484375, y: 0.015625 },\n  { x: 0.484375, y: 0.015625 },\n  { x: 0.515625, y: 0.015625 },\n  { x: 0.515625, y: 0.015625 },\n  { x: 0.546875, y: 0.015625 },\n  { x: 0.546875, y: 0.015625 },\n  { x: 0.578125, y: 0.015625 },\n  { x: 0.578125, y: 0.015625 },\n  { x: 0.609375, y: 0.015625 },\n  { x: 0.609375, y: 0.015625 },\n  { x: 0.640625, y: 0.015625 },\n  { x: 0.640625, y: 0.015625 },\n  { x: 0.671875, y: 0.015625 },\n  { x: 0.671875, y: 0.015625 },\n  { x: 0.703125, y: 0.015625 },\n  { x: 0.703125, y: 0.015625 },\n  { x: 0.734375, y: 0.015625 },\n  { x: 0.734375, y: 0.015625 },\n  { x: 0.765625, y: 0.015625 },\n  { x: 0.765625, y: 0.015625 },\n  { x: 0.796875, y: 0.015625 },\n  { x: 0.796875, y: 0.015625 },\n  { x: 0.828125, y: 0.015625 },\n  { x: 0.828125, y: 0.015625 },\n  { x: 0.859375, y: 0.015625 },\n  { x: 0.859375, y: 0.015625 },\n  { x: 0.890625, y: 0.015625 },\n  { x: 0.890625, y: 0.015625 },\n  { x: 0.921875, y: 0.015625 },\n  { x: 0.921875, y: 0.015625 },\n  { x: 0.953125, y: 0.015625 },\n  { x: 0.953125, y: 0.015625 },\n  { x: 0.984375, y: 0.015625 },\n  { x: 0.984375, y: 0.015625 },\n  { x: 0.015625, y: 0.046875 },\n  { x: 0.015625, y: 0.046875 },\n  { x: 0.046875, y: 0.046875 },\n  { x: 0.046875, y: 0.046875 },\n  { x: 0.078125, y: 0.046875 },\n  { x: 0.078125, y: 0.046875 },\n  { x: 0.109375, y: 0.046875 },\n  { x: 0.109375, y: 0.046875 },\n  { x: 0.140625, y: 0.046875 },\n  { x: 0.140625, y: 0.046875 },\n  { x: 0.171875, y: 0.046875 },\n  { x: 0.171875, y: 0.046875 },\n  { x: 0.203125, y: 0.046875 },\n  { x: 0.203125, y: 0.046875 },\n  { x: 0.234375, y: 0.046875 },\n  { x: 0.234375, y: 0.046875 },\n  { x: 0.265625, y: 0.046875 },\n  { x: 0.265625, y: 0.046875 },\n  { x: 0.296875, y: 0.046875 },\n  { x: 0.296875, y: 0.046875 },\n  { x: 0.328125, y: 0.046875 },\n  { x: 0.328125, y: 0.046875 },\n  { x: 0.359375, y: 0.046875 },\n  { x: 0.359375, y: 0.046875 },\n  { x: 0.390625, y: 0.046875 },\n  { x: 0.390625, y: 0.046875 },\n  { x: 0.421875, y: 0.046875 },\n  { x: 0.421875, y: 0.046875 },\n  { x: 0.453125, y: 0.046875 },\n  { x: 0.453125, y: 0.046875 },\n  { x: 0.484375, y: 0.046875 },\n  { x: 0.484375, y: 0.046875 },\n  { x: 0.515625, y: 0.046875 },\n  { x: 0.515625, y: 0.046875 },\n  { x: 0.546875, y: 0.046875 },\n  { x: 0.546875, y: 0.046875 },\n  { x: 0.578125, y: 0.046875 },\n  { x: 0.578125, y: 0.046875 },\n  { x: 0.609375, y: 0.046875 },\n  { x: 0.609375, y: 0.046875 },\n  { x: 0.640625, y: 0.046875 },\n  { x: 0.640625, y: 0.046875 },\n  { x: 0.671875, y: 0.046875 },\n  { x: 0.671875, y: 0.046875 },\n  { x: 0.703125, y: 0.046875 },\n  { x: 0.703125, y: 0.046875 },\n  { x: 0.734375, y: 0.046875 },\n  { x: 0.734375, y: 0.046875 },\n  { x: 0.765625, y: 0.046875 },\n  { x: 0.765625, y: 0.046875 },\n  { x: 0.796875, y: 0.046875 },\n  { x: 0.796875, y: 0.046875 },\n  { x: 0.828125, y: 0.046875 },\n  { x: 0.828125, y: 0.046875 },\n  { x: 0.859375, y: 0.046875 },\n  { x: 0.859375, y: 0.046875 },\n  { x: 0.890625, y: 0.046875 },\n  { x: 0.890625, y: 0.046875 },\n  { x: 0.921875, y: 0.046875 },\n  { x: 0.921875, y: 0.046875 },\n  { x: 0.953125, y: 0.046875 },\n  { x: 0.953125, y: 0.046875 },\n  { x: 0.984375, y: 0.046875 },\n  { x: 0.984375, y: 0.046875 },\n  { x: 0.015625, y: 0.078125 },\n  { x: 0.015625, y: 0.078125 },\n  { x: 0.046875, y: 0.078125 },\n  { x: 0.046875, y: 0.078125 },\n  { x: 0.078125, y: 0.078125 },\n  { x: 0.078125, y: 0.078125 },\n  { x: 0.109375, y: 0.078125 },\n  { x: 0.109375, y: 0.078125 },\n  { x: 0.140625, y: 0.078125 },\n  { x: 0.140625, y: 0.078125 },\n  { x: 0.171875, y: 0.078125 },\n  { x: 0.171875, y: 0.078125 },\n  { x: 0.203125, y: 0.078125 },\n  { x: 0.203125, y: 0.078125 },\n  { x: 0.234375, y: 0.078125 },\n  { x: 0.234375, y: 0.078125 },\n  { x: 0.265625, y: 0.078125 },\n  { x: 0.265625, y: 0.078125 },\n  { x: 0.296875, y: 0.078125 },\n  { x: 0.296875, y: 0.078125 },\n  { x: 0.328125, y: 0.078125 },\n  { x: 0.328125, y: 0.078125 },\n  { x: 0.359375, y: 0.078125 },\n  { x: 0.359375, y: 0.078125 },\n  { x: 0.390625, y: 0.078125 },\n  { x: 0.390625, y: 0.078125 },\n  { x: 0.421875, y: 0.078125 },\n  { x: 0.421875, y: 0.078125 },\n  { x: 0.453125, y: 0.078125 },\n  { x: 0.453125, y: 0.078125 },\n  { x: 0.484375, y: 0.078125 },\n  { x: 0.484375, y: 0.078125 },\n  { x: 0.515625, y: 0.078125 },\n  { x: 0.515625, y: 0.078125 },\n  { x: 0.546875, y: 0.078125 },\n  { x: 0.546875, y: 0.078125 },\n  { x: 0.578125, y: 0.078125 },\n  { x: 0.578125, y: 0.078125 },\n  { x: 0.609375, y: 0.078125 },\n  { x: 0.609375, y: 0.078125 },\n  { x: 0.640625, y: 0.078125 },\n  { x: 0.640625, y: 0.078125 },\n  { x: 0.671875, y: 0.078125 },\n  { x: 0.671875, y: 0.078125 },\n  { x: 0.703125, y: 0.078125 },\n  { x: 0.703125, y: 0.078125 },\n  { x: 0.734375, y: 0.078125 },\n  { x: 0.734375, y: 0.078125 },\n  { x: 0.765625, y: 0.078125 },\n  { x: 0.765625, y: 0.078125 },\n  { x: 0.796875, y: 0.078125 },\n  { x: 0.796875, y: 0.078125 },\n  { x: 0.828125, y: 0.078125 },\n  { x: 0.828125, y: 0.078125 },\n  { x: 0.859375, y: 0.078125 },\n  { x: 0.859375, y: 0.078125 },\n  { x: 0.890625, y: 0.078125 },\n  { x: 0.890625, y: 0.078125 },\n  { x: 0.921875, y: 0.078125 },\n  { x: 0.921875, y: 0.078125 },\n  { x: 0.953125, y: 0.078125 },\n  { x: 0.953125, y: 0.078125 },\n  { x: 0.984375, y: 0.078125 },\n  { x: 0.984375, y: 0.078125 },\n  { x: 0.015625, y: 0.109375 },\n  { x: 0.015625, y: 0.109375 },\n  { x: 0.046875, y: 0.109375 },\n  { x: 0.046875, y: 0.109375 },\n  { x: 0.078125, y: 0.109375 },\n  { x: 0.078125, y: 0.109375 },\n  { x: 0.109375, y: 0.109375 },\n  { x: 0.109375, y: 0.109375 },\n  { x: 0.140625, y: 0.109375 },\n  { x: 0.140625, y: 0.109375 },\n  { x: 0.171875, y: 0.109375 },\n  { x: 0.171875, y: 0.109375 },\n  { x: 0.203125, y: 0.109375 },\n  { x: 0.203125, y: 0.109375 },\n  { x: 0.234375, y: 0.109375 },\n  { x: 0.234375, y: 0.109375 },\n  { x: 0.265625, y: 0.109375 },\n  { x: 0.265625, y: 0.109375 },\n  { x: 0.296875, y: 0.109375 },\n  { x: 0.296875, y: 0.109375 },\n  { x: 0.328125, y: 0.109375 },\n  { x: 0.328125, y: 0.109375 },\n  { x: 0.359375, y: 0.109375 },\n  { x: 0.359375, y: 0.109375 },\n  { x: 0.390625, y: 0.109375 },\n  { x: 0.390625, y: 0.109375 },\n  { x: 0.421875, y: 0.109375 },\n  { x: 0.421875, y: 0.109375 },\n  { x: 0.453125, y: 0.109375 },\n  { x: 0.453125, y: 0.109375 },\n  { x: 0.484375, y: 0.109375 },\n  { x: 0.484375, y: 0.109375 },\n  { x: 0.515625, y: 0.109375 },\n  { x: 0.515625, y: 0.109375 },\n  { x: 0.546875, y: 0.109375 },\n  { x: 0.546875, y: 0.109375 },\n  { x: 0.578125, y: 0.109375 },\n  { x: 0.578125, y: 0.109375 },\n  { x: 0.609375, y: 0.109375 },\n  { x: 0.609375, y: 0.109375 },\n  { x: 0.640625, y: 0.109375 },\n  { x: 0.640625, y: 0.109375 },\n  { x: 0.671875, y: 0.109375 },\n  { x: 0.671875, y: 0.109375 },\n  { x: 0.703125, y: 0.109375 },\n  { x: 0.703125, y: 0.109375 },\n  { x: 0.734375, y: 0.109375 },\n  { x: 0.734375, y: 0.109375 },\n  { x: 0.765625, y: 0.109375 },\n  { x: 0.765625, y: 0.109375 },\n  { x: 0.796875, y: 0.109375 },\n  { x: 0.796875, y: 0.109375 },\n  { x: 0.828125, y: 0.109375 },\n  { x: 0.828125, y: 0.109375 },\n  { x: 0.859375, y: 0.109375 },\n  { x: 0.859375, y: 0.109375 },\n  { x: 0.890625, y: 0.109375 },\n  { x: 0.890625, y: 0.109375 },\n  { x: 0.921875, y: 0.109375 },\n  { x: 0.921875, y: 0.109375 },\n  { x: 0.953125, y: 0.109375 },\n  { x: 0.953125, y: 0.109375 },\n  { x: 0.984375, y: 0.109375 },\n  { x: 0.984375, y: 0.109375 },\n  { x: 0.015625, y: 0.140625 },\n  { x: 0.015625, y: 0.140625 },\n  { x: 0.046875, y: 0.140625 },\n  { x: 0.046875, y: 0.140625 },\n  { x: 0.078125, y: 0.140625 },\n  { x: 0.078125, y: 0.140625 },\n  { x: 0.109375, y: 0.140625 },\n  { x: 0.109375, y: 0.140625 },\n  { x: 0.140625, y: 0.140625 },\n  { x: 0.140625, y: 0.140625 },\n  { x: 0.171875, y: 0.140625 },\n  { x: 0.171875, y: 0.140625 },\n  { x: 0.203125, y: 0.140625 },\n  { x: 0.203125, y: 0.140625 },\n  { x: 0.234375, y: 0.140625 },\n  { x: 0.234375, y: 0.140625 },\n  { x: 0.265625, y: 0.140625 },\n  { x: 0.265625, y: 0.140625 },\n  { x: 0.296875, y: 0.140625 },\n  { x: 0.296875, y: 0.140625 },\n  { x: 0.328125, y: 0.140625 },\n  { x: 0.328125, y: 0.140625 },\n  { x: 0.359375, y: 0.140625 },\n  { x: 0.359375, y: 0.140625 },\n  { x: 0.390625, y: 0.140625 },\n  { x: 0.390625, y: 0.140625 },\n  { x: 0.421875, y: 0.140625 },\n  { x: 0.421875, y: 0.140625 },\n  { x: 0.453125, y: 0.140625 },\n  { x: 0.453125, y: 0.140625 },\n  { x: 0.484375, y: 0.140625 },\n  { x: 0.484375, y: 0.140625 },\n  { x: 0.515625, y: 0.140625 },\n  { x: 0.515625, y: 0.140625 },\n  { x: 0.546875, y: 0.140625 },\n  { x: 0.546875, y: 0.140625 },\n  { x: 0.578125, y: 0.140625 },\n  { x: 0.578125, y: 0.140625 },\n  { x: 0.609375, y: 0.140625 },\n  { x: 0.609375, y: 0.140625 },\n  { x: 0.640625, y: 0.140625 },\n  { x: 0.640625, y: 0.140625 },\n  { x: 0.671875, y: 0.140625 },\n  { x: 0.671875, y: 0.140625 },\n  { x: 0.703125, y: 0.140625 },\n  { x: 0.703125, y: 0.140625 },\n  { x: 0.734375, y: 0.140625 },\n  { x: 0.734375, y: 0.140625 },\n  { x: 0.765625, y: 0.140625 },\n  { x: 0.765625, y: 0.140625 },\n  { x: 0.796875, y: 0.140625 },\n  { x: 0.796875, y: 0.140625 },\n  { x: 0.828125, y: 0.140625 },\n  { x: 0.828125, y: 0.140625 },\n  { x: 0.859375, y: 0.140625 },\n  { x: 0.859375, y: 0.140625 },\n  { x: 0.890625, y: 0.140625 },\n  { x: 0.890625, y: 0.140625 },\n  { x: 0.921875, y: 0.140625 },\n  { x: 0.921875, y: 0.140625 },\n  { x: 0.953125, y: 0.140625 },\n  { x: 0.953125, y: 0.140625 },\n  { x: 0.984375, y: 0.140625 },\n  { x: 0.984375, y: 0.140625 },\n  { x: 0.015625, y: 0.171875 },\n  { x: 0.015625, y: 0.171875 },\n  { x: 0.046875, y: 0.171875 },\n  { x: 0.046875, y: 0.171875 },\n  { x: 0.078125, y: 0.171875 },\n  { x: 0.078125, y: 0.171875 },\n  { x: 0.109375, y: 0.171875 },\n  { x: 0.109375, y: 0.171875 },\n  { x: 0.140625, y: 0.171875 },\n  { x: 0.140625, y: 0.171875 },\n  { x: 0.171875, y: 0.171875 },\n  { x: 0.171875, y: 0.171875 },\n  { x: 0.203125, y: 0.171875 },\n  { x: 0.203125, y: 0.171875 },\n  { x: 0.234375, y: 0.171875 },\n  { x: 0.234375, y: 0.171875 },\n  { x: 0.265625, y: 0.171875 },\n  { x: 0.265625, y: 0.171875 },\n  { x: 0.296875, y: 0.171875 },\n  { x: 0.296875, y: 0.171875 },\n  { x: 0.328125, y: 0.171875 },\n  { x: 0.328125, y: 0.171875 },\n  { x: 0.359375, y: 0.171875 },\n  { x: 0.359375, y: 0.171875 },\n  { x: 0.390625, y: 0.171875 },\n  { x: 0.390625, y: 0.171875 },\n  { x: 0.421875, y: 0.171875 },\n  { x: 0.421875, y: 0.171875 },\n  { x: 0.453125, y: 0.171875 },\n  { x: 0.453125, y: 0.171875 },\n  { x: 0.484375, y: 0.171875 },\n  { x: 0.484375, y: 0.171875 },\n  { x: 0.515625, y: 0.171875 },\n  { x: 0.515625, y: 0.171875 },\n  { x: 0.546875, y: 0.171875 },\n  { x: 0.546875, y: 0.171875 },\n  { x: 0.578125, y: 0.171875 },\n  { x: 0.578125, y: 0.171875 },\n  { x: 0.609375, y: 0.171875 },\n  { x: 0.609375, y: 0.171875 },\n  { x: 0.640625, y: 0.171875 },\n  { x: 0.640625, y: 0.171875 },\n  { x: 0.671875, y: 0.171875 },\n  { x: 0.671875, y: 0.171875 },\n  { x: 0.703125, y: 0.171875 },\n  { x: 0.703125, y: 0.171875 },\n  { x: 0.734375, y: 0.171875 },\n  { x: 0.734375, y: 0.171875 },\n  { x: 0.765625, y: 0.171875 },\n  { x: 0.765625, y: 0.171875 },\n  { x: 0.796875, y: 0.171875 },\n  { x: 0.796875, y: 0.171875 },\n  { x: 0.828125, y: 0.171875 },\n  { x: 0.828125, y: 0.171875 },\n  { x: 0.859375, y: 0.171875 },\n  { x: 0.859375, y: 0.171875 },\n  { x: 0.890625, y: 0.171875 },\n  { x: 0.890625, y: 0.171875 },\n  { x: 0.921875, y: 0.171875 },\n  { x: 0.921875, y: 0.171875 },\n  { x: 0.953125, y: 0.171875 },\n  { x: 0.953125, y: 0.171875 },\n  { x: 0.984375, y: 0.171875 },\n  { x: 0.984375, y: 0.171875 },\n  { x: 0.015625, y: 0.203125 },\n  { x: 0.015625, y: 0.203125 },\n  { x: 0.046875, y: 0.203125 },\n  { x: 0.046875, y: 0.203125 },\n  { x: 0.078125, y: 0.203125 },\n  { x: 0.078125, y: 0.203125 },\n  { x: 0.109375, y: 0.203125 },\n  { x: 0.109375, y: 0.203125 },\n  { x: 0.140625, y: 0.203125 },\n  { x: 0.140625, y: 0.203125 },\n  { x: 0.171875, y: 0.203125 },\n  { x: 0.171875, y: 0.203125 },\n  { x: 0.203125, y: 0.203125 },\n  { x: 0.203125, y: 0.203125 },\n  { x: 0.234375, y: 0.203125 },\n  { x: 0.234375, y: 0.203125 },\n  { x: 0.265625, y: 0.203125 },\n  { x: 0.265625, y: 0.203125 },\n  { x: 0.296875, y: 0.203125 },\n  { x: 0.296875, y: 0.203125 },\n  { x: 0.328125, y: 0.203125 },\n  { x: 0.328125, y: 0.203125 },\n  { x: 0.359375, y: 0.203125 },\n  { x: 0.359375, y: 0.203125 },\n  { x: 0.390625, y: 0.203125 },\n  { x: 0.390625, y: 0.203125 },\n  { x: 0.421875, y: 0.203125 },\n  { x: 0.421875, y: 0.203125 },\n  { x: 0.453125, y: 0.203125 },\n  { x: 0.453125, y: 0.203125 },\n  { x: 0.484375, y: 0.203125 },\n  { x: 0.484375, y: 0.203125 },\n  { x: 0.515625, y: 0.203125 },\n  { x: 0.515625, y: 0.203125 },\n  { x: 0.546875, y: 0.203125 },\n  { x: 0.546875, y: 0.203125 },\n  { x: 0.578125, y: 0.203125 },\n  { x: 0.578125, y: 0.203125 },\n  { x: 0.609375, y: 0.203125 },\n  { x: 0.609375, y: 0.203125 },\n  { x: 0.640625, y: 0.203125 },\n  { x: 0.640625, y: 0.203125 },\n  { x: 0.671875, y: 0.203125 },\n  { x: 0.671875, y: 0.203125 },\n  { x: 0.703125, y: 0.203125 },\n  { x: 0.703125, y: 0.203125 },\n  { x: 0.734375, y: 0.203125 },\n  { x: 0.734375, y: 0.203125 },\n  { x: 0.765625, y: 0.203125 },\n  { x: 0.765625, y: 0.203125 },\n  { x: 0.796875, y: 0.203125 },\n  { x: 0.796875, y: 0.203125 },\n  { x: 0.828125, y: 0.203125 },\n  { x: 0.828125, y: 0.203125 },\n  { x: 0.859375, y: 0.203125 },\n  { x: 0.859375, y: 0.203125 },\n  { x: 0.890625, y: 0.203125 },\n  { x: 0.890625, y: 0.203125 },\n  { x: 0.921875, y: 0.203125 },\n  { x: 0.921875, y: 0.203125 },\n  { x: 0.953125, y: 0.203125 },\n  { x: 0.953125, y: 0.203125 },\n  { x: 0.984375, y: 0.203125 },\n  { x: 0.984375, y: 0.203125 },\n  { x: 0.015625, y: 0.234375 },\n  { x: 0.015625, y: 0.234375 },\n  { x: 0.046875, y: 0.234375 },\n  { x: 0.046875, y: 0.234375 },\n  { x: 0.078125, y: 0.234375 },\n  { x: 0.078125, y: 0.234375 },\n  { x: 0.109375, y: 0.234375 },\n  { x: 0.109375, y: 0.234375 },\n  { x: 0.140625, y: 0.234375 },\n  { x: 0.140625, y: 0.234375 },\n  { x: 0.171875, y: 0.234375 },\n  { x: 0.171875, y: 0.234375 },\n  { x: 0.203125, y: 0.234375 },\n  { x: 0.203125, y: 0.234375 },\n  { x: 0.234375, y: 0.234375 },\n  { x: 0.234375, y: 0.234375 },\n  { x: 0.265625, y: 0.234375 },\n  { x: 0.265625, y: 0.234375 },\n  { x: 0.296875, y: 0.234375 },\n  { x: 0.296875, y: 0.234375 },\n  { x: 0.328125, y: 0.234375 },\n  { x: 0.328125, y: 0.234375 },\n  { x: 0.359375, y: 0.234375 },\n  { x: 0.359375, y: 0.234375 },\n  { x: 0.390625, y: 0.234375 },\n  { x: 0.390625, y: 0.234375 },\n  { x: 0.421875, y: 0.234375 },\n  { x: 0.421875, y: 0.234375 },\n  { x: 0.453125, y: 0.234375 },\n  { x: 0.453125, y: 0.234375 },\n  { x: 0.484375, y: 0.234375 },\n  { x: 0.484375, y: 0.234375 },\n  { x: 0.515625, y: 0.234375 },\n  { x: 0.515625, y: 0.234375 },\n  { x: 0.546875, y: 0.234375 },\n  { x: 0.546875, y: 0.234375 },\n  { x: 0.578125, y: 0.234375 },\n  { x: 0.578125, y: 0.234375 },\n  { x: 0.609375, y: 0.234375 },\n  { x: 0.609375, y: 0.234375 },\n  { x: 0.640625, y: 0.234375 },\n  { x: 0.640625, y: 0.234375 },\n  { x: 0.671875, y: 0.234375 },\n  { x: 0.671875, y: 0.234375 },\n  { x: 0.703125, y: 0.234375 },\n  { x: 0.703125, y: 0.234375 },\n  { x: 0.734375, y: 0.234375 },\n  { x: 0.734375, y: 0.234375 },\n  { x: 0.765625, y: 0.234375 },\n  { x: 0.765625, y: 0.234375 },\n  { x: 0.796875, y: 0.234375 },\n  { x: 0.796875, y: 0.234375 },\n  { x: 0.828125, y: 0.234375 },\n  { x: 0.828125, y: 0.234375 },\n  { x: 0.859375, y: 0.234375 },\n  { x: 0.859375, y: 0.234375 },\n  { x: 0.890625, y: 0.234375 },\n  { x: 0.890625, y: 0.234375 },\n  { x: 0.921875, y: 0.234375 },\n  { x: 0.921875, y: 0.234375 },\n  { x: 0.953125, y: 0.234375 },\n  { x: 0.953125, y: 0.234375 },\n  { x: 0.984375, y: 0.234375 },\n  { x: 0.984375, y: 0.234375 },\n  { x: 0.015625, y: 0.265625 },\n  { x: 0.015625, y: 0.265625 },\n  { x: 0.046875, y: 0.265625 },\n  { x: 0.046875, y: 0.265625 },\n  { x: 0.078125, y: 0.265625 },\n  { x: 0.078125, y: 0.265625 },\n  { x: 0.109375, y: 0.265625 },\n  { x: 0.109375, y: 0.265625 },\n  { x: 0.140625, y: 0.265625 },\n  { x: 0.140625, y: 0.265625 },\n  { x: 0.171875, y: 0.265625 },\n  { x: 0.171875, y: 0.265625 },\n  { x: 0.203125, y: 0.265625 },\n  { x: 0.203125, y: 0.265625 },\n  { x: 0.234375, y: 0.265625 },\n  { x: 0.234375, y: 0.265625 },\n  { x: 0.265625, y: 0.265625 },\n  { x: 0.265625, y: 0.265625 },\n  { x: 0.296875, y: 0.265625 },\n  { x: 0.296875, y: 0.265625 },\n  { x: 0.328125, y: 0.265625 },\n  { x: 0.328125, y: 0.265625 },\n  { x: 0.359375, y: 0.265625 },\n  { x: 0.359375, y: 0.265625 },\n  { x: 0.390625, y: 0.265625 },\n  { x: 0.390625, y: 0.265625 },\n  { x: 0.421875, y: 0.265625 },\n  { x: 0.421875, y: 0.265625 },\n  { x: 0.453125, y: 0.265625 },\n  { x: 0.453125, y: 0.265625 },\n  { x: 0.484375, y: 0.265625 },\n  { x: 0.484375, y: 0.265625 },\n  { x: 0.515625, y: 0.265625 },\n  { x: 0.515625, y: 0.265625 },\n  { x: 0.546875, y: 0.265625 },\n  { x: 0.546875, y: 0.265625 },\n  { x: 0.578125, y: 0.265625 },\n  { x: 0.578125, y: 0.265625 },\n  { x: 0.609375, y: 0.265625 },\n  { x: 0.609375, y: 0.265625 },\n  { x: 0.640625, y: 0.265625 },\n  { x: 0.640625, y: 0.265625 },\n  { x: 0.671875, y: 0.265625 },\n  { x: 0.671875, y: 0.265625 },\n  { x: 0.703125, y: 0.265625 },\n  { x: 0.703125, y: 0.265625 },\n  { x: 0.734375, y: 0.265625 },\n  { x: 0.734375, y: 0.265625 },\n  { x: 0.765625, y: 0.265625 },\n  { x: 0.765625, y: 0.265625 },\n  { x: 0.796875, y: 0.265625 },\n  { x: 0.796875, y: 0.265625 },\n  { x: 0.828125, y: 0.265625 },\n  { x: 0.828125, y: 0.265625 },\n  { x: 0.859375, y: 0.265625 },\n  { x: 0.859375, y: 0.265625 },\n  { x: 0.890625, y: 0.265625 },\n  { x: 0.890625, y: 0.265625 },\n  { x: 0.921875, y: 0.265625 },\n  { x: 0.921875, y: 0.265625 },\n  { x: 0.953125, y: 0.265625 },\n  { x: 0.953125, y: 0.265625 },\n  { x: 0.984375, y: 0.265625 },\n  { x: 0.984375, y: 0.265625 },\n  { x: 0.015625, y: 0.296875 },\n  { x: 0.015625, y: 0.296875 },\n  { x: 0.046875, y: 0.296875 },\n  { x: 0.046875, y: 0.296875 },\n  { x: 0.078125, y: 0.296875 },\n  { x: 0.078125, y: 0.296875 },\n  { x: 0.109375, y: 0.296875 },\n  { x: 0.109375, y: 0.296875 },\n  { x: 0.140625, y: 0.296875 },\n  { x: 0.140625, y: 0.296875 },\n  { x: 0.171875, y: 0.296875 },\n  { x: 0.171875, y: 0.296875 },\n  { x: 0.203125, y: 0.296875 },\n  { x: 0.203125, y: 0.296875 },\n  { x: 0.234375, y: 0.296875 },\n  { x: 0.234375, y: 0.296875 },\n  { x: 0.265625, y: 0.296875 },\n  { x: 0.265625, y: 0.296875 },\n  { x: 0.296875, y: 0.296875 },\n  { x: 0.296875, y: 0.296875 },\n  { x: 0.328125, y: 0.296875 },\n  { x: 0.328125, y: 0.296875 },\n  { x: 0.359375, y: 0.296875 },\n  { x: 0.359375, y: 0.296875 },\n  { x: 0.390625, y: 0.296875 },\n  { x: 0.390625, y: 0.296875 },\n  { x: 0.421875, y: 0.296875 },\n  { x: 0.421875, y: 0.296875 },\n  { x: 0.453125, y: 0.296875 },\n  { x: 0.453125, y: 0.296875 },\n  { x: 0.484375, y: 0.296875 },\n  { x: 0.484375, y: 0.296875 },\n  { x: 0.515625, y: 0.296875 },\n  { x: 0.515625, y: 0.296875 },\n  { x: 0.546875, y: 0.296875 },\n  { x: 0.546875, y: 0.296875 },\n  { x: 0.578125, y: 0.296875 },\n  { x: 0.578125, y: 0.296875 },\n  { x: 0.609375, y: 0.296875 },\n  { x: 0.609375, y: 0.296875 },\n  { x: 0.640625, y: 0.296875 },\n  { x: 0.640625, y: 0.296875 },\n  { x: 0.671875, y: 0.296875 },\n  { x: 0.671875, y: 0.296875 },\n  { x: 0.703125, y: 0.296875 },\n  { x: 0.703125, y: 0.296875 },\n  { x: 0.734375, y: 0.296875 },\n  { x: 0.734375, y: 0.296875 },\n  { x: 0.765625, y: 0.296875 },\n  { x: 0.765625, y: 0.296875 },\n  { x: 0.796875, y: 0.296875 },\n  { x: 0.796875, y: 0.296875 },\n  { x: 0.828125, y: 0.296875 },\n  { x: 0.828125, y: 0.296875 },\n  { x: 0.859375, y: 0.296875 },\n  { x: 0.859375, y: 0.296875 },\n  { x: 0.890625, y: 0.296875 },\n  { x: 0.890625, y: 0.296875 },\n  { x: 0.921875, y: 0.296875 },\n  { x: 0.921875, y: 0.296875 },\n  { x: 0.953125, y: 0.296875 },\n  { x: 0.953125, y: 0.296875 },\n  { x: 0.984375, y: 0.296875 },\n  { x: 0.984375, y: 0.296875 },\n  { x: 0.015625, y: 0.328125 },\n  { x: 0.015625, y: 0.328125 },\n  { x: 0.046875, y: 0.328125 },\n  { x: 0.046875, y: 0.328125 },\n  { x: 0.078125, y: 0.328125 },\n  { x: 0.078125, y: 0.328125 },\n  { x: 0.109375, y: 0.328125 },\n  { x: 0.109375, y: 0.328125 },\n  { x: 0.140625, y: 0.328125 },\n  { x: 0.140625, y: 0.328125 },\n  { x: 0.171875, y: 0.328125 },\n  { x: 0.171875, y: 0.328125 },\n  { x: 0.203125, y: 0.328125 },\n  { x: 0.203125, y: 0.328125 },\n  { x: 0.234375, y: 0.328125 },\n  { x: 0.234375, y: 0.328125 },\n  { x: 0.265625, y: 0.328125 },\n  { x: 0.265625, y: 0.328125 },\n  { x: 0.296875, y: 0.328125 },\n  { x: 0.296875, y: 0.328125 },\n  { x: 0.328125, y: 0.328125 },\n  { x: 0.328125, y: 0.328125 },\n  { x: 0.359375, y: 0.328125 },\n  { x: 0.359375, y: 0.328125 },\n  { x: 0.390625, y: 0.328125 },\n  { x: 0.390625, y: 0.328125 },\n  { x: 0.421875, y: 0.328125 },\n  { x: 0.421875, y: 0.328125 },\n  { x: 0.453125, y: 0.328125 },\n  { x: 0.453125, y: 0.328125 },\n  { x: 0.484375, y: 0.328125 },\n  { x: 0.484375, y: 0.328125 },\n  { x: 0.515625, y: 0.328125 },\n  { x: 0.515625, y: 0.328125 },\n  { x: 0.546875, y: 0.328125 },\n  { x: 0.546875, y: 0.328125 },\n  { x: 0.578125, y: 0.328125 },\n  { x: 0.578125, y: 0.328125 },\n  { x: 0.609375, y: 0.328125 },\n  { x: 0.609375, y: 0.328125 },\n  { x: 0.640625, y: 0.328125 },\n  { x: 0.640625, y: 0.328125 },\n  { x: 0.671875, y: 0.328125 },\n  { x: 0.671875, y: 0.328125 },\n  { x: 0.703125, y: 0.328125 },\n  { x: 0.703125, y: 0.328125 },\n  { x: 0.734375, y: 0.328125 },\n  { x: 0.734375, y: 0.328125 },\n  { x: 0.765625, y: 0.328125 },\n  { x: 0.765625, y: 0.328125 },\n  { x: 0.796875, y: 0.328125 },\n  { x: 0.796875, y: 0.328125 },\n  { x: 0.828125, y: 0.328125 },\n  { x: 0.828125, y: 0.328125 },\n  { x: 0.859375, y: 0.328125 },\n  { x: 0.859375, y: 0.328125 },\n  { x: 0.890625, y: 0.328125 },\n  { x: 0.890625, y: 0.328125 },\n  { x: 0.921875, y: 0.328125 },\n  { x: 0.921875, y: 0.328125 },\n  { x: 0.953125, y: 0.328125 },\n  { x: 0.953125, y: 0.328125 },\n  { x: 0.984375, y: 0.328125 },\n  { x: 0.984375, y: 0.328125 },\n  { x: 0.015625, y: 0.359375 },\n  { x: 0.015625, y: 0.359375 },\n  { x: 0.046875, y: 0.359375 },\n  { x: 0.046875, y: 0.359375 },\n  { x: 0.078125, y: 0.359375 },\n  { x: 0.078125, y: 0.359375 },\n  { x: 0.109375, y: 0.359375 },\n  { x: 0.109375, y: 0.359375 },\n  { x: 0.140625, y: 0.359375 },\n  { x: 0.140625, y: 0.359375 },\n  { x: 0.171875, y: 0.359375 },\n  { x: 0.171875, y: 0.359375 },\n  { x: 0.203125, y: 0.359375 },\n  { x: 0.203125, y: 0.359375 },\n  { x: 0.234375, y: 0.359375 },\n  { x: 0.234375, y: 0.359375 },\n  { x: 0.265625, y: 0.359375 },\n  { x: 0.265625, y: 0.359375 },\n  { x: 0.296875, y: 0.359375 },\n  { x: 0.296875, y: 0.359375 },\n  { x: 0.328125, y: 0.359375 },\n  { x: 0.328125, y: 0.359375 },\n  { x: 0.359375, y: 0.359375 },\n  { x: 0.359375, y: 0.359375 },\n  { x: 0.390625, y: 0.359375 },\n  { x: 0.390625, y: 0.359375 },\n  { x: 0.421875, y: 0.359375 },\n  { x: 0.421875, y: 0.359375 },\n  { x: 0.453125, y: 0.359375 },\n  { x: 0.453125, y: 0.359375 },\n  { x: 0.484375, y: 0.359375 },\n  { x: 0.484375, y: 0.359375 },\n  { x: 0.515625, y: 0.359375 },\n  { x: 0.515625, y: 0.359375 },\n  { x: 0.546875, y: 0.359375 },\n  { x: 0.546875, y: 0.359375 },\n  { x: 0.578125, y: 0.359375 },\n  { x: 0.578125, y: 0.359375 },\n  { x: 0.609375, y: 0.359375 },\n  { x: 0.609375, y: 0.359375 },\n  { x: 0.640625, y: 0.359375 },\n  { x: 0.640625, y: 0.359375 },\n  { x: 0.671875, y: 0.359375 },\n  { x: 0.671875, y: 0.359375 },\n  { x: 0.703125, y: 0.359375 },\n  { x: 0.703125, y: 0.359375 },\n  { x: 0.734375, y: 0.359375 },\n  { x: 0.734375, y: 0.359375 },\n  { x: 0.765625, y: 0.359375 },\n  { x: 0.765625, y: 0.359375 },\n  { x: 0.796875, y: 0.359375 },\n  { x: 0.796875, y: 0.359375 },\n  { x: 0.828125, y: 0.359375 },\n  { x: 0.828125, y: 0.359375 },\n  { x: 0.859375, y: 0.359375 },\n  { x: 0.859375, y: 0.359375 },\n  { x: 0.890625, y: 0.359375 },\n  { x: 0.890625, y: 0.359375 },\n  { x: 0.921875, y: 0.359375 },\n  { x: 0.921875, y: 0.359375 },\n  { x: 0.953125, y: 0.359375 },\n  { x: 0.953125, y: 0.359375 },\n  { x: 0.984375, y: 0.359375 },\n  { x: 0.984375, y: 0.359375 },\n  { x: 0.015625, y: 0.390625 },\n  { x: 0.015625, y: 0.390625 },\n  { x: 0.046875, y: 0.390625 },\n  { x: 0.046875, y: 0.390625 },\n  { x: 0.078125, y: 0.390625 },\n  { x: 0.078125, y: 0.390625 },\n  { x: 0.109375, y: 0.390625 },\n  { x: 0.109375, y: 0.390625 },\n  { x: 0.140625, y: 0.390625 },\n  { x: 0.140625, y: 0.390625 },\n  { x: 0.171875, y: 0.390625 },\n  { x: 0.171875, y: 0.390625 },\n  { x: 0.203125, y: 0.390625 },\n  { x: 0.203125, y: 0.390625 },\n  { x: 0.234375, y: 0.390625 },\n  { x: 0.234375, y: 0.390625 },\n  { x: 0.265625, y: 0.390625 },\n  { x: 0.265625, y: 0.390625 },\n  { x: 0.296875, y: 0.390625 },\n  { x: 0.296875, y: 0.390625 },\n  { x: 0.328125, y: 0.390625 },\n  { x: 0.328125, y: 0.390625 },\n  { x: 0.359375, y: 0.390625 },\n  { x: 0.359375, y: 0.390625 },\n  { x: 0.390625, y: 0.390625 },\n  { x: 0.390625, y: 0.390625 },\n  { x: 0.421875, y: 0.390625 },\n  { x: 0.421875, y: 0.390625 },\n  { x: 0.453125, y: 0.390625 },\n  { x: 0.453125, y: 0.390625 },\n  { x: 0.484375, y: 0.390625 },\n  { x: 0.484375, y: 0.390625 },\n  { x: 0.515625, y: 0.390625 },\n  { x: 0.515625, y: 0.390625 },\n  { x: 0.546875, y: 0.390625 },\n  { x: 0.546875, y: 0.390625 },\n  { x: 0.578125, y: 0.390625 },\n  { x: 0.578125, y: 0.390625 },\n  { x: 0.609375, y: 0.390625 },\n  { x: 0.609375, y: 0.390625 },\n  { x: 0.640625, y: 0.390625 },\n  { x: 0.640625, y: 0.390625 },\n  { x: 0.671875, y: 0.390625 },\n  { x: 0.671875, y: 0.390625 },\n  { x: 0.703125, y: 0.390625 },\n  { x: 0.703125, y: 0.390625 },\n  { x: 0.734375, y: 0.390625 },\n  { x: 0.734375, y: 0.390625 },\n  { x: 0.765625, y: 0.390625 },\n  { x: 0.765625, y: 0.390625 },\n  { x: 0.796875, y: 0.390625 },\n  { x: 0.796875, y: 0.390625 },\n  { x: 0.828125, y: 0.390625 },\n  { x: 0.828125, y: 0.390625 },\n  { x: 0.859375, y: 0.390625 },\n  { x: 0.859375, y: 0.390625 },\n  { x: 0.890625, y: 0.390625 },\n  { x: 0.890625, y: 0.390625 },\n  { x: 0.921875, y: 0.390625 },\n  { x: 0.921875, y: 0.390625 },\n  { x: 0.953125, y: 0.390625 },\n  { x: 0.953125, y: 0.390625 },\n  { x: 0.984375, y: 0.390625 },\n  { x: 0.984375, y: 0.390625 },\n  { x: 0.015625, y: 0.421875 },\n  { x: 0.015625, y: 0.421875 },\n  { x: 0.046875, y: 0.421875 },\n  { x: 0.046875, y: 0.421875 },\n  { x: 0.078125, y: 0.421875 },\n  { x: 0.078125, y: 0.421875 },\n  { x: 0.109375, y: 0.421875 },\n  { x: 0.109375, y: 0.421875 },\n  { x: 0.140625, y: 0.421875 },\n  { x: 0.140625, y: 0.421875 },\n  { x: 0.171875, y: 0.421875 },\n  { x: 0.171875, y: 0.421875 },\n  { x: 0.203125, y: 0.421875 },\n  { x: 0.203125, y: 0.421875 },\n  { x: 0.234375, y: 0.421875 },\n  { x: 0.234375, y: 0.421875 },\n  { x: 0.265625, y: 0.421875 },\n  { x: 0.265625, y: 0.421875 },\n  { x: 0.296875, y: 0.421875 },\n  { x: 0.296875, y: 0.421875 },\n  { x: 0.328125, y: 0.421875 },\n  { x: 0.328125, y: 0.421875 },\n  { x: 0.359375, y: 0.421875 },\n  { x: 0.359375, y: 0.421875 },\n  { x: 0.390625, y: 0.421875 },\n  { x: 0.390625, y: 0.421875 },\n  { x: 0.421875, y: 0.421875 },\n  { x: 0.421875, y: 0.421875 },\n  { x: 0.453125, y: 0.421875 },\n  { x: 0.453125, y: 0.421875 },\n  { x: 0.484375, y: 0.421875 },\n  { x: 0.484375, y: 0.421875 },\n  { x: 0.515625, y: 0.421875 },\n  { x: 0.515625, y: 0.421875 },\n  { x: 0.546875, y: 0.421875 },\n  { x: 0.546875, y: 0.421875 },\n  { x: 0.578125, y: 0.421875 },\n  { x: 0.578125, y: 0.421875 },\n  { x: 0.609375, y: 0.421875 },\n  { x: 0.609375, y: 0.421875 },\n  { x: 0.640625, y: 0.421875 },\n  { x: 0.640625, y: 0.421875 },\n  { x: 0.671875, y: 0.421875 },\n  { x: 0.671875, y: 0.421875 },\n  { x: 0.703125, y: 0.421875 },\n  { x: 0.703125, y: 0.421875 },\n  { x: 0.734375, y: 0.421875 },\n  { x: 0.734375, y: 0.421875 },\n  { x: 0.765625, y: 0.421875 },\n  { x: 0.765625, y: 0.421875 },\n  { x: 0.796875, y: 0.421875 },\n  { x: 0.796875, y: 0.421875 },\n  { x: 0.828125, y: 0.421875 },\n  { x: 0.828125, y: 0.421875 },\n  { x: 0.859375, y: 0.421875 },\n  { x: 0.859375, y: 0.421875 },\n  { x: 0.890625, y: 0.421875 },\n  { x: 0.890625, y: 0.421875 },\n  { x: 0.921875, y: 0.421875 },\n  { x: 0.921875, y: 0.421875 },\n  { x: 0.953125, y: 0.421875 },\n  { x: 0.953125, y: 0.421875 },\n  { x: 0.984375, y: 0.421875 },\n  { x: 0.984375, y: 0.421875 },\n  { x: 0.015625, y: 0.453125 },\n  { x: 0.015625, y: 0.453125 },\n  { x: 0.046875, y: 0.453125 },\n  { x: 0.046875, y: 0.453125 },\n  { x: 0.078125, y: 0.453125 },\n  { x: 0.078125, y: 0.453125 },\n  { x: 0.109375, y: 0.453125 },\n  { x: 0.109375, y: 0.453125 },\n  { x: 0.140625, y: 0.453125 },\n  { x: 0.140625, y: 0.453125 },\n  { x: 0.171875, y: 0.453125 },\n  { x: 0.171875, y: 0.453125 },\n  { x: 0.203125, y: 0.453125 },\n  { x: 0.203125, y: 0.453125 },\n  { x: 0.234375, y: 0.453125 },\n  { x: 0.234375, y: 0.453125 },\n  { x: 0.265625, y: 0.453125 },\n  { x: 0.265625, y: 0.453125 },\n  { x: 0.296875, y: 0.453125 },\n  { x: 0.296875, y: 0.453125 },\n  { x: 0.328125, y: 0.453125 },\n  { x: 0.328125, y: 0.453125 },\n  { x: 0.359375, y: 0.453125 },\n  { x: 0.359375, y: 0.453125 },\n  { x: 0.390625, y: 0.453125 },\n  { x: 0.390625, y: 0.453125 },\n  { x: 0.421875, y: 0.453125 },\n  { x: 0.421875, y: 0.453125 },\n  { x: 0.453125, y: 0.453125 },\n  { x: 0.453125, y: 0.453125 },\n  { x: 0.484375, y: 0.453125 },\n  { x: 0.484375, y: 0.453125 },\n  { x: 0.515625, y: 0.453125 },\n  { x: 0.515625, y: 0.453125 },\n  { x: 0.546875, y: 0.453125 },\n  { x: 0.546875, y: 0.453125 },\n  { x: 0.578125, y: 0.453125 },\n  { x: 0.578125, y: 0.453125 },\n  { x: 0.609375, y: 0.453125 },\n  { x: 0.609375, y: 0.453125 },\n  { x: 0.640625, y: 0.453125 },\n  { x: 0.640625, y: 0.453125 },\n  { x: 0.671875, y: 0.453125 },\n  { x: 0.671875, y: 0.453125 },\n  { x: 0.703125, y: 0.453125 },\n  { x: 0.703125, y: 0.453125 },\n  { x: 0.734375, y: 0.453125 },\n  { x: 0.734375, y: 0.453125 },\n  { x: 0.765625, y: 0.453125 },\n  { x: 0.765625, y: 0.453125 },\n  { x: 0.796875, y: 0.453125 },\n  { x: 0.796875, y: 0.453125 },\n  { x: 0.828125, y: 0.453125 },\n  { x: 0.828125, y: 0.453125 },\n  { x: 0.859375, y: 0.453125 },\n  { x: 0.859375, y: 0.453125 },\n  { x: 0.890625, y: 0.453125 },\n  { x: 0.890625, y: 0.453125 },\n  { x: 0.921875, y: 0.453125 },\n  { x: 0.921875, y: 0.453125 },\n  { x: 0.953125, y: 0.453125 },\n  { x: 0.953125, y: 0.453125 },\n  { x: 0.984375, y: 0.453125 },\n  { x: 0.984375, y: 0.453125 },\n  { x: 0.015625, y: 0.484375 },\n  { x: 0.015625, y: 0.484375 },\n  { x: 0.046875, y: 0.484375 },\n  { x: 0.046875, y: 0.484375 },\n  { x: 0.078125, y: 0.484375 },\n  { x: 0.078125, y: 0.484375 },\n  { x: 0.109375, y: 0.484375 },\n  { x: 0.109375, y: 0.484375 },\n  { x: 0.140625, y: 0.484375 },\n  { x: 0.140625, y: 0.484375 },\n  { x: 0.171875, y: 0.484375 },\n  { x: 0.171875, y: 0.484375 },\n  { x: 0.203125, y: 0.484375 },\n  { x: 0.203125, y: 0.484375 },\n  { x: 0.234375, y: 0.484375 },\n  { x: 0.234375, y: 0.484375 },\n  { x: 0.265625, y: 0.484375 },\n  { x: 0.265625, y: 0.484375 },\n  { x: 0.296875, y: 0.484375 },\n  { x: 0.296875, y: 0.484375 },\n  { x: 0.328125, y: 0.484375 },\n  { x: 0.328125, y: 0.484375 },\n  { x: 0.359375, y: 0.484375 },\n  { x: 0.359375, y: 0.484375 },\n  { x: 0.390625, y: 0.484375 },\n  { x: 0.390625, y: 0.484375 },\n  { x: 0.421875, y: 0.484375 },\n  { x: 0.421875, y: 0.484375 },\n  { x: 0.453125, y: 0.484375 },\n  { x: 0.453125, y: 0.484375 },\n  { x: 0.484375, y: 0.484375 },\n  { x: 0.484375, y: 0.484375 },\n  { x: 0.515625, y: 0.484375 },\n  { x: 0.515625, y: 0.484375 },\n  { x: 0.546875, y: 0.484375 },\n  { x: 0.546875, y: 0.484375 },\n  { x: 0.578125, y: 0.484375 },\n  { x: 0.578125, y: 0.484375 },\n  { x: 0.609375, y: 0.484375 },\n  { x: 0.609375, y: 0.484375 },\n  { x: 0.640625, y: 0.484375 },\n  { x: 0.640625, y: 0.484375 },\n  { x: 0.671875, y: 0.484375 },\n  { x: 0.671875, y: 0.484375 },\n  { x: 0.703125, y: 0.484375 },\n  { x: 0.703125, y: 0.484375 },\n  { x: 0.734375, y: 0.484375 },\n  { x: 0.734375, y: 0.484375 },\n  { x: 0.765625, y: 0.484375 },\n  { x: 0.765625, y: 0.484375 },\n  { x: 0.796875, y: 0.484375 },\n  { x: 0.796875, y: 0.484375 },\n  { x: 0.828125, y: 0.484375 },\n  { x: 0.828125, y: 0.484375 },\n  { x: 0.859375, y: 0.484375 },\n  { x: 0.859375, y: 0.484375 },\n  { x: 0.890625, y: 0.484375 },\n  { x: 0.890625, y: 0.484375 },\n  { x: 0.921875, y: 0.484375 },\n  { x: 0.921875, y: 0.484375 },\n  { x: 0.953125, y: 0.484375 },\n  { x: 0.953125, y: 0.484375 },\n  { x: 0.984375, y: 0.484375 },\n  { x: 0.984375, y: 0.484375 },\n  { x: 0.015625, y: 0.515625 },\n  { x: 0.015625, y: 0.515625 },\n  { x: 0.046875, y: 0.515625 },\n  { x: 0.046875, y: 0.515625 },\n  { x: 0.078125, y: 0.515625 },\n  { x: 0.078125, y: 0.515625 },\n  { x: 0.109375, y: 0.515625 },\n  { x: 0.109375, y: 0.515625 },\n  { x: 0.140625, y: 0.515625 },\n  { x: 0.140625, y: 0.515625 },\n  { x: 0.171875, y: 0.515625 },\n  { x: 0.171875, y: 0.515625 },\n  { x: 0.203125, y: 0.515625 },\n  { x: 0.203125, y: 0.515625 },\n  { x: 0.234375, y: 0.515625 },\n  { x: 0.234375, y: 0.515625 },\n  { x: 0.265625, y: 0.515625 },\n  { x: 0.265625, y: 0.515625 },\n  { x: 0.296875, y: 0.515625 },\n  { x: 0.296875, y: 0.515625 },\n  { x: 0.328125, y: 0.515625 },\n  { x: 0.328125, y: 0.515625 },\n  { x: 0.359375, y: 0.515625 },\n  { x: 0.359375, y: 0.515625 },\n  { x: 0.390625, y: 0.515625 },\n  { x: 0.390625, y: 0.515625 },\n  { x: 0.421875, y: 0.515625 },\n  { x: 0.421875, y: 0.515625 },\n  { x: 0.453125, y: 0.515625 },\n  { x: 0.453125, y: 0.515625 },\n  { x: 0.484375, y: 0.515625 },\n  { x: 0.484375, y: 0.515625 },\n  { x: 0.515625, y: 0.515625 },\n  { x: 0.515625, y: 0.515625 },\n  { x: 0.546875, y: 0.515625 },\n  { x: 0.546875, y: 0.515625 },\n  { x: 0.578125, y: 0.515625 },\n  { x: 0.578125, y: 0.515625 },\n  { x: 0.609375, y: 0.515625 },\n  { x: 0.609375, y: 0.515625 },\n  { x: 0.640625, y: 0.515625 },\n  { x: 0.640625, y: 0.515625 },\n  { x: 0.671875, y: 0.515625 },\n  { x: 0.671875, y: 0.515625 },\n  { x: 0.703125, y: 0.515625 },\n  { x: 0.703125, y: 0.515625 },\n  { x: 0.734375, y: 0.515625 },\n  { x: 0.734375, y: 0.515625 },\n  { x: 0.765625, y: 0.515625 },\n  { x: 0.765625, y: 0.515625 },\n  { x: 0.796875, y: 0.515625 },\n  { x: 0.796875, y: 0.515625 },\n  { x: 0.828125, y: 0.515625 },\n  { x: 0.828125, y: 0.515625 },\n  { x: 0.859375, y: 0.515625 },\n  { x: 0.859375, y: 0.515625 },\n  { x: 0.890625, y: 0.515625 },\n  { x: 0.890625, y: 0.515625 },\n  { x: 0.921875, y: 0.515625 },\n  { x: 0.921875, y: 0.515625 },\n  { x: 0.953125, y: 0.515625 },\n  { x: 0.953125, y: 0.515625 },\n  { x: 0.984375, y: 0.515625 },\n  { x: 0.984375, y: 0.515625 },\n  { x: 0.015625, y: 0.546875 },\n  { x: 0.015625, y: 0.546875 },\n  { x: 0.046875, y: 0.546875 },\n  { x: 0.046875, y: 0.546875 },\n  { x: 0.078125, y: 0.546875 },\n  { x: 0.078125, y: 0.546875 },\n  { x: 0.109375, y: 0.546875 },\n  { x: 0.109375, y: 0.546875 },\n  { x: 0.140625, y: 0.546875 },\n  { x: 0.140625, y: 0.546875 },\n  { x: 0.171875, y: 0.546875 },\n  { x: 0.171875, y: 0.546875 },\n  { x: 0.203125, y: 0.546875 },\n  { x: 0.203125, y: 0.546875 },\n  { x: 0.234375, y: 0.546875 },\n  { x: 0.234375, y: 0.546875 },\n  { x: 0.265625, y: 0.546875 },\n  { x: 0.265625, y: 0.546875 },\n  { x: 0.296875, y: 0.546875 },\n  { x: 0.296875, y: 0.546875 },\n  { x: 0.328125, y: 0.546875 },\n  { x: 0.328125, y: 0.546875 },\n  { x: 0.359375, y: 0.546875 },\n  { x: 0.359375, y: 0.546875 },\n  { x: 0.390625, y: 0.546875 },\n  { x: 0.390625, y: 0.546875 },\n  { x: 0.421875, y: 0.546875 },\n  { x: 0.421875, y: 0.546875 },\n  { x: 0.453125, y: 0.546875 },\n  { x: 0.453125, y: 0.546875 },\n  { x: 0.484375, y: 0.546875 },\n  { x: 0.484375, y: 0.546875 },\n  { x: 0.515625, y: 0.546875 },\n  { x: 0.515625, y: 0.546875 },\n  { x: 0.546875, y: 0.546875 },\n  { x: 0.546875, y: 0.546875 },\n  { x: 0.578125, y: 0.546875 },\n  { x: 0.578125, y: 0.546875 },\n  { x: 0.609375, y: 0.546875 },\n  { x: 0.609375, y: 0.546875 },\n  { x: 0.640625, y: 0.546875 },\n  { x: 0.640625, y: 0.546875 },\n  { x: 0.671875, y: 0.546875 },\n  { x: 0.671875, y: 0.546875 },\n  { x: 0.703125, y: 0.546875 },\n  { x: 0.703125, y: 0.546875 },\n  { x: 0.734375, y: 0.546875 },\n  { x: 0.734375, y: 0.546875 },\n  { x: 0.765625, y: 0.546875 },\n  { x: 0.765625, y: 0.546875 },\n  { x: 0.796875, y: 0.546875 },\n  { x: 0.796875, y: 0.546875 },\n  { x: 0.828125, y: 0.546875 },\n  { x: 0.828125, y: 0.546875 },\n  { x: 0.859375, y: 0.546875 },\n  { x: 0.859375, y: 0.546875 },\n  { x: 0.890625, y: 0.546875 },\n  { x: 0.890625, y: 0.546875 },\n  { x: 0.921875, y: 0.546875 },\n  { x: 0.921875, y: 0.546875 },\n  { x: 0.953125, y: 0.546875 },\n  { x: 0.953125, y: 0.546875 },\n  { x: 0.984375, y: 0.546875 },\n  { x: 0.984375, y: 0.546875 },\n  { x: 0.015625, y: 0.578125 },\n  { x: 0.015625, y: 0.578125 },\n  { x: 0.046875, y: 0.578125 },\n  { x: 0.046875, y: 0.578125 },\n  { x: 0.078125, y: 0.578125 },\n  { x: 0.078125, y: 0.578125 },\n  { x: 0.109375, y: 0.578125 },\n  { x: 0.109375, y: 0.578125 },\n  { x: 0.140625, y: 0.578125 },\n  { x: 0.140625, y: 0.578125 },\n  { x: 0.171875, y: 0.578125 },\n  { x: 0.171875, y: 0.578125 },\n  { x: 0.203125, y: 0.578125 },\n  { x: 0.203125, y: 0.578125 },\n  { x: 0.234375, y: 0.578125 },\n  { x: 0.234375, y: 0.578125 },\n  { x: 0.265625, y: 0.578125 },\n  { x: 0.265625, y: 0.578125 },\n  { x: 0.296875, y: 0.578125 },\n  { x: 0.296875, y: 0.578125 },\n  { x: 0.328125, y: 0.578125 },\n  { x: 0.328125, y: 0.578125 },\n  { x: 0.359375, y: 0.578125 },\n  { x: 0.359375, y: 0.578125 },\n  { x: 0.390625, y: 0.578125 },\n  { x: 0.390625, y: 0.578125 },\n  { x: 0.421875, y: 0.578125 },\n  { x: 0.421875, y: 0.578125 },\n  { x: 0.453125, y: 0.578125 },\n  { x: 0.453125, y: 0.578125 },\n  { x: 0.484375, y: 0.578125 },\n  { x: 0.484375, y: 0.578125 },\n  { x: 0.515625, y: 0.578125 },\n  { x: 0.515625, y: 0.578125 },\n  { x: 0.546875, y: 0.578125 },\n  { x: 0.546875, y: 0.578125 },\n  { x: 0.578125, y: 0.578125 },\n  { x: 0.578125, y: 0.578125 },\n  { x: 0.609375, y: 0.578125 },\n  { x: 0.609375, y: 0.578125 },\n  { x: 0.640625, y: 0.578125 },\n  { x: 0.640625, y: 0.578125 },\n  { x: 0.671875, y: 0.578125 },\n  { x: 0.671875, y: 0.578125 },\n  { x: 0.703125, y: 0.578125 },\n  { x: 0.703125, y: 0.578125 },\n  { x: 0.734375, y: 0.578125 },\n  { x: 0.734375, y: 0.578125 },\n  { x: 0.765625, y: 0.578125 },\n  { x: 0.765625, y: 0.578125 },\n  { x: 0.796875, y: 0.578125 },\n  { x: 0.796875, y: 0.578125 },\n  { x: 0.828125, y: 0.578125 },\n  { x: 0.828125, y: 0.578125 },\n  { x: 0.859375, y: 0.578125 },\n  { x: 0.859375, y: 0.578125 },\n  { x: 0.890625, y: 0.578125 },\n  { x: 0.890625, y: 0.578125 },\n  { x: 0.921875, y: 0.578125 },\n  { x: 0.921875, y: 0.578125 },\n  { x: 0.953125, y: 0.578125 },\n  { x: 0.953125, y: 0.578125 },\n  { x: 0.984375, y: 0.578125 },\n  { x: 0.984375, y: 0.578125 },\n  { x: 0.015625, y: 0.609375 },\n  { x: 0.015625, y: 0.609375 },\n  { x: 0.046875, y: 0.609375 },\n  { x: 0.046875, y: 0.609375 },\n  { x: 0.078125, y: 0.609375 },\n  { x: 0.078125, y: 0.609375 },\n  { x: 0.109375, y: 0.609375 },\n  { x: 0.109375, y: 0.609375 },\n  { x: 0.140625, y: 0.609375 },\n  { x: 0.140625, y: 0.609375 },\n  { x: 0.171875, y: 0.609375 },\n  { x: 0.171875, y: 0.609375 },\n  { x: 0.203125, y: 0.609375 },\n  { x: 0.203125, y: 0.609375 },\n  { x: 0.234375, y: 0.609375 },\n  { x: 0.234375, y: 0.609375 },\n  { x: 0.265625, y: 0.609375 },\n  { x: 0.265625, y: 0.609375 },\n  { x: 0.296875, y: 0.609375 },\n  { x: 0.296875, y: 0.609375 },\n  { x: 0.328125, y: 0.609375 },\n  { x: 0.328125, y: 0.609375 },\n  { x: 0.359375, y: 0.609375 },\n  { x: 0.359375, y: 0.609375 },\n  { x: 0.390625, y: 0.609375 },\n  { x: 0.390625, y: 0.609375 },\n  { x: 0.421875, y: 0.609375 },\n  { x: 0.421875, y: 0.609375 },\n  { x: 0.453125, y: 0.609375 },\n  { x: 0.453125, y: 0.609375 },\n  { x: 0.484375, y: 0.609375 },\n  { x: 0.484375, y: 0.609375 },\n  { x: 0.515625, y: 0.609375 },\n  { x: 0.515625, y: 0.609375 },\n  { x: 0.546875, y: 0.609375 },\n  { x: 0.546875, y: 0.609375 },\n  { x: 0.578125, y: 0.609375 },\n  { x: 0.578125, y: 0.609375 },\n  { x: 0.609375, y: 0.609375 },\n  { x: 0.609375, y: 0.609375 },\n  { x: 0.640625, y: 0.609375 },\n  { x: 0.640625, y: 0.609375 },\n  { x: 0.671875, y: 0.609375 },\n  { x: 0.671875, y: 0.609375 },\n  { x: 0.703125, y: 0.609375 },\n  { x: 0.703125, y: 0.609375 },\n  { x: 0.734375, y: 0.609375 },\n  { x: 0.734375, y: 0.609375 },\n  { x: 0.765625, y: 0.609375 },\n  { x: 0.765625, y: 0.609375 },\n  { x: 0.796875, y: 0.609375 },\n  { x: 0.796875, y: 0.609375 },\n  { x: 0.828125, y: 0.609375 },\n  { x: 0.828125, y: 0.609375 },\n  { x: 0.859375, y: 0.609375 },\n  { x: 0.859375, y: 0.609375 },\n  { x: 0.890625, y: 0.609375 },\n  { x: 0.890625, y: 0.609375 },\n  { x: 0.921875, y: 0.609375 },\n  { x: 0.921875, y: 0.609375 },\n  { x: 0.953125, y: 0.609375 },\n  { x: 0.953125, y: 0.609375 },\n  { x: 0.984375, y: 0.609375 },\n  { x: 0.984375, y: 0.609375 },\n  { x: 0.015625, y: 0.640625 },\n  { x: 0.015625, y: 0.640625 },\n  { x: 0.046875, y: 0.640625 },\n  { x: 0.046875, y: 0.640625 },\n  { x: 0.078125, y: 0.640625 },\n  { x: 0.078125, y: 0.640625 },\n  { x: 0.109375, y: 0.640625 },\n  { x: 0.109375, y: 0.640625 },\n  { x: 0.140625, y: 0.640625 },\n  { x: 0.140625, y: 0.640625 },\n  { x: 0.171875, y: 0.640625 },\n  { x: 0.171875, y: 0.640625 },\n  { x: 0.203125, y: 0.640625 },\n  { x: 0.203125, y: 0.640625 },\n  { x: 0.234375, y: 0.640625 },\n  { x: 0.234375, y: 0.640625 },\n  { x: 0.265625, y: 0.640625 },\n  { x: 0.265625, y: 0.640625 },\n  { x: 0.296875, y: 0.640625 },\n  { x: 0.296875, y: 0.640625 },\n  { x: 0.328125, y: 0.640625 },\n  { x: 0.328125, y: 0.640625 },\n  { x: 0.359375, y: 0.640625 },\n  { x: 0.359375, y: 0.640625 },\n  { x: 0.390625, y: 0.640625 },\n  { x: 0.390625, y: 0.640625 },\n  { x: 0.421875, y: 0.640625 },\n  { x: 0.421875, y: 0.640625 },\n  { x: 0.453125, y: 0.640625 },\n  { x: 0.453125, y: 0.640625 },\n  { x: 0.484375, y: 0.640625 },\n  { x: 0.484375, y: 0.640625 },\n  { x: 0.515625, y: 0.640625 },\n  { x: 0.515625, y: 0.640625 },\n  { x: 0.546875, y: 0.640625 },\n  { x: 0.546875, y: 0.640625 },\n  { x: 0.578125, y: 0.640625 },\n  { x: 0.578125, y: 0.640625 },\n  { x: 0.609375, y: 0.640625 },\n  { x: 0.609375, y: 0.640625 },\n  { x: 0.640625, y: 0.640625 },\n  { x: 0.640625, y: 0.640625 },\n  { x: 0.671875, y: 0.640625 },\n  { x: 0.671875, y: 0.640625 },\n  { x: 0.703125, y: 0.640625 },\n  { x: 0.703125, y: 0.640625 },\n  { x: 0.734375, y: 0.640625 },\n  { x: 0.734375, y: 0.640625 },\n  { x: 0.765625, y: 0.640625 },\n  { x: 0.765625, y: 0.640625 },\n  { x: 0.796875, y: 0.640625 },\n  { x: 0.796875, y: 0.640625 },\n  { x: 0.828125, y: 0.640625 },\n  { x: 0.828125, y: 0.640625 },\n  { x: 0.859375, y: 0.640625 },\n  { x: 0.859375, y: 0.640625 },\n  { x: 0.890625, y: 0.640625 },\n  { x: 0.890625, y: 0.640625 },\n  { x: 0.921875, y: 0.640625 },\n  { x: 0.921875, y: 0.640625 },\n  { x: 0.953125, y: 0.640625 },\n  { x: 0.953125, y: 0.640625 },\n  { x: 0.984375, y: 0.640625 },\n  { x: 0.984375, y: 0.640625 },\n  { x: 0.015625, y: 0.671875 },\n  { x: 0.015625, y: 0.671875 },\n  { x: 0.046875, y: 0.671875 },\n  { x: 0.046875, y: 0.671875 },\n  { x: 0.078125, y: 0.671875 },\n  { x: 0.078125, y: 0.671875 },\n  { x: 0.109375, y: 0.671875 },\n  { x: 0.109375, y: 0.671875 },\n  { x: 0.140625, y: 0.671875 },\n  { x: 0.140625, y: 0.671875 },\n  { x: 0.171875, y: 0.671875 },\n  { x: 0.171875, y: 0.671875 },\n  { x: 0.203125, y: 0.671875 },\n  { x: 0.203125, y: 0.671875 },\n  { x: 0.234375, y: 0.671875 },\n  { x: 0.234375, y: 0.671875 },\n  { x: 0.265625, y: 0.671875 },\n  { x: 0.265625, y: 0.671875 },\n  { x: 0.296875, y: 0.671875 },\n  { x: 0.296875, y: 0.671875 },\n  { x: 0.328125, y: 0.671875 },\n  { x: 0.328125, y: 0.671875 },\n  { x: 0.359375, y: 0.671875 },\n  { x: 0.359375, y: 0.671875 },\n  { x: 0.390625, y: 0.671875 },\n  { x: 0.390625, y: 0.671875 },\n  { x: 0.421875, y: 0.671875 },\n  { x: 0.421875, y: 0.671875 },\n  { x: 0.453125, y: 0.671875 },\n  { x: 0.453125, y: 0.671875 },\n  { x: 0.484375, y: 0.671875 },\n  { x: 0.484375, y: 0.671875 },\n  { x: 0.515625, y: 0.671875 },\n  { x: 0.515625, y: 0.671875 },\n  { x: 0.546875, y: 0.671875 },\n  { x: 0.546875, y: 0.671875 },\n  { x: 0.578125, y: 0.671875 },\n  { x: 0.578125, y: 0.671875 },\n  { x: 0.609375, y: 0.671875 },\n  { x: 0.609375, y: 0.671875 },\n  { x: 0.640625, y: 0.671875 },\n  { x: 0.640625, y: 0.671875 },\n  { x: 0.671875, y: 0.671875 },\n  { x: 0.671875, y: 0.671875 },\n  { x: 0.703125, y: 0.671875 },\n  { x: 0.703125, y: 0.671875 },\n  { x: 0.734375, y: 0.671875 },\n  { x: 0.734375, y: 0.671875 },\n  { x: 0.765625, y: 0.671875 },\n  { x: 0.765625, y: 0.671875 },\n  { x: 0.796875, y: 0.671875 },\n  { x: 0.796875, y: 0.671875 },\n  { x: 0.828125, y: 0.671875 },\n  { x: 0.828125, y: 0.671875 },\n  { x: 0.859375, y: 0.671875 },\n  { x: 0.859375, y: 0.671875 },\n  { x: 0.890625, y: 0.671875 },\n  { x: 0.890625, y: 0.671875 },\n  { x: 0.921875, y: 0.671875 },\n  { x: 0.921875, y: 0.671875 },\n  { x: 0.953125, y: 0.671875 },\n  { x: 0.953125, y: 0.671875 },\n  { x: 0.984375, y: 0.671875 },\n  { x: 0.984375, y: 0.671875 },\n  { x: 0.015625, y: 0.703125 },\n  { x: 0.015625, y: 0.703125 },\n  { x: 0.046875, y: 0.703125 },\n  { x: 0.046875, y: 0.703125 },\n  { x: 0.078125, y: 0.703125 },\n  { x: 0.078125, y: 0.703125 },\n  { x: 0.109375, y: 0.703125 },\n  { x: 0.109375, y: 0.703125 },\n  { x: 0.140625, y: 0.703125 },\n  { x: 0.140625, y: 0.703125 },\n  { x: 0.171875, y: 0.703125 },\n  { x: 0.171875, y: 0.703125 },\n  { x: 0.203125, y: 0.703125 },\n  { x: 0.203125, y: 0.703125 },\n  { x: 0.234375, y: 0.703125 },\n  { x: 0.234375, y: 0.703125 },\n  { x: 0.265625, y: 0.703125 },\n  { x: 0.265625, y: 0.703125 },\n  { x: 0.296875, y: 0.703125 },\n  { x: 0.296875, y: 0.703125 },\n  { x: 0.328125, y: 0.703125 },\n  { x: 0.328125, y: 0.703125 },\n  { x: 0.359375, y: 0.703125 },\n  { x: 0.359375, y: 0.703125 },\n  { x: 0.390625, y: 0.703125 },\n  { x: 0.390625, y: 0.703125 },\n  { x: 0.421875, y: 0.703125 },\n  { x: 0.421875, y: 0.703125 },\n  { x: 0.453125, y: 0.703125 },\n  { x: 0.453125, y: 0.703125 },\n  { x: 0.484375, y: 0.703125 },\n  { x: 0.484375, y: 0.703125 },\n  { x: 0.515625, y: 0.703125 },\n  { x: 0.515625, y: 0.703125 },\n  { x: 0.546875, y: 0.703125 },\n  { x: 0.546875, y: 0.703125 },\n  { x: 0.578125, y: 0.703125 },\n  { x: 0.578125, y: 0.703125 },\n  { x: 0.609375, y: 0.703125 },\n  { x: 0.609375, y: 0.703125 },\n  { x: 0.640625, y: 0.703125 },\n  { x: 0.640625, y: 0.703125 },\n  { x: 0.671875, y: 0.703125 },\n  { x: 0.671875, y: 0.703125 },\n  { x: 0.703125, y: 0.703125 },\n  { x: 0.703125, y: 0.703125 },\n  { x: 0.734375, y: 0.703125 },\n  { x: 0.734375, y: 0.703125 },\n  { x: 0.765625, y: 0.703125 },\n  { x: 0.765625, y: 0.703125 },\n  { x: 0.796875, y: 0.703125 },\n  { x: 0.796875, y: 0.703125 },\n  { x: 0.828125, y: 0.703125 },\n  { x: 0.828125, y: 0.703125 },\n  { x: 0.859375, y: 0.703125 },\n  { x: 0.859375, y: 0.703125 },\n  { x: 0.890625, y: 0.703125 },\n  { x: 0.890625, y: 0.703125 },\n  { x: 0.921875, y: 0.703125 },\n  { x: 0.921875, y: 0.703125 },\n  { x: 0.953125, y: 0.703125 },\n  { x: 0.953125, y: 0.703125 },\n  { x: 0.984375, y: 0.703125 },\n  { x: 0.984375, y: 0.703125 },\n  { x: 0.015625, y: 0.734375 },\n  { x: 0.015625, y: 0.734375 },\n  { x: 0.046875, y: 0.734375 },\n  { x: 0.046875, y: 0.734375 },\n  { x: 0.078125, y: 0.734375 },\n  { x: 0.078125, y: 0.734375 },\n  { x: 0.109375, y: 0.734375 },\n  { x: 0.109375, y: 0.734375 },\n  { x: 0.140625, y: 0.734375 },\n  { x: 0.140625, y: 0.734375 },\n  { x: 0.171875, y: 0.734375 },\n  { x: 0.171875, y: 0.734375 },\n  { x: 0.203125, y: 0.734375 },\n  { x: 0.203125, y: 0.734375 },\n  { x: 0.234375, y: 0.734375 },\n  { x: 0.234375, y: 0.734375 },\n  { x: 0.265625, y: 0.734375 },\n  { x: 0.265625, y: 0.734375 },\n  { x: 0.296875, y: 0.734375 },\n  { x: 0.296875, y: 0.734375 },\n  { x: 0.328125, y: 0.734375 },\n  { x: 0.328125, y: 0.734375 },\n  { x: 0.359375, y: 0.734375 },\n  { x: 0.359375, y: 0.734375 },\n  { x: 0.390625, y: 0.734375 },\n  { x: 0.390625, y: 0.734375 },\n  { x: 0.421875, y: 0.734375 },\n  { x: 0.421875, y: 0.734375 },\n  { x: 0.453125, y: 0.734375 },\n  { x: 0.453125, y: 0.734375 },\n  { x: 0.484375, y: 0.734375 },\n  { x: 0.484375, y: 0.734375 },\n  { x: 0.515625, y: 0.734375 },\n  { x: 0.515625, y: 0.734375 },\n  { x: 0.546875, y: 0.734375 },\n  { x: 0.546875, y: 0.734375 },\n  { x: 0.578125, y: 0.734375 },\n  { x: 0.578125, y: 0.734375 },\n  { x: 0.609375, y: 0.734375 },\n  { x: 0.609375, y: 0.734375 },\n  { x: 0.640625, y: 0.734375 },\n  { x: 0.640625, y: 0.734375 },\n  { x: 0.671875, y: 0.734375 },\n  { x: 0.671875, y: 0.734375 },\n  { x: 0.703125, y: 0.734375 },\n  { x: 0.703125, y: 0.734375 },\n  { x: 0.734375, y: 0.734375 },\n  { x: 0.734375, y: 0.734375 },\n  { x: 0.765625, y: 0.734375 },\n  { x: 0.765625, y: 0.734375 },\n  { x: 0.796875, y: 0.734375 },\n  { x: 0.796875, y: 0.734375 },\n  { x: 0.828125, y: 0.734375 },\n  { x: 0.828125, y: 0.734375 },\n  { x: 0.859375, y: 0.734375 },\n  { x: 0.859375, y: 0.734375 },\n  { x: 0.890625, y: 0.734375 },\n  { x: 0.890625, y: 0.734375 },\n  { x: 0.921875, y: 0.734375 },\n  { x: 0.921875, y: 0.734375 },\n  { x: 0.953125, y: 0.734375 },\n  { x: 0.953125, y: 0.734375 },\n  { x: 0.984375, y: 0.734375 },\n  { x: 0.984375, y: 0.734375 },\n  { x: 0.015625, y: 0.765625 },\n  { x: 0.015625, y: 0.765625 },\n  { x: 0.046875, y: 0.765625 },\n  { x: 0.046875, y: 0.765625 },\n  { x: 0.078125, y: 0.765625 },\n  { x: 0.078125, y: 0.765625 },\n  { x: 0.109375, y: 0.765625 },\n  { x: 0.109375, y: 0.765625 },\n  { x: 0.140625, y: 0.765625 },\n  { x: 0.140625, y: 0.765625 },\n  { x: 0.171875, y: 0.765625 },\n  { x: 0.171875, y: 0.765625 },\n  { x: 0.203125, y: 0.765625 },\n  { x: 0.203125, y: 0.765625 },\n  { x: 0.234375, y: 0.765625 },\n  { x: 0.234375, y: 0.765625 },\n  { x: 0.265625, y: 0.765625 },\n  { x: 0.265625, y: 0.765625 },\n  { x: 0.296875, y: 0.765625 },\n  { x: 0.296875, y: 0.765625 },\n  { x: 0.328125, y: 0.765625 },\n  { x: 0.328125, y: 0.765625 },\n  { x: 0.359375, y: 0.765625 },\n  { x: 0.359375, y: 0.765625 },\n  { x: 0.390625, y: 0.765625 },\n  { x: 0.390625, y: 0.765625 },\n  { x: 0.421875, y: 0.765625 },\n  { x: 0.421875, y: 0.765625 },\n  { x: 0.453125, y: 0.765625 },\n  { x: 0.453125, y: 0.765625 },\n  { x: 0.484375, y: 0.765625 },\n  { x: 0.484375, y: 0.765625 },\n  { x: 0.515625, y: 0.765625 },\n  { x: 0.515625, y: 0.765625 },\n  { x: 0.546875, y: 0.765625 },\n  { x: 0.546875, y: 0.765625 },\n  { x: 0.578125, y: 0.765625 },\n  { x: 0.578125, y: 0.765625 },\n  { x: 0.609375, y: 0.765625 },\n  { x: 0.609375, y: 0.765625 },\n  { x: 0.640625, y: 0.765625 },\n  { x: 0.640625, y: 0.765625 },\n  { x: 0.671875, y: 0.765625 },\n  { x: 0.671875, y: 0.765625 },\n  { x: 0.703125, y: 0.765625 },\n  { x: 0.703125, y: 0.765625 },\n  { x: 0.734375, y: 0.765625 },\n  { x: 0.734375, y: 0.765625 },\n  { x: 0.765625, y: 0.765625 },\n  { x: 0.765625, y: 0.765625 },\n  { x: 0.796875, y: 0.765625 },\n  { x: 0.796875, y: 0.765625 },\n  { x: 0.828125, y: 0.765625 },\n  { x: 0.828125, y: 0.765625 },\n  { x: 0.859375, y: 0.765625 },\n  { x: 0.859375, y: 0.765625 },\n  { x: 0.890625, y: 0.765625 },\n  { x: 0.890625, y: 0.765625 },\n  { x: 0.921875, y: 0.765625 },\n  { x: 0.921875, y: 0.765625 },\n  { x: 0.953125, y: 0.765625 },\n  { x: 0.953125, y: 0.765625 },\n  { x: 0.984375, y: 0.765625 },\n  { x: 0.984375, y: 0.765625 },\n  { x: 0.015625, y: 0.796875 },\n  { x: 0.015625, y: 0.796875 },\n  { x: 0.046875, y: 0.796875 },\n  { x: 0.046875, y: 0.796875 },\n  { x: 0.078125, y: 0.796875 },\n  { x: 0.078125, y: 0.796875 },\n  { x: 0.109375, y: 0.796875 },\n  { x: 0.109375, y: 0.796875 },\n  { x: 0.140625, y: 0.796875 },\n  { x: 0.140625, y: 0.796875 },\n  { x: 0.171875, y: 0.796875 },\n  { x: 0.171875, y: 0.796875 },\n  { x: 0.203125, y: 0.796875 },\n  { x: 0.203125, y: 0.796875 },\n  { x: 0.234375, y: 0.796875 },\n  { x: 0.234375, y: 0.796875 },\n  { x: 0.265625, y: 0.796875 },\n  { x: 0.265625, y: 0.796875 },\n  { x: 0.296875, y: 0.796875 },\n  { x: 0.296875, y: 0.796875 },\n  { x: 0.328125, y: 0.796875 },\n  { x: 0.328125, y: 0.796875 },\n  { x: 0.359375, y: 0.796875 },\n  { x: 0.359375, y: 0.796875 },\n  { x: 0.390625, y: 0.796875 },\n  { x: 0.390625, y: 0.796875 },\n  { x: 0.421875, y: 0.796875 },\n  { x: 0.421875, y: 0.796875 },\n  { x: 0.453125, y: 0.796875 },\n  { x: 0.453125, y: 0.796875 },\n  { x: 0.484375, y: 0.796875 },\n  { x: 0.484375, y: 0.796875 },\n  { x: 0.515625, y: 0.796875 },\n  { x: 0.515625, y: 0.796875 },\n  { x: 0.546875, y: 0.796875 },\n  { x: 0.546875, y: 0.796875 },\n  { x: 0.578125, y: 0.796875 },\n  { x: 0.578125, y: 0.796875 },\n  { x: 0.609375, y: 0.796875 },\n  { x: 0.609375, y: 0.796875 },\n  { x: 0.640625, y: 0.796875 },\n  { x: 0.640625, y: 0.796875 },\n  { x: 0.671875, y: 0.796875 },\n  { x: 0.671875, y: 0.796875 },\n  { x: 0.703125, y: 0.796875 },\n  { x: 0.703125, y: 0.796875 },\n  { x: 0.734375, y: 0.796875 },\n  { x: 0.734375, y: 0.796875 },\n  { x: 0.765625, y: 0.796875 },\n  { x: 0.765625, y: 0.796875 },\n  { x: 0.796875, y: 0.796875 },\n  { x: 0.796875, y: 0.796875 },\n  { x: 0.828125, y: 0.796875 },\n  { x: 0.828125, y: 0.796875 },\n  { x: 0.859375, y: 0.796875 },\n  { x: 0.859375, y: 0.796875 },\n  { x: 0.890625, y: 0.796875 },\n  { x: 0.890625, y: 0.796875 },\n  { x: 0.921875, y: 0.796875 },\n  { x: 0.921875, y: 0.796875 },\n  { x: 0.953125, y: 0.796875 },\n  { x: 0.953125, y: 0.796875 },\n  { x: 0.984375, y: 0.796875 },\n  { x: 0.984375, y: 0.796875 },\n  { x: 0.015625, y: 0.828125 },\n  { x: 0.015625, y: 0.828125 },\n  { x: 0.046875, y: 0.828125 },\n  { x: 0.046875, y: 0.828125 },\n  { x: 0.078125, y: 0.828125 },\n  { x: 0.078125, y: 0.828125 },\n  { x: 0.109375, y: 0.828125 },\n  { x: 0.109375, y: 0.828125 },\n  { x: 0.140625, y: 0.828125 },\n  { x: 0.140625, y: 0.828125 },\n  { x: 0.171875, y: 0.828125 },\n  { x: 0.171875, y: 0.828125 },\n  { x: 0.203125, y: 0.828125 },\n  { x: 0.203125, y: 0.828125 },\n  { x: 0.234375, y: 0.828125 },\n  { x: 0.234375, y: 0.828125 },\n  { x: 0.265625, y: 0.828125 },\n  { x: 0.265625, y: 0.828125 },\n  { x: 0.296875, y: 0.828125 },\n  { x: 0.296875, y: 0.828125 },\n  { x: 0.328125, y: 0.828125 },\n  { x: 0.328125, y: 0.828125 },\n  { x: 0.359375, y: 0.828125 },\n  { x: 0.359375, y: 0.828125 },\n  { x: 0.390625, y: 0.828125 },\n  { x: 0.390625, y: 0.828125 },\n  { x: 0.421875, y: 0.828125 },\n  { x: 0.421875, y: 0.828125 },\n  { x: 0.453125, y: 0.828125 },\n  { x: 0.453125, y: 0.828125 },\n  { x: 0.484375, y: 0.828125 },\n  { x: 0.484375, y: 0.828125 },\n  { x: 0.515625, y: 0.828125 },\n  { x: 0.515625, y: 0.828125 },\n  { x: 0.546875, y: 0.828125 },\n  { x: 0.546875, y: 0.828125 },\n  { x: 0.578125, y: 0.828125 },\n  { x: 0.578125, y: 0.828125 },\n  { x: 0.609375, y: 0.828125 },\n  { x: 0.609375, y: 0.828125 },\n  { x: 0.640625, y: 0.828125 },\n  { x: 0.640625, y: 0.828125 },\n  { x: 0.671875, y: 0.828125 },\n  { x: 0.671875, y: 0.828125 },\n  { x: 0.703125, y: 0.828125 },\n  { x: 0.703125, y: 0.828125 },\n  { x: 0.734375, y: 0.828125 },\n  { x: 0.734375, y: 0.828125 },\n  { x: 0.765625, y: 0.828125 },\n  { x: 0.765625, y: 0.828125 },\n  { x: 0.796875, y: 0.828125 },\n  { x: 0.796875, y: 0.828125 },\n  { x: 0.828125, y: 0.828125 },\n  { x: 0.828125, y: 0.828125 },\n  { x: 0.859375, y: 0.828125 },\n  { x: 0.859375, y: 0.828125 },\n  { x: 0.890625, y: 0.828125 },\n  { x: 0.890625, y: 0.828125 },\n  { x: 0.921875, y: 0.828125 },\n  { x: 0.921875, y: 0.828125 },\n  { x: 0.953125, y: 0.828125 },\n  { x: 0.953125, y: 0.828125 },\n  { x: 0.984375, y: 0.828125 },\n  { x: 0.984375, y: 0.828125 },\n  { x: 0.015625, y: 0.859375 },\n  { x: 0.015625, y: 0.859375 },\n  { x: 0.046875, y: 0.859375 },\n  { x: 0.046875, y: 0.859375 },\n  { x: 0.078125, y: 0.859375 },\n  { x: 0.078125, y: 0.859375 },\n  { x: 0.109375, y: 0.859375 },\n  { x: 0.109375, y: 0.859375 },\n  { x: 0.140625, y: 0.859375 },\n  { x: 0.140625, y: 0.859375 },\n  { x: 0.171875, y: 0.859375 },\n  { x: 0.171875, y: 0.859375 },\n  { x: 0.203125, y: 0.859375 },\n  { x: 0.203125, y: 0.859375 },\n  { x: 0.234375, y: 0.859375 },\n  { x: 0.234375, y: 0.859375 },\n  { x: 0.265625, y: 0.859375 },\n  { x: 0.265625, y: 0.859375 },\n  { x: 0.296875, y: 0.859375 },\n  { x: 0.296875, y: 0.859375 },\n  { x: 0.328125, y: 0.859375 },\n  { x: 0.328125, y: 0.859375 },\n  { x: 0.359375, y: 0.859375 },\n  { x: 0.359375, y: 0.859375 },\n  { x: 0.390625, y: 0.859375 },\n  { x: 0.390625, y: 0.859375 },\n  { x: 0.421875, y: 0.859375 },\n  { x: 0.421875, y: 0.859375 },\n  { x: 0.453125, y: 0.859375 },\n  { x: 0.453125, y: 0.859375 },\n  { x: 0.484375, y: 0.859375 },\n  { x: 0.484375, y: 0.859375 },\n  { x: 0.515625, y: 0.859375 },\n  { x: 0.515625, y: 0.859375 },\n  { x: 0.546875, y: 0.859375 },\n  { x: 0.546875, y: 0.859375 },\n  { x: 0.578125, y: 0.859375 },\n  { x: 0.578125, y: 0.859375 },\n  { x: 0.609375, y: 0.859375 },\n  { x: 0.609375, y: 0.859375 },\n  { x: 0.640625, y: 0.859375 },\n  { x: 0.640625, y: 0.859375 },\n  { x: 0.671875, y: 0.859375 },\n  { x: 0.671875, y: 0.859375 },\n  { x: 0.703125, y: 0.859375 },\n  { x: 0.703125, y: 0.859375 },\n  { x: 0.734375, y: 0.859375 },\n  { x: 0.734375, y: 0.859375 },\n  { x: 0.765625, y: 0.859375 },\n  { x: 0.765625, y: 0.859375 },\n  { x: 0.796875, y: 0.859375 },\n  { x: 0.796875, y: 0.859375 },\n  { x: 0.828125, y: 0.859375 },\n  { x: 0.828125, y: 0.859375 },\n  { x: 0.859375, y: 0.859375 },\n  { x: 0.859375, y: 0.859375 },\n  { x: 0.890625, y: 0.859375 },\n  { x: 0.890625, y: 0.859375 },\n  { x: 0.921875, y: 0.859375 },\n  { x: 0.921875, y: 0.859375 },\n  { x: 0.953125, y: 0.859375 },\n  { x: 0.953125, y: 0.859375 },\n  { x: 0.984375, y: 0.859375 },\n  { x: 0.984375, y: 0.859375 },\n  { x: 0.015625, y: 0.890625 },\n  { x: 0.015625, y: 0.890625 },\n  { x: 0.046875, y: 0.890625 },\n  { x: 0.046875, y: 0.890625 },\n  { x: 0.078125, y: 0.890625 },\n  { x: 0.078125, y: 0.890625 },\n  { x: 0.109375, y: 0.890625 },\n  { x: 0.109375, y: 0.890625 },\n  { x: 0.140625, y: 0.890625 },\n  { x: 0.140625, y: 0.890625 },\n  { x: 0.171875, y: 0.890625 },\n  { x: 0.171875, y: 0.890625 },\n  { x: 0.203125, y: 0.890625 },\n  { x: 0.203125, y: 0.890625 },\n  { x: 0.234375, y: 0.890625 },\n  { x: 0.234375, y: 0.890625 },\n  { x: 0.265625, y: 0.890625 },\n  { x: 0.265625, y: 0.890625 },\n  { x: 0.296875, y: 0.890625 },\n  { x: 0.296875, y: 0.890625 },\n  { x: 0.328125, y: 0.890625 },\n  { x: 0.328125, y: 0.890625 },\n  { x: 0.359375, y: 0.890625 },\n  { x: 0.359375, y: 0.890625 },\n  { x: 0.390625, y: 0.890625 },\n  { x: 0.390625, y: 0.890625 },\n  { x: 0.421875, y: 0.890625 },\n  { x: 0.421875, y: 0.890625 },\n  { x: 0.453125, y: 0.890625 },\n  { x: 0.453125, y: 0.890625 },\n  { x: 0.484375, y: 0.890625 },\n  { x: 0.484375, y: 0.890625 },\n  { x: 0.515625, y: 0.890625 },\n  { x: 0.515625, y: 0.890625 },\n  { x: 0.546875, y: 0.890625 },\n  { x: 0.546875, y: 0.890625 },\n  { x: 0.578125, y: 0.890625 },\n  { x: 0.578125, y: 0.890625 },\n  { x: 0.609375, y: 0.890625 },\n  { x: 0.609375, y: 0.890625 },\n  { x: 0.640625, y: 0.890625 },\n  { x: 0.640625, y: 0.890625 },\n  { x: 0.671875, y: 0.890625 },\n  { x: 0.671875, y: 0.890625 },\n  { x: 0.703125, y: 0.890625 },\n  { x: 0.703125, y: 0.890625 },\n  { x: 0.734375, y: 0.890625 },\n  { x: 0.734375, y: 0.890625 },\n  { x: 0.765625, y: 0.890625 },\n  { x: 0.765625, y: 0.890625 },\n  { x: 0.796875, y: 0.890625 },\n  { x: 0.796875, y: 0.890625 },\n  { x: 0.828125, y: 0.890625 },\n  { x: 0.828125, y: 0.890625 },\n  { x: 0.859375, y: 0.890625 },\n  { x: 0.859375, y: 0.890625 },\n  { x: 0.890625, y: 0.890625 },\n  { x: 0.890625, y: 0.890625 },\n  { x: 0.921875, y: 0.890625 },\n  { x: 0.921875, y: 0.890625 },\n  { x: 0.953125, y: 0.890625 },\n  { x: 0.953125, y: 0.890625 },\n  { x: 0.984375, y: 0.890625 },\n  { x: 0.984375, y: 0.890625 },\n  { x: 0.015625, y: 0.921875 },\n  { x: 0.015625, y: 0.921875 },\n  { x: 0.046875, y: 0.921875 },\n  { x: 0.046875, y: 0.921875 },\n  { x: 0.078125, y: 0.921875 },\n  { x: 0.078125, y: 0.921875 },\n  { x: 0.109375, y: 0.921875 },\n  { x: 0.109375, y: 0.921875 },\n  { x: 0.140625, y: 0.921875 },\n  { x: 0.140625, y: 0.921875 },\n  { x: 0.171875, y: 0.921875 },\n  { x: 0.171875, y: 0.921875 },\n  { x: 0.203125, y: 0.921875 },\n  { x: 0.203125, y: 0.921875 },\n  { x: 0.234375, y: 0.921875 },\n  { x: 0.234375, y: 0.921875 },\n  { x: 0.265625, y: 0.921875 },\n  { x: 0.265625, y: 0.921875 },\n  { x: 0.296875, y: 0.921875 },\n  { x: 0.296875, y: 0.921875 },\n  { x: 0.328125, y: 0.921875 },\n  { x: 0.328125, y: 0.921875 },\n  { x: 0.359375, y: 0.921875 },\n  { x: 0.359375, y: 0.921875 },\n  { x: 0.390625, y: 0.921875 },\n  { x: 0.390625, y: 0.921875 },\n  { x: 0.421875, y: 0.921875 },\n  { x: 0.421875, y: 0.921875 },\n  { x: 0.453125, y: 0.921875 },\n  { x: 0.453125, y: 0.921875 },\n  { x: 0.484375, y: 0.921875 },\n  { x: 0.484375, y: 0.921875 },\n  { x: 0.515625, y: 0.921875 },\n  { x: 0.515625, y: 0.921875 },\n  { x: 0.546875, y: 0.921875 },\n  { x: 0.546875, y: 0.921875 },\n  { x: 0.578125, y: 0.921875 },\n  { x: 0.578125, y: 0.921875 },\n  { x: 0.609375, y: 0.921875 },\n  { x: 0.609375, y: 0.921875 },\n  { x: 0.640625, y: 0.921875 },\n  { x: 0.640625, y: 0.921875 },\n  { x: 0.671875, y: 0.921875 },\n  { x: 0.671875, y: 0.921875 },\n  { x: 0.703125, y: 0.921875 },\n  { x: 0.703125, y: 0.921875 },\n  { x: 0.734375, y: 0.921875 },\n  { x: 0.734375, y: 0.921875 },\n  { x: 0.765625, y: 0.921875 },\n  { x: 0.765625, y: 0.921875 },\n  { x: 0.796875, y: 0.921875 },\n  { x: 0.796875, y: 0.921875 },\n  { x: 0.828125, y: 0.921875 },\n  { x: 0.828125, y: 0.921875 },\n  { x: 0.859375, y: 0.921875 },\n  { x: 0.859375, y: 0.921875 },\n  { x: 0.890625, y: 0.921875 },\n  { x: 0.890625, y: 0.921875 },\n  { x: 0.921875, y: 0.921875 },\n  { x: 0.921875, y: 0.921875 },\n  { x: 0.953125, y: 0.921875 },\n  { x: 0.953125, y: 0.921875 },\n  { x: 0.984375, y: 0.921875 },\n  { x: 0.984375, y: 0.921875 },\n  { x: 0.015625, y: 0.953125 },\n  { x: 0.015625, y: 0.953125 },\n  { x: 0.046875, y: 0.953125 },\n  { x: 0.046875, y: 0.953125 },\n  { x: 0.078125, y: 0.953125 },\n  { x: 0.078125, y: 0.953125 },\n  { x: 0.109375, y: 0.953125 },\n  { x: 0.109375, y: 0.953125 },\n  { x: 0.140625, y: 0.953125 },\n  { x: 0.140625, y: 0.953125 },\n  { x: 0.171875, y: 0.953125 },\n  { x: 0.171875, y: 0.953125 },\n  { x: 0.203125, y: 0.953125 },\n  { x: 0.203125, y: 0.953125 },\n  { x: 0.234375, y: 0.953125 },\n  { x: 0.234375, y: 0.953125 },\n  { x: 0.265625, y: 0.953125 },\n  { x: 0.265625, y: 0.953125 },\n  { x: 0.296875, y: 0.953125 },\n  { x: 0.296875, y: 0.953125 },\n  { x: 0.328125, y: 0.953125 },\n  { x: 0.328125, y: 0.953125 },\n  { x: 0.359375, y: 0.953125 },\n  { x: 0.359375, y: 0.953125 },\n  { x: 0.390625, y: 0.953125 },\n  { x: 0.390625, y: 0.953125 },\n  { x: 0.421875, y: 0.953125 },\n  { x: 0.421875, y: 0.953125 },\n  { x: 0.453125, y: 0.953125 },\n  { x: 0.453125, y: 0.953125 },\n  { x: 0.484375, y: 0.953125 },\n  { x: 0.484375, y: 0.953125 },\n  { x: 0.515625, y: 0.953125 },\n  { x: 0.515625, y: 0.953125 },\n  { x: 0.546875, y: 0.953125 },\n  { x: 0.546875, y: 0.953125 },\n  { x: 0.578125, y: 0.953125 },\n  { x: 0.578125, y: 0.953125 },\n  { x: 0.609375, y: 0.953125 },\n  { x: 0.609375, y: 0.953125 },\n  { x: 0.640625, y: 0.953125 },\n  { x: 0.640625, y: 0.953125 },\n  { x: 0.671875, y: 0.953125 },\n  { x: 0.671875, y: 0.953125 },\n  { x: 0.703125, y: 0.953125 },\n  { x: 0.703125, y: 0.953125 },\n  { x: 0.734375, y: 0.953125 },\n  { x: 0.734375, y: 0.953125 },\n  { x: 0.765625, y: 0.953125 },\n  { x: 0.765625, y: 0.953125 },\n  { x: 0.796875, y: 0.953125 },\n  { x: 0.796875, y: 0.953125 },\n  { x: 0.828125, y: 0.953125 },\n  { x: 0.828125, y: 0.953125 },\n  { x: 0.859375, y: 0.953125 },\n  { x: 0.859375, y: 0.953125 },\n  { x: 0.890625, y: 0.953125 },\n  { x: 0.890625, y: 0.953125 },\n  { x: 0.921875, y: 0.953125 },\n  { x: 0.921875, y: 0.953125 },\n  { x: 0.953125, y: 0.953125 },\n  { x: 0.953125, y: 0.953125 },\n  { x: 0.984375, y: 0.953125 },\n  { x: 0.984375, y: 0.953125 },\n  { x: 0.015625, y: 0.984375 },\n  { x: 0.015625, y: 0.984375 },\n  { x: 0.046875, y: 0.984375 },\n  { x: 0.046875, y: 0.984375 },\n  { x: 0.078125, y: 0.984375 },\n  { x: 0.078125, y: 0.984375 },\n  { x: 0.109375, y: 0.984375 },\n  { x: 0.109375, y: 0.984375 },\n  { x: 0.140625, y: 0.984375 },\n  { x: 0.140625, y: 0.984375 },\n  { x: 0.171875, y: 0.984375 },\n  { x: 0.171875, y: 0.984375 },\n  { x: 0.203125, y: 0.984375 },\n  { x: 0.203125, y: 0.984375 },\n  { x: 0.234375, y: 0.984375 },\n  { x: 0.234375, y: 0.984375 },\n  { x: 0.265625, y: 0.984375 },\n  { x: 0.265625, y: 0.984375 },\n  { x: 0.296875, y: 0.984375 },\n  { x: 0.296875, y: 0.984375 },\n  { x: 0.328125, y: 0.984375 },\n  { x: 0.328125, y: 0.984375 },\n  { x: 0.359375, y: 0.984375 },\n  { x: 0.359375, y: 0.984375 },\n  { x: 0.390625, y: 0.984375 },\n  { x: 0.390625, y: 0.984375 },\n  { x: 0.421875, y: 0.984375 },\n  { x: 0.421875, y: 0.984375 },\n  { x: 0.453125, y: 0.984375 },\n  { x: 0.453125, y: 0.984375 },\n  { x: 0.484375, y: 0.984375 },\n  { x: 0.484375, y: 0.984375 },\n  { x: 0.515625, y: 0.984375 },\n  { x: 0.515625, y: 0.984375 },\n  { x: 0.546875, y: 0.984375 },\n  { x: 0.546875, y: 0.984375 },\n  { x: 0.578125, y: 0.984375 },\n  { x: 0.578125, y: 0.984375 },\n  { x: 0.609375, y: 0.984375 },\n  { x: 0.609375, y: 0.984375 },\n  { x: 0.640625, y: 0.984375 },\n  { x: 0.640625, y: 0.984375 },\n  { x: 0.671875, y: 0.984375 },\n  { x: 0.671875, y: 0.984375 },\n  { x: 0.703125, y: 0.984375 },\n  { x: 0.703125, y: 0.984375 },\n  { x: 0.734375, y: 0.984375 },\n  { x: 0.734375, y: 0.984375 },\n  { x: 0.765625, y: 0.984375 },\n  { x: 0.765625, y: 0.984375 },\n  { x: 0.796875, y: 0.984375 },\n  { x: 0.796875, y: 0.984375 },\n  { x: 0.828125, y: 0.984375 },\n  { x: 0.828125, y: 0.984375 },\n  { x: 0.859375, y: 0.984375 },\n  { x: 0.859375, y: 0.984375 },\n  { x: 0.890625, y: 0.984375 },\n  { x: 0.890625, y: 0.984375 },\n  { x: 0.921875, y: 0.984375 },\n  { x: 0.921875, y: 0.984375 },\n  { x: 0.953125, y: 0.984375 },\n  { x: 0.953125, y: 0.984375 },\n  { x: 0.984375, y: 0.984375 },\n  { x: 0.984375, y: 0.984375 },\n  { x: 0.03125, y: 0.03125 },\n  { x: 0.03125, y: 0.03125 },\n  { x: 0.09375, y: 0.03125 },\n  { x: 0.09375, y: 0.03125 },\n  { x: 0.15625, y: 0.03125 },\n  { x: 0.15625, y: 0.03125 },\n  { x: 0.21875, y: 0.03125 },\n  { x: 0.21875, y: 0.03125 },\n  { x: 0.28125, y: 0.03125 },\n  { x: 0.28125, y: 0.03125 },\n  { x: 0.34375, y: 0.03125 },\n  { x: 0.34375, y: 0.03125 },\n  { x: 0.40625, y: 0.03125 },\n  { x: 0.40625, y: 0.03125 },\n  { x: 0.46875, y: 0.03125 },\n  { x: 0.46875, y: 0.03125 },\n  { x: 0.53125, y: 0.03125 },\n  { x: 0.53125, y: 0.03125 },\n  { x: 0.59375, y: 0.03125 },\n  { x: 0.59375, y: 0.03125 },\n  { x: 0.65625, y: 0.03125 },\n  { x: 0.65625, y: 0.03125 },\n  { x: 0.71875, y: 0.03125 },\n  { x: 0.71875, y: 0.03125 },\n  { x: 0.78125, y: 0.03125 },\n  { x: 0.78125, y: 0.03125 },\n  { x: 0.84375, y: 0.03125 },\n  { x: 0.84375, y: 0.03125 },\n  { x: 0.90625, y: 0.03125 },\n  { x: 0.90625, y: 0.03125 },\n  { x: 0.96875, y: 0.03125 },\n  { x: 0.96875, y: 0.03125 },\n  { x: 0.03125, y: 0.09375 },\n  { x: 0.03125, y: 0.09375 },\n  { x: 0.09375, y: 0.09375 },\n  { x: 0.09375, y: 0.09375 },\n  { x: 0.15625, y: 0.09375 },\n  { x: 0.15625, y: 0.09375 },\n  { x: 0.21875, y: 0.09375 },\n  { x: 0.21875, y: 0.09375 },\n  { x: 0.28125, y: 0.09375 },\n  { x: 0.28125, y: 0.09375 },\n  { x: 0.34375, y: 0.09375 },\n  { x: 0.34375, y: 0.09375 },\n  { x: 0.40625, y: 0.09375 },\n  { x: 0.40625, y: 0.09375 },\n  { x: 0.46875, y: 0.09375 },\n  { x: 0.46875, y: 0.09375 },\n  { x: 0.53125, y: 0.09375 },\n  { x: 0.53125, y: 0.09375 },\n  { x: 0.59375, y: 0.09375 },\n  { x: 0.59375, y: 0.09375 },\n  { x: 0.65625, y: 0.09375 },\n  { x: 0.65625, y: 0.09375 },\n  { x: 0.71875, y: 0.09375 },\n  { x: 0.71875, y: 0.09375 },\n  { x: 0.78125, y: 0.09375 },\n  { x: 0.78125, y: 0.09375 },\n  { x: 0.84375, y: 0.09375 },\n  { x: 0.84375, y: 0.09375 },\n  { x: 0.90625, y: 0.09375 },\n  { x: 0.90625, y: 0.09375 },\n  { x: 0.96875, y: 0.09375 },\n  { x: 0.96875, y: 0.09375 },\n  { x: 0.03125, y: 0.15625 },\n  { x: 0.03125, y: 0.15625 },\n  { x: 0.09375, y: 0.15625 },\n  { x: 0.09375, y: 0.15625 },\n  { x: 0.15625, y: 0.15625 },\n  { x: 0.15625, y: 0.15625 },\n  { x: 0.21875, y: 0.15625 },\n  { x: 0.21875, y: 0.15625 },\n  { x: 0.28125, y: 0.15625 },\n  { x: 0.28125, y: 0.15625 },\n  { x: 0.34375, y: 0.15625 },\n  { x: 0.34375, y: 0.15625 },\n  { x: 0.40625, y: 0.15625 },\n  { x: 0.40625, y: 0.15625 },\n  { x: 0.46875, y: 0.15625 },\n  { x: 0.46875, y: 0.15625 },\n  { x: 0.53125, y: 0.15625 },\n  { x: 0.53125, y: 0.15625 },\n  { x: 0.59375, y: 0.15625 },\n  { x: 0.59375, y: 0.15625 },\n  { x: 0.65625, y: 0.15625 },\n  { x: 0.65625, y: 0.15625 },\n  { x: 0.71875, y: 0.15625 },\n  { x: 0.71875, y: 0.15625 },\n  { x: 0.78125, y: 0.15625 },\n  { x: 0.78125, y: 0.15625 },\n  { x: 0.84375, y: 0.15625 },\n  { x: 0.84375, y: 0.15625 },\n  { x: 0.90625, y: 0.15625 },\n  { x: 0.90625, y: 0.15625 },\n  { x: 0.96875, y: 0.15625 },\n  { x: 0.96875, y: 0.15625 },\n  { x: 0.03125, y: 0.21875 },\n  { x: 0.03125, y: 0.21875 },\n  { x: 0.09375, y: 0.21875 },\n  { x: 0.09375, y: 0.21875 },\n  { x: 0.15625, y: 0.21875 },\n  { x: 0.15625, y: 0.21875 },\n  { x: 0.21875, y: 0.21875 },\n  { x: 0.21875, y: 0.21875 },\n  { x: 0.28125, y: 0.21875 },\n  { x: 0.28125, y: 0.21875 },\n  { x: 0.34375, y: 0.21875 },\n  { x: 0.34375, y: 0.21875 },\n  { x: 0.40625, y: 0.21875 },\n  { x: 0.40625, y: 0.21875 },\n  { x: 0.46875, y: 0.21875 },\n  { x: 0.46875, y: 0.21875 },\n  { x: 0.53125, y: 0.21875 },\n  { x: 0.53125, y: 0.21875 },\n  { x: 0.59375, y: 0.21875 },\n  { x: 0.59375, y: 0.21875 },\n  { x: 0.65625, y: 0.21875 },\n  { x: 0.65625, y: 0.21875 },\n  { x: 0.71875, y: 0.21875 },\n  { x: 0.71875, y: 0.21875 },\n  { x: 0.78125, y: 0.21875 },\n  { x: 0.78125, y: 0.21875 },\n  { x: 0.84375, y: 0.21875 },\n  { x: 0.84375, y: 0.21875 },\n  { x: 0.90625, y: 0.21875 },\n  { x: 0.90625, y: 0.21875 },\n  { x: 0.96875, y: 0.21875 },\n  { x: 0.96875, y: 0.21875 },\n  { x: 0.03125, y: 0.28125 },\n  { x: 0.03125, y: 0.28125 },\n  { x: 0.09375, y: 0.28125 },\n  { x: 0.09375, y: 0.28125 },\n  { x: 0.15625, y: 0.28125 },\n  { x: 0.15625, y: 0.28125 },\n  { x: 0.21875, y: 0.28125 },\n  { x: 0.21875, y: 0.28125 },\n  { x: 0.28125, y: 0.28125 },\n  { x: 0.28125, y: 0.28125 },\n  { x: 0.34375, y: 0.28125 },\n  { x: 0.34375, y: 0.28125 },\n  { x: 0.40625, y: 0.28125 },\n  { x: 0.40625, y: 0.28125 },\n  { x: 0.46875, y: 0.28125 },\n  { x: 0.46875, y: 0.28125 },\n  { x: 0.53125, y: 0.28125 },\n  { x: 0.53125, y: 0.28125 },\n  { x: 0.59375, y: 0.28125 },\n  { x: 0.59375, y: 0.28125 },\n  { x: 0.65625, y: 0.28125 },\n  { x: 0.65625, y: 0.28125 },\n  { x: 0.71875, y: 0.28125 },\n  { x: 0.71875, y: 0.28125 },\n  { x: 0.78125, y: 0.28125 },\n  { x: 0.78125, y: 0.28125 },\n  { x: 0.84375, y: 0.28125 },\n  { x: 0.84375, y: 0.28125 },\n  { x: 0.90625, y: 0.28125 },\n  { x: 0.90625, y: 0.28125 },\n  { x: 0.96875, y: 0.28125 },\n  { x: 0.96875, y: 0.28125 },\n  { x: 0.03125, y: 0.34375 },\n  { x: 0.03125, y: 0.34375 },\n  { x: 0.09375, y: 0.34375 },\n  { x: 0.09375, y: 0.34375 },\n  { x: 0.15625, y: 0.34375 },\n  { x: 0.15625, y: 0.34375 },\n  { x: 0.21875, y: 0.34375 },\n  { x: 0.21875, y: 0.34375 },\n  { x: 0.28125, y: 0.34375 },\n  { x: 0.28125, y: 0.34375 },\n  { x: 0.34375, y: 0.34375 },\n  { x: 0.34375, y: 0.34375 },\n  { x: 0.40625, y: 0.34375 },\n  { x: 0.40625, y: 0.34375 },\n  { x: 0.46875, y: 0.34375 },\n  { x: 0.46875, y: 0.34375 },\n  { x: 0.53125, y: 0.34375 },\n  { x: 0.53125, y: 0.34375 },\n  { x: 0.59375, y: 0.34375 },\n  { x: 0.59375, y: 0.34375 },\n  { x: 0.65625, y: 0.34375 },\n  { x: 0.65625, y: 0.34375 },\n  { x: 0.71875, y: 0.34375 },\n  { x: 0.71875, y: 0.34375 },\n  { x: 0.78125, y: 0.34375 },\n  { x: 0.78125, y: 0.34375 },\n  { x: 0.84375, y: 0.34375 },\n  { x: 0.84375, y: 0.34375 },\n  { x: 0.90625, y: 0.34375 },\n  { x: 0.90625, y: 0.34375 },\n  { x: 0.96875, y: 0.34375 },\n  { x: 0.96875, y: 0.34375 },\n  { x: 0.03125, y: 0.40625 },\n  { x: 0.03125, y: 0.40625 },\n  { x: 0.09375, y: 0.40625 },\n  { x: 0.09375, y: 0.40625 },\n  { x: 0.15625, y: 0.40625 },\n  { x: 0.15625, y: 0.40625 },\n  { x: 0.21875, y: 0.40625 },\n  { x: 0.21875, y: 0.40625 },\n  { x: 0.28125, y: 0.40625 },\n  { x: 0.28125, y: 0.40625 },\n  { x: 0.34375, y: 0.40625 },\n  { x: 0.34375, y: 0.40625 },\n  { x: 0.40625, y: 0.40625 },\n  { x: 0.40625, y: 0.40625 },\n  { x: 0.46875, y: 0.40625 },\n  { x: 0.46875, y: 0.40625 },\n  { x: 0.53125, y: 0.40625 },\n  { x: 0.53125, y: 0.40625 },\n  { x: 0.59375, y: 0.40625 },\n  { x: 0.59375, y: 0.40625 },\n  { x: 0.65625, y: 0.40625 },\n  { x: 0.65625, y: 0.40625 },\n  { x: 0.71875, y: 0.40625 },\n  { x: 0.71875, y: 0.40625 },\n  { x: 0.78125, y: 0.40625 },\n  { x: 0.78125, y: 0.40625 },\n  { x: 0.84375, y: 0.40625 },\n  { x: 0.84375, y: 0.40625 },\n  { x: 0.90625, y: 0.40625 },\n  { x: 0.90625, y: 0.40625 },\n  { x: 0.96875, y: 0.40625 },\n  { x: 0.96875, y: 0.40625 },\n  { x: 0.03125, y: 0.46875 },\n  { x: 0.03125, y: 0.46875 },\n  { x: 0.09375, y: 0.46875 },\n  { x: 0.09375, y: 0.46875 },\n  { x: 0.15625, y: 0.46875 },\n  { x: 0.15625, y: 0.46875 },\n  { x: 0.21875, y: 0.46875 },\n  { x: 0.21875, y: 0.46875 },\n  { x: 0.28125, y: 0.46875 },\n  { x: 0.28125, y: 0.46875 },\n  { x: 0.34375, y: 0.46875 },\n  { x: 0.34375, y: 0.46875 },\n  { x: 0.40625, y: 0.46875 },\n  { x: 0.40625, y: 0.46875 },\n  { x: 0.46875, y: 0.46875 },\n  { x: 0.46875, y: 0.46875 },\n  { x: 0.53125, y: 0.46875 },\n  { x: 0.53125, y: 0.46875 },\n  { x: 0.59375, y: 0.46875 },\n  { x: 0.59375, y: 0.46875 },\n  { x: 0.65625, y: 0.46875 },\n  { x: 0.65625, y: 0.46875 },\n  { x: 0.71875, y: 0.46875 },\n  { x: 0.71875, y: 0.46875 },\n  { x: 0.78125, y: 0.46875 },\n  { x: 0.78125, y: 0.46875 },\n  { x: 0.84375, y: 0.46875 },\n  { x: 0.84375, y: 0.46875 },\n  { x: 0.90625, y: 0.46875 },\n  { x: 0.90625, y: 0.46875 },\n  { x: 0.96875, y: 0.46875 },\n  { x: 0.96875, y: 0.46875 },\n  { x: 0.03125, y: 0.53125 },\n  { x: 0.03125, y: 0.53125 },\n  { x: 0.09375, y: 0.53125 },\n  { x: 0.09375, y: 0.53125 },\n  { x: 0.15625, y: 0.53125 },\n  { x: 0.15625, y: 0.53125 },\n  { x: 0.21875, y: 0.53125 },\n  { x: 0.21875, y: 0.53125 },\n  { x: 0.28125, y: 0.53125 },\n  { x: 0.28125, y: 0.53125 },\n  { x: 0.34375, y: 0.53125 },\n  { x: 0.34375, y: 0.53125 },\n  { x: 0.40625, y: 0.53125 },\n  { x: 0.40625, y: 0.53125 },\n  { x: 0.46875, y: 0.53125 },\n  { x: 0.46875, y: 0.53125 },\n  { x: 0.53125, y: 0.53125 },\n  { x: 0.53125, y: 0.53125 },\n  { x: 0.59375, y: 0.53125 },\n  { x: 0.59375, y: 0.53125 },\n  { x: 0.65625, y: 0.53125 },\n  { x: 0.65625, y: 0.53125 },\n  { x: 0.71875, y: 0.53125 },\n  { x: 0.71875, y: 0.53125 },\n  { x: 0.78125, y: 0.53125 },\n  { x: 0.78125, y: 0.53125 },\n  { x: 0.84375, y: 0.53125 },\n  { x: 0.84375, y: 0.53125 },\n  { x: 0.90625, y: 0.53125 },\n  { x: 0.90625, y: 0.53125 },\n  { x: 0.96875, y: 0.53125 },\n  { x: 0.96875, y: 0.53125 },\n  { x: 0.03125, y: 0.59375 },\n  { x: 0.03125, y: 0.59375 },\n  { x: 0.09375, y: 0.59375 },\n  { x: 0.09375, y: 0.59375 },\n  { x: 0.15625, y: 0.59375 },\n  { x: 0.15625, y: 0.59375 },\n  { x: 0.21875, y: 0.59375 },\n  { x: 0.21875, y: 0.59375 },\n  { x: 0.28125, y: 0.59375 },\n  { x: 0.28125, y: 0.59375 },\n  { x: 0.34375, y: 0.59375 },\n  { x: 0.34375, y: 0.59375 },\n  { x: 0.40625, y: 0.59375 },\n  { x: 0.40625, y: 0.59375 },\n  { x: 0.46875, y: 0.59375 },\n  { x: 0.46875, y: 0.59375 },\n  { x: 0.53125, y: 0.59375 },\n  { x: 0.53125, y: 0.59375 },\n  { x: 0.59375, y: 0.59375 },\n  { x: 0.59375, y: 0.59375 },\n  { x: 0.65625, y: 0.59375 },\n  { x: 0.65625, y: 0.59375 },\n  { x: 0.71875, y: 0.59375 },\n  { x: 0.71875, y: 0.59375 },\n  { x: 0.78125, y: 0.59375 },\n  { x: 0.78125, y: 0.59375 },\n  { x: 0.84375, y: 0.59375 },\n  { x: 0.84375, y: 0.59375 },\n  { x: 0.90625, y: 0.59375 },\n  { x: 0.90625, y: 0.59375 },\n  { x: 0.96875, y: 0.59375 },\n  { x: 0.96875, y: 0.59375 },\n  { x: 0.03125, y: 0.65625 },\n  { x: 0.03125, y: 0.65625 },\n  { x: 0.09375, y: 0.65625 },\n  { x: 0.09375, y: 0.65625 },\n  { x: 0.15625, y: 0.65625 },\n  { x: 0.15625, y: 0.65625 },\n  { x: 0.21875, y: 0.65625 },\n  { x: 0.21875, y: 0.65625 },\n  { x: 0.28125, y: 0.65625 },\n  { x: 0.28125, y: 0.65625 },\n  { x: 0.34375, y: 0.65625 },\n  { x: 0.34375, y: 0.65625 },\n  { x: 0.40625, y: 0.65625 },\n  { x: 0.40625, y: 0.65625 },\n  { x: 0.46875, y: 0.65625 },\n  { x: 0.46875, y: 0.65625 },\n  { x: 0.53125, y: 0.65625 },\n  { x: 0.53125, y: 0.65625 },\n  { x: 0.59375, y: 0.65625 },\n  { x: 0.59375, y: 0.65625 },\n  { x: 0.65625, y: 0.65625 },\n  { x: 0.65625, y: 0.65625 },\n  { x: 0.71875, y: 0.65625 },\n  { x: 0.71875, y: 0.65625 },\n  { x: 0.78125, y: 0.65625 },\n  { x: 0.78125, y: 0.65625 },\n  { x: 0.84375, y: 0.65625 },\n  { x: 0.84375, y: 0.65625 },\n  { x: 0.90625, y: 0.65625 },\n  { x: 0.90625, y: 0.65625 },\n  { x: 0.96875, y: 0.65625 },\n  { x: 0.96875, y: 0.65625 },\n  { x: 0.03125, y: 0.71875 },\n  { x: 0.03125, y: 0.71875 },\n  { x: 0.09375, y: 0.71875 },\n  { x: 0.09375, y: 0.71875 },\n  { x: 0.15625, y: 0.71875 },\n  { x: 0.15625, y: 0.71875 },\n  { x: 0.21875, y: 0.71875 },\n  { x: 0.21875, y: 0.71875 },\n  { x: 0.28125, y: 0.71875 },\n  { x: 0.28125, y: 0.71875 },\n  { x: 0.34375, y: 0.71875 },\n  { x: 0.34375, y: 0.71875 },\n  { x: 0.40625, y: 0.71875 },\n  { x: 0.40625, y: 0.71875 },\n  { x: 0.46875, y: 0.71875 },\n  { x: 0.46875, y: 0.71875 },\n  { x: 0.53125, y: 0.71875 },\n  { x: 0.53125, y: 0.71875 },\n  { x: 0.59375, y: 0.71875 },\n  { x: 0.59375, y: 0.71875 },\n  { x: 0.65625, y: 0.71875 },\n  { x: 0.65625, y: 0.71875 },\n  { x: 0.71875, y: 0.71875 },\n  { x: 0.71875, y: 0.71875 },\n  { x: 0.78125, y: 0.71875 },\n  { x: 0.78125, y: 0.71875 },\n  { x: 0.84375, y: 0.71875 },\n  { x: 0.84375, y: 0.71875 },\n  { x: 0.90625, y: 0.71875 },\n  { x: 0.90625, y: 0.71875 },\n  { x: 0.96875, y: 0.71875 },\n  { x: 0.96875, y: 0.71875 },\n  { x: 0.03125, y: 0.78125 },\n  { x: 0.03125, y: 0.78125 },\n  { x: 0.09375, y: 0.78125 },\n  { x: 0.09375, y: 0.78125 },\n  { x: 0.15625, y: 0.78125 },\n  { x: 0.15625, y: 0.78125 },\n  { x: 0.21875, y: 0.78125 },\n  { x: 0.21875, y: 0.78125 },\n  { x: 0.28125, y: 0.78125 },\n  { x: 0.28125, y: 0.78125 },\n  { x: 0.34375, y: 0.78125 },\n  { x: 0.34375, y: 0.78125 },\n  { x: 0.40625, y: 0.78125 },\n  { x: 0.40625, y: 0.78125 },\n  { x: 0.46875, y: 0.78125 },\n  { x: 0.46875, y: 0.78125 },\n  { x: 0.53125, y: 0.78125 },\n  { x: 0.53125, y: 0.78125 },\n  { x: 0.59375, y: 0.78125 },\n  { x: 0.59375, y: 0.78125 },\n  { x: 0.65625, y: 0.78125 },\n  { x: 0.65625, y: 0.78125 },\n  { x: 0.71875, y: 0.78125 },\n  { x: 0.71875, y: 0.78125 },\n  { x: 0.78125, y: 0.78125 },\n  { x: 0.78125, y: 0.78125 },\n  { x: 0.84375, y: 0.78125 },\n  { x: 0.84375, y: 0.78125 },\n  { x: 0.90625, y: 0.78125 },\n  { x: 0.90625, y: 0.78125 },\n  { x: 0.96875, y: 0.78125 },\n  { x: 0.96875, y: 0.78125 },\n  { x: 0.03125, y: 0.84375 },\n  { x: 0.03125, y: 0.84375 },\n  { x: 0.09375, y: 0.84375 },\n  { x: 0.09375, y: 0.84375 },\n  { x: 0.15625, y: 0.84375 },\n  { x: 0.15625, y: 0.84375 },\n  { x: 0.21875, y: 0.84375 },\n  { x: 0.21875, y: 0.84375 },\n  { x: 0.28125, y: 0.84375 },\n  { x: 0.28125, y: 0.84375 },\n  { x: 0.34375, y: 0.84375 },\n  { x: 0.34375, y: 0.84375 },\n  { x: 0.40625, y: 0.84375 },\n  { x: 0.40625, y: 0.84375 },\n  { x: 0.46875, y: 0.84375 },\n  { x: 0.46875, y: 0.84375 },\n  { x: 0.53125, y: 0.84375 },\n  { x: 0.53125, y: 0.84375 },\n  { x: 0.59375, y: 0.84375 },\n  { x: 0.59375, y: 0.84375 },\n  { x: 0.65625, y: 0.84375 },\n  { x: 0.65625, y: 0.84375 },\n  { x: 0.71875, y: 0.84375 },\n  { x: 0.71875, y: 0.84375 },\n  { x: 0.78125, y: 0.84375 },\n  { x: 0.78125, y: 0.84375 },\n  { x: 0.84375, y: 0.84375 },\n  { x: 0.84375, y: 0.84375 },\n  { x: 0.90625, y: 0.84375 },\n  { x: 0.90625, y: 0.84375 },\n  { x: 0.96875, y: 0.84375 },\n  { x: 0.96875, y: 0.84375 },\n  { x: 0.03125, y: 0.90625 },\n  { x: 0.03125, y: 0.90625 },\n  { x: 0.09375, y: 0.90625 },\n  { x: 0.09375, y: 0.90625 },\n  { x: 0.15625, y: 0.90625 },\n  { x: 0.15625, y: 0.90625 },\n  { x: 0.21875, y: 0.90625 },\n  { x: 0.21875, y: 0.90625 },\n  { x: 0.28125, y: 0.90625 },\n  { x: 0.28125, y: 0.90625 },\n  { x: 0.34375, y: 0.90625 },\n  { x: 0.34375, y: 0.90625 },\n  { x: 0.40625, y: 0.90625 },\n  { x: 0.40625, y: 0.90625 },\n  { x: 0.46875, y: 0.90625 },\n  { x: 0.46875, y: 0.90625 },\n  { x: 0.53125, y: 0.90625 },\n  { x: 0.53125, y: 0.90625 },\n  { x: 0.59375, y: 0.90625 },\n  { x: 0.59375, y: 0.90625 },\n  { x: 0.65625, y: 0.90625 },\n  { x: 0.65625, y: 0.90625 },\n  { x: 0.71875, y: 0.90625 },\n  { x: 0.71875, y: 0.90625 },\n  { x: 0.78125, y: 0.90625 },\n  { x: 0.78125, y: 0.90625 },\n  { x: 0.84375, y: 0.90625 },\n  { x: 0.84375, y: 0.90625 },\n  { x: 0.90625, y: 0.90625 },\n  { x: 0.90625, y: 0.90625 },\n  { x: 0.96875, y: 0.90625 },\n  { x: 0.96875, y: 0.90625 },\n  { x: 0.03125, y: 0.96875 },\n  { x: 0.03125, y: 0.96875 },\n  { x: 0.09375, y: 0.96875 },\n  { x: 0.09375, y: 0.96875 },\n  { x: 0.15625, y: 0.96875 },\n  { x: 0.15625, y: 0.96875 },\n  { x: 0.21875, y: 0.96875 },\n  { x: 0.21875, y: 0.96875 },\n  { x: 0.28125, y: 0.96875 },\n  { x: 0.28125, y: 0.96875 },\n  { x: 0.34375, y: 0.96875 },\n  { x: 0.34375, y: 0.96875 },\n  { x: 0.40625, y: 0.96875 },\n  { x: 0.40625, y: 0.96875 },\n  { x: 0.46875, y: 0.96875 },\n  { x: 0.46875, y: 0.96875 },\n  { x: 0.53125, y: 0.96875 },\n  { x: 0.53125, y: 0.96875 },\n  { x: 0.59375, y: 0.96875 },\n  { x: 0.59375, y: 0.96875 },\n  { x: 0.65625, y: 0.96875 },\n  { x: 0.65625, y: 0.96875 },\n  { x: 0.71875, y: 0.96875 },\n  { x: 0.71875, y: 0.96875 },\n  { x: 0.78125, y: 0.96875 },\n  { x: 0.78125, y: 0.96875 },\n  { x: 0.84375, y: 0.96875 },\n  { x: 0.84375, y: 0.96875 },\n  { x: 0.90625, y: 0.96875 },\n  { x: 0.90625, y: 0.96875 },\n  { x: 0.96875, y: 0.96875 },\n  { x: 0.96875, y: 0.96875 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.0625, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.1875, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.3125, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.4375, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.5625, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.6875, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.8125, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.9375, y: 0.0625 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.0625, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.1875, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.3125, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.4375, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.5625, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.6875, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.8125, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.9375, y: 0.1875 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.0625, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.1875, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.3125, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.4375, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.5625, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.6875, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.8125, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.9375, y: 0.3125 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.0625, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.1875, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.3125, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.4375, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.5625, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.6875, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.8125, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.9375, y: 0.4375 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.0625, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.1875, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.3125, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.4375, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.5625, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.6875, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.8125, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.9375, y: 0.5625 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.0625, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.1875, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.3125, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.4375, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.5625, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.6875, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.8125, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.9375, y: 0.6875 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.0625, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.1875, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.3125, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.4375, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.5625, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.6875, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.8125, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.9375, y: 0.8125 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.0625, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.1875, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.3125, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.4375, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.5625, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.6875, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.8125, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n  { x: 0.9375, y: 0.9375 },\n];\n", "/**\n * HandPose model implementation\n * See `handpose.ts` for entry point\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as util from './handposeutil';\nimport * as anchors from './handposeanchors';\nimport { constants } from '../tfjs/constants';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Point } from '../result';\n\nexport class HandDetector {\n  model: GraphModel;\n  anchors: number[][];\n  anchorsTensor: Tensor;\n  inputSize: number;\n  inputSizeTensor: Tensor;\n  doubleInputSizeTensor: Tensor;\n\n  constructor(model) {\n    this.model = model;\n    this.anchors = anchors.anchors.map((anchor) => [anchor.x, anchor.y]);\n    this.anchorsTensor = tf.tensor2d(this.anchors);\n    this.inputSize = (this.model && this.model.inputs && this.model.inputs[0].shape) ? this.model.inputs[0].shape[2] : 0;\n    this.inputSizeTensor = tf.tensor1d([this.inputSize, this.inputSize]);\n    this.doubleInputSizeTensor = tf.tensor1d([this.inputSize * 2, this.inputSize * 2]);\n  }\n\n  normalizeBoxes(boxes) {\n    const t: Record<string, Tensor> = {};\n    t.boxOffsets = tf.slice(boxes, [0, 0], [-1, 2]);\n    t.boxSizes = tf.slice(boxes, [0, 2], [-1, 2]);\n    t.div = tf.div(t.boxOffsets, this.inputSizeTensor);\n    t.boxCenterPoints = tf.add(t.div, this.anchorsTensor);\n    t.halfBoxSizes = tf.div(t.boxSizes, this.doubleInputSizeTensor);\n    t.sub = tf.sub(t.boxCenterPoints, t.halfBoxSizes);\n    t.startPoints = tf.mul(t.sub, this.inputSizeTensor);\n    t.add = tf.add(t.boxCenterPoints, t.halfBoxSizes);\n    t.endPoints = tf.mul(t.add, this.inputSizeTensor);\n    const res = tf.concat2d([t.startPoints, t.endPoints], 1);\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return res;\n  }\n\n  normalizeLandmarks(rawPalmLandmarks, index) {\n    const t: Record<string, Tensor> = {};\n    t.reshape = tf.reshape(rawPalmLandmarks, [-1, 7, 2]);\n    t.div = tf.div(t.reshape, this.inputSizeTensor);\n    t.landmarks = tf.add(t.div, this.anchors[index]);\n    const res = tf.mul(t.landmarks, this.inputSizeTensor);\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return res;\n  }\n\n  async predict(input, config): Promise<{ startPoint: Point; endPoint: Point, palmLandmarks: Point[]; confidence: number }[]> {\n    const t: Record<string, Tensor> = {};\n    t.resize = tf.image.resizeBilinear(input, [this.inputSize, this.inputSize]);\n    t.div = tf.div(t.resize, constants.tf127);\n    t.image = tf.sub(t.div, constants.tf1);\n    t.batched = this.model.execute(t.image) as Tensor;\n    t.predictions = tf.squeeze(t.batched);\n    t.slice = tf.slice(t.predictions, [0, 0], [-1, 1]);\n    t.sigmoid = tf.sigmoid(t.slice);\n    t.scores = tf.squeeze(t.sigmoid);\n    const scores = await t.scores.data();\n    t.boxes = tf.slice(t.predictions, [0, 1], [-1, 4]);\n    t.norm = this.normalizeBoxes(t.boxes);\n    // box detection is flaky so we look for 3x boxes than we need results\n    t.nms = await tf.image.nonMaxSuppressionAsync(t.norm, t.scores, 3 * config.hand.maxDetected, config.hand.iouThreshold, config.hand.minConfidence);\n    const nms = await t.nms.array() as Array<number>;\n    const hands: Array<{ startPoint: Point; endPoint: Point; palmLandmarks: Point[]; confidence: number }> = [];\n    for (const index of nms) {\n      const p: Record<string, Tensor> = {};\n      p.box = tf.slice(t.norm, [index, 0], [1, -1]);\n      p.slice = tf.slice(t.predictions, [index, 5], [1, 14]);\n      p.norm = this.normalizeLandmarks(p.slice, index);\n      p.palmLandmarks = tf.reshape(p.norm, [-1, 2]);\n      const box = await p.box.data();\n      const startPoint = box.slice(0, 2) as unknown as Point;\n      const endPoint = box.slice(2, 4) as unknown as Point;\n      const palmLandmarks = await p.palmLandmarks.array();\n      const hand = { startPoint, endPoint, palmLandmarks, confidence: scores[index] };\n      const scaled = util.scaleBoxCoordinates(hand, [input.shape[2] / this.inputSize, input.shape[1] / this.inputSize]);\n      hands.push(scaled);\n      Object.keys(p).forEach((tensor) => tf.dispose(p[tensor]));\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return hands;\n  }\n}\n", "/**\n * HandPose model implementation\n * See `handpose.ts` for entry point\n */\n\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as util from './handposeutil';\nimport type * as detector from './handposedetector';\nimport { constants } from '../tfjs/constants';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport { env } from '../util/env';\nimport { now } from '../util/util';\nimport type { Point } from '../result';\n\nconst palmBoxEnlargeFactor = 5; // default 3\nconst handBoxEnlargeFactor = 1.65; // default 1.65\nconst palmLandmarkIds = [0, 5, 9, 13, 17, 1, 2];\nconst palmLandmarksPalmBase = 0;\nconst palmLandmarksMiddleFingerBase = 2;\nlet lastTime = 0;\n\nexport class HandPipeline {\n  handDetector: detector.HandDetector;\n  handPoseModel: GraphModel;\n  inputSize: number;\n  storedBoxes: Array<{ startPoint: Point; endPoint: Point; palmLandmarks: Point[]; confidence: number } | null>;\n  skipped: number;\n  detectedHands: number;\n\n  constructor(handDetector, handPoseModel) {\n    this.handDetector = handDetector;\n    this.handPoseModel = handPoseModel;\n    this.inputSize = this.handPoseModel && this.handPoseModel.inputs[0].shape ? this.handPoseModel.inputs[0].shape[2] : 0;\n    this.storedBoxes = [];\n    this.skipped = Number.MAX_SAFE_INTEGER;\n    this.detectedHands = 0;\n  }\n\n  // eslint-disable-next-line class-methods-use-this\n  calculateLandmarksBoundingBox(landmarks) {\n    const xs = landmarks.map((d) => d[0]);\n    const ys = landmarks.map((d) => d[1]);\n    const startPoint = [Math.min(...xs), Math.min(...ys)];\n    const endPoint = [Math.max(...xs), Math.max(...ys)];\n    return { startPoint, endPoint };\n  }\n\n  getBoxForPalmLandmarks(palmLandmarks, rotationMatrix) {\n    const rotatedPalmLandmarks = palmLandmarks.map((coord) => util.rotatePoint([...coord, 1], rotationMatrix));\n    const boxAroundPalm = this.calculateLandmarksBoundingBox(rotatedPalmLandmarks);\n    return util.enlargeBox(util.squarifyBox(boxAroundPalm), palmBoxEnlargeFactor);\n  }\n\n  getBoxForHandLandmarks(landmarks) {\n    const boundingBox = this.calculateLandmarksBoundingBox(landmarks);\n    const boxAroundHand = util.enlargeBox(util.squarifyBox(boundingBox), handBoxEnlargeFactor);\n    boxAroundHand.palmLandmarks = [];\n    for (let i = 0; i < palmLandmarkIds.length; i++) {\n      boxAroundHand.palmLandmarks.push(landmarks[palmLandmarkIds[i]].slice(0, 2));\n    }\n    return boxAroundHand;\n  }\n\n  transformRawCoords(rawCoords, box2, angle, rotationMatrix) {\n    const boxSize = util.getBoxSize(box2);\n    const scaleFactor = [boxSize[0] / this.inputSize, boxSize[1] / this.inputSize, (boxSize[0] + boxSize[1]) / this.inputSize / 2];\n    const coordsScaled = rawCoords.map((coord) => [\n      scaleFactor[0] * (coord[0] - this.inputSize / 2),\n      scaleFactor[1] * (coord[1] - this.inputSize / 2),\n      scaleFactor[2] * coord[2],\n    ]);\n    const coordsRotationMatrix = util.buildRotationMatrix(angle, [0, 0]);\n    const coordsRotated = coordsScaled.map((coord) => {\n      const rotated = util.rotatePoint(coord, coordsRotationMatrix);\n      return [...rotated, coord[2]];\n    });\n    const inverseRotationMatrix = util.invertTransformMatrix(rotationMatrix);\n    const boxCenter = [...util.getBoxCenter(box2), 1];\n    const originalBoxCenter = [\n      util.dot(boxCenter, inverseRotationMatrix[0]),\n      util.dot(boxCenter, inverseRotationMatrix[1]),\n    ];\n    return coordsRotated.map((coord) => [\n      Math.trunc(coord[0] + originalBoxCenter[0]),\n      Math.trunc(coord[1] + originalBoxCenter[1]),\n      Math.trunc(coord[2]),\n    ]);\n  }\n\n  async estimateHands(image, config) {\n    let useFreshBox = false;\n\n    // run new detector every skipFrames\n    let boxes;\n    const skipTime = (config.hand.skipTime || 0) > (now() - lastTime);\n    const skipFrame = this.skipped < (config.hand.skipFrames || 0);\n    if (config.skipAllowed && skipTime && skipFrame) {\n      boxes = await this.handDetector.predict(image, config);\n      this.skipped = 0;\n    }\n    if (config.skipAllowed) this.skipped++;\n\n    // if detector result count doesn't match current working set, use it to reset current working set\n    if (boxes && (boxes.length > 0) && ((boxes.length !== this.detectedHands) && (this.detectedHands !== config.hand.maxDetected) || !config.hand.landmarks)) {\n      this.detectedHands = 0;\n      this.storedBoxes = [...boxes];\n      // for (const possible of boxes) this.storedBoxes.push(possible);\n      if (this.storedBoxes.length > 0) useFreshBox = true;\n    }\n    const hands: Array<{ landmarks: Point[], confidence: number, boxConfidence: number, fingerConfidence: number, box: { topLeft: Point, bottomRight: Point } }> = [];\n\n    // go through working set of boxes\n    for (let i = 0; i < this.storedBoxes.length; i++) {\n      const currentBox = this.storedBoxes[i];\n      if (!currentBox) continue;\n      if (config.hand.landmarks) {\n        const angle = config.hand.rotation ? util.computeRotation(currentBox.palmLandmarks[palmLandmarksPalmBase], currentBox.palmLandmarks[palmLandmarksMiddleFingerBase]) : 0;\n        const palmCenter = util.getBoxCenter(currentBox);\n        const palmCenterNormalized = [palmCenter[0] / image.shape[2], palmCenter[1] / image.shape[1]];\n        const rotatedImage = config.hand.rotation && env.kernels.includes('rotatewithoffset') ? tf.image.rotateWithOffset(image, angle, 0, palmCenterNormalized) : image.clone();\n        const rotationMatrix = util.buildRotationMatrix(-angle, palmCenter);\n        const newBox = useFreshBox ? this.getBoxForPalmLandmarks(currentBox.palmLandmarks, rotationMatrix) : currentBox;\n        const croppedInput = util.cutBoxFromImageAndResize(newBox, rotatedImage, [this.inputSize, this.inputSize]);\n        const handImage = tf.div(croppedInput, constants.tf255);\n        tf.dispose(croppedInput);\n        tf.dispose(rotatedImage);\n        const [confidenceT, keypoints] = this.handPoseModel.execute(handImage) as Array<Tensor>;\n        lastTime = now();\n        tf.dispose(handImage);\n        const confidence = (await confidenceT.data())[0];\n        tf.dispose(confidenceT);\n        if (confidence >= config.hand.minConfidence / 4) {\n          const keypointsReshaped = tf.reshape(keypoints, [-1, 3]);\n          const rawCoords = await keypointsReshaped.array();\n          tf.dispose(keypoints);\n          tf.dispose(keypointsReshaped);\n          const coords = this.transformRawCoords(rawCoords, newBox, angle, rotationMatrix);\n          const nextBoundingBox = this.getBoxForHandLandmarks(coords);\n          this.storedBoxes[i] = { ...nextBoundingBox, confidence };\n          const result = {\n            landmarks: coords,\n            confidence,\n            boxConfidence: currentBox.confidence,\n            fingerConfidence: confidence,\n            box: { topLeft: nextBoundingBox.startPoint, bottomRight: nextBoundingBox.endPoint },\n          };\n          hands.push(result);\n        } else {\n          this.storedBoxes[i] = null;\n        }\n        tf.dispose(keypoints);\n      } else {\n        // const enlarged = box.enlargeBox(box.squarifyBox(box.shiftBox(currentBox, HAND_BOX_SHIFT_VECTOR)), handBoxEnlargeFactor);\n        const enlarged = util.enlargeBox(util.squarifyBox(currentBox), handBoxEnlargeFactor);\n        const result = {\n          confidence: currentBox.confidence,\n          boxConfidence: currentBox.confidence,\n          fingerConfidence: 0,\n          box: { topLeft: enlarged.startPoint, bottomRight: enlarged.endPoint },\n          landmarks: [],\n        };\n        hands.push(result);\n      }\n    }\n    this.storedBoxes = this.storedBoxes.filter((a) => a !== null);\n    this.detectedHands = hands.length;\n    if (hands.length > config.hand.maxDetected) hands.length = config.hand.maxDetected;\n    return hands;\n  }\n}\n", "/**\n * FingerPose algorithm implementation\n * See `fingerpose.ts` for entry point\n */\n\nexport const Finger = {\n  thumb: 0,\n  index: 1,\n  middle: 2,\n  ring: 3,\n  pinky: 4,\n  all: [0, 1, 2, 3, 4], // just for convenience\n  nameMapping: { 0: 'thumb', 1: 'index', 2: 'middle', 3: 'ring', 4: 'pinky' },\n  // Describes mapping of joints based on the 21 points returned by handpose.\n  // [0]     Palm\n  // [1-4]   Thumb\n  // [5-8]   Index\n  // [9-12]  Middle\n  // [13-16] Ring\n  // [17-20] Pinky\n  pointsMapping: {\n    0: [[0, 1], [1, 2], [2, 3], [3, 4]],\n    1: [[0, 5], [5, 6], [6, 7], [7, 8]],\n    2: [[0, 9], [9, 10], [10, 11], [11, 12]],\n    3: [[0, 13], [13, 14], [14, 15], [15, 16]],\n    4: [[0, 17], [17, 18], [18, 19], [19, 20]],\n  },\n  getName: (value) => Finger.nameMapping[value],\n  getPoints: (value) => Finger.pointsMapping[value],\n};\n\nexport const FingerCurl = {\n  none: 0,\n  half: 1,\n  full: 2,\n  nameMapping: { 0: 'none', 1: 'half', 2: 'full' },\n  getName: (value) => FingerCurl.nameMapping[value],\n};\n\nexport const FingerDirection = {\n  verticalUp: 0,\n  verticalDown: 1,\n  horizontalLeft: 2,\n  horizontalRight: 3,\n  diagonalUpRight: 4,\n  diagonalUpLeft: 5,\n  diagonalDownRight: 6,\n  diagonalDownLeft: 7,\n  nameMapping: { 0: 'verticalUp', 1: 'verticalDown', 2: 'horizontalLeft', 3: 'horizontalRight', 4: 'diagonalUpRight', 5: 'diagonalUpLeft', 6: 'diagonalDownRight', 7: 'diagonalDownLeft' },\n  getName: (value) => FingerDirection.nameMapping[value],\n};\n\nexport class FingerGesture {\n  name;\n  curls;\n  directions;\n  weights;\n  weightsRelative;\n\n  constructor(name) {\n    // name (should be unique)\n    this.name = name;\n    this.curls = {};\n    this.directions = {};\n    this.weights = [1.0, 1.0, 1.0, 1.0, 1.0];\n    this.weightsRelative = [1.0, 1.0, 1.0, 1.0, 1.0];\n  }\n\n  curl(finger, curl, confidence) {\n    if (typeof this.curls[finger] === 'undefined') this.curls[finger] = [];\n    this.curls[finger].push([curl, confidence]);\n  }\n\n  direction(finger, position, confidence) {\n    if (!this.directions[finger]) this.directions[finger] = [];\n    this.directions[finger].push([position, confidence]);\n  }\n\n  weight(finger, weight) {\n    this.weights[finger] = weight;\n    // recalculate relative weights\n    const total = this.weights.reduce((a, b) => a + b, 0);\n    this.weightsRelative = this.weights.map((el) => el * 5 / total);\n  }\n\n  matchAgainst(detectedCurls, detectedDirections) {\n    let confidence = 0.0;\n    // look at the detected curl of each finger and compare with\n    // the expected curl of this finger inside current gesture\n    for (const fingerIdx in detectedCurls) {\n      const detectedCurl = detectedCurls[fingerIdx];\n      const expectedCurls = this.curls[fingerIdx];\n      if (typeof expectedCurls === 'undefined') {\n        // no curl description available for this finger\n        // add default confidence of \"1\"\n        confidence += this.weightsRelative[fingerIdx];\n        continue;\n      }\n      // compare to each possible curl of this specific finger\n      for (const [expectedCurl, score] of expectedCurls) {\n        if (detectedCurl === expectedCurl) {\n          confidence += score * this.weightsRelative[fingerIdx];\n          break;\n        }\n      }\n    }\n    // same for detected direction of each finger\n    for (const fingerIdx in detectedDirections) {\n      const detectedDirection = detectedDirections[fingerIdx];\n      const expectedDirections = this.directions[fingerIdx];\n      if (typeof expectedDirections === 'undefined') {\n        // no direction description available for this finger\n        // add default confidence of \"1\"\n        confidence += this.weightsRelative[fingerIdx];\n        continue;\n      }\n      // compare to each possible direction of this specific finger\n      for (const [expectedDirection, score] of expectedDirections) {\n        if (detectedDirection === expectedDirection) {\n          confidence += score * this.weightsRelative[fingerIdx];\n          break;\n        }\n      }\n    }\n    return confidence / 10;\n  }\n}\n", "/**\n * FingerPose algorithm implementation\n * See `fingerpose.ts` for entry point\n */\n\nimport { Finger, FingerCurl, FingerDirection, FingerGesture } from './fingerdef';\n\n// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\nexport const { thumb, index, middle, ring, pinky } = Finger;\n// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\nexport const { none, half, full } = FingerCurl;\n// eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\nexport const { verticalUp, verticalDown, horizontalLeft, horizontalRight, diagonalUpRight, diagonalUpLeft, diagonalDownRight, diagonalDownLeft } = FingerDirection;\n\n// describe thumbs up gesture \uD83D\uDC4D\nconst ThumbsUp = new FingerGesture('thumbs up');\nThumbsUp.curl(thumb, none, 1.0);\nThumbsUp.direction(thumb, verticalUp, 1.0);\nThumbsUp.direction(thumb, diagonalUpLeft, 0.25);\nThumbsUp.direction(thumb, diagonalUpRight, 0.25);\nfor (const finger of [Finger.index, Finger.middle, Finger.ring, Finger.pinky]) {\n  ThumbsUp.curl(finger, full, 1.0);\n  ThumbsUp.direction(finger, horizontalLeft, 1.0);\n  ThumbsUp.direction(finger, horizontalRight, 1.0);\n}\n\n// describe Victory gesture \u270C\uFE0F\nconst Victory = new FingerGesture('victory');\nVictory.curl(thumb, half, 0.5);\nVictory.curl(thumb, none, 0.5);\nVictory.direction(thumb, verticalUp, 1.0);\nVictory.direction(thumb, diagonalUpLeft, 1.0);\nVictory.curl(index, none, 1.0);\nVictory.direction(index, verticalUp, 0.75);\nVictory.direction(index, diagonalUpLeft, 1.0);\nVictory.curl(middle, none, 1.0);\nVictory.direction(middle, verticalUp, 1.0);\nVictory.direction(middle, diagonalUpLeft, 0.75);\nVictory.curl(ring, full, 1.0);\nVictory.direction(ring, verticalUp, 0.2);\nVictory.direction(ring, diagonalUpLeft, 1.0);\nVictory.direction(ring, horizontalLeft, 0.2);\nVictory.curl(pinky, full, 1.0);\nVictory.direction(pinky, verticalUp, 0.2);\nVictory.direction(pinky, diagonalUpLeft, 1.0);\nVictory.direction(pinky, horizontalLeft, 0.2);\nVictory.weight(index, 2);\nVictory.weight(middle, 2);\n\n// describe Point gesture \u270C\uFE0F\nconst Point = new FingerGesture('point');\nPoint.curl(thumb, full, 1.0);\nPoint.curl(index, none, 0.5);\nPoint.curl(middle, full, 0.5);\nPoint.curl(ring, full, 0.5);\nPoint.curl(pinky, full, 0.5);\nPoint.weight(index, 2);\nPoint.weight(middle, 2);\n\n// describe Point gesture \u270C\uFE0F\nconst MiddleFinger = new FingerGesture('middle finger');\nMiddleFinger.curl(thumb, none, 1.0);\nMiddleFinger.curl(index, full, 0.5);\nMiddleFinger.curl(middle, full, 0.5);\nMiddleFinger.curl(ring, full, 0.5);\nMiddleFinger.curl(pinky, full, 0.5);\nMiddleFinger.weight(index, 2);\nMiddleFinger.weight(middle, 2);\n\n// describe Open Palm gesture \u270C\uFE0F\nconst OpenPalm = new FingerGesture('open palm');\nOpenPalm.curl(thumb, none, 0.75);\nOpenPalm.curl(index, none, 0.75);\nOpenPalm.curl(middle, none, 0.75);\nOpenPalm.curl(ring, none, 0.75);\nOpenPalm.curl(pinky, none, 0.75);\n\nexport default [ThumbsUp, Victory, Point, MiddleFinger, OpenPalm];\n", "/**\n * FingerPose algorithm implementation constants\n *\n * Based on: [**FingerPose***](https://github.com/andypotato/fingerpose)\n */\n\nimport { Finger, FingerCurl, FingerDirection } from './fingerdef';\nimport Gestures from '../hand/fingergesture';\n\nconst minConfidence = 0.7;\nconst options = {\n  // curl estimation\n  HALF_CURL_START_LIMIT: 60.0,\n  NO_CURL_START_LIMIT: 130.0,\n  // direction estimation\n  DISTANCE_VOTE_POWER: 1.1,\n  SINGLE_ANGLE_VOTE_POWER: 0.9,\n  TOTAL_ANGLE_VOTE_POWER: 1.6,\n};\n\nfunction calculateSlope(point1x, point1y, point2x, point2y) {\n  const value = (point1y - point2y) / (point1x - point2x);\n  let slope = Math.atan(value) * 180 / Math.PI;\n  if (slope <= 0) slope = -slope;\n  else if (slope > 0) slope = 180 - slope;\n  return slope;\n}\n\n// point1, point2 are 2d or 3d point arrays (xy[z])\n// returns either a single scalar (2d) or array of two slopes (3d)\nfunction getSlopes(point1, point2) {\n  if (!point1 || !point2) return [0, 0];\n  const slopeXY = calculateSlope(point1[0], point1[1], point2[0], point2[1]);\n  if (point1.length === 2) return slopeXY;\n  const slopeYZ = calculateSlope(point1[1], point1[2], point2[1], point2[2]);\n  return [slopeXY, slopeYZ];\n}\n\nfunction angleOrientationAt(angle, weightageAt = 1.0) {\n  let isVertical = 0;\n  let isDiagonal = 0;\n  let isHorizontal = 0;\n  if (angle >= 75.0 && angle <= 105.0) isVertical = 1 * weightageAt;\n  else if (angle >= 25.0 && angle <= 155.0) isDiagonal = 1 * weightageAt;\n  else isHorizontal = 1 * weightageAt;\n  return [isVertical, isDiagonal, isHorizontal];\n}\n\nfunction estimateFingerCurl(startPoint, midPoint, endPoint) {\n  const start_mid_x_dist = startPoint[0] - midPoint[0];\n  const start_end_x_dist = startPoint[0] - endPoint[0];\n  const mid_end_x_dist = midPoint[0] - endPoint[0];\n  const start_mid_y_dist = startPoint[1] - midPoint[1];\n  const start_end_y_dist = startPoint[1] - endPoint[1];\n  const mid_end_y_dist = midPoint[1] - endPoint[1];\n  const start_mid_z_dist = startPoint[2] - midPoint[2];\n  const start_end_z_dist = startPoint[2] - endPoint[2];\n  const mid_end_z_dist = midPoint[2] - endPoint[2];\n  const start_mid_dist = Math.sqrt(start_mid_x_dist * start_mid_x_dist + start_mid_y_dist * start_mid_y_dist + start_mid_z_dist * start_mid_z_dist);\n  const start_end_dist = Math.sqrt(start_end_x_dist * start_end_x_dist + start_end_y_dist * start_end_y_dist + start_end_z_dist * start_end_z_dist);\n  const mid_end_dist = Math.sqrt(mid_end_x_dist * mid_end_x_dist + mid_end_y_dist * mid_end_y_dist + mid_end_z_dist * mid_end_z_dist);\n  let cos_in = (mid_end_dist * mid_end_dist + start_mid_dist * start_mid_dist - start_end_dist * start_end_dist) / (2 * mid_end_dist * start_mid_dist);\n  if (cos_in > 1.0) cos_in = 1.0;\n  else if (cos_in < -1.0) cos_in = -1.0;\n  let angleOfCurve = Math.acos(cos_in);\n  angleOfCurve = (57.2958 * angleOfCurve) % 180;\n  let fingerCurl;\n  if (angleOfCurve > options.NO_CURL_START_LIMIT) fingerCurl = FingerCurl.none;\n  else if (angleOfCurve > options.HALF_CURL_START_LIMIT) fingerCurl = FingerCurl.half;\n  else fingerCurl = FingerCurl.full;\n  return fingerCurl;\n}\n\nfunction estimateHorizontalDirection(start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x) {\n  let estimatedDirection;\n  if (max_dist_x === Math.abs(start_end_x_dist)) {\n    if (start_end_x_dist > 0) estimatedDirection = FingerDirection.horizontalLeft;\n    else estimatedDirection = FingerDirection.horizontalRight;\n  } else if (max_dist_x === Math.abs(start_mid_x_dist)) {\n    if (start_mid_x_dist > 0) estimatedDirection = FingerDirection.horizontalLeft;\n    else estimatedDirection = FingerDirection.horizontalRight;\n  } else {\n    if (mid_end_x_dist > 0) estimatedDirection = FingerDirection.horizontalLeft;\n    else estimatedDirection = FingerDirection.horizontalRight;\n  }\n  return estimatedDirection;\n}\n\nfunction estimateVerticalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y) {\n  let estimatedDirection;\n  if (max_dist_y === Math.abs(start_end_y_dist)) {\n    if (start_end_y_dist < 0) estimatedDirection = FingerDirection.verticalDown;\n    else estimatedDirection = FingerDirection.verticalUp;\n  } else if (max_dist_y === Math.abs(start_mid_y_dist)) {\n    if (start_mid_y_dist < 0) estimatedDirection = FingerDirection.verticalDown;\n    else estimatedDirection = FingerDirection.verticalUp;\n  } else {\n    if (mid_end_y_dist < 0) estimatedDirection = FingerDirection.verticalDown;\n    else estimatedDirection = FingerDirection.verticalUp;\n  }\n  return estimatedDirection;\n}\n\nfunction estimateDiagonalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y, start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x) {\n  let estimatedDirection;\n  const reqd_vertical_direction = estimateVerticalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y);\n  const reqd_horizontal_direction = estimateHorizontalDirection(start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x);\n  if (reqd_vertical_direction === FingerDirection.verticalUp) {\n    if (reqd_horizontal_direction === FingerDirection.horizontalLeft) estimatedDirection = FingerDirection.diagonalUpLeft;\n    else estimatedDirection = FingerDirection.diagonalUpRight;\n  } else {\n    if (reqd_horizontal_direction === FingerDirection.horizontalLeft) estimatedDirection = FingerDirection.diagonalDownLeft;\n    else estimatedDirection = FingerDirection.diagonalDownRight;\n  }\n  return estimatedDirection;\n}\n\nfunction calculateFingerDirection(startPoint, midPoint, endPoint, fingerSlopes) {\n  const start_mid_x_dist = startPoint[0] - midPoint[0];\n  const start_end_x_dist = startPoint[0] - endPoint[0];\n  const mid_end_x_dist = midPoint[0] - endPoint[0];\n  const start_mid_y_dist = startPoint[1] - midPoint[1];\n  const start_end_y_dist = startPoint[1] - endPoint[1];\n  const mid_end_y_dist = midPoint[1] - endPoint[1];\n  const max_dist_x = Math.max(Math.abs(start_mid_x_dist), Math.abs(start_end_x_dist), Math.abs(mid_end_x_dist));\n  const max_dist_y = Math.max(Math.abs(start_mid_y_dist), Math.abs(start_end_y_dist), Math.abs(mid_end_y_dist));\n  let voteVertical = 0.0;\n  let voteDiagonal = 0.0;\n  let voteHorizontal = 0.0;\n  const start_end_x_y_dist_ratio = max_dist_y / (max_dist_x + 0.00001);\n  if (start_end_x_y_dist_ratio > 1.5) voteVertical += options.DISTANCE_VOTE_POWER;\n  else if (start_end_x_y_dist_ratio > 0.66) voteDiagonal += options.DISTANCE_VOTE_POWER;\n  else voteHorizontal += options.DISTANCE_VOTE_POWER;\n  const start_mid_dist = Math.sqrt(start_mid_x_dist * start_mid_x_dist + start_mid_y_dist * start_mid_y_dist);\n  const start_end_dist = Math.sqrt(start_end_x_dist * start_end_x_dist + start_end_y_dist * start_end_y_dist);\n  const mid_end_dist = Math.sqrt(mid_end_x_dist * mid_end_x_dist + mid_end_y_dist * mid_end_y_dist);\n  const max_dist = Math.max(start_mid_dist, start_end_dist, mid_end_dist);\n  let calc_start_point_x = startPoint[0];\n  let calc_start_point_y = startPoint[1];\n  let calc_end_point_x = endPoint[0];\n  let calc_end_point_y = endPoint[1];\n  if (max_dist === start_mid_dist) {\n    calc_end_point_x = endPoint[0];\n    calc_end_point_y = endPoint[1];\n  } else if (max_dist === mid_end_dist) {\n    calc_start_point_x = midPoint[0];\n    calc_start_point_y = midPoint[1];\n  }\n  const calcStartPoint = [calc_start_point_x, calc_start_point_y];\n  const calcEndPoint = [calc_end_point_x, calc_end_point_y];\n  const totalAngle = getSlopes(calcStartPoint, calcEndPoint);\n  const votes = angleOrientationAt(totalAngle, options.TOTAL_ANGLE_VOTE_POWER);\n  voteVertical += votes[0];\n  voteDiagonal += votes[1];\n  voteHorizontal += votes[2];\n  for (const fingerSlope of fingerSlopes) {\n    const fingerVotes = angleOrientationAt(fingerSlope, options.SINGLE_ANGLE_VOTE_POWER);\n    voteVertical += fingerVotes[0];\n    voteDiagonal += fingerVotes[1];\n    voteHorizontal += fingerVotes[2];\n  }\n  // in case of tie, highest preference goes to Vertical,\n  // followed by horizontal and then diagonal\n  let estimatedDirection;\n  if (voteVertical === Math.max(voteVertical, voteDiagonal, voteHorizontal)) {\n    estimatedDirection = estimateVerticalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y);\n  } else if (voteHorizontal === Math.max(voteDiagonal, voteHorizontal)) {\n    estimatedDirection = estimateHorizontalDirection(start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x);\n  } else {\n    estimatedDirection = estimateDiagonalDirection(start_end_y_dist, start_mid_y_dist, mid_end_y_dist, max_dist_y, start_end_x_dist, start_mid_x_dist, mid_end_x_dist, max_dist_x);\n  }\n  return estimatedDirection;\n}\n\nfunction estimate(landmarks) {\n  // step 1: calculate slopes\n  const slopesXY: Array<number[]> = [];\n  const slopesYZ: Array<number[]> = [];\n  const fingerCurls: Array<number> = [];\n  const fingerDirections: Array<number> = [];\n  if (!landmarks) return { curls: fingerCurls, directions: fingerDirections };\n\n  // step 1: calculate slopes\n  for (const finger of Finger.all) {\n    const points = Finger.getPoints(finger);\n    const slopeAtXY: Array<number> = [];\n    const slopeAtYZ: Array<number> = [];\n    for (const point of points) {\n      const point1 = landmarks[point[0]];\n      const point2 = landmarks[point[1]];\n      // calculate single slope\n      const slopes = getSlopes(point1, point2);\n      const slopeXY = slopes[0];\n      const slopeYZ = slopes[1];\n      slopeAtXY.push(slopeXY);\n      slopeAtYZ.push(slopeYZ);\n    }\n    slopesXY.push(slopeAtXY);\n    slopesYZ.push(slopeAtYZ);\n  }\n\n  // step 2: calculate orientations\n  for (const finger of Finger.all) {\n    // start finger predictions from palm - except for thumb\n    const pointIndexAt = (finger === Finger.thumb) ? 1 : 0;\n    const fingerPointsAt = Finger.getPoints(finger);\n    const startPoint = landmarks[fingerPointsAt[pointIndexAt][0]];\n    const midPoint = landmarks[fingerPointsAt[pointIndexAt + 1][1]];\n    const endPoint = landmarks[fingerPointsAt[3][1]];\n    // check if finger is curled\n    const fingerCurled = estimateFingerCurl(startPoint, midPoint, endPoint);\n    const fingerPosition = calculateFingerDirection(startPoint, midPoint, endPoint, slopesXY[finger].slice(pointIndexAt));\n    fingerCurls[finger] = fingerCurled;\n    fingerDirections[finger] = fingerPosition;\n  }\n  return { curls: fingerCurls, directions: fingerDirections };\n}\n\nexport function analyze(keypoints) { // get estimations of curl / direction for each finger\n  if (!keypoints || keypoints.length === 0) return null;\n  const estimatorRes = estimate(keypoints);\n  const landmarks = {};\n  for (const fingerIdx of Finger.all) {\n    landmarks[Finger.getName(fingerIdx)] = {\n      curl: FingerCurl.getName(estimatorRes.curls[fingerIdx]),\n      direction: FingerDirection.getName(estimatorRes.directions[fingerIdx]),\n    };\n  }\n  return landmarks;\n}\n\nexport function match(keypoints) { // compare gesture description to each known gesture\n  const poses: Array<{ name: string, confidence: number }> = [];\n  if (!keypoints || keypoints.length === 0) return poses;\n  const estimatorRes = estimate(keypoints);\n  for (const gesture of Gestures) {\n    const confidence = gesture.matchAgainst(estimatorRes.curls, estimatorRes.directions);\n    if (confidence >= minConfidence) poses.push({ name: gesture.name, confidence });\n  }\n  return poses;\n}\n", "/**\n * HandPose model implementation\n *\n * Based on: [**MediaPipe HandPose**](https://drive.google.com/file/d/1sv4sSb9BSNVZhLzxXJ0jBv9DqD-4jnAz/view)\n */\n\nimport { log } from '../util/util';\nimport * as handdetector from './handposedetector';\nimport * as handpipeline from './handposepipeline';\nimport * as fingerPose from './fingerpose';\nimport { loadModel } from '../tfjs/load';\nimport type { HandResult, Box, Point } from '../result';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nconst meshAnnotations = {\n  thumb: [1, 2, 3, 4],\n  index: [5, 6, 7, 8],\n  middle: [9, 10, 11, 12],\n  ring: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  palm: [0],\n};\n\nlet handDetectorModel: GraphModel | null;\nlet handPoseModel: GraphModel | null;\nlet handPipeline: handpipeline.HandPipeline;\n\nexport async function predict(input: Tensor, config: Config): Promise<HandResult[]> {\n  const predictions = await handPipeline.estimateHands(input, config);\n  if (!predictions) return [];\n  const hands: Array<HandResult> = [];\n  for (let i = 0; i < predictions.length; i++) {\n    const annotations = {};\n    if (predictions[i].landmarks) {\n      for (const key of Object.keys(meshAnnotations)) {\n        annotations[key] = meshAnnotations[key].map((index) => predictions[i].landmarks[index]);\n      }\n    }\n    const keypoints = predictions[i].landmarks as unknown as Array<Point>;\n    let box: Box = [Number.MAX_SAFE_INTEGER, Number.MAX_SAFE_INTEGER, 0, 0]; // maximums so conditionals work\n    let boxRaw: Box = [0, 0, 0, 0];\n    if (keypoints && keypoints.length > 0) { // if we have landmarks, calculate box based on landmarks\n      for (const pt of keypoints) {\n        if (pt[0] < box[0]) box[0] = pt[0];\n        if (pt[1] < box[1]) box[1] = pt[1];\n        if (pt[0] > box[2]) box[2] = pt[0];\n        if (pt[1] > box[3]) box[3] = pt[1];\n      }\n      box[2] -= box[0];\n      box[3] -= box[1];\n      boxRaw = [box[0] / (input.shape[2] || 0), box[1] / (input.shape[1] || 0), box[2] / (input.shape[2] || 0), box[3] / (input.shape[1] || 0)];\n    } else { // otherwise use box from prediction\n      box = predictions[i].box ? [\n        Math.trunc(Math.max(0, predictions[i].box.topLeft[0])),\n        Math.trunc(Math.max(0, predictions[i].box.topLeft[1])),\n        Math.trunc(Math.min((input.shape[2] || 0), predictions[i].box.bottomRight[0]) - Math.max(0, predictions[i].box.topLeft[0])),\n        Math.trunc(Math.min((input.shape[1] || 0), predictions[i].box.bottomRight[1]) - Math.max(0, predictions[i].box.topLeft[1])),\n      ] : [0, 0, 0, 0];\n      boxRaw = [\n        (predictions[i].box.topLeft[0]) / (input.shape[2] || 0),\n        (predictions[i].box.topLeft[1]) / (input.shape[1] || 0),\n        (predictions[i].box.bottomRight[0] - predictions[i].box.topLeft[0]) / (input.shape[2] || 0),\n        (predictions[i].box.bottomRight[1] - predictions[i].box.topLeft[1]) / (input.shape[1] || 0),\n      ];\n    }\n    const landmarks = fingerPose.analyze(keypoints);\n    hands.push({\n      id: i,\n      score: Math.round(100 * predictions[i].confidence) / 100,\n      boxScore: Math.round(100 * predictions[i].boxConfidence) / 100,\n      fingerScore: Math.round(100 * predictions[i].fingerConfidence) / 100,\n      label: 'hand',\n      box,\n      boxRaw,\n      keypoints,\n      annotations: annotations as HandResult['annotations'],\n      landmarks: landmarks as HandResult['landmarks'],\n    });\n  }\n  return hands;\n}\n\nexport async function load(config: Config): Promise<[GraphModel | null, GraphModel | null]> {\n  if (env.initial) {\n    handDetectorModel = null;\n    handPoseModel = null;\n  }\n  if (!handDetectorModel || !handPoseModel) {\n    [handDetectorModel, handPoseModel] = await Promise.all([\n      config.hand.enabled ? loadModel(config.hand.detector?.modelPath) : null,\n      config.hand.landmarks ? loadModel(config.hand.skeleton?.modelPath) : null,\n    ]);\n  } else {\n    if (config.debug) log('cached model:', handDetectorModel['modelUrl']);\n    if (config.debug) log('cached model:', handPoseModel['modelUrl']);\n  }\n  const handDetector = new handdetector.HandDetector(handDetectorModel);\n  handPipeline = new handpipeline.HandPipeline(handDetector, handPoseModel);\n  return [handDetectorModel, handPoseModel];\n}\n", "/**\n * HandTrack model implementation\n *\n * Based on:\n * - Hand Detection & Skeleton: [**MediaPipe HandPose**](https://drive.google.com/file/d/1sv4sSb9BSNVZhLzxXJ0jBv9DqD-4jnAz/view)\n * - Hand Tracking: [**HandTracking**](https://github.com/victordibia/handtracking)\n */\n\nimport { log, now } from '../util/util';\nimport * as box from '../util/box';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { HandResult, HandType, Box, Point } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\nimport * as fingerPose from './fingerpose';\nimport { fakeOps } from '../tfjs/backend';\nimport { constants } from '../tfjs/constants';\n\nconst models: [GraphModel | null, GraphModel | null] = [null, null];\nconst modelOutputNodes = ['StatefulPartitionedCall/Postprocessor/Slice', 'StatefulPartitionedCall/Postprocessor/ExpandDims_1'];\n\nconst inputSize = [[0, 0], [0, 0]];\n\nconst classes = ['hand', 'fist', 'pinch', 'point', 'face', 'tip', 'pinchtip'];\nconst faceIndex = 4;\n\nconst boxExpandFact = 1.6;\nconst maxDetectorResolution = 512;\nconst detectorExpandFact = 1.4;\n\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet lastTime = 0;\nlet outputSize: [number, number] = [0, 0];\n\ntype HandDetectResult = {\n  id: number,\n  score: number,\n  box: Box,\n  boxRaw: Box,\n  label: HandType,\n}\n\nconst cache: {\n  boxes: Array<HandDetectResult>,\n  hands: Array<HandResult>;\n} = {\n  boxes: [],\n  hands: [],\n};\n\nconst fingerMap = {\n  /*\n  thumb: [0, 1, 2, 3, 4],\n  index: [0, 5, 6, 7, 8],\n  middle: [0, 9, 10, 11, 12],\n  ring: [0, 13, 14, 15, 16],\n  pinky: [0, 17, 18, 19, 20],\n  palm: [0],\n  */\n  thumb: [1, 2, 3, 4],\n  index: [5, 6, 7, 8],\n  middle: [9, 10, 11, 12],\n  ring: [13, 14, 15, 16],\n  pinky: [17, 18, 19, 20],\n  base: [0],\n  palm: [0, 17, 13, 9, 5, 1, 0],\n};\n\nexport async function loadDetect(config: Config): Promise<GraphModel> {\n  // HandTrack Model: Original: <https://github.com/victordibia/handtracking> TFJS Port: <https://github.com/victordibia/handtrack.js/>\n  if (env.initial) models[0] = null;\n  if (!models[0]) {\n    // handtrack model has some kernel ops defined in model but those are never referenced and non-existent in tfjs\n    // ideally need to prune the model itself\n    fakeOps(['tensorlistreserve', 'enter', 'tensorlistfromtensor', 'merge', 'loopcond', 'switch', 'exit', 'tensorliststack', 'nextiteration', 'tensorlistsetitem', 'tensorlistgetitem', 'reciprocal', 'shape', 'split', 'where'], config);\n    models[0] = await loadModel(config.hand.detector?.modelPath);\n    const inputs = Object.values(models[0].modelSignature['inputs']);\n    inputSize[0][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize[0][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', models[0]['modelUrl']);\n  return models[0];\n}\n\nexport async function loadSkeleton(config: Config): Promise<GraphModel> {\n  if (env.initial) models[1] = null;\n  if (!models[1]) {\n    models[1] = await loadModel(config.hand.skeleton?.modelPath);\n    const inputs = Object.values(models[1].modelSignature['inputs']);\n    inputSize[1][0] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[1].size) : 0;\n    inputSize[1][1] = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', models[1]['modelUrl']);\n  return models[1];\n}\n\nexport async function load(config: Config): Promise<[GraphModel | null, GraphModel | null]> {\n  if (!models[0]) await loadDetect(config);\n  if (!models[1]) await loadSkeleton(config);\n  return models;\n}\n\nasync function detectHands(input: Tensor, config: Config): Promise<HandDetectResult[]> {\n  const hands: HandDetectResult[] = [];\n  if (!input || !models[0]) return hands;\n  const t: Record<string, Tensor> = {};\n  const ratio = (input.shape[2] || 1) / (input.shape[1] || 1);\n  const height = Math.min(Math.round((input.shape[1] || 0) / 8) * 8, maxDetectorResolution); // use dynamic input size but cap at 512\n  const width = Math.round(height * ratio / 8) * 8;\n  t.resize = tf.image.resizeBilinear(input, [height, width]); // todo: resize with padding\n  t.cast = tf.cast(t.resize, 'int32');\n  [t.rawScores, t.rawBoxes] = await models[0].executeAsync(t.cast, modelOutputNodes) as Tensor[];\n  t.boxes = tf.squeeze(t.rawBoxes, [0, 2]);\n  t.scores = tf.squeeze(t.rawScores, [0]);\n  const classScores: Array<Tensor> = tf.unstack(t.scores, 1); // unstack scores based on classes\n  tf.dispose(classScores[faceIndex]);\n  classScores.splice(faceIndex, 1); // remove faces\n  t.filtered = tf.stack(classScores, 1); // restack\n  tf.dispose(classScores);\n  // t.filtered = t.scores;\n  t.max = tf.max(t.filtered, 1); // max overall score\n  t.argmax = tf.argMax(t.filtered, 1); // class index of max overall score\n  let id = 0;\n  t.nms = await tf.image.nonMaxSuppressionAsync(t.boxes, t.max, (config.hand.maxDetected || 0) + 1, config.hand.iouThreshold || 0, config.hand.minConfidence || 1);\n  const nms = await t.nms.data();\n  const scores = await t.max.data();\n  const classNum = await t.argmax.data();\n  for (const nmsIndex of Array.from(nms)) { // generates results for each class\n    const boxSlice = tf.slice(t.boxes, nmsIndex, 1);\n    const boxYX = await boxSlice.data();\n    tf.dispose(boxSlice);\n    const boxData: Box = [boxYX[1], boxYX[0], boxYX[3] - boxYX[1], boxYX[2] - boxYX[0]]; // yx box reshaped to standard box\n    const boxRaw: Box = box.scale(boxData, detectorExpandFact);\n    const boxFull: Box = [Math.trunc(boxData[0] * outputSize[0]), Math.trunc(boxData[1] * outputSize[1]), Math.trunc(boxData[2] * outputSize[0]), Math.trunc(boxData[3] * outputSize[1])];\n    const score = scores[nmsIndex];\n    const label = classes[classNum[nmsIndex]] as HandType;\n    const hand: HandDetectResult = { id: id++, score, box: boxFull, boxRaw, label };\n    hands.push(hand);\n  }\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  hands.sort((a, b) => b.score - a.score);\n  if (hands.length > (config.hand.maxDetected || 1)) hands.length = (config.hand.maxDetected || 1);\n  return hands;\n}\n\nasync function detectFingers(input: Tensor, h: HandDetectResult, config: Config): Promise<HandResult> {\n  const hand: HandResult = { // initial values inherited from hand detect\n    id: h.id,\n    score: Math.round(100 * h.score) / 100,\n    boxScore: Math.round(100 * h.score) / 100,\n    fingerScore: 0,\n    box: h.box,\n    boxRaw: h.boxRaw,\n    label: h.label,\n    keypoints: [],\n    landmarks: {} as HandResult['landmarks'],\n    annotations: {} as HandResult['annotations'],\n  };\n  if (input && models[1] && config.hand.landmarks && h.score > (config.hand.minConfidence || 0)) {\n    const t: Record<string, Tensor> = {};\n    const boxCrop = [h.boxRaw[1], h.boxRaw[0], h.boxRaw[3] + h.boxRaw[1], h.boxRaw[2] + h.boxRaw[0]] as Box;\n    t.crop = tf.image.cropAndResize(input, [boxCrop], [0], [inputSize[1][0], inputSize[1][1]], 'bilinear');\n    t.div = tf.div(t.crop, constants.tf255);\n    [t.score, t.keypoints] = models[1].execute(t.div, ['Identity_1', 'Identity']) as Tensor[];\n    const rawScore = (await t.score.data())[0];\n    const score = (100 - Math.trunc(100 / (1 + Math.exp(rawScore)))) / 100; // reverse sigmoid value\n    if (score >= (config.hand.minConfidence || 0)) {\n      hand.fingerScore = score;\n      t.reshaped = tf.reshape(t.keypoints, [-1, 3]);\n      const coordsData: Point[] = await t.reshaped.array() as Point[];\n      const coordsRaw: Point[] = coordsData.map((kpt) => [kpt[0] / inputSize[1][1], kpt[1] / inputSize[1][0], (kpt[2] || 0)]);\n      const coordsNorm: Point[] = coordsRaw.map((kpt) => [kpt[0] * h.boxRaw[2], kpt[1] * h.boxRaw[3], (kpt[2] || 0)]);\n      hand.keypoints = (coordsNorm).map((kpt) => [outputSize[0] * (kpt[0] + h.boxRaw[0]), outputSize[1] * (kpt[1] + h.boxRaw[1]), (kpt[2] || 0)]);\n      hand.landmarks = fingerPose.analyze(hand.keypoints) as HandResult['landmarks']; // calculate finger gestures\n      for (const key of Object.keys(fingerMap)) { // map keypoints to per-finger annotations\n        hand.annotations[key] = fingerMap[key].map((index: number) => (hand.landmarks && hand.keypoints[index] ? hand.keypoints[index] : null));\n      }\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  }\n  return hand;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<HandResult[]> {\n  if (!models[0] || !models[1] || !models[0]?.inputs[0].shape || !models[1]?.inputs[0].shape) return []; // something is wrong with the model\n  outputSize = [input.shape[2] || 0, input.shape[1] || 0];\n  skipped++; // increment skip frames\n  const skipTime = (config.hand.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.hand.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame) {\n    return cache.hands; // return cached results without running anything\n  }\n  return new Promise(async (resolve) => {\n    const skipTimeExtended = 3 * (config.hand.skipTime || 0) > (now() - lastTime);\n    const skipFrameExtended = skipped < 3 * (config.hand.skipFrames || 0);\n    if (config.skipAllowed && cache.hands.length === config.hand.maxDetected) { // we have all detected hands so we're definitely skipping\n      cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));\n    } else if (config.skipAllowed && skipTimeExtended && skipFrameExtended && cache.hands.length > 0) { // we have some cached results: maybe not enough but anyhow continue for bit longer\n      cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));\n    } else { // finally rerun detector\n      cache.boxes = await detectHands(input, config);\n      lastTime = now();\n      cache.hands = await Promise.all(cache.boxes.map((handBox) => detectFingers(input, handBox, config)));\n      skipped = 0;\n    }\n\n    const oldCache = [...cache.boxes];\n    cache.boxes.length = 0; // reset cache\n    if (config.cacheSensitivity > 0) {\n      for (let i = 0; i < cache.hands.length; i++) {\n        const boxKpt = box.square(cache.hands[i].keypoints, outputSize);\n        if (boxKpt.box[2] / (input.shape[2] || 1) > 0.05 && boxKpt.box[3] / (input.shape[1] || 1) > 0.05 && cache.hands[i].fingerScore && cache.hands[i].fingerScore > (config.hand.minConfidence || 0)) {\n          const boxScale = box.scale(boxKpt.box, boxExpandFact);\n          const boxScaleRaw = box.scale(boxKpt.boxRaw, boxExpandFact);\n          // const boxCrop = box.crop(boxScaleRaw);\n          cache.boxes.push({ ...oldCache[i], box: boxScale, boxRaw: boxScaleRaw });\n        }\n      }\n    }\n    for (let i = 0; i < cache.hands.length; i++) { // replace detected boxes with calculated boxes in final output\n      const bbox = box.calc(cache.hands[i].keypoints, outputSize);\n      cache.hands[i].box = bbox.box;\n      cache.hands[i].boxRaw = bbox.boxRaw;\n    }\n    resolve(cache.hands);\n  });\n}\n", "/**\n * Anti-spoofing model implementation\n */\n\nimport { log, now } from '../util/util';\nimport { loadModel } from '../tfjs/load';\nimport type { Config } from '../config';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nconst cached: Array<number> = [];\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet lastCount = 0;\nlet lastTime = 0;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) model = await loadModel(config.face.liveness?.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function predict(image: Tensor, config: Config, idx: number, count: number): Promise<number> {\n  if (!model) return 0;\n  const skipTime = (config.face.liveness?.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.face.liveness?.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (lastCount === count) && cached[idx]) {\n    skipped++;\n    return cached[idx];\n  }\n  skipped = 0;\n  return new Promise(async (resolve) => {\n    const resize = tf.image.resizeBilinear(image, [model?.inputs[0].shape ? model.inputs[0].shape[2] : 0, model?.inputs[0].shape ? model.inputs[0].shape[1] : 0], false);\n    const res = model?.execute(resize) as Tensor;\n    const num = (await res.data())[0];\n    cached[idx] = Math.round(100 * num) / 100;\n    lastCount = count;\n    lastTime = now();\n    tf.dispose([resize, res]);\n    resolve(cached[idx]);\n  });\n}\n", "export const kpt: Array<string> = [ // used to create part labels\n  'nose',\n  'leftEye',\n  'rightEye',\n  'leftEar',\n  'rightEar',\n  'leftShoulder',\n  'rightShoulder',\n  'leftElbow',\n  'rightElbow',\n  'leftWrist',\n  'rightWrist',\n  'leftHip',\n  'rightHip',\n  'leftKnee',\n  'rightKnee',\n  'leftAnkle',\n  'rightAnkle',\n];\n\nexport const horizontal: Array<string[]> = [ // used to fix left vs right\n  ['leftEye', 'rightEye'],\n  ['leftEar', 'rightEar'],\n  ['leftShoulder', 'rightShoulder'],\n  ['leftElbow', 'rightElbow'],\n  ['leftWrist', 'rightWrist'],\n  ['leftHip', 'rightHip'],\n  ['leftKnee', 'rightKnee'],\n  ['leftAnkle', 'rightAnkle'],\n];\n\nexport const vertical: Array<string[]> = [ // used to remove unlikely keypoint positions\n  ['leftKnee', 'leftShoulder'],\n  ['rightKnee', 'rightShoulder'],\n  ['leftAnkle', 'leftKnee'],\n  ['rightAnkle', 'rightKnee'],\n];\n\nexport const relative: Array<string[][]> = [ // used to match relative body parts\n  [['leftHip', 'rightHip'], ['leftShoulder', 'rightShoulder']],\n  [['leftElbow', 'rightElbow'], ['leftShoulder', 'rightShoulder']],\n];\n\nexport const connected: Record<string, string[]> = { // used to create body outline in annotations\n  leftLeg: ['leftHip', 'leftKnee', 'leftAnkle'],\n  rightLeg: ['rightHip', 'rightKnee', 'rightAnkle'],\n  torso: ['leftShoulder', 'rightShoulder', 'rightHip', 'leftHip', 'leftShoulder'],\n  leftArm: ['leftShoulder', 'leftElbow', 'leftWrist'],\n  rightArm: ['rightShoulder', 'rightElbow', 'rightWrist'],\n  head: [],\n};\n", "import type { BodyKeypoint, BodyResult } from '../result';\nimport * as box from '../util/box';\nimport * as coords from './movenetcoords';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport type { Tensor } from '../tfjs/types';\n\nconst maxJitter = 0.005; // default allowed jitter is within 0.5%\n\nconst cache: {\n  keypoints: Array<BodyKeypoint>,\n  padding: [number, number][];\n} = {\n  keypoints: [],\n  padding: [[0, 0], [0, 0], [0, 0], [0, 0]],\n};\n\nexport function bodyParts(body: BodyResult) { // model sometimes mixes up left vs right keypoints so we fix them\n  for (const pair of coords.horizontal) { // fix body parts left vs right\n    const left = body.keypoints.findIndex((kp) => kp.part === pair[0]);\n    const right = body.keypoints.findIndex((kp) => kp.part === pair[1]);\n    if (body.keypoints[left] && body.keypoints[right]) {\n      if (body.keypoints[left].position[0] < body.keypoints[right].position[0]) {\n        const tmp = body.keypoints[left];\n        body.keypoints[left] = body.keypoints[right];\n        body.keypoints[right] = tmp;\n      }\n    }\n  }\n  for (const pair of coords.vertical) { // remove body parts with improbable vertical position\n    const lower = body.keypoints.findIndex((kp) => (kp && kp.part === pair[0]));\n    const higher = body.keypoints.findIndex((kp) => (kp && kp.part === pair[1]));\n    if (body.keypoints[lower] && body.keypoints[higher]) {\n      if (body.keypoints[lower].position[1] < body.keypoints[higher].position[1]) {\n        body.keypoints.splice(lower, 1);\n      }\n    }\n  }\n  for (const [pair, compare] of coords.relative) { // rearrange body parts according to their relative position\n    const left = body.keypoints.findIndex((kp) => (kp && kp.part === pair[0]));\n    const right = body.keypoints.findIndex((kp) => (kp && kp.part === pair[1]));\n    const leftTo = body.keypoints.findIndex((kp) => (kp && kp.part === compare[0]));\n    const rightTo = body.keypoints.findIndex((kp) => (kp && kp.part === compare[1]));\n    if (!body.keypoints[leftTo] || !body.keypoints[rightTo]) continue; // only if we have both compare points\n    const distanceLeft = body.keypoints[left] ? [\n      Math.abs(body.keypoints[leftTo].position[0] - body.keypoints[left].position[0]),\n      Math.abs(body.keypoints[rightTo].position[0] - body.keypoints[left].position[0]),\n    ] : [0, 0];\n    const distanceRight = body.keypoints[right] ? [\n      Math.abs(body.keypoints[rightTo].position[0] - body.keypoints[right].position[0]),\n      Math.abs(body.keypoints[leftTo].position[0] - body.keypoints[right].position[0]),\n    ] : [0, 0];\n    if (distanceLeft[0] > distanceLeft[1] || distanceRight[0] > distanceRight[1]) { // should flip keypoints\n      const tmp = body.keypoints[left];\n      body.keypoints[left] = body.keypoints[right];\n      body.keypoints[right] = tmp;\n    }\n  }\n}\n\nexport function jitter(keypoints: Array<BodyKeypoint>): Array<BodyKeypoint> {\n  for (let i = 0; i < keypoints.length; i++) {\n    if (keypoints[i] && cache.keypoints[i]) {\n      const diff = [Math.abs(keypoints[i].positionRaw[0] - cache.keypoints[i].positionRaw[0]), Math.abs(keypoints[i].positionRaw[1] - cache.keypoints[i].positionRaw[1])];\n      if (diff[0] < maxJitter && diff[1] < maxJitter) {\n        keypoints[i] = cache.keypoints[i]; // below jitter so replace keypoint\n      } else {\n        cache.keypoints[i] = keypoints[i]; // above jitter so update cache\n      }\n    } else {\n      cache.keypoints[i] = keypoints[i]; // cache for keypoint doesnt exist so create it here\n    }\n  }\n  return keypoints;\n}\n\nexport function padInput(input: Tensor, inputSize: number): Tensor {\n  const t: Record<string, Tensor> = {};\n  if (!input.shape || !input.shape[1] || !input.shape[2]) return input;\n  cache.padding = [\n    [0, 0], // dont touch batch\n    [input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0, input.shape[2] > input.shape[1] ? Math.trunc((input.shape[2] - input.shape[1]) / 2) : 0], // height before&after\n    [input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0, input.shape[1] > input.shape[2] ? Math.trunc((input.shape[1] - input.shape[2]) / 2) : 0], // width before&after\n    [0, 0], // dont touch rbg\n  ];\n  t.pad = tf.pad(input, cache.padding);\n  t.resize = tf.image.resizeBilinear(t.pad, [inputSize, inputSize]);\n  const final = tf.cast(t.resize, 'int32');\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  return final;\n}\n\nexport function rescaleBody(body: BodyResult, outputSize: [number, number]): BodyResult {\n  body.keypoints = body.keypoints.filter((kpt) => kpt && kpt.position); // filter invalid keypoints\n  for (const kpt of body.keypoints) {\n    kpt.position = [\n      kpt.position[0] * (outputSize[0] + cache.padding[2][0] + cache.padding[2][1]) / outputSize[0] - cache.padding[2][0],\n      kpt.position[1] * (outputSize[1] + cache.padding[1][0] + cache.padding[1][1]) / outputSize[1] - cache.padding[1][0],\n    ];\n    kpt.positionRaw = [\n      kpt.position[0] / outputSize[0], kpt.position[1] / outputSize[1],\n    ];\n  }\n  const rescaledBoxes = box.calc(body.keypoints.map((pt) => pt.position), outputSize);\n  body.box = rescaledBoxes.box;\n  body.boxRaw = rescaledBoxes.boxRaw;\n  return body;\n}\n", "/**\n * MoveNet model implementation\n *\n * Based on: [**MoveNet**](https://blog.tensorflow.org/2021/05/next-generation-pose-detection-with-movenet-and-tensorflowjs.html)\n */\n\nimport { log, now } from '../util/util';\nimport * as box from '../util/box';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as coords from './movenetcoords';\nimport * as fix from './movenetfix';\nimport { loadModel } from '../tfjs/load';\nimport type { BodyKeypoint, BodyResult, BodyLandmark, BodyAnnotation, Box, Point } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { fakeOps } from '../tfjs/backend';\nimport { env } from '../util/env';\n\nlet model: GraphModel | null;\nlet inputSize = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\n// const boxExpandFact = 1.5; // increase to 150%\n\nconst cache: {\n  boxes: Array<Box>, // unused\n  bodies: Array<BodyResult>;\n  last: number,\n} = {\n  boxes: [],\n  bodies: [],\n  last: 0,\n};\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (env.initial) model = null;\n  if (!model) {\n    fakeOps(['size'], config);\n    model = await loadModel(config.body.modelPath);\n  } else if (config.debug) log('cached model:', model['modelUrl']);\n  inputSize = model.inputs[0].shape ? model.inputs[0].shape[2] : 0;\n  if (inputSize < 64) inputSize = 256;\n  return model;\n}\n\nasync function parseSinglePose(res, config, image) {\n  const kpt = res[0][0];\n  const keypoints: Array<BodyKeypoint> = [];\n  let score = 0;\n  for (let id = 0; id < kpt.length; id++) {\n    score = kpt[id][2];\n    if (score > config.body.minConfidence) {\n      const positionRaw: Point = [kpt[id][1], kpt[id][0]];\n      keypoints.push({\n        score: Math.round(100 * score) / 100,\n        part: coords.kpt[id] as BodyLandmark,\n        positionRaw,\n        position: [ // normalized to input image size\n          Math.round((image.shape[2] || 0) * positionRaw[0]),\n          Math.round((image.shape[1] || 0) * positionRaw[1]),\n        ],\n      });\n    }\n  }\n  score = keypoints.reduce((prev, curr) => (curr.score > prev ? curr.score : prev), 0);\n  const bodies: Array<BodyResult> = [];\n  const newBox = box.calc(keypoints.map((pt) => pt.position), [image.shape[2], image.shape[1]]);\n  const annotations: Record<string, Point[][]> = {};\n  for (const [name, indexes] of Object.entries(coords.connected)) {\n    const pt: Array<Point[]> = [];\n    for (let i = 0; i < indexes.length - 1; i++) {\n      const pt0 = keypoints.find((kp) => kp.part === indexes[i]);\n      const pt1 = keypoints.find((kp) => kp.part === indexes[i + 1]);\n      if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n    }\n    annotations[name] = pt;\n  }\n  const body: BodyResult = { id: 0, score, box: newBox.box, boxRaw: newBox.boxRaw, keypoints, annotations };\n  fix.bodyParts(body);\n  bodies.push(body);\n  return bodies;\n}\n\nasync function parseMultiPose(res, config, image) {\n  const bodies: Array<BodyResult> = [];\n  for (let id = 0; id < res[0].length; id++) {\n    const kpt = res[0][id];\n    const totalScore = Math.round(100 * kpt[51 + 4]) / 100;\n    if (totalScore > config.body.minConfidence) {\n      const keypoints: Array<BodyKeypoint> = [];\n      for (let i = 0; i < 17; i++) {\n        const score = kpt[3 * i + 2];\n        if (score > config.body.minConfidence) {\n          const positionRaw: Point = [kpt[3 * i + 1], kpt[3 * i + 0]];\n          keypoints.push({\n            part: coords.kpt[i] as BodyLandmark,\n            score: Math.round(100 * score) / 100,\n            positionRaw,\n            position: [Math.round((image.shape[2] || 0) * positionRaw[0]), Math.round((image.shape[1] || 0) * positionRaw[1])],\n          });\n        }\n      }\n      const newBox = box.calc(keypoints.map((pt) => pt.position), [image.shape[2], image.shape[1]]);\n      // movenet-multipose has built-in box details\n      // const boxRaw: Box = [kpt[51 + 1], kpt[51 + 0], kpt[51 + 3] - kpt[51 + 1], kpt[51 + 2] - kpt[51 + 0]];\n      // const box: Box = [Math.trunc(boxRaw[0] * (image.shape[2] || 0)), Math.trunc(boxRaw[1] * (image.shape[1] || 0)), Math.trunc(boxRaw[2] * (image.shape[2] || 0)), Math.trunc(boxRaw[3] * (image.shape[1] || 0))];\n      const annotations: Record<BodyAnnotation, Point[][]> = {} as Record<BodyAnnotation, Point[][]>;\n      for (const [name, indexes] of Object.entries(coords.connected)) {\n        const pt: Array<Point[]> = [];\n        for (let i = 0; i < indexes.length - 1; i++) {\n          const pt0 = keypoints.find((kp) => kp.part === indexes[i]);\n          const pt1 = keypoints.find((kp) => kp.part === indexes[i + 1]);\n          if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n        }\n        annotations[name] = pt;\n      }\n      const body: BodyResult = { id, score: totalScore, box: newBox.box, boxRaw: newBox.boxRaw, keypoints: [...keypoints], annotations };\n      fix.bodyParts(body);\n      bodies.push(body);\n    }\n  }\n  bodies.sort((a, b) => b.score - a.score);\n  if (bodies.length > config.body.maxDetected) bodies.length = config.body.maxDetected;\n  return bodies;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {\n  if (!model || !model?.inputs[0].shape) return []; // something is wrong with the model\n  if (!config.skipAllowed) cache.boxes.length = 0; // allowed to use cache or not\n  skipped++; // increment skip frames\n  const skipTime = (config.body.skipTime || 0) > (now() - cache.last);\n  const skipFrame = skipped < (config.body.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame) {\n    return cache.bodies; // return cached results without running anything\n  }\n  return new Promise(async (resolve) => {\n    const t: Record<string, Tensor> = {};\n    skipped = 0;\n    // run detection on squared input and cached boxes\n    /*\n    cache.bodies = []; // reset bodies result\n    if (cache.boxes.length >= (config.body.maxDetected || 0)) { // if we have enough cached boxes run detection using cache\n      for (let i = 0; i < cache.boxes.length; i++) { // run detection based on cached boxes\n        t.crop = tf.image.cropAndResize(input, [cache.boxes[i]], [0], [inputSize, inputSize], 'bilinear');\n        t.cast = tf.cast(t.crop, 'int32');\n        // t.input = prepareImage(input);\n        t.res = model?.execute(t.cast) as Tensor;\n        const res = await t.res.array();\n        const newBodies = (t.res.shape[2] === 17) ? await parseSinglePose(res, config, input, cache.boxes[i]) : await parseMultiPose(res, config, input, cache.boxes[i]);\n        cache.bodies = cache.bodies.concat(newBodies);\n        Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n      }\n    }\n    if (cache.bodies.length !== config.body.maxDetected) { // did not find enough bodies based on cached boxes so run detection on full frame\n      t.input = prepareImage(input);\n      t.res = model?.execute(t.input) as Tensor;\n      const res = await t.res.array();\n      cache.bodies = (t.res.shape[2] === 17) ? await parseSinglePose(res, config, input, [0, 0, 1, 1]) : await parseMultiPose(res, config, input, [0, 0, 1, 1]);\n      for (const body of cache.bodies) rescaleBody(body, [input.shape[2] || 1, input.shape[1] || 1]);\n      Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    }\n    cache.boxes.length = 0; // reset cache\n    for (let i = 0; i < cache.bodies.length; i++) {\n      if (cache.bodies[i].keypoints.length > (coords.kpt.length / 2)) { // only update cache if we detected at least half keypoints\n        const scaledBox = box.scale(cache.bodies[i].boxRaw, boxExpandFact);\n        const cropBox = box.crop(scaledBox);\n        cache.boxes.push(cropBox);\n      }\n    }\n    */\n\n    // run detection on squared input and no cached boxes\n    t.input = fix.padInput(input, inputSize);\n    t.res = model?.execute(t.input) as Tensor;\n    cache.last = now();\n    const res = await t.res.array();\n    cache.bodies = (t.res.shape[2] === 17)\n      ? await parseSinglePose(res, config, input)\n      : await parseMultiPose(res, config, input);\n    for (const body of cache.bodies) {\n      fix.rescaleBody(body, [input.shape[2] || 1, input.shape[1] || 1]);\n      fix.jitter(body.keypoints);\n    }\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n\n    resolve(cache.bodies);\n  });\n}\n", "/**\n * NanoDet object detection model implementation\n *\n * Based on: [**MB3-CenterNet**](https://github.com/610265158/mobilenetv3_centernet)\n */\n\nimport { log, now } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport { constants } from '../tfjs/constants';\nimport { labels } from './labels';\nimport type { ObjectResult, ObjectType, Box } from '../result';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\n\nlet model: GraphModel;\nlet last: Array<ObjectResult> = [];\nlet lastTime = 0;\nlet skipped = Number.MAX_SAFE_INTEGER;\nlet inputSize = 0;\n\nconst scaleBox = 2.5; // increase box size\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (!model || env.initial) {\n    model = await loadModel(config.object.modelPath);\n    const inputs = Object.values(model.modelSignature['inputs']);\n    inputSize = Array.isArray(inputs) ? parseInt(inputs[0].tensorShape.dim[2].size) : 0;\n  } else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nasync function process(res: Tensor[], outputShape: [number, number], config: Config) {\n  let id = 0;\n  let results: Array<ObjectResult> = [];\n  for (const strideSize of [1, 2, 4]) { // try each stride size as it detects large/medium/small objects\n    // find scores, boxes, classes\n    tf.tidy(async () => { // wrap in tidy to automatically deallocate temp tensors\n      const baseSize = strideSize * 13; // 13x13=169, 26x26=676, 52x52=2704\n      // find boxes and scores output depending on stride\n      const scoresT = tf.squeeze(res.find((a: Tensor) => (a.shape[1] === (baseSize ** 2) && (a.shape[2] || 0) === labels.length)));\n      const featuresT = tf.squeeze(res.find((a: Tensor) => (a.shape[1] === (baseSize ** 2) && (a.shape[2] || 0) < labels.length)));\n      const boxesMax = featuresT.reshape([-1, 4, featuresT.shape[1] / 4]); // reshape [output] to [4, output / 4] where number is number of different features inside each stride\n      const boxIdx = await boxesMax.argMax(2).array(); // what we need is indexes of features with highest scores, not values itself\n      const scores = await scoresT.array(); // optionally use exponential scores or just as-is\n      for (let i = 0; i < scoresT.shape[0]; i++) { // total strides (x * y matrix)\n        for (let j = 0; j < scoresT.shape[1]; j++) { // one score for each class\n          const score = scores[i][j]; // get score for current position\n          if (score > (config.object.minConfidence || 0) && j !== 61) {\n            const cx = (0.5 + Math.trunc(i % baseSize)) / baseSize; // center.x normalized to range 0..1\n            const cy = (0.5 + Math.trunc(i / baseSize)) / baseSize; // center.y normalized to range 0..1\n            const boxOffset = boxIdx[i].map((a: number) => a * (baseSize / strideSize / inputSize)); // just grab indexes of features with highest scores\n            const [x, y] = [\n              cx - (scaleBox / strideSize * boxOffset[0]),\n              cy - (scaleBox / strideSize * boxOffset[1]),\n            ];\n            const [w, h] = [\n              cx + (scaleBox / strideSize * boxOffset[2]) - x,\n              cy + (scaleBox / strideSize * boxOffset[3]) - y,\n            ];\n            let boxRaw: Box = [x, y, w, h]; // results normalized to range 0..1\n            boxRaw = boxRaw.map((a) => Math.max(0, Math.min(a, 1))) as Box; // fix out-of-bounds coords\n            const box = [ // results normalized to input image pixels\n              boxRaw[0] * outputShape[0],\n              boxRaw[1] * outputShape[1],\n              boxRaw[2] * outputShape[0],\n              boxRaw[3] * outputShape[1],\n            ];\n            const result = {\n              id: id++,\n              // strideSize,\n              score: Math.round(100 * score) / 100,\n              class: j + 1,\n              label: labels[j].label as ObjectType,\n              // center: [Math.trunc(outputShape[0] * cx), Math.trunc(outputShape[1] * cy)],\n              // centerRaw: [cx, cy],\n              box: box.map((a) => Math.trunc(a)) as Box,\n              boxRaw,\n            };\n            results.push(result);\n          }\n        }\n      }\n    });\n  }\n  // deallocate tensors\n  res.forEach((t) => tf.dispose(t));\n\n  // normally nms is run on raw results, but since boxes need to be calculated this way we skip calulcation of\n  // unnecessary boxes and run nms only on good candidates (basically it just does IOU analysis as scores are already filtered)\n  const nmsBoxes = results.map((a) => [a.boxRaw[1], a.boxRaw[0], a.boxRaw[3], a.boxRaw[2]]); // switches coordinates from x,y to y,x as expected by tf.nms\n  const nmsScores = results.map((a) => a.score);\n  let nmsIdx: Array<number> = [];\n  if (nmsBoxes && nmsBoxes.length > 0) {\n    const nms = await tf.image.nonMaxSuppressionAsync(nmsBoxes, nmsScores, config.object.maxDetected, config.object.iouThreshold, config.object.minConfidence);\n    nmsIdx = await nms.data();\n    tf.dispose(nms);\n  }\n\n  // filter & sort results\n  results = results\n    .filter((_val, idx) => nmsIdx.includes(idx))\n    .sort((a, b) => (b.score - a.score));\n\n  return results;\n}\n\nexport async function predict(image: Tensor, config: Config): Promise<ObjectResult[]> {\n  const skipTime = (config.object.skipTime || 0) > (now() - lastTime);\n  const skipFrame = skipped < (config.object.skipFrames || 0);\n  if (config.skipAllowed && skipTime && skipFrame && (last.length > 0)) {\n    skipped++;\n    return last;\n  }\n  skipped = 0;\n  if (!env.kernels.includes('mod') || !env.kernels.includes('sparsetodense')) return last;\n  return new Promise(async (resolve) => {\n    const outputSize = [image.shape[2] || 0, image.shape[1] || 0];\n    const resize = tf.image.resizeBilinear(image, [inputSize, inputSize], false);\n    const norm = tf.div(resize, constants.tf255);\n    const transpose = norm.transpose([0, 3, 1, 2]);\n    tf.dispose(norm);\n    tf.dispose(resize);\n\n    let objectT;\n    if (config.object.enabled) objectT = model.execute(transpose);\n    lastTime = now();\n    tf.dispose(transpose);\n\n    const obj = await process(objectT as Tensor[], outputSize as [number, number], config);\n    last = obj;\n    resolve(obj);\n  });\n}\n", "/**\n * PoseNet body detection model implementation constants\n * See `posenet.ts` for entry point\n */\n\nimport type { Point, BodyResult, BodyAnnotation, BodyLandmark } from '../result';\n\nexport const partNames = [\n  'nose', 'leftEye', 'rightEye', 'leftEar', 'rightEar', 'leftShoulder',\n  'rightShoulder', 'leftElbow', 'rightElbow', 'leftWrist', 'rightWrist',\n  'leftHip', 'rightHip', 'leftKnee', 'rightKnee', 'leftAnkle', 'rightAnkle',\n];\n\nexport const count = partNames.length; // 17 keypoints\n\nexport const partIds = partNames.reduce((result, jointName, i) => {\n  result[jointName] = i;\n  return result;\n}, {});\n\nconst connectedPartNames = [\n  ['leftHip', 'leftShoulder'], ['leftElbow', 'leftShoulder'],\n  ['leftElbow', 'leftWrist'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['rightHip', 'rightShoulder'],\n  ['rightElbow', 'rightShoulder'], ['rightElbow', 'rightWrist'],\n  ['rightHip', 'rightKnee'], ['rightKnee', 'rightAnkle'],\n  ['leftShoulder', 'rightShoulder'], ['leftHip', 'rightHip'],\n];\nexport const connectedPartIndices = connectedPartNames.map(([jointNameA, jointNameB]) => ([partIds[jointNameA], partIds[jointNameB]]));\n\nexport const poseChain = [\n  ['nose', 'leftEye'], ['leftEye', 'leftEar'], ['nose', 'rightEye'],\n  ['rightEye', 'rightEar'], ['nose', 'leftShoulder'],\n  ['leftShoulder', 'leftElbow'], ['leftElbow', 'leftWrist'],\n  ['leftShoulder', 'leftHip'], ['leftHip', 'leftKnee'],\n  ['leftKnee', 'leftAnkle'], ['nose', 'rightShoulder'],\n  ['rightShoulder', 'rightElbow'], ['rightElbow', 'rightWrist'],\n  ['rightShoulder', 'rightHip'], ['rightHip', 'rightKnee'],\n  ['rightKnee', 'rightAnkle'],\n];\n\nexport function eitherPointDoesntMeetConfidence(a: number, b: number, minConfidence: number) {\n  return (a < minConfidence || b < minConfidence);\n}\n\nexport function getAdjacentKeyPoints(keypoints, minConfidence: number) {\n  return connectedPartIndices.reduce((result, [leftJoint, rightJoint]) => {\n    if (eitherPointDoesntMeetConfidence(keypoints[leftJoint].score, keypoints[rightJoint].score, minConfidence)) {\n      return result;\n    }\n    result.push([keypoints[leftJoint], keypoints[rightJoint]]);\n    return result;\n  }, []);\n}\n\nexport function getBoundingBox(keypoints): [number, number, number, number] {\n  const coord = keypoints.reduce(({ maxX, maxY, minX, minY }, { position: { x, y } }) => ({\n    maxX: Math.max(maxX, x),\n    maxY: Math.max(maxY, y),\n    minX: Math.min(minX, x),\n    minY: Math.min(minY, y),\n  }), {\n    maxX: Number.NEGATIVE_INFINITY,\n    maxY: Number.NEGATIVE_INFINITY,\n    minX: Number.POSITIVE_INFINITY,\n    minY: Number.POSITIVE_INFINITY,\n  });\n  return [coord.minX, coord.minY, coord.maxX - coord.minX, coord.maxY - coord.minY];\n}\n\nexport function scalePoses(poses, [height, width], [inputResolutionHeight, inputResolutionWidth]): Array<BodyResult> {\n  const scaleY = height / inputResolutionHeight;\n  const scaleX = width / inputResolutionWidth;\n  const scalePose = (pose, i): BodyResult => ({\n    id: i,\n    score: pose.score,\n    boxRaw: [pose.box[0] / inputResolutionWidth, pose.box[1] / inputResolutionHeight, pose.box[2] / inputResolutionWidth, pose.box[3] / inputResolutionHeight],\n    box: [Math.trunc(pose.box[0] * scaleX), Math.trunc(pose.box[1] * scaleY), Math.trunc(pose.box[2] * scaleX), Math.trunc(pose.box[3] * scaleY)],\n    keypoints: pose.keypoints.map(({ score, part, position }) => ({\n      score: score as number,\n      part: part as BodyLandmark,\n      position: [Math.trunc(position.x * scaleX), Math.trunc(position.y * scaleY)] as Point,\n      positionRaw: [position.x / inputResolutionHeight, position.y / inputResolutionHeight] as Point,\n    })),\n    annotations: {} as Record<BodyAnnotation, Point[][]>,\n  });\n  const scaledPoses = poses.map((pose, i) => scalePose(pose, i));\n  return scaledPoses;\n}\n\n// algorithm based on Coursera Lecture from Algorithms, Part 1: https://www.coursera.org/learn/algorithms-part1/lecture/ZjoSM/heapsort\nexport class MaxHeap {\n  priorityQueue: Array<unknown>; // don't touch\n  numberOfElements: number;\n  getElementValue: unknown; // function call\n\n  constructor(maxSize, getElementValue) {\n    this.priorityQueue = new Array(maxSize);\n    this.numberOfElements = -1;\n    this.getElementValue = getElementValue;\n  }\n\n  enqueue(x) {\n    this.priorityQueue[++this.numberOfElements] = x;\n    this.swim(this.numberOfElements);\n  }\n\n  dequeue() {\n    const max = this.priorityQueue[0];\n    this.exchange(0, this.numberOfElements--);\n    this.sink(0);\n    this.priorityQueue[this.numberOfElements + 1] = null;\n    return max;\n  }\n\n  empty() { return this.numberOfElements === -1; }\n\n  size() { return this.numberOfElements + 1; }\n\n  all() { return this.priorityQueue.slice(0, this.numberOfElements + 1); }\n\n  max() { return this.priorityQueue[0]; }\n\n  swim(k) {\n    while (k > 0 && this.less(Math.floor(k / 2), k)) {\n      this.exchange(k, Math.floor(k / 2));\n      k = Math.floor(k / 2);\n    }\n  }\n\n  sink(k) {\n    while (2 * k <= this.numberOfElements) {\n      let j = 2 * k;\n      if (j < this.numberOfElements && this.less(j, j + 1)) j++;\n      if (!this.less(k, j)) break;\n      this.exchange(k, j);\n      k = j;\n    }\n  }\n\n  getValueAt(i) {\n    // @ts-ignore getter is of unknown type\n    return this.getElementValue(this.priorityQueue[i]);\n  }\n\n  less(i, j) {\n    return this.getValueAt(i) < this.getValueAt(j);\n  }\n\n  exchange(i, j) {\n    const t = this.priorityQueue[i];\n    this.priorityQueue[i] = this.priorityQueue[j];\n    this.priorityQueue[j] = t;\n  }\n}\n\nexport function getOffsetPoint(y, x, keypoint, offsets) {\n  return {\n    y: offsets.get(y, x, keypoint),\n    x: offsets.get(y, x, keypoint + count),\n  };\n}\n\nexport function getImageCoords(part, outputStride, offsets) {\n  const { heatmapY, heatmapX, id: keypoint } = part;\n  const { y, x } = getOffsetPoint(heatmapY, heatmapX, keypoint, offsets);\n  return {\n    x: part.heatmapX * outputStride + x,\n    y: part.heatmapY * outputStride + y,\n  };\n}\n\nexport function fillArray(element, size) {\n  const result = new Array(size);\n  for (let i = 0; i < size; i++) {\n    result[i] = element;\n  }\n  return result;\n}\n\nexport function clamp(a, min, max) {\n  if (a < min) return min;\n  if (a > max) return max;\n  return a;\n}\n\nexport function squaredDistance(y1, x1, y2, x2) {\n  const dy = y2 - y1;\n  const dx = x2 - x1;\n  return dy * dy + dx * dx;\n}\n\nexport function addVectors(a, b) {\n  return { x: a.x + b.x, y: a.y + b.y };\n}\n\nexport function clampVector(a, min, max) {\n  return { y: clamp(a.y, min, max), x: clamp(a.x, min, max) };\n}\n", "/**\n * PoseNet body detection model implementation\n *\n * Based on: [**PoseNet**](https://medium.com/tensorflow/real-time-human-pose-estimation-in-the-browser-with-tensorflow-js-7dd0bc881cd5)\n */\n\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport type { BodyResult, BodyLandmark, Box } from '../result';\nimport type { Tensor, GraphModel } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\nimport * as utils from './posenetutils';\n\nlet model: GraphModel;\nconst poseNetOutputs = ['MobilenetV1/offset_2/BiasAdd'/* offsets */, 'MobilenetV1/heatmap_2/BiasAdd'/* heatmapScores */, 'MobilenetV1/displacement_fwd_2/BiasAdd'/* displacementFwd */, 'MobilenetV1/displacement_bwd_2/BiasAdd'/* displacementBwd */];\nconst localMaximumRadius = 1;\nconst outputStride = 16;\nconst squaredNmsRadius = 50 ** 2;\n\nfunction traverse(edgeId, sourceKeypoint, targetId, scores, offsets, displacements, offsetRefineStep = 2) {\n  const getDisplacement = (point) => ({\n    y: displacements.get(point.y, point.x, edgeId),\n    x: displacements.get(point.y, point.x, (displacements.shape[2] / 2) + edgeId),\n  });\n  const getStridedIndexNearPoint = (point, height, width) => ({\n    y: utils.clamp(Math.round(point.y / outputStride), 0, height - 1),\n    x: utils.clamp(Math.round(point.x / outputStride), 0, width - 1),\n  });\n\n  const [height, width] = scores.shape;\n  // Nearest neighbor interpolation for the source->target displacements.\n  const sourceKeypointIndices = getStridedIndexNearPoint(sourceKeypoint.position, height, width);\n  const displacement = getDisplacement(sourceKeypointIndices);\n  const displacedPoint = utils.addVectors(sourceKeypoint.position, displacement);\n  let targetKeypoint = displacedPoint;\n  for (let i = 0; i < offsetRefineStep; i++) {\n    const targetKeypointIndices = getStridedIndexNearPoint(targetKeypoint, height, width);\n    const offsetPoint = utils.getOffsetPoint(targetKeypointIndices.y, targetKeypointIndices.x, targetId, offsets);\n    targetKeypoint = utils.addVectors(\n      { x: targetKeypointIndices.x * outputStride, y: targetKeypointIndices.y * outputStride },\n      { x: offsetPoint.x, y: offsetPoint.y },\n    );\n  }\n  const targetKeyPointIndices = getStridedIndexNearPoint(targetKeypoint, height, width);\n  const score = scores.get(targetKeyPointIndices.y, targetKeyPointIndices.x, targetId);\n  return { position: targetKeypoint, part: utils.partNames[targetId], score };\n}\n\nexport function decodePose(root, scores, offsets, displacementsFwd, displacementsBwd) {\n  const tuples = utils.poseChain.map(([parentJoinName, childJoinName]) => ([utils.partIds[parentJoinName], utils.partIds[childJoinName]]));\n  const edgesFwd = tuples.map(([, childJointId]) => childJointId);\n  const edgesBwd = tuples.map(([parentJointId]) => parentJointId);\n  const numParts = scores.shape[2]; // [21,21,17]\n  const numEdges = edgesFwd.length;\n  const keypoints = new Array(numParts);\n  // Start a new detection instance at the position of the root.\n  const rootPoint = utils.getImageCoords(root.part, outputStride, offsets);\n  keypoints[root.part.id] = {\n    score: root.score,\n    part: utils.partNames[root.part.id] as BodyLandmark,\n    position: rootPoint,\n  };\n  // Decode the part positions upwards in the tree, following the backward displacements.\n  for (let edge = numEdges - 1; edge >= 0; --edge) {\n    const sourceId = edgesFwd[edge];\n    const targetId = edgesBwd[edge];\n    if (keypoints[sourceId] && !keypoints[targetId]) {\n      keypoints[targetId] = traverse(edge, keypoints[sourceId], targetId, scores, offsets, displacementsBwd);\n    }\n  }\n  // Decode the part positions downwards in the tree, following the forward displacements.\n  for (let edge = 0; edge < numEdges; ++edge) {\n    const sourceId = edgesBwd[edge];\n    const targetId = edgesFwd[edge];\n    if (keypoints[sourceId] && !keypoints[targetId]) {\n      keypoints[targetId] = traverse(edge, keypoints[sourceId], targetId, scores, offsets, displacementsFwd);\n    }\n  }\n  return keypoints;\n}\n\nfunction scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, scores) {\n  const [height, width] = scores.shape;\n  let localMaximum = true;\n  const yStart = Math.max(heatmapY - localMaximumRadius, 0);\n  const yEnd = Math.min(heatmapY + localMaximumRadius + 1, height);\n  for (let yCurrent = yStart; yCurrent < yEnd; ++yCurrent) {\n    const xStart = Math.max(heatmapX - localMaximumRadius, 0);\n    const xEnd = Math.min(heatmapX + localMaximumRadius + 1, width);\n    for (let xCurrent = xStart; xCurrent < xEnd; ++xCurrent) {\n      if (scores.get(yCurrent, xCurrent, keypointId) > score) {\n        localMaximum = false;\n        break;\n      }\n    }\n    if (!localMaximum) break;\n  }\n  return localMaximum;\n}\n\nexport function buildPartWithScoreQueue(minConfidence, scores) {\n  const [height, width, numKeypoints] = scores.shape;\n  const queue = new utils.MaxHeap(height * width * numKeypoints, ({ score }) => score);\n  for (let heatmapY = 0; heatmapY < height; ++heatmapY) {\n    for (let heatmapX = 0; heatmapX < width; ++heatmapX) {\n      for (let keypointId = 0; keypointId < numKeypoints; ++keypointId) {\n        const score = scores.get(heatmapY, heatmapX, keypointId);\n        // Only consider parts with score greater or equal to threshold as root candidates.\n        if (score < minConfidence) continue;\n        // Only consider keypoints whose score is maximum in a local window.\n        if (scoreIsMaximumInLocalWindow(keypointId, score, heatmapY, heatmapX, scores)) queue.enqueue({ score, part: { heatmapY, heatmapX, id: keypointId } });\n      }\n    }\n  }\n  return queue;\n}\n\nfunction withinRadius(poses, { x, y }, keypointId) {\n  return poses.some(({ keypoints }) => {\n    const correspondingKeypoint = keypoints[keypointId]?.position;\n    if (!correspondingKeypoint) return false;\n    return utils.squaredDistance(y, x, correspondingKeypoint.y, correspondingKeypoint.x) <= squaredNmsRadius;\n  });\n}\n\nfunction getInstanceScore(existingPoses, keypoints) {\n  const notOverlappedKeypointScores = keypoints.reduce((result, { position, score }, keypointId) => {\n    if (!withinRadius(existingPoses, position, keypointId)) result += score;\n    return result;\n  }, 0.0);\n  return notOverlappedKeypointScores / keypoints.length;\n}\n\nexport function decode(offsets, scores, displacementsFwd, displacementsBwd, maxDetected, minConfidence) {\n  const poses: Array<{ keypoints, box: Box, score: number }> = [];\n  const queue = buildPartWithScoreQueue(minConfidence, scores);\n  // Generate at most maxDetected object instances per image in decreasing root part score order.\n  while (poses.length < maxDetected && !queue.empty()) {\n    // The top element in the queue is the next root candidate.\n    const root = queue.dequeue();\n    // Part-based non-maximum suppression: We reject a root candidate if it is within a disk of `nmsRadius` pixels from the corresponding part of a previously detected instance.\n    // @ts-ignore this one is tree walk\n    const rootImageCoords = utils.getImageCoords(root.part, outputStride, offsets);\n    // @ts-ignore this one is tree walk\n    if (withinRadius(poses, rootImageCoords, root.part.id)) continue;\n    // Else start a new detection instance at the position of the root.\n    let keypoints = decodePose(root, scores, offsets, displacementsFwd, displacementsBwd);\n    keypoints = keypoints.filter((a) => a.score > minConfidence);\n    const score = getInstanceScore(poses, keypoints);\n    const box = utils.getBoundingBox(keypoints);\n    if (score > minConfidence) poses.push({ keypoints, box, score: Math.round(100 * score) / 100 });\n  }\n  return poses;\n}\n\nexport async function predict(input: Tensor, config: Config): Promise<BodyResult[]> {\n  /** posenet is mostly obsolete\n   * caching is not implemented\n   */\n  const res = tf.tidy(() => {\n    if (!model.inputs[0].shape) return [];\n    const resized = tf.image.resizeBilinear(input, [model.inputs[0].shape[2], model.inputs[0].shape[1]]);\n    const normalized = tf.sub(tf.div(tf.cast(resized, 'float32'), 127.5), 1.0);\n    const results: Array<Tensor> = model.execute(normalized, poseNetOutputs) as Array<Tensor>;\n    const results3d = results.map((y) => tf.squeeze(y, [0]));\n    results3d[1] = tf.sigmoid(results3d[1]); // apply sigmoid on scores\n    return results3d;\n  });\n\n  const buffers = await Promise.all(res.map((tensor: Tensor) => tensor.buffer()));\n  for (const t of res) tf.dispose(t);\n\n  const decoded = await decode(buffers[0], buffers[1], buffers[2], buffers[3], config.body.maxDetected, config.body.minConfidence);\n  if (!model.inputs[0].shape) return [];\n  const scaled = utils.scalePoses(decoded, [input.shape[1], input.shape[2]], [model.inputs[0].shape[2], model.inputs[0].shape[1]]) as BodyResult[];\n  return scaled;\n}\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (!model || env.initial) model = await loadModel(config.body.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n", "/**\n * Image segmentation for body detection model\n *\n * Based on:\n * - [**MediaPipe Meet**](https://drive.google.com/file/d/1lnP1bRi9CSqQQXUHa13159vLELYDgDu0/preview)\n * - [**MediaPipe Selfie**](https://drive.google.com/file/d/1dCfozqknMa068vVsO2j_1FgZkW_e3VWv/preview)\n */\n\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { loadModel } from '../tfjs/load';\nimport * as image from '../image/image';\nimport { constants } from '../tfjs/constants';\nimport type { GraphModel, Tensor } from '../tfjs/types';\nimport type { Config } from '../config';\nimport { env } from '../util/env';\nimport type { Input, AnyCanvas } from '../exports';\n\nlet model: GraphModel;\nlet busy = false;\n\nexport async function load(config: Config): Promise<GraphModel> {\n  if (!model || env.initial) model = await loadModel(config.segmentation.modelPath);\n  else if (config.debug) log('cached model:', model['modelUrl']);\n  return model;\n}\n\nexport async function process(input: Input, background: Input | undefined, config: Config)\n: Promise<{ data: Array<number> | Tensor, canvas: AnyCanvas | null, alpha: AnyCanvas | null }> {\n  if (busy) return { data: [], canvas: null, alpha: null };\n  busy = true;\n  if (!model) await load(config);\n  const inputImage = await image.process(input, config);\n  const width = inputImage.tensor?.shape[2] || 0;\n  const height = inputImage.tensor?.shape[1] || 0;\n  if (!inputImage.tensor) return { data: [], canvas: null, alpha: null };\n  const t: Record<string, Tensor> = {};\n\n  t.resize = tf.image.resizeBilinear(inputImage.tensor, [model.inputs[0].shape ? model.inputs[0].shape[1] : 0, model.inputs[0].shape ? model.inputs[0].shape[2] : 0], false);\n  tf.dispose(inputImage.tensor);\n  t.norm = tf.div(t.resize, constants.tf255);\n  t.res = model.execute(t.norm) as Tensor;\n\n  t.squeeze = tf.squeeze(t.res, 0); // meet.shape:[1,256,256,1], selfie.shape:[1,144,256,2]\n  if (t.squeeze.shape[2] === 2) {\n    t.softmax = tf.softmax(t.squeeze); // model meet has two channels for fg and bg\n    [t.bg, t.fg] = tf.unstack(t.softmax, 2);\n    t.expand = tf.expandDims(t.fg, 2);\n    t.pad = tf.expandDims(t.expand, 0);\n    t.crop = tf.image.cropAndResize(t.pad, [[0, 0, 0.5, 0.5]], [0], [width, height]);\n    // running sofmax before unstack creates 2x2 matrix so we only take upper-left quadrant\n    // otherwise run softmax after unstack and use standard resize\n    // resizeOutput = tf.image.resizeBilinear(expand, [input.tensor?.shape[1], input.tensor?.shape[2]]);\n    t.data = tf.squeeze(t.crop, 0);\n  } else {\n    t.data = tf.image.resizeBilinear(t.squeeze, [height, width]); // model selfie has a single channel that we can use directly\n  }\n  const data = Array.from(await t.data.data()) as number[];\n\n  if (env.node && !env.Canvas && (typeof ImageData === 'undefined')) {\n    if (config.debug) log('canvas support missing');\n    Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n    return { data, canvas: null, alpha: null }; // running in nodejs so return alpha array as-is\n  }\n\n  const alphaCanvas = image.canvas(width, height);\n  // @ts-ignore browser is not defined in tfjs-node\n  if (tf.browser) await tf.browser.toPixels(t.data, alphaCanvas);\n  const alphaCtx = alphaCanvas.getContext('2d') as CanvasRenderingContext2D;\n  if (config.segmentation.blur && config.segmentation.blur > 0) alphaCtx.filter = `blur(${config.segmentation.blur}px)`; // use css filter for bluring, can be done with gaussian blur manually instead\n  const alphaData = alphaCtx.getImageData(0, 0, width, height);\n\n  const compositeCanvas = image.canvas(width, height);\n  const compositeCtx = compositeCanvas.getContext('2d') as CanvasRenderingContext2D;\n  if (inputImage.canvas) compositeCtx.drawImage(inputImage.canvas, 0, 0);\n  compositeCtx.globalCompositeOperation = 'darken'; // https://developer.mozilla.org/en-US/docs/Web/API/CanvasRenderingContext2D/globalCompositeOperation // best options are: darken, color-burn, multiply\n  if (config.segmentation.blur && config.segmentation.blur > 0) compositeCtx.filter = `blur(${config.segmentation.blur}px)`; // use css filter for bluring, can be done with gaussian blur manually instead\n  compositeCtx.drawImage(alphaCanvas, 0, 0);\n  compositeCtx.globalCompositeOperation = 'source-over'; // reset composite operation\n  compositeCtx.filter = 'none'; // reset css filter\n  const compositeData = compositeCtx.getImageData(0, 0, width, height);\n  for (let i = 0; i < width * height; i++) compositeData.data[4 * i + 3] = alphaData.data[4 * i + 0]; // copy original alpha value to new composite canvas\n  compositeCtx.putImageData(compositeData, 0, 0);\n\n  let mergedCanvas: AnyCanvas | null = null;\n  if (background && compositeCanvas) { // draw background with segmentation as overlay if background is present\n    mergedCanvas = image.canvas(width, height);\n    const bgImage = await image.process(background, config);\n    tf.dispose(bgImage.tensor);\n    const ctxMerge = mergedCanvas.getContext('2d') as CanvasRenderingContext2D;\n    ctxMerge.drawImage(bgImage.canvas as HTMLCanvasElement, 0, 0, mergedCanvas.width, mergedCanvas.height);\n    ctxMerge.drawImage(compositeCanvas, 0, 0);\n  }\n\n  Object.keys(t).forEach((tensor) => tf.dispose(t[tensor]));\n  busy = false;\n  // return { data, canvas: mergedCanvas || compositeCanvas, alpha: alphaCanvas };\n  return { data, canvas: compositeCanvas, alpha: alphaCanvas };\n}\n", "/** TFJS custom backend registration */\n\nimport type { Human } from '../human';\nimport { log } from '../util/util';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as image from '../image/image';\nimport * as models from '../models';\nimport type { AnyCanvas } from '../exports';\n// import { env } from '../env';\n\nexport const config = {\n  name: 'humangl',\n  priority: 999,\n  canvas: <null | AnyCanvas>null,\n  gl: <null | WebGL2RenderingContext>null,\n  extensions: <string[]> [],\n  webGLattr: { // https://www.khronos.org/registry/webgl/specs/latest/1.0/#5.2\n    alpha: false,\n    antialias: false,\n    premultipliedAlpha: false,\n    preserveDrawingBuffer: false,\n    depth: false,\n    stencil: false,\n    failIfMajorPerformanceCaveat: false,\n    desynchronized: true,\n  },\n};\n\nfunction extensions(): void {\n  /*\n  https://www.khronos.org/registry/webgl/extensions/\n  https://webglreport.com/?v=2\n  */\n  const gl = config.gl;\n  if (!gl) return;\n  config.extensions = gl.getSupportedExtensions() as string[];\n  // gl.getExtension('KHR_parallel_shader_compile');\n}\n\n/**\n * Registers custom WebGL2 backend to be used by Human library\n *\n * @returns void\n */\nexport async function register(instance: Human): Promise<void> {\n  // force backend reload if gl context is not valid\n  if (instance.config.backend !== 'humangl') return;\n  if ((config.name in tf.engine().registry) && (!config.gl || !config.gl.getParameter(config.gl.VERSION))) {\n    log('error: humangl backend invalid context');\n    models.reset(instance);\n    /*\n    log('resetting humangl backend');\n    await tf.removeBackend(config.name);\n    await register(instance); // re-register\n    */\n  }\n  if (!tf.findBackend(config.name)) {\n    try {\n      config.canvas = await image.canvas(100, 100);\n    } catch (err) {\n      log('error: cannot create canvas:', err);\n      return;\n    }\n    try {\n      config.gl = config.canvas?.getContext('webgl2', config.webGLattr) as WebGL2RenderingContext;\n      const glv2 = config.gl.getParameter(config.gl.VERSION).includes('2.0');\n      if (!glv2) {\n        log('override: using fallback webgl backend as webgl 2.0 is not detected');\n        instance.config.backend = 'webgl';\n        return;\n      }\n      if (config.canvas) {\n        config.canvas.addEventListener('webglcontextlost', async (e) => {\n          log('error: humangl:', e.type);\n          log('possible browser memory leak using webgl or conflict with multiple backend registrations');\n          instance.emit('error');\n          throw new Error('backend error: webgl context lost');\n          // log('resetting humangl backend');\n          // env.initial = true;\n          // models.reset(instance);\n          // await tf.removeBackend(config.name);\n          // await register(instance); // re-register\n        });\n        config.canvas.addEventListener('webglcontextrestored', (e) => {\n          log('error: humangl context restored:', e);\n        });\n        config.canvas.addEventListener('webglcontextcreationerror', (e) => {\n          log('error: humangl context create:', e);\n        });\n      }\n    } catch (err) {\n      log('error: cannot get WebGL context:', err);\n      return;\n    }\n    try {\n      tf.setWebGLContext(2, config.gl);\n    } catch (err) {\n      log('error: cannot set WebGL context:', err);\n      return;\n    }\n    try {\n      const ctx = new tf.GPGPUContext(config.gl);\n      tf.registerBackend(config.name, () => new tf.MathBackendWebGL(ctx), config.priority);\n    } catch (err) {\n      log('error: cannot register WebGL backend:', err);\n      return;\n    }\n    try {\n      const kernels = tf.getKernelsForBackend('webgl');\n      kernels.forEach((kernelConfig) => {\n        const newKernelConfig = { ...kernelConfig, backendName: config.name };\n        tf.registerKernel(newKernelConfig);\n      });\n    } catch (err) {\n      log('error: cannot update WebGL backend registration:', err);\n      return;\n    }\n    const current = tf.backend().getGPGPUContext ? tf.backend().getGPGPUContext().gl : null;\n    if (current) {\n      log(`humangl webgl version:${current.getParameter(current.VERSION)} renderer:${current.getParameter(current.RENDERER)}`);\n    } else {\n      log('error: no current gl context:', current, config.gl);\n      return;\n    }\n    try {\n      if (tf.env().flagRegistry['WEBGL_VERSION']) tf.env().set('WEBGL_VERSION', 2);\n    } catch (err) {\n      log('error: cannot set WebGL backend flags:', err);\n      return;\n    }\n    extensions();\n    log('backend registered:', config.name);\n  }\n}\n", "/** TFJS backend initialization and customization */\n\nimport type { Human } from '../human';\nimport { log, now } from '../util/util';\nimport { env } from '../util/env';\nimport * as humangl from './humangl';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as constants from './constants';\n\nfunction registerCustomOps() {\n  if (!env.kernels.includes('mod')) {\n    const kernelMod = {\n      kernelName: 'Mod',\n      backendName: tf.getBackend(),\n      kernelFunc: (op) => tf.tidy(() => tf.sub(op.inputs.a, tf.mul(tf.div(op.inputs.a, op.inputs.b), op.inputs.b))),\n    };\n    tf.registerKernel(kernelMod);\n    env.kernels.push('mod');\n  }\n  if (!env.kernels.includes('floormod')) {\n    const kernelMod = {\n      kernelName: 'FloorMod',\n      backendName: tf.getBackend(),\n      kernelFunc: (op) => tf.tidy(() => tf.floorDiv(op.inputs.a / op.inputs.b) * op.inputs.b + tf.mod(op.inputs.a, op.inputs.b)),\n    };\n    tf.registerKernel(kernelMod);\n    env.kernels.push('floormod');\n  }\n}\n\nexport async function check(instance: Human, force = false) {\n  instance.state = 'backend';\n  if (force || env.initial || (instance.config.backend && (instance.config.backend.length > 0) && (tf.getBackend() !== instance.config.backend))) {\n    const timeStamp = now();\n\n    if (instance.config.backend && instance.config.backend.length > 0) {\n      // detect web worker\n      // @ts-ignore ignore missing type for WorkerGlobalScope as that is the point\n      if (typeof window === 'undefined' && typeof WorkerGlobalScope !== 'undefined' && instance.config.debug) {\n        if (instance.config.debug) log('running inside web worker');\n      }\n\n      // force browser vs node backend\n      if (env.browser && instance.config.backend === 'tensorflow') {\n        if (instance.config.debug) log('override: backend set to tensorflow while running in browser');\n        instance.config.backend = 'humangl';\n      }\n      if (env.node && (instance.config.backend === 'webgl' || instance.config.backend === 'humangl')) {\n        if (instance.config.debug) log(`override: backend set to ${instance.config.backend} while running in nodejs`);\n        instance.config.backend = 'tensorflow';\n      }\n\n      // handle webgpu\n      if (env.browser && instance.config.backend === 'webgpu') {\n        if (typeof navigator === 'undefined' || typeof navigator['gpu'] === 'undefined') {\n          log('override: backend set to webgpu but browser does not support webgpu');\n          instance.config.backend = 'humangl';\n        } else {\n          const adapter = await navigator['gpu'].requestAdapter();\n          if (instance.config.debug) log('enumerated webgpu adapter:', adapter);\n          if (!adapter) {\n            log('override: backend set to webgpu but browser reports no available gpu');\n            instance.config.backend = 'humangl';\n          } else {\n            // @ts-ignore requestAdapterInfo is not in tslib\n            // eslint-disable-next-line no-undef\n            const adapterInfo = 'requestAdapterInfo' in adapter ? await (adapter as GPUAdapter).requestAdapterInfo() : undefined;\n            // if (adapter.features) adapter.features.forEach((feature) => log('webgpu features:', feature));\n            log('webgpu adapter info:', adapterInfo);\n          }\n        }\n      }\n\n      // check available backends\n      if (instance.config.backend === 'humangl') await humangl.register(instance);\n      const available = Object.keys(tf.engine().registryFactory);\n      if (instance.config.debug) log('available backends:', available);\n\n      if (!available.includes(instance.config.backend)) {\n        log(`error: backend ${instance.config.backend} not found in registry`);\n        instance.config.backend = env.node ? 'tensorflow' : 'webgl';\n        if (instance.config.debug) log(`override: setting backend ${instance.config.backend}`);\n      }\n\n      if (instance.config.debug) log('setting backend:', instance.config.backend);\n\n      // customize wasm\n      if (instance.config.backend === 'wasm') {\n        if (tf.env().flagRegistry['CANVAS2D_WILL_READ_FREQUENTLY']) tf.env().set('CANVAS2D_WILL_READ_FREQUENTLY', true);\n        if (instance.config.debug) log('wasm path:', instance.config.wasmPath);\n        if (typeof tf?.setWasmPaths !== 'undefined') await tf.setWasmPaths(instance.config.wasmPath, instance.config.wasmPlatformFetch);\n        else throw new Error('backend error: attempting to use wasm backend but wasm path is not set');\n        const simd = await tf.env().getAsync('WASM_HAS_SIMD_SUPPORT');\n        const mt = await tf.env().getAsync('WASM_HAS_MULTITHREAD_SUPPORT');\n        if (instance.config.debug) log(`wasm execution: ${simd ? 'SIMD' : 'no SIMD'} ${mt ? 'multithreaded' : 'singlethreaded'}`);\n        if (instance.config.debug && !simd) log('warning: wasm simd support is not enabled');\n      }\n\n      try {\n        await tf.setBackend(instance.config.backend);\n        await tf.ready();\n        constants.init();\n      } catch (err) {\n        log('error: cannot set backend:', instance.config.backend, err);\n        return false;\n      }\n    }\n\n    // customize humangl\n    if (tf.getBackend() === 'humangl') {\n      if (tf.env().flagRegistry['CHECK_COMPUTATION_FOR_ERRORS']) tf.env().set('CHECK_COMPUTATION_FOR_ERRORS', false);\n      if (tf.env().flagRegistry['WEBGL_CPU_FORWARD']) tf.env().set('WEBGL_CPU_FORWARD', true);\n      if (tf.env().flagRegistry['WEBGL_USE_SHAPES_UNIFORMS']) tf.env().set('WEBGL_USE_SHAPES_UNIFORMS', true);\n      if (tf.env().flagRegistry['CPU_HANDOFF_SIZE_THRESHOLD']) tf.env().set('CPU_HANDOFF_SIZE_THRESHOLD', 256);\n      if (tf.env().flagRegistry['WEBGL_EXP_CONV']) tf.env().set('WEBGL_EXP_CONV', true); // <https://github.com/tensorflow/tfjs/issues/6678>\n      if (tf.env().flagRegistry['USE_SETTIMEOUTWPM']) tf.env().set('USE_SETTIMEOUTWPM', true); // <https://github.com/tensorflow/tfjs/issues/6687>\n      // if (tf.env().flagRegistry['WEBGL_PACK_DEPTHWISECONV'])  tf.env().set('WEBGL_PACK_DEPTHWISECONV', false);\n      // if (if (tf.env().flagRegistry['WEBGL_FORCE_F16_TEXTURES']) && !instance.config.object.enabled) tf.env().set('WEBGL_FORCE_F16_TEXTURES', true); // safe to use 16bit precision\n      if (typeof instance.config['deallocate'] !== 'undefined' && instance.config['deallocate']) { // hidden param\n        log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', true);\n        tf.env().set('WEBGL_DELETE_TEXTURE_THRESHOLD', 0);\n      }\n      if (tf.backend().getGPGPUContext) {\n        const gl = await tf.backend().getGPGPUContext().gl;\n        if (instance.config.debug) log(`gl version:${gl.getParameter(gl.VERSION)} renderer:${gl.getParameter(gl.RENDERER)}`);\n      }\n    }\n\n    // customize webgpu\n    if (tf.getBackend() === 'webgpu') {\n      // if (tf.env().flagRegistry['WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD']) tf.env().set('WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD', 512);\n      // if (tf.env().flagRegistry['WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE']) tf.env().set('WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE', 0);\n      // if (tf.env().flagRegistry['WEBGPU_CPU_FORWARD']) tf.env().set('WEBGPU_CPU_FORWARD', true);\n    }\n\n    // wait for ready\n    tf.enableProdMode();\n    await tf.ready();\n\n    instance.performance.initBackend = Math.trunc(now() - timeStamp);\n    instance.config.backend = tf.getBackend();\n\n    await env.updateBackend(); // update env on backend init\n    registerCustomOps();\n    // await env.updateBackend(); // update env on backend init\n  }\n  return true;\n}\n\n// register fake missing tfjs ops\nexport function fakeOps(kernelNames: Array<string>, config) {\n  // if (config.debug) log('registerKernel:', kernelNames);\n  for (const kernelName of kernelNames) {\n    const kernelConfig = {\n      kernelName,\n      backendName: config.backend,\n      kernelFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },\n      // setupFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },\n      // disposeFunc: () => { if (config.debug) log('kernelFunc', kernelName, config.backend); },\n    };\n    tf.registerKernel(kernelConfig);\n  }\n  env.kernels = tf.getKernelsForBackend(tf.getBackend()).map((kernel) => kernel.kernelName.toLowerCase()); // re-scan registered ops\n}\n", "/**\n * Module that implements helper draw functions, exposed as human.draw\n */\n\nimport { mergeDeep, now } from '../util/util';\nimport { env } from '../util/env';\nimport { getCanvasContext, rect } from './primitives';\nimport { options } from './options';\nimport { face } from './face';\nimport { body } from './body';\nimport { hand } from './hand';\nimport { object } from './object';\nimport { gesture } from './gesture';\nimport type { Result, PersonResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\nlet drawTime = 0;\n\nexport { options } from './options';\nexport { face } from './face';\nexport { body } from './body';\nexport { hand } from './hand';\nexport { object } from './object';\nexport { gesture } from './gesture';\n\n/** draw combined person results instead of individual detection result objects */\nexport async function person(inCanvas: AnyCanvas, result: Array<PersonResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = localOptions.font;\n\n  for (let i = 0; i < result.length; i++) {\n    if (localOptions.drawBoxes) {\n      ctx.strokeStyle = localOptions.color;\n      ctx.fillStyle = localOptions.color;\n      rect(ctx, result[i].box[0], result[i].box[1], result[i].box[2], result[i].box[3], localOptions);\n      if (localOptions.drawLabels) {\n        const label = `person #${i}`;\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(label, result[i].box[0] + 3, 1 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(label, result[i].box[0] + 2, 0 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n\n/** draw processed canvas */\nexport async function canvas(input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas) {\n  if (!input || !output) return;\n  const ctx = getCanvasContext(output);\n  if (!ctx) return;\n  ctx.drawImage(input, 0, 0);\n}\n\n/** meta-function that performs draw for: canvas, face, body, hand */\nexport async function all(inCanvas: AnyCanvas, result: Result, drawOptions?: Partial<DrawOptions>) {\n  if (!result || !result.performance || !result || !inCanvas) return null;\n  const timeStamp = now();\n  const localOptions = mergeDeep(options, drawOptions);\n  const promise = Promise.all([\n    face(inCanvas, result.face, localOptions),\n    body(inCanvas, result.body, localOptions),\n    hand(inCanvas, result.hand, localOptions),\n    object(inCanvas, result.object, localOptions),\n    gesture(inCanvas, result.gesture, localOptions), // gestures do not have buffering\n    // person(inCanvas, result.persons, localOptions); // already included above\n  ]);\n  drawTime = env.perfadd ? drawTime + Math.round(now() - timeStamp) : Math.round(now() - timeStamp);\n  result.performance.draw = drawTime;\n  return promise;\n}\n", "import { log } from '../util/util';\nimport type { AnyCanvas } from '../exports';\nimport type { Point } from '../result';\nimport type { DrawOptions } from './options';\n\nexport const getCanvasContext = (input: AnyCanvas) => {\n  if (!input) log('draw error: invalid canvas');\n  else if (!input.getContext) log('draw error: canvas context not defined');\n  else {\n    const ctx = input.getContext('2d');\n    if (!ctx) log('draw error: cannot get canvas context');\n    else return ctx;\n  }\n  return null;\n};\n\nexport const rad2deg = (theta: number) => Math.round((theta * 180) / Math.PI);\n\nexport const colorDepth = (z: number | undefined, opt: DrawOptions): string => {\n  if (!opt.useDepth || typeof z === 'undefined') return opt.color;\n  const rgb = Uint8ClampedArray.from([127 + (2 * z), 127 - (2 * z), 255]);\n  const color = `rgba(${rgb[0]}, ${rgb[1]}, ${rgb[2]}, ${opt.alpha})`;\n  return color;\n};\n\nexport function point(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, x: number, y: number, z: number | undefined, localOptions: DrawOptions) {\n  ctx.fillStyle = colorDepth(z, localOptions);\n  ctx.beginPath();\n  ctx.arc(x, y, localOptions.pointSize, 0, 2 * Math.PI);\n  ctx.fill();\n}\n\nexport function rect(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, x: number, y: number, width: number, height: number, localOptions: DrawOptions) {\n  ctx.beginPath();\n  ctx.lineWidth = localOptions.lineWidth;\n  if (localOptions.useCurves) {\n    const cx = (x + x + width) / 2;\n    const cy = (y + y + height) / 2;\n    ctx.ellipse(cx, cy, width / 2, height / 2, 0, 0, 2 * Math.PI);\n  } else {\n    ctx.moveTo(x + localOptions.roundRect, y);\n    ctx.lineTo(x + width - localOptions.roundRect, y);\n    ctx.quadraticCurveTo(x + width, y, x + width, y + localOptions.roundRect);\n    ctx.lineTo(x + width, y + height - localOptions.roundRect);\n    ctx.quadraticCurveTo(x + width, y + height, x + width - localOptions.roundRect, y + height);\n    ctx.lineTo(x + localOptions.roundRect, y + height);\n    ctx.quadraticCurveTo(x, y + height, x, y + height - localOptions.roundRect);\n    ctx.lineTo(x, y + localOptions.roundRect);\n    ctx.quadraticCurveTo(x, y, x + localOptions.roundRect, y);\n    ctx.closePath();\n  }\n  ctx.stroke();\n}\n\nexport function lines(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, points: Point[], localOptions: DrawOptions) {\n  if (points.length < 2) return;\n  ctx.beginPath();\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (const pt of points) {\n    ctx.strokeStyle = colorDepth(pt[2] || 0, localOptions);\n    ctx.lineTo(Math.trunc(pt[0]), Math.trunc(pt[1]));\n  }\n  ctx.stroke();\n  if (localOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport function curves(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, points: Point[], localOptions: DrawOptions) {\n  if (points.length < 2) return;\n  ctx.lineWidth = localOptions.lineWidth;\n  if (!localOptions.useCurves || points.length <= 2) {\n    lines(ctx, points, localOptions);\n    return;\n  }\n  ctx.moveTo(points[0][0], points[0][1]);\n  for (let i = 0; i < points.length - 2; i++) {\n    const xc = (points[i][0] + points[i + 1][0]) / 2;\n    const yc = (points[i][1] + points[i + 1][1]) / 2;\n    ctx.quadraticCurveTo(points[i][0], points[i][1], xc, yc);\n  }\n  ctx.quadraticCurveTo(points[points.length - 2][0], points[points.length - 2][1], points[points.length - 1][0], points[points.length - 1][1]);\n  ctx.stroke();\n  if (localOptions.fillPolygons) {\n    ctx.closePath();\n    ctx.fill();\n  }\n}\n\nexport function arrow(ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D, from: Point, to: Point, radius = 5) {\n  let angle;\n  let x;\n  let y;\n  ctx.beginPath();\n  ctx.moveTo(from[0], from[1]);\n  ctx.lineTo(to[0], to[1]);\n  angle = Math.atan2(to[1] - from[1], to[0] - from[0]);\n  x = radius * Math.cos(angle) + to[0];\n  y = radius * Math.sin(angle) + to[1];\n  ctx.moveTo(x, y);\n  angle += (1.0 / 3.0) * (2 * Math.PI);\n  x = radius * Math.cos(angle) + to[0];\n  y = radius * Math.sin(angle) + to[1];\n  ctx.lineTo(x, y);\n  angle += (1.0 / 3.0) * (2 * Math.PI);\n  x = radius * Math.cos(angle) + to[0];\n  y = radius * Math.sin(angle) + to[1];\n  ctx.lineTo(x, y);\n  ctx.closePath();\n  ctx.stroke();\n  ctx.fill();\n}\n", "/** Draw Options\n * - Accessed via `human.draw.options` or provided per each draw method as the drawOptions optional parameter\n */\nexport type DrawOptions = {\n  /** draw line color */\n  color: string,\n  /** alpha value used for lines */\n  alpha: number,\n  /** label color */\n  labelColor: string,\n  /** label shadow color */\n  shadowColor: string,\n  /** label font */\n  font: string,\n  /** line spacing between labels */\n  lineHeight: number,\n  /** line width for drawn lines */\n  lineWidth: number,\n  /** size of drawn points */\n  pointSize: number,\n  /** draw rounded boxes by n pixels */\n  roundRect: number,\n  /** should points be drawn? */\n  drawPoints: boolean,\n  /** should labels be drawn? */\n  drawLabels: boolean,\n  /** should face attention keypoints be highlighted */\n  drawAttention: boolean;\n  /** should detected gestures be drawn? */\n  drawGestures: boolean,\n  /** should draw boxes around detection results? */\n  drawBoxes: boolean,\n  /** should draw polygons from detection points? */\n  drawPolygons: boolean,\n  /** should draw gaze arrows? */\n  drawGaze: boolean,\n  /** should fill polygons? */\n  fillPolygons: boolean,\n  /** use z-coordinate when available */\n  useDepth: boolean,\n  /** should lines be curved? */\n  useCurves: boolean,\n}\n\n/** currently set draw options {@link DrawOptions} */\nexport const options: DrawOptions = {\n  color: <string>'rgba(173, 216, 230, 0.6)', // 'lightblue' with light alpha channel\n  labelColor: <string>'rgba(173, 216, 230, 1)', // 'lightblue' with dark alpha channel\n  shadowColor: <string>'black',\n  alpha: 0.5,\n  font: <string>'small-caps 16px \"Segoe UI\"',\n  lineHeight: <number>18,\n  lineWidth: <number>4,\n  pointSize: <number>2,\n  roundRect: <number>8,\n  drawPoints: <boolean>false,\n  drawLabels: <boolean>true,\n  drawBoxes: <boolean>true,\n  drawAttention: <boolean>true,\n  drawGestures: <boolean>true,\n  drawPolygons: <boolean>true,\n  drawGaze: <boolean>true,\n  fillPolygons: <boolean>false,\n  useDepth: <boolean>true,\n  useCurves: <boolean>false,\n};\n", "import { TRI468 as triangulation } from '../face/facemeshcoords';\nimport { mergeDeep } from '../util/util';\nimport { getCanvasContext, rad2deg, rect, point, lines, arrow } from './primitives';\nimport { options } from './options';\nimport * as facemeshConstants from '../face/constants';\nimport type { FaceResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\nlet opt: DrawOptions;\n\nfunction drawLabels(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawLabels) {\n    // silly hack since fillText does not suport new line\n    const labels:string[] = [];\n    labels.push(`face: ${Math.trunc(100 * f.score)}%`);\n    if (f.genderScore) labels.push(`${f.gender || ''} ${Math.trunc(100 * f.genderScore)}%`);\n    if (f.age) labels.push(`age: ${f.age || ''}`);\n    if (f.iris) labels.push(`distance: ${f.iris}`);\n    if (f.real) labels.push(`real: ${Math.trunc(100 * f.real)}%`);\n    if (f.live) labels.push(`live: ${Math.trunc(100 * f.live)}%`);\n    if (f.emotion && f.emotion.length > 0) {\n      const emotion = f.emotion.map((a) => `${Math.trunc(100 * a.score)}% ${a.emotion}`);\n      if (emotion.length > 3) emotion.length = 3;\n      labels.push(emotion.join(' '));\n    }\n    if (f.rotation && f.rotation.angle && f.rotation.gaze) {\n      if (f.rotation.angle.roll) labels.push(`roll: ${rad2deg(f.rotation.angle.roll)}\u00B0 yaw:${rad2deg(f.rotation.angle.yaw)}\u00B0 pitch:${rad2deg(f.rotation.angle.pitch)}\u00B0`);\n      if (f.rotation.gaze.bearing) labels.push(`gaze: ${rad2deg(f.rotation.gaze.bearing)}\u00B0`);\n    }\n    if (labels.length === 0) labels.push('face');\n    ctx.fillStyle = opt.color;\n    for (let i = labels.length - 1; i >= 0; i--) {\n      const x = Math.max(f.box[0], 0);\n      const y = i * opt.lineHeight + f.box[1];\n      if (opt.shadowColor && opt.shadowColor !== '') {\n        ctx.fillStyle = opt.shadowColor;\n        ctx.fillText(labels[i], x + 5, y + 16);\n      }\n      ctx.fillStyle = opt.labelColor;\n      ctx.fillText(labels[i], x + 4, y + 15);\n    }\n  }\n}\n\nfunction drawIrisElipse(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  // iris: array[center, left, top, right, bottom]\n  if (f.annotations && f.annotations['leftEyeIris'] && f.annotations['leftEyeIris'][0]) {\n    ctx.strokeStyle = opt.useDepth ? 'rgba(255, 200, 255, 0.3)' : opt.color;\n    ctx.beginPath();\n    const sizeX = Math.abs(f.annotations['leftEyeIris'][3][0] - f.annotations['leftEyeIris'][1][0]) / 2;\n    const sizeY = Math.abs(f.annotations['leftEyeIris'][4][1] - f.annotations['leftEyeIris'][2][1]) / 2;\n    ctx.ellipse(f.annotations['leftEyeIris'][0][0], f.annotations['leftEyeIris'][0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n    ctx.stroke();\n    if (opt.fillPolygons) {\n      ctx.fillStyle = opt.useDepth ? 'rgba(255, 255, 200, 0.3)' : opt.color;\n      ctx.fill();\n    }\n  }\n  if (f.annotations && f.annotations['rightEyeIris'] && f.annotations['rightEyeIris'][0]) {\n    ctx.strokeStyle = opt.useDepth ? 'rgba(255, 200, 255, 0.3)' : opt.color;\n    ctx.beginPath();\n    const sizeX = Math.abs(f.annotations['rightEyeIris'][3][0] - f.annotations['rightEyeIris'][1][0]) / 2;\n    const sizeY = Math.abs(f.annotations['rightEyeIris'][4][1] - f.annotations['rightEyeIris'][2][1]) / 2;\n    ctx.ellipse(f.annotations['rightEyeIris'][0][0], f.annotations['rightEyeIris'][0][1], sizeX, sizeY, 0, 0, 2 * Math.PI);\n    ctx.stroke();\n    if (opt.fillPolygons) {\n      ctx.fillStyle = opt.useDepth ? 'rgba(255, 255, 200, 0.3)' : opt.color;\n      ctx.fill();\n    }\n  }\n}\n\nfunction drawGazeSpheres(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawGaze && f.rotation?.angle && typeof Path2D !== 'undefined') {\n    ctx.strokeStyle = 'pink';\n    const valX = (f.box[0] + f.box[2] / 2) - (f.box[3] * rad2deg(f.rotation.angle.yaw) / 90);\n    const valY = (f.box[1] + f.box[3] / 2) + (f.box[2] * rad2deg(f.rotation.angle.pitch) / 90);\n    const pathV = new Path2D(`\n      M ${f.box[0] + f.box[2] / 2} ${f.box[1]}\n      C\n        ${valX} ${f.box[1]},\n        ${valX} ${f.box[1] + f.box[3]},\n        ${f.box[0] + f.box[2] / 2} ${f.box[1] + f.box[3]}\n    `);\n    const pathH = new Path2D(`\n      M ${f.box[0]} ${f.box[1] + f.box[3] / 2}\n      C \n        ${f.box[0]} ${valY},\n        ${f.box[0] + f.box[2]} ${valY},\n        ${f.box[0] + f.box[2]} ${f.box[1] + f.box[3] / 2}\n    `);\n    ctx.stroke(pathH);\n    ctx.stroke(pathV);\n  }\n}\n\nfunction drawGazeArrows(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawGaze && f.rotation?.gaze?.strength && f.rotation?.gaze?.bearing && f.annotations['leftEyeIris'] && f.annotations['rightEyeIris'] && f.annotations['leftEyeIris'][0] && f.annotations['rightEyeIris'][0]) {\n    ctx.strokeStyle = 'pink';\n    ctx.fillStyle = 'pink';\n    const leftGaze = [\n      f.annotations['leftEyeIris'][0][0] + (Math.sin(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[3]),\n      f.annotations['leftEyeIris'][0][1] + (Math.cos(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[2]),\n    ];\n    arrow(ctx, [f.annotations['leftEyeIris'][0][0], f.annotations['leftEyeIris'][0][1]], [leftGaze[0], leftGaze[1]], 4);\n    const rightGaze = [\n      f.annotations['rightEyeIris'][0][0] + (Math.sin(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[3]),\n      f.annotations['rightEyeIris'][0][1] + (Math.cos(f.rotation.gaze.bearing) * f.rotation.gaze.strength * f.box[2]),\n    ];\n    arrow(ctx, [f.annotations['rightEyeIris'][0][0], f.annotations['rightEyeIris'][0][1]], [rightGaze[0], rightGaze[1]], 4);\n  }\n}\n\nfunction drawFacePolygons(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawPolygons && f.mesh.length >= 468) {\n    ctx.lineWidth = 1;\n    for (let i = 0; i < triangulation.length / 3; i++) {\n      const points = [triangulation[i * 3 + 0], triangulation[i * 3 + 1], triangulation[i * 3 + 2]].map((index) => f.mesh[index]);\n      lines(ctx, points, opt);\n    }\n    drawIrisElipse(f, ctx);\n  }\n  /*\n  if (opt.drawPolygons && f.contours.length > 1) {\n    ctx.lineWidth = 5;\n    lines(ctx, f.contours, opt);\n  }\n  ctx.lineWidth = 1;\n  */\n}\n\nfunction drawFacePoints(f: FaceResult, ctx: CanvasRenderingContext2D | OffscreenCanvasRenderingContext2D) {\n  if (opt.drawPoints && f.mesh.length >= 468) {\n    for (let i = 0; i < f.mesh.length; i++) {\n      point(ctx, f.mesh[i][0], f.mesh[i][1], f.mesh[i][2], opt);\n      if (opt.drawAttention) {\n        if (facemeshConstants.LANDMARKS_REFINEMENT_LIPS_CONFIG.includes(i)) point(ctx, f.mesh[i][0], f.mesh[i][1], (f.mesh[i][2] as number) + 127, opt);\n        if (facemeshConstants.LANDMARKS_REFINEMENT_LEFT_EYE_CONFIG.includes(i)) point(ctx, f.mesh[i][0], f.mesh[i][1], (f.mesh[i][2] as number) - 127, opt);\n        if (facemeshConstants.LANDMARKS_REFINEMENT_RIGHT_EYE_CONFIG.includes(i)) point(ctx, f.mesh[i][0], f.mesh[i][1], (f.mesh[i][2] as number) - 127, opt);\n      }\n    }\n  }\n}\n\nfunction drawFaceBoxes(f: FaceResult, ctx) {\n  if (opt.drawBoxes) {\n    rect(ctx, f.box[0], f.box[1], f.box[2], f.box[3], opt);\n  }\n}\n\n/** draw detected faces */\nexport async function face(inCanvas: AnyCanvas, result: Array<FaceResult>, drawOptions?: Partial<DrawOptions>) {\n  opt = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.font = opt.font;\n  ctx.strokeStyle = opt.color;\n  ctx.fillStyle = opt.color;\n  for (const f of result) {\n    drawFaceBoxes(f, ctx);\n    drawLabels(f, ctx);\n    if (f.mesh && f.mesh.length > 0) {\n      drawFacePoints(f, ctx);\n      drawFacePolygons(f, ctx);\n      drawGazeSpheres(f, ctx);\n      drawGazeArrows(f, ctx);\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext, rect, point, curves, colorDepth } from './primitives';\nimport { options } from './options';\nimport type { BodyResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\n/** draw detected bodies */\nexport async function body(inCanvas: AnyCanvas, result: Array<BodyResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  for (let i = 0; i < result.length; i++) {\n    ctx.strokeStyle = localOptions.color;\n    ctx.fillStyle = localOptions.color;\n    ctx.lineWidth = localOptions.lineWidth;\n    ctx.font = localOptions.font;\n    if (localOptions.drawBoxes && result[i].box && result[i].box?.length === 4) {\n      rect(ctx, result[i].box[0], result[i].box[1], result[i].box[2], result[i].box[3], localOptions);\n      if (localOptions.drawLabels) {\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(`body ${100 * result[i].score}%`, result[i].box[0] + 3, 1 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(`body ${100 * result[i].score}%`, result[i].box[0] + 2, 0 + result[i].box[1] + localOptions.lineHeight, result[i].box[2]);\n      }\n    }\n    if (localOptions.drawPoints && result[i].keypoints) {\n      for (let pt = 0; pt < result[i].keypoints.length; pt++) {\n        if (!result[i].keypoints[pt].score || (result[i].keypoints[pt].score === 0)) continue;\n        ctx.fillStyle = colorDepth(result[i].keypoints[pt].position[2], localOptions);\n        point(ctx, result[i].keypoints[pt].position[0], result[i].keypoints[pt].position[1], 0, localOptions);\n      }\n    }\n    if (localOptions.drawLabels && result[i].keypoints) {\n      ctx.font = localOptions.font;\n      for (const pt of result[i].keypoints) {\n        if (!pt.score || (pt.score === 0)) continue;\n        ctx.fillStyle = colorDepth(pt.position[2], localOptions);\n        ctx.fillText(`${pt.part} ${Math.trunc(100 * pt.score)}%`, pt.position[0] + 4, pt.position[1] + 4);\n      }\n    }\n    if (localOptions.drawPolygons && result[i].keypoints && result[i].annotations) {\n      for (const part of Object.values(result[i].annotations)) {\n        for (const connected of part) curves(ctx, connected, localOptions);\n      }\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext, rect, point, colorDepth } from './primitives';\nimport { options } from './options';\nimport type { HandResult } from '../result';\nimport type { AnyCanvas, DrawOptions, Point } from '../exports';\n\n/** draw detected hands */\nexport async function hand(inCanvas: AnyCanvas, result: Array<HandResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = localOptions.font;\n  for (const h of result) {\n    if (localOptions.drawBoxes) {\n      ctx.strokeStyle = localOptions.color;\n      ctx.fillStyle = localOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3], localOptions);\n      if (localOptions.drawLabels) {\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(`hand:${Math.trunc(100 * h.score)}%`, h.box[0] + 3, 1 + h.box[1] + localOptions.lineHeight, h.box[2]); // can use h.label\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(`hand:${Math.trunc(100 * h.score)}%`, h.box[0] + 2, 0 + h.box[1] + localOptions.lineHeight, h.box[2]); // can use h.label\n      }\n      ctx.stroke();\n    }\n    if (localOptions.drawPoints) {\n      if (h.keypoints && h.keypoints.length > 0) {\n        for (const pt of h.keypoints) {\n          ctx.fillStyle = colorDepth(pt[2], localOptions);\n          point(ctx, pt[0], pt[1], 0, localOptions);\n        }\n      }\n    }\n    if (localOptions.drawLabels && h.annotations) {\n      const addHandLabel = (part: Array<Point>, title: string) => {\n        if (!part || part.length === 0 || !part[0]) return;\n        const z = part[part.length - 1][2] || -256;\n        ctx.fillStyle = colorDepth(z, localOptions);\n        ctx.fillText(title, part[part.length - 1][0] + 4, part[part.length - 1][1] + 4);\n      };\n      ctx.font = localOptions.font;\n      addHandLabel(h.annotations['index'], 'index');\n      addHandLabel(h.annotations['middle'], 'middle');\n      addHandLabel(h.annotations['ring'], 'ring');\n      addHandLabel(h.annotations['pinky'], 'pinky');\n      addHandLabel(h.annotations['thumb'], 'thumb');\n      addHandLabel(h.annotations['palm'], 'palm');\n    }\n    if (localOptions.drawPolygons && h.annotations) {\n      const addHandLine = (part: Array<Point>) => {\n        if (!part || part.length === 0 || !part[0]) return;\n        for (let i = 0; i < part.length; i++) {\n          ctx.beginPath();\n          const z = part[i][2] || 0;\n          ctx.strokeStyle = colorDepth(i * z, localOptions);\n          ctx.moveTo(part[i > 0 ? i - 1 : 0][0], part[i > 0 ? i - 1 : 0][1]);\n          ctx.lineTo(part[i][0], part[i][1]);\n          ctx.stroke();\n        }\n      };\n      ctx.lineWidth = localOptions.lineWidth;\n      addHandLine(h.annotations['index']);\n      addHandLine(h.annotations['middle']);\n      addHandLine(h.annotations['ring']);\n      addHandLine(h.annotations['pinky']);\n      addHandLine(h.annotations['thumb']);\n      // addPart(h.annotations.palm);\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext, rect } from './primitives';\nimport { options } from './options';\nimport type { ObjectResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\n/** draw detected objects */\nexport async function object(inCanvas: AnyCanvas, result: Array<ObjectResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  const ctx = getCanvasContext(inCanvas);\n  if (!ctx) return;\n  ctx.lineJoin = 'round';\n  ctx.font = localOptions.font;\n  for (const h of result) {\n    if (localOptions.drawBoxes) {\n      ctx.strokeStyle = localOptions.color;\n      ctx.fillStyle = localOptions.color;\n      rect(ctx, h.box[0], h.box[1], h.box[2], h.box[3], localOptions);\n      if (localOptions.drawLabels) {\n        const label = `${h.label} ${Math.round(100 * h.score)}%`;\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(label, h.box[0] + 3, 1 + h.box[1] + localOptions.lineHeight, h.box[2]);\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(label, h.box[0] + 2, 0 + h.box[1] + localOptions.lineHeight, h.box[2]);\n      }\n      ctx.stroke();\n    }\n  }\n}\n", "import { mergeDeep } from '../util/util';\nimport { getCanvasContext } from './primitives';\nimport { options } from './options';\nimport type { GestureResult } from '../result';\nimport type { AnyCanvas, DrawOptions } from '../exports';\n\n/** draw detected gestures */\nexport async function gesture(inCanvas: AnyCanvas, result: Array<GestureResult>, drawOptions?: Partial<DrawOptions>) {\n  const localOptions = mergeDeep(options, drawOptions);\n  if (!result || !inCanvas) return;\n  if (localOptions.drawGestures) {\n    const ctx = getCanvasContext(inCanvas);\n    if (!ctx) return;\n    ctx.font = localOptions.font;\n    ctx.fillStyle = localOptions.color;\n    let i = 1;\n    for (let j = 0; j < result.length; j++) {\n      let where: unknown[] = []; // what&where is a record\n      let what: unknown[] = []; // what&where is a record\n      [where, what] = Object.entries(result[j]);\n      if ((what.length > 1) && ((what[1] as string).length > 0)) {\n        const who = where[1] as number > 0 ? `#${where[1]}` : '';\n        const label = `${where[0]} ${who}: ${what[1]}`;\n        if (localOptions.shadowColor && localOptions.shadowColor !== '') {\n          ctx.fillStyle = localOptions.shadowColor;\n          ctx.fillText(label, 8, 2 + (i * localOptions.lineHeight));\n        }\n        ctx.fillStyle = localOptions.labelColor;\n        ctx.fillText(label, 6, 0 + (i * localOptions.lineHeight));\n        i += 1;\n      }\n    }\n  }\n}\n", "import type { Tensor } from '../tfjs/types';\nimport type { FaceResult } from '../result';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport { meshAnnotations } from './facemeshcoords';\n\nconst expandFact = 0.1;\nconst alpha = 0.5;\n\n// point inclusion in polygon based on https://wrf.ecse.rpi.edu/Research/Short_Notes/pnpoly.html\nfunction insidePoly(x: number, y: number, polygon: Array<{ x: number, y: number }>): boolean {\n  let inside = false;\n  let j = polygon.length - 1;\n  for (let i = 0; i < polygon.length; j = i++) {\n    if (((polygon[i].y > y) !== (polygon[j].y > y)) && (x < (polygon[j].x - polygon[i].x) * (y - polygon[i].y) / (polygon[j].y - polygon[i].y) + polygon[i].x)) inside = !inside;\n  }\n  return inside;\n}\n\nexport async function mask(face: FaceResult): Promise<Tensor | undefined> {\n  if (!face.tensor) return face.tensor;\n  if (!face.mesh || face.mesh.length < 100) return face.tensor;\n  const width = face.tensor.shape[2] || 0;\n  const height = face.tensor.shape[1] || 0;\n  const buffer = await face.tensor.buffer();\n  let silhouette: Array<{ x: number, y: number }> = [];\n  for (const pt of meshAnnotations.silhouette) silhouette.push({ x: (face.mesh[pt][0] - face.box[0]) / face.box[2], y: (face.mesh[pt][1] - face.box[1]) / face.box[3] }); // add all silhouette points scaled to local box\n  if (expandFact && expandFact > 0) silhouette = silhouette.map((pt) => ({ x: pt.x > 0.5 ? pt.x + expandFact : pt.x - expandFact, y: pt.y > 0.5 ? pt.y + expandFact : pt.y - expandFact })); // expand silhouette\n  for (let x = 0; x < width; x++) {\n    for (let y = 0; y < height; y++) {\n      const inside = insidePoly(x / width, y / width, silhouette);\n      if (!inside) {\n        buffer.set(alpha * buffer.get(0, y, x, 0), 0, y, x, 0);\n        buffer.set(alpha * buffer.get(0, y, x, 1), 0, y, x, 1);\n        buffer.set(alpha * buffer.get(0, y, x, 2), 0, y, x, 2);\n      }\n    }\n  }\n  const output = buffer.toTensor();\n  tf.dispose(buffer);\n  return output;\n}\n", "import type { Point, FaceResult } from '../result';\n\ntype Vector = [number, number, number];\n\nconst calculateGaze = (face: FaceResult): { bearing: number, strength: number } => {\n  const radians = (pt1: Point, pt2: Point) => Math.atan2(pt1[1] - pt2[1], pt1[0] - pt2[0]); // function to calculate angle between any two points\n  if (!face.annotations['rightEyeIris'] || !face.annotations['leftEyeIris']) return { bearing: 0, strength: 0 };\n\n  const offsetIris = [0, -0.1]; // iris center may not align with average of eye extremes\n  const eyeRatio = 1; // factor to normalize changes x vs y\n\n  const left = (face.mesh[33][2] || 0) > (face.mesh[263][2] || 0); // pick left or right eye depending which one is closer bazed on outsize point z axis\n  const irisCenter = left ? face.mesh[473] : face.mesh[468];\n  const eyeCenter = left // eye center is average of extreme points on x axis for both x and y, ignoring y extreme points as eyelids naturally open/close more when gazing up/down so relative point is less precise\n    ? [(face.mesh[133][0] + face.mesh[33][0]) / 2, (face.mesh[133][1] + face.mesh[33][1]) / 2]\n    : [(face.mesh[263][0] + face.mesh[362][0]) / 2, (face.mesh[263][1] + face.mesh[362][1]) / 2];\n  const eyeSize = left // eye size is difference between extreme points for both x and y, used to normalize & squarify eye dimensions\n    ? [face.mesh[133][0] - face.mesh[33][0], face.mesh[23][1] - face.mesh[27][1]]\n    : [face.mesh[263][0] - face.mesh[362][0], face.mesh[253][1] - face.mesh[257][1]];\n  const eyeDiff: Point = [ // x distance between extreme point and center point normalized with eye size\n    (eyeCenter[0] - irisCenter[0]) / eyeSize[0] - offsetIris[0],\n    eyeRatio * (irisCenter[1] - eyeCenter[1]) / eyeSize[1] - offsetIris[1],\n  ];\n  let strength = Math.sqrt((eyeDiff[0] * eyeDiff[0]) + (eyeDiff[1] * eyeDiff[1])); // vector length is a diagonal between two differences\n  strength = Math.min(strength, face.boxRaw[2] / 2, face.boxRaw[3] / 2); // limit strength to half of box size to avoid clipping due to low precision\n  const bearing = (radians([0, 0], eyeDiff) + (Math.PI / 2)) % Math.PI; // using eyeDiff instead eyeCenter/irisCenter combo due to manual adjustments and rotate clockwise 90degrees\n  return { bearing, strength };\n};\n\nexport const calculateFaceAngle = (face: FaceResult, imageSize: [number, number]): {\n  angle: { pitch: number, yaw: number, roll: number },\n  matrix: [number, number, number, number, number, number, number, number, number],\n  gaze: { bearing: number, strength: number },\n} => {\n  // const degrees = (theta) => Math.abs(((theta * 180) / Math.PI) % 360);\n  const normalize = (v: Vector): Vector => { // normalize vector\n    const length = Math.sqrt(v[0] * v[0] + v[1] * v[1] + v[2] * v[2]);\n    v[0] /= length;\n    v[1] /= length;\n    v[2] /= length;\n    return v;\n  };\n  const subVectors = (a: Vector, b: Vector): Vector => { // vector subtraction (a - b)\n    const x = a[0] - b[0];\n    const y = a[1] - b[1];\n    const z = a[2] - b[2];\n    return [x, y, z];\n  };\n  const crossVectors = (a: Vector, b: Vector): Vector => { // vector cross product (a x b)\n    const x = a[1] * b[2] - a[2] * b[1];\n    const y = a[2] * b[0] - a[0] * b[2];\n    const z = a[0] * b[1] - a[1] * b[0];\n    return [x, y, z];\n  };\n  // 3x3 rotation matrix to Euler angles based on https://www.geometrictools.com/Documentation/EulerAngles.pdf\n  const rotationMatrixToEulerAngle = (r: number[]): { pitch: number, yaw: number, roll: number } => {\n    // eslint-disable-next-line no-unused-vars, @typescript-eslint/no-unused-vars\n    const [r00, _r01, _r02, r10, r11, r12, r20, r21, r22] = r;\n    let thetaX: number;\n    let thetaY: number;\n    let thetaZ: number;\n    if (r10 < 1) { // YZX calculation\n      if (r10 > -1) {\n        thetaZ = Math.asin(r10);\n        thetaY = Math.atan2(-r20, r00);\n        thetaX = Math.atan2(-r12, r11);\n      } else {\n        thetaZ = -Math.PI / 2;\n        thetaY = -Math.atan2(r21, r22);\n        thetaX = 0;\n      }\n    } else {\n      thetaZ = Math.PI / 2;\n      thetaY = Math.atan2(r21, r22);\n      thetaX = 0;\n    }\n    if (isNaN(thetaX)) thetaX = 0;\n    if (isNaN(thetaY)) thetaY = 0;\n    if (isNaN(thetaZ)) thetaZ = 0;\n    return { pitch: 2 * -thetaX, yaw: 2 * -thetaY, roll: 2 * -thetaZ };\n  };\n\n  /*\n  const meshToEulerAngle = (mesh) => { // simple Euler angle calculation based existing 3D mesh\n    const radians = (a1, a2, b1, b2) => Math.atan2(b2 - a2, b1 - a1);\n    return { // values are in radians in range of -pi/2 to pi/2 which is -90 to +90 degrees, value of 0 means center\n      pitch: radians(mesh[10][1], mesh[10][2], mesh[152][1], mesh[152][2]), // looking at y,z of top and bottom points of the face // pitch is face move up/down\n      yaw: radians(mesh[33][0], mesh[33][2], mesh[263][0], mesh[263][2]), // looking at x,z of outside corners of leftEye and rightEye // yaw is face turn left/right\n      roll: radians(mesh[33][0], mesh[33][1], mesh[263][0], mesh[263][1]), // looking at x,y of outside corners of leftEye and rightEye // roll is face lean left/right\n    };\n  };\n  */\n\n  // initialize gaze and mesh\n  const mesh = face.meshRaw;\n  if (!mesh || mesh.length < 300) return { angle: { pitch: 0, yaw: 0, roll: 0 }, matrix: [1, 0, 0, 0, 1, 0, 0, 0, 1], gaze: { bearing: 0, strength: 0 } };\n\n  const size = Math.max(face.boxRaw[2] * imageSize[0], face.boxRaw[3] * imageSize[1]) / 1.5;\n  // top, bottom, left, right\n  const pts: Point[] = [mesh[10], mesh[152], mesh[234], mesh[454]].map((pt) => [pt[0] * imageSize[0] / size, pt[1] * imageSize[1] / size, pt[2]] as Point); // make the xyz coordinates proportional, independent of the image/box size\n\n  const y_axis = normalize(subVectors(pts[1] as Vector, pts[0] as Vector));\n  let x_axis = normalize(subVectors(pts[3] as Vector, pts[2] as Vector));\n  const z_axis = normalize(crossVectors(x_axis, y_axis));\n  // adjust x_axis to make sure that all axes are perpendicular to each other\n  x_axis = crossVectors(y_axis, z_axis);\n\n  // Rotation Matrix from Axis Vectors - http://renderdan.blogspot.com/2006/05/rotation-matrix-from-axis-vectors.html\n  // 3x3 rotation matrix is flatten to array in row-major order. Note that the rotation represented by this matrix is inverted.\n  const matrix: [number, number, number, number, number, number, number, number, number] = [\n    x_axis[0], x_axis[1], x_axis[2],\n    y_axis[0], y_axis[1], y_axis[2],\n    z_axis[0], z_axis[1], z_axis[2],\n  ];\n  const angle = rotationMatrixToEulerAngle(matrix);\n  // const angle = meshToEulerAngle(mesh);\n\n  // we have iris keypoints so we can calculate gaze direction\n  const gaze = mesh.length === 478 ? calculateGaze(face) : { bearing: 0, strength: 0 };\n\n  return { angle, matrix, gaze };\n};\n", "/**\n * Face algorithm implementation\n * Uses FaceMesh, Emotion and FaceRes models to create a unified pipeline\n */\n\nimport { log, now } from '../util/util';\nimport { env } from '../util/env';\nimport * as tf from '../../dist/tfjs.esm.js';\nimport * as facemesh from './facemesh';\nimport * as emotion from '../gear/emotion';\nimport * as faceres from './faceres';\nimport * as mask from './mask';\nimport * as antispoof from './antispoof';\nimport * as liveness from './liveness';\nimport * as gear from '../gear/gear';\nimport * as ssrnetAge from '../gear/ssrnet-age';\nimport * as ssrnetGender from '../gear/ssrnet-gender';\nimport * as mobilefacenet from './mobilefacenet';\nimport type { FaceResult, Emotion, Gender, Race } from '../result';\nimport type { Tensor } from '../tfjs/types';\nimport type { Human } from '../human';\nimport { calculateFaceAngle } from './angles';\n\ntype DescRes = { age: number, gender: Gender, genderScore: number, descriptor: number[], race?: { score: number, race: Race }[] };\n\nexport const detectFace = async (instance: Human /* instance of human */, input: Tensor): Promise<FaceResult[]> => {\n  // run facemesh, includes blazeface and iris\n  // eslint-disable-next-line no-async-promise-executor\n  let timeStamp: number = now();\n  let ageRes: { age: number } | Promise<{ age: number }> | null;\n  let gearRes: gear.GearType | Promise<gear.GearType> | null;\n  let genderRes: { gender: string, genderScore: number } | Promise<{ gender: string, genderScore: number }> | null;\n  let emotionRes: { score: number, emotion: Emotion }[] | Promise<{ score: number, emotion: Emotion }[]>;\n  let mobilefacenetRes: number[] | Promise<number[]> | null;\n  let antispoofRes: number | Promise<number> | null;\n  let livenessRes: number | Promise<number> | null;\n  let descRes: DescRes | Promise<DescRes> | null;\n\n  const faceRes: Array<FaceResult> = [];\n  instance.state = 'run:face';\n\n  const faces = await facemesh.predict(input, instance.config);\n  instance.performance.face = env.perfadd ? (instance.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n  if (!input.shape || input.shape.length !== 4) return [];\n  if (!faces) return [];\n  // for (const face of faces) {\n  for (let i = 0; i < faces.length; i++) {\n    instance.analyze('Get Face');\n\n    // is something went wrong, skip the face\n    // @ts-ignore possibly undefied\n    if (!faces[i].tensor || faces[i].tensor['isDisposedInternal']) {\n      log('Face object is disposed:', faces[i].tensor);\n      continue;\n    }\n\n    // optional face mask\n    if (instance.config.face.detector?.mask) {\n      const masked = await mask.mask(faces[i]);\n      tf.dispose(faces[i].tensor);\n      faces[i].tensor = masked as Tensor;\n    }\n\n    // calculate face angles\n    const rotation = faces[i].mesh && (faces[i].mesh.length > 200) ? calculateFaceAngle(faces[i], [input.shape[2], input.shape[1]]) : null;\n\n    // run emotion, inherits face from blazeface\n    instance.analyze('Start Emotion:');\n    if (instance.config.async) {\n      emotionRes = instance.config.face.emotion?.enabled ? emotion.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : [];\n    } else {\n      instance.state = 'run:emotion';\n      timeStamp = now();\n      emotionRes = instance.config.face.emotion?.enabled ? await emotion.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : [];\n      instance.performance.emotion = env.perfadd ? (instance.performance.emotion || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End Emotion:');\n\n    // run antispoof, inherits face from blazeface\n    instance.analyze('Start AntiSpoof:');\n    if (instance.config.async) {\n      antispoofRes = instance.config.face.antispoof?.enabled ? antispoof.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n    } else {\n      instance.state = 'run:antispoof';\n      timeStamp = now();\n      antispoofRes = instance.config.face.antispoof?.enabled ? await antispoof.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n      instance.performance.antispoof = env.perfadd ? (instance.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End AntiSpoof:');\n\n    // run liveness, inherits face from blazeface\n    instance.analyze('Start Liveness:');\n    if (instance.config.async) {\n      livenessRes = instance.config.face.liveness?.enabled ? liveness.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n    } else {\n      instance.state = 'run:liveness';\n      timeStamp = now();\n      livenessRes = instance.config.face.liveness?.enabled ? await liveness.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : 0;\n      instance.performance.liveness = env.perfadd ? (instance.performance.antispoof || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End Liveness:');\n\n    // run gear, inherits face from blazeface\n    instance.analyze('Start GEAR:');\n    if (instance.config.async) {\n      gearRes = instance.config.face['gear']?.enabled ? gear.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:gear';\n      timeStamp = now();\n      gearRes = instance.config.face['gear']?.enabled ? await gear.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.gear = Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End GEAR:');\n\n    // run gear, inherits face from blazeface\n    instance.analyze('Start SSRNet:');\n    if (instance.config.async) {\n      ageRes = instance.config.face['ssrnet']?.enabled ? ssrnetAge.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      genderRes = instance.config.face['ssrnet']?.enabled ? ssrnetGender.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:ssrnet';\n      timeStamp = now();\n      ageRes = instance.config.face['ssrnet']?.enabled ? await ssrnetAge.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      genderRes = instance.config.face['ssrnet']?.enabled ? await ssrnetGender.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.ssrnet = Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End SSRNet:');\n\n    // run gear, inherits face from blazeface\n    instance.analyze('Start MobileFaceNet:');\n    if (instance.config.async) {\n      mobilefacenetRes = instance.config.face['mobilefacenet']?.enabled ? mobilefacenet.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:mobilefacenet';\n      timeStamp = now();\n      mobilefacenetRes = instance.config.face['mobilefacenet']?.enabled ? await mobilefacenet.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.mobilefacenet = Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End MobileFaceNet:');\n\n    // run emotion, inherits face from blazeface\n    instance.analyze('Start Description:');\n    if (instance.config.async) {\n      descRes = instance.config.face.description?.enabled ? faceres.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n    } else {\n      instance.state = 'run:description';\n      timeStamp = now();\n      descRes = instance.config.face.description?.enabled ? await faceres.predict(faces[i].tensor || tf.tensor([]), instance.config, i, faces.length) : null;\n      instance.performance.description = env.perfadd ? (instance.performance.description || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n    }\n    instance.analyze('End Description:');\n\n    // if async wait for results\n    if (instance.config.async) {\n      [ageRes, genderRes, emotionRes, mobilefacenetRes, descRes, gearRes, antispoofRes, livenessRes] = await Promise.all([ageRes, genderRes, emotionRes, mobilefacenetRes, descRes, gearRes, antispoofRes, livenessRes]);\n    }\n    instance.analyze('Finish Face:');\n\n    if (instance.config.face['ssrnet']?.enabled && ageRes && genderRes) { // override age/gender if ssrnet model is used\n      descRes = {\n        ...(descRes as DescRes),\n        age: (ageRes as { age: number}).age,\n        gender: (genderRes as { gender: Gender, genderScore: number }).gender,\n        genderScore: (genderRes as { gender: Gender, genderScore: number }).genderScore,\n      };\n    }\n    if (instance.config.face['gear']?.enabled && gearRes) { // override age/gender/race if gear model is used\n      descRes = {\n        ...(descRes as DescRes),\n        age: (gearRes as gear.GearType).age,\n        gender: (gearRes as gear.GearType).gender,\n        genderScore: (gearRes as gear.GearType).genderScore,\n        race: (gearRes as gear.GearType).race,\n      };\n    }\n    if (instance.config.face['mobilefacenet']?.enabled && mobilefacenetRes) { // override descriptor if embedding model is used\n      (descRes as DescRes).descriptor = mobilefacenetRes as number[];\n    }\n\n    // calculate iris distance\n    // iris: array[ center, left, top, right, bottom]\n    if (!instance.config.face.iris?.enabled) {\n      // if (faces[i]?.annotations?.leftEyeIris) delete faces[i].annotations.leftEyeIris;\n      // if (faces[i]?.annotations?.rightEyeIris) delete faces[i].annotations.rightEyeIris;\n    }\n    const irisSize = (faces[i].annotations && faces[i].annotations.leftEyeIris && faces[i].annotations.leftEyeIris[0] && faces[i].annotations.rightEyeIris && faces[i].annotations.rightEyeIris[0]\n      && (faces[i].annotations.leftEyeIris.length > 0) && (faces[i].annotations.rightEyeIris.length > 0)\n      && (faces[i].annotations.leftEyeIris[0] !== null) && (faces[i].annotations.rightEyeIris[0] !== null))\n      ? Math.max(Math.abs(faces[i].annotations.leftEyeIris[3][0] - faces[i].annotations.leftEyeIris[1][0]), Math.abs(faces[i].annotations.rightEyeIris[4][1] - faces[i].annotations.rightEyeIris[2][1])) / input.shape[2]\n      : 0; // note: average human iris size is 11.7mm\n\n    // optionally return tensor\n    const tensor = instance.config.face.detector?.return ? tf.squeeze(faces[i].tensor) : null;\n    // dispose original face tensor\n    tf.dispose(faces[i].tensor);\n    // delete temp face image\n    if (faces[i].tensor) delete faces[i].tensor;\n    // combine results\n    const res: FaceResult = {\n      ...faces[i],\n      id: i,\n    };\n    if ((descRes as DescRes)?.age) res.age = (descRes as DescRes).age as number;\n    if ((descRes as DescRes)?.gender) res.gender = (descRes as DescRes).gender as Gender;\n    if ((descRes as DescRes)?.genderScore) res.genderScore = (descRes as DescRes)?.genderScore as number;\n    if ((descRes as DescRes)?.descriptor) res.embedding = (descRes as DescRes)?.descriptor as Array<number>;\n    if ((descRes as DescRes)?.race) res.race = (descRes as DescRes)?.race as { score: number, race: Race }[];\n    if (emotionRes) res.emotion = emotionRes as Array<{ score: number, emotion: Emotion }>;\n    if (antispoofRes) res.real = antispoofRes as number;\n    if (livenessRes) res.live = livenessRes as number;\n    if (irisSize && irisSize !== 0) res.iris = Math.trunc(500 / irisSize / 11.7) / 100;\n    if (rotation) res.rotation = rotation;\n    if (tensor) res.tensor = tensor;\n    faceRes.push(res);\n    instance.analyze('End Face');\n  }\n  instance.analyze('End FaceMesh:');\n  if (instance.config.async) {\n    if (instance.performance.face) delete instance.performance.face;\n    if (instance.performance.age) delete instance.performance.age;\n    if (instance.performance.gender) delete instance.performance.gender;\n    if (instance.performance.emotion) delete instance.performance.emotion;\n  }\n  return faceRes;\n};\n", "/**\n * Gesture detection algorithm\n */\n\nimport type { GestureResult, BodyResult, FaceResult, HandResult, Point } from '../result';\nimport * as fingerPose from '../hand/fingerpose';\n\n/** face gesture type */\nexport type FaceGesture =\n  `facing ${'left' | 'center' | 'right'}`\n  | `blink ${'left' | 'right'} eye`\n  | `mouth ${number}% open`\n  | `head ${'up' | 'down'}`;\n\n/** iris gesture type */\nexport type IrisGesture =\n  'facing center'\n  | `looking ${'left' | 'right' | 'up' | 'down'}`\n  | 'looking center';\n\n/** body gesture type */\nexport type BodyGesture =\n  `leaning ${'left' | 'right'}`\n  | `raise ${'left' | 'right'} hand`\n  | 'i give up';\n\n/** hand gesture type */\nexport type HandGesture =\n  `${'thumb' | 'index' | 'middle' | 'ring' | 'pinky'} forward`\n  | `${'thumb' | 'index' | 'middle' | 'ring' | 'pinky'} up`\n  | 'victory'\n  | 'thumbs up';\n\nexport const body = (res: BodyResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ body: number, gesture: BodyGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    // raising hands\n    const leftWrist = res[i].keypoints.find((a) => (a.part === 'leftWrist'));\n    const rightWrist = res[i].keypoints.find((a) => (a.part === 'rightWrist'));\n    const nose = res[i].keypoints.find((a) => (a.part === 'nose'));\n    if (nose && leftWrist && rightWrist && (leftWrist.position[1] < nose.position[1]) && (rightWrist.position[1] < nose.position[1])) gestures.push({ body: i, gesture: 'i give up' });\n    else if (nose && leftWrist && (leftWrist.position[1] < nose.position[1])) gestures.push({ body: i, gesture: 'raise left hand' });\n    else if (nose && rightWrist && (rightWrist.position[1] < nose.position[1])) gestures.push({ body: i, gesture: 'raise right hand' });\n\n    // leaning\n    const leftShoulder = res[i].keypoints.find((a) => (a.part === 'leftShoulder'));\n    const rightShoulder = res[i].keypoints.find((a) => (a.part === 'rightShoulder'));\n    if (leftShoulder && rightShoulder && Math.abs(leftShoulder.positionRaw[1] - rightShoulder.positionRaw[1]) > 0.1) {\n      gestures.push({ body: i, gesture: `leaning ${(leftShoulder.position[1] > rightShoulder.position[1]) ? 'left' : 'right'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const face = (res: FaceResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ face: number, gesture: FaceGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (res[i].mesh && res[i].mesh.length > 450) {\n      const zDiff = (res[i].mesh[33][2] || 0) - (res[i].mesh[263][2] || 0);\n      const xDiff = res[i].mesh[33][0] - res[i].mesh[263][0];\n      if (Math.abs(zDiff / xDiff) <= 0.15) gestures.push({ face: i, gesture: 'facing center' });\n      else gestures.push({ face: i, gesture: `facing ${zDiff < 0 ? 'left' : 'right'}` });\n      const openLeft = Math.abs(res[i].mesh[374][1] - res[i].mesh[386][1]) / Math.abs(res[i].mesh[443][1] - res[i].mesh[450][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openLeft < 0.2) gestures.push({ face: i, gesture: 'blink left eye' });\n      const openRight = Math.abs(res[i].mesh[145][1] - res[i].mesh[159][1]) / Math.abs(res[i].mesh[223][1] - res[i].mesh[230][1]); // center of eye inner lid y coord div center of wider eye border y coord\n      if (openRight < 0.2) gestures.push({ face: i, gesture: 'blink right eye' });\n      const mouthOpen = Math.min(100, 500 * Math.abs(res[i].mesh[13][1] - res[i].mesh[14][1]) / Math.abs(res[i].mesh[10][1] - res[i].mesh[152][1]));\n      if (mouthOpen > 10) gestures.push({ face: i, gesture: `mouth ${Math.trunc(mouthOpen)}% open` });\n      const chinDepth = res[i].mesh[152][2] || 0;\n      if (Math.abs(chinDepth) > 10) gestures.push({ face: i, gesture: `head ${chinDepth < 0 ? 'up' : 'down'}` });\n    }\n  }\n  return gestures;\n};\n\nexport const iris = (res: FaceResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ iris: number, gesture: IrisGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    if (!res[i].annotations || !res[i].annotations.leftEyeIris || !res[i].annotations.leftEyeIris[0] || !res[i].annotations.rightEyeIris || !res[i].annotations.rightEyeIris[0]) continue;\n    const sizeXLeft = res[i].annotations.leftEyeIris[3][0] - res[i].annotations.leftEyeIris[1][0];\n    const sizeYLeft = res[i].annotations.leftEyeIris[4][1] - res[i].annotations.leftEyeIris[2][1];\n    const areaLeft = Math.abs(sizeXLeft * sizeYLeft);\n\n    const sizeXRight = res[i].annotations.rightEyeIris[3][0] - res[i].annotations.rightEyeIris[1][0];\n    const sizeYRight = res[i].annotations.rightEyeIris[4][1] - res[i].annotations.rightEyeIris[2][1];\n    const areaRight = Math.abs(sizeXRight * sizeYRight);\n\n    let center = false;\n    const difference = Math.abs(areaLeft - areaRight) / Math.max(areaLeft, areaRight);\n    if (difference < 0.25) {\n      center = true;\n      gestures.push({ iris: i, gesture: 'facing center' });\n    }\n\n    const leftIrisCenterX = Math.abs(res[i].mesh[263][0] - res[i].annotations.leftEyeIris[0][0]) / res[i].box[2];\n    const rightIrisCenterX = Math.abs(res[i].mesh[33][0] - res[i].annotations.rightEyeIris[0][0]) / res[i].box[2];\n    if (leftIrisCenterX > 0.06 || rightIrisCenterX > 0.06) center = false;\n    if (leftIrisCenterX > rightIrisCenterX) { // check eye with bigger offset\n      if (leftIrisCenterX > 0.05) gestures.push({ iris: i, gesture: 'looking right' });\n    } else {\n      if (rightIrisCenterX > 0.05) gestures.push({ iris: i, gesture: 'looking left' });\n    }\n\n    const rightIrisCenterY = Math.abs(res[i].mesh[145][1] - res[i].annotations.rightEyeIris[0][1]) / res[i].box[3];\n    const leftIrisCenterY = Math.abs(res[i].mesh[374][1] - res[i].annotations.leftEyeIris[0][1]) / res[i].box[3];\n    if (leftIrisCenterY < 0.01 || rightIrisCenterY < 0.01 || leftIrisCenterY > 0.022 || rightIrisCenterY > 0.022) center = false;\n    if (leftIrisCenterY < 0.01 || rightIrisCenterY < 0.01) gestures.push({ iris: i, gesture: 'looking down' });\n    if (leftIrisCenterY > 0.022 || rightIrisCenterY > 0.022) gestures.push({ iris: i, gesture: 'looking up' });\n\n    // still center;\n    if (center) gestures.push({ iris: i, gesture: 'looking center' });\n  }\n  return gestures;\n};\n\nexport const hand = (res: HandResult[]): GestureResult[] => {\n  if (!res) return [];\n  const gestures: Array<{ hand: number, gesture: HandGesture }> = [];\n  for (let i = 0; i < res.length; i++) {\n    const fingers: Array<{ name: string, position: Point }> = [];\n    if (res[i]['annotations']) {\n      for (const [finger, pos] of Object.entries(res[i]['annotations'])) {\n        if (finger !== 'palmBase' && Array.isArray(pos) && pos[0]) fingers.push({ name: finger.toLowerCase(), position: pos[0] }); // get tip of each finger\n      }\n    }\n    if (fingers && fingers.length > 0) {\n      const closest = fingers.reduce((best, a) => ((best.position[2] || 0) < (a.position[2] || 0) ? best : a));\n      gestures.push({ hand: i, gesture: `${closest.name} forward` as HandGesture });\n      const highest = fingers.reduce((best, a) => (best.position[1] < a.position[1] ? best : a));\n      gestures.push({ hand: i, gesture: `${highest.name} up` as HandGesture });\n    }\n    if (res[i]['keypoints']) {\n      const poses = fingerPose.match(res[i]['keypoints']);\n      for (const pose of poses) gestures.push({ hand: i, gesture: pose.name as HandGesture });\n    }\n  }\n  return gestures;\n};\n", "/**\n * Results interpolation for smoothening of video detection results inbetween detected frames\n */\n\nimport type { Result, FaceResult, BodyResult, HandResult, ObjectResult, GestureResult, PersonResult, Box, Point, BodyLandmark, BodyAnnotation } from '../result';\nimport type { Config } from '../config';\n\nimport * as moveNetCoords from '../body/movenetcoords';\nimport * as blazePoseCoords from '../body/blazeposecoords';\nimport * as efficientPoseCoords from '../body/efficientposecoords';\nimport { now } from './util';\nimport { env } from './env';\n\nconst bufferedResult: Result = { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0, error: null };\nlet interpolateTime = 0;\n\nexport function calc(newResult: Result, config: Config): Result {\n  const t0 = now();\n  if (!newResult) return { face: [], body: [], hand: [], gesture: [], object: [], persons: [], performance: {}, timestamp: 0, error: null };\n  // each record is only updated using deep clone when number of detected record changes, otherwise it will converge by itself\n  // otherwise bufferedResult is a shallow clone of result plus updated local calculated values\n  // thus mixing by-reference and by-value assignments to minimize memory operations\n\n  const elapsed = Date.now() - newResult.timestamp;\n  // curve fitted: buffer = 8 - ln(delay)\n  // interpolation formula: current = ((buffer - 1) * previous + live) / buffer\n  // - at  50ms delay buffer = ~4.1 => 28% towards live data\n  // - at 250ms delay buffer = ~2.5 => 40% towards live data\n  // - at 500ms delay buffer = ~1.8 => 55% towards live data\n  // - at 750ms delay buffer = ~1.4 => 71% towards live data\n  // - at  1sec delay buffer = 1 which means live data is used\n  const bufferedFactor = elapsed < 1000 ? 8 - Math.log(elapsed + 1) : 1;\n\n  if (newResult.canvas) bufferedResult.canvas = newResult.canvas;\n  if (newResult.error) bufferedResult.error = newResult.error;\n\n  // interpolate body results\n  if (!bufferedResult.body || (newResult.body.length !== bufferedResult.body.length)) {\n    bufferedResult.body = JSON.parse(JSON.stringify(newResult.body as BodyResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.body.length; i++) {\n      const box = newResult.body[i].box // update box\n        .map((newBoxCoord, j) => ((bufferedFactor - 1) * bufferedResult.body[i].box[j] + newBoxCoord) / bufferedFactor) as Box;\n      const boxRaw = newResult.body[i].boxRaw // update boxRaw\n        .map((newBoxCoord, j) => ((bufferedFactor - 1) * bufferedResult.body[i].boxRaw[j] + newBoxCoord) / bufferedFactor) as Box;\n      const keypoints = (newResult.body[i].keypoints // update keypoints\n        .map((newKpt, j) => ({\n          score: newKpt.score,\n          part: newKpt.part as BodyLandmark,\n          position: [\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].position[0] || 0) + (newKpt.position[0] || 0)) / bufferedFactor : newKpt.position[0],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].position[1] || 0) + (newKpt.position[1] || 0)) / bufferedFactor : newKpt.position[1],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].position[2] || 0) + (newKpt.position[2] || 0)) / bufferedFactor : newKpt.position[2],\n          ],\n          positionRaw: [\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].positionRaw[0] || 0) + (newKpt.positionRaw[0] || 0)) / bufferedFactor : newKpt.positionRaw[0],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].positionRaw[1] || 0) + (newKpt.positionRaw[1] || 0)) / bufferedFactor : newKpt.positionRaw[1],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].positionRaw[2] || 0) + (newKpt.positionRaw[2] || 0)) / bufferedFactor : newKpt.positionRaw[2],\n          ],\n          distance: [\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].distance?.[0] || 0) + (newKpt.distance?.[0] || 0)) / bufferedFactor : newKpt.distance?.[0],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].distance?.[1] || 0) + (newKpt.distance?.[1] || 0)) / bufferedFactor : newKpt.distance?.[1],\n            bufferedResult.body[i].keypoints[j] ? ((bufferedFactor - 1) * (bufferedResult.body[i].keypoints[j].distance?.[2] || 0) + (newKpt.distance?.[2] || 0)) / bufferedFactor : newKpt.distance?.[2],\n          ],\n        }))) as Array<{ score: number, part: BodyLandmark, position: [number, number, number?], positionRaw: [number, number, number?] }>;\n\n      const annotations: Record<BodyAnnotation, Point[][]> = {} as Record<BodyAnnotation, Point[][]>; // recreate annotations\n      let coords = { connected: {} };\n      if (config.body?.modelPath?.includes('efficientpose')) coords = efficientPoseCoords;\n      else if (config.body?.modelPath?.includes('blazepose')) coords = blazePoseCoords;\n      else if (config.body?.modelPath?.includes('movenet')) coords = moveNetCoords;\n      for (const [name, indexes] of Object.entries(coords.connected as Record<string, string[]>)) {\n        const pt: Array<Point[]> = [];\n        for (let j = 0; j < indexes.length - 1; j++) {\n          const pt0 = keypoints.find((kp) => kp.part === indexes[j]);\n          const pt1 = keypoints.find((kp) => kp.part === indexes[j + 1]);\n          // if (pt0 && pt1 && pt0.score > (config.body.minConfidence || 0) && pt1.score > (config.body.minConfidence || 0)) pt.push([pt0.position, pt1.position]);\n          if (pt0 && pt1) pt.push([pt0.position, pt1.position]);\n        }\n        annotations[name] = pt;\n      }\n      bufferedResult.body[i] = { ...newResult.body[i], box, boxRaw, keypoints, annotations: annotations as BodyResult['annotations'] }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate hand results\n  if (!bufferedResult.hand || (newResult.hand.length !== bufferedResult.hand.length)) {\n    bufferedResult.hand = JSON.parse(JSON.stringify(newResult.hand as HandResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.hand.length; i++) {\n      const box = (newResult.hand[i].box// update box\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.hand[i].box[j] + b) / bufferedFactor)) as Box;\n      const boxRaw = (newResult.hand[i].boxRaw // update boxRaw\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.hand[i].boxRaw[j] + b) / bufferedFactor)) as Box;\n      if (bufferedResult.hand[i].keypoints.length !== newResult.hand[i].keypoints.length) bufferedResult.hand[i].keypoints = newResult.hand[i].keypoints; // reset keypoints as previous frame did not have them\n      const keypoints = newResult.hand[i].keypoints && newResult.hand[i].keypoints.length > 0 ? newResult.hand[i].keypoints // update landmarks\n        .map((landmark, j) => landmark\n          .map((coord, k) => (((bufferedFactor - 1) * (bufferedResult.hand[i].keypoints[j][k] || 1) + (coord || 0)) / bufferedFactor)) as Point)\n        : [];\n      let annotations = {};\n      if (Object.keys(bufferedResult.hand[i].annotations).length !== Object.keys(newResult.hand[i].annotations).length) {\n        bufferedResult.hand[i].annotations = newResult.hand[i].annotations; // reset annotations as previous frame did not have them\n        annotations = bufferedResult.hand[i].annotations;\n      } else if (newResult.hand[i].annotations) {\n        for (const key of Object.keys(newResult.hand[i].annotations)) { // update annotations\n          annotations[key] = newResult.hand[i].annotations[key] && newResult.hand[i].annotations[key][0]\n            ? newResult.hand[i].annotations[key]\n              .map((val, j: number) => val\n                .map((coord: number, k: number) => ((bufferedFactor - 1) * bufferedResult.hand[i].annotations[key][j][k] + coord) / bufferedFactor))\n            : null;\n        }\n      }\n      bufferedResult.hand[i] = { ...newResult.hand[i], box, boxRaw, keypoints, annotations: annotations as HandResult['annotations'] }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate face results\n  if (!bufferedResult.face || (newResult.face.length !== bufferedResult.face.length)) {\n    bufferedResult.face = JSON.parse(JSON.stringify(newResult.face as FaceResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.face.length; i++) {\n      const box = (newResult.face[i].box // update box\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i].box[j] + b) / bufferedFactor)) as Box;\n      const boxRaw = (newResult.face[i].boxRaw // update boxRaw\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.face[i].boxRaw[j] + b) / bufferedFactor)) as Box;\n      if (newResult.face[i].rotation) {\n        const rotation: {\n          matrix: [number, number, number, number, number, number, number, number, number],\n          angle: { roll: number, yaw: number, pitch: number },\n          gaze: { bearing: number, strength: number }\n        } = { matrix: [0, 0, 0, 0, 0, 0, 0, 0, 0], angle: { roll: 0, yaw: 0, pitch: 0 }, gaze: { bearing: 0, strength: 0 } };\n        rotation.matrix = newResult.face[i].rotation?.matrix as [number, number, number, number, number, number, number, number, number];\n        rotation.angle = {\n          roll: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.roll || 0) + (newResult.face[i].rotation?.angle?.roll || 0)) / bufferedFactor,\n          yaw: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.yaw || 0) + (newResult.face[i].rotation?.angle?.yaw || 0)) / bufferedFactor,\n          pitch: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.angle?.pitch || 0) + (newResult.face[i].rotation?.angle?.pitch || 0)) / bufferedFactor,\n        };\n        rotation.gaze = {\n          // not fully correct due projection on circle, also causes wrap-around draw on jump from negative to positive\n          bearing: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.gaze?.bearing || 0) + (newResult.face[i].rotation?.gaze?.bearing || 0)) / bufferedFactor,\n          strength: ((bufferedFactor - 1) * (bufferedResult.face[i].rotation?.gaze?.strength || 0) + (newResult.face[i].rotation?.gaze?.strength || 0)) / bufferedFactor,\n        };\n        bufferedResult.face[i] = { ...newResult.face[i], rotation, box, boxRaw }; // shallow clone plus updated values\n      }\n      bufferedResult.face[i] = { ...newResult.face[i], box, boxRaw }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate object detection results\n  if (!bufferedResult.object || (newResult.object.length !== bufferedResult.object.length)) {\n    bufferedResult.object = JSON.parse(JSON.stringify(newResult.object as ObjectResult[])); // deep clone once\n  } else {\n    for (let i = 0; i < newResult.object.length; i++) {\n      const box = (newResult.object[i].box // update box\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.object[i].box[j] + b) / bufferedFactor)) as Box;\n      const boxRaw = (newResult.object[i].boxRaw // update boxRaw\n        .map((b, j) => ((bufferedFactor - 1) * bufferedResult.object[i].boxRaw[j] + b) / bufferedFactor)) as Box;\n      bufferedResult.object[i] = { ...newResult.object[i], box, boxRaw }; // shallow clone plus updated values\n    }\n  }\n\n  // interpolate person results\n  if (newResult.persons) {\n    const newPersons = newResult.persons; // trigger getter function\n    if (!bufferedResult.persons || (newPersons.length !== bufferedResult.persons.length)) {\n      bufferedResult.persons = JSON.parse(JSON.stringify(newPersons as PersonResult[]));\n    } else {\n      for (let i = 0; i < newPersons.length; i++) { // update person box, we don't update the rest as it's updated as reference anyhow\n        bufferedResult.persons[i].box = (newPersons[i].box\n          .map((box, j) => ((bufferedFactor - 1) * bufferedResult.persons[i].box[j] + box) / bufferedFactor)) as Box;\n      }\n    }\n  }\n\n  // just copy latest gestures without interpolation\n  if (newResult.gesture) bufferedResult.gesture = newResult.gesture as GestureResult[];\n\n  // append interpolation performance data\n  const t1 = now();\n  interpolateTime = env.perfadd ? interpolateTime + Math.round(t1 - t0) : Math.round(t1 - t0);\n  if (newResult.performance) bufferedResult.performance = { ...newResult.performance, interpolate: interpolateTime };\n\n  return bufferedResult;\n}\n", "/** Face descriptor type as number array */\nexport type Descriptor = Array<number>\nexport type MatchOptions = { order?: number, threshold?: number, multiplier?: number, min?: number, max?: number } | undefined;\n\n/** Calculates distance between two descriptors\n * @param options - calculation options\n * - order - algorithm to use\n *   Euclidean distance if `order` is 2 (default), Minkowski distance algorithm of nth order if `order` is higher than 2\n * - multiplier - by how much to enhance difference analysis in range of 1..100\n *   default is 20 which normalizes results to similarity above 0.5 can be considered a match\n */\nexport function distance(descriptor1: Descriptor, descriptor2: Descriptor, options: MatchOptions = { order: 2, multiplier: 25 }) {\n  // general minkowski distance, euclidean distance is limited case where order is 2\n  let sum = 0;\n  for (let i = 0; i < descriptor1.length; i++) {\n    const diff = (!options.order || options.order === 2) ? (descriptor1[i] - descriptor2[i]) : (Math.abs(descriptor1[i] - descriptor2[i]));\n    sum += (!options.order || options.order === 2) ? (diff * diff) : (diff ** options.order);\n  }\n  return (options.multiplier || 20) * sum;\n}\n\n// invert distance to similarity, normalize to given range and clamp\nconst normalizeDistance = (dist, order, min, max) => {\n  if (dist === 0) return 1; // short circuit for identical inputs\n  const root = order === 2 ? Math.sqrt(dist) : dist ** (1 / order); // take root of distance\n  const norm = (1 - (root / 100) - min) / (max - min); // normalize to range\n  const clamp = Math.max(Math.min(norm, 1), 0); // clamp to 0..1\n  return clamp;\n};\n\n/** Calculates normalized similarity between two face descriptors based on their `distance`\n * @param options - calculation options\n * - order - algorithm to use\n *   Euclidean distance if `order` is 2 (default), Minkowski distance algorithm of nth order if `order` is higher than 2\n * - multiplier - by how much to enhance difference analysis in range of 1..100\n *   default is 20 which normalizes results to similarity above 0.5 can be considered a match\n * - min - normalize similarity result to a given range\n * - max - normalzie similarity resutl to a given range\n *   default is 0.2...0.8\n * Returns similarity between two face descriptors normalized to 0..1 range where 0 is no similarity and 1 is perfect similarity\n */\nexport function similarity(descriptor1: Descriptor, descriptor2: Descriptor, options: MatchOptions = { order: 2, multiplier: 25, min: 0.2, max: 0.8 }) {\n  const dist = distance(descriptor1, descriptor2, options);\n  return normalizeDistance(dist, options.order || 2, options.min || 0, options.max || 1);\n}\n\n/** Matches given descriptor to a closest entry in array of descriptors\n * @param descriptor - face descriptor\n * @param descriptors - array of face descriptors to commpare given descriptor to\n * @param options - see `similarity` method for options description\n * Returns\n * - `index` index array index where best match was found or -1 if no matches\n * - `distance` calculated `distance` of given descriptor to the best match\n * - `similarity` calculated normalized `similarity` of given descriptor to the best match\n*/\nexport function match(descriptor: Descriptor, descriptors: Array<Descriptor>, options: MatchOptions = { order: 2, multiplier: 25, threshold: 0, min: 0.2, max: 0.8 }) {\n  if (!Array.isArray(descriptor) || !Array.isArray(descriptors) || descriptor.length < 64 || descriptors.length === 0 || descriptor.length !== descriptors[0].length) { // validate input\n    return { index: -1, distance: Number.POSITIVE_INFINITY, similarity: 0 };\n  }\n  let lowestDistance = Number.MAX_SAFE_INTEGER;\n  let index = -1;\n  for (let i = 0; i < descriptors.length; i++) {\n    const res = distance(descriptor, descriptors[i], options);\n    if (res < lowestDistance) {\n      lowestDistance = res;\n      index = i;\n    }\n    if (lowestDistance < (options.threshold || 0)) break;\n  }\n  const normalizedSimilarity = normalizeDistance(lowestDistance, options.order || 2, options.min || 0, options.max || 1);\n  return { index, distance: lowestDistance, similarity: normalizedSimilarity };\n}\n", "/**\n * Analyze detection Results and sort&combine them into per-person view\n */\n\nimport type { FaceResult, BodyResult, HandResult, GestureResult, PersonResult, Box } from '../result';\n\nexport function join(faces: Array<FaceResult>, bodies: Array<BodyResult>, hands: Array<HandResult>, gestures: Array<GestureResult>, shape: Array<number> | undefined): Array<PersonResult> {\n  let id = 0;\n  const persons: Array<PersonResult> = [];\n  for (const face of faces) { // person is defined primarily by face and then we append other objects as found\n    const person: PersonResult = { id: id++, face, body: null, hands: { left: null, right: null }, gestures: [], box: [0, 0, 0, 0] };\n    for (const body of bodies) {\n      if (face.box[0] > body.box[0] // x within body\n        && face.box[0] < body.box[0] + body.box[2]\n        && face.box[1] + face.box[3] > body.box[1] // y within body\n        && face.box[1] + face.box[3] < body.box[1] + body.box[3]) {\n        person.body = body;\n      }\n    }\n    if (person.body) { // only try to join hands if body is found\n      for (const hand of hands) {\n        if (hand.box[0] + hand.box[2] > person.body.box[0] // x within body for left hand\n          && hand.box[0] + hand.box[2] < person.body.box[0] + person.body.box[2]\n          && hand.box[1] + hand.box[3] > person.body.box[1] // x within body for left hand\n          && hand.box[1] + hand.box[3] < person.body.box[1] + person.body.box[3]) {\n          if (person.hands) person.hands.left = hand;\n        }\n        if (hand.box[0] < person.body.box[0] + person.body.box[2] // x within body for right hand\n          && hand.box[0] > person.body.box[0]\n          && hand.box[1] + hand.box[3] > person.body.box[1] // x within body for right hand\n          && hand.box[1] + hand.box[3] < person.body.box[1] + person.body.box[3]) {\n          if (person.hands) person.hands.right = hand;\n        }\n      }\n    }\n    for (const gesture of gestures) { // append all gestures according to ids\n      if (gesture['face'] !== undefined && gesture['face'] === face.id) person.gestures?.push(gesture);\n      else if (gesture['iris'] !== undefined && gesture['iris'] === face.id) person.gestures?.push(gesture);\n      else if (gesture['body'] !== undefined && gesture['body'] === person.body?.id) person.gestures?.push(gesture);\n      else if (gesture['hand'] !== undefined && gesture['hand'] === person.hands?.left?.id) person.gestures?.push(gesture);\n      else if (gesture['hand'] !== undefined && gesture['hand'] === person.hands?.right?.id) person.gestures?.push(gesture);\n    }\n\n    // create new overarching box from all boxes belonging to person\n    const x: number[] = [];\n    const y: number[] = [];\n    const extractXY = (box: Box | undefined) => { // extract all [x, y] coordinates from boxes [x, y, width, height]\n      if (box && box.length === 4) {\n        x.push(box[0], box[0] + box[2]);\n        y.push(box[1], box[1] + box[3]);\n      }\n    };\n    extractXY(person.face?.box);\n    extractXY(person.body?.box);\n    extractXY(person.hands?.left?.box);\n    extractXY(person.hands?.right?.box);\n    const minX = Math.min(...x);\n    const minY = Math.min(...y);\n    person.box = [minX, minY, Math.max(...x) - minX, Math.max(...y) - minY]; // create new overarching box\n\n    // shape is known so we calculate boxRaw as well\n    if (shape && shape[1] && shape[2]) person.boxRaw = [person.box[0] / shape[2], person.box[1] / shape[1], person.box[2] / shape[2], person.box[3] / shape[1]];\n\n    persons.push(person);\n  }\n  return persons;\n}\n", "/**\n * Embedded sample images used during warmup in dataURL format\n */\n\n// data:image/jpeg;base64,\nexport const face = `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`;\n\n// data:image/jpeg;base64,\nexport const body = `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\n2Q==`;\n", "/**\n * Warmup algorithm that uses embedded images to exercise loaded models for faster future inference\n */\n\nimport { log, now, mergeDeep } from './util/util';\nimport * as sample from './sample';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as image from './image/image';\nimport { env } from './util/env';\nimport type { Config } from './config';\nimport type { Result } from './result';\nimport type { Human, Models } from './human';\nimport type { Tensor } from './tfjs/types';\n\nasync function warmupBitmap(instance: Human): Promise<Result | undefined> {\n  const b64toBlob = (base64: string, type = 'application/octet-stream') => fetch(`data:${type};base64,${base64}`).then((res) => res.blob());\n  let blob;\n  let res;\n  switch (instance.config.warmup) {\n    case 'face': blob = await b64toBlob(sample.face); break;\n    case 'body':\n    case 'full': blob = await b64toBlob(sample.body); break;\n    default: blob = null;\n  }\n  if (blob) {\n    const bitmap = await createImageBitmap(blob);\n    res = await instance.detect(bitmap, instance.config);\n    bitmap.close();\n  }\n  return res;\n}\n\nasync function warmupCanvas(instance: Human): Promise<Result | undefined> {\n  return new Promise((resolve) => {\n    let src;\n    // let size = 0;\n    switch (instance.config.warmup) {\n      case 'face':\n        // size = 256;\n        src = 'data:image/jpeg;base64,' + sample.face;\n        break;\n      case 'full':\n      case 'body':\n        // size = 1200;\n        src = 'data:image/jpeg;base64,' + sample.body;\n        break;\n      default:\n        src = null;\n    }\n    // src = encodeURI('../assets/human-sample-upper.jpg');\n    let img: HTMLImageElement;\n    if (typeof Image !== 'undefined') img = new Image();\n    // @ts-ignore env.image is an external monkey-patch\n    else if (env.Image) img = new env.Image();\n    else return;\n    img.onload = async () => {\n      const canvas = image.canvas(img.naturalWidth, img.naturalHeight);\n      if (!canvas) {\n        log('Warmup: Canvas not found');\n        resolve(undefined);\n      } else {\n        const ctx = canvas.getContext('2d');\n        if (ctx) ctx.drawImage(img, 0, 0);\n        // const data = ctx?.getImageData(0, 0, canvas.height, canvas.width);\n        const tensor = await instance.image(canvas);\n        const res = await instance.detect(tensor.tensor as Tensor, instance.config);\n        resolve(res);\n      }\n    };\n    if (src) img.src = src;\n    else resolve(undefined);\n  });\n}\n\nasync function warmupNode(instance: Human): Promise<Result | undefined> {\n  const atob = (str: string) => Buffer.from(str, 'base64');\n  let img;\n  if (instance.config.warmup === 'face') img = atob(sample.face);\n  else img = atob(sample.body);\n  let res;\n  if ('node' in tf) {\n    // @ts-ignore tf.node may be undefined\n    const data = tf['node'].decodeJpeg(img);\n    const expanded = data.expandDims(0);\n    instance.tf.dispose(data);\n    // log('Input:', expanded);\n    res = await instance.detect(expanded, instance.config);\n    instance.tf.dispose(expanded);\n  } else {\n    if (instance.config.debug) log('Warmup tfjs-node not loaded');\n    /*\n    const input = await canvasJS.loadImage(img);\n    const canvas = canvasJS.createCanvas(input.width, input.height);\n    const ctx = canvas.getContext('2d');\n    ctx.drawImage(img, 0, 0, input.width, input.height);\n    res = await instance.detect(input, instance.config);\n    */\n  }\n  return res;\n}\n\nasync function runInference(instance: Human) {\n  let res: Result | undefined;\n  if (typeof createImageBitmap === 'function') res = await warmupBitmap(instance);\n  else if (typeof Image !== 'undefined' || env.Canvas !== undefined) res = await warmupCanvas(instance);\n  else res = await warmupNode(instance);\n  return res;\n}\n\n/** Runs pre-compile on all loaded models */\nexport async function runCompile(allModels: Models) {\n  if (!tf.env().flagRegistry['ENGINE_COMPILE_ONLY']) return; // tfjs does not support compile-only inference\n  const backendType = tf.getBackend();\n  const webGLBackend = tf.backend();\n  if ((backendType !== 'webgl' && backendType !== 'humangl') || (!webGLBackend || !webGLBackend.checkCompileCompletion)) {\n    // log('compile pass: skip');\n    return;\n  }\n  tf.env().set('ENGINE_COMPILE_ONLY', true);\n  const numTensorsStart = tf.engine().state.numTensors;\n  const compiledModels: string[] = [];\n  for (const [modelName, model] of Object.entries(allModels).filter(([key, val]) => (key !== null && val !== null))) {\n    const shape = (model.inputs && model.inputs[0] && model.inputs[0].shape) ? [...model.inputs[0].shape] : [1, 64, 64, 3];\n    const dtype = (model.inputs && model.inputs[0] && model.inputs[0].dtype) ? model.inputs[0].dtype : 'float32';\n    for (let dim = 0; dim < shape.length; dim++) {\n      if (shape[dim] === -1) shape[dim] = dim === 0 ? 1 : 64; // override batch number and any dynamic dimensions\n    }\n    const tensor = tf.zeros(shape, dtype);\n    // const res = await model.executeAsync(tensor); // fails with current tfjs\n    try {\n      const res = model.execute(tensor);\n      compiledModels.push(modelName);\n      if (Array.isArray(res)) res.forEach((t) => tf.dispose(t));\n      else tf.dispose(res);\n    } catch {\n      log('compile fail model:', modelName);\n    }\n    tf.dispose(tensor);\n  }\n  const kernels = await webGLBackend.checkCompileCompletionAsync();\n  webGLBackend.getUniformLocations();\n  log('compile pass models:', compiledModels);\n  log('compile pass kernels:', kernels.length);\n  tf.env().set('ENGINE_COMPILE_ONLY', false);\n  const numTensorsEnd = tf.engine().state.numTensors;\n  if ((numTensorsEnd - numTensorsStart) > 0) log('tensor leak:', numTensorsEnd - numTensorsStart);\n}\n\n/** Warmup method pre-initializes all configured models for faster inference\n * - can take significant time on startup\n * - only used in browser environments for `webgl` and `humangl` backends\n * @param userConfig?: Config\n*/\nexport async function warmup(instance: Human, userConfig?: Partial<Config>): Promise<Result | undefined> {\n  const t0 = now();\n  instance.state = 'warmup';\n  if (userConfig) instance.config = mergeDeep(instance.config, userConfig) as Config;\n  if (!instance.config.warmup || instance.config.warmup.length === 0 || instance.config.warmup === 'none') {\n    return { face: [], body: [], hand: [], gesture: [], object: [], performance: instance.performance, timestamp: now(), persons: [], error: null };\n  }\n  return new Promise(async (resolve) => {\n    await runCompile(instance.models);\n    const res = await runInference(instance);\n    const t1 = now();\n    if (instance.config.debug) log('warmup', instance.config.warmup, Math.round(t1 - t0), 'ms');\n    instance.emit('warmup');\n    resolve(res);\n  });\n}\n", "/**\n * Human main module\n * @default Human Library\n * @summary <https://github.com/vladmandic/human>\n * @author <https://github.com/vladmandic>\n * @copyright <https://github.com/vladmandic>\n * @license MIT\n */\n\n// module imports\nimport { log, now, mergeDeep, validate } from './util/util';\nimport { defaults } from './config';\nimport { env, Env } from './util/env';\nimport { setModelLoadOptions } from './tfjs/load';\nimport * as tf from '../dist/tfjs.esm.js';\nimport * as app from '../package.json';\nimport * as backend from './tfjs/backend';\nimport * as blazepose from './body/blazepose';\nimport * as centernet from './object/centernet';\nimport * as draw from './draw/draw';\nimport * as efficientpose from './body/efficientpose';\nimport * as face from './face/face';\nimport * as facemesh from './face/facemesh';\nimport * as faceres from './face/faceres';\nimport * as gesture from './gesture/gesture';\nimport * as handpose from './hand/handpose';\nimport * as handtrack from './hand/handtrack';\nimport * as humangl from './tfjs/humangl';\nimport * as image from './image/image';\nimport * as interpolate from './util/interpolate';\nimport * as match from './face/match';\nimport * as models from './models';\nimport * as movenet from './body/movenet';\nimport * as nanodet from './object/nanodet';\nimport * as persons from './util/persons';\nimport * as posenet from './body/posenet';\nimport * as segmentation from './segmentation/segmentation';\nimport * as warmups from './warmup';\n// type definitions\nimport type { Input, Tensor, DrawOptions, Config, Result, FaceResult, HandResult, BodyResult, ObjectResult, GestureResult, PersonResult, AnyCanvas, ModelStats } from './exports';\n// type exports\nexport * from './exports';\n\n/** **Human** library main class\n *\n * All methods and properties are available only as members of Human class\n *\n * - Configuration object definition: {@link Config}\n * - Results object definition: {@link Result}\n * - Possible inputs: {@link Input}\n *\n * @param userConfig - {@link Config}\n * @returns instance of {@link Human}\n */\nexport class Human {\n  /** Current version of Human library in *semver* format */\n  version: string;\n\n  /** Current configuration\n   * - Defaults: [config](https://github.com/vladmandic/human/blob/main/src/config.ts#L262)\n   */\n  config: Config;\n\n  /** Last known result of detect run\n   * - Can be accessed anytime after initial detection\n  */\n  result: Result;\n\n  /** Current state of Human library\n   * - Can be polled to determine operations that are currently executed\n   * - Progresses through: 'config', 'check', 'backend', 'load', 'run:<model>', 'idle'\n   */\n  state: string;\n\n  /** currenty processed image tensor and canvas */\n  process: { tensor: Tensor | null, canvas: AnyCanvas | null };\n\n  /** Instance of TensorFlow/JS used by Human\n   *  - Can be embedded or externally provided\n   * [TFJS API](https://js.tensorflow.org/api/latest/)\n   */\n  tf;\n\n  /** Object containing environment information used for diagnostics */\n  env: Env;\n\n  /** Draw helper classes that can draw detected objects on canvas using specified draw\n   * - canvas: draws input to canvas\n   * - options: are global settings for all draw operations, can be overriden for each draw method {@link DrawOptions}\n   * - face, body, hand, gesture, object, person: draws detected results as overlays on canvas\n   */\n  draw: { canvas: typeof draw.canvas, face: typeof draw.face, body: typeof draw.body, hand: typeof draw.hand, gesture: typeof draw.gesture, object: typeof draw.object, person: typeof draw.person, all: typeof draw.all, options: DrawOptions };\n\n  /** Currently loaded models\n   * @internal\n   * {@link Models}\n  */\n  models: models.Models;\n\n  /** Container for events dispatched by Human\n   * Possible events:\n   * - `create`: triggered when Human object is instantiated\n   * - `load`: triggered when models are loaded (explicitly or on-demand)\n   * - `image`: triggered when input image is processed\n   * - `result`: triggered when detection is complete\n   * - `warmup`: triggered when warmup is complete\n   * - `error`: triggered on some errors\n   */\n  events: EventTarget | undefined;\n  /** Reference face triangualtion array of 468 points, used for triangle references between points */\n  faceTriangulation: number[];\n  /** Refernce UV map of 468 values, used for 3D mapping of the face mesh */\n  faceUVMap: [number, number][];\n  /** Performance object that contains values for all recently performed operations */\n  performance: Record<string, number>; // perf members are dynamically defined as needed\n  #numTensors: number;\n  #analyzeMemoryLeaks: boolean;\n  #checkSanity: boolean;\n  /** WebGL debug info */\n  gl: Record<string, unknown>;\n  // definition end\n\n  /** Constructor for **Human** library that is futher used for all operations\n   * @param userConfig - user configuration object {@link Config}\n   */\n  constructor(userConfig?: Partial<Config>) {\n    this.env = env;\n    /*\n    defaults.wasmPath = tf.version['tfjs-core'].includes('-') // custom build or official build\n      ? 'https://vladmandic.github.io/tfjs/dist/'\n      : `https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${tf.version_core}/dist/`;\n    */\n    const tfVersion = (tf.version?.tfjs || tf.version_core).replace(/-(.*)/, '');\n    defaults.wasmPath = `https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${tfVersion}/dist/`;\n    defaults.modelBasePath = env.browser ? '../models/' : 'file://models/';\n    defaults.backend = env.browser ? 'humangl' : 'tensorflow';\n    this.version = app.version; // expose version property on instance of class\n    Object.defineProperty(this, 'version', { value: app.version }); // expose version property directly on class itself\n    this.config = JSON.parse(JSON.stringify(defaults));\n    Object.seal(this.config);\n    this.config.cacheModels = typeof indexedDB !== 'undefined';\n    if (userConfig) this.config = mergeDeep(this.config, userConfig);\n    setModelLoadOptions(this.config);\n    this.tf = tf;\n    this.state = 'idle';\n    this.#numTensors = 0;\n    this.#analyzeMemoryLeaks = false;\n    this.#checkSanity = false;\n    this.performance = {};\n    this.events = (typeof EventTarget !== 'undefined') ? new EventTarget() : undefined;\n    // object that contains all initialized models\n    this.models = new models.Models();\n    // reexport draw methods\n    this.draw = {\n      options: draw.options as DrawOptions,\n      canvas: (input: AnyCanvas | HTMLImageElement | HTMLVideoElement, output: AnyCanvas) => draw.canvas(input, output),\n      face: (output: AnyCanvas, result: FaceResult[], options?: Partial<DrawOptions>) => draw.face(output, result, options),\n      body: (output: AnyCanvas, result: BodyResult[], options?: Partial<DrawOptions>) => draw.body(output, result, options),\n      hand: (output: AnyCanvas, result: HandResult[], options?: Partial<DrawOptions>) => draw.hand(output, result, options),\n      gesture: (output: AnyCanvas, result: GestureResult[], options?: Partial<DrawOptions>) => draw.gesture(output, result, options),\n      object: (output: AnyCanvas, result: ObjectResult[], options?: Partial<DrawOptions>) => draw.object(output, result, options),\n      person: (output: AnyCanvas, result: PersonResult[], options?: Partial<DrawOptions>) => draw.person(output, result, options),\n      all: (output: AnyCanvas, result: Result, options?: Partial<DrawOptions>) => draw.all(output, result, options),\n    };\n    this.result = { face: [], body: [], hand: [], gesture: [], object: [], performance: {}, timestamp: 0, persons: [], error: null };\n    // export access to image processing\n    // @ts-ignore eslint-typescript cannot correctly infer type in anonymous function\n    this.process = { tensor: null, canvas: null };\n    // export raw access to underlying models\n    this.faceTriangulation = facemesh.triangulation;\n    this.faceUVMap = facemesh.uvmap;\n    // set gl info\n    this.gl = humangl.config;\n    // include platform info\n    this.emit('create');\n  }\n\n  /** internal function to measure tensor leaks */\n  analyze = (...msg: string[]) => {\n    if (!this.#analyzeMemoryLeaks) return;\n    const currentTensors = this.tf.engine().state.numTensors;\n    const previousTensors = this.#numTensors;\n    this.#numTensors = currentTensors;\n    const leaked = currentTensors - previousTensors;\n    if (leaked !== 0) log(...msg, leaked);\n  };\n\n  /** internal function for quick sanity check on inputs @hidden */\n  #sanity = (input: Input): null | string => {\n    if (!this.#checkSanity) return null;\n    if (!input) return 'input is not defined';\n    if (this.env.node && !(input instanceof tf.Tensor)) return 'input must be a tensor';\n    try {\n      this.tf.getBackend();\n    } catch {\n      return 'backend not loaded';\n    }\n    return null;\n  };\n\n  /** Reset configuration to default values */\n  reset(): void {\n    const currentBackend = this.config.backend; // save backend;\n    this.config = JSON.parse(JSON.stringify(defaults));\n    this.config.backend = currentBackend;\n  }\n\n  /** Validate current configuration schema */\n  validate(userConfig?: Partial<Config>) {\n    return validate(defaults, userConfig || this.config);\n  }\n\n  /** Exports face matching methods {@link match#similarity} */\n  public similarity = match.similarity;\n  /** Exports face matching methods {@link match#distance} */\n  public distance = match.distance;\n  /** Exports face matching methods {@link match#match} */\n  public match = match.match;\n\n  /** Utility wrapper for performance.now() */\n  now(): number {\n    return now();\n  }\n\n  /** Process input as return canvas and tensor\n   *\n   * @param input - any input {@link Input}\n   * @param getTensor - should image processing also return tensor or just canvas\n   * Returns object with `tensor` and `canvas`\n   */\n  image(input: Input, getTensor: boolean = true) {\n    return image.process(input, this.config, getTensor);\n  }\n\n  /** Segmentation method takes any input and returns processed canvas with body segmentation\n   *  - Segmentation is not triggered as part of detect process\n   * @param input - {@link Input}\n   * @param background - {@link Input}\n   *  - Optional parameter background is used to fill the background with specific input\n   *  Returns:\n   *  - `data` as raw data array with per-pixel segmentation values\n   *  - `canvas` as canvas which is input image filtered with segementation data and optionally merged with background image. canvas alpha values are set to segmentation values for easy merging\n   *  - `alpha` as grayscale canvas that represents segmentation alpha values\n   */\n  async segmentation(input: Input, background?: Input): Promise<{ data: number[] | Tensor, canvas: AnyCanvas | null, alpha: AnyCanvas | null }> {\n    return segmentation.process(input, background, this.config);\n  }\n\n  /** Enhance method performs additional enhacements to face image previously detected for futher processing\n   *\n   * @param input - Tensor as provided in human.result.face[n].tensor\n   * @returns Tensor\n   */\n  // eslint-disable-next-line class-methods-use-this\n  enhance(input: Tensor): Tensor | null {\n    return faceres.enhance(input);\n  }\n\n  /** Compare two input tensors for pixel simmilarity\n   * - use `human.image` to process any valid input and get a tensor that can be used for compare\n   * - when passing manually generated tensors:\n   *  - both input tensors must be in format [1, height, width, 3]\n   *  - if resolution of tensors does not match, second tensor will be resized to match resolution of the first tensor\n   * - return value is pixel similarity score normalized by input resolution and rgb channels\n  */\n  compare(firstImageTensor: Tensor, secondImageTensor: Tensor): Promise<number> {\n    return image.compare(this.config, firstImageTensor, secondImageTensor);\n  }\n\n  /** Explicit backend initialization\n   *  - Normally done implicitly during initial load phase\n   *  - Call to explictly register and initialize TFJS backend without any other operations\n   *  - Use when changing backend during runtime\n   */\n  async init(): Promise<void> {\n    await backend.check(this, true);\n    await this.tf.ready();\n  }\n\n  /** Load method preloads all configured models on-demand\n   * - Not explicitly required as any required model is load implicitly on it's first run\n   *\n   * @param userConfig - {@link Config}\n  */\n  async load(userConfig?: Partial<Config>): Promise<void> {\n    this.state = 'load';\n    const timeStamp = now();\n    const count = Object.values(this.models).filter((model) => model).length;\n    if (userConfig) this.config = mergeDeep(this.config, userConfig) as Config;\n\n    if (this.env.initial) { // print version info on first run and check for correct backend setup\n      if (this.config.debug) log(`version: ${this.version}`);\n      if (this.config.debug) log(`tfjs version: ${this.tf.version['tfjs-core']}`);\n      if (!await backend.check(this)) log('error: backend check failed');\n      await tf.ready();\n      if (this.env.browser) {\n        if (this.config.debug) log('configuration:', this.config);\n        if (this.config.debug) log('environment:', this.env);\n        if (this.config.debug) log('tf flags:', this.tf.ENV['flags']);\n      }\n    }\n\n    await models.load(this); // actually loads models\n    if (this.env.initial && this.config.debug) log('tf engine state:', this.tf.engine().state.numBytes, 'bytes', this.tf.engine().state.numTensors, 'tensors'); // print memory stats on first run\n    this.env.initial = false;\n\n    const loaded = Object.values(this.models).filter((model) => model).length;\n    if (loaded !== count) { // number of loaded models changed\n      await models.validate(this); // validate kernel ops used by model against current backend\n      this.emit('load');\n    }\n\n    const current = Math.trunc(now() - timeStamp);\n    if (current > (this.performance.loadModels as number || 0)) this.performance.loadModels = this.env.perfadd ? (this.performance.loadModels || 0) + current : current;\n  }\n\n  /** emit event */\n  emit = (event: string) => {\n    if (this.events && this.events.dispatchEvent) this.events?.dispatchEvent(new Event(event));\n  };\n\n  /** Runs interpolation using last known result and returns smoothened result\n   * Interpolation is based on time since last known result so can be called independently\n   *\n   * @param result - {@link Result} optional use specific result set to run interpolation on\n   * @returns result - {@link Result}\n   */\n  next(result: Result = this.result): Result {\n    return interpolate.calc(result, this.config) as Result;\n  }\n\n  /** get model loading/loaded stats */\n  getModelStats(): ModelStats { return models.getModelStats(this); }\n\n  /** Warmup method pre-initializes all configured models for faster inference\n   * - can take significant time on startup\n   * - only used for `webgl` and `humangl` backends\n   * @param userConfig - {@link Config}\n   * @returns result - {@link Result}\n  */\n  async warmup(userConfig?: Partial<Config>) {\n    const t0 = now();\n    const res = await warmups.warmup(this, userConfig);\n    const t1 = now();\n    this.performance.warmup = Math.trunc(t1 - t0);\n    return res;\n  }\n\n  /** Run detect with tensorflow profiling\n   * - result object will contain total exeuction time information for top-20 kernels\n   * - actual detection object can be accessed via `human.result`\n  */\n  async profile(input: Input, userConfig?: Partial<Config>): Promise<Array<{ kernel: string, time: number, perc: number }>> {\n    const profile = await this.tf.profile(() => this.detect(input, userConfig));\n    const kernels: Record<string, number> = {};\n    let total = 0;\n    for (const kernel of profile.kernels) { // sum kernel time values per kernel\n      if (kernels[kernel.name]) kernels[kernel.name] += kernel.kernelTimeMs;\n      else kernels[kernel.name] = kernel.kernelTimeMs;\n      total += kernel.kernelTimeMs;\n    }\n    const kernelArr: Array<{ kernel: string, time: number, perc: number }> = [];\n    Object.entries(kernels).forEach((key) => kernelArr.push({ kernel: key[0], time: key[1] as unknown as number, perc: 0 })); // convert to array\n    for (const kernel of kernelArr) {\n      kernel.perc = Math.round(1000 * kernel.time / total) / 1000;\n      kernel.time = Math.round(1000 * kernel.time) / 1000;\n    }\n    kernelArr.sort((a, b) => b.time - a.time); // sort\n    kernelArr.length = 20; // crop\n    // const res: Record<string, number> = {};\n    // for (const kernel of kernelArr) res[kernel.name] = kernel.ms; // create perf objects\n    return kernelArr;\n  }\n\n  /** Main detection method\n   * - Analyze configuration: {@link Config}\n   * - Pre-process input: {@link Input}\n   * - Run inference for all configured models\n   * - Process and return result: {@link Result}\n   *\n   * @param input - {@link Input}\n   * @param userConfig - {@link Config}\n   * @returns result - {@link Result}\n  */\n  async detect(input: Input, userConfig?: Partial<Config>): Promise<Result> {\n    // detection happens inside a promise\n    this.state = 'detect';\n    return new Promise(async (resolve) => {\n      this.state = 'config';\n      let timeStamp;\n\n      // update configuration\n      this.config = mergeDeep(this.config, userConfig) as Config;\n\n      // sanity checks\n      this.state = 'check';\n      const error = this.#sanity(input);\n      if (error) {\n        log(error, input);\n        this.emit('error');\n        resolve({ face: [], body: [], hand: [], gesture: [], object: [], performance: this.performance, timestamp: now(), persons: [], error });\n      }\n\n      const timeStart = now();\n\n      // configure backend if needed\n      await backend.check(this);\n\n      // load models if enabled\n      await this.load();\n\n      timeStamp = now();\n      this.state = 'image';\n      const img = await image.process(input, this.config) as { canvas: AnyCanvas, tensor: Tensor };\n      this.process = img;\n      this.performance.inputProcess = this.env.perfadd ? (this.performance.inputProcess || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      this.analyze('Get Image:');\n\n      if (!img.tensor) {\n        if (this.config.debug) log('could not convert input to tensor');\n        this.emit('error');\n        resolve({ face: [], body: [], hand: [], gesture: [], object: [], performance: this.performance, timestamp: now(), persons: [], error: 'could not convert input to tensor' });\n        return;\n      }\n      this.emit('image');\n\n      timeStamp = now();\n      this.config.skipAllowed = await image.skip(this.config, img.tensor);\n      if (!this.performance.totalFrames) this.performance.totalFrames = 0;\n      if (!this.performance.cachedFrames) this.performance.cachedFrames = 0;\n      (this.performance.totalFrames as number)++;\n      if (this.config.skipAllowed) this.performance.cachedFrames++;\n      this.performance.cacheCheck = this.env.perfadd ? (this.performance.cacheCheck || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      this.analyze('Check Changed:');\n\n      // prepare where to store model results\n      // keep them with weak typing as it can be promise or not\n      let faceRes: FaceResult[] | Promise<FaceResult[]> | never[] = [];\n      let bodyRes: BodyResult[] | Promise<BodyResult[]> | never[] = [];\n      let handRes: HandResult[] | Promise<HandResult[]> | never[] = [];\n      let objectRes: ObjectResult[] | Promise<ObjectResult[]> | never[] = [];\n\n      // run face detection followed by all models that rely on face bounding box: face mesh, age, gender, emotion\n      this.state = 'detect:face';\n      if (this.config.async) {\n        faceRes = this.config.face.enabled ? face.detectFace(this, img.tensor) : [];\n        if (this.performance.face) delete this.performance.face;\n      } else {\n        timeStamp = now();\n        faceRes = this.config.face.enabled ? await face.detectFace(this, img.tensor) : [];\n        this.performance.face = this.env.perfadd ? (this.performance.face || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n\n      if (this.config.async && (this.config.body.maxDetected === -1 || this.config.hand.maxDetected === -1)) faceRes = await faceRes; // need face result for auto-detect number of hands or bodies\n\n      // run body: can be posenet, blazepose, efficientpose, movenet\n      this.analyze('Start Body:');\n      this.state = 'detect:body';\n      const bodyConfig = this.config.body.maxDetected === -1 ? mergeDeep(this.config, { body: { maxDetected: this.config.face.enabled ? 1 * (faceRes as FaceResult[]).length : 1 } }) : this.config; // autodetect number of bodies\n      if (this.config.async) {\n        if (this.config.body.modelPath?.includes('posenet')) bodyRes = this.config.body.enabled ? posenet.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('blazepose')) bodyRes = this.config.body.enabled ? blazepose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('efficientpose')) bodyRes = this.config.body.enabled ? efficientpose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('movenet')) bodyRes = this.config.body.enabled ? movenet.predict(img.tensor, bodyConfig) : [];\n        if (this.performance.body) delete this.performance.body;\n      } else {\n        timeStamp = now();\n        if (this.config.body.modelPath?.includes('posenet')) bodyRes = this.config.body.enabled ? await posenet.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('blazepose')) bodyRes = this.config.body.enabled ? await blazepose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('efficientpose')) bodyRes = this.config.body.enabled ? await efficientpose.predict(img.tensor, bodyConfig) : [];\n        else if (this.config.body.modelPath?.includes('movenet')) bodyRes = this.config.body.enabled ? await movenet.predict(img.tensor, bodyConfig) : [];\n        this.performance.body = this.env.perfadd ? (this.performance.body || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n      this.analyze('End Body:');\n\n      // run handpose\n      this.analyze('Start Hand:');\n      this.state = 'detect:hand';\n      const handConfig = this.config.hand.maxDetected === -1 ? mergeDeep(this.config, { hand: { maxDetected: this.config.face.enabled ? 2 * (faceRes as FaceResult[]).length : 1 } }) : this.config; // autodetect number of hands\n      if (this.config.async) {\n        if (this.config.hand.detector?.modelPath?.includes('handdetect')) handRes = this.config.hand.enabled ? handpose.predict(img.tensor, handConfig) : [];\n        else if (this.config.hand.detector?.modelPath?.includes('handtrack')) handRes = this.config.hand.enabled ? handtrack.predict(img.tensor, handConfig) : [];\n        if (this.performance.hand) delete this.performance.hand;\n      } else {\n        timeStamp = now();\n        if (this.config.hand.detector?.modelPath?.includes('handdetect')) handRes = this.config.hand.enabled ? await handpose.predict(img.tensor, handConfig) : [];\n        else if (this.config.hand.detector?.modelPath?.includes('handtrack')) handRes = this.config.hand.enabled ? await handtrack.predict(img.tensor, handConfig) : [];\n        this.performance.hand = this.env.perfadd ? (this.performance.hand || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n      this.analyze('End Hand:');\n\n      // run object detection\n      this.analyze('Start Object:');\n      this.state = 'detect:object';\n      if (this.config.async) {\n        if (this.config.object.modelPath?.includes('nanodet')) objectRes = this.config.object.enabled ? nanodet.predict(img.tensor, this.config) : [];\n        else if (this.config.object.modelPath?.includes('centernet')) objectRes = this.config.object.enabled ? centernet.predict(img.tensor, this.config) : [];\n        if (this.performance.object) delete this.performance.object;\n      } else {\n        timeStamp = now();\n        if (this.config.object.modelPath?.includes('nanodet')) objectRes = this.config.object.enabled ? await nanodet.predict(img.tensor, this.config) : [];\n        else if (this.config.object.modelPath?.includes('centernet')) objectRes = this.config.object.enabled ? await centernet.predict(img.tensor, this.config) : [];\n        this.performance.object = this.env.perfadd ? (this.performance.object || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n      }\n      this.analyze('End Object:');\n\n      // if async wait for results\n      this.state = 'detect:await';\n      if (this.config.async) [faceRes, bodyRes, handRes, objectRes] = await Promise.all([faceRes, bodyRes, handRes, objectRes]);\n\n      // run gesture analysis last\n      this.state = 'detect:gesture';\n      let gestureRes: GestureResult[] = [];\n      if (this.config.gesture.enabled) {\n        timeStamp = now();\n        gestureRes = [...gesture.face(faceRes as FaceResult[]), ...gesture.body(bodyRes as BodyResult[]), ...gesture.hand(handRes as HandResult[]), ...gesture.iris(faceRes as FaceResult[])];\n        if (!this.config.async) this.performance.gesture = this.env.perfadd ? (this.performance.gesture || 0) + Math.trunc(now() - timeStamp) : Math.trunc(now() - timeStamp);\n        else if (this.performance.gesture) delete this.performance.gesture;\n      }\n\n      this.performance.total = this.env.perfadd ? (this.performance.total || 0) + Math.trunc(now() - timeStart) : Math.trunc(now() - timeStart);\n      const shape = this.process?.tensor?.shape || [];\n      this.result = {\n        face: faceRes as FaceResult[],\n        body: bodyRes as BodyResult[],\n        hand: handRes as HandResult[],\n        gesture: gestureRes,\n        object: objectRes as ObjectResult[],\n        performance: this.performance,\n        canvas: this.process.canvas,\n        timestamp: Date.now(),\n        error: null,\n        get persons() { return persons.join(faceRes as FaceResult[], bodyRes as BodyResult[], handRes as HandResult[], gestureRes, shape); },\n      };\n\n      // finally dispose input tensor\n      tf.dispose(img.tensor);\n\n      // log('Result:', result);\n      this.emit('detect');\n      this.state = 'idle';\n      resolve(this.result);\n    });\n  }\n}\n\n/** Class Human as default export */\n/* eslint no-restricted-exports: [\"off\", { \"restrictedNamedExports\": [\"default\"] }] */\nexport { Human as default, match, draw, models };\n"],
+  "mappings": ";;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;AAOO,SAAS,OAAO,KAAW;AAChC,QAAM,KAAK,IAAI,KAAK;AACpB,QAAM,KAAK,GAAG,GAAG,SAAS,EAAE,SAAS,EAAE,SAAS,GAAG,GAAG,KAAK,GAAG,WAAW,EAAE,SAAS,EAAE,SAAS,GAAG,GAAG,KAAK,GAAG,WAAW,EAAE,SAAS,EAAE,SAAS,GAAG,GAAG,KAAK,GAAG,gBAAgB,EAAE,SAAS,EAAE,SAAS,GAAG,GAAG;AAExM,MAAI;AAAK,YAAQ,IAAI,IAAI,UAAU,GAAG,GAAG;AAC3C;AAGO,SAAS,KAAK,QAAgB,MAAsB;AACzD,QAAM,YAAY,OAAO,SAAS,GAAG,IAAI,KAAK;AAC9C,QAAM,WAAW,KAAK,WAAW,GAAG,KAAK,KAAK,WAAW,GAAG,KAAK,KAAK,WAAW,OAAO,KAAK,KAAK,WAAW,QAAQ,KAAK,KAAK,WAAW,OAAO;AACjJ,QAAM,OAAO,WAAW,GAAG,SAAS,GAAG,SAAS,YAAY;AAC5D,MAAI,CAAC,KAAK,kBAAkB,EAAE,SAAS,OAAO;AAAG,UAAM,IAAI,MAAM,yCAAyC,MAAM;AAChH,SAAO;AACT;AAGO,IAAM,MAAM,MAAM;AACvB,MAAI,OAAO,gBAAgB;AAAa,WAAO,YAAY,IAAI;AAC/D,SAAO,UAAU,OAAO,QAAQ,OAAO,OAAO,CAAC,IAAI,MAAO,KAAM,SAAS,CAAC;AAC5E;AAGO,SAAS,SAAS,UAA2BA,SAAyB,SAAS,UAAU,OAAoE,CAAC,GAAG;AACtK,aAAW,OAAO,OAAO,KAAKA,OAAM,GAAG;AACrC,QAAI,OAAOA,QAAO,SAAS,UAAU;AACnC,eAAS,SAAS,MAAMA,QAAO,MAAM,KAAK,IAAI;AAAA,IAChD,OAAO;AACL,YAAM,UAAU,YAAa,OAAO,SAAS,SAAS;AACtD,UAAI,CAAC;AAAS,aAAK,KAAK,EAAE,QAAQ,oBAAoB,OAAO,GAAG,UAAU,SAASA,QAAO,OAAO,CAAC;AAClG,YAAM,OAAO,YAAY,OAAO,SAAS,SAAS,OAAOA,QAAO;AAChE,UAAI,WAAW,CAAC;AAAM,aAAK,KAAK,EAAE,QAAQ,0BAA0B,OAAO,GAAG,UAAU,SAASA,QAAO,QAAQ,UAAU,OAAO,SAAS,KAAK,CAAC;AAAA,IAClJ;AAAA,EAEF;AACA,MAAIA,QAAO,SAAS,WAAW,YAAY,KAAK,SAAS;AAAG,QAAI,yBAAyB,IAAI;AAC7F,SAAO;AACT;AAGO,SAAS,aAAa,SAAS;AACpC,QAAM,WAAW,CAAC,QAAQ,OAAO,OAAO,QAAQ;AAChD,SAAO,QAAQ,OAAO,CAAC,MAAM,QAAQ;AACnC,WAAO,KAAK,OAAO,CAAC,CAAC,EAAE,QAAQ,CAAC,QAAQ;AACtC,YAAM,OAAO,KAAK;AAClB,YAAM,OAAO,IAAI;AACjB,UAAI,MAAM,QAAQ,IAAI,KAAK,MAAM,QAAQ,IAAI;AAAG,aAAK,OAAO,KAAK,OAAO,GAAG,IAAI;AAAA,eACtE,SAAS,IAAI,KAAK,SAAS,IAAI;AAAG,aAAK,OAAO,UAAU,MAAM,IAAI;AAAA;AACtE,aAAK,OAAO;AAAA,IACnB,CAAC;AACD,WAAO;AAAA,EACT,GAAG,CAAC,CAAC;AACP;;;AC6PA,IAAM,SAAiB;AAAA,EACrB,SAAS;AAAA,EACT,eAAe;AAAA,EACf,aAAa;AAAA,EACb,UAAU;AAAA,EACV,mBAAmB;AAAA,EACnB,OAAO;AAAA,EACP,OAAO;AAAA,EACP,QAAQ;AAAA,EACR,kBAAkB;AAAA,EAClB,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,QAAQ;AAAA,IACN,SAAS;AAAA,IACT,cAAc;AAAA,IACd,OAAO;AAAA,IACP,QAAQ;AAAA,IACR,MAAM;AAAA,IACN,QAAQ;AAAA,IACR,YAAY;AAAA,IACZ,UAAU;AAAA,IACV,WAAW;AAAA,IACX,MAAM;AAAA,IACN,YAAY;AAAA,IACZ,KAAK;AAAA,IACL,UAAU;AAAA,IACV,OAAO;AAAA,IACP,SAAS;AAAA,IACT,YAAY;AAAA,IACZ,aAAa;AAAA,IACb,UAAU;AAAA,IACV,UAAU;AAAA,EACZ;AAAA,EACA,SAAS;AAAA,IACP,SAAS;AAAA,EACX;AAAA,EACA,MAAM;AAAA,IACJ,SAAS;AAAA,IACT,UAAU;AAAA,MACR,WAAW;AAAA,MACX,UAAU;AAAA,MACV,aAAa;AAAA,MACb,YAAY;AAAA,MACZ,UAAU;AAAA,MACV,eAAe;AAAA,MACf,cAAc;AAAA,MACd,MAAM;AAAA,MACN,QAAQ;AAAA,IACV;AAAA,IACA,MAAM;AAAA,MACJ,SAAS;AAAA,MACT,WAAW;AAAA,MACX,aAAa;AAAA,IACf;AAAA,IACA,WAAW;AAAA,MACT,SAAS;AAAA,MACT,WAAW;AAAA,IACb;AAAA,IACA,MAAM;AAAA,MACJ,SAAS;AAAA,MACT,WAAW;AAAA,IACb;AAAA,IACA,SAAS;AAAA,MACP,SAAS;AAAA,MACT,eAAe;AAAA,MACf,YAAY;AAAA,MACZ,UAAU;AAAA,MACV,WAAW;AAAA,IACb;AAAA,IACA,aAAa;AAAA,MACX,SAAS;AAAA,MACT,WAAW;AAAA,MACX,YAAY;AAAA,MACZ,UAAU;AAAA,MACV,eAAe;AAAA,IACjB;AAAA,IACA,WAAW;AAAA,MACT,SAAS;AAAA,MACT,YAAY;AAAA,MACZ,UAAU;AAAA,MACV,WAAW;AAAA,IACb;AAAA,IACA,UAAU;AAAA,MACR,SAAS;AAAA,MACT,YAAY;AAAA,MACZ,UAAU;AAAA,MACV,WAAW;AAAA,IACb;AAAA,EACF;AAAA,EACA,MAAM;AAAA,IACJ,SAAS;AAAA,IACT,WAAW;AAAA,IACX,aAAa;AAAA,IACb,eAAe;AAAA,IACf,YAAY;AAAA,IACZ,UAAU;AAAA,EACZ;AAAA,EACA,MAAM;AAAA,IACJ,SAAS;AAAA,IACT,UAAU;AAAA,IACV,YAAY;AAAA,IACZ,UAAU;AAAA,IACV,eAAe;AAAA,IACf,cAAc;AAAA,IACd,aAAa;AAAA,IACb,WAAW;AAAA,IACX,UAAU;AAAA,MACR,WAAW;AAAA,IACb;AAAA,IACA,UAAU;AAAA,MACR,WAAW;AAAA,IACb;AAAA,EACF;AAAA,EACA,QAAQ;AAAA,IACN,SAAS;AAAA,IACT,WAAW;AAAA,IACX,eAAe;AAAA,IACf,cAAc;AAAA,IACd,aAAa;AAAA,IACb,YAAY;AAAA,IACZ,UAAU;AAAA,EACZ;AAAA,EACA,cAAc;AAAA,IACZ,SAAS;AAAA,IACT,WAAW;AAAA,IACX,MAAM;AAAA,EACR;AACF;;;ACvbA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,aAAAC;AAAA,EAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAMA,IAAI,WAAW,OAAO;AACtB,IAAIC,aAAY,OAAO;AACvB,IAAI,mBAAmB,OAAO;AAC9B,IAAI,oBAAoB,OAAO;AAC/B,IAAI,eAAe,OAAO;AAC1B,IAAI,eAAe,OAAO,UAAU;AACpC,IAAI,aAAa,CAAC,IAAI,SAAS,SAAS,YAAY;AAClD,SAAO,SAAS,GAAG,GAAG,kBAAkB,EAAE,EAAE,MAAM,OAAO,EAAE,SAAS,CAAC,EAAE,GAAG,SAAS,IAAI,GAAG,KAAK;AACjG;AACA,IAAIC,YAAW,CAAC,QAAQC,UAAS;AAC/B,WAAS,QAAQA;AACf,IAAAF,WAAU,QAAQ,MAAM,EAAE,KAAKE,MAAK,OAAO,YAAY,KAAK,CAAC;AACjE;AACA,IAAI,cAAc,CAAC,IAAI,MAAM,QAAQ,SAAS;AAC5C,MAAI,QAAQ,OAAO,SAAS,YAAY,OAAO,SAAS,YAAY;AAClE,aAAS,OAAO,kBAAkB,IAAI;AACpC,UAAI,CAAC,aAAa,KAAK,IAAI,GAAG,KAAK,QAAQ;AACzC,QAAAF,WAAU,IAAI,KAAK,EAAE,KAAK,MAAM,KAAK,MAAM,YAAY,EAAE,OAAO,iBAAiB,MAAM,GAAG,MAAM,KAAK,WAAW,CAAC;AAAA,EACvH;AACA,SAAO;AACT;AACA,IAAI,UAAU,CAAC,MAAM,YAAY,YAAY,SAAS,QAAQ,OAAO,SAAS,aAAa,IAAI,CAAC,IAAI,CAAC,GAAG;AAAA,EACtG,cAAc,CAAC,QAAQ,CAAC,KAAK,aAAaA,WAAU,QAAQ,WAAW,EAAE,OAAO,MAAM,YAAY,KAAK,CAAC,IAAI;AAAA,EAC5G;AACF;AAGA,IAAI,eAAe,WAAW;AAAA,EAC5B,8DAA8D,SAAS,QAAQ;AAC7E,WAAO,UAAU;AACjB,QAAI,OAAO;AACX,QAAI;AACF,aAAO,IAAI,YAAY,SAAS,IAAI,YAAY,OAAO,IAAI,WAAW;AAAA,QACpE;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,MACF,CAAC,CAAC,GAAG,CAAC,CAAC,EAAE;AAAA,IACX,SAAS,IAAP;AAAA,IACF;AACA,aAAS,MAAM,KAAK,MAAM,UAAU;AAClC,WAAK,MAAM,MAAM;AACjB,WAAK,OAAO,OAAO;AACnB,WAAK,WAAW,CAAC,CAAC;AAAA,IACpB;AACA,UAAM,UAAU;AAChB,WAAO,eAAe,MAAM,WAAW,cAAc,EAAE,OAAO,KAAK,CAAC;AACpE,aAAS,OAAO,KAAK;AACnB,cAAQ,OAAO,IAAI,mBAAmB;AAAA,IACxC;AACA,UAAM,SAAS;AACf,QAAI,YAAY,CAAC;AACjB,QAAI,aAAa,CAAC;AAClB,aAAS,QAAQ,OAAO,UAAU;AAChC,UAAI,KAAK,WAAWG;AACpB,UAAI,UAAU;AACZ,mBAAW;AACX,YAAIA,SAAQ,KAAK,SAAS,QAAQ,KAAK;AACrC,sBAAY,WAAW;AACvB,cAAI;AACF,mBAAO;AAAA,QACX;AACA,cAAM,SAAS,QAAQ,QAAQ,KAAK,IAAI,KAAK,GAAG,IAAI;AACpD,YAAIA;AACF,qBAAW,SAAS;AACtB,eAAO;AAAA,MACT,OAAO;AACL,iBAAS;AACT,YAAIA,SAAQ,QAAQ,SAAS,QAAQ,KAAK;AACxC,sBAAY,UAAU;AACtB,cAAI;AACF,mBAAO;AAAA,QACX;AACA,cAAM,SAAS,OAAO,QAAQ,IAAI,KAAK,GAAG,KAAK;AAC/C,YAAIA;AACF,oBAAU,SAAS;AACrB,eAAO;AAAA,MACT;AAAA,IACF;AACA,UAAM,UAAU;AAChB,aAAS,WAAW,OAAO,UAAU;AACnC,UAAI,MAAM,KAAK;AACb,eAAO,WAAW,QAAQ;AAC5B,UAAI,UAAU;AACZ,YAAI,QAAQ;AACV,iBAAO;AACT,YAAI,SAAS;AACX,iBAAO;AAAA,MACX,OAAO;AACL,YAAI,SAAS,CAAC;AACZ,iBAAO;AACT,YAAI,QAAQ,KAAK;AACf,iBAAO;AAAA,MACX;AACA,UAAI,QAAQ;AACV,eAAO,WAAW,CAAC,OAAO,QAAQ,EAAE,IAAI;AAC1C,aAAO,SAAS,QAAQ,iBAAiB,GAAG,QAAQ,iBAAiB,GAAG,QAAQ;AAAA,IAClF;AACA,UAAM,aAAa;AACnB,aAAS,SAAS,SAAS,UAAU,UAAU;AAC7C,aAAO,IAAI,MAAM,SAAS,UAAU,QAAQ;AAAA,IAC9C;AACA,UAAM,WAAW;AACjB,QAAI,UAAU,KAAK;AACnB,aAAS,WAAW,KAAK,UAAU,OAAO;AACxC,UAAI,IAAI,WAAW;AACjB,cAAM,MAAM,cAAc;AAC5B,UAAI,QAAQ,SAAS,QAAQ,cAAc,QAAQ,eAAe,QAAQ;AACxE,eAAO;AACT,UAAI,OAAO,aAAa,UAAU;AAChC,gBAAQ,UAAU,WAAW;AAAA,MAC/B,OAAO;AACL,mBAAW,CAAC,CAAC;AAAA,MACf;AACA,cAAQ,SAAS;AACjB,UAAI,QAAQ,KAAK,KAAK;AACpB,cAAM,WAAW,OAAO;AAC1B,UAAI;AACJ,WAAK,KAAK,IAAI,QAAQ,GAAG,KAAK;AAC5B,cAAM,MAAM,iBAAiB;AAAA,eACtB,OAAO,GAAG;AACjB,eAAO,WAAW,IAAI,UAAU,CAAC,GAAG,UAAU,KAAK,EAAE,IAAI;AAAA,MAC3D;AACA,UAAI,eAAe,WAAW,QAAQ,OAAO,CAAC,CAAC;AAC/C,UAAI,SAAS;AACb,eAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,MAAM,GAAG;AACzC,YAAIC,QAAO,KAAK,IAAI,GAAG,IAAI,SAAS,EAAE,GAAG,QAAQ,SAAS,IAAI,UAAU,IAAI,KAAKA,KAAI,GAAG,KAAK;AAC7F,YAAIA,QAAO,GAAG;AACZ,cAAI,QAAQ,WAAW,QAAQ,OAAOA,KAAI,CAAC;AAC3C,mBAAS,OAAO,IAAI,KAAK,EAAE,IAAI,WAAW,KAAK,CAAC;AAAA,QAClD,OAAO;AACL,mBAAS,OAAO,IAAI,YAAY;AAChC,mBAAS,OAAO,IAAI,WAAW,KAAK,CAAC;AAAA,QACvC;AAAA,MACF;AACA,aAAO,WAAW;AAClB,aAAO;AAAA,IACT;AACA,UAAM,aAAa;AACnB,aAAS,UAAU,KAAK,UAAU;AAChC,UAAI,OAAO,QAAQ;AACjB,eAAO,WAAW,KAAK,QAAQ;AACjC,UAAI,OAAO,QAAQ;AACjB,eAAO,WAAW,KAAK,QAAQ;AACjC,aAAO,SAAS,IAAI,KAAK,IAAI,MAAM,OAAO,aAAa,YAAY,WAAW,IAAI,QAAQ;AAAA,IAC5F;AACA,UAAM,YAAY;AAClB,QAAI,iBAAiB,KAAK;AAC1B,QAAI,iBAAiB,KAAK;AAC1B,QAAI,iBAAiB,iBAAiB;AACtC,QAAI,iBAAiB,iBAAiB;AACtC,QAAI,iBAAiB,iBAAiB;AACtC,QAAI,aAAa,QAAQ,cAAc;AACvC,QAAI,OAAO,QAAQ,CAAC;AACpB,UAAM,OAAO;AACb,QAAI,QAAQ,QAAQ,GAAG,IAAI;AAC3B,UAAM,QAAQ;AACd,QAAI,MAAM,QAAQ,CAAC;AACnB,UAAM,MAAM;AACZ,QAAI,OAAO,QAAQ,GAAG,IAAI;AAC1B,UAAM,OAAO;AACb,QAAI,UAAU,QAAQ,EAAE;AACxB,UAAM,UAAU;AAChB,QAAI,YAAY,SAAS,aAAa,GAAG,aAAa,GAAG,KAAK;AAC9D,UAAM,YAAY;AAClB,QAAI,qBAAqB,SAAS,aAAa,GAAG,aAAa,GAAG,IAAI;AACtE,UAAM,qBAAqB;AAC3B,QAAI,YAAY,SAAS,GAAG,aAAa,GAAG,KAAK;AACjD,UAAM,YAAY;AAClB,QAAI,gBAAgB,MAAM;AAC1B,kBAAc,QAAQ,SAAS,QAAQ;AACrC,aAAO,KAAK,WAAW,KAAK,QAAQ,IAAI,KAAK;AAAA,IAC/C;AACA,kBAAc,WAAW,SAAS,WAAW;AAC3C,UAAI,KAAK;AACP,gBAAQ,KAAK,SAAS,KAAK,kBAAkB,KAAK,QAAQ;AAC5D,aAAO,KAAK,OAAO,kBAAkB,KAAK,QAAQ;AAAA,IACpD;AACA,kBAAc,WAAW,SAAS,SAAS,OAAO;AAChD,cAAQ,SAAS;AACjB,UAAI,QAAQ,KAAK,KAAK;AACpB,cAAM,WAAW,OAAO;AAC1B,UAAI,KAAK,OAAO;AACd,eAAO;AACT,UAAI,KAAK,WAAW,GAAG;AACrB,YAAI,KAAK,GAAG,SAAS,GAAG;AACtB,cAAI,YAAY,WAAW,KAAK,GAAG,OAAO,KAAK,IAAI,SAAS,GAAG,OAAO,KAAK,IAAI,SAAS,EAAE,IAAI,IAAI;AAClG,iBAAO,KAAK,SAAS,KAAK,IAAI,KAAK,MAAM,EAAE,SAAS,KAAK;AAAA,QAC3D;AACE,iBAAO,MAAM,KAAK,IAAI,EAAE,SAAS,KAAK;AAAA,MAC1C;AACA,UAAI,eAAe,WAAW,QAAQ,OAAO,CAAC,GAAG,KAAK,QAAQ,GAAG,MAAM;AACvE,UAAI,SAAS;AACb,aAAO,MAAM;AACX,YAAI,SAAS,IAAI,IAAI,YAAY,GAAG,SAAS,IAAI,IAAI,OAAO,IAAI,YAAY,CAAC,EAAE,MAAM,MAAM,GAAG,SAAS,OAAO,SAAS,KAAK;AAC5H,cAAM;AACN,YAAI,IAAI,OAAO;AACb,iBAAO,SAAS;AAAA,aACb;AACH,iBAAO,OAAO,SAAS;AACrB,qBAAS,MAAM;AACjB,mBAAS,KAAK,SAAS;AAAA,QACzB;AAAA,MACF;AAAA,IACF;AACA,kBAAc,cAAc,SAAS,cAAc;AACjD,aAAO,KAAK;AAAA,IACd;AACA,kBAAc,sBAAsB,SAAS,sBAAsB;AACjE,aAAO,KAAK,SAAS;AAAA,IACvB;AACA,kBAAc,aAAa,SAAS,aAAa;AAC/C,aAAO,KAAK;AAAA,IACd;AACA,kBAAc,qBAAqB,SAAS,qBAAqB;AAC/D,aAAO,KAAK,QAAQ;AAAA,IACtB;AACA,kBAAc,gBAAgB,SAAS,gBAAgB;AACrD,UAAI,KAAK,WAAW;AAClB,eAAO,KAAK,GAAG,SAAS,IAAI,KAAK,KAAK,IAAI,EAAE,cAAc;AAC5D,UAAI,MAAM,KAAK,QAAQ,IAAI,KAAK,OAAO,KAAK;AAC5C,eAAS,MAAM,IAAI,MAAM,GAAG;AAC1B,aAAK,MAAM,KAAK,QAAQ;AACtB;AACJ,aAAO,KAAK,QAAQ,IAAI,MAAM,KAAK,MAAM;AAAA,IAC3C;AACA,kBAAc,SAAS,SAAS,SAAS;AACvC,aAAO,KAAK,SAAS,KAAK,KAAK,QAAQ;AAAA,IACzC;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,aAAa,SAAS,aAAa;AAC/C,aAAO,CAAC,KAAK,YAAY,KAAK,OAAO;AAAA,IACvC;AACA,kBAAc,aAAa,SAAS,aAAa;AAC/C,aAAO,KAAK,YAAY,KAAK,QAAQ;AAAA,IACvC;AACA,kBAAc,QAAQ,SAAS,QAAQ;AACrC,cAAQ,KAAK,MAAM,OAAO;AAAA,IAC5B;AACA,kBAAc,SAAS,SAAS,UAAU;AACxC,cAAQ,KAAK,MAAM,OAAO;AAAA,IAC5B;AACA,kBAAc,SAAS,SAAS,OAAO,OAAO;AAC5C,UAAI,CAAC,OAAO,KAAK;AACf,gBAAQ,UAAU,KAAK;AACzB,UAAI,KAAK,aAAa,MAAM,YAAY,KAAK,SAAS,OAAO,KAAK,MAAM,SAAS,OAAO;AACtF,eAAO;AACT,aAAO,KAAK,SAAS,MAAM,QAAQ,KAAK,QAAQ,MAAM;AAAA,IACxD;AACA,kBAAc,KAAK,cAAc;AACjC,kBAAc,YAAY,SAAS,UAAU,OAAO;AAClD,aAAO,CAAC,KAAK,GAAG,KAAK;AAAA,IACvB;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,KAAK,cAAc;AACjC,kBAAc,WAAW,SAAS,SAAS,OAAO;AAChD,aAAO,KAAK,KAAK,KAAK,IAAI;AAAA,IAC5B;AACA,kBAAc,KAAK,cAAc;AACjC,kBAAc,kBAAkB,SAAS,gBAAgB,OAAO;AAC9D,aAAO,KAAK,KAAK,KAAK,KAAK;AAAA,IAC7B;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,KAAK,cAAc;AACjC,kBAAc,cAAc,SAAS,YAAY,OAAO;AACtD,aAAO,KAAK,KAAK,KAAK,IAAI;AAAA,IAC5B;AACA,kBAAc,KAAK,cAAc;AACjC,kBAAc,qBAAqB,SAAS,mBAAmB,OAAO;AACpE,aAAO,KAAK,KAAK,KAAK,KAAK;AAAA,IAC7B;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,KAAK,cAAc;AACjC,kBAAc,UAAU,SAASC,SAAQ,OAAO;AAC9C,UAAI,CAAC,OAAO,KAAK;AACf,gBAAQ,UAAU,KAAK;AACzB,UAAI,KAAK,GAAG,KAAK;AACf,eAAO;AACT,UAAI,UAAU,KAAK,WAAW,GAAG,WAAW,MAAM,WAAW;AAC7D,UAAI,WAAW,CAAC;AACd,eAAO;AACT,UAAI,CAAC,WAAW;AACd,eAAO;AACT,UAAI,CAAC,KAAK;AACR,eAAO,KAAK,IAAI,KAAK,EAAE,WAAW,IAAI,KAAK;AAC7C,aAAO,MAAM,SAAS,IAAI,KAAK,SAAS,KAAK,MAAM,SAAS,KAAK,QAAQ,MAAM,QAAQ,IAAI,KAAK,QAAQ,IAAI,KAAK;AAAA,IACnH;AACA,kBAAc,OAAO,cAAc;AACnC,kBAAc,SAAS,SAAS,SAAS;AACvC,UAAI,CAAC,KAAK,YAAY,KAAK,GAAG,SAAS;AACrC,eAAO;AACT,aAAO,KAAK,IAAI,EAAE,IAAI,GAAG;AAAA,IAC3B;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,MAAM,SAAS,KAAK,QAAQ;AACxC,UAAI,CAAC,OAAO,MAAM;AAChB,iBAAS,UAAU,MAAM;AAC3B,UAAI,MAAM,KAAK,SAAS;AACxB,UAAI,MAAM,KAAK,OAAO;AACtB,UAAI,MAAM,KAAK,QAAQ;AACvB,UAAI,MAAM,KAAK,MAAM;AACrB,UAAI,MAAM,OAAO,SAAS;AAC1B,UAAI,MAAM,OAAO,OAAO;AACxB,UAAI,MAAM,OAAO,QAAQ;AACzB,UAAI,MAAM,OAAO,MAAM;AACvB,UAAI,MAAM,GAAG,MAAM,GAAG,MAAM,GAAG,MAAM;AACrC,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO;AACP,aAAO,SAAS,OAAO,KAAK,KAAK,OAAO,KAAK,KAAK,KAAK,QAAQ;AAAA,IACjE;AACA,kBAAc,WAAW,SAAS,SAAS,YAAY;AACrD,UAAI,CAAC,OAAO,UAAU;AACpB,qBAAa,UAAU,UAAU;AACnC,aAAO,KAAK,IAAI,WAAW,IAAI,CAAC;AAAA,IAClC;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,WAAW,SAAS,UAAU,YAAY;AACtD,UAAI,KAAK,OAAO;AACd,eAAO;AACT,UAAI,CAAC,OAAO,UAAU;AACpB,qBAAa,UAAU,UAAU;AACnC,UAAI,MAAM;AACR,YAAI,MAAM,KAAK;AAAA,UACb,KAAK;AAAA,UACL,KAAK;AAAA,UACL,WAAW;AAAA,UACX,WAAW;AAAA,QACb;AACA,eAAO,SAAS,KAAK,KAAK,SAAS,GAAG,KAAK,QAAQ;AAAA,MACrD;AACA,UAAI,WAAW,OAAO;AACpB,eAAO;AACT,UAAI,KAAK,GAAG,SAAS;AACnB,eAAO,WAAW,MAAM,IAAI,YAAY;AAC1C,UAAI,WAAW,GAAG,SAAS;AACzB,eAAO,KAAK,MAAM,IAAI,YAAY;AACpC,UAAI,KAAK,WAAW,GAAG;AACrB,YAAI,WAAW,WAAW;AACxB,iBAAO,KAAK,IAAI,EAAE,IAAI,WAAW,IAAI,CAAC;AAAA;AAEtC,iBAAO,KAAK,IAAI,EAAE,IAAI,UAAU,EAAE,IAAI;AAAA,MAC1C,WAAW,WAAW,WAAW;AAC/B,eAAO,KAAK,IAAI,WAAW,IAAI,CAAC,EAAE,IAAI;AACxC,UAAI,KAAK,GAAG,UAAU,KAAK,WAAW,GAAG,UAAU;AACjD,eAAO,WAAW,KAAK,SAAS,IAAI,WAAW,SAAS,GAAG,KAAK,QAAQ;AAC1E,UAAI,MAAM,KAAK,SAAS;AACxB,UAAI,MAAM,KAAK,OAAO;AACtB,UAAI,MAAM,KAAK,QAAQ;AACvB,UAAI,MAAM,KAAK,MAAM;AACrB,UAAI,MAAM,WAAW,SAAS;AAC9B,UAAI,MAAM,WAAW,OAAO;AAC5B,UAAI,MAAM,WAAW,QAAQ;AAC7B,UAAI,MAAM,WAAW,MAAM;AAC3B,UAAI,MAAM,GAAG,MAAM,GAAG,MAAM,GAAG,MAAM;AACrC,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM;AACb,aAAO,QAAQ;AACf,aAAO;AACP,aAAO,MAAM,MAAM,MAAM,MAAM,MAAM,MAAM,MAAM;AACjD,aAAO;AACP,aAAO,SAAS,OAAO,KAAK,KAAK,OAAO,KAAK,KAAK,KAAK,QAAQ;AAAA,IACjE;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,SAAS,SAAS,OAAO,SAAS;AAC9C,UAAI,CAAC,OAAO,OAAO;AACjB,kBAAU,UAAU,OAAO;AAC7B,UAAI,QAAQ,OAAO;AACjB,cAAM,MAAM,kBAAkB;AAChC,UAAI,MAAM;AACR,YAAI,CAAC,KAAK,YAAY,KAAK,SAAS,eAAe,QAAQ,QAAQ,MAAM,QAAQ,SAAS,IAAI;AAC5F,iBAAO;AAAA,QACT;AACA,YAAI,OAAO,KAAK,WAAW,KAAK,QAAQ,KAAK;AAAA,UAC3C,KAAK;AAAA,UACL,KAAK;AAAA,UACL,QAAQ;AAAA,UACR,QAAQ;AAAA,QACV;AACA,eAAO,SAAS,KAAK,KAAK,SAAS,GAAG,KAAK,QAAQ;AAAA,MACrD;AACA,UAAI,KAAK,OAAO;AACd,eAAO,KAAK,WAAW,QAAQ;AACjC,UAAI,QAAQ,KAAK;AACjB,UAAI,CAAC,KAAK,UAAU;AAClB,YAAI,KAAK,GAAG,SAAS,GAAG;AACtB,cAAI,QAAQ,GAAG,GAAG,KAAK,QAAQ,GAAG,OAAO;AACvC,mBAAO;AAAA,mBACA,QAAQ,GAAG,SAAS;AAC3B,mBAAO;AAAA,eACJ;AACH,gBAAI,WAAW,KAAK,IAAI,CAAC;AACzB,qBAAS,SAAS,IAAI,OAAO,EAAE,IAAI,CAAC;AACpC,gBAAI,OAAO,GAAG,IAAI,GAAG;AACnB,qBAAO,QAAQ,WAAW,IAAI,MAAM;AAAA,YACtC,OAAO;AACL,oBAAM,KAAK,IAAI,QAAQ,IAAI,MAAM,CAAC;AAClC,oBAAM,OAAO,IAAI,IAAI,IAAI,OAAO,CAAC;AACjC,qBAAO;AAAA,YACT;AAAA,UACF;AAAA,QACF,WAAW,QAAQ,GAAG,SAAS;AAC7B,iBAAO,KAAK,WAAW,QAAQ;AACjC,YAAI,KAAK,WAAW,GAAG;AACrB,cAAI,QAAQ,WAAW;AACrB,mBAAO,KAAK,IAAI,EAAE,IAAI,QAAQ,IAAI,CAAC;AACrC,iBAAO,KAAK,IAAI,EAAE,IAAI,OAAO,EAAE,IAAI;AAAA,QACrC,WAAW,QAAQ,WAAW;AAC5B,iBAAO,KAAK,IAAI,QAAQ,IAAI,CAAC,EAAE,IAAI;AACrC,cAAM;AAAA,MACR,OAAO;AACL,YAAI,CAAC,QAAQ;AACX,oBAAU,QAAQ,WAAW;AAC/B,YAAI,QAAQ,GAAG,IAAI;AACjB,iBAAO;AACT,YAAI,QAAQ,GAAG,KAAK,KAAK,CAAC,CAAC;AACzB,iBAAO;AACT,cAAM;AAAA,MACR;AACA,YAAM;AACN,aAAO,IAAI,IAAI,OAAO,GAAG;AACvB,iBAAS,KAAK,IAAI,GAAG,KAAK,MAAM,IAAI,SAAS,IAAI,QAAQ,SAAS,CAAC,CAAC;AACpE,YAAIC,SAAQ,KAAK,KAAK,KAAK,IAAI,MAAM,IAAI,KAAK,GAAG,GAAG,QAAQA,UAAS,KAAK,IAAI,QAAQ,GAAGA,SAAQ,EAAE,GAAG,YAAY,WAAW,MAAM,GAAG,YAAY,UAAU,IAAI,OAAO;AACvK,eAAO,UAAU,WAAW,KAAK,UAAU,GAAG,GAAG,GAAG;AAClD,oBAAU;AACV,sBAAY,WAAW,QAAQ,KAAK,QAAQ;AAC5C,sBAAY,UAAU,IAAI,OAAO;AAAA,QACnC;AACA,YAAI,UAAU,OAAO;AACnB,sBAAY;AACd,cAAM,IAAI,IAAI,SAAS;AACvB,cAAM,IAAI,IAAI,SAAS;AAAA,MACzB;AACA,aAAO;AAAA,IACT;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,SAAS,SAAS,OAAO,SAAS;AAC9C,UAAI,CAAC,OAAO,OAAO;AACjB,kBAAU,UAAU,OAAO;AAC7B,UAAI,MAAM;AACR,YAAI,OAAO,KAAK,WAAW,KAAK,QAAQ,KAAK;AAAA,UAC3C,KAAK;AAAA,UACL,KAAK;AAAA,UACL,QAAQ;AAAA,UACR,QAAQ;AAAA,QACV;AACA,eAAO,SAAS,KAAK,KAAK,SAAS,GAAG,KAAK,QAAQ;AAAA,MACrD;AACA,aAAO,KAAK,IAAI,KAAK,IAAI,OAAO,EAAE,IAAI,OAAO,CAAC;AAAA,IAChD;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,MAAM,cAAc;AAClC,kBAAc,MAAM,SAAS,MAAM;AACjC,aAAO,SAAS,CAAC,KAAK,KAAK,CAAC,KAAK,MAAM,KAAK,QAAQ;AAAA,IACtD;AACA,kBAAc,MAAM,SAAS,IAAI,OAAO;AACtC,UAAI,CAAC,OAAO,KAAK;AACf,gBAAQ,UAAU,KAAK;AACzB,aAAO,SAAS,KAAK,MAAM,MAAM,KAAK,KAAK,OAAO,MAAM,MAAM,KAAK,QAAQ;AAAA,IAC7E;AACA,kBAAc,KAAK,SAAS,GAAG,OAAO;AACpC,UAAI,CAAC,OAAO,KAAK;AACf,gBAAQ,UAAU,KAAK;AACzB,aAAO,SAAS,KAAK,MAAM,MAAM,KAAK,KAAK,OAAO,MAAM,MAAM,KAAK,QAAQ;AAAA,IAC7E;AACA,kBAAc,MAAM,SAAS,IAAI,OAAO;AACtC,UAAI,CAAC,OAAO,KAAK;AACf,gBAAQ,UAAU,KAAK;AACzB,aAAO,SAAS,KAAK,MAAM,MAAM,KAAK,KAAK,OAAO,MAAM,MAAM,KAAK,QAAQ;AAAA,IAC7E;AACA,kBAAc,YAAY,SAAS,UAAU,SAAS;AACpD,UAAI,OAAO,OAAO;AAChB,kBAAU,QAAQ,MAAM;AAC1B,WAAK,WAAW,QAAQ;AACtB,eAAO;AAAA,eACA,UAAU;AACjB,eAAO,SAAS,KAAK,OAAO,SAAS,KAAK,QAAQ,UAAU,KAAK,QAAQ,KAAK,SAAS,KAAK,QAAQ;AAAA;AAEpG,eAAO,SAAS,GAAG,KAAK,OAAO,UAAU,IAAI,KAAK,QAAQ;AAAA,IAC9D;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,aAAa,SAAS,WAAW,SAAS;AACtD,UAAI,OAAO,OAAO;AAChB,kBAAU,QAAQ,MAAM;AAC1B,WAAK,WAAW,QAAQ;AACtB,eAAO;AAAA,eACA,UAAU;AACjB,eAAO,SAAS,KAAK,QAAQ,UAAU,KAAK,QAAQ,KAAK,SAAS,KAAK,QAAQ,SAAS,KAAK,QAAQ;AAAA;AAErG,eAAO,SAAS,KAAK,QAAQ,UAAU,IAAI,KAAK,QAAQ,IAAI,IAAI,IAAI,KAAK,QAAQ;AAAA,IACrF;AACA,kBAAc,MAAM,cAAc;AAClC,kBAAc,qBAAqB,SAAS,mBAAmB,SAAS;AACtE,UAAI,OAAO,OAAO;AAChB,kBAAU,QAAQ,MAAM;AAC1B,iBAAW;AACX,UAAI,YAAY;AACd,eAAO;AAAA,WACJ;AACH,YAAI,OAAO,KAAK;AAChB,YAAI,UAAU,IAAI;AAChB,cAAI,MAAM,KAAK;AACf,iBAAO,SAAS,QAAQ,UAAU,QAAQ,KAAK,SAAS,SAAS,SAAS,KAAK,QAAQ;AAAA,QACzF,WAAW,YAAY;AACrB,iBAAO,SAAS,MAAM,GAAG,KAAK,QAAQ;AAAA;AAEtC,iBAAO,SAAS,SAAS,UAAU,IAAI,GAAG,KAAK,QAAQ;AAAA,MAC3D;AAAA,IACF;AACA,kBAAc,OAAO,cAAc;AACnC,kBAAc,QAAQ,cAAc;AACpC,kBAAc,WAAW,SAAS,WAAW;AAC3C,UAAI,CAAC,KAAK;AACR,eAAO;AACT,aAAO,SAAS,KAAK,KAAK,KAAK,MAAM,KAAK;AAAA,IAC5C;AACA,kBAAc,aAAa,SAAS,aAAa;AAC/C,UAAI,KAAK;AACP,eAAO;AACT,aAAO,SAAS,KAAK,KAAK,KAAK,MAAM,IAAI;AAAA,IAC3C;AACA,kBAAc,UAAU,SAAS,QAAQ,IAAI;AAC3C,aAAO,KAAK,KAAK,UAAU,IAAI,KAAK,UAAU;AAAA,IAChD;AACA,kBAAc,YAAY,SAAS,YAAY;AAC7C,UAAI,KAAK,KAAK,MAAM,KAAK,KAAK;AAC9B,aAAO;AAAA,QACL,KAAK;AAAA,QACL,OAAO,IAAI;AAAA,QACX,OAAO,KAAK;AAAA,QACZ,OAAO;AAAA,QACP,KAAK;AAAA,QACL,OAAO,IAAI;AAAA,QACX,OAAO,KAAK;AAAA,QACZ,OAAO;AAAA,MACT;AAAA,IACF;AACA,kBAAc,YAAY,SAAS,YAAY;AAC7C,UAAI,KAAK,KAAK,MAAM,KAAK,KAAK;AAC9B,aAAO;AAAA,QACL,OAAO;AAAA,QACP,OAAO,KAAK;AAAA,QACZ,OAAO,IAAI;AAAA,QACX,KAAK;AAAA,QACL,OAAO;AAAA,QACP,OAAO,KAAK;AAAA,QACZ,OAAO,IAAI;AAAA,QACX,KAAK;AAAA,MACP;AAAA,IACF;AACA,UAAM,YAAY,SAAS,UAAU,OAAO,UAAU,IAAI;AACxD,aAAO,KAAK,MAAM,YAAY,OAAO,QAAQ,IAAI,MAAM,YAAY,OAAO,QAAQ;AAAA,IACpF;AACA,UAAM,cAAc,SAAS,YAAY,OAAO,UAAU;AACxD,aAAO,IAAI;AAAA,QACT,MAAM,KAAK,MAAM,MAAM,IAAI,MAAM,MAAM,KAAK,MAAM,MAAM;AAAA,QACxD,MAAM,KAAK,MAAM,MAAM,IAAI,MAAM,MAAM,KAAK,MAAM,MAAM;AAAA,QACxD;AAAA,MACF;AAAA,IACF;AACA,UAAM,cAAc,SAAS,YAAY,OAAO,UAAU;AACxD,aAAO,IAAI;AAAA,QACT,MAAM,MAAM,KAAK,MAAM,MAAM,KAAK,MAAM,MAAM,IAAI,MAAM;AAAA,QACxD,MAAM,MAAM,KAAK,MAAM,MAAM,KAAK,MAAM,MAAM,IAAI,MAAM;AAAA,QACxD;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACF,CAAC;AAGD,IAAI,kBAAkB,WAAW;AAAA,EAC/B,sFAAsF;AAAA,EACtF;AACF,CAAC;AAGD,IAAI,eAAe,WAAW;AAAA,EAC5B,oBAAoB;AAAA,EACpB;AACF,CAAC;AAGD,IAAI,eAAe,WAAW;AAAA,EAC5B,0EAA0E,SAAS,QAAQ;AACzF,KAAC,SAAS,SAAS,SAAS,SAAS;AACnC,eAAS,KAAK,MAAM;AAClB,YAAI,KAAK,MAAM,OAAO,KAAK;AAC3B,WAAG,OAAO,WAAW;AACnB,cAAI,KAAK,UAAU,GAAG,KAAK,GAAG,IAAI;AAClC,aAAG,KAAK,GAAG;AACX,aAAG,KAAK,GAAG;AACX,iBAAO,GAAG,KAAK,MAAM,GAAG,IAAI,KAAK;AAAA,QACnC;AACA,WAAG,IAAI;AACP,WAAG,KAAK,KAAK,GAAG;AAChB,WAAG,KAAK,KAAK,GAAG;AAChB,WAAG,KAAK,KAAK,GAAG;AAChB,WAAG,MAAM,KAAK,IAAI;AAClB,YAAI,GAAG,KAAK,GAAG;AACb,aAAG,MAAM;AAAA,QACX;AACA,WAAG,MAAM,KAAK,IAAI;AAClB,YAAI,GAAG,KAAK,GAAG;AACb,aAAG,MAAM;AAAA,QACX;AACA,WAAG,MAAM,KAAK,IAAI;AAClB,YAAI,GAAG,KAAK,GAAG;AACb,aAAG,MAAM;AAAA,QACX;AACA,eAAO;AAAA,MACT;AACA,eAASC,MAAK,GAAG,IAAI;AACnB,WAAG,IAAI,EAAE;AACT,WAAG,KAAK,EAAE;AACV,WAAG,KAAK,EAAE;AACV,WAAG,KAAK,EAAE;AACV,eAAO;AAAA,MACT;AACA,eAAS,KAAK,MAAM,MAAM;AACxB,YAAI,KAAK,IAAI,KAAK,IAAI,GAAG,QAAQ,QAAQ,KAAK,OAAO,OAAO,GAAG;AAC/D,aAAK,QAAQ,WAAW;AACtB,iBAAO,GAAG,KAAK,IAAI,aAAa;AAAA,QAClC;AACA,aAAK,SAAS,WAAW;AACvB,iBAAO,KAAK,KAAK,KAAK,IAAI,UAAU,KAAK;AAAA,QAC3C;AACA,aAAK,QAAQ;AACb,YAAI,OAAO;AACT,cAAI,OAAO,SAAS;AAClB,YAAAA,MAAK,OAAO,EAAE;AAChB,eAAK,QAAQ,WAAW;AACtB,mBAAOA,MAAK,IAAI,CAAC,CAAC;AAAA,UACpB;AAAA,QACF;AACA,eAAO;AAAA,MACT;AACA,eAAS,OAAO;AACd,YAAI,KAAK;AACT,YAAI,OAAO,SAAS,MAAM;AACxB,iBAAO,OAAO,IAAI;AAClB,mBAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,kBAAM,KAAK,WAAW,EAAE;AACxB,gBAAI,IAAI,sBAAsB;AAC9B,iBAAK,MAAM;AACX,iBAAK;AACL,iBAAK;AACL,iBAAK,MAAM;AACX,iBAAK;AACL,kBAAM,IAAI;AAAA,UACZ;AACA,kBAAQ,OAAO,KAAK;AAAA,QACtB;AACA,eAAO;AAAA,MACT;AACA,UAAI,WAAW,QAAQ,SAAS;AAC9B,gBAAQ,UAAU;AAAA,MACpB,WAAW,WAAW,QAAQ,KAAK;AACjC,gBAAQ,WAAW;AACjB,iBAAO;AAAA,QACT,CAAC;AAAA,MACH,OAAO;AACL,aAAK,OAAO;AAAA,MACd;AAAA,IACF;AAAA,MACE;AAAA,MACA,OAAO,UAAU,YAAY;AAAA,MAC7B,OAAO,UAAU,cAAc;AAAA,IACjC;AAAA,EACF;AACF,CAAC;AAGD,IAAI,iBAAiB,WAAW;AAAA,EAC9B,4EAA4E,SAAS,QAAQ;AAC3F,KAAC,SAAS,SAAS,SAAS,SAAS;AACnC,eAAS,OAAO,MAAM;AACpB,YAAI,KAAK,MAAM,UAAU;AACzB,WAAG,IAAI;AACP,WAAG,IAAI;AACP,WAAG,IAAI;AACP,WAAG,IAAI;AACP,WAAG,OAAO,WAAW;AACnB,cAAI,KAAK,GAAG,IAAI,GAAG,KAAK;AACxB,aAAG,IAAI,GAAG;AACV,aAAG,IAAI,GAAG;AACV,aAAG,IAAI,GAAG;AACV,iBAAO,GAAG,KAAK,GAAG,MAAM,KAAK,KAAK,OAAO;AAAA,QAC3C;AACA,YAAI,UAAU,OAAO,IAAI;AACvB,aAAG,IAAI;AAAA,QACT,OAAO;AACL,qBAAW;AAAA,QACb;AACA,iBAAS,IAAI,GAAG,IAAI,QAAQ,SAAS,IAAI,KAAK;AAC5C,aAAG,KAAK,QAAQ,WAAW,CAAC,IAAI;AAChC,aAAG,KAAK;AAAA,QACV;AAAA,MACF;AACA,eAASA,MAAK,GAAG,IAAI;AACnB,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,eAAO;AAAA,MACT;AACA,eAAS,KAAK,MAAM,MAAM;AACxB,YAAI,KAAK,IAAI,OAAO,IAAI,GAAG,QAAQ,QAAQ,KAAK,OAAO,OAAO,WAAW;AACvE,kBAAQ,GAAG,KAAK,MAAM,KAAK;AAAA,QAC7B;AACA,aAAK,SAAS,WAAW;AACvB,aAAG;AACD,gBAAI,MAAM,GAAG,KAAK,MAAM,IAAI,OAAO,GAAG,KAAK,MAAM,KAAK,YAAY,UAAU,MAAM,QAAQ,KAAK;AAAA,UACjG,SAAS,WAAW;AACpB,iBAAO;AAAA,QACT;AACA,aAAK,QAAQ,GAAG;AAChB,aAAK,QAAQ;AACb,YAAI,OAAO;AACT,cAAI,OAAO,SAAS;AAClB,YAAAA,MAAK,OAAO,EAAE;AAChB,eAAK,QAAQ,WAAW;AACtB,mBAAOA,MAAK,IAAI,CAAC,CAAC;AAAA,UACpB;AAAA,QACF;AACA,eAAO;AAAA,MACT;AACA,UAAI,WAAW,QAAQ,SAAS;AAC9B,gBAAQ,UAAU;AAAA,MACpB,WAAW,WAAW,QAAQ,KAAK;AACjC,gBAAQ,WAAW;AACjB,iBAAO;AAAA,QACT,CAAC;AAAA,MACH,OAAO;AACL,aAAK,SAAS;AAAA,MAChB;AAAA,IACF;AAAA,MACE;AAAA,MACA,OAAO,UAAU,YAAY;AAAA,MAC7B,OAAO,UAAU,cAAc;AAAA,IACjC;AAAA,EACF;AACF,CAAC;AAGD,IAAI,iBAAiB,WAAW;AAAA,EAC9B,4EAA4E,SAAS,QAAQ;AAC3F,KAAC,SAAS,SAAS,SAAS,SAAS;AACnC,eAAS,OAAO,MAAM;AACpB,YAAI,KAAK,MAAM,UAAU;AACzB,WAAG,OAAO,WAAW;AACnB,cAAI,KAAK,GAAG,IAAI,GAAG,MAAM;AACzB,aAAG,IAAI,GAAG;AACV,aAAG,IAAI,GAAG;AACV,aAAG,IAAI,GAAG;AACV,aAAG,IAAI,GAAG;AACV,kBAAQ,GAAG,IAAI,GAAG,IAAI,SAAS,MAAM,GAAG,IAAI,GAAG,IAAI,GAAG,KAAK,KAAK,KAAK,MAAM,MAAM;AAAA,QACnF;AACA,WAAG,IAAI;AACP,WAAG,IAAI;AACP,WAAG,IAAI;AACP,WAAG,IAAI;AACP,WAAG,IAAI;AACP,YAAI,UAAU,OAAO,IAAI;AACvB,aAAG,IAAI;AAAA,QACT,OAAO;AACL,qBAAW;AAAA,QACb;AACA,iBAAS,IAAI,GAAG,IAAI,QAAQ,SAAS,IAAI,KAAK;AAC5C,aAAG,KAAK,QAAQ,WAAW,CAAC,IAAI;AAChC,cAAI,KAAK,QAAQ,QAAQ;AACvB,eAAG,IAAI,GAAG,KAAK,KAAK,GAAG,MAAM;AAAA,UAC/B;AACA,aAAG,KAAK;AAAA,QACV;AAAA,MACF;AACA,eAASA,MAAK,GAAG,IAAI;AACnB,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,eAAO;AAAA,MACT;AACA,eAAS,KAAK,MAAM,MAAM;AACxB,YAAI,KAAK,IAAI,OAAO,IAAI,GAAG,QAAQ,QAAQ,KAAK,OAAO,OAAO,WAAW;AACvE,kBAAQ,GAAG,KAAK,MAAM,KAAK;AAAA,QAC7B;AACA,aAAK,SAAS,WAAW;AACvB,aAAG;AACD,gBAAI,MAAM,GAAG,KAAK,MAAM,IAAI,OAAO,GAAG,KAAK,MAAM,KAAK,YAAY,UAAU,MAAM,QAAQ,KAAK;AAAA,UACjG,SAAS,WAAW;AACpB,iBAAO;AAAA,QACT;AACA,aAAK,QAAQ,GAAG;AAChB,aAAK,QAAQ;AACb,YAAI,OAAO;AACT,cAAI,OAAO,SAAS;AAClB,YAAAA,MAAK,OAAO,EAAE;AAChB,eAAK,QAAQ,WAAW;AACtB,mBAAOA,MAAK,IAAI,CAAC,CAAC;AAAA,UACpB;AAAA,QACF;AACA,eAAO;AAAA,MACT;AACA,UAAI,WAAW,QAAQ,SAAS;AAC9B,gBAAQ,UAAU;AAAA,MACpB,WAAW,WAAW,QAAQ,KAAK;AACjC,gBAAQ,WAAW;AACjB,iBAAO;AAAA,QACT,CAAC;AAAA,MACH,OAAO;AACL,aAAK,SAAS;AAAA,MAChB;AAAA,IACF;AAAA,MACE;AAAA,MACA,OAAO,UAAU,YAAY;AAAA,MAC7B,OAAO,UAAU,cAAc;AAAA,IACjC;AAAA,EACF;AACF,CAAC;AAGD,IAAI,oBAAoB,WAAW;AAAA,EACjC,+EAA+E,SAAS,QAAQ;AAC9F,KAAC,SAAS,SAAS,SAAS,SAAS;AACnC,eAAS,OAAO,MAAM;AACpB,YAAI,KAAK;AACT,WAAG,OAAO,WAAW;AACnB,cAAI,IAAI,GAAG,GAAG,KAAK,GAAG,GAAG,IAAI,GAAG;AAChC,eAAK,EAAE;AACP,gBAAM,OAAO;AACb,cAAI,KAAK,MAAM;AACf,eAAK,EAAE,KAAK,IAAI;AAChB,eAAK,KAAK,OAAO;AACjB,eAAK,EAAE,KAAK,IAAI;AAChB,eAAK,KAAK,OAAO;AACjB,eAAK,EAAE,KAAK,IAAI;AAChB,eAAK,KAAK,MAAM;AAChB,eAAK,EAAE,KAAK,IAAI;AAChB,eAAK,KAAK,MAAM;AAChB,eAAK,KAAK,MAAM;AAChB,YAAE,MAAM;AACR,aAAG,IAAI,KAAK,IAAI;AAChB,iBAAO;AAAA,QACT;AACA,iBAASC,OAAM,KAAK,OAAO;AACzB,cAAI,GAAG,GAAG,IAAI,CAAC;AACf,cAAI,WAAW,QAAQ,IAAI;AACzB,gBAAI,EAAE,KAAK;AAAA,UACb,OAAO;AACL,oBAAQ,KAAK;AACb,iBAAK,IAAI,GAAG,IAAI,MAAM,QAAQ,EAAE,GAAG;AACjC,gBAAE,IAAI,KAAK,EAAE,IAAI,MAAM,KAAK,MAAM,WAAW,CAAC,IAAI,EAAE,IAAI,IAAI,MAAM;AAAA,YACpE;AAAA,UACF;AACA,iBAAO,EAAE,SAAS;AAChB,cAAE,KAAK,CAAC;AACV,eAAK,IAAI,GAAG,IAAI,KAAK,EAAE,OAAO,GAAG,EAAE;AACjC;AACF,cAAI,KAAK;AACP,gBAAI,EAAE,KAAK;AAAA;AAEX,gBAAI,EAAE;AACR,cAAI,IAAI;AACR,cAAI,IAAI;AACR,eAAK,IAAI,KAAK,IAAI,GAAG,EAAE,GAAG;AACxB,gBAAI,KAAK;AAAA,UACX;AAAA,QACF;AACA,QAAAA,OAAM,IAAI,IAAI;AAAA,MAChB;AACA,eAASD,MAAK,GAAG,IAAI;AACnB,WAAG,IAAI,EAAE,EAAE,MAAM;AACjB,WAAG,IAAI,EAAE;AACT,eAAO;AAAA,MACT;AACA,eAAS,KAAK,MAAM,MAAM;AACxB,YAAI,QAAQ;AACV,iBAAO,CAAC,IAAI,KAAK;AACnB,YAAI,KAAK,IAAI,OAAO,IAAI,GAAG,QAAQ,QAAQ,KAAK,OAAO,OAAO,WAAW;AACvE,kBAAQ,GAAG,KAAK,MAAM,KAAK;AAAA,QAC7B;AACA,aAAK,SAAS,WAAW;AACvB,aAAG;AACD,gBAAI,MAAM,GAAG,KAAK,MAAM,IAAI,OAAO,GAAG,KAAK,MAAM,KAAK,YAAY,UAAU,MAAM,QAAQ,KAAK;AAAA,UACjG,SAAS,WAAW;AACpB,iBAAO;AAAA,QACT;AACA,aAAK,QAAQ,GAAG;AAChB,aAAK,QAAQ;AACb,YAAI,OAAO;AACT,cAAI,MAAM;AACR,YAAAA,MAAK,OAAO,EAAE;AAChB,eAAK,QAAQ,WAAW;AACtB,mBAAOA,MAAK,IAAI,CAAC,CAAC;AAAA,UACpB;AAAA,QACF;AACA,eAAO;AAAA,MACT;AACA,UAAI,WAAW,QAAQ,SAAS;AAC9B,gBAAQ,UAAU;AAAA,MACpB,WAAW,WAAW,QAAQ,KAAK;AACjC,gBAAQ,WAAW;AACjB,iBAAO;AAAA,QACT,CAAC;AAAA,MACH,OAAO;AACL,aAAK,YAAY;AAAA,MACnB;AAAA,IACF;AAAA,MACE;AAAA,MACA,OAAO,UAAU,YAAY;AAAA,MAC7B,OAAO,UAAU,cAAc;AAAA,IACjC;AAAA,EACF;AACF,CAAC;AAGD,IAAI,kBAAkB,WAAW;AAAA,EAC/B,6EAA6E,SAAS,QAAQ;AAC5F,KAAC,SAAS,SAAS,SAAS,SAAS;AACnC,eAAS,OAAO,MAAM;AACpB,YAAI,KAAK;AACT,WAAG,OAAO,WAAW;AACnB,cAAI,IAAI,GAAG,GAAG,IAAI,GAAG,GAAG,KAAK,GAAG,GAAG,IAAI;AACvC,aAAG,IAAI,IAAI,IAAI,aAAa;AAC5B,cAAI,EAAE,KAAK,KAAK;AAChB,eAAK,EAAE,KAAK,KAAK,IAAI;AACrB,eAAK,KAAK;AACV,gBAAM,MAAM;AACZ,eAAK,MAAM;AACX,gBAAM,OAAO;AACb,cAAI,EAAE,MAAM,IAAI;AAChB,aAAG,IAAI;AACP,iBAAO,KAAK,IAAI,MAAM,MAAM;AAAA,QAC9B;AACA,iBAASC,OAAM,KAAK,OAAO;AACzB,cAAI,IAAI,GAAG,IAAI,GAAG,GAAG,IAAI,CAAC,GAAG,QAAQ;AACrC,cAAI,WAAW,QAAQ,IAAI;AACzB,gBAAI;AACJ,oBAAQ;AAAA,UACV,OAAO;AACL,oBAAQ,QAAQ;AAChB,gBAAI;AACJ,oBAAQ,KAAK,IAAI,OAAO,MAAM,MAAM;AAAA,UACtC;AACA,eAAK,KAAK,GAAG,IAAI,KAAK,IAAI,OAAO,EAAE,GAAG;AACpC,gBAAI;AACF,mBAAK,MAAM,YAAY,IAAI,MAAM,MAAM,MAAM;AAC/C,gBAAI,MAAM;AACR,kBAAI;AACN,iBAAK,KAAK;AACV,iBAAK,MAAM;AACX,iBAAK,KAAK;AACV,iBAAK,MAAM;AACX,gBAAI,KAAK,GAAG;AACV,kBAAI,IAAI,aAAa;AACrB,mBAAK,EAAE,IAAI,QAAQ,IAAI;AACvB,mBAAK,KAAK,KAAK,KAAK,IAAI;AAAA,YAC1B;AAAA,UACF;AACA,cAAI,MAAM,KAAK;AACb,eAAG,SAAS,MAAM,UAAU,KAAK,OAAO;AAAA,UAC1C;AACA,eAAK;AACL,eAAK,IAAI,IAAI,KAAK,IAAI,GAAG,EAAE,GAAG;AAC5B,gBAAI,EAAE,KAAK,KAAK;AAChB,iBAAK,EAAE,KAAK,KAAK,IAAI;AACrB,iBAAK,KAAK;AACV,kBAAM,MAAM;AACZ,iBAAK,MAAM;AACX,kBAAM,OAAO;AACb,cAAE,MAAM,IAAI;AAAA,UACd;AACA,cAAI,IAAI;AACR,cAAI,IAAI;AACR,cAAI,IAAI;AAAA,QACV;AACA,QAAAA,OAAM,IAAI,IAAI;AAAA,MAChB;AACA,eAASD,MAAK,GAAG,IAAI;AACnB,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE,EAAE,MAAM;AACjB,eAAO;AAAA,MACT;AACA;AACA,eAAS,KAAK,MAAM,MAAM;AACxB,YAAI,QAAQ;AACV,iBAAO,CAAC,IAAI,KAAK;AACnB,YAAI,KAAK,IAAI,OAAO,IAAI,GAAG,QAAQ,QAAQ,KAAK,OAAO,OAAO,WAAW;AACvE,kBAAQ,GAAG,KAAK,MAAM,KAAK;AAAA,QAC7B;AACA,aAAK,SAAS,WAAW;AACvB,aAAG;AACD,gBAAI,MAAM,GAAG,KAAK,MAAM,IAAI,OAAO,GAAG,KAAK,MAAM,KAAK,YAAY,UAAU,MAAM,QAAQ,KAAK;AAAA,UACjG,SAAS,WAAW;AACpB,iBAAO;AAAA,QACT;AACA,aAAK,QAAQ,GAAG;AAChB,aAAK,QAAQ;AACb,YAAI,OAAO;AACT,cAAI,MAAM;AACR,YAAAA,MAAK,OAAO,EAAE;AAChB,eAAK,QAAQ,WAAW;AACtB,mBAAOA,MAAK,IAAI,CAAC,CAAC;AAAA,UACpB;AAAA,QACF;AACA,eAAO;AAAA,MACT;AACA,UAAI,WAAW,QAAQ,SAAS;AAC9B,gBAAQ,UAAU;AAAA,MACpB,WAAW,WAAW,QAAQ,KAAK;AACjC,gBAAQ,WAAW;AACjB,iBAAO;AAAA,QACT,CAAC;AAAA,MACH,OAAO;AACL,aAAK,UAAU;AAAA,MACjB;AAAA,IACF;AAAA,MACE;AAAA,MACA,OAAO,UAAU,YAAY;AAAA,MAC7B,OAAO,UAAU,cAAc;AAAA,IACjC;AAAA,EACF;AACF,CAAC;AAGD,IAAI,iBAAiB,WAAW;AAAA,EAC9B,4EAA4E,SAAS,QAAQ;AAC3F,KAAC,SAAS,SAAS,SAAS,SAAS;AACnC,eAAS,OAAO,MAAM;AACpB,YAAI,KAAK,MAAM,UAAU;AACzB,WAAG,OAAO,WAAW;AACnB,cAAI,IAAI,GAAG,GAAG,IAAI,GAAG,GAAG,IAAI,GAAG,GAAG,IAAI,GAAG;AACzC,cAAI,KAAK,KAAK,MAAM,IAAI;AACxB,cAAI,IAAI,IAAI;AACZ,cAAI,KAAK,KAAK,MAAM,IAAI;AACxB,cAAI,IAAI,IAAI;AACZ,aAAG,IAAI,IAAI,KAAK,KAAK,MAAM,KAAK;AAChC,aAAG,IAAI,IAAI,IAAI,IAAI;AACnB,aAAG,IAAI,KAAK,KAAK,MAAM,KAAK;AAC5B,iBAAO,GAAG,IAAI,IAAI,IAAI;AAAA,QACxB;AACA,WAAG,IAAI;AACP,WAAG,IAAI;AACP,WAAG,IAAI,aAAa;AACpB,WAAG,IAAI;AACP,YAAI,SAAS,KAAK,MAAM,IAAI,GAAG;AAC7B,aAAG,IAAI,OAAO,aAAa;AAC3B,aAAG,IAAI,OAAO;AAAA,QAChB,OAAO;AACL,qBAAW;AAAA,QACb;AACA,iBAAS,IAAI,GAAG,IAAI,QAAQ,SAAS,IAAI,KAAK;AAC5C,aAAG,KAAK,QAAQ,WAAW,CAAC,IAAI;AAChC,aAAG,KAAK;AAAA,QACV;AAAA,MACF;AACA,eAASA,MAAK,GAAG,IAAI;AACnB,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,eAAO;AAAA,MACT;AACA;AACA,eAAS,KAAK,MAAM,MAAM;AACxB,YAAI,KAAK,IAAI,OAAO,IAAI,GAAG,QAAQ,QAAQ,KAAK,OAAO,OAAO,WAAW;AACvE,kBAAQ,GAAG,KAAK,MAAM,KAAK;AAAA,QAC7B;AACA,aAAK,SAAS,WAAW;AACvB,aAAG;AACD,gBAAI,MAAM,GAAG,KAAK,MAAM,IAAI,OAAO,GAAG,KAAK,MAAM,KAAK,YAAY,UAAU,MAAM,QAAQ,KAAK;AAAA,UACjG,SAAS,WAAW;AACpB,iBAAO;AAAA,QACT;AACA,aAAK,QAAQ,GAAG;AAChB,aAAK,QAAQ;AACb,YAAI,OAAO;AACT,cAAI,OAAO,SAAS;AAClB,YAAAA,MAAK,OAAO,EAAE;AAChB,eAAK,QAAQ,WAAW;AACtB,mBAAOA,MAAK,IAAI,CAAC,CAAC;AAAA,UACpB;AAAA,QACF;AACA,eAAO;AAAA,MACT;AACA,UAAI,WAAW,QAAQ,SAAS;AAC9B,gBAAQ,UAAU;AAAA,MACpB,WAAW,WAAW,QAAQ,KAAK;AACjC,gBAAQ,WAAW;AACjB,iBAAO;AAAA,QACT,CAAC;AAAA,MACH,OAAO;AACL,aAAK,SAAS;AAAA,MAChB;AAAA,IACF;AAAA,MACE;AAAA,MACA,OAAO,UAAU,YAAY;AAAA,MAC7B,OAAO,UAAU,cAAc;AAAA,IACjC;AAAA,EACF;AACF,CAAC;AAGD,IAAI,iBAAiB,WAAW;AAAA,EAC9B,sBAAsB;AAAA,EACtB;AACF,CAAC;AAGD,IAAI,qBAAqB,WAAW;AAAA,EAClC,4EAA4E,SAAS,QAAQ;AAC3F,KAAC,SAAS,SAAS,OAAO,MAAM;AAC9B,UAAI,QAAQ,KAAK,SAAS,GAAG,SAAS,IAAI,UAAU,UAAU,aAAa,KAAK,IAAI,OAAO,MAAM,GAAG,eAAe,KAAK,IAAI,GAAG,MAAM,GAAG,WAAW,eAAe,GAAGE,QAAO,QAAQ,GAAG;AACvL,eAAS,YAAY,MAAMC,UAAS,UAAU;AAC5C,YAAI,MAAM,CAAC;AACX,QAAAA,WAAUA,YAAW,OAAO,EAAE,SAAS,KAAK,IAAIA,YAAW,CAAC;AAC5D,YAAI,YAAY,OAAO;AAAA,UACrBA,SAAQ,UAAU,CAAC,MAAM,SAAS,KAAK,CAAC,IAAI,QAAQ,OAAO,SAAS,IAAI;AAAA,UACxE;AAAA,QACF,GAAG,GAAG;AACN,YAAI,OAAO,IAAI,KAAK,GAAG;AACvB,YAAI,OAAO,WAAW;AACpB,cAAI,KAAK,KAAK,EAAE,MAAM,GAAG,IAAI,YAAY,IAAI;AAC7C,iBAAO,KAAK,cAAc;AACxB,kBAAM,KAAK,KAAK;AAChB,iBAAK;AACL,gBAAI,KAAK,EAAE,CAAC;AAAA,UACd;AACA,iBAAO,MAAM,UAAU;AACrB,kBAAM;AACN,iBAAK;AACL,mBAAO;AAAA,UACT;AACA,kBAAQ,KAAK,KAAK;AAAA,QACpB;AACA,aAAK,QAAQ,WAAW;AACtB,iBAAO,KAAK,EAAE,CAAC,IAAI;AAAA,QACrB;AACA,aAAK,QAAQ,WAAW;AACtB,iBAAO,KAAK,EAAE,CAAC,IAAI;AAAA,QACrB;AACA,aAAK,SAAS;AACd,eAAO,SAAS,KAAK,CAAC,GAAG,KAAK;AAC9B,gBAAQA,SAAQ,QAAQ,YAAY,SAAS,OAAO,OAAO,cAAc,OAAO;AAC9E,cAAI,OAAO;AACT,gBAAI,MAAM,GAAG;AACX,cAAAH,MAAK,OAAO,IAAI;AAAA,YAClB;AACA,kBAAM,QAAQ,WAAW;AACvB,qBAAOA,MAAK,MAAM,CAAC,CAAC;AAAA,YACtB;AAAA,UACF;AACA,cAAI,cAAc;AAChB,iBAAK,WAAW;AAChB,mBAAO;AAAA,UACT;AACE,mBAAO;AAAA,QACX;AAAA,UACE;AAAA,UACA;AAAA,UACA,YAAYG,WAAUA,SAAQ,SAAS,QAAQ;AAAA,UAC/CA,SAAQ;AAAA,QACV;AAAA,MACF;AACA,eAAS,KAAK,KAAK;AACjB,YAAI,IAAI,SAAS,IAAI,QAAQ,KAAK,MAAM,KAAK,GAAG,IAAI,GAAG,IAAI,GAAG,IAAI,GAAG,KAAK,GAAG,IAAI,CAAC;AAClF,YAAI,CAAC,QAAQ;AACX,gBAAM,CAAC,QAAQ;AAAA,QACjB;AACA,eAAO,KAAK,OAAO;AACjB,aAAG,MAAM;AAAA,QACX;AACA,aAAK,KAAK,GAAG,KAAK,OAAO,MAAM;AAC7B,aAAG,MAAM,GAAG,IAAID,QAAO,IAAI,IAAI,KAAK,WAAW,KAAK,GAAG;AACvD,aAAG,KAAK;AAAA,QACV;AACA,SAAC,GAAG,IAAI,SAASE,SAAQ;AACvB,cAAI,IAAI,KAAK,GAAG,KAAK,GAAG,GAAG,KAAK,GAAG,GAAG,KAAK,GAAG;AAC9C,iBAAOA,WAAU;AACf,iBAAK,GAAG,KAAKF,QAAO,KAAK;AACzB,iBAAK,KAAK,QAAQ,GAAGA,SAAQ,GAAG,MAAM,GAAG,KAAKA,QAAO,KAAK,QAAQ,GAAG,MAAM;AAAA,UAC7E;AACA,aAAG,IAAI;AACP,aAAG,IAAI;AACP,iBAAO;AAAA,QACT,GAAG,KAAK;AAAA,MACV;AACA,eAASF,MAAK,GAAG,IAAI;AACnB,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE;AACT,WAAG,IAAI,EAAE,EAAE,MAAM;AACjB,eAAO;AAAA,MACT;AACA;AACA,eAAS,SAAS,KAAK,OAAO;AAC5B,YAAI,SAAS,CAAC,GAAG,MAAM,OAAO,KAAK;AACnC,YAAI,SAAS,OAAO,UAAU;AAC5B,eAAK,QAAQ,KAAK;AAChB,gBAAI;AACF,qBAAO,KAAK,SAAS,IAAI,OAAO,QAAQ,CAAC,CAAC;AAAA,YAC5C,SAAS,IAAP;AAAA,YACF;AAAA,UACF;AAAA,QACF;AACA,eAAO,OAAO,SAAS,SAAS,OAAO,WAAW,MAAM,MAAM;AAAA,MAChE;AACA,eAAS,OAAO,MAAM,KAAK;AACzB,YAAI,aAAa,OAAO,IAAI,OAAO,IAAI;AACvC,eAAO,IAAI,WAAW,QAAQ;AAC5B,cAAIE,QAAO,KAAKA,SAAQ,SAAS,IAAIA,QAAO,KAAK,MAAM,WAAW,WAAW,GAAG;AAAA,QAClF;AACA,eAAO,SAAS,GAAG;AAAA,MACrB;AACA,eAAS,WAAW;AAClB,YAAI;AACF,cAAI;AACJ,cAAI,eAAe,MAAM,WAAW,cAAc;AAChD,kBAAM,IAAI,KAAK;AAAA,UACjB,OAAO;AACL,kBAAM,IAAI,WAAW,KAAK;AAC1B,aAAC,QAAQ,UAAU,QAAQ,UAAU,gBAAgB,GAAG;AAAA,UAC1D;AACA,iBAAO,SAAS,GAAG;AAAA,QACrB,SAAS,IAAP;AACA,cAAI,UAAU,QAAQ,WAAW,UAAU,WAAW,QAAQ;AAC9D,iBAAO,CAAC,CAAC,IAAI,KAAK,GAAG,SAAS,SAAS,QAAQ,QAAQ,SAAS,KAAK,CAAC;AAAA,QACxE;AAAA,MACF;AACA,eAAS,SAAS,GAAG;AACnB,eAAO,OAAO,aAAa,MAAM,GAAG,CAAC;AAAA,MACvC;AACA,aAAO,KAAK,OAAO,GAAG,KAAK;AAC3B,UAAI,OAAO,UAAU,YAAY,OAAO,SAAS;AAC/C,eAAO,UAAU;AACjB,YAAI;AACF,uBAAa,eAAe;AAAA,QAC9B,SAAS,IAAP;AAAA,QACF;AAAA,MACF,WAAW,OAAO,UAAU,cAAc,OAAO,KAAK;AACpD,eAAO,WAAW;AAChB,iBAAO;AAAA,QACT,CAAC;AAAA,MACH,OAAO;AACL,aAAK,SAAS,WAAW;AAAA,MAC3B;AAAA,IACF;AAAA,MACE,OAAO,SAAS,cAAc,OAAO;AAAA,MACrC,CAAC;AAAA,MACD;AAAA,IACF;AAAA,EACF;AACF,CAAC;AAGD,IAAI,sBAAsB,WAAW;AAAA,EACnC,uEAAuE,SAAS,QAAQ;AACtF,QAAI,QAAQ,aAAa;AACzB,QAAI,SAAS,eAAe;AAC5B,QAAI,SAAS,eAAe;AAC5B,QAAI,YAAY,kBAAkB;AAClC,QAAI,UAAU,gBAAgB;AAC9B,QAAI,SAAS,eAAe;AAC5B,QAAI,KAAK,mBAAmB;AAC5B,OAAG,OAAO;AACV,OAAG,SAAS;AACZ,OAAG,SAAS;AACZ,OAAG,YAAY;AACf,OAAG,UAAU;AACb,OAAG,SAAS;AACZ,WAAO,UAAU;AAAA,EACnB;AACF,CAAC;AAGD,IAAI,yBAAyB,WAAW;AAAA,EACtC,yGAAyG;AAAA,EACzG;AACF,CAAC;AAGD,IAAI,aAAa,WAAW;AAAA,EAC1B,kBAAkB;AAAA,EAClB;AACF,CAAC;AAGD,IAAI,eAAe,WAAW;AAAA,EAC5B,oBAAoB;AAAA,EACpB;AACF,CAAC;AAGD,IAAI,yBAAyB,WAAW;AAAA,EACtC,8BAA8B;AAAA,EAC9B;AACF,CAAC;AAGD,IAAI,qBAAqB,WAAW;AAAA,EAClC,0BAA0B;AAAA,EAC1B;AACF,CAAC;AAGD,IAAI,aAAa,WAAW;AAAA,EAC1B,kBAAkB;AAAA,EAClB;AACF,CAAC;AAGD,IAAI,0CAA0C,WAAW;AAAA,EACvD,4KAA4K,SAAS,QAAQ;AAC3L,QAAI,kCAAkC,MAAM;AAC1C,UAAI,aAAa,OAAO,aAAa,eAAe,SAAS,gBAAgB,SAAS,cAAc,MAAM;AAC1G,UAAI,OAAO,eAAe;AACxB,qBAAa,cAAc;AAC7B,aAAO,SAAS,gCAAgC;AAC9C,yCAAiC,kCAAkC,CAAC;AACpE,iBAAS,mBAAmB;AAC1B,cAAI,WAAW,UAAU,SAAS;AAChC,uCAA2B,WAAW,MAAM;AAAA,UAC9C;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,mBAAmB;AAC1B,cAAI,WAAW,UAAU,SAAS;AAChC,uCAA2B,WAAW,MAAM;AAAA,UAC9C;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,oBAAoB;AAC3B,cAAI,WAAW,UAAU,SAAS;AAChC,uCAA2B,WAAW,MAAM;AAAA,UAC9C;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,oBAAoB;AAC3B,cAAI,WAAW,UAAU,SAAS;AAChC,uCAA2B,WAAW,MAAM;AAAA,UAC9C;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,oBAAoB;AAC3B,cAAI,WAAW,UAAU,SAAS;AAChC,uCAA2B,WAAW,MAAM;AAAA,UAC9C;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,oBAAoB;AAC3B,cAAI,WAAW,UAAU,SAAS;AAChC,uCAA2B,WAAW,MAAM;AAAA,UAC9C;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,oBAAoB;AAC3B,cAAI,WAAW,UAAU,SAAS;AAChC,uCAA2B,WAAW,MAAM;AAAA,UAC9C;AACA,iBAAO;AAAA,QACT;AACA,YAAI,SAAS,OAAO,mCAAmC,cAAc,iCAAiC,CAAC;AACvG,YAAI,qBAAqB;AACzB,eAAO,WAAW,IAAI,QAAQ,SAAS,SAAS,QAAQ;AACtD,gCAAsB;AACtB,+BAAqB;AAAA,QACvB,CAAC;AACD,YAAI;AACJ,YAAI,OAAO,YAAY,eAAe,QAAQ,WAAW;AACvD,4BAAkB,EAAE,mBAAmB,QAAQ,UAAU,mBAAmB,GAAG,oBAAoB,QAAQ,UAAU,oBAAoB,EAAE;AAAA,QAC7I;AACA,YAAI,kBAAkB,OAAO,OAAO,CAAC,GAAG,MAAM;AAC9C,YAAI,aAAa,CAAC;AAClB,YAAI,cAAc;AAClB,YAAI,QAAQ,CAAC,QAAQ,YAAY;AAC/B,gBAAM;AAAA,QACR;AACA,YAAI,qBAAqB,OAAO,WAAW;AAC3C,YAAI,wBAAwB,OAAO,kBAAkB;AACrD,YAAI,sBAAsB,OAAO,YAAY,YAAY,OAAO,QAAQ,aAAa,YAAY,OAAO,QAAQ,SAAS,SAAS;AAClI,YAAI,yBAAyB,OAAO,6BAA6B;AACjE,YAAI,kBAAkB;AACtB,iBAAS,WAAW,MAAM;AACxB,cAAI,OAAO,eAAe;AACxB,mBAAO,OAAO,cAAc,MAAM,eAAe;AAAA,UACnD;AACA,iBAAO,kBAAkB;AAAA,QAC3B;AACA,YAAI,OAAO,WAAW,YAAY;AAClC,iBAAS,mBAAmB,IAAI;AAC9B,cAAI,cAAc;AAChB;AACF,cAAI,QAAQ;AACZ,cAAI,+BAA+B,KAAK;AAAA,QAC1C;AACA,YAAI;AACJ,YAAI;AACJ,YAAI;AACJ,YAAI,qBAAqB;AACvB,cAAI,uBAAuB;AACzB,8BAAkB,aAAa,EAAE,QAAQ,eAAe,IAAI;AAAA,UAC9D,OAAO;AACL,8BAAkB,YAAY;AAAA,UAChC;AACA,0BAAgB,MAAM;AACpB,gBAAI,CAAC,UAAU;AACb,mBAAK,WAAW;AAChB,yBAAW,aAAa;AAAA,YAC1B;AAAA,UACF;AACA,kBAAQ,SAAS,WAAW,UAAU,QAAQ;AAC5C,0BAAc;AACd,uBAAW,SAAS,aAAa,QAAQ;AACzC,mBAAO,GAAG,aAAa,UAAU,SAAS,SAAS,MAAM;AAAA,UAC3D;AACA,uBAAa,CAAC,aAAa;AACzB,gBAAI,MAAM,MAAM,UAAU,IAAI;AAC9B,gBAAI,CAAC,IAAI,QAAQ;AACf,oBAAM,IAAI,WAAW,GAAG;AAAA,YAC1B;AACA,mBAAO;AAAA,UACT;AACA,sBAAY,CAAC,UAAU,QAAQ,YAAY;AACzC,0BAAc;AACd,uBAAW,SAAS,aAAa,QAAQ;AACzC,eAAG,SAAS,UAAU,SAAS,MAAM,MAAM;AACzC,kBAAI;AACF,wBAAQ,IAAI;AAAA;AAEZ,uBAAO,KAAK,MAAM;AAAA,YACtB,CAAC;AAAA,UACH;AACA,cAAI,QAAQ,QAAQ,SAAS,GAAG;AAC9B,0BAAc,QAAQ,QAAQ,GAAG,QAAQ,OAAO,GAAG;AAAA,UACrD;AACA,uBAAa,QAAQ,QAAQ,MAAM,CAAC;AACpC,kBAAQ,MAAM,qBAAqB,SAAS,IAAI;AAC9C,gBAAI,EAAE,cAAc,aAAa;AAC/B,oBAAM;AAAA,YACR;AAAA,UACF,CAAC;AACD,kBAAQ,MAAM,sBAAsB,SAAS,QAAQ;AACnD,kBAAM;AAAA,UACR,CAAC;AACD,kBAAQ,CAAC,QAAQ,YAAY;AAC3B,gBAAI,iBAAiB,GAAG;AACtB,sBAAQ,cAAc;AACtB,oBAAM;AAAA,YACR;AACA,+BAAmB,OAAO;AAC1B,oBAAQ,QAAQ,MAAM;AAAA,UACxB;AACA,iBAAO,aAAa,WAAW;AAC7B,mBAAO;AAAA,UACT;AACA,cAAI;AACJ,cAAI;AACF,gCAAoB,uBAAuB;AAAA,UAC7C,SAAS,IAAP;AACA,oBAAQ,MAAM,yGAAyG;AACvH,kBAAM;AAAA,UACR;AACA,iBAAO,SAAS,kBAAkB;AAAA,QACpC,WAAW,sBAAsB,uBAAuB;AACtD,cAAI,uBAAuB;AACzB,8BAAkB,KAAK,SAAS;AAAA,UAClC,WAAW,OAAO,aAAa,eAAe,SAAS,eAAe;AACpE,8BAAkB,SAAS,cAAc;AAAA,UAC3C;AACA,cAAI,OAAO,eAAe,eAAe,YAAY;AACnD,8BAAkB;AAAA,UACpB;AACA,cAAI,gBAAgB,QAAQ,OAAO,MAAM,GAAG;AAC1C,8BAAkB,gBAAgB,OAAO,GAAG,gBAAgB,QAAQ,UAAU,EAAE,EAAE,YAAY,GAAG,IAAI,CAAC;AAAA,UACxG,OAAO;AACL,8BAAkB;AAAA,UACpB;AACA,cAAI,CAAC,qBAAqB;AACxB,oBAAQ,CAAC,QAAQ;AACf,kBAAI,MAAM,IAAI,eAAe;AAC7B,kBAAI,KAAK,OAAO,KAAK,KAAK;AAC1B,kBAAI,KAAK,IAAI;AACb,qBAAO,IAAI;AAAA,YACb;AACA,gBAAI,uBAAuB;AACzB,2BAAa,CAAC,QAAQ;AACpB,oBAAI,MAAM,IAAI,eAAe;AAC7B,oBAAI,KAAK,OAAO,KAAK,KAAK;AAC1B,oBAAI,eAAe;AACnB,oBAAI,KAAK,IAAI;AACb,uBAAO,IAAI,WAAW,IAAI,QAAQ;AAAA,cACpC;AAAA,YACF;AACA,wBAAY,CAAC,KAAK,QAAQ,YAAY;AACpC,kBAAI,MAAM,IAAI,eAAe;AAC7B,kBAAI,KAAK,OAAO,KAAK,IAAI;AACzB,kBAAI,eAAe;AACnB,kBAAI,SAAS,MAAM;AACjB,oBAAI,IAAI,UAAU,OAAO,IAAI,UAAU,KAAK,IAAI,UAAU;AACxD,yBAAO,IAAI,QAAQ;AACnB;AAAA,gBACF;AACA,wBAAQ;AAAA,cACV;AACA,kBAAI,UAAU;AACd,kBAAI,KAAK,IAAI;AAAA,YACf;AAAA,UACF;AACA,2BAAiB,CAAC,UAAU,SAAS,QAAQ;AAAA,QAC/C,OAAO;AAAA,QACP;AACA,YAAI,qBAAqB;AACvB,cAAI,OAAO,gBAAgB,aAAa;AACtC,mBAAO,cAAc,mBAAmB,EAAE;AAAA,UAC5C;AAAA,QACF;AACA,YAAI,eAAe,QAAQ,IAAI,KAAK,OAAO;AAC3C,YAAI,kBAAkB,QAAQ,KAAK,KAAK,OAAO;AAC/C,YAAI,qBAAqB;AACvB,wBAAc;AACd,yBAAe,CAAC,QAAQ,GAAG,UAAU,GAAG,MAAM,IAAI;AAClD,4BAAkB,CAAC,QAAQ,GAAG,UAAU,GAAG,MAAM,IAAI;AAAA,QACvD;AACA,YAAI,MAAM,OAAO,YAAY;AAC7B,YAAI,MAAM,OAAO,eAAe;AAChC,eAAO,OAAO,QAAQ,eAAe;AACrC,0BAAkB;AAClB,YAAI,OAAO;AACT,uBAAa,OAAO;AACtB,YAAI,OAAO;AACT,wBAAc,OAAO;AACvB,YAAI,OAAO;AACT,kBAAQ,OAAO;AACjB,YAAI,eAAe;AACnB,iBAAS,SAAS,MAAM;AACtB,cAAI,CAAC,SAAS;AACZ,qBAAS,QAAQ,CAAC;AACpB,cAAI,CAAC,SAAS,MAAM,OAAO;AACzB,qBAAS,MAAM,QAAQ;AACvB,gBAAI,IAAI;AAAA,UACV;AAAA,QACF;AACA,iBAAS,wBAAwB,OAAO,KAAK;AAC3C,cAAI,OAAO,YAAY,aAAa,YAAY;AAC9C,gBAAI,YAAY,EAAE,KAAK,OAAO,KAAK,OAAO,KAAK,OAAO,KAAK,MAAM;AACjE,gBAAI,OAAO,EAAE,YAAY,CAAC,GAAG,SAAS,IAAI,MAAM,MAAM,CAAC,IAAI,CAAC,UAAU,IAAI,GAAG,EAAE;AAC/E,qBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,mBAAK,WAAW,KAAK,UAAU,IAAI,IAAI;AAAA,YACzC;AACA,mBAAO,IAAI,YAAY,SAAS,MAAM,KAAK;AAAA,UAC7C;AACA,cAAI,cAAc,CAAC,GAAG,GAAG,GAAG,EAAE;AAC9B,cAAI,SAAS,IAAI,MAAM,GAAG,CAAC;AAC3B,cAAI,WAAW,IAAI,MAAM,CAAC;AAC1B,cAAI,YAAY,EAAE,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,IAAI;AACzD,sBAAY,KAAK,SAAS,MAAM;AAChC,mBAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,EAAE,IAAI;AAC3C,wBAAY,KAAK,UAAU,SAAS,IAAI;AAAA,UAC1C;AACA,cAAI,UAAU,KAAK;AACjB,wBAAY,KAAK,CAAC;AAAA,UACpB,OAAO;AACL,0BAAc,YAAY,OAAO,CAAC,GAAG,UAAU,OAAO,CAAC;AAAA,UACzD;AACA,sBAAY,KAAK,YAAY,SAAS;AACtC,cAAI,QAAQ,IAAI,WAAW,CAAC,GAAG,IAAI,KAAK,KAAK,GAAG,GAAG,GAAG,CAAC,EAAE,OAAO,aAAa,CAAC,GAAG,GAAG,GAAG,GAAG,KAAK,GAAG,KAAK,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,KAAK,GAAG,CAAC,CAAC,CAAC;AACpI,cAAI,UAAU,IAAI,YAAY,OAAO,KAAK;AAC1C,cAAI,WAAW,IAAI,YAAY,SAAS,SAAS,EAAE,KAAK,EAAE,KAAK,MAAM,EAAE,CAAC;AACxE,cAAI,cAAc,SAAS,QAAQ;AACnC,iBAAO;AAAA,QACT;AACA,YAAI,mBAAmB,CAAC;AACxB,YAAI;AACJ,iBAAS,oBAAoB;AAC3B,cAAI,iBAAiB,QAAQ;AAC3B,mBAAO,iBAAiB,IAAI;AAAA,UAC9B;AACA,cAAI;AACF,sBAAU,KAAK,CAAC;AAAA,UAClB,SAAS,MAAP;AACA,gBAAI,EAAE,gBAAgB,aAAa;AACjC,oBAAM;AAAA,YACR;AACA,kBAAM;AAAA,UACR;AACA,iBAAO,UAAU,SAAS;AAAA,QAC5B;AACA,iBAAS,eAAe,QAAQE,SAAQ;AACtC,mBAAS,KAAK,QAAQ,KAAK,SAASA,SAAQ,MAAM;AAChD,gBAAI,OAAO,kBAAkB,EAAE;AAC/B,gBAAI,MAAM;AACR,kCAAoB,IAAI,MAAM,EAAE;AAAA,YAClC;AAAA,UACF;AAAA,QACF;AACA,YAAI,WAAW;AACf,YAAI,cAAc,CAAC,UAAU;AAC3B,qBAAW;AAAA,QACb;AACA,YAAI,eAAe,QAAQ;AAC3B,YAAI,gBAAgB,QAAQ;AAC5B,YAAI,0BAA0B,QAAQ;AACtC,YAAI;AACJ,YAAI,OAAO;AACT,uBAAa,OAAO;AACtB,YAAI,gBAAgB,OAAO,oBAAoB;AAC/C,YAAI,OAAO,gBAAgB,UAAU;AACnC,gBAAM,iCAAiC;AAAA,QACzC;AACA,YAAI;AACJ,YAAI;AACJ,YAAI,QAAQ;AACZ,YAAI;AACJ,iBAAS,QAAQ,WAAW,MAAM;AAChC,cAAI,CAAC,WAAW;AACd,kBAAM,IAAI;AAAA,UACZ;AAAA,QACF;AACA,iBAAS,SAAS,OAAO;AACvB,cAAI,QAAQ,OAAO,MAAM;AACzB,iBAAO;AAAA,QACT;AACA,iBAAS,MAAM,OAAO,YAAY,UAAU,MAAM,MAAM;AACtD,cAAI,MAAM,EAAE,UAAU,SAAS,KAAK;AAClC,gBAAI,OAAO;AACX,gBAAI,QAAQ,QAAQ,QAAQ,UAAU,QAAQ,GAAG;AAC/C,kBAAI,OAAO,IAAI,UAAU,KAAK;AAC9B,qBAAO,WAAW,GAAG;AACrB,2BAAa,KAAK,MAAM,GAAG;AAAA,YAC7B;AACA,mBAAO;AAAA,UACT,GAAG,SAAS,SAAS,KAAK;AACxB,gBAAI,OAAO,WAAW,IAAI,MAAM;AAChC,+BAAmB,KAAK,IAAI;AAC5B,mBAAO;AAAA,UACT,EAAE;AACF,mBAAS,mBAAmB,MAAM;AAChC,gBAAI,eAAe;AACjB,qBAAO,aAAa,IAAI;AAC1B,gBAAI,eAAe;AACjB,qBAAO,QAAQ,IAAI;AACrB,mBAAO;AAAA,UACT;AACA,cAAI,QAAQ,SAAS,KAAK;AAC1B,cAAI,QAAQ,CAAC;AACb,cAAI,SAAS;AACb,cAAI,MAAM;AACR,qBAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,kBAAI,YAAY,IAAI,SAAS;AAC7B,kBAAI,WAAW;AACb,oBAAI,WAAW;AACb,2BAAS,UAAU;AACrB,sBAAM,MAAM,UAAU,KAAK,GAAG;AAAA,cAChC,OAAO;AACL,sBAAM,MAAM,KAAK;AAAA,cACnB;AAAA,YACF;AAAA,UACF;AACA,cAAI,MAAM,MAAM,MAAM,MAAM,KAAK;AACjC,mBAAS,OAAO,MAAM;AACpB,gBAAI,WAAW;AACb,2BAAa,MAAM;AACrB,mBAAO,mBAAmB,IAAI;AAAA,UAChC;AACA,gBAAM,OAAO,GAAG;AAChB,iBAAO;AAAA,QACT;AACA,iBAAS,MAAM,OAAO,YAAY,UAAU,MAAM;AAChD,qBAAW,YAAY,CAAC;AACxB,cAAI,cAAc,SAAS,MAAM,SAAS,MAAM;AAC9C,mBAAO,SAAS;AAAA,UAClB,CAAC;AACD,cAAI,aAAa,eAAe;AAChC,cAAI,cAAc,eAAe,CAAC,MAAM;AACtC,mBAAO,SAAS,KAAK;AAAA,UACvB;AACA,iBAAO,WAAW;AAChB,mBAAO,MAAM,OAAO,YAAY,UAAU,WAAW,IAAI;AAAA,UAC3D;AAAA,QACF;AACA,YAAI,cAAc;AAClB,iBAAS,mBAAmB,UAAU;AACpC,cAAI,cAAc,IAAI,YAAY,QAAQ;AAC1C,eAAK,SAAS,CAAC,SAAS;AACtB,gBAAI,KAAK,kBAAkB,mBAAmB;AAC5C,qBAAO,IAAI,WAAW,IAAI;AAAA,YAC5B;AACA,mBAAO,YAAY,OAAO,KAAK,aAAa,IAAI;AAAA,UAClD;AAAA,QACF;AACA,YAAI,cAAc,OAAO,gBAAgB,cAAc,IAAI,mBAAmB,MAAM,IAAI;AACxF,iBAAS,kBAAkB,MAAM,KAAK,gBAAgB;AACpD,cAAI,SAAS,MAAM;AACnB,cAAI,SAAS;AACb,iBAAO,KAAK,WAAW,EAAE,UAAU;AACjC,cAAE;AACJ,cAAI,SAAS,MAAM,MAAM,KAAK,YAAY,aAAa;AACrD,mBAAO,YAAY,OAAO,KAAK,SAAS,KAAK,MAAM,CAAC;AAAA,UACtD,OAAO;AACL,gBAAI,MAAM;AACV,mBAAO,MAAM,QAAQ;AACnB,kBAAI,KAAK,KAAK;AACd,kBAAI,EAAE,KAAK,MAAM;AACf,uBAAO,OAAO,aAAa,EAAE;AAC7B;AAAA,cACF;AACA,kBAAI,KAAK,KAAK,SAAS;AACvB,mBAAK,KAAK,QAAQ,KAAK;AACrB,uBAAO,OAAO,cAAc,KAAK,OAAO,IAAI,EAAE;AAC9C;AAAA,cACF;AACA,kBAAI,KAAK,KAAK,SAAS;AACvB,mBAAK,KAAK,QAAQ,KAAK;AACrB,sBAAM,KAAK,OAAO,KAAK,MAAM,IAAI;AAAA,cACnC,OAAO;AACL,sBAAM,KAAK,MAAM,KAAK,MAAM,KAAK,MAAM,IAAI,KAAK,SAAS;AAAA,cAC3D;AACA,kBAAI,KAAK,OAAO;AACd,uBAAO,OAAO,aAAa,EAAE;AAAA,cAC/B,OAAO;AACL,oBAAI,KAAK,KAAK;AACd,uBAAO,OAAO,aAAa,QAAQ,MAAM,IAAI,QAAQ,KAAK,IAAI;AAAA,cAChE;AAAA,YACF;AAAA,UACF;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,aAAa,KAAK,gBAAgB;AACzC,iBAAO,MAAM,kBAAkB,iBAAiB,GAAG,KAAK,cAAc,IAAI;AAAA,QAC5E;AACA,iBAAS,kBAAkB,KAAK,MAAM,QAAQ,iBAAiB;AAC7D,cAAI,EAAE,kBAAkB;AACtB,mBAAO;AACT,cAAI,WAAW;AACf,cAAI,SAAS,SAAS,kBAAkB;AACxC,mBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,gBAAI,IAAI,IAAI,WAAW,EAAE;AACzB,gBAAI,KAAK,SAAS,KAAK,OAAO;AAC5B,kBAAI,KAAK,IAAI,WAAW,EAAE,EAAE;AAC5B,kBAAI,UAAU,IAAI,SAAS,MAAM,KAAK;AAAA,YACxC;AACA,gBAAI,KAAK,KAAK;AACZ,kBAAI,UAAU;AACZ;AACF,mBAAK,YAAY;AAAA,YACnB,WAAW,KAAK,MAAM;AACpB,kBAAI,SAAS,KAAK;AAChB;AACF,mBAAK,YAAY,MAAM,KAAK;AAC5B,mBAAK,YAAY,MAAM,IAAI;AAAA,YAC7B,WAAW,KAAK,OAAO;AACrB,kBAAI,SAAS,KAAK;AAChB;AACF,mBAAK,YAAY,MAAM,KAAK;AAC5B,mBAAK,YAAY,MAAM,KAAK,IAAI;AAChC,mBAAK,YAAY,MAAM,IAAI;AAAA,YAC7B,OAAO;AACL,kBAAI,SAAS,KAAK;AAChB;AACF,mBAAK,YAAY,MAAM,KAAK;AAC5B,mBAAK,YAAY,MAAM,KAAK,KAAK;AACjC,mBAAK,YAAY,MAAM,KAAK,IAAI;AAChC,mBAAK,YAAY,MAAM,IAAI;AAAA,YAC7B;AAAA,UACF;AACA,eAAK,UAAU;AACf,iBAAO,SAAS;AAAA,QAClB;AACA,iBAAS,aAAa,KAAK,QAAQ,iBAAiB;AAClD,iBAAO,kBAAkB,KAAK,iBAAiB,GAAG,QAAQ,eAAe;AAAA,QAC3E;AACA,iBAAS,gBAAgB,KAAK;AAC5B,cAAI,MAAM;AACV,mBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,gBAAI,IAAI,IAAI,WAAW,EAAE;AACzB,gBAAI,KAAK,SAAS,KAAK;AACrB,kBAAI,UAAU,IAAI,SAAS,MAAM,IAAI,WAAW,EAAE,EAAE,IAAI;AAC1D,gBAAI,KAAK;AACP,gBAAE;AAAA,qBACK,KAAK;AACZ,qBAAO;AAAA,qBACA,KAAK;AACZ,qBAAO;AAAA;AAEP,qBAAO;AAAA,UACX;AACA,iBAAO;AAAA,QACT;AACA,YAAI,eAAe,OAAO,gBAAgB,cAAc,IAAI,mBAAmB,UAAU,IAAI;AAC7F,iBAAS,mBAAmB,QAAQ,SAAS;AAC3C,2BAAiB,EAAE,IAAI,QAAQ,OAAO;AAAA,QACxC;AACA,iBAAS,mBAAmB,KAAK,SAAS,aAAa;AACrD,mBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,6BAAiB,EAAE,aAAa,KAAK,IAAI,WAAW,EAAE;AAAA,UACxD;AACA,cAAI,CAAC;AACH,6BAAiB,EAAE,WAAW,KAAK;AAAA,QACvC;AACA,iBAAS,QAAQ,GAAG,UAAU;AAC5B,cAAI,IAAI,WAAW,GAAG;AACpB,iBAAK,WAAW,IAAI;AAAA,UACtB;AACA,iBAAO;AAAA,QACT;AACA,YAAI,SAAS,OAAO,QAAQ,QAAQ,SAAS,QAAQ,SAAS,SAAS;AACvE,YAAI,wBAAwB;AAC1B,oBAAU,OAAO;AAAA,QACnB;AACA,iBAAS,2BAA2B,KAAK;AACvC,oBAAU;AACV,iBAAO,WAAW,QAAQ,IAAI,UAAU,GAAG;AAC3C,iBAAO,YAAY,SAAS,IAAI,WAAW,GAAG;AAC9C,iBAAO,YAAY,SAAS,IAAI,WAAW,GAAG;AAC9C,iBAAO,YAAY,SAAS,IAAI,WAAW,GAAG;AAC9C,iBAAO,aAAa,UAAU,IAAI,YAAY,GAAG;AACjD,iBAAO,aAAa,UAAU,IAAI,YAAY,GAAG;AACjD,iBAAO,aAAa,UAAU,IAAI,aAAa,GAAG;AAClD,iBAAO,aAAa,UAAU,IAAI,aAAa,GAAG;AAAA,QACpD;AACA,YAAI,iBAAiB,OAAO,qBAAqB;AACjD,YAAI,wBAAwB;AAC1B,uBAAa,OAAO;AACpB,oBAAU,OAAO;AAAA,QACnB,OAAO;AACL,cAAI,OAAO,eAAe;AACxB,yBAAa,OAAO;AAAA,UACtB,OAAO;AACL,yBAAa,IAAI,YAAY,OAAO,EAAE,WAAW,iBAAiB,OAAO,WAAW,aAAa,OAAO,UAAU,KAAK,CAAC;AACxH,gBAAI,EAAE,WAAW,kBAAkB,oBAAoB;AACrD,kBAAI,6NAA6N;AACjO,kBAAI,qBAAqB;AACvB,wBAAQ,IAAI,mHAAmH;AAAA,cACjI;AACA,oBAAM,MAAM,YAAY;AAAA,YAC1B;AAAA,UACF;AAAA,QACF;AACA,YAAI,YAAY;AACd,oBAAU,WAAW;AAAA,QACvB;AACA,yBAAiB,QAAQ;AACzB,mCAA2B,OAAO;AAClC,YAAI;AACJ,YAAI,eAAe,CAAC;AACpB,YAAI,aAAa,CAAC;AAClB,YAAI,aAAa,CAAC;AAClB,YAAI,gBAAgB,CAAC;AACrB,YAAI,qBAAqB;AACzB,YAAI,gBAAgB;AACpB,YAAI,0BAA0B;AAC9B,iBAAS,mBAAmB;AAC1B,iBAAO,iBAAiB,0BAA0B;AAAA,QACpD;AACA,iBAAS,SAAS;AAChB,cAAI,OAAO,WAAW;AACpB,gBAAI,OAAO,OAAO,aAAa;AAC7B,qBAAO,YAAY,CAAC,OAAO,SAAS;AACtC,mBAAO,OAAO,UAAU,QAAQ;AAC9B,0BAAY,OAAO,UAAU,MAAM,CAAC;AAAA,YACtC;AAAA,UACF;AACA,+BAAqB,YAAY;AAAA,QACnC;AACA,iBAAS,cAAc;AACrB,+BAAqB;AACrB,cAAI;AACF;AACF,+BAAqB,UAAU;AAAA,QACjC;AACA,iBAAS,cAAc;AACrB,cAAI;AACF;AACF,kBAAQ,oBAAoB;AAC5B,0BAAgB;AAAA,QAClB;AACA,iBAAS,UAAU;AACjB,cAAI;AACF;AACF,cAAI,OAAO,YAAY;AACrB,gBAAI,OAAO,OAAO,cAAc;AAC9B,qBAAO,aAAa,CAAC,OAAO,UAAU;AACxC,mBAAO,OAAO,WAAW,QAAQ;AAC/B,2BAAa,OAAO,WAAW,MAAM,CAAC;AAAA,YACxC;AAAA,UACF;AACA,+BAAqB,aAAa;AAAA,QACpC;AACA,iBAAS,YAAY,IAAI;AACvB,uBAAa,QAAQ,EAAE;AAAA,QACzB;AACA,iBAAS,UAAU,IAAI;AACrB,qBAAW,QAAQ,EAAE;AAAA,QACvB;AACA,iBAAS,aAAa,IAAI;AACxB,wBAAc,QAAQ,EAAE;AAAA,QAC1B;AACA,YAAI,kBAAkB;AACtB,YAAI,uBAAuB;AAC3B,YAAI,wBAAwB;AAC5B,iBAAS,iBAAiB,IAAI;AAC5B;AACA,cAAI,OAAO,2BAA2B;AACpC,mBAAO,0BAA0B,eAAe;AAAA,UAClD;AAAA,QACF;AACA,iBAAS,oBAAoB,IAAI;AAC/B;AACA,cAAI,OAAO,2BAA2B;AACpC,mBAAO,0BAA0B,eAAe;AAAA,UAClD;AACA,cAAI,mBAAmB,GAAG;AACxB,gBAAI,yBAAyB,MAAM;AACjC,4BAAc,oBAAoB;AAClC,qCAAuB;AAAA,YACzB;AACA,gBAAI,uBAAuB;AACzB,kBAAI,WAAW;AACf,sCAAwB;AACxB,uBAAS;AAAA,YACX;AAAA,UACF;AAAA,QACF;AACA,eAAO,qBAAqB,CAAC;AAC7B,eAAO,qBAAqB,CAAC;AAC7B,iBAAS,MAAM,MAAM;AACnB,cAAI,wBAAwB;AAC1B,wBAAY,EAAE,OAAO,WAAW,OAAO,KAAK,CAAC;AAAA,UAC/C,OAAO;AACL,gBAAI,OAAO,YAAY;AACrB,qBAAO,WAAW,IAAI;AAAA,YACxB;AAAA,UACF;AACA,iBAAO,aAAa,OAAO;AAC3B,cAAI,IAAI;AACR,kBAAQ;AACR,uBAAa;AACb,kBAAQ;AACR,cAAI,KAAK,IAAI,YAAY,aAAa,IAAI;AAC1C,6BAAmB,EAAE;AACrB,gBAAM;AAAA,QACR;AACA,YAAI,gBAAgB;AACpB,iBAAS,UAAU,UAAU;AAC3B,iBAAO,SAAS,WAAW,aAAa;AAAA,QAC1C;AACA,iBAAS,UAAU,UAAU;AAC3B,iBAAO,SAAS,WAAW,SAAS;AAAA,QACtC;AACA,YAAI;AACJ,yBAAiB;AACjB,YAAI,CAAC,UAAU,cAAc,GAAG;AAC9B,2BAAiB,WAAW,cAAc;AAAA,QAC5C;AACA,iBAAS,UAAU,MAAM;AACvB,cAAI;AACF,gBAAI,QAAQ,kBAAkB,YAAY;AACxC,qBAAO,IAAI,WAAW,UAAU;AAAA,YAClC;AACA,gBAAI,YAAY;AACd,qBAAO,WAAW,IAAI;AAAA,YACxB,OAAO;AACL,oBAAM;AAAA,YACR;AAAA,UACF,SAAS,MAAP;AACA,kBAAM,IAAI;AAAA,UACZ;AAAA,QACF;AACA,iBAAS,mBAAmB;AAC1B,cAAI,CAAC,eAAe,sBAAsB,wBAAwB;AAChE,gBAAI,OAAO,UAAU,cAAc,CAAC,UAAU,cAAc,GAAG;AAC7D,qBAAO,MAAM,gBAAgB,EAAE,aAAa,cAAc,CAAC,EAAE,KAAK,SAAS,UAAU;AACnF,oBAAI,CAAC,SAAS,OAAO;AACnB,wBAAM,yCAAyC,iBAAiB;AAAA,gBAClE;AACA,uBAAO,SAAS,eAAe;AAAA,cACjC,CAAC,EAAE,MAAM,WAAW;AAClB,uBAAO,UAAU,cAAc;AAAA,cACjC,CAAC;AAAA,YACH,OAAO;AACL,kBAAI,WAAW;AACb,uBAAO,IAAI,QAAQ,SAAS,SAAS,QAAQ;AAC3C,4BAAU,gBAAgB,SAAS,UAAU;AAC3C,4BAAQ,IAAI,WAAW,QAAQ,CAAC;AAAA,kBAClC,GAAG,MAAM;AAAA,gBACX,CAAC;AAAA,cACH;AAAA,YACF;AAAA,UACF;AACA,iBAAO,QAAQ,QAAQ,EAAE,KAAK,WAAW;AACvC,mBAAO,UAAU,cAAc;AAAA,UACjC,CAAC;AAAA,QACH;AACA,iBAAS,aAAa;AACpB,cAAI,OAAO,EAAE,OAAO,eAAe,0BAA0B,cAAc;AAC3E,mBAAS,gBAAgB,UAAU,SAAS;AAC1C,gBAAI,WAAW,SAAS;AACxB,mBAAO,SAAS;AAChB,4BAAgB,OAAO,OAAO,sBAAsB;AACpD,wBAAY,OAAO,OAAO;AAC1B,sBAAU,OAAO,OAAO,oBAAoB;AAC5C,yBAAa;AACb,gBAAI,CAAC,wBAAwB;AAC3B,kBAAI,mBAAmB,QAAQ,cAAc;AAC7C,sBAAQ,cAAc,QAAQ,SAAS,GAAG;AACxC,wBAAQ,uBAAuB,GAAG,WAAW;AAC3C,sBAAI,CAAC,EAAE;AACL,wCAAoB,kBAAkB;AAAA,gBAC1C,CAAC;AAAA,cACH,CAAC;AAAA,YACH;AAAA,UACF;AACA,cAAI,CAAC,wBAAwB;AAC3B,6BAAiB,kBAAkB;AAAA,UACrC;AACA,mBAAS,2BAA2B,QAAQ;AAC1C,4BAAgB,OAAO,aAAa,OAAO,SAAS;AAAA,UACtD;AACA,mBAAS,uBAAuB,UAAU;AACxC,mBAAO,iBAAiB,EAAE,KAAK,SAAS,QAAQ;AAC9C,qBAAO,YAAY,YAAY,QAAQ,IAAI;AAAA,YAC7C,CAAC,EAAE,KAAK,SAAS,UAAU;AACzB,qBAAO;AAAA,YACT,CAAC,EAAE,KAAK,UAAU,SAAS,QAAQ;AACjC,kBAAI,4CAA4C,MAAM;AACtD,oBAAM,MAAM;AAAA,YACd,CAAC;AAAA,UACH;AACA,mBAAS,mBAAmB;AAC1B,gBAAI,CAAC,cAAc,OAAO,YAAY,yBAAyB,cAAc,CAAC,UAAU,cAAc,KAAK,CAAC,UAAU,cAAc,KAAK,OAAO,UAAU,YAAY;AACpK,qBAAO,MAAM,gBAAgB,EAAE,aAAa,cAAc,CAAC,EAAE,KAAK,SAAS,UAAU;AACnF,oBAAI,SAAS,YAAY,qBAAqB,UAAU,IAAI;AAC5D,uBAAO,OAAO,KAAK,4BAA4B,SAAS,QAAQ;AAC9D,sBAAI,oCAAoC,MAAM;AAC9C,sBAAI,2CAA2C;AAC/C,yBAAO,uBAAuB,0BAA0B;AAAA,gBAC1D,CAAC;AAAA,cACH,CAAC;AAAA,YACH,OAAO;AACL,qBAAO,uBAAuB,0BAA0B;AAAA,YAC1D;AAAA,UACF;AACA,cAAI,OAAO,oBAAoB;AAC7B,gBAAI;AACF,kBAAI,WAAW,OAAO,mBAAmB,MAAM,eAAe;AAC9D,qBAAO;AAAA,YACT,SAAS,IAAP;AACA,kBAAI,wDAAwD,EAAE;AAC9D,qBAAO;AAAA,YACT;AAAA,UACF;AACA,2BAAiB,EAAE,MAAM,kBAAkB;AAC3C,iBAAO,CAAC;AAAA,QACV;AACA,YAAI;AACJ,YAAI;AACJ,YAAI,aAAa,CAAC;AAClB,iBAAS,qBAAqB,YAAY;AACxC,iBAAO,WAAW,SAAS,GAAG;AAC5B,gBAAI,WAAW,WAAW,MAAM;AAChC,gBAAI,OAAO,YAAY,YAAY;AACjC,uBAAS,MAAM;AACf;AAAA,YACF;AACA,gBAAI,QAAQ,SAAS;AACrB,gBAAI,OAAO,UAAU,UAAU;AAC7B,kBAAI,SAAS,QAAQ,QAAQ;AAC3B,kCAAkB,KAAK,EAAE;AAAA,cAC3B,OAAO;AACL,kCAAkB,KAAK,EAAE,SAAS,GAAG;AAAA,cACvC;AAAA,YACF,OAAO;AACL,oBAAM,SAAS,QAAQ,SAAS,OAAO,SAAS,GAAG;AAAA,YACrD;AAAA,UACF;AAAA,QACF;AACA,iBAAS,cAAc,GAAG;AACxB,cAAI,SAAS,UAAU;AACvB,cAAI,MAAM,EAAE;AACZ,uBAAa,MAAM;AACnB,iBAAO;AAAA,QACT;AACA,iBAAS,SAAS,OAAO;AACvB,iBAAO;AAAA,QACT;AACA,iBAAS,YAAY,MAAM;AACzB,cAAI,QAAQ;AACZ,iBAAO,KAAK,QAAQ,OAAO,SAAS,GAAG;AACrC,gBAAI,IAAI,SAAS,CAAC;AAClB,mBAAO,MAAM,IAAI,IAAI,IAAI,OAAO,IAAI;AAAA,UACtC,CAAC;AAAA,QACH;AACA,iBAAS,WAAW,aAAa;AAC/B,4BAAkB,EAAE,eAAe,KAAK;AACxC,cAAI,UAAU,QAAQ,SAAS;AAC/B,iBAAO,QAAQ,SAAS;AACxB,kBAAQ,OAAO,UAAU;AACzB,wCAA8B,WAAW;AACzC,kBAAQ,eAAe,OAAO,QAAQ,eAAe,QAAQ,QAAQ,MAAM,GAAG,CAAC;AAC/E,kBAAQ,OAAO,UAAU;AAAA,QAC3B;AACA,iBAAS,aAAa,aAAa;AACjC,cAAI,UAAU,QAAQ,SAAS;AAC/B,kBAAQ,OAAO,YAAY,EAAE,OAAO,SAAS,CAAC;AAAA,QAChD;AACA,iBAAS,cAAc,aAAa;AAClC,cAAI,UAAU,QAAQ,SAAS;AAC/B,cAAI,SAAS;AACX,8BAAkB,EAAE,eAAe,KAAK;AACxC,gBAAI,SAAS,QAAQ;AACrB,oBAAQ,mBAAmB,MAAM;AAAA,UACnC;AAAA,QACF;AACA,iBAAS,MAAM,QAAQ;AACrB,eAAK,MAAM;AAAA,QACb;AACA,iBAAS,gBAAgB,IAAI;AAC3B,cAAI,cAAc,cAAc,MAAM,UAAU;AAC9C,mBAAO;AAAA,UACT;AACA,gBAAM,GAAG,EAAE;AAAA,QACb;AACA,YAAI,UAAU,EAAE,eAAe,CAAC,GAAG,gBAAgB,CAAC,GAAG,kBAAkB,CAAC,GAAG,MAAM,WAAW;AAC5F,cAAI,wBAAwB;AAC1B,oBAAQ,WAAW;AAAA,UACrB,OAAO;AACL,oBAAQ,eAAe;AAAA,UACzB;AAAA,QACF,GAAG,gBAAgB,WAAW;AAC5B,cAAI,kBAAkB;AACtB,mBAAS,KAAK,GAAG,KAAK,iBAAiB,EAAE,IAAI;AAC3C,oBAAQ,qBAAqB;AAAA,UAC/B;AAAA,QACF,GAAG,YAAY,WAAW;AACxB,0BAAgB;AAAA,QAClB,GAAG,UAAU,CAAC,GAAG,eAAe,SAAS,QAAQ;AAC/C,uBAAa;AAAA,QACf,GAAG,qBAAqB,WAAW;AACjC,mBAAS,MAAM,QAAQ,UAAU;AAC/B,gBAAI,UAAU,QAAQ,SAAS;AAC/B,gBAAI,WAAW,QAAQ,QAAQ;AAC7B,sBAAQ,mBAAmB,QAAQ,MAAM;AAAA,YAC3C;AAAA,UACF;AACA,mBAAS,KAAK,GAAG,KAAK,QAAQ,cAAc,QAAQ,EAAE,IAAI;AACxD,gBAAI,SAAS,QAAQ,cAAc;AACnC,mBAAO,UAAU;AAAA,UACnB;AACA,kBAAQ,gBAAgB,CAAC;AAAA,QAC3B,GAAG,oBAAoB,SAAS,QAAQ;AACtC,kBAAQ,gCAAgC,WAAW;AACjD,mBAAO,QAAQ,SAAS,OAAO,QAAQ;AACvC,oBAAQ,cAAc,KAAK,MAAM;AACjC,oBAAQ,eAAe,OAAO,QAAQ,eAAe,QAAQ,MAAM,GAAG,CAAC;AACvE,0CAA8B,OAAO,QAAQ,gBAAgB;AAC7D,mBAAO,UAAU;AAAA,UACnB,CAAC;AAAA,QACH,GAAG,iCAAiC,SAAS,OAAO;AAClD,4BAAkB,EAAE,gDAAgD,KAAK;AACzE,cAAI;AACF,kBAAM;AAAA,UACR,UAAE;AACA,8BAAkB,EAAE,gDAAgD,KAAK;AAAA,UAC3E;AAAA,QACF,GAAG,uBAAuB,SAAS,MAAM;AAAA,QACzC,GAAG,YAAY,WAAW;AACxB,mBAAS,MAAM,QAAQ,kBAAkB;AACvC,oBAAQ,iBAAiB,IAAI;AAAA,UAC/B;AAAA,QACF,GAAG,wBAAwB,SAAS,QAAQ,mBAAmB;AAC7D,iBAAO,YAAY,CAAC,OAAO;AACzB,gBAAI,IAAI,GAAG;AACX,gBAAI,MAAM,EAAE;AACZ,gBAAI,OAAO;AACT,sBAAQ,sCAAsC,OAAO,QAAQ;AAC/D,gBAAI,EAAE,mBAAmB,EAAE,mBAAmB,cAAc,GAAG;AAC7D,kBAAI,SAAS,QAAQ,SAAS,EAAE;AAChC,kBAAI,QAAQ;AACV,uBAAO,OAAO,YAAY,GAAG,EAAE,eAAe;AAAA,cAChD,OAAO;AACL,oBAAI,4CAA4C,MAAM,yBAAyB,EAAE,kBAAkB,qCAAqC;AAAA,cAC1I;AACA,sBAAQ,sCAAsC;AAC9C;AAAA,YACF;AACA,gBAAI,QAAQ,+BAA+B;AACzC,2DAA6C;AAAA,YAC/C,WAAW,QAAQ,eAAe;AAChC,0BAAY,CAAC;AAAA,YACf,WAAW,QAAQ,iBAAiB;AAClC,4BAAc,EAAE,SAAS;AAAA,YAC3B,WAAW,QAAQ,cAAc;AAC/B,yBAAW,EAAE,SAAS;AAAA,YACxB,WAAW,QAAQ,gBAAgB;AACjC,2BAAa,EAAE,SAAS;AAAA,YAC1B,WAAW,QAAQ,UAAU;AAC3B,qBAAO,SAAS;AAChB,kBAAI;AACF,kCAAkB,MAAM;AAC1B,kBAAI,OAAO,YAAY;AACrB,uBAAO,WAAW;AAClB,uBAAO,OAAO;AAAA,cAChB;AAAA,YACF,WAAW,QAAQ,SAAS;AAC1B,kBAAI,YAAY,EAAE,cAAc,OAAO,EAAE,OAAO;AAAA,YAClD,WAAW,QAAQ,YAAY;AAC7B,kBAAI,YAAY,EAAE,cAAc,OAAO,EAAE,OAAO;AAAA,YAClD,WAAW,QAAQ,SAAS;AAC1B,oBAAM,YAAY,EAAE,cAAc,OAAO,EAAE,OAAO;AAAA,YACpD,WAAW,EAAE,WAAW,gBAAgB;AACtC,qBAAO,YAAY,CAAC;AAAA,YACtB,WAAW,QAAQ,WAAW;AAC5B,kBAAI,OAAO,YAAY;AACrB,uBAAO,WAAW,EAAE,MAAM;AAAA,cAC5B;AAAA,YACF,OAAO;AACL,kBAAI,oCAAoC,GAAG;AAAA,YAC7C;AACA,oBAAQ,sCAAsC;AAAA,UAChD;AACA,iBAAO,UAAU,CAAC,OAAO;AACvB,gBAAI,UAAU;AACd,gBAAI,UAAU,MAAM,GAAG,WAAW,MAAM,GAAG,SAAS,OAAO,GAAG,OAAO;AACrE,kBAAM;AAAA,UACR;AACA,cAAI,qBAAqB;AACvB,mBAAO,GAAG,WAAW,SAAS,MAAM;AAClC,qBAAO,UAAU,EAAE,KAAK,CAAC;AAAA,YAC3B,CAAC;AACD,mBAAO,GAAG,SAAS,SAAS,IAAI;AAC9B,qBAAO,QAAQ,EAAE;AAAA,YACnB,CAAC;AACD,mBAAO,GAAG,gBAAgB,WAAW;AAAA,YACrC,CAAC;AAAA,UACH;AACA,iBAAO,YAAY,EAAE,OAAO,QAAQ,aAAa,OAAO,0BAA0B,YAAY,cAAc,YAAY,cAAc,WAAW,CAAC;AAAA,QACpJ,GAAG,sBAAsB,WAAW;AAClC,cAAI,gBAAgB,WAAW,2CAA2C;AAC1E,kBAAQ,cAAc,KAAK,IAAI,OAAO,aAAa,CAAC;AAAA,QACtD,GAAG,cAAc,WAAW;AAC1B,cAAI,QAAQ,cAAc,UAAU,GAAG;AACrC,oBAAQ,qBAAqB;AAC7B,oBAAQ,uBAAuB,QAAQ,cAAc,EAAE;AAAA,UACzD;AACA,iBAAO,QAAQ,cAAc,IAAI;AAAA,QACnC,EAAE;AACF,iBAAS,sBAAsB;AAC7B,cAAI,cAAc,cAAc;AAChC,cAAI,WAAW,kBAAkB,EAAE,cAAc,MAAM;AACvD,cAAI,YAAY,kBAAkB,EAAE,cAAc,MAAM;AACxD,cAAI,WAAW,WAAW;AAC1B,uCAA6B,UAAU,QAAQ;AAC/C,uBAAa,QAAQ;AAAA,QACvB;AACA,eAAO,yBAAyB;AAChC,iBAAS,iBAAiB,YAAY;AACpC,cAAI;AACF,mBAAO,oCAAoC,GAAG,GAAG,UAAU;AAC7D,cAAI;AACF,kBAAM,UAAU;AAAA,UAClB,SAAS,IAAP;AACA,4BAAgB,EAAE;AAAA,UACpB;AAAA,QACF;AACA,YAAI,kBAAkB,CAAC;AACvB,iBAAS,kBAAkB,SAAS;AAClC,cAAI,QAAQ,gBAAgB;AAC5B,cAAI,CAAC,OAAO;AACV,gBAAI,WAAW,gBAAgB;AAC7B,8BAAgB,SAAS,UAAU;AACrC,4BAAgB,WAAW,QAAQ,UAAU,IAAI,OAAO;AAAA,UAC1D;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,iBAAiB,KAAK,KAAK;AAClC,iBAAO,kBAAkB,GAAG,EAAE,GAAG;AAAA,QACnC;AACA,eAAO,sBAAsB;AAC7B,iBAAS,eAAe;AACtB,cAAI,QAAQ,IAAI,MAAM;AACtB,cAAI,CAAC,MAAM,OAAO;AAChB,gBAAI;AACF,oBAAM,IAAI,MAAM;AAAA,YAClB,SAAS,IAAP;AACA,sBAAQ;AAAA,YACV;AACA,gBAAI,CAAC,MAAM,OAAO;AAChB,qBAAO;AAAA,YACT;AAAA,UACF;AACA,iBAAO,MAAM,MAAM,SAAS;AAAA,QAC9B;AACA,iBAAS,gBAAgB,aAAa,eAAe,UAAU;AAC7D,kBAAQ,iBAAiB,KAAK,WAAW;AAAA,QAC3C;AACA,iBAAS,kBAAkB,KAAK,OAAO;AACrC,oBAAU,IAAI,KAAK,KAAK;AACxB,0BAAgB,OAAO;AAAA,QACzB;AACA,YAAI;AACJ,YAAI,qBAAqB;AACvB,gCAAsB,MAAM;AAC1B,gBAAI,KAAK,QAAQ,UAAU;AAC3B,mBAAO,GAAG,KAAK,MAAM,GAAG,KAAK;AAAA,UAC/B;AAAA,QACF,WAAW,wBAAwB;AACjC,gCAAsB,MAAM,YAAY,IAAI,IAAI,OAAO;AAAA,QACzD;AACE,gCAAsB,MAAM,YAAY,IAAI;AAC9C,YAAI,mCAAmC;AACvC,iBAAS,SAAS,OAAO;AACvB,4BAAkB,EAAE,kBAAkB,KAAK,KAAK;AAChD,iBAAO;AAAA,QACT;AACA,iBAAS,eAAe,QAAQ,IAAI;AAClC,cAAIC;AACJ,cAAI,WAAW,GAAG;AAChB,YAAAA,QAAO,KAAK,IAAI;AAAA,UAClB,YAAY,WAAW,KAAK,WAAW,MAAM,kCAAkC;AAC7E,YAAAA,QAAO,oBAAoB;AAAA,UAC7B,OAAO;AACL,qBAAS,EAAE;AACX,mBAAO;AAAA,UACT;AACA,4BAAkB,EAAE,MAAM,KAAKA,QAAO,MAAM;AAC5C,4BAAkB,EAAE,KAAK,KAAK,KAAKA,QAAO,MAAM,MAAM,MAAM;AAC5D,iBAAO;AAAA,QACT;AACA,iBAAS,iBAAiB,IAAI,KAAK;AACjC,iBAAO,eAAe,IAAI,GAAG;AAAA,QAC/B;AACA,iBAAS,kCAAkC,IAAI;AAC7C,mCAAyB,IAAI,CAAC,uBAAuB,GAAG,CAAC,kBAAkB;AAC3E,kBAAQ,WAAW;AAAA,QACrB;AACA,iBAAS,6BAA6B,QAAQ;AAC5C,cAAI,CAAC;AACH,0BAAc,MAAM;AAAA;AAEpB,wBAAY,EAAE,OAAO,iBAAiB,UAAU,OAAO,CAAC;AAAA,QAC5D;AACA,iBAAS,YAAY,cAAc;AACjC,cAAI,SAAS,QAAQ,aAAa;AAClC,cAAI,CAAC,QAAQ;AACX,mBAAO;AAAA,UACT;AACA,kBAAQ,eAAe,KAAK,MAAM;AAClC,cAAI,UAAU,QAAQ,SAAS,aAAa,eAAe,EAAE,QAAQ,kBAAkB,aAAa,YAAY;AAChH,iBAAO,UAAU;AACjB,cAAI,MAAM,EAAE,OAAO,OAAO,iBAAiB,aAAa,cAAc,OAAO,aAAa,KAAK,oBAAoB,aAAa,YAAY;AAC5I,iBAAO,aAAa,MAAM;AACxB,gBAAI,OAAO,YAAY,IAAI;AAC3B,mBAAO,YAAY,KAAK,aAAa,YAAY;AAAA,UACnD;AACA,cAAI,OAAO,QAAQ;AACjB,mBAAO,WAAW;AAClB,mBAAO,OAAO;AAAA,UAChB;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,qBAAqB,aAAa,MAAM,eAAe,KAAK;AACnE,cAAI,OAAO,sBAAsB,aAAa;AAC5C,gBAAI,qFAAqF;AACzF,mBAAO;AAAA,UACT;AACA,cAAI,eAAe,CAAC;AACpB,cAAI,QAAQ;AACZ,cAAI,2BAA2B,aAAa,WAAW,KAAK,QAAQ;AAClE,mBAAO,sCAAsC,WAAW,aAAa,MAAM,eAAe,GAAG;AAAA,UAC/F;AACA,cAAI;AACF,mBAAO;AACT,cAAI,eAAe,EAAE,cAAc,eAAe,aAAa,KAAK,aAAa;AACjF,cAAI,wBAAwB;AAC1B,yBAAa,MAAM;AACnB,wBAAY,cAAc,YAAY;AACtC,mBAAO;AAAA,UACT;AACA,iBAAO,YAAY,YAAY;AAAA,QACjC;AACA,iBAAS,0CAA0C;AACjD,iBAAO;AAAA,QACT;AACA,iBAAS,iCAAiC,gBAAgB,cAAc;AACtE,cAAI,kBAAkB,cAAc;AAClC,wBAAY,EAAE,OAAO,8BAA8B,CAAC;AAAA,UACtD,WAAW,wBAAwB;AACjC,wBAAY,EAAE,gBAAgB,gBAAgB,OAAO,qBAAqB,CAAC;AAAA,UAC7E,OAAO;AACL,gBAAI,UAAU,QAAQ,SAAS;AAC/B,gBAAI,SAAS,WAAW,QAAQ;AAChC,gBAAI,CAAC,QAAQ;AACX;AAAA,YACF;AACA,mBAAO,YAAY,EAAE,OAAO,qBAAqB,CAAC;AAAA,UACpD;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,SAAS;AAChB,gBAAM,EAAE;AAAA,QACV;AACA,iBAAS,qCAAqC;AAC5C,cAAI;AACF;AACF,cAAI;AACF;AACF,mBAAS,0IAA0I;AAAA,QACrJ;AACA,iBAAS,2BAA2B;AAClC,iBAAO;AAAA,QACT;AACA,iBAAS,uBAAuB,MAAM,KAAK,KAAK;AAC9C,2BAAiB,EAAE,WAAW,MAAM,KAAK,MAAM,GAAG;AAAA,QACpD;AACA,iBAAS,gCAAgC;AACvC,cAAI;AACF,mBAAO,WAAW,EAAE,KAAK,EAAE;AAC7B,iBAAO,UAAU;AAAA,QACnB;AACA,iBAAS,oCAAoCC,QAAO,MAAM;AACxD,cAAI,cAAc,UAAU,SAAS;AACrC,cAAI,YAAY;AAChB,iBAAO,cAAc,WAAW;AAC9B,gBAAI,wBAAwB;AAC5B,gBAAI,OAAO,WAAW,wBAAwB,CAAC;AAC/C,gBAAI,IAAI,QAAQ;AAChB,qBAAS,KAAK,GAAG,KAAK,aAAa,MAAM;AACvC,kBAAI,MAAM,UAAU,IAAI;AACxB,gCAAkB,EAAE,IAAI,MAAM;AAAA,YAChC;AACA,mBAAO,0CAA0CA,QAAO,uBAAuB,MAAM,IAAI;AAAA,UAC3F,CAAC;AAAA,QACH;AACA,YAAI,iDAAiD,CAAC;AACtD,iBAAS,sCAAsCA,QAAO,aAAa,MAAM;AACvE,yDAA+C,SAAS;AACxD,cAAI,IAAI,QAAQ;AAChB,mBAAS,KAAK,GAAG,KAAK,aAAa,MAAM;AACvC,2DAA+C,MAAM,kBAAkB,EAAE,IAAI;AAAA,UAC/E;AACA,cAAI,eAAeA,SAAQ;AAC3B,cAAI,QAAQ,CAAC,eAAe,qBAAqBA,UAAS,WAAW,CAACA,SAAQ;AAC9E,iBAAO,MAAM,MAAM,MAAM,8CAA8C;AAAA,QACzE;AACA,iBAAS,0BAA0BT,OAAM;AACvC,cAAI;AACF,uBAAW,KAAKA,QAAO,QAAQ,aAAa,UAAU,EAAE;AACxD,uCAA2B,WAAW,MAAM;AAC5C,mBAAO;AAAA,UACT,SAAS,IAAP;AAAA,UACF;AAAA,QACF;AACA,iBAAS,wBAAwB,eAAe;AAC9C,cAAI,UAAU,iBAAiB,EAAE;AACjC,0BAAgB,kBAAkB;AAClC,cAAI,iBAAiB,SAAS;AAC5B,mBAAO;AAAA,UACT;AACA,cAAI,cAAc,yBAAyB;AAC3C,cAAI,gBAAgB,aAAa;AAC/B,mBAAO;AAAA,UACT;AACA,mBAAS,UAAU,GAAG,WAAW,GAAG,WAAW,GAAG;AAChD,gBAAI,oBAAoB,WAAW,IAAI,MAAM;AAC7C,gCAAoB,KAAK,IAAI,mBAAmB,gBAAgB,SAAS;AACzE,gBAAI,UAAU,KAAK,IAAI,aAAa,QAAQ,KAAK,IAAI,eAAe,iBAAiB,GAAG,KAAK,CAAC;AAC9F,gBAAI,cAAc,0BAA0B,OAAO;AACnD,gBAAI,aAAa;AACf,qBAAO;AAAA,YACT;AAAA,UACF;AACA,iBAAO;AAAA,QACT;AACA,YAAI,WAAW,EAAE,gBAAgB,GAAG,yBAAyB,WAAW;AACtE,mBAAS,KAAK,SAAS,cAAc,SAAS,GAAG,MAAM,GAAG,EAAE,IAAI;AAC9D,qBAAS,eAAe,EAAE;AAAA,UAC5B;AACA,mBAAS,gBAAgB,CAAC;AAC1B,mBAAS,gBAAgB,CAAC;AAAA,QAC5B,GAAG,8BAA8B,WAAW;AAC1C,cAAI,CAAC,SAAS,gCAAgC;AAC5C,uBAAW,KAAK,SAAS,uBAAuB;AAChD,qBAAS,iCAAiC;AAAA,UAC5C;AAAA,QACF,GAAG,eAAe,CAAC,GAAG,WAAW,SAAS,gBAAgB,YAAY,UAAU;AAC9E,mBAAS,uBAAuB,MAAM,MAAM;AAC1C,gBAAI,KAAK,UAAU,KAAK;AACtB,qBAAO;AACT,qBAAS,MAAM,MAAM;AACnB,kBAAI,KAAK,OAAO,KAAK;AACnB,uBAAO;AAAA,YACX;AACA,mBAAO;AAAA,UACT;AACA,mBAAS,MAAM,SAAS,eAAe;AACrC,gBAAI,OAAO,SAAS,cAAc;AAClC,gBAAI,KAAK,kBAAkB,kBAAkB,uBAAuB,KAAK,UAAU,QAAQ,GAAG;AAC5F;AAAA,YACF;AAAA,UACF;AACA,mBAAS,cAAc,KAAK,EAAE,gBAAgB,YAAY,SAAS,CAAC;AACpE,mBAAS,cAAc,KAAK,SAAS,GAAG,GAAG;AACzC,mBAAO,EAAE,aAAa,EAAE;AAAA,UAC1B,CAAC;AAAA,QACH,GAAG,qBAAqB,SAAS,gBAAgB;AAC/C,mBAAS,KAAK,GAAG,KAAK,SAAS,cAAc,QAAQ,EAAE,IAAI;AACzD,gBAAI,SAAS,cAAc,IAAI,kBAAkB,gBAAgB;AAC/D,uBAAS,cAAc,OAAO,IAAI,CAAC;AACnC,gBAAE;AAAA,YACJ;AAAA,UACF;AAAA,QACF,GAAG,gCAAgC,WAAW;AAC5C,iBAAO,SAAS,kBAAkB,SAAS,oBAAoB;AAAA,QACjE,GAAG,kBAAkB,WAAW;AAC9B,cAAI,CAAC,SAAS,+BAA+B,GAAG;AAC9C;AAAA,UACF;AACA,mBAAS,KAAK,GAAG,KAAK,SAAS,cAAc,QAAQ,EAAE,IAAI;AACzD,gBAAI,OAAO,SAAS,cAAc;AAClC,qBAAS,cAAc,OAAO,IAAI,CAAC;AACnC,cAAE;AACF,iBAAK,eAAe,MAAM,MAAM,KAAK,QAAQ;AAAA,UAC/C;AAAA,QACF,GAAG,eAAe,CAAC,GAAG,2BAA2B,SAAS,QAAQ,iBAAiB;AACjF,mBAAS,KAAK,GAAG,KAAK,SAAS,cAAc,QAAQ,EAAE,IAAI;AACzD,gBAAI,SAAS,cAAc,IAAI,UAAU,WAAW,CAAC,mBAAmB,mBAAmB,SAAS,cAAc,IAAI,kBAAkB;AACtI,uBAAS,eAAe,IAAI;AAAA,YAC9B;AAAA,UACF;AAAA,QACF,GAAG,gBAAgB,SAAS,IAAI;AAC9B,cAAI,IAAI,SAAS,cAAc;AAC/B,YAAE,OAAO,oBAAoB,EAAE,iBAAiB,EAAE,mBAAmB,EAAE,UAAU;AACjF,mBAAS,cAAc,OAAO,IAAI,CAAC;AAAA,QACrC,GAAG,yBAAyB,SAAS,cAAc;AACjD,cAAI,iBAAiB,SAAS,gBAAgB,OAAO;AACnD,cAAE,SAAS;AACX,qBAAS,sBAAsB;AAC/B,qBAAS,iBAAiB;AAC1B,yBAAa,YAAY,KAAK;AAC9B,qBAAS,iBAAiB;AAC1B,cAAE,SAAS;AAAA,UACb;AACA,cAAI,aAAa,cAAc;AAC7B,yBAAa,oBAAoB;AACjC,yBAAa,OAAO,iBAAiB,aAAa,iBAAiB,gBAAgB,aAAa,UAAU;AAC1G,qBAAS,cAAc,KAAK,YAAY;AACxC,qBAAS,6BAA6B;AAAA,UACxC,OAAO;AACL,qBAAS,KAAK,GAAG,KAAK,SAAS,cAAc,QAAQ,EAAE,IAAI;AACzD,kBAAI,SAAS,cAAc,IAAI,UAAU,aAAa,UAAU,SAAS,cAAc,IAAI,mBAAmB,aAAa,iBAAiB;AAC1I,yBAAS,eAAe,IAAI;AAAA,cAC9B;AAAA,YACF;AAAA,UACF;AAAA,QACF,GAAG,gCAAgC,SAAS,cAAc,kBAAkB,aAAa,WAAW,UAAU;AAC5G,wBAAc,WAAW;AACvB,gBAAI,UAAU,WAAW,EAAE;AAC3B,8BAAkB,EAAE,WAAW,KAAK;AACpC,8BAAkB,EAAE,UAAU,KAAK,KAAK;AACxC,8BAAkB,EAAE,UAAU,KAAK,KAAK;AACxC,4CAAgC,cAAc,WAAW,kBAAkB,WAAW,OAAO;AAAA,UAC/F,CAAC;AAAA,QACH,GAAG,iCAAiC,SAAS,cAAc;AACzD,kBAAQ;AAAA,iBACD;AACH,qBAAO;AAAA,iBACJ;AACH,qBAAO,QAAQ;AAAA;AAEf,qBAAO;AAAA;AAAA,QAEb,GAAG,sBAAsB,SAAS,QAAQ;AACxC,cAAI,CAAC;AACH,mBAAO;AACT,cAAI,UAAU;AACZ,mBAAO;AACT,cAAI,UAAU;AACZ,mBAAO;AACT,iBAAO,UAAU,OAAO,WAAW,OAAO,WAAW;AAAA,QACvD,GAAG,mBAAmB,WAAW;AAC/B,iBAAO,SAAS,qBAAqB,SAAS;AAAA,QAChD,EAAE;AACF,iBAAS,gBAAgB,UAAU;AACjC,cAAI,SAAS,gBAAgB,QAAQ,IAAI;AACzC,cAAI,UAAU,QAAQ,MAAM;AAC5B,uBAAa,UAAU,SAAS,MAAM;AACtC,iBAAO;AAAA,QACT;AACA,iBAAS,yDAAyD,cAAc,cAAc,OAAO,QAAQ;AAC3G,wBAAc,WAAW;AACvB,gBAAI,UAAU,WAAW,EAAE;AAC3B,gBAAI,kBAAkB;AACtB,gBAAI,cAAc;AAChB,gCAAkB,gBAAgB,YAAY;AAAA,YAChD;AACA,8BAAkB,EAAE,WAAW,KAAK;AACpC,8BAAkB,EAAE,UAAU,KAAK,KAAK;AACxC,8BAAkB,EAAE,UAAU,KAAK,KAAK;AACxC,4CAAgC,cAAc,WAAW,GAAG,iBAAiB,OAAO;AAAA,UACtF,CAAC;AAAA,QACH;AACA,iBAAS,sDAAsD,cAAc,cAAc,OAAO,QAAQ;AACxG,yBAAe,eAAe,aAAa,YAAY,IAAI;AAC3D,mEAAyD,cAAc,cAAc,OAAO,MAAM;AAAA,QACpG;AACA,iBAAS,uBAAuB,SAAS;AACvC,iBAAO,UAAU,IAAI,aAAa,OAAO,IAAI;AAAA,QAC/C;AACA,YAAI,qBAAqB,CAAC,GAAG,OAAO,aAAa,cAAc,WAAW,GAAG,OAAO,WAAW,cAAc,SAAS,CAAC;AACvH,iBAAS,gBAAgB,QAAQ;AAC/B,mBAAS,uBAAuB,MAAM;AACtC,cAAI,aAAa,mBAAmB,YAAY,OAAO,aAAa,cAAc,SAAS,cAAc,MAAM,IAAI;AACnH,iBAAO;AAAA,QACT;AACA,iBAAS,sBAAsB,QAAQ;AACrC,iBAAO,gBAAgB,MAAM;AAAA,QAC/B;AACA,iBAAS,mDAAmD,QAAQ,OAAO,QAAQ;AACjF,cAAIU,UAAS,sBAAsB,MAAM;AACzC,cAAI,CAACA;AACH,mBAAO;AACT,cAAIA,QAAO,iBAAiB;AAC1B,8BAAkB,EAAEA,QAAO,mBAAmB,KAAK;AACnD,8BAAkB,EAAEA,QAAO,kBAAkB,KAAK,KAAK;AAAA,UACzD;AACA,cAAIA,QAAO,mBAAmB,CAACA,QAAO,6BAA6B;AACjE,gBAAIA,QAAO;AACT,cAAAA,UAASA,QAAO;AAClB,gBAAI,qBAAqB;AACzB,gBAAIA,QAAO,eAAeA,QAAO,YAAY,OAAO;AAClD,kBAAI,eAAeA,QAAO,YAAY,MAAM,aAAa,IAAI;AAC7D,mCAAqB,aAAa,OAAO,KAAK,aAAa,OAAO,KAAK,aAAa,OAAOA,QAAO,SAAS,aAAa,OAAOA,QAAO;AAAA,YACxI;AACA,YAAAA,QAAO,QAAQ;AACf,YAAAA,QAAO,SAAS;AAChB,gBAAI,oBAAoB;AACtB,cAAAA,QAAO,YAAY,MAAM,SAAS,GAAG,GAAG,OAAO,MAAM;AAAA,YACvD;AAAA,UACF,WAAWA,QAAO,iBAAiB;AACjC,gBAAI,eAAe,kBAAkB,EAAEA,QAAO,kBAAkB,KAAK;AACrE,kEAAsD,cAAc,QAAQ,OAAO,MAAM;AACzF,mBAAO;AAAA,UACT,OAAO;AACL,mBAAO;AAAA,UACT;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,gDAAgD,QAAQ,OAAO,QAAQ;AAC9E,cAAI;AACF,mBAAO,oCAAoC,GAAG,GAAG,QAAQ,OAAO,MAAM;AACxE,iBAAO,mDAAmD,QAAQ,OAAO,MAAM;AAAA,QACjF;AACA,iBAAS,oCAAoC,QAAQ,OAAO,QAAQ;AAClE,cAAIA,UAAS,sBAAsB,MAAM;AACzC,cAAIA,SAAQ;AACV,mBAAO,mDAAmD,QAAQ,OAAO,MAAM;AAAA,UACjF,OAAO;AACL,mBAAO,gDAAgD,QAAQ,OAAO,MAAM;AAAA,UAC9E;AAAA,QACF;AACA,iBAAS,sCAAsC;AAC7C,gBAAM;AAAA,QACR;AACA,iBAAS,sCAAsC,KAAK;AAClD,cAAI,MAAM,IAAI,aAAa,wBAAwB;AACnD,cAAI,KAAK;AACP,gBAAI,yBAAyB,SAASD,QAAO,SAAS;AACpD,kBAAI,4BAA4BA,QAAO,OAAO;AAAA,YAChD;AACA,gBAAI,yBAAyB,SAAS,MAAM,OAAOF,SAAQ,WAAW;AACpE,kBAAI,4BAA4B,MAAM,OAAOA,SAAQ,SAAS;AAAA,YAChE;AACA,gBAAI,2BAA2B,SAAS,MAAMA,SAAQ,MAAM,SAAS,WAAW;AAC9E,kBAAI,8BAA8B,MAAMA,SAAQ,MAAM,SAAS,SAAS;AAAA,YAC1E;AACA,mBAAO;AAAA,UACT;AAAA,QACF;AACA,iBAAS,uCAAuC,KAAK;AACnD,cAAI,MAAM,IAAI,aAAa,yBAAyB;AACpD,cAAI,KAAK;AACP,gBAAI,uBAAuB,WAAW;AACpC,qBAAO,IAAI,wBAAwB;AAAA,YACrC;AACA,gBAAI,uBAAuB,SAAS,KAAK;AACvC,kBAAI,wBAAwB,GAAG;AAAA,YACjC;AACA,gBAAI,qBAAqB,SAAS,KAAK;AACrC,kBAAI,sBAAsB,GAAG;AAAA,YAC/B;AACA,gBAAI,mBAAmB,SAAS,KAAK;AACnC,qBAAO,IAAI,oBAAoB,GAAG;AAAA,YACpC;AACA,mBAAO;AAAA,UACT;AAAA,QACF;AACA,iBAAS,kCAAkC,KAAK;AAC9C,cAAI,MAAM,IAAI,aAAa,oBAAoB;AAC/C,cAAI,KAAK;AACP,gBAAI,iBAAiB,SAAS,IAAI,MAAM;AACtC,kBAAI,oBAAoB,IAAI,IAAI;AAAA,YAClC;AACA,mBAAO;AAAA,UACT;AAAA,QACF;AACA,iBAAS,gCAAgC,KAAK;AAC5C,iBAAO,CAAC,EAAE,IAAI,iBAAiB,IAAI,aAAa,kBAAkB;AAAA,QACpE;AACA,YAAI,KAAK,EAAE,SAAS,GAAG,SAAS,CAAC,GAAG,UAAU,CAAC,GAAG,cAAc,CAAC,GAAG,eAAe,CAAC,GAAG,UAAU,CAAC,GAAG,SAAS,CAAC,GAAG,MAAM,CAAC,GAAG,UAAU,CAAC,GAAG,mBAAmB,CAAC,GAAG,SAAS,CAAC,GAAG,aAAa,CAAC,GAAG,iBAAiB,GAAG,aAAa,SAAS,YAAY,WAAW;AAC9P,cAAI,CAAC,GAAG,WAAW;AACjB,eAAG,YAAY;AAAA,UACjB;AAAA,QACF,GAAG,UAAU,SAAS,OAAO;AAC3B,cAAI,MAAM,GAAG;AACb,mBAAS,KAAK,MAAM,QAAQ,KAAK,KAAK,MAAM;AAC1C,kBAAM,MAAM;AAAA,UACd;AACA,iBAAO;AAAA,QACT,GAAG,WAAW,SAAS,QAAQA,SAAQ,SAAS,QAAQ;AACtD,cAAI,SAAS;AACb,mBAAS,KAAK,GAAG,KAAKA,SAAQ,EAAE,IAAI;AAClC,gBAAI,MAAM,SAAS,kBAAkB,EAAE,SAAS,KAAK,KAAK,KAAK;AAC/D,sBAAU,aAAa,kBAAkB,EAAE,UAAU,KAAK,KAAK,IAAI,MAAM,IAAI,SAAS,GAAG;AAAA,UAC3F;AACA,iBAAO;AAAA,QACT,GAAG,eAAe,SAASG,SAAQ,wBAAwB;AACzD,cAAI,CAACA,QAAO,6BAA6B;AACvC,YAAAA,QAAO,8BAA8BA,QAAO;AAC5C,YAAAA,QAAO,aAAa,SAAS,KAAK,OAAO;AACvC,kBAAI,KAAKA,QAAO,4BAA4B,KAAK,KAAK;AACtD,qBAAO,OAAO,WAAW,cAAc,wBAAwB,KAAK;AAAA,YACtE;AAAA,UACF;AACA,cAAI,MAAMA,QAAO,WAAW,SAAS,sBAAsB;AAC3D,cAAI,CAAC;AACH,mBAAO;AACT,cAAI,SAAS,GAAG,gBAAgB,KAAK,sBAAsB;AAC3D,iBAAO;AAAA,QACT,GAAG,iBAAiB,SAAS,KAAK,wBAAwB;AACxD,cAAI,SAAS,QAAQ,CAAC;AACtB,4BAAkB,EAAE,SAAS,KAAK,KAAK,cAAc;AACrD,cAAI,UAAU,EAAE,QAAQ,YAAY,wBAAwB,SAAS,uBAAuB,cAAc,OAAO,IAAI;AACrH,cAAI,IAAI;AACN,gBAAI,OAAO,cAAc;AAC3B,aAAG,SAAS,UAAU;AACtB,cAAI,OAAO,uBAAuB,8BAA8B,eAAe,uBAAuB,2BAA2B;AAC/H,eAAG,eAAe,OAAO;AAAA,UAC3B;AACA,iBAAO;AAAA,QACT,GAAG,oBAAoB,SAAS,eAAe;AAC7C,aAAG,iBAAiB,GAAG,SAAS;AAChC,iBAAO,MAAM,QAAQ,GAAG,kBAAkB,GAAG,eAAe;AAC5D,iBAAO,EAAE,iBAAiB,CAAC;AAAA,QAC7B,GAAG,YAAY,SAAS,eAAe;AACrC,iBAAO,GAAG,SAAS;AAAA,QACrB,GAAG,eAAe,SAAS,eAAe;AACxC,cAAI,GAAG,mBAAmB,GAAG,SAAS;AACpC,eAAG,iBAAiB;AACtB,cAAI,OAAO,aAAa;AACtB,qBAAS,0BAA0B,GAAG,SAAS,eAAe,MAAM,MAAM;AAC5E,cAAI,GAAG,SAAS,kBAAkB,GAAG,SAAS,eAAe,MAAM;AACjE,eAAG,SAAS,eAAe,MAAM,OAAO,cAAc;AACxD,gBAAM,GAAG,SAAS,eAAe,MAAM;AACvC,aAAG,SAAS,iBAAiB;AAAA,QAC/B,GAAG,gBAAgB,SAAS,SAAS;AACnC,cAAI,CAAC;AACH,sBAAU,GAAG;AACf,cAAI,QAAQ;AACV;AACF,kBAAQ,qBAAqB;AAC7B,cAAI,SAAS,QAAQ;AACrB,gDAAsC,MAAM;AAC5C,iDAAuC,MAAM;AAC7C,4CAAkC,MAAM;AACxC;AACE,mBAAO,wBAAwB,OAAO,aAAa,0BAA0B;AAAA,UAC/E;AACA,0CAAgC,MAAM;AACtC,cAAI,OAAO,OAAO,uBAAuB,KAAK,CAAC;AAC/C,eAAK,QAAQ,SAAS,KAAK;AACzB,gBAAI,CAAC,IAAI,SAAS,cAAc,KAAK,CAAC,IAAI,SAAS,OAAO,GAAG;AAC3D,qBAAO,aAAa,GAAG;AAAA,YACzB;AAAA,UACF,CAAC;AAAA,QACH,EAAE;AACF,YAAI,uCAAuC,CAAC,WAAW,aAAa,kBAAkB;AACtF,iBAAS,oCAAoC,QAAQ,YAAY;AAC/D,cAAI,IAAI,cAAc;AACtB,cAAI,kBAAkB,kBAAkB,EAAE,KAAK,MAAM;AACrD,cAAI,oBAAoB,EAAE,SAAS,CAAC,CAAC,kBAAkB,EAAE,KAAK,KAAK,KAAK,SAAS,CAAC,CAAC,kBAAkB,EAAE,KAAK,KAAK,KAAK,WAAW,CAAC,CAAC,kBAAkB,EAAE,KAAK,KAAK,KAAK,aAAa,CAAC,CAAC,kBAAkB,EAAE,KAAK,MAAM,KAAK,sBAAsB,CAAC,CAAC,kBAAkB,EAAE,KAAK,MAAM,KAAK,yBAAyB,CAAC,CAAC,kBAAkB,EAAE,KAAK,MAAM,KAAK,mBAAmB,qCAAqC,kBAAkB,gCAAgC,CAAC,CAAC,kBAAkB,EAAE,KAAK,MAAM,KAAK,cAAc,kBAAkB,EAAE,KAAK,MAAM,KAAK,cAAc,kBAAkB,EAAE,KAAK,MAAM,KAAK,2BAA2B,kBAAkB,EAAE,KAAK,MAAM,KAAK,qBAAqB,kBAAkB,EAAE,KAAK,MAAM,KAAK,0BAA0B,kBAAkB,EAAE,KAAK,MAAM,KAAK,8BAA8B,kBAAkB,EAAE,KAAK,MAAM,IAAI;AAC/zB,cAAIA,UAAS,sBAAsB,MAAM;AACzC,cAAI,CAACA,SAAQ;AACX,mBAAO;AAAA,UACT;AACA,cAAI,kBAAkB,qBAAqB;AACzC,mBAAO;AAAA,UACT;AACA,cAAI,gBAAgB,GAAG,cAAcA,SAAQ,iBAAiB;AAC9D,iBAAO;AAAA,QACT;AACA,iBAAS,iCAAiC,IAAI,KAAK;AACjD,iBAAO,oCAAoC,IAAI,GAAG;AAAA,QACpD;AACA,YAAI,WAAW,EAAE,UAAU,CAAC,GAAG,SAAS,CAAC,MAAM,CAAC,GAAG,CAAC,CAAC,GAAG,WAAW,SAAS,QAAQ,MAAM;AACxF,cAAI,UAAU,SAAS,QAAQ;AAC/B,cAAI,SAAS,KAAK,SAAS,IAAI;AAC7B,aAAC,WAAW,IAAI,MAAM,KAAK,kBAAkB,SAAS,CAAC,CAAC;AACxD,oBAAQ,SAAS;AAAA,UACnB,OAAO;AACL,oBAAQ,KAAK,IAAI;AAAA,UACnB;AAAA,QACF,GAAG,SAAS,QAAQ,KAAK,WAAW;AAClC,mBAAS,WAAW;AACpB,cAAI,MAAM,kBAAkB,EAAE,SAAS,UAAU,KAAK;AACtD,iBAAO;AAAA,QACT,GAAG,QAAQ,SAAS,KAAK;AACvB,cAAI,MAAM,aAAa,GAAG;AAC1B,iBAAO;AAAA,QACT,GAAG,OAAO,SAAS,KAAK,MAAM;AAC5B,iBAAO;AAAA,QACT,EAAE;AACF,iBAAS,UAAU,IAAI;AACrB,cAAI;AACF,mBAAO,oCAAoC,GAAG,GAAG,EAAE;AACrD,iBAAO;AAAA,QACT;AACA,iBAAS,SAAS,IAAI,YAAY,aAAa,QAAQ,WAAW;AAChE,cAAI;AACF,mBAAO,oCAAoC,GAAG,GAAG,IAAI,YAAY,aAAa,QAAQ,SAAS;AAAA,QACnG;AACA,iBAAS,UAAU,IAAI,KAAK,QAAQ,MAAM;AACxC,cAAI;AACF,mBAAO,oCAAoC,GAAG,GAAG,IAAI,KAAK,QAAQ,IAAI;AACxE,cAAI,MAAM;AACV,mBAAS,KAAK,GAAG,KAAK,QAAQ,MAAM;AAClC,gBAAI,MAAM,kBAAkB,EAAE,OAAO;AACrC,gBAAI,MAAM,kBAAkB,EAAE,MAAM,KAAK;AACzC,mBAAO;AACP,qBAAS,IAAI,GAAG,IAAI,KAAK,KAAK;AAC5B,uBAAS,UAAU,IAAI,iBAAiB,EAAE,MAAM,EAAE;AAAA,YACpD;AACA,mBAAO;AAAA,UACT;AACA,4BAAkB,EAAE,QAAQ,KAAK;AACjC,iBAAO;AAAA,QACT;AACA,iBAAS,aAAa,KAAK;AACzB,sBAAY,GAAG;AAAA,QACjB;AACA,gBAAQ,KAAK;AACb,YAAI;AACJ,YAAI,uBAAuB,CAAC,MAAM,kBAAkB,iDAAiD,WAAW,UAAU,SAAS;AACnI,YAAI,aAAa;AACjB,YAAI,gBAAgB,EAAE,mBAAmB,kBAAkB,oCAAoC,mCAAmC,+BAA+B,8BAA8B,uBAAuB,sBAAsB,0CAA0C,yCAAyC,mCAAmC,kCAAkC,SAAS,QAAQ,qCAAqC,oCAAoC,2BAA2B,0BAA0B,sBAAsB,qBAAqB,yBAAyB,wBAAwB,gCAAgC,+BAA+B,wCAAwC,uCAAuC,0BAA0B,yBAAyB,sCAAsC,qCAAqC,sCAAsC,qCAAqC,mCAAmC,kCAAkC,QAAQ,OAAO,YAAY,WAAW,WAAW,UAAU,YAAY,WAAW,UAAU,cAAc,OAAO,eAAe,eAAe,aAAa;AACvqC,YAAI,MAAM,WAAW;AACrB,YAAI,qBAAqB,OAAO,wBAAwB,WAAW;AACjE,kBAAQ,qBAAqB,OAAO,wBAAwB,OAAO,OAAO,sBAAsB,MAAM,MAAM,SAAS;AAAA,QACvH;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,2BAA2B,OAAO,8BAA8B,WAAW;AAC7E,kBAAQ,2BAA2B,OAAO,8BAA8B,OAAO,OAAO,4BAA4B,MAAM,MAAM,SAAS;AAAA,QACzI;AACA,YAAI,qBAAqB,OAAO,wBAAwB,WAAW;AACjE,kBAAQ,qBAAqB,OAAO,wBAAwB,OAAO,OAAO,sBAAsB,MAAM,MAAM,SAAS;AAAA,QACvH;AACA,YAAI,mBAAmB,OAAO,sBAAsB,WAAW;AAC7D,kBAAQ,mBAAmB,OAAO,sBAAsB,OAAO,OAAO,oBAAoB,MAAM,MAAM,SAAS;AAAA,QACjH;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,gBAAgB,MAAM,MAAM,SAAS;AAAA,QACrG;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,gBAAgB,MAAM,MAAM,SAAS;AAAA,QACrG;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,iBAAiB,OAAO,oBAAoB,WAAW;AACzD,kBAAQ,iBAAiB,OAAO,oBAAoB,OAAO,OAAO,kBAAkB,MAAM,MAAM,SAAS;AAAA,QAC3G;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,yBAAyB,OAAO,4BAA4B,WAAW;AACzE,kBAAQ,yBAAyB,OAAO,4BAA4B,OAAO,OAAO,0BAA0B,MAAM,MAAM,SAAS;AAAA,QACnI;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,iBAAiB,OAAO,oBAAoB,WAAW;AACzD,kBAAQ,iBAAiB,OAAO,oBAAoB,OAAO,OAAO,kBAAkB,MAAM,MAAM,SAAS;AAAA,QAC3G;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,kBAAkB,OAAO,qBAAqB,WAAW;AAC3D,kBAAQ,kBAAkB,OAAO,qBAAqB,OAAO,OAAO,mBAAmB,MAAM,MAAM,SAAS;AAAA,QAC9G;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,gBAAgB,MAAM,MAAM,SAAS;AAAA,QACrG;AACA,YAAI,wBAAwB,OAAO,2BAA2B,WAAW;AACvE,kBAAQ,wBAAwB,OAAO,2BAA2B,OAAO,OAAO,yBAAyB,MAAM,MAAM,SAAS;AAAA,QAChI;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,cAAc,OAAO,iBAAiB,WAAW;AACnD,kBAAQ,cAAc,OAAO,iBAAiB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAClG;AACA,YAAI,cAAc,OAAO,iBAAiB,WAAW;AACnD,kBAAQ,cAAc,OAAO,iBAAiB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAClG;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,cAAc,OAAO,iBAAiB,WAAW;AACnD,kBAAQ,cAAc,OAAO,iBAAiB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAClG;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,kBAAkB,OAAO,qBAAqB,WAAW;AAC3D,kBAAQ,kBAAkB,OAAO,qBAAqB,OAAO,OAAO,mBAAmB,MAAM,MAAM,SAAS;AAAA,QAC9G;AACA,YAAI,yBAAyB,OAAO,4BAA4B,WAAW;AACzE,kBAAQ,yBAAyB,OAAO,4BAA4B,OAAO,OAAO,0BAA0B,MAAM,MAAM,SAAS;AAAA,QACnI;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,oBAAoB,OAAO,uBAAuB,WAAW;AAC/D,kBAAQ,oBAAoB,OAAO,uBAAuB,OAAO,OAAO,qBAAqB,MAAM,MAAM,SAAS;AAAA,QACpH;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,iBAAiB,OAAO,oBAAoB,WAAW;AACzD,kBAAQ,iBAAiB,OAAO,oBAAoB,OAAO,OAAO,kBAAkB,MAAM,MAAM,SAAS;AAAA,QAC3G;AACA,YAAI,0BAA0B,OAAO,6BAA6B,WAAW;AAC3E,kBAAQ,0BAA0B,OAAO,6BAA6B,OAAO,OAAO,2BAA2B,MAAM,MAAM,SAAS;AAAA,QACtI;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,qBAAqB,OAAO,wBAAwB,WAAW;AACjE,kBAAQ,qBAAqB,OAAO,wBAAwB,OAAO,OAAO,sBAAsB,MAAM,MAAM,SAAS;AAAA,QACvH;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,oBAAoB,OAAO,uBAAuB,WAAW;AAC/D,kBAAQ,oBAAoB,OAAO,uBAAuB,OAAO,OAAO,qBAAqB,MAAM,MAAM,SAAS;AAAA,QACpH;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,+CAA+C,OAAO,kDAAkD,WAAW;AACrH,kBAAQ,+CAA+C,OAAO,kDAAkD,OAAO,OAAO,gDAAgD,MAAM,MAAM,SAAS;AAAA,QACrM;AACA,YAAI,8BAA8B,OAAO,iCAAiC,WAAW;AACnF,kBAAQ,8BAA8B,OAAO,iCAAiC,OAAO,OAAO,+BAA+B,MAAM,MAAM,SAAS;AAAA,QAClJ;AACA,YAAI,2BAA2B,OAAO,8BAA8B,WAAW;AAC7E,kBAAQ,2BAA2B,OAAO,8BAA8B,OAAO,OAAO,4BAA4B,MAAM,MAAM,SAAS;AAAA,QACzI;AACA,YAAI,kDAAkD,OAAO,qDAAqD,WAAW;AAC3H,kBAAQ,kDAAkD,OAAO,qDAAqD,OAAO,OAAO,mDAAmD,MAAM,MAAM,SAAS;AAAA,QAC9M;AACA,YAAI,qCAAqC,OAAO,wCAAwC,WAAW;AACjG,kBAAQ,qCAAqC,OAAO,wCAAwC,OAAO,OAAO,sCAAsC,MAAM,MAAM,SAAS;AAAA,QACvK;AACA,YAAI,wCAAwC,OAAO,2CAA2C,WAAW;AACvG,kBAAQ,wCAAwC,OAAO,2CAA2C,OAAO,OAAO,yCAAyC,MAAM,MAAM,SAAS;AAAA,QAChL;AACA,YAAI,wCAAwC,OAAO,2CAA2C,WAAW;AACvG,kBAAQ,wCAAwC,OAAO,2CAA2C,OAAO,OAAO,yCAAyC,MAAM,MAAM,SAAS;AAAA,QAChL;AACA,YAAI,4CAA4C,OAAO,+CAA+C,WAAW;AAC/G,kBAAQ,4CAA4C,OAAO,+CAA+C,OAAO,OAAO,6CAA6C,MAAM,MAAM,SAAS;AAAA,QAC5L;AACA,YAAI,kCAAkC,OAAO,qCAAqC,WAAW;AAC3F,kBAAQ,kCAAkC,OAAO,qCAAqC,OAAO,OAAO,mCAAmC,MAAM,MAAM,SAAS;AAAA,QAC9J;AACA,YAAI,gCAAgC,OAAO,mCAAmC,WAAW;AACvF,kBAAQ,gCAAgC,OAAO,mCAAmC,OAAO,OAAO,iCAAiC,MAAM,MAAM,SAAS;AAAA,QACxJ;AACA,YAAI,2BAA2B,OAAO,8BAA8B,WAAW;AAC7E,kBAAQ,2BAA2B,OAAO,8BAA8B,OAAO,OAAO,4BAA4B,MAAM,MAAM,SAAS;AAAA,QACzI;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,+BAA+B,OAAO,kCAAkC,WAAW;AACrF,kBAAQ,+BAA+B,OAAO,kCAAkC,OAAO,OAAO,gCAAgC,MAAM,MAAM,SAAS;AAAA,QACrJ;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC7F;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACtG;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAChG;AACA,YAAI,mBAAmB,OAAO,sBAAsB,WAAW;AAC7D,kBAAQ,mBAAmB,OAAO,sBAAsB,OAAO,OAAO,qBAAqB,MAAM,MAAM,SAAS;AAAA,QAClH;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACtG;AACA,YAAI,+CAA+C,OAAO,kDAAkD;AAC5G,eAAO,WAAW;AAClB,eAAO,sBAAsB;AAC7B,eAAO,aAAa;AACpB,eAAO,aAAa;AACpB,eAAO,gBAAgB;AACvB,eAAO,gBAAgB;AACvB,YAAI;AACJ,iBAAS,WAAW,QAAQ;AAC1B,eAAK,OAAO;AACZ,eAAK,UAAU,kCAAkC,SAAS;AAC1D,eAAK,SAAS;AAAA,QAChB;AACA,gCAAwB,SAAS,YAAY;AAC3C,cAAI,CAAC;AACH,gBAAI;AACN,cAAI,CAAC;AACH,oCAAwB;AAAA,QAC5B;AACA,iBAAS,IAAI,MAAM;AACjB,iBAAO,QAAQ;AACf,cAAI,kBAAkB,GAAG;AACvB;AAAA,UACF;AACA,cAAI,wBAAwB;AAC1B,gCAAoB,MAAM;AAC1B,wBAAY;AACZ,wBAAY,EAAE,OAAO,SAAS,CAAC;AAC/B;AAAA,UACF;AACA,iBAAO;AACP,cAAI,kBAAkB,GAAG;AACvB;AAAA,UACF;AACA,mBAAS,QAAQ;AACf,gBAAI;AACF;AACF,wBAAY;AACZ,mBAAO,eAAe;AACtB,gBAAI;AACF;AACF,wBAAY;AACZ,gCAAoB,MAAM;AAC1B,gBAAI,OAAO;AACT,qBAAO,wBAAwB;AACjC,oBAAQ;AAAA,UACV;AACA,cAAI,OAAO,cAAc;AACvB,mBAAO,aAAa,YAAY;AAChC,uBAAW,WAAW;AACpB,yBAAW,WAAW;AACpB,uBAAO,aAAa,EAAE;AAAA,cACxB,GAAG,CAAC;AACJ,oBAAM;AAAA,YACR,GAAG,CAAC;AAAA,UACN,OAAO;AACL,kBAAM;AAAA,UACR;AAAA,QACF;AACA,eAAO,SAAS;AAChB,iBAAS,KAAK,QAAQ,UAAU;AAC9B,uBAAa;AACb,cAAI,CAAC,UAAU;AACb,gBAAI,wBAAwB;AAC1B,+BAAiB,MAAM;AACvB,oBAAM;AAAA,YACR,OAAO;AAAA,YACP;AAAA,UACF;AACA,cAAI,iBAAiB,GAAG;AAAA,UACxB,OAAO;AACL,wBAAY;AAAA,UACd;AACA,mBAAS,MAAM;AAAA,QACjB;AACA,iBAAS,SAAS,MAAM;AACtB,uBAAa;AACb,cAAI,CAAC,iBAAiB,GAAG;AACvB,oBAAQ,oBAAoB;AAC5B,gBAAI,OAAO;AACT,qBAAO,UAAU,IAAI;AACvB,oBAAQ;AAAA,UACV;AACA,gBAAM,MAAM,IAAI,WAAW,IAAI,CAAC;AAAA,QAClC;AACA,YAAI,OAAO,YAAY;AACrB,cAAI,OAAO,OAAO,cAAc;AAC9B,mBAAO,aAAa,CAAC,OAAO,UAAU;AACxC,iBAAO,OAAO,WAAW,SAAS,GAAG;AACnC,mBAAO,WAAW,IAAI,EAAE;AAAA,UAC1B;AAAA,QACF;AACA,YAAI;AACJ,YAAI;AACJ,YAAI,iBAAiB;AACnB,2BAAiB,EAAE,mBAAmB,QAAQ,UAAU,mBAAmB,EAAE,OAAO,SAAS,UAAU;AACrG,mBAAO,CAAC,gBAAgB,kBAAkB,QAAQ,QAAQ,IAAI;AAAA,UAChE,CAAC,GAAG,oBAAoB,QAAQ,UAAU,oBAAoB,EAAE,OAAO,SAAS,UAAU;AACxF,mBAAO,CAAC,gBAAgB,mBAAmB,QAAQ,QAAQ,IAAI;AAAA,UACjE,CAAC,EAAE;AAAA,QACL;AACA,YAAI;AACJ,YAAI,OAAO,sBAAsB,aAAa;AAC5C,yBAAe;AAAA,QACjB,WAAW,OAAO,mCAAmC,aAAa;AAChE,yBAAe;AAAA,QACjB,OAAO;AACL,gBAAM,IAAI,MAAM,uCAAuC;AAAA,QACzD;AACA,YAAI,gBAAgB;AAClB,cAAI,aAAa,aAAa;AAC9B,uBAAa,cAAc,WAAW;AACpC,uBAAW;AACX,2BAAe,kBAAkB,QAAQ,SAAS,UAAU;AAC1D,sBAAQ,eAAe,qBAAqB,QAAQ;AAAA,YACtD,CAAC;AACD,2BAAe,mBAAmB,QAAQ,SAAS,UAAU;AAC3D,sBAAQ,eAAe,sBAAsB,QAAQ;AAAA,YACvD,CAAC;AAAA,UACH;AAAA,QACF;AACA,eAAO,+BAA+B;AAAA,MACxC;AAAA,IACF,GAAG;AACH,QAAI,OAAO,YAAY,YAAY,OAAO,WAAW;AACnD,aAAO,UAAU;AAAA,aACV,OAAO,WAAW,cAAc,OAAO;AAC9C,aAAO,CAAC,GAAG,WAAW;AACpB,eAAO;AAAA,MACT,CAAC;AAAA,aACM,OAAO,YAAY;AAC1B,cAAQ,mCAAmC;AAAA,EAC/C;AACF,CAAC;AAGD,IAAI,iDAAiD,WAAW;AAAA,EAC9D,mLAAmL,SAAS,QAAQ;AAClM,WAAO,QAAQ,qBAAqB;AAAA;AAAA,EAEtC;AACF,CAAC;AAGD,IAAI,4BAA4B,WAAW;AAAA,EACzC,8JAA8J,SAAS,QAAQ;AAC7K,QAAI,sBAAsB,MAAM;AAC9B,UAAI,aAAa,OAAO,aAAa,eAAe,SAAS,gBAAgB,SAAS,cAAc,MAAM;AAC1G,UAAI,OAAO,eAAe;AACxB,qBAAa,cAAc;AAC7B,aAAO,SAAS,oBAAoB;AAClC,6BAAqB,sBAAsB,CAAC;AAC5C,YAAI,SAAS,OAAO,uBAAuB,cAAc,qBAAqB,CAAC;AAC/E,YAAI,qBAAqB;AACzB,eAAO,WAAW,IAAI,QAAQ,SAAS,SAAS,QAAQ;AACtD,gCAAsB;AACtB,+BAAqB;AAAA,QACvB,CAAC;AACD,YAAI;AACJ,YAAI,OAAO,YAAY,eAAe,QAAQ,WAAW;AACvD,4BAAkB,EAAE,mBAAmB,QAAQ,UAAU,mBAAmB,GAAG,oBAAoB,QAAQ,UAAU,oBAAoB,EAAE;AAAA,QAC7I;AACA,YAAI,kBAAkB,OAAO,OAAO,CAAC,GAAG,MAAM;AAC9C,YAAI,aAAa,CAAC;AAClB,YAAI,cAAc;AAClB,YAAI,QAAQ,CAAC,QAAQ,YAAY;AAC/B,gBAAM;AAAA,QACR;AACA,YAAI,qBAAqB,OAAO,WAAW;AAC3C,YAAI,wBAAwB,OAAO,kBAAkB;AACrD,YAAI,sBAAsB,OAAO,YAAY,YAAY,OAAO,QAAQ,aAAa,YAAY,OAAO,QAAQ,SAAS,SAAS;AAClI,YAAI,kBAAkB;AACtB,iBAAS,WAAW,MAAM;AACxB,cAAI,OAAO,eAAe;AACxB,mBAAO,OAAO,cAAc,MAAM,eAAe;AAAA,UACnD;AACA,iBAAO,kBAAkB;AAAA,QAC3B;AACA,YAAI,OAAO,WAAW,YAAY;AAClC,iBAAS,mBAAmB,IAAI;AAC9B,cAAI,cAAc;AAChB;AACF,cAAI,QAAQ;AACZ,cAAI,+BAA+B,KAAK;AAAA,QAC1C;AACA,YAAI;AACJ,YAAI;AACJ,YAAI;AACJ,YAAI,qBAAqB;AACvB,cAAI,uBAAuB;AACzB,8BAAkB,aAAa,EAAE,QAAQ,eAAe,IAAI;AAAA,UAC9D,OAAO;AACL,8BAAkB,YAAY;AAAA,UAChC;AACA,0BAAgB,MAAM;AACpB,gBAAI,CAAC,UAAU;AACb,mBAAK,WAAW;AAChB,yBAAW,aAAa;AAAA,YAC1B;AAAA,UACF;AACA,kBAAQ,SAAS,WAAW,UAAU,QAAQ;AAC5C,0BAAc;AACd,uBAAW,SAAS,aAAa,QAAQ;AACzC,mBAAO,GAAG,aAAa,UAAU,SAAS,SAAS,MAAM;AAAA,UAC3D;AACA,uBAAa,CAAC,aAAa;AACzB,gBAAI,MAAM,MAAM,UAAU,IAAI;AAC9B,gBAAI,CAAC,IAAI,QAAQ;AACf,oBAAM,IAAI,WAAW,GAAG;AAAA,YAC1B;AACA,mBAAO;AAAA,UACT;AACA,sBAAY,CAAC,UAAU,QAAQ,YAAY;AACzC,0BAAc;AACd,uBAAW,SAAS,aAAa,QAAQ;AACzC,eAAG,SAAS,UAAU,SAAS,MAAM,MAAM;AACzC,kBAAI;AACF,wBAAQ,IAAI;AAAA;AAEZ,uBAAO,KAAK,MAAM;AAAA,YACtB,CAAC;AAAA,UACH;AACA,cAAI,QAAQ,QAAQ,SAAS,GAAG;AAC9B,0BAAc,QAAQ,QAAQ,GAAG,QAAQ,OAAO,GAAG;AAAA,UACrD;AACA,uBAAa,QAAQ,QAAQ,MAAM,CAAC;AACpC,kBAAQ,MAAM,qBAAqB,SAAS,IAAI;AAC9C,gBAAI,EAAE,cAAc,aAAa;AAC/B,oBAAM;AAAA,YACR;AAAA,UACF,CAAC;AACD,kBAAQ,MAAM,sBAAsB,SAAS,QAAQ;AACnD,kBAAM;AAAA,UACR,CAAC;AACD,kBAAQ,CAAC,QAAQ,YAAY;AAC3B,gBAAI,iBAAiB,GAAG;AACtB,sBAAQ,cAAc;AACtB,oBAAM;AAAA,YACR;AACA,+BAAmB,OAAO;AAC1B,oBAAQ,QAAQ,MAAM;AAAA,UACxB;AACA,iBAAO,aAAa,WAAW;AAC7B,mBAAO;AAAA,UACT;AAAA,QACF,WAAW,sBAAsB,uBAAuB;AACtD,cAAI,uBAAuB;AACzB,8BAAkB,KAAK,SAAS;AAAA,UAClC,WAAW,OAAO,aAAa,eAAe,SAAS,eAAe;AACpE,8BAAkB,SAAS,cAAc;AAAA,UAC3C;AACA,cAAI,YAAY;AACd,8BAAkB;AAAA,UACpB;AACA,cAAI,gBAAgB,QAAQ,OAAO,MAAM,GAAG;AAC1C,8BAAkB,gBAAgB,OAAO,GAAG,gBAAgB,QAAQ,UAAU,EAAE,EAAE,YAAY,GAAG,IAAI,CAAC;AAAA,UACxG,OAAO;AACL,8BAAkB;AAAA,UACpB;AACA;AACE,oBAAQ,CAAC,QAAQ;AACf,kBAAI,MAAM,IAAI,eAAe;AAC7B,kBAAI,KAAK,OAAO,KAAK,KAAK;AAC1B,kBAAI,KAAK,IAAI;AACb,qBAAO,IAAI;AAAA,YACb;AACA,gBAAI,uBAAuB;AACzB,2BAAa,CAAC,QAAQ;AACpB,oBAAI,MAAM,IAAI,eAAe;AAC7B,oBAAI,KAAK,OAAO,KAAK,KAAK;AAC1B,oBAAI,eAAe;AACnB,oBAAI,KAAK,IAAI;AACb,uBAAO,IAAI,WAAW,IAAI,QAAQ;AAAA,cACpC;AAAA,YACF;AACA,wBAAY,CAAC,KAAK,QAAQ,YAAY;AACpC,kBAAI,MAAM,IAAI,eAAe;AAC7B,kBAAI,KAAK,OAAO,KAAK,IAAI;AACzB,kBAAI,eAAe;AACnB,kBAAI,SAAS,MAAM;AACjB,oBAAI,IAAI,UAAU,OAAO,IAAI,UAAU,KAAK,IAAI,UAAU;AACxD,yBAAO,IAAI,QAAQ;AACnB;AAAA,gBACF;AACA,wBAAQ;AAAA,cACV;AACA,kBAAI,UAAU;AACd,kBAAI,KAAK,IAAI;AAAA,YACf;AAAA,UACF;AACA,2BAAiB,CAAC,UAAU,SAAS,QAAQ;AAAA,QAC/C,OAAO;AAAA,QACP;AACA,YAAI,MAAM,OAAO,YAAY,QAAQ,IAAI,KAAK,OAAO;AACrD,YAAI,MAAM,OAAO,eAAe,QAAQ,KAAK,KAAK,OAAO;AACzD,eAAO,OAAO,QAAQ,eAAe;AACrC,0BAAkB;AAClB,YAAI,OAAO;AACT,uBAAa,OAAO;AACtB,YAAI,OAAO;AACT,wBAAc,OAAO;AACvB,YAAI,OAAO;AACT,kBAAQ,OAAO;AACjB,YAAI,eAAe;AACnB,iBAAS,SAAS,MAAM;AACtB,cAAI,CAAC,SAAS;AACZ,qBAAS,QAAQ,CAAC;AACpB,cAAI,CAAC,SAAS,MAAM,OAAO;AACzB,qBAAS,MAAM,QAAQ;AACvB,gBAAI,IAAI;AAAA,UACV;AAAA,QACF;AACA,iBAAS,wBAAwB,OAAO,KAAK;AAC3C,cAAI,OAAO,YAAY,aAAa,YAAY;AAC9C,gBAAI,YAAY,EAAE,KAAK,OAAO,KAAK,OAAO,KAAK,OAAO,KAAK,MAAM;AACjE,gBAAI,OAAO,EAAE,YAAY,CAAC,GAAG,SAAS,IAAI,MAAM,MAAM,CAAC,IAAI,CAAC,UAAU,IAAI,GAAG,EAAE;AAC/E,qBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,mBAAK,WAAW,KAAK,UAAU,IAAI,IAAI;AAAA,YACzC;AACA,mBAAO,IAAI,YAAY,SAAS,MAAM,KAAK;AAAA,UAC7C;AACA,cAAI,cAAc,CAAC,GAAG,GAAG,GAAG,EAAE;AAC9B,cAAI,SAAS,IAAI,MAAM,GAAG,CAAC;AAC3B,cAAI,WAAW,IAAI,MAAM,CAAC;AAC1B,cAAI,YAAY,EAAE,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,IAAI;AACzD,sBAAY,KAAK,SAAS,MAAM;AAChC,mBAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,EAAE,IAAI;AAC3C,wBAAY,KAAK,UAAU,SAAS,IAAI;AAAA,UAC1C;AACA,cAAI,UAAU,KAAK;AACjB,wBAAY,KAAK,CAAC;AAAA,UACpB,OAAO;AACL,0BAAc,YAAY,OAAO,CAAC,GAAG,UAAU,OAAO,CAAC;AAAA,UACzD;AACA,sBAAY,KAAK,YAAY,SAAS;AACtC,cAAI,QAAQ,IAAI,WAAW,CAAC,GAAG,IAAI,KAAK,KAAK,GAAG,GAAG,GAAG,CAAC,EAAE,OAAO,aAAa,CAAC,GAAG,GAAG,GAAG,GAAG,KAAK,GAAG,KAAK,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,KAAK,GAAG,CAAC,CAAC,CAAC;AACpI,cAAI,UAAU,IAAI,YAAY,OAAO,KAAK;AAC1C,cAAI,WAAW,IAAI,YAAY,SAAS,SAAS,EAAE,KAAK,EAAE,KAAK,MAAM,EAAE,CAAC;AACxE,cAAI,cAAc,SAAS,QAAQ;AACnC,iBAAO;AAAA,QACT;AACA,YAAI,mBAAmB,CAAC;AACxB,YAAI;AACJ,iBAAS,oBAAoB;AAC3B,cAAI,iBAAiB,QAAQ;AAC3B,mBAAO,iBAAiB,IAAI;AAAA,UAC9B;AACA,cAAI;AACF,sBAAU,KAAK,CAAC;AAAA,UAClB,SAAS,MAAP;AACA,gBAAI,EAAE,gBAAgB,aAAa;AACjC,oBAAM;AAAA,YACR;AACA,kBAAM;AAAA,UACR;AACA,iBAAO,UAAU,SAAS;AAAA,QAC5B;AACA,iBAAS,eAAe,QAAQH,SAAQ;AACtC,mBAAS,KAAK,QAAQ,KAAK,SAASA,SAAQ,MAAM;AAChD,gBAAI,OAAO,kBAAkB,EAAE;AAC/B,gBAAI,MAAM;AACR,kCAAoB,IAAI,MAAM,EAAE;AAAA,YAClC;AAAA,UACF;AAAA,QACF;AACA,YAAI,WAAW;AACf,YAAI,cAAc,CAAC,UAAU;AAC3B,qBAAW;AAAA,QACb;AACA,YAAI;AACJ,YAAI,OAAO;AACT,uBAAa,OAAO;AACtB,YAAI,gBAAgB,OAAO,oBAAoB;AAC/C,YAAI,OAAO,gBAAgB,UAAU;AACnC,gBAAM,iCAAiC;AAAA,QACzC;AACA,YAAI;AACJ,YAAI,QAAQ;AACZ,YAAI;AACJ,iBAAS,QAAQ,WAAW,MAAM;AAChC,cAAI,CAAC,WAAW;AACd,kBAAM,IAAI;AAAA,UACZ;AAAA,QACF;AACA,iBAAS,SAAS,OAAO;AACvB,cAAI,QAAQ,OAAO,MAAM;AACzB,iBAAO;AAAA,QACT;AACA,iBAAS,MAAM,OAAO,YAAY,UAAU,MAAM,MAAM;AACtD,cAAI,MAAM,EAAE,UAAU,SAAS,KAAK;AAClC,gBAAI,OAAO;AACX,gBAAI,QAAQ,QAAQ,QAAQ,UAAU,QAAQ,GAAG;AAC/C,kBAAI,OAAO,IAAI,UAAU,KAAK;AAC9B,qBAAO,WAAW,GAAG;AACrB,2BAAa,KAAK,MAAM,GAAG;AAAA,YAC7B;AACA,mBAAO;AAAA,UACT,GAAG,SAAS,SAAS,KAAK;AACxB,gBAAI,OAAO,WAAW,IAAI,MAAM;AAChC,+BAAmB,KAAK,IAAI;AAC5B,mBAAO;AAAA,UACT,EAAE;AACF,mBAAS,mBAAmB,MAAM;AAChC,gBAAI,eAAe;AACjB,qBAAO,aAAa,IAAI;AAC1B,gBAAI,eAAe;AACjB,qBAAO,QAAQ,IAAI;AACrB,mBAAO;AAAA,UACT;AACA,cAAI,QAAQ,SAAS,KAAK;AAC1B,cAAI,QAAQ,CAAC;AACb,cAAI,SAAS;AACb,cAAI,MAAM;AACR,qBAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,kBAAI,YAAY,IAAI,SAAS;AAC7B,kBAAI,WAAW;AACb,oBAAI,WAAW;AACb,2BAAS,UAAU;AACrB,sBAAM,MAAM,UAAU,KAAK,GAAG;AAAA,cAChC,OAAO;AACL,sBAAM,MAAM,KAAK;AAAA,cACnB;AAAA,YACF;AAAA,UACF;AACA,cAAI,MAAM,MAAM,MAAM,MAAM,KAAK;AACjC,mBAAS,OAAO,MAAM;AACpB,gBAAI,WAAW;AACb,2BAAa,MAAM;AACrB,mBAAO,mBAAmB,IAAI;AAAA,UAChC;AACA,gBAAM,OAAO,GAAG;AAChB,iBAAO;AAAA,QACT;AACA,iBAAS,MAAM,OAAO,YAAY,UAAU,MAAM;AAChD,qBAAW,YAAY,CAAC;AACxB,cAAI,cAAc,SAAS,MAAM,SAAS,MAAM;AAC9C,mBAAO,SAAS;AAAA,UAClB,CAAC;AACD,cAAI,aAAa,eAAe;AAChC,cAAI,cAAc,eAAe,CAAC,MAAM;AACtC,mBAAO,SAAS,KAAK;AAAA,UACvB;AACA,iBAAO,WAAW;AAChB,mBAAO,MAAM,OAAO,YAAY,UAAU,WAAW,IAAI;AAAA,UAC3D;AAAA,QACF;AACA,YAAI,cAAc;AAClB,YAAI,cAAc,OAAO,gBAAgB,cAAc,IAAI,YAAY,MAAM,IAAI;AACjF,iBAAS,kBAAkB,MAAM,KAAK,gBAAgB;AACpD,cAAI,SAAS,MAAM;AACnB,cAAI,SAAS;AACb,iBAAO,KAAK,WAAW,EAAE,UAAU;AACjC,cAAE;AACJ,cAAI,SAAS,MAAM,MAAM,KAAK,YAAY,aAAa;AACrD,mBAAO,YAAY,OAAO,KAAK,SAAS,KAAK,MAAM,CAAC;AAAA,UACtD,OAAO;AACL,gBAAI,MAAM;AACV,mBAAO,MAAM,QAAQ;AACnB,kBAAI,KAAK,KAAK;AACd,kBAAI,EAAE,KAAK,MAAM;AACf,uBAAO,OAAO,aAAa,EAAE;AAC7B;AAAA,cACF;AACA,kBAAI,KAAK,KAAK,SAAS;AACvB,mBAAK,KAAK,QAAQ,KAAK;AACrB,uBAAO,OAAO,cAAc,KAAK,OAAO,IAAI,EAAE;AAC9C;AAAA,cACF;AACA,kBAAI,KAAK,KAAK,SAAS;AACvB,mBAAK,KAAK,QAAQ,KAAK;AACrB,sBAAM,KAAK,OAAO,KAAK,MAAM,IAAI;AAAA,cACnC,OAAO;AACL,sBAAM,KAAK,MAAM,KAAK,MAAM,KAAK,MAAM,IAAI,KAAK,SAAS;AAAA,cAC3D;AACA,kBAAI,KAAK,OAAO;AACd,uBAAO,OAAO,aAAa,EAAE;AAAA,cAC/B,OAAO;AACL,oBAAI,KAAK,KAAK;AACd,uBAAO,OAAO,aAAa,QAAQ,MAAM,IAAI,QAAQ,KAAK,IAAI;AAAA,cAChE;AAAA,YACF;AAAA,UACF;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,aAAa,KAAK,gBAAgB;AACzC,iBAAO,MAAM,kBAAkB,QAAQ,KAAK,cAAc,IAAI;AAAA,QAChE;AACA,iBAAS,kBAAkB,KAAK,MAAM,QAAQ,iBAAiB;AAC7D,cAAI,EAAE,kBAAkB;AACtB,mBAAO;AACT,cAAI,WAAW;AACf,cAAI,SAAS,SAAS,kBAAkB;AACxC,mBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,gBAAI,IAAI,IAAI,WAAW,EAAE;AACzB,gBAAI,KAAK,SAAS,KAAK,OAAO;AAC5B,kBAAI,KAAK,IAAI,WAAW,EAAE,EAAE;AAC5B,kBAAI,UAAU,IAAI,SAAS,MAAM,KAAK;AAAA,YACxC;AACA,gBAAI,KAAK,KAAK;AACZ,kBAAI,UAAU;AACZ;AACF,mBAAK,YAAY;AAAA,YACnB,WAAW,KAAK,MAAM;AACpB,kBAAI,SAAS,KAAK;AAChB;AACF,mBAAK,YAAY,MAAM,KAAK;AAC5B,mBAAK,YAAY,MAAM,IAAI;AAAA,YAC7B,WAAW,KAAK,OAAO;AACrB,kBAAI,SAAS,KAAK;AAChB;AACF,mBAAK,YAAY,MAAM,KAAK;AAC5B,mBAAK,YAAY,MAAM,KAAK,IAAI;AAChC,mBAAK,YAAY,MAAM,IAAI;AAAA,YAC7B,OAAO;AACL,kBAAI,SAAS,KAAK;AAChB;AACF,mBAAK,YAAY,MAAM,KAAK;AAC5B,mBAAK,YAAY,MAAM,KAAK,KAAK;AACjC,mBAAK,YAAY,MAAM,KAAK,IAAI;AAChC,mBAAK,YAAY,MAAM,IAAI;AAAA,YAC7B;AAAA,UACF;AACA,eAAK,UAAU;AACf,iBAAO,SAAS;AAAA,QAClB;AACA,iBAAS,aAAa,KAAK,QAAQ,iBAAiB;AAClD,iBAAO,kBAAkB,KAAK,QAAQ,QAAQ,eAAe;AAAA,QAC/D;AACA,iBAAS,gBAAgB,KAAK;AAC5B,cAAI,MAAM;AACV,mBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,gBAAI,IAAI,IAAI,WAAW,EAAE;AACzB,gBAAI,KAAK,SAAS,KAAK;AACrB,kBAAI,UAAU,IAAI,SAAS,MAAM,IAAI,WAAW,EAAE,EAAE,IAAI;AAC1D,gBAAI,KAAK;AACP,gBAAE;AAAA,qBACK,KAAK;AACZ,qBAAO;AAAA,qBACA,KAAK;AACZ,qBAAO;AAAA;AAEP,qBAAO;AAAA,UACX;AACA,iBAAO;AAAA,QACT;AACA,YAAI,eAAe,OAAO,gBAAgB,cAAc,IAAI,YAAY,UAAU,IAAI;AACtF,iBAAS,mBAAmB,QAAQ,SAAS;AAC3C,gBAAM,IAAI,QAAQ,OAAO;AAAA,QAC3B;AACA,iBAAS,mBAAmB,KAAK,SAAS,aAAa;AACrD,mBAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,kBAAM,aAAa,KAAK,IAAI,WAAW,EAAE;AAAA,UAC3C;AACA,cAAI,CAAC;AACH,kBAAM,WAAW,KAAK;AAAA,QAC1B;AACA,iBAAS,QAAQ,GAAG,UAAU;AAC5B,cAAI,IAAI,WAAW,GAAG;AACpB,iBAAK,WAAW,IAAI;AAAA,UACtB;AACA,iBAAO;AAAA,QACT;AACA,YAAI,SAAS,OAAO,QAAQ,QAAQ,SAAS,QAAQ,SAAS,SAAS;AACvE,iBAAS,2BAA2B,KAAK;AACvC,oBAAU;AACV,iBAAO,WAAW,QAAQ,IAAI,UAAU,GAAG;AAC3C,iBAAO,YAAY,SAAS,IAAI,WAAW,GAAG;AAC9C,iBAAO,YAAY,SAAS,IAAI,WAAW,GAAG;AAC9C,iBAAO,YAAY,SAAS,IAAI,WAAW,GAAG;AAC9C,iBAAO,aAAa,UAAU,IAAI,YAAY,GAAG;AACjD,iBAAO,aAAa,UAAU,IAAI,YAAY,GAAG;AACjD,iBAAO,aAAa,UAAU,IAAI,aAAa,GAAG;AAClD,iBAAO,aAAa,UAAU,IAAI,aAAa,GAAG;AAAA,QACpD;AACA,YAAI,iBAAiB,OAAO,qBAAqB;AACjD,YAAI;AACJ,YAAI,eAAe,CAAC;AACpB,YAAI,aAAa,CAAC;AAClB,YAAI,gBAAgB,CAAC;AACrB,YAAI,qBAAqB;AACzB,YAAI,gBAAgB;AACpB,YAAI,0BAA0B;AAC9B,iBAAS,mBAAmB;AAC1B,iBAAO,iBAAiB,0BAA0B;AAAA,QACpD;AACA,iBAAS,SAAS;AAChB,cAAI,OAAO,WAAW;AACpB,gBAAI,OAAO,OAAO,aAAa;AAC7B,qBAAO,YAAY,CAAC,OAAO,SAAS;AACtC,mBAAO,OAAO,UAAU,QAAQ;AAC9B,0BAAY,OAAO,UAAU,MAAM,CAAC;AAAA,YACtC;AAAA,UACF;AACA,+BAAqB,YAAY;AAAA,QACnC;AACA,iBAAS,cAAc;AACrB,+BAAqB;AACrB,+BAAqB,UAAU;AAAA,QACjC;AACA,iBAAS,cAAc;AACrB,0BAAgB;AAAA,QAClB;AACA,iBAAS,UAAU;AACjB,cAAI,OAAO,YAAY;AACrB,gBAAI,OAAO,OAAO,cAAc;AAC9B,qBAAO,aAAa,CAAC,OAAO,UAAU;AACxC,mBAAO,OAAO,WAAW,QAAQ;AAC/B,2BAAa,OAAO,WAAW,MAAM,CAAC;AAAA,YACxC;AAAA,UACF;AACA,+BAAqB,aAAa;AAAA,QACpC;AACA,iBAAS,YAAY,IAAI;AACvB,uBAAa,QAAQ,EAAE;AAAA,QACzB;AACA,iBAAS,UAAU,IAAI;AACrB,qBAAW,QAAQ,EAAE;AAAA,QACvB;AACA,iBAAS,aAAa,IAAI;AACxB,wBAAc,QAAQ,EAAE;AAAA,QAC1B;AACA,YAAI,kBAAkB;AACtB,YAAI,uBAAuB;AAC3B,YAAI,wBAAwB;AAC5B,iBAAS,iBAAiB,IAAI;AAC5B;AACA,cAAI,OAAO,2BAA2B;AACpC,mBAAO,0BAA0B,eAAe;AAAA,UAClD;AAAA,QACF;AACA,iBAAS,oBAAoB,IAAI;AAC/B;AACA,cAAI,OAAO,2BAA2B;AACpC,mBAAO,0BAA0B,eAAe;AAAA,UAClD;AACA,cAAI,mBAAmB,GAAG;AACxB,gBAAI,yBAAyB,MAAM;AACjC,4BAAc,oBAAoB;AAClC,qCAAuB;AAAA,YACzB;AACA,gBAAI,uBAAuB;AACzB,kBAAI,WAAW;AACf,sCAAwB;AACxB,uBAAS;AAAA,YACX;AAAA,UACF;AAAA,QACF;AACA,eAAO,qBAAqB,CAAC;AAC7B,eAAO,qBAAqB,CAAC;AAC7B,iBAAS,MAAM,MAAM;AACnB;AACE,gBAAI,OAAO,YAAY;AACrB,qBAAO,WAAW,IAAI;AAAA,YACxB;AAAA,UACF;AACA,iBAAO,aAAa,OAAO;AAC3B,cAAI,IAAI;AACR,kBAAQ;AACR,uBAAa;AACb,kBAAQ;AACR,cAAI,KAAK,IAAI,YAAY,aAAa,IAAI;AAC1C,6BAAmB,EAAE;AACrB,gBAAM;AAAA,QACR;AACA,YAAI,gBAAgB;AACpB,iBAAS,UAAU,UAAU;AAC3B,iBAAO,SAAS,WAAW,aAAa;AAAA,QAC1C;AACA,iBAAS,UAAU,UAAU;AAC3B,iBAAO,SAAS,WAAW,SAAS;AAAA,QACtC;AACA,YAAI;AACJ,yBAAiB;AACjB,YAAI,CAAC,UAAU,cAAc,GAAG;AAC9B,2BAAiB,WAAW,cAAc;AAAA,QAC5C;AACA,iBAAS,UAAU,MAAM;AACvB,cAAI;AACF,gBAAI,QAAQ,kBAAkB,YAAY;AACxC,qBAAO,IAAI,WAAW,UAAU;AAAA,YAClC;AACA,gBAAI,YAAY;AACd,qBAAO,WAAW,IAAI;AAAA,YACxB,OAAO;AACL,oBAAM;AAAA,YACR;AAAA,UACF,SAAS,MAAP;AACA,kBAAM,IAAI;AAAA,UACZ;AAAA,QACF;AACA,iBAAS,mBAAmB;AAC1B,cAAI,CAAC,eAAe,sBAAsB,wBAAwB;AAChE,gBAAI,OAAO,UAAU,cAAc,CAAC,UAAU,cAAc,GAAG;AAC7D,qBAAO,MAAM,gBAAgB,EAAE,aAAa,cAAc,CAAC,EAAE,KAAK,SAAS,UAAU;AACnF,oBAAI,CAAC,SAAS,OAAO;AACnB,wBAAM,yCAAyC,iBAAiB;AAAA,gBAClE;AACA,uBAAO,SAAS,eAAe;AAAA,cACjC,CAAC,EAAE,MAAM,WAAW;AAClB,uBAAO,UAAU,cAAc;AAAA,cACjC,CAAC;AAAA,YACH,OAAO;AACL,kBAAI,WAAW;AACb,uBAAO,IAAI,QAAQ,SAAS,SAAS,QAAQ;AAC3C,4BAAU,gBAAgB,SAAS,UAAU;AAC3C,4BAAQ,IAAI,WAAW,QAAQ,CAAC;AAAA,kBAClC,GAAG,MAAM;AAAA,gBACX,CAAC;AAAA,cACH;AAAA,YACF;AAAA,UACF;AACA,iBAAO,QAAQ,QAAQ,EAAE,KAAK,WAAW;AACvC,mBAAO,UAAU,cAAc;AAAA,UACjC,CAAC;AAAA,QACH;AACA,iBAAS,aAAa;AACpB,cAAI,OAAO,EAAE,OAAO,eAAe,0BAA0B,cAAc;AAC3E,mBAAS,gBAAgB,UAAU,SAAS;AAC1C,gBAAI,WAAW,SAAS;AACxB,mBAAO,SAAS;AAChB,yBAAa,OAAO,OAAO;AAC3B,uCAA2B,WAAW,MAAM;AAC5C,wBAAY,OAAO,OAAO;AAC1B,sBAAU,OAAO,OAAO,oBAAoB;AAC5C,gCAAoB,kBAAkB;AAAA,UACxC;AACA,2BAAiB,kBAAkB;AACnC,mBAAS,2BAA2B,QAAQ;AAC1C,4BAAgB,OAAO,WAAW;AAAA,UACpC;AACA,mBAAS,uBAAuB,UAAU;AACxC,mBAAO,iBAAiB,EAAE,KAAK,SAAS,QAAQ;AAC9C,qBAAO,YAAY,YAAY,QAAQ,IAAI;AAAA,YAC7C,CAAC,EAAE,KAAK,SAAS,UAAU;AACzB,qBAAO;AAAA,YACT,CAAC,EAAE,KAAK,UAAU,SAAS,QAAQ;AACjC,kBAAI,4CAA4C,MAAM;AACtD,oBAAM,MAAM;AAAA,YACd,CAAC;AAAA,UACH;AACA,mBAAS,mBAAmB;AAC1B,gBAAI,CAAC,cAAc,OAAO,YAAY,yBAAyB,cAAc,CAAC,UAAU,cAAc,KAAK,CAAC,UAAU,cAAc,KAAK,OAAO,UAAU,YAAY;AACpK,qBAAO,MAAM,gBAAgB,EAAE,aAAa,cAAc,CAAC,EAAE,KAAK,SAAS,UAAU;AACnF,oBAAI,SAAS,YAAY,qBAAqB,UAAU,IAAI;AAC5D,uBAAO,OAAO,KAAK,4BAA4B,SAAS,QAAQ;AAC9D,sBAAI,oCAAoC,MAAM;AAC9C,sBAAI,2CAA2C;AAC/C,yBAAO,uBAAuB,0BAA0B;AAAA,gBAC1D,CAAC;AAAA,cACH,CAAC;AAAA,YACH,OAAO;AACL,qBAAO,uBAAuB,0BAA0B;AAAA,YAC1D;AAAA,UACF;AACA,cAAI,OAAO,oBAAoB;AAC7B,gBAAI;AACF,kBAAI,WAAW,OAAO,mBAAmB,MAAM,eAAe;AAC9D,qBAAO;AAAA,YACT,SAAS,IAAP;AACA,kBAAI,wDAAwD,EAAE;AAC9D,qBAAO;AAAA,YACT;AAAA,UACF;AACA,2BAAiB,EAAE,MAAM,kBAAkB;AAC3C,iBAAO,CAAC;AAAA,QACV;AACA,YAAI;AACJ,YAAI;AACJ,iBAAS,qBAAqB,YAAY;AACxC,iBAAO,WAAW,SAAS,GAAG;AAC5B,gBAAI,WAAW,WAAW,MAAM;AAChC,gBAAI,OAAO,YAAY,YAAY;AACjC,uBAAS,MAAM;AACf;AAAA,YACF;AACA,gBAAI,QAAQ,SAAS;AACrB,gBAAI,OAAO,UAAU,UAAU;AAC7B,kBAAI,SAAS,QAAQ,QAAQ;AAC3B,kCAAkB,KAAK,EAAE;AAAA,cAC3B,OAAO;AACL,kCAAkB,KAAK,EAAE,SAAS,GAAG;AAAA,cACvC;AAAA,YACF,OAAO;AACL,oBAAM,SAAS,QAAQ,SAAS,OAAO,SAAS,GAAG;AAAA,YACrD;AAAA,UACF;AAAA,QACF;AACA,iBAAS,SAAS,OAAO;AACvB,iBAAO;AAAA,QACT;AACA,iBAAS,YAAY,MAAM;AACzB,cAAI,QAAQ;AACZ,iBAAO,KAAK,QAAQ,OAAO,SAAS,GAAG;AACrC,gBAAI,IAAI,SAAS,CAAC;AAClB,mBAAO,MAAM,IAAI,IAAI,IAAI,OAAO,IAAI;AAAA,UACtC,CAAC;AAAA,QACH;AACA,YAAI,kBAAkB,CAAC;AACvB,iBAAS,kBAAkB,SAAS;AAClC,cAAI,QAAQ,gBAAgB;AAC5B,cAAI,CAAC,OAAO;AACV,gBAAI,WAAW,gBAAgB;AAC7B,8BAAgB,SAAS,UAAU;AACrC,4BAAgB,WAAW,QAAQ,UAAU,IAAI,OAAO;AAAA,UAC1D;AACA,iBAAO;AAAA,QACT;AACA,iBAAS,eAAe;AACtB,cAAI,QAAQ,IAAI,MAAM;AACtB,cAAI,CAAC,MAAM,OAAO;AAChB,gBAAI;AACF,oBAAM,IAAI,MAAM;AAAA,YAClB,SAAS,IAAP;AACA,sBAAQ;AAAA,YACV;AACA,gBAAI,CAAC,MAAM,OAAO;AAChB,qBAAO;AAAA,YACT;AAAA,UACF;AACA,iBAAO,MAAM,MAAM,SAAS;AAAA,QAC9B;AACA,iBAAS,kBAAkB,KAAK,OAAO;AACrC,oBAAU,IAAI,KAAK,KAAK;AACxB,0BAAgB,OAAO;AAAA,QACzB;AACA,iBAAS,SAAS;AAChB,gBAAM,EAAE;AAAA,QACV;AACA,iBAAS,2BAA2B;AAClC,iBAAO;AAAA,QACT;AACA,iBAAS,uBAAuB,MAAM,KAAK,KAAK;AAC9C,iBAAO,WAAW,MAAM,KAAK,MAAM,GAAG;AAAA,QACxC;AACA,iBAAS,0BAA0BP,OAAM;AACvC,cAAI;AACF,uBAAW,KAAKA,QAAO,QAAQ,aAAa,UAAU,EAAE;AACxD,uCAA2B,WAAW,MAAM;AAC5C,mBAAO;AAAA,UACT,SAAS,IAAP;AAAA,UACF;AAAA,QACF;AACA,iBAAS,wBAAwB,eAAe;AAC9C,cAAI,UAAU,OAAO;AACrB,0BAAgB,kBAAkB;AAClC,cAAI,cAAc,yBAAyB;AAC3C,cAAI,gBAAgB,aAAa;AAC/B,mBAAO;AAAA,UACT;AACA,mBAAS,UAAU,GAAG,WAAW,GAAG,WAAW,GAAG;AAChD,gBAAI,oBAAoB,WAAW,IAAI,MAAM;AAC7C,gCAAoB,KAAK,IAAI,mBAAmB,gBAAgB,SAAS;AACzE,gBAAI,UAAU,KAAK,IAAI,aAAa,QAAQ,KAAK,IAAI,eAAe,iBAAiB,GAAG,KAAK,CAAC;AAC9F,gBAAI,cAAc,0BAA0B,OAAO;AACnD,gBAAI,aAAa;AACf,qBAAO;AAAA,YACT;AAAA,UACF;AACA,iBAAO;AAAA,QACT;AACA,YAAI,WAAW,EAAE,UAAU,CAAC,GAAG,SAAS,CAAC,MAAM,CAAC,GAAG,CAAC,CAAC,GAAG,WAAW,SAAS,QAAQ,MAAM;AACxF,cAAI,UAAU,SAAS,QAAQ;AAC/B,cAAI,SAAS,KAAK,SAAS,IAAI;AAC7B,aAAC,WAAW,IAAI,MAAM,KAAK,kBAAkB,SAAS,CAAC,CAAC;AACxD,oBAAQ,SAAS;AAAA,UACnB,OAAO;AACL,oBAAQ,KAAK,IAAI;AAAA,UACnB;AAAA,QACF,GAAG,SAAS,QAAQ,KAAK,WAAW;AAClC,mBAAS,WAAW;AACpB,cAAI,MAAM,OAAO,SAAS,UAAU,KAAK;AACzC,iBAAO;AAAA,QACT,GAAG,QAAQ,SAAS,KAAK;AACvB,cAAI,MAAM,aAAa,GAAG;AAC1B,iBAAO;AAAA,QACT,GAAG,OAAO,SAAS,KAAK,MAAM;AAC5B,iBAAO;AAAA,QACT,EAAE;AACF,iBAAS,UAAU,IAAI;AACrB,iBAAO;AAAA,QACT;AACA,iBAAS,SAAS,IAAI,YAAY,aAAa,QAAQ,WAAW;AAAA,QAClE;AACA,iBAAS,UAAU,IAAI,KAAK,QAAQ,MAAM;AACxC,cAAI,MAAM;AACV,mBAAS,KAAK,GAAG,KAAK,QAAQ,MAAM;AAClC,gBAAI,MAAM,OAAO,OAAO;AACxB,gBAAI,MAAM,OAAO,MAAM,KAAK;AAC5B,mBAAO;AACP,qBAAS,IAAI,GAAG,IAAI,KAAK,KAAK;AAC5B,uBAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AAAA,YACxC;AACA,mBAAO;AAAA,UACT;AACA,iBAAO,QAAQ,KAAK;AACpB,iBAAO;AAAA,QACT;AACA,iBAAS,aAAa,KAAK;AACzB,sBAAY,GAAG;AAAA,QACjB;AACA,YAAI,aAAa;AACjB,YAAI,gBAAgB,EAAE,SAAS,QAAQ,2BAA2B,0BAA0B,yBAAyB,wBAAwB,0BAA0B,yBAAyB,YAAY,WAAW,WAAW,UAAU,YAAY,WAAW,eAAe,aAAa;AAC/R,YAAI,MAAM,WAAW;AACrB,YAAI,qBAAqB,OAAO,wBAAwB,WAAW;AACjE,kBAAQ,qBAAqB,OAAO,wBAAwB,OAAO,OAAO,sBAAsB,MAAM,MAAM,SAAS;AAAA,QACvH;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,2BAA2B,OAAO,8BAA8B,WAAW;AAC7E,kBAAQ,2BAA2B,OAAO,8BAA8B,OAAO,OAAO,4BAA4B,MAAM,MAAM,SAAS;AAAA,QACzI;AACA,YAAI,qBAAqB,OAAO,wBAAwB,WAAW;AACjE,kBAAQ,qBAAqB,OAAO,wBAAwB,OAAO,OAAO,sBAAsB,MAAM,MAAM,SAAS;AAAA,QACvH;AACA,YAAI,mBAAmB,OAAO,sBAAsB,WAAW;AAC7D,kBAAQ,mBAAmB,OAAO,sBAAsB,OAAO,OAAO,oBAAoB,MAAM,MAAM,SAAS;AAAA,QACjH;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,gBAAgB,MAAM,MAAM,SAAS;AAAA,QACrG;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,gBAAgB,MAAM,MAAM,SAAS;AAAA,QACrG;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,iBAAiB,OAAO,oBAAoB,WAAW;AACzD,kBAAQ,iBAAiB,OAAO,oBAAoB,OAAO,OAAO,kBAAkB,MAAM,MAAM,SAAS;AAAA,QAC3G;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,yBAAyB,OAAO,4BAA4B,WAAW;AACzE,kBAAQ,yBAAyB,OAAO,4BAA4B,OAAO,OAAO,0BAA0B,MAAM,MAAM,SAAS;AAAA,QACnI;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,iBAAiB,OAAO,oBAAoB,WAAW;AACzD,kBAAQ,iBAAiB,OAAO,oBAAoB,OAAO,OAAO,kBAAkB,MAAM,MAAM,SAAS;AAAA,QAC3G;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,kBAAkB,OAAO,qBAAqB,WAAW;AAC3D,kBAAQ,kBAAkB,OAAO,qBAAqB,OAAO,OAAO,mBAAmB,MAAM,MAAM,SAAS;AAAA,QAC9G;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,gBAAgB,MAAM,MAAM,SAAS;AAAA,QACrG;AACA,YAAI,wBAAwB,OAAO,2BAA2B,WAAW;AACvE,kBAAQ,wBAAwB,OAAO,2BAA2B,OAAO,OAAO,yBAAyB,MAAM,MAAM,SAAS;AAAA,QAChI;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,cAAc,OAAO,iBAAiB,WAAW;AACnD,kBAAQ,cAAc,OAAO,iBAAiB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAClG;AACA,YAAI,cAAc,OAAO,iBAAiB,WAAW;AACnD,kBAAQ,cAAc,OAAO,iBAAiB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAClG;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,cAAc,OAAO,iBAAiB,WAAW;AACnD,kBAAQ,cAAc,OAAO,iBAAiB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAClG;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,kBAAkB,OAAO,qBAAqB,WAAW;AAC3D,kBAAQ,kBAAkB,OAAO,qBAAqB,OAAO,OAAO,mBAAmB,MAAM,MAAM,SAAS;AAAA,QAC9G;AACA,YAAI,yBAAyB,OAAO,4BAA4B,WAAW;AACzE,kBAAQ,yBAAyB,OAAO,4BAA4B,OAAO,OAAO,0BAA0B,MAAM,MAAM,SAAS;AAAA,QACnI;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,oBAAoB,OAAO,uBAAuB,WAAW;AAC/D,kBAAQ,oBAAoB,OAAO,uBAAuB,OAAO,OAAO,qBAAqB,MAAM,MAAM,SAAS;AAAA,QACpH;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,SAAS,OAAO,YAAY,WAAW;AACzC,kBAAQ,SAAS,OAAO,YAAY,OAAO,OAAO,UAAU,MAAM,MAAM,SAAS;AAAA,QACnF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,aAAa,MAAM,MAAM,SAAS;AAAA,QAC5F;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,WAAW,OAAO,cAAc,WAAW;AAC7C,kBAAQ,WAAW,OAAO,cAAc,OAAO,OAAO,YAAY,MAAM,MAAM,SAAS;AAAA,QACzF;AACA,YAAI,uBAAuB,OAAO,0BAA0B,WAAW;AACrE,kBAAQ,uBAAuB,OAAO,0BAA0B,OAAO,OAAO,wBAAwB,MAAM,MAAM,SAAS;AAAA,QAC7H;AACA,YAAI,iBAAiB,OAAO,oBAAoB,WAAW;AACzD,kBAAQ,iBAAiB,OAAO,oBAAoB,OAAO,OAAO,kBAAkB,MAAM,MAAM,SAAS;AAAA,QAC3G;AACA,YAAI,0BAA0B,OAAO,6BAA6B,WAAW;AAC3E,kBAAQ,0BAA0B,OAAO,6BAA6B,OAAO,OAAO,2BAA2B,MAAM,MAAM,SAAS;AAAA,QACtI;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,qBAAqB,OAAO,wBAAwB,WAAW;AACjE,kBAAQ,qBAAqB,OAAO,wBAAwB,OAAO,OAAO,sBAAsB,MAAM,MAAM,SAAS;AAAA,QACvH;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,OAAO,OAAO,UAAU,WAAW;AACrC,kBAAQ,OAAO,OAAO,UAAU,OAAO,OAAO,QAAQ,MAAM,MAAM,SAAS;AAAA,QAC7E;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC/F;AACA,YAAI,gBAAgB,OAAO,mBAAmB,WAAW;AACvD,kBAAQ,gBAAgB,OAAO,mBAAmB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACxG;AACA,YAAI,UAAU,OAAO,aAAa,WAAW;AAC3C,kBAAQ,UAAU,OAAO,aAAa,OAAO,OAAO,WAAW,MAAM,MAAM,SAAS;AAAA,QACtF;AACA,YAAI,QAAQ,OAAO,WAAW,WAAW;AACvC,kBAAQ,QAAQ,OAAO,WAAW,OAAO,OAAO,SAAS,MAAM,MAAM,SAAS;AAAA,QAChF;AACA,YAAI,oBAAoB,OAAO,uBAAuB,WAAW;AAC/D,kBAAQ,oBAAoB,OAAO,uBAAuB,OAAO,OAAO,qBAAqB,MAAM,MAAM,SAAS;AAAA,QACpH;AACA,YAAI,+CAA+C,OAAO,kDAAkD,WAAW;AACrH,kBAAQ,+CAA+C,OAAO,kDAAkD,OAAO,OAAO,gDAAgD,MAAM,MAAM,SAAS;AAAA,QACrM;AACA,YAAI,YAAY,OAAO,eAAe,WAAW;AAC/C,kBAAQ,YAAY,OAAO,eAAe,OAAO,OAAO,cAAc,MAAM,MAAM,SAAS;AAAA,QAC7F;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACtG;AACA,YAAI,aAAa,OAAO,gBAAgB,WAAW;AACjD,kBAAQ,aAAa,OAAO,gBAAgB,OAAO,OAAO,eAAe,MAAM,MAAM,SAAS;AAAA,QAChG;AACA,YAAI,mBAAmB,OAAO,sBAAsB,WAAW;AAC7D,kBAAQ,mBAAmB,OAAO,sBAAsB,OAAO,OAAO,qBAAqB,MAAM,MAAM,SAAS;AAAA,QAClH;AACA,YAAI,eAAe,OAAO,kBAAkB,WAAW;AACrD,kBAAQ,eAAe,OAAO,kBAAkB,OAAO,OAAO,iBAAiB,MAAM,MAAM,SAAS;AAAA,QACtG;AACA,eAAO,WAAW;AAClB,YAAI;AACJ,iBAAS,WAAW,QAAQ;AAC1B,eAAK,OAAO;AACZ,eAAK,UAAU,kCAAkC,SAAS;AAC1D,eAAK,SAAS;AAAA,QAChB;AACA,gCAAwB,SAAS,YAAY;AAC3C,cAAI,CAAC;AACH,gBAAI;AACN,cAAI,CAAC;AACH,oCAAwB;AAAA,QAC5B;AACA,iBAAS,IAAI,MAAM;AACjB,iBAAO,QAAQ;AACf,cAAI,kBAAkB,GAAG;AACvB;AAAA,UACF;AACA,iBAAO;AACP,cAAI,kBAAkB,GAAG;AACvB;AAAA,UACF;AACA,mBAAS,QAAQ;AACf,gBAAI;AACF;AACF,wBAAY;AACZ,mBAAO,eAAe;AACtB,gBAAI;AACF;AACF,wBAAY;AACZ,gCAAoB,MAAM;AAC1B,gBAAI,OAAO;AACT,qBAAO,wBAAwB;AACjC,oBAAQ;AAAA,UACV;AACA,cAAI,OAAO,cAAc;AACvB,mBAAO,aAAa,YAAY;AAChC,uBAAW,WAAW;AACpB,yBAAW,WAAW;AACpB,uBAAO,aAAa,EAAE;AAAA,cACxB,GAAG,CAAC;AACJ,oBAAM;AAAA,YACR,GAAG,CAAC;AAAA,UACN,OAAO;AACL,kBAAM;AAAA,UACR;AAAA,QACF;AACA,eAAO,SAAS;AAChB,iBAAS,SAAS,MAAM;AACtB,uBAAa;AACb,cAAI,CAAC,iBAAiB,GAAG;AACvB,gBAAI,OAAO;AACT,qBAAO,UAAU,IAAI;AACvB,oBAAQ;AAAA,UACV;AACA,gBAAM,MAAM,IAAI,WAAW,IAAI,CAAC;AAAA,QAClC;AACA,YAAI,OAAO,YAAY;AACrB,cAAI,OAAO,OAAO,cAAc;AAC9B,mBAAO,aAAa,CAAC,OAAO,UAAU;AACxC,iBAAO,OAAO,WAAW,SAAS,GAAG;AACnC,mBAAO,WAAW,IAAI,EAAE;AAAA,UAC1B;AAAA,QACF;AACA,YAAI;AACJ,YAAI;AACJ,YAAI,iBAAiB;AACnB,2BAAiB,EAAE,mBAAmB,QAAQ,UAAU,mBAAmB,EAAE,OAAO,SAAS,UAAU;AACrG,mBAAO,CAAC,gBAAgB,kBAAkB,QAAQ,QAAQ,IAAI;AAAA,UAChE,CAAC,GAAG,oBAAoB,QAAQ,UAAU,oBAAoB,EAAE,OAAO,SAAS,UAAU;AACxF,mBAAO,CAAC,gBAAgB,mBAAmB,QAAQ,QAAQ,IAAI;AAAA,UACjE,CAAC,EAAE;AAAA,QACL;AACA,YAAI;AACJ,YAAI,OAAO,uBAAuB,aAAa;AAC7C,yBAAe;AAAA,QACjB,WAAW,OAAO,kCAAkC,aAAa;AAC/D,yBAAe;AAAA,QACjB,OAAO;AACL,gBAAM,IAAI,MAAM,uCAAuC;AAAA,QACzD;AACA,YAAI,gBAAgB;AAClB,cAAI,aAAa,aAAa;AAC9B,uBAAa,cAAc,WAAW;AACpC,uBAAW;AACX,2BAAe,kBAAkB,QAAQ,SAAS,UAAU;AAC1D,sBAAQ,eAAe,qBAAqB,QAAQ;AAAA,YACtD,CAAC;AACD,2BAAe,mBAAmB,QAAQ,SAAS,UAAU;AAC3D,sBAAQ,eAAe,sBAAsB,QAAQ;AAAA,YACvD,CAAC;AAAA,UACH;AAAA,QACF;AACA,eAAO,mBAAmB;AAAA,MAC5B;AAAA,IACF,GAAG;AACH,QAAI,OAAO,YAAY,YAAY,OAAO,WAAW;AACnD,aAAO,UAAU;AAAA,aACV,OAAO,WAAW,cAAc,OAAO;AAC9C,aAAO,CAAC,GAAG,WAAW;AACpB,eAAO;AAAA,MACT,CAAC;AAAA,aACM,OAAO,YAAY;AAC1B,cAAQ,uBAAuB;AAAA,EACnC;AACF,CAAC;AAGD,IAAI,kBAAkB;AACtB,IAAI,kBAAkB;AACtB,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,UAAU,WAAW;AAC/B,SAAK,UAAU;AACf,SAAK,YAAY;AACjB,SAAK,OAAuB,oBAAI,QAAQ;AACxC,SAAK,eAAe;AAAA,EACtB;AAAA,EACA,IAAI,QAAQ;AACV,QAAI,CAAC,KAAK,KAAK,IAAI,MAAM,GAAG;AAC1B,WAAK,UAAU,SAAS,KAAK,SAAS,MAAM;AAAA,IAC9C;AACA,WAAO,KAAK,KAAK,IAAI,MAAM;AAAA,EAC7B;AAAA,EACA,IAAI,QAAQ,OAAO;AACjB,SAAK;AACL,SAAK,KAAK,IAAI,QAAQ,KAAK;AAAA,EAC7B;AAAA,EACA,IAAI,QAAQ;AACV,WAAO,KAAK,KAAK,IAAI,MAAM;AAAA,EAC7B;AAAA,EACA,OAAO,QAAQ;AACb,SAAK;AACL,WAAO,KAAK,KAAK,OAAO,MAAM;AAAA,EAChC;AAAA,EACA,aAAa;AACX,WAAO,KAAK;AAAA,EACd;AACF;AACA,IAAI,gBAAgB,MAAM;AAAA,EACxB,SAAS,QAAQ;AACf,WAAO,kBAAkB,UAAU;AAAA,EACrC;AAAA,EACA,OAAO,QAAQ;AACb,WAAO,kBAAkB,QAAQ;AAAA,EACnC;AAAA,EACA,iBAAiB;AACf,WAAO;AAAA,EACT;AAAA,EACA,KAAK,GAAG;AACN,WAAO,kBAAkB,MAAM;AAAA,EACjC;AAAA,EACA,KAAK,QAAQ;AACX,WAAO,kBAAkB,MAAM;AAAA,EACjC;AAAA,EACA,SAAS,QAAQ;AACf,WAAO,kBAAkB,UAAU;AAAA,EACrC;AAAA,EACA,UAAU,QAAQM,UAAS;AACzB,WAAO,kBAAkB,WAAW;AAAA,EACtC;AAAA,EACA,aAAa;AACX,WAAO,kBAAkB,YAAY;AAAA,EACvC;AAAA,EACA,YAAY,QAAQ,OAAO;AACzB,WAAO,kBAAkB,aAAa;AAAA,EACxC;AAAA,EACA,MAAM,QAAQ,OAAO,OAAO;AAC1B,WAAO,kBAAkB,OAAO;AAAA,EAClC;AAAA,EACA,KAAK,QAAQ,QAAQ,OAAO,OAAO,UAAU;AAC3C,WAAO,kBAAkB,MAAM;AAAA,EACjC;AAAA,EACA,SAAS;AACP,WAAO,kBAAkB,QAAQ;AAAA,EACnC;AAAA,EACA,iBAAiB;AACf,WAAO,kBAAkB,gBAAgB;AAAA,EAC3C;AAAA,EACA,UAAU;AACR,WAAO,KAAK,eAAe,MAAM,KAAK,kBAAkB;AAAA,EAC1D;AAAA,EACA,UAAU;AACR,WAAO,kBAAkB,SAAS;AAAA,EACpC;AACF;AACA,SAAS,kBAAkB,YAAY;AACrC,QAAM,IAAI,MAAM,IAAI,oIAAoI;AAC1J;AAGA,SAAS,QAAQ,QAAQ;AACvB,MAAI,UAAU,OAAO;AACrB,MAAIG,SAAQ;AACZ,SAAO,UAAU,GAAG;AAClB,IAAAA,SAAQ,KAAK,OAAO,IAAI,UAAU;AAClC;AACA,SAAK,QAAQ,SAASA,MAAK;AAAA,EAC7B;AACF;AACA,SAAS,aAAa,QAAQ,SAAS;AACrC,MAAI,OAAO,WAAW,QAAQ,QAAQ;AACpC,UAAM,IAAI,MAAM,yEAAyE,OAAO,iCAAiC,QAAQ,QAAQ;AAAA,EACnJ;AACA,MAAI,UAAU,OAAO;AACrB,MAAIA,SAAQ;AACZ,SAAO,UAAU,GAAG;AAClB,IAAAA,SAAQ,KAAK,OAAO,IAAI,UAAU;AAClC;AACA,SAAK,QAAQ,SAASA,MAAK;AAC3B,SAAK,SAAS,SAASA,MAAK;AAAA,EAC9B;AACF;AACA,SAAS,MAAM,MAAM,GAAG,MAAM;AAC5B,SAAO,KAAK,IAAI,MAAM,KAAK,IAAI,GAAG,IAAI,CAAC;AACzC;AACA,SAAS,kBAAkB,KAAK;AAC9B,SAAO,MAAM,MAAM,IAAI,MAAM,MAAM;AACrC;AACA,SAAS,KAAKE,SAAQ,MAAM,OAAO;AACjC,QAAM,OAAOA,QAAO;AACpB,EAAAA,QAAO,QAAQA,QAAO;AACtB,EAAAA,QAAO,SAAS;AAClB;AACA,SAAS,IAAI,KAAK;AAChB,MAAI,OAAO;AACX,WAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,MAAM;AACtC,YAAQ,IAAI;AAAA,EACd;AACA,SAAO;AACT;AACA,SAAS,YAAY,GAAG,GAAG;AACzB,QAAM,KAAK,KAAK,OAAO;AACvB,SAAO,IAAI,MAAM,IAAI,MAAM;AAC7B;AACA,SAAS,YAAY,GAAG,GAAG;AACzB,MAAI,SAAS;AACb,WAAS,KAAK,GAAG,KAAK,EAAE,QAAQ,MAAM;AACpC,UAAM,OAAO,OAAO,EAAE,GAAG,IAAI,OAAO,EAAE,GAAG;AACzC,cAAU,OAAO;AAAA,EACnB;AACA,SAAO;AACT;AACA,SAAS,OAAO,MAAM,KAAK;AACzB,MAAI,CAAC,MAAM;AACT,UAAM,IAAI,MAAM,OAAO,QAAQ,WAAW,MAAM,IAAI,CAAC;AAAA,EACvD;AACF;AACA,SAAS,kBAAkB,QAAQ,QAAQ,qBAAqB,IAAI;AAClE,SAAO,YAAY,QAAQ,MAAM,GAAG,MAAM,qBAAqB,WAAW,cAAc,mBAAmB;AAC7G;AACA,SAAS,cAAc,GAAG;AACxB,SAAO,KAAK,MAAM,MAAM,+DAA+D;AACzF;AACA,SAAS,QAAQ,KAAK,SAAS,CAAC,GAAG,iBAAiB,OAAO;AACzD,MAAI,UAAU,MAAM;AAClB,aAAS,CAAC;AAAA,EACZ;AACA,MAAI,MAAM,QAAQ,GAAG,KAAK,aAAa,GAAG,KAAK,CAAC,gBAAgB;AAC9D,aAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,cAAQ,IAAI,KAAK,QAAQ,cAAc;AAAA,IACzC;AAAA,EACF,OAAO;AACL,WAAO,KAAK,GAAG;AAAA,EACjB;AACA,SAAO;AACT;AACA,SAAS,cAAc,OAAO;AAC5B,MAAI,MAAM,WAAW,GAAG;AACtB,WAAO;AAAA,EACT;AACA,MAAIX,QAAO,MAAM;AACjB,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,IAAAA,SAAQ,MAAM;AAAA,EAChB;AACA,SAAOA;AACT;AACA,SAAS,cAAc,OAAO;AAC5B,SAAO,MAAM,WAAW;AAC1B;AACA,SAAS,YAAY,IAAI,IAAI;AAC3B,MAAI,OAAO,IAAI;AACb,WAAO;AAAA,EACT;AACA,MAAI,MAAM,QAAQ,MAAM,MAAM;AAC5B,WAAO;AAAA,EACT;AACA,MAAI,GAAG,WAAW,GAAG,QAAQ;AAC3B,WAAO;AAAA,EACT;AACA,WAAS,KAAK,GAAG,KAAK,GAAG,QAAQ,MAAM;AACrC,QAAI,GAAG,QAAQ,GAAG,KAAK;AACrB,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,MAAM,GAAG;AAChB,SAAO,IAAI,MAAM;AACnB;AACA,SAAS,KAAK,GAAG;AACf,MAAI,KAAK,QAAQ,MAAM;AACrB,WAAO,KAAK,KAAK,CAAC;AAAA,EACpB;AACA,MAAI,MAAM,UAAU;AAClB,WAAO;AAAA,EACT,WAAW,MAAM,WAAW;AAC1B,WAAO;AAAA,EACT,OAAO;AACL,UAAM,MAAM,KAAK,IAAI,IAAI,CAAC;AAC1B,YAAQ,MAAM,MAAM,MAAM;AAAA,EAC5B;AACF;AACA,SAAS,oBAAoBA,OAAM;AACjC,QAAM,QAAQ,KAAK,KAAK,KAAK,KAAKA,KAAI,CAAC;AACvC,SAAO,CAAC,OAAO,KAAK,KAAKA,QAAO,KAAK,CAAC;AACxC;AACA,SAAS,sBAAsB,IAAI;AACjC,QAAM,kBAAkB,IAAI,YAAY,EAAE;AAC1C,WAAS,KAAK,GAAG,KAAK,IAAI,EAAE,IAAI;AAC9B,oBAAgB,MAAM;AAAA,EACxB;AACA,UAAQ,eAAe;AACvB,SAAO;AACT;AACA,SAAS,SAAS,GAAGA,OAAM;AACzB,MAAIA,SAAQ,EAAE,QAAQ;AACpB,WAAO;AAAA,EACT;AACA,SAAO,IAAI,IAAI,OAAOA,QAAO,EAAE,MAAM;AACvC;AACA,SAAS,YAAY,SAAS,UAAU,CAAC,YAAY,GAAG,YAAY;AAClE,SAAO,IAAI,QAAQ,CAAC,SAAS,WAAW;AACtC,QAAI,WAAW;AACf,UAAM,QAAQ,MAAM;AAClB,UAAI,QAAQ,GAAG;AACb,gBAAQ;AACR;AAAA,MACF;AACA;AACA,YAAM,cAAc,QAAQ,QAAQ;AACpC,UAAI,cAAc,QAAQ,YAAY,YAAY;AAChD,eAAO;AACP;AAAA,MACF;AACA,iBAAW,OAAO,WAAW;AAAA,IAC/B;AACA,UAAM;AAAA,EACR,CAAC;AACH;AACA,SAAS,uBAAuB,OAAOA,OAAM;AAC3C,MAAI,YAAY;AAChB,MAAI,cAAc;AAClB,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,QAAI,MAAM,OAAO,GAAG;AAClB,mBAAa,MAAM;AAAA,IACrB,WAAW,MAAM,QAAQ,IAAI;AAC3B,UAAI,gBAAgB,IAAI;AACtB,cAAM,MAAM,yDAAyD,uBAAuB,IAAI;AAAA,MAClG;AACA,oBAAc;AAAA,IAChB,WAAW,MAAM,MAAM,GAAG;AACxB,YAAM,MAAM,gCAAgC,MAAM,cAAc,IAAI;AAAA,IACtE;AAAA,EACF;AACA,MAAI,gBAAgB,IAAI;AACtB,QAAIA,QAAO,KAAKA,UAAS,WAAW;AAClC,YAAM,MAAM,QAAQA,0CAAyC,OAAO;AAAA,IACtE;AACA,WAAO;AAAA,EACT;AACA,MAAI,cAAc,GAAG;AACnB,UAAM,MAAM,qCAAqC,kCAAkC;AAAA,EACrF;AACA,MAAIA,QAAO,cAAc,GAAG;AAC1B,UAAM,MAAM,wDAAwDA,WAAU,WAAW;AAAA,EAC3F;AACA,QAAM,WAAW,MAAM,MAAM;AAC7B,WAAS,eAAeA,QAAO;AAC/B,SAAO;AACT;AACA,SAAS,eAAe,MAAM,OAAO;AACnC,QAAM,OAAO,MAAM;AACnB,SAAO,QAAQ,OAAO,MAAM,IAAI,CAAC,IAAI,OAAO,EAAE,IAAI,CAAC,EAAE,OAAO,IAAI;AAChE,SAAO,KAAK,MAAM,CAAC,OAAO,MAAM,CAAC,QAAQ,KAAK,IAAI,GAAG,MAAM,+CAA+C,SAAS,sBAAsB,MAAM;AAC/I,SAAO,KAAK,MAAM,CAAC,OAAO,MAAM,EAAE,CAAC,GAAG,MAAM,0DAA0D,MAAM;AAC5G,SAAO,KAAK,IAAI,CAAC,MAAM,IAAI,IAAI,OAAO,IAAI,CAAC;AAC7C;AACA,SAAS,aAAa,OAAO,MAAM;AACjC,QAAM,WAAW,CAAC;AAClB,QAAM,WAAW,CAAC;AAClB,QAAM,eAAe,QAAQ,QAAQ,MAAM,QAAQ,IAAI,KAAK,KAAK,WAAW;AAC5E,QAAM,OAAO,QAAQ,QAAQ,eAAe,OAAO,eAAe,MAAM,KAAK,EAAE,KAAK;AACpF,MAAI,IAAI;AACR,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,QAAI,QAAQ,MAAM;AAChB,UAAI,KAAK,OAAO,MAAM,MAAM,QAAQ,GAAG;AACrC,cAAM,IAAI,MAAM,sBAAsB,qBAAqB,MAAM,eAAe;AAAA,MAClF;AACA,WAAK,KAAK,MAAM,QAAQ,KAAK,KAAK,OAAO,MAAM,QAAQ,GAAG;AACxD,iBAAS,KAAK,MAAM,GAAG;AACvB,iBAAS,KAAK,EAAE;AAAA,MAClB;AACA,UAAI,KAAK,MAAM,IAAI;AACjB;AAAA,MACF;AAAA,IACF;AACA,QAAI,MAAM,QAAQ,GAAG;AACnB,eAAS,KAAK,MAAM,GAAG;AACvB,eAAS,KAAK,EAAE;AAAA,IAClB;AAAA,EACF;AACA,SAAO,EAAE,UAAU,SAAS;AAC9B;AACA,SAAS,uBAAuB,OAAOA,OAAM;AAC3C,MAAI,SAAS;AACb,MAAI,SAAS,QAAQ,UAAU,WAAW;AACxC,aAAS,IAAI,aAAaA,KAAI;AAAA,EAChC,WAAW,UAAU,SAAS;AAC5B,aAAS,IAAI,WAAWA,KAAI;AAAA,EAC9B,WAAW,UAAU,QAAQ;AAC3B,aAAS,IAAI,WAAWA,KAAI;AAAA,EAC9B,OAAO;AACL,UAAM,IAAI,MAAM,qBAAqB,OAAO;AAAA,EAC9C;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,OAAOA,OAAM;AACtC,MAAI,SAAS;AACb,MAAI,SAAS,QAAQ,UAAU,WAAW;AACxC,aAAS,IAAI,aAAaA,KAAI;AAAA,EAChC,WAAW,UAAU,SAAS;AAC5B,aAAS,IAAI,WAAWA,KAAI;AAAA,EAC9B,WAAW,UAAU,QAAQ;AAC3B,aAAS,IAAI,WAAWA,KAAI;AAAA,EAC9B,WAAW,UAAU,UAAU;AAC7B,aAAS,IAAI,MAAMA,KAAI;AAAA,EACzB,OAAO;AACL,UAAM,IAAI,MAAM,qBAAqB,OAAO;AAAA,EAC9C;AACA,SAAO;AACT;AACA,SAAS,yBAAyB,MAAM,OAAO;AAC7C,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,UAAM,MAAM,KAAK;AACjB,QAAI,MAAM,GAAG,KAAK,CAAC,SAAS,GAAG,GAAG;AAChC,YAAM,MAAM,oBAAoB,iCAAiC,MAAM;AAAA,IACzE;AAAA,EACF;AACF;AACA,SAAS,aAAa,OAAO;AAC3B,SAAO,UAAU,UAAU,UAAU,eAAe,UAAU,aAAa,UAAU,WAAW,UAAU;AAC5G;AACA,SAAS,gBAAgB,SAAS,SAAS;AACzC,MAAI,YAAY,aAAa;AAC3B,WAAO;AAAA,EACT;AACA,MAAI,YAAY,aAAa,YAAY,aAAa;AACpD,WAAO;AAAA,EACT;AACA,MAAI,YAAY,WAAW,YAAY,aAAa,YAAY,aAAa;AAC3E,WAAO;AAAA,EACT;AACA,MAAI,YAAY,UAAU,YAAY,QAAQ;AAC5C,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,aAAa,GAAG;AACvB,SAAO,aAAa,gBAAgB,aAAa,cAAc,aAAa,cAAc,aAAa;AACzG;AACA,SAAS,gBAAgB,OAAO;AAC9B,MAAI,UAAU,aAAa,UAAU,SAAS;AAC5C,WAAO;AAAA,EACT,WAAW,UAAU,aAAa;AAChC,WAAO;AAAA,EACT,WAAW,UAAU,QAAQ;AAC3B,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,iBAAiB,OAAO;AAAA,EAC1C;AACF;AACA,SAAS,qBAAqB,KAAK;AACjC,MAAI,OAAO,MAAM;AACf,WAAO;AAAA,EACT;AACA,MAAI,QAAQ;AACZ,MAAI,QAAQ,CAAC,MAAM,SAAS,EAAE,MAAM;AACpC,SAAO;AACT;AACA,SAAS,SAAS,OAAO;AACvB,SAAO,OAAO,UAAU,YAAY,iBAAiB;AACvD;AACA,SAAS,UAAU,OAAO;AACxB,SAAO,OAAO,UAAU;AAC1B;AACA,SAAS,SAAS,OAAO;AACvB,SAAO,OAAO,UAAU;AAC1B;AACA,SAAS,WAAW,QAAQ;AAC1B,MAAI,MAAM,QAAQ,MAAM,GAAG;AACzB,WAAO,WAAW,OAAO,EAAE;AAAA,EAC7B;AACA,MAAI,kBAAkB,cAAc;AAClC,WAAO;AAAA,EACT,WAAW,kBAAkB,cAAc,kBAAkB,cAAc,kBAAkB,mBAAmB;AAC9G,WAAO;AAAA,EACT,WAAW,SAAS,MAAM,GAAG;AAC3B,WAAO;AAAA,EACT,WAAW,SAAS,MAAM,GAAG;AAC3B,WAAO;AAAA,EACT,WAAW,UAAU,MAAM,GAAG;AAC5B,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,WAAW,GAAG;AACrB,SAAO,CAAC,EAAE,KAAK,EAAE,eAAe,EAAE,QAAQ,EAAE;AAC9C;AACA,SAAS,eAAeA,OAAM,OAAO;AACnC,WAAS,KAAK,OAAO,KAAKA,OAAM,EAAE,IAAI;AACpC,QAAIA,QAAO,OAAO,GAAG;AACnB,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAOA;AACT;AACA,SAAS,eAAe,OAAO;AAC7B,QAAM,OAAO,MAAM;AACnB,MAAI,OAAO,GAAG;AACZ,WAAO,CAAC;AAAA,EACV;AACA,QAAMY,WAAU,IAAI,MAAM,OAAO,CAAC;AAClC,EAAAA,SAAQ,OAAO,KAAK,MAAM,OAAO;AACjC,WAAS,KAAK,OAAO,GAAG,MAAM,GAAG,EAAE,IAAI;AACrC,IAAAA,SAAQ,MAAMA,SAAQ,KAAK,KAAK,MAAM,KAAK;AAAA,EAC7C;AACA,SAAOA;AACT;AACA,SAAS,kBAAkB,QAAQ,OAAO,GAAG,YAAY,OAAO;AAC9D,QAAM,MAAM,IAAI,MAAM;AACtB,MAAI,MAAM,WAAW,GAAG;AACtB,UAAM,IAAI,MAAM,MAAM,YAAY,IAAI;AACtC,aAAS,KAAK,GAAG,KAAK,GAAG,MAAM;AAC7B,UAAI,MAAM,EAAE,SAAS;AAAA,IACvB;AAAA,EACF,OAAO;AACL,UAAM,IAAI,MAAM;AAChB,UAAM,OAAO,MAAM,MAAM,CAAC;AAC1B,UAAM,MAAM,KAAK,OAAO,CAAC,KAAK,MAAM,MAAM,CAAC,KAAK,YAAY,IAAI;AAChE,aAAS,KAAK,GAAG,KAAK,GAAG,MAAM;AAC7B,UAAI,MAAM,kBAAkB,SAAS,KAAK,KAAK,MAAM,GAAG,SAAS;AAAA,IACnE;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,cAAc,OAAO,GAAG,YAAY,OAAO;AAClD,MAAI,MAAM,WAAW,GAAG;AACtB,WAAO,EAAE;AAAA,EACX;AACA,QAAMZ,QAAO,MAAM,OAAO,CAAC,KAAK,MAAM,MAAM,CAAC,KAAK,YAAY,IAAI;AAClE,MAAIA,UAAS,GAAG;AACd,WAAO,CAAC;AAAA,EACV;AACA,MAAIA,UAAS,EAAE,QAAQ;AACrB,UAAM,IAAI,MAAM,IAAI,wCAAwC,EAAE,SAAS,YAAY,0BAA0B,KAAK;AAAA,EACpH;AACA,SAAO,kBAAkB,GAAG,OAAO,GAAG,SAAS;AACjD;AACA,SAAS,mBAAmBA,OAAM,OAAO;AACvC,QAAM,SAAS,oBAAoBA,OAAM,KAAK;AAC9C,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,WAAO,MAAM;AAAA,EACf;AACA,SAAO;AACT;AACA,SAAS,oBAAoBA,OAAM,OAAO;AACxC,MAAI,SAAS,QAAQ,UAAU,aAAa,UAAU,aAAa;AACjE,WAAO,IAAI,aAAaA,KAAI;AAAA,EAC9B,WAAW,UAAU,SAAS;AAC5B,WAAO,IAAI,WAAWA,KAAI;AAAA,EAC5B,WAAW,UAAU,QAAQ;AAC3B,WAAO,IAAI,WAAWA,KAAI;AAAA,EAC5B,OAAO;AACL,UAAM,IAAI,MAAM,qBAAqB,OAAO;AAAA,EAC9C;AACF;AACA,SAAS,0BAA0B,OAAO,OAAO;AAC/C,QAAMA,QAAO,MAAM,OAAO,CAAC,MAAM,SAAS,OAAO,MAAM,CAAC;AACxD,MAAI,SAAS,QAAQ,UAAU,WAAW;AACxC,WAAO,cAAc,OAAO,IAAI,aAAaA,KAAI,CAAC;AAAA,EACpD,WAAW,UAAU,SAAS;AAC5B,WAAO,cAAc,OAAO,IAAI,WAAWA,KAAI,CAAC;AAAA,EAClD,WAAW,UAAU,QAAQ;AAC3B,WAAO,cAAc,OAAO,IAAI,WAAWA,KAAI,CAAC;AAAA,EAClD,OAAO;AACL,UAAM,IAAI,MAAM,qBAAqB,OAAO;AAAA,EAC9C;AACF;AACA,SAAS,mCAAmC,OAAO;AACjD,QAAM,QAAQ,CAAC,YAAY;AACzB,WAAO,OAAO,UAAU,OAAO,KAAK,WAAW,GAAG,MAAM,0EAA0E,SAAS;AAAA,EAC7I,CAAC;AACH;AACA,SAAS,WAAW,MAAM,MAAMY,UAAS;AACvC,MAAI,SAAS,GAAG;AACd,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO,KAAK;AAAA,EACd;AACA,MAAIH,SAAQ,KAAK,KAAK,SAAS;AAC/B,WAAS,KAAK,GAAG,KAAK,KAAK,SAAS,GAAG,EAAE,IAAI;AAC3C,IAAAA,UAASG,SAAQ,MAAM,KAAK;AAAA,EAC9B;AACA,SAAOH;AACT;AACA,SAAS,WAAWA,QAAO,MAAMG,UAAS;AACxC,MAAI,SAAS,GAAG;AACd,WAAO,CAAC;AAAA,EACV,WAAW,SAAS,GAAG;AACrB,WAAO,CAACH,MAAK;AAAA,EACf;AACA,QAAM,OAAO,IAAI,MAAM,IAAI;AAC3B,WAAS,KAAK,GAAG,KAAK,KAAK,SAAS,GAAG,EAAE,IAAI;AAC3C,SAAK,MAAM,KAAK,MAAMA,SAAQG,SAAQ,GAAG;AACzC,IAAAH,UAAS,KAAK,MAAMG,SAAQ;AAAA,EAC9B;AACA,OAAK,KAAK,SAAS,KAAKH;AACxB,SAAO;AACT;AACA,SAAS,UAAUE,SAAQ;AACzB,SAAOA,WAAUA,QAAO,QAAQ,OAAOA,QAAO,SAAS;AACzD;AAGA,IAAI,4BAA4B;AAChC,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,SAAS;AACnB,SAAK,SAAS;AACd,SAAK,QAAQ,CAAC;AACd,SAAK,eAAe,CAAC;AACrB,SAAK,WAAW,CAAC;AACjB,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AAAA,EACxB;AAAA,EACA,YAAY,cAAc,UAAU;AAClC,QAAI,KAAK,YAAY,MAAM;AACzB,UAAI,EAAE,IAAI,EAAE,QAAQ,SAAS,KAAK,IAAI,EAAE,QAAQ,MAAM,IAAI;AACxD,gBAAQ,KAAK,YAAY,KAAK,oEAAoE,eAAe;AAAA,MACnH;AAAA,IACF;AACA,SAAK,eAAe;AACpB,SAAK,WAAW;AAAA,EAClB;AAAA,EACA,aAAa,UAAU,cAAc,SAAS;AAC5C,SAAK,aAAa,YAAY,EAAE,cAAc,QAAQ;AACtD,QAAI,KAAK,SAAS,aAAa,MAAM;AACnC,YAAM,YAAY,KAAK,SAAS;AAChC,UAAI,EAAE,IAAI,EAAE,QAAQ,SAAS,KAAK,IAAI,EAAE,QAAQ,MAAM,IAAI;AACxD,gBAAQ,KAAK,qCAAqC,aAAa,YAAY;AAAA,MAC7E;AACA,WAAK,IAAI,UAAU,SAAS;AAAA,IAC9B;AAAA,EACF;AAAA,EACA,MAAM,SAAS,UAAU;AACvB,QAAI,YAAY,KAAK,OAAO;AAC1B,aAAO,KAAK,MAAM;AAAA,IACpB;AACA,SAAK,MAAM,YAAY,MAAM,KAAK,aAAa,QAAQ;AACvD,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,IAAI,UAAU;AACZ,QAAI,YAAY,KAAK,OAAO;AAC1B,aAAO,KAAK,MAAM;AAAA,IACpB;AACA,UAAM,YAAY,KAAK,aAAa,QAAQ;AAC5C,QAAI,UAAU,SAAS,GAAG;AACxB,YAAM,IAAI,MAAM,QAAQ,4EAA4E;AAAA,IACtG;AACA,SAAK,MAAM,YAAY;AACvB,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,UAAU,UAAU;AAClB,WAAO,KAAK,IAAI,QAAQ;AAAA,EAC1B;AAAA,EACA,QAAQ,UAAU;AAChB,WAAO,KAAK,IAAI,QAAQ;AAAA,EAC1B;AAAA,EACA,WAAW;AACT,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,WAAW;AACb,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,UAAU,OAAO;AACnB,QAAI,KAAK,aAAa,aAAa,MAAM;AACvC,YAAM,IAAI,MAAM,mBAAmB,yCAAyC;AAAA,IAC9E;AACA,SAAK,MAAM,YAAY;AACvB,QAAI,KAAK,aAAa,UAAU,WAAW,MAAM;AAC/C,WAAK,aAAa,UAAU,QAAQ,KAAK;AAAA,IAC3C;AAAA,EACF;AAAA,EACA,aAAa,UAAU;AACrB,QAAI,KAAK,aAAa,aAAa,MAAM;AACvC,YAAM,IAAI,MAAM,yBAAyB,0CAA0C;AAAA,IACrF;AACA,WAAO,KAAK,aAAa,UAAU,aAAa;AAAA,EAClD;AAAA,EACA,SAAS,OAAO;AACd,SAAK,QAAQ,OAAO,OAAO,CAAC,GAAG,KAAK;AAAA,EACtC;AAAA,EACA,QAAQ;AACN,SAAK,QAAQ,CAAC;AACd,SAAK,WAAW,CAAC;AACjB,SAAK,iBAAiB;AAAA,EACxB;AAAA,EACA,mBAAmB;AACjB,QAAI,OAAO,KAAK,WAAW,eAAe,OAAO,KAAK,OAAO,aAAa,eAAe,OAAO,KAAK,OAAO,SAAS,WAAW,aAAa;AAC3I;AAAA,IACF;AACA,UAAM,YAAY,KAAK,eAAe,KAAK,OAAO,SAAS,MAAM;AACjE,QAAI,6BAA6B,WAAW;AAC1C,YAAM,YAAY,UAAU,2BAA2B,MAAM,GAAG;AAChE,gBAAU,QAAQ,CAAC,aAAa;AAC9B,cAAM,CAAC,KAAK,KAAK,IAAI,SAAS,MAAM,GAAG;AACvC,aAAK,SAAS,OAAO,WAAW,KAAK,KAAK;AAAA,MAC5C,CAAC;AAAA,IACH;AAAA,EACF;AACF;AACA,SAAS,eAAe,aAAa;AACnC,QAAM,SAAS,CAAC;AAChB,cAAY,QAAQ,+BAA+B,CAAC,OAAO,OAAO;AAChE,gBAAY,QAAQ,GAAG,IAAI,GAAG,EAAE;AAChC,WAAO,GAAG,KAAK,GAAG;AAAA,EACpB,CAAC;AACD,SAAO;AACT;AACA,SAAS,YAAY,QAAQ,MAAM,OAAO;AACxC,SAAO,mBAAmB,IAAI,KAAK,mBAAmB,SAAS,EAAE;AACnE;AACA,SAAS,WAAW,UAAU,OAAO;AACnC,UAAQ,MAAM,YAAY;AAC1B,MAAI,UAAU,UAAU,UAAU,SAAS;AACzC,WAAO,UAAU;AAAA,EACnB,WAAW,GAAG,CAAC,YAAY,OAAO;AAChC,WAAO,CAAC;AAAA,EACV;AACA,QAAM,IAAI,MAAM,oCAAoC,kBAAkB,WAAW;AACnF;AACA,SAAS,MAAM;AACb,SAAO;AACT;AACA,IAAI,MAAM;AACV,SAAS,qBAAqB,aAAa;AACzC,QAAM;AACR;AAGA,IAAI;AACJ,SAAS,qBAAqB;AAC5B,MAAI,mBAAmB,MAAM;AAC3B,QAAI;AACJ,QAAI,OAAO,WAAW,aAAa;AACjC,WAAK;AAAA,IACP,WAAW,OAAO,WAAW,aAAa;AACxC,WAAK;AAAA,IACP,WAAW,OAAO,YAAY,aAAa;AACzC,WAAK;AAAA,IACP,WAAW,OAAO,SAAS,aAAa;AACtC,WAAK;AAAA,IACP,OAAO;AACL,YAAM,IAAI,MAAM,gCAAgC;AAAA,IAClD;AACA,sBAAkB;AAAA,EACpB;AACA,SAAO;AACT;AACA,SAAS,eAAe;AACtB,QAAM,KAAK,mBAAmB;AAC9B,MAAI,GAAG,cAAc,MAAM;AACzB,OAAG,aAA6B,oBAAI,IAAI;AAAA,EAC1C;AACA,SAAO,GAAG;AACZ;AACA,SAAS,UAAU,KAAKP,QAAO;AAC7B,QAAM,YAAY,aAAa;AAC/B,MAAI,UAAU,IAAI,GAAG,GAAG;AACtB,WAAO,UAAU,IAAI,GAAG;AAAA,EAC1B,OAAO;AACL,UAAM,YAAYA,OAAM;AACxB,cAAU,IAAI,KAAK,SAAS;AAC5B,WAAO,UAAU,IAAI,GAAG;AAAA,EAC1B;AACF;AAGA,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,QAAQ;AACZ,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,MAAM;AACV,IAAI,MAAM;AACV,IAAI,SAAS;AACb,IAAI,SAAS;AACb,IAAI,OAAO;AACX,IAAI,QAAQ;AACZ,IAAI,OAAO;AACX,IAAI,QAAQ;AACZ,IAAI,QAAQ;AACZ,IAAI,UAAU;AACd,IAAI,cAAc;AAClB,IAAI,YAAY;AAChB,IAAI,gBAAgB;AACpB,IAAI,cAAc;AAClB,IAAI,iBAAiB;AACrB,IAAI,WAAW;AACf,IAAI,cAAc;AAClB,IAAI,gBAAgB;AACpB,IAAI,OAAO;AACX,IAAI,OAAO;AACX,IAAI,cAAc;AAClB,IAAI,UAAU;AACd,IAAI,aAAa;AACjB,IAAI,SAAS;AACb,IAAI,SAAS;AACb,IAAI,uBAAuB;AAC3B,IAAI,sBAAsB;AAC1B,IAAI,SAAS;AACb,IAAI,yBAAyB;AAC7B,IAAI,wBAAwB;AAC5B,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,UAAU;AACd,IAAI,SAAS;AACb,IAAI,gBAAgB;AACpB,IAAI,gBAAgB;AACpB,IAAI,eAAe;AACnB,IAAI,wBAAwB;AAC5B,IAAI,sCAAsC;AAC1C,IAAI,qCAAqC;AACzC,IAAI,OAAO;AACX,IAAI,aAAa;AACjB,IAAI,0BAA0B;AAC9B,IAAI,2BAA2B;AAC/B,IAAI,UAAU;AACd,IAAI,SAAS;AACb,IAAI,MAAM;AACV,IAAI,UAAU;AACd,IAAI,MAAM;AACV,IAAI,QAAQ;AACZ,IAAI,MAAM;AACV,IAAI,aAAa;AACjB,IAAI,QAAQ;AACZ,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,gBAAgB;AACpB,IAAI,QAAQ;AACZ,IAAI,WAAW;AACf,IAAI,iBAAiB;AACrB,IAAI,WAAW;AACf,IAAI,WAAW;AACf,IAAI,UAAU;AACd,IAAI,eAAe;AACnB,IAAI,WAAW;AACf,IAAI,OAAO;AACX,IAAI,OAAO;AACX,IAAI,WAAW;AACf,IAAI,QAAQ;AACZ,IAAI,QAAQ;AACZ,IAAI,YAAY;AAChB,IAAI,OAAO;AACX,IAAI,YAAY;AAChB,IAAI,WAAW;AACf,IAAI,MAAM;AACV,IAAI,QAAQ;AACZ,IAAI,aAAa;AACjB,IAAI,aAAa;AACjB,IAAI,YAAY;AAChB,IAAI,aAAa;AACjB,IAAI,aAAa;AACjB,IAAI,aAAa;AACjB,IAAI,MAAM;AACV,IAAI,UAAU;AACd,IAAI,MAAM;AACV,IAAI,UAAU;AACd,IAAI,UAAU;AACd,IAAI,cAAc;AAClB,IAAI,YAAY;AAChB,IAAI,gBAAgB;AACpB,IAAI,oBAAoB;AACxB,IAAI,OAAO;AACX,IAAI,MAAM;AACV,IAAI,UAAU;AACd,IAAI,YAAY;AAChB,IAAI,MAAM;AACV,IAAI,cAAc;AAClB,IAAI,WAAW;AACf,IAAI,MAAM;AACV,IAAI,WAAW;AACf,IAAI,sBAAsB;AAC1B,IAAI,sBAAsB;AAC1B,IAAI,sBAAsB;AAC1B,IAAI,WAAW;AACf,IAAI,SAAS;AACb,IAAI,OAAO;AACX,IAAI,QAAQ;AACZ,IAAI,OAAO;AACX,IAAI,MAAM;AACV,IAAI,QAAQ;AACZ,IAAI,OAAO;AACX,IAAI,QAAQ;AACZ,IAAI,OAAO;AACX,IAAI,aAAa;AACjB,IAAI,OAAO;AACX,IAAI,UAAU;AACd,IAAI,wBAAwB;AAC5B,IAAI,4BAA4B;AAChC,IAAI,iBAAiB;AACrB,IAAI,qBAAqB;AACzB,IAAI,QAAQ;AACZ,IAAI,UAAU;AACd,IAAI,QAAQ;AACZ,IAAI,QAAQ;AACZ,IAAI,YAAY;AAChB,IAAI,eAAe;AACnB,IAAI,SAAS;AACb,IAAI,OAAO;AACX,IAAI,QAAQ;AACZ,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,OAAO;AACX,IAAI,UAAU;AACd,IAAI,WAAW;AACf,IAAI,OAAO;AACX,IAAI,MAAM;AACV,IAAI,iBAAiB;AACrB,IAAI,SAAS;AACb,IAAI,UAAU;AACd,IAAI,sBAAsB;AAC1B,IAAI,gBAAgB;AACpB,IAAI,oBAAoB;AACxB,IAAI,mBAAmB;AACvB,IAAI,gBAAgB;AACpB,IAAI,oBAAoB;AACxB,IAAI,SAAS;AACb,IAAI,eAAe;AACnB,IAAI,eAAe;AACnB,IAAI,cAAc;AAClB,IAAI,yBAAyB;AAC7B,IAAI,MAAM;AACV,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,OAAO;AACX,IAAI,OAAO;AACX,IAAI,YAAY;AAChB,IAAI,YAAY;AAChB,IAAI,SAAS;AACb,IAAI,SAAS;AACb,IAAI,qBAAqB;AACzB,IAAI,aAAa;AACjB,IAAI,YAAY;AAChB,IAAI,OAAO;AACX,IAAI,aAAa;AACjB,IAAI,mBAAmB;AACvB,IAAI,eAAe;AACnB,IAAI,cAAc;AAClB,IAAI,uBAAuB;AAG3B,SAAS,QAAQ,KAAK;AACpB,MAAI,EAAE,IAAI,EAAE,QAAQ,SAAS,KAAK,IAAI,EAAE,QAAQ,MAAM,IAAI;AACxD,YAAQ,KAAK,GAAG,GAAG;AAAA,EACrB;AACF;AACA,SAASS,QAAO,KAAK;AACnB,MAAI,EAAE,IAAI,EAAE,QAAQ,SAAS,KAAK,IAAI,EAAE,QAAQ,MAAM,IAAI;AACxD,YAAQ,IAAI,GAAG,GAAG;AAAA,EACpB;AACF;AAGA,IAAI,iBAAiB,UAAU,kBAAkB,MAAsB,oBAAI,IAAI,CAAC;AAChF,IAAI,eAAe,UAAU,gBAAgB,MAAsB,oBAAI,IAAI,CAAC;AAC5E,SAAS,UAAU,YAAY,aAAa;AAC1C,QAAM,MAAM,QAAQ,YAAY,WAAW;AAC3C,SAAO,eAAe,IAAI,GAAG;AAC/B;AACA,SAAS,YAAY,YAAY;AAC/B,SAAO,aAAa,IAAI,UAAU;AACpC;AACA,SAAS,qBAAqB,aAAa;AACzC,QAAM,KAAK,eAAe,QAAQ;AAClC,QAAM,SAAS,CAAC;AAChB,SAAO,MAAM;AACX,UAAM,EAAE,MAAM,MAAM,IAAI,GAAG,KAAK;AAChC,QAAI,MAAM;AACR;AAAA,IACF;AACA,UAAM,CAAC,KAAKC,OAAM,IAAI;AACtB,UAAM,CAAC,QAAQ,IAAI,IAAI,MAAM,GAAG;AAChC,QAAI,aAAa,aAAa;AAC5B,aAAO,KAAKA,OAAM;AAAA,IACpB;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,eAAeA,SAAQ;AAC9B,QAAM,EAAE,YAAY,YAAY,IAAIA;AACpC,QAAM,MAAM,QAAQ,YAAY,WAAW;AAC3C,MAAI,eAAe,IAAI,GAAG,GAAG;AAC3B,SAAK,eAAe,4BAA4B,oCAAoC;AAAA,EACtF;AACA,iBAAe,IAAI,KAAKA,OAAM;AAChC;AACA,SAAS,iBAAiBA,SAAQ;AAChC,QAAM,EAAE,WAAW,IAAIA;AACvB,MAAI,aAAa,IAAI,UAAU,GAAG;AAChC,QAAI,IAAI,EAAE,QAAQ,OAAO,GAAG;AAC1B,WAAK,gCAAgC,aAAa;AAAA,IACpD;AAAA,EACF;AACA,eAAa,IAAI,YAAYA,OAAM;AACrC;AACA,SAAS,iBAAiB,YAAY,aAAa;AACjD,QAAM,MAAM,QAAQ,YAAY,WAAW;AAC3C,MAAI,CAAC,eAAe,IAAI,GAAG,GAAG;AAC5B,UAAM,IAAI,MAAM,eAAe,4BAA4B,gCAAgC;AAAA,EAC7F;AACA,iBAAe,OAAO,GAAG;AAC3B;AACA,SAAS,mBAAmB,YAAY;AACtC,MAAI,CAAC,aAAa,IAAI,UAAU,GAAG;AACjC,UAAM,IAAI,MAAM,iBAAiB,2CAA2C;AAAA,EAC9E;AACA,eAAa,OAAO,UAAU;AAChC;AACA,SAAS,sBAAsB,uBAAuB,gBAAgB;AACpE,QAAM,UAAU,qBAAqB,qBAAqB;AAC1D,UAAQ,QAAQ,CAAC,iBAAiB;AAChC,UAAM,kBAAkB,OAAO,OAAO,CAAC,GAAG,cAAc,EAAE,aAAa,eAAe,CAAC;AACvF,mBAAe,eAAe;AAAA,EAChC,CAAC;AACH;AACA,SAAS,QAAQ,YAAY,aAAa;AACxC,SAAO,GAAG,eAAe;AAC3B;AAGA,IAAI,eAAe,CAAC;AACpBjB,UAAS,cAAc;AAAA,EACrB,aAAa,MAAM;AAAA,EACnB,QAAQ,MAAM;AAAA,EACd,oCAAoC,MAAM;AAAA,EAC1C,eAAe,MAAM;AAAA,EACrB,mBAAmB,MAAM;AAAA,EACzB,sBAAsB,MAAM;AAAA,EAC5B,iBAAiB,MAAM;AAAA,EACvB,0BAA0B,MAAM;AAAA,EAChC,OAAO,MAAM;AAAA,EACb,gBAAgB,MAAM;AAAA,EACtB,mBAAmB,MAAM;AAAA,EACzB,uBAAuB,MAAM;AAAA,EAC7B,cAAc,MAAM;AAAA,EACpB,aAAa,MAAM;AAAA,EACnB,cAAc,MAAM;AAAA,EACpB,OAAO,MAAM;AAAA,EACb,eAAe,MAAM;AAAA,EACrB,SAAS,MAAM;AAAA,EACf,mBAAmB,MAAM;AAAA,EACzB,wBAAwB,MAAM;AAAA,EAC9B,iBAAiB,MAAM;AAAA,EACvB,WAAW,MAAM;AAAA,EACjB,YAAY,MAAM;AAAA,EAClB,YAAY,MAAM;AAAA,EAClB,wBAAwB,MAAM;AAAA,EAC9B,WAAW,MAAM;AAAA,EACjB,YAAY,MAAM;AAAA,EAClB,OAAO,MAAM;AAAA,EACb,UAAU,MAAM;AAAA,EAChB,WAAW,MAAM;AAAA,EACjB,eAAe,MAAM;AAAA,EACrB,UAAU,MAAM;AAAA,EAChB,cAAc,MAAM;AAAA,EACpB,cAAc,MAAM;AAAA,EACpB,YAAY,MAAM;AAAA,EAClB,oBAAoB,MAAM;AAAA,EAC1B,2BAA2B,MAAM;AAAA,EACjC,qBAAqB,MAAM;AAAA,EAC3B,gBAAgB,MAAM;AAAA,EACtB,mBAAmB,MAAM;AAAA,EACzB,KAAK,MAAMkB;AAAA,EACX,gBAAgB,MAAM;AAAA,EACtB,aAAa,MAAM;AAAA,EACnB,aAAa,MAAM;AAAA,EACnB,UAAU,MAAM;AAAA,EAChB,SAAS,MAAM;AAAA,EACf,cAAc,MAAM;AAAA,EACpB,eAAe,MAAM;AAAA,EACrB,qBAAqB,MAAM;AAAA,EAC3B,cAAc,MAAM;AAAA,EACpB,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,MAAM,MAAM;AAAA,EACZ,eAAe,MAAM;AAAA,EACrB,cAAc,MAAM;AACtB,CAAC;AAGD,IAAI,cAAc,QAAQ,aAAa,CAAC;AACxC,IAAI,OAAO,YAAY,WAAW;AAClC,SAAS,UAAU,KAAK;AACtB,SAAO,KAAK,WAAW,KAAK,MAAM,EAAE;AACtC;AACA,IAAI,KAAK,UAAU,kBAAkB;AACrC,IAAI,KAAK,UAAU,kBAAkB;AACrC,IAAI,KAAK,UAAU,kBAAkB;AACrC,SAAS,SAAS,KAAK;AACrB,SAAO,IAAI,IAAI,IAAI,KAAK,EAAE,CAAC;AAC7B;AACA,SAAS,OAAO,IAAI,QAAQ,UAAU;AACpC,QAAM,QAAQ,GAAG,MAAM,QAAQ,SAAS,QAAQ;AAChD,SAAO,KAAK,UAAU,MAAM,KAAK,KAAK,GAAG,MAAM,IAAI;AACrD;AACA,SAAS,QAAQ,IAAI,QAAQ;AAC3B,SAAO,OAAO,IAAI,QAAQ,CAAC;AAC7B;AACA,SAAS,QAAQ,IAAI,QAAQ;AAC3B,SAAO,OAAO,IAAI,QAAQ,CAAC;AAC7B;AACA,SAAS,SAAS,KAAK,OAAO;AAC5B,SAAO,UAAU,IAAI,MAAM,IAAI,KAAK,KAAK,EAAE,GAAG,IAAI,IAAI,KAAK,KAAK,CAAC;AACnE;AACA,SAAS,UAAU,GAAG,GAAG,OAAO,UAAU,kBAAkB,GAAG;AAC7D,MAAI,IAAI,EAAE,IAAI,CAAC,EAAE,IAAI,IAAI;AACzB,MAAI,EAAE,IAAI,EAAE,KAAK,EAAE,CAAC;AACpB,MAAI,IAAI,EAAE,IAAI,CAAC,EAAE,IAAI,IAAI;AACzB,MAAI,EAAE,IAAI,EAAE,KAAK,EAAE,CAAC;AACpB,MAAI,EAAE,IAAI,IAAI;AACd,SAAO;AACT;AACA,SAAS,uBAAuB,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG;AAChD,MAAI,EAAE,IAAI,CAAC;AACX,MAAI,SAAS,EAAE,IAAI,CAAC,EAAE,IAAI,CAAC,GAAG,EAAE;AAChC,QAAM,IAAI;AACV,MAAI,EAAE,IAAI,CAAC;AACX,MAAI,EAAE,IAAI,CAAC;AACX,MAAI,EAAE,IAAI,SAAS,GAAG,EAAE,CAAC;AACzB,SAAO,CAAC,EAAE,IAAI,CAAC,GAAG,EAAE,IAAI,CAAC,CAAC;AAC5B;AACA,SAAS,0BAA0B,IAAI,QAAQ,GAAG,GAAG;AACnD,SAAO,uBAAuB,QAAQ,IAAI,MAAM,GAAG,QAAQ,IAAI,SAAS,CAAC,GAAG,QAAQ,IAAI,SAAS,EAAE,GAAG,QAAQ,IAAI,SAAS,EAAE,GAAG,GAAG,CAAC;AACtI;AACA,SAAS,aAAa,IAAI,MAAM,GAAG,QAAQ;AACzC,MAAI,OAAO,GAAG;AACZ,UAAM,OAAO,GAAG,IAAI,MAAM,CAAC;AAC3B,UAAM,IAAI,QAAQ,IAAI,CAAC,EAAE,IAAI,EAAE;AAC/B,UAAM,IAAI,QAAQ,IAAI,MAAM,CAAC;AAC7B,UAAM,IAAI,SAAS,GAAG,EAAE,EAAE,IAAI,IAAI,EAAE,IAAI,CAAC;AACzC,UAAM,IAAI,SAAS,GAAG,EAAE,EAAE,IAAI,CAAC,EAAE,IAAI,IAAI;AACzC,WAAO,UAAU,GAAG,GAAG,IAAI;AAAA,EAC7B;AACA,MAAI,OAAO,GAAG;AACZ,UAAM,OAAO,GAAG,IAAI,MAAM,CAAC;AAC3B,UAAM,IAAI,QAAQ,IAAI,CAAC;AACvB,WAAO,UAAU,EAAE,IAAI,CAAC,EAAE,IAAI,GAAG,GAAG,QAAQ,IAAI,MAAM,CAAC,GAAG,IAAI;AAAA,EAChE;AACA,MAAI,MAAM,GAAG;AACX,UAAM,IAAI,GAAG;AACb,UAAM,IAAI,GAAG,OAAO;AACpB,UAAM,IAAI,GAAG,MAAM;AACnB,UAAM,IAAI,KAAK,KAAK;AACpB,UAAM,IAAI,OAAO,KAAK;AACtB,WAAO,SAAS,GAAG,IAAI,CAAC,EAAE,IAAI,GAAG,IAAI,CAAC,CAAC,CAAC,EAAE,IAAI,EAAE;AAAA,EAClD;AACA,SAAO;AACT;AACA,SAAS,cAAc,IAAI,MAAM,GAAG,QAAQ;AAC1C,QAAM,OAAO,GAAG,IAAI,MAAM,CAAC;AAC3B,QAAM,IAAI,QAAQ,IAAI,CAAC,EAAE,IAAI,EAAE;AAC/B,QAAM,IAAI,QAAQ,IAAI,CAAC;AACvB,QAAM,IAAI,QAAQ,IAAI,MAAM,CAAC,EAAE,IAAI,IAAI;AACvC,QAAM,IAAI,QAAQ,IAAI,MAAM,EAAE,EAAE,IAAI,EAAE;AACtC,SAAO,UAAU,SAAS,EAAE,IAAI,CAAC,GAAG,EAAE,EAAE,IAAI,SAAS,GAAG,EAAE,CAAC,EAAE,IAAI,CAAC,GAAG,EAAE,IAAI,SAAS,EAAE,IAAI,EAAE,GAAG,EAAE,CAAC,EAAE,IAAI,CAAC,GAAG,IAAI;AAClH;AACA,SAAS,cAAc,IAAI,MAAM,GAAG,QAAQ;AAC1C,QAAM,OAAO,GAAG,IAAI,MAAM,CAAC;AAC3B,QAAM,IAAI,QAAQ,IAAI,CAAC,EAAE,IAAI,EAAE;AAC/B,QAAM,IAAI,QAAQ,IAAI,CAAC;AACvB,QAAM,IAAI,QAAQ,IAAI,MAAM,CAAC,EAAE,IAAI,IAAI;AACvC,QAAM,IAAI,QAAQ,IAAI,MAAM,EAAE,EAAE,IAAI,EAAE;AACtC,QAAM,IAAI,SAAS,EAAE,IAAI,CAAC,GAAG,EAAE,EAAE,IAAI,SAAS,GAAG,EAAE,CAAC,EAAE,IAAI,CAAC;AAC3D,QAAM,IAAI,UAAU,GAAG,EAAE,IAAI,SAAS,EAAE,IAAI,EAAE,GAAG,EAAE,CAAC,EAAE,IAAI,CAAC,GAAG,IAAI;AAClE,QAAM,KAAK,QAAQ,IAAI,EAAE,EAAE,IAAI,IAAI;AACnC,QAAM,IAAI,QAAQ,IAAI,EAAE;AACxB,QAAM,IAAI,EAAE,IAAI,QAAQ,IAAI,MAAM,EAAE,CAAC,EAAE,IAAI,IAAI;AAC/C,QAAM,IAAI,EAAE,IAAI,QAAQ,IAAI,MAAM,EAAE,CAAC,EAAE,IAAI,IAAI;AAC/C,SAAO,UAAU,SAAS,GAAG,IAAI,CAAC,GAAG,EAAE,EAAE,IAAI,SAAS,GAAG,EAAE,CAAC,EAAE,IAAI,CAAC,GAAG,GAAG,IAAI,SAAS,EAAE,IAAI,CAAC,GAAG,EAAE,CAAC,EAAE,IAAI,CAAC,GAAG,IAAI;AACnH;AACA,SAAS,cAAc,IAAI,MAAM,GAAG,QAAQ;AAC1C,QAAM,OAAO,KAAK,WAAW,IAAI,IAAI;AACrC,MAAI,OAAO,IAAI;AACb,QAAI,OAAO,IAAI;AACb,aAAO,aAAa,IAAI,GAAG;AAAA,IAC7B,OAAO;AACL,aAAO,cAAc,IAAI,GAAG;AAAA,IAC9B;AAAA,EACF,WAAW,OAAO,IAAI;AACpB,WAAO,cAAc,IAAI,GAAG;AAAA,EAC9B;AACA,MAAI,IAAI;AACR,MAAI,IAAI,KAAK,IAAI,EAAE,EAAE,IAAI,GAAG;AAC5B,MAAI,IAAI,SAAS,EAAE,IAAI,EAAE,EAAE,IAAI,GAAG,CAAC,EAAE,IAAI,EAAE;AAC3C,MAAI,IAAI,CAAC,KAAK,OAAO,KAAK,KAAK;AAC/B,MAAI,IAAI,CAAC,KAAK,OAAO,KAAK,KAAK;AAC/B,MAAI,EAAE,IAAI,EAAE,EAAE,IAAI,QAAQ,IAAI,CAAC,CAAC;AAChC,MAAI,SAAS;AACb,QAAM,OAAO,MAAM,KAAK,KAAK;AAC7B,QAAM,SAAS,OAAO,MAAM,IAAI,MAAM;AACtC,KAAG;AACD,QAAI,SAAS,EAAE,IAAI,CAAC,EAAE,IAAI,EAAE,EAAE,EAAE,IAAI,QAAQ,IAAI,SAAS,CAAC,CAAC,GAAG,EAAE,EAAE,IAAI,EAAE;AACxE,QAAI,SAAS,EAAE,IAAI,EAAE,EAAE,EAAE,IAAI,QAAQ,IAAI,SAAS,EAAE,CAAC,GAAG,EAAE,EAAE,IAAI,EAAE;AAClE,QAAI,EAAE,IAAI,EAAE,EAAE;AACd,QAAI,EAAE,IAAI,EAAE,EAAE,EAAE,IAAI,QAAQ,IAAI,SAAS,EAAE,CAAC;AAC5C,QAAI,SAAS,EAAE,IAAI,EAAE,EAAE,GAAG,EAAE,EAAE,IAAI,EAAE;AACpC,QAAI,0BAA0B,IAAI,QAAQ,EAAE,GAAG,IAAI,EAAE,GAAG,EAAE,IAAI,EAAE,EAAE,CAAC;AACnE,QAAI,0BAA0B,IAAI,SAAS,IAAI,EAAE,IAAI,EAAE,EAAE,GAAG,EAAE,IAAI,QAAQ,IAAI,SAAS,EAAE,CAAC,CAAC;AAC3F,KAAC,GAAG,CAAC,IAAI,CAAC,GAAG,CAAC;AACd,cAAU;AAAA,EACZ,SAAS,WAAW;AACpB,QAAM,OAAO,GAAG,IAAI,EAAE,IAAI,GAAG,EAAE,IAAI,CAAC,CAAC;AACrC,WAAS;AACT,IAAE,KAAK,EAAE,GAAG,IAAI,MAAM,IAAI,EAAE;AAC5B,IAAE,KAAK,EAAE,GAAG,IAAI,EAAE,EAAE;AACpB,IAAE,KAAK,EAAE,GAAG,IAAI,EAAE,EAAE;AACpB,MAAI,SAAS,EAAE,IAAI,CAAC,EAAE,IAAI,EAAE,EAAE,EAAE,IAAI,QAAQ,IAAI,SAAS,CAAC,CAAC,GAAG,EAAE,EAAE,IAAI,IAAI;AAC1E,MAAI,SAAS,EAAE,IAAI,EAAE,EAAE,EAAE,IAAI,QAAQ,IAAI,SAAS,EAAE,CAAC,GAAG,EAAE,EAAE,IAAI,IAAI;AACpE,MAAI,EAAE,IAAI,EAAE,GAAG,IAAI,CAAC,CAAC;AACrB,MAAI,EAAE,IAAI,EAAE,GAAG,IAAI,CAAC,EAAE,IAAI,QAAQ,IAAI,SAAS,EAAE,CAAC,CAAC;AACnD,MAAI,SAAS,EAAE,IAAI,EAAE,EAAE,GAAG,EAAE,EAAE,IAAI,IAAI;AACtC,MAAI,0BAA0B,IAAI,QAAQ,EAAE,GAAG,IAAI,IAAI,GAAG,EAAE,IAAI,EAAE,EAAE,CAAC;AACrE,MAAI,0BAA0B,IAAI,SAAS,IAAI,EAAE,IAAI,EAAE,EAAE,GAAG,EAAE,IAAI,QAAQ,IAAI,SAAS,EAAE,CAAC,CAAC;AAC3F,GAAC,GAAG,CAAC,IAAI,CAAC,GAAG,CAAC;AACd,SAAO,UAAU,UAAU,EAAE,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,SAAS,CAAC,EAAE,IAAI,EAAE,CAAC,EAAE,IAAI,CAAC,GAAG,UAAU,EAAE,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,CAAC,GAAG,IAAI;AACxH;AAGA,SAAS,kBAAkB,OAAO,OAAO;AACvC,MAAI,UAAU,UAAU;AACtB,WAAO,aAAa,KAAK;AAAA,EAC3B;AACA,SAAO,aAAa,CAAC,KAAK,GAAG,KAAK;AACpC;AACA,SAAS,mBAAmB,GAAG,OAAO;AACpC,SAAO,aAAa,gBAAgB,UAAU,aAAa,aAAa,cAAc,UAAU,WAAW,aAAa,cAAc,UAAU;AAClJ;AACA,SAAS,aAAa,GAAG,OAAO;AAC9B,MAAI,UAAU,UAAU;AACtB,UAAM,IAAI,MAAM,2CAA2C;AAAA,EAC7D;AACA,MAAI,MAAM,QAAQ,CAAC,GAAG;AACpB,QAAI,QAAQ,CAAC;AAAA,EACf;AACA,MAAI,IAAI,EAAE,QAAQ,OAAO,GAAG;AAC1B,6BAAyB,GAAG,KAAK;AAAA,EACnC;AACA,MAAI,mBAAmB,GAAG,KAAK,GAAG;AAChC,WAAO;AAAA,EACT;AACA,MAAI,SAAS,QAAQ,UAAU,aAAa,UAAU,aAAa;AACjE,WAAO,IAAI,aAAa,CAAC;AAAA,EAC3B,WAAW,UAAU,SAAS;AAC5B,WAAO,IAAI,WAAW,CAAC;AAAA,EACzB,WAAW,UAAU,QAAQ;AAC3B,UAAM,OAAO,IAAI,WAAW,EAAE,MAAM;AACpC,aAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAI,KAAK,MAAM,EAAE,GAAG,MAAM,GAAG;AAC3B,aAAK,MAAM;AAAA,MACb;AAAA,IACF;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,qBAAqB,OAAO;AAAA,EAC9C;AACF;AACA,SAASA,OAAM;AACb,SAAO,IAAI,EAAE,SAAS,IAAI;AAC5B;AACA,SAAS,OAAO,MAAM,cAAc;AAClC,SAAO,IAAI,EAAE,SAAS,MAAM,MAAM,YAAY;AAChD;AACA,SAAS,aAAa,IAAI,WAAW,SAAS;AAC5C,aAAW,YAAY;AACvB,SAAO,IAAI,EAAE,SAAS,OAAO,IAAI,QAAQ;AAC3C;AACA,SAAS,aAAa,OAAO,WAAW,SAAS;AAC/C,aAAW,YAAY;AACvB,SAAO,IAAI,EAAE,SAAS,OAAO,OAAO,QAAQ;AAC9C;AAGA,IAAI,WAAW,MAAM;AAAA,EACnB,YAAY,cAAc,QAAQ;AAChC,SAAK,eAAe;AACpB,SAAK,SAAS;AACd,QAAI,UAAU,MAAM;AAClB,WAAK,SAAS,IAAI,OAAO;AAAA,IAC3B;AAAA,EACF;AAAA,EACA,cAAc,YAAY,QAAQ,GAAG;AACnC,QAAI;AACJ,UAAM,sBAAsB,MAAM;AAChC,gBAAU,EAAE;AAAA,IACd;AACA,QAAI;AACJ,UAAM,QAAQA,KAAI;AAClB,QAAI,KAAK,aAAa,eAAe,GAAG;AACtC,cAAQ,KAAK,aAAa,KAAK,mBAAmB;AAAA,IACpD,OAAO;AACL,0BAAoB;AACpB,iBAAW,UAAU,SAAS;AAC5B,eAAO,SAAS;AAAA,MAClB;AACA,cAAQ,QAAQ,QAAQ,EAAE,UAAUA,KAAI,IAAI,MAAM,CAAC;AAAA,IACrD;AACA,QAAI,IAAI,EAAE,QAAQ,8BAA8B,GAAG;AACjD,eAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,cAAM,SAAS,QAAQ;AACvB,eAAO,KAAK,EAAE,KAAK,CAAC,eAAe;AACjC,oCAA0B,YAAY,OAAO,OAAO,UAAU;AAAA,QAChE,CAAC;AAAA,MACH;AAAA,IACF;AACA,UAAM,gBAAgB;AAAA,MACpB;AAAA,MACA;AAAA,MACA;AAAA,MACA,QAAQ,MAAM,KAAK,CAAC,WAAW,OAAO,QAAQ;AAAA,MAC9C,WAAW,MAAM,KAAK,CAAC,WAAW,OAAO,uBAAuB,OAAO,OAAO,oBAAoB,IAAI,EAAE;AAAA,IAC1G;AACA,WAAO;AAAA,EACT;AAAA,EACA,iBAAiB,eAAe;AAC9B,UAAM,EAAE,YAAY,SAAS,QAAQ,QAAQ,UAAU,IAAI;AAC3D,YAAQ,QAAQ,CAAC,WAAW;AAC1B,cAAQ,IAAI,CAAC,OAAO,KAAK,GAAG,QAAQ,SAAS,CAAC,EAAE,KAAK,CAAC,mBAAmB;AACvE,aAAK,OAAO,iBAAiB,YAAY,QAAQ,eAAe,IAAI,eAAe,IAAI,QAAQ,eAAe,EAAE;AAAA,MAClH,CAAC;AAAA,IACH,CAAC;AAAA,EACH;AACF;AACA,SAAS,0BAA0B,MAAM,OAAO,YAAY;AAC1D,MAAI,UAAU,WAAW;AACvB,WAAO;AAAA,EACT;AACA,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,UAAM,MAAM,KAAK;AACjB,QAAI,MAAM,GAAG,KAAK,CAAC,SAAS,GAAG,GAAG;AAChC,cAAQ,KAAK,SAAS,yBAAyB,aAAa;AAC5D,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO;AACT;AACA,IAAI,SAAS,MAAM;AAAA,EACjB,iBAAiB,MAAM,QAAQ,MAAM,QAAQ,QAAQ,WAAW;AAC9D,UAAM,QAAQ,OAAO,WAAW,WAAW,SAAS,GAAG,YAAY,CAAC,IAAI,OAAO;AAC/E,UAAM,aAAa,SAAS,MAAM,EAAE;AACpC,UAAM,OAAO,OAAO;AACpB,UAAMf,QAAO,OAAO;AACpB,UAAM,QAAQ,SAAS,OAAO,MAAM,SAAS,GAAG,EAAE;AAClD,QAAI,yBAAyB;AAC7B,eAAW,SAAS,QAAQ;AAC1B,YAAM,SAAS,OAAO;AACtB,UAAI,UAAU,MAAM;AAClB,cAAM,aAAa,OAAO,SAAS,OAAO;AAC1C,cAAM,YAAY,WAAW;AAC7B,kCAA0B,GAAG,UAAU,cAAc,YAAY,IAAI,aAAa;AAAA,MACpF;AAAA,IACF;AACA,YAAQ,IAAI,KAAK,gBAAgB,WAAW,SAAS,WAAWA,WAAU,4BAA4B,aAAa,oBAAoB,aAAa,cAAc,iBAAiB,gBAAgB,kBAAkB;AAAA,EACvN;AACF;AAGA,SAAS,qBAAqB,MAAM,IAAI,GAAG;AACzC,QAAM,eAAe,CAAC;AACtB,QAAM,aAAa,CAAC;AACpB,WAAS,KAAK,GAAG,KAAK,GAAG,QAAQ,MAAM;AACrC,iBAAa,GAAG,IAAI,MAAM;AAAA,EAC5B;AACA,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,UAAMgB,QAAO,KAAK;AAClB,UAAM,aAAaA,MAAK;AACxB,eAAW,aAAa,YAAY;AAClC,YAAM,SAAS,WAAW;AAC1B,UAAI,gBAAgB;AACpB,eAAS,IAAI,GAAG,IAAI,GAAG,QAAQ,KAAK;AAClC,YAAI,aAAa,OAAO,KAAK;AAC3B,UAAAA,MAAK,QAAQ,QAAQ,CAAC,WAAW,aAAa,OAAO,MAAM,IAAI;AAC/D,0BAAgB;AAChB,qBAAWA,MAAK,MAAM;AACtB;AAAA,QACF;AAAA,MACF;AACA,UAAI,eAAe;AACjB;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,QAAM,iBAAiB,CAAC;AACxB,iBAAe,EAAE,MAAM;AACvB,QAAM,WAAW,CAAC;AAClB,WAAS,KAAK,KAAK,SAAS,GAAG,MAAM,GAAG,MAAM;AAC5C,UAAMA,QAAO,KAAK;AAClB,UAAM,aAAaA,MAAK;AACxB,aAAS,IAAI,GAAG,IAAIA,MAAK,QAAQ,QAAQ,KAAK;AAC5C,UAAI,eAAeA,MAAK,QAAQ,GAAG,KAAK;AACtC,mBAAW,aAAa,YAAY;AAClC,yBAAe,WAAW,WAAW,MAAM;AAC3C,mBAASA,MAAK,MAAM;AAAA,QACtB;AACA;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,QAAM,eAAe,CAAC;AACtB,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,UAAMA,QAAO,KAAK;AAClB,QAAI,WAAWA,MAAK,OAAO,SAASA,MAAK,KAAK;AAC5C,YAAM,eAAe,CAAC;AACtB,iBAAW,aAAaA,MAAK,QAAQ;AACnC,cAAM,YAAYA,MAAK,OAAO;AAC9B,YAAI,aAAa,UAAU,KAAK;AAC9B,uBAAa,aAAa;AAAA,QAC5B;AAAA,MACF;AACA,YAAM,aAAa,OAAO,OAAO,CAAC,GAAGA,KAAI;AACzC,iBAAW,SAAS;AACpB,iBAAW,UAAUA,MAAK;AAC1B,mBAAa,KAAK,UAAU;AAAA,IAC9B;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,uBAAuB,8BAA8B,cAAc,OAAO,MAAM;AACvF,WAAS,KAAK,aAAa,SAAS,GAAG,MAAM,GAAG,MAAM;AACpD,UAAMA,QAAO,aAAa;AAC1B,UAAM,MAAM,CAAC;AACb,IAAAA,MAAK,QAAQ,QAAQ,CAAC,MAAM;AAC1B,YAAM,aAAa,6BAA6B,EAAE;AAClD,UAAI,cAAc,MAAM;AACtB,YAAI,KAAK,UAAU;AAAA,MACrB,OAAO;AACL,YAAI,KAAK,IAAI;AAAA,MACf;AAAA,IACF,CAAC;AACD,QAAIA,MAAK,YAAY,MAAM;AACzB,YAAM,IAAI,MAAM,4DAA4DA,MAAK,aAAa;AAAA,IAChG;AACA,UAAM,iBAAiBA,MAAK,SAAS,GAAG;AACxC,eAAW,aAAaA,MAAK,QAAQ;AACnC,UAAI,EAAE,aAAa,iBAAiB;AAClC,cAAM,IAAI,MAAM,iCAAiC,yCAAyC,OAAO,KAAK,cAAc,IAAI;AAAA,MAC1H;AACA,YAAM,KAAK,MAAM,MAAM,eAAe,WAAW,CAAC;AAClD,UAAI,GAAG,UAAU,WAAW;AAC1B,cAAM,IAAI,MAAM,4BAA4BA,MAAK,qCAAqC,iDAAiD,GAAG,QAAQ;AAAA,MACpJ;AACA,YAAM,IAAIA,MAAK,OAAO;AACtB,UAAI,CAAC,YAAY,GAAG,OAAO,EAAE,KAAK,GAAG;AACnC,cAAM,IAAI,MAAM,4BAA4BA,MAAK,sCAAsC,yBAAyB,GAAG,wDAAwD,EAAE,QAAQ;AAAA,MACvL;AACA,UAAI,6BAA6B,EAAE,OAAO,MAAM;AAC9C,qCAA6B,EAAE,MAAM;AAAA,MACvC,OAAO;AACL,cAAM,cAAc,6BAA6B,EAAE;AACnD,qCAA6B,EAAE,MAAM,KAAK,aAAa,EAAE;AACzD,oBAAY,QAAQ;AAAA,MACtB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,wBAAwB;AAC5B,IAAI,6BAA6B;AACjC,IAAI,wBAAwB;AAC5B,SAAS,eAAe,MAAM,OAAO,OAAO,SAAS;AACnD,QAAMJ,WAAU,eAAe,KAAK;AACpC,QAAM,YAAY,wBAAwB,MAAM,OAAO,OAAOA,QAAO;AACrE,QAAM,OAAO,MAAM;AACnB,QAAM,YAAY,kBAAkB,MAAM,OAAO,OAAOA,UAAS,SAAS;AAC1E,QAAMK,SAAQ,CAAC,QAAQ;AACvB,MAAI,SAAS;AACX,IAAAA,OAAM,KAAK,YAAY,OAAO;AAC9B,IAAAA,OAAM,KAAK,WAAW,MAAM;AAC5B,IAAAA,OAAM,KAAK,aAAa,QAAQ;AAChC,IAAAA,OAAM,KAAK,WAAW;AAAA,EACxB;AACA,EAAAA,OAAM,KAAK,UAAU,IAAI,CAAC,OAAO,SAAS,EAAE,EAAE,KAAK,IAAI,CAAC;AACxD,SAAOA,OAAM,KAAK,IAAI;AACxB;AACA,SAAS,wBAAwB,MAAM,OAAO,OAAOL,UAAS;AAC5D,QAAM,KAAK,cAAc,KAAK;AAC9B,QAAM,UAAUA,SAAQA,SAAQ,SAAS;AACzC,QAAM,YAAY,IAAI,MAAM,OAAO,EAAE,KAAK,CAAC;AAC3C,QAAM,OAAO,MAAM;AACnB,QAAM,iBAAiB,UAAU,cAAc,oBAAoB,IAAI,IAAI;AAC3E,MAAI,OAAO,GAAG;AACZ,aAAS,MAAM,GAAG,MAAM,KAAK,SAAS,OAAO;AAC3C,YAAM,SAAS,MAAM;AACrB,eAAS,IAAI,GAAG,IAAI,SAAS,KAAK;AAChC,kBAAU,KAAK,KAAK,IAAI,UAAU,IAAI,YAAY,eAAe,SAAS,IAAI,GAAG,KAAK,EAAE,MAAM;AAAA,MAChG;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,YAAY,KAAK,MAAM,OAAO;AACrC,MAAI;AACJ,MAAI,MAAM,QAAQ,GAAG,GAAG;AACtB,aAAS,GAAG,WAAW,IAAI,GAAG,QAAQ,qBAAqB,CAAC,OAAO,WAAW,IAAI,GAAG,QAAQ,qBAAqB,CAAC;AAAA,EACrH,WAAW,SAAS,GAAG,GAAG;AACxB,aAAS,IAAI;AAAA,EACf,WAAW,UAAU,QAAQ;AAC3B,aAAS,gBAAgB,GAAG;AAAA,EAC9B,OAAO;AACL,aAAS,WAAW,IAAI,QAAQ,qBAAqB,CAAC,EAAE,SAAS;AAAA,EACnE;AACA,SAAO,SAAS,QAAQ,IAAI;AAC9B;AACA,SAAS,gBAAgB,GAAG;AAC1B,SAAO,MAAM,IAAI,UAAU;AAC7B;AACA,SAAS,kBAAkB,MAAM,OAAO,OAAOA,UAAS,WAAW,SAAS,MAAM;AAChF,QAAM,oBAAoB,UAAU,cAAc,IAAI;AACtD,QAAMZ,QAAO,MAAM;AACnB,QAAM,OAAO,MAAM;AACnB,MAAI,SAAS,GAAG;AACd,QAAI,UAAU,aAAa;AACzB,YAAM,eAAe,oBAAoB,IAAI;AAC7C,aAAO,CAAC,YAAY,aAAa,IAAI,GAAG,KAAK,CAAC;AAAA,IAChD;AACA,QAAI,UAAU,QAAQ;AACpB,aAAO,CAAC,gBAAgB,KAAK,EAAE,CAAC;AAAA,IAClC;AACA,WAAO,CAAC,KAAK,GAAG,SAAS,CAAC;AAAA,EAC5B;AACA,MAAI,SAAS,GAAG;AACd,QAAIA,QAAO,uBAAuB;AAChC,YAAM,gBAAgB,6BAA6B;AACnD,UAAI,YAAY,MAAM,KAAK,KAAK,MAAM,GAAG,aAAa,CAAC;AACvD,UAAI,WAAW,MAAM,KAAK,KAAK,OAAOA,QAAO,8BAA8B,mBAAmBA,QAAO,iBAAiB,CAAC;AACvH,UAAI,UAAU,aAAa;AACzB,oBAAY,oBAAoB,SAAS;AACzC,mBAAW,oBAAoB,QAAQ;AAAA,MACzC;AACA,aAAO;AAAA,QACL,MAAM,UAAU,IAAI,CAAC,GAAG,OAAO,YAAY,GAAG,UAAU,KAAK,KAAK,CAAC,EAAE,KAAK,IAAI,IAAI,YAAY,SAAS,IAAI,CAAC,GAAG,OAAO,YAAY,GAAG,UAAUA,QAAO,6BAA6B,KAAK,KAAK,CAAC,EAAE,KAAK,IAAI,IAAI;AAAA,MAC/M;AAAA,IACF;AACA,UAAM,cAAc,UAAU,cAAc,oBAAoB,IAAI,IAAI,MAAM,KAAK,IAAI;AACvF,WAAO;AAAA,MACL,MAAM,YAAY,IAAI,CAAC,GAAG,OAAO,YAAY,GAAG,UAAU,KAAK,KAAK,CAAC,EAAE,KAAK,IAAI,IAAI;AAAA,IACtF;AAAA,EACF;AACA,QAAM,WAAW,MAAM,MAAM,CAAC;AAC9B,QAAM,aAAaY,SAAQ,MAAM,CAAC;AAClC,QAAM,SAASA,SAAQ,KAAK;AAC5B,QAAMK,SAAQ,CAAC;AACf,MAAIjB,QAAO,uBAAuB;AAChC,aAAS,KAAK,GAAG,KAAK,4BAA4B,MAAM;AACtD,YAAM,QAAQ,KAAK;AACnB,YAAM,MAAM,QAAQ;AACpB,MAAAiB,OAAM,KAAK,GAAG,kBAAkB,KAAK,MAAM,OAAO,GAAG,GAAG,UAAU,OAAO,YAAY,WAAW,KAAK,CAAC;AAAA,IACxG;AACA,IAAAA,OAAM,KAAK,KAAK;AAChB,aAAS,KAAKjB,QAAO,4BAA4B,KAAKA,OAAM,MAAM;AAChE,YAAM,QAAQ,KAAK;AACnB,YAAM,MAAM,QAAQ;AACpB,MAAAiB,OAAM,KAAK,GAAG,kBAAkB,KAAK,MAAM,OAAO,GAAG,GAAG,UAAU,OAAO,YAAY,WAAW,OAAOjB,QAAO,CAAC,CAAC;AAAA,IAClH;AAAA,EACF,OAAO;AACL,aAAS,KAAK,GAAG,KAAKA,OAAM,MAAM;AAChC,YAAM,QAAQ,KAAK;AACnB,YAAM,MAAM,QAAQ;AACpB,MAAAiB,OAAM,KAAK,GAAG,kBAAkB,KAAK,MAAM,OAAO,GAAG,GAAG,UAAU,OAAO,YAAY,WAAW,OAAOjB,QAAO,CAAC,CAAC;AAAA,IAClH;AAAA,EACF;AACA,QAAM,MAAM,SAAS,IAAI,MAAM;AAC/B,EAAAiB,OAAM,KAAK,MAAMA,OAAM,KAAK;AAC5B,WAAS,KAAK,GAAG,KAAKA,OAAM,SAAS,GAAG,MAAM;AAC5C,IAAAA,OAAM,MAAM,MAAMA,OAAM,MAAM;AAAA,EAChC;AACA,MAAI,aAAa;AACjB,WAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,kBAAc;AAAA,EAChB;AACA,EAAAA,OAAMA,OAAM,SAAS,KAAK,MAAMA,OAAMA,OAAM,SAAS,KAAK,OAAO,SAAS,KAAK;AAC/E,SAAOA;AACT;AACA,SAAS,oBAAoB,MAAM;AACjC,QAAM,gBAAgB,CAAC;AACvB,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM,GAAG;AAC1C,kBAAc,KAAK,CAAC,KAAK,KAAK,KAAK,KAAK,EAAE,CAAC;AAAA,EAC7C;AACA,SAAO;AACT;AAGA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,OAAO,OAAO,QAAQ;AAChC,SAAK,QAAQ;AACb,SAAK,QAAQ,MAAM,MAAM;AACzB,SAAK,OAAO,cAAc,KAAK;AAC/B,QAAI,UAAU,MAAM;AAClB,YAAM,KAAK,OAAO;AAClB,aAAO,OAAO,KAAK,MAAM,MAAM,qBAAqB,sDAAsD,KAAK,QAAQ;AAAA,IACzH;AACA,QAAI,UAAU,aAAa;AACzB,YAAM,IAAI,MAAM,4JAA4J;AAAA,IAC9K;AACA,SAAK,SAAS,UAAU,kBAAkB,OAAO,KAAK,IAAI;AAC1D,SAAK,UAAU,eAAe,KAAK;AAAA,EACrC;AAAA,EACA,IAAI,UAAU,MAAM;AAClB,QAAI,KAAK,WAAW,GAAG;AACrB,aAAO,CAAC,CAAC;AAAA,IACX;AACA,WAAO,KAAK,WAAW,KAAK,MAAM,MAAM,uCAAuC,KAAK,gCAAgC,KAAK,OAAO;AAChI,UAAMR,SAAQ,KAAK,WAAW,IAAI;AAClC,SAAK,OAAOA,UAAS;AAAA,EACvB;AAAA,EACA,OAAO,MAAM;AACX,QAAI,KAAK,WAAW,GAAG;AACrB,aAAO,CAAC,CAAC;AAAA,IACX;AACA,QAAI,KAAK;AACT,eAAW,OAAO,MAAM;AACtB,UAAI,MAAM,KAAK,OAAO,KAAK,MAAM,KAAK;AACpC,cAAM,MAAM,qCAAqC,wBAAwB,KAAK;AAC9E,cAAM,IAAI,MAAM,GAAG;AAAA,MACrB;AACA;AAAA,IACF;AACA,QAAIA,SAAQ,KAAK,KAAK,SAAS;AAC/B,aAAS,KAAK,GAAG,KAAK,KAAK,SAAS,GAAG,EAAE,IAAI;AAC3C,MAAAA,UAAS,KAAK,QAAQ,MAAM,KAAK;AAAA,IACnC;AACA,WAAO,KAAK,OAAOA;AAAA,EACrB;AAAA,EACA,WAAW,MAAM;AACf,QAAI,KAAK,SAAS,GAAG;AACnB,aAAO;AAAA,IACT,WAAW,KAAK,SAAS,GAAG;AAC1B,aAAO,KAAK;AAAA,IACd;AACA,QAAIA,SAAQ,KAAK,KAAK,SAAS;AAC/B,aAAS,KAAK,GAAG,KAAK,KAAK,SAAS,GAAG,EAAE,IAAI;AAC3C,MAAAA,UAAS,KAAK,QAAQ,MAAM,KAAK;AAAA,IACnC;AACA,WAAOA;AAAA,EACT;AAAA,EACA,WAAWA,QAAO;AAChB,QAAI,KAAK,SAAS,GAAG;AACnB,aAAO,CAAC;AAAA,IACV,WAAW,KAAK,SAAS,GAAG;AAC1B,aAAO,CAACA,MAAK;AAAA,IACf;AACA,UAAM,OAAO,IAAI,MAAM,KAAK,MAAM,MAAM;AACxC,aAAS,KAAK,GAAG,KAAK,KAAK,SAAS,GAAG,EAAE,IAAI;AAC3C,WAAK,MAAM,KAAK,MAAMA,SAAQ,KAAK,QAAQ,GAAG;AAC9C,MAAAA,UAAS,KAAK,MAAM,KAAK,QAAQ;AAAA,IACnC;AACA,SAAK,KAAK,SAAS,KAAKA;AACxB,WAAO;AAAA,EACT;AAAA,EACA,IAAI,OAAO;AACT,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,WAAW;AACT,WAAO,UAAU,EAAE,WAAW,KAAK,QAAQ,KAAK,OAAO,KAAK,KAAK;AAAA,EACnE;AACF;AACA,IAAI,YAAY;AAChB,IAAI,YAAY;AAChB,IAAI,uBAAuB;AAC3B,SAAS,iBAAiB,IAAI;AAC5B,cAAY;AACd;AACA,SAAS,aAAa,SAAS;AAC7B,cAAY;AACd;AACA,SAAS,wBAAwB,IAAI;AACnC,yBAAuB;AACzB;AACA,IAAI,SAAS,MAAM;AAAA,EACjB,YAAY,OAAO,OAAO,QAAQ,IAAI;AACpC,SAAK,OAAO;AACZ,SAAK,qBAAqB;AAC1B,SAAK,QAAQ,MAAM,MAAM;AACzB,SAAK,QAAQ,SAAS;AACtB,SAAK,OAAO,cAAc,KAAK;AAC/B,SAAK,UAAU,eAAe,KAAK;AACnC,SAAK,SAAS;AACd,SAAK,KAAK;AACV,SAAK,WAAW,KAAK,OAAO,IAAI,KAAK,KAAK,SAAS,IAAI;AAAA,EACzD;AAAA,EACA,IAAI,OAAO;AACT,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,MAAM,SAAS;AACb,UAAM,OAAO,MAAM,KAAK,KAAK;AAC7B,WAAO,UAAU,OAAO,KAAK,OAAO,KAAK,OAAO,IAAI;AAAA,EACtD;AAAA,EACA,aAAa;AACX,WAAO,UAAU,OAAO,KAAK,OAAO,KAAK,OAAO,KAAK,SAAS,CAAC;AAAA,EACjE;AAAA,EACA,MAAM,QAAQ;AACZ,UAAM,OAAO,MAAM,KAAK,KAAK;AAC7B,WAAO,cAAc,KAAK,OAAO,MAAM,KAAK,UAAU,WAAW;AAAA,EACnE;AAAA,EACA,YAAY;AACV,WAAO,cAAc,KAAK,OAAO,KAAK,SAAS,GAAG,KAAK,UAAU,WAAW;AAAA,EAC9E;AAAA,EACA,MAAM,OAAO;AACX,SAAK,gBAAgB;AACrB,UAAM,OAAO,UAAU,EAAE,KAAK,KAAK,MAAM;AACzC,QAAI,KAAK,UAAU,UAAU;AAC3B,YAAM,QAAQ,MAAM;AACpB,UAAI;AACF,eAAO,MAAM,IAAI,CAAC,MAAM,aAAa,CAAC,CAAC;AAAA,MACzC,SAAS,IAAP;AACA,cAAM,IAAI,MAAM,+FAA+F;AAAA,MACjH;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,UAAUH,UAAS;AACjB,SAAK,gBAAgB;AACrB,WAAO,UAAU,EAAE,UAAU,KAAK,QAAQA,QAAO;AAAA,EACnD;AAAA,EACA,WAAW;AACT,SAAK,gBAAgB;AACrB,UAAM,OAAO,UAAU,EAAE,SAAS,KAAK,MAAM;AAC7C,QAAI,KAAK,UAAU,UAAU;AAC3B,UAAI;AACF,eAAO,KAAK,IAAI,CAAC,MAAM,aAAa,CAAC,CAAC;AAAA,MACxC,SAAS,IAAP;AACA,cAAM,IAAI,MAAM,+FAA+F;AAAA,MACjH;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,QAAQ;AACZ,SAAK,gBAAgB;AACrB,UAAM,OAAO,MAAM,UAAU,EAAE,KAAK,KAAK,MAAM;AAC/C,QAAI,KAAK,UAAU,UAAU;AAC3B,aAAO;AAAA,IACT,OAAO;AACL,aAAO,IAAI,WAAW,KAAK,MAAM;AAAA,IACnC;AAAA,EACF;AAAA,EACA,UAAU;AACR,QAAI,KAAK,YAAY;AACnB;AAAA,IACF;AACA,cAAU,EAAE,cAAc,IAAI;AAC9B,SAAK,qBAAqB;AAAA,EAC5B;AAAA,EACA,IAAI,aAAa;AACf,WAAO,KAAK;AAAA,EACd;AAAA,EACA,kBAAkB;AAChB,QAAI,KAAK,YAAY;AACnB,YAAM,IAAI,MAAM,qBAAqB;AAAA,IACvC;AAAA,EACF;AAAA,EACA,MAAM,UAAU,OAAO;AACrB,WAAO,UAAU,MAAM,MAAM,OAAO;AAAA,EACtC;AAAA,EACA,QAAQ;AACN,SAAK,gBAAgB;AACrB,WAAO,UAAU,MAAM,IAAI;AAAA,EAC7B;AAAA,EACA,SAAS,UAAU,OAAO;AACxB,UAAM,OAAO,KAAK,SAAS;AAC3B,WAAO,eAAe,MAAM,KAAK,OAAO,KAAK,OAAO,OAAO;AAAA,EAC7D;AAAA,EACA,KAAK,OAAO;AACV,SAAK,gBAAgB;AACrB,WAAO,UAAU,KAAK,MAAM,KAAK;AAAA,EACnC;AAAA,EACA,SAAS,YAAY,MAAM,MAAM,OAAO;AACtC,SAAK,gBAAgB;AACrB,WAAO,UAAU,EAAE,aAAa,MAAM,WAAW,MAAM,KAAK;AAAA,EAC9D;AACF;AACA,OAAO,eAAe,QAAQ,OAAO,aAAa;AAAA,EAChD,OAAO,CAAC,aAAa;AACnB,WAAO,CAAC,CAAC,YAAY,SAAS,QAAQ,QAAQ,SAAS,YAAY,QAAQ,SAAS,mBAAmB;AAAA,EACzG;AACF,CAAC;AACD,SAAS,uBAAuB;AAC9B,SAAO,UAAU,UAAU,MAAM;AAC/B,WAAO;AAAA,EACT,CAAC;AACH;AACA,qBAAqB;AACrB,IAAI,WAAW,cAAc,OAAO;AAAA,EAClC,YAAY,cAAc,WAAW,MAAM,UAAU;AACnD,UAAM,aAAa,OAAO,aAAa,OAAO,aAAa,QAAQ,QAAQ;AAC3E,SAAK,YAAY;AACjB,SAAK,OAAO;AAAA,EACd;AAAA,EACA,OAAO,UAAU;AACf,QAAI,SAAS,UAAU,KAAK,OAAO;AACjC,YAAM,IAAI,MAAM,2BAA2B,SAAS,8BAA8B,KAAK,mBAAmB;AAAA,IAC5G;AACA,QAAI,CAAC,YAAY,SAAS,OAAO,KAAK,KAAK,GAAG;AAC5C,YAAM,IAAI,MAAM,2BAA2B,SAAS,8BAA8B,KAAK,mBAAmB;AAAA,IAC5G;AACA,cAAU,EAAE,cAAc,IAAI;AAC9B,SAAK,SAAS,SAAS;AACvB,cAAU,EAAE,OAAO,MAAM,IAAI;AAAA,EAC/B;AAAA,EACA,UAAU;AACR,cAAU,EAAE,gBAAgB,IAAI;AAChC,SAAK,qBAAqB;AAAA,EAC5B;AACF;AACA,OAAO,eAAe,UAAU,OAAO,aAAa;AAAA,EAClD,OAAO,CAAC,aAAa;AACnB,WAAO,oBAAoB,UAAU,SAAS,UAAU,QAAQ,SAAS,kBAAkB;AAAA,EAC7F;AACF,CAAC;AAGD,IAAI,sBAAsB,CAAC;AAC3BT,UAAS,qBAAqB;AAAA,EAC5B,kBAAkB,MAAM;AAAA,EACxB,uBAAuB,MAAM;AAAA,EAC7B,gBAAgB,MAAM;AAAA,EACtB,gBAAgB,MAAM;AACxB,CAAC;AAGD,IAAI;AAAA,CACH,SAAS,OAAO;AACf,QAAM,QAAQ;AACd,QAAM,QAAQ;AACd,QAAM,QAAQ;AACd,QAAM,QAAQ;AACd,QAAM,QAAQ;AACd,QAAM,QAAQ;AACd,QAAM,QAAQ;AAChB,GAAG,SAAS,OAAO,CAAC,EAAE;AACtB,IAAI;AAAA,CACH,SAAS,oBAAoB;AAC5B,qBAAmB,aAAa;AAChC,qBAAmB,WAAW;AAC9B,qBAAmB,UAAU;AAC7B,qBAAmB,eAAe;AACpC,GAAG,sBAAsB,oBAAoB,CAAC,EAAE;AAChD,IAAI;AAAA,CACH,SAAS,mBAAmB;AAC3B,oBAAkB,aAAa;AAC/B,oBAAkB,WAAW;AAC7B,oBAAkB,UAAU;AAC5B,oBAAkB,eAAe;AACnC,GAAG,qBAAqB,mBAAmB,CAAC,EAAE;AAC9C,IAAI;AAAA,CACH,SAAS,sBAAsB;AAC9B,uBAAqB,aAAa;AAClC,uBAAqB,WAAW;AAChC,uBAAqB,UAAU;AAC/B,uBAAqB,eAAe;AACtC,GAAG,wBAAwB,sBAAsB,CAAC,EAAE;AACpD,IAAI;AAAA,CACH,SAAS,wBAAwB;AAChC,yBAAuB,aAAa;AACpC,yBAAuB,WAAW;AAClC,yBAAuB,UAAU;AACjC,yBAAuB,eAAe;AACxC,GAAG,0BAA0B,wBAAwB,CAAC,EAAE;AACxD,IAAI,gBAAgB;AAAA,EAClB,WAAW;AAAA,EACX,SAAS;AAAA,EACT,QAAQ;AAAA,EACR,aAAa;AACf;AACA,SAAS,WAAW,OAAO,OAAO;AAChC,MAAI,UAAU,YAAY,UAAU,UAAU;AAC5C,QAAI,UAAU,YAAY,UAAU,UAAU;AAC5C,aAAO;AAAA,IACT;AACA,UAAM,IAAI,MAAM,kBAAkB,cAAc,OAAO;AAAA,EACzD;AACA,SAAO,cAAc,OAAO;AAC9B;AACA,SAAS,WAAW,MAAM;AACxB,SAAO,WAAW,MAAM,OAAO;AACjC;AAGA,SAAS,eAAe,GAAG,GAAG;AAC5B,MAAI,EAAE,UAAU,EAAE,OAAO;AACvB,WAAO,CAAC,GAAG,CAAC;AAAA,EACd;AACA,QAAM,QAAQ,WAAW,EAAE,OAAO,EAAE,KAAK;AACzC,SAAO,CAAC,EAAE,KAAK,KAAK,GAAG,EAAE,KAAK,KAAK,CAAC;AACtC;AACA,SAAS,iBAAiB,GAAG,GAAG;AAC9B,SAAO,EAAE,UAAU,EAAE,OAAO,MAAM,2BAA2B,EAAE,qBAAqB,EAAE,yBAAyB;AACjH;AACA,SAAS,eAAe,SAAS,YAAY;AAC3C,SAAO,WAAW,KAAK,CAAC,MAAM,EAAE,OAAO,QAAQ,EAAE;AACnD;AACA,SAAS,sBAAsB,QAAQ;AACrC,QAAM,OAAO,CAAC;AACd,QAAM,OAAuB,oBAAI,IAAI;AACrC,sBAAoB,QAAQ,MAAM,IAAI;AACtC,SAAO;AACT;AACA,SAAS,oBAAoB,WAAW,MAAM,MAAM;AAClD,MAAI,aAAa,MAAM;AACrB;AAAA,EACF;AACA,MAAI,qBAAqB,QAAQ;AAC/B,SAAK,KAAK,SAAS;AACnB;AAAA,EACF;AACA,MAAI,CAAC,WAAW,SAAS,GAAG;AAC1B;AAAA,EACF;AACA,QAAM,WAAW;AACjB,aAAW,KAAK,UAAU;AACxB,UAAM,MAAM,SAAS;AACrB,QAAI,CAAC,KAAK,IAAI,GAAG,GAAG;AAClB,WAAK,IAAI,GAAG;AACZ,0BAAoB,KAAK,MAAM,IAAI;AAAA,IACrC;AAAA,EACF;AACF;AACA,SAAS,WAAW,KAAK;AACvB,SAAO,MAAM,QAAQ,GAAG,KAAK,OAAO,QAAQ;AAC9C;AAGA,SAAS,6BAA6B,kBAAkB;AACtD,SAAO,iBAAiB,cAAc;AACxC;AACA,IAAI,cAAc,MAAM;AAAA,EACtB,cAAc;AACZ,SAAK,sBAAsB,CAAC;AAC5B,SAAK,iBAAiB;AACtB,SAAK,WAAW;AAChB,SAAK,aAAa;AAClB,SAAK,mBAAmB;AACxB,SAAK,iBAAiB;AACtB,SAAK,gBAAgB;AACrB,SAAK,cAAc;AACnB,SAAK,aAAa,CAAC;AACnB,SAAK,oBAAoB,CAAC;AAC1B,SAAK,cAAc;AACnB,SAAK,aAA6B,oBAAI,QAAQ;AAC9C,SAAK,YAAY;AACjB,SAAK,gBAAgB;AAAA,MACnB,UAAU;AAAA,MACV,YAAY;AAAA,MACZ,WAAW;AAAA,MACX,SAAS,CAAC;AAAA,MACV,QAAQ;AAAA,MACR,IAAI,cAAc;AAChB,eAAO,MAAM,KAAK,IAAI,IAAI,KAAK,QAAQ,IAAI,CAAC,MAAM,EAAE,IAAI,CAAC,CAAC;AAAA,MAC5D;AAAA,IACF;AAAA,EACF;AAAA,EACA,UAAU;AACR,eAAW,gBAAgB,KAAK,qBAAqB;AACnD,WAAK,oBAAoB,cAAc,QAAQ;AAAA,IACjD;AAAA,EACF;AACF;AACA,IAAI,SAAS,MAAM;AAAA,EACjB,YAAY,MAAM;AAChB,SAAK,MAAM;AACX,SAAK,WAAW,CAAC;AACjB,SAAK,kBAAkB,CAAC;AACxB,SAAK,uBAAuB;AAC5B,SAAK,QAAQ,IAAI,YAAY;AAAA,EAC/B;AAAA,EACA,MAAM,QAAQ;AACZ,QAAI,KAAK,sBAAsB,MAAM;AACnC,aAAO,KAAK,mBAAmB,KAAK,MAAM;AAAA,MAC1C,CAAC;AAAA,IACH;AACA,QAAI,KAAK,mBAAmB,MAAM;AAChC;AAAA,IACF;AACA,UAAM,iBAAiB,KAAK,kBAAkB;AAC9C,aAAS,KAAK,GAAG,KAAK,eAAe,QAAQ,MAAM;AACjD,YAAM,cAAc,eAAe;AACnC,YAAM,UAAU,MAAM,KAAK,kBAAkB,WAAW,EAAE;AAC1D,UAAI,SAAS;AACX,cAAM,KAAK,WAAW,WAAW;AACjC;AAAA,MACF;AAAA,IACF;AACA,UAAM,IAAI,MAAM,wEAAwE;AAAA,EAC1F;AAAA,EACA,IAAI,UAAU;AACZ,QAAI,KAAK,sBAAsB,MAAM;AACnC,YAAM,IAAI,MAAM,YAAY,KAAK,gIAAgI;AAAA,IACnK;AACA,QAAI,KAAK,mBAAmB,MAAM;AAChC,YAAM,EAAE,MAAM,UAAU,IAAI,KAAK,gCAAgC;AACjE,UAAI,WAAW;AACb,cAAM,IAAI,MAAM,iCAAiC,yHAAyH;AAAA,MAC5K;AACA,WAAK,WAAW,IAAI;AAAA,IACtB;AACA,WAAO,KAAK;AAAA,EACd;AAAA,EACA,eAAe;AACb,WAAO,OAAO,KAAK,KAAK,eAAe;AAAA,EACzC;AAAA,EACA,YAAY,aAAa;AACvB,QAAI,EAAE,eAAe,KAAK,WAAW;AACnC,UAAI,eAAe,KAAK,iBAAiB;AACvC,cAAM,EAAE,UAAU,IAAI,KAAK,kBAAkB,WAAW;AACxD,YAAI,WAAW;AACb,iBAAO;AAAA,QACT;AAAA,MACF,OAAO;AACL,eAAO;AAAA,MACT;AAAA,IACF;AACA,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,mBAAmB,aAAa;AAC9B,QAAI,EAAE,eAAe,KAAK,kBAAkB;AAC1C,aAAO;AAAA,IACT;AACA,WAAO,KAAK,gBAAgB,aAAa;AAAA,EAC3C;AAAA,EACA,gBAAgB,aAAa,SAAS,WAAW,GAAG;AAClD,QAAI,eAAe,KAAK,iBAAiB;AACvC,WAAK,GAAG,+EAA+E;AACvF,aAAO;AAAA,IACT;AACA,SAAK,gBAAgB,eAAe,EAAE,SAAS,SAAS;AACxD,WAAO;AAAA,EACT;AAAA,EACA,MAAM,WAAW,aAAa;AAC5B,QAAI,KAAK,gBAAgB,gBAAgB,MAAM;AAC7C,YAAM,IAAI,MAAM,iBAAiB,oCAAoC;AAAA,IACvE;AACA,SAAK,cAAc;AACnB,QAAI,KAAK,SAAS,gBAAgB,MAAM;AACtC,WAAK,kBAAkB;AACvB,YAAM,EAAE,SAAS,UAAU,IAAI,KAAK,kBAAkB,WAAW;AACjE,YAAM,SAAS,YAAY,MAAM,UAAU;AAC3C,UAAI,CAAC,QAAQ;AACX,eAAO;AAAA,MACT;AAAA,IACF;AACA,SAAK,kBAAkB,KAAK,SAAS;AACrC,SAAK,uBAAuB;AAC5B,SAAK,WAAW,IAAI,SAAS,KAAK,eAAe;AACjD,WAAO;AAAA,EACT;AAAA,EACA,yBAAyB;AACvB,UAAM,UAAU,qBAAqB,KAAK,WAAW;AACrD,YAAQ,QAAQ,CAAC,WAAW;AAC1B,UAAI,OAAO,aAAa,MAAM;AAC5B,eAAO,UAAU,KAAK,eAAe;AAAA,MACvC;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,yBAAyB,aAAa;AACpC,UAAM,UAAU,qBAAqB,WAAW;AAChD,YAAQ,QAAQ,CAAC,WAAW;AAC1B,UAAI,OAAO,eAAe,MAAM;AAC9B,eAAO,YAAY,KAAK,SAAS,YAAY;AAAA,MAC/C;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,kBAAkB,aAAa;AAC7B,UAAM,uBAAuB,KAAK,gBAAgB;AAClD,QAAI,wBAAwB,MAAM;AAChC,YAAM,IAAI,MAAM,6BAA6B,qCAAqC;AAAA,IACpF;AACA,QAAI;AACF,YAAM,WAAW,qBAAqB,QAAQ;AAC9C,UAAI,YAAY,EAAE,oBAAoB,kBAAkB,OAAO,SAAS,SAAS,YAAY;AAC3F,cAAM,YAAY,EAAE,KAAK;AACzB,cAAM,UAAU,SAAS,KAAK,CAAC,oBAAoB;AACjD,cAAI,YAAY,KAAK,sBAAsB;AACzC,mBAAO;AAAA,UACT;AACA,eAAK,SAAS,eAAe;AAC7B,eAAK,qBAAqB;AAC1B,iBAAO;AAAA,QACT,CAAC,EAAE,MAAM,CAAC,QAAQ;AAChB,cAAI,YAAY,KAAK,sBAAsB;AACzC,mBAAO;AAAA,UACT;AACA,eAAK,qBAAqB;AAC1B,eAAK,6BAA6B,oBAAoB;AACtD,eAAK,IAAI,SAAS,IAAI,OAAO;AAC7B,iBAAO;AAAA,QACT,CAAC;AACD,aAAK,qBAAqB;AAC1B,eAAO,EAAE,SAAS,WAAW,KAAK;AAAA,MACpC,OAAO;AACL,aAAK,SAAS,eAAe;AAC7B,eAAO,EAAE,SAAS,MAAM,WAAW,MAAM;AAAA,MAC3C;AAAA,IACF,SAAS,KAAP;AACA,WAAK,6BAA6B,oBAAoB;AACtD,WAAK,IAAI,SAAS,IAAI,OAAO;AAC7B,aAAO,EAAE,SAAS,OAAO,WAAW,MAAM;AAAA,IAC5C;AAAA,EACF;AAAA,EACA,cAAc,aAAa;AACzB,QAAI,EAAE,eAAe,KAAK,kBAAkB;AAC1C,YAAM,IAAI,MAAM,GAAG,2CAA2C;AAAA,IAChE;AACA,QAAI,KAAK,gBAAgB,eAAe,KAAK,sBAAsB,MAAM;AACvE,WAAK;AAAA,IACP;AACA,QAAI,eAAe,KAAK,UAAU;AAChC,WAAK,yBAAyB,WAAW;AACzC,WAAK,SAAS,aAAa,QAAQ;AACnC,aAAO,KAAK,SAAS;AAAA,IACvB;AACA,WAAO,KAAK,gBAAgB;AAC5B,QAAI,KAAK,gBAAgB,aAAa;AACpC,WAAK,qBAAqB;AAC1B,WAAK,cAAc;AACnB,WAAK,kBAAkB;AAAA,IACzB;AAAA,EACF;AAAA,EACA,oBAAoB;AAClB,QAAI,OAAO,KAAK,KAAK,eAAe,EAAE,WAAW,GAAG;AAClD,YAAM,IAAI,MAAM,+BAA+B;AAAA,IACjD;AACA,WAAO,OAAO,KAAK,KAAK,eAAe,EAAE,KAAK,CAAC,GAAG,MAAM;AACtD,aAAO,KAAK,gBAAgB,GAAG,WAAW,KAAK,gBAAgB,GAAG;AAAA,IACpE,CAAC;AAAA,EACH;AAAA,EACA,kCAAkC;AAChC,UAAM,iBAAiB,KAAK,kBAAkB;AAC9C,aAAS,KAAK,GAAG,KAAK,eAAe,QAAQ,MAAM;AACjD,YAAM,cAAc,eAAe;AACnC,YAAM,EAAE,SAAS,UAAU,IAAI,KAAK,kBAAkB,WAAW;AACjE,UAAI,aAAa,SAAS;AACxB,eAAO,EAAE,MAAM,aAAa,UAAU;AAAA,MACxC;AAAA,IACF;AACA,UAAM,IAAI,MAAM,wEAAwE;AAAA,EAC1F;AAAA,EACA,SAAS,UAAU,QAAQ;AACzB,UAAM,OAAO,KAAK,MAAM,WAAW,IAAI,MAAM;AAC7C,UAAM,aAAa,KAAK;AACxB,UAAM,SAAS,KAAK,SAAS,MAAM;AACnC,UAAM,WAAW,WAAW,SAAS,MAAM;AAC3C,eAAW,YAAY,QAAQ,IAAI;AACnC,SAAK,UAAU;AACf,aAAS,KAAK,QAAQ,QAAQ,KAAK,OAAO,KAAK,OAAO,QAAQ;AAC9D,QAAI,KAAK,uBAAuB,GAAG;AACjC,WAAK,MAAM,kBAAkB,KAAK,MAAM,kBAAkB,SAAS;AAAA,IACrE;AAAA,EACF;AAAA,EACA,KAAK,UAAU,IAAI;AACjB,QAAI,OAAO;AACX,QAAI,MAAM,MAAM;AACd,UAAI,OAAO,aAAa,YAAY;AAClC,cAAM,IAAI,MAAM,qCAAqC;AAAA,MACvD;AACA,WAAK;AAAA,IACP,OAAO;AACL,UAAI,OAAO,aAAa,YAAY,EAAE,oBAAoB,SAAS;AACjE,cAAM,IAAI,MAAM,gFAAgF;AAAA,MAClG;AACA,UAAI,OAAO,OAAO,YAAY;AAC5B,cAAM,IAAI,MAAM,gFAAgF;AAAA,MAClG;AACA,aAAO;AAAA,IACT;AACA,QAAI;AACJ,WAAO,KAAK,UAAU,MAAM,KAAK,WAAW,IAAI,GAAG,MAAM,KAAK,SAAS,MAAM,GAAG,MAAM;AACpF,eAAS,GAAG;AACZ,UAAI,kBAAkB,SAAS;AAC7B,gBAAQ,MAAM,yCAAyC;AAAA,MACzD;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,UAAU,OAAO,KAAK,GAAG;AACvB,UAAM;AACN,QAAI;AACF,YAAM,MAAM,EAAE;AACd,UAAI;AACJ,aAAO;AAAA,IACT,SAAS,IAAP;AACA,UAAI;AACJ,YAAM;AAAA,IACR;AAAA,EACF;AAAA,EACA,eAAe;AACb,WAAO,OAAO;AAAA,EAChB;AAAA,EACA,iBAAiB;AACf,WAAO,OAAO;AAAA,EAChB;AAAA,EACA,MAAM,GAAG;AACP,UAAM,IAAI,OAAO,UAAU,UAAU,EAAE,EAAE,CAAC;AAC1C,UAAM,SAAS,EAAE,EAAE;AACnB,UAAM,QAAQ,CAAC,QAAQ;AAAA,MACrB,GAAG,MAAM;AACP,cAAM,QAAQ;AACd,cAAM,aAAa,EAAE,GAAG,GAAG;AAC3B,cAAM,QAAQ,EAAE,MAAM;AACtB,eAAO,OAAO;AAAA,UACZ;AAAA,UACA;AAAA,UACA;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,QAAQ,CAAC;AACf,SAAK,YAAY,KAAK,MAAM,YAAY,MAAM,QAAQ,CAAC,CAAC,GAAG,OAAO,OAAO,CAAC,CAAC;AAC3E,WAAO;AAAA,EACT;AAAA,EACA,UAAU,YAAY,QAAQ,OAAO;AACnC,QAAI,KAAK,eAAe,MAAM;AAC5B,WAAK;AAAA,IACP;AACA,UAAM,YAAY,UAAU,YAAY,KAAK,WAAW,KAAK;AAC7D,QAAI,CAAC,WAAW;AACd,YAAM,IAAI,MAAM,WAAW,2CAA2C,KAAK,cAAc;AAAA,IAC3F;AACA,WAAO,KAAK,cAAc,EAAE,YAAY,QAAQ,MAAM,CAAC;AAAA,EACzD;AAAA,EACA,yBAAyB;AACvB,WAAO,KAAK,IAAI,QAAQ,SAAS;AAAA,EACnC;AAAA,EACA,sBAAsB,YAAY,kBAAkB,UAAU;AAC5D,UAAM,kBAAkB,KAAK,QAAQ,WAAW;AAChD,QAAI,mBAAmB;AACvB,aAAS,QAAQ,CAAC,SAAS;AACzB,0BAAoB,KAAK,UAAU,cAAc,IAAI;AAAA,IACvD,CAAC;AACD,UAAM,WAAW,KAAK,MAAM,kBAAkB,KAAK,MAAM,kBAAkB,SAAS;AACpF,UAAM,gBAAgB,kBAAkB,mBAAmB,mBAAmB;AAC9E,QAAI,gBAAgB,GAAG;AACrB,YAAM,IAAI,MAAM,YAAY,KAAK,6CAA6C,0CAA0C,aAAa;AAAA,IACvI;AAAA,EACF;AAAA,EACA,cAAc,cAAc;AAC1B,QAAI;AACJ,QAAI,QAAQ,CAAC;AACb,UAAM,WAAW,KAAK,SAAS;AAC/B,UAAM,oBAAoB,KAAK,MAAM;AACrC,UAAM,qBAAqB,KAAK,MAAM;AACtC,QAAI,KAAK,uBAAuB,GAAG;AACjC,WAAK,MAAM,kBAAkB,KAAK,CAAC;AAAA,IACrC;AACA,QAAI;AACJ,QAAI,KAAK,eAAe,MAAM;AAC5B,WAAK;AAAA,IACP;AACA,QAAI;AACJ,UAAM,oBAAoB,6BAA6B,YAAY,IAAI,aAAa,aAAa,KAAK,MAAM,eAAe,OAAO,KAAK,MAAM,YAAY,OAAO;AAChK,QAAI,6BAA6B,YAAY,GAAG;AAC9C,YAAM,EAAE,YAAY,QAAQ,SAAS,OAAO,OAAO,IAAI;AACvD,UAAI,KAAK,eAAe,MAAM;AAC5B,aAAK;AAAA,MACP;AACA,YAAM,SAAS,UAAU,YAAY,KAAK,WAAW;AACrD,aAAO,UAAU,MAAM,MAAM,kCAAkC,4BAA4B,KAAK,cAAc;AAC9G,oBAAc,MAAM;AAClB,cAAM,mBAAmB,KAAK,QAAQ,WAAW;AACjD,cAAM,OAAO,WAAW,EAAE,QAAQ,SAAS,OAAO,QAAQ,SAAS,KAAK,QAAQ,CAAC;AACjF,cAAM,WAAW,MAAM,QAAQ,GAAG,IAAI,MAAM,CAAC,GAAG;AAChD,YAAI,KAAK,uBAAuB,GAAG;AACjC,eAAK,sBAAsB,YAAY,kBAAkB,QAAQ;AAAA,QACnE;AACA,cAAM,aAAa,SAAS,IAAI,CAAC,YAAY;AAC3C,cAAI,QAAQ,QAAQ,MAAM;AACxB,mBAAO;AAAA,UACT;AACA,iBAAO,KAAK,yBAAyB,OAAO;AAAA,QAC9C,CAAC;AACD,YAAI,UAAU;AACZ,gBAAM,gBAAgB,KAAK,sBAAsB,YAAY,SAAS,UAAU;AAChF,kBAAQ,KAAK,2BAA2B,aAAa;AAAA,QACvD;AACA,eAAO;AAAA,MACT;AAAA,IACF,OAAO;AACL,YAAM,EAAE,YAAY,IAAI;AACxB,YAAM,WAAW,CAAC,YAAY;AAC5B,YAAI,CAAC,UAAU;AACb;AAAA,QACF;AACA,gBAAQ,QAAQ,IAAI,CAAC,YAAY,KAAK,KAAK,KAAK,MAAM,OAAO,CAAC,CAAC;AAAA,MACjE;AACA,oBAAc,MAAM;AAClB,cAAM,mBAAmB,KAAK,QAAQ,WAAW;AACjD,cAAM,KAAK,KAAK,MAAM,YAAY,KAAK,SAAS,QAAQ,CAAC;AACzD,cAAM,OAAO,MAAM,QAAQ,GAAG,IAAI,MAAM,CAAC,GAAG;AAC5C,YAAI,KAAK,uBAAuB,GAAG;AACjC,eAAK,sBAAsB,mBAAmB,kBAAkB,IAAI;AAAA,QACtE;AACA,eAAO;AAAA,MACT;AAAA,IACF;AACA,UAAM,EAAE,QAAQ,MAAM,IAAI;AAC1B,UAAM,gBAAgB,6BAA6B,YAAY,IAAI,OAAO,aAAa;AACvF,QAAI;AACJ,SAAK;AAAA,MACH,MAAM,KAAK,MAAM;AAAA,MACjB,MAAM,KAAK,MAAM;AAAA,MACjB,MAAM;AACJ,YAAI,CAAC,KAAK,IAAI,QAAQ,OAAO,KAAK,CAAC,KAAK,MAAM,WAAW;AACvD,oBAAU,YAAY;AAAA,QACxB,OAAO;AACL,0BAAgB,KAAK,SAAS,cAAc,mBAAmB,QAAQ,MAAM,YAAY,CAAC;AAC1F,cAAI,KAAK,IAAI,QAAQ,OAAO,GAAG;AAC7B,iBAAK,SAAS,iBAAiB,aAAa;AAAA,UAC9C;AACA,oBAAU,cAAc;AAAA,QAC1B;AAAA,MACF;AAAA,IACF;AACA,QAAI,UAAU;AACZ,WAAK,YAAY,mBAAmB,QAAQ,SAAS,eAAe,OAAO,KAAK;AAAA,IAClF;AACA,QAAI,KAAK,MAAM,WAAW;AACxB,WAAK,MAAM,cAAc,QAAQ,KAAK;AAAA,QACpC,MAAM;AAAA,QACN,YAAY,KAAK,MAAM,WAAW;AAAA,QAClC,oBAAoB,KAAK,MAAM;AAAA,QAC/B,cAAc,KAAK,MAAM,aAAa;AAAA,QACtC,sBAAsB,KAAK,MAAM;AAAA,QACjC,aAAa,OAAO,KAAK,MAAM,EAAE,IAAI,CAAC,QAAQ,OAAO,QAAQ,OAAO,OAAO,KAAK,QAAQ,IAAI;AAAA,QAC5F,cAAc,QAAQ,IAAI,CAAC,SAAS,KAAK,KAAK;AAAA,QAC9C,cAAc,cAAc;AAAA,QAC5B,WAAW,cAAc;AAAA,MAC3B,CAAC;AAAA,IACH;AACA,WAAO,MAAM,QAAQ,GAAG,IAAI,UAAU,QAAQ;AAAA,EAChD;AAAA,EACA,2BAA2B,SAAS;AAClC,UAAM,QAAQ,QAAQ,IAAI,CAAC,YAAY,KAAK,KAAK,KAAK,MAAM,OAAO,CAAC,CAAC;AACrE,WAAO;AAAA,EACT;AAAA,EACA,sBAAsB,YAAY,QAAQ,SAAS;AACjD,UAAM,aAAa,YAAY,UAAU;AACzC,QAAI,cAAc,MAAM;AACtB,YAAM,eAAe,WAAW,gBAAgB,CAAC;AACjD,YAAM,gBAAgB,WAAW,iBAAiB,CAAC;AACnD,UAAI;AACJ,UAAI,WAAW,eAAe;AAC5B,eAAO,MAAM,QAAQ,MAAM,GAAG,MAAM,wDAAwD;AAC5F,6BAAqB,OAAO,KAAK,MAAM,EAAE,IAAI,CAAC,QAAQ,OAAO,IAAI;AAAA,MACnE,OAAO;AACL,6BAAqB,aAAa,IAAI,CAAC,cAAc,OAAO,UAAU;AAAA,MACxE;AACA,YAAM,sBAAsB,QAAQ,OAAO,CAAC,GAAG,OAAO,cAAc,GAAG;AACvE,aAAO,mBAAmB,OAAO,mBAAmB;AAAA,IACtD;AACA,WAAO,CAAC;AAAA,EACV;AAAA,EACA,WAAW,QAAQ,OAAO,OAAO,UAAU;AACzC,QAAI,UAAU,MAAM;AAClB,YAAM,IAAI,MAAM,+CAA+C;AAAA,IACjE;AACA,YAAQ,SAAS;AACjB,eAAW,YAAY,KAAK;AAC5B,QAAI,cAAc;AAClB,QAAI,UAAU,YAAY,SAAS,OAAO,EAAE,GAAG;AAC7C,oBAAc,OAAO,IAAI,CAAC,MAAM,aAAa,CAAC,CAAC;AAAA,IACjD;AACA,UAAM,SAAS,SAAS,MAAM,aAAa,OAAO,KAAK;AACvD,UAAM,KAAK,IAAI,OAAO,OAAO,OAAO,QAAQ,KAAK,aAAa,CAAC;AAC/D,SAAK,YAAY,IAAI,QAAQ;AAC7B,QAAI,UAAU,UAAU;AACtB,YAAM,OAAO,KAAK,MAAM,WAAW,IAAI,MAAM;AAC7C,YAAM,WAAW,qBAAqB,WAAW;AACjD,WAAK,MAAM,YAAY,WAAW,KAAK;AACvC,WAAK,QAAQ;AAAA,IACf;AACA,WAAO;AAAA,EACT;AAAA,EACA,qBAAqB,QAAQ,OAAO,OAAO,UAAU;AACnD,YAAQ,SAAS;AACjB,UAAM,aAAa,EAAE,QAAQ,OAAO,MAAM;AAC1C,WAAO,KAAK,yBAAyB,YAAY,QAAQ;AAAA,EAC3D;AAAA,EACA,yBAAyB,YAAY,UAAU;AAC7C,UAAM,EAAE,QAAQ,OAAO,MAAM,IAAI;AACjC,UAAM,KAAK,IAAI,OAAO,OAAO,OAAO,QAAQ,KAAK,aAAa,CAAC;AAC/D,SAAK,YAAY,IAAI,QAAQ;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,aAAa,cAAc,YAAY,MAAM,MAAM,OAAO;AACxD,WAAO,QAAQ,KAAK,eAAe,EAAE,SAAS;AAC9C,QAAI,SAAS,QAAQ,UAAU,aAAa,OAAO;AACjD,qBAAe,aAAa,KAAK,KAAK;AAAA,IACxC;AACA,UAAM,IAAI,IAAI,SAAS,cAAc,WAAW,MAAM,KAAK,aAAa,CAAC;AACzE,QAAI,KAAK,MAAM,oBAAoB,EAAE,SAAS,MAAM;AAClD,YAAM,IAAI,MAAM,sBAAsB,EAAE,6BAA6B;AAAA,IACvE;AACA,SAAK,MAAM,oBAAoB,EAAE,QAAQ;AACzC,SAAK,OAAO,GAAG,KAAK,OAAO;AAC3B,WAAO;AAAA,EACT;AAAA,EACA,YAAY,GAAG,UAAU;AACvB,SAAK,MAAM;AACX,QAAI,EAAE,UAAU,UAAU;AACxB,WAAK,MAAM;AAAA,IACb;AACA,QAAI,QAAQ;AACZ,QAAI,EAAE,UAAU,eAAe,EAAE,UAAU,UAAU;AACnD,cAAQ,EAAE,OAAO,gBAAgB,EAAE,KAAK;AAAA,IAC1C;AACA,SAAK,MAAM,YAAY;AACvB,QAAI,CAAC,KAAK,MAAM,WAAW,IAAI,EAAE,MAAM,GAAG;AACxC,WAAK,MAAM;AACX,WAAK,MAAM,WAAW,IAAI,EAAE,QAAQ;AAAA,QAClC,SAAS,YAAY,KAAK;AAAA,QAC1B,OAAO,EAAE;AAAA,QACT,OAAO,EAAE;AAAA,QACT;AAAA,MACF,CAAC;AAAA,IACH;AACA,QAAI,EAAE,aAAa,WAAW;AAC5B,WAAK,MAAM,CAAC;AAAA,IACd;AAAA,EACF;AAAA,EACA,OAAO,GAAG,UAAU;AAClB,SAAK,YAAY,GAAG,QAAQ;AAC5B,SAAK,QAAQ,OAAO,EAAE,MAAM;AAAA,EAC9B;AAAA,EACA,aAAa,QAAQ,UAAU;AAC7B,QAAI,KAAK,MAAM,WAAW,IAAI,MAAM,KAAK,KAAK,MAAM,WAAW,IAAI,MAAM,EAAE,YAAY,UAAU;AAC/F,WAAK,MAAM,WAAW,OAAO,MAAM;AACnC,WAAK,MAAM;AAAA,IACb;AAAA,EACF;AAAA,EACA,cAAc,GAAG;AACf,QAAI,CAAC,KAAK,MAAM,WAAW,IAAI,EAAE,MAAM,GAAG;AACxC;AAAA,IACF;AACA,UAAM,OAAO,KAAK,MAAM,WAAW,IAAI,EAAE,MAAM;AAC/C,SAAK,MAAM;AACX,QAAI,EAAE,UAAU,UAAU;AACxB,WAAK,MAAM;AACX,WAAK,MAAM,YAAY,KAAK;AAAA,IAC9B;AACA,QAAI,EAAE,UAAU,eAAe,EAAE,UAAU,UAAU;AACnD,YAAM,QAAQ,EAAE,OAAO,gBAAgB,EAAE,KAAK;AAC9C,WAAK,MAAM,YAAY;AAAA,IACzB;AACA,QAAI,KAAK,QAAQ,YAAY,EAAE,MAAM,GAAG;AACtC,WAAK,aAAa,EAAE,QAAQ,KAAK,OAAO;AAAA,IAC1C;AAAA,EACF;AAAA,EACA,mBAAmB;AACjB,eAAW,WAAW,KAAK,MAAM,qBAAqB;AACpD,YAAM,IAAI,KAAK,MAAM,oBAAoB;AACzC,WAAK,gBAAgB,CAAC;AAAA,IACxB;AAAA,EACF;AAAA,EACA,gBAAgB,GAAG;AACjB,SAAK,cAAc,CAAC;AACpB,QAAI,KAAK,MAAM,oBAAoB,EAAE,SAAS,MAAM;AAClD,aAAO,KAAK,MAAM,oBAAoB,EAAE;AAAA,IAC1C;AAAA,EACF;AAAA,EACA,SAAS;AACP,UAAM,OAAO,KAAK,QAAQ,OAAO;AACjC,SAAK,aAAa,KAAK,MAAM;AAC7B,SAAK,iBAAiB,KAAK,MAAM;AACjC,SAAK,WAAW,KAAK,MAAM;AAC3B,QAAI,KAAK,MAAM,mBAAmB,GAAG;AACnC,WAAK,aAAa;AAClB,UAAI,KAAK,WAAW,MAAM;AACxB,aAAK,UAAU,CAAC;AAAA,MAClB;AACA,WAAK,QAAQ,KAAK,uEAAuE;AAAA,IAC3F;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,QAAQ,OAAO;AACnB,SAAK,MAAM,YAAY;AACvB,UAAM,aAAa,KAAK,MAAM;AAC9B,UAAM,kBAAkB,KAAK,MAAM;AACnC,SAAK,MAAM,cAAc,UAAU,CAAC;AACpC,SAAK,MAAM,cAAc,SAAS,MAAM,MAAM;AAC9C,SAAK,MAAM,YAAY;AACvB,SAAK,MAAM,cAAc,YAAY,KAAK,IAAI,GAAG,KAAK,MAAM,cAAc,QAAQ,IAAI,CAAC,MAAM,EAAE,kBAAkB,CAAC;AAClH,SAAK,MAAM,cAAc,WAAW,KAAK,MAAM,WAAW;AAC1D,SAAK,MAAM,cAAc,aAAa,KAAK,MAAM,aAAa;AAC9D,eAAW,UAAU,KAAK,MAAM,cAAc,SAAS;AACrD,aAAO,eAAe,MAAM,OAAO;AACnC,aAAO,YAAY,MAAM,OAAO;AAAA,IAClC;AACA,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,WAAW;AACT,WAAO,KAAK,MAAM,gBAAgB,KAAK,KAAK,MAAM,gBAAgB;AAAA,EACpE;AAAA,EACA,YAAY,YAAY,QAAQ,SAAS,eAAe,OAAO,OAAO;AACpE,UAAM,WAAW,EAAE,IAAI,KAAK,MAAM,kBAAkB,YAAY,QAAQ,SAAS,MAAM;AACvF,UAAM,aAAa,YAAY,UAAU;AACzC,QAAI,cAAc,MAAM;AACtB,sBAAgB,WAAW;AAAA,IAC7B;AACA,QAAI,iBAAiB,MAAM;AACzB,eAAS,WAAW,CAAC,QAAQ;AAC3B,cAAM,IAAI,IAAI,CAAC,IAAI,OAAO;AACxB,cAAI,MAAM,MAAM;AACd,kBAAM,SAAS,QAAQ;AACvB,kBAAM,OAAO,oBAAoB,OAAO,MAAM,OAAO,KAAK;AAC1D,mBAAO,KAAK,WAAW,MAAM,OAAO,OAAO,OAAO,KAAK;AAAA,UACzD;AACA,iBAAO;AAAA,QACT,CAAC;AACD,eAAO,cAAc,IAAI,SAAS,IAAI,MAAM,IAAI,IAAI,OAAO,KAAK;AAAA,MAClE;AAAA,IACF;AACA,SAAK,MAAM,WAAW,KAAK,QAAQ;AAAA,EACrC;AAAA,EACA,KAAK,QAAQ;AACX,WAAO,OAAO;AACd,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,QAAI,KAAK,MAAM,kBAAkB,GAAG;AAClC,WAAK,MAAM,aAAa,CAAC;AAAA,IAC3B;AACA,SAAK,MAAM;AAAA,EACb;AAAA,EACA,UAAU;AACR,SAAK,MAAM;AAAA,EACb;AAAA,EACA,WAAW,MAAM;AACf,UAAM,YAAY;AAAA,MAChB,OAAO,CAAC;AAAA,MACR,MAAM;AAAA,MACN,IAAI,KAAK,MAAM;AAAA,IACjB;AACA,QAAI,MAAM;AACR,gBAAU,OAAO;AAAA,IACnB;AACA,SAAK,MAAM,WAAW,KAAK,SAAS;AACpC,SAAK,MAAM,cAAc;AAAA,EAC3B;AAAA,EACA,SAAS,QAAQ;AACf,UAAM,yBAAyB,sBAAsB,MAAM;AAC3D,UAAM,4BAA4B,IAAI,IAAI,uBAAuB,IAAI,CAAC,OAAO,GAAG,EAAE,CAAC;AACnF,aAAS,KAAK,GAAG,KAAK,KAAK,MAAM,YAAY,MAAM,QAAQ,MAAM;AAC/D,YAAM,UAAU,KAAK,MAAM,YAAY,MAAM;AAC7C,UAAI,CAAC,QAAQ,QAAQ,CAAC,0BAA0B,IAAI,QAAQ,EAAE,GAAG;AAC/D,gBAAQ,QAAQ;AAAA,MAClB;AAAA,IACF;AACA,UAAM,WAAW,KAAK,MAAM,WAAW,IAAI;AAC3C,SAAK,MAAM,cAAc,KAAK,MAAM,WAAW,WAAW,IAAI,OAAO,KAAK,MAAM,WAAW,KAAK,MAAM,WAAW,SAAS;AAC1H,2BAAuB,QAAQ,CAAC,YAAY;AAC1C,UAAI,CAAC,QAAQ,QAAQ,QAAQ,YAAY,SAAS,IAAI;AACpD,aAAK,MAAM,OAAO;AAAA,MACpB;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,UAAU,GAAG,IAAI,IAAI,mBAAmB,OAAO;AAC7C,WAAO,GAAG,SAAS,GAAG,MAAM,2CAA2C;AACvE,QAAI,MAAM,QAAQ,GAAG,UAAU,WAAW;AACxC,YAAM,IAAI,MAAM,0CAA0C,GAAG,QAAQ;AAAA,IACvE;AACA,UAAM,IAAI,KAAK,UAAU,MAAM,KAAK,UAAU,GAAG,MAAM,KAAK,QAAQ,GAAG,MAAM,KAAK,KAAK,WAAW,CAAC,CAAC;AACpG,WAAO,aAAa,QAAQ,MAAM,gDAAgD;AAClF,UAAM,eAAe,qBAAqB,KAAK,MAAM,YAAY,IAAI,CAAC;AACtE,QAAI,CAAC,oBAAoB,aAAa,WAAW,KAAK,GAAG,SAAS,GAAG;AACnE,YAAM,IAAI,MAAM,qIAAqI;AAAA,IACvJ;AACA,WAAO,KAAK,KAAK,YAAY,MAAM;AACjC,YAAM,yBAAyB,CAAC;AAChC,6BAAuB,EAAE,MAAM,MAAM,OAAO,KAAK,EAAE,KAAK,IAAI;AAC5D;AAAA,QACE;AAAA,QACA;AAAA,QACA,CAAC,OAAO,KAAK,KAAK,EAAE;AAAA,QACpB;AAAA,MACF;AACA,YAAM,SAAS,GAAG,IAAI,CAAC,MAAM,uBAAuB,EAAE,GAAG;AACzD,UAAI,KAAK,MAAM,kBAAkB,GAAG;AAClC,aAAK,MAAM,WAAW,QAAQ,CAACmB,UAAS;AACtC,qBAAW,WAAWA,MAAK,OAAO;AAChC,oBAAQ,QAAQ;AAAA,UAClB;AAAA,QACF,CAAC;AACD,aAAK,MAAM,aAAa;AAAA,MAC1B;AACA,aAAO,EAAE,OAAO,GAAG,OAAO,OAAO;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,WAAW,GAAG;AACZ,WAAO,WAAW,CAAC,GAAG,MAAM,mDAAmD;AAC/E,WAAO,IAAI,WAAW;AACpB,aAAO,OAAO,MAAM,CAAC,OAAO,cAAc,MAAM,GAAG,MAAM,kEAAkE;AAC3H,UAAI;AACJ,YAAM,WAAW,CAAC;AAClB,aAAO,QAAQ,CAAC,QAAQ,OAAO;AAC7B,iBAAS,MAAM;AAAA,MACjB,CAAC;AACD,YAAM,cAAc,CAAC,GAAG,SAAS;AAC/B,cAAM,EAAE,GAAG,CAAC,GAAG,QAAQ,IAAI,CAAC;AAC5B,eAAO,IAAI,iBAAiB,QAAQ,MAAM,4FAA4F;AACtI,eAAO,WAAW,IAAI,QAAQ,GAAG,MAAM,kGAAkG;AACzI,eAAO,IAAI;AAAA,MACb;AACA,YAAM,gBAAgB,CAAC,IAAI,UAAU;AACnC,cAAM,UAAU,IAAI,SAAS,IAAI,KAAK;AACtC,cAAM,SAAS,MAAM,QAAQ,OAAO,IAAI,UAAU,CAAC,OAAO;AAC1D,eAAO,OAAO,WAAW,OAAO,QAAQ,MAAM,qKAAqK;AACnN,eAAO,OAAO,MAAM,CAAC,OAAO,cAAc,MAAM,GAAG,MAAM,sIAAsI;AAC/L,cAAM,UAAU,CAAC;AACjB,eAAO,QAAQ,CAAC,OAAO,OAAO;AAC5B,kBAAQ,MAAM,MAAM;AAAA,QACtB,CAAC;AACD,eAAO;AAAA,MACT;AACA,aAAO,KAAK,cAAc;AAAA,QACxB;AAAA,QACA;AAAA,QACA,QAAQ;AAAA,MACV,CAAC;AAAA,IACH;AAAA,EACF;AAAA,EACA,SAAS,QAAQ;AACf,UAAM,OAAO,KAAK,MAAM,WAAW,IAAI,MAAM;AAC7C,WAAO,KAAK,QAAQ,SAAS,MAAM;AAAA,EACrC;AAAA,EACA,KAAK,QAAQ;AACX,UAAM,OAAO,KAAK,MAAM,WAAW,IAAI,MAAM;AAC7C,WAAO,KAAK,QAAQ,KAAK,MAAM;AAAA,EACjC;AAAA,EACA,UAAU,QAAQV,UAAS;AACzB,UAAM,OAAO,KAAK,MAAM,WAAW,IAAI,MAAM;AAC7C,WAAO,KAAK,QAAQ,UAAU,QAAQA,QAAO;AAAA,EAC/C;AAAA,EACA,MAAM,KAAK,OAAO;AAChB,UAAM,QAAQS,KAAI;AAClB,UAAM,aAAa,MAAM,KAAK,QAAQ,KAAK,KAAK;AAChD,eAAW,SAASA,KAAI,IAAI;AAC5B,WAAO;AAAA,EACT;AAAA,EACA,MAAM,QAAQ;AACZ,QAAI,KAAK,MAAM,eAAe,MAAM;AAClC,aAAO,UAAU,KAAK,MAAM,YAAY;AACxC,WAAK,MAAM,YAAY,MAAM,KAAK,MAAM;AAAA,IAC1C;AACA,WAAO;AAAA,EACT;AAAA,EACA,IAAI,sBAAsB;AACxB,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,QAAQ;AACN,SAAK;AACL,SAAK,MAAM,QAAQ;AACnB,SAAK,IAAI,MAAM;AACf,SAAK,QAAQ,IAAI,YAAY;AAC7B,eAAW,eAAe,KAAK,UAAU;AACvC,WAAK,yBAAyB,WAAW;AACzC,WAAK,SAAS,aAAa,QAAQ;AACnC,aAAO,KAAK,SAAS;AAAA,IACvB;AACA,SAAK,cAAc;AACnB,SAAK,kBAAkB;AACvB,SAAK,qBAAqB;AAAA,EAC5B;AACF;AACA,OAAO,eAAe;AACtB,OAAO,iBAAiB;AACxB,SAAS,KAAK,OAAO;AACnB,QAAM,SAAS,mBAAmB,cAAc,KAAK,GAAG,SAAS;AACjE,SAAO,OAAO,WAAW,QAAQ,OAAO,SAAS;AACnD;AACA,SAAS,kBAAkB;AACzB,QAAM,KAAK,mBAAmB;AAC9B,MAAI,GAAG,aAAa,MAAM;AACxB,UAAM,cAAc,IAAI,YAAY,EAAE;AACtC,OAAG,YAAY,IAAI,OAAO,WAAW;AAAA,EACvC;AACA,uBAAqB,GAAG,UAAU,GAAG;AACrC,mBAAiB,MAAM,GAAG,SAAS;AACnC,SAAO,GAAG;AACZ;AACA,IAAI,SAAS,gBAAgB;AAC7B,SAAS,IAAI,GAAG,GAAG;AACjB,QAAM,SAAS,EAAE,GAAG,EAAE;AACtB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AAGA,IAAI,sBAAsB,CAAC;AAC3BlB,UAAS,qBAAqB;AAAA,EAC5B,WAAW,MAAM;AAAA,EACjB,UAAU,MAAM;AAAA,EAChB,cAAc,MAAM;AACtB,CAAC;AACD,SAAS,sBAAsB;AAC7B,SAAO,OAAO,cAAc,eAAe,aAAa;AAC1D;AACA,IAAI;AACJ,SAAS,aAAa,OAAO;AAC3B,sBAAoB;AACtB;AACA,SAAS,SAAS,KAAK;AACrB,MAAI,sBAAsB,QAAQ;AAChC,WAAO;AAAA,EACT;AACA,MAAI,OAAO,oBAAoB,GAAG;AAChC,QAAI,CAAC,KAAK;AACR,YAAM;AAAA,IACR;AACA,QAAI,IAAI,YAAY,eAAe;AACjC,aAAO;AAAA,IACT;AACA,UAAM,IAAI,IAAI,aAAa,IAAI,WAAW,OAAO,WAAW,cAAc,OAAO,QAAQ;AACzF,QAAI,CAAC,GAAG;AACN,YAAM,SAAS;AACf,aAAO,OAAO,iBAAiB,OAAO,cAAc;AAAA,IACtD;AACA,WAAO,2TAA2T,KAAK,CAAC,KAAK,0kDAA0kD,KAAK,EAAE,OAAO,GAAG,CAAC,CAAC;AAAA,EAC56D;AACA,SAAO;AACT;AACA,SAAS,YAAY;AACnB,SAAO,OAAO,WAAW,eAAe,OAAO,YAAY,QAAQ,OAAO,sBAAsB;AAClG;AAGA,IAAI,OAAO,IAAI;AACf,KAAK,aAAa,SAAS,MAAM,OAAO,CAAC,eAAe;AACtD,MAAI,YAAY;AACd,YAAQ,KAAK,6IAA6I;AAAA,EAC5J;AACF,CAAC;AACD,KAAK,aAAa,cAAc,MAAM,UAAU,CAAC;AACjD,KAAK,aAAa,WAAW,MAAM,OAAO,YAAY,eAAe,OAAO,QAAQ,aAAa,eAAe,OAAO,QAAQ,SAAS,SAAS,WAAW;AAC5J,KAAK,aAAa,aAAa,MAAM,OAAO,cAAc,eAAe,aAAa,QAAQ,UAAU,aAAa,QAAQ,SAAS,KAAK,UAAU,SAAS,KAAK,aAAa,KAAK,UAAU,MAAM,CAAC;AACtM,KAAK,aAAa,QAAQ,MAAM,KAAK;AACrC,KAAK,aAAa,sCAAsC,MAAM,KAAK,QAAQ,OAAO,CAAC;AACnF,KAAK,aAAa,gCAAgC,MAAM,IAAI;AAC5D,KAAK,aAAa,WAAW,MAAM,KAAK;AACxC,KAAK,aAAa,gCAAgC,MAAM,IAAI;AAC5D,KAAK,aAAa,uBAAuB,MAAM,KAAK;AACpD,KAAK,aAAa,uBAAuB,MAAM,KAAK;AAGpD,SAAS,WAAW,KAAK,OAAO;AAC9B,MAAI,YAAY;AAChB,MAAI,aAAa,GAAG,GAAG;AACrB,WAAO,UAAU,WAAW,CAAC,IAAI,CAAC,IAAI,MAAM;AAAA,EAC9C;AACA,MAAI,CAAC,MAAM,QAAQ,GAAG,GAAG;AACvB,WAAO,CAAC;AAAA,EACV;AACA,QAAM,QAAQ,CAAC;AACf,SAAO,MAAM,QAAQ,SAAS,KAAK,aAAa,SAAS,KAAK,UAAU,UAAU;AAChF,UAAM,KAAK,UAAU,MAAM;AAC3B,gBAAY,UAAU;AAAA,EACxB;AACA,MAAI,MAAM,QAAQ,GAAG,KAAK,IAAI,EAAE,QAAQ,oCAAoC,GAAG;AAC7E,+BAA2B,KAAK,OAAO,CAAC,CAAC;AAAA,EAC3C;AACA,SAAO;AACT;AACA,SAAS,2BAA2B,KAAK,OAAO,SAAS;AACvD,YAAU,WAAW,CAAC;AACtB,MAAI,CAAC,MAAM,QAAQ,GAAG,KAAK,CAAC,aAAa,GAAG,GAAG;AAC7C,WAAO,MAAM,WAAW,GAAG,MAAM,eAAe,QAAQ,KAAK,IAAI,2DAA2D,MAAM,aAAa;AAC/I;AAAA,EACF;AACA,SAAO,MAAM,SAAS,GAAG,MAAM,eAAe,QAAQ,KAAK,IAAI,gDAAgD,IAAI,iBAAiB;AACpI,SAAO,IAAI,WAAW,MAAM,IAAI,MAAM,eAAe,QAAQ,KAAK,IAAI,kBAAkB,MAAM,wBAAwB,IAAI,iBAAiB;AAC3I,QAAM,WAAW,MAAM,MAAM,CAAC;AAC9B,WAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,+BAA2B,IAAI,KAAK,UAAU,QAAQ,OAAO,EAAE,CAAC;AAAA,EAClE;AACF;AACA,SAAS,YAAY,eAAe,aAAa,SAAS,cAAc;AACtE,MAAI,kBAAkB,qBAAqB;AACzC;AAAA,EACF;AACA,MAAI,iBAAiB,MAAM;AACzB,UAAM,IAAI,MAAM,gCAAgC;AAAA,EAClD;AACA,MAAI,kBAAkB,aAAa,kBAAkB,eAAe,kBAAkB,aAAa,gBAAgB,UAAU;AAC3H,UAAM,IAAI,MAAM,aAAa,uBAAuB,yBAAyB,iCAAiC,oBAAoB;AAAA,EACpI;AACF;AACA,SAAS,gBAAgB,GAAG,SAAS,cAAc,eAAe,WAAW;AAC3E,MAAI,aAAa,QAAQ;AACvB,gBAAY,cAAc,EAAE,OAAO,SAAS,YAAY;AACxD,WAAO;AAAA,EACT;AACA,MAAI,gBAAgB,WAAW,CAAC;AAChC,MAAI,kBAAkB,YAAY,CAAC,QAAQ,SAAS,SAAS,EAAE,QAAQ,YAAY,KAAK,GAAG;AACzF,oBAAgB;AAAA,EAClB;AACA,cAAY,cAAc,eAAe,SAAS,YAAY;AAC9D,MAAI,KAAK,QAAQ,CAAC,aAAa,CAAC,KAAK,CAAC,MAAM,QAAQ,CAAC,KAAK,OAAO,MAAM,YAAY,OAAO,MAAM,aAAa,OAAO,MAAM,UAAU;AAClI,UAAM,OAAO,KAAK,OAAO,SAAS,EAAE,YAAY;AAChD,UAAM,IAAI,MAAM,aAAa,uBAAuB,0DAA0D,OAAO;AAAA,EACvH;AACA,QAAM,gBAAgB,WAAW,GAAG,aAAa;AACjD,MAAI,CAAC,aAAa,CAAC,KAAK,CAAC,MAAM,QAAQ,CAAC,GAAG;AACzC,QAAI,CAAC,CAAC;AAAA,EACR;AACA,QAAM,iBAAiB;AACvB,QAAM,SAAS,kBAAkB,WAAW,aAAa,GAAG,aAAa,IAAI,QAAQ,GAAG,CAAC,GAAG,cAAc;AAC1G,SAAO,OAAO,WAAW,QAAQ,eAAe,aAAa;AAC/D;AACA,SAAS,qBAAqB,KAAK,SAAS,cAAc,eAAe,WAAW;AAClF,MAAI,CAAC,MAAM,QAAQ,GAAG,GAAG;AACvB,UAAM,IAAI,MAAM,YAAY,qBAAqB,yDAAyD;AAAA,EAC5G;AACA,QAAM,UAAU;AAChB,SAAO,QAAQ,IAAI,CAAC,IAAI,OAAO,gBAAgB,IAAI,GAAG,WAAW,OAAO,cAAc,YAAY,CAAC;AACrG;AAGA,IAAI,kBAAkB;AACtB,SAAS,GAAG,GAAG;AACb,QAAM,OAAO,OAAO,KAAK,CAAC;AAC1B,MAAI,KAAK,WAAW,GAAG;AACrB,UAAM,IAAI,MAAM,yGAAyG,KAAK,cAAc;AAAA,EAC9I;AACA,MAAI,SAAS,KAAK;AAClB,QAAM,KAAK,EAAE;AACb,MAAI,OAAO,SAAS,GAAG,GAAG;AACxB,aAAS,OAAO,UAAU,GAAG,OAAO,SAAS,CAAC;AAAA,EAChD;AACA,WAAS,SAAS;AAClB,QAAM,KAAK,IAAI,SAAS;AACtB,WAAO,WAAW,MAAM;AACxB,QAAI;AACF,YAAM,SAAS,GAAG,GAAG,IAAI;AACzB,UAAI,UAAU,MAAM,GAAG;AACrB,gBAAQ,MAAM,yCAAyC;AAAA,MACzD;AACA,aAAO,SAAS,MAAM;AACtB,aAAO;AAAA,IACT,SAAS,IAAP;AACA,aAAO,SAAS,IAAI;AACpB,YAAM;AAAA,IACR;AAAA,EACF;AACA,SAAO,eAAe,IAAI,QAAQ,EAAE,OAAO,QAAQ,cAAc,KAAK,CAAC;AACvE,SAAO;AACT;AAGA,SAAS,SAAS,OAAO,OAAO;AAC9B,QAAM,QAAQ,gBAAgB,OAAO,QAAQ,SAAS;AACtD,QAAM,QAAQ,gBAAgB,OAAO,QAAQ,SAAS;AACtD,oBAAkB,MAAM,OAAO,MAAM,OAAO,yBAAyB,MAAM,aAAa,MAAM,4CAA4C;AAC1I,QAAM,SAAS,EAAE,MAAM,OAAO,MAAM,MAAM;AAC1C,SAAO,OAAO,UAAU,SAAS,MAAM;AACzC;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,WAAW,QAAQ,OAAO,eAAe,OAAO;AACvD,MAAI,SAAS,MAAM;AACjB,YAAQ,WAAW,MAAM;AAAA,EAC3B;AACA,MAAI,UAAU,aAAa;AACzB,UAAM,IAAI,MAAM,kFAAkF;AAAA,EACpG;AACA,MAAI,CAAC,aAAa,MAAM,KAAK,CAAC,MAAM,QAAQ,MAAM,KAAK,OAAO,WAAW,YAAY,OAAO,WAAW,aAAa,OAAO,WAAW,UAAU;AAC9I,UAAM,IAAI,MAAM,0HAA0H;AAAA,EAC5I;AACA,MAAI,SAAS,MAAM;AACjB,uCAAmC,KAAK;AACxC,UAAM,eAAe,cAAc,KAAK;AACxC,UAAM,eAAe,cAAc,aAAa;AAChD,WAAO,iBAAiB,cAAc,MAAM,iCAAiC,kCAAkC,+BAA+B,cAAc;AAC5J,aAAS,KAAK,GAAG,KAAK,cAAc,QAAQ,EAAE,IAAI;AAChD,YAAM,WAAW,cAAc;AAC/B,YAAM,oBAAoB,OAAO,cAAc,SAAS,IAAI,aAAa,cAAc,MAAM,MAAM,EAAE,CAAC,IAAI;AAC1G,aAAO,cAAc,QAAQ,MAAM,OAAO,CAAC,mBAAmB,MAAM,gDAAgD,qDAAqD,UAAU;AAAA,IACrL;AAAA,EACF;AACA,MAAI,CAAC,aAAa,MAAM,KAAK,CAAC,MAAM,QAAQ,MAAM,GAAG;AACnD,aAAS,CAAC,MAAM;AAAA,EAClB;AACA,UAAQ,SAAS;AACjB,WAAS,UAAU,WAAW,aAAa,QAAQ,KAAK,IAAI,QAAQ,QAAQ,CAAC,GAAG,IAAI;AACpF,SAAO,OAAO,WAAW,QAAQ,OAAO,KAAK;AAC/C;AAGA,SAAS,OAAO,QAAQ,OAAO,OAAO;AACpC,QAAM,gBAAgB,WAAW,QAAQ,KAAK;AAC9C,SAAO,WAAW,QAAQ,OAAO,eAAe,KAAK;AACvD;AAGA,IAAI,uBAAuB;AAAA,EACzB,WAAW;AAAA,EACX,WAAW;AAAA,EACX,SAAS;AAAA,EACT,UAAU;AAAA,EACV,SAAS;AAAA,EACT,QAAQ;AAAA,EACR,aAAa;AACf;AAGA,IAAI,0BAA0B;AAC9B,eAAe,cAAc,SAAS,OAAO;AAC3C,QAAM,QAAQ,CAAC;AACf,QAAM,eAAe,CAAC;AACtB,QAAM,QAAQ,MAAM,QAAQ,OAAO,IAAI,QAAQ,IAAI,CAAC,YAAY,QAAQ,IAAI,IAAI,OAAO,KAAK,OAAO;AACnG,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,UAAM,OAAO,MAAM;AACnB,UAAM,KAAK,MAAM,QAAQ,OAAO,IAAI,QAAQ,IAAI,SAAS,QAAQ;AACjE,QAAI,GAAG,UAAU,aAAa,GAAG,UAAU,WAAW,GAAG,UAAU,UAAU,GAAG,UAAU,YAAY,GAAG,UAAU,aAAa;AAC9H,YAAM,IAAI,MAAM,gCAAgC,UAAU,GAAG,OAAO;AAAA,IACtE;AACA,UAAM,OAAO,EAAE,MAAM,OAAO,GAAG,OAAO,OAAO,GAAG,MAAM;AACtD,QAAI,GAAG,UAAU,UAAU;AACzB,YAAM,YAAY,IAAI,QAAQ,OAAO,YAAY;AAC/C,cAAM,OAAO,MAAM,GAAG,MAAM;AAC5B,cAAM,gBAAgB,KAAK,OAAO,CAAC,IAAI,MAAM,KAAK,EAAE,QAAQ,CAAC,IAAI,0BAA0B,KAAK;AAChG,cAAM,QAAQ,IAAI,WAAW,aAAa;AAC1C,YAAI,SAAS;AACb,iBAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,gBAAM,MAAM,KAAK;AACjB,gBAAM,gBAAgB,IAAI,WAAW,IAAI,YAAY,CAAC,IAAI,MAAM,CAAC,EAAE,MAAM;AACzE,gBAAM,IAAI,eAAe,MAAM;AAC/B,oBAAU;AACV,gBAAM,IAAI,KAAK,MAAM;AACrB,oBAAU,IAAI;AAAA,QAChB;AACA,gBAAQ,KAAK;AAAA,MACf,CAAC;AACD,mBAAa,KAAK,SAAS;AAAA,IAC7B,OAAO;AACL,mBAAa,KAAK,GAAG,KAAK,CAAC;AAAA,IAC7B;AACA,QAAI,SAAS,MAAM;AACjB,WAAK,QAAQ;AAAA,IACf;AACA,UAAM,KAAK,IAAI;AAAA,EACjB;AACA,QAAM,eAAe,MAAM,QAAQ,IAAI,YAAY;AACnD,SAAO,EAAE,MAAM,uBAAuB,YAAY,GAAG,MAAM;AAC7D;AACA,SAAS,cAAc,SAAS,OAAO;AACrC,QAAM,MAAM,CAAC;AACb,MAAI;AACJ,MAAI,SAAS;AACb,aAAW,QAAQ,OAAO;AACxB,UAAM,OAAO,KAAK;AAClB,UAAM,QAAQ,KAAK;AACnB,UAAM,QAAQ,KAAK;AACnB,UAAMG,QAAO,cAAc,KAAK;AAChC,QAAI;AACJ,QAAI,kBAAkB,MAAM;AAC1B,YAAM,eAAe,KAAK;AAC1B,UAAI,aAAa,UAAU,WAAW,aAAa,UAAU,UAAU;AACrE,YAAI,EAAE,SAAS,gBAAgB,WAAW,eAAe;AACvD,gBAAM,IAAI,MAAM,UAAU,KAAK,0BAA0B,aAAa,0DAA0D;AAAA,QAClI;AAAA,MACF,WAAW,aAAa,UAAU,WAAW;AAC3C,YAAI,UAAU,WAAW;AACvB,gBAAM,IAAI,MAAM,UAAU,KAAK,0BAA0B,aAAa,yDAAyD,QAAQ;AAAA,QACzI;AAAA,MACF,OAAO;AACL,cAAM,IAAI,MAAM,UAAU,KAAK,uCAAuC,aAAa,6EAA6E;AAAA,MAClK;AACA,YAAM,yBAAyB,qBAAqB,aAAa;AACjE,YAAM,aAAa,QAAQ,MAAM,QAAQ,SAASA,QAAO,sBAAsB;AAC/E,YAAM,iBAAiB,aAAa,UAAU,UAAU,IAAI,WAAW,UAAU,IAAI,IAAI,YAAY,UAAU;AAC/G,UAAI,UAAU,WAAW;AACvB,YAAI,aAAa,UAAU,WAAW,aAAa,UAAU,UAAU;AACrE,mBAAS,IAAI,aAAa,eAAe,MAAM;AAC/C,mBAAS,KAAK,GAAG,KAAK,eAAe,QAAQ,MAAM;AACjD,kBAAM,IAAI,eAAe;AACzB,mBAAO,MAAM,IAAI,aAAa,QAAQ,aAAa;AAAA,UACrD;AAAA,QACF,WAAW,aAAa,UAAU,WAAW;AAC3C,cAAI,kBAAkB,QAAQ;AAC5B,4BAAgB,kBAAkB;AAAA,UACpC;AACA,mBAAS,cAAc,cAAc;AAAA,QACvC,OAAO;AACL,gBAAM,IAAI,MAAM,iCAAiC,aAAa,gCAAgC;AAAA,QAChG;AAAA,MACF,WAAW,UAAU,SAAS;AAC5B,YAAI,aAAa,UAAU,WAAW,aAAa,UAAU,UAAU;AACrE,gBAAM,IAAI,MAAM,iCAAiC,aAAa,8BAA8B;AAAA,QAC9F;AACA,iBAAS,IAAI,WAAW,eAAe,MAAM;AAC7C,iBAAS,KAAK,GAAG,KAAK,eAAe,QAAQ,MAAM;AACjD,gBAAM,IAAI,eAAe;AACzB,iBAAO,MAAM,KAAK,MAAM,IAAI,aAAa,QAAQ,aAAa,GAAG;AAAA,QACnE;AAAA,MACF,OAAO;AACL,cAAM,IAAI,MAAM,gCAAgC,UAAU,OAAO;AAAA,MACnE;AACA,gBAAUA,QAAO;AAAA,IACnB,WAAW,UAAU,UAAU;AAC7B,YAAMkB,SAAQ,cAAc,KAAK,KAAK;AACtC,eAAS,CAAC;AACV,eAAS,KAAK,GAAG,KAAKA,QAAO,MAAM;AACjC,cAAM,aAAa,IAAI,YAAY,QAAQ,MAAM,QAAQ,SAAS,uBAAuB,CAAC,EAAE;AAC5F,kBAAU;AACV,cAAM,QAAQ,IAAI,WAAW,QAAQ,MAAM,QAAQ,SAAS,UAAU,CAAC;AACvE,eAAO,KAAK,KAAK;AACjB,kBAAU;AAAA,MACZ;AAAA,IACF,OAAO;AACL,YAAM,cAAc,qBAAqB;AACzC,YAAM,aAAa,QAAQ,MAAM,QAAQ,SAASlB,QAAO,WAAW;AACpE,UAAI,UAAU,WAAW;AACvB,iBAAS,IAAI,aAAa,UAAU;AAAA,MACtC,WAAW,UAAU,SAAS;AAC5B,iBAAS,IAAI,WAAW,UAAU;AAAA,MACpC,WAAW,UAAU,QAAQ;AAC3B,iBAAS,IAAI,WAAW,UAAU;AAAA,MACpC,WAAW,UAAU,aAAa;AAChC,iBAAS,IAAI,aAAa,UAAU;AACpC,cAAM,QAAQ,IAAI,aAAa,OAAO,SAAS,CAAC;AAChD,cAAM,SAAS,IAAI,aAAa,OAAO,SAAS,CAAC;AACjD,iBAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,gBAAM,MAAM,OAAO,KAAK;AACxB,iBAAO,MAAM,OAAO,KAAK,IAAI;AAAA,QAC/B;AACA,cAAM,aAAa,OAAO,OAAO,OAAO,SAAS;AACjD,cAAM,cAAc,OAAO,QAAQ,OAAO,SAAS;AACnD,YAAI,QAAQ,QAAQ,YAAY,WAAW;AAC3C,mBAAW,QAAQ;AACnB,oBAAY,QAAQ;AAAA,MACtB,OAAO;AACL,cAAM,IAAI,MAAM,gCAAgC,UAAU,OAAO;AAAA,MACnE;AACA,gBAAUA,QAAO;AAAA,IACnB;AACA,QAAI,UAAU,aAAa;AACzB,UAAI,QAAQ,OAAO,QAAQ,OAAO,KAAK;AAAA,IACzC;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,uBAAuB,IAAI;AAClC,MAAI,OAAO,MAAM;AACf,UAAM,IAAI,MAAM,wBAAwB,KAAK,UAAU,EAAE,GAAG;AAAA,EAC9D;AACA,MAAI,kBAAkB;AACtB,QAAM,eAAe,CAAC;AACtB,KAAG,QAAQ,CAAC,MAAM;AAChB,uBAAmB,EAAE;AACrB,iBAAa,KAAK,EAAE,eAAe,EAAE,OAAO,aAAa,IAAI,IAAI,EAAE,YAAY,CAAC,CAAC;AACjF,QAAI,EAAE,aAAa,gBAAgB,aAAa,cAAc,aAAa,aAAa;AACtF,YAAM,IAAI,MAAM,mCAAmC,EAAE,YAAY,MAAM;AAAA,IACzE;AAAA,EACF,CAAC;AACD,QAAM,IAAI,IAAI,WAAW,eAAe;AACxC,MAAI,SAAS;AACb,eAAa,QAAQ,CAAC,MAAM;AAC1B,MAAE,IAAI,IAAI,WAAW,EAAE,MAAM,GAAG,MAAM;AACtC,cAAU,EAAE;AAAA,EACd,CAAC;AACD,SAAO,EAAE;AACX;AACA,IAAI,gBAAgB,OAAO,WAAW,gBAAgB,OAAO,SAAS,eAAe,OAAO,SAAS,eAAe,OAAO,SAAS;AACpI,SAAS,iBAAiB,KAAK;AAC7B,MAAI,eAAe;AACjB,WAAO,OAAO,WAAW,GAAG;AAAA,EAC9B;AACA,SAAO,IAAI,KAAK,CAAC,GAAG,CAAC,EAAE;AACzB;AACA,SAAS,0BAA0B,SAAS;AAC1C,MAAI,eAAe;AACjB,WAAO,OAAO,KAAK,OAAO,EAAE,SAAS,QAAQ;AAAA,EAC/C;AACA,QAAM,MAAM,IAAI,WAAW,OAAO;AAClC,MAAI,KAAK;AACT,WAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,KAAK,IAAI,MAAM;AAC/C,UAAM,OAAO,aAAa,IAAI,GAAG;AAAA,EACnC;AACA,SAAO,KAAK,EAAE;AAChB;AACA,SAAS,0BAA0B,KAAK;AACtC,MAAI,eAAe;AACjB,UAAM,MAAM,OAAO,KAAK,KAAK,QAAQ;AACrC,WAAO,IAAI,OAAO,MAAM,IAAI,YAAY,IAAI,aAAa,IAAI,UAAU;AAAA,EACzE;AACA,QAAM,KAAK,KAAK,GAAG;AACnB,QAAM,UAAU,IAAI,WAAW,GAAG,MAAM;AACxC,WAAS,KAAK,GAAG,KAAK,GAAG,QAAQ,EAAE,IAAI;AACrC,YAAQ,IAAI,CAAC,GAAG,WAAW,EAAE,CAAC,GAAG,EAAE;AAAA,EACrC;AACA,SAAO,QAAQ;AACjB;AACA,SAAS,wBAAwB,SAAS;AACxC,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO,QAAQ;AAAA,EACjB;AACA,MAAI,kBAAkB;AACtB,UAAQ,QAAQ,CAAC,YAAY;AAC3B,uBAAmB,QAAQ;AAAA,EAC7B,CAAC;AACD,QAAM,OAAO,IAAI,WAAW,eAAe;AAC3C,MAAI,SAAS;AACb,UAAQ,QAAQ,CAAC,YAAY;AAC3B,SAAK,IAAI,IAAI,WAAW,OAAO,GAAG,MAAM;AACxC,cAAU,QAAQ;AAAA,EACpB,CAAC;AACD,SAAO,KAAK;AACd;AACA,SAAS,SAAS,MAAM;AACtB,QAAM,YAAY;AAClB,SAAO,KAAK,KAAK;AACjB,SAAO,KAAK,SAAS,SAAS,GAAG;AAC/B,WAAO,KAAK,MAAM,GAAG,KAAK,SAAS,CAAC;AAAA,EACtC;AACA,QAAM,QAAQ,KAAK,MAAM,SAAS;AAClC,SAAO,MAAM,MAAM,SAAS;AAC9B;AACA,SAAS,8BAA8B,WAAW,UAAU;AAC1D,QAAM,SAAS;AAAA,IACb,eAAe,UAAU;AAAA,IACzB,QAAQ,UAAU;AAAA,IAClB,aAAa,UAAU;AAAA,IACvB,aAAa,UAAU;AAAA,IACvB,iBAAiB;AAAA,EACnB;AACA,MAAI,UAAU,aAAa,MAAM;AAC/B,WAAO,YAAY,UAAU;AAAA,EAC/B;AACA,MAAI,UAAU,uBAAuB,MAAM;AACzC,WAAO,sBAAsB,UAAU;AAAA,EACzC;AACA,MAAI,UAAU,oBAAoB,MAAM;AACtC,WAAO,mBAAmB,UAAU;AAAA,EACtC;AACA,MAAI,UAAU,kBAAkB,MAAM;AACpC,WAAO,iBAAiB,UAAU;AAAA,EACpC;AACA,SAAO;AACT;AACA,eAAe,yBAAyB,WAAW,cAAc;AAC/D,QAAM,iBAAiB;AAAA,IACrB,eAAe,UAAU;AAAA,IACzB,QAAQ,UAAU;AAAA,IAClB,aAAa,UAAU;AAAA,IACvB,aAAa,UAAU;AAAA,EACzB;AACA,MAAI,UAAU,kBAAkB,MAAM;AACpC,mBAAe,iBAAiB,UAAU;AAAA,EAC5C;AACA,MAAI,UAAU,mBAAmB,MAAM;AACrC,UAAM,CAAC,aAAa,UAAU,IAAI,MAAM,aAAa,UAAU,eAAe;AAC9E,mBAAe,cAAc;AAC7B,mBAAe,aAAa;AAAA,EAC9B;AACA,MAAI,UAAU,aAAa,MAAM;AAC/B,mBAAe,YAAY,UAAU;AAAA,EACvC;AACA,MAAI,UAAU,uBAAuB,MAAM;AACzC,mBAAe,sBAAsB,UAAU;AAAA,EACjD;AACA,MAAI,UAAU,oBAAoB,MAAM;AACtC,mBAAe,mBAAmB,UAAU;AAAA,EAC9C;AACA,SAAO;AACT;AACA,SAAS,6BAA6B,gBAAgB;AACpD,MAAI,eAAe,yBAAyB,aAAa;AACvD,UAAM,IAAI,MAAM,qDAAqD;AAAA,EACvE;AACA,SAAO;AAAA,IACL,WAAW,IAAI,KAAK;AAAA,IACpB,mBAAmB;AAAA,IACnB,oBAAoB,eAAe,iBAAiB,OAAO,IAAI,iBAAiB,KAAK,UAAU,eAAe,aAAa,CAAC;AAAA,IAC5H,kBAAkB,eAAe,eAAe,OAAO,IAAI,iBAAiB,KAAK,UAAU,eAAe,WAAW,CAAC;AAAA,IACtH,iBAAiB,eAAe,cAAc,OAAO,IAAI,eAAe,WAAW;AAAA,EACrF;AACF;AACA,SAAS,6BAA6B;AACpC,QAAM,kBAAkB,CAAC,OAAO;AAC9B,QAAI,IAAI,MAAM;AACd,QAAI,KAAK;AACT,YAAQ,IAAI,aAAa,GAAG;AAC1B,YAAM;AACN,YAAM;AAAA,IACR;AACA,SAAK,CAAC;AACN,UAAM;AACN,WAAO,IAAI;AAAA,EACb;AACA,QAAM,eAAe,IAAI,YAAY,IAAI;AACzC,eAAa,KAAK;AAClB,WAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,iBAAa,MAAM,gBAAgB,EAAE;AAAA,EACvC;AACA,WAAS,KAAK,MAAM,KAAK,MAAM,MAAM;AACnC,iBAAa,MAAM,aAAa,KAAK,QAAQ;AAAA,EAC/C;AACA,SAAO;AACT;AACA,SAAS,8BAA8B;AACrC,QAAM,gBAAgB,IAAI,YAAY,EAAE;AACxC,gBAAc,KAAK;AACnB,gBAAc,MAAM;AACpB,gBAAc,MAAM;AACpB,gBAAc,MAAM;AACpB,WAAS,KAAK,GAAG,KAAK,IAAI,MAAM;AAC9B,kBAAc,MAAM,MAAM;AAAA,EAC5B;AACA,WAAS,KAAK,IAAI,KAAK,IAAI,MAAM;AAC/B,kBAAc,MAAM,cAAc,KAAK,MAAM;AAAA,EAC/C;AACA,SAAO;AACT;AACA,SAAS,4BAA4B;AACnC,QAAM,cAAc,IAAI,YAAY,EAAE;AACtC,WAAS,KAAK,GAAG,KAAK,IAAI,MAAM;AAC9B,gBAAY,MAAM;AAAA,EACpB;AACA,cAAY,KAAK,YAAY,MAAM;AACnC,SAAO;AACT;AACA,SAAS,oBAAoB;AAC3B,QAAM,eAAe,2BAA2B;AAChD,QAAM,gBAAgB,4BAA4B;AAClD,QAAM,cAAc,0BAA0B;AAC9C,SAAO,CAAC,mBAAmB;AACzB,UAAM,UAAU,IAAI,YAAY,IAAI,eAAe,MAAM;AACzD,UAAM,mBAAmB,IAAI,YAAY,OAAO;AAChD,aAASS,SAAQ,GAAGA,SAAQ,eAAe,QAAQA,UAAS;AAC1D,YAAM,cAAc,eAAeA;AACnC,YAAM,cAAc,aAAa,YAAY,eAAe,OAAO,cAAc,SAAS,cAAc,eAAe;AACvH,uBAAiBA,UAAS;AAAA,IAC5B;AACA,WAAO,IAAI,aAAa,OAAO;AAAA,EACjC;AACF;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,cAAc;AACZ,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc,CAAC;AAAA,EACtB;AAAA,EACA,OAAO,cAAc;AACnB,QAAI,iBAAiB,YAAY,MAAM;AACrC,uBAAiB,WAAW,IAAI,iBAAiB;AAAA,IACnD;AACA,WAAO,iBAAiB;AAAA,EAC1B;AAAA,EACA,OAAO,mBAAmB,YAAY;AACpC,qBAAiB,YAAY,EAAE,YAAY,KAAK,UAAU;AAAA,EAC5D;AAAA,EACA,OAAO,mBAAmB,YAAY;AACpC,qBAAiB,YAAY,EAAE,YAAY,KAAK,UAAU;AAAA,EAC5D;AAAA,EACA,OAAO,gBAAgB,KAAK;AAC1B,WAAO,iBAAiB,YAAY,KAAK,MAAM;AAAA,EACjD;AAAA,EACA,OAAO,gBAAgB,KAAK,aAAa;AACvC,WAAO,iBAAiB,YAAY,KAAK,QAAQ,WAAW;AAAA,EAC9D;AAAA,EACA,OAAO,YAAY,KAAK,aAAa,aAAa;AAChD,UAAM,gBAAgB,CAAC;AACvB,UAAM,UAAU,gBAAgB,SAAS,iBAAiB,YAAY,EAAE,cAAc,iBAAiB,YAAY,EAAE;AACrH,YAAQ,QAAQ,CAAC,WAAW;AAC1B,YAAM,UAAU,OAAO,KAAK,WAAW;AACvC,UAAI,YAAY,MAAM;AACpB,sBAAc,KAAK,OAAO;AAAA,MAC5B;AAAA,IACF,CAAC;AACD,WAAO;AAAA,EACT;AACF;AACA,IAAI,qBAAqB,CAAC,eAAe,iBAAiB,mBAAmB,UAAU;AACvF,IAAI,qBAAqB,CAAC,eAAe,iBAAiB,mBAAmB,UAAU;AACvF,IAAI,kBAAkB,CAAC,QAAQ,iBAAiB,gBAAgB,GAAG;AACnE,IAAI,kBAAkB,CAAC,KAAK,gBAAgB,iBAAiB,gBAAgB,KAAK,WAAW;AAG7F,IAAI,gBAAgB;AACpB,IAAI,mBAAmB;AACvB,IAAI,mBAAmB;AACvB,IAAI,kBAAkB;AACtB,SAAS,sBAAsB;AAC7B,MAAI,CAAC,IAAI,EAAE,QAAQ,YAAY,GAAG;AAChC,UAAM,IAAI,MAAM,yFAAyF;AAAA,EAC3G;AACA,QAAM,YAAY,OAAO,WAAW,cAAc,OAAO;AACzD,QAAM,UAAU,UAAU,aAAa,UAAU,gBAAgB,UAAU,mBAAmB,UAAU,eAAe,UAAU;AACjI,MAAI,WAAW,MAAM;AACnB,UAAM,IAAI,MAAM,2DAA2D;AAAA,EAC7E;AACA,SAAO;AACT;AACA,SAAS,cAAc,aAAa;AAClC,QAAM,KAAK,YAAY;AACvB,KAAG,kBAAkB,kBAAkB,EAAE,SAAS,YAAY,CAAC;AAC/D,KAAG,kBAAkB,iBAAiB,EAAE,SAAS,YAAY,CAAC;AAChE;AACA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,WAAW;AACrB,SAAK,YAAY,oBAAoB;AACrC,QAAI,aAAa,QAAQ,CAAC,WAAW;AACnC,YAAM,IAAI,MAAM,gEAAgE;AAAA,IAClF;AACA,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,MAAM,KAAK,gBAAgB;AACzB,QAAI,eAAe,yBAAyB,aAAa;AACvD,YAAM,IAAI,MAAM,0FAA0F;AAAA,IAC5G;AACA,WAAO,KAAK,eAAe,KAAK,WAAW,cAAc;AAAA,EAC3D;AAAA,EACA,MAAM,OAAO;AACX,WAAO,KAAK,eAAe,KAAK,SAAS;AAAA,EAC3C;AAAA,EACA,eAAe,WAAW,gBAAgB;AACxC,WAAO,IAAI,QAAQ,CAAC,SAAS,WAAW;AACtC,YAAM,cAAc,KAAK,UAAU,KAAK,eAAe,gBAAgB;AACvE,kBAAY,kBAAkB,MAAM,cAAc,WAAW;AAC7D,kBAAY,YAAY,MAAM;AAC5B,cAAM,KAAK,YAAY;AACvB,YAAI,kBAAkB,MAAM;AAC1B,gBAAM,UAAU,GAAG,YAAY,kBAAkB,UAAU;AAC3D,gBAAM,aAAa,QAAQ,YAAY,gBAAgB;AACvD,gBAAM,aAAa,WAAW,IAAI,KAAK,SAAS;AAChD,qBAAW,YAAY,MAAM;AAC3B,gBAAI,WAAW,UAAU,MAAM;AAC7B,iBAAG,MAAM;AACT,qBAAO,OAAO,IAAI,MAAM,gCAAgC,KAAK,0BAA0B,CAAC;AAAA,YAC1F,OAAO;AACL,sBAAQ,WAAW,OAAO,cAAc;AAAA,YAC1C;AAAA,UACF;AACA,qBAAW,UAAU,CAAC,UAAU;AAC9B,eAAG,MAAM;AACT,mBAAO,OAAO,WAAW,KAAK;AAAA,UAChC;AACA,kBAAQ,aAAa,MAAM,GAAG,MAAM;AAAA,QACtC,OAAO;AACL,gBAAM,qBAAqB,6BAA6B,cAAc;AACtE,gBAAM,SAAS,GAAG,YAAY,iBAAiB,WAAW;AAC1D,cAAI,YAAY,OAAO,YAAY,eAAe;AAClD,gBAAM,iBAAiB,UAAU,IAAI,EAAE,WAAW,KAAK,WAAW,mBAAmB,CAAC;AACtF,cAAI;AACJ,yBAAe,YAAY,MAAM;AAC/B,sBAAU,GAAG,YAAY,kBAAkB,WAAW;AACtD,kBAAM,aAAa,QAAQ,YAAY,gBAAgB;AACvD,kBAAM,kBAAkB,WAAW,IAAI;AAAA,cACrC,WAAW,KAAK;AAAA,cAChB;AAAA,cACA;AAAA,YACF,CAAC;AACD,4BAAgB,YAAY,MAAM,QAAQ,EAAE,mBAAmB,CAAC;AAChE,4BAAgB,UAAU,CAAC,UAAU;AACnC,0BAAY,OAAO,YAAY,eAAe;AAC9C,oBAAM,oBAAoB,UAAU,OAAO,KAAK,SAAS;AACzD,gCAAkB,YAAY,MAAM;AAClC,mBAAG,MAAM;AACT,uBAAO,OAAO,gBAAgB,KAAK;AAAA,cACrC;AACA,gCAAkB,UAAU,CAAC,WAAW;AACtC,mBAAG,MAAM;AACT,uBAAO,OAAO,gBAAgB,KAAK;AAAA,cACrC;AAAA,YACF;AAAA,UACF;AACA,yBAAe,UAAU,CAAC,UAAU;AAClC,eAAG,MAAM;AACT,mBAAO,OAAO,eAAe,KAAK;AAAA,UACpC;AACA,iBAAO,aAAa,MAAM;AACxB,gBAAI,WAAW,MAAM;AACnB,iBAAG,MAAM;AAAA,YACX,OAAO;AACL,sBAAQ,aAAa,MAAM,GAAG,MAAM;AAAA,YACtC;AAAA,UACF;AAAA,QACF;AAAA,MACF;AACA,kBAAY,UAAU,CAAC,UAAU,OAAO,YAAY,KAAK;AAAA,IAC3D,CAAC;AAAA,EACH;AACF;AACA,iBAAiB,aAAa;AAC9B,IAAI,kBAAkB,CAAC,QAAQ;AAC7B,MAAI,CAAC,IAAI,EAAE,QAAQ,YAAY,GAAG;AAChC,WAAO;AAAA,EACT,OAAO;AACL,QAAI,CAAC,MAAM,QAAQ,GAAG,KAAK,IAAI,WAAW,iBAAiB,UAAU,GAAG;AACtE,aAAO,iBAAiB,IAAI,MAAM,iBAAiB,WAAW,MAAM,CAAC;AAAA,IACvE,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AACF;AACA,iBAAiB,mBAAmB,eAAe;AACnD,iBAAiB,mBAAmB,eAAe;AACnD,SAAS,iBAAiB,WAAW;AACnC,SAAO,IAAI,iBAAiB,SAAS;AACvC;AACA,SAAS,iBAAiB,KAAK;AAC7B,SAAO,IAAI,WAAW,iBAAiB,UAAU,IAAI,IAAI,MAAM,iBAAiB,WAAW,MAAM,IAAI;AACvG;AACA,IAAI,0BAA0B,MAAM;AAAA,EAClC,cAAc;AACZ,SAAK,YAAY,oBAAoB;AAAA,EACvC;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,IAAI,QAAQ,CAAC,SAAS,WAAW;AACtC,YAAM,cAAc,KAAK,UAAU,KAAK,eAAe,gBAAgB;AACvE,kBAAY,kBAAkB,MAAM,cAAc,WAAW;AAC7D,kBAAY,YAAY,MAAM;AAC5B,cAAM,KAAK,YAAY;AACvB,cAAM,KAAK,GAAG,YAAY,iBAAiB,UAAU;AACrD,cAAM,QAAQ,GAAG,YAAY,eAAe;AAC5C,cAAM,oBAAoB,MAAM,OAAO;AACvC,0BAAkB,YAAY,MAAM;AAClC,gBAAM,MAAM,CAAC;AACb,qBAAW,QAAQ,kBAAkB,QAAQ;AAC3C,gBAAI,KAAK,aAAa,KAAK;AAAA,UAC7B;AACA,kBAAQ,GAAG;AAAA,QACb;AACA,0BAAkB,UAAU,CAAC,UAAU;AACrC,aAAG,MAAM;AACT,iBAAO,OAAO,kBAAkB,KAAK;AAAA,QACvC;AACA,WAAG,aAAa,MAAM,GAAG,MAAM;AAAA,MACjC;AACA,kBAAY,UAAU,CAAC,UAAU,OAAO,YAAY,KAAK;AAAA,IAC3D,CAAC;AAAA,EACH;AAAA,EACA,MAAM,YAAY,MAAM;AACtB,WAAO,iBAAiB,IAAI;AAC5B,WAAO,IAAI,QAAQ,CAAC,SAAS,WAAW;AACtC,YAAM,cAAc,KAAK,UAAU,KAAK,eAAe,gBAAgB;AACvE,kBAAY,kBAAkB,MAAM,cAAc,WAAW;AAC7D,kBAAY,YAAY,MAAM;AAC5B,cAAM,KAAK,YAAY;AACvB,cAAM,SAAS,GAAG,YAAY,iBAAiB,WAAW;AAC1D,cAAM,YAAY,OAAO,YAAY,eAAe;AACpD,cAAM,iBAAiB,UAAU,IAAI,IAAI;AACzC,YAAI;AACJ,uBAAe,YAAY,MAAM;AAC/B,cAAI,eAAe,UAAU,MAAM;AACjC,eAAG,MAAM;AACT,mBAAO,OAAO,IAAI,MAAM,gCAAgC,qBAAqB,CAAC;AAAA,UAChF,OAAO;AACL,kBAAM,oBAAoB,UAAU,OAAO,IAAI;AAC/C,kBAAM,kBAAkB,MAAM;AAC5B,wBAAU,GAAG,YAAY,kBAAkB,WAAW;AACtD,oBAAM,aAAa,QAAQ,YAAY,gBAAgB;AACvD,oBAAM,qBAAqB,WAAW,OAAO,IAAI;AACjD,iCAAmB,YAAY,MAAM,QAAQ,eAAe,OAAO,kBAAkB;AACrF,iCAAmB,UAAU,CAAC,UAAU,OAAO,eAAe,KAAK;AAAA,YACrE;AACA,8BAAkB,YAAY;AAC9B,8BAAkB,UAAU,CAAC,UAAU;AACrC,8BAAgB;AAChB,iBAAG,MAAM;AACT,qBAAO,OAAO,eAAe,KAAK;AAAA,YACpC;AAAA,UACF;AAAA,QACF;AACA,uBAAe,UAAU,CAAC,UAAU;AAClC,aAAG,MAAM;AACT,iBAAO,OAAO,eAAe,KAAK;AAAA,QACpC;AACA,eAAO,aAAa,MAAM;AACxB,cAAI,WAAW,MAAM;AACnB,eAAG,MAAM;AAAA,UACX,OAAO;AACL,oBAAQ,aAAa,MAAM,GAAG,MAAM;AAAA,UACtC;AAAA,QACF;AAAA,MACF;AACA,kBAAY,UAAU,CAAC,UAAU,OAAO,YAAY,KAAK;AAAA,IAC3D,CAAC;AAAA,EACH;AACF;AAGA,IAAI,iBAAiB;AACrB,IAAI,cAAc;AAClB,IAAI,cAAc;AAClB,IAAI,wBAAwB;AAC5B,IAAI,sBAAsB;AAC1B,IAAI,qBAAqB;AACzB,IAAI,wBAAwB;AAC5B,SAAS,aAAa,MAAM;AAC1B,SAAO;AAAA,IACL,MAAM,CAAC,aAAa,MAAM,WAAW,EAAE,KAAK,cAAc;AAAA,IAC1D,UAAU,CAAC,aAAa,MAAM,qBAAqB,EAAE,KAAK,cAAc;AAAA,IACxE,aAAa,CAAC,aAAa,MAAM,mBAAmB,EAAE,KAAK,cAAc;AAAA,IACzE,YAAY,CAAC,aAAa,MAAM,kBAAkB,EAAE,KAAK,cAAc;AAAA,IACvE,eAAe,CAAC,aAAa,MAAM,qBAAqB,EAAE,KAAK,cAAc;AAAA,EAC/E;AACF;AACA,SAAS,YAAY,MAAM;AACzB,aAAW,OAAO,OAAO,OAAO,IAAI,GAAG;AACrC,WAAO,aAAa,WAAW,GAAG;AAAA,EACpC;AACF;AACA,SAAS,oBAAoB,KAAK;AAChC,QAAM,QAAQ,IAAI,MAAM,cAAc;AACtC,MAAI,MAAM,SAAS,GAAG;AACpB,UAAM,IAAI,MAAM,uBAAuB,KAAK;AAAA,EAC9C;AACA,SAAO,MAAM,MAAM,GAAG,MAAM,SAAS,CAAC,EAAE,KAAK,cAAc;AAC7D;AACA,SAAS,kBAAkB,KAAK;AAC9B,SAAO,IAAI,WAAW,oBAAoB,UAAU,IAAI,IAAI,MAAM,oBAAoB,WAAW,MAAM,IAAI;AAC7G;AACA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,WAAW;AACrB,QAAI,CAAC,IAAI,EAAE,QAAQ,YAAY,KAAK,OAAO,WAAW,eAAe,OAAO,OAAO,iBAAiB,aAAa;AAC/G,YAAM,IAAI,MAAM,yDAAyD;AAAA,IAC3E;AACA,SAAK,KAAK,OAAO;AACjB,QAAI,aAAa,QAAQ,CAAC,WAAW;AACnC,YAAM,IAAI,MAAM,oEAAoE;AAAA,IACtF;AACA,SAAK,YAAY;AACjB,SAAK,OAAO,aAAa,KAAK,SAAS;AAAA,EACzC;AAAA,EACA,MAAM,KAAK,gBAAgB;AACzB,QAAI,eAAe,yBAAyB,aAAa;AACvD,YAAM,IAAI,MAAM,0FAA0F;AAAA,IAC5G,OAAO;AACL,YAAM,WAAW,KAAK,UAAU,eAAe,aAAa;AAC5D,YAAM,cAAc,KAAK,UAAU,eAAe,WAAW;AAC7D,YAAM,qBAAqB,6BAA6B,cAAc;AACtE,UAAI;AACF,aAAK,GAAG,QAAQ,KAAK,KAAK,MAAM,KAAK,UAAU,kBAAkB,CAAC;AAClE,aAAK,GAAG,QAAQ,KAAK,KAAK,UAAU,QAAQ;AAC5C,aAAK,GAAG,QAAQ,KAAK,KAAK,aAAa,WAAW;AAClD,aAAK,GAAG,QAAQ,KAAK,KAAK,YAAY,0BAA0B,eAAe,UAAU,CAAC;AAC1F,cAAM,WAAW;AAAA,UACf,QAAQ,eAAe;AAAA,UACvB,aAAa,eAAe;AAAA,UAC5B,aAAa,eAAe;AAAA,UAC5B,WAAW,eAAe,aAAa,OAAO,eAAe,YAAY;AAAA,UACzE,qBAAqB,eAAe,uBAAuB,OAAO,eAAe,sBAAsB;AAAA,UACvG,kBAAkB,eAAe,oBAAoB,OAAO,eAAe,mBAAmB;AAAA,UAC9F,gBAAgB,eAAe,kBAAkB,OAAO,eAAe,iBAAiB;AAAA,QAC1F;AACA,aAAK,GAAG,QAAQ,KAAK,KAAK,eAAe,KAAK,UAAU,QAAQ,CAAC;AACjE,eAAO,EAAE,mBAAmB;AAAA,MAC9B,SAAS,KAAP;AACA,oBAAY,KAAK,IAAI;AACrB,cAAM,IAAI,MAAM,yBAAyB,KAAK,kHAAkH,mBAAmB,wCAAwC,mBAAmB,qCAAqC,mBAAmB,kBAAkB;AAAA,MAC1T;AAAA,IACF;AAAA,EACF;AAAA,EACA,MAAM,OAAO;AACX,UAAM,OAAO,KAAK,MAAM,KAAK,GAAG,QAAQ,KAAK,KAAK,IAAI,CAAC;AACvD,QAAI,QAAQ,MAAM;AAChB,YAAM,IAAI,MAAM,kDAAkD,KAAK,YAAY;AAAA,IACrF;AACA,QAAI,KAAK,sBAAsB,QAAQ;AACrC,YAAM,IAAI,MAAM,2EAA2E;AAAA,IAC7F;AACA,UAAM,MAAM,CAAC;AACb,UAAM,WAAW,KAAK,MAAM,KAAK,GAAG,QAAQ,KAAK,KAAK,QAAQ,CAAC;AAC/D,QAAI,YAAY,MAAM;AACpB,YAAM,IAAI,MAAM,4CAA4C,KAAK,wBAAwB;AAAA,IAC3F;AACA,QAAI,gBAAgB;AACpB,UAAM,cAAc,KAAK,MAAM,KAAK,GAAG,QAAQ,KAAK,KAAK,WAAW,CAAC;AACrE,QAAI,eAAe,MAAM;AACvB,YAAM,IAAI,MAAM,gDAAgD,KAAK,yBAAyB;AAAA,IAChG;AACA,QAAI,cAAc;AAClB,UAAM,iBAAiB,KAAK,GAAG,QAAQ,KAAK,KAAK,aAAa;AAC9D,QAAI,kBAAkB,MAAM;AAC1B,YAAM,WAAW,KAAK,MAAM,cAAc;AAC1C,UAAI,SAAS,SAAS;AACtB,UAAI,cAAc,SAAS;AAC3B,UAAI,cAAc,SAAS;AAC3B,UAAI,SAAS,aAAa,MAAM;AAC9B,YAAI,YAAY,SAAS;AAAA,MAC3B;AACA,UAAI,SAAS,uBAAuB,MAAM;AACxC,YAAI,sBAAsB,SAAS;AAAA,MACrC;AACA,UAAI,SAAS,oBAAoB,MAAM;AACrC,YAAI,mBAAmB,SAAS;AAAA,MAClC;AACA,UAAI,SAAS,kBAAkB,MAAM;AACnC,YAAI,iBAAiB,SAAS;AAAA,MAChC;AAAA,IACF;AACA,UAAM,mBAAmB,KAAK,GAAG,QAAQ,KAAK,KAAK,UAAU;AAC7D,QAAI,oBAAoB,MAAM;AAC5B,YAAM,IAAI,MAAM,wDAAwD,KAAK,yBAAyB;AAAA,IACxG;AACA,QAAI,aAAa,0BAA0B,gBAAgB;AAC3D,WAAO;AAAA,EACT;AACF;AACA,oBAAoB,aAAa;AACjC,IAAI,qBAAqB,CAAC,QAAQ;AAChC,MAAI,CAAC,IAAI,EAAE,QAAQ,YAAY,GAAG;AAChC,WAAO;AAAA,EACT,OAAO;AACL,QAAI,CAAC,MAAM,QAAQ,GAAG,KAAK,IAAI,WAAW,oBAAoB,UAAU,GAAG;AACzE,aAAO,oBAAoB,IAAI,MAAM,oBAAoB,WAAW,MAAM,CAAC;AAAA,IAC7E,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AACF;AACA,iBAAiB,mBAAmB,kBAAkB;AACtD,iBAAiB,mBAAmB,kBAAkB;AACtD,SAAS,oBAAoB,WAAW;AACtC,SAAO,IAAI,oBAAoB,SAAS;AAC1C;AACA,IAAI,6BAA6B,MAAM;AAAA,EACrC,cAAc;AACZ,WAAO,IAAI,EAAE,QAAQ,YAAY,GAAG,MAAM,0CAA0C;AACpF,WAAO,OAAO,WAAW,eAAe,OAAO,OAAO,iBAAiB,aAAa,MAAM,yDAAyD;AACnJ,SAAK,KAAK,OAAO;AAAA,EACnB;AAAA,EACA,MAAM,aAAa;AACjB,UAAM,MAAM,CAAC;AACb,UAAM,SAAS,cAAc;AAC7B,UAAM,SAAS,iBAAiB;AAChC,aAAS,KAAK,GAAG,KAAK,KAAK,GAAG,QAAQ,EAAE,IAAI;AAC1C,YAAM,MAAM,KAAK,GAAG,IAAI,EAAE;AAC1B,UAAI,IAAI,WAAW,MAAM,KAAK,IAAI,SAAS,MAAM,GAAG;AAClD,cAAM,YAAY,oBAAoB,GAAG;AACzC,YAAI,aAAa,KAAK,MAAM,KAAK,GAAG,QAAQ,GAAG,CAAC;AAAA,MAClD;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,YAAY,MAAM;AACtB,WAAO,kBAAkB,IAAI;AAC7B,UAAM,OAAO,aAAa,IAAI;AAC9B,QAAI,KAAK,GAAG,QAAQ,KAAK,IAAI,KAAK,MAAM;AACtC,YAAM,IAAI,MAAM,8BAA8B,OAAO;AAAA,IACvD;AACA,UAAM,OAAO,KAAK,MAAM,KAAK,GAAG,QAAQ,KAAK,IAAI,CAAC;AAClD,gBAAY,IAAI;AAChB,WAAO;AAAA,EACT;AACF;AAGA,IAAI,oBAAoB;AACxB,IAAI,4BAA4B,MAAM;AAAA,EACpC,cAAc;AACZ,SAAK,WAAW,CAAC;AAAA,EACnB;AAAA,EACA,OAAO,cAAc;AACnB,QAAI,0BAA0B,YAAY,MAAM;AAC9C,gCAA0B,WAAW,IAAI,0BAA0B;AAAA,IACrE;AACA,WAAO,0BAA0B;AAAA,EACnC;AAAA,EACA,OAAO,gBAAgB,QAAQ,SAAS;AACtC,WAAO,UAAU,MAAM,MAAM,uCAAuC;AACpE,QAAI,OAAO,SAAS,iBAAiB,GAAG;AACtC,eAAS,OAAO,MAAM,GAAG,OAAO,QAAQ,iBAAiB,CAAC;AAAA,IAC5D;AACA,WAAO,OAAO,SAAS,GAAG,MAAM,qCAAqC;AACrE,UAAM,WAAW,0BAA0B,YAAY;AACvD,WAAO,SAAS,SAAS,WAAW,MAAM,MAAM,2DAA2D,UAAU;AACrH,aAAS,SAAS,UAAU;AAAA,EAC9B;AAAA,EACA,OAAO,WAAW,QAAQ;AACxB,UAAM,UAAU,0BAA0B,YAAY,EAAE,SAAS;AACjE,QAAI,WAAW,MAAM;AACnB,YAAM,IAAI,MAAM,yCAAyC,SAAS;AAAA,IACpE;AACA,WAAO;AAAA,EACT;AAAA,EACA,OAAO,aAAa;AAClB,WAAO,OAAO,KAAK,0BAA0B,YAAY,EAAE,QAAQ;AAAA,EACrE;AACF;AACA,SAAS,SAAS,KAAK;AACrB,MAAI,IAAI,QAAQ,iBAAiB,MAAM,IAAI;AACzC,UAAM,IAAI,MAAM,6EAA6E,0BAA0B,WAAW,EAAE,KAAK,GAAG,GAAG;AAAA,EACjJ;AACA,SAAO;AAAA,IACL,QAAQ,IAAI,MAAM,iBAAiB,EAAE;AAAA,IACrC,MAAM,IAAI,MAAM,iBAAiB,EAAE;AAAA,EACrC;AACF;AACA,eAAe,mBAAmB,WAAW,SAAS,eAAe,OAAO;AAC1E,SAAO,cAAc,SAAS,MAAM,wCAAwC,YAAY;AACxF,QAAM,eAAe,iBAAiB,gBAAgB,SAAS;AAC/D,SAAO,aAAa,SAAS,GAAG,MAAM,kEAAkE,YAAY;AACpH,SAAO,aAAa,SAAS,GAAG,MAAM,yCAAyC,aAAa,wCAAwC,YAAY;AAChJ,QAAM,cAAc,aAAa;AACjC,QAAM,eAAe,iBAAiB,gBAAgB,OAAO;AAC7D,SAAO,aAAa,SAAS,GAAG,MAAM,uEAAuE,UAAU;AACvH,SAAO,aAAa,SAAS,GAAG,MAAM,yCAAyC,aAAa,6CAA6C,UAAU;AACnJ,QAAM,cAAc,aAAa;AACjC,QAAM,eAAe,SAAS,SAAS,EAAE;AACzC,QAAM,aAAa,SAAS,SAAS,EAAE;AACvC,QAAM,aAAa,iBAAiB,SAAS,SAAS,EAAE;AACxD,QAAM,iBAAiB,MAAM,YAAY,KAAK;AAC9C,MAAI,gBAAgB,YAAY;AAC9B,UAAM,0BAA0B,WAAW,YAAY,EAAE,YAAY,UAAU;AAAA,EACjF;AACA,QAAM,aAAa,MAAM,YAAY,KAAK,cAAc;AACxD,MAAI,gBAAgB,CAAC,YAAY;AAC/B,UAAM,0BAA0B,WAAW,YAAY,EAAE,YAAY,UAAU;AAAA,EACjF;AACA,SAAO,WAAW;AACpB;AACA,eAAe,aAAa;AAC1B,QAAM,UAAU,0BAA0B,WAAW;AACrD,QAAM,MAAM,CAAC;AACb,aAAW,UAAU,SAAS;AAC5B,UAAM,YAAY,MAAM,0BAA0B,WAAW,MAAM,EAAE,WAAW;AAChF,eAAW,QAAQ,WAAW;AAC5B,YAAM,MAAM,SAAS,oBAAoB;AACzC,UAAI,OAAO,UAAU;AAAA,IACvB;AAAA,EACF;AACA,SAAO;AACT;AACA,eAAe,YAAY,KAAK;AAC9B,QAAM,gBAAgB,SAAS,GAAG;AAClC,QAAM,UAAU,0BAA0B,WAAW,cAAc,MAAM;AACzE,SAAO,QAAQ,YAAY,cAAc,IAAI;AAC/C;AACA,eAAe,UAAU,WAAW,SAAS;AAC3C,QAAM,eAAe;AACrB,SAAO,mBAAmB,WAAW,SAAS,YAAY;AAC5D;AACA,eAAe,UAAU,WAAW,SAAS;AAC3C,QAAM,eAAe;AACrB,SAAO,mBAAmB,WAAW,SAAS,YAAY;AAC5D;AAGA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,MAAM,MAAML,QAAO;AACjB,WAAO,MAAM,MAAMA,MAAK;AAAA,EAC1B;AAAA,EACA,MAAM;AACJ,WAAO,YAAY,IAAI;AAAA,EACzB;AAAA,EACA,OAAO,MAAM,UAAU;AACrB,QAAI,aAAa,WAAW,aAAa,QAAQ;AAC/C,YAAM,IAAI,MAAM,kDAAkD,UAAU;AAAA,IAC9E;AACA,QAAI,KAAK,eAAe,MAAM;AAC5B,WAAK,cAAc,IAAI,YAAY;AAAA,IACrC;AACA,WAAO,KAAK,YAAY,OAAO,IAAI;AAAA,EACrC;AAAA,EACA,OAAO,OAAO,UAAU;AACtB,WAAO,IAAI,YAAY,QAAQ,EAAE,OAAO,KAAK;AAAA,EAC/C;AACF;AACA,IAAI,IAAI,EAAE,IAAI,YAAY,GAAG;AAC3B,MAAI,EAAE,YAAY,WAAW,IAAI,gBAAgB,CAAC;AAClD,MAAI;AACF,8BAA0B,gBAAgB,oBAAoB,YAAY,IAAI,2BAA2B,CAAC;AAAA,EAC5G,SAAS,KAAP;AAAA,EACF;AACA,MAAI;AACF,8BAA0B,gBAAgB,iBAAiB,YAAY,IAAI,wBAAwB,CAAC;AAAA,EACtG,SAAS,KAAP;AAAA,EACF;AACF;AAGA,IAAI,eAAe;AAAA,EACjB,aAAa,MAAM,gBAAgB;AACrC;AACA,IAAI;AACJ,IAAI,eAAe,MAAM;AAAA,EACvB,cAAc;AACZ,SAAK,OAAO,aAAa;AACzB,SAAK,cAAc,IAAI,KAAK,KAAK,YAAY;AAAA,EAC/C;AAAA,EACA,MAAM,MAAM,cAAc;AACxB,QAAI,IAAI,EAAE,OAAO,SAAS,MAAM;AAC9B,aAAO,IAAI,EAAE,OAAO,MAAM,MAAM,YAAY;AAAA,IAC9C;AACA,QAAI,eAAe,MAAM;AACvB,oBAAc,aAAa,YAAY;AAAA,IACzC;AACA,WAAO,YAAY,MAAM,YAAY;AAAA,EACvC;AAAA,EACA,MAAM;AACJ,UAAM,QAAQ,QAAQ,OAAO;AAC7B,WAAO,MAAM,KAAK,MAAM,MAAM,KAAK;AAAA,EACrC;AAAA,EACA,OAAO,MAAM,UAAU;AACrB,QAAI,aAAa,WAAW,aAAa,QAAQ;AAC/C,YAAM,IAAI,MAAM,sDAAsD,UAAU;AAAA,IAClF;AACA,WAAO,KAAK,YAAY,OAAO,IAAI;AAAA,EACrC;AAAA,EACA,OAAO,OAAO,UAAU;AACtB,QAAI,MAAM,WAAW,GAAG;AACtB,aAAO;AAAA,IACT;AACA,WAAO,IAAI,KAAK,KAAK,YAAY,QAAQ,EAAE,OAAO,KAAK;AAAA,EACzD;AACF;AACA,IAAI,IAAI,EAAE,IAAI,SAAS,KAAK,CAAC,IAAI,EAAE,IAAI,YAAY,GAAG;AACpD,MAAI,EAAE,YAAY,QAAQ,IAAI,aAAa,CAAC;AAC9C;AAGA,SAAS,OAAO,OAAO,QAAQ,WAAW,QAAQ;AAChD,UAAQ,SAAS;AACjB,qCAAmC,KAAK;AACxC,SAAO,IAAI,aAAa,OAAO,OAAO,MAAM;AAC9C;AAGA,SAAS,MAAM,GAAG,OAAO;AACvB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,MAAI,CAAC,aAAa,KAAK,GAAG;AACxB,UAAM,IAAI,MAAM,mCAAmC,OAAO;AAAA,EAC5D;AACA,MAAI,UAAU,YAAY,GAAG,UAAU,YAAY,UAAU,YAAY,GAAG,UAAU,UAAU;AAC9F,UAAM,IAAI,MAAM,uCAAuC;AAAA,EACzD;AACA,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM;AACtB,SAAO,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC7C;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS,mBAAmB;AAC/D,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,GAAG,UAAU,OAAO;AACjC,UAAQ,IAAI,EAAE,SAAS,OAAO,CAAC;AACjC;AAGA,gBAAgB;AAChB,IAAI,aAAa;AAAA,EACf;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,aAAa,UAAU;AAGvB,IAAI,aAAa,CAAC;AAClBP,UAAS,YAAY;AAAA,EACnB,cAAc,MAAM;AAAA,EACpB,oBAAoB,MAAM;AAAA,EAC1B,yBAAyB,MAAM;AAAA,EAC/B,WAAW,MAAM;AAAA,EACjB,eAAe,MAAM;AAAA,EACrB,eAAe,MAAM;AAAA,EACrB,YAAY,MAAM;AAAA,EAClB,gBAAgB,MAAM;AAAA,EACtB,iBAAiB,MAAM;AAAA,EACvB,0BAA0B,MAAM;AAAA,EAChC,8BAA8B,MAAM;AAAA,EACpC,iBAAiB,MAAM;AAAA,EACvB,MAAM,MAAM;AAAA,EACZ,cAAc,MAAM;AAAA,EACpB,YAAY,MAAM;AAAA,EAClB,aAAa,MAAM;AAAA,EACnB,WAAW,MAAM;AAAA,EACjB,oBAAoB,MAAM;AAAA,EAC1B,oBAAoB,MAAM;AAAA,EAC1B,aAAa,MAAM;AAAA,EACnB,sBAAsB,MAAM;AAAA,EAC5B,iBAAiB,MAAM;AAAA,EACvB,qBAAqB,MAAM;AAC7B,CAAC;AAGD,IAAI,2BAA2B;AAC/B,IAAI,8BAA8B;AAClC,IAAI,qCAAqC;AACzC,SAAS,MAAM,GAAG;AAChB,SAAO,IAAI,QAAQ,CAAC,YAAY,WAAW,OAAO,CAAC,EAAE,KAAK,CAAC;AAC7D;AACA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,gBAAgB;AAC1B,QAAI,CAAC,IAAI,EAAE,QAAQ,YAAY,GAAG;AAChC,YAAM,IAAI,MAAM,qFAAqF;AAAA,IACvG;AACA,QAAI,eAAe,WAAW,iBAAiB,UAAU,GAAG;AAC1D,uBAAiB,eAAe,MAAM,iBAAiB,WAAW,MAAM;AAAA,IAC1E;AACA,QAAI,kBAAkB,QAAQ,eAAe,WAAW,GAAG;AACzD,uBAAiB;AAAA,IACnB;AACA,SAAK,oBAAoB,iBAAiB;AAC1C,SAAK,qBAAqB,iBAAiB;AAAA,EAC7C;AAAA,EACA,MAAM,KAAK,gBAAgB;AACzB,QAAI,OAAO,aAAa,aAAa;AACnC,YAAM,IAAI,MAAM,yFAAyF;AAAA,IAC3G;AACA,UAAM,aAAa,OAAO,IAAI,gBAAgB,IAAI,KAAK,CAAC,eAAe,UAAU,GAAG,EAAE,MAAM,2BAA2B,CAAC,CAAC;AACzH,QAAI,eAAe,yBAAyB,aAAa;AACvD,YAAM,IAAI,MAAM,uFAAuF;AAAA,IACzG,OAAO;AACL,YAAM,kBAAkB,CAAC;AAAA,QACvB,OAAO,CAAC,OAAO,KAAK,kBAAkB;AAAA,QACtC,SAAS,eAAe;AAAA,MAC1B,CAAC;AACD,YAAM,YAAY,8BAA8B,gBAAgB,eAAe;AAC/E,YAAM,eAAe,OAAO,IAAI,gBAAgB,IAAI,KAAK,CAAC,KAAK,UAAU,SAAS,CAAC,GAAG,EAAE,MAAM,mBAAmB,CAAC,CAAC;AACnH,YAAM,aAAa,KAAK,mBAAmB,OAAO,SAAS,cAAc,GAAG,IAAI,KAAK;AACrF,iBAAW,WAAW,KAAK;AAC3B,iBAAW,OAAO;AAClB,YAAM,MAAM,MAAM,WAAW,cAAc,IAAI,WAAW,OAAO,CAAC,CAAC;AACnE,UAAI,eAAe,cAAc,MAAM;AACrC,cAAM,mBAAmB,KAAK,oBAAoB,OAAO,SAAS,cAAc,GAAG,IAAI,KAAK;AAC5F,yBAAiB,WAAW,KAAK;AACjC,yBAAiB,OAAO;AACxB,cAAM,MAAM,MAAM,iBAAiB,cAAc,IAAI,WAAW,OAAO,CAAC,CAAC;AAAA,MAC3E;AACA,aAAO,EAAE,oBAAoB,6BAA6B,cAAc,EAAE;AAAA,IAC5E;AAAA,EACF;AACF;AACA,iBAAiB,aAAa;AAC9B,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,OAAO;AACjB,QAAI,SAAS,QAAQ,MAAM,SAAS,GAAG;AACrC,YAAM,IAAI,MAAM,wEAAwE,OAAO;AAAA,IACjG;AACA,SAAK,WAAW,MAAM;AACtB,SAAK,eAAe,MAAM,MAAM,CAAC;AAAA,EACnC;AAAA,EACA,MAAM,OAAO;AACX,WAAO,IAAI,QAAQ,CAAC,SAAS,WAAW;AACtC,YAAM,aAAa,IAAI,WAAW;AAClC,iBAAW,SAAS,CAAC,UAAU;AAC7B,cAAM,YAAY,KAAK,MAAM,MAAM,OAAO,MAAM;AAChD,cAAM,gBAAgB,UAAU;AAChC,YAAI,iBAAiB,MAAM;AACzB,iBAAO,IAAI,MAAM,4CAA4C,KAAK,SAAS,MAAM,CAAC;AAClF;AAAA,QACF;AACA,cAAM,kBAAkB,UAAU;AAClC,YAAI,mBAAmB,MAAM;AAC3B,iBAAO,IAAI,MAAM,6CAA6C,KAAK,SAAS,MAAM,CAAC;AACnF;AAAA,QACF;AACA,YAAI,KAAK,aAAa,WAAW,GAAG;AAClC,kBAAQ,EAAE,cAAc,CAAC;AACzB;AAAA,QACF;AACA,cAAM,wBAAwB,yBAAyB,WAAW,CAAC,qBAAqB,KAAK,YAAY,gBAAgB,CAAC;AAC1H,gBAAQ,qBAAqB;AAAA,MAC/B;AACA,iBAAW,UAAU,CAAC,UAAU,OAAO,sEAAsE,KAAK,SAAS,2EAA2E;AACtM,iBAAW,WAAW,KAAK,QAAQ;AAAA,IACrC,CAAC;AAAA,EACH;AAAA,EACA,YAAY,iBAAiB;AAC3B,UAAM,cAAc,CAAC;AACrB,UAAM,QAAQ,CAAC;AACf,eAAW,SAAS,iBAAiB;AACnC,kBAAY,KAAK,GAAG,MAAM,OAAO;AACjC,YAAM,KAAK,GAAG,MAAM,KAAK;AAAA,IAC3B;AACA,UAAM,aAAa,KAAK,4BAA4B,eAAe;AACnE,UAAM,WAAW,MAAM,IAAI,CAAC,SAAS,KAAK,gBAAgB,MAAM,WAAW,KAAK,CAAC;AACjF,WAAO,QAAQ,IAAI,QAAQ,EAAE,KAAK,CAAC,YAAY,CAAC,aAAa,wBAAwB,OAAO,CAAC,CAAC;AAAA,EAChG;AAAA,EACA,gBAAgB,MAAM,MAAM;AAC1B,WAAO,IAAI,QAAQ,CAAC,SAAS,WAAW;AACtC,YAAM,mBAAmB,IAAI,WAAW;AACxC,uBAAiB,SAAS,CAAC,UAAU;AACnC,cAAM,aAAa,MAAM,OAAO;AAChC,gBAAQ,UAAU;AAAA,MACpB;AACA,uBAAiB,UAAU,CAAC,UAAU,OAAO,6CAA6C,QAAQ;AAClG,uBAAiB,kBAAkB,IAAI;AAAA,IACzC,CAAC;AAAA,EACH;AAAA,EACA,4BAA4B,UAAU;AACpC,UAAM,YAAY,CAAC;AACnB,UAAM,YAAY,KAAK,aAAa,IAAI,CAAC,SAAS,SAAS,KAAK,IAAI,CAAC;AACrE,UAAM,aAAa,CAAC;AACpB,eAAW,SAAS,UAAU;AAC5B,YAAM,MAAM,QAAQ,CAAC,SAAS;AAC5B,cAAM,eAAe,SAAS,IAAI;AAClC,YAAI,UAAU,QAAQ,YAAY,MAAM,IAAI;AAC1C,gBAAM,IAAI,MAAM,uDAAuD,eAAe;AAAA,QACxF;AACA,kBAAU,KAAK,YAAY;AAC3B,YAAI,UAAU,QAAQ,YAAY,MAAM,IAAI;AAC1C,gBAAM,IAAI,MAAM,8BAA8B,gCAAgC;AAAA,QAChF,OAAO;AACL,qBAAW,QAAQ,KAAK,aAAa,UAAU,QAAQ,YAAY;AAAA,QACrE;AAAA,MACF,CAAC;AAAA,IACH;AACA,QAAI,UAAU,WAAW,KAAK,aAAa,QAAQ;AACjD,YAAM,IAAI,MAAM,wDAAwD,UAAU,oDAAoD,KAAK,aAAa,UAAU;AAAA,IACpK;AACA,WAAO;AAAA,EACT;AACF;AACA,IAAI,yBAAyB,CAAC,QAAQ;AACpC,MAAI,CAAC,IAAI,EAAE,QAAQ,YAAY,GAAG;AAChC,WAAO;AAAA,EACT,OAAO;AACL,QAAI,CAAC,MAAM,QAAQ,GAAG,KAAK,IAAI,WAAW,iBAAiB,UAAU,GAAG;AACtE,aAAO,iBAAiB,IAAI,MAAM,iBAAiB,WAAW,MAAM,CAAC;AAAA,IACvE,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AACF;AACA,iBAAiB,mBAAmB,sBAAsB;AAC1D,SAAS,iBAAiB,iBAAiB,SAAS;AAClD,SAAO,IAAI,iBAAiB,cAAc;AAC5C;AACA,SAAS,aAAa,OAAO;AAC3B,SAAO,IAAI,aAAa,KAAK;AAC/B;AAGA,SAAS,wBAAwB,UAAU,YAAY,eAAe,aAAa;AACjF,gBAAc,QAAQ;AACtB,kBAAgB,iBAAiB,OAAO,IAAI;AAC5C,gBAAc,eAAe,OAAO,IAAI;AACxC,gBAAc,eAAe,WAAW;AACxC,MAAI,kBAAkB;AACtB,QAAM,kBAAkB,CAAC,YAAY;AACnC,YAAQ,KAAK,CAAC,UAAU;AACtB,YAAM,WAAW,gBAAgB,EAAE,kBAAkB,SAAS,UAAU,cAAc;AACtF,iBAAW,QAAQ;AACnB,aAAO;AAAA,IACT,CAAC;AACD,WAAO;AAAA,EACT;AACA,WAAS,cAAc,WAAW;AAChC,WAAO,aAAa,QAAQ,MAAM,QAAQ,SAAS,KAAK,UAAU,SAAS,GAAG,MAAM,qCAAqC;AAAA,EAC3H;AACA,WAAS,cAAc,gBAAgB,cAAc;AACnD,WAAO,kBAAkB,KAAK,kBAAkB,GAAG,MAAM,oEAAoE,gBAAgB;AAC7I,WAAO,gBAAgB,KAAK,gBAAgB,GAAG,MAAM,kEAAkE,cAAc;AACrI,WAAO,gBAAgB,gBAAgB,MAAM,yEAAyE,kCAAkC,cAAc;AAAA,EACxK;AACA,SAAO,QAAQ,IAAI,SAAS,IAAI,eAAe,CAAC;AAClD;AAGA,eAAe,yBAAyB,WAAW,aAAa;AAC9D,MAAI,eAAe,MAAM;AACvB,kBAAc,CAAC;AAAA,EACjB;AACA,QAAM,YAAY,YAAY,aAAa,OAAO,IAAI,EAAE,SAAS,QAAQ,YAAY;AACrF,QAAM,WAAW,UAAU,IAAI,CAAC,aAAa,UAAU,UAAU,YAAY,aAAa,EAAE,UAAU,KAAK,CAAC,CAAC;AAC7G,QAAM,qBAAqB;AAC3B,QAAM,mBAAmB;AACzB,QAAM,YAAY,YAAY,cAAc,OAAO,MAAM,QAAQ,IAAI,QAAQ,IAAI,MAAM,wBAAwB,UAAU,YAAY,YAAY,oBAAoB,gBAAgB;AACrL,QAAM,iBAAiB,UAAU,IAAI,CAAC,aAAa,SAAS,YAAY,CAAC;AACzE,QAAM,sBAAsB;AAC5B,QAAM,oBAAoB;AAC1B,QAAM,UAAU,YAAY,cAAc,OAAO,MAAM,QAAQ,IAAI,cAAc,IAAI,MAAM,wBAAwB,gBAAgB,YAAY,YAAY,qBAAqB,iBAAiB;AACjM,SAAO;AACT;AACA,eAAe,YAAY,UAAU,iBAAiB,IAAI,aAAa,aAAa;AAClF,QAAM,eAAe,CAAC,cAAc,yBAAyB,WAAW,EAAE,YAAY,CAAC;AACvF,QAAM,eAAe,qBAAqB,YAAY;AACtD,SAAO,aAAa,UAAU,gBAAgB,WAAW;AAC3D;AACA,SAAS,qBAAqB,sBAAsB;AAClD,SAAO,OAAO,UAAU,iBAAiB,IAAI,gBAAgB;AAC3D,UAAM,yBAAyB,SAAS,IAAI,MAAM,KAAK;AACvD,UAAM,sBAAsB,CAAC;AAC7B,UAAM,eAAe,eAAe,OAAO,YAAY,IAAI,MAAM,KAAK,IAAI,CAAC;AAC3E,UAAM,yBAAyB,CAAC;AAChC,aAAS,QAAQ,CAAC,qBAAqB,eAAe;AACpD,UAAI,cAAc;AAClB,0BAAoB,QAAQ,QAAQ,CAAC,iBAAiB;AACpD,cAAM,WAAW,kBAAkB,eAAe,aAAa,aAAa,QAAQ,aAAa;AACjG,cAAM,eAAe,qBAAqB,YAAY,cAAc,aAAa,KAAK;AACtF,cAAM,8BAA8B,MAAM;AACxC,iCAAuB,cAAc;AACrC,cAAI,oBAAoB,eAAe,MAAM;AAC3C,gCAAoB,cAAc,CAAC;AAAA,UACrC;AACA,8BAAoB,YAAY,KAAK;AAAA,YACnC,eAAe;AAAA,YACf;AAAA,YACA,WAAW;AAAA,UACb,CAAC;AAAA,QACH;AACA,YAAI,eAAe,MAAM;AACvB,sBAAY,QAAQ,CAAC,YAAY,gBAAgB;AAC/C,gBAAI,eAAe,aAAa,MAAM;AACpC,0CAA4B;AAC5B,2BAAa,eAAe;AAAA,YAC9B;AAAA,UACF,CAAC;AAAA,QACH,OAAO;AACL,sCAA4B;AAAA,QAC9B;AACA,+BAAuB,KAAK,aAAa,IAAI;AAC7C,uBAAe;AAAA,MACjB,CAAC;AAAA,IACH,CAAC;AACD,QAAI,CAAC,aAAa,MAAM,CAAC,UAAU,KAAK,GAAG;AACzC,YAAM,kBAAkB,YAAY,OAAO,CAAC,GAAG,OAAO,CAAC,aAAa,GAAG;AACvE,YAAM,IAAI,MAAM,kDAAkD,gBAAgB,KAAK,IAAI;AAAA,wCACzD,uBAAuB,KAAK,IAAI,IAAI;AAAA,IACxE;AACA,UAAM,sBAAsB,uBAAuB,OAAO,CAAC,aAAa,aAAa,OAAO;AAC1F,UAAI,aAAa;AACf,oBAAY,KAAK,EAAE;AAAA,MACrB;AACA,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AACL,UAAM,YAAY,CAAC;AACnB,wBAAoB,QAAQ,CAAC,OAAO;AAClC,eAAS,IAAI,MAAM,QAAQ,CAAC,aAAa;AACvC,cAAM,WAAW,kBAAkB,CAAC,eAAe,SAAS,GAAG,IAAI,MAAM,MAAM;AAC/E,kBAAU,KAAK,QAAQ;AAAA,MACzB,CAAC;AAAA,IACH,CAAC;AACD,UAAM,UAAU,MAAM,qBAAqB,SAAS;AACpD,UAAM,mBAAmB,CAAC;AAC1B,QAAI,oBAAoB;AACxB,wBAAoB,QAAQ,CAAC,OAAO;AAClC,YAAM,aAAa,SAAS,IAAI,MAAM;AACtC,UAAI,aAAa;AACjB,eAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,sBAAc,QAAQ,oBAAoB,IAAI;AAAA,MAChD;AACA,YAAM,cAAc,IAAI,YAAY,UAAU;AAC9C,YAAM,kBAAkB,IAAI,WAAW,WAAW;AAClD,UAAI,oBAAoB;AACxB,eAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,cAAM,UAAU,IAAI,WAAW,QAAQ,oBAAoB,GAAG;AAC9D,wBAAgB,IAAI,SAAS,iBAAiB;AAC9C,6BAAqB,QAAQ;AAAA,MAC/B;AACA,YAAM,iBAAiB,oBAAoB;AAC3C,qBAAe,QAAQ,CAAC,iBAAiB;AACvC,cAAM,aAAa,YAAY,MAAM,aAAa,aAAa,aAAa,cAAc,aAAa,SAAS;AAChH,cAAM,kBAAkB,cAAc,YAAY,CAAC,aAAa,aAAa,CAAC;AAC9E,mBAAW,QAAQ,iBAAiB;AAClC,2BAAiB,QAAQ,gBAAgB;AAAA,QAC3C;AAAA,MACF,CAAC;AACD,2BAAqB;AAAA,IACvB,CAAC;AACD,WAAO;AAAA,EACT;AACF;AAGA,IAAI,yBAAyB;AAC7B,IAAI,YAAY;AAChB,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,MAAM,aAAa;AAC7B,SAAK,iBAAiB;AACtB,QAAI,eAAe,MAAM;AACvB,oBAAc,CAAC;AAAA,IACjB;AACA,SAAK,mBAAmB,YAAY;AACpC,SAAK,aAAa,YAAY;AAC9B,SAAK,qBAAqB,YAAY;AACtC,QAAI,YAAY,aAAa,MAAM;AACjC,aAAO,OAAO,YAAY,cAAc,YAAY,MAAM,6HAA6H;AACvL,WAAK,QAAQ,YAAY;AAAA,IAC3B,OAAO;AACL,WAAK,QAAQ,IAAI,EAAE,SAAS;AAAA,IAC9B;AACA,WAAO,QAAQ,QAAQ,KAAK,SAAS,GAAG,MAAM,yDAAyD;AACvG,QAAI,MAAM,QAAQ,IAAI,GAAG;AACvB,aAAO,KAAK,WAAW,GAAG,MAAM,iEAAiE,KAAK,UAAU;AAAA,IAClH;AACA,SAAK,OAAO;AACZ,QAAI,YAAY,eAAe,QAAQ,YAAY,YAAY,QAAQ,MAAM;AAC3E,YAAM,IAAI,MAAM,oEAAoE;AAAA,IACtF;AACA,SAAK,cAAc,YAAY,eAAe,CAAC;AAAA,EACjD;AAAA,EACA,MAAM,KAAK,gBAAgB;AACzB,QAAI,eAAe,yBAAyB,aAAa;AACvD,YAAM,IAAI,MAAM,yFAAyF;AAAA,IAC3G;AACA,UAAMO,SAAQ,OAAO,OAAO,EAAE,QAAQ,KAAK,eAAe,GAAG,KAAK,WAAW;AAC7E,IAAAA,OAAM,OAAO,IAAI,SAAS;AAC1B,UAAM,kBAAkB,CAAC;AAAA,MACvB,OAAO,CAAC,qBAAqB;AAAA,MAC7B,SAAS,eAAe;AAAA,IAC1B,CAAC;AACD,UAAM,iCAAiC,8BAA8B,gBAAgB,eAAe;AACpG,IAAAA,OAAM,KAAK,OAAO,cAAc,IAAI,KAAK,CAAC,KAAK,UAAU,8BAA8B,CAAC,GAAG,EAAE,MAAM,UAAU,CAAC,GAAG,YAAY;AAC7H,QAAI,eAAe,cAAc,MAAM;AACrC,MAAAA,OAAM,KAAK,OAAO,qBAAqB,IAAI,KAAK,CAAC,eAAe,UAAU,GAAG,EAAE,MAAM,uBAAuB,CAAC,GAAG,mBAAmB;AAAA,IACrI;AACA,UAAM,WAAW,MAAM,KAAK,MAAM,KAAK,MAAMA,MAAK;AAClD,QAAI,SAAS,IAAI;AACf,aAAO;AAAA,QACL,oBAAoB,6BAA6B,cAAc;AAAA,QAC/D,WAAW,CAAC,QAAQ;AAAA,MACtB;AAAA,IACF,OAAO;AACL,YAAM,IAAI,MAAM,gEAAgE,SAAS,SAAS;AAAA,IACpG;AAAA,EACF;AAAA,EACA,MAAM,OAAO;AACX,UAAM,qBAAqB,MAAM,KAAK,MAAM,KAAK,MAAM,KAAK,WAAW;AACvE,QAAI,CAAC,mBAAmB,IAAI;AAC1B,YAAM,IAAI,MAAM,cAAc,KAAK,gCAAgC,mBAAmB,+EAA+E;AAAA,IACvK;AACA,QAAI;AACJ,QAAI;AACF,kBAAY,MAAM,mBAAmB,KAAK;AAAA,IAC5C,SAAS,IAAP;AACA,UAAI,UAAU,+CAA+C,KAAK;AAClE,UAAI,KAAK,KAAK,SAAS,KAAK,GAAG;AAC7B,mBAAW;AAAA,MACb,OAAO;AACL,mBAAW;AAAA,MACb;AACA,YAAM,IAAI,MAAM,OAAO;AAAA,IACzB;AACA,UAAM,gBAAgB,UAAU;AAChC,UAAM,kBAAkB,UAAU;AAClC,QAAI,iBAAiB,QAAQ,mBAAmB,MAAM;AACpD,YAAM,IAAI,MAAM,2BAA2B,KAAK,+DAA+D;AAAA,IACjH;AACA,WAAO,yBAAyB,WAAW,CAAC,qBAAqB,KAAK,YAAY,gBAAgB,CAAC;AAAA,EACrG;AAAA,EACA,MAAM,YAAY,iBAAiB;AACjC,UAAM,aAAa,MAAM,QAAQ,KAAK,IAAI,IAAI,KAAK,KAAK,KAAK,KAAK;AAClE,UAAM,CAAC,QAAQ,MAAM,IAAI,SAAS,UAAU;AAC5C,UAAM,aAAa,KAAK,oBAAoB;AAC5C,UAAM,cAAc,CAAC;AACrB,eAAW,SAAS,iBAAiB;AACnC,kBAAY,KAAK,GAAG,MAAM,OAAO;AAAA,IACnC;AACA,UAAM,YAAY,CAAC;AACnB,UAAM,cAAc,CAAC;AACrB,eAAW,gBAAgB,iBAAiB;AAC1C,iBAAW,QAAQ,aAAa,OAAO;AACrC,YAAI,KAAK,sBAAsB,MAAM;AACnC,sBAAY,KAAK,KAAK,mBAAmB,IAAI,CAAC;AAAA,QAChD,OAAO;AACL,oBAAU,KAAK,aAAa,OAAO,MAAM;AAAA,QAC3C;AAAA,MACF;AAAA,IACF;AACA,QAAI,KAAK,oBAAoB;AAC3B,gBAAU,KAAK,GAAG,MAAM,QAAQ,IAAI,WAAW,CAAC;AAAA,IAClD;AACA,UAAM,UAAU,MAAM,yBAAyB,WAAW;AAAA,MACxD,aAAa,KAAK;AAAA,MAClB,WAAW,KAAK;AAAA,MAChB,YAAY,KAAK;AAAA,IACnB,CAAC;AACD,WAAO,CAAC,aAAa,wBAAwB,OAAO,CAAC;AAAA,EACvD;AACF;AACA,YAAY,mBAAmB;AAC/B,SAAS,SAAS,KAAK;AACrB,QAAM,YAAY,IAAI,YAAY,GAAG;AACrC,QAAM,kBAAkB,IAAI,YAAY,GAAG;AAC3C,QAAM,SAAS,IAAI,UAAU,GAAG,SAAS;AACzC,QAAM,SAAS,kBAAkB,YAAY,IAAI,UAAU,eAAe,IAAI;AAC9E,SAAO,CAAC,SAAS,KAAK,MAAM;AAC9B;AACA,SAAS,aAAa,KAAK;AACzB,SAAO,IAAI,MAAM,YAAY,gBAAgB,KAAK;AACpD;AACA,IAAI,aAAa,CAAC,KAAK,gBAAgB;AACrC,MAAI,OAAO,UAAU,gBAAgB,eAAe,QAAQ,YAAY,aAAa,OAAO;AAC1F,WAAO;AAAA,EACT,OAAO;AACL,QAAI,SAAS;AACb,QAAI,MAAM,QAAQ,GAAG,GAAG;AACtB,eAAS,IAAI,MAAM,CAAC,YAAY,aAAa,OAAO,CAAC;AAAA,IACvD,OAAO;AACL,eAAS,aAAa,GAAG;AAAA,IAC3B;AACA,QAAI,QAAQ;AACV,aAAO,KAAK,KAAK,WAAW;AAAA,IAC9B;AAAA,EACF;AACA,SAAO;AACT;AACA,iBAAiB,mBAAmB,UAAU;AAC9C,iBAAiB,mBAAmB,UAAU;AAC9C,SAAS,KAAK,MAAM,aAAa;AAC/B,SAAO,IAAI,YAAY,MAAM,WAAW;AAC1C;AACA,SAAS,mBAAmB,MAAM,aAAa;AAC7C,SAAO,KAAK,MAAM,WAAW;AAC/B;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,gBAAgB;AAC1B,SAAK,iBAAiB;AAAA,EACxB;AAAA,EACA,OAAO;AACL,WAAO,KAAK;AAAA,EACd;AACF;AACA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,aAAa;AACvB,SAAK,cAAc;AAAA,EACrB;AAAA,EACA,KAAK,gBAAgB;AACnB,WAAO,KAAK,YAAY,cAAc;AAAA,EACxC;AACF;AACA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,SAAS;AACnB,QAAI,QAAQ,MAAM;AAChB,WAAK,OAAO,MAAM,QAAQ,QAAQ,QAAQ,KAAK,CAAC;AAAA,IAClD;AACA,QAAI,QAAQ,MAAM;AAChB,WAAK,OAAO,CAAC,mBAAmB,QAAQ,QAAQ,QAAQ,KAAK,cAAc,CAAC;AAAA,IAC9E;AAAA,EACF;AACF;AACA,SAAS,WAAW,gBAAgB,aAAa,YAAY,gBAAgB;AAC3E,QAAM,OAAO;AACb,SAAO,IAAI,iBAAiB,eAAe,GAAG,IAAI,CAAC;AACrD;AACA,SAAS,eAAe,gBAAgB,aAAa,YAAY,gBAAgB;AAC/E,MAAI,UAAU,WAAW,GAAG;AAC1B,UAAM,mBAAmB,eAAe,iBAAiB,QAAQ,eAAe,eAAe;AAC/F,QAAI,kBAAkB;AACpB,aAAO,IAAI,kBAAkB,cAAc;AAAA,IAC7C,OAAO;AACL,cAAQ,KAAK,uNAAuN;AACpO,aAAO,IAAI,kBAAkB,EAAE,eAAe,eAAe,CAAC;AAAA,IAChE;AAAA,EACF,OAAO;AACL,YAAQ,KAAK,uNAAuN;AACpO,WAAO,IAAI,kBAAkB;AAAA,MAC3B,eAAe;AAAA,MACf;AAAA,MACA;AAAA,MACA;AAAA,IACF,CAAC;AAAA,EACH;AACF;AACA,SAAS,gBAAgB,aAAa;AACpC,SAAO,IAAI,iBAAiB,WAAW;AACzC;AACA,SAAS,oBAAoB,aAAa;AACxC,SAAO,IAAI,iBAAiB,WAAW;AACzC;AAGA,IAAI,eAAe,CAAC;AACpBP,UAAS,cAAc;AAAA,EACrB,iBAAiB,MAAM;AACzB,CAAC;AAGD,SAAS,QAAQ,GAAG,GAAG,aAAa,OAAO,aAAa,OAAO;AAC7D,MAAI,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AACzC,MAAI,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AACzC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,QAAM,QAAQ,EAAE,YAAY,WAAW;AACvC,SAAO,OAAO,UAAU,aAAa,QAAQ,KAAK;AACpD;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,QAAQ,SAAS,OAAO,UAAU,GAAG,WAAW,GAAG;AAC1D,MAAI,QAAQ,GAAG;AACb,UAAM,IAAI,MAAM,iDAAiD,OAAO;AAAA,EAC1E;AACA,QAAM,WAAW,gBAAgB,SAAS,WAAW,UAAU,OAAO;AACtE,QAAM,SAAS,EAAE,SAAS,SAAS;AACnC,QAAM,QAAQ,EAAE,OAAO,SAAS,SAAS;AACzC,SAAO,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAC/C;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,iBAAiB;AACxB,MAAI,EAAE,IAAI,QAAQ,IAAI;AACxB;AACA,SAAS,kBAAkB;AACzB,MAAI,EAAE,IAAI,SAAS,IAAI;AACzB;AACA,SAAS,6BAA6B;AACpC,MAAI,EAAE,IAAI,gCAAgC,KAAK;AAC/C,UAAQ,KAAK,wDAAwD;AACvE;AACA,SAAS,gBAAgB,KAAK;AAC5B,MAAI,IAAI,EAAE,QAAQ,8BAA8B,GAAG;AACjD,YAAQ,KAAK,MAAM,6EAA6E;AAAA,EAClG;AACF;AACA,wBAAwB,eAAe;AACvC,SAAS,mBAAmB;AAC1B,SAAO,iBAAiB;AAC1B;AACA,SAAS,SAAS;AAChB,SAAO;AACT;AACA,SAAS,SAAS;AAChB,SAAO,OAAO,OAAO;AACvB;AACA,SAAS,QAAQ,GAAG;AAClB,SAAO,OAAO,QAAQ,CAAC;AACzB;AACA,SAAS,KAAK,UAAU,IAAI;AAC1B,SAAO,OAAO,KAAK,UAAU,EAAE;AACjC;AACA,SAAS,QAAQ,WAAW;AAC1B,QAAM,UAAU,sBAAsB,SAAS;AAC/C,UAAQ,QAAQ,CAAC,YAAY,QAAQ,QAAQ,CAAC;AAChD;AACA,SAAS,KAAK,QAAQ;AACpB,SAAO,OAAO,KAAK,MAAM;AAC3B;AACA,SAAS,KAAK,GAAG;AACf,SAAO,OAAO,KAAK,CAAC;AACtB;AACA,SAAS,WAAW,aAAa;AAC/B,SAAO,OAAO,WAAW,WAAW;AACtC;AACA,SAAS,QAAQ;AACf,SAAO,OAAO,MAAM;AACtB;AACA,SAAS,aAAa;AACpB,SAAO,OAAO;AAChB;AACA,SAAS,cAAc,MAAM;AAC3B,SAAO,cAAc,IAAI;AAC3B;AACA,SAAS,YAAY,MAAM;AACzB,SAAO,OAAO,YAAY,IAAI;AAChC;AACA,SAAS,mBAAmB,MAAM;AAChC,SAAO,OAAO,mBAAmB,IAAI;AACvC;AACA,SAAS,gBAAgB,MAAM,SAAS,WAAW,GAAG;AACpD,SAAO,OAAO,gBAAgB,MAAM,SAAS,QAAQ;AACvD;AACA,SAAS,UAAU;AACjB,SAAO,OAAO;AAChB;AACA,SAAS,YAAY,cAAc,UAAU;AAC3C,MAAI,EAAE,YAAY,cAAc,QAAQ;AAC1C;AAGA,SAAS,MAAM,QAAQ;AACrB,QAAM,SAAS,gBAAgB,QAAQ,SAAS,MAAM;AACtD,QAAM,SAAS,EAAE,OAAO,OAAO;AAC/B,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACxC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,MAAM,QAAQ;AACrB,QAAM,SAAS,gBAAgB,QAAQ,SAAS,MAAM;AACtD,QAAM,SAAS,EAAE,OAAO,OAAO;AAC/B,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,WAAW,GAAG,MAAM,WAAW;AACtC,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,MAAI,QAAQ,MAAM;AAChB,WAAO,GAAG,MAAM,IAAI,CAAC,IAAI,OAAO,EAAE,EAAE,QAAQ;AAAA,EAC9C;AACA,SAAO,GAAG,SAAS,KAAK,QAAQ,MAAM,qCAAqC,GAAG,kCAAkC,OAAO;AACvH,OAAK,QAAQ,CAAC,SAAS;AACrB,WAAO,QAAQ,KAAK,OAAO,GAAG,MAAM,MAAM,+CAA+C,GAAG,OAAO,aAAa,MAAM;AAAA,EACxH,CAAC;AACD,MAAI,GAAG,QAAQ,GAAG;AAChB,WAAO,GAAG,MAAM;AAAA,EAClB;AACA,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,KAAK;AACrB,MAAI,GAAG,UAAU,aAAa;AAC5B,WAAO,KAAK,MAAM;AAChB,UAAI,QAAQ,KAAK,EAAE;AACnB,UAAI,QAAQ,KAAK,EAAE;AACnB,cAAQ,OAAO,UAAU,WAAW,EAAE,GAAG,MAAM,GAAG,KAAK;AACvD,cAAQ,OAAO,UAAU,WAAW,EAAE,GAAG,MAAM,GAAG,KAAK;AACvD,UAAI,WAAW;AACb,gBAAQ,IAAI,KAAK;AAAA,MACnB;AACA,aAAO,QAAQ,OAAO,KAAK;AAAA,IAC7B,CAAC;AAAA,EACH;AACA,SAAO,OAAO,UAAU,WAAW,QAAQ,KAAK;AAClD;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,iBAAiBsB,SAAQ,aAAa,YAAY;AACzD,QAAM,UAAU,gBAAgBA,SAAQ,UAAU,iBAAiB;AACnE,QAAM,eAAe,gBAAgB,aAAa,eAAe,iBAAiB;AAClF,SAAO,cAAc,QAAQ,aAAa,KAAK,OAAO,UAAU,UAAU,GAAG,MAAM,+DAA+D,YAAY;AAC9J,SAAO,QAAQ,SAAS,GAAG,MAAM,gDAAgD,QAAQ,MAAM;AAC/F,SAAO,aAAa,SAAS,GAAG,MAAM,qDAAqD,aAAa,MAAM;AAC9G,SAAO,QAAQ,MAAM,OAAO,aAAa,MAAM,IAAI,MAAM,uCAAuC,QAAQ,MAAM,UAAU,aAAa,MAAM,qEAAqE;AAChN,SAAO,aAAa,KAAK,OAAO,UAAU,UAAU,GAAG,MAAM,4DAA4D,YAAY;AACrI,QAAM,eAAe,OAAO,KAAK,SAAS,OAAO,GAAG,UAAU;AAC9D,QAAM,oBAAoB,OAAO,KAAK,cAAc,OAAO,GAAG,UAAU;AACxE,QAAM,gBAAgB,UAAU,YAAY;AAC5C,QAAM,UAAU,OAAO,eAAe,iBAAiB;AACvD,SAAO,KAAK,SAAS,OAAO;AAC9B;AACA,IAAI,kBAAkB,GAAG,EAAE,iBAAiB,CAAC;AAG7C,IAAI,yBAAyB,CAAC;AAC9BtB,UAAS,wBAAwB;AAAA,EAC/B,4BAA4B,MAAM;AAAA,EAClC,kBAAkB,MAAM;AAAA,EACxB,kBAAkB,MAAM;AAC1B,CAAC;AACD,SAAS,iBAAiB,SAAS,UAAU;AAC3C,QAAM,SAAS,QAAQ;AACvB,QAAM,OAAO,CAAC;AACd,WAAS,KAAK,GAAG,KAAK,QAAQ,MAAM;AAClC,UAAM,MAAM,SAAS,IAAI;AACzB,UAAM,IAAI,QAAQ,QAAQ;AAC1B,UAAM,IAAI,SAAS,SAAS,SAAS,IAAI,OAAO;AAChD,QAAI,IAAI,KAAK,MAAM,GAAG;AACpB,WAAK,QAAQ,GAAG;AAAA,IAClB;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,SAAS,UAAU;AAC3C,QAAM,SAAS,CAAC;AAChB,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,UAAM,QAAQ,QAAQ,QAAQ,SAAS,KAAK;AAC5C,UAAM,UAAU,SAAS,SAAS,KAAK;AACvC,UAAM,SAAS,SAAS;AACxB,QAAI,SAAS,QAAQ,UAAU,KAAK,SAAS,GAAG;AAC9C,aAAO,QAAQ,OAAO;AAAA,IACxB;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,2BAA2B,QAAQ,QAAQ;AAClD,QAAM,SAAS,CAAC;AAChB,QAAM,KAAK,KAAK,IAAI,OAAO,QAAQ,OAAO,MAAM;AAChD,WAAS,KAAK,GAAG,KAAK,IAAI,MAAM;AAC9B,QAAI,IAAI,OAAO,OAAO,SAAS,KAAK;AACpC,QAAI,KAAK,MAAM;AACb,UAAI;AAAA,IACN;AACA,QAAI,IAAI,OAAO,OAAO,SAAS,KAAK;AACpC,QAAI,KAAK,MAAM;AACb,UAAI;AAAA,IACN;AACA,QAAI,MAAM,GAAG;AACX,aAAO,QAAQ,CAAC;AAAA,IAClB,WAAW,MAAM,GAAG;AAClB,aAAO,QAAQ,CAAC;AAAA,IAClB,WAAW,MAAM,GAAG;AAClB,YAAM,SAAS,wDAAwD,cAAc;AACrF,YAAM,MAAM,MAAM;AAAA,IACpB,OAAO;AACL,aAAO,QAAQ,CAAC;AAAA,IAClB;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,kBAAkB,CAAC;AACvBA,UAAS,iBAAiB;AAAA,EACxB,YAAY,MAAM;AAAA,EAClB,iBAAiB,MAAM;AAAA,EACvB,UAAU,MAAM;AAClB,CAAC;AAGD,SAAS,SAAS,QAAQ,OAAO,OAAO;AACtC,gBAAc,MAAM;AACpB,MAAI,SAAS,QAAQ,MAAM,WAAW,GAAG;AACvC,UAAM,IAAI,MAAM,iDAAiD;AAAA,EACnE;AACA,QAAM,gBAAgB,WAAW,QAAQ,KAAK;AAC9C,MAAI,cAAc,WAAW,KAAK,cAAc,WAAW,GAAG;AAC5D,UAAM,IAAI,MAAM,kEAAkE;AAAA,EACpF;AACA,MAAI,cAAc,WAAW,KAAK,SAAS,MAAM;AAC/C,UAAM,IAAI,MAAM,yEAAyE;AAAA,EAC3F;AACA,SAAO,WAAW,QAAQ,OAAO,eAAe,KAAK;AACvD;AAGA,IAAI;AACJ,SAAS,YAAY,QAAQ,cAAc,GAAG;AAC5C,MAAI,cAAc,GAAG;AACnB,UAAM,IAAI,MAAM,gEAAgE;AAAA,EAClF;AACA,MAAI,UAAU,MAAM;AAClB,UAAM,IAAI,MAAM,0DAA0D;AAAA,EAC5E;AACA,MAAI,eAAe;AACnB,MAAI,cAAc;AAClB,MAAI,UAAU;AACd,MAAI,UAAU;AACd,MAAI,eAAe;AACnB,MAAI,gBAAgB;AACpB,MAAI,OAAO,gBAAgB,YAAY;AACrC,mBAAe;AAAA,EACjB,WAAW,OAAO,cAAc,eAAe,kBAAkB,WAAW;AAC1E,kBAAc;AAAA,EAChB,WAAW,OAAO,qBAAqB,eAAe,kBAAkB,kBAAkB;AACxF,cAAU;AAAA,EACZ,WAAW,OAAO,qBAAqB,eAAe,kBAAkB,kBAAkB;AACxF,cAAU;AAAA,EACZ,WAAW,OAAO,cAAc,MAAM;AACpC,mBAAe;AAAA,EACjB,WAAW,OAAO,gBAAgB,eAAe,kBAAkB,aAAa;AAC9E,oBAAgB;AAAA,EAClB,OAAO;AACL,UAAM,IAAI,MAAM,qPAAqP,OAAO,YAAY,MAAM;AAAA,EAChS;AACA,MAAI,SAAS;AACX,UAAM,gCAAgC;AACtC,QAAI,WAAW,OAAO,aAAa,+BAA+B;AAChE,YAAM,IAAI,MAAM,uGAAuG;AAAA,IACzH;AAAA,EACF;AACA,QAAM,SAAS,UAAU,YAAY,OAAO,WAAW;AACvD,MAAI,UAAU,MAAM;AAClB,UAAM,SAAS,EAAE,OAAO;AACxB,UAAM,QAAQ,EAAE,YAAY;AAC5B,WAAO,OAAO,UAAU,YAAY,QAAQ,KAAK;AAAA,EACnD;AACA,QAAM,CAAC,OAAO,MAAM,IAAI,UAAU;AAAA,IAChC,OAAO;AAAA,IACP,OAAO;AAAA,EACT,IAAI,CAAC,OAAO,OAAO,OAAO,MAAM;AAChC,MAAI;AACJ,MAAI,cAAc;AAChB,WAAO,OAAO,WAAW,IAAI,EAAE,aAAa,GAAG,GAAG,OAAO,MAAM,EAAE;AAAA,EACnE,WAAW,eAAe,cAAc;AACtC,WAAO,OAAO;AAAA,EAChB,WAAW,WAAW,WAAW,eAAe;AAC9C,QAAI,uBAAuB,MAAM;AAC/B,UAAI,OAAO,aAAa,aAAa;AACnC,YAAI,OAAO,oBAAoB,eAAe,OAAO,sCAAsC,aAAa;AACtG,gCAAsB,IAAI,gBAAgB,GAAG,CAAC,EAAE,WAAW,IAAI;AAAA,QACjE,OAAO;AACL,gBAAM,IAAI,MAAM,sGAAsG;AAAA,QACxH;AAAA,MACF,OAAO;AACL,8BAAsB,SAAS,cAAc,QAAQ,EAAE,WAAW,MAAM,EAAE,oBAAoB,KAAK,CAAC;AAAA,MACtG;AAAA,IACF;AACA,wBAAoB,OAAO,QAAQ;AACnC,wBAAoB,OAAO,SAAS;AACpC,wBAAoB,UAAU,QAAQ,GAAG,GAAG,OAAO,MAAM;AACzD,WAAO,oBAAoB,aAAa,GAAG,GAAG,OAAO,MAAM,EAAE;AAAA,EAC/D;AACA,MAAI;AACJ,MAAI,gBAAgB,GAAG;AACrB,aAAS,IAAI,WAAW,IAAI;AAAA,EAC9B,OAAO;AACL,UAAM,YAAY,QAAQ;AAC1B,aAAS,IAAI,WAAW,YAAY,WAAW;AAC/C,aAAS,KAAK,GAAG,KAAK,WAAW,MAAM;AACrC,eAAS,UAAU,GAAG,UAAU,aAAa,EAAE,SAAS;AACtD,eAAO,KAAK,cAAc,WAAW,KAAK,KAAK,IAAI;AAAA,MACrD;AAAA,IACF;AAAA,EACF;AACA,QAAM,WAAW,CAAC,QAAQ,OAAO,WAAW;AAC5C,SAAO,SAAS,QAAQ,UAAU,OAAO;AAC3C;AACA,SAAS,YAAY,QAAQ;AAC3B,SAAO,UAAU,QAAQ,OAAO,gBAAgB;AAClD;AACA,SAAS,8BAA8B;AACrC,SAAO,OAAO,WAAW,eAAe,OAAO,gBAAgB,eAAe,OAAO,eAAe,mBAAmB;AACzH;AACA,SAAS,iBAAiB,QAAQ;AAChC,SAAO,UAAU,QAAQ,OAAO,UAAU,KAAK,OAAO,WAAW;AACnE;AACA,SAAS,2BAA2B,QAAQ;AAC1C,SAAO,4BAA4B,KAAK,EAAE,kBAAkB,gBAAgB,iBAAiB,MAAM,KAAK,CAAC,YAAY,MAAM;AAC7H;AACA,eAAe,gBAAgB,QAAQ,cAAc,GAAG;AACtD,MAAI,SAAS;AACb,MAAI,IAAI,EAAE,QAAQ,qBAAqB,KAAK,2BAA2B,MAAM,GAAG;AAC9E,QAAI;AACJ,QAAI;AACF,oBAAc,MAAM,kBAAkB,QAAQ,EAAE,kBAAkB,OAAO,CAAC;AAAA,IAC5E,SAAS,IAAP;AACA,oBAAc;AAAA,IAChB;AACA,QAAI,eAAe,QAAQ,YAAY,UAAU,OAAO,SAAS,YAAY,WAAW,OAAO,QAAQ;AACrG,eAAS;AAAA,IACX,OAAO;AACL,eAAS;AAAA,IACX;AAAA,EACF,OAAO;AACL,aAAS;AAAA,EACX;AACA,SAAO,YAAY,QAAQ,WAAW;AACxC;AACA,eAAe,SAAS,KAAKa,SAAQ;AACnC,MAAI,OAAO,gBAAgB,KAAK,OAAO,UAAU;AACjD,MAAI,EAAE,eAAe,SAAS;AAC5B,UAAM,oBAAoB;AAC1B,WAAO,KAAK,mBAAmB,OAAO;AACtC,sBAAkB,QAAQ;AAAA,EAC5B;AACA,MAAI,KAAK,SAAS,KAAK,KAAK,SAAS,GAAG;AACtC,UAAM,IAAI,MAAM,wDAAwD,KAAK,OAAO;AAAA,EACtF;AACA,QAAM,CAAC,QAAQ,KAAK,IAAI,KAAK,MAAM,MAAM,GAAG,CAAC;AAC7C,QAAM,QAAQ,KAAK,SAAS,IAAI,IAAI,KAAK,MAAM;AAC/C,MAAI,QAAQ,KAAK,UAAU,GAAG;AAC5B,UAAM,IAAI,MAAM,0DAA0D,OAAO;AAAA,EACnF;AACA,MAAI,KAAK,UAAU,aAAa,KAAK,UAAU,SAAS;AACtD,UAAM,IAAI,MAAM,kCAAkC,KAAK,6CAA6C;AAAA,EACtG;AACA,QAAM,OAAO,MAAM,KAAK,KAAK;AAC7B,QAAM,aAAa,KAAK,UAAU,YAAY,MAAM;AACpD,QAAM,QAAQ,IAAI,kBAAkB,QAAQ,SAAS,CAAC;AACtD,WAAS,KAAK,GAAG,KAAK,SAAS,OAAO,EAAE,IAAI;AAC1C,UAAM,OAAO,CAAC,GAAG,GAAG,GAAG,GAAG;AAC1B,aAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,YAAM,QAAQ,KAAK,KAAK,QAAQ;AAChC,UAAI,KAAK,UAAU,WAAW;AAC5B,YAAI,QAAQ,KAAK,QAAQ,GAAG;AAC1B,gBAAM,IAAI,MAAM,mFAAmF,QAAQ;AAAA,QAC7G;AAAA,MACF,WAAW,KAAK,UAAU,SAAS;AACjC,YAAI,QAAQ,KAAK,QAAQ,KAAK;AAC5B,gBAAM,IAAI,MAAM,mFAAmF,QAAQ;AAAA,QAC7G;AAAA,MACF;AACA,UAAI,UAAU,GAAG;AACf,aAAK,KAAK,QAAQ;AAClB,aAAK,KAAK,QAAQ;AAClB,aAAK,KAAK,QAAQ;AAAA,MACpB,OAAO;AACL,aAAK,KAAK,QAAQ;AAAA,MACpB;AAAA,IACF;AACA,UAAM,IAAI,KAAK;AACf,UAAM,IAAI,KAAK,KAAK,MAAM,KAAK,EAAE;AACjC,UAAM,IAAI,KAAK,KAAK,MAAM,KAAK,EAAE;AACjC,UAAM,IAAI,KAAK,KAAK,MAAM,KAAK,EAAE;AACjC,UAAM,IAAI,KAAK,KAAK,MAAM,KAAK,EAAE;AAAA,EACnC;AACA,MAAIA,WAAU,MAAM;AAClB,IAAAA,QAAO,QAAQ;AACf,IAAAA,QAAO,SAAS;AAChB,UAAM,MAAMA,QAAO,WAAW,IAAI;AAClC,UAAM,YAAY,IAAI,UAAU,OAAO,OAAO,MAAM;AACpD,QAAI,aAAa,WAAW,GAAG,CAAC;AAAA,EAClC;AACA,MAAI,SAAS,KAAK;AAChB,SAAK,QAAQ;AAAA,EACf;AACA,SAAO;AACT;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,IAAI,yBAAyB,CAAC;AAC9Bb,UAAS,wBAAwB;AAAA,EAC/B,oBAAoB,MAAM;AAC5B,CAAC;AACD,SAAS,mBAAmB,SAAS,SAAS;AAC5C,QAAM,aAAa,QAAQ,MAAM;AACjC,QAAM,cAAc,QAAQ,MAAM;AAClC,MAAI,aAAa,GAAG;AAClB,UAAM,IAAI,MAAM,4EAA4E,aAAa;AAAA,EAC3G;AACA,MAAI,cAAc,GAAG;AACnB,UAAM,IAAI,MAAM,8EAA8E,cAAc;AAAA,EAC9G;AACA,MAAI,QAAQ,UAAU,SAAS;AAC7B,UAAM,IAAI,MAAM,yEAAyE,QAAQ,QAAQ;AAAA,EAC3G;AACA,MAAI,QAAQ,MAAM,cAAc,KAAK,YAAY;AAC/C,UAAM,IAAI,MAAM,iEAAiE,QAAQ,MAAM,cAAc,UAAU,YAAY;AAAA,EACrI;AACA,MAAI,cAAc,QAAQ,KAAK,MAAM,GAAG;AACtC,UAAM,IAAI,MAAM,mEAAmE,QAAQ,QAAQ;AAAA,EACrG;AACA,QAAM,eAAe,QAAQ;AAC7B,QAAM,YAAY,aAAa,aAAa,SAAS;AACrD,MAAI,UAAU;AACd,WAAS,KAAK,GAAG,KAAK,aAAa,SAAS,GAAG,EAAE,IAAI;AACnD,eAAW,aAAa;AAAA,EAC1B;AACA,QAAM,aAAa,QAAQ;AAC3B,QAAM,cAAc,aAAa,MAAM;AACvC,cAAY,IAAI;AAChB,MAAI,YAAY;AAChB,WAAS,KAAK,WAAW,KAAK,YAAY,EAAE,IAAI;AAC9C,iBAAa,WAAW;AACxB,gBAAY,KAAK,WAAW,GAAG;AAAA,EACjC;AACA,QAAMe,WAAU;AAAA,IACd,GAAG,eAAe,QAAQ,KAAK,EAAE,IAAI,CAAC,WAAW,SAAS,SAAS;AAAA,IACnE;AAAA,EACF,EAAE,MAAM,GAAG,SAAS;AACpB,SAAO,CAAC,aAAa,SAAS,WAAWA,QAAO;AAClD;AAGA,IAAI,0BAA0B,CAAC;AAC/Bf,UAAS,yBAAyB;AAAA,EAChC,iBAAiB,MAAM;AAAA,EACvB,eAAe,MAAM;AAAA,EACrB,qBAAqB,MAAM;AAC7B,CAAC;AACD,SAAS,oBAAoB,OAAO,SAAS,SAAS;AACpD,QAAM,WAAW,QAAQ,OAAO,IAAI,QAAQ,MAAM,QAAQ,OAAO,KAAK;AACtE,QAAM,WAAW,QAAQ,OAAO,IAAI,QAAQ,OAAO,IAAI;AACvD,QAAM,aAAa,6FAA6F,QAAQ,yBAAyB,QAAQ,iBAAiB,oBAAoB,2BAA2B;AACzN,MAAI,QAAQ,OAAO,UAAU;AAC3B,UAAM,IAAI,MAAM,aAAa,kBAAkB,YAAY;AAAA,EAC7D;AACA,MAAI,MAAM,SAAS,YAAY,QAAQ,OAAO,WAAW;AACvD,UAAM,IAAI,MAAM,aAAa,0BAA0B,YAAY,QAAQ,OAAO,WAAW;AAAA,EAC/F;AACA,MAAI,QAAQ,SAAS,WAAW,MAAM,SAAS,UAAU;AACvD,UAAM,IAAI,MAAM,aAAa,mBAAmB,WAAW,MAAM,SAAS,UAAU;AAAA,EACtF;AACA,WAAS,IAAI,GAAG,IAAI,UAAU,EAAE,GAAG;AACjC,QAAI,QAAQ,MAAM,OAAO,QAAQ,MAAM,IAAI;AACzC,YAAM,IAAI,MAAM,aAAa,kBAAkB,OAAO,QAAQ,MAAM,wBAAwB,OAAO,QAAQ,MAAM,MAAM;AAAA,IACzH;AAAA,EACF;AACA,WAAS,IAAI,GAAG,IAAI,QAAQ,OAAO,UAAU,EAAE,GAAG;AAChD,QAAI,QAAQ,MAAM,IAAI,cAAc,MAAM,IAAI,WAAW;AACvD,YAAM,IAAI,MAAM,aAAa,kBAAkB,IAAI,cAAc,QAAQ,MAAM,IAAI,uBAAuB,IAAI,cAAc,MAAM,IAAI,YAAY;AAAA,IACpJ;AAAA,EACF;AACF;AACA,SAAS,cAAc,SAAS,SAAS,OAAO;AAC9C,MAAI,QAAQ,OAAO,GAAG;AACpB,UAAM,IAAI,MAAM,+EAA+E,QAAQ,OAAO;AAAA,EAChH;AACA,MAAI,QAAQ,OAAO,GAAG;AACpB,UAAM,IAAI,MAAM,+EAA+E,QAAQ,OAAO;AAAA,EAChH;AACA,MAAI,QAAQ,UAAU,SAAS;AAC7B,UAAM,IAAI,MAAM,0DAA0D,QAAQ,OAAO;AAAA,EAC3F;AACA,MAAI,MAAM,SAAS,GAAG;AACpB,UAAM,IAAI,MAAM,6DAA6D,OAAO;AAAA,EACtF;AACA,MAAI,MAAM,WAAW,GAAG;AACtB,QAAI,QAAQ,SAAS,GAAG;AACtB,YAAM,IAAI,MAAM,sDAAsD,QAAQ,OAAO;AAAA,IACvF;AACA,QAAI,QAAQ,SAAS,GAAG;AACtB,YAAM,IAAI,MAAM,sDAAsD,QAAQ,OAAO;AAAA,IACvF;AAAA,EACF;AACA,sBAAoB,OAAO,SAAS,OAAO;AAC7C;AACA,SAAS,gBAAgB,SAAS,SAAS,OAAO;AAChD,QAAM,cAAc,QAAQ,MAAM;AAClC,QAAM,YAAY,cAAc,IAAI,QAAQ,MAAM,cAAc,KAAK;AACrE,QAAM,UAAU,MAAM;AACtB,MAAI,YAAY;AAChB,WAAS,KAAK,WAAW,KAAK,SAAS,EAAE,IAAI;AAC3C,iBAAa,MAAM;AAAA,EACrB;AACA,QAAM,eAAe,YAAY,IAAI,IAAI;AACzC,QAAM,aAAa,cAAc,QAAQ,KAAK,IAAI;AAClD,QAAMe,WAAU,CAAC,GAAG,eAAe,MAAM,MAAM,GAAG,SAAS,CAAC,GAAG,CAAC;AAChE,QAAMQ,cAAa,cAAc,KAAK;AACtC,SAAO,EAAE,WAAW,YAAY,WAAW,SAAAR,UAAS,YAAAQ,YAAW;AACjE;AAGA,IAAI,qBAAqB,CAAC;AAC1BvB,UAAS,oBAAoB;AAAA,EAC3B,mBAAmB,MAAM;AAAA,EACzB,mBAAmB,MAAM;AAAA,EACzB,iBAAiB,MAAM;AAAA,EACvB,mBAAmB,MAAM;AAAA,EACzB,kBAAkB,MAAM;AAAA,EACxB,YAAY,MAAM;AAAA,EAClB,kBAAkB,MAAM;AAAA,EACxB,WAAW,MAAM;AAAA,EACjB,cAAc,MAAM;AAAA,EACpB,4BAA4B,MAAM;AAAA,EAClC,aAAa,MAAM;AAAA,EACnB,2BAA2B,MAAM;AAAA,EACjC,gBAAgB,MAAM;AAAA,EACtB,uBAAuB,MAAM;AAC/B,CAAC;AACD,IAAI,WAAW;AACf,IAAI,cAAc;AAClB,SAAS,kBAAkB,QAAQ,OAAOG,OAAM;AAC9C,QAAM,YAAY,OAAO,MAAM;AAC/B,SAAO,cAAc,MAAM,QAAQ,MAAM,iBAAiB,+BAA+B,2CAA2C,aAAa;AACjJ,SAAO,cAAcA,MAAK,QAAQ,MAAM,iBAAiB,8BAA8BA,2CAA0C,aAAa;AAC9I,WAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,WAAO,MAAM,MAAMA,MAAK,OAAO,OAAO,MAAM,KAAK,MAAM,iBAAiB,qBAAqB,cAAc,QAAQ,MAAM,MAAMA,MAAK,mCAAmC,QAAQ,OAAO,MAAM,MAAM;AAAA,EACpM;AACF;AACA,SAAS,WAAWK,OAAM;AACxB,QAAM,OAAO,CAAC;AACd,MAAI,OAAO;AACX,SAAOA,QAAO,GAAG;AACf,QAAIA,QAAO,GAAG;AACZ,WAAK,KAAK,IAAI;AAAA,IAChB;AACA,IAAAA,SAAQ;AACR;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,gBAAgB,OAAO,KAAKO,UAAS;AAC5C,QAAMZ,QAAO,CAAC;AACd,WAAS,OAAO,GAAG,OAAO,MAAM,QAAQ,QAAQ;AAC9C,IAAAA,MAAK,QAAQ,KAAK,MAAM,IAAI,QAAQ,MAAM,SAASY,SAAQ,KAAK;AAAA,EAClE;AACA,SAAOZ;AACT;AACA,SAAS,sBAAsBY,UAAS,wBAAwB,eAAe,YAAY;AACzF,QAAM,aAAa,CAAC,GAAGA,QAAO;AAC9B,WAAS,KAAK,WAAW,QAAQ,KAAK,WAAW,QAAQ,MAAM;AAC7D,eAAW,KAAK,CAAC;AAAA,EACnB;AACA,WAAS,KAAK,GAAG,KAAK,eAAe,MAAM;AACzC,QAAI,OAAO,GAAG;AACZ,iBAAW,0BAA0B;AAAA,IACvC,OAAO;AACL,iBAAW,OAAO,wBAAwB,GAAG,CAAC;AAC9C,iBAAW,IAAI;AAAA,IACjB;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,gBAAgB,wBAAwB,eAAe,gBAAgB;AAC9E,MAAI,kBAAkB,wBAAwB;AAC5C,WAAO;AAAA,EACT;AACA,SAAO,kBAAkB,gBAAgB;AAC3C;AACA,SAAS,cAAc,eAAe,wBAAwB;AAC5D,QAAM,aAAa,CAAC;AACpB,WAAS,KAAK,GAAG,KAAK,eAAe,MAAM;AACzC,eAAW,KAAK,yBAAyB,EAAE;AAAA,EAC7C;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,YAAY,cAAc,qBAAqB,OAAO,KAAKA,UAAS,WAAW,SAAS,cAAc;AAC/H,QAAM,YAAY,WAAW;AAC7B,MAAI,kBAAkB,IAAI,MAAM,SAAS,GAAG,gBAAgB,IAAI,MAAM,SAAS,GAAG,oBAAoB,IAAI,MAAM,SAAS;AACzH,MAAI,aAAa,UAAU,sBAAsB,GAAG;AAClD,UAAM,YAAY,aAAa;AAC/B,UAAM,gBAAgB,sBAAsB;AAC5C,sBAAkB,2BAA2B,WAAW,WAAW,eAAe,OAAO,UAAU;AACnG,oBAAgB,0BAA0B,SAAS,WAAW,eAAe,KAAK,UAAU;AAC5F,wBAAoB,sBAAsBA,UAAS,WAAW,eAAe,UAAU;AAAA,EACzF,OAAO;AACL,aAAS,OAAO,GAAG,OAAO,WAAW,QAAQ;AAC3C,sBAAgB,QAAQ,aAAa,WAAW,OAAOA,UAAS,YAAY,MAAM,YAAY;AAC9F,oBAAc,QAAQ,YAAY,SAAS,KAAKA,UAAS,YAAY,MAAM,YAAY;AACvF,wBAAkB,QAAQ,eAAeA,UAAS,MAAM,YAAY;AAAA,IACtE;AAAA,EACF;AACA,SAAO;AAAA,IACL,OAAO;AAAA,IACP,KAAK;AAAA,IACL,SAAS;AAAA,EACX;AACF;AACA,SAAS,2BAA2B,WAAW,wBAAwB,eAAe,eAAe,YAAY;AAC/G,QAAM,aAAa,CAAC,GAAG,UAAU;AACjC,QAAM,aAAa,cAAc,eAAe,sBAAsB;AACtE,WAAS,OAAO,GAAG,OAAO,WAAW,QAAQ,QAAQ;AACnD,QAAI,WAAW,QAAQ,IAAI,IAAI,IAAI;AACjC,iBAAW,QAAQ;AAAA,IACrB,OAAO;AACL,YAAM,eAAe,gBAAgB,wBAAwB,eAAe,IAAI;AAChF,UAAI,gBAAgB,cAAc;AAClC,UAAI,YAAY,KAAK,cAAc;AACjC,wBAAgB;AAAA,MAClB;AACA,iBAAW,QAAQ;AAAA,IACrB;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,0BAA0B,SAAS,wBAAwB,eAAe,aAAa,YAAY;AAC1G,QAAM,aAAa,CAAC,GAAG,UAAU;AACjC,QAAM,aAAa,cAAc,eAAe,sBAAsB;AACtE,WAAS,OAAO,GAAG,OAAO,WAAW,QAAQ,QAAQ;AACnD,QAAI,WAAW,QAAQ,IAAI,IAAI,IAAI;AACjC,iBAAW,QAAQ,OAAO;AAAA,IAC5B,OAAO;AACL,YAAM,eAAe,gBAAgB,wBAAwB,eAAe,IAAI;AAChF,UAAI,gBAAgB,YAAY;AAChC,UAAI,UAAU,KAAK,cAAc;AAC/B,wBAAgB,OAAO;AAAA,MACzB;AACA,iBAAW,QAAQ;AAAA,IACrB;AAAA,EACF;AACA,WAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,MAAM;AAC7C,UAAM,WAAW,WAAW;AAC5B,QAAI,WAAW,MAAM,GAAG;AACtB,iBAAW,OAAO;AAAA,IACpB;AACA,eAAW,MAAM,MAAM,GAAG,WAAW,KAAK,WAAW,GAAG;AAAA,EAC1D;AACA,SAAO;AACT;AACA,SAAS,eAAeA,UAAS,MAAM,cAAc;AACnD,MAAI,SAASA,SAAQ;AACrB,MAAI,eAAe,KAAK,QAAQ,UAAU,MAAM;AAC9C,aAAS;AAAA,EACX;AACA,SAAO;AACT;AACA,SAAS,aAAa,WAAW,cAAcA,UAAS,YAAY,MAAM,cAAc;AACtF,MAAI,QAAQ,aAAa;AACzB,QAAM,SAASA,SAAQ,SAAS;AAChC,MAAI,YAAY,KAAK,QAAQ,eAAe,KAAK,QAAQ,SAAS,MAAM;AACtE,QAAI,SAAS,GAAG;AACd,cAAQ,OAAO;AAAA,IACjB,OAAO;AACL,cAAQ,OAAO;AAAA,IACjB;AAAA,EACF;AACA,QAAM,WAAW,WAAW;AAC5B,MAAI,QAAQ,GAAG;AACb,aAAS;AAAA,EACX;AACA,UAAQ,MAAM,GAAG,OAAO,WAAW,CAAC;AACpC,SAAO;AACT;AACA,SAAS,YAAY,SAAS,aAAaA,UAAS,YAAY,MAAM,cAAc;AAClF,MAAI,OAAO,YAAY;AACvB,QAAM,SAASA,SAAQ,SAAS;AAChC,MAAI,UAAU,KAAK,QAAQ,eAAe,KAAK,QAAQ,QAAQ,MAAM;AACnE,QAAI,SAAS,GAAG;AACd,aAAO,OAAO;AAAA,IAChB,OAAO;AACL,aAAO,OAAO;AAAA,IAChB;AAAA,EACF;AACA,QAAM,WAAW,WAAW;AAC5B,MAAI,OAAO,GAAG;AACZ,YAAQ;AAAA,EACV;AACA,MAAI,SAAS,GAAG;AACd,WAAO,MAAM,GAAG,MAAM,QAAQ;AAAA,EAChC,OAAO;AACL,WAAO,MAAM,IAAI,MAAM,WAAW,CAAC;AAAA,EACrC;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,OAAO,OAAOZ,OAAM;AAC5C,MAAI,kBAAkBA,MAAK;AAC3B,WAAS,KAAK,GAAG,KAAKA,MAAK,QAAQ,MAAM;AACvC,QAAIA,MAAK,MAAM,GAAG;AAChB,wBAAkB;AAClB;AAAA,IACF;AAAA,EACF;AACA,WAAS,KAAK,kBAAkB,GAAG,KAAKA,MAAK,QAAQ,MAAM;AACzD,QAAI,MAAM,MAAM,KAAKA,MAAK,QAAQ,MAAM,KAAK;AAC3C,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,OAAOY,UAAS;AACzC,MAAI,aAAa,MAAM,SAAS,IAAI,MAAM,MAAM,SAAS,KAAK;AAC9D,WAAS,KAAK,GAAG,KAAK,MAAM,SAAS,GAAG,MAAM;AAC5C,kBAAc,MAAM,MAAMA,SAAQ;AAAA,EACpC;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,GAAG,OAAOZ,OAAM;AACxC,MAAI;AACJ,QAAM,QAAQ,EAAE,MAAM;AACtB,MAAI,OAAO,UAAU,UAAU;AAC7B,aAAS,CAAC,OAAO,GAAG,IAAI,MAAM,QAAQ,CAAC,EAAE,KAAK,CAAC,CAAC;AAAA,EAClD,WAAW,MAAM,SAAS,OAAO;AAC/B,aAAS,MAAM,OAAO,IAAI,MAAM,QAAQ,MAAM,MAAM,EAAE,KAAK,CAAC,CAAC;AAAA,EAC/D,OAAO;AACL,aAAS,MAAM,MAAM;AAAA,EACvB;AACA,SAAO,QAAQ,CAAC,MAAM;AACpB,WAAO,MAAM,IAAI,MAAM,mDAAmD;AAAA,EAC5E,CAAC;AACD,MAAI;AACJ,MAAIA,SAAQ,MAAM;AAChB,YAAQ,IAAI,MAAM,KAAK,EAAE,KAAK,EAAE;AAAA,EAClC,WAAW,OAAOA,UAAS,UAAU;AACnC,YAAQ,CAACA,OAAM,GAAG,IAAI,MAAM,QAAQ,CAAC,EAAE,KAAK,EAAE,CAAC;AAAA,EACjD,WAAWA,MAAK,SAAS,OAAO;AAC9B,YAAQA,MAAK,OAAO,IAAI,MAAM,QAAQA,MAAK,MAAM,EAAE,KAAK,EAAE,CAAC;AAAA,EAC7D,OAAO;AACL,YAAQA;AAAA,EACV;AACA,UAAQ,MAAM,IAAI,CAAC,GAAG,OAAO;AAC3B,QAAI,KAAK,GAAG;AACV,aAAO;AAAA,IACT,OAAO;AACL,aAAO,MAAM,IAAI,MAAM,qDAAqD,mCAAmC,KAAK;AACpH,aAAO,EAAE,MAAM,MAAM,OAAO;AAAA,IAC9B;AAAA,EACF,CAAC;AACD,SAAO,CAAC,QAAQ,KAAK;AACvB;AACA,SAAS,UAAU,QAAQ,OAAO,KAAKY,UAAS,WAAW,SAAS,cAAc,aAAa,gBAAgB;AAC7G,MAAI;AACJ,MAAIA,YAAW,MAAM;AACnB,qBAAiB,IAAI,MAAM,MAAM,MAAM;AACvC,mBAAe,KAAK,CAAC;AAAA,EACvB,OAAO;AACL,qBAAiBA;AAAA,EACnB;AACA,MAAI,gBAAgB,SAAS,eAAe,eAAe,OAAO,GAAG;AACnE,UAAM,IAAI,MAAM,4CAA4C;AAAA,EAC9D;AACA,MAAI,eAAe;AACnB,QAAM,aAAa;AAAA,IACjB,MAAM,eAAe;AAAA,IACrB,yBAAyB;AAAA,IACzB,OAAO,MAAM,MAAM;AAAA,IACnB,KAAK,IAAI,MAAM;AAAA,IACf,SAAS,eAAe,MAAM;AAAA,IAC9B;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACA,WAAS,KAAK,GAAG,KAAK,WAAW,MAAM,MAAM;AAC3C,QAAI,iBAAiB,KAAK,KAAK,iBAAiB,GAAG;AACjD,iBAAW;AAAA,IACb;AACA,QAAI,KAAK,KAAK,cAAc;AAC1B,qBAAe;AAAA,IACjB;AAAA,EACF;AACA,MAAI,CAAC,cAAc;AACjB,eAAW,gBAAgB,KAAK,WAAW;AAC3C,eAAW;AAAA,EACb;AACA,QAAM,YAAY;AAAA,IAChB,MAAM,OAAO;AAAA,IACb,WAAW;AAAA,IACX,SAAS;AAAA,IACT,YAAY;AAAA,IACZ,UAAU;AAAA,EACZ;AACA,iBAAe,YAAY,SAAS;AACpC,MAAI,aAAa;AACjB,MAAI,YAAY;AAChB,MAAI,gBAAgB;AACpB,QAAM,kBAAkB,CAAC;AACzB,QAAM,aAAa,CAAC;AACpB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,QAAI,UAAU,QAAQ,QAAQ,GAAG;AAC/B,YAAM,MAAM,WAAW,sBAAsB;AAAA,IAC/C;AACA,UAAM,UAAU,CAAC,EAAE,UAAU,iBAAiB,KAAK;AACnD,UAAM,OAAO,OAAO;AACpB,QAAI,SAAS,IAAI;AACf,sBAAgB,KAAK,UAAU,IAAI,EAAE;AACrC;AAAA,IACF;AACA,UAAM,QAAQ,CAAC,UAAU,YAAY,KAAK,IAAI,UAAU,UAAU,KAAK,EAAE;AACzE,UAAM,aAAa;AAAA,MACjB,UAAU,QAAQ,MAAM,IAAI,IAAI;AAAA,MAChC,UAAU,QAAQ,MAAM,IAAI,OAAO,OAAO;AAAA,IAC5C;AACA,QAAI,WAAW,UAAU,QAAQ,OAAO,GAAG;AACzC,YAAM,MAAM,8CAA8C;AAAA,IAC5D;AACA,oBAAgB,iBAAiB,UAAU,QAAQ,QAAQ;AAC3D,UAAM,oBAAoB,CAAC,EAAE,UAAU,YAAY,KAAK,MAAM,UAAU,UAAU,KAAK;AACvF,QAAI,UAAU,cAAc,UAAU,UAAU;AAC9C,UAAI,SAAS;AACX,cAAM,OAAO,UAAU,MAAM,MAAM,IAAI,OAAO,UAAU,MAAM,MAAM,UAAU,MAAM;AACpF,kBAAU,MAAM,MAAM;AACtB,kBAAU,IAAI,MAAM,UAAU,MAAM,MAAM;AAC1C,YAAI,OAAO,KAAK,QAAQ,MAAM;AAC5B,gBAAM,MAAM,eAAe,UAAU,MAAM,oBAAoB,mBAAmB;AAAA,QACpF;AAAA,MACF,OAAO;AACL,kBAAU,MAAM,MAAM,UAAU,UAAU,MAAM,KAAK,GAAG,UAAU,QAAQ,KAAK,MAAM,OAAO,UAAU;AACtG,kBAAU,IAAI,MAAM,UAAU,UAAU,IAAI,KAAK,GAAG,UAAU,QAAQ,KAAK,MAAM,OAAO,UAAU;AAAA,MACpG;AACA,YAAM,qBAAqB,UAAU,QAAQ,QAAQ,KAAK,UAAU,MAAM,QAAQ,KAAK,UAAU,IAAI,QAAQ;AAC7G,mBAAa,cAAc;AAC3B,kBAAY,cAAc,OAAO,KAAK,UAAU,QAAQ,QAAQ,KAAK;AAAA,IACvE,OAAO;AACL,mBAAa,eAAe,UAAU,QAAQ,QAAQ,KAAK;AAC3D,kBAAY,cAAc,OAAO,KAAK,UAAU,QAAQ,QAAQ,KAAK;AAAA,IACvE;AACA,QAAI;AACJ,QAAI,gBAAgB;AACpB,QAAI,UAAU,cAAc,UAAU,UAAU;AAC9C,uBAAiB,UAAU,IAAI,MAAM,UAAU,MAAM;AACrD,sBAAgB;AAAA,IAClB,WAAW,SAAS;AAClB,uBAAiB;AACjB,sBAAgB;AAAA,IAClB,WAAW,mBAAmB;AAC5B,UAAI,QAAQ,GAAG;AACb,YAAI,UAAU,QAAQ,MAAM,GAAG;AAC7B,2BAAiB,CAAC;AAAA,QACpB,OAAO;AACL,2BAAiB;AAAA,QACnB;AACA,wBAAgB;AAAA,MAClB;AAAA,IACF;AACA,QAAI,eAAe;AACjB,UAAI;AACJ,UAAI,mBAAmB,KAAK,iBAAiB,MAAM,UAAU,QAAQ,MAAM,GAAG;AAC5E,gBAAQ;AAAA,MACV,OAAO;AACL,gBAAQ,KAAK,MAAM,iBAAiB,UAAU,QAAQ,GAAG,KAAK,iBAAiB,UAAU,QAAQ,QAAQ,IAAI,IAAI;AAAA,MACnH;AACA,sBAAgB,KAAK,KAAK;AAAA,IAC5B,OAAO;AACL,sBAAgB,KAAK,EAAE;AAAA,IACzB;AAAA,EACF;AACA,WAAS,WAAW,GAAG,WAAW,UAAU,wBAAwB,QAAQ,EAAE,UAAU;AACtF,UAAM,cAAc,UAAU,wBAAwB;AACtD,QAAI,eAAe,GAAG;AACpB,iBAAW,KAAK,gBAAgB,YAAY;AAAA,IAC9C,WAAW,gBAAgB,UAAU;AACnC,iBAAW,KAAK,CAAC;AAAA,IACnB;AAAA,EACF;AACA,QAAM,mBAAmB,WAAW,OAAO,CAAC,KAAK,OAAO,UAAU,wBAAwB,QAAQ,QAAQ;AAC1G,SAAO;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA,OAAO,UAAU;AAAA,IACjB,KAAK,UAAU;AAAA,IACf,SAAS,UAAU;AAAA,EACrB;AACF;AACA,SAAS,eAAe,SAAS,QAAQ;AACvC,SAAO,YAAY;AACnB,SAAO,UAAU;AACjB,SAAO,iBAAiB;AACxB,MAAI,YAAY;AAChB,SAAO,aAAa,QAAQ,SAAS;AACrC,SAAO,WAAW,QAAQ,OAAO;AACjC,SAAO,QAAQ,IAAI,MAAM,OAAO,IAAI;AACpC,SAAO,MAAM,IAAI,MAAM,OAAO,IAAI;AAClC,SAAO,UAAU,IAAI,MAAM,OAAO,IAAI;AACtC,SAAO,0BAA0B,CAAC;AAClC,SAAO,gCAAgC,CAAC;AACxC,SAAO,gCAAgC,IAAI,MAAM,OAAO,IAAI;AAC5D,WAAS,KAAK,GAAG,KAAK,QAAQ,MAAM,MAAM;AACxC,QAAI,KAAK,KAAK,QAAQ,cAAc;AAClC,YAAM,YAAY,KAAK,IAAI,OAAO,QAAQ,QAAQ,OAAO,MAAM,IAAI,QAAQ,yBAAyB,OAAO,IAAI;AAC/G,aAAO,YAAY,WAAW,aAAa;AACzC,eAAO,MAAM,aAAa;AAC1B,eAAO,IAAI,aAAa;AACxB,eAAO,QAAQ,aAAa;AAC5B,eAAO,aAAa,KAAK;AACzB,eAAO,WAAW,KAAK;AACvB,eAAO,wBAAwB,KAAK,SAAS;AAC7C,eAAO,8BAA8B,KAAK,EAAE;AAC5C,eAAO,8BAA8B,aAAa;AAAA,MACpD;AAAA,IACF,WAAW,KAAK,KAAK,QAAQ,aAAa;AACxC,aAAO,wBAAwB,KAAK,QAAQ;AAC5C,aAAO,8BAA8B,KAAK,EAAE;AAAA,IAC9C,OAAO;AACL,UAAI,cAAc,OAAO,MAAM,QAAQ;AACrC,cAAM,MAAM,sCAAsC,6BAA6B,OAAO,cAAc,OAAO,MAAM,SAAS;AAAA,MAC5H;AACA,UAAI,QAAQ,SAAS,MAAM;AACzB,eAAO,MAAM,aAAa,QAAQ,MAAM;AAAA,MAC1C;AACA,UAAI,QAAQ,OAAO,MAAM;AACvB,eAAO,IAAI,aAAa,QAAQ,IAAI;AAAA,MACtC;AACA,aAAO,QAAQ,aAAa,QAAQ,QAAQ;AAC5C,UAAI,QAAQ,YAAY,KAAK,IAAI;AAC/B,eAAO,aAAa,KAAK;AAAA,MAC3B;AACA,UAAI,QAAQ,UAAU,KAAK,IAAI;AAC7B,eAAO,WAAW,KAAK;AAAA,MACzB;AACA,UAAI,QAAQ,iBAAiB,KAAK,IAAI;AACpC,eAAO,wBAAwB,KAAK,WAAW;AAC/C,eAAO,8BAA8B,KAAK,EAAE;AAC5C,eAAO,kBAAkB,KAAK;AAAA,MAChC,OAAO;AACL,eAAO,wBAAwB,KAAK,SAAS;AAC7C,eAAO,8BAA8B,KAAK,EAAE;AAAA,MAC9C;AACA,aAAO,8BAA8B,aAAa;AAClD;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,UAAU,GAAG,GAAG,SAAS,MAAM,OAAO,YAAY;AACzD,MAAI,MAAM,IAAI;AACZ,WAAO,UAAU,IAAI,WAAW,KAAK,WAAW,IAAI,IAAI;AAAA,EAC1D,OAAO;AACL,UAAM,OAAO,IAAI,IAAI,OAAO,IAAI;AAChC,WAAO,OAAO,WAAW,KAAK,WAAW,KAAK,OAAO,WAAW,KAAK,WAAW,KAAK;AAAA,EACvF;AACF;AAGA,IAAI,wBAAwB,CAAC;AAC7Bf,UAAS,uBAAuB;AAAA,EAC9B,cAAc,MAAM;AAAA,EACpB,kBAAkB,MAAM;AAAA,EACxB,eAAe,MAAM;AACvB,CAAC;AACD,IAAI,eAAe,MAAM;AAAA,EACvB,eAAe;AACb,WAAO,KAAK,YAAY;AAAA,EAC1B;AAAA,EACA,OAAO,WAAW,KAAKiB,SAAQ;AAC7B,WAAO,IAAI,IAAIA,OAAM;AAAA,EACvB;AACF;AACA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,cAAc;AACZ,SAAK,eAAe,CAAC;AAAA,EACvB;AAAA,EACA,OAAO,SAAS;AACd,QAAI,iBAAiB,YAAY,MAAM;AACrC,uBAAiB,WAAW,IAAI,iBAAiB;AAAA,IACnD;AACA,WAAO,iBAAiB;AAAA,EAC1B;AAAA,EACA,OAAO,SAAS,KAAK;AACnB,qBAAiB,OAAO,EAAE,aAAa,IAAI,aAAa,CAAC,KAAK,IAAI,UAAU;AAAA,EAC9E;AACF;AACA,SAAS,cAAc,KAAK;AAC1B,SAAO,IAAI,aAAa,MAAM,MAAM,6EAA6E;AACjH,SAAO,OAAO,IAAI,cAAc,UAAU,MAAM,wDAAwD,OAAO,IAAI,SAAS;AAC5H,SAAO,IAAI,UAAU,SAAS,GAAG,MAAM,mFAAmF;AAC1H,mBAAiB,SAAS,GAAG;AAC/B;AAGA,IAAI,oBAAoB,CAAC;AACzBjB,UAAS,mBAAmB;AAAA,EAC1B,sBAAsB,MAAM;AAAA,EAC5B,eAAe,MAAM;AAAA,EACrB,yBAAyB,MAAM;AAAA,EAC/B,mBAAmB,MAAM;AAAA,EACzB,mBAAmB,MAAM;AAAA,EACzB,oBAAoB,MAAM;AAAA,EAC1B,qBAAqB,MAAM;AAAA,EAC3B,qBAAqB,MAAM;AAAA,EAC3B,aAAa,MAAM;AACrB,CAAC;AACD,IAAI,uBAAuB;AAC3B,IAAI,uBAAuB;AAC3B,SAAS,kBAAkB,QAAQ,UAAU,UAAU;AACrD,MAAI,YAAY,MAAM;AACpB,eAAW,YAAY;AAAA,EACzB;AACA,SAAO,sBAAsB,QAAQ,UAAU,CAAC,GAAG,MAAM,SAAS,GAAG,GAAG,QAAQ,CAAC;AACnF;AACA,SAAS,cAAc;AACrB,SAAO,OAAO,QAAQ,eAAe,MAAM,KAAK,uBAAuB;AACzE;AACA,SAAS,sBAAsB,QAAQ,UAAU,WAAW;AAC1D,MAAI,iBAAiB;AACrB,MAAI,aAAa,MAAM,KAAK,aAAa,QAAQ,GAAG;AAClD,qBAAiB;AAAA,EACnB;AACA,MAAI,aAAa,MAAM,KAAK,aAAa,QAAQ,GAAG;AAClD,qBAAiB;AAAA,EACnB;AACA,MAAI,gBAAgB;AAClB,UAAM,QAAQ,OAAO,YAAY;AACjC,UAAM,QAAQ,SAAS,YAAY;AACnC,QAAI,UAAU,OAAO;AACnB,YAAM,IAAI,MAAM,yCAAyC,oBAAoB,OAAO;AAAA,IACtF;AAAA,EACF;AACA,MAAI,MAAM,QAAQ,MAAM,KAAK,MAAM,QAAQ,QAAQ,GAAG;AACpD,UAAM,cAAc,WAAW,MAAM;AACrC,UAAM,gBAAgB,WAAW,QAAQ;AACzC,QAAI,CAAC,YAAY,aAAa,aAAa,GAAG;AAC5C,YAAM,IAAI,MAAM,0CAA0C,4BAA4B,gBAAgB;AAAA,IACxG;AAAA,EACF;AACA,QAAM,aAAa,aAAa,MAAM,IAAI,SAAS,QAAQ,MAAM;AACjE,QAAM,eAAe,aAAa,QAAQ,IAAI,WAAW,QAAQ,QAAQ;AACzE,MAAI,WAAW,WAAW,aAAa,QAAQ;AAC7C,UAAM,IAAI,MAAM,yCAAyC,WAAW,uBAAuB,aAAa;AAAA,YAChG;AAAA,YACA,eAAe;AAAA,EACzB;AACA,WAAS,KAAK,GAAG,KAAK,aAAa,QAAQ,EAAE,IAAI;AAC/C,UAAM,IAAI,WAAW;AACrB,UAAM,KAAK,aAAa;AACxB,QAAI,CAAC,UAAU,GAAG,EAAE,GAAG;AACrB,YAAM,IAAI,MAAM,yBAAyB,SAAS,eAAe,SAAS;AAAA,YACpE;AAAA,YACA,eAAe;AAAA,IACvB;AAAA,EACF;AACF;AACA,SAAS,oBAAoB,IAAI,MAAM;AACrC,KAAG,EAAE,KAAK,MAAM,KAAK,KAAK,GAAG,MAAM,KAAK,CAAC;AAC3C;AACA,SAAS,kBAAkB,QAAQ,UAAU;AAC3C,QAAM,OAAO,OAAO,aAAa,YAAY,OAAO,aAAa,YAAY,OAAO,aAAa,YAAY,CAAC,QAAQ,IAAI;AAC1H,MAAI,SAAS,MAAM,KAAK,SAAS,OAAO,EAAE,KAAK,SAAS,QAAQ,KAAK,SAAS,SAAS,EAAE,GAAG;AAC1F,WAAO,sBAAsB,QAAQ,MAAM,CAAC,GAAG,MAAM,KAAK,CAAC;AAAA,EAC7D;AACA,SAAO,sBAAsB,QAAQ,UAAU,CAAC,GAAG,MAAM,SAAS,GAAG,GAAG,CAAC,CAAC;AAC5E;AACA,SAAS,mBAAmB,GAAG,IAAI,UAAU;AAC3C,MAAI,YAAY,MAAM;AACpB,eAAW,YAAY;AAAA,EACzB;AACA,MAAI,CAAC,SAAS,GAAG,IAAI,QAAQ,GAAG;AAC9B,UAAM,IAAI,MAAM,8BAA8B,mBAAmB,IAAI;AAAA,EACvE;AACF;AACA,SAAS,SAAS,GAAG,IAAI,UAAU;AACjC,MAAI,CAAC,SAAS,CAAC,KAAK,CAAC,SAAS,EAAE,GAAG;AACjC,WAAO;AAAA,EACT;AACA,MAAI,MAAM,CAAC,KAAK,MAAM,EAAE,KAAK,KAAK,IAAI,IAAI,EAAE,IAAI,UAAU;AACxD,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,oBAAoB,QAAQ,KAAK,MAAM;AAC9C,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,QAAI,OAAO,MAAM,OAAO,OAAO,MAAM,MAAM;AACzC,YAAM,IAAI,MAAM,sBAAsB,OAAO,YAAY,cAAc,MAAM;AAAA,IAC/E;AAAA,EACF;AACF;AACA,SAAS,wBAAwB,QAAQ,UAAU;AACjD,QAAM,cAAc,IAAI,aAAa,MAAM;AAC3C,QAAM,gBAAgB,IAAI,aAAa,QAAQ;AAC/C,MAAI,YAAY,WAAW,cAAc,QAAQ;AAC/C,UAAM,IAAI,MAAM,wCAAwC,cAAc,sBAAsB,YAAY,QAAQ;AAAA,EAClH;AACA,WAAS,KAAK,GAAG,KAAK,cAAc,QAAQ,MAAM;AAChD,QAAI,YAAY,QAAQ,cAAc,KAAK;AACzC,YAAM,IAAI,MAAM,iCAAiC,YAAY,cAAc,eAAe,YAAY,aAAa;AAAA,IACrH;AAAA,EACF;AACF;AACA,SAAS,cAAc,GAAG;AACxB,WAAS,KAAK,GAAG,KAAK,EAAE,QAAQ,MAAM;AACpC,UAAM,MAAM,EAAE;AACd,QAAI,MAAM,QAAQ,GAAG,GAAG;AACtB,oBAAc,GAAG;AAAA,IACnB,OAAO;AACL,QAAE,MAAM,aAAa,GAAG;AAAA,IAC1B;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,UAAU;AAGd,SAAS,KAAK,GAAG,GAAG;AAClB,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,OAAO,GAAG,EAAE,KAAK,CAAC;AAGtB,SAAS,UAAU,GAAG,GAAG;AACvB,MAAI,KAAK,gBAAgB,GAAG,KAAK,UAAU;AAC3C,MAAI,KAAK,gBAAgB,GAAG,KAAK,UAAU;AAC3C,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,KAAK,GAAG,GAAG;AAClB,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,MAAI,GAAG,UAAU,WAAW,GAAG,UAAU,SAAS;AAChD,WAAO,SAAS,IAAI,EAAE;AAAA,EACxB;AACA,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,QAAM,QAAQ,CAAC;AACf,SAAO,OAAO,UAAU,SAAS,QAAQ,KAAK;AAChD;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,KAAK,GAAG,GAAG;AAClB,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACxC,MAAI,GAAG,UAAU,aAAa;AAC5B,UAAM,SAAS,EAAE,GAAG,GAAG;AACvB,WAAO,OAAO,UAAU,YAAY,MAAM;AAAA,EAC5C,OAAO;AACL,UAAM,SAAS,EAAE,GAAG,GAAG;AACvB,WAAO,OAAO,UAAU,KAAK,MAAM;AAAA,EACrC;AACF;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,SAAS;AACtB,SAAO,MAAM,QAAQ,OAAO,GAAG,MAAM,4DAA4D;AACjG,SAAO,QAAQ,UAAU,GAAG,MAAM,uDAAuD,QAAQ,QAAQ;AACzG,QAAM,WAAW,QAAQ,IAAI,CAAC,IAAI,OAAO,gBAAgB,IAAI,UAAU,MAAM,MAAM,CAAC;AACpF,QAAM,cAAc,SAAS;AAC7B,WAAS,QAAQ,CAAC,OAAO;AACvB,QAAI,GAAG,UAAU,YAAY,OAAO;AAClC,YAAM,IAAI,MAAM,0DAA0D;AAAA,IAC5E;AAAA,EACF,CAAC;AACD,WAAS,QAAQ,CAAC,OAAO;AACvB,QAAI,CAAC,YAAY,GAAG,OAAO,YAAY,KAAK,GAAG;AAC7C,YAAM,IAAI,MAAM,0DAA0D;AAAA,IAC5E;AAAA,EACF,CAAC;AACD,QAAM,SAAS;AACf,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,KAAK,GAAG,OAAO,MAAM,WAAW,OAAO;AAC9C,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO,MAAM;AAChD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,SAAS;AAC/B,SAAO,OAAO,UAAU,KAAK,QAAQ,KAAK;AAC5C;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,KAAK,GAAG,OAAO,MAAM,WAAW,OAAO;AAC9C,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO,MAAM;AAChD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,SAAS;AAC/B,SAAO,OAAO,UAAU,KAAK,QAAQ,KAAK;AAC5C;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,QAAQ,GAAG,OAAO,GAAG;AAC5B,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AAC3C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,KAAK;AACrB,SAAO,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAC/C;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,QAAQ,GAAG,OAAO,GAAG;AAC5B,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AAC3C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,KAAK;AACrB,SAAO,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAC/C;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,OAAO,GAAG,GAAG;AACpB,MAAI,KAAK,gBAAgB,GAAG,KAAK,OAAO;AACxC,MAAI,KAAK,gBAAgB,GAAG,KAAK,OAAO;AACxC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,sBAAsB,YAAY,aAAae,UAAS,MAAM,aAAa,QAAQ,WAAW;AACrG,QAAM,gBAAgB,WAAW;AACjC,QAAM,eAAe,CAAC,GAAG,aAAa,aAAa;AACnD,QAAM,cAAc,wBAAwB,UAAU;AACtD,SAAO,kBAAkB,YAAY,cAAcA,UAAS,WAAW,MAAM,MAAM,MAAM,WAAW;AACtG;AACA,SAAS,kBAAkB,SAAS,YAAYA,UAAS,WAAW,MAAM,cAAc,aAAa,gBAAgB;AACnH,QAAM,CAAC,cAAc,WAAW,IAAI,gBAAgB,UAAU;AAC9D,MAAI;AACJ,MAAI,eAAe,gBAAgB;AACjC,kBAAc,CAAC,cAAc,aAAa,QAAQ,IAAI,QAAQ,EAAE;AAAA,EAClE,WAAW,eAAe,iBAAiB;AACzC,kBAAc,CAAC,cAAc,aAAa,QAAQ,IAAI,QAAQ,EAAE;AAAA,EAClE,OAAO;AACL,UAAM,IAAI,MAAM,sBAAsB,YAAY;AAAA,EACpD;AACA,SAAO,kBAAkB,SAAS,aAAaA,UAAS,WAAW,MAAM,cAAc,OAAO,UAAU;AAC1G;AACA,SAAS,kBAAkB,SAAS,YAAYA,UAAS,WAAW,MAAM,cAAc,aAAa,SAAS;AAC5G,QAAM,CAAC,aAAa,cAAc,WAAW,IAAI,iBAAiB,UAAU;AAC5E,MAAI;AACJ,MAAI;AACJ,MAAI,eAAe,SAAS;AAC1B,kBAAc;AACd,kBAAc,CAAC,aAAa,cAAc,aAAa,QAAQ,IAAI,QAAQ,EAAE;AAAA,EAC/E,WAAW,eAAe,SAAS;AACjC,kBAAc;AACd,kBAAc,CAAC,aAAa,cAAc,aAAa,QAAQ,IAAI,QAAQ,EAAE;AAAA,EAC/E,OAAO;AACL,UAAM,IAAI,MAAM,sBAAsB,YAAY;AAAA,EACpD;AACA,SAAO,kBAAkB,SAAS,aAAaA,UAAS,WAAW,MAAM,OAAO,aAAa,YAAY;AAC3G;AACA,SAAS,kBAAkB,SAAS,aAAaA,UAAS,WAAW,MAAM,cAAc,YAAY,OAAO,aAAa,gBAAgB;AACvI,MAAI,CAAC,WAAW,UAAU,SAAS,UAAU,IAAI,CAAC,IAAI,IAAI,IAAI,EAAE;AAChE,MAAI,eAAe,gBAAgB;AACjC,KAAC,WAAW,UAAU,SAAS,UAAU,IAAI;AAAA,EAC/C,WAAW,eAAe,iBAAiB;AACzC,KAAC,WAAW,YAAY,UAAU,OAAO,IAAI;AAAA,EAC/C,OAAO;AACL,UAAM,IAAI,MAAM,sBAAsB,YAAY;AAAA,EACpD;AACA,QAAM,CAAC,cAAc,aAAa,EAAE,cAAc,IAAI;AACtD,QAAM,CAAC,cAAc,WAAW,IAAI,gBAAgBA,QAAO;AAC3D,QAAM,CAAC,gBAAgB,aAAa,IAAI,gBAAgB,SAAS;AACjE,QAAM,wBAAwB,uBAAuB,cAAc,cAAc;AACjF,QAAM,uBAAuB,uBAAuB,aAAa,aAAa;AAC9E,QAAM,EAAE,SAAS,WAAW,SAAS,IAAI,iBAAiB,MAAM,UAAU,SAAS,cAAc,aAAa,uBAAuB,sBAAsB,cAAc,UAAU;AACnL,QAAM,cAAc,YAAY,iBAAiB,aAAa;AAC9D,MAAI;AACJ,MAAI,eAAe,iBAAiB;AAClC,eAAW,CAAC,WAAW,aAAa,WAAW,QAAQ;AAAA,EACzD,WAAW,eAAe,gBAAgB;AACxC,eAAW,CAAC,WAAW,WAAW,UAAU,WAAW;AAAA,EACzD;AACA,SAAO;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AACA,SAAS,kBAAkB,SAAS,aAAaA,UAAS,WAAW,MAAM,YAAY,OAAO,aAAa,gBAAgB,cAAc;AACvI,MAAI,CAAC,WAAW,SAAS,UAAU,SAAS,UAAU,IAAI,CAAC,IAAI,IAAI,IAAI,IAAI,EAAE;AAC7E,MAAI,eAAe,gBAAgB;AACjC,KAAC,WAAW,SAAS,UAAU,SAAS,UAAU,IAAI;AAAA,EACxD,WAAW,eAAe,iBAAiB;AACzC,KAAC,WAAW,YAAY,SAAS,UAAU,OAAO,IAAI;AAAA,EACxD,OAAO;AACL,UAAM,IAAI,MAAM,sBAAsB,YAAY;AAAA,EACpD;AACA,QAAM,CAAC,aAAa,cAAc,aAAa,EAAE,cAAc,IAAI;AACnE,QAAM,CAAC,aAAa,cAAc,WAAW,IAAI,iBAAiBA,QAAO;AACzE,QAAM,CAAC,eAAe,gBAAgB,aAAa,IAAI,iBAAiB,SAAS;AACjF,QAAM,uBAAuB,uBAAuB,aAAa,aAAa;AAC9E,QAAM,wBAAwB,uBAAuB,cAAc,cAAc;AACjF,QAAM,uBAAuB,uBAAuB,aAAa,aAAa;AAC9E,QAAM,EAAE,SAAS,UAAU,WAAW,SAAS,IAAI,mBAAmB,MAAM,SAAS,UAAU,SAAS,aAAa,cAAc,aAAa,sBAAsB,uBAAuB,sBAAsB,YAAY;AAC/N,QAAM,cAAc,YAAY,iBAAiB,aAAa;AAC9D,MAAI;AACJ,MAAI,eAAe,iBAAiB;AAClC,eAAW,CAAC,WAAW,aAAa,UAAU,WAAW,QAAQ;AAAA,EACnE,WAAW,eAAe,gBAAgB;AACxC,eAAW,CAAC,WAAW,UAAU,WAAW,UAAU,WAAW;AAAA,EACnE;AACA,SAAO;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AACA,SAAS,qBAAqB,SAAS,WAAW,QAAQ,SAAS,cAAc;AAC/E,MAAI,WAAW,MAAM;AACnB,cAAU,kBAAkB,SAAS,WAAW,MAAM;AAAA,EACxD;AACA,QAAM,YAAY,QAAQ;AAC1B,QAAM,YAAY,QAAQ;AAC1B,QAAM,aAAa,OAAO,YAAY,YAAY,IAAI,WAAW,SAAS,GAAG,YAAY;AACzF,QAAM,aAAa,OAAO,YAAY,YAAY,IAAI,WAAW,SAAS,GAAG,YAAY;AACzF,SAAO,CAAC,YAAY,UAAU;AAChC;AACA,SAAS,qBAAqB,SAAS,WAAW,aAAa,QAAQ,SAAS,cAAc;AAC5F,MAAI,WAAW,MAAM;AACnB,cAAU,kBAAkB,SAAS,WAAW,MAAM;AAAA,EACxD;AACA,QAAM,aAAa,QAAQ;AAC3B,QAAM,YAAY,QAAQ;AAC1B,QAAM,YAAY,QAAQ;AAC1B,QAAM,eAAe,OAAO,aAAa,YAAY,IAAI,WAAW,SAAS,GAAG,YAAY;AAC5F,QAAM,aAAa,OAAO,YAAY,YAAY,IAAI,WAAW,SAAS,GAAG,YAAY;AACzF,QAAM,aAAa,OAAO,YAAY,YAAY,IAAI,WAAW,SAAS,GAAG,YAAY;AACzF,SAAO,CAAC,cAAc,YAAY,YAAY,WAAW;AAC3D;AACA,SAAS,kBAAkB,YAAY,WAAW,QAAQ,WAAW,GAAG;AACtE,QAAM,qBAAqB,uBAAuB,WAAW,QAAQ;AACrE,SAAO,KAAK,OAAO,WAAW,MAAM,SAAS,KAAK,SAAS,sBAAsB,CAAC;AACpF;AACA,SAAS,gBAAgB,OAAO;AAC9B,MAAI,OAAO,UAAU,UAAU;AAC7B,WAAO,CAAC,OAAO,OAAO,KAAK;AAAA,EAC7B;AACA,MAAI,MAAM,WAAW,GAAG;AACtB,WAAO,CAAC,MAAM,IAAI,MAAM,IAAI,CAAC;AAAA,EAC/B;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,OAAO;AAC/B,SAAO,OAAO,UAAU,WAAW,CAAC,OAAO,OAAO,KAAK,IAAI;AAC7D;AACA,SAAS,uBAAuB,YAAY,UAAU;AACpD,MAAI,YAAY,GAAG;AACjB,WAAO;AAAA,EACT;AACA,SAAO,cAAc,aAAa,MAAM,WAAW;AACrD;AACA,SAAS,iBAAiB,MAAM,UAAU,SAAS,cAAc,aAAa,cAAc,aAAa,cAAc,YAAY;AACjI,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI,OAAO,SAAS,UAAU;AAC5B,UAAM,UAAU,SAAS,IAAI,UAAU;AACvC,cAAU,EAAE,KAAK,MAAM,QAAQ,MAAM,MAAM,MAAM,OAAO,MAAM,MAAM,QAAQ;AAC5E,UAAM,WAAW,qBAAqB,CAAC,UAAU,OAAO,GAAG,cAAc,cAAc,MAAM,YAAY;AACzG,gBAAY,SAAS;AACrB,eAAW,SAAS;AAAA,EACtB,WAAW,SAAS,QAAQ;AAC1B,gBAAY,KAAK,KAAK,WAAW,YAAY;AAC7C,eAAW,KAAK,KAAK,UAAU,WAAW;AAC1C,UAAM,iBAAiB,KAAK,IAAI,IAAI,YAAY,KAAK,eAAe,eAAe,QAAQ;AAC3F,UAAM,gBAAgB,KAAK,IAAI,IAAI,WAAW,KAAK,cAAc,cAAc,OAAO;AACtF,UAAM,MAAM,KAAK,MAAM,iBAAiB,CAAC;AACzC,UAAM,SAAS,iBAAiB;AAChC,UAAM,OAAO,KAAK,MAAM,gBAAgB,CAAC;AACzC,UAAM,QAAQ,gBAAgB;AAC9B,cAAU,EAAE,KAAK,QAAQ,MAAM,OAAO,MAAM,OAAO;AAAA,EACrD,WAAW,SAAS,SAAS;AAC3B,cAAU,EAAE,KAAK,GAAG,QAAQ,GAAG,MAAM,GAAG,OAAO,GAAG,MAAM,QAAQ;AAChE,gBAAY,KAAK,MAAM,WAAW,eAAe,KAAK,YAAY;AAClE,eAAW,KAAK,MAAM,UAAU,cAAc,KAAK,WAAW;AAAA,EAChE,WAAW,OAAO,SAAS,UAAU;AACnC,UAAM,MAAM,eAAe,iBAAiB,KAAK,GAAG,KAAK,KAAK,GAAG;AACjE,UAAM,SAAS,eAAe,iBAAiB,KAAK,GAAG,KAAK,KAAK,GAAG;AACpE,UAAM,OAAO,eAAe,iBAAiB,KAAK,GAAG,KAAK,KAAK,GAAG;AAClE,UAAM,QAAQ,eAAe,iBAAiB,KAAK,GAAG,KAAK,KAAK,GAAG;AACnE,UAAM,UAAU,QAAQ,KAAK,WAAW,KAAK,SAAS,KAAK,UAAU,IAAI,UAAU;AACnF,cAAU,EAAE,KAAK,QAAQ,MAAM,OAAO,MAAM,QAAQ;AACpD,gBAAY,OAAO,WAAW,eAAe,MAAM,UAAU,eAAe,GAAG,YAAY;AAC3F,eAAW,OAAO,UAAU,cAAc,OAAO,SAAS,cAAc,GAAG,YAAY;AAAA,EACzF,OAAO;AACL,UAAM,MAAM,8BAA8B,MAAM;AAAA,EAClD;AACA,SAAO,EAAE,SAAS,WAAW,SAAS;AACxC;AACA,SAAS,mBAAmB,MAAM,SAAS,UAAU,SAAS,aAAa,cAAc,aAAa,aAAa,cAAc,aAAa,cAAc;AAC1J,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI,OAAO,SAAS,UAAU;AAC5B,UAAM,UAAU,SAAS,IAAI,UAAU;AACvC,cAAU;AAAA,MACR,KAAK;AAAA,MACL,QAAQ;AAAA,MACR,MAAM;AAAA,MACN,OAAO;AAAA,MACP,OAAO;AAAA,MACP,MAAM;AAAA,MACN,MAAM;AAAA,IACR;AACA,UAAM,WAAW,qBAAqB,CAAC,SAAS,UAAU,SAAS,CAAC,GAAG,aAAa,GAAG,aAAa,MAAM,YAAY;AACtH,eAAW,SAAS;AACpB,gBAAY,SAAS;AACrB,eAAW,SAAS;AAAA,EACtB,WAAW,SAAS,QAAQ;AAC1B,eAAW,KAAK,KAAK,UAAU,WAAW;AAC1C,gBAAY,KAAK,KAAK,WAAW,YAAY;AAC7C,eAAW,KAAK,KAAK,UAAU,WAAW;AAC1C,UAAM,iBAAiB,WAAW,KAAK,cAAc,cAAc;AACnE,UAAM,kBAAkB,YAAY,KAAK,eAAe,eAAe;AACvE,UAAM,iBAAiB,WAAW,KAAK,cAAc,cAAc;AACnE,UAAM,QAAQ,KAAK,MAAM,gBAAgB,CAAC;AAC1C,UAAM,OAAO,gBAAgB;AAC7B,UAAM,MAAM,KAAK,MAAM,iBAAiB,CAAC;AACzC,UAAM,SAAS,iBAAiB;AAChC,UAAM,OAAO,KAAK,MAAM,gBAAgB,CAAC;AACzC,UAAM,QAAQ,gBAAgB;AAC9B,cAAU,EAAE,KAAK,QAAQ,MAAM,OAAO,OAAO,MAAM,MAAM,OAAO;AAAA,EAClE,WAAW,SAAS,SAAS;AAC3B,cAAU;AAAA,MACR,KAAK;AAAA,MACL,QAAQ;AAAA,MACR,MAAM;AAAA,MACN,OAAO;AAAA,MACP,OAAO;AAAA,MACP,MAAM;AAAA,MACN,MAAM;AAAA,IACR;AACA,eAAW,KAAK,MAAM,UAAU,cAAc,KAAK,WAAW;AAC9D,gBAAY,KAAK,MAAM,WAAW,eAAe,KAAK,YAAY;AAClE,eAAW,KAAK,MAAM,UAAU,cAAc,KAAK,WAAW;AAAA,EAChE,OAAO;AACL,UAAM,MAAM,8BAA8B,MAAM;AAAA,EAClD;AACA,SAAO,EAAE,SAAS,UAAU,WAAW,SAAS;AAClD;AACA,SAAS,MAAM,OAAO,cAAc;AAClC,MAAI,CAAC,cAAc;AACjB,WAAO,KAAK,MAAM,KAAK;AAAA,EACzB;AACA,UAAQ;AAAA,SACD;AACH,aAAO,KAAK,MAAM,KAAK;AAAA,SACpB;AACH,aAAO,KAAK,KAAK,KAAK;AAAA,SACnB;AACH,aAAO,KAAK,MAAM,KAAK;AAAA;AAEvB,YAAM,IAAI,MAAM,wBAAwB,cAAc;AAAA;AAE5D;AACA,SAAS,kBAAkB,OAAO;AAChC,QAAM,CAAC,MAAM,MAAM,IAAI,IAAI,gBAAgB,KAAK;AAChD,SAAO,SAAS,KAAK,SAAS,KAAK,SAAS;AAC9C;AACA,SAAS,+BAA+BA,UAAS,WAAW;AAC1D,SAAO,kBAAkBA,QAAO,KAAK,kBAAkB,SAAS;AAClE;AACA,SAAS,wBAAwB,YAAY;AAC3C,MAAI,eAAe,QAAQ;AACzB,WAAO;AAAA,EACT,WAAW,eAAe,QAAQ;AAChC,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,sBAAsB,YAAY;AAAA,EACpD;AACF;AACA,SAAS,0BAA0B,QAAQ,MAAM,iBAAiB;AAChE,MAAI,mBAAmB,MAAM;AAC3B,QAAI,OAAO,SAAS,UAAU;AAC5B,YAAM,MAAM,YAAY,6DAA6D,+BAA+B,OAAO;AAAA,IAC7H,WAAW,OAAO,SAAS,UAAU;AACnC,aAAO,MAAM,IAAI,GAAG,MAAM,YAAY,6DAA6D,+BAA+B,OAAO;AAAA,IAC3I,WAAW,OAAO,SAAS,UAAU;AACnC,WAAK,QAAQ,CAAC,OAAO;AACnB,WAAG,QAAQ,CAAC,MAAM;AAChB,iBAAO,MAAM,CAAC,GAAG,MAAM,YAAY,6DAA6D,+BAA+B,IAAI;AAAA,QACrI,CAAC;AAAA,MACH,CAAC;AAAA,IACH,OAAO;AACL,YAAM,MAAM,YAAY,sCAAsC,MAAM;AAAA,IACtE;AAAA,EACF;AACF;AAGA,SAAS,SAAS,GAAG,OAAO;AAC1B,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW,mBAAmB;AACjE,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM;AACtB,SAAO,OAAO,UAAU,SAAS,QAAQ,KAAK;AAChD;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,SAAS,GAAG,YAAYA,UAAS,MAAM,iBAAiB;AAC/D,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW,SAAS;AACvD,QAAM,YAAY;AAClB,SAAO,+BAA+BA,UAAS,SAAS,GAAG,MAAM,wEAAwEA,2BAA0B,YAAY;AAC/K,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,mDAAmD,IAAI,OAAO;AAC3F,4BAA0B,WAAW,MAAM,eAAe;AAC1D,QAAM,SAAS,EAAE,GAAG,IAAI;AACxB,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB;AAChE,MAAI,MAAM,OAAO,UAAU,SAAS,QAAQ,KAAK;AACjD,QAAM,KAAK,KAAK,GAAG,KAAK;AACxB,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,WAAW,GAAG,YAAYA,UAAS,MAAM,iBAAiB,aAAa,SAAS;AACvF,QAAM,KAAK,gBAAgB,GAAG,KAAK,aAAa,SAAS;AACzD,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC3E;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,qDAAqD,IAAI,OAAO;AAC7F,SAAO,eAAe,SAAS,MAAM,gFAAgF,YAAY;AACjI,4BAA0B,aAAa,MAAM,eAAe;AAC5D,QAAM,SAAS,EAAE,GAAG,IAAI;AACxB,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,iBAAiB,WAAW;AAC5E,MAAI,MAAM,OAAO,UAAU,WAAW,QAAQ,KAAK;AACnD,QAAM,KAAK,KAAK,IAAI,KAAK;AACzB,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAC9E;AACA,SAAO;AACT;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,QAAQ,SAAS,OAAO,GAAG;AAClC,SAAO,QAAQ,UAAU,GAAG,MAAM,oCAAoC;AACtE,QAAM,WAAW,qBAAqB,SAAS,WAAW,UAAU,mBAAmB;AACvF,MAAI,SAAS,GAAG,UAAU,aAAa;AACrC,aAAS,QAAQ,CAAC,YAAY;AAC5B,UAAI,QAAQ,UAAU,aAAa;AACjC,cAAM,IAAI,MAAM;AAAA,uBACD,QAAQ,SAAS;AAAA,MAClC;AAAA,IACF,CAAC;AAAA,EACH;AACA,MAAI,SAAS,WAAW,GAAG;AACzB,WAAO,MAAM,SAAS,EAAE;AAAA,EAC1B;AACA,QAAM,SAAS;AACf,QAAM,OAAO,EAAE,KAAK;AACpB,SAAO,OAAO,UAAU,QAAQ,QAAQ,IAAI;AAC9C;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,SAAS,GAAG;AACnB,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW,SAAS;AACvD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,SAAS,MAAM;AACzC;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,OAAO,GAAG,OAAOZ,OAAM;AAC9B,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS,mBAAmB;AAC/D,MAAI,GAAG,SAAS,GAAG;AACjB,UAAM,IAAI,MAAM,gCAAgC;AAAA,EAClD;AACA,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,OAAO,MAAAA,MAAK;AAC5B,SAAO,OAAO,UAAU,OAAO,QAAQ,KAAK;AAC9C;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ,SAAS;AACpD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,QAAQ,GAAG,EAAE,MAAM,CAAC;AAGxB,SAAS,eAAe,YAAY,YAAY,UAAU,MAAM,GAAG,GAAG;AACpE,QAAM,cAAc,gBAAgB,YAAY,cAAc,eAAe;AAC7E,QAAM,cAAc,gBAAgB,YAAY,cAAc,eAAe;AAC7E,QAAM,YAAY,gBAAgB,UAAU,YAAY,eAAe;AACvE,QAAM,QAAQ,gBAAgB,MAAM,QAAQ,eAAe;AAC3D,QAAM,KAAK,gBAAgB,GAAG,KAAK,eAAe;AAClD,QAAM,KAAK,gBAAgB,GAAG,KAAK,eAAe;AAClD,QAAM,WAAW,OAAO,CAAC,OAAO,EAAE,GAAG,CAAC;AACtC,QAAM,WAAW,OAAO,UAAU,WAAW;AAC7C,QAAM,MAAM,KAAK,UAAU,SAAS;AACpC,QAAM,YAAY,IAAI,MAAM;AAC5B,QAAM,YAAY,IAAI,MAAM,KAAK;AACjC,QAAM,YAAY,CAAC,WAAW,SAAS;AACvC,QAAM,KAAK,MAAM,KAAK,CAAC,GAAG,CAAC,GAAG,SAAS;AACvC,QAAM,IAAI,MAAM,KAAK,CAAC,GAAG,SAAS,GAAG,SAAS;AAC9C,QAAM,IAAI,MAAM,KAAK,CAAC,GAAG,YAAY,CAAC,GAAG,SAAS;AAClD,QAAM,IAAI,MAAM,KAAK,CAAC,GAAG,YAAY,CAAC,GAAG,SAAS;AAClD,QAAM,OAAO,KAAK,IAAI,QAAQ,EAAE,GAAG,MAAM,CAAC,CAAC,GAAG,IAAI,IAAI,QAAQ,KAAK,aAAa,CAAC,CAAC,CAAC,CAAC;AACpF,QAAM,OAAO,IAAI,MAAM,IAAI,GAAG,QAAQ,CAAC,CAAC;AACxC,SAAO,CAAC,MAAM,IAAI;AACpB;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,gBAAgB,GAAG,YAAY,OAAO;AAC7C,QAAM,KAAK,gBAAgB,GAAG,KAAK,gBAAgB;AACnD,QAAM,QAAQ,WAAW,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAC/C,SAAO,GAAG,QAAQ,IAAI,WAAW,QAAQ,MAAM,iBAAiB,GAAG,+CAA+C,WAAW,QAAQ;AACrI,SAAO,MAAM,WAAW,WAAW,QAAQ,MAAM,mBAAmB,MAAM,oDAAoD,WAAW,QAAQ;AACjJ,SAAO,GAAG,MAAM,KAAK,UAAU,GAAG,MAAM,yBAAyB,GAAG,MAAM,wEAAwE,WAAW,KAAK,KAAK,SAAS,OAAO;AACvL,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,YAAY,MAAM;AAClC,SAAO,OAAO,UAAU,gBAAgB,QAAQ,KAAK;AACvD;AACA,IAAI,iBAAiB,GAAG,EAAE,gBAAgB,CAAC;AAG3C,SAAS,MAAM,GAAG;AAChB,MAAI;AACJ,MAAI,EAAE,SAAS,KAAK,EAAE,SAAS,GAAG;AAChC,UAAM,QAAQ,GAAG,CAAC,GAAG,GAAG,GAAG,EAAE,IAAI,CAAC;AAAA,EACpC,WAAW,EAAE,SAAS,GAAG;AACvB,UAAM,QAAQ,GAAG,CAAC,GAAG,GAAG,EAAE,MAAM,IAAI,EAAE,MAAM,EAAE,CAAC;AAAA,EACjD,WAAW,EAAE,SAAS,GAAG;AACvB,UAAM,QAAQ,GAAG,CAAC,GAAG,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,EAAE,CAAC;AAAA,EAC1D,OAAO;AACL,UAAM;AAAA,EACR;AACA,SAAO;AACT;AAGA,SAAS,WAAW,GAAG,OAAO,UAAU,QAAQqB,SAAQ,iBAAiB;AACvE,MAAI,mBAAmB,MAAM;AAC3B,sBAAkB;AAAA,EACpB;AACA,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,QAAQ,gBAAgB,OAAO,QAAQ,WAAW;AACxD,QAAM,YAAY,gBAAgB,UAAU,YAAY,WAAW;AACnE,MAAI;AACJ,MAAIA,WAAU,MAAM;AAClB,aAAS,gBAAgBA,SAAQ,SAAS,WAAW;AAAA,EACvD;AACA,MAAI;AACJ,MAAI,UAAU,MAAM;AAClB,cAAU,gBAAgB,QAAQ,UAAU,WAAW;AAAA,EACzD;AACA,SAAO,MAAM,SAAS,UAAU,MAAM,MAAM,8EAA8E;AAC1H,SAAO,WAAW,QAAQ,MAAM,SAAS,QAAQ,MAAM,MAAM,4EAA4E;AACzI,SAAO,UAAU,QAAQ,MAAM,SAAS,OAAO,MAAM,MAAM,2EAA2E;AACtI,QAAM,MAAM,MAAM,EAAE;AACpB,QAAM,SAAS;AAAA,IACb,GAAG;AAAA,IACH,OAAO;AAAA,IACP,QAAQ;AAAA,IACR,MAAM;AAAA,IACN,UAAU;AAAA,EACZ;AACA,QAAM,QAAQ,EAAE,gBAAgB;AAChC,QAAM,MAAM,OAAO,UAAU,gBAAgB,QAAQ,KAAK;AAC1D,SAAO,QAAQ,KAAK,GAAG,KAAK;AAC9B;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,aAAa,GAAG,OAAO,UAAU,QAAQA,SAAQ,iBAAiB;AACzE,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,QAAQ,gBAAgB,OAAO,QAAQ,WAAW;AACxD,QAAM,YAAY,gBAAgB,UAAU,YAAY,WAAW;AACnE,MAAI;AACJ,MAAIA,WAAU,MAAM;AAClB,aAAS,gBAAgBA,SAAQ,SAAS,WAAW;AAAA,EACvD;AACA,MAAI;AACJ,MAAI,UAAU,MAAM;AAClB,cAAU,gBAAgB,QAAQ,UAAU,WAAW;AAAA,EACzD;AACA,SAAO,GAAG,SAAS,GAAG,MAAM,uDAAuD,GAAG,OAAO;AAC7F,SAAO,MAAM,SAAS,KAAK,MAAM,SAAS,GAAG,MAAM,oEAAoE,MAAM,OAAO;AACpI,SAAO,UAAU,SAAS,KAAK,UAAU,SAAS,GAAG,MAAM,wEAAwE,UAAU,OAAO;AACpJ,MAAI,UAAU,MAAM;AAClB,WAAO,OAAO,SAAS,KAAK,OAAO,SAAS,GAAG,MAAM,qEAAqE,OAAO,OAAO;AAAA,EAC1I;AACA,MAAI,WAAW,MAAM;AACnB,WAAO,QAAQ,SAAS,KAAK,QAAQ,SAAS,GAAG,MAAM,sEAAsE,QAAQ,OAAO;AAAA,EAC9I;AACA,SAAO,UAAU,IAAI,OAAO,WAAW,SAAS,QAAQ,eAAe;AACzE;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,aAAa,GAAG,OAAO,UAAU,QAAQA,SAAQ,iBAAiB;AACzE,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,QAAQ,gBAAgB,OAAO,QAAQ,WAAW;AACxD,QAAM,YAAY,gBAAgB,UAAU,YAAY,WAAW;AACnE,MAAI;AACJ,MAAIA,WAAU,MAAM;AAClB,aAAS,gBAAgBA,SAAQ,SAAS,WAAW;AAAA,EACvD;AACA,MAAI;AACJ,MAAI,UAAU,MAAM;AAClB,cAAU,gBAAgB,QAAQ,UAAU,WAAW;AAAA,EACzD;AACA,SAAO,GAAG,SAAS,GAAG,MAAM,uDAAuD,GAAG,OAAO;AAC7F,SAAO,MAAM,SAAS,KAAK,MAAM,SAAS,GAAG,MAAM,oEAAoE,MAAM,OAAO;AACpI,SAAO,UAAU,SAAS,KAAK,UAAU,SAAS,GAAG,MAAM,wEAAwE,UAAU,OAAO;AACpJ,MAAI,UAAU,MAAM;AAClB,WAAO,OAAO,SAAS,KAAK,OAAO,SAAS,GAAG,MAAM,qEAAqE,OAAO,OAAO;AAAA,EAC1I;AACA,MAAI,WAAW,MAAM;AACnB,WAAO,QAAQ,SAAS,KAAK,QAAQ,SAAS,GAAG,MAAM,sEAAsE,QAAQ,OAAO;AAAA,EAC9I;AACA,SAAO,UAAU,IAAI,OAAO,WAAW,SAAS,QAAQ,eAAe;AACzE;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,aAAa,GAAG,OAAO,UAAU,QAAQA,SAAQ,iBAAiB;AACzE,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,QAAQ,gBAAgB,OAAO,QAAQ,WAAW;AACxD,QAAM,YAAY,gBAAgB,UAAU,YAAY,WAAW;AACnE,MAAI;AACJ,MAAIA,WAAU,MAAM;AAClB,aAAS,gBAAgBA,SAAQ,SAAS,WAAW;AAAA,EACvD;AACA,MAAI;AACJ,MAAI,UAAU,MAAM;AAClB,cAAU,gBAAgB,QAAQ,UAAU,WAAW;AAAA,EACzD;AACA,SAAO,GAAG,SAAS,GAAG,MAAM,uDAAuD,GAAG,OAAO;AAC7F,SAAO,MAAM,SAAS,KAAK,MAAM,SAAS,GAAG,MAAM,oEAAoE,MAAM,OAAO;AACpI,SAAO,UAAU,SAAS,KAAK,UAAU,SAAS,GAAG,MAAM,wEAAwE,UAAU,OAAO;AACpJ,MAAI,UAAU,MAAM;AAClB,WAAO,OAAO,SAAS,KAAK,OAAO,SAAS,GAAG,MAAM,qEAAqE,OAAO,OAAO;AAAA,EAC1I;AACA,MAAI,WAAW,MAAM;AACnB,WAAO,QAAQ,SAAS,KAAK,QAAQ,SAAS,GAAG,MAAM,sEAAsE,QAAQ,OAAO;AAAA,EAC9I;AACA,SAAO,UAAU,IAAI,OAAO,WAAW,SAAS,QAAQ,eAAe;AACzE;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,UAAU,GAAG,SAASrB,OAAM;AACnC,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU;AAC7C,QAAM,WAAW,gBAAgB,SAAS,WAAW,UAAU;AAC/D,SAAO,GAAG,UAAU,SAAS,MAAM,yDAAyD,GAAG,OAAO;AACtG,SAAOA,SAAQ,GAAG,MAAM,sCAAsCA,QAAO;AACrE,SAAO,SAAS,SAAS,GAAG,QAAQ,SAAS,SAAS,GAAG,MAAM,gGAAgG,GAAG,yBAAyB,SAAS,QAAQ;AAC5M,QAAM,SAAS,EAAE,GAAG,IAAI,SAAS,SAAS;AAC1C,QAAM,QAAQ,EAAE,MAAAA,MAAK;AACrB,SAAO,OAAO,UAAU,UAAU,QAAQ,KAAK;AACjD;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,eAAe,IAAI,IAAI;AAC9B,QAAM,cAAc,gBAAgB,IAAI,MAAM,iBAAiB,OAAO;AACtE,QAAM,cAAc,gBAAgB,IAAI,MAAM,iBAAiB,OAAO;AACtE,MAAI,YAAY,SAAS,GAAG;AAC1B,UAAM,IAAI,MAAM,oEAAoE,YAAY,MAAM;AAAA,EACxG;AACA,MAAI,YAAY,SAAS,GAAG;AAC1B,UAAM,IAAI,MAAM,qEAAqE,YAAY,MAAM;AAAA,EACzG;AACA,QAAM,SAAS,EAAE,IAAI,aAAa,IAAI,YAAY;AAClD,SAAO,OAAO,UAAU,eAAe,MAAM;AAC/C;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,aAAa,GAAG,OAAO;AAC9B,MAAI,SAAS,gBAAgB,GAAG,eAAe,GAAG;AAClD,QAAM,SAAS,OAAO;AACtB,MAAI,MAAM,KAAK,CAAC,MAAM,EAAE,IAAI,MAAM,IAAI,MAAM,CAAC,GAAG;AAC9C,UAAM,IAAI,MAAM,2CAA2C,SAAS;AAAA,EACtE;AACA,MAAI,MAAM,SAAS,OAAO,MAAM;AAC9B,UAAM,IAAI,MAAM,+BAA+B,MAAM,uBAAuB,OAAO,OAAO;AAAA,EAC5F;AACA,MAAI,MAAM,SAAS,OAAO,MAAM;AAC9B,UAAM,WAAW,OAAO,MAAM,MAAM;AACpC,WAAO,SAAS,SAAS,MAAM,QAAQ;AACrC,eAAS,QAAQ,CAAC;AAAA,IACpB;AACA,aAAS,QAAQ,QAAQ,QAAQ;AAAA,EACnC;AACA,QAAM,aAAa,OAAO;AAC1B,QAAM,OAAO,MAAM,KAAK,KAAK;AAC7B,WAAS,KAAK,MAAM,SAAS,GAAG,MAAM,GAAG,MAAM;AAC7C,QAAI,WAAW,QAAQ,MAAM,KAAK;AAChC,WAAK,MAAM;AAAA,IACb,WAAW,OAAO,MAAM,QAAQ,GAAG;AACjC,YAAM,IAAI,MAAM,mBAAmB,mCAAmC,SAAS;AAAA,IACjF;AAAA,EACF;AACA,QAAM,OAAO,KAAK,IAAI,CAAC,IAAI,OAAO,KAAK,IAAI,KAAK,EAAE,EAAE,OAAO,CAAC,OAAO,MAAM,CAAC;AAC1E,MAAI,KAAK,WAAW,GAAG;AACrB,WAAO,MAAM,MAAM;AAAA,EACrB;AACA,QAAM,SAAS,EAAE,GAAG,OAAO;AAC3B,QAAM,QAAQ,EAAE,KAAK;AACrB,SAAO,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC7C;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ,SAAS;AACpD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,aAAa,GAAG,cAAc,cAAc;AACnD,QAAM,KAAK,gBAAgB,GAAG,KAAK,aAAa;AAChD,SAAO,gBAAgB,cAAc,MAAM,uBAAuB,oDAAoD,gBAAgB;AACtI,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,cAAc,aAAa;AAC3C,SAAO,OAAO,UAAU,aAAa,QAAQ,KAAK;AACpD;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,UAAU,SAAS;AAC1B,SAAO,OAAO,SAAS,CAAC;AAC1B;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,UAAU,SAAS,MAAM;AAChC,SAAO,OAAO,SAAS,IAAI;AAC7B;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,UAAU,SAAS,MAAM;AAChC,SAAO,OAAO,SAAS,IAAI;AAC7B;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,UAAU,SAAS,MAAM;AAChC,SAAO,OAAO,SAAS,IAAI;AAC7B;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,QAAQ,GAAG,QAAQY,UAAS,MAAM,aAAa,QAAQ,YAAY,CAAC,GAAG,CAAC,GAAG,iBAAiB;AACnG,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU,SAAS;AACtD,QAAM,UAAU,gBAAgB,QAAQ,UAAU,UAAU,SAAS;AACrE,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,uDAAuD,IAAI,OAAO;AAC/F,SAAO,QAAQ,SAAS,GAAG,MAAM,wDAAwD,QAAQ,OAAO;AACxG,4BAA0B,UAAU,MAAM,eAAe;AACzD,QAAM,UAAU,eAAe,SAAS,IAAI,MAAM,KAAK,IAAI,MAAM;AACjE,SAAO,YAAY,QAAQ,MAAM,IAAI,MAAM,oCAAoC,8CAA8C,QAAQ,MAAM,KAAK;AAChJ,SAAO,+BAA+BA,UAAS,SAAS,GAAG,MAAM,uEAAuEA,2BAA0B,YAAY;AAC9K,QAAM,SAAS,EAAE,GAAG,KAAK,QAAQ,QAAQ;AACzC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB;AAC3E,QAAM,MAAM,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAClD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,QAAQ,GAAG,QAAQ,QAAQ,MAAM,aAAa,OAAO,WAAW,GAAG,iBAAiB;AAC3F,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AAC3C,QAAM,UAAU,gBAAgB,QAAQ,UAAU,QAAQ;AAC1D,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EACjD;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,uDAAuD,IAAI,OAAO;AAC/F,SAAO,QAAQ,SAAS,GAAG,MAAM,wDAAwD,QAAQ,OAAO;AACxG,4BAA0B,UAAU,MAAM,eAAe;AACzD,SAAO,IAAI,MAAM,OAAO,QAAQ,MAAM,IAAI,MAAM,oCAAoC,IAAI,MAAM,yCAAyC,QAAQ,MAAM,KAAK;AAC1J,SAAO,+BAA+B,QAAQ,QAAQ,GAAG,MAAM,oEAAoE,wBAAwB,WAAW;AACtK,SAAO,eAAe,OAAO,MAAM,sCAAsC,iDAAiD;AAC1H,QAAM,WAAW,QAAQ,SAAS,CAAC,GAAG,QAAQ,MAAM,IAAI,QAAQ,MAAM,IAAI,QAAQ,MAAM,EAAE,CAAC;AAC3F,QAAM,UAAU,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,GAAG,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAC1E,QAAMA,WAAU,CAAC,GAAG,MAAM;AAC1B,QAAM,YAAY,CAAC,GAAG,QAAQ;AAC9B,QAAM,mBAAmB;AACzB,QAAM,MAAM,OAAO,SAAS,UAAUA,UAAS,MAAM,kBAAkB,WAAW,eAAe;AACjG,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAClD;AACA,SAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAChE;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,qBAAqB,QAAQ,IAAI,QAAQA,UAAS,MAAM,aAAa,QAAQ,iBAAiB;AACrG,SAAO,OAAO,WAAW,GAAG,MAAM,MAAM,sBAAsB,OAAO,2BAA2B,GAAG,kBAAkB;AACrH,MAAI,WAAW;AACf,MAAI,OAAO;AACX,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,WAAO,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAC7D,eAAW,CAAC,GAAG,OAAO,IAAI,OAAO,IAAI,OAAO,EAAE;AAAA,EAChD;AACA,SAAO,SAAS,WAAW,GAAG,MAAM,qEAAqE,SAAS,SAAS;AAC3H,SAAO,KAAK,SAAS,GAAG,MAAM,4DAA4D,KAAK,MAAM;AACrG,SAAO,OAAO,SAAS,GAAG,MAAM,gEAAgE,OAAO,MAAM;AAC7G,QAAM,UAAU,eAAe,SAAS,SAAS,KAAK,SAAS;AAC/D,QAAM,WAAW,eAAe,SAAS,KAAK,MAAM,KAAK,KAAK,MAAM;AACpE,SAAO,YAAY,OAAO,MAAM,IAAI,MAAM,4CAA4C,8CAA8C,OAAO,MAAM,KAAK;AACtJ,SAAO,aAAa,OAAO,MAAM,IAAI,MAAM,6CAA6C,gDAAgD,OAAO,MAAM,KAAK;AAC1J,4BAA0B,kBAAkB,MAAM,eAAe;AACjE,QAAM,SAAS,EAAE,IAAI,MAAM,OAAO;AAClC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,iBAAiB,YAAY,SAAS;AACtF,QAAM,MAAM,OAAO,UAAU,qBAAqB,QAAQ,KAAK;AAC/D,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,sBAAsB,GAAG,EAAE,qBAAqB,CAAC;AAGrD,SAAS,iBAAiB,GAAG,QAAQ,aAAaA,UAAS,MAAM,iBAAiB;AAChF,QAAM,KAAK,gBAAgB,GAAG,KAAK,iBAAiB;AACpD,QAAM,UAAU,gBAAgB,QAAQ,UAAU,iBAAiB;AACnE,SAAO,oBAAoB,aAAa,IAAI,SAASA,UAAS,MAAM,QAAQ,eAAe;AAC7F;AACA,IAAI,kBAAkB,GAAG,EAAE,iBAAiB,CAAC;AAG7C,SAAS,QAAQ,GAAG,QAAQA,UAAS,MAAM,aAAa,SAAS,YAAY,CAAC,GAAG,GAAG,CAAC,GAAG;AACtF,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AAC3C,QAAM,UAAU,gBAAgB,QAAQ,UAAU,QAAQ;AAC1D,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC3E;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,uDAAuD,IAAI,OAAO;AAC/F,SAAO,QAAQ,SAAS,GAAG,MAAM,wDAAwD,QAAQ,OAAO;AACxG,SAAO,IAAI,MAAM,OAAO,QAAQ,MAAM,IAAI,MAAM,oCAAoC,IAAI,MAAM,yCAAyC,QAAQ,MAAM,KAAK;AAC1J,SAAO,+BAA+BA,UAAS,SAAS,GAAG,MAAM,uEAAuEA,2BAA0B,YAAY;AAC9K,SAAO,eAAe,SAAS,MAAM,sCAAsC,mDAAmD;AAC9H,QAAM,SAAS,EAAE,GAAG,KAAK,QAAQ,QAAQ;AACzC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,UAAU;AAC1D,QAAM,MAAM,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAClD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAC9E;AACA,SAAO;AACT;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,qBAAqB,QAAQ,IAAI,QAAQA,UAAS,MAAM;AAC/D,SAAO,OAAO,WAAW,GAAG,MAAM,MAAM,sBAAsB,OAAO,2BAA2B,GAAG,kBAAkB;AACrH,MAAI,WAAW;AACf,MAAI,OAAO;AACX,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,WAAO,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAC1E,eAAW,CAAC,GAAG,OAAO,IAAI,OAAO,IAAI,OAAO,IAAI,OAAO,EAAE;AAAA,EAC3D;AACA,QAAM,UAAU,SAAS;AACzB,QAAM,WAAW,KAAK,MAAM;AAC5B,SAAO,SAAS,WAAW,GAAG,MAAM,qEAAqE,SAAS,SAAS;AAC3H,SAAO,KAAK,SAAS,GAAG,MAAM,4DAA4D,KAAK,MAAM;AACrG,SAAO,OAAO,SAAS,GAAG,MAAM,gEAAgE,OAAO,MAAM;AAC7G,SAAO,YAAY,OAAO,MAAM,IAAI,MAAM,4CAA4C,8CAA8C,OAAO,MAAM,KAAK;AACtJ,SAAO,aAAa,OAAO,MAAM,IAAI,MAAM,6CAA6C,gDAAgD,OAAO,MAAM,KAAK;AAC1J,QAAM,SAAS,EAAE,IAAI,MAAM,OAAO;AAClC,QAAM,QAAQ,EAAE,KAAK,MAAM,SAAAA,UAAS,YAAY,SAAS;AACzD,QAAM,MAAM,OAAO,UAAU,uBAAuB,QAAQ,KAAK;AACjE,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAC9E;AACA,SAAO;AACT;AACA,IAAI,sBAAsB,GAAG,EAAE,qBAAqB,CAAC;AAGrD,SAAS,iBAAiB,GAAG,QAAQ,aAAaA,UAAS,MAAM;AAC/D,QAAM,KAAK,gBAAgB,GAAG,KAAK,iBAAiB;AACpD,QAAM,UAAU,gBAAgB,QAAQ,UAAU,iBAAiB;AACnE,SAAO,oBAAoB,aAAa,IAAI,SAASA,UAAS,IAAI;AACpE;AACA,IAAI,kBAAkB,GAAG,EAAE,iBAAiB,CAAC;AAG7C,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO,SAAS;AACnD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ,SAAS;AACpD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,SAAS,GAAG,OAAO,GAAG,YAAY,OAAO,WAAW,OAAO;AAClE,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,WAAW,SAAS,SAAS;AACnD,SAAO,OAAO,UAAU,SAAS,QAAQ,KAAK;AAChD;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,QAAQ,GAAG,OAAO,GAAG,YAAY,OAAO,WAAW,OAAO;AACjE,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AAC3C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,WAAW,SAAS,SAAS;AACnD,SAAO,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAC/C;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,eAAe,GAAG,SAASZ,OAAM,eAAe,OAAO;AAC9D,QAAM,KAAK,gBAAgB,GAAG,KAAK,eAAe;AAClD,QAAM,WAAW,gBAAgB,SAAS,WAAW,eAAe;AACpE,SAAO,GAAG,UAAU,SAAS,MAAM,8DAA8D,GAAG,OAAO;AAC3G,SAAO,GAAG,QAAQ,GAAG,MAAM,sEAAsE,GAAG,OAAO;AAC3G,SAAOA,SAAQ,GAAG,MAAM,sCAAsCA,QAAO;AACrE,SAAO,SAAS,SAAS,GAAG,QAAQ,SAAS,SAAS,GAAG,MAAM,+FAA+F,GAAG,yBAAyB,SAAS,QAAQ;AAC3M,QAAM,SAAS,EAAE,GAAG,IAAI,SAAS,SAAS;AAC1C,QAAM,QAAQ,EAAE,MAAAA,OAAM,aAAa;AACnC,SAAO,OAAO,UAAU,eAAe,QAAQ,KAAK;AACtD;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,cAAc,GAAG,WAAW,aAAa,QAAQ;AACxD,QAAM,KAAK,gBAAgB,GAAG,KAAK,gBAAgB,SAAS;AAC5D,QAAM,cAAc,eAAe,SAAS,GAAG,MAAM,KAAK,GAAG,MAAM;AACnE,QAAM,aAAa,eAAe,SAAS,GAAG,MAAM,KAAK,GAAG,MAAM;AAClE,QAAM,aAAa,eAAe,SAAS,GAAG,MAAM,KAAK,GAAG,MAAM;AAClE,SAAO,YAAY,GAAG,MAAM,sDAAsD,WAAW;AAC7F,SAAO,cAAc,aAAa,GAAG,MAAM;AAAA,MACvC,mBAAmB;AAAA,MACnB,GAAG,OAAO;AACd,SAAO,aAAa,aAAa,GAAG,MAAM;AAAA,MACtC,kBAAkB;AAAA,UACd,GAAG,OAAO;AAClB,SAAO,cAAc,YAAY,eAAe,GAAG,MAAM,8CAA8C,YAAY,oBAAoB,gDAAgD,GAAG,OAAO;AACjM,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,WAAW,WAAW;AACtC,SAAO,OAAO,UAAU,cAAc,QAAQ,KAAK;AACrD;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,iBAAiB,GAAG,QAAQY,UAAS,MAAM,aAAa,QAAQ,YAAY,CAAC,GAAG,CAAC,GAAG,iBAAiB;AAC5G,QAAM,KAAK,gBAAgB,GAAG,KAAK,mBAAmB,SAAS;AAC/D,QAAM,UAAU,gBAAgB,QAAQ,UAAU,mBAAmB,SAAS;AAC9E,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,gEAAgE,IAAI,OAAO;AACxG,SAAO,QAAQ,SAAS,GAAG,MAAM,iEAAiE,QAAQ,OAAO;AACjH,QAAM,aAAa,eAAe,SAAS,IAAI,MAAM,KAAK,IAAI,MAAM;AACpE,SAAO,eAAe,QAAQ,MAAM,IAAI,MAAM,uDAAuD,6DAA6D,QAAQ,MAAM,KAAK;AACrL,4BAA0B,mBAAmB,MAAM,eAAe;AAClE,QAAM,SAAS,EAAE,GAAG,KAAK,QAAQ,QAAQ;AACzC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB;AAC3E,QAAM,MAAM,OAAO,UAAU,uBAAuB,QAAQ,KAAK;AACjE,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,kBAAkB,GAAG,EAAE,iBAAiB,CAAC;AAG7C,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,YAAY,GAAG,QAAQA,UAAS,MAAM,YAAY,CAAC,GAAG,CAAC,GAAG,aAAa,QAAQ;AACtF,QAAM,KAAK,gBAAgB,GAAG,KAAK,YAAY;AAC/C,QAAM,UAAU,gBAAgB,QAAQ,UAAU,YAAY;AAC9D,SAAO,GAAG,SAAS,KAAK,GAAG,SAAS,GAAG,MAAM,gEAAgE,GAAG,OAAO;AACvH,SAAO,QAAQ,SAAS,GAAG,MAAM,4DAA4D,QAAQ,OAAO;AAC5G,SAAO,eAAe,QAAQ,MAAM,gFAAgF,YAAY;AAChI,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAC5D,mBAAe;AAAA,EACjB;AACA,QAAM,SAAS,EAAE,GAAG,KAAK,QAAQ,QAAQ;AACzC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,UAAU;AAC9C,QAAM,MAAM,OAAO,UAAU,YAAY,QAAQ,KAAK;AACtD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,OAAO,GAAG,GAAG;AACpB,MAAI,KAAK,gBAAgB,GAAG,KAAK,SAAS,mBAAmB;AAC7D,MAAI,KAAK,gBAAgB,GAAG,KAAK,SAAS,mBAAmB;AAC7D,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,OAAO,WAAW,GAAG,GAAG;AAC/B,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,aAAa,gBAAgB,WAAW,aAAa,SAAS,MAAM;AAC1E,QAAM,iBAAiB,2BAA2B,2BAA2B,WAAW,OAAO,GAAG,KAAK,GAAG,GAAG,KAAK;AAClH,QAAM,wBAAwB,YAAY,YAAY,cAAc;AACpE,QAAM,gBAAgB,YAAY,IAAI,cAAc;AACpD,QAAM,gBAAgB,YAAY,IAAI,cAAc;AACpD,QAAM,SAAS;AAAA,IACb,WAAW;AAAA,IACX,GAAG;AAAA,IACH,GAAG;AAAA,EACL;AACA,SAAO,OAAO,UAAU,QAAQ,MAAM;AACxC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,WAAW,GAAG;AACrB,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,WAAW,MAAM;AAC3C;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,UAAU,GAAG,GAAG;AACvB,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,YAAY,IAAI,IAAI,EAAE;AAC5B,QAAM,SAAS,UAAU,SAAS;AAClC,QAAM,cAAc,MAAM,IAAI,MAAM;AACpC,SAAO,MAAM,aAAa,QAAQ,SAAS;AAC7C;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,KAAK,IAAI,IAAI;AACpB,QAAM,MAAM,gBAAgB,IAAI,MAAM,KAAK;AAC3C,QAAM,MAAM,gBAAgB,IAAI,MAAM,KAAK;AAC3C,UAAQ,IAAI,SAAS,KAAK,IAAI,SAAS,OAAO,IAAI,SAAS,KAAK,IAAI,SAAS,IAAI,MAAM,+DAA+D,IAAI,YAAY,IAAI,OAAO;AACjL,QAAM,UAAU,IAAI,SAAS,IAAI,IAAI,OAAO,IAAI,MAAM;AACtD,QAAM,UAAU,IAAI,SAAS,IAAI,IAAI,OAAO,IAAI,MAAM;AACtD,SAAO,YAAY,SAAS,MAAM,gEAAgE,eAAe,UAAU;AAC3H,MAAI,IAAI,SAAS,KAAK,IAAI,SAAS,GAAG;AACpC,UAAM,OAAO,QAAQ,KAAK,CAAC,GAAG,EAAE,CAAC;AACjC,UAAM,OAAO,QAAQ,KAAK,CAAC,IAAI,CAAC,CAAC;AACjC,UAAM,OAAO,OAAO,MAAM,IAAI;AAC9B,WAAO,QAAQ,MAAM,CAAC,CAAC;AAAA,EACzB,WAAW,IAAI,SAAS,KAAK,IAAI,SAAS,GAAG;AAC3C,UAAM,OAAO,QAAQ,KAAK,CAAC,GAAG,EAAE,CAAC;AACjC,UAAM,OAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AACtD,UAAM,OAAO,OAAO,MAAM,IAAI;AAC9B,WAAO,QAAQ,MAAM,CAAC,KAAK,IAAI,CAAC;AAAA,EAClC,WAAW,IAAI,SAAS,KAAK,IAAI,SAAS,GAAG;AAC3C,UAAM,OAAO,QAAQ,KAAK,CAAC,IAAI,CAAC,CAAC;AACjC,UAAM,OAAO,OAAO,KAAK,IAAI;AAC7B,WAAO,QAAQ,MAAM,CAAC,KAAK,IAAI,CAAC;AAAA,EAClC,OAAO;AACL,UAAM,OAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AACtD,UAAM,OAAO,OAAO,KAAK,IAAI;AAC7B,WAAO;AAAA,EACT;AACF;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,QAAQ,aAAa,SAAS;AACrC,QAAM,WAAW,QAAQ,IAAI,CAAC,IAAI,OAAO,gBAAgB,IAAI,UAAU,MAAM,QAAQ,CAAC;AACtF,QAAM,QAAQ,EAAE,SAAS;AACzB,SAAO,OAAO,UAAU,QAAQ,UAAU,KAAK;AACjD;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO,SAAS;AACnD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,KAAK,GAAG;AACf,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,SAAO,GAAG,UAAU,WAAW,GAAG,UAAU,WAAW,MAAM,2CAA2C;AACxG,MAAI,GAAG,UAAU,SAAS;AACxB,SAAK,KAAK,IAAI,SAAS;AAAA,EACzB;AACA,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,qBAAqB,MAAM,MAAM;AACxC,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,QAAI,KAAK,KAAK,SAAS,KAAK,OAAO,OAAO,IAAI,IAAI;AAChD,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,WAAW,WAAW,MAAM;AACpD,QAAM,OAAO,UAAU,SAAS,UAAU;AAC1C,QAAM,MAAM,CAAC;AACb,MAAI,SAAS;AACb,MAAI,YAAY;AAChB,WAAS,MAAM,GAAG,MAAM,MAAM,OAAO;AACnC,QAAI,KAAK,QAAQ,GAAG,MAAM,IAAI;AAC5B,UAAI,KAAK,UAAU,SAAS;AAAA,IAC9B,OAAO;AACL,UAAI,KAAK,UAAU,YAAY;AAAA,IACjC;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,0BAA0B,QAAQ,MAAM;AAC/C,QAAM,WAAW,CAAC;AAClB,QAAM,OAAO,OAAO;AACpB,WAAS,MAAM,GAAG,MAAM,MAAM,OAAO;AACnC,QAAI,KAAK,QAAQ,GAAG,MAAM,IAAI;AAC5B,eAAS,KAAK,OAAO,IAAI;AAAA,IAC3B;AAAA,EACF;AACA,QAAM,cAAc,KAAK,IAAI,CAAC,QAAQ,OAAO,IAAI;AACjD,SAAO,CAAC,UAAU,WAAW;AAC/B;AACA,SAAS,qBAAqB,OAAO,MAAM;AACzC,QAAM,iBAAiB,KAAK,IAAI,CAAC,MAAM,CAAC;AACxC,SAAO,iBAAiB,OAAO,gBAAgB,IAAI;AACrD;AACA,SAAS,2BAA2B,KAAK,MAAM,MAAM;AACnD,SAAO,qBAAqB,MAAM,IAAI,GAAG,MAAM,GAAG,uDAAuD,iBAAiB,aAAa;AACzI;AACA,SAAS,mBAAmB,MAAM,MAAM;AACtC,MAAI,qBAAqB,MAAM,IAAI,GAAG;AACpC,WAAO;AAAA,EACT;AACA,QAAM,SAAS,CAAC;AAChB,WAAS,KAAK,GAAG,KAAK,MAAM,EAAE,IAAI;AAChC,QAAI,KAAK,QAAQ,EAAE,MAAM,IAAI;AAC3B,aAAO,KAAK,EAAE;AAAA,IAChB;AAAA,EACF;AACA,OAAK,QAAQ,CAAC,SAAS,OAAO,KAAK,IAAI,CAAC;AACxC,SAAO;AACT;AACA,SAAS,uBAAuB,MAAM;AACpC,SAAO,KAAK,IAAI,CAAC,MAAM,OAAO,CAAC,IAAI,IAAI,CAAC,EAAE,KAAK,CAAC,GAAG,MAAM,EAAE,KAAK,EAAE,EAAE,EAAE,IAAI,CAAC,MAAM,EAAE,EAAE;AACvF;AACA,SAAS,iBAAiB,SAAS,MAAM;AACvC,QAAM,MAAM,CAAC;AACb,WAAS,KAAK,OAAO,SAAS,KAAK,MAAM,EAAE,IAAI;AAC7C,QAAI,KAAK,EAAE;AAAA,EACb;AACA,SAAO;AACT;AAGA,SAAS,KAAK,GAAG,OAAO,MAAM,WAAW,OAAO;AAC9C,QAAM,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACxC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,kBAAkB,MAAM,SAAS;AACjD,SAAO,OAAO,UAAU,KAAK,QAAQ,KAAK;AAC5C;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,KAAK,GAAG,OAAO,MAAM,WAAW,OAAO;AAC9C,QAAM,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACxC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,SAAS;AAC/B,SAAO,OAAO,UAAU,KAAK,QAAQ,KAAK;AAC5C;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,KAAK,MAAM,MAAM;AACxB,MAAI,QAAQ,gBAAgB,MAAM,QAAQ,KAAK;AAC/C,MAAI,OAAO,gBAAgB,MAAM,OAAO,KAAK;AAC7C,GAAC,OAAO,IAAI,IAAI,eAAe,OAAO,IAAI;AAC1C,QAAM,SAAS,EAAE,GAAG,OAAO,GAAG,KAAK;AACnC,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,OAAO,OAAO,OAAO;AAC5B,OAAK,aAAa,KAAK,KAAK,UAAU,YAAY,MAAM,QAAQ,KAAK,MAAM,UAAU,aAAa;AAChG,UAAM,IAAI,MAAM,gFAAgF;AAAA,EAClG;AACA,MAAI,UAAU,YAAY,aAAa,KAAK,KAAK,EAAE,iBAAiB,aAAa;AAC/E,UAAM,IAAI,MAAM,2EAA2E;AAAA,EAC7F;AACA,QAAM,QAAQ,CAAC;AACf,QAAM,gBAAgB,CAAC;AACvB,SAAO,WAAW,OAAO,OAAO,eAAe,KAAK;AACtD;AAGA,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ,SAAS;AACpD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,QAAQ,GAAG;AAClB,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AAC3C,QAAM,QAAQ,CAAC;AACf,SAAO,OAAO,UAAU,UAAU,EAAE,GAAG,GAAG,GAAG,KAAK;AACpD;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,KAAK,GAAG,OAAO,MAAM,WAAW,OAAO;AAC9C,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,MAAI,GAAG,UAAU,QAAQ;AACvB,SAAK,KAAK,IAAI,OAAO;AAAA,EACvB;AACA,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,SAAS;AAC/B,SAAO,OAAO,UAAU,KAAK,QAAQ,KAAK;AAC5C;AACA,IAAI,OAAO,GAAG,EAAE,KAAK,CAAC;AAGtB,SAAS,MAAM,GAAG,MAAM,aAAa,OAAO,MAAM,WAAW,OAAO;AAClE,MAAI,gBAAgB,GAAG,KAAK,MAAM;AAClC,QAAM,QAAQ,SAAS,GAAG,KAAK,IAAI;AACnC,MAAI,gBAAgB,MAAM;AAC1B,MAAI,UAAU;AACZ,UAAM,OAAO,eAAe,MAAM,EAAE,KAAK;AACzC,oBAAgB,qBAAqB,MAAM,OAAO,IAAI;AAAA,EACxD;AACA,SAAO,QAAQ,OAAO,aAAa;AACrC;AACA,SAAS,SAAS,GAAG,IAAI,OAAO,MAAM;AACpC,MAAI,EAAE,SAAS,GAAG;AAChB,WAAO,IAAI,CAAC;AAAA,EACd;AACA,MAAI,EAAE,SAAS,KAAK,SAAS,MAAM;AACjC,WAAO,SAAS,QAAQ,GAAG,CAAC,EAAE,CAAC,GAAG,IAAI,IAAI;AAAA,EAC5C;AACA,MAAI,EAAE,SAAS,KAAK,OAAO,SAAS,YAAY,MAAM,QAAQ,IAAI,KAAK,KAAK,WAAW,GAAG;AACxF,QAAI,OAAO,GAAG;AACZ,aAAO,KAAK,IAAI,CAAC,GAAG,IAAI;AAAA,IAC1B;AACA,QAAI,OAAO,UAAU;AACnB,aAAO,IAAI,IAAI,CAAC,GAAG,IAAI;AAAA,IACzB;AACA,QAAI,OAAO,WAAW;AACpB,aAAO,IAAI,IAAI,CAAC,GAAG,IAAI;AAAA,IACzB;AACA,QAAI,OAAO,eAAe,OAAO,GAAG;AAClC,aAAO,KAAK,KAAK,IAAI,IAAI,CAAC,GAAG,OAAO,GAAG,OAAO,CAAC,GAAG,IAAI,CAAC;AAAA,IACzD;AACA,UAAM,IAAI,MAAM,qCAAqC,IAAI;AAAA,EAC3D;AACA,MAAI,MAAM,QAAQ,IAAI,KAAK,KAAK,WAAW,GAAG;AAC5C,QAAI,OAAO,GAAG;AACZ,aAAO,IAAI,KAAK,IAAI,CAAC,GAAG,KAAK,EAAE,GAAG,KAAK,KAAK,CAAC;AAAA,IAC/C;AACA,QAAI,OAAO,UAAU;AACnB,aAAO,IAAI,KAAK,IAAI,CAAC,GAAG,KAAK,EAAE,GAAG,KAAK,EAAE;AAAA,IAC3C;AACA,QAAI,OAAO,WAAW;AACpB,aAAO,IAAI,KAAK,IAAI,CAAC,GAAG,KAAK,EAAE,GAAG,KAAK,EAAE;AAAA,IAC3C;AACA,QAAI,OAAO,SAAS,OAAO,aAAa;AACtC,aAAO,KAAK,KAAK,OAAO,CAAC,GAAG,IAAI,CAAC;AAAA,IACnC;AACA,UAAM,IAAI,MAAM,qCAAqC,IAAI;AAAA,EAC3D;AACA,QAAM,IAAI,MAAM,gCAAgC,MAAM;AACxD;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,eAAe,GAAG,OAAO,MAAM,WAAW,OAAO;AACxD,SAAO,KAAK,GAAG,aAAa,MAAM,QAAQ;AAC5C;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACxC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,YAAY,GAAG,OAAO,GAAG;AAChC,QAAM,KAAK,gBAAgB,GAAG,KAAK,cAAc,mBAAmB;AACpE,SAAO,QAAQ,GAAG,MAAM,MAAM,oCAAoC;AAClE,QAAM,SAAS,EAAE,OAAO,GAAG;AAC3B,QAAM,QAAQ,EAAE,KAAK,KAAK;AAC1B,SAAO,OAAO,UAAU,YAAY,QAAQ,KAAK;AACnD;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,GAAG,MAAM;AACtB,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ,mBAAmB;AAC9D,SAAO,GAAG,SAAS,KAAK,QAAQ,MAAM,qCAAqC,GAAG,kCAAkC,OAAO;AACvH,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,KAAK;AACrB,SAAO,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC7C;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,KAAK,SAAS,YAAY,YAAY,QAAQ,WAAW;AAChE,MAAI,cAAc,MAAM;AACtB,iBAAa;AAAA,EACf;AACA,QAAM,OAAO,OAAO,CAAC,SAAS,UAAU,GAAG,KAAK;AAChD,QAAM,KAAK,WAAW,aAAa,UAAU;AAC7C,WAAS,KAAK,GAAG,KAAK,IAAI,EAAE,IAAI;AAC9B,SAAK,IAAI,GAAG,IAAI,EAAE;AAAA,EACpB;AACA,QAAM,MAAM,QAAQ,KAAK,SAAS,GAAG,CAAC,SAAS,UAAU,CAAC;AAC1D,MAAI,cAAc,MAAM;AACtB,WAAO;AAAA,EACT,OAAO;AACL,QAAI,WAAW,WAAW,GAAG;AAC3B,aAAO,KAAK,WAAW,KAAK,CAAC,GAAG,CAAC,WAAW,IAAI,GAAG,CAAC,CAAC;AAAA,IACvD,WAAW,WAAW,WAAW,GAAG;AAClC,aAAO,KAAK,WAAW,WAAW,KAAK,CAAC,GAAG,CAAC,GAAG,CAAC,WAAW,IAAI,WAAW,IAAI,GAAG,CAAC,CAAC;AAAA,IACrF,WAAW,WAAW,WAAW,GAAG;AAClC,aAAO,KAAK,WAAW,WAAW,WAAW,KAAK,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG;AAAA,QAC5D,WAAW;AAAA,QACX,WAAW;AAAA,QACX,WAAW;AAAA,QACX;AAAA,QACA;AAAA,MACF,CAAC;AAAA,IACH,OAAO;AACL,YAAM,IAAI,MAAM,qEAAqE,WAAW,UAAU;AAAA,IAC5G;AAAA,EACF;AACF;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,KAAK,OAAO,OAAO,OAAO;AACjC,QAAM,QAAQ,EAAE,OAAO,OAAO,MAAM;AACpC,SAAO,OAAO,UAAU,MAAM,CAAC,GAAG,KAAK;AACzC;AAGA,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS,SAAS;AACrD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,QAAQ,GAAG,SAAS,OAAO,GAAG,YAAY,GAAG;AACpD,QAAM,KAAK,gBAAgB,GAAG,KAAK,QAAQ;AAC3C,QAAM,WAAW,gBAAgB,SAAS,WAAW,UAAU,OAAO;AACtE,QAAM,SAAS,EAAE,GAAG,IAAI,SAAS,SAAS;AAC1C,QAAM,QAAQ,EAAE,MAAM,UAAU;AAChC,SAAO,OAAO,UAAU,UAAU,QAAQ,KAAK;AACjD;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,SAAS,GAAG,GAAG;AACtB,MAAI,KAAK,gBAAgB,GAAG,KAAK,WAAW,mBAAmB;AAC/D,MAAI,KAAK,gBAAgB,GAAG,KAAK,WAAW,mBAAmB;AAC/D,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,SAAS,MAAM;AACzC;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,cAAc,GAAG,GAAG;AAC3B,MAAI,KAAK,gBAAgB,GAAG,KAAK,gBAAgB,mBAAmB;AACpE,MAAI,KAAK,gBAAgB,GAAG,KAAK,gBAAgB,mBAAmB;AACpE,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,cAAc,MAAM;AAC9C;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,UAAU,GAAG;AACpB,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU;AAC7C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,YAAY,GAAG,EAAE,UAAU,CAAC;AAGhC,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,SAAS,GAAG,EAAE,OAAO,CAAC;AAG1B,SAAS,WAAW,GAAGU,SAAQ,KAAK;AAClC,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,OAAAA,OAAM;AACtB,SAAO,OAAO,UAAU,WAAW,QAAQ,KAAK;AAClD;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,MAAM,GAAG,GAAG;AACnB,MAAI,KAAK,gBAAgB,GAAG,KAAK,QAAQ,mBAAmB;AAC5D,MAAI,KAAK,gBAAgB,GAAG,KAAK,QAAQ,mBAAmB;AAC5D,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,WAAW,GAAG,GAAG;AACxB,MAAI,KAAK,gBAAgB,GAAG,KAAK,aAAa,mBAAmB;AACjE,MAAI,KAAK,gBAAgB,GAAG,KAAK,aAAa,mBAAmB;AACjE,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,WAAW,MAAM;AAC3C;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,SAAS,OAAO,MAAM,KAAK;AAClC,MAAI,OAAO,GAAG;AACZ,UAAM,IAAI,MAAM,0CAA0C;AAAA,EAC5D;AACA,QAAM,QAAQ,EAAE,OAAO,MAAM,IAAI;AACjC,SAAO,OAAO,UAAU,UAAU,CAAC,GAAG,KAAK;AAC7C;AAGA,SAAS,4BAA4B,GAAG,cAAc,GAAG,OAAO,GAAGA,SAAQ,GAAG,OAAO,KAAK;AACxF,QAAM,KAAK,gBAAgB,GAAG,KAAK,4BAA4B;AAC/D,SAAO,GAAG,SAAS,KAAK,GAAG,SAAS,GAAG,MAAM;AAAA,sBACzB,GAAG,OAAO;AAC9B,SAAO,MAAM,WAAW,GAAG,MAAM,2FAA2F,cAAc;AAC1I,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,QAAM,SAAS,EAAE,GAAG,IAAI;AACxB,QAAM,QAAQ,EAAE,aAAa,MAAM,OAAAA,QAAO,KAAK;AAC/C,QAAM,MAAM,OAAO,UAAU,KAAK,QAAQ,KAAK;AAC/C,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE,OAAO;AACL,WAAO;AAAA,EACT;AACF;AACA,IAAI,6BAA6B,GAAG,EAAE,4BAA4B,CAAC;AAGnE,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO,SAAS;AACnD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI3B,QAAO,GAAG,EAAE,KAAK,CAAC;AAGtB,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,KAAK,GAAG;AACf,SAAO,WAAW,CAAC,GAAG,MAAM,4CAA4C;AACxE,SAAO,CAAC,GAAG,OAAO;AAChB,UAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW,mBAAmB;AACjE,UAAM,MAAM,MAAM,OAAO,gBAAgB,IAAI,MAAM,SAAS,IAAI;AAChE,WAAO,OAAO,KAAK,MAAM;AACvB,YAAM,EAAE,OAAO,OAAO,OAAO,IAAI,OAAO,UAAU,MAAM,EAAE,EAAE,GAAG,CAAC,EAAE,GAAG,GAAG;AACxE,UAAI,OAAO,MAAM;AACf,0BAAkB,MAAM,OAAO,IAAI,OAAO,gFAAgF;AAAA,MAC5H;AACA,iBAAW,MAAM;AACjB,aAAO,OAAO;AAAA,IAChB,CAAC;AAAA,EACH;AACF;AACA,SAAS,MAAM,GAAG;AAChB,SAAO,WAAW,CAAC,GAAG,MAAM,6CAA6C;AACzE,SAAO,CAAC,MAAM,OAAO;AACnB,WAAO,MAAM,QAAQ,IAAI,GAAG,MAAM,kFAAkF;AACpH,UAAM,QAAQ,qBAAqB,MAAM,QAAQ,YAAY,mBAAmB;AAChF,UAAM,MAAM,MAAM,OAAO,gBAAgB,IAAI,MAAM,UAAU,IAAI;AACjE,WAAO,OAAO,KAAK,MAAM;AACvB,YAAM,EAAE,OAAO,OAAO,OAAO,IAAI,OAAO,UAAU,MAAM,EAAE,GAAG,KAAK,GAAG,OAAO,GAAG;AAC/E,UAAI,OAAO,MAAM;AACf,0BAAkB,MAAM,OAAO,IAAI,OAAO,+FAA+F;AAAA,MAC3I;AACA,iBAAW,MAAM;AACjB,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,SAAS,aAAa,GAAG;AACvB,SAAO,WAAW,CAAC,GAAG,MAAM,oDAAoD;AAChF,SAAO,CAAC,GAAG,OAAO;AAChB,WAAO,aAAa,QAAQ,MAAM,qDAAqD;AACvF,WAAO,MAAM,QAAQ,cAAc,QAAQ,MAAM,0DAA0D;AAC3G,UAAM,EAAE,OAAO,QAAQ,MAAM,IAAI,OAAO,UAAU,MAAM,EAAE,CAAC,GAAG,CAAC,CAAC,GAAG,EAAE;AACrE,eAAW,MAAM;AACjB,WAAO,EAAE,MAAM,OAAO,IAAI,MAAM;AAAA,EAClC;AACF;AACA,SAAS,cAAc,GAAG;AACxB,SAAO,WAAW,CAAC,GAAG,MAAM,qDAAqD;AACjF,SAAO,CAAC,MAAM,OAAO;AACnB,WAAO,MAAM,QAAQ,IAAI,KAAK,KAAK,MAAM,CAAC,QAAQ,eAAe,MAAM,GAAG,MAAM,oEAAoE;AACpJ,WAAO,MAAM,QAAQ,cAAc,QAAQ,MAAM,8DAA8D;AAC/G,UAAM,MAAM,OAAO,UAAU,MAAM,EAAE,GAAG,IAAI,GAAG,MAAM,EAAE;AACvD,QAAI,MAAM,MAAM;AACd,wBAAkB,IAAI,MAAM,OAAO,GAAG,OAAO,uGAAuG;AAAA,IACtJ;AACA,eAAW,IAAI,KAAK;AACpB,WAAO;AAAA,EACT;AACF;AACA,SAAS,cAAc,GAAG,SAAS;AACjC,SAAO,WAAW,CAAC,GAAG,MAAM,qDAAqD;AACjF,SAAO,WAAW,QAAQ,MAAM,QAAQ,OAAO,KAAK,QAAQ,MAAM,CAAC,MAAM,aAAa,QAAQ,GAAG,MAAM,+EAA+E;AACtL,QAAM,mBAAmB,WAAW;AACpC,MAAI,CAAC,kBAAkB;AACrB,cAAU,CAAC;AACX,eAAW,WAAW,OAAO,qBAAqB;AAChD,cAAQ,KAAK,OAAO,oBAAoB,QAAQ;AAAA,IAClD;AAAA,EACF;AACA,QAAM,wBAAwB,mBAAmB,QAAQ,OAAO,CAAC,cAAc,CAAC,UAAU,SAAS,IAAI;AACvG,QAAM,mBAAmB,QAAQ;AACjC,YAAU,QAAQ,OAAO,CAAC,cAAc,UAAU,SAAS;AAC3D,SAAO,QAAQ,SAAS,GAAG,MAAM,gGAAgG,0CAA0C;AAC3K,QAAM,mBAAmB;AACzB,QAAM,EAAE,OAAO,OAAO,OAAO,IAAI,OAAO,UAAU,GAAG,SAAS,MAAM,gBAAgB;AACpF,SAAO,OAAO,KAAK,CAAC,MAAM,KAAK,IAAI,GAAG,MAAM,8LAA8L;AAC1O,SAAO,MAAM,SAAS,GAAG,MAAM,iFAAiF,MAAM,aAAa;AACnI,QAAM,aAAa,CAAC;AACpB,UAAQ,QAAQ,CAAC,GAAG,OAAO;AACzB,QAAI,OAAO,OAAO,MAAM;AACtB,iBAAW,EAAE,QAAQ,OAAO;AAAA,IAC9B;AAAA,EACF,CAAC;AACD,MAAI,yBAAyB,MAAM;AACjC,0BAAsB,QAAQ,CAAC,MAAM,WAAW,EAAE,QAAQ,IAAI;AAAA,EAChE;AACA,SAAO,EAAE,OAAO,OAAO,WAAW;AACpC;AACA,SAAS,WAAW,GAAG;AACrB,SAAO,OAAO,WAAW,CAAC;AAC5B;AACA,SAAS,WAAW,QAAQ;AAC1B,QAAM,mBAAmB,OAAO,OAAO,CAAC,MAAM,KAAK,IAAI,EAAE;AACzD,MAAI,mBAAmB,GAAG;AACxB,UAAM,IAAI,MAAM;AAAA,oEACgD;AAAA,EAClE;AACF;AAGA,SAAS,UAAU,GAAG;AACpB,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU;AAC7C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,YAAY,GAAG;AACtB,QAAM,KAAK,gBAAgB,GAAG,KAAK,YAAY;AAC/C,QAAM,WAAW,WAAW,CAAC,OAAO;AAClC,UAAM,QAAQ,IAAI,SAAS,IAAI,EAAE,CAAC,CAAC;AACnC,UAAM,WAAW,CAAC,OAAO;AACvB,YAAM,OAAO,IAAI,IAAI,QAAQ,IAAI,EAAE,CAAC,CAAC;AACrC,aAAO;AAAA,IACT;AACA,WAAO,EAAE,OAAO,SAAS;AAAA,EAC3B,CAAC;AACD,SAAO,SAAS,EAAE;AACpB;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,KAAK,GAAG,GAAG;AAClB,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,YAAY,QAAQ,OAAO,IAAI;AACtC,QAAM,UAAU,gBAAgB,QAAQ,UAAU,YAAY;AAC9D,MAAI,SAAS,IAAI;AACf,WAAO,QAAQ,OAAO;AAAA,EACxB;AACA,MAAI,SAAS,QAAQ,OAAO,GAAG;AAC7B,UAAM,MAAM,gFAAgF,QAAQ,qBAAqB,MAAM;AAAA,EACjI;AACA,QAAM,WAAW,WAAW,CAAC,SAAS,SAAS;AAC7C,UAAM,WAAW;AACjB,UAAM,OAAO,IAAI,SAAS,MAAM,IAAI;AACpC,UAAM,UAAU,IAAI,SAAS,IAAI;AACjC,UAAM,QAAQ,IAAI,KAAK,SAAS,SAAS,GAAGA,MAAK,KAAK,IAAI,OAAO,GAAG,MAAM,QAAQ,CAAC,CAAC;AACpF,SAAK,CAAC,KAAK,CAAC;AACZ,UAAM,WAAW,CAAC,IAAI,UAAU;AAC9B,YAAM,CAAC,MAAM,IAAI;AACjB,YAAM,YAAY;AAClB,YAAM,WAAW,IAAI,MAAM;AAC3B,aAAO,IAAI,IAAI,IAAI,KAAK,IAAI,MAAM,SAAS,GAAG,QAAQ,CAAC;AAAA,IACzD;AACA,WAAO,EAAE,OAAO,SAAS;AAAA,EAC3B,CAAC;AACD,SAAO,SAAS,OAAO;AACzB;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,WAAW,GAAG,OAAO,MAAM,WAAW,OAAO;AACpD,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,OAAO,eAAe,MAAM,GAAG,KAAK;AAC1C,QAAM,OAAO,IAAI,IAAI,MAAM,IAAI;AAC/B,QAAM,IAAI,IAAI,IAAI,IAAI;AACtB,QAAM,IAAI,IAAI,CAAC;AACf,QAAM,IAAI,KAAK,GAAG,IAAI;AACtB,QAAM,IAAIA,MAAK,CAAC;AAChB,QAAM,MAAM,KAAK,QAAQ,MAAM,EAAE,KAAK,GAAG,CAAC;AAC1C,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,IAAI,OAAO,IAAI;AACrD,WAAO,QAAQ,KAAK,QAAQ;AAAA,EAC9B;AACA,SAAO;AACT;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,YAAY,GAAG,GAAG;AACzB,QAAM,KAAK,gBAAgB,GAAG,KAAK,cAAc,MAAM;AACvD,QAAM,KAAK,gBAAgB,GAAG,KAAK,cAAc,MAAM;AACvD,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,YAAY,MAAM;AAC5C;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,YAAY,GAAG;AACtB,QAAM,KAAK,gBAAgB,GAAG,KAAK,cAAc,MAAM;AACvD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,YAAY,MAAM;AAC5C;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,WAAW,GAAG,GAAG;AACxB,QAAM,KAAK,gBAAgB,GAAG,KAAK,aAAa,MAAM;AACtD,QAAM,KAAK,gBAAgB,GAAG,KAAK,aAAa,MAAM;AACtD,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,WAAW,MAAM;AAC3C;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,YAAY,GAAG,GAAG;AACzB,QAAM,KAAK,gBAAgB,GAAG,KAAK,cAAc,MAAM;AACvD,QAAM,KAAK,gBAAgB,GAAG,KAAK,cAAc,MAAM;AACvD,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,SAAO,WAAW,UAAU,GAAG,CAAC,GAAG,WAAW,WAAW,GAAG,CAAC,CAAC,CAAC;AACjE;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,IAAI,YAAY;AAChB,SAAS,cAAc,gBAAgB,QAAQ,OAAO,QAAQ;AAC5D,QAAM,kBAAkB,gBAAgB,gBAAgB,kBAAkB,cAAc;AACxF,QAAM,UAAU,gBAAgB,QAAQ,UAAU,cAAc;AAChE,QAAM,eAAe,gBAAgB,MAAM,gBAAgB,MAAM,SAAS;AAC1E,QAAM,aAAa,QAAQ,MAAM,QAAQ,MAAM,SAAS;AACxD,QAAM,oBAAoB,QAAQ,iBAAiB,CAAC,IAAI,YAAY,CAAC;AACrE,QAAM,YAAY,QAAQ,SAAS,CAAC,IAAI,UAAU,CAAC;AACnD,MAAI,kBAAkB,OAAO,GAAG;AAC9B,UAAM,IAAI,MAAM,sDAAsD;AAAA,EACxE;AACA,MAAI,kBAAkB,MAAM,OAAO,UAAU,MAAM,IAAI;AACrD,UAAM,IAAI,MAAM,gEAAgE;AAAA,EAClF;AACA,MAAI,cAAc,UAAU,KAAK,KAAK,WAAW;AAC/C,UAAM,IAAI,MAAM,qCAAqC,WAAW;AAAA,EAClE;AACA,MAAI,kBAAkB,MAAM,MAAM,WAAW;AAC3C,UAAM,IAAI,MAAM,oCAAoC,wCAAwC,kBAAkB,MAAM,IAAI;AAAA,EAC1H;AACA,QAAM,SAAS;AAAA,IACb,gBAAgB;AAAA,IAChB,QAAQ;AAAA,EACV;AACA,QAAM,QAAQ,EAAE,KAAK;AACrB,SAAO,OAAO,UAAU,cAAc,QAAQ,KAAK;AACrD;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,WAAW,gBAAgB,QAAQ;AAC1C,SAAO,aAAa,gBAAgB,QAAQ,MAAM;AACpD;AAGA,SAAS,SAAS,GAAG,YAAYiB,UAAS,MAAM,iBAAiB;AAC/D,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,QAAM,YAAY;AAClB,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,uDAAuD,IAAI,OAAO;AAC/F,SAAO,+BAA+BA,UAAS,SAAS,GAAG,MAAM,wEAAwEA,2BAA0B,YAAY;AAC/K,4BAA0B,WAAW,MAAM,eAAe;AAC1D,QAAM,SAAS,EAAE,GAAG,IAAI;AACxB,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB;AAChE,QAAM,MAAM,OAAO,UAAU,SAAS,QAAQ,KAAK;AACnD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,WAAW,GAAG,aAAa,CAAC,GAAG,GAAG,CAAC,GAAGA,UAAS,MAAM,iBAAiB,aAAa,SAAS;AACnG,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC3E;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,qDAAqD,IAAI,OAAO;AAC7F,SAAO,eAAe,SAAS,MAAM,gFAAgF,YAAY;AACjI,4BAA0B,aAAa,MAAM,eAAe;AAC5D,QAAM,SAAS,EAAE,GAAG,IAAI;AACxB,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,iBAAiB,WAAW;AAC5E,QAAM,MAAM,OAAO,UAAU,WAAW,QAAQ,KAAK;AACrD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAC9E;AACA,SAAO;AACT;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,mBAAmB,GAAG,YAAYA,UAAS,MAAM,sBAAsB,OAAO;AACrF,QAAM,KAAK,gBAAgB,GAAG,KAAK,mBAAmB;AACtD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,oBAAoB;AACpE,QAAM,SAAS,OAAO,UAAU,mBAAmB,QAAQ,KAAK;AAChE,SAAO,EAAE,QAAQ,OAAO,IAAI,SAAS,OAAO,GAAG;AACjD;AACA,IAAI,oBAAoB,GAAG,EAAE,mBAAmB,CAAC;AAGjD,SAAS,SAAS,GAAG,GAAG;AACtB,MAAI,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC1C,MAAI,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC1C,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,MAAI,GAAG,UAAU,QAAQ;AACvB,SAAK,KAAK,IAAI,OAAO;AACrB,SAAK,KAAK,IAAI,OAAO;AAAA,EACvB;AACA,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,SAAS,MAAM;AACzC;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,MAAM,GAAG,OAAO,MAAM,WAAW,OAAO;AAC/C,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,SAAS;AAC/B,SAAO,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC7C;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,MAAM,OAAO,QAAQ,WAAW;AACvC,MAAI,UAAU,aAAa;AACzB,UAAM,QAAQ,MAAM,OAAO,SAAS;AACpC,UAAM,QAAQ,MAAM,OAAO,SAAS;AACpC,WAAO,QAAQ,OAAO,KAAK;AAAA,EAC7B;AACA,QAAM,SAAS,oBAAoB,cAAc,KAAK,GAAG,KAAK;AAC9D,SAAO,OAAO,WAAW,QAAQ,OAAO,KAAK;AAC/C;AAGA,SAAS,MAAM,OAAO,QAAQ,WAAW;AACvC,MAAI,UAAU,aAAa;AACzB,UAAM,QAAQ,MAAM,OAAO,SAAS;AACpC,UAAM,QAAQ,MAAM,OAAO,SAAS;AACpC,WAAO,QAAQ,OAAO,KAAK;AAAA,EAC7B;AACA,QAAM,SAAS,mBAAmB,cAAc,KAAK,GAAG,KAAK;AAC7D,SAAO,OAAO,WAAW,QAAQ,OAAO,KAAK;AAC/C;AAGA,SAAS,SAAS,GAAG,GAAG,EAAE,WAAW,KAAK,IAAI,CAAC,GAAG;AAChD,MAAI,aAAa,QAAQ,aAAa,MAAM;AAC1C,UAAM,IAAI,UAAU,GAAG,oDAAoD;AAAA,EAC7E;AACA,MAAI,MAAM,QAAQ;AAChB,WAAO,CAAC;AAAA,EACV;AACA,MAAI,KAAK,gBAAgB,GAAG,KAAK,YAAY,aAAa,SAAS,EAAE,QAAQ,SAAS;AACtF,MAAI,MAAM,QAAQ;AAChB,WAAO,CAAC,EAAE;AAAA,EACZ;AACA,MAAI,KAAK,gBAAgB,GAAG,KAAK,YAAY,aAAa,SAAS,EAAE,QAAQ,SAAS;AACtF,QAAM,IAAI,cAAc,GAAG,KAAK;AAChC,QAAM,IAAI,cAAc,GAAG,KAAK;AAChC,MAAI,aAAa,MAAM;AACrB,SAAK,QAAQ,IAAI,CAAC,GAAG,EAAE,CAAC;AACxB,SAAK,QAAQ,IAAI,CAAC,IAAI,CAAC,CAAC;AACxB,WAAO;AAAA,MACL,OAAO,MAAM,CAAC,GAAG,CAAC,GAAG,GAAG,KAAK,GAAG,EAAE;AAAA,MAClC,OAAO,IAAI,MAAM,CAAC,GAAG,CAAC,GAAG,GAAG,KAAK,CAAC;AAAA,IACpC;AAAA,EACF;AACA,OAAK,QAAQ,IAAI,CAAC,IAAI,CAAC,CAAC;AACxB,OAAK,QAAQ,IAAI,CAAC,GAAG,EAAE,CAAC;AACxB,SAAO;AAAA,IACL,OAAO,IAAI,MAAM,CAAC,GAAG,CAAC,GAAG,GAAG,KAAK,CAAC;AAAA,IAClC,OAAO,MAAM,CAAC,GAAG,CAAC,GAAG,GAAG,KAAK,GAAG,EAAE;AAAA,EACpC;AACF;AAGA,SAAS,SAAS,GAAG,GAAG;AACtB,MAAI,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC1C,MAAI,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC1C,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,MAAI,GAAG,UAAU,QAAQ;AACvB,SAAK,KAAK,IAAI,OAAO;AACrB,SAAK,KAAK,IAAI,OAAO;AAAA,EACvB;AACA,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,SAAS,MAAM;AACzC;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,WAAW,GAAG,UAAU,MAAM;AACrC,SAAO,SAAS,aAAa,SAAS,aAAa,MAAM,+DAA+D,OAAO;AAC/H,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,MAAI,GAAG,SAAS,GAAG;AACjB,UAAM,IAAI,MAAM,gEAAgE;AAAA,EAClF;AACA,SAAO,SAAS,WAAW,GAAG,MAAM,MAAM,wCAAwC,GAAG,aAAa,SAAS,SAAS;AACpH,QAAM,cAAc,SAAS,YAAY,IAAI;AAC7C,WAAS,KAAK,GAAG,KAAK,GAAG,MAAM,MAAM;AACnC,WAAO,SAAS,IAAI,WAAW,GAAG,MAAM,uDAAuD;AAC/F,WAAO,SAAS,IAAI,MAAM,KAAK,SAAS,IAAI,MAAM,GAAG,MAAM,MAAM,eAAe,SAAS,IAAI,MAAM,KAAK,SAAS,IAAI,MAAM,GAAG,MAAM,MAAM,aAAa,MAAM,wBAAwB,yCAAyC,GAAG,MAAM,MAAM,iDAAiD,GAAG,OAAO;AAAA,EAC1S;AACA,QAAM,QAAQ,EAAE,UAAU,KAAK;AAC/B,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,WAAW,QAAQ,KAAK;AAClD;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,KAAK,GAAG,GAAG;AAClB,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,MAAI,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACtC,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,SAAS,GAAG,OAAO,MAAM,WAAW,OAAO;AAClD,MAAI,gBAAgB,GAAG,KAAK,SAAS;AACrC,QAAM,OAAO,eAAe,MAAM,EAAE,KAAK;AACzC,QAAM,QAAQ,KAAK,GAAG,MAAM,QAAQ;AACpC,MAAI,gBAAgB,MAAM;AAC1B,MAAI,CAAC,UAAU;AACb,oBAAgB,qBAAqB,MAAM,OAAO,IAAI;AAAA,EACxD;AACA,QAAM,aAAa,OAAO,IAAI,KAAK,GAAG,SAAS,GAAG,QAAQ,OAAO,aAAa,CAAC,CAAC;AAChF,QAAM,WAAW,KAAK,YAAY,MAAM,QAAQ;AAChD,SAAO,EAAE,MAAM,OAAO,SAAS;AACjC;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,cAAc,WAAW,MAAM,GAAG,GAAG;AAC5C,QAAM,QAAQ,gBAAgB,MAAM,QAAQ,cAAc;AAC1D,QAAM,KAAK,qBAAqB,GAAG,KAAK,cAAc;AACtD,QAAM,KAAK,qBAAqB,GAAG,KAAK,cAAc;AACtD,MAAI,SAAS;AACb,QAAM,YAAY,CAAC;AACnB,WAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,MAAM;AAC5C,UAAM,SAAS,UAAU,IAAI,QAAQ,GAAG,KAAK,GAAG,GAAG;AACnD,cAAU,KAAK,OAAO,EAAE;AACxB,cAAU,KAAK,OAAO,EAAE;AACxB,aAAS,OAAO;AAAA,EAClB;AACA,QAAM,OAAO,CAAC;AACd,QAAM,OAAO,CAAC;AACd,WAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,MAAM,GAAG;AAC/C,SAAK,KAAK,UAAU,GAAG;AACvB,SAAK,KAAK,UAAU,KAAK,EAAE;AAAA,EAC7B;AACA,SAAO,CAAC,MAAM,IAAI;AACpB;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,aAAa,QAAQ,YAAY,MAAM,aAAa,OAAO;AAClE,QAAM,UAAU,gBAAgB,QAAQ,UAAU,aAAa;AAC/D,QAAM,cAAc,QAAQ;AAC5B,QAAM,WAAW,QAAQ;AACzB,MAAI,cAAc,GAAG;AACnB,UAAM,IAAI,MAAM,+DAA+D,cAAc;AAAA,EAC/F;AACA,MAAI,WAAW,GAAG;AAChB,UAAM,IAAI,MAAM,gDAAgD,UAAU;AAAA,EAC5E;AACA,SAAO,QAAQ,KAAK,OAAO;AAC3B,QAAM,WAAW,aAAa,IAAI,QAAQ,SAAS,CAAC,GAAG,EAAE,CAAC,IAAI;AAC9D,QAAM,SAAS,EAAE,QAAQ,SAAS;AAClC,QAAM,QAAQ,EAAE,YAAY,MAAM,WAAW;AAC7C,QAAM,MAAM,OAAO,UAAU,aAAa,QAAQ,KAAK;AACvD,SAAO,aAAa,IAAI,QAAQ,KAAK,CAAC,IAAI,IAAI,CAAC,IAAI;AACrD;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,UAAU,GAAG,GAAG;AACvB,MAAI,KAAK,gBAAgB,GAAG,KAAK,YAAY,mBAAmB;AAChE,MAAI,KAAK,gBAAgB,GAAG,KAAK,YAAY,mBAAmB;AAChE,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,UAAU,GAAG;AACpB,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU;AAC7C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,cAAc,IAAI,IAAI;AAC7B,QAAM,MAAM,gBAAgB,IAAI,MAAM,cAAc;AACpD,QAAM,MAAM,gBAAgB,IAAI,MAAM,cAAc;AACpD,SAAO,IAAI,SAAS,KAAK,IAAI,SAAS,GAAG,MAAM,+DAA+D,IAAI,YAAY,IAAI,OAAO;AACzI,QAAM,OAAO,QAAQ,KAAK,CAAC,IAAI,CAAC,CAAC;AACjC,QAAM,OAAO,QAAQ,KAAK,CAAC,GAAG,EAAE,CAAC;AACjC,SAAO,OAAO,MAAM,IAAI;AAC1B;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,KAAK,GAAG,UAAU,gBAAgB,GAAG;AAC5C,QAAM,KAAK,gBAAgB,GAAG,KAAK,KAAK;AACxC,MAAI,GAAG,SAAS,GAAG;AACjB,UAAM,IAAI,MAAM,oDAAoD;AAAA,EACtE;AACA,QAAM,QAAQ,EAAE,UAAU,cAAc;AACxC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,QAAQ,KAAK;AAC9C;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,OAAO,GAAG,UAAU,gBAAgB,GAAG;AAC9C,SAAO,SAAS,WAAW,GAAG,MAAM,kDAAkD;AACtF,SAAO,IAAI,GAAG,CAAC,QAAQ,GAAG,aAAa;AACzC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,OAAO,GAAG,UAAU,gBAAgB,GAAG;AAC9C,SAAO,SAAS,WAAW,KAAK,SAAS,GAAG,WAAW,KAAK,SAAS,GAAG,WAAW,GAAG,MAAM,uDAAuD;AACnJ,SAAO,IAAI,GAAG,UAAU,aAAa;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,OAAO,GAAG,UAAU,gBAAgB,GAAG;AAC9C,SAAO,SAAS,WAAW,KAAK,SAAS,GAAG,WAAW,KAAK,SAAS,GAAG,WAAW,KAAK,SAAS,GAAG,WAAW,GAAG,MAAM,uDAAuD;AAC/K,SAAO,IAAI,GAAG,UAAU,aAAa;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,OAAO,GAAG,UAAU,gBAAgB,GAAG;AAC9C,SAAO,SAAS,WAAW,KAAK,SAAS,GAAG,WAAW,KAAK,SAAS,GAAG,WAAW,KAAK,SAAS,GAAG,WAAW,KAAK,SAAS,GAAG,WAAW,GAAG,MAAM,uDAAuD;AAC3M,SAAO,IAAI,GAAG,UAAU,aAAa;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,gBAAgB,GAAG,YAAY,UAAU;AAChD,QAAM,KAAK,gBAAgB,GAAG,KAAK,gBAAgB;AACnD,SAAO,GAAG,QAAQ,IAAI,WAAW,QAAQ,MAAM,cAAc,GAAG,sCAAsC,WAAW,QAAQ;AACzH,SAAO,SAAS,WAAW,WAAW,QAAQ,MAAM,qBAAqB,SAAS,wCAAwC,WAAW,QAAQ;AAC7I,SAAO,GAAG,MAAM,OAAO,CAAC,GAAG,GAAG,OAAO;AACnC,QAAI,KAAK,KAAK,MAAM,WAAW,QAAQ;AACrC,aAAO,MAAM,IAAI,SAAS,KAAK,GAAG,KAAK,SAAS,KAAK,GAAG,MAAM,WAAW,KAAK,OAAO;AAAA,IACvF;AACA,WAAO;AAAA,EACT,GAAG,IAAI,GAAG,MAAM,4BAA4B,GAAG,MAAM,MAAM,CAAC,mBAAmB,SAAS,SAAS,sCAAsC,WAAW,SAAS,GAAG;AAC9J,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,YAAY,SAAS;AACrC,SAAO,OAAO,UAAU,gBAAgB,QAAQ,KAAK;AACvD;AACA,IAAI,iBAAiB,GAAG,EAAE,gBAAgB,CAAC;AAG3C,SAAS,MAAM,QAAQ,aAAa,aAAa,MAAM,WAAWA,UAAS,iBAAiB;AAC1F,MAAI,aAAa,MAAM;AACrB,gBAAY,CAAC,GAAG,CAAC;AAAA,EACnB;AACA,MAAIA,YAAW,MAAM;AACnB,IAAAA,WAAU;AAAA,EACZ;AACA,MAAI,SAAS,GAAG;AACd,WAAO;AAAA,EACT;AACA,QAAM,KAAK,gBAAgB,QAAQ,KAAK,SAAS;AACjD,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,SAAO,+BAA+BA,UAAS,SAAS,GAAG,MAAM,qEAAqEA,2BAA0B,YAAY;AAC5K,QAAM,WAAW,kBAAkB,IAAI,OAAO,aAAaA,UAAS,WAAW,IAAI;AACnF,QAAM,WAAW,CAAC,SAAS,gBAAgB,SAAS,aAAa;AACjE,MAAI;AACJ,MAAI,SAAS,QAAQ;AACnB,kBAAc,6BAA6B,CAAC,SAAS,cAAc,SAAS,WAAW,GAAG,QAAQ;AAAA,EACpG,OAAO;AACL,kBAAc,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAAA,EAC/B;AACA,QAAM,gBAAgB,SAAS,OAAO,KAAK,SAAS,OAAO;AAC3D,QAAM,CAAC,iBAAiB,aAAa,IAAI,6BAA6B,CAAC,SAAS,UAAU,SAAS,OAAO,GAAG,UAAU,WAAW;AAClI,QAAM,eAAe,gBAAgB,OAAO;AAC5C,QAAM,aAAa,gBAAgB,MAAM,eAAe,KAAK,UAAU,eAAe;AACtF,QAAM,YAAY,gBAAgB,QAAQ,MAAM,QAAQ,YAAY,aAAaA,UAAS,cAAc,eAAe,IAAI,MAAM,QAAQ,YAAY,aAAaA,UAAS,cAAc,eAAe;AACxM,QAAM,IAAI,UAAU;AACpB,QAAM,MAAM,gBAAgB,IAAI,eAAe,GAAG,UAAU,aAAa;AACzE,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,SAAS,6BAA6B,YAAY,YAAY,aAAa;AACzE,QAAM,WAAW,YAAY,IAAI,CAAC,MAAM,EAAE,EAAE;AAC5C,QAAM,aAAa,YAAY,IAAI,CAAC,MAAM,EAAE,EAAE;AAC9C,QAAM,iBAAiB,WAAW,OAAO,UAAU,UAAU;AAC7D,QAAM,cAAc,WAAW,IAAI,CAAC,GAAG,QAAQ,IAAI,eAAe,MAAM,KAAK,CAAC;AAC9E,QAAM,SAAS,WAAW,IAAI,CAAC,IAAI,OAAO,KAAK,YAAY,GAAG;AAC9D,QAAM,WAAW,WAAW,IAAI,CAAC,GAAG,OAAO,CAAC,SAAS,KAAK,OAAO,GAAG,CAAC;AACrE,QAAM,QAAQ,WAAW,IAAI,CAAC,GAAG,OAAO,CAAC,GAAG,YAAY,GAAG,CAAC;AAC5D,SAAO,CAAC,UAAU,KAAK;AACzB;AACA,SAAS,6BAA6B,aAAa,UAAU;AAC3D,QAAM,qBAAqB,YAAY,IAAI,CAAC,IAAI,OAAO;AACrD,WAAO,MAAM,KAAK,MAAM,SAAS,MAAM;AAAA,EACzC,CAAC;AACD,QAAM,gBAAgB,mBAAmB,IAAI,CAAC,OAAO,KAAK,CAAC;AAC3D,QAAM,gBAAgB,cAAc,IAAI,CAAC,OAAO,KAAK,MAAM,KAAK,CAAC,CAAC;AAClE,QAAM,cAAc,cAAc,IAAI,CAAC,IAAI,OAAO,KAAK,cAAc,GAAG;AACxE,SAAO,cAAc,IAAI,CAAC,GAAG,OAAO;AAClC,WAAO,CAAC,cAAc,KAAK,YAAY,GAAG;AAAA,EAC5C,CAAC;AACH;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,OAAO,GAAGU,QAAO;AACxB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,gBAAgBA,QAAO,SAAS,OAAO;AACtD,QAAM,SAAS,EAAE,GAAG,IAAI,OAAO,OAAO;AACtC,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,GAAG,OAAO,MAAM,WAAW,OAAO;AAC/C,MAAI,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACvC,MAAI,GAAG,UAAU,QAAQ;AACvB,SAAK,KAAK,IAAI,OAAO;AAAA,EACvB;AACA,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,SAAS;AAC/B,SAAO,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC7C;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,MAAM,OAAO,cAAc,OAAO;AACzC,QAAMtB,QAAO,cAAc,KAAK;AAChC,MAAI,SAAS;AACb,MAAI,SAAS,QAAQ,UAAU,WAAW;AACxC,aAAS,IAAI,aAAaA,KAAI;AAAA,EAChC,WAAW,UAAU,SAAS;AAC5B,aAAS,IAAI,WAAWA,KAAI;AAAA,EAC9B,WAAW,UAAU,QAAQ;AAC3B,aAAS,IAAI,WAAWA,KAAI;AAAA,EAC9B,OAAO;AACL,UAAM,IAAI,MAAM,qBAAqB,OAAO;AAAA,EAC9C;AACA,WAAS,KAAK,GAAG,KAAKA,OAAM,MAAM;AAChC,WAAO,MAAM,aAAa;AAAA,EAC5B;AACA,SAAO,OAAO,WAAW,QAAQ,OAAO,KAAK;AAC/C;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,IAAI,aAAa,QAAQ,oBAAoB,CAAC;AAC9C,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,OAAO,cAAc,OAAO,WAAW,MAAM;AACvD,SAAK,OAAO;AACZ,SAAK,SAAS;AACd,SAAK,QAAQ;AACb,SAAK,UAAU;AACf,SAAK,YAAY;AACjB,QAAI,KAAK,WAAW;AAClB,WAAK,QAAQ,KAAK,OAAO,KAAK,SAAS;AACvC,WAAK,QAAQ,KAAK,OAAO,KAAK,SAAS;AAAA,IACzC;AACA,UAAM,YAAY,OAAO,OAAO,KAAK,OAAO;AAC5C,SAAK,SAAS,WAAW,KAAK,UAAU,SAAS,CAAC;AAAA,EACpD;AAAA,EACA,YAAY;AACV,QAAI,CAAC,MAAM,KAAK,OAAO,GAAG;AACxB,YAAM,QAAQ,KAAK;AACnB,WAAK,UAAU;AACf,aAAO;AAAA,IACT;AACA,QAAI,SAAS;AACb,QAAI,UAAU;AACd,WAAO,CAAC,SAAS;AACf,UAAI,IAAI,IAAI;AACZ,SAAG;AACD,aAAK,IAAI,KAAK,OAAO,IAAI;AACzB,aAAK,IAAI,KAAK,OAAO,IAAI;AACzB,aAAK,KAAK,KAAK,KAAK;AAAA,MACtB,SAAS,MAAM,KAAK,OAAO;AAC3B,YAAM,OAAO,KAAK,KAAK,KAAK,KAAK,IAAI,EAAE,IAAI,EAAE;AAC7C,gBAAU,KAAK,OAAO,KAAK,SAAS,KAAK;AACzC,gBAAU,KAAK,OAAO,KAAK,SAAS,KAAK;AACzC,UAAI,CAAC,KAAK,aAAa,KAAK,iBAAiB,OAAO,GAAG;AACrD,kBAAU;AAAA,MACZ;AAAA,IACF;AACA,QAAI,CAAC,KAAK,aAAa,KAAK,iBAAiB,OAAO,GAAG;AACrD,WAAK,UAAU,KAAK,aAAa,OAAO;AAAA,IAC1C;AACA,WAAO,KAAK,aAAa,OAAO;AAAA,EAClC;AAAA,EACA,aAAa,OAAO;AAClB,QAAI,KAAK,SAAS,QAAQ,KAAK,UAAU,WAAW;AAClD,aAAO;AAAA,IACT;AACA,WAAO,KAAK,MAAM,KAAK;AAAA,EACzB;AAAA,EACA,iBAAiB,OAAO;AACtB,WAAO,SAAS,KAAK,SAAS,SAAS,KAAK;AAAA,EAC9C;AACF;AACA,IAAI,YAAY,MAAM;AAAA,EACpB,YAAYsB,QAAO,MAAM,OAAO,MAAM;AACpC,SAAK,QAAQA;AACb,SAAK,OAAO,IAAI;AAChB,SAAK,QAAQ;AACb,UAAM,YAAY,OAAO,OAAO,KAAK,OAAO;AAC5C,SAAK,QAAQ,WAAW,KAAK,UAAU,SAAS,CAAC;AACjD,SAAK,QAAQ,IAAI,YAAY,GAAG,GAAG,OAAO,OAAO,KAAK,MAAM,CAAC;AAC7D,QAAIA,SAAQ,GAAG;AACb,WAAK,IAAIA,SAAQ,IAAI;AAAA,IACvB,OAAO;AACL,WAAK,IAAIA,SAAQ,IAAI;AAAA,IACvB;AACA,SAAK,IAAI,IAAI,KAAK,KAAK,IAAI,KAAK,CAAC;AAAA,EACnC;AAAA,EACA,YAAY;AACV,QAAI,IAAI,IAAI,IAAI,GAAG,GAAG;AACtB,WAAO,MAAM;AACX,SAAG;AACD,YAAI,KAAK,MAAM,UAAU;AACzB,YAAI,IAAI,KAAK,IAAI;AAAA,MACnB,SAAS,KAAK;AACd,WAAK,IAAI;AACT,WAAK,IAAI;AACT,WAAK,IAAI,QAAQ,KAAK;AACtB,WAAK,MAAM,KAAK,KAAK,KAAK,IAAI,IAAI,KAAK,IAAI,CAAC;AAC5C,UAAI,KAAK,MAAM;AACf,UAAI,IAAI,MAAM,KAAK,IAAI,CAAC,IAAI,IAAI;AAC9B;AAAA,MACF;AAAA,IACF;AACA,QAAI,IAAI,KAAK,OAAO,KAAK,IAAI;AAC7B,QAAI,KAAK,QAAQ,GAAG;AAClB,WAAK,KAAK,IAAI,KAAK,MAAM,GAAG,IAAI,KAAK,KAAK;AAAA,IAC5C;AACA,WAAO,KAAK,aAAa,CAAC;AAAA,EAC5B;AAAA,EACA,aAAa,OAAO;AAClB,QAAI,KAAK,UAAU,WAAW;AAC5B,aAAO;AAAA,IACT;AACA,WAAO,KAAK,MAAM,KAAK;AAAA,EACzB;AACF;AACA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,OAAO,GAAG,OAAO,GAAG,OAAO,MAAM;AAC3C,SAAK,iBAAiB,MAAM,KAAK,SAAS,QAAQ,KAAK,UAAU;AACjE,SAAK,MAAM;AACX,SAAK,QAAQ,OAAO;AACpB,SAAK,QAAQ;AACb,QAAI,QAAQ,MAAM;AAChB,aAAO,KAAK,OAAO;AAAA,IACrB;AACA,QAAI,OAAO,SAAS,UAAU;AAC5B,aAAO,KAAK,SAAS;AAAA,IACvB;AACA,QAAI,CAAC,KAAK,eAAe,KAAK,KAAK,SAAS,GAAG;AAC7C,YAAM,IAAI,MAAM,0BAA0B,UAAU,kCAAkC;AAAA,IACxF;AACA,SAAK,SAAS,WAAW,KAAK,IAAI;AAAA,EACpC;AAAA,EACA,aAAa,OAAO;AAClB,QAAI,KAAK,eAAe,GAAG;AACzB,aAAO;AAAA,IACT;AACA,WAAO,KAAK,MAAM,KAAK;AAAA,EACzB;AAAA,EACA,YAAY;AACV,WAAO,KAAK,aAAa,KAAK,MAAM,KAAK,QAAQ,KAAK,OAAO,CAAC;AAAA,EAChE;AACF;AAGA,SAAS,aAAa,OAAOA,QAAO,OAAO,GAAG,QAAQ,WAAW,MAAM;AACrE,MAAI,QAAQ,MAAM;AAChB,WAAO;AAAA,EACT;AACA,MAAI,SAAS,MAAM;AACjB,YAAQ;AAAA,EACV;AACA,MAAI,UAAU,aAAa,UAAU,SAAS;AAC5C,UAAM,IAAI,MAAM,yBAAyB,OAAO;AAAA,EAClD;AACA,QAAM,SAAS,IAAI,UAAUA,QAAO,MAAM,OAAO,IAAI;AACrD,QAAM,MAAM,OAAO,OAAO,KAAK;AAC/B,WAAS,KAAK,GAAG,KAAK,IAAI,OAAO,QAAQ,MAAM;AAC7C,QAAI,OAAO,MAAM,OAAO,UAAU;AAAA,EACpC;AACA,SAAO,IAAI,SAAS;AACtB;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,cAAc,OAAO,QAAQ,GAAG,SAAS,GAAG,OAAO,MAAM;AAChE,MAAI,SAAS,QAAQ,UAAU,QAAQ;AACrC,UAAM,IAAI,MAAM,yBAAyB,OAAO;AAAA,EAClD;AACA,QAAM,YAAY,IAAI,YAAY,OAAO,QAAQ,OAAO,OAAO,IAAI;AACnE,QAAM,MAAM,OAAO,OAAO,KAAK;AAC/B,WAAS,KAAK,GAAG,KAAK,IAAI,OAAO,QAAQ,MAAM;AAC7C,QAAI,OAAO,MAAM,UAAU,UAAU;AAAA,EACvC;AACA,SAAO,IAAI,SAAS;AACtB;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,sBAAsB,OAAO,OAAO,MAAM;AACjD,MAAI,SAAS,QAAQ,UAAU,QAAQ;AACrC,UAAM,IAAI,MAAM,yBAAyB,OAAO;AAAA,EAClD;AACA,SAAO,aAAa,OAAO,GAAG,GAAG,OAAO,IAAI;AAC9C;AACA,IAAI,uBAAuB,GAAG,EAAE,sBAAsB,CAAC;AAGvD,SAAS,eAAe,OAAO,SAAS,GAAG,SAAS,GAAG,QAAQ,WAAW,MAAM;AAC9E,QAAM,MAAM,OAAO,OAAO,KAAK;AAC/B,QAAM,SAAS,IAAI,cAAc,QAAQ,QAAQ,MAAM,IAAI;AAC3D,WAAS,KAAK,GAAG,KAAK,IAAI,OAAO,QAAQ,MAAM;AAC7C,QAAI,OAAO,MAAM,OAAO,UAAU;AAAA,EACpC;AACA,SAAO,IAAI,SAAS;AACtB;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,MAAM,OAAO,MAAM,QAAQ,GAAG,QAAQ,WAAW;AACxD,MAAI,UAAU,GAAG;AACf,UAAM,IAAI,MAAM,4BAA4B;AAAA,EAC9C;AACA,QAAM,QAAQ,EAAE,OAAO,MAAM,MAAM,OAAO,MAAM;AAChD,SAAO,OAAO,UAAU,OAAO,CAAC,GAAG,KAAK;AAC1C;AAGA,SAAS,YAAY,GAAG;AACtB,QAAM,KAAK,gBAAgB,GAAG,KAAK,YAAY;AAC/C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,YAAY,MAAM;AAC5C;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,SAAS,GAAG,MAAM;AACzB,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,MAAM,KAAK;AAC3B,SAAO,OAAO,UAAU,SAAS,QAAQ,KAAK;AAChD;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,WAAW,GAAG;AACrB,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,qDAAqD,GAAG,OAAO;AAC3F,SAAO,QAAQ,IAAI,CAAC;AACtB;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,WAAW,GAAG,MAAM;AAC3B,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,qDAAqD,GAAG,OAAO;AAC3F,SAAO,QAAQ,IAAI,IAAI;AACzB;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,WAAW,GAAG,MAAM;AAC3B,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,qDAAqD,GAAG,OAAO;AAC3F,SAAO,QAAQ,IAAI,IAAI;AACzB;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,WAAW,GAAG,MAAM;AAC3B,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,qDAAqD,GAAG,OAAO;AAC3F,SAAO,QAAQ,IAAI,IAAI;AACzB;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,SAAS,GAAG,EAAE,OAAO,CAAC;AAG1B,SAAS,OAAO,GAAG;AACjB,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS,SAAS;AACrD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,OAAO,MAAM;AACvC;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,iBAAiB,GAAG,iBAAiB,iBAAiBV,UAAS,MAAM,WAAW,CAAC,GAAG,CAAC,GAAG,aAAa,QAAQ;AACpH,QAAM,KAAK,gBAAgB,GAAG,KAAK,iBAAiB;AACpD,QAAM,mBAAmB,gBAAgB,iBAAiB,mBAAmB,iBAAiB;AAC9F,QAAM,mBAAmB,gBAAgB,iBAAiB,mBAAmB,iBAAiB;AAC9F,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,MAAI,eAAe,QAAQ;AACzB,UAAM,IAAI,MAAM,oFAAoF;AAAA,EACtG;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,gEAAgE,IAAI,OAAO;AACxG,SAAO,iBAAiB,SAAS,GAAG,MAAM,2EAA2E,iBAAiB,OAAO;AAC7I,SAAO,iBAAiB,SAAS,GAAG,MAAM,2EAA2E,iBAAiB,OAAO;AAC7I,SAAO,iBAAiB,MAAM,OAAO,GAAG,MAAM,yFAAyF,iBAAiB,MAAM,KAAK;AACnK,SAAO,iBAAiB,MAAM,OAAO,GAAG,MAAM,yFAAyF,iBAAiB,MAAM,KAAK;AACnK,QAAM,aAAa,iBAAiB,MAAM;AAC1C,QAAM,oBAAoB,iBAAiB,MAAM;AACjD,SAAO,iBAAiB,MAAM,OAAO,aAAa,mBAAmB,MAAM,6EAA6E,aAAa,8BAA8B,iBAAiB,MAAM,KAAK;AAC/N,QAAM,YAAY,gBAAgB,KAAK,kBAAkBA,UAAS,MAAM,YAAY,QAAQ;AAC5F,QAAM,kBAAkB;AACxB,QAAM,MAAM,OAAO,WAAW,kBAAkB,iBAAiB,SAAS,UAAU;AACpF,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,kBAAkB,GAAG,EAAE,iBAAiB,CAAC;AAG7C,eAAe,gBAAgB,GAAG,GAAG;AACnC,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW;AAC9C,SAAO,GAAG,UAAU,GAAG,OAAO,MAAM,kDAAkD,GAAG,iBAAiB,GAAG,SAAS;AACtH,SAAO,GAAG,SAAS,GAAG,MAAM,qCAAqC,GAAG,SAAS;AAC7E,SAAO,GAAG,SAAS,GAAG,MAAM,qCAAqC,GAAG,SAAS;AAC7E,QAAM,QAAQ,MAAM,GAAG,KAAK;AAC5B,QAAM,QAAQ,MAAM,GAAG,KAAK;AAC5B,QAAM,OAAO,IAAI,IAAI,KAAK;AAC1B,MAAIQ,cAAa;AACjB,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,QAAI,CAAC,KAAK,IAAI,MAAM,GAAG,GAAG;AACxB,MAAAA;AAAA,IACF;AAAA,EACF;AACA,QAAM,UAAU,IAAI,aAAa,CAACA,WAAU,GAAG,GAAG,KAAK;AACvD,QAAM,UAAU,IAAI,aAAa,CAACA,WAAU,GAAG,OAAO;AACtD,WAAS,KAAK,GAAG,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AAChD,QAAI,CAAC,KAAK,IAAI,MAAM,GAAG,GAAG;AACxB,cAAQ,OAAO,MAAM,MAAM;AAC3B,cAAQ,OAAO,MAAM;AACrB;AAAA,IACF;AAAA,EACF;AACA,SAAO,CAAC,QAAQ,SAAS,GAAG,QAAQ,SAAS,CAAC;AAChD;AACA,IAAI,iBAAiB;AAGrB,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO,SAAS;AACnD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,MAAM,GAAG;AAChB,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,SAAS,GAAG,OAAOpB,OAAM;AAChC,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,mDAAmD,GAAG,aAAa;AAC/F,SAAO,MAAM,IAAI,CAAC,KAAK,GAAG,CAACA,KAAI,CAAC;AAClC;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,SAAS,GAAG,OAAOA,OAAM;AAChC,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,mDAAmD,GAAG,aAAa;AAC/F,SAAO,MAAM,IAAI,OAAOA,KAAI;AAC9B;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,SAAS,GAAG,OAAOA,OAAM;AAChC,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,mDAAmD,GAAG,aAAa;AAC/F,SAAO,MAAM,IAAI,OAAOA,KAAI;AAC9B;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,SAAS,GAAG,OAAOA,OAAM;AAChC,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,SAAS,GAAG,MAAM,mDAAmD,GAAG,aAAa;AAC/F,SAAO,MAAM,IAAI,OAAOA,KAAI;AAC9B;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,SAAS,QAAQ,MAAM,IAAI;AAClC,QAAM,UAAU,gBAAgB,QAAQ,UAAU,WAAW,SAAS;AACtE,MAAI,QAAQ,IAAI;AACd,UAAM,QAAQ,OAAO;AAAA,EACvB;AACA,MAAI,QAAQ,QAAQ,OAAO,GAAG;AAC5B,UAAM,MAAM,4EAA4E,QAAQ,oBAAoB,KAAK;AAAA,EAC3H;AACA,QAAM,SAAS,EAAE,QAAQ,QAAQ;AACjC,QAAM,QAAQ,EAAE,IAAI;AACpB,SAAO,OAAO,UAAU,SAAS,QAAQ,KAAK;AAChD;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,KAAK,QAAQ;AACpB,SAAO,OAAO,UAAU,aAAa,MAAM,6DAA6D,OAAO,QAAQ;AACvH,QAAM,SAAS,EAAE,OAAO,OAAO;AAC/B,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,MAAM,QAAQ;AACrB,SAAO,OAAO,UAAU,aAAa,MAAM,8DAA8D,OAAO,QAAQ;AACxH,QAAM,SAAS,EAAE,OAAO,OAAO;AAC/B,SAAO,OAAO,UAAU,MAAM,MAAM;AACtC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,OAAO,QAAQ;AACtB,QAAM,qBAAqB,OAAO,MAAM,OAAO,MAAM,SAAS;AAC9D,QAAM,QAAQ,OAAO,OAAO;AAC5B,MAAI;AACJ,MAAI,sBAAsB,GAAG;AAC3B,UAAM,eAAe,QAAQ,QAAQ,CAAC,OAAO,kBAAkB,CAAC;AAChE,UAAM,KAAK,YAAY;AAAA,EACzB,OAAO;AACL,UAAM,cAAc,CAAC,OAAO,KAAK,qBAAqB,EAAE;AACxD,UAAM,YAAY,QAAQ,KAAK,MAAM,GAAG,CAAC,OAAO,kBAAkB,CAAC;AACnE,UAAM,YAAY,QAAQ,KAAK,MAAM,GAAG,CAAC,OAAO,kBAAkB,CAAC;AACnE,UAAM,gBAAgB,QAAQ,MAAM,WAAW,CAAC,GAAG,CAAC,GAAG,CAAC,OAAO,qBAAqB,CAAC,CAAC,GAAG,CAAC;AAC1F,UAAM,gBAAgB,IAAI,QAAQ,MAAM,WAAW,CAAC,GAAG,CAAC,GAAG,CAAC,OAAO,qBAAqB,CAAC,CAAC,GAAG,CAAC,GAAG,OAAO,EAAE,CAAC;AAC3G,UAAM,KAAK,OAAO,CAAC,WAAW,aAAa,GAAG,CAAC;AAC/C,UAAM,KAAK,OAAO,CAAC,WAAW,aAAa,GAAG,CAAC;AAC/C,UAAM,eAAe,QAAQ,QAAQ,IAAI,EAAE,GAAG,CAAC,YAAY,IAAI,YAAY,EAAE,CAAC;AAC9E,UAAM,KAAK,YAAY;AAAA,EACzB;AACA,QAAM,KAAK,GAAG;AACd,MAAI,OAAO,SAAS,KAAK,OAAO,MAAM,OAAO,GAAG;AAC9C,UAAM,OAAO;AACb,UAAM,SAAS,OAAO,MAAM;AAC5B,UAAM,QAAQ,KAAK,CAAC,QAAQ,IAAI,MAAM,KAAK,QAAQ,IAAI,MAAM,EAAE,CAAC;AAChE,SAAK,QAAQ;AAAA,EACf;AACA,SAAO;AACT;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,OAAO,GAAG,iBAAiB,OAAO,GAAG;AAC5C,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO;AAC1C,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,OAAO,EAAE,iBAAiB,KAAK;AACrC,SAAO,OAAO,UAAU,QAAQ,QAAQ,IAAI;AAC9C;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,QAAQ,WAAW;AAChC,SAAO,OAAO,UAAU,WAAW,MAAM,mDAAmD,OAAO,OAAO;AAC1G,MAAI,qBAAqB,OAAO,MAAM,OAAO,MAAM,SAAS;AAC5D,QAAM,QAAQ,OAAO,OAAO;AAC5B,MAAI;AACJ,MAAI,aAAa,QAAQ,YAAY,oBAAoB;AACvD,UAAM,QAAQ,OAAO,MAAM,IAAI,CAAC,MAAM,CAAC;AACvC,UAAMA,QAAO,OAAO,MAAM,IAAI,CAAC,MAAM,CAAC;AACtC,IAAAA,MAAK,OAAO,MAAM,SAAS,KAAK;AAChC,oBAAgB,MAAM,QAAQ,OAAOA,KAAI;AACzC,yBAAqB;AAAA,EACvB,WAAW,aAAa,QAAQ,YAAY,oBAAoB;AAC9D,UAAM,aAAa,OAAO,MAAM,IAAI,CAAC,MAAM,CAAC;AAC5C,eAAW,OAAO,MAAM,SAAS,KAAK,YAAY;AAClD,oBAAgB,OAAO,CAAC,QAAQ,MAAM,UAAU,CAAC,GAAG,OAAO,MAAM,SAAS,CAAC;AAC3E,yBAAqB;AAAA,EACvB,OAAO;AACL,oBAAgB;AAAA,EAClB;AACA,QAAM,aAAa,UAAU,aAAa;AAC1C,QAAM,eAAe,QAAQ,QAAQ,eAAe,UAAU,GAAG,CAAC,OAAO,kBAAkB,CAAC;AAC5F,QAAM,MAAM,IAAI,YAAY;AAC5B,QAAMuB,QAAO,KAAK,MAAM,qBAAqB,CAAC,IAAI;AAClD,QAAM,aAAa,KAAK,GAAG;AAC3B,QAAM,aAAa,KAAK,GAAG;AAC3B,QAAM,uBAAuB,MAAM,YAAY,CAACA,OAAM,qBAAqBA,KAAI,GAAG,WAAW,MAAM,SAAS,CAAC;AAC7G,QAAM,uBAAuB,MAAM,YAAY,CAACA,OAAM,qBAAqBA,KAAI,GAAG,WAAW,MAAM,SAAS,CAAC;AAC7G,QAAM,cAAc,cAAc,MAAM,MAAM;AAC9C,cAAY,cAAc,MAAM,SAAS,KAAKA;AAC9C,SAAO,QAAQ,QAAQ,qBAAqB,IAAI,qBAAqB,EAAE,GAAG,WAAW;AACvF;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,mBAAmB,GAAG,GAAG;AAChC,MAAI,KAAK,gBAAgB,GAAG,KAAK,mBAAmB;AACpD,MAAI,KAAK,gBAAgB,GAAG,KAAK,mBAAmB;AACpD,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,6BAA2B,GAAG,OAAO,GAAG,KAAK;AAC7C,QAAM,SAAS,EAAE,GAAG,IAAI,GAAG,GAAG;AAC9B,QAAM,QAAQ,CAAC;AACf,SAAO,OAAO,UAAU,mBAAmB,QAAQ,KAAK;AAC1D;AACA,IAAI,oBAAoB,GAAG,EAAE,mBAAmB,CAAC;AAGjD,SAAS,SAAS,GAAG,MAAM;AACzB,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW,mBAAmB;AACjE,SAAO,QAAQ,IAAI,aAAa,GAAG,OAAO,IAAI,EAAE,QAAQ;AAC1D;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,OAAO,SAAS,OAAO,GAAG;AACjC,QAAM,WAAW,qBAAqB,SAAS,WAAW,SAAS,mBAAmB;AACtF,SAAO,SAAS,UAAU,GAAG,MAAM,sCAAsC;AACzE,MAAI,SAAS,SAAS,GAAG;AACvB,WAAO,QAAQ,SAAS,GAAG,MAAM,MAAM,oCAAoC;AAAA,EAC7E;AACA,QAAM,SAAS;AACf,QAAM,QAAQ,EAAE,KAAK;AACrB,SAAO,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC7C;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,GAAGD,SAAQ,GAAG;AAC3B,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,OAAAA,OAAM;AACtB,SAAO,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC7C;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,cAAc,GAAG,OAAO,KAAKV,UAAS,YAAY,GAAG,UAAU,GAAG,eAAe,GAAG,cAAc,GAAG,iBAAiB,GAAG;AAChI,QAAM,KAAK,gBAAgB,GAAG,KAAK,gBAAgB,mBAAmB;AACtE,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ;AAAA,IACZ;AAAA,IACA;AAAA,IACA,SAAAA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACA,SAAO,OAAO,UAAU,cAAc,QAAQ,KAAK;AACrD;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,KAAK,GAAG;AACf,QAAM,KAAK,gBAAgB,GAAG,KAAK,OAAO,SAAS;AACnD,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,SAAO,OAAO,UAAU,KAAK,MAAM;AACrC;AACA,IAAI,MAAM,GAAG,EAAE,KAAK,CAAC;AAGrB,SAAS,SAAS,QAAQ,OAAO;AAC/B,gBAAc,MAAM;AACpB,QAAM,gBAAgB,WAAW,QAAQ,KAAK;AAC9C,MAAI,cAAc,WAAW,GAAG;AAC9B,UAAM,IAAI,MAAM,oDAAoD;AAAA,EACtE;AACA,QAAM,QAAQ;AACd,SAAO,WAAW,QAAQ,OAAO,eAAe,KAAK;AACvD;AAGA,SAAS,SAAS,QAAQ,OAAO,OAAO;AACtC,gBAAc,MAAM;AACpB,MAAI,SAAS,QAAQ,MAAM,WAAW,GAAG;AACvC,UAAM,IAAI,MAAM,+CAA+C;AAAA,EACjE;AACA,QAAM,gBAAgB,WAAW,QAAQ,KAAK;AAC9C,MAAI,cAAc,WAAW,KAAK,cAAc,WAAW,GAAG;AAC5D,UAAM,IAAI,MAAM,gEAAgE;AAAA,EAClF;AACA,MAAI,cAAc,WAAW,KAAK,SAAS,MAAM;AAC/C,UAAM,IAAI,MAAM,8EAA8E;AAAA,EAChG;AACA,SAAO,WAAW,QAAQ,OAAO,eAAe,KAAK;AACvD;AAGA,SAAS,SAAS,QAAQ,OAAO,OAAO;AACtC,gBAAc,MAAM;AACpB,MAAI,SAAS,QAAQ,MAAM,WAAW,GAAG;AACvC,UAAM,IAAI,MAAM,gDAAgD;AAAA,EAClE;AACA,QAAM,gBAAgB,WAAW,QAAQ,KAAK;AAC9C,MAAI,cAAc,WAAW,KAAK,cAAc,WAAW,GAAG;AAC5D,UAAM,IAAI,MAAM,oEAAoE;AAAA,EACtF;AACA,MAAI,cAAc,WAAW,KAAK,SAAS,MAAM;AAC/C,UAAM,IAAI,MAAM,yEAAyE;AAAA,EAC3F;AACA,SAAO,WAAW,QAAQ,OAAO,eAAe,KAAK;AACvD;AAGA,SAAS,SAAS,QAAQ,OAAO,OAAO;AACtC,gBAAc,MAAM;AACpB,MAAI,SAAS,QAAQ,MAAM,WAAW,GAAG;AACvC,UAAM,IAAI,MAAM,gDAAgD;AAAA,EAClE;AACA,QAAM,gBAAgB,WAAW,QAAQ,KAAK;AAC9C,MAAI,cAAc,WAAW,KAAK,cAAc,WAAW,GAAG;AAC5D,UAAM,IAAI,MAAM,sEAAsE;AAAA,EACxF;AACA,MAAI,cAAc,WAAW,KAAK,SAAS,MAAM;AAC/C,UAAM,IAAI,MAAM,yEAAyE;AAAA,EAC3F;AACA,SAAO,WAAW,QAAQ,OAAO,eAAe,KAAK;AACvD;AAGA,SAAS,SAAS,QAAQ,OAAO,OAAO;AACtC,gBAAc,MAAM;AACpB,MAAI,SAAS,QAAQ,MAAM,WAAW,GAAG;AACvC,UAAM,IAAI,MAAM,+CAA+C;AAAA,EACjE;AACA,QAAM,gBAAgB,WAAW,QAAQ,KAAK;AAC9C,MAAI,cAAc,WAAW,KAAK,cAAc,WAAW,GAAG;AAC5D,UAAM,IAAI,MAAM,wEAAwE;AAAA,EAC1F;AACA,MAAI,cAAc,WAAW,KAAK,SAAS,MAAM;AAC/C,UAAM,IAAI,MAAM,yEAAyE;AAAA,EAC3F;AACA,UAAQ,SAAS;AACjB,SAAO,WAAW,QAAQ,OAAO,eAAe,KAAK;AACvD;AAGA,SAAS,MAAM,GAAG,IAAI,GAAG,SAAS,MAAM;AACtC,QAAM,KAAK,gBAAgB,GAAG,KAAK,MAAM;AACzC,MAAI,GAAG,SAAS,GAAG;AACjB,UAAM,IAAI,MAAM,oDAAoD;AAAA,EACtE;AACA,QAAM,UAAU,GAAG,MAAM,GAAG,MAAM,SAAS;AAC3C,MAAI,IAAI,GAAG;AACT,UAAM,IAAI,MAAM,6CAA6C,GAAG;AAAA,EAClE;AACA,MAAI,IAAI,SAAS;AACf,UAAM,IAAI,MAAM,uDAAuD,oBAAoB,GAAG;AAAA,EAChG;AACA,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,GAAG,OAAO;AAC1B,QAAM,CAAC,QAAQ,OAAO,IAAI,OAAO,UAAU,MAAM,QAAQ,KAAK;AAC9D,SAAO,EAAE,QAAQ,QAAQ;AAC3B;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,iBAAiB,OAAO,QAAQ,GAAG,SAAS,GAAG,OAAO,MAAM;AACnE,MAAI,SAAS,QAAQ,UAAU,QAAQ;AACrC,UAAM,IAAI,MAAM,mCAAmC;AAAA,EACrD;AACA,QAAM,YAAY,IAAI,YAAY,OAAO,QAAQ,OAAO,MAAM,IAAI;AAClE,QAAM,MAAM,OAAO,OAAO,KAAK;AAC/B,WAAS,KAAK,GAAG,KAAK,IAAI,OAAO,QAAQ,MAAM;AAC7C,QAAI,OAAO,MAAM,UAAU,UAAU;AAAA,EACvC;AACA,SAAO,IAAI,SAAS;AACtB;AACA,IAAI,kBAAkB,GAAG,EAAE,iBAAiB,CAAC;AAG7C,SAAS,QAAQ,GAAG,OAAO,GAAG;AAC5B,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU,mBAAmB;AAChE,SAAO,GAAG,OAAO,GAAG,MAAM,sCAAsC;AAChE,QAAM,SAAS,EAAE,GAAG,GAAG;AACvB,QAAM,QAAQ,EAAE,KAAK;AACrB,QAAM,CAAC,QAAQ,OAAO,IAAI,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAChE,SAAO,EAAE,QAAQ,QAAQ;AAC3B;AACA,IAAI,SAAS,GAAG,EAAE,QAAQ,CAAC;AAG3B,SAAS,oBAAoB,GAAG,YAAY,aAAa;AACvD,QAAM,KAAK,gBAAgB,GAAG,KAAK,oBAAoB;AACvD,QAAM,cAAc,gBAAgB,YAAY,cAAc,sBAAsB,OAAO;AAC3F,SAAO,MAAM,WAAW,GAAG,MAAM,kCAAkC;AACnE,QAAM,SAAS,EAAE,GAAG,IAAI,YAAY,YAAY;AAChD,QAAM,QAAQ,EAAE,YAAY;AAC5B,SAAO,OAAO,UAAU,oBAAoB,QAAQ,KAAK;AAC3D;AACA,IAAI,qBAAqB,GAAG,EAAE,oBAAoB,CAAC;AAGnD,SAAS,SAAS,GAAG,OAAO,GAAG;AAC7B,QAAM,KAAK,gBAAgB,GAAG,KAAK,WAAW,mBAAmB;AACjE,SAAO,QAAQ,CAAC,GAAG,MAAM,UAAU,OAAO,GAAG,MAAM,QAAQ,MAAM,UAAU,oBAAoB,GAAG,MAAM,WAAW,GAAG,MAAM,SAAS;AACrI,QAAM,SAAS,EAAE,OAAO,GAAG;AAC3B,QAAM,QAAQ,EAAE,KAAK;AACrB,SAAO,OAAO,UAAU,QAAQ,QAAQ,KAAK;AAC/C;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,WAAW,gBAAgB,QAAQ;AAC1C,SAAO,aAAa,gBAAgB,QAAQ,OAAO;AACrD;AAGA,SAAS,SAAS,cAAc,YAAY,MAAM,MAAM,OAAO;AAC7D,SAAO,OAAO,aAAa,cAAc,WAAW,MAAM,KAAK;AACjE;AAGA,SAAS,UAAU,WAAW,UAAU;AACtC,QAAM,UAAU,CAAC;AACjB,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,QAAI,SAAS,KAAK;AAChB,cAAQ,KAAK,EAAE;AAAA,IACjB;AAAA,EACF;AACA,QAAM,WAAW,OAAO,WAAW,OAAO;AAC1C,QAAM,MAAM,OAAO,CAAC,QAAQ,QAAQ,UAAU,MAAM,GAAG,OAAO;AAC9D,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,UAAM,MAAM,SAAS,WAAW,QAAQ,GAAG;AAC3C,UAAM,SAAS,KAAK,UAAU;AAC9B,QAAI,OAAO,IAAI,KAAK,MAAM;AAAA,EAC5B;AACA,SAAO,IAAI,SAAS;AACtB;AAGA,eAAe,YAAY,WAAW;AACpC,QAAM,aAAa,gBAAgB,WAAW,aAAa,cAAc,MAAM;AAC/E,QAAM,OAAO,MAAM,WAAW,KAAK;AACnC,QAAM,MAAM,UAAU,WAAW,OAAO,IAAI;AAC5C,MAAI,cAAc,YAAY;AAC5B,eAAW,QAAQ;AAAA,EACrB;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAGjB,eAAe,kBAAkB,SAASP,OAAM,MAAM;AACpD,QAAM,UAAU,gBAAgB,SAAS,UAAU,UAAU;AAC7D,QAAM,QAAQ,gBAAgBA,OAAM,QAAQ,YAAY,MAAM;AAC9D,QAAM,WAAW,QAAQ,OAAO,IAAI;AACpC,QAAM,UAAU,MAAM;AACtB,QAAM,cAAc,QAAQ;AAC5B,SAAO,UAAU,GAAG,MAAM,uBAAuB;AACjD,oBAAkB,YAAY,MAAM,UAAU,WAAW,OAAO,GAAG,MAAM,OAAO,mEAAmE;AACnJ,MAAI,cAAc;AAClB,WAAS,KAAK,UAAU,KAAK,WAAW,SAAS,MAAM;AACrD,mBAAe,YAAY;AAAA,EAC7B;AACA,QAAM,oBAAoB,YAAY,MAAM,GAAG,QAAQ,EAAE,OAAO,CAAC,WAAW,GAAG,YAAY,MAAM,WAAW,OAAO,CAAC;AACpH,QAAM,iBAAiB,QAAQ,SAAS,iBAAiB;AACzD,QAAM,eAAe,QAAQ,OAAO,CAAC,EAAE,CAAC;AACxC,QAAM,oBAAoB,MAAM,WAAW,YAAY;AACvD,QAAM,UAAU,QAAQ,mBAAmB,CAAC,CAAC,CAAC;AAC9C,QAAM,MAAM,OAAO,gBAAgB,SAAS,QAAQ;AACpD,MAAI,YAAY,SAAS;AACvB,YAAQ,QAAQ;AAAA,EAClB;AACA,MAAIA,UAAS,OAAO;AAClB,UAAM,QAAQ;AAAA,EAChB;AACA,UAAQ,QAAQ;AAChB,iBAAe,QAAQ;AACvB,eAAa,QAAQ;AACrB,oBAAkB,QAAQ;AAC1B,SAAO;AACT;AACA,IAAI,mBAAmB;AAGvB,SAAS,eAAe,GAAG,GAAG,OAAO,OAAO,aAAa,MAAM;AAC7D,QAAM,KAAK,gBAAgB,GAAG,KAAK,eAAe;AAClD,QAAM,KAAK,gBAAgB,GAAG,KAAK,eAAe;AAClD,QAAM,SAAS,gBAAgB,OAAO,SAAS,eAAe;AAC9D,mBAAiB,IAAI,EAAE;AACvB,SAAO,YAAY,GAAG,OAAO,GAAG,KAAK,GAAG,MAAM,2BAA2B;AACzE,QAAM,MAAM,OAAO,CAAC;AACpB,QAAM,gBAAgB,IAAI,KAAK,MAAM;AACrC,MAAI,SAAS,IAAI,IAAI,IAAI,EAAE,GAAG,aAAa;AAC3C,MAAI,YAAY;AACd,WAAO,SAAS,MAAM,MAAM,gDAAgD;AAC5E,UAAM,QAAQ,gBAAgB,OAAO,QAAQ,eAAe;AAC5D,aAAS,IAAI,QAAQ,IAAI,KAAK,IAAI,QAAQ,KAAK,CAAC,CAAC;AAAA,EACnD;AACA,SAAO,KAAK,IAAI,MAAM;AACxB;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,WAAW,SAAS,SAAS,OAAO;AAC3C,QAAM,WAAW,gBAAgB,SAAS,WAAW,aAAa,OAAO;AACzE,QAAM,WAAW,gBAAgB,SAAS,WAAW,WAAW;AAChE,gBAAc,UAAU,UAAU,KAAK;AACvC,QAAM,SAAS,EAAE,SAAS,UAAU,SAAS,SAAS;AACtD,QAAM,QAAQ,EAAE,MAAM;AACtB,SAAO,OAAO,UAAU,WAAW,QAAQ,KAAK;AAClD;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,eAAe,eAAe,cAAc,aAAa,eAAe;AAC/E,MAAI,cAAc,UAAU,SAAS;AACnC,UAAM,IAAI,MAAM,8EAA8E,cAAc,QAAQ;AAAA,EACtH;AACA,MAAI,cAAc,OAAO,GAAG;AAC1B,UAAM,IAAI,MAAM,sEAAsE,cAAc,QAAQ;AAAA,EAC9G;AACA,QAAM,WAAW,cAAc,OAAO,IAAI,cAAc,MAAM,KAAK;AACnE,QAAM,UAAU,cAAc,OAAO,IAAI,cAAc,MAAM,KAAK;AAClE,MAAI,YAAY,WAAW,SAAS;AAClC,UAAM,IAAI,MAAM,kDAAkD,YAAY,sBAAsB,UAAU;AAAA,EAChH;AACA,QAAM,YAAY,aAAa;AAC/B,MAAI,EAAE,aAAa,SAAS,KAAK,aAAa,SAAS,KAAK,cAAc,WAAW;AACnF,UAAM,IAAI,MAAM,oCAAoC,aAAa,2BAA2B,WAAW;AAAA,EACzG;AACA,MAAI,aAAa,UAAU,cAAc,OAAO;AAC9C,UAAM,IAAI,MAAM,mDAAmD;AAAA,EACrE;AACF;AAGA,SAAS,eAAe,eAAe,cAAc,aAAa,eAAe,GAAG;AAClF,QAAM,iBAAiB,gBAAgB,eAAe,iBAAiB,iBAAiB,OAAO;AAC/F,QAAM,gBAAgB,gBAAgB,cAAc,gBAAgB,iBAAiB,mBAAmB;AACxG,QAAM,gBAAgB,gBAAgB,cAAc,gBAAgB,iBAAiB,cAAc,KAAK;AACxG,iBAAe,gBAAgB,eAAe,aAAa,aAAa;AACxE,QAAM,SAAS;AAAA,IACb,eAAe;AAAA,IACf,cAAc;AAAA,IACd,cAAc;AAAA,EAChB;AACA,QAAM,QAAQ,EAAE,YAAY;AAC5B,SAAO,OAAO,UAAU,eAAe,QAAQ,KAAK;AACtD;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,UAAU,GAAG,SAAS;AAC7B,QAAM,WAAW,gBAAgB,SAAS,WAAW,YAAY,OAAO;AACxE,QAAM,KAAK,gBAAgB,GAAG,KAAK,YAAY,mBAAmB;AAClE,QAAM,SAAS,EAAE,QAAQ,IAAI,SAAS,SAAS;AAC/C,SAAO,OAAO,UAAU,UAAU,MAAM;AAC1C;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,cAAc,GAAG,YAAY;AACpC,MAAI,cAAc,MAAM;AACtB,WAAO,EAAE,MAAM,MAAM;AAAA,EACvB;AACA,MAAI,YAAY,EAAE,OAAO,UAAU,GAAG;AACpC,WAAO;AAAA,EACT;AACA,MAAI,EAAE,MAAM,WAAW,WAAW,QAAQ;AACxC,UAAM,eAAe,CAAC;AACtB,aAAS,KAAK,GAAG,KAAK,EAAE,MAAM,QAAQ,MAAM;AAC1C,UAAI,WAAW,OAAO,QAAQ,EAAE,MAAM,OAAO,MAAM;AACjD,qBAAa,KAAK,EAAE,MAAM,GAAG;AAAA,MAC/B,OAAO;AACL,qBAAa,KAAK,WAAW,GAAG;AAAA,MAClC;AAAA,IACF;AACA,WAAO;AAAA,EACT;AACA,SAAO;AACT;AAGA,SAAS,SAAS,GAAG,MAAM,YAAY,MAAM;AAC3C,QAAM,KAAK,gBAAgB,GAAG,KAAK,SAAS;AAC5C,SAAO,GAAG,UAAU,WAAW,MAAM,gFAAgF,GAAG,uBAAuB;AAC/I,SAAO,QAAQ,KAAK,OAAO,GAAG,MAAM,qDAAqD,OAAO;AAChG,MAAI,SAAS,GAAG;AACd,WAAO,aAAa,SAAS,GAAG,MAAM,IAAI;AAAA,EAC5C;AACA,QAAM,cAAc,cAAc,IAAI,UAAU;AAChD,QAAM,WAAW,IAAI;AACrB,QAAM,aAAa,IAAI,MAAM,KAAK,cAAc,aAAa,GAAG,GAAG,WAAW,IAAI,GAAG,QAAQ,CAAC,GAAG,QAAQ;AACzG,SAAO,IAAI,IAAI,UAAU;AAC3B;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,oBAAoB,OAAO;AAClC,SAAO,KAAK,MAAM,KAAK,IAAI,GAAG,KAAK,KAAK,KAAK,IAAI,KAAK,IAAI,KAAK,IAAI,CAAC,CAAC,CAAC,CAAC;AACzE;AACA,SAAS,aAAa,cAAc,GAAG,GAAG;AACxC,QAAM,OAAO,IAAI,eAAe;AAChC,QAAM,YAAY,IAAI,aAAa,YAAY;AAC/C,WAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,UAAM,SAAS,IAAI,KAAK,KAAK,MAAM,eAAe,OAAO;AACzD,cAAU,MAAM,IAAI,IAAI,KAAK,IAAI,MAAM;AAAA,EACzC;AACA,SAAO,SAAS,WAAW,SAAS;AACtC;AAGA,eAAe,aAAa,aAAa,SAAS,IAAI,GAAG;AACvD,QAAM,eAAe,gBAAgB,aAAa,eAAe,QAAQ;AACzE,QAAM,WAAW,gBAAgB,SAAS,WAAW,QAAQ;AAC7D,SAAO,aAAa,OAAO,GAAG,MAAM,uEAAuE,aAAa,MAAM;AAC9H,SAAO,aAAa,OAAO,MAAM,SAAS,MAAM,MAAM,mFAAmF,aAAa,yBAAyB,SAAS,MAAM;AAC9L,oBAAkB,aAAa,MAAM,MAAM,GAAG,aAAa,MAAM,SAAS,CAAC,GAAG,SAAS,OAAO,yFAAyF;AACvL,QAAM,UAAU,aAAa,MAAM,aAAa,MAAM,SAAS;AAC/D,SAAO,IAAI,KAAK,KAAK,SAAS,MAAM,4EAA4E,qBAAqB,GAAG;AACxI,QAAM,kBAAkB,MAAM,aAAa,KAAK;AAChD,QAAM,cAAc,MAAM,SAAS,KAAK;AACxC,QAAM,CAAC,OAAOL,KAAI,IAAI,CAAC,gBAAgB,SAAS,SAAS,OAAO;AAChE,QAAM,aAAa,uBAAuB,QAAQ,KAAK;AACvD,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,UAAM,SAAS,IAAIA;AACnB,UAAM,OAAO,gBAAgB,SAAS,QAAQ,SAASA,KAAI;AAC3D,UAAM,YAAY,CAAC;AACnB,aAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,gBAAU,KAAK,EAAE,OAAO,KAAK,KAAK,OAAO,GAAG,CAAC;AAAA,IAC/C;AACA,cAAU,KAAK,CAAC,GAAG,OAAO,GAAG,QAAQ,EAAE,KAAK;AAC5C,eAAW,KAAK;AAChB,aAAS,KAAK,GAAG,KAAK,GAAG,MAAM;AAC7B,UAAI,UAAU,IAAI,UAAU,YAAY,IAAI;AAC1C,mBAAW,KAAK;AAChB;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,MAAI,gBAAgB,cAAc;AAChC,iBAAa,QAAQ;AAAA,EACvB;AACA,MAAI,YAAY,UAAU;AACxB,aAAS,QAAQ;AAAA,EACnB;AACA,SAAO,OAAO,YAAY,SAAS,OAAO,MAAM;AAClD;AACA,IAAI,cAAc;AAGlB,IAAI,oBAAoB,CAAC;AACzBH,UAAS,mBAAmB;AAAA,EAC1B,QAAQ,MAAM;AAAA,EACd,iBAAiB,MAAM;AAAA,EACvB,QAAQ,MAAM;AAChB,CAAC;AAGD,SAAS,sBAAsB,GAAG,IAAI,aAAae,UAAS,MAAM,aAAa,QAAQ,iBAAiB;AACtG,MAAI,MAAM;AACV,MAAI,EAAE,SAAS,GAAG;AAChB,UAAM,QAAQ,GAAG,CAAC,GAAG,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,EAAE,CAAC;AAAA,EAC1D;AACA,MAAI,OAAO;AACX,MAAI,KAAK,SAAS,GAAG;AACnB,WAAO,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC/D;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,iEAAiE,IAAI,QAAQ;AAC1G,SAAO,KAAK,SAAS,GAAG,MAAM,8DAA8D,KAAK,QAAQ;AACzG,SAAO,YAAY,WAAW,GAAG,MAAM,mEAAmE,cAAc;AACxH,QAAM,UAAU,eAAe,SAAS,IAAI,MAAM,KAAK,IAAI,MAAM;AACjE,QAAM,WAAW,eAAe,SAAS,KAAK,MAAM,KAAK,KAAK,MAAM;AACpE,SAAO,YAAY,YAAY,IAAI,MAAM,4CAA4C,8CAA8C,YAAY,KAAK;AACpJ,SAAO,aAAa,YAAY,IAAI,MAAM,0CAA0C,iDAAiD,YAAY,MAAM;AACvJ,4BAA0B,mBAAmB,MAAM,eAAe;AAClE,QAAM,SAAS,EAAE,GAAG,KAAK,IAAI,KAAK;AAClC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,iBAAiB,YAAY;AAC7E,SAAO,OAAO,UAAU,sBAAsB,QAAQ,KAAK;AAC7D;AACA,IAAI,uBAAuB,GAAG,EAAE,sBAAsB,CAAC;AAGvD,SAAS,qBAAqB,IAAI,GAAG,aAAa;AAChD,MAAI,eAAe,QAAQ,gBAAgB,UAAU;AACnD,WAAO;AAAA,EACT;AACA,MAAI,gBAAgB,QAAQ;AAC1B,WAAO,IAAI,IAAI,KAAK,CAAC,CAAC;AAAA,EACxB;AACA,QAAM,IAAI,MAAM,gDAAgD,cAAc;AAChF;AACA,SAAS,qBAAqB,MAAM,cAAc;AAChD,MAAI,MAAM;AACV,QAAM,aAAa,iBAAiB,KAAK,OAAO,aAAa,KAAK;AAClE,MAAI,WAAW,SAAS,GAAG;AACzB,UAAM,KAAK,KAAK,UAAU;AAAA,EAC5B;AACA,SAAO,QAAQ,KAAK,KAAK,KAAK;AAChC;AACA,SAAS,gBAAgB,GAAG,aAAa,wBAAwB,gBAAgB;AAC/E,MAAI,gBAAgB,UAAU;AAC5B,WAAO;AAAA,EACT,WAAW,gBAAgB,QAAQ;AACjC,WAAO,KAAK,CAAC;AAAA,EACf,WAAW,gBAAgB,OAAO;AAChC,WAAO,IAAI,CAAC;AAAA,EACd,WAAW,gBAAgB,SAAS;AAClC,WAAO,MAAM,CAAC;AAAA,EAChB,WAAW,gBAAgB,SAAS;AAClC,WAAO,MAAM,GAAG,sBAAsB;AAAA,EACxC,WAAW,gBAAgB,aAAa;AACtC,WAAO,UAAU,GAAG,cAAc;AAAA,EACpC,WAAW,gBAAgB,WAAW;AACpC,WAAO,QAAQ,CAAC;AAAA,EAClB;AACA,QAAM,IAAI,MAAM,4BAA4B,cAAc;AAC5D;AACA,IAAI,aAAa,CAAC,eAAe,gBAAgB;AAC/C,QAAM,eAAe,gBAAgB;AACrC,SAAO,CAAC,gBAAgB,gBAAgB;AAC1C;AAGA,SAAS,aAAa,EAAE,GAAG,QAAQ,SAAAA,UAAS,KAAK,MAAM,aAAa,QAAQ,YAAY,CAAC,GAAG,CAAC,GAAG,iBAAiB,MAAM,YAAY,cAAc,UAAU,wBAAwB,eAAe,GAAG;AACnM,gBAAc,eAAe;AAC7B,MAAI,WAAW,OAAO,MAAM,eAAe,WAAW,MAAM,OAAO;AACjE,WAAO,eAAe,QAAQ,MAAM,4CAA4C,uHAAuH;AACvM,QAAI,SAAS,OAAO,GAAG,QAAQA,UAAS,MAAM,YAAY,WAAW,eAAe;AACpF,QAAI,QAAQ,MAAM;AAChB,eAAS,KAAK,QAAQ,IAAI;AAAA,IAC5B;AACA,WAAO,gBAAgB,QAAQ,aAAa,wBAAwB,cAAc;AAAA,EACpF;AACA,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU,SAAS;AACtD,QAAM,UAAU,gBAAgB,QAAQ,UAAU,UAAU,SAAS;AACrE,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,6DAA6D,IAAI,OAAO;AACrG,SAAO,QAAQ,SAAS,GAAG,MAAM,8DAA8D,QAAQ,OAAO;AAC9G,4BAA0B,gBAAgB,MAAM,eAAe;AAC/D,QAAM,gBAAgB,eAAe,SAAS,IAAI,MAAM,KAAK,IAAI,MAAM;AACvE,SAAO,QAAQ,MAAM,OAAO,eAAe,MAAM,oCAAoC,oDAAoD,QAAQ,MAAM,KAAK;AAC5J,SAAO,+BAA+BA,UAAS,SAAS,GAAG,MAAM,uEAAuEA,2BAA0B,YAAY;AAC9K,QAAM,WAAW,kBAAkB,IAAI,OAAO,QAAQ,OAAOA,UAAS,WAAW,MAAM,eAAe;AACtG,MAAI;AACJ,MAAI,QAAQ,MAAM;AAChB,YAAQ,gBAAgB,MAAM,QAAQ,cAAc;AACpD,KAAC,KAAK,IAAI,eAAe,OAAO,EAAE;AAClC,QAAI,eAAe,QAAQ;AACzB,iCAA2B,SAAS,UAAU,MAAM,KAAK;AAAA,IAC3D,OAAO;AACL,aAAO,MAAM,MAAM,UAAU,GAAG,MAAM,2GAA2G,MAAM,MAAM,SAAS;AACtK,aAAO,MAAM,MAAM,WAAW,KAAK,MAAM,MAAM,OAAO,SAAS,eAAe,MAAM,MAAM,OAAO,GAAG,MAAM,sCAAsC,MAAM,gEAAgE,SAAS,cAAc;AAAA,IAC/O;AAAA,EACF;AACA,MAAI;AACJ,MAAI,0BAA0B,MAAM;AAClC,UAAM,aAAa,uBAAuB;AAC1C,WAAO,WAAW,UAAU,KAAK,WAAW,WAAW,GAAG,MAAM,2HAA2H,WAAW,SAAS;AAC/M,QAAI,WAAW,WAAW,GAAG;AAC3B,aAAO,WAAW,OAAO,KAAK,WAAW,OAAO,SAAS,aAAa,MAAM,oDAAoD,qEAAqE,SAAS,eAAe;AAAA,IAC/N,WAAW,WAAW,WAAW,GAAG;AAClC,UAAI;AACF,mCAA2B,YAAY,SAAS,QAAQ;AAAA,MAC1D,SAAS,IAAP;AACA,cAAM,SAAS,oDAAoD,sEAAsE,SAAS;AAClJ,cAAM,MAAM,MAAM;AAAA,MACpB;AAAA,IACF;AACA,8BAA0B,gBAAgB,wBAAwB,iBAAiB,cAAc;AAAA,EACnG;AACA,QAAM,QAAQ,CAAC,IAAI,UAAU;AAC3B,WAAO,eAAe,QAAQ,MAAM,wDAAwD,kDAAkD;AAC9I,UAAM,CAAC,UAAU,MAAM,GAAG,MAAM,IAAI;AACpC,UAAM,eAAe,qBAAqB,IAAI,GAAG,WAAW;AAC5D,WAAO,kBAAkB,SAAS,GAAG,MAAM,uHAAuH,YAAY;AAC9K,UAAM,OAAO,oBAAoB,KAAK,OAAO,cAAc,UAAUA,UAAS,IAAI;AAClF,UAAM,YAAY,qBAAqB,MAAM,cAAc,SAAS,OAAOA,UAAS,IAAI;AACxF,UAAM,MAAM,CAAC,MAAM,SAAS;AAC5B,QAAI,UAAU,MAAM;AAClB,YAAM,UAAU,qBAAqB,QAAQ,YAAY;AACzD,UAAI,KAAK,OAAO;AAAA,IAClB;AACA,WAAO;AAAA,EACT;AACA,QAAM,SAAS;AAAA,IACb,GAAG;AAAA,IACH,QAAQ;AAAA,IACR,MAAM;AAAA,IACN,wBAAwB;AAAA,EAC1B;AACA,QAAM,QAAQ;AAAA,IACZ,SAAAA;AAAA,IACA,KAAK;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA,YAAY;AAAA,IACZ;AAAA,EACF;AACA,MAAI,QAAQ,MAAM;AAChB,UAAM,WAAW,WAAW,CAAC,MAAM,SAAS,SAAS;AACnD,UAAI,MAAM,OAAO,UAAU,aAAa,QAAQ,KAAK;AACrD,WAAK,CAAC,SAAS,MAAM,GAAG,CAAC;AACzB,UAAI,cAAc;AAChB,cAAM,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,MAC/D;AACA,aAAO,EAAE,OAAO,KAAK,UAAU,MAAM;AAAA,IACvC,CAAC;AACD,WAAO,SAAS,KAAK,OAAO;AAAA,EAC9B,OAAO;AACL,UAAM,mBAAmB,WAAW,CAAC,MAAM,SAAS,OAAO,SAAS;AAClE,UAAI,MAAM,OAAO,UAAU,aAAa,QAAQ,KAAK;AACrD,WAAK,CAAC,SAAS,MAAM,KAAK,KAAK,CAAC;AAChC,UAAI,cAAc;AAChB,cAAM,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,MAC/D;AACA,aAAO,EAAE,OAAO,KAAK,UAAU,MAAM;AAAA,IACvC,CAAC;AACD,WAAO,iBAAiB,KAAK,SAAS,KAAK;AAAA,EAC7C;AACF;AACA,IAAI,UAAU,GAAG,EAAE,aAAa,CAAC;AAGjC,SAAS,qCAAqC,GAAG,IAAI,aAAaA,UAAS,MAAM,YAAY,CAAC,GAAG,CAAC,GAAG,iBAAiB;AACpH,MAAI,MAAM;AACV,MAAI,EAAE,SAAS,GAAG;AAChB,UAAM,QAAQ,GAAG,CAAC,GAAG,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,EAAE,CAAC;AAAA,EAC1D;AACA,MAAI,OAAO;AACX,MAAI,KAAK,SAAS,GAAG;AACnB,WAAO,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC/D;AACA,QAAM,SAAS,EAAE,GAAG,KAAK,IAAI,KAAK;AAClC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,iBAAiB,WAAW,YAAY;AAC5E,SAAO,OAAO,UAAU,qCAAqC,QAAQ,KAAK;AAC5E;AACA,IAAI,sCAAsC,GAAG,EAAE,qCAAqC,CAAC;AAGrF,SAAS,oCAAoC,QAAQ,IAAI,QAAQA,UAAS,MAAM,YAAY,CAAC,GAAG,CAAC,GAAG,iBAAiB;AACnH,MAAI,OAAO;AACX,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,WAAO,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC/D;AACA,QAAM,SAAS,EAAE,IAAI,MAAM,OAAO;AAClC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,iBAAiB,WAAW,YAAY,OAAO;AACnF,QAAM,MAAM,OAAO,UAAU,oCAAoC,QAAQ,KAAK;AAC9E,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,qCAAqC,GAAG,EAAE,oCAAoC,CAAC;AAGnF,SAAS,sBAAsB,EAAE,GAAG,QAAQ,SAAAA,UAAS,KAAK,MAAM,aAAa,QAAQ,YAAY,CAAC,GAAG,CAAC,GAAG,iBAAiB,MAAM,YAAY,cAAc,UAAU,wBAAwB,eAAe,GAAG;AAC5M,MAAI,WAAW,OAAO,MAAM,eAAe,WAAW,MAAM,OAAO;AACjE,QAAI,SAAS,gBAAgB,GAAG,QAAQA,UAAS,MAAM,YAAY,WAAW,eAAe;AAC7F,QAAI,QAAQ,MAAM;AAChB,eAAS,KAAK,QAAQ,IAAI;AAAA,IAC5B;AACA,WAAO,gBAAgB,QAAQ,aAAa,wBAAwB,cAAc;AAAA,EACpF;AACA,QAAM,KAAK,gBAAgB,GAAG,KAAK,mBAAmB,SAAS;AAC/D,QAAM,UAAU,gBAAgB,QAAQ,UAAU,mBAAmB,SAAS;AAC9E,MAAI,MAAM;AACV,MAAI,eAAe;AACnB,MAAI,GAAG,SAAS,GAAG;AACjB,mBAAe;AACf,UAAM,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC9D;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,sEAAsE,IAAI,OAAO;AAC9G,SAAO,QAAQ,SAAS,GAAG,MAAM,uEAAuE,QAAQ,OAAO;AACvH,SAAO,IAAI,MAAM,OAAO,QAAQ,MAAM,IAAI,MAAM,6DAA6D,IAAI,MAAM,qDAAqD,QAAQ,MAAM,KAAK;AAC/L,MAAI,aAAa,MAAM;AACrB,gBAAY,CAAC,GAAG,CAAC;AAAA,EACnB;AACA,SAAO,+BAA+BA,UAAS,SAAS,GAAG,MAAM,sFAAsFA,2BAA0B,YAAY;AAC7L,4BAA0B,yBAAyB,MAAM,eAAe;AACxE,QAAM,WAAW,kBAAkB,IAAI,OAAO,QAAQ,OAAOA,UAAS,WAAW,MAAM,iBAAiB,IAAI;AAC5G,MAAI;AACJ,MAAI,QAAQ,MAAM;AAChB,YAAQ,gBAAgB,MAAM,QAAQ,cAAc;AACpD,KAAC,KAAK,IAAI,eAAe,OAAO,EAAE;AAClC,+BAA2B,SAAS,UAAU,MAAM,KAAK;AAAA,EAC3D;AACA,MAAI;AACJ,MAAI,0BAA0B,MAAM;AAClC,8BAA0B,gBAAgB,wBAAwB,iBAAiB,uBAAuB;AAAA,EAC5G;AACA,QAAM,QAAQ,CAAC,IAAI,UAAU;AAC3B,WAAO,kBAAkB,SAAS,GAAG,MAAM,mHAAmH,YAAY;AAC1K,UAAM,CAAC,UAAU,MAAM,GAAG,KAAK,IAAI;AACnC,UAAM,eAAe,qBAAqB,IAAI,GAAG,WAAW;AAC5D,UAAM,OAAO,mCAAmC,KAAK,OAAO,cAAc,UAAUA,UAAS,MAAM,WAAW,eAAe;AAC7H,UAAM,YAAY,oCAAoC,MAAM,cAAc,SAAS,OAAOA,UAAS,MAAM,WAAW,eAAe;AACnI,QAAI,SAAS,MAAM;AACjB,YAAM,UAAU,qBAAqB,OAAO,YAAY;AACxD,aAAO,CAAC,MAAM,WAAW,OAAO;AAAA,IAClC;AACA,WAAO,CAAC,MAAM,SAAS;AAAA,EACzB;AACA,QAAM,SAAS;AAAA,IACb,GAAG;AAAA,IACH,QAAQ;AAAA,IACR,MAAM;AAAA,IACN,wBAAwB;AAAA,EAC1B;AACA,QAAM,QAAQ;AAAA,IACZ,SAAAA;AAAA,IACA,KAAK;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA,YAAY;AAAA,IACZ;AAAA,EACF;AACA,MAAI,QAAQ,MAAM;AAChB,UAAM,WAAW,WAAW,CAAC,MAAM,SAAS,SAAS;AACnD,UAAI,MAAM,OAAO,UAAU,sBAAsB,QAAQ,KAAK;AAC9D,WAAK,CAAC,SAAS,MAAM,GAAG,CAAC;AACzB,UAAI,cAAc;AAChB,cAAM,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,MAC/D;AACA,aAAO,EAAE,OAAO,KAAK,UAAU,MAAM;AAAA,IACvC,CAAC;AACD,WAAO,SAAS,KAAK,OAAO;AAAA,EAC9B,OAAO;AACL,UAAM,mBAAmB,WAAW,CAAC,MAAM,SAAS,OAAO,SAAS;AAClE,UAAI,MAAM,OAAO,UAAU,sBAAsB,QAAQ,KAAK;AAC9D,WAAK,CAAC,SAAS,MAAM,KAAK,KAAK,CAAC;AAChC,UAAI,cAAc;AAChB,cAAM,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,MAC/D;AACA,aAAO,EAAE,OAAO,KAAK,UAAU,MAAM;AAAA,IACvC,CAAC;AACD,WAAO,iBAAiB,KAAK,SAAS,KAAK;AAAA,EAC7C;AACF;AACA,IAAI,mBAAmB,GAAG,EAAE,sBAAsB,CAAC;AAGnD,SAAS,aAAa,EAAE,GAAG,GAAG,aAAa,OAAO,aAAa,OAAO,MAAM,YAAY,cAAc,UAAU,wBAAwB,iBAAiB,IAAI,GAAG;AAC9J,MAAI,WAAW,OAAO,MAAM,eAAe,WAAW,MAAM,OAAO;AACjE,QAAI,SAAS,OAAO,GAAG,GAAG,YAAY,UAAU;AAChD,QAAI,QAAQ,MAAM;AAChB,eAAS,KAAK,QAAQ,IAAI;AAAA,IAC5B;AACA,WAAO,gBAAgB,QAAQ,aAAa,wBAAwB,cAAc;AAAA,EACpF;AACA,MAAI,KAAK,gBAAgB,GAAG,KAAK,cAAc;AAC/C,MAAI,KAAK,gBAAgB,GAAG,KAAK,cAAc;AAC/C,GAAC,IAAI,EAAE,IAAI,eAAe,IAAI,EAAE;AAChC,QAAM,cAAc,aAAa,GAAG,MAAM,GAAG,OAAO,KAAK,GAAG,MAAM,GAAG,OAAO;AAC5E,QAAM,cAAc,aAAa,GAAG,MAAM,GAAG,OAAO,KAAK,GAAG,MAAM,GAAG,OAAO;AAC5E,QAAM,cAAc,aAAa,GAAG,MAAM,GAAG,OAAO,KAAK,GAAG,MAAM,GAAG,OAAO;AAC5E,QAAM,cAAc,aAAa,GAAG,MAAM,GAAG,OAAO,KAAK,GAAG,MAAM,GAAG,OAAO;AAC5E,QAAM,aAAa,GAAG,MAAM,MAAM,GAAG,EAAE;AACvC,QAAM,aAAa,GAAG,MAAM,MAAM,GAAG,EAAE;AACvC,QAAM,YAAY,cAAc,UAAU;AAC1C,QAAM,YAAY,cAAc,UAAU;AAC1C,SAAO,gBAAgB,aAAa,MAAM,wCAAwC,qBAAqB,uCAAuC,GAAG,aAAa,GAAG,wBAAwB,6BAA6B,wBAAwB;AAC9O,QAAM,oBAAoB,2BAA2B,GAAG,MAAM,MAAM,GAAG,EAAE,GAAG,GAAG,MAAM,MAAM,GAAG,EAAE,CAAC;AACjG,QAAM,WAAW,kBAAkB,OAAO,CAAC,aAAa,WAAW,CAAC;AACpE,QAAM,MAAM,aAAa,QAAQ,IAAI,CAAC,WAAW,aAAa,WAAW,CAAC,IAAI,QAAQ,IAAI,CAAC,WAAW,aAAa,WAAW,CAAC;AAC/H,QAAM,MAAM,aAAa,QAAQ,IAAI,CAAC,WAAW,aAAa,WAAW,CAAC,IAAI,QAAQ,IAAI,CAAC,WAAW,aAAa,WAAW,CAAC;AAC/H,MAAI;AACJ,MAAI,QAAQ,MAAM;AAChB,YAAQ,gBAAgB,MAAM,QAAQ,cAAc;AACpD,KAAC,KAAK,IAAI,eAAe,OAAO,EAAE;AAClC,+BAA2B,UAAU,MAAM,KAAK;AAAA,EAClD;AACA,MAAI;AACJ,MAAI,0BAA0B,MAAM;AAClC,8BAA0B,gBAAgB,wBAAwB,iBAAiB,cAAc;AAAA,EACnG;AACA,QAAM,QAAQ,CAAC,IAAI,UAAU;AAC3B,UAAM,CAAC,MAAM,MAAM,GAAG,MAAM,IAAI;AAChC,UAAM,eAAe,qBAAqB,QAAQ,IAAI,EAAE,KAAK,GAAG,GAAG,WAAW;AAC9E,QAAI;AACJ,QAAI;AACJ,QAAI,CAAC,cAAc,CAAC,YAAY;AAC9B,aAAO,OAAO,cAAc,MAAM,OAAO,IAAI;AAC7C,aAAO,OAAO,MAAM,cAAc,MAAM,KAAK;AAAA,IAC/C,WAAW,CAAC,cAAc,YAAY;AACpC,aAAO,OAAO,cAAc,MAAM,OAAO,KAAK;AAC9C,aAAO,OAAO,cAAc,MAAM,MAAM,KAAK;AAAA,IAC/C,WAAW,cAAc,CAAC,YAAY;AACpC,aAAO,OAAO,MAAM,cAAc,OAAO,IAAI;AAC7C,aAAO,OAAO,MAAM,cAAc,OAAO,KAAK;AAAA,IAChD,OAAO;AACL,aAAO,OAAO,MAAM,cAAc,MAAM,IAAI;AAC5C,aAAO,OAAO,cAAc,MAAM,MAAM,IAAI;AAAA,IAC9C;AACA,QAAI,QAAQ,MAAM;AAChB,YAAM,UAAU,qBAAqB,QAAQ,YAAY;AACzD,aAAO,CAAC,MAAM,MAAM,OAAO;AAAA,IAC7B,OAAO;AACL,aAAO,CAAC,MAAM,IAAI;AAAA,IACpB;AAAA,EACF;AACA,QAAM,SAAS;AAAA,IACb,GAAG;AAAA,IACH,GAAG;AAAA,IACH,MAAM;AAAA,IACN,wBAAwB;AAAA,EAC1B;AACA,QAAM,QAAQ,EAAE,YAAY,YAAY,YAAY,aAAa,eAAe;AAChF,MAAI,QAAQ,MAAM;AAChB,UAAM,WAAW,WAAW,CAAC,MAAM,MAAM,SAAS;AAChD,YAAM,MAAM,OAAO,UAAU,cAAc,QAAQ,KAAK;AACxD,WAAK,CAAC,MAAM,MAAM,GAAG,CAAC;AACtB,aAAO,EAAE,OAAO,QAAQ,KAAK,QAAQ,GAAG,UAAU,MAAM;AAAA,IAC1D,CAAC;AACD,WAAO,SAAS,KAAK,GAAG;AAAA,EAC1B,OAAO;AACL,UAAM,mBAAmB,WAAW,CAAC,MAAM,MAAM,QAAQ,SAAS;AAChE,YAAM,MAAM,OAAO,UAAU,cAAc,QAAQ,KAAK;AACxD,WAAK,CAAC,MAAM,MAAM,KAAK,MAAM,CAAC;AAC9B,aAAO,EAAE,OAAO,QAAQ,KAAK,QAAQ,GAAG,UAAU,MAAM;AAAA,IAC1D,CAAC;AACD,WAAO,iBAAiB,KAAK,KAAK,KAAK;AAAA,EACzC;AACF;AACA,IAAI,UAAU,GAAG,EAAE,aAAa,CAAC;AAGjC,SAAS,eAAe,cAAc;AACpC,SAAO,aAAa,cAAc,MAAM,IAAI;AAC9C;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,YAAY,cAAc;AACjC,SAAO,aAAa,cAAc,KAAK,GAAG;AAC5C;AACA,IAAI,aAAa,GAAG,EAAE,YAAY,CAAC;AAGnC,SAAS,OAAO,SAAS,aAAa,WAAW,SAAS,OAAO,WAAW,GAAG;AAC7E,MAAI,QAAQ;AACZ,QAAM,SAAS,CAAC;AAChB,SAAO,QAAQ,eAAe,QAAQ,MAAM;AAC1C,WAAO,KAAK,MAAM,SAAS,OAAO,WAAW,CAAC;AAC9C,aAAS;AAAA,EACX;AACA,MAAI,QAAQ;AACV,WAAO,QAAQ,QAAQ,MAAM;AAC3B,YAAM,SAAS,QAAQ,cAAc,QAAQ;AAC7C,YAAM,OAAO,OAAO;AAAA,QAClB,MAAM,SAAS,OAAO,cAAc,MAAM;AAAA,QAC1C,KAAK,CAAC,MAAM,GAAG,QAAQ;AAAA,MACzB,CAAC;AACD,aAAO,KAAK,IAAI;AAChB,eAAS;AAAA,IACX;AAAA,EACF;AACA,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,SAAS,CAAC,GAAG,CAAC,GAAG,WAAW,CAAC;AAAA,EACtC;AACA,SAAO,QAAQ,OAAO,MAAM,GAAG,CAAC,OAAO,QAAQ,WAAW,CAAC;AAC7D;AACA,IAAI,QAAQ,GAAG,EAAE,OAAO,CAAC;AAGzB,SAAS,MAAM,SAAS,aAAa,WAAW,WAAW,WAAW,YAAY;AAChF,MAAI,aAAa,MAAM;AACrB,gBAAY,oBAAoB,WAAW;AAAA,EAC7C;AACA,QAAM,eAAe,MAAM,SAAS,aAAa,SAAS;AAC1D,QAAM,iBAAiB,IAAI,cAAc,SAAS,WAAW,CAAC;AAC9D,SAAO,KAAK,gBAAgB,SAAS;AACvC;AACA,IAAI,OAAO,GAAG,EAAE,MAAM,CAAC;AAGvB,SAAS,eAAe,QAAQ,OAAO,QAAQ,UAAU,SAAS,YAAY,qBAAqB,GAAG;AACpG,QAAM,SAAS,gBAAgB,QAAQ,SAAS,eAAe;AAC/D,QAAM,SAAS,gBAAgB,OAAO,SAAS,iBAAiB,SAAS;AACzE,QAAM,UAAU,gBAAgB,QAAQ,UAAU,iBAAiB,OAAO;AAC1E,QAAM,WAAW,OAAO,MAAM;AAC9B,SAAO,OAAO,SAAS,GAAG,MAAM,6DAA6D,OAAO,OAAO;AAC3G,SAAO,OAAO,SAAS,KAAK,OAAO,MAAM,OAAO,GAAG,MAAM,oDAAoD,6BAA6B,OAAO,QAAQ;AACzJ,SAAO,QAAQ,SAAS,KAAK,QAAQ,MAAM,OAAO,UAAU,MAAM,qDAAqD,2BAA2B,OAAO,QAAQ;AACjK,SAAO,SAAS,WAAW,GAAG,MAAM,wEAAwE,SAAS,SAAS;AAC9H,SAAO,SAAS,MAAM,KAAK,SAAS,MAAM,GAAG,MAAM,2CAA2C,UAAU;AACxG,SAAO,WAAW,cAAc,WAAW,WAAW,MAAM,+CAA+C,QAAQ;AACnH,QAAM,SAAS,EAAE,OAAO,QAAQ,OAAO,QAAQ,QAAQ,QAAQ;AAC/D,QAAM,QAAQ,EAAE,QAAQ,oBAAoB,SAAS;AACrD,QAAM,MAAM,OAAO,UAAU,eAAe,QAAQ,KAAK;AACzD,SAAO;AACT;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,eAAe,QAAQ;AAC9B,QAAM,SAAS,gBAAgB,QAAQ,SAAS,iBAAiB,SAAS;AAC1E,SAAO,OAAO,SAAS,GAAG,MAAM,6DAA6D,OAAO,OAAO;AAC3G,QAAM,SAAS,EAAE,OAAO,OAAO;AAC/B,QAAM,MAAM,OAAO,UAAU,eAAe,QAAQ,CAAC,CAAC;AACtD,SAAO;AACT;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,gBAAgB,QAAQ;AAC/B,QAAM,SAAS,gBAAgB,QAAQ,SAAS,gBAAgB;AAChE,QAAM,cAAc,OAAO,OAAO;AAClC,QAAM,WAAW,OAAO,MAAM;AAC9B,SAAO,OAAO,QAAQ,GAAG,MAAM,yEAAyE,OAAO,OAAO;AACtH,SAAO,aAAa,GAAG,MAAM,+FAA+F,WAAW;AACvI,QAAM,OAAO,IAAI,MAAM,OAAO,IAAI;AAClC,OAAK,KAAK,GAAG,GAAG,WAAW;AAC3B,OAAK,eAAe;AACpB,SAAO,KAAK,QAAQ,IAAI;AAC1B;AACA,IAAI,iBAAiB,GAAG,EAAE,gBAAgB,CAAC;AAG3C,SAAS,kBAAkB,QAAQ,SAAS,YAAY,GAAG,SAAS,KAAK;AACvE,QAAM,SAAS,gBAAgB,QAAQ,SAAS,oBAAoB,SAAS;AAC7E,SAAO,OAAO,SAAS,GAAG,MAAM,gEAAgE,OAAO,OAAO;AAC9G,QAAM,SAAS,EAAE,OAAO,OAAO;AAC/B,QAAM,QAAQ,EAAE,SAAS,WAAW,OAAO;AAC3C,QAAM,MAAM,OAAO,UAAU,kBAAkB,QAAQ,KAAK;AAC5D,SAAO;AACT;AACA,IAAI,mBAAmB,GAAG,EAAE,kBAAkB,CAAC;AAG/C,SAAS,sBAAsB,OAAO,QAAQ,eAAe,cAAc,gBAAgB,cAAc;AACvG,MAAI,gBAAgB,MAAM;AACxB,mBAAe;AAAA,EACjB;AACA,MAAI,kBAAkB,MAAM;AAC1B,qBAAiB,OAAO;AAAA,EAC1B;AACA,MAAI,gBAAgB,MAAM;AACxB,mBAAe;AAAA,EACjB;AACA,QAAM,WAAW,MAAM,MAAM;AAC7B,kBAAgB,KAAK,IAAI,eAAe,QAAQ;AAChD,SAAO,KAAK,gBAAgB,gBAAgB,GAAG,MAAM,4CAA4C,eAAe;AAChH,SAAO,MAAM,SAAS,GAAG,MAAM,+CAA+C,MAAM,OAAO;AAC3F,SAAO,MAAM,MAAM,OAAO,GAAG,MAAM,oDAAoD,MAAM,MAAM,IAAI;AACvG,SAAO,OAAO,SAAS,GAAG,MAAM,4BAA4B;AAC5D,SAAO,OAAO,MAAM,OAAO,UAAU,MAAM,sDAAsD,qBAAqB,OAAO,MAAM,IAAI;AACvI,SAAO,KAAK,gBAAgB,gBAAgB,GAAG,MAAM,4CAA4C,eAAe;AAChH,SAAO,EAAE,eAAe,cAAc,gBAAgB,aAAa;AACrE;AAGA,SAAS,mBAAmB,OAAO,QAAQ,eAAe,eAAe,KAAK,iBAAiB,OAAO,mBAAmB;AACvH,QAAM,SAAS,gBAAgB,OAAO,SAAS,qBAAqB,SAAS;AAC7E,QAAM,UAAU,gBAAgB,QAAQ,UAAU,qBAAqB,SAAS;AAChF,QAAM,SAAS,sBAAsB,QAAQ,SAAS,eAAe,cAAc,cAAc;AACjG,kBAAgB,OAAO;AACvB,iBAAe,OAAO;AACtB,mBAAiB,OAAO;AACxB,QAAM,QAAQ,EAAE,eAAe,cAAc,eAAe;AAC5D,SAAO,OAAO,UAAU,qBAAqB,EAAE,OAAO,QAAQ,QAAQ,QAAQ,GAAG,KAAK;AACxF;AACA,IAAI,oBAAoB,GAAG,EAAE,mBAAmB,CAAC;AAGjD,SAAS,aAAa,KAAK,SAAS,YAAY;AAC9C,QAAMH,SAAQ,aAAa,KAAK,SAAS,UAAU;AACnD,QAAM,iBAAiBA,SAAQ,IAAI,EAAEA,SAAQ,KAAKA;AAClD,MAAI,OAAO,gBAAgB,GAAG,OAAO;AACvC;AACA,SAAS,aAAa,KAAK,QAAQ,YAAY;AAC7C,SAAO,cAAc,KAAK,QAAQ,cAAc,iBAAiB;AACnE;AACA,SAAS,kBAAkB,GAAG,GAAG;AAC/B,SAAO,IAAI,IAAI,IAAI,IAAI,IAAI,KAAK;AAClC;AACA,SAAS,cAAc,KAAK,QAAQ,YAAY;AAC9C,MAAI,OAAO;AACX,MAAI,QAAQ,IAAI;AAChB,MAAIe,UAAS;AACb,MAAI,QAAQ;AACZ,SAAO,OAAO,OAAO;AACnB,IAAAA,UAAS,QAAQ,QAAQ,SAAS;AAClC,UAAM,gBAAgB,WAAW,QAAQ,IAAIA,QAAO;AACpD,QAAI,gBAAgB,GAAG;AACrB,aAAOA,UAAS;AAAA,IAClB,OAAO;AACL,cAAQA;AACR,cAAQ,CAAC;AAAA,IACX;AAAA,EACF;AACA,SAAO,QAAQ,OAAO,CAAC,OAAO;AAChC;AAGA,SAAS,wBAAwB,OAAO,QAAQ,eAAe,cAAc,gBAAgB;AAC3F,SAAO,uBAAuB,OAAO,QAAQ,eAAe,cAAc,gBAAgB,CAAC;AAC7F;AACA,SAAS,wBAAwB,OAAO,QAAQ,eAAe,cAAc,gBAAgB,oBAAoB;AAC/G,SAAO;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AACA,SAAS,wBAAwB,OAAO,QAAQ,eAAe,cAAc,gBAAgB,cAAc;AACzG,SAAO,uBAAuB,OAAO,QAAQ,eAAe,cAAc,gBAAgB,cAAc,IAAI;AAC9G;AACA,SAAS,uBAAuB,OAAO,QAAQ,eAAe,cAAc,gBAAgB,cAAc,qBAAqB,OAAO,qBAAqB,OAAO,qBAAqB,OAAO;AAC5L,QAAM,aAAa,CAAC;AACpB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,QAAI,OAAO,MAAM,gBAAgB;AAC/B,iBAAW,KAAK,EAAE,OAAO,OAAO,KAAK,UAAU,IAAI,oBAAoB,EAAE,CAAC;AAAA,IAC5E;AAAA,EACF;AACA,aAAW,KAAK,mBAAmB;AACnC,QAAMH,UAAS,eAAe,IAAI,OAAO,eAAe;AACxD,QAAM,kBAAkB,CAAC;AACzB,QAAM,iBAAiB,CAAC;AACxB,SAAO,gBAAgB,SAAS,iBAAiB,WAAW,SAAS,GAAG;AACtE,UAAM,YAAY,WAAW,IAAI;AACjC,UAAM,EAAE,OAAO,eAAe,UAAU,mBAAmB,IAAI;AAC/D,QAAI,gBAAgB,gBAAgB;AAClC;AAAA,IACF;AACA,QAAI,kBAAkB;AACtB,aAAS,IAAI,gBAAgB,SAAS,GAAG,KAAK,oBAAoB,EAAE,GAAG;AACrE,YAAM,MAAM,sBAAsB,OAAO,UAAU,gBAAgB,EAAE;AACrE,UAAI,OAAO,cAAc;AACvB,0BAAkB;AAClB;AAAA,MACF;AACA,gBAAU,QAAQ,UAAU,QAAQ,eAAe,cAAcA,SAAQ,GAAG;AAC5E,UAAI,UAAU,SAAS,gBAAgB;AACrC;AAAA,MACF;AAAA,IACF;AACA,cAAU,qBAAqB,gBAAgB;AAC/C,QAAI,CAAC,iBAAiB;AACpB,UAAI,UAAU,UAAU,eAAe;AACrC,wBAAgB,KAAK,QAAQ;AAC7B,uBAAe,KAAK,UAAU,KAAK;AAAA,MACrC,WAAW,UAAU,QAAQ,gBAAgB;AAC3C,qBAAa,YAAY,WAAW,mBAAmB;AAAA,MACzD;AAAA,IACF;AAAA,EACF;AACA,QAAM,eAAe,gBAAgB;AACrC,QAAM,aAAa,gBAAgB;AACnC,MAAI,sBAAsB,aAAa,GAAG;AACxC,oBAAgB,KAAK,GAAG,IAAI,MAAM,UAAU,EAAE,KAAK,CAAC,CAAC;AACrD,mBAAe,KAAK,GAAG,IAAI,MAAM,UAAU,EAAE,KAAK,CAAC,CAAC;AAAA,EACtD;AACA,QAAM,SAAS,EAAE,gBAAgB;AACjC,MAAI,oBAAoB;AACtB,WAAO,oBAAoB;AAAA,EAC7B;AACA,MAAI,oBAAoB;AACtB,WAAO,kBAAkB;AAAA,EAC3B;AACA,SAAO;AACT;AACA,SAAS,sBAAsB,OAAO,IAAI,GAAG;AAC3C,QAAM,SAAS,MAAM,SAAS,KAAK,GAAG,KAAK,IAAI,CAAC;AAChD,QAAM,SAAS,MAAM,SAAS,IAAI,GAAG,IAAI,IAAI,CAAC;AAC9C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,QAAQ,KAAK,IAAI,OAAO,IAAI,OAAO,EAAE;AAC3C,QAAM,SAAS,QAAQ,UAAU,QAAQ;AACzC,QAAM,SAAS,QAAQ,UAAU,QAAQ;AACzC,MAAI,SAAS,KAAK,SAAS,GAAG;AAC5B,WAAO;AAAA,EACT;AACA,QAAM,mBAAmB,KAAK,IAAI,OAAO,KAAK;AAC9C,QAAM,mBAAmB,KAAK,IAAI,OAAO,KAAK;AAC9C,QAAM,mBAAmB,KAAK,IAAI,OAAO,KAAK;AAC9C,QAAM,mBAAmB,KAAK,IAAI,OAAO,KAAK;AAC9C,QAAM,mBAAmB,KAAK,IAAI,mBAAmB,kBAAkB,CAAC,IAAI,KAAK,IAAI,mBAAmB,kBAAkB,CAAC;AAC3H,SAAO,oBAAoB,QAAQ,QAAQ;AAC7C;AACA,SAAS,eAAe,cAAcA,SAAQ,KAAK;AACjD,QAAM,SAAS,KAAK,IAAIA,UAAS,MAAM,GAAG;AAC1C,SAAO,OAAO,eAAe,SAAS;AACxC;AACA,SAAS,oBAAoB,IAAI,IAAI;AACnC,SAAO,GAAG,QAAQ,GAAG,SAAS,GAAG,UAAU,GAAG,SAAS,GAAG,WAAW,GAAG;AAC1E;AAGA,eAAe,wBAAwB,OAAO,QAAQ,eAAe,eAAe,KAAK,iBAAiB,OAAO,mBAAmB;AAClI,QAAM,SAAS,gBAAgB,OAAO,SAAS,wBAAwB;AACvE,QAAM,UAAU,gBAAgB,QAAQ,UAAU,wBAAwB;AAC1E,QAAM,SAAS,sBAAsB,QAAQ,SAAS,eAAe,cAAc,cAAc;AACjG,kBAAgB,OAAO;AACvB,iBAAe,OAAO;AACtB,mBAAiB,OAAO;AACxB,QAAM,iBAAiB,MAAM,QAAQ,IAAI,CAAC,OAAO,KAAK,GAAG,QAAQ,KAAK,CAAC,CAAC;AACxE,QAAM,YAAY,eAAe;AACjC,QAAM,aAAa,eAAe;AAClC,QAAM,EAAE,gBAAgB,IAAI,wBAAwB,WAAW,YAAY,eAAe,cAAc,cAAc;AACtH,MAAI,WAAW,OAAO;AACpB,WAAO,QAAQ;AAAA,EACjB;AACA,MAAI,YAAY,QAAQ;AACtB,YAAQ,QAAQ;AAAA,EAClB;AACA,SAAO,SAAS,iBAAiB,OAAO;AAC1C;AACA,IAAI,yBAAyB;AAG7B,SAAS,4BAA4B,OAAO,QAAQ,eAAe,eAAe,KAAK,iBAAiB,OAAO,mBAAmB,eAAe,GAAG;AAClJ,QAAM,SAAS,gBAAgB,OAAO,SAAS,mBAAmB;AAClE,QAAM,UAAU,gBAAgB,QAAQ,UAAU,mBAAmB;AACrE,QAAM,SAAS,sBAAsB,QAAQ,SAAS,eAAe,cAAc,gBAAgB,YAAY;AAC/G,kBAAgB,OAAO;AACvB,iBAAe,OAAO;AACtB,mBAAiB,OAAO;AACxB,iBAAe,OAAO;AACtB,QAAM,SAAS,EAAE,OAAO,QAAQ,QAAQ,QAAQ;AAChD,QAAM,QAAQ,EAAE,eAAe,cAAc,gBAAgB,aAAa;AAC1E,QAAM,SAAS,OAAO,UAAU,qBAAqB,QAAQ,KAAK;AAClE,SAAO,EAAE,iBAAiB,OAAO,IAAI,gBAAgB,OAAO,GAAG;AACjE;AACA,IAAI,6BAA6B,GAAG,EAAE,4BAA4B,CAAC;AAGnE,eAAe,iCAAiC,OAAO,QAAQ,eAAe,eAAe,KAAK,iBAAiB,OAAO,mBAAmB,eAAe,GAAG;AAC7J,QAAM,SAAS,gBAAgB,OAAO,SAAS,wBAAwB;AACvE,QAAM,UAAU,gBAAgB,QAAQ,UAAU,wBAAwB;AAC1E,QAAM,SAAS,sBAAsB,QAAQ,SAAS,eAAe,cAAc,gBAAgB,YAAY;AAC/G,kBAAgB,OAAO;AACvB,iBAAe,OAAO;AACtB,mBAAiB,OAAO;AACxB,iBAAe,OAAO;AACtB,QAAM,iBAAiB,MAAM,QAAQ,IAAI,CAAC,OAAO,KAAK,GAAG,QAAQ,KAAK,CAAC,CAAC;AACxE,QAAM,YAAY,eAAe;AACjC,QAAM,aAAa,eAAe;AAClC,QAAM,EAAE,iBAAiB,eAAe,IAAI,wBAAwB,WAAW,YAAY,eAAe,cAAc,gBAAgB,YAAY;AACpJ,MAAI,WAAW,OAAO;AACpB,WAAO,QAAQ;AAAA,EACjB;AACA,MAAI,YAAY,QAAQ;AACtB,YAAQ,QAAQ;AAAA,EAClB;AACA,SAAO;AAAA,IACL,iBAAiB,SAAS,iBAAiB,OAAO;AAAA,IAClD,gBAAgB,SAAS,cAAc;AAAA,EACzC;AACF;AACA,IAAI,kCAAkC;AAGtC,SAAS,yBAAyB,OAAO,QAAQ,eAAe,eAAe,KAAK,iBAAiB,OAAO,mBAAmB,qBAAqB,OAAO;AACzJ,QAAM,SAAS,gBAAgB,OAAO,SAAS,mBAAmB;AAClE,QAAM,UAAU,gBAAgB,QAAQ,UAAU,mBAAmB;AACrE,QAAM,SAAS,sBAAsB,QAAQ,SAAS,eAAe,cAAc,gBAAgB,IAAI;AACvG,QAAM,iBAAiB,OAAO;AAC9B,QAAM,gBAAgB,OAAO;AAC7B,QAAM,kBAAkB,OAAO;AAC/B,QAAM,SAAS,EAAE,OAAO,QAAQ,QAAQ,QAAQ;AAChD,QAAM,QAAQ;AAAA,IACZ,eAAe;AAAA,IACf,cAAc;AAAA,IACd,gBAAgB;AAAA,IAChB;AAAA,EACF;AACA,QAAM,SAAS,OAAO,UAAU,qBAAqB,QAAQ,KAAK;AAClE,SAAO,EAAE,iBAAiB,OAAO,IAAI,cAAc,OAAO,GAAG;AAC/D;AACA,IAAI,0BAA0B,GAAG,EAAE,yBAAyB,CAAC;AAG7D,eAAe,8BAA8B,OAAO,QAAQ,eAAe,eAAe,KAAK,iBAAiB,OAAO,mBAAmB,qBAAqB,OAAO;AACpK,QAAM,SAAS,gBAAgB,OAAO,SAAS,wBAAwB;AACvE,QAAM,UAAU,gBAAgB,QAAQ,UAAU,wBAAwB;AAC1E,QAAM,SAAS,sBAAsB,QAAQ,SAAS,eAAe,cAAc,gBAAgB,IAAI;AACvG,QAAM,iBAAiB,OAAO;AAC9B,QAAM,gBAAgB,OAAO;AAC7B,QAAM,kBAAkB,OAAO;AAC/B,QAAM,CAAC,WAAW,UAAU,IAAI,MAAM,QAAQ,IAAI,CAAC,OAAO,KAAK,GAAG,QAAQ,KAAK,CAAC,CAAC;AACjF,QAAM,EAAE,iBAAiB,aAAa,IAAI,wBAAwB,WAAW,YAAY,gBAAgB,eAAe,iBAAiB,kBAAkB;AAC3J,MAAI,WAAW,OAAO;AACpB,WAAO,QAAQ;AAAA,EACjB;AACA,MAAI,YAAY,QAAQ;AACtB,YAAQ,QAAQ;AAAA,EAClB;AACA,SAAO;AAAA,IACL,iBAAiB,SAAS,iBAAiB,OAAO;AAAA,IAClD,cAAc,OAAO,cAAc,OAAO;AAAA,EAC5C;AACF;AACA,IAAI,+BAA+B;AAGnC,SAAS,gBAAgB,QAAQrB,OAAM,eAAe,OAAO,mBAAmB,OAAO;AACrF,QAAM,UAAU,gBAAgB,QAAQ,UAAU,gBAAgB;AAClE,SAAO,QAAQ,SAAS,KAAK,QAAQ,SAAS,GAAG,MAAM,gEAAgE,QAAQ,OAAO;AACtI,SAAOA,MAAK,WAAW,GAAG,MAAM,6DAA6DA,QAAO;AACpG,SAAO,qBAAqB,SAAS,iBAAiB,OAAO,MAAM,mFAAmF;AACtJ,MAAI,cAAc;AAClB,MAAI,eAAe;AACnB,MAAI,QAAQ,SAAS,GAAG;AACtB,mBAAe;AACf,kBAAc,QAAQ,SAAS,CAAC,GAAG,QAAQ,MAAM,IAAI,QAAQ,MAAM,IAAI,QAAQ,MAAM,EAAE,CAAC;AAAA,EAC1F;AACA,QAAM,CAAC,IAAIA;AACX,QAAM,SAAS,EAAE,QAAQ,YAAY;AACrC,QAAM,QAAQ,EAAE,cAAc,kBAAkB,MAAAA,MAAK;AACrD,QAAM,MAAM,OAAO,UAAU,gBAAgB,QAAQ,KAAK;AAC1D,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,iBAAiB,GAAG,EAAE,gBAAgB,CAAC;AAG3C,SAAS,uBAAuB,QAAQA,OAAM,eAAe,OAAO,mBAAmB,OAAO;AAC5F,QAAM,UAAU,gBAAgB,QAAQ,UAAU,uBAAuB;AACzE,SAAO,QAAQ,SAAS,KAAK,QAAQ,SAAS,GAAG,MAAM,uEAAuE,QAAQ,OAAO;AAC7I,SAAOA,MAAK,WAAW,GAAG,MAAM,oEAAoEA,QAAO;AAC3G,SAAO,QAAQ,UAAU,aAAa,QAAQ,UAAU,SAAS,MAAM,kDAAkD;AACzH,SAAO,qBAAqB,SAAS,iBAAiB,OAAO,MAAM,0FAA0F;AAC7J,MAAI,cAAc;AAClB,MAAI,eAAe;AACnB,MAAI,QAAQ,SAAS,GAAG;AACtB,mBAAe;AACf,kBAAc,QAAQ,SAAS,CAAC,GAAG,QAAQ,MAAM,IAAI,QAAQ,MAAM,IAAI,QAAQ,MAAM,EAAE,CAAC;AAAA,EAC1F;AACA,QAAM,CAAC,IAAIA;AACX,QAAM,SAAS,EAAE,QAAQ,YAAY;AACrC,QAAM,QAAQ,EAAE,cAAc,kBAAkB,MAAAA,MAAK;AACrD,QAAM,MAAM,OAAO,UAAU,uBAAuB,QAAQ,KAAK;AACjE,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,wBAAwB,GAAG,EAAE,uBAAuB,CAAC;AAGzD,SAAS,WAAW,QAAQ,SAAS,UAAU,WAAW,OAAO,cAAc,KAAK;AAClF,QAAM,SAAS,gBAAgB,QAAQ,SAAS,WAAW;AAC3D,QAAM,qBAAqB;AAC3B,QAAM,uBAAuB;AAC7B,QAAM,sBAAsB;AAC5B,QAAM,qBAAqB,OAAO,MAAM,KAAK,OAAO,MAAM;AAC1D,MAAI,aAAa,IAAI,SAAS,CAAC,WAAW,CAAC,GAAG,GAAG;AACjD,MAAI,IAAI,GAAG,GAAG;AACd,SAAO,OAAO,SAAS,GAAG,MAAM,yDAAyD,OAAO,OAAO;AACvG,SAAO,OAAO,MAAM,OAAO,KAAK,OAAO,MAAM,OAAO,GAAG,MAAM,0EAA0E,OAAO,MAAM,KAAK;AACzJ,SAAO,OAAO,UAAU,WAAW,OAAO,UAAU,WAAW,MAAM,sEAAsE,OAAO,QAAQ;AAC1J,SAAO,WAAW,UAAU,WAAW,UAAU,MAAM,0CAA0C,QAAQ;AACzG,MAAI,OAAO,MAAM,OAAO,GAAG;AACzB,KAAC,IAAI,GAAG,CAAC,IAAI,MAAM,QAAQ,CAAC,GAAG,GAAG,CAAC,GAAG,EAAE;AACxC,UAAM,KAAK,IAAI,IAAI,kBAAkB;AACrC,UAAM,KAAK,IAAI,GAAG,oBAAoB;AACtC,UAAM,KAAK,IAAI,GAAG,mBAAmB;AACrC,gBAAY,KAAK,KAAK,IAAI,EAAE,GAAG,EAAE;AAAA,EACnC,OAAO;AACL,gBAAY;AAAA,EACd;AACA,MAAI,WAAW,QAAQ;AACrB,UAAM,aAAa,SAAS,KAAK,OAAO,SAAS,GAAG,OAAO,GAAG,OAAO,CAAC,CAAC,GAAG,GAAG;AAC7E,iBAAa,KAAK,YAAY,kBAAkB;AAAA,EAClD;AACA,QAAM,eAAe,WAAW,UAAU,WAAW,UAAU,IAAI,QAAQ,WAAW,UAAU;AAChG,QAAM,SAAS,KAAK,IAAI,cAAc,GAAG,GAAG,OAAO;AACnD,SAAO;AACT;AACA,SAAS,KAAK,WAAW,OAAO;AAC9B,MAAI,aAAa,SAAS,CAAC,EAAE,CAAC;AAC9B,MAAI,eAAe,SAAS,CAAC,CAAC,CAAC;AAC/B,MAAI,YAAY,SAAS,CAAC,CAAC,CAAC;AAC5B,MAAI,YAAY,aAAa,WAAW,SAAS,kBAAkB;AACnE,WAASS,SAAQ,GAAGA,SAAQ,UAAU,OAAO,GAAGA,UAAS;AACvD,iBAAa,MAAM,WAAW,GAAGA,SAAQ,CAAC;AAC1C,kBAAc,MAAM,WAAWA,SAAQ,CAAC;AACxC,uBAAmB,IAAI,KAAK,UAAU,GAAG,KAAK;AAC9C,iBAAa,IAAI,KAAK,WAAW,GAAG,KAAK;AACzC,UAAM,gBAAgB,KAAK,IAAI,YAAY,MAAM,GAAG,WAAW,IAAI,CAAC,CAAC;AACrE,gBAAY,IAAI,eAAe,KAAK,UAAU,CAAC;AAC/C,UAAM,cAAc,KAAK,YAAY,OAAO,WAAW,IAAI;AAC3D,UAAM,aAAa,KAAK,MAAM,GAAG,YAAY,IAAI,GAAG,WAAW;AAC/D,UAAM,aAAa,IAAI,aAAa,UAAU;AAC9C,cAAU,IAAI,KAAK,UAAU,GAAG,KAAK,WAAW,CAAC;AACjD,UAAM,gBAAgB,IAAI,WAAW,OAAO;AAC5C,UAAM,gBAAgB,IAAI,WAAW,OAAO;AAC5C,UAAM,eAAe,IAAI,kBAAkB,UAAU;AACrD,gBAAY,IAAI,IAAI,cAAc,aAAa,GAAG,aAAa;AAC/D,UAAM,YAAY,QAAQ,WAAW,YAAY;AACjD,mBAAe,MAAM,WAAW,WAAW,YAAY;AACvD,iBAAa,MAAM,WAAW,SAAS,CAACA,MAAK,CAAC,GAAG,UAAU;AAAA,EAC7D;AACA,SAAO;AACT;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,WAAW,QAAQ,YAAY,gBAAgB,WAAW,WAAW,YAAY,YAAY,GAAG,aAAa;AACpH,QAAM,SAAS,gBAAgB,QAAQ,SAAS,aAAa,SAAS;AACtE,QAAM,cAAc,gBAAgB,YAAY,cAAc,aAAa,SAAS;AACpF,SAAO,OAAO,SAAS,GAAG,MAAM,yDAAyD,OAAO,OAAO;AACvG,SAAO,YAAY,SAAS,MAAM,YAAY,MAAM,OAAO,OAAO,MAAM,MAAM,YAAY,MAAM,OAAO,MAAM,YAAY,MAAM,OAAO,GAAG,MAAM,kEAAkE;AACjN,SAAO,eAAe,QAAQ,YAAY,WAAW,GAAG,MAAM,4EAA4E,cAAc;AACxJ,QAAM,SAAS,EAAE,OAAO,QAAQ,YAAY,YAAY;AACxD,QAAM,QAAQ,EAAE,eAAe,UAAU,WAAW,YAAY;AAChE,SAAO,OAAO,UAAU,WAAW,QAAQ,KAAK;AAClD;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,UAAU,GAAG,UAAU,UAAU;AACxC,SAAO,WAAW,MAAM,GAAG,MAAM,gDAAgD,WAAW;AAC5F,SAAO,WAAW,MAAM,GAAG,MAAM,gDAAgD,WAAW;AAC5F,QAAM,KAAK,gBAAgB,GAAG,KAAK,UAAU;AAC7C,SAAO,GAAG,QAAQ,GAAG,MAAM,4CAA4C,GAAG,OAAO;AACjF,QAAM,QAAQ,GAAG;AACjB,QAAM,CAAC,GAAG,CAAC,IAAI,GAAG,MAAM,MAAM,EAAE;AAChC,MAAI,EAAE,YAAY,IAAI;AACpB,UAAM,IAAI,MAAM,yBAAyB,0DAA0D,KAAK;AAAA,EAC1G;AACA,MAAI,EAAE,YAAY,IAAI;AACpB,UAAM,IAAI,MAAM,yBAAyB,6DAA6D,KAAK;AAAA,EAC7G;AACA,MAAI,WAAW,GAAG;AAChB,eAAW;AAAA,EACb;AACA,MAAI,WAAW,GAAG;AAChB,eAAW;AAAA,EACb;AACA,QAAM,KAAK,QAAQ,MAAM,GAAG,GAAG,GAAG,OAAO,GAAG,CAAC,IAAI,CAAC,CAAC;AACnD,QAAM,IAAI,MAAM,GAAG,GAAG,GAAG,OAAO;AAChC,QAAM,KAAK,IAAI,IAAI,CAAC;AACpB,QAAM,SAAS,WAAW,UAAU,IAAI,OAAO,CAAC,UAAU,OAAO,CAAC,GAAG,aAAa,IAAI,OAAO,CAAC,UAAU,OAAO,CAAC,CAAC;AACjH,QAAM,OAAO,MAAM,CAAC,GAAG,CAAC,GAAG,GAAG,KAAK;AACnC,SAAO,QAAQ,MAAM,QAAQ,QAAQ,IAAI,CAAC,IAAI,GAAG,CAAC,CAAC,CAAC,EAAE,IAAI,CAAC,QAAQ,MAAM,QAAQ,KAAK,IAAI,CAAC,CAAC,GAAG,KAAK;AACtG;AACA,IAAI,WAAW,GAAG,EAAE,UAAU,CAAC;AAG/B,SAAS,aAAa,IAAI;AACxB,MAAI;AACJ,MAAI,MAAM,QAAQ,EAAE,GAAG;AACrB,sBAAkB;AAClB,WAAO,MAAM,QAAQ,GAAG,SAAS,GAAG,MAAM,mEAAmE;AAC7G,UAAM,MAAM,GAAG,GAAG,MAAM;AACxB,aAAS,KAAK,GAAG,KAAK,GAAG,QAAQ,EAAE,IAAI;AACrC,aAAO,GAAG,IAAI,MAAM,OAAO,KAAK,MAAM,iEAAiE,GAAG,IAAI,MAAM,UAAU,MAAM;AAAA,IACtI;AAAA,EACF,OAAO;AACL,sBAAkB;AAClB,SAAK,MAAM,IAAI,GAAG,MAAM,IAAI,CAAC,EAAE,IAAI,CAAC,MAAM,QAAQ,GAAG,CAAC,CAAC,CAAC,CAAC;AAAA,EAC3D;AACA,SAAO,GAAG,UAAU,GAAG,GAAG,MAAM,IAAI,MAAM,oCAAoC,GAAG,yCAAyC,GAAG,GAAG,MAAM,MAAM;AAC5I,QAAM,KAAK,CAAC;AACZ,QAAM,OAAO;AACb,WAAS,KAAK,GAAG,KAAK,GAAG,QAAQ,EAAE,IAAI;AACrC,OAAG,KAAK,OAAO,KAAK,MAAM;AACxB,UAAI,IAAI,KAAK;AACb,UAAI,KAAK,GAAG;AACV,iBAAS,IAAI,GAAG,IAAI,IAAI,EAAE,GAAG;AAC3B,gBAAM,OAAO,IAAI,KAAK,IAAI,GAAG,IAAI,CAAC,CAAC,GAAG,GAAG,EAAE;AAC3C,cAAI,IAAI,GAAG,IAAI;AAAA,QACjB;AAAA,MACF;AACA,aAAO,IAAI,GAAG,KAAK,GAAG,WAAW,CAAC;AAAA,IACpC,CAAC,CAAC;AAAA,EACJ;AACA,MAAI,iBAAiB;AACnB,WAAO,MAAM,IAAI,CAAC;AAAA,EACpB,OAAO;AACL,WAAO;AAAA,EACT;AACF;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,IAAI,GAAG,eAAe,OAAO;AACpC,SAAO,EAAE,QAAQ,GAAG,MAAM,gEAAgE,EAAE,MAAM;AAClG,MAAI,EAAE,SAAS,GAAG;AAChB,WAAO,KAAK,GAAG,YAAY;AAAA,EAC7B,OAAO;AACL,UAAM,gBAAgB,EAAE,MAAM,MAAM,GAAG,EAAE,MAAM,SAAS,CAAC,EAAE,OAAO,CAAC,OAAO,SAAS,QAAQ,IAAI;AAC/F,UAAM,OAAO,QAAQ,QAAQ,GAAG;AAAA,MAC9B;AAAA,MACA,EAAE,MAAM,EAAE,MAAM,SAAS;AAAA,MACzB,EAAE,MAAM,EAAE,MAAM,SAAS;AAAA,IAC3B,CAAC,GAAG,CAAC;AACL,UAAM,OAAO,CAAC;AACd,UAAM,OAAO,CAAC;AACd,SAAK,QAAQ,CAAC,QAAQ;AACpB,YAAM,CAAC,KAAK,GAAG,IAAI,KAAK,KAAK,YAAY;AACzC,WAAK,KAAK,GAAG;AACb,WAAK,KAAK,GAAG;AAAA,IACf,CAAC;AACD,UAAM,IAAI,QAAQ,MAAM,MAAM,CAAC,GAAG,EAAE,KAAK;AACzC,UAAM,KAAK,QAAQ,MAAM,MAAM,CAAC,GAAG,EAAE,KAAK;AAC1C,WAAO,CAAC,GAAG,EAAE;AAAA,EACf;AACF;AACA,SAAS,KAAK,GAAG,eAAe,OAAO;AACrC,SAAO,OAAO,KAAK,MAAM;AACvB,WAAO,EAAE,MAAM,WAAW,GAAG,MAAM,0CAA0C,EAAE,MAAM,iBAAiB;AACtG,UAAM,IAAI,EAAE,MAAM;AAClB,UAAM,KAAK,EAAE,MAAM;AACnB,QAAI,IAAI,IAAI,CAAC;AACb,QAAI,KAAK,MAAM,CAAC;AAChB,UAAM,QAAQ,SAAS,CAAC,CAAC,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AACpC,QAAI,IAAI,MAAM,KAAK;AACnB,UAAM,QAAQ,KAAK,KAAK,KAAK;AAC7B,aAAS,IAAI,GAAG,IAAI,OAAO,EAAE,GAAG;AAC9B,YAAM,QAAQ;AACd,YAAM,QAAQ;AACd,YAAM,QAAQ;AACd,OAAC,GAAG,IAAI,CAAC,IAAI,OAAO,KAAK,MAAM;AAC7B,cAAM,SAAS,MAAM,IAAI,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,GAAG,CAAC,CAAC;AAC3C,cAAM,QAAQ,KAAK,MAAM;AACzB,cAAM,MAAM,MAAM,IAAI,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AACpC,cAAM,KAAK,MAAM,QAAQ,KAAK,CAAC,GAAG,SAAS,CAAC,CAAC,EAAE,CAAC,CAAC,GAAG,SAAS,CAAC,CAAC,CAAC,CAAC,CAAC,CAAC;AACnE,cAAM,KAAK,IAAI,KAAK,IAAI,IAAI,KAAK,CAAC;AAClC,cAAM,OAAO,IAAI,QAAQ,EAAE;AAC3B,YAAI,KAAK,MAAM,OAAO,GAAG;AACvB,cAAI,MAAM,KAAK;AAAA,QACjB,OAAO;AACL,cAAI,OAAO;AAAA,YACT;AAAA,YACA,MAAM,MAAM,CAAC,GAAG,CAAC,GAAG,CAAC,KAAK,MAAM,KAAK,GAAG,KAAK,MAAM,EAAE,CAAC;AAAA,UACxD,GAAG,CAAC;AAAA,QACN;AACA,cAAM,MAAM,IAAI,IAAI,OAAO,IAAI,EAAE,GAAG,KAAK,CAAC;AAC1C,cAAM,WAAW,MAAM,IAAI,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,GAAG,EAAE,CAAC;AAC9C,cAAM,YAAY,IAAI,KAAK,CAAC;AAC5B,cAAM,KAAK,UAAU,CAAC;AACtB,YAAI,MAAM,GAAG;AACX,eAAK,IAAI,UAAU,OAAO,WAAW,OAAO,IAAI,QAAQ,CAAC,CAAC;AAAA,QAC5D,OAAO;AACL,gBAAM,YAAY,IAAI,UAAU,OAAO,WAAW,OAAO,IAAI,QAAQ,CAAC,CAAC;AACvE,eAAK,OAAO,CAAC,MAAM,IAAI,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,EAAE,CAAC,GAAG,SAAS,GAAG,CAAC;AAAA,QACxD;AACA,cAAM,aAAa,UAAU,SAAS;AACtC,cAAM,WAAW,MAAM,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,EAAE,MAAM,KAAK,CAAC,CAAC;AACrD,YAAI,MAAM,GAAG;AACX,cAAI,IAAI,UAAU,OAAO,OAAO,UAAU,CAAC,GAAG,UAAU,CAAC;AAAA,QAC3D,OAAO;AACL,gBAAM,YAAY,IAAI,UAAU,OAAO,OAAO,UAAU,CAAC,GAAG,UAAU,CAAC;AACvE,cAAI,OAAO,CAAC,MAAM,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC,GAAG,SAAS,GAAG,CAAC;AAAA,QACrD;AACA,eAAO,CAAC,GAAG,IAAI,CAAC;AAAA,MAClB,CAAC;AACD,cAAQ,CAAC,OAAO,OAAO,KAAK,CAAC;AAAA,IAC/B;AACA,QAAI,CAAC,gBAAgB,IAAI,IAAI;AAC3B,UAAI,MAAM,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,EAAE,CAAC;AAC5B,WAAK,MAAM,IAAI,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,EAAE,CAAC;AAAA,IACjC;AACA,WAAO,CAAC,GAAG,EAAE;AAAA,EACf,CAAC;AACH;AACA,IAAI,KAAK,GAAG,EAAE,IAAI,CAAC;AAGnB,IAAI;AAAA,CACH,SAAS,YAAY;AACpB,aAAW,WAAW,UAAU,KAAK;AACrC,aAAW,WAAW,UAAU,KAAK;AACrC,aAAW,WAAW,SAAS,KAAK;AACpC,aAAW,WAAW,4BAA4B,KAAK;AACzD,GAAG,cAAc,YAAY,CAAC,EAAE;AAGhC,SAAS,qBAAqB,SAAS,SAAS,YAAY,UAAU,wBAAwB;AAC5F,QAAM,UAAU,gBAAgB,SAAS,UAAU,qBAAqB;AACxE,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,qBAAqB;AAAA,EACtE;AACA,QAAM,eAAe,YAAY,OAAO,UAAU,IAAI,SAAS,QAAQ;AACvE,MAAI,cAAc,UAAU,MAAM;AAChC,WAAO;AAAA,EACT;AACA,MAAI,cAAc,UAAU,KAAK;AAC/B,WAAO,KAAK,YAAY;AAAA,EAC1B;AACA,MAAI,cAAc,UAAU,MAAM;AAChC,QAAI,YAAY,MAAM;AACpB,aAAO,KAAK,YAAY;AAAA,IAC1B,OAAO;AACL,YAAM,kBAAkB,QAAQ,OAAO,SAAS;AAChD,YAAM,SAAS,IAAI,KAAK,YAAY,GAAG,KAAK,QAAQ,CAAC;AACrD,aAAO,kBAAkB,IAAI,IAAI,QAAQ,OAAO,eAAe,CAAC,IAAI;AAAA,IACtE;AAAA,EACF;AACA,MAAI,cAAc,UAAU,wBAAwB;AAClD,QAAI,YAAY,MAAM;AACpB,aAAO,IAAI,KAAK,YAAY,GAAG,OAAO,QAAQ,IAAI,CAAC;AAAA,IACrD,OAAO;AACL,YAAM,qBAAqB,IAAI,UAAU,MAAM,QAAQ,KAAK,CAAC;AAC7D,YAAM,cAAc,KAAK,KAAK,SAAS,oBAAoB,OAAO,CAAC,CAAC,CAAC,GAAG,SAAS;AACjF,aAAO,IAAI,KAAK,YAAY,GAAG,WAAW;AAAA,IAC5C;AAAA,EACF;AACA,QAAM,MAAM,sBAAsB,WAAW;AAC/C;AACA,IAAI,sBAAsB,GAAG,EAAE,qBAAqB,CAAC;AAGrD,SAAS,oBAAoBU,SAAQ,aAAa,SAAS,YAAY,UAAU,wBAAwB;AACvG,QAAM,UAAU,gBAAgBA,SAAQ,UAAU,oBAAoB;AACtE,QAAM,eAAe,gBAAgB,aAAa,eAAe,oBAAoB;AACrF,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,oBAAoB;AAAA,EACrE;AACA,oBAAkB,QAAQ,OAAO,aAAa,OAAO,+BAA+B;AACpF,QAAM,UAAU,IAAI,IAAI,SAAS,YAAY,CAAC;AAC9C,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,qBAAqB,GAAG,EAAE,oBAAoB,CAAC;AAGnD,SAAS,gBAAgBA,SAAQ,aAAa,MAAM,SAAS,YAAY,UAAU,wBAAwB;AACzG,QAAM,UAAU,gBAAgBA,SAAQ,UAAU,gBAAgB;AAClE,QAAM,eAAe,gBAAgB,aAAa,eAAe,gBAAgB;AACjF,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,gBAAgB;AAAA,EACjE;AACA,oBAAkB,QAAQ,OAAO,aAAa,OAAO,2BAA2B;AAChF,QAAM,MAAM,OAAO,CAAC;AACpB,QAAM,UAAU,IAAI,KAAK,KAAK,IAAI,SAAS,YAAY,GAAG,MAAM,IAAI,CAAC;AACrE,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,iBAAiB,GAAG,EAAE,gBAAgB,CAAC;AAG3C,SAAS,WAAWA,SAAQ,aAAa,SAAS,YAAY,UAAU,wBAAwB;AAC9F,MAAI,UAAU,gBAAgBA,SAAQ,UAAU,WAAW;AAC3D,QAAM,eAAe,gBAAgB,aAAa,eAAe,WAAW;AAC5E,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,WAAW;AAAA,EAC5D;AACA,oBAAkB,QAAQ,OAAO,aAAa,OAAO,sBAAsB;AAC3E,QAAM,MAAM,OAAO,CAAC;AACpB,YAAU,IAAI,IAAI,OAAO,CAAC,GAAG,OAAO,GAAG,GAAG;AAC1C,QAAM,UAAU,KAAK,IAAI,KAAK,IAAI,SAAS,YAAY,CAAC,CAAC;AACzD,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,WAAWA,SAAQ,aAAa,SAAS,QAAQ,GAAG,YAAY,UAAU,wBAAwB;AACzG,QAAM,UAAU,gBAAgBA,SAAQ,UAAU,WAAW;AAC7D,QAAM,eAAe,gBAAgB,aAAa,eAAe,WAAW;AAC5E,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,WAAW;AAAA,EAC5D;AACA,oBAAkB,QAAQ,OAAO,aAAa,OAAO,sBAAsB;AAC3E,QAAM,cAAc,OAAO,KAAK;AAChC,QAAM,QAAQ,IAAI,IAAI,cAAc,OAAO,CAAC;AAC5C,QAAM,YAAY,QAAQ,OAAO,WAAW;AAC5C,QAAM,SAAS,IAAI,OAAO,SAAS;AACnC,QAAM,UAAU,KAAK,IAAI,OAAO,GAAG,GAAG,OAAO,SAAS,CAAC,GAAG,IAAI,aAAa,MAAM,CAAC;AAClF,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,YAAY,GAAG,EAAE,WAAW,CAAC;AAGjC,SAAS,SAASA,SAAQ,aAAa,SAAS,WAAW,MAAM,YAAY,UAAU,wBAAwB;AAC7G,QAAM,UAAU,gBAAgBA,SAAQ,UAAU,SAAS;AAC3D,QAAM,eAAe,gBAAgB,aAAa,eAAe,SAAS;AAC1E,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,SAAS;AAAA,EAC1D;AACA,oBAAkB,QAAQ,OAAO,aAAa,OAAO,oBAAoB;AACzE,QAAM,MAAM,OAAO,CAAC;AACpB,QAAM,gBAAgB,OAAO,QAAQ;AACrC,QAAM,MAAM,IAAI,IAAI,SAASxB,MAAK,KAAK,cAAc,aAAa,CAAC,CAAC,CAAC;AACrE,QAAM,MAAM,IAAI,IAAI,KAAK,OAAO,GAAGA,MAAK,KAAK,IAAI,KAAK,YAAY,GAAG,aAAa,CAAC,CAAC;AACpF,QAAM,UAAU,IAAI,KAAK,GAAG;AAC5B,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,UAAU,GAAG,EAAE,SAAS,CAAC;AAG7B,SAAS,kBAAkBwB,SAAQ,aAAa,SAAS,YAAY,UAAU,wBAAwB;AACrG,QAAM,UAAU,gBAAgBA,SAAQ,UAAU,kBAAkB;AACpE,QAAM,eAAe,gBAAgB,aAAa,eAAe,kBAAkB;AACnF,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,kBAAkB;AAAA,EACnE;AACA,oBAAkB,QAAQ,OAAO,aAAa,OAAO,6BAA6B;AAClF,QAAM,UAAU,kBAAkB,SAAS,YAAY;AACvD,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,mBAAmB,GAAG,EAAE,kBAAkB,CAAC;AAG/C,SAAS,+BAA+BA,SAAQ,QAAQ;AACtD,QAAM,UAAU,gBAAgBA,SAAQ,UAAU,+BAA+B;AACjF,QAAM,UAAU,gBAAgB,QAAQ,UAAU,+BAA+B;AACjF,oBAAkB,QAAQ,OAAO,QAAQ,OAAO,0CAA0C;AAC1F,QAAM,YAAY,KAAK,OAAO;AAC9B,QAAM,gBAAgB,IAAI,SAAS,OAAO;AAC1C,QAAM,gBAAgB,MAAM,IAAI,IAAI,IAAI,OAAO,CAAC,CAAC,CAAC;AAClD,SAAO,KAAK,IAAI,WAAW,aAAa,GAAG,aAAa;AAC1D;AACA,SAAS,qBAAqB,kBAAkB,QAAQ,SAAS,iBAAiB,GAAG,YAAY,UAAU,wBAAwB;AACjI,MAAI,oBAAoB,gBAAgB,kBAAkB,oBAAoB,qBAAqB;AACnG,QAAM,UAAU,gBAAgB,QAAQ,UAAU,qBAAqB;AACvE,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,qBAAqB;AAAA,EACtE;AACA,oBAAkB,kBAAkB,OAAO,QAAQ,OAAO,gCAAgC;AAC1F,MAAI,iBAAiB,GAAG;AACtB,UAAM,uBAAuB,OAAO,cAAc;AAClD,UAAM,MAAM,OAAO,CAAC;AACpB,UAAMI,QAAO,OAAO,GAAG;AACvB,wBAAoB,KAAK,IAAI,mBAAmB,IAAI,KAAK,oBAAoB,CAAC,GAAG,IAAIA,OAAM,oBAAoB,CAAC;AAAA,EAClH;AACA,QAAM,UAAU,+BAA+B,mBAAmB,OAAO;AACzE,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,sBAAsB,GAAG,EAAE,qBAAqB,CAAC;AAGrD,SAAS,+BAA+BJ,SAAQ,QAAQ,MAAM,IAAI;AAChE,MAAI,QAAQ,IAAI;AACd,UAAM,OAAO,OAAO;AAAA,EACtB;AACA,MAAI,QAAQ,OAAO,OAAO,GAAG;AAC3B,UAAM,MAAM,mGAAmG,OAAO,oBAAoB,KAAK;AAAA,EACjJ;AACA,QAAM,WAAW,WAAW,CAACM,UAAS,SAAS,SAAS;AACtD,UAAM,WAAW;AACjB,UAAM,MAAM,UAAU,SAAS,CAAC,GAAG,GAAG,QAAQ;AAC9C,UAAM,YAAY,IAAI,KAAK,SAAS,SAAS,GAAG,GAAG;AACnD,SAAK,CAACA,UAAS,SAAS,CAAC;AACzB,UAAM,aAAa,IAAI,IAAI,WAAWA,QAAO,CAAC;AAC9C,UAAM,QAAQ,KAAK,YAAY,CAAC,GAAG,CAAC;AACpC,UAAM,WAAW,CAAC,IAAI,UAAU;AAC9B,YAAM,CAAC,SAAS,UAAU,IAAI;AAC9B,YAAM,UAAU,qBAAqB,GAAG,OAAO,CAAC,GAAG,CAAC;AACpD,aAAO;AAAA,QACL,IAAI,QAAQ,IAAI,OAAO,GAAG,IAAI,KAAK,SAAS,SAAS,GAAG,IAAI,UAAU,CAAC,CAAC;AAAA,QACxE,IAAI,QAAQ,IAAI,OAAO,GAAG,IAAI,IAAI,UAAU,GAAG,KAAK,SAAS,SAAS,CAAC,CAAC;AAAA,MAC1E;AAAA,IACF;AACA,WAAO,EAAE,OAAO,SAAS;AAAA,EAC3B,CAAC;AACD,SAAO,SAASN,SAAQ,MAAM;AAChC;AACA,SAAS,qBAAqB,cAAc,QAAQ,SAAS,iBAAiB,GAAG,YAAY,UAAU,wBAAwB;AAC7H,MAAI,gBAAgB,gBAAgB,cAAc,gBAAgB,qBAAqB;AACvF,QAAM,UAAU,gBAAgB,QAAQ,UAAU,qBAAqB;AACvE,MAAI,WAAW;AACf,MAAI,WAAW,MAAM;AACnB,eAAW,gBAAgB,SAAS,WAAW,qBAAqB;AAAA,EACtE;AACA,oBAAkB,cAAc,OAAO,QAAQ,OAAO,gCAAgC;AACtF,MAAI,iBAAiB,GAAG;AACtB,UAAM,uBAAuB,OAAO,cAAc;AAClD,UAAM,MAAM,OAAO,CAAC;AACpB,UAAM,aAAa,OAAO,cAAc,MAAM,EAAE;AAChD,oBAAgB,KAAK,IAAI,eAAe,IAAI,KAAK,oBAAoB,CAAC,GAAG,IAAI,sBAAsB,UAAU,CAAC;AAAA,EAChH;AACA,QAAM,UAAU,+BAA+B,eAAe,OAAO;AACrE,SAAO,oBAAoB,SAAS,UAAU,SAAS;AACzD;AACA,IAAI,sBAAsB,GAAG,EAAE,qBAAqB,CAAC;AAGrD,SAAS,qBAAqB,SAAS,QAAQ,YAAY,cAAc;AACvE,QAAM,WAAW,gBAAgB,SAAS,WAAW,uBAAuB,OAAO;AACnF,QAAM,UAAU,gBAAgB,QAAQ,UAAU,qBAAqB;AACvE,QAAM,cAAc,gBAAgB,YAAY,cAAc,uBAAuB,OAAO;AAC5F,QAAM,gBAAgB,gBAAgB,cAAc,gBAAgB,uBAAuB,QAAQ,KAAK;AACxG,MAAI,SAAS,SAAS,GAAG;AACvB,UAAM,IAAI,MAAM;AAAA,UACV,SAAS,OAAO;AAAA,EACxB;AACA,MAAI,QAAQ,SAAS,GAAG;AACtB,UAAM,IAAI,MAAM,gDAAgD,QAAQ,OAAO;AAAA,EACjF;AACA,MAAI,YAAY,SAAS,GAAG;AAC1B,UAAM,IAAI,MAAM,qDAAqD,YAAY,OAAO;AAAA,EAC1F;AACA,MAAI,cAAc,SAAS,GAAG;AAC5B,UAAM,IAAI,MAAM,uDAAuD,cAAc,OAAO;AAAA,EAC9F;AACA,QAAM,SAAS;AAAA,IACb,SAAS;AAAA,IACT,QAAQ;AAAA,IACR,YAAY;AAAA,IACZ,cAAc;AAAA,EAChB;AACA,QAAM,SAAS,OAAO,UAAU,qBAAqB,MAAM;AAC3D,SAAO;AAAA,IACL,eAAe,OAAO;AAAA,IACtB,cAAc,OAAO;AAAA,IACrB,mBAAmB,OAAO;AAAA,IAC1B,iBAAiB,OAAO;AAAA,EAC1B;AACF;AACA,IAAI,sBAAsB,GAAG,EAAE,qBAAqB,CAAC;AAGrD,SAAS,eAAe,cAAc,YAAY,UAAU;AAC1D,QAAM,gBAAgB,gBAAgB,cAAc,gBAAgB,iBAAiB,OAAO;AAC5F,QAAM,cAAc,gBAAgB,YAAY,cAAc,iBAAiB,OAAO;AACtF,QAAM,YAAY,gBAAgB,UAAU,YAAY,iBAAiB,OAAO;AAChF,MAAI,cAAc,SAAS,GAAG;AAC5B,UAAM,IAAI,MAAM;AAAA,UACV,cAAc,OAAO;AAAA,EAC7B;AACA,MAAI,YAAY,SAAS,GAAG;AAC1B,UAAM,IAAI,MAAM,qDAAqD,YAAY,OAAO;AAAA,EAC1F;AACA,MAAI,UAAU,SAAS,GAAG;AACxB,UAAM,IAAI,MAAM,mDAAmD,UAAU,OAAO;AAAA,EACtF;AACA,QAAM,SAAS;AAAA,IACb,cAAc;AAAA,IACd,YAAY;AAAA,IACZ,UAAU;AAAA,EACZ;AACA,QAAM,SAAS,OAAO,UAAU,eAAe,MAAM;AACrD,SAAO,EAAE,eAAe,OAAO,IAAI,aAAa,OAAO,GAAG;AAC5D;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,SAAS,mBAAmB,MAAM,SAAS,YAAY;AACrD,QAAM,QAAQ,gBAAgB,MAAM,QAAQ,mBAAmB;AAC/D,QAAM,WAAW,gBAAgB,SAAS,WAAW,qBAAqB,OAAO;AACjF,QAAM,cAAc,gBAAgB,YAAY,cAAc,qBAAqB,OAAO;AAC1F,MAAI,MAAM,OAAO,GAAG;AAClB,UAAM,IAAI,MAAM,2DAA2D;AAAA,EAC7E;AACA,MAAI,SAAS,SAAS,GAAG;AACvB,UAAM,IAAI,MAAM;AAAA,YACR,SAAS,OAAO;AAAA,EAC1B;AACA,MAAI,YAAY,SAAS,GAAG;AAC1B,UAAM,IAAI,MAAM;AAAA,YACR,YAAY,OAAO;AAAA,EAC7B;AACA,QAAM,SAAS;AAAA,IACb,MAAM;AAAA,IACN,SAAS;AAAA,IACT,YAAY;AAAA,EACd;AACA,SAAO,OAAO,UAAU,mBAAmB,MAAM;AACnD;AACA,IAAI,oBAAoB,GAAG,EAAE,mBAAmB,CAAC;AAGjD,SAAS,kBAAkB,MAAM,SAAS,YAAY;AACpD,QAAM,QAAQ,gBAAgB,MAAM,QAAQ,kBAAkB;AAC9D,QAAM,WAAW,gBAAgB,SAAS,WAAW,oBAAoB,OAAO;AAChF,QAAM,cAAc,gBAAgB,YAAY,cAAc,oBAAoB,OAAO;AACzF,MAAI,MAAM,OAAO,GAAG;AAClB,UAAM,IAAI,MAAM,2DAA2D;AAAA,EAC7E;AACA,MAAI,SAAS,SAAS,GAAG;AACvB,UAAM,IAAI,MAAM;AAAA,WACT,SAAS,OAAO;AAAA,EACzB;AACA,MAAI,YAAY,SAAS,GAAG;AAC1B,UAAM,IAAI,MAAM;AAAA,WACT,YAAY,OAAO;AAAA,EAC5B;AACA,QAAM,SAAS;AAAA,IACb,MAAM;AAAA,IACN,SAAS;AAAA,IACT,YAAY;AAAA,EACd;AACA,SAAO,OAAO,UAAU,kBAAkB,MAAM;AAClD;AACA,IAAI,mBAAmB,GAAG,EAAE,kBAAkB,CAAC;AAG/C,SAAS,cAAc,MAAM,YAAY,WAAW,aAAa,SAAS,WAAW,UAAU,wBAAwB;AACrH,QAAM,QAAQ,gBAAgB,MAAM,QAAQ,gBAAgB,QAAQ;AACpE,MAAI,MAAM,UAAU,UAAU;AAC5B,UAAM,IAAI,MAAM,iCAAiC;AAAA,EACnD;AACA,MAAI,MAAM,MAAM,WAAW,GAAG;AAC5B,UAAM,IAAI,MAAM,+BAA+B,MAAM,OAAO;AAAA,EAC9D;AACA,QAAM,cAAc,gBAAgB,YAAY,cAAc,cAAc;AAC5E,MAAI,YAAY,UAAU,SAAS;AACjC,UAAM,IAAI,MAAM,uCAAuC;AAAA,EACzD;AACA,QAAM,QAAQ;AAAA,IACZ;AAAA,IACA;AAAA,IACA;AAAA,IACA,UAAU;AAAA,IACV;AAAA,IACA;AAAA,EACF;AACA,QAAM,SAAS,EAAE,MAAM,OAAO,YAAY,YAAY;AACtD,QAAM,SAAS,OAAO,UAAU,cAAc,QAAQ,KAAK;AAC3D,SAAO,EAAE,QAAQ,OAAO,IAAI,cAAc,OAAO,GAAG;AACtD;AACA,IAAI,eAAe,GAAG,EAAE,cAAc,CAAC;AAGvC,SAAS,aAAa,QAAQ,WAAW,YAAY,MAAM;AACzD,QAAM,SAAS,gBAAgB,QAAQ,SAAS,eAAe,QAAQ;AACvE,QAAM,aAAa,gBAAgB,WAAW,aAAa,eAAe,QAAQ;AAClF,MAAI,OAAO,SAAS,GAAG;AACrB,UAAM,IAAI,MAAM,+CAA+C,OAAO,OAAO;AAAA,EAC/E;AACA,MAAI,WAAW,SAAS,GAAG;AACzB,UAAM,IAAI,MAAM,mDAAmD,WAAW,OAAO;AAAA,EACvF;AACA,QAAM,QAAQ,EAAE,UAAU;AAC1B,QAAM,SAAS,EAAE,OAAO,QAAQ,WAAW,WAAW;AACtD,QAAM,SAAS,OAAO,UAAU,aAAa,QAAQ,KAAK;AAC1D,SAAO,EAAE,SAAS,OAAO,IAAI,QAAQ,OAAO,IAAI,OAAO,OAAO,GAAG;AACnE;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,SAAS,wBAAwB,QAAQ,YAAY;AACnD,QAAM,SAAS,gBAAgB,QAAQ,SAAS,0BAA0B,QAAQ;AAClF,QAAM,QAAQ,EAAE,WAAW;AAC3B,MAAI,cAAc,GAAG;AACnB,UAAM,IAAI,MAAM,sCAAsC;AAAA,EACxD;AACA,QAAM,SAAS,EAAE,OAAO,OAAO;AAC/B,SAAO,OAAO,UAAU,wBAAwB,QAAQ,KAAK;AAC/D;AACA,IAAI,yBAAyB,GAAG,EAAE,wBAAwB,CAAC;AAG3D,IAAI,WAAW;AAAA,EACb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cAAc,aAAa;AAAA,EACzC,SAAS,GAAG,aAAa,OAAO,SAAS;AACvC,UAAM,EAAE,OAAO,OAAO,OAAO,IAAI,KAAK,iBAAiB,GAAG,OAAO;AACjE,QAAI,WAAW,MAAM;AACnB,YAAM,YAAY,QAAQ,IAAI,CAAC,OAAO,EAAE,MAAM,EAAE,MAAM,QAAQ,OAAO,EAAE,MAAM,EAAE;AAC/E,WAAK,eAAe,SAAS;AAAA,IAC/B,OAAO;AACL,WAAK,eAAe,MAAM;AAAA,IAC5B;AACA,YAAQ,MAAM;AACd,QAAI,YAAY;AACd,aAAO;AAAA,IACT,OAAO;AACL,YAAM,QAAQ;AACd,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,IAAI,aAAa;AACf,QAAI,KAAK,eAAe,MAAM;AAC5B,WAAK,cAAc;AAAA,IACrB;AACA,WAAO,KAAK;AAAA,EACd;AAAA,EACA,sBAAsB;AACpB,SAAK,cAAc,KAAK,aAAa;AAAA,EACvC;AAAA,EACA,iBAAiB,GAAG,SAAS;AAC3B,WAAO,cAAc,GAAG,OAAO;AAAA,EACjC;AAAA,EACA,UAAU;AACR,QAAI,KAAK,eAAe,MAAM;AAC5B,cAAQ,KAAK,WAAW;AAAA,IAC1B;AAAA,EACF;AAAA,EACA,MAAM,iBAAiB;AACrB,QAAI,KAAK,eAAe,MAAM;AAC5B,WAAK,cAAc;AAAA,IACrB;AACA,WAAO;AAAA,MACL,MAAM;AAAA,MACN,QAAQ,OAAO,KAAK,aAAa,OAAO;AAAA,IAC1C;AAAA,EACF;AAAA,EACA,MAAM,aAAa;AACjB,UAAM,IAAI,MAAM,yDAAyD;AAAA,EAC3E;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,UAAM,IAAI,MAAM,4DAA4D,KAAK,aAAa,GAAG;AAAA,EACnG;AAAA,EACA,MAAM,kBAAkB,cAAc;AACpC,SAAK,eAAe,MAAM,aAAa,GAAG,OAAO,KAAK,GAAG;AACzD,WAAO,aAAa,MAAM,CAAC;AAAA,EAC7B;AACF;AACA,OAAO,eAAe,WAAW,OAAO,aAAa;AAAA,EACnD,OAAO,CAAC,aAAa;AACnB,WAAO,SAAS,YAAY,QAAQ,SAAS,oBAAoB,QAAQ,SAAS,kBAAkB;AAAA,EACtG;AACF,CAAC;AAGD,IAAI,oBAAoB,cAAc,UAAU;AAAA,EAC9C,YAAY,cAAc,KAAK,WAAW,MAAM;AAC9C,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,MAAM;AACX,SAAK,UAAU;AACf,SAAK,mBAAmB,CAAC;AACzB,SAAK,qBAAqB,CAAC;AAC3B,QAAI,YAAY,MAAM;AACpB,WAAK,UAAU,OAAO,QAAQ,QAAQ;AAAA,IACxC;AAAA,EACF;AAAA,EACA,eAAe,mBAAmB;AAChC,UAAM,gBAAgB,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,CAAC,SAAS,KAAK,IAAI,IAAI,OAAO,KAAK,iBAAiB;AACnI,kBAAc,QAAQ,CAAC,MAAM,OAAO;AAClC,YAAM,QAAQ,OAAO,oBAAoB;AACzC,YAAM,YAAY;AAClB,UAAI,KAAK,iBAAiB,OAAO,MAAM;AACrC,aAAK,iBAAiB,MAAM;AAAA,UAC1B,cAAc,GAAG;AAAA,UACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,QAC3D;AAAA,MACF;AACA,UAAI,KAAK,mBAAmB,OAAO,MAAM;AACvC,aAAK,mBAAmB,MAAM;AAAA,UAC5B,cAAc,GAAG;AAAA,UACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,QAC3D;AAAA,MACF;AACA,YAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,SAAS,kBAAkB;AACrG,UAAI,YAAY,MAAM;AACpB;AAAA,MACF;AACA,YAAM,kBAAkB,KAAK,iBAAiB,IAAI;AAClD,YAAM,oBAAoB,KAAK,mBAAmB,IAAI;AACtD,WAAK,MAAM;AACT,cAAM,qBAAqB,KAAK,IAAI,iBAAiB,KAAK,GAAG,GAAG,IAAI,OAAO,QAAQ,GAAG,IAAI,KAAK,GAAG,CAAC;AACnG,cAAM,UAAU,IAAI,IAAI,KAAK,KAAK,mBAAmB,KAAK,OAAO,CAAC,GAAG,KAAK,KAAK,iBAAiB,KAAK,OAAO,CAAC,CAAC,GAAG,QAAQ;AACzH,cAAM,uBAAuB,KAAK,IAAI,mBAAmB,KAAK,GAAG,GAAG,IAAI,OAAO,OAAO,GAAG,IAAI,KAAK,GAAG,CAAC;AACtG,wBAAgB,OAAO,kBAAkB;AACzC,0BAAkB,OAAO,oBAAoB;AAC7C,cAAM,WAAW,KAAK,IAAI,SAAS,CAAC,KAAK,YAAY,GAAG,KAAK;AAC7D,cAAM,OAAO,QAAQ;AAAA,MACvB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,UAAU;AACR,QAAI,KAAK,sBAAsB,MAAM;AACnC,cAAQ,KAAK,iBAAiB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AACpD,cAAQ,KAAK,mBAAmB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IACxD;AAAA,EACF;AAAA,EACA,MAAM,aAAa;AACjB,UAAM,YAAY,CAAC,GAAG,KAAK,kBAAkB,GAAG,KAAK,kBAAkB;AACvE,WAAO,CAAC,MAAM,KAAK,eAAe,CAAC,EAAE,OAAO,UAAU,IAAI,CAAC,OAAO,EAAE,MAAM,EAAE,cAAc,QAAQ,EAAE,SAAS,EAAE,CAAC;AAAA,EAClH;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,mBAAe,MAAM,KAAK,kBAAkB,YAAY;AACxD,UAAM,gBAAgB,aAAa,SAAS;AAC5C,UAAM,YAAY;AAClB,SAAK,mBAAmB,aAAa,MAAM,GAAG,aAAa,EAAE,IAAI,CAAC,OAAO;AAAA,MACvE,cAAc,EAAE;AAAA,MAChB,UAAU,EAAE,OAAO,SAAS,SAAS;AAAA,IACvC,EAAE;AACF,SAAK,qBAAqB,aAAa,MAAM,eAAe,gBAAgB,CAAC,EAAE,IAAI,CAAC,OAAO;AAAA,MACzF,cAAc,EAAE;AAAA,MAChB,UAAU,EAAE,OAAO,SAAS,SAAS;AAAA,IACvC,EAAE;AAAA,EACJ;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,gBAAgB,KAAK;AAAA,MACrB,OAAO,KAAK;AAAA,MACZ,WAAW,KAAK;AAAA,IAClB;AAAA,EACF;AAAA,EACA,OAAO,WAAW,KAAKL,SAAQ;AAC7B,WAAO,IAAI,IAAIA,QAAO,iBAAiBA,QAAO,QAAQA,QAAO,UAAU;AAAA,EACzE;AACF;AACA,kBAAkB,YAAY;AAC9B,cAAc,iBAAiB;AAG/B,IAAI,mBAAmB,cAAc,UAAU;AAAA,EAC7C,YAAY,cAAc,0BAA0B,KAAK;AACvD,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,0BAA0B;AAC/B,SAAK,mBAAmB,CAAC;AAAA,EAC3B;AAAA,EACA,eAAe,mBAAmB;AAChC,UAAM,gBAAgB,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,CAAC,SAAS,KAAK,IAAI,IAAI,OAAO,KAAK,iBAAiB;AACnI,kBAAc,QAAQ,CAAC,MAAM,OAAO;AAClC,YAAM,QAAQ,OAAO,oBAAoB;AACzC,UAAI,KAAK,iBAAiB,OAAO,MAAM;AACrC,cAAM,YAAY;AAClB,aAAK,iBAAiB,MAAM;AAAA,UAC1B,cAAc,GAAG;AAAA,UACjB,UAAU,KAAK,MAAM,KAAK,MAAM,OAAO,KAAK,uBAAuB,EAAE,SAAS,SAAS,CAAC;AAAA,QAC1F;AAAA,MACF;AACA,YAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,SAAS,kBAAkB;AACrG,UAAI,YAAY,MAAM;AACpB;AAAA,MACF;AACA,YAAM,kBAAkB,KAAK,iBAAiB,IAAI;AAClD,WAAK,MAAM;AACT,cAAM,qBAAqB,KAAK,iBAAiB,OAAO,QAAQ,CAAC;AACjE,wBAAgB,OAAO,kBAAkB;AACzC,cAAM,WAAW,KAAK,IAAI,IAAI,UAAU,KAAK,KAAK,oBAAoB,OAAO,QAAQ,QAAQ,CAAC,CAAC,CAAC,GAAG,CAAC,KAAK,YAAY,GAAG,KAAK;AAC7H,cAAM,OAAO,QAAQ;AAAA,MACvB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,UAAU;AACR,QAAI,KAAK,oBAAoB,MAAM;AACjC,cAAQ,KAAK,iBAAiB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IACtD;AAAA,EACF;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,CAAC,MAAM,KAAK,eAAe,CAAC,EAAE,OAAO,KAAK,iBAAiB,IAAI,CAAC,OAAO,EAAE,MAAM,EAAE,cAAc,QAAQ,EAAE,SAAS,EAAE,CAAC;AAAA,EAC9H;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,mBAAe,MAAM,KAAK,kBAAkB,YAAY;AACxD,UAAM,YAAY;AAClB,SAAK,mBAAmB,aAAa,IAAI,CAAC,OAAO,EAAE,cAAc,EAAE,MAAM,UAAU,EAAE,OAAO,SAAS,SAAS,EAAE,EAAE;AAAA,EACpH;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,gBAAgB,KAAK;AAAA,MACrB,2BAA2B,KAAK;AAAA,IAClC;AAAA,EACF;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,WAAO,IAAI,IAAIA,QAAO,iBAAiBA,QAAO,0BAA0B;AAAA,EAC1E;AACF;AACA,iBAAiB,YAAY;AAC7B,cAAc,gBAAgB;AAG9B,IAAI,gBAAgB,cAAc,UAAU;AAAA,EAC1C,YAAY,cAAc,OAAO,OAAO,WAAW,MAAM;AACvD,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,QAAQ;AACb,SAAK,QAAQ;AACb,SAAK,UAAU;AACf,SAAK,yBAAyB,CAAC;AAC/B,SAAK,0BAA0B,CAAC;AAChC,SAAK,MAAM;AACT,WAAK,WAAW,OAAO,KAAK,EAAE,SAAS;AACvC,WAAK,WAAW,OAAO,KAAK,EAAE,SAAS;AAAA,IACzC,CAAC;AACD,QAAI,YAAY,MAAM;AACpB,WAAK,UAAU,OAAO,QAAQ,QAAQ;AAAA,IACxC;AAAA,EACF;AAAA,EACA,eAAe,mBAAmB;AAChC,UAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,CAAC,MAAM,EAAE,IAAI,IAAI,OAAO,KAAK,iBAAiB;AACxH,SAAK,MAAM;AACT,YAAM,mBAAmB,IAAI,GAAG,KAAK,QAAQ;AAC7C,YAAM,mBAAmB,IAAI,GAAG,KAAK,QAAQ;AAC7C,eAAS,QAAQ,CAAC,MAAM,OAAO;AAC7B,cAAM,QAAQ,OAAO,oBAAoB;AACzC,cAAM,YAAY;AAClB,YAAI,KAAK,uBAAuB,OAAO,MAAM;AAC3C,eAAK,uBAAuB,MAAM;AAAA,YAChC,cAAc,GAAG;AAAA,YACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,UAC3D;AAAA,QACF;AACA,YAAI,KAAK,wBAAwB,OAAO,MAAM;AAC5C,eAAK,wBAAwB,MAAM;AAAA,YACjC,cAAc,GAAG;AAAA,YACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,UAC3D;AAAA,QACF;AACA,cAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,SAAS,kBAAkB;AACrG,YAAI,YAAY,MAAM;AACpB;AAAA,QACF;AACA,cAAM,cAAc,KAAK,uBAAuB,IAAI;AACpD,cAAM,eAAe,KAAK,wBAAwB,IAAI;AACtD,cAAM,iBAAiB,KAAK,IAAI,aAAa,KAAK,KAAK,GAAG,IAAI,UAAU,IAAI,KAAK,KAAK,CAAC;AACvF,cAAM,kBAAkB,KAAK,IAAI,cAAc,KAAK,KAAK,GAAG,IAAI,OAAO,QAAQ,GAAG,IAAI,KAAK,KAAK,CAAC;AACjG,cAAM,2BAA2B,IAAI,gBAAgB,gBAAgB;AACrE,cAAM,4BAA4B,IAAI,iBAAiB,gBAAgB;AACvE,oBAAY,OAAO,cAAc;AACjC,qBAAa,OAAO,eAAe;AACnC,cAAM,WAAW,KAAK,IAAI,IAAI,0BAA0B,KAAK,KAAK,yBAAyB,GAAG,KAAK,OAAO,CAAC,GAAG,CAAC,KAAK,YAAY,GAAG,KAAK;AACxI,cAAM,OAAO,QAAQ;AAAA,MACvB,CAAC;AACD,WAAK,SAAS,OAAO,IAAI,KAAK,UAAU,KAAK,KAAK,CAAC;AACnD,WAAK,SAAS,OAAO,IAAI,KAAK,UAAU,KAAK,KAAK,CAAC;AAAA,IACrD,CAAC;AACD,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,UAAU;AACR,SAAK,SAAS,QAAQ;AACtB,SAAK,SAAS,QAAQ;AACtB,QAAI,KAAK,0BAA0B,MAAM;AACvC,cAAQ,KAAK,uBAAuB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IAC5D;AACA,QAAI,KAAK,2BAA2B,MAAM;AACxC,cAAQ,KAAK,wBAAwB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IAC7D;AAAA,EACF;AAAA,EACA,MAAM,aAAa;AACjB,UAAM,YAAY,CAAC,GAAG,KAAK,wBAAwB,GAAG,KAAK,uBAAuB;AAClF,WAAO,CAAC,MAAM,KAAK,eAAe,CAAC,EAAE,OAAO,UAAU,IAAI,CAAC,OAAO,EAAE,MAAM,EAAE,cAAc,QAAQ,EAAE,SAAS,EAAE,CAAC;AAAA,EAClH;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,mBAAe,MAAM,KAAK,kBAAkB,YAAY;AACxD,SAAK,MAAM;AACT,WAAK,SAAS,OAAO,IAAI,KAAK,OAAO,KAAK,cAAc,CAAC,CAAC;AAC1D,WAAK,SAAS,OAAO,IAAI,KAAK,OAAO,KAAK,cAAc,CAAC,CAAC;AAAA,IAC5D,CAAC;AACD,UAAM,gBAAgB,aAAa,SAAS;AAC5C,UAAM,YAAY;AAClB,SAAK,yBAAyB,aAAa,MAAM,GAAG,aAAa,EAAE,IAAI,CAAC,OAAO;AAAA,MAC7E,cAAc,EAAE;AAAA,MAChB,UAAU,EAAE,OAAO,SAAS,SAAS;AAAA,IACvC,EAAE;AACF,SAAK,0BAA0B,aAAa,MAAM,eAAe,gBAAgB,CAAC,EAAE,IAAI,CAAC,OAAO;AAAA,MAC9F,cAAc,EAAE;AAAA,MAChB,UAAU,EAAE,OAAO,SAAS,SAAS;AAAA,IACvC,EAAE;AAAA,EACJ;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,gBAAgB,KAAK;AAAA,MACrB,SAAS,KAAK;AAAA,MACd,SAAS,KAAK;AAAA,MACd,WAAW,KAAK;AAAA,IAClB;AAAA,EACF;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,WAAO,IAAI,IAAIA,QAAO,iBAAiBA,QAAO,UAAUA,QAAO,UAAUA,QAAO,UAAU;AAAA,EAC5F;AACF;AACA,cAAc,YAAY;AAC1B,cAAc,aAAa;AAG3B,IAAI,kBAAkB,cAAc,UAAU;AAAA,EAC5C,YAAY,cAAc,OAAO,OAAO,WAAW,MAAM,QAAQ,GAAG;AAClE,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,QAAQ;AACb,SAAK,QAAQ;AACb,SAAK,UAAU;AACf,SAAK,QAAQ;AACb,SAAK,yBAAyB,CAAC;AAC/B,SAAK,6BAA6B,CAAC;AACnC,SAAK,MAAM;AACT,WAAK,YAAY,OAAO,CAAC,EAAE,SAAS;AACpC,WAAK,WAAW,OAAO,KAAK,EAAE,SAAS;AAAA,IACzC,CAAC;AACD,QAAI,YAAY,MAAM;AACpB,WAAK,UAAU,OAAO,QAAQ,QAAQ;AAAA,IACxC;AAAA,EACF;AAAA,EACA,eAAe,mBAAmB;AAChC,UAAM,gBAAgB,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,CAAC,SAAS,KAAK,IAAI,IAAI,OAAO,KAAK,iBAAiB;AACnI,SAAK,MAAM;AACT,YAAM,mBAAmB,IAAI,GAAG,KAAK,QAAQ;AAC7C,YAAM,KAAK,IAAI,CAAC,KAAK,cAAc,KAAK,IAAI,KAAK,WAAW,KAAK,KAAK,GAAG,CAAC,CAAC;AAC3E,oBAAc,QAAQ,CAAC,MAAM,OAAO;AAClC,cAAM,QAAQ,OAAO,oBAAoB;AACzC,cAAM,YAAY;AAClB,YAAI,KAAK,uBAAuB,OAAO,MAAM;AAC3C,eAAK,uBAAuB,MAAM;AAAA,YAChC,cAAc,GAAG;AAAA,YACjB,UAAU,UAAU,KAAK,EAAE,SAAS,SAAS;AAAA,UAC/C;AAAA,QACF;AACA,YAAI,KAAK,2BAA2B,OAAO,MAAM;AAC/C,eAAK,2BAA2B,MAAM;AAAA,YACpC,cAAc,GAAG;AAAA,YACjB,UAAU,UAAU,KAAK,EAAE,SAAS,SAAS;AAAA,UAC/C;AAAA,QACF;AACA,cAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,SAAS,kBAAkB;AACrG,YAAI,YAAY,MAAM;AACpB;AAAA,QACF;AACA,cAAM,cAAc,KAAK,uBAAuB,IAAI;AACpD,cAAM,kBAAkB,KAAK,2BAA2B,IAAI;AAC5D,cAAM,iBAAiB,KAAK,IAAI,aAAa,KAAK,KAAK,GAAG,IAAI,UAAU,IAAI,KAAK,KAAK,CAAC;AACvF,cAAM,MAAM,IAAI,iBAAiB,KAAK,KAAK;AAC3C,cAAM,MAAM,IAAI,QAAQ;AACxB,cAAM,qBAAqB,QAAQ,KAAK,GAAG;AAC3C,oBAAY,OAAO,cAAc;AACjC,wBAAgB,OAAO,kBAAkB;AACzC,cAAM,WAAW,KAAK,IAAI,IAAI,IAAI,gBAAgB,GAAG,IAAI,gBAAgB,KAAK,oBAAoB,KAAK,OAAO,CAAC,CAAC,GAAG,KAAK;AACxH,cAAM,OAAO,QAAQ;AAAA,MACvB,CAAC;AACD,WAAK,UAAU,OAAO,KAAK,KAAK,WAAW,CAAC,CAAC;AAC7C,WAAK,SAAS,OAAO,IAAI,KAAK,UAAU,KAAK,KAAK,CAAC;AAAA,IACrD,CAAC;AACD,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,UAAU;AACR,SAAK,SAAS,QAAQ;AACtB,SAAK,UAAU,QAAQ;AACvB,QAAI,KAAK,0BAA0B,MAAM;AACvC,cAAQ,KAAK,uBAAuB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IAC5D;AACA,QAAI,KAAK,8BAA8B,MAAM;AAC3C,cAAQ,KAAK,2BAA2B,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IAChE;AAAA,EACF;AAAA,EACA,MAAM,aAAa;AACjB,UAAM,IAAI,MAAM,iDAAiD;AAAA,EACnE;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,UAAM,IAAI,MAAM,iDAAiD;AAAA,EACnE;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,gBAAgB,KAAK;AAAA,MACrB,SAAS,KAAK;AAAA,MACd,SAAS,KAAK;AAAA,MACd,WAAW,KAAK;AAAA,MAChB,SAAS,KAAK;AAAA,IAChB;AAAA,EACF;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,WAAO,IAAI,IAAIA,QAAO,iBAAiBA,QAAO,UAAUA,QAAO,UAAUA,QAAO,YAAYA,QAAO,QAAQ;AAAA,EAC7G;AACF;AACA,gBAAgB,YAAY;AAC5B,cAAc,eAAe;AAG7B,IAAI,eAAe,cAAc,UAAU;AAAA,EACzC,YAAY,cAAc;AACxB,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,gBAAgB,YAAY;AAAA,EACnC;AAAA,EACA,eAAe,mBAAmB;AAChC,UAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,CAAC,MAAM,EAAE,IAAI,IAAI,OAAO,KAAK,iBAAiB;AACxH,aAAS,QAAQ,CAAC,MAAM,OAAO;AAC7B,YAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,SAAS,kBAAkB;AACrG,UAAI,YAAY,MAAM;AACpB;AAAA,MACF;AACA,YAAM,QAAQ,OAAO,oBAAoB;AACzC,WAAK,MAAM;AACT,cAAM,WAAW,KAAK,IAAI,KAAK,GAAG,QAAQ,GAAG,KAAK;AAClD,cAAM,OAAO,QAAQ;AAAA,MACvB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,gBAAgB,cAAc;AAC5B,SAAK,eAAe;AACpB,QAAI,KAAK,KAAK,MAAM;AAClB,WAAK,EAAE,QAAQ;AAAA,IACjB;AACA,SAAK,IAAI,KAAK,OAAO,CAAC,YAAY,CAAC;AAAA,EACrC;AAAA,EACA,UAAU;AACR,SAAK,EAAE,QAAQ;AAAA,EACjB;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,CAAC,MAAM,KAAK,eAAe,CAAC;AAAA,EACrC;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,mBAAe,MAAM,KAAK,kBAAkB,YAAY;AACxD,QAAI,aAAa,WAAW,GAAG;AAC7B,YAAM,IAAI,MAAM,+CAA+C;AAAA,IACjE;AAAA,EACF;AAAA,EACA,YAAY;AACV,WAAO,EAAE,gBAAgB,KAAK,aAAa;AAAA,EAC7C;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,WAAO,IAAI,IAAIA,QAAO,eAAe;AAAA,EACvC;AACF;AACA,aAAa,YAAY;AACzB,cAAc,YAAY;AAG1B,IAAI,oBAAoB,cAAc,aAAa;AAAA,EACjD,YAAY,cAAc,UAAU,cAAc,OAAO;AACvD,UAAM,YAAY;AAClB,SAAK,eAAe;AACpB,SAAK,WAAW;AAChB,SAAK,cAAc;AACnB,SAAK,gBAAgB,CAAC;AACtB,SAAK,IAAI,OAAO,KAAK,QAAQ;AAAA,EAC/B;AAAA,EACA,eAAe,mBAAmB;AAChC,UAAM,gBAAgB,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,CAAC,SAAS,KAAK,IAAI,IAAI,OAAO,KAAK,iBAAiB;AACnI,kBAAc,QAAQ,CAAC,MAAM,OAAO;AAClC,YAAM,QAAQ,OAAO,oBAAoB;AACzC,UAAI,KAAK,cAAc,OAAO,MAAM;AAClC,cAAM,YAAY;AAClB,aAAK,cAAc,MAAM;AAAA,UACvB,cAAc,GAAG;AAAA,UACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,QAC3D;AAAA,MACF;AACA,YAAM,eAAe,KAAK,cAAc,IAAI;AAC5C,YAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,SAAS,kBAAkB;AACrG,UAAI,YAAY,MAAM;AACpB;AAAA,MACF;AACA,WAAK,MAAM;AACT,YAAI;AACJ,cAAM,kBAAkB,KAAK,IAAI,KAAK,GAAG,YAAY,GAAG,QAAQ;AAChE,YAAI,KAAK,aAAa;AACpB,qBAAW,KAAK,IAAI,KAAK,GAAG,KAAK,UAAU,IAAI,iBAAiB,KAAK,CAAC,CAAC,CAAC,GAAG,KAAK;AAAA,QAClF,OAAO;AACL,qBAAW,KAAK,IAAI,KAAK,GAAG,eAAe,GAAG,KAAK;AAAA,QACrD;AACA,qBAAa,OAAO,eAAe;AACnC,cAAM,OAAO,QAAQ;AAAA,MACvB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,UAAU;AACR,SAAK,EAAE,QAAQ;AACf,QAAI,KAAK,iBAAiB,MAAM;AAC9B,cAAQ,KAAK,cAAc,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IACnD;AAAA,EACF;AAAA,EACA,YAAY,UAAU;AACpB,SAAK,WAAW;AAAA,EAClB;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,CAAC,MAAM,KAAK,eAAe,CAAC,EAAE,OAAO,KAAK,cAAc,IAAI,CAAC,OAAO,EAAE,MAAM,EAAE,cAAc,QAAQ,EAAE,SAAS,EAAE,CAAC;AAAA,EAC3H;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,mBAAe,MAAM,KAAK,kBAAkB,YAAY;AACxD,UAAM,YAAY;AAClB,SAAK,gBAAgB,aAAa,IAAI,CAAC,OAAO,EAAE,cAAc,EAAE,MAAM,UAAU,EAAE,OAAO,SAAS,SAAS,EAAE,EAAE;AAAA,EACjH;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,gBAAgB,KAAK;AAAA,MACrB,YAAY,KAAK;AAAA,MACjB,eAAe,KAAK;AAAA,IACtB;AAAA,EACF;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,WAAO,IAAI,IAAIA,QAAO,iBAAiBA,QAAO,aAAaA,QAAO,cAAc;AAAA,EAClF;AACF;AACA,kBAAkB,YAAY;AAC9B,cAAc,iBAAiB;AAG/B,IAAI,mBAAmB,cAAc,UAAU;AAAA,EAC7C,YAAY,cAAc,QAAQ,KAAK,WAAW,GAAG,WAAW,MAAM,WAAW,OAAO;AACtF,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,QAAQ;AACb,SAAK,WAAW;AAChB,SAAK,UAAU;AACf,SAAK,yBAAyB,CAAC;AAC/B,SAAK,qBAAqB,CAAC;AAC3B,SAAK,uBAAuB,CAAC;AAC7B,SAAK,WAAW;AAChB,QAAI,YAAY,MAAM;AACpB,WAAK,UAAU,OAAO,QAAQ,QAAQ;AAAA,IACxC;AACA,QAAI,gBAAgB,MAAM;AACxB,YAAM,IAAI,MAAM,oDAAoD;AAAA,IACtE;AAAA,EACF;AAAA,EACA,eAAe,mBAAmB;AAChC,UAAM,gBAAgB,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,CAAC,SAAS,KAAK,IAAI,IAAI,OAAO,KAAK,iBAAiB;AACnI,kBAAc,QAAQ,CAAC,MAAM,OAAO;AAClC,YAAM,QAAQ,OAAO,oBAAoB;AACzC,YAAM,YAAY;AAClB,UAAI,KAAK,uBAAuB,OAAO,MAAM;AAC3C,aAAK,uBAAuB,MAAM;AAAA,UAChC,cAAc,GAAG;AAAA,UACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,QAC3D;AAAA,MACF;AACA,UAAI,KAAK,mBAAmB,OAAO,MAAM;AACvC,aAAK,mBAAmB,MAAM;AAAA,UAC5B,cAAc,GAAG;AAAA,UACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,QAC3D;AAAA,MACF;AACA,UAAI,KAAK,qBAAqB,OAAO,QAAQ,KAAK,UAAU;AAC1D,aAAK,qBAAqB,MAAM;AAAA,UAC9B,cAAc,GAAG;AAAA,UACjB,UAAU,KAAK,MAAM,UAAU,KAAK,EAAE,SAAS,SAAS,CAAC;AAAA,QAC3D;AAAA,MACF;AACA,YAAM,WAAW,MAAM,QAAQ,iBAAiB,IAAI,kBAAkB,IAAI,SAAS,kBAAkB;AACrG,UAAI,YAAY,MAAM;AACpB;AAAA,MACF;AACA,YAAM,wBAAwB,KAAK,uBAAuB,IAAI;AAC9D,YAAM,qBAAqB,KAAK,mBAAmB,IAAI;AACvD,WAAK,MAAM;AACT,cAAM,2BAA2B,KAAK,IAAI,uBAAuB,KAAK,KAAK,GAAG,IAAI,OAAO,QAAQ,GAAG,IAAI,KAAK,KAAK,CAAC;AACnH,YAAI,KAAK,UAAU;AACjB,gBAAM,sBAAsB,KAAK,qBAAqB,IAAI;AAC1D,gBAAM,yBAAyB,KAAK,IAAI,qBAAqB,KAAK,KAAK,GAAG,IAAI,UAAU,IAAI,KAAK,KAAK,CAAC;AACvG,gBAAM,mBAAmB,IAAI,IAAI,UAAU,KAAK,YAAY,GAAG,KAAK,IAAI,0BAA0B,KAAK,OAAO,sBAAsB,GAAG,KAAK,OAAO,CAAC,CAAC,CAAC;AACtJ,gBAAM,wBAAwB,KAAK,IAAI,oBAAoB,KAAK,QAAQ,GAAG,gBAAgB;AAC3F,gCAAsB,OAAO,wBAAwB;AACrD,8BAAoB,OAAO,sBAAsB;AACjD,6BAAmB,OAAO,qBAAqB;AAC/C,gBAAM,WAAW,IAAI,OAAO,qBAAqB;AACjD,gBAAM,OAAO,QAAQ;AAAA,QACvB,OAAO;AACL,gBAAM,4BAA4B,KAAK,IAAI,uBAAuB,KAAK,KAAK,GAAG,IAAI,OAAO,QAAQ,GAAG,IAAI,KAAK,KAAK,CAAC;AACpH,gBAAM,wBAAwB,KAAK,IAAI,oBAAoB,KAAK,QAAQ,GAAG,IAAI,IAAI,UAAU,KAAK,YAAY,GAAG,KAAK,KAAK,2BAA2B,KAAK,OAAO,CAAC,CAAC,CAAC;AACrK,gCAAsB,OAAO,yBAAyB;AACtD,6BAAmB,OAAO,qBAAqB;AAC/C,gBAAM,WAAW,IAAI,OAAO,qBAAqB;AACjD,gBAAM,OAAO,QAAQ;AAAA,QACvB;AAAA,MACF,CAAC;AAAA,IACH,CAAC;AACD,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,UAAU;AACR,QAAI,KAAK,0BAA0B,MAAM;AACvC,cAAQ,KAAK,uBAAuB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IAC5D;AACA,QAAI,KAAK,wBAAwB,QAAQ,KAAK,UAAU;AACtD,cAAQ,KAAK,qBAAqB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IAC1D;AACA,QAAI,KAAK,sBAAsB,MAAM;AACnC,cAAQ,KAAK,mBAAmB,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAAA,IACxD;AAAA,EACF;AAAA,EACA,MAAM,aAAa;AACjB,UAAM,YAAY,CAAC,GAAG,KAAK,wBAAwB,GAAG,KAAK,kBAAkB;AAC7E,QAAI,KAAK,UAAU;AACjB,gBAAU,KAAK,GAAG,KAAK,oBAAoB;AAAA,IAC7C;AACA,WAAO,CAAC,MAAM,KAAK,eAAe,CAAC,EAAE,OAAO,UAAU,IAAI,CAAC,OAAO,EAAE,MAAM,EAAE,cAAc,QAAQ,EAAE,SAAS,EAAE,CAAC;AAAA,EAClH;AAAA,EACA,MAAM,WAAW,cAAc;AAC7B,mBAAe,MAAM,KAAK,kBAAkB,YAAY;AACxD,UAAM,gBAAgB,KAAK,WAAW,aAAa,SAAS,IAAI,aAAa,SAAS;AACtF,UAAM,YAAY;AAClB,SAAK,yBAAyB,aAAa,MAAM,GAAG,aAAa,EAAE,IAAI,CAAC,OAAO;AAAA,MAC7E,cAAc,EAAE;AAAA,MAChB,UAAU,EAAE,OAAO,SAAS,SAAS;AAAA,IACvC,EAAE;AACF,SAAK,qBAAqB,aAAa,MAAM,eAAe,gBAAgB,CAAC,EAAE,IAAI,CAAC,OAAO;AAAA,MACzF,cAAc,EAAE;AAAA,MAChB,UAAU,EAAE,OAAO,SAAS,SAAS;AAAA,IACvC,EAAE;AACF,QAAI,KAAK,UAAU;AACjB,WAAK,uBAAuB,aAAa,MAAM,gBAAgB,GAAG,gBAAgB,CAAC,EAAE,IAAI,CAAC,OAAO;AAAA,QAC/F,cAAc,EAAE;AAAA,QAChB,UAAU,EAAE,OAAO,SAAS,SAAS;AAAA,MACvC,EAAE;AAAA,IACJ;AAAA,EACF;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,gBAAgB,KAAK;AAAA,MACrB,SAAS,KAAK;AAAA,MACd,YAAY,KAAK;AAAA,MACjB,WAAW,KAAK;AAAA,MAChB,YAAY,KAAK;AAAA,IACnB;AAAA,EACF;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,WAAO,IAAI,IAAIA,QAAO,iBAAiBA,QAAO,UAAUA,QAAO,aAAaA,QAAO,YAAYA,QAAO,WAAW;AAAA,EACnH;AACF;AACA,iBAAiB,YAAY;AAC7B,cAAc,gBAAgB;AAG9B,IAAI,wBAAwB,MAAM;AAAA,EAChC,OAAO,IAAI,cAAc;AACvB,WAAO,IAAI,aAAa,YAAY;AAAA,EACtC;AAAA,EACA,OAAO,SAAS,cAAc,UAAU,cAAc,OAAO;AAC3D,WAAO,IAAI,kBAAkB,cAAc,UAAU,WAAW;AAAA,EAClE;AAAA,EACA,OAAO,QAAQ,cAAc,QAAQ,KAAK,WAAW,GAAG,WAAW,MAAM,WAAW,OAAO;AACzF,WAAO,IAAI,iBAAiB,cAAc,OAAO,UAAU,UAAU,QAAQ;AAAA,EAC/E;AAAA,EACA,OAAO,KAAK,eAAe,MAAM,QAAQ,KAAK,QAAQ,OAAO,WAAW,MAAM;AAC5E,WAAO,IAAI,cAAc,cAAc,OAAO,OAAO,QAAQ;AAAA,EAC/D;AAAA,EACA,OAAO,SAAS,eAAe,MAAM,MAAM,MAAM,WAAW,MAAM;AAChE,WAAO,IAAI,kBAAkB,cAAc,KAAK,QAAQ;AAAA,EAC1D;AAAA,EACA,OAAO,OAAO,eAAe,MAAM,QAAQ,KAAK,QAAQ,OAAO,WAAW,MAAM,QAAQ,GAAG;AACzF,WAAO,IAAI,gBAAgB,cAAc,OAAO,OAAO,UAAU,KAAK;AAAA,EACxE;AAAA,EACA,OAAO,QAAQ,cAAc,0BAA0B,KAAK;AAC1D,WAAO,IAAI,iBAAiB,cAAc,uBAAuB;AAAA,EACnE;AACF;AAGA,IAAI,QAAQ;AAAA,EACV,KAAK,sBAAsB;AAAA,EAC3B,UAAU,sBAAsB;AAAA,EAChC,UAAU,sBAAsB;AAAA,EAChC,SAAS,sBAAsB;AAAA,EAC/B,SAAS,sBAAsB;AAAA,EAC/B,QAAQ,sBAAsB;AAAA,EAC9B,MAAM,sBAAsB;AAC9B;AAGA,IAAI,iBAAiB,MAAM;AACzB,MAAI,OAAO,0BAA0B,aAAa;AAChD,WAAO;AAAA,EACT,WAAW,OAAO,iBAAiB,aAAa;AAC9C,WAAO;AAAA,EACT;AACA,SAAO,CAAC,MAAM,EAAE;AAClB,GAAG;AACH,SAAS,YAAY;AACnB,SAAO,IAAI,QAAQ,CAAC,YAAY,cAAc,MAAM,QAAQ,CAAC,CAAC;AAChE;AAGA,IAAI,uBAAuB,CAAC;AAC5BjB,UAAS,sBAAsB;AAAA,EAC7B,QAAQ,MAAM;AAAA,EACd,QAAQ,MAAM;AAAA,EACd,QAAQ,MAAM;AAAA,EACd,QAAQ,MAAM;AAAA,EACd,QAAQ,MAAM;AAAA,EACd,OAAO,MAAM;AAAA,EACb,uBAAuB,MAAM;AAAA,EAC7B,YAAY,MAAM;AAAA,EAClB,iBAAiB,MAAM;AAAA,EACvB,iBAAiB,MAAM;AAAA,EACvB,4BAA4B,MAAM;AAAA,EAClC,4BAA4B,MAAM;AAAA,EAClC,wBAAwB,MAAM;AAAA,EAC9B,oBAAoB,MAAM;AAAA,EAC1B,sBAAsB,MAAM;AAAA,EAC5B,iBAAiB,MAAM;AAAA,EACvB,qBAAqB,MAAM;AAAA,EAC3B,2BAA2B,MAAM;AAAA,EACjC,kBAAkB,MAAM;AAAA,EACxB,sBAAsB,MAAM;AAAA,EAC5B,qBAAqB,MAAM;AAAA,EAC3B,mBAAmB,MAAM;AAAA,EACzB,mBAAmB,MAAM;AAAA,EACzB,mBAAmB,MAAM;AAAA,EACzB,uBAAuB,MAAM;AAAA,EAC7B,0BAA0B,MAAM;AAAA,EAChC,2BAA2B,MAAM;AAAA,EACjC,iBAAiB,MAAM;AAAA,EACvB,mBAAmB,MAAM;AAAA,EACzB,mBAAmB,MAAM;AAAA,EACzB,yBAAyB,MAAM;AAAA,EAC/B,sBAAsB,MAAM;AAAA,EAC5B,gCAAgC,MAAM;AAAA,EACtC,sBAAsB,MAAM;AAAA,EAC5B,UAAU,MAAM;AAAA,EAChB,WAAW,MAAM;AAAA,EACjB,wBAAwB,MAAM;AAAA,EAC9B,wBAAwB,MAAM;AAAA,EAC9B,oBAAoB,MAAM;AAAA,EAC1B,kBAAkB,MAAM;AAAA,EACxB,qBAAqB,MAAM;AAAA,EAC3B,sBAAsB,MAAM;AAAA,EAC5B,sBAAsB,MAAM;AAAA,EAC5B,sBAAsB,MAAM;AAAA,EAC5B,sBAAsB,MAAM;AAAA,EAC5B,gBAAgB,MAAM;AAAA,EACtB,kBAAkB,MAAM;AAAA,EACxB,aAAa,MAAM;AAAA,EACnB,kBAAkB,MAAM;AAAA,EACxB,aAAa,MAAM;AAAA,EACnB,qBAAqB,MAAM;AAAA,EAC3B,qBAAqB,MAAM;AAAA,EAC3B,cAAc,MAAM;AAAA,EACpB,iDAAiD,MAAM;AAAA,EACvD,iDAAiD,MAAM;AAAA,EACvD,mDAAmD,MAAM;AAAA,EACzD,sDAAsD,MAAM;AAAA,EAC5D,iDAAiD,MAAM;AAAA,EACvD,iDAAiD,MAAM;AAAA,EACvD,0DAA0D,MAAM;AAAA,EAChE,+CAA+C,MAAM;AAAA,EACrD,wDAAwD,MAAM;AAAA,EAC9D,yDAAyD,MAAM;AAAA,EAC/D,8DAA8D,MAAM;AAAA,EACpE,0DAA0D,MAAM;AAAA,EAChE,wBAAwB,MAAM;AAAA,EAC9B,uBAAuB,MAAM;AAAA,EAC7B,KAAK,MAAMgB;AAAA,EACX,wBAAwB,MAAM;AAAA,EAC9B,oBAAoB,MAAM;AAAA,EAC1B,kBAAkB,MAAM;AAAA,EACxB,cAAc,MAAM;AAAA,EACpB,YAAY,MAAM;AAAA,EAClB,YAAY,MAAM;AAAA,EAClB,wBAAwB,MAAM;AAAA,EAC9B,mBAAmB,MAAM;AAAA,EACzB,YAAY,MAAM;AAAA,EAClB,eAAe,MAAM;AAAA,EACrB,qBAAqB,MAAM;AAAA,EAC3B,MAAM,MAAM;AACd,CAAC;AAGD,SAAS,uBAAuB,QAAQ,MAAM;AAC5C,QAAM,OAAO,OAAO,GAAG;AACvB,SAAO,QAAQ,CAAC,OAAO,OAAO;AAC5B,WAAO,MAAM,WAAW,MAAM,MAAM,kBAAkB,0BAA0B,iDAAiD,OAAO;AAAA,EAC1I,CAAC;AACD,SAAO,QAAQ,KAAK,OAAO,MAAM,MAAM,kBAAkB,qCAAqC,OAAO,IAAI;AACzG,QAAM,aAAa,OAAO;AAC1B,SAAO,QAAQ,CAAC,OAAO,OAAO;AAC5B,aAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,aAAO,OAAO,QAAQ,MAAM,QAAQ,WAAW,KAAK,MAAM,kBAAkB,2BAA2B,QAAQ,gDAAgD,+CAA+C,KAAK;AAAA,IACrN;AAAA,EACF,CAAC;AACH;AACA,SAAS,iBAAiB,QAAQ,MAAM;AACtC,QAAM,cAAc,OAAO,GAAG,MAAM;AACpC,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,gBAAY,SAAS,OAAO,IAAI;AAAA,EAClC;AACA,SAAO;AACT;AAGA,IAAI,wBAAwB;AAC5B,SAAS,yBAAyB,QAAQ;AACxC,MAAI,UAAU,uBAAuB;AACnC,WAAO;AAAA,EACT;AACA,SAAO,eAAe,QAAQ,KAAK,MAAM,KAAK,KAAK,MAAM,CAAC,CAAC;AAC7D;AAGA,SAAS,eAAe,QAAQ,aAAa,YAAY;AACvD,QAAM,UAAU,cAAc,OAAO,WAAW,WAAW,SAAS,OAAO;AAC3E,QAAM,UAAU,eAAe,OAAO,WAAW,WAAW,SAAS,OAAO;AAC5E,SAAO,CAAC,SAAS,OAAO;AAC1B;AAGA,SAAS,YAAY,YAAY,YAAY,OAAO,eAAe,MAAM;AACvE,MAAI,WAAW,CAAC;AAChB,MAAI,cAAc;AAChB,eAAW,SAAS,OAAO,WAAW,MAAM,CAAC,CAAC;AAC9C,aAAS,KAAK,WAAW,KAAK,KAAK;AACnC,eAAW,SAAS,OAAO,WAAW,MAAM,CAAC,CAAC;AAAA,EAChD,OAAO;AACL,eAAW,SAAS,OAAO,WAAW,EAAE;AACxC,UAAM,gBAAgB,WAAW;AACjC,aAAS,KAAK,GAAG,KAAK,eAAe,EAAE,IAAI;AACzC,iBAAW,SAAS,OAAO,CAAC,WAAW,KAAK,KAAK,WAAW,KAAK,WAAW,GAAG,CAAC;AAAA,IAClF;AACA,eAAW,SAAS,OAAO,WAAW,MAAM,gBAAgB,CAAC,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,SAAS,YAAY,cAAc,gBAAgB,eAAe,MAAM;AACtE,QAAM,WAAW,CAAC;AAClB,MAAI,cAAc;AAChB,aAAS,KAAK,cAAc;AAC5B,aAAS,KAAK,iBAAiB,GAAG,KAAK,cAAc,EAAE,IAAI;AACzD,UAAI,MAAM,IAAI,gBAAgB;AAC5B,iBAAS,KAAK,EAAE;AAChB,iBAAS,KAAK,MAAM,iBAAiB,EAAE;AAAA,MACzC,OAAO;AACL,iBAAS,KAAK,EAAE;AAAA,MAClB;AAAA,IACF;AAAA,EACF,OAAO;AACL,UAAM,sBAAsB,CAAC;AAC7B,UAAM,qBAAqB,CAAC;AAC5B,aAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,UAAI,MAAM,iBAAiB,IAAI,KAAK,KAAK,MAAM,GAAG;AAChD,2BAAmB,KAAK,EAAE;AAAA,MAC5B,OAAO;AACL,4BAAoB,KAAK,EAAE;AAAA,MAC7B;AAAA,IACF;AACA,aAAS,KAAK,GAAG,mBAAmB;AACpC,aAAS,KAAK,CAAC;AACf,aAAS,KAAK,GAAG,kBAAkB;AAAA,EACrC;AACA,SAAO;AACT;AACA,SAAS,oBAAoB,YAAY,YAAY,OAAO,eAAe,MAAM;AAC/E,QAAM,mBAAmB,CAAC;AAC1B,MAAI,cAAc;AAChB,qBAAiB,KAAK,WAAW,KAAK,KAAK;AAAA,EAC7C,OAAO;AACL,qBAAiB,KAAK,WAAW,KAAK,KAAK;AAAA,EAC7C;AACA,WAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,QAAI,MAAM,WAAW,QAAQ;AAC3B,UAAI,cAAc;AAChB,yBAAiB,KAAK,WAAW,KAAK,KAAK,WAAW,GAAG;AAAA,MAC3D,OAAO;AACL,yBAAiB,KAAK,WAAW,MAAM,WAAW,KAAK,EAAE;AAAA,MAC3D;AAAA,IACF,OAAO;AACL,uBAAiB,KAAK,WAAW,GAAG;AAAA,IACtC;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,oBAAoB,OAAO,YAAY;AAC9C,QAAM,mBAAmB,CAAC,CAAC;AAC3B,WAAS,KAAK,GAAG,KAAK,YAAY,EAAE,IAAI;AACtC,qBAAiB,KAAK,MAAM,IAAI,EAAE;AAAA,EACpC;AACA,SAAO;AACT;AACA,SAAS,aAAa,gBAAgB,OAAO,YAAY;AACvD,QAAM,YAAY,eAAe,MAAM,GAAG,CAAC;AAC3C,WAAS,KAAK,GAAG,KAAK,YAAY,EAAE,IAAI;AACtC,cAAU,KAAK,eAAe,KAAK,KAAK,MAAM,IAAI,KAAK,MAAM,IAAI,EAAE;AAAA,EACrE;AACA,SAAO;AACT;AAGA,IAAI,kBAAkB;AACtB,IAAI,aAAa;AAGjB,IAAI,QAAQ;AACZ,IAAI,SAAS;AACb,IAAI,SAAS;AACb,IAAI,SAAS;AACb,IAAI,SAAS;AACb,IAAI,SAAS;AAGb,SAAS,uBAAuB,OAAO,OAAO;AAC5C,MAAI,MAAM,WAAW,MAAM,QAAQ;AACjC,UAAM,IAAI,MAAM,gEAAgE,MAAM,iBAAiB,MAAM,SAAS;AAAA,EACxH;AACA,QAAM,SAAS,IAAI,aAAa,MAAM,SAAS,CAAC;AAChD,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM,GAAG;AAC5C,WAAO,MAAM,MAAM,KAAK;AACxB,WAAO,KAAK,KAAK,MAAM,KAAK;AAAA,EAC9B;AACA,SAAO;AACT;AACA,SAAS,uBAAuB,UAAU;AACxC,QAAM,QAAQ,IAAI,aAAa,SAAS,SAAS,CAAC;AAClD,QAAM,QAAQ,IAAI,aAAa,SAAS,SAAS,CAAC;AAClD,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM,GAAG;AAC9C,UAAM,KAAK,KAAK,SAAS;AACzB,UAAM,KAAK,KAAK,SAAS,KAAK;AAAA,EAChC;AACA,SAAO,EAAE,MAAM,OAAO,MAAM,MAAM;AACpC;AACA,SAAS,qBAAqB,UAAU;AACtC,QAAM,MAAM,KAAK,KAAK,SAAS,SAAS,CAAC;AACzC,QAAM,QAAQ,IAAI,aAAa,GAAG;AAClC,QAAM,QAAQ,IAAI,aAAa,GAAG;AAClC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM,GAAG;AAC9C,UAAM,KAAK,MAAM,KAAK,CAAC,KAAK,SAAS;AACrC,UAAM,KAAK,MAAM,KAAK,CAAC,KAAK,SAAS,KAAK;AAAA,EAC5C;AACA,SAAO,EAAE,MAAM,OAAO,MAAM,MAAM;AACpC;AACA,SAAS,oBAAoB,UAAU;AACrC,QAAM,MAAM,KAAK,MAAM,SAAS,SAAS,CAAC;AAC1C,QAAM,QAAQ,IAAI,aAAa,GAAG;AAClC,QAAM,QAAQ,IAAI,aAAa,GAAG;AAClC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM,GAAG;AAC9C,UAAM,KAAK,MAAM,KAAK,CAAC,KAAK,SAAS;AACrC,UAAM,KAAK,MAAM,KAAK,CAAC,KAAK,SAAS,KAAK;AAAA,EAC5C;AACA,SAAO,EAAE,MAAM,OAAO,MAAM,MAAM;AACpC;AACA,SAAS,oBAAoB,UAAUJ,QAAO;AAC5C,QAAM,QAAQ,SAASA,SAAQ;AAC/B,QAAM,QAAQ,SAASA,SAAQ,IAAI;AACnC,SAAO,EAAE,MAAM,OAAO,MAAM,MAAM;AACpC;AACA,SAAS,mBAAmB,MAAM,OAAO,OAAOA,QAAO;AACrD,OAAKA,SAAQ,KAAK;AAClB,OAAKA,SAAQ,IAAI,KAAK;AACxB;AACA,SAAS,UAAU,IAAI,SAAS;AAC9B,QAAM,QAAQ,IAAI,aAAa,KAAK,CAAC;AACrC,QAAM,QAAQ,IAAI,aAAa,KAAK,CAAC;AACrC,WAAS,KAAK,GAAG,KAAK,KAAK,KAAK,KAAK,CAAC,GAAG,MAAM;AAC7C,UAAM,KAAK,UAAU,IAAI,MAAM,KAAK,MAAM,KAAK;AAC/C,UAAM,MAAM,KAAK,IAAI,CAAC;AACtB,UAAM,MAAM,KAAK,IAAI,CAAC;AAAA,EACxB;AACA,SAAO,EAAE,MAAM,OAAO,MAAM,MAAM;AACpC;AACA,SAAS,SAAS,GAAG,IAAI,SAAS;AAChC,QAAM,KAAK,UAAU,IAAI,MAAM,KAAK,MAAM,IAAI;AAC9C,QAAM,QAAQ,KAAK,IAAI,CAAC;AACxB,QAAM,QAAQ,KAAK,IAAI,CAAC;AACxB,SAAO,EAAE,MAAM,OAAO,MAAM,MAAM;AACpC;AAGA,IAAI,QAAQ;AACZ,IAAI,cAAc;AAClB,IAAI,QAAQ;AACZ,IAAI,WAAW;AACf,SAAS,qBAAqB,UAAU,YAAY;AAClD,aAAW,SAAS,QAAQ,OAAO,EAAE;AACrC,QAAM,aAAa,SAAS,SAAS,SAAS,QAAQ,aAAa,EAAE,EAAE,UAAU,MAAM;AACvF,MAAI,YAAY,GAAG;AACjB,UAAM,IAAI,MAAM,+CAA+C;AAAA,EACjE,WAAW,YAAY,GAAG;AACxB,UAAM,IAAI,MAAM,6CAA6C,UAAU;AAAA,EACzE;AACA,QAAM,CAAC,aAAa,YAAY,IAAI,SAAS,MAAM,KAAK;AACxD,SAAO,YAAY,QAAQ,QAAQ,MAAM,IAAI,MAAM,2BAA2B,kCAAkC;AAChH,QAAM,aAAa,YAAY,MAAM,KAAK;AAC1C,QAAM,YAAY,WAAW;AAC7B,MAAI,eAAe,WAAW;AAC5B,UAAM,IAAI,MAAM,YAAY,qCAAqC,YAAY;AAAA,EAC/E;AACA,MAAI,YAAY,GAAG;AACjB,UAAM,IAAI,MAAM,+DAA+D;AAAA,EACjF;AACA,QAAM,UAAU,CAAC;AACjB,WAAS,KAAK,GAAG,KAAK,aAAa,QAAQ,EAAE,IAAI;AAC/C,UAAM,UAAU,aAAa;AAC7B,QAAI,CAAC,WAAW,KAAK,CAAC,cAAc,UAAU,QAAQ,OAAO,MAAM,EAAE,GAAG;AACtE,YAAM,IAAI,MAAM,uCAAuC,8CAA8C;AAAA,IACvG;AACA,QAAI,QAAQ,QAAQ,OAAO,MAAM,IAAI;AACnC,cAAQ,KAAK,OAAO;AAAA,IACtB;AAAA,EACF;AACA,WAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,EAAE,IAAI;AAC9C,UAAM,UAAU,YAAY;AAC5B,QAAI,QAAQ,QAAQ,OAAO,MAAM,MAAM,YAAY,OAAO;AACxD,cAAQ,KAAK,OAAO;AAAA,IACtB;AAAA,EACF;AACA,QAAM,SAAS,IAAI,MAAM,WAAW,MAAM;AAC1C,WAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,QAAI,IAAI,IAAI,WAAW,IAAI,MAAM,EAAE,CAAC,EAAE,SAAS,WAAW,IAAI,QAAQ;AACpE,YAAM,IAAI,MAAM,2CAA2C,WAAW,kEAAkE;AAAA,IAC1I;AACA,WAAO,MAAM,CAAC;AACd,aAAS,IAAI,GAAG,IAAI,WAAW,IAAI,QAAQ,EAAE,GAAG;AAC9C,aAAO,IAAI,KAAK,QAAQ,QAAQ,WAAW,IAAI,EAAE,CAAC;AAAA,IACpD;AAAA,EACF;AACA,QAAM,UAAU,QAAQ;AACxB,QAAM,aAAa,aAAa;AAChC,QAAM,aAAa,CAAC;AACpB,WAAS,KAAK,YAAY,KAAK,SAAS,EAAE,IAAI;AAC5C,eAAW,KAAK,EAAE;AAAA,EACpB;AACA,SAAO,EAAE,SAAS,YAAY,OAAO;AACvC;AACA,SAAS,qBAAqB,OAAO,QAAQ;AAC3C,MAAI,qBAAqB,IAAI,MAAM,KAAK;AACxC,qBAAmB,KAAK,EAAE;AAC1B,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,uBAAmB,OAAO,OAAO;AAAA,EACnC;AACA,QAAM,cAAc,CAAC;AACrB,WAAS,KAAK,GAAG,KAAK,OAAO,EAAE,IAAI;AACjC,QAAI,mBAAmB,QAAQ,IAAI;AACjC,kBAAY,KAAK,EAAE;AAAA,IACrB;AAAA,EACF;AACA,uBAAqB,mBAAmB,OAAO,CAAC,MAAM,MAAM,EAAE;AAC9D,SAAO,EAAE,oBAAoB,YAAY,YAAY;AACvD;AACA,SAAS,oBAAoB,OAAO,QAAQ,SAAS;AACnD,QAAM,WAAW,IAAI,MAAM,KAAK;AAChC,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC1C,UAAM,QAAQ,QAAQ,IAAI;AAC1B,aAAS,IAAI,GAAG,IAAI,OAAO,IAAI,QAAQ,EAAE,GAAG;AAC1C,UAAI,SAAS,OAAO,IAAI,QAAQ,QAAQ;AACtC,iBAAS,OAAO,IAAI,MAAM,MAAM;AAAA,MAClC,OAAO;AACL,eAAO,SAAS,OAAO,IAAI,QAAQ,MAAM,IAAI,MAAM,sBAAsB,SAAS,OAAO,IAAI,eAAe,qBAAqB,KAAK,UAAU,KAAK,wBAAwB,MAAM,IAAI;AAAA,MACzL;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,qBAAqB,YAAY,QAAQ;AAChD,QAAM,OAAO;AACb,QAAM,QAAQ,CAAC;AACf,MAAI,SAAS;AACb,MAAI,WAAW,WAAW,GAAG;AAC3B,SAAK,KAAK,EAAE;AAAA,EACd;AACA,WAAS,WAAW,SAAS;AAC7B,WAAS,KAAK,GAAG,KAAK,QAAQ,EAAE,IAAI;AAClC,UAAM,KAAK,CAAC,CAAC;AAAA,EACf;AACA,QAAM,sBAAsB,CAAC;AAC7B,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,YAAY,KAAK;AACvB,UAAM,cAAc,iBAAiB,QAAQ,SAAS;AACtD,eAAW,aAAa,aAAa;AACnC,UAAI,oBAAoB,QAAQ,SAAS,MAAM,IAAI;AACjD,cAAM,IAAI,KAAK,SAAS;AACxB,4BAAoB,KAAK,SAAS;AAAA,MACpC;AAAA,IACF;AAAA,EACF;AACA,SAAO,EAAE,MAAM,MAAM;AACvB;AACA,SAAS,sBAAsB,MAAM;AACnC,SAAO,KAAK,MAAM,CAAC,KAAKA,WAAU,QAAQA,MAAK;AACjD;AACA,SAAS,iBAAiB,QAAQ,KAAK;AACrC,QAAM,cAAc,CAAC;AACrB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,QAAI,OAAO,IAAI,WAAW,KAAK,OAAO,IAAI,QAAQ,GAAG,MAAM,MAAM,QAAQ,IAAI;AAC3E,kBAAY,KAAK,EAAE;AAAA,IACrB;AAAA,EACF;AACA,SAAO;AACT;AAGA,SAAS,iBAAiB,GAAG,iBAAiB,OAAO,GAAG;AACtD,MAAI,aAAa,CAAC;AAClB,MAAI,OAAO,oBAAoB,UAAU;AACvC,WAAO,EAAE,MAAM,QAAQ,oBAAoB,GAAG,MAAM,+CAA+C;AACnG,iBAAa,IAAI,MAAM,eAAe,EAAE,KAAK,EAAE,MAAM,QAAQ,eAAe;AAAA,EAC9E,OAAO;AACL,UAAM,YAAY,gBAAgB,OAAO,CAACF,SAAQ,UAAU;AAC1D,UAAI,UAAU,IAAI;AAChB,QAAAA,WAAU;AAAA,MACZ;AACA,aAAOA;AAAA,IACT,GAAG,CAAC;AACJ,WAAO,aAAa,GAAG,MAAM,yDAAyD;AACtF,UAAM,WAAW,gBAAgB,QAAQ,EAAE;AAC3C,QAAI,aAAa,IAAI;AACnB,YAAM,QAAQ,gBAAgB,OAAO,CAAC,GAAG,MAAM,IAAI,IAAI,IAAI,IAAI,CAAC;AAChE,sBAAgB,YAAY,EAAE,MAAM,QAAQ;AAAA,IAC9C;AACA,WAAO,EAAE,MAAM,UAAU,gBAAgB,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC,GAAG,MAAM,6DAA6D;AACrI,iBAAa;AAAA,EACf;AACA,SAAO;AACT;AAGA,SAAS,gDAAgD,eAAe;AACtE,SAAO;AAAA,uBACc;AACvB;AACA,SAAS,gDAAgDE,QAAO,OAAO;AACrE,SAAO,WAAWA,0BAAyB;AAC7C;AACA,SAAS,kDAAkDA,QAAO,OAAO,OAAO;AAC9E,SAAO,WAAWA,0BAAyB,YAAY;AACzD;AAGA,SAAS,yDAAyD,MAAM,MAAM;AAC5E,SAAO,iDAAiD,YAAY;AACtE;AACA,SAAS,8CAA8C,KAAK,OAAO;AACjE,SAAO,QAAQ,iCAAiC;AAClD;AACA,SAAS,uDAAuD;AAC9D,SAAO;AACT;AACA,SAAS,gDAAgD,YAAY,aAAa;AAChF,QAAMiB,cAAY,cAAc,UAAU;AAC1C,QAAMN,cAAa,cAAc,WAAW;AAC5C,SAAO,2CAA2CM;AAAA,iEACaN,2BAA0B,2BAA2B;AACtH;AACA,SAAS,gDAAgD,YAAY,aAAa;AAChF,QAAMM,cAAY,cAAc,UAAU;AAC1C,QAAMN,cAAa,cAAc,WAAW;AAC5C,SAAO,qCAAqCM,yDAAuDN,2BAA0B,0BAA0B;AACzJ;AAGA,SAAS,0DAA0D;AACjE,SAAO;AACT;AACA,SAAS,+DAA+D;AACtE,SAAO;AACT;AACA,SAAS,yDAAyD,WAAW,YAAY;AACvF,SAAO,cAAc,8BAA8B;AACrD;AACA,SAAS,uDAAuDX,QAAO,YAAY,WAAW;AAC5F,SAAO,gBAAgBA,cAAa,+BAA+B;AACrE;AAGA,IAAI,uBAAuB,CAAC;AAC5BZ,UAAS,sBAAsB;AAAA,EAC7B,0BAA0B,MAAM;AAAA,EAChC,iBAAiB,MAAM;AAAA,EACvB,+BAA+B,MAAM;AACvC,CAAC;AACD,SAAS,8BAA8B,QAAQ,aAAa;AAC1D,MAAI,OAAO;AACX,MAAI;AACJ,MAAI,UAAU,uBAAuB;AACnC,UAAM;AACN,WAAO;AAAA,EACT,OAAO;AACL,UAAM,eAAe,QAAQ,KAAK,MAAM,KAAK,KAAK,MAAM,CAAC,CAAC;AAAA,EAC5D;AACA,SAAO,CAAC,MAAM;AACZ,QAAI,MAAM,eAAe,QAAQ,QAAQ;AACvC,aAAO;AAAA,IACT,OAAO;AACL,YAAM,eAAe,QAAQ,MAAM,CAAC;AAAA,IACtC;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,QAAQ,MAAM,aAAa;AACnD,QAAM,WAAW,CAAC;AAClB,QAAM,OAAO,OAAO;AACpB,WAAS,MAAM,GAAG,MAAM,MAAM,OAAO;AACnC,QAAI,QAAQ,MAAM;AAChB,eAAS,KAAK,OAAO,IAAI;AAAA,IAC3B,OAAO;AACL,eAAS,KAAK,WAAW;AAAA,IAC3B;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,yBAAyB,GAAG,SAAS,MAAM,WAAW;AAC7D,QAAM,cAAc,QAAQ,MAAM;AAClC,QAAM,QAAQ,EAAE,MAAM;AACtB,MAAI,cAAc,GAAG;AACnB,QAAI,YAAY,CAAC,eAAe,YAAY,aAAa;AACvD,YAAM,IAAI,MAAM,sCAAsC,gBAAgB,yBAAyB,WAAW;AAAA,IAC5G;AAAA,EACF;AACA,MAAI,YAAY,GAAG;AACjB,iBAAa;AAAA,EACf;AACA,MAAI,YAAY,OAAO;AACrB,UAAM,IAAI,MAAM,cAAc;AAAA,MAC5B,SAAS;AAAA,EACb;AACA,MAAI,OAAO,WAAW;AACpB,UAAM,IAAI,MAAM,cAAc,kDAAkD,QAAQ;AAAA,EAC1F;AACA,WAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,QAAI,EAAE,MAAM,QAAQ,QAAQ,MAAM,KAAK;AACrC,YAAM,IAAI,MAAM,WAAW,QAAQ,EAAE,MAAM,wCAAwC,QAAQ,QAAQ,MAAM,MAAM;AAAA,IACjH;AAAA,EACF;AACA,QAAM,UAAU,EAAE,MAAM;AACxB,QAAM,cAAc,CAAC;AACrB,MAAI,YAAY;AAChB,MAAI,YAAY;AAChB,MAAI,YAAY;AAChB,WAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,gBAAY,KAAK,EAAE,MAAM,GAAG;AAC5B,iBAAa,EAAE,MAAM;AAAA,EACvB;AACA,WAAS,KAAK,WAAW,KAAK,MAAM,MAAM;AACxC,gBAAY,KAAK,EAAE,MAAM,GAAG;AAC5B,iBAAa,EAAE,MAAM;AAAA,EACvB;AACA,WAAS,KAAK,WAAW,KAAK,aAAa,MAAM;AAC/C,gBAAY,KAAK,QAAQ,MAAM,GAAG;AAAA,EACpC;AACA,WAAS,KAAK,OAAO,GAAG,KAAK,OAAO,MAAM;AACxC,gBAAY,KAAK,EAAE,MAAM,GAAG;AAC5B,iBAAa,EAAE,MAAM;AAAA,EACvB;AACA,SAAO,EAAE,WAAW,WAAW,WAAW,SAAS,YAAY;AACjE;AAGA,SAAS,uBAAuB,MAAM;AACpC,MAAI;AACF,WAAO,KAAK,IAAI,CAAC,QAAQ,aAAa,GAAG,CAAC;AAAA,EAC5C,SAAS,KAAP;AACA,UAAM,IAAI,MAAM,4DAA4D,KAAK;AAAA,EACnF;AACF;AACA,SAAS,uBAAuB,SAAS;AACvC,SAAO,QAAQ,IAAI,CAAC,OAAO,aAAa,EAAE,CAAC;AAC7C;AAGA,IAAI,uBAAuB,CAAC;AAC5BA,UAAS,sBAAsB;AAAA,EAC7B,yBAAyB,MAAM;AAAA,EAC/B,yBAAyB,MAAM;AAAA,EAC/B,yBAAyB,MAAM;AAAA,EAC/B,WAAW,MAAM;AACnB,CAAC;AAGD,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAK,KAAK,GAAG,SAAS,GAAG,EAAE,CAAC,EAAE;AAAA,EAC1D;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO;AAAA,MACL,GAAG,MAAM;AACP,cAAM,IAAI,OAAO,KAAK,GAAG,SAAS,CAAC;AACnC,cAAM,IAAI,KAAK,IAAI,OAAO,CAAC,GAAG,CAAC,CAAC;AAChC,eAAO,IAAI,IAAI,IAAI,CAAC,CAAC;AAAA,MACvB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO;AAAA,MACL,GAAG,MAAM;AACP,cAAM,IAAI,KAAK,IAAI,OAAO,KAAK,GAAG,SAAS,CAAC,GAAG,CAAC,CAAC;AACjD,eAAO,IAAI,IAAI,CAAC;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,2BAA2B,EAAE,OAAO,EAAE,KAAK;AAC5D,UAAM,OAAO,MAAM;AACjB,UAAI,MAAM;AACV,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,KAAK,EAAE,KAAK;AAAA,IAC7B;AACA,UAAM,OAAO,MAAM;AACjB,UAAI,MAAM;AACV,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,KAAK,EAAE,KAAK;AAAA,IAC7B;AACA,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,eAAe;AAAA,EACf,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,OAAO,CAAC;AACd,UAAM,QAAQ,CAAC,GAAG,OAAO;AACvB,WAAK,MAAM,MAAM,GAAG,MAAM;AAAA,IAC5B,CAAC;AACD,WAAO;AAAA,EACT;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,UAAU,CAAC,EAAE;AAAA,EACjC;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,UAAU,CAAC,EAAE;AAAA,EACjC;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAK,IAAI,OAAO,CAAC,GAAG,OAAO,KAAK,GAAG,SAAS,CAAC,CAAC,CAAC,CAAC,EAAE;AAAA,EAC9E;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO;AAAA,MACL,GAAG,MAAM;AACP,cAAM,IAAI,KAAK,KAAK,OAAO,CAAC,GAAG,OAAO,KAAK,GAAG,SAAS,CAAC,CAAC,CAAC;AAC1D,eAAO,IAAI,IAAI,CAAC;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,2BAA2B,EAAE,OAAO,EAAE,KAAK;AAC5D,UAAM,OAAO,MAAM;AACjB,YAAM,IAAI,KAAK,OAAO,CAAC,GAAG,OAAO,CAAC,CAAC;AACnC,UAAI,MAAM,IAAI,IAAI,IAAI,GAAG,CAAC,CAAC;AAC3B,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,KAAK,EAAE,KAAK;AAAA,IAC7B;AACA,UAAM,OAAO,MAAM;AACjB,YAAM,IAAI,KAAK,OAAO,CAAC,GAAG,OAAO,CAAC,CAAC;AACnC,UAAI,MAAM,IAAI,IAAI,IAAI,IAAI,GAAG,CAAC,CAAC,CAAC;AAChC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,KAAK,EAAE,KAAK;AAAA,IAC7B;AACA,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAK,OAAO,KAAK,GAAG,SAAS,CAAC,GAAG,CAAC,CAAC,EAAE;AAAA,EACjE;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,OAAO,CAAC,GAAG,OAAO,KAAK,GAAG,SAAS,CAAC,CAAC,CAAC,EAAE;AAAA,EACxE;AACF;AAGA,SAAS,eAAe,IAAI,QAAQ,YAAYe,UAAS,MAAM,iBAAiB;AAC9E,QAAM,MAAM,gBAAgB,IAAI,MAAM,eAAe;AACrD,QAAM,SAAS,gBAAgB,QAAQ,SAAS,eAAe;AAC/D,MAAI,OAAO;AACX,MAAI,UAAU;AACd,MAAI,eAAe;AACnB,MAAI,OAAO,SAAS,GAAG;AACrB,mBAAe;AACf,WAAO,QAAQ,KAAK,CAAC,GAAG,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAC/E,cAAU,QAAQ,QAAQ;AAAA,MACxB;AAAA,MACA,OAAO,MAAM;AAAA,MACb,OAAO,MAAM;AAAA,MACb,OAAO,MAAM;AAAA,MACb,OAAO,MAAM;AAAA,IACf,CAAC;AAAA,EACH;AACA,SAAO,KAAK,SAAS,GAAG,MAAM,0DAA0D,KAAK,OAAO;AACpG,SAAO,QAAQ,SAAS,GAAG,MAAM,6DAA6D,QAAQ,OAAO;AAC7G,4BAA0B,iBAAiB,MAAM,eAAe;AAChE,QAAM,SAAS,EAAE,IAAI,MAAM,OAAO,QAAQ;AAC1C,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB;AAChE,QAAM,MAAM,OAAO,UAAU,eAAe,QAAQ,KAAK;AACzD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAC9E;AACA,SAAO;AACT;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,WAAO;AAAA,MACL,GAAG,MAAM,cAAc,IAAI,GAAG,YAAYA,UAAS,MAAM,eAAe;AAAA,IAC1E;AAAA,EACF;AACF;AAGA,SAAS,aAAa,IAAI,QAAQ,YAAYA,UAAS,MAAM;AAC3D,QAAM,MAAM,gBAAgB,IAAI,MAAM,aAAa;AACnD,QAAM,SAAS,gBAAgB,QAAQ,SAAS,aAAa;AAC7D,SAAO,OAAO,SAAS,IAAI,MAAM,MAAM,kBAAkB,OAAO,oCAAoC,IAAI,OAAO;AAC/G,MAAI,UAAU;AACd,MAAI,OAAO;AACX,MAAI,eAAe;AACnB,MAAI,OAAO,SAAS,GAAG;AACrB,mBAAe;AACf,cAAU,QAAQ,QAAQ,CAAC,GAAG,OAAO,MAAM,IAAI,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE,CAAC;AAChF,WAAO,QAAQ,KAAK,CAAC,GAAG,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EACnE;AACA,SAAO,KAAK,SAAS,GAAG,MAAM,wDAAwD,KAAK,OAAO;AAClG,SAAO,QAAQ,SAAS,GAAG,MAAM,2DAA2D,QAAQ,OAAO;AAC3G,QAAM,SAAS,EAAE,IAAI,MAAM,OAAO,QAAQ;AAC1C,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,KAAK;AAC/C,QAAM,MAAM,OAAO,UAAU,aAAa,QAAQ,KAAK;AACvD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,KAAK,IAAI;AAC3C,WAAO,EAAE,GAAG,MAAM,YAAY,IAAI,GAAG,YAAYA,UAAS,IAAI,EAAE;AAAA,EAClE;AACF;AAGA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,EAAE,YAAY,WAAW,IAAI;AACnC,QAAI,CAAC,cAAc,CAAC,YAAY;AAC9B,aAAO;AAAA,QACL,GAAG,MAAM,OAAO,IAAI,GAAG,OAAO,IAAI;AAAA,QAClC,GAAG,MAAM,OAAO,GAAG,IAAI,MAAM,KAAK;AAAA,MACpC;AAAA,IACF,WAAW,CAAC,cAAc,YAAY;AACpC,aAAO;AAAA,QACL,GAAG,MAAM,OAAO,IAAI,GAAG,OAAO,KAAK;AAAA,QACnC,GAAG,MAAM,OAAO,IAAI,GAAG,MAAM,KAAK;AAAA,MACpC;AAAA,IACF,WAAW,cAAc,CAAC,YAAY;AACpC,aAAO;AAAA,QACL,GAAG,MAAM,OAAO,GAAG,IAAI,OAAO,IAAI;AAAA,QAClC,GAAG,MAAM,OAAO,GAAG,IAAI,OAAO,KAAK;AAAA,MACrC;AAAA,IACF,OAAO;AACL,aAAO;AAAA,QACL,GAAG,MAAM,OAAO,GAAG,IAAI,MAAM,IAAI;AAAA,QACjC,GAAG,MAAM,OAAO,IAAI,GAAG,MAAM,IAAI;AAAA,MACnC;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,YAAY,MAAM,IAAI;AAC9B,WAAO,EAAE,GAAG,MAAM,eAAe,IAAI,YAAY,KAAK,EAAE;AAAA,EAC1D;AACF;AAGA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,mBAAmB;AACzB,UAAM,aAAa,iBAAiB;AACpC,UAAM,cAAc,iBAAiB;AACrC,UAAM,OAAO,MAAM,KAAK,WAAW;AACnC,aAAS,KAAK,WAAW,SAAS,GAAG,MAAM,GAAG,MAAM;AAClD,UAAI,WAAW,QAAQ,YAAY,KAAK;AACtC,aAAK,MAAM;AAAA,MACb,WAAW,WAAW,QAAQ,GAAG;AAC/B,cAAM,IAAI,MAAM,mBAAmB,uCAAuC,eAAe;AAAA,MAC3F;AAAA,IACF;AACA,UAAM,OAAO,CAAC;AACd,aAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,UAAI,KAAK,MAAM,GAAG;AAChB,aAAK,KAAK,EAAE;AAAA,MACd;AAAA,IACF;AACA,WAAO,EAAE,GAAG,MAAM,KAAK,IAAI,MAAM,IAAI,EAAE;AAAA,EACzC;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,GAAG,MAAM,EAAE;AAAA,EAC/B;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,cAAc,aAAa,IAAI;AACvC,WAAO;AAAA,MACL,GAAG,MAAM,MAAM,WAAW,aAAa,GAAG,YAAY,GAAG,UAAU,GAAG,YAAY,CAAC,GAAG,IAAI,UAAU,EAAE,CAAC;AAAA,IACzG;AAAA,EACF;AACF;AAGA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,cAAc;AAC1B;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,eAAe;AAAA,EACf,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,SAAS,MAAM,IAAI,CAAC,OAAO,GAAG,KAAK;AACzC,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,QAAQ,eAAe,MAAM,MAAM,GAAG,KAAK,EAAE;AACnD,UAAM,aAAa,OAAO,IAAI,CAAC,OAAO,GAAG,MAAM;AAC/C,UAAM,aAAa,MAAM,IAAI,YAAY,KAAK;AAC9C,WAAO,WAAW,IAAI,CAAC,OAAO,MAAM,EAAE;AAAA,EACxC;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,QAAQ;AAAA,EAC5B,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,KAAK,OAAO,IAAI;AACvB,UAAM,EAAE,WAAW,SAAAA,UAAS,KAAK,MAAM,WAAW,IAAI;AACtD,WAAO,kBAAkB,SAAS,GAAG,MAAM,iHAAiH,YAAY;AACxK,WAAO;AAAA,MACL,GAAG,MAAM,oBAAoB,IAAI,OAAO,IAAI,SAASA,UAAS,MAAM,UAAU;AAAA,MAC9E,QAAQ,MAAM,qBAAqB,KAAK,IAAI,QAAQ,OAAOA,UAAS,MAAM,UAAU;AAAA,IACtF;AAAA,EACF;AACF;AAGA,IAAI,gCAAgC;AAAA,EAClC,YAAY;AAAA,EACZ,cAAc,CAAC,MAAM,QAAQ;AAAA,EAC7B,UAAU,CAAC,KAAK,OAAO,UAAU;AAC/B,UAAM,CAAC,IAAI,MAAM,IAAI;AACrB,UAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,gBAAgB,IAAI;AAC5D,WAAO;AAAA,MACL,IAAI,MAAM,OAAO,KAAK,QAAQA,UAAS,MAAM,YAAY,GAAG,eAAe;AAAA,MAC3E,QAAQ,MAAM,qBAAqB,KAAK,IAAI,OAAO,OAAOA,UAAS,MAAM,YAAY,eAAe;AAAA,IACtG;AAAA,EACF;AACF;AAGA,SAAS,sBAAsB,GAAG,IAAI,aAAaA,UAAS,MAAM;AAChE,MAAI,MAAM;AACV,MAAI,EAAE,SAAS,GAAG;AAChB,UAAM,QAAQ,GAAG,CAAC,GAAG,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,EAAE,CAAC;AAAA,EACtE;AACA,MAAI,OAAO;AACX,MAAI,KAAK,SAAS,GAAG;AACnB,WAAO,QAAQ,IAAI,CAAC,GAAG,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,IAAI,GAAG,MAAM,EAAE,CAAC;AAAA,EAC5E;AACA,SAAO,IAAI,SAAS,GAAG,MAAM,iEAAiE,IAAI,QAAQ;AAC1G,SAAO,KAAK,SAAS,GAAG,MAAM,8DAA8D,KAAK,QAAQ;AACzG,SAAO,YAAY,WAAW,GAAG,MAAM,mEAAmE,cAAc;AACxH,SAAO,IAAI,MAAM,OAAO,YAAY,IAAI,MAAM,4CAA4C,IAAI,MAAM,yCAAyC,YAAY,KAAK;AAC9J,SAAO,KAAK,MAAM,OAAO,YAAY,IAAI,MAAM,0CAA0C,KAAK,MAAM,2CAA2C,YAAY,MAAM;AACjK,QAAM,SAAS,EAAE,GAAG,KAAK,IAAI,KAAK;AAClC,QAAM,QAAQ,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY;AAChD,SAAO,OAAO,UAAU,wBAAwB,QAAQ,KAAK;AAC/D;AACA,IAAI,uBAAuB,GAAG,EAAE,sBAAsB,CAAC;AAGvD,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,QAAQ;AAAA,EAC5B,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,WAAW,SAAAA,UAAS,KAAK,KAAK,IAAI;AAC1C,WAAO,kBAAkB,SAAS,GAAG,MAAM,iHAAiH,YAAY;AACxK,UAAM,CAAC,KAAK,OAAO,IAAI;AACvB,WAAO;AAAA,MACL,GAAG,MAAM,oBAAoB,IAAI,OAAO,IAAI,SAASA,UAAS,IAAI;AAAA,MAClE,QAAQ,MAAM,qBAAqB,KAAK,IAAI,QAAQ,OAAOA,UAAS,IAAI;AAAA,IAC1E;AAAA,EACF;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC,CAAC,GAAG,EAAE,EAAE;AAAA,EAC1D;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,KAAK,KAAK,GAAG,SAAS,CAAC,GAAG,EAAE,EAAE;AAAA,EACtD;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,WAAO;AAAA,MACL,GAAG,MAAM;AACP,cAAM,cAAc,mBAAmB,CAAC,IAAI,GAAG,EAAE,IAAI;AACrD,YAAI,MAAM,OAAO,IAAI,MAAM,WAAW,CAAC,QAAQ;AAC/C,YAAI,eAAe,MAAM;AACvB,gBAAM,UAAU,KAAK,WAAW;AAAA,QAClC;AACA,eAAO;AAAA,MACT;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,kCAAkC;AAAA,EACpC,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,QAAQ;AAAA,EAC5B,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,WAAW,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC3D,UAAM,aAAa,aAAa,OAAO,CAAC,GAAG,CAAC,IAAI;AAChD,WAAO,kBAAkB,UAAU,GAAG,MAAM,mHAAmH,aAAa;AAC5K,UAAM,CAAC,GAAG,MAAM,IAAI;AACpB,WAAO,EAAE,SAAS,GAAG,MAAM,kFAAkF,EAAE,OAAO;AACtH,WAAO,OAAO,SAAS,GAAG,MAAM,mFAAmF,OAAO,OAAO;AACjI,WAAO,EAAE,MAAM,OAAO,OAAO,MAAM,IAAI,MAAM,mEAAmE,EAAE,MAAM,qDAAqD,OAAO,MAAM,KAAK;AAC/L,WAAO,+BAA+BA,UAAS,UAAU,GAAG,MAAM,6FAA6FA,2BAA0B,cAAc;AACvM,8BAA0B,mBAAmB,MAAM,eAAe;AAClE,WAAO;AAAA,MACL,GAAG,MAAM,mCAAmC,EAAE,OAAO,IAAI,QAAQA,UAAS,MAAM,YAAY,eAAe;AAAA,MAC3G,QAAQ,MAAM,oCAAoC,GAAG,IAAI,OAAO,OAAOA,UAAS,MAAM,YAAY,eAAe;AAAA,IACnH;AAAA,EACF;AACF;AAGA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,QAAQ;AAAA,EAC5B,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,GAAG,MAAM,IAAI;AACpB,UAAM,cAAc,EAAE,GAAG,QAAQ,GAAG;AACpC,UAAM,eAAe,EAAE,GAAG,QAAQ,GAAG;AACrC,WAAO;AAAA,MACL,GAAG,MAAM,OAAO,UAAU,yBAAyB,aAAa,KAAK;AAAA,MACrE,QAAQ,MAAM,OAAO,UAAU,0BAA0B,cAAc,KAAK;AAAA,IAC9E;AAAA,EACF;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,SAAS,EAAE,IAAI,EAAE;AACvB,WAAO,EAAE,GAAG,MAAM,OAAO,UAAU,SAAS,MAAM,EAAE;AAAA,EACtD;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,IAAI,IAAI,IAAI,IAAI,OAAO,CAAC,CAAC,CAAC,GAAG,IAAI,KAAK,KAAK,KAAK,EAAE,CAAC;AACzD,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,CAAC,EAAE;AAAA,EAC/B;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,CAAC,EAAE;AAAA,EAC/B;AACF;AAGA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,cAAc,CAAC,OAAO;AAAA,EACtB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,MAAM,IAAI;AACjB,WAAO,EAAE,OAAO,MAAM,QAAQ,IAAI,OAAO,KAAK,EAAE;AAAA,EAClD;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,CAAC,CAAC,EAAE;AAAA,EACpC;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,2BAA2B,EAAE,OAAO,EAAE,KAAK;AAC5D,UAAM,OAAO,MAAM;AACjB,YAAM,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC;AACtC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,eAAO,QAAQ,KAAK,KAAK,UAAU,GAAG,EAAE,KAAK;AAAA,MAC/C;AACA,aAAO;AAAA,IACT;AACA,UAAM,OAAO,MAAM;AACjB,UAAI,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC;AACpC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,QAAQ,KAAK,KAAK,UAAU,GAAG,EAAE,KAAK;AAAA,MAC9C;AACA,YAAM,MAAM,OAAO,CAAC;AACpB,aAAO,IAAI,IAAI,KAAK,KAAK,KAAK,SAAS,CAAC,CAAC;AAAA,IAC3C;AACA,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,QAAQ,YAAY,OAAO;AAAA,EAC/C,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,gBAAgB,IAAI;AAC5B,UAAM,CAAC,GAAG,OAAO,UAAUS,OAAM,IAAI;AACrC,UAAM,aAAaA,WAAU,OAAO,OAAO,CAAC,IAAIA;AAChD,UAAM,gBAAgB,iBAAiB,MAAM,OAAO,EAAE,KAAK;AAC3D,UAAM,YAAY,CAAC;AACnB,QAAI,MAAM,SAAS,GAAG;AACpB,eAAS,KAAK,GAAG,KAAK,EAAE,MAAM,SAAS,GAAG,EAAE,IAAI;AAC9C,kBAAU,KAAK,EAAE,MAAM,GAAG;AAAA,MAC5B;AACA,gBAAU,KAAK,CAAC;AAAA,IAClB;AACA,UAAM,aAAa,IAAI,GAAG,KAAK;AAC/B,UAAM,oBAAoB,IAAI,IAAI,UAAU;AAC5C,UAAM,sBAAsB,MAAM,KAAK,UAAU,OAAO,eAAe,CAAC,CAAC;AACzE,UAAM,iBAAiB,IAAI,IAAI,IAAI,qBAAqB,mBAAmB,GAAG,mBAAmB,GAAG,OAAO,IAAI,CAAC;AAChH,UAAM,OAAO,MAAM;AACjB,UAAI,MAAM,SAAS,GAAG;AACpB,eAAO,QAAQ,IAAI,IAAI,IAAI,KAAK,QAAQ,qBAAqB,CAAC,GAAG,GAAG,GAAG,MAAM,MAAM,EAAE,CAAC,GAAG,SAAS,CAAC,GAAG,UAAU,GAAG,EAAE,KAAK;AAAA,MAC5H,OAAO;AACL,eAAO,QAAQ,IAAI,IAAI,IAAI,mBAAmB,GAAG,UAAU,GAAG,EAAE,KAAK;AAAA,MACvE;AAAA,IACF;AACA,UAAM,UAAU,MAAM;AACpB,UAAI,UAAU,IAAI,IAAI,qBAAqB,OAAO,EAAE,CAAC,GAAG,iBAAiB;AACzE,UAAI,MAAM,SAAS,GAAG;AACpB,kBAAU,KAAK,SAAS,aAAa;AAAA,MACvC;AACA,aAAO,QAAQ,SAAS,MAAM,KAAK;AAAA,IACrC;AACA,UAAM,cAAc,MAAM;AACxB,UAAI,cAAc,IAAI,IAAI,gBAAgB,UAAU,GAAG,iBAAiB;AACxE,UAAI,MAAM,SAAS,GAAG;AACpB,sBAAc,KAAK,aAAa,aAAa;AAAA,MAC/C;AACA,aAAO,QAAQ,aAAa,MAAM,KAAK;AAAA,IACzC;AACA,UAAM,WAAW,MAAM;AACrB,YAAM,wBAAwB,IAAI,YAAY,mBAAmB;AACjE,UAAI,WAAW,IAAI,IAAI,qBAAqB;AAC5C,UAAI,MAAM,SAAS,GAAG;AACpB,mBAAW,KAAK,UAAU,aAAa;AAAA,MACzC;AACA,aAAO,QAAQ,UAAU,MAAM,KAAK;AAAA,IACtC;AACA,UAAM,YAAY,MAAM;AACtB,UAAI,YAAY;AAChB,UAAI,MAAM,SAAS,GAAG;AACpB,oBAAY,KAAK,WAAW,aAAa;AAAA,MAC3C;AACA,aAAO,QAAQ,WAAW,MAAM,KAAK;AAAA,IACvC;AACA,WAAO;AAAA,MACL,GAAG;AAAA,MACH,MAAM;AAAA,MACN,UAAU;AAAA,MACV,OAAO;AAAA,MACP,QAAQ;AAAA,IACV;AAAA,EACF;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,SAAS;AAAA,EAC7B,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,GAAG,OAAO,IAAI;AACrB,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AACjD,UAAM,OAAO,MAAM;AACjB,YAAM,cAAc,EAAE;AACtB,YAAM,cAAc,QAAQ;AAC5B,YAAM,aAAa,YAAY,MAAM,GAAG,UAAU;AAClD,YAAM,YAAY,WAAW;AAC7B,YAAM,aAAa,YAAY,MAAM,MAAM,YAAY,MAAM,EAAE,MAAM,CAAC;AACtE,YAAM,YAAY,WAAW;AAC7B,YAAM,mBAAmB,WAAW,GAAG,SAAS;AAChD,YAAM,mBAAmB,WAAW,YAAY,GAAG,YAAY,IAAI,SAAS;AAC5E,YAAM,cAAc,YAAY,CAAC,YAAY,CAAC,WAAW,GAAG,UAAU,CAAC;AACvE,YAAM,SAAS,QAAQ,IAAI,WAAW;AACtC,YAAM,kBAAkB,QAAQ,SAAS,CAAC,WAAW,CAAC;AACtD,YAAM,gBAAgB,YAAY,CAAC,CAAC,SAAS,GAAG,kBAAkB,gBAAgB,CAAC;AACnF,YAAM,kBAAkB,UAAU,QAAQ,aAAa;AACvD,UAAI,aAAa,mBAAmB,iBAAiB,iBAAiB,EAAE,MAAM,WAAW;AACzF,YAAM,sBAAsB,uBAAuB,aAAa;AAChE,mBAAa,UAAU,YAAY,mBAAmB;AACtD,aAAO;AAAA,IACT;AACA,WAAO,EAAE,GAAG,MAAM,SAAS,MAAM,QAAQ;AAAA,EAC3C;AACF;AACA,SAAS,WAAW,OAAO,MAAM;AAC/B,QAAM,SAAS,CAAC;AAChB,WAAS,KAAK,OAAO,KAAK,MAAM,EAAE,IAAI;AACpC,WAAO,KAAK,EAAE;AAAA,EAChB;AACA,SAAO;AACT;AACA,SAAS,YAAY,QAAQ;AAC3B,QAAM,SAAS,CAAC;AAChB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,aAAS,IAAI,GAAG,IAAI,OAAO,IAAI,QAAQ,EAAE,GAAG;AAC1C,aAAO,KAAK,OAAO,IAAI,EAAE;AAAA,IAC3B;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,yBAAyB;AAAA,EAC3B,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,WAAO,EAAE,GAAG,MAAM,UAAU,CAAC,GAAG,GAAG,MAAM,UAAU,CAAC,EAAE;AAAA,EACxD;AACF;AAGA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,KAAK,IAAI,SAAS,EAAE;AAAA,EACxC;AACF;AAGA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,OAAAC,OAAM,IAAI;AAClB,UAAMjB,QAAO,QAAQ,GAAG,CAAC;AACzB,WAAO,EAAE,GAAG,MAAM,MAAMA,OAAM,IAAI,IAAI,IAAIiB,MAAK,CAAC,EAAE;AAAA,EACpD;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAK,GAAG,CAAC,CAAC,EAAE;AAAA,EACxC;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC,EAAE;AAAA,EAChD;AACF;AAGA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,cAAc,CAAC;AAAA,EACf,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,KAAK,IAAI;AAChB,UAAM,EAAE,KAAK,IAAI;AACjB,WAAO;AAAA,MACL,QAAQ,MAAM;AACZ,cAAM,WAAW;AACjB,cAAM,WAAW,IAAI,KAAK;AAC1B,eAAO,IAAI,IAAI,IAAI,KAAK,IAAI,MAAM,QAAQ,GAAG,QAAQ,CAAC;AAAA,MACxD;AAAA,IACF;AAAA,EACF;AACF;AAGA,SAAS,oCAAoC,GAAG,GAAG,IAAI,cAAc,GAAG,OAAO,GAAGA,SAAQ,GAAG,OAAO,KAAK;AACvG,QAAM,SAAS,EAAE,GAAG,GAAG,GAAG;AAC1B,QAAM,QAAQ,EAAE,aAAa,MAAM,OAAAA,QAAO,KAAK;AAC/C,SAAO,OAAO,UAAU,SAAS,QAAQ,KAAK;AAChD;AACA,IAAI,qCAAqC,GAAG,EAAE,oCAAoC,CAAC;AAGnF,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,EAAE,aAAa,MAAM,OAAAA,QAAO,KAAK,IAAI;AAC3C,WAAO;AAAA,MACL,GAAG,MAAM,mCAAmC,GAAG,GAAG,IAAI,aAAa,MAAMA,QAAO,IAAI;AAAA,IACtF;AAAA,EACF;AACF;AAGA,SAAS,iBAAiB,IAAI,GAAG,OAAO,UAAU;AAChD,MAAI,EAAE,OAAO,MAAM,MAAM;AACvB,QAAI,QAAQ,GAAG,qBAAqB,EAAE,OAAO,QAAQ,CAAC;AAAA,EACxD;AACA,MAAI,GAAG,OAAO,MAAM,MAAM;AACxB,SAAK,QAAQ,IAAI,qBAAqB,GAAG,OAAO,QAAQ,CAAC;AAAA,EAC3D;AACA,SAAO;AAAA,IACL,GAAG,MAAM;AACP,YAAM,KAAK,IAAI,IAAI,KAAK,MAAM,OAAO,CAAC,GAAG,GAAG,KAAK,CAAC;AAClD,aAAO;AAAA,IACT;AAAA,EACF;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,WAAW;AACjB,UAAM,EAAE,iBAAiB,IAAI;AAC7B,UAAM,IAAI,MAAM;AAChB,UAAM,IAAI,MAAM;AAChB,UAAM,WAAW,eAAe,kBAAkB,EAAE,KAAK;AACzD,UAAM,UAAU,iBAAiB,IAAI,GAAG,GAAG,QAAQ;AACnD,WAAO;AAAA,MACL,GAAG,MAAM;AACP,eAAO,QAAQ,KAAK;AAAA,MACtB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,OAAO,MAAM,IAAI,IAAI,KAAK,aAAa,GAAG,CAAC,GAAG,SAAS,CAAC;AAC9D,UAAM,OAAO,MAAM,IAAI,IAAI,KAAK,KAAK,GAAG,CAAC,GAAG,SAAS,CAAC;AACtD,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,SAAS,eAAe,IAAI,QAAQ,QAAQ,YAAYV,UAAS,MAAM,iBAAiB;AACtF,QAAM,MAAM,gBAAgB,IAAI,MAAM,eAAe;AACrD,QAAM,SAAS,gBAAgB,QAAQ,SAAS,eAAe;AAC/D,QAAM,UAAU,gBAAgB,QAAQ,UAAU,eAAe;AACjE,MAAI,OAAO;AACX,MAAI,UAAU;AACd,MAAI,WAAW;AACf,MAAI,eAAe;AACnB,MAAI,OAAO,SAAS,GAAG;AACrB,mBAAe;AACf,WAAO,QAAQ,KAAK,CAAC,GAAG,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAC/E,cAAU,QAAQ,QAAQ;AAAA,MACxB;AAAA,MACA,OAAO,MAAM;AAAA,MACb,OAAO,MAAM;AAAA,MACb,OAAO,MAAM;AAAA,MACb,OAAO,MAAM;AAAA,IACf,CAAC;AACD,eAAW,QAAQ,SAAS;AAAA,MAC1B;AAAA,MACA,QAAQ,MAAM;AAAA,MACd,QAAQ,MAAM;AAAA,MACd,QAAQ,MAAM;AAAA,MACd,QAAQ,MAAM;AAAA,IAChB,CAAC;AAAA,EACH;AACA,SAAO,KAAK,SAAS,GAAG,MAAM,0DAA0D,KAAK,OAAO;AACpG,SAAO,QAAQ,SAAS,GAAG,MAAM,6DAA6D,QAAQ,OAAO;AAC7G,SAAO,SAAS,SAAS,GAAG,MAAM,8DAA8D,SAAS,OAAO;AAChH,4BAA0B,iBAAiB,MAAM,eAAe;AAChE,QAAM,SAAS,EAAE,IAAI,MAAM,OAAO,SAAS,QAAQ,SAAS;AAC5D,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB;AAChE,QAAM,MAAM,OAAO,UAAU,eAAe,QAAQ,KAAK;AACzD,MAAI,cAAc;AAChB,WAAO,QAAQ,KAAK,CAAC,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,IAAI,IAAI,MAAM,EAAE,CAAC;AAAA,EAC9E;AACA,SAAO;AACT;AACA,IAAI,gBAAgB,GAAG,EAAE,eAAe,CAAC;AAGzC,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,WAAO;AAAA,MACL,GAAG,MAAM,cAAc,IAAI,GAAG,GAAG,YAAYA,UAAS,MAAM,eAAe;AAAA,IAC7E;AAAA,EACF;AACF;AAGA,SAAS,aAAa,IAAI,QAAQ,QAAQ,YAAYA,UAAS,MAAM,iBAAiB;AACpF,QAAM,MAAM,gBAAgB,IAAI,MAAM,aAAa;AACnD,QAAM,SAAS,gBAAgB,QAAQ,SAAS,aAAa;AAC7D,QAAM,UAAU,gBAAgB,QAAQ,UAAU,aAAa;AAC/D,SAAO,OAAO,SAAS,IAAI,MAAM,MAAM,kBAAkB,OAAO,oCAAoC,IAAI,OAAO;AAC/G,SAAO,IAAI,SAAS,GAAG,MAAM,wDAAwD,IAAI,OAAO;AAChG,SAAO,OAAO,SAAS,GAAG,MAAM,2DAA2D,OAAO,OAAO;AACzG,4BAA0B,eAAe,MAAM,eAAe;AAC9D,QAAM,SAAS,EAAE,IAAI,KAAK,OAAO,QAAQ,QAAQ,QAAQ;AACzD,QAAM,QAAQ,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB;AAChE,SAAO,OAAO,UAAU,aAAa,QAAQ,KAAK;AACpD;AACA,IAAI,cAAc,GAAG,EAAE,aAAa,CAAC;AAGrC,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,KAAK,IAAI;AAC3C,WAAO;AAAA,MACL,GAAG,MAAM,YAAY,IAAI,GAAG,GAAG,YAAYA,UAAS,IAAI;AAAA,IAC1D;AAAA,EACF;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,OAAO,eAAe,MAAM,EAAE,KAAK;AACzC,UAAM,SAAS,0BAA0B,EAAE,OAAO,IAAI;AACtD,UAAM,cAAc,OAAO;AAC3B,UAAM,aAAa,cAAc,WAAW;AAC5C,UAAM,OAAO,MAAM;AACjB,YAAM,kBAAkB,EAAE,MAAM,MAAM;AACtC,WAAK,QAAQ,CAAC,UAAU;AACtB,wBAAgB,SAAS;AAAA,MAC3B,CAAC;AACD,YAAM,aAAa,QAAQ,IAAI,eAAe;AAC9C,YAAM,MAAM,IAAI,IAAI,YAAY,MAAM,EAAE,OAAO,SAAS,CAAC,GAAG,UAAU;AACtE,aAAO;AAAA,IACT;AACA,WAAO,EAAE,GAAG,KAAK;AAAA,EACnB;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,WAAW;AACjB,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,eAAe,MAAM,EAAE,KAAK;AAC7C,UAAM,UAAU,iBAAiB,IAAI,GAAG,GAAG,QAAQ;AACnD,WAAO;AAAA,MACL,GAAG,MAAM;AACP,eAAO,QAAQ,KAAK;AAAA,MACtB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,OAAO,MAAM,IAAI,IAAI,KAAK,UAAU,GAAG,CAAC,GAAG,SAAS,CAAC;AAC3D,UAAM,OAAO,MAAM,IAAI,IAAI,KAAK,QAAQ,GAAG,CAAC,GAAG,SAAS,CAAC;AACzD,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,IAAI,MAAM;AAChB,UAAM,EAAE,SAAS,IAAI;AACrB,UAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE;AACxC,WAAO,EAAE,GAAG,MAAM,MAAM,IAAI,OAAO,EAAE,KAAK,EAAE;AAAA,EAC9C;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,2BAA2B,EAAE,OAAO,EAAE,KAAK;AAC5D,UAAM,OAAO,MAAM;AACjB,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,eAAO,QAAQ,KAAK,IAAI,UAAU,GAAG,EAAE,KAAK;AAAA,MAC9C;AACA,aAAO;AAAA,IACT;AACA,UAAM,OAAO,MAAM;AACjB,YAAM,MAAM,IAAI,IAAI,IAAI,MAAM,IAAI,GAAG,CAAC,CAAC,CAAC,CAAC;AACzC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,eAAO,QAAQ,KAAK,KAAK,UAAU,GAAG,EAAE,KAAK;AAAA,MAC/C;AACA,aAAO;AAAA,IACT;AACA,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,2BAA2B,EAAE,OAAO,EAAE,KAAK;AAC5D,UAAM,OAAO,MAAM;AACjB,YAAM,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC;AACtC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,eAAO,QAAQ,KAAK,KAAK,UAAU,GAAG,EAAE,KAAK;AAAA,MAC/C;AACA,aAAO;AAAA,IACT;AACA,UAAM,OAAO,MAAM;AACjB,YAAM,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC;AACtC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,eAAO,QAAQ,KAAK,KAAK,UAAU,GAAG,EAAE,KAAK;AAAA,MAC/C;AACA,aAAO;AAAA,IACT;AACA,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,IAAI,EAAE,EAAE;AAAA,EAC5B;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,SAAS;AAAA,EACxB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,UAAU,MAAM;AACtB,WAAO,EAAE,SAAS,MAAM,MAAM,QAAQ,OAAO,SAAS,EAAE;AAAA,EAC1D;AACF;AAGA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,eAAe;AAAA,EACf,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,aAAa,QAAQ,IAAI,IAAI;AACnC,WAAO,WAAW,IAAI,CAAC,OAAO,MAAM,EAAE;AAAA,EACxC;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,IAAI,MAAM;AAChB,UAAM,EAAE,SAAS,IAAI;AACrB,UAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE;AACxC,WAAO,EAAE,GAAG,MAAM,MAAM,IAAI,OAAO,EAAE,KAAK,EAAE;AAAA,EAC9C;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,GAAG,CAAC,IAAI;AAClB,UAAM,OAAO;AACb,UAAM,OAAO;AACb,UAAM,WAAW,2BAA2B,KAAK,OAAO,KAAK,KAAK;AAClE,UAAM,UAAU,MAAM;AACpB,YAAM,WAAW,KAAK,MAAM,SAAS;AACrC,UAAI,MAAM,IAAI,IAAI,IAAI,UAAU,IAAI,MAAM,IAAI,UAAU,OAAO,CAAC,CAAC,CAAC,CAAC,CAAC;AACpE,YAAM,aAAa,iBAAiB,KAAK,OAAO,QAAQ;AACxD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,KAAK,KAAK,KAAK;AAAA,IAChC;AACA,UAAM,SAAS,MAAM;AACnB,YAAM,YAAY,QAAQ,MAAM,CAAC;AACjC,YAAM,UAAU,MAAM,WAAWjB,MAAK,IAAI,GAAG,UAAU,IAAI,CAAC;AAC5D,UAAI,MAAM,IAAI,IAAI,IAAI,GAAG,OAAO,CAAC;AACjC,YAAM,aAAa,iBAAiB,KAAK,OAAO,QAAQ;AACxD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,KAAK,KAAK,KAAK;AAAA,IAChC;AACA,WAAO,EAAE,GAAG,SAAS,GAAG,OAAO;AAAA,EACjC;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,OAAO;AAAA,EAC3B,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG2B,MAAK,IAAI;AACnB,UAAMjB,QAAO,QAAQ,GAAG,CAAC;AACzB,WAAO;AAAA,MACL,GAAG,MAAM,MAAMA,OAAM,IAAI,IAAI,IAAIiB,MAAK,CAAC;AAAA,MACvC,OAAO,MAAM;AACX,YAAI,MAAM,MAAMjB,OAAM,UAAU,EAAE,GAAG,IAAI,IAAI,CAAC,CAAC;AAC/C,cAAM,aAAa,iBAAiBiB,OAAM,OAAO,GAAG,KAAK;AACzD,YAAI,WAAW,SAAS,GAAG;AACzB,gBAAM,KAAK,KAAK,UAAU;AAAA,QAC5B;AACA,eAAO,QAAQ,KAAKA,OAAM,KAAK;AAAA,MACjC;AAAA,IACF;AAAA,EACF;AACF;AAGA,SAAS,YAAY,GAAG,IAAI,MAAM;AAChC,QAAM,iBAAiB,EAAE,MAAM,MAAM;AACrC,iBAAe,QAAQ;AACvB,QAAM,aAAa,QAAQ,IAAI,cAAc;AAC7C,QAAM,WAAW,QAAQ,GAAG,MAAM,MAAM,KAAK;AAC7C,QAAM,cAAc,QAAQ,GAAG,MAAM,MAAM,IAAI;AAC/C,QAAM,KAAK,IAAI,UAAU,WAAW;AACpC,SAAO,IAAI,YAAY,EAAE;AAC3B;AACA,SAAS,aAAa,GAAG,IAAI,MAAM;AACjC,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,gBAAgB,QAAQ,KAAK;AACnC,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,YAAY;AAChB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,UAAU,GAAG,YAAY;AAAA,EACvC;AACA,QAAM,WAAW,UAAU,MAAM,MAAM;AACvC,QAAM,eAAe,SAAS,OAAO,QAAQ,KAAK,QAAQ,KAAK,MAAM;AACrE,QAAM,eAAe,aAAa,OAAO,CAAC,IAAI,MAAM,KAAK,GAAG,CAAC;AAC7D,WAAS,KAAK,YAAY;AAC1B,QAAM,oBAAoB,UAAU,QAAQ,QAAQ;AACpD,MAAI,WAAW,YAAY,mBAAmB,IAAI,aAAa;AAC/D,aAAW,SAAS,QAAQ,UAAU,KAAK;AAC3C,MAAI,gBAAgB,MAAM;AACxB,UAAM,kBAAkB,qBAAqB,uBAAuB,YAAY;AAChF,eAAW,UAAU,UAAU,eAAe;AAAA,EAChD;AACA,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,KAAK,IAAI;AACjB,QAAI,UAAU,CAAC;AACf,QAAI,SAAS,UAAU,SAAS,MAAM;AACpC,gBAAU,EAAE,MAAM,IAAI,CAAC,GAAG,OAAO,EAAE;AAAA,IACrC,WAAW,OAAO,SAAS,UAAU;AACnC,gBAAU,CAAC,IAAI;AAAA,IACjB,OAAO;AACL,gBAAU;AAAA,IACZ;AACA,WAAO,EAAE,GAAG,MAAM,aAAa,GAAG,IAAI,OAAO,EAAE;AAAA,EACjD;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,2BAA2B,EAAE,OAAO,EAAE,KAAK;AAC5D,UAAM,OAAO,MAAM;AACjB,YAAM,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC;AACtC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,eAAO,QAAQ,KAAK,KAAK,UAAU,GAAG,EAAE,KAAK;AAAA,MAC/C;AACA,aAAO;AAAA,IACT;AACA,UAAM,OAAO,MAAM;AACjB,UAAI,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC;AACpC,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,QAAQ,KAAK,KAAK,UAAU,GAAG,EAAE,KAAK;AAAA,MAC9C;AACA,YAAM,MAAM,OAAO,CAAC;AACpB,aAAO,IAAI,IAAI,KAAK,KAAK,KAAK,SAAS,CAAC,CAAC;AAAA,IAC3C;AACA,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,OAAO,CAAC,CAAC,CAAC,EAAE;AAAA,EAC5C;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,UAAMjB,QAAO,IAAI,UAAU,GAAG,CAAC,GAAG,KAAK,CAAC,CAAC;AACzC,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAKA,OAAM,SAAS,CAAC,EAAE;AAAA,EACnD;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAK,KAAK,CAAC,GAAG,SAAS,CAAC,EAAE;AAAA,EACtD;AACF;AAGA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,QAAQ,IAAI,EAAE,KAAK,EAAE;AAAA,EACzC;AACF;AAGA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,cAAc,CAAC,QAAQ;AAAA,EACvB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,MAAM,IAAI;AACjB,UAAM,SAAS,EAAE,IAAI,OAAO;AAC5B,UAAM,YAAY,MAAM,OAAO,UAAU,oBAAoB,QAAQ,KAAK;AAC1E,WAAO,EAAE,QAAQ,UAAU;AAAA,EAC7B;AACF;AAGA,IAAI,kCAAkC;AAAA,EACpC,YAAY;AAAA,EACZ,cAAc,CAAC,QAAQ;AAAA,EACvB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,MAAM,IAAI;AACjB,UAAM,SAAS,EAAE,IAAI,OAAO;AAC5B,UAAM,YAAY,MAAM,OAAO,UAAU,2BAA2B,QAAQ,KAAK;AACjF,WAAO,EAAE,QAAQ,UAAU;AAAA,EAC7B;AACF;AAGA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,OAAO,eAAe,MAAM,GAAG,KAAK;AAC1C,WAAO,EAAE,GAAG,MAAM,QAAQ,IAAI,IAAI,EAAE;AAAA,EACtC;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,IAAI,IAAI,GAAG,GAAG,GAAG,CAAC,CAAC,CAAC,EAAE;AAAA,EACtD;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,WAAW;AAAA,EAC1B,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,SAAS,IAAI;AACpB,WAAO;AAAA,MACL,WAAW,MAAM,KAAK,UAAU,SAAS,GAAG,SAAS;AAAA,MACrD,GAAG,MAAM,IAAI,IAAI,KAAK,WAAW,GAAG,KAAK,CAAC;AAAA,MAC1C,GAAG,MAAM,IAAI,IAAI,KAAK,WAAW,SAAS,GAAG,GAAG,KAAK,CAAC;AAAA,IACxD;AAAA,EACF;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO;AAAA,MACL,GAAG,MAAM;AACP,cAAMA,QAAO,QAAQ,GAAG,OAAO,CAAC,CAAC;AACjC,cAAM,cAAc,OAAO,eAAe;AAC1C,cAAMgB,UAAS,OAAO,UAAU;AAChC,cAAM,qBAAqB,IAAI,IAAIA,OAAM;AACzC,cAAM,mBAAmB,IAAI,IAAI,IAAI,WAAW,GAAG,IAAI,KAAK,GAAG,SAAS,CAAC,CAAC;AAC1E,eAAO,MAAMhB,OAAM,oBAAoB,gBAAgB;AAAA,MACzD;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,GAAG,IAAI,OAAO,CAAC,GAAG,CAAC,CAAC,CAAC,EAAE;AAAA,EACvD;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,KAAK,GAAG,SAAS,CAAC,GAAG,EAAE,EAAE;AAAA,EACrD;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,KAAK,KAAK,GAAG,SAAS,CAAC,GAAG,EAAE,EAAE;AAAA,EACtD;AACF;AAGA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,OAAO,MAAAL,MAAK,IAAI;AACxB,UAAM,aAAa,EAAE;AACrB,UAAM,CAAC,QAAQ,KAAK,IAAI,iBAAiB,GAAG,OAAOA,KAAI;AACvD,UAAM,WAAW,CAAC;AAClB,aAAS,KAAK,GAAG,KAAK,GAAG,MAAM,MAAM;AACnC,eAAS,KAAK,CAAC,OAAO,KAAK,WAAW,MAAM,OAAO,MAAM,MAAM,GAAG,CAAC;AAAA,IACrE;AACA,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,QAAQ,EAAE;AAAA,EACtC;AACF;AAGA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,IAAI,IAAI;AAChB,UAAM,WAAW;AACjB,UAAM,WAAW,IAAI,IAAI,CAAC;AAC1B,WAAO;AAAA,MACL,QAAQ,MAAM,IAAI,UAAU,IAAI,KAAK,UAAU,CAAC,GAAG,GAAG,QAAQ,GAAG,CAAC,CAAC;AAAA,IACrE;AAAA,EACF;AACF;AAGA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,QAAQ,CAAC,CAAC,EAAE;AAAA,EACxC;AACF;AAGA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,YAAY,SAAS,IAAI;AACjC,WAAO,EAAE,GAAG,MAAM,eAAe,IAAI,YAAY,QAAQ,EAAE;AAAA,EAC7D;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,EAAE,KAAK,IAAI;AACjB,WAAO,EAAE,GAAG,MAAM,OAAO,IAAI,IAAI,EAAE;AAAA,EACrC;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,KAAK,KAAK,GAAG,SAAS,CAAC,GAAG,CAAC,CAAC,EAAE;AAAA,EAC9D;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,IAAI,KAAK,GAAG,SAAS,GAAG,CAAC,CAAC,EAAE;AAAA,EACxD;AACF;AAGA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,MAAM,OAAO,CAAC;AACpB,UAAM,OAAO,MAAM,IAAI,IAAI,IAAI,KAAK,IAAI,GAAG,CAAC,CAAC,CAAC;AAC9C,UAAM,OAAO,MAAM,IAAI,IAAI,IAAI,KAAK,IAAI,GAAG,CAAC,CAAC,CAAC;AAC9C,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,KAAK,GAAG;AAAA,EACvB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,GAAG,CAAC,IAAI;AACf,UAAM,WAAW,2BAA2B,EAAE,OAAO,EAAE,KAAK;AAC5D,UAAM,OAAO,MAAM;AACjB,UAAI,MAAM;AACV,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,KAAK,EAAE,KAAK;AAAA,IAC7B;AACA,UAAM,OAAO,MAAM;AACjB,UAAI,MAAM;AACV,YAAM,aAAa,iBAAiB,EAAE,OAAO,QAAQ;AACrD,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,KAAK,KAAK,UAAU;AAAA,MAC5B;AACA,aAAO,QAAQ,IAAI,GAAG,GAAG,EAAE,KAAK;AAAA,IAClC;AACA,WAAO,EAAE,GAAG,MAAM,GAAG,KAAK;AAAA,EAC5B;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,kBAAkB,EAAE,MAAM,MAAM;AACtC,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,OAAO,eAAe,MAAM,EAAE,KAAK;AACzC,SAAK,QAAQ,CAAC,UAAU;AACtB,sBAAgB,SAAS;AAAA,IAC3B,CAAC;AACD,UAAM,aAAa,QAAQ,IAAI,eAAe;AAC9C,UAAM,OAAO,IAAI,YAAY,MAAM,EAAE,OAAO,SAAS,CAAC;AACtD,WAAO,EAAE,GAAG,MAAM,KAAK;AAAA,EACzB;AACF;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,OAAO,IAAI,CAAC,CAAC,CAAC,EAAE;AAAA,EAC5C;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,eAAe,CAAC,IAAI;AAAA,EACpB,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,CAAC,IAAI;AACZ,WAAO,EAAE,GAAG,MAAM,IAAI,IAAI,OAAO,CAAC,GAAG,OAAO,CAAC,CAAC,GAAG,EAAE,EAAE;AAAA,EACvD;AACF;AAGA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,cAAc,CAAC,GAAG;AAAA,EAClB,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,CAAC,CAAC,IAAI;AACZ,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,OAAO,MAAM;AACjB,UAAI,QAAQ,UAAU,CAAC;AACvB,UAAI,EAAE,SAAS,GAAG;AAChB,iBAAS,KAAK,GAAG,KAAK,KAAK,IAAI,EAAE,IAAI;AACnC,kBAAQ,KAAK,OAAO,MAAM,IAAI,CAAC,KAAK,EAAE,MAAM,EAAE,GAAG,CAAC,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,QAChE;AAAA,MACF,WAAW,EAAE,SAAS,GAAG;AACvB,iBAAS,KAAK,GAAG,KAAK,KAAK,IAAI,EAAE,IAAI;AACnC,mBAAS,IAAI,GAAG,IAAI,KAAK,IAAI,EAAE,GAAG;AAChC,oBAAQ,KAAK,OAAO,MAAM,IAAI,CAAC,KAAK,EAAE,MAAM,IAAI,IAAI,EAAE,MAAM,EAAE,GAAG;AAAA,cAC/D,EAAE,MAAM;AAAA,cACR,EAAE,MAAM;AAAA,YACV,CAAC,CAAC;AAAA,UACJ;AAAA,QACF;AAAA,MACF,WAAW,EAAE,SAAS,GAAG;AACvB,iBAAS,KAAK,GAAG,KAAK,KAAK,IAAI,EAAE,IAAI;AACnC,mBAAS,IAAI,GAAG,IAAI,KAAK,IAAI,EAAE,GAAG;AAChC,qBAAS,IAAI,GAAG,IAAI,KAAK,IAAI,EAAE,GAAG;AAChC,sBAAQ,KAAK,OAAO,MAAM,IAAI,CAAC,KAAK,EAAE,MAAM,IAAI,IAAI,EAAE,MAAM,IAAI,IAAI,EAAE,MAAM,EAAE,GAAG,CAAC,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,YACxH;AAAA,UACF;AAAA,QACF;AAAA,MACF,WAAW,EAAE,SAAS,GAAG;AACvB,iBAAS,KAAK,GAAG,KAAK,KAAK,IAAI,EAAE,IAAI;AACnC,mBAAS,IAAI,GAAG,IAAI,KAAK,IAAI,EAAE,GAAG;AAChC,qBAAS,IAAI,GAAG,IAAI,KAAK,IAAI,EAAE,GAAG;AAChC,uBAAS,KAAK,GAAG,KAAK,KAAK,IAAI,EAAE,IAAI;AACnC,wBAAQ,KAAK,OAAO,MAAM,IAAI;AAAA,kBAC5B,KAAK,EAAE,MAAM;AAAA,kBACb,IAAI,EAAE,MAAM;AAAA,kBACZ,IAAI,EAAE,MAAM;AAAA,kBACZ,KAAK,EAAE,MAAM;AAAA,gBACf,GAAG,CAAC,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,cACtD;AAAA,YACF;AAAA,UACF;AAAA,QACF;AAAA,MACF,OAAO;AACL,cAAM,IAAI,MAAM,2DAA2D,EAAE,mBAAmB;AAAA,MAClG;AACA,aAAO;AAAA,IACT;AACA,WAAO,EAAE,GAAG,KAAK;AAAA,EACnB;AACF;AAGA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,iBAAiB;AACvB,UAAM,EAAE,KAAK,IAAI;AACjB,UAAM,WAAW,uBAAuB,IAAI;AAC5C,WAAO,EAAE,GAAG,MAAM,UAAU,IAAI,QAAQ,EAAE;AAAA,EAC5C;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,UAAU,CAAC,IAAI,OAAO,UAAU;AAC9B,UAAM,cAAc;AACpB,UAAM,EAAE,KAAK,IAAI;AACjB,WAAO,EAAE,OAAO,MAAM,MAAM,IAAI,IAAI,EAAE;AAAA,EACxC;AACF;AAGA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,cAAc,CAAC,YAAY;AAAA,EAC3B,UAAU,CAAC,IAAI,UAAU;AACvB,UAAM,CAAC,UAAU,IAAI;AACrB,UAAM,OAAO,MAAM;AACjB,aAAO,oBAAoB,IAAI,UAAU;AAAA,IAC3C;AACA,WAAO,EAAE,GAAG,KAAK;AAAA,EACnB;AACF;AACA,SAAS,oBAAoB,GAAG,SAAS;AACvC,QAAM,qBAAqB,QAAQ,SAAS,UAAU,OAAO,CAAC;AAC9D,QAAM,WAAW,OAAO,GAAG,kBAAkB;AAC7C,MAAI,aAAa,aAAa,SAAS,OAAO,GAAG,OAAO,CAAC;AACzD,QAAM,WAAW,SAAS,OAAO,WAAW;AAC5C,WAAS,KAAK,GAAG,KAAK,UAAU,EAAE,IAAI;AACpC,iBAAa,WAAW,YAAY,KAAK,CAAC;AAAA,EAC5C;AACA,eAAa,WAAW,YAAY,MAAM,SAAS,OAAO,MAAM,CAAC;AACjE,QAAM,YAAY,UAAU,QAAQ;AACpC,SAAO,MAAM,YAAY,UAAU,SAAS;AAC9C;AAGA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,UAAU,CAAC,OAAO;AAChB,WAAO,EAAE,GAAG,MAAM,UAAU,EAAE,EAAE;AAAA,EAClC;AACF;AAGA,IAAI,cAAc;AAAA,EAChB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,WAAW,kBAAkB,aAAa;AACxC,mBAAiB,cAAc;AACjC;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,GAAG;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,CAAC;AACrB;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,MAAM,UAAU;AAC9D,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,MAAM,QAAQ;AACjC;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,MAAM,UAAU;AAC9D,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,MAAM,QAAQ;AACjC;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,MAAM;AACvD,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,IAAI;AAC1B;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,MAAM;AACvD,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,IAAI;AAC1B;AAGA,qBAAqB,EAAE,UAAU,WAAW,WAAW;AACrD,OAAK,gBAAgB;AACrB,SAAO,KAAK,SAAS,GAAG,MAAM,qCAAqC;AACnE,SAAO,QAAQ,MAAM,CAAC,CAAC;AACzB;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,OAAO;AACxD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,KAAK;AACzB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC,KAAK,IAAI,CAAC;AAClC;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,MAAM,SAAS;AAC9D,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC,MAAM,OAAO,CAAC;AACtC;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,MAAM,SAAS,OAAO;AACrE,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC,MAAM,SAAS,KAAK,CAAC;AAC7C;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,MAAM,SAAS,OAAO,QAAQ;AAC7E,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC,MAAM,SAAS,OAAO,MAAM,CAAC;AACrD;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,MAAM,SAAS,OAAO,QAAQ,QAAQ;AACrF,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC,MAAM,SAAS,OAAO,QAAQ,MAAM,CAAC;AAC7D;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,SAAS,GAAG;AACnD,OAAK,gBAAgB;AACrB,SAAO,MAAM,MAAM,CAAC;AACtB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,YAAYY,UAAS,MAAM,iBAAiB;AAC9F,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,YAAYA,UAAS,MAAM,eAAe;AACjE;AAGA,qBAAqB,EAAE,UAAU,iBAAiB,SAAS,YAAY,OAAO;AAC5E,OAAK,gBAAgB;AACrB,SAAO,eAAe,MAAM,YAAY,KAAK;AAC/C;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAAS,OAAO,UAAU,QAAQS,SAAQ,iBAAiB;AACtG,OAAK,gBAAgB;AACrB,SAAO,UAAU,MAAM,OAAO,UAAU,QAAQA,SAAQ,eAAe;AACzE;AAGA,qBAAqB,EAAE,UAAU,cAAc,SAAS,OAAO;AAC7D,OAAK,gBAAgB;AACrB,SAAO,YAAY,MAAM,KAAK;AAChC;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,OAAO;AACtD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,KAAK;AACzB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,cAAc,SAAS,MAAM,MAAM;AAClE,OAAK,gBAAgB;AACrB,SAAO,YAAY,MAAM,MAAM,IAAI;AACrC;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,GAAG,MAAM;AAC1D,OAAK,gBAAgB;AACrB,MAAI,aAAa,QAAQ;AACvB,QAAI,CAAC,CAAC;AAAA,EACR;AACA,SAAO,OAAO,CAAC,MAAM,GAAG,CAAC,GAAG,IAAI;AAClC;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,QAAQ,QAAQ,MAAM,YAAY,UAAU,iBAAiB;AAC9G,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,QAAQ,QAAQ,MAAM,YAAY,UAAU,eAAe;AACjF;AAGA,qBAAqB,EAAE,UAAU,kBAAkB,SAAS,QAAQ,aAAaT,UAAS,MAAM,iBAAiB;AAC/G,OAAK,gBAAgB;AACrB,SAAO,gBAAgB,MAAM,QAAQ,aAAaA,UAAS,MAAM,eAAe;AAClF;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,QAAQA,UAAS,MAAM,YAAY,WAAW,iBAAiB;AAChH,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,QAAQA,UAAS,MAAM,YAAY,WAAW,eAAe;AACnF;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,MAAM,WAAW,UAAU;AAC7E,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,MAAM,WAAW,QAAQ;AAChD;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,MAAM,WAAW,UAAU;AAC5E,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,MAAM,WAAW,QAAQ;AAC/C;AAGA,qBAAqB,EAAE,UAAU,eAAe,SAAS,WAAW,YAAY;AAC9E,OAAK,gBAAgB;AACrB,SAAO,aAAa,MAAM,WAAW,UAAU;AACjD;AAGA,qBAAqB,EAAE,UAAU,kBAAkB,SAAS,QAAQA,UAAS,MAAM,YAAY,WAAW,iBAAiB;AACzH,OAAK,gBAAgB;AACrB,SAAO,gBAAgB,MAAM,QAAQA,UAAS,MAAM,YAAY,WAAW,eAAe;AAC5F;AAGA,qBAAqB,EAAE,UAAU,aAAa,SAAS,QAAQA,UAAS,MAAM,WAAW,YAAY;AACnG,OAAK,gBAAgB;AACrB,SAAO,WAAW,MAAM,QAAQA,UAAS,MAAM,WAAW,UAAU;AACtE;AAGA,qBAAqB,EAAE,UAAU,WAAW,SAAS,GAAG;AACtD,OAAK,gBAAgB;AACrB,SAAO,SAAS,MAAM,CAAC;AACzB;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,GAAG;AACjD,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,CAAC;AACpB;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,GAAG;AACjD,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,CAAC;AACpB;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,SAAS,GAAG;AACnD,OAAK,gBAAgB;AACrB,SAAO,MAAM,MAAM,CAAC;AACtB;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,gBAAgB,SAAS,MAAM,UAAU;AACxE,OAAK,gBAAgB;AACrB,SAAO,cAAc,MAAM,MAAM,QAAQ;AAC3C;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,aAAa,SAAS,MAAM;AAC3D,OAAK,gBAAgB;AACrB,SAAO,WAAW,MAAM,IAAI;AAC9B;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,UAAU,WAAW;AACpD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC,KAAK,IAAI,CAAC;AAClC;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,WAAW,SAAS,GAAG;AACtD,OAAK,gBAAgB;AACrB,SAAO,SAAS,MAAM,CAAC;AACzB;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,SAAS,MAAM;AAChE,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,SAAS,IAAI;AACnC;AAGA,qBAAqB,EAAE,UAAU,eAAe,SAAS,GAAG;AAC1D,OAAK,gBAAgB;AACrB,SAAO,aAAa,MAAM,CAAC;AAC7B;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,GAAG;AACrD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC;AACxB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,WAAW,WAAW;AACrD,OAAK,gBAAgB;AACrB,SAAO,UAAU,IAAI;AACvB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,OAAO,IAAI;AACpB;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAASU,QAAO;AAC3D,OAAK,gBAAgB;AACrB,SAAO,UAAU,MAAMA,MAAK;AAC9B;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAAS,GAAG;AACvD,OAAK,gBAAgB;AACrB,SAAO,UAAU,MAAM,CAAC;AAC1B;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,GAAG;AAClD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,CAAC;AACrB;AAGA,qBAAqB,EAAE,UAAU,6BAA6B,SAAS,aAAa,MAAMA,QAAO,MAAM;AACrG,OAAK,gBAAgB;AACrB,SAAO,2BAA2B,MAAM,aAAa,MAAMA,QAAO,IAAI;AACxE;AAGA,qBAAqB,EAAE,UAAU,aAAa,WAAW;AACvD,OAAK,gBAAgB;AACrB,SAAO,WAAW,IAAI;AACxB;AAGA,qBAAqB,EAAE,UAAU,aAAa,SAAS,MAAM;AAC3D,OAAK,gBAAgB;AACrB,SAAO,WAAW,MAAM,IAAI;AAC9B;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAAS,MAAM,UAAU;AACpE,OAAK,gBAAgB;AACrB,SAAO,UAAU,MAAM,MAAM,QAAQ;AACvC;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO3B,MAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,aAAa,SAAS,GAAG;AACxD,OAAK,gBAAgB;AACrB,SAAO,WAAW,MAAM,CAAC;AAC3B;AAGA,qBAAqB,EAAE,UAAU,aAAa,WAAW;AACvD,OAAK,gBAAgB;AACrB,SAAO,WAAW,IAAI;AACxB;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAAS,GAAG;AACvD,OAAK,gBAAgB;AACrB,SAAO,UAAU,MAAM,CAAC;AAC1B;AAGA,qBAAqB,EAAE,UAAU,aAAa,SAAS,GAAG;AACxD,OAAK,gBAAgB;AACrB,SAAO,WAAW,MAAM,CAAC;AAC3B;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,GAAG,YAAY,YAAY;AAC5E,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,GAAG,YAAY,UAAU;AAC/C;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,YAAYiB,UAAS,MAAM,iBAAiB;AAC9F,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,YAAYA,UAAS,MAAM,eAAe;AACjE;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,MAAM,UAAU;AAC9D,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,MAAM,QAAQ;AACjC;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,GAAG;AACrD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC;AACxB;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,MAAM,UAAU;AAC/D,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,MAAM,QAAQ;AAClC;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,MAAM,UAAU;AAC9D,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,MAAM,QAAQ;AACjC;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,GAAG;AACrD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,CAAC;AACxB;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAAS,UAAU,MAAM;AACpE,OAAK,gBAAgB;AACrB,SAAO,UAAU,MAAM,UAAU,IAAI;AACvC;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,GAAG;AACjD,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,CAAC;AACpB;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,GAAG;AACjD,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,CAAC;AACpB;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,KAAK,MAAM,UAAU;AACpE,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,KAAK,MAAM,QAAQ;AACvC;AAGA,qBAAqB,EAAE,UAAU,WAAW,SAAS,GAAG;AACtD,OAAK,gBAAgB;AACrB,SAAO,SAAS,MAAM,CAAC;AACzB;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,OAAO,UAAU,GAAG,WAAW,GAAG;AACnF,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,OAAO,SAAS,QAAQ;AAC9C;AAGA,qBAAqB,EAAE,UAAU,WAAW,WAAW;AACrD,OAAK,gBAAgB;AACrB,SAAO,SAAS,IAAI;AACtB;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,UAAU,eAAe;AACvE,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,UAAU,aAAa;AAC1C;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,aAAa,aAAae,UAAS,cAAcf,UAAS,iBAAiB;AAC1H,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,aAAa,aAAae,UAAS,cAAcf,UAAS,eAAe;AAC7F;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,MAAM;AACpD,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,IAAI;AACvB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,SAASU,QAAO;AACvD,OAAK,gBAAgB;AACrB,SAAO,MAAM,MAAMA,MAAK;AAC1B;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,MAAM,UAAU;AAC/D,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,MAAM,QAAQ;AAClC;AAGA,qBAAqB,EAAE,UAAU,aAAa,WAAW;AACvD,OAAK,gBAAgB;AACrB,SAAO,WAAW,IAAI;AACxB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAAS,GAAG;AACvD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,EAAE,KAAK;AAC9B;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,OAAO;AACzD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,KAAK;AAC5B;AAGA,qBAAqB,EAAE,UAAU,iBAAiB,SAAS,YAAY,cAAc,kBAAkB;AACrG,OAAK,gBAAgB;AACrB,SAAO,eAAe,MAAM,YAAY,cAAc,gBAAgB;AACxE;AAGA,qBAAqB,EAAE,UAAU,wBAAwB,SAAS,YAAY,cAAc,kBAAkB;AAC5G,OAAK,gBAAgB;AACrB,SAAO,sBAAsB,MAAM,YAAY,cAAc,gBAAgB;AAC/E;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,MAAM;AACxD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,IAAI;AAC3B;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,OAAO,IAAI;AACpB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,kBAAkB,SAAS,iBAAiB,iBAAiBV,UAAS,MAAM,UAAU,YAAY;AACjI,OAAK,gBAAgB;AACrB,SAAO,gBAAgB,MAAM,iBAAiB,iBAAiBA,UAAS,MAAM,UAAU,UAAU;AACpG;AAGA,qBAAqB,EAAE,UAAU,UAAU,WAAW;AACpD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,IAAI;AACrB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,QAAQ,SAAS,OAAOZ,OAAM;AAC7D,OAAK,gBAAgB;AACrB,SAAO,MAAM,MAAM,OAAOA,KAAI;AAChC;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,KAAK;AACvD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,GAAG;AAC1B;AAGA,qBAAqB,EAAE,UAAU,WAAW,WAAW;AACrD,OAAK,gBAAgB;AACrB,SAAO,SAAS,IAAI;AACtB;AAGA,qBAAqB,EAAE,UAAU,iBAAiB,SAAS,YAAY,UAAU;AAC/E,OAAK,gBAAgB;AACrB,SAAO,eAAe,MAAM,YAAY,QAAQ;AAClD;AAGA,qBAAqB,EAAE,UAAU,QAAQ,SAAS,iBAAiB,MAAM;AACvE,OAAK,gBAAgB;AACrB,SAAO,MAAM,MAAM,iBAAiB,IAAI;AAC1C;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,KAAK,IAAI;AAClB;AAGA,qBAAqB,EAAE,UAAU,SAAS,WAAW;AACnD,OAAK,gBAAgB;AACrB,SAAO,OAAO,IAAI;AACpB;AAGA,qBAAqB,EAAE,UAAU,oBAAoB,SAAS,GAAG;AAC/D,OAAK,gBAAgB;AACrB,SAAO,kBAAkB,MAAM,CAAC;AAClC;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,MAAM;AACxD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,IAAI;AAC3B;AAGA,qBAAqB,EAAE,UAAU,QAAQ,SAAS,GAAG,MAAM;AACzD,OAAK,gBAAgB;AACrB,QAAM,qBAAqB,aAAa,SAAS,CAAC,MAAM,CAAC,IAAI,CAAC,MAAM,GAAG,CAAC;AACxE,SAAO,MAAM,oBAAoB,IAAI;AACvC;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAASsB,QAAO;AACtD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAMA,MAAK;AACzB;AAGA,qBAAqB,EAAE,UAAU,eAAe,SAAS,OAAO,KAAKV,UAAS,WAAW,SAAS,cAAc,aAAa,gBAAgB;AAC3I,OAAK,gBAAgB;AACrB,SAAO,aAAa,MAAM,OAAO,KAAKA,UAAS,WAAW,SAAS,cAAc,aAAa,cAAc;AAC9G;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,GAAG;AACjD,OAAK,gBAAgB;AACrB,SAAO,IAAI,MAAM,CAAC;AACpB;AAGA,qBAAqB,EAAE,UAAU,MAAM,SAAS,MAAM,UAAU;AAC9D,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,MAAM,QAAQ;AAClC;AAGA,qBAAqB,EAAE,UAAU,MAAM,WAAW;AAChD,OAAK,gBAAgB;AACrB,SAAO,IAAI,IAAI;AACjB;AAGA,qBAAqB,EAAE,UAAU,OAAO,WAAW;AACjD,OAAK,gBAAgB;AACrB,SAAO,MAAM,IAAI;AACnB;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,MAAM;AACrD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,IAAI;AACxB;AAGA,qBAAqB,EAAE,UAAU,SAAS,WAAW;AACnD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,MAAM;AAC1B;AAGA,qBAAqB,EAAE,UAAU,UAAU,WAAW;AACpD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,SAAS;AAC7B;AAGA,qBAAqB,EAAE,UAAU,QAAQ,WAAW;AAClD,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,OAAO;AAC3B;AAGA,qBAAqB,EAAE,UAAU,OAAO,SAAS,GAAG,QAAQ;AAC1D,OAAK,gBAAgB;AACrB,SAAO,KAAK,MAAM,GAAG,MAAM;AAC7B;AAGA,qBAAqB,EAAE,UAAU,YAAY,SAAS,MAAM;AAC1D,OAAK,gBAAgB;AACrB,SAAO,UAAU,MAAM,IAAI;AAC7B;AAGA,qBAAqB,EAAE,UAAU,SAAS,SAAS,MAAM;AACvD,OAAK,gBAAgB;AACrB,SAAO,OAAO,MAAM,IAAI;AAC1B;AAGA,qBAAqB,EAAE,UAAU,qBAAqB,SAAS,YAAY,aAAa;AACtF,OAAK,gBAAgB;AACrB,SAAO,mBAAmB,MAAM,YAAY,WAAW;AACzD;AAGA,qBAAqB,EAAE,UAAU,UAAU,SAAS,MAAM;AACxD,OAAK,gBAAgB;AACrB,SAAO,QAAQ,MAAM,IAAI;AAC3B;AAGA,qBAAqB,EAAE,UAAU,QAAQ,SAAS,WAAW,GAAG;AAC9D,OAAK,gBAAgB;AACrB,SAAO,MAAM,WAAW,MAAM,CAAC;AACjC;AAGA,qBAAqB,EAAE,UAAU,YAAY,WAAW;AACtD,OAAK,gBAAgB;AACrB,SAAO,UAAU,IAAI;AACvB;AAGA,IAAI,iBAAiB,cAAc,MAAM;AAAA,EACvC,YAAY,SAAS;AACnB,UAAM,OAAO;AACb,WAAO,eAAe,MAAM,eAAe,SAAS;AAAA,EACtD;AACF;AACA,IAAI,eAAe,cAAc,MAAM;AAAA,EACrC,YAAY,SAAS;AACnB,UAAM,OAAO;AACb,WAAO,eAAe,MAAM,aAAa,SAAS;AAAA,EACpD;AACF;AACA,IAAI,aAAa,cAAc,MAAM;AAAA,EACnC,YAAY,SAAS;AACnB,UAAM,OAAO;AACb,WAAO,eAAe,MAAM,WAAW,SAAS;AAAA,EAClD;AACF;AACA,IAAI,sBAAsB,cAAc,MAAM;AAAA,EAC5C,YAAY,SAAS;AACnB,UAAM,OAAO;AACb,WAAO,eAAe,MAAM,oBAAoB,SAAS;AAAA,EAC3D;AACF;AACA,IAAI,iBAAiB,cAAc,MAAM;AAAA,EACvC,YAAY,SAAS;AACnB,UAAM,OAAO;AACb,WAAO,eAAe,MAAM,eAAe,SAAS;AAAA,EACtD;AACF;AAGA,IAAI,WAAW,MAAM;AAAA,EACnB,YAAY,YAAY;AACtB,SAAK,aAAa,cAAc;AAChC,SAAK,QAAwB,oBAAI,IAAI;AAAA,EACvC;AAAA,EACA,IAAI,KAAK;AACP,QAAI;AACJ,QAAI,KAAK,MAAM,IAAI,GAAG,GAAG;AACvB,cAAQ,KAAK,MAAM,IAAI,GAAG;AAC1B,WAAK,MAAM,OAAO,GAAG;AACrB,WAAK,MAAM,IAAI,KAAK,KAAK;AAAA,IAC3B;AACA,WAAO;AAAA,EACT;AAAA,EACA,IAAI,KAAK,OAAO;AACd,QAAI,KAAK,MAAM,IAAI,GAAG,GAAG;AACvB,WAAK,MAAM,OAAO,GAAG;AAAA,IACvB,WAAW,KAAK,MAAM,QAAQ,KAAK,YAAY;AAC7C,YAAM,cAAc,KAAK,MAAM,KAAK,EAAE,KAAK,EAAE;AAC7C,WAAK,MAAM,OAAO,WAAW;AAAA,IAC/B;AACA,SAAK,MAAM,IAAI,KAAK,KAAK;AAAA,EAC3B;AAAA,EACA,gBAAgB;AACd,WAAO,KAAK;AAAA,EACd;AAAA,EACA,cAAc,YAAY;AACxB,QAAI,aAAa,GAAG;AAClB,YAAM,IAAI,MAAM,4DAA4D,aAAa;AAAA,IAC3F;AACA,QAAI,KAAK,aAAa,YAAY;AAChC,eAAS,KAAK,GAAG,KAAK,KAAK,aAAa,YAAY,MAAM;AACxD,cAAM,cAAc,KAAK,MAAM,KAAK,EAAE,KAAK,EAAE;AAC7C,aAAK,MAAM,OAAO,WAAW;AAAA,MAC/B;AAAA,IACF;AACA,SAAK,aAAa;AAAA,EACpB;AACF;AAGA,SAAS,aAAa,OAAO,WAAW;AACtC,MAAI,MAAM,QAAQ,KAAK,GAAG;AACxB,QAAI,WAAW,CAAC;AAChB,aAAS,KAAK,GAAG,KAAK,WAAW,MAAM;AACrC,iBAAW,SAAS,OAAO,KAAK;AAAA,IAClC;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAM,WAAW,IAAI,MAAM,SAAS;AACpC,aAAS,KAAK,KAAK;AACnB,WAAO;AAAA,EACT;AACF;AACA,SAAS,QAAQ,KAAK,SAAS;AAC7B,MAAI,CAAC,KAAK;AACR,UAAM,IAAI,eAAe,OAAO;AAAA,EAClC;AACF;AACA,SAAS,MAAM,QAAQ,UAAU;AAC/B,MAAI,UAAU;AACd,aAAW,QAAQ,QAAQ;AACzB,QAAI,SAAS,UAAU;AACrB;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,IAAI;AAC5B,MAAI,GAAG,WAAW,GAAG;AACnB,WAAO,GAAG;AAAA,EACZ;AACA,SAAO;AACT;AACA,SAAS,OAAO,GAAG;AACjB,MAAI,MAAM,QAAQ,CAAC,GAAG;AACpB,WAAO;AAAA,EACT;AACA,SAAO,CAAC,CAAC;AACX;AACA,SAAS,YAAY,MAAM;AACzB,QAAM,eAAe,KAAK,QAAQ,wBAAwB,OAAO;AACjE,QAAM,WAAW,aAAa,QAAQ,mBAAmB,OAAO,EAAE,YAAY;AAC9E,MAAI,SAAS,OAAO,KAAK;AACvB,WAAO;AAAA,EACT;AACA,SAAO,YAAY;AACrB;AACA,SAAS,YAAY,YAAY;AAC/B,MAAI,WAAW,UAAU,GAAG;AAC1B,WAAO;AAAA,EACT;AACA,MAAI,WAAW,QAAQ,GAAG,MAAM,IAAI;AAClC,WAAO;AAAA,EACT;AACA,SAAO,WAAW,QAAQ,eAAe,CAAC,GAAG,OAAO,GAAG,YAAY,CAAC;AACtE;AACA,IAAI,yBAAyB,CAAC;AAC9B,SAAS,qBAAqB,UAAU;AACtC,MAAI,aAAa,QAAQ,aAAa,QAAQ;AAC5C,WAAO;AAAA,EACT;AACA,QAAM,OAAO,CAAC;AACd,OAAK,eAAe,SAAS,aAAa;AAC1C,OAAK,YAAY,SAAS,UAAU;AACpC,SAAO;AACT;AACA,SAAS,8BAA8BE,SAAQ;AAC7C,MAAIA,WAAU,QAAQ,OAAOA,YAAW,UAAU;AAChD;AAAA,EACF,WAAW,MAAM,QAAQA,OAAM,GAAG;AAChC,IAAAA,QAAO,QAAQ,CAAC,eAAe,8BAA8B,UAAU,CAAC;AAAA,EAC1E,OAAO;AACL,UAAM,SAAS,OAAO,KAAKA,OAAM;AACjC,eAAW,SAAS,QAAQ;AAC1B,YAAM,QAAQA,QAAO;AACrB,UAAI,SAAS,QAAQ,OAAO,UAAU,UAAU;AAC9C,YAAI,CAAC,MAAM,QAAQ,KAAK,KAAK,MAAM,YAAY,aAAa,OAAO,MAAM,aAAa,UAAU;AAC9F,UAAAA,QAAO,SAAS,MAAM;AAAA,QACxB,OAAO;AACL,wCAA8B,KAAK;AAAA,QACrC;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,uBAAuB,YAAY,gBAAgB,CAAC,GAAG,gBAAgB,CAAC,GAAG,sBAAsB,UAAU,iBAAiB,OAAO;AAC1I,MAAI,OAAO,eAAe,UAAU;AAClC,UAAM,eAAe;AACrB,QAAI;AACJ,QAAI,gBAAgB,eAAe;AACjC,WAAK,cAAc;AAAA,IACrB,WAAW,gBAAgB,wBAAwB;AACjD,WAAK,uBAAuB;AAAA,IAC9B,OAAO;AACL,WAAK,cAAc;AACnB,UAAI,MAAM,MAAM;AACd,cAAM,IAAI,WAAW,WAAW,wBAAwB;AAAA,SACvD;AAAA,gBACO,qHAAqH;AAAA,MAC/H;AAAA,IACF;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAMA,UAAS;AACf,QAAIA,QAAO,gBAAgB,QAAQA,QAAO,aAAa,MAAM;AAC3D,YAAM,IAAI,WAAW,GAAG,gDAAgD,KAAK,UAAUA,OAAM;AAAA,mCAChE;AAAA,IAC/B;AACA,UAAM,YAAYA,QAAO;AACzB,QAAI,KAAK;AACT,QAAI,aAAa,eAAe;AAC9B,OAAC,KAAK,UAAU,IAAI,cAAc;AAAA,IACpC,WAAW,aAAa,wBAAwB;AAC9C,OAAC,KAAK,UAAU,IAAI,uBAAuB;AAAA,IAC7C,WAAW,aAAa,eAAe;AACrC,OAAC,KAAK,UAAU,IAAI,cAAc;AAAA,IACpC;AACA,QAAI,OAAO,MAAM;AACf,YAAM,IAAI,WAAW,WAAW,wBAAwB;AAAA,SACrD;AAAA,gBACO,qHAAqH;AAAA,IACjI;AACA,QAAI,cAAc,MAAM;AACtB,YAAM,wBAAwB,CAAC;AAC/B,iBAAW,OAAO,OAAO,KAAK,sBAAsB,GAAG;AACrD,8BAAsB,OAAO,uBAAuB;AAAA,MACtD;AACA,iBAAW,OAAO,OAAO,KAAK,aAAa,GAAG;AAC5C,8BAAsB,OAAO,cAAc;AAAA,MAC7C;AACA,YAAM,eAAeA,QAAO;AAC5B,mBAAa,mBAAmB;AAChC,YAAM,sBAAsB,OAAO,OAAO,CAAC,GAAG,sBAAsB;AACpE,iBAAW,OAAO,OAAO,KAAK,aAAa,GAAG;AAC5C,+BAAuB,OAAO,cAAc;AAAA,MAC9C;AACA,oCAA8BA,QAAO,SAAS;AAC9C,YAAM,YAAY,WAAW,KAAKA,QAAO,WAAW,eAAe,cAAc;AACjF,+BAAyB,OAAO,OAAO,CAAC,GAAG,mBAAmB;AAC9D,aAAO;AAAA,IACT,OAAO;AACL,YAAM,sBAAsB,OAAO,OAAO,CAAC,GAAG,sBAAsB;AACpE,iBAAW,OAAO,OAAO,KAAK,aAAa,GAAG;AAC5C,+BAAuB,OAAO,cAAc;AAAA,MAC9C;AACA,YAAM,YAAY,IAAI,IAAIA,QAAO,SAAS;AAC1C,+BAAyB,OAAO,OAAO,CAAC,GAAG,mBAAmB;AAC9D,aAAO;AAAA,IACT;AAAA,EACF;AACF;AACA,SAAS,cAAc,GAAG,GAAG;AAC3B,SAAO,IAAI,IAAI,KAAK,IAAI,IAAI,IAAI;AAClC;AACA,SAAS,qBAAqB,GAAG,GAAG;AAClC,SAAO,KAAK,cAAc,GAAG,CAAC;AAChC;AACA,SAAS,QAAQ,IAAI;AACnB,MAAI,MAAM,MAAM;AACd,WAAO;AAAA,EACT;AACA,QAAM,MAAM,CAAC;AACb,aAAW,KAAK,IAAI;AAClB,QAAI,IAAI,QAAQ,CAAC,MAAM,IAAI;AACzB,UAAI,KAAK,CAAC;AAAA,IACZ;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,cAAc,KAAK;AAC1B,MAAI,OAAO,MAAM;AACf,UAAM,IAAI,WAAW,yBAAyB,KAAK,UAAU,GAAG,GAAG;AAAA,EACrE;AACA,aAAW,OAAO,KAAK;AACrB,QAAI,IAAI,eAAe,GAAG,GAAG;AAC3B,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,0BAA0B,QAAQ,OAAO,OAAO;AACvD,MAAI,SAAS,MAAM;AACjB;AAAA,EACF;AACA,MAAI,OAAO,QAAQ,KAAK,IAAI,GAAG;AAC7B,UAAM,IAAI,WAAW,GAAG,wBAAwB,4BAA4B,2BAA2B;AAAA,EACzG;AACF;AACA,SAAS,wBAAwB,GAAG,cAAc,YAAY,GAAG,YAAY,UAAU;AACrF,UAAQ,aAAa,CAAC;AACtB,UAAQ,aAAa,SAAS;AAC9B,SAAO,MAAM,QAAQ,CAAC,KAAK,EAAE,UAAU,aAAa,EAAE,UAAU,aAAa,EAAE,MAAM,CAAC,OAAO,OAAO,OAAO,YAAY;AACzH;AACA,SAAS,sBAAsB,OAAO,MAAM;AAC1C,MAAI,MAAM,QAAQ,KAAK,GAAG;AACxB,iBAAa,OAAO,MAAM,SAAS,GAAG,MAAM,GAAG,sCAAsC;AACrF,UAAM,QAAQ,CAAC,GAAG,OAAO,sBAAsB,GAAG,WAAW,KAAK,QAAQ,MAAM,CAAC;AAAA,EACnF,OAAO;AACL,iBAAa,OAAO,OAAO,UAAU,KAAK,KAAK,QAAQ,GAAG,MAAM,YAAY,0CAA0C,uBAAuB,KAAK,IAAI;AAAA,EACxJ;AACF;AACA,SAAS,uBAAuB,OAAO;AACrC,MAAI,UAAU,MAAM;AAClB,WAAO;AAAA,EACT,WAAW,MAAM,QAAQ,KAAK,GAAG;AAC/B,WAAO,MAAM,MAAM,IAAI,CAAC,MAAM,uBAAuB,CAAC,CAAC,EAAE,KAAK,GAAG,IAAI;AAAA,EACvE,WAAW,OAAO,UAAU,UAAU;AACpC,WAAO,IAAI;AAAA,EACb,OAAO;AACL,WAAO,GAAG;AAAA,EACZ;AACF;AACA,SAAS,SAAS,GAAG,QAAQ,SAAS;AACpC,MAAIc,aAAW,WAAW,OAAO,QAAQ,IAAI,aAAa,IAAI;AAC9D,MAAI;AACJ,QAAM,KAAK,IAAI,SAAS;AACtB,UAAMpB,QAAO,WAAW,OAAO,QAAQ,IAAI,aAAa,IAAI;AAC5D,QAAIA,QAAOoB,aAAW,QAAQ;AAC5B,aAAO;AAAA,IACT;AACA,IAAAA,aAAWpB;AACX,iBAAa,EAAE,GAAG,IAAI;AACtB,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,2BAA2B,gBAAgB;AAClD,MAAI,mBAAmB,QAAQ;AAC7B,WAAO;AAAA,EACT;AACA,MAAI,mBAAmB,UAAU;AAC/B,WAAO;AAAA,EACT;AACA,MAAI,mBAAmB,OAAO;AAC5B,WAAO;AAAA,EACT;AACA,SAAO;AACT;AAGA,IAAI,sBAAsB;AAC1B,SAAS,wBAAwB;AAC/B,SAAO;AACT;AACA,IAAI,eAAe,CAAC;AACpB,SAAS,OAAO,SAAS,IAAI;AAC3B,MAAI,EAAE,UAAU,eAAe;AAC7B,iBAAa,UAAU;AAAA,EACzB;AACA,eAAa,WAAW;AACxB,SAAO,SAAS,aAAa,QAAQ,SAAS;AAChD;AAGA,IAAI,2BAA2B,CAAC,iBAAiB,cAAc;AAC/D,IAAI,oCAAoC,CAAC,WAAW,UAAU;AAC9D,IAAI,4BAA4B,CAAC,SAAS,QAAQ,QAAQ;AAC1D,IAAI,yBAAyB,CAAC,OAAO,KAAK;AAC1C,IAAI,kCAAkC,CAAC,OAAO,OAAO,UAAU,KAAK;AAGpE,IAAI,UAA0B,oBAAI,IAAI;AACtC,SAAS,gBAAgB,OAAO;AAC9B,4BAA0B,0BAA0B,cAAc,KAAK;AACzE;AACA,SAAS,yBAAyB,OAAO;AACvC,4BAA0B,mCAAmC,uBAAuB,KAAK;AAC3F;AACA,SAAS,iBAAiB,OAAO;AAC/B,4BAA0B,2BAA2B,eAAe,KAAK;AAC3E;AACA,SAAS,cAAc,OAAO;AAC5B,4BAA0B,wBAAwB,YAAY,KAAK;AACrE;AACA,IAAI,kBAAkB,CAAC;AACvB,IAAI,oBAAoB;AACxB,SAAS,UAAU,MAAM,IAAI;AAC3B,kBAAgB,KAAK,IAAI;AACzB,MAAI;AACF,UAAM,MAAM,GAAG;AACf,oBAAgB,IAAI;AACpB,WAAO;AAAA,EACT,SAAS,IAAP;AACA,oBAAgB,IAAI;AACpB,UAAM;AAAA,EACR;AACF;AACA,SAAS,yBAAyB;AAChC,MAAI,gBAAgB,WAAW,GAAG;AAChC,WAAO;AAAA,EACT,OAAO;AACL,WAAO,gBAAgB,KAAK,iBAAiB,IAAI;AAAA,EACnD;AACF;AACA,SAAS,oBAAoB,YAAY;AACvC,MAAI,CAAC,kBAAkB,UAAU,GAAG;AAClC,UAAM,IAAI,MAAM,+BAA+B,aAAa,GAAG;AAAA,EACjE;AACA,SAAO,uBAAuB,IAAI;AACpC;AACA,SAAS,oBAAoB,YAAY;AACvC,MAAI,CAAC,kBAAkB,UAAU,GAAG;AAClC,UAAM,IAAI,MAAM,+BAA+B,aAAa,GAAG;AAAA,EACjE;AACA,MAAI,CAAC,QAAQ,IAAI,UAAU,GAAG;AAC5B,YAAQ,IAAI,YAAY,CAAC;AAAA,EAC3B;AACA,QAAMC,SAAQ,QAAQ,IAAI,UAAU;AACpC,UAAQ,IAAI,YAAY,QAAQ,IAAI,UAAU,IAAI,CAAC;AACnD,MAAIA,SAAQ,GAAG;AACb,UAAM,SAAS,GAAG,cAAcA;AAChC,YAAQ,IAAI,QAAQ,CAAC;AACrB,WAAO;AAAA,EACT,OAAO;AACL,WAAO;AAAA,EACT;AACF;AACA,IAAI,kBAAkB,IAAI,OAAO,iCAAiC;AAClE,SAAS,kBAAkB,MAAM;AAC/B,SAAO,CAAC,CAAC,KAAK,MAAM,eAAe;AACrC;AAGA,SAAS,UAAU,GAAG;AACpB,SAAO,MAAM,SAAS,EAAE,SAAS,GAAG,EAAE;AACxC;AACA,SAAS,UAAU,QAAQ,OAAO,KAAK;AACrC,MAAI,SAAS,MAAM;AACjB,YAAQ;AAAA,EACV;AACA,MAAI,OAAO,MAAM;AACf,UAAM,OAAO;AAAA,EACf;AACA,MAAI,QAAQ;AACZ,WAAS,KAAK,OAAO,KAAK,KAAK,EAAE,IAAI;AACnC,aAAS,OAAO;AAAA,EAClB;AACA,SAAO;AACT;AACA,SAAS,KAAK,QAAQ;AACpB,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,OAAO;AAAA,EAChB;AACA,MAAI,OAAO,OAAO;AAClB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,UAAM,QAAQ,OAAO;AACrB,QAAI,QAAQ,MAAM;AAChB,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,KAAK,QAAQ;AACpB,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,OAAO;AAAA,EAChB;AACA,MAAI,OAAO,OAAO;AAClB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,UAAM,QAAQ,OAAO;AACrB,QAAI,QAAQ,MAAM;AAChB,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,OAAO,OAAO,KAAK;AAC1B,MAAI,MAAM,OAAO;AACf,UAAM,IAAI,WAAW,QAAQ,iBAAiB,sBAAsB;AAAA,EACtE;AACA,QAAM,MAAM,CAAC;AACb,WAAS,KAAK,OAAO,KAAK,KAAK,EAAE,IAAI;AACnC,QAAI,KAAK,EAAE;AAAA,EACb;AACA,SAAO;AACT;AAGA,IAAI;AACJ,SAAS,UAAU;AACjB,MAAI,YAAY,MAAM;AACpB,eAAW,QAAQ,EAAE,QAAQ;AAAA,EAC/B;AACA,SAAO;AACT;AACA,SAAS,kBAAkB;AACzB,SAAO;AACT;AAGA,SAAS,MAAM,GAAG,OAAO;AACvB,SAAO,KAAK,GAAG,KAAK;AACtB;AACA,SAAS,YAAY,GAAG,OAAO,IAAI;AACjC,QAAM,WAAW,EAAE,MAAM,MAAM;AAC/B,MAAI,OAAO,GAAG;AACZ,WAAO,SAAS,SAAS,OAAO;AAAA,EAClC;AACA,WAAS,OAAO,MAAM,GAAG,CAAC;AAC1B,SAAO,QAAQ,GAAG,QAAQ;AAC5B;AACA,SAAS,OAAO,GAAG,IAAI;AACrB,SAAO,KAAK,MAAM;AAChB,QAAI,EAAE,MAAM,WAAW,GAAG;AACxB,YAAM,IAAI,WAAW,yDAAyD,EAAE,MAAM,gBAAgB;AAAA,IACxG;AACA,UAAM,IAAI,YAAY,GAAG,CAAC;AAC1B,WAAO,MAAM,GAAG,CAAC,GAAG,IAAI,CAAC,CAAC;AAAA,EAC5B,CAAC;AACH;AACA,SAAS,SAAS,GAAG;AACnB,QAAM,WAAW,CAAC,UAAU,EAAE,KAAK,CAAC;AACpC,SAAO,QAAQ,GAAG,QAAQ;AAC5B;AACA,SAAS,aAAa,GAAG;AACvB,MAAI,EAAE,QAAQ,GAAG;AACf,UAAM,IAAI,WAAW,wDAAwD,EAAE,OAAO;AAAA,EACxF;AACA,QAAM,WAAW,CAAC,EAAE,MAAM,IAAI,UAAU,EAAE,OAAO,CAAC,CAAC;AACnD,SAAO,QAAQ,GAAG,QAAQ;AAC5B;AACA,SAAS,oBAAoB,QAAQ,OAAOT,OAAM;AAChD,SAAO,KAAK,MAAM;AAChB,YAAQ,OAAO;AAAA,WACR;AACH,eAAO,QAAQ,QAAQ,OAAOA,KAAI;AAAA,WAC/B;AACH,eAAO,QAAQ,QAAQ,CAAC,OAAO,CAAC,GAAG,CAACA,OAAM,OAAO,MAAM,EAAE,CAAC;AAAA,WACvD;AACH,eAAO,QAAQ,QAAQ,CAAC,OAAO,GAAG,CAAC,GAAG,CAACA,OAAM,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE,CAAC;AAAA,WAC3E;AACH,eAAO,QAAQ,QAAQ,CAAC,OAAO,GAAG,GAAG,CAAC,GAAG,CAACA,OAAM,OAAO,MAAM,IAAI,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE,CAAC;AAAA,WAC/F;AACH,eAAO,MAAM,QAAQ,CAAC,OAAO,GAAG,GAAG,GAAG,CAAC,GAAG;AAAA,UACxCA;AAAA,UACA,OAAO,MAAM;AAAA,UACb,OAAO,MAAM;AAAA,UACb,OAAO,MAAM;AAAA,UACb,OAAO,MAAM;AAAA,QACf,CAAC;AAAA,WACE;AACH,eAAO,MAAM,QAAQ,CAAC,OAAO,GAAG,GAAG,GAAG,GAAG,CAAC,GAAG;AAAA,UAC3CA;AAAA,UACA,OAAO,MAAM;AAAA,UACb,OAAO,MAAM;AAAA,UACb,OAAO,MAAM;AAAA,UACb,OAAO,MAAM;AAAA,UACb,OAAO,MAAM;AAAA,QACf,CAAC;AAAA;AAED,cAAM,IAAI,WAAW,8DAA8D,OAAO,MAAM;AAAA;AAAA,EAEtG,CAAC;AACH;AACA,SAAS,mBAAmB,QAAQ,OAAOA,OAAM;AAC/C,SAAO,KAAK,MAAM;AAChB,YAAQ,OAAO;AAAA,WACR;AACH,eAAO,QAAQ,QAAQ,OAAOA,KAAI;AAAA,WAC/B;AACH,eAAO,QAAQ,QAAQ,CAAC,GAAG,KAAK,GAAG,CAAC,OAAO,MAAM,IAAIA,KAAI,CAAC;AAAA,WACvD;AACH,eAAO,QAAQ,QAAQ,CAAC,GAAG,GAAG,KAAK,GAAG,CAAC,OAAO,MAAM,IAAI,OAAO,MAAM,IAAIA,KAAI,CAAC;AAAA,WAC3E;AACH,eAAO,QAAQ,QAAQ,CAAC,GAAG,GAAG,GAAG,KAAK,GAAG,CAAC,OAAO,MAAM,IAAI,OAAO,MAAM,IAAI,OAAO,MAAM,IAAIA,KAAI,CAAC;AAAA;AAElG,cAAM,IAAI,WAAW,6DAA6D,OAAO,MAAM;AAAA;AAAA,EAErG,CAAC;AACH;AACA,SAAS,eAAe,QAAQ,OAAOA,OAAM,MAAM;AACjD,SAAO,KAAK,MAAM;AAChB,YAAQ,OAAO;AAAA,WACR;AACH,eAAO,QAAQ,QAAQ,OAAOA,KAAI;AAAA,WAC/B;AACH,gBAAQ;AAAA,eACD;AACH,mBAAO,oBAAoB,QAAQ,OAAOA,KAAI;AAAA,eAC3C;AACH,mBAAO,mBAAmB,QAAQ,OAAOA,KAAI;AAAA;AAE7C,kBAAM,IAAI,WAAW,iDAAiD,MAAM;AAAA;AAAA,WAE7E;AACH,gBAAQ;AAAA,eACD;AACH,mBAAO,oBAAoB,QAAQ,OAAOA,KAAI;AAAA,eAC3C;AACH,mBAAO,QAAQ,QAAQ,CAAC,GAAG,OAAO,CAAC,GAAG,CAAC,OAAO,MAAM,IAAIA,OAAM,OAAO,MAAM,EAAE,CAAC;AAAA,eAC3E;AACH,mBAAO,mBAAmB,QAAQ,OAAOA,KAAI;AAAA;AAE7C,kBAAM,IAAI,WAAW,iDAAiD,MAAM;AAAA;AAAA,WAE7E;AACH,gBAAQ;AAAA,eACD;AACH,mBAAO,oBAAoB,QAAQ,OAAOA,KAAI;AAAA,eAC3C;AACH,mBAAO,QAAQ,QAAQ,CAAC,GAAG,OAAO,GAAG,CAAC,GAAG,CAAC,OAAO,MAAM,IAAIA,OAAM,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE,CAAC;AAAA,eAC/F;AACH,mBAAO,QAAQ,QAAQ,CAAC,GAAG,GAAG,OAAO,CAAC,GAAG,CAAC,OAAO,MAAM,IAAI,OAAO,MAAM,IAAIA,OAAM,OAAO,MAAM,EAAE,CAAC;AAAA,eAC/F;AACH,mBAAO,mBAAmB,QAAQ,OAAOA,KAAI;AAAA;AAE7C,kBAAM,IAAI,WAAW,iDAAiD,MAAM;AAAA;AAAA;AAGhF,cAAM,IAAI,WAAW,6DAA6D,OAAO,MAAM;AAAA;AAAA,EAErG,CAAC;AACH;AACA,SAAS,YAAY,SAAS,OAAO,IAAI;AACvC,MAAI;AACJ,MAAI,OAAO,GAAG;AACZ,WAAO,QAAQ,GAAG;AAClB,QAAI,SAAS,GAAG;AACd,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AACA,MAAI,SAAS,QAAQ,GAAG,MAAM;AAC5B,WAAO;AAAA,EACT;AACA,SAAO,OAAO,SAAS,IAAI;AAC7B;AACA,SAAS,qBAAqB,GAAG,GAAG;AAClC,UAAQ,EAAE;AAAA,SACH;AACH,aAAO,SAAS,CAAC,GAAG,CAAC,CAAC;AAAA,SACnB;AACH,aAAO,SAAS,CAAC,GAAG,CAAC,GAAG,CAAC;AAAA,SACtB;AACH,aAAO,SAAS,CAAC,GAAG,CAAC,GAAG,CAAC;AAAA,SACtB;AACH,aAAO,SAAS,CAAC,GAAG,CAAC,GAAG,CAAC;AAAA;AAEzB,YAAM,IAAI,WAAW,+DAA+D,EAAE,MAAM;AAAA;AAElG;AACA,SAAS,MAAM,GAAG,IAAI;AACpB,MAAI,CAAC,MAAM,QAAQ,EAAE,GAAG;AACtB,SAAK,CAAC,EAAE;AAAA,EACV;AACA,MAAI,EAAE,SAAS,GAAG,QAAQ;AACxB,UAAM,IAAI,WAAW,0BAA0B,GAAG,+DAA+D,EAAE,OAAO;AAAA,EAC5H;AACA,SAAO,KAAK,GAAG,EAAE;AACnB;AACA,SAAS,cAAc,OAAO,QAAQ,GAAG,SAAS,GAAG,OAAO,MAAM;AAChE,SAAO,aAAa,OAAO,OAAO,QAAQ,OAAO,IAAI;AACvD;AACA,SAAS,KAAK,GAAG,GAAG,aAAa,MAAM;AACrC,MAAI,EAAE,OAAO,KAAK,EAAE,OAAO,GAAG;AAC5B,UAAM,IAAI,oBAAoB,8DAA8D,EAAE,uBAAuB,EAAE,OAAO;AAAA,EAChI;AACA,MAAI,EAAE,QAAQ,GAAG;AACf,UAAM,WAAW,EAAE,MAAM,MAAM,EAAE,EAAE;AACnC,UAAM,iBAAiB,EAAE,MAAM,MAAM,EAAE,EAAE;AACzC,QAAI,aAAa,gBAAgB;AAC/B,YAAM,IAAI,oBAAoB,gGAAgG,EAAE,wBAAwB,EAAE,OAAO;AAAA,IACnK;AAAA,EACF;AACA,MAAI,EAAE,SAAS,KAAK,EAAE,SAAS,GAAG;AAChC,UAAM,aAAa;AACnB,UAAM,aAAa;AACnB,WAAO,kBAAkB,OAAO;AAAA,MAC9B;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA,MAAM,OAAO,YAAY,EAAE,MAAM,MAAM,gBAAgB,CAAC,IAAI;AAAA,MAC5D,YAAY;AAAA,IACd,CAAC;AAAA,EACH,OAAO;AACL,UAAM,aAAa,EAAE,MAAM,MAAM;AACjC,UAAM,WAAW,WAAW,IAAI;AAChC,QAAI,QAAQ,GAAG,CAAC,IAAI,QAAQ,CAAC;AAC7B,UAAM,SAAS,EAAE,MAAM,MAAM;AAC7B,UAAM,WAAW,OAAO,IAAI;AAC5B,UAAM,iBAAiB,OAAO,IAAI;AAClC,UAAM,aAAa,CAAC,GAAG,QAAQ,QAAQ;AACvC,UAAM,OAAO,MAAM,KAAK,EAAE,QAAQ,EAAE,KAAK,GAAG,CAAC,GAAG,OAAO;AACrD,UAAI,OAAO,GAAG;AACZ,eAAO,EAAE,OAAO;AAAA,MAClB,WAAW,MAAM,EAAE,OAAO,GAAG;AAC3B,eAAO,KAAK;AAAA,MACd;AACA,aAAO;AAAA,IACT,CAAC;AACD,QAAI,QAAQ,UAAU,GAAG,IAAI,GAAG,CAAC,gBAAgB,EAAE,CAAC;AACpD,UAAM,cAAc,CAAC,GAAG,YAAY,GAAG,UAAU;AACjD,UAAM,aAAa;AACnB,UAAM,aAAa;AACnB,WAAO,QAAQ,kBAAkB,OAAO;AAAA,MACtC;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA,MAAM,OAAO,YAAY,EAAE,MAAM,MAAM,gBAAgB,CAAC,IAAI;AAAA,MAC5D,YAAY;AAAA,IACd,CAAC,GAAG,WAAW;AAAA,EACjB;AACF;AACA,SAAS,QAAQ,WAAW,SAAS,MAAM;AACzC,SAAO,KAAK,MAAM;AAChB,QAAI,MAAM,QAAQ,OAAO,GAAG;AAC1B,gBAAU,SAAS,SAAS,OAAO;AAAA,IACrC,OAAO;AACL,gBAAU,KAAK,SAAS,OAAO;AAAA,IACjC;AACA,WAAO,OAAO,WAAW,SAAS,IAAI;AAAA,EACxC,CAAC;AACH;AACA,SAAS,QAAQ,GAAG;AAClB,SAAO,IAAI,GAAG,CAAC;AACjB;AACA,SAAS,YAAY,OAAO,MAAM,YAAY;AAC5C,QAAM,YAAY,KAAK;AACvB,MAAI,KAAK,SAAS,KAAK,KAAK,SAAS,OAAO;AAC1C,UAAM,IAAI,WAAW,+BAA+B,KAAK,gCAAgC,OAAO;AAAA,EAClG;AACA,MAAI,UAAU,GAAG;AACf,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,WAAW,GAAG;AAC1B,eAAO,QAAQ,MAAM,CAAC,GAAG,UAAU,IAAI,GAAG,GAAG,CAAC,CAAC;AAAA,MACjD,OAAO;AACL,eAAO,QAAQ,MAAM,CAAC,GAAG,UAAU,IAAI,UAAU,IAAI,UAAU,IAAI,UAAU,EAAE,CAAC;AAAA,MAClF;AAAA,IACF,WAAW,eAAe,gBAAgB;AACxC,UAAI,UAAU,WAAW,GAAG;AAC1B,eAAO,QAAQ,MAAM,CAAC,GAAG,GAAG,GAAG,GAAG,UAAU,EAAE,CAAC;AAAA,MACjD,OAAO;AACL,eAAO,QAAQ,MAAM,CAAC,CAAC,EAAE,OAAO,SAAS,CAAC;AAAA,MAC5C;AAAA,IACF;AAAA,EACF,WAAW,UAAU,GAAG;AACtB,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,WAAW,GAAG;AAC1B,eAAO,QAAQ,MAAM,CAAC,GAAG,UAAU,IAAI,GAAG,CAAC,CAAC;AAAA,MAC9C,OAAO;AACL,eAAO,QAAQ,MAAM,CAAC,GAAG,UAAU,IAAI,UAAU,IAAI,UAAU,EAAE,CAAC;AAAA,MACpE;AAAA,IACF,WAAW,eAAe,gBAAgB;AACxC,UAAI,UAAU,WAAW,GAAG;AAC1B,eAAO,QAAQ,MAAM,CAAC,GAAG,GAAG,GAAG,UAAU,EAAE,CAAC;AAAA,MAC9C,OAAO;AACL,eAAO,QAAQ,MAAM,CAAC,CAAC,EAAE,OAAO,SAAS,CAAC;AAAA,MAC5C;AAAA,IACF;AAAA,EACF,WAAW,UAAU,GAAG;AACtB,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,WAAW,GAAG;AAC1B,eAAO,QAAQ,MAAM,CAAC,GAAG,UAAU,IAAI,CAAC,CAAC;AAAA,MAC3C,OAAO;AACL,eAAO,QAAQ,MAAM,CAAC,GAAG,UAAU,IAAI,UAAU,EAAE,CAAC;AAAA,MACtD;AAAA,IACF,WAAW,eAAe,gBAAgB;AACxC,UAAI,UAAU,WAAW,GAAG;AAC1B,eAAO,QAAQ,MAAM,CAAC,GAAG,GAAG,UAAU,EAAE,CAAC;AAAA,MAC3C,OAAO;AACL,eAAO,QAAQ,MAAM,CAAC,CAAC,EAAE,OAAO,SAAS,CAAC;AAAA,MAC5C;AAAA,IACF;AAAA,EACF,WAAW,QAAQ,GAAG;AACpB,WAAO;AAAA,EACT;AACA,QAAM,IAAI,WAAW,sCAAsC,KAAK,MAAM;AACxE;AACA,SAAS,QAAQ,GAAG,MAAM,YAAY;AACpC,SAAO,KAAK,MAAM;AAChB,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,oBAAgB,UAAU;AAC1B,WAAO,KAAK,GAAG,YAAY,EAAE,MAAM,MAAM,UAAU,CAAC;AAAA,EACtD,CAAC;AACH;AACA,SAAS,KAAK,GAAGsB,SAAQ,GAAG;AAC1B,MAAIA,WAAU,GAAG;AACf,UAAM,IAAI,oBAAoB,0CAA0CA,iCAAgC;AAAA,EAC1G;AACA,SAAO,IAAI,CAAC;AACd;AACA,SAAS,SAAS,GAAG;AACnB,SAAO,KAAK,MAAM,IAAI,GAAG,KAAK,IAAI,CAAC,GAAG,CAAC,CAAC,CAAC;AAC3C;AACA,SAAS,SAAS,GAAG,OAAO,YAAY,MAAM;AAC5C,SAAO,KAAK,MAAM,QAAQ,GAAG,OAAO,YAAY,IAAI,CAAC;AACvD;AACA,SAAS,YAAY,GAAG;AACtB,SAAO,KAAK,MAAM;AAChB,UAAM,IAAI,KAAK,KAAK,IAAI,KAAK,CAAC,CAAC;AAC/B,WAAO,YAAY,GAAG,GAAG,CAAC;AAAA,EAC5B,CAAC;AACH;AACA,SAAS,aAAa,GAAG,KAAK,WAAW,OAAO;AAC9C,SAAO,WAAW,EAAE,IAAI,IAAI;AAC9B;AAGA,IAAI,wBAAwB,CAAC,SAAS,UAAU,QAAQ;AACxD,IAAI,4BAA4B,CAAC,UAAU,WAAW,iBAAiB;AAGvE,SAAS,aAAa,OAAO;AAC3B,4BAA0B,uBAAuB,WAAW,KAAK;AACnE;AACA,SAAS,kBAAkB,OAAO;AAChC,4BAA0B,2BAA2B,gBAAgB,KAAK;AAC5E;AACA,IAAI,cAAc,cAAc,sBAAsB,aAAa;AAAA,EACjE,8BAA8B;AAC5B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,WAAO,CAAC;AAAA,EACV;AACF;AACA,IAAI,QAAQ,cAAc,YAAY;AAAA,EACpC,MAAM,OAAO,OAAO;AAClB,WAAO,MAAM,OAAO,KAAK;AAAA,EAC3B;AACF;AACA,MAAM,YAAY;AAClB,sBAAsB,cAAc,KAAK;AACzC,IAAI,OAAO,cAAc,YAAY;AAAA,EACnC,MAAM,OAAO,OAAO;AAClB,WAAO,MAAM,OAAO,KAAK;AAAA,EAC3B;AACF;AACA,KAAK,YAAY;AACjB,sBAAsB,cAAc,IAAI;AACxC,IAAI,WAAW,cAAc,YAAY;AAAA,EACvC,YAAY,MAAM;AAChB,UAAM;AACN,QAAI,OAAO,SAAS,UAAU;AAC5B,YAAM,IAAI,WAAW,oDAAoD,MAAM;AAAA,IACjF;AACA,QAAI,KAAK,UAAU,QAAQ;AACzB,YAAM,IAAI,WAAW,sCAAsC,MAAM;AAAA,IACnE;AACA,SAAK,QAAQ,KAAK;AAAA,EACpB;AAAA,EACA,MAAM,OAAO,OAAO;AAClB,WAAO,KAAK,MAAM,IAAI,OAAO,KAAK,KAAK,GAAG,MAAM,OAAO,KAAK,CAAC,CAAC;AAAA,EAChE;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,OAAO,KAAK;AAAA,IACd;AAAA,EACF;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,gBAAgB,cAAc,YAAY;AAAA,EAC5C,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AACtB,SAAK,SAAS,KAAK,UAAU,KAAK;AAClC,SAAK,SAAS,KAAK,UAAU,KAAK;AAClC,SAAK,OAAO,KAAK;AAAA,EACnB;AAAA,EACA,MAAM,OAAO,OAAO;AAClB,WAAO,cAAc,OAAO,KAAK,QAAQ,KAAK,QAAQ,KAAK;AAAA,EAC7D;AAAA,EACA,YAAY;AACV,WAAO,EAAE,QAAQ,KAAK,QAAQ,QAAQ,KAAK,QAAQ,MAAM,KAAK,KAAK;AAAA,EACrE;AACF;AACA,cAAc,YAAY;AAC1B,sBAAsB,cAAc,aAAa;AACjD,IAAI,eAAe,cAAc,YAAY;AAAA,EAC3C,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,iBAAiB;AACtB,SAAK,OAAO,KAAK,QAAQ,KAAK;AAC9B,SAAK,SAAS,KAAK,UAAU,KAAK;AAClC,SAAK,OAAO,KAAK;AAAA,EACnB;AAAA,EACA,MAAM,OAAO,OAAO;AAClB,YAAQ,SAAS;AACjB,QAAI,UAAU,aAAa,UAAU,SAAS;AAC5C,YAAM,IAAI,oBAAoB,uCAAuC,QAAQ;AAAA,IAC/E;AACA,WAAO,cAAc,OAAO,KAAK,MAAM,KAAK,QAAQ,OAAO,KAAK,IAAI;AAAA,EACtE;AAAA,EACA,YAAY;AACV,WAAO,EAAE,MAAM,KAAK,MAAM,QAAQ,KAAK,QAAQ,MAAM,KAAK,KAAK;AAAA,EACjE;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAChD,IAAI,kBAAkB,cAAc,YAAY;AAAA,EAC9C,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,iBAAiB;AACtB,SAAK,OAAO,KAAK,QAAQ,KAAK;AAC9B,SAAK,SAAS,KAAK,UAAU,KAAK;AAClC,SAAK,OAAO,KAAK;AAAA,EACnB;AAAA,EACA,MAAM,OAAO,OAAO;AAClB,YAAQ,SAAS;AACjB,QAAI,UAAU,aAAa,UAAU,SAAS;AAC5C,YAAM,IAAI,oBAAoB,0CAA0C,QAAQ;AAAA,IAClF;AACA,WAAO,gBAAgB,OAAO,KAAK,MAAM,KAAK,QAAQ,OAAO,KAAK,IAAI;AAAA,EACxE;AAAA,EACA,YAAY;AACV,WAAO,EAAE,MAAM,KAAK,MAAM,QAAQ,KAAK,QAAQ,MAAM,KAAK,KAAK;AAAA,EACjE;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,IAAI,YAAY,cAAc,YAAY;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,OAAO;AAAA,EAC9C;AAAA,EACA,MAAM,OAAO,OAAO;AAClB,WAAO,KAAK,MAAM;AAChB,UAAI,MAAM,WAAW,KAAK,MAAM,OAAO,MAAM,IAAI;AAC/C,cAAM,IAAI,WAAW,sEAAsE;AAAA,MAC7F,OAAO;AACL,eAAO,IAAI,KAAK,MAAM,IAAI,MAAM,EAAE,CAAC;AAAA,MACrC;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,WAAO,EAAE,MAAM,KAAK,KAAK;AAAA,EAC3B;AACF;AACA,UAAU,YAAY;AACtB,sBAAsB,cAAc,SAAS;AAC7C,SAAS,YAAY,OAAO,aAAa,gBAAgB;AACvD,MAAI;AACJ,MAAI;AACJ,kBAAgB,UAAU;AAC1B,MAAI,MAAM,WAAW,GAAG;AACtB,YAAQ,MAAM;AACd,aAAS,MAAM;AAAA,EACjB,WAAW,CAAC,GAAG,GAAG,CAAC,EAAE,QAAQ,MAAM,MAAM,MAAM,IAAI;AACjD,QAAI,eAAe,iBAAiB;AAClC,YAAM,qBAAqB,UAAU,OAAO,CAAC;AAC7C,cAAQ,MAAM,KAAK;AACnB,eAAS,MAAM,KAAK;AAAA,IACtB,WAAW,eAAe,gBAAgB;AACxC,YAAM,qBAAqB,UAAU,OAAO,GAAG,MAAM,SAAS,CAAC;AAC/D,cAAQ,MAAM,MAAM,SAAS,KAAK;AAClC,eAAS,MAAM,MAAM,SAAS,KAAK;AAAA,IACrC;AAAA,EACF,OAAO;AACL,UAAM,YAAY,UAAU,KAAK;AACjC,YAAQ,KAAK,KAAK,SAAS;AAC3B,aAAS,KAAK,KAAK,SAAS;AAAA,EAC9B;AACA,SAAO,CAAC,OAAO,MAAM;AACvB;AACA,IAAI,kBAAkB,cAAc,YAAY;AAAA,EAC9C,YAAY,MAAM;AAChB,UAAM;AACN,QAAI,KAAK,QAAQ,GAAG;AAClB,YAAM,IAAI,WAAW,wCAAwC,KAAK,OAAO;AAAA,IAC3E;AACA,SAAK,QAAQ,KAAK,SAAS,OAAO,IAAI,KAAK;AAC3C,SAAK,OAAO,KAAK,QAAQ,OAAO,UAAU,KAAK;AAC/C,iBAAa,KAAK,IAAI;AACtB,SAAK,eAAe,KAAK,gBAAgB,OAAO,WAAW,KAAK;AAChE,sBAAkB,KAAK,YAAY;AACnC,SAAK,OAAO,KAAK;AAAA,EACnB;AAAA,EACA,MAAM,OAAO,OAAO;AAClB,UAAM,OAAO,YAAY,KAAK;AAC9B,UAAM,QAAQ,KAAK;AACnB,UAAM,SAAS,KAAK;AACpB,QAAID,UAAS,KAAK;AAClB,QAAI,KAAK,SAAS,SAAS;AACzB,MAAAA,WAAU,KAAK,IAAI,GAAG,KAAK;AAAA,IAC7B,WAAW,KAAK,SAAS,UAAU;AACjC,MAAAA,WAAU,KAAK,IAAI,GAAG,MAAM;AAAA,IAC9B,OAAO;AACL,MAAAA,WAAU,KAAK,IAAI,IAAI,QAAQ,UAAU,CAAC;AAAA,IAC5C;AACA,QAAI,KAAK,iBAAiB,UAAU;AAClC,YAAM,SAAS,KAAK,KAAKA,OAAM;AAC/B,cAAQ,SAAS;AACjB,UAAI,UAAU,aAAa,UAAU,SAAS;AAC5C,cAAM,IAAI,oBAAoB,GAAG,KAAK,aAAa,4BAA4B,QAAQ;AAAA,MACzF;AACA,aAAO,gBAAgB,OAAO,GAAG,QAAQ,OAAO,KAAK,IAAI;AAAA,IAC3D,OAAO;AACL,YAAM,QAAQ,KAAK,KAAK,IAAIA,OAAM;AAClC,aAAO,cAAc,OAAO,CAAC,OAAO,OAAO,KAAK;AAAA,IAClD;AAAA,EACF;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,OAAO,KAAK;AAAA,MACZ,MAAM,KAAK;AAAA,MACX,cAAc,KAAK;AAAA,MACnB,MAAM,KAAK;AAAA,IACb;AAAA,EACF;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,IAAI,gBAAgB,cAAc,gBAAgB;AAAA,EAChD,YAAY,MAAM;AAChB,UAAM;AAAA,MACJ,OAAO;AAAA,MACP,MAAM;AAAA,MACN,cAAc;AAAA,MACd,MAAM,QAAQ,OAAO,OAAO,KAAK;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,eAAe;AACb,WAAO,gBAAgB;AAAA,EACzB;AACF;AACA,cAAc,YAAY;AAC1B,sBAAsB,cAAc,aAAa;AACjD,IAAI,eAAe,cAAc,gBAAgB;AAAA,EAC/C,YAAY,MAAM;AAChB,UAAM;AAAA,MACJ,OAAO;AAAA,MACP,MAAM;AAAA,MACN,cAAc;AAAA,MACd,MAAM,QAAQ,OAAO,OAAO,KAAK;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,eAAe;AACb,WAAO,gBAAgB;AAAA,EACzB;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAChD,IAAI,WAAW,cAAc,gBAAgB;AAAA,EAC3C,YAAY,MAAM;AAChB,UAAM;AAAA,MACJ,OAAO;AAAA,MACP,MAAM;AAAA,MACN,cAAc;AAAA,MACd,MAAM,QAAQ,OAAO,OAAO,KAAK;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,eAAe;AACb,WAAO,gBAAgB;AAAA,EACzB;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,YAAY,cAAc,gBAAgB;AAAA,EAC5C,YAAY,MAAM;AAChB,UAAM;AAAA,MACJ,OAAO;AAAA,MACP,MAAM;AAAA,MACN,cAAc;AAAA,MACd,MAAM,QAAQ,OAAO,OAAO,KAAK;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,eAAe;AACb,WAAO,gBAAgB;AAAA,EACzB;AACF;AACA,UAAU,YAAY;AACtB,sBAAsB,cAAc,SAAS;AAC7C,IAAI,cAAc,cAAc,gBAAgB;AAAA,EAC9C,YAAY,MAAM;AAChB,UAAM;AAAA,MACJ,OAAO;AAAA,MACP,MAAM;AAAA,MACN,cAAc;AAAA,MACd,MAAM,QAAQ,OAAO,OAAO,KAAK;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,eAAe;AACb,WAAO,gBAAgB;AAAA,EACzB;AACF;AACA,YAAY,YAAY;AACxB,sBAAsB,cAAc,WAAW;AAC/C,IAAI,eAAe,cAAc,gBAAgB;AAAA,EAC/C,YAAY,MAAM;AAChB,UAAM;AAAA,MACJ,OAAO;AAAA,MACP,MAAM;AAAA,MACN,cAAc;AAAA,MACd,MAAM,QAAQ,OAAO,OAAO,KAAK;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,eAAe;AACb,WAAO,gBAAgB;AAAA,EACzB;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAChD,IAAI,aAAa,cAAc,YAAY;AAAA,EACzC,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,eAAe,KAAK;AACzD,SAAK,OAAO,KAAK;AACjB,QAAI,KAAK,QAAQ,MAAM;AACrB,YAAM,IAAI,oBAAoB,gEAAgE;AAAA,IAChG;AAAA,EACF;AAAA,EACA,MAAM,OAAO,OAAO;AAClB,WAAO,KAAK,MAAM;AAChB,UAAI,MAAM,SAAS,GAAG;AACpB,cAAM,IAAI,oBAAoB,4BAA4B;AAAA,MAC5D;AACA,UAAI,MAAM,KAAK,MAAM,KAAK,KAAK;AAC7B,gBAAQ,KAAK,2EAA2E,MAAM,KAAK,MAAM,oCAAoC;AAAA,MAC/I;AACA,YAAM,kBAAkB,MAAM,KAAK,MAAM,KAAK,CAAC,MAAM,IAAI,MAAM,EAAE,IAAI;AACrE,YAAM,IAAI,cAAc,iBAAiB,GAAG,GAAG,SAAS;AACxD,UAAI,IAAI,OAAO,YAAY,CAAC;AAC5B,UAAI,MAAM,KAAK,MAAM,IAAI;AACvB,YAAI,UAAU,CAAC;AAAA,MACjB;AACA,aAAO,IAAI,KAAK,MAAM,CAAC;AAAA,IACzB,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,MAAM,KAAK;AAAA,MACX,MAAM,KAAK;AAAA,IACb;AAAA,EACF;AACF;AACA,WAAW,YAAY;AACvB,sBAAsB,cAAc,UAAU;AAC9C,IAAI,6CAA6C;AAAA,EAC/C,YAAY;AAAA,EACZ,gBAAgB;AAAA,EAChB,iBAAiB;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,eAAe;AAAA,EACf,gBAAgB;AAAA,EAChB,QAAQ;AAAA,EACR,cAAc;AAAA,EACd,gBAAgB;AAAA,EAChB,iBAAiB;AAAA,EACjB,mBAAmB;AAAA,EACnB,mBAAmB;AAAA,EACnB,SAAS;AACX;AACA,SAAS,uBAAuBP,SAAQ,gBAAgB,CAAC,GAAG;AAC1D,SAAO,uBAAuBA,SAAQ,sBAAsB,iBAAiB,OAAO,EAAE,cAAc,eAAe,aAAa;AAClI;AACA,SAAS,qBAAqB,aAAa;AACzC,SAAO,qBAAqB,WAAW;AACzC;AACA,SAAS,eAAe,YAAY;AAClC,MAAI,OAAO,eAAe,UAAU;AAClC,UAAM,YAAY,cAAc,6CAA6C,2CAA2C,cAAc;AACtI,QAAI,cAAc,gBAAgB;AAChC,aAAO,IAAI,aAAa;AAAA,IAC1B,WAAW,cAAc,iBAAiB;AACxC,aAAO,IAAI,cAAc;AAAA,IAC3B,WAAW,cAAc,YAAY;AACnC,aAAO,IAAI,SAAS;AAAA,IACtB,WAAW,cAAc,aAAa;AACpC,aAAO,IAAI,UAAU;AAAA,IACvB,WAAW,cAAc,eAAe;AACtC,aAAO,IAAI,YAAY;AAAA,IACzB,WAAW,cAAc,gBAAgB;AACvC,aAAO,IAAI,aAAa;AAAA,IAC1B,OAAO;AACL,YAAMA,UAAS,CAAC;AAChB,MAAAA,QAAO,eAAe;AACtB,MAAAA,QAAO,YAAY,CAAC;AACpB,aAAO,uBAAuBA,OAAM;AAAA,IACtC;AAAA,EACF,WAAW,sBAAsB,aAAa;AAC5C,WAAO;AAAA,EACT,OAAO;AACL,WAAO,uBAAuB,UAAU;AAAA,EAC1C;AACF;AAGA,SAAS,gBAAgB,GAAG;AAC1B,SAAO,MAAM,QAAQ,CAAC,KAAK,MAAM,QAAQ,EAAE,EAAE;AAC/C;AACA,SAAS,mBAAmB,GAAG;AAC7B,MAAI,EAAE,WAAW,GAAG;AAClB,WAAO,CAAC;AAAA,EACV;AACA,MAAI,CAAC,MAAM,QAAQ,EAAE,EAAE,GAAG;AACxB,WAAO,CAAC,CAAC;AAAA,EACX;AACA,SAAO;AACT;AACA,SAAS,oBAAoB,IAAI;AAC/B,MAAI;AACJ,MAAI,MAAM,QAAQ,EAAE,GAAG;AACrB,QAAI,GAAG,WAAW,GAAG;AACnB,YAAM,IAAI,WAAW,uCAAuC,GAAG,QAAQ;AAAA,IACzE;AACA,QAAI,GAAG;AAAA,EACT,OAAO;AACL,QAAI;AAAA,EACN;AACA,SAAO;AACT;AACA,SAAS,mBAAmB,QAAQ;AAClC,MAAI,MAAM,QAAQ,MAAM,KAAK,MAAM,QAAQ,OAAO,EAAE,GAAG;AACrD,QAAI,OAAO,WAAW,GAAG;AACvB,eAAS;AACT,aAAO,OAAO;AAAA,IAChB,OAAO;AACL,YAAM,IAAI,WAAW,iCAAiC,OAAO,QAAQ;AAAA,IACvE;AAAA,EACF,OAAO;AACL,WAAO;AAAA,EACT;AACF;AAGA,SAAS,qBAAqB,SAAS;AACrC,MAAIP,UAAS;AACb,aAAW,UAAU,SAAS;AAC5B,QAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,MAAAA,WAAU;AAAA,IACZ,OAAO;AACL,MAAAA,WAAU,OAAO,MAAM,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAAA,IAC/C;AAAA,EACF;AACA,SAAOA;AACT;AAGA,IAAI,+BAA+B;AACnC,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,KAAK,QAAQ,WAAW,OAAO,8BAA8B,YAAY,MAAM,aAAa,MAAM;AAC5G,SAAK,QAAQ,SAAS,OAAO,YAAY;AACzC,SAAK,QAAQ,IAAI;AACjB,SAAK,KAAK,sBAAsB;AAChC,WAAO,QAAQ,OAAO,+BAA+B;AACrD,SAAK,eAAe,oBAAoB,IAAI;AAC5C,SAAK,OAAO,oBAAoB,KAAK,YAAY;AACjD,SAAK,aAAa;AAClB,SAAK,aAAa;AAClB,SAAK,MAAM,SAAS,KAAK,KAAK,YAAY,KAAK,MAAM,KAAK,KAAK;AAAA,EACjE;AAAA,EACA,OAAO;AACL,SAAK,kBAAkB;AACvB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,QAAQ;AACZ,SAAK,kBAAkB;AACvB,qBAAiB,KAAK,KAAK,MAAM;AACjC,QAAI,KAAK,IAAI,OAAO,OAAO,IAAI;AAC7B,WAAK,IAAI,OAAO,MAAM;AACtB,UAAI,KAAK,cAAc,MAAM;AAC3B,aAAK,IAAI,OAAO,KAAK,WAAW,MAAM,KAAK,GAAG,CAAC;AAAA,MACjD;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,UAAU;AACR,SAAK,kBAAkB;AACvB,SAAK,IAAI,QAAQ;AAAA,EACnB;AAAA,EACA,oBAAoB;AAClB,QAAI,KAAK,IAAI,YAAY;AACvB,YAAM,IAAI,MAAM,kBAAkB,KAAK,2BAA2B;AAAA,IACpE;AAAA,EACF;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,UAAU,WAAW;AACvB,SAAK,aAAa;AAClB,SAAK,IAAI,YAAY;AAAA,EACvB;AACF;AACA,SAAS,iBAAiB,GAAG,GAAG;AAC9B,MAAI,EAAE,MAAM,SAAS,MAAM,EAAE,MAAM,SAAS,GAAG;AAC7C,UAAM,IAAI,MAAM,qBAAqB,KAAK,UAAU,EAAE,KAAK,IAAI,UAAU,KAAK,UAAU,EAAE,KAAK,CAAC;AAAA,EAClG;AACF;AACA,SAAS,cAAc,IAAI;AACzB,SAAO,GAAG,IAAI,CAAC,MAAM,EAAE,KAAK,CAAC;AAC/B;AACA,SAAS,cAAc,oBAAoB;AACzC,qBAAmB,QAAQ,CAAC,qBAAqB;AAC/C,UAAM,YAAY,iBAAiB;AACnC,cAAU,MAAM,iBAAiB,EAAE;AAAA,EACrC,CAAC;AACH;AAGA,IAAI,YAAY,MAAM;AAAA,EACpB,YAAY,MAAM;AAChB,SAAK,QAAQ,KAAK;AAClB,SAAK,QAAQ,KAAK;AAClB,QAAI,KAAK,SAAS,MAAM;AACtB,WAAK,OAAO,KAAK,MAAM;AAAA,IACzB,OAAO;AACL,WAAK,OAAO,KAAK;AAAA,IACnB;AACA,SAAK,UAAU,KAAK;AACpB,SAAK,UAAU,KAAK;AACpB,SAAK,OAAO,KAAK,QAAQ,CAAC;AAAA,EAC5B;AACF;AACA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,OAAO,OAAO,aAAa,QAAQ,UAAU,MAAM,mBAAmB;AAChF,SAAK,QAAQ;AACb,SAAK,QAAQ;AACb,SAAK,cAAc;AACnB,SAAK,SAAS;AACd,SAAK,WAAW;AAChB,SAAK,oBAAoB;AACzB,SAAK,KAAK,sBAAsB;AAChC,QAAI,QAAQ,MAAM;AAChB,WAAK,eAAe,oBAAoB,IAAI;AAC5C,WAAK,OAAO,oBAAoB,KAAK,YAAY;AAAA,IACnD;AACA,SAAK,OAAO,MAAM;AAAA,EACpB;AACF;AACA,IAAI,cAAc;AAClB,IAAI,OAAO,MAAM;AAAA,EACf,YAAY,MAAM,UAAU;AAC1B,SAAK,WAAW;AAChB,SAAK,KAAK;AACV,SAAK,gBAAgB,KAAK;AAC1B,SAAK,gBAAgB,KAAK;AAC1B,SAAK,cAAc,KAAK;AACxB,SAAK,gBAAgB,KAAK;AAC1B,SAAK,eAAe,KAAK;AACzB,SAAK,gBAAgB,KAAK;AAC1B,SAAK,aAAa,KAAK;AACvB,SAAK,cAAc,KAAK;AACxB,SAAK,cAAc,KAAK;AACxB,SAAK,eAAe,KAAK;AACzB,eAAW,SAAS,KAAK,eAAe;AACtC,UAAI,SAAS,MAAM;AACjB,cAAM,cAAc,KAAK,IAAI;AAAA,MAC/B;AAAA,IACF;AACA,SAAK,cAAc,aAAa,KAAK,IAAI;AAAA,EAC3C;AAAA,EACA,YAAY;AACV,UAAM,eAAe,CAAC;AACtB,eAAW,SAAS,KAAK,eAAe;AACtC,UAAI,SAAS,MAAM;AACjB,qBAAa,KAAK,MAAM,IAAI;AAAA,MAC9B,OAAO;AACL,qBAAa,KAAK,IAAI;AAAA,MACxB;AAAA,IACF;AACA,WAAO;AAAA,MACL,eAAe,KAAK,gBAAgB,KAAK,cAAc,OAAO;AAAA,MAC9D,eAAe;AAAA,MACf,aAAa,KAAK;AAAA,MAClB,eAAe,KAAK;AAAA,IACtB;AAAA,EACF;AACF;AACA,IAAI,eAAe;AACnB,IAAI,QAAQ,cAAc,sBAAsB,aAAa;AAAA,EAC3D,YAAY,OAAO,CAAC,GAAG;AACrB,UAAM;AACN,SAAK,YAAY;AACjB,SAAK,oBAAoB,CAAC;AAC1B,SAAK,YAAY;AACjB,SAAK,KAAK;AACV,SAAK,sBAAsB;AAC3B,SAAK,YAAY;AACjB,SAAK,kBAAkB;AACvB,SAAK,oBAAoB,CAAC;AAC1B,SAAK,uBAAuB,CAAC;AAC7B,SAAK,UAAU,CAAC;AAChB,SAAK,WAAW,CAAC;AACjB,SAAK,SAAS;AACd,SAAK,eAAe,CAAC;AACrB,SAAK,gBAAgB,CAAC;AACtB,QAAI,OAAO,KAAK;AAChB,QAAI,CAAC,MAAM;AACT,YAAM,SAAS,KAAK,aAAa;AACjC,aAAO,YAAY,MAAM,IAAI,MAAM,OAAO,MAAM;AAAA,IAClD;AACA,SAAK,OAAO;AACZ,SAAK,aAAa,KAAK,aAAa,OAAO,OAAO,KAAK;AACvD,QAAI,KAAK,cAAc,QAAQ,KAAK,mBAAmB,MAAM;AAC3D,UAAI;AACJ,UAAI,KAAK,mBAAmB,MAAM;AAChC,0BAAkB,KAAK;AAAA,MACzB,WAAW,KAAK,cAAc,MAAM;AAClC,YAAI,YAAY;AAChB,YAAI,KAAK,aAAa,MAAM;AAC1B,sBAAY,KAAK;AAAA,QACnB;AACA,0BAAkB,CAAC,SAAS,EAAE,OAAO,KAAK,UAAU;AAAA,MACtD;AACA,WAAK,kBAAkB;AACvB,UAAI,QAAQ,KAAK;AACjB,UAAI,SAAS,MAAM;AACjB,gBAAQ,KAAK;AAAA,MACf;AACA,UAAI,SAAS,MAAM;AACjB,gBAAQ;AAAA,MACV;AACA,WAAK,QAAQ;AAAA,IACf;AACA,QAAI,KAAK,WAAW,MAAM;AACxB,WAAK,iBAAiB,KAAK;AAAA,IAC7B,OAAO;AACL,WAAK,iBAAiB;AAAA,IACxB;AACA,SAAK,YAAY;AACjB,SAAK,4BAA4B;AAAA,EACnC;AAAA,EACA,OAAO,QAAQ,OAAO,WAAW;AAC/B,WAAO,MAAM,OAAO,SAAS,UAAU,SAAS;AAAA,EAClD;AAAA,EACA,eAAe,WAAW,UAAU;AAClC,QAAI,KAAK,aAAa,WAAW,GAAG;AAClC,YAAM,IAAI,aAAa,2DAA2D,WAAW;AAAA,IAC/F;AACA,QAAI,KAAK,aAAa,UAAU,WAAW;AACzC,YAAM,IAAI,WAAW,gBAAgB,oBAAoB,qCAAqC,KAAK,aAAa,uBAAuB;AAAA,IACzI;AACA,WAAO,KAAK,aAAa;AAAA,EAC3B;AAAA,EACA,WAAW,WAAW;AACpB,WAAO,iBAAiB,KAAK,eAAe,WAAW,OAAO,EAAE,YAAY;AAAA,EAC9E;AAAA,EACA,YAAY,WAAW;AACrB,WAAO,iBAAiB,KAAK,eAAe,WAAW,QAAQ,EAAE,aAAa;AAAA,EAChF;AAAA,EACA,IAAI,QAAQ;AACV,QAAI,KAAK,aAAa,SAAS,GAAG;AAChC,YAAM,IAAI,eAAe,SAAS,KAAK,2HAA2H;AAAA,IACpK,WAAW,KAAK,aAAa,WAAW,GAAG;AACzC,YAAM,IAAI,eAAe,SAAS,KAAK,4CAA4C;AAAA,IACrF;AACA,WAAO,iBAAiB,KAAK,eAAe,GAAG,OAAO,EAAE,YAAY;AAAA,EACtE;AAAA,EACA,IAAI,SAAS;AACX,QAAI,KAAK,aAAa,WAAW,GAAG;AAClC,YAAM,IAAI,eAAe,SAAS,KAAK,4BAA4B;AAAA,IACrE;AACA,QAAI,KAAK,aAAa,SAAS,GAAG;AAChC,YAAM,IAAI,eAAe,SAAS,KAAK,6HAA6H;AAAA,IACtK;AACA,WAAO,iBAAiB,KAAK,eAAe,GAAG,QAAQ,EAAE,aAAa;AAAA,EACxE;AAAA,EACA,IAAI,SAAS;AACX,WAAO,KAAK;AAAA,EACd;AAAA,EACA,kBAAkB;AAChB,WAAO,KAAK,OAAO,IAAI,CAAC,WAAW,OAAO,CAAC;AAAA,EAC7C;AAAA,EACA,IAAI,UAAU;AACZ,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,QAAQ;AACV,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,MAAM,OAAO;AACf,SAAK,SAAS;AAAA,EAChB;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,UAAU,WAAW;AACvB,SAAK,kBAAkB,QAAQ,CAAC,MAAM,EAAE,YAAY,SAAS;AAC7D,SAAK,aAAa;AAAA,EACpB;AAAA,EACA,IAAI,mBAAmB;AACrB,QAAI,KAAK,YAAY;AACnB,aAAO,KAAK,kBAAkB,OAAO,CAAC,MAAM,EAAE,SAAS;AAAA,IACzD,OAAO;AACL,aAAO,CAAC;AAAA,IACV;AAAA,EACF;AAAA,EACA,IAAI,iBAAiB,SAAS;AAC5B,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,IAAI,sBAAsB;AACxB,QAAI,KAAK,WAAW;AAClB,aAAO,KAAK,kBAAkB,OAAO,CAAC,MAAM,CAAC,EAAE,SAAS,EAAE,OAAO,KAAK,oBAAoB;AAAA,IAC5F,OAAO;AACL,aAAO,KAAK,kBAAkB,OAAO,KAAK,oBAAoB;AAAA,IAChE;AAAA,EACF;AAAA,EACA,IAAI,oBAAoB,SAAS;AAC/B,SAAK,uBAAuB;AAAA,EAC9B;AAAA,EACA,IAAI,UAAU;AACZ,WAAO,KAAK,iBAAiB,OAAO,KAAK,mBAAmB;AAAA,EAC9D;AAAA,EACA,IAAI,WAAW;AACb,WAAO,KAAK;AAAA,EACd;AAAA,EACA,cAAc;AACZ,QAAI,CAAC,KAAK,UAAU;AAClB,YAAM,IAAI,MAAM,sEAAsE;AAAA,IACxF;AAAA,EACF;AAAA,EACA,yBAAyB,QAAQ;AAC/B,aAAS,OAAO,MAAM;AACtB,QAAI,KAAK,aAAa,QAAQ,KAAK,UAAU,WAAW,GAAG;AACzD;AAAA,IACF;AACA,UAAM,YAAY,OAAO,KAAK,SAAS;AACvC,QAAI,OAAO,WAAW,UAAU,QAAQ;AACtC,YAAM,IAAI,WAAW,SAAS,KAAK,gBAAgB,UAAU,kCAAkC,OAAO,yCAAyC,QAAQ;AAAA,IACzJ;AACA,aAAS,aAAa,GAAG,aAAa,OAAO,QAAQ,cAAc;AACjE,YAAM,IAAI,OAAO;AACjB,YAAM,OAAO,UAAU;AACvB,UAAI,QAAQ,MAAM;AAChB;AAAA,MACF;AACA,YAAM,OAAO,EAAE;AACf,UAAI,KAAK,QAAQ,MAAM;AACrB,YAAI,SAAS,KAAK,MAAM;AACtB,gBAAM,IAAI,WAAW,SAAS,yCAAyC,KAAK,uBAAuB,KAAK,oBAAoB,MAAM;AAAA,QACpI;AAAA,MACF;AACA,UAAI,KAAK,WAAW,MAAM;AACxB,YAAI,OAAO,KAAK,SAAS;AACvB,gBAAM,IAAI,WAAW,SAAS,yCAAyC,KAAK,2BAA2B,KAAK,uBAAuB,MAAM;AAAA,QAC3I;AAAA,MACF;AACA,UAAI,KAAK,WAAW,MAAM;AACxB,YAAI,OAAO,KAAK,SAAS;AACvB,gBAAM,IAAI,WAAW,SAAS,yCAAyC,KAAK,2BAA2B,KAAK,uBAAuB,OAAO;AAAA,QAC5I;AAAA,MACF;AACA,UAAI,KAAK,SAAS,MAAM;AACtB,YAAI,EAAE,UAAU,KAAK,OAAO;AAC1B,gBAAM,IAAI,WAAW,SAAS,yCAAyC,KAAK,yBAAyB,KAAK,sBAAsB,EAAE,QAAQ;AAAA,QAC5I;AAAA,MACF;AACA,UAAI,KAAK,MAAM;AACb,cAAM,SAAS,EAAE;AACjB,mBAAW,OAAO,KAAK,MAAM;AAC3B,gBAAM,OAAO,OAAO,GAAG;AACvB,gBAAM,QAAQ,KAAK,KAAK;AACxB,gBAAM,eAAe,QAAQ,IAAI,OAAO,QAAQ,OAAO,OAAO,SAAS;AACvE,cAAI,SAAS,QAAQ,CAAC,OAAO,IAAI,EAAE,QAAQ,YAAY,MAAM,IAAI;AAC/D,kBAAM,IAAI,WAAW,SAAS,yCAAyC,KAAK,uBAAuB,qCAAqC,uBAAuB,SAAS;AAAA,UAC1K;AAAA,QACF;AAAA,MACF;AACA,UAAI,KAAK,SAAS,MAAM;AACtB,iBAAS,KAAK,GAAG,KAAK,KAAK,MAAM,QAAQ,EAAE,IAAI;AAC7C,gBAAM,UAAU,KAAK,MAAM;AAC3B,gBAAM,MAAM,EAAE,MAAM;AACpB,cAAI,WAAW,QAAQ,OAAO,MAAM;AAClC,gBAAI,YAAY,KAAK;AACnB,oBAAM,IAAI,WAAW,SAAS,yCAAyC,KAAK,wBAAwB,KAAK,sBAAsB,EAAE,QAAQ;AAAA,YAC3I;AAAA,UACF;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO;AAAA,EACT;AAAA,EACA,eAAe,QAAQ,QAAQ;AAC7B,QAAI,KAAK,aAAa,MAAM;AAC1B,WAAK,UAAU,QAAQ,MAAM;AAAA,IAC/B;AAAA,EACF;AAAA,EACA,YAAY,UAAU;AACpB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,gBAAgB;AACd,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,MAAM,QAAQ,QAAQ;AACpB,aAAS,UAAU,CAAC;AACpB,SAAK,kBAAkB;AACvB,UAAM,aAAa,OAAO,MAAM;AAChC,QAAI,iBAAiB;AACrB,eAAW,UAAU,YAAY;AAC/B,UAAI,EAAE,kBAAkB,iBAAiB;AACvC,yBAAiB;AACjB;AAAA,MACF;AAAA,IACF;AACA,QAAI,kBAAkB;AACtB,eAAW,UAAU,YAAY;AAC/B,UAAI,kBAAkB,gBAAgB;AACpC,0BAAkB;AAClB;AAAA,MACF;AAAA,IACF;AACA,QAAI,mBAAmB,iBAAiB;AACtC,YAAM,IAAI,WAAW,iEAAiE;AAAA,IACxF;AACA,WAAO,UAAU,KAAK,MAAM,MAAM;AAChC,UAAI,CAAC,KAAK,OAAO;AACf,aAAK,yBAAyB,MAAM;AACpC,cAAM,cAAc,CAAC;AACrB,mBAAW,SAAS,OAAO,MAAM,GAAG;AAClC,sBAAY,KAAK,MAAM,KAAK;AAAA,QAC9B;AACA,aAAK,MAAM,iBAAiB,WAAW,CAAC;AACxC,aAAK,QAAQ;AACb,YAAI,KAAK,gBAAgB;AACvB,eAAK,WAAW,KAAK,cAAc;AAAA,QACrC;AACA,YAAI,KAAK,cAAc,QAAQ,iBAAiB;AAC9C,eAAK,YAAY;AAAA,QACnB;AAAA,MACF;AACA,WAAK,yBAAyB,MAAM;AACpC,UAAI,iBAAiB;AACnB,YAAI,SAAS,KAAK,KAAK,QAAQ,MAAM;AACrC,cAAM,aAAa,OAAO,MAAM;AAChC,cAAM,iBAAiB,CAAC;AACxB,iBAAS,KAAK,YAAY;AACxB,cAAI,WAAW,QAAQ,CAAC,MAAM,IAAI;AAChC,gBAAI,EAAE,MAAM;AAAA,UACd;AACA,yBAAe,KAAK,CAAC;AAAA,QACvB;AACA,iBAAS,iBAAiB,cAAc;AACxC,YAAI,KAAK,uBAAuB,MAAM;AACpC,gBAAM,IAAI,oBAAoB,mFAAmF;AAAA,QACnH;AACA,eAAO;AAAA,MACT,OAAO;AACL,cAAM,aAAa,kBAAkB,MAAM;AAC3C,cAAM,cAAc,KAAK,mBAAmB,UAAU;AACtD,YAAI;AACJ,cAAM,cAAc,iBAAiB,MAAM;AAC3C,aAAK,6BAA6B,MAAM,QAAQ,MAAM,IAAI,WAAW,KAAK,UAAU;AACpF,YAAI,eAAe,QAAQ,YAAY,SAAS,KAAK,MAAM,QAAQ,YAAY,EAAE,GAAG;AAClF,mBAAS,YAAY,IAAI,CAAC,OAAOE,WAAU,IAAI,eAAe,aAAa,OAAO,MAAM,OAAO,MAAM,GAAG,QAAQ,KAAK,MAAMA,MAAK,CAAC;AAAA,QACnI,OAAO;AACL,mBAAS,IAAI,eAAe,aAAa,aAAa,MAAM,OAAO,MAAM,GAAG,QAAQ,KAAK,IAAI;AAAA,QAC/F;AACA,aAAK,eAAe,QAAQ,QAAQ,MAAM,MAAM,YAAY,aAAa,MAAM;AAC/E,aAAK;AACL,YAAI,KAAK,uBAAuB,MAAM;AACpC,gBAAM,IAAI,oBAAoB,mFAAmF;AAAA,QACnH;AACA,eAAO;AAAA,MACT;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,6BAA6B,YAAY;AACvC,QAAI,KAAK,mBAAmB,MAAM;AAChC;AAAA,IACF,WAAW,WAAW,WAAW,KAAK,gBAAgB,QAAQ;AAC5D,cAAQ,KAAK,iDAAiD,KAAK,UAAU,UAAU,kDAAkD,KAAK,UAAU,KAAK,eAAe,mBAAmB,KAAK,MAAM;AAAA,IAC5M,OAAO;AACL,UAAI,cAAc;AAClB,WAAK,gBAAgB,QAAQ,CAAC,WAAW,OAAO;AAC9C,YAAI,aAAa,QAAQ,WAAW,OAAO,QAAQ,WAAW,QAAQ,WAAW;AAC/E,wBAAc;AAAA,QAChB;AAAA,MACF,CAAC;AACD,UAAI,aAAa;AACf,gBAAQ,KAAK,kCAAkC,KAAK,UAAU,UAAU,8CAA8C,KAAK,SAAS,KAAK,UAAU,KAAK,eAAe,GAAG;AAAA,MAC5K;AAAA,IACF;AAAA,EACF;AAAA,EACA,IAAI,cAAc;AAChB,QAAI,KAAK,gBAAgB,QAAQ,KAAK,aAAa,WAAW,GAAG;AAC/D,YAAM,IAAI,eAAe,aAAa,KAAK,kEAAkE;AAAA,IAC/G;AACA,UAAM,kBAAkB,CAAC;AACzB,eAAWO,SAAQ,KAAK,cAAc;AACpC,YAAM,cAAc,KAAK,UAAUA,MAAK,YAAY;AACpD,UAAI,gBAAgB,QAAQ,WAAW,MAAM,IAAI;AAC/C,wBAAgB,KAAK,WAAW;AAAA,MAClC;AAAA,IACF;AACA,QAAI,gBAAgB,WAAW,GAAG;AAChC,YAAM,eAAe,KAAK,aAAa,GAAG;AAC1C,UAAI,MAAM,QAAQ,YAAY,KAAK,MAAM,QAAQ,aAAa,EAAE,KAAK,aAAa,WAAW,GAAG;AAC9F,eAAO,aAAa;AAAA,MACtB,OAAO;AACL,eAAO;AAAA,MACT;AAAA,IACF,OAAO;AACL,YAAM,IAAI,eAAe,aAAa,KAAK,gIAAgI;AAAA,IAC7K;AAAA,EACF;AAAA,EACA,cAAc;AACZ,QAAI,CAAC,KAAK,OAAO;AACf,YAAM,IAAI,aAAa,sCAAsC,KAAK,yFAAyF;AAAA,IAC7J;AACA,WAAO,qBAAqB,KAAK,OAAO;AAAA,EAC1C;AAAA,EACA,MAAM,YAAY;AAChB,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,WAAW,gBAAgB,OAAO;AAChC,WAAO,cAAc,gBAAgB,KAAK,mBAAmB,KAAK,OAAO;AAAA,EAC3E;AAAA,EACA,WAAW,SAAS;AAClB,SAAK,MAAM;AACT,YAAM,SAAS,KAAK;AACpB,UAAI,OAAO,WAAW,QAAQ,QAAQ;AACpC,cAAM,IAAI,WAAW,4CAA4C,KAAK,sCAAsC,QAAQ,uCAAuC,OAAO,qCAAqC,YAAY;AAAA,MACrN;AACA,UAAI,OAAO,WAAW,GAAG;AACvB;AAAA,MACF;AACA,YAAM,oBAAoB,CAAC;AAC3B,YAAM,cAAc,cAAc,MAAM;AACxC,eAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,EAAE,IAAI;AAC9C,cAAM,KAAK,YAAY;AACvB,cAAM,KAAK,OAAO;AAClB,cAAM,IAAI,QAAQ;AAClB,YAAI,CAAC,aAAa,YAAY,GAAG,OAAO,EAAE,KAAK,GAAG;AAChD,gBAAM,IAAI,WAAW,sBAAsB,GAAG,mDAAmD,EAAE,OAAO;AAAA,QAC5G;AACA,0BAAkB,KAAK,CAAC,IAAI,CAAC,CAAC;AAAA,MAChC;AACA,oBAAc,iBAAiB;AAAA,IACjC,CAAC;AAAA,EACH;AAAA,EACA,UAAU,MAAM,OAAO,OAAO,aAAa,aAAa,WAAW,YAAY,oBAAoB;AACjG,QAAI,KAAK,kBAAkB,QAAQ,IAAI,MAAM,IAAI;AAC/C,YAAM,IAAI,WAAW,yBAAyB,kBAAkB,KAAK,MAAM;AAAA,IAC7E;AACA,SAAK,kBAAkB,KAAK,IAAI;AAChC,QAAI,SAAS,MAAM;AACjB,cAAQ;AAAA,IACV;AACA,QAAI,KAAK,2BAA2B;AAClC,oBAAc,sBAAsB,OAAO,mBAAmB,IAAI,eAAe,OAAO;AAAA,IAC1F;AACA,UAAM,YAAY,YAAY,MAAM,OAAO,KAAK;AAChD,UAAM,SAAS,IAAI,cAAc,WAAW,OAAO,MAAM,WAAW,UAAU;AAC9E,cAAU,QAAQ;AAClB,QAAI,eAAe,MAAM;AACvB,WAAK,QAAQ,MAAM,YAAY,MAAM,OAAO,KAAK,CAAC,CAAC;AAAA,IACrD;AACA,QAAI,aAAa,MAAM;AACrB,kBAAY;AAAA,IACd;AACA,QAAI,WAAW;AACb,WAAK,kBAAkB,KAAK,MAAM;AAAA,IACpC,OAAO;AACL,WAAK,qBAAqB,KAAK,MAAM;AAAA,IACvC;AACA,WAAO;AAAA,EACT;AAAA,EACA,6BAA6B,OAAO;AAClC,SAAK,4BAA4B;AAAA,EACnC;AAAA,EACA,QAAQ,SAAS;AACf,QAAI,WAAW,QAAQ,MAAM,QAAQ,OAAO,KAAK,QAAQ,WAAW,GAAG;AACrE;AAAA,IACF;AACA,cAAU,OAAO,OAAO;AACxB,QAAI,KAAK,YAAY,UAAU,KAAK,YAAY,MAAM;AACpD,WAAK,OAAO,KAAK,GAAG,OAAO;AAAA,IAC7B;AAAA,EACF;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY,QAAQX,OAAM;AACxB,QAAI,CAAC,KAAK,iBAAiB;AACzB,UAAIA,SAAQ,MAAM;AAChB,YAAI,MAAM,QAAQA,KAAI,GAAG;AACvB,UAAAA,MAAK,QAAQ,CAAC,gBAAgB;AAC5B,gBAAI,eAAe,MAAM;AACvB,oBAAM,IAAI,UAAU,SAAS,KAAK,6DAA6D;AAAA,YACjG;AAAA,UACF,CAAC;AAAA,QACH,OAAO;AACL,gBAAM,IAAI,UAAU,SAAS,KAAK,6DAA6D;AAAA,QACjG;AAAA,MACF;AACA,aAAO;AAAA,IACT;AACA,WAAOA;AAAA,EACT;AAAA,EACA,eAAe,cAAc,eAAe,YAAY,aAAa,aAAa,cAAc,SAAS,MAAM;AAC7G,UAAM,kBAAkB,OAAO,YAAY;AAC3C,oBAAgB,OAAO,aAAa;AACpC,iBAAa,OAAO,UAAU;AAC9B,kBAAc,OAAO,WAAW;AAChC,kBAAc,mBAAmB,WAAW;AAC5C,mBAAe,mBAAmB,YAAY;AAC9C,UAAM,gBAAgB,CAAC;AACvB,UAAM,cAAc,CAAC;AACrB,UAAM,gBAAgB,CAAC;AACvB,eAAW,KAAK,iBAAiB;AAC/B,oBAAc,KAAK,EAAE,WAAW;AAChC,kBAAY,KAAK,EAAE,SAAS;AAC5B,oBAAc,KAAK,EAAE,WAAW;AAAA,IAClC;AACA,QAAI,KAAK;AAAA,MACP,eAAe;AAAA,MACf;AAAA,MACA;AAAA,MACA;AAAA,MACA,cAAc;AAAA,MACd;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF,GAAG,MAAM;AACT,aAAS,KAAK,GAAG,KAAK,cAAc,QAAQ,MAAM;AAChD,oBAAc,IAAI,cAAc;AAChC,oBAAc,IAAI,YAAY,KAAK,aAAa,SAAS;AACzD,oBAAc,IAAI,cAAc;AAAA,IAClC;AAAA,EACF;AAAA,EACA,YAAY;AACV,UAAMS,UAAS,EAAE,MAAM,KAAK,MAAM,WAAW,KAAK,UAAU;AAC5D,QAAI,KAAK,mBAAmB,MAAM;AAChC,MAAAA,QAAO,qBAAqB,KAAK;AAAA,IACnC;AACA,QAAI,KAAK,SAAS,MAAM;AACtB,MAAAA,QAAO,WAAW,KAAK;AAAA,IACzB;AACA,WAAOA;AAAA,EACT;AAAA,EACA,iBAAiB;AACf,SAAK,QAAQ,QAAQ,CAAC,WAAW,OAAO,QAAQ,CAAC;AACjD,WAAO,KAAK,QAAQ;AAAA,EACtB;AAAA,EACA,oBAAoB;AAClB,QAAI,KAAK,cAAc,GAAG;AACxB,YAAM,IAAI,MAAM,UAAU,KAAK,4BAA4B;AAAA,IAC7D;AAAA,EACF;AAAA,EACA,UAAU;AACR,QAAI,CAAC,KAAK,OAAO;AACf,YAAM,IAAI,MAAM,wBAAwB,KAAK,yCAAyC;AAAA,IACxF;AACA,QAAI,KAAK,cAAc,MAAM;AAC3B,YAAM,IAAI,MAAM,wBAAwB,KAAK,wCAAwC;AAAA,IACvF;AACA,SAAK,kBAAkB;AACvB,QAAI,uBAAuB;AAC3B,QAAI,EAAE,KAAK,cAAc,GAAG;AAC1B,6BAAuB,KAAK,eAAe;AAAA,IAC7C;AACA,WAAO,EAAE,sBAAsB,KAAK,WAAW,qBAAqB;AAAA,EACtE;AACF;AACA,SAAS,kBAAkB,cAAc;AACvC,iBAAe,OAAO,YAAY;AAClC,QAAM,SAAS,CAAC;AAChB,aAAW,KAAK,cAAc;AAC5B,WAAO,KAAK,EAAE,KAAK;AAAA,EACrB;AACA,SAAO,iBAAiB,MAAM;AAChC;AACA,SAAS,iBAAiB,cAAc;AACtC,SAAO;AACT;AACA,SAAS,gBAAgB,SAAS,OAAO,WAAW;AAClD,MAAI,SAAS,QAAQ,aAAa,QAAQ,YAAY,GAAG;AACvD,YAAQ,QAAQ;AAChB,gBAAY,QAAQ;AAAA,EACtB;AACA,MAAI,MAAM,aAAa,WAAW,GAAG;AACnC,WAAO,CAAC,OAAO;AAAA,EACjB,OAAO;AACL,UAAME,QAAO,MAAM,aAAa;AAChC,QAAIA,MAAK,cAAc,WAAW,GAAG;AACnC,aAAOA,MAAK;AAAA,IACd,OAAO;AACL,YAAM,gBAAgB,CAAC;AACvB,eAAS,KAAK,GAAG,KAAKA,MAAK,cAAc,QAAQ,MAAM;AACrD,cAAM,IAAIA,MAAK,aAAa;AAC5B,cAAM,SAASA,MAAK,cAAc;AAClC,cAAM,aAAaA,MAAK,YAAY;AACpC,cAAM,kBAAkB,gBAAgB,GAAG,QAAQ,UAAU;AAC7D,mBAAW,MAAM,iBAAiB;AAChC,cAAI,cAAc,QAAQ,EAAE,MAAM,IAAI;AACpC,0BAAc,KAAK,EAAE;AAAA,UACvB;AAAA,QACF;AAAA,MACF;AACA,aAAO;AAAA,IACT;AAAA,EACF;AACF;AAGA,IAAI,aAAa,cAAc,MAAM;AAAA,EACnC,YAAY,MAAM;AAChB,UAAM;AAAA,MACJ,OAAO,KAAK;AAAA,MACZ,MAAM,KAAK,QAAQ,OAAO,KAAK,OAAO,OAAO,OAAO,EAAE,SAAS;AAAA,IACjE,CAAC;AACD,QAAI,KAAK,aAAa,MAAM;AAC1B,WAAK,YAAY;AAAA,IACnB;AACA,QAAI,KAAK,UAAU,MAAM;AACvB,WAAK,SAAS;AAAA,IAChB;AACA,SAAK,YAAY;AACjB,SAAK,QAAQ;AACb,SAAK,SAAS,KAAK;AACnB,QAAI,KAAK,cAAc,QAAQ,KAAK,mBAAmB,MAAM;AAC3D,YAAM,IAAI,WAAW,mGAAmG;AAAA,IAC1H;AACA,QAAI,kBAAkB,KAAK;AAC3B,QAAI,mBAAmB,MAAM;AAC3B,UAAI,KAAK,cAAc,MAAM;AAC3B,cAAM,IAAI,WAAW,+EAA+E;AAAA,MACtG,OAAO;AACL,0BAAkB,CAAC,KAAK,SAAS,EAAE,OAAO,KAAK,UAAU;AAAA,MAC3D;AAAA,IACF,OAAO;AACL,UAAI,KAAK,aAAa,MAAM;AAC1B,cAAM,IAAI,WAAW,uFAAuF;AAAA,MAC9G;AAAA,IACF;AACA,UAAM,QAAQ,KAAK,SAAS;AAC5B,SAAK,kBAAkB;AACvB,SAAK,QAAQ;AACb,SAAK,YAAY,CAAC,EAAE,OAAO,gBAAgB,CAAC;AAC5C,UAAM,cAAc,IAAI,eAAe,KAAK,OAAO,KAAK,iBAAiB,MAAM,CAAC,GAAG,CAAC,GAAG,KAAK,IAAI;AAChG,gBAAY,YAAY;AACxB,gBAAY,cAAc;AAC1B,QAAI,KAAK;AAAA,MACP,eAAe;AAAA,MACf,eAAe,CAAC;AAAA,MAChB,aAAa,CAAC;AAAA,MACd,eAAe,CAAC;AAAA,MAChB,cAAc,CAAC,WAAW;AAAA,MAC1B,eAAe,CAAC,WAAW;AAAA,MAC3B,YAAY,CAAC,IAAI;AAAA,MACjB,aAAa,CAAC,IAAI;AAAA,MAClB,aAAa,CAAC,eAAe;AAAA,MAC7B,cAAc,CAAC,eAAe;AAAA,IAChC,CAAC;AAAA,EACH;AAAA,EACA,MAAM,QAAQ,QAAQ;AACpB,UAAM,IAAI,WAAW,6EAA6E,KAAK,MAAM;AAAA,EAC/G;AAAA,EACA,UAAU;AACR,WAAO,EAAE,sBAAsB,KAAK,WAAW,sBAAsB,EAAE;AAAA,EACzE;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,iBAAiB,KAAK;AAAA,MACtB,OAAO,KAAK;AAAA,MACZ,QAAQ,KAAK;AAAA,MACb,MAAM,KAAK;AAAA,IACb;AAAA,EACF;AACF;AACA,WAAW,YAAY;AACvB,sBAAsB,cAAc,UAAU;AAC9C,SAAS,MAAMF,SAAQ;AACrB,MAAIA,QAAO,cAAc,QAAQA,QAAO,SAAS,MAAM;AACrD,UAAM,IAAI,MAAM,8HAA8H;AAAA,EAChJ;AACA,MAAIA,QAAO,cAAc,QAAQA,QAAO,SAAS,MAAM;AACrD,UAAM,IAAI,WAAW,kFAAkF;AAAA,EACzG;AACA,MAAI,aAAaA,QAAO;AACxB,MAAIA,QAAO,SAAS,QAAQ,cAAc,MAAM;AAC9C,iBAAa,CAAC,IAAI,EAAE,OAAOA,QAAO,KAAK;AAAA,EACzC;AACA,MAAI,QAAQA,QAAO;AACnB,MAAI,SAAS,MAAM;AACjB,YAAQ;AAAA,EACV;AACA,QAAM,cAAc,IAAI,WAAW;AAAA,IACjC,iBAAiB;AAAA,IACjB,MAAMA,QAAO;AAAA,IACb;AAAA,IACA,QAAQA,QAAO;AAAA,EACjB,CAAC;AACD,QAAM,UAAU,YAAY,aAAa,GAAG;AAC5C,SAAO,QAAQ;AACjB;AAGA,SAAS,wBAAwB,KAAK,KAAK;AACzC,MAAI,IAAI,SAAS,QAAQ,IAAI,UAAU,IAAI,OAAO;AAChD,WAAO;AAAA,EACT;AACA,MAAI;AACF,WAAO,KAAK,KAAK,IAAI,KAAK;AAAA,EAC5B,SAAS,KAAP;AACA,UAAM,IAAI,WAAW,0BAA0B,IAAI,mDAAmD,IAAI,UAAU,IAAI,SAAS;AAAA,EACnI;AACF;AACA,IAAI,WAAW,MAAM;AAAA,EACnB,YAAY,OAAO;AACjB,SAAK,WAAW,CAAC;AACjB,SAAK,UAAU,CAAC;AAChB,SAAK,UAAU,CAAC;AAChB,QAAI,iBAAiB,UAAU;AAC7B,iBAAW,MAAM,MAAM,UAAU;AAC/B,aAAK,SAAS,MAAM,MAAM,SAAS;AACnC,YAAI,MAAM,MAAM,SAAS;AACvB,eAAK,QAAQ,MAAM,MAAM,QAAQ;AAAA,QACnC;AAAA,MACF;AAAA,IACF,OAAO;AACL,UAAI,SAAS,MAAM;AACjB;AAAA,MACF;AACA,iBAAW,QAAQ,OAAO;AACxB,aAAK,IAAI,KAAK,KAAK,KAAK,KAAK;AAAA,MAC/B;AAAA,IACF;AAAA,EACF;AAAA,EACA,IAAI,KAAK,OAAOT,OAAM;AACpB,QAAI,KAAK,SAAS,IAAI,OAAO,MAAM;AACjC,WAAK,SAAS,IAAI,MAAM,wBAAwB,KAAK,KAAK;AAC1D,WAAK,QAAQ,IAAI,QAAQ,IAAI;AAC7B,UAAIA,SAAQ,MAAM;AAChB,aAAK,QAAQ,IAAI,MAAMA;AAAA,MACzB;AAAA,IACF,OAAO;AACL,YAAM,IAAI,WAAW,uBAAuB,IAAI,YAAY,IAAI,IAAI;AAAA,IACtE;AACA,WAAO;AAAA,EACT;AAAA,EACA,QAAQ,MAAM;AACZ,SAAK,IAAI,KAAK,KAAK,KAAK,KAAK;AAAA,EAC/B;AAAA,EACA,OAAO,KAAK;AACV,WAAO,KAAK,SAAS,IAAI,OAAO;AAAA,EAClC;AAAA,EACA,QAAQ;AACN,WAAO,OAAO,KAAK,KAAK,OAAO;AAAA,EACjC;AAAA,EACA,SAAS,KAAK;AACZ,QAAI,eAAe,gBAAgB;AACjC,UAAI,KAAK,SAAS,IAAI,OAAO,MAAM;AACjC,cAAM,IAAI,WAAW,oBAAoB,IAAI,MAAM;AAAA,MACrD,OAAO;AACL,eAAO,KAAK,SAAS,IAAI;AAAA,MAC3B;AAAA,IACF,OAAO;AACL,YAAM,KAAK,KAAK,QAAQ;AACxB,UAAI,MAAM,MAAM;AACd,cAAM,IAAI,WAAW,yCAAyC,KAAK;AAAA,MACrE;AACA,aAAO,KAAK,SAAS;AAAA,IACvB;AAAA,EACF;AAAA,EACA,QAAQ,KAAK;AACX,QAAI,eAAe,gBAAgB;AACjC,UAAI,KAAK,SAAS,IAAI,OAAO,MAAM;AACjC,cAAM,IAAI,WAAW,oBAAoB,IAAI,MAAM;AAAA,MACrD,OAAO;AACL,eAAO,KAAK,QAAQ,IAAI;AAAA,MAC1B;AAAA,IACF,OAAO;AACL,YAAM,KAAK,KAAK,QAAQ;AACxB,UAAI,MAAM,MAAM;AACd,cAAM,IAAI,WAAW,yCAAyC,KAAK;AAAA,MACrE;AACA,aAAO,KAAK,QAAQ;AAAA,IACtB;AAAA,EACF;AAAA,EACA,eAAe;AACb,QAAI,KAAK,WAAW,MAAM;AACxB,cAAQ,KAAK,OAAO;AAAA,IACtB;AAAA,EACF;AACF;AACA,IAAI,eAAe,IAAI,SAAS;AAChC,IAAI,wBAAwB,IAAI,SAAS;AACzC,SAAS,sBAAsB,YAAY;AACzC,MAAI,gBAAgB,MAAM;AACxB,iBAAa,cAAc,UAAU;AAAA,EACvC;AACA,MAAI,yBAAyB,MAAM;AACjC,0BAAsB,cAAc,UAAU;AAAA,EAChD;AACF;AACA,SAAS,QAAQ,SAAS,UAAU,QAAQ,OAAO;AACjD,QAAM,WAAW,UAAU,OAAO,QAAQ,OAAO;AACjD,QAAM,eAAe,MAAM,QAAQ,OAAO;AAC1C,QAAM,aAAa,eAAe,UAAU,CAAC,OAAO;AACpD,QAAM,cAAc,WAAW,IAAI,CAAC,OAAO,GAAG,IAAI;AAClD,QAAM,eAAe,CAAC;AACtB,QAAM,YAAY,SAAS,MAAM;AACjC,aAAW,cAAc,aAAa;AACpC,QAAI,UAAU,QAAQ,UAAU,MAAM,IAAI;AACxC,mBAAa,KAAK,SAAS,SAAS,UAAU,CAAC;AAAA,IACjD,OAAO;AACL,mBAAa,KAAK,IAAI;AAAA,IACxB;AAAA,EACF;AACA,MAAI,SAAS,MAAM;AACjB,UAAM,gBAAgB;AACtB,UAAM,gBAAgB;AAAA,EACxB;AACA,QAAM,kBAAkB,YAAY,KAAK,GAAG,IAAI,MAAM,SAAS,MAAM,EAAE,KAAK,EAAE,KAAK,GAAG;AACtF,MAAI,SAAS,aAAa,IAAI,eAAe;AAC7C,MAAI;AACJ,MAAI,UAAU,MAAM;AAClB,UAAM,MAAM,qCAAqC,YAAY,QAAQ;AACrE,aAAS,IAAI;AACb,sBAAkB,IAAI;AACtB,iBAAa,IAAI,iBAAiB,MAAM;AACxC,0BAAsB,IAAI,iBAAiB,eAAe;AAAA,EAC5D;AACA,oBAAkB,CAAC;AACnB,MAAI,CAAC,UAAU;AACb,WAAO,OAAO,iBAAiB,sBAAsB,IAAI,eAAe,CAAC;AAAA,EAC3E;AACA,QAAM,mBAAmB,IAAI,SAAS,QAAQ;AAC9C,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,QAAI,SAAS,MAAM;AACjB,YAAM,aAAa,OAAO,EAAE;AAC5B,UAAI,aAAa,MAAM,eAAe;AACpC,cAAM,gBAAgB;AAAA,MACxB;AACA,UAAI,aAAa,MAAM,eAAe;AACpC,cAAM,gBAAgB;AAAA,MACxB;AAAA,IACF;AACA,UAAM,WAAW,OAAO;AACxB,UAAM,WAAW,SAAS;AAC1B,QAAI,oBAAoB,YAAY;AAClC;AAAA,IACF;AACA,UAAM,cAAc,CAAC;AACrB,UAAM,aAAa,CAAC;AACpB,UAAM,mBAAmB,CAAC;AAC1B,QAAI,aAAa;AACjB,eAAW,UAAU,SAAS,QAAQ;AACpC,YAAM,QAAQ,iBAAiB,SAAS,MAAM;AAC9C,YAAMA,QAAO,iBAAiB,QAAQ,MAAM;AAC5C,kBAAY,KAAK,KAAK;AACtB,iBAAW,KAAKA,KAAI;AACpB,UAAIA,SAAQ,MAAM;AAChB,qBAAa;AAAA,MACf;AACA,UAAI,CAAC,UAAU;AACb,wBAAgB,OAAO;AACvB,YAAI,gBAAgB,OAAO,UAAU,KAAK,CAAC,SAAS,OAAO,MAAM,KAAK,YAAY,QAAQ,OAAO,IAAI,MAAM,MAAM,CAAC,MAAM,cAAc,OAAO,YAAY,aAAa,MAAM;AAC1K,2BAAiB,KAAK,KAAK;AAAA,QAC7B;AAAA,MACF;AAAA,IACF;AACA,QAAI,YAAY;AACd,eAAS,UAAU,CAAC;AACpB,aAAO,UAAU,WAAW;AAAA,IAC9B;AACA,UAAM,gBAAgB,OAAO,SAAS,MAAM,aAAa,MAAM,CAAC;AAChE,QAAI,aAAa;AACjB,QAAI,SAAS,iBAAiB;AAC5B,mBAAa,SAAS,YAAY,aAAa,UAAU;AAAA,IAC3D;AACA,UAAM,eAAe,eAAe,QAAQ;AAC5C,UAAM,wBAAwB,MAAM,QAAQ,YAAY,IAAI,eAAe,CAAC,YAAY;AACxF,aAAS,KAAK,GAAG,KAAK,sBAAsB,QAAQ,EAAE,IAAI;AACxD,UAAI,CAAC,iBAAiB,OAAO,sBAAsB,GAAG,GAAG;AACvD,yBAAiB,IAAI,sBAAsB,KAAK,cAAc,KAAK,MAAM,QAAQ,UAAU,IAAI,WAAW,KAAK,UAAU;AAAA,MAC3H;AACA,YAAMI,SAAQ,YAAY,QAAQ,sBAAsB,IAAI,IAAI;AAChE,UAAIA,WAAU,IAAI;AAChB,qBAAaA,UAAS,cAAc;AAAA,MACtC;AAAA,IACF;AACA,QAAI,CAAC,UAAU;AACb,cAAQ,gBAAgB;AAAA,IAC1B;AAAA,EACF;AACA,mBAAiB,aAAa;AAC9B,SAAO,eAAe,eAAe,aAAa;AACpD;AACA,SAAS,qCAAqC,SAAS,UAAU;AAC/D,eAAa,OAAO,WAAW,QAAQ,QAAQ,SAAS,GAAG,MAAM,uCAAuC;AACxG,MAAI,cAAc,CAAC;AACnB,MAAI,oBAAoB,CAAC;AACzB,MAAI,QAAQ,WAAW,GAAG;AACxB,UAAM,MAAM,gDAAgD,QAAQ,IAAI,QAAQ;AAChF,kBAAc,IAAI;AAClB,wBAAoB,IAAI;AAAA,EAC1B,OAAO;AACL,UAAM,UAA0B,oBAAI,IAAI;AACxC,eAAW,UAAU,SAAS;AAC5B,YAAM,EAAE,QAAQ,aAAa,IAAI,gDAAgD,QAAQ,QAAQ;AACjG,iBAAW,kBAAkB,QAAQ;AACnC,YAAI,CAAC,QAAQ,IAAI,eAAe,IAAI,GAAG;AACrC,sBAAY,KAAK,cAAc;AAC/B,kBAAQ,IAAI,eAAe,IAAI;AAAA,QACjC;AAAA,MACF;AACA,iBAAW,QAAQ,cAAc;AAC/B,YAAI,kBAAkB,SAAS,MAAM;AACnC,4BAAkB,QAAwB,oBAAI,IAAI;AAAA,QACpD;AACA,qBAAa,MAAM,QAAQ,CAAC,cAAc,kBAAkB,MAAM,IAAI,SAAS,CAAC;AAAA,MAClF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AAAA,IACL,QAAQ;AAAA,IACR,iBAAiB,oBAAoB,iBAAiB;AAAA,EACxD;AACF;AACA,SAAS,oBAAoB,cAAc;AACzC,QAAM,kBAAkB,CAAC;AACzB,aAAW,QAAQ,cAAc;AAC/B,oBAAgB,QAAQ,aAAa,MAAM;AAAA,EAC7C;AACA,SAAO;AACT;AACA,SAAS,gDAAgD,QAAQ,UAAU;AACzE,QAAM,UAA0B,oBAAI,IAAI;AACxC,QAAM,SAAS,CAAC;AAChB,QAAM,eAAe,CAAC;AACtB,aAAW,OAAO,SAAS,MAAM,GAAG;AAClC,YAAQ,IAAI,GAAG;AAAA,EACjB;AACA,QAAM,SAAS,CAAC;AAChB,QAAM,QAAQ,CAAC;AACf,SAAO,KAAK,MAAM;AAClB,SAAO,OAAO,SAAS,GAAG;AACxB,UAAM,MAAM,OAAO,OAAO,SAAS;AACnC,QAAI,QAAQ,IAAI,IAAI,IAAI,GAAG;AACzB,aAAO,IAAI;AACX;AAAA,IACF;AACA,UAAM,cAAc,MAAM,MAAM,SAAS,OAAO,OAAO,SAAS;AAChE,QAAI,IAAI,OAAO,WAAW,KAAK,aAAa;AAC1C,aAAO,IAAI;AACX,aAAO,KAAK,GAAG;AACf,cAAQ,IAAI,IAAI,IAAI;AACpB,UAAI,aAAa;AACf,cAAM,IAAI;AAAA,MACZ;AAAA,IACF,OAAO;AACL,YAAM,KAAK,OAAO,SAAS,CAAC;AAC5B,iBAAW,UAAU,IAAI,QAAQ;AAC/B,YAAI,aAAa,OAAO,SAAS,MAAM;AACrC,uBAAa,OAAO,QAAwB,oBAAI,IAAI;AAAA,QACtD;AACA,qBAAa,OAAO,MAAM,IAAI,IAAI,IAAI;AACtC,YAAI,QAAQ,IAAI,OAAO,IAAI,GAAG;AAC5B;AAAA,QACF;AACA,eAAO,KAAK,MAAM;AAAA,MACpB;AAAA,IACF;AAAA,EACF;AACA,SAAO,EAAE,QAAQ,aAAa;AAChC;AACA,SAAS,eAAe,QAAQ;AAC9B,MAAI;AACJ,MAAI,OAAO,YAAY,aAAa,WAAW,GAAG;AAChD,mBAAe,OAAO,YAAY;AAAA,EACpC,OAAO;AACL,QAAI,YAAY;AAChB,aAAS,KAAK,GAAG,KAAK,OAAO,YAAY,aAAa,QAAQ,EAAE,IAAI;AAClE,iBAAW,gBAAgB,OAAO,YAAY,aAAa,IAAI,eAAe;AAC5E,YAAI,aAAa,OAAO,OAAO,IAAI;AACjC,sBAAY;AACZ;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,mBAAe,OAAO,YAAY,YAAY,SAAS;AAAA,EACzD;AACA,SAAO;AACT;AAGA,IAAI,OAAO,IAAI;AACf,KAAK,aAAa,sCAAsC,MAAM,KAAK,qBAAqB;AAGxF,IAAI,8BAA8B,CAAC;AACnCZ,UAAS,6BAA6B;AAAA,EACpC,SAAS,MAAM;AAAA,EACf,YAAY,MAAM;AAAA,EAClB,QAAQ,MAAM;AAAA,EACd,UAAU,MAAM;AAClB,CAAC;AAGD,SAAS,YAAY,GAAG,MAAM;AAC5B,SAAO,KAAK,MAAM,KAAK,KAAK,IAAI,GAAG,CAAC,GAAG,MAAM,IAAI,CAAC,CAAC;AACrD;AACA,IAAI,aAAa,cAAc,sBAAsB,aAAa;AAAA,EAChE,YAAY;AACV,WAAO,CAAC;AAAA,EACV;AACF;AACA,IAAI,UAAU,cAAc,WAAW;AAAA,EACrC,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,kBAAkB;AACvB,SAAK,cAAc;AACnB,SAAK,WAAW,KAAK,YAAY,OAAO,KAAK,WAAW,KAAK;AAC7D,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,OAAO,KAAK;AAAA,EACnD;AAAA,EACA,MAAM,GAAG;AACP,WAAO,KAAK,MAAM;AAChB,YAAM,QAAQ,YAAY,GAAG,KAAK,IAAI;AACtC,YAAM,UAAU,YAAY,OAAO,GAAG,KAAK,QAAQ;AACnD,aAAO,IAAI,GAAG,IAAI,SAAS,KAAK,QAAQ,GAAG,KAAK,CAAC,CAAC;AAAA,IACpD,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,WAAO,EAAE,UAAU,KAAK,UAAU,MAAM,KAAK,KAAK;AAAA,EACpD;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,WAAW,cAAc,WAAW;AAAA,EACtC,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,cAAc;AACnB,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,OAAO,KAAK;AAAA,EACnD;AAAA,EACA,MAAM,GAAG;AACP,WAAO,KAAK,MAAM,IAAI,GAAG,KAAK,QAAQ,GAAG,YAAY,GAAG,KAAK,IAAI,CAAC,CAAC,CAAC;AAAA,EACtE;AAAA,EACA,YAAY;AACV,WAAO,EAAE,MAAM,KAAK,KAAK;AAAA,EAC3B;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,SAAS,cAAc,WAAW;AAAA,EACpC,MAAM,GAAG;AACP,WAAO,KAAK,CAAC;AAAA,EACf;AACF;AACA,OAAO,YAAY;AACnB,sBAAsB,cAAc,MAAM;AAC1C,IAAI,aAAa,cAAc,WAAW;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AACvB,SAAK,cAAc;AACnB,SAAK,cAAc;AACnB,SAAK,WAAW,KAAK,YAAY,OAAO,KAAK,WAAW,KAAK;AAC7D,SAAK,WAAW,KAAK,YAAY,OAAO,KAAK,WAAW,KAAK;AAC7D,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,OAAO,KAAK;AACjD,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,OAAO,KAAK;AAAA,EACnD;AAAA,EACA,MAAM,GAAG;AACP,WAAO,KAAK,MAAM;AAChB,YAAM,QAAQ,YAAY,GAAG,KAAK,IAAI;AACtC,YAAM,UAAU,KAAK,IAAI,KAAK,MAAM,YAAY,OAAO,KAAK,UAAU,KAAK,QAAQ,CAAC,GAAG,IAAI,IAAI,KAAK,MAAM,KAAK,CAAC;AAChH,aAAO,IAAI,GAAG,IAAI,SAAS,KAAK,QAAQ,GAAG,KAAK,CAAC,CAAC;AAAA,IACpD,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,WAAO;AAAA,MACL,UAAU,KAAK;AAAA,MACf,UAAU,KAAK;AAAA,MACf,MAAM,KAAK;AAAA,MACX,MAAM,KAAK;AAAA,IACb;AAAA,EACF;AACF;AACA,WAAW,YAAY;AACvB,sBAAsB,cAAc,UAAU;AAC9C,IAAI,4CAA4C;AAAA,EAC9C,WAAW;AAAA,EACX,cAAc;AAAA,EACd,UAAU;AAAA,EACV,YAAY;AACd;AACA,SAAS,oBAAoB,YAAY;AACvC,SAAO,qBAAqB,UAAU;AACxC;AACA,SAAS,sBAAsBiB,SAAQ,gBAAgB,CAAC,GAAG;AACzD,SAAO,uBAAuBA,SAAQ,sBAAsB,iBAAiB,OAAO,EAAE,cAAc,eAAe,YAAY;AACjI;AACA,SAAS,cAAc,YAAY;AACjC,MAAI,cAAc,MAAM;AACtB,WAAO;AAAA,EACT;AACA,MAAI,OAAO,eAAe,UAAU;AAClC,UAAM,YAAY,cAAc,4CAA4C,0CAA0C,cAAc;AACpI,UAAMA,UAAS,EAAE,WAAW,QAAQ,CAAC,EAAE;AACvC,WAAO,sBAAsBA,OAAM;AAAA,EACrC,WAAW,sBAAsB,YAAY;AAC3C,WAAO;AAAA,EACT,OAAO;AACL,WAAO,sBAAsB,UAAU;AAAA,EACzC;AACF;AAGA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,SAAS;AAChB,SAAO,IAAI,OAAO;AACpB;AACA,SAAS,WAAWA,SAAQ;AAC1B,SAAO,IAAI,WAAWA,OAAM;AAC9B;AAGA,IAAI,+BAA+B,CAAC;AACpCjB,UAAS,8BAA8B;AAAA,EACrC,UAAU,MAAM;AAAA,EAChB,cAAc,MAAM;AAAA,EACpB,eAAe,MAAM;AAAA,EACrB,UAAU,MAAM;AAAA,EAChB,WAAW,MAAM;AAAA,EACjB,UAAU,MAAM;AAAA,EAChB,aAAa,MAAM;AAAA,EACnB,cAAc,MAAM;AAAA,EACpB,MAAM,MAAM;AAAA,EACZ,YAAY,MAAM;AAAA,EAClB,cAAc,MAAM;AAAA,EACpB,eAAe,MAAM;AAAA,EACrB,iBAAiB,MAAM;AAAA,EACvB,iBAAiB,MAAM;AAAA,EACvB,OAAO,MAAM;AACf,CAAC;AACD,SAAS,SAAS;AAChB,SAAO,IAAI,MAAM;AACnB;AACA,SAAS,QAAQ;AACf,SAAO,IAAI,KAAK;AAClB;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,eAAe,MAAM;AAC5B,SAAO,IAAI,cAAc,IAAI;AAC/B;AACA,SAAS,cAAc,MAAM;AAC3B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,UAAU,IAAI;AAC3B;AACA,SAAS,gBAAgBiB,SAAQ;AAC/B,SAAO,IAAI,gBAAgBA,OAAM;AACnC;AACA,SAAS,cAAc,MAAM;AAC3B,SAAO,IAAI,cAAc,IAAI;AAC/B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,UAAU,MAAM;AACvB,SAAO,IAAI,UAAU,IAAI;AAC3B;AACA,SAAS,YAAY,MAAM;AACzB,SAAO,IAAI,YAAY,IAAI;AAC7B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,WAAW,MAAM;AACxB,SAAO,IAAI,WAAW,IAAI;AAC5B;AAGA,IAAI,yBAAyB,CAAC;AAC9BjB,UAAS,wBAAwB;AAAA,EAC/B,OAAO,MAAM;AAAA,EACb,KAAK,MAAM;AAAA,EACX,SAAS,MAAM;AAAA,EACf,YAAY,MAAM;AAAA,EAClB,KAAK,MAAM;AAAA,EACX,cAAc,MAAM;AAAA,EACpB,SAAS,MAAM;AAAA,EACf,kBAAkB,MAAM;AAAA,EACxB,kBAAkB,MAAM;AAAA,EACxB,kBAAkB,MAAM;AAAA,EACxB,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,cAAc,MAAM;AAAA,EACpB,cAAc,MAAM;AAAA,EACpB,cAAc,MAAM;AAAA,EACpB,oBAAoB,MAAM;AAAA,EAC1B,eAAe,MAAM;AAAA,EACrB,aAAa,MAAM;AAAA,EACnB,QAAQ,MAAM;AAAA,EACd,QAAQ,MAAM;AAAA,EACd,iBAAiB,MAAM;AAAA,EACvB,QAAQ,MAAM;AAAA,EACd,iBAAiB,MAAM;AAAA,EACvB,YAAY,MAAM;AAAA,EAClB,gBAAgB,MAAM;AAAA,EACtB,YAAY,MAAM;AAAA,EAClB,OAAO,MAAM;AAAA,EACb,iBAAiB,MAAM;AAAA,EACvB,KAAK,MAAM;AAAA,EACX,SAAS,MAAM;AAAA,EACf,KAAK,MAAM;AAAA,EACX,WAAW,MAAM;AAAA,EACjB,SAAS,MAAM;AAAA,EACf,iBAAiB,MAAM;AAAA,EACvB,eAAe,MAAM;AAAA,EACrB,wBAAwB,MAAM;AAAA,EAC9B,wBAAwB,MAAM;AAAA,EAC9B,iBAAiB,MAAM;AAAA,EACvB,iBAAiB,MAAM;AAAA,EACvB,oBAAoB,MAAM;AAAA,EAC1B,oBAAoB,MAAM;AAAA,EAC1B,KAAK,MAAM;AAAA,EACX,SAAS,MAAM;AAAA,EACf,OAAO,MAAM;AAAA,EACb,YAAY,MAAM;AAAA,EAClB,oBAAoB,MAAM;AAAA,EAC1B,WAAW,MAAM;AAAA,EACjB,MAAM,MAAM;AAAA,EACZ,UAAU,MAAM;AAAA,EAChB,SAAS,MAAM;AAAA,EACf,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,cAAc,MAAM;AAAA,EACpB,cAAc,MAAM;AAAA,EACpB,cAAc,MAAM;AAAA,EACpB,SAAS,MAAM;AAAA,EACf,SAAS,MAAM;AAAA,EACf,UAAU,MAAM;AAAA,EAChB,SAAS,MAAM;AAAA,EACf,OAAO,MAAM;AAAA,EACb,MAAM,MAAM;AAAA,EACZ,cAAc,MAAM;AAAA,EACpB,SAAS,MAAM;AAAA,EACf,KAAK,MAAM;AAAA,EACX,iBAAiB,MAAM;AAAA,EACvB,WAAW,MAAM;AAAA,EACjB,eAAe,MAAM;AAAA,EACrB,SAAS,MAAM;AAAA,EACf,kBAAkB,MAAM;AAAA,EACxB,iBAAiB,MAAM;AAAA,EACvB,iBAAiB,MAAM;AAAA,EACvB,iBAAiB,MAAM;AAAA,EACvB,cAAc,MAAM;AAAA,EACpB,eAAe,MAAM;AACvB,CAAC;AAGD,eAAe,qBAAqB,MAAM;AACxC,MAAI,QAAQ,MAAM;AAChB;AAAA,EACF;AACA,QAAM,WAAW,CAAC;AAClB,QAAM,OAAO,CAAC;AACd,QAAM,mBAAmB,CAAC;AAC1B,aAAW,OAAO,MAAM;AACtB,UAAM,QAAQ,KAAK;AACnB,QAAI,OAAO,UAAU,UAAU;AAC7B,YAAM,cAAc;AACpB,eAAS,KAAK,YAAY,KAAK,CAAC;AAChC,WAAK,KAAK,GAAG;AACb,uBAAiB,KAAK,WAAW;AAAA,IACnC;AAAA,EACF;AACA,MAAI,SAAS,SAAS,GAAG;AACvB,UAAM,SAAS,MAAM,QAAQ,IAAI,QAAQ;AACzC,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,WAAK,KAAK,OAAO,OAAO,IAAI;AAAA,IAC9B;AACA,YAAQ,gBAAgB;AAAA,EAC1B;AACF;AACA,SAAS,qBAAqB,MAAM;AAClC,MAAI,QAAQ,MAAM;AAChB;AAAA,EACF;AACA,aAAW,OAAO,MAAM;AACtB,UAAM,QAAQ,KAAK;AACnB,QAAI,OAAO,UAAU,UAAU;AAC7B,YAAM,QAAQ;AAAA,IAChB;AAAA,EACF;AACF;AAGA,IAAI;AAAA,CACH,SAAS,wBAAwB;AAChC,yBAAuB,uBAAuB,YAAY,KAAK;AAC/D,yBAAuB,uBAAuB,aAAa,KAAK;AAClE,GAAG,0BAA0B,wBAAwB,CAAC,EAAE;AACxD,IAAI,yBAAyB;AAC7B,IAAI,eAAe,MAAM;AAAA,EACvB,cAAc;AACZ,SAAK,iBAAiB;AAAA,EACxB;AAAA,EACA,UAAU,QAAQ;AAChB,SAAK,SAAS;AAAA,EAChB;AAAA,EACA,MAAM,aAAa,OAAO,MAAM;AAAA,EAChC;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAAA,EAC9B;AAAA,EACA,MAAM,aAAa,OAAO,MAAM;AAAA,EAChC;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAAA,EAC9B;AAAA,EACA,MAAM,aAAa,MAAM;AAAA,EACzB;AAAA,EACA,MAAM,WAAW,MAAM;AAAA,EACvB;AAAA,EACA,SAASgC,SAAQ;AAAA,EACjB;AACF;AACA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,YAAY,cAAc,IAAI;AACxC,QAAI,cAAc,MAAM;AACtB,mBAAa,CAAC;AAAA,IAChB;AACA,SAAK,YAAY;AACjB,SAAK,cAAc;AAAA,EACrB;AAAA,EACA,OAAO,UAAU;AACf,SAAK,UAAU,KAAK,QAAQ;AAAA,EAC9B;AAAA,EACA,UAAU,QAAQ;AAChB,eAAW,YAAY,KAAK,WAAW;AACrC,eAAS,UAAU,MAAM;AAAA,IAC3B;AAAA,EACF;AAAA,EACA,SAASA,SAAQ;AACf,eAAW,YAAY,KAAK,WAAW;AACrC,eAAS,SAASA,OAAM;AAAA,IAC1B;AAAA,EACF;AAAA,EACA,MAAM,aAAa,OAAO,MAAM;AAC9B,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,eAAW,YAAY,KAAK,WAAW;AACrC,YAAM,SAAS,aAAa,OAAO,IAAI;AAAA,IACzC;AAAA,EACF;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,eAAW,YAAY,KAAK,WAAW;AACrC,YAAM,SAAS,WAAW,OAAO,IAAI;AAAA,IACvC;AAAA,EACF;AAAA,EACA,MAAM,aAAa,OAAO,MAAM;AAC9B,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,eAAW,YAAY,KAAK,WAAW;AACrC,YAAM,SAAS,aAAa,OAAO,IAAI;AAAA,IACzC;AAAA,EACF;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,eAAW,YAAY,KAAK,WAAW;AACrC,YAAM,SAAS,WAAW,OAAO,IAAI;AAAA,IACvC;AAAA,EACF;AAAA,EACA,MAAM,aAAa,MAAM;AACvB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,eAAW,YAAY,KAAK,WAAW;AACrC,YAAM,SAAS,aAAa,IAAI;AAAA,IAClC;AAAA,EACF;AAAA,EACA,MAAM,WAAW,MAAM;AACrB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,eAAW,YAAY,KAAK,WAAW;AACrC,YAAM,SAAS,WAAW,IAAI;AAAA,IAChC;AAAA,EACF;AACF;AACA,IAAI,aAAa,cAAc,aAAa;AAAA,EAC1C,cAAc;AACZ,UAAM;AAAA,EACR;AAAA,EACA,MAAM,aAAa,OAAO;AACxB,SAAK,OAAO;AACZ,SAAK,SAAS,CAAC;AAAA,EACjB;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,UAAM,YAAY,KAAK,WAAW,OAAO,IAAI,KAAK;AAClD,SAAK,QAAQ;AACb,eAAW,OAAO,MAAM;AACtB,YAAM,QAAQ,KAAK;AACnB,UAAI,OAAO,UAAU,UAAU;AAC7B,YAAI,CAAC,KAAK,OAAO,eAAe,GAAG,GAAG;AACpC,eAAK,OAAO,OAAO;AAAA,QACrB;AACA,aAAK,OAAO,OAAO,KAAK,OAAO,OAAO,QAAQ;AAAA,MAChD,OAAO;AACL,YAAI;AACJ,YAAI,OAAO,KAAK,QAAQ;AACtB,+BAAqB,KAAK,OAAO;AAAA,QACnC,OAAO;AACL,eAAK,OAAO,OAAO;AAAA,QACrB;AACA,cAAM,QAAQ,KAAK,MAAM,KAAK,KAAK,OAAO,MAAM,IAAI,OAAO,SAAS,CAAC,CAAC;AACtE,aAAK,OAAO,OAAO;AACnB,YAAI,sBAAsB,MAAM;AAC9B,6BAAmB,QAAQ;AAAA,QAC7B;AAAA,MACF;AAAA,IACF;AAAA,EACF;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,QAAI,QAAQ,MAAM;AAChB,iBAAW,OAAO,KAAK,OAAO,YAAY;AACxC,YAAI,KAAK,OAAO,QAAQ,MAAM;AAC5B;AAAA,QACF;AACA,YAAI,OAAO,KAAK,OAAO,SAAS,UAAU;AACxC,eAAK,OAAO,KAAK,OAAO,OAAO,KAAK;AAAA,QACtC,OAAO;AACL,eAAK,MAAM;AACT,kBAAM,OAAO,IAAI,IAAI,GAAG,KAAK,IAAI,GAAG,KAAK,OAAO,IAAI;AACpD,iBAAK,OAAO;AACZ,iBAAK,OAAO,KAAK,QAAQ;AACzB,iBAAK,KAAK,IAAI;AAAA,UAChB,CAAC;AAAA,QACH;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACF;AACA,IAAI,UAAU,cAAc,aAAa;AAAA,EACvC,MAAM,aAAa,MAAM;AACvB,SAAK,QAAQ,CAAC;AACd,SAAK,UAAU,CAAC;AAAA,EAClB;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,SAAK,MAAM,KAAK,KAAK;AACrB,eAAW,OAAO,MAAM;AACtB,UAAI,KAAK,QAAQ,QAAQ,MAAM;AAC7B,aAAK,QAAQ,OAAO,CAAC;AAAA,MACvB;AACA,WAAK,QAAQ,KAAK,KAAK,KAAK,IAAI;AAAA,IAClC;AAAA,EACF;AAAA,EACA,MAAM,WAAW;AACf,UAAM,WAAW,CAAC;AAClB,UAAM,OAAO,CAAC;AACd,UAAM,UAAU,CAAC;AACjB,eAAW,OAAO,KAAK,SAAS;AAC9B,YAAM,aAAa,KAAK,QAAQ;AAChC,eAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,YAAI,OAAO,WAAW,QAAQ,UAAU;AACtC,gBAAM,cAAc,WAAW;AAC/B,mBAAS,KAAK,YAAY,KAAK,CAAC;AAChC,eAAK,KAAK,GAAG;AACb,kBAAQ,KAAK,EAAE;AAAA,QACjB;AAAA,MACF;AAAA,IACF;AACA,UAAM,SAAS,MAAM,QAAQ,IAAI,QAAQ;AACzC,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,YAAM,kBAAkB,KAAK,QAAQ,KAAK,KAAK,QAAQ;AACvD,sBAAgB,QAAQ;AACxB,WAAK,QAAQ,KAAK,KAAK,QAAQ,OAAO,OAAO,IAAI;AAAA,IACnD;AAAA,EACF;AACF;AACA,IAAI,iBAAiB,cAAc,aAAa;AAAA,EAC9C,YAAY,MAAM,YAAY;AAC5B,UAAM;AACN,SAAK,eAAe;AACpB,SAAK,UAAU,KAAK;AACpB,SAAK,gBAAgB,KAAK,iBAAiB;AAC3C,SAAK,aAAa,cAAc;AAChC,QAAI,KAAK,eAAe,QAAQ;AAC9B,WAAK,aAAa;AAAA,IACpB;AACA,QAAI,KAAK,eAAe,WAAW,KAAK,WAAW,MAAM;AACvD,YAAM,IAAI,MAAM,iHAAiH;AAAA,IACnI;AACA,QAAI,aAAa,SAAS,KAAK,UAAU,GAAG;AAC1C,WAAK,YAAY,SAAS,KAAK,UAAU,KAAK,IAAI,GAAG,KAAK,YAAY,KAAK,OAAO;AAAA,IACpF;AACA,SAAK,aAAa,KAAK;AACvB,SAAK,WAAW,KAAK;AACrB,SAAK,aAAa,KAAK;AACvB,SAAK,WAAW,KAAK;AACrB,SAAK,aAAa,KAAK;AACvB,SAAK,WAAW,KAAK;AACrB,SAAK,QAAQ,KAAK;AAAA,EACpB;AAAA,EACA,MAAM,UAAU,OAAO,OAAO,MAAM;AAClC,UAAM,KAAK,CAAC;AACZ,QAAI,KAAK,SAAS,MAAM;AACtB,YAAM,qBAAqB,IAAI;AAC/B,SAAG,KAAK,KAAK,MAAM,OAAO,OAAO,IAAI,CAAC;AAAA,IACxC;AACA,OAAG,KAAK,KAAK,cAAc,CAAC;AAC5B,UAAM,QAAQ,IAAI,EAAE;AAAA,EACtB;AAAA,EACA,MAAM,aAAa,OAAO,MAAM;AAC9B,SAAK,eAAe;AACpB,QAAI,KAAK,cAAc,MAAM;AAC3B,YAAM,qBAAqB,IAAI;AAC/B,YAAM,KAAK,WAAW,OAAO,IAAI;AAAA,IACnC;AAAA,EACF;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,UAAM,KAAK,CAAC;AACZ,QAAI,KAAK,YAAY,MAAM;AACzB,YAAM,qBAAqB,IAAI;AAC/B,SAAG,KAAK,KAAK,SAAS,OAAO,IAAI,CAAC;AAAA,IACpC;AACA,QAAI,KAAK,eAAe,SAAS;AAC/B,SAAG,KAAK,KAAK,cAAc,CAAC;AAAA,IAC9B;AACA,UAAM,QAAQ,IAAI,EAAE;AAAA,EACtB;AAAA,EACA,MAAM,aAAa,OAAO,MAAM;AAC9B,QAAI,KAAK,cAAc,MAAM;AAC3B,YAAM,qBAAqB,IAAI;AAC/B,YAAM,KAAK,WAAW,OAAO,IAAI;AAAA,IACnC;AAAA,EACF;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,UAAM,KAAK,CAAC;AACZ,QAAI,KAAK,YAAY,MAAM;AACzB,YAAM,qBAAqB,IAAI;AAC/B,SAAG,KAAK,KAAK,SAAS,OAAO,IAAI,CAAC;AAAA,IACpC;AACA,QAAI,KAAK,eAAe,SAAS;AAC/B,SAAG,KAAK,KAAK,cAAc,CAAC;AAAA,IAC9B,WAAW,aAAa,SAAS,KAAK,UAAU,GAAG;AACjD,SAAG,KAAK,KAAK,UAAU,KAAK,cAAc,OAAO,IAAI,CAAC;AAAA,IACxD;AACA,UAAM,QAAQ,IAAI,EAAE;AAAA,EACtB;AAAA,EACA,MAAM,aAAa,MAAM;AACvB,QAAI,KAAK,cAAc,MAAM;AAC3B,YAAM,qBAAqB,IAAI;AAC/B,YAAM,KAAK,WAAW,IAAI;AAAA,IAC5B;AAAA,EACF;AAAA,EACA,MAAM,WAAW,MAAM;AACrB,QAAI,KAAK,YAAY,MAAM;AACzB,YAAM,qBAAqB,IAAI;AAC/B,YAAM,KAAK,SAAS,IAAI;AAAA,IAC1B;AAAA,EACF;AACF;AACA,SAAS,qBAAqB,YAAY,YAAY;AACpD,MAAI,cAAc,MAAM;AACtB,iBAAa,CAAC;AAAA,EAChB;AACA,MAAI,sBAAsB,cAAc;AACtC,WAAO,CAAC,UAAU;AAAA,EACpB;AACA,MAAI,MAAM,QAAQ,UAAU,KAAK,WAAW,cAAc,cAAc;AACtE,WAAO;AAAA,EACT;AACA,QAAM,kBAAkB,OAAO,UAAU;AACzC,SAAO,gBAAgB,IAAI,CAAC,mBAAmB,IAAI,eAAe,gBAAgB,UAAU,CAAC;AAC/F;AACA,IAAI,8BAA8B,MAAM;AAAA,EACtC,cAAc;AAAA,EACd;AAAA,EACA,OAAO,4BAA4B,gBAAgB,qBAAqB;AACtE,iBAAa,OAAO,kBAAkB,KAAK,OAAO,UAAU,cAAc,GAAG,MAAM,8DAA8D,gBAAgB;AACjK,gCAA4B,kBAAkB,mBAAmB;AACjE,QAAI,4BAA4B,aAAa,mBAAmB,MAAM;AACpE,kCAA4B,aAAa,kBAAkB,CAAC;AAAA,IAC9D;AACA,gCAA4B,aAAa,gBAAgB,KAAK,mBAAmB;AAAA,EACnF;AAAA,EACA,OAAO,kBAAkB,qBAAqB;AAC5C,eAAW,aAAa,4BAA4B,cAAc;AAChE,YAAM,eAAe,4BAA4B,aAAa,CAAC;AAC/D,mBAAa,QAAQ,CAAC,SAAS;AAC7B,YAAI,SAAS,qBAAqB;AAChC,gBAAM,IAAI,WAAW,iCAAiC;AAAA,QACxD;AAAA,MACF,CAAC;AAAA,IACH;AAAA,EACF;AAAA,EACA,OAAO,QAAQ;AACb,gCAA4B,eAAe,CAAC;AAAA,EAC9C;AAAA,EACA,OAAO,gBAAgB,gBAAgB;AACrC,UAAM,eAAe,CAAC;AACtB,eAAW,aAAa,4BAA4B,cAAc;AAChE,YAAM,QAAQ,CAAC;AACf,UAAI,kBAAkB,OAAO;AAC3B,qBAAa,KAAK,GAAG,4BAA4B,aAAa,MAAM;AAAA,MACtE;AAAA,IACF;AACA,WAAO,aAAa,IAAI,CAAC,SAAS,IAAI,KAAK,CAAC;AAAA,EAC9C;AACF;AACA,4BAA4B,eAAe,CAAC;AAC5C,SAAS,mBAAmB,YAAY,SAAS,QAAQ,cAAc,iBAAiB,eAAe,WAAW,cAAc,iBAAiB;AAC/I,QAAM,UAAU,IAAI,QAAQ;AAC5B,QAAM,kBAAkB;AAAA,IACtB,IAAI,WAAW;AAAA,IACf,GAAG,4BAA4B,gBAAgB,OAAO;AAAA,EACxD;AACA,MAAI,cAAc,MAAM;AACtB,oBAAgB,KAAK,GAAG,UAAU;AAAA,EACpC;AACA,kBAAgB,KAAK,OAAO;AAC5B,QAAM,eAAe,IAAI,aAAa,eAAe;AACrD,eAAa,UAAU;AAAA,IACrB;AAAA,IACA;AAAA,IACA,SAAS;AAAA,IACT,OAAO;AAAA,IACP;AAAA,IACA;AAAA,IACA;AAAA,IACA,SAAS;AAAA,EACX,CAAC;AACD,SAAO,EAAE,cAAc,QAAQ;AACjC;AAGA,SAAS,YAAYf,SAAQ,gBAAgB,CAAC,GAAG,iBAAiB,OAAO;AACvE,SAAO,uBAAuBA,SAAQ,sBAAsB,iBAAiB,OAAO,EAAE,cAAc,eAAe,SAAS,cAAc;AAC5I;AAGA,SAAS,YAAY,GAAG,MAAM;AAC5B,SAAO,KAAK,MAAM;AAChB,QAAI,EAAE,UAAU,WAAW;AACzB,UAAI,KAAK,GAAG,SAAS;AAAA,IACvB;AACA,UAAM,YAAY,KAAK,QAAQ,CAAC,GAAG,MAAM,IAAI;AAC7C,UAAM,gBAAgB,KAAK,UAAU,OAAO,QAAQ,CAAC;AACrD,UAAM,QAAQ,KAAK,QAAQ,WAAW,aAAa,CAAC;AACpD,WAAO,IAAI,GAAG,KAAK;AAAA,EACrB,CAAC;AACH;AACA,SAAS,kBAAkB,OAAO,OAAO;AACvC,SAAO,KAAK,MAAM,KAAK,QAAQ,IAAI,OAAO,KAAK,CAAC,GAAG,EAAE,CAAC;AACxD;AACA,SAAS,kBAAkB,OAAO,OAAO;AACvC,SAAO,KAAK,MAAM,KAAK,IAAI,IAAI,OAAO,KAAK,CAAC,GAAG,EAAE,CAAC;AACpD;AACA,SAAS,4BAA4B,OAAO,OAAO;AACjD,SAAO,KAAK,MAAM;AAChB,UAAM,OAAO,IAAI,OAAO,KAAK;AAC7B,UAAM,cAAc,YAAY,IAAI,KAAK,GAAG,QAAQ,GAAG,OAAO,SAAS;AACvE,UAAM,YAAY,IAAI,IAAI,MAAM,WAAW,CAAC;AAC5C,WAAO,IAAI,KAAK,KAAK,WAAW,EAAE,CAAC;AAAA,EACrC,CAAC;AACH;AACA,SAAS,4BAA4B,OAAO,OAAO;AACjD,SAAO,KAAK,MAAM;AAChB,UAAM,cAAc,YAAY,OAAO,QAAQ,GAAG,OAAO,SAAS;AAClE,UAAM,WAAWnB,MAAK,KAAK,GAAG,WAAW,CAAC;AAC1C,UAAM,cAAc,YAAY,OAAO,QAAQ,GAAG,OAAO,SAAS;AAClE,UAAM,YAAYA,MAAK,KAAK,GAAG,WAAW,CAAC;AAC3C,WAAO,KAAK,QAAQ,IAAI,UAAU,SAAS,CAAC,GAAG,EAAE;AAAA,EACnD,CAAC;AACH;AACA,SAAS,aAAa,OAAO,OAAO;AAClC,SAAO,KAAK,MAAM;AAChB,UAAM,YAAY,QAAQ,GAAG,IAAI,GAAG,IAAI,OAAO,KAAK,CAAC,CAAC;AACtD,WAAO,KAAK,QAAQ,SAAS,GAAG,EAAE;AAAA,EACpC,CAAC;AACH;AACA,SAAS,MAAM,OAAO,OAAO;AAC3B,SAAO,KAAK,MAAM;AAChB,UAAM,YAAY,QAAQ,GAAG,IAAI,GAAG,IAAI,OAAO,KAAK,CAAC,CAAC;AACtD,WAAO,KAAK,WAAW,EAAE;AAAA,EAC3B,CAAC;AACH;AACA,SAAS,iBAAiB,OAAO,OAAO;AACtC,SAAO,KAAK,MAAM;AAChB,UAAM,MAAM,KAAK,IAAI,OAAO,KAAK,GAAG,EAAE;AACtC,UAAM,OAAO,IAAI,IAAI,IAAI,GAAG,KAAK,GAAG,KAAK,GAAG,EAAE;AAC9C,WAAO,QAAQ,GAAG,KAAK,GAAG,IAAI,MAAM,GAAG,CAAC,CAAC;AAAA,EAC3C,CAAC;AACH;AACA,SAAS,QAAQ,OAAO,OAAO;AAC7B,SAAO,KAAK,MAAM;AAChB,UAAMO,SAAQ,KAAK,IAAI,CAAC;AACxB,UAAM,iBAAiB,IAAI,OAAO,KAAK;AACvC,UAAM,gBAAgB,IAAI,KAAK,gBAAgB,SAAS,IAAI,IAAI,cAAc,CAAC,CAAC,GAAGA,MAAK;AACxF,WAAO,KAAK,eAAe,EAAE;AAAA,EAC/B,CAAC;AACH;AACA,SAAS,wBAAwB,QAAQ,QAAQ,aAAa,OAAO;AACnE,SAAO,KAAK,MAAM;AAChB,QAAI,YAAY;AACd,eAAS,QAAQ,MAAM;AAAA,IACzB,OAAO;AACL,YAAM,YAAY,KAAK,QAAQ,OAAO,MAAM,SAAS,GAAG,IAAI;AAC5D,eAAS,IAAI,QAAQ,SAAS;AAAA,IAChC;AACA,aAAS,YAAY,QAAQ,QAAQ,GAAG,IAAI,QAAQ,CAAC;AACrD,WAAO,IAAI,KAAK,IAAI,KAAK,QAAQ,SAAS,GAAGP,MAAK,MAAM,CAAC,GAAG,OAAO,MAAM,SAAS,CAAC,CAAC;AAAA,EACtF,CAAC;AACH;AACA,SAAS,8BAA8B,QAAQ,QAAQ,aAAa,OAAO;AACzE,SAAO,KAAK,MAAM;AAChB,UAAM,aAAa,KAAK,MAAM,SAAS,MAAM,CAAC,GAAG,OAAO;AACxD,aAAS,YAAY,QAAQ,QAAQ,GAAG,IAAI,QAAQ,CAAC;AACrD,UAAM,cAAc,OAAO;AAC3B,UAAM,eAAe,QAAQ,OAAO,YAAY,YAAY,YAAY,SAAS,EAAE,GAAG,WAAW;AACjG,WAAO,wBAAwB,cAAc,QAAQ,UAAU;AAAA,EACjE,CAAC;AACH;AACA,SAAS,8BAA8BwB,SAAQ,QAAQ;AACrD,MAAI,CAAC,aAAa,YAAYA,QAAO,OAAO,OAAO,KAAK,GAAG;AACzD,UAAM,IAAI,WAAW,8DAA8D,KAAK,UAAUA,QAAO,KAAK,SAAS,KAAK,UAAU,OAAO,KAAK,GAAG;AAAA,EACvJ;AACA,SAAO,KAAK,MAAM;AAChB,UAAM,aAAa,KAAK,MAAM;AAC9B,UAAM,eAAe,IAAI,IAAI,MAAM,CAAC;AACpC,WAAO,KAAK,IAAI,YAAY,IAAI,QAAQA,OAAM,CAAC,GAAG,MAAM,IAAI,YAAY,CAAC,CAAC;AAAA,EAC5E,CAAC;AACH;AACA,SAAS,mBAAmB,OAAO,OAAO;AACxC,SAAO,KAAK,MAAM;AAChB,QAAI;AACJ,QAAI,YAAY,OAAO,QAAQ,GAAG,IAAI,QAAQ,CAAC;AAC/C,QAAIxB,MAAK,IAAI,GAAG,IAAI,GAAG,CAAC,CAAC,CAAC;AAC1B,WAAO,KAAK,8BAA8B,OAAO,CAAC,GAAG,EAAE;AAAA,EACzD,CAAC;AACH;AACA,SAAS,0BAA0B,OAAO,OAAO;AAC/C,SAAO,KAAK,MAAM;AAChB,UAAM,cAAc,YAAY,OAAO,QAAQ,GAAG,CAAC;AACnD,UAAM,cAAc,YAAY,OAAO,QAAQ,GAAG,CAAC;AACnD,WAAO,KAAK,IAAI,OAAOA,MAAK,IAAI,aAAa,WAAW,CAAC,CAAC,GAAG,EAAE;AAAA,EACjE,CAAC;AACH;AACA,SAAS,QAAQ,OAAO,OAAO;AAC7B,SAAO,KAAK,MAAM;AAChB,UAAM,UAAUA,MAAK,KAAK,QAAQ,GAAG,KAAK,CAAC;AAC3C,WAAO,KAAK,IAAI,OAAO,IAAI,OAAO,OAAO,CAAC,GAAG,EAAE;AAAA,EACjD,CAAC;AACH;AACA,SAAS,gBAAgB,OAAO,OAAO;AACrC,SAAO,KAAK,MAAM;AAChB,UAAM,iBAAiB,YAAY,OAAO,EAAE;AAC5C,UAAM,iBAAiB,YAAY,OAAO,EAAE;AAC5C,UAAM,YAAY,IAAI,gBAAgB,cAAc;AACpD,WAAO,IAAI,KAAK,WAAW,EAAE,CAAC;AAAA,EAChC,CAAC;AACH;AACA,IAAI,YAAY;AAAA,EACd,kBAAkB;AAAA,EAClB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,SAAS,IAAI,gBAAgB;AAC3B,MAAI,OAAO,mBAAmB,UAAU;AACtC,QAAI,kBAAkB,WAAW;AAC/B,aAAO,UAAU;AAAA,IACnB;AACA,QAAI,SAAS,gBAAgB;AAC7B,QAAI,eAAe,YAAY,EAAE,SAAS,qBAAqB,GAAG;AAChE,eAAS,gBAAgB;AAAA,IAC3B;AACA,UAAM,IAAI,WAAW,MAAM;AAAA,EAC7B,OAAO;AACL,WAAO;AAAA,EACT;AACF;AAGA,SAAS,eAAe,OAAO,OAAO;AACpC,SAAO,KAAK,MAAM;AAChB,UAAM,aAAa,IAAI,KAAK,SAAS,KAAK,CAAC;AAC3C,UAAM,mBAAmB,MAAM,QAAQ,OAAO,UAAU,GAAG,MAAM,KAAK;AACtE,WAAO,KAAK,MAAM,OAAO,gBAAgB,GAAG,EAAE;AAAA,EAChD,CAAC;AACH;AACA,SAAS,oBAAoB,OAAO,OAAO;AACzC,SAAO,KAAK,MAAM,MAAM,MAAM,OAAO,OAAO,EAAE,GAAG,OAAO,OAAO,EAAE,CAAC,GAAG,SAAS,CAAC;AACjF;AACA,SAAS,cAAc,OAAO,OAAO;AACnC,SAAO,KAAK,MAAM;AAChB,WAAO,KAAK,KAAK,WAAW,MAAM,OAAO,CAAC,GAAG,MAAM,OAAO,CAAC,CAAC,CAAC,GAAG,SAAS;AAAA,EAC3E,CAAC;AACH;AACA,SAAS,eAAe,OAAO,OAAO;AACpC,SAAO,KAAK,MAAM;AAChB,WAAO,KAAK,KAAK,WAAW,MAAM,OAAO,CAAC,GAAG,MAAM,OAAO,CAAC,CAAC,CAAC,GAAG,SAAS;AAAA,EAC3E,CAAC;AACH;AACA,SAAS,eAAe,OAAO,OAAO;AACpC,SAAO,KAAK,MAAM;AAChB,WAAO,KAAK,KAAK,WAAW,MAAM,OAAO,CAAC,GAAG,MAAM,OAAO,CAAC,CAAC,CAAC,GAAG,SAAS;AAAA,EAC3E,CAAC;AACH;AACA,SAAS,UAAU,OAAO,OAAO;AAC/B,SAAO,KAAK,MAAM;AAChB,UAAM,KAAK,cAAc,OAAO,KAAK;AACrC,UAAM,KAAK,eAAe,OAAO,KAAK;AACtC,UAAM,cAAc,KAAK,IAAI,EAAE;AAC/B,WAAO,KAAK,MAAM,QAAQ,aAAa,CAAC,GAAG,IAAI,IAAI,WAAW,GAAG,CAAC,GAAG,SAAS;AAAA,EAChF,CAAC;AACH;AACA,SAAS,OAAO,OAAO,OAAO;AAC5B,SAAO,KAAK,MAAM;AAChB,UAAM,KAAK,cAAc,OAAO,KAAK;AACrC,UAAM,KAAK,eAAe,OAAO,KAAK;AACtC,UAAM,cAAc,KAAK,IAAI,EAAE;AAC/B,WAAO,KAAK,MAAM,QAAQ,aAAa,CAAC,GAAG,IAAI,IAAI,WAAW,GAAG,CAAC,GAAG,SAAS;AAAA,EAChF,CAAC;AACH;AACA,SAAS,oBAAoB,OAAO,OAAO;AACzC,SAAO,mBAAmB,OAAO,KAAK;AACxC;AACA,SAAS,0BAA0B,OAAO,OAAO;AAC/C,MAAI,MAAM,SAAS,MAAM,MAAM;AAC7B,YAAQ,QAAQ,OAAO,CAAC,MAAM,OAAO,CAAC,CAAC;AAAA,EACzC;AACA,UAAQ,OAAO,OAAO,EAAE;AACxB,MAAI,MAAM,UAAU,MAAM,OAAO;AAC/B,YAAQ,KAAK,OAAO,MAAM,KAAK;AAAA,EACjC;AACA,SAAO,KAAK,MAAM,OAAO,KAAK,GAAG,SAAS;AAC5C;AACA,IAAI,MAAM;AACV,IAAI,MAAM;AACV,IAAI,MAAM;AACV,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,OAAO;AACX,IAAI,2BAA2B;AAC/B,IAAI,SAAS;AACb,IAAI,iCAAiC;AACrC,IAAI,aAAa;AAAA,EACf;AAAA,EACA;AAAA,EACA;AAAA,EACA,yBAAyB;AAAA,EACzB,+BAA+B;AAAA,EAC/B;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,SAAS,KAAK,YAAY;AACxB,MAAI,OAAO,eAAe,YAAY,cAAc,YAAY;AAC9D,WAAO,WAAW;AAAA,EACpB,WAAW,OAAO,eAAe,YAAY,cAAc,MAAM;AAC/D,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,WAAW,kBAAkB,YAAY;AAAA,EACrD;AACF;AACA,SAAS,oBAAoB,IAAI;AAC/B,UAAQ,OAAO,MAAM,0BAA0B,IAAI;AACnD,MAAI,OAAO,OAAO,UAAU;AAC1B,WAAO;AAAA,EACT,OAAO;AACL,QAAI;AACJ,eAAW,OAAO,OAAO,KAAK,SAAS,GAAG;AACxC,UAAI,UAAU,SAAS,IAAI;AACzB,iBAAS;AACT;AAAA,MACF;AAAA,IACF;AACA,QAAI,WAAW,QAAQ;AACrB,aAAO;AAAA,IACT;AACA,eAAW,OAAO,OAAO,KAAK,UAAU,GAAG;AACzC,UAAI,WAAW,SAAS,IAAI;AAC1B,iBAAS;AACT;AAAA,MACF;AAAA,IACF;AACA,QAAI,WAAW,QAAQ;AACrB,aAAO;AAAA,IACT;AACA,WAAO,GAAG;AAAA,EACZ;AACF;AAGA,SAAS,aAAa,YAAY;AAChC,QAAM,eAAe;AAAA,IACnB,WAAW,MAAM,MAAM,QAAQ,IAAI;AAAA,IACnC,YAAY,MAAM,MAAM,SAAS,GAAG,MAAM,QAAQ,CAAC;AAAA,IACnD,QAAQ,MAAM,MAAM,KAAK,MAAM,KAAK,OAAO,QAAQ,CAAC;AAAA,IACpD,UAAU,MAAM,MAAM,OAAO,MAAM,KAAK,OAAO,QAAQ,GAAG,CAAC;AAAA,IAC3D,WAAW,MAAM,MAAM,QAAQ,MAAM,KAAK,GAAG,QAAQ,CAAC;AAAA,IACtD,OAAO,MAAM,MAAM,IAAI,IAAI;AAAA,EAC7B;AACA,eAAa,aAAa,aAAa;AACvC,eAAa,cAAc,aAAa;AACxC,eAAa,UAAU,aAAa;AACpC,eAAa,YAAY,aAAa;AACtC,eAAa,aAAa,aAAa;AACvC,eAAa,SAAS,aAAa;AACnC,MAAI,cAAc,cAAc;AAC9B,WAAO,aAAa,YAAY;AAAA,EAClC;AACA,QAAM,IAAI,WAAW,qBAAqB,YAAY;AACxD;AAGA,IAAI,8CAA8C,IAAI,OAAO;AAC7D,SAAS,yBAAyB,qBAAqB,WAAW,YAAY,OAAO;AACnF,MAAI,uBAAuB,QAAQ,OAAO,wBAAwB,YAAY,OAAO,eAAe,mBAAmB,MAAM,OAAO,aAAa,CAAC,iBAAiB,mBAAmB,GAAG;AACvL,UAAM,IAAI,MAAM,oEAAoE;AAAA,EACtF;AACA,MAAI,WAAW;AACb,UAAM,MAAM,KAAK,UAAU,mBAAmB;AAC9C,QAAI,IAAI,SAAS,6CAA6C;AAC5D,cAAQ,KAAK,mCAAmC,2CAA2C,IAAI,qJAAqJ,8CAA8C;AAAA,IACpS;AAAA,EACF;AACF;AACA,SAAS,iBAAiB,GAAG;AAC3B,MAAI,MAAM,MAAM;AACd,WAAO;AAAA,EACT,WAAW,OAAO,MAAM,UAAU;AAChC,QAAI,OAAO,eAAe,CAAC,MAAM,OAAO,WAAW;AACjD,YAAM,OAAO,OAAO,KAAK,CAAC;AAC1B,iBAAW,OAAO,MAAM;AACtB,YAAI,OAAO,QAAQ,UAAU;AAC3B,iBAAO;AAAA,QACT;AACA,YAAI,CAAC,iBAAiB,EAAE,IAAI,GAAG;AAC7B,iBAAO;AAAA,QACT;AAAA,MACF;AACA,aAAO;AAAA,IACT,OAAO;AACL,UAAI,MAAM,QAAQ,CAAC,GAAG;AACpB,mBAAW,QAAQ,GAAG;AACpB,cAAI,CAAC,iBAAiB,IAAI,GAAG;AAC3B,mBAAO;AAAA,UACT;AAAA,QACF;AACA,eAAO;AAAA,MACT,OAAO;AACL,eAAO;AAAA,MACT;AAAA,IACF;AAAA,EACF,OAAO;AACL,UAAM,QAAQ,OAAO;AACrB,WAAO,UAAU,YAAY,UAAU,YAAY,UAAU;AAAA,EAC/D;AACF;AAGA,SAAS,aAAakC,SAAQ,YAAY,WAAW,UAAU,QAAQ,KAAK;AAC1E,QAAM,iBAAiB,sBAAsBA,OAAM;AACnD,QAAM,YAAY,CAAC,gBAAgB,eAAe,gBAAgB,SAAS;AAC3E,MAAI,gBAAgB;AAClB,iBAAa,cAAc;AAC3B,gBAAY,aAAa,CAAC,MAAM,MAAM,MAAM,CAAC;AAAA,EAC/C,OAAO;AACL,iBAAa,cAAc;AAC3B,gBAAY,aAAa,CAAC,MAAM,MAAM,KAAK,KAAK,CAAC;AAAA,EACnD;AACA,MAAI,UAAU,UAAU,SAAS,MAAM,GAAG;AACxC,gBAAY,UAAU,IAAI,CAAC,OAAO,KAAK,MAAM,aAAa,EAAE,CAAC;AAAA,EAC/D;AACA,MAAI;AACJ,MAAI,CAAC,gBAAgB;AACnB,cAAU,KAAK,iBAAiB;AAChC,oBAAgB,CAAC;AACjB,eAAW,SAASA,QAAO,cAAc;AACvC,oBAAc,KAAK,GAAGA,QAAO,aAAa,MAAM;AAAA,IAClD;AAAA,EACF;AACA,UAAQ,IAAI,OAAO,UAAU,CAAC;AAC9B,WAAS,WAAW,WAAW,OAAO;AACtC,UAAQ,IAAI,OAAO,UAAU,CAAC;AAC9B,QAAM,SAASA,QAAO;AACtB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,QAAI,gBAAgB;AAClB,wBAAkB,OAAO,KAAK,WAAW,OAAO;AAAA,IAClD,OAAO;AACL,uCAAiC,OAAO,KAAK,WAAW,eAAe,OAAO;AAAA,IAChF;AACA,aAAS,OAAO,OAAO,SAAS,IAAI,MAAM,KAAK,OAAO,UAAU,CAAC;AAAA,EACnE;AACA,EAAAA,QAAO,iCAAiC;AACxC,QAAM,iBAAiB,qBAAqBA,OAAM;AAClD,QAAM,oBAAoB,qBAAqBA,QAAO,mBAAmB;AACzE,UAAQ,iBAAiB,iBAAiB,mBAAmB;AAC7D,UAAQ,qBAAqB,gBAAgB;AAC7C,UAAQ,yBAAyB,mBAAmB;AACpD,UAAQ,IAAI,OAAO,UAAU,CAAC;AAChC;AACA,SAAS,qBAAqBA,SAAQ;AACpC,MAAI;AACJ,MAAIA,QAAO,6BAA6B,MAAM;AAC5C,qBAAiB,qBAAqBA,QAAO,yBAAyB;AAAA,EACxE,OAAO;AACL,qBAAiB,qBAAqBA,QAAO,gBAAgB;AAAA,EAC/D;AACA,SAAO;AACT;AACA,SAAS,sBAAsBA,SAAQ;AACrC,MAAI,iBAAiB;AACrB,QAAM,eAAe,CAAC;AACtB,QAAM,QAAQ,CAAC;AACf,aAAW,SAASA,QAAO,cAAc;AACvC,iBAAa,KAAKA,QAAO,aAAa,MAAM;AAAA,EAC9C;AACA,aAAW,cAAc,cAAc;AACrC,QAAI,WAAW,SAAS,KAAK,WAAW,WAAW,KAAK,WAAW,GAAG,cAAc,SAAS,GAAG;AAC9F,uBAAiB;AACjB;AAAA,IACF;AACA,UAAM,KAAK,GAAG,UAAU;AAAA,EAC1B;AACA,MAAI,gBAAgB;AAClB,eAAW,SAASA,QAAO,QAAQ;AACjC,UAAI,OAAO;AACX,iBAAWb,SAAQ,MAAM,cAAc;AACrC,YAAI,MAAM,QAAQA,KAAI,MAAM,IAAI;AAC9B,cAAI,MAAM;AACR,6BAAiB;AACjB;AAAA,UACF,OAAO;AACL,mBAAO;AAAA,UACT;AAAA,QACF;AAAA,MACF;AACA,UAAI,CAAC,gBAAgB;AACnB;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,SAAS,QAAQ,WAAW,UAAU,QAAQ,KAAK;AAC1D,MAAI,OAAO;AACX,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,QAAI,KAAK,GAAG;AACV,aAAO,KAAK,MAAM,GAAG,KAAK,SAAS,CAAC,IAAI;AAAA,IAC1C;AACA,YAAQ,OAAO;AACf,WAAO,KAAK,MAAM,GAAG,UAAU,GAAG;AAClC,YAAQ,IAAI,OAAO,UAAU,MAAM,KAAK,MAAM;AAAA,EAChD;AACA,UAAQ,IAAI;AACd;AACA,SAAS,kBAAkB,OAAO,WAAW,SAAS;AACpD,MAAI;AACJ,MAAI;AACJ,MAAI;AACF,iBAAa,MAAM,aAAa,IAAI,CAAC,MAAM,KAAK,UAAU,EAAE,WAAW,CAAC,EAAE,KAAK,GAAG;AAAA,EACpF,SAAS,KAAP;AACA,iBAAa;AAAA,EACf;AACA,MAAI;AACF,kBAAc,KAAK,UAAU,MAAM,WAAW;AAAA,EAChD,SAAS,KAAP;AACA,kBAAc;AAAA,EAChB;AACA,QAAM,OAAO,MAAM;AACnB,QAAM,YAAY,MAAM,aAAa;AACrC,QAAM,SAAS;AAAA,IACb,GAAG,SAAS;AAAA,IACZ;AAAA,IACA;AAAA,IACA,MAAM,YAAY,EAAE,SAAS;AAAA,EAC/B;AACA,WAAS,QAAQ,WAAW,OAAO;AACrC;AACA,SAAS,iCAAiC,OAAO,WAAW,eAAe,SAAS;AAClF,MAAI;AACJ,MAAI;AACJ,MAAI;AACF,iBAAa,MAAM,aAAa,IAAI,CAAC,MAAM,KAAK,UAAU,EAAE,WAAW,CAAC,EAAE,KAAK,GAAG;AAAA,EACpF,SAAS,KAAP;AACA,iBAAa;AAAA,EACf;AACA,MAAI;AACF,kBAAc,KAAK,UAAU,MAAM,WAAW;AAAA,EAChD,SAAS,KAAP;AACA,kBAAc;AAAA,EAChB;AACA,QAAM,cAAc,CAAC;AACrB,aAAWA,SAAQ,MAAM,cAAc;AACrC,QAAI,iBAAiB,QAAQ,cAAc,SAAS,KAAK,cAAc,QAAQA,KAAI,MAAM,IAAI;AAC3F;AAAA,IACF;AACA,aAAS,KAAK,GAAG,KAAKA,MAAK,cAAc,QAAQ,EAAE,IAAI;AACrD,YAAM,eAAeA,MAAK,cAAc,IAAI;AAC5C,YAAM,oBAAoBA,MAAK,YAAY;AAC3C,YAAM,qBAAqBA,MAAK,cAAc;AAC9C,kBAAY,KAAK,GAAG,gBAAgB,sBAAsB,qBAAqB;AAAA,IACjF;AAAA,EACF;AACA,QAAM,OAAO,MAAM;AACnB,QAAM,YAAY,MAAM,aAAa;AACrC,QAAM,kBAAkB,YAAY,WAAW,IAAI,KAAK,YAAY;AACpE,QAAM,SAAS;AAAA,IACb,GAAG,SAAS;AAAA,IACZ;AAAA,IACA;AAAA,IACA,MAAM,YAAY,EAAE,SAAS;AAAA,IAC7B;AAAA,EACF;AACA,WAAS,QAAQ,WAAW,OAAO;AACnC,WAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,EAAE,IAAI;AAC9C,aAAS,CAAC,IAAI,IAAI,IAAI,IAAI,YAAY,GAAG,GAAG,WAAW,OAAO;AAAA,EAChE;AACF;AAGA,SAAS,6BAA6B,KAAKP,QAAO,OAAO;AACvD,UAAQ,QAAQ,kBAAkB,QAAQ,kBAAkB,QAAQ,kBAAkBA,WAAU,KAAK,OAAO,UAAU;AACxH;AACA,SAAS,oBAAoB,gBAAgB,KAAK;AAChD,MAAI,mBAAmB,MAAM;AAC3B,WAAO;AAAA,EACT,WAAW,OAAO,mBAAmB,UAAU;AAC7C,WAAO,YAAY,cAAc;AAAA,EACnC,WAAW,OAAO,mBAAmB,YAAY,OAAO,mBAAmB,WAAW;AACpF,WAAO;AAAA,EACT,WAAW,0BAA0B,OAAO;AAC1C,UAAM,UAAU,CAAC;AACjB,UAAM,cAAc,eAAe;AACnC,aAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,YAAM,OAAO,eAAe;AAC5B,UAAI,6BAA6B,KAAK,IAAI,IAAI,GAAG;AAC/C,gBAAQ,KAAK,IAAI;AAAA,MACnB,OAAO;AACL,gBAAQ,KAAK,oBAAoB,MAAM,GAAG,CAAC;AAAA,MAC7C;AAAA,IACF;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAM,SAAS,CAAC;AAChB,eAAW,eAAe,OAAO,KAAK,cAAc,GAAG;AACrD,YAAM,gBAAgB,eAAe;AACrC,UAAI,gBAAgB,UAAU,OAAO,kBAAkB,UAAU;AAC/D,eAAO,eAAe;AAAA,MACxB,OAAO;AACL,cAAM,QAAQ,YAAY,WAAW;AACrC,eAAO,SAAS,oBAAoB,eAAe,KAAK;AAAA,MAC1D;AAAA,IACF;AACA,WAAO;AAAA,EACT;AACF;AACA,SAAS,oBAAoB,UAAU,KAAK;AAC1C,MAAI,aAAa,QAAQ,aAAa,QAAQ;AAC5C,WAAO;AAAA,EACT,WAAW,OAAO,aAAa,UAAU;AACvC,WAAO,YAAY,QAAQ;AAAA,EAC7B,WAAW,OAAO,aAAa,YAAY,OAAO,aAAa,WAAW;AACxE,WAAO;AAAA,EACT,WAAW,oBAAoB,OAAO;AACpC,UAAM,UAAU,CAAC;AACjB,UAAM,cAAc,SAAS;AAC7B,aAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,YAAM,OAAO,SAAS;AACtB,UAAI,6BAA6B,KAAK,IAAI,IAAI,GAAG;AAC/C,gBAAQ,KAAK,IAAI;AAAA,MACnB,OAAO;AACL,gBAAQ,KAAK,oBAAoB,MAAM,GAAG,CAAC;AAAA,MAC7C;AAAA,IACF;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAM,SAAS,CAAC;AAChB,eAAW,SAAS,OAAO,KAAK,QAAQ,GAAG;AACzC,YAAM,UAAU,SAAS;AACzB,YAAM,QAAQ,YAAY,KAAK;AAC/B,WAAK,UAAU,UAAU,UAAU,gBAAgB,OAAO,YAAY,UAAU;AAC9E,eAAO,SAAS;AAAA,MAClB,OAAO;AACL,eAAO,SAAS,oBAAoB,SAAS,KAAK;AAAA,MACpD;AAAA,IACF;AACA,WAAO;AAAA,EACT;AACF;AAGA,IAAI,WAAW;AAGf,IAAI,YAAY,cAAc,MAAM;AAAA,EAClC,YAAY,MAAM;AAChB,UAAM,CAAC,CAAC;AACR,SAAK,iBAAiC,oBAAI,IAAI;AAC9C,SAAK,OAAO,KAAK;AACjB,QAAI,KAAK,QAAQ,MAAM;AACrB,YAAM,SAAS,KAAK,aAAa,EAAE,YAAY;AAC/C,WAAK,OAAO,OAAO,MAAM;AAAA,IAC3B;AACA,SAAK,kBAAkB;AACvB,SAAK,aAAa;AAClB,QAAI,MAAM,QAAQ,KAAK,MAAM,GAAG;AAC9B,WAAK,SAAS,KAAK,OAAO,MAAM;AAAA,IAClC,OAAO;AACL,WAAK,SAAS,CAAC,KAAK,MAAM;AAAA,IAC5B;AACA,QAAI,MAAM,QAAQ,KAAK,OAAO,GAAG;AAC/B,WAAK,UAAU,KAAK,QAAQ,MAAM;AAAA,IACpC,OAAO;AACL,WAAK,UAAU,CAAC,KAAK,OAAO;AAAA,IAC9B;AACA,QAAI,QAAQ,KAAK,MAAM,EAAE,WAAW,KAAK,OAAO,QAAQ;AACtD,YAAM,IAAI,WAAW,mGAAmG,KAAK,OAAO,IAAI,CAAC,MAAM,EAAE,IAAI,GAAG;AAAA,IAC1J;AACA,QAAI,QAAQ,KAAK,OAAO,EAAE,WAAW,KAAK,QAAQ,QAAQ;AACxD,cAAQ,KAAK,qGAAqG,KAAK,QAAQ,IAAI,CAAC,MAAM,EAAE,IAAI,GAAG;AAAA,IACrJ;AACA,SAAK,cAAc,CAAC;AACpB,SAAK,yBAAyB,CAAC;AAC/B,SAAK,2BAA2B,CAAC;AACjC,SAAK,eAAe,CAAC;AACrB,SAAK,0BAA0B,CAAC;AAChC,SAAK,4BAA4B,CAAC;AAClC,SAAK,SAAS,CAAC;AACf,SAAK,wBAAwB,CAAC;AAC9B,eAAW,KAAK,KAAK,SAAS;AAC5B,YAAM,QAAQ,EAAE;AAChB,YAAM,YAAY,EAAE;AACpB,YAAM,cAAc,EAAE;AACtB,WAAK,aAAa,KAAK,KAAK;AAC5B,WAAK,wBAAwB,KAAK,SAAS;AAC3C,WAAK,0BAA0B,KAAK,WAAW;AAAA,IACjD;AACA,eAAW,KAAK,KAAK,QAAQ;AAC3B,YAAM,QAAQ,EAAE;AAChB,YAAM,YAAY,EAAE;AACpB,YAAM,cAAc,EAAE;AACtB,cAAQ,cAAc,GAAG,0BAA0B;AACnD,cAAQ,gBAAgB,GAAG,4BAA4B;AACvD,WAAK,YAAY,KAAK,KAAK;AAC3B,WAAK,uBAAuB,KAAK,SAAS;AAC1C,WAAK,yBAAyB,KAAK,WAAW;AAAA,IAChD;AACA,SAAK,aAAa,CAAC;AACnB,SAAK,cAAc,CAAC;AACpB,SAAK,kBAAkB,CAAC;AACxB,SAAK,iBAAiB,CAAC;AACvB,SAAK,kBAAkB,CAAC;AACxB,aAAS,KAAK,GAAG,KAAK,KAAK,YAAY,QAAQ,MAAM;AACnD,YAAM,QAAQ,KAAK,YAAY;AAC/B,UAAI,EAAE,iBAAiB,aAAa;AAClC,cAAM,IAAI,UAAU,8EAA8E,KAAK,iBAAiB,2CAA2C,MAAM,aAAa,IAAI;AAAA,MAC5L;AACA,WAAK,WAAW,KAAK,MAAM,IAAI;AAC/B,WAAK,gBAAgB,KAAK,MAAM,eAAe;AAC/C,WAAK,eAAe,KAAK,MAAM,IAAI;AAAA,IACrC;AACA,eAAW,SAAS,KAAK,cAAc;AACrC,WAAK,YAAY,KAAK,MAAM,IAAI;AAAA,IAClC;AACA,SAAK,sBAAsB,KAAK,OAAO,IAAI,CAAC,MAAM,EAAE,KAAK;AACzD,SAAK,uBAAuB,KAAK,QAAQ,IAAI,CAAC,MAAM,EAAE,KAAK;AAC3D,UAAM,cAAc,CAAC;AACrB,UAAM,eAAe,CAAC;AACtB,UAAM,eAAe,CAAC;AACtB,UAAM,iBAAiB,CAAC;AACxB,UAAM,eAAe,CAAC;AACtB,UAAM,yBAAyB,CAAC;AAChC,UAAM,kBAAkB,CAAC,SAAS,gBAAgB,kBAAkB,OAAO,WAAW,gBAAgB;AACpG,UAAI,SAAS,QAAQ,aAAa,QAAQ,eAAe,MAAM;AAC7D,gBAAQ,QAAQ;AAChB,oBAAY,QAAQ;AACpB,sBAAc,QAAQ;AAAA,MACxB;AACA,YAAMO,QAAO,MAAM,aAAa;AAChC,UAAI,iBAAiB,QAAQA,KAAI,MAAM,IAAI;AACzC,cAAM,IAAI,aAAa,cAAc,QAAQ,kBAAkB,MAAM,2BAA2B;AAAA,MAClG;AACA,UAAI,eAAe,QAAQA,KAAI,MAAM,IAAI;AACvC;AAAA,MACF;AACA,WAAK,eAAe,IAAI,UAAU,QAAQ,OAAO,SAAS,CAAC;AAC3D,UAAI,EAAE,MAAM,MAAM,eAAe;AAC/B,qBAAa,MAAM,MAAM,OAAO,KAAK,YAAY,EAAE;AAAA,MACrD;AACA,UAAI,iBAAiB,QAAQA,KAAI,MAAM,IAAI;AACzC,yBAAiB,KAAKA,KAAI;AAAA,MAC5B;AACA,YAAM,mBAAmBA,MAAK,cAAc;AAC5C,eAAS,KAAK,GAAG,KAAK,kBAAkB,MAAM;AAC5C,cAAM,IAAIA,MAAK,aAAa;AAC5B,cAAM,SAASA,MAAK,cAAc;AAClC,cAAM,aAAaA,MAAK,YAAY;AACpC,cAAM,eAAeA,MAAK,cAAc;AACxC,wBAAgB,GAAG,gBAAgB,kBAAkB,QAAQ,YAAY,YAAY;AAAA,MACvF;AACA,qBAAe,KAAKA,KAAI;AACxB,aAAO,iBAAiB,QAAQA,KAAI,KAAK,GAAG;AAC1C,yBAAiB,OAAO,iBAAiB,QAAQA,KAAI,GAAG,CAAC;AAAA,MAC3D;AACA,6BAAuB,KAAKA,KAAI;AAAA,IAClC;AACA,UAAM,gBAAgB,CAAC;AACvB,UAAM,kBAAkB,CAAC;AACzB,eAAW,KAAK,KAAK,SAAS;AAC5B,sBAAgB,GAAG,eAAe,eAAe;AAAA,IACnD;AACA,UAAM,iCAAiC,uBAAuB,MAAM,EAAE,QAAQ;AAC9E,eAAWA,SAAQ,gCAAgC;AACjD,mBAAaA,MAAK,MAAMA;AACxB,UAAI,EAAEA,MAAK,MAAM,cAAc;AAC7B,oBAAYA,MAAK,MAAM;AAAA,MACzB;AACA,UAAI,QAAQ,YAAYA,MAAK;AAC7B,YAAM,gBAAgB,aAAaA,MAAK,cAAc,OAAO,OAAO,IAAI,aAAaA,MAAK,cAAc;AACxG,cAAQ,KAAK,IAAI,OAAO,aAAa;AACrC,mBAAaA,MAAK,cAAc,MAAM;AACtC,qBAAeA,MAAK,cAAc,MAAMA,MAAK;AAC7C,kBAAYA,MAAK,MAAM;AACvB,eAAS,KAAK,GAAG,KAAKA,MAAK,cAAc,QAAQ,MAAM;AACrD,cAAM,eAAeA,MAAK,cAAc;AACxC,cAAM,YAAYA,MAAK,YAAY;AACnC,cAAM,cAAc,aAAa,aAAa;AAC9C,cAAM,iBAAiB,YAAY,YAAY,OAAO,OAAO,IAAI,YAAY,YAAY;AACzF,oBAAY,YAAY,MAAM,KAAK,IAAI,QAAQ,GAAG,cAAc;AAChE,qBAAa,YAAY,MAAM;AAAA,MACjC;AAAA,IACF;AACA,UAAM,eAAe,CAAC;AACtB,eAAW,UAAU,aAAa;AAChC,YAAM,QAAQ,YAAY;AAC1B,UAAI,EAAE,SAAS,eAAe;AAC5B,qBAAa,SAAS,CAAC;AAAA,MACzB;AACA,mBAAa,OAAO,KAAK,aAAa,OAAO;AAAA,IAC/C;AACA,UAAM,gBAAgB,CAAC;AACvB,eAAW,WAAW,cAAc;AAClC,YAAM,QAAQ,aAAa;AAC3B,UAAI,EAAE,SAAS,gBAAgB;AAC7B,sBAAc,SAAS,CAAC;AAAA,MAC1B;AACA,oBAAc,OAAO,KAAK,eAAe,QAAQ;AAAA,IACnD;AACA,QAAI,YAAY,OAAO,KAAK,aAAa,EAAE,IAAI,CAAC,MAAM,SAAS,GAAG,EAAE,CAAC,EAAE,KAAK,oBAAoB;AAChG,SAAK,SAAS,CAAC;AACf,eAAW,SAAS,WAAW;AAC7B,YAAM,iBAAiB,cAAc;AACrC,qBAAe,KAAK,CAAC,GAAG,MAAM;AAC5B,cAAM,SAAS,aAAa,EAAE;AAC9B,cAAM,SAAS,aAAa,EAAE;AAC9B,YAAI,SAAS,QAAQ;AACnB,iBAAO;AAAA,QACT;AACA,YAAI,SAAS,QAAQ;AACnB,iBAAO;AAAA,QACT;AACA,eAAO;AAAA,MACT,CAAC;AACD,iBAAW,SAAS,gBAAgB;AAClC,YAAI,iBAAiB,WAAW;AAC9B,eAAK,sBAAsB,KAAK,KAAK;AAAA,QACvC;AACA,aAAK,OAAO,KAAK,KAAK;AAAA,MACxB;AAAA,IACF;AACA,SAAK,gBAAgB;AACrB,gBAAY,OAAO,KAAK,YAAY,EAAE,IAAI,CAAC,MAAM,SAAS,GAAG,EAAE,CAAC,EAAE,KAAK,oBAAoB;AAC3F,UAAM,oBAAoB,KAAK,OAAO,MAAM;AAC5C,UAAM,0BAA0B,CAAC;AACjC,eAAW,SAAS,WAAW;AAC7B,iBAAWA,SAAQ,aAAa,QAAQ;AACtC,cAAM,QAAQA,MAAK;AACnB,YAAI,SAAS,MAAM;AACjB,qBAAW,KAAKA,MAAK,cAAc;AACjC,gBAAI,kBAAkB,QAAQ,CAAC,MAAM,IAAI;AACvC,oBAAM,IAAI,aAAa,sDAAsD,eAAe,MAAM,qEAAqE,yBAAyB;AAAA,YAClM;AAAA,UACF;AACA,qBAAW,KAAKA,MAAK,eAAe;AAClC,8BAAkB,KAAK,CAAC;AAAA,UAC1B;AACA,kCAAwB,KAAK,MAAM,IAAI;AAAA,QACzC;AAAA,MACF;AAAA,IACF;AACA,SAAK,eAAe;AACpB,UAAM,WAAW,KAAK,OAAO,IAAI,CAAC,MAAM,EAAE,IAAI;AAC9C,eAAW,QAAQ,UAAU;AAC3B,YAAM,iBAAiB,SAAS,OAAO,CAAC,MAAM,MAAM,IAAI,EAAE;AAC1D,UAAI,mBAAmB,GAAG;AACxB,cAAM,IAAI,aAAa,aAAa,iBAAiB,uFAAuF,KAAK,UAAU,QAAQ,CAAC;AAAA,MACtK;AAAA,IACF;AACA,SAAK,gBAAgB,CAAC;AACtB,SAAK,eAAe,CAAC;AACrB,QAAI,KAAK;AAAA,MACP,eAAe;AAAA,MACf,eAAe,CAAC;AAAA,MAChB,aAAa,CAAC;AAAA,MACd,eAAe,CAAC;AAAA,MAChB,cAAc,KAAK;AAAA,MACnB,eAAe,KAAK;AAAA,MACpB,YAAY,KAAK,OAAO,IAAI,CAAC,MAAM,IAAI;AAAA,MACvC,aAAa,KAAK,QAAQ,IAAI,CAAC,MAAM,IAAI;AAAA,MACzC,aAAa,KAAK,OAAO,IAAI,CAAC,MAAM,EAAE,KAAK;AAAA,MAC3C,cAAc,KAAK,QAAQ,IAAI,CAAC,MAAM,EAAE,KAAK;AAAA,IAC/C,CAAC;AACD,SAAK,QAAQ;AACb,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,oBAAoB;AAClB,QAAI,KAAK,cAAc,GAAG;AACxB,YAAM,IAAI,MAAM,cAAc,KAAK,4BAA4B;AAAA,IACjE;AAAA,EACF;AAAA,EACA,UAAU;AACR,SAAK,kBAAkB;AACvB,UAAM,SAAS,EAAE,sBAAsB,MAAM,sBAAsB,EAAE;AACrE,QAAI,EAAE,KAAK,cAAc,GAAG;AAC1B,iBAAW,SAAS,KAAK,QAAQ;AAC/B,eAAO,wBAAwB,MAAM,QAAQ,EAAE;AAAA,MACjD;AACA,iBAAW,aAAa,KAAK,uBAAuB;AAClD,eAAO,wBAAwB,UAAU,QAAQ,EAAE;AAAA,MACrD;AAAA,IACF;AACA,WAAO,uBAAuB,KAAK;AACnC,WAAO;AAAA,EACT;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,UAAU,WAAW;AACvB,SAAK,OAAO,QAAQ,CAAC,UAAU;AAC7B,YAAM,kBAAkB,QAAQ,CAAC,MAAM,EAAE,YAAY,SAAS;AAAA,IAChE,CAAC;AACD,SAAK,aAAa;AAAA,EACpB;AAAA,EACA,IAAI,mBAAmB;AACrB,QAAI,KAAK,kBAAkB,SAAS,GAAG;AACrC,YAAM,IAAI,WAAW,sNAAsN;AAAA,IAC7O;AACA,QAAI,CAAC,KAAK,WAAW;AACnB,aAAO,CAAC;AAAA,IACV;AACA,QAAI,UAAU,CAAC;AACf,eAAW,SAAS,KAAK,QAAQ;AAC/B,gBAAU,QAAQ,OAAO,MAAM,gBAAgB;AAAA,IACjD;AACA,WAAO;AAAA,EACT;AAAA,EACA,IAAI,sBAAsB;AACxB,UAAM,UAAU,CAAC;AACjB,eAAW,SAAS,KAAK,QAAQ;AAC/B,cAAQ,KAAK,GAAG,MAAM,mBAAmB;AAAA,IAC3C;AACA,QAAI,CAAC,KAAK,WAAW;AACnB,YAAM,mBAAmB,CAAC;AAC1B,iBAAW,SAAS,KAAK,QAAQ;AAC/B,yBAAiB,KAAK,GAAG,MAAM,gBAAgB;AAAA,MACjD;AACA,aAAO,iBAAiB,OAAO,OAAO;AAAA,IACxC;AACA,WAAO;AAAA,EACT;AAAA,EACA,IAAI,UAAU;AACZ,WAAO,KAAK,iBAAiB,OAAO,KAAK,mBAAmB;AAAA,EAC9D;AAAA,EACA,YAAY,SAAS,SAAS,MAAM;AAClC,UAAM,eAAe,CAAC;AACtB,QAAI,oBAAoB;AACxB,eAAW,SAAS,KAAK,QAAQ;AAC/B,iBAAW,UAAU,MAAM,SAAS;AAClC,YAAI,aAAa,OAAO,iBAAiB,MAAM;AAC7C,gBAAM,IAAI,WAAW,0BAA0B,OAAO,cAAc;AAAA,QACtE;AACA,qBAAa,OAAO,gBAAgB;AACpC;AAAA,MACF;AAAA,IACF;AACA,UAAM,oBAAoB,CAAC;AAC3B,eAAW,QAAQ,SAAS;AAC1B,UAAI,gBAAgB;AACpB,UAAI,aAAa,SAAS,MAAM;AAC9B,cAAM,SAAS,KAAK,MAAM,GAAG;AAC7B,cAAM,mBAAmB,OAAO,MAAM,GAAG,EAAE,EAAE,OAAO,CAAC,OAAO,OAAO,SAAS,EAAE,CAAC;AAC/E,wBAAgB,iBAAiB,KAAK,GAAG;AAAA,MAC3C;AACA,UAAI,aAAa,kBAAkB,MAAM;AACvC,0BAAkB,KAAK,CAAC,aAAa,gBAAgB,QAAQ,KAAK,CAAC;AAAA,MACrE,WAAW,QAAQ;AACjB,cAAM,IAAI,WAAW,gDAAgD,MAAM;AAAA,MAC7E;AACA,aAAO,aAAa;AAAA,IACtB;AACA,QAAI,QAAQ;AACV,YAAM,aAAa,CAAC;AACpB,iBAAW,QAAQ,cAAc;AAC/B,mBAAW,KAAK,IAAI;AAAA,MACtB;AACA,UAAI,WAAW,SAAS,GAAG;AACzB,cAAM,IAAI,WAAW,GAAG,WAAW,aAAa,0CAA0C,YAAY;AAAA,MACxG;AAAA,IACF;AACA,kBAAc,iBAAiB;AAAA,EACjC;AAAA,EACA,gBAAgB;AACd,UAAM,YAAY,KAAK,UAAU;AACjC,UAAM,cAAc,CAAC;AACrB,gBAAY,eAAe,KAAK,aAAa;AAC7C,gBAAY,YAAY;AACxB,gBAAY,kBAAkB,eAAe;AAC7C,gBAAY,aAAa;AACzB,WAAO;AAAA,EACT;AAAA,EACA,OAAO,QAAQ,eAAe,MAAM;AAClC,UAAM,cAAc,oBAAoB,KAAK,cAAc,CAAC;AAC5D,WAAO,eAAe,KAAK,UAAU,WAAW,IAAI;AAAA,EACtD;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS,OAAO,MAAM;AACtB,YAAM,WAAW,IAAI,SAAS;AAC9B,eAAS,KAAK,GAAG,KAAK,KAAK,OAAO,QAAQ,EAAE,IAAI;AAC9C,iBAAS,IAAI,KAAK,OAAO,KAAK,OAAO,GAAG;AAAA,MAC1C;AACA,aAAO,QAAQ,KAAK,SAAS,UAAU,MAAM;AAAA,IAC/C,CAAC;AAAA,EACH;AAAA,EACA,YAAY,QAAQX,OAAM;AACxB,WAAO,KAAK,MAAM;AAChB,eAAS,OAAO,MAAM;AACtB,UAAI;AACJ,UAAIA,SAAQ,MAAM;AAChB,gBAAQ,aAAa,MAAM,OAAO,MAAM;AAAA,MAC1C,OAAO;AACL,gBAAQ,OAAOA,KAAI;AAAA,MACrB;AACA,aAAO,KAAK,iBAAiB,QAAQ,KAAK,EAAE;AAAA,IAC9C,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,UAAM,cAAc,mBAAmB,UAAU;AACjD,QAAI,YAAY,WAAW,KAAK,YAAY,QAAQ;AAClD,YAAM,IAAI,WAAW,+BAA+B,yBAAyB,KAAK,YAAY,uBAAuB;AAAA,IACvH;AACA,UAAM,uBAAuB,CAAC;AAC9B,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,MAAM;AAC9C,YAAM,QAAQ,KAAK,YAAY;AAC/B,YAAM,cAAc,YAAY;AAChC,YAAM,WAAW,MAAM,OAAO;AAC9B,2BAAqB,YAAY;AAAA,IACnC;AACA,UAAM,YAAY,OAAO,KAAK,KAAK,YAAY,EAAE,IAAI,CAAC,MAAM,SAAS,GAAG,EAAE,CAAC,EAAE,KAAK,oBAAoB;AACtG,QAAI,UAAU,SAAS,GAAG;AACxB,iBAAW,SAAS,WAAW;AAC7B,cAAM,QAAQ,KAAK,aAAa;AAChC,mBAAWW,SAAQ,OAAO;AACxB,gBAAM,QAAQA,MAAK;AACnB,cAAI,KAAK,YAAY,IAAI,CAAC,MAAM,EAAE,EAAE,EAAE,QAAQ,MAAM,EAAE,MAAM,IAAI;AAC9D;AAAA,UACF;AACA,gBAAM,eAAe,CAAC;AACtB,mBAAS,IAAI,GAAG,IAAIA,MAAK,cAAc,QAAQ,KAAK;AAClD,kBAAM,eAAeA,MAAK,cAAc;AACxC,kBAAM,aAAaA,MAAK,YAAY;AACpC,kBAAM,cAAcA,MAAK,cAAc;AACvC,kBAAM,WAAW,GAAG,aAAa,QAAQ,cAAc;AACvD,kBAAM,cAAc,qBAAqB;AACzC,yBAAa,KAAK,WAAW;AAAA,UAC/B;AACA,gBAAM,cAAc,MAAM,mBAAmB,iBAAiB,YAAY,CAAC;AAC3E,gBAAM,gBAAgB,mBAAmB,WAAW;AACpD,gBAAM,YAAY,MAAM,aAAa,QAAQA,KAAI;AACjD,mBAAS,IAAI,GAAG,IAAI,cAAc,QAAQ,KAAK;AAC7C,kBAAM,WAAW,GAAG,MAAM,QAAQ,aAAa;AAC/C,iCAAqB,YAAY,cAAc;AAAA,UACjD;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,eAAe,CAAC;AACtB,UAAM,kBAAkB,CAAC;AACzB,aAAS,KAAK,GAAG,KAAK,KAAK,aAAa,QAAQ,MAAM;AACpD,YAAM,QAAQ,KAAK,aAAa;AAChC,YAAM,YAAY,KAAK,wBAAwB;AAC/C,YAAM,cAAc,KAAK,0BAA0B;AACnD,YAAM,WAAW,GAAG,MAAM,QAAQ,aAAa;AAC/C,sBAAgB,KAAK,QAAQ;AAAA,IAC/B;AACA,aAAS,KAAK,GAAG,KAAK,gBAAgB,QAAQ,MAAM;AAClD,YAAM,MAAM,gBAAgB;AAC5B,cAAQ,OAAO,oBAAoB;AACnC,mBAAa,KAAK,qBAAqB,IAAI;AAAA,IAC7C;AACA,WAAO,iBAAiB,YAAY;AAAA,EACtC;AAAA,EACA,iBAAiB,QAAQ,OAAO;AAC9B,QAAI,SAAS,MAAM;AACjB,cAAQ,aAAa,MAAM,OAAO,MAAM;AAAA,IAC1C;AACA,UAAM,YAAY,CAAC;AACnB,aAAS,KAAK,GAAG,KAAK,KAAK,OAAO,QAAQ,EAAE,IAAI;AAC9C,YAAM,IAAI,KAAK,OAAO;AACtB,YAAM,IAAI,OAAO;AACjB,YAAMX,QAAO,MAAM;AACnB,gBAAU,EAAE,MAAM,CAAC,GAAGA,KAAI;AAAA,IAC5B;AACA,UAAM,YAAY,OAAO,KAAK,KAAK,YAAY,EAAE,IAAI,CAAC,MAAM,SAAS,GAAG,EAAE,CAAC,EAAE,KAAK,oBAAoB;AACtG,eAAW,SAAS,WAAW;AAC7B,YAAM,QAAQ,KAAK,aAAa;AAChC,iBAAWW,SAAQ,OAAO;AACxB,cAAM,QAAQA,MAAK;AACnB,cAAM,wBAAwBA,MAAK;AACnC,cAAM,yBAAyBA,MAAK;AACpC,cAAM,eAAe,IAAI,MAAM;AAC/B,mBAAW,KAAK,uBAAuB;AACrC,cAAI,EAAE,MAAM,WAAW;AACrB,yBAAa,KAAK,UAAU,EAAE,GAAG;AAAA,UACnC;AAAA,QACF;AACA,YAAI,aAAa,WAAW,sBAAsB,QAAQ;AACxD,cAAI,SAAS,CAAC;AACd,cAAI;AACJ,cAAI;AACJ,cAAI;AACJ,cAAI;AACJ,cAAIA,MAAK,YAAY,MAAM;AACzB,qBAASA,MAAK;AAAA,UAChB;AACA,cAAI,aAAa,WAAW,GAAG;AAC7B,kBAAM,CAAC,gBAAgB,YAAY,IAAI,aAAa;AACpD,gBAAI,OAAO,WAAW,MAAM;AAC1B,qBAAO,UAAU;AAAA,YACnB;AACA,6BAAiB,OAAO,MAAM,KAAK,gBAAgB,MAAM,CAAC;AAC1D,2BAAe,OAAO,MAAM,YAAY,gBAAgB,YAAY,CAAC;AACrE,8BAAkB,CAAC,cAAc;AACjC,4BAAgB,CAAC,YAAY;AAAA,UAC/B,OAAO;AACL,8BAAkB,aAAa,IAAI,CAAC,MAAM,EAAE,EAAE;AAC9C,4BAAgB,aAAa,IAAI,CAAC,MAAM,EAAE,EAAE;AAC5C,gBAAI,OAAO,WAAW,MAAM;AAC1B,qBAAO,UAAU;AAAA,YACnB;AACA,6BAAiB,OAAO,MAAM,KAAK,iBAAiB,MAAM,CAAC;AAC3D,2BAAe,OAAO,MAAM,YAAY,iBAAiB,aAAa,CAAC;AAAA,UACzE;AACA,cAAI,MAAM,qBAAqB;AAC7B,kBAAM,IAAI,oBAAoB,uHAAuH;AAAA,UACvJ;AACA,mBAAS,KAAK,GAAG,KAAK,uBAAuB,QAAQ,EAAE,IAAI;AACzD,kBAAM,IAAI,uBAAuB;AACjC,kBAAM,IAAI,eAAe;AACzB,kBAAMX,QAAO,aAAa;AAC1B,sBAAU,EAAE,MAAM,CAAC,GAAGA,KAAI;AAAA,UAC5B;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,gBAAgB,CAAC;AACvB,UAAM,cAAc,CAAC;AACrB,UAAM,eAAe,CAAC;AACtB,eAAW,KAAK,KAAK,SAAS;AAC5B,cAAQ,EAAE,MAAM,WAAW,4BAA4B,EAAE,UAAU,EAAE,IAAI;AACzE,YAAM,CAAC,SAASA,KAAI,IAAI,UAAU,EAAE;AACpC,mBAAa,KAAK,QAAQ,KAAK;AAC/B,oBAAc,KAAK,OAAO;AAC1B,kBAAY,KAAKA,KAAI;AAAA,IACvB;AACA,WAAO,CAAC,eAAe,aAAa,YAAY;AAAA,EAClD;AAAA,EACA,uBAAuB,QAAQ;AAC7B,UAAM,oBAAoB,CAAC;AAC3B,QAAI;AACJ,eAAW,SAAS,KAAK,QAAQ;AAC/B,kBAAY,iBAAiB,YAAY,IAAI;AAC7C,eAAS,oBAAoB,GAAG,oBAAoB,MAAM,aAAa,QAAQ,qBAAqB;AAClG,cAAM,UAAU,UAAU,QAAQ,OAAO,iBAAiB;AAC1D,YAAI,KAAK,eAAe,IAAI,OAAO,GAAG;AACpC,4BAAkB,WAAW;AAC7B,uBAAa;AAAA,QACf;AAAA,MACF;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,SAAS,MAAMI,QAAO;AACpB,QAAIA,UAAS,MAAM;AACjB,UAAI,KAAK,OAAO,UAAUA,QAAO;AAC/B,cAAM,IAAI,WAAW,wCAAwCA,8BAA6B,KAAK,OAAO,kBAAkB;AAAA,MAC1H,OAAO;AACL,eAAO,KAAK,OAAOA;AAAA,MACrB;AAAA,IACF,OAAO;AACL,UAAI,QAAQ,MAAM;AAChB,cAAM,IAAI,WAAW,4CAA4C;AAAA,MACnE;AAAA,IACF;AACA,eAAW,SAAS,KAAK,QAAQ;AAC/B,UAAI,MAAM,SAAS,MAAM;AACvB,eAAO;AAAA,MACT;AAAA,IACF;AACA,UAAM,IAAI,WAAW,kBAAkB,MAAM;AAAA,EAC/C;AAAA,EACA,kBAAkB;AAChB,WAAO,KAAK,MAAM;AAChB,YAAM,UAAU,CAAC;AACjB,iBAAW,SAAS,KAAK,QAAQ;AAC/B,iBAAS,YAAY,GAAG,YAAY,MAAM,aAAa,QAAQ,EAAE,WAAW;AAC1E,gBAAM,UAAU,UAAU,QAAQ,OAAO,SAAS;AAClD,cAAI,KAAK,eAAe,IAAI,OAAO,GAAG;AACpC,oBAAQ,KAAK,GAAG,MAAM,gBAAgB,CAAC;AAAA,UACzC;AAAA,QACF;AAAA,MACF;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMK,UAAS,EAAE,MAAM,KAAK,KAAK;AACjC,UAAM,oBAAoB,KAAK,uBAAuB,KAAK,MAAM;AACjE,UAAM,eAAe,CAAC;AACtB,eAAW,SAAS,KAAK,QAAQ;AAC/B,YAAM,iBAAiB,MAAM,aAAa;AAC1C,YAAM,cAAc,MAAM,UAAU;AACpC,YAAM,uBAAuB,CAAC;AAC9B,eAAS,oBAAoB,GAAG,oBAAoB,MAAM,aAAa,QAAQ,qBAAqB;AAClG,cAAME,QAAO,MAAM,aAAa;AAChC,cAAM,UAAU,UAAU,QAAQ,OAAO,iBAAiB;AAC1D,YAAI,SAAS,CAAC;AACd,YAAI,KAAK,eAAe,IAAI,OAAO,GAAG;AACpC,cAAIA,MAAK,UAAU;AACjB,gBAAI;AACF,mBAAK,UAAUA,MAAK,QAAQ;AAC5B,uBAASA,MAAK;AAAA,YAChB,SAAS,KAAP;AACA,sBAAQ,KAAK,SAAS,MAAM,uDAAuDA,MAAK,iHAAiH;AACzM,uBAAS,CAAC;AAAA,YACZ;AAAA,UACF;AACA,cAAIA,MAAK,cAAc,SAAS,GAAG;AACjC,kBAAM,WAAW,CAAC;AAClB,qBAAS,KAAK,GAAG,KAAKA,MAAK,cAAc,QAAQ,MAAM;AACrD,oBAAM,eAAeA,MAAK,cAAc;AACxC,oBAAM,YAAYA,MAAK,YAAY;AACnC,oBAAM,cAAcA,MAAK,cAAc;AACvC,oBAAM,WAAW,UAAU,QAAQ,cAAc,SAAS;AAC1D,kBAAI,eAAe,kBAAkB;AACrC,kBAAI,gBAAgB,MAAM;AACxB,+BAAe;AAAA,cACjB;AACA,uBAAS,KAAK,CAAC,aAAa,MAAM,cAAc,aAAa,MAAM,CAAC;AAAA,YACtE;AACA,iCAAqB,KAAK,QAAQ;AAAA,UACpC;AAAA,QACF;AAAA,MACF;AACA,YAAM,OAAO,CAAC;AACd,WAAK,UAAU,MAAM;AACrB,WAAK,eAAe;AACpB,WAAK,YAAY;AACjB,WAAK,kBAAkB;AACvB,mBAAa,KAAK,IAAI;AAAA,IACxB;AACA,IAAAF,QAAO,YAAY;AACnB,UAAM,cAAc,CAAC;AACrB,aAAS,KAAK,GAAG,KAAK,KAAK,YAAY,QAAQ,MAAM;AACnD,YAAM,QAAQ,KAAK,YAAY;AAC/B,YAAM,YAAY,KAAK,uBAAuB;AAC9C,YAAM,UAAU,UAAU,QAAQ,OAAO,SAAS;AAClD,UAAI,CAAC,KAAK,eAAe,IAAI,OAAO,GAAG;AACrC;AAAA,MACF;AACA,UAAI,eAAe,kBAAkB;AACrC,UAAI,iBAAiB,QAAQ,iBAAiB,QAAQ;AACpD,uBAAe;AAAA,MACjB;AACA,YAAM,cAAc,KAAK,yBAAyB;AAClD,kBAAY,KAAK,CAAC,MAAM,MAAM,cAAc,WAAW,CAAC;AAAA,IAC1D;AACA,IAAAA,QAAO,iBAAiB;AACxB,UAAM,eAAe,CAAC;AACtB,aAAS,KAAK,GAAG,KAAK,KAAK,aAAa,QAAQ,MAAM;AACpD,YAAM,QAAQ,KAAK,aAAa;AAChC,YAAM,YAAY,KAAK,wBAAwB;AAC/C,YAAM,UAAU,UAAU,QAAQ,OAAO,SAAS;AAClD,UAAI,CAAC,KAAK,eAAe,IAAI,OAAO,GAAG;AACrC;AAAA,MACF;AACA,UAAI,eAAe,kBAAkB;AACrC,UAAI,iBAAiB,QAAQ,iBAAiB,QAAQ;AACpD,uBAAe;AAAA,MACjB;AACA,YAAM,cAAc,KAAK,0BAA0B;AACnD,mBAAa,KAAK,CAAC,MAAM,MAAM,cAAc,WAAW,CAAC;AAAA,IAC3D;AACA,IAAAA,QAAO,kBAAkB;AACzB,WAAOA;AAAA,EACT;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ,gBAAgB,CAAC,GAAG,iBAAiB,OAAO;AACzE,UAAM,gBAAgB,CAAC;AACvB,UAAM,mBAAmB,CAAC;AAC1B,aAAS,mBAAmB,OAAO,UAAU;AAC3C,UAAI,EAAE,MAAM,QAAQ,mBAAmB;AACrC,yBAAiB,MAAM,QAAQ,CAAC,QAAQ;AAAA,MAC1C,OAAO;AACL,yBAAiB,MAAM,MAAM,KAAK,QAAQ;AAAA,MAC5C;AAAA,IACF;AACA,aAAS,YAAY,OAAO,UAAU;AACpC,YAAM,gBAAgB,CAAC;AACvB,UAAI;AACJ,iBAAW,aAAa,UAAU;AAChC,cAAM,mBAAmB,UAAU;AACnC,cAAM,mBAAmB,UAAU;AACnC,cAAM,qBAAqB,UAAU;AACrC,iBAAS,UAAU,MAAM,OAAO,CAAC,IAAI,UAAU;AAC/C,YAAI,EAAE,oBAAoB,gBAAgB;AACxC,6BAAmB,OAAO,QAAQ;AAClC;AAAA,QACF;AACA,cAAM,eAAe,cAAc;AACnC,YAAI,aAAa,aAAa,UAAU,kBAAkB;AACxD,6BAAmB,OAAO,QAAQ;AAClC;AAAA,QACF;AACA,cAAM,cAAc,aAAa,aAAa;AAC9C,sBAAc,KAAK,YAAY,cAAc,mBAAmB;AAAA,MAClE;AACA,UAAI,cAAc,SAAS,GAAG;AAC5B,cAAM,MAAM,iBAAiB,aAAa,GAAG,MAAM;AAAA,MACrD;AAAA,IACF;AACA,aAAS,aAAa,WAAW;AAC/B,YAAM,YAAY,UAAU;AAC5B,YAAM,QAAQ,YAAY,WAAWA,QAAO,oBAAoB,OAAOA,QAAO,mBAAmB,CAAC,CAAC;AACnG,YAAM,6BAA6B,cAAc;AACjD,oBAAc,aAAa;AAC3B,YAAM,mBAAmB,UAAU;AACnC,uBAAiB,QAAQ,CAAC,aAAa;AACrC,YAAI,EAAE,oBAAoB,QAAQ;AAChC,gBAAM,IAAI,WAAW,yDAAyD,UAAU;AAAA,QAC1F;AACA,2BAAmB,OAAO,QAAQ;AAAA,MACpC,CAAC;AAAA,IACH;AACA,UAAM,OAAOA,QAAO;AACpB,UAAM,mBAAmBA,QAAO;AAChC,eAAW,aAAa,kBAAkB;AACxC,mBAAa,SAAS;AAAA,IACxB;AACA,WAAO,CAAC,cAAc,gBAAgB,GAAG;AACvC,iBAAW,aAAa,kBAAkB;AACxC,cAAM,QAAQ,cAAc,UAAU;AACtC,YAAI,MAAM,QAAQ,kBAAkB;AAClC,gBAAM,kCAAkC,iBAAiB,MAAM;AAC/D,iBAAO,iBAAiB,MAAM;AAC9B,qBAAW,YAAY,iCAAiC;AACtD,wBAAY,OAAO,QAAQ;AAAA,UAC7B;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,eAAe,CAAC;AACtB,UAAM,gBAAgB,CAAC;AACvB,UAAM,wBAAwBA,QAAO;AACrC,eAAW,aAAa,uBAAuB;AAC7C,YAAM,YAAY,UAAU;AAC5B,YAAM,YAAY,UAAU;AAC5B,YAAM,cAAc,UAAU;AAC9B,cAAQ,aAAa,aAAa;AAClC,YAAM,QAAQ,cAAc;AAC5B,YAAM,qBAAqB,MAAM,aAAa,WAAW;AACzD,mBAAa,KAAK,mBAAmB,YAAY;AAAA,IACnD;AACA,UAAM,yBAAyBA,QAAO;AACtC,eAAW,aAAa,wBAAwB;AAC9C,YAAM,YAAY,UAAU;AAC5B,YAAM,YAAY,UAAU;AAC5B,YAAM,cAAc,UAAU;AAC9B,cAAQ,aAAa,aAAa;AAClC,YAAM,QAAQ,cAAc;AAC5B,YAAM,qBAAqB,MAAM,aAAa,WAAW;AACzD,oBAAc,KAAK,mBAAmB,YAAY;AAAA,IACpD;AACA,WAAO,IAAI,IAAI,EAAE,QAAQ,cAAc,SAAS,eAAe,KAAK,CAAC;AAAA,EACvE;AAAA,EACA,IAAI,WAAW;AACb,QAAI,KAAK,WAAW;AAClB,YAAM,IAAI,WAAW,sLAAsL;AAAA,IAC7M;AACA,eAAW,SAAS,KAAK,QAAQ;AAC/B,UAAI,MAAM,UAAU;AAClB,eAAO;AAAA,MACT;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,cAAc;AACZ,SAAK,MAAM;AACT,WAAK,OAAO,QAAQ,CAAC,UAAU;AAC7B,YAAI,MAAM,UAAU;AAClB,gBAAM,YAAY;AAAA,QACpB;AAAA,MACF,CAAC;AAAA,IACH,CAAC;AAAA,EACH;AACF;AAGA,SAAS,gCAAgC,SAAS,aAAa,YAAY;AACzE,QAAM,aAAa,YAAY;AAC/B,MAAI,WAAW,QAAQ,MAAM,QAAQ,OAAO,KAAK,QAAQ,WAAW,GAAG;AACrE,WAAO,YAAY,IAAI,CAAC,SAAS,IAAI;AAAA,EACvC;AACA,MAAI,eAAe,GAAG;AACpB,QAAI,MAAM,QAAQ,OAAO,KAAK,QAAQ,WAAW,GAAG;AAClD,aAAO;AAAA,IACT,WAAW,OAAO,YAAY,YAAY,YAAY,MAAM,SAAS;AACnE,aAAO,CAAC,QAAQ,YAAY,GAAG;AAAA,IACjC,OAAO;AACL,aAAO,CAAC,OAAO;AAAA,IACjB;AAAA,EACF;AACA,MAAI,MAAM,QAAQ,OAAO,GAAG;AAC1B,QAAI,QAAQ,WAAW,YAAY;AACjC,YAAM,IAAI,MAAM,YAAY,6BAA6B,QAAQ,wCAAwC,mFAAmF;AAAA,IAC9L;AACA,WAAO;AAAA,EACT,WAAW,OAAO,YAAY,YAAY,OAAO,KAAK,OAAO,EAAE,SAAS,KAAK,OAAO,QAAQ,OAAO,KAAK,OAAO,EAAE,QAAQ,UAAU;AACjI,UAAM,SAAS,CAAC;AAChB,gBAAY,QAAQ,CAAC,eAAe;AAClC,UAAI,cAAc,SAAS;AACzB,eAAO,KAAK,QAAQ,WAAW;AAAA,MACjC,OAAO;AACL,eAAO,KAAK,IAAI;AAAA,MAClB;AAAA,IACF,CAAC;AACD,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,2BAA2B,2BAA2B,2CAA2C,yCAAyC,8BAA8B,8BAA8B,KAAK,UAAU,OAAO,GAAG;AAAA,EACjP;AACF;AACA,SAAS,wBAAwB,aAAa,aAAa;AACzD,SAAO,gCAAgC,aAAa,aAAa,aAAa;AAChF;AACA,eAAe,mBAAmB,GAAG,cAAc,aAAa,kBAAkB;AAChF,MAAI,gBAAgB,QAAQ,oBAAoB,MAAM;AACpD,UAAM,IAAI,MAAM,6CAA6C;AAAA,EAC/D;AACA,MAAI,eAAe,MAAM;AACvB,UAAM,WAAW,KAAK,MAAM;AAC1B,UAAI,EAAE,MAAM,WAAW,GAAG;AACxB,eAAO,MAAM,CAAC;AAAA,MAChB,WAAW,EAAE,MAAM,WAAW,GAAG;AAC/B,YAAI,EAAE,MAAM,KAAK,GAAG;AAClB,gBAAM,OAAO;AACb,iBAAO,OAAO,GAAG,IAAI;AAAA,QACvB,WAAW,EAAE,MAAM,OAAO,GAAG;AAC3B,iBAAO,QAAQ,GAAG,CAAC,EAAE,MAAM,EAAE,CAAC;AAAA,QAChC,OAAO;AACL,gBAAM,IAAI,MAAM,+CAA+C,EAAE,MAAM,wEAAwE;AAAA,QACjJ;AAAA,MACF,OAAO;AACL,cAAM,IAAI,MAAM,yCAAyC,EAAE,4EAA4E;AAAA,MACzI;AAAA,IACF,CAAC;AACD,UAAM,gBAAgB,MAAM,KAAK,MAAM,SAAS,KAAK,CAAC;AACtD,YAAQ,QAAQ;AAChB,UAAM,oBAAoB,CAAC;AAC3B,kBAAc,QAAQ,CAAC,eAAe;AACpC,UAAI,YAAY,eAAe,MAAM;AACnC,cAAM,IAAI,MAAM,wEAAwE,sDAAsD;AAAA,MAChJ,OAAO;AACL,0BAAkB,KAAK,YAAY,WAAW;AAAA,MAChD;AAAA,IACF,CAAC;AACD,WAAO,SAAS,mBAAmB,SAAS;AAAA,EAC9C,OAAO;AACL,WAAO;AAAA,EACT;AACF;AACA,SAAS,qBAAqB,SAAS,eAAe;AACpD,SAAO,IAAI,SAAS,aAAa;AACnC;AAGA,IAAI,gCAAgC;AACpC,SAAS,8BAA8Be,SAAQ,aAAa;AAC1D,MAAI;AACJ,MAAI;AACJ,QAAM,iBAAiB;AACvB,OAAK,eAAe;AACpB,OAAK,eAAe;AACpB,eAAa,OAAO,MAAM,QAAQ,MAAM,MAAM,MAAM,mPAAmP,aAAa;AACpT,QAAM,cAAc,0BAA0B,SAASA,QAAO,YAAY,EAAE;AAC5E,QAAM,cAAc,0BAA0B,UAAUA,QAAO,aAAa,EAAE;AAC9E,QAAM,YAAY,YAAY,GAAG,MAAM;AACvC,eAAa,OAAO,YAAY,WAAWA,QAAO,OAAO,QAAQ,MAAM,mBAAmBA,QAAO,OAAO,2CAA2C,YAAY,yCAAyC,KAAK,UAAUA,QAAO,UAAU,IAAI;AAC5O,eAAa,OAAO,YAAY,WAAWA,QAAO,QAAQ,QAAQ,MAAM,mBAAmBA,QAAO,QAAQ,4CAA4C,YAAY,2CAA2C,KAAK,UAAUA,QAAO,WAAW,IAAI;AAClP,WAAS,SAAS,GAAG,SAAS,YAAY,QAAQ,UAAU;AAC1D,iBAAa,OAAO,YAAY,QAAQ,MAAM,OAAO,WAAW,MAAM,8BAA8BA,QAAO,WAAW,eAAe,YAAY,QAAQ,MAAM,iBAAiB,4BAA4BA,QAAO,WAAW,KAAK;AAAA,EACrO;AACA,WAAS,SAAS,GAAG,SAAS,YAAY,QAAQ,UAAU;AAC1D,iBAAa,OAAO,YAAY,QAAQ,MAAM,OAAO,WAAW,MAAM,+BAA+BA,QAAO,YAAY,eAAe,YAAY,QAAQ,MAAM,iBAAiB,4BAA4BA,QAAO,WAAW,KAAK;AAAA,EACvO;AACA,SAAO,EAAE,IAAI,aAAa,IAAI,YAAY;AAC5C;AACA,SAAS,0BAA0B,eAAe,OAAO,QAAQ;AAC/D,MAAI,kBAAkB,QAAQ;AAC5B,WAAO,CAAC,MAAM;AAAA,EAChB,WAAW,MAAM,QAAQ,MAAM,GAAG;AAChC,iBAAa,OAAO,OAAO,WAAW,MAAM,QAAQ,MAAM,wBAAwB,OAAO,gCAAgC,MAAM,uBAAuB,sBAAsB,QAAQ;AACpL,WAAO;AAAA,EACT,OAAO;AACL,UAAM,SAAS,CAAC;AAChB,eAAW,QAAQ,OAAO;AACxB,UAAI,OAAO,SAAS,MAAM;AACxB,cAAM,IAAI,WAAW,gEAAgE,sBAAsB,QAAQ;AAAA,MACrH;AACA,aAAO,KAAK,OAAO,KAAK;AAAA,IAC1B;AACA,WAAO;AAAA,EACT;AACF;AACA,SAAS,gCAAgC,MAAM;AAC7C,MAAI,KAAK,WAAW,GAAG;AACrB,UAAM,IAAI,oBAAoB,wDAAwD;AAAA,EACxF;AACA,SAAO,EAAE,IAAI,KAAK,IAAI,IAAI,KAAK,GAAG;AACpC;AACA,eAAe,WAAWA,SAAQ,SAAS,MAAM;AAC/C,QAAM,qBAAqB,KAAK,mBAAmB;AACnD,eAAa,OAAOA,QAAO,aAAa,MAAM,MAAM,gGAAgG;AACpJ,eAAa,OAAO,QAAQ,MAAM,MAAM,+FAA+F;AACvI,eAAa,OAAO,KAAK,UAAU,QAAQ,KAAK,SAAS,KAAK,OAAO,UAAU,KAAK,MAAM,GAAG,MAAM,iFAAiF,KAAK,QAAQ;AACjM,eAAa,OAAO,CAAC,sBAAsB,KAAK,kBAAkB,KAAK,OAAO,UAAU,KAAK,eAAe,GAAG,MAAM,uGAAuG,KAAK,iBAAiB;AAClP,eAAa;AAAA,IACX,KAAK,sBAAsB;AAAA,IAC3B,MAAM;AAAA,EACR;AACA,MAAIA,QAAO,YAAY;AACrB,UAAM,IAAI,MAAM,8DAA8D;AAAA,EAChF;AACA,EAAAA,QAAO,aAAa;AACpB,MAAI;AACF,UAAM,eAAe,KAAK,kBAAkB;AAC5C,QAAI;AACJ,QAAI;AACJ,QAAI,cAAc;AAChB,UAAI,gBAAgB,KAAK,cAAc,GAAG;AACxC,qBAAa,OAAO,KAAK,qBAAqB,QAAQ,KAAK,oBAAoB,KAAK,OAAO,UAAU,KAAK,iBAAiB,GAAG,MAAM,iJAAiJ,KAAK,mBAAmB;AAAA,MAC/S,OAAO;AACL,cAAM,iBAAiB,gCAAgC,KAAK,cAAc;AAC1E,gBAAQ,eAAe;AACvB,gBAAQ,eAAe;AAAA,MACzB;AAAA,IACF;AACA,UAAM,gBAAgBA,QAAO,kBAAkB;AAC/C,UAAM,YAAYA,QAAO,uBAAuB;AAChD,QAAI;AACJ,QAAI,cAAc;AAChB,wBAAkB,UAAU,MAAM,EAAE,OAAO,UAAU,IAAI,CAAC,OAAO,SAAS,EAAE,CAAC;AAAA,IAC/E,OAAO;AACL,wBAAkB,UAAU,MAAM;AAAA,IACpC;AACA,UAAM,aAAa,qBAAqB,KAAK,WAAW,KAAK,UAAU;AACvE,UAAM,UAAU,KAAK,WAAW,OAAO,IAAI,KAAK;AAChD,UAAM,EAAE,cAAc,QAAQ,IAAI;AAAA,MAChC;AAAA,MACA;AAAA,MACA,KAAK;AAAA,MACL;AAAA,MACA;AAAA,MACA,iBAAiB,SAAS,IAAI;AAAA,MAC9B;AAAA,MACA;AAAA,MACA;AAAA,IACF;AACA,iBAAa,SAASA,OAAM;AAC5B,IAAAA,QAAO,UAAU;AACjB,UAAM,aAAa,aAAa;AAChC,IAAAA,QAAO,gBAAgB;AACvB,QAAI,QAAQ,KAAK,gBAAgB,OAAO,IAAI,KAAK;AACjD,QAAI,eAAe,MAAM,QAAQ,SAAS;AAC1C,WAAO,QAAQ,KAAK,QAAQ;AAC1B,YAAM,YAAY,CAAC;AACnB,YAAM,aAAa,aAAa,KAAK;AACrC,UAAI,YAAY;AAChB,UAAI,aAAa;AACjB,UAAI,CAAC,oBAAoB;AACvB,uBAAe,MAAM,QAAQ,SAAS;AAAA,MACxC;AACA,aAAO,qBAAqB,YAAY,KAAK,kBAAkB,MAAM;AACnE,cAAM,cAAc,MAAM,aAAa,KAAK;AAC5C,YAAI,sBAAsB,YAAY,MAAM;AAC1C,kBAAQ,KAAK,uCAAuC,KAAK,oEAAoE,mJAAmJ,KAAK,kBAAkB,KAAK,wFAAwF;AACpY;AAAA,QACF;AACA,YAAI,YAAY,SAAS,MAAM;AAC7B,gBAAM,EAAE,IAAI,GAAG,IAAI,8BAA8BA,SAAQ,YAAY,KAAK;AAC1E,gBAAM,YAAY,CAAC;AACnB,oBAAU,WAAW;AACrB,oBAAU,UAAU,GAAG,GAAG,MAAM;AAChC,gBAAM,aAAa,aAAa,YAAY,SAAS;AACrD,gBAAM,gBAAgB,CAAC;AACvB,cAAI,KAAK,eAAe,MAAM;AAC5B,kBAAM,uBAAuB,wBAAwB,KAAK,aAAaA,QAAO,WAAW;AACzF,qBAAS,KAAK,GAAG,KAAK,qBAAqB,QAAQ,EAAE,IAAI;AACvD,4BAAc,KAAK,MAAM,mBAAmB,GAAG,KAAK,MAAM,qBAAqB,GAAG,CAAC;AAAA,YACrF;AAAA,UACF;AACA,gBAAM,MAAM,GAAG,OAAO,EAAE,EAAE,OAAO,aAAa;AAC9C,gBAAM,OAAO,cAAc,GAAG;AAC9B,kBAAQ,GAAG;AACX,mBAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,kBAAM,QAAQ,UAAU;AACxB,kBAAM,MAAM,KAAK;AACjB,sBAAU,SAAS;AACnB,iBAAK,GAAG;AAAA,UACV;AACA,gBAAM,aAAa,WAAW,YAAY,SAAS;AACnD,+BAAqB,SAAS;AAC9B;AACA;AAAA,QACF;AACA,YAAI,qBAAqB,aAAa,KAAK,kBAAkB,YAAY,MAAM;AAC7E,cAAI,cAAc;AAChB,gBAAI;AACJ,gBAAI,gBAAgB,KAAK,cAAc,GAAG;AACxC,wBAAU,OAAO,MAAMA,QAAO,gBAAgB,KAAK,gBAAgB,EAAE,SAAS,KAAK,kBAAkB,CAAC,CAAC;AAAA,YACzG,OAAO;AACL,wBAAU,OAAOA,QAAO,SAAS,OAAO,OAAO;AAAA,gBAC7C,WAAW,KAAK,uBAAuB,OAAO,gCAAgC,KAAK;AAAA,gBACnF,SAAS;AAAA,cACX,CAAC,CAAC;AAAA,YACJ;AACA,qBAAS,KAAK,GAAG,KAAKA,QAAO,aAAa,QAAQ,EAAE,IAAI;AACtD,wBAAU,OAAOA,QAAO,aAAa,SAAS,QAAQ;AAAA,YACxD;AAAA,UACF;AACA;AAAA,QACF;AACA,YAAIA,QAAO,eAAe;AACxB;AAAA,QACF;AAAA,MACF;AACA,YAAM,aAAa,WAAW,OAAO,SAAS;AAC9C;AACA,UAAIA,QAAO,eAAe;AACxB;AAAA,MACF;AAAA,IACF;AACA,UAAM,aAAa,WAAW;AAC9B,UAAMA,QAAO,QAAQ,SAAS;AAC9B,WAAOA,QAAO;AAAA,EAChB,UAAE;AACA,IAAAA,QAAO,aAAa;AAAA,EACtB;AACF;AACA,SAAS,iBAAiB,SAAS,MAAM;AACvC,MAAI,gBAAgB;AACpB,MAAI,KAAK,mBAAmB,MAAM;AAChC,oBAAgB,KAAK;AAAA,EACvB,WAAW,OAAO,SAAS,QAAQ,IAAI,GAAG;AACxC,oBAAgB,QAAQ;AAAA,EAC1B;AACA,SAAO;AACT;AACA,SAAS,gBAAgB,SAAS;AAChC,SAAO,OAAO,QAAQ,aAAa;AACrC;AACA,SAAS,qBAAqB,UAAU;AACtC,SAAO,OAAO,SAAS,SAAS;AAClC;AACA,eAAe,gBAAgBA,SAAQ,SAAS,MAAM;AACpD,SAAO,QAAQ,CAAC;AAChB,QAAM,aAAa,KAAK,WAAW;AACnC,QAAM,IAAIA,QAAO;AACjB,MAAI,OAAO,CAAC;AACZ,MAAI,KAAK,UAAU,GAAG;AACpB,UAAM,IAAI,oBAAoB,sCAAsC;AAAA,EACtE;AACA,eAAa,OAAO,CAAC,cAAc,KAAK,UAAU,KAAK,OAAO,UAAU,KAAK,OAAO,GAAG,MAAM,wEAAwE,KAAK,UAAU,KAAK,OAAO,GAAG;AACnM,QAAM,eAAe,qBAAqB,OAAO,IAAI,UAAU,MAAM,QAAQ,SAAS;AACtF,MAAI,cAAc;AAClB,MAAI,QAAQ;AACZ,SAAO,aAAa,QAAQ,KAAK,UAAU,MAAM;AAC/C,UAAM,cAAc,MAAM,aAAa,KAAK;AAC5C,WAAO,KAAK,MAAM;AAChB,UAAI,YAAY,OAAO;AACrB,cAAM,EAAE,IAAI,GAAG,IAAI,8BAA8BA,SAAQ,YAAY,KAAK;AAC1E,cAAM,UAAU,GAAG,OAAO,EAAE;AAC5B,cAAM,YAAY,KAAK,MAAM,EAAE,OAAO,CAAC;AACvC,gBAAQ,OAAO;AACf,YAAI,UAAU,GAAG;AACf,mBAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,iBAAK,KAAK,OAAO,CAAC,CAAC;AAAA,UACrB;AAAA,QACF;AACA,cAAM,YAAY,QAAQ,GAAG,MAAM;AACnC,iBAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,gBAAM,WAAW,UAAU;AAC3B,gBAAM,YAAY,KAAK;AACvB,eAAK,MAAM,KAAK,MAAM,KAAK,KAAK,KAAK,IAAI,WAAW,QAAQ,CAAC,CAAC;AAC9D,cAAI,QAAQ,GAAG;AACb,oBAAQ,SAAS;AAAA,UACnB;AAAA,QACF;AACA,gBAAQ,SAAS;AACjB,uBAAe;AACf,UAAE;AAAA,MACJ;AACA,aAAO;AAAA,IACT,CAAC;AACD,QAAI,YAAY,MAAM;AACpB,UAAI,YAAY;AACd,gBAAQ,KAAK,gLAAgL,KAAK,yFAAyF;AAAA,MAC7R;AACA;AAAA,IACF;AAAA,EACF;AACA,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,YAAY,KAAK;AACvB,SAAK,MAAM,IAAI,KAAK,KAAK,WAAW;AACpC,YAAQ,SAAS;AAAA,EACnB;AACA,SAAO,iBAAiB,IAAI;AAC9B;AAGA,SAAS,eAAe,WAAW;AACjC,eAAa,OAAO,YAAY,KAAK,OAAO,UAAU,SAAS,GAAG,MAAM,2DAA2D,WAAW;AAChJ;AACA,SAAS,YAAY,QAAQ,OAAO,MAAM;AACxC,MAAI,UAAU,MAAM;AAClB,WAAO,CAAC,IAAI;AAAA,EACd,WAAW,MAAM,QAAQ,MAAM,GAAG;AAChC,WAAO,OAAO,IAAI,CAAC,WAAW,oBAAoB,QAAQ,OAAO,OAAO,KAAK,CAAC;AAAA,EAChF,OAAO;AACL,WAAO,oBAAoB,QAAQ,OAAO,OAAO,KAAK;AAAA,EACxD;AACF;AACA,SAAS,qBAAqB,QAAQ,SAAS;AAC7C,SAAO,KAAK,MAAM;AAChB,QAAI,UAAU,MAAM;AAClB,aAAO;AAAA,IACT,WAAW,MAAM,QAAQ,MAAM,GAAG;AAChC,aAAO,OAAO,IAAI,CAAC,WAAW,qBAAqB,QAAQ,OAAO,CAAC;AAAA,IACrE,OAAO;AACL,aAAO,QAAQ,QAAQ,QAAQ,UAAU,UAAU,UAAU,KAAK,SAAS,OAAO,CAAC;AAAA,IACrF;AAAA,EACF,CAAC;AACH;AACA,SAAS,YAAY7B,OAAM,WAAW;AACpC,QAAM,SAAS,CAAC;AAChB,MAAI,aAAa;AACjB,MAAI,WAAW;AACf,SAAO,aAAaA,OAAM;AACxB,eAAW,aAAa;AACxB,QAAI,YAAYA,OAAM;AACpB,iBAAWA;AAAA,IACb;AACA,WAAO,KAAK,CAAC,YAAY,QAAQ,CAAC;AAClC,iBAAa;AAAA,EACf;AACA,SAAO;AACT;AACA,eAAe,QAAQ6B,SAAQ,GAAG,KAAK,WAAW,WAAW,QAAQ,SAAS,YAAY,MAAM,QAAQ,UAAU,iBAAiB,cAAc,eAAe,iBAAiB;AAC/K,MAAI,aAAa,MAAM;AACrB,gBAAY;AAAA,EACd;AACA,MAAI,UAAU,MAAM;AAClB,aAAS;AAAA,EACX;AACA,MAAI,YAAY,MAAM;AACpB,eAAW;AAAA,EACb;AACA,MAAI,gBAAgB,MAAM;AACxB,mBAAe;AAAA,EACjB;AACA,MAAI,eAAe;AACnB,MAAI,QAAQ,QAAQ,UAAU,MAAM;AAClC,mBAAe;AAAA,EACjB;AACA,MAAI,mBAAmB,MAAM;AAC3B,mBAAe;AACf,QAAI,iBAAiB,MAAM;AACzB,YAAM,IAAI,WAAW,kGAAkG;AAAA,IACzH;AAAA,EACF;AACA,QAAM,kBAAkBA,QAAO,gBAAgB,KAAK,WAAW,eAAe,iBAAiB;AAC/F,MAAI;AACJ,MAAI,mBAAmB,MAAM;AAC3B,iBAAa,OAAO,GAAG,eAAe;AAAA,EACxC;AACA,MAAI,WAAW,MAAM;AACnB,cAAU;AAAA,EACZ;AACA,QAAM,EAAE,cAAc,QAAQ,IAAI,mBAAmB,YAAY,SAAS,QAAQ,cAAc,iBAAiB,eAAe,WAAW,cAAc,eAAe;AACxK,eAAa,SAASA,OAAM;AAC5B,EAAAA,QAAO,UAAU;AACjB,QAAM,aAAa,aAAa;AAChC,EAAAA,QAAO,gBAAgB;AACvB,WAAS,QAAQ,cAAc,QAAQ,QAAQ,EAAE,OAAO;AACtD,UAAM,aAAa,aAAa,KAAK;AACrC,UAAM,YAAY,CAAC;AACnB,QAAI,iBAAiB,MAAM;AACzB,YAAM,IAAI,oBAAoB,4CAA4C;AAAA,IAC5E,OAAO;AACL,UAAI,aAAa,SAAS;AACxB,cAAM,IAAI,oBAAoB,wCAAwC;AAAA,MACxE,WAAW,UAAU;AACnB,qBAAa,QAAQ,UAAU;AAAA,MACjC;AACA,YAAM,oBAAoB,SAAS,UAAU;AAC7C,YAAM,UAAU,YAAY,iBAAiB,SAAS;AACtD,eAAS,aAAa,GAAG,aAAa,QAAQ,QAAQ,EAAE,YAAY;AAClE,cAAM,YAAY,CAAC;AACnB,cAAM,aAAa,aAAa,YAAY,SAAS;AACrD,aAAK,MAAM;AACT,gBAAM,aAAa,QAAQ,YAAY;AACvC,gBAAM,WAAW,QAAQ,YAAY;AACrC,gBAAM,WAAW,oBAAoB,mBAAmB,YAAY,WAAW,UAAU;AACzF,oBAAU,WAAW;AACrB,oBAAU,UAAU,WAAW;AAC/B,gBAAM,WAAW,qBAAqB,KAAK,QAAQ;AACnD,gBAAM,OAAO,EAAE,QAAQ;AACvB,mBAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,kBAAM,QAAQ,UAAU;AACxB,kBAAM,MAAM,KAAK;AACjB,sBAAU,SAAS;AACnB,iBAAK,GAAG;AAAA,UACV;AACA,cAAI,eAAe,QAAQ,SAAS,GAAG;AACrC,gBAAI,cAAc;AAChB,oBAAM,UAAUA,QAAO,SAAS,MAAM,QAAQ,SAAS;AACvD,uBAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,sBAAM,QAAQ,UAAU;AACxB,sBAAM,MAAM,QAAQ;AACpB,qBAAK,GAAG;AACR,0BAAU,SAAS,SAAS;AAAA,cAC9B;AAAA,YACF;AAAA,UACF;AAAA,QACF,CAAC;AACD,cAAM,aAAa,WAAW,YAAY,SAAS;AACnD,6BAAqB,SAAS;AAC9B,YAAIA,QAAO,eAAe;AACxB;AAAA,QACF;AAAA,MACF;AACA,wBAAkB,QAAQ;AAAA,IAC5B;AACA,UAAM,aAAa,WAAW,OAAO,SAAS;AAC9C,QAAIA,QAAO,eAAe;AACxB;AAAA,IACF;AAAA,EACF;AACA,QAAM,aAAa,WAAW;AAC9B,QAAMA,QAAO,QAAQ,SAAS;AAC9B,SAAOA,QAAO;AAChB;AACA,eAAe,WAAWA,SAAQ,GAAG,GAAG,OAAO,CAAC,GAAG;AACjD,MAAIA,QAAO,YAAY;AACrB,UAAM,IAAI,MAAM,8DAA8D;AAAA,EAChF;AACA,EAAAA,QAAO,aAAa;AACpB,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACF,UAAM,YAAY,KAAK,aAAa,OAAO,KAAK,KAAK;AACrD,mBAAe,SAAS;AACxB,UAAM,iBAAiB;AACvB,UAAM,mBAAmB,MAAMA,QAAO,oBAAoB,GAAG,GAAG,KAAK,cAAc,KAAK,aAAa,gBAAgB,SAAS;AAC9H,aAAS,iBAAiB;AAC1B,cAAU,iBAAiB;AAC3B,oBAAgB,iBAAiB;AACjC,QAAI,eAAe;AACnB,QAAI;AACJ,QAAI,KAAK,kBAAkB,QAAQ,KAAK,eAAe,SAAS,GAAG;AACjE,qBAAe;AACf,UAAI,KAAK,eAAe,WAAW,GAAG;AACpC,oBAAY,KAAK,eAAe;AAChC,oBAAY,KAAK,eAAe;AAAA,MAClC,WAAW,KAAK,eAAe,WAAW,GAAG;AAC3C,cAAM,IAAI,oBAAoB,+DAA+D;AAAA,MAC/F,OAAO;AACL,cAAM,IAAI,WAAW,0GAA0G,KAAK,4BAA4B;AAAA,MAClK;AACA,YAAM,kBAAkB;AACxB,YAAM,kBAAkB,MAAMA,QAAO,oBAAoB,WAAW,WAAW,MAAM,MAAM,iBAAiB,SAAS;AACrH,aAAO,gBAAgB;AACvB,aAAO,gBAAgB;AACvB,eAAS,KAAK,OAAO,IAAI;AAAA,IAC3B,WAAW,KAAK,mBAAmB,QAAQ,KAAK,kBAAkB,KAAK,KAAK,kBAAkB,GAAG;AAC/F,qBAAe;AACf,YAAM,UAAU,KAAK,MAAM,OAAO,GAAG,MAAM,MAAM,IAAI,KAAK,gBAAgB;AAC1E,YAAM,oBAAoB,OAAO,GAAG,MAAM;AAC1C,aAAO,YAAY,QAAQ,SAAS,iBAAiB;AACrD,uBAAiB;AACjB,eAAS,YAAY,QAAQ,GAAG,OAAO;AACvC,aAAO,YAAY,SAAS,SAAS,iBAAiB;AACtD,wBAAkB;AAClB,gBAAU,YAAY,SAAS,GAAG,OAAO;AACzC,eAAS,KAAK,OAAO,IAAI;AAAA,IAC3B,WAAW,KAAK,mBAAmB,MAAM;AACvC,qBAAe;AAAA,IACjB;AACA,UAAM,MAAM,OAAO,OAAO,OAAO,EAAE,OAAO,aAAa;AACvD,IAAAA,QAAO,iCAAiC;AACxC,UAAM,gBAAgBA,QAAO,kBAAkB;AAC/C,UAAM,YAAYA,QAAO,uBAAuB;AAChD,QAAI;AACJ,QAAI;AACJ,QAAI,cAAc;AAChB,MAAAA,QAAO,iBAAiB;AACxB,oBAAcA,QAAO;AACrB,wBAAkB,UAAU,MAAM,EAAE,OAAO,UAAU,IAAI,CAAC,OAAO,SAAS,EAAE,CAAC;AAAA,IAC/E,OAAO;AACL,oBAAc;AACd,eAAS,CAAC;AACV,wBAAkB,UAAU,MAAM;AAAA,IACpC;AACA,UAAM,aAAa,qBAAqB,KAAK,WAAW,KAAK,UAAU;AACvE,UAAM,MAAM,MAAM,QAAQA,SAAQ,eAAe,KAAK,WAAW,WAAW,KAAK,QAAQ,KAAK,SAAS,YAAY,aAAa,QAAQ,KAAK,SAAS,iBAAiB,KAAK,cAAc,MAAM,IAAI;AACpM,WAAO;AAAA,EACT,UAAE;AACA,IAAAA,QAAO,aAAa;AACpB,sBAAkB,QAAQ,CAAC;AAC3B,sBAAkB,SAAS,CAAC;AAC5B,sBAAkB,gBAAgB,CAAC;AACnC,sBAAkB,iBAAiB,CAAC;AACpC,sBAAkB,MAAM,SAAS;AACjC,sBAAkB,MAAM,SAAS;AACjC,QAAI,iBAAiB,MAAM;AACzB,cAAQ,aAAa;AAAA,IACvB;AAAA,EACF;AACF;AACA,SAAS,2BAA2B,SAAS;AAC3C,QAAM,OAAO,CAAC;AACd,MAAI,mBAAmB,QAAQ;AAC7B,cAAU,CAAC,OAAO;AAAA,EACpB;AACA,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC1C,UAAM,UAAU,QAAQ;AACxB,QAAI,QAAQ,SAAS,GAAG;AACtB,WAAK,KAAK,YAAY,SAAS,CAAC,CAAC;AAAA,IACnC,WAAW,QAAQ,SAAS,GAAG;AAC7B,YAAM,IAAI,MAAM,uEAAuE;AAAA,IACzF,OAAO;AACL,WAAK,KAAK,OAAO;AAAA,IACnB;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,SAAS,YAAY;AAC9C,MAAI,WAAW,MAAM;AACnB;AAAA,EACF;AACA,QAAM,eAAe,CAAC;AACtB,MAAI,sBAAsB,QAAQ;AAChC,iBAAa,KAAK,WAAW,EAAE;AAAA,EACjC,WAAW,MAAM,QAAQ,UAAU,GAAG;AACpC,eAAW,QAAQ,CAAC,OAAO,aAAa,KAAK,GAAG,EAAE,CAAC;AAAA,EACrD,WAAW,cAAc,MAAM;AAC7B,eAAW,QAAQ,YAAY;AAC7B,YAAM,YAAY,WAAW;AAC7B,mBAAa,KAAK,UAAU,EAAE;AAAA,IAChC;AAAA,EACF;AACA,QAAM,mBAAmB,CAAC;AAC1B,MAAI,mBAAmB,QAAQ;AAC7B,QAAI,aAAa,QAAQ,QAAQ,EAAE,MAAM,IAAI;AAC3C,uBAAiB,KAAK,OAAO;AAAA,IAC/B;AAAA,EACF,WAAW,MAAM,QAAQ,OAAO,GAAG;AACjC,YAAQ,QAAQ,CAAC,OAAO;AACtB,UAAI,aAAa,QAAQ,GAAG,EAAE,MAAM,IAAI;AACtC,yBAAiB,KAAK,EAAE;AAAA,MAC1B;AAAA,IACF,CAAC;AAAA,EACH,WAAW,WAAW,MAAM;AAC1B,eAAW,QAAQ,SAAS;AAC1B,YAAM,UAAU,QAAQ;AACxB,UAAI,aAAa,QAAQ,QAAQ,EAAE,MAAM,IAAI;AAC3C,yBAAiB,KAAK,OAAO;AAAA,MAC/B;AAAA,IACF;AAAA,EACF;AACA,mBAAiB,QAAQ,CAAC,OAAO;AAC/B,QAAI,CAAC,GAAG,YAAY;AAClB,SAAG,QAAQ;AAAA,IACb;AAAA,EACF,CAAC;AACH;AAGA,SAAS,aAAa,GAAG;AACvB,SAAO,aAAa;AACtB;AACA,SAAS,YAAY,GAAG;AACtB,SAAO,MAAM,QAAQ,CAAC;AACxB;AACA,SAAS,WAAW,GAAG;AACrB,SAAO,CAAC,aAAa,CAAC,KAAK,CAAC,YAAY,CAAC;AAC3C;AACA,SAAS,qBAAqB,MAAM,OAAO,QAAQ,iBAAiB,MAAM,kBAAkB,IAAI;AAC9F,MAAI,SAAS,QAAQ,MAAM,WAAW,GAAG;AACvC,QAAI,QAAQ,MAAM;AAChB,UAAI,oBAAoB;AACxB,UAAI,YAAY,IAAI,KAAK,KAAK,SAAS,GAAG;AACxC,4BAAoB;AAAA,MACtB,WAAW,WAAW,IAAI,GAAG;AAC3B,mBAAW,OAAO,MAAM;AACtB,cAAI,KAAK,eAAe,GAAG,GAAG;AAC5B,gCAAoB;AACpB;AAAA,UACF;AAAA,QACF;AAAA,MACF,OAAO;AACL,4BAAoB;AAAA,MACtB;AACA,UAAI,mBAAmB;AACrB,cAAM,IAAI,WAAW,6BAA6B,6CAA6C,MAAM;AAAA,MACvG;AAAA,IACF;AACA,WAAO,CAAC;AAAA,EACV;AACA,MAAI,QAAQ,MAAM;AAChB,WAAO,MAAM,IAAI,CAAC,SAAS,IAAI;AAAA,EACjC;AACA,MAAI;AACJ,MAAI,WAAW,IAAI,GAAG;AACpB,WAAO;AACP,aAAS,CAAC;AACV,eAAW,QAAQ,OAAO;AACxB,UAAI,KAAK,SAAS,MAAM;AACtB,cAAM,IAAI,WAAW,yBAAyB,qCAAqC,OAAO;AAAA,MAC5F;AACA,aAAO,KAAK,KAAK,KAAK;AAAA,IACxB;AAAA,EACF,WAAW,YAAY,IAAI,GAAG;AAC5B,WAAO;AACP,QAAI,KAAK,WAAW,MAAM,QAAQ;AAChC,YAAM,IAAI,WAAW,6BAA6B,gIAAgI,MAAM,sEAAsE,MAAM;AAAA,IACtQ;AACA,aAAS;AAAA,EACX,OAAO;AACL,WAAO;AACP,QAAI,MAAM,SAAS,GAAG;AACpB,YAAM,IAAI,WAAW,aAAa,2BAA2B,MAAM,4EAA4E,KAAK,OAAO;AAAA,IAC7J;AACA,aAAS,CAAC,IAAI;AAAA,EAChB;AACA,WAAS,2BAA2B,MAAM;AAC1C,MAAI,UAAU,MAAM;AAClB,aAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,UAAI,OAAO,OAAO,MAAM;AACtB;AAAA,MACF;AACA,YAAM,SAAS,OAAO;AACtB,UAAI,OAAO,MAAM,WAAW,OAAO,IAAI,QAAQ;AAC7C,cAAM,IAAI,WAAW,uBAAuB,6BAA6B,MAAM,eAAe,OAAO,IAAI,iDAAiD,OAAO,OAAO;AAAA,MAC1K;AACA,eAAS,IAAI,GAAG,IAAI,OAAO,IAAI,QAAQ,EAAE,GAAG;AAC1C,YAAI,MAAM,KAAK,CAAC,gBAAgB;AAC9B;AAAA,QACF;AACA,cAAM,MAAM,OAAO,MAAM;AACzB,cAAM,SAAS,OAAO,IAAI;AAC1B,YAAI,UAAU,QAAQ,UAAU,KAAK,QAAQ,QAAQ;AACnD,gBAAM,IAAI,WAAW,GAAG,8EAA8E,OAAO,IAAI,MAAM,GAAG,OAAO,IAAI,MAAM,4BAA4B,OAAO,IAAI,MAAM,GAAG,OAAO,IAAI,MAAM,eAAe,0CAA0C,OAAO,MAAM,iCAAiC,OAAO,MAAM,MAAM,GAAG,OAAO,MAAM,MAAM,qBAAqB,OAAO,SAAS;AAAA,QACnY;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,QAAQ,SAAS,SAAS;AACnD,QAAM,OAAO,QAAQ,OAAO,IAAI,CAAC,WAAW,OAAO,MAAM,EAAE,CAAC;AAC5D,OAAK,KAAK;AACV,QAAM,OAAO,QAAQ,QAAQ,IAAI,CAAC,WAAW,OAAO,MAAM,EAAE,CAAC;AAC7D,OAAK,KAAK;AACV,MAAI,KAAK,SAAS,GAAG;AACnB,UAAM,IAAI,WAAW,mFAAmF,KAAK,UAAU,OAAO,IAAI,CAAC,WAAW,OAAO,KAAK,CAAC,GAAG;AAAA,EAChK;AACA,MAAI,KAAK,SAAS,GAAG;AACnB,UAAM,IAAI,WAAW,oFAAoF,KAAK,UAAU,QAAQ,IAAI,CAAC,WAAW,OAAO,KAAK,CAAC,GAAG;AAAA,EAClK;AACA,MAAI,KAAK,SAAS,KAAK,KAAK,SAAS,KAAK,CAAC,aAAa,YAAY,MAAM,IAAI,GAAG;AAC/E,UAAM,IAAI,WAAW,iFAAiF,KAAK,0BAA0B,KAAK,sBAAsB;AAAA,EAClK;AACF;AACA,SAAS,gCAAgC,SAAS,SAAS,cAAc;AACvE,QAAM,YAAY;AAAA,IAChB;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACA,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC1C,UAAM,IAAI,QAAQ;AAClB,UAAM,OAAO,QAAQ;AACrB,UAAM,QAAQ,aAAa;AAC3B,QAAI,QAAQ,MAAM;AAChB;AAAA,IACF;AACA,QAAI,SAAS,yBAAyB;AACpC,UAAI,EAAE,MAAM,EAAE,MAAM,SAAS,OAAO,GAAG;AACrC,cAAM,IAAI,WAAW,2CAA2C,EAAE,+JAA+J;AAAA,MACnO;AAAA,IACF;AACA,QAAI,UAAU,QAAQ,IAAI,MAAM,IAAI;AAClC,YAAM,eAAe,EAAE,MAAM,MAAM,CAAC;AACpC,YAAM,cAAc,MAAM,MAAM,CAAC;AACjC,eAAS,IAAI,GAAG,IAAI,aAAa,QAAQ,EAAE,GAAG;AAC5C,cAAM,YAAY,aAAa;AAC/B,cAAM,SAAS,YAAY;AAC3B,YAAI,UAAU,QAAQ,cAAc,QAAQ;AAC1C,gBAAM,IAAI,WAAW,8BAA8B,EAAE,2CAA2C,+FAA+F;AAAA,QACjM;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,eAAe,MAAM,OAAO,QAAQ,iBAAiB,MAAM,kBAAkB,IAAI;AACxF,MAAI;AACJ,MAAI,MAAM,QAAQ,IAAI,GAAG;AACvB,QAAI,KAAK,WAAW,MAAM,QAAQ;AAChC,YAAM,IAAI,WAAW,6BAA6B,oIAAoI,MAAM,qCAAqC,KAAK,oBAAoB;AAAA,IAC5P;AACA,aAAS;AAAA,EACX,OAAO;AACL,QAAI,MAAM,SAAS,GAAG;AACpB,YAAM,IAAI,WAAW,qBAAqB,MAAM,UAAU,kFAAkF,KAAK,UAAU,KAAK,KAAK,IAAI;AAAA,IAC3K;AACA,aAAS,CAAC,IAAI;AAAA,EAChB;AACA,MAAI,UAAU,MAAM;AAClB,aAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,UAAI,OAAO,OAAO,MAAM;AACtB;AAAA,MACF;AACA,YAAM,SAAS,OAAO;AACtB,UAAI,OAAO,MAAM,WAAW,OAAO,IAAI,QAAQ;AAC7C,cAAM,IAAI,WAAW,uBAAuB,6BAA6B,MAAM,eAAe,OAAO,IAAI,iDAAiD,KAAK,UAAU,OAAO,KAAK,GAAG;AAAA,MAC1L;AACA,eAAS,IAAI,GAAG,IAAI,OAAO,IAAI,QAAQ,EAAE,GAAG;AAC1C,YAAI,MAAM,KAAK,CAAC,gBAAgB;AAC9B;AAAA,QACF;AACA,cAAM,MAAM,OAAO,MAAM;AACzB,cAAM,SAAS,OAAO,IAAI;AAC1B,YAAI,UAAU,MAAM;AAClB,cAAI,WAAW,KAAK;AAClB,kBAAM,IAAI,WAAW,uBAAuB,6BAA6B,MAAM,qBAAqB,KAAK,UAAU,OAAO,GAAG,8BAA8B,KAAK,UAAU,OAAO,KAAK,IAAI;AAAA,UAC5L;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,eAAe,SAAS,aAAa;AAC5C,MAAI,WAAW,QAAQ,MAAM,QAAQ,OAAO,KAAK,QAAQ,WAAW,GAAG;AACrE,WAAO,YAAY,IAAI,CAAC,SAAS,CAAC,CAAC;AAAA,EACrC;AACA,MAAI;AACJ,MAAI,OAAO,YAAY,YAAY,OAAO,YAAY,YAAY;AAChE,qBAAiB,CAAC,OAAO;AAAA,EAC3B,WAAW,MAAM,QAAQ,OAAO,KAAK,OAAO,YAAY,UAAU;AAChE,qBAAiB;AAAA,EACnB,OAAO;AACL,UAAM,IAAI,UAAU,kGAAkG,SAAS;AAAA,EACjI;AACA,MAAI,MAAM,QAAQ,cAAc,GAAG;AACjC,WAAO,YAAY,IAAI,CAAC,SAAS,cAAc;AAAA,EACjD,OAAO;AACL,UAAM,gBAAgB,CAAC;AACvB,eAAW,QAAQ,aAAa;AAC9B,UAAI,gBAAgB,eAAe,eAAe,IAAI,IAAI,eAAe,QAAQ,CAAC;AAClF,UAAI,CAAC,MAAM,QAAQ,aAAa,GAAG;AACjC,wBAAgB,CAAC,aAAa;AAAA,MAChC;AACA,oBAAc,KAAK,aAAa;AAAA,IAClC;AACA,WAAO;AAAA,EACT;AACF;AACA,IAAI,2BAA2B;AAC/B,IAAI,cAAc,cAAc,UAAU;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,aAAa;AAAA,EACpB;AAAA,EACA,QAAQ,YAAY,WAAW,UAAU,QAAQ,KAAK;AACpD,QAAI,CAAC,KAAK,OAAO;AACf,YAAM,IAAI,WAAW,8KAA8K;AAAA,IACrM;AACA,iBAAa,MAAM,YAAY,WAAW,OAAO;AAAA,EACnD;AAAA,EACA,QAAQ,MAAM;AACZ,QAAI,KAAK,QAAQ,MAAM;AACrB,WAAK,OAAO,CAAC;AAAA,IACf;AACA,SAAK,OAAO,KAAK;AACjB,QAAI,OAAO,KAAK,cAAc,UAAU;AACtC,WAAK,aAAa,aAAa,KAAK,SAAS;AAC7C,WAAK,mBAAmB;AAAA,IAC1B,OAAO;AACL,UAAI,EAAE,KAAK,qBAAqB,YAAY;AAC1C,cAAM,IAAI,WAAW,6DAA6D;AAAA,MACpF;AACA,WAAK,aAAa,KAAK;AACvB,WAAK,mBAAmB;AAAA,IAC1B;AACA,QAAI,gBAAgB,CAAC;AACrB,QAAI,CAAC,MAAM,QAAQ,KAAK,IAAI,KAAK,OAAO,KAAK,SAAS,YAAY,OAAO,KAAK,SAAS,YAAY;AACjG,WAAK,OAAO,KAAK;AACjB,iBAAW,QAAQ,KAAK,MAAM;AAC5B,YAAI,KAAK,YAAY,QAAQ,IAAI,MAAM,IAAI;AACzC,gBAAM,IAAI,WAAW,sCAAsC,4CAA4C,KAAK,aAAa;AAAA,QAC3H;AAAA,MACF;AACA,iBAAW,QAAQ,KAAK,aAAa;AACnC,YAAI,KAAK,KAAK,SAAS,MAAM;AAC3B,kBAAQ,KAAK,WAAW,gIAAgI,sBAAsB;AAAA,QAChL;AACA,sBAAc,KAAK,IAAI,KAAK,KAAK,KAAK,CAAC;AAAA,MACzC;AAAA,IACF,WAAW,MAAM,QAAQ,KAAK,IAAI,GAAG;AACnC,UAAI,KAAK,KAAK,WAAW,KAAK,QAAQ,QAAQ;AAC5C,cAAM,IAAI,WAAW,2FAA2F,KAAK,QAAQ,yCAAyC,KAAK,OAAO;AAAA,MACpL;AACA,YAAM,YAAY,KAAK;AACvB,sBAAgB,UAAU,IAAI,CAAC,OAAO,IAAI,EAAE,CAAC;AAAA,IAC/C,OAAO;AACL,YAAM,eAAe,IAAI,KAAK,IAAI;AAClC,WAAK,QAAQ,QAAQ,CAAC,MAAM;AAC1B,sBAAc,KAAK,YAAY;AAAA,MACjC,CAAC;AAAA,IACH;AACA,SAAK,gBAAgB;AACrB,SAAK,kBAAkB,CAAC;AACxB,SAAK,mBAAmB,CAAC;AACzB,SAAK,cAAc,CAAC;AACpB,aAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC/C,YAAM,QAAQ,KAAK,qBAAqB;AACxC,YAAM,OAAO,KAAK,YAAY;AAC9B,WAAK,gBAAgB,KAAK,IAAI;AAC9B,WAAK,iBAAiB,KAAK,KAAK;AAChC,WAAK,YAAY,KAAK,KAAK,cAAc,GAAG;AAAA,IAC9C;AACA,UAAM,oBAAoB,CAAC;AAC3B,SAAK,UAAU,KAAK;AACpB,SAAK,eAAe,CAAC,MAAM;AAC3B,SAAK,iBAAiB,CAAC;AACvB,cAAU,QAAQ,MAAM;AACtB,eAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC/C,YAAI,kBAAkB,QAAQ,EAAE,MAAM,IAAI;AACxC;AAAA,QACF;AACA,cAAM,eAAe,KAAK,cAAc;AACxC,YAAI,KAAK,QAAQ,SAAS,GAAG;AAC3B,eAAK,eAAe,KAAK,CAAC,cAAc,EAAE,CAAC;AAC3C,eAAK,aAAa,KAAK,KAAK,YAAY,MAAM,OAAO;AAAA,QACvD;AAAA,MACF;AAAA,IACF,CAAC;AACD,UAAM,gBAAgB,eAAe,KAAK,SAAS,KAAK,WAAW;AACnE,UAAM,eAAe,CAAC,aAAa,YAAY,iBAAiB;AAC9D,UAAI,KAAK,YAAY,SAAS,GAAG;AAC/B,qBAAa,KAAK,YAAY,eAAe,MAAM;AAAA,MACrD;AACA,WAAK,aAAa,KAAK,UAAU;AACjC,WAAK,eAAe,KAAK,CAAC,cAAc,WAAW,CAAC;AAAA,IACtD;AACA,cAAU,UAAU,MAAM;AACxB,eAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC/C,YAAI,kBAAkB,QAAQ,EAAE,MAAM,IAAI;AACxC;AAAA,QACF;AACA,cAAM,gBAAgB,cAAc;AACpC,cAAM,gBAAgB,CAAC,YAAY;AACjC,gBAAM,mBAAmB;AACzB,cAAI;AACJ,cAAI;AACJ,cAAI;AACJ,qBAAW,UAAU,SAAS;AAC5B,gBAAI,OAAO,WAAW,YAAY,CAAC,YAAY,OAAO,gBAAgB,IAAI,EAAE,QAAQ,MAAM,MAAM,IAAI;AAClG,oBAAM,cAAc,KAAK,qBAAqB;AAC9C,kBAAI,YAAY,YAAY,SAAS,OAAO,KAAK,KAAK,cAAc,QAAQ,oBAAoB;AAC9F,oBAAI,CAAC,YAAY,KAAK,EAAE,QAAQ,MAAM,MAAM,IAAI;AAC9C,0BAAQ;AAAA,gBACV,WAAW,CAAC,gBAAgB,IAAI,EAAE,QAAQ,MAAM,MAAM,IAAI;AACxD,0BAAQ;AAAA,gBACV;AAAA,cACF,WAAW,KAAK,cAAc,QAAQ,+BAA+B;AACnE,oBAAI,CAAC,YAAY,KAAK,EAAE,QAAQ,MAAM,MAAM,IAAI;AAC9C,0BAAQ;AAAA,gBACV,WAAW,CAAC,gBAAgB,IAAI,EAAE,QAAQ,MAAM,MAAM,IAAI;AACxD,0BAAQ;AAAA,gBACV;AAAA,cACF,OAAO;AACL,oBAAI,CAAC,YAAY,KAAK,EAAE,QAAQ,MAAM,MAAM,IAAI;AAC9C,0BAAQ;AAAA,gBACV,WAAW,CAAC,gBAAgB,IAAI,EAAE,QAAQ,MAAM,MAAM,IAAI;AACxD,0BAAQ;AAAA,gBACV;AAAA,cACF;AACA,kBAAI;AACJ,kBAAI,CAAC,YAAY,KAAK,EAAE,QAAQ,MAAM,MAAM,IAAI;AAC9C,yBAAS;AAAA,cACX,WAAW,CAAC,gBAAgB,IAAI,EAAE,QAAQ,MAAM,MAAM,IAAI;AACxD,yBAAS;AAAA,cACX;AACA,iCAAmB;AACnB,2BAAa,mBAAmB;AAAA,YAClC,OAAO;AACL,oBAAM,WAAW,KAAK,MAAM;AAC5B,iCAAmB;AACnB,2BAAa,mBAAmB,oBAAoB,MAAM;AAAA,YAC5D;AACA,gBAAI;AACJ,sBAAU,YAAY,MAAM;AAC1B,6BAAe;AAAA,YACjB,CAAC;AACD,yBAAa,IAAI,YAAY,YAAY;AAAA,UAC3C;AAAA,QACF;AACA,sBAAc,aAAa;AAAA,MAC7B;AAAA,IACF,CAAC;AACD,SAAK,4BAA4B,KAAK;AAAA,EACxC;AAAA,EACA,mCAAmC;AACjC,QAAI,KAAK,6BAA6B,MAAM;AAC1C;AAAA,IACF;AACA,QAAI,KAAK,iBAAiB,WAAW,KAAK,0BAA0B,QAAQ;AAC1E,cAAQ,KAAK,mJAAmJ;AAAA,IAClK;AAAA,EACF;AAAA,EACA,SAAS,GAAG,GAAG,OAAO,CAAC,GAAG;AACxB,UAAM,YAAY,KAAK,aAAa,OAAO,KAAK,KAAK;AACrD,mBAAe,SAAS;AACxB,UAAM,iBAAiB;AACvB,UAAM,mBAAmB,KAAK,sBAAsB,GAAG,GAAG,gBAAgB,SAAS;AACnF,QAAI;AACF,YAAM,MAAM,iBAAiB,GAAG,OAAO,iBAAiB,EAAE;AAC1D,WAAK,iBAAiB;AACtB,YAAM,IAAI,KAAK;AACf,YAAM,WAAW,KAAK,SAAS,GAAG,KAAK,WAAW,KAAK,SAAS,KAAK,KAAK;AAC1E,aAAO,iBAAiB,QAAQ;AAAA,IAClC,UAAE;AACA,wBAAkB,iBAAiB,IAAI,CAAC;AACxC,wBAAkB,iBAAiB,IAAI,CAAC;AAAA,IAC1C;AAAA,EACF;AAAA,EACA,MAAM,gBAAgB,SAAS,MAAM;AACnC,SAAK,iBAAiB;AACtB,WAAO,gBAAgB,MAAM,SAAS,IAAI;AAAA,EAC5C;AAAA,EACA,gBAAgB,KAAK,WAAW,OAAO,YAAY,SAAS;AAC1D,QAAI;AACJ,QAAI,SAAS,MAAM;AACjB,mBAAa;AACb,UAAI,aAAa,MAAM;AACrB,cAAM,IAAI,WAAW,MAAM,yEAAyE,WAAW;AAAA,MACjH;AAAA,IACF,WAAW,OAAO,MAAM;AACtB,UAAI,MAAM,QAAQ,GAAG,GAAG;AACtB,qBAAa,IAAI,GAAG,MAAM;AAAA,MAC5B,OAAO;AACL,qBAAa,IAAI,MAAM;AAAA,MACzB;AAAA,IACF,OAAO;AACL,YAAM,IAAI,WAAW,yDAAyD,+BAA+B;AAAA,IAC/G;AACA,WAAO;AAAA,EACT;AAAA,EACA,QAAQ,QAAQ,SAAS;AACvB,QAAI,MAAM,QAAQ,OAAO,KAAK,QAAQ,WAAW,GAAG;AAClD,YAAM,IAAI,WAAW,oDAAoD;AAAA,IAC3E;AACA,UAAM,iBAAiB,MAAM,QAAQ,OAAO;AAC5C,UAAM,cAAc,iBAAiB,UAAU,CAAC,OAAO;AACvD,UAAM,wBAAwB,KAAK,wBAAwB,WAAW;AACtE,UAAM,WAAW,IAAI,SAAS;AAC9B,QAAI,kBAAkB,QAAQ;AAC5B,eAAS,CAAC,MAAM;AAAA,IAClB;AACA,QAAI,MAAM,QAAQ,MAAM,GAAG;AACzB,UAAI,OAAO,WAAW,KAAK,OAAO,QAAQ;AACxC,cAAM,IAAI,WAAW,kCAAkC,OAAO,8DAA8D,KAAK,OAAO,UAAU;AAAA,MACpJ;AACA,eAAS,KAAK,GAAG,KAAK,KAAK,OAAO,QAAQ,EAAE,IAAI;AAC9C,iBAAS,IAAI,KAAK,OAAO,KAAK,OAAO,GAAG;AAAA,MAC1C;AAAA,IACF,OAAO;AACL,iBAAW,UAAU,KAAK,QAAQ;AAChC,cAAM,cAAc,OAAO,OAAO;AAClC,YAAI,eAAe,MAAM;AACvB,gBAAM,IAAI,WAAW,8CAA8C,OAAO,MAAM;AAAA,QAClF;AACA,iBAAS,IAAI,QAAQ,WAAW;AAAA,MAClC;AAAA,IACF;AACA,UAAM,iBAAiB,QAAQ,uBAAuB,QAAQ;AAC9D,WAAO,iBAAiB,iBAAiB,eAAe;AAAA,EAC1D;AAAA,EACA,wBAAwB,qBAAqB;AAC3C,UAAM,wBAAwB,aAAa,MAAM,oBAAoB,MAAM;AAC3E,QAAI,mBAAmB,oBAAoB;AAC3C,eAAW,SAAS,KAAK,QAAQ;AAC/B,YAAM,eAAe,MAAM,QAAQ,MAAM,MAAM,IAAI,MAAM,SAAS,CAAC,MAAM,MAAM;AAC/E,YAAM,mBAAmB,aAAa,IAAI,CAAC,WAAW,OAAO,IAAI;AACjE,eAAS,KAAK,GAAG,KAAK,oBAAoB,QAAQ,EAAE,IAAI;AACtD,cAAMpB,SAAQ,iBAAiB,QAAQ,oBAAoB,GAAG;AAC9D,YAAIA,WAAU,IAAI;AAChB,gCAAsB,MAAM,aAAaA;AACzC;AAAA,QACF;AACA,YAAI,qBAAqB,GAAG;AAC1B;AAAA,QACF;AAAA,MACF;AACA,UAAI,qBAAqB,GAAG;AAC1B;AAAA,MACF;AAAA,IACF;AACA,QAAI,mBAAmB,GAAG;AACxB,YAAM,iBAAiB,CAAC;AACxB,4BAAsB,QAAQ,CAAC,SAAS,OAAO;AAC7C,YAAI,WAAW,MAAM;AACnB,yBAAe,KAAK,oBAAoB,GAAG;AAAA,QAC7C;AAAA,MACF,CAAC;AACD,YAAM,IAAI,WAAW,mDAAmD,KAAK,UAAU,cAAc,GAAG;AAAA,IAC1G;AACA,WAAO;AAAA,EACT;AAAA,EACA,YAAY,KAAK,YAAY,IAAI,UAAU,OAAO;AAChD,WAAO,KAAK,MAAM;AAChB,YAAM,aAAa,KAAK,gBAAgB,GAAG;AAC3C,UAAI,SAAS;AACX,cAAM,IAAI,oBAAoB,+CAA+C;AAAA,MAC/E;AACA,YAAM,UAAU,YAAY,YAAY,SAAS;AACjD,YAAM,cAAc,KAAK,QAAQ,IAAI,CAAC,WAAW,CAAC,CAAC;AACnD,eAAS,aAAa,GAAG,aAAa,QAAQ,QAAQ,EAAE,YAAY;AAClE,cAAM,YAAY,KAAK,MAAM;AAC3B,gBAAM,aAAa,QAAQ,YAAY;AACvC,gBAAM,WAAW,QAAQ,YAAY;AACrC,gBAAM,WAAW,YAAY,KAAK,YAAY,QAAQ;AACtD,gBAAM,QAAQ,CAAC;AACf,cAAI,MAAM,QAAQ,QAAQ,GAAG;AAC3B,qBAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,EAAE,IAAI;AAC3C,oBAAM,KAAK,EAAE,KAAK,KAAK,OAAO,KAAK,OAAO,SAAS,IAAI,CAAC;AAAA,YAC1D;AAAA,UACF,OAAO;AACL,kBAAM,KAAK,EAAE,KAAK,KAAK,OAAO,IAAI,OAAO,SAAS,CAAC;AAAA,UACrD;AACA,gBAAM,WAAW,IAAI,SAAS,KAAK;AACnC,iBAAO,QAAQ,KAAK,SAAS,QAAQ;AAAA,QACvC,CAAC;AACD,kBAAU,QAAQ,CAAC,UAAU,OAAO,YAAY,IAAI,KAAK,QAAQ,CAAC;AAAA,MACpE;AACA,aAAO,iBAAiB,YAAY,IAAI,CAAC,aAAa,OAAO,UAAU,CAAC,CAAC,CAAC;AAAA,IAC5E,CAAC;AAAA,EACH;AAAA,EACA,QAAQ,GAAG,OAAO,CAAC,GAAG;AACpB,UAAM,kBAAkB,2BAA2B,CAAC;AACpD,mBAAe,iBAAiB,KAAK,YAAY,KAAK,iBAAiB,KAAK;AAC5E,QAAI;AACF,YAAM,YAAY,KAAK,aAAa,OAAO,KAAK,KAAK;AACrD,qBAAe,SAAS;AACxB,aAAO,KAAK,YAAY,iBAAiB,SAAS;AAAA,IACpD,UAAE;AACA,wBAAkB,iBAAiB,CAAC;AAAA,IACtC;AAAA,EACF;AAAA,EACA,eAAe,GAAG;AAChB,mBAAe,GAAG,KAAK,YAAY,KAAK,iBAAiB,IAAI;AAC7D,UAAM,aAAa,MAAM,QAAQ,CAAC,IAAI,EAAE,KAAK,GAAG,MAAM;AACtD,WAAO,KAAK,YAAY,GAAG,SAAS;AAAA,EACtC;AAAA,EACA,sBAAsB,GAAG,GAAG,iBAAiB,MAAM,WAAW;AAC5D,QAAI,KAAK,cAAc,MAAM;AAC3B,YAAM,IAAI,aAAa,8FAA8F;AAAA,IACvH;AACA,UAAM,eAAe,CAAC;AACtB,aAAS,KAAK,GAAG,KAAK,KAAK,iBAAiB,QAAQ,EAAE,IAAI;AACxD,YAAM,cAAc,KAAK,iBAAiB;AAC1C,YAAM,SAAS,KAAK,YAAY;AAChC,UAAI,WAAW,+BAA+B;AAC5C,qBAAa,KAAK,YAAY,MAAM,GAAG,YAAY,SAAS,CAAC,EAAE,OAAO,CAAC,CAAC,CAAC,CAAC;AAAA,MAC5E,OAAO;AACL,qBAAa,KAAK,WAAW;AAAA,MAC/B;AAAA,IACF;AACA,QAAI,qBAAqB,GAAG,KAAK,gBAAgB,KAAK,iBAAiB,OAAO,OAAO;AACrF,QAAI,qBAAqB,GAAG,KAAK,iBAAiB,cAAc,OAAO,QAAQ;AAC/E,sBAAkB,GAAG,GAAG,IAAI;AAC5B,oCAAgC,GAAG,KAAK,aAAa,KAAK,gBAAgB;AAC1E,QAAI,KAAK,YAAY,aAAa,QAAQ,YAAY,GAAG;AACvD,UAAI,EAAE,GAAG,MAAM,KAAK,cAAc,GAAG;AACnC,cAAM,IAAI,WAAW,mHAAmH,qBAAqB,EAAE,GAAG,MAAM,eAAe;AAAA,MACzL;AAAA,IACF;AACA,WAAO,CAAC,GAAG,CAAC;AAAA,EACd;AAAA,EACA,MAAM,oBAAoB,GAAG,GAAG,cAAc,aAAa,iBAAiB,MAAM,WAAW;AAC3F,UAAM,CAAC,YAAY,UAAU,IAAI,KAAK,sBAAsB,GAAG,GAAG,gBAAgB,SAAS;AAC3F,QAAI,gBAAgB,MAAM;AACxB,YAAM,IAAI,MAAM,qCAAqC;AAAA,IACvD;AACA,QAAI,wBAAwB;AAC5B,QAAI,eAAe,MAAM;AACvB,YAAM,eAAe,wBAAwB,aAAa,KAAK,WAAW;AAC1E,8BAAwB,CAAC;AACzB,eAAS,KAAK,GAAG,KAAK,aAAa,QAAQ,EAAE,IAAI;AAC/C,8BAAsB,KAAK,MAAM,mBAAmB,WAAW,KAAK,MAAM,aAAa,GAAG,CAAC;AAAA,MAC7F;AAAA,IACF;AACA,WAAO,CAAC,YAAY,YAAY,qBAAqB;AAAA,EACvD;AAAA,EACA,SAAS,GAAG,KAAK,WAAW,UAAU,GAAG,OAAO;AAC9C,WAAO,KAAK,MAAM;AAChB,YAAM,aAAa,KAAK,gBAAgB,KAAK,WAAW,OAAO,OAAO;AACtE,YAAM,OAAO,CAAC;AACd,UAAI,UAAU,GAAG;AACf,cAAM,IAAI,oBAAoB,sCAAsC;AAAA,MACtE;AACA,UAAI,SAAS,MAAM;AACjB,cAAM,IAAI,oBAAoB,iDAAiD;AAAA,MACjF,OAAO;AACL,cAAM,UAAU,YAAY,YAAY,SAAS;AACjD,cAAM,aAAa,SAAS,OAAO,GAAG,UAAU,CAAC;AACjD,iBAAS,aAAa,GAAG,aAAa,QAAQ,QAAQ,EAAE,YAAY;AAClE,gBAAM,aAAa,QAAQ,YAAY;AACvC,gBAAM,WAAW,QAAQ,YAAY;AACrC,gBAAM,WAAW,oBAAoB,YAAY,YAAY,WAAW,UAAU;AAClF,gBAAM,WAAW,qBAAqB,KAAK,QAAQ;AACnD,gBAAM,YAAY,EAAE,QAAQ;AAC5B,cAAI,eAAe,GAAG;AACpB,qBAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,mBAAK,KAAK,OAAO,CAAC,CAAC;AAAA,YACrB;AAAA,UACF;AACA,mBAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,kBAAM,WAAW,UAAU;AAC3B,iBAAK,MAAM,KAAK,KAAK,KAAK,IAAI,WAAW,YAAY,QAAQ,CAAC;AAAA,UAChE;AAAA,QACF;AACA,iBAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,eAAK,MAAM,IAAI,KAAK,KAAK,UAAU;AAAA,QACrC;AAAA,MACF;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,yBAAyB;AACvB,UAAM,YAAY,KAAK;AACvB,UAAM,mBAAmB,CAAC;AAC1B,aAAS,KAAK,GAAG,KAAK,UAAU,QAAQ,EAAE,IAAI;AAC5C,YAAM,QAAQ,UAAU;AACxB,UAAI,WAAW;AACf,UAAI,MAAM,WAAW,KAAK,IAAI,GAAG;AAC/B,cAAM,WAAW,MAAM,UAAU,MAAM,GAAG,EAAE,GAAG,KAAK;AACpD,oBAAY,IAAI;AAAA,MAClB;AACA,uBAAiB,KAAK,QAAQ;AAAA,IAChC;AACA,WAAO;AAAA,EACT;AAAA,EACA,oBAAoB;AAClB,WAAO,CAAC,SAAS;AACf,YAAM,aAAa,CAAC;AACpB,YAAM,SAAS,KAAK,MAAM,GAAG,KAAK,OAAO,MAAM;AAC/C,YAAM,UAAU,KAAK,MAAM,KAAK,OAAO,QAAQ,KAAK,OAAO,SAAS,KAAK,QAAQ,MAAM;AACvF,YAAM,gBAAgB,KAAK,MAAM,KAAK,OAAO,SAAS,KAAK,QAAQ,QAAQ,KAAK,OAAO,SAAS,KAAK,QAAQ,SAAS,CAAC;AACvH,YAAM,gBAAgB,CAAC;AACvB,YAAM,oBAAoB,MAAM;AAC9B,cAAM,QAAQ,CAAC;AACf,iBAAS,KAAK,GAAG,KAAK,KAAK,OAAO,QAAQ,EAAE,IAAI;AAC9C,gBAAM,KAAK,EAAE,KAAK,KAAK,OAAO,KAAK,OAAO,OAAO,IAAI,CAAC;AAAA,QACxD;AACA,cAAM,WAAW,IAAI,SAAS,KAAK;AACnC,cAAM,UAAU,QAAQ,KAAK,SAAS,UAAU,EAAE,YAAY,KAAK,CAAC;AACpE,YAAI;AACJ,iBAAS,KAAK,GAAG,KAAK,KAAK,cAAc,QAAQ,EAAE,IAAI;AACrD,gBAAM,eAAe,KAAK,cAAc;AACxC,cAAI,OAAO,aAAa,QAAQ,KAAK,QAAQ,GAAG;AAChD,cAAI,cAAc,OAAO,MAAM;AAC7B,mBAAO,qBAAqB,MAAM,cAAc,GAAG;AAAA,UACrD;AACA,gBAAM,WAAW,KAAK,IAAI;AAC1B,qBAAW,KAAK,QAAQ;AACxB,cAAI,OAAO,GAAG;AACZ,wBAAY;AAAA,UACd,OAAO;AACL,wBAAY,KAAK,WAAW,IAAI;AAAA,UAClC;AAAA,QACF;AACA,iBAAS,KAAK,GAAG,KAAK,KAAK,eAAe,QAAQ,EAAE,IAAI;AACtD,cAAI;AACJ,cAAI,KAAK,QAAQ,SAAS,KAAK,KAAK,KAAK,QAAQ,QAAQ;AACvD,6BAAiB,WAAW;AAAA,UAC9B,OAAO;AACL,kBAAM,SAAS,KAAK,eAAe,IAAI;AACvC,kBAAM,cAAc,KAAK,eAAe,IAAI;AAC5C,6BAAiB,KAAK,OAAO,QAAQ,cAAc,QAAQ,YAAY,CAAC;AAAA,UAC1E;AACA,eAAK,cAAc;AACnB,wBAAc,KAAK,cAAc;AAAA,QACnC;AACA,oBAAY,KAAK,SAAS;AAC1B,aAAK,gBAAgB,EAAE,QAAQ,CAAC,oBAAoB;AAClD,sBAAY,KAAK,WAAW,eAAe;AAAA,QAC7C,CAAC;AACD,eAAO;AAAA,MACT;AACA,YAAM,YAAY,KAAK,0BAA0B,IAAI,CAAC,UAAU,MAAM,KAAK,CAAC;AAC5E,YAAM,aAAa;AACnB,YAAM,iBAAiB,KAAK,WAAW,SAAS,mBAAmB,YAAY,SAAS;AACxF,aAAO,CAAC,cAAc,EAAE,OAAO,aAAa;AAAA,IAC9C;AAAA,EACF;AAAA,EACA,mBAAmB;AACjB,SAAK,eAAe,CAAC,SAAS;AAC5B,aAAO,KAAK,MAAM;AAChB,cAAM,aAAa,CAAC;AACpB,YAAI;AACJ,cAAM,SAAS,KAAK,MAAM,GAAG,KAAK,OAAO,MAAM;AAC/C,cAAM,UAAU,KAAK,MAAM,KAAK,OAAO,QAAQ,KAAK,OAAO,SAAS,KAAK,QAAQ,MAAM;AACvF,cAAM,QAAQ,CAAC;AACf,iBAAS,KAAK,GAAG,KAAK,KAAK,OAAO,QAAQ,EAAE,IAAI;AAC9C,gBAAM,KAAK,EAAE,KAAK,KAAK,OAAO,KAAK,OAAO,OAAO,IAAI,CAAC;AAAA,QACxD;AACA,cAAM,WAAW,IAAI,SAAS,KAAK;AACnC,cAAM,UAAU,QAAQ,KAAK,SAAS,QAAQ;AAC9C,iBAAS,KAAK,GAAG,KAAK,KAAK,cAAc,QAAQ,EAAE,IAAI;AACrD,gBAAM,eAAe,KAAK,cAAc;AACxC,gBAAM,OAAO,KAAK,aAAa,QAAQ,KAAK,QAAQ,GAAG,CAAC;AACxD,cAAI,OAAO,GAAG;AACZ,wBAAY;AAAA,UACd,OAAO;AACL,wBAAY,KAAK,WAAW,IAAI;AAAA,UAClC;AACA,qBAAW,KAAK,SAAS;AAAA,QAC3B;AACA,iBAAS,KAAK,GAAG,KAAK,KAAK,eAAe,QAAQ,EAAE,IAAI;AACtD,gBAAM,SAAS,KAAK,eAAe,IAAI;AACvC,gBAAM,cAAc,KAAK,eAAe,IAAI;AAC5C,gBAAM,aAAa,KAAK,OAAO,QAAQ,cAAc,QAAQ,YAAY,CAAC;AAC1E,qBAAW,KAAK,UAAU;AAAA,QAC5B;AACA,eAAO;AAAA,MACT,CAAC;AAAA,IACH;AAAA,EACF;AAAA,EACA,MAAM,IAAI,GAAG,GAAG,OAAO,CAAC,GAAG;AACzB,WAAO,WAAW,MAAM,GAAG,GAAG,IAAI;AAAA,EACpC;AAAA,EACA,MAAM,WAAW,SAAS,MAAM;AAC9B,WAAO,WAAW,MAAM,SAAS,IAAI;AAAA,EACvC;AAAA,EACA,MAAM,aAAa,GAAG,GAAG;AACvB,UAAM,iBAAiB,MAAM,KAAK,oBAAoB,GAAG,CAAC;AAC1D,UAAM,SAAS,eAAe;AAC9B,UAAM,UAAU,eAAe;AAC/B,UAAM,gBAAgB,KAAK,kBAAkB;AAC7C,UAAM,UAAU,cAAc,OAAO,OAAO,OAAO,CAAC;AACpD,UAAM,aAAa,CAAC;AACpB,eAAW,QAAQ,SAAS;AAC1B,YAAM,IAAI,MAAM,KAAK,KAAK;AAC1B,iBAAW,KAAK,EAAE,EAAE;AAAA,IACtB;AACA,YAAQ,OAAO;AACf,sBAAkB,eAAe,IAAI,CAAC;AACtC,sBAAkB,eAAe,IAAI,CAAC;AACtC,WAAO,iBAAiB,UAAU;AAAA,EACpC;AAAA,EACA,gBAAgBK,SAAQ;AACtB,UAAM,eAAe,CAAC;AACtB,UAAM,gBAAgBA,WAAU,QAAQA,QAAO;AAC/C,UAAM,UAAU,gBAAgB,KAAK,mBAAmB,KAAK;AAC7D,UAAM,eAAe,KAAK,WAAW,aAAa;AAClD,aAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC1C,UAAI,iBAAiB,CAAC,QAAQ,IAAI,WAAW;AAC3C;AAAA,MACF;AACA,mBAAa,KAAK,EAAE,MAAM,QAAQ,IAAI,cAAc,QAAQ,aAAa,IAAI,CAAC;AAAA,IAChF;AACA,WAAO;AAAA,EACT;AAAA,EACA,IAAI,aAAa,MAAM;AACrB,SAAK,gBAAgB;AAAA,EACvB;AAAA,EACA,IAAI,eAAe;AACjB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,UAAU,WAAW;AACvB,QAAI,KAAK,eAAe,WAAW;AACjC,WAAK,aAAa;AAClB,WAAK,mBAAmB;AAAA,IAC1B;AAAA,EACF;AAAA,EACA,UAAU;AACR,UAAM,SAAS,MAAM,QAAQ;AAC7B,QAAI,OAAO,yBAAyB,KAAK,KAAK,aAAa,QAAQ,KAAK,kBAAkB;AACxF,YAAM,mCAAmC,OAAO,EAAE;AAClD,WAAK,WAAW,QAAQ;AACxB,aAAO,wBAAwB,mCAAmC,OAAO,EAAE;AAAA,IAC7E;AACA,WAAO;AAAA,EACT;AAAA,EACA,qBAAqB;AACnB,QAAI;AACJ,QAAI,OAAO,KAAK,SAAS,UAAU;AACjC,kBAAY,YAAY,KAAK,IAAI;AAAA,IACnC,WAAW,MAAM,QAAQ,KAAK,IAAI,GAAG;AACnC,iBAAW,QAAQ,KAAK,MAAM;AAC5B,YAAI,OAAO,SAAS,UAAU;AAC5B,gBAAM,IAAI,MAAM,oDAAoD;AAAA,QACtE;AAAA,MACF;AACA,kBAAY,KAAK,KAAK,IAAI,CAAC,SAAS,YAAY,IAAI,CAAC;AAAA,IACvD,OAAO;AACL,YAAM,cAAc,OAAO,KAAK,KAAK,IAAI;AACzC,kBAAY,CAAC;AACb,YAAM,UAAU,KAAK;AACrB,iBAAW,cAAc,aAAa;AACpC,YAAI,OAAO,QAAQ,gBAAgB,UAAU;AAC3C,oBAAU,cAAc,YAAY,QAAQ,WAAW;AAAA,QACzD,OAAO;AACL,gBAAM,IAAI,MAAM,oDAAoD;AAAA,QACtE;AAAA,MACF;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,uBAAuB;AACrB,QAAI,OAAO,KAAK,YAAY,YAAY,OAAO,KAAK,YAAY,YAAY;AAC1E,aAAO,CAAC,YAAY,oBAAoB,KAAK,OAAO,CAAC,CAAC;AAAA,IACxD,WAAW,MAAM,QAAQ,KAAK,OAAO,GAAG;AACtC,aAAO,KAAK,QAAQ,IAAI,CAAC,WAAW,YAAY,oBAAoB,MAAM,CAAC,CAAC;AAAA,IAC9E,OAAO;AACL,YAAM,qBAAqB,CAAC;AAC5B,iBAAW,OAAO,KAAK,SAAS;AAC9B,2BAAmB,OAAO,YAAY,oBAAoB,KAAK,QAAQ,IAAI,CAAC;AAAA,MAC9E;AACA,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,oBAAoB;AAClB,WAAO;AAAA,MACL,MAAM,KAAK,mBAAmB;AAAA,MAC9B,SAAS,KAAK,qBAAqB;AAAA,MACnC,kBAAkB;AAAA,QAChB,YAAY,KAAK,UAAU,aAAa;AAAA,QACxC,QAAQ,KAAK,UAAU,UAAU;AAAA,MACnC;AAAA,IACF;AAAA,EACF;AAAA,EACA,mBAAmB,gBAAgB;AACjC,QAAI,eAAe,oBAAoB,MAAM;AAC3C,YAAM,IAAI,MAAM,8CAA8C;AAAA,IAChE;AACA,QAAI,eAAe,gBAAgB,MAAM;AACvC,YAAM,IAAI,MAAM,4CAA4C;AAAA,IAC9D;AACA,QAAI,eAAe,sBAAsB,MAAM;AAC7C,YAAM,IAAI,MAAM,kDAAkD;AAAA,IACpE;AACA,UAAM,WAAW,oBAAoB,eAAe,gBAAgB;AACpE,UAAM,YAAY,YAAY,QAAQ;AACtC,QAAI;AACJ,QAAI,OAAO,eAAe,SAAS,UAAU;AAC3C,aAAO,YAAY,eAAe,IAAI;AAAA,IACxC,WAAW,MAAM,QAAQ,eAAe,IAAI,GAAG;AAC7C,aAAO,eAAe,KAAK,IAAI,CAAC,cAAc,YAAY,SAAS,CAAC;AAAA,IACtE,WAAW,eAAe,QAAQ,MAAM;AACtC,aAAO,CAAC;AACR,iBAAW,OAAO,eAAe,MAAM;AACrC,aAAK,OAAO,YAAY,eAAe,KAAK,IAAI;AAAA,MAClD;AAAA,IACF;AACA,QAAI;AACJ,QAAI,MAAM,QAAQ,eAAe,OAAO,GAAG;AACzC,gBAAU,eAAe,QAAQ,IAAI,CAAC,WAAW,YAAY,MAAM,CAAC;AAAA,IACtE,WAAW,eAAe,WAAW,MAAM;AACzC,gBAAU,CAAC;AACX,iBAAW,OAAO,eAAe,SAAS;AACxC,gBAAQ,OAAO,YAAY,eAAe,QAAQ,IAAI;AAAA,MACxD;AAAA,IACF;AACA,SAAK,QAAQ,EAAE,MAAM,SAAS,UAAU,CAAC;AAAA,EAC3C;AAAA,EACA,MAAM,KAAK,cAAcA,SAAQ;AAC/B,QAAI,OAAO,iBAAiB,UAAU;AACpC,YAAM,WAAW,WAAW,gBAAgB,YAAY;AACxD,UAAI,SAAS,WAAW,GAAG;AACzB,cAAM,IAAI,WAAW,0CAA0C,eAAe;AAAA,MAChF,WAAW,SAAS,SAAS,GAAG;AAC9B,cAAM,IAAI,WAAW,wBAAwB,SAAS,kCAAkC,eAAe;AAAA,MACzG;AACA,qBAAe,SAAS;AAAA,IAC1B;AACA,QAAI,aAAa,QAAQ,MAAM;AAC7B,YAAM,IAAI,WAAW,8GAA8G;AAAA,IACrI;AACA,UAAM,qBAAqB,MAAM,WAAW,cAAc,KAAK,gBAAgBA,OAAM,CAAC;AACtF,UAAM,eAAe;AACrB,UAAM,YAAY;AAClB,UAAM,cAAc,KAAK,OAAO,WAAW,YAAY;AACvD,UAAM,iBAAiB;AAAA,MACrB,eAAe;AAAA,MACf,QAAQ;AAAA,MACR,aAAa,8BAA8B;AAAA,MAC3C,aAAa;AAAA,IACf;AACA,UAAM,mBAAmBA,WAAU,OAAO,QAAQA,QAAO;AACzD,QAAI,oBAAoB,KAAK,aAAa,MAAM;AAC9C,qBAAe,iBAAiB,KAAK,kBAAkB;AACvD,YAAM,aAAa;AACnB,YAAM,EAAE,MAAM,qBAAqB,OAAO,qBAAqB,IAAI,MAAM,WAAW,cAAc,MAAM,KAAK,UAAU,WAAW,GAAG,UAAU;AAC/I,yBAAmB,MAAM,KAAK,GAAG,oBAAoB;AACrD,yBAAmB,OAAO,WAAW,wBAAwB,CAAC,mBAAmB,MAAM,mBAAmB,CAAC;AAAA,IAC7G;AACA,QAAI,KAAK,uBAAuB,MAAM;AACpC,YAAM,YAAY;AAClB,+BAAyB,KAAK,qBAAqB,KAAK,MAAM,SAAS;AACvE,qBAAe,sBAAsB,KAAK;AAAA,IAC5C;AACA,mBAAe,aAAa,mBAAmB;AAC/C,mBAAe,cAAc,mBAAmB;AAChD,WAAO,aAAa,KAAK,cAAc;AAAA,EACzC;AAAA,EACA,uBAAuB,qBAAqB;AAC1C,6BAAyB,qBAAqB,KAAK,IAAI;AACvD,SAAK,sBAAsB;AAAA,EAC7B;AAAA,EACA,yBAAyB;AACvB,WAAO,KAAK;AAAA,EACd;AACF;AACA,YAAY,YAAY;AACxB,sBAAsB,cAAc,WAAW;AAC/C,IAAI,aAAa,cAAc,YAAY;AAC3C;AACA,WAAW,YAAY;AACvB,sBAAsB,cAAc,UAAU;AAG9C,eAAe,cAAc,uBAAuB,eAAe;AACjE,MAAI,EAAE,mBAAmB,wBAAwB;AAC/C,4BAAwB,EAAE,eAAe,sBAAsB;AAAA,EACjE;AACA,0BAAwB;AACxB,MAAI,gBAAgB,sBAAsB;AAC1C,MAAI,cAAc,mBAAmB,MAAM;AACzC,oBAAgB,cAAc;AAAA,EAChC;AACA,QAAM,WAAW,oBAAoB,aAAa;AAClD,QAAMe,UAAS,YAAY,UAAU,aAAa;AAClD,MAAI,sBAAsB,mBAAmB,MAAM;AACjD,UAAM,eAAe,MAAM,WAAW,YAAY,sBAAsB,iBAAiB,sBAAsB,YAAYA,QAAO,QAAQ,IAAI,CAAC,WAAW,OAAO,YAAY,CAAC;AAC9K,UAAM,qBAAqB,CAAC;AAC5B,eAAW,UAAUA,QAAO,SAAS;AACnC,yBAAmB,OAAO,gBAAgB,aAAa,OAAO;AAAA,IAChE;AACA,IAAAA,QAAO,YAAY,kBAAkB;AACrC,YAAQ,YAAY;AAAA,EACtB;AACA,SAAOA;AACT;AACA,eAAe,wBAAwB,iBAAiBvB,UAAS;AAC/D,MAAIA,YAAW,MAAM;AACnB,IAAAA,WAAU,CAAC;AAAA,EACb;AACA,MAAI,OAAO,oBAAoB,UAAU;AACvC,UAAM,WAAW,WAAW,gBAAgB,iBAAiBA,QAAO;AACpE,QAAI,SAAS,WAAW,GAAG;AACzB,eAAS,KAAK,WAAW,mBAAmB,iBAAiBA,QAAO,CAAC;AAAA,IACvE,WAAW,SAAS,SAAS,GAAG;AAC9B,YAAM,IAAI,WAAW,wBAAwB,SAAS,kCAAkC,kBAAkB;AAAA,IAC5G;AACA,sBAAkB,SAAS;AAAA,EAC7B;AACA,SAAO,6BAA6B,iBAAiB,QAAQA,QAAO;AACtE;AACA,eAAe,6BAA6B,SAAS,eAAeA,UAAS;AAC3E,MAAIA,YAAW,MAAM;AACnB,IAAAA,WAAU,CAAC;AAAA,EACb;AACA,MAAI,QAAQ,QAAQ,MAAM;AACxB,UAAM,IAAI,WAAW,+GAA+G;AAAA,EACtI;AACA,QAAM,YAAY,MAAM,QAAQ,KAAK;AACrC,MAAI,gBAAgB,UAAU;AAC9B,MAAI,cAAc,mBAAmB,MAAM;AACzC,oBAAgB,cAAc;AAAA,EAChC;AACA,QAAM,SAASA,SAAQ,UAAU,OAAO,OAAOA,SAAQ;AACvD,QAAM,iBAAiB,UAAU,cAAc,QAAQ,UAAU,eAAe,QAAQ;AACxF,QAAMuB,UAAS,YAAY,oBAAoB,aAAa,GAAG,eAAe,cAAc;AAC5F,QAAM,iBAAiB,UAAU;AACjC,MAAI,kBAAkB,MAAM;AAC1B,IAAAA,QAAO,mBAAmB,cAAc;AAAA,EAC1C;AACA,MAAI,UAAU,uBAAuB,MAAM;AACzC,IAAAA,QAAO,uBAAuB,UAAU,mBAAmB;AAAA,EAC7D;AACA,MAAI,UAAU,cAAc,MAAM;AAChC,QAAI,UAAU,eAAe,MAAM;AACjC,YAAM,IAAI,WAAW,gHAAgH;AAAA,IACvI;AACA,UAAM,EAAE,cAAc,iBAAiB,IAAI,+BAA+B,UAAU,YAAY,UAAU,WAAW;AACrH,IAAAA,QAAO,YAAY,cAAc,MAAM;AACvC,QAAIA,QAAO,aAAa,QAAQ,iBAAiB,SAAS,GAAG;AAC3D,YAAMA,QAAO,UAAU,WAAW,gBAAgB;AAAA,IACpD;AACA,YAAQ,YAAY;AACpB,YAAQ,iBAAiB,IAAI,CAAC,MAAM,EAAE,MAAM,CAAC;AAAA,EAC/C;AACA,SAAOA;AACT;AACA,SAAS,+BAA+B,SAAS,OAAO;AACtD,QAAM,cAAc,WAAW,cAAc,SAAS,KAAK;AAC3D,QAAM,eAAe,CAAC;AACtB,QAAM,mBAAmB,CAAC;AAC1B,QAAM,QAAQ,CAAC,SAAS;AACtB,QAAI,KAAK,UAAU,aAAa;AAC9B,uBAAiB,KAAK,EAAE,MAAM,KAAK,MAAM,QAAQ,YAAY,KAAK,MAAM,CAAC;AAAA,IAC3E,OAAO;AACL,mBAAa,KAAK,QAAQ,YAAY,KAAK;AAAA,IAC7C;AAAA,EACF,CAAC;AACD,SAAO,EAAE,cAAc,iBAAiB;AAC1C;AACA,IAAI,aAAa,cAAc,YAAY;AAAA,EACzC,YAAY,MAAM;AAChB,UAAM,EAAE,QAAQ,CAAC,GAAG,SAAS,CAAC,EAAE,CAAC;AACjC,WAAO,QAAQ,CAAC;AAChB,SAAK,YAAY;AACjB,SAAK,QAAQ;AACb,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,OAAO,OAAO,aAAa;AAChE,QAAI,KAAK,UAAU,MAAM;AACvB,iBAAW,SAAS,KAAK,QAAQ;AAC/B,aAAK,IAAI,KAAK;AAAA,MAChB;AAAA,IACF;AAAA,EACF;AAAA,EACA,WAAW,OAAO;AAChB,UAAM,QAAQ,MAAM,aAAa,GAAG,cAAc,GAAG;AACrD,QAAI,MAAM,KAAK,CAAC,MAAM,IAAI,CAAC,GAAG;AAC5B,YAAM,IAAI,WAAW,kDAAkD,MAAM,0BAA0B,MAAM,aAAa,GAAG,aAAa,GAAG,QAAQ;AAAA,IACvJ;AAAA,EACF;AAAA,EACA,IAAI,OAAO;AACT,UAAM,uBAAuB,iBAAiB,cAAc,iBAAiB;AAC7E,QAAI;AACJ,QAAI,sBAAsB;AACxB,mBAAa;AACb,UAAI,WAAW,QAAQ,WAAW,GAAG;AACnC,cAAM,IAAI,WAAW,uHAAuH;AAAA,MAC9I;AACA,UAAI,WAAW,OAAO,WAAW,GAAG;AAClC,cAAM,IAAI,WAAW,qHAAqH;AAAA,MAC5I;AAAA,IACF;AACA,QAAI,KAAK,QAAQ,WAAW,GAAG;AAC7B,UAAI,MAAM,aAAa,WAAW,GAAG;AACnC,YAAI,MAAM,mBAAmB,MAAM;AACjC,gBAAM,IAAI,WAAW,+FAA+F;AAAA,QACtH;AACA,cAAM,IAAI,MAAM;AAAA,UACd,YAAY,MAAM;AAAA,UAClB,OAAO,MAAM;AAAA,UACb,MAAM,MAAM,OAAO;AAAA,QACrB,CAAC;AACD,cAAM,MAAM,CAAC;AAAA,MACf;AACA,UAAI,sBAAsB;AACxB,aAAK,UAAU,WAAW;AAC1B,aAAK,SAAS,WAAW;AAAA,MAC3B,OAAO;AACL,YAAI,MAAM,aAAa,WAAW,GAAG;AACnC,gBAAM,IAAI,WAAW,gHAAgH,MAAM,kBAAkB,MAAM,aAAa,0CAA0C;AAAA,QAC5N;AACA,YAAI,MAAM,aAAa,GAAG,cAAc,WAAW,GAAG;AACpD,gBAAM,IAAI,WAAW,uHAAuH;AAAA,QAC9I;AACA,aAAK,WAAW,KAAK;AACrB,aAAK,UAAU,CAAC,MAAM,aAAa,GAAG,cAAc,EAAE;AACtD,aAAK,SAAS,gBAAgB,KAAK,QAAQ,EAAE;AAAA,MAC/C;AACA,WAAK,eAAe,CAAC;AACrB,UAAI,KAAK;AAAA,QACP,eAAe;AAAA,QACf,eAAe,CAAC;AAAA,QAChB,aAAa,CAAC;AAAA,QACd,eAAe,CAAC;AAAA,QAChB,cAAc,KAAK;AAAA,QACnB,eAAe,KAAK;AAAA,QACpB,YAAY,aAAa,MAAM,KAAK,OAAO,MAAM;AAAA,QACjD,aAAa,CAAC,IAAI;AAAA,QAClB,aAAa,KAAK,OAAO,IAAI,CAAC,MAAM,EAAE,KAAK;AAAA,QAC3C,cAAc,KAAK,QAAQ,GAAG;AAAA,MAChC,CAAC;AAAA,IACH,OAAO;AACL,YAAM,eAAe,MAAM,MAAM,KAAK,QAAQ,EAAE;AAChD,UAAI,MAAM,QAAQ,YAAY,GAAG;AAC/B,cAAM,IAAI,UAAU,uHAAuH;AAAA,MAC7I;AACA,WAAK,WAAW,KAAK;AACrB,WAAK,UAAU,CAAC,YAAY;AAC5B,WAAK,aAAa,GAAG,gBAAgB,KAAK;AAC1C,WAAK,aAAa,GAAG,eAAe,CAAC,KAAK,QAAQ,GAAG,KAAK;AAAA,IAC5D;AACA,SAAK,OAAO,KAAK,KAAK;AACtB,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,MAAM;AACJ,QAAI,KAAK,OAAO,WAAW,GAAG;AAC5B,YAAM,IAAI,UAAU,mCAAmC;AAAA,IACzD;AACA,SAAK,OAAO,IAAI;AAChB,QAAI,KAAK,OAAO,WAAW,GAAG;AAC5B,WAAK,UAAU,CAAC;AAChB,WAAK,eAAe,CAAC;AACrB,WAAK,gBAAgB,CAAC;AAAA,IACxB,OAAO;AACL,YAAM,iBAAiB,KAAK,OAAO,SAAS;AAC5C,WAAK,OAAO,gBAAgB,gBAAgB,CAAC;AAC7C,WAAK,UAAU,CAAC,KAAK,OAAO,gBAAgB,MAAM;AAClD,WAAK,aAAa,GAAG,gBAAgB,KAAK;AAC1C,WAAK,aAAa,GAAG,eAAe,CAAC,KAAK,QAAQ,GAAG,KAAK;AAAA,IAC5D;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,QAAI,KAAK,SAAS,MAAM;AACtB,WAAK,MAAM;AAAA,IACb;AACA,WAAO,KAAK,MAAM,KAAK,QAAQ,MAAM;AAAA,EACvC;AAAA,EACA,MAAM,YAAY;AAChB,uBAAmB,UAAU;AAC7B,QAAI,KAAK,OAAO,WAAW,KAAK,KAAK,QAAQ,WAAW,GAAG;AACzD,YAAM,IAAI,UAAU,0EAA0E;AAAA,IAChG;AACA,SAAK,QAAQ,IAAI,YAAY;AAAA,MAC3B,QAAQ,KAAK;AAAA,MACb,SAAS,KAAK,QAAQ;AAAA,MACtB,MAAM,KAAK,OAAO;AAAA,IACpB,CAAC;AACD,SAAK,MAAM,YAAY,KAAK;AAC5B,SAAK,kBAAkB,KAAK,MAAM;AAClC,SAAK,cAAc,KAAK,MAAM;AAC9B,SAAK,yBAAyB,KAAK,MAAM;AACzC,SAAK,2BAA2B,KAAK,MAAM;AAC3C,SAAK,eAAe,KAAK,MAAM;AAC/B,SAAK,0BAA0B,KAAK,MAAM;AAC1C,SAAK,4BAA4B,KAAK,MAAM;AAC5C,SAAK,eAAe,KAAK,MAAM;AAC/B,SAAK,iBAAiB,KAAK,MAAM;AACjC,SAAK,cAAc,KAAK,MAAM;AAC9B,SAAK,aAAa,KAAK,MAAM;AAC7B,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,cAAc;AACZ,QAAI,CAAC,KAAK,OAAO;AACf,WAAK,MAAM;AAAA,IACb;AACA,WAAO,MAAM,YAAY;AAAA,EAC3B;AAAA,EACA,QAAQ,YAAY,WAAW,UAAU,QAAQ,KAAK;AACpD,QAAI,CAAC,KAAK,OAAO;AACf,WAAK,MAAM;AAAA,IACb;AACA,UAAM,QAAQ,YAAY,WAAW,OAAO;AAAA,EAC9C;AAAA,EACA,WAAW,SAAS;AAClB,QAAI,KAAK,SAAS,MAAM;AACtB,WAAK,MAAM;AAAA,IACb;AACA,SAAK,MAAM,WAAW,OAAO;AAAA,EAC/B;AAAA,EACA,SAAS,GAAG,GAAG,OAAO,CAAC,GAAG;AACxB,QAAI,CAAC,KAAK,OAAO;AACf,YAAM,IAAI,aAAa,mDAAmD;AAAA,IAC5E;AACA,WAAO,KAAK,MAAM,SAAS,GAAG,GAAG,IAAI;AAAA,EACvC;AAAA,EACA,MAAM,gBAAgB,SAAS,MAAM;AACnC,QAAI,CAAC,KAAK,OAAO;AACf,YAAM,IAAI,aAAa,mDAAmD;AAAA,IAC5E;AACA,WAAO,KAAK,MAAM,gBAAgB,SAAS,IAAI;AAAA,EACjD;AAAA,EACA,QAAQ,GAAG,OAAO,CAAC,GAAG;AACpB,QAAI,KAAK,SAAS,MAAM;AACtB,WAAK,MAAM;AAAA,IACb;AACA,WAAO,KAAK,MAAM,QAAQ,GAAG,IAAI;AAAA,EACnC;AAAA,EACA,eAAe,GAAG;AAChB,QAAI,KAAK,SAAS,MAAM;AACtB,WAAK,MAAM;AAAA,IACb;AACA,WAAO,KAAK,MAAM,eAAe,CAAC;AAAA,EACpC;AAAA,EACA,QAAQ,MAAM;AACZ,SAAK,MAAM;AACX,SAAK,MAAM,QAAQ,IAAI;AACvB,SAAK,aAAa,KAAK,MAAM;AAC7B,SAAK,mBAAmB,KAAK,MAAM;AACnC,SAAK,OAAO,KAAK,MAAM;AACvB,SAAK,UAAU,KAAK,MAAM;AAC1B,SAAK,iBAAiB,KAAK,MAAM;AACjC,SAAK,eAAe,KAAK,MAAM;AAAA,EACjC;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK,SAAS,OAAO,SAAS,KAAK,MAAM;AAAA,EAClD;AAAA,EACA,IAAI,UAAU,WAAW;AACvB,SAAK,MAAM,YAAY;AAAA,EACzB;AAAA,EACA,MAAM,IAAI,GAAG,GAAG,OAAO,CAAC,GAAG;AACzB,QAAI,CAAC,KAAK,OAAO;AACf,YAAM,IAAI,aAAa,mDAAmD;AAAA,IAC5E;AACA,WAAO,KAAK,MAAM,IAAI,GAAG,GAAG,IAAI;AAAA,EAClC;AAAA,EACA,MAAM,WAAW,SAAS,MAAM;AAC9B,QAAI,CAAC,KAAK,OAAO;AACf,YAAM,IAAI,aAAa,mDAAmD;AAAA,IAC5E;AACA,WAAO,KAAK,MAAM,WAAW,SAAS,IAAI;AAAA,EAC5C;AAAA,EACA,MAAM,aAAa,GAAG,GAAG;AACvB,WAAO,KAAK,MAAM,aAAa,GAAG,CAAC;AAAA,EACrC;AAAA,EACA,OAAO,WAAW,KAAKf,SAAQ,gBAAgB,CAAC,GAAG,iBAAiB,OAAO;AACzE,QAAI;AACJ,QAAI,mBAAmB,CAAC;AACxB,QAAIA,mBAAkB,OAAO;AAC3B,UAAI,EAAEA,QAAO,GAAG,aAAa,SAASA,QAAO,GAAG,iBAAiB,SAAS;AACxE,cAAM,IAAI,WAAW,gDAAgD;AAAA,MACvE;AACA,oBAAcA;AAAA,IAChB,OAAO;AACL,mBAAa,OAAOA,QAAO,aAAa,MAAM,MAAM,qHAAqH;AACzK,oBAAcA,QAAO;AACrB,aAAOA,QAAO;AACd,yBAAmBA;AAAA,IACrB;AACA,UAAMe,UAAS,IAAI,IAAI,gBAAgB;AACvC,QAAI,EAAEA,mBAAkB,aAAa;AACnC,YAAM,IAAI,oBAAoB,yDAAyDA,SAAQ;AAAA,IACjG;AACA,eAAW,QAAQ,aAAa;AAC9B,YAAM,iBAAiB;AACvB,YAAM,QAAQ,YAAY,MAAM,gBAAgB,cAAc;AAC9D,UAAI,gBAAgB;AAClB,cAAM,6BAA6B,IAAI;AAAA,MACzC;AACA,MAAAA,QAAO,IAAI,KAAK;AAAA,IAClB;AACA,WAAOA;AAAA,EACT;AAAA,EACA,IAAI,aAAa,MAAM;AACrB,QAAI,KAAK,SAAS,MAAM;AACtB,YAAM,IAAI,WAAW,mFAAmF;AAAA,IAC1G;AACA,SAAK,MAAM,eAAe;AAAA,EAC5B;AAAA,EACA,IAAI,eAAe;AACjB,QAAI,KAAK,SAAS,MAAM;AACtB,YAAM,IAAI,WAAW,mFAAmF;AAAA,IAC1G;AACA,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,YAAY;AACV,UAAM,SAAS,CAAC;AAChB,eAAW,SAAS,KAAK,QAAQ;AAC/B,YAAM,OAAO,CAAC;AACd,WAAK,eAAe,MAAM,aAAa;AACvC,WAAK,YAAY,MAAM,UAAU;AACjC,aAAO,KAAK,IAAI;AAAA,IAClB;AACA,WAAO,EAAE,MAAM,KAAK,MAAM,OAAO;AAAA,EACnC;AACF;AACA,WAAW,YAAY;AACvB,sBAAsB,cAAc,UAAU;AAG9C,SAAS,MAAM,MAAM;AACnB,SAAO,IAAI,YAAY,IAAI;AAC7B;AACA,SAAS,WAAWf,SAAQ;AAC1B,SAAO,IAAI,WAAWA,OAAM;AAC9B;AACA,SAAS,gBAAgB,iBAAiBR,UAAS;AACjD,MAAIA,YAAW,MAAM;AACnB,IAAAA,WAAU,CAAC;AAAA,EACb;AACA,SAAO,wBAAwB,iBAAiBA,QAAO;AACzD;AACA,SAAS,MAAMQ,SAAQ;AACrB,SAAO,MAAMA,OAAM;AACrB;AACA,SAAS,4BAA4B,gBAAgB,qBAAqB;AACxE,8BAA4B,4BAA4B,gBAAgB,mBAAmB;AAC7F;AAGA,IAAI,aAAa,cAAc,sBAAsB,aAAa;AAAA,EAChE,YAAY;AACV,WAAO,CAAC;AAAA,EACV;AACF;AACA,IAAI,OAAO,cAAc,WAAW;AAAA,EAClC,MAAM,GAAGQ,SAAQ,GAAG;AAClB,WAAO,KAAK,GAAGA,MAAK;AAAA,EACtB;AACF;AACA,KAAK,YAAY;AACjB,sBAAsB,cAAc,IAAI;AACxC,IAAI,QAAQ,cAAc,WAAW;AAAA,EACnC,MAAM,GAAG;AACP,WAAO,KAAK,CAAC;AAAA,EACf;AACF;AACA,MAAM,YAAY;AAClB,sBAAsB,cAAc,KAAK;AACzC,IAAI,QAAQ,cAAc,WAAW;AAAA,EACnC,MAAM,GAAG;AACP,WAAO,KAAK,CAAC;AAAA,EACf;AACF;AACA,MAAM,YAAY;AAClB,sBAAsB,cAAc,KAAK;AACzC,IAAI,SAAS,cAAc,WAAW;AAAA,EACpC,MAAM,GAAG;AACP,WAAO,KAAK,MAAM,QAAQ,GAAG,KAAK,CAAC,CAAC,CAAC;AAAA,EACvC;AACF;AACA,OAAO,YAAY;AACnB,sBAAsB,cAAc,MAAM;AAC1C,IAAI,SAAS,cAAc,WAAW;AAAA,EACpC,MAAM,GAAG;AACP,WAAO;AAAA,EACT;AACF;AACA,OAAO,YAAY;AACnB,sBAAsB,cAAc,MAAM;AAC1C,IAAI,WAAW,cAAc,WAAW;AAAA,EACtC,MAAM,GAAG;AACP,WAAO,QAAQ,CAAC;AAAA,EAClB;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,cAAc,cAAc,WAAW;AAAA,EACzC,MAAM,GAAG;AACP,WAAO,YAAY,CAAC;AAAA,EACtB;AACF;AACA,YAAY,YAAY;AACxB,sBAAsB,cAAc,WAAW;AAC/C,IAAI,YAAY,cAAc,WAAW;AAAA,EACvC,MAAM,GAAG;AACP,WAAO,SAAS,CAAC;AAAA,EACnB;AACF;AACA,UAAU,YAAY;AACtB,sBAAsB,cAAc,SAAS;AAC7C,IAAI,WAAW,cAAc,WAAW;AAAA,EACtC,MAAM,GAAG;AACP,WAAO,SAAS,CAAC;AAAA,EACnB;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,QAAQ,cAAc,WAAW;AAAA,EACnC,MAAM,GAAG;AACP,WAAO,MAAM,CAAC;AAAA,EAChB;AACF;AACA,MAAM,YAAY;AAClB,sBAAsB,cAAc,KAAK;AACzC,IAAI,WAAW,cAAc,WAAW;AAAA,EACtC,MAAM,GAAG,OAAO,IAAI;AAClB,WAAO,QAAQ,GAAG,IAAI;AAAA,EACxB;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,cAAc,cAAc,WAAW;AAAA,EACzC,MAAM,GAAG,OAAO,IAAI;AAClB,WAAO,WAAW,GAAG,IAAI;AAAA,EAC3B;AACF;AACA,YAAY,YAAY;AACxB,sBAAsB,cAAc,WAAW;AAC/C,IAAI,QAAQ,cAAc,WAAW;AAAA,EACnC,MAAM,GAAGA,SAAQ,GAAG;AAClB,WAAO,KAAK,MAAM,IAAI,QAAQ,IAAI,GAAGA,MAAK,CAAC,GAAG,CAAC,CAAC;AAAA,EAClD;AACF;AACA,MAAM,YAAY;AAClB,sBAAsB,cAAc,KAAK;AACzC,IAAI,OAAO,cAAc,WAAW;AAAA,EAClC,MAAM,GAAG;AACP,WAAO,KAAK,MAAM,IAAI,GAAG,MAAM,SAAS,CAAC,CAAC,CAAC,CAAC;AAAA,EAC9C;AACF;AACA,KAAK,YAAY;AACjB,sBAAsB,cAAc,IAAI;AACxC,SAAS,oBAAoB,aAAa;AACxC,SAAO,YAAY,aAAa;AAClC;AACA,SAAS,sBAAsBR,SAAQ,gBAAgB,CAAC,GAAG;AACzD,SAAO,uBAAuBA,SAAQ,sBAAsB,iBAAiB,OAAO,EAAE,cAAc,eAAe,YAAY;AACjI;AACA,SAAS,cAAc,YAAY;AACjC,MAAI,cAAc,MAAM;AACtB,UAAMA,UAAS,CAAC;AAChB,IAAAA,QAAO,eAAe;AACtB,IAAAA,QAAO,YAAY,CAAC;AACpB,WAAO,sBAAsBA,OAAM;AAAA,EACrC;AACA,MAAI,OAAO,eAAe,UAAU;AAClC,UAAMA,UAAS,CAAC;AAChB,IAAAA,QAAO,eAAe;AACtB,IAAAA,QAAO,YAAY,CAAC;AACpB,WAAO,sBAAsBA,OAAM;AAAA,EACrC,WAAW,sBAAsB,YAAY;AAC3C,WAAO;AAAA,EACT,OAAO;AACL,WAAO,sBAAsB,UAAU;AAAA,EACzC;AACF;AAGA,SAAS,iBAAiB,MAAM;AAC9B,MAAI,QAAQ,QAAQ,OAAO,SAAS,UAAU;AAC5C,UAAM,IAAI,MAAM,yFAAyF,MAAM;AAAA,EACjH;AACF;AACA,IAAI,cAAc,cAAc,sBAAsB,aAAa;AACnE;AACA,IAAI,OAAO,cAAc,YAAY;AAAA,EACnC,YAAY,MAAM;AAChB,UAAM;AACN,qBAAiB,IAAI;AACrB,SAAK,KAAK,QAAQ,QAAQ,KAAK,MAAM,OAAO,OAAO,KAAK;AACxD,SAAK,KAAK,QAAQ,QAAQ,KAAK,MAAM,OAAO,OAAO,KAAK;AACxD,SAAK,QAAQ,KAAK,OAAO;AACzB,SAAK,QAAQ,KAAK,OAAO;AAAA,EAC3B;AAAA,EACA,MAAM,GAAG;AACP,WAAO,KAAK,MAAM;AAChB,UAAI,iBAAiB,MAAM,CAAC,CAAC,CAAC;AAC9B,UAAI,KAAK,OAAO;AACd,yBAAiB,KAAK,gBAAgB,KAAK,IAAI,KAAK,IAAI,IAAI,CAAC,CAAC,CAAC,CAAC;AAAA,MAClE;AACA,UAAI,KAAK,OAAO;AACd,yBAAiB,KAAK,gBAAgB,KAAK,IAAI,KAAK,IAAI,QAAQ,CAAC,CAAC,CAAC,CAAC;AAAA,MACtE;AACA,aAAO,QAAQ,gBAAgB,CAAC,CAAC;AAAA,IACnC,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,WAAO,EAAE,MAAM,KAAK,IAAI,MAAM,KAAK,GAAG;AAAA,EACxC;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,WAAO,IAAI,IAAI,EAAE,IAAIA,QAAO,OAAO,IAAIA,QAAO,MAAM,CAAC;AAAA,EACvD;AACF;AACA,KAAK,YAAY;AACjB,sBAAsB,cAAc,IAAI;AACxC,SAAS,GAAG,MAAM;AAChB,mBAAiB,IAAI;AACrB,SAAO,IAAI,KAAK,EAAE,IAAI,QAAQ,OAAO,KAAK,KAAK,MAAM,IAAI,EAAE,CAAC;AAC9D;AACA,SAAS,GAAG,MAAM;AAChB,mBAAiB,IAAI;AACrB,SAAO,IAAI,KAAK,EAAE,IAAI,QAAQ,OAAO,KAAK,KAAK,MAAM,IAAI,EAAE,CAAC;AAC9D;AACA,IAAI,6CAA6C;AAAA,EAC/C,QAAQ;AACV;AACA,SAAS,qBAAqB,YAAY;AACxC,SAAO,qBAAqB,UAAU;AACxC;AACA,SAAS,uBAAuBA,SAAQ,gBAAgB,CAAC,GAAG;AAC1D,SAAO,uBAAuBA,SAAQ,sBAAsB,iBAAiB,OAAO,EAAE,cAAc,eAAe,aAAa;AAClI;AACA,SAAS,eAAe,YAAY;AAClC,MAAI,cAAc,MAAM;AACtB,WAAO;AAAA,EACT;AACA,MAAI,OAAO,eAAe,UAAU;AAClC,UAAM,YAAY,cAAc,6CAA6C,2CAA2C,cAAc;AACtI,UAAMA,UAAS,EAAE,WAAW,QAAQ,CAAC,EAAE;AACvC,WAAO,uBAAuBA,OAAM;AAAA,EACtC,WAAW,sBAAsB,aAAa;AAC5C,WAAO;AAAA,EACT,OAAO;AACL,WAAO,uBAAuB,UAAU;AAAA,EAC1C;AACF;AAGA,IAAI,OAAO,cAAc,MAAM;AAAA,EAC7B,YAAY,MAAM;AAChB,UAAM,QAAQ,OAAO,CAAC,IAAI,IAAI;AAC9B,SAAK,kBAAkB;AACvB,QAAI,QAAQ,MAAM;AAChB,WAAK,WAAW,KAAK;AAAA,IACvB;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,aAAS,oBAAoB,MAAM;AACnC,QAAI,SAAS,KAAK,MAAM;AACxB,QAAI,KAAK,YAAY,MAAM;AACzB,eAAS,YAAY,QAAQ,GAAG,KAAK,QAAQ;AAAA,IAC/C;AACA,WAAO;AAAA,EACT;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,EAAE,UAAU,KAAK,SAAS;AACzC,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,KAAK,YAAY;AACjB,sBAAsB,cAAc,IAAI;AACxC,IAAI,YAAY,cAAc,MAAM;AAAA,EAClC,YAAY,MAAM;AAChB,UAAM,QAAQ,OAAO,CAAC,IAAI,IAAI;AAC9B,SAAK,gBAAgB;AACrB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,SAAK,QAAQ,KAAK,SAAS,OAAO,KAAK,gBAAgB,KAAK;AAAA,EAC9D;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,UAAM,IAAI,oBAAoB,MAAM;AACpC,WAAO,UAAU,GAAG,KAAK,KAAK;AAAA,EAChC;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,EAAE,OAAO,KAAK,MAAM;AACnC,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,UAAU,YAAY;AACtB,sBAAsB,cAAc,SAAS;AAC7C,IAAI,QAAQ,cAAc,MAAM;AAAA,EAC9B,YAAY,MAAM;AAChB,UAAM,QAAQ,OAAO,CAAC,IAAI,IAAI;AAC9B,SAAK,4BAA4B;AACjC,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,SAAK,kBAAkB;AACvB,SAAK,mBAAmB,eAAe,KAAK,oBAAoB,KAAK,yBAAyB;AAC9F,SAAK,mBAAmB,eAAe,KAAK,gBAAgB;AAC5D,SAAK,kBAAkB,cAAc,KAAK,eAAe;AACzD,QAAI,KAAK,cAAc,MAAM;AAC3B,WAAK,aAAa;AAAA,IACpB,WAAW,MAAM,QAAQ,KAAK,UAAU,GAAG;AACzC,WAAK,aAAa,KAAK;AAAA,IACzB,WAAW,OAAO,KAAK,eAAe,UAAU;AAC9C,WAAK,aAAa,CAAC,KAAK,UAAU;AAAA,IACpC,OAAO;AACL,YAAM,IAAI,WAAW,sEAAsE,KAAK,YAAY;AAAA,IAC9G;AAAA,EACF;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,aAAa,WAAW,MAAM,CAAC;AACrC,QAAI,KAAK,cAAc,MAAM;AAC3B,iBAAW,MAAM,KAAK,YAAY;AAChC,mBAAW,KAAK,KAAK;AAAA,MACvB;AAAA,IACF;AACA,SAAK,QAAQ,KAAK,UAAU,SAAS,YAAY,WAAW,KAAK,kBAAkB,KAAK,kBAAkB,MAAM,KAAK,eAAe;AACpI,UAAM,OAAO,CAAC;AACd,QAAI,KAAK,cAAc,MAAM;AAC3B,eAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,aAAK,MAAM,WAAW;AAAA,MACxB;AAAA,IACF;AACA,SAAK,YAAY,CAAC,IAAI,UAAU;AAAA,MAC9B,MAAM,WAAW;AAAA,MACjB;AAAA,IACF,CAAC,CAAC;AACF,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,aAAS,oBAAoB,MAAM;AACnC,WAAO,MAAM,QAAQ,KAAK,MAAM,KAAK,CAAC;AAAA,EACxC;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,kBAAkB,qBAAqB,KAAK,gBAAgB;AAAA,MAC5D,kBAAkB,qBAAqB,KAAK,gBAAgB;AAAA,MAC5D,iBAAiB,oBAAoB,KAAK,eAAe;AAAA,MACzD,YAAY,KAAK;AAAA,IACnB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,MAAM,YAAY;AAClB,sBAAsB,cAAc,KAAK;AACzC,IAAI,MAAM,cAAc,MAAM;AAAA,EAC5B,YAAY,MAAM;AAChB,UAAM,QAAQ,OAAO,CAAC,IAAI,IAAI;AAC9B,SAAK,gBAAgB;AACrB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,QAAI,KAAK,SAAS,QAAQ,KAAK,UAAU,KAAK,eAAe;AAC3D,YAAM,IAAI,oBAAoB,4BAA4B,KAAK,+CAA+C;AAAA,IAChH;AACA,SAAK,QAAQ,KAAK,SAAS,OAAO,KAAK,gBAAgB,KAAK;AAAA,EAC9D;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,UAAM,IAAI,oBAAoB,MAAM;AACpC,WAAO,IAAI,CAAC;AAAA,EACd;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,EAAE,OAAO,KAAK,MAAM;AACnC,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,IAAI,YAAY;AAChB,sBAAsB,cAAc,GAAG;AACvC,IAAI,kBAAkB,cAAc,MAAM;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM,QAAQ,OAAO,CAAC,IAAI,IAAI;AAC9B,SAAK,gBAAgB;AACrB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,SAAK,QAAQ,KAAK,SAAS,OAAO,KAAK,gBAAgB,KAAK;AAAA,EAC9D;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,UAAM,IAAI,oBAAoB,MAAM;AACpC,WAAO,IAAI,GAAG,KAAK,QAAQ,GAAG,KAAK,KAAK,GAAG,SAAS,CAAC;AAAA,EACvD;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,EAAE,OAAO,KAAK,MAAM;AACnC,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,IAAI,WAAW,cAAc,MAAM;AAAA,EACjC,YAAY,MAAM;AAChB,UAAM,QAAQ,OAAO,CAAC,IAAI,IAAI;AAC9B,SAAK,eAAe;AACpB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,SAAK,UAAU,IAAI,SAAS,EAAE;AAC9B,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,eAAe,KAAK;AAAA,EAC3D;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,UAAM,IAAI,oBAAoB,MAAM;AACpC,WAAO,KAAK,QAAQ,GAAG,KAAK,IAAI;AAAA,EAClC;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,EAAE,MAAM,KAAK,KAAK;AACjC,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAG5C,SAAS,eAAe,OAAO,IAAI,MAAM;AACvC,MAAI,OAAO,UAAU,UAAU;AAC7B,WAAO,aAAa,OAAO,EAAE;AAAA,EAC/B,OAAO;AACL,QAAI,MAAM,WAAW,IAAI;AACvB,YAAM,IAAI,WAAW,OAAO,gDAAgD,0BAA0B,MAAM,kBAAkB;AAAA,IAChI;AACA,aAAS,KAAK,GAAG,KAAK,IAAI,EAAE,IAAI;AAC9B,YAAM,cAAc,MAAM;AAC1B,UAAI,CAAC,UAAU,WAAW,GAAG;AAC3B,cAAM,IAAI,WAAW,OAAO,gDAAgD,0BAA0B,KAAK,UAAU,KAAK,oCAAoC,aAAa;AAAA,MAC7K;AAAA,IACF;AACA,WAAO;AAAA,EACT;AACF;AACA,SAAS,iBAAiB,aAAa,YAAYa,UAAS,QAAQ,WAAW,GAAG;AAChF,MAAI,eAAe,MAAM;AACvB,WAAO;AAAA,EACT;AACA,QAAM,oBAAoB,cAAc,aAAa,MAAM,WAAW;AACtE,MAAI;AACJ,MAAIA,aAAY,QAAQ;AACtB,mBAAe;AAAA,EACjB,OAAO;AACL,mBAAe,cAAc,oBAAoB;AAAA,EACnD;AACA,SAAO,KAAK,OAAO,eAAe,SAAS,KAAK,MAAM;AACxD;AACA,SAAS,aAAa,SAAS,YAAY,YAAYA,UAAS;AAC9D,MAAI,WAAW,MAAM;AACnB,WAAO;AAAA,EACT;AACA,MAAIA,aAAY,SAAS;AACvB,cAAU,UAAU,aAAa,KAAK,CAAC,aAAa,YAAY,CAAC,CAAC;AAAA,EACpE,WAAWA,aAAY,QAAQ;AAC7B,cAAU,UAAU;AAAA,EACtB,OAAO;AACL,UAAM,IAAI,WAAW,2BAA2BA,WAAU;AAAA,EAC5D;AACA,SAAO;AACT;AAGA,SAAS,sBAAsB,GAAG,YAAY;AAC5C,SAAO,KAAK,MAAM;AAChB,oBAAgB,UAAU;AAC1B,QAAI,eAAe,iBAAiB;AAClC,aAAO,UAAU,GAAG,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,IAClC,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF,CAAC;AACH;AACA,SAAS,sBAAsB,GAAG,YAAY;AAC5C,SAAO,KAAK,MAAM;AAChB,oBAAgB,UAAU;AAC1B,QAAI,eAAe,iBAAiB;AAClC,aAAO,UAAU,GAAG,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,IACrC,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF,CAAC;AACH;AACA,SAAS,eAAe,GAAG,QAAQ,MAAMf,WAAU,GAAGe,WAAU,SAAS,YAAY,eAAe,GAAG;AACrG,SAAO,KAAK,MAAM;AAChB,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,oBAAgB,UAAU;AAC1B,QAAI,EAAE,MAAM,WAAW,GAAG;AACxB,YAAM,IAAI,WAAW,+DAA+D,EAAE,MAAM,iBAAiB;AAAA,IAC/G;AACA,QAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,YAAM,IAAI,WAAW,iEAAiE,OAAO,MAAM,gBAAgB;AAAA,IACrH;AACA,QAAI,QAAQ,QAAQ,KAAK,MAAM,WAAW,GAAG;AAC3C,YAAM,IAAI,WAAW,+DAA+D,OAAO,MAAM,gBAAgB;AAAA,IACnH;AACA,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC;AAAA,IAC5B;AACA,QAAIA,aAAY,UAAU;AACxB,YAAM,IAAI,oBAAoB,+EAA+E;AAAA,IAC/G;AACA,QAAI,IAAI,OAAO,GAAG,QAAQf,UAASe,aAAY,SAAS,SAAS,SAAS,OAAO,YAAY;AAC7F,QAAI,QAAQ,MAAM;AAChB,UAAI,QAAQ,GAAG,IAAI;AAAA,IACrB;AACA,WAAO;AAAA,EACT,CAAC;AACH;AACA,SAAS,yBAAyB,GAAG,QAAQ,MAAMf,WAAU,CAAC,GAAG,CAAC,GAAGe,WAAU,SAAS,YAAY,cAAc,cAAc,MAAM;AACpI,SAAO,KAAK,MAAM;AAChB,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,oBAAgB,UAAU;AAC1B,QAAI,EAAE,SAAS,KAAK,EAAE,SAAS,GAAG;AAChC,YAAM,IAAI,WAAW,6EAA6E,EAAE,OAAO;AAAA,IAC7G;AACA,QAAI,OAAO,SAAS,KAAK,OAAO,SAAS,GAAG;AAC1C,YAAM,IAAI,WAAW,8EAA8E,EAAE,OAAO;AAAA,IAC9G;AACA,QAAI,IAAI,sBAAsB,GAAG,UAAU;AAC3C,QAAIA,aAAY,UAAU;AACxB,YAAM,IAAI,oBAAoB,+EAA+E;AAAA,IAC/G;AACA,QAAI,kBAAkB,OAAO;AAAA,MAC3B,GAAG;AAAA,MACH,QAAQ;AAAA,MACR,SAAAf;AAAA,MACA,KAAKe,aAAY,SAAS,SAAS;AAAA,MACnC,WAAW;AAAA,MACX,YAAY;AAAA,MACZ;AAAA,MACA,YAAY;AAAA,IACd,CAAC;AACD,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,GAAG,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,IAC/B;AACA,WAAO;AAAA,EACT,CAAC;AACH;AACA,SAAS,eAAe,GAAG,QAAQ,MAAMf,WAAU,CAAC,GAAG,GAAG,CAAC,GAAGe,WAAU,SAAS,YAAY,cAAc;AACzG,SAAO,KAAK,MAAM;AAChB,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,oBAAgB,UAAU;AAC1B,QAAI,EAAE,SAAS,KAAK,EAAE,SAAS,GAAG;AAChC,YAAM,IAAI,WAAW,mEAAmE,EAAE,OAAO;AAAA,IACnG;AACA,QAAI,OAAO,SAAS,KAAK,OAAO,SAAS,GAAG;AAC1C,YAAM,IAAI,WAAW,oEAAoE,EAAE,OAAO;AAAA,IACpG;AACA,QAAI,IAAI,sBAAsB,GAAG,UAAU;AAC3C,QAAIA,aAAY,UAAU;AACxB,YAAM,IAAI,oBAAoB,+EAA+E;AAAA,IAC/G;AACA,QAAI,OAAO,GAAG,QAAQf,UAASe,aAAY,SAAS,SAAS,SAAS,SAAS,YAAY;AAC3F,QAAI,QAAQ,MAAM;AAChB,UAAI,QAAQ,GAAG,IAAI;AAAA,IACrB;AACA,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,GAAG,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,IAClC;AACA,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,WAAW,cAAc,MAAM;AAAA,EACjC,YAAY,MAAM,MAAM;AACtB,UAAM,IAAI;AACV,SAAK,OAAO;AACZ,SAAK,6BAA6B;AAClC,SAAK,2BAA2B;AAChC,aAAS,WAAW,IAAI;AACxB,SAAK,OAAO;AACZ,0BAAsB,KAAK,MAAM,MAAM;AACvC,QAAI,KAAK,SAAS,KAAK,KAAK,SAAS,KAAK,KAAK,SAAS,GAAG;AACzD,YAAM,IAAI,oBAAoB,qDAAqD,KAAK,+BAA+B;AAAA,IACzH;AACA,SAAK,aAAa,eAAe,KAAK,YAAY,MAAM,YAAY;AACpE,SAAK,UAAU,eAAe,KAAK,WAAW,OAAO,IAAI,KAAK,SAAS,MAAM,SAAS;AACtF,SAAK,UAAU,KAAK,WAAW,OAAO,UAAU,KAAK;AACrD,qBAAiB,KAAK,OAAO;AAC7B,SAAK,aAAa,KAAK,cAAc,OAAO,iBAAiB,KAAK;AAClE,oBAAgB,KAAK,UAAU;AAC/B,SAAK,aAAa,cAAc,KAAK,UAAU;AAC/C,SAAK,UAAU,KAAK,WAAW,OAAO,OAAO,KAAK;AAClD,SAAK,kBAAkB,eAAe,KAAK,mBAAmB,KAAK,wBAAwB;AAC3F,SAAK,iBAAiB,cAAc,KAAK,cAAc;AACvD,SAAK,kBAAkB,eAAe,KAAK,eAAe;AAC1D,SAAK,sBAAsB,eAAe,KAAK,mBAAmB;AAClE,SAAK,eAAe,eAAe,KAAK,gBAAgB,OAAO,IAAI,KAAK,cAAc,MAAM,cAAc;AAC1G,QAAI,KAAK,SAAS,MAAM,MAAM,QAAQ,KAAK,YAAY,KAAK,KAAK,aAAa,WAAW,IAAI;AAC3F,YAAM,IAAI,WAAW,iGAAiG,KAAK,UAAU,KAAK,YAAY,GAAG;AAAA,IAC3J,WAAW,KAAK,SAAS,GAAG;AAC1B,UAAI,OAAO,KAAK,iBAAiB,UAAU;AACzC,aAAK,eAAe,CAAC,KAAK,cAAc,KAAK,YAAY;AAAA,MAC3D,WAAW,KAAK,aAAa,WAAW,GAAG;AACzC,cAAM,IAAI,WAAW,0FAA0F,KAAK,UAAU,KAAK,YAAY,GAAG;AAAA,MACpJ;AAAA,IACF,WAAW,KAAK,SAAS,GAAG;AAC1B,UAAI,OAAO,KAAK,iBAAiB,UAAU;AACzC,aAAK,eAAe,CAAC,KAAK,cAAc,KAAK,cAAc,KAAK,YAAY;AAAA,MAC9E,WAAW,KAAK,aAAa,WAAW,GAAG;AACzC,cAAM,IAAI,WAAW,4FAA4F,KAAK,UAAU,KAAK,YAAY,GAAG;AAAA,MACtJ;AAAA,IACF;AAAA,EACF;AAAA,EACA,OAAO,WAAW,MAAM;AACtB,YAAQ,gBAAgB,MAAM,yCAAyC;AACvE,QAAI,OAAO,KAAK,eAAe,YAAY,CAAC,wBAAwB,KAAK,YAAY,UAAU,GAAG,CAAC,GAAG;AACpG,YAAM,IAAI,WAAW,oGAAoG,KAAK,UAAU,KAAK,UAAU,IAAI;AAAA,IAC7J;AAAA,EACF;AAAA,EACA,YAAY;AACV,UAAMb,UAAS;AAAA,MACb,YAAY,KAAK;AAAA,MACjB,SAAS,KAAK;AAAA,MACd,SAAS,KAAK;AAAA,MACd,YAAY,KAAK;AAAA,MACjB,cAAc,KAAK;AAAA,MACnB,YAAY,oBAAoB,KAAK,UAAU;AAAA,MAC/C,SAAS,KAAK;AAAA,MACd,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,qBAAqB,qBAAqB,KAAK,mBAAmB;AAAA,MAClE,gBAAgB,oBAAoB,KAAK,cAAc;AAAA,IACzD;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,IAAI,OAAO,cAAc,SAAS;AAAA,EAChC,YAAY,MAAM,MAAM;AACtB,UAAM,MAAM,IAAI;AAChB,SAAK,SAAS;AACd,SAAK,WAAW,IAAI;AACpB,SAAK,UAAU,KAAK;AACpB,0BAAsB,KAAK,SAAS,SAAS;AAC7C,SAAK,oBAAoB,eAAe,KAAK,qBAAqB,KAAK,0BAA0B;AACjG,SAAK,mBAAmB,cAAc,KAAK,gBAAgB;AAC3D,SAAK,oBAAoB,eAAe,KAAK,iBAAiB;AAAA,EAChE;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,cAAc,KAAK,eAAe,kBAAkB,IAAI,WAAW,SAAS;AAClF,QAAI,WAAW,gBAAgB,MAAM;AACnC,YAAM,IAAI,WAAW,+DAA+D,WAAW,cAAc;AAAA,IAC/G;AACA,UAAM,WAAW,WAAW;AAC5B,UAAM,cAAc,KAAK,WAAW,OAAO,CAAC,UAAU,KAAK,OAAO,CAAC;AACnE,SAAK,SAAS,KAAK,UAAU,UAAU,aAAa,MAAM,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AACrI,QAAI,KAAK,SAAS;AAChB,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,OAAO,GAAG,MAAM,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IAChI;AACA,SAAK,YAAY,CAAC,EAAE,MAAM,KAAK,OAAO,GAAG,MAAM,EAAE,CAAC,cAAc,SAAS,EAAE,CAAC;AAC5E,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS,oBAAoB,MAAM;AACnC,UAAI;AACJ,YAAM,YAAY,KAAK,QAAQ,OAAO,OAAO,KAAK,KAAK,KAAK;AAC5D,YAAM,sBAAsB,2BAA2B,KAAK,WAAW,aAAa,CAAC;AACrF,UAAI,uBAAuB,QAAQ,KAAK,SAAS,GAAG;AAClD,kBAAU,yBAAyB,QAAQ,KAAK,OAAO,KAAK,GAAG,WAAW,KAAK,SAAS,KAAK,SAAS,KAAK,YAAY,KAAK,cAAc,mBAAmB;AAAA,MAC/J,OAAO;AACL,YAAI,KAAK,SAAS,GAAG;AACnB,oBAAU,eAAe,QAAQ,KAAK,OAAO,KAAK,GAAG,WAAW,KAAK,QAAQ,IAAI,KAAK,SAAS,KAAK,YAAY,KAAK,aAAa,EAAE;AAAA,QACtI,WAAW,KAAK,SAAS,GAAG;AAC1B,oBAAU,yBAAyB,QAAQ,KAAK,OAAO,KAAK,GAAG,WAAW,KAAK,SAAS,KAAK,SAAS,KAAK,YAAY,KAAK,YAAY;AAAA,QAC1I,WAAW,KAAK,SAAS,GAAG;AAC1B,oBAAU,eAAe,QAAQ,KAAK,OAAO,KAAK,GAAG,WAAW,KAAK,SAAS,KAAK,SAAS,KAAK,YAAY,KAAK,YAAY;AAAA,QAChI,OAAO;AACL,gBAAM,IAAI,oBAAoB,uDAAuD;AAAA,QACvF;AACA,YAAI,KAAK,cAAc,MAAM;AAC3B,oBAAU,KAAK,WAAW,MAAM,OAAO;AAAA,QACzC;AAAA,MACF;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,WAAW,CAAC;AAClB,UAAM,QAAQ,KAAK,eAAe,iBAAiB,WAAW,MAAM,GAAG,WAAW,SAAS,CAAC,IAAI,WAAW,MAAM,CAAC;AAClH,aAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,YAAM,SAAS,iBAAiB,MAAM,KAAK,KAAK,WAAW,KAAK,KAAK,SAAS,KAAK,QAAQ,KAAK,OAAO,KAAK,iBAAiB,WAAW,KAAK,eAAe,KAAK,aAAa,GAAG;AACjL,eAAS,KAAK,MAAM;AAAA,IACtB;AACA,QAAI,cAAc,CAAC,WAAW,EAAE;AAChC,QAAI,KAAK,eAAe,gBAAgB;AACtC,oBAAc,YAAY,OAAO,QAAQ;AACzC,kBAAY,KAAK,KAAK,OAAO;AAAA,IAC/B,OAAO;AACL,kBAAY,KAAK,KAAK,OAAO;AAC7B,oBAAc,YAAY,OAAO,QAAQ;AAAA,IAC3C;AACA,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,SAAS,KAAK;AAAA,MACd,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,kBAAkB,oBAAoB,KAAK,gBAAgB;AAAA,IAC7D;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,OAAO,WAAW,MAAM;AACtB,QAAI,EAAE,aAAa,SAAS,OAAO,KAAK,YAAY,YAAY,KAAK,UAAU,GAAG;AAChF,YAAM,IAAI,WAAW,0EAA0E,KAAK,UAAU,KAAK,OAAO,GAAG;AAAA,IAC/H;AAAA,EACF;AACF;AACA,IAAI,UAAU,cAAc,KAAK;AAAA,EAC/B,YAAY,MAAM;AAChB,UAAM,GAAG,IAAI;AACb,YAAQ,WAAW,IAAI;AAAA,EACzB;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,MAAM,UAAU;AAC/B,WAAOA,QAAO;AACd,WAAOA;AAAA,EACT;AAAA,EACA,OAAO,WAAW,MAAM;AACtB,QAAI,OAAO,KAAK,eAAe,YAAY,CAAC,wBAAwB,KAAK,YAAY,UAAU,GAAG,CAAC,GAAG;AACpG,YAAM,IAAI,WAAW,8FAA8F,KAAK,UAAU,KAAK,UAAU,IAAI;AAAA,IACvJ;AAAA,EACF;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,UAAU,cAAc,KAAK;AAAA,EAC/B,YAAY,MAAM;AAChB,UAAM,GAAG,IAAI;AACb,YAAQ,WAAW,IAAI;AAAA,EACzB;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,MAAM,UAAU;AAC/B,WAAOA,QAAO;AACd,WAAOA;AAAA,EACT;AAAA,EACA,OAAO,WAAW,MAAM;AACtB,QAAI,OAAO,KAAK,eAAe,UAAU;AACvC,UAAI,EAAE,MAAM,QAAQ,KAAK,UAAU,MAAM,KAAK,WAAW,WAAW,KAAK,KAAK,WAAW,WAAW,KAAK;AACvG,cAAM,IAAI,WAAW,2FAA2F,KAAK,UAAU,KAAK,UAAU,IAAI;AAAA,MACpJ;AAAA,IACF;AAAA,EACF;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,kBAAkB,cAAc,QAAQ;AAAA,EAC1C,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAC5C,QAAI,KAAK,YAAY,UAAU,KAAK,YAAY,SAAS;AACvD,YAAM,IAAI,WAAW,uGAAuG,KAAK,SAAS;AAAA,IAC5I;AAAA,EACF;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,WAAW,WAAW,GAAG;AAC3B,YAAM,IAAI,WAAW,qDAAqD,KAAK,UAAU,UAAU,CAAC;AAAA,IACtG;AACA,UAAM,cAAc,KAAK,eAAe,kBAAkB,IAAI,WAAW,SAAS;AAClF,QAAI,WAAW,gBAAgB,MAAM;AACnC,YAAM,IAAI,WAAW,sEAAsE;AAAA,IAC7F;AACA,UAAM,WAAW,WAAW;AAC5B,UAAM,cAAc,KAAK,WAAW,OAAO,CAAC,KAAK,SAAS,QAAQ,CAAC;AACnE,SAAK,SAAS,KAAK,UAAU,UAAU,aAAa,WAAW,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AAC1I,QAAI,KAAK,SAAS;AAChB,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,OAAO,GAAG,WAAW,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IACrI;AACA,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,GAAG,MAAM,EAAE,CAAC,cAAc,SAAS,EAAE,CAAC,CAAC;AAC/E,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,oBAAoB,MAAM;AACvC,UAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,cAAM,IAAI,WAAW,2FAA2F,OAAO,MAAM,QAAQ;AAAA,MACvI;AACA,YAAM,aAAa,OAAO;AAC1B,YAAM,YAAY,WAAW;AAC7B,UAAI;AACJ,UAAI;AACJ,UAAI,KAAK,eAAe,iBAAiB;AACvC,gBAAQ;AACR,gBAAQ;AAAA,MACV,OAAO;AACL,gBAAQ;AACR,gBAAQ;AAAA,MACV;AACA,YAAM,SAAS,WAAW;AAC1B,YAAM,QAAQ,WAAW;AACzB,YAAM,UAAU,KAAK,WAAW;AAChC,YAAM,UAAU,KAAK,WAAW;AAChC,YAAM,UAAU,KAAK,QAAQ;AAC7B,YAAM,UAAU,KAAK,QAAQ;AAC7B,YAAM,YAAY,aAAa,QAAQ,SAAS,SAAS,KAAK,OAAO;AACrE,YAAM,WAAW,aAAa,OAAO,SAAS,SAAS,KAAK,OAAO;AACnE,YAAM,cAAc,CAAC,WAAW,WAAW,UAAU,KAAK,OAAO;AACjE,UAAI,KAAK,eAAe,gBAAgB;AACtC,iBAAS,UAAU,QAAQ,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,MACzC;AACA,UAAI,UAAU,gBAAgB,QAAQ,KAAK,OAAO,KAAK,GAAG,aAAa,KAAK,SAAS,KAAK,OAAO;AACjG,UAAI,KAAK,eAAe,gBAAgB;AACtC,kBAAU,UAAU,SAAS,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,MAC3C;AACA,UAAI,KAAK,QAAQ,MAAM;AACrB,kBAAU,QAAQ,SAAS,KAAK,KAAK,KAAK,GAAG,KAAK,UAAU;AAAA,MAC9D;AACA,UAAI,KAAK,cAAc,MAAM;AAC3B,kBAAU,KAAK,WAAW,MAAM,OAAO;AAAA,MACzC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,cAAc,WAAW,MAAM;AACrC,QAAI;AACJ,QAAI;AACJ,QAAI;AACJ,QAAI,KAAK,eAAe,iBAAiB;AACvC,oBAAc;AACd,mBAAa;AACb,kBAAY;AAAA,IACd,OAAO;AACL,oBAAc;AACd,mBAAa;AACb,kBAAY;AAAA,IACd;AACA,UAAM,UAAU,KAAK,WAAW;AAChC,UAAM,UAAU,KAAK,WAAW;AAChC,UAAM,UAAU,KAAK,QAAQ;AAC7B,UAAM,UAAU,KAAK,QAAQ;AAC7B,gBAAY,eAAe,KAAK;AAChC,gBAAY,cAAc,aAAa,YAAY,aAAa,SAAS,SAAS,KAAK,OAAO;AAC9F,gBAAY,aAAa,aAAa,YAAY,YAAY,SAAS,SAAS,KAAK,OAAO;AAC5F,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,MAAM,UAAU;AAC/B,WAAOA,QAAO;AACd,WAAOA;AAAA,EACT;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,IAAI,kBAAkB,cAAc,QAAQ;AAAA,EAC1C,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAC5C,QAAI,KAAK,YAAY,UAAU,KAAK,YAAY,SAAS;AACvD,YAAM,IAAI,WAAW,uGAAuG,KAAK,SAAS;AAAA,IAC5I;AAAA,EACF;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,WAAW,WAAW,GAAG;AAC3B,YAAM,IAAI,WAAW,qDAAqD,KAAK,UAAU,UAAU,CAAC;AAAA,IACtG;AACA,UAAM,cAAc,KAAK,eAAe,kBAAkB,IAAI,WAAW,SAAS;AAClF,QAAI,WAAW,gBAAgB,MAAM;AACnC,YAAM,IAAI,WAAW,sEAAsE;AAAA,IAC7F;AACA,UAAM,WAAW,WAAW;AAC5B,UAAM,cAAc,KAAK,WAAW,OAAO,CAAC,KAAK,SAAS,QAAQ,CAAC;AACnE,SAAK,SAAS,KAAK,UAAU,UAAU,aAAa,WAAW,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AAC1I,QAAI,KAAK,SAAS;AAChB,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,OAAO,GAAG,WAAW,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IACrI;AACA,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,GAAG,MAAM,EAAE,CAAC,cAAc,SAAS,EAAE,CAAC,CAAC;AAC/E,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,oBAAoB,MAAM;AACvC,UAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,cAAM,IAAI,WAAW,2FAA2F,OAAO,MAAM,QAAQ;AAAA,MACvI;AACA,YAAM,aAAa,OAAO;AAC1B,YAAM,YAAY,WAAW;AAC7B,UAAI;AACJ,UAAI;AACJ,UAAI;AACJ,UAAI,KAAK,eAAe,iBAAiB;AACvC,gBAAQ;AACR,gBAAQ;AACR,gBAAQ;AAAA,MACV,OAAO;AACL,gBAAQ;AACR,gBAAQ;AACR,gBAAQ;AAAA,MACV;AACA,YAAM,QAAQ,WAAW;AACzB,YAAM,SAAS,WAAW;AAC1B,YAAM,QAAQ,WAAW;AACzB,YAAM,UAAU,KAAK,WAAW;AAChC,YAAM,UAAU,KAAK,WAAW;AAChC,YAAM,UAAU,KAAK,WAAW;AAChC,YAAM,UAAU,KAAK,QAAQ;AAC7B,YAAM,UAAU,KAAK,QAAQ;AAC7B,YAAM,UAAU,KAAK,QAAQ;AAC7B,YAAM,WAAW,aAAa,OAAO,SAAS,SAAS,KAAK,OAAO;AACnE,YAAM,YAAY,aAAa,QAAQ,SAAS,SAAS,KAAK,OAAO;AACrE,YAAM,WAAW,aAAa,OAAO,SAAS,SAAS,KAAK,OAAO;AACnE,YAAM,cAAc,CAAC,WAAW,UAAU,WAAW,UAAU,KAAK,OAAO;AAC3E,UAAI,KAAK,eAAe,gBAAgB;AACtC,iBAAS,UAAU,QAAQ,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,MAC5C;AACA,UAAI,UAAU,gBAAgB,QAAQ,KAAK,OAAO,KAAK,GAAG,aAAa,KAAK,SAAS,KAAK,OAAO;AACjG,UAAI,KAAK,eAAe,gBAAgB;AACtC,kBAAU,UAAU,SAAS,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,MAC9C;AACA,UAAI,KAAK,SAAS,MAAM;AACtB,kBAAU,QAAQ,SAAS,KAAK,KAAK,KAAK,GAAG,KAAK,UAAU;AAAA,MAC9D;AACA,UAAI,KAAK,eAAe,MAAM;AAC5B,kBAAU,KAAK,WAAW,MAAM,OAAO;AAAA,MACzC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,cAAc,WAAW,MAAM;AACrC,QAAI;AACJ,QAAI;AACJ,QAAI;AACJ,QAAI;AACJ,QAAI,KAAK,eAAe,iBAAiB;AACvC,oBAAc;AACd,kBAAY;AACZ,mBAAa;AACb,kBAAY;AAAA,IACd,OAAO;AACL,oBAAc;AACd,kBAAY;AACZ,mBAAa;AACb,kBAAY;AAAA,IACd;AACA,UAAM,UAAU,KAAK,WAAW;AAChC,UAAM,UAAU,KAAK,WAAW;AAChC,UAAM,UAAU,KAAK,WAAW;AAChC,UAAM,UAAU,KAAK,QAAQ;AAC7B,UAAM,UAAU,KAAK,QAAQ;AAC7B,UAAM,UAAU,KAAK,QAAQ;AAC7B,gBAAY,eAAe,KAAK;AAChC,gBAAY,aAAa,aAAa,YAAY,YAAY,SAAS,SAAS,KAAK,OAAO;AAC5F,gBAAY,cAAc,aAAa,YAAY,aAAa,SAAS,SAAS,KAAK,OAAO;AAC9F,gBAAY,aAAa,aAAa,YAAY,YAAY,SAAS,SAAS,KAAK,OAAO;AAC5F,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,MAAM,UAAU;AAC/B,WAAOA,QAAO;AACd,WAAOA;AAAA,EACT;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,IAAI,gBAAgB,cAAc,KAAK;AAAA,EACrC,YAAY,MAAMA,SAAQ;AACxB,UAAM,MAAMA,OAAM;AAClB,SAAK,gCAAgC;AACrC,SAAK,gCAAgC;AACrC,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AACvB,QAAIA,QAAO,WAAW,MAAM;AAC1B,YAAM,IAAI,WAAW,qFAAqF;AAAA,IAC5G;AACA,QAAIA,QAAO,qBAAqB,QAAQA,QAAO,qBAAqB,QAAQA,QAAO,oBAAoB,MAAM;AAC3G,YAAM,IAAI,WAAW,oPAAoP;AAAA,IAC3Q;AACA,QAAIA,QAAO,WAAW,QAAQA,QAAO,YAAY,UAAUA,QAAO,YAAY,SAAS;AACrF,YAAM,IAAI,WAAW,gBAAgB,KAAK,uEAAuE,KAAK,UAAUA,QAAO,OAAO,GAAG;AAAA,IACnJ;AACA,SAAK,kBAAkBA,QAAO,mBAAmB,OAAO,IAAIA,QAAO;AACnE,SAAK,uBAAuB,eAAeA,QAAO,wBAAwB,KAAK,6BAA6B;AAC5G,SAAK,uBAAuB,eAAeA,QAAO,oBAAoB;AACtE,SAAK,sBAAsB,cAAcA,QAAO,mBAAmB;AACnE,SAAK,uBAAuB,eAAeA,QAAO,wBAAwB,KAAK,6BAA6B;AAC5G,SAAK,uBAAuB,eAAeA,QAAO,oBAAoB;AACtE,SAAK,sBAAsB,cAAcA,QAAO,mBAAmB;AAAA,EACrE;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,WAAW,SAAS,KAAK,OAAO,GAAG;AACrC,YAAM,IAAI,WAAW,0BAA0B,KAAK,0BAA0B,KAAK,OAAO,gCAAgC,KAAK,UAAU,UAAU,GAAG;AAAA,IACxJ;AACA,UAAM,cAAc,KAAK,eAAe,kBAAkB,IAAI,WAAW,SAAS;AAClF,QAAI,WAAW,gBAAgB,QAAQ,WAAW,eAAe,GAAG;AAClE,YAAM,IAAI,WAAW,oEAAoE,KAAK,UAAU,WAAW,YAAY,GAAG;AAAA,IACpI;AACA,UAAM,WAAW,WAAW;AAC5B,UAAM,uBAAuB,KAAK,WAAW,OAAO,CAAC,UAAU,KAAK,eAAe,CAAC;AACpF,UAAM,uBAAuB,CAAC;AAC9B,aAAS,KAAK,GAAG,KAAK,KAAK,MAAM,EAAE,IAAI;AACrC,2BAAqB,KAAK,CAAC;AAAA,IAC7B;AACA,yBAAqB,KAAK,WAAW,KAAK,iBAAiB,KAAK,OAAO;AACvE,UAAM,YAAY;AAClB,SAAK,kBAAkB,KAAK,UAAU,oBAAoB,sBAAsB,WAAW,KAAK,sBAAsB,KAAK,sBAAsB,WAAW,KAAK,mBAAmB;AACpL,SAAK,kBAAkB,KAAK,UAAU,oBAAoB,sBAAsB,WAAW,KAAK,sBAAsB,KAAK,sBAAsB,WAAW,KAAK,mBAAmB;AACpL,QAAI,KAAK,SAAS;AAChB,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,OAAO,GAAG,WAAW,KAAK,iBAAiB,KAAK,iBAAiB,WAAW,KAAK,cAAc;AAAA,IAC1I,OAAO;AACL,WAAK,OAAO;AAAA,IACd;AACA,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,KAAK,OAAO,GAAG,MAAM,EAAE,CAAC,cAAc,SAAS,EAAE,CAAC,CAAC;AAC3F,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS,oBAAoB,MAAM;AACnC,UAAI;AACJ,UAAI,KAAK,SAAS,GAAG;AACnB,cAAM,IAAI,oBAAoB,kDAAkD;AAAA,MAClF,WAAW,KAAK,SAAS,GAAG;AAC1B,YAAI,KAAK,eAAe,iBAAiB;AACvC,mBAAS,UAAU,QAAQ,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,QACzC;AACA,iBAAS,gBAAgB,QAAQ,KAAK,gBAAgB,KAAK,GAAG,KAAK,gBAAgB,KAAK,GAAG,KAAK,SAAS,KAAK,SAAS,KAAK,cAAc,MAAM;AAAA,MAClJ;AACA,UAAI,KAAK,SAAS;AAChB,iBAAS,QAAQ,QAAQ,KAAK,KAAK,KAAK,GAAG,KAAK,UAAU;AAAA,MAC5D;AACA,UAAI,KAAK,cAAc,MAAM;AAC3B,iBAAS,KAAK,WAAW,MAAM,MAAM;AAAA,MACvC;AACA,UAAI,KAAK,eAAe,iBAAiB;AACvC,iBAAS,UAAU,QAAQ,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,MACzC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,MAAM,UAAU;AAC/B,WAAOA,QAAO;AACd,WAAOA,QAAO;AACd,WAAOA,QAAO;AACd,WAAOA,QAAO;AACd,IAAAA,QAAO,0BAA0B,qBAAqB,KAAK,oBAAoB;AAC/E,IAAAA,QAAO,0BAA0B,qBAAqB,KAAK,oBAAoB;AAC/E,IAAAA,QAAO,0BAA0B,qBAAqB,KAAK,oBAAoB;AAC/E,IAAAA,QAAO,0BAA0B,qBAAqB,KAAK,oBAAoB;AAC/E,IAAAA,QAAO,yBAAyB,oBAAoB,KAAK,mBAAmB;AAC5E,IAAAA,QAAO,yBAAyB,oBAAoB,KAAK,mBAAmB;AAC5E,WAAOA;AAAA,EACT;AACF;AACA,cAAc,YAAY;AAC1B,IAAI,kBAAkB,cAAc,cAAc;AAAA,EAChD,YAAY,MAAM;AAChB,UAAM,GAAG,IAAI;AAAA,EACf;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,IAAI,SAAS,cAAc,KAAK;AAAA,EAC9B,YAAY,MAAM;AAChB,UAAM,GAAG,IAAI;AACb,WAAO,WAAW,IAAI;AACtB,SAAK,YAAY,CAAC,EAAE,MAAM,EAAE,CAAC;AAAA,EAC/B;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,MAAM,UAAU;AAC/B,WAAOA,QAAO;AACd,WAAOA,QAAO;AACd,WAAOA;AAAA,EACT;AAAA,EACA,OAAO,WAAW,MAAM;AACtB,QAAI,OAAO,KAAK,eAAe,YAAY,CAAC,wBAAwB,KAAK,YAAY,UAAU,GAAG,CAAC,GAAG;AACpG,YAAM,IAAI,WAAW,yFAAyF,KAAK,UAAU,KAAK,UAAU,IAAI;AAAA,IAClJ;AAAA,EACF;AACF;AACA,OAAO,YAAY;AACnB,sBAAsB,cAAc,MAAM;AAC1C,IAAI,aAAa,cAAc,MAAM;AAAA,EACnC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,QAAI,OAAO,KAAK,aAAa,UAAU;AACrC,WAAK,WAAW,CAAC,CAAC,KAAK,UAAU,KAAK,QAAQ,GAAG,CAAC,KAAK,UAAU,KAAK,QAAQ,CAAC;AAAA,IACjF,WAAW,OAAO,KAAK,SAAS,OAAO,UAAU;AAC/C,WAAK,WAAW;AAAA,QACd,CAAC,KAAK,SAAS,IAAI,KAAK,SAAS,EAAE;AAAA,QACnC,CAAC,KAAK,SAAS,IAAI,KAAK,SAAS,EAAE;AAAA,MACrC;AAAA,IACF,OAAO;AACL,WAAK,WAAW,KAAK;AAAA,IACvB;AACA,SAAK,aAAa,KAAK,eAAe,SAAS,iBAAiB,KAAK;AACrE,SAAK,YAAY,CAAC,EAAE,MAAM,EAAE,CAAC;AAAA,EAC/B;AAAA,EACA,mBAAmB,YAAY;AAC7B,QAAI,KAAK,eAAe,iBAAiB;AACvC,aAAO;AAAA,QACL,WAAW;AAAA,QACX,WAAW;AAAA,QACX,WAAW,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG;AAAA,QACvD,WAAW,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG;AAAA,MACzD;AAAA,IACF,OAAO;AACL,aAAO;AAAA,QACL,WAAW;AAAA,QACX,WAAW,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG;AAAA,QACvD,WAAW,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG;AAAA,QACvD,WAAW;AAAA,MACb;AAAA,IACF;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS,oBAAoB,MAAM;AACnC,UAAI,KAAK,eAAe,gBAAgB;AACtC,cAAM,UAAU,eAAe,QAAQ,KAAK,SAAS,GAAG,IAAI,OAAO,MAAM,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG,IAAI,CAAC;AAC1H,eAAO,eAAe,SAAS,KAAK,SAAS,GAAG,IAAI,OAAO,MAAM,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG,IAAI,CAAC;AAAA,MACpH,OAAO;AACL,cAAM,UAAU,eAAe,QAAQ,KAAK,SAAS,GAAG,IAAI,OAAO,MAAM,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG,IAAI,CAAC;AAC1H,eAAO,eAAe,SAAS,KAAK,SAAS,GAAG,IAAI,OAAO,MAAM,KAAK,KAAK,SAAS,GAAG,KAAK,KAAK,SAAS,GAAG,IAAI,CAAC;AAAA,MACpH;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,EAAE,UAAU,KAAK,UAAU,YAAY,KAAK,WAAW;AACtE,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,WAAW,YAAY;AACvB,sBAAsB,cAAc,UAAU;AAC9C,IAAI,eAAe,cAAc,MAAM;AAAA,EACrC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,eAAe,CAAC,GAAG,CAAC;AACzB,SAAK,YAAY,CAAC,EAAE,MAAM,EAAE,CAAC;AAC7B,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,eAAe,KAAK;AACzD,SAAK,aAAa,KAAK,cAAc,OAAO,iBAAiB,KAAK;AAClE,oBAAgB,KAAK,UAAU;AAC/B,SAAK,gBAAgB,KAAK,iBAAiB,OAAO,YAAY,KAAK;AACnE,6BAAyB,KAAK,aAAa;AAAA,EAC7C;AAAA,EACA,mBAAmB,YAAY;AAC7B,QAAI,KAAK,eAAe,iBAAiB;AACvC,YAAM,SAAS,WAAW,MAAM,OAAO,OAAO,KAAK,KAAK,KAAK,WAAW;AACxE,YAAM,QAAQ,WAAW,MAAM,OAAO,OAAO,KAAK,KAAK,KAAK,WAAW;AACvE,aAAO,CAAC,WAAW,IAAI,WAAW,IAAI,QAAQ,KAAK;AAAA,IACrD,OAAO;AACL,YAAM,SAAS,WAAW,MAAM,OAAO,OAAO,KAAK,KAAK,KAAK,WAAW;AACxE,YAAM,QAAQ,WAAW,MAAM,OAAO,OAAO,KAAK,KAAK,KAAK,WAAW;AACvE,aAAO,CAAC,WAAW,IAAI,QAAQ,OAAO,WAAW,EAAE;AAAA,IACrD;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,oBAAoB,MAAM;AACvC,YAAM,aAAa,OAAO;AAC1B,UAAI,KAAK,eAAe,iBAAiB;AACvC,iBAAS,UAAU,QAAQ,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AACvC,cAAM,SAAS,KAAK,KAAK,KAAK,WAAW;AACzC,cAAM,QAAQ,KAAK,KAAK,KAAK,WAAW;AACxC,cAAM,UAAU,KAAK,kBAAkB,YAAY,MAAM,sBAAsB,QAAQ,CAAC,QAAQ,KAAK,CAAC,IAAI,MAAM,eAAe,QAAQ,CAAC,QAAQ,KAAK,CAAC;AACtJ,eAAO,UAAU,SAAS,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,MACxC,OAAO;AACL,cAAM,SAAS,KAAK,KAAK,KAAK,WAAW;AACzC,cAAM,QAAQ,KAAK,KAAK,KAAK,WAAW;AACxC,eAAO,KAAK,kBAAkB,YAAY,MAAM,sBAAsB,QAAQ,CAAC,QAAQ,KAAK,CAAC,IAAI,MAAM,eAAe,QAAQ,CAAC,QAAQ,KAAK,CAAC;AAAA,MAC/I;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,MAAM,KAAK;AAAA,MACX,YAAY,KAAK;AAAA,MACjB,eAAe,KAAK;AAAA,IACtB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAGhD,SAAS,iBAAiB,GAAG,iBAAiBF,WAAU,CAAC,GAAG,CAAC,GAAGe,WAAU,SAAS,YAAY,cAAc;AAC3G,SAAO,KAAK,MAAM;AAChB,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,oBAAgB,UAAU;AAC1B,QAAI,IAAI,sBAAsB,GAAG,UAAU;AAC3C,QAAI,EAAE,SAAS,GAAG;AAChB,YAAM,IAAI,WAAW,mEAAmE,EAAE,QAAQ;AAAA,IACpG;AACA,QAAI,gBAAgB,SAAS,GAAG;AAC9B,YAAM,IAAI,WAAW,yDAAyD,gBAAgB,QAAQ;AAAA,IACxG;AACA,QAAI,gBAAgB,GAAG,iBAAiBf,UAASe,aAAY,SAAS,SAAS,SAAS,QAAQ,YAAY;AAC5G,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,GAAG,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,IAC/B;AACA,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,kBAAkB,cAAc,SAAS;AAAA,EAC3C,YAAY,MAAM;AAChB,UAAM,GAAG,IAAI;AACb,SAAK,kBAAkB;AACvB,SAAK,kBAAkB,KAAK,mBAAmB,OAAO,IAAI,KAAK;AAC/D,SAAK,uBAAuB,eAAe,KAAK,wBAAwB,KAAK,0BAA0B;AACvG,SAAK,sBAAsB,cAAc,KAAK,mBAAmB;AACjE,SAAK,uBAAuB,eAAe,KAAK,oBAAoB;AAAA,EACtE;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,WAAW,SAAS,GAAG;AACzB,YAAM,IAAI,WAAW,uEAAuE,KAAK,UAAU,UAAU,IAAI;AAAA,IAC3H;AACA,UAAM,cAAc,KAAK,eAAe,kBAAkB,IAAI;AAC9D,QAAI,WAAW,gBAAgB,QAAQ,WAAW,eAAe,GAAG;AAClE,YAAM,IAAI,WAAW,yFAAyF,WAAW,gBAAgB;AAAA,IAC3I;AACA,UAAM,WAAW,WAAW;AAC5B,UAAM,uBAAuB;AAAA,MAC3B,KAAK,WAAW;AAAA,MAChB,KAAK,WAAW;AAAA,MAChB;AAAA,MACA,KAAK;AAAA,IACP;AACA,SAAK,kBAAkB,KAAK,UAAU,oBAAoB,sBAAsB,MAAM,KAAK,sBAAsB,KAAK,sBAAsB,MAAM,KAAK,mBAAmB;AAC1K,QAAI,KAAK,SAAS;AAChB,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,WAAW,KAAK,eAAe,GAAG,MAAM,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IACnJ,OAAO;AACL,WAAK,OAAO;AAAA,IACd;AACA,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS,oBAAoB,MAAM;AACnC,UAAI,UAAU,iBAAiB,QAAQ,KAAK,gBAAgB,KAAK,GAAG,KAAK,SAAS,KAAK,SAAS,KAAK,YAAY,IAAI;AACrH,UAAI,KAAK,SAAS;AAChB,kBAAU,QAAQ,SAAS,KAAK,KAAK,KAAK,GAAG,KAAK,UAAU;AAAA,MAC9D;AACA,UAAI,KAAK,cAAc,MAAM;AAC3B,kBAAU,KAAK,WAAW,MAAM,OAAO;AAAA,MACzC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,OAAO,KAAK,eAAe,kBAAkB,WAAW,KAAK,WAAW;AAC9E,UAAM,OAAO,KAAK,eAAe,kBAAkB,WAAW,KAAK,WAAW;AAC9E,UAAM,aAAa,KAAK,eAAe,kBAAkB,WAAW,KAAK,KAAK,kBAAkB,WAAW,KAAK,KAAK;AACrH,UAAM,UAAU,iBAAiB,MAAM,KAAK,WAAW,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AACxF,UAAM,UAAU,iBAAiB,MAAM,KAAK,WAAW,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AACxF,QAAI,KAAK,eAAe,iBAAiB;AACvC,aAAO,CAAC,WAAW,IAAI,YAAY,SAAS,OAAO;AAAA,IACrD,OAAO;AACL,aAAO,CAAC,WAAW,IAAI,SAAS,SAAS,UAAU;AAAA,IACrD;AAAA,EACF;AAAA,EACA,YAAY;AACV,UAAMb,UAAS,MAAM,UAAU;AAC/B,IAAAA,QAAO,qBAAqB,KAAK;AACjC,IAAAA,QAAO,0BAA0B,qBAAqB,KAAK,oBAAoB;AAC/E,IAAAA,QAAO,0BAA0B,qBAAqB,KAAK,oBAAoB;AAC/E,IAAAA,QAAO,yBAAyB,oBAAoB,KAAK,oBAAoB;AAC7E,WAAOA;AAAA,EACT;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AAGnD,SAAS,gBAAgB,QAAQ,cAAcgB,YAAW,cAAc;AACtE,MAAI,MAAM,QAAQ,MAAM,GAAG;AACzB,QAAI,gBAAgB,QAAQA,cAAa,MAAM;AAC7C,YAAM,IAAI,WAAW,+EAA+E;AAAA,IACtG;AACA,QAAI,gBAAgB,MAAM;AACxB,MAAAA,aAAY,OAAO,MAAM,OAAO,SAAS,cAAc,OAAO,MAAM;AACpE,eAAS,OAAO,MAAM,GAAG,OAAO,SAAS,YAAY;AAAA,IACvD;AACA,QAAI,OAAO,SAAS,GAAG;AACrB,qBAAe,OAAO,MAAM,GAAG,OAAO,MAAM;AAAA,IAC9C;AACA,aAAS,OAAO;AAAA,EAClB;AACA,WAAS,aAAa,GAAG;AACvB,QAAI,KAAK,QAAQ,MAAM,QAAQ,CAAC,GAAG;AACjC,aAAO;AAAA,IACT,OAAO;AACL,aAAO,CAAC,CAAC;AAAA,IACX;AAAA,EACF;AACA,iBAAe,aAAa,YAAY;AACxC,EAAAA,aAAY,aAAaA,UAAS;AAClC,SAAO,EAAE,QAAQ,cAAc,WAAAA,WAAU;AAC3C;AACA,SAAS,IAAI,cAAc,QAAQ,eAAe,cAAc,OAAOzB,OAAMyB,YAAW,SAAS,OAAO,qBAAqB,OAAO;AAClI,SAAO,KAAK,MAAM;AAChB,UAAM,OAAO,OAAO,MAAM;AAC1B,QAAI,OAAO,GAAG;AACZ,YAAM,IAAI,WAAW,uCAAuC,QAAQ;AAAA,IACtE;AACA,UAAM,OAAO,CAAC,GAAG,CAAC,EAAE,OAAO,OAAO,GAAG,IAAI,CAAC;AAC1C,aAAS,UAAU,QAAQ,IAAI;AAC/B,QAAIA,cAAa,MAAM;AACrB,YAAM,IAAI,oBAAoB,gFAAgF;AAAA,IAChH;AACA,QAAI,QAAQ;AACV,cAAQ,KAAK,mGAAmG;AAAA,IAClH;AACA,QAAIzB,SAAQ,MAAM;AAChB,MAAAA,QAAO,KAAK,KAAKA,OAAM,MAAM,GAAG,SAAS;AACzC,UAAIA,MAAK,SAAS,OAAO,GAAG;AAC1B,QAAAA,QAAO,WAAWA,OAAM,EAAE;AAAA,MAC5B;AACA,MAAAA,QAAO,UAAUA,OAAM,IAAI;AAAA,IAC7B;AACA,QAAI,aAAa;AACf,eAAS,QAAQ,QAAQ,CAAC;AAC1B,UAAIA,SAAQ,MAAM;AAChB,QAAAA,QAAO,QAAQA,OAAM,CAAC;AAAA,MACxB;AAAA,IACF;AACA,UAAM,iBAAiB,CAAC;AACxB,QAAI;AACJ,QAAI,SAAS;AACb,UAAM,YAAY,OAAO,MAAM;AAC/B,UAAM,gBAAgB,QAAQ,MAAM;AACpC,QAAI;AACJ,QAAIA,SAAQ,MAAM;AAChB,qBAAe,QAAQA,KAAI;AAAA,IAC7B;AACA,aAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,YAAM,eAAe,cAAc;AACnC,YAAM,cAAc,KAAK,MAAM,aAAa,cAAc,MAAM,CAAC;AACjE,UAAIA,SAAQ,MAAM;AAChB,qBAAa,YAAY;AACzB,iBAAS,YAAY;AAAA,MACvB,OAAO;AACL,cAAM,gBAAgB,KAAK,MAAM;AAC/B,gBAAM,WAAW,aAAa;AAC9B,gBAAM,cAAc,IAAI,SAAS,QAAQ,GAAG,QAAQ;AACpD,gBAAM,SAAS,KAAK,IAAI,YAAY,IAAI,QAAQ,GAAG,IAAI,OAAO,IAAI,WAAW,CAAC;AAC9E,gBAAM,YAAY,OAAO,IAAI,CAAC,OAAO,OAAO;AAC1C,mBAAO,KAAK,IAAI,YAAY,GAAG,KAAK,QAAQ,GAAG,IAAI,OAAO,WAAW,CAAC;AAAA,UACxE,CAAC;AACD,iBAAO,EAAE,QAAQ,UAAU;AAAA,QAC7B,CAAC;AACD,qBAAa,cAAc;AAC3B,iBAAS,cAAc;AAAA,MACzB;AACA,UAAI,oBAAoB;AACtB,uBAAe,KAAK,UAAU;AAAA,MAChC;AAAA,IACF;AACA,QAAI;AACJ,QAAI,oBAAoB;AACtB,YAAM,OAAO;AACb,gBAAU,MAAM,gBAAgB,IAAI;AAAA,IACtC;AACA,WAAO,CAAC,YAAY,SAAS,MAAM;AAAA,EACrC,CAAC;AACH;AACA,IAAI,MAAM,cAAc,MAAM;AAAA,EAC5B,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,QAAI;AACJ,QAAI,KAAK,QAAQ,MAAM;AACrB,YAAM,IAAI,WAAW,sDAAsD;AAAA,IAC7E,WAAW,MAAM,QAAQ,KAAK,IAAI,GAAG;AACnC,aAAO,IAAI,gBAAgB,EAAE,OAAO,KAAK,KAAK,CAAC;AAAA,IACjD,OAAO;AACL,aAAO,KAAK;AAAA,IACd;AACA,QAAI,KAAK,aAAa,MAAM;AAC1B,YAAM,IAAI,WAAW,mGAAmG;AAAA,IAC1H;AACA,SAAK,OAAO;AACZ,SAAK,kBAAkB,KAAK,mBAAmB,OAAO,QAAQ,KAAK;AACnE,SAAK,cAAc,KAAK,eAAe,OAAO,QAAQ,KAAK;AAC3D,SAAK,cAAc,KAAK,eAAe,OAAO,QAAQ,KAAK;AAC3D,SAAK,YAAY,KAAK,YAAY,OAAO,QAAQ,KAAK;AACtD,SAAK,SAAS,KAAK,UAAU,OAAO,QAAQ,KAAK;AACjD,SAAK,kBAAkB;AACvB,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAC5C,SAAK,YAAY;AACjB,SAAK,UAAU;AACf,SAAK,eAAe;AACpB,SAAK,aAAa,CAAC;AAAA,EACrB;AAAA,EACA,YAAY;AACV,QAAI,KAAK,WAAW,MAAM;AACxB,YAAM,YAAY,MAAM,QAAQ,KAAK,KAAK,SAAS,IAAI,KAAK,KAAK,UAAU,SAAS;AACpF,aAAO,OAAO,GAAG,SAAS,EAAE,IAAI,CAAC,MAAM,IAAI;AAAA,IAC7C,OAAO;AACL,aAAO,KAAK;AAAA,IACd;AAAA,EACF;AAAA,EACA,UAAU,QAAQ;AAChB,SAAK,UAAU;AAAA,EACjB;AAAA,EACA,mBAAmB,YAAY;AAC7B,QAAI,gBAAgB,UAAU,GAAG;AAC/B,mBAAa,WAAW;AAAA,IAC1B;AACA,iBAAa;AACb,QAAI,YAAY,KAAK,KAAK;AAC1B,QAAI,CAAC,MAAM,QAAQ,SAAS,GAAG;AAC7B,kBAAY,CAAC,SAAS;AAAA,IACxB;AACA,UAAM,YAAY,UAAU;AAC5B,QAAI;AACJ,QAAI,KAAK,iBAAiB;AACxB,oBAAc,CAAC,WAAW,IAAI,WAAW,IAAI,SAAS;AAAA,IACxD,OAAO;AACL,oBAAc,CAAC,WAAW,IAAI,SAAS;AAAA,IACzC;AACA,QAAI,KAAK,aAAa;AACpB,YAAM,aAAa,CAAC;AACpB,iBAAW,OAAO,WAAW;AAC3B,mBAAW,KAAK,CAAC,WAAW,IAAI,GAAG,CAAC;AAAA,MACtC;AACA,aAAO,CAAC,WAAW,EAAE,OAAO,UAAU;AAAA,IACxC,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,YAAY,QAAQA,OAAM;AACxB,WAAO,KAAK,MAAM;AAChB,UAAI,MAAM,QAAQA,KAAI,GAAG;AACvB,QAAAA,QAAOA,MAAK;AAAA,MACd;AACA,YAAM,aAAa,KAAK,kBAAkBA,QAAO;AACjD,UAAI,KAAK,aAAa;AACpB,cAAM,YAAY,KAAK,OAAO,IAAI,CAAC,OAAO,IAAI;AAC9C,eAAO,CAAC,UAAU,EAAE,OAAO,SAAS;AAAA,MACtC,OAAO;AACL,eAAO;AAAA,MACT;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,IAAI,SAAS;AACX,QAAI,KAAK,WAAW,MAAM;AACxB,YAAM,YAAY,MAAM,QAAQ,KAAK,KAAK,SAAS,IAAI,KAAK,KAAK,UAAU,SAAS;AACpF,YAAM,SAAS,CAAC;AAChB,eAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,eAAO,KAAK,IAAI;AAAA,MAClB;AACA,aAAO;AAAA,IACT,OAAO;AACL,aAAO,KAAK;AAAA,IACd;AAAA,EACF;AAAA,EACA,IAAI,OAAO,IAAI;AACb,SAAK,UAAU;AAAA,EACjB;AAAA,EACA,MAAM,YAAY;AAChB,UAAM,gBAAgB;AACtB,QAAI,KAAK,gBAAgB,MAAM;AAC7B,YAAM,IAAI,oBAAoB,kDAAkD;AAAA,IAClF;AACA,QAAI,gBAAgB,UAAU,GAAG;AAC/B,mBAAa,WAAW;AAAA,IAC1B;AACA,iBAAa;AACb,UAAM,YAAY,KAAK,WAAW,WAAW,KAAK;AAClD,UAAM,WAAW,WAAW,MAAM,CAAC;AACnC,SAAK,UAAU,KAAK,IAAI,UAAU,EAAE,OAAO,CAAC,WAAW,MAAM,GAAG,QAAQ,EAAE,CAAC;AAC3E,UAAM,iBAAiB,CAAC,WAAW,EAAE,EAAE,OAAO,WAAW,MAAM,CAAC,CAAC;AACjE,QAAI,iBAAiB,MAAM;AACzB,YAAM,IAAI,oBAAoB,kDAAkD;AAAA,IAClF,OAAO;AACL,WAAK,KAAK,MAAM,cAAc;AAAA,IAChC;AACA,QAAI;AACJ,QAAI,MAAM,QAAQ,KAAK,KAAK,SAAS,GAAG;AACtC,kBAAY,KAAK,KAAK;AAAA,IACxB,OAAO;AACL,kBAAY,CAAC,KAAK,KAAK,SAAS;AAAA,IAClC;AACA,QAAI,KAAK,aAAa,MAAM;AAC1B,UAAI,CAAC,aAAa,YAAY,KAAK,UAAU,IAAI,CAAC,SAAS,KAAK,MAAM,KAAK,MAAM,SAAS,EAAE,GAAG,SAAS,GAAG;AACzG,cAAM,IAAI,WAAW,6FAA6F,KAAK,wCAAwC,KAAK,KAAK,WAAW;AAAA,MACtL;AAAA,IACF,OAAO;AACL,WAAK,YAAY,UAAU,IAAI,CAAC,QAAQ,IAAI,UAAU,EAAE,OAAO,CAAC,MAAM,GAAG,EAAE,CAAC,CAAC;AAAA,IAC/E;AACA,QAAI,KAAK,UAAU;AACjB,WAAK,YAAY;AAAA,IACnB;AAAA,EACF;AAAA,EACA,YAAY,QAAQ,WAAW,OAAO;AACpC,SAAK,MAAM;AACT,UAAI,CAAC,KAAK,UAAU;AAClB,cAAM,IAAI,eAAe,iEAAiE;AAAA,MAC5F;AACA,YAAM,YAAY,KAAK,UAAU,GAAG,MAAM;AAC1C,UAAI,aAAa,MAAM;AACrB,cAAM,IAAI,WAAW,uUAAuU;AAAA,MAC9V;AACA,UAAI,KAAK,WAAW,MAAM;AACxB,YAAI,MAAM,QAAQ,KAAK,KAAK,SAAS,GAAG;AACtC,eAAK,UAAU,KAAK,KAAK,UAAU,IAAI,CAAC,QAAQ,MAAM,CAAC,WAAW,GAAG,CAAC,CAAC;AAAA,QACzE,OAAO;AACL,eAAK,UAAU,CAAC,MAAM,CAAC,WAAW,KAAK,KAAK,SAAS,CAAC,CAAC;AAAA,QACzD;AAAA,MACF,WAAW,UAAU,MAAM;AACzB,gBAAQ,KAAK,OAAO;AACpB,YAAI,KAAK,cAAc,MAAM;AAC3B,kBAAQ,KAAK,UAAU;AACvB,eAAK,aAAa,CAAC;AAAA,QACrB;AACA,YAAI,MAAM,QAAQ,KAAK,KAAK,SAAS,GAAG;AACtC,eAAK,UAAU,KAAK,KAAK,UAAU,IAAI,CAAC,QAAQ,MAAM,CAAC,WAAW,GAAG,CAAC,CAAC;AAAA,QACzE,OAAO;AACL,eAAK,QAAQ,KAAK,MAAM,CAAC,WAAW,KAAK,KAAK,SAAS,CAAC;AAAA,QAC1D;AAAA,MACF,OAAO;AACL,YAAI,CAAC,MAAM,QAAQ,MAAM,GAAG;AAC1B,mBAAS,CAAC,MAAM;AAAA,QAClB;AACA,YAAI,OAAO,WAAW,KAAK,QAAQ,QAAQ;AACzC,gBAAM,IAAI,WAAW,SAAS,KAAK,gBAAgB,KAAK,QAAQ,oCAAoC,OAAO,0CAA0C,QAAQ;AAAA,QAC/J;AACA,YAAI,aAAa,MAAM;AACrB,eAAK,WAAW,KAAK,KAAK,QAAQ,MAAM,CAAC;AAAA,QAC3C,OAAO;AACL,kBAAQ,KAAK,OAAO;AAAA,QACtB;AACA,iBAASI,SAAQ,GAAGA,SAAQ,KAAK,QAAQ,QAAQ,EAAEA,QAAO;AACxD,gBAAM,QAAQ,OAAOA;AACrB,gBAAM,MAAM,MAAM,QAAQ,KAAK,KAAK,SAAS,IAAI,KAAK,KAAK,UAAUA,UAAS,KAAK,KAAK;AACxF,gBAAM,gBAAgB,CAAC,WAAW,GAAG;AACrC,cAAI,CAAC,aAAa,YAAY,MAAM,OAAO,aAAa,GAAG;AACzD,kBAAM,IAAI,WAAW,SAASA,qCAAoC,KAAK,wBAAwB,iCAAiC,MAAM,OAAO;AAAA,UAC/I;AACA,eAAK,QAAQA,UAAS;AAAA,QACxB;AAAA,MACF;AACA,WAAK,UAAU,KAAK,QAAQ,IAAI,CAAC,UAAU,KAAK,MAAM,MAAM,CAAC,CAAC;AAAA,IAChE,CAAC;AAAA,EACH;AAAA,EACA,MAAM,QAAQ,QAAQ;AACpB,QAAI,eAAe,UAAU,OAAO,OAAO,OAAO;AAClD,QAAIqB,aAAY,UAAU,OAAO,OAAO,OAAO;AAC/C,QAAI,UAAU,MAAM;AAClB,eAAS,CAAC;AAAA,IACZ;AACA,UAAM,eAAe,gBAAgB,QAAQ,cAAcA,YAAW,KAAK,YAAY;AACvF,aAAS,aAAa;AACtB,mBAAe,aAAa;AAC5B,IAAAA,aAAY,aAAa;AACzB,QAAI,mBAAmB,CAAC;AACxB,QAAI,kBAAkB,CAAC;AACvB,QAAI,gBAAgB,MAAM;AACxB,aAAO,kBAAkB;AACzB,yBAAmB,iBAAiB,OAAO,YAAY;AACvD,WAAK,YAAY,CAAC;AAClB,iBAAW,SAAS,cAAc;AAChC,aAAK,UAAU,KAAK,IAAI,UAAU,EAAE,OAAO,MAAM,MAAM,CAAC,CAAC;AAAA,MAC3D;AACA,wBAAkB,gBAAgB,OAAO,KAAK,SAAS;AAAA,IACzD;AACA,QAAIA,cAAa,MAAM;AACrB,aAAO,eAAeA;AACtB,yBAAmB,iBAAiB,OAAOA,UAAS;AACpD,WAAK,eAAeA,WAAU;AAAA,IAChC;AACA,UAAM,WAAW,iBAAiB,cAAc;AAChD,QAAI,UAAU;AACZ,YAAM,YAAY,CAAC,MAAM,EAAE,OAAO,gBAAgB;AAClD,YAAM,gBAAgB,KAAK,UAAU,OAAO,eAAe;AAC3D,YAAM,oBAAoB,KAAK;AAC/B,WAAK,YAAY;AACjB,YAAM,SAAS,MAAM,MAAM,WAAW,MAAM;AAC5C,WAAK,YAAY;AACjB,aAAO;AAAA,IACT,OAAO;AACL,aAAO,MAAM,MAAM,QAAQ,MAAM;AAAA,IACnC;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAMzB,QAAO,UAAU,OAAO,OAAO,OAAO;AAC5C,YAAM,WAAW,UAAU,OAAO,OAAO,OAAO;AAChD,UAAI,eAAe,UAAU,OAAO,OAAO,OAAO;AAClD,eAAS,oBAAoB,MAAM;AACnC,UAAI,gBAAgB,MAAM;AACxB,YAAI,KAAK,UAAU;AACjB,yBAAe,KAAK;AAAA,QACtB,OAAO;AACL,yBAAe,KAAK,gBAAgB,MAAM;AAAA,QAC5C;AAAA,MACF;AACA,YAAM,YAAY,MAAM,QAAQ,KAAK,KAAK,SAAS,IAAI,KAAK,KAAK,UAAU,SAAS;AACpF,UAAI,aAAa,WAAW,WAAW;AACrC,cAAM,IAAI,WAAW,iBAAiB,qCAAqC,aAAa,0BAA0B;AAAA,MACpH;AACA,UAAI,KAAK,QAAQ;AACf,gBAAQ,KAAK,kEAAkE;AAAA,MACjF;AACA,YAAM,iBAAiB,EAAE,SAAS;AAClC,YAAM,QAAQ,CAAC,SAAS,YAAY;AAClC,cAAM,WAAW,KAAK,KAAK,KAAK,CAAC,OAAO,EAAE,OAAO,OAAO,GAAG,cAAc;AACzE,eAAO,CAAC,SAAS,IAAI,SAAS,MAAM,CAAC,CAAC;AAAA,MACxC;AACA,YAAM,aAAa,IAAI,OAAO,QAAQ,cAAc,KAAK,aAAaA,OAAM,MAAM,KAAK,QAAQ,KAAK,eAAe;AACnH,YAAM,aAAa,WAAW;AAC9B,YAAM,UAAU,WAAW;AAC3B,YAAM,SAAS,WAAW;AAC1B,UAAI,KAAK,UAAU;AACjB,aAAK,YAAY,QAAQ,QAAQ;AAAA,MACnC;AACA,YAAM,SAAS,KAAK,kBAAkB,UAAU;AAChD,UAAI,KAAK,aAAa;AACpB,eAAO,CAAC,MAAM,EAAE,OAAO,MAAM;AAAA,MAC/B,OAAO;AACL,eAAO;AAAA,MACT;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,gBAAgB,QAAQ;AACtB,WAAO,KAAK,MAAM;AAChB,UAAI,eAAe,MAAM,OAAO,KAAK;AACrC,qBAAe,KAAK,cAAc,CAAC,GAAG,CAAC,CAAC;AACxC,qBAAe,YAAY,YAAY;AACvC,UAAI,MAAM,QAAQ,KAAK,KAAK,SAAS,GAAG;AACtC,eAAO,KAAK,KAAK,UAAU,IAAI,CAAC,QAAQ,MAAM,IAAI,MAAM,cAAc,CAAC,GAAG,GAAG,CAAC,IAAI,YAAY;AAAA,MAChG,OAAO;AACL,eAAO,KAAK,KAAK,YAAY,IAAI,CAAC,MAAM,cAAc,CAAC,GAAG,KAAK,KAAK,SAAS,CAAC,CAAC,IAAI,CAAC,YAAY;AAAA,MAClG;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,IAAI,mBAAmB;AACrB,QAAI,CAAC,KAAK,WAAW;AACnB,aAAO,CAAC;AAAA,IACV;AACA,WAAO,KAAK,KAAK;AAAA,EACnB;AAAA,EACA,IAAI,sBAAsB;AACxB,QAAI,CAAC,KAAK,WAAW;AACnB,aAAO,KAAK,KAAK;AAAA,IACnB;AACA,WAAO,KAAK,KAAK;AAAA,EACnB;AAAA,EACA,6BAA6B,OAAO;AAClC,UAAM,6BAA6B,KAAK;AACxC,QAAI,KAAK,QAAQ,MAAM;AACrB,WAAK,KAAK,6BAA6B,KAAK;AAAA,IAC9C;AAAA,EACF;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMS,UAAS;AAAA,MACb,iBAAiB,KAAK;AAAA,MACtB,aAAa,KAAK;AAAA,MAClB,aAAa,KAAK;AAAA,MAClB,UAAU,KAAK;AAAA,MACf,QAAQ,KAAK;AAAA,IACf;AACA,QAAI,KAAK,gBAAgB,MAAM;AAC7B,MAAAA,QAAO,kBAAkB,KAAK;AAAA,IAChC;AACA,UAAM,aAAa,KAAK,KAAK,UAAU;AACvC,QAAI,KAAK,aAAa,MAAM,IAAI,WAAW;AACzC,MAAAA,QAAO,UAAU;AAAA,QACf,aAAa,KAAK,KAAK,aAAa;AAAA,QACpC,UAAU;AAAA,MACZ;AAAA,IACF;AACA,WAAO,OAAO,OAAO,CAAC,GAAG,YAAY,YAAYA,OAAM;AAAA,EACzD;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ,gBAAgB,CAAC,GAAG;AACjD,UAAM,aAAaA,QAAO;AAC1B,UAAM,OAAO,YAAY,YAAY,aAAa;AAClD,WAAO,IAAI,IAAI,OAAO,OAAOA,SAAQ,EAAE,KAAK,CAAC,CAAC;AAAA,EAChD;AACF;AACA,IAAI,YAAY;AAChB,sBAAsB,cAAc,GAAG;AACvC,IAAI,UAAU,cAAc,MAAM;AAClC;AACA,IAAI,gBAAgB,cAAc,QAAQ;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,qBAAqB;AAC1B,SAAK,6BAA6B;AAClC,SAAK,gCAAgC;AACrC,SAAK,2BAA2B;AAChC,SAAK,QAAQ,KAAK;AAClB,0BAAsB,KAAK,OAAO,OAAO;AACzC,SAAK,aAAa,cAAc,KAAK,cAAc,OAAO,KAAK,qBAAqB,KAAK,UAAU;AACnG,SAAK,UAAU,KAAK,WAAW,OAAO,OAAO,KAAK;AAClD,SAAK,oBAAoB,eAAe,KAAK,qBAAqB,KAAK,0BAA0B;AACjG,SAAK,uBAAuB,eAAe,KAAK,wBAAwB,KAAK,6BAA6B;AAC1G,SAAK,kBAAkB,eAAe,KAAK,mBAAmB,KAAK,wBAAwB;AAC3F,SAAK,oBAAoB,eAAe,KAAK,iBAAiB;AAC9D,SAAK,uBAAuB,eAAe,KAAK,oBAAoB;AACpE,SAAK,kBAAkB,eAAe,KAAK,eAAe;AAC1D,SAAK,mBAAmB,cAAc,KAAK,gBAAgB;AAC3D,SAAK,sBAAsB,cAAc,KAAK,mBAAmB;AACjE,SAAK,iBAAiB,cAAc,KAAK,cAAc;AACvD,SAAK,UAAU,KAAK,CAAC,GAAG,KAAK,CAAC,GAAG,KAAK,WAAW,OAAO,IAAI,KAAK,OAAO,CAAC,CAAC,CAAC;AAC3E,SAAK,mBAAmB,KAAK;AAAA,MAC3B;AAAA,MACA,KAAK,CAAC,GAAG,KAAK,oBAAoB,OAAO,IAAI,KAAK,gBAAgB,CAAC;AAAA,IACrE,CAAC;AACD,SAAK,cAAc,KAAK;AACxB,SAAK,YAAY,KAAK;AACtB,SAAK,cAAc;AACnB,SAAK,uBAAuB;AAAA,EAC9B;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,SAAK,SAAS,KAAK,UAAU,UAAU,CAAC,WAAW,WAAW,SAAS,IAAI,KAAK,KAAK,GAAG,MAAM,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AACzK,SAAK,kBAAkB,KAAK,UAAU,oBAAoB,CAAC,KAAK,OAAO,KAAK,KAAK,GAAG,MAAM,KAAK,sBAAsB,KAAK,sBAAsB,MAAM,KAAK,mBAAmB;AAC9K,QAAI,KAAK,SAAS;AAChB,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,KAAK,GAAG,MAAM,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IAC9H,OAAO;AACL,WAAK,OAAO;AAAA,IACd;AACA,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS;AACT,UAAI,OAAO,WAAW,GAAG;AACvB,cAAM,IAAI,WAAW,8CAA8C,OAAO,SAAS;AAAA,MACrF;AACA,UAAI,aAAa,OAAO;AACxB,eAAS,OAAO;AAChB,YAAM,WAAW,OAAO,eAAe,OAAO,QAAQ,OAAO;AAC7D,UAAI,IAAI,KAAK,WAAW,KAAK,UAAU,KAAK,KAAK,eAAe,MAAM;AACpE,aAAK,cAAc,oBAAoB;AAAA,UACrC,MAAM,MAAM,SAAS,MAAM;AAAA,UAC3B,MAAM,KAAK;AAAA,UACX;AAAA,UACA,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,UAAI,IAAI,KAAK,oBAAoB,KAAK,mBAAmB,KAAK,KAAK,wBAAwB,MAAM;AAC/F,aAAK,uBAAuB,oBAAoB;AAAA,UAC9C,MAAM,MAAM,SAAS,UAAU;AAAA,UAC/B,MAAM,KAAK;AAAA,UACX;AAAA,UACA,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,UAAI;AACJ,YAAM,SAAS,KAAK;AACpB,YAAM,YAAY,KAAK;AACvB,UAAI,UAAU,MAAM;AAClB,YAAI,KAAK,IAAI,QAAQ,MAAM,GAAG,KAAK,OAAO,KAAK,CAAC;AAAA,MAClD,OAAO;AACL,YAAI,KAAK,QAAQ,KAAK,OAAO,KAAK,CAAC;AAAA,MACrC;AACA,UAAI,KAAK,QAAQ,MAAM;AACrB,YAAI,QAAQ,GAAG,KAAK,KAAK,KAAK,CAAC;AAAA,MACjC;AACA,UAAI,aAAa,MAAM;AACrB,qBAAa,IAAI,YAAY,SAAS;AAAA,MACxC;AACA,UAAI,SAAS,KAAK,GAAG,KAAK,YAAY,KAAK,gBAAgB,KAAK,CAAC,CAAC;AAClE,UAAI,KAAK,cAAc,MAAM;AAC3B,iBAAS,KAAK,WAAW,MAAM,MAAM;AAAA,MACvC;AACA,aAAO,CAAC,QAAQ,MAAM;AAAA,IACxB,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMA,UAAS;AAAA,MACb,OAAO,KAAK;AAAA,MACZ,YAAY,oBAAoB,KAAK,UAAU;AAAA,MAC/C,SAAS,KAAK;AAAA,MACd,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,sBAAsB,qBAAqB,KAAK,oBAAoB;AAAA,MACpE,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,sBAAsB,qBAAqB,KAAK,oBAAoB;AAAA,MACpE,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,qBAAqB,qBAAqB,KAAK,mBAAmB;AAAA,MAClE,kBAAkB,oBAAoB,KAAK,gBAAgB;AAAA,MAC3D,qBAAqB,oBAAoB,KAAK,mBAAmB;AAAA,MACjE,gBAAgB,oBAAoB,KAAK,cAAc;AAAA,MACvD,SAAS,KAAK;AAAA,MACd,kBAAkB,KAAK;AAAA,IACzB;AACA,WAAO,OAAO,OAAO,CAAC,GAAG,YAAYA,OAAM;AAAA,EAC7C;AACF;AACA,cAAc,YAAY;AAC1B,sBAAsB,cAAc,aAAa;AACjD,IAAI,YAAY,cAAc,IAAI;AAAA,EAChC,YAAY,MAAM;AAChB,SAAK,OAAO,IAAI,cAAc,IAAI;AAClC,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,KAAK,KAAK,eAAe,MAAM;AACjC,gBAAQ,KAAK,KAAK,WAAW;AAC7B,aAAK,KAAK,cAAc;AAAA,MAC1B;AACA,UAAI,KAAK,KAAK,wBAAwB,MAAM;AAC1C,gBAAQ,KAAK,KAAK,oBAAoB;AACtC,aAAK,KAAK,uBAAuB;AAAA,MACnC;AACA,YAAMT,QAAO,UAAU,OAAO,OAAO,OAAO;AAC5C,YAAM,WAAW,UAAU,OAAO,OAAO,OAAO;AAChD,YAAM,eAAe,UAAU,OAAO,OAAO,OAAO;AACpD,aAAO,MAAM,KAAK,QAAQ,EAAE,MAAAA,OAAM,UAAU,aAAa,CAAC;AAAA,IAC5D,CAAC;AAAA,EACH;AAAA,EACA,OAAO,WAAW,KAAKS,SAAQ;AAC7B,WAAO,IAAI,IAAIA,OAAM;AAAA,EACvB;AACF;AACA,UAAU,YAAY;AACtB,sBAAsB,cAAc,SAAS;AAC7C,IAAI,UAAU,cAAc,QAAQ;AAAA,EAClC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,qBAAqB;AAC1B,SAAK,+BAA+B;AACpC,SAAK,6BAA6B;AAClC,SAAK,gCAAgC;AACrC,SAAK,2BAA2B;AAChC,QAAI,KAAK,YAAY;AACnB,YAAM,IAAI,WAAW,6DAA6D;AAAA,IACpF;AACA,SAAK,QAAQ,KAAK;AAClB,0BAAsB,KAAK,OAAO,OAAO;AACzC,SAAK,aAAa,cAAc,KAAK,eAAe,SAAS,KAAK,qBAAqB,KAAK,UAAU;AACtG,SAAK,sBAAsB,cAAc,KAAK,wBAAwB,SAAS,KAAK,+BAA+B,KAAK,mBAAmB;AAC3I,SAAK,UAAU,KAAK,WAAW,OAAO,OAAO,KAAK;AAClD,SAAK,oBAAoB,eAAe,KAAK,qBAAqB,KAAK,0BAA0B;AACjG,SAAK,uBAAuB,eAAe,KAAK,wBAAwB,KAAK,6BAA6B;AAC1G,SAAK,kBAAkB,eAAe,KAAK,mBAAmB,KAAK,wBAAwB;AAC3F,SAAK,oBAAoB,eAAe,KAAK,iBAAiB;AAC9D,SAAK,uBAAuB,eAAe,KAAK,oBAAoB;AACpE,SAAK,kBAAkB,eAAe,KAAK,eAAe;AAC1D,SAAK,mBAAmB,cAAc,KAAK,gBAAgB;AAC3D,SAAK,sBAAsB,cAAc,KAAK,mBAAmB;AACjE,SAAK,iBAAiB,cAAc,KAAK,cAAc;AACvD,SAAK,UAAU,KAAK,CAAC,GAAG,KAAK,CAAC,GAAG,KAAK,WAAW,OAAO,IAAI,KAAK,OAAO,CAAC,CAAC,CAAC;AAC3E,SAAK,mBAAmB,KAAK;AAAA,MAC3B;AAAA,MACA,KAAK,CAAC,GAAG,KAAK,oBAAoB,OAAO,IAAI,KAAK,gBAAgB,CAAC;AAAA,IACrE,CAAC;AACD,SAAK,cAAc,KAAK;AACxB,SAAK,iBAAiB,KAAK;AAC3B,SAAK,YAAY,KAAK;AACtB,SAAK,cAAc;AACnB,SAAK,uBAAuB;AAAA,EAC9B;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,WAAW,WAAW,WAAW,SAAS;AAChD,SAAK,SAAS,KAAK,UAAU,UAAU,CAAC,UAAU,KAAK,QAAQ,CAAC,GAAG,MAAM,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AACpJ,SAAK,kBAAkB,KAAK,UAAU,oBAAoB,CAAC,KAAK,OAAO,KAAK,QAAQ,CAAC,GAAG,MAAM,KAAK,sBAAsB,KAAK,sBAAsB,MAAM,KAAK,mBAAmB;AAClL,QAAI,KAAK,SAAS;AAChB,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,QAAQ,CAAC,GAAG,MAAM,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IAClI,OAAO;AACL,WAAK,OAAO;AAAA,IACd;AACA,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS;AACT,UAAI,OAAO,WAAW,GAAG;AACvB,cAAM,IAAI,WAAW,uDAAuD,OAAO,SAAS;AAAA,MAC9F;AACA,YAAM,WAAW,OAAO,eAAe,OAAO,QAAQ,OAAO;AAC7D,UAAI,WAAW,OAAO;AACtB,eAAS,OAAO;AAChB,UAAI,IAAI,KAAK,WAAW,KAAK,UAAU,KAAK,KAAK,eAAe,MAAM;AACpE,aAAK,cAAc,oBAAoB;AAAA,UACrC,MAAM,MAAM,SAAS,MAAM;AAAA,UAC3B,MAAM,KAAK;AAAA,UACX;AAAA,UACA,OAAO;AAAA,UACP,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,UAAI,IAAI,KAAK,oBAAoB,KAAK,mBAAmB,KAAK,KAAK,wBAAwB,MAAM;AAC/F,aAAK,uBAAuB,oBAAoB;AAAA,UAC9C,MAAM,MAAM,SAAS,QAAQ;AAAA,UAC7B,MAAM,KAAK;AAAA,UACX;AAAA,UACA,OAAO;AAAA,UACP,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,YAAM,SAAS,KAAK;AACpB,YAAM,YAAY,KAAK;AACvB,UAAI;AACJ,UAAI;AACJ,UAAI;AACJ,UAAI,IAAI,KAAK,WAAW,KAAK,UAAU,GAAG;AACxC,iBAAS,IAAI,QAAQ,OAAO,EAAE;AAAA,MAChC;AACA,UAAI,UAAU,KAAK,QAAQ,KAAK,OAAO,KAAK,CAAC;AAC7C,UAAI,KAAK,SAAS;AAChB,kBAAU,QAAQ,SAAS,KAAK,KAAK,KAAK,CAAC;AAAA,MAC7C;AACA,UAAI,IAAI,KAAK,oBAAoB,KAAK,mBAAmB,GAAG;AAC1D,mBAAW,IAAI,UAAU,UAAU,EAAE;AAAA,MACvC;AACA,YAAM,uBAAuB,KAAK,gBAAgB,KAAK;AACvD,YAAM,CAAC,KAAK,GAAG,IAAI,MAAM,sBAAsB,CAAC,IAAI,KAAK,OAAO,KAAK,KAAK,GAAG,qBAAqB,OAAO,CAAC;AAC1G,YAAM,cAAc,KAAK,UAAU,GAAG;AACtC,YAAM,CAAC,IAAI,IAAI,EAAE,IAAI,MAAM,SAAS,GAAG,QAAQ,OAAO,CAAC;AACvD,YAAM,CAAC,YAAY,UAAU,IAAI,MAAM,aAAa,GAAG,YAAY,OAAO,CAAC;AAC3E,UAAI,KAAK,oBAAoB,MAAM,KAAK,IAAI,UAAU,CAAC;AACvD,WAAK,KAAK,oBAAoB,MAAM,KAAK,IAAI,UAAU,CAAC;AACxD,YAAM,aAAa,KAAK,IAAI,IAAI,QAAQ,GAAG,GAAG;AAC9C,WAAK,KAAK,WAAW,MAAM,KAAK,IAAI,UAAU,CAAC;AAC/C,YAAM,IAAI,KAAK,IAAI,GAAG,QAAQ,GAAG,IAAI,KAAK,GAAG,IAAI,CAAC,CAAC,GAAG,EAAE,CAAC;AACzD,aAAO,CAAC,GAAG,CAAC;AAAA,IACd,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMA,UAAS;AAAA,MACb,OAAO,KAAK;AAAA,MACZ,YAAY,oBAAoB,KAAK,UAAU;AAAA,MAC/C,qBAAqB,oBAAoB,KAAK,mBAAmB;AAAA,MACjE,SAAS,KAAK;AAAA,MACd,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,sBAAsB,qBAAqB,KAAK,oBAAoB;AAAA,MACpE,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,sBAAsB,qBAAqB,KAAK,oBAAoB;AAAA,MACpE,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,qBAAqB,qBAAqB,KAAK,mBAAmB;AAAA,MAClE,kBAAkB,oBAAoB,KAAK,gBAAgB;AAAA,MAC3D,qBAAqB,oBAAoB,KAAK,mBAAmB;AAAA,MACjE,gBAAgB,oBAAoB,KAAK,cAAc;AAAA,MACvD,SAAS,KAAK;AAAA,MACd,kBAAkB,KAAK;AAAA,MACvB,gBAAgB,KAAK;AAAA,MACrB,YAAY;AAAA,IACd;AACA,WAAO,OAAO,OAAO,CAAC,GAAG,YAAYA,OAAM;AAAA,EAC7C;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,MAAM,cAAc,IAAI;AAAA,EAC1B,YAAY,MAAM;AAChB,QAAI,KAAK,mBAAmB,GAAG;AAC7B,cAAQ,KAAK,gHAAgH;AAAA,IAC/H;AACA,SAAK,OAAO,IAAI,QAAQ,IAAI;AAC5B,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,KAAK,KAAK,eAAe,MAAM;AACjC,gBAAQ,KAAK,KAAK,WAAW;AAC7B,aAAK,KAAK,cAAc;AAAA,MAC1B;AACA,UAAI,KAAK,KAAK,wBAAwB,MAAM;AAC1C,gBAAQ,KAAK,KAAK,oBAAoB;AACtC,aAAK,KAAK,uBAAuB;AAAA,MACnC;AACA,YAAMT,QAAO,UAAU,OAAO,OAAO,OAAO;AAC5C,YAAM,WAAW,UAAU,OAAO,OAAO,OAAO;AAChD,YAAM,eAAe,UAAU,OAAO,OAAO,OAAO;AACpD,aAAO,MAAM,KAAK,QAAQ,EAAE,MAAAA,OAAM,UAAU,aAAa,CAAC;AAAA,IAC5D,CAAC;AAAA,EACH;AAAA,EACA,OAAO,WAAW,KAAKS,SAAQ;AAC7B,QAAIA,QAAO,qBAAqB,GAAG;AACjC,MAAAA,QAAO,oBAAoB;AAAA,IAC7B;AACA,WAAO,IAAI,IAAIA,OAAM;AAAA,EACvB;AACF;AACA,IAAI,YAAY;AAChB,sBAAsB,cAAc,GAAG;AACvC,IAAI,WAAW,cAAc,QAAQ;AAAA,EACnC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,qBAAqB;AAC1B,SAAK,+BAA+B;AACpC,SAAK,6BAA6B;AAClC,SAAK,gCAAgC;AACrC,SAAK,2BAA2B;AAChC,SAAK,QAAQ,KAAK;AAClB,0BAAsB,KAAK,OAAO,OAAO;AACzC,SAAK,aAAa,cAAc,KAAK,eAAe,SAAS,KAAK,qBAAqB,KAAK,UAAU;AACtG,SAAK,sBAAsB,cAAc,KAAK,wBAAwB,SAAS,KAAK,+BAA+B,KAAK,mBAAmB;AAC3I,SAAK,UAAU,KAAK,WAAW,OAAO,OAAO,KAAK;AAClD,SAAK,oBAAoB,eAAe,KAAK,qBAAqB,KAAK,0BAA0B;AACjG,SAAK,uBAAuB,eAAe,KAAK,wBAAwB,KAAK,6BAA6B;AAC1G,SAAK,kBAAkB,eAAe,KAAK,mBAAmB,KAAK,wBAAwB;AAC3F,SAAK,iBAAiB,KAAK;AAC3B,SAAK,oBAAoB,eAAe,KAAK,iBAAiB;AAC9D,SAAK,uBAAuB,eAAe,KAAK,oBAAoB;AACpE,SAAK,kBAAkB,eAAe,KAAK,eAAe;AAC1D,SAAK,mBAAmB,cAAc,KAAK,gBAAgB;AAC3D,SAAK,sBAAsB,cAAc,KAAK,mBAAmB;AACjE,SAAK,iBAAiB,cAAc,KAAK,cAAc;AACvD,SAAK,UAAU,KAAK,CAAC,GAAG,KAAK,CAAC,GAAG,KAAK,WAAW,OAAO,IAAI,KAAK,OAAO,CAAC,CAAC,CAAC;AAC3E,SAAK,mBAAmB,KAAK;AAAA,MAC3B;AAAA,MACA,KAAK,CAAC,GAAG,KAAK,oBAAoB,OAAO,IAAI,KAAK,gBAAgB,CAAC;AAAA,IACrE,CAAC;AACD,SAAK,cAAc,KAAK;AACxB,SAAK,iBAAiB,KAAK;AAC3B,SAAK,YAAY,CAAC,KAAK,OAAO,KAAK,KAAK;AACxC,SAAK,cAAc;AACnB,SAAK,uBAAuB;AAAA,EAC9B;AAAA,EACA,MAAM,YAAY;AAChB,QAAI;AACJ,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,WAAW,WAAW,WAAW,SAAS;AAChD,SAAK,SAAS,KAAK,UAAU,UAAU,CAAC,UAAU,KAAK,QAAQ,CAAC,GAAG,MAAM,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AACpJ,SAAK,kBAAkB,KAAK,UAAU,oBAAoB,CAAC,KAAK,OAAO,KAAK,QAAQ,CAAC,GAAG,MAAM,KAAK,sBAAsB,KAAK,sBAAsB,MAAM,KAAK,mBAAmB;AAClL,QAAI;AACJ,QAAI,KAAK,SAAS;AAChB,UAAI,KAAK,gBAAgB;AACvB,cAAM,mBAAmB,KAAK;AAC9B,cAAM,gBAAgB,KAAK;AAC3B,0BAAkB,KAAK,KAAK,MAAM,mBAAmB,YAAY;AAAA,UAC/D,MAAM,OAAO,OAAO;AAClB,kBAAM,KAAK,iBAAiB,MAAM,CAAC,aAAa,CAAC;AACjD,kBAAM,KAAK,IAAI,KAAK,EAAE,MAAM,CAAC,aAAa,CAAC;AAC3C,kBAAM,SAAS,iBAAiB,MAAM,CAAC,gBAAgB,CAAC,CAAC;AACzD,mBAAO,qBAAqB,qBAAqB,IAAI,EAAE,GAAG,MAAM;AAAA,UAClE;AAAA,QACF,GAAG,GAAG,YAAY,cAAc,IAAI;AAAA,MACtC,OAAO;AACL,0BAAkB,KAAK;AAAA,MACzB;AACA,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,QAAQ,CAAC,GAAG,MAAM,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IAC7H,OAAO;AACL,WAAK,OAAO;AAAA,IACd;AACA,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAM,WAAW,OAAO,eAAe,OAAO,QAAQ,OAAO;AAC7D,eAAS;AACT,UAAI,OAAO,WAAW,GAAG;AACvB,cAAM,IAAI,WAAW,wDAAwD,OAAO,SAAS;AAAA,MAC/F;AACA,UAAI,WAAW,OAAO;AACtB,YAAM,WAAW,OAAO;AACxB,eAAS,OAAO;AAChB,UAAI,IAAI,KAAK,WAAW,KAAK,UAAU,KAAK,KAAK,eAAe,MAAM;AACpE,aAAK,cAAc,oBAAoB;AAAA,UACrC,MAAM,MAAM,SAAS,MAAM;AAAA,UAC3B,MAAM,KAAK;AAAA,UACX;AAAA,UACA,OAAO;AAAA,UACP,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,UAAI,IAAI,KAAK,oBAAoB,KAAK,mBAAmB,KAAK,KAAK,wBAAwB,MAAM;AAC/F,aAAK,uBAAuB,oBAAoB;AAAA,UAC9C,MAAM,MAAM,SAAS,QAAQ;AAAA,UAC7B,MAAM,KAAK;AAAA,UACX;AAAA,UACA,OAAO;AAAA,UACP,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,YAAM,SAAS,KAAK;AACpB,YAAM,YAAY,KAAK;AACvB,UAAI;AACJ,UAAI;AACJ,UAAI;AACJ,UAAI;AACJ,UAAI,IAAI,KAAK,WAAW,KAAK,UAAU,GAAG;AACxC,iBAAS,IAAI,QAAQ,OAAO,EAAE;AAAA,MAChC;AACA,UAAI,IAAI,KAAK,QAAQ,KAAK,OAAO,KAAK,CAAC;AACvC,UAAI,IAAI,KAAK,oBAAoB,KAAK,mBAAmB,GAAG;AAC1D,mBAAW,IAAI,UAAU,UAAU,EAAE;AAAA,MACvC;AACA,UAAI,KAAK,GAAG,KAAK,UAAU,KAAK,gBAAgB,KAAK,CAAC,CAAC;AACvD,UAAI,KAAK,SAAS;AAChB,YAAI,QAAQ,GAAG,KAAK,KAAK,KAAK,CAAC;AAAA,MACjC;AACA,YAAM,CAAC,IAAI,IAAI,IAAI,EAAE,IAAI,MAAM,GAAG,GAAG,EAAE,OAAO,CAAC;AAC/C,WAAK,KAAK,oBAAoB,MAAM,EAAE;AACtC,UAAI,KAAK,oBAAoB,MAAM,EAAE;AACrC,UAAI,KAAK,IAAI,GAAG,QAAQ,GAAG,IAAI,IAAI,KAAK,WAAW,MAAM,EAAE,CAAC,CAAC;AAC7D,UAAI,KAAK,oBAAoB,MAAM,EAAE;AACrC,YAAM,IAAI,IAAI,GAAG,KAAK,WAAW,MAAM,CAAC,CAAC;AACzC,aAAO,CAAC,GAAG,GAAG,CAAC;AAAA,IACjB,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMA,UAAS;AAAA,MACb,OAAO,KAAK;AAAA,MACZ,YAAY,oBAAoB,KAAK,UAAU;AAAA,MAC/C,qBAAqB,oBAAoB,KAAK,mBAAmB;AAAA,MACjE,SAAS,KAAK;AAAA,MACd,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,sBAAsB,qBAAqB,KAAK,oBAAoB;AAAA,MACpE,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,gBAAgB,KAAK;AAAA,MACrB,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,sBAAsB,qBAAqB,KAAK,oBAAoB;AAAA,MACpE,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,qBAAqB,qBAAqB,KAAK,mBAAmB;AAAA,MAClE,kBAAkB,oBAAoB,KAAK,gBAAgB;AAAA,MAC3D,qBAAqB,oBAAoB,KAAK,mBAAmB;AAAA,MACjE,gBAAgB,oBAAoB,KAAK,cAAc;AAAA,MACvD,SAAS,KAAK;AAAA,MACd,kBAAkB,KAAK;AAAA,MACvB,gBAAgB,KAAK;AAAA,IACvB;AACA,WAAO,OAAO,OAAO,CAAC,GAAG,YAAYA,OAAM;AAAA,EAC7C;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,OAAO,cAAc,IAAI;AAAA,EAC3B,YAAY,MAAM;AAChB,QAAI,KAAK,mBAAmB,GAAG;AAC7B,cAAQ,KAAK,gHAAgH;AAAA,IAC/H;AACA,SAAK,OAAO,IAAI,SAAS,IAAI;AAC7B,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,KAAK,KAAK,eAAe,MAAM;AACjC,gBAAQ,KAAK,KAAK,WAAW;AAC7B,aAAK,KAAK,cAAc;AAAA,MAC1B;AACA,UAAI,KAAK,KAAK,wBAAwB,MAAM;AAC1C,gBAAQ,KAAK,KAAK,oBAAoB;AACtC,aAAK,KAAK,uBAAuB;AAAA,MACnC;AACA,YAAMT,QAAO,UAAU,OAAO,OAAO,OAAO;AAC5C,YAAM,WAAW,UAAU,OAAO,OAAO,OAAO;AAChD,YAAM,eAAe,UAAU,OAAO,OAAO,OAAO;AACpD,aAAO,MAAM,KAAK,QAAQ,EAAE,MAAAA,OAAM,UAAU,aAAa,CAAC;AAAA,IAC5D,CAAC;AAAA,EACH;AAAA,EACA,OAAO,WAAW,KAAKS,SAAQ;AAC7B,QAAIA,QAAO,qBAAqB,GAAG;AACjC,MAAAA,QAAO,oBAAoB;AAAA,IAC7B;AACA,WAAO,IAAI,IAAIA,OAAM;AAAA,EACvB;AACF;AACA,KAAK,YAAY;AACjB,sBAAsB,cAAc,IAAI;AACxC,IAAI,kBAAkB,cAAc,QAAQ;AAAA,EAC1C,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,QAAQ,KAAK;AAAA,EACpB;AAAA,EACA,IAAI,YAAY;AACd,UAAM,YAAY,CAAC;AACnB,eAAW,QAAQ,KAAK,MAAM,MAAM,EAAE,QAAQ,GAAG;AAC/C,UAAI,MAAM,QAAQ,KAAK,SAAS,GAAG;AACjC,kBAAU,KAAK,GAAG,KAAK,SAAS;AAAA,MAClC,OAAO;AACL,kBAAU,KAAK,KAAK,SAAS;AAAA,MAC/B;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS;AACT,UAAI,SAAS,OAAO,MAAM,CAAC;AAC3B,YAAM,eAAe,CAAC;AACtB,iBAAW,QAAQ,KAAK,MAAM,MAAM,EAAE,QAAQ,GAAG;AAC/C,YAAI,MAAM,QAAQ,KAAK,SAAS,GAAG;AACjC,uBAAa,KAAK,OAAO,OAAO,GAAG,KAAK,UAAU,MAAM,CAAC;AAAA,QAC3D,OAAO;AACL,uBAAa,KAAK,OAAO,OAAO,GAAG,CAAC,CAAC;AAAA,QACvC;AAAA,MACF;AACA,mBAAa,QAAQ;AACrB,YAAM,kBAAkB,CAAC;AACzB,UAAI;AACJ,eAAS,KAAK,GAAG,KAAK,KAAK,MAAM,QAAQ,EAAE,IAAI;AAC7C,cAAM,OAAO,KAAK,MAAM;AACxB,iBAAS,aAAa;AACtB,YAAI,OAAO,GAAG;AACZ,uBAAa,CAAC,OAAO,EAAE,EAAE,OAAO,MAAM;AAAA,QACxC,OAAO;AACL,uBAAa,CAAC,WAAW,EAAE,EAAE,OAAO,MAAM;AAAA,QAC5C;AACA,qBAAa,KAAK,KAAK,YAAY,MAAM;AACzC,wBAAgB,KAAK,WAAW,MAAM,CAAC,CAAC;AAAA,MAC1C;AACA,eAAS,CAAC;AACV,iBAAW,cAAc,gBAAgB,MAAM,EAAE,QAAQ,GAAG;AAC1D,eAAO,KAAK,GAAG,UAAU;AAAA,MAC3B;AACA,aAAO,CAAC,WAAW,EAAE,EAAE,OAAO,MAAM;AAAA,IACtC,CAAC;AAAA,EACH;AAAA,EACA,MAAM,YAAY;AAChB,QAAI,gBAAgB,UAAU,GAAG;AAC/B,mBAAa,WAAW;AAAA,IAC1B;AACA,iBAAa;AACb,QAAI;AACJ,SAAK,MAAM,QAAQ,CAAC,MAAM,OAAO;AAC/B,gBAAU,WAAW,MAAM,MAAM;AAC/B,aAAK,MAAM,UAAU;AACrB,YAAI,MAAM,QAAQ,KAAK,SAAS,GAAG;AACjC,sBAAY,KAAK,UAAU;AAAA,QAC7B,OAAO;AACL,sBAAY,KAAK;AAAA,QACnB;AACA,qBAAa,CAAC,WAAW,IAAI,SAAS;AAAA,MACxC,CAAC;AAAA,IACH,CAAC;AACD,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAM,gBAAgB,CAAC,SAAS;AAC9B,aAAO;AAAA,QACL,aAAa,KAAK,aAAa;AAAA,QAC/B,UAAU,KAAK,UAAU;AAAA,MAC3B;AAAA,IACF;AACA,UAAM,cAAc,KAAK,MAAM,IAAI,aAAa;AAChD,UAAMA,UAAS,EAAE,SAAS,YAAY;AACtC,WAAO,OAAO,OAAO,CAAC,GAAG,YAAYA,OAAM;AAAA,EAC7C;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ,gBAAgB,CAAC,GAAG;AACjD,UAAM,QAAQ,CAAC;AACf,eAAW,cAAcA,QAAO,UAAU;AACxC,YAAM,KAAK,YAAY,YAAY,aAAa,CAAC;AAAA,IACnD;AACA,WAAO,IAAI,IAAI,EAAE,MAAM,CAAC;AAAA,EAC1B;AAAA,EACA,IAAI,mBAAmB;AACrB,QAAI,CAAC,KAAK,WAAW;AACnB,aAAO,CAAC;AAAA,IACV;AACA,UAAM,UAAU,CAAC;AACjB,eAAW,QAAQ,KAAK,OAAO;AAC7B,cAAQ,KAAK,GAAG,KAAK,gBAAgB;AAAA,IACvC;AACA,WAAO;AAAA,EACT;AAAA,EACA,IAAI,sBAAsB;AACxB,UAAM,UAAU,CAAC;AACjB,eAAW,QAAQ,KAAK,OAAO;AAC7B,cAAQ,KAAK,GAAG,KAAK,mBAAmB;AAAA,IAC1C;AACA,QAAI,CAAC,KAAK,WAAW;AACnB,YAAM,mBAAmB,CAAC;AAC1B,iBAAW,QAAQ,KAAK,OAAO;AAC7B,yBAAiB,KAAK,GAAG,KAAK,gBAAgB;AAAA,MAChD;AACA,aAAO,iBAAiB,OAAO,OAAO;AAAA,IACxC;AACA,WAAO;AAAA,EACT;AAAA,EACA,aAAa;AACX,UAAM,UAAU,CAAC;AACjB,eAAW,QAAQ,KAAK,OAAO;AAC7B,cAAQ,KAAK,GAAG,KAAK,OAAO;AAAA,IAC9B;AACA,WAAO,cAAc,OAAO;AAAA,EAC9B;AAAA,EACA,WAAW,SAAS;AAClB,UAAM,SAAS,CAAC;AAChB,eAAW,QAAQ,KAAK,OAAO;AAC7B,YAAM,YAAY,KAAK,QAAQ;AAC/B,YAAM,eAAe,QAAQ,OAAO,SAAS;AAC7C,eAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC/C,eAAO,KAAK,CAAC,KAAK,QAAQ,KAAK,aAAa,GAAG,CAAC;AAAA,MAClD;AAAA,IACF;AACA,kBAAc,MAAM;AAAA,EACtB;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,SAAS,oBAAoB,MAAM;AACjC,QAAM,EAAE,MAAM,OAAO,MAAM,WAAW,OAAO,OAAOP,UAAS,GAAG,YAAY,IAAI;AAChF,QAAM,gBAAgB,MAAM,eAAe,OAAO,YAAY,MAAM,GAAG,IAAI,IAAI,SAAS,MAAM,GAAG,IAAI;AACrG,QAAM,aAAa,MAAM,aAAa,eAAe,OAAO,QAAQ;AACpE,MAAI,CAACA,WAAUA,WAAU,GAAG;AAC1B,WAAO,KAAK,WAAW,EAAE,MAAM,CAAC;AAAA,EAClC;AACA,QAAM,QAAQ,MAAMA,OAAM,EAAE,KAAK,MAAM,EAAE,IAAI,UAAU;AACvD,SAAO,MAAM,IAAI,CAAC,MAAM,KAAK,EAAE,MAAM,CAAC,CAAC;AACzC;AAGA,IAAI,SAAS,SAAS,IAAI,IAAI;AAC5B,MAAI,KAAK,CAAC;AACV,WAAS,MAAM;AACb,QAAI,OAAO,UAAU,eAAe,KAAK,IAAI,EAAE,KAAK,GAAG,QAAQ,EAAE,IAAI;AACnE,SAAG,MAAM,GAAG;AAChB,MAAI,MAAM,QAAQ,OAAO,OAAO,0BAA0B;AACxD,aAAS,KAAK,GAAG,KAAK,OAAO,sBAAsB,EAAE,GAAG,KAAK,GAAG,QAAQ,MAAM;AAC5E,UAAI,GAAG,QAAQ,GAAG,GAAG,IAAI,KAAK,OAAO,UAAU,qBAAqB,KAAK,IAAI,GAAG,GAAG;AACjF,WAAG,GAAG,OAAO,GAAG,GAAG;AAAA,IACvB;AACF,SAAO;AACT;AACA,IAAI,YAAY,cAAc,IAAI;AAAA,EAChC,YAAY,MAAM;AAChB,QAAI,KAAK,QAAQ;AACf,YAAM,IAAI,oBAAoB,oDAAoD;AAAA,IACpF;AACA,QAAI,MAAM,QAAQ,KAAK,IAAI,GAAG;AAC5B,YAAM,IAAI,oBAAoB,gEAAgE;AAAA,IAChG;AACA,UAAM,IAAI;AACV,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,EAC9C;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,KAAK,KAAK,eAAe,MAAM;AACjC,gBAAQ,KAAK,KAAK,WAAW;AAC7B,aAAK,KAAK,cAAc;AAAA,MAC1B;AACA,UAAI,KAAK,KAAK,wBAAwB,MAAM;AAC1C,gBAAQ,KAAK,KAAK,oBAAoB;AACtC,aAAK,KAAK,uBAAuB;AAAA,MACnC;AACA,UAAI,UAAU,OAAO,cAAc;AACjC,cAAM,IAAI,WAAW,2CAA2C;AAAA,MAClE;AACA,YAAMF,QAAO,UAAU,OAAO,OAAO,OAAO;AAC5C,YAAM,WAAW,UAAU,OAAO,OAAO,OAAO;AAChD,YAAM,eAAe,UAAU,OAAO,OAAO,OAAO;AACpD,aAAO,MAAM,KAAK,QAAQ,EAAE,MAAAA,OAAM,UAAU,aAAa,CAAC;AAAA,IAC5D,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,QAAI,WAAW,KAAK,yBAAyB,UAAU;AACvD,QAAI,CAAC,KAAK,iBAAiB;AACzB,iBAAW,CAAC,SAAS,IAAI,GAAG,SAAS,MAAM,CAAC,CAAC;AAAA,IAC/C;AACA,QAAI,KAAK,aAAa;AACpB,iBAAW,CAAC,UAAU,GAAG,MAAM,CAAC,EAAE,KAAK,CAAC,WAAW,IAAI,GAAG,SAAS,MAAM,EAAE,CAAC,CAAC,CAAC;AAAA,IAChF;AACA,WAAO;AAAA,EACT;AAAA,EACA,gBAAgB,QAAQ;AACtB,WAAO,KAAK,MAAM;AAChB,YAAM,EAAE,UAAU,IAAI,KAAK;AAC3B,YAAM,aAAa,OAAO;AAC1B,YAAM,cAAc,KAAK,yBAAyB,UAAU;AAC5D,YAAM,aAAa,CAAC,YAAY,IAAI,GAAG,YAAY,MAAM,CAAC,CAAC;AAC3D,YAAM,eAAe,MAAM,UAAU;AACrC,UAAI,MAAM,QAAQ,SAAS,GAAG;AAC5B,eAAO,MAAM,UAAU,MAAM,EAAE,KAAK,YAAY;AAAA,MAClD;AACA,aAAO,CAAC,YAAY;AAAA,IACtB,CAAC;AAAA,EACH;AAAA,EACA,YAAY,QAAQ,WAAW,OAAO;AACpC,SAAK,MAAM;AACT,UAAI,CAAC,KAAK,UAAU;AAClB,cAAM,IAAI,eAAe,iEAAiE;AAAA,MAC5F;AACA,YAAM,aAAa,KAAK,UAAU,GAAG;AACrC,YAAM,cAAc,KAAK,yBAAyB,UAAU;AAC5D,YAAM,aAAa,CAAC,YAAY,IAAI,GAAG,YAAY,MAAM,CAAC,CAAC;AAC3D,YAAM,YAAY,WAAW;AAC7B,UAAI,aAAa,MAAM;AACrB,cAAM,IAAI,WAAW,uUAAuU;AAAA,MAC9V;AACA,UAAI,KAAK,UAAU,KAAK,MAAM;AAC5B,YAAI,MAAM,QAAQ,KAAK,KAAK,SAAS,GAAG;AACtC,eAAK,UAAU,KAAK,KAAK,UAAU,IAAI,MAAM,MAAM,UAAU,CAAC;AAAA,QAChE,OAAO;AACL,eAAK,UAAU,CAAC,MAAM,UAAU,CAAC;AAAA,QACnC;AAAA,MACF,WAAW,UAAU,MAAM;AACzB,gBAAQ,KAAK,OAAO;AACpB,YAAI,KAAK,cAAc,MAAM;AAC3B,kBAAQ,KAAK,UAAU;AACvB,eAAK,aAAa,CAAC;AAAA,QACrB;AACA,YAAI,MAAM,QAAQ,KAAK,KAAK,SAAS,GAAG;AACtC,eAAK,UAAU,KAAK,KAAK,UAAU,IAAI,MAAM,MAAM,UAAU,CAAC;AAAA,QAChE,OAAO;AACL,eAAK,QAAQ,KAAK,MAAM,UAAU;AAAA,QACpC;AAAA,MACF,OAAO;AACL,YAAI,CAAC,MAAM,QAAQ,MAAM,GAAG;AAC1B,mBAAS,CAAC,MAAM;AAAA,QAClB;AACA,YAAI,OAAO,WAAW,KAAK,QAAQ,QAAQ;AACzC,gBAAM,IAAI,WAAW,SAAS,KAAK,gBAAgB,KAAK,QAAQ,oCAAoC,OAAO,0CAA0C,QAAQ;AAAA,QAC/J;AACA,YAAI,UAAU;AACZ,eAAK,WAAW,KAAK,KAAK,QAAQ,MAAM,CAAC;AAAA,QAC3C,OAAO;AACL,kBAAQ,KAAK,OAAO;AAAA,QACtB;AACA,iBAASI,SAAQ,GAAGA,SAAQ,KAAK,QAAQ,QAAQ,EAAEA,QAAO;AACxD,gBAAM,QAAQ,OAAOA;AACrB,gBAAM,gBAAgB;AACtB,cAAI,CAAC,aAAa,YAAY,MAAM,OAAO,aAAa,GAAG;AACzD,kBAAM,IAAI,WAAW,SAASA,qCAAoC,KAAK,wBAAwB,iCAAiC,MAAM,OAAO;AAAA,UAC/I;AACA,eAAK,QAAQA,UAAS;AAAA,QACxB;AAAA,MACF;AACA,WAAK,UAAU,KAAK,QAAQ,IAAI,CAAC,UAAU,KAAK,MAAM,MAAM,CAAC,CAAC;AAAA,IAChE,CAAC;AAAA,EACH;AAAA,EACA,yBAAyB,YAAY;AACnC,UAAM,EAAE,YAAY,SAAS,YAAY,SAAAkB,UAAS,SAAAf,UAAS,aAAa,IAAI,KAAK;AACjF,UAAM,kBAAkB,eAAe;AACvC,UAAM,IAAI,WAAW,kBAAkB,IAAI;AAC3C,UAAM,IAAI,WAAW,kBAAkB,IAAI;AAC3C,UAAM,OAAO,iBAAiB,GAAG,WAAW,IAAIe,UAASf,SAAQ,IAAI,aAAa,EAAE;AACpF,UAAM,OAAO,iBAAiB,GAAG,WAAW,IAAIe,UAASf,SAAQ,IAAI,aAAa,EAAE;AACpF,UAAM,WAAW;AAAA,MACf,GAAG,WAAW,MAAM,GAAG,CAAC;AAAA,MACxB,GAAG,kBAAkB,CAAC,SAAS,MAAM,IAAI,IAAI,CAAC,MAAM,MAAM,OAAO;AAAA,IACnE;AACA,WAAO;AAAA,EACT;AACF;AACA,UAAU,YAAY;AACtB,IAAI,iBAAiB,cAAc,SAAS;AAAA,EAC1C,YAAY,MAAM;AAChB,UAAM,EAAE,SAAS,YAAY,SAAAA,UAAS,SAAAe,UAAS,YAAY,aAAa,IAAI;AAC5E,UAAM,OAAO,OAAO,CAAC,GAAG,MAAM,EAAE,OAAO,QAAQ,CAAC,CAAC;AACjD,SAAK,UAAU;AACf,0BAAsB,KAAK,SAAS,SAAS;AAC7C,SAAK,aAAa,eAAe,YAAY,GAAG,YAAY;AAC5D,SAAK,WAAW,QAAQ,CAAC3B,UAAS,sBAAsBA,OAAM,YAAY,CAAC;AAC3E,SAAK,UAAU,eAAeY,YAAW,GAAG,GAAG,SAAS;AACxD,SAAK,QAAQ,QAAQ,CAAC,WAAW,sBAAsB,QAAQ,SAAS,CAAC;AACzE,SAAK,UAAUe,YAAW;AAC1B,qBAAiB,KAAK,OAAO;AAC7B,SAAK,aAAa,cAAc;AAChC,oBAAgB,KAAK,UAAU;AAC/B,SAAK,eAAe,eAAe,gBAAgB,GAAG,GAAG,cAAc;AACvE,SAAK,aAAa,QAAQ,CAAC,SAAS,sBAAsB,MAAM,cAAc,CAAC;AAAA,EACjF;AAAA,EACA,MAAM,YAAY;AAChB,QAAI;AACJ,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,cAAc,KAAK,eAAe,kBAAkB,IAAI,WAAW,SAAS;AAClF,QAAI,WAAW,gBAAgB,MAAM;AACnC,YAAM,IAAI,WAAW,+DAA+D,WAAW,cAAc;AAAA,IAC/G;AACA,UAAM,WAAW,WAAW;AAC5B,UAAM,eAAe;AACrB,UAAM,cAAc,KAAK,WAAW,OAAO,CAAC,UAAU,KAAK,UAAU,YAAY,CAAC;AAClF,SAAK,SAAS,KAAK,UAAU,UAAU,aAAa,MAAM,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AACrI,UAAM,uBAAuB,KAAK,WAAW,OAAO,CAAC,KAAK,SAAS,KAAK,UAAU,YAAY,CAAC;AAC/F,SAAK,kBAAkB,KAAK,UAAU,oBAAoB,sBAAsB,MAAM,KAAK,sBAAsB,KAAK,sBAAsB,MAAM,KAAK,mBAAmB;AAC1K,QAAI,KAAK,SAAS;AAChB,UAAI;AACJ,UAAI,KAAK,gBAAgB;AACvB,cAAMvB,SAAQ,KAAK;AACnB,cAAM,UAAU,KAAK;AACrB,0BAAkB,KAAK,KAAK,MAAM,mBAAmB,YAAY;AAAA,UAC/D,MAAM,OAAO,OAAO;AAClB,kBAAM,QAAQA,OAAM,MAAM,CAAC,OAAO,CAAC;AACnC,kBAAM,QAAQ,MAAM,CAAC,OAAO,CAAC;AAC7B,kBAAM,YAAYA,OAAM,MAAM,CAAC,UAAU,CAAC,CAAC;AAC3C,mBAAO,YAAY,CAAC,OAAO,OAAO,SAAS,CAAC;AAAA,UAC9C;AAAA,QACF,GAAG,GAAG,YAAY,cAAc,IAAI;AAAA,MACtC,OAAO;AACL,0BAAkB,KAAK;AAAA,MACzB;AACA,WAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,UAAU,YAAY,GAAG,MAAM,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IAC1I;AACA,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,OAAO,WAAW,GAAG;AACvB,cAAM,IAAI,WAAW,8DAA8D,OAAO,SAAS;AAAA,MACrG;AACA,YAAM,WAAW,OAAO,eAAe;AACvC,YAAM,IAAI,OAAO;AACjB,YAAM,WAAW,OAAO;AACxB,YAAM,WAAW,OAAO;AACxB,YAAM,eAAe;AACrB,UAAI,IAAI,KAAK,WAAW,KAAK,UAAU,KAAK,KAAK,eAAe,MAAM;AACpE,aAAK,cAAc,oBAAoB;AAAA,UACrC,MAAM,MAAM,SAAS,CAAC;AAAA,UACtB,MAAM,KAAK;AAAA,UACX;AAAA,UACA,OAAO;AAAA,UACP,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,YAAM,cAAc,KAAK;AACzB,YAAM,eAAe,CAAC,IAAIC,OAAMI,WAAU;AACxC,YAAI,CAACJ,SAAQ,CAACA,MAAKI,SAAQ;AACzB,iBAAO;AAAA,QACT;AACA,eAAO,IAAIJ,MAAKI,SAAQ,EAAE;AAAA,MAC5B;AACA,UAAI,KAAK,aAAa,GAAG,aAAa,CAAC;AACvC,UAAI,KAAK,aAAa,GAAG,aAAa,CAAC;AACvC,UAAI,KAAK,aAAa,GAAG,aAAa,CAAC;AACvC,UAAI,KAAK,aAAa,GAAG,aAAa,CAAC;AACvC,UAAI,IAAI,KAAK,oBAAoB,KAAK,mBAAmB,KAAK,KAAK,wBAAwB,MAAM;AAC/F,aAAK,uBAAuB,oBAAoB;AAAA,UAC9C,MAAM,MAAM,SAAS,QAAQ;AAAA,UAC7B,MAAM,KAAK;AAAA,UACX;AAAA,UACA,OAAO;AAAA,UACP,aAAa,KAAK;AAAA,QACpB,CAAC;AAAA,MACH;AACA,YAAM,iBAAiB,KAAK;AAC5B,UAAI,KAAK,aAAa,UAAU,gBAAgB,CAAC;AACjD,UAAI,KAAK,aAAa,UAAU,gBAAgB,CAAC;AACjD,UAAI,KAAK,aAAa,UAAU,gBAAgB,CAAC;AACjD,UAAI,KAAK,aAAa,UAAU,gBAAgB,CAAC;AACjD,YAAM,oBAAoB;AAC1B,YAAM,CAAC,SAAS,SAAS,SAAS,OAAO,IAAI,MAAM,KAAK,OAAO,KAAK,GAAG,cAAc,iBAAiB;AACtG,YAAM,CAAC,OAAO,OAAO,OAAO,KAAK,IAAI,KAAK,UAAU,MAAM,KAAK,KAAK,KAAK,GAAG,YAAY,IAAI,CAAC,MAAM,MAAM,MAAM,IAAI;AACnH,WAAK,KAAK,UAAU,IAAI,SAAS,OAAO,KAAK,OAAO;AACpD,WAAK,KAAK,UAAU,IAAI,SAAS,OAAO,KAAK,OAAO;AACpD,WAAK,KAAK,UAAU,IAAI,SAAS,OAAO,KAAK,OAAO;AACpD,WAAK,KAAK,UAAU,IAAI,SAAS,OAAO,KAAK,OAAO;AACpD,YAAM,CAAC,YAAY,YAAY,YAAY,UAAU,IAAI,MAAM,KAAK,gBAAgB,KAAK,GAAG,cAAc,iBAAiB;AAC3H,WAAK,KAAK,cAAc,IAAI,UAAU;AACtC,WAAK,KAAK,cAAc,IAAI,UAAU;AACtC,WAAK,KAAK,cAAc,IAAI,UAAU;AACtC,WAAK,KAAK,cAAc,IAAI,UAAU;AACtC,YAAM,KAAK,KAAK,oBAAoB,MAAM,KAAK,IAAI,EAAE,CAAC;AACtD,YAAM,IAAI,KAAK,oBAAoB,MAAM,KAAK,IAAI,EAAE,CAAC;AACrD,YAAM,IAAI,KAAK,IAAI,GAAG,QAAQ,GAAG,IAAI,IAAI,KAAK,WAAW,MAAM,KAAK,IAAI,EAAE,CAAC,CAAC,CAAC;AAC7E,YAAM,IAAI,IAAI,KAAK,oBAAoB,MAAM,KAAK,IAAI,EAAE,CAAC,GAAG,KAAK,WAAW,MAAM,CAAC,CAAC;AACpF,aAAO,CAAC,GAAG,GAAG,CAAC;AAAA,IACjB,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAM,KAAK,MAAM,UAAU,GAAG,EAAE,SAAS,EAAE,IAAI,IAAI,aAAa,OAAO,IAAI,CAAC,OAAO,CAAC;AACpF,UAAMK,UAAS;AAAA,MACb,SAAS,KAAK;AAAA,MACd,YAAY,KAAK;AAAA,MACjB,SAAS,KAAK;AAAA,MACd,YAAY,KAAK;AAAA,MACjB,cAAc,KAAK;AAAA,MACnB,SAAS,KAAK;AAAA,IAChB;AACA,WAAO,OAAO,OAAO,CAAC,GAAG,YAAYA,OAAM;AAAA,EAC7C;AAAA,EACA,UAAU,GAAG,GAAG,GAAGa,UAAS;AAC1B,UAAM,MAAM,OAAO,GAAG,GAAG,KAAK,SAASA,YAAW,SAAS,KAAK,eAAe,kBAAkB,SAAS,QAAQ,KAAK,YAAY;AACnI,QAAI,GAAG;AACL,aAAO,QAAQ,KAAK,GAAG,KAAK,UAAU;AAAA,IACxC;AACA,WAAO;AAAA,EACT;AAAA,EACA,cAAc,GAAG,GAAG;AAClB,UAAMf,WAAU;AAChB,WAAO,OAAO,GAAG,GAAGA,UAAS,QAAQ,KAAK,eAAe,kBAAkB,SAAS,MAAM;AAAA,EAC5F;AACF;AACA,eAAe,YAAY;AAC3B,sBAAsB,cAAc,cAAc;AAClD,IAAI,aAAa,cAAc,UAAU;AAAA,EACvC,YAAY,MAAM;AAChB,UAAM,OAAO,IAAI,eAAe,IAAI;AACpC,UAAM,OAAO,OAAO,CAAC,GAAG,MAAM,EAAE,KAAK,CAAC,CAAC;AAAA,EACzC;AAAA,EACA,OAAO,WAAW,KAAKE,SAAQ;AAC7B,WAAO,IAAI,IAAIA,OAAM;AAAA,EACvB;AACF;AACA,WAAW,YAAY;AACvB,sBAAsB,cAAc,UAAU;AAG9C,IAAI,UAAU,cAAc,MAAM;AAAA,EAChC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,OAAO,KAAK,IAAI,KAAK,IAAI,KAAK,MAAM,CAAC,GAAG,CAAC;AAC9C,SAAK,aAAa,KAAK;AACvB,SAAK,OAAO,KAAK;AACjB,SAAK,kBAAkB;AAAA,EACzB;AAAA,EACA,cAAc,QAAQ;AACpB,QAAI,KAAK,cAAc,MAAM;AAC3B,aAAO,KAAK;AAAA,IACd;AACA,UAAM,aAAa,OAAO;AAC1B,UAAM,aAAa,CAAC;AACpB,aAAS,KAAK,GAAG,KAAK,KAAK,WAAW,QAAQ,EAAE,IAAI;AAClD,iBAAW,KAAK,KAAK,WAAW,OAAO,OAAO,WAAW,MAAM,KAAK,WAAW,GAAG;AAAA,IACpF;AACA,WAAO;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,YAAM,SAAS,oBAAoB,MAAM;AACzC,UAAI,IAAI,KAAK,QAAQ,KAAK,OAAO,GAAG;AAClC,cAAM,WAAW,OAAO,eAAe,OAAO,QAAQ,OAAO;AAC7D,cAAM,aAAa,KAAK,cAAc,MAAM;AAC5C,cAAM,SAAS,aAAa,MAAM,SAAS,QAAQ,KAAK,MAAM,YAAY,KAAK,IAAI,GAAG,MAAM,QAAQ,QAAQ;AAC5G,eAAO;AAAA,MACT;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,MAAM,KAAK;AAAA,MACX,YAAY,KAAK;AAAA,MACjB,MAAM,KAAK;AAAA,IACb;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,UAAU;AACR,WAAO,MAAM,QAAQ;AAAA,EACvB;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,mBAAmB,cAAc,QAAQ;AAAA,EAC3C,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,YAAY,CAAC,EAAE,MAAM,EAAE,CAAC;AAAA,EAC/B;AAAA,EACA,cAAc,QAAQ;AACpB,UAAM,aAAa,OAAO;AAC1B,WAAO,CAAC,WAAW,IAAI,GAAG,WAAW,EAAE;AAAA,EACzC;AACF;AACA,iBAAiB,YAAY;AAC7B,sBAAsB,cAAc,gBAAgB;AACpD,IAAI,QAAQ,cAAc,MAAM;AAAA,EAC9B,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,aAAa;AAClB,SAAK,UAAU;AACf,SAAK,SAAS;AACd,SAAK,OAAO;AACZ,SAAK,6BAA6B;AAClC,SAAK,2BAA2B;AAChC,QAAI,KAAK,mBAAmB,QAAQ,KAAK,cAAc,QAAQ,KAAK,YAAY,MAAM;AACpF,UAAI,YAAY;AAChB,UAAI,KAAK,aAAa,MAAM;AAC1B,oBAAY,KAAK;AAAA,MACnB;AACA,WAAK,kBAAkB,CAAC,WAAW,KAAK,QAAQ;AAAA,IAClD;AACA,SAAK,QAAQ,KAAK;AAClB,0BAAsB,KAAK,OAAO,OAAO;AACzC,SAAK,aAAa,cAAc,KAAK,UAAU;AAC/C,QAAI,KAAK,WAAW,MAAM;AACxB,WAAK,UAAU,KAAK;AAAA,IACtB;AACA,SAAK,oBAAoB,eAAe,KAAK,qBAAqB,KAAK,0BAA0B;AACjG,SAAK,kBAAkB,eAAe,KAAK,mBAAmB,KAAK,wBAAwB;AAC3F,SAAK,mBAAmB,cAAc,KAAK,gBAAgB;AAC3D,SAAK,iBAAiB,cAAc,KAAK,cAAc;AACvD,SAAK,oBAAoB,eAAe,KAAK,iBAAiB;AAC9D,SAAK,kBAAkB,eAAe,KAAK,eAAe;AAC1D,SAAK,sBAAsB,eAAe,KAAK,mBAAmB;AAClE,SAAK,kBAAkB;AACvB,SAAK,YAAY,CAAC,EAAE,SAAS,EAAE,CAAC;AAAA,EAClC;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,eAAe,WAAW,WAAW,SAAS;AACpD,QAAI,KAAK,UAAU,MAAM;AACvB,WAAK,SAAS,KAAK,UAAU,UAAU,CAAC,cAAc,KAAK,KAAK,GAAG,MAAM,KAAK,mBAAmB,KAAK,mBAAmB,MAAM,KAAK,gBAAgB;AACpJ,UAAI,KAAK,SAAS;AAChB,aAAK,OAAO,KAAK,UAAU,QAAQ,CAAC,KAAK,KAAK,GAAG,MAAM,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,MAC9H;AAAA,IACF;AACA,SAAK,YAAY,CAAC,EAAE,SAAS,GAAG,MAAM,EAAE,CAAC,KAAK,aAAa,EAAE,CAAC;AAC9D,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,cAAc,WAAW,MAAM;AACrC,gBAAY,YAAY,SAAS,KAAK,KAAK;AAC3C,WAAO;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,YAAM,SAAS,oBAAoB,MAAM;AACzC,YAAM,sBAAsB,2BAA2B,KAAK,WAAW,aAAa,CAAC;AACrF,UAAI;AACJ,UAAI,uBAAuB,MAAM;AAC/B,iBAAS,KAAK,QAAQ,KAAK,OAAO,KAAK,GAAG,qBAAqB,KAAK,OAAO,KAAK,KAAK,KAAK,IAAI,IAAI;AAAA,MACpG,OAAO;AACL,iBAAS,KAAK,QAAQ,KAAK,OAAO,KAAK,CAAC;AACxC,YAAI,KAAK,QAAQ,MAAM;AACrB,mBAAS,QAAQ,QAAQ,KAAK,KAAK,KAAK,CAAC;AAAA,QAC3C;AACA,YAAI,KAAK,cAAc,MAAM;AAC3B,mBAAS,KAAK,WAAW,MAAM,MAAM;AAAA,QACvC;AAAA,MACF;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,OAAO,KAAK;AAAA,MACZ,YAAY,oBAAoB,KAAK,UAAU;AAAA,MAC/C,SAAS,KAAK;AAAA,MACd,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,mBAAmB,qBAAqB,KAAK,iBAAiB;AAAA,MAC9D,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,qBAAqB,qBAAqB,KAAK,mBAAmB;AAAA,MAClE,kBAAkB,oBAAoB,KAAK,gBAAgB;AAAA,MAC3D,gBAAgB,oBAAoB,KAAK,cAAc;AAAA,IACzD;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,MAAM,YAAY;AAClB,sBAAsB,cAAc,KAAK;AACzC,IAAI,UAAU,cAAc,MAAM;AAAA,EAChC,YAAY,MAAM;AAChB,WAAO,QAAQ,CAAC;AAChB,UAAM,IAAI;AACV,SAAK,YAAY,CAAC,EAAE,SAAS,EAAE,CAAC;AAChC,SAAK,aAAa,KAAK;AAAA,EACzB;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,eAAW,OAAO,WAAW,MAAM,CAAC,GAAG;AACrC,UAAI,OAAO,MAAM;AACf,cAAM,IAAI,WAAW,iEAAiE,WAAW,MAAM,CAAC,kHAAkH;AAAA,MAC5N;AAAA,IACF;AACA,WAAO,CAAC,WAAW,IAAI,UAAU,YAAY,CAAC,CAAC;AAAA,EACjD;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,UAAI,SAAS,oBAAoB,MAAM;AACvC,UAAI,KAAK,eAAe,mBAAmB,OAAO,OAAO,GAAG;AAC1D,cAAM,cAAc,CAAC,CAAC;AACtB,iBAAS,KAAK,GAAG,KAAK,OAAO,MAAM,EAAE,IAAI;AACvC,sBAAY,KAAK,EAAE;AAAA,QACrB;AACA,oBAAY,KAAK,CAAC;AAClB,iBAAS,UAAU,QAAQ,WAAW;AAAA,MACxC;AACA,aAAO,aAAa,MAAM;AAAA,IAC5B,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,CAAC;AAChB,QAAI,KAAK,cAAc,MAAM;AAC3B,MAAAA,QAAO,gBAAgB,KAAK;AAAA,IAC9B;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,cAAc,cAAc,MAAM;AAAA,EACpC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,kBAAkB;AACvB,SAAK,aAAa,cAAc,KAAK,UAAU;AAAA,EACjD;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,YAAM,SAAS,oBAAoB,MAAM;AACzC,aAAO,KAAK,WAAW,MAAM,MAAM;AAAA,IACrC,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS,EAAE,YAAY,oBAAoB,KAAK,UAAU,EAAE;AAClE,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,YAAY,YAAY;AACxB,sBAAsB,cAAc,WAAW;AAC/C,IAAI,eAAe,cAAc,MAAM;AAAA,EACrC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,IAAI,KAAK;AACd,SAAK,YAAY,CAAC,EAAE,MAAM,EAAE,CAAC;AAAA,EAC/B;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO,CAAC,WAAW,IAAI,KAAK,GAAG,WAAW,EAAE;AAAA,EAC9C;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS,oBAAoB,MAAM;AACnC,aAAO,OAAO,QAAQ,KAAK,CAAC;AAAA,IAC9B,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,GAAG,KAAK;AAAA,IACV;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAChD,IAAI,WAAW,cAAc,MAAM;AAAA,EACjC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,cAAc,KAAK;AACxB,aAAS,KAAK,GAAG,KAAK,KAAK,YAAY,QAAQ,EAAE,IAAI;AACnD,UAAI,KAAK,UAAU,KAAK,YAAY,GAAG,GAAG;AACxC,aAAK,YAAY,MAAM;AAAA,MACzB;AAAA,IACF;AAAA,EACF;AAAA,EACA,UAAU,KAAK;AACb,WAAO,MAAM,KAAK,OAAO;AAAA,EAC3B;AAAA,EACA,oBAAoB,YAAY,aAAa;AAC3C,UAAM,WAAW;AACjB,UAAM,aAAa,YAAY,MAAM;AACrC,QAAI,QAAQ;AACZ,QAAI,UAAU;AACd,aAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,YAAM,MAAM,WAAW;AACvB,UAAI,KAAK,UAAU,GAAG,GAAG;AACvB,YAAI,YAAY,MAAM;AACpB,oBAAU;AAAA,QACZ,OAAO;AACL,gBAAM,IAAI,WAAW,0CAA0C;AAAA,QACjE;AAAA,MACF,OAAO;AACL,iBAAS;AAAA,MACX;AAAA,IACF;AACA,UAAM,eAAe,UAAU,UAAU;AACzC,QAAI,YAAY,MAAM;AACpB,UAAI,UAAU,KAAK,eAAe,UAAU,GAAG;AAC7C,cAAM,IAAI,WAAW,QAAQ;AAAA,MAC/B;AACA,iBAAW,WAAW,eAAe;AAAA,IACvC,WAAW,iBAAiB,OAAO;AACjC,YAAM,IAAI,WAAW,QAAQ;AAAA,IAC/B;AACA,WAAO;AAAA,EACT;AAAA,EACA,mBAAmB,YAAY;AAC7B,QAAI,iBAAiB;AACrB,aAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,UAAI,KAAK,UAAU,WAAW,GAAG,GAAG;AAClC,yBAAiB;AACjB;AAAA,MACF;AAAA,IACF;AACA,QAAI,gBAAgB;AAClB,aAAO,WAAW,MAAM,GAAG,CAAC,EAAE,OAAO,KAAK,WAAW;AAAA,IACvD,OAAO;AACL,aAAO,WAAW,MAAM,GAAG,CAAC,EAAE,OAAO,KAAK,oBAAoB,WAAW,MAAM,CAAC,GAAG,KAAK,WAAW,CAAC;AAAA,IACtG;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,YAAM,SAAS,oBAAoB,MAAM;AACzC,YAAM,aAAa,OAAO;AAC1B,YAAM,cAAc,WAAW,MAAM,GAAG,CAAC,EAAE,OAAO,KAAK,oBAAoB,WAAW,MAAM,CAAC,GAAG,KAAK,WAAW,CAAC;AACjH,aAAO,QAAQ,QAAQ,WAAW;AAAA,IACpC,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,aAAa,KAAK;AAAA,IACpB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,UAAU,cAAc,MAAM;AAAA,EAChC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,QAAI,KAAK,QAAQ,MAAM;AACrB,YAAM,IAAI,MAAM,iFAAiF;AAAA,IACnG;AACA,QAAI,CAAC,MAAM,QAAQ,KAAK,IAAI,GAAG;AAC7B,YAAM,IAAI,MAAM,sEAAsE,KAAK,eAAe;AAAA,IAC5G;AACA,UAAM,wBAAwB,OAAO,GAAG,KAAK,KAAK,SAAS,CAAC;AAC5D,QAAI,CAAC,aAAa,YAAY,KAAK,KAAK,MAAM,EAAE,KAAK,GAAG,qBAAqB,GAAG;AAC9E,YAAM,IAAI,MAAM,iCAAiC,KAAK,UAAU,KAAK,IAAI,IAAI,4DAA4D;AAAA,IAC3I;AACA,SAAK,OAAO,KAAK;AACjB,SAAK,qBAAqB,CAAC,CAAC,EAAE,OAAO,KAAK,IAAI;AAC9C,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,KAAK,KAAK,SAAS,EAAE,CAAC,CAAC;AAAA,EACjE;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,cAAc,WAAW,MAAM;AACrC,SAAK,KAAK,QAAQ,CAAC,KAAK,OAAO;AAC7B,kBAAY,KAAK,KAAK,WAAW;AAAA,IACnC,CAAC;AACD,WAAO;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,UAAU,oBAAoB,MAAM,GAAG,KAAK,kBAAkB;AAAA,EACvE;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,MAAM,KAAK;AAAA,IACb;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,UAAU,cAAc,MAAM;AAAA,EAChC,YAAY,MAAM;AAChB,UAAM,QAAQ,OAAO,CAAC,IAAI,IAAI;AAC9B,SAAK,kBAAkB;AACvB,QAAI,QAAQ,MAAM;AAChB,WAAK,YAAY,KAAK,aAAa,OAAO,IAAI,KAAK;AAAA,IACrD,OAAO;AACL,WAAK,YAAY;AAAA,IACnB;AAAA,EACF;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMA,UAAS,EAAE,WAAW,KAAK,UAAU;AAC3C,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,YAAY,QAAQT,OAAM;AACxB,UAAM,SAAS,oBAAoB,MAAM;AACzC,UAAM,OAAO;AACb,WAAO,IAAI,SAAS,QAAQ,KAAK,SAAS,GAAG,IAAI;AAAA,EACnD;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,YAAM,SAAS,oBAAoB,MAAM;AACzC,YAAM,OAAO;AACb,YAAM,WAAW;AACjB,YAAM,cAAc,IAAI,SAAS,QAAQ,KAAK,SAAS,GAAG,MAAM,QAAQ;AACxE,YAAM,SAAS,IAAI,QAAQ,KAAK,aAAa,OAAO,KAAK,CAAC;AAC1D,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAG3C,IAAI,YAAY,cAAc,MAAM;AAAA,EAClC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,aAAa;AAClB,SAAK,iCAAiC;AACtC,QAAI,KAAK,mBAAmB,QAAQ,KAAK,cAAc,MAAM;AAC3D,UAAI,YAAY;AAChB,UAAI,KAAK,aAAa,MAAM;AAC1B,oBAAY,KAAK;AAAA,MACnB;AACA,UAAI,KAAK,eAAe,MAAM;AAC5B,aAAK,kBAAkB,CAAC,WAAW,IAAI;AAAA,MACzC,OAAO;AACL,aAAK,kBAAkB,CAAC,SAAS,EAAE,OAAO,OAAO,KAAK,WAAW,CAAC;AAAA,MACpE;AAAA,IACF;AACA,SAAK,WAAW,KAAK;AACrB,0BAAsB,KAAK,UAAU,UAAU;AAC/C,SAAK,YAAY,KAAK;AACtB,0BAAsB,KAAK,WAAW,WAAW;AACjD,SAAK,wBAAwB,eAAe,KAAK,yBAAyB,KAAK,8BAA8B;AAC7G,SAAK,wBAAwB,eAAe,KAAK,qBAAqB;AACtE,SAAK,sBAAsB,eAAe,KAAK,mBAAmB;AAClE,SAAK,uBAAuB,cAAc,KAAK,oBAAoB;AACnE,SAAK,WAAW,KAAK;AACrB,SAAK,kBAAkB,KAAK;AAC5B,SAAK,cAAc,KAAK;AAAA,EAC1B;AAAA,EACA,MAAM,YAAY;AAChB,SAAK,aAAa,KAAK,UAAU,cAAc,CAAC,KAAK,UAAU,KAAK,SAAS,GAAG,KAAK,OAAO,KAAK,uBAAuB,KAAK,uBAAuB,MAAM,KAAK,oBAAoB;AACnL,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,6BAA6B,YAAY;AAAA,EACzC;AAAA,EACA,YAAY,QAAQA,OAAM;AACxB,WAAO,KAAK,MAAM;AAChB,UAAI,CAAC,KAAK,UAAU;AAClB,eAAO;AAAA,MACT,OAAO;AACL,iBAAS,oBAAoB,MAAM;AACnC,eAAO,SAAS,QAAQ,UAAU,MAAM,CAAC;AAAA,MAC3C;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,KAAK,eAAe,MAAM;AAC5B,aAAO,CAAC,GAAG,YAAY,KAAK,SAAS;AAAA,IACvC;AACA,UAAM,SAAS,OAAO,KAAK,WAAW;AACtC,QAAI,OAAO,WAAW,WAAW,SAAS,GAAG;AAC3C,YAAM,IAAI,WAAW,oBAAoB,KAAK,mDAAmD,YAAY;AAAA,IAC/G,OAAO;AACL,UAAI,KAAK;AACT,eAAS,IAAI,GAAG,IAAI,OAAO,QAAQ,EAAE,GAAG;AACtC,cAAM,KAAK,OAAO;AAClB,cAAM,KAAK,WAAW,IAAI;AAC1B,YAAI,MAAM,QAAQ,MAAM,QAAQ,OAAO,IAAI;AACzC,gBAAM,IAAI,WAAW,oBAAoB,KAAK,mDAAmD,YAAY;AAAA,QAC/G,WAAW,MAAM,MAAM;AACrB,iBAAO,MAAM;AAAA,QACf;AACA;AAAA,MACF;AAAA,IACF;AACA,WAAO,CAAC,WAAW,IAAI,GAAG,QAAQ,KAAK,SAAS;AAAA,EAClD;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,UAAI,SAAS,oBAAoB,MAAM;AACvC,UAAI,OAAO,UAAU,SAAS;AAC5B,iBAAS,MAAM,QAAQ,OAAO;AAAA,MAChC;AACA,YAAM,SAAS,QAAQ,KAAK,WAAW,KAAK,GAAG,QAAQ,QAAQ,CAAC,OAAO,IAAI,CAAC,CAAC;AAC7E,aAAO,QAAQ,QAAQ,mBAAmB,KAAK,mBAAmB,OAAO,KAAK,CAAC,CAAC;AAAA,IAClF,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMS,UAAS;AAAA,MACb,UAAU,KAAK;AAAA,MACf,WAAW,KAAK;AAAA,MAChB,uBAAuB,qBAAqB,KAAK,qBAAqB;AAAA,MACtE,uBAAuB,qBAAqB,KAAK,qBAAqB;AAAA,MACtE,qBAAqB,qBAAqB,KAAK,mBAAmB;AAAA,MAClE,sBAAsB,oBAAoB,KAAK,oBAAoB;AAAA,MACnE,UAAU,KAAK;AAAA,MACf,aAAa,KAAK;AAAA,IACpB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,UAAU,YAAY;AACtB,sBAAsB,cAAc,SAAS;AAG7C,IAAI,QAAQ,cAAc,MAAM;AAAA,EAC9B,YAAY,MAAM;AAChB,UAAM,QAAQ,CAAC,CAAC;AAChB,SAAK,kBAAkB;AAAA,EACzB;AAAA,EACA,cAAc,QAAQ;AACpB,UAAM,IAAI,oBAAoB;AAAA,EAChC;AAAA,EACA,gCAAgC,QAAQ,QAAQ;AAC9C,QAAI,UAAU,QAAQ,UAAU,MAAM;AACpC,aAAO;AAAA,IACT,WAAW,OAAO,SAAS,OAAO,QAAQ;AACxC,aAAO,KAAK,gCAAgC,QAAQ,MAAM;AAAA,IAC5D,WAAW,OAAO,WAAW,GAAG;AAC9B,aAAO;AAAA,IACT;AACA,UAAM,cAAc,OAAO,MAAM,GAAG,OAAO,SAAS,OAAO,MAAM;AACjE,aAAS,IAAI,GAAG,IAAI,OAAO,QAAQ,EAAE,GAAG;AACtC,YAAM,KAAK,OAAO,OAAO,SAAS,OAAO,SAAS;AAClD,YAAM,IAAI,OAAO;AACjB,UAAI,MAAM,QAAQ,KAAK,QAAQ,KAAK,KAAK,IAAI,GAAG;AAC9C,oBAAY,KAAK,IAAI;AAAA,MACvB,WAAW,OAAO,GAAG;AACnB,oBAAY,KAAK,CAAC;AAAA,MACpB,WAAW,MAAM,GAAG;AAClB,oBAAY,KAAK,EAAE;AAAA,MACrB,OAAO;AACL,YAAI,OAAO,GAAG;AACZ,gBAAM,IAAI,WAAW,0DAA0D,KAAK,UAAU,MAAM,IAAI,MAAM,KAAK,UAAU,MAAM,CAAC;AAAA,QACtI;AACA,oBAAY,KAAK,EAAE;AAAA,MACrB;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,YAAY;AAChB,QAAI,MAAM,QAAQ,UAAU,KAAK,CAAC,MAAM,QAAQ,WAAW,EAAE,GAAG;AAC9D,mBAAa,CAAC,mBAAmB,UAAU,CAAC;AAAA,IAC9C;AACA,iBAAa;AACb,QAAI,WAAW,SAAS,GAAG;AACzB,YAAM,IAAI,WAAW,wEAAwE,WAAW,kBAAkB;AAAA,IAC5H;AACA,QAAI,aAAa,CAAC;AAClB,eAAW,SAAS,YAAY;AAC9B,UAAI,SAAS,QAAQ,MAAM,OAAO,MAAM;AACtC,mBAAW,KAAK,MAAM,EAAE;AAAA,MAC1B;AAAA,IACF;AACA,iBAAa,QAAQ,UAAU;AAC/B,QAAI,WAAW,SAAS,GAAG;AACzB,YAAM,IAAI,WAAW,8EAA8E,KAAK,UAAU,UAAU,IAAI;AAAA,IAClI;AACA,QAAI,cAAc,WAAW,MAAM,OAAO,OAAO,WAAW,GAAG,MAAM,CAAC;AACtE,aAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,YAAM,QAAQ,WAAW,OAAO,OAAO,OAAO,WAAW,IAAI,MAAM,CAAC;AACpE,oBAAc,KAAK,gCAAgC,aAAa,KAAK;AAAA,IACvE;AACA,UAAM,WAAW,WAAW,IAAI,CAAC,UAAU,MAAM,MAAM;AACvD,QAAI,WAAW,QAAQ,IAAI,MAAM,MAAM,QAAQ,QAAQ,EAAE,WAAW,GAAG;AACrE,WAAK,kBAAkB;AAAA,IACzB,OAAO;AACL,WAAK,kBAAkB;AAAA,IACzB;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS;AACT,UAAI,KAAK,iBAAiB;AACxB,cAAM,iBAAiB,CAAC;AACxB,cAAM,YAAY,OAAO,IAAI,CAAC,WAAW,OAAO,IAAI;AACpD,YAAI,UAAU,QAAQ,IAAI,MAAM,IAAI;AAClC,gBAAM,UAAU,KAAK,SAAS;AAC9B,mBAAS,KAAK,QAAQ;AACpB,kBAAM,QAAQ,EAAE;AAChB,qBAAS,IAAI,GAAG,IAAI,UAAU,OAAO,EAAE,GAAG;AACxC,kBAAI,YAAY,GAAG,CAAC;AAAA,YACtB;AACA,2BAAe,KAAK,CAAC;AAAA,UACvB;AACA,iBAAO,KAAK,cAAc,cAAc;AAAA,QAC1C,OAAO;AACL,cAAI,aAAa;AACjB,qBAAW,KAAK,QAAQ;AACtB,kBAAM,QAAQ,EAAE;AAChB,gBAAI,SAAS,MAAM;AACjB,oBAAM,SAAS,EAAE;AACjB,oBAAM,YAAY,OAAO;AACzB,oBAAM,WAAW,OAAO,MAAM,CAAC,EAAE,OAAO,CAAC,SAAS,CAAC;AACnD,kBAAI,cAAc,QAAQ,GAAG,CAAC,SAAS,EAAE,OAAO,UAAU,OAAO,MAAM,CAAC,CAAC,CAAC,CAAC;AAC3E,4BAAc,UAAU,aAAa,CAAC,GAAG,CAAC,CAAC;AAC3C,4BAAc,QAAQ,aAAa,QAAQ;AAC3C,6BAAe,KAAK,WAAW;AAC/B,2BAAa;AAAA,YACf,WAAW,QAAQ,GAAG;AACpB,oBAAM,OAAO,OAAO,GAAG,KAAK,EAAE,OAAO,CAAC,CAAC,CAAC;AACxC,6BAAe,KAAK,UAAU,GAAG,IAAI,CAAC;AACtC,2BAAa;AAAA,YACf,OAAO;AACL,6BAAe,KAAK,CAAC;AAAA,YACvB;AAAA,UACF;AACA,cAAI,IAAI,KAAK,cAAc,cAAc;AACzC,gBAAM,QAAQ,EAAE;AAChB,cAAI,YAAY;AACd,gBAAI,SAAS,MAAM;AACjB,oBAAM,SAAS,EAAE;AACjB,oBAAM,SAAS,OAAO;AACtB,oBAAM,YAAY,OAAO,SAAS;AAClC,oBAAM,WAAW,CAAC,SAAS,EAAE,OAAO,OAAO,MAAM,GAAG,OAAO,SAAS,CAAC,CAAC;AACtE,kBAAI,QAAQ,UAAU,QAAQ,GAAG,CAAC,IAAI,SAAS,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC,GAAG,QAAQ;AAAA,YACtE,WAAW,QAAQ,GAAG;AACpB,oBAAM,OAAO,CAAC,QAAQ,CAAC,EAAE,OAAO,OAAO,GAAG,QAAQ,CAAC,CAAC;AACpD,kBAAI,UAAU,GAAG,IAAI;AAAA,YACvB;AAAA,UACF;AACA,iBAAO;AAAA,QACT;AAAA,MACF,OAAO;AACL,eAAO,KAAK,cAAc,MAAM;AAAA,MAClC;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa;AACb,QAAI;AACJ,QAAI,WAAW,MAAM,MAAM;AACzB,oBAAc;AAAA,IAChB,OAAO;AACL,oBAAc,WAAW,GAAG,MAAM,CAAC;AAAA,IACrC;AACA,aAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,YAAM,QAAQ,WAAW,OAAO,OAAO,OAAO,WAAW,IAAI,MAAM,CAAC;AACpE,oBAAc,KAAK,gCAAgC,aAAa,KAAK;AAAA,IACvE;AACA,QAAI,aAAa,CAAC;AAClB,eAAW,SAAS,YAAY;AAC9B,UAAI,SAAS,QAAQ,MAAM,OAAO,MAAM;AACtC,mBAAW,KAAK,MAAM,EAAE;AAAA,MAC1B;AAAA,IACF;AACA,iBAAa,QAAQ,UAAU;AAC/B,QAAI,WAAW,WAAW,GAAG;AAC3B,oBAAc,WAAW,OAAO,WAAW;AAAA,IAC7C,OAAO;AACL,oBAAc,CAAC,IAAI,EAAE,OAAO,WAAW;AAAA,IACzC;AACA,WAAO;AAAA,EACT;AAAA,EACA,YAAY,QAAQT,OAAM;AACxB,WAAO,KAAK,MAAM;AAChB,UAAIA,SAAQ,MAAM;AAChB,eAAO;AAAA,MACT;AACA,UAAI,CAAC,MAAM,QAAQA,KAAI,GAAG;AACxB,cAAM,IAAI,WAAW,2BAA2B;AAAA,MAClD;AACA,UAAI,CAAC,MAAM,QAAQ,MAAM,GAAG;AAC1B,cAAM,IAAI,WAAW,6BAA6B;AAAA,MACpD;AACA,UAAIA,MAAK,WAAW,OAAO,QAAQ;AACjC,cAAM,IAAI,WAAW,mGAAmG,OAAO,aAAaA,MAAK,SAAS;AAAA,MAC5J;AACA,UAAIA,MAAK,MAAM,CAAC,MAAM,KAAK,IAAI,GAAG;AAChC,eAAO;AAAA,MACT;AACA,MAAAA,QAAOA,MAAK,IAAI,CAAC,MAAM,KAAK,OAAO,IAAI,WAAW,GAAG,CAAC,CAAC;AACvD,UAAI,SAASA,MAAK;AAClB,eAAS,KAAK,GAAG,KAAKA,MAAK,SAAS,GAAG,EAAE,IAAI;AAC3C,iBAAS,WAAW,QAAQA,MAAK,GAAG;AAAA,MACtC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,IAAI,OAAO,cAAc,MAAM;AAAA,EAC7B,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,cAAc,QAAQ;AACpB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,OAAO,GAAG,MAAM;AAC7B,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,iBAAS,KAAK,QAAQ,OAAO,GAAG;AAAA,MAClC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,KAAK,YAAY;AACjB,sBAAsB,cAAc,IAAI;AACxC,IAAI,YAAY,cAAc,MAAM;AAAA,EAClC,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,cAAc,QAAQ;AACpB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,OAAO,GAAG,MAAM;AAC7B,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,iBAAS,IAAI,QAAQ,OAAO,GAAG;AAAA,MACjC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,UAAU,YAAY;AACtB,sBAAsB,cAAc,SAAS;AAC7C,IAAI,UAAU,cAAc,MAAM;AAAA,EAChC,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,cAAc,QAAQ;AACpB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,OAAO,GAAG,MAAM;AAC7B,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,iBAAS,KAAK,QAAQ,OAAO,GAAG;AAAA,MAClC;AACA,aAAO,IAAI,IAAI,OAAO,QAAQ,MAAM;AAAA,IACtC,CAAC;AAAA,EACH;AACF;AACA,QAAQ,YAAY;AACpB,sBAAsB,cAAc,OAAO;AAC3C,IAAI,WAAW,cAAc,MAAM;AAAA,EACjC,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,cAAc,QAAQ;AACpB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,OAAO;AACpB,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,iBAAS,QAAQ,QAAQ,OAAO,GAAG;AAAA,MACrC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,WAAW,cAAc,MAAM;AAAA,EACjC,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,cAAc,QAAQ;AACpB,WAAO,KAAK,MAAM;AAChB,UAAI,SAAS,OAAO;AACpB,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,iBAAS,QAAQ,QAAQ,OAAO,GAAG;AAAA,MACrC;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,SAAS,YAAY;AACrB,sBAAsB,cAAc,QAAQ;AAC5C,IAAI,cAAc,cAAc,MAAM;AAAA,EACpC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,eAAe;AACpB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,eAAe,KAAK;AACzD,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AAAA,EACzB;AAAA,EACA,MAAM,YAAY;AAChB,QAAI,EAAE,MAAM,QAAQ,UAAU,KAAK,MAAM,QAAQ,WAAW,EAAE,MAAM,WAAW,WAAW,GAAG;AAC3F,YAAM,IAAI,WAAW,uEAAuE;AAAA,IAC9F;AACA,iBAAa;AACb,QAAI,eAAe;AACnB,eAAW,SAAS,YAAY;AAC9B,UAAI,SAAS,MAAM;AACjB,uBAAe;AACf;AAAA,MACF;AAAA,IACF;AACA,QAAI,cAAc;AAChB;AAAA,IACF;AACA,UAAM,WAAW,CAAC;AAClB,aAAS,KAAK,GAAG,KAAK,WAAW,QAAQ,EAAE,IAAI;AAC7C,YAAM,yBAAyB,WAAW,IAAI,MAAM;AACpD,6BAAuB,OAAO,KAAK,MAAM,CAAC;AAC1C,UAAI,SAAS;AACb,iBAAW,SAAS,UAAU;AAC5B,YAAI,aAAa,YAAY,OAAO,sBAAsB,GAAG;AAC3D,mBAAS;AACT;AAAA,QACF;AAAA,MACF;AACA,UAAI,CAAC,QAAQ;AACX,iBAAS,KAAK,sBAAsB;AAAA,MACtC;AAAA,IACF;AACA,QAAI,SAAS,SAAS,GAAG;AACvB,YAAM,IAAI,WAAW,8GAA8G,KAAK,UAAU,UAAU,CAAC;AAAA,IAC/J;AAAA,EACF;AAAA,EACA,cAAc,QAAQ;AACpB,WAAO,KAAK,MAAM;AAChB,aAAO,YAAY,QAAQ,KAAK,IAAI;AAAA,IACtC,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,YAAY;AAC7B,QAAI,EAAE,MAAM,QAAQ,UAAU,KAAK,MAAM,QAAQ,WAAW,EAAE,IAAI;AAChE,YAAM,IAAI,WAAW,6DAA6D;AAAA,IACpF;AACA,UAAM,cAAc;AACpB,UAAM,cAAc,YAAY,GAAG,MAAM;AACzC,UAAM,OAAO,KAAK,OAAO,IAAI,YAAY,SAAS,KAAK,OAAO,KAAK;AACnE,eAAW,SAAS,YAAY,MAAM,CAAC,GAAG;AACxC,UAAI,YAAY,SAAS,QAAQ,MAAM,SAAS,MAAM;AACpD,oBAAY,QAAQ;AACpB;AAAA,MACF;AACA,kBAAY,SAAS,MAAM;AAAA,IAC7B;AACA,WAAO;AAAA,EACT;AAAA,EACA,YAAY,QAAQA,OAAM;AACxB,QAAIA,SAAQ,MAAM;AAChB,aAAO;AAAA,IACT;AACA,QAAI,CAAC,MAAM,QAAQA,KAAI,GAAG;AACxB,YAAM,IAAI,WAAW,2CAA2C;AAAA,IAClE;AACA,QAAI,CAAC,MAAM,QAAQ,MAAM,GAAG;AAC1B,YAAM,IAAI,WAAW,6CAA6C;AAAA,IACpE;AACA,QAAIA,MAAK,WAAW,OAAO,QAAQ;AACjC,YAAM,IAAI,WAAW,mCAAmCA,MAAK,qCAAqC,OAAO,SAAS;AAAA,IACpH;AACA,WAAO,KAAK,MAAM;AAChB,UAAI,eAAe;AACnB,MAAAA,MAAK,QAAQ,CAAC,MAAM;AAClB,YAAI,KAAK,MAAM;AACb,yBAAe;AACf;AAAA,QACF;AAAA,MACF,CAAC;AACD,UAAI,cAAc;AAChB,eAAO;AAAA,MACT;AACA,YAAM,cAAc,CAAC;AACrB,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,YAAIA,MAAK,OAAO,MAAM;AACpB,sBAAY,KAAK,KAAK,SAAS,OAAO,GAAG,GAAG,MAAM,CAAC;AAAA,QACrD,WAAWA,MAAK,IAAI,OAAO,OAAO,IAAI,MAAM;AAC1C,sBAAY,KAAK,WAAWA,MAAK,KAAK,EAAE,CAAC;AAAA,QAC3C,OAAO;AACL,sBAAY,KAAKA,MAAK,GAAG;AAAA,QAC3B;AAAA,MACF;AACA,YAAM,oBAAoB,OAAO,aAAa,KAAK,IAAI;AACvD,aAAO,IAAI,mBAAmB,IAAI,KAAK;AAAA,IACzC,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMS,UAAS;AAAA,MACb,QAAQ,KAAK;AAAA,IACf;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,YAAY,YAAY;AACxB,sBAAsB,cAAc,WAAW;AAC/C,SAAS,cAAc,MAAM,KAAK;AAChC,SAAO,OAAO,GAAG;AACf,YAAQ;AAAA,EACV;AACA,SAAO;AACT;AACA,SAAS,SAAS,GAAG,GAAG,MAAM;AAC5B,MAAI,EAAE,MAAM,SAAS,KAAK,EAAE,MAAM,SAAS,GAAG;AAC5C,UAAM,IAAI,oBAAoB,kEAAkE;AAAA,EAClG;AACA,eAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,uDAAuD,EAAE,MAAM,QAAQ;AACtH,eAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,uDAAuD,EAAE,MAAM,QAAQ;AACtH,MAAI,OAAO,SAAS,UAAU;AAC5B,WAAO,CAAC,MAAM,IAAI;AAAA,EACpB;AACA,MAAI,EAAE,UAAU,eAAe,EAAE,UAAU,aAAa;AACtD,UAAM,IAAI,oBAAoB,6DAA6D;AAAA,EAC7F;AACA,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,EAAE,MAAM;AACtB,MAAI,QAAQ,MAAM;AAChB,WAAO,CAAC,QAAQ,GAAG,QAAQ,CAAC;AAAA,EAC9B;AACA,QAAM,YAAY;AAClB,SAAO,KAAK,MAAM;AAChB,QAAI;AACJ,QAAI,QAAQ,OAAO;AACjB,aAAO,QAAQ;AACf,YAAM,YAAY,CAAC;AACnB,eAAS,KAAK,GAAG,KAAK,MAAM,EAAE,IAAI;AAChC,kBAAU,KAAK,CAAC;AAAA,MAClB;AACA,UAAI,QAAQ,GAAG,EAAE,MAAM,OAAO,SAAS,CAAC;AAAA,IAC1C,WAAW,QAAQ,OAAO;AACxB,aAAO,QAAQ;AACf,YAAM,YAAY,CAAC;AACnB,eAAS,KAAK,GAAG,KAAK,MAAM,EAAE,IAAI;AAChC,kBAAU,KAAK,CAAC;AAAA,MAClB;AACA,UAAI,QAAQ,GAAG,EAAE,MAAM,OAAO,SAAS,CAAC;AAAA,IAC1C,OAAO;AACL,aAAO;AAAA,IACT;AACA,QAAI;AACJ,QAAI,EAAE,MAAM,WAAW,KAAK,EAAE,MAAM,WAAW,GAAG;AAChD,UAAI,UAAU,OAAO,UAAU,IAAI;AACjC,cAAM,KAAK,IAAI,GAAG,CAAC,GAAG,UAAU,EAAE;AAAA,MACpC,OAAO;AACL,cAAM,KAAK,IAAI,UAAU,GAAG,CAAC,GAAG,CAAC,CAAC,GAAG,CAAC,GAAG,UAAU,EAAE;AAAA,MACvD;AAAA,IACF,OAAO;AACL,YAAM,OAAO,UAAU,OAAO,EAAE,MAAM,SAAS;AAC/C,YAAM,OAAO,UAAU,OAAO,EAAE,MAAM,SAAS;AAC/C,YAAM,OAAO,GAAG,GAAG,MAAM,IAAI;AAAA,IAC/B;AACA,QAAI,OAAO,GAAG;AACZ,UAAI;AACJ,UAAI,QAAQ,OAAO;AACjB,cAAM,QAAQ,QAAQ;AAAA,MACxB,OAAO;AACL,cAAM,QAAQ;AAAA,MAChB;AACA,YAAM,cAAc,CAAC;AACrB,eAAS,KAAK,KAAK,KAAK,MAAM,MAAM,EAAE,IAAI;AACxC,oBAAY,KAAK,EAAE;AAAA,MACrB;AACA,YAAM,QAAQ,KAAK,WAAW;AAAA,IAChC;AACA,QAAI,IAAI,MAAM,WAAW,GAAG;AAC1B,YAAM,WAAW,KAAK,CAAC;AAAA,IACzB;AACA,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,MAAM,cAAc,MAAM;AAAA,EAC5B,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,OAAO,KAAK;AACjB,SAAK,YAAY,KAAK,aAAa,OAAO,QAAQ,KAAK;AACvD,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AAAA,EACzB;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,OAAO,MAAM,QAAQ,UAAU,KAAK,WAAW,WAAW,KAAK,MAAM,QAAQ,WAAW,EAAE,KAAK,MAAM,QAAQ,WAAW,EAAE,GAAG,MAAM,+DAA+D;AAC/M,UAAM,SAAS,WAAW;AAC1B,UAAM,SAAS,WAAW;AAC1B,QAAI,OAAO,SAAS,KAAK,OAAO,SAAS,GAAG;AAC1C,YAAM,IAAI,oBAAoB,8DAA8D;AAAA,IAC9F;AACA,UAAM,OAAO,KAAK,cAAc,QAAQ,MAAM;AAC9C,QAAI,OAAO,KAAK,QAAQ,OAAO,KAAK,KAAK;AACvC,YAAM,IAAI,WAAW,8BAA8B,OAAO,KAAK,WAAW,OAAO,KAAK,KAAK;AAAA,IAC7F;AAAA,EACF;AAAA,EACA,cAAc,QAAQ;AACpB,QAAI,OAAO,WAAW,GAAG;AACvB,YAAM,IAAI,WAAW,oEAAoE,OAAO,kBAAkB;AAAA,IACpH;AACA,QAAI,KAAK,OAAO;AAChB,QAAI,KAAK,OAAO;AAChB,QAAI;AACJ,QAAI,CAAC,MAAM,QAAQ,KAAK,IAAI,GAAG;AAC7B,aAAO;AAAA,QACL,cAAc,KAAK,MAAM,GAAG,MAAM,MAAM;AAAA,QACxC,cAAc,KAAK,MAAM,GAAG,MAAM,MAAM;AAAA,MAC1C;AAAA,IACF,OAAO;AACL,aAAO,KAAK,KAAK,IAAI,CAAC,MAAM,OAAO,cAAc,MAAM,OAAO,IAAI,MAAM,MAAM,CAAC;AAAA,IACjF;AACA,QAAI,KAAK,WAAW;AAClB,WAAK,YAAY,IAAI,KAAK,EAAE;AAC5B,WAAK,YAAY,IAAI,KAAK,EAAE;AAAA,IAC9B;AACA,WAAO,SAAS,IAAI,IAAI,IAAI;AAAA,EAC9B;AAAA,EACA,cAAc,QAAQ,QAAQ;AAC5B,QAAI;AACJ,QAAI,CAAC,MAAM,QAAQ,KAAK,IAAI,GAAG;AAC7B,aAAO;AAAA,QACL,cAAc,KAAK,MAAM,OAAO,MAAM;AAAA,QACtC,cAAc,KAAK,MAAM,OAAO,MAAM;AAAA,MACxC;AAAA,IACF,OAAO;AACL,aAAO,KAAK;AAAA,IACd;AACA,WAAO;AAAA,EACT;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,OAAO,MAAM,QAAQ,UAAU,KAAK,WAAW,WAAW,KAAK,MAAM,QAAQ,WAAW,EAAE,KAAK,MAAM,QAAQ,WAAW,EAAE,GAAG,MAAM,+DAA+D;AAC/M,UAAM,SAAS,WAAW,GAAG,MAAM;AACnC,UAAM,SAAS,WAAW,GAAG,MAAM;AACnC,QAAI,OAAO,SAAS,KAAK,OAAO,SAAS,GAAG;AAC1C,YAAM,IAAI,oBAAoB,8DAA8D;AAAA,IAC9F;AACA,UAAM,OAAO,KAAK,cAAc,QAAQ,MAAM;AAC9C,WAAO,OAAO,KAAK,IAAI,CAAC;AACxB,WAAO,OAAO,KAAK,IAAI,CAAC;AACxB,WAAO,OAAO,GAAG,CAAC;AAClB,UAAM,cAAc,OAAO,OAAO,MAAM;AACxC,QAAI,YAAY,WAAW,GAAG;AAC5B,kBAAY,KAAK,CAAC;AAAA,IACpB;AACA,WAAO;AAAA,EACT;AAAA,EACA,YAAY,QAAQT,OAAM;AACxB,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAMS,UAAS;AAAA,MACb,QAAQ,KAAK;AAAA,MACb,aAAa,KAAK;AAAA,IACpB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,IAAI,YAAY;AAChB,sBAAsB,cAAc,GAAG;AAGvC,IAAI,gBAAgB,cAAc,MAAM;AAAA,EACtC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,kBAAkB;AACvB,SAAK,SAAS,KAAK;AAAA,EACrB;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMA,UAAS,EAAE,QAAQ,KAAK,OAAO;AACrC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,YAAM,SAAS,oBAAoB,MAAM;AACzC,YAAM,SAAS,MAAM,KAAK,cAAc,OAAO,OAAO,GAAG,KAAK,MAAM,GAAG,MAAM;AAC7E,YAAM,SAAS,aAAa,QAAQ,MAAM,QAAQ,OAAO,eAAe,KAAK;AAC7E,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,cAAc,YAAY;AAC1B,sBAAsB,cAAc,aAAa;AACjD,IAAI,kBAAkB,cAAc,MAAM;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,kBAAkB;AACvB,SAAK,OAAO,KAAK;AAAA,EACnB;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMA,UAAS,EAAE,MAAM,KAAK,KAAK;AACjC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,YAAM,SAAS,oBAAoB,MAAM;AACzC,UAAI,KAAK,OAAO,KAAK,KAAK,OAAO,GAAG;AAClC,cAAM,SAAS,MAAM;AACnB,gBAAM,SAAS,KAAK,KAAK,KAAK,QAAQ,IAAI,KAAK,KAAK;AACpD,iBAAO,IAAI,QAAQ,cAAc,OAAO,OAAO,GAAG,MAAM,CAAC;AAAA,QAC3D;AACA,eAAO,aAAa,QAAQ,MAAM,QAAQ,OAAO,eAAe,KAAK;AAAA,MACvE;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,IAAI,eAAe,cAAc,MAAM;AAAA,EACrC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,kBAAkB;AACvB,SAAK,OAAO,KAAK;AACjB,SAAK,aAAa,KAAK;AAAA,EACzB;AAAA,EACA,eAAe,QAAQ;AACrB,WAAO,KAAK,cAAc,oBAAoB,MAAM,EAAE;AAAA,EACxD;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO;AAAA,EACT;AAAA,EACA,YAAY;AACV,UAAM,aAAa,MAAM,UAAU;AACnC,UAAMA,UAAS,EAAE,MAAM,KAAK,KAAK;AACjC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,UAAI,KAAK,OAAO,KAAK,KAAK,OAAO,GAAG;AAClC,cAAM,aAAa,KAAK,eAAe,MAAM;AAC7C,cAAM,gBAAgB,MAAM;AAC1B,gBAAM,SAAS,oBAAoB,MAAM;AACzC,gBAAMQ,SAAQ;AACd,gBAAMD,UAAS;AACf,gBAAM,SAAS,CAACC,SAAQD;AACxB,cAAI,UAAU,aAAa,cAAc,UAAU,GAAG,KAAK,IAAI;AAC/D,oBAAU,MAAM,SAAS,SAAS;AAClC,gBAAM,MAAM,IAAI,KAAK,SAAS,IAAI,KAAK,OAAO,UAAU,OAAO;AAC/D,gBAAM,IAAI,CAAC,IAAI,SAAS,KAAK;AAC7B,gBAAM,IAAI,KAAK,IAAI,QAAQ,OAAO,GAAG,IAAI,KAAK,SAAS,EAAE,GAAG,MAAM,CAAC;AACnE,iBAAO,KAAK,IAAI,GAAG,CAAC,GAAG,CAAC;AAAA,QAC1B;AACA,eAAO,aAAa,eAAe,MAAM,oBAAoB,MAAM,GAAG,OAAO,eAAe,KAAK;AAAA,MACnG;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAGhD,SAAS,mBAAmB,GAAG,OAAO,UAAU,MAAM,OAAO,WAAW,MAAM;AAC5E,MAAI;AACJ,MAAI,EAAE,SAAS,GAAG;AAChB,UAAM,YAAY,GAAG,OAAO,UAAU,MAAM,OAAO,QAAQ;AAAA,EAC7D,WAAW,EAAE,SAAS,GAAG;AACvB,UAAM,YAAY,GAAG,OAAO,UAAU,MAAM,OAAO,QAAQ;AAAA,EAC7D,WAAW,EAAE,SAAS,GAAG;AACvB,UAAM,YAAY,GAAG,OAAO,UAAU,MAAM,OAAO,QAAQ;AAAA,EAC7D,OAAO;AACL,UAAM,IAAI,oBAAoB,2DAA2D,EAAE,UAAU;AAAA,EACvG;AACA,SAAO;AACT;AACA,SAAS,gCAAgC,GAAG,OAAO,MAAM,eAAe,WAAW,MAAM;AACvF,SAAO,KAAK,MAAM;AAChB,UAAM,kBAAkB,QAAQ,GAAG,aAAa;AAChD,UAAM,QAAQ,gBAAgB;AAC9B,UAAM,WAAW,gBAAgB;AACjC,UAAM,SAAS,mBAAmB,GAAG,OAAO,UAAU,MAAM,OAAO,QAAQ;AAC3E,WAAO,CAAC,QAAQ,OAAO,QAAQ;AAAA,EACjC,CAAC;AACH;AACA,SAAS,kCAAkC,GAAG,OAAO,MAAM,eAAe,WAAW,MAAM;AACzF,SAAO,KAAK,MAAM;AAChB,UAAM,kBAAkB,QAAQ,GAAG,aAAa;AAChD,UAAM,QAAQ,gBAAgB;AAC9B,UAAM,WAAW,gBAAgB;AACjC,UAAM,cAAc,CAAC;AACrB,eAAW,QAAQ,OAAO,GAAG,EAAE,IAAI,GAAG;AACpC,UAAI,cAAc,QAAQ,IAAI,MAAM,IAAI;AACtC,oBAAY,KAAK,CAAC;AAAA,MACpB,OAAO;AACL,oBAAY,KAAK,EAAE,MAAM,KAAK;AAAA,MAChC;AAAA,IACF;AACA,UAAM,gBAAgB,QAAQ,OAAO,WAAW;AAChD,UAAM,oBAAoB,QAAQ,UAAU,WAAW;AACvD,UAAM,iBAAiB,SAAS,OAAO,OAAO,QAAQ,OAAO,WAAW;AACxE,UAAM,gBAAgB,QAAQ,OAAO,OAAO,QAAQ,MAAM,WAAW;AACrE,UAAM,SAAS,mBAAmB,GAAG,eAAe,mBAAmB,eAAe,gBAAgB,QAAQ;AAC9G,WAAO,CAAC,QAAQ,OAAO,QAAQ;AAAA,EACjC,CAAC;AACH;AACA,SAAS,yBAAyB,GAAG,OAAO,MAAM,eAAe,WAAW,MAAM;AAChF,MAAI,aAAa,YAAY,cAAc,MAAM,EAAE,KAAK,GAAG,OAAO,GAAG,EAAE,OAAO,CAAC,CAAC,GAAG;AACjF,WAAO,gCAAgC,GAAG,OAAO,MAAM,eAAe,QAAQ;AAAA,EAChF,OAAO;AACL,WAAO,kCAAkC,GAAG,OAAO,MAAM,eAAe,QAAQ;AAAA,EAClF;AACF;AACA,IAAI,qBAAqB,cAAc,MAAM;AAAA,EAC3C,YAAY,MAAM;AAChB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,UAAM,IAAI;AACV,SAAK,kBAAkB;AACvB,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,KAAK;AAC1C,SAAK,WAAW,KAAK,YAAY,OAAO,OAAO,KAAK;AACpD,SAAK,UAAU,KAAK,WAAW,OAAO,OAAO,KAAK;AAClD,SAAK,SAAS,KAAK,UAAU,OAAO,OAAO,KAAK;AAChD,SAAK,QAAQ,KAAK,SAAS,OAAO,OAAO,KAAK;AAC9C,SAAK,kBAAkB,eAAe,KAAK,mBAAmB,OAAO;AACrE,SAAK,mBAAmB,eAAe,KAAK,oBAAoB,MAAM;AACtE,SAAK,wBAAwB,eAAe,KAAK,yBAAyB,OAAO;AACjF,SAAK,4BAA4B,eAAe,KAAK,6BAA6B,MAAM;AACxF,SAAK,iBAAiB,cAAc,KAAK,cAAc;AACvD,SAAK,kBAAkB,cAAc,KAAK,eAAe;AACzD,SAAK,kBAAkB,eAAe,KAAK,eAAe;AAC1D,SAAK,mBAAmB,eAAe,KAAK,gBAAgB;AAAA,EAC9D;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,OAAO,KAAK,QAAQ,IAAI,KAAK,OAAO,KAAK,OAAO,WAAW;AACjE,UAAM,MAAM,WAAW;AACvB,QAAI,OAAO,MAAM;AACf,YAAM,IAAI,WAAW,QAAQ,mGAAmG,KAAK,UAAU,UAAU,IAAI;AAAA,IAC/J;AACA,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,WAAW,QAAQ,MAAM,EAAE,CAAC,OAAO,IAAI,EAAE,CAAC,CAAC;AACnF,UAAM,QAAQ,CAAC,GAAG;AAClB,QAAI,KAAK,OAAO;AACd,WAAK,QAAQ,KAAK,UAAU,SAAS,OAAO,MAAM,KAAK,kBAAkB,KAAK,kBAAkB,MAAM,KAAK,eAAe;AAAA,IAC5H;AACA,QAAI,KAAK,QAAQ;AACf,WAAK,OAAO,KAAK,UAAU,QAAQ,OAAO,MAAM,KAAK,iBAAiB,KAAK,iBAAiB,MAAM,KAAK,cAAc;AAAA,IACvH;AACA,SAAK,aAAa,KAAK,UAAU,eAAe,OAAO,MAAM,KAAK,uBAAuB,MAAM,KAAK;AACpG,SAAK,iBAAiB,KAAK,UAAU,mBAAmB,OAAO,MAAM,KAAK,2BAA2B,MAAM,KAAK;AAChH,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAM,WAAW,OAAO,eAAe,OAAO,QAAQ,OAAO;AAC7D,YAAM,SAAS,oBAAoB,MAAM;AACzC,YAAM,aAAa,OAAO;AAC1B,YAAM,OAAO,WAAW;AACxB,YAAM,gBAAgB,OAAO,GAAG,IAAI;AACpC,YAAM,OAAO,KAAK,QAAQ,IAAI,KAAK,OAAO,KAAK,OAAO;AACtD,oBAAc,OAAO,MAAM,CAAC;AAC5B,YAAM,iBAAiB,aAAa,GAAG,IAAI;AAC3C,qBAAe,QAAQ,WAAW;AAClC,YAAM,sBAAsB,cAAc,MAAM;AAChD,0BAAoB,KAAK;AACzB,YAAM,oBAAoB,CAAC,aAAa,YAAY,qBAAqB,OAAO,GAAG,IAAI,EAAE,MAAM,GAAG,OAAO,CAAC,CAAC;AAC3G,YAAM,qBAAqB,MAAM;AAC/B,YAAI,mBAAmB;AACrB,gBAAM,sBAAsB,QAAQ,KAAK,WAAW,KAAK,GAAG,cAAc;AAC1E,gBAAM,0BAA0B,QAAQ,KAAK,eAAe,KAAK,GAAG,cAAc;AAClF,gBAAM,gBAAgB,KAAK,SAAS,QAAQ,KAAK,KAAK,KAAK,GAAG,cAAc,IAAI;AAChF,gBAAM,iBAAiB,KAAK,QAAQ,QAAQ,KAAK,MAAM,KAAK,GAAG,cAAc,IAAI;AACjF,iBAAO,mBAAmB,QAAQ,qBAAqB,yBAAyB,eAAe,gBAAgB,KAAK,OAAO;AAAA,QAC7H,OAAO;AACL,iBAAO,mBAAmB,QAAQ,KAAK,WAAW,KAAK,GAAG,KAAK,eAAe,KAAK,GAAG,KAAK,QAAQ,OAAO,OAAO,KAAK,KAAK,KAAK,GAAG,KAAK,SAAS,OAAO,OAAO,KAAK,MAAM,KAAK,GAAG,KAAK,OAAO;AAAA,QAChM;AAAA,MACF;AACA,UAAI,CAAC,UAAU;AACb,eAAO,mBAAmB;AAAA,MAC5B;AACA,YAAM,CAAC,gBAAgB,OAAO,QAAQ,IAAI,yBAAyB,QAAQ,KAAK,MAAM,KAAK,GAAG,KAAK,KAAK,KAAK,GAAG,eAAe,KAAK,OAAO;AAC3I,YAAM,kBAAkB,CAAC,WAAW,OAAO,aAAa;AACtD,aAAK,MAAM;AACT,gBAAM,QAAQ,IAAI;AAClB,gBAAM,YAAY,UAAU,KAAK;AACjC,gBAAM,cAAc,IAAI,IAAI,WAAW,KAAK,GAAG,KAAK;AACpD,oBAAU,MAAM,IAAI,WAAW,WAAW,CAAC;AAAA,QAC7C,CAAC;AAAA,MACH;AACA,YAAM,8BAA8B,MAAM;AACxC,wBAAgB,KAAK,YAAY,OAAO,KAAK,QAAQ;AACrD,wBAAgB,KAAK,gBAAgB,UAAU,KAAK,QAAQ;AAAA,MAC9D;AACA,kCAA4B;AAC5B,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMP,UAAS;AAAA,MACb,MAAM,KAAK;AAAA,MACX,UAAU,KAAK;AAAA,MACf,SAAS,KAAK;AAAA,MACd,QAAQ,KAAK;AAAA,MACb,OAAO,KAAK;AAAA,MACZ,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,kBAAkB,qBAAqB,KAAK,gBAAgB;AAAA,MAC5D,uBAAuB,qBAAqB,KAAK,qBAAqB;AAAA,MACtE,2BAA2B,qBAAqB,KAAK,yBAAyB;AAAA,MAC9E,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,kBAAkB,qBAAqB,KAAK,gBAAgB;AAAA,MAC5D,gBAAgB,oBAAoB,KAAK,cAAc;AAAA,MACvD,iBAAiB,oBAAoB,KAAK,eAAe;AAAA,IAC3D;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,mBAAmB,YAAY;AAC/B,sBAAsB,cAAc,kBAAkB;AACtD,IAAI,qBAAqB,cAAc,MAAM;AAAA,EAC3C,YAAY,MAAM;AAChB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,UAAM,IAAI;AACV,SAAK,OAAO,KAAK,QAAQ,OAAO,KAAK,KAAK;AAC1C,QAAI,OAAO,KAAK,SAAS,UAAU;AACjC,UAAI,CAAC,OAAO,UAAU,KAAK,IAAI,GAAG;AAChC,cAAM,IAAI,MAAM,gDAAgD,KAAK,MAAM;AAAA,MAC7E;AAAA,IACF,WAAW,MAAM,QAAQ,KAAK,IAAI,GAAG;AACnC,iBAAW,QAAQ,KAAK,MAAM;AAC5B,YAAI,CAAC,OAAO,UAAU,IAAI,GAAG;AAC3B,gBAAM,IAAI,MAAM,0DAA0D,KAAK,UAAU,KAAK,IAAI,GAAG;AAAA,QACvG;AAAA,MACF;AAAA,IACF,OAAO;AACL,YAAM,IAAI,MAAM,wEAAwE,KAAK,UAAU,KAAK,IAAI,GAAG;AAAA,IACrH;AACA,SAAK,UAAU,KAAK,WAAW,OAAO,OAAO,KAAK;AAClD,SAAK,SAAS,KAAK,UAAU,OAAO,OAAO,KAAK;AAChD,SAAK,QAAQ,KAAK,SAAS,OAAO,OAAO,KAAK;AAC9C,SAAK,kBAAkB,eAAe,KAAK,mBAAmB,OAAO;AACrE,SAAK,mBAAmB,eAAe,KAAK,oBAAoB,MAAM;AACtE,SAAK,kBAAkB,eAAe,KAAK,eAAe;AAC1D,SAAK,mBAAmB,eAAe,KAAK,gBAAgB;AAC5D,SAAK,kBAAkB;AAAA,EACzB;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,QAAQ,WAAW;AACzB,QAAI,OAAO,KAAK,SAAS,UAAU;AACjC,WAAK,OAAO,CAAC,KAAK,IAAI;AAAA,IACxB;AACA,aAAS,KAAK,GAAG,KAAK,KAAK,KAAK,QAAQ,EAAE,IAAI;AAC5C,UAAI,KAAK,KAAK,MAAM,GAAG;AACrB,aAAK,KAAK,OAAO;AAAA,MACnB;AAAA,IACF;AACA,eAAW,QAAQ,KAAK,MAAM;AAC5B,UAAI,OAAO,KAAK,QAAQ,OAAO;AAC7B,cAAM,IAAI,MAAM,iBAAiB,MAAM;AAAA,MACzC;AAAA,IACF;AACA,QAAI,KAAK,KAAK,WAAW,QAAQ,KAAK,IAAI,EAAE,QAAQ;AAClD,YAAM,IAAI,MAAM,4BAA4B,KAAK,MAAM;AAAA,IACzD;AACA,UAAM,aAAa,KAAK,KAAK,IAAI,CAAC,SAAS,WAAW,KAAK;AAC3D,UAAM,YAAY;AAClB,QAAI,KAAK,OAAO;AACd,WAAK,QAAQ,KAAK,UAAU,SAAS,YAAY,WAAW,KAAK,kBAAkB,KAAK,kBAAkB,SAAS;AAAA,IACrH,OAAO;AACL,WAAK,QAAQ;AAAA,IACf;AACA,QAAI,KAAK,QAAQ;AACf,WAAK,OAAO,KAAK,UAAU,QAAQ,YAAY,WAAW,KAAK,iBAAiB,KAAK,iBAAiB,SAAS;AAAA,IACjH,OAAO;AACL,WAAK,OAAO;AAAA,IACd;AACA,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,UAAM,SAAS,oBAAoB,MAAM;AACzC,UAAM,aAAa,OAAO;AAC1B,UAAM,QAAQ,WAAW;AACzB,WAAO,KAAK,MAAM;AAChB,YAAM,WAAW;AACjB,UAAI,EAAE,MAAM,OAAO,SAAS,IAAI,QAAQ,QAAQ,KAAK,MAAM,QAAQ;AACnE,YAAM,iBAAiB,aAAa,GAAG,KAAK;AAC5C,iBAAW,OAAO,KAAK,MAAM;AAC3B,uBAAe,OAAO,WAAW;AAAA,MACnC;AACA,YAAM,YAAY,CAAC,MAAM;AACvB,YAAI,KAAK,QAAQ,EAAE,MAAM,WAAW,OAAO;AACzC,iBAAO,QAAQ,GAAG,cAAc;AAAA,QAClC,OAAO;AACL,iBAAO;AAAA,QACT;AAAA,MACF;AACA,UAAIO,UAAS,KAAK,QAAQ,UAAU,KAAK,MAAM,KAAK,CAAC,IAAI;AACzD,UAAI,SAAS,KAAK,SAAS,UAAU,KAAK,KAAK,KAAK,CAAC,IAAI;AACzD,YAAM,gBAAgB,CAAC;AACvB,YAAM,oBAAoB,CAAC;AAC3B,eAAS,KAAK,GAAG,KAAK,OAAO,EAAE,IAAI;AACjC,YAAI,KAAK,KAAK,QAAQ,EAAE,MAAM,IAAI;AAChC,wBAAc,KAAK,WAAW,GAAG;AACjC,4BAAkB,KAAK,CAAC;AAAA,QAC1B,OAAO;AACL,wBAAc,KAAK,CAAC;AACpB,4BAAkB,KAAK,WAAW,GAAG;AAAA,QACvC;AAAA,MACF;AACA,cAAQ,KAAK,OAAO,aAAa;AACjC,iBAAW,KAAK,UAAU,aAAa;AACvC,UAAIA,WAAU,MAAM;AAClB,QAAAA,UAAS,KAAKA,SAAQ,iBAAiB;AAAA,MACzC;AACA,UAAI,UAAU,MAAM;AAClB,iBAAS,KAAK,QAAQ,iBAAiB;AAAA,MACzC;AACA,aAAO,mBAAmB,QAAQ,OAAO,UAAU,QAAQA,SAAQ,KAAK,OAAO;AAAA,IACjF,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMP,UAAS;AAAA,MACb,MAAM,KAAK;AAAA,MACX,SAAS,KAAK;AAAA,MACd,QAAQ,KAAK;AAAA,MACb,OAAO,KAAK;AAAA,MACZ,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,kBAAkB,qBAAqB,KAAK,gBAAgB;AAAA,MAC5D,iBAAiB,qBAAqB,KAAK,eAAe;AAAA,MAC1D,kBAAkB,qBAAqB,KAAK,gBAAgB;AAAA,IAC9D;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,mBAAmB,YAAY;AAC/B,sBAAsB,cAAc,kBAAkB;AAGtD,SAAS,iBAAiB,GAAGa,UAAS,YAAY;AAChD,SAAO,KAAK,MAAM;AAChB,QAAI,EAAE,SAAS,GAAG;AAChB,YAAM,IAAI,WAAW,kEAAkE,EAAE,gBAAgB;AAAA,IAC3G;AACA,QAAIA,YAAW,MAAM;AACnB,MAAAA,WAAU,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAAA,IAC3B;AACA,QAAIA,SAAQ,WAAW,KAAKA,SAAQ,GAAG,WAAW,KAAKA,SAAQ,GAAG,WAAW,GAAG;AAC9E,YAAM,IAAI,WAAW,6GAA6G;AAAA,IACpI;AACA,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,QAAI,eAAe,kBAAkB,eAAe,iBAAiB;AACnE,YAAM,IAAI,WAAW,wBAAwB,2EAA2E;AAAA,IAC1H;AACA,QAAI;AACJ,QAAI,eAAe,iBAAiB;AAClC,gBAAU,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAGA,SAAQ,IAAIA,SAAQ,EAAE;AAAA,IACnD,OAAO;AACL,gBAAU,CAAC,CAAC,GAAG,CAAC,GAAGA,SAAQ,IAAIA,SAAQ,IAAI,CAAC,GAAG,CAAC,CAAC;AAAA,IACnD;AACA,WAAO,IAAI,GAAG,OAAO;AAAA,EACvB,CAAC;AACH;AACA,IAAI,gBAAgB,cAAc,MAAM;AAAA,EACtC,YAAY,MAAM;AAChB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,UAAM,IAAI;AACV,SAAK,aAAa,KAAK,cAAc,OAAO,gBAAgB,IAAI,KAAK;AACrE,QAAI,KAAK,WAAW,MAAM;AACxB,WAAK,UAAU,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAAA,IAChC,WAAW,OAAO,KAAK,YAAY,UAAU;AAC3C,WAAK,UAAU,CAAC,CAAC,KAAK,SAAS,KAAK,OAAO,GAAG,CAAC,KAAK,SAAS,KAAK,OAAO,CAAC;AAAA,IAC5E,OAAO;AACL,WAAK,UAAU,KAAK;AACpB,UAAI,KAAK,QAAQ,WAAW,GAAG;AAC7B,cAAM,IAAI,WAAW,+EAA+E,KAAK,QAAQ,eAAe;AAAA,MAClI;AACA,UAAI;AACJ,UAAI;AACJ,UAAI,OAAO,KAAK,QAAQ,OAAO,UAAU;AACvC,wBAAgB,CAAC,KAAK,QAAQ,IAAI,KAAK,QAAQ,EAAE;AACjD,uBAAe,CAAC,KAAK,QAAQ,IAAI,KAAK,QAAQ,EAAE;AAAA,MAClD,OAAO;AACL,aAAK,UAAU,KAAK;AACpB,YAAI,KAAK,QAAQ,GAAG,WAAW,GAAG;AAChC,gBAAM,IAAI,WAAW,sFAAsF,KAAK,QAAQ,GAAG,eAAe;AAAA,QAC5I;AACA,wBAAgB,KAAK,QAAQ;AAC7B,YAAI,KAAK,QAAQ,GAAG,WAAW,GAAG;AAChC,gBAAM,IAAI,WAAW,qFAAqF,KAAK,QAAQ,GAAG,eAAe;AAAA,QAC3I;AACA,uBAAe,KAAK,QAAQ;AAAA,MAC9B;AACA,WAAK,UAAU,CAAC,eAAe,YAAY;AAAA,IAC7C;AACA,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,EAC9C;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,QAAI;AACJ,QAAI;AACJ,QAAI,KAAK,eAAe,iBAAiB;AACvC,UAAI,WAAW,MAAM,QAAQ,WAAW,MAAM,GAAG;AAC/C,eAAO,WAAW,KAAK,KAAK,QAAQ,GAAG,KAAK,KAAK,QAAQ,GAAG;AAAA,MAC9D,OAAO;AACL,eAAO;AAAA,MACT;AACA,UAAI,WAAW,MAAM,QAAQ,WAAW,MAAM,GAAG;AAC/C,eAAO,WAAW,KAAK,KAAK,QAAQ,GAAG,KAAK,KAAK,QAAQ,GAAG;AAAA,MAC9D,OAAO;AACL,eAAO;AAAA,MACT;AACA,aAAO,CAAC,WAAW,IAAI,WAAW,IAAI,MAAM,IAAI;AAAA,IAClD,OAAO;AACL,UAAI,WAAW,MAAM,QAAQ,WAAW,MAAM,GAAG;AAC/C,eAAO,WAAW,KAAK,KAAK,QAAQ,GAAG,KAAK,KAAK,QAAQ,GAAG;AAAA,MAC9D,OAAO;AACL,eAAO;AAAA,MACT;AACA,UAAI,WAAW,MAAM,QAAQ,WAAW,MAAM,GAAG;AAC/C,eAAO,WAAW,KAAK,KAAK,QAAQ,GAAG,KAAK,KAAK,QAAQ,GAAG;AAAA,MAC9D,OAAO;AACL,eAAO;AAAA,MACT;AACA,aAAO,CAAC,WAAW,IAAI,MAAM,MAAM,WAAW,EAAE;AAAA,IAClD;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM,iBAAiB,oBAAoB,MAAM,GAAG,KAAK,SAAS,KAAK,UAAU,CAAC;AAAA,EAChG;AAAA,EACA,YAAY;AACV,UAAMb,UAAS;AAAA,MACb,SAAS,KAAK;AAAA,MACd,YAAY,KAAK;AAAA,IACnB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,cAAc,YAAY;AAC1B,sBAAsB,cAAc,aAAa;AAGjD,SAAS,OAAO,GAAG,UAAUF,UAASe,UAAS,YAAY,UAAU;AACnE,SAAO,KAAK,MAAM;AAChB,oBAAgB,UAAU;AAC1B,kBAAc,QAAQ;AACtB,qBAAiBA,QAAO;AACxB,QAAIf,YAAW,MAAM;AACnB,MAAAA,WAAU,CAAC,GAAG,CAAC;AAAA,IACjB;AACA,QAAIe,YAAW,MAAM;AACnB,MAAAA,WAAU;AAAA,IACZ;AACA,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,QAAI,YAAY,MAAM;AACpB,iBAAW;AAAA,IACb;AACA,QAAI,sBAAsB,GAAG,UAAU;AACvC,QAAI;AACJ,UAAM,gBAAgBA,aAAY,SAAS,SAAS;AACpD,QAAI,aAAa,OAAO;AACtB,UAAI,QAAQ,GAAG,UAAUf,UAAS,aAAa;AAAA,IACjD,OAAO;AACL,UAAI;AAAA,QACF;AAAA,QACA;AAAA,QACAA;AAAA,QACA;AAAA,MACF;AAAA,IACF;AACA,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,GAAG,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,IAC/B;AACA,WAAO;AAAA,EACT,CAAC;AACH;AACA,SAAS,OAAO,GAAG,UAAUA,UAASe,UAAS,YAAY,UAAU;AACnE,SAAO,KAAK,MAAM;AAChB,oBAAgB,UAAU;AAC1B,kBAAc,QAAQ;AACtB,qBAAiBA,QAAO;AACxB,QAAIf,YAAW,MAAM;AACnB,MAAAA,WAAU,CAAC,GAAG,GAAG,CAAC;AAAA,IACpB;AACA,QAAIe,YAAW,MAAM;AACnB,MAAAA,WAAU;AAAA,IACZ;AACA,QAAI,cAAc,MAAM;AACtB,mBAAa,gBAAgB;AAAA,IAC/B;AACA,QAAI,YAAY,MAAM;AACpB,iBAAW;AAAA,IACb;AACA,QAAI,sBAAsB,GAAG,UAAU;AACvC,QAAI;AACJ,UAAM,gBAAgBA,aAAY,SAAS,SAAS;AACpD,QAAI,aAAa,OAAO;AACtB,UAAI,UAAU,GAAG,UAAUf,UAAS,aAAa;AAAA,IACnD,OAAO;AACL,UAAI,UAAU,GAAG,UAAUA,UAAS,aAAa;AAAA,IACnD;AACA,QAAI,eAAe,iBAAiB;AAClC,UAAI,UAAU,GAAG,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC,CAAC;AAAA,IAClC;AACA,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,YAAY,cAAc,MAAM;AAAA,EAClC,YAAY,MAAM;AAChB,QAAI,KAAK,YAAY,MAAM;AACzB,WAAK,WAAW;AAAA,IAClB;AACA,UAAM,IAAI;AACV,QAAI,OAAO,KAAK,aAAa,UAAU;AACrC,WAAK,WAAW,CAAC,KAAK,QAAQ;AAAA,IAChC,WAAW,MAAM,QAAQ,KAAK,QAAQ,KAAK,KAAK,SAAS,WAAW,KAAK,OAAO,KAAK,SAAS,OAAO,UAAU;AAC7G,WAAK,WAAW,KAAK;AAAA,IACvB,OAAO;AACL,YAAM,IAAI,WAAW,qGAAqG,KAAK,UAAU,KAAK,QAAQ,GAAG;AAAA,IAC3J;AACA,0BAAsB,KAAK,UAAU,UAAU;AAC/C,QAAI,KAAK,WAAW,MAAM;AACxB,WAAK,UAAU,KAAK;AAAA,IACtB,OAAO;AACL,UAAI,OAAO,KAAK,YAAY,UAAU;AACpC,aAAK,UAAU,CAAC,KAAK,OAAO;AAAA,MAC9B,WAAW,MAAM,QAAQ,KAAK,OAAO,KAAK,KAAK,QAAQ,WAAW,KAAK,OAAO,KAAK,QAAQ,OAAO,UAAU;AAC1G,aAAK,UAAU,KAAK;AAAA,MACtB,OAAO;AACL,cAAM,IAAI,WAAW,oGAAoG,KAAK,UAAU,KAAK,OAAO,GAAG;AAAA,MACzJ;AAAA,IACF;AACA,0BAAsB,KAAK,SAAS,SAAS;AAC7C,SAAK,UAAU,KAAK,WAAW,OAAO,UAAU,KAAK;AACrD,qBAAiB,KAAK,OAAO;AAC7B,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,EAC9C;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,SAAS,iBAAiB,WAAW,IAAI,KAAK,SAAS,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AAC9F,WAAO,CAAC,WAAW,IAAI,QAAQ,WAAW,EAAE;AAAA,EAC9C;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,eAAS,YAAY,oBAAoB,MAAM,GAAG,CAAC;AACnD,YAAM,SAAS,KAAK,gBAAgB,oBAAoB,MAAM,GAAG,CAAC,KAAK,SAAS,IAAI,CAAC,GAAG,CAAC,KAAK,QAAQ,IAAI,CAAC,GAAG,KAAK,SAAS,cAAc;AAC1I,aAAO,QAAQ,QAAQ,CAAC,CAAC,CAAC;AAAA,IAC5B,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAME,UAAS;AAAA,MACb,UAAU,KAAK;AAAA,MACf,SAAS,KAAK;AAAA,MACd,SAAS,KAAK;AAAA,IAChB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,IAAI,eAAe,cAAc,UAAU;AAAA,EACzC,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,gBAAgB,QAAQ,UAAUF,UAASe,UAAS,YAAY;AAC9D,oBAAgB,UAAU;AAC1B,qBAAiBA,QAAO;AACxB,WAAO,OAAO,QAAQ,UAAUf,UAASe,UAAS,YAAY,KAAK;AAAA,EACrE;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAChD,IAAI,mBAAmB,cAAc,UAAU;AAAA,EAC7C,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,gBAAgB,QAAQ,UAAUf,UAASe,UAAS,YAAY;AAC9D,oBAAgB,UAAU;AAC1B,qBAAiBA,QAAO;AACxB,WAAO,OAAO,QAAQ,UAAUf,UAASe,UAAS,YAAY,KAAK;AAAA,EACrE;AACF;AACA,iBAAiB,YAAY;AAC7B,sBAAsB,cAAc,gBAAgB;AACpD,IAAI,YAAY,cAAc,MAAM;AAAA,EAClC,YAAY,MAAM;AAChB,QAAI,KAAK,YAAY,MAAM;AACzB,WAAK,WAAW,CAAC,GAAG,CAAC;AAAA,IACvB;AACA,UAAM,IAAI;AACV,SAAK,WAAW,MAAM,QAAQ,KAAK,QAAQ,IAAI,KAAK,WAAW,CAAC,KAAK,UAAU,KAAK,QAAQ;AAC5F,QAAI,KAAK,WAAW,MAAM;AACxB,WAAK,UAAU,KAAK;AAAA,IACtB,WAAW,MAAM,QAAQ,KAAK,OAAO,GAAG;AACtC,UAAI,KAAK,QAAQ,WAAW,GAAG;AAC7B,cAAM,IAAI,WAAW,wHAAwH,KAAK,QAAQ,SAAS;AAAA,MACrK;AACA,WAAK,UAAU,KAAK;AAAA,IACtB,OAAO;AACL,WAAK,UAAU,CAAC,KAAK,SAAS,KAAK,OAAO;AAAA,IAC5C;AACA,0BAAsB,KAAK,UAAU,UAAU;AAC/C,0BAAsB,KAAK,SAAS,SAAS;AAC7C,SAAK,UAAU,KAAK,WAAW,OAAO,UAAU,KAAK;AACrD,SAAK,aAAa,KAAK,cAAc,OAAO,iBAAiB,KAAK;AAClE,oBAAgB,KAAK,UAAU;AAC/B,qBAAiB,KAAK,OAAO;AAC7B,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,EAC9C;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,OAAO,KAAK,eAAe,kBAAkB,WAAW,KAAK,WAAW;AAC5E,QAAI,OAAO,KAAK,eAAe,kBAAkB,WAAW,KAAK,WAAW;AAC5E,WAAO,iBAAiB,MAAM,KAAK,SAAS,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AAC7E,WAAO,iBAAiB,MAAM,KAAK,SAAS,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AAC7E,QAAI,KAAK,eAAe,iBAAiB;AACvC,aAAO,CAAC,WAAW,IAAI,WAAW,IAAI,MAAM,IAAI;AAAA,IAClD,OAAO;AACL,aAAO,CAAC,WAAW,IAAI,MAAM,MAAM,WAAW,EAAE;AAAA,IAClD;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,aAAO,KAAK,gBAAgB,oBAAoB,MAAM,GAAG,KAAK,UAAU,KAAK,SAAS,KAAK,SAAS,KAAK,UAAU;AAAA,IACrH,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMb,UAAS;AAAA,MACb,UAAU,KAAK;AAAA,MACf,SAAS,KAAK;AAAA,MACd,SAAS,KAAK;AAAA,MACd,YAAY,KAAK;AAAA,IACnB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,IAAI,eAAe,cAAc,UAAU;AAAA,EACzC,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,gBAAgB,QAAQ,UAAUF,UAASe,UAAS,YAAY;AAC9D,oBAAgB,UAAU;AAC1B,qBAAiBA,QAAO;AACxB,WAAO,OAAO,QAAQ,UAAUf,UAASe,UAAS,YAAY,KAAK;AAAA,EACrE;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAChD,IAAI,mBAAmB,cAAc,UAAU;AAAA,EAC7C,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,gBAAgB,QAAQ,UAAUf,UAASe,UAAS,YAAY;AAC9D,oBAAgB,UAAU;AAC1B,qBAAiBA,QAAO;AACxB,WAAO,OAAO,QAAQ,UAAUf,UAASe,UAAS,YAAY,KAAK;AAAA,EACrE;AACF;AACA,iBAAiB,YAAY;AAC7B,sBAAsB,cAAc,gBAAgB;AACpD,IAAI,YAAY,cAAc,MAAM;AAAA,EAClC,YAAY,MAAM;AAChB,QAAI,KAAK,YAAY,MAAM;AACzB,WAAK,WAAW,CAAC,GAAG,GAAG,CAAC;AAAA,IAC1B;AACA,UAAM,IAAI;AACV,SAAK,WAAW,MAAM,QAAQ,KAAK,QAAQ,IAAI,KAAK,WAAW,CAAC,KAAK,UAAU,KAAK,UAAU,KAAK,QAAQ;AAC3G,QAAI,KAAK,WAAW,MAAM;AACxB,WAAK,UAAU,KAAK;AAAA,IACtB,WAAW,MAAM,QAAQ,KAAK,OAAO,GAAG;AACtC,UAAI,KAAK,QAAQ,WAAW,GAAG;AAC7B,cAAM,IAAI,WAAW,wHAAwH,KAAK,QAAQ,SAAS;AAAA,MACrK;AACA,WAAK,UAAU,KAAK;AAAA,IACtB,OAAO;AACL,WAAK,UAAU,CAAC,KAAK,SAAS,KAAK,SAAS,KAAK,OAAO;AAAA,IAC1D;AACA,0BAAsB,KAAK,UAAU,UAAU;AAC/C,0BAAsB,KAAK,SAAS,SAAS;AAC7C,SAAK,UAAU,KAAK,WAAW,OAAO,UAAU,KAAK;AACrD,SAAK,aAAa,KAAK,cAAc,OAAO,iBAAiB,KAAK;AAClE,oBAAgB,KAAK,UAAU;AAC/B,qBAAiB,KAAK,OAAO;AAC7B,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,EAC9C;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,SAAS,KAAK,eAAe,kBAAkB,WAAW,KAAK,WAAW;AAC9E,QAAI,OAAO,KAAK,eAAe,kBAAkB,WAAW,KAAK,WAAW;AAC5E,QAAI,OAAO,KAAK,eAAe,kBAAkB,WAAW,KAAK,WAAW;AAC5E,aAAS,iBAAiB,QAAQ,KAAK,SAAS,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AACjF,WAAO,iBAAiB,MAAM,KAAK,SAAS,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AAC7E,WAAO,iBAAiB,MAAM,KAAK,SAAS,IAAI,KAAK,SAAS,KAAK,QAAQ,EAAE;AAC7E,QAAI,KAAK,eAAe,iBAAiB;AACvC,aAAO,CAAC,WAAW,IAAI,WAAW,IAAI,QAAQ,MAAM,IAAI;AAAA,IAC1D,OAAO;AACL,aAAO,CAAC,WAAW,IAAI,QAAQ,MAAM,MAAM,WAAW,EAAE;AAAA,IAC1D;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,WAAK,eAAe,QAAQ,MAAM;AAClC,aAAO,KAAK,gBAAgB,oBAAoB,MAAM,GAAG,KAAK,UAAU,KAAK,SAAS,KAAK,SAAS,KAAK,UAAU;AAAA,IACrH,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMb,UAAS;AAAA,MACb,UAAU,KAAK;AAAA,MACf,SAAS,KAAK;AAAA,MACd,SAAS,KAAK;AAAA,MACd,YAAY,KAAK;AAAA,IACnB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,IAAI,eAAe,cAAc,UAAU;AAAA,EACzC,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,gBAAgB,QAAQ,UAAUF,UAASe,UAAS,YAAY;AAC9D,oBAAgB,UAAU;AAC1B,qBAAiBA,QAAO;AACxB,WAAO,OAAO,QAAQ,UAAUf,UAASe,UAAS,YAAY,KAAK;AAAA,EACrE;AACF;AACA,aAAa,YAAY;AACzB,sBAAsB,cAAc,YAAY;AAChD,IAAI,mBAAmB,cAAc,UAAU;AAAA,EAC7C,YAAY,MAAM;AAChB,UAAM,IAAI;AAAA,EACZ;AAAA,EACA,gBAAgB,QAAQ,UAAUf,UAASe,UAAS,YAAY;AAC9D,oBAAgB,UAAU;AAC1B,qBAAiBA,QAAO;AACxB,WAAO,OAAO,QAAQ,UAAUf,UAASe,UAAS,YAAY,KAAK;AAAA,EACrE;AACF;AACA,iBAAiB,YAAY;AAC7B,sBAAsB,cAAc,gBAAgB;AACpD,IAAI,kBAAkB,cAAc,MAAM;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,EAC9C;AAAA,EACA,mBAAmB,YAAY;AAC7B,WAAO,CAAC,WAAW,IAAI,WAAW,EAAE;AAAA,EACtC;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,UAAM,IAAI,oBAAoB;AAAA,EAChC;AACF;AACA,IAAI,yBAAyB,cAAc,gBAAgB;AAAA,EACzD,YAAY,MAAM;AAChB,UAAM,QAAQ,CAAC,CAAC;AAAA,EAClB;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAM,SAAS,oBAAoB,MAAM;AACzC,aAAO,KAAK,QAAQ,CAAC;AAAA,IACvB,CAAC;AAAA,EACH;AACF;AACA,uBAAuB,YAAY;AACnC,sBAAsB,cAAc,sBAAsB;AAC1D,IAAI,qBAAqB,cAAc,gBAAgB;AAAA,EACrD,YAAY,MAAM;AAChB,UAAM,QAAQ,CAAC,CAAC;AAAA,EAClB;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAM,SAAS,oBAAoB,MAAM;AACzC,aAAO,IAAI,QAAQ,CAAC;AAAA,IACtB,CAAC;AAAA,EACH;AACF;AACA,mBAAmB,YAAY;AAC/B,sBAAsB,cAAc,kBAAkB;AACtD,IAAI,kBAAkB,cAAc,MAAM;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,aAAa,KAAK,cAAc,OAAO,iBAAiB,KAAK;AAClE,oBAAgB,KAAK,UAAU;AAC/B,SAAK,YAAY,CAAC,IAAI,UAAU,EAAE,MAAM,EAAE,CAAC,CAAC;AAAA,EAC9C;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa;AACb,QAAI,KAAK,eAAe,gBAAgB;AACtC,aAAO,CAAC,WAAW,IAAI,WAAW,EAAE;AAAA,IACtC,OAAO;AACL,aAAO,CAAC,WAAW,IAAI,WAAW,EAAE;AAAA,IACtC;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,UAAM,IAAI,oBAAoB;AAAA,EAChC;AAAA,EACA,YAAY;AACV,UAAMb,UAAS,EAAE,YAAY,KAAK,WAAW;AAC7C,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AACF;AACA,IAAI,yBAAyB,cAAc,gBAAgB;AAAA,EACzD,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAM,SAAS,oBAAoB,MAAM;AACzC,UAAI,KAAK,eAAe,gBAAgB;AACtC,eAAO,KAAK,QAAQ,CAAC,GAAG,CAAC,CAAC;AAAA,MAC5B,OAAO;AACL,eAAO,KAAK,QAAQ,CAAC,GAAG,CAAC,CAAC;AAAA,MAC5B;AAAA,IACF,CAAC;AAAA,EACH;AACF;AACA,uBAAuB,YAAY;AACnC,sBAAsB,cAAc,sBAAsB;AAC1D,IAAI,qBAAqB,cAAc,gBAAgB;AAAA,EACrD,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAM,SAAS,oBAAoB,MAAM;AACzC,UAAI,KAAK,eAAe,gBAAgB;AACtC,eAAO,IAAI,QAAQ,CAAC,GAAG,CAAC,CAAC;AAAA,MAC3B,OAAO;AACL,eAAO,IAAI,QAAQ,CAAC,GAAG,CAAC,CAAC;AAAA,MAC3B;AAAA,IACF,CAAC;AAAA,EACH;AACF;AACA,mBAAmB,YAAY;AAC/B,sBAAsB,cAAc,kBAAkB;AAGtD,IAAI,UAAU,cAAc,MAAM;AAAA,EAChC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,QAAQ,KAAK;AAAA,EACpB;AAAA,EACA,MAAM,YAAY;AAChB,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,IAAI,YAAY;AACd,QAAI,KAAK,SAAS,MAAM;AACtB,aAAO,KAAK,MAAM;AAAA,IACpB,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,IAAI,UAAU,OAAO;AACnB,QAAI,KAAK,SAAS,MAAM;AACtB,WAAK,MAAM,YAAY;AAAA,IACzB;AAAA,EACF;AAAA,EACA,IAAI,mBAAmB;AACrB,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,IAAI,sBAAsB;AACxB,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,IAAI,UAAU;AACZ,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,IAAI,SAAS;AACX,WAAO,KAAK,MAAM;AAAA,EACpB;AAAA,EACA,aAAa;AACX,WAAO,KAAK,MAAM,WAAW;AAAA,EAC/B;AAAA,EACA,WAAW,SAAS;AAClB,SAAK,MAAM,WAAW,OAAO;AAAA,EAC/B;AAAA,EACA,YAAY;AACV,UAAMA,UAAS;AAAA,MACb,SAAS;AAAA,QACP,aAAa,KAAK,MAAM,aAAa;AAAA,QACrC,UAAU,KAAK,MAAM,UAAU;AAAA,MACjC;AAAA,IACF;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,6BAA6B,OAAO;AAClC,UAAM,6BAA6B,KAAK;AACxC,QAAI,KAAK,SAAS,MAAM;AACtB,WAAK,MAAM,6BAA6B,KAAK;AAAA,IAC/C;AAAA,EACF;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ,gBAAgB,CAAC,GAAG;AACjD,UAAM,cAAcA,QAAO;AAC3B,UAAM,QAAQ,YAAY,aAAa,aAAa;AACpD,WAAOA,QAAO;AACd,UAAM,YAAY,EAAE,MAAM;AAC1B,WAAO,OAAO,WAAWA,OAAM;AAC/B,WAAO,IAAI,IAAI,SAAS;AAAA,EAC1B;AACF;AACA,IAAI,kBAAkB,cAAc,QAAQ;AAAA,EAC1C,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,SAAK,kBAAkB;AAAA,EACzB;AAAA,EACA,MAAM,YAAY;AAChB,iBAAa,mBAAmB,UAAU;AAC1C,QAAI,WAAW,SAAS,GAAG;AACzB,YAAM,IAAI,WAAW,gFAAgF,KAAK,UAAU,UAAU,GAAG;AAAA,IACnI;AACA,SAAK,YAAY,CAAC,EAAE,OAAO,WAAW,CAAC;AACvC,UAAM,kBAAkB,CAAC,WAAW,EAAE,EAAE,OAAO,WAAW,MAAM,CAAC,CAAC;AAClE,QAAI,CAAC,KAAK,MAAM,OAAO;AACrB,WAAK,MAAM,MAAM,eAAe;AAChC,WAAK,MAAM,QAAQ;AAAA,IACrB;AACA,UAAM,MAAM,UAAU;AAAA,EACxB;AAAA,EACA,mBAAmB,YAAY;AAC7B,iBAAa,mBAAmB,UAAU;AAC1C,UAAM,kBAAkB,CAAC,WAAW,EAAE,EAAE,OAAO,WAAW,MAAM,CAAC,CAAC;AAClE,UAAM,mBAAmB,KAAK,MAAM,mBAAmB,eAAe;AACtE,UAAM,YAAY,WAAW;AAC7B,WAAO,CAAC,iBAAiB,IAAI,SAAS,EAAE,OAAO,iBAAiB,MAAM,CAAC,CAAC;AAAA,EAC1E;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,eAAS,oBAAoB,MAAM;AACnC,YAAM,QAAQ,CAAC,SAAS,WAAW;AACjC,cAAM,SAAS,oBAAoB,KAAK,MAAM,KAAK,SAAS,MAAM,CAAC;AACnE,eAAO,CAAC,QAAQ,CAAC,CAAC;AAAA,MACpB;AACA,YAAM,aAAa,IAAI,OAAO,QAAQ,CAAC,GAAG,OAAO,MAAM,MAAM,OAAO,IAAI;AACxE,YAAM,IAAI,WAAW;AACrB,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AACF;AACA,gBAAgB,YAAY;AAC5B,sBAAsB,cAAc,eAAe;AACnD,SAAS,4BAA4B,OAAO;AAC1C,4BAA0B,iCAAiC,0BAA0B,KAAK;AAC5F;AACA,IAAI,mCAAmC;AACvC,IAAI,gBAAgB,cAAc,QAAQ;AAAA,EACxC,YAAY,MAAM;AAChB,UAAM,IAAI;AACV,UAAM,cAAc,KAAK,MAAM,UAAU;AACzC,UAAM,WAAW,CAAC;AAClB,aAAS,eAAe,KAAK,MAAM,aAAa;AAChD,aAAS,YAAY;AACrB,SAAK,eAAe,YAAY,QAAQ;AACxC,gBAAY,iBAAiB,YAAY,mBAAmB,OAAO,QAAQ;AAC3E,UAAM,WAAW,CAAC;AAClB,aAAS,eAAe,KAAK,MAAM,aAAa;AAChD,aAAS,YAAY;AACrB,SAAK,gBAAgB,YAAY,QAAQ;AACzC,SAAK,aAAa,OAAO,aAAa,KAAK,aAAa;AACxD,SAAK,cAAc,OAAO,cAAc,KAAK,cAAc;AAC3D,SAAK,YAAY,KAAK,cAAc,SAAS,mCAAmC,KAAK;AACrF,gCAA4B,KAAK,SAAS;AAC1C,QAAI,KAAK,SAAS;AAChB,YAAM,IAAI,oBAAoB,iEAAiE;AAAA,IACjG;AACA,SAAK,YAAY,KAAK,MAAM;AAC5B,SAAK,kBAAkB,KAAK,MAAM;AAClC,SAAK,cAAc,KAAK,MAAM;AAC9B,SAAK,kBAAkB;AACvB,SAAK,aAAa;AAClB,SAAK,YAAY,KAAK,MAAM;AAC5B,SAAK,eAAe;AAAA,EACtB;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,UAAU,OAAO;AACnB,SAAK,aAAa;AAClB,QAAI,KAAK,gBAAgB,MAAM;AAC7B,WAAK,aAAa,YAAY;AAAA,IAChC;AACA,QAAI,KAAK,iBAAiB,MAAM;AAC9B,WAAK,cAAc,YAAY;AAAA,IACjC;AAAA,EACF;AAAA,EACA,aAAa;AACX,WAAO,KAAK,aAAa,WAAW,EAAE,OAAO,KAAK,cAAc,WAAW,CAAC;AAAA,EAC9E;AAAA,EACA,WAAW,SAAS;AAClB,UAAM,aAAa,QAAQ;AAC3B,UAAM,iBAAiB,KAAK,MAAM,aAAa,CAAC;AAChD,SAAK,aAAa,WAAW,QAAQ,MAAM,GAAG,cAAc,CAAC;AAC7D,SAAK,cAAc,WAAW,QAAQ,MAAM,cAAc,CAAC;AAAA,EAC7D;AAAA,EACA,mBAAmB,YAAY;AAC7B,QAAI,cAAc,KAAK,aAAa,mBAAmB,UAAU;AACjE,QAAI,EAAE,MAAM,QAAQ,WAAW,KAAK,MAAM,QAAQ,YAAY,EAAE,IAAI;AAClE,oBAAc,CAAC,WAAW;AAAA,IAC5B;AACA,kBAAc;AACd,QAAI;AACJ,QAAI;AACJ,QAAI;AACJ,QAAI,KAAK,aAAa;AACpB,mBAAa,YAAY,MAAM,CAAC;AAChC,oBAAc,YAAY;AAAA,IAC5B,OAAO;AACL,oBAAc,YAAY;AAAA,IAC5B;AACA,kBAAc;AACd,QAAI,KAAK,cAAc,UAAU;AAC/B,kBAAY,YAAY,SAAS,MAAM;AACvC,qBAAe,CAAC,WAAW;AAAA,IAC7B,WAAW,KAAK,aAAa,MAAM;AACjC,qBAAe,CAAC,aAAa,YAAY,MAAM,CAAC;AAAA,IAClD,OAAO;AACL,qBAAe,CAAC,WAAW;AAAA,IAC7B;AACA,QAAI,KAAK,aAAa;AACpB,UAAI,KAAK,aAAa,MAAM;AAC1B,eAAO,aAAa,OAAO,UAAU,EAAE,OAAO,WAAW,MAAM,CAAC;AAAA,MAClE;AACA,aAAO,CAAC,WAAW,EAAE,OAAO,UAAU,EAAE,OAAO,WAAW,MAAM,CAAC;AAAA,IACnE;AACA,WAAO,iBAAiB,YAAY;AAAA,EACtC;AAAA,EACA,MAAM,QAAQ,QAAQ;AACpB,QAAI,eAAe,UAAU,OAAO,OAAO,OAAO;AAClD,QAAIgB,aAAY,UAAU,OAAO,OAAO,OAAO;AAC/C,QAAI,UAAU,MAAM;AAClB,eAAS,CAAC;AAAA,IACZ;AACA,UAAM,eAAe,gBAAgB,QAAQ,cAAcA,YAAW,KAAK,YAAY;AACvF,aAAS,aAAa;AACtB,mBAAe,aAAa;AAC5B,IAAAA,aAAY,aAAa;AACzB,QAAI,MAAM,QAAQ,MAAM,GAAG;AACzB,qBAAe,OAAO,MAAM,CAAC;AAC7B,eAAS,OAAO;AAAA,IAClB;AACA,SAAK,gBAAgB,QAAQ,aAAa,WAAW,MAAMA,cAAa,MAAM;AAC5E,aAAO,MAAM,MAAM,QAAQ,MAAM;AAAA,IACnC;AACA,UAAM,mBAAmB,CAAC;AAC1B,UAAM,kBAAkB,CAAC;AACzB,QAAI,gBAAgB,MAAM;AACxB,YAAM,YAAY,aAAa;AAC/B,UAAI,YAAY,IAAI,GAAG;AACrB,cAAM,IAAI,WAAW,+HAA+H;AAAA,MACtJ;AACA,aAAO,kBAAkB;AACzB,uBAAiB,KAAK,GAAG,YAAY;AACrC,YAAM,aAAa,aAAa,IAAI,CAAC,UAAU,IAAI,UAAU,EAAE,OAAO,MAAM,MAAM,CAAC,CAAC;AACpF,WAAK,aAAa,YAAY,WAAW,MAAM,GAAG,YAAY,CAAC;AAC/D,WAAK,cAAc,YAAY,WAAW,MAAM,YAAY,CAAC;AAC7D,sBAAgB,KAAK,GAAG,UAAU;AAAA,IACpC;AACA,QAAIA,cAAa,MAAM;AACrB,YAAM,IAAI,oBAAoB,uEAAuE;AAAA,IACvG;AACA,UAAM,mBAAmB,iBAAiB,cAAc;AACxD,eAAW,WAAW,kBAAkB;AACtC,UAAI,mBAAmB,mBAAmB,kBAAkB;AAC1D,cAAM,IAAI,WAAW,8GAA8G;AAAA,MACrI;AAAA,IACF;AACA,QAAI,kBAAkB;AACpB,YAAM,YAAY,CAAC,MAAM,EAAE,OAAO,gBAAgB;AAClD,YAAM,gBAAgB,KAAK,UAAU,OAAO,eAAe;AAC3D,YAAM,oBAAoB,KAAK;AAC/B,WAAK,YAAY;AACjB,YAAM,SAAS,MAAM,MAAM,WAAW,MAAM;AAC5C,WAAK,YAAY;AACjB,aAAO;AAAA,IACT,OAAO;AACL,aAAO,MAAM,MAAM,QAAQ,MAAM;AAAA,IACnC;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ;AACnB,WAAO,KAAK,MAAM;AAChB,YAAM,eAAe,OAAO;AAC5B,UAAI;AACJ,UAAI;AACJ,UAAI,gBAAgB,MAAM;AACxB,YAAI,KAAK,aAAa,KAAK,QAAQ,MAAM;AACzC,eAAO,KAAK,cAAc,KAAK,QAAQ,MAAM;AAAA,MAC/C,OAAO;AACL,cAAM,eAAe,aAAa,MAAM,GAAG,aAAa,SAAS,CAAC;AAClE,cAAM,gBAAgB,aAAa,MAAM,aAAa,SAAS,CAAC;AAChE,YAAI,KAAK,aAAa,KAAK,QAAQ,OAAO,OAAO,QAAQ,EAAE,cAAc,aAAa,CAAC,CAAC;AACxF,eAAO,KAAK,cAAc,KAAK,QAAQ,OAAO,OAAO,QAAQ,EAAE,cAAc,cAAc,CAAC,CAAC;AAAA,MAC/F;AACA,UAAI;AACJ,UAAI,KAAK,aAAa;AACpB,YAAI,MAAM,QAAQ,CAAC,GAAG;AACpB,mBAAS,EAAE,MAAM,CAAC,EAAE,OAAO,KAAK,MAAM,CAAC,CAAC;AAAA,QAC1C,OAAO;AAAA,QACP;AACA,YAAI,EAAE;AACN,eAAO,KAAK;AAAA,MACd;AACA,UAAI,KAAK,iBAAiB;AACxB,eAAO,QAAQ,MAAM,CAAC;AAAA,MACxB;AACA,UAAI;AACJ,UAAI,KAAK,cAAc,UAAU;AAC/B,iBAAS,YAAY,CAAC,GAAG,IAAI,CAAC;AAAA,MAChC,WAAW,KAAK,cAAc,OAAO;AACnC,iBAAS,KAAK,GAAG,IAAI;AAAA,MACvB,WAAW,KAAK,cAAc,OAAO;AACnC,iBAAS,IAAI,KAAK,KAAK,GAAG,IAAI,CAAC;AAAA,MACjC,WAAW,KAAK,cAAc,OAAO;AACnC,iBAAS,IAAI,GAAG,IAAI;AAAA,MACtB,WAAW,KAAK,aAAa,MAAM;AACjC,iBAAS,CAAC,GAAG,IAAI;AAAA,MACnB;AACA,UAAI,KAAK,aAAa;AACpB,YAAI,KAAK,aAAa,MAAM;AAC1B,iBAAO,OAAO,OAAO,MAAM;AAAA,QAC7B;AACA,eAAO,CAAC,MAAM,EAAE,OAAO,MAAM;AAAA,MAC/B;AACA,aAAO;AAAA,IACT,CAAC;AAAA,EACH;AAAA,EACA,YAAY,QAAQ;AAClB,SAAK,aAAa,YAAY;AAC9B,SAAK,cAAc,YAAY;AAAA,EACjC;AAAA,EACA,MAAM,YAAY;AAChB,cAAU,KAAK,aAAa,MAAM,MAAM;AACtC,WAAK,aAAa,MAAM,UAAU;AAAA,IACpC,CAAC;AACD,cAAU,KAAK,cAAc,MAAM,MAAM;AACvC,WAAK,cAAc,MAAM,UAAU;AAAA,IACrC,CAAC;AACD,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,YAAY,QAAQzB,OAAM;AACxB,QAAI,MAAM,QAAQA,KAAI,GAAG;AACvB,MAAAA,QAAOA,MAAK;AAAA,IACd;AACA,QAAI;AACJ,QAAI,KAAK,iBAAiB;AACxB,UAAI,KAAK,aAAa,MAAM;AAC1B,qBAAa,CAACA,OAAMA,KAAI;AAAA,MAC1B,OAAO;AACL,qBAAaA;AAAA,MACf;AAAA,IACF,OAAO;AACL,UAAI,KAAK,aAAa,MAAM;AAC1B,qBAAa,CAAC,MAAM,IAAI;AAAA,MAC1B,OAAO;AACL,qBAAa;AAAA,MACf;AAAA,IACF;AACA,QAAI,KAAK,aAAa;AACpB,YAAM,SAAS,KAAK,aAAa;AACjC,YAAM,YAAY,OAAO,IAAI,CAAC,UAAU,IAAI;AAC5C,UAAI,MAAM,QAAQ,UAAU,GAAG;AAC7B,eAAO,WAAW,OAAO,SAAS,EAAE,OAAO,SAAS;AAAA,MACtD,OAAO;AACL,eAAO,CAAC,UAAU,EAAE,OAAO,SAAS,EAAE,OAAO,SAAS;AAAA,MACxD;AAAA,IACF,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,IAAI,mBAAmB;AACrB,WAAO,KAAK,aAAa,iBAAiB,OAAO,KAAK,cAAc,gBAAgB;AAAA,EACtF;AAAA,EACA,IAAI,sBAAsB;AACxB,WAAO,KAAK,aAAa,oBAAoB,OAAO,KAAK,cAAc,mBAAmB;AAAA,EAC5F;AAAA,EACA,6BAA6B,OAAO;AAClC,UAAM,6BAA6B,KAAK;AACxC,QAAI,KAAK,gBAAgB,MAAM;AAC7B,WAAK,aAAa,6BAA6B,KAAK;AAAA,IACtD;AACA,QAAI,KAAK,iBAAiB,MAAM;AAC9B,WAAK,cAAc,6BAA6B,KAAK;AAAA,IACvD;AAAA,EACF;AAAA,EACA,YAAY;AACV,UAAMS,UAAS;AAAA,MACb,aAAa,KAAK;AAAA,IACpB;AACA,UAAM,aAAa,MAAM,UAAU;AACnC,WAAO,OAAOA,SAAQ,UAAU;AAChC,WAAOA;AAAA,EACT;AAAA,EACA,OAAO,WAAW,KAAKA,SAAQ;AAC7B,UAAM,WAAW,YAAYA,QAAO,QAAQ;AAC5C,WAAOA,QAAO;AACd,QAAIA,QAAO,mBAAmB,MAAM;AAClC,YAAM,IAAI,oBAAoB,0FAA0F;AAAA,IAC1H;AACA,UAAM,YAAYA;AAClB,cAAU,WAAW;AACrB,WAAO,IAAI,IAAI,SAAS;AAAA,EAC1B;AACF;AACA,cAAc,YAAY;AAC1B,sBAAsB,cAAc,aAAa;AAGjD,SAAS,WAAW,MAAM;AACxB,SAAO,IAAI,WAAW,IAAI;AAC5B;AACA,SAAS,KAAK,MAAM;AAClB,SAAO,IAAI,IAAI,IAAI;AACrB;AACA,SAAS,KAAK,MAAM;AAClB,SAAO,IAAI,KAAK,IAAI;AACtB;AACA,SAAS,UAAU,MAAM;AACvB,SAAO,IAAI,UAAU,IAAI;AAC3B;AACA,SAAS,OAAO,MAAM;AACpB,SAAO,IAAI,MAAM,IAAI;AACvB;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,gBAAgB,MAAM;AAC7B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,OAAO,IAAI;AACxB;AACA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,WAAW,MAAM;AACxB,SAAO,IAAI,WAAW,IAAI;AAC5B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,WAAW,MAAM;AACxB,SAAO,IAAI,YAAY,IAAI;AAC7B;AACA,SAAS,MAAM,MAAM;AACnB,SAAO,IAAI,MAAM,IAAI;AACvB;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,iBAAiB,IAAI;AAClC;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,UAAU,MAAM;AACvB,SAAO,IAAI,UAAU,IAAI;AAC3B;AACA,SAAS,KAAK,MAAM;AAClB,SAAO,IAAI,KAAK,IAAI;AACtB;AACA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,YAAY,IAAI;AAC7B;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,UAAU,IAAI;AAC3B;AACA,SAAS,KAAK,MAAM;AAClB,SAAO,IAAI,IAAI,IAAI;AACrB;AACA,SAAS,oBAAoB,MAAM;AACjC,SAAO,IAAI,mBAAmB,IAAI;AACpC;AACA,SAAS,mBAAmB,MAAM;AAChC,SAAO,IAAI,mBAAmB,IAAI;AACpC;AACA,SAAS,cAAc,MAAM;AAC3B,SAAO,IAAI,cAAc,IAAI;AAC/B;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,iBAAiB,IAAI;AAClC;AACA,SAAS,UAAU,MAAM;AACvB,SAAO,iBAAiB,IAAI;AAC9B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,iBAAiB,IAAI;AAC9B;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,iBAAiB,IAAI;AAClC;AACA,SAAS,UAAU,MAAM;AACvB,SAAO,iBAAiB,IAAI;AAC9B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,iBAAiB,IAAI;AAC9B;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,iBAAiB,IAAI;AAClC;AACA,SAAS,WAAW,MAAM;AACxB,SAAO,iBAAiB,IAAI;AAC9B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,iBAAiB,IAAI;AAC9B;AACA,SAAS,uBAAuB,MAAM;AACpC,SAAO,IAAI,uBAAuB,IAAI;AACxC;AACA,SAAS,uBAAuB,MAAM;AACpC,SAAO,IAAI,uBAAuB,IAAI;AACxC;AACA,SAAS,mBAAmB,MAAM;AAChC,SAAO,IAAI,mBAAmB,IAAI;AACpC;AACA,SAAS,mBAAmB,MAAM;AAChC,SAAO,IAAI,mBAAmB,IAAI;AACpC;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,IAAI,MAAM;AACjB,SAAO,IAAI,IAAI,IAAI;AACrB;AACA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,QAAQ,IAAI;AACzB;AACA,SAAS,KAAK,MAAM;AAClB,SAAO,IAAI,KAAK,IAAI;AACtB;AACA,SAAS,SAAS,MAAM;AACtB,SAAO,IAAI,SAAS,IAAI;AAC1B;AACA,SAAS,UAAU,MAAM;AACvB,SAAO,IAAI,UAAU,IAAI;AAC3B;AACA,SAAS,cAAc,MAAM;AAC3B,SAAO,IAAI,cAAc,IAAI;AAC/B;AACA,SAAS,WAAW,MAAM;AACxB,SAAO,IAAI,WAAW,IAAI;AAC5B;AACA,SAAS,eAAe,MAAM;AAC5B,SAAO,IAAI,eAAe,IAAI;AAChC;AACA,SAAS,KAAK,MAAM;AAClB,SAAO,IAAI,IAAI,IAAI;AACrB;AACA,SAAS,gBAAgB,MAAM;AAC7B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,cAAc,MAAM;AAC3B,SAAO,IAAI,cAAc,IAAI;AAC/B;AACA,SAAS,gBAAgB,MAAM;AAC7B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,IAAI,kBAAkB;AACtB,IAAI,kBAAkB;AACtB,IAAI,YAAY;AAChB,IAAI,YAAY;AAChB,SAAS,cAAc,MAAM;AAC3B,SAAO,IAAI,cAAc,IAAI;AAC/B;AACA,SAAS,gBAAgB,MAAM;AAC7B,SAAO,IAAI,gBAAgB,IAAI;AACjC;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,IAAI,aAAa,IAAI;AAC9B;AACA,SAAS,QAAQ,MAAM;AACrB,SAAO,IAAI,QAAQ,IAAI;AACzB;AAGA,IAAI,0BAA0B,CAAC;AAC/BjB,UAAS,yBAAyB;AAAA,EAChC,MAAM,MAAM;AAAA,EACZ,KAAK,MAAM;AAAA,EACX,gBAAgB,MAAM;AAAA,EACtB,oBAAoB,MAAM;AAAA,EAC1B,qBAAqB,MAAM;AAAA,EAC3B,yBAAyB,MAAM;AAAA,EAC/B,iBAAiB,MAAM;AAAA,EACvB,MAAM,MAAM;AAAA,EACZ,mBAAmB,MAAM;AAAA,EACzB,6BAA6B,MAAM;AAAA,EACnC,kBAAkB,MAAM;AAAA,EACxB,KAAK,MAAM;AAAA,EACX,WAAW,MAAM;AAAA,EACjB,QAAQ,MAAM;AAAA,EACd,2BAA2B,MAAM;AACnC,CAAC;AACD,SAAS,gBAAgB,OAAO,OAAO;AACrC,SAAO,eAAe,OAAO,KAAK;AACpC;AACA,SAAS,oBAAoB,OAAO,OAAO;AACzC,SAAO,oBAAoB,OAAO,KAAK;AACzC;AACA,SAAS,2BAA2B,OAAO,OAAO;AAChD,SAAO,0BAA0B,OAAO,KAAK;AAC/C;AACA,SAAS,qBAAqB,OAAO,OAAO;AAC1C,SAAO,oBAAoB,OAAO,KAAK;AACzC;AACA,SAAS,yBAAyB,OAAO,OAAO;AAC9C,SAAO,yBAAyB,OAAO,KAAK;AAC9C;AACA,SAAS,WAAW,OAAO,OAAO;AAChC,SAAO,UAAU,OAAO,KAAK;AAC/B;AACA,SAAS,QAAQ,OAAO,OAAO;AAC7B,SAAO,OAAO,OAAO,KAAK;AAC5B;AACA,SAAS,iBAAiB,OAAO,OAAO;AACtC,SAAO,gBAAgB,OAAO,KAAK;AACrC;AACA,SAAS,mBAAmB,OAAO,OAAO;AACxC,SAAO,kBAAkB,OAAO,KAAK;AACvC;AACA,SAAS,6BAA6B,OAAO,OAAO;AAClD,SAAO,4BAA4B,OAAO,KAAK;AACjD;AACA,SAAS,MAAM,OAAO,OAAO;AAC3B,SAAO,4BAA4B,OAAO,KAAK;AACjD;AACA,SAAS,MAAM,OAAO,OAAO;AAC3B,SAAO,4BAA4B,OAAO,KAAK;AACjD;AACA,SAAS,kBAAkB,OAAO,OAAO;AACvC,SAAO,kBAAkB,OAAO,KAAK;AACvC;AACA,SAAS,KAAK,OAAO,OAAO;AAC1B,SAAO,kBAAkB,OAAO,KAAK;AACvC;AACA,SAAS,KAAK,OAAO,OAAO;AAC1B,SAAO,kBAAkB,OAAO,KAAK;AACvC;AAGA,IAAI,yBAAyB,CAAC;AAC9BA,UAAS,wBAAwB;AAAA,EAC/B,eAAe,MAAM;AACvB,CAAC;AAGD,IAAI,+BAA+B,CAAC;AACpCA,UAAS,8BAA8B;AAAA,EACrC,IAAI,MAAM;AAAA,EACV,MAAM,MAAM;AAAA,EACZ,IAAI,MAAM;AACZ,CAAC;AACD,SAAS,KAAKiB,SAAQ;AACpB,SAAO,IAAI,KAAKA,OAAM;AACxB;AACA,SAAS,IAAIA,SAAQ;AACnB,SAAO,GAAGA,OAAM;AAClB;AACA,SAAS,IAAIA,SAAQ;AACnB,SAAO,GAAGA,OAAM;AAClB;AAGA,IAAI,WAAW,cAAc,aAAa;AAAA,EACxC,cAAc;AACZ,UAAM,GAAG,SAAS;AAClB,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,SAASe,SAAQ;AACf,QAAI,EAAEA,mBAAkB,cAAc;AACpC,YAAM,IAAI,MAAM,uDAAuD;AAAA,IACzE;AACA,SAAK,QAAQA;AAAA,EACf;AACF;AACA,SAAS,MAAM,SAAS,SAAS;AAC/B,SAAO,UAAU;AACnB;AACA,SAAS,SAAS,SAAS,SAAS;AAClC,SAAO,UAAU;AACnB;AACA,IAAI,gBAAgB,cAAc,SAAS;AAAA,EACzC,YAAY,MAAM;AAChB,UAAM;AACN,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,QAAI,KAAK,oBAAoB;AAC3B,YAAM,IAAI,oBAAoB,oEAAoE;AAAA,IACpG;AACA,SAAK,UAAU,KAAK,WAAW;AAC/B,SAAK,WAAW,KAAK,IAAI,KAAK,YAAY,CAAC;AAC3C,SAAK,WAAW,KAAK,YAAY;AACjC,SAAK,UAAU,KAAK,WAAW;AAC/B,SAAK,OAAO,KAAK,QAAQ;AACzB,SAAK,WAAW,KAAK;AACrB,QAAI,CAAC,QAAQ,OAAO,KAAK,EAAE,QAAQ,KAAK,IAAI,MAAM,IAAI;AACpD,cAAQ,KAAK,uBAAuB,KAAK,gDAAgD;AACzF,WAAK,OAAO;AAAA,IACd;AACA,QAAI,KAAK,SAAS,OAAO;AACvB,WAAK,cAAc;AAAA,IACrB,WAAW,KAAK,SAAS,OAAO;AAC9B,WAAK,cAAc;AAAA,IACrB,OAAO;AACL,UAAI,KAAK,QAAQ,QAAQ,KAAK,MAAM,IAAI;AACtC,aAAK,cAAc;AAAA,MACrB,OAAO;AACL,aAAK,cAAc;AAAA,MACrB;AAAA,IACF;AACA,QAAI,KAAK,gBAAgB,OAAO;AAC9B,WAAK,YAAY;AAAA,IACnB;AAAA,EACF;AAAA,EACA,MAAM,aAAa,MAAM;AACvB,SAAK,OAAO;AACZ,SAAK,eAAe;AACpB,QAAI,KAAK,YAAY,MAAM;AACzB,WAAK,OAAO,KAAK;AAAA,IACnB,OAAO;AACL,WAAK,OAAO,KAAK,gBAAgB,QAAQ,WAAW;AAAA,IACtD;AAAA,EACF;AAAA,EACA,MAAM,WAAW,OAAO,MAAM;AAC5B,UAAM,qBAAqB,IAAI;AAC/B,UAAM,UAAU,KAAK,gBAAgB,IAAI;AACzC,QAAI,WAAW,MAAM;AACnB;AAAA,IACF;AACA,QAAI,KAAK,YAAY,UAAU,KAAK,UAAU,KAAK,IAAI,GAAG;AACxD,WAAK,OAAO;AACZ,WAAK,OAAO;AAAA,IACd,OAAO;AACL,WAAK;AACL,UAAI,KAAK,QAAQ,KAAK,UAAU;AAC9B,aAAK,eAAe;AACpB,aAAK,MAAM,eAAe;AAAA,MAC5B;AAAA,IACF;AAAA,EACF;AAAA,EACA,MAAM,WAAW,MAAM;AACrB,QAAI,KAAK,eAAe,KAAK,KAAK,SAAS;AACzC,cAAQ,IAAI,SAAS,KAAK,+BAA+B;AAAA,IAC3D;AAAA,EACF;AAAA,EACA,gBAAgB,MAAM;AACpB,QAAI,QAAQ,MAAM;AAChB,aAAO,CAAC;AAAA,IACV;AACA,UAAM,eAAe,KAAK,KAAK;AAC/B,QAAI,gBAAgB,MAAM;AACxB,cAAQ,KAAK,4BAA4B,KAAK,oDAAoD,OAAO,KAAK,IAAI,GAAG;AAAA,IACvH;AACA,WAAO;AAAA,EACT;AACF;AACA,SAAS,cAAc,MAAM;AAC3B,SAAO,IAAI,cAAc,IAAI;AAC/B;AACA,IAAI,YAAY,EAAE,cAAc;AAGhC,IAAI,OAAO,IAAI;AACf,KAAK,aAAa,6BAA6B,MAAM,OAAO,CAAC,eAAe;AAC1E,MAAI,YAAY;AACd,YAAQ,KAAK,+OAA+O;AAAA,EAC9P;AACF,CAAC;AAGD,IAAI;AAAA,CACH,SAAS,WAAW;AACnB,YAAU,UAAU,gBAAgB,KAAK;AACzC,YAAU,UAAU,cAAc,KAAK;AACvC,YAAU,UAAU,eAAe,KAAK;AACxC,YAAU,UAAU,cAAc,KAAK;AACvC,YAAU,UAAU,cAAc,KAAK;AACvC,YAAU,UAAU,cAAc,KAAK;AACvC,YAAU,UAAU,aAAa,KAAK;AACtC,YAAU,UAAU,eAAe,KAAK;AACxC,YAAU,UAAU,kBAAkB,KAAK;AAC3C,YAAU,UAAU,cAAc,KAAK;AACvC,YAAU,UAAU,aAAa,MAAM;AACvC,YAAU,UAAU,cAAc,MAAM;AACxC,YAAU,UAAU,eAAe,MAAM;AACzC,YAAU,UAAU,eAAe,MAAM;AACzC,YAAU,UAAU,iBAAiB,MAAM;AAC3C,YAAU,UAAU,eAAe,MAAM;AACzC,YAAU,UAAU,gBAAgB,MAAM;AAC1C,YAAU,UAAU,eAAe,MAAM;AACzC,YAAU,UAAU,mBAAmB,MAAM;AAC7C,YAAU,UAAU,aAAa,MAAM;AACvC,YAAU,UAAU,iBAAiB,MAAM;AAC3C,YAAU,UAAU,gBAAgB,MAAM;AAC1C,YAAU,UAAU,eAAe,MAAM;AACzC,YAAU,UAAU,eAAe,MAAM;AACzC,YAAU,UAAU,kBAAkB,OAAO;AAC7C,YAAU,UAAU,mBAAmB,OAAO;AAC9C,YAAU,UAAU,kBAAkB,OAAO;AAC7C,YAAU,UAAU,kBAAkB,OAAO;AAC7C,YAAU,UAAU,kBAAkB,OAAO;AAC7C,YAAU,UAAU,iBAAiB,OAAO;AAC5C,YAAU,UAAU,mBAAmB,OAAO;AAC9C,YAAU,UAAU,sBAAsB,OAAO;AACjD,YAAU,UAAU,kBAAkB,OAAO;AAC7C,YAAU,UAAU,iBAAiB,OAAO;AAC5C,YAAU,UAAU,kBAAkB,OAAO;AAC7C,YAAU,UAAU,mBAAmB,OAAO;AAC9C,YAAU,UAAU,mBAAmB,OAAO;AAC9C,YAAU,UAAU,qBAAqB,OAAO;AAChD,YAAU,UAAU,mBAAmB,OAAO;AAC9C,YAAU,UAAU,oBAAoB,OAAO;AAC/C,YAAU,UAAU,mBAAmB,OAAO;AAC9C,YAAU,UAAU,uBAAuB,OAAO;AAClD,YAAU,UAAU,iBAAiB,OAAO;AAC5C,YAAU,UAAU,qBAAqB,OAAO;AAChD,YAAU,UAAU,oBAAoB,OAAO;AAC/C,YAAU,UAAU,mBAAmB,OAAO;AAC9C,YAAU,UAAU,mBAAmB,OAAO;AAChD,GAAG,aAAa,WAAW,CAAC,EAAE;AAC9B,IAAI;AAAA,CACH,SAAS,WAAW;AACnB,MAAI;AACJ,GAAC,SAAS,0BAA0B;AAClC,6BAAyB,yBAAyB,YAAY,KAAK;AACnE,6BAAyB,yBAAyB,QAAQ,KAAK;AAC/D,6BAAyB,yBAAyB,QAAQ,KAAK;AAAA,EACjE,GAAG,0BAA0B,UAAU,4BAA4B,UAAU,0BAA0B,CAAC,EAAE;AAC5G,GAAG,aAAa,WAAW,CAAC,EAAE;AAG9B,IAAI,aAAa,CAAC;AAClB,SAAS,WAAW,MAAM,QAAQ;AAChC,QAAM,WAAW;AAAA,IACf,UAAU;AAAA,IACV,UAAU;AAAA,IACV,QAAQ,CAAC;AAAA,IACT,OAAO,CAAC;AAAA,IACR,gBAAgB;AAAA,EAClB;AACA,aAAW,QAAQ;AACrB;AACA,SAAS,gBAAgB,MAAM;AAC7B,SAAO,WAAW;AACpB;AACA,SAAS,aAAa,MAAM;AAC1B,SAAO,WAAW;AACpB;AAGA,SAAS,cAAc,WAAWb,OAAM,WAAW,SAAS,iBAAiB;AAC3E,QAAM,aAAaA,MAAK,YAAY;AACpC,MAAI,cAAc,WAAW,oBAAoB,QAAQ;AACvD,UAAM,QAAQ,WAAW;AACzB,UAAM,MAAM,WAAW,kBAAkB,IAAI,SAAS,WAAW,kBAAkB,SAAS,QAAQ,IAAI,WAAW;AACnH,QAAI,WAAW,SAAS,UAAU;AAChC,aAAO,UAAUA,MAAK,WAAW,WAAW,kBAAkB,WAAW,SAAS,eAAe;AAAA,IACnG;AACA,QAAI,WAAW,SAAS,WAAW;AACjC,YAAM,SAASA,MAAK,WAAW,MAAM,OAAO,GAAG;AAC/C,aAAO,OAAO,IAAI,CAAC,SAAS,UAAU,MAAM,WAAW,SAAS,eAAe,CAAC;AAAA,IAClF;AACA,UAAM,UAAU,UAAUA,MAAK,WAAW,MAAM,KAAK,EAAE,IAAI,WAAW,SAAS,eAAe;AAC9F,UAAM,OAAO,QAAQ,SAAS;AAC9B,WAAO,WAAW,SAAS,WAAW,KAAK,KAAK,aAAa,cAAc,QAAQ,OAAO,IAAI;AAAA,EAChG;AACA,QAAM,YAAYA,MAAK,WAAW;AAClC,SAAO,aAAa,UAAU;AAChC;AACA,SAAS,UAAU,MAAM,YAAY,SAAS,iBAAiB;AAC7D,QAAM,CAAC,UAAUP,MAAK,IAAI,cAAc,IAAI;AAC5C,MAAI,mBAAmB,MAAM;AAC3B,UAAM,UAAU,gBAAgB,yBAAyB,QAAQ;AACjE,QAAI,WAAW,MAAM;AACnB,aAAO;AAAA,IACT;AAAA,EACF;AACA,QAAM,YAAY,QAAQ,kBAAkB,KAAK,CAAC,eAAe;AAC/D,WAAO,CAAC,CAAC,WAAW,yBAAyB,UAAU,UAAU;AAAA,EACnE,CAAC;AACD,SAAO,cAAc,SAAS,WAAW,yBAAyB,UAAU,SAAS,GAAGA,UAAS;AACnG;AACA,SAAS,6BAA6B,MAAM,YAAY,SAAS;AAC/D,SAAO,WAAW,yBAAyB,MAAM,QAAQ,gBAAgB;AAC3E;AACA,SAAS,oBAAoB,WAAW,SAAS;AAC/C,QAAM,CAAC,UAAUA,QAAO,UAAU,IAAI,cAAc,SAAS;AAC7D,SAAO;AAAA,IACL,yBAAyB,UAAU,WAAW,QAAQ,gBAAgB;AAAA,IACtEA;AAAA,IACA;AAAA,EACF;AACF;AACA,SAAS,yBAAyB,MAAM,WAAW;AACjD,SAAO,CAAC,CAAC,YAAY,GAAG,QAAQ,cAAc;AAChD;AACA,SAAS,cAAc,MAAM;AAC3B,QAAM,QAAQ,KAAK,MAAM,GAAG;AAC5B,MAAI,MAAM,WAAW,GAAG;AACtB,WAAO,CAAC,MAAM,GAAG,MAAM;AAAA,EACzB;AACA,QAAM,WAAW,MAAM;AACvB,QAAM,aAAa,MAAM,WAAW,IAAI,MAAM,KAAK;AACnD,QAAMA,SAAQ,OAAO,MAAM,MAAM,SAAS,EAAE;AAC5C,SAAO,CAAC,UAAUA,QAAO,UAAU;AACrC;AACA,SAAS,WAAWO,OAAM,WAAW,SAAS;AAC5C,MAAI,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AACxD,MAAI,SAAS,YAAY;AACvB,WAAO,cAAc,oBAAoBA,OAAM,WAAW,OAAO;AACjE,UAAM,kBAAkB,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AACvD,aAAS,KAAK,GAAG,KAAK,GAAG,MAAM;AAC7B,sBAAgB,IAAI,KAAK,KAAK,KAAK;AACnC,sBAAgB,IAAI,KAAK,KAAK,KAAK,IAAI;AAAA,IACzC;AACA,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,YAAY,SAAS;AAC5B,SAAO,QAAQ,OAAO,UAAU,MAAM,OAAO;AAC/C;AAGA,IAAI,qBAAqB,CAAC;AAC1BnB,UAAS,oBAAoB;AAAA,EAC3B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,OAAO;AAAA,EACT;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,qBAAqB,CAAC;AAC1BA,UAAS,oBAAoB;AAAA,EAC3B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,kBAAkB,CAAC;AACvBA,UAAS,iBAAiB;AAAA,EACxB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,sBAAsB,CAAC;AAC3BA,UAAS,qBAAqB;AAAA,EAC5B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,QACjB,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,UACd;AAAA,UACA;AAAA,UACA;AAAA,UACA;AAAA,QACF;AAAA,MACF;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,UACd;AAAA,UACA;AAAA,UACA;AAAA,UACA;AAAA,QACF;AAAA,MACF;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,mBAAmB,CAAC;AACxBA,UAAS,kBAAkB;AAAA,EACzB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,QAChB,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,QAChB,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,QAChB,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,kBAAkB,CAAC;AACvBA,UAAS,iBAAiB;AAAA,EACxB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,qBAAqB,CAAC;AAC1BA,UAAS,oBAAoB;AAAA,EAC3B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,gBAAgB,CAAC;AACrBA,UAAS,eAAe;AAAA,EACtB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,EACd;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU,CAAC;AAAA,EACb;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,qBAAqB,CAAC;AAC1BA,UAAS,oBAAoB;AAAA,EAC3B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,QAAQ;AAAA,EACV;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU,CAAC;AAAA,IACX,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU,CAAC;AAAA,IACX,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,gBAAgB,CAAC;AACrBA,UAAS,eAAe;AAAA,EACtB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,kBAAkB,CAAC;AACvBA,UAAS,iBAAiB;AAAA,EACxB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,mBAAmB,CAAC;AACxBA,UAAS,kBAAkB;AAAA,EACzB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB,CAAC;AAAA,MACnB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,wBAAwB,CAAC;AAC7BA,UAAS,uBAAuB;AAAA,EAC9B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,QAChB,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,oBAAoB,CAAC;AACzBA,UAAS,mBAAmB;AAAA,EAC1B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,qBAAqB,CAAC;AAC1BA,UAAS,oBAAoB;AAAA,EAC3B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,OAAO;AAAA,QACP,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,QAChB,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,QAChB,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,iBAAiB,CAAC;AACtBA,UAAS,gBAAgB;AAAA,EACvB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,mBAAmB,CAAC;AACxBA,UAAS,kBAAkB;AAAA,EACzB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,iBAAiB,CAAC;AACtBA,UAAS,gBAAgB;AAAA,EACvB,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,WAAW;AAAA,MACT;AAAA,MACA;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,WAAW;AAAA,MACT;AAAA,MACA;AAAA,MACA;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AACF;AAGA,IAAI,yBAAyB,CAAC;AAC9BA,UAAS,wBAAwB;AAAA,EAC/B,MAAM,MAAM;AACd,CAAC;AACD,IAAI,SAAS;AAAA,EACX;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,QACR,gBAAgB;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,oBAAoB;AAAA,QACpB,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS;AAAA,MACP;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,UAAU;AAAA,QACV,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,EACF;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS,CAAC;AAAA,EACZ;AAAA,EACA;AAAA,IACE,YAAY;AAAA,IACZ,YAAY;AAAA,IACZ,UAAU;AAAA,MACR;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,MACA;AAAA,QACE,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,QAAQ;AAAA,MACV;AAAA,IACF;AAAA,IACA,SAAS,CAAC;AAAA,EACZ;AACF;AAGA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,WAAW,WAAW;AACpB,WAAO,KAAK,cAAc,KAAK,YAAY,IAAI,KAAK;AAAA,EACtD;AAAA,EACA,cAAc;AACZ,UAAM,MAAM;AAAA,MACV;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF;AACA,UAAM,cAAc,CAAC,EAAE,OAAO,GAAG,IAAI,IAAI,CAAC,QAAQ,IAAI,IAAI,CAAC;AAC3D,SAAK,YAAY,YAAY,OAAO,CAAC,KAAK,WAAW;AACnD,UAAI,OAAO,YAAY;AACvB,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AAAA,EACP;AAAA,EACA,eAAe,OAAO,YAAY,CAAC,GAAG;AACpC,UAAM,UAAU,MAAM;AACtB,UAAM,eAAe,CAAC;AACtB,UAAM,UAAU,CAAC;AACjB,UAAM,YAAY,CAAC;AACnB,UAAM,QAAQ,QAAQ,OAAO,CAAC,KAAKmB,UAAS;AAC1C,UAAIA,MAAK,QAAQ,KAAK,QAAQA,KAAI;AAClC,UAAIA,MAAK,GAAG,WAAW,aAAa,GAAG;AACrC,qBAAa,KAAK,IAAIA,MAAK,KAAK;AAAA,MAClC,WAAWA,MAAK,OAAO,SAAS;AAC9B,gBAAQ,KAAK,IAAIA,MAAK,KAAK;AAAA,MAC7B,WAAWA,MAAK,SAAS,QAAQA,MAAK,MAAM,WAAW,GAAG;AACxD,kBAAU,KAAK,IAAIA,MAAK,KAAK;AAAA,MAC/B;AACA,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AACL,QAAI,SAAS,CAAC;AACd,UAAM,UAAU,CAAC;AACjB,QAAI,qBAAqB,CAAC;AAC1B,QAAI,sBAAsB,CAAC;AAC3B,QAAI,aAAa,MAAM;AACrB,2BAAqB,KAAK,oBAAoB,UAAU,MAAM;AAC9D,4BAAsB,KAAK,oBAAoB,UAAU,OAAO;AAAA,IAClE;AACA,UAAM,WAAW,OAAO,KAAK,KAAK;AAClC,aAAS,QAAQ,CAAC,QAAQ;AACxB,YAAMA,QAAO,MAAM;AACnB,MAAAA,MAAK,WAAW,QAAQ,CAAC,MAAMP,WAAU;AACvC,cAAM,CAAC,UAAU,EAAE,UAAU,IAAI,oBAAoB,IAAI;AACzD,cAAM,YAAY,MAAM;AACxB,YAAI,UAAU,WAAW,MAAM;AAC7B,gBAAM,cAAc,UAAU,QAAQ,QAAQ,UAAU;AACxD,cAAI,gBAAgB,IAAI;AACtB,kBAAM,YAAY,GAAG,YAAY;AACjC,YAAAO,MAAK,WAAWP,UAAS;AAAA,UAC3B;AAAA,QACF;AACA,QAAAO,MAAK,OAAO,KAAK,SAAS;AAC1B,kBAAU,SAAS,KAAKA,KAAI;AAAA,MAC9B,CAAC;AAAA,IACH,CAAC;AACD,QAAI,OAAO,KAAK,mBAAmB,EAAE,WAAW,GAAG;AACjD,eAAS,QAAQ,CAAC,QAAQ;AACxB,cAAMA,QAAO,MAAM;AACnB,YAAIA,MAAK,SAAS,WAAW,GAAG;AAC9B,kBAAQ,KAAKA,KAAI;AAAA,QACnB;AAAA,MACF,CAAC;AAAA,IACH,OAAO;AACL,aAAO,KAAK,mBAAmB,EAAE,QAAQ,CAAC,SAAS;AACjD,cAAM,CAAC,QAAQ,IAAI,oBAAoB,IAAI;AAC3C,cAAMA,QAAO,MAAM;AACnB,YAAIA,SAAQ,MAAM;AAChB,UAAAA,MAAK,eAAe,oBAAoB;AACxC,kBAAQ,KAAKA,KAAI;AAAA,QACnB;AAAA,MACF,CAAC;AAAA,IACH;AACA,QAAI,OAAO,KAAK,kBAAkB,EAAE,SAAS,GAAG;AAC9C,aAAO,KAAK,kBAAkB,EAAE,QAAQ,CAAC,SAAS;AAChD,cAAM,CAAC,QAAQ,IAAI,oBAAoB,IAAI;AAC3C,cAAMA,QAAO,MAAM;AACnB,YAAIA,OAAM;AACR,UAAAA,MAAK,eAAe,mBAAmB;AACvC,iBAAO,KAAKA,KAAI;AAAA,QAClB;AAAA,MACF,CAAC;AAAA,IACH,OAAO;AACL,eAAS;AAAA,IACX;AACA,QAAI,YAAY,CAAC;AACjB,QAAI,MAAM,WAAW,QAAQ,MAAM,QAAQ,YAAY,MAAM;AAC3D,kBAAY,MAAM,QAAQ,SAAS,OAAO,CAAC,YAAY,UAAU;AAC/D,mBAAW,MAAM,UAAU,QAAQ,KAAK,YAAY,KAAK;AACzD,eAAO;AAAA,MACT,GAAG,CAAC,CAAC;AAAA,IACP;AACA,UAAM,SAAS,EAAE,OAAO,QAAQ,SAAS,SAAS,cAAc,WAAW,UAAU;AACrF,QAAI,UAAU,SAAS,GAAG;AACxB,aAAO,YAAY;AAAA,IACrB;AACA,WAAO;AAAA,EACT;AAAA,EACA,oBAAoB,SAAS;AAC3B,WAAO,OAAO,KAAK,WAAW,CAAC,CAAC,EAAE,OAAO,CAAC,MAAM,SAAS;AACvD,WAAK,QAAQ,MAAM,QAAQ;AAC3B,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AAAA,EACP;AAAA,EACA,QAAQA,OAAM;AACZ,UAAM,SAAS,gBAAgBA,MAAK,EAAE,KAAK,KAAK,UAAUA,MAAK,OAAO,CAAC;AACvE,QAAIA,MAAK,QAAQ,MAAM;AACrB,MAAAA,MAAK,OAAO,CAAC;AAAA,IACf;AACA,UAAM,UAAU;AAAA,MACd,MAAMA,MAAK;AAAA,MACX,IAAIA,MAAK;AAAA,MACT,UAAU,OAAO;AAAA,MACjB,aAAaA,MAAK,SAAS,CAAC,GAAG,IAAI,CAAC,WAAW,OAAO,WAAW,GAAG,IAAI,OAAO,MAAM,CAAC,IAAI,MAAM;AAAA,MAChG,QAAQ,CAAC;AAAA,MACT,UAAU,CAAC;AAAA,MACX,aAAa,CAAC;AAAA,MACd,YAAY,CAAC;AAAA,MACb,UAAUA,MAAK;AAAA,MACf,SAAS,OAAO;AAAA,IAClB;AACA,QAAI,OAAO,UAAU,MAAM;AACzB,cAAQ,cAAc,OAAO,OAAO,OAAO,CAAC,KAAK,UAAU;AACzD,YAAI,MAAM,QAAQ;AAAA,UAChB,MAAM,MAAM;AAAA,UACZ,iBAAiB,MAAM;AAAA,UACvB,eAAe,MAAM;AAAA,QACvB;AACA,eAAO;AAAA,MACT,GAAG,CAAC,CAAC;AAAA,IACP;AACA,QAAI,OAAO,SAAS,MAAM;AACxB,cAAQ,aAAa,OAAO,MAAM,OAAO,CAAC,KAAK,UAAU;AACvD,cAAM,OAAO,MAAM;AACnB,YAAI,QAAQ;AACZ,gBAAQ,MAAM;AAAA,eACP;AACH,oBAAQ,eAAeA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AAClE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,eAAeA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YAC9E;AACA;AAAA,eACG;AACH,oBAAQ,oBAAoBA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AACvE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,oBAAoBA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YACnF;AACA;AAAA,eACG;AACH,oBAAQ,eAAeA,MAAK,MAAM,MAAM,QAAQ,MAAM,gBAAgB,CAAC;AACvE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,eAAeA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YAC9E;AACA;AAAA,eACG;AACH,oBAAQ,qBAAqBA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AACxE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,qBAAqBA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YACpF;AACA;AAAA,eACG;AACH,oBAAQ,aAAaA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AAChE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,aAAaA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YAC5E;AACA;AAAA,eACG;AACH,oBAAQ,kBAAkBA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AACrE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,kBAAkBA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YACjF;AACA;AAAA,eACG;AACH,oBAAQ,oBAAoBA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AACvE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,oBAAoBA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YACnF;AACA;AAAA,eACG;AACH,oBAAQ,yBAAyBA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AAC5E,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,yBAAyBA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YACxF;AACA;AAAA,eACG;AACH,oBAAQ,cAAcA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AACjE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,cAAcA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YAC7E;AACA;AAAA,eACG;AACH,oBAAQ,mBAAmBA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AACtE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,mBAAmBA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YAClF;AACA;AAAA,eACG;AACH,oBAAQ,aAAaA,MAAK,MAAM,MAAM,QAAQ,MAAM,YAAY;AAChE,gBAAI,UAAU,UAAU,CAAC,CAAC,MAAM,kBAAkB;AAChD,sBAAQ,aAAaA,MAAK,MAAM,MAAM,kBAAkB,MAAM,YAAY;AAAA,YAC5E;AACA;AAAA,eACG;AAAA,eACA;AACH;AAAA;AAEA,kBAAM,IAAI,MAAM,2BAA2B,MAAM,gBAAgBA,MAAK,IAAI;AAAA;AAE9E,YAAI,MAAM,QAAQ,EAAE,OAAO,KAAK;AAChC,eAAO;AAAA,MACT,GAAG,CAAC,CAAC;AAAA,IACP;AACA,WAAO;AAAA,EACT;AAAA,EACA,YAAY,aAAa;AACvB,UAAM,UAAU,YAAY;AAC5B,UAAM,eAAe,CAAC;AACtB,UAAM,UAAU,CAAC;AACjB,QAAI,QAAQ,CAAC;AACb,QAAI,WAAW,MAAM;AACnB,cAAQ,QAAQ,OAAO,CAAC,KAAKA,UAAS;AACpC,YAAIA,MAAK,QAAQ,KAAK,QAAQA,KAAI;AAClC,YAAIA,MAAK,OAAO,SAAS;AACvB,kBAAQ,KAAK,IAAIA,MAAK,KAAK;AAAA,QAC7B;AACA,eAAO;AAAA,MACT,GAAG,CAAC,CAAC;AAAA,IACP;AACA,UAAM,SAAS,CAAC;AAChB,UAAM,UAAU,CAAC;AACjB,gBAAY,UAAU,SAAS,QAAQ,CAAC,QAAQ;AAC9C,YAAM,CAAC,QAAQ,IAAI,oBAAoB,IAAI,IAAI;AAC/C,YAAMA,QAAO;AAAA,QACX,MAAM;AAAA,QACN,IAAI;AAAA,QACJ,QAAQ,CAAC;AAAA,QACT,YAAY,CAAC;AAAA,QACb,UAAU;AAAA,QACV,aAAa,CAAC;AAAA,QACd,YAAY,EAAE,OAAO,EAAE,OAAO,gBAAgB,IAAI,IAAI,GAAG,MAAM,QAAQ,EAAE;AAAA,QACzE,UAAU,CAAC;AAAA,MACb;AACA,MAAAA,MAAK,eAAe,IAAI;AACxB,aAAO,KAAKA,KAAI;AAChB,YAAM,YAAYA;AAAA,IACpB,CAAC;AACD,UAAM,WAAW,OAAO,KAAK,KAAK;AAClC,aAAS,QAAQ,CAAC,QAAQ;AACxB,YAAMA,QAAO,MAAM;AACnB,MAAAA,MAAK,WAAW,QAAQ,CAAC,MAAMP,WAAU;AACvC,cAAM,CAAC,UAAU,EAAE,UAAU,IAAI,oBAAoB,IAAI;AACzD,cAAM,YAAY,MAAM;AACxB,YAAI,UAAU,WAAW,MAAM;AAC7B,gBAAM,cAAc,UAAU,QAAQ,QAAQ,UAAU;AACxD,cAAI,gBAAgB,IAAI;AACtB,kBAAM,YAAY,GAAG,YAAY;AACjC,YAAAO,MAAK,WAAWP,UAAS;AAAA,UAC3B;AAAA,QACF;AACA,QAAAO,MAAK,OAAO,KAAK,SAAS;AAC1B,kBAAU,SAAS,KAAKA,KAAI;AAAA,MAC9B,CAAC;AAAA,IACH,CAAC;AACD,UAAM,gBAAgB,YAAY;AAClC,gBAAY,UAAU,UAAU,QAAQ,CAAC,WAAW;AAClD,YAAM,CAAC,UAAUP,MAAK,IAAI,oBAAoB,cAAc,OAAO,KAAK;AACxE,YAAMO,QAAO,MAAM;AACnB,UAAIA,SAAQ,MAAM;AAChB,QAAAA,MAAK,gBAAgBP;AACrB,gBAAQ,KAAKO,KAAI;AAAA,MACnB;AAAA,IACF,CAAC;AACD,UAAM,YAAY,KAAK,mBAAmB,WAAW;AACrD,WAAO,EAAE,OAAO,QAAQ,SAAS,SAAS,cAAc,UAAU;AAAA,EACpE;AAAA,EACA,mBAAmB,aAAa;AAC9B,WAAO;AAAA,MACL,YAAY,YAAY,UAAU;AAAA,MAClC,QAAQ,YAAY,UAAU,SAAS,OAAO,CAAC,KAAK,QAAQ;AAC1D,YAAI,IAAI,QAAQ,KAAK,mBAAmB,GAAG;AAC3C,eAAO;AAAA,MACT,GAAG,CAAC,CAAC;AAAA,MACL,SAAS,YAAY,UAAU,UAAU,OAAO,CAAC,KAAK,QAAQ;AAC5D,YAAI,IAAI,QAAQ,KAAK,mBAAmB,KAAK,YAAY,GAAG;AAC5D,eAAO;AAAA,MACT,GAAG,CAAC,CAAC;AAAA,IACP;AAAA,EACF;AAAA,EACA,mBAAmB,KAAK,UAAU;AAChC,QAAI,OAAO,IAAI;AACf,QAAI,YAAY,MAAM;AACpB,aAAO,SAAS;AAAA,IAClB;AACA,WAAO,EAAE,MAAM,OAAO,IAAI,KAAK;AAAA,EACjC;AACF;AACA,SAAS,aAAa,MAAM;AAC1B,QAAM,UAAU,IAAI,EAAE;AACtB,MAAI,OAAO,QAAQ,SAAS,aAAa;AACvC,WAAO,QAAQ,KAAK,IAAI;AAAA,EAC1B,WAAW,OAAO,WAAW,aAAa;AACxC,WAAO,IAAI,OAAO,MAAM,QAAQ,EAAE,SAAS;AAAA,EAC7C,OAAO;AACL,UAAM,IAAI,MAAM,kFAAkF;AAAA,EACpG;AACF;AACA,SAAS,iBAAiB,IAAI,UAAU;AACtC,QAAM,QAAQ,MAAM,QAAQ,EAAE,IAAI,OAAO,aAAa,MAAM,MAAM,EAAE,IAAI,aAAa,EAAE;AACvF,SAAO,WAAW,QAAQ,MAAM,YAAY;AAC9C;AACA,SAAS,eAAe,OAAO,MAAM,KAAK,WAAW,OAAO;AAC1D,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM;AACjB,WAAO,iBAAiB,MAAM,GAAG,QAAQ;AAAA,EAC3C;AACA,SAAO;AACT;AACA,SAAS,aAAa,OAAO,MAAM,KAAK;AACtC,QAAM,QAAQ,MAAM;AACpB,SAAO,QAAQ,MAAM,IAAI;AAC3B;AACA,SAAS,eAAe,OAAO,MAAM,KAAK;AACxC,QAAM,QAAQ,MAAM,SAAS,CAAC;AAC9B,QAAM,QAAQ,MAAM,QAAQ,OAAO,MAAM,OAAO,MAAM,QAAQ,OAAO,MAAM,OAAO;AAClF,SAAO,OAAO,UAAU,WAAW,QAAQ,SAAS,OAAO,EAAE;AAC/D;AACA,SAAS,gBAAgB,OAAO;AAC9B,MAAI,OAAO,UAAU,UAAU;AAC7B,YAAQ,SAAS;AAAA,EACnB;AACA,UAAQ;AAAA,SACD,SAAS;AAAA,SACT,SAAS;AACZ,aAAO;AAAA,SACJ,SAAS;AAAA,SACT,SAAS;AAAA,SACT,SAAS;AAAA,SACT,SAAS;AACZ,aAAO;AAAA,SACJ,SAAS;AACZ,aAAO;AAAA,SACJ,SAAS;AACZ,aAAO;AAAA,SACJ,SAAS;AACZ,aAAO;AAAA;AAEP,aAAO;AAAA;AAEb;AACA,SAAS,aAAa,OAAO,MAAM,KAAK;AACtC,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM,MAAM;AACvB,WAAO,MAAM,KAAK;AAAA,EACpB;AACA,SAAO;AACT;AACA,SAAS,cAAc,OAAO,MAAM,KAAK;AACvC,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM,MAAM;AACvB,WAAO,gBAAgB,MAAM,IAAI;AAAA,EACnC;AACA,SAAO;AACT;AACA,SAAS,mBAAmB,OAAO,MAAM,KAAK;AAC5C,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM,QAAQ,MAAM,KAAK,MAAM;AAC1C,WAAO,MAAM,KAAK,KAAK,IAAI,CAAC,MAAM,gBAAgB,CAAC,CAAC;AAAA,EACtD;AACA,SAAO;AACT;AACA,SAAS,sBAAsB,OAAO;AACpC,MAAI,MAAM,aAAa;AACrB,WAAO;AAAA,EACT;AACA,MAAI,MAAM,OAAO,MAAM;AACrB,WAAO,MAAM,IAAI,IAAI,CAAC,QAAQ,OAAO,IAAI,SAAS,WAAW,IAAI,OAAO,SAAS,IAAI,MAAM,EAAE,CAAC;AAAA,EAChG;AACA,SAAO,CAAC;AACV;AACA,SAAS,oBAAoB,OAAO,MAAM,KAAK;AAC7C,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM,OAAO;AACxB,WAAO,sBAAsB,MAAM,KAAK;AAAA,EAC1C;AACA,SAAO;AACT;AACA,SAAS,qBAAqB,OAAO,MAAM,KAAK;AAC9C,QAAM,QAAQ,MAAM;AACpB,MAAI,OAAO;AACT,aAAS,MAAM,KAAK,KAAK,MAAM,KAAK,EAAE,SAAS,MAAM,KAAK,IAAI,MAAM,KAAK,MAAM,CAAC,GAAG,IAAI,CAAC,MAAM,OAAO,MAAM,WAAW,IAAI,SAAS,GAAG,EAAE,CAAC;AAAA,EAC3I;AACA,SAAO;AACT;AACA,SAAS,oBAAoB,OAAO,MAAM,KAAK,WAAW,OAAO;AAC/D,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM,QAAQ,MAAM,KAAK,GAAG;AACvC,WAAO,MAAM,KAAK,EAAE,IAAI,CAAC,MAAM;AAC7B,aAAO,iBAAiB,GAAG,QAAQ;AAAA,IACrC,CAAC;AAAA,EACH;AACA,SAAO;AACT;AACA,SAAS,yBAAyB,OAAO,MAAM,KAAK;AAClD,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM,QAAQ,MAAM,KAAK,OAAO;AAC3C,WAAO,MAAM,KAAK,MAAM,IAAI,CAAC,MAAM;AACjC,aAAO,sBAAsB,CAAC;AAAA,IAChC,CAAC;AAAA,EACH;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,OAAO,MAAM,KAAK;AAC3C,QAAM,QAAQ,MAAM;AACpB,MAAI,SAAS,MAAM,QAAQ,MAAM,KAAK,GAAG;AACvC,WAAO,MAAM,KAAK;AAAA,EACpB;AACA,SAAO;AACT;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAYA,OAAM,WAAW,SAAS;AACpC,SAAK,OAAOA;AACZ,SAAK,YAAY;AACjB,SAAK,UAAU;AACf,SAAK,SAAS,CAAC;AACf,SAAK,QAAQ,CAAC;AACd,SAAK,SAASA,MAAK,WAAW,IAAI,CAAC,SAAS,KAAK,SAAS,IAAI,CAAC;AAC/D,QAAIA,MAAK,YAAY,MAAM;AACzB,WAAK,QAAQ,OAAO,KAAKA,MAAK,QAAQ,EAAE,OAAO,CAAC,OAAO,QAAQ;AAC7D,cAAM,OAAO,KAAK,QAAQ,GAAG;AAC7B,eAAO;AAAA,MACT,GAAG,CAAC,CAAC;AAAA,IACP;AAAA,EACF;AAAA,EACA,SAAS,MAAM;AACb,WAAO,UAAU,MAAM,KAAK,WAAW,KAAK,OAAO;AAAA,EACrD;AAAA,EACA,QAAQ,MAAM,cAAc;AAC1B,UAAM,QAAQ,KAAK,KAAK,SAAS;AACjC,QAAI,MAAM,UAAU,MAAM;AACxB,aAAO,UAAU,MAAM,KAAK,WAAW,KAAK,OAAO;AAAA,IACrD;AACA,QAAI,MAAM,KAAK,QAAQ,MAAM,KAAK,MAAM;AACtC,aAAO,eAAe,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,IAC9D;AACA,QAAI,MAAM,KAAK,MAAM;AACnB,aAAO,eAAe,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,IAC9D;AACA,QAAI,MAAM,KAAK,MAAM;AACnB,aAAO,aAAa,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,IAC5D;AACA,QAAI,MAAM,SAAS,MAAM;AACvB,aAAO,oBAAoB,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,IACnE;AACA,QAAI,MAAM,QAAQ,MAAM;AACtB,aAAO,cAAc,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,IAC7D;AACA,QAAI,MAAM,QAAQ,MAAM;AACtB,UAAI,MAAM,KAAK,KAAK,QAAQ,MAAM,KAAK,KAAK,MAAM;AAChD,eAAO,qBAAqB,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,MACpE;AACA,UAAI,MAAM,KAAK,KAAK,MAAM;AACxB,eAAO,oBAAoB,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,MACnE;AACA,UAAI,MAAM,KAAK,SAAS,MAAM;AAC5B,eAAO,yBAAyB,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,MACxE;AACA,UAAI,MAAM,KAAK,KAAK,MAAM;AACxB,eAAO,kBAAkB,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,MACjE;AACA,UAAI,MAAM,KAAK,QAAQ,MAAM;AAC3B,eAAO,mBAAmB,KAAK,KAAK,UAAU,MAAM,YAAY;AAAA,MAClE;AAAA,IACF;AACA,WAAO;AAAA,EACT;AACF;AAGA,IAAI,4BAA4B,CAAC;AACjCnB,UAAS,2BAA2B;AAAA,EAClC,iBAAiB,MAAM;AAAA,EACvB,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,KAAK,MAAM;AAAA,EACX,KAAK,MAAM;AAAA,EACX,QAAQ,MAAM;AAAA,EACd,QAAQ,MAAM;AAAA,EACd,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,OAAO,MAAM;AAAA,EACb,SAAS,MAAM;AAAA,EACf,WAAW,MAAM;AAAA,EACjB,eAAe,MAAM;AAAA,EACrB,WAAW,MAAM;AAAA,EACjB,aAAa,MAAM;AAAA,EACnB,aAAa,MAAM;AAAA,EACnB,aAAa,MAAM;AAAA,EACnB,gBAAgB,MAAM;AAAA,EACtB,UAAU,MAAM;AAAA,EAChB,kBAAkB,MAAM;AAAA,EACxB,eAAe,MAAM;AAAA,EACrB,aAAa,MAAM;AAAA,EACnB,QAAQ,MAAM;AAAA,EACd,MAAM,MAAM;AAAA,EACZ,MAAM,MAAM;AAAA,EACZ,aAAa,MAAM;AAAA,EACnB,OAAO,MAAM;AAAA,EACb,SAAS,MAAM;AAAA,EACf,QAAQ,MAAM;AAAA,EACd,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,QAAQ,MAAM;AAAA,EACd,QAAQ,MAAM;AAAA,EACd,iBAAiB,MAAM;AAAA,EACvB,QAAQ,MAAM;AAAA,EACd,iBAAiB,MAAM;AAAA,EACvB,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,cAAc,MAAM;AAAA,EACpB,SAAS,MAAM;AAAA,EACf,QAAQ,MAAM;AAAA,EACd,eAAe,MAAM;AAAA,EACrB,cAAc,MAAM;AAAA,EACpB,iBAAiB,MAAM;AAAA,EACvB,MAAM,MAAM;AAAA,EACZ,YAAY,MAAM;AAAA,EAClB,KAAK,MAAM;AAAA,EACX,UAAU,MAAM;AAAA,EAChB,KAAK,MAAM;AAAA,EACX,SAAS,MAAM;AAAA,EACf,QAAQ,MAAM;AAAA,EACd,KAAK,MAAM;AAAA,EACX,qBAAqB,MAAM;AAAA,EAC3B,OAAO,MAAM;AAAA,EACb,KAAK,MAAM;AAAA,EACX,eAAe,MAAM;AAAA,EACrB,KAAK,MAAM;AAAA,EACX,YAAY,MAAM;AAAA,EAClB,OAAO,MAAM;AAAA,EACb,KAAK,MAAM;AAAA,EACX,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,UAAU,MAAM;AAAA,EAChB,OAAO,MAAM;AAAA,EACb,QAAQ,MAAM;AAAA,EACd,UAAU,MAAM;AAAA,EAChB,SAAS,MAAM;AAAA,EACf,cAAc,MAAM;AAAA,EACpB,MAAM,MAAM;AAAA,EACZ,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,aAAa,MAAM;AAAA,EACnB,OAAO,MAAM;AAAA,EACb,UAAU,MAAM;AAAA,EAChB,OAAO,MAAM;AAAA,EACb,OAAO,MAAM;AAAA,EACb,WAAW,MAAM;AAAA,EACjB,MAAM,MAAM;AAAA,EACZ,WAAW,MAAM;AAAA,EACjB,QAAQ,MAAM;AAAA,EACd,UAAU,MAAM;AAAA,EAChB,4BAA4B,MAAM;AAAA,EAClC,KAAK,MAAMF;AAAA,EACX,OAAO,MAAM;AAAA,EACb,YAAY,MAAM;AAAA,EAClB,YAAY,MAAM;AAAA,EAClB,WAAW,MAAM;AAAA,EACjB,YAAY,MAAM;AAAA,EAClB,YAAY,MAAM;AAAA,EAClB,WAAW,MAAM;AAAA,EACjB,YAAY,MAAM;AAAA,EAClB,QAAQ,MAAM;AAAA,EACd,YAAY,MAAM;AAAA,EAClB,QAAQ,MAAM;AAAA,EACd,KAAK,MAAM;AAAA,EACX,SAAS,MAAM;AAAA,EACf,WAAW,MAAM;AAAA,EACjB,mBAAmB,MAAM;AAAA,EACzB,SAAS,MAAM;AAAA,EACf,MAAM,MAAM;AAAA,EACZ,UAAU,MAAM;AAAA,EAChB,KAAK,MAAM;AAAA,EACX,SAAS,MAAM;AAAA,EACf,WAAW,MAAM;AAAA,EACjB,KAAK,MAAM;AAAA,EACX,SAAS,MAAM;AAAA,EACf,eAAe,MAAM;AAAA,EACrB,KAAK,MAAM;AAAA,EACX,cAAc,MAAM;AAAA,EACpB,aAAa,MAAM;AAAA,EACnB,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,UAAU,MAAM;AAAA,EAChB,QAAQ,MAAM;AAAA,EACd,MAAM,MAAM;AAAA,EACZ,UAAU,MAAM;AAAA,EAChB,IAAI,MAAM;AAAA,EACV,cAAc,MAAM;AAAA,EACpB,KAAK,MAAM;AAAA,EACX,OAAO,MAAM;AAAA,EACb,OAAO,MAAM;AAAA,EACb,OAAO,MAAM;AAAA,EACb,OAAO,MAAM;AAAA,EACb,MAAM,MAAM;AAAA,EACZ,KAAK,MAAM;AAAA,EACX,OAAO,MAAM;AAAA,EACb,OAAO,MAAM;AAAA,EACb,MAAM,MAAM;AAAA,EACZ,MAAM,MAAM;AAAA,EACZ,aAAa,MAAM;AAAA,EACnB,cAAc,MAAM;AAAA,EACpB,sBAAsB,MAAM;AAAA,EAC5B,eAAe,MAAM;AAAA,EACrB,OAAO,MAAM;AAAA,EACb,MAAM,MAAM;AAAA,EACZ,YAAY,MAAM;AAAA,EAClB,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,SAAS,MAAM;AAAA,EACf,SAAS,MAAM;AAAA,EACf,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,OAAO,MAAM;AAAA,EACb,QAAQ,MAAM;AAAA,EACd,WAAW,MAAM;AAAA,EACjB,cAAc,MAAM;AAAA,EACpB,MAAM,MAAM;AAAA,EACZ,iBAAiB,MAAM;AAAA,EACvB,gBAAgB,MAAM;AAAA,EACtB,SAAS,MAAM;AAAA,EACf,MAAM,MAAM;AAAA,EACZ,QAAQ,MAAM;AAAA,EACd,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,OAAO,MAAM;AAAA,EACb,SAAS,MAAM;AAAA,EACf,SAAS,MAAM;AAAA,EACf,SAAS,MAAM;AAAA,EACf,SAAS,MAAM;AAAA,EACf,SAAS,MAAM;AAAA,EACf,UAAU,MAAM;AAAA,EAChB,gBAAgB,MAAM;AAAA,EACtB,QAAQ,MAAM;AAAA,EACd,eAAe,MAAM;AAAA,EACrB,UAAU,MAAM;AAAA,EAChB,OAAO,MAAM;AAAA,EACb,MAAM,MAAM;AAAA,EACZ,QAAQ,MAAM;AAAA,EACd,mBAAmB,MAAM;AAAA,EACzB,SAAS,MAAM;AAAA,EACf,OAAO,MAAM;AAAA,EACb,MAAM,MAAM;AAAA,EACZ,cAAc,MAAM;AAAA,EACpB,QAAQ,MAAM;AAAA,EACd,KAAK,MAAM;AAAA,EACX,KAAK,MAAM;AAAA,EACX,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,QAAQ,MAAM;AAAA,EACd,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,MAAM,MAAM;AAAA,EACZ,MAAM,MAAM;AAAA,EACZ,WAAW,MAAM;AAAA,EACjB,iBAAiB,MAAM;AAAA,EACvB,QAAQ,MAAM;AAAA,EACd,oBAAoB,MAAM;AAAA,EAC1B,SAAS,MAAM;AAAA,EACf,YAAY,MAAM;AAAA,EAClB,UAAU,MAAM;AAAA,EAChB,OAAO,MAAM;AAAA,EACb,YAAY,MAAM;AAAA,EAClB,OAAO,MAAM;AAAA,EACb,WAAW,MAAM;AACnB,CAAC;AAGD,IAAI,YAAY,CAACqB,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC7E,UAAQA,MAAK;AAAA,SACN;AAAA,SACA;AAAA,SACA,OAAO;AACV,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC7G;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,WAAWA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACtE;AAAA,SACK;AAAA,SACA;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SACxG;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SACxG;AAAA,SACA,OAAO;AACV,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC7G;AAAA,SACK,YAAY;AACf,aAAO,CAAC,IAAI,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAClH;AAAA,SACK,YAAY;AACf,aAAO,CAAC,IAAI,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAClH;AAAA,SACK,OAAO;AACV,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC7G;AAAA,SACK,WAAW;AACd,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACjH;AAAA,SACK,WAAW;AACd,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACjH;AAAA,SACK,OAAO;AACV,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC7G;AAAA,SACK,qBAAqB;AACxB,aAAO,CAAC,IAAI,kBAAkB,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC3H;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,aAAa,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC9E,UAAQA,MAAK;AAAA,SACN;AAAA,SACA;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC5D;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC5D;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1G;AACH,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC5D;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,QAAQ,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAClH;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D,SAAS;AACZ,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACjE;AAAA,SACK;AACH,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC5D;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D,SAAS;AACZ,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACjE;AAAA,SACK;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D,cAAc;AACjB,aAAO,CAAC,IAAI,WAAW,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACtE;AAAA,SACK;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D,SAAS;AACZ,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACjE;AAAA,SACK;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3D;AACH,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC9D;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAChE;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAChE;AAAA,SACK,YAAY;AACf,aAAO,CAAC,IAAI,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACpE;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAChE;AAAA,SACK,UAAU;AACb,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAClE;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAChE;AAAA,SACK;AACH,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1D;AACH,aAAO,CAAC,IAAI,YAAY,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,gBAAgBA,OAAM,WAAW,OAAO,GAAG,cAAc,gBAAgBA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SACpL;AACH,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC5D;AACH,aAAO,CAAC,IAAI,MAAM,UAAUA,MAAK,WAAW,IAAI,WAAW,OAAO,CAAC,CAAC;AAAA,SACjE;AACH,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC5G;AACH,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAClH;AACH,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC9G;AACH,aAAO,CAAC,IAAI,MAAM,UAAUA,MAAK,WAAW,IAAI,WAAW,OAAO,CAAC,CAAC;AAAA;AAEpE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,SAAS,oCAAoC,QAAQ,QAAQ,qBAAqB,IAAI;AACpF,MAAI,OAAO,WAAW,YAAY,OAAO,WAAW,UAAU;AAC5D;AAAA,EACF;AACA,eAAa,OAAO,OAAO,WAAW,OAAO,QAAQ,MAAM,qBAAqB,WAAW,cAAc,mBAAmB;AAC5H,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,UAAM,OAAO,OAAO;AACpB,UAAM,OAAO,OAAO;AACpB,iBAAa,OAAO,OAAO,KAAK,OAAO,KAAK,SAAS,MAAM,MAAM,qBAAqB,WAAW,cAAc,mBAAmB;AAAA,EACpI;AACF;AACA,SAAS,iBAAiB,cAAc;AACtC,MAAI,OAAO,iBAAiB,YAAY,aAAa,KAAK,CAAC,QAAQ,MAAM,CAAC,GAAG;AAC3E,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,kBAAkB,SAAS,cAAc;AAClE,MAAI,eAAe,kBAAkB,kBAAkB,YAAY;AACnE,QAAM,sBAAsB,CAAC,iBAAiB,YAAY;AAC1D,MAAI,uBAAuB,QAAQ,WAAW,GAAG;AAC/C,UAAM,IAAI,MAAM,qFAAqF,cAAc;AAAA,EACrH;AACA,MAAI,qBAAqB;AACvB,YAAQ,QAAQ,CAAC,YAAY;AAC3B,qBAAe,kBAAkB,QAAQ,OAAO,YAAY;AAAA,IAC9D,CAAC;AAAA,EACH;AACA,MAAI,CAAC,iBAAiB,YAAY,GAAG;AACnC,UAAM,IAAI,MAAM,mCAAmC,cAAc;AAAA,EACnE;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,eAAe,eAAe;AACvD,MAAI,OAAO,kBAAkB,UAAU;AACrC,WAAO;AAAA,EACT;AACA,MAAI,OAAO,kBAAkB,UAAU;AACrC,WAAO;AAAA,EACT;AACA,MAAI,cAAc,WAAW,cAAc,QAAQ;AACjD,UAAM,IAAI,MAAM,oCAAoC,qBAAqB,eAAe;AAAA,EAC1F;AACA,QAAM,SAAS,CAAC;AAChB,WAAS,KAAK,GAAG,KAAK,cAAc,QAAQ,EAAE,IAAI;AAChD,UAAM,OAAO,cAAc;AAC3B,UAAM,OAAO,cAAc;AAC3B,QAAI,QAAQ,KAAK,QAAQ,KAAK,SAAS,MAAM;AAC3C,YAAM,IAAI,MAAM,oCAAoC,qBAAqB,eAAe;AAAA,IAC1F;AACA,WAAO,MAAM,QAAQ,IAAI,OAAO;AAAA,EAClC;AACA,SAAO;AACT;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,MAAM,OAAOe,UAAS,cAAc,wBAAwB,aAAa,gBAAgB;AACnG,SAAK,OAAO;AACZ,SAAK,QAAQ;AACb,SAAK,UAAUA;AACf,SAAK,eAAe;AACpB,SAAK,yBAAyB;AAC9B,SAAK,cAAc;AACnB,SAAK,iBAAiB;AACtB,SAAK,UAAU,CAAC;AAChB,SAAK,UAAU;AACf,SAAK,WAAW,OAAO,CAAC;AACxB,SAAK,KAAK,QAAQ;AAAA,EACpB;AAAA,EACA,IAAI,KAAK;AACP,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,IAAI,SAAS;AACX,WAAO,KAAK;AAAA,EACd;AAAA,EACA,cAAc,SAAS;AACrB,SAAK,QAAQ,QAAQ,CAAC,YAAY;AAChC,UAAI,WAAW,QAAQ,CAAC,QAAQ,IAAI,QAAQ,OAAO,EAAE,GAAG;AACtD,gBAAQ,OAAO,QAAQ;AAAA,MACzB;AAAA,IACF,CAAC;AACD,SAAK,UAAU,CAAC;AAChB,SAAK,UAAU;AACf,SAAK,SAAS,QAAQ;AAAA,EACxB;AAAA,EACA,OAAO;AACL,WAAO,KAAK,QAAQ;AAAA,EACtB;AAAA,EACA,KAAKtB,QAAO;AACV,QAAI,KAAK,SAAS;AAChB,YAAM,IAAI,MAAM,eAAe,KAAK,+BAA+B;AAAA,IACrE;AACA,QAAIA,SAAQ,KAAKA,UAAS,KAAK,KAAK,GAAG;AACrC,YAAM,IAAI,MAAM,4BAA4BA,8BAA6B,KAAK,KAAK,GAAG;AAAA,IACxF;AACA,UAAM,kBAAkB,KAAK,QAAQA;AACrC,QAAI,gBAAgB,SAAS;AAC3B,YAAM,IAAI,MAAM,eAAe,KAAK,8BAA8BA,4GAA2G;AAAA,IAC/K;AACA,QAAI,KAAK,gBAAgB;AACvB,sBAAgB,UAAU;AAAA,IAC5B;AACA,oBAAgB,OAAO;AACvB,WAAO,gBAAgB;AAAA,EACzB;AAAA,EACA,SAAS,SAAS;AAChB,WAAO,QAAQ,IAAI,CAACA,WAAU,KAAK,KAAKA,MAAK,CAAC;AAAA,EAChD;AAAA,EACA,MAAMA,QAAO,SAAS;AACpB,QAAI,KAAK,SAAS;AAChB,YAAM,IAAI,MAAM,eAAe,KAAK,+BAA+B;AAAA,IACrE;AACA,QAAIA,SAAQ,KAAK,CAAC,KAAK,eAAeA,UAAS,KAAK,SAAS;AAC3D,YAAM,IAAI,MAAM,2BAA2BA,oDAAmD,KAAK,SAAS;AAAA,IAC9G;AACA,UAAM,KAAK,KAAK,QAAQA,WAAU,CAAC;AACnC,QAAI,QAAQ,UAAU,KAAK,OAAO;AAChC,YAAM,IAAI,MAAM,eAAe,KAAK,8CAA8CA;AAAA,uCACjD,QAAQ,mCAAmC,KAAK,QAAQ;AAAA,IAC3F;AACA,QAAI,KAAK,KAAK,MAAM,MAAM,KAAK,gBAAgB,QAAQ,KAAK,aAAa,WAAW,IAAI;AACtF,WAAK,eAAe,QAAQ;AAAA,IAC9B;AACA,wCAAoC,KAAK,cAAc,QAAQ,OAAO,eAAe,KAAK,8CAA8CA,SAAQ;AAChJ,QAAI,GAAG,MAAM;AACX,YAAM,IAAI,MAAM,eAAe,KAAK,8CAA8CA,2CAA0C;AAAA,IAC9H;AACA,QAAI,GAAG,SAAS;AACd,YAAM,IAAI,MAAM,eAAe,KAAK,8CAA8CA,8CAA6C;AAAA,IACjI;AACA,OAAG,SAAS;AACZ,SAAK,OAAO;AACZ,OAAG,UAAU;AACb,SAAK,QAAQA,UAAS;AAAA,EACxB;AAAA,EACA,UAAU,SAAS,SAAS;AAC1B,QAAI,QAAQ,WAAW,QAAQ,QAAQ;AACrC,YAAM,IAAI,MAAM,eAAe,KAAK,kEAAkE,QAAQ,2CAA2C,QAAQ,SAAS;AAAA,IAC5K;AACA,YAAQ,QAAQ,CAAC,IAAIA,WAAU,KAAK,MAAM,IAAI,QAAQA,OAAM,CAAC;AAAA,EAC/D;AAAA,EACA,OAAO,SAAS,OAAO;AACrB,QAAI,CAAC,CAAC,SAAS,UAAU,KAAK,OAAO;AACnC,YAAM,IAAI,MAAM,wBAAwB,KAAK,oCAAoC,OAAO;AAAA,IAC1F;AACA,QAAI,CAAC,SAAS;AACZ,gBAAU,CAAC;AACX,eAAS,KAAK,GAAG,KAAK,KAAK,KAAK,GAAG,MAAM;AACvC,gBAAQ,KAAK,EAAE;AAAA,MACjB;AAAA,IACF,OAAO;AACL,gBAAU,QAAQ,MAAM,GAAG,KAAK,KAAK,CAAC;AAAA,IACxC;AACA,QAAI,QAAQ,WAAW,GAAG;AACxB,aAAO,OAAO,CAAC,GAAG,CAAC,CAAC,EAAE,OAAO,KAAK,YAAY,CAAC;AAAA,IACjD;AACA,UAAM,UAAU,KAAK,SAAS,OAAO;AACrC,wCAAoC,KAAK,cAAc,QAAQ,GAAG,OAAO,8BAA8B;AACvG,WAAO,MAAM,SAAS,CAAC;AAAA,EACzB;AAAA,EACA,OAAO,OAAO;AACZ,QAAI,CAAC,CAAC,SAAS,UAAU,KAAK,OAAO;AACnC,YAAM,IAAI,MAAM,wBAAwB,KAAK,oCAAoC,OAAO;AAAA,IAC1F;AACA,QAAI,KAAK,KAAK,MAAM,GAAG;AACrB,aAAO,OAAO,CAAC,GAAG,CAAC,CAAC,EAAE,OAAO,KAAK,YAAY,CAAC;AAAA,IACjD;AACA,UAAM,UAAU,CAAC;AACjB,aAAS,KAAK,GAAG,KAAK,KAAK,KAAK,GAAG,MAAM;AACvC,cAAQ,KAAK,EAAE;AAAA,IACjB;AACA,UAAM,UAAU,KAAK,SAAS,OAAO;AACrC,wCAAoC,KAAK,cAAc,QAAQ,GAAG,OAAO,mDAAmD,KAAK,wCAAwC,QAAQ,GAAG,QAAQ;AAC5L,WAAO,OAAO,SAAS,CAAC;AAAA,EAC1B;AAAA,EACA,QAAQ,SAAS,SAAS;AACxB,QAAI,QAAQ,UAAU,KAAK,OAAO;AAChC,YAAM,IAAI,MAAM,wBAAwB,KAAK,8BAA8B,QAAQ,OAAO;AAAA,IAC5F;AACA,QAAI,QAAQ,WAAW,QAAQ,MAAM,IAAI;AACvC,YAAM,IAAI,MAAM,sDAAsD,QAAQ,cAAc,QAAQ,MAAM,IAAI;AAAA,IAChH;AACA,UAAM,WAAW,KAAK,IAAI,GAAG,OAAO;AACpC,QAAI,CAAC,KAAK,eAAe,YAAY,KAAK,SAAS;AACjD,YAAM,IAAI,MAAM,mCAAmC,iBAAiB,KAAK,UAAU;AAAA,IACrF;AACA,SAAK,UAAU,SAAS,QAAQ,SAAS,CAAC,CAAC;AAAA,EAC7C;AAAA,EACA,MAAM,QAAQ,SAAS;AACrB,QAAI,QAAQ,UAAU,KAAK,OAAO;AAChC,YAAM,IAAI,MAAM,wBAAwB,KAAK,8BAA8B,QAAQ,OAAO;AAAA,IAC5F;AACA,QAAI,cAAc;AAClB,UAAM,oBAAoB,OAAO,IAAI,CAAC,QAAQ;AAC5C,qBAAe;AACf,aAAO;AAAA,IACT,CAAC;AACD,QAAI,gBAAgB,QAAQ,MAAM,IAAI;AACpC,YAAM,IAAI,MAAM;AAAA;AAAA,UAEZ,uCAAuC,QAAQ,OAAO;AAAA,IAC5D;AACA,QAAI,CAAC,KAAK,eAAe,OAAO,WAAW,KAAK,SAAS;AACvD,YAAM,IAAI,MAAM,2DAA2D,KAAK,eAAe,OAAO,sEAAsE;AAAA,IAC9K;AACA,UAAM,gBAAgB,gBAAgB,IAAI,IAAI,QAAQ,OAAO;AAC7D,UAAM,UAAU,CAAC;AACjB,SAAK,MAAM;AACT,gBAAU,QAAQ,SAAS,CAAC,GAAG,aAAa,aAAa,CAAC;AAC1D,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,cAAM,iBAAiB,OAAO,IAAI,IAAI,kBAAkB,KAAK;AAC7D,cAAM,WAAW,CAAC,GAAG,gBAAgB,CAAC;AACtC,cAAM,QAAQ,CAAC,GAAG,OAAO,KAAK,aAAa;AAC3C,gBAAQ,MAAM,QAAQ,MAAM,SAAS,UAAU,KAAK,GAAG,KAAK,YAAY;AAAA,MAC1E;AACA,aAAO;AAAA,IACT,CAAC;AACD,UAAM,UAAU,CAAC;AACjB,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,cAAQ,MAAM;AAAA,IAChB;AACA,SAAK,UAAU,SAAS,OAAO;AAAA,EACjC;AACF;AAGA,IAAI,aAAa,MAAM;AAAA,EACrB,YAAY,SAAS,cAAc,cAAc,iBAAiB,IAAI;AACpE,SAAK,UAAU;AACf,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,QAAI,WAAW,MAAM;AACnB,cAAQ,QAAQ,CAAC,YAAY;AAC3B,YAAI,iBAAiB,QAAQ,OAAO;AAClC,gBAAM,IAAI,MAAM,mCAAmC,mCAAmC,QAAQ,OAAO;AAAA,QACvG;AACA,4CAAoC,cAAc,QAAQ,OAAO,6BAA6B;AAC9F,aAAK,OAAO;AAAA,MACd,CAAC;AAAA,IACH;AACA,SAAK,WAAW,OAAO,CAAC;AACxB,SAAK,iBAAiB;AACtB,SAAK,KAAK,QAAQ;AAAA,EACpB;AAAA,EACA,IAAI,KAAK;AACP,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,OAAO;AACL,WAAO,IAAI,WAAW,CAAC,GAAG,KAAK,OAAO,GAAG,KAAK,cAAc,KAAK,YAAY;AAAA,EAC/E;AAAA,EACA,cAAc,SAAS;AACrB,SAAK,QAAQ,QAAQ,CAAC,YAAY;AAChC,UAAI,WAAW,QAAQ,CAAC,QAAQ,IAAI,QAAQ,EAAE,GAAG;AAC/C,gBAAQ,QAAQ;AAAA,MAClB;AAAA,IACF,CAAC;AACD,SAAK,QAAQ,SAAS;AACtB,SAAK,SAAS,QAAQ;AAAA,EACxB;AAAA,EACA,OAAO;AACL,WAAO,KAAK,QAAQ;AAAA,EACtB;AAAA,EACA,MAAM,cAAc,cAAc,cAAc,IAAI;AAClD,QAAI,iBAAiB,KAAK,cAAc;AACtC,YAAM,IAAI,MAAM,mCAAmC,mCAAmC,KAAK,cAAc;AAAA,IAC3G;AACA,QAAI,gBAAgB,MAAM,KAAK,QAAQ,WAAW,aAAa;AAC7D,YAAM,IAAI,MAAM,kCAAkC,4CAA4C,KAAK,QAAQ,kBAAkB;AAAA,IAC/H;AACA,wCAAoC,cAAc,KAAK,cAAc,6BAA6B;AAClG,UAAM,qBAAqB,kBAAkB,KAAK,cAAc,KAAK,SAAS,YAAY;AAC1F,WAAO,KAAK,MAAM;AAChB,YAAM,kBAAkB,KAAK,QAAQ,IAAI,CAAC,YAAY,QAAQ,SAAS,kBAAkB,CAAC;AAC1F,aAAO,MAAM,iBAAiB,CAAC;AAAA,IACjC,CAAC;AAAA,EACH;AAAA,EACA,QAAQ,cAAc,cAAc;AAClC,QAAI,iBAAiB,KAAK,cAAc;AACtC,YAAM,IAAI,MAAM,mCAAmC,mCAAmC,KAAK,cAAc;AAAA,IAC3G;AACA,QAAI,KAAK,KAAK,MAAM,GAAG;AACrB,YAAM,IAAI,MAAM,mCAAmC;AAAA,IACrD;AACA,UAAM,qBAAqB,kBAAkB,KAAK,cAAc,KAAK,SAAS,YAAY;AAC1F,UAAM,UAAU,KAAK,QAAQ,IAAI;AACjC,wCAAoC,QAAQ,OAAO,cAAc,6BAA6B;AAC9F,WAAO,QAAQ,SAAS,kBAAkB;AAAA,EAC5C;AAAA,EACA,SAAS,SAAS;AAChB,QAAI,QAAQ,UAAU,KAAK,cAAc;AACvC,YAAM,IAAI,MAAM,mCAAmC,QAAQ,4BAA4B,KAAK,cAAc;AAAA,IAC5G;AACA,wCAAoC,QAAQ,OAAO,KAAK,cAAc,6BAA6B;AACnG,QAAI,KAAK,mBAAmB,KAAK,KAAK,GAAG;AACvC,YAAM,IAAI,MAAM,0CAA0C;AAAA,IAC5D;AACA,SAAK,OAAO;AACZ,SAAK,QAAQ,KAAK,OAAO;AAAA,EAC3B;AAAA,EACA,OAAOT,OAAM;AACX,QAAIA,QAAO,GAAG;AACZ,YAAM,IAAI,MAAM,0DAA0DA,OAAM;AAAA,IAClF;AACA,QAAI,KAAK,mBAAmB,MAAMA,QAAO,KAAK,gBAAgB;AAC5D,YAAM,IAAI,MAAM,+BAA+BA,kCAAiC,KAAK,iBAAiB;AAAA,IACxG;AACA,UAAM,iBAAiB,IAAI,WAAW,CAAC,GAAG,KAAK,cAAc,KAAK,cAAc,KAAK,cAAc;AACnG,mBAAe,QAAQ,SAASA;AAChC,aAAS,KAAK,GAAG,KAAK,KAAK,IAAI,KAAK,QAAQ,QAAQA,KAAI,GAAG,EAAE,IAAI;AAC/D,qBAAe,QAAQ,MAAM,KAAK,QAAQ;AAAA,IAC5C;AACA,WAAO;AAAA,EACT;AAAA,EACA,QAAQ,cAAc,cAAc,cAAc;AAChD,QAAI,iBAAiB,KAAK,cAAc;AACtC,YAAM,IAAI,MAAM,mCAAmC,mCAAmC,KAAK,cAAc;AAAA,IAC3G;AACA,QAAI,eAAe,KAAK,eAAe,KAAK,QAAQ,QAAQ;AAC1D,YAAM,IAAI,MAAM,4BAA4B,+BAA+B,KAAK,QAAQ,kBAAkB;AAAA,IAC5G;AACA,QAAI,KAAK,QAAQ,iBAAiB,MAAM;AACtC,YAAM,IAAI,MAAM,oBAAoB,uBAAuB;AAAA,IAC7D;AACA,wCAAoC,KAAK,QAAQ,cAAc,OAAO,cAAc,6BAA6B;AACjH,UAAM,qBAAqB,kBAAkB,KAAK,cAAc,KAAK,SAAS,YAAY;AAC1F,WAAO,QAAQ,KAAK,QAAQ,eAAe,kBAAkB;AAAA,EAC/D;AAAA,EACA,QAAQ,cAAc,SAAS;AAC7B,QAAI,QAAQ,UAAU,KAAK,cAAc;AACvC,YAAM,IAAI,MAAM,mCAAmC,QAAQ,4BAA4B,KAAK,cAAc;AAAA,IAC5G;AACA,QAAI,eAAe,KAAK,KAAK,mBAAmB,MAAM,gBAAgB,KAAK,gBAAgB;AACzF,YAAM,IAAI,MAAM,yBAAyB,mCAAmC,KAAK,0BAA0B;AAAA,IAC7G;AACA,wCAAoC,KAAK,cAAc,QAAQ,OAAO,6BAA6B;AACnG,SAAK,OAAO;AACZ,SAAK,QAAQ,gBAAgB;AAAA,EAC/B;AAAA,EACA,OAAO,SAAS,cAAc,cAAc;AAC1C,QAAI,iBAAiB,KAAK,cAAc;AACtC,YAAM,IAAI,MAAM,mCAAmC,mCAAmC,KAAK,cAAc;AAAA,IAC3G;AACA,wCAAoC,KAAK,cAAc,cAAc,6BAA6B;AAClG,cAAU,QAAQ,MAAM,GAAG,KAAK,KAAK,CAAC;AACtC,UAAM,qBAAqB,kBAAkB,KAAK,cAAc,KAAK,SAAS,YAAY;AAC1F,QAAI,QAAQ,WAAW,GAAG;AACxB,aAAO,OAAO,CAAC,GAAG,CAAC,CAAC,EAAE,OAAO,kBAAkB,CAAC;AAAA,IAClD;AACA,WAAO,KAAK,MAAM;AAChB,YAAM,UAAU,QAAQ,IAAI,CAAC,OAAO,QAAQ,KAAK,QAAQ,KAAK,kBAAkB,CAAC;AACjF,aAAO,MAAM,SAAS,CAAC;AAAA,IACzB,CAAC;AAAA,EACH;AAAA,EACA,OAAO,cAAc,cAAc;AACjC,QAAI,CAAC,CAAC,gBAAgB,iBAAiB,KAAK,cAAc;AACxD,YAAM,IAAI,MAAM,uBAAuB,KAAK,2CAA2C,cAAc;AAAA,IACvG;AACA,wCAAoC,KAAK,cAAc,cAAc,6BAA6B;AAClG,UAAM,qBAAqB,kBAAkB,KAAK,cAAc,KAAK,SAAS,YAAY;AAC1F,QAAI,KAAK,KAAK,MAAM,GAAG;AACrB,aAAO,OAAO,CAAC,GAAG,CAAC,CAAC,EAAE,OAAO,kBAAkB,CAAC;AAAA,IAClD;AACA,WAAO,KAAK,MAAM;AAChB,YAAM,UAAU,KAAK,QAAQ,IAAI,CAAC,OAAO,QAAQ,IAAI,kBAAkB,CAAC;AACxE,aAAO,OAAO,SAAS,CAAC;AAAA,IAC1B,CAAC;AAAA,EACH;AACF;AACA,SAAS,WAAW,SAAS,cAAc,cAAc;AACvD,QAAM,QAAQ,QAAQ;AACtB,MAAI,QAAQ,MAAM,SAAS,GAAG;AAC5B,UAAM,IAAI,MAAM,oDAAoD,QAAQ,OAAO;AAAA,EACrF;AACA,MAAI,QAAQ,UAAU,cAAc;AAClC,UAAM,IAAI,MAAM,mCAAmC,QAAQ,4BAA4B,cAAc;AAAA,EACvG;AACA,QAAM,qBAAqB,QAAQ,MAAM,MAAM,CAAC;AAChD,sCAAoC,oBAAoB,cAAc,6BAA6B;AACnG,QAAM,aAAa,QAAQ,OAAO;AAClC,SAAO,IAAI,WAAW,YAAY,cAAc,KAAK;AACvD;AACA,SAAS,QAAQ,cAAc,cAAc,aAAa,gBAAgB;AACxE,SAAO,IAAI,WAAW,CAAC,GAAG,cAAc,cAAc,cAAc;AACtE;AACA,SAAS,QAAQ,SAAS,SAAS,cAAc,aAAa;AAC5D,MAAI,QAAQ,WAAW,QAAQ,MAAM,IAAI;AACvC,UAAM,IAAI,MAAM,sDAAsD,QAAQ,cAAc,QAAQ,MAAM,IAAI;AAAA,EAChH;AACA,QAAM,WAAW,KAAK,IAAI,GAAG,OAAO;AACpC,MAAI,eAAe,QAAQ,gBAAgB,MAAM,YAAY,aAAa;AACxE,UAAM,IAAI,MAAM,mCAAmC,iBAAiB,cAAc;AAAA,EACpF;AACA,QAAM,OAAO,IAAI,WAAW,CAAC,GAAG,cAAc,QAAQ,OAAO,WAAW;AACxE,QAAM,UAAU,QAAQ,SAAS,CAAC;AAClC,UAAQ,QAAQ,CAAC,OAAOS,WAAU;AAChC,SAAK,QAAQ,OAAO,QAAQA,OAAM;AAAA,EACpC,CAAC;AACD,SAAO;AACT;AACA,SAAS,OAAO,SAAS,QAAQ,cAAc;AAC7C,MAAI,cAAc;AAClB,QAAM,oBAAoB,OAAO,IAAI,CAAC,QAAQ;AAC5C,mBAAe;AACf,WAAO;AAAA,EACT,CAAC;AACD,MAAI,gBAAgB,QAAQ,MAAM,IAAI;AACpC,UAAM,IAAI,MAAM;AAAA;AAAA,UAEV,uCAAuC,QAAQ,OAAO;AAAA,EAC9D;AACA,QAAM,uBAAuB,QAAQ,MAAM,MAAM,CAAC;AAClD,QAAM,qBAAqB,kBAAkB,sBAAsB,YAAY;AAC/E,QAAM,gBAAgB,gBAAgB,IAAI,IAAI,QAAQ,OAAO;AAC7D,QAAM,UAAU,KAAK,MAAM;AACzB,UAAM,WAAW,CAAC;AAClB,cAAU,QAAQ,SAAS,CAAC,GAAG,aAAa,aAAa,CAAC;AAC1D,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,YAAM,iBAAiB,OAAO,IAAI,IAAI,kBAAkB,KAAK;AAC7D,YAAM,UAAU,CAAC,GAAG,gBAAgB,CAAC;AACrC,YAAM,QAAQ,CAAC,GAAG,OAAO,KAAK,aAAa;AAC3C,eAAS,MAAM,QAAQ,MAAM,SAAS,SAAS,KAAK,GAAG,kBAAkB;AAAA,IAC3E;AACA,YAAQ,QAAQ;AAChB,WAAO;AAAA,EACT,CAAC;AACD,QAAM,OAAO,IAAI,WAAW,CAAC,GAAG,cAAc,QAAQ,OAAO,OAAO,MAAM;AAC1E,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,SAAK,QAAQ,IAAI,QAAQ,GAAG;AAAA,EAC9B;AACA,SAAO;AACT;AAGA,IAAI,aAAa,OAAOO,OAAM,WAAW,YAAY;AACnD,UAAQA,MAAK;AAAA,SACN;AAAA,SACA,eAAe;AAClB,YAAM,WAAW,cAAc,cAAcA,OAAM,WAAW,OAAO;AACrE,YAAM,WAAW,cAAc,cAAcA,OAAM,WAAW,OAAO;AACrE,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,YAAY,MAAM,KAAK,KAAK;AAClC,UAAI,UAAU,IAAI;AAChB,eAAO,QAAQ,YAAY,UAAU,qBAAqB,MAAM,QAAQ,gBAAgB,QAAQ,aAAa;AAAA,MAC/G,OAAO;AACL,eAAO,QAAQ,YAAY,UAAU,qBAAqB,MAAM,QAAQ,gBAAgB,QAAQ,aAAa;AAAA,MAC/G;AAAA,IACF;AAAA,SACK;AAAA,SACA,kBAAkB;AACrB,YAAM,WAAW,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC/D,YAAM,WAAW,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC/D,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,aAAa,MAAM,QAAQ,YAAY,UAAU,qBAAqB,MAAM,QAAQ,gBAAgB,QAAQ,aAAa;AAC/H,YAAM,SAAS,KAAK,IAAI,CAAC,YAAY,QAAQ,EAAE;AAC/C,UAAI,YAAY,MAAM,WAAW,GAAG,KAAK;AACzC,iBAAW,QAAQ,CAAC,YAAY;AAC9B,YAAI,CAAC,QAAQ,QAAQ,OAAO,QAAQ,QAAQ,EAAE,MAAM,IAAI;AACtD,kBAAQ,QAAQ;AAAA,QAClB;AAAA,MACF,CAAC;AACD,UAAI,SAAS;AACb,aAAO,UAAU,IAAI;AACnB,cAAM,aAAa;AACnB,iBAAS,MAAM,QAAQ,YAAY,UAAU,qBAAqB,QAAQ,QAAQ,gBAAgB,QAAQ,aAAa;AACvH,cAAM,YAAY,OAAO,IAAI,CAAC,YAAY,QAAQ,EAAE;AACpD,mBAAW,QAAQ,CAAC,YAAY;AAC9B,cAAI,CAAC,QAAQ,QAAQ,OAAO,QAAQ,QAAQ,EAAE,MAAM,MAAM,UAAU,QAAQ,QAAQ,EAAE,MAAM,IAAI;AAC9F,oBAAQ,QAAQ;AAAA,UAClB;AAAA,QACF,CAAC;AACD,cAAM,cAAc,MAAM,QAAQ,YAAY,UAAU,qBAAqB,QAAQ,QAAQ,gBAAgB,QAAQ,aAAa;AAClI,oBAAY,MAAM,YAAY,GAAG,KAAK;AACtC,oBAAY,QAAQ,CAAC,YAAY;AAC/B,cAAI,CAAC,QAAQ,QAAQ,OAAO,QAAQ,QAAQ,EAAE,MAAM,MAAM,UAAU,QAAQ,QAAQ,EAAE,MAAM,IAAI;AAC9F,oBAAQ,QAAQ;AAAA,UAClB;AAAA,QACF,CAAC;AAAA,MACH;AACA,aAAO;AAAA,IACT;AAAA,SACK,YAAY;AACf,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,YAAY,IAAI,CAAC;AAAA,IAC3B;AAAA,SACK,UAAU;AACb,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,UAAI,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AACzD,UAAI,CAAC,KAAK,MAAM;AACd,eAAO,YAAY,IAAI;AAAA,MACzB;AACA,cAAQ,MAAM,KAAK,KAAK,GAAG,KAAK,CAAC,QAAQ,IAAI,IAAI,CAAC,MAAM,MAAM;AAAA,IAChE;AAAA,SACK,SAAS;AACZ,YAAM,YAAYA,MAAK,WAAW,KAAK,CAAC,SAAS,UAAU,MAAM,WAAW,OAAO,MAAM,MAAM;AAC/F,UAAI,WAAW;AACb,cAAM,OAAO,UAAU,WAAW,WAAW,OAAO;AACpD,eAAO,CAAC,YAAY,IAAI,CAAC;AAAA,MAC3B;AACA,aAAO;AAAA,IACT;AAAA,SACK,SAAS;AACZ,YAAM,UAAU,cAAc,aAAaA,OAAM,WAAW,OAAO;AACnE,YAAM,OAAO,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC7D,cAAQ,WAAW,OAAO;AAC1B,aAAO,CAAC,YAAY,IAAI,CAAC;AAAA,IAC3B;AAAA,SACK,QAAQ;AACX,YAAM,OAAO,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC7D,cAAQ,UAAU;AAClB,aAAO,CAAC,YAAY,IAAI,CAAC;AAAA,IAC3B;AAAA,SACK,iBAAiB;AACpB,YAAM,OAAO,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC7D,cAAQ,cAAc;AACtB,aAAO,CAAC,YAAY,IAAI,CAAC;AAAA,IAC3B;AAAA,SACK,iBAAiB;AACpB,YAAMhB,QAAO,cAAc,QAAQgB,OAAM,WAAW,OAAO;AAC3D,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,cAAc,cAAc,eAAeA,OAAM,WAAW,OAAO;AACzE,YAAM,iBAAiB,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC/E,YAAM,yBAAyB,cAAc,0BAA0BA,OAAM,WAAW,OAAO;AAC/F,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,cAAc,IAAI,YAAY,MAAM,OAAOhB,OAAM,cAAc,wBAAwB,aAAa,cAAc;AACxH,cAAQ,eAAe,WAAW;AAClC,aAAO,CAAC,YAAY,UAAU,OAAO,CAAC,CAAC;AAAA,IACzC;AAAA,SACK,sBAAsB;AACzB,YAAM,KAAK,cAAc,iBAAiBgB,OAAM,WAAW,OAAO;AAClE,YAAMP,SAAQ,cAAc,SAASO,OAAM,WAAW,OAAO;AAC7D,YAAM,cAAc,cAAc,UAAUA,OAAM,WAAW,OAAO;AACpE,YAAM,mBAAmB,QAAQ,eAAe,GAAG,EAAE;AACrD,uBAAiB,MAAMP,QAAO,WAAW;AACzC,aAAO,CAAC,iBAAiB,QAAQ;AAAA,IACnC;AAAA,SACK,qBAAqB;AACxB,YAAM,SAAS,cAAc,iBAAiBO,OAAM,WAAW,OAAO;AACtE,YAAM,YAAY,cAAc,SAASA,OAAM,WAAW,OAAO;AACjE,YAAM,kBAAkB,QAAQ,eAAe,OAAO,EAAE;AACxD,aAAO,CAAC,gBAAgB,KAAK,SAAS,CAAC;AAAA,IACzC;AAAA,SACK,uBAAuB;AAC1B,YAAM,WAAW,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AACxE,YAAM,gBAAgB,cAAc,WAAWA,OAAM,WAAW,OAAO;AACvE,YAAM,cAAc,cAAc,SAASA,OAAM,WAAW,OAAO;AACnE,YAAM,oBAAoB,QAAQ,eAAe,SAAS,EAAE;AAC5D,aAAO,CAAC,kBAAkB,OAAO,eAAe,WAAW,CAAC;AAAA,IAC9D;AAAA,SACK,wBAAwB;AAC3B,YAAM,YAAY,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AACzE,YAAM,iBAAiB,cAAc,WAAWA,OAAM,WAAW,OAAO;AACxE,YAAM,gBAAgB,cAAc,UAAUA,OAAM,WAAW,OAAO;AACtE,YAAM,qBAAqB,QAAQ,eAAe,UAAU,EAAE;AAC9D,yBAAmB,QAAQ,gBAAgB,aAAa;AACxD,aAAO,CAAC,mBAAmB,QAAQ;AAAA,IACrC;AAAA,SACK,uBAAuB;AAC1B,YAAM,WAAW,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AACxE,YAAM,oBAAoB,QAAQ,eAAe,SAAS,EAAE;AAC5D,YAAM,cAAc,cAAc,SAASA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,kBAAkB,OAAO,WAAW,CAAC;AAAA,IAC/C;AAAA,SACK,sBAAsB;AACzB,YAAM,UAAU,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AACvE,YAAM,cAAc,cAAc,UAAUA,OAAM,WAAW,OAAO;AACpE,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,mBAAmB,QAAQ,eAAe,QAAQ,EAAE;AAC1D,uBAAiB,MAAM,SAAS,WAAW;AAC3C,aAAO,CAAC,iBAAiB,QAAQ;AAAA,IACnC;AAAA,SACK,qBAAqB;AACxB,YAAM,SAAS,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AACtE,YAAM,kBAAkB,QAAQ,eAAe,OAAO,EAAE;AACxD,aAAO,CAAC,OAAO,gBAAgB,KAAK,GAAG,OAAO,CAAC;AAAA,IACjD;AAAA,SACK,sBAAsB;AACzB,YAAM,UAAU,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AACvE,YAAM,mBAAmB,QAAQ,eAAe,QAAQ,EAAE;AAC1D,uBAAiB,cAAc;AAC/B,aAAO,CAAC,iBAAiB,QAAQ;AAAA,IACnC;AAAA,SACK,qBAAqB;AACxB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAMP,SAAQ,cAAc,SAASO,OAAM,WAAW,OAAO;AAC7D,YAAM,cAAc,cAAc,UAAUA,OAAM,WAAW,OAAO;AACpE,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,iBAAW,QAAQP,QAAO,WAAW;AACrC,aAAO,CAAC,WAAW,QAAQ;AAAA,IAC7B;AAAA,SACK,qBAAqB;AACxB,YAAM,WAAW,cAAc,gBAAgBO,OAAM,WAAW,OAAO;AACvE,YAAM,YAAY,cAAc,SAASA,OAAM,WAAW,OAAO;AACjE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,aAAO,CAAC,WAAW,QAAQ,WAAW,cAAc,YAAY,CAAC;AAAA,IACnE;AAAA,SACK;AAAA,SACA,qBAAqB;AACxB,YAAM,iBAAiB,cAAc,WAAWA,OAAM,WAAW,OAAO;AACxE,YAAM,gBAAgB,cAAc,UAAUA,OAAM,WAAW,OAAO;AACtE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,cAAc,cAAc,eAAeA,OAAM,WAAW,OAAO;AACzE,YAAM,aAAa,QAAQ,eAAe,gBAAgB,cAAc,WAAW;AACnF,cAAQ,cAAc,UAAU;AAChC,aAAO,CAAC,WAAW,QAAQ;AAAA,IAC7B;AAAA,SACK;AAAA,SACA,mBAAmB;AACtB,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,UAAI;AACJ,UAAIA,MAAK,OAAO,qBAAqB;AACnC,2BAAmB;AAAA,MACrB,OAAO;AACL,2BAAmB;AAAA,MACrB;AACA,YAAM,cAAc,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC5E,YAAM,iBAAiBA,MAAK,OAAO,sBAAsB,KAAK;AAC9D,YAAM,aAAa,QAAQ,cAAc,cAAc,aAAa,cAAc;AAClF,cAAQ,cAAc,UAAU;AAChC,aAAO,CAAC,WAAW,QAAQ;AAAA,IAC7B;AAAA,SACK,oBAAoB;AACvB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAM,gBAAgB,cAAc,WAAWA,OAAM,WAAW,OAAO;AACvE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,aAAO,CAAC,WAAW,OAAO,eAAe,cAAc,YAAY,CAAC;AAAA,IACtE;AAAA,SACK,mBAAmB;AACtB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,cAAc,cAAc,eAAeA,OAAM,WAAW,OAAO;AACzE,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,aAAO,CAAC,WAAW,MAAM,cAAc,cAAc,WAAW,CAAC;AAAA,IACnE;AAAA,SACK,wBAAwB;AAC3B,YAAM,UAAU,cAAc,UAAUA,OAAM,WAAW,OAAO;AAChE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,aAAa,WAAW,SAAS,cAAc,YAAY;AACjE,cAAQ,cAAc,UAAU;AAChC,aAAO,CAAC,WAAW,QAAQ;AAAA,IAC7B;AAAA,SACK;AAAA,SACA,sBAAsB;AACzB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,YAAM,cAAc,cAAc,SAASA,OAAM,WAAW,OAAO;AACnE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,aAAO,CAAC,WAAW,OAAO,aAAa,YAAY,CAAC;AAAA,IACtD;AAAA,SACK,sBAAsB;AACzB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAM,cAAc,cAAc,UAAUA,OAAM,WAAW,OAAO;AACpE,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,iBAAW,SAAS,WAAW;AAC/B,aAAO,CAAC,WAAW,QAAQ;AAAA,IAC7B;AAAA,SACK,qBAAqB;AACxB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,aAAO,CAAC,WAAW,QAAQ,cAAc,YAAY,CAAC;AAAA,IACxD;AAAA,SACK,mBAAmB;AACtB,YAAM,cAAc,cAAc,UAAUA,OAAM,WAAW,OAAO;AACpE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,aAAa,OAAO,aAAa,SAAS,YAAY;AAC5D,cAAQ,cAAc,UAAU;AAChC,aAAO,CAAC,WAAW,QAAQ;AAAA,IAC7B;AAAA,SACK,oBAAoB;AACvB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAM,aAAa,QAAQ,cAAc,SAAS,EAAE;AACpD,aAAO,CAAC,OAAO,WAAW,KAAK,GAAG,OAAO,CAAC;AAAA,IAC5C;AAAA,SACK,oBAAoB;AACvB,YAAM,WAAW,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AACvE,YAAMhB,QAAO,cAAc,QAAQgB,OAAM,WAAW,OAAO;AAC3D,YAAM,gBAAgB,QAAQ,cAAc,SAAS,EAAE;AACvD,YAAM,iBAAiB,cAAc,OAAOhB,KAAI;AAChD,cAAQ,cAAc,cAAc;AACpC,aAAO,CAAC,eAAe,QAAQ;AAAA,IACjC;AAAA;AAEE,YAAM,UAAU,aAAagB,MAAK,uBAAuB;AAAA;AAE/D;AAGA,SAAS,4BAA4BA,OAAM,WAAW,SAAS;AAC7D,QAAM,CAAC,SAAS,cAAc,IAAI,cAAc,YAAYA,OAAM,WAAW,OAAO;AACpF,QAAM,YAAY,YAAY;AAC9B,QAAM,YAAY,CAAC;AACnB,QAAM,UAAU,mBAAmB;AACnC,QAAM,cAAc,YAAY;AAChC,QAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,MAAI,WAAW;AACb,QAAI,WAAW,YAAY,GAAG;AAC5B,YAAM,IAAI,MAAM,uGAAuG;AAAA,IACzH;AACA,QAAI,CAAC,WAAW,aAAa,YAAY,GAAG;AAC1C,YAAM,IAAI,MAAM,kFAAkF;AAAA,IACpG;AAAA,EACF;AACA,MAAI,aAAa;AACf,UAAM,IAAI,MAAM,sEAAsE;AAAA,EACxF;AACA,QAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,QAAM,OAAO,WAAWA,OAAM,WAAW,OAAO;AAChD,QAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO,EAAE,YAAY;AACrF,QAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,MAAI,CAAC,SAAS,QAAQ,IAAI,cAAc,QAAQA,OAAM,WAAW,OAAO;AACxE,MAAI,WAAW;AACb,eAAW;AACX,cAAU;AAAA,EACZ;AACA,QAAM,iBAAiB,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC/E,SAAO;AAAA,IACL;AAAA,IACA,KAAK;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AACA,IAAI,aAAa,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC9E,UAAQA,MAAK;AAAA,SACN,UAAU;AACb,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO,EAAE,YAAY;AACrF,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,QAAQ,MAAM,YAAY,QAAQ,CAAC;AAAA,IACzJ;AAAA,SACK,UAAU;AACb,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,WAAWA,OAAM,WAAW,OAAO;AAChD,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO,EAAE,YAAY;AACrF,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,MAAM,YAAY,CAAC,UAAU,IAAI,UAAU,EAAE,CAAC,CAAC;AAAA,IAC7L;AAAA,SACK,gBAAgB;AACnB,YAAM,EAAE,QAAQ,KAAK,MAAM,YAAY,WAAW,SAAS,UAAU,gBAAgB,eAAe,IAAI,4BAA4BA,OAAM,WAAW,OAAO;AAC5J,aAAO,CAAC,IAAI,MAAM,OAAO;AAAA,QACvB,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO;AAAA,QAC9C,QAAQ,cAAc,UAAUA,OAAM,WAAW,OAAO;AAAA,QACxD,SAAS,CAAC,OAAO,IAAI,OAAO,EAAE;AAAA,QAC9B,KAAK;AAAA,QACL;AAAA,QACA,WAAW,CAAC,UAAU,IAAI,UAAU,EAAE;AAAA,QACtC,MAAM;AAAA,QACN,YAAY;AAAA,QACZ,wBAAwB;AAAA,QACxB;AAAA,MACF,CAAC,CAAC;AAAA,IACJ;AAAA,SACK,8BAA8B;AACjC,YAAM,EAAE,QAAQ,KAAK,MAAM,YAAY,WAAW,SAAS,UAAU,gBAAgB,eAAe,IAAI,4BAA4BA,OAAM,WAAW,OAAO;AAC5J,aAAO,CAAC,IAAI,MAAM,gBAAgB;AAAA,QAChC,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO;AAAA,QAC9C,QAAQ,cAAc,UAAUA,OAAM,WAAW,OAAO;AAAA,QACxD,SAAS,CAAC,OAAO,IAAI,OAAO,EAAE;AAAA,QAC9B,KAAK;AAAA,QACL;AAAA,QACA,WAAW,CAAC,UAAU,IAAI,UAAU,EAAE;AAAA,QACtC,MAAM;AAAA,QACN,YAAY;AAAA,QACZ,wBAAwB;AAAA,QACxB;AAAA,MACF,CAAC,CAAC;AAAA,IACJ;AAAA,SACK;AAAA,SACA,mBAAmB;AACtB,YAAM,QAAQ,cAAc,eAAeA,OAAM,WAAW,OAAO;AACnE,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,WAAWA,OAAM,WAAW,OAAO;AAChD,aAAO,CAAC,IAAI,gBAAgB,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,OAAO,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,IAAI,CAAC;AAAA,IACnK;AAAA,SACK;AAAA,SACA,mBAAmB;AACtB,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,WAAWA,OAAM,WAAW,OAAO;AAChD,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO,EAAE,YAAY;AACrF,aAAO,CAAC,IAAI,gBAAgB,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,MAAM,YAAY,CAAC,UAAU,IAAI,UAAU,EAAE,CAAC,CAAC;AAAA,IAC1M;AAAA,SACK,UAAU;AACb,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO,EAAE,YAAY;AACrF,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,CAAC,OAAO,IAAI,OAAO,IAAI,OAAO,EAAE,GAAG,MAAM,YAAY,CAAC,UAAU,IAAI,UAAU,IAAI,UAAU,EAAE,CAAC,CAAC;AAAA,IACtN;AAAA,SACK,WAAW;AACd,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,CAAC,WAAW,IAAI,WAAW,EAAE,GAAG,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,IAAI,CAAC;AAAA,IACjI;AAAA,SACK,WAAW;AACd,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,CAAC,WAAW,IAAI,WAAW,EAAE,GAAG,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,IAAI,CAAC;AAAA,IACjI;AAAA,SACK,qBAAqB;AACxB,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,YAAM,sBAAsB,cAAc,uBAAuBA,OAAM,WAAW,OAAO;AACzF,YAAM,EAAE,QAAQ,QAAQ,IAAI,IAAI,kBAAkB,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,CAAC,WAAW,IAAI,WAAW,EAAE,GAAG,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,MAAM,mBAAmB;AACjL,aAAO,CAAC,QAAQ,OAAO;AAAA,IACzB;AAAA,SACK,aAAa;AAChB,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,CAAC,WAAW,IAAI,WAAW,IAAI,WAAW,EAAE,GAAG,CAAC,OAAO,IAAI,OAAO,IAAI,OAAO,EAAE,GAAG,IAAI,CAAC;AAAA,IAC7J;AAAA,SACK,aAAa;AAChB,YAAM,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAChE,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,CAAC,WAAW,IAAI,WAAW,IAAI,WAAW,EAAE,GAAG,CAAC,OAAO,IAAI,OAAO,IAAI,OAAO,EAAE,GAAG,IAAI,CAAC;AAAA,IAC7J;AAAA,SACK,cAAc;AACjB,YAAMJ,WAAU,cAAc,WAAWI,OAAM,WAAW,OAAO;AACjE,YAAM,OAAO,cAAc,OAAOA,OAAM,WAAW,OAAO;AAC1D,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,eAAeJ,SAAQ;AAC7B,YAAM,cAAcA,SAAQ;AAC5B,YAAM,iBAAiB,UAAU;AACjC,YAAM,gBAAgB,UAAU;AAChC,aAAO,CAAC,IAAI,WAAW,cAAc,KAAKI,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,CAAC,cAAc,WAAW,GAAG,MAAM,CAAC,gBAAgB,aAAa,GAAG,MAAM,CAAC;AAAA,IACrM;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,aAAa,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC9E,UAAQA,MAAK;AAAA,SACN,QAAQ;AACX,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,aAAO,CAAC,IAAI,KAAK,OAAO,OAAO,KAAK,CAAC;AAAA,IACvC;AAAA,SACK,YAAY;AACf,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,MAAM,cAAc,OAAOA,OAAM,WAAW,OAAO;AACzD,aAAO,CAAC,IAAI,SAAS,OAAO,MAAM,GAAG,CAAC;AAAA,IACxC;AAAA,SACK,eAAe;AAClB,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,YAAY,QAAQ,YAAY,IAAI,CAAC;AAAA,IACnD;AAAA,SACK,UAAU;AACb,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,OAAO,SAAS,OAAO,SAAS,QAAQ,CAAC;AAAA,IACvD;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACtH;AAAA,SACK,YAAY;AACf,aAAO,CAAC,IAAI,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACpE;AAAA,SACK,wBAAwB;AAC3B,aAAO,CAAC,IAAI,qBAAqB,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACvL;AAAA,SACK,iBAAiB;AACpB,aAAO,CAAC,IAAI;AAAA,QACV,cAAc,SAASA,OAAM,WAAW,OAAO;AAAA,QAC/C,cAAc,UAAUA,OAAM,WAAW,OAAO;AAAA,QAChD,cAAc,UAAUA,OAAM,WAAW,OAAO;AAAA,QAChD,cAAc,SAASA,OAAM,WAAW,OAAO;AAAA,MACjD,CAAC;AAAA,IACH;AAAA,SACK,SAAS;AACZ,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,QAAQ,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC5D,aAAO,CAAC,IAAI,MAAM,OAAO,MAAM,OAAO,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACzF;AAAA,SACK,mBAAmB;AACtB,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,QAAQ,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC5D,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,gBAAgB,OAAO,OAAO,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,IAAI,CAAC;AAAA,IAC3G;AAAA,SACK,SAAS;AACZ,aAAO,CAAC,IAAI,MAAM,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACvH;AAAA,SACK,aAAa;AAChB,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACrE;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,SAAS,UAAUA,OAAM,WAAW,SAAS;AAC3C,QAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,QAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,QAAM,gBAAgB,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AAC7E,QAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,QAAM,iBAAiB,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC/E,QAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,SAAO;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AACA,IAAI,aAAa,OAAOA,OAAM,WAAW,SAAS,iBAAiB,MAAM,8BAA8B;AACrG,UAAQA,MAAK;AAAA,SACN,uBAAuB;AAC1B,YAAM,EAAE,OAAO,QAAQ,eAAe,cAAc,gBAAgB,aAAa,IAAI,UAAUA,OAAM,WAAW,OAAO;AACvH,YAAM,SAAS,MAAM,IAAI,MAAM,gCAAgC,OAAO,QAAQ,eAAe,cAAc,gBAAgB,YAAY;AACvI,aAAO,CAAC,OAAO,iBAAiB,OAAO,cAAc;AAAA,IACvD;AAAA,SACK,uBAAuB;AAC1B,YAAM,EAAE,OAAO,QAAQ,eAAe,cAAc,eAAe,IAAI,UAAUA,OAAM,WAAW,OAAO;AACzG,YAAM,qBAAqB,cAAc,sBAAsBA,OAAM,WAAW,OAAO;AACvF,YAAM,SAAS,MAAM,IAAI,MAAM,6BAA6B,OAAO,QAAQ,eAAe,cAAc,gBAAgB,kBAAkB;AAC1I,aAAO,CAAC,OAAO,iBAAiB,OAAO,YAAY;AAAA,IACrD;AAAA,SACK;AAAA,SACA,uBAAuB;AAC1B,YAAM,EAAE,OAAO,QAAQ,eAAe,cAAc,eAAe,IAAI,UAAUA,OAAM,WAAW,OAAO;AACzG,aAAO,CAAC,MAAM,IAAI,MAAM,uBAAuB,OAAO,QAAQ,eAAe,cAAc,cAAc,CAAC;AAAA,IAC5G;AAAA,SACK,SAAS;AACZ,YAAM,YAAY,IAAI,KAAK,cAAc,aAAaA,OAAM,WAAW,OAAO,GAAG,MAAM;AACvF,YAAM,SAAS,CAAC,MAAM,IAAI,WAAW,SAAS,CAAC;AAC/C,gBAAU,QAAQ;AAClB,aAAO;AAAA,IACT;AAAA,SACK,YAAY;AACf,aAAO,IAAI,eAAe,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC;AAAA,IACtH;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,aAAa,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC9E,UAAQA,MAAK;AAAA,SACN,cAAc;AACjB,YAAM,iBAAiB,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC/E,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,aAAO,CAAC,IAAI,WAAW,gBAAgB,MAAM,CAAC;AAAA,IAChD;AAAA,SACK,UAAU;AACb,YAAM,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO;AACrD,YAAM,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO;AACrD,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,SAAS,IAAI,KAAK,GAAG,GAAG,MAAM;AACpC,aAAO,CAAC,OAAO,QAAQ,OAAO,OAAO;AAAA,IACvC;AAAA,SACK,cAAc;AACjB,YAAM,iBAAiB,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC/E,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,aAAO,CAAC,IAAI,WAAW,gBAAgB,MAAM,CAAC;AAAA,IAChD;AAAA,SACK,UAAU;AACb,YAAM,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO;AACrD,YAAM,SAAS,IAAI,OAAO,CAAC;AAC3B,aAAO,CAAC,OAAO,QAAQ,OAAO,OAAO;AAAA,IACvC;AAAA,SACK,YAAY;AACf,YAAM,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO;AACrD,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,SAAS,IAAI,OAAO,GAAG,IAAI;AACjC,aAAO,CAAC,OAAO,QAAQ,OAAO,OAAO;AAAA,IACvC;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,aAAa,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC9E,UAAQA,MAAK;AAAA,SACN,SAAS;AACZ,aAAO,UAAUA,MAAK;AAAA,IACxB;AAAA,SACK;AACH,YAAM,MAAM,cAAc,WAAWA,OAAM,WAAW,OAAO;AAC7D,aAAO,CAAC,UAAUA,MAAK,MAAM,WAAW,OAAO,KAAK,GAAG;AAAA,SACpD;AACH,aAAO,CAAC,UAAUA,MAAK,MAAM,WAAW,OAAO,CAAC;AAAA,SAC7C;AAAA,SACA;AAAA,SACA,2BAA2B;AAC9B,YAAM,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO;AACzD,aAAO,CAAC,YAAY,KAAK,CAAC;AAAA,IAC5B;AAAA,SACK;AACH,aAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,EAAE,IAAI,CAAC,OAAO,YAAY,EAAE,CAAC;AAAA,SAC5E;AACH,YAAM,WAAW,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC5D,aAAO,CAAC,YAAY,QAAQ,CAAC;AAAA,SAC1B;AACH,aAAO,CAAC,IAAI,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO,EAAE,OAAO,OAAO,CAAC;AAAA,SAC9E;AACH,aAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,EAAE,IAAI,CAAC,OAAO,IAAI,SAAS,GAAG,KAAK,CAAC;AAAA,SACnF;AACH,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,EAAE,MAAM,OAAO,CAAC;AAAA,SAC3E;AACH,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,EAAE,MAAM,OAAO,CAAC;AAAA,SAC3E;AACH,aAAO,CAAC,IAAI,OAAO,CAAC,CAAC;AAAA,SAClB;AACH,YAAM,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC1D,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,cAAQ,KAAK,gGAAgG;AAC7G,cAAQ,IAAI,OAAO;AACnB,eAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,gBAAQ,IAAI,MAAM,UAAU,MAAM,KAAK,KAAK,IAAI,SAAS,CAAC,EAAE,MAAM,GAAG,SAAS,CAAC;AAAA,MACjF;AACA,aAAO,CAAC,MAAM;AAAA;AAEd,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,YAAY,MAAM;AAAA,EACpB,YAAY,UAAU,YAAY;AAChC,SAAK,WAAW;AAChB,SAAK,aAAa;AAClB,SAAK,SAAS,OAAO,CAAC;AACtB,SAAK,YAA4B,oBAAI,IAAI;AACzC,SAAK,KAAK,MAAM;AAAA,EAClB;AAAA,EACA,IAAI,KAAK;AACP,WAAO,KAAK,OAAO;AAAA,EACrB;AAAA,EACA,gBAAgB;AACd,SAAK,UAAU,QAAQ,CAAC,UAAU,MAAM,QAAQ,CAAC;AACjD,SAAK,UAAU,MAAM;AACrB,SAAK,OAAO,QAAQ;AAAA,EACtB;AAAA,EACA,OAAO;AACL,WAAO,KAAK,UAAU;AAAA,EACxB;AAAA,EACA,aAAa;AACX,WAAO,OAAO,KAAK,KAAK,GAAG,OAAO;AAAA,EACpC;AAAA,EACA,MAAM,OAAO,MAAM,QAAQ;AACzB,SAAK,uBAAuB,MAAM,MAAM;AACxC,UAAM,QAAQ,MAAM,KAAK,KAAK;AAC9B,SAAK,UAAU,QAAQ,CAAC,UAAU,MAAM,QAAQ,CAAC;AACjD,SAAK,UAAU,MAAM;AACrB,WAAO,KAAK,MAAM;AAChB,YAAM,UAAU,QAAQ,MAAM;AAC9B,YAAM,aAAa,MAAM;AACzB,YAAM,eAAe,QAAQ;AAC7B,mBAAa,OAAO,eAAe,cAAc,MAAM,kDAAkD,uCAAuC,wBAAwB;AACxK,eAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,cAAM,MAAM,MAAM;AAClB,cAAM,QAAQ,QAAQ;AACtB,aAAK,KAAK;AACV,aAAK,UAAU,IAAI,KAAK,KAAK;AAAA,MAC/B;AACA,aAAO,KAAK;AAAA,IACd,CAAC;AAAA,EACH;AAAA,EACA,MAAM,KAAK,MAAM,cAAc;AAC7B,SAAK,uBAAuB,MAAM,YAAY;AAC9C,UAAM,QAAQ,MAAM,KAAK,KAAK;AAC9B,WAAO,KAAK,MAAM;AAChB,YAAM,SAAS,CAAC;AAChB,eAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,cAAM,MAAM,MAAM;AAClB,cAAM,QAAQ,KAAK,gBAAgB,KAAK,YAAY;AACpD,eAAO,KAAK,KAAK;AAAA,MACnB;AACA,aAAO,MAAM,MAAM;AAAA,IACrB,CAAC;AAAA,EACH;AAAA,EACA,gBAAgB,KAAK,cAAc;AACjC,UAAM,SAAS,KAAK,UAAU,IAAI,GAAG;AACrC,WAAO,UAAU,OAAO,SAAS;AAAA,EACnC;AAAA,EACA,uBAAuB,KAAK,OAAO;AACjC,QAAI,IAAI,UAAU,KAAK,UAAU;AAC/B,YAAM,IAAI,MAAM,oBAAoB,KAAK,qBAAqB,IAAI,OAAO;AAAA,IAC3E;AACA,QAAI,MAAM,UAAU,KAAK,YAAY;AACnC,YAAM,IAAI,MAAM,sBAAsB,KAAK,uBAAuB,MAAM,OAAO;AAAA,IACjF;AAAA,EACF;AACF;AAGA,IAAI,aAAa,OAAOA,OAAM,WAAW,SAAS,oBAAoB;AACpE,UAAQA,MAAK;AAAA,SACN;AAAA,SACA,eAAe;AAClB,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,YAAM,YAAY,IAAI,UAAU,UAAU,UAAU;AACpD,sBAAgB,aAAaA,MAAK,MAAM,SAAS;AACjD,aAAO,CAAC,UAAU,MAAM;AAAA,IAC1B;AAAA,SACK;AAAA,SACA,uBAAuB;AAC1B,YAAM,SAAS,cAAc,eAAeA,OAAM,WAAW,SAAS,eAAe;AACrF,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,YAAY,gBAAgB,iBAAiB,OAAO,EAAE;AAC5D,aAAO,CAAC,MAAM,UAAU,OAAO,MAAM,MAAM,CAAC;AAAA,IAC9C;AAAA,SACK;AAAA,SACA,qBAAqB;AACxB,YAAM,SAAS,cAAc,eAAeA,OAAM,WAAW,SAAS,eAAe;AACrF,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,YAAY,gBAAgB,iBAAiB,OAAO,EAAE;AAC5D,aAAO,CAAC,MAAM,UAAU,KAAK,MAAM,YAAY,CAAC;AAAA,IAClD;AAAA,SACK;AAAA,SACA,qBAAqB;AACxB,YAAM,SAAS,cAAc,eAAeA,OAAM,WAAW,SAAS,eAAe;AACrF,YAAM,YAAY,gBAAgB,iBAAiB,OAAO,EAAE;AAC5D,aAAO,CAAC,UAAU,WAAW,CAAC;AAAA,IAChC;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN,kBAAkB;AACrB,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAMhB,QAAO,cAAc,QAAQgB,OAAM,WAAW,OAAO;AAC3D,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,mBAAmB,cAAc,oBAAoBA,OAAM,WAAW,OAAO;AACnF,aAAO,CAAC,IAAI,MAAM,eAAe,QAAQ,CAAChB,MAAK,IAAIA,MAAK,EAAE,GAAG,cAAc,gBAAgB,CAAC;AAAA,IAC9F;AAAA,SACK,yBAAyB;AAC5B,YAAM,SAAS,cAAc,UAAUgB,OAAM,WAAW,OAAO;AAC/D,YAAMhB,QAAO,cAAc,QAAQgB,OAAM,WAAW,OAAO;AAC3D,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,mBAAmB,cAAc,oBAAoBA,OAAM,WAAW,OAAO;AACnF,aAAO,CAAC,IAAI,MAAM,sBAAsB,QAAQ,CAAChB,MAAK,IAAIA,MAAK,EAAE,GAAG,cAAc,gBAAgB,CAAC;AAAA,IACrG;AAAA,SACK,iBAAiB;AACpB,YAAM,SAAS,cAAc,SAASgB,OAAM,WAAW,OAAO;AAC9D,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,qBAAqB,cAAc,sBAAsBA,OAAM,WAAW,OAAO;AACvF,aAAO,CAAC,IAAI,MAAM,cAAc,QAAQ,OAAO,QAAQ,UAAU,QAAQ,kBAAkB,CAAC;AAAA,IAC9F;AAAA,SACK,8BAA8B;AACjC,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,YAAM,cAAc,cAAc,eAAeA,OAAM,WAAW,OAAO;AACzE,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,gBAAgB,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AAC7E,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,MAAM,UAAU,QAAQ,YAAY,cAAc,YAAY,GAAG,SAAS,YAAY,GAAG,WAAW,WAAW,CAAC;AAAA,IAC9H;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN,SAAS;AACZ,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC/G;AAAA,SACK,YAAY;AACf,aAAO,CAAC,IAAI,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAClH;AAAA,SACK,WAAW;AACd,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACjH;AAAA,SACK,gBAAgB;AACnB,aAAO,CAAC,IAAI,aAAa,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACtH;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC9G;AAAA,SACK,aAAa;AAChB,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACnH;AAAA,SACK,cAAc;AACjB,aAAO,CAAC,IAAI,WAAW,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACpH;AAAA,SACK,cAAc;AACjB,aAAO,CAAC,IAAI,WAAW,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACtE;AAAA,SACK,aAAa;AAChB,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACnH;AAAA,SACK;AAAA,SACA,YAAY;AACf,aAAO,CAAC,IAAI,MAAM,cAAc,aAAaA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACrK;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN;AAAA,SACA;AAAA,SACA;AACH,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SACzN;AACH,aAAO,CAAC,IAAI,OAAO,cAAc,YAAYA,OAAM,WAAW,OAAO,GAAG,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC3H;AACH,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SACjH;AACH,YAAM,CAAC,SAAS,cAAc,IAAI,cAAc,YAAYA,OAAM,WAAW,OAAO;AACpF,YAAM,YAAY,YAAY;AAC9B,YAAM,UAAU,mBAAmB;AACnC,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,iBAAiB,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC/E,UAAI,WAAW;AACb,YAAI,WAAW,YAAY,GAAG;AAC5B,gBAAM,IAAI,MAAM,oFAAoF;AAAA,QACtG;AACA,YAAI,CAAC,WAAW,YAAY,GAAG;AAC7B,gBAAM,IAAI,MAAM,+DAA+D;AAAA,QACjF;AAAA,MACF;AACA,YAAM,CAAC,SAAS,QAAQ,IAAI,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC1E,aAAO,CAAC,IAAI,MAAM,OAAO;AAAA,QACvB,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO;AAAA,QAC9C,GAAG,cAAc,KAAKA,OAAM,WAAW,OAAO;AAAA,QAC9C,YAAY,cAAc,cAAcA,OAAM,WAAW,OAAO;AAAA,QAChE,YAAY,cAAc,cAAcA,OAAM,WAAW,OAAO;AAAA,QAChE,MAAM;AAAA,QACN,YAAY;AAAA,QACZ,wBAAwB;AAAA,QACxB;AAAA,MACF,CAAC,CAAC;AAAA;AAEF,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN;AACH,aAAO,CAAC,IAAI,cAAc,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,YAAYA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,SAC1K;AAAA,SACA,oBAAoB;AACvB,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,YAAYA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACpU;AAAA,SACK,oBAAoB;AACvB,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,YAAYA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACpU;AAAA,SACK,OAAO;AACV,aAAO,CAAC,IAAI,2BAA2B,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC7R;AAAA,SACK,WAAW;AACd,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACnE;AAAA,SACK,cAAc;AACjB,aAAO,CAAC,IAAI,WAAW,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACtE;AAAA,SACK,iBAAiB;AACpB,aAAO,CAAC,IAAI,cAAc,cAAc,iBAAiBA,OAAM,WAAW,OAAO,GAAG,cAAc,eAAeA,OAAM,WAAW,OAAO,GAAG,cAAc,gBAAgBA,OAAM,WAAW,OAAO,GAAG,cAAc,gBAAgBA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC/P;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN,OAAO;AACV,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,QAAQ,CAAC;AAAA,IAC/E;AAAA,SACK,QAAQ;AACX,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,QAAQ,CAAC;AAAA,IAChF;AAAA,SACK,OAAO;AACV,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,QAAQ,CAAC;AAAA,IAC/E;AAAA,SACK,OAAO;AACV,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,QAAQ,CAAC;AAAA,IAC/E;AAAA,SACK,OAAO;AACV,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,QAAQ,CAAC;AAAA,IAC/E;AAAA,SACK,OAAO;AACV,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,QAAQ,CAAC;AAAA,IAC/E;AAAA,SACK,UAAU;AACb,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,IAAI,CAAC;AAAA,IACxE;AAAA,SACK,UAAU;AACb,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,IAAI,CAAC;AAAA,IACxE;AAAA,SACK,QAAQ;AACX,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,QAAQ,CAAC;AAAA,IAChF;AAAA,SACK,WAAW;AACd,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,WAAW,cAAc,WAAWA,OAAM,WAAW,OAAO;AAClE,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,WAAW,QAAQ,CAAC;AAAA,IAC9F;AAAA,SACK,UAAU;AACb,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,WAAW,cAAc,WAAWA,OAAM,WAAW,OAAO;AAClE,aAAO,CAAC,IAAI,OAAO,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,MAAM,WAAW,QAAQ,CAAC;AAAA,IAC7F;AAAA,SACK;AACH,YAAM,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO;AACrD,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAMhB,QAAO,cAAc,QAAQgB,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,SAAS,GAAG,SAAShB,KAAI,CAAC;AAAA,SACnC,iBAAiB;AACpB,YAAM,KAAK,cAAc,KAAKgB,OAAM,WAAW,OAAO;AACtD,YAAM,WAAW,cAAc,WAAWA,OAAM,WAAW,OAAO;AAClE,YAAME,SAAQ,cAAc,QAAQF,OAAM,WAAW,OAAO;AAC5D,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,aAAO,CAAC,IAAI,cAAc,IAAI,UAAUE,QAAO,YAAY,CAAC;AAAA,IAC9D;AAAA;AAEE,YAAM,UAAU,aAAaF,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN;AAAA,SACA,UAAU;AACb,YAAM,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO;AACtD,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,UAAI,SAAS,cAAc,WAAWA,OAAM,WAAW,OAAO;AAC9D,eAAS,OAAO,MAAM,GAAG,EAAE;AAC3B,aAAO,CAAC,IAAI,OAAO,QAAQ,IAAI,CAAC;AAAA,IAClC;AAAA,SACK,UAAU;AACb,YAAM,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC1D,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,aAAO,CAAC,IAAI,OAAO,QAAQ,IAAI,KAAK,SAAS,OAAO,GAAG,CAAC,CAAC;AAAA,IAC3D;AAAA,SACK,YAAY;AACf,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC1D,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,aAAO,CAAC,IAAI,OAAO,QAAQ,IAAI,KAAK,SAAS,OAAO,GAAG,MAAM,SAAS,CAAC;AAAA,IACzE;AAAA,SACK,WAAW;AACd,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,OAAO,CAAC;AACd,eAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,YAAI,KAAK,KAAK;AACZ,eAAK,KAAK,EAAE;AAAA,QACd;AAAA,MACF;AACA,YAAM,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC1D,aAAO,CAAC,IAAI,QAAQ,QAAQ,IAAI,CAAC;AAAA,IACnC;AAAA,SACK,aAAa;AAChB,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,SAAS,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC1D,aAAO,CAAC,IAAI,QAAQ,QAAQ,IAAI,CAAC;AAAA,IACnC;AAAA,SACK,SAAS;AACZ,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,YAAMhB,QAAO,cAAc,QAAQgB,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,OAAOhB,KAAI,CAAC;AAAA,IAC9E;AAAA,SACK,gBAAgB;AACnB,YAAM,QAAQ,cAAc,SAASgB,OAAM,WAAW,OAAO;AAC7D,YAAM,MAAM,cAAc,OAAOA,OAAM,WAAW,OAAO;AACzD,YAAMJ,WAAU,cAAc,WAAWI,OAAM,WAAW,OAAO;AACjE,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,cAAc,cAAc,eAAeA,OAAM,WAAW,OAAO;AACzE,YAAM,iBAAiB,cAAc,kBAAkBA,OAAM,WAAW,OAAO;AAC/E,YAAM,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,aAAa,SAAS,OAAO,KAAKJ,UAAS,WAAW,SAAS,cAAc,aAAa,cAAc,CAAC;AAAA,IACvH;AAAA,SACK,QAAQ;AACX,aAAO,KAAK,MAAM;AAChB,cAAM,OAAO,cAAc,QAAQI,OAAM,WAAW,OAAO;AAC3D,cAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,cAAM,QAAQ,QAAQ,GAAG;AACzB,cAAM,gBAAgB,IAAI,QAAQ,QAAQ,EAAE,EAAE;AAC9C,cAAM,SAAS,QAAQ,IAAI,CAAC,YAAY;AACtC,gBAAM,YAAY,aAAa,YAAY,QAAQ,OAAO,KAAK;AAC/D,cAAI,CAAC,aAAa,CAAC,aAAa,YAAY,IAAI,QAAQ,OAAO,EAAE,OAAO,aAAa,GAAG;AACtF,kBAAM,IAAI,MAAM,wCAAwC;AAAA,UAC1D;AACA,iBAAO,YAAY,UAAU,IAAI,QAAQ,SAAS,KAAK;AAAA,QACzD,CAAC;AACD,eAAO,CAAC,IAAI,MAAM,QAAQ,IAAI,CAAC;AAAA,MACjC,CAAC;AAAA,IACH;AAAA,SACK,UAAU;AACb,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,UAAU,cAAc,UAAUA,OAAM,WAAW,OAAO;AAChE,aAAO,IAAI,QAAQ,SAAS,IAAI;AAAA,IAClC;AAAA,SACK,QAAQ;AACX,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,IAAI,CAAC;AAAA,IACtE;AAAA,SACK;AAAA,SACA,UAAU;AACb,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,YAAM,kBAAkB,cAAc,mBAAmBA,OAAM,WAAW,OAAO;AACjF,YAAM,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO;AAC3D,aAAO,IAAI,MAAM,SAAS,iBAAiB,IAAI;AAAA,IACjD;AAAA,SACK,aAAa;AAChB,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,YAAM,SAAS,cAAc,UAAUA,OAAM,WAAW,OAAO;AAC/D,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,aAAO,CAAC,IAAI,UAAU,SAAS,QAAQ,KAAK,CAAC;AAAA,IAC/C;AAAA,SACK,YAAY;AACf,YAAM,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO;AACrD,YAAM,UAAU,cAAc,WAAWA,OAAM,WAAW,OAAO;AACjE,aAAO,CAAC,IAAI,SAAS,GAAG,OAAO,CAAC;AAAA,IAClC;AAAA,SACK,iBAAiB;AACpB,YAAM,UAAU,cAAc,iBAAiBA,OAAM,WAAW,OAAO;AACvE,YAAM,QAAQ,cAAc,eAAeA,OAAM,WAAW,OAAO;AACnE,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,YAAM,eAAe,cAAc,gBAAgBA,OAAM,WAAW,OAAO;AAC3E,aAAO,CAAC,IAAI,cAAc,SAAS,cAAc,OAAO,aAAa,UAAU,aAAa,QAAQ,eAAe,IAAI,KAAK,cAAc,aAAa,KAAK,CAAC,CAAC;AAAA,IAChK;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN,uBAAuB;AAC1B,YAAM,EAAE,eAAe,cAAc,mBAAmB,gBAAgB,IAAI,IAAI,OAAO,oBAAoB,cAAc,WAAWA,OAAM,WAAW,OAAO,GAAG,cAAc,UAAUA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,GAAG,cAAc,gBAAgBA,OAAM,WAAW,OAAO,CAAC;AAChU,aAAO;AAAA,QACL;AAAA,QACA;AAAA,QACA;AAAA,QACA;AAAA,MACF;AAAA,IACF;AAAA,SACK,iBAAiB;AACpB,YAAM,EAAE,eAAe,YAAY,IAAI,IAAI,OAAO,cAAc,cAAc,gBAAgBA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,GAAG,cAAc,YAAYA,OAAM,WAAW,OAAO,CAAC;AACnO,aAAO,CAAC,eAAe,WAAW;AAAA,IACpC;AAAA,SACK,qBAAqB;AACxB,YAAM,aAAa,IAAI,OAAO,kBAAkB,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,CAAC;AAC1M,aAAO,CAAC,UAAU;AAAA,IACpB;AAAA,SACK,oBAAoB;AACvB,YAAM,aAAa,IAAI,OAAO,iBAAiB,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,CAAC;AACzM,aAAO,CAAC,UAAU;AAAA,IACpB;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN,OAAO;AACV,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC/D;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAChE;AAAA,SACK,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAChE;AAAA,SACK,SAAS;AACZ,aAAO,CAAC,IAAI,MAAM,cAAc,KAAKA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACjE;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN,gBAAgB;AACnB,YAAM,EAAE,QAAQ,aAAa,IAAI,IAAI,OAAO,aAAa,cAAc,QAAQA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,GAAG,cAAc,aAAaA,OAAM,WAAW,OAAO,GAAG,cAAc,eAAeA,OAAM,WAAW,OAAO,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,GAAG,cAAc,YAAYA,OAAM,WAAW,OAAO,GAAG,cAAc,YAAYA,OAAM,WAAW,OAAO,GAAG,cAAc,0BAA0BA,OAAM,WAAW,OAAO,CAAC;AAC9e,aAAO,CAAC,QAAQ,YAAY;AAAA,IAC9B;AAAA,SACK,eAAe;AAClB,YAAM,EAAE,SAAS,QAAQ,MAAM,IAAI,IAAI,OAAO,YAAY,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,aAAaA,OAAM,WAAW,OAAO,GAAG,cAAc,aAAaA,OAAM,WAAW,OAAO,CAAC;AACtN,aAAO,CAAC,SAAS,QAAQ,KAAK;AAAA,IAChC;AAAA,SACK,0BAA0B;AAC7B,YAAM,SAAS,IAAI,OAAO,uBAAuB,cAAc,SAASA,OAAM,WAAW,OAAO,GAAG,cAAc,cAAcA,OAAM,WAAW,OAAO,CAAC;AACxJ,aAAO,CAAC,MAAM;AAAA,IAChB;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,IAAI,cAAc,CAACA,OAAM,WAAW,SAAS,MAAM,8BAA8B;AAC/E,UAAQA,MAAK;AAAA,SACN,QAAQ;AACX,aAAO,CAAC,IAAI,KAAK,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAClH;AAAA,SACK,cAAc;AACjB,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,WAAW,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,IAAI,CAAC;AAAA,IAC5E;AAAA,SACK,WAAW;AACd,YAAM,OAAO,cAAc,QAAQA,OAAM,WAAW,OAAO;AAC3D,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,IAAI,CAAC;AAAA,IACzE;AAAA,SACK,WAAW;AACd,aAAO,CAAC,IAAI,QAAQ,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACrH;AAAA,SACK,aAAa;AAChB,aAAO,CAAC,IAAI,UAAU,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,GAAG,cAAc,QAAQA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC1K;AAAA,SACK;AAAA,SACA,OAAO;AACV,aAAO,CAAC,IAAI,IAAI,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,WAAWA,OAAM,WAAW,OAAO,GAAG,cAAc,iBAAiBA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IAC7K;AAAA,SACK,kBAAkB;AACrB,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,YAAM,WAAW,cAAc,YAAYA,OAAM,WAAW,OAAO;AACnE,aAAO,CAAC,IAAI,eAAe,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,YAAY,QAAQ,CAAC;AAAA,IAChG;AAAA,SACK,kBAAkB;AACrB,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO;AACvE,YAAM,QAAQ,cAAc,SAASA,OAAM,WAAW,OAAO;AAC7D,aAAO,CAAC,IAAI,eAAe,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,YAAY,KAAK,CAAC;AAAA,IAC7F;AAAA,SACK,gBAAgB;AACnB,YAAM,YAAY,cAAc,aAAaA,OAAM,WAAW,OAAO;AACrE,YAAM,aAAa,cAAc,cAAcA,OAAM,WAAW,OAAO,EAAE,YAAY;AACrF,aAAO,CAAC,IAAI,aAAa,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,WAAW,UAAU,CAAC;AAAA,IAC/F;AAAA,SACK,eAAe;AAClB,aAAO,CAAC,IAAI,YAAY,cAAc,KAAKA,OAAM,WAAW,OAAO,GAAG,cAAc,SAASA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACzH;AAAA,SACK,iBAAiB;AACpB,aAAO,CAAC,IAAI,cAAc,cAAc,MAAMA,OAAM,WAAW,OAAO,GAAG,cAAc,MAAMA,OAAM,WAAW,OAAO,CAAC,CAAC;AAAA,IACzH;AAAA;AAEE,YAAM,UAAU,aAAaA,MAAK,uBAAuB;AAAA;AAE/D;AAGA,SAAS,YAAYA,OAAM,WAAW,SAAS,iBAAiB,QAAQ,MAAM;AAC5E,QAAM,SAAS,CAACgB,QAAO,YAAY,aAAa;AAC9C,YAAQA,OAAM;AAAA,WACP;AACH,eAAO,MAAM,MAAM,UAAUA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACtD;AACH,eAAO,MAAM,MAAM,WAAWA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACvD;AACH,eAAO,WAAWA,QAAO,YAAY,QAAQ;AAAA,WAC1C;AACH,eAAO,MAAM,MAAM,WAAWA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACvD;AACH,eAAO,MAAM,MAAM,WAAWA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACvD;AACH,eAAO,WAAWA,QAAO,YAAY,QAAQ;AAAA,WAC1C;AACH,eAAO,MAAM,MAAM,WAAWA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACvD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,WAAWA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACvD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,MAAM,MAAM,YAAYA,QAAO,YAAY,QAAQ,CAAC;AAAA,WACxD;AACH,eAAO,WAAWA,QAAO,YAAY,UAAU,eAAe;AAAA,WAC3D;AACH,cAAM,WAAW,gBAAgBA,OAAM,EAAE;AACzC,YAAI,YAAY,SAAS,gBAAgB;AACvC,iBAAO,SAAS,eAAe,IAAI,cAAcA,QAAO,YAAY,QAAQ,CAAC;AAAA,QAC/E,OAAO;AACL,gBAAM,UAAU,aAAaA,OAAM,uBAAuB;AAAA,QAC5D;AAAA;AAEA,cAAM,UAAU,eAAeA,OAAM,uIAAuI;AAAA;AAAA,EAElL,GAAGhB,OAAM,WAAW,OAAO;AAC3B,MAAI,aAAa,UAAU,KAAK,GAAG;AACjC,WAAO,MAAM,KAAK,CAAC,SAAS,CAAC,EAAE,OAAO,IAAI,CAAC;AAAA,EAC7C;AACA,SAAO,CAAC,EAAE,OAAO,KAAK;AACxB;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,YAAY,CAAC,GAAG,iBAAiB,CAAC,GAAG,gBAAgB,CAAC,GAAG,cAAc,CAAC,GAAG;AACrF,SAAK,YAAY;AACjB,SAAK,iBAAiB;AACtB,SAAK,gBAAgB;AACrB,SAAK,cAAc;AACnB,SAAK,cAAc,EAAE,IAAI,GAAG,WAAW,IAAI,aAAa,EAAE;AAC1D,SAAK,WAAW,CAAC,KAAK,WAAW;AACjC,SAAK,SAAS;AACd,SAAK,0BAA0B;AAAA,EACjC;AAAA,EACA,SAAS,IAAI,WAAW;AACtB,WAAO,EAAE,IAAI,WAAW,aAAa,EAAE;AAAA,EACzC;AAAA,EACA,IAAI,eAAe,WAAW;AAC5B,QAAI,KAAK,aAAa,WAAW;AAC/B,WAAK,WAAW;AAChB,WAAK,0BAA0B;AAAA,IACjC;AAAA,EACF;AAAA,EACA,IAAI,iBAAiB;AACnB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,mBAAmB;AACrB,WAAO,KAAK,mBAAmB;AAAA,EACjC;AAAA,EACA,IAAI,oBAAoB;AACtB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,4BAA4B;AAC1B,UAAM,QAAQ,CAAC;AACf,aAAS,KAAK,GAAG,KAAK,KAAK,SAAS,SAAS,GAAG,MAAM;AACpD,YAAM,YAAY,KAAK,SAAS,MAAM,GAAG,KAAK,SAAS,SAAS,EAAE;AAClE,YAAM,KAAK,KAAK,qBAAqB,SAAS,CAAC;AAAA,IACjD;AACA,UAAM,KAAK,EAAE;AACb,SAAK,qBAAqB;AAAA,EAC5B;AAAA,EACA,qBAAqB,WAAW;AAC9B,WAAO,YAAY,UAAU,IAAI,CAAC,YAAY,QAAQ,OAAO,KAAK,QAAQ,gBAAgB,IAAI,KAAK,GAAG,QAAQ,aAAa,QAAQ,aAAa,EAAE,KAAK,GAAG,IAAI;AAAA,EAChK;AAAA,EACA,WAAW,SAAS;AAClB,QAAI,KAAK,UAAU;AACjB,WAAK;AACL,WAAK,WAAW,KAAK,SAAS,MAAM;AACpC,WAAK,SAAS,KAAK,KAAK,SAAS,KAAK,QAAQ,OAAO,CAAC;AACtD,WAAK,mBAAmB,QAAQ,KAAK,qBAAqB,KAAK,QAAQ,CAAC;AAAA,IAC1E;AAAA,EACF;AAAA,EACA,YAAY;AACV,QAAI,KAAK,YAAY,KAAK,SAAS,SAAS,GAAG;AAC7C,WAAK,WAAW,KAAK,SAAS,MAAM;AACpC,WAAK,SAAS,OAAO,EAAE;AACvB,WAAK,kBAAkB,MAAM;AAAA,IAC/B,OAAO;AACL,YAAM,IAAI,MAAM,yCAAyC;AAAA,IAC3D;AAAA,EACF;AAAA,EACA,gBAAgB;AACd,QAAI,KAAK,YAAY,KAAK,SAAS,SAAS,GAAG;AAC7C,WAAK,WAAW,KAAK,SAAS,MAAM;AACpC,WAAK;AACL,YAAM,UAAU,OAAO,OAAO,CAAC,GAAG,KAAK,SAAS,KAAK,SAAS,SAAS,EAAE;AACzE,cAAQ,eAAe;AACvB,cAAQ,KAAK,KAAK;AAClB,WAAK,SAAS,OAAO,IAAI,GAAG,OAAO;AACnC,WAAK,mBAAmB,OAAO,GAAG,GAAG,KAAK,qBAAqB,KAAK,QAAQ,CAAC;AAAA,IAC/E,OAAO;AACL,YAAM,IAAI,MAAM,uDAAuD;AAAA,IACzE;AAAA,EACF;AAAA,EACA,UAAU,MAAM;AACd,WAAO,KAAK,UAAU;AAAA,EACxB;AAAA,EACA,eAAe,aAAa;AAC1B,SAAK,eAAe,YAAY,MAAM;AAAA,EACxC;AAAA,EACA,eAAe,IAAI;AACjB,WAAO,KAAK,eAAe;AAAA,EAC7B;AAAA,EACA,cAAc,YAAY;AACxB,SAAK,cAAc,WAAW,MAAM;AAAA,EACtC;AAAA,EACA,cAAc,IAAI;AAChB,WAAO,KAAK,cAAc;AAAA,EAC5B;AAAA,EACA,QAAQ,SAAS;AACf,eAAW,OAAO,KAAK,gBAAgB;AACrC,WAAK,eAAe,KAAK,cAAc,OAAO;AAAA,IAChD;AACA,eAAW,OAAO,KAAK,eAAe;AACpC,WAAK,cAAc,KAAK,cAAc,OAAO;AAAA,IAC/C;AAAA,EACF;AACF;AAGA,SAAS,qBAAqB,QAAQ,SAAS,WAAW,WAAW;AACnE,QAAM,YAA4B,oBAAI,IAAI;AAC1C,QAAM,gBAAgB,CAAC;AACvB,MAAI,cAAc;AAClB,MAAI,aAAa;AACjB,QAAM,OAAuB,oBAAI,IAAI;AACrC,QAAM,iBAAiB,OAAO,KAAK,MAAM,EAAE,IAAI,CAAC,SAAS,cAAc,IAAI,EAAE,EAAE;AAC/E,MAAI,gBAAgB,CAAC;AACrB,MAAI,aAAa,MAAM;AACrB,oBAAgB,UAAU,IAAI,CAACA,UAAS,cAAcA,MAAK,IAAI,EAAE,EAAE;AAAA,EACrE;AACA,QAAM,WAAW,CAAC,GAAG,OAAO;AAC5B,SAAO,SAAS,SAAS,GAAG;AAC1B,UAAMA,QAAO,SAAS,IAAI;AAC1B,QAAI,cAAcA,KAAI,KAAK,eAAeA,KAAI,KAAK,YAAYA,KAAI,GAAG;AACpE,UAAI,eAAe,MAAM;AACvB,sBAAcA;AACd,qBAAa,YAAY,SAAS,IAAI,CAAC,UAAU,MAAM,IAAI,EAAE,OAAO,CAAC,SAAS,UAAU,IAAI,IAAI,CAAC;AAAA,MACnG;AAAA,IACF;AACA,cAAU,IAAIA,MAAK,IAAI;AACvB,QAAI,UAAUA,MAAK,SAAS,MAAM;AAChC;AAAA,IACF;AACA,QAAI,eAAe,QAAQA,MAAK,IAAI,MAAM,IAAI;AAC5C;AAAA,IACF;AACA,QAAI,cAAc,QAAQA,MAAK,IAAI,MAAM,IAAI;AAC3C;AAAA,IACF;AACA,QAAIA,MAAK,OAAO,WAAW,GAAG;AAC5B,oBAAc,KAAKA,MAAK,IAAI;AAC5B;AAAA,IACF;AACA,IAAAA,MAAK,OAAO,QAAQ,CAAC,WAAW;AAC9B,UAAI,KAAK,IAAI,OAAO,IAAI,GAAG;AACzB;AAAA,MACF;AACA,WAAK,IAAI,OAAO,IAAI;AACpB,eAAS,KAAK,MAAM;AAAA,IACtB,CAAC;AAAA,EACH;AACA,SAAO,EAAE,QAAQ,SAAS,WAAW,eAAe,aAAa,WAAW;AAC9E;AACA,SAAS,2BAA2B,OAAO,WAAW,eAAe;AACnE,QAAM,EAAE,WAAW,OAAO,IAAI;AAC9B,QAAM,WAAW,CAAC;AAClB,QAAM,aAAa,OAAO,KAAK,MAAM,EAAE,IAAI,CAAC,SAAS,cAAc,IAAI,EAAE,EAAE,EAAE,IAAI,CAAC,SAAS,MAAM,MAAM,KAAK;AAC5G,QAAM,YAAY,MAAM;AACxB,aAAW,QAAQ,CAAC,WAAW;AAC7B,QAAI,UAAU,IAAI,OAAO,IAAI,GAAG;AAC9B,eAAS,KAAK,MAAM;AAAA,IACtB;AAAA,EACF,CAAC;AACD,QAAM,QAAQ,QAAQ,CAAC,WAAW;AAChC,QAAI,UAAU,IAAI,OAAO,IAAI,GAAG;AAC9B,eAAS,KAAK,MAAM;AAAA,IACtB;AAAA,EACF,CAAC;AACD,MAAI,aAAa,MAAM;AACrB,cAAU,QAAQ,CAACA,UAAS;AAC1B,UAAI,UAAU,IAAIA,MAAK,IAAI,GAAG;AAC5B,iBAAS,KAAKA,KAAI;AAAA,MACpB;AAAA,IACF,CAAC;AAAA,EACH;AACA,QAAM,OAAuB,oBAAI,IAAI;AACrC,QAAM,eAAe,CAAC;AACtB,SAAO,SAAS,SAAS,GAAG;AAC1B,UAAMA,QAAO,SAAS,IAAI;AAC1B,SAAK,IAAIA,MAAK,IAAI;AAClB,QAAI,CAAC,UAAUA,MAAK,OAAO;AACzB,mBAAa,KAAKA,KAAI;AAAA,IACxB;AACA,IAAAA,MAAK,SAAS,QAAQ,CAAC,UAAU;AAC/B,UAAI,CAAC,KAAK,IAAI,MAAM,IAAI,KAAK,UAAU,IAAI,MAAM,IAAI,KAAK,MAAM,OAAO,MAAM,CAAC,WAAW,KAAK,IAAI,OAAO,IAAI,CAAC,GAAG;AAC/G,iBAAS,KAAK,KAAK;AAAA,MACrB;AAAA,IACF,CAAC;AAAA,EACH;AACA,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,IAAI,oBAAoB;AAAA,EACtB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,IAAI,iBAAiB;AAAA,EACnB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,SAAS,cAAcA,OAAM;AAC3B,SAAO,iBAAiB,QAAQA,MAAK,EAAE,KAAK;AAC9C;AACA,SAAS,eAAeA,OAAM;AAC5B,SAAO,kBAAkB,QAAQA,MAAK,EAAE,KAAK;AAC/C;AACA,SAAS,YAAYA,OAAM;AACzB,SAAO,eAAe,QAAQA,MAAK,EAAE,KAAK;AAC5C;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,OAAO,QAAQ;AACzB,SAAK,QAAQ;AACb,SAAK,SAAS;AACd,SAAK,cAA8B,oBAAI,IAAI;AAC3C,SAAK,aAAa,CAAC;AACnB,SAAK,YAAY;AACjB,SAAK,aAAa,CAAC;AACnB,SAAK,uBAAuB,CAAC;AAC7B,SAAK,sBAAsB,CAAC;AAC5B,SAAK,qBAAqB;AAC1B,SAAK,WAAW,MAAM;AACtB,SAAK,UAAU,MAAM;AACrB,SAAK,aAAa,MAAM;AACxB,SAAK,aAAa,MAAM;AACxB,SAAK,aAAa,MAAM;AACxB,QAAI,MAAM,aAAa,MAAM;AAC3B,aAAO,KAAK,MAAM,SAAS,EAAE,QAAQ,CAAC,SAAS;AAC7C,aAAK,qBAAqB,QAAQ,IAAI,cAAc,MAAM,UAAU,OAAO,IAAI;AAAA,MACjF,CAAC;AAAA,IACH;AAAA,EACF;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK,SAAS,KAAK,OAAO,YAAY,KAAK;AAAA,EACpD;AAAA,EACA,IAAI,sBAAsB;AACxB,WAAO,KAAK,SAAS,KAAK,OAAO,sBAAsB,KAAK;AAAA,EAC9D;AAAA,EACA,IAAI,YAAY;AACd,WAAO,KAAK,SAAS,KAAK,OAAO,YAAY,KAAK;AAAA,EACpD;AAAA,EACA,IAAI,UAAU,WAAW;AACvB,UAAM,YAAY,OAAO,KAAK,SAAS,EAAE,IAAI,CAAC,QAAQ,UAAU,KAAK,IAAI,CAAC,YAAY,QAAQ,EAAE,CAAC;AACjG,SAAK,aAAa,CAAC,EAAE,OAAO,GAAG,SAAS;AACxC,SAAK,aAAa;AAAA,EACpB;AAAA,EACA,IAAI,gBAAgB,iBAAiB;AACnC,SAAK,mBAAmB;AAAA,EAC1B;AAAA,EACA,IAAI,SAAS;AACX,WAAO,KAAK,QAAQ,IAAI,CAACA,UAAS;AAChC,aAAO;AAAA,QACL,MAAMA,MAAK;AAAA,QACX,OAAOA,MAAK,WAAW,WAAWA,MAAK,WAAW,SAAS,QAAQ;AAAA,QACnE,OAAOA,MAAK,WAAW,WAAWA,MAAK,WAAW,SAAS,QAAQ;AAAA,MACrE;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,IAAI,UAAU;AACZ,WAAO,KAAK,SAAS,IAAI,CAACA,UAAS;AACjC,aAAO;AAAA,QACL,MAAMA,MAAK;AAAA,QACX,OAAOA,MAAK,WAAW,WAAWA,MAAK,WAAW,SAAS,QAAQ;AAAA,QACnE,OAAOA,MAAK,WAAW,WAAWA,MAAK,WAAW,SAAS,QAAQ;AAAA,MACrE;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,IAAI,aAAa;AACf,WAAO,KAAK,QAAQ,IAAI,CAACA,UAASA,MAAK,gBAAgBA,MAAK,IAAI;AAAA,EAClE;AAAA,EACA,IAAI,cAAc;AAChB,WAAO,KAAK,SAAS,IAAI,CAACA,UAAS;AACjC,YAAM,OAAOA,MAAK,gBAAgBA,MAAK;AACvC,aAAOA,MAAK,gBAAgB,GAAG,QAAQA,MAAK,kBAAkB;AAAA,IAChE,CAAC;AAAA,EACH;AAAA,EACA,IAAI,YAAY;AACd,WAAO,OAAO,KAAK,KAAK,UAAU,EAAE,OAAO,CAAC,KAAK,QAAQ;AACvD,UAAI,OAAO,KAAK,WAAW,KAAK;AAChC,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AAAA,EACP;AAAA,EACA,kBAAkB,QAAQ,SAAS;AACjC,UAAM,eAAe,OAAO,IAAI,CAACA,UAASA,MAAK,IAAI,EAAE,KAAK;AAC1D,UAAM,gBAAgB,QAAQ,IAAI,CAACA,UAASA,MAAK,IAAI,EAAE,KAAK;AAC5D,WAAO,aAAa,KAAK,KAAK,SAAS,IAAI,OAAO,cAAc,KAAK,KAAK,SAAS;AAAA,EACrF;AAAA,EACA,QAAQ,QAAQ,SAAS;AACvB,UAAM,gBAAgB,qBAAqB,QAAQ,SAAS,KAAK,WAAW,KAAK,UAAU;AAC3F,UAAM,EAAE,eAAe,aAAa,WAAW,IAAI;AACnD,QAAI,eAAe,MAAM;AACvB,YAAM,IAAI,MAAM,qCAAqC,YAAY,oCAAoC,YAAY,8GAA8G,aAAa;AAAA,IAC9O;AACA,QAAI,cAAc,SAAS,GAAG;AAC5B,YAAM,WAAW,QAAQ,IAAI,CAAC,OAAO,GAAG,IAAI;AAC5C,YAAM,UAAU,OAAO,KAAK,MAAM;AAClC,YAAM,IAAI,MAAM,+BAA+B,uCAAuC,4CAA4C,gBAAgB;AAAA,IACpJ;AACA,WAAO,2BAA2B,KAAK,OAAO,KAAK,WAAW,aAAa;AAAA,EAC7E;AAAA,EACA,QAAQ,QAAQ,SAAS;AACvB,aAAS,KAAK,UAAU,MAAM;AAC9B,UAAM,QAAQ,OAAO,KAAK,MAAM,EAAE,KAAK;AACvC,SAAK,YAAY,MAAM;AACvB,SAAK,uBAAuB,MAAM;AAClC,cAAU,KAAK,WAAW,OAAO;AACjC,SAAK,aAAa,OAAO;AACzB,UAAM,aAAa,MAAM,IAAI,CAAC,SAAS,KAAK,MAAM,MAAM,cAAc,IAAI,EAAE,GAAG;AAC/E,UAAM,kBAAkB,QAAQ,IAAI,CAAC,SAAS,cAAc,IAAI,EAAE,EAAE;AACpE,QAAIiB,eAAc,gBAAgB,IAAI,CAAC,SAAS,KAAK,MAAM,MAAM,KAAK;AACtE,SAAK,yBAAyB;AAC9B,QAAIA,aAAY,WAAW,GAAG;AAC5B,MAAAA,eAAc,KAAK;AAAA,IACrB;AACA,UAAM,iBAAiB,KAAK,kBAAkB,YAAYA,YAAW;AACrE,QAAI,eAAe,KAAK,YAAY,IAAI,cAAc;AACtD,QAAI,gBAAgB,MAAM;AACxB,qBAAe,KAAK,QAAQ,QAAQA,YAAW;AAC/C,WAAK,YAAY,IAAI,gBAAgB,YAAY;AAAA,IACnD;AACA,UAAM,iBAAiB,CAAC;AACxB,UAAM,gBAAgB,CAAC;AACvB,WAAO,KAAK,MAAM;AAChB,YAAM,UAAU,IAAI,iBAAiB,KAAK,WAAW,gBAAgB,eAAe,KAAK,mBAAmB;AAC5G,YAAM,aAAa,OAAO,OAAO,CAAC,GAAG,KAAK,SAAS;AACnD,aAAO,KAAK,MAAM,EAAE,QAAQ,CAAC,SAAS;AACpC,cAAM,CAAC,UAAUxB,MAAK,IAAI,cAAc,IAAI;AAC5C,cAAM,UAAU,CAAC;AACjB,gBAAQA,UAAS,OAAO;AACxB,mBAAW,YAAY;AAAA,MACzB,CAAC;AACD,YAAM,gBAAgB,KAAK,mBAAmB,UAAU;AACxD,YAAM,kCAAkC,CAAC;AACzC,eAAS,KAAK,GAAG,KAAK,aAAa,QAAQ,MAAM;AAC/C,cAAMO,QAAO,aAAa;AAC1B,YAAI,CAAC,WAAWA,MAAK,OAAO;AAC1B,gBAAM,UAAU,YAAYA,OAAM,YAAY,SAAS,KAAK,gBAAgB;AAC5E,cAAI,aAAa,UAAU,OAAO,GAAG;AACnC,kBAAM,IAAI,MAAM,4BAA4BA,MAAK,kEAAkE;AAAA,UACrH;AACA,qBAAWA,MAAK,QAAQ;AACxB,eAAK,uBAAuBA,MAAK,MAAMA,OAAM,YAAY,SAAS,eAAe,iBAAiB,+BAA+B;AAAA,QACnI;AAAA,MACF;AACA,UAAI,KAAK,UAAU,MAAM;AACvB,gBAAQ,QAAQ,aAAa;AAAA,MAC/B;AACA,aAAO,QAAQ,IAAI,CAAC,SAAS,UAAU,MAAM,YAAY,OAAO,CAAC;AAAA,IACnE,CAAC;AAAA,EACH;AAAA,EACA,mBAAmB,WAAW;AAC5B,UAAM,MAAM,CAAC,EAAE,OAAO,MAAM,CAAC,GAAG,OAAO,KAAK,SAAS,EAAE,IAAI,CAAC,QAAQ,UAAU,IAAI,EAAE,IAAI,CAAC,YAAY,QAAQ,IAAI,CAAC,YAAY,QAAQ,EAAE,CAAC,CAAC;AAC1I,WAAO,IAAI,IAAI,GAAG;AAAA,EACpB;AAAA,EACA,uBAAuB,UAAUA,OAAM,WAAW,SAAS,eAAe,aAAa,iCAAiC;AACtH,QAAIA,MAAK,aAAa,aAAa,YAAY,QAAQ,QAAQ,MAAM,IAAI;AACvE;AAAA,IACF;AACA,cAAU,UAAU,QAAQ,CAAC,YAAY;AACvC,UAAI,WAAW,MAAM;AACnB,wCAAgC,QAAQ,OAAO,gCAAgC,QAAQ,OAAO,KAAKA,MAAK,SAAS;AAAA,MACnH;AAAA,IACF,CAAC;AACD,IAAAA,MAAK,OAAO,QAAQ,CAAC,WAAW;AAC9B,UAAI,OAAO,aAAa,WAAW;AACjC,cAAM,UAAU,6BAA6B,OAAO,MAAM,WAAW,OAAO;AAC5E,YAAI,WAAW,MAAM;AACnB,kBAAQ,QAAQ,CAAC,YAAY;AAC3B,gBAAI,WAAW,CAAC,QAAQ,QAAQ,CAAC,cAAc,IAAI,QAAQ,EAAE,GAAG;AAC9D,oBAAMT,UAAS,gCAAgC,QAAQ;AACvD,kBAAIA,YAAW,GAAG;AAChB,oBAAI,CAAC,KAAK,oBAAoB;AAC5B,0BAAQ,QAAQ;AAAA,gBAClB,OAAO;AACL,wBAAM,CAAC,WAAWE,MAAK,IAAI,oBAAoBO,MAAK,MAAM,OAAO;AACjE,sBAAI,KAAK,oBAAoB,YAAY;AACvC,yBAAK,oBAAoB,WAAWP,UAAS;AAAA,kBAC/C,OAAO;AACL,yBAAK,oBAAoB,aAAa,CAAC;AACvC,yBAAK,oBAAoB,WAAWA,UAAS;AAAA,kBAC/C;AAAA,gBACF;AACA,uBAAO,gCAAgC,QAAQ;AAAA,cACjD,WAAWF,WAAU,MAAM;AACzB,gDAAgC,QAAQ;AAAA,cAC1C;AAAA,YACF;AAAA,UACF,CAAC;AAAA,QACH;AAAA,MACF;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,MAAM,aAAa,QAAQ,SAAS;AAClC,WAAO,KAAK,cAAc,QAAQ,OAAO;AAAA,EAC3C;AAAA,EACA,6BAA6B;AAC3B,QAAI,CAAC,KAAK,qBAAqB;AAC7B;AAAA,IACF;AACA,WAAO,KAAK,KAAK,mBAAmB,EAAE,QAAQ,CAAC,QAAQ,KAAK,oBAAoB,KAAK,QAAQ,CAAC,YAAY,QAAQ,QAAQ,CAAC,CAAC;AAC5H,SAAK,kBAAkB;AAAA,EACzB;AAAA,EACA,oBAAoB;AAClB,QAAI,CAAC,KAAK,YAAY;AACpB;AAAA,IACF;AACA,WAAO,KAAK,KAAK,UAAU,EAAE,QAAQ,CAAC,QAAQ;AAC5C,YAAM,cAAc,KAAK,WAAW;AACpC,kBAAY,QAAQ,CAAC,YAAY;AAC/B,YAAI,WAAW,CAAC,QAAQ,QAAQ,CAAC,QAAQ,cAAc,CAAC,KAAK,QAAQ,IAAI,QAAQ,EAAE,GAAG;AACpF,kBAAQ,QAAQ;AAAA,QAClB;AAAA,MACF,CAAC;AAAA,IACH,CAAC;AAAA,EACH;AAAA,EACA,yBAAyB;AACvB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,2BAA2B;AACzB,eAAW,OAAO,KAAK,qBAAqB;AAC1C,WAAK,oBAAoB,KAAK,QAAQ,CAAC,YAAY,QAAQ,QAAQ,CAAC;AACpE,aAAO,KAAK,oBAAoB;AAAA,IAClC;AAAA,EACF;AAAA,EACA,MAAM,cAAc,QAAQ,SAAS,sBAAsB,OAAO,iBAAiB,CAAC,GAAG,gBAAgB,CAAC,GAAG;AACzG,QAAI,CAAC,qBAAqB;AACxB,eAAS,KAAK,UAAU,MAAM;AAC9B,WAAK,YAAY,MAAM;AACvB,WAAK,uBAAuB,MAAM;AAClC,gBAAU,KAAK,WAAW,OAAO;AACjC,WAAK,aAAa,OAAO;AAAA,IAC3B;AACA,QAAI;AACF,WAAK,qBAAqB,IAAI,EAAE,QAAQ,2BAA2B;AAAA,IACrE,SAAS,IAAP;AACA,cAAQ,KAAK,GAAG,OAAO;AAAA,IACzB;AACA,SAAK,yBAAyB;AAC9B,UAAM,UAAU,IAAI,iBAAiB,KAAK,WAAW,gBAAgB,eAAe,KAAK,mBAAmB;AAC5G,SAAK,aAAa,MAAM,KAAK,uBAAuB,QAAQ,SAAS,SAAS,mBAAmB;AACjG,UAAM,UAAU,QAAQ,IAAI,CAAC,SAAS,UAAU,MAAM,KAAK,YAAY,OAAO,CAAC;AAC/E,UAAM,YAAY,QAAQ,IAAI,CAAC,OAAO,GAAG,EAAE;AAC3C,UAAM,WAAW,OAAO,KAAK,MAAM,EAAE,IAAI,CAAC,SAAS,OAAO,MAAM,EAAE;AAClE,SAAK,UAA0B,oBAAI,IAAI,CAAC,GAAG,WAAW,GAAG,UAAU,GAAG,KAAK,SAAS,CAAC;AACrF,QAAI,CAAC,KAAK,oBAAoB;AAC5B,WAAK,kBAAkB;AAAA,IACzB;AACA,QAAI,KAAK,UAAU,MAAM;AACvB,cAAQ,QAAQ,KAAK,OAAO;AAAA,IAC9B;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,qBAAqB,QAAQ,gBAAgB,eAAe;AAChE,UAAM,eAAe,OAAO,OAAO,CAAC,KAAK,SAASE,WAAU;AAC1D,UAAI,KAAK,OAAOA,QAAO,QAAQ;AAC/B,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AACL,WAAO,KAAK,cAAc,cAAc,KAAK,aAAa,MAAM,gBAAgB,aAAa;AAAA,EAC/F;AAAA,EACA,MAAM,uBAAuB,QAAQ,SAAS,aAAa,qBAAqB;AAC9E,UAAM,QAAQ,OAAO,KAAK,MAAM;AAChC,UAAM,aAAa,MAAM,IAAI,CAAC,SAAS,KAAK,MAAM,MAAM,cAAc,IAAI,EAAE,GAAG;AAC/E,UAAM,kBAAkB,YAAY,IAAI,CAAC,SAAS,cAAc,IAAI,EAAE,EAAE;AACxE,QAAIwB,eAAc,gBAAgB,IAAI,CAAC,SAAS,KAAK,MAAM,MAAM,KAAK;AACtE,QAAIA,aAAY,WAAW,GAAG;AAC5B,MAAAA,eAAc,KAAK;AAAA,IACrB;AACA,UAAM,EAAE,WAAW,eAAe,aAAa,WAAW,IAAI,qBAAqB,QAAQA,cAAa,KAAK,WAAW,KAAK,UAAU;AACvI,UAAM,SAAS;AAAA,MACb,GAAG;AAAA,MACH,GAAG,KAAK,MAAM;AAAA,MACd,GAAG,KAAK,cAAc,CAAC;AAAA,IACzB,EAAE,IAAI,CAACjB,UAAS;AACd,aAAO,EAAE,MAAAA,OAAM,UAAU,QAAQ,eAAe;AAAA,IAClD,CAAC;AACD,UAAM,aAAa,OAAO,OAAO,CAAC,GAAG,KAAK,SAAS;AACnD,WAAO,KAAK,MAAM,EAAE,QAAQ,CAAC,SAAS;AACpC,YAAM,CAAC,UAAUP,MAAK,IAAI,cAAc,IAAI;AAC5C,YAAM,UAAU,CAAC;AACjB,cAAQA,UAAS,OAAO;AACxB,iBAAW,YAAY;AAAA,IACzB,CAAC;AACD,UAAM,kCAAkC,CAAC;AACzC,UAAM,gBAAgB,KAAK,mBAAmB,UAAU;AACxD,UAAM,QAAQ,CAAC;AACf,WAAO,OAAO,SAAS,GAAG;AACxB,YAAM,WAAW,KAAK,aAAa,YAAY,QAAQ,SAAS,YAAY,OAAO,eAAe,iBAAiB,iCAAiC,SAAS;AAC7J,YAAM,QAAQ,IAAI,QAAQ;AAAA,IAC5B;AACA,QAAI,eAAe,QAAQ,CAAC,qBAAqB;AAC/C,cAAQ,KAAK,iIAAiI;AAAA,IAChJ;AACA,UAAM,iBAAiBwB,aAAY,OAAO,CAACjB,UAAS,CAAC,cAAcA,KAAI,KAAK,CAAC,UAAUA,MAAK,MAAM,YAAY,OAAO,CAAC,EAAE,IAAI,CAACA,UAASA,MAAK,IAAI;AAC/I,QAAI,eAAe,SAAS,GAAG;AAC7B,UAAI,iBAAiB;AACrB,UAAI,eAAe,MAAM;AACvB,yBAAiB,wFAAwF;AAAA,MAC3G;AACA,YAAM,IAAI,MAAM,+BAA+B,6CAA6C,qDAAqD,mBAAmB,gBAAgB;AAAA,IACtL;AACA,WAAO;AAAA,EACT;AAAA,EACA,aAAa,YAAY,QAAQ,SAAS,WAAW,OAAO,eAAe,aAAa,iCAAiC,WAAW;AAClI,UAAM,WAAW,CAAC;AAClB,WAAO,OAAO,SAAS,GAAG;AACxB,YAAM,OAAO,OAAO,IAAI;AACxB,cAAQ,iBAAiB,KAAK;AAC9B,UAAI,WAAW;AACf,UAAI,KAAK,KAAK,OAAO,WAAW,cAAc,cAAc,KAAK,MAAM,WAAW,OAAO,GAAG;AAC1F,SAAC,QAAQ,IAAI,oBAAoB,KAAK,KAAK,MAAM,OAAO;AAAA,MAC1D;AACA,UAAI,UAAU,KAAK,KAAK,SAAS,MAAM;AACrC,cAAM,UAAU,YAAY,KAAK,MAAM,WAAW,SAAS,KAAK,gBAAgB;AAChF,YAAI,CAAC,UAAU;AACb,WAAC,QAAQ,IAAI,oBAAoB,KAAK,KAAK,MAAM,OAAO;AAAA,QAC1D;AACA,cAAM,iBAAiB,QAAQ;AAC/B,YAAI,aAAa,UAAU,OAAO,GAAG;AACnC,mBAAS,KAAK,QAAQ,KAAK,CAAC,OAAO;AACjC,sBAAU,YAAY;AACtB,oBAAQ,iBAAiB;AACzB,iBAAK,uBAAuB,UAAU,KAAK,MAAM,WAAW,SAAS,eAAe,aAAa,+BAA+B;AAChI,iBAAK,kBAAkB,KAAK,MAAM,QAAQ,SAAS,WAAW,OAAO,SAAS;AAC9E,mBAAO;AAAA,UACT,CAAC,CAAC;AAAA,QACJ,OAAO;AACL,oBAAU,YAAY;AACtB,eAAK,uBAAuB,UAAU,KAAK,MAAM,WAAW,SAAS,eAAe,aAAa,+BAA+B;AAChI,eAAK,kBAAkB,KAAK,MAAM,QAAQ,SAAS,WAAW,OAAO,SAAS;AAAA,QAChF;AAAA,MACF,OAAO;AACL,aAAK,kBAAkB,KAAK,MAAM,QAAQ,SAAS,WAAW,OAAO,SAAS;AAAA,MAChF;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,kBAAkBA,OAAM,QAAQ,SAAS,WAAW,OAAO,WAAW;AACpE,IAAAA,MAAK,SAAS,QAAQ,CAAC,cAAc;AACnC,YAAM,CAAC,QAAQ,IAAI,oBAAoB,UAAU,MAAM,OAAO;AAC9D,UAAI,MAAM,aAAa,CAAC,UAAU,IAAI,UAAU,IAAI,GAAG;AACrD;AAAA,MACF;AACA,UAAI,UAAU,OAAO,SAAS;AAC5B,YAAI,UAAU,WAAW,KAAK,CAAC,SAAS;AACtC,iBAAO,CAAC,CAAC,UAAU,MAAM,WAAW,OAAO;AAAA,QAC7C,CAAC,GAAG;AACF,gBAAM,YAAY;AAClB,iBAAO,KAAK,EAAE,UAAU,QAAQ,gBAAgB,MAAM,UAAU,CAAC;AAAA,QACnE;AAAA,MACF,WAAW,UAAU,WAAW,MAAM,CAAC,SAAS;AAC9C,eAAO,CAAC,CAAC,UAAU,MAAM,WAAW,OAAO;AAAA,MAC7C,CAAC,GAAG;AACF,cAAM,YAAY;AAClB,eAAO,KAAK,EAAE,UAAU,QAAQ,gBAAgB,MAAM,UAAU,CAAC;AAAA,MACnE;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,UAAU;AACR,WAAO,KAAK,KAAK,SAAS,EAAE,QAAQ,CAAC,QAAQ,KAAK,UAAU,KAAK,QAAQ,CAAC,YAAY,QAAQ,QAAQ,CAAC,CAAC;AAAA,EAC1G;AAAA,EACA,uBAAuB,QAAQ;AAC7B,WAAO,KAAK,MAAM,EAAE,QAAQ,CAAC,SAAS;AACpC,YAAM,SAAS,OAAO;AACtB,YAAM,CAAC,QAAQ,IAAI,cAAc,IAAI;AACrC,YAAMA,QAAO,KAAK,MAAM,MAAM;AAC9B,UAAIA,MAAK,WAAW,YAAYA,MAAK,WAAW,SAAS,OAAO;AAC9D,cAAM,QAAQA,MAAK,WAAW,SAAS;AACvC,cAAMkB,SAAQ,MAAM,WAAW,OAAO,MAAM,UAAU,OAAO,MAAM,MAAM,CAAC,KAAKzB,WAAU,MAAMA,YAAW,MAAM,MAAMA,YAAW,GAAG;AACpI,qBAAa,OAAOyB,QAAO,MAAM,sBAAsBlB,MAAK,mDAAmD,oBAAoB,OAAO,QAAQ;AAAA,MACpJ;AACA,UAAIA,MAAK,WAAW,YAAYA,MAAK,WAAW,SAAS,OAAO;AAC9D,qBAAa,OAAO,OAAO,UAAUA,MAAK,WAAW,SAAS,OAAO,MAAM,sBAAsBA,MAAK,kDAAkDA,MAAK,WAAW,SAAS,kBAAkB,OAAO,OAAO;AAAA,MACnN;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,UAAU,QAAQ;AAChB,UAAM,SAAS,CAAC;AAChB,eAAW,aAAa,QAAQ;AAC9B,UAAI,KAAK,cAAc,QAAQ,KAAK,WAAW,UAAU,QAAQ,KAAK,WAAW,OAAO,cAAc,MAAM;AAC1G,cAAM,UAAU,KAAK,WAAW,OAAO;AACvC,eAAO,QAAQ,QAAQ,OAAO;AAAA,MAChC,OAAO;AACL,eAAO,aAAa,OAAO;AAAA,MAC7B;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,YAAY,QAAQ;AAClB,UAAM,aAAa,OAAO,KAAK,MAAM,EAAE,OAAO,CAAC,SAAS;AACtD,YAAM,CAAC,QAAQ,IAAI,cAAc,IAAI;AACrC,aAAO,KAAK,MAAM,MAAM,aAAa;AAAA,IACvC,CAAC;AACD,QAAI,WAAW,SAAS,GAAG;AACzB,YAAM,IAAI,MAAM,uDAAuD,wCAAwC;AAAA,IACjH;AAAA,EACF;AAAA,EACA,WAAW,SAAS;AAClB,WAAO,QAAQ,IAAI,CAAC,SAAS;AAC3B,UAAI,KAAK,cAAc,QAAQ,KAAK,WAAW,WAAW,QAAQ,KAAK,WAAW,QAAQ,SAAS,MAAM;AACvG,cAAM,UAAU,KAAK,WAAW,QAAQ;AACxC,eAAO,QAAQ;AAAA,MACjB;AACA,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AAAA,EACP;AAAA,EACA,aAAa,SAAS;AACpB,YAAQ,QAAQ,CAAC,SAAS;AACxB,YAAM,CAAC,cAAc,IAAI,cAAc,IAAI;AAC3C,UAAI,CAAC,KAAK,MAAM,MAAM,iBAAiB;AACrC,cAAM,IAAI,MAAM,eAAe,iCAAiC;AAAA,MAClE;AAAA,IACF,CAAC;AAAA,EACH;AACF;AAGA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,YAAY,wBAAwB,CAAC,GAAG,eAAe,CAAC,GAAG;AACzD,SAAK,wBAAwB;AAC7B,SAAK,eAAe;AAAA,EACtB;AAAA,EACA,aAAa,MAAM,WAAW;AAC5B,SAAK,sBAAsB,QAAQ,UAAU;AAC7C,SAAK,aAAa,UAAU,MAAM;AAAA,EACpC;AAAA,EACA,yBAAyB,MAAM;AAC7B,WAAO,KAAK,sBAAsB;AAAA,EACpC;AAAA,EACA,iBAAiB,IAAI;AACnB,WAAO,KAAK,aAAa;AAAA,EAC3B;AAAA,EACA,UAAU;AACR,eAAW,OAAO,KAAK,cAAc;AACnC,WAAK,aAAa,KAAK,cAAc;AACrC,aAAO,KAAK,aAAa;AAAA,IAC3B;AACA,eAAW,QAAQ,KAAK,uBAAuB;AAC7C,WAAK,sBAAsB,MAAM,QAAQ;AACzC,aAAO,KAAK,sBAAsB;AAAA,IACpC;AAAA,EACF;AACF;AAGA,IAAI,qBAAqB;AACzB,IAAI,qBAAqB;AACzB,IAAI,aAAa,MAAM;AAAA,EACrB,YAAY,UAAU,cAAc,CAAC,GAAG,OAAO,YAAY;AACzD,SAAK,WAAW;AAChB,SAAK,cAAc;AACnB,SAAK,UAAU;AACf,SAAK,KAAK;AACV,QAAI,eAAe,MAAM;AACvB,WAAK,cAAc,CAAC;AAAA,IACtB;AACA,SAAK,kBAAkB,IAAI,gBAAgB;AAAA,EAC7C;AAAA,EACA,IAAI,eAAe;AACjB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,aAAa;AACf,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,IAAI,cAAc;AAChB,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,IAAI,SAAS;AACX,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,IAAI,UAAU;AACZ,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,IAAI,UAAU;AACZ,WAAO,KAAK,SAAS;AAAA,EACvB;AAAA,EACA,IAAI,WAAW;AACb,WAAO,KAAK,UAAU;AAAA,EACxB;AAAA,EACA,IAAI,iBAAiB;AACnB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,4BAA4B;AAC9B,WAAO,KAAK;AAAA,EACd;AAAA,EACA,gBAAgB;AACd,UAAM,OAAO,KAAK;AAClB,QAAI,KAAK,QAAQ,MAAM;AACrB,WAAK,UAAU;AAAA,IACjB,WAAW,KAAK,YAAY,eAAe,MAAM;AAC/C,WAAK,UAAU,KAAK,GAAG,mBAAmB,MAAM,KAAK,WAAW;AAAA,IAClE,OAAO;AACL,YAAM,WAAW,KAAK,GAAG,gBAAgB,MAAM,KAAK,WAAW;AAC/D,UAAI,SAAS,WAAW,GAAG;AACzB,iBAAS,KAAK,KAAK,GAAG,mBAAmB,MAAM,KAAK,WAAW,CAAC;AAAA,MAClE,WAAW,SAAS,SAAS,GAAG;AAC9B,cAAM,IAAI,MAAM,wBAAwB,SAAS,kCAAkC,CAAC,IAAI,IAAI;AAAA,MAC9F;AACA,WAAK,UAAU,SAAS;AAAA,IAC1B;AAAA,EACF;AAAA,EACA,OAAO;AACL,SAAK,cAAc;AACnB,QAAI,KAAK,QAAQ,QAAQ,MAAM;AAC7B,YAAM,IAAI,MAAM,+GAA+G;AAAA,IACjI;AACA,UAAM,aAAa,KAAK,QAAQ,KAAK;AACrC,QAAI,aAAa,UAAU,UAAU,GAAG;AACtC,aAAO,WAAW,KAAK,CAAC,cAAc,KAAK,SAAS,SAAS,CAAC;AAAA,IAChE;AACA,WAAO,KAAK,SAAS,UAAU;AAAA,EACjC;AAAA,EACA,SAAS,WAAW;AAClB,SAAK,YAAY;AACjB,UAAM,QAAQ,KAAK,UAAU;AAC7B,QAAI,YAAY,KAAK,UAAU;AAC/B,QAAI,KAAK,UAAU,uBAAuB,MAAM;AAC9C,YAAM,WAAW,KAAK,UAAU;AAChC,UAAI,SAAS,aAAa,MAAM;AAC9B,oBAAY,SAAS;AAAA,MACvB;AACA,UAAI,SAAS,wBAAwB,MAAM;AACzC,aAAK,uBAAuB,SAAS;AAAA,MACvC;AAAA,IACF;AACA,SAAK,YAAY;AACjB,SAAK,UAAU,GAAG,MAAM,SAAS,YAAY,MAAM,SAAS;AAC5D,UAAM,YAAY,KAAK,GAAG,cAAc,KAAK,UAAU,YAAY,KAAK,UAAU,WAAW;AAC7F,SAAK,WAAW,IAAI,cAAc,gBAAgB,SAAS,eAAe,OAAO,KAAK,SAAS,CAAC;AAChG,SAAK,SAAS,YAAY,KAAK,6BAA6B,SAAS;AACrE,SAAK,SAAS,kBAAkB,KAAK;AACrC,QAAI,UAAU,oBAAoB,QAAQ,UAAU,iBAAiB,QAAQ,MAAM;AACjF,YAAM,cAAc,gBAAgB,SAAS,eAAe,UAAU,gBAAgB;AACtF,WAAK,cAAc,IAAI,cAAc,WAAW;AAChD,WAAK,YAAY,YAAY,KAAK,SAAS;AAC3C,WAAK,YAAY,kBAAkB,KAAK;AACxC,WAAK,YAAY,aAAa,CAAC,GAAG,CAAC,CAAC;AAAA,IACtC;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,KAAK,cAAcF,SAAQ;AAC/B,QAAI,OAAO,iBAAiB,UAAU;AACpC,YAAM,WAAW,KAAK,GAAG,gBAAgB,YAAY;AACrD,UAAI,SAAS,WAAW,GAAG;AACzB,cAAM,IAAI,MAAM,0CAA0C,eAAe;AAAA,MAC3E,WAAW,SAAS,SAAS,GAAG;AAC9B,cAAM,IAAI,MAAM,wBAAwB,SAAS,kCAAkC,eAAe;AAAA,MACpG;AACA,qBAAe,SAAS;AAAA,IAC1B;AACA,QAAI,aAAa,QAAQ,MAAM;AAC7B,YAAM,IAAI,MAAM,6GAA6G;AAAA,IAC/H;AACA,WAAO,aAAa,KAAK,KAAK,SAAS;AAAA,EACzC;AAAA,EACA,QAAQ,QAAQA,SAAQ;AACtB,UAAM,gBAAgB,KAAK,QAAQ,QAAQ,KAAK,WAAW;AAC3D,QAAI,KAAK,sBAAsB;AAC7B,YAAM,qBAAqB,yBAAyB,SAAS,CAAC,aAAa,IAAI;AAC/E,YAAM,kBAAkB,CAAC;AACzB,yBAAmB,QAAQ,CAAC,cAAc,OAAO,gBAAgB,KAAK,qBAAqB,OAAO,YAAY;AAC9G,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT;AAAA,EACA,gBAAgB,QAAQ;AACtB,QAAI,EAAE,kBAAkB,WAAW,CAAC,MAAM,QAAQ,MAAM,GAAG;AACzD,aAAO;AAAA,IACT;AACA,aAAS,MAAM,QAAQ,MAAM,IAAI,SAAS,CAAC,MAAM;AACjD,QAAI,OAAO,WAAW,KAAK,WAAW,QAAQ;AAC5C,YAAM,IAAI,MAAM,mDAAmD,KAAK,WAAW,wCAAwC,OAAO,uBAAuB;AAAA,IAC3J;AACA,WAAO,KAAK,WAAW,OAAO,CAAC,KAAK,WAAW,OAAO;AACpD,UAAI,aAAa,OAAO;AACxB,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AAAA,EACP;AAAA,EACA,iBAAiB,SAAS;AACxB,cAAU,WAAW,KAAK;AAC1B,WAAO,CAAC,MAAM,QAAQ,OAAO,IAAI,CAAC,OAAO,IAAI;AAAA,EAC/C;AAAA,EACA,QAAQ,QAAQ,SAAS;AACvB,aAAS,KAAK,gBAAgB,MAAM;AACpC,cAAU,KAAK,iBAAiB,OAAO;AACvC,UAAM,SAAS,KAAK,SAAS,QAAQ,QAAQ,OAAO;AACpD,WAAO,OAAO,SAAS,IAAI,SAAS,OAAO;AAAA,EAC7C;AAAA,EACA,MAAM,aAAa,QAAQ,SAAS;AAClC,aAAS,KAAK,gBAAgB,MAAM;AACpC,cAAU,KAAK,iBAAiB,OAAO;AACvC,UAAM,SAAS,MAAM,KAAK,SAAS,aAAa,QAAQ,OAAO;AAC/D,WAAO,OAAO,SAAS,IAAI,SAAS,OAAO;AAAA,EAC7C;AAAA,EACA,yBAAyB;AACvB,WAAO,KAAK,SAAS,uBAAuB;AAAA,EAC9C;AAAA,EACA,6BAA6B;AAC3B,SAAK,SAAS,2BAA2B;AAAA,EAC3C;AAAA,EACA,6BAA6B,KAAK;AAChC,WAAO,OAAO,KAAK,GAAG,EAAE,OAAO,CAAC,QAAQ,QAAQ;AAC9C,aAAO,OAAO,CAAC,IAAI,IAAI;AACvB,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AAAA,EACP;AAAA,EACA,UAAU;AACR,SAAK,SAAS,QAAQ;AACtB,QAAI,KAAK,aAAa;AACpB,WAAK,YAAY,QAAQ;AAAA,IAC3B;AACA,SAAK,gBAAgB,QAAQ;AAAA,EAC/B;AACF;AACA,eAAe,eAAe,UAAUR,WAAU,CAAC,GAAG,OAAO,YAAY;AACvE,MAAI,YAAY,MAAM;AACpB,UAAM,IAAI,MAAM,wGAAwG;AAAA,EAC1H;AACA,MAAIA,YAAW,MAAM;AACnB,IAAAA,WAAU,CAAC;AAAA,EACb;AACA,MAAIA,SAAQ,aAAa,OAAO,aAAa,UAAU;AACrD,eAAW,YAAY,QAAQ;AAAA,EACjC;AACA,QAAMuB,UAAS,IAAI,WAAW,UAAUvB,UAAS,IAAI;AACrD,QAAMuB,QAAO,KAAK;AAClB,SAAOA;AACT;AACA,SAAS,mBAAmB,aAAa;AACvC,MAAI,eAAe,MAAM;AACvB,UAAM,IAAI,MAAM,4GAA4G;AAAA,EAC9H;AACA,MAAI,CAAC,YAAY,MAAM;AACrB,UAAM,IAAI,MAAM,uBAAuB,kCAAkC;AAAA,EAC3E;AACA,QAAMA,UAAS,IAAI,WAAW,WAAW;AACzC,EAAAA,QAAO,KAAK;AACZ,SAAOA;AACT;AACA,SAAS,YAAY,UAAU;AAC7B,MAAI,CAAC,SAAS,SAAS,GAAG,GAAG;AAC3B,eAAW,WAAW;AAAA,EACxB;AACA,SAAO,GAAG,WAAW,qBAAqB;AAC5C;AAGA,IAAI,WAAW;AAGf,IAAI,gBAAgB,CAAC;AACrBhC,UAAS,eAAe;AAAA,EACtB,YAAY,MAAM;AAAA,EAClB,SAAS,MAAM;AAAA,EACf,gBAAgB,MAAM;AAAA,EACtB,iBAAiB,MAAM;AAAA,EACvB,eAAe,MAAM;AAAA,EACrB,OAAO,MAAM;AAAA,EACb,KAAK,MAAM;AAAA,EACX,MAAM,MAAM;AAAA,EACZ,WAAW,MAAM;AAAA,EACjB,YAAY,MAAM;AAAA,EAClB,cAAc,MAAM;AAAA,EACpB,QAAQ,MAAM;AAAA,EACd,KAAK,MAAM;AACb,CAAC;AAGD,IAAI,cAAc,QAAQ,oBAAoB,CAAC;AAG/C,IAAI,cAAc,QAAQ,oBAAoB,CAAC;AAG/C,SAAS,QAAQ,QAAQ,OAAO;AAC9B,SAAO,gBAAgB,QAAQ,KAAK;AACtC;AACA,SAAS,gBAAgB,QAAQ,OAAO,OAAuB,oBAAI,IAAI,GAAG,cAA8B,oBAAI,IAAI,GAAG;AACjH,MAAI,UAAU,MAAM;AAClB,WAAO;AAAA,EACT;AACA,MAAI,OAAO,SAAS,cAAc,kBAAkB,MAAM;AACxD,WAAO,OAAO,MAAM;AAAA,EACtB;AACA,MAAI,YAAY,IAAI,MAAM,GAAG;AAC3B,UAAM,IAAI,MAAM,wCAAwC;AAAA,EAC1D;AACA,MAAI,KAAK,IAAI,MAAM,GAAG;AACpB,WAAO,KAAK,IAAI,MAAM;AAAA,EACxB;AACA,QAAM,SAAS,MAAM,MAAM;AAC3B,MAAI,OAAO,WAAW,OAAO,UAAU,MAAM;AAC3C,UAAM,IAAI,MAAM,mEAAmE;AAAA,EACrF;AACA,MAAI,CAAC,OAAO,SAAS;AACnB,SAAK,IAAI,QAAQ,OAAO,KAAK;AAC7B,WAAO,OAAO;AAAA,EAChB,WAAW,YAAY,MAAM,GAAG;AAC9B,UAAM,iBAAiB,MAAM,QAAQ,MAAM,IAAI,CAAC,IAAI,CAAC;AACrD,gBAAY,IAAI,MAAM;AACtB,eAAW,KAAK,QAAQ;AACtB,YAAM,QAAQ,OAAO;AACrB,YAAM,cAAc,gBAAgB,OAAO,OAAO,MAAM,WAAW;AACnE,qBAAe,KAAK;AAAA,IACtB;AACA,gBAAY,OAAO,MAAM;AACzB,QAAI,OAAO,WAAW;AACpB,qBAAe,YAAY,OAAO;AAAA,IACpC;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,yCAAyC,QAAQ;AAAA,EACnE;AACF;AACA,SAAS,QAAQ,QAAQ,QAAQ,WAAW;AAC1C,SAAO,gBAAgB,QAAQ,KAAK;AACtC;AACA,SAAS,gBAAgB,QAAQ,OAAO,cAA8B,oBAAI,IAAI,GAAG;AAC/E,QAAM,SAAS,OAAO;AACtB,MAAI,YAAY,IAAI,MAAM,GAAG;AAC3B,UAAM,IAAI,MAAM,wCAAwC;AAAA,EAC1D;AACA,QAAM,SAAS,MAAM,MAAM;AAC3B,MAAI,OAAO,WAAW,OAAO,UAAU,MAAM;AAC3C,UAAM,IAAI,MAAM,mEAAmE;AAAA,EACrF;AACA,MAAI,CAAC,OAAO,SAAS;AACnB,WAAO,OAAO;AAAA,EAChB,WAAW,YAAY,MAAM,GAAG;AAC9B,UAAM,iBAAiB,MAAM,QAAQ,MAAM,IAAI,CAAC,IAAI,CAAC;AACrD,gBAAY,IAAI,MAAM;AACtB,eAAW,KAAK,QAAQ;AACtB,YAAM,WAAW,OAAO,IAAI,CAAC,MAAM,EAAE,EAAE;AACvC,YAAM,cAAc,gBAAgB,UAAU,OAAO,WAAW;AAChE,qBAAe,KAAK;AAAA,IACtB;AACA,gBAAY,OAAO,MAAM;AACzB,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,yCAAyC,QAAQ;AAAA,EACnE;AACF;AACA,SAAS,UAAU,GAAG;AACpB,MAAI,MAAM,MAAM;AACd,WAAO;AAAA,EACT;AACA,MAAI,YAAY,EAAE,EAAE,GAAG;AACrB,WAAO,EAAE,OAAO,MAAM,SAAS,KAAK;AAAA,EACtC,OAAO;AACL,WAAO,EAAE,OAAO,GAAG,SAAS,MAAM;AAAA,EACpC;AACF;AACA,eAAe,mBAAmB,QAAQ,OAAO;AAC/C,QAAM,OAAuB,oBAAI,IAAI;AACrC,kBAAgB,QAAQ,OAAO,IAAI;AACnC,aAAW,OAAO,MAAM,KAAK,KAAK,KAAK,CAAC,GAAG;AACzC,UAAM,QAAQ,KAAK,IAAI,GAAG;AAC1B,QAAI,aAAa,UAAU,KAAK,GAAG;AACjC,YAAM,cAAc,MAAM;AAC1B,WAAK,IAAI,KAAK,WAAW;AAAA,IAC3B;AAAA,EACF;AACA,QAAM,SAAS,gBAAgB,QAAQ,OAAO,IAAI;AAClD,SAAO;AACT;AACA,SAAS,YAAY,KAAK;AACxB,MAAI,gBAAgB;AACpB,MAAI,IAAI,EAAE,IAAI,YAAY,GAAG;AAC3B,oBAAgB,eAAe;AAAA,EACjC,OAAO;AACL,UAAM,EAAE,cAAc,IAAI,uBAAuB;AACjD,oBAAgB,eAAe;AAAA,EACjC;AACA,SAAO,OAAO,QAAQ,CAAC,YAAY,OAAO,GAAG,MAAM,MAAM,QAAQ,GAAG,KAAK,OAAO,QAAQ,YAAY,EAAE,eAAe,WAAW,EAAE,eAAe,YAAY,CAAC;AAChK;AACA,SAAS,aAAa,KAAK;AACzB,SAAO,OAAO,QAAQ,YAAY,GAAG,KAAK,MAAM,QAAQ,GAAG,KAAK,OAAO,QAAQ,YAAY,eAAe,UAAU,aAAa,aAAa,GAAG;AACnJ;AACA,SAAS,YAAY,OAAO;AAC1B,SAAO,UAAU,QAAQ,OAAO,UAAU,YAAY,OAAO,UAAU;AACzE;AAGA,SAAS,UAAU,WAAW;AAC5B,SAAO,QAAQ,WAAW,aAAa;AACzC;AACA,SAAS,cAAc,MAAM;AAC3B,MAAI,gBAAgB,QAAQ;AAC1B,WAAO,EAAE,OAAO,KAAK,MAAM,GAAG,SAAS,MAAM;AAAA,EAC/C,WAAW,YAAY,IAAI,GAAG;AAC5B,WAAO,EAAE,OAAO,MAAM,SAAS,KAAK;AAAA,EACtC,OAAO;AACL,WAAO,EAAE,OAAO,MAAM,SAAS,MAAM;AAAA,EACvC;AACF;AAGA,IAAI,aAAa,MAAM;AAAA,EACrB,YAAY,UAAU;AACpB,SAAK,WAAW;AAChB,SAAK,QAAQ;AACb,SAAK,MAAM;AACX,QAAI,YAAY,MAAM;AACpB,YAAM,IAAI,WAAW,iDAAiD;AAAA,IACxE;AACA,QAAI,WAAW,GAAG;AAChB,YAAM,IAAI,WAAW,2CAA2C;AAAA,IAClE;AACA,SAAK,OAAO,IAAI,MAAM,QAAQ;AAC9B,SAAK,kBAAkB,IAAI;AAAA,EAC7B;AAAA,EACA,KAAKY,QAAO;AACV,WAAOA,SAAQ,GAAG;AAChB,MAAAA,UAAS,KAAK;AAAA,IAChB;AACA,WAAOA,SAAQ,KAAK;AAAA,EACtB;AAAA,EACA,IAAIA,QAAO;AACT,QAAIA,SAAQ,GAAG;AACb,YAAM,IAAI,WAAW,qCAAqC;AAAA,IAC5D;AACA,WAAO,KAAK,KAAKA,SAAQ,KAAK;AAAA,EAChC;AAAA,EACA,IAAIA,QAAO,OAAO;AAChB,QAAIA,SAAQ,GAAG;AACb,YAAM,IAAI,WAAW,qCAAqC;AAAA,IAC5D;AACA,SAAK,KAAKA,SAAQ,KAAK,YAAY;AAAA,EACrC;AAAA,EACA,SAAS;AACP,QAAI,SAAS,KAAK,MAAM,KAAK;AAC7B,QAAI,SAAS,GAAG;AACd,eAAS,KAAK,kBAAkB;AAAA,IAClC;AACA,WAAO;AAAA,EACT;AAAA,EACA,SAAS;AACP,WAAO,KAAK,OAAO,MAAM,KAAK;AAAA,EAChC;AAAA,EACA,UAAU;AACR,WAAO,KAAK,OAAO,MAAM;AAAA,EAC3B;AAAA,EACA,KAAK,OAAO;AACV,QAAI,KAAK,OAAO,GAAG;AACjB,YAAM,IAAI,WAAW,sBAAsB;AAAA,IAC7C;AACA,SAAK,IAAI,KAAK,KAAK,KAAK;AACxB,SAAK,MAAM,KAAK,KAAK,KAAK,MAAM,CAAC;AAAA,EACnC;AAAA,EACA,QAAQ,QAAQ;AACd,eAAW,SAAS,QAAQ;AAC1B,WAAK,KAAK,KAAK;AAAA,IACjB;AAAA,EACF;AAAA,EACA,MAAM;AACJ,QAAI,KAAK,QAAQ,GAAG;AAClB,YAAM,IAAI,WAAW,uBAAuB;AAAA,IAC9C;AACA,SAAK,MAAM,KAAK,KAAK,KAAK,MAAM,CAAC;AACjC,UAAM,SAAS,KAAK,IAAI,KAAK,GAAG;AAChC,SAAK,IAAI,KAAK,KAAK,MAAM;AACzB,WAAO;AAAA,EACT;AAAA,EACA,QAAQ,OAAO;AACb,QAAI,KAAK,OAAO,GAAG;AACjB,YAAM,IAAI,WAAW,sBAAsB;AAAA,IAC7C;AACA,SAAK,QAAQ,KAAK,KAAK,KAAK,QAAQ,CAAC;AACrC,SAAK,IAAI,KAAK,OAAO,KAAK;AAAA,EAC5B;AAAA,EACA,QAAQ;AACN,QAAI,KAAK,QAAQ,GAAG;AAClB,YAAM,IAAI,WAAW,uBAAuB;AAAA,IAC9C;AACA,UAAM,SAAS,KAAK,IAAI,KAAK,KAAK;AAClC,SAAK,IAAI,KAAK,OAAO,MAAM;AAC3B,SAAK,QAAQ,KAAK,KAAK,KAAK,QAAQ,CAAC;AACrC,WAAO;AAAA,EACT;AAAA,EACA,cAAc,eAAe;AAC3B,QAAI,KAAK,QAAQ,GAAG;AAClB,YAAM,IAAI,WAAW,uBAAuB;AAAA,IAC9C;AACA,UAAMA,SAAQ,KAAK,KAAK,KAAK,QAAQ,aAAa;AAClD,UAAM,SAAS,KAAK,IAAIA,MAAK;AAC7B,SAAK,IAAIA,QAAO,KAAK,IAAI,CAAC;AAC1B,WAAO;AAAA,EACT;AACF;AAGA,IAAI,oBAAoB,cAAc,WAAW;AAAA,EAC/C,cAAc;AACZ,UAAM,kBAAkB,gBAAgB;AAAA,EAC1C;AAAA,EACA,SAAS;AACP,WAAO;AAAA,EACT;AAAA,EACA,KAAK,OAAO;AACV,QAAI,MAAM,OAAO,GAAG;AAClB,WAAK,OAAO;AAAA,IACd;AACA,UAAM,KAAK,KAAK;AAAA,EAClB;AAAA,EACA,QAAQ,OAAO;AACb,QAAI,MAAM,OAAO,GAAG;AAClB,WAAK,OAAO;AAAA,IACd;AACA,UAAM,QAAQ,KAAK;AAAA,EACrB;AAAA,EACA,SAAS;AACP,UAAM,cAAc,KAAK,WAAW;AACpC,UAAM,UAAU,IAAI,MAAM,WAAW;AACrC,UAAM,MAAM,KAAK,OAAO;AACxB,aAAS,KAAK,GAAG,KAAK,KAAK,MAAM;AAC/B,cAAQ,MAAM,KAAK,IAAI,KAAK,KAAK,KAAK,QAAQ,EAAE,CAAC;AAAA,IACnD;AACA,SAAK,OAAO;AACZ,SAAK,WAAW;AAChB,SAAK,kBAAkB,IAAI,KAAK;AAChC,SAAK,QAAQ;AACb,SAAK,MAAM;AAAA,EACb;AACF;AACA,kBAAkB,mBAAmB;AAGrC,SAAS,kBAAkB,OAAO;AAChC,SAAO,IAAI,cAAc,KAAK;AAChC;AACA,SAAS,qBAAqB,OAAO;AACnC,SAAO,IAAI,qBAAqB,KAAK;AACvC;AACA,SAAS,yBAAyB,eAAe,kBAAkB;AACjE,SAAO,IAAI,gBAAgB,eAAe,gBAAgB;AAC5D;AACA,SAAS,mBAAmB,WAAW,eAAe,gBAAgB,MAAM;AAC1E,SAAO,IAAI,YAAY,WAAW,YAAY;AAChD;AACA,IAAI,eAAe,MAAM;AAAA,EACvB,MAAM,UAAU;AACd,UAAM,SAAS,CAAC;AAChB,QAAI,IAAI,MAAM,KAAK,KAAK;AACxB,WAAO,CAAC,EAAE,MAAM;AACd,aAAO,KAAK,EAAE,KAAK;AACnB,UAAI,MAAM,KAAK,KAAK;AAAA,IACtB;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,iBAAiB;AACrB,UAAM,SAAS,KAAK,SAAS,GAAG;AAChC,UAAM,SAAS,CAAC;AAChB,QAAI,IAAI,MAAM,OAAO,KAAK;AAC1B,WAAO,CAAC,EAAE,MAAM;AACd,aAAO,KAAK,EAAE,KAAK;AACnB,UAAI,MAAM,OAAO,KAAK;AAAA,IACxB;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,eAAe;AACnB,QAAI,IAAI,MAAM,KAAK,KAAK;AACxB,WAAO,CAAC,EAAE,MAAM;AACd,UAAI,MAAM,KAAK,KAAK;AAAA,IACtB;AAAA,EACF;AAAA,EACA,MAAM,aAAa,WAAW;AAC5B,QAAI,IAAI,MAAM,KAAK,KAAK;AACxB,QAAI,iBAAiB,UAAU,EAAE,KAAK;AACtC,WAAO,CAAC,EAAE,QAAQ,gBAAgB;AAChC,UAAI,MAAM,KAAK,KAAK;AACpB,uBAAiB,UAAU,EAAE,KAAK;AAAA,IACpC;AAAA,EACF;AAAA,EACA,aAAa,SAAS;AACpB,WAAO,IAAI,0BAA0B,MAAM,OAAO;AAAA,EACpD;AAAA,EACA,OAAO,WAAW;AAChB,WAAO,IAAI,eAAe,MAAM,SAAS;AAAA,EAC3C;AAAA,EACA,IAAI,YAAY;AACd,WAAO,IAAI,YAAY,MAAM,UAAU;AAAA,EACzC;AAAA,EACA,SAAS,YAAY;AACnB,WAAO,IAAI,iBAAiB,MAAM,UAAU;AAAA,EAC9C;AAAA,EACA,eAAe,YAAY;AACzB,WAAO,IAAI,iBAAiB,MAAM,UAAU,EAAE,OAAO;AAAA,EACvD;AAAA,EACA,QAAQ,YAAY;AAClB,WAAO,IAAI,gBAAgB,MAAM,UAAU;AAAA,EAC7C;AAAA,EACA,MAAM,aAAa,GAAG;AACpB,WAAO,KAAK,IAAI,CAAC,EAAE,aAAa;AAAA,EAClC;AAAA,EACA,MAAM,cAAc,GAAG;AACrB,WAAO,KAAK,eAAe,CAAC,EAAE,aAAa,CAAC,MAAM,MAAM,IAAI;AAAA,EAC9D;AAAA,EACA,cAAc,WAAW,iBAAiB,MAAM;AAC9C,WAAO,IAAI,sBAAsB,MAAM,WAAW,cAAc;AAAA,EAClE;AAAA,EACA,iBAAiB,WAAW,iBAAiB,MAAM,QAAQ,WAAW;AACpE,UAAM,aAAa,KAAK,cAAc,WAAW,cAAc;AAC/D,WAAO,WAAW,IAAI,CAAC,MAAM,QAAQ,GAAG,KAAK,CAAC;AAAA,EAChD;AAAA,EACA,YAAY,UAAU,kBAAkB;AACtC,WAAO,IAAI,gBAAgB,kBAAkB,CAAC,MAAM,QAAQ,CAAC,GAAG,gBAAgB;AAAA,EAClF;AAAA,EACA,KAAKF,SAAQ;AACX,QAAIA,UAAS,KAAKA,WAAU,MAAM;AAChC,aAAO;AAAA,IACT;AACA,WAAO,IAAI,aAAa,MAAMA,OAAM;AAAA,EACtC;AAAA,EACA,KAAKA,SAAQ;AACX,QAAIA,UAAS,KAAKA,WAAU,MAAM;AAChC,aAAO;AAAA,IACT;AACA,WAAO,IAAI,aAAa,MAAMA,OAAM;AAAA,EACtC;AAAA,EACA,SAAS,YAAY;AACnB,WAAO,IAAI,iBAAiB,MAAM,UAAU;AAAA,EAC9C;AAAA,EACA,QAAQ,YAAY,MAAM;AACxB,WAAO,IAAI,gBAAgB,MAAM,YAAY,IAAI;AAAA,EACnD;AAAA,EACA,SAAS;AACP,WAAO,IAAI,eAAe,IAAI;AAAA,EAChC;AACF;AACA,IAAI,gBAAgB,cAAc,aAAa;AAAA,EAC7C,YAAY,OAAO;AACjB,UAAM;AACN,SAAK,QAAQ;AACb,SAAK,OAAO;AAAA,EACd;AAAA,EACA,UAAU;AACR,WAAO,YAAY,KAAK,MAAM;AAAA,EAChC;AAAA,EACA,MAAM,OAAO;AACX,QAAI,KAAK,QAAQ,KAAK,MAAM,QAAQ;AAClC,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,UAAM,OAAO,KAAK,MAAM,KAAK;AAC7B,SAAK;AACL,WAAO,EAAE,OAAO,UAAU,IAAI,GAAG,MAAM,MAAM;AAAA,EAC/C;AACF;AACA,IAAI,uBAAuB,cAAc,aAAa;AAAA,EACpD,YAAY,QAAQ;AAClB,UAAM;AACN,SAAK,SAAS;AAAA,EAChB;AAAA,EACA,UAAU;AACR,WAAO;AAAA,EACT;AAAA,EACA,MAAM,OAAO;AACX,QAAI;AACF,aAAO,KAAK,OAAO;AAAA,IACrB,SAAS,IAAP;AACA,SAAG,UAAU,mDAAmD,GAAG;AACnE,YAAM;AAAA,IACR;AAAA,EACF;AACF;AACA,IAAI,iBAAiB,cAAc,aAAa;AAAA,EAC9C,YAAY,UAAU;AACpB,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,WAAW,QAAQ,QAAQ,EAAE,OAAO,MAAM,MAAM,MAAM,CAAC;AAAA,EAC9D;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,SAAS,KAAK,MAAM,KAAK,WAAW,CAAC;AAC1D,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,KAAK,SAAS,KAAK;AAAA,EAC5B;AACF;AACA,IAAI,eAAe,cAAc,aAAa;AAAA,EAC5C,YAAY,UAAU,UAAU;AAC9B,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,WAAW;AAChB,SAAK,QAAQ;AACb,SAAK,WAAW,QAAQ,QAAQ,EAAE,OAAO,MAAM,MAAM,MAAM,CAAC;AAAA,EAC9D;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,SAAS,KAAK,MAAM,KAAK,WAAW,CAAC;AAC1D,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,KAAK,UAAU,KAAK,UAAU;AACnC,YAAM4B,YAAU,MAAM,KAAK,SAAS,KAAK;AACzC,UAAIA,UAAQ,MAAM;AAChB,eAAOA;AAAA,MACT;AACA,cAAQA,UAAQ,KAAK;AAAA,IACvB;AACA,WAAO,KAAK,SAAS,KAAK;AAAA,EAC5B;AACF;AACA,IAAI,eAAe,cAAc,aAAa;AAAA,EAC5C,YAAY,UAAU,UAAU;AAC9B,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,WAAW;AAChB,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,QAAI,KAAK,WAAW,KAAK,UAAU;AACjC,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,WAAO,KAAK,SAAS,KAAK;AAAA,EAC5B;AACF;AACA,IAAI,wBAAwB,cAAc,aAAa;AAAA,EACrD,YAAY,UAAU,WAAW,uBAAuB,MAAM;AAC5D,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,YAAY;AACjB,SAAK,uBAAuB;AAC5B,SAAK,WAAW,QAAQ,QAAQ,EAAE,OAAO,MAAM,MAAM,MAAM,CAAC;AAAA,EAC9D;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,SAAS,KAAK,MAAM,KAAK,WAAW,CAAC;AAC1D,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,aAAa;AACjB,UAAM,QAAQ,CAAC;AACf,WAAO,MAAM,SAAS,KAAK,WAAW;AACpC,YAAM,OAAO,MAAM,KAAK,SAAS,KAAK;AACtC,UAAI,KAAK,MAAM;AACb,YAAI,KAAK,wBAAwB,MAAM,SAAS,GAAG;AACjD,iBAAO,EAAE,OAAO,OAAO,MAAM,MAAM;AAAA,QACrC;AACA,eAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,MACnC;AACA,YAAM,KAAK,KAAK,KAAK;AAAA,IACvB;AACA,WAAO,EAAE,OAAO,OAAO,MAAM,MAAM;AAAA,EACrC;AACF;AACA,IAAI,iBAAiB,cAAc,aAAa;AAAA,EAC9C,YAAY,UAAU,WAAW;AAC/B,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,YAAY;AACjB,SAAK,WAAW,QAAQ,QAAQ,EAAE,OAAO,MAAM,MAAM,MAAM,CAAC;AAAA,EAC9D;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,SAAS,KAAK,MAAM,KAAK,WAAW,CAAC;AAC1D,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,MAAM;AACX,YAAM,OAAO,MAAM,KAAK,SAAS,KAAK;AACtC,UAAI,KAAK,QAAQ,KAAK,UAAU,KAAK,KAAK,GAAG;AAC3C,eAAO;AAAA,MACT;AACA,cAAQ,KAAK,KAAK;AAAA,IACpB;AAAA,EACF;AACF;AACA,IAAI,cAAc,cAAc,aAAa;AAAA,EAC3C,YAAY,UAAU,YAAY;AAChC,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,UAAM,OAAO,MAAM,KAAK,SAAS,KAAK;AACtC,QAAI,KAAK,MAAM;AACb,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,UAAM,eAAe,oBAAoB,sBAAsB,KAAK,KAAK;AACzE,UAAM,SAAS,KAAK,UAAU,KAAK,KAAK;AACxC,UAAM,gBAAgB,oBAAoB,sBAAsB,MAAM;AACtE,eAAW,MAAM,cAAc;AAC7B,UAAI,CAAC,oBAAoB,eAAe,IAAI,aAAa,GAAG;AAC1D,WAAG,QAAQ;AAAA,MACb;AAAA,IACF;AACA,WAAO,EAAE,OAAO,QAAQ,MAAM,MAAM;AAAA,EACtC;AACF;AACA,IAAI,4BAA4B,cAAc,aAAa;AAAA,EACzD,YAAY,UAAU,SAAS;AAC7B,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,UAAU;AACf,SAAK,QAAQ;AACb,SAAK,WAAW,QAAQ,QAAQ,EAAE,OAAO,MAAM,MAAM,MAAM,CAAC;AAAA,EAC9D;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,SAAS,KAAK,MAAM,KAAK,WAAW,CAAC;AAC1D,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,MAAM;AACX,UAAI;AACF,eAAO,MAAM,KAAK,SAAS,KAAK;AAAA,MAClC,SAAS,IAAP;AACA,YAAI,CAAC,KAAK,QAAQ,EAAE,GAAG;AACrB,iBAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,QACnC;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACF;AACA,IAAI,mBAAmB,cAAc,aAAa;AAAA,EAChD,YAAY,UAAU,YAAY;AAChC,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,UAAM,OAAO,MAAM,KAAK,SAAS,KAAK;AACtC,QAAI,KAAK,MAAM;AACb,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,UAAM,eAAe,oBAAoB,sBAAsB,KAAK,KAAK;AACzE,UAAM,SAAS,MAAM,KAAK,UAAU,KAAK,KAAK;AAC9C,UAAM,gBAAgB,oBAAoB,sBAAsB,MAAM;AACtE,eAAW,MAAM,cAAc;AAC7B,UAAI,CAAC,oBAAoB,eAAe,IAAI,aAAa,GAAG;AAC1D,WAAG,QAAQ;AAAA,MACb;AAAA,IACF;AACA,WAAO,EAAE,OAAO,QAAQ,MAAM,MAAM;AAAA,EACtC;AACF;AACA,IAAI,oBAAoB,cAAc,aAAa;AAAA,EACjD,cAAc;AACZ,UAAM;AACN,SAAK,cAAc,IAAI,kBAAkB;AACzC,SAAK,WAAW,QAAQ,QAAQ,EAAE,OAAO,MAAM,MAAM,MAAM,CAAC;AAAA,EAC9D;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,SAAS,KAAK,MAAM,KAAK,WAAW,CAAC;AAC1D,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,aAAa;AACjB,WAAO,KAAK,YAAY,OAAO,MAAM,GAAG;AACtC,UAAI,CAAC,MAAM,KAAK,KAAK,GAAG;AACtB,eAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,MACnC;AAAA,IACF;AACA,WAAO,EAAE,OAAO,KAAK,YAAY,MAAM,GAAG,MAAM,MAAM;AAAA,EACxD;AACF;AACA,IAAI,kBAAkB,cAAc,kBAAkB;AAAA,EACpD,YAAY,UAAU,YAAY;AAChC,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,UAAM,OAAO,MAAM,KAAK,SAAS,KAAK;AACtC,QAAI,KAAK,MAAM;AACb,aAAO;AAAA,IACT;AACA,UAAM,eAAe,oBAAoB,sBAAsB,KAAK,KAAK;AACzE,UAAM,cAAc,KAAK,UAAU,KAAK,KAAK;AAC7C,UAAM,gBAAgB,oBAAoB,sBAAsB,WAAW;AAC3E,SAAK,YAAY,QAAQ,WAAW;AACpC,eAAW,MAAM,cAAc;AAC7B,UAAI,CAAC,oBAAoB,eAAe,IAAI,aAAa,GAAG;AAC1D,WAAG,QAAQ;AAAA,MACb;AAAA,IACF;AACA,WAAO;AAAA,EACT;AACF;AACA,IAAI,kBAAkB,cAAc,aAAa;AAAA,EAC/C,YAAY,WAAW,kBAAkB;AACvC,UAAM;AACN,SAAK,mBAAmB;AACxB,SAAK,WAAW;AAChB,SAAK,WAAW;AAChB,SAAK,gBAAgB;AAAA,EACvB;AAAA,EACA,UAAU;AACR,UAAM,oBAAoB;AAC1B,WAAO,GAAG;AAAA,EACZ;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,cAAc,KAAK,QAAQ;AAChD,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,cAAc,UAAU;AAC5B,UAAM;AACN,QAAI,KAAK,YAAY,MAAM;AACzB,YAAM,iBAAiB,MAAM,KAAK,cAAc,KAAK;AACrD,UAAI,eAAe,MAAM;AACvB,eAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,MACnC;AACA,WAAK,WAAW,eAAe;AAC/B,UAAI,KAAK,oBAAoB,MAAM;AACjC,aAAK,WAAW,KAAK,SAAS,aAAa,KAAK,gBAAgB;AAAA,MAClE;AAAA,IACF;AACA,UAAM,aAAa,MAAM,KAAK,SAAS,KAAK;AAC5C,QAAI,WAAW,MAAM;AACnB,WAAK,WAAW;AAChB,aAAO,KAAK,cAAc,QAAQ;AAAA,IACpC;AACA,WAAO;AAAA,EACT;AACF;AACA,IAAI;AAAA,CACH,SAAS,kBAAkB;AAC1B,mBAAiB,iBAAiB,UAAU,KAAK;AACjD,mBAAiB,iBAAiB,cAAc,KAAK;AACrD,mBAAiB,iBAAiB,aAAa,KAAK;AACtD,GAAG,oBAAoB,kBAAkB,CAAC,EAAE;AAC5C,IAAI,cAAc,cAAc,aAAa;AAAA,EAC3C,YAAY,WAAW,eAAe,gBAAgB,MAAM;AAC1D,UAAM;AACN,SAAK,YAAY;AACjB,SAAK,eAAe;AACpB,SAAK,QAAQ;AACb,SAAK,iBAAiB;AAAA,EACxB;AAAA,EACA,UAAU;AACR,UAAM,oBAAoB;AAC1B,WAAO,IAAI;AAAA,EACb;AAAA,EACA,MAAM,UAAU,YAAY;AAC1B,UAAM;AACN,QAAI,eAAe;AACnB,QAAI,gBAAgB;AACpB,aAAS,QAAQ,WAAW;AAC1B,UAAI,qBAAqB,cAAc;AACrC,cAAM,SAAS,UAAU,KAAK;AAC9B,eAAO;AAAA,UACL,OAAO,OAAO,KAAK,CAAC,MAAM;AACxB;AACA,gBAAI,EAAE,MAAM;AACV;AAAA,YACF;AACA,mBAAO,EAAE;AAAA,UACX,CAAC;AAAA,UACD,SAAS;AAAA,QACX;AAAA,MACF,OAAO;AACL,eAAO,EAAE,OAAO,MAAM,SAAS,KAAK;AAAA,MACtC;AAAA,IACF;AACA,UAAM,SAAS,MAAM,mBAAmB,KAAK,WAAW,OAAO;AAC/D,QAAI,iBAAiB,eAAe;AAClC,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,QAAI,gBAAgB,GAAG;AACrB,cAAQ,KAAK;AAAA,aACN,gBAAgB;AACnB,gBAAM,IAAI,MAAM,qEAAqE,KAAK,QAAQ;AAAA,aAC/F,gBAAgB;AACnB,iBAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,aAC9B,gBAAgB;AAAA;AAAA;AAAA,IAGzB;AACA,SAAK;AACL,WAAO,EAAE,OAAO,QAAQ,MAAM,MAAM;AAAA,EACtC;AAAA,EACA,MAAM,OAAO;AACX,SAAK,iBAAiB,KAAK,UAAU,KAAK,cAAc;AACxD,WAAO,KAAK;AAAA,EACd;AACF;AACA,IAAI,mBAAmB,cAAc,aAAa;AAAA,EAChD,YAAY,UAAU,YAAY;AAChC,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,aAAa;AAClB,SAAK,SAAS,IAAI,WAAW,UAAU;AAAA,EACzC;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,SAAS;AACP,WAAO,CAAC,KAAK,OAAO,OAAO,GAAG;AAC5B,YAAM,IAAI,KAAK,SAAS,KAAK;AAC7B,WAAK,OAAO,KAAK,CAAC;AAAA,IACpB;AAAA,EACF;AAAA,EACA,OAAO;AACL,SAAK,OAAO;AACZ,WAAO,KAAK,OAAO,MAAM;AAAA,EAC3B;AACF;AACA,IAAI,kBAAkB,cAAc,iBAAiB;AAAA,EACnD,YAAY,UAAU,YAAY,MAAM;AACtC,UAAM,UAAU,UAAU;AAC1B,SAAK,WAAW;AAChB,SAAK,aAAa;AAClB,SAAK,oBAAoB;AACzB,SAAK,SAAS,YAAY,KAAK,QAAQ,aAAa,IAAI,EAAE,SAAS,CAAC;AACpE,SAAK,WAAW,QAAQ,QAAQ,EAAE,OAAO,MAAM,MAAM,MAAM,CAAC;AAAA,EAC9D;AAAA,EACA,MAAM,OAAO;AACX,SAAK,WAAW,KAAK,SAAS,KAAK,MAAM,KAAK,WAAW,CAAC;AAC1D,WAAO,KAAK;AAAA,EACd;AAAA,EACA,UAAU,MAAM;AACd,WAAO,KAAK,MAAM,KAAK,OAAO,IAAI,IAAI;AAAA,EACxC;AAAA,EACA,cAAc;AACZ,WAAO,KAAK,UAAU,KAAK,OAAO,OAAO,CAAC;AAAA,EAC5C;AAAA,EACA,MAAM,aAAa;AACjB,QAAI,CAAC,KAAK,mBAAmB;AAC3B,WAAK,OAAO;AAAA,IACd;AACA,WAAO,CAAC,KAAK,OAAO,QAAQ,GAAG;AAC7B,YAAM,cAAc,KAAK,YAAY;AACrC,YAAM,SAAS,MAAM,KAAK,OAAO,cAAc,WAAW;AAC1D,UAAI,OAAO,MAAM;AACf,aAAK,oBAAoB;AAAA,MAC3B,OAAO;AACL,aAAK,OAAO;AACZ,eAAO;AAAA,MACT;AAAA,IACF;AACA,WAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,EACnC;AACF;AAGA,IAAI,UAAU,MAAM;AAAA,EAClB,cAAc;AACZ,SAAK,OAAO;AAAA,EACd;AAAA,EACA,MAAM,WAAW,iBAAiB,MAAM;AACtC,UAAM,OAAO;AACb,iBAAa,OAAO,YAAY,GAAG,MAAM;AAAA,QACrC,WAAW;AACf,QAAInC;AACJ,QAAI,KAAK,SAAS,YAAY,KAAK,QAAQ,MAAM;AAC/C,MAAAA,QAAO,KAAK;AAAA,IACd,WAAW,gBAAgB;AACzB,MAAAA,QAAO,KAAK,KAAK,KAAK,OAAO,SAAS;AAAA,IACxC,OAAO;AACL,MAAAA,QAAO,KAAK,MAAM,KAAK,OAAO,SAAS;AAAA,IACzC;AACA,WAAO,sBAAsB,YAAY;AACvC,cAAQ,MAAM,KAAK,SAAS,GAAG,iBAAiB,WAAW,gBAAgB,eAAe;AAAA,IAC5F,GAAGA,KAAI;AAAA,EACT;AAAA,EACA,YAAY,SAAS;AACnB,UAAM,OAAO;AACb,QAAIA;AACJ,QAAI,KAAK,SAAS,YAAY,QAAQ,SAAS,UAAU;AACvD,MAAAA,QAAO;AAAA,IACT,WAAW,KAAK,QAAQ,QAAQ,QAAQ,QAAQ,MAAM;AACpD,MAAAA,QAAO,KAAK,OAAO,QAAQ;AAAA,IAC7B,OAAO;AACL,MAAAA,QAAO;AAAA,IACT;AACA,WAAO,sBAAsB,aAAa,MAAM,KAAK,SAAS,GAAG,YAAY,MAAM,QAAQ,SAAS,CAAC,GAAGA,KAAI;AAAA,EAC9G;AAAA,EACA,OAAO,WAAW;AAChB,UAAM,OAAO;AACb,QAAIA;AACJ,QAAI,KAAK,SAAS,UAAU;AAC1B,MAAAA,QAAO;AAAA,IACT,OAAO;AACL,MAAAA,QAAO;AAAA,IACT;AACA,WAAO,sBAAsB,YAAY;AACvC,cAAQ,MAAM,KAAK,SAAS,GAAG,OAAO,CAAC,MAAM,KAAK,MAAM,UAAU,CAAC,CAAC,CAAC;AAAA,IACvE,GAAGA,KAAI;AAAA,EACT;AAAA,EACA,MAAM,aAAa,GAAG;AACpB,YAAQ,MAAM,KAAK,SAAS,GAAG,aAAa,CAAC;AAAA,EAC/C;AAAA,EACA,IAAI,YAAY;AACd,UAAM,OAAO;AACb,WAAO,sBAAsB,YAAY;AACvC,cAAQ,MAAM,KAAK,SAAS,GAAG,IAAI,CAAC,MAAM,KAAK,MAAM,WAAW,CAAC,CAAC,CAAC;AAAA,IACrE,GAAG,KAAK,IAAI;AAAA,EACd;AAAA,EACA,SAAS,YAAY;AACnB,UAAM,OAAO;AACb,WAAO,sBAAsB,YAAY;AACvC,cAAQ,MAAM,KAAK,SAAS,GAAG,SAAS,UAAU;AAAA,IACpD,GAAG,KAAK,IAAI;AAAA,EACd;AAAA,EACA,SAAS,YAAY;AACnB,QAAI,cAAc,MAAM;AACtB,YAAM,IAAI,WAAW,2DAA2D;AAAA,IAClF;AACA,UAAM,OAAO;AACb,WAAO,sBAAsB,aAAa,MAAM,KAAK,SAAS,GAAG,SAAS,UAAU,GAAG,KAAK,IAAI;AAAA,EAClG;AAAA,EACA,OAAOO,SAAQ;AACb,UAAM,OAAO;AACb,QAAIP;AACJ,QAAI,KAAK,QAAQ,QAAQO,UAAS,GAAG;AACnC,MAAAP,QAAO,KAAK,OAAOO;AAAA,IACrB,WAAWA,YAAW,GAAG;AACvB,MAAAP,QAAO;AAAA,IACT,WAAW,KAAK,QAAQ,SAASO,YAAW,UAAUA,UAAS,IAAI;AACjE,MAAAP,QAAO;AAAA,IACT,OAAO;AACL,MAAAA,QAAO;AAAA,IACT;AACA,WAAO,sBAAsB,YAAY;AACvC,YAAM,mBAAmB,qBAAqB,aAAa,EAAE,OAAO,MAAM,KAAK,SAAS,GAAG,MAAM,MAAM,EAAE;AACzG,aAAO,yBAAyB,iBAAiB,KAAKO,OAAM,CAAC;AAAA,IAC/D,GAAGP,KAAI;AAAA,EACT;AAAA,EACA,KAAKO,SAAQ;AACX,UAAM,OAAO;AACb,QAAIP;AACJ,QAAI,KAAK,QAAQ,QAAQO,WAAU,KAAK,KAAK,QAAQA,SAAQ;AAC3D,MAAAP,QAAO,KAAK,OAAOO;AAAA,IACrB,WAAW,KAAK,QAAQ,SAAS,KAAK,OAAOA,WAAUA,YAAW,UAAUA,UAAS,IAAI;AACvF,MAAAP,QAAO;AAAA,IACT,OAAO;AACL,MAAAA,QAAO;AAAA,IACT;AACA,WAAO,sBAAsB,aAAa,MAAM,KAAK,SAAS,GAAG,KAAKO,OAAM,GAAGP,KAAI;AAAA,EACrF;AAAA,EACA,QAAQ,YAAY,MAAM,yBAAyB,MAAM;AACvD,QAAI,cAAc,QAAQ,aAAa,GAAG;AACxC,UAAI,KAAK,QAAQ,MAAM;AACrB,cAAM,IAAI,WAAW,0DAA0D;AAAA,MACjF,OAAO;AACL,cAAM,IAAI,WAAW,mNAAmN,KAAK,gBAAgB;AAAA,MAC/P;AAAA,IACF;AACA,UAAM,OAAO;AACb,UAAM,SAAS,YAAY,KAAK,QAAQ,aAAa,IAAI,EAAE,SAAS,CAAC;AACrE,WAAO,sBAAsB,YAAY;AACvC,UAAI,QAAQ,OAAO,MAAM;AACzB,UAAI,wBAAwB;AAC1B,iBAAS,OAAO,MAAM;AAAA,MACxB;AACA,cAAQ,MAAM,KAAK,SAAS,GAAG,QAAQ,YAAY,MAAM,SAAS,CAAC;AAAA,IACrE,GAAG,KAAK,IAAI;AAAA,EACd;AAAA,EACA,KAAKO,SAAQ;AACX,UAAM,OAAO;AACb,QAAIP;AACJ,QAAI,KAAK,QAAQ,QAAQ,KAAK,OAAOO,SAAQ;AAC3C,MAAAP,QAAOO;AAAA,IACT,WAAW,KAAK,QAAQ,QAAQ,KAAK,QAAQA,SAAQ;AACnD,MAAAP,QAAO,KAAK;AAAA,IACd,OAAO;AACL,MAAAA,QAAO;AAAA,IACT;AACA,WAAO,sBAAsB,aAAa,MAAM,KAAK,SAAS,GAAG,KAAKO,OAAM,GAAGP,KAAI;AAAA,EACrF;AAAA,EACA,MAAM,UAAU;AACd,QAAI,KAAK,SAAS,UAAU;AAC1B,YAAM,IAAI,MAAM,gDAAgD;AAAA,IAClE;AACA,YAAQ,MAAM,KAAK,SAAS,GAAG,QAAQ;AAAA,EACzC;AAAA,EACA,MAAM,iBAAiB;AACrB,QAAI,KAAK,SAAS,UAAU;AAC1B,YAAM,IAAI,MAAM,gDAAgD;AAAA,IAClE;AACA,YAAQ,MAAM,KAAK,SAAS,GAAG,eAAe;AAAA,EAChD;AACF;AACA,QAAQ,kBAAkB;AAC1B,SAAS,sBAAsB,YAAYA,QAAO,MAAM;AACtD,SAAO,IAAI,cAAc,QAAQ;AAAA,IAC/B,cAAc;AACZ,YAAM,GAAG,SAAS;AAClB,WAAK,OAAOA;AAAA,IACd;AAAA,IACA,MAAM,WAAW;AACf,aAAO,WAAW;AAAA,IACpB;AAAA,EACF,EAAE;AACJ;AACA,SAAS,MAAM,OAAO;AACpB,SAAO,sBAAsB,YAAY,kBAAkB,KAAK,GAAG,MAAM,MAAM;AACjF;AACA,SAAS,IAAI,UAAU;AACrB,MAAI,CAAC,YAAY,QAAQ,GAAG;AAC1B,UAAM,IAAI,MAAM,mDAAmD;AAAA,EACrE;AACA,MAAIA;AACJ,MAAI,MAAM,QAAQ,QAAQ,GAAG;AAC3B,aAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,MAAAA,QAAOA,SAAQ,OAAO,SAAS,IAAI,OAAO,KAAK,IAAIA,OAAM,SAAS,IAAI,IAAI;AAAA,IAC5E;AAAA,EACF,WAAW,oBAAoB,QAAQ;AACrC,eAAW,MAAM,UAAU;AACzB,MAAAA,QAAOA,SAAQ,OAAO,SAAS,IAAI,OAAO,KAAK,IAAIA,OAAM,SAAS,IAAI,IAAI;AAAA,IAC5E;AAAA,EACF;AACA,SAAO,sBAAsB,YAAY;AACvC,UAAM,UAAU,MAAM,mBAAmB,UAAU,CAAC,MAAM;AACxD,UAAI,aAAa,SAAS;AACxB,eAAO,EAAE,OAAO,EAAE,SAAS,GAAG,SAAS,MAAM;AAAA,MAC/C,WAAW,YAAY,CAAC,GAAG;AACzB,eAAO,EAAE,OAAO,MAAM,SAAS,KAAK;AAAA,MACtC,OAAO;AACL,cAAM,IAAI,MAAM,2EAA2E;AAAA,MAC7F;AAAA,IACF,CAAC;AACD,WAAO,mBAAmB,SAAS,gBAAgB,QAAQ;AAAA,EAC7D,GAAGA,KAAI;AACT;AACA,SAAS,gBAAgB,MAAM;AAC7B,MAAI,SAAS,MAAM;AACjB,WAAO;AAAA,EACT;AACA,QAAM,aAAa,KAAK;AACxB,MAAI,aAAa,UAAU,GAAG;AAC5B,UAAM,QAAQ,YAAY,IAAI;AAC9B,WAAO,EAAE,OAAO,SAAS,MAAM;AAAA,EACjC;AACA,SAAO,EAAE,OAAO,MAAM,SAAS,KAAK;AACtC;AACA,SAAS,YAAY,QAAQ;AAC3B,MAAI,OAAO,WAAW,GAAG;AACvB,UAAM,IAAI,MAAM,sCAAsC;AAAA,EACxD;AACA,MAAI,OAAO,cAAc,QAAQ;AAC/B,WAAO,MAAM,MAAM;AAAA,EACrB,OAAO;AACL,WAAO,OAAO,MAAM;AAAA,EACtB;AACF;AAGA,IAAI,kBAAkB,cAAc,QAAQ;AAAA,EAC1C,YAAY,QAAQ;AAClB,UAAM;AACN,SAAK,QAAQ;AAAA,EACf;AAAA,EACA,MAAM,WAAW;AACf,UAAM,gBAAgB,MAAM,KAAK,MAAM,SAAS;AAChD,UAAM,eAAe,cAAc,WAAW;AAC9C,UAAM,eAAe,aAAa,MAAM,IAAI,EAAE,IAAI,CAAC,SAAS;AAC1D,UAAI,KAAK,SAAS,IAAI,GAAG;AACvB,eAAO,KAAK,MAAM,GAAG,EAAE;AAAA,MACzB;AACA,aAAO;AAAA,IACT,CAAC;AACD,WAAO;AAAA,EACT;AACF;AAGA,IAAI,aAAa;AACjB,IAAI,YAAY,OAAO,KAAK;AAC5B,IAAI,cAAc,OAAO,OAAO;AAChC,IAAI,cAAc,OAAO,OAAO;AAChC,IAAI,0BAA0B,OAAO,iBAAiB;AACtD,IAAI,8BAA8B,OAAO,cAAc;AACvD,IAAI,aAAa,cAAc,QAAQ;AAAA,EACrC,YAAY,QAAQ,WAAW;AAC7B,UAAM;AACN,SAAK,QAAQ;AACb,SAAK,YAAY;AACjB,SAAK,kBAAkB;AACvB,SAAK,uBAAuB;AAC5B,SAAK,gBAAgB;AACrB,SAAK,wBAAwB;AAC7B,SAAK,YAAY;AACjB,SAAK,kBAAkB;AACvB,SAAK,OAAO,IAAI,gBAAgB,MAAM;AACtC,QAAI,CAAC,WAAW;AACd,kBAAY,CAAC;AAAA,IACf;AACA,SAAK,YAAY,UAAU,cAAc,QAAQ,QAAQ;AACzD,SAAK,kBAAkB,UAAU;AACjC,SAAK,gBAAgB,UAAU;AAC/B,SAAK,wBAAwB,UAAU;AACvC,QAAI,UAAU,iBAAiB;AAC7B,mBAAa,OAAO,UAAU,aAAa,MAAM,MAAM,gEAAgE;AACvH,WAAK,kBAAkB;AACvB,WAAK,YAAY;AAAA,IACnB,OAAO;AACL,WAAK,YAAY,UAAU,YAAY,UAAU,YAAY;AAAA,IAC/D;AAAA,EACF;AAAA,EACA,MAAM,cAAc;AAClB,QAAI,CAAC,KAAK,sBAAsB;AAC9B,YAAM,KAAK,eAAe;AAAA,IAC5B;AACA,WAAO,KAAK,wBAAwB,OAAO,KAAK,KAAK,aAAa,IAAI,KAAK;AAAA,EAC7E;AAAA,EACA,MAAM,iBAAiB;AACrB,UAAM,sBAAsB,MAAM,KAAK,oBAAoB;AAC3D,QAAI,CAAC,KAAK,mBAAmB,CAAC,qBAAqB;AACjD,YAAM,IAAI,MAAM,2DAA2D;AAAA,IAC7E,WAAW,KAAK,mBAAmB,qBAAqB;AACtD,mBAAa,OAAO,oBAAoB,WAAW,KAAK,gBAAgB,QAAQ,MAAM,yCAAyC,KAAK,gBAAgB,OAAO,SAAS,IAAI,oEAAoE,oBAAoB,OAAO,SAAS,IAAI,IAAI;AAAA,IAC1R;AACA,QAAI,CAAC,KAAK,iBAAiB;AACzB,WAAK,kBAAkB;AAAA,IACzB;AACA,UAAM,SAAS,KAAK,gBAAgB,OAAO,CAAC,UAAU,SAAS;AAC7D,eAAS,QAAQ,SAAS,QAAQ,KAAK;AACvC,aAAO;AAAA,IACT,GAAG,CAAC,CAAC;AACL,UAAM,iBAAiB,OAAO,KAAK,MAAM,EAAE,OAAO,CAAC,SAAS,OAAO,QAAQ,CAAC;AAC5E,iBAAa,OAAO,eAAe,WAAW,GAAG,MAAM,mCAAmC,eAAe,SAAS,CAAC;AACnH,QAAI,KAAK,eAAe;AACtB,iBAAW,OAAO,OAAO,KAAK,KAAK,aAAa,GAAG;AACjD,cAAMS,SAAQ,KAAK,gBAAgB,QAAQ,GAAG;AAC9C,YAAIA,WAAU,IAAI;AAChB,gBAAM,IAAI,MAAM,cAAc,MAAM,yEAAyE,KAAK,gBAAgB,SAAS,IAAI,IAAI;AAAA,QACrJ;AAAA,MACF;AAAA,IACF;AACA,SAAK,uBAAuB;AAAA,EAC9B;AAAA,EACA,MAAM,sBAAsB;AAC1B,QAAI,KAAK,WAAW;AAClB,YAAM,OAAO,MAAM,KAAK,KAAK,SAAS;AACtC,YAAM,eAAe,MAAM,KAAK,KAAK;AACrC,UAAI,aAAa,MAAM;AACrB,cAAM,IAAI,MAAM,oCAAoC;AAAA,MACtD;AACA,YAAM,YAAY,aAAa;AAC/B,YAAM,UAAU,KAAK,SAAS,WAAW,KAAK;AAC9C,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,MAAM,WAAW;AACf,QAAI,CAAC,KAAK,sBAAsB;AAC9B,YAAM,KAAK,eAAe;AAAA,IAC5B;AACA,QAAIQ,SAAQ,MAAM,KAAK,KAAK,SAAS;AACrC,QAAI,KAAK,WAAW;AAClB,MAAAA,SAAQA,OAAM,KAAK,CAAC;AAAA,IACtB;AACA,WAAOA,OAAM,IAAI,CAAC,MAAM,KAAK,gBAAgB,CAAC,CAAC;AAAA,EACjD;AAAA,EACA,gBAAgB,MAAM;AACpB,UAAM,SAAS,KAAK,SAAS,IAAI;AACjC,UAAM,WAAW,CAAC;AAClB,UAAME,UAAS,CAAC;AAChB,aAAS,KAAK,GAAG,KAAK,KAAK,gBAAgB,QAAQ,MAAM;AACvD,YAAM,MAAM,KAAK,gBAAgB;AACjC,YAAML,UAAS,KAAK,gBAAgB,KAAK,cAAc,OAAO;AAC9D,UAAI,KAAK,yBAAyB,CAACA,SAAQ;AACzC;AAAA,MACF,OAAO;AACL,cAAM,QAAQ,OAAO;AACrB,YAAI,cAAc;AAClB,YAAI,UAAU,IAAI;AAChB,cAAIA,WAAUA,QAAO,YAAY,QAAQ;AACvC,0BAAcA,QAAO;AAAA,UACvB,WAAWA,YAAWA,QAAO,YAAYA,QAAO,UAAU;AACxD,kBAAM,IAAI,MAAM,mBAAmB,8BAA8B,MAAM;AAAA,UACzE,OAAO;AACL,0BAAc;AAAA,UAChB;AAAA,QACF,OAAO;AACL,gBAAM,aAAa,OAAO,KAAK;AAC/B,cAAI,MAAM,UAAU,GAAG;AACrB,gBAAIA,WAAUA,QAAO,UAAU,QAAQ;AACrC,4BAAc,KAAK,WAAW,KAAK;AAAA,YACrC,OAAO;AACL,4BAAc;AAAA,YAChB;AAAA,UACF,WAAW,CAACA,WAAU,CAACA,QAAO,OAAO;AACnC,0BAAc;AAAA,UAChB,OAAO;AACL,oBAAQA,QAAO;AAAA,mBACR;AACH,8BAAc;AACd;AAAA,mBACG;AACH,8BAAc,KAAK,MAAM,UAAU;AACnC;AAAA,mBACG;AACH,8BAAc,KAAK,WAAW,KAAK;AACnC;AAAA;AAEA,8BAAc;AAAA;AAAA,UAEpB;AAAA,QACF;AACA,QAAAA,WAAUA,QAAO,UAAUK,QAAO,OAAO,cAAc,SAAS,OAAO;AAAA,MACzE;AAAA,IACF;AACA,QAAI,OAAO,KAAKA,OAAM,EAAE,WAAW,GAAG;AACpC,aAAO;AAAA,IACT,OAAO;AACL,aAAO,EAAE,IAAI,UAAU,IAAIA,QAAO;AAAA,IACpC;AAAA,EACF;AAAA,EACA,WAAW,OAAO;AAChB,QAAI,UAAU,OAAO,MAAM,YAAY,MAAM,QAAQ;AACnD,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,SAAS,MAAM,uBAAuB,MAAM;AAC1C,UAAM,SAAS,CAAC;AAChB,QAAI,aAAa;AACjB,UAAM,aAAa,KAAK;AACxB,QAAI,eAAe;AACnB,aAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,cAAQ;AAAA,aACD;AACH,kBAAQ,KAAK,OAAO,EAAE;AAAA,iBACf;AACH,2BAAa,KAAK;AAClB,6BAAe;AACf;AAAA,iBACG,KAAK;AACR,2BAAa,KAAK;AAClB,kBAAI,KAAK,cAAc,OAAO,KAAK,iBAAiB;AAClD;AAAA,cACF;AACA,qBAAO,KAAK,EAAE;AACd,6BAAe;AACf;AAAA;AAEA,6BAAe;AACf,2BAAa;AACb;AAAA;AAEJ;AAAA,aACG;AACH,kBAAQ,KAAK,OAAO,EAAE;AAAA,iBACf,KAAK;AACR,qBAAO,KAAK,KAAK,UAAU,YAAY,EAAE,CAAC;AAC1C,6BAAe;AACf,2BAAa,KAAK;AAClB;AAAA;AAAA;AAGJ;AAAA,aACG;AACH,kBAAQ,KAAK,OAAO,EAAE;AAAA,iBACf;AACH,6BAAe;AACf;AAAA;AAAA;AAGJ;AAAA,aACG;AACH,kBAAQ,KAAK,OAAO,EAAE;AAAA,iBACf,KAAK;AACR,qBAAO,KAAK,KAAK,UAAU,YAAY,KAAK,CAAC,CAAC;AAC9C,6BAAe;AACf,2BAAa,KAAK;AAClB;AAAA,iBACG;AACH,6BAAe;AACf;AAAA;AAEA,6BAAe;AACf;AAAA;AAEJ;AAAA,aACG;AACH,kBAAQ,KAAK,OAAO,EAAE;AAAA,iBACf;AACH,6BAAe;AACf;AAAA;AAAA;AAGJ;AAAA;AAAA;AAAA,IAGN;AACA,QAAI,iBAAiB,yBAAyB;AAC5C,aAAO,KAAK,KAAK,UAAU,YAAY,aAAa,CAAC,CAAC;AAAA,IACxD,OAAO;AACL,aAAO,KAAK,KAAK,UAAU,UAAU,CAAC;AAAA,IACxC;AACA,QAAI,wBAAwB,OAAO,WAAW,KAAK,gBAAgB,QAAQ;AACzE,YAAM,IAAI,MAAM,wCAAwC,KAAK,gBAAgB,qCAAqC,QAAQ;AAAA,IAC5H;AACA,WAAO;AAAA,EACT;AACF;AAGA,IAAI,qBAAqB,cAAc,aAAa;AAAA,EAClD,YAAY,kBAAkB;AAC5B,UAAM;AACN,SAAK,mBAAmB;AACxB,SAAK,WAAW;AAChB,SAAK,UAAU,iBAAiB,WAAW;AAC3C,UAAM,cAAc,KAAK,KAAK,KAAK,OAAO;AAC1C,QAAI,KAAK,UAAU,KAAK,cAAc,KAAK,cAAc,MAAM,CAAC,OAAO,UAAU,WAAW,GAAG;AAC7F,YAAM,IAAI,MAAM,gFAAgF,KAAK,SAAS;AAAA,IAChH;AACA,SAAK,YAAY,iBAAiB,2BAA2B;AAC7D,SAAK,eAAe,iBAAiB;AACrC,SAAK,uBAAuB,iBAAiB,wBAAwB,KAAK;AAC1E,SAAK,wBAAwB,iBAAiB;AAC9C,SAAK,wBAAwB,iBAAiB,yBAAyB;AACvE,SAAK,qBAAqB,iBAAiB,uBAAuB,QAAQ,QAAQ;AAClF,SAAK,kBAAkB,iBAAiB,oBAAoB,OAAO,OAAO;AAC1E,QAAI,CAAC,KAAK,sBAAsB,CAAC,KAAK,iBAAiB;AACrD,YAAM,IAAI,MAAM,sGAAsG;AAAA,IACxH;AAAA,EACF;AAAA,EACA,UAAU;AACR,WAAO;AAAA,EACT;AAAA,EACA,aAAa,OAAO,mBAAmB,CAAC,GAAG;AACzC,QAAI,CAAC,IAAI,EAAE,IAAI,YAAY,GAAG;AAC5B,YAAM,IAAI,MAAM,0DAA0D;AAAA,IAC5E;AACA,UAAM,qBAAqB,IAAI,mBAAmB,gBAAgB;AAClE,UAAM,mBAAmB,MAAM;AAC/B,WAAO;AAAA,EACT;AAAA,EACA,MAAM,QAAQ;AACZ,QAAI;AACF,WAAK,SAAS,MAAM,UAAU,aAAa,aAAa;AAAA,QACtD,OAAO,KAAK,yBAAyB,OAAO,OAAO,KAAK;AAAA,QACxD,OAAO;AAAA,MACT,CAAC;AAAA,IACH,SAAS,IAAP;AACA,YAAM,IAAI,MAAM,iDAAiD,GAAG,SAAS;AAAA,IAC/E;AACA,QAAI,CAAC,KAAK,QAAQ;AAChB,YAAM,IAAI,MAAM,yCAAyC;AAAA,IAC3D;AACA,UAAM,iBAAiB,OAAO,gBAAgB,OAAO;AACrD,SAAK,eAAe,IAAI,eAAe;AACvC,QAAI,CAAC,KAAK,cAAc;AACtB,WAAK,eAAe,KAAK,aAAa;AAAA,IACxC,WAAW,KAAK,aAAa,eAAe,KAAK,cAAc;AAC7D,YAAM,IAAI,MAAM,wCAAwC,KAAK,yBAAyB,KAAK,aAAa,YAAY;AAAA,IACtH;AACA,UAAM,eAAe,KAAK,aAAa,wBAAwB,KAAK,MAAM;AAC1E,SAAK,WAAW,KAAK,aAAa,eAAe;AACjD,SAAK,SAAS,UAAU,KAAK,UAAU;AACvC,SAAK,SAAS,wBAAwB,KAAK;AAC3C,iBAAa,QAAQ,KAAK,QAAQ;AAClC,SAAK,WAAW,IAAI,aAAa,KAAK,OAAO;AAC7C,SAAK,WAAW,IAAI,aAAa,KAAK,OAAO;AAC7C;AAAA,EACF;AAAA,EACA,MAAM,OAAO;AACX,QAAI,KAAK,UAAU;AACjB,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,QAAI;AACJ,QAAI;AACJ,UAAM,iBAAiB,MAAM,KAAK,aAAa;AAC/C,QAAI,KAAK,oBAAoB;AAC3B,YAAM,WAAW,KAAK,aAAa,eAAe,aAAa;AAC/D,0BAAoB,KAAK,4BAA4B,UAAU,CAAC,KAAK,WAAW,KAAK,sBAAsB,CAAC,CAAC;AAAA,IAC/G;AACA,QAAI,KAAK,iBAAiB;AACxB,YAAM,WAAW,KAAK,aAAa,eAAe,aAAa;AAC/D,uBAAiB,KAAK,4BAA4B,UAAU,CAAC,KAAK,YAAY,KAAK,SAAS,CAAC,CAAC;AAAA,IAChG;AACA,WAAO;AAAA,MACL,OAAO,EAAE,eAAe,mBAAmB,YAAY,eAAe;AAAA,MACtE,MAAM;AAAA,IACR;AAAA,EACF;AAAA,EACA,MAAM,UAAU;AACd,YAAQ,MAAM,KAAK,KAAK,GAAG;AAAA,EAC7B;AAAA,EACA,MAAM,eAAe;AACnB,UAAM,gBAAgB,CAAC;AACvB,UAAM,gBAAgB,CAAC;AACvB,QAAI,gBAAgB;AACpB,WAAO,IAAI,QAAQ,CAAC,YAAY;AAC9B,YAAM,aAAa,YAAY,MAAM;AACnC,YAAI,KAAK,oBAAoB;AAC3B,eAAK,SAAS,sBAAsB,KAAK,QAAQ;AACjD,cAAI,KAAK,SAAS,OAAO,WAAW;AAClC,oBAAQ,EAAE,eAAe,cAAc,CAAC;AAAA,UAC1C;AACA,wBAAc,KAAK,KAAK,SAAS,MAAM,GAAG,KAAK,oBAAoB,CAAC;AAAA,QACtE;AACA,YAAI,KAAK,iBAAiB;AACxB,eAAK,SAAS,uBAAuB,KAAK,QAAQ;AAClD,wBAAc,KAAK,KAAK,SAAS,MAAM,CAAC;AAAA,QAC1C;AACA,YAAI,EAAE,kBAAkB,KAAK,WAAW;AACtC,wBAAc,UAAU;AACxB,kBAAQ,EAAE,eAAe,cAAc,CAAC;AAAA,QAC1C;AAAA,MACF,GAAG,KAAK,UAAU,KAAK,eAAe,GAAG;AAAA,IAC3C,CAAC;AAAA,EACH;AAAA,EACA,OAAO;AACL,QAAI,CAAC,KAAK,UAAU;AAClB,WAAK,WAAW;AAChB,WAAK,SAAS,WAAW;AACzB,WAAK,aAAa,MAAM;AACxB,UAAI,KAAK,UAAU,QAAQ,KAAK,OAAO,UAAU,EAAE,SAAS,GAAG;AAC7D,aAAK,OAAO,UAAU,EAAE,GAAG,KAAK;AAAA,MAClC;AAAA,IACF;AAAA,EACF;AAAA,EACA,UAAU;AACR,UAAM,IAAI,MAAM,iDAAiD;AAAA,EACnE;AAAA,EACA,gBAAgB;AACd,WAAO,KAAK;AAAA,EACd;AAAA,EACA,aAAa,OAAO;AAClB,UAAM,YAAY,MAAM,GAAG;AAC3B,UAAM,WAAW,IAAI,aAAa,MAAM,SAAS,SAAS;AAC1D,UAAM,QAAQ,CAAC,MAAM,OAAO,SAAS,IAAI,MAAM,KAAK,SAAS,CAAC;AAC9D,WAAO;AAAA,EACT;AAAA,EACA,4BAA4B,UAAU,OAAO;AAC3C,UAAM,OAAO,IAAI,aAAa,aAAa,cAAc,KAAK,CAAC;AAC/D,SAAK,IAAI,UAAU,KAAK,SAAS,SAAS,MAAM;AAChD,WAAO,OAAO,MAAM,KAAK;AAAA,EAC3B;AACF;AAGA,IAAI,iBAAiB,cAAc,aAAa;AAAA,EAC9C,YAAY,oBAAoB,cAAc;AAC5C,UAAM;AACN,SAAK,qBAAqB;AAC1B,SAAK,eAAe;AACpB,SAAK,WAAW;AAChB,SAAK,SAAS;AACd,QAAI,KAAK,aAAa,GAAG;AACvB,WAAK,SAAS;AACd,WAAK,WAAW,CAAC,KAAK,aAAa,cAAc,KAAK,aAAa,WAAW;AAC9E,WAAK,aAAa,SAAS,CAAC,CAAC,GAAG,OAAO;AACvC,UAAI,KAAK,aAAa,YAAY;AAChC,cAAM,qBAAqB,KAAK,aAAa,cAAc,IAAI,KAAK,mBAAmB;AACvF,cAAM,sBAAsB,KAAK,aAAa,eAAe,IAAI,KAAK,mBAAmB;AACzF,cAAM,kBAAkB,IAAI,sBAAsB;AAClD,cAAM,mBAAmB,IAAI,uBAAuB;AACpD,cAAM,eAAe,iBAAiB;AACtC,cAAM,gBAAgB,sBAAsB;AAC5C,aAAK,UAAU,SAAS,CAAC,iBAAiB,gBAAgB,eAAe,YAAY,GAAG,CAAC,GAAG,CAAC,CAAC;AAAA,MAChG,OAAO;AACL,aAAK,UAAU,SAAS,CAAC,GAAG,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAAA,MAC9C;AAAA,IACF;AAAA,EACF;AAAA,EACA,UAAU;AACR,WAAO;AAAA,EACT;AAAA,EACA,aAAa,OAAO,oBAAoB,eAAe,CAAC,GAAG;AACzD,QAAI,CAAC,IAAI,EAAE,IAAI,YAAY,GAAG;AAC5B,YAAM,IAAI,MAAM,0DAA0D;AAAA,IAC5E;AACA,QAAI,CAAC,oBAAoB;AACvB,2BAAqB,SAAS,cAAc,OAAO;AACnD,UAAI,CAAC,aAAa,eAAe,CAAC,aAAa,cAAc;AAC3D,cAAM,IAAI,MAAM,wGAAwG;AAAA,MAC1H;AACA,yBAAmB,QAAQ,aAAa;AACxC,yBAAmB,SAAS,aAAa;AAAA,IAC3C;AACA,UAAM,iBAAiB,IAAI,eAAe,oBAAoB,YAAY;AAC1E,UAAM,eAAe,MAAM;AAC3B,WAAO;AAAA,EACT;AAAA,EACA,MAAM,QAAQ;AACZ,QAAI,KAAK,aAAa,YAAY;AAChC,mBAAa,OAAO,KAAK,aAAa,eAAe,UAAU,KAAK,aAAa,eAAe,eAAe,MAAM,+BAA+B,KAAK,aAAa,oDAAoD;AAAA,IAC5N;AACA,QAAI;AACF,WAAK,SAAS,MAAM,UAAU,aAAa,aAAa;AAAA,QACtD,OAAO;AAAA,UACL,UAAU,KAAK,aAAa;AAAA,UAC5B,YAAY,KAAK,aAAa,aAAa,KAAK,aAAa,aAAa;AAAA,UAC1E,OAAO,KAAK,mBAAmB;AAAA,UAC/B,QAAQ,KAAK,mBAAmB;AAAA,QAClC;AAAA,MACF,CAAC;AAAA,IACH,SAAS,IAAP;AACA,SAAG,UAAU,iDAAiD,GAAG;AACjE,YAAM;AAAA,IACR;AACA,QAAI,CAAC,KAAK,QAAQ;AAChB,YAAM,IAAI,MAAM,qCAAqC;AAAA,IACvD;AACA,QAAI;AACF,WAAK,mBAAmB,YAAY,KAAK;AAAA,IAC3C,SAAS,OAAP;AACA,cAAQ,IAAI,KAAK;AACjB,WAAK,mBAAmB,MAAM,OAAO,IAAI,gBAAgB,KAAK,MAAM;AAAA,IACtE;AACA,SAAK,mBAAmB,KAAK;AAC7B,SAAK,WAAW;AAChB,WAAO,IAAI,QAAQ,CAAC,YAAY;AAC9B,WAAK,mBAAmB,mBAAmB,MAAM;AAC/C,gBAAQ;AAAA,MACV;AAAA,IACF,CAAC;AAAA,EACH;AAAA,EACA,MAAM,OAAO;AACX,QAAI,KAAK,UAAU;AACjB,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,QAAI;AACJ,QAAI;AACF,YAAM,gBAAgB,WAAW,KAAK,kBAAkB;AAAA,IAC1D,SAAS,IAAP;AACA,YAAM,IAAI,MAAM,4CAA4C,KAAK,UAAU,EAAE,GAAG;AAAA,IAClF;AACA,QAAI,KAAK,QAAQ;AACf,UAAI;AACF,eAAO,EAAE,OAAO,KAAK,mBAAmB,GAAG,GAAG,MAAM,MAAM;AAAA,MAC5D,SAAS,IAAP;AACA,cAAM,IAAI,MAAM,oCAAoC,GAAG,SAAS;AAAA,MAClE,UAAE;AACA,YAAI,QAAQ;AAAA,MACd;AAAA,IACF,OAAO;AACL,aAAO,EAAE,OAAO,KAAK,MAAM,MAAM;AAAA,IACnC;AAAA,EACF;AAAA,EACA,eAAe;AACb,QAAI,KAAK,aAAa,eAAe,KAAK,aAAa,iBAAiB,KAAK,mBAAmB,UAAU,KAAK,aAAa,eAAe,KAAK,mBAAmB,WAAW,KAAK,aAAa,eAAe;AAC7M,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT;AAAA,EACA,mBAAmB,KAAK;AACtB,WAAO,KAAK,MAAM;AAChB,YAAM,gBAAgB,WAAW,KAAK,KAAK,SAAS,GAAG,CAAC;AACxD,UAAI;AACJ,qBAAe,MAAM,cAAc,eAAe,KAAK,SAAS,KAAK,YAAY,KAAK,UAAU,UAAU;AAC1G,YAAM,QAAQ,aAAa;AAC3B,aAAO,QAAQ,cAAc,MAAM,MAAM,CAAC,CAAC;AAAA,IAC7C,CAAC;AAAA,EACH;AAAA,EACA,MAAM,UAAU;AACd,YAAQ,MAAM,KAAK,KAAK,GAAG;AAAA,EAC7B;AAAA,EACA,OAAO;AACL,UAAM,SAAS,KAAK,OAAO,UAAU;AACrC,WAAO,QAAQ,CAAC,UAAU,MAAM,KAAK,CAAC;AACtC,QAAI;AACF,WAAK,mBAAmB,YAAY;AAAA,IACtC,SAAS,OAAP;AACA,cAAQ,IAAI,KAAK;AACjB,WAAK,mBAAmB,MAAM;AAAA,IAChC;AACA,SAAK,WAAW;AAAA,EAClB;AAAA,EACA,UAAU;AACR,UAAM,IAAI,MAAM,iDAAiD;AAAA,EACnE;AACF;AAGA,IAAI,aAAa,MAAM;AACvB;AAGA,IAAI,iBAAiB,cAAc,aAAa;AAAA,EAC9C,MAAM,WAAW;AACf,WAAO,IAAI,cAAc,MAAM,SAAS;AAAA,EAC1C;AACF;AACA,IAAI,gBAAgB,cAAc,eAAe;AAAA,EAC/C,YAAY,UAAU,WAAW;AAC/B,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,OAAO,IAAI,kBAAkB,UAAU,SAAS;AAAA,EACvD;AAAA,EACA,UAAU;AACR,WAAO,KAAK,KAAK,QAAQ;AAAA,EAC3B;AAAA,EACA,MAAM,OAAO;AACX,WAAO,KAAK,KAAK,KAAK;AAAA,EACxB;AACF;AACA,IAAI,oBAAoB,cAAc,kBAAkB;AAAA,EACtD,YAAY,UAAU,WAAW;AAC/B,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,YAAY;AACjB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ,eAAe,KAAK;AAAA,EACtD;AAAA,EACA,MAAM,OAAO;AACX,UAAM,cAAc,MAAM,KAAK,SAAS,KAAK;AAC7C,QAAI,YAAY,MAAM;AACpB,UAAI,KAAK,cAAc,IAAI;AACzB,eAAO;AAAA,MACT;AACA,WAAK,YAAY,KAAK,KAAK,SAAS;AACpC,WAAK,YAAY;AACjB,aAAO;AAAA,IACT;AACA,UAAMF,SAAQ,YAAY,MAAM,MAAM,KAAK,SAAS;AACpD,IAAAA,OAAM,KAAK,KAAK,YAAYA,OAAM;AAClC,eAAW,QAAQA,OAAM,MAAM,GAAG,EAAE,GAAG;AACrC,WAAK,YAAY,KAAK,IAAI;AAAA,IAC5B;AACA,SAAK,YAAYA,OAAMA,OAAM,SAAS;AACtC,WAAO;AAAA,EACT;AACF;AAGA,IAAI,oBAAoB,cAAc,aAAa;AAAA,EACjD,aAAa;AACX,WAAO,IAAI,aAAa,IAAI;AAAA,EAC9B;AACF;AACA,IAAI,eAAe,cAAc,eAAe;AAAA,EAC9C,YAAY,UAAU;AACpB,UAAM;AACN,SAAK,WAAW;AAChB,SAAK,OAAO,IAAI,iBAAiB,QAAQ;AAAA,EAC3C;AAAA,EACA,UAAU;AACR,WAAO,KAAK,KAAK,QAAQ;AAAA,EAC3B;AAAA,EACA,MAAM,OAAO;AACX,WAAO,KAAK,KAAK,KAAK;AAAA,EACxB;AACF;AACA,IAAI,mBAAmB,cAAc,kBAAkB;AAAA,EACrD,YAAY,UAAU;AACpB,UAAM;AACN,SAAK,WAAW;AAChB,QAAI,IAAI,EAAE,IAAI,YAAY,GAAG;AAC3B,WAAK,UAAU,IAAI,YAAY,OAAO;AAAA,IACxC,OAAO;AACL,YAAM,EAAE,cAAc,IAAI,uBAAuB;AACjD,WAAK,UAAU,IAAI,cAAc,MAAM;AAAA,IACzC;AAAA,EACF;AAAA,EACA,UAAU;AACR,WAAO,GAAG,KAAK,SAAS,QAAQ;AAAA,EAClC;AAAA,EACA,MAAM,OAAO;AACX,UAAM,cAAc,MAAM,KAAK,SAAS,KAAK;AAC7C,QAAI;AACJ,QAAI,YAAY,MAAM;AACpB,aAAO;AAAA,IACT,OAAO;AACL,cAAQ,YAAY;AAAA,IACtB;AACA,QAAI;AACJ,QAAI,IAAI,EAAE,IAAI,YAAY,GAAG;AAC3B,aAAO,KAAK,QAAQ,OAAO,OAAO,EAAE,QAAQ,KAAK,CAAC;AAAA,IACpD,OAAO;AACL,aAAO,KAAK,QAAQ,MAAM,OAAO,KAAK,MAAM,MAAM,CAAC;AAAA,IACrD;AACA,SAAK,YAAY,KAAK,IAAI;AAC1B,WAAO;AAAA,EACT;AACF;AAGA,IAAI,oBAAoB,cAAc,kBAAkB;AAAA,EACtD,YAAY,MAAMX,WAAU,CAAC,GAAG;AAC9B,UAAM;AACN,SAAK,OAAO;AACZ,SAAK,UAAUA;AACf,iBAAa,OAAO,gBAAgB,eAAe,IAAI,EAAE,IAAI,YAAY,IAAI,gBAAgB,QAAQ,gBAAgB,OAAO,QAAQ,MAAM,sEAAsE;AAChN,SAAK,SAASA,SAAQ,UAAU;AAChC,SAAK,YAAYA,SAAQ,aAAa,OAAO;AAAA,EAC/C;AAAA,EACA,UAAU;AACR,WAAO,cAAc,KAAK;AAAA,EAC5B;AAAA,EACA,MAAM,OAAO;AACX,QAAI,KAAK,WAAW,KAAK,gBAAgB,aAAa,KAAK,KAAK,aAAa,KAAK,KAAK,OAAO;AAC5F,aAAO,EAAE,OAAO,MAAM,MAAM,KAAK;AAAA,IACnC;AACA,UAAM,QAAQ,IAAI,QAAQ,CAAC,SAAS,WAAW;AAC7C,YAAM,MAAM,KAAK,SAAS,KAAK;AAC/B,UAAI,KAAK,gBAAgB,YAAY;AACnC,gBAAQ,IAAI,WAAW,KAAK,KAAK,MAAM,KAAK,QAAQ,GAAG,CAAC,CAAC;AAAA,MAC3D,OAAO;AACL,cAAM,aAAa,IAAI,WAAW;AAClC,mBAAW,SAAS,CAAC,UAAU;AAC7B,cAAI,OAAO,WAAW;AACtB,cAAI,gBAAgB,aAAa;AAC/B,mBAAO,IAAI,WAAW,IAAI;AAAA,UAC5B;AACA,cAAI,EAAE,gBAAgB,aAAa;AACjC,mBAAO,OAAO,IAAI,UAAU,mCAAmC,CAAC;AAAA,UAClE;AACA,kBAAQ,IAAI;AAAA,QACd;AACA,mBAAW,UAAU,CAAC,UAAU;AAC9B,iBAAO,OAAO,IAAI,MAAM,SAAS,CAAC;AAAA,QACpC;AACA,mBAAW,UAAU,CAAC,UAAU;AAC9B,iBAAO,OAAO,IAAI,MAAM,MAAM,IAAI,CAAC;AAAA,QACrC;AACA,cAAM,SAAS,KAAK,KAAK,MAAM,KAAK,QAAQ,GAAG;AAC/C,mBAAW,kBAAkB,MAAM;AAAA,MACrC;AACA,WAAK,SAAS;AAAA,IAChB,CAAC;AACD,WAAO,EAAE,OAAO,MAAM,OAAO,MAAM,MAAM;AAAA,EAC3C;AACF;AAGA,eAAe,iBAAiB,KAAKA,WAAU,CAAC,GAAG,WAAW;AAC5D,MAAI;AACJ,MAAI;AACJ,MAAI,OAAO,QAAQ,UAAU;AAC3B,gBAAY;AAAA,EACd,OAAO;AACL,gBAAY,IAAI;AAChB,kBAAc,0BAA0B,GAAG;AAAA,EAC7C;AACA,QAAM,WAAW,OAAO,aAAa,aAAa,OAAO,WAAW,WAAW;AAC/E,MAAI,SAAS,IAAI;AACf,UAAM,aAAa,IAAI,WAAW,MAAM,SAAS,YAAY,CAAC;AAC9D,WAAO,IAAI,kBAAkB,YAAYA,QAAO;AAAA,EAClD,OAAO;AACL,UAAM,IAAI,MAAM,SAAS,UAAU;AAAA,EACrC;AACF;AACA,IAAI,4BAA4B,CAAC,YAAY;AAC3C,QAAMF,SAAQ;AAAA,IACZ,QAAQ,QAAQ;AAAA,IAChB,SAAS,QAAQ;AAAA,IACjB,MAAM,QAAQ;AAAA,IACd,MAAM,QAAQ;AAAA,IACd,aAAa,QAAQ;AAAA,IACrB,OAAO,QAAQ;AAAA,IACf,UAAU,QAAQ;AAAA,IAClB,UAAU,QAAQ;AAAA,IAClB,WAAW,QAAQ;AAAA,EACrB;AACA,SAAOA;AACT;AAGA,SAAS,YAAY,QAAQ;AAC3B,SAAO,OAAO,WAAW,YAAY,OAAO,MAAM,GAAG,CAAC,MAAM;AAC9D;AAGA,IAAI,iBAAiB,cAAc,WAAW;AAAA,EAC5C,YAAY,QAAQE,WAAU,CAAC,GAAG;AAChC,UAAM;AACN,SAAK,QAAQ;AACb,SAAK,UAAUA;AAAA,EACjB;AAAA,EACA,MAAM,WAAW;AACf,QAAI,YAAY,KAAK,KAAK,KAAK,IAAI,EAAE,IAAI,SAAS,GAAG;AACnD,YAAM,KAAK,WAAW;AACtB,WAAK,QAAQ,GAAG,aAAa,KAAK,MAAM,MAAM,CAAC,CAAC;AAAA,IAClD;AACA,WAAO,IAAI,kBAAkB,KAAK,OAAO,KAAK,OAAO;AAAA,EACvD;AACF;AAGA,IAAI,gBAAgB,cAAc,WAAW;AAAA,EAC3C,YAAY,KAAK,cAAc,CAAC,GAAG;AACjC,UAAM;AACN,SAAK,MAAM;AACX,SAAK,cAAc;AAAA,EACrB;AAAA,EACA,MAAM,WAAW;AACf,QAAI,YAAY,KAAK,GAAG,GAAG;AACzB,aAAO,IAAI,eAAe,KAAK,KAAK,KAAK,WAAW,EAAE,SAAS;AAAA,IACjE,OAAO;AACL,aAAO,iBAAiB,KAAK,KAAK,KAAK,WAAW;AAAA,IACpD;AAAA,EACF;AACF;AAGA,SAAS,IAAI,QAAQ,YAAY,CAAC,GAAG;AACnC,SAAO,IAAI,WAAW,IAAI,cAAc,MAAM,GAAG,SAAS;AAC5D;AACA,SAAS,KAAK,GAAG;AACf,QAAM,OAAO,qBAAqB,CAAC;AACnC,SAAO,sBAAsB,YAAY,IAAI;AAC/C;AACA,SAAS,UAAU,YAAY;AAC7B,SAAO,sBAAsB,YAAY;AACvC,UAAM,MAAM,MAAM,WAAW;AAC7B,WAAO,qBAAqB,MAAM,IAAI,KAAK,CAAC;AAAA,EAC9C,CAAC;AACH;AACA,eAAe,OAAO,oBAAoB,cAAc;AACtD,SAAO,eAAe,OAAO,oBAAoB,YAAY;AAC/D;AACA,eAAe,WAAW,kBAAkB;AAC1C,SAAO,mBAAmB,OAAO,gBAAgB;AACnD;AAGA,IAAI,WAAW;AAGf,SAAS,iBAAiB,SAAS,QAAQ;AACzC,MAAI,CAAC,MAAM,QAAQ,OAAO,GAAG;AAC3B,cAAU,CAAC,OAAO;AAAA,EACpB;AACA,UAAQ,QAAQ,CAAC,OAAO;AACtB,QAAI,MAAM,MAAM;AACd,mBAAa,OAAO,GAAG,UAAU,aAAa,MAAM,GAAG,+DAA+D;AAAA,IACxH;AAAA,EACF,CAAC;AACH;AAGA,IAAI,aAAa,qBAAqB;AACtC,IAAI,iBAAiB,cAAc,cAAc;AAAA,EAC/C,cAAc;AACZ,UAAM;AACN,SAAK,YAAY;AACjB,SAAK,WAAW;AAChB,SAAK,OAAO,IAAI,YAAY,MAAM,OAAO,CAAC;AAAA,EAC5C;AAAA,EACA,aAAa;AACX,WAAO,eAAe;AAAA,EACxB;AAAA,EACA,MAAM,QAAQ,OAAO,OAAO;AAC1B,QAAI,KAAK,UAAU;AACjB,WAAK,WAAW;AAChB,UAAI,IAAI,EAAE,IAAI,SAAS,GAAG;AACxB,6BAAqB,KAAK,oPAAoP;AAAA,MAChR;AAAA,IACF;AACA,UAAM,SAAS,EAAE,IAAI,KAAK,WAAW,EAAE;AACvC,SAAK,KAAK,IAAI,QAAQ,EAAE,QAAQ,OAAO,UAAU,EAAE,CAAC;AACpD,WAAO;AAAA,EACT;AAAA,EACA,eAAe,OAAO,OAAO,QAAQ;AACnC,QAAI;AACJ,QAAI,UAAU,YAAY,UAAU,QAAQ,OAAO,SAAS,KAAK,aAAa,SAAS,OAAO,EAAE,GAAG;AACjG,YAAM,gBAAgB,OAAO,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC;AACpE,cAAQ,KAAK,MAAM,eAAe,OAAO,KAAK;AAAA,IAChD,OAAO;AACL,cAAQ,KAAK,MAAM,QAAQ,OAAO,KAAK;AAAA,IACzC;AACA,WAAO,EAAE,QAAQ,OAAO,OAAO,MAAM;AAAA,EACvC;AAAA,EACA,SAAS,QAAQ;AACf,QAAI,KAAK,KAAK,IAAI,MAAM,GAAG;AACzB,YAAM,aAAa,KAAK,KAAK,IAAI,MAAM;AACvC,aAAO,WAAW;AAAA,IACpB;AACA,WAAO;AAAA,EACT;AAAA,EACA,OAAO,QAAQ;AACb,UAAM,aAAa,KAAK,KAAK,IAAI,MAAM;AACvC,eAAW;AAAA,EACb;AAAA,EACA,OAAO,QAAQ;AACb,QAAI,KAAK,KAAK,IAAI,MAAM,GAAG;AACzB,YAAM,aAAa,KAAK,KAAK,IAAI,MAAM;AACvC,iBAAW;AAAA,IACb;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ,OAAO,OAAO,UAAU;AAC3C,SAAK,KAAK,IAAI,QAAQ,EAAE,QAAQ,OAAO,SAAS,CAAC;AAAA,EACnD;AAAA,EACA,aAAa;AACX,WAAO,KAAK,KAAK,WAAW;AAAA,EAC9B;AAAA,EACA,MAAM,KAAK,QAAQ;AACjB,WAAO,KAAK,SAAS,MAAM;AAAA,EAC7B;AAAA,EACA,SAAS,QAAQ;AACf,UAAM,EAAE,OAAO,mBAAmB,IAAI,KAAK,KAAK,IAAI,MAAM;AAC1D,QAAI,UAAU,aAAa;AACzB,YAAM,aAAa,KAAK,SAAS,mBAAmB,KAAK,MAAM;AAC/D,YAAM,aAAa,KAAK,SAAS,mBAAmB,KAAK,MAAM;AAC/D,aAAO,qBAAqB,uBAAuB,YAAY,UAAU;AAAA,IAC3E;AACA,WAAO,KAAK,KAAK,IAAI,MAAM,EAAE;AAAA,EAC/B;AAAA,EACA,WAAW,IAAI;AACb,UAAM,OAAO,KAAK,SAAS,GAAG,MAAM;AACpC,QAAI,GAAG,UAAU,UAAU;AACzB,UAAI;AACF,cAAM,UAAU,KAAK,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC;AAC5D,eAAO,OAAO,GAAG,OAAO,GAAG,OAAO,OAAO;AAAA,MAC3C,SAAS,IAAP;AACA,cAAM,IAAI,MAAM,kDAAkD;AAAA,MACpE;AAAA,IACF;AACA,WAAO,OAAO,GAAG,OAAO,GAAG,OAAO,IAAI;AAAA,EACxC;AAAA,EACA,WAAW,QAAQ,OAAO,OAAO;AAC/B,WAAO,OAAO,EAAE,yBAAyB,KAAK,eAAe,OAAO,OAAO,MAAM,GAAG,IAAI;AAAA,EAC1F;AAAA,EACA,YAAY,QAAQ,QAAQ,OAAO;AACjC,QAAI,KAAK,KAAK,IAAI,MAAM,GAAG;AACzB,WAAK,KAAK,IAAI,MAAM,EAAE;AACtB,UAAI,CAAC,SAAS,KAAK,KAAK,IAAI,MAAM,EAAE,WAAW,GAAG;AAChD,eAAO;AAAA,MACT;AACA,YAAM,EAAE,mBAAmB,IAAI,KAAK,KAAK,IAAI,MAAM;AACnD,UAAI,sBAAsB,MAAM;AAC9B,aAAK,YAAY,mBAAmB,KAAK,QAAQ,IAAI;AACrD,aAAK,YAAY,mBAAmB,KAAK,QAAQ,IAAI;AAAA,MACvD;AACA,WAAK,KAAK,OAAO,MAAM;AAAA,IACzB;AACA,WAAO;AAAA,EACT;AAAA,EACA,8BAA8B,YAAY;AACxC,SAAK,YAAY,WAAW,MAAM;AAAA,EACpC;AAAA,EACA,MAAM,KAAK,GAAG;AACZ,UAAM,QAAQ,aAAa,IAAI;AAC/B,MAAE;AACF,UAAM,WAAW,aAAa,IAAI,IAAI;AACtC,WAAO,EAAE,SAAS;AAAA,EACpB;AAAA,EACA,SAAS;AACP,WAAO;AAAA,MACL,YAAY;AAAA,MACZ,SAAS,CAAC,oHAAoH;AAAA,IAChI;AAAA,EACF;AAAA,EACA,MAAM,WAAW;AACf,qBAAiB,CAAC,SAAS,GAAG,OAAO;AACrC,UAAM,WAAW,KAAK,SAAS,UAAU,MAAM;AAC/C,WAAO,WAAW,UAAU,OAAO,QAAQ;AAAA,EAC7C;AAAA,EACA,UAAU;AAAA,EACV;AAAA,EACA,iBAAiB;AACf,WAAO;AAAA,EACT;AAAA,EACA,UAAU;AACR,WAAO,MAAM,QAAQ;AAAA,EACvB;AACF;AACA,eAAe,aAAa;AAG5B,IAAI,iBAAiB,CAAC;AACtBT,UAAS,gBAAgB;AAAA,EACvB,SAAS,MAAM;AAAA,EACf,cAAc,MAAM;AAAA,EACpB,oBAAoB,MAAM;AAAA,EAC1B,UAAU,MAAM;AAAA,EAChB,YAAY,MAAM;AAAA,EAClB,WAAW,MAAM;AAAA,EACjB,SAAS,MAAM;AAAA,EACf,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,cAAc,MAAM;AAAA,EACpB,cAAc,MAAM;AAAA,EACpB,kBAAkB,MAAM;AAAA,EACxB,aAAa,MAAM;AAAA,EACnB,eAAe,MAAM;AAAA,EACrB,UAAU,MAAM;AAAA,EAChB,cAAc,MAAM;AAAA,EACpB,SAAS,MAAM;AAAA,EACf,SAAS,MAAM;AAAA,EACf,aAAa,MAAM;AAAA,EACnB,aAAa,MAAM;AAAA,EACnB,cAAc,MAAM;AAAA,EACpB,SAAS,MAAM;AAAA,EACf,cAAc,MAAM;AAAA,EACpB,UAAU,MAAM;AAAA,EAChB,WAAW,MAAM;AAAA,EACjB,WAAW,MAAM;AAAA,EACjB,aAAa,MAAM;AAAA,EACnB,aAAa,MAAM;AAAA,EACnB,eAAe,MAAM;AAAA,EACrB,WAAW,MAAM;AAAA,EACjB,yBAAyB,MAAM;AAAA,EAC/B,mBAAmB,MAAM;AAAA,EACzB,4BAA4B,MAAM;AAAA,EAClC,UAAU,MAAM;AAAA,EAChB,uBAAuB,MAAM;AAAA,EAC7B,kBAAkB,MAAM;AAAA,EACxB,kBAAkB,MAAM;AAAA,EACxB,iBAAiB,MAAM;AAAA,EACvB,4BAA4B,MAAM;AAAA,EAClC,SAAS,MAAM;AAAA,EACf,UAAU,MAAM;AAAA,EAChB,UAAU,MAAM;AAAA,EAChB,eAAe,MAAM;AAAA,EACrB,YAAY,MAAM;AACpB,CAAC;AAGD,SAAS,cAAc,MAAM;AAC3B,QAAM,eAAe,IAAI,aAAa,KAAK,MAAM;AACjD,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,iBAAa,MAAM,KAAK,IAAI,KAAK,GAAG;AAAA,EACtC;AACA,SAAO;AACT;AACA,IAAI,OAAO,CAAC,SAAS;AACnB,QAAM,EAAE,EAAE,IAAI,KAAK;AACnB,QAAM,aAAa,KAAK;AACxB,mBAAiB,GAAG,KAAK;AACzB,MAAI,eAAe,IAAI,aAAa,aAAa,cAAc,EAAE,KAAK,CAAC;AACvE,QAAM,SAAS,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC7C,iBAAe,cAAc,MAAM;AACnC,SAAO,WAAW,WAAW,cAAc,EAAE,OAAO,EAAE,KAAK;AAC7D;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,6BAA6B,KAAK;AACzC,SAAO,CAAC,QAAQ,QAAQ,OAAO,OAAO,UAAU;AAC9C,UAAM,WAAW,qBAAqB,2BAA2B,QAAQ,MAAM;AAC/E,UAAM,aAAa,SAAS;AAC5B,UAAM,gBAAgB,aAAa,eAAe,QAAQ;AAC1D,UAAM,aAAa,aAAa,cAAc,QAAQ;AACtD,UAAM,SAAS,aAAa,uBAAuB,OAAO,UAAU;AACpE,UAAM,QAAQ,OAAO;AACrB,UAAM,QAAQ,OAAO;AACrB,UAAM,WAAW,aAAa,eAAe,MAAM;AACnD,UAAM,WAAW,aAAa,eAAe,MAAM;AACnD,UAAM,iBAAiB,qBAAqB,iBAAiB,QAAQ,QAAQ;AAC7E,UAAM,iBAAiB,qBAAqB,iBAAiB,QAAQ,QAAQ;AAC7E,QAAI,eAAe,SAAS,eAAe,WAAW,GAAG;AACvD,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,eAAO,MAAM,IAAI,MAAM,KAAK,MAAM,SAAS,MAAM,KAAK,MAAM,OAAO;AAAA,MACrE;AAAA,IACF,OAAO;AACL,eAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,cAAM,MAAM,aAAa,WAAW,IAAI,YAAY,aAAa;AACjE,cAAM,OAAO,IAAI,MAAM,CAAC,KAAK;AAC7B,uBAAe,QAAQ,CAAC,MAAM,KAAK,KAAK,CAAC;AACzC,cAAM,SAAS,aAAa,WAAW,MAAM,OAAO,QAAQ;AAC5D,cAAM,OAAO,IAAI,MAAM,CAAC,KAAK;AAC7B,uBAAe,QAAQ,CAAC,MAAM,KAAK,KAAK,CAAC;AACzC,cAAM,SAAS,aAAa,WAAW,MAAM,OAAO,QAAQ;AAC5D,eAAO,MAAM,IAAI,MAAM,SAAS,MAAM,OAAO;AAAA,MAC/C;AAAA,IACF;AACA,WAAO,CAAC,QAAQ,QAAQ;AAAA,EAC1B;AACF;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,MAAM,OAAO,MAAM,MAAM,IAAI;AACrC,QAAM,WAAW,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AACjD,QAAM,WAAW,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AACjD,QAAM,cAAc,SAAS,eAAe,MAAM,OAAO,WAAW;AACpE,QAAM,WAAW,SAAS,KAAK,IAAI,YAAY,MAAM;AACrD,WAAS,qBAAqB;AAAA,IAC5B,MAAM,SAAS,eAAe,MAAM,OAAO,WAAW,QAAQ;AAAA,IAC9D,MAAM,SAAS,eAAe,MAAM,OAAO,WAAW,QAAQ;AAAA,EAChE;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,OAAO,UAAU,OAAO,QAAQ,WAAW;AAClD,MAAI,UAAU,aAAa;AACzB,UAAM,QAAQ,OAAO,UAAU,OAAO,SAAS;AAC/C,UAAM,QAAQ,OAAO,UAAU,OAAO,SAAS;AAC/C,WAAO,SAAS,EAAE,QAAQ,EAAE,MAAM,OAAO,MAAM,MAAM,GAAG,SAAS,SAAS,CAAC;AAAA,EAC7E;AACA,QAAM,SAAS,aAAa,oBAAoB,aAAa,cAAc,KAAK,GAAG,KAAK;AACxF,SAAO,SAAS,eAAe,OAAO,OAAO,MAAM;AACrD;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,WAAS,OAAO,EAAE,MAAM;AACxB,SAAO,EAAE,QAAQ,EAAE,QAAQ,OAAO,EAAE,OAAO,OAAO,EAAE,MAAM;AAC5D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,QAAQ,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE,mBAAmB;AAClE,QAAM,UAAU,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AAChD,SAAO,SAAS,eAAe,MAAM,OAAO,MAAM,OAAO,OAAO;AAClE;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,IAAI;AAClB,MAAI,UAAU,aAAa;AACzB,QAAI,EAAE,UAAU,aAAa;AAC3B,aAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,IACvD;AACA,UAAM,kBAAkB,OAAO,UAAU,EAAE,OAAO,EAAE,KAAK;AACzD,UAAM,SAAS,MAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AACtF,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,QAAQ,MAAM,gBAAgB,GAAG,SAAS,SAAS,CAAC;AAC9F,aAAS,8BAA8B,eAAe;AACtD,aAAS,8BAA8B,MAAM;AAC7C,WAAO;AAAA,EACT;AACA,MAAI,EAAE,UAAU,aAAa;AAC3B,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,SAAS,MAAM,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AACrF,aAAS,8BAA8B,QAAQ;AAC/C,WAAO;AAAA,EACT;AACA,MAAI,CAAC,aAAa,gBAAgB,EAAE,OAAO,KAAK,GAAG;AACjD,UAAM,SAAS,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAC7D,WAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO,OAAO,OAAO,MAAM;AAAA,EAC7D;AACA,MAAI,UAAU,SAAS;AACrB,UAAM,SAAS,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC3C,UAAM,eAAe,WAAW,KAAK,MAAM;AAC3C,WAAO,SAAS,eAAe,EAAE,OAAO,SAAS,YAAY;AAAA,EAC/D;AACA,MAAI,UAAU,QAAQ;AACpB,UAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,UAAM,OAAO,aAAa,aAAa,CAAC,CAAC,GAAG,EAAE,KAAK;AACnD,UAAM,CAAC,YAAY,WAAW,IAAI,6BAA6B,CAAC,GAAG,MAAM,MAAM,IAAI,IAAI,CAAC,EAAE,EAAE,OAAO,CAAC,GAAG,OAAO,MAAM,MAAM;AAC1H,WAAO,SAAS,eAAe,aAAa,QAAQ,UAAU;AAAA,EAChE;AACA,QAAM,IAAI,MAAM,iCAAiC,EAAE,YAAY,OAAO;AACxE;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,iBAAiB,MAAM,YAAY,aAAa,OAAO;AAC9D,MAAI,eAAe,MAAM;AACvB,WAAO,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AACxC,YAAM,EAAE,GAAG,EAAE,IAAI;AACjB,YAAM,aAAa;AACnB,uBAAiB,CAAC,GAAG,CAAC,GAAG,IAAI;AAC7B,YAAM,QAAQ,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,YAAM,QAAQ,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,YAAM,eAAe,EAAE,UAAU,WAAW,qBAAqB,uBAAuB,KAAK,IAAI;AACjG,YAAM,eAAe,EAAE,UAAU,WAAW,qBAAqB,uBAAuB,KAAK,IAAI;AACjG,YAAM,SAAS,SAAS,EAAE;AAC1B,YAAM,CAAC,YAAY,WAAW,IAAI,WAAW,EAAE,OAAO,EAAE,OAAO,cAAc,cAAc,MAAM;AACjG,aAAO,WAAW,eAAe,aAAa,QAAQ,UAAU;AAAA,IAClE;AAAA,EACF;AACA,SAAO,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AACxC,UAAM,EAAE,GAAG,EAAE,IAAI;AACjB,UAAM,aAAa;AACnB,QAAI,EAAE,UAAU,eAAe,EAAE,UAAU,aAAa;AACtD,YAAM,YAAY,MAAM,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,YAAY,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAChG,YAAM,gBAAgB,WAAW,KAAK,IAAI,UAAU,MAAM;AAC1D,YAAM,QAAQ,cAAc,mBAAmB;AAC/C,YAAM,QAAQ,cAAc,mBAAmB;AAC/C,YAAM,YAAY,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACpD,YAAM,YAAY,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACpD,YAAM,YAAY,MAAM,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,YAAY,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAChG,YAAM,gBAAgB,WAAW,KAAK,IAAI,UAAU,MAAM;AAC1D,YAAM,QAAQ,cAAc,mBAAmB;AAC/C,YAAM,QAAQ,cAAc,mBAAmB;AAC/C,YAAM,YAAY,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACpD,YAAM,YAAY,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACpD,YAAM,CAAC,gBAAgB,gBAAgB,WAAW,IAAI,YAAY,EAAE,OAAO,EAAE,OAAO,WAAW,WAAW,WAAW,SAAS;AAC9H,YAAM,aAAa,WAAW,eAAe,aAAa,WAAW,cAAc;AACnF,YAAM,aAAa,WAAW,eAAe,aAAa,WAAW,cAAc;AACnF,YAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,YAAY,MAAM,WAAW,GAAG,SAAS,WAAW,CAAC;AAC/F,iBAAW,8BAA8B,SAAS;AAClD,iBAAW,8BAA8B,SAAS;AAClD,iBAAW,8BAA8B,UAAU;AACnD,iBAAW,8BAA8B,UAAU;AACnD,aAAO;AAAA,IACT,OAAO;AACL,YAAM,QAAQ,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,YAAM,QAAQ,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,YAAM,SAAS,SAAS,EAAE;AAC1B,YAAM,CAAC,YAAY,WAAW,IAAI,WAAW,EAAE,OAAO,EAAE,OAAO,OAAO,OAAO,MAAM;AACnF,aAAO,WAAW,eAAe,aAAa,QAAQ,UAAU;AAAA,IAClE;AAAA,EACF;AACF;AACA,SAAS,8BAA8B,KAAK;AAC1C,SAAO,CAAC,QAAQ,QAAQ,WAAW,WAAW,WAAW,cAAc;AACrE,UAAM,cAAc,qBAAqB,2BAA2B,QAAQ,MAAM;AAClF,UAAM,aAAa,aAAa,cAAc,WAAW;AACzD,UAAM,aAAa,YAAY;AAC/B,UAAM,gBAAgB,aAAa,eAAe,WAAW;AAC7D,UAAM,iBAAiB,aAAa,uBAAuB,WAAW,UAAU;AAChF,UAAM,iBAAiB,aAAa,uBAAuB,WAAW,UAAU;AAChF,UAAM,iBAAiB,qBAAqB,iBAAiB,QAAQ,WAAW;AAChF,UAAM,iBAAiB,qBAAqB,iBAAiB,QAAQ,WAAW;AAChF,UAAM,QAAQ,qBAAqB,uBAAuB,WAAW,SAAS;AAC9E,UAAM,QAAQ,qBAAqB,uBAAuB,WAAW,SAAS;AAC9E,UAAM,QAAQ,OAAO;AACrB,UAAM,WAAW,aAAa,eAAe,MAAM;AACnD,UAAM,QAAQ,OAAO;AACrB,UAAM,WAAW,aAAa,eAAe,MAAM;AACnD,QAAI,eAAe,SAAS,eAAe,WAAW,GAAG;AACvD,eAAS,KAAK,GAAG,KAAK,eAAe,QAAQ,MAAM;AACjD,cAAM,OAAO,KAAK,MAAM;AACxB,cAAM,OAAO,KAAK,MAAM;AACxB,cAAM,SAAS,IAAI,MAAM,OAAO,IAAI,MAAM,OAAO,IAAI,IAAI,MAAM,OAAO,IAAI,MAAM,OAAO,IAAI,EAAE;AAC7F,uBAAe,MAAM,OAAO;AAC5B,uBAAe,MAAM,OAAO;AAAA,MAC9B;AAAA,IACF,OAAO;AACL,eAAS,KAAK,GAAG,KAAK,eAAe,QAAQ,MAAM;AACjD,cAAM,MAAM,aAAa,WAAW,IAAI,YAAY,aAAa;AACjE,cAAM,OAAO,IAAI,MAAM,CAAC,KAAK;AAC7B,uBAAe,QAAQ,CAAC,MAAM,KAAK,KAAK,CAAC;AACzC,cAAM,SAAS,aAAa,WAAW,MAAM,OAAO,QAAQ;AAC5D,cAAM,OAAO,IAAI,MAAM,CAAC,KAAK;AAC7B,uBAAe,QAAQ,CAAC,MAAM,KAAK,KAAK,CAAC;AACzC,cAAM,SAAS,aAAa,WAAW,MAAM,OAAO,QAAQ;AAC5D,cAAM,WAAW,IAAI,MAAM,SAAS,IAAI,MAAM,SAAS,IAAI,IAAI,MAAM,SAAS,IAAI,MAAM,SAAS,IAAI,EAAE;AACvG,uBAAe,MAAM,SAAS;AAC9B,uBAAe,MAAM,SAAS;AAAA,MAChC;AAAA,IACF;AACA,WAAO,CAAC,gBAAgB,gBAAgB,WAAW;AAAA,EACrD;AACF;AAGA,IAAI,UAAU,6BAA6B,CAAC,GAAG,MAAM,IAAI,CAAC;AAC1D,IAAI,iBAAiB,8BAA8B,CAAC,OAAO,OAAO,OAAO,UAAU;AACjF,SAAO,EAAE,MAAM,QAAQ,OAAO,MAAM,QAAQ,MAAM;AACpD,CAAC;AACD,IAAI,OAAO,iBAAiB,KAAK,SAAS,cAAc;AACxD,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,OAAO,aAAa,cAAc,cAAcG,OAAM;AAC1E,QAAM,cAAc,aAAa,cAAc,YAAY;AAC3D,QAAM,UAAU,aAAa,oBAAoBA,OAAM,YAAY;AACnE,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,UAAM,QAAQ,MAAM;AACpB,QAAI,QAAQ,GAAG;AACb,YAAM,IAAI,MAAM,+BAA+B;AAAA,IACjD;AACA,QAAI,SAASA,OAAM;AACjB;AAAA,IACF;AACA,QAAI,cAAc,GAAG;AACnB,cAAQ,UAAU,YAAY;AAAA,IAChC,OAAO;AACL,cAAQ,UAAU;AAAA,IACpB;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,mBAAmB,MAAM,YAAYA,OAAM,eAAe,OAAO;AACxE,QAAM,UAAU,KAAK,MAAM;AAC3B,QAAM,UAAU,KAAK,MAAM;AAC3B,QAAM,SAAS,OAAO,CAAC,SAASA,KAAI,GAAG,WAAW,KAAK;AACvD,WAAS,KAAK,GAAG,KAAK,SAAS,MAAM;AACnC,aAAS,IAAI,GAAG,IAAI,SAAS,KAAK;AAChC,YAAM,QAAQ,KAAK,IAAI,IAAI,CAAC;AAC5B,UAAI,QAAQ,GAAG;AACb,cAAM,IAAI,MAAM,+BAA+B;AAAA,MACjD;AACA,UAAI,SAASA,OAAM;AACjB;AAAA,MACF;AACA,UAAI,cAAc;AAChB,eAAO,IAAI,GAAG,IAAI,KAAK;AAAA,MACzB,OAAO;AACL,YAAI,WAAW,OAAO,GAAG;AACvB,iBAAO,IAAI,OAAO,IAAI,IAAI,KAAK,IAAI,WAAW,IAAI,IAAI,CAAC,GAAG,IAAI,KAAK;AAAA,QACrE,OAAO;AACL,iBAAO,IAAI,OAAO,IAAI,IAAI,KAAK,IAAI,GAAG,IAAI,KAAK;AAAA,QACjD;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AAGA,SAAS,sBAAsB,KAAK;AAClC,SAAO,CAAC,QAAQ,OAAO,UAAU;AAC/B,UAAM,YAAY,aAAa,uBAAuB,OAAO,OAAO,MAAM;AAC1E,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,gBAAU,MAAM,IAAI,OAAO,KAAK,KAAK;AAAA,IACvC;AACA,WAAO;AAAA,EACT;AACF;AAGA,SAAS,gBAAgB,MAAM,KAAK,OAAO;AACzC,SAAO,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AAC/C,UAAM,EAAE,EAAE,IAAI;AACd,qBAAiB,GAAG,IAAI;AACxB,QAAI,EAAE,UAAU,YAAY,UAAU,UAAU;AAC9C,YAAM,IAAI,MAAM,sDAAsD;AAAA,IACxE;AACA,UAAM,aAAa;AACnB,UAAM,SAAS,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,UAAM,SAAS,SAAS,EAAE;AAC1B,UAAM,YAAY,aAAa,kBAAkB,QAAQ,KAAK;AAC9D,aAAS,KAAK,GAAG,KAAK,OAAO,EAAE,IAAI;AACjC,gBAAU,MAAM,IAAI,OAAO,KAAK,KAAK;AAAA,IACvC;AACA,WAAO,WAAW,eAAe,EAAE,OAAO,QAAQ,SAAS;AAAA,EAC7D;AACF;AACA,SAAS,wBAAwB,MAAM,WAAW,OAAO;AACvD,SAAO,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AAC/C,UAAM,EAAE,EAAE,IAAI;AACd,qBAAiB,GAAG,IAAI;AACxB,QAAI,EAAE,UAAU,YAAY,UAAU,UAAU;AAC9C,YAAM,IAAI,MAAM,sDAAsD;AAAA,IACxE;AACA,UAAM,aAAa;AACnB,UAAM,SAAS,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,SAAS,SAAS,EAAE;AAC1B,UAAM,YAAY,UAAU,QAAQ,QAAQ,KAAK;AACjD,WAAO,WAAW,eAAe,EAAE,OAAO,QAAQ,SAAS;AAAA,EAC7D;AACF;AAGA,IAAI,WAAW,sBAAsB,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AAC1D,IAAI,QAAQ,wBAAwB,MAAM,QAAQ;AAClD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,QAAQ,UAAU,OAAO,cAAc;AACzD,QAAM,UAAU,aAAa,kBAAkB,OAAO,aAAa,cAAc,QAAQ,CAAC;AAC1F,MAAI,gBAAgB,UAAU,UAAU;AACtC,QAAI,SAAS;AACb,WAAO,QAAQ,CAAC,WAAW;AACzB,YAAMA,QAAO,aAAa,cAAc,OAAO,KAAK;AACpD,cAAQ,IAAI,OAAO,MAAM,MAAM;AAC/B,gBAAUA;AAAA,IACZ,CAAC;AAAA,EACH,OAAO;AACL,QAAI,YAAY;AAChB,WAAO,QAAQ,CAAC,WAAW;AACzB,YAAM,cAAc,UAAU,WAAW,qBAAqB,uBAAuB,OAAO,IAAI,IAAI,OAAO;AAC3G,UAAI,OAAO;AACX,eAAS,MAAM,GAAG,MAAM,OAAO,MAAM,IAAI,EAAE,KAAK;AAC9C,cAAM,SAAS,MAAM,SAAS,KAAK;AACnC,iBAAS,MAAM,GAAG,MAAM,OAAO,MAAM,IAAI,EAAE,KAAK;AAC9C,kBAAQ,SAAS,OAAO,YAAY;AAAA,QACtC;AAAA,MACF;AACA,mBAAa,OAAO,MAAM;AAAA,IAC5B,CAAC;AAAA,EACH;AACA,SAAO;AACT;AAGA,IAAI,YAAY,6BAA6B,CAAC,GAAG,MAAM,MAAM,IAAI,IAAI,CAAC;AACtE,IAAI,SAAS,iBAAiB,OAAO,WAAW,MAAM,MAAM;AAC5D,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU,sBAAsB,CAAC,OAAO,KAAK,IAAI,EAAE,CAAC;AACxD,IAAI,OAAO,wBAAwB,KAAK,SAAS,SAAS;AAC1D,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY,sBAAsB,CAAC,OAAO,KAAK,MAAM,EAAE,CAAC;AAC5D,IAAI,SAAS,wBAAwB,OAAO,SAAS;AACrD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY,sBAAsB,CAAC,OAAO,KAAK,MAAM,EAAE,CAAC;AAC5D,IAAI,SAAS,wBAAwB,OAAO,SAAS;AACrD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,aAAa,WAAW,OAAO,WAAW,WAAW,WAAWY,UAAS,aAAa,YAAY;AACtH,QAAM,SAAS,OAAO,CAAC,WAAW,SAAS,GAAG,KAAK;AACnD,WAAS,KAAK,GAAG,KAAK,WAAW,MAAM;AACrC,UAAMH,SAAQ,CAAC;AACf,QAAI,eAAe;AACnB,aAAS,IAAI,GAAG,IAAI,WAAW,KAAK;AAClC,YAAM,MAAM,YAAY,KAAK,YAAY;AACzC,sBAAgB,MAAMG,SAAQ;AAC9B,MAAAH,OAAM,KAAK,GAAG;AAAA,IAChB;AACA,QAAI,eAAe,KAAK,gBAAgB,aAAa,WAAW;AAC9D,YAAM,IAAI,MAAM,oBAAoBA,8BAA6B,aAAa;AAAA,IAChF;AACA,aAAS,IAAI,GAAG,IAAI,WAAW,KAAK;AAClC,aAAO,OAAO,KAAK,YAAY,KAAK,UAAU,IAAI,GAAG,UAAU,WAAW,eAAe,YAAY,CAAC,CAAC;AAAA,IACzG;AAAA,EACF;AACA,SAAO;AACT;AAGA,SAAS,aAAa,MAAM,YAAY,oBAAoB;AAC1D,QAAM,SAAS,OAAO,oBAAoB,KAAK,KAAK;AACpD,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM,EAAE,IAAI;AACvC,UAAM,SAAS,OAAO,WAAW,EAAE;AACnC,UAAM,cAAc,OAAO,MAAM;AACjC,UAAM,WAAW,YAAY;AAC7B,UAAM,aAAa,YAAY;AAC/B,UAAM,eAAe,WAAW,WAAW,CAAC,UAAU,UAAU,CAAC;AACjE,gBAAY,KAAK,WAAW,OAAO;AACnC,UAAM,gBAAgB,KAAK,WAAW,WAAW;AACjD,QAAI,KAAK,iBAAiB,gBAAgB,KAAK,OAAO,QAAQ;AAC5D,aAAO,OAAO,MAAM,KAAK,OAAO;AAAA,IAClC;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,cAAc,6BAA6B,CAAC,GAAG,MAAM,IAAI,IAAI,IAAI,CAAC;AACtE,IAAI,WAAW,iBAAiB,SAAS,aAAa,MAAM,MAAM;AAClE,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB,6BAA6B,CAAC,GAAG,MAAM,KAAK,IAAI,IAAI,CAAC;AAC5E,IAAI,gBAAgB,iBAAiB,cAAc,kBAAkB,MAAM,MAAM;AACjF,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW,6BAA6B,CAAC,GAAG,MAAM,IAAI,IAAI,IAAI,CAAC;AACnE,IAAI,QAAQ,iBAAiB,MAAM,UAAU,MAAM,MAAM;AACzD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,6BAA6B,CAAC,GAAG,MAAM,KAAK,IAAI,IAAI,CAAC;AACzE,IAAI,aAAa,iBAAiB,WAAW,eAAe,MAAM,MAAM;AACxE,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,OAAO,MAAM,KAAK;AACtC,QAAM,SAAS,OAAO,UAAU,MAAM;AACtC,QAAM,SAAS,aAAa,oBAAoB,KAAK,SAAS;AAC9D,SAAO,KAAK;AACZ,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,WAAO,MAAM,OAAO,KAAK,KAAK;AAAA,EAChC;AACA,SAAO;AACT;AAGA,IAAI,UAAU,sBAAsB,CAAC,OAAO,KAAK,IAAI,EAAE,CAAC;AACxD,IAAI,OAAO,wBAAwB,KAAK,OAAO;AAC/C,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,OAAO,YAAY,UAAU,OAAO;AACnD,QAAM,OAAO,aAAa,uBAAuB,OAAO,aAAa,cAAc,QAAQ,CAAC;AAC5F,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,SAAS,KAAK;AACpB,QAAI,OAAO,MAAM;AACjB,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,YAAM,QAAQ,MAAM,SAAS;AAC7B,UAAI,OAAO,MAAM,KAAK,KAAK,QAAQ,MAAM;AACvC,eAAO;AAAA,MACT;AAAA,IACF;AACA,SAAK,MAAM;AAAA,EACb;AACA,SAAO;AACT;AAGA,IAAI,cAAc,6BAA6B,CAAC,QAAQ,WAAW,KAAK,IAAI,QAAQ,MAAM,CAAC;AAC3F,IAAI,WAAW,iBAAiB,SAAS,WAAW;AACpD,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,6BAA6B,CAAC,QAAQ,WAAW,KAAK,IAAI,QAAQ,MAAM,CAAC;AAC3F,IAAI,WAAW,iBAAiB,SAAS,WAAW;AACpD,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe,6BAA6B,CAAC,QAAQ,WAAW,SAAS,MAAM;AACnF,IAAI,sBAAsB,8BAA8B,CAAC,OAAO,OAAO,OAAO,UAAU;AACtF,SAAO;AAAA,IACL,MAAM,QAAQ,QAAQ,QAAQ;AAAA,IAC9B,MAAM,QAAQ,QAAQ,QAAQ;AAAA,EAChC;AACF,CAAC;AACD,IAAI,YAAY,iBAAiB,UAAU,cAAc,mBAAmB;AAC5E,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,OAAO,QAAQ,QAAQ;AACtC,QAAM,WAAW,aAAa,kBAAkB,IAAI,MAAM;AAC1D,SAAO,aAAa,CAAC,GAAG,QAAQ,UAAU,OAAO,MAAM;AACzD;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,mBAAiB,GAAG,KAAK;AACzB,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,CAAC,KAAK,QAAQ,IAAI,QAAQ,OAAO,EAAE,OAAO,EAAE,KAAK;AACvD,SAAO,SAAS,eAAe,UAAU,EAAE,OAAO,GAAG;AACvD;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe,6BAA6B,CAAC,GAAG,MAAM,MAAM,IAAI,IAAI,CAAC;AACzE,IAAI,YAAY,iBAAiB,UAAU,cAAc,MAAM,MAAM;AACrE,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,OAAO,QAAQ,OAAO,MAAM,UAAU;AAC3D,QAAM,QAAQ,OAAO;AACrB,QAAM,QAAQ,aAAa,cAAc,MAAM;AAC/C,QAAM,WAAW,aAAa,eAAe,MAAM;AACnD,QAAM,aAAa,aAAa,eAAe,QAAQ;AACvD,QAAM,SAAS,aAAa,uBAAuB,OAAO,aAAa,cAAc,QAAQ,CAAC;AAC9F,WAAS,KAAK,GAAG,KAAK,OAAO,EAAE,IAAI;AACjC,UAAM,MAAM,aAAa,WAAW,IAAI,OAAO,QAAQ;AACvD,UAAM,SAAS,IAAI,MAAM,IAAI,MAAM;AACnC,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,aAAO,MAAM,IAAI,KAAK;AAAA,IACxB;AACA,UAAM,WAAW,aAAa,WAAW,QAAQ,OAAO,UAAU;AAClE,WAAO,YAAY,MAAM;AAAA,EAC3B;AACA,SAAO;AACT;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,mBAAiB,GAAG,WAAW;AAC/B,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,IAAI,MAAM,KAAK;AAChC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,aAAS,MAAM,EAAE,MAAM,KAAK;AAAA,EAC9B;AACA,QAAM,SAAS,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC3C,QAAM,SAAS,cAAc,QAAQ,EAAE,OAAO,EAAE,OAAO,MAAM,QAAQ;AACrE,QAAM,SAAS,SAAS,MAAM,QAAQ,UAAU,EAAE,KAAK;AACvD,SAAO,EAAE,QAAQ,OAAO,UAAU,OAAO,EAAE,MAAM;AACnD;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,QAAQ,QAAQ,OAAO,eAAe;AACtD,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,QAAQ,aAAa;AACpG,QAAM,WAAW,WAAW,QAAQ,OAAO;AAC3C,QAAM,UAAU,aAAa,oBAAoB,aAAa,cAAc,QAAQ,GAAG,QAAQ;AAC/F,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC1C,UAAM,SAAS,KAAK;AACpB,QAAI,QAAQ;AACZ,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,eAAS,MAAM,SAAS;AAAA,IAC1B;AACA,YAAQ,MAAM;AAAA,EAChB;AACA,SAAO,EAAE,SAAS,UAAU,SAAS;AACvC;AACA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,mBAAiB,GAAG,MAAM;AAC1B,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACtD,QAAM,cAAc,qBAAqB,mBAAmB,MAAM,KAAK;AACvE,MAAI,gBAAgB;AACpB,MAAI,YAAY;AAChB,QAAM,0BAA0B,CAAC;AACjC,MAAI,eAAe,MAAM;AACvB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,YAAY,EAAE,CAAC;AACzF,4BAAwB,KAAK,SAAS;AACtC,oBAAgB,qBAAqB,iBAAiB,cAAc,QAAQ,KAAK;AAAA,EACnF;AACA,QAAM,QAAQ,SAAS,KAAK,IAAI,UAAU,MAAM,EAAE;AAClD,QAAM,EAAE,SAAS,UAAU,SAAS,IAAI,SAAS,UAAU,OAAO,UAAU,OAAO,OAAO,aAAa;AACvG,MAAI,cAAc;AAClB,MAAI,UAAU;AACZ,kBAAc,qBAAqB,qBAAqB,UAAU,IAAI;AAAA,EACxE;AACA,0BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,SAAO,SAAS,eAAe,aAAa,UAAU,OAAO;AAC/D;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,OAAO,MAAM,OAAO,OAAO;AAC5C,QAAM,gBAAgB,UAAU;AAChC,QAAM,8BAA8B,QAAQ,QAAQ,QAAQ;AAC5D,QAAM,8BAA8B,OAAO,SAAS,QAAQ;AAC5D,MAAI,iBAAiB,+BAA+B,6BAA6B;AAC/E,WAAO,aAAa,oBAAoB,GAAG,KAAK;AAAA,EAClD;AACA,QAAM,cAAc,KAAK,IAAI,KAAK,MAAM,OAAO,SAAS,KAAK,CAAC;AAC9D,QAAM,SAAS,aAAa,oBAAoB,aAAa,KAAK;AAClE,MAAI,OAAO,SAAS,UAAU,GAAG;AAC/B,YAAQ;AAAA,EACV;AACA,SAAO,KAAK;AACZ,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,WAAO,MAAM,OAAO,KAAK,KAAK;AAAA,EAChC;AACA,SAAO;AACT;AAGA,IAAI,YAAY,sBAAsB,CAAC,OAAO,IAAI,KAAK,KAAK,EAAE,CAAC;AAC/D,IAAI,SAAS,wBAAwB,OAAO,SAAS;AACrD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,SAAS,SAAS,OAAOW,aAAY,WAAW,YAAY,WAAWR,UAAS,cAAc,gBAAgB;AACjI,QAAM,eAAe,CAACQ,cAAa,WAAW,SAAS;AACvD,QAAM,cAAc,QAAQ;AAC5B,QAAM,cAAc,QAAQ;AAC5B,MAAIA,gBAAe,GAAG;AACpB,WAAO,OAAO,OAAO,QAAQ,KAAK;AAAA,EACpC;AACA,QAAM,SAAS,OAAO,cAAc,QAAQ,KAAK;AACjD,MAAI,OAAO,iBAAiB,UAAU;AACpC,WAAO,OAAO,KAAK,YAAY;AAAA,EACjC,WAAW,OAAO,iBAAiB,UAAU;AAC3C,WAAO,OAAO,KAAK,YAAY;AAAA,EACjC,WAAW,OAAO,iBAAiB,WAAW;AAC5C,WAAO,OAAO,KAAK,CAAC,YAAY;AAAA,EAClC;AACA,WAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,UAAMX,SAAQ,CAAC;AACf,QAAI,eAAe;AACnB,aAAS,IAAI,GAAG,IAAI,WAAW,KAAK;AAClC,YAAM,MAAM,YAAY,KAAK,YAAY;AACzC,MAAAA,OAAM,KAAK,GAAG;AACd,sBAAgB,MAAMG,SAAQ;AAAA,IAChC;AACA,QAAI,eAAe,KAAK,gBAAgBQ,cAAa,WAAW;AAC9D,YAAM,IAAI,MAAM,oBAAoBX,8BAA6B,OAAO;AAAA,IAC1E;AACA,aAAS,IAAI,GAAG,IAAI,WAAW,KAAK;AAClC,UAAI,gBAAgB;AAClB,eAAO,OAAO,eAAe,YAAY,MAAM,YAAY,KAAK,YAAY;AAAA,MAC9E,OAAO;AACL,eAAO,OAAO,eAAe,YAAY,KAAK,QAAQ,SAAS,IAAI,YAAY,KAAK,YAAY,KAAK,YAAY;AAAA,MACnH;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,cAAc,sBAAsB,CAAC,OAAO,KAAK,IAAI,KAAK,IAAI,CAAC,EAAE,EAAE;AACvE,IAAI,WAAW,gBAAgB,SAAS,CAAC,OAAO,KAAK,IAAI,KAAK,IAAI,CAAC,EAAE,EAAE;AACvE,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM,OAAOT,OAAM,OAAO,OAAO;AAClD,QAAM,cAAc,mBAAmB,iBAAiB,OAAO,OAAOA,KAAI;AAC1E,QAAM,SAAS,aAAa,cAAcA,KAAI;AAC9C,QAAM,WAAW,aAAa,eAAe,KAAK;AAClD,MAAI,aAAa;AACf,UAAM,aAAa,mBAAmB,kBAAkB,OAAO,QAAQ;AACvE,QAAI,UAAU,UAAU;AACtB,aAAO,KAAK,MAAM,YAAY,aAAa,MAAM;AAAA,IACnD;AACA,WAAO,KAAK,SAAS,YAAY,aAAa,MAAM;AAAA,EACtD;AACA,QAAM,cAAc,UAAU,WAAW,qBAAqB,uBAAuB,IAAI,IAAI;AAC7F,QAAM,QAAQ,OAAO,OAAO,OAAO,WAAW;AAC9C,QAAM,SAAS,OAAOA,OAAM,KAAK;AACjC,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM,EAAE,IAAI;AACvC,UAAM,SAAS,OAAO,WAAW,EAAE;AACnC,UAAM,QAAQ,OAAO,IAAI,CAAC,KAAK,MAAM,MAAM,MAAM,EAAE;AACnD,WAAO,IAAI,MAAM,IAAI,GAAG,KAAK,GAAG,GAAG,MAAM;AAAA,EAC3C;AACA,MAAI,UAAU,UAAU;AACtB,WAAO,qBAAqB,uBAAuB,OAAO,MAAM;AAAA,EAClE;AACA,SAAO,OAAO;AAChB;AACA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAO,MAAAA,MAAK,IAAI;AACxB,mBAAiB,GAAG,OAAO;AAC3B,QAAM,CAAC,QAAQ,KAAK,IAAI,mBAAmB,iBAAiB,GAAG,OAAOA,KAAI;AAC1E,qBAAmB,kBAAkB,GAAG,QAAQ,KAAK;AACrD,QAAM,OAAO,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AACzC,QAAM,UAAU,UAAU,MAAM,QAAQ,OAAO,EAAE,OAAO,EAAE,KAAK;AAC/D,SAAO,SAAS,eAAe,OAAO,EAAE,OAAO,OAAO;AACxD;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,wBAAwB,SAAS,cAAc,cAAc,QAAQ,aAAa,YAAY,cAAc;AACnH,QAAM,eAAe,aAAa;AAClC,QAAM,YAAY,WAAW;AAC7B,QAAM,oBAAoB,IAAI,MAAM,SAAS;AAC7C,QAAM,kBAAkB,IAAI,MAAM,YAAY;AAC9C,QAAM,OAAO,aAAa;AAC1B,MAAI,cAAc,GAAG;AACnB,QAAI,iBAAiB,GAAG;AACtB,YAAM,IAAI,MAAM,qBAAqB,gDAAgD,YAAY,CAAC;AAAA,IACpG;AACA,UAAM,gBAAgB,aAAa,kBAAkB,cAAc,CAAC;AACpE,UAAM,eAAe,aAAa,kBAAkB,aAAa,CAAC;AAClE,WAAO;AAAA,MACL;AAAA,MACA,CAAC,GAAG,IAAI;AAAA,MACR;AAAA,MACA;AAAA,MACA;AAAA,IACF;AAAA,EACF;AACA,MAAI,iBAAiB;AACrB,MAAI,iBAAiB;AACrB,QAAM,YAAY,IAAI,MAAM,SAAS,EAAE,KAAK,CAAC;AAC7C,WAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,UAAM,MAAM,QAAQ,KAAK;AACzB,QAAI,MAAM,GAAG;AACX,YAAM,IAAI,MAAM,qBAAqB,gDAAgD,IAAI,GAAG,CAAC;AAAA,IAC/F;AACA,QAAI,OAAO,WAAW;AACpB,YAAM,IAAI,MAAM,qBAAqB,kDAAkD,IAAI,KAAK,SAAS,CAAC;AAAA,IAC5G;AACA,MAAE,UAAU;AACZ,qBAAiB,kBAAkB,OAAO;AAC1C,qBAAiB;AAAA,EACnB;AACA,MAAI,cAAc;AAClB,WAAS,MAAM,GAAG,MAAM,WAAW,EAAE,KAAK;AACxC,UAAM,WAAW,UAAU,SAAS;AACpC,sBAAkB,OAAO;AACzB,kBAAc,eAAe,CAAC;AAC9B,cAAU,OAAO,KAAK,IAAI,UAAU,MAAM,CAAC;AAC3C,QAAI,MAAM,GAAG;AACX,gBAAU,QAAQ,UAAU,MAAM;AAAA,IACpC;AAAA,EACF;AACA,MAAI,eAAe,gBAAgB;AACjC,UAAM,gBAAgB;AACtB,UAAM,eAAe;AACrB,aAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,sBAAgB,MAAM;AAAA,IACxB;AACA,WAAO;AAAA,MACL;AAAA,MACA,CAAC,cAAc,IAAI;AAAA,MACnB;AAAA,MACA;AAAA,MACA;AAAA,IACF;AAAA,EACF,OAAO;AACL,UAAM,mBAAmB,UAAU,YAAY;AAC/C,UAAM,gBAAgB,aAAa,kBAAkB,cAAc,mBAAmB,IAAI;AAC1F,UAAM,eAAe,aAAa,kBAAkB,aAAa,gBAAgB;AACjF,UAAM,cAAc,IAAI,MAAM,SAAS,EAAE,KAAK,CAAC;AAC/C,aAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,YAAM,MAAM,QAAQ,KAAK;AACzB,YAAM,SAAS,YAAY;AAC3B,YAAM,WAAW,QAAQ,IAAI,IAAI,UAAU,MAAM,MAAM;AACvD,kBAAY;AACZ,eAAS,IAAI,GAAG,IAAI,MAAM,EAAE,GAAG;AAC7B,sBAAc,UAAU,OAAO,KAAK,QAAQ,KAAK,OAAO;AAAA,MAC1D;AACA,mBAAa,WAAW,OAAO;AAC/B,sBAAgB,MAAM;AAAA,IACxB;AACA,aAAS,MAAM,GAAG,MAAM,WAAW,EAAE,KAAK;AACxC,YAAM,WAAW,YAAY;AAC7B,UAAI,aAAa,GAAG;AAClB,cAAM,gBAAgB,QAAQ,IAAI,IAAI,UAAU,MAAM;AACtD,sBAAc,gBAAgB,OAAO,KAAK;AAC1C,iBAAS,MAAM,GAAG,MAAM,MAAM,EAAE,KAAK;AACnC,wBAAc,gBAAgB,OAAO,OAAO;AAAA,QAC9C;AACA,qBAAa,iBAAiB;AAAA,MAChC;AAAA,IACF;AACA,WAAO;AAAA,MACL;AAAA,MACA,CAAC,kBAAkB,IAAI;AAAA,MACvB;AAAA,MACA;AAAA,MACA;AAAA,IACF;AAAA,EACF;AACF;AAGA,SAAS,kBAAkB,cAAc,mBAAmB,YAAY,YAAY,aAAa;AAC/F,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,MAAM,kBAAkB;AAC9B,QAAM,aAAa,YAAY;AAC/B,QAAM,cAAc,CAAC;AACrB,MAAI,UAAU;AACd,MAAI,eAAe;AACnB,WAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,UAAMA,QAAO,YAAY;AACzB,QAAIA,UAAS,IAAI;AACf,UAAI,iBAAiB,IAAI;AACvB,cAAM,IAAI,MAAM,qBAAqB,yDAAyD,cAAc,CAAC,CAAC;AAAA,MAChH;AACA,qBAAe;AACf,kBAAY,KAAK,CAAC;AAAA,IACpB,OAAO;AACL,UAAIA,QAAO,GAAG;AACZ,cAAM,IAAI,MAAM,qBAAqB,8CAA8C,GAAGA,KAAI,CAAC;AAAA,MAC7F;AACA,iBAAWA;AACX,kBAAY,KAAKA,KAAI;AAAA,IACvB;AAAA,EACF;AACA,MAAI,iBAAiB,IAAI;AACvB,QAAI,WAAW,GAAG;AAChB,YAAM,IAAI,MAAM,qBAAqB,qDAAqD,CAAC;AAAA,IAC7F;AACA,UAAM,UAAU,KAAK,MAAM,YAAY,OAAO;AAC9C,QAAI,UAAU,YAAY,WAAW;AACnC,YAAM,IAAI,MAAM,qBAAqB,gDAAgD,YAAY,WAAW,CAAC;AAAA,IAC/G;AACA,gBAAY,gBAAgB;AAAA,EAC9B;AACA,QAAMoB,cAAa,aAAa,cAAc,WAAW;AACzD,MAAIA,gBAAe,WAAW;AAC5B,UAAM,IAAI,MAAM,qBAAqB,gDAAgD,YAAY,WAAW,CAAC;AAAA,EAC/G;AACA,QAAM,YAAY,WAAW;AAC7B,QAAM,eAAe,CAAC;AACtB,MAAI,YAAY,GAAG;AACjB,iBAAa,YAAY,KAAK;AAC9B,aAAS,IAAI,YAAY,GAAG,KAAK,GAAG,EAAE,GAAG;AACvC,mBAAa,KAAK,aAAa,IAAI,KAAK,WAAW,IAAI;AAAA,IACzD;AAAA,EACF;AACA,QAAM,gBAAgB,CAAC;AACvB,MAAI,aAAa,GAAG;AAClB,kBAAc,aAAa,KAAK;AAChC,aAAS,IAAI,aAAa,GAAG,KAAK,GAAG,EAAE,GAAG;AACxC,oBAAc,KAAK,cAAc,IAAI,KAAK,YAAY,IAAI;AAAA,IAC5D;AAAA,EACF;AACA,QAAM,aAAa,aAAa,kBAAkB,YAAY,MAAM,UAAU;AAC9E,WAAS,KAAK,GAAG,KAAK,KAAK,EAAE,IAAI;AAC/B,QAAI,KAAK;AACT,aAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,YAAM,aAAa,KAAK,YAAY,KAAK,aAAa;AAAA,IACxD;AACA,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,iBAAW,KAAK,aAAa,KAAK,KAAK,MAAM,KAAK,cAAc,EAAE;AAClE,YAAM,cAAc;AAAA,IACtB;AAAA,EACF;AACA,SAAO,CAAC,YAAY,CAAC,KAAK,UAAU,GAAG,WAAW;AACpD;AAGA,SAAS,2BAA2B,QAAQ,YAAY,YAAY,SAAS,YAAY,SAAS,OAAO,eAAe,GAAG;AACzH,QAAM,aAAa,QAAQ;AAC3B,QAAM,YAAY,CAAC,WAAW,IAAI,OAAO,SAAS,WAAW,EAAE;AAC/D,QAAM,SAAS,UAAU;AACzB,QAAM,uBAAuB,aAAa,IAAI,WAAW,aAAa,KAAK,IAAI;AAC/E,QAAM,aAAa;AACnB,MAAI,aAAa,GAAG;AAClB,UAAM,IAAI,MAAM,qBAAqB,wDAAwD,CAAC;AAAA,EAChG;AACA,QAAM,cAAc,WAAW,MAAM;AACrC,cAAY,KAAK;AACjB,QAAM,eAAe,YAAY,OAAO,CAAC,SAAS,UAAU,UAAU,OAAO,CAAC;AAC9E,QAAM,SAAS,aAAa,kBAAkB,YAAY,YAAY;AACtE,MAAI,eAAe,GAAG;AACpB,QAAI,aAAa,GAAG;AAClB,aAAO,KAAK,YAAY;AAAA,IAC1B;AACA,WAAO,CAAC,QAAQ,WAAW;AAAA,EAC7B;AACA,MAAI,cAAc,GAAG;AACnB,UAAM,IAAI,MAAM,qBAAqB,wDAAwD,CAAC;AAAA,EAChG;AACA,MAAI,QAAQ,GAAG,MAAM;AACrB,MAAI,qBAAqB;AACzB,MAAI,WAAW,WAAW;AAC1B,SAAO,MAAM;AACX,QAAI,YAAY;AAChB,QAAI,MAAM,YAAY;AACpB,kBAAY,WAAW;AACvB,UAAI,aAAa,WAAW;AAC1B,UAAE;AACF;AAAA,MACF;AACA,UAAI,YAAY,WAAW;AACzB,cAAM,IAAI,MAAM,qBAAqB,6DAA6D,CAAC;AAAA,MACrG;AAAA,IACF;AACA,QAAI,WAAW,KAAK,YAAY,YAAY;AAC1C,YAAM,IAAI,MAAM,qBAAqB,yDAAyD,UAAU,UAAU,CAAC;AAAA,IACrH;AACA,QAAI,WAAW,oBAAoB;AACjC,aAAO,KAAK,cAAc,qBAAqB,QAAQ,WAAW,MAAM;AAAA,IAC1E;AACA,aAAS,KAAK,OAAO,KAAK,KAAK,EAAE,IAAI;AACnC,YAAMX,SAAQ,QAAQ;AACtB,UAAIA,SAAQ,KAAKA,UAAS,UAAU,IAAI;AACtC,cAAM,IAAI,MAAM,qBAAqB,uDAAuD,IAAI,QAAQ,KAAK,UAAU,EAAE,CAAC;AAAA,MAC5H;AACA,eAAS,IAAI,GAAG,IAAI,QAAQ,KAAK;AAC/B,eAAO,WAAW,SAAS,MAAM,OAAOA,SAAQ,SAAS;AAAA,MAC3D;AAAA,IACF;AACA,QAAI,QAAQ;AACV,eAAS,IAAI,GAAG,IAAI,QAAQ,KAAK;AAC/B,eAAO,WAAW,SAAS,MAAM,MAAM;AAAA,MACzC;AAAA,IACF;AACA,YAAQ;AACR,MAAE;AACF,yBAAqB,WAAW;AAChC,eAAW;AACX,QAAI,MAAM,YAAY;AACpB;AAAA,IACF;AAAA,EACF;AACA,MAAI,qBAAqB,YAAY;AACnC,WAAO,KAAK,cAAc,qBAAqB,QAAQ,aAAa,MAAM;AAAA,EAC5E;AACA,SAAO,CAAC,QAAQ,WAAW;AAC7B;AAGA,IAAI,WAAW,sBAAsB,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AAC1D,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,wBAAwB,6BAA6B,CAAC,GAAG,MAAM;AACjE,QAAM,OAAO,IAAI;AACjB,SAAO,OAAO;AAChB,CAAC;AACD,IAAI,qBAAqB,iBAAiB,mBAAmB,qBAAqB;AAClF,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,iBAAiB,UAAU,MAAMG,UAAS,OAAO;AACxD,QAAM,SAAS,OAAO,UAAU,KAAK,KAAK;AAC1C,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM,MAAM;AACvC,UAAM,MAAM,OAAO,WAAW,EAAE;AAChC,UAAM,SAAS,IAAI,MAAM,IAAI,MAAM;AACnC,aAAS,IAAI,GAAG,IAAI,OAAO,QAAQ,KAAK;AACtC,aAAO,KAAK,IAAI,KAAKA,SAAQ,KAAK,MAAM;AAAA,IAC1C;AACA,WAAO,IAAI,KAAK,IAAI,GAAG,MAAM,GAAG,GAAG,GAAG;AAAA,EACxC;AACA,SAAO;AACT;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,WAAW,aAAa,SAAS,WAAW,UAAU,wBAAwB;AACxF,SAAK,YAAY,aAAa,aAAa,SAAS;AACpD,SAAK,cAAc;AACnB,SAAK,UAAU,aAAa,aAAa,OAAO;AAChD,SAAK,WAAW,aAAa,aAAa,SAAS;AACnD,SAAK,WAAW;AAChB,SAAK,gBAAgB;AAAA,EACvB;AAAA,EACA,YAAY,YAAY;AACtB,WAAO,KAAK,IAAI,KAAK,WAAW,IAAI,aAAa,IAAI,KAAK,UAAU,aAAa,CAAC;AAAA,EACpF;AAAA,EACA,aAAa,QAAQ,YAAY;AAC/B,UAAM,WAAW,KAAK,YAAY,UAAU;AAC5C,WAAO,KAAK,IAAI,GAAG,SAAS,IAAI,WAAW,aAAa,CAAC;AAAA,EAC3D;AAAA,EACA,aAAa,MAAM,YAAY,QAAQ,kBAAkB,WAAW,YAAY;AAC9E,aAAS,aAAa,GAAG,aAAa,WAAW,EAAE,YAAY;AAC7D,YAAM,WAAW,KAAK,YAAY,UAAU;AAC5C,YAAM,cAAc,KAAK,IAAI,GAAG,WAAW,UAAU;AACrD,YAAM,eAAe,KAAK,IAAI,GAAG,YAAY,aAAa,aAAa,GAAG;AAC1E,YAAM,YAAY,cAAc,cAAc;AAC9C,YAAM,iBAAiB,cAAc,cAAc,IAAI,IAAI,aAAa;AACxE,UAAI,YAAY;AAChB,mBAAa,cAAc,KAAK,QAAQ;AACxC,eAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,qBAAa,KAAK,iBAAiB,IAAI;AAAA,MACzC;AACA,mBAAa,eAAe,KAAK,SAAS;AAC1C,YAAM,gBAAgB,cAAc,eAAe,YAAY;AAC/D,mBAAa,gBAAgB,KAAK,UAAU;AAC5C,aAAO,mBAAmB,cAAc,IAAI,WAAW,SAAS;AAChE,YAAM,QAAQ,OAAO,mBAAmB;AACxC,UAAI,iBAAiB;AACrB,YAAM,gBAAgB,CAAC,QAAQ,IAAI,QAAQ,CAAC,UAAU,MAAM,oBAAoB,KAAK;AACrF,eAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,sBAAc,KAAK,OAAO;AAC1B,sBAAc,KAAK,SAAS;AAAA,MAC9B;AACA,eAAS,KAAK,GAAG,KAAK,YAAY,GAAG,EAAE,IAAI;AACzC,sBAAc,KAAK,iBAAiB,GAAG;AACvC,sBAAc,KAAK,SAAS;AAAA,MAC9B;AACA,UAAI,YAAY,GAAG;AACjB,sBAAc,KAAK,iBAAiB,YAAY,EAAE;AAClD,iBAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,wBAAc,KAAK,SAAS;AAC5B,wBAAc,KAAK,QAAQ;AAAA,QAC7B;AAAA,MACF,OAAO;AACL,iBAAS,KAAK,GAAG,KAAK,eAAe,GAAG,EAAE,IAAI;AAC5C,wBAAc,KAAK,QAAQ;AAC3B,wBAAc,KAAK,SAAS;AAAA,QAC9B;AACA,sBAAc,KAAK,QAAQ;AAAA,MAC7B;AAAA,IACF;AAAA,EACF;AAAA,EACA,QAAQ,MAAM,QAAQ;AACpB,UAAM,gBAAgB,KAAK;AAC3B,UAAM,aAAa,OAAO;AAC1B,QAAI,aAAa,GAAG;AAClB,UAAI,YAAY,OAAO;AACvB,UAAI,cAAc,GAAG;AACnB,cAAM,IAAI,MAAM,oCAAoC,WAAW;AAAA,MACjE;AACA,eAAS,KAAK,GAAG,KAAK,YAAY,EAAE,IAAI;AACtC,YAAI,cAAc,OAAO,OAAO;AAChC,sBAAc,eAAe,OAAO,OAAO;AAC3C,YAAI,CAAC,aAAa;AAChB,gBAAM,IAAI,MAAM,uBAAuB,OAAO,oBAAoB,cAAc,gBAAgB;AAAA,QAClG;AACA,oBAAY,OAAO;AAAA,MACrB;AACA,UAAI,cAAc,eAAe;AAC/B,cAAM,IAAI,MAAM,gDAAgD,sBAAsB,WAAW;AAAA,MACnG;AAAA,IACF;AACA,UAAM,gBAAgB,aAAa;AACnC,UAAM,eAAe,aAAa,kBAAkB,SAAS,UAAU;AACvE,QAAI,kBAAkB,KAAK,eAAe,GAAG;AAC3C,YAAM,QAAQ,IAAI,MAAM,aAAa;AACrC,eAAS,KAAK,GAAG,MAAM,eAAe,EAAE,IAAI;AAC1C,qBAAa,MAAM;AAAA,MACrB;AACA,aAAO,CAAC,OAAO,YAAY;AAAA,IAC7B;AACA,iBAAa,KAAK;AAClB,aAAS,KAAK,GAAG,MAAM,eAAe,EAAE,IAAI;AAC1C,YAAM,SAAS,OAAO,MAAM,OAAO,KAAK;AACxC,UAAI,YAAY;AAChB,WAAK,YAAY,QAAQ,CAAC,eAAe;AACvC,qBAAa,KAAK,aAAa,QAAQ,UAAU;AAAA,MACnD,CAAC;AACD,UAAI,KAAK,iBAAiB,SAAS,KAAK,cAAc,GAAG;AACvD,oBAAY;AAAA,MACd;AACA,mBAAa,MAAM,aAAa,KAAK,KAAK;AAAA,IAC5C;AACA,UAAM,SAAS,IAAI,MAAM,aAAa,cAAc;AACpD,aAAS,KAAK,GAAG,KAAK,eAAe,EAAE,IAAI;AACzC,YAAM,aAAa,OAAO;AAC1B,UAAI,iBAAiB,aAAa;AAClC,WAAK,YAAY,QAAQ,CAAC,eAAe;AACvC,cAAM,SAAS,OAAO,KAAK,KAAK,OAAO;AACvC,cAAM,YAAY,KAAK,aAAa,QAAQ,UAAU;AACtD,aAAK,aAAa,MAAM,YAAY,QAAQ,gBAAgB,WAAW,UAAU;AACjF,0BAAkB;AAAA,MACpB,CAAC;AACD,UAAI,KAAK,iBAAiB,mBAAmB,aAAa,KAAK;AAC7D,cAAM,aAAa,OAAO,KAAK,KAAK,OAAO;AAC3C,YAAI,eAAe,GAAG;AACpB;AAAA,QACF;AACA,cAAM,aAAa,aAAa,IAAI,KAAK;AACzC,cAAM,YAAY;AAClB,aAAK,aAAa,MAAM,YAAY,QAAQ,gBAAgB,WAAW,UAAU;AAAA,MACnF;AAAA,IACF;AACA,WAAO,CAAC,QAAQ,YAAY;AAAA,EAC9B;AACF;AACA,SAAS,iBAAiB,MAAM,YAAY,WAAW,aAAa,SAAS,WAAW,UAAU,wBAAwB;AACxH,SAAO,IAAI,eAAe,WAAW,aAAa,SAAS,WAAW,UAAU,sBAAsB,EAAE,QAAQ,MAAM,UAAU;AAClI;AAGA,SAAS,OAAO,KAAK,YAAY,WAAW,QAAQ;AAClD,MAAI,CAAC,IAAI,QAAQ;AACf;AAAA,EACF;AACA,MAAI,WAAW,WAAW,GAAG;AAC3B,aAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,EAAE,IAAI;AACtC,aAAO,KAAK,IAAI,SAAS,IAAI,KAAK,CAAC,CAAC;AAAA,IACtC;AACA;AAAA,EACF;AACA,MAAI,WAAW,WAAW,GAAG;AAC3B,UAAM,YAAY,WAAW;AAC7B,QAAI,IAAI,IAAI,QAAQ,SAAS;AAC7B,WAAO,MAAM,IAAI;AACf,YAAM,QAAQ,IAAI,SAAS,GAAG,CAAC;AAC/B,UAAI,CAAC,aAAa,MAAM,WAAW,GAAG;AACpC,eAAO,KAAK,KAAK;AAAA,MACnB;AACA,YAAM,IAAI,SAAS,IAAI,CAAC;AACxB,UAAI,IAAI,QAAQ,SAAS;AAAA,IAC3B;AACA,QAAI,CAAC,aAAa,IAAI,WAAW,GAAG;AAClC,aAAO,KAAK,GAAG;AAAA,IACjB;AACA;AAAA,EACF;AACA,MAAI,aAAa;AACjB,WAAS,KAAK,GAAG,KAAK,IAAI,SAAS,GAAG,MAAM;AAC1C,QAAI,OAAO,IAAI,UAAU,WAAW,QAAQ,IAAI,GAAG,MAAM,IAAI;AAC3D,YAAM,QAAQ,IAAI,SAAS,YAAY,EAAE;AACzC,UAAI,CAAC,aAAa,MAAM,WAAW,GAAG;AACpC,eAAO,KAAK,KAAK;AAAA,MACnB;AACA,mBAAa,KAAK;AAAA,IACpB;AAAA,EACF;AACF;AACA,SAAS,gBAAgB,QAAQ,WAAW,WAAW;AACrD,QAAM,YAAY,OAAO;AACzB,QAAM,SAAS,CAAC;AAChB,MAAIQ,cAAa;AACjB,MAAI,gBAAgB;AACpB,QAAM,aAAa,IAAI,MAAM,SAAS;AACtC,WAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,UAAM,mBAAmB,OAAO;AAChC,WAAO,OAAO,KAAK,WAAW,WAAW,MAAM;AAC/C,UAAM,WAAW,OAAO,SAAS;AACjC,eAAW,MAAM;AACjB,IAAAA,eAAc;AACd,oBAAgB,KAAK,IAAI,eAAe,QAAQ;AAAA,EAClD;AACA,QAAM,UAAU,aAAa,kBAAkB,SAASA,cAAa,CAAC;AACtE,QAAM,SAAS,IAAI,MAAMA,WAAU;AACnC,QAAM,QAAQ,CAAC,WAAW,aAAa;AACvC,MAAI,IAAI;AACR,WAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,aAAS,IAAI,GAAG,IAAI,WAAW,KAAK,EAAE,GAAG;AACvC,cAAQ,IAAI,KAAK;AACjB,cAAQ,IAAI,IAAI,KAAK;AACrB,aAAO,KAAK,OAAO;AACnB,QAAE;AAAA,IACJ;AAAA,EACF;AACA,SAAO,CAAC,SAAS,QAAQ,KAAK;AAChC;AAGA,SAAS,2BAA2B,QAAQ,YAAY;AACtD,QAAM,SAAS,aAAa,kBAAkB,SAAS,OAAO,MAAM;AACpE,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,WAAO,MAAM,aAAa,cAAc,OAAO,GAAG,EAAE,OAAO,UAAU,EAAE,mBAAmB;AAAA,EAC5F;AACA,SAAO;AACT;AAGA,IAAI,UAAU,6BAA6B,CAAC,QAAQ,WAAW,SAAS,MAAM;AAC9E,IAAI,iBAAiB,8BAA8B,CAAC,OAAO,OAAO,OAAO,UAAU;AACjF,SAAO,EAAE,MAAM,QAAQ,OAAO,MAAM,QAAQ,MAAM;AACpD,CAAC;AACD,IAAI,OAAO,iBAAiB,KAAK,SAAS,cAAc;AACxD,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM,MAAM;AAC5B,QAAM,WAAW,IAAI,MAAM,KAAK,IAAI;AACpC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,aAAS,MAAM,KAAK,MAAM,MAAM,KAAK;AAAA,EACvC;AACA,QAAM,SAAS,OAAO,UAAU,KAAK,KAAK;AAC1C,WAAS,KAAK,GAAG,KAAK,OAAO,OAAO,QAAQ,EAAE,IAAI;AAChD,UAAM,SAAS,OAAO,WAAW,EAAE;AACnC,UAAM,cAAc,IAAI,MAAM,KAAK,IAAI;AACvC,aAAS,IAAI,GAAG,IAAI,YAAY,QAAQ,KAAK;AAC3C,kBAAY,KAAK,OAAO,KAAK,KAAK,MAAM;AAAA,IAC1C;AACA,UAAM,gBAAgB,KAAK,WAAW,WAAW;AACjD,WAAO,OAAO,MAAM,KAAK,OAAO;AAAA,EAClC;AACA,SAAO;AACT;AAGA,IAAI,cAAc,CAAC,GAAG,MAAM;AAC1B,QAAM,YAAY,EAAE,QAAQ,EAAE;AAC9B,SAAO,cAAc,IAAI,EAAE,QAAQ,EAAE,QAAQ;AAC/C;AACA,SAAS,OAAO,QAAQ,GAAG,OAAO,GAAG,QAAQ,OAAO,SAAS,GAAG;AAC9D,SAAO,QAAQ,MAAM;AACnB,QAAI,QAAQ,OAAO,KAAK;AACtB,YAAM,KAAK,QAAQ,OAAO;AAC1B,YAAM,KAAK,IAAI,OAAO;AACtB,YAAM,IAAI,KAAK,IAAI,EAAE;AACrB,YAAM,KAAK,MAAM,KAAK,IAAI,IAAI,IAAI,CAAC;AACnC,YAAM,KAAK,MAAM,KAAK,KAAK,IAAI,MAAM,KAAK,MAAM,EAAE,IAAI,KAAK,KAAK,KAAK,KAAK,CAAC;AAC3E,YAAM,UAAU,KAAK,IAAI,MAAM,KAAK,MAAM,IAAI,KAAK,KAAK,KAAK,EAAE,CAAC;AAChE,YAAM,WAAW,KAAK,IAAI,OAAO,KAAK,MAAM,KAAK,KAAK,MAAM,KAAK,KAAK,EAAE,CAAC;AACzE,aAAO,QAAQ,GAAG,SAAS,QAAQ;AAAA,IACrC;AACA,UAAM,KAAK,OAAO;AAClB,QAAI,KAAK;AACT,QAAI,IAAI;AACR,iBAAa,KAAK,QAAQ,MAAM,CAAC;AACjC,QAAI,YAAY,OAAO,QAAQ,EAAE,IAAI,GAAG;AACtC,mBAAa,KAAK,QAAQ,MAAM,KAAK;AAAA,IACvC;AACA,WAAO,KAAK,GAAG;AACb,mBAAa,KAAK,QAAQ,IAAI,CAAC;AAC/B;AACA;AACA,aAAO,YAAY,OAAO,KAAK,EAAE,IAAI,GAAG;AACtC,aAAK,KAAK;AAAA,MACZ;AACA,aAAO,YAAY,OAAO,IAAI,EAAE,IAAI,GAAG;AACrC,YAAI,IAAI;AAAA,MACV;AAAA,IACF;AACA,QAAI,YAAY,OAAO,OAAO,EAAE,MAAM,GAAG;AACvC,mBAAa,KAAK,QAAQ,MAAM,CAAC;AAAA,IACnC,OAAO;AACL,UAAI,IAAI;AACR,mBAAa,KAAK,QAAQ,GAAG,KAAK;AAAA,IACpC;AACA,QAAI,KAAK,GAAG;AACV,aAAO,IAAI;AAAA,IACb;AACA,QAAI,KAAK,GAAG;AACV,cAAQ,IAAI;AAAA,IACd;AAAA,EACF;AACF;AACA,SAAS,SAAS,GAAG,QAAQ,QAAQ,GAAG,QAAQ;AAC9C,QAAM,UAAU,OAAO,OAAO,SAAS;AACvC,QAAM,CAAC,OAAOpB,KAAI,IAAI,CAAC,EAAE,SAAS,SAAS,OAAO;AAClD,QAAM,cAAc,aAAa,uBAAuB,QAAQ,QAAQ,CAAC;AACzE,QAAM,iBAAiB,aAAa,uBAAuB,SAAS,QAAQ,CAAC;AAC7E,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,UAAM,SAAS,IAAIA;AACnB,UAAM,OAAO,EAAE,SAAS,QAAQ,SAASA,KAAI;AAC7C,QAAI,YAAY,IAAI,MAAM,KAAK,MAAM;AACrC,SAAK,QAAQ,CAAC,OAAOS,WAAU,UAAUA,UAAS,EAAE,OAAO,OAAAA,OAAM,CAAC;AAClE,QAAI,IAAI,UAAU,QAAQ;AACxB,aAAO,WAAW,CAAC;AACnB,kBAAY,UAAU,MAAM,GAAG,CAAC;AAAA,IAClC;AACA,QAAI,QAAQ;AACV,gBAAU,KAAK,WAAW;AAAA,IAC5B;AACA,UAAM,YAAY,IAAI;AACtB,UAAM,WAAW,YAAY,SAAS,WAAW,YAAY,CAAC;AAC9D,UAAM,cAAc,eAAe,SAAS,WAAW,YAAY,CAAC;AACpE,aAAS,KAAK,GAAG,KAAK,GAAG,MAAM;AAC7B,eAAS,MAAM,UAAU,IAAI;AAC7B,kBAAY,MAAM,UAAU,IAAI;AAAA,IAClC;AAAA,EACF;AACA,QAAM,cAAc,OAAO,MAAM;AACjC,cAAY,YAAY,SAAS,KAAK;AACtC,SAAO;AAAA,IACL,OAAO,aAAa,QAAQ,WAAW;AAAA,IACvC,OAAO,aAAa,SAAS,cAAc;AAAA,EAC7C;AACF;AAGA,SAAS,WAAW,QAAQ,MAAM,OAAO,OAAO;AAC9C,QAAM,QAAQ,aAAa,eAAe,MAAM,KAAK,EAAE;AACvD,QAAM,WAAW,CAAC,GAAG,MAAM,IAAI,CAAC;AAChC,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM;AACjC,aAAS,MAAM,MAAM;AAAA,EACvB;AACA,WAAS,KAAK,MAAM;AACpB,WAAS,KAAK,QAAQ,GAAG,KAAK,MAAM,QAAQ,MAAM;AAChD,aAAS,MAAM,MAAM;AAAA,EACvB;AACA,QAAM,iBAAiB,CAAC;AACxB,QAAM,UAAU,IAAI,WAAW,MAAM,MAAM;AAC3C,QAAM,cAAc,IAAI,aAAa,UAAU,OAAO,MAAM;AAC5D,QAAM,gBAAgB,CAAC;AACvB,QAAM,aAAa,SAAS,OAAO,KAAK,SAAS,OAAO;AACxD,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,QAAI;AACJ,QAAI,YAAY;AACd,gBAAU,OAAO,IAAI,SAAS;AAAA,IAChC,OAAO;AACL,YAAM,aAAa,CAAC;AACpB,eAAS,IAAI,GAAG,IAAI,SAAS,IAAI,KAAK;AACpC,iBAAS,KAAK,GAAG,KAAK,SAAS,IAAI,MAAM;AACvC,qBAAW,KAAK,YAAY,IAAI,GAAG,IAAI,EAAE,CAAC;AAAA,QAC5C;AAAA,MACF;AACA,gBAAU,WAAW,KAAK,GAAG;AAAA,IAC/B;AACA,QAAI,eAAe,aAAa,QAAQ;AACtC,cAAQ,MAAM,eAAe;AAAA,IAC/B,OAAO;AACL,YAAM,cAAc,OAAO,KAAK,cAAc,EAAE;AAChD,qBAAe,WAAW;AAC1B,cAAQ,MAAM;AACd,oBAAc,KAAK,EAAE;AAAA,IACvB;AAAA,EACF;AACA,QAAM,iBAAiB,SAAS,MAAM;AACtC,iBAAe,KAAK,OAAO,KAAK,cAAc,EAAE;AAChD,QAAM,eAAe,IAAI,aAAa,gBAAgB,KAAK;AAC3D,gBAAc,QAAQ,CAAC,oBAAoB,OAAO;AAChD,aAAS,IAAI,GAAG,IAAI,SAAS,IAAI,KAAK;AACpC,eAAS,KAAK,GAAG,KAAK,SAAS,IAAI,MAAM;AACvC,qBAAa,IAAI,YAAY,IAAI,GAAG,oBAAoB,EAAE,GAAG,GAAG,IAAI,EAAE;AAAA,MACxE;AAAA,IACF;AAAA,EACF,CAAC;AACD,QAAM,cAAc,MAAM,MAAM;AAChC,cAAY,SAAS,eAAe;AACpC,SAAO;AAAA,IACL,cAAc,aAAa;AAAA,IAC3B;AAAA,IACA;AAAA,EACF;AACF;AAGA,gBAAgB,OAAO,MAAM,IAAI,eAAe,GAAG,CAAC;AAGpD,IAAI,OAAO,gBAAgB,KAAK,CAAC,OAAO,MAAM,IAAI,KAAK,KAAK,IAAI,EAAE,IAAI,CAAC;AACvE,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAAa,OAAM,IAAI;AAClB,mBAAiB,CAAC,CAAC,GAAG,WAAW;AACjC,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,UAAU,aAAa,uBAAuB,WAAW,KAAK;AACpE,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,YAAQ,MAAM,MAAM,MAAM,IAAIA,SAAQ,MAAM,MAAM,MAAM;AAAA,EAC1D;AACA,SAAO,SAAS,eAAe,EAAE,OAAO,WAAW,OAAO;AAC5D;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY,6BAA6B,CAAC,QAAQ,WAAW,SAAS,IAAI,SAAS,SAAS,MAAM;AACtG,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,GAAG,OAAAA,OAAM,IAAI;AACrB,mBAAiB,CAAC,GAAGA,MAAK,GAAG,OAAO;AACpC,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,QAAQ,SAAS,KAAK,IAAIA,OAAM,MAAM,EAAE;AAC9C,QAAM,CAAC,YAAY,WAAW,IAAI,UAAU,EAAE,OAAOA,OAAM,OAAO,OAAO,OAAO,SAAS;AACzF,SAAO,SAAS,eAAe,aAAa,WAAW,UAAU;AACnE;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,IAAI,GAAG,EAAE,CAAC;AACzD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO,KAAK,IAAI,KAAK,IAAI,GAAG,EAAE,GAAG,CAAC,CAAC;AACxE,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,iBAAiB,UAAU,GAAG,aAAa,wBAAwB,gBAAgB;AAC1F,MAAI,gBAAgB,UAAU;AAC5B,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD,WAAW,gBAAgB,QAAQ;AACjC,WAAO,MAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACnD,WAAW,gBAAgB,OAAO;AAChC,WAAO,KAAK,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EAClD,WAAW,gBAAgB,SAAS;AAClC,WAAO,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACpD,WAAW,gBAAgB,SAAS;AAClC,WAAO,OAAO,EAAE,QAAQ,EAAE,GAAG,OAAO,uBAAuB,GAAG,SAAS,SAAS,CAAC;AAAA,EACnF,WAAW,gBAAgB,aAAa;AACtC,WAAO,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,eAAe,EAAE,CAAC;AAAA,EAC1F,WAAW,gBAAgB,WAAW;AACpC,WAAO,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACtD;AACA,QAAM,IAAI,MAAM,cAAc,2DAA2D;AAC3F;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,SAAS,aAAa,uBAAuB,OAAO,KAAK;AAC/D,QAAM,SAAS,aAAa,cAAc,MAAM;AAChD,eAAa,OAAO,UAAU,QAAQ,MAAM,kBAAkB,eAAe,sCAAsC,EAAE,cAAc,oFAAoF;AACvN,WAAS,OAAO,EAAE,MAAM;AACxB,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM;AACxC,MAAI,MAAM,sBAAsB,MAAM;AACpC,UAAM,QAAQ,MAAM,mBAAmB;AACvC,UAAM,QAAQ,MAAM,mBAAmB;AACvC,UAAM,QAAQ;AACd,UAAM,QAAQ;AAAA,EAChB;AACA,SAAO,EAAE,QAAQ,EAAE,QAAQ,OAAO,QAAQ,OAAO,EAAE,MAAM;AAC3D;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,EAAE,IAAI;AACjB,QAAM,EAAE,YAAY,WAAW,IAAI;AACnC,mBAAiB,CAAC,GAAG,CAAC,GAAG,QAAQ;AACjC,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,oBAAoB,uBAAuB,2BAA2B,EAAE,MAAM,MAAM,GAAG,EAAE,GAAG,EAAE,MAAM,MAAM,GAAG,EAAE,CAAC;AACtH,QAAM,WAAW,kBAAkB,OAAO,CAAC,aAAa,WAAW,CAAC;AACpE,eAAa,OAAO,gBAAgB,aAAa,MAAM,kCAAkC,qBAAqB,uCAAuC,EAAE,aAAa,EAAE,wBAAwB,6BAA6B,wBAAwB;AACnP,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,YAAY,aAAa,IAAI,MAAM,KAAK,IAAI,MAAM;AACxD,QAAM,UAAU,aAAa,IAAI,MAAM,KAAK,IAAI,MAAM;AACtD,QAAM,WAAW,aAAa,IAAI,MAAM,KAAK,IAAI,MAAM;AACvD,QAAM,WAAW,KAAK,IAAI,WAAW,SAAS;AAC9C,QAAM,YAAY,SAAS,KAAK,IAAI,IAAI,MAAM,EAAE;AAChD,QAAM,YAAY,SAAS,KAAK,IAAI,IAAI,MAAM,EAAE;AAChD,QAAM,aAAa,aAAa,eAAe,IAAI,KAAK;AACxD,QAAM,aAAa,aAAa,eAAe,IAAI,KAAK;AACxD,QAAM,CAAC,QAAQ,YAAY,UAAU,IAAI,aAAa,CAAC,WAAW,IAAI,GAAG,WAAW,EAAE,IAAI,CAAC,WAAW,IAAI,WAAW,IAAI,CAAC;AAC1H,QAAM,CAAC,YAAY,YAAY,MAAM,IAAI,aAAa,CAAC,GAAG,WAAW,IAAI,WAAW,EAAE,IAAI,CAAC,WAAW,IAAI,GAAG,WAAW,EAAE;AAC1H,QAAMtB,QAAO,UAAU;AACvB,QAAM,SAAS,OAAO,CAAC,UAAU,SAAS,QAAQ,GAAG,IAAI,KAAK;AAC9D,QAAM,UAAU,OAAO;AACvB,QAAM,YAAY,SAAS;AAC3B,WAAS,KAAK,GAAG,KAAK,UAAU,MAAM;AACpC,aAAS,KAAK,GAAG,KAAK,SAAS,MAAM,WAAW;AAC9C,eAAS,KAAK,GAAG,KAAK,UAAU,MAAM,WAAW;AAC/C,iBAAS,MAAM,GAAG,MAAM,WAAW,OAAO,WAAW;AACnD,gBAAM,SAAS,KAAK,IAAI,KAAK,WAAW,OAAO;AAC/C,gBAAM,SAAS,KAAK,IAAI,KAAK,WAAW,QAAQ;AAChD,gBAAM,SAAS,KAAK,IAAI,MAAM,WAAW,SAAS;AAClD,mBAAS,KAAK,IAAI,KAAK,QAAQ,MAAM;AACnC,qBAAS,IAAI,IAAI,IAAI,QAAQ,KAAK;AAChC,kBAAI,OAAO;AACX,uBAAS,IAAI,KAAK,IAAI,QAAQ,KAAK;AACjC,sBAAM,eAAe,KAAK,IAAI,IAAI,YAAY,CAAC,IAAI;AACnD,sBAAM,eAAe,KAAK,IAAI,IAAI,YAAY,CAAC,IAAI;AACnD,sBAAM,OAAO,UAAU,eAAe,KAAK,aAAa,IAAI;AAC5D,sBAAM,OAAO,UAAU,IAAI,aAAa,IAAI,aAAa;AACzD,wBAAQ,OAAO;AAAA,cACjB;AACA,sBAAQ,KAAKA,SAAQ,KAAK,WAAW,OAAO;AAAA,YAC9C;AAAA,UACF;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,WAAS,8BAA8B,GAAG;AAC1C,WAAS,8BAA8B,GAAG;AAC1C,SAAO,SAAS,eAAe,UAAU,OAAO,OAAO,OAAO,MAAM;AACtE;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,MAAM,uBAAuB,IAAI;AAC/C,QAAM,EAAE,YAAY,YAAY,YAAY,aAAa,eAAe,IAAI;AAC5E,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,QAAM,gBAAgB,CAAC;AACvB,QAAM,YAAY,YAAY,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,OAAO,EAAE,YAAY,WAAW,GAAG,SAAS,SAAS,CAAC;AACxG,YAAU;AACV,MAAI,MAAM;AACR,aAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,KAAK,GAAG,SAAS,SAAS,CAAC;AACpE,kBAAc,KAAK,OAAO;AAC1B,cAAU;AAAA,EACZ;AACA,MAAI,aAAa;AACf,oBAAgB,iBAAiB,UAAU,SAAS,aAAa,wBAAwB,cAAc;AACvG,kBAAc,KAAK,OAAO;AAC1B,cAAU;AAAA,EACZ;AACA,aAAW,MAAM,eAAe;AAC9B,aAAS,8BAA8B,EAAE;AAAA,EAC3C;AACA,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO,KAAK,MAAM,EAAE,CAAC;AAC1D,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,UAAU;AAChB,mBAAiB,QAAQ,MAAM;AAC/B,QAAM,OAAO,QAAQ,IAAI,CAAC,OAAO,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE,MAAM;AACpE,QAAM,SAAS,OAAO,QAAQ,GAAG,OAAO,QAAQ,GAAG,KAAK;AACxD,QAAM,UAAU,OAAO;AACvB,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,UAAM,WAAW,KAAK;AACtB,aAAS,IAAI,GAAG,IAAI,QAAQ,QAAQ,KAAK;AACvC,cAAQ,MAAM,SAAS;AAAA,IACzB;AAAA,EACF;AACA,SAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC1E;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,mBAAiB,GAAG,KAAK;AACzB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,EAAE,MAAM,MAAM;AAAA,EAC1E;AACA,uBAAqB,2BAA2B,OAAO,MAAM,GAAG,MAAM,MAAM;AAC5E,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,GAAG,OAAO,IAAI;AAC7F,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,OAAO,aAAa,oBAAoB,aAAa,cAAc,QAAQ,GAAG,GAAG,KAAK;AAC5F,QAAM,QAAQ,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC3C,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,SAAS,KAAK;AACpB,QAAIF,QAAO,MAAM;AACjB,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,YAAM,QAAQ,MAAM,SAAS;AAC7B,MAAAA,QAAOA,SAAQ;AAAA,IACjB;AACA,SAAK,MAAMA;AAAA,EACb;AACA,MAAI,gBAAgB,MAAM;AACxB,aAAS,8BAA8B,EAAE;AAAA,EAC3C;AACA,QAAM,SAAS,SAAS,eAAe,UAAU,GAAG,OAAO,IAAI;AAC/D,MAAI,UAAU;AACZ,UAAM,gBAAgB,qBAAqB,qBAAqB,UAAU,QAAQ;AAClF,UAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAC7G,aAAS,8BAA8B,MAAM;AAC7C,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,mBAAiB,GAAG,KAAK;AACzB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,EAAE,MAAM,MAAM;AAAA,EAC1E;AACA,uBAAqB,2BAA2B,OAAO,MAAM,GAAG,MAAM,MAAM;AAC5E,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,GAAG,OAAO,IAAI;AAC7F,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,OAAO,aAAa,oBAAoB,aAAa,cAAc,QAAQ,GAAG,GAAG,KAAK;AAC5F,QAAM,QAAQ,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC3C,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,SAAS,KAAK;AACpB,QAAI,SAAS,MAAM;AACnB,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,YAAM,QAAQ,MAAM,SAAS;AAC7B,eAAS,UAAU;AAAA,IACrB;AACA,SAAK,MAAM;AAAA,EACb;AACA,MAAI,gBAAgB,MAAM;AACxB,aAAS,8BAA8B,EAAE;AAAA,EAC3C;AACA,QAAM,SAAS,SAAS,eAAe,UAAU,GAAG,OAAO,IAAI;AAC/D,MAAI,UAAU;AACZ,UAAM,gBAAgB,qBAAqB,qBAAqB,UAAU,QAAQ;AAClF,UAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAC7G,aAAS,8BAA8B,MAAM;AAC7C,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,mBAAiB,GAAG,QAAQ;AAC5B,MAAI,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACpD,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,QAAM,0BAA0B,CAAC;AACjC,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,4BAAwB,KAAK,EAAE;AAC/B,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,GAAG,MAAM,MAAM;AAAA,EAC3E;AACA,SAAO,CAAC,KAAK,EAAE;AACf,uBAAqB,2BAA2B,UAAU,MAAM,GAAG,MAAM,MAAM;AAC/E,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,GAAG,OAAO,IAAI;AAC7F,QAAM,UAAU,aAAa,cAAc,QAAQ;AACnD,QAAM,OAAO,aAAa,oBAAoB,SAAS,OAAO;AAC9D,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,QAAQ,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC3C,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,SAAS,KAAK;AACpB,QAAI,OAAO,MAAM;AACjB,QAAI,WAAW;AACf,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,YAAM,QAAQ,MAAM,SAAS;AAC7B,UAAI,QAAQ,MAAM;AAChB,eAAO;AACP,mBAAW;AAAA,MACb;AAAA,IACF;AACA,SAAK,MAAM;AAAA,EACb;AACA,0BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,SAAO,SAAS,eAAe,UAAU,SAAS,IAAI;AACxD;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,mBAAiB,GAAG,QAAQ;AAC5B,MAAI,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACpD,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,QAAM,0BAA0B,CAAC;AACjC,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,4BAAwB,KAAK,EAAE;AAC/B,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,GAAG,MAAM,MAAM;AAAA,EAC3E;AACA,SAAO,CAAC,KAAK,EAAE;AACf,uBAAqB,2BAA2B,UAAU,MAAM,GAAG,MAAM,MAAM;AAC/E,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,GAAG,OAAO,IAAI;AAC7F,QAAM,UAAU,aAAa,cAAc,QAAQ;AACnD,QAAM,OAAO,aAAa,oBAAoB,SAAS,OAAO;AAC9D,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,QAAQ,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC3C,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,SAAS,KAAK;AACpB,QAAI,OAAO,MAAM;AACjB,QAAI,WAAW;AACf,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,YAAM,QAAQ,MAAM,SAAS;AAC7B,UAAI,QAAQ,MAAM;AAChB,eAAO;AACP,mBAAW;AAAA,MACb;AAAA,IACF;AACA,SAAK,MAAM;AAAA,EACb;AACA,0BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,SAAO,SAAS,eAAe,UAAU,SAAS,IAAI;AACxD;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO,KAAK,MAAM,EAAE,CAAC;AAC1D,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY,6BAA6B,CAAC,QAAQ,WAAW,KAAK,MAAM,QAAQ,MAAM,CAAC;AAC3F,IAAI,SAAS,iBAAiB,OAAO,SAAS;AAC9C,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO,KAAK,MAAM,EAAE,CAAC;AAC1D,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,SAAS,QAAQ,OAAOc,UAAS,UAAU,UAAU;AAClE,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,eAAe,aAAa,QAAQ,OAAO,oBAAoB,OAAO;AAC5E,QAAM,SAAS,OAAO,SAAS,UAAU,KAAK;AAC9C,QAAM,aAAa,OAAO;AAC1B,QAAM,qBAAqB,SAAS,SAAS,KAAK,SAAS,SAAS,KAAK,SAAS,SAAS;AAC3F,QAAM,mBAAmB,SAAS,SAAS,KAAK,SAAS,SAAS;AAClE,QAAM,mBAAmB,SAAS,SAAS;AAC3C,WAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,UAAM,oBAAoB,IAAI;AAC9B,UAAM,mBAAmB,IAAIA,SAAQ;AACrC,aAAS,IAAI,GAAG,IAAI,SAAS,YAAY,EAAE,GAAG;AAC5C,eAAS,KAAK,GAAG,KAAK,SAAS,WAAW,EAAE,IAAI;AAC9C,cAAM,WAAW,KAAK,eAAe;AACrC,cAAM,QAAQ,KAAK,IAAI,GAAG,QAAQ;AAClC,cAAM,QAAQ,KAAK,IAAI,SAAS,UAAU,wBAAwB,QAAQ;AAC1E,cAAM,kBAAkB,oBAAoB,KAAK;AACjD,iBAAS,KAAK,GAAG,KAAK,SAAS,UAAU,EAAE,IAAI;AAC7C,gBAAM,WAAW,KAAK,cAAc;AACpC,gBAAM,QAAQ,KAAK,IAAI,GAAG,QAAQ;AAClC,gBAAM,QAAQ,KAAK,IAAI,SAAS,SAAS,uBAAuB,QAAQ;AACxE,cAAI,cAAc;AAClB,cAAI,WAAW;AACf,cAAIL,UAAS;AACb,mBAAS,KAAK,OAAO,KAAK,OAAO,MAAM,gBAAgB;AACrD,kBAAM,WAAW,mBAAmB,KAAKK,SAAQ;AACjD,qBAAS,KAAK,OAAO,KAAK,OAAO,MAAM,eAAe;AACpD,oBAAM,WAAW,WAAW,KAAKA,SAAQ;AACzC,oBAAM,QAAQ,QAAQ,WAAW;AACjC,kBAAI,aAAa,SAAS,QAAQ,aAAa;AAC7C,8BAAc;AAAA,cAChB,WAAW,aAAa,OAAO;AAC7B,4BAAY;AACZ,gBAAAL;AAAA,cACF;AAAA,YACF;AACA,gBAAI,MAAM,WAAW,GAAG;AACtB;AAAA,YACF;AAAA,UACF;AACA,gBAAM,eAAe,kBAAkB,KAAK,mBAAmB;AAC/D,qBAAW,gBAAgB,aAAa,QAAQ,WAAWA,UAAS;AAAA,QACtE;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,SAAS,QAAQ,OAAO,UAAU,mBAAmB,OAAO,sBAAsB,OAAO;AACjH,QAAM,eAAe,OAAO,SAAS,UAAU,OAAO;AACtD,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,OAAO,OAAO,QAAQ,OAAO,OAAO;AAC1C,WAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,aAAS,IAAI,GAAG,IAAI,SAAS,YAAY,EAAE,GAAG;AAC5C,eAAS,KAAK,GAAG,KAAK,SAAS,WAAW,EAAE,IAAI;AAC9C,cAAM,WAAW,KAAK,eAAe;AACrC,YAAI,QAAQ;AACZ,eAAO,QAAQ,GAAG;AAChB,mBAAS;AAAA,QACX;AACA,cAAM,QAAQ,KAAK,IAAI,SAAS,UAAU,wBAAwB,QAAQ;AAC1E,iBAAS,KAAK,GAAG,KAAK,SAAS,UAAU,EAAE,IAAI;AAC7C,gBAAM,WAAW,KAAK,cAAc;AACpC,cAAI,QAAQ;AACZ,iBAAO,QAAQ,GAAG;AAChB,qBAAS;AAAA,UACX;AACA,gBAAM,QAAQ,KAAK,IAAI,SAAS,SAAS,uBAAuB,QAAQ;AACxE,cAAI,WAAW,OAAO;AACtB,cAAI,cAAc;AAClB,mBAAS,KAAK,OAAO,KAAK,OAAO,MAAM,gBAAgB;AACrD,kBAAM,KAAK,KAAK;AAChB,qBAAS,KAAK,OAAO,KAAK,OAAO,MAAM,eAAe;AACpD,oBAAM,KAAK,KAAK;AAChB,oBAAM,QAAQ,KAAK,IAAI,GAAG,IAAI,IAAI,CAAC;AACnC,kBAAI,QAAQ,UAAU;AACpB,2BAAW;AACX,oBAAI,kBAAkB;AACpB,gCAAc,wBAAwB,IAAI,SAAS,WAAW,MAAM,SAAS,UAAU,MAAM,SAAS,aAAa,KAAK,KAAK,SAAS,UAAU,MAAM,SAAS,aAAa;AAAA,gBAC9K,OAAO;AACL,gCAAc,KAAK,uBAAuB;AAAA,gBAC5C;AAAA,cACF;AAAA,YACF;AAAA,UACF;AACA,uBAAa,IAAI,aAAa,GAAG,IAAI,IAAI,CAAC;AAAA,QAC5C;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,QAAQ,SAAS,QAAQ,OAAOK,UAAS,UAAU,UAAU;AACpE,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,uBAAuB,SAAS;AACtC,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,eAAe,aAAa,QAAQ,OAAO,oBAAoB,OAAO;AAC5E,QAAM,SAAS,OAAO,SAAS,UAAU,KAAK;AAC9C,QAAM,aAAa,OAAO;AAC1B,QAAM,qBAAqB,SAAS,SAAS,KAAK,SAAS,SAAS,KAAK,SAAS,SAAS,KAAK,SAAS,SAAS;AAClH,QAAM,qBAAqB,SAAS,SAAS,KAAK,SAAS,SAAS,KAAK,SAAS,SAAS;AAC3F,QAAM,mBAAmB,SAAS,SAAS,KAAK,SAAS,SAAS;AAClE,QAAM,mBAAmB,SAAS,SAAS;AAC3C,WAAS,QAAQ,GAAG,QAAQ,SAAS,WAAW,EAAE,OAAO;AACvD,UAAM,oBAAoB,QAAQ;AAClC,UAAM,mBAAmB,QAAQA,SAAQ;AACzC,aAAS,UAAU,GAAG,UAAU,SAAS,YAAY,EAAE,SAAS;AAC9D,eAAS,SAAS,GAAG,SAAS,SAAS,UAAU,EAAE,QAAQ;AACzD,cAAM,eAAe,SAAS,cAAc;AAC5C,YAAI,YAAY;AAChB,eAAO,YAAY,GAAG;AACpB,uBAAa;AAAA,QACf;AACA,cAAM,YAAY,KAAK,IAAI,SAAS,SAAS,uBAAuB,YAAY;AAChF,cAAM,oBAAoB,oBAAoB,SAAS;AACvD,iBAAS,OAAO,GAAG,OAAO,SAAS,WAAW,EAAE,MAAM;AACpD,gBAAM,aAAa,OAAO,eAAe;AACzC,cAAI,UAAU;AACd,iBAAO,UAAU,GAAG;AAClB,uBAAW;AAAA,UACb;AACA,gBAAM,UAAU,KAAK,IAAI,SAAS,UAAU,wBAAwB,UAAU;AAC9E,gBAAM,kBAAkB,oBAAoB,OAAO;AACnD,mBAAS,OAAO,GAAG,OAAO,SAAS,UAAU,EAAE,MAAM;AACnD,kBAAM,aAAa,OAAO,cAAc;AACxC,gBAAI,UAAU;AACd,mBAAO,UAAU,GAAG;AAClB,yBAAW;AAAA,YACb;AACA,kBAAM,UAAU,KAAK,IAAI,SAAS,SAAS,uBAAuB,UAAU;AAC5E,kBAAM,kBAAkB,kBAAkB,OAAO;AACjD,gBAAI,cAAc;AAClB,gBAAI,WAAW;AACf,gBAAIL,UAAS;AACb,qBAAS,SAAS,WAAW,SAAS,WAAW,UAAU,eAAe;AACxE,oBAAM,eAAe,mBAAmB,SAASK,SAAQ;AACzD,uBAAS,OAAO,SAAS,OAAO,SAAS,QAAQ,gBAAgB;AAC/D,sBAAM,aAAa,eAAe,OAAOA,SAAQ;AACjD,yBAAS,OAAO,SAAS,OAAO,SAAS,QAAQ,eAAe;AAC9D,wBAAM,aAAa,aAAa,OAAOA,SAAQ;AAC/C,wBAAM,QAAQ,QAAQ,aAAa;AACnC,sBAAI,aAAa,SAAS,QAAQ,aAAa;AAC7C,kCAAc;AAAA,kBAChB,WAAW,aAAa,OAAO;AAC7B,gCAAY;AACZ,oBAAAL;AAAA,kBACF;AACA,sBAAI,MAAM,WAAW,GAAG;AACtB;AAAA,kBACF;AAAA,gBACF;AACA,oBAAI,MAAM,WAAW,GAAG;AACtB;AAAA,gBACF;AAAA,cACF;AACA,kBAAI,MAAM,WAAW,GAAG;AACtB;AAAA,cACF;AAAA,YACF;AACA,kBAAM,eAAe,kBAAkB;AACvC,uBAAW,gBAAgB,aAAa,QAAQ,WAAWA,UAAS;AAAA,UACtE;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,mBAAmB,MAAM,UAAU;AAC1C,QAAM,eAAe,OAAO,SAAS,UAAU,OAAO;AACtD,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,uBAAuB,SAAS;AACtC,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,UAAU,SAAS,QAAQ;AACjC,WAAS,QAAQ,GAAG,QAAQ,SAAS,WAAW,EAAE,OAAO;AACvD,aAAS,UAAU,GAAG,UAAU,SAAS,YAAY,EAAE,SAAS;AAC9D,eAAS,SAAS,GAAG,SAAS,SAAS,UAAU,EAAE,QAAQ;AACzD,cAAM,eAAe,SAAS,cAAc;AAC5C,YAAI,YAAY;AAChB,eAAO,YAAY,GAAG;AACpB,uBAAa;AAAA,QACf;AACA,cAAM,YAAY,KAAK,IAAI,SAAS,SAAS,uBAAuB,YAAY;AAChF,iBAAS,OAAO,GAAG,OAAO,SAAS,WAAW,EAAE,MAAM;AACpD,gBAAM,aAAa,OAAO,eAAe;AACzC,cAAI,UAAU;AACd,iBAAO,UAAU,GAAG;AAClB,uBAAW;AAAA,UACb;AACA,gBAAM,UAAU,KAAK,IAAI,SAAS,UAAU,wBAAwB,UAAU;AAC9E,mBAAS,OAAO,GAAG,OAAO,SAAS,UAAU,EAAE,MAAM;AACnD,kBAAM,aAAa,OAAO,cAAc;AACxC,gBAAI,UAAU;AACd,mBAAO,UAAU,GAAG;AAClB,yBAAW;AAAA,YACb;AACA,kBAAM,UAAU,KAAK,IAAI,SAAS,SAAS,uBAAuB,UAAU;AAC5E,gBAAI,WAAW,OAAO;AACtB,gBAAI,cAAc;AAClB,qBAAS,SAAS,WAAW,SAAS,WAAW,UAAU,eAAe;AACxE,oBAAM,SAAS,SAAS;AACxB,uBAAS,OAAO,SAAS,OAAO,SAAS,QAAQ,gBAAgB;AAC/D,sBAAM,OAAO,OAAO;AACpB,yBAAS,OAAO,SAAS,OAAO,SAAS,QAAQ,eAAe;AAC9D,wBAAM,OAAO,OAAO;AACpB,wBAAM,QAAQ,KAAK,IAAI,OAAO,QAAQ,MAAM,MAAM,OAAO;AACzD,sBAAI,SAAS,UAAU;AACrB,+BAAW;AACX,kCAAc,SAAS,wBAAwB,uBAAuB,OAAO,wBAAwB;AAAA,kBACvG;AAAA,gBACF;AAAA,cACF;AAAA,YACF;AACA,yBAAa,IAAI,aAAa,OAAO,QAAQ,MAAM,MAAM,OAAO;AAAA,UAClE;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,mBAAiB,GAAG,SAAS;AAC7B,QAAM,EAAE,YAAY,SAAAK,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY;AAClB,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,SAAS,GAAG,MAAM,wEAAwEA,2BAA0B,YAAY;AACjN,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,MAAI;AACJ,MAAI,SAAS,gBAAgB,KAAK,SAAS,iBAAiB,KAAK,aAAa,YAAY,SAAS,SAAS,SAAS,QAAQ,GAAG;AAC9H,UAAM,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACtD,OAAO;AACL,UAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,UAAMwB,YAAW,aAAa,eAAe,EAAE,KAAK;AACpD,UAAM,UAAU,MAAM,SAAS,EAAE,OAAO,EAAE,OAAOA,WAAU,UAAU,KAAK;AAC1E,UAAM,SAAS,eAAe,SAAS,UAAU,EAAE,OAAO,QAAQ,MAAM;AAAA,EAC1E;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAAxB,UAAS,KAAK,MAAM,iBAAiB,WAAW,IAAI;AACxE,mBAAiB,GAAG,WAAW;AAC/B,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,MAAM,iBAAiB,UAAU;AAC1H,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAM,SAAS,QAAQ,SAAS,EAAE,OAAO,EAAE,OAAO,aAAa,eAAe,EAAE,KAAK,GAAG,UAAU,KAAK;AACvG,SAAO,SAAS,eAAe,OAAO,OAAO,WAAW,OAAO,MAAM;AACvE;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,OAAO,IAAI;AAC9B,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,mBAAiB,CAAC,IAAI,MAAM,GAAG,eAAe;AAC9C,QAAM,WAAW,qBAAqB,kBAAkB,OAAO,OAAO,YAAYA,UAAS,GAAG,MAAM,eAAe;AACnH,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,uBAAuB,SAAS;AACtC,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,WAAW,uBAAuB,IAAI,SAAS,QAAQ;AAC7D,QAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,QAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,QAAM,KAAK,OAAO,OAAO,OAAO,SAAS;AACzC,QAAM,gBAAgB,KAAK,cAAc,eAAe;AACxD,QAAM,QAAQ,SAAS,WAAW,EAAE;AACpC,WAAS,QAAQ,GAAG,QAAQ,SAAS,WAAW,EAAE,OAAO;AACvD,aAAS,UAAU,GAAG,UAAU,SAAS,YAAY,EAAE,SAAS;AAC9D,eAAS,UAAU,GAAG,UAAU,SAAS,SAAS,EAAE,SAAS;AAC3D,iBAAS,QAAQ,GAAG,QAAQ,SAAS,UAAU,EAAE,OAAO;AACtD,mBAAS,QAAQ,GAAG,QAAQ,SAAS,SAAS,EAAE,OAAO;AACrD,kBAAM,gBAAgB,UAAU;AAChC,kBAAM,cAAc,QAAQ;AAC5B,kBAAM,cAAc,QAAQ;AAC5B,gBAAI,UAAU;AACd,qBAAS,SAAS,GAAG,SAAS,sBAAsB,UAAU,eAAe;AAC3E,oBAAM,WAAW,gBAAgB,UAAU;AAC3C,kBAAI,UAAU,KAAK,WAAW,SAAS,YAAY,KAAK,MAAM,OAAO,MAAM,SAAS;AAClF;AAAA,cACF;AACA,uBAAS,OAAO,GAAG,OAAO,uBAAuB,QAAQ,gBAAgB;AACvE,sBAAM,SAAS,cAAc,QAAQ;AACrC,oBAAI,QAAQ,KAAK,SAAS,SAAS,aAAa,KAAK,MAAM,KAAK,MAAM,OAAO;AAC3E;AAAA,gBACF;AACA,yBAAS,OAAO,GAAG,OAAO,sBAAsB,QAAQ,eAAe;AACrE,wBAAM,SAAS,cAAc,QAAQ;AACrC,sBAAI,QAAQ,KAAK,SAAS,SAAS,YAAY,KAAK,MAAM,KAAK,MAAM,OAAO;AAC1E;AAAA,kBACF;AACA,wBAAM,QAAQ,MAAM,IAAI,OAAO,SAAS,OAAO,OAAO,OAAO;AAC7D,6BAAW;AAAA,gBACb;AAAA,cACF;AAAA,YACF;AACA,eAAG,IAAI,UAAU,eAAe,OAAO,SAAS,OAAO,OAAO,OAAO;AAAA,UACvE;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,OAAO,IAAI;AAC9B,QAAM,IAAI;AACV,mBAAiB,CAAC,IAAI,MAAM,GAAG,aAAa;AAC5C,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,KAAK,IAAI;AAC3C,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,IAAI;AAC7F,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,QAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,QAAM,KAAK,OAAO,EAAE,OAAO,SAAS;AACpC,QAAM,gBAAgB,KAAK,eAAe;AAC1C,QAAM,SAAS,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC5C,QAAM,QAAQ,OAAO,GAAG,OAAO,WAAW,MAAM;AAChD,WAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,aAAS,IAAI,GAAG,IAAI,SAAS,YAAY,EAAE,GAAG;AAC5C,eAAS,MAAM,GAAG,MAAM,SAAS,UAAU,EAAE,KAAK;AAChD,iBAAS,MAAM,GAAG,MAAM,SAAS,SAAS,EAAE,KAAK;AAC/C,gBAAM,YAAY,MAAM;AACxB,gBAAM,YAAY,MAAM;AACxB,cAAI,UAAU;AACd,mBAAS,KAAK,GAAG,KAAK,uBAAuB,MAAM,gBAAgB;AACjE,kBAAM,OAAO,YAAY,MAAM;AAC/B,gBAAI,MAAM,KAAK,OAAO,SAAS,aAAa,KAAK,MAAM,GAAG,MAAM,KAAK;AACnE;AAAA,YACF;AACA,qBAAS,KAAK,GAAG,KAAK,sBAAsB,MAAM,eAAe;AAC/D,oBAAM,OAAO,YAAY,MAAM;AAC/B,kBAAI,MAAM,KAAK,OAAO,SAAS,YAAY,KAAK,MAAM,GAAG,MAAM,KAAK;AAClE;AAAA,cACF;AACA,oBAAM,QAAQ,MAAM,IAAI,GAAG,KAAK,KAAK,CAAC;AACtC,yBAAW;AAAA,YACb;AAAA,UACF;AACA,aAAG,IAAI,UAAU,eAAe,GAAG,KAAK,KAAK,CAAC;AAAA,QAChD;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAOS,SAAQ,QAAQ,MAAM,OAAO,SAAS,IAAI;AAC5D,eAAa,OAAO,MAAM,MAAM,WAAW,SAAS,MAAM,QAAQ,MAAM,8EAA8E;AACtJ,eAAa,OAAO,UAAU,QAAQ,MAAM,MAAM,WAAW,OAAO,MAAM,QAAQ,MAAM,4EAA4E;AACpK,eAAa,OAAOA,WAAU,QAAQ,MAAM,MAAM,WAAWA,QAAO,MAAM,QAAQ,MAAM,2EAA2E;AACnK,mBAAiB,CAAC,GAAG,OAAO,UAAUA,SAAQ,MAAM,GAAG,WAAW;AAClE,MAAI,EAAE,gBAAgB,IAAI;AAC1B,MAAI,mBAAmB,MAAM;AAC3B,sBAAkB;AAAA,EACpB;AACA,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,QAAQ,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AAC9C,QAAM,UAAU,SAAS,KAAK,IAAI,SAAS,MAAM,EAAE;AACnD,QAAM,QAAQA,UAAS,SAAS,KAAK,IAAIA,QAAO,MAAM,EAAE,SAAS,IAAI,aAAa,CAAC,CAAC,CAAC;AACrF,QAAM,UAAU,SAAS,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE,SAAS,IAAI,aAAa,CAAC,CAAC,CAAC;AACvF,QAAM,UAAU,IAAI,aAAa,MAAM,MAAM;AAC7C,QAAM,gBAAgB,QAAQ;AAC9B,QAAM,cAAc,MAAM;AAC1B,QAAM,gBAAgB,QAAQ;AAC9B,QAAM,cAAc,MAAM;AAC1B,MAAI,OAAO;AACX,MAAI,KAAK;AACT,MAAI,KAAK;AACT,MAAI,KAAK;AACT,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,YAAQ,MAAM,QAAQ,WAAW,MAAM,MAAM,MAAM,SAAS,MAAM,QAAQ,KAAK,KAAK,QAAQ,QAAQ,eAAe;AACnH,QAAI,QAAQ,eAAe;AACzB,aAAO;AAAA,IACT;AACA,QAAI,MAAM,aAAa;AACrB,WAAK;AAAA,IACP;AACA,QAAI,MAAM,aAAa;AACrB,WAAK;AAAA,IACP;AACA,QAAI,MAAM,eAAe;AACvB,WAAK;AAAA,IACP;AAAA,EACF;AACA,SAAO,SAAS,eAAe,EAAE,OAAO,EAAE,OAAO,OAAO;AAC1D;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,MAAM,IAAI;AAC9B,mBAAiB,CAAC,CAAC,GAAG,gBAAgB;AACtC,QAAM,QAAQ,WAAW,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAC/C,QAAM,WAAW,qBAAqB,YAAY,EAAE,OAAO,YAAY,KAAK;AAC5E,QAAM,WAAW,qBAAqB,YAAY,SAAS,QAAQ,WAAW,MAAM;AACpF,QAAM,mBAAmB,qBAAqB,oBAAoB,EAAE,OAAO,YAAY,KAAK;AAC5F,QAAM,mBAAmB,qBAAqB,oBAAoB,OAAO,WAAW,MAAM;AAC1F,QAAM,YAAY,qBAAqB,aAAa,kBAAkB,OAAO,WAAW,MAAM;AAC9F,QAAM,YAAY,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC3F,QAAM,cAAc,WAAW,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,SAAS,EAAE,CAAC;AACzG,QAAM,sBAAsB,SAAS,EAAE,QAAQ,EAAE,GAAG,YAAY,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,iBAAiB,EAAE,CAAC;AAC1H,QAAM,SAAS,OAAO;AAAA,IACpB,QAAQ,EAAE,GAAG,oBAAoB;AAAA,IACjC,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,kBAAkB,MAAM,UAAU;AAAA,EACpD,CAAC;AACD,WAAS,8BAA8B,SAAS;AAChD,WAAS,8BAA8B,WAAW;AAClD,WAAS,8BAA8B,mBAAmB;AAC1D,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAArB,MAAK,IAAI;AACjB,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,cAAc,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACtD,QAAM,UAAU,aAAa,OAAO,aAAa,QAAQ,OAAO,QAAQ,OAAOA,KAAI;AACnF,SAAO,SAAS,eAAe,CAACA,KAAI,GAAG,QAAQ,OAAO,OAAO;AAC/D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,IAAI,GAAG,IAAI;AACnB,QAAM,SAAS,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC5C,QAAM,SAAS,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC5C,QAAM,iBAAiB,qBAAqB,2BAA2B,MAAM,KAAK,MAAM,GAAG,MAAM,KAAK,MAAM,CAAC;AAC7G,SAAO,SAAS,eAAe,CAAC,eAAe,MAAM,GAAG,SAAS,WAAW,KAAK,cAAc,CAAC;AAClG;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe,gBAAgB,aAAa,CAAC,IAAI,UAAU;AAC7D,QAAM,YAAY;AAClB,MAAI,KAAK,UAAU,cAAc;AAC/B,WAAO,UAAU;AAAA,EACnB;AACA,SAAO,KAAK,UAAU,eAAe,UAAU,eAAe;AAChE,CAAC;AACD,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa,CAAC,SAAS;AACzB,QAAM,EAAE,EAAE,IAAI,KAAK;AACnB,QAAM,aAAa,KAAK;AACxB,QAAM,eAAe,IAAI,aAAa,aAAa,cAAc,EAAE,KAAK,CAAC;AACzE,QAAM,cAAc,WAAW,KAAK,IAAI,EAAE,MAAM;AAChD,QAAM,QAAQ,YAAY,mBAAmB;AAC7C,QAAM,QAAQ,YAAY,mBAAmB;AAC7C,QAAM,WAAW,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACnD,QAAM,WAAW,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACnD,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,UAAM,QAAQ,SAAS;AACvB,UAAM,QAAQ,SAAS;AACvB,iBAAa,MAAM,KAAK,MAAM,OAAO,KAAK;AAAA,EAC5C;AACA,SAAO,WAAW,WAAW,cAAc,EAAE,OAAO,SAAS;AAC/D;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,QAAQ,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE,mBAAmB;AAClE,QAAM,UAAU,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AAChD,SAAO,SAAS,eAAe,MAAM,OAAO,MAAM,OAAO,OAAO;AAClE;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,QAAQ,aAAa,eAAe,MAAM,OAAO,GAAG,KAAK,EAAE;AACjE,MAAI,WAAW,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,KAAK;AACvF,MAAI,aAAa,cAAc,QAAQ,MAAM,GAAG;AAC9C,WAAO,SAAS,eAAe,UAAU,OAAO,GAAG,OAAO,CAAC,CAAC;AAAA,EAC9D;AACA,QAAM,UAAU,OAAO,OAAO,CAAC,OAAO,aAAa,cAAc,GAAG,KAAK,IAAI,CAAC;AAC9E,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,GAAG,SAAS,SAAS,CAAC;AAAA,EACnE;AACA,QAAM,SAAS,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK;AAC3C,uBAAqB,uBAAuB,QAAQ,KAAK;AACzD,MAAI,QAAQ,GAAG,UAAU,aAAa;AACpC,UAAM,QAAQ,QAAQ,IAAI,CAAC,OAAO,MAAM,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,SAAS,CAAC,CAAC;AACrF,UAAM,QAAQ,QAAQ,IAAI,CAAC,OAAO,MAAM,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,SAAS,CAAC,CAAC;AACrF,UAAM,eAAe,QAAQ,EAAE,QAAQ,OAAO,SAAS,UAAU,OAAO,EAAE,MAAM,MAAM,EAAE,CAAC;AACzF,UAAM,eAAe,QAAQ,EAAE,QAAQ,OAAO,SAAS,UAAU,OAAO,EAAE,MAAM,MAAM,EAAE,CAAC;AACzF,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,cAAc,MAAM,aAAa,GAAG,SAAS,SAAS,CAAC;AACjG,UAAM,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAChE,UAAM,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAChE,aAAS,8BAA8B,YAAY;AACnD,aAAS,8BAA8B,YAAY;AACnD,WAAO;AAAA,EACT;AACA,QAAM,WAAW,QAAQ,IAAI,CAAC,OAAO;AACnC,UAAM,YAAY,aAAa,cAAc,GAAG,MAAM,MAAM,KAAK,CAAC;AAClE,UAAM,QAAQ,CAAC,IAAI,SAAS;AAC5B,WAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AAAA,EAC5E,CAAC;AACD,QAAM,kBAAkB,SAAS,IAAI,CAAC,OAAO;AAC3C,WAAO,EAAE,MAAM,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE,QAAQ,OAAO,GAAG,MAAM;AAAA,EACtE,CAAC;AACD,aAAW,qBAAqB,gBAAgB,SAAS,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,CAAC;AACjF,QAAM,eAAe,SAAS,GAAG,MAAM,OAAO;AAC9C,QAAM,UAAU,WAAW,iBAAiB,UAAU,OAAO,GAAG,OAAO,YAAY;AACnF,QAAM,gBAAgB,qBAAqB,gBAAgB,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,KAAK;AAC/F,QAAM,UAAU,SAAS,eAAe,eAAe,OAAO,GAAG,OAAO,OAAO;AAC/E,WAAS,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACnE,SAAO;AACT;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAY,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB,IAAI;AACvE,mBAAiB,CAAC,GAAG,MAAM,GAAG,QAAQ;AACtC,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,OAAO,WAAW;AAC5I,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,iBAAiB,SAAS,eAAe;AAC/C,QAAM,IAAI,IAAI,aAAa,SAAS,UAAU,EAAE,KAAK;AACrD,QAAM,WAAW,aAAa,eAAe,EAAE,KAAK;AACpD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,eAAe,SAAS;AAC9B,QAAM,aAAa,iBAAiB,SAAS,KAAK,SAAS;AAC3D,QAAM,aAAa,iBAAiB,SAAS,KAAK;AAClD,QAAM,iBAAiB,iBAAiB,IAAI,SAAS;AACrD,QAAM,eAAe,EAAE,QAAQ;AAC/B,QAAM,aAAa,iBAAiB,EAAE,QAAQ,KAAK,EAAE,QAAQ;AAC7D,QAAM,aAAa,iBAAiB,EAAE,QAAQ,KAAK;AACnD,QAAM,iBAAiB,iBAAiB,IAAI,EAAE,QAAQ;AACtD,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,QAAQ,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AAC/C,QAAM,QAAQ,EAAE;AAChB,WAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,UAAM,WAAW,IAAI;AACrB,UAAM,WAAW,IAAI;AACrB,aAAS,KAAK,GAAG,KAAK,SAAS,WAAW,EAAE,IAAI;AAC9C,YAAM,WAAW,WAAW,KAAK;AACjC,YAAM,WAAW,KAAK,SAAS,eAAe;AAC9C,eAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,cAAM,KAAK,WAAW,KAAK;AAC3B,YAAI,KAAK,KAAK,MAAM,SAAS,UAAU;AACrC;AAAA,QACF;AACA,cAAM,WAAW,KAAK,cAAc;AACpC,cAAM,WAAW,WAAW,KAAK;AACjC,iBAAS,KAAK,GAAG,KAAK,SAAS,UAAU,EAAE,IAAI;AAC7C,gBAAM,WAAW,WAAW,KAAK;AACjC,gBAAM,WAAW,KAAK,SAAS,cAAc;AAC7C,mBAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,kBAAM,KAAK,WAAW,KAAK;AAC3B,gBAAI,KAAK,KAAK,MAAM,SAAS,SAAS;AACpC;AAAA,YACF;AACA,kBAAM,WAAW,WAAW,KAAK,cAAc;AAC/C,kBAAM,WAAW,WAAW,KAAK;AACjC,gBAAI,WAAW;AACf,qBAAS,KAAK,GAAG,KAAK,SAAS,YAAY,EAAE,IAAI;AAC/C,oBAAM,OAAO,MAAM,WAAW,KAAK;AACnC,uBAAS,KAAK,GAAG,KAAK,SAAS,aAAa,EAAE,IAAI;AAChD,sBAAM,WAAW,KAAK,mBAAmB,OAAO,MAAM,WAAW;AAAA,cACnE;AACA,0BAAY,SAAS;AAAA,YACvB;AAAA,UACF;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,EAAE,OAAO,EAAE,OAAO,KAAK;AACxD;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,sBAAsB,MAAM;AACnC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,IAAI;AAClB,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,iBAAiB,YAAY,IAAI;AACzE,mBAAiB,CAAC,GAAG,EAAE,GAAG,sBAAsB;AAChD,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,aAAaA,UAAS,GAAG,MAAM,iBAAiB,OAAO,WAAW;AACnI,QAAM,EAAE,cAAc,aAAa,cAAc,YAAY,IAAI;AACjE,QAAM,iBAAiB,SAAS,eAAe;AAC/C,QAAM,KAAK,IAAI,aAAa,SAAS,aAAa,SAAS;AAC3D,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,SAAS,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC5C,QAAM,OAAO,IAAI,aAAa,EAAE,OAAO,EAAE,OAAO,KAAK;AACrD,QAAM,QAAQ,IAAI,aAAa,GAAG,OAAO,GAAG,OAAO,MAAM;AACzD,WAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,UAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,MAAM,SAAS,MAAM,YAAY,CAAC;AACjE,UAAM,QAAQ,KAAK,IAAI,SAAS,YAAY,SAAS,WAAW,SAAS,MAAM,YAAY;AAC3F,aAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,YAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,MAAM,UAAU,MAAM,WAAW,CAAC;AACjE,YAAM,QAAQ,KAAK,IAAI,SAAS,WAAW,SAAS,UAAU,UAAU,MAAM,WAAW;AACzF,eAAS,KAAK,GAAG,KAAK,SAAS,YAAY,EAAE,IAAI;AAC/C,iBAAS,KAAK,GAAG,KAAK,SAAS,aAAa,EAAE,IAAI;AAChD,cAAI,UAAU;AACd,mBAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,qBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,oBAAM,KAAK,KAAK,KAAK,eAAe;AACpC,uBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,sBAAM,KAAK,KAAK,KAAK,cAAc;AACnC,oBAAI,gBAAgB;AAClB,6BAAW,KAAK,IAAI,GAAG,IAAI,IAAI,EAAE,IAAI,MAAM,IAAI,GAAG,IAAI,IAAI,EAAE;AAAA,gBAC9D,OAAO;AACL,6BAAW,KAAK,IAAI,GAAG,IAAI,IAAI,EAAE,IAAI,MAAM,IAAI,GAAG,IAAI,IAAI,EAAE;AAAA,gBAC9D;AAAA,cACF;AAAA,YACF;AAAA,UACF;AACA,aAAG,IAAI,SAAS,IAAI,IAAI,IAAI,EAAE;AAAA,QAChC;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,YAAY,gBAAgB,IAAI;AACxE,mBAAiB,CAAC,IAAI,MAAM,GAAG,qBAAqB;AACpD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,YAAY,aAAa,eAAe,GAAG,KAAK;AACtD,MAAI,cAAc,qBAAqB,wBAAwB,UAAU;AACzE,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,GAAG,MAAM,iBAAiB,OAAO,WAAW;AACvI,QAAM,KAAK,IAAI,aAAa,SAAS,SAAS,SAAS;AACvD,QAAM,WAAW,GAAG;AACpB,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,YAAY,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACnD,QAAM,CAAC,OAAO,OAAO,KAAK,IAAI;AAC9B,QAAM,EAAE,WAAW,cAAc,aAAa,YAAY,UAAU,SAAS,aAAa,WAAW,UAAU,cAAc,YAAY,IAAI;AAC7I,gBAAc,SAAS;AACvB,QAAM,SAAS,eAAe,IAAI,SAAS,QAAQ;AACnD,QAAM,UAAU,cAAc,IAAI,SAAS,QAAQ;AACnD,QAAM,iBAAiB,gBAAgB;AACvC,QAAM,eAAe,GAAG,QAAQ;AAChC,QAAM,aAAa,iBAAiB,GAAG,QAAQ,KAAK,GAAG,QAAQ;AAC/D,QAAM,aAAa,iBAAiB,GAAG,QAAQ,KAAK;AACpD,QAAM,iBAAiB,iBAAiB,IAAI,GAAG,QAAQ;AACvD,QAAM,eAAe,UAAU;AAC/B,QAAM,aAAa,iBAAiB,UAAU,KAAK,UAAU;AAC7D,QAAM,aAAa,iBAAiB,UAAU,KAAK;AACnD,QAAM,iBAAiB,iBAAiB,IAAI,UAAU;AACtD,WAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,aAAS,KAAK,GAAG,KAAK,YAAY,EAAE,IAAI;AACtC,eAAS,KAAK,GAAG,KAAK,UAAU,EAAE,IAAI;AACpC,cAAM,WAAW,KAAK;AACtB,cAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,KAAK,WAAW,YAAY,CAAC;AAC5D,cAAM,QAAQ,KAAK,IAAI,YAAY,eAAe,YAAY,YAAY;AAC1E,iBAAS,KAAK,GAAG,KAAK,SAAS,EAAE,IAAI;AACnC,gBAAM,WAAW,KAAK;AACtB,gBAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,KAAK,WAAW,WAAW,CAAC;AAC3D,gBAAM,QAAQ,KAAK,IAAI,WAAW,cAAc,YAAY,WAAW;AACvE,cAAI,UAAU;AACd,mBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,kBAAM,KAAK,KAAK,eAAe;AAC/B,qBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,oBAAM,KAAK,KAAK,cAAc;AAC9B,oBAAM,WAAW,eAAe,IAAI,aAAa,KAAK,aAAa;AACnE,oBAAM,YAAY,SAAS,eAAe,IAAI,MAAM,SAAS,cAAc,IAAI,MAAM,QAAQ;AAC7F,uBAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,sBAAM,QAAQ,SAAS,WAAW,iBAAiB;AACnD,sBAAM,SAAS,UAAU,YAAY;AACrC,2BAAW,QAAQ;AAAA,cACrB;AAAA,YACF;AAAA,UACF;AACA,gBAAM,WAAW,eAAe,IAAI,aAAa,KAAK,aAAa,KAAK,iBAAiB;AACzF,mBAAS,YAAY;AAAA,QACvB;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,UAAU,IAAI;AAC1C,mBAAiB,CAAC,GAAG,MAAM,GAAG,QAAQ;AACtC,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,IAAI;AACvG,QAAM,EAAE,aAAa,cAAc,aAAa,eAAe,gBAAgB,eAAe,QAAQ,IAAI;AAC1G,QAAM,WAAW,QAAQ;AACzB,QAAM,UAAU,QAAQ;AACxB,QAAM,SAAS,QAAQ;AACvB,QAAM,IAAI,IAAI,aAAa,SAAS,UAAU,EAAE,KAAK;AACrD,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,QAAQ,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AAC/C,QAAM,QAAQ,EAAE;AAChB,QAAM,WAAW,aAAa,eAAe,EAAE,KAAK;AACpD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,WAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,UAAM,WAAW,IAAI,SAAS;AAC9B,UAAM,WAAW,IAAI,EAAE,QAAQ;AAC/B,aAAS,KAAK,GAAG,KAAK,SAAS,UAAU,EAAE,IAAI;AAC7C,YAAM,WAAW,WAAW,KAAK,EAAE,QAAQ;AAC3C,YAAM,WAAW,KAAK,SAAS,cAAc;AAC7C,eAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,cAAM,KAAK,WAAW,KAAK;AAC3B,YAAI,KAAK,KAAK,MAAM,SAAS,SAAS;AACpC;AAAA,QACF;AACA,cAAM,WAAW,KAAK,cAAc;AACpC,cAAM,WAAW,WAAW,KAAK,SAAS;AAC1C,iBAAS,KAAK,GAAG,KAAK,SAAS,WAAW,EAAE,IAAI;AAC9C,gBAAM,WAAW,WAAW,KAAK,EAAE,QAAQ;AAC3C,gBAAM,WAAW,KAAK,SAAS,eAAe;AAC9C,mBAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,kBAAM,KAAK,WAAW,KAAK;AAC3B,gBAAI,KAAK,KAAK,MAAM,SAAS,UAAU;AACrC;AAAA,YACF;AACA,kBAAM,WAAW,WAAW,KAAK,cAAc;AAC/C,kBAAM,WAAW,WAAW,KAAK,SAAS;AAC1C,qBAAS,KAAK,GAAG,KAAK,SAAS,UAAU,EAAE,IAAI;AAC7C,oBAAM,WAAW,WAAW,KAAK,SAAS;AAC1C,oBAAM,WAAW,KAAK,SAAS,cAAc;AAC7C,uBAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,sBAAM,KAAK,WAAW,KAAK;AAC3B,oBAAI,KAAK,KAAK,MAAM,SAAS,SAAS;AACpC;AAAA,gBACF;AACA,sBAAM,WAAW,WAAW,KAAK,cAAc;AAC/C,sBAAM,WAAW,WAAW,KAAK,SAAS;AAC1C,oBAAI,WAAW;AACf,yBAAS,KAAK,GAAG,KAAK,SAAS,YAAY,EAAE,IAAI;AAC/C,wBAAM,OAAO,MAAM,WAAW;AAC9B,2BAAS,KAAK,GAAG,KAAK,SAAS,aAAa,EAAE,IAAI;AAChD,0BAAM,WAAW,OAAO,OAAO,MAAM,WAAW;AAAA,kBAClD;AACA,8BAAY,SAAS;AAAA,gBACvB;AAAA,cACF;AAAA,YACF;AAAA,UACF;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,EAAE,OAAO,EAAE,OAAO,EAAE,MAAM;AAC3D;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,uBAAuB,MAAM;AACpC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,IAAI;AAClB,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,IAAI;AAC5C,mBAAiB,CAAC,GAAG,EAAE,GAAG,wBAAwB;AAClD,QAAM,WAAW,aAAa,eAAe,EAAE,KAAK;AACpD,QAAM,YAAY,aAAa,eAAe,GAAG,KAAK;AACtD,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,aAAaA,UAAS,GAAG,IAAI;AAC9F,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,KAAK,IAAI,aAAa,SAAS,aAAa,SAAS;AAC3D,QAAM,WAAW,GAAG;AACpB,QAAM,CAAC,MAAM,MAAM,MAAM,IAAI,IAAI,GAAG;AACpC,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,CAAC,MAAM,MAAM,MAAM,IAAI,IAAI;AACjC,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAM,CAAC,KAAK,KAAK,KAAK,GAAG,IAAI;AAC7B,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,SAAS,SAAS,QAAQ;AAChC,WAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,UAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,MAAM,WAAW,MAAM,WAAW,CAAC;AAClE,UAAM,QAAQ,KAAK,IAAI,SAAS,WAAW,SAAS,UAAU,WAAW,MAAM,WAAW;AAC1F,UAAM,WAAW,KAAK;AACtB,aAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,YAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,MAAM,SAAS,MAAM,YAAY,CAAC;AACjE,YAAM,QAAQ,KAAK,IAAI,SAAS,YAAY,SAAS,WAAW,SAAS,MAAM,YAAY;AAC3F,YAAM,WAAW,KAAK,OAAO;AAC7B,eAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,cAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,MAAM,UAAU,MAAM,WAAW,CAAC;AACjE,cAAM,QAAQ,KAAK,IAAI,SAAS,WAAW,SAAS,UAAU,UAAU,MAAM,WAAW;AACzF,cAAM,WAAW,KAAK,OAAO;AAC7B,iBAAS,KAAK,GAAG,KAAK,SAAS,YAAY,EAAE,IAAI;AAC/C,gBAAM,WAAW,KAAK,OAAO;AAC7B,mBAAS,KAAK,GAAG,KAAK,SAAS,aAAa,EAAE,IAAI;AAChD,gBAAI,UAAU;AACd,qBAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,oBAAM,WAAW,IAAI;AACrB,oBAAM,WAAW,IAAI;AACrB,uBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,sBAAM,KAAK,KAAK,KAAK,cAAc;AACnC,sBAAM,WAAW,KAAK,MAAM;AAC5B,sBAAM,WAAW,KAAK,OAAO;AAC7B,yBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,wBAAM,KAAK,KAAK,KAAK,eAAe;AACpC,wBAAM,WAAW,KAAK,MAAM;AAC5B,wBAAM,WAAW,KAAK,OAAO;AAC7B,2BAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,0BAAM,KAAK,KAAK,KAAK,cAAc;AACnC,0BAAM,WAAW,KAAK,MAAM;AAC5B,0BAAM,WAAW,KAAK,OAAO;AAC7B,+BAAW,QAAQ,WAAW,MAAM,SAAS,WAAW;AAAA,kBAC1D;AAAA,gBACF;AAAA,cACF;AAAA,YACF;AACA,qBAAS,WAAW,MAAM;AAAA,UAC5B;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,sBAAsB,MAAM;AACnC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,KAAK,MAAM,SAAAA,UAAS,WAAW,IAAI;AAC3C,mBAAiB,CAAC,EAAE,GAAG,uBAAuB;AAC9C,QAAM,YAAY,aAAa,eAAe,GAAG,KAAK;AACtD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,GAAG,IAAI;AAClG,QAAM,KAAK,IAAI,aAAa,SAAS,SAAS,SAAS;AACvD,QAAM,WAAW,GAAG;AACpB,QAAM,CAAC,MAAM,MAAM,MAAM,IAAI,IAAI,GAAG;AACpC,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,CAAC,MAAM,MAAM,MAAM,IAAI,IAAI;AACjC,QAAM,YAAY,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACnD,QAAM,CAAC,OAAO,OAAO,OAAO,KAAK,IAAI;AACrC,QAAM,EAAE,WAAW,aAAa,cAAc,aAAa,YAAY,SAAS,UAAU,SAAS,aAAa,UAAU,WAAW,UAAU,aAAa,cAAc,YAAY,IAAI;AAC1L,QAAM,WAAW,cAAc,IAAI,SAAS,QAAQ;AACpD,QAAM,SAAS,eAAe,IAAI,SAAS,QAAQ;AACnD,QAAM,UAAU,cAAc,IAAI,SAAS,QAAQ;AACnD,WAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,aAAS,KAAK,GAAG,KAAK,YAAY,EAAE,IAAI;AACtC,eAAS,KAAK,GAAG,KAAK,SAAS,EAAE,IAAI;AACnC,cAAM,WAAW,KAAK;AACtB,cAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,KAAK,WAAW,WAAW,CAAC;AAC3D,cAAM,QAAQ,KAAK,IAAI,WAAW,cAAc,YAAY,WAAW;AACvE,iBAAS,KAAK,GAAG,KAAK,UAAU,EAAE,IAAI;AACpC,gBAAM,WAAW,KAAK;AACtB,gBAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,KAAK,WAAW,YAAY,CAAC;AAC5D,gBAAM,QAAQ,KAAK,IAAI,YAAY,eAAe,YAAY,YAAY;AAC1E,mBAAS,KAAK,GAAG,KAAK,SAAS,EAAE,IAAI;AACnC,kBAAM,WAAW,KAAK;AACtB,kBAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,KAAK,WAAW,WAAW,CAAC;AAC3D,kBAAM,QAAQ,KAAK,IAAI,WAAW,cAAc,YAAY,WAAW;AACvE,gBAAI,UAAU;AACd,qBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,oBAAM,KAAK,KAAK,cAAc;AAC9B,uBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,sBAAM,KAAK,KAAK,eAAe;AAC/B,yBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,wBAAM,KAAK,KAAK,cAAc;AAC9B,wBAAM,WAAW,OAAO,IAAI,OAAO,KAAK,OAAO,KAAK,OAAO;AAC3D,wBAAM,YAAY,SAAS,cAAc,IAAI,MAAM,SAAS,eAAe,IAAI,MAAM,SAAS,cAAc,IAAI,MAAM,QAAQ;AAC9H,2BAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,0BAAM,QAAQ,SAAS,WAAW;AAClC,0BAAM,SAAS,UAAU,YAAY;AACrC,+BAAW,QAAQ;AAAA,kBACrB;AAAA,gBACF;AAAA,cACF;AAAA,YACF;AACA,qBAAS,OAAO,IAAI,OAAO,KAAK,OAAO,KAAK,OAAO,KAAK,MAAM;AAAA,UAChE;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,gBAAgB,KAAK,CAAC,OAAO,KAAK,IAAI,EAAE,CAAC;AACpD,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,OAAO,OAAO,IAAI;AACzC,QAAM,EAAE,UAAU,QAAQ,mBAAmB,IAAI;AACjD,QAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,QAAM,WAAW,MAAM,MAAM;AAC7B,QAAM,CAAC,YAAY,SAAS,IAAI;AAChC,QAAM,SAAS,OAAO,CAAC,UAAU,YAAY,WAAW,WAAW,GAAG,SAAS;AAC/E,QAAM,UAAU,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AAChD,QAAM,aAAa,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACpD,QAAM,YAAY,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACnD,QAAM,WAAW,aAAa,eAAe,OAAO,KAAK;AACzD,QAAM,YAAY,aAAa,eAAe,OAAO,KAAK;AAC1D,WAAS,IAAI,GAAG,IAAI,UAAU,KAAK;AACjC,UAAM,WAAW,IAAI;AACrB,UAAM,KAAK,QAAQ;AACnB,UAAM,KAAK,QAAQ,WAAW;AAC9B,UAAM,KAAK,QAAQ,WAAW;AAC9B,UAAM,KAAK,QAAQ,WAAW;AAC9B,UAAM,OAAO,WAAW;AACxB,QAAI,QAAQ,OAAO;AACjB;AAAA,IACF;AACA,UAAM,cAAc,aAAa,KAAK,KAAK,OAAO,cAAc,MAAM,aAAa,KAAK;AACxF,UAAM,aAAa,YAAY,KAAK,KAAK,OAAO,aAAa,MAAM,YAAY,KAAK;AACpF,aAAS,IAAI,GAAG,IAAI,YAAY,KAAK;AACnC,YAAM,OAAO,aAAa,IAAI,MAAM,cAAc,KAAK,IAAI,cAAc,OAAO,KAAK,OAAO,cAAc;AAC1G,UAAI,OAAO,KAAK,OAAO,cAAc,GAAG;AACtC,iBAAS,IAAI,GAAG,IAAI,WAAW,KAAK;AAClC,mBAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,kBAAM,MAAM,IAAI,IAAI,UAAU,KAAK,IAAI,UAAU,KAAK,IAAI,UAAU;AACpE,mBAAO,OAAO,OAAO;AAAA,UACvB;AAAA,QACF;AACA;AAAA,MACF;AACA,UAAI,WAAW,YAAY;AACzB,cAAM,SAAS,KAAK,MAAM,IAAI;AAC9B,cAAM,YAAY,KAAK,KAAK,IAAI;AAChC,cAAM,QAAQ,OAAO;AACrB,iBAAS,IAAI,GAAG,IAAI,WAAW,KAAK;AAClC,gBAAM,OAAO,YAAY,IAAI,MAAM,aAAa,KAAK,IAAI,aAAa,OAAO,KAAK,OAAO,aAAa;AACtG,cAAI,OAAO,KAAK,OAAO,aAAa,GAAG;AACrC,qBAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,oBAAM,MAAM,IAAI,IAAI,UAAU,KAAK,IAAI,UAAU,KAAK,IAAI,UAAU;AACpE,qBAAO,OAAO,OAAO;AAAA,YACvB;AACA;AAAA,UACF;AACA,gBAAM,UAAU,KAAK,MAAM,IAAI;AAC/B,gBAAM,WAAW,KAAK,KAAK,IAAI;AAC/B,gBAAM,QAAQ,OAAO;AACrB,mBAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,gBAAI,MAAM,IAAI,UAAU,SAAS,KAAK,SAAS,SAAS,KAAK,OAAO,SAAS;AAC7E,kBAAM,UAAU,UAAU;AAC1B,kBAAM,IAAI,WAAW,SAAS,KAAK,SAAS,SAAS,KAAK,OAAO,SAAS;AAC1E,kBAAM,WAAW,UAAU;AAC3B,kBAAM,IAAI,UAAU,SAAS,KAAK,YAAY,SAAS,KAAK,OAAO,SAAS;AAC5E,kBAAM,aAAa,UAAU;AAC7B,kBAAM,IAAI,WAAW,SAAS,KAAK,YAAY,SAAS,KAAK,OAAO,SAAS;AAC7E,kBAAM,cAAc,UAAU;AAC9B,kBAAM,MAAM,WAAW,WAAW,WAAW;AAC7C,kBAAM,SAAS,cAAc,cAAc,cAAc;AACzD,kBAAM,IAAI,IAAI,UAAU,KAAK,IAAI,UAAU,KAAK,IAAI,UAAU;AAC9D,mBAAO,OAAO,OAAO,OAAO,SAAS,OAAO;AAAA,UAC9C;AAAA,QACF;AAAA,MACF,OAAO;AACL,iBAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,gBAAM,OAAO,YAAY,IAAI,MAAM,aAAa,KAAK,IAAI,aAAa,OAAO,KAAK,OAAO,aAAa;AACtG,cAAI,OAAO,KAAK,OAAO,aAAa,GAAG;AACrC,qBAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,oBAAM,MAAM,IAAI,IAAI,UAAU,KAAK,IAAI,UAAU,KAAK,IAAI,UAAU;AACpE,qBAAO,OAAO,OAAO;AAAA,YACvB;AACA;AAAA,UACF;AACA,gBAAM,WAAW,KAAK,MAAM,IAAI;AAChC,gBAAM,WAAW,KAAK,MAAM,IAAI;AAChC,mBAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,kBAAM,QAAQ,IAAI,WAAW,SAAS,KAAK,WAAW,SAAS,KAAK,OAAO,SAAS;AACpF,kBAAM,SAAS,IAAI,IAAI,UAAU,KAAK,IAAI,UAAU,KAAK,IAAI,UAAU;AACvE,mBAAO,OAAO,UAAU,UAAU;AAAA,UACpC;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC1E;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,mBAAiB,GAAG,SAAS;AAC7B,QAAM,cAAc,qBAAqB,mBAAmB,CAAC,IAAI,GAAG,EAAE,MAAM,MAAM;AAClF,MAAI,KAAK;AACT,MAAI,eAAe,MAAM;AACvB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,YAAY,EAAE,CAAC;AAAA,EACpF;AACA,QAAM,eAAe,qBAAqB,iBAAiB,GAAG,EAAE,MAAM,MAAM,EAAE;AAC9E,MAAI,iBAAiB,GAAG,MAAM,SAAS,GAAG;AACxC,UAAM,IAAI,MAAM,qDAAqD,GAAG,MAAM,SAAS,kBAAkB,cAAc;AAAA,EACzH;AACA,QAAM,cAAc,WAAW,GAAG,OAAO,OAAO;AAChD,QAAM,OAAO,aAAa,mBAAmB,aAAa,cAAc,GAAG,KAAK,GAAG,WAAW;AAC9F,QAAM,QAAQ,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC3C,QAAM,WAAW,GAAG,MAAM,GAAG,MAAM,SAAS;AAC5C,QAAM,gBAAgB,WAAW,CAAC,IAAI,MAAM,KAAK,WAAW,IAAI,IAAI,CAAC,IAAI,MAAM,KAAK;AACpF,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM,UAAU;AAClD,aAAS,IAAI,GAAG,IAAI,UAAU,KAAK;AACjC,YAAM,MAAM,cAAc,IAAI,CAAC;AAC/B,UAAI,MAAM,GAAG;AACX,aAAK,OAAO,YAAY,IAAI,MAAM;AAAA,MACpC,OAAO;AACL,cAAM,UAAU,cAAc,IAAI,IAAI,CAAC;AACvC,aAAK,OAAO,YAAY,MAAM,WAAW,KAAK,WAAW,MAAM,OAAO,KAAK;AAAA,MAC7E;AAAA,IACF;AAAA,EACF;AACA,QAAM,SAAS,SAAS,eAAe,GAAG,OAAO,aAAa,IAAI;AAClE,MAAI,eAAe,MAAM;AACvB,UAAM,qBAAqB,qBAAqB,uBAAuB,WAAW;AAClF,UAAM,0BAA0B,WAAW,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,mBAAmB,EAAE,CAAC;AAC5H,aAAS,8BAA8B,MAAM;AAC7C,aAAS,8BAA8B,EAAE;AACzC,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,mBAAiB,GAAG,QAAQ;AAC5B,QAAM,cAAc,qBAAqB,mBAAmB,CAAC,IAAI,GAAG,EAAE,MAAM,MAAM;AAClF,MAAI,KAAK;AACT,MAAI,eAAe,MAAM;AACvB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,YAAY,EAAE,CAAC;AAAA,EACpF;AACA,QAAM,eAAe,qBAAqB,iBAAiB,GAAG,EAAE,MAAM,MAAM,EAAE;AAC9E,MAAI,iBAAiB,GAAG,MAAM,SAAS,GAAG;AACxC,UAAM,IAAI,MAAM,oDAAoD,GAAG,MAAM,SAAS,kBAAkB,cAAc;AAAA,EACxH;AACA,QAAM,cAAc,WAAW,GAAG,OAAO,OAAO;AAChD,QAAM,OAAO,aAAa,oBAAoB,aAAa,cAAc,GAAG,KAAK,GAAG,WAAW;AAC/F,QAAM,QAAQ,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC3C,QAAM,WAAW,GAAG,MAAM,GAAG,MAAM,SAAS;AAC5C,QAAM,gBAAgB,WAAW,CAAC,IAAI,MAAM,KAAK,WAAW,IAAI,IAAI,CAAC,IAAI,MAAM,KAAK;AACpF,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM,UAAU;AAClD,aAAS,IAAI,GAAG,IAAI,UAAU,KAAK;AACjC,YAAM,MAAM,cAAc,IAAI,CAAC;AAC/B,UAAI,MAAM,GAAG;AACX,aAAK,OAAO,YAAY,IAAI,MAAM;AAAA,MACpC,OAAO;AACL,cAAM,UAAU,cAAc,IAAI,IAAI,CAAC;AACvC,aAAK,OAAO,YAAY,MAAM,WAAW,KAAK,WAAW,MAAM,OAAO,KAAK;AAAA,MAC7E;AAAA,IACF;AAAA,EACF;AACA,QAAM,SAAS,SAAS,eAAe,GAAG,OAAO,aAAa,IAAI;AAClE,MAAI,eAAe,MAAM;AACvB,UAAM,qBAAqB,qBAAqB,uBAAuB,WAAW;AAClF,UAAM,0BAA0B,WAAW,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,mBAAmB,EAAE,CAAC;AAC5H,aAAS,8BAA8B,MAAM;AAC7C,aAAS,8BAA8B,EAAE;AACzC,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAAZ,OAAM,aAAa,IAAI;AAC/B,MAAI,EAAE,MAAM,WAAW,GAAG;AACxB,UAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,UAAM,cAAc,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACtD,UAAM,UAAU,aAAa,OAAO,aAAa,QAAQ,OAAO,QAAQ,OAAOA,KAAI;AACnF,WAAO,SAAS,eAAe,CAACA,KAAI,GAAG,QAAQ,OAAO,OAAO;AAAA,EAC/D,WAAW,EAAE,MAAM,WAAW,GAAG;AAC/B,UAAM,OAAO,SAAS,WAAW,CAAC;AAClC,UAAM,aAAa,SAAS,WAAW,OAAO;AAC9C,UAAM,SAAS,mBAAmB,MAAM,YAAYA,OAAM,YAAY;AACtE,WAAO,SAAS,eAAe,OAAO,OAAO,QAAQ,OAAO,OAAO,MAAM;AAAA,EAC3E;AACA,QAAM,IAAI,MAAM,qEAAqE,EAAE,MAAM,SAAS;AACxG;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,WAAW,WAAW,IAAI;AAClC,eAAa,OAAO,eAAe,QAAQ,MAAM,+DAA+D,YAAY;AAC5H,QAAM,YAAY,EAAE,MAAM;AAC1B,QAAM,cAAc,EAAE,MAAM;AAC5B,QAAM,aAAa,EAAE,MAAM;AAC3B,QAAM,aAAa,EAAE,MAAM;AAC3B,QAAM,eAAe,cAAc;AACnC,QAAM,cAAc,aAAa;AACjC,QAAM,cAAc,cAAc,YAAY;AAC9C,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAM,SAAS,IAAI,aAAa,YAAY,eAAe,cAAc,WAAW;AACpF,MAAI,YAAY;AAChB,WAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,aAAS,IAAI,GAAG,IAAI,cAAc,EAAE,GAAG;AACrC,YAAM,MAAM,KAAK,MAAM,IAAI,SAAS;AACpC,YAAM,UAAU,IAAI;AACpB,eAAS,IAAI,GAAG,IAAI,aAAa,EAAE,GAAG;AACpC,cAAM,MAAM,KAAK,MAAM,IAAI,SAAS;AACpC,cAAM,UAAU,IAAI;AACpB,cAAM,WAAW,UAAU,YAAY,WAAW;AAClD,iBAAS,IAAI,GAAG,IAAI,aAAa,EAAE,GAAG;AACpC,gBAAM,MAAM,IAAI;AAChB,gBAAM,WAAW,MAAM,cAAc,MAAM,cAAc,MAAM,cAAc;AAC7E,iBAAO,eAAe,QAAQ;AAAA,QAChC;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,CAAC,WAAW,cAAc,aAAa,WAAW,GAAG,EAAE,OAAO,MAAM;AACrG;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,sBAAsB,MAAM;AACnC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAY,UAAS,KAAK,MAAM,WAAW,gBAAgB,IAAI;AAC3D,mBAAiB,CAAC,GAAG,MAAM,GAAG,uBAAuB;AACrD,QAAM,WAAW,aAAa,eAAe,EAAE,KAAK;AACpD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,MAAI,aAAa;AACjB,MAAI,cAAc,MAAM;AACtB,iBAAa,CAAC,GAAG,CAAC;AAAA,EACpB;AACA,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,UAAU,GAAG,MAAM,gFAAgFA,2BAA0B,aAAa;AAC3N,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,YAAY,MAAM,iBAAiB,IAAI;AAC/H,QAAM,EAAE,cAAc,aAAa,gBAAgB,eAAe,QAAQ,IAAI;AAC9E,QAAM,UAAU,QAAQ;AACxB,QAAM,SAAS,QAAQ;AACvB,QAAM,QAAQ,SAAS,cAAc,SAAS;AAC9C,QAAM,IAAI,IAAI,aAAa,SAAS,UAAU,EAAE,KAAK;AACrD,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,QAAQ,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AAC/C,QAAM,QAAQ,EAAE;AAChB,WAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,UAAM,WAAW,IAAI,SAAS;AAC9B,UAAM,WAAW,IAAI,EAAE,QAAQ;AAC/B,aAAS,KAAK,GAAG,KAAK,SAAS,WAAW,EAAE,IAAI;AAC9C,YAAM,WAAW,WAAW,KAAK,EAAE,QAAQ;AAC3C,YAAM,WAAW,KAAK,SAAS,eAAe;AAC9C,eAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,cAAM,KAAK,WAAW,KAAK;AAC3B,YAAI,KAAK,KAAK,MAAM,SAAS,UAAU;AACrC;AAAA,QACF;AACA,cAAM,WAAW,KAAK,cAAc;AACpC,cAAM,WAAW,WAAW,KAAK,SAAS;AAC1C,iBAAS,KAAK,GAAG,KAAK,SAAS,UAAU,EAAE,IAAI;AAC7C,gBAAM,WAAW,WAAW,KAAK,EAAE,QAAQ;AAC3C,gBAAM,WAAW,KAAK,SAAS,cAAc;AAC7C,mBAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,kBAAM,KAAK,WAAW,KAAK;AAC3B,gBAAI,KAAK,KAAK,MAAM,SAAS,SAAS;AACpC;AAAA,YACF;AACA,kBAAM,WAAW,WAAW,KAAK,cAAc;AAC/C,kBAAM,WAAW,WAAW,KAAK,SAAS;AAC1C,gBAAI,WAAW;AACf,gBAAI,WAAW;AACf,qBAAS,KAAK,GAAG,KAAK,SAAS,YAAY,EAAE,IAAI;AAC/C,oBAAM,OAAO,MAAM,WAAW;AAC9B,uBAAS,IAAI,GAAG,IAAI,OAAO,EAAE,GAAG;AAC9B,sBAAM,WAAW,MAAM,OAAO,MAAM,WAAW;AAAA,cACjD;AACA,0BAAY;AACZ,0BAAY;AAAA,YACd;AAAA,UACF;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,EAAE,OAAO,EAAE,OAAO,EAAE,MAAM;AAC3D;AACA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qCAAqC,MAAM;AAClD,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,IAAI;AAClB,QAAM,EAAE,SAAAA,UAAS,WAAW,KAAK,MAAM,iBAAiB,YAAY,IAAI;AACxE,mBAAiB,CAAC,GAAG,EAAE,GAAG,qCAAqC;AAC/D,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,aAAaA,UAAS,WAAW,MAAM,iBAAiB,IAAI;AAC7H,QAAM,EAAE,cAAc,aAAa,cAAc,YAAY,IAAI;AACjE,QAAM,KAAK,IAAI,aAAa,SAAS,aAAa,SAAS;AAC3D,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,QAAQ,SAAS,cAAc,SAAS;AAC9C,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,OAAO,IAAI,aAAa,EAAE,OAAO,EAAE,OAAO,KAAK;AACrD,QAAM,SAAS,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC5C,QAAM,QAAQ,IAAI,aAAa,GAAG,OAAO,GAAG,OAAO,MAAM;AACzD,WAAS,KAAK,GAAG,KAAK,cAAc,EAAE,IAAI;AACxC,UAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,MAAM,SAAS,MAAM,YAAY,CAAC;AACjE,UAAM,QAAQ,KAAK,IAAI,SAAS,YAAY,SAAS,WAAW,SAAS,MAAM,YAAY;AAC3F,aAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,YAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,MAAM,UAAU,MAAM,WAAW,CAAC;AACjE,YAAM,QAAQ,KAAK,IAAI,SAAS,WAAW,SAAS,UAAU,UAAU,MAAM,WAAW;AACzF,eAAS,KAAK,GAAG,KAAK,SAAS,aAAa,EAAE,IAAI;AAChD,cAAM,KAAK,KAAK,MAAM,KAAK,KAAK;AAChC,cAAM,KAAK,KAAK;AAChB,YAAI,UAAU;AACd,iBAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,mBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,kBAAM,KAAK,KAAK,KAAK,eAAe;AACpC,qBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,oBAAM,KAAK,KAAK,KAAK,cAAc;AACnC,yBAAW,KAAK,IAAI,GAAG,IAAI,IAAI,EAAE,IAAI,MAAM,IAAI,GAAG,IAAI,IAAI,EAAE;AAAA,YAC9D;AAAA,UACF;AAAA,QACF;AACA,WAAG,IAAI,SAAS,IAAI,IAAI,IAAI,EAAE;AAAA,MAChC;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,4CAA4C;AAAA,EAC9C,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,oCAAoC,MAAM;AACjD,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,SAAAA,UAAS,WAAW,KAAK,MAAM,iBAAiB,WAAW,IAAI;AACvE,mBAAiB,CAAC,IAAI,MAAM,GAAG,oCAAoC;AACnE,QAAM,YAAY,aAAa,eAAe,GAAG,KAAK;AACtD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,IAAI;AACjI,QAAM,KAAK,IAAI,aAAa,SAAS,SAAS,SAAS;AACvD,QAAM,WAAW,GAAG;AACpB,QAAM,CAAC,MAAM,MAAM,IAAI,IAAI,GAAG;AAC9B,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,CAAC,MAAM,MAAM,IAAI,IAAI;AAC3B,QAAM,YAAY,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACnD,QAAM,CAAC,OAAO,OAAO,KAAK,IAAI;AAC9B,QAAM,EAAE,WAAW,cAAc,aAAa,YAAY,UAAU,SAAS,aAAa,WAAW,UAAU,cAAc,YAAY,IAAI;AAC7I,QAAM,SAAS,eAAe,IAAI,SAAS,QAAQ;AACnD,QAAM,UAAU,cAAc,IAAI,SAAS,QAAQ;AACnD,QAAM,QAAQ,cAAc;AAC5B,WAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,aAAS,KAAK,GAAG,KAAK,YAAY,EAAE,IAAI;AACtC,eAAS,KAAK,GAAG,KAAK,UAAU,EAAE,IAAI;AACpC,cAAM,WAAW,KAAK;AACtB,cAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,KAAK,WAAW,YAAY,CAAC;AAC5D,cAAM,QAAQ,KAAK,IAAI,YAAY,eAAe,YAAY,YAAY;AAC1E,iBAAS,KAAK,GAAG,KAAK,SAAS,EAAE,IAAI;AACnC,gBAAM,WAAW,KAAK;AACtB,gBAAM,QAAQ,KAAK,IAAI,GAAG,KAAK,KAAK,WAAW,WAAW,CAAC;AAC3D,gBAAM,QAAQ,KAAK,IAAI,WAAW,cAAc,YAAY,WAAW;AACvE,cAAI,UAAU;AACd,mBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,kBAAM,KAAK,KAAK,eAAe;AAC/B,qBAAS,KAAK,OAAO,KAAK,OAAO,EAAE,IAAI;AACrC,oBAAM,KAAK,KAAK,cAAc;AAC9B,oBAAM,WAAW,OAAO,IAAI,OAAO,KAAK,OAAO;AAC/C,oBAAM,YAAY,SAAS,eAAe,IAAI,MAAM,SAAS,cAAc,IAAI,MAAM,QAAQ;AAC7F,uBAAS,KAAK,GAAG,KAAK,OAAO,EAAE,IAAI;AACjC,sBAAM,KAAK,KAAK,QAAQ;AACxB,sBAAM,QAAQ,SAAS,WAAW;AAClC,sBAAM,SAAS,UAAU,YAAY;AACrC,2BAAW,QAAQ;AAAA,cACrB;AAAA,YACF;AAAA,UACF;AACA,mBAAS,OAAO,IAAI,OAAO,KAAK,OAAO,KAAK,MAAM;AAAA,QACpD;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,2CAA2C;AAAA,EAC7C,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,SAAS,OAAO,CAAC,OAAO,KAAK,GAAG,EAAE,KAAK;AAC7C,QAAM,OAAO,OAAO;AACpB,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,SAAK,KAAK,QAAQ,MAAM,MAAM;AAAA,EAChC;AACA,QAAM,WAAW,CAAC,GAAG,EAAE,OAAO,GAAG,EAAE,KAAK;AACxC,SAAO,SAAS,eAAe,UAAU,OAAO,OAAO,OAAO,MAAM;AACtE;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,SAAS,UAAU,MAAM,MAAM;AACpD,UAAM,EAAE,GAAG,OAAO,IAAI;AACtB,UAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,UAAU,IAAI;AAC1C,UAAM,aAAa;AACnB,UAAM,QAAQ,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,UAAM,QAAQ,EAAE,MAAM;AACtB,UAAM,aAAa,WAAW,KAAK,IAAI,OAAO,MAAM,EAAE;AACtD,UAAM,aAAa,OAAO,MAAM;AAChC,UAAM,EAAE,WAAW,UAAU,SAAS,YAAY,WAAW,UAAU,SAAS,cAAc,aAAa,cAAc,aAAa,gBAAgB,eAAe,SAAS,IAAI,qBAAqB,sBAAsB,EAAE,OAAO,OAAO,OAAOA,UAAS,MAAM,QAAQ,SAAS;AACpR,UAAM,UAAU,aAAa,cAAc,QAAQ;AACnD,UAAM,UAAU,SAAS;AACzB,UAAM,aAAa,aAAa,kBAAkB,EAAE,OAAO,OAAO;AAClE,aAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,eAAS,OAAO,GAAG,OAAO,WAAW,EAAE,MAAM;AAC3C,cAAM,OAAO,OAAO,eAAe,QAAQ;AAC3C,iBAAS,OAAO,GAAG,OAAO,UAAU,EAAE,MAAM;AAC1C,gBAAM,OAAO,OAAO,cAAc,QAAQ;AAC1C,mBAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,gBAAI,SAAS,OAAO;AACpB,qBAAS,IAAI,GAAG,IAAI,cAAc,EAAE,GAAG;AACrC,oBAAM,MAAM,OAAO,IAAI;AACvB,kBAAI,OAAO,KAAK,MAAM,UAAU;AAC9B,yBAAS,IAAI,GAAG,IAAI,aAAa,EAAE,GAAG;AACpC,wBAAM,MAAM,OAAO,IAAI;AACvB,sBAAI,OAAO,KAAK,MAAM,SAAS;AAC7B,0BAAM,SAAS,aAAa,WAAW,CAAC,GAAG,KAAK,KAAK,CAAC,GAAG,OAAO,aAAa,eAAe,EAAE,KAAK,CAAC;AACpG,0BAAM,cAAc,aAAa,WAAW,CAAC,GAAG,GAAG,CAAC,GAAG,YAAY,aAAa,eAAe,OAAO,KAAK,CAAC;AAC5G,0BAAM,MAAM,MAAM,UAAU,WAAW;AACvC,wBAAI,MAAM,QAAQ;AAChB,+BAAS;AAAA,oBACX;AAAA,kBACF;AAAA,gBACF;AAAA,cACF;AAAA,YACF;AACA,kBAAM,cAAc,aAAa,WAAW,CAAC,GAAG,MAAM,MAAM,CAAC,GAAG,SAAS,aAAa,eAAe,QAAQ,CAAC;AAC9G,uBAAW,eAAe;AAAA,UAC5B;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,SAAS,WAAW,MAAM,aAAa,aAAa,YAAY,EAAE,KAAK,GAAG,UAAU,EAAE,KAAK;AACjG,WAAO,EAAE,QAAQ,OAAO,UAAU,OAAO,EAAE,MAAM;AAAA,EACnD;AACF;AAGA,IAAI,iCAAiC;AAAA,EACnC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,SAAS,UAAU,MAAM,MAAM;AACpD,UAAM,EAAE,GAAG,QAAQ,GAAG,IAAI;AAC1B,UAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,UAAU,IAAI;AAC1C,UAAM,aAAa;AACnB,UAAM,KAAK,aAAa,cAAc,EAAE,OAAO,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE,MAAM;AACnF,UAAM,UAAU,aAAa,cAAc,OAAO,OAAO,WAAW,KAAK,IAAI,OAAO,MAAM,EAAE,MAAM;AAClG,UAAM,EAAE,WAAW,UAAU,SAAS,YAAY,WAAW,UAAU,SAAS,cAAc,aAAa,cAAc,aAAa,gBAAgB,eAAe,SAAS,IAAI,qBAAqB,sBAAsB,EAAE,OAAO,OAAO,OAAOA,UAAS,MAAM,QAAQ,SAAS;AACpR,iBAAa,OAAO,GAAG,SAAS,SAAS,QAAQ,MAAM,YAAY,kEAAkE,SAAS,mBAAmB,GAAG,MAAM;AAC1K,UAAM,MAAM,aAAa,cAAc,UAAU,WAAW,KAAK,IAAI,GAAG,MAAM,EAAE,MAAM;AACtF,UAAM,YAAY,aAAa,0BAA0B,OAAO,OAAO,OAAO,KAAK;AACnF,aAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,eAAS,OAAO,GAAG,OAAO,WAAW,EAAE,MAAM;AAC3C,cAAM,OAAO,OAAO,eAAe,QAAQ;AAC3C,iBAAS,OAAO,GAAG,OAAO,UAAU,EAAE,MAAM;AAC1C,gBAAM,OAAO,OAAO,cAAc,QAAQ;AAC1C,mBAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,gBAAI,SAAS,OAAO;AACpB,gBAAI,OAAO;AACX,gBAAI,OAAO;AACX,qBAAS,IAAI,GAAG,IAAI,cAAc,EAAE,GAAG;AACrC,oBAAM,MAAM,OAAO,IAAI;AACvB,kBAAI,OAAO,KAAK,MAAM,UAAU;AAC9B,yBAAS,IAAI,GAAG,IAAI,aAAa,EAAE,GAAG;AACpC,wBAAM,MAAM,OAAO,IAAI;AACvB,sBAAI,OAAO,KAAK,MAAM,SAAS;AAC7B,0BAAM,MAAM,GAAG,GAAG,KAAK,KAAK,KAAK,QAAQ,GAAG,GAAG;AAC/C,wBAAI,MAAM,QAAQ;AAChB,+BAAS;AACT,6BAAO;AACP,6BAAO;AAAA,oBACT;AAAA,kBACF;AAAA,gBACF;AAAA,cACF;AAAA,YACF;AACA,sBAAU,MAAM,MAAM,MAAM,IAAI,GAAG,MAAM,MAAM;AAAA,UACjD;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,SAAS,WAAW,MAAM,aAAa,aAAa,WAAW,EAAE,KAAK,GAAG,OAAO,OAAO,OAAO,KAAK;AACzG,WAAO,EAAE,QAAQ,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAAA,EAC5D;AACF;AAGA,IAAI,gCAAgC;AAAA,EAClC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,SAAS,UAAU,MAAM,MAAM;AACpD,UAAM,EAAE,GAAG,QAAQ,GAAG,IAAI;AAC1B,UAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,UAAU,IAAI;AAC1C,UAAM,aAAa;AACnB,UAAM,KAAK,aAAa,cAAc,EAAE,OAAO,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE,MAAM;AACnF,UAAM,UAAU,aAAa,cAAc,OAAO,OAAO,WAAW,KAAK,IAAI,OAAO,MAAM,EAAE,MAAM;AAClG,UAAM,EAAE,WAAW,UAAU,SAAS,YAAY,WAAW,UAAU,SAAS,cAAc,aAAa,cAAc,aAAa,gBAAgB,eAAe,SAAS,IAAI,qBAAqB,sBAAsB,EAAE,OAAO,OAAO,OAAOA,UAAS,MAAM,QAAQ,SAAS;AACpR,iBAAa,OAAO,GAAG,SAAS,SAAS,QAAQ,MAAM,YAAY,iEAAiE,SAAS,mBAAmB,GAAG,MAAM;AACzK,UAAM,MAAM,aAAa,cAAc,UAAU,WAAW,KAAK,IAAI,GAAG,MAAM,EAAE,MAAM;AACtF,UAAM,YAAY,aAAa,0BAA0B,EAAE,OAAO,EAAE,KAAK;AACzE,aAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,eAAS,OAAO,GAAG,OAAO,WAAW,EAAE,MAAM;AAC3C,cAAM,OAAO,OAAO,eAAe,QAAQ;AAC3C,iBAAS,OAAO,GAAG,OAAO,UAAU,EAAE,MAAM;AAC1C,gBAAM,OAAO,OAAO,cAAc,QAAQ;AAC1C,mBAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,gBAAI,SAAS,OAAO;AACpB,gBAAI,SAAS,OAAO,IAAI,IAAI;AAC5B,gBAAI,SAAS,OAAO,IAAI,IAAI;AAC5B,qBAAS,IAAI,GAAG,IAAI,cAAc,EAAE,GAAG;AACrC,oBAAM,MAAM,OAAO,IAAI;AACvB,kBAAI,OAAO,KAAK,MAAM,UAAU;AAC9B,yBAAS,IAAI,GAAG,IAAI,aAAa,EAAE,GAAG;AACpC,wBAAM,MAAM,OAAO,IAAI;AACvB,sBAAI,OAAO,KAAK,MAAM,SAAS;AAC7B,0BAAM,MAAM,GAAG,GAAG,KAAK,KAAK,KAAK,QAAQ,GAAG,GAAG;AAC/C,wBAAI,MAAM,QAAQ;AAChB,+BAAS;AACT,+BAAS;AACT,+BAAS;AAAA,oBACX;AAAA,kBACF;AAAA,gBACF;AAAA,cACF;AAAA,YACF;AACA,sBAAU,GAAG,QAAQ,QAAQ,MAAM,IAAI,GAAG,MAAM,MAAM;AAAA,UACxD;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,SAAS,WAAW,MAAM,aAAa,aAAa,WAAW,EAAE,KAAK,GAAG,EAAE,OAAO,EAAE,KAAK;AAC/F,WAAO,EAAE,QAAQ,OAAO,EAAE,OAAO,OAAO,EAAE,MAAM;AAAA,EAClD;AACF;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,mBAAiB,GAAG,KAAK;AACzB,MAAI;AACJ,MAAI,EAAE,UAAU,QAAQ;AACtB,SAAK,MAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,QAAQ,EAAE,CAAC;AAAA,EAC5E,OAAO;AACL,SAAK,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACrD;AACA,QAAM,QAAQ,GAAG,MAAM;AACvB,QAAM,OAAO,aAAa,eAAe,MAAM,GAAG,KAAK;AACvD,QAAM,cAAc,qBAAqB,mBAAmB,MAAM,KAAK;AACvE,MAAI,gBAAgB;AACpB,MAAI,YAAY;AAChB,MAAI,eAAe,MAAM;AACvB,gBAAY,WAAW,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,YAAY,EAAE,CAAC;AAC7F,oBAAgB,qBAAqB,iBAAiB,cAAc,QAAQ,KAAK;AAAA,EACnF;AACA,uBAAqB,2BAA2B,OAAO,eAAe,UAAU,MAAM,MAAM;AAC5F,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,UAAU,OAAO,aAAa;AAC7G,QAAM,cAAc,qBAAqB,WAAW,UAAU,OAAO,OAAO;AAC5E,MAAI,SAAS,OAAO,UAAU,UAAU,WAAW;AACnD,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,OAAO,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AAC9C,QAAM,QAAQ,SAAS,KAAK,IAAI,UAAU,MAAM,EAAE;AAClD,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,SAAS,KAAK;AACpB,QAAI,OAAO;AACX,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,cAAQ,MAAM,SAAS;AAAA,IACzB;AACA,SAAK,MAAM;AAAA,EACb;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,OAAO,OAAO,IAAI;AAC7E,UAAM,YAAY;AAClB,aAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC1F,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,WAAS,8BAA8B,EAAE;AACzC,MAAI,eAAe,MAAM;AACvB,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,SAAO;AACT;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,SAAS,IAAI;AACrB,QAAM,UAAU;AAChB,QAAM,EAAE,SAAS,YAAY,OAAO,IAAI,qBAAqB,qBAAqB,UAAU,QAAQ,MAAM;AAC1G,uBAAqB,oBAAoB,QAAQ,QAAQ,QAAQ,OAAO;AACxE,QAAM,EAAE,MAAM,MAAM,IAAI,qBAAqB,qBAAqB,YAAY,MAAM;AACpF,QAAM,SAAS,MAAM;AACrB,MAAI,MAAM;AACV,MAAI,mBAAmB,QAAQ;AAC/B,QAAM,mBAAmB,CAAC;AAC1B,WAAS,KAAK,GAAG,KAAK,QAAQ,EAAE,IAAI;AAClC,eAAW,UAAU,MAAM,KAAK;AAC9B,YAAM,EAAE,oBAAoB,MAAM,YAAY,aAAa,IAAI,qBAAqB,qBAAqB,kBAAkB,OAAO,OAAO;AACzI,UAAI;AACJ,UAAI,qBAAqB,sBAAsB,IAAI,GAAG;AACpD,YAAI,QAAQ;AAAA,MACd,OAAO;AACL,YAAI,WAAW,EAAE,QAAQ,EAAE,GAAG,QAAQ,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AACrF,yBAAiB,KAAK,CAAC;AAAA,MACzB;AACA,YAAM,cAAc,EAAE,MAAM,MAAM;AAClC,eAAS,IAAI,GAAG,IAAI,aAAa,QAAQ,EAAE,GAAG;AAC5C,oBAAY,OAAO,aAAa,IAAI,GAAG,CAAC;AAAA,MAC1C;AACA,UAAI,CAAC,aAAa,YAAY,EAAE,OAAO,WAAW,GAAG;AACnD,YAAI,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAChF,yBAAiB,KAAK,CAAC;AAAA,MACzB;AACA,UAAI,QAAQ,MAAM;AAChB,cAAM;AAAA,MACR,OAAO;AACL,cAAM,UAAU,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,IAAI,GAAG,SAAS,SAAS,CAAC;AAC/D,yBAAiB,KAAK,GAAG;AAAA,MAC3B;AAAA,IACF;AACA,QAAI,KAAK,SAAS,GAAG;AACnB,UAAI,KAAK,OAAO,GAAG;AACjB,cAAM,KAAK;AAAA,UACT,QAAQ,EAAE,GAAG,IAAI;AAAA,UACjB,SAAS;AAAA,UACT,OAAO;AAAA,YACL,MAAM,KAAK,OAAO,QAAQ,SAAS;AAAA,YACnC,UAAU;AAAA,UACZ;AAAA,QACF,CAAC;AACD,yBAAiB,KAAK,GAAG;AAAA,MAC3B;AACA;AAAA,IACF;AAAA,EACF;AACA,aAAW,cAAc,kBAAkB;AACzC,QAAI,eAAe,KAAK;AACtB;AAAA,IACF;AACA,aAAS,8BAA8B,UAAU;AAAA,EACnD;AACA,SAAO;AACT;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,IAAI,EAAE,IAAI;AAClB,mBAAiB,CAAC,IAAI,CAAC,GAAG,SAAS;AACnC,QAAM,eAAe,IAAI,aAAa,aAAa,cAAc,EAAE,KAAK,CAAC;AACzE,QAAM,SAAS,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC3C,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,UAAM,IAAI,OAAO;AACjB,QAAI,KAAK,GAAG;AACV,mBAAa,MAAM,SAAS;AAAA,IAC9B,OAAO;AACL,mBAAa,MAAM,SAAS,OAAO,IAAI;AAAA,IACzC;AAAA,EACF;AACA,SAAO,SAAS,eAAe,EAAE,OAAO,WAAW,YAAY;AACjE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,IAAI,qBAAqB;AAC7B,IAAI,KAAK,qBAAqB;AAC9B,IAAI,KAAK,qBAAqB;AAC9B,IAAI,KAAK,qBAAqB;AAC9B,IAAI,KAAK,qBAAqB;AAC9B,IAAI,KAAK,qBAAqB;AAC9B,IAAI,OAAO,gBAAgB,KAAK,CAAC,OAAO;AACtC,QAAM,QAAQ,KAAK,KAAK,EAAE;AAC1B,QAAM,IAAI,KAAK,IAAI,EAAE;AACrB,QAAM,KAAK,KAAK,IAAI,IAAI;AACxB,SAAO,SAAS,QAAQ,KAAK,KAAK,MAAM,KAAK,MAAM,KAAK,MAAM,KAAK,MAAM,KAAK,KAAK,IAAI,CAAC,IAAI,CAAC;AAC/F,CAAC;AACD,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,IAAI,IAAI;AAChB,QAAM,YAAY,OAAO,MAAM;AAC/B,QAAM,WAAW,OAAO,MAAM,MAAM;AACpC,MAAI,OAAO;AACX,MAAI,MAAM,GAAG;AACX,iBAAa,OAAO,EAAE,YAAY,MAAM,KAAK,MAAM,iCAAiC,EAAE,YAAY,OAAO,YAAY;AACrH,WAAO,YAAY,MAAM;AAAA,EAC3B;AACA,WAAS,OAAO,MAAM,GAAG,CAAC;AAC1B,SAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC1F;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,6BAA6B,CAAC,GAAG,MAAM,IAAI,CAAC;AAC9D,IAAI,OAAO,iBAAiB,SAAS,WAAW;AAChD,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,QAAQ,SAAS,YAAY;AAC7C,QAAM,aAAa,OAAO;AAC1B,QAAM,QAAQ,WAAW;AACzB,QAAM,WAAW,WAAW;AAC5B,QAAM,YAAY,WAAW,KAAK,IAAI,OAAO,MAAM;AACnD,QAAM,SAAS,UAAU,mBAAmB;AAC5C,QAAM,SAAS,UAAU,mBAAmB;AAC5C,QAAM,cAAc,CAAC,OAAO,QAAQ;AACpC,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,aAAa,aAAa,uBAAuB,WAAW,UAAU;AAC5E,QAAM,aAAa,aAAa,uBAAuB,WAAW,UAAU;AAC5E,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,UAAM,KAAK,OAAO;AAAA,MAChB,QAAQ,EAAE,GAAG,OAAO;AAAA,MACpB,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,CAAC,GAAG,CAAC,GAAG,MAAM,CAAC,GAAG,QAAQ,EAAE;AAAA,IAC9C,CAAC;AACD,UAAM,KAAK,OAAO;AAAA,MAChB,QAAQ,EAAE,GAAG,OAAO;AAAA,MACpB,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,CAAC,GAAG,CAAC,GAAG,MAAM,CAAC,GAAG,QAAQ,EAAE;AAAA,IAC9C,CAAC;AACD,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,IAAI,MAAM,GAAG,GAAG,SAAS,WAAW,CAAC;AAC/E,UAAM,EAAE,MAAM,OAAO,MAAM,MAAM,IAAI,QAAQ,QAAQ,SAAS,UAAU;AACxE,UAAM,MAAM,qBAAqB,uBAAuB,OAAO,KAAK;AACpE,aAAS,IAAI,GAAG,IAAI,UAAU,KAAK;AACjC,YAAM,IAAI,qBAAqB,oBAAoB,KAAK,CAAC;AACzD,iBAAW,IAAI,WAAW,KAAK,EAAE;AACjC,iBAAW,IAAI,WAAW,KAAK,EAAE;AAAA,IACnC;AACA,eAAW,8BAA8B,EAAE;AAC3C,eAAW,8BAA8B,EAAE;AAC3C,eAAW,8BAA8B,MAAM;AAAA,EACjD;AACA,QAAM,YAAY,WAAW,eAAe,aAAa,WAAW,UAAU;AAC9E,QAAM,YAAY,WAAW,eAAe,aAAa,WAAW,UAAU;AAC9E,QAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,WAAW,MAAM,UAAU,GAAG,SAAS,WAAW,CAAC;AAC7F,aAAW,8BAA8B,SAAS;AAClD,aAAW,8BAA8B,SAAS;AAClD,SAAO;AACT;AACA,SAAS,QAAQ,QAAQ,SAAS,YAAY;AAC5C,QAAMc,cAAY,aAAa,cAAc,OAAO,KAAK;AACzD,QAAM,YAAY,WAAW,KAAK,IAAI,OAAO,MAAM;AACnD,QAAM,WAAW,WAAW,KAAK,IAAI,UAAU,mBAAmB,KAAK,MAAM,EAAE;AAC/E,QAAM,WAAW,WAAW,KAAK,IAAI,UAAU,mBAAmB,KAAK,MAAM,EAAE;AAC/E,MAAI,cAAcA,WAAS,GAAG;AAC5B,UAAM,SAAS,UAAU,UAAU,UAAUA,aAAW,SAAS,UAAU;AAC3E,UAAM,cAAc,CAAC,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE;AACrD,QAAI,SAAS;AACX,YAAM,WAAW,WAAW,eAAe,aAAa,WAAW,OAAO,IAAI;AAC9E,YAAM,WAAW,WAAW,eAAe,aAAa,WAAW,OAAO,IAAI;AAC9E,YAAM,WAAW,WAAW,eAAe,CAAC,GAAG,WAAW,aAAa,kBAAkBA,aAAW,SAAS,CAAC;AAC9G,YAAM,eAAe,UAAU,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,WAAW,CAAC;AAC/E,YAAM,cAAc,cAAc,WAAW,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,GAAG,SAAS,WAAW,CAAC;AAC1G,YAAM,cAAc,cAAc,WAAW,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,aAAa,GAAG,SAAS,WAAW,CAAC;AAC9G,YAAM,cAAc,WAAW,KAAK,IAAI,YAAY,MAAM,EAAE;AAC5D,YAAM,cAAc,WAAW,KAAK,IAAI,YAAY,MAAM,EAAE;AAC5D,iBAAW,8BAA8B,QAAQ;AACjD,iBAAW,8BAA8B,QAAQ;AACjD,iBAAW,8BAA8B,QAAQ;AACjD,iBAAW,8BAA8B,YAAY;AACrD,iBAAW,8BAA8B,WAAW;AACpD,iBAAW,8BAA8B,WAAW;AACpD,aAAO,EAAE,MAAM,aAAa,MAAM,YAAY;AAAA,IAChD;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAM,OAAO,qBAAqB,uBAAuB,UAAU,QAAQ;AAC3E,UAAM,YAAY,yBAAyB,MAAMA,aAAW,OAAO;AACnE,WAAO,qBAAqB,uBAAuB,SAAS;AAAA,EAC9D;AACF;AACA,SAAS,cAAc1B,OAAM;AAC3B,UAAQA,QAAOA,QAAO,OAAO;AAC/B;AACA,SAAS,UAAU,UAAU,UAAUA,OAAM,SAAS,YAAY;AAChE,MAAIA,UAAS,GAAG;AACd,WAAO,EAAE,MAAM,UAAU,MAAM,SAAS;AAAA,EAC1C;AACA,QAAM,OAAO,qBAAqB,uBAAuB,UAAU,QAAQ;AAC3E,QAAMuB,QAAOvB,QAAO;AACpB,QAAM,cAAc,qBAAqB,qBAAqB,IAAI;AAClE,QAAM,eAAe,YAAY;AACjC,QAAM,eAAe,YAAY;AACjC,QAAM,YAAY,CAAC,aAAa,MAAM;AACtC,QAAM,eAAe,WAAW,eAAe,WAAW,WAAW,YAAY;AACjF,QAAM,eAAe,WAAW,eAAe,WAAW,WAAW,YAAY;AACjF,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,MAAM,cAAc,MAAM,aAAa,GAAG,SAAS,WAAW,CAAC;AAC3G,QAAM,aAAa,qBAAqB,oBAAoB,IAAI;AAChE,QAAM,cAAc,WAAW;AAC/B,QAAM,cAAc,WAAW;AAC/B,QAAM,WAAW,CAAC,YAAY,MAAM;AACpC,QAAM,cAAc,WAAW,eAAe,UAAU,WAAW,WAAW;AAC9E,QAAM,cAAc,WAAW,eAAe,UAAU,WAAW,WAAW;AAC9E,QAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,MAAM,aAAa,MAAM,YAAY,GAAG,SAAS,WAAW,CAAC;AACxG,QAAM,eAAe,UAAU,cAAc,cAAcuB,OAAM,SAAS,UAAU;AACpF,QAAM,gBAAgB,aAAa;AACnC,QAAM,gBAAgB,aAAa;AACnC,QAAM,aAAa,CAAC,cAAc,MAAM;AACxC,QAAM,gBAAgB,WAAW,eAAe,YAAY,WAAW,aAAa;AACpF,QAAM,gBAAgB,WAAW,eAAe,YAAY,WAAW,aAAa;AACpF,QAAM,kBAAkB,SAAS;AAAA,IAC/B,QAAQ,EAAE,MAAM,eAAe,MAAM,cAAc;AAAA,IACnD,SAAS;AAAA,EACX,CAAC;AACD,QAAM,cAAc,UAAU,aAAa,aAAaA,OAAM,SAAS,UAAU;AACjF,QAAM,eAAe,YAAY;AACjC,QAAM,eAAe,YAAY;AACjC,QAAM,YAAY,CAAC,aAAa,MAAM;AACtC,QAAM,eAAe,WAAW,eAAe,WAAW,WAAW,YAAY;AACjF,QAAM,eAAe,WAAW,eAAe,WAAW,WAAW,YAAY;AACjF,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,MAAM,cAAc,MAAM,aAAa,GAAG,SAAS,WAAW,CAAC;AAC3G,QAAM,KAAK,qBAAqB,UAAUvB,OAAM,OAAO;AACvD,QAAM,SAAS,CAAC,GAAG,KAAK,MAAM;AAC9B,QAAM,YAAY,WAAW,eAAe,QAAQ,WAAW,GAAG,IAAI;AACtE,QAAM,YAAY,WAAW,eAAe,QAAQ,WAAW,GAAG,IAAI;AACtE,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,MAAM,WAAW,MAAM,UAAU,GAAG,SAAS,WAAW,CAAC;AAClG,QAAM,eAAe,UAAU,EAAE,QAAQ,EAAE,GAAG,aAAa,GAAG,eAAe,GAAG,SAAS,WAAW,CAAC;AACrG,QAAM,UAAU,KAAK;AAAA,IACnB,QAAQ,EAAE,GAAG,iBAAiB,GAAG,aAAa;AAAA,IAC9C,SAAS;AAAA,EACX,CAAC;AACD,QAAM,UAAU,KAAK;AAAA,IACnB,QAAQ,EAAE,GAAG,iBAAiB,GAAG,aAAa;AAAA,IAC9C,SAAS;AAAA,EACX,CAAC;AACD,QAAM,cAAc,MAAM,EAAE,QAAQ,EAAE,OAAO,QAAQ,GAAG,SAAS,WAAW,CAAC;AAC7E,QAAM,cAAc,MAAM,EAAE,QAAQ,EAAE,OAAO,QAAQ,GAAG,SAAS,WAAW,CAAC;AAC7E,QAAM,cAAc,MAAM,EAAE,QAAQ,EAAE,OAAO,QAAQ,GAAG,SAAS,WAAW,CAAC;AAC7E,QAAM,cAAc,MAAM,EAAE,QAAQ,EAAE,OAAO,QAAQ,GAAG,SAAS,WAAW,CAAC;AAC7E,QAAM,QAAQ,QAAQ;AAAA,IACpB,QAAQ,CAAC,aAAa,WAAW;AAAA,IACjC,SAAS;AAAA,IACT,OAAO,EAAE,MAAM,EAAE;AAAA,EACnB,CAAC;AACD,QAAM,QAAQ,QAAQ;AAAA,IACpB,QAAQ,CAAC,aAAa,WAAW;AAAA,IACjC,SAAS;AAAA,IACT,OAAO,EAAE,MAAM,EAAE;AAAA,EACnB,CAAC;AACD,QAAM,YAAY,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACpD,QAAM,YAAY,WAAW,KAAK,IAAI,MAAM,MAAM,EAAE;AACpD,aAAW,8BAA8B,YAAY;AACrD,aAAW,8BAA8B,YAAY;AACrD,aAAW,8BAA8B,cAAc;AACvD,aAAW,8BAA8B,WAAW;AACpD,aAAW,8BAA8B,WAAW;AACpD,aAAW,8BAA8B,aAAa;AACtD,aAAW,8BAA8B,aAAa;AACtD,aAAW,8BAA8B,aAAa;AACtD,aAAW,8BAA8B,eAAe;AACxD,aAAW,8BAA8B,YAAY;AACrD,aAAW,8BAA8B,YAAY;AACrD,aAAW,8BAA8B,cAAc;AACvD,aAAW,8BAA8B,SAAS;AAClD,aAAW,8BAA8B,SAAS;AAClD,aAAW,8BAA8B,WAAW;AACpD,aAAW,8BAA8B,YAAY;AACrD,aAAW,8BAA8B,OAAO;AAChD,aAAW,8BAA8B,OAAO;AAChD,aAAW,8BAA8B,WAAW;AACpD,aAAW,8BAA8B,WAAW;AACpD,aAAW,8BAA8B,WAAW;AACpD,aAAW,8BAA8B,WAAW;AACpD,aAAW,8BAA8B,KAAK;AAC9C,aAAW,8BAA8B,KAAK;AAC9C,SAAO,EAAE,MAAM,WAAW,MAAM,UAAU;AAC5C;AACA,SAAS,yBAAyB,MAAMA,OAAM,SAAS;AACrD,QAAM,MAAM,IAAI,aAAaA,QAAO,CAAC;AACrC,WAAS,KAAK,GAAG,KAAKA,OAAM,MAAM;AAChC,QAAI,QAAQ;AACZ,QAAI,QAAQ;AACZ,aAAS,IAAI,GAAG,IAAIA,OAAM,KAAK;AAC7B,YAAM,KAAK,qBAAqB,SAAS,KAAK,GAAGA,OAAM,OAAO;AAC9D,YAAM,OAAO,qBAAqB,oBAAoB,MAAM,CAAC;AAC7D,eAAS,KAAK,OAAO,GAAG,OAAO,KAAK,OAAO,GAAG;AAC9C,eAAS,KAAK,OAAO,GAAG,OAAO,KAAK,OAAO,GAAG;AAAA,IAChD;AACA,QAAI,SAAS;AACX,eAASA;AACT,eAASA;AAAA,IACX;AACA,yBAAqB,mBAAmB,KAAK,OAAO,OAAO,EAAE;AAAA,EAC/D;AACA,SAAO;AACT;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM0B,cAAY,aAAa,cAAc,OAAO,KAAK;AACzD,QAAM,qBAAqB,OAAO,MAAM,OAAO,MAAM,SAAS;AAC9D,QAAM,QAAQA,cAAY;AAC1B,QAAM,UAAU,SAAS;AAAA,IACvB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,OAAO,kBAAkB,EAAE;AAAA,EAC9C,CAAC;AACD,QAAM,SAAS,SAAS,SAAS,OAAO,QAAQ;AAChD,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,OAAO,MAAM,EAAE,CAAC;AAC5G,WAAS,8BAA8B,OAAO;AAC9C,WAAS,8BAA8B,MAAM;AAC7C,SAAO;AACT;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,OAAO,MAAM,IAAI;AAChC,QAAM,SAAS,SAAS,aAAa,WAAW,KAAK;AACrD,QAAM,SAAS,aAAa,kBAAkB,QAAQ,aAAa,cAAc,KAAK,CAAC;AACvF,aAAW,QAAQ,OAAO,MAAM;AAChC,SAAO,SAAS,eAAe,OAAO,QAAQ,MAAM;AACtD;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AACA,SAAS,WAAW,QAAQ,OAAO,OAAO;AACxC,MAAI,UAAU,UAAU;AACtB,WAAO,KAAK,KAAK;AAAA,EACnB,OAAO;AACL,WAAO,KAAK,KAAK;AAAA,EACnB;AACF;AAGA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,UAAM,aAAa;AACnB,UAAM,SAAS,aAAa,uBAAuB,OAAO,OAAO,aAAa,cAAc,OAAO,KAAK,CAAC;AACzG,UAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,UAAM,YAAY,WAAW,KAAK,IAAI,OAAO,MAAM,EAAE;AACrD,aAAS,WAAW,GAAG,WAAW,OAAO,YAAY;AACnD,YAAM,cAAc,WAAW,aAAa,cAAc;AAC1D,eAAS,MAAM,GAAG,MAAM,aAAa,OAAO;AAC1C,cAAM,YAAY,OAAO,aAAa;AACtC,iBAAS,MAAM,GAAG,MAAM,YAAY,OAAO;AACzC,gBAAM,YAAY,MAAM;AACxB,mBAAS,UAAU,GAAG,UAAU,aAAa,WAAW;AACtD,kBAAM,SAAS,KAAK,MAAM,aAAa,MAAM,CAAC;AAC9C,kBAAM,SAAS,cAAc,YAAY,YAAY;AACrD,gBAAI,cAAc,UAAU;AAC5B,gBAAI,UAAU,KAAK,SAAS,YAAY;AACtC,oBAAM,mBAAmB,SAAS;AAClC,oBAAM,WAAW,cAAc,YAAY,mBAAmB;AAC9D,4BAAc,UAAU;AAAA,YAC1B;AACA,mBAAO,UAAU;AAAA,UACnB;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,SAAS,WAAW,MAAM,QAAQ,OAAO,OAAO,OAAO,KAAK;AAClE,WAAO,EAAE,QAAQ,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAAA,EAC5D;AACF;AAGA,IAAI,eAAe,6BAA6B,CAAC,GAAG,MAAM,KAAK,MAAM,IAAI,CAAC,CAAC;AAC3E,IAAI,YAAY,iBAAiB,UAAU,cAAc,MAAM,OAAO;AACtE,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAd,UAAS,KAAK,MAAM,YAAY,WAAW,iBAAiB,YAAY,aAAa,eAAe,IAAI;AAChH,MAAI,SAAS,OAAO;AAAA,IAClB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB;AAAA,EACtE,CAAC;AACD,MAAI,MAAM;AACR,UAAM,YAAY;AAClB,QAAI,eAAe,UAAU,KAAK,MAAM,WAAW,KAAK,KAAK,MAAM,OAAO,GAAG;AAC3E,YAAM,eAAe,SAAS,EAAE,QAAQ,EAAE,GAAG,KAAK,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,KAAK,MAAM,IAAI,GAAG,CAAC,EAAE,EAAE,CAAC;AACjH,eAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,aAAa,GAAG,SAAS,SAAS,CAAC;AAC3E,eAAS,8BAA8B,YAAY;AAAA,IACrD,OAAO;AACL,eAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,KAAK,GAAG,SAAS,SAAS,CAAC;AAAA,IACrE;AACA,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,MAAI,aAAa;AACf,UAAM,YAAY;AAClB,QAAI,eAAe,UAAU,gBAAgB,WAAW,uBAAuB,MAAM,WAAW,KAAK,uBAAuB,MAAM,OAAO,GAAG;AAC1I,YAAM,gBAAgB,SAAS;AAAA,QAC7B,QAAQ,EAAE,GAAG,uBAAuB;AAAA,QACpC,SAAS;AAAA,QACT,OAAO,EAAE,OAAO,CAAC,uBAAuB,MAAM,IAAI,GAAG,CAAC,EAAE;AAAA,MAC1D,CAAC;AACD,eAAS,iBAAiB,UAAU,QAAQ,aAAa,eAAe,cAAc;AACtF,eAAS,8BAA8B,aAAa;AAAA,IACtD,OAAO;AACL,eAAS,iBAAiB,UAAU,QAAQ,aAAa,wBAAwB,cAAc;AAAA,IACjG;AACA,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,SAAO;AACT;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,WAAW,iBAAiB,YAAY,aAAa,eAAe,IAAI;AAChH,MAAI,SAAS,sBAAsB;AAAA,IACjC,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB;AAAA,EACtE,CAAC;AACD,MAAI,MAAM;AACR,UAAM,YAAY;AAClB,aAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,KAAK,GAAG,SAAS,SAAS,CAAC;AACnE,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,MAAI,aAAa;AACf,UAAM,YAAY;AAClB,aAAS,iBAAiB,UAAU,QAAQ,aAAa,wBAAwB,cAAc;AAC/F,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,SAAO;AACT;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,QAAQ,QAAQ,IAAI;AAC5B,QAAM,aAAa,aAAa,cAAc,OAAO,KAAK;AAC1D,QAAM,eAAe,QAAQ;AAC7B,QAAM,YAAY,aAAa,aAAa,SAAS;AACrD,QAAM,CAAC,aAAa,WAAW,WAAWA,QAAO,IAAI,qBAAqB,mBAAmB,QAAQ,OAAO;AAC5G,MAAI,cAAc,GAAG;AACnB,WAAO,SAAS,eAAe,aAAa,OAAO,OAAO,CAAC,CAAC;AAAA,EAC9D;AACA,QAAM,cAAc,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACtD,QAAM,YAAY,SAAS,WAAW,MAAM;AAC5C,QAAM,SAAS,aAAa,aAAa,WAAW,OAAO,OAAO,WAAW,WAAW,WAAWA,UAAS,OAAO,OAAO,UAAU;AACpI,SAAO,SAAS,eAAe,aAAa,OAAO,OAAO,OAAO,MAAM;AACzE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAM,UAAU,IAAI;AAC5B,mBAAiB,CAAC,GAAG,OAAO,GAAG,UAAU;AACzC,QAAM,aAAa,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AAC9D,QAAM,cAAc,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACtD,QAAM,UAAU,EAAE,MAAM;AACxB,WAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,EAAE,IAAI;AAC9C,UAAMH,SAAQ,YAAY;AAC1B,iBAAa,OAAOA,UAAS,UAAU,KAAKA,UAAS,GAAG,MAAM,6BAA6BA,wBAAuB,UAAU,IAAI;AAAA,EAClI;AACA,MAAI,aAAa;AACjB,MAAI,aAAa,MAAM;AACrB,iBAAa;AAAA,EACf;AACA,QAAM,cAAc,aAAa,cAAc,QAAQ,KAAK;AAC5D,QAAM,YAAY,qBAAqB,aAAa,yBAAyB,GAAG,SAAS,YAAY,UAAU;AAC/G,QAAM,WAAW,SAAS;AAAA,IACxB,QAAQ,EAAE,EAAE;AAAA,IACZ,SAAS;AAAA,IACT,OAAO;AAAA,MACL,OAAO;AAAA,QACL,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,MACZ;AAAA,IACF;AAAA,EACF,CAAC;AACD,QAAM,eAAe,SAAS;AAAA,IAC5B,QAAQ,EAAE,GAAG,QAAQ;AAAA,IACrB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,UAAU,WAAW,cAAc,UAAU,SAAS,EAAE;AAAA,EAC3E,CAAC;AACD,QAAM,qBAAqB;AAAA,IACzB,UAAU;AAAA,IACV,UAAU;AAAA,IACV,cAAc,UAAU;AAAA,IACxB,UAAU;AAAA,EACZ;AACA,QAAM,aAAa,SAAS,WAAW,YAAY;AACnD,QAAM,OAAO,SAAS,WAAW,QAAQ;AACzC,QAAM,SAAS,aAAa,MAAM,YAAY,kBAAkB;AAChE,WAAS,8BAA8B,QAAQ;AAC/C,WAAS,8BAA8B,YAAY;AACnD,SAAO,SAAS,eAAe,UAAU,aAAa,OAAO,OAAO,OAAO,MAAM;AACnF;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAMiB,cAAY,aAAa,cAAc,OAAO,KAAK;AACzD,QAAM,qBAAqB,OAAO,MAAM,OAAO,MAAM,SAAS;AAC9D,QAAM,QAAQA,cAAY;AAC1B,QAAM,UAAU,SAAS;AAAA,IACvB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,OAAO,kBAAkB,EAAE;AAAA,EAC9C,CAAC;AACD,QAAM,SAAS,SAAS,SAAS,MAAM,QAAQ;AAC/C,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,OAAO,MAAM,EAAE,CAAC;AAC5G,WAAS,8BAA8B,OAAO;AAC9C,WAAS,8BAA8B,MAAM;AAC7C,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY,gBAAgB,UAAU,CAAC,OAAO,OAAO,SAAS,EAAE,IAAI,IAAI,GAAG,MAAM;AACrF,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO,KAAK,IAAI,EAAE,MAAM,WAAW,IAAI,GAAG,MAAM;AACrF,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO,OAAO,MAAM,EAAE,IAAI,IAAI,GAAG,MAAM;AAC5E,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,IAAI,IAAI;AAC7B,QAAM,UAAU,aAAa,OAAO,MAAM,GAAG;AAC7C,SAAO,SAAS,eAAe,CAAC,QAAQ,MAAM,GAAG,WAAW,OAAO;AACrE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO,KAAK,MAAM,EAAE,CAAC;AAC1D,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,6BAA6B,CAAC,GAAG,MAAM,KAAK,CAAC;AAClE,IAAI,cAAc,iBAAiB,YAAY,gBAAgB,MAAM,MAAM;AAC3E,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,gBAAgB,YAAY,CAAC,OAAO,KAAK,IAAI,GAAG,MAAM;AACxE,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,6BAA6B,CAAC,GAAG,MAAM,KAAK,CAAC;AACjE,IAAI,aAAa,iBAAiB,WAAW,eAAe,MAAM,MAAM;AACxE,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,IAAI,MAAM;AACjB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,aAAa,MAAM,OAAAJ,QAAO,KAAK,IAAI;AAC3C,mBAAiB,GAAG,KAAK;AACzB,QAAM,WAAW,EAAE,MAAM;AACzB,QAAM,OAAO,WAAW;AACxB,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAMtB,QAAO,aAAa,cAAc,EAAE,KAAK;AAC/C,QAAM,SAAS,IAAI,aAAaA,KAAI;AACpC,WAAS,kBAAkB,QAAQ;AACjC,UAAM,iBAAiB,SAAS;AAChC,QAAI,iBAAiB,SAAS,iBAAiB,KAAK,IAAI,GAAG,iBAAiB,WAAW;AACvF,UAAM,eAAe,SAAS,iBAAiB,KAAK,IAAI,iBAAiB,aAAa,IAAI;AAC1F,QAAI,OAAO;AACX,WAAO,kBAAkB,cAAc,kBAAkB;AACvD,YAAM,IAAI,QAAQ;AAClB,cAAQ,IAAI;AAAA,IACd;AACA,WAAO;AAAA,EACT;AACA,WAAS,SAAS,GAAG,SAASA,OAAM,UAAU;AAC5C,UAAM,OAAO,kBAAkB,MAAM;AACrC,UAAM,MAAM,QAAQ,UAAU,KAAK,IAAI,OAAOsB,SAAQ,MAAM,CAAC,IAAI;AACjE,WAAO,UAAU;AAAA,EACnB;AACA,SAAO,SAAS,eAAe,EAAE,OAAO,EAAE,OAAO,MAAM;AACzD;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,GAAG,IAAI;AACrB,QAAM,EAAE,aAAa,MAAM,OAAAA,QAAO,KAAK,IAAI;AAC3C,mBAAiB,IAAI,SAAS;AAC9B,QAAM,SAAS,aAAa,cAAc,GAAG,KAAK;AAClD,QAAM,WAAW,GAAG,MAAM;AAC1B,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAM,SAAS,IAAI,aAAa,MAAM;AACtC,QAAMtB,QAAO;AACb,WAAS,SAAS,GAAG,SAASA,OAAM,UAAU;AAC5C,UAAM,iBAAiB,SAAS;AAChC,UAAM,aAAa,SAAS,iBAAiB,KAAK,IAAI,GAAG,iBAAiB,WAAW;AACrF,UAAM,WAAW,SAAS,iBAAiB,KAAK,IAAI,UAAU,iBAAiB,cAAc,CAAC;AAC9F,QAAI,QAAQ;AACZ,aAAS,IAAI,YAAY,IAAI,UAAU,KAAK;AAC1C,eAAS,KAAK,IAAI,QAAQ,IAAI,CAAC;AAAA,IACjC;AACA,YAAQsB,SAAQ,QAAQ;AACxB,aAAS,IAAI,YAAY,IAAI,UAAU,KAAK;AAC1C,UAAI,MAAM,KAAKA,SAAQ,OAAO,QAAQ,KAAK,QAAQ,UAAU;AAC7D,UAAI,WAAW,GAAG;AAChB,eAAO,KAAK,IAAI,OAAO,CAAC,IAAI;AAAA,MAC9B;AACA,aAAO,SAAS;AAChB,aAAO,MAAM;AAAA,IACf;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,EAAE,OAAO,MAAM;AAC1D;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,kBAAkB,SAAS,IAAI;AACvC,QAAM,aAAa;AACnB,MAAI,SAAS,EAAE;AACf,QAAM,QAAQ,OAAO;AACrB,QAAM,WAAW,aAAa,eAAe,kBAAkB,MAAM;AACrE,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,QAAQ,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,MAAI,gBAAgB,MAAM;AACxB,UAAM,WAAW,IAAI,MAAM,KAAK;AAChC,aAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,eAAS,MAAM,OAAO,aAAa;AAAA,IACrC;AACA,YAAQ,cAAc,OAAO,QAAQ,EAAE,OAAO,cAAc,QAAQ;AACpE,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAC/D,aAAS;AAAA,EACX;AACA,mBAAiB,GAAG,KAAK;AACzB,uBAAqB,2BAA2B,OAAO,MAAM,KAAK;AAClE,QAAM,CAAC,aAAa,WAAW,IAAI,qBAAqB,0BAA0B,QAAQ,IAAI;AAC9F,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,SAAS,QAAQ,OAAO,YAAY,aAAa,EAAE,KAAK;AAC9D,QAAM,SAAS,WAAW,MAAM,QAAQ,aAAa,EAAE,KAAK;AAC5D,MAAI,WAAW;AACf,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,aAAa,QAAQ;AAChF,eAAW;AAAA,EACb;AACA,SAAO,EAAE,QAAQ,OAAO,UAAU,OAAO,EAAE,MAAM;AACnD;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,mBAAiB,GAAG,SAAS;AAC7B,QAAM,EAAE,YAAY,SAAAV,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY;AAClB,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,SAAS,GAAG,MAAM,wEAAwEA,2BAA0B,YAAY;AACjN,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,MAAI;AACJ,MAAI,SAAS,gBAAgB,KAAK,SAAS,iBAAiB,KAAK,aAAa,YAAY,SAAS,SAAS,SAAS,QAAQ,GAAG;AAC9H,UAAM,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACtD,OAAO;AACL,UAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,UAAMwB,YAAW,aAAa,eAAe,EAAE,KAAK;AACpD,UAAM,UAAU,MAAM,SAAS,EAAE,OAAO,EAAE,OAAOA,WAAU,UAAU,KAAK;AAC1E,UAAM,SAAS,eAAe,SAAS,UAAU,EAAE,OAAO,QAAQ,MAAM;AAAA,EAC1E;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAAxB,UAAS,KAAK,MAAM,iBAAiB,WAAW,IAAI;AACxE,mBAAiB,GAAG,WAAW;AAC/B,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,MAAM,iBAAiB,UAAU;AAC1H,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAM,SAAS,QAAQ,SAAS,EAAE,OAAO,EAAE,OAAO,aAAa,eAAe,EAAE,KAAK,GAAG,UAAU,KAAK;AACvG,SAAO,SAAS,eAAe,OAAO,OAAO,WAAW,OAAO,MAAM;AACvE;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,OAAO,IAAI;AAC9B,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,mBAAiB,CAAC,IAAI,MAAM,GAAG,eAAe;AAC9C,QAAM,WAAW,qBAAqB,kBAAkB,OAAO,OAAO,YAAYA,UAAS,GAAG,MAAM,eAAe;AACnH,QAAM,WAAW,SAAS,WAAW,MAAM;AAC3C,QAAM,YAAY,mBAAmB,UAAU,QAAQ;AACvD,QAAM,cAAc,SAAS;AAC7B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,uBAAuB,SAAS;AACtC,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,WAAW,uBAAuB,IAAI,SAAS,QAAQ;AAC7D,QAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,QAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,QAAM,KAAK,OAAO,OAAO,OAAO,SAAS;AACzC,QAAM,QAAQ,SAAS,WAAW,EAAE;AACpC,WAAS,QAAQ,GAAG,QAAQ,SAAS,WAAW,EAAE,OAAO;AACvD,aAAS,UAAU,GAAG,UAAU,SAAS,YAAY,EAAE,SAAS;AAC9D,eAAS,UAAU,GAAG,UAAU,SAAS,SAAS,EAAE,SAAS;AAC3D,iBAAS,QAAQ,GAAG,QAAQ,SAAS,UAAU,EAAE,OAAO;AACtD,mBAAS,QAAQ,GAAG,QAAQ,SAAS,SAAS,EAAE,OAAO;AACrD,kBAAM,gBAAgB,UAAU;AAChC,kBAAM,cAAc,QAAQ;AAC5B,kBAAM,cAAc,QAAQ;AAC5B,gBAAI,UAAU;AACd,qBAAS,SAAS,GAAG,SAAS,sBAAsB,UAAU,eAAe;AAC3E,oBAAM,WAAW,gBAAgB,UAAU;AAC3C,kBAAI,UAAU,KAAK,WAAW,SAAS,YAAY,KAAK,MAAM,OAAO,MAAM,SAAS;AAClF;AAAA,cACF;AACA,uBAAS,OAAO,GAAG,OAAO,uBAAuB,QAAQ,gBAAgB;AACvE,sBAAM,SAAS,cAAc,QAAQ;AACrC,oBAAI,QAAQ,KAAK,SAAS,SAAS,aAAa,KAAK,MAAM,KAAK,MAAM,OAAO;AAC3E;AAAA,gBACF;AACA,yBAAS,OAAO,GAAG,OAAO,sBAAsB,QAAQ,eAAe;AACrE,wBAAM,SAAS,cAAc,QAAQ;AACrC,sBAAI,QAAQ,KAAK,SAAS,SAAS,YAAY,KAAK,MAAM,KAAK,MAAM,OAAO;AAC1E;AAAA,kBACF;AACA,wBAAM,SAAS,uBAAuB,wBAAwB,uBAAuB,IAAI,UAAU,IAAI,OAAO,SAAS,OAAO,OAAO,OAAO;AAC5I,wBAAM,SAAS,SAAS,wBAAwB,uBAAuB,OAAO,uBAAuB;AACrG,wBAAMP,QAAO,WAAW,SAAS,IAAI;AACrC,sBAAIA,UAAS,GAAG;AACd;AAAA,kBACF;AACA,wBAAM,QAAQ,MAAM,IAAI,OAAO,SAAS,OAAO,OAAO,OAAO;AAC7D,6BAAW,QAAQA;AAAA,gBACrB;AAAA,cACF;AAAA,YACF;AACA,eAAG,IAAI,SAAS,OAAO,SAAS,OAAO,OAAO,OAAO;AAAA,UACvD;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,QAAQ,OAAO,IAAI;AACtC,QAAM,IAAI;AACV,mBAAiB,CAAC,QAAQ,MAAM,GAAG,aAAa;AAChD,QAAM,EAAE,YAAY,SAAAO,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,MAAM,eAAe;AAC9G,QAAM,UAAU,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC5C,QAAM,YAAY,OAAO,SAAS,UAAU,EAAE,OAAO,iBAAiB,SAAS,EAAE,OAAO,EAAE,OAAO,QAAQ,EAAE,MAAM;AACjH,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,wBAAwB,SAAS;AACvC,QAAM,uBAAuB,SAAS;AACtC,QAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,QAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,QAAM,KAAK,OAAO,EAAE,OAAO,SAAS;AACpC,QAAM,SAAS,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC5C,QAAM,QAAQ,OAAO,GAAG,OAAO,WAAW,MAAM;AAChD,WAAS,IAAI,GAAG,IAAI,SAAS,WAAW,EAAE,GAAG;AAC3C,aAAS,IAAI,GAAG,IAAI,SAAS,YAAY,EAAE,GAAG;AAC5C,eAAS,MAAM,GAAG,MAAM,SAAS,UAAU,EAAE,KAAK;AAChD,iBAAS,MAAM,GAAG,MAAM,SAAS,SAAS,EAAE,KAAK;AAC/C,gBAAM,YAAY,MAAM;AACxB,gBAAM,YAAY,MAAM;AACxB,cAAI,UAAU;AACd,mBAAS,KAAK,GAAG,KAAK,uBAAuB,MAAM,gBAAgB;AACjE,kBAAM,OAAO,YAAY,MAAM;AAC/B,gBAAI,MAAM,KAAK,OAAO,SAAS,aAAa,KAAK,MAAM,GAAG,MAAM,KAAK;AACnE;AAAA,YACF;AACA,qBAAS,KAAK,GAAG,KAAK,sBAAsB,MAAM,eAAe;AAC/D,oBAAM,OAAO,YAAY,MAAM;AAC/B,kBAAI,MAAM,KAAK,OAAO,SAAS,YAAY,KAAK,MAAM,GAAG,MAAM,KAAK;AAClE;AAAA,cACF;AACA,oBAAM,SAAS,wBAAwB,uBAAuB,IAAI,UAAU,IAAI,GAAG,KAAK,KAAK,CAAC;AAC9F,oBAAM,SAAS,KAAK,uBAAuB;AAC3C,oBAAMP,QAAO,WAAW,SAAS,IAAI;AACrC,kBAAIA,UAAS,GAAG;AACd;AAAA,cACF;AACA,oBAAM,QAAQ,MAAM,IAAI,GAAG,KAAK,KAAK,CAAC;AACtC,yBAAW,QAAQA;AAAA,YACrB;AAAA,UACF;AACA,aAAG,IAAI,SAAS,GAAG,KAAK,KAAK,CAAC;AAAA,QAChC;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,GAAG,OAAO,GAAG,MAAM;AAC9D;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,sBAAsB,SAAS,QAAQ,OAAO,qBAAqB,UAAU;AACpF,QAAMO,WAAU,aAAa,eAAe,MAAM;AAClD,QAAM,WAAW,MAAM,SAAS,QAAQ,OAAOA,UAAS,UAAU,KAAK;AACvE,QAAM,eAAe,iBAAiB,SAAS,QAAQ,OAAO,UAAU,MAAM,mBAAmB;AACjG,SAAO,CAAC,SAAS,QAAQ,aAAa,MAAM;AAC9C;AAGA,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,oBAAoB,IAAI;AAChE,UAAM,aAAa;AACnB,qBAAiB,GAAG,mBAAmB;AACvC,UAAM,SAAS,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,CAAC,GAAG,CAAC,GAAG,IAAI;AAClG,UAAM,CAAC,QAAQ,OAAO,IAAI,sBAAsB,QAAQ,EAAE,OAAO,EAAE,OAAO,qBAAqB,QAAQ;AACvG,UAAM,eAAe,WAAW,MAAM,QAAQ,SAAS,UAAU,EAAE,KAAK;AACxE,UAAM,gBAAgB,WAAW,MAAM,SAAS,SAAS,UAAU,EAAE,KAAK;AAC1E,WAAO;AAAA,MACL,EAAE,QAAQ,cAAc,OAAO,SAAS,UAAU,OAAO,EAAE,MAAM;AAAA,MACjE,EAAE,QAAQ,eAAe,OAAO,SAAS,UAAU,OAAO,QAAQ;AAAA,IACpE;AAAA,EACF;AACF;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACtD,QAAM,SAAS,qBAAqB,0BAA0B,EAAE,OAAO,IAAI;AAC3E,QAAM,cAAc,OAAO;AAC3B,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,YAAY,CAAC;AACnB,QAAM,mBAAmB,SAAS,eAAe,CAAC,GAAG,WAAW,IAAI,aAAa,CAAC,UAAU,CAAC,CAAC;AAC9F,YAAU,KAAK,gBAAgB;AAC/B,QAAM,KAAK,MAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AAClF,YAAU,KAAK,EAAE;AACjB,QAAM,MAAM,KAAK,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,iBAAiB,GAAG,SAAS,SAAS,CAAC;AAC9E,YAAU,KAAK,GAAG;AAClB,QAAM,SAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,SAAS,EAAE,CAAC;AACxF,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,mBAAiB,GAAG,KAAK;AACzB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,EAAE,MAAM,MAAM;AAAA,EAC1E;AACA,uBAAqB,2BAA2B,OAAO,MAAM,GAAG,MAAM,MAAM;AAC5E,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,GAAG,OAAO,IAAI;AAC7F,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,OAAO,aAAa,oBAAoB,aAAa,cAAc,QAAQ,GAAG,GAAG,KAAK;AAC5F,QAAM,QAAQ,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC3C,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,EAAE,IAAI;AACvC,UAAM,SAAS,KAAK;AACpB,QAAI,OAAO,MAAM;AACjB,aAAS,IAAI,GAAG,IAAI,YAAY,EAAE,GAAG;AACnC,YAAM,QAAQ,MAAM,SAAS;AAC7B,UAAI,OAAO,MAAM,KAAK,KAAK,QAAQ,MAAM;AACvC,eAAO;AAAA,MACT;AAAA,IACF;AACA,SAAK,MAAM;AAAA,EACb;AACA,MAAI,gBAAgB,MAAM;AACxB,aAAS,8BAA8B,EAAE;AAAA,EAC3C;AACA,QAAM,SAAS,SAAS,eAAe,UAAU,GAAG,OAAO,IAAI;AAC/D,MAAI,UAAU;AACZ,UAAM,gBAAgB,qBAAqB,qBAAqB,UAAU,QAAQ;AAClF,UAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAC7G,aAAS,8BAA8B,MAAM;AAC7C,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,UAAU,KAAK,IAAI;AAC3B,mBAAiB,GAAG,WAAW;AAC/B,QAAM,WAAW,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,EAAE,MAAM,MAAM,GAAG,EAAE;AACrE,QAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE;AACxC,QAAM,MAAM,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,EAAE,MAAM,GAAG;AACxD,QAAM,SAAS,SAAS,YAAY,IAAI;AACxC,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,aAAa,eAAe,EAAE,KAAK;AACpD,QAAM,aAAa,aAAa,cAAc,QAAQ;AACtD,QAAM,aAAa,SAAS;AAC5B,QAAM,gBAAgB,aAAa,eAAe,QAAQ;AAC1D,QAAM,UAAU,aAAa,uBAAuB,EAAE,OAAO,UAAU;AACvE,WAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,QAAI,UAAU,aAAa,WAAW,IAAI,YAAY,aAAa;AACnE,aAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,UAAI,QAAQ,MAAM,MAAM,KAAK;AAC3B,gBAAQ,MAAM,MAAM,MAAM,IAAI,QAAQ,MAAM;AAAA,MAC9C,WAAW,QAAQ,OAAO,IAAI,KAAK;AACjC,gBAAQ,OAAO,IAAI,MAAM,KAAK,IAAI,QAAQ,MAAM;AAAA,MAClD;AAAA,IACF;AACA,cAAU,QAAQ,IAAI,CAAC,GAAG,OAAO,IAAI,MAAM,GAAG;AAC9C,UAAM,UAAU,aAAa,WAAW,SAAS,OAAO,QAAQ;AAChE,YAAQ,MAAM,MAAM;AAAA,EACtB;AACA,QAAM,QAAQ,SAAS,MAAM,SAAS,UAAU,EAAE,KAAK;AACvD,SAAO,EAAE,QAAQ,OAAO,OAAO,UAAU,OAAO,EAAE,MAAM;AAC1D;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU,6BAA6B,CAAC,QAAQ,WAAW;AAC7D,QAAM,MAAM,SAAS;AACrB,MAAI,SAAS,KAAK,SAAS,KAAK,UAAU,KAAK,UAAU,GAAG;AAC1D,WAAO;AAAA,EACT,OAAO;AACL,YAAQ,MAAM,UAAU;AAAA,EAC1B;AACF,CAAC;AACD,IAAI,OAAO,iBAAiB,KAAK,OAAO;AACxC,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,QAAQ,oBAAoB,CAAC;AAG/C,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,IAAI,IAAI;AAChB,QAAM,aAAa,OAAO,MAAM;AAChC,MAAI,OAAO;AACX,MAAI,SAAS,IAAI;AACf,WAAO,aAAa;AAAA,EACtB;AACA,MAAI,SAAS,aAAa,GAAG;AAC3B,UAAM,MAAM,4EAA4E,0BAA0B,MAAM;AAAA,EAC1H;AACA,QAAM,OAAO,aAAa,eAAe,CAAC,IAAI,GAAG,OAAO,KAAK;AAC7D,QAAM,WAAW,KAAK;AAAA,IACpB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,kBAAkB,MAAM,UAAU,MAAM;AAAA,EACnD,CAAC;AACD,QAAM,gBAAgB,qBAAqB,qBAAqB,SAAS,OAAO,IAAI;AACpF,QAAM,mBAAmB,SAAS,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AACjH,QAAM,IAAI,KAAK,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,iBAAiB,GAAG,SAAS,SAAS,CAAC;AAChF,QAAM,IAAI,KAAK,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,SAAS,CAAC;AACtD,QAAM,SAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,MAAM,UAAU,MAAM,EAAE,CAAC;AACnG,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAC1G,QAAM,SAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,YAAY,GAAG,SAAS,SAAS,CAAC;AAC3E,WAAS,8BAA8B,QAAQ;AAC/C,WAAS,8BAA8B,gBAAgB;AACvD,WAAS,8BAA8B,CAAC;AACxC,WAAS,8BAA8B,CAAC;AACxC,WAAS,8BAA8B,MAAM;AAC7C,WAAS,8BAA8B,WAAW;AAClD,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,YAAY,MAAM,WAAW,IAAI;AACzC,mBAAiB,QAAQ,aAAa;AACtC,QAAM,gBAAgB,aAAa,SAAS,SAAS,EAAE,QAAQ,EAAE,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,GAAG,EAAE,CAAC;AAClH,QAAM,YAAY,cAAc,MAAM;AACtC,QAAM,YAAY,cAAc,MAAM;AACtC,QAAM,WAAW,SAAS,KAAK,IAAI,cAAc,MAAM,EAAE;AACzD,QAAM,WAAW,CAAC,WAAW,UAAU;AACvC,QAAM,UAAU,aAAa,oBAAoB,aAAa,cAAc,QAAQ,GAAG,OAAO;AAC9F,WAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,UAAM,SAAS,IAAI;AACnB,UAAM,MAAM,IAAI,aAAa,YAAY,CAAC;AAC1C,QAAI,KAAK,SAAS;AAClB,aAAS,QAAQ,GAAG,QAAQ,IAAI,QAAQ,EAAE,OAAO;AAC/C,UAAI,SAAS,IAAI,QAAQ,KAAK,SAAS,SAAS;AAAA,IAClD;AACA,UAAM,SAAS,YAAY,KAAK,KAAK,SAAS,CAAC;AAC/C,UAAM,YAAY,IAAI;AACtB,aAAS,WAAW,GAAG,WAAW,YAAY,EAAE,UAAU;AACxD,YAAM,KAAK,OAAO;AAClB,cAAQ,YAAY,YAAY,IAAI;AACpC,eAAS,QAAQ,GAAG,QAAQ,IAAI,QAAQ,SAAS;AAC/C,YAAI,KAAK,IAAI,QAAQ;AACnB,kBAAQ,YAAY,YAAY;AAChC;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,MAAI,CAAC,YAAY;AACf,aAAS,8BAA8B,aAAa;AAAA,EACtD;AACA,SAAO,SAAS,eAAe,UAAU,SAAS,OAAO;AAC3D;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,qBAAqB;AACpD,SAAS,oBAAoB,MAAM;AACjC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,eAAe,IAAI;AACxD,mBAAiB,OAAO,mBAAmB;AAC3C,QAAM,YAAY,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AAClD,QAAM,aAAa,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACpD,QAAM,EAAE,gBAAgB,IAAI,yBAAyB,WAAW,YAAY,eAAe,cAAc,cAAc;AACvH,SAAO,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AACnG;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,qBAAqB;AACpD,SAAS,oBAAoB,MAAM;AACjC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,gBAAgB,mBAAmB,IAAI;AAC5E,mBAAiB,OAAO,yBAAyB;AACjD,QAAM,YAAY,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AAClD,QAAM,aAAa,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACpD,QAAM,EAAE,iBAAiB,aAAa,IAAI,yBAAyB,WAAW,YAAY,eAAe,cAAc,gBAAgB,kBAAkB;AACzJ,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AAAA,IAC1F,SAAS,eAAe,CAAC,GAAG,SAAS,IAAI,WAAW,CAAC,YAAY,CAAC,CAAC;AAAA,EACrE;AACF;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,qBAAqB;AACpD,SAAS,oBAAoB,MAAM;AACjC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,gBAAgB,aAAa,IAAI;AACtE,mBAAiB,OAAO,4BAA4B;AACpD,QAAM,YAAY,SAAS,KAAK,IAAI,MAAM,MAAM,EAAE;AAClD,QAAM,aAAa,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACpD,QAAM,mBAAmB;AACzB,QAAM,kBAAkB;AACxB,QAAM,oBAAoB;AAC1B,QAAM,kBAAkB;AACxB,QAAM,EAAE,iBAAiB,eAAe,IAAI,yBAAyB,WAAW,YAAY,kBAAkB,iBAAiB,mBAAmB,eAAe;AACjK,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AAAA,IAC1F,SAAS,eAAe,CAAC,eAAe,MAAM,GAAG,WAAW,IAAI,aAAa,cAAc,CAAC;AAAA,EAC9F;AACF;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,IAAI;AACpB,QAAM,EAAE,OAAO,SAAS,SAAS,IAAI;AACrC,mBAAiB,SAAS,QAAQ;AAClC,QAAM,cAAc,aAAa,cAAc,QAAQ,KAAK;AAC5D,QAAM,MAAM,IAAI,aAAa,cAAc,KAAK;AAChD,MAAI,KAAK,QAAQ;AACjB,QAAM,aAAa,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACrD,WAAS,QAAQ,GAAG,QAAQ,aAAa,EAAE,OAAO;AAChD,QAAI,WAAW,UAAU,KAAK,WAAW,SAAS,OAAO;AACvD,UAAI,QAAQ,QAAQ,WAAW,UAAU;AAAA,IAC3C;AAAA,EACF;AACA,SAAO,SAAS,eAAe,CAAC,GAAG,QAAQ,OAAO,KAAK,GAAG,SAAS,GAAG;AACxE;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,EAAE,UAAU,UAAU;AACxB,UAAM,IAAI,MAAM,+CAA+C;AAAA,EACjE,WAAW,EAAE,UAAU,aAAa;AAClC,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,IAAI,MAAM,GAAG,GAAG,SAAS,SAAS,CAAC;AAC7E,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,WAAO;AAAA,EACT,OAAO;AACL,WAAO,MAAM,EAAE,SAAS,UAAU,OAAO,EAAE,OAAO,EAAE,OAAO,OAAO,GAAG,OAAO,EAAE,MAAM,EAAE,CAAC;AAAA,EACzF;AACF;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,EAAE,UAAU,UAAU;AACxB,UAAM,IAAI,MAAM,8CAA8C;AAAA,EAChE,WAAW,EAAE,UAAU,aAAa;AAClC,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,UAAU,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACnE,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,IAAI,MAAM,GAAG,GAAG,SAAS,SAAS,CAAC;AAC7E,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,WAAO;AAAA,EACT,OAAO;AACL,WAAO,MAAM,EAAE,SAAS,UAAU,OAAO,EAAE,OAAO,EAAE,OAAO,OAAO,GAAG,OAAO,EAAE,MAAM,EAAE,CAAC;AAAA,EACzF;AACF;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,YAAY,EAAE,QAAQ,EAAE,OAAO,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAAA,EAC9F;AACA,QAAM,QAAQ,OAAO,GAAG;AACxB,QAAM,QAAQ,OAAO,GAAG;AACxB,SAAO,QAAQ,CAAC,OAAO;AACrB,iBAAa,kBAAkB,OAAO,GAAG,OAAO,uDAAuD;AACvG,iBAAa,OAAO,UAAU,GAAG,OAAO,MAAM,uDAAuD;AAAA,EACvG,CAAC;AACD,QAAM,0BAA0B,CAAC;AACjC,QAAM,kBAAkB,OAAO,IAAI,CAAC,OAAO;AACzC,UAAM,YAAY,YAAY,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAChG,4BAAwB,KAAK,SAAS;AACtC,WAAO;AAAA,EACT,CAAC;AACD,QAAM,SAAS,QAAQ,EAAE,QAAQ,iBAAiB,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AACtF,0BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,UAAU,cAAc,IAAI;AACpC,mBAAiB,GAAG,KAAK;AACzB,QAAM,WAAW,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,EAAE,MAAM,MAAM,GAAG,EAAE;AACrE,QAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE;AACxC,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,aAAa,eAAe,EAAE,KAAK;AACpD,QAAM,aAAa,aAAa,cAAc,QAAQ;AACtD,QAAM,aAAa,SAAS;AAC5B,QAAM,gBAAgB,aAAa,eAAe,QAAQ;AAC1D,QAAM,UAAU,aAAa,uBAAuB,EAAE,OAAO,UAAU;AACvE,MAAI,kBAAkB,GAAG;AACvB,YAAQ,KAAK,aAAa;AAAA,EAC5B;AACA,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM;AACjC,UAAM,UAAU,aAAa,WAAW,IAAI,OAAO,QAAQ;AAC3D,UAAM,YAAY,QAAQ,IAAI,CAAC,GAAG,OAAO,IAAI,MAAM,GAAG;AACtD,UAAM,WAAW,aAAa,WAAW,WAAW,YAAY,aAAa;AAC7E,YAAQ,YAAY,MAAM;AAAA,EAC5B;AACA,QAAM,QAAQ,SAAS,MAAM,SAAS,UAAU,EAAE,KAAK;AACvD,SAAO,EAAE,QAAQ,OAAO,OAAO,UAAU,OAAO,EAAE,MAAM;AAC1D;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU,6BAA6B,CAAC,GAAG,MAAM,KAAK,IAAI,GAAG,CAAC,CAAC;AACnE,IAAI,OAAO,iBAAiB,KAAK,OAAO;AACxC,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,OAAO,MAAM,MAAM,IAAI;AAC5C,QAAM,SAAS,UAAU,OAAO,MAAM,OAAO,KAAK;AAClD,SAAO,SAAS,eAAe,CAAC,OAAO,MAAM,GAAG,OAAO,MAAM;AAC/D;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,gBAAgB,YAAY,CAAC,OAAO,IAAI,EAAE;AAC5D,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,kBAAkB,MAAAZ,MAAK,IAAI;AACjD,mBAAiB,QAAQ,gBAAgB;AACzC,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,CAAC,OAAO,WAAW,UAAU,WAAW,IAAI,OAAO;AACzD,QAAM,UAAU,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACjD,QAAM,SAAS,IAAI,aAAa,aAAa,cAAc,CAAC,OAAO,WAAW,UAAU,WAAW,CAAC,CAAC;AACrG,QAAM,qBAAqB;AAAA,IACzB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,IAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,EAChD;AACA,QAAM,sBAAsB;AAAA,IAC1B,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,IAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,EAChD;AACA,MAAI,YAAY;AAChB,QAAM,wBAAwB,mBAAmB,KAAK,oBAAoB;AAC1E,QAAM,wBAAwB,mBAAmB,KAAK,oBAAoB;AAC1E,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,aAAS,KAAK,GAAG,KAAK,WAAW,MAAM;AACrC,UAAI;AACJ,UAAI,kBAAkB;AACpB,wBAAgB,yBAAyB,KAAK,OAAO;AAAA,MACvD,OAAO;AACL,wBAAgB,wBAAwB;AAAA,MAC1C;AACA,YAAM,iBAAiB,KAAK,IAAI,GAAG,KAAK,MAAM,aAAa,CAAC;AAC5D,YAAM,UAAU,gBAAgB;AAChC,YAAM,gBAAgB,KAAK,IAAI,YAAY,GAAG,KAAK,KAAK,aAAa,CAAC;AACtE,YAAM,eAAe,IAAI,cAAc,KAAK,iBAAiB,cAAc;AAC3E,YAAM,eAAe,IAAI,cAAc,KAAK,gBAAgB,cAAc;AAC1E,eAAS,IAAI,GAAG,IAAI,UAAU,KAAK;AACjC,YAAI;AACJ,YAAI,kBAAkB;AACpB,0BAAgB,yBAAyB,IAAI,OAAO;AAAA,QACtD,OAAO;AACL,0BAAgB,wBAAwB;AAAA,QAC1C;AACA,cAAM,iBAAiB,KAAK,IAAI,GAAG,KAAK,MAAM,aAAa,CAAC;AAC5D,cAAM,UAAU,gBAAgB;AAChC,cAAM,gBAAgB,KAAK,IAAI,WAAW,GAAG,KAAK,KAAK,aAAa,CAAC;AACrE,cAAM,gBAAgB,eAAe,iBAAiB,cAAc;AACpE,cAAM,gBAAgB,eAAe,iBAAiB,cAAc;AACpE,cAAM,iBAAiB,eAAe,gBAAgB,cAAc;AACpE,cAAM,iBAAiB,eAAe,gBAAgB,cAAc;AACpE,iBAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,gBAAM,UAAU,QAAQ,gBAAgB;AACxC,gBAAM,aAAa,QAAQ,gBAAgB;AAC3C,gBAAM,WAAW,QAAQ,iBAAiB;AAC1C,gBAAM,cAAc,QAAQ,iBAAiB;AAC7C,gBAAM,MAAM,WAAW,WAAW,WAAW;AAC7C,gBAAM,SAAS,cAAc,cAAc,cAAc;AACzD,gBAAM,WAAW,OAAO,SAAS,OAAO;AACxC,iBAAO,eAAe;AAAA,QACxB;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,CAAC,OAAO,WAAW,UAAU,WAAW,GAAG,WAAW,MAAM;AAC7F;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,mBAAmB,MAAM;AAChC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,GAAG,IAAI;AACvB,QAAM,EAAE,aAAa,IAAI;AACzB,mBAAiB,CAAC,IAAI,MAAM,GAAG,oBAAoB;AACnD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,CAAC,OAAO,SAAS,QAAQ,KAAK,IAAI,OAAO;AAC/C,QAAM,CAAC,EAAE,SAAS,MAAM,IAAI,GAAG;AAC/B,QAAM,SAAS,IAAI,aAAa,QAAQ,UAAU,SAAS,KAAK;AAChE,QAAM,iBAAiB;AAAA,IACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,IAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,EAC5C;AACA,QAAM,iBAAiB;AAAA,IACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,IAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,EAC5C;AACA,QAAM,cAAc,eAAe,KAAK,eAAe;AACvD,QAAM,aAAa,eAAe,KAAK,eAAe;AACtD,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,MAAI,SAAS;AACb,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,UAAM,UAAU,IAAI,cAAc;AAClC,aAAS,KAAK,GAAG,KAAK,SAAS,MAAM;AACnC,YAAM,MAAM,KAAK;AACjB,YAAM,cAAc,KAAK,MAAM,GAAG;AAClC,YAAM,iBAAiB,KAAK,IAAI,KAAK,KAAK,GAAG,GAAG,UAAU,CAAC;AAC3D,YAAM,eAAe,UAAU,cAAc,cAAc;AAC3D,YAAM,kBAAkB,UAAU,iBAAiB,cAAc;AACjE,YAAM,UAAU,MAAM;AACtB,YAAM,iBAAiB,IAAI;AAC3B,eAAS,IAAI,GAAG,IAAI,QAAQ,KAAK;AAC/B,cAAM,MAAM,IAAI;AAChB,cAAM,eAAe,KAAK,MAAM,GAAG;AACnC,cAAM,gBAAgB,KAAK,IAAI,KAAK,KAAK,GAAG,GAAG,SAAS,CAAC;AACzD,cAAM,UAAU,MAAM;AACtB,cAAM,iBAAiB,IAAI;AAC3B,cAAM,kBAAkB,eAAe,eAAe,cAAc;AACpE,cAAM,mBAAmB,eAAe,gBAAgB,cAAc;AACtE,cAAM,qBAAqB,kBAAkB,eAAe,cAAc;AAC1E,cAAM,sBAAsB,kBAAkB,gBAAgB,cAAc;AAC5E,cAAM,oCAAoC,iBAAiB;AAC3D,cAAM,6BAA6B,iBAAiB;AACpD,cAAM,6BAA6B,UAAU;AAC7C,cAAM,sBAAsB,UAAU;AACtC,iBAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,gBAAM,QAAQ,SAAS;AACvB,iBAAO,kBAAkB,MAAM,QAAQ;AACvC,iBAAO,mBAAmB,MAAM,QAAQ;AACxC,iBAAO,qBAAqB,MAAM,QAAQ;AAC1C,iBAAO,sBAAsB,MAAM,QAAQ;AAAA,QAC7C;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,CAAC,OAAO,QAAQ,SAAS,KAAK,GAAG,WAAW,MAAM;AACnF;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,uBAAuB,MAAM;AACpC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,kBAAkB,MAAAA,MAAK,IAAI;AACjD,mBAAiB,QAAQ,uBAAuB;AAChD,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,CAAC,OAAO,WAAW,UAAU,WAAW,IAAI,OAAO;AACzD,QAAM,UAAU,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACjD,QAAM,SAAS,IAAI,aAAa,QAAQ,YAAY,WAAW,WAAW;AAC1E,QAAM,qBAAqB;AAAA,IACzB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,IAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,EAChD;AACA,QAAM,sBAAsB;AAAA,IAC1B,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,IAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,EAChD;AACA,QAAM,wBAAwB,mBAAmB,KAAK,oBAAoB;AAC1E,QAAM,wBAAwB,mBAAmB,KAAK,oBAAoB;AAC1E,MAAI,eAAe;AACnB,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,UAAM,cAAc,IAAI,cAAc;AACtC,aAAS,KAAK,GAAG,KAAK,WAAW,MAAM;AACrC,YAAM,gBAAgB,mBAAmB,yBAAyB,KAAK,OAAO,wBAAwB;AACtG,UAAI,mBAAmB,KAAK,IAAI,YAAY,GAAG,eAAe,KAAK,MAAM,aAAa,IAAI,KAAK,MAAM,aAAa,CAAC;AACnH,UAAI,kBAAkB;AACpB,2BAAmB,KAAK,IAAI,GAAG,gBAAgB;AAAA,MACjD;AACA,YAAM,YAAY,cAAc,mBAAmB,cAAc;AACjE,eAAS,IAAI,GAAG,IAAI,UAAU,KAAK;AACjC,cAAM,gBAAgB,mBAAmB,yBAAyB,IAAI,OAAO,wBAAwB;AACrG,YAAI,mBAAmB,KAAK,IAAI,WAAW,GAAG,eAAe,KAAK,MAAM,aAAa,IAAI,KAAK,MAAM,aAAa,CAAC;AAClH,YAAI,kBAAkB;AACpB,6BAAmB,KAAK,IAAI,GAAG,gBAAgB;AAAA,QACjD;AACA,cAAM,YAAY,YAAY,mBAAmB,cAAc;AAC/D,iBAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,gBAAM,SAAS,QAAQ,YAAY;AACnC,iBAAO,kBAAkB;AAAA,QAC3B;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,CAAC,OAAO,WAAW,UAAU,WAAW,GAAG,OAAO,OAAO,MAAM;AAChG;AACA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,0BAA0B,MAAM;AACvC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,GAAG,IAAI;AACvB,QAAM,EAAE,aAAa,IAAI;AACzB,mBAAiB,CAAC,IAAI,MAAM,GAAG,2BAA2B;AAC1D,QAAM,gBAAgB,aAAa,eAAe,OAAO,KAAK;AAC9D,QAAM,YAAY,aAAa,eAAe,GAAG,KAAK;AACtD,QAAM,CAAC,OAAO,SAAS,QAAQ,KAAK,IAAI,OAAO;AAC/C,QAAM,CAAC,EAAE,SAAS,MAAM,IAAI,GAAG;AAC/B,QAAM,SAAS,IAAI,aAAa,QAAQ,UAAU,SAAS,KAAK;AAChE,QAAM,WAAW,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,iBAAiB;AAAA,IACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,IAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,EAC5C;AACA,QAAM,iBAAiB;AAAA,IACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,IAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,EAC5C;AACA,QAAM,cAAc,eAAe,KAAK,eAAe;AACvD,QAAM,aAAa,eAAe,KAAK,eAAe;AACtD,QAAM,iBAAiB,IAAI;AAC3B,QAAM,gBAAgB,IAAI;AAC1B,QAAM,YAAY,KAAK,KAAK,cAAc,IAAI,IAAI;AAClD,QAAM,WAAW,KAAK,KAAK,aAAa,IAAI,IAAI;AAChD,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,UAAM,cAAc,IAAI,cAAc;AACtC,aAAS,KAAK,GAAG,KAAK,SAAS,MAAM;AACnC,YAAM,YAAY,cAAc,KAAK,cAAc;AACnD,YAAM,aAAa,KAAK,MAAM,KAAK,cAAc;AACjD,YAAM,WAAW,KAAK,MAAM,aAAa,YAAY,CAAC;AACtD,eAAS,IAAI,GAAG,IAAI,QAAQ,KAAK;AAC/B,cAAM,YAAY,YAAY,IAAI,cAAc;AAChD,cAAM,aAAa,KAAK,MAAM,IAAI,aAAa;AAC/C,cAAM,WAAW,KAAK,MAAM,aAAa,WAAW,CAAC;AACrD,iBAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,cAAI,QAAQ;AACZ,mBAAS,WAAW,GAAG,WAAW,WAAW,YAAY;AACvD,kBAAM,MAAM,WAAW;AACvB,gBAAI,MAAM,KAAK,OAAO,SAAS;AAC7B;AAAA,YACF;AACA,kBAAM,YAAY,cAAc,MAAM,UAAU;AAChD,kBAAM,gBAAgB,MAAM;AAC5B,kBAAM,mBAAmB,KAAK,IAAI,UAAU,GAAG,eAAe,KAAK,MAAM,aAAa,IAAI,KAAK,MAAM,aAAa,CAAC;AACnH,gBAAI,OAAO,kBAAkB;AAC3B;AAAA,YACF;AACA,qBAAS,WAAW,GAAG,WAAW,UAAU,YAAY;AACtD,oBAAM,MAAM,WAAW;AACvB,kBAAI,MAAM,KAAK,OAAO,QAAQ;AAC5B;AAAA,cACF;AACA,oBAAM,YAAY,YAAY,MAAM,UAAU;AAC9C,oBAAM,gBAAgB,MAAM;AAC5B,oBAAM,mBAAmB,KAAK,IAAI,SAAS,GAAG,eAAe,KAAK,MAAM,aAAa,IAAI,KAAK,MAAM,aAAa,CAAC;AAClH,kBAAI,MAAM,kBAAkB;AAC1B,yBAAS,SAAS,YAAY;AAAA,cAChC;AAAA,YACF;AAAA,UACF;AACA,iBAAO,YAAY,KAAK;AAAA,QAC1B;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,MAAM;AACnE;AACA,IAAI,mCAAmC;AAAA,EACrC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,mBAAiB,GAAG,SAAS;AAC7B,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,aAAa,eAAe,MAAM,EAAE,KAAK;AACvD,MAAI,UAAU,GAAG;AACf,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD;AACA,QAAM,SAAS,IAAI,aAAa,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,OAAO,SAAS,WAAW,CAAC;AAClC,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM,MAAM;AACvC,UAAM,SAAS,OAAO,WAAW,EAAE;AACnC,UAAM,QAAQ,OAAO,MAAM;AAC3B,UAAM,QAAQ,CAAC,MAAM,MAAM,KAAK,EAAE,MAAM,KAAK,IAAI,MAAM,EAAE;AACzD,WAAO,IAAI,KAAK,IAAI,GAAG,KAAK,GAAG,GAAG,MAAM;AAAA,EAC1C;AACA,SAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC1E;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,yBAAyB;AAAA,EAC3B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,UAAM,EAAE,SAAS,WAAW,OAAO,IAAI;AACvC,UAAM,aAAa;AACnB,UAAM,SAAS,aAAa,uBAAuB,OAAO,OAAO,aAAa,cAAc,OAAO,KAAK,CAAC;AACzG,UAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,UAAM,CAAC,SAAS,OAAO,IAAI,qBAAqB,eAAe,QAAQ,aAAa,UAAU;AAC9F,UAAM,mBAAmB;AACzB,UAAM,YAAY,KAAK,IAAI,OAAO;AAClC,UAAM,YAAY,KAAK,IAAI,OAAO;AAClC,UAAM,YAAY,WAAW,KAAK,IAAI,OAAO,MAAM,EAAE;AACrD,aAAS,WAAW,GAAG,WAAW,OAAO,YAAY;AACnD,YAAM,cAAc,WAAW,aAAa,cAAc;AAC1D,eAAS,MAAM,GAAG,MAAM,aAAa,OAAO;AAC1C,cAAM,YAAY,OAAO,aAAa;AACtC,iBAAS,MAAM,GAAG,MAAM,YAAY,OAAO;AACzC,gBAAM,YAAY,MAAM;AACxB,mBAAS,UAAU,GAAG,UAAU,aAAa,WAAW;AACtD,kBAAM,UAAU,CAAC,OAAO,KAAK,KAAK,OAAO;AACzC,kBAAM,IAAI,QAAQ;AAClB,kBAAM,IAAI,QAAQ;AAClB,gBAAI,UAAU,IAAI,WAAW,aAAa,IAAI,WAAW;AACzD,gBAAI,UAAU,IAAI,WAAW,aAAa,IAAI,WAAW;AACzD,qBAAS,KAAK,MAAM,SAAS,OAAO;AACpC,qBAAS,KAAK,MAAM,SAAS,OAAO;AACpC,gBAAI,cAAc;AAClB,gBAAI,OAAO,cAAc,UAAU;AACjC,kBAAI,YAAY,GAAG;AACjB,8BAAc;AAAA,cAChB,OAAO;AACL,8BAAc,UAAU;AAAA,cAC1B;AAAA,YACF;AACA,gBAAI,UAAU,KAAK,SAAS,cAAc,UAAU,KAAK,SAAS,aAAa;AAC7E,oBAAM,mBAAmB,UAAU,aAAa;AAChD,oBAAM,mBAAmB,SAAS;AAClC,oBAAM,WAAW,cAAc,mBAAmB,mBAAmB;AACrE,4BAAc,UAAU;AAAA,YAC1B;AACA,kBAAM,SAAS,cAAc,YAAY,YAAY;AACrD,mBAAO,UAAU;AAAA,UACnB;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,UAAM,SAAS,WAAW,MAAM,QAAQ,OAAO,OAAO,OAAO,KAAK;AAClE,WAAO,EAAE,QAAQ,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAAA,EAC5D;AACF;AAGA,IAAI,SAAS,gBAAgB,OAAO,CAAC,OAAO;AAC1C,QAAM,OAAO,KAAK,MAAM,EAAE;AAC1B,MAAI,KAAK,OAAO,KAAK;AACnB,WAAO,KAAK,MAAM,EAAE;AAAA,EACtB,WAAW,KAAK,OAAO,KAAK;AAC1B,WAAO,KAAK,KAAK,EAAE;AAAA,EACrB,OAAO;AACL,QAAI,OAAO,MAAM,GAAG;AAClB,aAAO;AAAA,IACT,OAAO;AACL,aAAO,OAAO;AAAA,IAChB;AAAA,EACF;AACF,CAAC;AACD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,SAAS,QAAQ,IAAI;AAC7B,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,EAAE,WAAW,YAAY,WAAW,SAAAY,UAAS,YAAAQ,YAAW,IAAI,qBAAqB,gBAAgB,SAAS,SAAS,KAAK;AAC9H,QAAM,iBAAiB;AACvB,QAAM,aAAa,SAAS,WAAW,OAAO;AAC9C,QAAM,aAAa,SAAS,WAAW,OAAO;AAC9C,QAAM,SAAS,YAAY,YAAY,YAAY,OAAOA,aAAY,WAAW,YAAY,WAAWR,UAAS,GAAG,cAAc;AAClI,SAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,MAAM;AACnE;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,QAAQ,OAAO;AAClC,MAAI,OAAO;AACX,MAAI,QAAQ,OAAO;AACnB,MAAI,MAAM;AACV,SAAO,OAAO,OAAO;AACnB,UAAM,KAAK,OAAO,OAAO,SAAS,CAAC;AACnC,QAAI,OAAO,OAAO,OAAO;AACvB,aAAO,MAAM;AAAA,IACf,OAAO;AACL,cAAQ;AAAA,IACV;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,YAAY,QAAQ,OAAO;AAClC,MAAI,OAAO;AACX,MAAI,QAAQ,OAAO;AACnB,MAAI,MAAM;AACV,SAAO,OAAO,OAAO;AACnB,UAAM,KAAK,OAAO,OAAO,SAAS,CAAC;AACnC,QAAI,OAAO,QAAQ,OAAO;AACxB,aAAO,MAAM;AAAA,IACf,OAAO;AACL,cAAQ;AAAA,IACV;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,cAAc,QAAQ,WAAW,WAAW,WAAW,MAAM;AACrF,QAAM,SAAS,aAAa,kBAAkB,SAAS,YAAY,SAAS;AAC5E,WAAS,IAAI,GAAG,IAAI,WAAW,EAAE,GAAG;AAClC,UAAM,oBAAoB,aAAa,MAAM,IAAI,YAAY,IAAI,KAAK,SAAS;AAC/E,UAAM,eAAe,IAAI;AACzB,aAAS,KAAK,GAAG,KAAK,WAAW,EAAE,IAAI;AACrC,aAAO,eAAe,MAAM,SAAS,SAAS,YAAY,mBAAmB,OAAO,KAAK,aAAa,IAAI,YAAY,mBAAmB,OAAO,KAAK,aAAa;AAAA,IACpK;AAAA,EACF;AACA,SAAO;AACT;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,gBAAgB,OAAO,IAAI;AACnC,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,kBAAkB,SAAS,KAAK,IAAI,eAAe,MAAM,EAAE;AACjE,QAAM,UAAU,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACjD,QAAM,SAAS,iBAAiB,iBAAiB,SAAS,eAAe,MAAM,IAAI,eAAe,MAAM,IAAI,OAAO,MAAM,IAAI,IAAI;AACjI,SAAO,SAAS,eAAe,OAAO,OAAO,SAAS,MAAM;AAC9D;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,WAAW,GAAG,IAAI,GAAG,GAAG,IAAI;AACpC,mBAAiB,CAAC,WAAW,IAAI,EAAE,GAAG,QAAQ;AAC9C,QAAM,gBAAgB,UAAU,MAAM;AACtC,QAAM,SAAS,SAAS,KAAK,IAAI,UAAU,MAAM,EAAE;AACnD,QAAM,UAAU,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC7C,QAAM,UAAU,SAAS,KAAK,IAAI,GAAG,MAAM,EAAE;AAC7C,QAAM,cAAc,WAAW,GAAG,OAAO,GAAG,KAAK;AACjD,QAAM,YAAY,aAAa,oBAAoB,aAAa,cAAc,GAAG,KAAK,GAAG,WAAW;AACpG,MAAIH,SAAQ;AACZ,QAAM,SAAS,kBAAkB,KAAK,gBAAgB,KAAK,GAAG,MAAM,WAAW,IAAI,IAAI,aAAa,cAAc,GAAG,MAAM,MAAM,CAAC,CAAC;AACnI,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,aAAS,IAAI,GAAG,IAAI,QAAQ,KAAK;AAC/B,UAAI,OAAO,QAAQ,GAAG;AACpB,kBAAUA,YAAW,QAAQ;AAAA,MAC/B,OAAO;AACL,kBAAUA,YAAW,QAAQ;AAAA,MAC/B;AAAA,IACF;AAAA,EACF;AACA,SAAO,SAAS,eAAe,GAAG,OAAO,aAAa,SAAS;AACjE;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa,qBAAqB;AACtC,IAAI,QAAQ,qBAAqB;AACjC,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO;AACxC,MAAI,MAAM,GAAG;AACX,WAAO,QAAQ;AAAA,EACjB,OAAO;AACL,WAAO,cAAc,KAAK,IAAI,EAAE,IAAI;AAAA,EACtC;AACF,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO;AACxC,MAAI,KAAK,GAAG;AACV,WAAO;AAAA,EACT,WAAW,KAAK,GAAG;AACjB,WAAO;AAAA,EACT,OAAO;AACL,WAAO;AAAA,EACT;AACF,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,gBAAgB,KAAK,CAAC,OAAO,KAAK,IAAI,EAAE,CAAC;AACpD,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW;AACf,IAAI,aAAa,KAAK,IAAI,QAAQ,IAAI;AACtC,IAAI,YAAY,gBAAgB,UAAU,CAAC,OAAO;AAChD,QAAM,WAAW,KAAK,CAAC;AACvB,QAAM,WAAW,KAAK;AACtB,QAAM,OAAO,KAAK,IAAI,EAAE;AACxB,MAAI;AACJ,MAAI,UAAU;AACZ,aAAS;AAAA,EACX,WAAW,UAAU;AACnB,aAAS;AAAA,EACX,OAAO;AACL,aAAS,KAAK,IAAI,IAAI,IAAI;AAAA,EAC5B;AACA,SAAO;AACT,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAS,IAAI;AACjC,mBAAiB,CAAC,CAAC,GAAG,gBAAgB;AACtC,QAAM,QAAQ,aAAa,cAAc,UAAU;AACnD,QAAM,mBAAmB,CAAC,CAAC,GAAG,CAAC,CAAC;AAChC,mBAAiB,KAAK,GAAG,QAAQ;AACjC,WAAS,KAAK,IAAI,WAAW,QAAQ,KAAK,EAAE,MAAM,QAAQ,EAAE,IAAI;AAC9D,qBAAiB,KAAK,CAAC,GAAG,CAAC,CAAC;AAAA,EAC9B;AACA,QAAM,UAAU,YAAY,WAAW;AAAA,IACrC,QAAQ,EAAE,EAAE;AAAA,IACZ,SAAS;AAAA,IACT,OAAO,EAAE,UAAU,kBAAkB,eAAe,EAAE;AAAA,EACxD,CAAC;AACD,QAAM,sBAAsB,qBAAqB,YAAY,QAAQ,OAAO,YAAY,OAAO,KAAK;AACpG,QAAM,oCAAoC,qBAAqB,YAAY,oBAAoB,QAAQ,WAAW,QAAQ,KAAK;AAC/H,QAAM,eAAe,qBAAqB,oBAAoB,QAAQ,OAAO,YAAY,OAAO,KAAK;AACrG,QAAM,gBAAgB,EAAE,GAAG,QAAQ;AACnC,QAAM,eAAe,EAAE,OAAO,oBAAoB;AAClD,QAAM,kBAAkB,SAAS,EAAE,QAAQ,eAAe,SAAS,UAAU,OAAO,aAAa,CAAC;AAClG,QAAM,kBAAkB,EAAE,GAAG,gBAAgB;AAC7C,QAAM,iBAAiB,EAAE,MAAM,kCAAkC;AACjE,QAAM,WAAW,WAAW,EAAE,QAAQ,iBAAiB,SAAS,UAAU,OAAO,eAAe,CAAC;AACjG,QAAM,sBAAsB,EAAE,GAAG,SAAS;AAC1C,QAAM,qBAAqB,EAAE,OAAO,aAAa;AACjD,QAAM,SAAS,SAAS,EAAE,QAAQ,qBAAqB,SAAS,UAAU,OAAO,mBAAmB,CAAC;AACrG,WAAS,8BAA8B,OAAO;AAC9C,WAAS,8BAA8B,eAAe;AACtD,WAAS,8BAA8B,QAAQ;AAC/C,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,SAAS,QAAQ,YAAY,aAAa,IAAI;AACtD,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,UACV,WAAW,OAAO;AAAA,EAC1B;AACA,MAAI,QAAQ,MAAM,WAAW,GAAG;AAC9B,UAAM,IAAI,MAAM;AAAA,UACV,QAAQ,OAAO;AAAA,EACvB;AACA,MAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,UAAM,IAAI,MAAM;AAAA,UACV,OAAO,OAAO;AAAA,EACtB;AACA,MAAI,aAAa,MAAM,WAAW,GAAG;AACnC,UAAM,IAAI,MAAM;AAAA,UACV,aAAa,OAAO;AAAA,EAC5B;AACA,QAAM,WAAW,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACnD,QAAM,UAAU,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACjD,QAAM,cAAc,SAAS,KAAK,IAAI,WAAW,MAAM,EAAE;AACzD,QAAM,gBAAgB,SAAS,KAAK,IAAI,aAAa,MAAM,EAAE,OAAO;AACpE,QAAM,CAAC,eAAe,oBAAoB,cAAc,mBAAmB,eAAe,IAAI,wBAAwB,UAAU,QAAQ,OAAO,QAAQ,OAAO,SAAS,OAAO,OAAO,aAAa,aAAa;AAC/M,SAAO;AAAA,IACL,SAAS,eAAe,oBAAoB,QAAQ,OAAO,aAAa;AAAA,IACxE,SAAS,eAAe,CAAC,mBAAmB,EAAE,GAAG,OAAO,OAAO,YAAY;AAAA,IAC3E,SAAS,eAAe,CAAC,kBAAkB,MAAM,GAAG,QAAQ,IAAI,WAAW,kBAAkB,IAAI,CAAC,UAAU,OAAO,KAAK,CAAC,CAAC,CAAC;AAAA,IAC3H,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,QAAQ,OAAO,IAAI,WAAW,eAAe,CAAC;AAAA,EAClG;AACF;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,cAAc,YAAY,SAAS,IAAI;AAC/C,MAAI,aAAa,MAAM,WAAW,GAAG;AACnC,UAAM,IAAI,MAAM;AAAA,UACV,aAAa,OAAO;AAAA,EAC5B;AACA,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,UACV,WAAW,OAAO;AAAA,EAC1B;AACA,MAAI,SAAS,MAAM,WAAW,GAAG;AAC/B,UAAM,IAAI,MAAM,sDAAsD,SAAS,OAAO;AAAA,EACxF;AACA,QAAM,cAAc,MAAM,KAAK,SAAS,KAAK,IAAI,WAAW,MAAM,EAAE,MAAM;AAC1E,QAAM,gBAAgB,SAAS,KAAK,IAAI,aAAa,MAAM,EAAE;AAC7D,QAAM,cAAc,MAAM,KAAK,SAAS,KAAK,IAAI,SAAS,MAAM,EAAE,MAAM;AACxE,QAAM,CAAC,YAAY,cAAc,WAAW,IAAI,kBAAkB,eAAe,aAAa,OAAO,aAAa,OAAO,aAAa,WAAW;AACjJ,SAAO;AAAA,IACL,SAAS,eAAe,cAAc,aAAa,OAAO,UAAU;AAAA,IACpE,SAAS,eAAe,CAAC,YAAY,MAAM,GAAG,SAAS,OAAO,IAAI,WAAW,WAAW,CAAC;AAAA,EAC3F;AACF;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,mBAAmB,MAAM;AAChC,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,MAAM,SAAS,WAAW,IAAI;AACtC,MAAI,KAAK,MAAM,SAAS,GAAG;AACzB,UAAM,IAAI,MAAM,2DAA2D;AAAA,EAC7E;AACA,MAAI,QAAQ,MAAM,WAAW,GAAG;AAC9B,UAAM,IAAI,MAAM;AAAA,YACR,QAAQ,OAAO;AAAA,EACzB;AACA,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,YACR,WAAW,OAAO;AAAA,EAC5B;AACA,MAAI,QAAQ,MAAM,OAAO,WAAW,MAAM,IAAI;AAC5C,UAAM,IAAI,MAAM,+CAA+C;AAAA,EACjE;AACA,QAAM,QAAQ,SAAS,KAAK,IAAI,KAAK,MAAM,EAAE;AAC7C,QAAM,WAAW,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACnD,QAAM,cAAc,SAAS,KAAK,IAAI,WAAW,MAAM,EAAE;AACzD,QAAM,CAAC,YAAY,eAAe,IAAI,2BAA2B,OAAO,KAAK,OAAO,KAAK,OAAO,UAAU,aAAa,IAAI;AAC3H,SAAO,SAAS,eAAe,iBAAiB,KAAK,OAAO,UAAU;AACxE;AACA,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,kBAAkB,MAAM;AAC/B,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,MAAM,SAAS,WAAW,IAAI;AACtC,MAAI,KAAK,MAAM,SAAS,GAAG;AACzB,UAAM,IAAI,MAAM,2DAA2D;AAAA,EAC7E;AACA,MAAI,QAAQ,MAAM,WAAW,GAAG;AAC9B,UAAM,IAAI,MAAM;AAAA,WACT,QAAQ,OAAO;AAAA,EACxB;AACA,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,WACT,WAAW,OAAO;AAAA,EAC3B;AACA,MAAI,QAAQ,MAAM,OAAO,WAAW,MAAM,IAAI;AAC5C,UAAM,IAAI,MAAM,+CAA+C;AAAA,EACjE;AACA,QAAM,QAAQ,SAAS,KAAK,IAAI,KAAK,MAAM,EAAE;AAC7C,QAAM,WAAW,SAAS,KAAK,IAAI,QAAQ,MAAM,EAAE;AACnD,QAAM,cAAc,SAAS,KAAK,IAAI,WAAW,MAAM,EAAE;AACzD,QAAM,CAAC,YAAY,eAAe,IAAI,2BAA2B,OAAO,KAAK,OAAO,KAAK,OAAO,UAAU,WAAW;AACrH,SAAO,SAAS,eAAe,iBAAiB,KAAK,OAAO,UAAU;AACxE;AACA,IAAI,yBAAyB;AAAA,EAC3B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,eAAe,cAAc,aAAa,IAAI;AACtD,QAAM,EAAE,YAAY,IAAI;AACxB,QAAM,EAAE,WAAW,YAAY,WAAW,SAAAG,UAAS,YAAAQ,YAAW,IAAI,qBAAqB,gBAAgB,cAAc,eAAe,WAAW;AAC/I,QAAM,iBAAiB;AACvB,QAAM,aAAa,SAAS,WAAW,aAAa;AACpD,MAAI;AACJ,UAAQ,aAAa;AAAA,SACd,QAAQ;AACX,YAAM,aAAa,SAAS,WAAW,YAAY;AACnD,YAAM,gBAAgB,QAAQ,SAAS,KAAK,IAAI,aAAa,MAAM,EAAE,OAAO,EAAE;AAC9E,eAAS,YAAY,YAAY,YAAY,aAAaA,aAAY,WAAW,YAAY,WAAWR,UAAS,eAAe,cAAc;AAC9I;AAAA,IACF;AAAA,SACK,WAAW;AACd,YAAM,aAAa,SAAS,WAAW,YAAY;AACnD,YAAM,gBAAgB,SAAS,KAAK,IAAI,aAAa,MAAM,EAAE,OAAO;AACpE,eAAS,YAAY,YAAY,YAAY,aAAaQ,aAAY,WAAW,YAAY,WAAWR,UAAS,eAAe,cAAc;AAC9I;AAAA,IACF;AAAA,SACK,SAAS;AACZ,YAAM,aAAa,SAAS,WAAW,YAAY;AACnD,YAAM,gBAAgB,SAAS,KAAK,IAAI,aAAa,MAAM,EAAE,OAAO;AACpE,eAAS,YAAY,YAAY,YAAY,aAAaQ,aAAY,WAAW,YAAY,WAAWR,UAAS,eAAe,cAAc;AAC9I;AAAA,IACF;AAAA,SACK,UAAU;AACb,YAAM,aAAa,SAAS,WAAW,YAAY;AACnD,YAAM,gBAAgB,aAAa,aAAa,SAAS,KAAK,IAAI,aAAa,MAAM,EAAE,OAAO,EAAE;AAChG,eAAS,YAAY,YAAY,YAAY,aAAaQ,aAAY,WAAW,YAAY,WAAWR,UAAS,eAAe,cAAc;AAC9I;AAAA,IACF;AAAA;AAEE,YAAM,IAAI,MAAM,oBAAoB,aAAa,OAAO;AAAA;AAE5D,SAAO,SAAS,eAAe,aAAa,OAAO,OAAO,OAAO,MAAM;AACzE;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,iBAAiB,KAAK,IAAI;AAClC,QAAM,QAAQ,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AACzD,QAAM,aAAa,qBAAqB,iBAAiB,GAAG,iBAAiB,KAAK;AAClF,QAAM,QAAQ,IAAI,MAAM,EAAE,MAAM,MAAM,EAAE,KAAK,CAAC;AAC9C,QAAMZ,QAAO,EAAE,MAAM,MAAM;AAC3B,SAAO,WAAW,IAAI,CAAC,OAAO;AAC5B,UAAM,YAAY,CAAC,GAAGA,KAAI;AAC1B,cAAU,SAAS;AACnB,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,MAAM,UAAU,EAAE,CAAC;AAC7F,UAAM,UAAU;AAChB,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AAC7C,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,aAAa;AACnB,qBAAiB,GAAG,QAAQ;AAC5B,UAAM,SAAS,WAAW,KAAK,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,YAAY,IAAI,aAAa,OAAO,MAAM;AAChD,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,YAAM,QAAQ,OAAO;AACrB,gBAAU,MAAM,QAAQ;AAAA,IAC1B;AACA,UAAM,SAAS,WAAW,MAAM,WAAW,EAAE,OAAO,EAAE,KAAK;AAC3D,WAAO,EAAE,QAAQ,OAAO,EAAE,OAAO,OAAO,EAAE,MAAM;AAAA,EAClD;AACF;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,IAAI,UAAU;AAC/C,QAAM,YAAY;AAClB,MAAI,MAAM,EAAE,GAAG;AACb,WAAO;AAAA,EACT,OAAO;AACL,WAAO,KAAK,IAAI,IAAI,UAAU;AAAA,EAChC;AACF,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAO,KAAK,SAAAY,UAAS,WAAW,SAAS,cAAc,aAAa,eAAe,IAAI;AAC/F,mBAAiB,GAAG,cAAc;AAClC,QAAM,EAAE,kBAAkB,YAAY,YAAY,WAAW,eAAe,OAAO,QAAQ,KAAK,MAAM,SAAS,SAAS,IAAI,mBAAmB,UAAU,EAAE,OAAO,OAAO,KAAKA,UAAS,WAAW,SAAS,cAAc,aAAa,cAAc;AACpP,MAAI;AACJ,MAAI,YAAY;AACd,aAAS,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAAA,EACtF,WAAW,aAAa,eAAe;AACrC,iBAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,yCAAyC,EAAE,MAAM,QAAQ;AACxG,UAAMZ,QAAO,mBAAmB,gBAAgB,QAAQ,MAAM,QAAQ;AACtE,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,QAAQ,MAAAA,MAAK,EAAE,CAAC;AAC1F,aAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAC5F,aAAS,8BAA8B,MAAM;AAAA,EAC/C,OAAO;AACL,UAAM,OAAO,SAAS,WAAW,CAAC;AAClC,UAAM,SAAS,iBAAiB,kBAAkB,MAAM,UAAU,MAAM;AACxE,aAAS,SAAS,eAAe,YAAY,OAAO,OAAO,OAAO,MAAM;AAAA,EAC1E;AACA,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,WAAW,aAAa,SAAS,UAAU,WAAW,UAAU,uBAAuB,IAAI;AACnG,QAAM,EAAE,MAAM,WAAW,IAAI;AAC7B,QAAM,QAAQ,SAAS,KAAK,IAAI,KAAK,MAAM,EAAE;AAC7C,QAAM,cAAc,SAAS,KAAK,IAAI,WAAW,MAAM,EAAE;AACzD,QAAM,CAAC,QAAQ,YAAY,IAAI,iBAAiB,OAAO,aAAa,WAAW,aAAa,SAAS,WAAW,UAAU,sBAAsB;AAChJ,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,OAAO,MAAM,GAAG,UAAU,MAAM;AAAA,IACzD,SAAS,eAAe,WAAW,OAAO,SAAS,YAAY;AAAA,EACjE;AACF;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,UAAU,IAAI;AACtB,QAAM,EAAE,OAAO,QAAQ,UAAU,IAAI;AACrC,MAAI,OAAO,UAAU,UAAU;AAC7B,UAAM,IAAI,MAAM,kCAAkC;AAAA,EACpD;AACA,MAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,UAAM,IAAI,MAAM,sCAAsC,OAAO,OAAO;AAAA,EACtE;AACA,MAAI,UAAU,MAAM,WAAW,GAAG;AAChC,UAAM,IAAI,MAAM,0CAA0C,UAAU,OAAO;AAAA,EAC7E;AACA,QAAM,SAAS,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AAChD,QAAM,aAAa,SAAS,KAAK,IAAI,UAAU,MAAM,EAAE,OAAO;AAC9D,QAAM,CAAC,SAAS,QAAQ,KAAK,IAAI,gBAAgB,QAAQ,YAAY,SAAS;AAC9E,QAAMoB,cAAa,OAAO;AAC1B,SAAO;AAAA,IACL,SAAS,eAAe,CAACA,aAAY,CAAC,GAAG,SAAS,OAAO;AAAA,IACzD,SAAS,eAAe,CAACA,WAAU,GAAG,UAAU,MAAM;AAAA,IACtD,SAAS,eAAe,CAAC,CAAC,GAAG,SAAS,IAAI,WAAW,KAAK,CAAC;AAAA,EAC7D;AACF;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,wBAAwB,MAAM;AACrC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,WAAW,IAAI;AACvB,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,MAAI,OAAO,UAAU,UAAU;AAC7B,UAAM,IAAI,MAAM,kCAAkC;AAAA,EACpD;AACA,MAAI,cAAc,GAAG;AACnB,UAAM,IAAI,MAAM,sCAAsC;AAAA,EACxD;AACA,QAAM,SAAS,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AAChD,QAAM,SAAS,2BAA2B,QAAQ,UAAU;AAC5D,SAAO,SAAS,eAAe,OAAO,OAAO,SAAS,MAAM;AAC9D;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,gBAAgB,KAAK,CAAC,OAAO,KAAK,IAAI,EAAE,CAAC;AACpD,IAAI,YAAY;AAAA,EACd,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,gBAAgB,MAAM,CAAC,OAAO,KAAK,KAAK,EAAE,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,mBAAiB,GAAG,MAAM;AAC1B,QAAM,SAAS,SAAS,SAAS,WAAW,CAAC,GAAG,IAAI;AACpD,SAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC1E;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,mBAAiB,GAAG,MAAM;AAC1B,QAAM,QAAQ,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC1C,QAAM,CAAC,aAAa,cAAc,IAAI,SAAS,OAAO,EAAE,OAAO,EAAE,OAAO,GAAG,MAAM;AACjF,SAAO;AAAA,IACL,SAAS,eAAe,YAAY,OAAO,YAAY,OAAO,YAAY,MAAM;AAAA,IAChF,SAAS,eAAe,eAAe,OAAO,eAAe,OAAO,eAAe,MAAM;AAAA,EAC3F;AACF;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,WAAW,IAAI;AACtC,QAAM,EAAE,eAAe,UAAU,WAAW,YAAY,IAAI;AAC5D,QAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,QAAM,CAAC,WAAW,QAAQ,IAAI,eAAe,OAAO,cAAc,CAAC,aAAa,UAAU;AAC1F,QAAM,WAAW,CAAC,OAAO,WAAW,UAAU,WAAW;AACzD,QAAMR,WAAU,aAAa,eAAe,OAAO,KAAK;AACxD,QAAM,cAAcA,SAAQ;AAC5B,QAAM,YAAYA,SAAQ;AAC1B,QAAM,YAAYA,SAAQ;AAC1B,QAAM,UAAU,aAAa,uBAAuB,OAAO,OAAO,aAAa,cAAc,QAAQ,CAAC;AACtG,UAAQ,KAAK,SAAS;AACtB,QAAM,YAAY,SAAS,KAAK,IAAI,OAAO,MAAM,EAAE;AACnD,QAAM,gBAAgB,SAAS,KAAK,IAAI,WAAW,MAAM,EAAE;AAC3D,WAAS,IAAI,GAAG,IAAI,OAAO,EAAE,GAAG;AAC9B,UAAM,aAAa,WAAW,MAAM,OAAO,IAAI,gBAAgB,cAAc,SAAS,IAAI,GAAG,IAAI,IAAI,CAAC;AACtG,aAAS,OAAO,GAAG,OAAO,WAAW,EAAE,MAAM;AAC3C,eAAS,OAAO,GAAG,OAAO,UAAU,EAAE,MAAM;AAC1C,iBAAS,UAAU,GAAG,UAAU,aAAa,EAAE,SAAS;AACtD,cAAI;AACJ,gBAAM,aAAa,WAAW,KAAK,OAAO,WAAW,KAAK,OAAO;AACjE,cAAI,eAAe,GAAG;AACpB;AAAA,UACF;AACA,gBAAM,OAAO,WAAW,KAAK,OAAO,WAAW,KAAK,OAAO,WAAW,MAAM;AAC5E,gBAAM,OAAO,WAAW,KAAK,OAAO,WAAW,KAAK,OAAO,WAAW,MAAM;AAC5E,gBAAM,IAAI,SAAS,KAAK,YAAY,QAAQ;AAC5C,gBAAM,IAAI,SAAS,KAAK,aAAa,QAAQ;AAC7C,kBAAQ;AAAA,iBACD;AACH,oBAAM,qBAAqB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,GAAG,GAAG,GAAG,SAAS,SAAS;AAC7H;AAAA,iBACG;AACH,oBAAM,sBAAsB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,GAAG,GAAG,GAAG,SAAS,SAAS;AAC9H;AAAA;AAEA,oBAAM,IAAI,MAAM,+DAA+D,eAAe;AAAA;AAElG,gBAAM,MAAM,IAAI,cAAc,OAAO,YAAY,OAAO,YAAY;AACpE,kBAAQ,OAAO;AAAA,QACjB;AAAA,MACF;AAAA,IACF;AACA,WAAO,SAAS,eAAe,UAAU,OAAO,OAAO,OAAO;AAAA,EAChE;AACA,QAAM,SAAS,SAAS,MAAM,SAAS,UAAU,OAAO,KAAK;AAC7D,SAAO,EAAE,QAAQ,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC5D;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AACA,SAAS,SAAS,UAAU,KAAK,MAAM;AACrC,UAAQ;AAAA,SACD;AACH,aAAO,gBAAgB,UAAU,GAAG;AAAA,SACjC;AACH,aAAO,aAAa,UAAU,GAAG;AAAA,SAC9B;AACH,aAAO,gBAAgB,UAAU,GAAG;AAAA,SACjC;AAAA;AAEH,aAAO,iBAAiB,UAAU,GAAG;AAAA;AAE3C;AACA,SAAS,gBAAgB,UAAU,KAAK;AACtC,MAAI,UAAU;AACd,MAAI,UAAU,GAAG;AACf,QAAI,OAAO,GAAG;AACZ,gBAAU;AAAA,IACZ,OAAO;AACL,YAAM,MAAM,IAAI;AAChB,UAAI,UAAU,KAAK;AACjB,kBAAU,MAAM,KAAK,MAAM,CAAC,UAAU,GAAG,IAAI;AAAA,MAC/C;AACA,gBAAU,UAAU,CAAC,MAAM,UAAU,MAAM,CAAC,UAAU;AAAA,IACxD;AAAA,EACF,WAAW,UAAU,MAAM,GAAG;AAC5B,QAAI,OAAO,GAAG;AACZ,gBAAU;AAAA,IACZ,OAAO;AACL,YAAM,MAAM,IAAI;AAChB,iBAAW,MAAM,KAAK,MAAM,UAAU,GAAG;AACzC,UAAI,WAAW,KAAK;AAClB,kBAAU,MAAM,UAAU;AAAA,MAC5B;AAAA,IACF;AAAA,EACF;AACA,SAAO,aAAa,MAAM,GAAG,SAAS,MAAM,CAAC;AAC/C;AACA,SAAS,aAAa,UAAU,KAAK;AACnC,MAAI,UAAU;AACd,MAAI,UAAU,GAAG;AACf,QAAI,OAAO,GAAG;AACZ,gBAAU;AAAA,IACZ,OAAO;AACL,YAAM,KAAK,MAAM;AACjB,iBAAW,OAAO,KAAK,MAAM,CAAC,UAAU,EAAE,IAAI;AAAA,IAChD;AAAA,EACF,WAAW,UAAU,MAAM,GAAG;AAC5B,QAAI,OAAO,GAAG;AACZ,gBAAU;AAAA,IACZ,OAAO;AACL,YAAM,KAAK,MAAM;AACjB,iBAAW,MAAM,KAAK,MAAM,UAAU,EAAE;AAAA,IAC1C;AAAA,EACF;AACA,SAAO,aAAa,MAAM,GAAG,SAAS,MAAM,CAAC;AAC/C;AACA,SAAS,iBAAiB,UAAU,KAAK;AACvC,SAAO;AACT;AACA,SAAS,gBAAgB,UAAU,KAAK;AACtC,SAAO,aAAa,MAAM,GAAG,UAAU,MAAM,CAAC;AAChD;AACA,SAAS,kBAAkB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,GAAG,GAAG,SAAS,WAAW;AACjI,QAAM,MAAM,QAAQ,cAAc,IAAI,YAAY,IAAI,YAAY;AAClE,MAAI,KAAK,KAAK,IAAI,eAAe,KAAK,KAAK,IAAI,YAAY;AACzD,WAAO,UAAU;AAAA,EACnB,OAAO;AACL,WAAO;AAAA,EACT;AACF;AACA,SAAS,qBAAqB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,GAAG,GAAG,SAAS,WAAW;AACpI,QAAM,KAAK,KAAK,MAAM,CAAC;AACvB,QAAM,KAAK,KAAK,MAAM,CAAC;AACvB,SAAO,kBAAkB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,IAAI,IAAI,SAAS,SAAS;AACnI;AACA,SAAS,sBAAsB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,GAAG,GAAG,SAAS,WAAW;AACrI,QAAM,SAAS,KAAK,MAAM,CAAC;AAC3B,QAAM,SAAS,KAAK,MAAM,CAAC;AAC3B,QAAM,QAAQ,SAAS;AACvB,QAAM,QAAQ,SAAS;AACvB,QAAM,eAAe,QAAQ,KAAK,kBAAkB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,QAAQ,QAAQ,SAAS,SAAS,KAAK,IAAI,UAAU,kBAAkB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,QAAQ,OAAO,SAAS,SAAS;AACxT,QAAM,cAAc,QAAQ,KAAK,kBAAkB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,OAAO,QAAQ,SAAS,SAAS,KAAK,IAAI,UAAU,kBAAkB,WAAW,aAAa,YAAY,aAAa,WAAW,WAAW,OAAO,OAAO,OAAO,SAAS,SAAS;AACrT,UAAQ,QAAQ,KAAK,eAAe,IAAI,UAAU;AACpD;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,EAAE,EAAE,IAAI;AACd,mBAAiB,GAAG,QAAQ;AAC5B,QAAM,SAAS,SAAS,KAAK,IAAI,EAAE,MAAM,EAAE;AAC3C,QAAM,EAAE,cAAc,aAAa,QAAQ,IAAI,WAAW,QAAQ,MAAM,EAAE,OAAO,EAAE,KAAK;AACxF,SAAO;AAAA,IACL,SAAS,eAAe,aAAa,EAAE,OAAO,YAAY;AAAA,IAC1D,SAAS,eAAe,CAAC,QAAQ,MAAM,GAAG,SAAS,OAAO;AAAA,EAC5D;AACF;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,IAAI;AAClB,MAAI,EAAE,KAAK,IAAI;AACf,MAAI,OAAO,GAAG;AACZ,YAAQ,MAAM,MAAM;AAAA,EACtB;AACA,QAAM,YAAY,MAAM,MAAM;AAC9B,QAAM,MAAM,MAAM,MAAM;AACxB,QAAM,WAAW,IAAI,MAAM,YAAY,CAAC;AACxC,MAAI,WAAW;AACf,WAAS,KAAK,GAAG,KAAK,WAAW,MAAM;AACrC,QAAI,OAAO,MAAM;AACf,eAAS,cAAc,MAAM,MAAM;AAAA,IACrC;AAAA,EACF;AACA,QAAM,QAAQ,IAAI,MAAM,SAAS,EAAE,KAAK,CAAC;AACzC,QAAMZ,QAAO,MAAM,MAAM,MAAM;AAC/B,EAAAA,MAAK,QAAQ;AACb,QAAM,MAAM,IAAI,MAAM,GAAG;AACzB,WAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,MAAM;AACtC,UAAM,QAAQ;AACd,UAAM,UAAU,OAAO,EAAE,QAAQ,EAAE,GAAG,MAAM,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,MAAAA,MAAK,EAAE,CAAC;AAC1F,QAAI,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC5F,aAAS,8BAA8B,OAAO;AAAA,EAChD;AACA,SAAO;AACT;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,oBAAoB,MAAM;AACjC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,WAAW,IAAI;AAC1B,QAAM,EAAE,YAAY,IAAI;AACxB,mBAAiB,GAAG,oBAAoB;AACxC,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,iBAAiB,WAAW,MAAM;AACxC,QAAM,MAAM,CAAC;AACb,QAAM,gBAAgB,CAAC;AACvB,QAAM,WAAW,QAAQ;AACzB,MAAI,cAAc;AAClB,WAAS,KAAK,GAAG,KAAK,UAAU,EAAE,IAAI;AACpC,UAAM,WAAW,YAAY,EAAE,QAAQ,EAAE,OAAO,YAAY,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,EAAE,CAAC;AAC1G,kBAAc;AACd,kBAAc,KAAK,QAAQ;AAAA,EAC7B;AACA,WAAS,KAAK,GAAG,KAAK,aAAa,EAAE,IAAI;AACvC,UAAM,cAAc,aAAa,kBAAkB,IAAI,OAAO;AAC9D,UAAM,YAAY,SAAS,eAAe,CAAC,GAAG,SAAS,WAAW;AAClE,UAAMK,QAAO,OAAO,EAAE,QAAQ,EAAE,GAAG,WAAW,GAAG,YAAY,GAAG,SAAS,SAAS,CAAC;AACnF,UAAM,aAAa,MAAM,EAAE,QAAQ,EAAE,GAAGA,MAAK,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AAChG,UAAM,OAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,YAAY,GAAG,EAAE,GAAG,SAAS,SAAS,CAAC;AAC7E,UAAM,gBAAgB,KAAK,EAAE,QAAQ,EAAE,GAAG,KAAK,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,GAAG,UAAU,MAAM,EAAE,CAAC;AAC1G,QAAI,KAAK,aAAa;AACtB,kBAAc,KAAK,SAAS;AAC5B,kBAAc,KAAKA,KAAI;AACvB,kBAAc,KAAK,UAAU;AAC7B,kBAAc,KAAK,IAAI;AACvB,kBAAc,KAAK,aAAa;AAAA,EAClC;AACA,QAAM,SAAS,KAAK,EAAE,QAAQ,KAAK,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,EAAE,CAAC;AAC1E,gBAAc,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACxE,SAAO;AACT;AACA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB;AAAA,EAClB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,WAAW,gBAAgB,eAAe;AACxC,iBAAe,YAAY;AAC7B;AAGA,IAAI,qBAAqB,CAAC;AAC1BR,UAAS,oBAAoB;AAAA,EAC3B,kBAAkB,MAAM;AAAA,EACxB,yBAAyB,MAAM;AAAA,EAC/B,+BAA+B,MAAM;AAAA,EACrC,oCAAoC,MAAM;AAAA,EAC1C,iBAAiB,MAAM;AAAA,EACvB,oCAAoC,MAAM;AAAA,EAC1C,cAAc,MAAM;AAAA,EACpB,kBAAkB,MAAM;AAAA,EACxB,sBAAsB,MAAM;AAAA,EAC5B,mBAAmB,MAAM;AAAA,EACzB,eAAe,MAAM;AAAA,EACrB,yBAAyB,MAAM;AAAA,EAC/B,0BAA0B,MAAM;AAAA,EAChC,eAAe,MAAM;AAAA,EACrB,oBAAoB,MAAM;AAAA,EAC1B,aAAa,MAAM;AAAA,EACnB,qBAAqB,MAAM;AAAA,EAC3B,4BAA4B,MAAM;AAAA,EAClC,wBAAwB,MAAM;AAAA,EAC9B,gBAAgB,MAAM;AAAA,EACtB,2BAA2B,MAAM;AAAA,EACjC,kCAAkC,MAAM;AAAA,EACxC,aAAa,MAAM;AAAA,EACnB,cAAc,MAAM;AAAA,EACpB,iCAAiC,MAAM;AAAA,EACvC,mCAAmC,MAAM;AAAA,EACzC,sBAAsB,MAAM;AAAA,EAC5B,wBAAwB,MAAM;AAAA,EAC9B,cAAc,MAAM;AAAA,EACpB,oCAAoC,MAAM;AAAA,EAC1C,+BAA+B,MAAM;AAAA,EACrC,eAAe,MAAM;AAAA,EACrB,qBAAqB,MAAM;AAAA,EAC3B,uBAAuB,MAAM;AAAA,EAC7B,aAAa,MAAM;AAAA,EACnB,2BAA2B,MAAM;AAAA,EACjC,qBAAqB,MAAM;AAAA,EAC3B,0BAA0B,MAAM;AAAA,EAChC,mCAAmC,MAAM;AAAA,EACzC,mBAAmB,MAAM;AAAA,EACzB,qBAAqB,MAAM;AAAA,EAC3B,iBAAiB,MAAM;AAAA,EACvB,qBAAqB,MAAM;AAC7B,CAAC;AAGD,IAAI,WAAW,CAAC;AAChB,IAAI,mBAAmB;AAAA,EACrB,OAAO;AAAA,EACP,WAAW;AAAA,EACX,oBAAoB;AAAA,EACpB,uBAAuB;AAAA,EACvB,OAAO;AAAA,EACP,SAAS;AAAA,EACT,8BAA8B;AAChC;AACA,SAAS,gBAAgB,cAAc,IAAI;AACzC,WAAS,gBAAgB;AAC3B;AACA,SAAS,gBAAgB,cAAc,cAAc;AACnD,MAAI,EAAE,gBAAgB,aAAa,gBAAgB,MAAM;AACvD,UAAM,SAAS,yBAAyB,cAAc,YAAY;AAClE,QAAI,WAAW,MAAM;AACnB,eAAS,gBAAgB;AAAA,IAC3B,OAAO;AACL,cAAQ,IAAI,2CAA2C,YAAY;AACnE,aAAO;AAAA,IACT;AAAA,EACF;AACA,QAAM,KAAK,SAAS;AACpB,MAAI,MAAM,QAAQ,GAAG,cAAc,GAAG;AACpC,WAAO,SAAS;AAChB,WAAO,gBAAgB,YAAY;AAAA,EACrC;AACA,KAAG,QAAQ,GAAG,UAAU;AACxB,KAAG,QAAQ,GAAG,YAAY;AAC1B,KAAG,QAAQ,GAAG,KAAK;AACnB,KAAG,QAAQ,GAAG,MAAM;AACpB,KAAG,QAAQ,GAAG,mBAAmB;AACjC,KAAG,QAAQ,GAAG,eAAe;AAC7B,KAAG,OAAO,GAAG,YAAY;AACzB,KAAG,OAAO,GAAG,SAAS;AACtB,KAAG,SAAS,GAAG,IAAI;AACnB,SAAO,SAAS;AAClB;AACA,SAAS,aAAa,cAAc;AAClC,MAAI,OAAO,oBAAoB,eAAe,iBAAiB,GAAG;AAChE,WAAO,IAAI,gBAAgB,KAAK,GAAG;AAAA,EACrC,WAAW,OAAO,aAAa,aAAa;AAC1C,WAAO,SAAS,cAAc,QAAQ;AAAA,EACxC,OAAO;AACL,UAAM,IAAI,MAAM,wCAAwC;AAAA,EAC1D;AACF;AACA,SAAS,yBAAyB,cAAc,cAAc;AAC5D,MAAI,iBAAiB,KAAK,iBAAiB,GAAG;AAC5C,UAAM,IAAI,MAAM,wDAAwD;AAAA,EAC1E;AACA,QAAMa,UAAS,gBAAgB,OAAO,aAAa,YAAY,IAAI;AACnE,EAAAA,QAAO,iBAAiB,oBAAoB,CAAC,OAAO;AAClD,OAAG,eAAe;AAClB,WAAO,SAAS;AAAA,EAClB,GAAG,KAAK;AACR,MAAI,iBAAiB,GAAG;AACtB,WAAOA,QAAO,WAAW,SAAS,gBAAgB,KAAKA,QAAO,WAAW,sBAAsB,gBAAgB;AAAA,EACjH;AACA,SAAOA,QAAO,WAAW,UAAU,gBAAgB;AACrD;AAGA,IAAI;AAAA,CACH,SAAS,gBAAgB;AACxB,iBAAe,eAAe,WAAW,KAAK;AAC9C,iBAAe,eAAe,kBAAkB,KAAK;AACvD,GAAG,kBAAkB,gBAAgB,CAAC,EAAE;AACxC,IAAI;AAAA,CACH,SAAS,eAAe;AACvB,gBAAc,cAAc,YAAY,KAAK;AAC7C,gBAAc,cAAc,YAAY,KAAK;AAC7C,gBAAc,cAAc,YAAY,KAAK;AAC7C,gBAAc,cAAc,cAAc,KAAK;AACjD,GAAG,iBAAiB,eAAe,CAAC,EAAE;AACtC,IAAI;AAAA,CACH,SAAS,sBAAsB;AAC9B,uBAAqB,qBAAqB,sBAAsB,KAAK;AACrE,uBAAqB,qBAAqB,sBAAsB,KAAK;AACrE,uBAAqB,qBAAqB,8BAA8B,KAAK;AAC7E,uBAAqB,qBAAqB,wBAAwB,KAAK;AACvE,uBAAqB,qBAAqB,wBAAwB,KAAK;AACzE,GAAG,wBAAwB,sBAAsB,CAAC,EAAE;AACpD,SAAS,yCAAyC,MAAM,SAAS;AAC/D,SAAO,CAAC,SAAS,IAAI;AACvB;AACA,SAAS,mCAAmC,YAAY,oBAAoB;AAC1E,SAAO,aAAa;AACtB;AACA,SAAS,iBAAiB,OAAO;AAC/B,QAAMV,QAAO,aAAa,cAAc,KAAK;AAC7C,QAAM,eAAe,KAAK,KAAKA,QAAO,CAAC;AACvC,SAAO,aAAa,oBAAoB,YAAY;AACtD;AACA,SAAS,uCAAuC,MAAM,SAAS;AAC7D,SAAO;AAAA,IACL,KAAK,IAAI,GAAG,KAAK,KAAK,UAAU,CAAC,CAAC;AAAA,IAClC,KAAK,IAAI,GAAG,KAAK,KAAK,OAAO,CAAC,CAAC;AAAA,EACjC;AACF;AACA,SAAS,sCAAsC,MAAM,SAAS;AAC5D,QAAM,CAAC,GAAG,CAAC,IAAI,uCAAuC,MAAM,OAAO;AACnE,SAAO,IAAI,IAAI;AACjB;AACA,SAAS,iBAAiB,IAAI,2BAA2B;AACvD,QAAM,QAAQ;AACd,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,0BAAsB,MAAM;AAC5B,8BAA0B,MAAM;AAChC,oCAAgC,MAAM;AACtC,gCAA4B,MAAM;AAClC,yBAAqB,MAAM;AAC3B,gCAA4B;AAC5B,yBAAqB;AACrB,2BAAuB,MAAM;AAC7B,uBAAmB,MAAM;AACzB,4BAAwB,MAAM;AAAA,EAChC,OAAO;AACL,0BAAsB,GAAG;AACzB,8BAA0B,GAAG;AAC7B,oCAAgC,GAAG;AACnC,gCAA4B,MAAM;AAClC,yBAAqB,GAAG;AACxB,gCAA4B;AAC5B,yBAAqB;AACrB,2BAAuB,6BAA6B,OAAO,0BAA0B,iBAAiB;AACtG,uBAAmB,GAAG;AACtB,4BAAwB,GAAG;AAAA,EAC7B;AACA,SAAO;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AAGA,SAAS,aAAa,IAAI,OAAO;AAC/B,QAAM,cAAc,MAAM;AAC1B,MAAI,IAAI,EAAE,QAAQ,OAAO,GAAG;AAC1B,oBAAgB,EAAE;AAAA,EACpB;AACA,SAAO;AACT;AACA,SAAS,gBAAgB,IAAI;AAC3B,QAAM,QAAQ,GAAG,SAAS;AAC1B,MAAI,UAAU,GAAG,UAAU;AACzB,UAAM,IAAI,MAAM,kBAAkB,qBAAqB,IAAI,KAAK,CAAC;AAAA,EACnE;AACF;AACA,IAAI,cAAc;AAClB,IAAI,cAAc;AAClB,SAAS,iBAAiB,KAAK;AAC7B,MAAI,IAAI,EAAE,QAAQ,8BAA8B,KAAK,QAAQ,KAAK,cAAc,KAAK,IAAI,GAAG,KAAK,KAAK,IAAI,GAAG,IAAI,aAAa;AAC5H,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,qBAAqB,IAAI,QAAQ;AACxC,UAAQ;AAAA,SACD,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA;AAEP,aAAO,sBAAsB;AAAA;AAEnC;AACA,SAAS,oBAAoB,IAAI,eAAe;AAC9C,SAAO,YAAY,IAAI,MAAM,GAAG,aAAa,aAAa,GAAG,gBAAgB,gBAAgB,kCAAkC;AACjI;AACA,SAAS,mBAAmB,IAAI,oBAAoB;AAClD,QAAM,eAAe,YAAY,IAAI,MAAM,GAAG,aAAa,GAAG,aAAa,GAAG,sCAAsC;AACpH,eAAa,IAAI,MAAM,GAAG,aAAa,cAAc,kBAAkB,CAAC;AACxE,eAAa,IAAI,MAAM,GAAG,cAAc,YAAY,CAAC;AACrD,MAAI,GAAG,mBAAmB,cAAc,GAAG,cAAc,MAAM,OAAO;AACpE,YAAQ,IAAI,GAAG,iBAAiB,YAAY,CAAC;AAC7C,UAAM,IAAI,MAAM,kCAAkC;AAAA,EACpD;AACA,SAAO;AACT;AACA,SAAS,qBAAqB,IAAI,sBAAsB;AACtD,QAAM,iBAAiB,YAAY,IAAI,MAAM,GAAG,aAAa,GAAG,eAAe,GAAG,wCAAwC;AAC1H,eAAa,IAAI,MAAM,GAAG,aAAa,gBAAgB,oBAAoB,CAAC;AAC5E,eAAa,IAAI,MAAM,GAAG,cAAc,cAAc,CAAC;AACvD,MAAI,IAAI,EAAE,IAAI,qBAAqB,GAAG;AACpC,WAAO;AAAA,EACT;AACA,MAAI,GAAG,mBAAmB,gBAAgB,GAAG,cAAc,MAAM,OAAO;AACtE,8BAA0B,sBAAsB,GAAG,iBAAiB,cAAc,CAAC;AACnF,UAAM,IAAI,MAAM,oCAAoC;AAAA,EACtD;AACA,SAAO;AACT;AACA,IAAI,kBAAkB;AACtB,SAAS,0BAA0B,cAAc,eAAe;AAC9D,QAAM,wBAAwB,gBAAgB,KAAK,aAAa;AAChE,MAAI,yBAAyB,MAAM;AACjC,YAAQ,IAAI,wCAAwC,eAAe;AACnE,YAAQ,IAAI,YAAY;AACxB;AAAA,EACF;AACA,QAAM,aAAa,CAAC,sBAAsB;AAC1C,QAAM,cAAc,aAAa,MAAM,IAAI;AAC3C,QAAM,OAAO,YAAY,OAAO,SAAS,EAAE,SAAS;AACpD,QAAM,uBAAuB,YAAY,IAAI,CAAC,MAAM,gBAAgB,aAAa,UAAU,cAAc,GAAG,SAAS,GAAG,IAAI,IAAI,IAAI;AACpI,MAAI,gBAAgB;AACpB,WAAS,KAAK,GAAG,KAAK,qBAAqB,QAAQ,MAAM;AACvD,oBAAgB,KAAK,IAAI,qBAAqB,IAAI,QAAQ,aAAa;AAAA,EACzE;AACA,QAAM,mBAAmB,qBAAqB,MAAM,GAAG,aAAa,CAAC;AACrE,QAAM,YAAY,qBAAqB,MAAM,aAAa,GAAG,UAAU;AACvE,QAAM,kBAAkB,qBAAqB,MAAM,UAAU;AAC7D,UAAQ,IAAI,iBAAiB,KAAK,IAAI,CAAC;AACvC,UAAQ,IAAI,cAAc,MAAM,IAAI,EAAE,EAAE;AACxC,UAAQ,IAAI,MAAM,aAAa,SAAS,UAAU,IAAI,aAAa,KAAK,+DAA+D;AACvI,UAAQ,IAAI,gBAAgB,KAAK,IAAI,CAAC;AACxC;AACA,SAAS,cAAc,IAAI;AACzB,SAAO,YAAY,IAAI,MAAM,GAAG,cAAc,GAAG,gCAAgC;AACnF;AACA,SAAS,YAAY,IAAI,SAAS;AAChC,eAAa,IAAI,MAAM,GAAG,YAAY,OAAO,CAAC;AAC9C,MAAI,IAAI,EAAE,IAAI,qBAAqB,GAAG;AACpC;AAAA,EACF;AACA,MAAI,GAAG,oBAAoB,SAAS,GAAG,WAAW,MAAM,OAAO;AAC7D,YAAQ,IAAI,GAAG,kBAAkB,OAAO,CAAC;AACzC,UAAM,IAAI,MAAM,6CAA6C;AAAA,EAC/D;AACF;AACA,SAAS,gBAAgB,IAAI,SAAS;AACpC,eAAa,IAAI,MAAM,GAAG,gBAAgB,OAAO,CAAC;AAClD,MAAI,GAAG,oBAAoB,SAAS,GAAG,eAAe,MAAM,OAAO;AACjE,YAAQ,IAAI,GAAG,kBAAkB,OAAO,CAAC;AACzC,UAAM,IAAI,MAAM,mCAAmC;AAAA,EACrD;AACF;AACA,SAAS,yBAAyB,IAAI,MAAM;AAC1C,QAAM,UAAU,YAAY,IAAI,MAAM,GAAG,aAAa,GAAG,8BAA8B;AACvF,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,cAAc,OAAO,CAAC;AAC9D,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,cAAc,MAAM,GAAG,WAAW,CAAC;AAC3E,SAAO;AACT;AACA,SAAS,wBAAwB,IAAI,MAAM;AACzC,QAAM,UAAU,YAAY,IAAI,MAAM,GAAG,aAAa,GAAG,8BAA8B;AACvF,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,sBAAsB,OAAO,CAAC;AACtE,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,sBAAsB,MAAM,GAAG,WAAW,CAAC;AACnF,SAAO;AACT;AACA,SAAS,iBAAiB;AACxB,MAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,cAAc,IAAI;AACzB,SAAO,YAAY,IAAI,MAAM,GAAG,cAAc,GAAG,gCAAgC;AACnF;AACA,SAAS,oBAAoB,OAAO,QAAQ;AAC1C,QAAM,iBAAiB,IAAI,EAAE,UAAU,wBAAwB;AAC/D,MAAI,SAAS,KAAK,UAAU,GAAG;AAC7B,UAAM,YAAY,IAAI,SAAS;AAC/B,UAAM,IAAI,MAAM,4BAA4B,YAAY,cAAc;AAAA,EACxE;AACA,MAAI,QAAQ,kBAAkB,SAAS,gBAAgB;AACrD,UAAM,YAAY,IAAI,SAAS;AAC/B,UAAM,OAAO,IAAI,kBAAkB;AACnC,UAAM,IAAI,MAAM,4BAA4B,YAAY,uDAAuD,OAAO,GAAG;AAAA,EAC3H;AACF;AACA,SAAS,kBAAkB,IAAI;AAC7B,SAAO,YAAY,IAAI,MAAM,GAAG,kBAAkB,GAAG,oCAAoC;AAC3F;AACA,SAAS,mCAAmC,IAAI,SAAS,WAAW,SAAS,qBAAqB,mBAAmB,mBAAmB;AACtI,QAAM,MAAM,GAAG,kBAAkB,SAAS,SAAS;AACnD,MAAI,QAAQ,IAAI;AACd,WAAO;AAAA,EACT;AACA,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,cAAc,OAAO,CAAC;AAC9D,eAAa,IAAI,MAAM,GAAG,oBAAoB,KAAK,qBAAqB,GAAG,OAAO,OAAO,mBAAmB,iBAAiB,CAAC;AAC9H,eAAa,IAAI,MAAM,GAAG,wBAAwB,GAAG,CAAC;AACtD,SAAO;AACT;AACA,SAAS,gBAAgB,IAAI,SAAS,aAAa;AACjD,sBAAoB,IAAI,WAAW;AACnC,eAAa,IAAI,MAAM,GAAG,cAAc,GAAG,WAAW,WAAW,CAAC;AAClE,eAAa,IAAI,MAAM,GAAG,YAAY,GAAG,YAAY,OAAO,CAAC;AAC/D;AACA,SAAS,kBAAkB,IAAI,aAAa;AAC1C,sBAAoB,IAAI,WAAW;AACnC,eAAa,IAAI,MAAM,GAAG,cAAc,GAAG,WAAW,WAAW,CAAC;AAClE,eAAa,IAAI,MAAM,GAAG,YAAY,GAAG,YAAY,IAAI,CAAC;AAC5D;AACA,SAAS,iCAAiC,IAAI,SAAS,aAAa;AAClE,SAAO,YAAY,IAAI,MAAM,GAAG,mBAAmB,SAAS,WAAW,GAAG,cAAc,cAAc,2BAA2B;AACnI;AACA,SAAS,0BAA0B,IAAI,SAAS,aAAa;AAC3D,SAAO,GAAG,mBAAmB,SAAS,WAAW;AACnD;AACA,SAAS,mCAAmC,IAAI,SAAS,wBAAwB,aAAa;AAC5F,eAAa,IAAI,MAAM,gBAAgB,IAAI,SAAS,WAAW,CAAC;AAChE,eAAa,IAAI,MAAM,GAAG,UAAU,wBAAwB,WAAW,CAAC;AAC1E;AACA,SAAS,wBAAwB,IAAI;AACnC,eAAa,IAAI,MAAM,GAAG,gBAAgB,GAAG,aAAa,IAAI,CAAC;AAC/D,eAAa,IAAI,MAAM,GAAG,SAAS,GAAG,GAAG,GAAG,OAAO,OAAO,GAAG,OAAO,MAAM,CAAC;AAC3E,eAAa,IAAI,MAAM,GAAG,QAAQ,GAAG,GAAG,GAAG,OAAO,OAAO,GAAG,OAAO,MAAM,CAAC;AAC5E;AACA,SAAS,8BAA8B,IAAI,SAAS,aAAa;AAC/D,eAAa,IAAI,MAAM,GAAG,gBAAgB,GAAG,aAAa,WAAW,CAAC;AACtE,eAAa,IAAI,MAAM,GAAG,qBAAqB,GAAG,aAAa,GAAG,mBAAmB,GAAG,YAAY,SAAS,CAAC,CAAC;AACjH;AACA,SAAS,kCAAkC,IAAI,aAAa;AAC1D,eAAa,IAAI,MAAM,GAAG,gBAAgB,GAAG,aAAa,WAAW,CAAC;AACtE,eAAa,IAAI,MAAM,GAAG,qBAAqB,GAAG,aAAa,GAAG,mBAAmB,GAAG,YAAY,MAAM,CAAC,CAAC;AAC9G;AACA,SAAS,oBAAoB,IAAI;AAC/B,QAAM,SAAS,GAAG,uBAAuB,GAAG,WAAW;AACvD,MAAI,WAAW,GAAG,sBAAsB;AACtC,UAAM,IAAI,MAAM,gCAAgC,2BAA2B,IAAI,MAAM,CAAC;AAAA,EACxF;AACF;AACA,SAAS,2BAA2B,IAAI,QAAQ;AAC9C,UAAQ;AAAA,SACD,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA,SACJ,GAAG;AACN,aAAO;AAAA;AAEP,aAAO,iBAAiB;AAAA;AAE9B;AACA,SAAS,YAAY,IAAI,eAAe,gBAAgB;AACtD,QAAM,UAAU,aAAa,IAAI,MAAM,cAAc,CAAC;AACtD,MAAI,WAAW,MAAM;AACnB,UAAM,IAAI,MAAM,cAAc;AAAA,EAChC;AACA,SAAO;AACT;AACA,SAAS,oBAAoB,IAAI,aAAa;AAC5C,QAAM,iBAAiB,GAAG,mCAAmC;AAC7D,QAAM,gBAAgB,cAAc,GAAG;AACvC,MAAI,gBAAgB,GAAG,YAAY,gBAAgB,gBAAgB;AACjE,UAAM,mBAAmB,2BAA2B;AACpD,UAAM,IAAI,MAAM,0BAA0B,mBAAmB;AAAA,EAC/D;AACF;AACA,SAAS,YAAY,OAAO,aAAa,GAAG;AAC1C,SAAO,aAAa,cAAc,MAAM,MAAM,GAAG,MAAM,SAAS,UAAU,CAAC;AAC7E;AACA,SAAS,YAAY,OAAO;AAC1B,MAAI,MAAM,WAAW,GAAG;AACtB,UAAM,MAAM,sDAAsD;AAAA,EACpE;AACA,SAAO;AAAA,IACL,MAAM,SAAS,IAAI,MAAM,MAAM,SAAS,KAAK;AAAA,IAC7C,MAAM,MAAM,SAAS;AAAA,EACvB;AACF;AACA,SAAS,aAAa,OAAO;AAC3B,MAAI,YAAY,CAAC,GAAG,GAAG,CAAC;AACxB,QAAM,WAAW,MAAM,WAAW,KAAK,MAAM,WAAW,KAAK,MAAM,OAAO;AAC1E,MAAI,CAAC,UAAU;AACb,gBAAY,CAAC,YAAY,KAAK,GAAG,GAAG,YAAY,KAAK,CAAC;AAAA,EACxD;AACA,SAAO;AACT;AACA,SAAS,gCAAgC,UAAU,WAAW,OAAO;AACnE,MAAI,aAAa,IAAI,EAAE,UAAU,wBAAwB;AACzD,MAAI,UAAU;AACZ,iBAAa,aAAa;AAC1B,eAAW,SAAS,IAAI,CAAC,GAAG,OAAO,MAAM,SAAS,SAAS,IAAI,aAAa,kBAAkB,SAAS,GAAG,IAAI,SAAS,GAAG;AAC1H,QAAI,SAAS,WAAW,GAAG;AACzB,iBAAW,CAAC,GAAG,SAAS,EAAE;AAAA,IAC5B;AAAA,EACF;AACA,MAAI,SAAS,WAAW,GAAG;AACzB,UAAM,gBAAgB,aAAa,aAAa,QAAQ;AACxD,eAAW,cAAc;AAAA,EAC3B;AACA,MAAIA,QAAO,aAAa,cAAc,QAAQ;AAC9C,MAAI,SAAS,UAAU,KAAKA,SAAQ,YAAY;AAC9C,WAAO,CAAC,GAAGA,KAAI;AAAA,EACjB,WAAW,SAAS,WAAW,KAAK,SAAS,MAAM,cAAc,SAAS,MAAM,YAAY;AAC1F,WAAO;AAAA,EACT,WAAW,SAAS,WAAW,KAAK,SAAS,KAAK,SAAS,MAAM,cAAc,SAAS,MAAM,YAAY;AACxG,WAAO,CAAC,SAAS,KAAK,SAAS,IAAI,SAAS,EAAE;AAAA,EAChD,WAAW,SAAS,WAAW,KAAK,SAAS,MAAM,cAAc,SAAS,KAAK,SAAS,MAAM,YAAY;AACxG,WAAO,CAAC,SAAS,IAAI,SAAS,KAAK,SAAS,EAAE;AAAA,EAChD,WAAW,SAAS,WAAW,KAAK,SAAS,KAAK,SAAS,KAAK,SAAS,MAAM,cAAc,SAAS,MAAM,YAAY;AACtH,WAAO,CAAC,SAAS,KAAK,SAAS,KAAK,SAAS,IAAI,SAAS,EAAE;AAAA,EAC9D,WAAW,SAAS,WAAW,KAAK,SAAS,MAAM,cAAc,SAAS,KAAK,SAAS,KAAK,SAAS,MAAM,YAAY;AACtH,WAAO,CAAC,SAAS,IAAI,SAAS,KAAK,SAAS,KAAK,SAAS,EAAE;AAAA,EAC9D,OAAO;AACL,QAAI,UAAU;AACZ,YAAM,WAAW,YAAY,QAAQ;AACrC,UAAI,OAAO,GAAG,OAAO;AACrB,UAAI,SAAS,QAAQ;AACnB,SAAC,MAAM,IAAI,IAAI,YAAY,QAAQ;AAAA,MACrC;AACA,MAAAA,QAAO,YAAY,OAAO,MAAM,OAAO;AACvC,aAAO,aAAa,oBAAoBA,KAAI,EAAE,IAAI,CAAC,MAAM,IAAI,CAAC;AAAA,IAChE;AACA,WAAO,aAAa,oBAAoBA,KAAI;AAAA,EAC9C;AACF;AACA,SAAS,OAAO,IAAI;AAClB,SAAO,KAAK,MAAM;AACpB;AACA,SAAS,cAAc,QAAQ,QAAQ;AACrC,WAAS,OAAO,MAAM,EAAE;AACxB,WAAS,OAAO,MAAM,EAAE;AACxB,MAAI,aAAa,YAAY,QAAQ,MAAM,GAAG;AAC5C,WAAO;AAAA,EACT;AACA,MAAI,CAAC,OAAO,UAAU,CAAC,OAAO,QAAQ;AACpC,WAAO;AAAA,EACT;AACA,MAAI,OAAO,OAAO,KAAK,OAAO,OAAO,KAAK,OAAO,OAAO,KAAK,OAAO,OAAO,GAAG;AAC5E,WAAO;AAAA,EACT;AACA,MAAI,OAAO,WAAW,OAAO,QAAQ;AACnC,UAAM,aAAa,OAAO,MAAM,EAAE,EAAE;AACpC,UAAM,aAAa,OAAO,MAAM,EAAE,EAAE;AACpC,QAAI,eAAe,YAAY;AAC7B,aAAO;AAAA,IACT;AACA,QAAI,OAAO,UAAU,KAAK,OAAO,UAAU,MAAM,OAAO,OAAO,KAAK,OAAO,OAAO,IAAI;AACpF,aAAO;AAAA,IACT;AAAA,EACF;AACA,SAAO,OAAO,OAAO,OAAO,MAAM,OAAO,OAAO,EAAE,KAAK,OAAO,OAAO,EAAE;AACzE;AACA,IAAI;AACJ,IAAI;AACJ,SAAS,uBAAuB,cAAc;AAC5C,MAAI,oBAAoB,MAAM;AAC5B,UAAM,KAAK,gBAAgB,YAAY;AACvC,uBAAmB,GAAG,aAAa,GAAG,gBAAgB;AAAA,EACxD;AACA,SAAO;AACT;AACA,SAAS,sBAAsB;AAC7B,qBAAmB;AACrB;AACA,SAAS,2BAA2B;AAClC,2BAAyB;AAC3B;AACA,SAAS,uBAAuB,cAAc;AAC5C,MAAI,0BAA0B,MAAM;AAClC,UAAM,KAAK,gBAAgB,YAAY;AACvC,6BAAyB,GAAG,aAAa,GAAG,uBAAuB;AAAA,EACrE;AACA,SAAO,KAAK,IAAI,IAAI,sBAAsB;AAC5C;AACA,SAAS,kCAAkC,cAAc;AACvD,MAAI,iBAAiB,GAAG;AACtB,WAAO;AAAA,EACT;AACA,MAAI;AACJ,QAAM,KAAK,gBAAgB,YAAY;AACvC,MAAI,aAAa,IAAI,iCAAiC,KAAK,iBAAiB,GAAG;AAC7E,wBAAoB;AAAA,EACtB,WAAW,aAAa,IAAI,0BAA0B,GAAG;AACvD,wBAAoB;AAAA,EACtB,OAAO;AACL,wBAAoB;AAAA,EACtB;AACA,SAAO;AACT;AACA,SAAS,aAAa,IAAI,eAAe;AACvC,QAAM,MAAM,GAAG,aAAa,aAAa;AACzC,SAAO,OAAO;AAChB;AACA,SAAS,sBAAsB,cAAc;AAC3C,MAAI;AACF,UAAM,KAAK,gBAAgB,YAAY;AACvC,QAAI,MAAM,MAAM;AACd,aAAO;AAAA,IACT;AAAA,EACF,SAAS,IAAP;AACA,YAAQ,IAAI,sCAAsC,EAAE;AACpD,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,mCAAmC,cAAc;AACxD,MAAI,iBAAiB,GAAG;AACtB,WAAO;AAAA,EACT;AACA,QAAM,KAAK,gBAAgB,YAAY;AACvC,MAAI,iBAAiB,GAAG;AACtB,QAAI,CAAC,aAAa,IAAI,mBAAmB,GAAG;AAC1C,aAAO;AAAA,IACT;AAAA,EACF,OAAO;AACL,QAAI,CAAC,aAAa,IAAI,wBAAwB,GAAG;AAC/C,aAAO;AAAA,IACT;AAAA,EACF;AACA,QAAM,wBAAwB,uCAAuC,EAAE;AACvE,SAAO;AACT;AACA,SAAS,8BAA8B,cAAc;AACnD,MAAI,iBAAiB,GAAG;AACtB,WAAO;AAAA,EACT;AACA,QAAM,KAAK,gBAAgB,YAAY;AACvC,MAAI,iBAAiB,GAAG;AACtB,QAAI,CAAC,aAAa,IAAI,mBAAmB,GAAG;AAC1C,aAAO;AAAA,IACT;AACA,QAAI,CAAC,aAAa,IAAI,0BAA0B,GAAG;AACjD,aAAO;AAAA,IACT;AAAA,EACF,OAAO;AACL,QAAI,aAAa,IAAI,wBAAwB,GAAG;AAC9C,aAAO,uCAAuC,EAAE;AAAA,IAClD;AACA,UAAM,0BAA0B;AAChC,QAAI,aAAa,IAAI,uBAAuB,GAAG;AAC7C,YAAM,4BAA4B,GAAG,aAAa,uBAAuB;AACzE,aAAO,2CAA2C,IAAI,yBAAyB;AAAA,IACjF;AACA,WAAO;AAAA,EACT;AACA,QAAM,wBAAwB,uCAAuC,EAAE;AACvE,SAAO;AACT;AACA,SAAS,uCAAuC,IAAI;AAClD,QAAM,YAAY,iBAAiB,EAAE;AACrC,QAAM,UAAU,GAAG,cAAc;AACjC,KAAG,YAAY,GAAG,YAAY,OAAO;AACrC,QAAM,QAAQ;AACd,QAAM,SAAS;AACf,KAAG,WAAW,GAAG,YAAY,GAAG,UAAU,qBAAqB,OAAO,QAAQ,GAAG,UAAU,oBAAoB,UAAU,kBAAkB,IAAI;AAC/I,QAAM,cAAc,GAAG,kBAAkB;AACzC,KAAG,gBAAgB,GAAG,aAAa,WAAW;AAC9C,KAAG,qBAAqB,GAAG,aAAa,GAAG,mBAAmB,GAAG,YAAY,SAAS,CAAC;AACvF,QAAM,wBAAwB,GAAG,uBAAuB,GAAG,WAAW,MAAM,GAAG;AAC/E,KAAG,YAAY,GAAG,YAAY,IAAI;AAClC,KAAG,gBAAgB,GAAG,aAAa,IAAI;AACvC,KAAG,cAAc,OAAO;AACxB,KAAG,kBAAkB,WAAW;AAChC,SAAO;AACT;AACA,SAAS,2CAA2C,IAAI,2BAA2B;AACjF,QAAM,YAAY,iBAAiB,IAAI,yBAAyB;AAChE,QAAM,UAAU,GAAG,cAAc;AACjC,KAAG,YAAY,GAAG,YAAY,OAAO;AACrC,QAAM,QAAQ;AACd,QAAM,SAAS;AACf,KAAG,WAAW,GAAG,YAAY,GAAG,UAAU,yBAAyB,OAAO,QAAQ,GAAG,UAAU,oBAAoB,UAAU,sBAAsB,IAAI;AACvJ,QAAM,cAAc,GAAG,kBAAkB;AACzC,KAAG,gBAAgB,GAAG,aAAa,WAAW;AAC9C,KAAG,qBAAqB,GAAG,aAAa,GAAG,mBAAmB,GAAG,YAAY,SAAS,CAAC;AACvF,QAAM,wBAAwB,GAAG,uBAAuB,GAAG,WAAW,MAAM,GAAG;AAC/E,KAAG,YAAY,GAAG,YAAY,IAAI;AAClC,KAAG,gBAAgB,GAAG,aAAa,IAAI;AACvC,KAAG,cAAc,OAAO;AACxB,KAAG,kBAAkB,WAAW;AAChC,SAAO;AACT;AACA,SAAS,oBAAoB,cAAc;AACzC,MAAI,iBAAiB,GAAG;AACtB,WAAO;AAAA,EACT;AACA,QAAM,KAAK,gBAAgB,YAAY;AACvC,QAAM,YAAY,GAAG,aAAa;AAClC,SAAO;AACT;AACA,SAAS,kBAAkB,SAAS,QAAQ;AAC1C,MAAI,CAAC,MAAM,QAAQ,OAAO,GAAG;AAC3B,cAAU,CAAC,OAAO;AAAA,EACpB;AACA,UAAQ,QAAQ,CAAC,OAAO;AACtB,QAAI,MAAM,MAAM;AACd,mBAAa,OAAO,GAAG,UAAU,aAAa,MAAM,GAAG,iEAAiE;AAAA,IAC1H;AAAA,EACF,CAAC;AACH;AAGA,IAAI,OAAO,IAAI;AACf,KAAK,aAAa,aAAa,MAAM,KAAK,UAAU,eAAe,IAAI,CAAC;AACxE,KAAK,aAAa,iBAAiB,MAAM;AACvC,MAAI,sBAAsB,CAAC,GAAG;AAC5B,WAAO;AAAA,EACT,WAAW,sBAAsB,CAAC,GAAG;AACnC,WAAO;AAAA,EACT;AACA,SAAO;AACT,CAAC;AACD,KAAK,aAAa,kCAAkC,MAAM,KAAK;AAC/D,KAAK,aAAa,0BAA0B,MAAM,KAAK,IAAI,eAAe,MAAM,CAAC;AACjF,KAAK,aAAa,qBAAqB,MAAM,IAAI;AACjD,KAAK,aAAa,4BAA4B,MAAM,KAAK;AACzD,KAAK,aAAa,cAAc,MAAM,KAAK,QAAQ,WAAW,CAAC;AAC/D,KAAK,aAAa,4BAA4B,MAAM,KAAK,QAAQ,YAAY,CAAC;AAC9E,KAAK,aAAa,mBAAmB,MAAM,KAAK,QAAQ,YAAY,CAAC;AACrE,KAAK,aAAa,4BAA4B,MAAM,KAAK,QAAQ,YAAY,CAAC;AAC9E,KAAK,aAAa,gCAAgC,MAAM,KAAK,QAAQ,YAAY,CAAC;AAClF,KAAK,aAAa,+BAA+B,MAAM,KAAK,QAAQ,YAAY,CAAC;AACjF,KAAK,aAAa,+BAA+B,MAAM,KAAK,QAAQ,YAAY,CAAC;AACjF,KAAK,aAAa,+BAA+B,MAAM,KAAK,QAAQ,YAAY,CAAC;AACjF,KAAK,aAAa,qBAAqB,MAAM,KAAK,QAAQ,YAAY,CAAC;AACvE,KAAK,aAAa,uBAAuB,MAAM,KAAK,QAAQ,YAAY,CAAC;AACzE,KAAK,aAAa,qBAAqB,MAAM,KAAK,QAAQ,YAAY,CAAC;AACvE,KAAK,aAAa,0BAA0B,MAAM,uBAAuB,KAAK,UAAU,eAAe,CAAC,CAAC;AACzG,KAAK,aAAa,gCAAgC,MAAM,uBAAuB,KAAK,UAAU,eAAe,CAAC,CAAC;AAC/G,KAAK,aAAa,gDAAgD,MAAM;AACtE,QAAM,eAAe,KAAK,UAAU,eAAe;AACnD,MAAI,iBAAiB,GAAG;AACtB,WAAO;AAAA,EACT;AACA,SAAO,kCAAkC,YAAY;AACvD,CAAC;AACD,KAAK,aAAa,iDAAiD,MAAM,KAAK,UAAU,8CAA8C,IAAI,KAAK,CAAC,oBAAoB,SAAS,CAAC;AAC9K,KAAK,aAAa,gCAAgC,MAAM,mCAAmC,KAAK,UAAU,eAAe,CAAC,CAAC;AAC3H,KAAK,aAAa,gCAAgC,MAAM;AACtD,SAAO,KAAK,QAAQ,0BAA0B,IAAI,QAAQ,KAAK,QAAQ,8BAA8B;AACvG,CAAC;AACD,KAAK,aAAa,gCAAgC,MAAM,8BAA8B,KAAK,UAAU,eAAe,CAAC,CAAC;AACtH,KAAK,aAAa,2BAA2B,MAAM,oBAAoB,KAAK,UAAU,eAAe,CAAC,CAAC;AACvG,KAAK,aAAa,6BAA6B,MAAM;AACnD,QAAM,cAAc,KAAK,QAAQ,8BAA8B;AAC/D,SAAO,cAAc,IAAI;AAC3B,CAAC;AACD,KAAK,aAAa,kCAAkC,MAAM;AACxD,SAAO;AACT,GAAG,CAAC,eAAe;AACjB,MAAI,aAAa,KAAK,eAAe,IAAI;AACvC,UAAM,IAAI,MAAM,8FAA8F,aAAa;AAAA,EAC7H;AACF,CAAC;AACD,KAAK,aAAa,yBAAyB,MAAM;AAC/C,SAAO,oBAAoB,SAAS,IAAI,IAAI;AAC9C,GAAG,CAAC,eAAe;AACjB,MAAI,aAAa,KAAK,eAAe,IAAI;AACvC,UAAM,IAAI,MAAM,2FAA2F,aAAa;AAAA,EAC1H;AACF,CAAC;AACD,KAAK,aAAa,8BAA8B,MAAM,GAAG;AACzD,KAAK,aAAa,6BAA6B,MAAM,KAAK;AAC1D,KAAK,aAAa,4CAA4C,MAAM,GAAG;AACvE,KAAK,aAAa,gCAAgC,MAAM,GAAG;AAG3D,SAAS,qBAAqB;AAC5B,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,eAAW;AACX,gBAAY;AACZ,gBAAY;AACZ,gBAAY;AACZ,gBAAY;AACZ,aAAS;AACT,mBAAe;AACf,uBAAmB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAanB,uBAAmB;AACnB,kBAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAUhB,OAAO;AACL,eAAW;AACX,gBAAY;AACZ,gBAAY;AACZ,gBAAY;AACZ,gBAAY;AACZ,aAAS;AACT,mBAAe;AACf,uBAAmB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AASnB,uBAAmB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUnB,kBAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAShB;AACA,SAAO;AAAA,IACL,SAAS;AAAA,IACT;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AAGA,SAAS,mCAAmC,SAAS,OAAOS,SAAQ,SAAS;AAC3E,QAAMG,WAAU,aAAa,eAAe,KAAK;AACjD,SAAOA,SAAQ,IAAI,CAAC,QAAQ,OAAO;AACjC,UAAM,QAAQ,OAAO,QAAQ,SAASH,YAAW;AACjD,UAAM,QAAQ,OAAOG,SAAQ,SAAS,IAAI,OAAO,QAAQ,KAAK,QAAQH,YAAW,QAAQ,SAAS,WAAW,YAAY,QAAQ,SAAS;AAC1I,WAAO,GAAG,UAAU;AAAA,EACtB,CAAC,EAAE,KAAK,EAAE;AACZ;AACA,SAAS,kDAAkD,SAAS,OAAOA,SAAQ,SAAS;AAC1F,QAAMG,WAAU,aAAa,eAAe,KAAK;AACjD,SAAOA,SAAQ,IAAI,CAAC,GAAG,OAAO;AAC5B,UAAM,QAAQ,OAAO,QAAQ,SAASH,4BAA2B;AACjE,UAAM,QAAQ,OAAOG,SAAQ,SAAS,IAAI,OAAO,QAAQ,KAAK,QAAQH,YAAW,QAAQ,yBAAyB,QAAQ,YAAY,QAAQ,yBAAyB;AACvK,WAAO,GAAG,UAAU;AAAA,EACtB,CAAC,EAAE,KAAK,EAAE;AACZ;AACA,SAAS,2BAA2B,YAAY,cAAc;AAC5D,QAAM,YAAY,WAAW;AAC7B,QAAM,QAAQ,WAAW,IAAI,CAAC,MAAM,GAAG,gBAAgB,IAAI;AAC3D,QAAMG,WAAU,IAAI,MAAM,YAAY,CAAC;AACvC,EAAAA,SAAQ,YAAY,KAAK,MAAM,YAAY;AAC3C,WAAS,KAAK,YAAY,GAAG,MAAM,GAAG,EAAE,IAAI;AAC1C,IAAAA,SAAQ,MAAM,IAAIA,SAAQ,KAAK,QAAQ,MAAM,KAAK;AAAA,EACpD;AACA,SAAOA;AACT;AACA,SAAS,4CAA4C,SAAS,cAAcH,SAAQ,SAAS;AAC3F,QAAM,eAAe,QAAQ,IAAI,CAAC,GAAG,OAAO,EAAE;AAC9C,QAAMG,WAAU,2BAA2B,cAAc,YAAY;AACrE,SAAOA,SAAQ,IAAI,CAAC,GAAG,OAAO;AAC5B,UAAM,QAAQ,OAAO,QAAQ,SAASH,YAAWG,SAAQ;AACzD,UAAM,QAAQ,OAAOA,SAAQ,SAAS,IAAI,OAAO,QAAQ,KAAK,QAAQH,YAAW,QAAQ,SAASG,SAAQ,QAAQ,YAAY,QAAQ,SAASA,SAAQ;AACvJ,WAAO,GAAG,UAAU;AAAA,EACtB,CAAC,EAAE,KAAK,EAAE;AACZ;AACA,SAAS,mBAAmB,OAAO;AACjC,QAAMA,WAAU,aAAa,eAAe,KAAK,EAAE,IAAI,CAAC,MAAM,EAAE,SAAS,CAAC;AAC1E,SAAO;AAAA;AAAA,wBAEeA,SAAQ,mBAAmBA,SAAQ;AAAA;AAAA;AAG3D;AACA,SAAS,2BAA2B;AAClC,SAAO;AAAA;AAAA;AAAA;AAAA;AAKT;AACA,IAAI,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AA0C3B,IAAI,EAAE,kBAAkB,kBAAkB,IAAI;AAC9C,SAAS,WAAW,YAAY,aAAa,SAAS;AACpD,QAAM,iBAAiB,CAAC;AACxB,aAAW,QAAQ,CAAC,MAAM;AACxB,UAAMZ,QAAO,aAAa,cAAc,EAAE,UAAU,YAAY;AAChE,QAAI,EAAE,UAAU,WAAW;AACzB,qBAAe,KAAK,iBAAiB,EAAE,OAAOA,QAAO,IAAI,IAAIA,WAAU,KAAK;AAAA,IAC9E,OAAO;AACL,qBAAe,KAAK,qBAAqB,EAAE,OAAO;AAClD,qBAAe,KAAK,qBAAqB,EAAE,OAAO;AAAA,IACpD;AACA,QAAI,QAAQ,qBAAqB;AAC/B,YAAM,EAAE,aAAa,IAAI,wBAAwB,QAAQ,cAAc,EAAE,UAAU,cAAc,EAAE,UAAU,QAAQ;AACrH,cAAQ,aAAa;AAAA,aACd;AACH,yBAAe,KAAK,eAAe,EAAE,YAAY;AACjD;AAAA,aACG;AACH,yBAAe,KAAK,iBAAiB,EAAE,YAAY;AACnD;AAAA,aACG;AACH,yBAAe,KAAK,iBAAiB,EAAE,YAAY;AACnD;AAAA,aACG;AACH,yBAAe,KAAK,iBAAiB,EAAE,YAAY;AACnD;AAAA;AAEA;AAAA;AAEJ,qBAAe,KAAK,iBAAiB,EAAE,eAAe;AAAA,IACxD;AAAA,EACF,CAAC;AACD,MAAI,QAAQ,qBAAqB;AAC/B,YAAQ,YAAY,aAAa;AAAA,WAC1B;AACH,uBAAe,KAAK,uBAAuB;AAC3C;AAAA,WACG;AACH,uBAAe,KAAK,yBAAyB;AAC7C,uBAAe,KAAK,8BAA8B;AAClD;AAAA,WACG;AACH,uBAAe,KAAK,yBAAyB;AAC7C,uBAAe,KAAK,gCAAgC;AACpD;AAAA,WACG;AACH,uBAAe,KAAK,yBAAyB;AAC7C,uBAAe,KAAK,gCAAgC;AACpD;AAAA;AAEA;AAAA;AAEJ,mBAAe,KAAK,4BAA4B;AAAA,EAClD;AACA,MAAI,QAAQ,gBAAgB;AAC1B,YAAQ,eAAe,QAAQ,CAAC,MAAM;AACpC,qBAAe,KAAK,WAAW,EAAE,QAAQ,EAAE,OAAO,EAAE,aAAa,IAAI,EAAE,gBAAgB,KAAK;AAAA,IAC9F,CAAC;AAAA,EACH;AACA,QAAM,qBAAqB,eAAe,KAAK,IAAI;AACnD,QAAM,uBAAuB,WAAW,IAAI,CAAC,MAAM,wBAAwB,GAAG,aAAa,QAAQ,cAAc,QAAQ,mBAAmB,CAAC,EAAE,KAAK,IAAI;AACxJ,QAAM,cAAc,YAAY;AAChC,QAAM,OAAO,mBAAmB;AAChC,QAAM,4BAA4B,6BAA6B,IAAI;AACnE,MAAI;AACJ,MAAI;AACJ,MAAI,eAAe,gBAAgB,IAAI;AACvC,MAAI,YAAY,UAAU;AACxB,4BAAwB,+BAA+B,YAAY,cAAc,aAAa,QAAQ,mBAAmB;AACzH,mCAA+B,8BAA8B,IAAI;AAAA,EACnE,OAAO;AACL,4BAAwB,yBAAyB,YAAY,cAAc,aAAa,QAAQ,mBAAmB;AACnH,mCAA+B,2BAA2B,IAAI;AAAA,EAChE;AACA,MAAI,QAAQ,cAAc;AACxB,oBAAgB;AAAA,EAClB;AACA,QAAM,SAAS;AAAA,IACb;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA,QAAQ;AAAA,EACV,EAAE,KAAK,IAAI;AACX,SAAO;AACT;AACA,SAAS,qBAAqB,QAAQ,sBAAsB,OAAO;AACjE,QAAM,QAAQ,OAAO,UAAU;AAC/B,UAAQ,MAAM;AAAA,SACP;AACH,aAAO,iBAAiB,QAAQ,mBAAmB;AAAA,SAChD;AACH,aAAO,aAAa,QAAQ,mBAAmB;AAAA,SAC5C;AACH,aAAO,aAAa,QAAQ,mBAAmB;AAAA,SAC5C;AACH,aAAO,aAAa,QAAQ,mBAAmB;AAAA,SAC5C;AACH,aAAO,aAAa,QAAQ,mBAAmB;AAAA,SAC5C;AACH,aAAO,aAAa,MAAM;AAAA,SACvB;AACH,aAAO,aAAa,MAAM;AAAA;AAE1B,YAAM,IAAI,MAAM,GAAG,MAAM,8CAA8C;AAAA;AAE7E;AACA,SAAS,2BAA2B,QAAQ,qBAAqB;AAC/D,QAAM,QAAQ,OAAO,UAAU;AAC/B,UAAQ,MAAM;AAAA,SACP;AACH,aAAO,uBAAuB,MAAM;AAAA,SACjC;AACH,aAAO,mBAAmB,QAAQ,mBAAmB;AAAA,SAClD;AACH,aAAO,mBAAmB,QAAQ,mBAAmB;AAAA,SAClD;AACH,aAAO,mBAAmB,QAAQ,mBAAmB;AAAA;AAErD,aAAO,mBAAmB,QAAQ,mBAAmB;AAAA;AAE3D;AACA,SAAS,wBAAwB,QAAQ,cAAc,qBAAqB,OAAO,qBAAqB;AACtG,MAAI,MAAM;AACV,MAAI,oBAAoB;AACtB,WAAO,2BAA2B,QAAQ,mBAAmB;AAAA,EAC/D,OAAO;AACL,WAAO,qBAAqB,QAAQ,mBAAmB;AAAA,EACzD;AACA,QAAM,UAAU,OAAO,UAAU;AACjC,QAAM,WAAW,aAAa;AAC9B,MAAI,QAAQ,UAAU,SAAS,QAAQ;AACrC,QAAI,oBAAoB;AACtB,aAAO,+BAA+B,QAAQ,YAAY;AAAA,IAC5D,OAAO;AACL,aAAO,yBAAyB,QAAQ,YAAY;AAAA,IACtD;AAAA,EACF;AACA,SAAO;AACT;AACA,SAAS,+BAA+B,UAAU,aAAa,qBAAqB;AAClF,UAAQ,SAAS;AAAA,SACV;AACH,aAAO,sBAAsB;AAAA,SAC1B;AACH,aAAO,wBAAwB,UAAU,aAAa,mBAAmB;AAAA,SACtE;AACH,aAAO,wBAAwB,UAAU,aAAa,mBAAmB;AAAA,SACtE;AACH,aAAO,wBAAwB,UAAU,aAAa,mBAAmB;AAAA;AAEzE,aAAO,wBAAwB,UAAU,aAAa,mBAAmB;AAAA;AAE/E;AACA,SAAS,yBAAyB,UAAU,aAAa,qBAAqB;AAC5E,UAAQ,SAAS;AAAA,SACV;AACH,aAAO,sBAAsB;AAAA,SAC1B;AACH,aAAO,kBAAkB,UAAU,aAAa,mBAAmB;AAAA,SAChE;AACH,aAAO,kBAAkB,UAAU,aAAa,mBAAmB;AAAA,SAChE;AACH,aAAO,kBAAkB,UAAU,aAAa,mBAAmB;AAAA,SAChE;AACH,aAAO,kBAAkB,UAAU,aAAa,mBAAmB;AAAA,SAChE;AACH,aAAO,kBAAkB,UAAU,WAAW;AAAA,SAC3C;AACH,aAAO,kBAAkB,UAAU,WAAW;AAAA;AAE9C,YAAM,IAAI,MAAM,GAAG,SAAS,+CAA+C;AAAA;AAEjF;AACA,SAAS,6BAA6B,MAAM;AAC1C,SAAO;AAAA;AAAA,eAEM,KAAK;AAAA;AAAA;AAGpB;AACA,SAAS,2BAA2B,MAAM;AACxC,SAAO;AAAA;AAAA,QAED,KAAK;AAAA;AAAA;AAGb;AACA,SAAS,8BAA8B,MAAM;AAC3C,SAAO;AAAA;AAAA,QAED,KAAK;AAAA;AAAA;AAGb;AACA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,gBAAgB,GAAG,KAAK;AAAA;AAAA;AAAA;AAAA,MAI1B,KAAK;AAAA,MACL,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,MAuBL,KAAK;AAAA,MACL,KAAK;AAAA,MACL,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,MAyBL;AAAA,MACA;AAAA,MACA;AAAA;AAEJ,SAAO;AACT;AACA,IAAI,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAaxB,IAAI,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AASxB,IAAI,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUxB,IAAI,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAY3B,SAAS,wBAAwB;AAC/B,SAAO;AAAA;AAAA;AAAA;AAAA;AAKT;AACA,SAAS,wBAAwB,OAAO,UAAU,qBAAqB;AACrE,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,MAAI,eAAe,OAAO,GAAG;AAC3B,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA,IAKT;AACA,WAAO;AAAA;AAAA,sCAE2B,eAAe;AAAA;AAAA;AAAA,EAGnD;AACA,MAAI,eAAe,OAAO,GAAG;AAC3B,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA,IAKT;AACA,WAAO;AAAA;AAAA,sCAE2B,eAAe;AAAA;AAAA;AAAA,EAGnD;AACA,MAAI,qBAAqB;AACvB,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAQT;AACA,SAAO;AAAA;AAAA;AAAA,oCAG2B,eAAe,OAAO,eAAe;AAAA,iCACxC,eAAe;AAAA;AAAA;AAGhD;AACA,SAAS,kBAAkB,OAAO,UAAU,qBAAqB;AAC/D,MAAI,SAAS,OAAO,GAAG;AACrB,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA,IAKT;AACA,WAAO;AAAA;AAAA,kCAEuB,SAAS;AAAA;AAAA;AAAA,EAGzC;AACA,MAAI,SAAS,OAAO,GAAG;AACrB,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA,IAKT;AACA,WAAO;AAAA;AAAA,kCAEuB,SAAS;AAAA;AAAA;AAAA,EAGzC;AACA,MAAI,qBAAqB;AACvB,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAOT;AACA,SAAO;AAAA;AAAA;AAAA,oCAG2B,SAAS,OAAO,SAAS;AAAA,4BACjC,SAAS;AAAA;AAAA;AAGrC;AACA,SAAS,wBAAwB,OAAO,UAAU,qBAAqB;AACrE,MAAI,qBAAqB;AACvB,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAkBT;AACA,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,QAAM,qBAAqB,KAAK,KAAK,MAAM,KAAK,CAAC;AACjD,QAAM,gBAAgB,qBAAqB,KAAK,KAAK,MAAM,KAAK,CAAC;AACjE,SAAO;AAAA;AAAA;AAAA,oCAG2B,eAAe,OAAO,eAAe;AAAA,iCACxC,eAAe;AAAA;AAAA,wBAExB;AAAA,qBACH;AAAA;AAAA,6BAEQ;AAAA,4BACD;AAAA;AAAA;AAAA;AAAA;AAK5B;AACA,SAAS,kBAAkB,OAAO,UAAU,qBAAqB;AAC/D,MAAI,qBAAqB;AACvB,UAAM,0BAA0B,kDAAkD,CAAC,KAAK,KAAK,GAAG,GAAG,KAAK;AACxG,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA,MAKL;AAAA;AAAA;AAAA;AAAA,EAIJ;AACA,QAAM,yBAAyB,mCAAmC,CAAC,KAAK,KAAK,GAAG,GAAG,KAAK;AACxF,SAAO;AAAA;AAAA;AAAA,oCAG2B,SAAS,OAAO,SAAS;AAAA,iCAC5B,SAAS;AAAA,QAClC;AAAA;AAAA;AAAA;AAIR;AACA,SAAS,wBAAwB,OAAO,UAAU,qBAAqB;AACrE,MAAI,qBAAqB;AACvB,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAuBT;AACA,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,QAAM,qBAAqB,KAAK,KAAK,MAAM,MAAM,SAAS,KAAK,CAAC;AAChE,QAAM,gBAAgB,qBAAqB,KAAK,KAAK,MAAM,MAAM,SAAS,KAAK,CAAC;AAChF,MAAI,iBAAiB;AACrB,MAAI,UAAU;AACd,MAAI,UAAU;AACd,WAAS,IAAI,GAAG,IAAI,MAAM,SAAS,GAAG,KAAK;AACzC,sBAAkB,MAAM,MAAM,SAAS,IAAI;AAC3C,cAAU;AAAA,aACD,eAAe;AAAA,kBACV,OAAO;AAAA,QACjB;AACJ,cAAU,IAAI,QAAQ;AAAA,EACxB;AACA,SAAO;AAAA,UACC,MAAM;AAAA;AAAA,oCAEoB,eAAe,OAAO,eAAe;AAAA,iCACxC,eAAe;AAAA;AAAA,QAExC;AAAA;AAAA,wBAEgB;AAAA,qBACH;AAAA;AAAA,6BAEQ;AAAA,4BACD;AAAA;AAAA,mBAET,MAAM,UAAU;AAAA;AAAA;AAGnC;AACA,SAAS,kBAAkB,OAAO,UAAU,qBAAqB;AAC/D,MAAI,qBAAqB;AACvB,UAAM,0BAA0B,kDAAkD,CAAC,KAAK,KAAK,KAAK,IAAI,GAAG,KAAK;AAC9G,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA,QAKH;AAAA;AAAA;AAAA;AAAA,EAIN;AACA,QAAM,yBAAyB,mCAAmC,CAAC,KAAK,KAAK,KAAK,IAAI,GAAG,KAAK;AAC9F,SAAO;AAAA;AAAA;AAAA,eAGM,SAAS,OAAO,SAAS;AAAA,iCACP,SAAS;AAAA,QAClC;AAAA;AAAA;AAAA;AAIR;AACA,SAAS,kBAAkB,OAAO,UAAU;AAC1C,QAAM,yBAAyB,mCAAmC,CAAC,KAAK,KAAK,KAAK,MAAM,IAAI,GAAG,KAAK;AACpG,SAAO;AAAA;AAAA,kDAEyC,SAAS;AAAA,+BAC5B,SAAS;AAAA;AAAA,iCAEP,SAAS;AAAA;AAAA,QAElC;AAAA;AAAA;AAAA;AAAA;AAAA;AAMR;AACA,SAAS,kBAAkB,OAAO,UAAU;AAC1C,QAAM,yBAAyB,mCAAmC,CAAC,KAAK,KAAK,KAAK,MAAM,MAAM,IAAI,GAAG,KAAK;AAC1G,SAAO;AAAA;AAAA;AAAA,eAGM,SAAS,OAAO,SAAS;AAAA,iCACP,SAAS;AAAA;AAAA,QAElC;AAAA;AAAA;AAAA;AAAA;AAAA;AAMR;AACA,SAAS,wBAAwB,OAAO,UAAU,qBAAqB;AACrE,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,MAAI,aAAa,YAAY,OAAO,QAAQ,GAAG;AAC7C,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAMT;AACA,WAAO;AAAA;AAAA,8CAEmC,eAAe,OAAO,eAAe;AAAA;AAAA;AAAA,EAGjF;AACA,QAAM,qBAAqB,KAAK,KAAK,MAAM,KAAK,CAAC;AACjD,MAAI,qBAAqB;AACvB,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAcT;AACA,SAAO;AAAA;AAAA;AAAA,oCAG2B,eAAe,OAAO,eAAe;AAAA;AAAA,iCAExC,eAAe;AAAA,6BACnB;AAAA,4BACD;AAAA;AAAA;AAAA;AAAA;AAK5B;AACA,SAAS,kBAAkB,OAAO,UAAU,qBAAqB;AAC/D,MAAI,aAAa,YAAY,OAAO,QAAQ,GAAG;AAC7C,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA,IAKT;AACA,WAAO;AAAA;AAAA,0CAE+B,SAAS,OAAO,SAAS;AAAA;AAAA;AAAA,EAGjE;AACA,MAAI,MAAM,OAAO,GAAG;AAClB,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAQT;AACA,WAAO;AAAA;AAAA;AAAA,sCAG2B,SAAS,OAAO,SAAS;AAAA,mCAC5B,SAAS;AAAA;AAAA;AAAA;AAAA,EAI1C;AACA,MAAI,MAAM,OAAO,GAAG;AAClB,QAAI,qBAAqB;AACvB,aAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAQT;AACA,WAAO;AAAA;AAAA;AAAA,sCAG2B,SAAS,OAAO,SAAS;AAAA,mCAC5B,SAAS;AAAA;AAAA;AAAA;AAAA,EAI1C;AACA,MAAI,qBAAqB;AACvB,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAUT;AACA,SAAO;AAAA;AAAA;AAAA,oCAG2B,SAAS,OAAO,SAAS;AAAA,iCAC5B,SAAS;AAAA,wBAClB,MAAM;AAAA,4BACF,MAAM;AAAA;AAAA;AAAA;AAIlC;AACA,SAAS,yBAAyB,SAAS;AACzC,SAAO,SAAS;AAClB;AACA,SAAS,uBAAuB,WAAW;AACzC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,OAAO,mBAAmB;AAChC,SAAO;AAAA,WACE;AAAA,eACI,KAAK,aAAa;AAAA;AAAA;AAGjC;AACA,SAAS,iBAAiB,WAAW,qBAAqB;AACxD,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,MAAI,UAAU,UAAU,WAAW;AACjC,WAAO,SAAS,sBAAsB;AAAA,EACxC;AACA,QAAM,CAAC,SAAS,OAAO,IAAI,UAAU,UAAU;AAC/C,MAAI,YAAY,KAAK,YAAY,GAAG;AAClC,WAAO;AAAA,cACG;AAAA,+BACiB;AAAA;AAAA;AAAA,EAG7B;AACA,QAAM,SAAS,yBAAyB,OAAO;AAC/C,MAAI,qBAAqB;AACvB,WAAO;AAAA,YACC;AAAA,6BACiB,uBAAuB,uBAAuB;AAAA,6BAC9C;AAAA;AAAA;AAAA,EAG3B;AACA,QAAM,CAAC,OAAO,KAAK,IAAI,UAAU,UAAU;AAC3C,SAAO;AAAA,YACG;AAAA,6BACiB,UAAU,UAAU;AAAA,6BACpB;AAAA;AAAA;AAG7B;AACA,SAAS,mBAAmB,WAAW,qBAAqB;AAC1D,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,OAAO,mBAAmB;AAChC,MAAI,qBAAqB;AACvB,WAAO;AAAA,WACA;AAAA,gDACqC,0CAA0C;AAAA;AAAA;AAAA,eAG3E,KAAK,aAAa;AAAA;AAAA;AAAA,EAG/B;AACA,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,SAAO;AAAA,WACE;AAAA;AAAA,UAED,eAAe,OAAO,eAAe;AAAA,eAChC,KAAK,aAAa;AAAA;AAAA;AAGjC;AACA,SAAS,aAAa,WAAW,qBAAqB;AACpD,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,MAAI,UAAU,UAAU,WAAW;AACjC,WAAO;AAAA,cACG;AAAA,UACJ,kBAAkB,SAAS;AAAA;AAAA;AAAA,EAGnC;AACA,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,QAAQ,SAAS;AACvB,QAAM,QAAQ,SAAS;AACvB,MAAI,UAAU,KAAK,UAAU,GAAG;AAC9B,WAAO;AAAA,cACG;AAAA,+BACiB;AAAA;AAAA;AAAA,EAG7B;AACA,QAAM,SAAS,yBAAyB,OAAO;AAC/C,MAAI,UAAU,GAAG;AACf,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,6CAC+B,0BAA0B;AAAA,+BACxC;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,cACG;AAAA,6CAC+B,oBAAoB;AAAA,+BAClC;AAAA;AAAA;AAAA,EAG7B;AACA,MAAI,UAAU,GAAG;AACf,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,wCAC0B,0BAA0B;AAAA,+BACnC;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,cACG;AAAA,wCAC0B,oBAAoB;AAAA,+BAC7B;AAAA;AAAA;AAAA,EAG7B;AACA,MAAI,qBAAqB;AACvB,WAAO;AAAA,YACC;AAAA,6BACiB,uBAAuB,+BAA+B;AAAA,6BACtD;AAAA;AAAA;AAAA,EAG3B;AACA,SAAO;AAAA,YACG;AAAA,6BACiB,UAAU,kBAAkB;AAAA,6BAC5B;AAAA;AAAA;AAG7B;AACA,SAAS,mBAAmB,WAAW,qBAAqB;AAC1D,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,UAAU,SAAS;AACzB,QAAM,UAAU,SAAS;AACzB,QAAM,OAAO,mBAAmB;AAChC,MAAI,YAAY,QAAQ,aAAa,YAAY,OAAO,QAAQ,GAAG;AACjE,QAAI,qBAAqB;AACvB,aAAO;AAAA,aACA;AAAA,qDACwC,uBAAuB;AAAA;AAAA,iBAE3D,KAAK,aAAa;AAAA;AAAA;AAAA,IAG/B;AACA,WAAO;AAAA,aACE;AAAA,qDACwC,cAAc;AAAA;AAAA,iBAElD,KAAK,aAAa;AAAA;AAAA;AAAA,EAGjC;AACA,MAAI,qBAAqB;AACvB,WAAO;AAAA,WACA;AAAA,gDACqC,0CAA0C;AAAA,0CAChD;AAAA;AAAA,eAE3B,KAAK,aAAa;AAAA;AAAA;AAAA,EAG/B;AACA,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,QAAM,eAAe,KAAK,KAAK,MAAM,KAAK,CAAC;AAC3C,SAAO;AAAA,WACE;AAAA,iCACsB,iBAAiB,eAAe,OAAO,eAAe;AAAA,eACxE,KAAK,aAAa;AAAA;AAAA;AAGjC;AACA,SAAS,aAAa,WAAW,qBAAqB;AACpD,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,WAAW,UAAU,UAAU;AACrC,MAAI,YAAY,QAAQ,aAAa,YAAY,OAAO,QAAQ,GAAG;AACjE,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,qDACuC,uBAAuB;AAAA,+BAC7C;AAAA;AAAA;AAAA,IAG3B;AACA,UAAM,WAAW,SAAS;AAC1B,UAAM,WAAW,SAAS;AAC1B,WAAO;AAAA,YACC;AAAA,mDACuC,eAAe;AAAA,6BACrC;AAAA;AAAA;AAAA,EAG3B;AACA,QAAM,EAAE,UAAU,SAAS,IAAI,aAAa,aAAa,KAAK;AAC9D,QAAM,gBAAgB;AACtB,MAAI,cAAc,SAAS,MAAM,QAAQ;AACvC,UAAM,eAAe,iBAAiB,WAAW,aAAa;AAC9D,UAAM,SAAS,CAAC,OAAO,KAAK;AAC5B,WAAO;AAAA,QACH,qBAAqB,cAAc,mBAAmB;AAAA,cAChD;AAAA,iBACG,YAAY,kBAAkB,QAAQ,QAAQ;AAAA;AAAA;AAAA,EAG7D;AACA,MAAI,UAAU,UAAU,WAAW;AACjC,WAAO;AAAA,cACG;AAAA,qDACuC,MAAM;AAAA,UACjD,kBAAkB,SAAS;AAAA;AAAA;AAAA,EAGnC;AACA,QAAM,UAAU,SAAS;AACzB,QAAM,UAAU,SAAS;AACzB,QAAM,SAAS,yBAAyB,OAAO;AAC/C,MAAI,YAAY,GAAG;AACjB,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,2CAC6B,iBAAiB;AAAA,oDACR;AAAA,+BACrB;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,YACC;AAAA,yCAC6B,iBAAiB,MAAM;AAAA,4CACpB;AAAA,6BACf;AAAA;AAAA;AAAA,EAG3B;AACA,MAAI,YAAY,GAAG;AACjB,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,2CAC6B,iBAAiB;AAAA,+CACb;AAAA,+BAChB;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,YACC;AAAA,yCAC6B,iBAAiB,MAAM;AAAA,uCACzB;AAAA,6BACV;AAAA;AAAA;AAAA,EAG3B;AACA,MAAI,qBAAqB;AACvB,WAAO;AAAA,cACG;AAAA;AAAA,4BAEc,2BAA2B;AAAA,+BACxB,uBAAuB;AAAA,+BACvB;AAAA;AAAA;AAAA,EAG7B;AACA,SAAO;AAAA,UACC;AAAA;AAAA,wBAEc,MAAM,cAAc;AAAA,2BACjB,YAAY;AAAA,2BACZ;AAAA;AAAA;AAG3B;AACA,SAAS,mBAAmB,WAAW,qBAAqB;AAC1D,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,MAAI,MAAM,OAAO,GAAG;AAClB,UAAM,gBAAgB,MAAM,MAAM,CAAC;AACnC,UAAM,WAAW,CAAC,GAAG,CAAC;AACtB,UAAM,eAAe,iBAAiB,WAAW,aAAa;AAC9D,UAAM,SAAS,CAAC,KAAK,OAAO,KAAK;AACjC,WAAO;AAAA,UACD,2BAA2B,cAAc,mBAAmB;AAAA,eACvD;AAAA,mBACI,YAAY,kBAAkB,QAAQ,QAAQ;AAAA;AAAA;AAAA,EAG/D;AACA,QAAM,OAAO,mBAAmB;AAChC,MAAI,qBAAqB;AACvB,WAAO;AAAA,WACA;AAAA,gDACqC,0CAA0C;AAAA,0CAChD;AAAA,0DACgB;AAAA;AAAA;AAAA,eAG3C,KAAK,aAAa;AAAA;AAAA;AAAA,EAG/B;AACA,QAAM,UAAU,eAAe;AAC/B,QAAM,UAAU,eAAe;AAC/B,QAAM,eAAe,KAAK,KAAK,MAAM,KAAK,CAAC;AAC3C,QAAM,gBAAgB,eAAe,KAAK,KAAK,MAAM,KAAK,CAAC;AAC3D,SAAO;AAAA,WACE;AAAA;AAAA,UAED,YAAY,YAAY,kBAAkB;AAAA,eACrC,KAAK,aAAa;AAAA;AAAA;AAGjC;AACA,SAAS,aAAa,WAAW,qBAAqB;AACpD,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,UAAU,MAAM,KAAK,MAAM;AACjC,QAAM,UAAU,MAAM;AACtB,QAAM,EAAE,UAAU,SAAS,IAAI,aAAa,aAAa,KAAK;AAC9D,QAAM,gBAAgB;AACtB,MAAI,cAAc,SAAS,MAAM,QAAQ;AACvC,UAAM,eAAe,iBAAiB,WAAW,aAAa;AAC9D,UAAM,SAAS,CAAC,OAAO,OAAO,OAAO;AACrC,WAAO;AAAA,UACD,qBAAqB,cAAc,mBAAmB;AAAA,gBAChD;AAAA,mBACG,YAAY,kBAAkB,QAAQ,QAAQ;AAAA;AAAA;AAAA,EAG/D;AACA,MAAI,UAAU,UAAU,WAAW;AACjC,WAAO;AAAA,cACG;AAAA;AAAA,iCAEmB,YAAY;AAAA,UACnC,kBAAkB,SAAS;AAAA;AAAA;AAAA,EAGnC;AACA,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,UAAU,SAAS;AACzB,QAAM,UAAU,SAAS;AACzB,QAAM,aAAa,UAAU,UAAU;AACvC,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,wBACU;AAAA;AAAA;AAAA;AAAA,0BAIE,uBAAuB;AAAA,+BAClB;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,gBACK;AAAA;AAAA,oDAEoC;AAAA;AAAA,4BAExB,cAAc;AAAA,iCACT;AAAA;AAAA;AAAA,EAG/B;AACA,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,gDACkC;AAAA;AAAA,uDAEO,uBAAuB;AAAA,+BAC/C;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,YACC;AAAA,8CACkC,MAAM;AAAA;AAAA,qDAEC,cAAc;AAAA,6BACtC;AAAA;AAAA;AAAA,EAG3B;AACA,QAAM,SAAS,yBAAyB,OAAO;AAC/C,MAAI,qBAAqB;AACvB,WAAO;AAAA,YACC;AAAA;AAAA,sBAEU,qBAAqB;AAAA,sBACrB;AAAA,0BACI,mBAAmB,qBAAqB;AAAA,6BACrC,uBAAuB;AAAA,6BACvB;AAAA;AAAA;AAAA,EAG3B;AACA,SAAO;AAAA,cACK;AAAA;AAAA,4BAEc,mBAAmB,qBAAqB;AAAA,+BACrC,YAAY;AAAA,+BACZ;AAAA;AAAA;AAG/B;AACA,SAAS,mBAAmB,WAAW,qBAAqB;AAC1D,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,OAAO,mBAAmB;AAChC,MAAI,qBAAqB;AACvB,WAAO;AAAA,WACA;AAAA,0CAC+B;AAAA,0DACgB;AAAA;AAAA,yBAEjC;AAAA;AAAA,gDAEuB,0CAA0C;AAAA;AAAA;AAAA,mGAGS,KAAK,aAAa;AAAA;AAAA;AAAA,EAGnH;AACA,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,OAAO,MAAM;AACnB,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,iBAAiB,CAAC,KAAK,KAAK,SAAS,KAAK,CAAC,GAAG,KAAK,KAAK,SAAS,KAAK,CAAC,CAAC;AAC9E,QAAM,UAAU,eAAe;AAC/B,QAAM,UAAU,eAAe;AAC/B,QAAM,eAAe,KAAK,KAAK,MAAM,OAAO,KAAK,CAAC;AAClD,MAAI,gBAAgB,eAAe,KAAK,KAAK,MAAM,OAAO,KAAK,CAAC;AAChE,MAAI,SAAS;AACb,MAAIS,SAAQ,OAAO,+BAA+B;AAClD,WAAS,IAAI,GAAG,IAAI,OAAO,GAAG,KAAK;AACjC,aAAS,QAAQ,QAAQ;AACzB,qBAAiB,MAAM,OAAO,IAAI;AAClC,IAAAA,SAAQ,IAAI,OAAO,qBAAqBA;AAAA,EAC1C;AACA,SAAO;AAAA,WACE,YAAY;AAAA,oBACHA;AAAA,2BACO;AAAA,kCACO;AAAA,qDACmB,YAAY;AAAA,eAClD,KAAK,aAAa;AAAA;AAAA;AAGjC;AACA,SAAS,aAAa,WAAW,qBAAqB;AACpD,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,UAAU,MAAM;AACtB,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,EAAE,UAAU,SAAS,IAAI,aAAa,aAAa,KAAK;AAC9D,MAAI,SAAS,SAAS,MAAM,QAAQ;AAClC,UAAM,eAAe,iBAAiB,WAAW,QAAQ;AACzD,UAAM,SAAS,CAAC,OAAO,OAAO,SAAS,QAAQ;AAC/C,WAAO;AAAA,QACH,qBAAqB,cAAc,mBAAmB;AAAA,cAChD;AAAA,iBACG,YAAY,kBAAkB,QAAQ,QAAQ;AAAA;AAAA;AAAA,EAG7D;AACA,MAAI,UAAU,UAAU,WAAW;AACjC,WAAO;AAAA,cACG;AAAA;AAAA,iCAEmB,YAAY,YAAY;AAAA,UAC/C,kBAAkB,SAAS;AAAA;AAAA;AAAA,EAGnC;AACA,QAAM,aAAa,UAAU,UAAU;AACvC,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,UAAU,SAAS;AACzB,QAAM,UAAU,SAAS;AACzB,QAAM,aAAa,iBAAiB;AACpC,QAAM,aAAa,iBAAiB;AACpC,QAAM,aAAa,iBAAiB;AACpC,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA,UACJ;AAAA,UACA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0BAMgB,uBAAuB;AAAA,+BAClB;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,cACG;AAAA;AAAA;AAAA;AAAA,uBAIS,YAAY;AAAA;AAAA,0BAET,cAAc;AAAA,+BACT;AAAA;AAAA;AAAA,EAG7B;AACA,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,QAAI,qBAAqB;AACvB,aAAO;AAAA,cACC;AAAA;AAAA,gCAEkB,qBAAqB,oBAAoB;AAAA;AAAA;AAAA,yBAGhD,uBAAuB;AAAA,+BACjB;AAAA;AAAA;AAAA,IAG3B;AACA,WAAO;AAAA,cACG;AAAA;AAAA,gCAEkB,MAAM,KAAK,MAAM,OAAO,MAAM;AAAA;AAAA;AAAA,yBAGrC,cAAc;AAAA,+BACR;AAAA;AAAA;AAAA,EAG7B;AACA,QAAM,SAAS,yBAAyB,OAAO;AAC/C,MAAI,qBAAqB;AACvB,WAAO;AAAA,YACC;AAAA;AAAA,QAEJ;AAAA,QACA;AAAA,QACA;AAAA;AAAA;AAAA,6BAGqB,uBAAuB,+BAA+B;AAAA,6BACtD;AAAA;AAAA;AAAA,EAG3B;AACA,SAAO;AAAA,YACG;AAAA;AAAA,0BAEc,mBAAmB;AAAA,oBACzB;AAAA,6BACS,YAAY,oBAAoB;AAAA,6BAChC;AAAA;AAAA;AAG7B;AACA,SAAS,aAAa,WAAW;AAC/B,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,UAAU,MAAM;AACtB,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,EAAE,UAAU,SAAS,IAAI,aAAa,aAAa,KAAK;AAC9D,MAAI,SAAS,SAAS,MAAM,QAAQ;AAClC,UAAM,eAAe,iBAAiB,WAAW,QAAQ;AACzD,UAAM,SAAS,CAAC,OAAO,OAAO,SAAS,UAAU,QAAQ;AACzD,WAAO;AAAA,QACH,qBAAqB,YAAY;AAAA,cAC3B;AAAA,iBACG,YAAY,kBAAkB,QAAQ,QAAQ;AAAA;AAAA;AAAA,EAG7D;AACA,MAAI,UAAU,UAAU,WAAW;AACjC,WAAO;AAAA,cACG;AAAA;AAAA;AAAA,iBAGG,YAAY,YAAY,YAAY;AAAA;AAAA,UAE3C,kBAAkB,SAAS;AAAA;AAAA;AAAA,EAGnC;AACA,QAAM,aAAa,UAAU,UAAU;AACvC,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,UAAU,SAAS;AACzB,QAAM,UAAU,SAAS;AACzB,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,WAAO;AAAA,cACG;AAAA;AAAA;AAAA,gCAGkB,YAAY,YAAY;AAAA;AAAA,0BAE9B,cAAc;AAAA,+BACT;AAAA;AAAA;AAAA,EAG7B;AACA,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,WAAO;AAAA,cACG;AAAA;AAAA;AAAA,iBAGG,MAAM,KAAK,MAAM,KAAK,MAAM;AAAA,iBAC5B,MAAM,KAAK,MAAM,OAAO,MAAM;AAAA;AAAA;AAAA,yBAGtB,cAAc;AAAA,+BACR;AAAA;AAAA;AAAA,EAG7B;AACA,QAAM,SAAS,yBAAyB,OAAO;AAC/C,SAAO;AAAA,YACG;AAAA;AAAA,0BAEc,mBAAmB,qBAAqB;AAAA,qBAC7C,sBAAsB;AAAA,6BACd,YAAY;AAAA,6BACZ;AAAA;AAAA;AAG7B;AACA,SAAS,aAAa,WAAW;AAC/B,QAAM,QAAQ,UAAU,UAAU;AAClC,QAAM,UAAU,UAAU;AAC1B,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,EAAE,UAAU,SAAS,IAAI,aAAa,aAAa,KAAK;AAC9D,MAAI,SAAS,SAAS,MAAM,QAAQ;AAClC,UAAM,eAAe,iBAAiB,WAAW,QAAQ;AACzD,UAAM,SAAS,CAAC,OAAO,OAAO,SAAS,UAAU,UAAU,QAAQ;AACnE,WAAO;AAAA,QACH,qBAAqB,YAAY;AAAA,cAC3B;AAAA;AAAA,iBAEG,YAAY,kBAAkB,QAAQ,QAAQ;AAAA;AAAA;AAAA,EAG7D;AACA,QAAM,UAAU,MAAM;AACtB,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,UAAU,MAAM,KAAK;AAC3B,QAAM,UAAU,MAAM,KAAK;AAC3B,MAAI,UAAU,UAAU,WAAW;AACjC,WAAO;AAAA,cACG;AAAA;AAAA;AAAA;AAAA,iBAIG,YAAY,YAAY,YAAY;AAAA;AAAA;AAAA,mBAGlC;AAAA,UACT,kBAAkB,SAAS;AAAA;AAAA;AAAA,EAGnC;AACA,QAAM,aAAa,UAAU,UAAU;AACvC,QAAM,WAAW,UAAU,UAAU;AACrC,QAAM,UAAU,SAAS;AACzB,QAAM,UAAU,SAAS;AACzB,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,WAAO;AAAA,cACG;AAAA;AAAA;AAAA;AAAA,iBAIG,YAAY,YAAY,YAAY;AAAA;AAAA;AAAA,0BAG3B,cAAc;AAAA,+BACT;AAAA;AAAA;AAAA,EAG7B;AACA,MAAI,YAAY,WAAW,cAAc,MAAM;AAC7C,WAAO;AAAA,cACG;AAAA;AAAA;AAAA,iBAGG,MAAM,KAAK,MAAM,KAAK,MAAM,KAAK,MAAM;AAAA,iBACvC,MAAM,KAAK,MAAM,KAAK,MAAM;AAAA,iBAC5B,MAAM,KAAK,MAAM;AAAA,iBACjB,MAAM;AAAA;AAAA;AAAA,yBAGE,cAAc;AAAA,+BACR;AAAA;AAAA;AAAA,EAG7B;AACA,QAAM,SAAS,yBAAyB,OAAO;AAC/C,SAAO;AAAA,YACG;AAAA;AAAA;AAAA,0BAGc,mBAAmB,qBAAqB;AAAA,qBAC7C,sBAAsB,sBAAsB;AAAA,6BACpC,YAAY;AAAA,6BACZ;AAAA;AAAA;AAG7B;AACA,SAAS,kBAAkB,WAAW;AACpC,QAAM,UAAU,UAAU;AAC1B,QAAM,SAAS,aAAa,cAAc,UAAU,UAAU,YAAY;AAC1E,MAAI,SAAS,GAAG;AACd,WAAO,UAAU;AAAA,EACnB;AACA,SAAO;AAAA,0BACiB;AAAA;AAAA,iBAET;AAAA;AAAA;AAAA;AAIjB;AACA,SAAS,+BAA+B,WAAW,cAAc;AAC/D,QAAM,UAAU,UAAU;AAC1B,QAAM,iBAAiB,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AACxE,QAAM,WAAW,QAAQ,iBAAiB;AAC1C,QAAM,SAAS,UAAU,UAAU,aAAa;AAChD,QAAM,UAAU,aAAa,aAAa;AAC1C,QAAM,gBAAgB,kBAAkB,UAAU,UAAU,cAAc,aAAa,YAAY;AACnG,QAAM,OAAO,kBAAkB,OAAO;AACtC,QAAM,WAAW,UAAU;AAC3B,MAAI;AACJ,QAAM,SAAS,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAC5C,MAAI,WAAW,GAAG;AAChB,oBAAgB;AAAA,EAClB,WAAW,UAAU,KAAK,cAAc,UAAU,GAAG;AACnD,oBAAgB;AAAA,EAClB,OAAO;AACL,oBAAgB,cAAc,IAAI,CAAC,MAAM,UAAU,OAAO,IAAI,gBAAgB,EAAE,KAAK,IAAI;AAAA,EAC3F;AACA,MAAI,wBAAwB;AAC5B,MAAI,UAAU,KAAK,SAAS,GAAG;AAC7B,4BAAwB;AAAA,EAC1B,OAAO;AACL,4BAAwB,UAAU,UAAU,aAAa,IAAI,CAAC,IAAI,OAAO,UAAU,OAAO,KAAK,WAAW,EAAE,KAAK,IAAI;AAAA,EACvH;AACA,MAAI,SAAS;AACb,QAAM,SAAS,aAAa,cAAc,UAAU,UAAU,YAAY;AAC1E,QAAM,gBAAgB,WAAW;AACjC,QAAM,UAAU,aAAa,cAAc,aAAa,YAAY;AACpE,QAAM,iBAAiB,YAAY;AACnC,MAAI,WAAW,KAAK,CAAC,iBAAiB,CAAC,gBAAgB;AACrD,aAAS;AAAA;AAAA;AAAA,EAGX,WAAW,iBAAiB,CAAC,gBAAgB;AAC3C,QAAI,YAAY,GAAG;AACjB,eAAS;AAAA;AAAA;AAAA,IAGX,OAAO;AACL,eAAS;AAAA;AAAA;AAAA,IAGX;AAAA,EACF,WAAW,cAAc,QAAQ;AAC/B,UAAM,OAAO,SAAS;AACtB,UAAM,OAAO,SAAS;AACtB,QAAI,cAAc,QAAQ,IAAI,IAAI,MAAM,cAAc,QAAQ,IAAI,IAAI,IAAI;AACxE,eAAS;AAAA,IACX,WAAW,cAAc,QAAQ,IAAI,IAAI,IAAI;AAC3C,eAAS;AAAA,IACX,WAAW,cAAc,QAAQ,IAAI,IAAI,IAAI;AAC3C,eAAS;AAAA,IACX;AAAA,EACF;AACA,SAAO;AAAA,WACE;AAAA,QACH;AAAA,QACA;AAAA,8BACsB,kBAAkB;AAAA,QACxC;AAAA;AAAA;AAGR;AACA,SAAS,yBAAyB,WAAW,cAAc;AACzD,QAAM,UAAU,UAAU;AAC1B,QAAM,iBAAiB,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AACxE,QAAM,WAAW,QAAQ,iBAAiB;AAC1C,QAAM,cAAc,aAAa;AACjC,QAAM,aAAa,UAAU,UAAU;AACvC,QAAM,SAAS,UAAU,UAAU,aAAa;AAChD,QAAM,UAAU,aAAa,aAAa;AAC1C,MAAI,CAAC,UAAU,UAAU,aAAa,WAAW,WAAW,UAAU,UAAU,cAAc,QAAQ,aAAa,YAAY,YAAY,WAAW,GAAG;AACvJ,WAAO;AAAA,cACG;AAAA,+BACiB;AAAA;AAAA;AAAA,EAG7B;AACA,QAAM,OAAO,kBAAkB,OAAO;AACtC,QAAM,gBAAgB,kBAAkB,UAAU,UAAU,cAAc,aAAa,YAAY;AACnG,QAAM,WAAW,UAAU;AAC3B,MAAI;AACJ,QAAM,SAAS,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAC5C,MAAI,WAAW,GAAG;AAChB,oBAAgB;AAAA,EAClB,WAAW,UAAU,KAAK,cAAc,UAAU,GAAG;AACnD,oBAAgB;AAAA,EAClB,OAAO;AACL,oBAAgB,cAAc,IAAI,CAAC,MAAM,UAAU,OAAO,IAAI,gBAAgB,EAAE,KAAK,IAAI;AAAA,EAC3F;AACA,MAAI,wBAAwB;AAC5B,MAAI,UAAU,KAAK,SAAS,GAAG;AAC7B,4BAAwB;AAAA,EAC1B,OAAO;AACL,4BAAwB,UAAU,UAAU,aAAa,IAAI,CAAC,IAAI,OAAO,UAAU,OAAO,KAAK,WAAW,EAAE,KAAK,IAAI;AAAA,EACvH;AACA,SAAO;AAAA,YACG;AAAA,QACJ;AAAA,QACA;AAAA,kBACU,kBAAkB;AAAA;AAAA;AAGpC;AACA,SAAS,kBAAkB,MAAM;AAC/B,MAAI,QAAQ,GAAG;AACb,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,OAAO;AACL,UAAM,MAAM,gBAAgB,2BAA2B;AAAA,EACzD;AACF;AACA,SAAS,wBAAwB,UAAU,OAAO,UAAU;AAC1D,QAAM,EAAE,UAAU,SAAS,IAAI,aAAa,aAAa,KAAK;AAC9D,QAAM,OAAO,MAAM;AACnB,QAAM,wBAAwB,YAAY,SAAS,KAAK,MAAM,OAAO;AACrE,QAAM,gBAAgB,wBAAwB,MAAM,MAAM,CAAC,IAAI;AAC/D,QAAM,kBAAkB,CAAC,YAAY,OAAO,KAAK,CAAC,aAAa,YAAY,OAAO,QAAQ,KAAK,SAAS,SAAS,QAAQ;AACzH,QAAM,eAAe,kBAAkB,gBAAgB;AACvD,SAAO,EAAE,iBAAiB,cAAc,SAAS;AACnD;AACA,SAAS,iBAAiB,QAAQ,eAAe;AAC/C,QAAM,eAAe,KAAK,MAAM,KAAK,UAAU,MAAM,CAAC;AACtD,eAAa,UAAU,eAAe;AACtC,SAAO;AACT;AACA,SAAS,kBAAkB,QAAQ,UAAU;AAC3C,SAAO,SAAS,IAAI,CAAC,MAAM,OAAO,EAAE,EAAE,KAAK,IAAI;AACjD;AAGA,SAAS,eAAe,OAAO,SAAS,QAAQ,QAAQ;AACtD,QAAM,aAAa,OAAO,IAAI,CAAC,QAAQ,OAAO;AAC5C,UAAM,YAAY;AAAA,MAChB,cAAc,OAAO;AAAA,MACrB,UAAU,OAAO,YAAY,OAAO,OAAO,QAAQ;AAAA,MACnD,WAAW,OAAO;AAAA,MAClB,UAAU,OAAO,YAAY,QAAQ,OAAO,QAAQ;AAAA,MACpD,YAAY;AAAA,IACd;AACA,QAAI,OAAO,WAAW,QAAQ,OAAO,QAAQ,SAAS,QAAQ,OAAO,QAAQ,MAAM,aAAa,GAAG;AACjG,gBAAU,aAAa,OAAO,QAAQ,MAAM;AAAA,IAC9C;AACA,WAAO,EAAE,MAAM,QAAQ,cAAc,KAAK,UAAU;AAAA,EACtD,CAAC;AACD,QAAM,eAAe,WAAW,IAAI,CAAC,MAAM,EAAE,SAAS;AACtD,QAAM,eAAe;AAAA,IACnB,cAAc,OAAO;AAAA,IACrB,UAAU,OAAO,QAAQ;AAAA,IACzB,WAAW;AAAA,IACX,UAAU,OAAO,QAAQ;AAAA,IACzB,YAAY;AAAA,EACd;AACA,QAAM,SAAS,WAAW,YAAY,cAAc,OAAO;AAC3D,QAAM,iBAAiB,qBAAqB,MAAM,IAAI,MAAM;AAC5D,QAAM,eAAe,MAAM,cAAc,cAAc;AACvD,MAAI,CAAC,IAAI,EAAE,IAAI,qBAAqB,GAAG;AACrC,WAAO,OAAO,OAAO;AAAA,MACnB;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF,GAAG,oBAAoB,OAAO,SAAS,YAAY,CAAC;AAAA,EACtD,OAAO;AACL,WAAO;AAAA,MACL;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA,kBAAkB;AAAA,MAClB,wBAAwB;AAAA,MACxB,QAAQ;AAAA,MACR,QAAQ;AAAA,MACR,mBAAmB;AAAA,MACnB,sBAAsB;AAAA,MACtB,kBAAkB;AAAA,MAClB,yBAAyB;AAAA,MACzB,qBAAqB;AAAA,IACvB;AAAA,EACF;AACF;AACA,SAAS,oBAAoB,OAAO,SAAS,cAAc;AACzD,QAAM,mBAAmB,CAAC;AAC1B,QAAM,oBAAoB,CAAC;AAC3B,QAAM,uBAAuB,CAAC;AAC9B,QAAM,yBAAyB,CAAC;AAChC,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI,SAAS;AACb,MAAI,SAAS;AACb,WAAS,MAAM,mBAAmB,cAAc,OAAO,KAAK;AAC5D,MAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,aAAS,MAAM,mBAAmB,cAAc,YAAY,KAAK;AAAA,EACnE;AACA,QAAM,cAAc;AACpB,WAAS,KAAK,GAAG,KAAK,QAAQ,cAAc,QAAQ,MAAM;AACxD,UAAM,UAAU,QAAQ,cAAc;AACtC,qBAAiB,WAAW,MAAM,mBAAmB,cAAc,SAAS,WAAW;AACvF,qBAAiB,SAAS,aAAa,MAAM,mBAAmB,cAAc,SAAS,WAAW,WAAW;AAC7G,QAAI,QAAQ,qBAAqB;AAC/B,wBAAkB,GAAG,kBAAkB,MAAM,mBAAmB,cAAc,GAAG,gBAAgB,WAAW;AAC5G,2BAAqB,GAAG,qBAAqB,MAAM,mBAAmB,cAAc,GAAG,mBAAmB,WAAW;AAAA,IACvH;AAAA,EACF;AACA,MAAI,QAAQ,qBAAqB;AAC/B,uBAAmB,MAAM,mBAAmB,cAAc,YAAY,WAAW;AACjF,8BAA0B,MAAM,mBAAmB,cAAc,mBAAmB,WAAW;AAC/F,0BAAsB,MAAM,mBAAmB,cAAc,eAAe,WAAW;AAAA,EACzF;AACA,MAAI,QAAQ,gBAAgB;AAC1B,YAAQ,eAAe,QAAQ,CAAC,GAAG,OAAO;AACxC,6BAAuB,MAAM,MAAM,mBAAmB,cAAc,EAAE,MAAM,WAAW;AAAA,IACzF,CAAC;AAAA,EACH;AACA,SAAO;AAAA,IACL;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACF;AACA,SAAS,yBAAyB,YAAY,QAAQ;AACpD,MAAI,WAAW,WAAW,OAAO,QAAQ;AACvC,UAAM,MAAM,4BAA4B,WAAW,wCAAwC,OAAO,eAAe;AAAA,EACnH;AACA,aAAW,QAAQ,CAAC,IAAI,OAAO;AAC7B,UAAM,SAAS,GAAG;AAClB,UAAM,SAAS,OAAO;AACtB,UAAM,SAAS,OAAO;AACtB,QAAI,CAAC,aAAa,YAAY,QAAQ,MAAM,GAAG;AAC7C,YAAM,MAAM,2EAA2E,cAAc,mBAAmB;AAAA,IAC1H;AACA,QAAI,GAAG,aAAa,OAAO,WAAW;AACpC;AAAA,IACF;AACA,UAAM,YAAY,GAAG;AACrB,UAAM,YAAY,OAAO,YAAY,OAAO,OAAO,QAAQ;AAC3D,QAAI,CAAC,aAAa,YAAY,WAAW,SAAS,GAAG;AACnD,YAAM,MAAM,kFAAkF,iBAAiB,sBAAsB;AAAA,IACvI;AAAA,EACF,CAAC;AACH;AACA,SAAS,WAAW,OAAO,QAAQ,QAAQ,QAAQ,qBAAqB;AACtE,MAAI,CAAC,OAAO,QAAQ,qBAAqB;AACvC,6BAAyB,OAAO,cAAc,MAAM;AACpD,6BAAyB,CAAC,OAAO,YAAY,GAAG,CAAC,MAAM,CAAC;AAAA,EAC1D;AACA,QAAM,SAAS,OAAO,QAAQ;AAC9B,QAAM,cAAc,OAAO,QAAQ;AACnC,MAAI,OAAO,QAAQ,UAAU;AAC3B,UAAM,6BAA6B,OAAO,SAAS,YAAY,IAAI,YAAY,EAAE;AAAA,EACnF,OAAO;AACL,UAAM,uBAAuB,OAAO,SAAS,YAAY,IAAI,YAAY,EAAE;AAAA,EAC7E;AACA,QAAM,WAAW,OAAO,YAAY;AACpC,MAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,QAAI,OAAO,WAAW,MAAM;AAC1B,YAAM,GAAG,UAAU,OAAO,QAAQ,QAAQ;AAAA,IAC5C;AAAA,EACF;AACA,MAAI,OAAO,WAAW,MAAM;AAC1B,UAAM,GAAG,UAAU,OAAO,QAAQ,GAAG;AAAA,EACvC;AACA,SAAO,QAAQ,CAAC,QAAQ,OAAO;AAC7B,UAAM,UAAU,OAAO,QAAQ,cAAc;AAC7C,UAAM,SAAS,OAAO,iBAAiB;AACvC,UAAM,eAAe,OAAO,iBAAiB,SAAS;AACtD,UAAM,cAAc,OAAO,kBAAkB,GAAG;AAChD,UAAM,iBAAiB,OAAO,qBAAqB,GAAG;AACtD,QAAI,aAAa;AACf,YAAM,EAAE,aAAa,IAAI,wBAAwB,OAAO,QAAQ,cAAc,OAAO,OAAO,OAAO,QAAQ,QAAQ;AACnH,cAAQ,aAAa;AAAA,aACd;AACH,gBAAM,GAAG,WAAW,aAAa,IAAI,WAAW,YAAY,CAAC;AAC7D;AAAA,aACG;AACH,gBAAM,GAAG,WAAW,aAAa,IAAI,WAAW,YAAY,CAAC;AAC7D;AAAA,aACG;AACH,gBAAM,GAAG,WAAW,aAAa,IAAI,WAAW,YAAY,CAAC;AAC7D;AAAA,aACG;AACH,gBAAM,GAAG,WAAW,aAAa,IAAI,WAAW,YAAY,CAAC;AAC7D;AAAA;AAEA;AAAA;AAAA,IAEN;AACA,QAAI,gBAAgB;AAClB,YAAM,GAAG,UAAU,gBAAgB,OAAO,QAAQ,SAAS,IAAI,OAAO,QAAQ,SAAS,EAAE;AAAA,IAC3F;AACA,QAAI,UAAU,MAAM;AAClB;AAAA,IACF;AACA,QAAI,OAAO,WAAW;AACpB,UAAI,aAAa,cAAc,OAAO,KAAK,IAAI,GAAG;AAChD,cAAM,GAAG,UAAU,QAAQ,OAAO,cAAc,EAAE;AAAA,MACpD,OAAO;AACL,YAAI,OAAO,OAAO;AAClB,YAAI,EAAE,gBAAgB,eAAe;AACnC,iBAAO,IAAI,aAAa,IAAI;AAAA,QAC9B;AACA,cAAM,GAAG,WAAW,QAAQ,IAAI;AAAA,MAClC;AACA;AAAA,IACF;AACA,QAAI,OAAO,QAAQ,SAAS,QAAQ,gBAAgB,MAAM;AACxD,YAAM,GAAG,UAAU,cAAc,OAAO,QAAQ,MAAM,UAAU;AAAA,IAClE;AACA,UAAM,sBAAsB,OAAO,QAAQ,QAAQ,SAAS,QAAQ,EAAE;AAAA,EACxE,CAAC;AACD,QAAM,cAAc,OAAO;AAC3B,MAAI,aAAa;AACf,YAAQ,OAAO,MAAM;AAAA,WACd;AACH,cAAM,GAAG,WAAW,aAAa,IAAI,WAAW,OAAO,KAAK,CAAC;AAC7D;AAAA,WACG;AACH,cAAM,GAAG,WAAW,aAAa,IAAI,WAAW,OAAO,KAAK,CAAC;AAC7D;AAAA,WACG;AACH,cAAM,GAAG,WAAW,aAAa,IAAI,WAAW,OAAO,KAAK,CAAC;AAC7D;AAAA,WACG;AACH,cAAM,GAAG,WAAW,aAAa,IAAI,WAAW,OAAO,KAAK,CAAC;AAC7D;AAAA;AAEA;AAAA;AAAA,EAEN;AACA,MAAI,OAAO,yBAAyB;AAClC,UAAMG,WAAU,aAAa,eAAe,OAAO,KAAK;AACxD,YAAQ,OAAO,MAAM;AAAA,WACd;AACH,cAAM,GAAG,WAAW,OAAO,yBAAyB,IAAI,WAAWA,QAAO,CAAC;AAC3E;AAAA,WACG;AACH,cAAM,GAAG,WAAW,OAAO,yBAAyB,IAAI,WAAWA,QAAO,CAAC;AAC3E;AAAA,WACG;AACH,cAAM,GAAG,WAAW,OAAO,yBAAyB,IAAI,WAAWA,QAAO,CAAC;AAC3E;AAAA;AAEA;AAAA;AAAA,EAEN;AACA,MAAI,OAAO,qBAAqB;AAC9B,UAAM,GAAG,UAAU,OAAO,qBAAqB,OAAO,QAAQ,SAAS,IAAI,OAAO,QAAQ,SAAS,EAAE;AAAA,EACvG;AACA,MAAI,OAAO,QAAQ,kBAAkB,qBAAqB;AACxD,WAAO,QAAQ,eAAe,QAAQ,CAAC,GAAG,OAAO;AAC/C,YAAM,YAAY,OAAO,uBAAuB;AAChD,YAAM,cAAc,oBAAoB;AACxC,UAAI,EAAE,SAAS,SAAS;AACtB,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,WAAW,EAAE,SAAS,QAAQ;AAC5B,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,WAAW,EAAE,SAAS,QAAQ;AAC5B,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,WAAW,EAAE,SAAS,QAAQ;AAC5B,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,WAAW,EAAE,SAAS,OAAO;AAC3B,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,WAAW,EAAE,SAAS,SAAS;AAC7B,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,WAAW,EAAE,SAAS,SAAS;AAC7B,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,WAAW,EAAE,SAAS,SAAS;AAC7B,cAAM,GAAG,WAAW,WAAW,WAAW;AAAA,MAC5C,OAAO;AACL,cAAM,MAAM,gBAAgB,EAAE,4BAA4B;AAAA,MAC5D;AAAA,IACF,CAAC;AAAA,EACH;AACA,QAAM,eAAe;AACvB;AACA,SAAS,cAAc,SAAS,QAAQ,QAAQ;AAC9C,MAAI,YAAY;AAChB,SAAO,OAAO,MAAM,EAAE,QAAQ,CAAC,MAAM;AACnC,UAAM,YAAY,EAAE,WAAW,QAAQ,EAAE,QAAQ,SAAS,QAAQ,EAAE,QAAQ,MAAM,aAAa;AAC/F,QAAI,QAAQ,uBAAuB,CAAC,EAAE,WAAW;AAC/C,YAAM,YAAY,EAAE,QAAQ;AAC5B,YAAM,EAAE,iBAAiB,cAAc,SAAS,IAAI,wBAAwB,QAAQ,cAAc,EAAE,OAAO,SAAS;AACpH,UAAI,QAAQ,IAAI,QAAQ,IAAI,SAAS;AACrC,UAAI,aAAa,WAAW,KAAK,QAAQ,cAAc;AACrD,cAAM,iBAAiB,CAAC,KAAK,KAAK,UAAU,KAAK,CAAC,GAAG,KAAK,KAAK,UAAU,KAAK,CAAC,CAAC;AAChF,gBAAQ,GAAG,eAAe,KAAK,KAAK,eAAe,KAAK;AAAA,MAC1D,WAAW,aAAa,WAAW,KAAK,CAAC,QAAQ,cAAc;AAC7D,gBAAQ,GAAG,aAAa,KAAK,KAAK,aAAa,KAAK;AAAA,MACtD,WAAW,aAAa,SAAS,KAAK,CAAC,QAAQ,cAAc;AAC3D,cAAMA,WAAU,aAAa,eAAe,YAAY;AACxD,iBAAS,GAAGA,SAAQ,OAAO,UAAU,MAAMA,SAAQA,SAAQ,SAAS,OAAO,UAAU;AAAA,MACvF;AACA,YAAM,QAAQ,EAAE,MAAM;AACtB,YAAM,6BAA6B,aAAa,WAAW,KAAK,aAAa,YAAY,EAAE,OAAO,SAAS;AAC3G,YAAM,WAAW,aAAa,cAAc,EAAE,KAAK,MAAM;AACzD,YAAM,gBAAgB,qBAAqB,iBAAiB,EAAE,OAAO,OAAO,KAAK;AACjF,YAAM,uBAAuB,CAAC,QAAQ,gBAAgB,UAAU,OAAO,MAAM,UAAU,aAAa,YAAY,WAAW,OAAO,QAAQ,QAAQ;AAClJ,YAAM,2BAA2B,QAAQ,gBAAgB,aAAa,SAAS,IAAI,KAAK,GAAG,UAAU,KAAK,KAAK,UAAU,KAAK;AAC9H,mBAAa,GAAG,SAAS,wBAAwB,kBAAkB,WAAW,MAAM,aAAa,UAAU,YAAY,iBAAiB,8BAA8B,SAAS,SAAS,UAAU,4BAA4B;AAAA,IAChO,OAAO;AACL,YAAM,WAAW,EAAE,YAAY,YAAY,EAAE,QAAQ;AACrD,mBAAa,GAAG,EAAE,SAAS,YAAY;AAAA,IACzC;AAAA,EACF,CAAC;AACD,QAAM,cAAc,QAAQ;AAC5B,MAAI,MAAM,QAAQ,YAAY;AAC9B,SAAO,MAAM,YAAY,MAAM,cAAc,GAAG,IAAI,EAAE,UAAU,eAAe;AAC/E,SAAO;AACT;AACA,SAAS,iBAAiB,MAAM;AAC9B,SAAO,IAAI,EAAE,QAAQ,2BAA2B,KAAK,QAAQ;AAC/D;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,mBAAmB,cAAc;AACtC,SAAK,iBAAiB,CAAC,EAAE,MAAM,YAAY,MAAM,QAAQ,CAAC;AAC1D,UAAM,OAAO,mBAAmB;AAChC,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,SAAK,WAAW;AAAA;AAAA,UAEV,KAAK,sBAAsB,kDAAkD,CAAC,KAAK,KAAK,GAAG,GAAG,WAAW,IAAI,mCAAmC,CAAC,KAAK,KAAK,GAAG,GAAG,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAgB5K,KAAK;AAAA;AAAA;AAAA,EAGb;AACF;AAGA,IAAI,4BAA4B,MAAM;AAAA,EACpC,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,mBAAmB,cAAc;AACtC,SAAK,iBAAiB,CAAC,EAAE,MAAM,YAAY,MAAM,QAAQ,CAAC;AAC1D,UAAM,OAAO,mBAAmB;AAChC,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,SAAK,WAAW;AAAA;AAAA,UAEV,KAAK,sBAAsB,kDAAkD,CAAC,KAAK,KAAK,GAAG,GAAG,WAAW,IAAI,mCAAmC,CAAC,KAAK,KAAK,GAAG,GAAG,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAgB5K,KAAK;AAAA;AAAA;AAAA,EAGb;AACF;AAGA,IAAI,qBAAqB,MAAM;AAAA,EAC7B,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,aAAa;AAChC,UAAM,OAAO,mBAAmB;AAChC,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA,QACZ;AAAA;AAAA;AAAA;AAAA,UAIE,KAAK;AAAA;AAAA;AAAA,EAGb;AACF;AAGA,IAAI,2BAA2B,MAAM;AAAA,EACnC,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc,aAAa;AAChC,UAAM,OAAO,mBAAmB;AAChC,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA,QACZ;AAAA;AAAA;AAAA;AAAA;AAAA,UAKE,KAAK;AAAA;AAAA;AAAA,EAGb;AACF;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,aAAa,sBAAsB,OAAO;AACpD,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,iBAAiB,CAAC,EAAE,MAAM,YAAY,MAAM,QAAQ,CAAC;AAC1D,UAAM,OAAO,mBAAmB;AAChC,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,QAAI,SAAS;AACb,QAAI,qBAAqB;AACvB,eAAS;AAAA,IACX;AACA,SAAK,WAAW;AAAA,QACZ,KAAK,sBAAsB,yBAAyB,IAAI,mBAAmB,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,wBAatE,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAcnB,KAAK,iBAAiB;AAAA;AAAA;AAAA,EAG9B;AACF;AAGA,IAAI,4BAA4B,MAAM;AAAA,EACpC,YAAY,aAAa,sBAAsB,OAAO;AACpD,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,iBAAiB,CAAC,EAAE,MAAM,YAAY,MAAM,QAAQ,CAAC;AAC1D,UAAM,OAAO,mBAAmB;AAChC,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,QAAI,WAAW;AACf,QAAI,SAAS;AACb,QAAI,qBAAqB;AACvB,eAAS;AAAA,IACX;AACA,aAAS,MAAM,GAAG,OAAO,GAAG,OAAO;AACjC,eAAS,MAAM,GAAG,OAAO,GAAG,OAAO;AACjC,cAAM,UAAU,MAAM,IAAI;AAC1B,oBAAY;AAAA;AAAA,gCAEY,SAAS,KAAK,sBAAsB,gBAAgB,GAAG,YAAY;AAAA,8BACrE;AAAA,iCACG,SAAS,KAAK,sBAAsB,gBAAgB,GAAG,YAAY;AAAA,gCACpE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,uBAUT,KAAK;AAAA;AAAA;AAAA,uBAGL;AAAA;AAAA,uBAEA;AAAA;AAAA,uBAEA;AAAA;AAAA,uBAEA;AAAA;AAAA;AAAA;AAAA;AAAA,MAKjB;AAAA,IACF;AACA,SAAK,WAAW;AAAA,UACV,KAAK,sBAAsB,yBAAyB,IAAI,mBAAmB,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAWpF;AAAA;AAAA,YAEA,KAAK,YAAY;AAAA;AAAA;AAAA,EAG3B;AACF;AAGA,IAAI,qBAAqB,CAAC;AAC1Bf,UAAS,oBAAoB;AAAA,EAC3B,mCAAmC,MAAM;AAAA,EACzC,+BAA+B,MAAM;AAAA,EACrC,4BAA4B,MAAM;AAAA,EAClC,kCAAkC,MAAM;AAAA,EACxC,4BAA4B,MAAM;AAAA,EAClC,mBAAmB,MAAM;AAAA,EACzB,2BAA2B,MAAM;AAAA,EACjC,kCAAkC,MAAM;AAAA,EACxC,oBAAoB,MAAM;AAAA,EAC1B,oBAAoB,MAAM;AAAA,EAC1B,iDAAiD,MAAM;AAAA,EACvD,iCAAiC,MAAM;AAAA,EACvC,uCAAuC,MAAM;AAAA,EAC7C,gCAAgC,MAAM;AAAA,EACtC,0CAA0C,MAAM;AAAA,EAChD,gDAAgD,MAAM;AAAA,EACtD,0CAA0C,MAAM;AAAA,EAChD,yCAAyC,MAAM;AAAA,EAC/C,gDAAgD,MAAM;AAAA,EACtD,4BAA4B,MAAM;AAAA,EAClC,0BAA0B,MAAM;AAClC,CAAC;AACD,SAAS,oBAAoB,IAAI;AAC/B,QAAM,OAAO,mBAAmB;AAChC,QAAM,qBAAqB,GAAG,KAAK;AAAA;AAAA,MAE/B,KAAK;AAAA,MACL,KAAK;AAAA,MACL,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAMT,SAAO,mBAAmB,IAAI,kBAAkB;AAClD;AACA,SAAS,mBAAmB,IAAI;AAC9B,QAAM,cAAc,IAAI,aAAa,CAAC,IAAI,GAAG,GAAG,GAAG,GAAG,IAAI,IAAI,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,IAAI,GAAG,GAAG,CAAC,CAAC;AACrG,SAAO,yBAAyB,IAAI,WAAW;AACjD;AACA,SAAS,kBAAkB,IAAI;AAC7B,QAAM,wBAAwB,IAAI,YAAY,CAAC,GAAG,GAAG,GAAG,GAAG,GAAG,CAAC,CAAC;AAChE,SAAO,wBAAwB,IAAI,qBAAqB;AAC1D;AACA,SAAS,0BAA0B,IAAI,OAAO,QAAQ,gBAAgB,eAAe,aAAa;AAChG,sBAAoB,OAAO,MAAM;AACjC,QAAM,UAAU,cAAc,EAAE;AAChC,QAAM,QAAQ,GAAG;AACjB,eAAa,IAAI,MAAM,GAAG,YAAY,OAAO,OAAO,CAAC;AACrD,eAAa,IAAI,MAAM,GAAG,cAAc,OAAO,GAAG,gBAAgB,GAAG,aAAa,CAAC;AACnF,eAAa,IAAI,MAAM,GAAG,cAAc,OAAO,GAAG,gBAAgB,GAAG,aAAa,CAAC;AACnF,eAAa,IAAI,MAAM,GAAG,cAAc,OAAO,GAAG,oBAAoB,GAAG,OAAO,CAAC;AACjF,eAAa,IAAI,MAAM,GAAG,cAAc,OAAO,GAAG,oBAAoB,GAAG,OAAO,CAAC;AACjF,MAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,iBAAa,IAAI,MAAM,GAAG,WAAW,OAAO,GAAG,gBAAgB,OAAO,QAAQ,GAAG,eAAe,aAAa,IAAI,CAAC;AAAA,EACpH,OAAO;AACL,iBAAa,IAAI,MAAM,GAAG,aAAa,OAAO,GAAG,gBAAgB,OAAO,MAAM,CAAC;AAAA,EACjF;AACA,eAAa,IAAI,MAAM,GAAG,YAAY,GAAG,YAAY,IAAI,CAAC;AAC1D,SAAO,EAAE,SAAS,UAAU,CAAC,QAAQ,KAAK,EAAE;AAC9C;AACA,SAAS,yCAAyC,eAAe;AAC/D,SAAO,cAAc;AACvB;AACA,SAAS,2BAA2B,IAAI,MAAM,SAAS,eAAe;AACpE,QAAM,CAAC,OAAO,MAAM,IAAI,yCAAyC,MAAM,OAAO;AAC9E,SAAO,0BAA0B,IAAI,OAAO,QAAQ,yCAAyC,aAAa,GAAG,cAAc,oBAAoB,GAAG,KAAK;AACzJ;AACA,SAAS,yCAAyC,eAAe;AAC/D,SAAO,cAAc;AACvB;AACA,SAAS,2BAA2B,IAAI,MAAM,SAAS,eAAe;AACpE,QAAM,CAAC,OAAO,MAAM,IAAI,yCAAyC,MAAM,OAAO;AAC9E,SAAO,0BAA0B,IAAI,OAAO,QAAQ,yCAAyC,aAAa,GAAG,cAAc,oBAAoB,cAAc,oBAAoB;AACnL;AACA,SAAS,+CAA+C,eAAe;AACrE,SAAO,cAAc;AACvB;AACA,SAAS,iCAAiC,IAAI,MAAM,SAAS,eAAe;AAC1E,QAAM,CAAC,OAAO,MAAM,IAAI,yCAAyC,MAAM,OAAO;AAC9E,SAAO,0BAA0B,IAAI,OAAO,QAAQ,+CAA+C,aAAa,GAAG,GAAG,MAAM,GAAG,aAAa;AAC9I;AACA,SAAS,wCAAwC,eAAe;AAC9D,SAAO,cAAc;AACvB;AACA,SAAS,0BAA0B,IAAI,MAAM,SAAS,eAAe;AACnE,QAAM,CAAC,OAAO,MAAM,IAAI,uCAAuC,MAAM,OAAO;AAC5E,SAAO,0BAA0B,IAAI,OAAO,QAAQ,wCAAwC,aAAa,GAAG,GAAG,MAAM,GAAG,KAAK;AAC/H;AACA,SAAS,+CAA+C,eAAe;AACrE,SAAO,cAAc;AACvB;AACA,SAAS,iCAAiC,IAAI,MAAM,SAAS,eAAe;AAC1E,QAAM,CAAC,OAAO,MAAM,IAAI,uCAAuC,MAAM,OAAO;AAC5E,SAAO,0BAA0B,IAAI,OAAO,QAAQ,+CAA+C,aAAa,GAAG,GAAG,MAAM,cAAc,oBAAoB;AAChK;AACA,SAAS,kCAAkC,IAAI,SAAS,cAAc;AACpE,QAAM,YAAY;AAClB,QAAM,WAAW,IAAI;AACrB,QAAM,SAAS,IAAI,IAAI,IAAI;AAC3B,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,cAAc,YAAY,CAAC;AACnE,QAAM,UAAU,mCAAmC,IAAI,SAAS,gBAAgB,cAAc,GAAG,QAAQ,SAAS;AAClH,SAAO,WAAW,mCAAmC,IAAI,SAAS,MAAM,cAAc,GAAG,QAAQ,QAAQ;AAC3G;AACA,SAAS,2BAA2B,IAAI,SAAS,OAAO,QAAQ,MAAM,eAAe;AACnF,eAAa,IAAI,MAAM,GAAG,YAAY,GAAG,YAAY,OAAO,CAAC;AAC7D,MAAI,eAAe,eAAe;AAClC,MAAI,gBAAgB,YAAY;AAC9B,oBAAgB,IAAI,WAAW,QAAQ,SAAS,CAAC;AACjD,oBAAgB,GAAG;AACnB,qBAAiB,GAAG;AAAA,EACtB,OAAO;AACL,oBAAgB,IAAI,aAAa,QAAQ,SAAS,CAAC;AACnD,oBAAgB,GAAG;AACnB,qBAAiB,cAAc;AAAA,EACjC;AACA,gBAAc,IAAI,IAAI;AACtB,MAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,iBAAa,IAAI,MAAM,GAAG,cAAc,GAAG,YAAY,GAAG,GAAG,GAAG,OAAO,QAAQ,GAAG,MAAM,eAAe,aAAa,CAAC;AAAA,EACvH,OAAO;AACL,iBAAa,IAAI,MAAM,GAAG,WAAW,GAAG,YAAY,GAAG,gBAAgB,OAAO,QAAQ,GAAG,GAAG,MAAM,eAAe,aAAa,CAAC;AAAA,EACjI;AACA,eAAa,IAAI,MAAM,GAAG,YAAY,GAAG,YAAY,IAAI,CAAC;AAC5D;AACA,SAAS,yBAAyB,IAAI,SAAS,QAAQ;AACrD,eAAa,IAAI,MAAM,GAAG,YAAY,GAAG,YAAY,OAAO,CAAC;AAC7D,MAAI,OAAO,gBAAgB,YAAY;AACrC,QAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,mBAAa,IAAI,MAAM,GAAG,cAAc,GAAG,YAAY,GAAG,GAAG,GAAG,OAAO,OAAO,OAAO,QAAQ,GAAG,MAAM,GAAG,eAAe,OAAO,IAAI,CAAC;AAAA,IACtI,OAAO;AACL,mBAAa,IAAI,MAAM,GAAG,WAAW,GAAG,YAAY,GAAG,GAAG,MAAM,OAAO,OAAO,OAAO,QAAQ,GAAG,GAAG,MAAM,GAAG,eAAe,OAAO,IAAI,CAAC;AAAA,IACzI;AAAA,EACF,OAAO;AACL,QAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,mBAAa,IAAI,MAAM,GAAG,cAAc,GAAG,YAAY,GAAG,GAAG,GAAG,GAAG,MAAM,GAAG,eAAe,MAAM,CAAC;AAAA,IACpG,OAAO;AACL,mBAAa,IAAI,MAAM,GAAG,WAAW,GAAG,YAAY,GAAG,GAAG,MAAM,GAAG,MAAM,GAAG,eAAe,MAAM,CAAC;AAAA,IACpG;AAAA,EACF;AACA,eAAa,IAAI,MAAM,GAAG,YAAY,GAAG,YAAY,IAAI,CAAC;AAC5D;AACA,SAAS,8BAA8B,KAAK,MAAM,SAAS,eAAe;AACxE,QAAM,UAAU,IAAI,aAAa;AACjC,eAAa,KAAK,MAAM,IAAI,WAAW,IAAI,mBAAmB,OAAO,CAAC;AACtE,QAAM,gBAAgB;AACtB,QAAM,iBAAiB;AACvB,QAAM,kBAAkB,gBAAgB,iBAAiB,OAAO;AAChE,eAAa,KAAK,MAAM,IAAI,WAAW,IAAI,mBAAmB,iBAAiB,IAAI,WAAW,CAAC;AAC/F,eAAa,KAAK,MAAM,IAAI,WAAW,GAAG,GAAG,SAAS,MAAM,IAAI,MAAM,IAAI,OAAO,CAAC,CAAC;AACnF,eAAa,KAAK,MAAM,IAAI,WAAW,IAAI,mBAAmB,IAAI,CAAC;AACnE,SAAO;AACT;AACA,SAAS,gCAAgC,IAAI,SAASG,OAAM;AAC1D,QAAM,MAAM;AACZ,QAAM,iBAAiB,IAAI,aAAaA,KAAI;AAC5C,MAAI,WAAW,IAAI,mBAAmB,OAAO;AAC7C,MAAI,iBAAiB,IAAI,mBAAmB,GAAG,cAAc;AAC7D,MAAI,WAAW,IAAI,mBAAmB,IAAI;AAC1C,SAAO;AACT;AACA,SAAS,gDAAgD,IAAI,MAAM,SAAS,eAAe;AACzF,QAAM,CAAC,GAAG,CAAC,IAAI,yCAAyC,MAAM,OAAO;AACrE,QAAM,cAAc;AACpB,QAAM,iBAAiB,IAAI,WAAW,mCAAmC,OAAO,SAAS,WAAW,CAAC;AACrG,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,GAAG,GAAG,GAAG,cAAc,uBAAuB,GAAG,eAAe,cAAc,CAAC;AACvH,SAAO,IAAI,aAAa,eAAe,MAAM;AAC/C;AACA,SAAS,+BAA+B,IAAI,SAAS,OAAO,MAAM,MAAM,cAAc,cAAc,eAAe;AACjH,QAAM,MAAM;AACZ,QAAM,iBAAiB,IAAI,aAAa,sCAAsC,cAAc,YAAY,CAAC;AACzG,MAAI,WAAW,IAAI,mBAAmB,OAAO;AAC7C,MAAI,iBAAiB,IAAI,mBAAmB,GAAG,cAAc;AAC7D,MAAI,WAAW,IAAI,mBAAmB,IAAI;AAC1C,SAAO;AACT;AACA,SAAS,sCAAsC,IAAI,cAAc,cAAc;AAC7E,QAAM,aAAa,IAAI,aAAa,eAAe,eAAe,CAAC;AACnE,eAAa,IAAI,MAAM,GAAG,WAAW,GAAG,GAAG,cAAc,cAAc,GAAG,MAAM,GAAG,OAAO,UAAU,CAAC;AACrG,SAAO;AACT;AAGA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,IAAI;AACd,SAAK,gBAAgB;AACrB,SAAK,UAAU;AACf,SAAK,WAAW;AAChB,SAAK,sBAAsB;AAC3B,SAAK,cAAc,CAAC;AACpB,UAAM,YAAY,IAAI,EAAE,UAAU,eAAe;AACjD,QAAI,MAAM,MAAM;AACd,WAAK,KAAK;AACV,sBAAgB,WAAW,EAAE;AAAA,IAC/B,OAAO;AACL,WAAK,KAAK,gBAAgB,SAAS;AAAA,IACrC;AACA,QAAI,qBAAqB;AACzB,UAAM,0BAA0B;AAChC,SAAK,+BAA+B,KAAK,GAAG,aAAa,6BAA6B;AACtF,QAAI,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC1C,YAAM,gBAAgB;AACtB,YAAM,qBAAqB;AAC3B,WAAK,wBAAwB,oBAAoB,KAAK,IAAI,aAAa;AACvE,UAAI,aAAa,KAAK,IAAI,kBAAkB,GAAG;AAC7C,aAAK,4BAA4B,oBAAoB,KAAK,IAAI,kBAAkB;AAAA,MAClF,WAAW,IAAI,EAAE,IAAI,0BAA0B,GAAG;AAChD,cAAM,IAAI,MAAM,oHAAoH;AAAA,MACtI;AACA,WAAK,4BAA4B,KAAK,GAAG,aAAa,kBAAkB;AACxE,UAAI,aAAa,KAAK,IAAI,uBAAuB,GAAG;AAClD,aAAK,gCAAgC,oBAAoB,KAAK,IAAI,uBAAuB;AAAA,MAC3F,WAAW,IAAI,EAAE,IAAI,0BAA0B,GAAG;AAChD,cAAM,IAAI,MAAM,6HAA6H;AAAA,MAC/I;AAAA,IACF,OAAO;AACL,2BAAqB;AACrB,UAAI,aAAa,KAAK,IAAI,kBAAkB,GAAG;AAC7C,aAAK,4BAA4B,KAAK,GAAG,aAAa,kBAAkB;AAAA,MAC1E,WAAW,aAAa,KAAK,IAAI,uBAAuB,GAAG;AACzD,aAAK,gCAAgC,KAAK,GAAG,aAAa,uBAAuB;AAAA,MACnF,OAAO;AACL,cAAM,IAAI,MAAM,qDAAqD;AAAA,MACvE;AAAA,IACF;AACA,SAAK,eAAe,mBAAmB,KAAK,EAAE;AAC9C,SAAK,cAAc,kBAAkB,KAAK,EAAE;AAC5C,SAAK,cAAc,kBAAkB,KAAK,EAAE;AAC5C,SAAK,gBAAgB,iBAAiB,KAAK,IAAI,KAAK,yBAAyB;AAAA,EAC/E;AAAA,EACA,IAAI,QAAQ;AACV,WAAO,IAAI,EAAE,QAAQ,OAAO;AAAA,EAC9B;AAAA,EACA,UAAU;AACR,QAAI,KAAK,UAAU;AACjB;AAAA,IACF;AACA,QAAI,KAAK,WAAW,MAAM;AACxB,cAAQ,KAAK,sKAAsK;AAAA,IACrL;AACA,QAAI,KAAK,iBAAiB,MAAM;AAC9B,cAAQ,KAAK,oMAAoM;AAAA,IACnN;AACA,UAAM,KAAK,KAAK;AAChB,iBAAa,IAAI,MAAM,GAAG,OAAO,CAAC;AAClC,iBAAa,IAAI,MAAM,GAAG,gBAAgB,GAAG,aAAa,IAAI,CAAC;AAC/D,iBAAa,IAAI,MAAM,GAAG,kBAAkB,KAAK,WAAW,CAAC;AAC7D,iBAAa,IAAI,MAAM,GAAG,WAAW,GAAG,cAAc,IAAI,CAAC;AAC3D,iBAAa,IAAI,MAAM,GAAG,WAAW,GAAG,sBAAsB,IAAI,CAAC;AACnE,iBAAa,IAAI,MAAM,GAAG,aAAa,KAAK,WAAW,CAAC;AACxD,SAAK,WAAW;AAAA,EAClB;AAAA,EACA,2BAA2B,MAAM,SAAS;AACxC,SAAK,gBAAgB;AACrB,WAAO,2BAA2B,KAAK,IAAI,MAAM,SAAS,KAAK,aAAa;AAAA,EAC9E;AAAA,EACA,2BAA2B,MAAM,SAAS;AACxC,SAAK,gBAAgB;AACrB,WAAO,2BAA2B,KAAK,IAAI,MAAM,SAAS,KAAK,aAAa;AAAA,EAC9E;AAAA,EACA,iCAAiC,MAAM,SAAS;AAC9C,SAAK,gBAAgB;AACrB,WAAO,iCAAiC,KAAK,IAAI,MAAM,SAAS,KAAK,aAAa;AAAA,EACpF;AAAA,EACA,yBAAyB,SAAS,QAAQ;AACxC,SAAK,gBAAgB;AACrB,6BAAyB,KAAK,IAAI,SAAS,MAAM;AAAA,EACnD;AAAA,EACA,2BAA2B,SAAS,OAAO,QAAQ,MAAM;AACvD,SAAK,gBAAgB;AACrB,+BAA2B,KAAK,IAAI,SAAS,OAAO,QAAQ,MAAM,KAAK,aAAa;AAAA,EACtF;AAAA,EACA,iCAAiC,MAAM,SAAS;AAC9C,SAAK,gBAAgB;AACrB,WAAO,iCAAiC,KAAK,IAAI,MAAM,SAAS,KAAK,aAAa;AAAA,EACpF;AAAA,EACA,0BAA0B,MAAM,SAAS;AACvC,SAAK,gBAAgB;AACrB,WAAO,0BAA0B,KAAK,IAAI,MAAM,SAAS,KAAK,aAAa;AAAA,EAC7E;AAAA,EACA,oBAAoB,SAAS;AAC3B,SAAK,gBAAgB;AACrB,QAAI,KAAK,kBAAkB,SAAS;AAClC,wCAAkC,KAAK,IAAI,KAAK,WAAW;AAC3D,WAAK,gBAAgB;AAAA,IACvB;AACA,iBAAa,KAAK,IAAI,MAAM,KAAK,GAAG,cAAc,OAAO,CAAC;AAAA,EAC5D;AAAA,EACA,gDAAgD,SAAS,MAAM,SAAS;AACtE,WAAO,KAAK,qBAAqB,SAAS,MAAM,gDAAgD,KAAK,IAAI,MAAM,SAAS,KAAK,aAAa,CAAC;AAAA,EAC7I;AAAA,EACA,+BAA+B,SAAS,OAAO,MAAM,SAAS,cAAc,cAAc;AACxF,WAAO,+BAA+B,KAAK,IAAI,SAAS,OAAO,MAAM,SAAS,cAAc,cAAc,KAAK,aAAa;AAAA,EAC9H;AAAA,EACA,gCAAgC,SAASA,OAAM;AAC7C,WAAO,gCAAgC,KAAK,IAAI,SAASA,KAAI;AAAA,EAC/D;AAAA,EACA,wBAAwB,SAAS,MAAM,SAAS;AAC9C,SAAK,yBAAyB,OAAO;AACrC,UAAM,SAAS,8BAA8B,KAAK,IAAI,MAAM,SAAS,KAAK,aAAa;AACvF,SAAK,2BAA2B;AAChC,WAAO;AAAA,EACT;AAAA,EACA,wBAAwB;AACtB,UAAM,eAAe,KAAK,YAAY,KAAK,EAAE;AAC7C,WAAO,KAAK,UAAU,YAAY;AAAA,EACpC;AAAA,EACA,YAAY,IAAI;AACd,QAAI;AACJ,QAAI;AACJ,QAAI,IAAI,EAAE,QAAQ,yBAAyB,GAAG;AAC5C,YAAM,MAAM;AACZ,YAAM,OAAO,IAAI,UAAU,IAAI,4BAA4B,CAAC;AAC5D,SAAG,MAAM;AACT,sBAAgB,MAAM;AACpB,cAAM,SAAS,IAAI,eAAe,MAAM,GAAG,CAAC;AAC5C,eAAO,WAAW,IAAI,oBAAoB,WAAW,IAAI;AAAA,MAC3D;AACA,cAAQ;AAAA,IACV,WAAW,IAAI,EAAE,UAAU,8CAA8C,IAAI,GAAG;AAC9E,cAAQ,KAAK,WAAW;AACxB,WAAK,SAAS;AACd,sBAAgB,MAAM,KAAK,iBAAiB,OAAO,IAAI,EAAE,UAAU,8CAA8C,CAAC;AAAA,IACpH,OAAO;AACL,sBAAgB,MAAM;AAAA,IACxB;AACA,WAAO,EAAE,OAAO,cAAc;AAAA,EAChC;AAAA,EACA,gCAAgC,SAAS,cAAc,cAAc;AACnE,WAAO,KAAK,qBAAqB,SAAS,MAAM,sCAAsC,KAAK,IAAI,cAAc,YAAY,CAAC;AAAA,EAC5H;AAAA,EACA,cAAc,gBAAgB;AAC5B,SAAK,gBAAgB;AACrB,UAAM,KAAK,KAAK;AAChB,QAAI,KAAK,gBAAgB,MAAM;AAC7B,WAAK,eAAe,oBAAoB,EAAE;AAAA,IAC5C;AACA,UAAM,UAAU,cAAc,EAAE;AAChC,iBAAa,IAAI,MAAM,GAAG,aAAa,SAAS,KAAK,YAAY,CAAC;AAClE,iBAAa,IAAI,MAAM,GAAG,aAAa,SAAS,cAAc,CAAC;AAC/D,gBAAY,IAAI,OAAO;AACvB,QAAI,KAAK,OAAO;AACd,sBAAgB,IAAI,OAAO;AAAA,IAC7B;AACA,QAAI,CAAC,KAAK,qBAAqB;AAC7B,WAAK,WAAW,OAAO;AACvB,WAAK,sBAAsB,kCAAkC,IAAI,KAAK,SAAS,KAAK,YAAY;AAAA,IAClG;AACA,WAAO;AAAA,EACT;AAAA,EACA,cAAc,SAAS;AACrB,SAAK,gBAAgB;AACrB,QAAI,YAAY,KAAK,SAAS;AAC5B,WAAK,UAAU;AAAA,IACjB;AACA,QAAI,WAAW,MAAM;AACnB,mBAAa,KAAK,IAAI,MAAM,KAAK,GAAG,cAAc,OAAO,CAAC;AAAA,IAC5D;AAAA,EACF;AAAA,EACA,WAAW,SAAS;AAClB,SAAK,gBAAgB;AACrB,SAAK,UAAU;AACf,QAAI,KAAK,WAAW,QAAQ,KAAK,OAAO;AACtC,sBAAgB,KAAK,IAAI,KAAK,OAAO;AAAA,IACvC;AACA,iBAAa,KAAK,IAAI,MAAM,KAAK,GAAG,WAAW,OAAO,CAAC;AAAA,EACzD;AAAA,EACA,mBAAmB,SAAS,aAAa,cAAc,MAAM;AAC3D,SAAK,gBAAgB;AACrB,QAAI,aAAa;AACf,aAAO,iCAAiC,KAAK,IAAI,SAAS,WAAW;AAAA,IACvE,OAAO;AACL,aAAO,0BAA0B,KAAK,IAAI,SAAS,WAAW;AAAA,IAChE;AAAA,EACF;AAAA,EACA,qBAAqB,SAAS,WAAW;AACvC,SAAK,gBAAgB;AACrB,WAAO,aAAa,KAAK,IAAI,MAAM,KAAK,GAAG,kBAAkB,SAAS,SAAS,CAAC;AAAA,EAClF;AAAA,EACA,0BAA0B,SAAS,aAAa;AAC9C,SAAK,gBAAgB;AACrB,WAAO,KAAK,GAAG,mBAAmB,SAAS,WAAW;AAAA,EACxD;AAAA,EACA,sBAAsB,oBAAoB,iBAAiB,aAAa;AACtE,SAAK,gBAAgB;AACrB,SAAK,iBAAiB;AACtB,uCAAmC,KAAK,IAAI,oBAAoB,iBAAiB,WAAW;AAAA,EAC9F;AAAA,EACA,uBAAuB,qBAAqB,MAAM,SAAS;AACzD,SAAK,6BAA6B,qBAAqB,SAAS,IAAI;AAAA,EACtE;AAAA,EACA,6BAA6B,2BAA2B,MAAM,SAAS;AACrE,SAAK,gBAAgB;AACrB,UAAM,CAAC,OAAO,MAAM,IAAI,uCAAuC,MAAM,OAAO;AAC5E,SAAK,6BAA6B,2BAA2B,OAAO,MAAM;AAAA,EAC5E;AAAA,EACA,2BAA2B,UAAU,SAAS,aAAa,YAAY;AACrE,SAAK,iCAAiC,aAAa,UAAU,YAAY,OAAO;AAAA,EAClF;AAAA,EACA,iCAAiC,UAAU,SAAS,aAAa,YAAY;AAC3E,UAAM,IAAI,MAAM,mDAAmD;AAAA,EACrE;AAAA,EACA,gBAAgB;AACd,QAAI,KAAK,WAAW,MAAM;AACxB,sBAAgB,KAAK,IAAI,KAAK,OAAO;AAAA,IACvC;AACA,wBAAoB,KAAK,EAAE;AAAA,EAC7B;AAAA,EACA,iBAAiB;AACf,SAAK,gBAAgB;AACrB,SAAK,iBAAiB;AACtB,UAAM,KAAK,KAAK;AAChB,QAAI,KAAK,OAAO;AACd,WAAK,cAAc;AAAA,IACrB;AACA,iBAAa,IAAI,MAAM,GAAG,aAAa,GAAG,WAAW,GAAG,GAAG,gBAAgB,CAAC,CAAC;AAAA,EAC/E;AAAA,EACA,iCAAiC;AAC/B,SAAK,gBAAgB;AACrB,iBAAa,KAAK,IAAI,MAAM,KAAK,GAAG,OAAO,CAAC;AAAA,EAC9C;AAAA,EACA,yBAAyB;AACvB,QAAI,KAAK,+BAA+B,MAAM;AAC5C,WAAK,8BAA8B,oBAAoB,KAAK,IAAI,IAAI,EAAE,UAAU,8CAA8C,MAAM,IAAI,oCAAoC,0BAA0B;AAAA,IACxM;AACA,WAAO,KAAK;AAAA,EACd;AAAA,EACA,+BAA+B;AAC7B,WAAO,KAAK,uBAAuB;AAAA,EACrC;AAAA,EACA,+BAA+B;AAC7B,WAAO,KAAK,uBAAuB;AAAA,EACrC;AAAA,EACA,aAAa;AACX,QAAI,IAAI,EAAE,UAAU,8CAA8C,MAAM,GAAG;AACzE,YAAM,MAAM,KAAK;AACjB,YAAM,OAAO,KAAK,6BAA6B;AAC/C,YAAM,SAAS,IAAI,YAAY;AAC/B,UAAI,WAAW,KAAK,kBAAkB,MAAM;AAC5C,aAAO;AAAA,IACT;AACA,UAAM,MAAM,KAAK,6BAA6B;AAC9C,UAAM,QAAQ,IAAI,eAAe;AACjC,QAAI,cAAc,IAAI,kBAAkB,KAAK;AAC7C,WAAO;AAAA,EACT;AAAA,EACA,WAAW;AACT,QAAI,IAAI,EAAE,UAAU,8CAA8C,MAAM,GAAG;AACzE,YAAM,MAAM,KAAK;AACjB,YAAM,OAAO,KAAK,6BAA6B;AAC/C,UAAI,SAAS,KAAK,gBAAgB;AAClC;AAAA,IACF;AACA,UAAM,MAAM,KAAK,6BAA6B;AAC9C,QAAI,YAAY,IAAI,gBAAgB;AAAA,EACtC;AAAA,EACA,MAAM,uBAAuB,OAAO;AAClC,UAAM,aAAa,YAAY,MAAM,KAAK,YAAY,KAAK,iBAAiB,OAAO,IAAI,EAAE,UAAU,8CAA8C,CAAC,CAAC;AACnJ,WAAO,KAAK,aAAa,OAAO,IAAI,EAAE,UAAU,8CAA8C,CAAC;AAAA,EACjG;AAAA,EACA,aAAa,OAAO,mBAAmB;AACrC,QAAI,sBAAsB,GAAG;AAC3B,aAAO;AAAA,IACT;AACA,QAAI,sBAAsB,GAAG;AAC3B,YAAM,MAAM,KAAK;AACjB,YAAM,mBAAmB,IAAI,kBAAkB,OAAO,IAAI,YAAY;AACtE,aAAO,mBAAmB;AAAA,IAC5B,OAAO;AACL,YAAM,MAAM,KAAK,6BAA6B;AAC9C,YAAM,mBAAmB,IAAI,kBAAkB,OAAO,IAAI,gBAAgB;AAC1E,aAAO,mBAAmB;AAAA,IAC5B;AAAA,EACF;AAAA,EACA,iBAAiB,OAAO,mBAAmB;AACzC,QAAI,sBAAsB,GAAG;AAC3B,aAAO;AAAA,IACT;AACA,QAAI,sBAAsB,GAAG;AAC3B,YAAM,MAAM,KAAK;AACjB,YAAM,MAAM,KAAK,6BAA6B;AAC9C,YAAM,YAAY,IAAI,kBAAkB,OAAO,IAAI,sBAAsB;AACzE,UAAI,KAAK,YAAY,MAAM;AACzB,aAAK,WAAW,KAAK,GAAG,aAAa,IAAI,gBAAgB;AAAA,MAC3D;AACA,aAAO,aAAa,CAAC,KAAK;AAAA,IAC5B,OAAO;AACL,YAAM,MAAM,KAAK,6BAA6B;AAC9C,YAAM,YAAY,IAAI,kBAAkB,OAAO,IAAI,0BAA0B;AAC7E,UAAI,KAAK,YAAY,MAAM;AACzB,aAAK,WAAW,KAAK,GAAG,aAAa,IAAI,gBAAgB;AAAA,MAC3D;AACA,aAAO,aAAa,CAAC,KAAK;AAAA,IAC5B;AAAA,EACF;AAAA,EACA,UAAU,cAAc;AACtB,WAAO,IAAI,QAAQ,CAAC,YAAY;AAC9B,WAAK,cAAc,MAAM,aAAa,cAAc,GAAG,MAAM,QAAQ,CAAC;AAAA,IACxE,CAAC;AAAA,EACH;AAAA,EACA,YAAY;AACV,UAAMS,SAAQ,qBAAqB,KAAK,YAAY,IAAI,CAAC,MAAM,EAAE,QAAQ,CAAC;AAC1E,aAAS,KAAK,GAAG,MAAMA,QAAO,EAAE,IAAI;AAClC,YAAM,EAAE,UAAU,IAAI,KAAK,YAAY;AACvC,gBAAU;AAAA,IACZ;AACA,SAAK,cAAc,KAAK,YAAY,MAAMA,SAAQ,CAAC;AAAA,EACrD;AAAA,EACA,cAAc,UAAU,WAAW;AACjC,SAAK,YAAY,KAAK,EAAE,UAAU,UAAU,CAAC;AAC7C,QAAI,KAAK,YAAY,SAAS,GAAG;AAC/B;AAAA,IACF;AACA,iBAAa,YAAY,MAAM;AAC7B,WAAK,UAAU;AACf,aAAO,KAAK,YAAY,WAAW;AAAA,IACrC,CAAC;AAAA,EACH;AAAA,EACA,yBAAyB,SAAS;AAChC,SAAK,gBAAgB;AACrB,kCAA8B,KAAK,IAAI,SAAS,KAAK,WAAW;AAChE,QAAI,KAAK,OAAO;AACd,0BAAoB,KAAK,EAAE;AAAA,IAC7B;AAAA,EACF;AAAA,EACA,6BAA6B;AAC3B,QAAI,KAAK,iBAAiB,MAAM;AAC9B,oCAA8B,KAAK,IAAI,KAAK,eAAe,KAAK,WAAW;AAC3E,UAAI,KAAK,OAAO;AACd,4BAAoB,KAAK,EAAE;AAAA,MAC7B;AAAA,IACF,OAAO;AACL,wCAAkC,KAAK,IAAI,KAAK,WAAW;AAAA,IAC7D;AAAA,EACF;AAAA,EACA,qBAAqB,SAAS,mBAAmB;AAC/C,SAAK,yBAAyB,OAAO;AACrC,UAAM,SAAS,kBAAkB;AACjC,SAAK,2BAA2B;AAChC,WAAO;AAAA,EACT;AAAA,EACA,6BAA6B,gCAAgC,OAAO,QAAQ;AAC1E,SAAK,gBAAgB;AACrB,UAAM,KAAK,KAAK;AAChB,kCAA8B,IAAI,gCAAgC,KAAK,WAAW;AAClF,QAAI,KAAK,OAAO;AACd,0BAAoB,EAAE;AAAA,IACxB;AACA,SAAK,gBAAgB;AACrB,iBAAa,IAAI,MAAM,GAAG,SAAS,GAAG,GAAG,OAAO,MAAM,CAAC;AACvD,iBAAa,IAAI,MAAM,GAAG,QAAQ,GAAG,GAAG,OAAO,MAAM,CAAC;AAAA,EACxD;AAAA,EACA,iCAAiC,GAAG,GAAG,OAAO,QAAQ;AACpD,SAAK,gBAAgB;AACrB,iBAAa,KAAK,IAAI,MAAM,KAAK,GAAG,QAAQ,GAAG,GAAG,OAAO,MAAM,CAAC;AAAA,EAClE;AAAA,EACA,kBAAkB;AAChB,QAAI,KAAK,UAAU;AACjB,YAAM,IAAI,MAAM,yCAAyC;AAAA,IAC3D;AAAA,EACF;AAAA,EACA,mBAAmB;AACjB,QAAI,KAAK,WAAW,MAAM;AACxB,YAAM,IAAI,MAAM,kCAAkC;AAAA,IACpD;AAAA,EACF;AACF;AACA,SAAS,qBAAqB,KAAK;AACjC,MAAI,KAAK;AACT,SAAO,KAAK,IAAI,QAAQ,EAAE,IAAI;AAC5B,UAAM,SAAS,IAAI,IAAI;AACvB,QAAI,CAAC,QAAQ;AACX;AAAA,IACF;AAAA,EACF;AACA,SAAO,KAAK;AACd;AAGA,IAAI,EAAE,SAAS,YAAY,cAAc,iBAAiB,oBAAoB,uBAAuB,UAAU,aAAa,YAAY,eAAe,WAAW,cAAc,SAAS,YAAY,WAAW,cAAc,WAAW,cAAc,cAAc,iBAAiB,cAAc,iBAAiB,aAAa,gBAAgB,kBAAkB,qBAAqB,UAAU,aAAa,eAAe,kBAAkB,cAAc,iBAAiB,SAAS,YAAY,SAAS,YAAY,aAAa,gBAAgB,aAAa,gBAAgB,cAAc,iBAAiB,SAAS,YAAY,cAAc,iBAAiB,UAAU,aAAa,WAAW,cAAc,WAAW,cAAc,aAAa,gBAAgB,aAAa,gBAAgB,eAAe,kBAAkB,WAAW,cAAc,yBAAyB,4BAA4B,mBAAmB,sBAAsB,4BAA4B,+BAA+B,UAAU,aAAa,kBAAkB,qBAAqB,kBAAkB,qBAAqB,iBAAiB,oBAAoB,4BAA4B,+BAA+B,SAAS,YAAY,UAAU,aAAa,UAAU,aAAa,eAAe,kBAAkB,YAAY,cAAc,IAAI;AAGpyC,SAAS,eAAe,MAAM,MAAM;AAClC,SAAO,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG,EAAE,MAAM,GAAG,IAAI,EAAE,IAAI,CAAC,MAAM,GAAG,QAAQ,GAAG;AAChF;AACA,SAAS,YAAY,MAAM,MAAM;AAC/B,MAAI,SAAS,GAAG;AACd,WAAO,CAAC,IAAI;AAAA,EACd;AACA,SAAO,eAAe,MAAM,IAAI;AAClC;AACA,SAAS,gBAAgB,MAAM,MAAM;AACnC,MAAI,SAAS,GAAG;AACd,WAAO;AAAA,EACT;AACA,MAAI,UAAU;AACd,WAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,eAAW,KAAK;AAChB,QAAI,KAAK,OAAO,GAAG;AACjB,iBAAW;AAAA,IACb;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc;AACnB,SAAK,OAAO,YAAY;AACxB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,QAAI,KAAK,SAAS,GAAG;AACnB,WAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,IAKlB,OAAO;AACL,YAAM,WAAW,YAAY,MAAM,KAAK,IAAI;AAC5C,YAAM,QAAQ,kBAAkB,KAAK,IAAI;AACzC,YAAM,uBAAuB,KAAK,wBAAwB,QAAQ;AAClE,YAAM,UAAU,KAAK,SAAS,QAAQ;AACtC,YAAM,SAAS,KAAK,UAAU,QAAQ;AACtC,WAAK,WAAW;AAAA;AAAA,YAEV;AAAA;AAAA,eAEG;AAAA;AAAA;AAAA,cAGD;AAAA;AAAA,6BAEe;AAAA;AAAA;AAAA;AAAA,IAIzB;AAAA,EACF;AAAA,EACA,mBAAmB,MAAM;AACvB,UAAM,UAAU,CAAC;AACjB,aAAS,MAAM,GAAG,OAAO,GAAG,OAAO;AACjC,eAAS,MAAM,GAAG,OAAO,GAAG,OAAO;AACjC,YAAI,QAAQ,GAAG,QAAQ,IAAI,MAAM,UAAU,QAAQ,IAAI,MAAM;AAC7D,iBAAS,IAAI,GAAG,IAAI,KAAK,MAAM,KAAK;AAClC,kBAAQ,GAAG,KAAK,KAAK,SAAS,IAAI,QAAQ;AAAA,QAC5C;AACA,gBAAQ,KAAK,KAAK;AAAA,MACpB;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,wBAAwB,MAAM;AAC5B,QAAI,KAAK,SAAS,GAAG;AACnB,aAAO,QAAQ,KAAK,sBAAsB,aAAa,KAAK,YAAY;AAAA,IAC1E;AACA,QAAI,OAAO;AACX,aAAS,KAAK,KAAK,OAAO,GAAG,KAAK,KAAK,MAAM,MAAM;AACjD,cAAQ,GAAG,KAAK,UAAU,KAAK,sBAAsB,YAAY,QAAQ,KAAK,YAAY;AAC1F,UAAI,KAAK,KAAK,OAAO,GAAG;AACtB,gBAAQ;AAAA,MACV;AAAA,IACF;AACA,WAAO;AAAA,EACT;AAAA,EACA,SAAS,MAAM;AACb,QAAI,KAAK,SAAS,GAAG;AACnB,aAAO;AAAA,IACT;AACA,UAAM,YAAY,KAAK,MAAM,EAAE;AAC/B,UAAM,MAAM,KAAK,sBAAsB,YAAY,KAAK,cAAc,KAAK,YAAY,KAAK,OAAO;AACnG,UAAM,MAAM,KAAK,sBAAsB,YAAY,KAAK,cAAc,KAAK,YAAY,KAAK,OAAO;AACnG,WAAO;AAAA,gBACK,UAAU;AAAA,gBACV,UAAU;AAAA;AAAA;AAAA;AAAA,4BAIE;AAAA,4BACA;AAAA;AAAA,EAE1B;AAAA,EACA,UAAU,MAAM;AACd,UAAM,eAAe,KAAK,mBAAmB,IAAI;AACjD,QAAI,KAAK,SAAS,GAAG;AACnB,YAAM,WAAW,KAAK,sBAAsB,aAAa,KAAK,YAAY;AAC1E,aAAO,wBAAwB;AAAA,IACjC;AACA,WAAO,QAAQ,aAAa;AAAA,gCACA,aAAa;AAAA,gCACb,aAAa;AAAA,yCACJ,aAAa;AAAA,EACpD;AACF;AAGA,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,aAAa,YAAY;AACnC,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,iBAAiB,CAAC,EAAE,MAAM,cAAc,MAAM,QAAQ,CAAC;AAC5D,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,QAAI,WAAW;AACf,aAAS,KAAK,GAAG,KAAK,GAAG,MAAM;AAC7B,UAAI,SAAS;AACb,UAAI,KAAK,MAAM,GAAG;AAChB,kBAAU;AAAA,MACZ;AACA,UAAI,KAAK,GAAG;AACV,kBAAU;AAAA,MACZ;AACA,kBAAY;AAAA,UACR;AAAA,UACA,KAAK,IAAI,4CAA4C;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,mBAM5C;AAAA;AAAA,UAET,KAAK,IAAI,MAAM;AAAA;AAAA,IAErB;AACA,SAAK,WAAW;AAAA,QACZ,uBAAuB,YAAY,KAAK,mBAAmB;AAAA,QAC3D,KAAK,sBAAsB,yBAAyB,IAAI,mBAAmB,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,qBAQzE,KAAK,sBAAsB,gBAAgB,YAAY;AAAA,qBACvD,KAAK,sBAAsB,gBAAgB,YAAY;AAAA;AAAA,UAElE;AAAA;AAAA;AAAA;AAAA;AAAA,EAKR;AACF;AACA,SAAS,uBAAuB,OAAO,qBAAqB;AAC1D,QAAM,yBAAyB,sBAAsB,4CAA4C,CAAC,KAAK,KAAK,GAAG,GAAG,YAAY,IAAI,mCAAmC,CAAC,KAAK,KAAK,GAAG,GAAG,KAAK;AAC3L,SAAO;AAAA;AAAA,QAED;AAAA;AAAA;AAAA;AAIR;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,OAAO;AACjB,SAAK,QAAQ;AACb,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AACvB,SAAK,qBAAqB;AAC1B,SAAK,gBAAgB;AACrB,SAAK,eAAe,CAAC;AACrB,SAAK,aAAa;AAClB,SAAK,eAAe,CAAC;AAAA,EACvB;AAAA,EACA,eAAe,SAAS,OAAO,UAAU;AACvC,UAAM,kBAAkB,kCAAkC,OAAO,QAAQ;AACzE,UAAM,WAAW,uBAAuB,SAAS,iBAAiB,QAAQ;AAC1E,QAAI,EAAE,YAAY,KAAK,eAAe;AACpC,WAAK,aAAa,YAAY,CAAC;AAAA,IACjC;AACA,QAAI,EAAE,YAAY,KAAK,eAAe;AACpC,WAAK,aAAa,YAAY,CAAC;AAAA,IACjC;AACA,UAAM,WAAW,aAAa,SAAS,iBAAiB,KAAK,MAAM,IAAI,KAAK,MAAM,eAAe,QAAQ;AACzG,QAAI,KAAK,aAAa,UAAU,SAAS,GAAG;AAC1C,WAAK;AACL,WAAK;AACL,WAAK,iBAAiB;AACtB,WAAK,IAAI;AACT,YAAM,cAAc,KAAK,aAAa,UAAU,MAAM;AACtD,WAAK,aAAa,UAAU,KAAK,WAAW;AAC5C,aAAO;AAAA,IACT;AACA,QAAI;AACJ,QAAI,oBAAoB,oBAAoB,oBAAoB;AAC9D,mBAAa,KAAK,MAAM,0BAA0B,QAAQ,IAAI,QAAQ,EAAE;AAAA,IAC1E,WAAW,oBAAoB,oBAAoB,oBAAoB;AACrE,mBAAa,KAAK,MAAM,iCAAiC,QAAQ,IAAI,QAAQ,EAAE;AAAA,IACjF,WAAW,oBAAoB,oBAAoB,kBAAkB;AACnE,mBAAa,KAAK,MAAM,2BAA2B,QAAQ,IAAI,QAAQ,EAAE;AAAA,IAC3E,WAAW,oBAAoB,oBAAoB,kBAAkB;AACnE,mBAAa,KAAK,MAAM,2BAA2B,QAAQ,IAAI,QAAQ,EAAE;AAAA,IAC3E,WAAW,oBAAoB,oBAAoB,0BAA0B;AAC3E,mBAAa,KAAK,MAAM,iCAAiC,QAAQ,IAAI,QAAQ,EAAE;AAAA,IACjF;AACA,SAAK,aAAa,UAAU,KAAK,UAAU;AAC3C,SAAK;AACL,SAAK,sBAAsB;AAC3B,SAAK,IAAI;AACT,WAAO;AAAA,EACT;AAAA,EACA,eAAe,SAAS,OAAO,gBAAgB,UAAU;AACvD,QAAI,KAAK,gBAAgB,MAAM;AAC7B;AAAA,IACF;AACA,UAAM,kBAAkB,kCAAkC,gBAAgB,QAAQ;AAClF,UAAM,WAAW,uBAAuB,OAAO,iBAAiB,QAAQ;AACxE,QAAI,EAAE,YAAY,KAAK,eAAe;AACpC,WAAK,aAAa,YAAY,CAAC;AAAA,IACjC;AACA,UAAM,WAAW,aAAa,OAAO,iBAAiB,KAAK,MAAM,IAAI,KAAK,MAAM,eAAe,QAAQ;AACvG,UAAM,qBAAqB,IAAI,EAAE,IAAI,gCAAgC;AACrE,QAAI,uBAAuB,MAAM,KAAK,qBAAqB,oBAAoB;AAC7E,WAAK,MAAM,oBAAoB,QAAQ,OAAO;AAC9C,WAAK,sBAAsB;AAAA,IAC7B,OAAO;AACL,WAAK,aAAa,UAAU,KAAK,OAAO;AACxC,WAAK;AACL,WAAK,iBAAiB;AAAA,IACxB;AACA,SAAK;AACL,UAAM,UAAU,KAAK,aAAa;AAClC,UAAM,WAAW,QAAQ,QAAQ,OAAO;AACxC,QAAI,WAAW,GAAG;AAChB,YAAM,IAAI,MAAM,0EAA0E;AAAA,IAC5F;AACA,YAAQ,OAAO,UAAU,CAAC;AAC1B,SAAK,IAAI;AAAA,EACX;AAAA,EACA,MAAM;AACJ,QAAI,CAAC,KAAK,YAAY;AACpB;AAAA,IACF;AACA,UAAM,QAAQ,KAAK,kBAAkB,KAAK;AAC1C,YAAQ,IAAI,aAAa,GAAG,KAAK,qBAAqB,KAAK,mBAAmB,IAAI,QAAQ;AAC1F,UAAM,YAAY,KAAK,gBAAgB,KAAK;AAC5C,YAAQ,IAAI,oBAAoB,KAAK,oBAAoB;AACzD,YAAQ,IAAI,iBAAiB,KAAK,kBAAkB,KAAK,MAAM,MAAM,SAAS,KAAK;AAAA,EACrF;AAAA,EACA,IAAI,oBAAoB;AACtB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,IAAI,eAAe;AACjB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,qBAAqB;AACnB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,qBAAqB;AACnB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,UAAU;AACR,QAAI,KAAK,gBAAgB,MAAM;AAC7B;AAAA,IACF;AACA,eAAW,YAAY,KAAK,cAAc;AACxC,WAAK,aAAa,UAAU,QAAQ,CAAC,QAAQ;AAC3C,aAAK,MAAM,oBAAoB,IAAI,OAAO;AAAA,MAC5C,CAAC;AAAA,IACH;AACA,eAAW,YAAY,KAAK,cAAc;AACxC,WAAK,aAAa,UAAU,QAAQ,CAAC,QAAQ;AAC3C,aAAK,MAAM,oBAAoB,IAAI,OAAO;AAAA,MAC5C,CAAC;AAAA,IACH;AACA,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AACvB,SAAK,qBAAqB;AAC1B,SAAK,gBAAgB;AAAA,EACvB;AACF;AACA,SAAS,0BAA0B,IAAI,gBAAgB;AACrD,QAAM,QAAQ;AACd,MAAI,mBAAmB,MAAM,MAAM;AACjC,WAAO;AAAA,EACT,WAAW,mBAAmB,MAAM,MAAM;AACxC,WAAO;AAAA,EACT,WAAW,mBAAmB,MAAM,SAAS;AAC3C,WAAO;AAAA,EACT,WAAW,mBAAmB,GAAG,MAAM;AACrC,WAAO;AAAA,EACT,WAAW,mBAAmB,MAAM,SAAS;AAC3C,WAAO;AAAA,EACT,WAAW,mBAAmB,MAAM,OAAO;AACzC,WAAO;AAAA,EACT;AACA,QAAM,IAAI,MAAM,2BAA2B,gBAAgB;AAC7D;AACA,SAAS,aAAa,OAAO,iBAAiB,IAAI,eAAe,UAAU;AACzE,QAAM,iBAAiB,iCAAiC,iBAAiB,aAAa;AACtF,MAAI;AACJ,MAAI,UAAU;AACZ,UAAM,CAAC,aAAa,YAAY,IAAI,uCAAuC,MAAM,IAAI,MAAM,EAAE;AAC7F,kBAAc,cAAc;AAAA,EAC9B,OAAO;AACL,UAAM,CAAC,OAAO,MAAM,IAAI,yCAAyC,MAAM,IAAI,MAAM,EAAE;AACnF,kBAAc,QAAQ;AAAA,EACxB;AACA,QAAM,mBAAmB,0BAA0B,IAAI,cAAc;AACrE,SAAO,cAAc;AACvB;AACA,SAAS,iCAAiC,iBAAiB,eAAe;AACxE,UAAQ;AAAA,SACD,oBAAoB;AACvB,aAAO,wCAAwC,aAAa;AAAA,SACzD,oBAAoB;AACvB,aAAO,+CAA+C,aAAa;AAAA,SAChE,oBAAoB;AACvB,aAAO,yCAAyC,aAAa;AAAA,SAC1D,oBAAoB;AACvB,aAAO,yCAAyC,aAAa;AAAA,SAC1D,oBAAoB;AACvB,aAAO,+CAA+C,aAAa;AAAA;AAEnE,YAAM,IAAI,MAAM,iCAAiC,iBAAiB;AAAA;AAExE;AACA,SAAS,+BAA+B,UAAU;AAChD,MAAI,IAAI,EAAE,QAAQ,8BAA8B,GAAG;AACjD,QAAI,UAAU;AACZ,aAAO,oBAAoB;AAAA,IAC7B;AACA,WAAO,oBAAoB;AAAA,EAC7B;AACA,MAAI,UAAU;AACZ,WAAO,oBAAoB;AAAA,EAC7B;AACA,SAAO,oBAAoB;AAC7B;AACA,SAAS,kCAAkC,gBAAgB,UAAU;AACnE,MAAI,mBAAmB,aAAa,QAAQ;AAC1C,WAAO,oBAAoB;AAAA,EAC7B,WAAW,mBAAmB,aAAa,UAAU,kBAAkB,MAAM;AAC3E,WAAO,+BAA+B,QAAQ;AAAA,EAChD,WAAW,mBAAmB,aAAa,YAAY,mBAAmB,aAAa,QAAQ;AAC7F,WAAO,oBAAoB;AAAA,EAC7B;AACA,QAAM,IAAI,MAAM,gCAAgC,gBAAgB;AAClE;AACA,SAAS,uBAAuB,cAAc,iBAAiB,UAAU;AACvE,SAAO,GAAG,aAAa,MAAM,aAAa,MAAM,mBAAmB;AACrE;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,QAAQ,WAAW;AAC7B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAUR;AACF;AACA,IAAI,oBAAoB;AACxB,IAAI,SAAS;AACb,IAAI,MAAM;AACV,IAAI,OAAO;AACX,IAAI,OAAO,oBAAoB;AAAA;AAAA;AAG/B,IAAI,QAAQ,oBAAoB;AAAA;AAAA;AAGhC,IAAI,QAAQ;AACZ,IAAI,UAAU;AAGd,IAAI,UAAU;AACd,IAAI,OAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUX,IAAI,QAAQ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWZ,IAAI,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWb,IAAI,WAAW;AACf,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,QAAQ,WAAW;AAC7B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAUR;AACF;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,UAAM,OAAO,YAAY;AACzB,UAAM,WAAW,YAAY,MAAM,IAAI;AACvC,UAAM,QAAQ,kBAAkB,IAAI;AACpC,UAAM,eAAe,gBAAgB,MAAM,QAAQ;AACnD,UAAM,YAAY,SAAS,MAAM,EAAE;AACnC,UAAM,UAAU,QAAQ,IAAI,OAAO,QAAQ,UAAU,KAAK,GAAG;AAC7D,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA,kCACwB;AAAA;AAAA,4CAEU;AAAA;AAAA;AAAA,EAG1C;AACF;AAGA,IAAI,aAAa,qBAAqB;AACtC,IAAI,mBAAmB;AACvB,IAAI,mBAAmB;AACvB,IAAI,eAAe,CAAC;AACpB,SAAS,eAAe,cAAc;AACpC,MAAI,gBAAgB,cAAc;AAChC,WAAO,aAAa;AAAA,EACtB;AACA,eAAa,gBAAgB,CAAC;AAC9B,SAAO,aAAa;AACtB;AACA,IAAI,6BAA6B,IAAI,EAAE,UAAU,4BAA4B;AAC7E,IAAI,yBAAyB;AAC7B,SAAS,qBAAqB;AAC5B,MAAI,IAAI,EAAE,OAAO,UAAU,MAAM;AAC/B,WAAO;AAAA,EACT;AACA,SAAO,IAAI,EAAE,OAAO,OAAO,SAAS,IAAI,EAAE,OAAO,OAAO,QAAQ,OAAO,mBAAmB,yBAAyB,OAAO;AAC5H;AACA,IAAI,mBAAmB,cAAc,cAAc;AAAA,EACjD,YAAY,aAAa;AACvB,UAAM;AACN,SAAK,cAA8B,oBAAI,QAAQ;AAC/C,SAAK,kBAAkC,oBAAI,QAAQ;AACnD,SAAK,eAA+B,oBAAI,QAAQ;AAChD,SAAK,gBAAgB;AACrB,SAAK,eAAe;AACpB,SAAK,iBAAiB;AACtB,SAAK,kBAAkB;AACvB,SAAK,oBAAoB;AACzB,SAAK,iBAAiB;AACtB,SAAK,WAAW;AAChB,QAAI,CAAC,IAAI,EAAE,QAAQ,WAAW,GAAG;AAC/B,YAAM,IAAI,MAAM,uCAAuC;AAAA,IACzD;AACA,QAAI;AACJ,QAAI,eAAe,MAAM;AACvB,UAAI,uBAAuB,cAAc;AACvC,mBAAW;AAAA,MACb,OAAO;AACL,cAAM,KAAK,gBAAgB,IAAI,EAAE,UAAU,eAAe,GAAG,WAAW;AACxE,mBAAW,IAAI,aAAa,EAAE;AAAA,MAChC;AACA,WAAK,cAAc,CAAC;AACpB,WAAK,sBAAsB;AAAA,IAC7B,OAAO;AACL,YAAM,KAAK,gBAAgB,IAAI,EAAE,UAAU,eAAe,CAAC;AAC3D,iBAAW,IAAI,aAAa,EAAE;AAC9B,WAAK,cAAc,eAAe,IAAI,EAAE,UAAU,eAAe,CAAC;AAClE,WAAK,sBAAsB;AAAA,IAC7B;AACA,SAAK,QAAQ;AACb,SAAK,SAAS,KAAK,MAAM,GAAG;AAC5B,SAAK,iBAAiB,IAAI,eAAe,KAAK,KAAK;AACnD,SAAK,qBAAqB,mBAAmB;AAC7C,SAAK,UAAU,IAAI,YAAY,MAAM,OAAO,CAAC;AAAA,EAC/C;AAAA,EACA,aAAa;AACX,WAAO,iBAAiB;AAAA,EAC1B;AAAA,EACA,aAAa;AACX,WAAO,KAAK,QAAQ,WAAW,IAAI,KAAK;AAAA,EAC1C;AAAA,EACA,MAAM,QAAQ,OAAO,OAAO;AAC1B,QAAI,IAAI,EAAE,QAAQ,gCAAgC,KAAK,IAAI,EAAE,QAAQ,OAAO,GAAG;AAC7E,WAAK,uBAAuB,MAAM;AAAA,IACpC;AACA,QAAI,UAAU,eAAe,UAAU,MAAM;AAC3C,YAAM,IAAI,MAAM,uEAAuE;AAAA,IACzF;AACA,UAAM,SAAS,EAAE,IAAI,KAAK,WAAW,EAAE;AACvC,SAAK,QAAQ,IAAI,QAAQ,EAAE,OAAO,OAAO,QAAQ,OAAO,aAAa,QAAQ,UAAU,EAAE,CAAC;AAC1F,WAAO;AAAA,EACT;AAAA,EACA,SAAS,QAAQ;AACf,QAAI,KAAK,QAAQ,IAAI,MAAM,GAAG;AAC5B,YAAM,aAAa,KAAK,QAAQ,IAAI,MAAM;AAC1C,aAAO,WAAW;AAAA,IACpB;AACA,WAAO;AAAA,EACT;AAAA,EACA,OAAO,QAAQ;AACb,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,YAAQ;AAAA,EACV;AAAA,EACA,OAAO,QAAQ;AACb,QAAI,KAAK,QAAQ,IAAI,MAAM,GAAG;AAC5B,YAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,cAAQ;AAAA,IACV;AAAA,EACF;AAAA,EACA,KAAK,QAAQ,QAAQ,OAAO,OAAO,UAAU;AAC3C,QAAI,IAAI,EAAE,QAAQ,OAAO,GAAG;AAC1B,WAAK,uBAAuB,MAAM;AAAA,IACpC;AACA,QAAI,UAAU,aAAa;AACzB,YAAM,IAAI,MAAM,uEAAuE;AAAA,IACzF;AACA,SAAK,QAAQ,IAAI,QAAQ,EAAE,OAAO,OAAO,QAAQ,OAAO,aAAa,QAAQ,SAAS,CAAC;AAAA,EACzF;AAAA,EACA,8BAA8B,YAAY;AACxC,SAAK,YAAY,WAAW,MAAM;AAAA,EACpC;AAAA,EACA,SAAS,QAAQ;AACf,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,UAAM,EAAE,QAAQ,OAAO,oBAAoB,OAAO,QAAQ,OAAO,SAAS,IAAI;AAC9E,QAAI,UAAU,MAAM;AAClB,UAAI;AACJ,UAAI,UAAU;AACZ,kBAAU,IAAI,qBAAqB,OAAO,KAAK;AAAA,MACjD,OAAO;AACL,kBAAU,IAAI,eAAe,OAAO,KAAK;AAAA,MAC3C;AACA,YAAM,MAAM,KAAK,gBAAgB,SAAS,CAAC,EAAE,QAAQ,OAAO,MAAM,CAAC,GAAG,KAAK;AAC3E,YAAM,OAAO,KAAK,SAAS,IAAI,MAAM;AACrC,WAAK,8BAA8B,GAAG;AACtC,aAAO;AAAA,IACT;AACA,QAAI,UAAU,MAAM;AAClB,aAAO,KAAK,qBAAqB,MAAM;AAAA,IACzC;AACA,QAAI,UAAU,UAAU;AACtB,aAAO;AAAA,IACT;AACA,UAAM,oBAAoB,KAAK,gBAAgB;AAC/C,QAAI;AACJ,QAAI,mBAAmB;AACrB,cAAQ,aAAa,IAAI;AAAA,IAC3B;AACA,QAAI;AACJ,QAAI,UAAU,aAAa;AACzB,YAAM,aAAa,KAAK,SAAS,mBAAmB,KAAK,MAAM;AAC/D,YAAM,aAAa,KAAK,SAAS,mBAAmB,KAAK,MAAM;AAC/D,eAAS,qBAAqB,uBAAuB,YAAY,UAAU;AAAA,IAC7E,OAAO;AACL,eAAS,KAAK,qBAAqB,MAAM;AAAA,IAC3C;AACA,QAAI,mBAAmB;AACrB,WAAK,kBAAkB,aAAa,IAAI,IAAI;AAAA,IAC9C;AACA,WAAO,KAAK,qBAAqB,QAAQ,MAAM;AAAA,EACjD;AAAA,EACA,MAAM,KAAK,QAAQ;AACjB,QAAI,KAAK,YAAY,IAAI,MAAM,GAAG;AAChC,YAAM,eAAe,KAAK,YAAY,IAAI,MAAM;AAChD,aAAO,IAAI,QAAQ,CAAC,YAAY,aAAa,KAAK,OAAO,CAAC;AAAA,IAC5D;AACA,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,UAAM,EAAE,QAAQ,OAAO,OAAO,QAAQ,OAAO,oBAAoB,SAAS,IAAI;AAC9E,QAAI,UAAU,MAAM;AAClB,UAAI;AACJ,UAAI,UAAU;AACZ,kBAAU,IAAI,qBAAqB,OAAO,KAAK;AAAA,MACjD,OAAO;AACL,kBAAU,IAAI,eAAe,OAAO,KAAK;AAAA,MAC3C;AACA,YAAM,MAAM,KAAK,gBAAgB,SAAS,CAAC,EAAE,QAAQ,OAAO,MAAM,CAAC,GAAG,KAAK;AAC3E,YAAM,OAAO,KAAK,KAAK,IAAI,MAAM;AACjC,WAAK,8BAA8B,GAAG;AACtC,aAAO;AAAA,IACT;AACA,QAAI,UAAU,MAAM;AAClB,aAAO,KAAK,qBAAqB,MAAM;AAAA,IACzC;AACA,QAAI,IAAI,EAAE,QAAQ,OAAO,GAAG;AAC1B,UAAI,CAAC,IAAI,EAAE,QAAQ,8BAA8B,KAAK,IAAI,EAAE,UAAU,eAAe,MAAM,GAAG;AAC5F,cAAM,IAAI,MAAM,8FAA8F;AAAA,MAChH;AAAA,IACF;AACA,QAAI,UAAU;AACd,QAAI;AACJ,QAAI,UAAU,eAAe,IAAI,EAAE,IAAI,wBAAwB,GAAG;AAChE,0BAAoB,KAAK,OAAO,MAAM;AACtC,YAAM,UAAU,KAAK,QAAQ,IAAI,kBAAkB,MAAM;AACzD,gBAAU,KAAK,MAAM,wBAAwB,QAAQ,QAAQ,SAAS,GAAG,iBAAiB,KAAK,CAAC;AAAA,IAClG;AACA,SAAK,YAAY,IAAI,QAAQ,CAAC,CAAC;AAC/B,QAAI,UAAU,aAAa;AACzB,YAAM,KAAK,MAAM,sBAAsB;AAAA,IACzC;AACA,QAAI;AACJ,QAAI,UAAU,aAAa;AACzB,YAAM,KAAK,MAAM,QAAQ,IAAI;AAAA,QAC3B,KAAK,KAAK,mBAAmB,KAAK,MAAM;AAAA,QACxC,KAAK,KAAK,mBAAmB,KAAK,MAAM;AAAA,MAC1C,CAAC;AACD,YAAM,aAAa,GAAG;AACtB,YAAM,aAAa,GAAG;AACtB,aAAO,qBAAqB,uBAAuB,YAAY,UAAU;AAAA,IAC3E,WAAW,WAAW,MAAM;AAC1B,aAAO,KAAK,qBAAqB,MAAM;AAAA,IACzC,OAAO;AACL,YAAMT,QAAO,aAAa,cAAc,KAAK;AAC7C,aAAO,KAAK,MAAM,gCAAgC,SAASA,KAAI;AAAA,IACjE;AACA,QAAI,qBAAqB,MAAM;AAC7B,WAAK,8BAA8B,iBAAiB;AAAA,IACtD;AACA,QAAI,WAAW,MAAM;AACnB,YAAM,KAAK,KAAK,MAAM;AACtB,mBAAa,IAAI,MAAM,GAAG,aAAa,OAAO,CAAC;AAAA,IACjD;AACA,UAAM,YAAY,KAAK,qBAAqB,QAAQ,IAAI;AACxD,UAAM,cAAc,KAAK,YAAY,IAAI,MAAM;AAC/C,SAAK,YAAY,OAAO,MAAM;AAC9B,gBAAY,QAAQ,CAAC,YAAY,QAAQ,SAAS,CAAC;AACnD,QAAI,KAAK,gBAAgB,IAAI,MAAM,GAAG;AACpC,WAAK,gBAAgB,OAAO,MAAM;AAClC,UAAI,KAAK,YAAY,MAAM,GAAG;AAC5B,eAAO,EAAE,aAAa,QAAQ,IAAI;AAAA,MACpC;AACA,WAAK;AAAA,IACP;AACA,WAAO;AAAA,EACT;AAAA,EACA,UAAU,QAAQM,WAAU,CAAC,GAAG;AAC9B,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,UAAM,EAAE,QAAQ,OAAO,OAAO,QAAQ,OAAO,UAAU,QAAQ,IAAI;AACnE,QAAI,UAAU,aAAa;AACzB,YAAM,IAAI,MAAM,uDAAuD;AAAA,IACzE;AACA,QAAI,UAAU,MAAM;AAClB,UAAI;AACJ,UAAI,UAAU;AACZ,kBAAU,IAAI,qBAAqB,OAAO,KAAK;AAAA,MACjD,OAAO;AACL,kBAAU,IAAI,eAAe,OAAO,KAAK;AAAA,MAC3C;AACA,YAAM,MAAM,KAAK,gBAAgB,SAAS,CAAC,EAAE,QAAQ,OAAO,MAAM,CAAC,GAAG,KAAK;AAC3E,YAAM,eAAe,KAAK,UAAU,KAAKA,QAAO;AAChD,WAAK,8BAA8B,GAAG;AACtC,aAAO;AAAA,IACT;AACA,QAAI,WAAW,MAAM;AACnB,UAAI,UAAU,MAAM;AAClB,cAAM,IAAI,MAAM,gCAAgC;AAAA,MAClD,OAAO;AACL,cAAM,IAAI,MAAM,iCAAiC;AAAA,MACnD;AAAA,IACF;AACA,UAAM,YAAY,KAAK,OAAO,QAAQA,SAAQ,cAAc;AAC5D,UAAM,YAAY,OAAO,EAAE,yBAAyB,SAAS;AAC7D,UAAM,UAAU,KAAK,QAAQ,IAAI,UAAU,MAAM;AACjD,WAAO,OAAO,OAAO,EAAE,UAAU,GAAG,QAAQ,OAAO;AAAA,EACrD;AAAA,EACA,WAAW,IAAI;AACb,UAAM,OAAO,KAAK,SAAS,GAAG,MAAM;AACpC,QAAI,GAAG,UAAU,UAAU;AACzB,UAAI;AACF,cAAM,UAAU,KAAK,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC;AAC5D,eAAO,OAAO,GAAG,OAAO,GAAG,OAAO,OAAO;AAAA,MAC3C,SAAS,IAAP;AACA,cAAM,IAAI,MAAM,kDAAkD;AAAA,MACpE;AAAA,IACF;AACA,WAAO,OAAO,GAAG,OAAO,GAAG,OAAO,IAAI;AAAA,EACxC;AAAA,EACA,uBAAuB,QAAQ;AAC7B,QAAI,UAAU,MAAM;AAClB;AAAA,IACF;AACA,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,YAAM,MAAM,OAAO;AACnB,UAAI,CAAC,iBAAiB,GAAG,GAAG;AAC1B,YAAI,IAAI,EAAE,QAAQ,8BAA8B,GAAG;AACjD,gBAAM,MAAM,aAAa,kJAAkJ;AAAA,QAC7K;AACA,cAAM,MAAM,aAAa,2CAA2C;AAAA,MACtE;AAAA,IACF;AAAA,EACF;AAAA,EACA,qBAAqB,QAAQ;AAC3B,UAAM,EAAE,OAAO,OAAO,SAAS,IAAI,KAAK,QAAQ,IAAI,MAAM;AAC1D,UAAMN,QAAO,aAAa,cAAc,KAAK;AAC7C,QAAI,IAAI,EAAE,QAAQ,8BAA8B,GAAG;AACjD,YAAM,YAAY,KAAK,OAAO,MAAM;AACpC,YAAM,WAAW,KAAK,QAAQ,IAAI,UAAU,MAAM;AAClD,YAAM,QAAQ,KAAK,MAAM,gCAAgC,SAAS,QAAQ,SAAS,GAAG,iBAAiB,KAAK,CAAC,EAAE,SAAS,GAAGA,KAAI;AAC/H,WAAK,8BAA8B,SAAS;AAC5C,aAAO;AAAA,IACT;AACA,UAAM,yBAAyB,IAAI,EAAE,QAAQ,YAAY,KAAK,aAAa;AAC3E,UAAM,cAAc,yBAAyB,aAAa,KAAK,IAAI;AACnE,UAAM,UAAU,yBAAyB,IAAI,yBAAyB,WAAW,IAAI,IAAI,mBAAmB,WAAW;AACvH,UAAM,SAAS,KAAK,gBAAgB,SAAS,CAAC,EAAE,OAAO,aAAa,OAAO,OAAO,CAAC,GAAG,SAAS;AAC/F,UAAM,UAAU,KAAK,QAAQ,IAAI,OAAO,MAAM;AAC9C,UAAM,OAAO,KAAK,MAAM,gDAAgD,QAAQ,QAAQ,SAAS,QAAQ,SAAS,IAAI,QAAQ,SAAS,EAAE,EAAE,SAAS,GAAGA,KAAI;AAC3J,SAAK,8BAA8B,MAAM;AACzC,WAAO;AAAA,EACT;AAAA,EACA,iBAAiB;AACf,WAAO,IAAI,EAAE,UAAU,+CAA+C,IAAI;AAAA,EAC5E;AAAA,EACA,KAAK,GAAG;AACN,UAAM,kBAAkB,KAAK;AAC7B,UAAM,kBAAkB,CAAC;AACzB,QAAI,gBAAgB;AACpB,QAAI,KAAK,sBAAsB,MAAM;AACnC,WAAK,qBAAqB;AAC1B,sBAAgB;AAAA,IAClB,OAAO;AACL,WAAK,aAAa,KAAK,eAAe;AAAA,IACxC;AACA,SAAK,eAAe;AACpB,MAAE;AACF,UAAM,8BAA8B,aAAa,QAAQ,KAAK,aAAa,IAAI,CAAC,MAAM,EAAE,KAAK,CAAC,EAAE,OAAO,CAAC,MAAM,KAAK,IAAI;AACvH,UAAM,4BAA4B,aAAa,QAAQ,KAAK,aAAa,IAAI,CAAC,MAAM,EAAE,IAAI,CAAC,EAAE,OAAO,CAAC,MAAM,KAAK,IAAI;AACpH,SAAK,eAAe;AACpB,QAAI,eAAe;AACjB,WAAK,qBAAqB;AAAA,IAC5B;AACA,UAAM,MAAM;AAAA,MACV,cAAc,KAAK;AAAA,MACnB,gBAAgB,KAAK;AAAA,MACrB,UAAU;AAAA,MACV,QAAQ;AAAA,IACV;AACA,YAAQ,YAAY;AAClB,UAAI,IAAI,EAAE,UAAU,+CAA+C,IAAI,GAAG;AACxE,cAAM,WAAW,MAAM,QAAQ,IAAI,2BAA2B;AAC9D,YAAI,cAAc,aAAa,IAAI,QAAQ;AAC3C,YAAI,yBAAyB,MAAM,SAAS,IAAI,CAAC,GAAG,QAAQ,EAAE,MAAM,0BAA0B,KAAK,IAAI,EAAE,EAAE,EAAE,IAAI,CAAC,MAAM,GAAG,EAAE,SAAS,EAAE,IAAI,EAAE,KAAK,IAAI;AAAA,MACzJ,OAAO;AACL,YAAI,cAAc;AAAA,UAChB,OAAO;AAAA,QACT;AAAA,MACF;AACA,WAAK,eAAe;AACpB,WAAK,iBAAiB;AACtB,aAAO;AAAA,IACT,GAAG;AAAA,EACL;AAAA,EACA,SAAS;AACP,WAAO;AAAA,MACL,YAAY;AAAA,MACZ,eAAe,KAAK;AAAA,MACpB,wBAAwB,KAAK,eAAe;AAAA,MAC5C,mBAAmB,KAAK,eAAe;AAAA,IACzC;AAAA,EACF;AAAA,EACA,aAAa;AACX,QAAI,IAAI,EAAE,UAAU,+CAA+C,IAAI,GAAG;AACxE,aAAO,KAAK,MAAM,WAAW;AAAA,IAC/B;AACA,WAAO,EAAE,SAAS,aAAa,IAAI,GAAG,OAAO,KAAK;AAAA,EACpD;AAAA,EACA,SAAS,OAAO;AACd,QAAI,IAAI,EAAE,UAAU,+CAA+C,IAAI,GAAG;AACxE,WAAK,MAAM,SAAS;AACpB,aAAO;AAAA,IACT;AACA,UAAM,QAAQ,aAAa,IAAI;AAC/B,WAAO;AAAA,EACT;AAAA,EACA,MAAM,aAAa,OAAO;AACxB,QAAI,IAAI,EAAE,UAAU,+CAA+C,IAAI,GAAG;AACxE,aAAO,KAAK,MAAM,uBAAuB,KAAK;AAAA,IAChD;AACA,UAAM,aAAa;AACnB,WAAO,WAAW,QAAQ,WAAW;AAAA,EACvC;AAAA,EACA,YAAY,QAAQ,QAAQ,OAAO;AACjC,QAAI,KAAK,gBAAgB,IAAI,MAAM,GAAG;AACpC,aAAO;AAAA,IACT;AACA,QAAI,CAAC,KAAK,QAAQ,IAAI,MAAM,GAAG;AAC7B,aAAO;AAAA,IACT;AACA,QAAI,OAAO;AACT,WAAK,QAAQ,IAAI,MAAM,EAAE,WAAW;AAAA,IACtC,OAAO;AACL,WAAK,QAAQ,IAAI,MAAM,EAAE;AAAA,IAC3B;AACA,QAAI,CAAC,SAAS,KAAK,QAAQ,IAAI,MAAM,EAAE,WAAW,GAAG;AACnD,aAAO;AAAA,IACT;AACA,QAAI,KAAK,YAAY,IAAI,MAAM,GAAG;AAChC,WAAK,gBAAgB,IAAI,MAAM;AAC/B,WAAK;AACL,aAAO;AAAA,IACT;AACA,SAAK,eAAe,MAAM;AAC1B,UAAM,EAAE,mBAAmB,IAAI,KAAK,QAAQ,IAAI,MAAM;AACtD,QAAI,sBAAsB,MAAM;AAC9B,WAAK,YAAY,mBAAmB,KAAK,QAAQ,KAAK;AACtD,WAAK,YAAY,mBAAmB,KAAK,QAAQ,KAAK;AAAA,IACxD;AACA,SAAK,QAAQ,OAAO,MAAM;AAC1B,WAAO;AAAA,EACT;AAAA,EACA,eAAe,QAAQ;AACrB,UAAM,EAAE,SAAS,OAAO,UAAU,OAAO,UAAU,OAAO,OAAO,IAAI,KAAK,QAAQ,IAAI,MAAM;AAC5F,UAAM,MAAM,UAAU,OAAO,cAAc;AAC3C,UAAM,WAAW,KAAK,aAAa,IAAI,GAAG;AAC1C,QAAI,WAAW,GAAG;AAChB,WAAK,aAAa,IAAI,KAAK,WAAW,CAAC;AAAA,IACzC,OAAO;AACL,WAAK,aAAa,OAAO,GAAG;AAC5B,UAAI,WAAW,MAAM;AACnB,aAAK,iBAAiB,KAAK,aAAa,UAAU,KAAK;AACvD,aAAK,eAAe,eAAe,SAAS,UAAU,OAAO,QAAQ;AAAA,MACvE;AAAA,IACF;AACA,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,YAAQ,UAAU;AAClB,YAAQ,WAAW;AACnB,YAAQ,WAAW;AACnB,YAAQ,QAAQ;AAAA,EAClB;AAAA,EACA,WAAW,QAAQ;AACjB,SAAK,YAAY,MAAM;AACvB,WAAO,KAAK,QAAQ,IAAI,MAAM,EAAE,QAAQ;AAAA,EAC1C;AAAA,EACA,YAAY,QAAQ;AAClB,WAAO,KAAK,QAAQ,IAAI,MAAM;AAAA,EAChC;AAAA,EACA,mBAAmB,QAAQ,gBAAgB,4BAA4B;AACrE,WAAO,IAAI,EAAE,QAAQ,mBAAmB,KAAK,OAAO,MAAM,CAAC,WAAW,KAAK,QAAQ,IAAI,OAAO,MAAM,EAAE,WAAW,QAAQ,aAAa,cAAc,OAAO,KAAK,IAAI,aAAa;AAAA,EACnL;AAAA,EACA,kBAAkB;AAChB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,WAAW;AACf,yBAAqB,KAAK,uEAAuE;AACjG,UAAM,WAAW,UAAU,SAAS;AACpC,WAAO,WAAW,UAAU,OAAO,QAAQ;AAAA,EAC7C;AAAA,EACA,cAAc,GAAG,KAAK,OAAO;AAC3B,UAAM,UAAU,IAAI,qBAAqB,EAAE,OAAO,GAAG;AACrD,UAAM,UAAU,KAAK,cAAc,SAAS,CAAC,CAAC,GAAG,KAAK;AACtD,WAAO,OAAO,EAAE,yBAAyB,OAAO;AAAA,EAClD;AAAA,EACA,IAAI,GAAG;AACL,QAAI,KAAK,mBAAmB,CAAC,CAAC,CAAC,KAAK,EAAE,UAAU,aAAa;AAC3D,YAAM,YAAY,iBAAiB,KAAK,QAAQ,IAAI,EAAE,MAAM,EAAE,MAAM;AACpE,aAAO,KAAK,WAAW,EAAE,OAAO,EAAE,OAAO,SAAS;AAAA,IACpD;AACA,QAAI,IAAI,EAAE,QAAQ,6BAA6B,GAAG;AAChD,aAAO,KAAK,cAAc,GAAG,KAAK,EAAE,KAAK;AAAA,IAC3C;AACA,UAAM,UAAU,IAAI,eAAe,EAAE,OAAO,GAAG;AAC/C,UAAM,UAAU,KAAK,cAAc,SAAS,CAAC,CAAC,CAAC;AAC/C,WAAO,OAAO,EAAE,yBAAyB,OAAO;AAAA,EAClD;AAAA,EACA,eAAe,OAAO,OAAO,QAAQ;AACnC,QAAI;AACJ,QAAI,UAAU,YAAY,UAAU,QAAQ,OAAO,SAAS,KAAK,aAAa,SAAS,OAAO,EAAE,GAAG;AACjG,YAAM,gBAAgB,OAAO,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC;AACpE,eAAS,KAAK,MAAM,eAAe,OAAO,KAAK;AAAA,IACjD,OAAO;AACL,eAAS,KAAK,MAAM,QAAQ,OAAO,KAAK;AAAA,IAC1C;AACA,SAAK,QAAQ,IAAI,MAAM,EAAE,QAAQ;AACjC,WAAO,EAAE,QAAQ,OAAO,MAAM;AAAA,EAChC;AAAA,EACA,WAAW,OAAO,OAAO,QAAQ;AAC/B,WAAO,OAAO,EAAE,yBAAyB,KAAK,eAAe,OAAO,OAAO,MAAM,GAAG,IAAI;AAAA,EAC1F;AAAA,EACA,aAAa,QAAQ;AACnB,UAAM,UAAU,IAAI,cAAc,OAAO,KAAK;AAC9C,WAAO,KAAK,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO,KAAK;AAAA,EAC7D;AAAA,EACA,WAAW,QAAQ;AACjB,UAAM,UAAU,IAAI,YAAY,OAAO,KAAK;AAC5C,UAAM,8BAA8B;AACpC,WAAO,KAAK,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO,OAAO,MAAM,2BAA2B;AAAA,EAChG;AAAA,EACA,cAAc,QAAQ,YAAY;AAChC,UAAM,eAAe;AAAA,MACnB,YAAY,OAAO,KAAK;AAAA,MACxB,GAAG,YAAY,OAAO,KAAK;AAAA,IAC7B;AACA,UAAM,UAAU;AAAA,MACd,OAAO,OAAO;AAAA,MACd,OAAO;AAAA,MACP,QAAQ,OAAO;AAAA,IACjB;AACA,UAAM,iBAAiB;AAAA,MACrB,YAAY,UAAU;AAAA,MACtB,GAAG,YAAY,UAAU;AAAA,IAC3B;AACA,UAAM,UAAU,IAAI,qBAAqB,gBAAgB,YAAY;AACrE,UAAM,gCAAgC;AACtC,UAAM,eAAe,CAAC,YAAY;AAClC,UAAM,SAAS,KAAK,gBAAgB,SAAS,CAAC,OAAO,GAAG,OAAO,OAAO,cAAc,6BAA6B;AACjH,WAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO,YAAY,OAAO,OAAO,MAAM;AAAA,EACzE;AAAA,EACA,OAAO,QAAQ,gBAAgB;AAC7B,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,UAAM,EAAE,UAAU,OAAO,MAAM,IAAI;AACnC,QAAI,kBAAkB,MAAM;AAC1B,YAAMA,QAAO,aAAa,cAAc,KAAK;AAC7C,YAAM,UAAU,eAAe,KAAK,eAAe,KAAK;AACxD,mBAAa,OAAOA,SAAQ,SAAS,MAAM,2GAA2G;AAAA,IACxJ;AACA,UAAM,YAAY,aAAa,KAAK;AACpC,QAAI;AACJ,QAAI,UAAU;AACZ,gBAAU,IAAI,0BAA0B,SAAS;AAAA,IACnD,OAAO;AACL,gBAAU,IAAI,oBAAoB,SAAS;AAAA,IAC7C;AACA,UAAM,gCAAgC;AACtC,UAAM,eAAe,CAAC,kBAAkB,OAAO,iBAAiB,iBAAiB,SAAS,CAAC;AAC3F,UAAM,MAAM,KAAK,gBAAgB,SAAS,CAAC,EAAE,OAAO,WAAW,OAAO,OAAO,CAAC,GAAG,OAAO,cAAc,+BAA+B,cAAc;AACnJ,WAAO,EAAE,OAAO,OAAO,QAAQ,IAAI,OAAO;AAAA,EAC5C;AAAA,EACA,gBAAgB,SAAS,QAAQ,aAAa,qBAAqB,gCAAgC,OAAO,gBAAgB;AACxH,UAAM,SAAS,KAAK,eAAe,QAAQ,aAAa,WAAW;AACnE,UAAM,UAAU,KAAK,QAAQ,IAAI,OAAO,MAAM;AAC9C,QAAI,QAAQ,cAAc;AACxB,cAAQ,WAAW;AAAA,IACrB;AACA,QAAI,QAAQ,qBAAqB,cAAc,OAAO;AACpD,YAAM,aAAa,kBAAkB,OAAO,iBAAiB,iBAAiB,QAAQ,WAAW;AACjG,cAAQ,WAAW,WAAW,IAAI,CAAC,MAAM,IAAI,CAAC;AAAA,IAChD;AACA,QAAI,QAAQ,eAAe,MAAM;AAC/B,cAAQ,QAAQ,QAAQ;AAAA,IAC1B;AACA,QAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,cAAQ,SAAS,aAAa,uBAAuB,OAAO,OAAO,CAAC;AACpE,aAAO;AAAA,IACT;AACA,UAAM,gBAAgB,CAAC;AACvB,UAAM,aAAa,OAAO,IAAI,CAAC,WAAW;AACxC,UAAI,OAAO,UAAU,aAAa;AAChC,cAAM,IAAI,MAAM,iIAAiI;AAAA,MACnJ;AACA,UAAI,UAAU,KAAK,QAAQ,IAAI,OAAO,MAAM;AAC5C,UAAI,QAAQ,WAAW,MAAM;AAC3B,YAAI,CAAC,QAAQ,gBAAgB,aAAa,cAAc,OAAO,KAAK,KAAK,IAAI,EAAE,UAAU,2BAA2B,GAAG;AACrH,iBAAO;AAAA,YACL,OAAO,OAAO;AAAA,YACd,SAAS;AAAA,YACT,WAAW;AAAA,YACX,eAAe,QAAQ;AAAA,UACzB;AAAA,QACF;AACA,YAAI,QAAQ,cAAc;AACxB,kBAAQ,WAAW;AACnB,kBAAQ,QAAQ,OAAO;AAAA,QACzB;AAAA,MACF;AACA,WAAK,YAAY,OAAO,MAAM;AAC9B,UAAI,CAAC,CAAC,QAAQ,aAAa,CAAC,CAAC,QAAQ,cAAc;AACjD,iBAAS,QAAQ,WAAW,KAAK,aAAa,MAAM,IAAI,KAAK,WAAW,MAAM;AAC9E,sBAAc,KAAK,MAAM;AACzB,kBAAU,KAAK,QAAQ,IAAI,OAAO,MAAM;AAAA,MAC1C,WAAW,QAAQ,YAAY,CAAC,cAAc,QAAQ,OAAO,OAAO,KAAK,GAAG;AAC1E,cAAM,aAAa;AACnB,cAAM,cAAc,OAAO;AAC3B,eAAO,QAAQ,QAAQ;AACvB,iBAAS,KAAK,cAAc,QAAQ,WAAW;AAC/C,sBAAc,KAAK,MAAM;AACzB,kBAAU,KAAK,QAAQ,IAAI,OAAO,MAAM;AACxC,mBAAW,QAAQ;AAAA,MACrB;AACA,aAAO,EAAE,OAAO,OAAO,OAAO,SAAS,WAAW,MAAM;AAAA,IAC1D,CAAC;AACD,SAAK,YAAY,OAAO,MAAM;AAC9B,UAAM,aAAa,EAAE,OAAO,OAAO,OAAO,SAAS,SAAS,WAAW,MAAM;AAC7E,UAAM,MAAM,cAAc,SAAS,YAAY,UAAU;AACzD,UAAM,SAAS,KAAK,iBAAiB,KAAK,MAAM;AAC9C,aAAO,eAAe,KAAK,OAAO,SAAS,YAAY,UAAU;AAAA,IACnE,CAAC;AACD,UAAM,oBAAoB,KAAK,gBAAgB;AAC/C,QAAI;AACJ,QAAI,mBAAmB;AACrB,cAAQ,KAAK,WAAW;AAAA,IAC1B;AACA,QAAI,CAAC,IAAI,EAAE,IAAI,qBAAqB,GAAG;AACrC,iBAAW,KAAK,OAAO,QAAQ,YAAY,YAAY,mBAAmB;AAAA,IAC5E;AACA,kBAAc,QAAQ,CAAC,SAAS,KAAK,8BAA8B,IAAI,CAAC;AACxE,QAAI,mBAAmB;AACrB,cAAQ,KAAK,SAAS,KAAK;AAC3B,WAAK,aAAa,KAAK,EAAE,MAAM,QAAQ,YAAY,MAAM,OAAO,KAAK,aAAa,KAAK,EAAE,CAAC;AAAA,IAC5F;AACA,UAAM,mBAAmB,IAAI,EAAE,IAAI,uBAAuB;AAC1D,QAAI,mBAAmB,GAAG;AACxB,YAAM,QAAQ,aAAa,IAAI;AAC/B,UAAI,QAAQ,KAAK,kBAAkB,kBAAkB;AACnD,aAAK,MAAM,GAAG,MAAM;AACpB,aAAK,kBAAkB;AAAA,MACzB;AAAA,IACF;AACA,QAAI,CAAC,IAAI,EAAE,QAAQ,qBAAqB,KAAK,QAAQ,YAAY,kCAAkC,OAAO;AACxG,YAAM,WAAW,KAAK,aAAa,MAAM;AACzC,WAAK,8BAA8B,MAAM;AACzC,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT;AAAA,EACA,cAAc,SAAS,QAAQ,aAAa,qBAAqB,gCAAgC,OAAO;AACtG,kBAAc,eAAe,OAAO,GAAG;AACvC,UAAM,UAAU,KAAK,gBAAgB,SAAS,QAAQ,aAAa,qBAAqB,6BAA6B;AACrH,WAAO;AAAA,EACT;AAAA,EACA,iBAAiB,KAAK,WAAW;AAC/B,QAAI,EAAE,OAAO,KAAK,cAAc;AAC9B,WAAK,YAAY,OAAO,UAAU;AAAA,IACpC;AACA,WAAO,KAAK,YAAY;AAAA,EAC1B;AAAA,EACA,oBAAoB;AAClB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,UAAU;AACR,QAAI,KAAK,UAAU;AACjB;AAAA,IACF;AACA,QAAI,CAAC,IAAI,EAAE,QAAQ,SAAS,GAAG;AAC7B,YAAM,UAAU,OAAO,KAAK,KAAK,WAAW;AAC5C,cAAQ,QAAQ,CAAC,QAAQ;AACvB,aAAK,MAAM,cAAc,KAAK,YAAY,KAAK,YAAY;AAC3D,eAAO,KAAK,YAAY;AAAA,MAC1B,CAAC;AAAA,IACH;AACA,SAAK,eAAe,QAAQ;AAC5B,QAAI,KAAK,UAAU,SAAS,OAAO,sBAAsB,eAAe,KAAK,kBAAkB,oBAAoB;AACjH,WAAK,OAAO,OAAO;AAAA,IACrB,OAAO;AACL,WAAK,SAAS;AAAA,IAChB;AACA,QAAI,KAAK,qBAAqB;AAC5B,WAAK,MAAM,UAAU;AACrB,WAAK,MAAM,QAAQ;AAAA,IACrB;AACA,SAAK,WAAW;AAAA,EAClB;AAAA,EACA,iBAAiB;AACf,QAAI,KAAK,uBAAuB,MAAM;AACpC,WAAK,sBAAsB,KAAK,MAAM;AACpC,YAAI,CAAC,IAAI,EAAE,IAAI,8BAA8B,GAAG;AAC9C,gBAAM,YAAY,IAAI,EAAE,QAAQ,OAAO;AACvC,cAAI,EAAE,IAAI,SAAS,KAAK;AACxB,gBAAM,sBAAsB,KAAK,IAAI,OAAO,IAAI,CAAC,EAAE,SAAS,EAAE;AAC9D,cAAI,EAAE,IAAI,SAAS,SAAS;AAC5B,cAAI,sBAAsB,GAAG;AAC3B,mBAAO;AAAA,UACT;AAAA,QACF;AACA,eAAO;AAAA,MACT,CAAC;AAAA,IACH;AACA,WAAO,KAAK;AAAA,EACd;AAAA,EACA,UAAU;AACR,WAAO,KAAK,eAAe,MAAM,KAAK,mBAAmB;AAAA,EAC3D;AAAA,EACA,YAAY,QAAQ;AAClB,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,UAAM,EAAE,OAAO,OAAO,QAAQ,SAAS,OAAO,SAAS,IAAI;AAC3D,QAAI,WAAW,MAAM;AACnB;AAAA,IACF;AACA,UAAM,oBAAoB,KAAK,gBAAgB;AAC/C,QAAI;AACJ,QAAI,mBAAmB;AACrB,cAAQ,aAAa,IAAI;AAAA,IAC3B;AACA,QAAI,WAAW,QAAQ;AACvB,QAAI,YAAY,MAAM;AACpB,iBAAW,gCAAgC,OAAO,QAAQ;AAC1D,cAAQ,WAAW;AAAA,IACrB;AACA,QAAI,UAAU,MAAM;AAClB,YAAM,YAAY,aAAa,KAAK;AACpC,UAAI;AACJ,UAAI,QAAQ,SAAS,IAAI,SAAS,SAAS;AAC3C,YAAM,cAAc,kBAAkB,cAAc,kBAAkB;AACtE,UAAI,YAAY,CAAC,aAAa;AAC5B,SAAC,OAAO,MAAM,IAAI,uCAAuC,SAAS,IAAI,SAAS,EAAE;AAAA,MACnF;AACA,UAAI,UAAU;AACZ,kBAAU,IAAI,0BAA0B,WAAW,WAAW;AAAA,MAChE,OAAO;AACL,kBAAU,IAAI,oBAAoB,WAAW,WAAW;AAAA,MAC1D;AACA,YAAM,yBAAyB,cAAc,CAAC,QAAQ,KAAK,IAAI;AAC/D,YAAM,uBAAuB,KAAK,eAAe,wBAAwB,KAAK;AAC9E,YAAM,wBAAwB,KAAK,QAAQ,IAAI,qBAAqB,MAAM;AAC1E,UAAI,aAAa;AACf,8BAAsB,QAAQ,aAAa;AAAA,MAC7C,OAAO;AACL,8BAAsB,QAAQ,aAAa;AAAA,MAC7C;AACA,4BAAsB,WAAW;AACjC,WAAK,MAAM,2BAA2B,KAAK,WAAW,qBAAqB,MAAM,GAAG,OAAO,QAAQ,MAAM;AACzG,YAAM,eAAe,CAAC,CAAC,QAAQ,KAAK,CAAC;AACrC,YAAM,wBAAwB;AAC9B,YAAM,sBAAsB,KAAK,gBAAgB,SAAS,CAAC,oBAAoB,GAAG,OAAO,cAAc,qBAAqB;AAC5H,YAAM,gBAAgB,KAAK,QAAQ,IAAI,oBAAoB,MAAM;AACjE,cAAQ,WAAW,cAAc;AACjC,cAAQ,WAAW,cAAc;AACjC,cAAQ,QAAQ,cAAc;AAC9B,UAAI,CAAC,IAAI,EAAE,IAAI,qBAAqB,GAAG;AACrC,gBAAQ,UAAU,cAAc;AAChC,gBAAQ,SAAS;AACjB,aAAK,QAAQ,OAAO,oBAAoB,MAAM;AAAA,MAChD,OAAO;AACL,aAAK,YAAY,oBAAoB,MAAM;AAAA,MAC7C;AACA,WAAK,8BAA8B,oBAAoB;AACvD,UAAI,mBAAmB;AACrB,aAAK,gBAAgB,aAAa,IAAI,IAAI;AAAA,MAC5C;AAAA,IACF,OAAO;AACL,YAAM,aAAa,KAAK,eAAe,UAAU,OAAO,OAAO,QAAQ;AACvE,cAAQ,UAAU;AAAA,IACpB;AAAA,EACF;AAAA,EACA,qBAAqB,QAAQ,eAAe;AAC1C,UAAM,UAAU,KAAK,QAAQ,IAAI,MAAM;AACvC,UAAM,EAAE,MAAM,IAAI;AAClB,SAAK,eAAe,MAAM;AAC1B,QAAI,iBAAiB,MAAM;AACzB,cAAQ,SAAS,oBAAoB,eAAe,KAAK;AAAA,IAC3D;AACA,WAAO,QAAQ;AAAA,EACjB;AAAA,EACA,eAAe,UAAU,SAAS,OAAO,UAAU;AACjD,SAAK,iBAAiB,KAAK,aAAa,UAAU,KAAK;AACvD,QAAI,CAAC,KAAK,qBAAqB,KAAK,gBAAgB,KAAK,qBAAqB,OAAO,MAAM;AACzF,YAAM,MAAM,KAAK,gBAAgB,OAAO,MAAM,QAAQ,CAAC;AACvD,WAAK,oBAAoB;AACzB,cAAQ,KAAK,6BAA6B,yCAAyC;AAAA,IACrF;AACA,WAAO,KAAK,eAAe,eAAe,UAAU,SAAS,QAAQ;AAAA,EACvE;AAAA,EACA,aAAa,OAAO,OAAO;AACzB,WAAO,MAAM,KAAK,MAAM,KAAK,aAAa,gBAAgB,KAAK;AAAA,EACjE;AAAA,EACA,yBAAyB;AACvB,eAAW,CAAC,EAAE,MAAM,KAAK,OAAO,QAAQ,KAAK,WAAW,GAAG;AACzD,WAAK,iBAAiB,MAAM;AAAA,IAC9B;AAAA,EACF;AAAA,EACA,MAAM,8BAA8B;AAClC,UAAM,KAAK,CAAC;AACZ,QAAI,KAAK,MAAM,8BAA8B;AAC3C,iBAAW,CAAC,EAAE,MAAM,KAAK,OAAO,QAAQ,KAAK,WAAW,GAAG;AACzD,WAAG,KAAK,KAAK,sBAAsB,MAAM,CAAC;AAAA,MAC5C;AACA,aAAO,QAAQ,IAAI,EAAE;AAAA,IACvB,OAAO;AACL,iBAAW,CAAC,EAAE,MAAM,KAAK,OAAO,QAAQ,KAAK,WAAW,GAAG;AACzD,cAAM,KAAK,IAAI,QAAQ,CAAC,YAAY;AAClC,cAAI;AACF,iBAAK,iBAAiB,MAAM;AAC5B,oBAAQ,IAAI;AAAA,UACd,SAAS,OAAP;AACA,kBAAM;AAAA,UACR;AAAA,QACF,CAAC;AACD,WAAG,KAAK,EAAE;AAAA,MACZ;AACA,aAAO,QAAQ,IAAI,EAAE;AAAA,IACvB;AAAA,EACF;AAAA,EACA,MAAM,sBAAsB,QAAQ;AAClC,QAAI,KAAK,MAAM,GAAG,oBAAoB,OAAO,cAAc,KAAK,MAAM,6BAA6B,qBAAqB,GAAG;AACzH,aAAO,KAAK,iBAAiB,MAAM;AAAA,IACrC,OAAO;AACL,YAAM,UAAU;AAChB,aAAO,KAAK,sBAAsB,MAAM;AAAA,IAC1C;AAAA,EACF;AAAA,EACA,iBAAiB,QAAQ;AACvB,QAAI,KAAK,MAAM,GAAG,oBAAoB,OAAO,cAAc,KAAK,MAAM,GAAG,WAAW,MAAM,OAAO;AAC/F,cAAQ,IAAI,KAAK,MAAM,GAAG,kBAAkB,OAAO,YAAY,CAAC;AAChE,UAAI,KAAK,MAAM,GAAG,mBAAmB,OAAO,gBAAgB,KAAK,MAAM,GAAG,cAAc,MAAM,OAAO;AACnG,kCAA0B,OAAO,QAAQ,KAAK,MAAM,GAAG,iBAAiB,OAAO,cAAc,CAAC;AAC9F,cAAM,IAAI,MAAM,oCAAoC;AAAA,MACtD;AACA,YAAM,IAAI,MAAM,6CAA6C;AAAA,IAC/D;AACA,WAAO;AAAA,EACT;AAAA,EACA,sBAAsB;AACpB,eAAW,CAAC,EAAE,MAAM,KAAK,OAAO,QAAQ,KAAK,WAAW,GAAG;AACzD,YAAM,EAAE,kBAAkB,wBAAwB,QAAQ,QAAQ,mBAAmB,sBAAsB,kBAAkB,yBAAyB,oBAAoB,IAAI,oBAAoB,KAAK,OAAO,OAAO,SAAS,OAAO,YAAY;AACjP,aAAO,mBAAmB;AAC1B,aAAO,yBAAyB;AAChC,aAAO,SAAS;AAChB,aAAO,SAAS;AAChB,aAAO,oBAAoB;AAC3B,aAAO,uBAAuB;AAC9B,aAAO,mBAAmB;AAC1B,aAAO,0BAA0B;AACjC,aAAO,sBAAsB;AAAA,IAC/B;AAAA,EACF;AACF;AACA,iBAAiB,aAAa;AAC9B,SAAS,oBAAoB,GAAG,OAAO;AACrC,MAAI,UAAU,aAAa,UAAU,aAAa;AAChD,WAAO;AAAA,EACT,WAAW,UAAU,WAAW,UAAU,QAAQ;AAChD,UAAM,SAAS,UAAU,UAAU,IAAI,WAAW,EAAE,MAAM,IAAI,IAAI,WAAW,EAAE,MAAM;AACrF,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,EAAE,IAAI;AACzC,aAAO,MAAM,KAAK,MAAM,EAAE,GAAG;AAAA,IAC/B;AACA,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,iBAAiB,OAAO;AAAA,EAC1C;AACF;AAGA,IAAI,WAAW;AAGf,SAAS,iBAAiB;AACxB,MAAI,EAAE,IAAI,4BAA4B,IAAI;AAC5C;AAGA,IAAI,oBAAoB,UAAU,GAAG;AACnC,kBAAgB,SAAS,MAAM,IAAI,iBAAiB,GAAG,CAAC;AAC1D;AACA,IAAI,QAAQ,EAAE,eAAe;AAG7B,IAAI,qBAAqB;AAAA;AAAA;AAAA;AAIzB,IAAI,kBAAkB,MAAM;AAAA,EAC1B,YAAY,KAAK,QAAQ,QAAQ;AAC/B,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,cAAc,qBAAqB,2BAA2B,QAAQ,MAAM;AACjF,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EASR;AACF;AAGA,IAAI,qBAAqB;AAAA;AAAA;AAAA;AAAA;AAAA;AAMzB,IAAI,wBAAwB,MAAM;AAAA,EAChC,YAAY,KAAK,QAAQ,QAAQ,mBAAmB,OAAO;AACzD,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,uBAAuB;AAC5B,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc,qBAAqB,2BAA2B,QAAQ,MAAM;AACjF,UAAM,OAAO,KAAK,YAAY;AAC9B,SAAK,sBAAsB,iBAAiB,IAAI;AAChD,QAAI,yBAAyB;AAC7B,QAAI,kBAAkB;AACpB,UAAI,SAAS,KAAK,aAAa,cAAc,KAAK,WAAW,MAAM,GAAG;AACpE,iCAAyB;AAAA;AAAA;AAAA;AAAA;AAAA,MAK3B,OAAO;AACL,cAAM,QAAQ,kBAAkB,IAAI;AACpC,iCAAyB;AAAA,YACrB;AAAA;AAEJ,YAAI,SAAS,GAAG;AACd,cAAI,KAAK,qBAAqB;AAC5B,sCAA0B;AAAA;AAAA;AAAA;AAAA;AAAA,UAK5B,OAAO;AACL,sCAA0B;AAAA,yCACG,KAAK,YAAY;AAAA;AAAA;AAAA;AAAA,UAIhD;AAAA,QACF,OAAO;AACL,gBAAM,WAAW,YAAY,UAAU,IAAI;AAC3C,cAAI,KAAK,qBAAqB;AAC5B,sCAA0B;AAAA;AAAA,iBAErB,SAAS,OAAO,uBAAuB;AAAA;AAAA,iBAEvC,SAAS,OAAO,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA,UAK9C,OAAO;AACL,sCAA0B;AAAA;AAAA,iBAErB,SAAS,OAAO,cAAc,KAAK,YAAY,OAAO;AAAA;AAAA,iBAEtD,SAAS,OAAO,cAAc,KAAK,YAAY,OAAO;AAAA;AAAA;AAAA;AAAA;AAAA,UAK7D;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAQA;AAAA;AAAA;AAAA;AAAA;AAAA,EAKR;AACF;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,WAAS,OAAO,EAAE,MAAM;AACxB,SAAO,EAAE,QAAQ,EAAE,QAAQ,OAAO,EAAE,OAAO,OAAO,EAAE,MAAM;AAC5D;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,MAAM,OAAO,MAAM,MAAM,IAAI;AACrC,QAAM,cAAc,SAAS,eAAe,MAAM,OAAO,WAAW;AACpE,QAAM,WAAW,SAAS,QAAQ,IAAI,YAAY,MAAM;AACxD,QAAM,iBAAiB,UAAU,EAAE,QAAQ,EAAE,GAAG,MAAM,GAAG,SAAS,SAAS,CAAC;AAC5E,QAAM,iBAAiB,UAAU,EAAE,QAAQ,EAAE,GAAG,MAAM,GAAG,SAAS,SAAS,CAAC;AAC5E,WAAS,qBAAqB,EAAE,MAAM,gBAAgB,MAAM,eAAe;AAC3E,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY;AAChB,IAAI,mBAAmB;AAAA;AAAA;AAAA;AAIvB,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAAsB,OAAM,IAAI;AAClB,QAAM,SAAS,SAAS,eAAe,CAAC,GAAG,WAAW,aAAa,kBAAkBA,QAAO,SAAS,CAAC;AACtG,QAAM,UAAU,IAAI,EAAE,QAAQ,8BAA8B,IAAI,IAAI,sBAAsB,kBAAkB,EAAE,OAAO,OAAO,KAAK,IAAI,IAAI,gBAAgB,WAAW,EAAE,OAAO,OAAO,KAAK;AACzL,QAAM,SAAS,SAAS,gBAAgB,SAAS,CAAC,GAAG,MAAM,GAAG,SAAS;AACvE,WAAS,8BAA8B,MAAM;AAC7C,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ;AACZ,IAAI,eAAe;AAAA;AAAA;AAAA;AAInB,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,GAAG,OAAAA,OAAM,IAAI;AACrB,QAAM,UAAU,IAAI,EAAE,QAAQ,8BAA8B,IAAI,IAAI,sBAAsB,cAAc,EAAE,OAAOA,OAAM,KAAK,IAAI,IAAI,gBAAgB,OAAO,EAAE,OAAOA,OAAM,KAAK;AAC/K,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAGA,MAAK,GAAG,SAAS;AAChE;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,0BAA0B;AAC9B,IAAI,2BAA2B;AAAA;AAAA;AAAA;AAI/B,IAAI,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAMtC,SAAS,iBAAiB,EAAE,WAAW,iBAAiB,eAAe,MAAM,GAAG;AAC9E,SAAO,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AACxC,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,eAAe;AACrB,UAAM,SAAS,SAAS,EAAE;AAC1B,QAAI,aAAa,mBAAmB,CAAC,CAAC,CAAC,KAAK,iBAAiB,MAAM;AACjE,YAAM,QAAQ,aAAa,QAAQ,IAAI,EAAE,MAAM;AAC/C,YAAM,YAAY,cAAc,MAAM,QAAQ,MAAM;AACpD,aAAO,aAAa,eAAe,EAAE,OAAO,QAAQ,SAAS;AAAA,IAC/D;AACA,UAAM,yBAAyB,IAAI,EAAE,QAAQ,6BAA6B,KAAK,mBAAmB;AAClG,QAAI;AACJ,QAAI,wBAAwB;AAC1B,gBAAU,IAAI,qBAAqB,EAAE,OAAO,eAAe;AAAA,IAC7D,OAAO;AACL,gBAAU,IAAI,eAAe,EAAE,OAAO,SAAS;AAAA,IACjD;AACA,WAAO,aAAa,gBAAgB,SAAS,CAAC,CAAC,GAAG,MAAM;AAAA,EAC1D;AACF;AACA,SAAS,kBAAkB,EAAE,WAAW,iBAAiB,mBAAmB,OAAO,kBAAkB,OAAO,eAAe,MAAM,GAAG;AAClI,SAAO,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AACxC,UAAM,EAAE,GAAG,EAAE,IAAI;AACjB,UAAM,eAAe;AACrB,QAAI,mBAAmB,EAAE,UAAU,aAAa;AAC9C,YAAM,QAAQ,aAAa,QAAQ,IAAI,EAAE,MAAM;AAC/C,YAAM,QAAQ,aAAa,QAAQ,IAAI,EAAE,MAAM;AAC/C,YAAM,CAAC,OAAO,KAAK,IAAI;AAAA,QACrB,CAAC,MAAM,mBAAmB,MAAM,MAAM,mBAAmB,IAAI;AAAA,QAC7D,CAAC,MAAM,mBAAmB,MAAM,MAAM,mBAAmB,IAAI;AAAA,MAC/D,EAAE,IAAI,CAAC,iBAAiB;AACtB,cAAM,CAAC,OAAO,KAAK,IAAI;AACvB,cAAM,UAAU;AAAA,UACd,QAAQ,MAAM;AAAA,UACd,OAAO,MAAM;AAAA,UACb,OAAO,EAAE;AAAA,QACX;AACA,cAAM,UAAU;AAAA,UACd,QAAQ,MAAM;AAAA,UACd,OAAO,MAAM;AAAA,UACb,OAAO,EAAE;AAAA,QACX;AACA,cAAM,WAAW,IAAI,gBAAgB,WAAW,EAAE,OAAO,EAAE,KAAK;AAChE,eAAO,aAAa,gBAAgB,UAAU,CAAC,SAAS,OAAO,GAAG,WAAW,MAAM,OAAO,MAAM,KAAK,CAAC;AAAA,MACxG,CAAC;AACD,YAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,MAAM,OAAO,MAAM,MAAM,GAAG,SAAS,aAAa,CAAC;AAC9F,mBAAa,8BAA8B,KAAK;AAChD,mBAAa,8BAA8B,KAAK;AAChD,aAAO;AAAA,IACT;AACA,UAAM,SAAS,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AACnD,SAAK,EAAE,UAAU,YAAY,EAAE,UAAU,YAAY,aAAa,mBAAmB,CAAC,GAAG,CAAC,CAAC,MAAM,iBAAiB,MAAM;AACtH,YAAM,QAAQ,aAAa,QAAQ,IAAI,EAAE,MAAM,EAAE;AACjD,YAAM,QAAQ,aAAa,QAAQ,IAAI,EAAE,MAAM,EAAE;AACjD,YAAM,eAAe,EAAE,UAAU,WAAW,qBAAqB,uBAAuB,KAAK,IAAI;AACjG,YAAM,eAAe,EAAE,UAAU,WAAW,qBAAqB,uBAAuB,KAAK,IAAI;AACjG,YAAM,CAAC,WAAW,QAAQ,IAAI,cAAc,EAAE,OAAO,EAAE,OAAO,cAAc,cAAc,MAAM;AAChG,YAAM,MAAM,aAAa,eAAe,UAAU,MAAM;AACxD,YAAM,UAAU,aAAa,QAAQ,IAAI,IAAI,MAAM;AACnD,cAAQ,SAAS;AACjB,aAAO;AAAA,IACT;AACA,UAAM,yBAAyB,IAAI,EAAE,QAAQ,8BAA8B,KAAK,mBAAmB;AACnG,QAAI;AACJ,QAAI,wBAAwB;AAC1B,gBAAU,IAAI,sBAAsB,iBAAiB,EAAE,OAAO,EAAE,OAAO,gBAAgB;AAAA,IACzF,OAAO;AACL,gBAAU,IAAI,gBAAgB,WAAW,EAAE,OAAO,EAAE,KAAK;AAAA,IAC3D;AACA,WAAO,aAAa,gBAAgB,SAAS,CAAC,GAAG,CAAC,GAAG,MAAM;AAAA,EAC7D;AACF;AACA,SAAS,6BAA6B,aAAa,SAAS,OAAO;AACjE,MAAI,gBAAgB,UAAU;AAC5B,QAAI,QAAQ;AACV,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT,WAAW,gBAAgB,QAAQ;AACjC,QAAI,QAAQ;AACV,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT,WAAW,gBAAgB,OAAO;AAChC,QAAI,QAAQ;AACV,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT,WAAW,gBAAgB,SAAS;AAClC,QAAI,QAAQ;AACV,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT,WAAW,gBAAgB,SAAS;AAClC,QAAI,QAAQ;AACV,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT,WAAW,gBAAgB,aAAa;AACtC,QAAI,QAAQ;AACV,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT,WAAW,gBAAgB,WAAW;AACpC,QAAI,QAAQ;AACV,aAAO;AAAA,IACT;AACA,WAAO;AAAA,EACT;AACA,QAAM,IAAI,MAAM,cAAc,6DAA6D;AAC7F;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,QAAQ,QAAQ,aAAa,aAAa,OAAO,aAAa,OAAO,UAAU,OAAO,cAAc,MAAM,qBAAqB,OAAO,yBAAyB,OAAO;AAChL,SAAK,gBAAgB,CAAC,WAAW,SAAS;AAC1C,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,UAAM,YAAY,aAAa,OAAO,KAAK,OAAO;AAClD,UAAM,wBAAwB,KAAK,KAAK,YAAY,CAAC;AACrD,UAAM,UAAU,aAAa,gBAAgB;AAC7C,UAAM,UAAU,aAAa,gBAAgB;AAC7C,UAAM,WAAW,aAAa,CAAC,UAAU,QAAQ,IAAI,CAAC,UAAU,QAAQ;AACxE,UAAM,WAAW,aAAa,CAAC,UAAU,QAAQ,IAAI,CAAC,UAAU,QAAQ;AACxE,QAAI,oBAAoB,IAAI,yBAAyB;AACrD,QAAI,aAAa;AACf,UAAI,oBAAoB;AACtB,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,WAAW,wBAAwB;AACjC,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,OAAO;AACL,4BAAoB;AAAA,YAChB;AAAA;AAAA,MAEN;AACA,+BAAyB;AAAA,IAC3B;AACA,UAAM,iBAAiB,UAAU,oCAAoC;AACrE,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,oBAAoB;AACtB,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,QAAI,wBAAwB;AAC1B,WAAK,cAAc,KAAK,gBAAgB;AAAA,IAC1C;AACA,QAAI,gBAAgB;AACpB,QAAI,gBAAgB;AACpB,QAAI,OAAO,KAAK,OAAO,IAAI;AACzB,sBAAgB,wBAAwB,OAAO,KAAK;AAAA,IACtD,WAAW,OAAO,KAAK,OAAO,IAAI;AAChC,sBAAgB,wBAAwB,OAAO,KAAK;AAAA,IACtD;AACA,SAAK,WAAW;AAAA,QACZ;AAAA;AAAA,sCAE8B;AAAA;AAAA;AAAA;AAAA,8BAIR;AAAA,yBACL;AAAA,yBACA;AAAA,wCACe;AAAA,wCACA;AAAA;AAAA;AAAA;AAAA,uBAIjB,SAAS,QAAQ,SAAS;AAAA,uBAC1B,SAAS,QAAQ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UASvC;AAAA;AAAA,UAEA;AAAA;AAAA;AAAA;AAAA;AAAA,EAKR;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,MAAM;AAAA,EACN,MAAM;AACR;AACA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,KAAK,QAAQ,QAAQ;AAC/B,SAAK,gBAAgB,CAAC,SAAS,SAAS,SAAS,OAAO;AACxD,SAAK,cAAc,qBAAqB,2BAA2B,QAAQ,MAAM;AACjF,SAAK,WAAW;AAAA;AAAA;AAAA,UAGV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAWR;AACF;AAGA,IAAI,MAAM;AACV,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,GAAG,EAAE,IAAI;AACjB,QAAM,QAAQ,qBAAqB,WAAW,EAAE,OAAO,EAAE,KAAK;AAC9D,MAAI,EAAE,UAAU,aAAa;AAC3B,UAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,UAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,UAAM,cAAc,IAAI,uBAAuB,iBAAiB,MAAM,EAAE,OAAO,EAAE,KAAK;AACtF,UAAM,cAAc,IAAI,uBAAuB,iBAAiB,MAAM,EAAE,OAAO,EAAE,KAAK;AACtF,UAAM,UAAU;AAAA,MACd;AAAA,QACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,QACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,QACrC,OAAO,EAAE;AAAA,MACX;AAAA,MACA;AAAA,QACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,QACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,QACrC,OAAO,EAAE;AAAA,MACX;AAAA,MACA;AAAA,QACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,QACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,QACrC,OAAO,EAAE;AAAA,MACX;AAAA,MACA;AAAA,QACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,QACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,QACrC,OAAO,EAAE;AAAA,MACX;AAAA,IACF;AACA,UAAM,WAAW,SAAS,gBAAgB,aAAa,SAAS,SAAS;AACzE,UAAM,WAAW,SAAS,gBAAgB,aAAa,SAAS,SAAS;AACzE,UAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,MAAM,UAAU,MAAM,SAAS,GAAG,SAAS,SAAS,CAAC;AAChG,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,QAAQ;AAC/C,WAAO;AAAA,EACT;AACA,MAAI,SAAS,mBAAmB,CAAC,GAAG,CAAC,CAAC,GAAG;AACvC,UAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,UAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,UAAM,CAAC,WAAW,QAAQ,IAAI,gBAAgB,EAAE,OAAO,EAAE,OAAO,MAAM,QAAQ,MAAM,QAAQ,KAAK;AACjG,UAAM,MAAM,SAAS,eAAe,UAAU,KAAK;AACnD,UAAM,UAAU,SAAS,QAAQ,IAAI,IAAI,MAAM;AAC/C,YAAQ,SAAS;AACjB,WAAO;AAAA,EACT;AACA,MAAI;AACJ,MAAI,IAAI,EAAE,QAAQ,8BAA8B,GAAG;AACjD,cAAU,IAAI,sBAAsB,KAAK,EAAE,OAAO,EAAE,KAAK;AAAA,EAC3D,OAAO;AACL,cAAU,IAAI,gBAAgB,KAAK,EAAE,OAAO,EAAE,KAAK;AAAA,EACrD;AACA,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,CAAC,GAAG,KAAK;AACxD;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,QAAQ,YAAY,UAAU;AACnD,QAAM,eAAe;AAAA,IACnB,YAAY,OAAO,KAAK;AAAA,IACxB,GAAG,YAAY,OAAO,KAAK;AAAA,EAC7B;AACA,QAAM,UAAU;AAAA,IACd,OAAO,OAAO;AAAA,IACd,OAAO;AAAA,IACP,QAAQ,OAAO;AAAA,EACjB;AACA,QAAM,iBAAiB;AAAA,IACrB,YAAY,UAAU;AAAA,IACtB,GAAG,YAAY,UAAU;AAAA,EAC3B;AACA,QAAM,UAAU,IAAI,qBAAqB,gBAAgB,YAAY;AACrE,QAAM,gCAAgC;AACtC,QAAM,eAAe,CAAC,YAAY;AAClC,QAAM,SAAS,SAAS,gBAAgB,SAAS,CAAC,OAAO,GAAG,OAAO,OAAO,cAAc,6BAA6B;AACrH,SAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO,YAAY,OAAO,OAAO,MAAM;AACzE;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,eAAe;AACrB,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,SAAS,aAAa,uBAAuB,OAAO,KAAK;AAC/D,QAAM,SAAS,aAAa,cAAc,MAAM;AAChD,eAAa,OAAO,UAAU,QAAQ,MAAM,kBAAkB,eAAe,sCAAsC,EAAE,cAAc,oFAAoF;AACvN,QAAM,WAAW,aAAa,QAAQ,IAAI,EAAE,MAAM;AAClD,MAAI,SAAS,YAAY,CAAC,cAAc,EAAE,OAAO,MAAM,KAAK,EAAE,SAAS,YAAY,QAAQ,cAAc,SAAS,OAAO,MAAM,IAAI;AACjI,WAAO,cAAc,GAAG,QAAQ,YAAY;AAAA,EAC9C;AACA,eAAa,OAAO,EAAE,MAAM;AAC5B,SAAO,EAAE,QAAQ,EAAE,QAAQ,OAAO,QAAQ,OAAO,EAAE,MAAM;AAC3D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,YAAY,SAAS;AAC/B,SAAK,gBAAgB,CAAC,GAAG;AACzB,UAAM,EAAE,YAAY,WAAW,QAAQ,QAAQ,IAAI;AACnD,SAAK,cAAc,CAAC,WAAW,OAAO;AACtC,UAAM,wBAAwB,KAAK,MAAM,aAAa,CAAC,IAAI;AAC3D,UAAM,0BAA0B,aAAa;AAC7C,QAAI,gBAAgB;AACpB,QAAI,WAAW,MAAM;AACnB,YAAM,cAAc,IAAI;AACxB,sBAAgB,4BAA4B,aAAa,MAAM,WAAW,IAAI,YAAY,YAAY,CAAC,IAAI;AAAA,IAC7G;AACA,QAAI,mBAAmB;AACvB,QAAI,SAAS,aAAa,GAAG;AAC3B,yBAAmB;AAAA,oCACW;AAAA;AAAA;AAAA;AAAA,IAIhC;AACA,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA,UAIV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAQwB;AAAA;AAAA;AAAA;AAAA,8BAIJ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YASlB;AAAA;AAAA;AAAA,iCAGqB;AAAA,cACnB,4BAA4B;AAAA;AAAA;AAAA,YAG9B;AAAA,qBACS,4BAA4B;AAAA;AAAA;AAAA;AAAA;AAAA,YAKrC;AAAA,qBACS,4BAA4B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAMrC;AAAA;AAAA;AAAA;AAAA;AAAA,EAKV;AACF;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,YAAY,YAAY;AAClC,SAAK,gBAAgB,CAAC,GAAG;AACzB,UAAM,EAAE,YAAY,WAAW,QAAQ,QAAQ,IAAI;AACnD,SAAK,cAAc,CAAC,WAAW,OAAO;AACtC,QAAI,sBAAsB;AAC1B,QAAI,YAAY;AAChB,QAAI,eAAe,QAAQ;AACzB,4BAAsB;AAAA,IACxB,WAAW,eAAe,OAAO;AAC/B,4BAAsB;AACtB,kBAAY;AAAA,IACd,WAAW,eAAe,OAAO;AAC/B,4BAAsB;AACtB,kBAAY;AAAA,IACd;AACA,QAAI,cAAc,GAAG,cAAc,cAAc;AACjD,QAAI,eAAe,OAAO;AACxB,oBAAc;AAAA,IAChB,WAAW,eAAe,QAAQ;AAChC,oBAAc;AAAA,IAChB,WAAW,eAAe,OAAO;AAC/B,oBAAc;AAAA,IAChB,WAAW,eAAe,OAAO;AAC/B,oBAAc;AAAA,IAChB;AACA,UAAM,wBAAwB,KAAK,MAAM,aAAa,CAAC,IAAI;AAC3D,UAAM,0BAA0B,aAAa;AAC7C,QAAI,gBAAgB;AAAA,YACZ,eAAe;AAAA;AAAA,mBAER,eAAe;AAAA;AAAA;AAAA;AAAA,wBAIV;AAAA,cACV,eAAe,YAAY,eAAe;AAAA,0BAC9B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAQtB,QAAI,UAAU;AACd,QAAI,eAAe,OAAO;AACxB,4BAAsB;AACtB,sBAAgB;AAAA;AAAA;AAAA;AAAA;AAKhB,gBAAU;AAAA,IACZ,WAAW,eAAe,OAAO;AAC/B,4BAAsB;AACtB,sBAAgB;AAAA;AAAA;AAAA;AAAA;AAKhB,gBAAU;AAAA,IACZ;AACA,QAAI,mBAAmB;AACvB,QAAI,SAAS,aAAa,GAAG;AAC3B,yBAAmB;AAAA,oCACW;AAAA;AAAA;AAAA;AAAA,IAIhC;AACA,SAAK,WAAW;AAAA,0CACsB;AAAA;AAAA;AAAA;AAAA,UAIhC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAQwB;AAAA;AAAA,kCAEA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAMJ;AAAA;AAAA,YAElB,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAOpB;AAAA;AAAA;AAAA,iCAGqB;AAAA,cACnB,4BAA4B;AAAA,YAC9B,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAOpB;AAAA,qBACS,4BAA4B;AAAA,YACrC,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAOpB;AAAA,qBACS,4BAA4B;AAAA,YACrC,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAOpB;AAAA;AAAA,oBAEQ;AAAA;AAAA;AAAA,EAGlB;AACF;AAGA,SAAS,mBAAmB,SAAS;AACnC,QAAM,SAAS,CAAC;AAChB,SAAO,OAAO,WAAW,KAAK,OAAO,OAAO,SAAS,GAAG,YAAY,GAAG;AACrE,UAAM,UAAU,OAAO,SAAS,OAAO,OAAO,SAAS,GAAG,UAAU,QAAQ;AAC5E,UAAM,aAAa,qBAAqB,yBAAyB,OAAO;AACxE,WAAO,KAAK;AAAA,MACV,QAAQ;AAAA,MACR;AAAA,MACA,SAAS,KAAK,KAAK,UAAU,UAAU;AAAA,IACzC,CAAC;AAAA,EACH;AACA,SAAO;AACT;AACA,SAAS,OAAO,GAAG,OAAO,eAAe,UAAU;AACjD,QAAM,kBAAkB,mBAAmB,EAAE,KAAK;AAClD,MAAI,SAAS;AACb,WAAS,KAAK,GAAG,KAAK,gBAAgB,QAAQ,MAAM;AAClD,UAAM,EAAE,QAAQ,YAAY,QAAQ,IAAI,gBAAgB;AACxD,QAAI;AACJ,QAAI;AACJ,QAAI,kBAAkB,QAAQ;AAC5B,gBAAU,OAAO,IAAI,IAAI,YAAY,EAAE,YAAY,QAAQ,WAAW,EAAE,MAAM,IAAI,QAAQ,GAAG,MAAM,IAAI,IAAI,YAAY,EAAE,YAAY,QAAQ,WAAW,EAAE,MAAM,IAAI,QAAQ,CAAC;AAAA,IAC/K,OAAO;AACL,gBAAU,IAAI,cAAc,EAAE,YAAY,QAAQ,WAAW,EAAE,MAAM,IAAI,QAAQ,GAAG,aAAa;AAAA,IACnG;AACA,qBAAiB;AACjB,aAAS,SAAS,gBAAgB,SAAS,CAAC,MAAM,GAAG,KAAK;AAC1D,QAAI,eAAe,WAAW,EAAE,QAAQ;AACtC,eAAS,8BAA8B,cAAc;AAAA,IACvD;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,QAAQ,QAAQ;AAC1B,SAAK,gBAAgB,CAAC,GAAG;AACzB,UAAM,cAAc,IAAI,MAAM,OAAO,MAAM;AAC3C,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,MAAM;AAC9C,kBAAY,MAAM,OAAO,OAAO;AAAA,IAClC;AACA,SAAK,cAAc;AACnB,SAAK,OAAO,YAAY;AACxB,UAAM,QAAQ,kBAAkB,KAAK,IAAI;AACzC,UAAM,WAAW,kBAAkB,MAAM;AACzC,SAAK,WAAW;AAAA;AAAA,QAEZ;AAAA,uBACe;AAAA;AAAA;AAAA,EAGrB;AACF;AACA,SAAS,kBAAkB,QAAQ;AACjC,QAAM,OAAO,OAAO;AACpB,MAAI,OAAO,GAAG;AACZ,UAAM,MAAM,sBAAsB,2BAA2B;AAAA,EAC/D;AACA,QAAM,gBAAgB,CAAC,WAAW,WAAW,WAAW,WAAW,WAAW,SAAS;AACvF,QAAM,iBAAiB,IAAI,MAAM,IAAI;AACrC,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,mBAAe,OAAO,OAAO,cAAc;AAAA,EAC7C;AACA,SAAO,eAAe,KAAK;AAC7B;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,QAAQ,QAAQ;AAC1B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,UAAM,cAAc,IAAI,MAAM,OAAO,MAAM;AAC3C,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,MAAM;AAC9C,kBAAY,MAAM,OAAO,OAAO;AAAA,IAClC;AACA,SAAK,cAAc;AACnB,SAAK,OAAO,YAAY;AACxB,QAAI,KAAK,OAAO,GAAG;AACjB,YAAM,MAAM,6BAA6B,KAAK,4BAA4B;AAAA,IAC5E;AACA,UAAM,QAAQ,kBAAkB,KAAK,IAAI;AACzC,UAAM,cAAc,eAAe,MAAM,KAAK,IAAI;AAClD,UAAM,gBAAgB,IAAI,MAAM,KAAK,IAAI;AACzC,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,oBAAc,OAAO,OAAO,YAAY;AAAA,IAC1C;AACA,UAAM,YAAY,QAAQ,cAAc,MAAM,EAAE,EAAE,KAAK;AACvD,UAAM,aAAa,KAAK,YAAY,KAAK,OAAO,QAAQ,YAAY,KAAK,OAAO;AAChF,UAAM,OAAO,mBAAmB,cAAc,KAAK,OAAO;AAC1D,SAAK,WAAW;AAAA;AAAA,QAEZ;AAAA;AAAA,oBAEY;AAAA,WACT;AAAA,sBACW;AAAA;AAAA,UAEZ,YAAY,KAAK,OAAO;AAAA,aACrB,YAAY,KAAK,OAAO,QAAQ,YAAY,KAAK,OAAO;AAAA,sBAC/C;AAAA,aACT;AAAA,wBACW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAMtB;AACF;AAGA,SAAS,eAAe,GAAG,MAAM,UAAU;AACzC,QAAM,UAAU,IAAI,EAAE,QAAQ,6BAA6B,IAAI,IAAI,uBAAuB,EAAE,OAAO,IAAI,IAAI,IAAI,iBAAiB,EAAE,OAAO,IAAI;AAC7I,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACvD;AAGA,SAAS,QAAQ,GAAG,MAAM,UAAU,UAAU;AAC5C,QAAM,mBAAmB;AACzB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,aAAa,eAAe,kBAAkB,EAAE,KAAK;AACtE,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,QAAM,uBAAuB,gBAAgB;AAC7C,MAAI,WAAW;AACf,MAAI,sBAAsB;AACxB,eAAW,eAAe,GAAG,cAAc,QAAQ;AACnD,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAAA,EACjE;AACA,uBAAqB,2BAA2B,OAAO,MAAM,KAAK;AAClE,QAAM,CAAC,aAAa,WAAW,IAAI,qBAAqB,0BAA0B,SAAS,OAAO,IAAI;AACtG,MAAI,WAAW;AACf,MAAI,UAAU;AACZ,eAAW,qBAAqB,qBAAqB,aAAa,QAAQ;AAAA,EAC5E;AACA,QAAM,SAAS,aAAa,cAAc,WAAW;AACrD,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,YAAY,QAAQ;AAC1B,QAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,OAAO,EAAE,OAAO,CAAC,WAAW,MAAM,EAAE,GAAG,SAAS,SAAS,CAAC;AACpH,QAAM,UAAU,WAAW,EAAE,KAAK;AAClC,QAAM,UAAU,OAAO,eAAe,SAAS,OAAO,QAAQ;AAC9D,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AAC9F,WAAS,8BAA8B,aAAa;AACpD,WAAS,8BAA8B,OAAO;AAC9C,MAAI,sBAAsB;AACxB,aAAS,8BAA8B,QAAQ;AAAA,EACjD;AACA,SAAO;AACT;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,SAAO,QAAQ,GAAG,MAAM,UAAU,QAAQ;AAC5C;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,eAAe;AACrB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,IAAI,MAAM,KAAK;AAChC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,aAAS,MAAM,EAAE,MAAM,KAAK;AAAA,EAC9B;AACA,MAAI;AACJ,MAAI,aAAa,mBAAmB,CAAC,CAAC,CAAC,GAAG;AACxC,UAAM,WAAW,aAAa,QAAQ,IAAI,EAAE,MAAM;AAClD,UAAM,SAAS,SAAS;AACxB,UAAM,YAAY,iBAAiB,QAAQ,EAAE,OAAO,EAAE,OAAO,MAAM,QAAQ;AAC3E,UAAM,aAAa,eAAe,UAAU,EAAE,KAAK;AACnD,UAAM,UAAU,aAAa,QAAQ,IAAI,IAAI,MAAM;AACnD,YAAQ,SAAS;AAAA,EACnB,OAAO;AACL,UAAM,eAAe,GAAG,MAAM,YAAY;AAAA,EAC5C;AACA,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,8BAA8B;AAClC,SAAS,gBAAgB,EAAE,GAAG,GAAG,YAAY,YAAY,SAAS,UAAU,OAAO,MAAM,yBAAyB,MAAM,iBAAiB,GAAG,YAAY,cAAc,KAAK,GAAG;AAC5K,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,oBAAoB,uBAAuB,2BAA2B,EAAE,MAAM,MAAM,GAAG,EAAE,GAAG,EAAE,MAAM,MAAM,GAAG,EAAE,CAAC;AACtH,QAAM,WAAW,kBAAkB,OAAO,CAAC,aAAa,WAAW,CAAC;AACpE,eAAa,OAAO,gBAAgB,aAAa,MAAM,kCAAkC,qBAAqB,uCAAuC,EAAE,aAAa,EAAE,wBAAwB,6BAA6B,wBAAwB;AACnP,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,gBAAgB,CAAC,KAAK,GAAG;AAC/B,QAAM,WAAW,KAAK,IAAI,WAAW,SAAS;AAC9C,QAAM,YAAY,aAAa,IAAI,MAAM,KAAK,IAAI,MAAM;AACxD,QAAM,UAAU,QAAQ;AACxB,QAAM,4BAA4B,0BAA0B;AAC5D,QAAM,oBAAoB,gBAAgB;AAC1C,QAAM,kBAAkB,eAAe,OAAO,6BAA6B,aAAa,IAAI,IAAI;AAChG,QAAM,mBAAmB,WAAW,6BAA6B,qBAAqB,mBAAmB;AACzG,MAAI;AACJ,OAAK,gBAAgB,KAAK,gBAAgB,MAAM,YAAY,+BAA+B,qBAAqB,OAAO;AACrH,QAAI,OAAO;AACX,QAAI,OAAO;AACX,QAAI,YAAY;AACd,aAAO,WAAW,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,CAAC,GAAG,GAAG,CAAC,EAAE,EAAE,CAAC;AACvF,oBAAc,KAAK,IAAI;AAAA,IACzB;AACA,QAAI,YAAY;AACd,aAAO,WAAW,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,CAAC,GAAG,GAAG,CAAC,EAAE,EAAE,CAAC;AACvF,oBAAc,KAAK,IAAI;AAAA,IACzB;AACA,UAAM,iBAAiB,gBAAgB;AACvC,UAAM,iBAAiB,gBAAgB;AACvC,QAAI,SAAS;AACb,QAAI,gBAAgB;AAClB,eAAS,SAAS;AAAA,QAChB,QAAQ,EAAE,GAAG,KAAK;AAAA,QAClB,SAAS;AAAA,QACT,OAAO,EAAE,OAAO,CAAC,UAAU,WAAW,CAAC,EAAE;AAAA,MAC3C,CAAC;AACD,oBAAc,KAAK,MAAM;AAAA,IAC3B;AACA,UAAM,OAAO,gBAAgB,IAAI,IAAI;AACrC,QAAI,SAAS;AACb,QAAI,gBAAgB;AAClB,eAAS,SAAS;AAAA,QAChB,QAAQ,EAAE,GAAG,KAAK;AAAA,QAClB,SAAS;AAAA,QACT,OAAO,EAAE,OAAO,CAAC,UAAU,GAAG,SAAS,EAAE;AAAA,MAC3C,CAAC;AACD,oBAAc,KAAK,MAAM;AAAA,IAC3B;AACA,UAAM,UAAU,UAAU,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,OAAO,GAAG,SAAS,SAAS,CAAC;AACjF,UAAM,KAAK,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,UAAU,KAAK,EAAE,CAAC;AACzF,kBAAc,KAAK,OAAO;AAAA,EAC5B,OAAO;AACL,UAAM,QAAQ,WAAW,EAAE,OAAO,EAAE,KAAK;AACzC,UAAM,UAAU,IAAI,oBAAoB,UAAU,UAAU,CAAC,UAAU,aAAa,WAAW,GAAG,YAAY,YAAY,SAAS,iBAAiB,2BAA2B,iBAAiB;AAChM,UAAM,SAAS,CAAC,KAAK,GAAG;AACxB,QAAI,QAAQ,MAAM;AAChB,aAAO,KAAK,IAAI;AAAA,IAClB;AACA,QAAI,2BAA2B;AAC7B,aAAO,KAAK,sBAAsB;AAAA,IACpC;AACA,QAAI,mBAAmB;AACrB,YAAM,kBAAkB,SAAS,eAAe,CAAC,GAAG,WAAW,aAAa,kBAAkB,gBAAgB,SAAS,CAAC;AACxH,aAAO,KAAK,eAAe;AAC3B,oBAAc,KAAK,eAAe;AAAA,IACpC;AACA,UAAM,SAAS,gBAAgB,SAAS,QAAQ,KAAK;AAAA,EACvD;AACA,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAClG,gBAAc,KAAK,GAAG;AACtB,aAAW,MAAM,eAAe;AAC9B,aAAS,8BAA8B,EAAE;AAAA,EAC3C;AACA,SAAO;AACT;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,MAAM,uBAAuB,IAAI;AAC/C,QAAM,EAAE,YAAY,YAAY,YAAY,aAAa,eAAe,IAAI;AAC5E,SAAO,gBAAgB;AAAA,IACrB;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA,SAAS;AAAA,IACT;AAAA,IACA;AAAA,IACA;AAAA,IACA,YAAY;AAAA,EACd,CAAC;AACH;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AACX,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,KAAK,EAAE,UAAU,aAAa;AAC/D,UAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,UAAM,YAAY,iBAAiB,MAAM,MAAM;AAC/C,WAAO,SAAS,eAAe,EAAE,OAAO,EAAE,OAAO,SAAS;AAAA,EAC5D;AACA,MAAI;AACJ,MAAI,IAAI,EAAE,QAAQ,6BAA6B,GAAG;AAChD,cAAU,IAAI,qBAAqB,EAAE,OAAO,IAAI;AAAA,EAClD,OAAO;AACL,cAAU,IAAI,eAAe,EAAE,OAAO,IAAI;AAAA,EAC5C;AACA,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACvD;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAM/B,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,oBAAoB;AAAA;AAAA;AAGhC,IAAI,SAAS,iBAAiB,EAAE,WAAW,MAAM,CAAC;AAClD,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM;AACV,IAAI,gBAAgB,kBAAkB;AAAA,EACpC,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,iBAAiB;AAAA,EACjB,eAAe;AACjB,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,aAAa,QAAQ;AAC/B,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc;AACnB,SAAK,gBAAgB,OAAO,IAAI,CAAC,GAAG,OAAO,IAAI,IAAI;AACnD,UAAM,WAAW,CAAC;AAClB,SAAK,cAAc,QAAQ,CAAC,cAAc;AACxC,eAAS,KAAK,UAAU,kBAAkB,yBAAyB;AAAA,IACrE,CAAC;AACD,UAAM,YAAY,KAAK,cAAc,IAAI,CAAC,cAAc;AACtD,aAAO,IAAI;AAAA,IACb,CAAC,EAAE,KAAK,KAAK;AACb,SAAK,WAAW;AAAA;AAAA,UAEV,SAAS,KAAK,YAAY;AAAA;AAAA,yBAEX;AAAA;AAAA;AAAA;AAAA,EAIvB;AACF;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,aAAa,QAAQ;AAC/B,SAAK,cAAc,CAAC;AACpB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc;AACnB,SAAK,gBAAgB,OAAO,IAAI,CAAC,GAAG,OAAO,IAAI,IAAI;AACnD,UAAM,WAAW,CAAC;AAClB,SAAK,cAAc,QAAQ,CAAC,cAAc;AACxC,eAAS,KAAK,SAAS,kBAAkB,yBAAyB;AAAA,IACpE,CAAC;AACD,UAAM,YAAY,KAAK,cAAc,IAAI,CAAC,cAAc;AACtD,aAAO,IAAI;AAAA,IACb,CAAC,EAAE,KAAK,KAAK;AACb,SAAK,WAAW;AAAA;AAAA,UAEV,SAAS,KAAK,YAAY;AAAA;AAAA,wBAEZ;AAAA;AAAA;AAAA;AAAA,EAItB;AACF;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,UAAU;AAChB,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,GAAG,SAAS,SAAS,CAAC;AAAA,EACnE;AACA,MAAI,QAAQ,SAAS,IAAI,EAAE,IAAI,8BAA8B,GAAG;AAC9D,UAAM,WAAW,KAAK,MAAM,QAAQ,SAAS,CAAC;AAC9C,UAAM,WAAW,MAAM,EAAE,QAAQ,QAAQ,MAAM,GAAG,QAAQ,GAAG,SAAS,SAAS,CAAC;AAChF,UAAM,YAAY,MAAM,EAAE,QAAQ,QAAQ,MAAM,QAAQ,GAAG,SAAS,SAAS,CAAC;AAC9E,WAAO,MAAM,EAAE,QAAQ,CAAC,UAAU,SAAS,GAAG,SAAS,SAAS,CAAC;AAAA,EACnE;AACA,QAAM,QAAQ,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK,EAAE,OAAO,CAAC,IAAI,OAAO,WAAW,IAAI,EAAE,CAAC;AACjF,QAAM,SAAS,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK;AAC3C,QAAM,cAAc,IAAI,EAAE,QAAQ,YAAY;AAC9C,QAAM,UAAU,cAAc,IAAI,kBAAkB,QAAQ,GAAG,OAAO,MAAM,IAAI,IAAI,YAAY,QAAQ,GAAG,OAAO,MAAM;AACxH,SAAO,SAAS,gBAAgB,SAAS,SAAS,KAAK;AACzD;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,YAAY;AAChB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AAC1F,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAAA,EACjE;AACA,uBAAqB,2BAA2B,OAAO,MAAM,KAAK;AAClE,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,UAAU,OAAO,IAAI;AACpG,QAAM,SAAS,aAAa,cAAc,WAAW;AACrD,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,IAAI,MAAM,EAAE,EAAE,CAAC;AACpG,QAAM,UAAU,OAAO,KAAK,IAAI,OAAO,OAAO,QAAQ;AACtD,MAAI;AACJ,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,UAAU,QAAQ;AAC7E,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAAA,EAC1F,OAAO;AACL,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAAA,EAC1F;AACA,WAAS,8BAA8B,GAAG;AAC1C,WAAS,8BAA8B,OAAO;AAC9C,MAAI,gBAAgB,MAAM;AACxB,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,YAAY;AAChB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AAC1F,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAAA,EACjE;AACA,uBAAqB,2BAA2B,OAAO,MAAM,KAAK;AAClE,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,UAAU,OAAO,IAAI;AACpG,QAAM,SAAS,aAAa,cAAc,WAAW;AACrD,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,IAAI,MAAM,EAAE,EAAE,CAAC;AACpG,QAAM,UAAU,OAAO,KAAK,IAAI,OAAO,OAAO,QAAQ;AACtD,MAAI;AACJ,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,UAAU,QAAQ;AAC7E,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAAA,EAC1F,OAAO;AACL,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAAA,EAC1F;AACA,WAAS,8BAA8B,GAAG;AAC1C,WAAS,8BAA8B,OAAO;AAC9C,MAAI,gBAAgB,MAAM;AACxB,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,YAAY,KAAK,WAAW;AACtC,SAAK,gBAAgB,CAAC,GAAG;AACzB,UAAM,EAAE,YAAY,WAAW,QAAQ,IAAI;AAC3C,QAAI,CAAC,WAAW;AACd,WAAK,cAAc,KAAK,cAAc;AAAA,IACxC;AACA,SAAK,cAAc,CAAC,WAAW,OAAO;AACtC,UAAM,SAAS,QAAQ,QAAQ,MAAM;AACrC,UAAM,eAAe,YAAY,kBAAkB;AACnD,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,kCAKc;AAAA;AAAA;AAAA;AAAA;AAAA,8BAKJ;AAAA,wBACN;AAAA;AAAA,0BAEE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAQxB;AACF;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,OAAO,YAAY,KAAK,WAAW;AAC7C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,iBAAa,OAAO,MAAM,SAAS,GAAG,MAAM,aAAa,IAAI,OAAO,CAAC,EAAE,YAAY,IAAI,IAAI,MAAM,CAAC,2CAA2C;AAC7I,UAAM,SAAS,MAAM,MAAM,SAAS;AACpC,UAAM,UAAU,KAAK,KAAK,SAAS,UAAU;AAC7C,SAAK,cAAc,MAAM,MAAM,GAAG,EAAE;AACpC,QAAI,UAAU,GAAG;AACf,WAAK,YAAY,KAAK,OAAO;AAAA,IAC/B;AACA,QAAI,CAAC,WAAW;AACd,WAAK,cAAc,KAAK,cAAc;AAAA,IACxC;AACA,UAAM,WAAW,KAAK;AACtB,UAAM,OAAO,SAAS;AACtB,UAAM,QAAQ,kBAAkB,IAAI;AACpC,UAAM,UAAU,YAAY,UAAU,IAAI;AAC1C,QAAI;AACJ,QAAI;AACJ,QAAI,YAAY,GAAG;AACjB,mBAAa,OAAO;AACpB,YAAM,iBAAiB,kBAAkB,UAAU;AACnD,uBAAiB;AAAA,UACb,+BAA+B,kBAAkB,QAAQ,KAAK;AAAA,YAC5D,QAAQ,OAAO;AAAA,UACjB,+BAA+B,kBAAkB,QAAQ,KAAK;AAAA,YAC5D,QAAQ,OAAO;AAAA,UACjB,+BAA+B,kBAAkB,QAAQ,KAAK;AAAA,YAC5D,QAAQ,OAAO;AAAA,UACjB,+BAA+B,kBAAkB,QAAQ,KAAK;AAAA,YAC5D,QAAQ,OAAO;AAAA,IACvB,OAAO;AACL,mBAAa;AACb,uBAAiB;AAAA,UACb;AAAA,YACE,QAAQ,OAAO;AAAA,UACjB;AAAA,YACE,QAAQ,OAAO;AAAA,UACjB;AAAA,YACE,QAAQ,OAAO;AAAA,UACjB;AAAA,YACE,QAAQ,OAAO;AAAA,IACvB;AACA,UAAM,WAAW,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG,EAAE,MAAM,GAAG,UAAU;AACnE,UAAM,YAAY,MAAM,SAAS,aAAa;AAC9C,UAAM,cAAc,SAAS,IAAI,CAAC,MAAM,SAAS,CAAC;AAClD,UAAM,aAAa,YAAY,cAAc,aAAa,CAAC,EAAE,OAAO,SAAS;AAC7E,UAAM,aAAa,YAAY,cAAc,aAAa,CAAC,EAAE,OAAO,SAAS;AAC7E,UAAM,aAAa,YAAY,cAAc,aAAa,CAAC,EAAE,OAAO,SAAS;AAC7E,UAAM,aAAa,YAAY,cAAc,aAAa,CAAC,EAAE,OAAO,SAAS;AAC7E,UAAM,SAAS,QAAQ,QAAQ,gBAAgB;AAC/C,UAAM,oBAAoB,YAAY,KAAK;AAAA,sDACO,WAAW,KAAK;AAAA,sDAChB,WAAW,KAAK;AAAA,sDAChB,WAAW,KAAK;AAAA,sDAChB,WAAW,KAAK;AAClE,UAAM,aAAa;AAAA,0BACG,WAAW,KAAK;AAAA,uCACH,WAAW,KAAK;AAAA,uCAChB,WAAW,KAAK;AAAA,qDACF,WAAW,KAAK;AACjE,UAAM,gCAAgC,YAAY,KAAK;AAAA,qCACtB,YAAY,KAAK;AAAA,4CACV,SAAS,KAAK;AAAA,iDACT,SAAS,MAAM,EAAE,EAAE,KAAK;AAAA;AAErE,SAAK,WAAW;AAAA,0BACM,YAAY,KAAK;AAAA,iCACV,SAAS,KAAK;AAAA,sCACT,SAAS,MAAM,EAAE,EAAE,KAAK;AAAA;AAAA,QAEtD;AAAA;AAAA,UAEE;AAAA,4BACkB,QAAQ,OAAO,QAAQ,SAAS,OAAO,KAAK;AAAA,4BAC5C,QAAQ,OAAO,QAAQ,SAAS,OAAO,KAAK;AAAA,UAC9D;AAAA,yCAC+B,wBAAwB;AAAA,sBAC3C,wBAAwB,gBAAgB;AAAA;AAAA;AAAA,2BAGnC;AAAA;AAAA,8BAEG;AAAA;AAAA,YAElB;AAAA,6BACiB;AAAA;AAAA;AAAA,mBAGV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAYjB;AACF;AAGA,SAAS,UAAU,UAAU,GAAG,YAAY,eAAe,MAAM;AAC/D,MAAI,YAAY,EAAE,MAAM;AACxB,MAAI,SAAS,EAAE,MAAM;AACrB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,aAAa,MAAM;AAC/B,aAAS,aAAa,MAAM;AAAA,EAC9B;AACA,QAAM,aAAa,qBAAqB,yBAAyB,MAAM;AACvE,QAAM,aAAa,EAAE,YAAY,QAAQ,WAAW,SAAS,KAAK,KAAK,SAAS,UAAU,EAAE;AAC5F,QAAM,UAAU,IAAI,iBAAiB,YAAY,YAAY,gBAAgB,IAAI;AACjF,QAAM,SAAS,CAAC,CAAC;AACjB,MAAI,gBAAgB,MAAM;AACxB,WAAO,KAAK,YAAY;AAAA,EAC1B;AACA,QAAM,SAAS,SAAS,gBAAgB,SAAS,QAAQ,OAAO;AAChE,MAAI,OAAO,MAAM,OAAO,GAAG;AACzB,WAAO;AAAA,EACT;AACA,QAAM,SAAS,UAAU,UAAU,GAAG,YAAY,MAAM;AACxD,WAAS,8BAA8B,MAAM;AAC7C,SAAO;AACT;AACA,SAAS,gBAAgB,UAAU,GAAG,YAAY,eAAe,MAAM;AACrE,QAAM,UAAU,gBAAgB,OAAO,aAAa,QAAQ,EAAE;AAC9D,QAAM,SAAS,QAAQ,QAAQ,SAAS;AACxC,QAAM,aAAa,qBAAqB,yBAAyB,MAAM;AACvE,QAAM,UAAU,IAAI,uBAAuB,SAAS,YAAY,YAAY,gBAAgB,IAAI;AAChG,QAAM,SAAS,gBAAgB,OAAO,CAAC,CAAC,IAAI,CAAC,GAAG,YAAY;AAC5D,QAAM,SAAS,SAAS,gBAAgB,SAAS,QAAQ,OAAO;AAChE,MAAI,OAAO,MAAM,WAAW,EAAE,MAAM,QAAQ;AAC1C,UAAM,SAAS,gBAAgB,UAAU,GAAG,YAAY,MAAM;AAC9D,aAAS,8BAA8B,MAAM;AAC7C,WAAO;AAAA,EACT;AACA,SAAO;AACT;AACA,SAAS,gBAAgB,UAAU,GAAG,MAAM,YAAY;AACtD,QAAM,OAAO,CAAC,IAAI;AAClB,uBAAqB,2BAA2B,QAAQ,WAAW,OAAO,CAAC,EAAE,YAAY,IAAI,WAAW,MAAM,CAAC,GAAG,MAAM,EAAE,MAAM,MAAM;AACtI,MAAI,CAAC,IAAI,EAAE,QAAQ,mBAAmB,KAAK,EAAE,MAAM,UAAU,GAAG;AAC9D,UAAM,0BAA0B,CAAC;AACjC,UAAM,WAAW,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC9C,UAAM,YAAY,aAAa,QAAQ,SAAS;AAChD,QAAI,YAAY;AAChB,QAAI,WAAW;AACb,kBAAY,SAAS,aAAa,CAAC;AACnC,8BAAwB,KAAK,SAAS;AAAA,IACxC;AACA,UAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,UAAU,OAAO,IAAI;AACpG,UAAM,SAAS,aAAa,cAAc,WAAW;AACrD,UAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,IAAI,MAAM,EAAE,EAAE,CAAC;AACpG,4BAAwB,KAAK,GAAG;AAChC,UAAM,UAAU,UAAU,UAAU,KAAK,UAAU;AACnD,4BAAwB,KAAK,OAAO;AACpC,UAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACnG,4BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,WAAO;AAAA,EACT;AACA,SAAO,gBAAgB,UAAU,GAAG,UAAU;AAChD;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACpD,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,QAAM,0BAA0B,CAAC;AACjC,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,4BAAwB,KAAK,EAAE;AAC/B,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,GAAG,MAAM,MAAM;AAAA,EAC3E;AACA,uBAAqB,2BAA2B,UAAU,CAAC,KAAK,EAAE,GAAG,GAAG,MAAM,MAAM;AACpF,QAAM,MAAM,gBAAgB,UAAU,IAAI,KAAK,IAAI,KAAK;AACxD,0BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACpD,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,QAAM,0BAA0B,CAAC;AACjC,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,4BAAwB,KAAK,EAAE;AAC/B,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,GAAG,MAAM,MAAM;AAAA,EAC3E;AACA,uBAAqB,2BAA2B,UAAU,CAAC,KAAK,EAAE,GAAG,GAAG,MAAM,MAAM;AACpF,QAAM,MAAM,gBAAgB,UAAU,IAAI,KAAK,IAAI,KAAK;AACxD,0BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAM/B,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,oBAAoB;AAChC,IAAI,SAAS,iBAAiB,EAAE,WAAW,MAAM,CAAC;AAClD,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,oBAAoB;AAAA;AAAA;AAG/B,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,2BAA2B;AAAA;AAAA;AAGvC,IAAI,eAAe;AAAA;AAAA;AAAA,MAGb,kCAAkC;AAAA;AAAA;AAGxC,IAAI,SAAS,kBAAkB,EAAE,WAAW,OAAO,iBAAiB,aAAa,CAAC;AAClF,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,oBAAoB;AAAA;AAAA;AAGhC,IAAI,SAAS,iBAAiB,EAAE,WAAW,MAAM,CAAC;AAClD,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,UAAU,UAAU,kBAAkB,mBAAmB,OAAO,sBAAsB,OAAO;AACvG,SAAK,gBAAgB,CAAC,GAAG;AACzB,QAAI,aAAa,SAAS,kBAAkB;AAC1C,YAAM,IAAI,MAAM,4CAA4C;AAAA,IAC9D;AACA,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,iBAAiB,SAAS;AAChC,UAAM,gBAAgB,SAAS;AAC/B,UAAM,wBAAwB,SAAS;AACvC,UAAM,uBAAuB,SAAS;AACtC,UAAM,SAAS,SAAS,QAAQ;AAChC,UAAM,UAAU,SAAS,QAAQ;AACjC,SAAK,cAAc,SAAS;AAC5B,UAAM,YAAY,aAAa;AAC/B,UAAM,0BAA0B,cAAc,SAAS,oBAAoB,SAAS,mBAAmB,SAAS;AAChH,UAAM,qBAAqB,SAAS,SAAS,mBAAmB,SAAS;AACzE,QAAI,sBAAsB;AAC1B,QAAI,CAAC,WAAW;AACd,4BAAsB;AAAA,IACxB;AACA,QAAI,kBAAkB;AACpB,YAAM,aAAa;AACnB,WAAK,WAAW;AAAA,sCACgB,iBAAiB;AAAA,mCACpB,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAkBZ;AAAA,sBACZ;AAAA;AAAA;AAAA,kCAGY,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP;AAAA,wBACZ;AAAA;AAAA;AAAA,oCAGY,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0BAUnB;AAAA;AAAA;AAAA,mCAGS,mBAAmB,sBAAsB,0BAA0B,qBAAqB,QAAQ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAO7H;AAAA,IACF;AACA,UAAM,YAAY;AAClB,QAAI,cAAc,GAAG,YAAY,YAAY;AAC7C,QAAI,aAAa,OAAO;AACtB,oBAAc;AAAA,IAChB;AACA,UAAM,yBAAyB,KAAK,MAAM,cAAc,CAAC,IAAI;AAC7D,UAAM,2BAA2B,cAAc;AAC/C,UAAM,gBAAgB;AAAA,YACd;AAAA;AAAA;AAAA,wBAGY;AAAA;AAAA;AAGpB,SAAK,WAAW;AAAA,oCACgB,iBAAiB;AAAA,iCACpB,WAAW;AAAA,0CACF;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAMZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAkBL;AAAA;AAAA;AAAA;AAAA,gCAIF;AAAA,oBACZ;AAAA;AAAA;AAAA,gCAGY,SAAS;AAAA;AAAA;AAAA;AAAA,kCAIP;AAAA,uCACK;AAAA;AAAA;AAAA;AAAA,yCAIE;AAAA,6CACI;AAAA,6CACA;AAAA;AAAA;AAAA,cAG/B;AAAA;AAAA;AAAA,gCAGkB;AAAA,gBAChB,6BAA6B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAQ/B;AAAA,uBACS,6BAA6B;AAAA;AAAA;AAAA,yCAGX;AAAA;AAAA;AAAA;AAAA;AAAA,cAK3B;AAAA,uBACS,6BAA6B;AAAA;AAAA;AAAA,yCAGX;AAAA,6CACI;AAAA;AAAA;AAAA;AAAA,cAI/B;AAAA;AAAA;AAAA,oBAGM;AAAA;AAAA;AAAA,EAGlB;AACF;AACA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,UAAU,UAAU,kBAAkB,mBAAmB,OAAO,sBAAsB,OAAO;AACvG,SAAK,gBAAgB,CAAC,GAAG;AACzB,QAAI,aAAa,SAAS,kBAAkB;AAC1C,YAAM,IAAI,MAAM,4CAA4C;AAAA,IAC9D;AACA,UAAM,cAAc,SAAS;AAC7B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,gBAAgB,SAAS;AAC/B,UAAM,iBAAiB,SAAS;AAChC,UAAM,gBAAgB,SAAS;AAC/B,UAAM,uBAAuB,SAAS;AACtC,UAAM,wBAAwB,SAAS;AACvC,UAAM,uBAAuB,SAAS;AACtC,UAAM,WAAW,SAAS,QAAQ;AAClC,UAAM,SAAS,SAAS,QAAQ;AAChC,UAAM,UAAU,SAAS,QAAQ;AACjC,SAAK,cAAc,SAAS;AAC5B,UAAM,YAAY,aAAa;AAC/B,QAAI,sBAAsB;AAC1B,QAAI,CAAC,WAAW;AACd,4BAAsB;AAAA,IACxB;AACA,QAAI,kBAAkB;AACpB,YAAM,aAAa;AACnB,WAAK,WAAW;AAAA;AAAA,oBAEF,gBAAgB,iBAAiB;AAAA,mCAClB,aAAa,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAkBzB;AAAA,sBACZ;AAAA;AAAA;AAAA,kCAGY,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP;AAAA,wBACZ;AAAA;AAAA;AAAA,oCAGY,SAAS;AAAA;AAAA;AAAA;AAAA,sCAIP;AAAA,0BACZ;AAAA;AAAA;AAAA,sCAGY,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,4BAUnB;AAAA;AAAA;AAAA,qCAGS,mBAAmB,sBAAsB,cAAc,SAAS,mBAAmB,SAAS,oBAAoB,SAAS,mBAAmB,SAAS,oBAAoB,UAAU,SAAS,oBAAoB,SAAS,mBAAmB,SAAS,oBAAoB,QAAQ,2BAA2B;AAAA,6BACpT;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAQvB;AAAA,IACF;AACA,UAAM,YAAY;AAClB,QAAI,cAAc,GAAG,YAAY,YAAY;AAC7C,QAAI,aAAa,OAAO;AACtB,oBAAc;AAAA,IAChB;AACA,UAAM,yBAAyB,KAAK,MAAM,cAAc,CAAC,IAAI;AAC7D,UAAM,2BAA2B,cAAc;AAC/C,UAAM,gBAAgB;AAAA,YACd;AAAA;AAAA;AAAA,wBAGY;AAAA;AAAA;AAGpB,SAAK,WAAW;AAAA;AAAA,gBAEJ,gBAAgB,iBAAiB;AAAA,iCAChB,aAAa,WAAW;AAAA,0CACf;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAMZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAmBL;AAAA;AAAA;AAAA;AAAA,gCAIF;AAAA,oBACZ;AAAA;AAAA;AAAA,gCAGY,SAAS;AAAA;AAAA;AAAA;AAAA,kCAIP;AAAA,oBACd;AAAA;AAAA;AAAA,kCAGc,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP;AAAA,yCACK;AAAA;AAAA;AAAA;AAAA,+CAIM;AAAA,mDACI;AAAA,mDACA;AAAA;AAAA;AAAA,gBAGnC;AAAA;AAAA;AAAA,kCAGkB;AAAA,kBAChB,6BAA6B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gBAQ/B;AAAA,yBACS,6BAA6B;AAAA;AAAA;AAAA,+CAGP;AAAA;AAAA;AAAA;AAAA;AAAA,gBAK/B;AAAA,yBACS,6BAA6B;AAAA;AAAA;AAAA,+CAGP;AAAA,mDACI;AAAA;AAAA;AAAA;AAAA,gBAInC;AAAA;AAAA;AAAA,sBAGM;AAAA;AAAA;AAAA;AAAA,EAIpB;AACF;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,oBAAkB,GAAG,SAAS;AAC9B,QAAM,EAAE,YAAY,SAAAV,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY;AAClB,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,SAAS,GAAG,MAAM,wEAAwEA,2BAA0B,YAAY;AACjN,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,MAAI,SAAS,gBAAgB,KAAK,SAAS,iBAAiB,KAAK,aAAa,YAAY,SAAS,SAAS,SAAS,QAAQ,GAAG;AAC9H,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD;AACA,QAAM,iBAAiB,IAAI,cAAc,UAAU,OAAO,KAAK;AAC/D,SAAO,SAAS,gBAAgB,gBAAgB,CAAC,CAAC,GAAG,SAAS;AAChE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,iBAAiB,WAAW,IAAI;AACxE,QAAM,YAAY,CAAC,GAAG,GAAG,CAAC;AAC1B,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,iBAAiB,UAAU;AAClI,QAAM,iBAAiB,IAAI,cAAc,UAAU,OAAO,KAAK;AAC/D,SAAO,SAAS,gBAAgB,gBAAgB,CAAC,CAAC,GAAG,SAAS;AAChE;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,MAAM;AAAA,EACnC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,IAAI;AAC1B,SAAK,cAAc,SAAS;AAC5B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,iBAAiB,SAAS;AAChC,UAAM,gBAAgB,SAAS;AAC/B,UAAM,wBAAwB,SAAS;AACvC,UAAM,uBAAuB,SAAS;AACtC,UAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,UAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,UAAM,gBAAgB,KAAK,eAAe;AAC1C,SAAK,WAAW;AAAA,iCACa,WAAW;AAAA,0CACF;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAcV;AAAA,oBACZ;AAAA,gDAC4B;AAAA;AAAA,oCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA,kCAKX;AAAA,mBACf;AAAA,kDAC+B;AAAA;AAAA,sCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAc7C;AACF;AACA,IAAI,2BAA2B,MAAM;AAAA,EACnC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,IAAI;AAC1B,SAAK,cAAc,SAAS;AAC5B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,gBAAgB,SAAS;AAC/B,UAAM,iBAAiB,SAAS;AAChC,UAAM,gBAAgB,SAAS;AAC/B,UAAM,uBAAuB,SAAS;AACtC,UAAM,wBAAwB,SAAS;AACvC,UAAM,uBAAuB,SAAS;AACtC,UAAM,WAAW,uBAAuB,IAAI,SAAS,QAAQ;AAC7D,UAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,UAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,UAAM,gBAAgB,KAAK,cAAc,eAAe;AACxD,SAAK,WAAW;AAAA,iCACa,aAAa,WAAW;AAAA,0CACf;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAiBV;AAAA,oBACZ;AAAA,gDAC4B;AAAA;AAAA,oCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA,kCAKX;AAAA,sBACZ;AAAA,kDAC4B;AAAA;AAAA,sCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oCAMX;AAAA,wBACZ;AAAA,oDAC4B;AAAA;AAAA,wCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAe/C;AACF;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,OAAO,IAAI;AAC9B,QAAM,IAAI;AACV,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY,CAAC,GAAG,GAAG,CAAC;AAC1B,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,QAAM,yBAAyB,IAAI,yBAAyB,QAAQ;AACpE,SAAO,SAAS,gBAAgB,wBAAwB,CAAC,EAAE,GAAG,EAAE,KAAK;AACvE;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,OAAO,IAAI;AAC9B,QAAM,IAAI;AACV,oBAAkB,CAAC,IAAI,MAAM,GAAG,aAAa;AAC7C,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,KAAK,IAAI;AAC3C,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,IAAI;AAC7F,QAAM,yBAAyB,IAAI,yBAAyB,QAAQ;AACpE,SAAO,SAAS,gBAAgB,wBAAwB,CAAC,EAAE,GAAG,EAAE,KAAK;AACvE;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,EAAE,IAAI;AACjB,QAAM,EAAE,YAAY,WAAW,IAAI;AACnC,SAAO,gBAAgB,EAAE,GAAG,GAAG,YAAY,YAAY,SAAS,SAAS,CAAC;AAC5E;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,QAAQ,WAAW,eAAe,aAAa,YAAY,iBAAiB;AACtF,SAAK,cAAc,CAAC;AACpB,SAAK,gBAAgB,CAAC,KAAK,QAAQ,UAAU;AAC7C,yBAAqB,2BAA2B,QAAQ,SAAS;AACjE,yBAAqB,2BAA2B,QAAQ,aAAa;AACrE,QAAI,gBAAgB;AACpB,QAAI,eAAe,MAAM;AACvB,2BAAqB,2BAA2B,QAAQ,WAAW;AACnE,WAAK,cAAc,KAAK,QAAQ;AAChC,sBAAgB;AAAA,IAClB;AACA,QAAI,eAAe;AACnB,QAAI,cAAc,MAAM;AACtB,2BAAqB,2BAA2B,QAAQ,UAAU;AAClE,WAAK,cAAc,KAAK,OAAO;AAC/B,qBAAe;AAAA,IACjB;AACA,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,yBAKK;AAAA,wBACD;AAAA,2DACmC;AAAA;AAAA;AAAA;AAAA,EAIzD;AACF;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,QAAQ,WAAW,eAAe,aAAa,YAAY,iBAAiB;AACtF,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,gBAAgB,CAAC,KAAK,QAAQ,UAAU;AAC7C,yBAAqB,2BAA2B,QAAQ,SAAS;AACjE,yBAAqB,2BAA2B,QAAQ,aAAa;AACrE,QAAI,gBAAgB;AACpB,QAAI,eAAe,MAAM;AACvB,2BAAqB,2BAA2B,QAAQ,WAAW;AACnE,WAAK,cAAc,KAAK,QAAQ;AAChC,sBAAgB;AAAA,IAClB;AACA,QAAI,eAAe;AACnB,QAAI,cAAc,MAAM;AACtB,2BAAqB,2BAA2B,QAAQ,UAAU;AAClE,WAAK,cAAc,KAAK,OAAO;AAC/B,qBAAe;AAAA,IACjB;AACA,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA,wBAEI;AAAA,uBACD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,yDAMkC;AAAA;AAAA;AAAA;AAAA;AAAA,EAKvD;AACF;AAGA,IAAI,aAAa,CAAC,EAAE,QAAQ,SAAS,UAAU,MAAM,MAAM;AACzD,QAAM,EAAE,GAAG,MAAM,OAAO,UAAU,QAAQ,OAAOS,QAAO,IAAI;AAC5D,eAAa,OAAO,MAAM,MAAM,WAAW,SAAS,MAAM,QAAQ,MAAM,8EAA8E;AACtJ,eAAa,OAAO,UAAU,QAAQ,MAAM,MAAM,WAAW,OAAO,MAAM,QAAQ,MAAM,4EAA4E;AACpK,eAAa,OAAOA,WAAU,QAAQ,MAAM,MAAM,WAAWA,QAAO,MAAM,QAAQ,MAAM,2EAA2E;AACnK,MAAI,EAAE,gBAAgB,IAAI;AAC1B,MAAI,mBAAmB,MAAM;AAC3B,sBAAkB;AAAA,EACpB;AACA,QAAM,cAAc,CAAC,GAAG,OAAO,QAAQ;AACvC,MAAI,cAAc;AAClB,MAAI,UAAU,MAAM;AAClB,kBAAc,OAAO;AACrB,gBAAY,KAAK,MAAM;AAAA,EACzB;AACA,MAAI,aAAa;AACjB,MAAIA,WAAU,MAAM;AAClB,iBAAaA,QAAO;AACpB,gBAAY,KAAKA,OAAM;AAAA,EACzB;AACA,QAAM,UAAU,IAAI,EAAE,QAAQ,0BAA0B,IAAI,IAAI,uBAAuB,EAAE,OAAO,MAAM,OAAO,SAAS,OAAO,aAAa,YAAY,eAAe,IAAI,IAAI,iBAAiB,EAAE,OAAO,MAAM,OAAO,SAAS,OAAO,aAAa,YAAY,eAAe;AAC5Q,QAAM,SAAS,SAAS,gBAAgB,SAAS,aAAa,YAAY,GAAG,KAAK;AAClF,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,QAAQ;AAC9B,SAAK,cAAc;AACnB,SAAK,OAAO,SAAS;AACrB,UAAM,QAAQ,kBAAkB,KAAK,IAAI;AACzC,SAAK,iBAAiB,CAAC,EAAE,MAAM,SAAS,YAAY,KAAK,MAAM,MAAM,MAAM,CAAC;AAC5E,UAAM,eAAe,UAAU,KAAK,IAAI;AACxC,QAAIgB;AACJ,UAAM,WAAW,SAAS,IAAI,CAAC,GAAG,OAAO;AACvC,aAAO,aAAa,OAAO,eAAe,gBAAgB,OAAO;AAAA,IACnE,CAAC;AACD,IAAAA,QAAO;AAAA,UACD;AAAA,UACA;AAAA,UACA,SAAS,KAAK,IAAI;AAAA;AAExB,SAAK,WAAW;AAAA;AAAA,UAEVA;AAAA,8BACoB;AAAA;AAAA;AAAA,EAG5B;AACF;AACA,IAAI,SAAS,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAC1C,SAAS,UAAU,MAAM;AACvB,MAAI,SAAS,GAAG;AACd,WAAO;AAAA,EACT,WAAW,QAAQ,GAAG;AACpB,WAAO,OAAO,MAAM,GAAG,IAAI,EAAE,IAAI,CAAC,MAAM,eAAe,CAAC,EAAE,KAAK,GAAG;AAAA,EACpE,OAAO;AACL,UAAM,MAAM,oBAAoB,2BAA2B;AAAA,EAC7D;AACF;AAGA,IAAI,qBAAqB,MAAM;AAAA,EAC7B,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,QAAQ;AAC9B,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc;AACnB,SAAK,OAAO,SAAS;AACrB,SAAK,iBAAiB,CAAC,EAAE,MAAM,SAAS,YAAY,KAAK,MAAM,MAAM,MAAM,CAAC;AAC5E,UAAM,QAAQ,kBAAkB,KAAK,IAAI;AACzC,UAAM,UAAU,YAAY,UAAU,KAAK,IAAI;AAC/C,UAAM,YAAY,YAAY,aAAa,KAAK,IAAI;AACpD,UAAM,YAAY,KAAK,SAAS,IAAI,cAAc,QAAQ,UAAU,MAAM,EAAE,EAAE,KAAK;AACnF,UAAM,aAAa,wBAAwB,UAAU,KAAK,OAAO;AACjE,UAAM,WAAW;AAAA,mBACF;AAAA,cACL,QAAQ,KAAK,OAAO,QAAQ,SAAS,KAAK,OAAO;AAAA,YACnD,UAAU,KAAK,OAAO;AAAA,qBACb;AAAA,YACT,UAAU,KAAK,OAAO;AAAA;AAAA;AAG9B,UAAM,WAAW,KAAK,SAAS,IAAI,KAAK;AAAA,UAClC,QAAQ,KAAK,OAAO;AAAA,cAChB,QAAQ,KAAK,OAAO,QAAQ,SAAS,KAAK,OAAO;AAAA,YACnD,UAAU,KAAK,OAAO;AAAA,qBACb;AAAA,gBACL,QAAQ,KAAK,OAAO,QAAQ,SAAS,KAAK,OAAO;AAAA,cACnD,UAAU,KAAK,OAAO;AAAA,uBACb;AAAA;AAAA;AAAA;AAInB,UAAM,iBAAiB,KAAK,QAAQ,IAAI;AAAA,cAC9B,SAAS,SAAS,IAAI,CAAC,GAAG,OAAO,SAAS,KAAK,EAAE,KAAK,QAAQ,SAAS,IAAI,CAAC,GAAG,OAAO,GAAG,UAAU,SAAS,QAAQ,eAAe,MAAM,EAAE,KAAK,IAAI;AAC9J,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA,UACA;AAAA,UACA;AAAA;AAAA,UAEA;AAAA,UACA;AAAA;AAAA;AAAA;AAAA,EAIR;AACF;AAGA,SAAS,aAAa,GAAG,OAAOrC,OAAM,UAAU;AAC9C,QAAM,WAAW,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC9C,QAAM,KAAK,SAAS,eAAeA,OAAM,EAAE,KAAK;AAChD,QAAM,aAAa,SAAS,QAAQ,IAAI,GAAG,MAAM;AACjD,SAAO,OAAO,YAAY,QAAQ;AAClC,aAAW,WAAW;AACtB,aAAW,QAAQA;AACnB,aAAW,QAAQ,EAAE;AACrB,MAAI,aAAa,mBAAmB,kBAAkB,OAAO,aAAa,eAAe,EAAE,KAAK,CAAC;AACjG,MAAI,SAAS,OAAO;AAClB,kBAAc,SAAS,MAAM;AAAA,EAC/B;AACA,aAAW,QAAQ;AAAA,IACjB;AAAA,IACA,YAAY,SAAS,SAAS,SAAS,MAAM,cAAc,EAAE;AAAA,EAC/D;AACA,QAAM,WAAW,SAAS,aAAa,IAAI,WAAW,MAAM,UAAU,KAAK;AAC3E,WAAS,aAAa,IAAI,WAAW,MAAM,YAAY,WAAW,CAAC;AACnE,SAAO;AACT;AACA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAO,MAAAA,MAAK,IAAI;AACxB,QAAM,CAAC,QAAQ,KAAK,IAAI,mBAAmB,iBAAiB,GAAG,OAAOA,KAAI;AAC1E,qBAAmB,kBAAkB,GAAG,QAAQ,KAAK;AACrD,MAAI,aAAa,cAAc,KAAK,MAAM,GAAG;AAC3C,WAAO,SAAS,eAAe,OAAO,EAAE,OAAO,CAAC,CAAC;AAAA,EACnD;AACA,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,KAAK,EAAE,UAAU,UAAU;AAC5D,UAAM,WAAW,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC9C,UAAM,YAAY,aAAa,SAAS,QAAQ,QAAQ,OAAO,EAAE,OAAO,EAAE,KAAK;AAC/E,WAAO,SAAS,eAAe,OAAO,EAAE,OAAO,SAAS;AAAA,EAC1D;AACA,QAAM,EAAE,SAAS,IAAI,SAAS,QAAQ,IAAI,EAAE,MAAM;AAClD,QAAM,cAAc,mBAAmB,iBAAiB,EAAE,OAAO,QAAQ,KAAK;AAC9E,MAAI,YAAY,CAAC,aAAa;AAC5B,UAAM,UAAU,IAAI,EAAE,QAAQ,6BAA6B,IAAI,IAAI,mBAAmB,KAAK,IAAI,IAAI,aAAa,KAAK;AACrH,UAAM,eAAe,CAAC,MAAM;AAC5B,WAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,YAAY;AAAA,EACrE;AACA,WAAS,YAAY,EAAE,MAAM;AAC7B,SAAO,aAAa,GAAG,QAAQ,OAAO,QAAQ;AAChD;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kBAAkB,CAAC,SAAS;AAC9B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,MAAM,IAAI;AAC9B,eAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,sEAAsE;AACrH,QAAM,QAAQ,WAAW,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAC/C,QAAM,WAAW,qBAAqB,YAAY,EAAE,OAAO,YAAY,KAAK;AAC5E,QAAM,WAAW,qBAAqB,YAAY,SAAS,QAAQ,WAAW,MAAM;AACpF,QAAM,mBAAmB,qBAAqB,oBAAoB,EAAE,OAAO,YAAY,KAAK;AAC5F,QAAM,mBAAmB,qBAAqB,oBAAoB,OAAO,WAAW,MAAM;AAC1F,QAAM,YAAY,qBAAqB,aAAa,kBAAkB,OAAO,WAAW,MAAM;AAC9F,QAAM,YAAY,CAAC;AACnB,QAAM,uBAAuB,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACtG,QAAM,yBAAyB,WAAW,EAAE,QAAQ,EAAE,GAAG,qBAAqB,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,SAAS,EAAE,CAAC;AAC/H,QAAM,wBAAwB,SAAS;AAAA,IACrC,QAAQ,EAAE,GAAG,uBAAuB;AAAA,IACpC,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,iBAAiB;AAAA,EACnC,CAAC;AACD,QAAM,SAAS,OAAO;AAAA,IACpB,QAAQ,EAAE,GAAG,sBAAsB;AAAA,IACnC,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,kBAAkB,MAAM,UAAU;AAAA,EACpD,CAAC;AACD,YAAU,KAAK,oBAAoB;AACnC,YAAU,KAAK,sBAAsB;AACrC,YAAU,KAAK,qBAAqB;AACpC,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,SAAO;AACT;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAAA,MAAK,IAAI;AACjB,QAAM,QAAQ,SAAS,SAAS,EAAE,MAAM;AACxC,QAAM,cAAc,SAAS,SAAS,QAAQ,MAAM;AACpD,QAAM,UAAU,gBAAgB,OAAO,aAAa,QAAQ,OAAO,QAAQ,OAAOA,KAAI;AACtF,SAAO,SAAS,eAAe,CAACA,KAAI,GAAG,QAAQ,OAAO,OAAO;AAC/D;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,IAAI,GAAG,IAAI;AACnB,QAAM,SAAS,SAAS,SAAS,GAAG,MAAM;AAC1C,QAAM,SAAS,SAAS,SAAS,GAAG,MAAM;AAC1C,QAAM,iBAAiB,qBAAqB,2BAA2B,MAAM,KAAK,MAAM,GAAG,MAAM,KAAK,MAAM,CAAC;AAC7G,SAAO,SAAS,eAAe,CAAC,eAAe,MAAM,GAAG,SAAS,WAAW,KAAK,cAAc,CAAC;AAClG;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY;AAChB,IAAI,YAAY,kBAAkB,EAAE,WAAW,WAAW,eAAe,iBAAiB,OAAO,OAAO,CAAC;AACzG,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,YAAY,SAAS,QAAQ,IAAI,OAAO,MAAM;AACpD,SAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,UAAU,mBAAmB,KAAK,GAAG,SAAS,SAAS,CAAC;AAC1F;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS;AACb,SAAS,IAAI,QAAQ,UAAU;AAC7B,QAAM,UAAU,IAAI,eAAe,OAAO,OAAO,MAAM;AACvD,QAAM,SAAS,SAAS,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO;AAClE,SAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC3E;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,IAAI;AAClB,MAAI,UAAU,aAAa;AACzB,QAAI,EAAE,UAAU,aAAa;AAC3B,aAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,IACvD;AACA,UAAM,cAAc,MAAM,EAAE,KAAK;AACjC,UAAM,SAAS,MAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AACtF,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,QAAQ,MAAM,YAAY,GAAG,SAAS,SAAS,CAAC;AAC1F,gBAAY,QAAQ;AACpB,aAAS,8BAA8B,MAAM;AAC7C,WAAO;AAAA,EACT;AACA,MAAI,EAAE,UAAU,aAAa;AAC3B,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,SAAS,MAAM,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AACrF,aAAS,8BAA8B,QAAQ;AAC/C,WAAO;AAAA,EACT;AACA,MAAI,CAAC,aAAa,gBAAgB,EAAE,OAAO,KAAK,GAAG;AACjD,UAAM,SAAS,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAC7D,WAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO,OAAO,OAAO,MAAM;AAAA,EAC7D;AACA,MAAI,UAAU,SAAS;AACrB,WAAO,IAAI,GAAG,QAAQ;AAAA,EACxB;AACA,MAAI,UAAU,QAAQ;AACpB,UAAM,kBAAkB,SAAS,eAAe,CAAC,GAAG,QAAQ,aAAa,uBAAuB,QAAQ,CAAC,CAAC;AAC1G,UAAM,eAAe,EAAE,GAAG,GAAG,GAAG,gBAAgB;AAChD,UAAM,SAAS,UAAU,EAAE,QAAQ,cAAc,SAAS,SAAS,CAAC;AACpE,aAAS,8BAA8B,eAAe;AACtD,WAAO;AAAA,EACT;AACA,QAAM,IAAI,MAAM,iCAAiC,EAAE,YAAY,OAAO;AACxE;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AACX,IAAI,QAAQ,iBAAiB,EAAE,WAAW,MAAM,iBAAiB,MAAM,eAAe,YAAY,CAAC;AACnG,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,QAAQ;AAClB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,iBAAiB;AAAA,MACpB,EAAE,MAAM,UAAU,MAAM,QAAQ;AAAA,MAChC,EAAE,MAAM,UAAU,MAAM,QAAQ;AAAA,IAClC;AACA,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAYlB;AACF;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,QAAQ;AAClB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,iBAAiB;AAAA,MACpB,EAAE,MAAM,UAAU,MAAM,QAAQ;AAAA,MAChC,EAAE,MAAM,UAAU,MAAM,QAAQ;AAAA,IAClC;AACA,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAYlB;AACF;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,cAAc,aAAa,IAAI;AACvC,MAAI;AACJ,MAAI,IAAI,EAAE,QAAQ,iBAAiB,GAAG;AACpC,cAAU,IAAI,kBAAkB,EAAE,KAAK;AAAA,EACzC,OAAO;AACL,cAAU,IAAI,YAAY,EAAE,KAAK;AAAA,EACnC;AACA,QAAM,eAAe,CAAC,CAAC,YAAY,GAAG,CAAC,YAAY,CAAC;AACpD,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,YAAY;AACrE;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,OAAO;AACjB,SAAK,gBAAgB,CAAC,QAAQ,MAAM;AACpC,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAclB;AACF;AAGA,SAAS,+BAA+B,eAAe,aAAa;AAClE,SAAO;AAAA,IACL,QAAQ,YAAY;AAAA,IACpB,OAAO,YAAY;AAAA,IACnB,OAAO,cAAc;AAAA,EACvB;AACF;AACA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,QAAM,UAAU,IAAI,kBAAkB,EAAE,KAAK;AAC7C,QAAM,gBAAgB;AAAA,IACpB,+BAA+B,GAAG,MAAM,mBAAmB,IAAI;AAAA,IAC/D,+BAA+B,GAAG,MAAM,mBAAmB,IAAI;AAAA,EACjE;AACA,SAAO,SAAS,gBAAgB,SAAS,eAAe,cAAc,GAAG,KAAK;AAChF;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,QAAQ;AAClB,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc,qBAAqB,gBAAgB,QAAQ,CAAC;AACjE,SAAK,gBAAgB,OAAO,IAAI,CAAC,GAAG,OAAO,IAAI,IAAI;AACnD,UAAM,UAAU,IAAI,MAAM,OAAO,SAAS,CAAC;AAC3C,YAAQ,KAAK,OAAO,GAAG;AACvB,aAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,cAAQ,MAAM,QAAQ,KAAK,KAAK,OAAO,IAAI;AAAA,IAC7C;AACA,UAAM,WAAW,CAAC,YAAY,QAAQ,+BAA+B;AACrE,aAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,YAAM,QAAQ,QAAQ,KAAK;AAC3B,eAAS,KAAK,iBAAiB,QAAQ,sBAAsB,aAAa,UAAU;AAAA,IACtF;AACA,UAAM,YAAY,QAAQ;AAC1B,UAAM,YAAY,QAAQ,QAAQ,SAAS;AAC3C,aAAS,KAAK,sBAAsB,oBAAoB,cAAc;AACtE,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAMV,SAAS,KAAK,YAAY;AAAA;AAAA;AAAA,EAGlC;AACF;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,QAAQ,MAAM;AACxB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc,qBAAqB,gBAAgB,QAAQ,IAAI;AACpE,UAAM,QAAQ,KAAK;AACnB,UAAM,OAAO,MAAM;AACnB,UAAM,QAAQ,kBAAkB,IAAI;AACpC,UAAM,UAAU,YAAY,UAAU,IAAI;AAC1C,UAAM,WAAW,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG,EAAE,MAAM,GAAG,IAAI;AAC7D,SAAK,gBAAgB,OAAO,IAAI,CAAC,GAAG,OAAO,IAAI,IAAI;AACnD,UAAM,UAAU,IAAI,MAAM,OAAO,SAAS,CAAC;AAC3C,YAAQ,KAAK,OAAO,GAAG;AACvB,aAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,cAAQ,MAAM,QAAQ,KAAK,KAAK,OAAO,IAAI;AAAA,IAC7C;AACA,UAAM,UAAU,SAAS;AACzB,UAAM,eAAe,SAAS,MAAM,EAAE;AACtC,UAAM,cAAc,SAAS,KAAK;AAClC,QAAI,kBAAkB,OAAO,aAAa,QAAQ;AAAA;AAAA,oBAElC,sBAAsB,aAAa,KAAK;AAAA;AAExD,aAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,YAAM,SAAS,QAAQ,KAAK;AAC5B,yBAAmB;AAAA,cACX,aAAa,QAAQ,WAAW,cAAc,QAAQ,KAAK;AAAA;AAAA,kBAEvD,MAAM,gBAAgB,UAAU,SAAS,MAAM;AAAA,mBAC9C,gBAAgB,cAAc,SAAS,MAAM;AAAA;AAAA,IAE5D;AACA,UAAM,YAAY,QAAQ;AAC1B,UAAM,QAAQ,QAAQ,QAAQ,SAAS;AACvC,uBAAmB;AAAA;AAAA,gBAEP,aAAa,gBAAgB,UAAU,SAAS,KAAK;AAAA,iBACpD,gBAAgB,cAAc,SAAS,KAAK;AACzD,SAAK,WAAW;AAAA,uBACG,SAAS,IAAI,CAAC,MAAM,SAAS,CAAC;AAAA,UAC3C;AAAA;AAAA;AAAA;AAAA,UAIA;AAAA,sCAC4B;AAAA;AAAA,UAE5B,QAAQ,OAAO,QAAQ,QAAQ,OAAO;AAAA,cAClC,QAAQ,OAAO,QAAQ,MAAM,OAAO;AAAA,gCAClB;AAAA;AAAA;AAAA,UAGtB,QAAQ,OAAO,QAAQ,QAAQ,OAAO;AAAA,cAClC,QAAQ,OAAO,QAAQ,MAAM,OAAO;AAAA,gCAClB;AAAA;AAAA;AAAA,UAGtB,QAAQ,OAAO,QAAQ,QAAQ,OAAO;AAAA,cAClC,QAAQ,OAAO,QAAQ,MAAM,OAAO;AAAA,cACpC,QAAQ,OAAO,QAAQ,MAAM,OAAO;AAAA,gCAClB;AAAA;AAAA;AAAA;AAAA;AAAA,EAK9B;AACF;AACA,SAAS,gBAAgB,UAAU,SAAS,OAAO;AACjD,QAAM,aAAa,SAAS,QAAQ,OAAO;AAC3C,QAAM,MAAM,SAAS,IAAI,CAAC,GAAG,QAAQ;AACnC,QAAI,QAAQ,YAAY;AACtB,aAAO,GAAG,OAAO;AAAA,IACnB,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF,CAAC;AACD,SAAO,IAAI,KAAK;AAClB;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,YAAY,SAAS,QAAQ,IAAI,OAAO,MAAM;AACpD,SAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,UAAU,mBAAmB,KAAK,GAAG,SAAS,SAAS,CAAC;AAC1F;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,QAAQ,MAAM,UAAU;AAC3C,QAAM,QAAQ,OAAO,GAAG;AACxB,MAAI,UAAU,aAAa;AACzB,UAAM,QAAQ,OAAO,IAAI,CAAC,OAAO,MAAM,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,SAAS,CAAC,CAAC;AACpF,UAAM,QAAQ,OAAO,IAAI,CAAC,OAAO,MAAM,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,SAAS,CAAC,CAAC;AACpF,UAAM,eAAe,YAAY,OAAO,MAAM,QAAQ;AACtD,UAAM,eAAe,YAAY,OAAO,MAAM,QAAQ;AACtD,UAAM,UAAU,SAAS,EAAE,QAAQ,EAAE,MAAM,cAAc,MAAM,aAAa,GAAG,SAAS,SAAS,CAAC;AAClG,UAAM,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAChE,UAAM,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAChE,aAAS,8BAA8B,YAAY;AACnD,aAAS,8BAA8B,YAAY;AACnD,WAAO;AAAA,EACT;AACA,MAAI,WAAW,SAAS,mBAAmB,MAAM;AACjD,MAAI,UAAU,UAAU;AACtB,eAAW;AAAA,EACb;AACA,MAAI,UAAU;AACZ,UAAM,aAAa,OAAO,IAAI,CAAC,OAAO;AACpC,YAAM,YAAY,aAAa,cAAc,GAAG,MAAM,MAAM,IAAI,CAAC;AACjE,YAAM,QAAQ,CAAC,IAAI,SAAS;AAC5B,aAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AAAA,IAC5E,CAAC;AACD,UAAM,kBAAkB,WAAW,IAAI,CAAC,OAAO;AAC7C,aAAO,EAAE,MAAM,SAAS,SAAS,GAAG,MAAM,GAAG,OAAO,GAAG,MAAM;AAAA,IAC/D,CAAC;AACD,UAAM,YAAY,qBAAqB,gBAAgB,WAAW,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,CAAC;AAC1F,UAAM,eAAe,WAAW,GAAG,MAAM,OAAO;AAChD,UAAM,UAAU,cAAc,iBAAiB,WAAW,OAAO,YAAY;AAC7E,UAAM,gBAAgB,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,IAAI;AAC7F,UAAM,UAAU,SAAS,eAAe,eAAe,OAAO,OAAO;AACrE,eAAW,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACrE,WAAO;AAAA,EACT;AACA,QAAM,sBAAsB,IAAI,EAAE,UAAU,8BAA8B;AAC1E,MAAI,OAAO,SAAS,qBAAqB;AACvC,UAAM,gBAAgB,CAAC;AACvB,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM,qBAAqB;AAC9D,YAAM,WAAW,OAAO,MAAM,IAAI,KAAK,mBAAmB;AAC1D,oBAAc,KAAK,YAAY,UAAU,MAAM,QAAQ,CAAC;AAAA,IAC1D;AACA,UAAM,UAAU,YAAY,eAAe,MAAM,QAAQ;AACzD,eAAW,MAAM,eAAe;AAC9B,eAAS,8BAA8B,EAAE;AAAA,IAC3C;AACA,WAAO;AAAA,EACT;AACA,MAAI,IAAI,EAAE,QAAQ,6BAA6B,KAAK,OAAO,GAAG,MAAM,SAAS,GAAG;AAC9E,UAAM,WAAW,IAAI,oBAAoB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,IAAI;AAC3E,WAAO,SAAS,gBAAgB,UAAU,QAAQ,KAAK;AAAA,EACzD;AACA,QAAM,EAAE,WAAW,SAAS,IAAI,iBAAiB,QAAQ,MAAM,QAAQ;AACvE,QAAM,UAAU,IAAI,cAAc,UAAU,IAAI,CAAC,OAAO,GAAG,KAAK,CAAC;AACjE,QAAM,SAAS,SAAS,gBAAgB,SAAS,WAAW,KAAK;AACjE,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AACxG,WAAS,8BAA8B,MAAM;AAC7C,SAAO;AACT;AACA,SAAS,iBAAiB,QAAQ,MAAM,UAAU;AAChD,QAAM,WAAW,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,IAAI;AACxF,QAAM,YAAY,OAAO,IAAI,CAAC,MAAM,SAAS;AAAA,IAC3C,QAAQ,EAAE,EAAE;AAAA,IACZ,OAAO,EAAE,OAAO,CAAC,IAAI,aAAa,cAAc,EAAE,MAAM,MAAM,IAAI,CAAC,CAAC,EAAE;AAAA,IACtE,SAAS;AAAA,EACX,CAAC,CAAC;AACF,SAAO,EAAE,WAAW,SAAS;AAC/B;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,QAAQ,aAAa,eAAe,MAAM,OAAO,GAAG,KAAK,EAAE;AACjE,QAAM,WAAW,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,KAAK;AACzF,MAAI,aAAa,cAAc,QAAQ,MAAM,GAAG;AAC9C,WAAO,SAAS,eAAe,UAAU,OAAO,GAAG,OAAO,CAAC,CAAC;AAAA,EAC9D;AACA,QAAM,UAAU,OAAO,OAAO,CAAC,OAAO,aAAa,cAAc,GAAG,KAAK,IAAI,CAAC;AAC9E,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,GAAG,SAAS,SAAS,CAAC;AAAA,EACnE;AACA,QAAM,SAAS,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK;AAC3C,uBAAqB,uBAAuB,QAAQ,KAAK;AACzD,SAAO,YAAY,SAAS,OAAO,QAAQ;AAC7C;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,UAAU,UAAU,OAAO,cAAc,MAAM,4BAA4B,OAAO,oBAAoB,OAAO;AACvH,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,cAAc,SAAS;AAC5B,UAAM,SAAS,SAAS,QAAQ;AAChC,UAAM,UAAU,SAAS,QAAQ;AACjC,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,iBAAiB,SAAS;AAChC,UAAM,gBAAgB,SAAS;AAC/B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,wBAAwB,KAAK,MAAM,SAAS,aAAa,CAAC,IAAI;AACpE,UAAM,0BAA0B,SAAS,aAAa;AACtD,UAAM,iBAAiB,SAAS,eAAe;AAC/C,UAAM,SAAS,iBAAiB,IAAI;AACpC,UAAM,SAAS,iBAAiB,IAAI;AACpC,UAAM,aAAa,iBAAiB,IAAI;AACxC,QAAI,oBAAoB,IAAI,yBAAyB;AACrD,QAAI,aAAa;AACf,UAAI,2BAA2B;AAC7B,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,WAAW,mBAAmB;AAC5B,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,OAAO;AACL,4BAAoB;AAAA;AAAA,cAEd;AAAA;AAAA;AAAA,MAGR;AACA,+BAAyB;AAAA,IAC3B;AACA,UAAM,iBAAiB,UAAU,oCAAoC;AACrE,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,2BAA2B;AAC7B,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,QAAI,mBAAmB;AACrB,WAAK,cAAc,KAAK,gBAAgB;AAAA,IAC1C;AACA,SAAK,WAAW;AAAA,QACZ;AAAA;AAAA,oCAE4B,iBAAiB;AAAA,iCACpB,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,0BAKlB;AAAA;AAAA;AAAA,2BAGC,mBAAmB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAOd;AAAA,qCACK;AAAA;AAAA,gCAEL,SAAS;AAAA;AAAA;AAAA;AAAA,kCAIP;AAAA,uCACK;AAAA;AAAA,kCAEL,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oBAQhB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kBAmBF,4BAA4B;AAAA;AAAA,oBAE1B;AAAA;AAAA,0CAEsB;AAAA,mCACP;AAAA;AAAA;AAAA,kCAGD;AAAA,mCACC;AAAA;AAAA;AAAA,yBAGV,4BAA4B;AAAA;AAAA,+BAEtB;AAAA,+BACA;AAAA;AAAA;AAAA,oBAGX;AAAA;AAAA,wCAEoB;AAAA,wCACA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAKR;AAAA,gCACA;AAAA;AAAA;AAAA;AAAA;AAAA,yBAKP,4BAA4B;AAAA;AAAA,+BAEtB;AAAA,+BACA;AAAA,+BACA;AAAA;AAAA;AAAA,oBAGX;AAAA;AAAA,wCAEoB;AAAA,wCACA;AAAA,wCACA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAKR;AAAA,gCACA;AAAA,gCACA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAUtB;AAAA,UACA;AAAA;AAAA;AAAA;AAAA,EAIR;AACF;AACA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,cAAc,SAAS;AAC5B,UAAM,WAAW,SAAS,QAAQ;AAClC,UAAM,SAAS,SAAS,QAAQ;AAChC,UAAM,UAAU,SAAS,QAAQ;AACjC,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,gBAAgB,SAAS;AAC/B,UAAM,iBAAiB,SAAS;AAChC,UAAM,gBAAgB,SAAS;AAC/B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,wBAAwB,KAAK,MAAM,SAAS,aAAa,CAAC,IAAI;AACpE,UAAM,0BAA0B,SAAS,aAAa;AACtD,SAAK,WAAW;AAAA,oCACgB,gBAAgB,iBAAiB;AAAA,iCACpC,aAAa,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAgBzB;AAAA,qCACK;AAAA;AAAA,gCAEL,SAAS;AAAA;AAAA;AAAA;AAAA,kCAIP;AAAA,uCACK;AAAA;AAAA,kCAEL,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP;AAAA,yCACK;AAAA;AAAA,oCAEL,SAAS;AAAA;AAAA;AAAA;AAAA,sCAIP;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oBAiBlB,4BAA4B;AAAA;AAAA,4CAEJ;AAAA,qCACP;AAAA,2BACV,4BAA4B;AAAA;AAAA,4CAEX;AAAA,4CACA;AAAA;AAAA;AAAA,qCAGP;AAAA,qCACA;AAAA;AAAA;AAAA,2BAGV,4BAA4B;AAAA;AAAA,4CAEX;AAAA,4CACA;AAAA,4CACA;AAAA;AAAA;AAAA,qCAGP;AAAA,qCACA;AAAA,qCACA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAUnC;AACF;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,aAAa,UAAU;AACjC,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,iBAAiB;AAAA,MACpB,EAAE,MAAM,cAAc,MAAM,QAAQ;AAAA,MACpC,EAAE,MAAM,OAAO,MAAM,QAAQ;AAAA,MAC7B,EAAE,MAAM,UAAU,MAAM,QAAQ;AAAA,MAChC,EAAE,MAAM,YAAY,MAAM,QAAQ;AAAA,MAClC,EAAE,MAAM,cAAc,MAAM,MAAM;AAAA,MAClC,EAAE,MAAM,oBAAoB,MAAM,MAAM;AAAA,MACxC,EAAE,MAAM,YAAY,MAAM,MAAM;AAAA,IAClC;AACA,SAAK,cAAc;AACnB,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,UAAM,EAAE,WAAW,IAAI;AACvB,UAAM,OAAO,mBAAmB;AAChC,UAAM,iBAAiB,eAAe;AACtC,UAAM,SAAS,iBAAiB,IAAI;AACpC,UAAM,SAAS,iBAAiB,IAAI;AACpC,UAAM,wBAAwB,KAAK,sBAAsB,wDAAwD,mBAAmB,YAAY,eAAe,YAAY;AAC3K,QAAI,WAAW;AACf,aAAS,MAAM,GAAG,OAAO,GAAG,OAAO;AACjC,eAAS,MAAM,GAAG,OAAO,GAAG,OAAO;AACjC,oBAAY;AAAA,gCACY;AAAA,yBACP;AAAA;AAAA,YAEb;AAAA;AAAA;AAAA;AAAA,iCAIqB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,mCAQE;AAAA;AAAA;AAAA;AAAA,sBAIb;AAAA;AAAA,2BAEK,MAAM,IAAI;AAAA;AAAA;AAAA;AAAA;AAAA,2BAKV,MAAM,IAAI;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,MAQ/B;AAAA,IACF;AACA,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UASV;AAAA;AAAA,UAEA,KAAK;AAAA;AAAA;AAAA,EAGb;AACF;AAGA,SAAS,uBAAuB,OAAO,gBAAgB;AACrD,QAAM,SAAS,MAAM;AACrB,MAAI,UAAU,GAAG;AACf,WAAO,iBAAiB;AAAA,MACtB,GAAG,MAAM,MAAM,GAAG,EAAE;AAAA,MACpB,MAAM,SAAS,KAAK,MAAM,SAAS;AAAA,MACnC,MAAM,SAAS;AAAA,IACjB,IAAI;AAAA,MACF,GAAG,MAAM,MAAM,GAAG,EAAE;AAAA,MACpB,MAAM,SAAS;AAAA,MACf,MAAM,SAAS,KAAK,MAAM,SAAS;AAAA,IACrC;AAAA,EACF,WAAW,CAAC,kBAAkB,WAAW,KAAK,MAAM,KAAK,GAAG;AAC1D,WAAO,CAAC,MAAM,IAAI,CAAC;AAAA,EACrB,OAAO;AACL,WAAO;AAAA,EACT;AACF;AACA,SAAS,eAAe,EAAE,GAAG,QAAQ,UAAU,SAAS,UAAU,OAAO,MAAM,yBAAyB,MAAM,iBAAiB,GAAG,YAAY,cAAc,KAAK,GAAG;AAClK,QAAM,SAAS,EAAE;AACjB,QAAM,WAAW,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC9C,QAAM,kBAAkB,SAAS;AACjC,QAAM,cAAc,OAAO,KAAK,OAAO,KAAK,OAAO;AACnD,QAAM,mBAAmB,SAAS;AAClC,QAAM,iBAAiB,SAAS,eAAe;AAC/C,QAAM,aAAa;AACnB,QAAM,aAAa;AACnB,MAAI;AACJ,QAAM,gBAAgB,CAAC;AACvB,MAAI,0BAA0B,MAAM;AAClC,UAAM,cAAc,uBAAuB,uBAAuB,OAAO,cAAc;AACvF,QAAI,eAAe,MAAM;AACvB,+BAAyB,SAAS;AAAA,QAChC,QAAQ,EAAE,GAAG,uBAAuB;AAAA,QACpC,SAAS;AAAA,QACT,OAAO,EAAE,OAAO,YAAY;AAAA,MAC9B,CAAC;AACD,oBAAc,KAAK,sBAAsB;AAAA,IAC3C;AAAA,EACF;AACA,MAAI,QAAQ,MAAM;AAChB,UAAM,cAAc,uBAAuB,KAAK,OAAO,cAAc;AACrE,QAAI,eAAe,MAAM;AACvB,aAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,KAAK,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AACzF,oBAAc,KAAK,IAAI;AAAA,IACzB;AAAA,EACF;AACA,QAAM,6BAA6B,gBAAgB,KAAK,qBAAqB,MAAM,kBAAkB;AACrG,QAAM,cAAc,CAAC,6BAA6B,SAAS,YAAY,kBAAkB,SAAS,WAAW,QAAQ,OAAO,KAAK,MAAM,KAAK,aAAa,YAAY,SAAS,MAAM,MAAM,EAAE,GAAG,OAAO,MAAM,EAAE,CAAC;AAC/M,MAAI,aAAa;AACf,UAAM,cAAc,OAAO,KAAK,OAAO,MAAM,OAAO,KAAK;AACzD,UAAM,YAAY;AAAA,MAChB,QAAQ,EAAE;AAAA,MACV,OAAO,CAAC,GAAG,aAAa,SAAS,UAAU;AAAA,MAC3C,OAAO,EAAE;AAAA,IACX;AACA,UAAM,wBAAwB,SAAS;AACvC,aAAS,QAAQ,SAAS,MAAM,MAAM;AACtC,aAAS,MAAM,SAAS,MAAM,SAAS;AACvC,iBAAa,OAAO,cAAc,SAAS,OAAO,UAAU,KAAK,GAAG,MAAM,kBAAkB,SAAS,YAAY,UAAU,kBAAkB;AAC7I,UAAM,iBAAiB,SAAS;AAAA,MAC9B,QAAQ,EAAE,GAAG,OAAO;AAAA,MACpB,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,CAAC,GAAG,SAAS,YAAY,SAAS,WAAW,EAAE;AAAA,IACjE,CAAC;AACD,kBAAc,KAAK,cAAc;AACjC,UAAM,gBAAgB,gBAAgB;AAAA,MACpC,GAAG;AAAA,MACH,GAAG;AAAA,MACH,SAAS;AAAA,MACT;AAAA,MACA;AAAA,MACA;AAAA,MACA,YAAY;AAAA,MACZ;AAAA,MACA;AAAA,IACF,CAAC;AACD,UAAM,uBAAuB,SAAS,QAAQ,IAAI,cAAc,MAAM;AACtE,iBAAa,OAAO,qBAAqB,UAAU,MAAM,6CAA6C;AACtG,aAAS,QAAQ;AACjB,yBAAqB,QAAQ,SAAS;AACtC,UAAM,UAAU,EAAE,QAAQ,EAAE,GAAG,cAAc,GAAG,SAAS,SAAS,CAAC;AACnE,QAAI,QAAQ,SAAS;AACrB,kBAAc,KAAK,aAAa;AAAA,EAClC,OAAO;AACL,UAAM,UAAU,SAAS,YAAY,SAAS;AAC9C,UAAM,YAAY,SAAS;AAAA,MACzB,QAAQ,EAAE,EAAE;AAAA,MACZ,SAAS;AAAA,MACT,OAAO;AAAA,QACL,OAAO,iBAAiB,CAAC,SAAS,WAAW,SAAS,SAAS,UAAU,IAAI,CAAC,SAAS,WAAW,SAAS,YAAY,OAAO;AAAA,MAChI;AAAA,IACF,CAAC;AACD,UAAM,iBAAiB,SAAS;AAAA,MAC9B,QAAQ,EAAE,GAAG,OAAO;AAAA,MACpB,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,CAAC,GAAG,SAAS,YAAY,SAAS,WAAW,EAAE;AAAA,IACjE,CAAC;AACD,UAAM,SAAS,gBAAgB;AAAA,MAC7B,GAAG,iBAAiB,YAAY;AAAA,MAChC,GAAG,iBAAiB,iBAAiB;AAAA,MACrC,YAAY,CAAC;AAAA,MACb;AAAA,MACA,SAAS;AAAA,MACT;AAAA,MACA,YAAY;AAAA,MACZ;AAAA,MACA;AAAA,IACF,CAAC;AACD,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,SAAS,EAAE,CAAC;AAChG,kBAAc,KAAK,SAAS;AAC5B,kBAAc,KAAK,cAAc;AACjC,kBAAc,KAAK,MAAM;AAAA,EAC3B;AACA,aAAW,MAAM,eAAe;AAC9B,aAAS,8BAA8B,EAAE;AAAA,EAC3C;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,EAAE,GAAG,QAAQ,UAAU,SAAS,UAAU,OAAO,MAAM,yBAAyB,MAAM,iBAAiB,GAAG,YAAY,cAAc,KAAK,GAAG;AACpK,QAAM,EAAE,aAAa,cAAc,YAAY,UAAU,WAAW,WAAW,IAAI;AACnF,QAAM,iBAAiB,eAAe;AACtC,QAAM,YAAY,cAAc,eAAe;AAC/C,QAAM,UAAU,YAAY;AAC5B,QAAM,aAAa,CAAC,SAAS,WAAW,WAAW,OAAO;AAC1D,QAAM,aAAa;AACnB,QAAM,aAAa;AACnB,QAAM,gBAAgB,CAAC;AACvB,MAAI,0BAA0B,MAAM;AAClC,UAAM,cAAc,uBAAuB,uBAAuB,OAAO,cAAc;AACvF,QAAI,eAAe,MAAM;AACvB,+BAAyB,SAAS;AAAA,QAChC,QAAQ,EAAE,GAAG,uBAAuB;AAAA,QACpC,SAAS;AAAA,QACT,OAAO,EAAE,OAAO,YAAY;AAAA,MAC9B,CAAC;AACD,oBAAc,KAAK,sBAAsB;AAAA,IAC3C;AAAA,EACF;AACA,MAAI,QAAQ,MAAM;AAChB,UAAM,cAAc,uBAAuB,KAAK,OAAO,cAAc;AACrE,QAAI,eAAe,MAAM;AACvB,aAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,KAAK,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AACzF,oBAAc,KAAK,IAAI;AAAA,IACzB;AAAA,EACF;AACA,QAAM,QAAQ,SAAS;AAAA,IACrB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,GAAG,WAAW,aAAa,cAAc,OAAO,KAAK,IAAI,SAAS,EAAE;AAAA,EACvF,CAAC;AACD,gBAAc,KAAK,KAAK;AACxB,QAAM,gBAAgB,IAAI,oBAAoB,YAAY,QAAQ;AAClE,QAAM,eAAe;AAAA,IACnB,EAAE;AAAA,IACF,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI;AAAA,IAC5C,CAAC,SAAS,cAAc,SAAS,WAAW;AAAA,IAC5C,CAAC,SAAS,gBAAgB,SAAS,aAAa;AAAA,IAChD,CAAC,SAAS,UAAU;AAAA,IACpB,CAAC,SAAS,cAAc,SAAS,UAAU;AAAA,IAC3C,CAAC,SAAS,QAAQ;AAAA,EACpB;AACA,QAAM,SAAS,SAAS,gBAAgB,eAAe,CAAC,CAAC,GAAG,WAAW,YAAY;AACnF,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAC1G,gBAAc,KAAK,MAAM;AACzB,gBAAc,KAAK,cAAc;AACjC,QAAM,UAAU,QAAQ;AACxB,QAAM,4BAA4B,0BAA0B;AAC5D,QAAM,oBAAoB,gBAAgB;AAC1C,QAAM,kBAAkB,cAAc,6BAA6B,aAAa,IAAI,IAAI;AACxF,QAAM,gBAAgB,IAAI,oBAAoB,iBAAiB,eAAe,QAAQ,MAAM,OAAO,iBAAiB,MAAM,QAAQ,eAAe,OAAO,iBAAiB,CAAC,SAAS,WAAW,SAAS,SAAS,WAAW,IAAI,CAAC,SAAS,WAAW,SAAS,aAAa,OAAO,GAAG,YAAY,YAAY,SAAS,iBAAiB,2BAA2B,iBAAiB;AAClX,QAAM,SAAS,iBAAiB,CAAC,gBAAgB,KAAK,IAAI,CAAC,OAAO,cAAc;AAChF,MAAI,MAAM;AACR,WAAO,KAAK,IAAI;AAAA,EAClB;AACA,MAAI,2BAA2B;AAC7B,WAAO,KAAK,sBAAsB;AAAA,EACpC;AACA,MAAI,mBAAmB;AACrB,UAAM,kBAAkB,SAAS,eAAe,CAAC,GAAG,WAAW,aAAa,kBAAkB,gBAAgB,SAAS,CAAC;AACxH,WAAO,KAAK,eAAe;AAC3B,kBAAc,KAAK,eAAe;AAAA,EACpC;AACA,QAAM,UAAU,SAAS,gBAAgB,eAAe,QAAQ,SAAS;AACzE,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,SAAS,EAAE,CAAC;AACvG,gBAAc,KAAK,OAAO;AAC1B,aAAW,MAAM,eAAe;AAC9B,aAAS,8BAA8B,EAAE;AAAA,EAC3C;AACA,SAAO;AACT;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAY,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB,IAAI;AACvE,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,OAAO,WAAW;AAC5I,MAAI;AACJ,MAAI,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,KAAK,SAAS,mBAAmB,KAAK,SAAS,kBAAkB,KAAK,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,MAAM,SAAS,QAAQ,SAAS,UAAU,SAAS,QAAQ,SAAS,UAAU;AACtQ,UAAM,eAAe,EAAE,GAAG,QAAQ,UAAU,SAAS,SAAS,CAAC;AAAA,EACjE,WAAW,IAAI,EAAE,QAAQ,mBAAmB,GAAG;AAC7C,UAAM,iBAAiB,EAAE,GAAG,QAAQ,UAAU,SAAS,SAAS,CAAC;AAAA,EACnE,OAAO;AACL,UAAM,UAAU,IAAI,cAAc,QAAQ;AAC1C,UAAM,SAAS,gBAAgB,SAAS,CAAC,GAAG,MAAM,GAAG,SAAS;AAAA,EAChE;AACA,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,SAAS,EAAE,CAAC;AAC3G,WAAS,8BAA8B,GAAG;AAC1C,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,KAAK,IAAI;AAC/B,SAAK,cAAc,SAAS;AAC5B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,SAAS,SAAS,QAAQ;AAChC,UAAM,UAAU,SAAS,QAAQ;AACjC,UAAM,iBAAiB,SAAS,eAAe;AAC/C,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAYU,SAAS;AAAA,kCACL,SAAS;AAAA,iCACV,kBAAkB;AAAA;AAAA,kCAEjB,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP,SAAS;AAAA,mCACV,iBAAiB;AAAA;AAAA,oCAEhB,SAAS;AAAA;AAAA;AAAA;AAAA,oBAIzB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAgBlB;AACF;AACA,IAAI,wBAAwB,MAAM;AAAA,EAChC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,MAAM,GAAG;AAC/B,SAAK,cAAc,SAAS;AAC5B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,iBAAiB,SAAS,eAAe;AAC/C,UAAM,SAAS,eAAe,IAAI,SAAS,QAAQ;AACnD,UAAM,UAAU,cAAc,IAAI,SAAS,QAAQ;AACnD,UAAM,SAAS,iBAAiB,IAAI;AACpC,UAAM,SAAS,iBAAiB,IAAI;AACpC,UAAM,aAAa,iBAAiB,IAAI;AACxC,SAAK,WAAW;AAAA,iCACa,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,0BAKlB;AAAA;AAAA,wCAEc,mBAAmB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAO3B;AAAA,gDACgB;AAAA;AAAA,oCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA,yBAKpB;AAAA;AAAA,kCAES;AAAA,kDACgB;AAAA;AAAA,sCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,2BAMpB;AAAA;AAAA,oCAES,SAAS;AAAA;AAAA,oBAEzB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAgBlB;AACF;AACA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,KAAK,IAAI;AAC/B,SAAK,cAAc,SAAS;AAC5B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,WAAW,SAAS,QAAQ;AAClC,UAAM,SAAS,SAAS,QAAQ;AAChC,UAAM,UAAU,SAAS,QAAQ;AACjC,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAWU,SAAS;AAAA,kCACL,SAAS;AAAA,iCACV,iBAAiB;AAAA;AAAA,kCAEhB,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP,SAAS;AAAA,mCACV,kBAAkB;AAAA;AAAA,oCAEjB,SAAS;AAAA;AAAA;AAAA;AAAA,sCAIP,SAAS;AAAA,qCACV,iBAAiB;AAAA;AAAA,sCAEhB,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAc7C;AACF;AACA,IAAI,wBAAwB,MAAM;AAAA,EAChC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,MAAM,GAAG;AAC/B,SAAK,cAAc,SAAS;AAC5B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,WAAW,cAAc,IAAI,SAAS,QAAQ;AACpD,UAAM,SAAS,eAAe,IAAI,SAAS,QAAQ;AACnD,UAAM,UAAU,cAAc,IAAI,SAAS,QAAQ;AACnD,SAAK,WAAW;AAAA,iCACa,aAAa,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAczB;AAAA,gDACgB;AAAA;AAAA,oCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA,yBAKpB;AAAA;AAAA,kCAES;AAAA,kDACgB;AAAA;AAAA,sCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,2BAMpB;AAAA;AAAA,oCAES;AAAA,oDACgB;AAAA;AAAA,wCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,6BAMpB;AAAA;AAAA,sCAES,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAW7C;AACF;AAGA,SAAS,sBAAsB,MAAM;AACnC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,IAAI;AAClB,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,iBAAiB,YAAY,IAAI;AACzE,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,aAAaA,UAAS,GAAG,MAAM,iBAAiB,OAAO,WAAW;AACnI,QAAM,UAAU,IAAI,uBAAuB,QAAQ;AACnD,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,EAAE,GAAG,SAAS;AAC7D;AACA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,YAAY,gBAAgB,IAAI;AACxE,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,GAAG,MAAM,iBAAiB,OAAO,WAAW;AACvI,QAAM,UAAU,IAAI,sBAAsB,QAAQ;AAClD,SAAO,SAAS,gBAAgB,SAAS,CAAC,IAAI,MAAM,GAAG,SAAS;AAClE;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,UAAU,IAAI;AAC1C,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,IAAI;AACvG,QAAM,UAAU,IAAI,cAAc,QAAQ;AAC1C,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,MAAM,GAAG,SAAS;AACjE;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,wBAAwB,MAAM;AACrC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,IAAI;AAClB,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,IAAI;AAC5C,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,aAAaA,UAAS,GAAG,IAAI;AAC9F,QAAM,UAAU,IAAI,uBAAuB,QAAQ;AACnD,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,EAAE,GAAG,SAAS;AAC7D;AACA,IAAI,gCAAgC;AAAA,EAClC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,KAAK,MAAM,SAAAA,UAAS,WAAW,IAAI;AAC3C,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,GAAG,IAAI;AAClG,QAAM,UAAU,IAAI,sBAAsB,QAAQ;AAClD,SAAO,SAAS,gBAAgB,SAAS,CAAC,IAAI,MAAM,GAAG,SAAS;AAClE;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM,0BAA0B;AAAA;AAAA;AAGpC,IAAI,OAAO,iBAAiB,EAAE,WAAW,IAAI,CAAC;AAC9C,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AAAA;AAAA;AAAA;AAIX,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,YAAY,UAAU,UAAU,QAAQ,oBAAoB;AACtE,SAAK,gBAAgB,CAAC,SAAS,SAAS,QAAQ;AAChD,SAAK,cAAc,CAAC;AACpB,UAAM,CAAC,OAAO,aAAa,YAAY,KAAK,IAAI;AAChD,UAAM,CAAC,QAAQ,IAAI;AACnB,UAAM,CAAC,YAAY,SAAS,IAAI;AAChC,SAAK,cAAc,CAAC,UAAU,YAAY,WAAW,KAAK;AAC1D,UAAM,WAAW,WAAW,aAAa,IAAI;AAC7C,UAAM,CAAC,kBAAkB,eAAe,IAAI,CAAC,GAAG,cAAc,OAAO,GAAG,aAAa,KAAK;AAC1F,UAAM,CAAC,aAAa,aAAa,GAAG,IAAI,aAAa,IAAI;AAAA,MACvD,IAAI,cAAc,MAAM,aAAa;AAAA,MACrC;AAAA,MACA,MAAM;AAAA,IACR,IAAI;AAAA,MACF;AAAA,MACA;AAAA,MACA,mBAAmB;AAAA,IACrB;AACA,UAAM,CAAC,YAAY,YAAY,GAAG,IAAI,YAAY,IAAI;AAAA,MACpD,IAAI,aAAa,MAAM,YAAY;AAAA,MACnC;AAAA,MACA,MAAM;AAAA,IACR,IAAI;AAAA,MACF;AAAA,MACA;AAAA,MACA,mBAAmB;AAAA,IACrB;AACA,SAAK,WAAW;AAAA,yCACqB;AAAA,wCACD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,iCAgBP;AAAA;AAAA;AAAA;AAAA,+BAIF;AAAA,8BACD;AAAA;AAAA,uBAEP;AAAA,mCACY;AAAA,4BACP;AAAA;AAAA;AAAA,uBAGL;AAAA,mCACY;AAAA,4BACP;AAAA;AAAA;AAAA;AAAA;AAAA,aAKf;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAyBX;AACF;AAGA,IAAI,iBAAiB,CAAC,SAAS;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,OAAO,OAAO,IAAI;AACzC,QAAM,EAAE,UAAU,QAAQ,mBAAmB,IAAI;AACjD,QAAM,UAAU,IAAI,qBAAqB,OAAO,OAAO,MAAM,OAAO,UAAU,QAAQ,kBAAkB;AACxG,SAAO,SAAS,gBAAgB,SAAS,CAAC,QAAQ,OAAO,MAAM,GAAG,SAAS;AAC7E;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AAAA,CACH,SAAS,YAAY;AACpB,aAAW,UAAU;AACrB,aAAW,SAAS;AACtB,GAAG,cAAc,YAAY,CAAC,EAAE;AAChC,IAAI,aAAa,MAAM;AAAA,EACrB,YAAY,KAAK,aAAa,WAAW,UAAU;AACjD,SAAK,KAAK;AACV,SAAK,cAAc;AACnB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,iBAAiB,CAAC,EAAE,MAAM,SAAS,MAAM,QAAQ,CAAC;AACvD,UAAM,OAAO,KAAK,YAAY;AAC9B,UAAM,UAAU,KAAK,OAAO,UAAU,OAAO,QAAQ;AACrD,UAAM,MAAM,YAAY,UAAU,QAAQ,WAAW,MAAM,UAAU,KAAK,EAAE;AAC5E,UAAM,SAAS,KAAK,YAAY,KAAK,YAAY,SAAS;AAC1D,QAAI,YAAY;AAChB,QAAI,YAAY;AAChB,QAAI,WAAW;AACb,kBAAY,WAAW,UAAU,SAAS,MAAM;AAChD,kBAAY,WAAW,YAAY;AAAA,IACrC,OAAO;AACL,kBAAY,WAAW,gBAAgB,WAAW;AAClD,kBAAY,WAAW,eAAe;AAAA,IACxC;AACA,SAAK,WAAW;AAAA;AAAA,UAEV,kBAAkB,IAAI;AAAA,oBACZ,cAAc,MAAM,UAAU,KAAK,EAAE;AAAA,sBACnC;AAAA;AAAA,cAER;AAAA,sBACQ;AAAA,YACV,cAAc,MAAM,UAAU,KAAK,EAAE;AAAA,gBACjC,KAAK,YAAY,WAAW,MAAM,UAAU,KAAK,EAAE;AAAA;AAAA;AAAA;AAAA;AAAA,EAKjE;AACF;AACA,SAAS,WAAW,MAAM,MAAM,KAAK;AACnC,MAAI,SAAS,GAAG;AACd,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG,WAAW;AAAA,EACvB,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG,WAAW,WAAW;AAAA,EAClC,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG,WAAW,WAAW,WAAW;AAAA,EAC7C,OAAO;AACL,UAAM,IAAI,MAAM,cAAc,gBAAgB,2BAA2B;AAAA,EAC3E;AACF;AACA,SAAS,cAAc,MAAM,MAAM,KAAK;AACtC,MAAI,SAAS,GAAG;AACd,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG;AAAA,EACZ,OAAO;AACL,UAAM,IAAI,MAAM,cAAc,gBAAgB,2BAA2B;AAAA,EAC3E;AACF;AAGA,SAAS,QAAQ,KAAK,GAAG,UAAU,MAAM,WAAW,UAAU;AAC5D,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,cAAc,qBAAqB,mBAAmB,CAAC,IAAI,GAAG,KAAK;AACzE,MAAI,YAAY;AAChB,MAAI,eAAe,MAAM;AACvB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,YAAY,EAAE,CAAC;AAAA,EAC3F;AACA,QAAM,eAAe,qBAAqB,iBAAiB,GAAG,KAAK,EAAE;AACrE,MAAI,iBAAiB,QAAQ,GAAG;AAC9B,UAAM,IAAI,MAAM,mDAAmD,EAAE,MAAM,SAAS,kBAAkB,MAAM;AAAA,EAC9G;AACA,QAAMZ,QAAO,UAAU,MAAM;AAC7B,MAAI,SAAS,UAAU,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,SAAS,CAAC;AACtE,WAAS,KAAK,GAAG,MAAM,KAAK,KAAK,KAAK,KAAKA,KAAI,CAAC,IAAI,GAAG,MAAM;AAC3D,UAAM,UAAU,IAAI,WAAW,KAAK,UAAU,OAAO,OAAO,QAAQ;AACpE,UAAM,eAAe,CAAC,CAAC,EAAE,CAAC;AAC1B,UAAM,aAAa;AACnB,aAAS,SAAS,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO,OAAO,YAAY;AAC/E,aAAS,8BAA8B,UAAU;AAAA,EACnD;AACA,MAAI,WAAW;AACb,UAAM,UAAU,IAAI,WAAW,KAAK,UAAU,OAAO,WAAW,QAAQ;AACxE,UAAM,aAAa;AACnB,aAAS,SAAS,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO,KAAK;AACjE,aAAS,8BAA8B,UAAU;AAAA,EACnD;AACA,MAAI,eAAe,MAAM;AACvB,UAAM,qBAAqB,qBAAqB,uBAAuB,WAAW;AAClF,UAAM,0BAA0B,WAAW,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,mBAAmB,EAAE,CAAC;AAC5H,aAAS,8BAA8B,MAAM;AAC7C,aAAS,8BAA8B,SAAS;AAChD,WAAO;AAAA,EACT;AACA,SAAO;AACT;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,SAAO,QAAQ,UAAU,MAAM,GAAG,UAAU,MAAM,WAAW,QAAQ;AACvE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,SAAO,QAAQ,UAAU,KAAK,GAAG,UAAU,MAAM,WAAW,QAAQ;AACtE;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAAA,OAAM,aAAa,IAAI;AAC/B,MAAI,EAAE,MAAM,WAAW,GAAG;AACxB,UAAM,QAAQ,SAAS,SAAS,EAAE,MAAM;AACxC,UAAM,cAAc,SAAS,SAAS,QAAQ,MAAM;AACpD,UAAM,UAAU,gBAAgB,OAAO,aAAa,QAAQ,OAAO,QAAQ,OAAOA,KAAI;AACtF,WAAO,SAAS,eAAe,CAACA,KAAI,GAAG,QAAQ,OAAO,OAAO;AAAA,EAC/D,WAAW,EAAE,MAAM,WAAW,GAAG;AAC/B,UAAM,OAAO,SAAS,WAAW,CAAC;AAClC,UAAM,aAAa,SAAS,WAAW,OAAO;AAC9C,UAAM,SAAS,sBAAsB,MAAM,YAAYA,OAAM,YAAY;AACzE,WAAO,SAAS,eAAe,OAAO,OAAO,QAAQ,OAAO,OAAO,MAAM;AAAA,EAC3E;AACA,QAAM,IAAI,MAAM,qEAAqE,EAAE,MAAM,SAAS;AACxG;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,aAAa,WAAW,YAAY;AAC9C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc;AACnB,SAAK,YAAY;AACjB,SAAK,aAAa;AAClB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA,gBAIJ,KAAK,qBAAqB;AAAA,gBAC1B,KAAK,oBAAoB;AAAA,gBACzB,KAAK,oBAAoB;AAAA;AAAA,uBAElB;AAAA,+BACQ;AAAA,uBACR;AAAA,+BACQ;AAAA,mCACI;AAAA,UACzB,KAAK,mBAAmB;AAAA;AAAA;AAAA,uBAGX,KAAK,uBAAuB;AAAA;AAAA;AAAA;AAAA,EAIjD;AAAA,EACA,uBAAuB;AACrB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,sBAAsB;AACpB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,sBAAsB;AACpB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,qBAAqB;AACnB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO,KAAK,YAAY;AAAA,IAC1B,OAAO;AACL,aAAO,KAAK,YAAY;AAAA,IAC1B;AAAA,EACF;AAAA,EACA,yBAAyB;AACvB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AACF;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,WAAW,WAAW,IAAI;AAClC,QAAM,YAAY,EAAE,MAAM;AAC1B,QAAM,cAAc,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AACjE,QAAM,aAAa,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AAChE,QAAM,aAAa,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AAChE,QAAM,eAAe,cAAc;AACnC,QAAM,cAAc,aAAa;AACjC,QAAM,cAAc,cAAc,YAAY;AAC9C,QAAM,cAAc,eAAe,SAAS,CAAC,WAAW,cAAc,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,cAAc,WAAW;AACpJ,QAAM,UAAU,IAAI,oBAAoB,aAAa,WAAW,UAAU;AAC1E,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACvD;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,UAAU,UAAU,OAAO,cAAc,MAAM,qBAAqB,OAAO,oBAAoB,OAAO;AAChH,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,iBAAiB;AAAA,MACpB,EAAE,MAAM,QAAQ,MAAM,QAAQ;AAAA,MAC9B,EAAE,MAAM,WAAW,MAAM,QAAQ;AAAA,MACjC,EAAE,MAAM,aAAa,MAAM,QAAQ;AAAA,MACnC,EAAE,MAAM,UAAU,MAAM,QAAQ;AAAA,IAClC;AACA,SAAK,cAAc,SAAS;AAC5B,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,aAAa,SAAS,cAAc,SAAS;AACnD,QAAI,oBAAoB,IAAI,yBAAyB;AACrD,QAAI,aAAa;AACf,UAAI,oBAAoB;AACtB,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,WAAW,mBAAmB;AAC5B,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,OAAO;AACL,4BAAoB;AAAA;AAAA,cAEd;AAAA;AAAA;AAAA,MAGR;AACA,+BAAyB;AAAA,IAC3B;AACA,UAAM,iBAAiB,UAAU,oCAAoC;AACrE,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,oBAAoB;AACtB,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,QAAI,mBAAmB;AACrB,WAAK,cAAc,KAAK,gBAAgB;AAAA,IAC1C;AACA,SAAK,WAAW;AAAA,QACZ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,wBAOgB;AAAA,4BACI;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCASI;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAOE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAcxB;AAAA,UACA;AAAA;AAAA;AAAA;AAAA,EAIR;AACF;AAGA,IAAI,+BAA+B,MAAM;AAAA,EACvC,YAAY,UAAU,UAAU,OAAO,cAAc,MAAM,qBAAqB,OAAO,oBAAoB,OAAO;AAChH,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,iBAAiB;AAAA,MACpB,EAAE,MAAM,QAAQ,MAAM,QAAQ;AAAA,MAC9B,EAAE,MAAM,WAAW,MAAM,QAAQ;AAAA,MACjC,EAAE,MAAM,aAAa,MAAM,QAAQ;AAAA,MACnC,EAAE,MAAM,UAAU,MAAM,QAAQ;AAAA,IAClC;AACA,SAAK,cAAc,SAAS;AAC5B,SAAK,sBAAsB,iBAAiB,KAAK,YAAY,MAAM;AACnE,UAAM,aAAa,SAAS,cAAc,SAAS;AACnD,UAAM,UAAU,SAAS,QAAQ;AACjC,UAAM,cAAc,SAAS;AAC7B,UAAM,gBAAgB,SAAS;AAC/B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe;AACrB,QAAI,WAAW;AAAA;AAAA;AAGf,aAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,kBAAY;AAAA,wBACM,IAAI;AAAA,uBACL,IAAI;AAAA,wBACH,IAAI,IAAI;AAAA,uBACT,IAAI,IAAI;AAAA,mBACZ;AAAA,IACf;AACA,gBAAY;AAAA,0BACU;AAAA;AAEtB,aAAS,IAAI,GAAG,IAAI,aAAa,KAAK;AACpC,kBAAY;AAAA,mBACC,IAAI;AAAA,mBACJ,IAAI;AAAA,mBACJ,IAAI,IAAI;AAAA,mBACR,IAAI,IAAI;AAAA,cACb;AAAA,IACV;AACA,gBAAY;AAAA;AAAA;AAAA;AAIZ,aAAS,SAAS,GAAG,UAAU,eAAe,KAAK,GAAG,UAAU;AAC9D,YAAM,WAAW,SAAS;AAC1B,kBAAY;AAAA,4BACU,WAAW;AAAA;AAEjC,UAAI,gBAAgB,GAAG;AACrB,YAAI,WAAW,aAAa;AAC1B,cAAI,UAAU,MAAM,GAAG;AACrB,wBAAY;AAAA;AAAA,sEAE8C;AAAA,2BAC3C;AAAA;AAAA;AAAA;AAAA;AAAA,6BAKE;AAAA;AAAA,2BAEF;AAAA;AAAA;AAGf,gBAAI,kBAAkB,KAAK,WAAW,GAAG;AACvC,0BAAY;AAAA,oBACN,0BAA0B,WAAW,gBAAgB;AAAA;AAAA,YAE7D,OAAO;AACL,0BAAY;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,wBAYF,uCAAuC;AAAA;AAAA,wBAEvC,oCAAoC;AAAA;AAAA;AAAA,YAGhD;AAAA,UACF,OAAO;AACL,wBAAY;AAAA,0DACkC;AAAA,2BAC/B;AAAA;AAAA,6BAEE;AAAA;AAAA,2BAEF;AAAA;AAAA;AAAA,oBAGP,qBAAqB;AAAA;AAAA,UAE/B;AACA,cAAI,WAAW,IAAI,aAAa;AAC9B,kBAAM,kBAAkB,UAAU,MAAM,IAAI,aAAa,kBAAkB,aAAa,IAAI;AAC5F,gBAAI,gBAAgB,MAAM,KAAK,UAAU,MAAM,KAAK,gBAAgB,MAAM,KAAK,UAAU,MAAM,GAAG;AAChG,0BAAY;AAAA,uDAC6B;AAAA;AAAA,wEAEiB,WAAW;AAAA,6BACtD,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,+BAKT,WAAW;AAAA;AAAA,6BAEb,WAAW;AAAA;AAAA;AAG1B,kBAAI,gBAAgB,GAAG;AACrB,4BAAY;AAAA;AAAA,0EAE8C;AAAA,+BAC3C;AAAA,+BACA;AAAA;AAAA;AAAA,cAGjB;AACA,0BAAY;AAAA,sBACJ,WAAW,mBAAmB,uBAAuB,WAAW;AAAA;AAAA,YAE1E,OAAO;AACL,kBAAI,oBAAoB,GAAG;AACzB,4BAAY;AAAA,wBACJ,WAAW,cAAc;AAAA;AAAA,cAEnC,OAAO;AACL,4BAAY;AAAA,sCACU;AAAA;AAAA,0EAEoC,WAAW;AAAA,+BACtD,WAAW;AAAA;AAAA,iCAET,WAAW;AAAA;AAAA,+BAEb,WAAW;AAAA;AAAA;AAAA,wBAGlB,WAAW,cAAc,WAAW;AAAA;AAAA,cAE9C;AAAA,YACF;AAAA,UACF;AAAA,QACF;AAAA,MACF,OAAO;AACL,YAAI,WAAW,aAAa;AAC1B,cAAI,UAAU,MAAM,GAAG;AACrB,wBAAY;AAAA;AAAA,qEAE6C;AAAA,2BAC1C;AAAA;AAAA;AAAA;AAAA,6BAIE;AAAA;AAAA,2BAEF;AAAA;AAAA;AAAA,iEAGsC,WAAW;AAAA,2BACjD,WAAW;AAAA;AAAA;AAAA;AAAA,6BAIT,WAAW;AAAA;AAAA,2BAEb,WAAW;AAAA;AAAA;AAAA,oBAGlB,0BAA0B,uBAAuB,WAAW;AAAA;AAEpE,gBAAI,WAAW,IAAI,aAAa;AAC9B,0BAAY;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,sBAMJ,WAAW,mBAAmB,WAAW;AAAA;AAAA,YAEnD;AAAA,UACF,OAAO;AACL,wBAAY;AAAA,yDACiC;AAAA,2BAC9B;AAAA;AAAA,6BAEE;AAAA;AAAA,2BAEF;AAAA;AAAA;AAAA;AAAA,qEAI0C,WAAW;AAAA,2BACrD,WAAW;AAAA;AAAA,6BAET,WAAW;AAAA;AAAA,2BAEb,WAAW;AAAA;AAAA;AAAA,oBAGlB;AAAA,2BACO,uBAAuB,WAAW;AAAA;AAEjD,gBAAI,WAAW,IAAI,aAAa;AAC9B,0BAAY;AAAA,sBACJ,WAAW,mBAAmB,uBAAuB,WAAW;AAAA;AAAA,YAE1E;AAAA,UACF;AAAA,QACF;AAAA,MACF;AACA,UAAI,WAAW,aAAa;AAC1B,oBAAY;AAAA,+BACW;AAAA,2BACJ;AAAA;AAEnB,YAAI,WAAW,IAAI,aAAa;AAC9B,sBAAY;AAAA,iCACW,WAAW;AAAA,6BACf,WAAW;AAAA;AAAA,QAEhC;AAAA,MACF;AAAA,IACF;AACA,gBAAY;AAAA;AAAA;AAGZ,gBAAY;AAAA;AAAA;AAGZ,QAAI,oBAAoB,IAAI,yBAAyB;AACrD,QAAI,aAAa;AACf,UAAI,oBAAoB;AACtB,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,WAAW,mBAAmB;AAC5B,4BAAoB;AAAA;AAAA,YAEhB;AAAA;AAAA,MAEN,OAAO;AACL,4BAAoB;AAAA,YAChB;AAAA;AAAA,MAEN;AACA,+BAAyB;AAAA,IAC3B;AACA,UAAM,iBAAiB,UAAU,oCAAoC;AACrE,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,oBAAoB;AACtB,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,QAAI,mBAAmB;AACrB,WAAK,cAAc,KAAK,gBAAgB;AAAA,IAC1C;AACA,SAAK,WAAW;AAAA,QACZ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,wBAOgB;AAAA,4BACI;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAOlB;AAAA;AAAA;AAAA,UAGA;AAAA,UACA;AAAA;AAAA;AAAA;AAAA,EAIR;AACF;AAGA,SAAS,uBAAuB,MAAM;AACpC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAY,UAAS,KAAK,MAAM,WAAW,gBAAgB,IAAI;AAC3D,MAAI,aAAa;AACjB,MAAI,cAAc,MAAM;AACtB,iBAAa,CAAC,GAAG,CAAC;AAAA,EACpB;AACA,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,UAAU,GAAG,MAAM,gFAAgFA,2BAA0B,aAAa;AAC3N,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,YAAY,MAAM,iBAAiB,IAAI;AAC/H,MAAI;AACJ,MAAI,IAAI,EAAE,QAAQ,0BAA0B,KAAK,SAAS,eAAe,KAAK,SAAS,cAAc,SAAS,eAAe,GAAG;AAC9H,cAAU,IAAI,6BAA6B,QAAQ;AAAA,EACrD,OAAO;AACL,cAAU,IAAI,uBAAuB,QAAQ;AAAA,EAC/C;AACA,QAAM,eAAe;AAAA,IACnB,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI;AAAA,IAC5C,CAAC,SAAS,cAAc,SAAS,WAAW;AAAA,IAC5C,CAAC,SAAS,gBAAgB,SAAS,aAAa;AAAA,IAChD,CAAC,SAAS,UAAU,SAAS,OAAO;AAAA,EACtC;AACA,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,MAAM,GAAG,WAAW,YAAY;AAC/E;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kCAAkC,MAAM;AAAA,EAC1C,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,KAAK,IAAI;AAC/B,SAAK,cAAc,SAAS;AAC5B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,SAAS,SAAS,QAAQ;AAChC,UAAM,UAAU,SAAS,QAAQ;AACjC,UAAM,aAAa,SAAS,cAAc,SAAS;AACnD,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,wBAOI;AAAA;AAAA;AAAA;AAAA;AAAA,8BAKM,SAAS;AAAA,kCACL,SAAS;AAAA,iCACV,kBAAkB;AAAA;AAAA,kCAEjB,SAAS;AAAA;AAAA;AAAA;AAAA,oCAIP,SAAS;AAAA,mCACV,iBAAiB;AAAA;AAAA,oCAEhB,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAa3C;AACF;AACA,IAAI,iCAAiC,MAAM;AAAA,EACzC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,MAAM,GAAG;AAC/B,SAAK,cAAc,SAAS;AAC5B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,SAAS,eAAe,IAAI,SAAS,QAAQ;AACnD,UAAM,UAAU,cAAc,IAAI,SAAS,QAAQ;AACnD,UAAM,aAAa,SAAS,cAAc,SAAS;AACnD,SAAK,WAAW;AAAA,iCACa,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAYZ;AAAA,gDACgB;AAAA;AAAA,oCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA,yBAKpB;AAAA;AAAA,kCAES;AAAA,kDACgB;AAAA;AAAA,sCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,2BAMpB;AAAA;AAAA;AAAA,oCAGS;AAAA,8BACN;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAU5B;AACF;AAGA,SAAS,qCAAqC,MAAM;AAClD,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,IAAI;AAClB,QAAM,EAAE,SAAAA,UAAS,WAAW,KAAK,MAAM,iBAAiB,YAAY,IAAI;AACxE,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,aAAaA,UAAS,WAAW,MAAM,iBAAiB,IAAI;AAC7H,QAAM,UAAU,IAAI,gCAAgC,QAAQ;AAC5D,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,EAAE,GAAG,SAAS;AAC7D;AACA,IAAI,6CAA6C;AAAA,EAC/C,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,oCAAoC,MAAM;AACjD,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,SAAAA,UAAS,WAAW,KAAK,MAAM,iBAAiB,WAAW,IAAI;AACvE,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,IAAI;AACjI,QAAM,UAAU,IAAI,+BAA+B,QAAQ;AAC3D,SAAO,SAAS,gBAAgB,SAAS,CAAC,IAAI,MAAM,GAAG,SAAS;AAClE;AACA,IAAI,4CAA4C;AAAA,EAC9C,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAYZ,OAAM;AAChB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,CAACA,OAAMA,KAAI;AAC9B,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAOlB;AACF;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,WAAW,CAAC,GAAG,EAAE,OAAO,GAAG,EAAE,KAAK;AACxC,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,OAAO,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,KAAK,EAAE,EAAE,CAAC;AACrF,QAAM,UAAU,IAAI,YAAY,KAAK;AACrC,QAAM,MAAM,SAAS,gBAAgB,SAAS,CAAC,IAAI,GAAG,KAAK,KAAK;AAChE,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC1F,WAAS,8BAA8B,IAAI;AAC3C,WAAS,8BAA8B,GAAG;AAC1C,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,cAAc,SAAS;AAC5B,UAAM,EAAE,UAAU,SAAS,SAAS,cAAc,aAAa,cAAc,aAAa,gBAAgB,cAAc,IAAI;AAC5H,UAAM,EAAE,KAAK,QAAQ,MAAM,QAAQ,IAAI;AACvC,SAAK,WAAW;AAAA,oCACgB,iBAAiB;AAAA,iCACpB,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAad;AAAA,iCACG;AAAA;AAAA,kCAEC;AAAA,kCACA;AAAA,qCACG;AAAA;AAAA,sCAEC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAiBpC;AACF;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAY,UAAS,KAAK,MAAM,UAAU,IAAI;AAC1C,QAAM,WAAW,qBAAqB,sBAAsB,EAAE,OAAO,OAAO,OAAOA,UAAS,MAAM,QAAQ,SAAS;AACnH,MAAI;AACJ,QAAM,UAAU,IAAI,kBAAkB,QAAQ;AAC9C,QAAM,SAAS,gBAAgB,SAAS,CAAC,GAAG,MAAM,GAAG,SAAS;AAC9D,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,SAAS,EAAE,CAAC;AAC3G,WAAS,8BAA8B,GAAG;AAC1C,SAAO;AACT;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,SAAS,IAAI;AACrB,QAAM,UAAU;AAChB,QAAM,EAAE,SAAS,YAAY,OAAO,IAAI,qBAAqB,qBAAqB,UAAU,QAAQ,MAAM;AAC1G,uBAAqB,oBAAoB,QAAQ,QAAQ,QAAQ,OAAO;AACxE,QAAM,EAAE,MAAM,MAAM,IAAI,qBAAqB,qBAAqB,YAAY,MAAM;AACpF,QAAM,SAAS,MAAM;AACrB,MAAI,MAAM;AACV,MAAI,mBAAmB,QAAQ;AAC/B,QAAM,mBAAmB,CAAC;AAC1B,WAAS,KAAK,GAAG,KAAK,QAAQ,EAAE,IAAI;AAClC,eAAW,UAAU,MAAM,KAAK;AAC9B,YAAM,EAAE,oBAAoB,MAAM,YAAY,aAAa,IAAI,qBAAqB,qBAAqB,kBAAkB,OAAO,OAAO;AACzI,UAAI;AACJ,UAAI,qBAAqB,sBAAsB,IAAI,GAAG;AACpD,YAAI,QAAQ;AAAA,MACd,OAAO;AACL,YAAI,WAAW,EAAE,QAAQ,EAAE,GAAG,QAAQ,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AACrF,yBAAiB,KAAK,CAAC;AAAA,MACzB;AACA,YAAM,cAAc,EAAE,MAAM,MAAM;AAClC,eAAS,IAAI,GAAG,IAAI,aAAa,QAAQ,EAAE,GAAG;AAC5C,oBAAY,OAAO,aAAa,IAAI,GAAG,CAAC;AAAA,MAC1C;AACA,UAAI,CAAC,aAAa,YAAY,EAAE,OAAO,WAAW,GAAG;AACnD,YAAI,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAChF,yBAAiB,KAAK,CAAC;AAAA,MACzB;AACA,UAAI,QAAQ,MAAM;AAChB,cAAM;AAAA,MACR,OAAO;AACL,cAAM,UAAU,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,IAAI,GAAG,SAAS,SAAS,CAAC;AAC/D,yBAAiB,KAAK,GAAG;AAAA,MAC3B;AAAA,IACF;AACA,QAAI,KAAK,SAAS,GAAG;AACnB,UAAI,KAAK,OAAO,GAAG;AACjB,cAAM,KAAK;AAAA,UACT,QAAQ,EAAE,GAAG,IAAI;AAAA,UACjB,SAAS;AAAA,UACT,OAAO;AAAA,YACL,MAAM,KAAK,OAAO,QAAQ,SAAS;AAAA,YACnC,UAAU;AAAA,UACZ;AAAA,QACF,CAAC;AACD,yBAAiB,KAAK,GAAG;AAAA,MAC3B;AACA;AAAA,IACF;AAAA,EACF;AACA,aAAW,cAAc,kBAAkB;AACzC,QAAI,eAAe,KAAK;AACtB;AAAA,IACF;AACA,aAAS,8BAA8B,UAAU;AAAA,EACnD;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AACX,IAAI,aAAa;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUjB,IAAI,OAAO,iBAAiB,EAAE,WAAW,MAAM,iBAAiB,WAAW,CAAC;AAC5E,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU;AACd,IAAI,iBAAiB;AAAA;AAAA;AAAA;AAIrB,IAAI,WAAW,CAAC,SAAS;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,IAAI,EAAE,IAAI;AAClB,QAAM,UAAU,IAAI,EAAE,QAAQ,8BAA8B,IAAI,IAAI,sBAAsB,gBAAgB,GAAG,OAAO,EAAE,KAAK,IAAI,IAAI,gBAAgB,SAAS,GAAG,OAAO,EAAE,KAAK;AAC7K,SAAO,SAAS,gBAAgB,SAAS,CAAC,IAAI,CAAC,GAAG,GAAG,KAAK;AAC5D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe;AAAA;AAAA;AAGnB,IAAI,QAAQ;AACZ,IAAI,SAAS,kBAAkB;AAAA,EAC7B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,OAAO;AAAA,EACP,eAAe;AACjB,CAAC;AACD,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM;AAAA;AAAA;AAAA;AAAA,cAII,qBAAqB;AAAA,eACpB,qBAAqB;AAAA,eACrB,qBAAqB;AAAA,eACrB,qBAAqB;AAAA,eACrB,qBAAqB;AAAA,eACrB,qBAAqB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAOpC,IAAI,OAAO,iBAAiB,EAAE,WAAW,IAAI,CAAC;AAC9C,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM,0BAA0B;AAAA;AAAA;AAGpC,IAAI,aAAa;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUjB,IAAI,OAAO,iBAAiB;AAAA,EAC1B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,eAAe;AAAA,EACf,OAAO;AACT,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,IAAI,IAAI;AAChB,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,YAAY,OAAO,MAAM;AAC/B,QAAM,WAAW,OAAO,MAAM,MAAM;AACpC,MAAI,OAAO;AACX,MAAI,MAAM,GAAG;AACX,iBAAa,OAAO,EAAE,YAAY,MAAM,KAAK,MAAM,iCAAiC,EAAE,YAAY,OAAO,YAAY;AACrH,WAAO,YAAY,MAAM;AAAA,EAC3B;AACA,WAAS,OAAO,MAAM,GAAG,CAAC;AAC1B,SAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC1F;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ;AACZ,IAAI,SAAS,iBAAiB,EAAE,WAAW,OAAO,iBAAiB,OAAO,eAAe,aAAa,CAAC;AACvG,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa,MAAM;AAAA,EACrB,YAAY,WAAW,YAAY,SAAS;AAC1C,SAAK,gBAAgB,CAAC,QAAQ,MAAM;AACpC,UAAM,WAAW,WAAW;AAC5B,SAAK,cAAc;AACnB,UAAM,4BAA4B,UAAU,SAAS,KAAK,OAAO,UAAU,KAAK;AAChF,UAAM,oBAAoB,UAAU,GAAG,eAAe;AACtD,QAAI;AACJ,QAAI,cAAc,QAAQ;AACxB,iBAAW;AAAA,IACb,WAAW,cAAc,QAAQ;AAC/B,iBAAW;AAAA,IACb,OAAO;AACL,YAAM,IAAI,MAAM,sDAAsD,YAAY;AAAA,IACpF;AACA,SAAK,WAAW;AAAA,yCACqB;AAAA;AAAA;AAAA,UAG/B;AAAA;AAAA;AAAA;AAAA,kDAIwC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAMpB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,yDAS2B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAWvD;AACF;AAGA,SAAS,SAAS,GAAG,SAAS,UAAU;AACtC,QAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,QAAMc,cAAY,aAAa,cAAc,EAAE,KAAK;AACpD,QAAM,qBAAqB,EAAE,MAAM,EAAE,MAAM,SAAS;AACpD,QAAM,QAAQA,cAAY;AAC1B,QAAM,UAAU,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,OAAO,kBAAkB,EAAE,EAAE,CAAC;AAC5G,QAAM,SAAS,QAAQ;AACvB,QAAM,cAAc,IAAI,WAAW,QAAQ,QAAQ,OAAO;AAC1D,QAAM,cAAc,IAAI,WAAW,QAAQ,QAAQ,OAAO;AAC1D,QAAM,SAAS;AAAA,IACb;AAAA,MACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,MACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,MACrC,OAAO;AAAA,IACT;AAAA,IACA;AAAA,MACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,MACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,MACrC,OAAO;AAAA,IACT;AAAA,EACF;AACA,QAAM,WAAW,SAAS,gBAAgB,aAAa,QAAQ,SAAS;AACxE,QAAM,WAAW,SAAS,gBAAgB,aAAa,QAAQ,SAAS;AACxE,QAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,MAAM,UAAU,MAAM,SAAS,GAAG,SAAS,SAAS,CAAC;AAChG,WAAS,8BAA8B,QAAQ;AAC/C,WAAS,8BAA8B,QAAQ;AAC/C,QAAM,wBAAwB,SAAS,EAAE,QAAQ,EAAE,GAAG,cAAc,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,EAAE,MAAM,EAAE,CAAC;AACrH,WAAS,8BAA8B,OAAO;AAC9C,WAAS,8BAA8B,aAAa;AACpD,SAAO;AACT;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,SAAO,SAAS,QAAQ,OAAO,QAAQ;AACzC;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,OAAO,OAAO;AACxB,SAAK,cAAc,CAAC;AACpB,SAAK,iBAAiB,CAAC,EAAE,MAAM,SAAS,MAAM,QAAQ,CAAC;AACvD,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAMlB;AACF;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,IAAI;AACzB,MAAI,EAAE,MAAM,IAAI;AAChB,UAAQ,SAAS,aAAa,WAAW,KAAK;AAC9C,MAAI,UAAU,UAAU;AACtB,UAAM,SAAS,aAAa,kBAAkB,OAAO,aAAa,cAAc,KAAK,CAAC;AACtF,WAAO,KAAK,KAAK;AACjB,WAAO,SAAS,eAAe,OAAO,OAAO,MAAM;AAAA,EACrD,OAAO;AACL,UAAM,UAAU,IAAI,YAAY,OAAO,KAAK;AAC5C,UAAM,eAAe,CAAC,CAAC,KAAK,CAAC;AAC7B,WAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,OAAO,YAAY;AAAA,EAClE;AACF;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,YAAY;AACtB,SAAK,gBAAgB,CAAC,OAAO;AAC7B,SAAK,cAAc,CAAC;AACpB,UAAM,aAAa,WAAW;AAC9B,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,yBAKK;AAAA;AAAA,uCAEc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAQrC;AACF;AAGA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AAC7C,UAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,UAAM,eAAe;AACrB,UAAM,UAAU,IAAI,qBAAqB,OAAO,KAAK;AACrD,UAAM,SAAS,aAAa,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO,KAAK;AAC3E,WAAO;AAAA,EACT;AACF;AAGA,IAAI,QAAQ;AACZ,IAAI,SAAS,iBAAiB,EAAE,WAAW,OAAO,iBAAiB,OAAO,eAAe,aAAa,CAAC;AACvG,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWd,IAAI,iBAAiB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAsBrB,IAAI,YAAY,kBAAkB,EAAE,WAAW,SAAS,iBAAiB,gBAAgB,OAAO,QAAQ,CAAC;AACzG,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,UAAM,OAAO,mBAAmB;AAChC,UAAM,CAAC,QAAQ,KAAK,IAAI;AACxB,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,uDAMmC,YAAY;AAAA;AAAA,wBAE3C,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAe3B;AACF;AAGA,IAAI,0BAA0B,MAAM;AAAA,EAClC,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,UAAM,OAAO,mBAAmB;AAChC,UAAM,CAAC,QAAQ,KAAK,IAAI;AACxB,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAeU,YAAY;AAAA,4BACd,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAgBvB,KAAK;AAAA;AAAA;AAAA,EAGb;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AACA,IAAI;AACJ,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,MAAI,EAAE,OAAO,IAAI;AACjB,QAAM,EAAE,YAAY,IAAI;AACxB,QAAM,UAAU,OAAO,qBAAqB,eAAe,kBAAkB;AAC7E,QAAM,UAAU,OAAO,qBAAqB,eAAe,kBAAkB;AAC7E,QAAM,CAAC,OAAO,MAAM,IAAI,UAAU;AAAA,IAChC,OAAO;AAAA,IACP,OAAO;AAAA,EACT,IAAI,CAAC,OAAO,OAAO,OAAO,MAAM;AAChC,QAAM,WAAW,CAAC,QAAQ,KAAK;AAC/B,QAAM,WAAW,CAAC,QAAQ,OAAO,WAAW;AAC5C,MAAI,WAAW,SAAS;AACtB,QAAI,wBAAwB,MAAM;AAChC,6BAAuB,SAAS,cAAc,QAAQ,EAAE,WAAW,IAAI;AAAA,IACzE;AACA,yBAAqB,OAAO,QAAQ;AACpC,yBAAqB,OAAO,SAAS;AACrC,yBAAqB,UAAU,QAAQ,GAAG,GAAG,OAAO,MAAM;AAC1D,aAAS,qBAAqB;AAAA,EAChC;AACA,QAAM,kBAAkB,SAAS,eAAe,UAAU,OAAO;AACjE,WAAS,QAAQ,IAAI,gBAAgB,MAAM,EAAE,QAAQ,aAAa;AAClE,WAAS,MAAM,yBAAyB,SAAS,WAAW,gBAAgB,MAAM,GAAG,MAAM;AAC3F,QAAM,UAAU,IAAI,EAAE,QAAQ,YAAY,IAAI,IAAI,wBAAwB,QAAQ,IAAI,IAAI,kBAAkB,QAAQ;AACpH,QAAM,MAAM,SAAS,gBAAgB,SAAS,CAAC,eAAe,GAAG,OAAO;AACxE,WAAS,YAAY,gBAAgB,MAAM;AAC3C,SAAO;AACT;AAGA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAd,UAAS,KAAK,MAAM,YAAY,WAAW,iBAAiB,YAAY,aAAa,eAAe,IAAI;AAChH,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,OAAO,WAAW;AAC5I,MAAI;AACJ,QAAM,gBAAgB,CAAC;AACvB,MAAI,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,KAAK,SAAS,mBAAmB,KAAK,SAAS,kBAAkB,KAAK,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,MAAM,SAAS,QAAQ,SAAS,UAAU,SAAS,QAAQ,SAAS,UAAU;AACtQ,UAAM,eAAe;AAAA,MACnB;AAAA,MACA;AAAA,MACA;AAAA,MACA,SAAS;AAAA,MACT;AAAA,MACA,YAAY;AAAA,MACZ;AAAA,MACA;AAAA,IACF,CAAC;AAAA,EACH,WAAW,IAAI,EAAE,QAAQ,mBAAmB,GAAG;AAC7C,UAAM,iBAAiB;AAAA,MACrB;AAAA,MACA;AAAA,MACA;AAAA,MACA,SAAS;AAAA,MACT;AAAA,MACA,YAAY;AAAA,MACZ;AAAA,MACA;AAAA,IACF,CAAC;AAAA,EACH,OAAO;AACL,UAAM,UAAU,QAAQ;AACxB,UAAM,4BAA4B,0BAA0B;AAC5D,UAAM,oBAAoB,gBAAgB;AAC1C,UAAM,kBAAkB,cAAc,6BAA6B,aAAa,KAAK,IAAI;AACzF,UAAM,UAAU,IAAI,cAAc,UAAU,SAAS,iBAAiB,2BAA2B,iBAAiB;AAClH,UAAM,UAAU,CAAC,GAAG,MAAM;AAC1B,UAAM,2BAA2B,CAAC,QAAQ,gBAAgB;AACxD,UAAI,gBAAgB,UAAU,OAAO,MAAM,WAAW,KAAK,OAAO,MAAM,OAAO,GAAG;AAChF,cAAM,eAAe,SAAS;AAAA,UAC5B,QAAQ,EAAE,GAAG,OAAO;AAAA,UACpB,SAAS;AAAA,UACT,OAAO,EAAE,OAAO,CAAC,OAAO,MAAM,IAAI,GAAG,CAAC,EAAE;AAAA,QAC1C,CAAC;AACD,sBAAc,KAAK,YAAY;AAC/B,eAAO;AAAA,MACT;AACA,aAAO;AAAA,IACT;AACA,QAAI,SAAS;AACX,cAAQ,KAAK,yBAAyB,MAAM,UAAU,CAAC;AAAA,IACzD;AACA,QAAI,2BAA2B;AAC7B,cAAQ,KAAK,yBAAyB,wBAAwB,UAAU,CAAC;AAAA,IAC3E;AACA,QAAI,mBAAmB;AACrB,YAAM,kBAAkB,SAAS,eAAe,CAAC,GAAG,WAAW,aAAa,kBAAkB,gBAAgB,SAAS,CAAC;AACxH,cAAQ,KAAK,eAAe;AAC5B,oBAAc,KAAK,eAAe;AAAA,IACpC;AACA,UAAM,SAAS,gBAAgB,SAAS,SAAS,SAAS;AAAA,EAC5D;AACA,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,SAAS,EAAE,CAAC;AAC3G,gBAAc,KAAK,GAAG;AACtB,gBAAc,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACxE,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,sBAAsB,MAAM;AACnC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,WAAW,iBAAiB,YAAY,aAAa,eAAe,IAAI;AACpG,QAAM,gBAAgB,CAAC;AACvB,MAAI,aAAa;AACjB,MAAI,cAAc,MAAM;AACtB,iBAAa,CAAC,GAAG,CAAC;AAAA,EACpB;AACA,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,UAAU,GAAG,MAAM,gFAAgFA,2BAA0B,aAAa;AAC3N,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,YAAY,MAAM,iBAAiB,IAAI;AAC/H,QAAM,0BAA0B,IAAI,EAAE,QAAQ,0BAA0B,KAAK,SAAS,eAAe,KAAK,SAAS,cAAc,SAAS,eAAe;AACzJ,QAAM,kBAAkB,cAAc,6BAA6B,aAAa,uBAAuB,IAAI;AAC3G,QAAM,gBAAgB,CAAC,GAAG,MAAM;AAChC,QAAM,UAAU,QAAQ;AACxB,QAAM,4BAA4B,0BAA0B;AAC5D,QAAM,oBAAoB,gBAAgB;AAC1C,MAAI,SAAS;AACX,kBAAc,KAAK,IAAI;AAAA,EACzB;AACA,MAAI,2BAA2B;AAC7B,kBAAc,KAAK,sBAAsB;AAAA,EAC3C;AACA,MAAI,mBAAmB;AACrB,UAAM,kBAAkB,SAAS,eAAe,CAAC,GAAG,WAAW,aAAa,kBAAkB,gBAAgB,SAAS,CAAC;AACxH,kBAAc,KAAK,eAAe;AAClC,kBAAc,KAAK,eAAe;AAAA,EACpC;AACA,MAAI;AACJ,MAAI,yBAAyB;AAC3B,cAAU,IAAI,6BAA6B,UAAU,SAAS,iBAAiB,2BAA2B,iBAAiB;AAAA,EAC7H,OAAO;AACL,cAAU,IAAI,uBAAuB,UAAU,SAAS,iBAAiB,2BAA2B,iBAAiB;AAAA,EACvH;AACA,QAAM,eAAe;AAAA,IACnB,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI;AAAA,IAC5C,CAAC,SAAS,cAAc,SAAS,WAAW;AAAA,IAC5C,CAAC,SAAS,gBAAgB,SAAS,aAAa;AAAA,IAChD,CAAC,SAAS,UAAU,SAAS,OAAO;AAAA,EACtC;AACA,QAAM,SAAS,SAAS,gBAAgB,SAAS,eAAe,WAAW,YAAY;AACvF,gBAAc,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACxE,SAAO;AACT;AACA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,YAAY,UAAUA,UAAS,OAAO,aAAa;AACjD,SAAK,WAAW;AAChB,SAAK,UAAUA;AACf,SAAK,cAAc;AACnB,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,cAAc;AACnB,UAAM,cAAc,kBAAkBA,SAAQ,MAAM;AACpD,UAAM,QAAQ,kBAAkB,MAAM,MAAM;AAC5C,UAAM,eAAe,KAAK,WAAW,IAAI,eAAe;AACxD,UAAM,kBAAkB,kBAAkB,YAAY,MAAM;AAC5D,UAAM,oBAAoB,YAAY,SAAS,IAAI,mBAAmB;AACtE,SAAK,WAAW;AAAA,UACV,yBAAyB,eAAe,KAAK;AAAA,UAC7C,iCAAiC,mBAAmB,KAAK;AAAA;AAAA,YAEvD;AAAA;AAAA;AAAA,gCAGoB,KAAK;AAAA;AAAA;AAAA,wDAGmB;AAAA,sCAClB;AAAA;AAAA;AAAA;AAAA;AAAA,EAKpC;AACF;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,QAAQ,QAAQ,IAAI;AAC5B,QAAM,eAAe,QAAQ;AAC7B,QAAM,YAAY,aAAa,aAAa,SAAS;AACrD,QAAM,aAAa,aAAa,cAAc,OAAO,KAAK;AAC1D,QAAM,CAAC,aAAa,WAAW,WAAWA,QAAO,IAAI,qBAAqB,mBAAmB,QAAQ,OAAO;AAC5G,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,WAAW,SAAS,EAAE,EAAE,CAAC;AACvH,QAAM,WAAW,SAAS;AAAA,IACxB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,aAAa,cAAc,OAAO,KAAK,IAAI,WAAW,SAAS,EAAE;AAAA,EACpF,CAAC;AACD,MAAI,SAAS,mBAAmB,CAAC,QAAQ,OAAO,CAAC,KAAK,OAAO,UAAU,UAAU;AAC/E,UAAM,cAAc,SAAS,SAAS,QAAQ,MAAM;AACpD,UAAM,YAAY,SAAS,WAAW,MAAM;AAC5C,UAAM,WAAW,gBAAgB,aAAa,WAAW,OAAO,OAAO,WAAW,WAAW,WAAWA,UAAS,OAAO,OAAO,UAAU;AACzI,WAAO,SAAS,eAAe,aAAa,OAAO,OAAO,SAAS,MAAM;AAAA,EAC3E;AACA,QAAM,UAAU,IAAI,gBAAgB,WAAWA,UAAS,CAAC,WAAW,SAAS,GAAG,OAAO,KAAK;AAC5F,QAAM,MAAM,SAAS,gBAAgB,SAAS,CAAC,UAAU,cAAc,GAAG,SAAS,KAAK;AACxF,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAClG,WAAS,8BAA8B,cAAc;AACrD,WAAS,8BAA8B,QAAQ;AAC/C,WAAS,8BAA8B,GAAG;AAC1C,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,QAAQ,aAAa;AAC/B,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,cAAc;AACnB,SAAK,OAAO,YAAY;AACxB,UAAM,QAAQ,kBAAkB,KAAK,IAAI;AACzC,UAAM,eAAe,iBAAiB,QAAQ,CAAC;AAC/C,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA;AAAA,oDAE0C,OAAO;AAAA,oCACvB;AAAA;AAAA;AAAA,EAGlC;AACF;AACA,SAAS,iBAAiB,QAAQ,MAAM;AACtC,QAAM,gBAAgB,CAAC,WAAW,WAAW,WAAW,SAAS;AACjE,QAAM,eAAe,CAAC;AACtB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,QAAI,OAAO,GAAG;AACZ,mBAAa,KAAK,OAAO;AAAA,IAC3B,OAAO;AACL,mBAAa,KAAK,GAAG,cAAc,KAAK;AAAA,IAC1C;AAAA,EACF;AACA,SAAO,aAAa,KAAK;AAC3B;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAM,UAAU,IAAI;AAC5B,QAAM,aAAa,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AAC9D,MAAI,IAAI,EAAE,IAAI,OAAO,GAAG;AACtB,UAAM,cAAc,SAAS,SAAS,QAAQ,MAAM;AACpD,UAAM,UAAU,EAAE,MAAM;AACxB,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,EAAE,IAAI;AAC9C,YAAMH,SAAQ,YAAY;AAC1B,mBAAa,OAAOA,UAAS,UAAU,KAAKA,UAAS,GAAG,MAAM,6BAA6BA,wBAAuB,UAAU,IAAI;AAAA,IAClI;AAAA,EACF;AACA,QAAM,YAAY,qBAAqB,aAAa,yBAAyB,GAAG,SAAS,YAAY,SAAS;AAC9G,QAAM,cAAc,aAAa,cAAc,QAAQ,KAAK;AAC5D,QAAM,YAAY,CAAC;AACnB,QAAM,WAAW,SAAS;AAAA,IACxB,QAAQ,EAAE,EAAE;AAAA,IACZ,SAAS;AAAA,IACT,OAAO;AAAA,MACL,OAAO;AAAA,QACL,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,MACZ;AAAA,IACF;AAAA,EACF,CAAC;AACD,QAAM,eAAe,SAAS;AAAA,IAC5B,QAAQ,EAAE,GAAG,QAAQ;AAAA,IACrB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,UAAU,WAAW,cAAc,UAAU,SAAS,EAAE;AAAA,EAC3E,CAAC;AACD,YAAU,KAAK,QAAQ;AACvB,YAAU,KAAK,YAAY;AAC3B,QAAM,qBAAqB;AAAA,IACzB,UAAU;AAAA,IACV,UAAU;AAAA,IACV,cAAc,UAAU;AAAA,IACxB,UAAU;AAAA,EACZ;AACA,MAAI,SAAS,mBAAmB,CAAC,GAAG,OAAO,CAAC,KAAK,EAAE,UAAU,UAAU;AACrE,UAAM,aAAa,SAAS,WAAW,YAAY;AACnD,UAAM,OAAO,SAAS,WAAW,QAAQ;AACzC,UAAM,SAAS,gBAAgB,MAAM,YAAY,kBAAkB;AACnE,cAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,WAAO,SAAS,eAAe,UAAU,aAAa,OAAO,OAAO,OAAO,MAAM;AAAA,EACnF;AACA,QAAM,UAAU,IAAI,cAAc,SAAS,OAAO,kBAAkB;AACpE,QAAM,MAAM,SAAS,gBAAgB,SAAS,CAAC,UAAU,YAAY,GAAG,SAAS,KAAK;AACtF,YAAU,KAAK,GAAG;AAClB,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,UAAU,YAAY,EAAE,CAAC;AAC5G,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU;AACd,IAAI,iBAAiB;AAAA;AAAA;AAGrB,IAAI,WAAW,kBAAkB;AAAA,EAC/B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,eAAe;AAAA,EACf,OAAO;AACT,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB;AACpB,IAAI,uBAAuB;AAAA;AAAA;AAG3B,IAAI,gBAAgB,kBAAkB;AAAA,EACpC,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,OAAO;AAAA,EACP,eAAe;AACjB,CAAC;AACD,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,SAAO,SAAS,QAAQ,MAAM,QAAQ;AACxC;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY;AAChB,IAAI,YAAY,iBAAiB,EAAE,WAAW,WAAW,OAAO,OAAO,CAAC;AACxE,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS;AACb,IAAI,SAAS,iBAAiB,EAAE,WAAW,QAAQ,OAAO,OAAO,CAAC;AAClE,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS;AACb,IAAI,SAAS,iBAAiB,EAAE,WAAW,QAAQ,OAAO,OAAO,CAAC;AAClE,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AACX,IAAI,cAAc;AAAA;AAAA;AAGlB,IAAI,QAAQ,kBAAkB;AAAA,EAC5B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,eAAe;AAAA,EACf,OAAO;AACT,CAAC;AACD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa;AACjB,IAAI,oBAAoB;AAAA;AAAA;AAGxB,IAAI,aAAa,kBAAkB;AAAA,EACjC,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,eAAe;AAAA,EACf,OAAO;AACT,CAAC;AACD,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,IAAI,IAAI;AAC7B,QAAM,UAAU,gBAAgB,OAAO,MAAM,GAAG;AAChD,SAAO,SAAS,eAAe,CAAC,QAAQ,MAAM,GAAG,WAAW,OAAO;AACrE;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM,0BAA0B;AAAA;AAAA;AAGpC,IAAI,aAAa;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AASjB,IAAI,OAAO,iBAAiB,EAAE,WAAW,KAAK,iBAAiB,YAAY,eAAe,WAAW,CAAC;AACtG,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,0BAA0B;AAAA;AAAA;AAGtC,IAAI,SAAS,iBAAiB,EAAE,WAAW,MAAM,CAAC;AAClD,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc;AAClB,IAAI,qBAAqB;AAAA;AAAA;AAAA;AAAA;AAKzB,IAAI,cAAc,kBAAkB;AAAA,EAClC,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,OAAO;AACT,CAAC;AACD,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc;AAClB,IAAI,cAAc,iBAAiB,EAAE,WAAW,YAAY,CAAC;AAC7D,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa;AACjB,IAAI,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAMxB,IAAI,aAAa,kBAAkB,EAAE,WAAW,YAAY,iBAAiB,mBAAmB,OAAO,OAAO,CAAC;AAC/G,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa,MAAM;AAAA,EACrB,YAAY,QAAQ,QAAQ,MAAMa,QAAO,MAAM;AAC7C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,CAAC;AACpB,UAAM,MAAM;AACZ,UAAM,OAAO,OAAO,KAAK;AACzB,SAAK,cAAc;AACnB,QAAI;AACJ,UAAM,QAAQ,SAAS,iBAAiBA;AACxC,QAAI,SAAS,KAAK;AAChB,oBAAc,eAAe;AAAA,IAC/B,WAAW,SAAS,GAAG;AACrB,oBAAc,QAAQ;AAAA,IACxB,OAAO;AACL,oBAAc,WAAW,mBAAmB;AAAA,IAC9C;AACA,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,wBASI,aAAa;AAAA;AAAA,oCAED;AAAA;AAAA;AAAA;AAAA;AAAA,0BAKV;AAAA;AAAA;AAAA;AAAA,EAIxB;AACF;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,QAAQ,QAAQ,MAAMA,QAAO,MAAM;AAC7C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,CAAC;AACpB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,UAAM,MAAM;AACZ,UAAM,OAAO,OAAO,KAAK;AACzB,SAAK,cAAc;AACnB,QAAI;AACJ,UAAM,QAAQ,SAAS,iBAAiBA;AACxC,QAAI,SAAS,KAAK;AAChB,oBAAc,eAAe;AAAA,IAC/B,WAAW,SAAS,GAAG;AACrB,oBAAc,QAAQ;AAAA,IACxB,OAAO;AACL,oBAAc,WAAW,mBAAmB;AAAA,IAC9C;AACA,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAQY,KAAK,YAAY;AAAA,gCACjB,KAAK,YAAY;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,iCAehB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,yBAWR,aAAa;AAAA;AAAA;AAAA,6DAGuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0CAqBnB;AAAA;AAAA;AAAA;AAAA,EAIxC;AACF;AAGA,IAAI,MAAM,CAAC,SAAS;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,aAAa,MAAM,OAAAA,QAAO,KAAK,IAAI;AAC3C,QAAM,UAAU,IAAI,EAAE,QAAQ,0BAA0B,IAAI,IAAI,iBAAiB,EAAE,OAAO,aAAa,MAAMA,QAAO,IAAI,IAAI,IAAI,WAAW,EAAE,OAAO,aAAa,MAAMA,QAAO,IAAI;AAClL,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACvD;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,YAAY,aAAa,MAAMA,QAAO,MAAM;AACtD,SAAK,gBAAgB,CAAC,cAAc,eAAe,IAAI;AACvD,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc;AACnB,SAAK,QAAQ,WAAW;AACxB,SAAK,cAAc;AACnB,SAAK,OAAO;AACZ,SAAK,QAAQA;AACb,SAAK,OAAO;AACZ,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAQU,KAAK;AAAA,oDACiB;AAAA,yCACX,KAAK;AAAA,0BACpB;AAAA;AAAA;AAAA,sCAGY,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,yBAelBA,0BAAyB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,yCAOTA;AAAA,0BACf;AAAA;AAAA;AAAA;AAAA,0CAIgB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAexC;AACF;AAGA,IAAI,UAAU,CAAC,SAAS;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,GAAG,IAAI;AACrB,QAAM,EAAE,aAAa,MAAM,OAAAA,QAAO,KAAK,IAAI;AAC3C,QAAM,UAAU,IAAI,eAAe,EAAE,OAAO,aAAa,MAAMA,QAAO,IAAI;AAC1E,SAAO,SAAS,gBAAgB,SAAS,CAAC,GAAG,GAAG,EAAE,GAAG,EAAE,KAAK;AAC9D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,GAAG,aAAa,UAAU,UAAU;AACpD,QAAM,SAAS,aAAa,cAAc,WAAW;AACrD,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,YAAY,QAAQ;AAC1B,QAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,OAAO,CAAC,WAAW,MAAM,EAAE,GAAG,SAAS,SAAS,CAAC;AAC1G,QAAM,UAAU,OAAO,eAAe,EAAE,OAAO,OAAO,QAAQ;AAC9D,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AACzG,WAAS,8BAA8B,aAAa;AACpD,WAAS,8BAA8B,OAAO;AAC9C,SAAO;AACT;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,kBAAkB,SAAS,IAAI;AACvC,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,aAAa,eAAe,kBAAkB,EAAE,KAAK;AACtE,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,QAAM,uBAAuB,gBAAgB;AAC7C,QAAM,qBAAqB,SAAS,mBAAmB,CAAC,CAAC,CAAC;AAC1D,MAAI,WAAW;AACf,MAAI,sBAAsB;AACxB,QAAI,oBAAoB;AACtB,YAAM,WAAW,SAAS,QAAQ,IAAI,SAAS,MAAM;AACrD,YAAM,SAAS,SAAS;AACxB,YAAM,WAAW,IAAI,MAAM,KAAK;AAChC,eAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,iBAAS,MAAM,EAAE,MAAM,aAAa;AAAA,MACtC;AACA,YAAM,iBAAiB,iBAAiB,QAAQ,EAAE,OAAO,EAAE,OAAO,cAAc,QAAQ;AACxF,iBAAW,SAAS,eAAe,UAAU,EAAE,KAAK;AACpD,YAAM,eAAe,SAAS,QAAQ,IAAI,SAAS,MAAM;AACzD,mBAAa,SAAS;AAAA,IACxB,OAAO;AACL,iBAAW,eAAe,GAAG,cAAc,QAAQ;AAAA,IACrD;AACA,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAAA,EACjE;AACA,uBAAqB,2BAA2B,OAAO,MAAM,KAAK;AAClE,QAAM,CAAC,aAAa,WAAW,IAAI,qBAAqB,0BAA0B,SAAS,OAAO,IAAI;AACtG,MAAI,WAAW;AACf,MAAI,UAAU;AACZ,eAAW,qBAAqB,qBAAqB,aAAa,QAAQ;AAAA,EAC5E;AACA,MAAI;AACJ,MAAI,oBAAoB;AACtB,UAAM,WAAW,SAAS,QAAQ,IAAI,SAAS,MAAM;AACrD,UAAM,SAAS,SAAS;AACxB,UAAM,YAAY,WAAW,QAAQ,aAAa,cAAc,WAAW,GAAG,UAAU,EAAE,KAAK;AAC/F,UAAM,SAAS,eAAe,UAAU,EAAE,KAAK;AAC/C,UAAM,UAAU,SAAS,QAAQ,IAAI,IAAI,MAAM;AAC/C,YAAQ,SAAS;AAAA,EACnB,OAAO;AACL,UAAM,SAAS,UAAU,aAAa,UAAU,QAAQ;AAAA,EAC1D;AACA,MAAI,sBAAsB;AACxB,aAAS,8BAA8B,QAAQ;AAAA,EACjD;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU,qBAAqB;AAAA;AAAA;AAGnC,IAAI,iBAAiB;AAAA;AAAA;AAAA,MAGf,qBAAqB;AAAA;AAAA;AAG3B,IAAI,WAAW,kBAAkB;AAAA,EAC/B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,eAAe;AACjB,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,oBAAkB,GAAG,SAAS;AAC9B,QAAM,EAAE,YAAY,SAAAV,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY;AAClB,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,SAAS,GAAG,MAAM,wEAAwEA,2BAA0B,YAAY;AACjN,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,MAAI,SAAS,gBAAgB,KAAK,SAAS,iBAAiB,KAAK,aAAa,YAAY,SAAS,SAAS,SAAS,QAAQ,GAAG;AAC9H,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD;AACA,QAAM,iBAAiB,IAAI,cAAc,UAAU,OAAO,KAAK;AAC/D,SAAO,SAAS,gBAAgB,gBAAgB,CAAC,CAAC,GAAG,EAAE,KAAK;AAC9D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,YAAY,gBAAgB,IAAI;AACxE,QAAM,YAAY,CAAC,GAAG,GAAG,CAAC;AAC1B,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,iBAAiB,UAAU;AAClI,QAAM,iBAAiB,IAAI,cAAc,UAAU,OAAO,KAAK;AAC/D,SAAO,SAAS,gBAAgB,gBAAgB,CAAC,CAAC,GAAG,EAAE,KAAK;AAC9D;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,MAAM;AAAA,EACnC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,MAAM,QAAQ;AACpC,SAAK,cAAc,SAAS;AAC5B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,iBAAiB,SAAS;AAChC,UAAM,wBAAwB,SAAS;AACvC,UAAM,uBAAuB,SAAS;AACtC,UAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,UAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,UAAM,YAAY,wBAAwB,uBAAuB;AACjE,SAAK,WAAW;AAAA,iCACa,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAcZ;AAAA,kBACd;AAAA,gDAC8B;AAAA;AAAA,oCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA,kCAKX;AAAA,kDACgB;AAAA;AAAA,sCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAOf;AAAA;AAAA;AAAA;AAAA,qCAIK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EASnC;AACF;AACA,IAAI,2BAA2B,MAAM;AAAA,EACnC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,MAAM,QAAQ;AACpC,SAAK,cAAc,SAAS;AAC5B,UAAM,cAAc,SAAS;AAC7B,UAAM,eAAe,SAAS;AAC9B,UAAM,cAAc,SAAS;AAC7B,UAAM,gBAAgB,SAAS;AAC/B,UAAM,iBAAiB,SAAS;AAChC,UAAM,gBAAgB,SAAS;AAC/B,UAAM,uBAAuB,SAAS;AACtC,UAAM,wBAAwB,SAAS;AACvC,UAAM,uBAAuB,SAAS;AACtC,UAAM,WAAW,uBAAuB,IAAI,SAAS,QAAQ;AAC7D,UAAM,SAAS,wBAAwB,IAAI,SAAS,QAAQ;AAC5D,UAAM,UAAU,uBAAuB,IAAI,SAAS,QAAQ;AAC5D,UAAM,YAAY,uBAAuB,wBAAwB,uBAAuB;AACxF,SAAK,WAAW;AAAA,iCACa,aAAa,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAiBzB;AAAA,mBACb;AAAA,gDAC6B;AAAA;AAAA,oCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA,kCAKX;AAAA,sBACZ;AAAA,kDAC4B;AAAA;AAAA,sCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oCAMX;AAAA,wBACZ;AAAA,oDAC4B;AAAA;AAAA,wCAEZ,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAOf;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,yBAMT,2BAA2B;AAAA,yBAC3B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAUvB;AACF;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,OAAO,IAAI;AAC9B,QAAM,IAAI;AACV,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY,CAAC,GAAG,GAAG,CAAC;AAC1B,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,QAAM,4BAA4B,IAAI,cAAc,UAAU,OAAO,IAAI;AACzE,QAAM,sBAAsB,SAAS,gBAAgB,2BAA2B,CAAC,CAAC,GAAG,EAAE,KAAK;AAC5F,QAAM,yBAAyB,IAAI,yBAAyB,QAAQ;AACpE,QAAM,SAAS,SAAS,gBAAgB,wBAAwB,CAAC,IAAI,mBAAmB,GAAG,EAAE,KAAK;AAClG,WAAS,8BAA8B,mBAAmB;AAC1D,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,QAAQ,OAAO,IAAI;AACtC,QAAM,IAAI;AACV,oBAAkB,CAAC,QAAQ,MAAM,GAAG,aAAa;AACjD,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,MAAM,eAAe;AAC9G,QAAM,eAAe;AACrB,QAAM,0BAA0B,IAAI,cAAc,UAAU,OAAO,YAAY;AAC/E,QAAM,oBAAoB,SAAS,gBAAgB,yBAAyB,CAAC,CAAC,GAAG,EAAE,KAAK;AACxF,QAAM,yBAAyB,IAAI,yBAAyB,QAAQ;AACpE,QAAM,SAAS,SAAS,gBAAgB,wBAAwB,CAAC,IAAI,iBAAiB,GAAG,EAAE,KAAK;AAChG,WAAS,8BAA8B,iBAAiB;AACxD,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,uBAAuB,GAAG,qBAAqB,UAAU,UAAU;AAC1E,MAAI,UAAU,IAAI,cAAc,UAAU,OAAO,KAAK;AACtD,QAAM,aAAa,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,SAAS;AACnE,YAAU,IAAI,cAAc,UAAU,OAAO,MAAM,MAAM,mBAAmB;AAC5E,QAAM,cAAc,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,SAAS;AACpE,SAAO,CAAC,YAAY,WAAW;AACjC;AAGA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,oBAAoB,IAAI;AAChE,UAAM,eAAe;AACrB,iBAAa,OAAO,EAAE,MAAM,WAAW,GAAG,MAAM,uDAAuD,EAAE,MAAM,SAAS;AACxH,UAAM,YAAY,CAAC,GAAG,CAAC;AACvB,iBAAa,OAAO,qBAAqB,+BAA+BA,UAAS,SAAS,GAAG,MAAM,wEAAwEA,2BAA0B,YAAY;AACjN,UAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,IAAI;AACrG,UAAM,CAAC,QAAQ,OAAO,IAAI,uBAAuB,GAAG,qBAAqB,UAAU,YAAY;AAC/F,WAAO,CAAC,QAAQ,OAAO;AAAA,EACzB;AACF;AAGA,SAAS,SAAS,GAAG,aAAa,UAAU,UAAU;AACpD,QAAM,SAAS,aAAa,cAAc,WAAW;AACrD,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,YAAY,QAAQ;AAC1B,QAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,OAAO,CAAC,WAAW,MAAM,EAAE,GAAG,SAAS,SAAS,CAAC;AAC1G,QAAM,UAAU,OAAO,eAAe,WAAW,QAAQ,QAAQ;AACjE,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AACzG,WAAS,8BAA8B,aAAa;AACpD,WAAS,8BAA8B,OAAO;AAC9C,SAAO;AACT;AAGA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,EAAE,UAAU,KAAK,IAAI;AAC3B,UAAM,eAAe;AACrB,UAAM,QAAQ,EAAE,MAAM;AACtB,UAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,QAAI,OAAO;AACX,UAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,UAAM,wBAAwB,gBAAgB;AAC9C,UAAM,qBAAqB,aAAa,mBAAmB,CAAC,CAAC,CAAC;AAC9D,UAAM,gBAAgB,CAAC;AACvB,QAAI,YAAY;AAChB,QAAI,uBAAuB;AACzB,UAAI,oBAAoB;AACtB,cAAM,WAAW,aAAa,QAAQ,IAAI,UAAU,MAAM;AAC1D,cAAM,SAAS,SAAS;AACxB,cAAM,WAAW,IAAI,MAAM,KAAK;AAChC,iBAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,mBAAS,MAAM,EAAE,MAAM,aAAa;AAAA,QACtC;AACA,cAAM,kBAAkB,iBAAiB,QAAQ,EAAE,OAAO,EAAE,OAAO,cAAc,QAAQ;AACzF,oBAAY,aAAa,eAAe,UAAU,EAAE,KAAK;AACzD,cAAM,gBAAgB,aAAa,QAAQ,IAAI,UAAU,MAAM;AAC/D,sBAAc,SAAS;AAAA,MACzB,OAAO;AACL,oBAAY,eAAe,GAAG,cAAc,YAAY;AAAA,MAC1D;AACA,oBAAc,KAAK,SAAS;AAC5B,aAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAAA,IACjE;AACA,yBAAqB,2BAA2B,OAAO,MAAM,KAAK;AAClE,UAAM,CAAC,cAAc,WAAW,IAAI,qBAAqB,0BAA0B,UAAU,OAAO,IAAI;AACxG,QAAI,WAAW;AACf,QAAI,UAAU;AACZ,iBAAW,qBAAqB,qBAAqB,cAAc,QAAQ;AAAA,IAC7E;AACA,UAAM,MAAM,SAAS,WAAW,aAAa,UAAU,YAAY;AACnE,eAAW,MAAM,eAAe;AAC9B,mBAAa,8BAA8B,EAAE;AAAA,IAC/C;AACA,WAAO;AAAA,EACT;AACF;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,YAAY;AAChB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AAC1F,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,EAAE,MAAM,MAAM;AAAA,EAC1E;AACA,uBAAqB,2BAA2B,OAAO,MAAM,KAAK;AAClE,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,UAAU,OAAO,IAAI;AACpG,QAAM,SAAS,aAAa,cAAc,WAAW;AACrD,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,IAAI,MAAM,EAAE,EAAE,CAAC;AACpG,QAAM,UAAU,OAAO,KAAK,IAAI,OAAO,OAAO,QAAQ;AACtD,MAAI;AACJ,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,UAAU,QAAQ;AAC7E,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAAA,EAC1F,OAAO;AACL,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAAA,EAC1F;AACA,WAAS,8BAA8B,GAAG;AAC1C,WAAS,8BAA8B,OAAO;AAC9C,MAAI,gBAAgB,MAAM;AACxB,aAAS,8BAA8B,SAAS;AAAA,EAClD;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,UAAU,qBAAqB;AAAA;AAAA;AAGnC,IAAI,iBAAiB;AAAA;AAAA;AAAA,MAGf,qBAAqB;AAAA;AAAA;AAG3B,IAAI,WAAW,kBAAkB;AAAA,EAC/B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,eAAe;AACjB,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,QAAQ,UAAU,MAAM;AAClC,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,MAAM,GAAG,EAAE;AACtE,UAAM,OAAO,OAAO;AACpB,UAAM,QAAQ,kBAAkB,IAAI;AACpC,UAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE,EAAE,KAAK,GAAG;AAClD,UAAM,MAAM,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,GAAG,EAAE,KAAK,GAAG;AACjE,UAAM,iBAAiB,CAAC,aAAa,aAAa,aAAa,WAAW,EAAE,MAAM,GAAG,IAAI;AACzF,UAAM,SAAS,SAAS,YAAY,IAAI;AACxC,QAAI,SAAS,GAAG;AACd,WAAK,WAAW;AAAA,sBACA;AAAA,oBACF;AAAA;AAAA;AAAA;AAAA;AAAA,wCAKoB;AAAA;AAAA,4CAEI;AAAA;AAAA;AAAA;AAAA;AAKtC;AAAA,IACF;AACA,SAAK,WAAW;AAAA,QACZ,iBAAiB,SAAS;AAAA,QAC1B,eAAe,SAAS;AAAA;AAAA;AAAA,UAGtB;AAAA,8BACoB;AAAA;AAAA,iDAEmB;AAAA;AAAA,qDAEI;AAAA;AAAA;AAAA,UAG3C;AAAA,yBACe;AAAA;AAAA;AAAA,EAGvB;AACF;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,QAAQ,UAAU,MAAM;AAClC,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,MAAM,GAAG,EAAE;AACtE,UAAM,OAAO,OAAO;AACpB,UAAM,QAAQ,kBAAkB,IAAI;AACpC,UAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE,EAAE,KAAK,GAAG;AAClD,UAAM,MAAM,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,GAAG,EAAE,KAAK,GAAG;AACjE,UAAM,UAAU,YAAY,MAAM,IAAI;AACtC,UAAM,SAAS,YAAY,UAAU,IAAI;AACzC,UAAM,SAAS,GAAG,QAAQ,OAAO,QAAQ,KAAK,YAAY,OAAO;AACjE,UAAM,YAAY,SAAS,IAAI,WAAW,QAAQ,OAAO,MAAM,EAAE,EAAE,KAAK;AACxE,UAAM,SAAS,SAAS,YAAY,IAAI;AACxC,QAAI,WAAW;AACf,QAAI,SAAS,GAAG;AACd,YAAM,WAAW;AAAA,UACb;AAAA;AAAA,0CAEgC;AAAA;AAAA,8CAEI;AAAA;AAAA;AAAA;AAIxC,iBAAW;AAAA,UACP;AAAA,UACA;AAAA,sCAC4B,OAAO,KAAK,OAAO;AAAA,UAC/C,QAAQ,OAAO;AAAA,aACZ;AAAA,YACD;AAAA,wCAC4B,OAAO,KAAK,OAAO;AAAA;AAAA;AAAA,IAGvD,OAAO;AACL,YAAM,WAAW;AAAA,UACb;AAAA,UACA,cAAc;AAAA,UACd,eAAe;AAAA,UACf;AAAA;AAAA,6CAEmC;AAAA,kDACK;AAAA;AAAA;AAG5C,iBAAW;AAAA,UACP;AAAA,UACA;AAAA,sCAC4B,OAAO,KAAK,OAAO;AAAA,UAC/C,QAAQ,OAAO;AAAA,aACZ;AAAA,YACD;AAAA,wCAC4B,OAAO,KAAK,OAAO;AAAA;AAAA;AAAA,UAGjD,QAAQ,OAAO;AAAA,aACZ,QAAQ,OAAO,QAAQ,KAAK,YAAY,OAAO;AAAA,YAChD;AAAA,wCAC4B,OAAO,KAAK,OAAO;AAAA,YAC/C,QAAQ,OAAO;AAAA,eACZ;AAAA,cACD;AAAA,0CAC4B,OAAO,KAAK,OAAO;AAAA;AAAA;AAAA;AAAA,IAIzD;AACA,SAAK,WAAW;AAAA,cACN,iBAAiB,SAAS;AAAA,cAC1B,eAAe,SAAS;AAAA;AAAA;AAAA,UAG5B;AAAA;AAAA,UAEA;AAAA;AAAA;AAAA;AAAA,EAIR;AACF;AAGA,IAAI,sBAAsB,CAAC,EAAE,QAAQ,SAAS,UAAU,MAAM,MAAM;AAClE,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,UAAU,KAAK,IAAI;AAC3B,QAAM,UAAU,IAAI,EAAE,QAAQ,6BAA6B,IAAI,IAAI,uBAAuB,EAAE,OAAO,UAAU,IAAI,IAAI,IAAI,iBAAiB,EAAE,OAAO,UAAU,IAAI;AACjK,QAAM,SAAS,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AAC7D,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM;AAAA;AAEV,IAAI,aAAa;AAAA;AAAA;AAAA,MAGX,qBAAqB;AAAA;AAAA;AAG3B,IAAI,OAAO,kBAAkB;AAAA,EAC3B,WAAW;AAAA,EACX,iBAAiB;AACnB,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,qBAAqB,MAAM;AAAA,EAC7B,YAAY,WAAW,aAAa,YAAY;AAC9C,SAAK,gBAAgB,CAAC,OAAO;AAC7B,SAAK,iBAAiB,CAAC,EAAE,MAAM,QAAQ,MAAM,QAAQ,CAAC;AACtD,SAAK,cAAc,CAAC,WAAW,UAAU;AACzC,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAQU,cAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0BAUlB,cAAc;AAAA;AAAA;AAAA,EAGtC;AACF;AAGA,IAAI,MAAM;AAAA;AAAA;AAAA;AAAA;AAKV,IAAI,aAAa;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAmBjB,IAAI,UAAU,kBAAkB,EAAE,WAAW,KAAK,iBAAiB,YAAY,kBAAkB,KAAK,CAAC;AACvG,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM;AACV,IAAI,OAAO,kBAAkB;AAAA,EAC3B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,iBAAiB;AAAA,EACjB,eAAe;AACjB,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,IAAI,IAAI;AAChB,QAAM,OAAO,aAAa,eAAe,CAAC,GAAG,GAAG,OAAO,KAAK;AAC5D,QAAM,WAAW,KAAK;AAAA,IACpB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,kBAAkB,MAAM,UAAU,MAAM;AAAA,EACnD,CAAC;AACD,QAAM,gBAAgB,qBAAqB,qBAAqB,SAAS,OAAO,IAAI;AACpF,QAAM,oBAAoB,SAAS,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAClH,QAAM,IAAI,KAAK,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,kBAAkB,GAAG,SAAS,SAAS,CAAC;AACjF,QAAM,IAAI,KAAK,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,SAAS,CAAC;AACtD,QAAM,SAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,MAAM,UAAU,MAAM,EAAE,CAAC;AACnG,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAC7G,QAAM,MAAM,QAAQ,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,eAAe,GAAG,SAAS,SAAS,CAAC;AAC9E,WAAS,8BAA8B,QAAQ;AAC/C,WAAS,8BAA8B,iBAAiB;AACxD,WAAS,8BAA8B,CAAC;AACxC,WAAS,8BAA8B,CAAC;AACxC,WAAS,8BAA8B,MAAM;AAC7C,WAAS,8BAA8B,cAAc;AACrD,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,YAAY,MAAM,WAAW,IAAI;AACzC,QAAM,QAAQ,aAAa,SAAS,SAAS,EAAE,QAAQ,EAAE,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,OAAO,MAAM,SAAS,EAAE,EAAE,CAAC;AAC/H,QAAM,YAAY,MAAM,MAAM;AAC9B,QAAM,cAAc,MAAM,MAAM;AAChC,QAAM,UAAU,IAAI,mBAAmB,WAAW,aAAa,UAAU;AACzE,QAAM,eAAe,CAAC,CAAC,IAAI,CAAC;AAC5B,QAAM,MAAM,SAAS,gBAAgB,SAAS,CAAC,KAAK,GAAG,SAAS,YAAY;AAC5E,MAAI,CAAC,YAAY;AACf,aAAS,8BAA8B,KAAK;AAAA,EAC9C;AACA,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM,oBAAoB;AAAA;AAAA;AAG9B,IAAI,aAAa;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWjB,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,GAAG;AACpC,UAAM,QAAQ,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC3C,UAAM,CAAC,WAAW,QAAQ,IAAI,WAAW,MAAM,QAAQ,EAAE,OAAO,EAAE,KAAK;AACvE,WAAO,SAAS,eAAe,UAAU,EAAE,OAAO,SAAS;AAAA,EAC7D;AACA,MAAI;AACJ,MAAI,IAAI,EAAE,QAAQ,6BAA6B,GAAG;AAChD,cAAU,IAAI,qBAAqB,EAAE,OAAO,UAAU;AAAA,EACxD,OAAO;AACL,cAAU,IAAI,eAAe,EAAE,OAAO,GAAG;AAAA,EAC3C;AACA,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACvD;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,qBAAqB;AACpD,SAAS,qBAAqB,MAAM;AAClC,uBAAqB,KAAK,+FAA+F;AACzH,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,eAAe,IAAI;AACxD,QAAM,YAAY,SAAS,SAAS,MAAM,MAAM;AAChD,QAAM,aAAa,SAAS,SAAS,OAAO,MAAM;AAClD,QAAM,EAAE,gBAAgB,IAAI,yBAAyB,WAAW,YAAY,eAAe,cAAc,cAAc;AACvH,SAAO,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AACnG;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,qBAAqB;AACpD,SAAS,qBAAqB,MAAM;AAClC,uBAAqB,KAAK,+FAA+F;AACzH,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,gBAAgB,mBAAmB,IAAI;AAC5E,QAAM,YAAY,SAAS,SAAS,MAAM,MAAM;AAChD,QAAM,aAAa,SAAS,SAAS,OAAO,MAAM;AAClD,QAAM,EAAE,iBAAiB,aAAa,IAAI,yBAAyB,WAAW,YAAY,eAAe,cAAc,gBAAgB,kBAAkB;AACzJ,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AAAA,IAC1F,SAAS,eAAe,CAAC,GAAG,SAAS,IAAI,WAAW,CAAC,YAAY,CAAC,CAAC;AAAA,EACrE;AACF;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,2BAA2B,qBAAqB;AACpD,SAAS,qBAAqB,MAAM;AAClC,uBAAqB,KAAK,+FAA+F;AACzH,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,gBAAgB,aAAa,IAAI;AACtE,QAAM,YAAY,SAAS,SAAS,MAAM,MAAM;AAChD,QAAM,aAAa,SAAS,SAAS,OAAO,MAAM;AAClD,QAAM,mBAAmB;AACzB,QAAM,kBAAkB;AACxB,QAAM,oBAAoB;AAC1B,QAAM,kBAAkB;AACxB,QAAM,EAAE,iBAAiB,eAAe,IAAI,yBAAyB,WAAW,YAAY,kBAAkB,iBAAiB,mBAAmB,eAAe;AACjK,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AAAA,IAC1F,SAAS,eAAe,CAAC,eAAe,MAAM,GAAG,WAAW,IAAI,aAAa,cAAc,CAAC;AAAA,EAC9F;AACF;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,YAAY,OAAO,SAAS,UAAU;AAChD,SAAK,gBAAgB,CAAC,SAAS;AAC/B,SAAK,cAAc,CAAC,YAAY,KAAK;AACrC,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA,8BAIU,oBAAoB;AAAA;AAAA;AAAA;AAAA,EAIhD;AACF;AAGA,IAAI,UAAU,CAAC,SAAS;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,IAAI;AACpB,QAAM,EAAE,OAAO,SAAS,SAAS,IAAI;AACrC,QAAM,cAAc,aAAa,cAAc,QAAQ,KAAK;AAC5D,QAAM,UAAU,IAAI,cAAc,aAAa,OAAO,SAAS,QAAQ;AACvE,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,WAAW,EAAE,EAAE,CAAC;AACxG,QAAM,SAAS,SAAS,gBAAgB,SAAS,CAAC,QAAQ,GAAG,QAAQ,KAAK;AAC1E,WAAS,8BAA8B,QAAQ;AAC/C,QAAM,WAAW,CAAC,GAAG,QAAQ,OAAO,KAAK;AACzC,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC7F,WAAS,8BAA8B,MAAM;AAC7C,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,EAAE,UAAU,aAAa;AAC3B,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,IAAI,MAAM,GAAG,GAAG,SAAS,SAAS,CAAC;AAC7E,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,WAAO;AAAA,EACT,OAAO;AACL,WAAO,MAAM;AAAA,MACX,OAAO;AAAA,QACL,OAAO,EAAE;AAAA,QACT,OAAO,EAAE;AAAA,QACT,OAAO,EAAE,UAAU,WAAW,KAAK;AAAA,MACrC;AAAA,MACA,SAAS;AAAA,IACX,CAAC;AAAA,EACH;AACF;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,EAAE,UAAU,UAAU;AACxB,UAAM,IAAI,MAAM,8CAA8C;AAAA,EAChE,WAAW,EAAE,UAAU,aAAa;AAClC,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,UAAU,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACnE,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,IAAI,MAAM,GAAG,GAAG,SAAS,SAAS,CAAC;AAC7E,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,aAAS,8BAA8B,QAAQ;AAC/C,aAAS,8BAA8B,EAAE;AACzC,WAAO;AAAA,EACT,OAAO;AACL,WAAO,MAAM,EAAE,OAAO,EAAE,OAAO,EAAE,OAAO,OAAO,EAAE,OAAO,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACzF;AACF;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,YAAY,EAAE,QAAQ,EAAE,OAAO,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAAA,EAC9F;AACA,QAAM,QAAQ,OAAO,GAAG;AACxB,QAAM,QAAQ,OAAO,GAAG;AACxB,SAAO,QAAQ,CAAC,OAAO;AACrB,iBAAa,kBAAkB,OAAO,GAAG,OAAO,uDAAuD;AACvG,iBAAa,OAAO,UAAU,GAAG,OAAO,MAAM,uDAAuD;AAAA,EACvG,CAAC;AACD,QAAM,0BAA0B,CAAC;AACjC,QAAM,kBAAkB,OAAO,IAAI,CAAC,OAAO;AACzC,UAAM,YAAY,YAAY,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAChG,4BAAwB,KAAK,SAAS;AACtC,WAAO;AAAA,EACT,CAAC;AACD,QAAM,SAAS,QAAQ,EAAE,QAAQ,iBAAiB,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AACtF,0BAAwB,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AAClF,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa,MAAM;AAAA,EACrB,YAAY,QAAQ,UAAU,eAAe;AAC3C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,iBAAiB,CAAC,EAAE,MAAM,SAAS,MAAM,QAAQ,CAAC;AACvD,SAAK,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,MAAM,GAAG,EAAE;AACtE,UAAM,OAAO,OAAO;AACpB,UAAM,OAAO,kBAAkB,IAAI;AACnC,UAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE,EAAE,KAAK,GAAG;AAClD,UAAM,MAAM,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,GAAG,EAAE,KAAK,GAAG;AACjE,UAAM,iBAAiB,CAAC,aAAa,aAAa,aAAa,WAAW,EAAE,MAAM,GAAG,IAAI;AACzF,QAAI,SAAS,GAAG;AACd,WAAK,WAAW;AAAA,sBACA;AAAA,oBACF;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWd;AAAA,IACF;AACA,SAAK,WAAW;AAAA,QACZ,gBAAgB,QAAQ;AAAA,QACxB,cAAc,QAAQ;AAAA;AAAA;AAAA,UAGpB;AAAA;AAAA;AAAA;AAAA,YAIE;AAAA,2BACe;AAAA;AAAA;AAAA;AAAA,EAIzB;AACF;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,QAAQ,UAAU,eAAe;AAC3C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,iBAAiB,CAAC,EAAE,MAAM,SAAS,MAAM,QAAQ,CAAC;AACvD,SAAK,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,MAAM,GAAG,EAAE;AACtE,UAAM,OAAO,OAAO;AACpB,UAAM,QAAQ,kBAAkB,IAAI;AACpC,UAAM,QAAQ,SAAS,IAAI,CAAC,OAAO,GAAG,EAAE,EAAE,KAAK,GAAG;AAClD,UAAM,MAAM,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,GAAG,EAAE,KAAK,GAAG;AACjE,UAAM,UAAU,YAAY,MAAM,IAAI;AACtC,UAAM,SAAS,YAAY,UAAU,IAAI;AACzC,UAAM,SAAS,GAAG,QAAQ,OAAO,QAAQ,KAAK,YAAY,OAAO;AACjE,UAAM,YAAY,SAAS,IAAI,WAAW,QAAQ,OAAO,MAAM,EAAE,EAAE,KAAK;AACxE,UAAM,iBAAiB;AAAA,MACrB,GAAG;AAAA,MACH,GAAG,QAAQ,OAAO;AAAA,YACZ;AAAA;AAAA,MAEN,SAAS,IAAI,KAAK;AAAA;AAAA,SAEf,QAAQ,OAAO;AAAA,YACZ,QAAQ,OAAO,QAAQ,KAAK,YAAY,OAAO;AAAA,MACrD,SAAS,IAAI,KAAK,KAAK,QAAQ,OAAO;AAAA,cAC9B;AAAA,IACV;AACA,UAAM,cAAc,SAAS,IAAI,4BAA4B;AAC7D,QAAI,WAAW;AACf,aAAS,KAAK,GAAG,IAAI,SAAS,IAAI,IAAI,GAAG,KAAK,GAAG,MAAM;AACrD,kBAAY;AAAA,UACR,eAAe;AAAA,cACX;AAAA,mBACK;AAAA;AAAA,YAEP;AAAA,mBACO,yBAAyB,OAAO,KAAK,OAAO;AAAA;AAAA;AAAA,IAG3D;AACA,gBAAY,SAAS,IAAI,OAAO;AAChC,SAAK,WAAW;AAAA,cACN,iBAAiB,SAAS;AAAA,cAC1B,eAAe,SAAS;AAAA;AAAA;AAAA,UAG5B;AAAA;AAAA,UAEA;AAAA;AAAA;AAAA;AAAA,EAIR;AACF;AAGA,IAAI,SAAS,CAAC,SAAS;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,UAAU,cAAc,IAAI;AACpC,MAAI,aAAa,cAAc,EAAE,KAAK,MAAM,GAAG;AAC7C,UAAM,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,EAAE,MAAM,MAAM,GAAG,EAAE;AACxE,WAAO,MAAM;AAAA,MACX,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,aAAa,OAAO,eAAe,OAAO,EAAE,MAAM;AAAA,IACpE,CAAC;AAAA,EACH;AACA,QAAM,UAAU,IAAI,EAAE,QAAQ,6BAA6B,IAAI,IAAI,iBAAiB,EAAE,OAAO,UAAU,aAAa,IAAI,IAAI,WAAW,EAAE,OAAO,UAAU,aAAa;AACvK,QAAM,eAAe,CAAC,CAAC,aAAa,CAAC;AACrC,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,YAAY;AACrE;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUV,IAAI,aAAa;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,MAcX,qBAAqB;AAAA;AAAA;AAG3B,IAAI,OAAO,kBAAkB,EAAE,WAAW,KAAK,iBAAiB,WAAW,CAAC;AAC5E,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,YAAY,CAAC;AACnB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,YAAY;AAChB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AAC1F,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAC/D,cAAU,KAAK,SAAS;AAAA,EAC1B;AACA,uBAAqB,2BAA2B,QAAQ,MAAM,KAAK;AACnE,MAAI;AACJ,MAAI,SAAS,mBAAmB,CAAC,SAAS,CAAC,GAAG;AAC5C,UAAM,QAAQ,SAAS,QAAQ,IAAI,UAAU,MAAM,EAAE;AACrD,UAAM,EAAE,SAAS,UAAU,SAAS,IAAI,YAAY,UAAU,OAAO,UAAU,OAAO,OAAO,IAAI;AACjG,UAAM,SAAS,eAAe,UAAU,UAAU,OAAO;AAAA,EAC3D,OAAO;AACL,UAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,UAAU,OAAO,IAAI;AACpG,UAAM,SAAS,aAAa,cAAc,WAAW;AACrD,UAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,IAAI,MAAM,EAAE,EAAE,CAAC;AACpG,UAAM,cAAc,WAAW,EAAE,KAAK;AACtC,UAAM,UAAU,OAAO,KAAK,aAAa,QAAQ,QAAQ;AACzD,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,cAAU,KAAK,GAAG;AAClB,cAAU,KAAK,OAAO;AAAA,EACxB;AACA,MAAI,UAAU;AACZ,cAAU,KAAK,GAAG;AAClB,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,QAAQ;AAC9E,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAAA,EACtF;AACA,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,CAAC,SAAS;AACrB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,MAAM,OAAO,MAAM,IAAI;AAC5C,QAAM,SAAS,aAAa,OAAO,MAAM,OAAO,KAAK;AACrD,SAAO,SAAS,eAAe,CAAC,OAAO,MAAM,GAAG,OAAO,MAAM;AAC/D;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa;AACjB,IAAI,cAAc,iBAAiB,EAAE,WAAW,WAAW,CAAC;AAC5D,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,oBAAoB;AAAA;AAAA;AAGhC,IAAI,cAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWlB,IAAI,QAAQ,iBAAiB,EAAE,WAAW,OAAO,iBAAiB,YAAY,CAAC;AAC/E,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,oBAAoB;AAAA;AAAA;AAGjC,IAAI,eAAe;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWnB,IAAI,SAAS,iBAAiB,EAAE,WAAW,QAAQ,iBAAiB,aAAa,CAAC;AAClF,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,wBAAwB,MAAM;AAAA,EAChC,YAAY,YAAY,WAAW,UAAU,cAAc,kBAAkB;AAC3E,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,CAAC;AACpB,UAAM,CAAC,OAAO,WAAW,UAAU,KAAK,IAAI;AAC5C,SAAK,cAAc,CAAC,OAAO,WAAW,UAAU,KAAK;AACrD,UAAM,kBAAkB;AAAA,MACtB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,UAAM,mBAAmB;AAAA,MACvB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,QAAI;AACJ,QAAI,kBAAkB;AACpB,0BAAoB;AAAA,IACtB,OAAO;AACL,0BAAoB;AAAA,IACtB;AACA,SAAK,WAAW;AAAA;AAAA,YAER,gBAAgB,KAAK,iBAAiB;AAAA,YACtC,gBAAgB,KAAK,iBAAiB;AAAA,uCACX,gBAAgB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,mCASpB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAqBjC;AACF;AAGA,IAAI,8BAA8B,MAAM;AAAA,EACtC,YAAY,YAAY,WAAW,UAAU,cAAc,kBAAkB;AAC3E,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc,CAAC;AACpB,UAAM,CAAC,OAAO,WAAW,UAAU,KAAK,IAAI;AAC5C,SAAK,cAAc,CAAC,OAAO,WAAW,UAAU,KAAK;AACrD,UAAM,kBAAkB;AAAA,MACtB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,UAAM,mBAAmB;AAAA,MACvB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,QAAI;AACJ,QAAI,kBAAkB;AACpB,0BAAoB;AAAA,IACtB,OAAO;AACL,0BAAoB;AAAA,IACtB;AACA,SAAK,WAAW;AAAA;AAAA,YAER,gBAAgB,KAAK,iBAAiB;AAAA,YACtC,gBAAgB,KAAK,iBAAiB;AAAA,YACtC,gBAAgB,KAAK,iBAAiB;AAAA,uCACX,gBAAgB;AAAA,uCAChB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,mCAcJ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAQH,QAAQ;AAAA,uCACD,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAiDhD;AACF;AAGA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,kBAAkB,MAAAZ,MAAK,IAAI;AACjD,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,UAAU,IAAI,EAAE,QAAQ,6BAA6B,IAAI,IAAI,4BAA4B,OAAO,OAAO,WAAW,UAAU,cAAc,gBAAgB,IAAI,IAAI,sBAAsB,OAAO,OAAO,WAAW,UAAU,cAAc,gBAAgB;AAC/P,SAAO,SAAS,gBAAgB,SAAS,CAAC,MAAM,GAAG,SAAS;AAC9D;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gCAAgC,MAAM;AAAA,EACxC,YAAY,SAAS,YAAY,cAAc;AAC7C,SAAK,gBAAgB,CAAC,IAAI;AAC1B,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc;AACnB,UAAM,CAAC,EAAE,SAAS,MAAM,IAAI;AAC5B,UAAM,CAAC,EAAE,SAAS,MAAM,IAAI;AAC5B,UAAM,iBAAiB;AAAA,MACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,MAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,IAC5C;AACA,UAAM,iBAAiB;AAAA,MACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,MAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,IAC5C;AACA,UAAM,cAAc,eAAe,KAAK,eAAe;AACvD,UAAM,aAAa,eAAe,KAAK,eAAe;AACtD,UAAM,iBAAiB,IAAI;AAC3B,UAAM,gBAAgB,IAAI;AAC1B,UAAM,YAAY,KAAK,KAAK,cAAc,IAAI,IAAI;AAClD,UAAM,WAAW,KAAK,KAAK,aAAa,IAAI,IAAI;AAChD,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0CAUsB;AAAA,yCACD;AAAA;AAAA,6CAEI;AAAA,4CACD;AAAA;AAAA,oCAER;AAAA,mCACD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAcD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oCAQE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,sDAMkB,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,qDAMX,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EA+B5D;AACF;AAGA,SAAS,oBAAoB,MAAM;AACjC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,GAAG,IAAI;AACvB,QAAM,EAAE,aAAa,IAAI;AACzB,QAAM,UAAU,IAAI,8BAA8B,GAAG,OAAO,OAAO,OAAO,YAAY;AACtF,SAAO,SAAS,gBAAgB,SAAS,CAAC,EAAE,GAAG,GAAG,KAAK;AACzD;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,+BAA+B,MAAM;AAAA,EACvC,YAAY,YAAY,WAAW,UAAU,cAAc,kBAAkB;AAC3E,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAc,CAAC;AACpB,UAAM,CAAC,OAAO,WAAW,UAAU,KAAK,IAAI;AAC5C,SAAK,cAAc,CAAC,OAAO,WAAW,UAAU,KAAK;AACrD,UAAM,kBAAkB;AAAA,MACtB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,UAAM,mBAAmB;AAAA,MACvB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,UAAM,YAAY,eAAe,QAAQ;AACzC,QAAI;AACJ,QAAI,kBAAkB;AACpB,0BAAoB;AAAA,IACtB,OAAO;AACL,0BAAoB;AAAA,IACtB;AACA,SAAK,WAAW;AAAA;AAAA,YAER,gBAAgB,KAAK,iBAAiB;AAAA,YACtC,gBAAgB,KAAK,iBAAiB;AAAA,uCACX,gBAAgB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,mCASpB;AAAA;AAAA;AAAA;AAAA,8DAI2B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAM5D;AACF;AAGA,IAAI,qCAAqC,MAAM;AAAA,EAC7C,YAAY,YAAY,WAAW,UAAU,cAAc,kBAAkB;AAC3E,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,SAAK,cAAc,CAAC;AACpB,UAAM,CAAC,OAAO,WAAW,UAAU,KAAK,IAAI;AAC5C,SAAK,cAAc,CAAC,OAAO,WAAW,UAAU,KAAK;AACrD,UAAM,kBAAkB;AAAA,MACtB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,UAAM,mBAAmB;AAAA,MACvB,gBAAgB,YAAY,IAAI,YAAY,IAAI;AAAA,MAChD,gBAAgB,WAAW,IAAI,WAAW,IAAI;AAAA,IAChD;AACA,UAAM,YAAY,eAAe,QAAQ;AACzC,QAAI;AACJ,QAAI,kBAAkB;AACpB,0BAAoB;AAAA,IACtB,OAAO;AACL,0BAAoB;AAAA,IACtB;AACA,SAAK,WAAW;AAAA;AAAA,YAER,gBAAgB,KAAK,iBAAiB;AAAA,YACtC,gBAAgB,KAAK,iBAAiB;AAAA,YACtC,gBAAgB,KAAK,iBAAiB;AAAA,uCACX,gBAAgB;AAAA,uCAChB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,mCAcJ;AAAA;AAAA;AAAA;AAAA,8DAI2B;AAAA;AAAA;AAAA,gCAG9B,QAAQ;AAAA,uCACD,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAchD;AACF;AAGA,SAAS,uBAAuB,MAAM;AACpC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,kBAAkB,MAAAA,MAAK,IAAI;AACjD,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,UAAU,IAAI,EAAE,QAAQ,6BAA6B,IAAI,IAAI,mCAAmC,OAAO,OAAO,WAAW,UAAU,cAAc,gBAAgB,IAAI,IAAI,6BAA6B,OAAO,OAAO,WAAW,UAAU,cAAc,gBAAgB;AAC7Q,SAAO,SAAS,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO,KAAK;AACjE;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,sCAAsC,MAAM;AAAA,EAC9C,YAAY,SAAS,YAAY,cAAc;AAC7C,SAAK,gBAAgB,CAAC,IAAI;AAC1B,SAAK,cAAc,CAAC;AACpB,SAAK,cAAc;AACnB,UAAM,CAAC,EAAE,SAAS,MAAM,IAAI;AAC5B,UAAM,CAAC,EAAE,SAAS,MAAM,IAAI;AAC5B,UAAM,iBAAiB;AAAA,MACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,MAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,IAC5C;AACA,UAAM,iBAAiB;AAAA,MACrB,gBAAgB,UAAU,IAAI,UAAU,IAAI;AAAA,MAC5C,gBAAgB,SAAS,IAAI,SAAS,IAAI;AAAA,IAC5C;AACA,UAAM,cAAc,eAAe,KAAK,eAAe;AACvD,UAAM,aAAa,eAAe,KAAK,eAAe;AACtD,UAAM,iBAAiB,IAAI;AAC3B,UAAM,gBAAgB,IAAI;AAC1B,UAAM,YAAY,KAAK,KAAK,cAAc,IAAI,IAAI;AAClD,UAAM,WAAW,KAAK,KAAK,aAAa,IAAI,IAAI;AAChD,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0CAUsB;AAAA,yCACD;AAAA;AAAA,6CAEI;AAAA,4CACD;AAAA;AAAA,oCAER;AAAA,mCACD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAcD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oCAQE;AAAA;AAAA;AAAA;AAAA;AAAA,sBAKd,eAAe;AAAA,sCACC,eAAe;AAAA;AAAA;AAAA,wBAG7B,eAAe;AAAA,wCACC,eAAe;AAAA;AAAA;AAAA,4BAG3B;AAAA,kBACV;AAAA;AAAA;AAAA;AAAA,4BAIU;AAAA,kBACV;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAahB;AACF;AAGA,SAAS,2BAA2B,MAAM;AACxC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,GAAG,IAAI;AACvB,QAAM,EAAE,aAAa,IAAI;AACzB,QAAM,UAAU,IAAI,oCAAoC,GAAG,OAAO,OAAO,OAAO,YAAY;AAC5F,SAAO,SAAS,gBAAgB,SAAS,CAAC,EAAE,GAAG,GAAG,KAAK;AACzD;AACA,IAAI,mCAAmC;AAAA,EACrC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,QAAQ,MAAM;AACxB,SAAK,gBAAgB,CAAC,GAAG;AACzB,UAAM,OAAO,OAAO;AACpB,QAAI,OAAO,GAAG;AACZ,YAAM,IAAI,MAAM,kCAAkC,kCAAkC;AAAA,IACtF;AACA,SAAK,cAAc;AACnB,QAAI,SAAS,GAAG;AACd,WAAK,WAAW;AAAA;AAAA;AAAA,2BAGK,OAAO;AAAA;AAAA;AAG5B;AAAA,IACF;AACA,UAAM,aAAa,CAAC,OAAO;AACzB,UAAI,KAAK,QAAQ,EAAE,MAAM,MAAM,OAAO,QAAQ,GAAG;AAC/C,eAAO,GAAG,OAAO,gBAAgB;AAAA,MACnC;AACA,aAAO,UAAU;AAAA,IACnB;AACA,UAAM,WAAW,OAAO,IAAI,CAAC,GAAG,OAAO,WAAW,EAAE,CAAC,EAAE,KAAK,GAAG;AAC/D,UAAM,OAAO,kBAAkB,IAAI;AACnC,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA,yBACe;AAAA;AAAA;AAAA,EAGvB;AACF;AAGA,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,QAAQ,MAAM;AACxB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,eAAe;AACpB,SAAK,eAAe;AACpB,UAAM,OAAO,OAAO;AACpB,QAAI,OAAO,GAAG;AACZ,YAAM,IAAI,MAAM,kCAAkC,kCAAkC;AAAA,IACtF;AACA,SAAK,cAAc;AACnB,UAAM,WAAW,YAAY,MAAM,IAAI;AACvC,UAAM,aAAa,GAAG,SAAS,OAAO,YAAY,KAAK,YAAY,OAAO;AAC1E,UAAM,UAAU,GAAG,SAAS,OAAO,YAAY,KAAK,YAAY,OAAO;AACvE,UAAM,OAAO,kBAAkB,IAAI;AACnC,QAAI,SAAS,GAAG;AACd,WAAK,WAAW;AAAA;AAAA;AAAA;AAAA,uCAIiB,OAAO;AAAA,cAChC,OAAO;AAAA,eACN;AAAA,2CAC4B,OAAO;AAAA,kBAChC,OAAO;AAAA;AAAA;AAAA;AAAA;AAAA,IAKrB,OAAO;AACL,WAAK,WAAW;AAAA;AAAA,YAEV;AAAA;AAAA,uBAEW,KAAK,SAAS,MAAM,CAAC;AAAA,eAC7B;AAAA,yBACU,KAAK,SAAS,MAAM,CAAC;AAAA;AAAA,eAE/B;AAAA,yBACU,KAAK,SAAS,MAAM,CAAC;AAAA,iBAC7B;AAAA,2BACU,KAAK,SAAS,MAAM,CAAC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAM5C;AACA,aAAS,KAAK,WAAW;AACvB,aAAO,WAAW,SAAS;AAAA,IAC7B;AACA,aAAS,KAAK,WAAW;AACvB,gBAAU,OAAO,KAAK,MAAM,UAAU,OAAO,KAAK;AAClD,aAAO,WAAW,SAAS;AAAA,IAC7B;AACA,aAAS,KAAK,WAAW;AACvB,gBAAU,OAAO,KAAK,MAAM,UAAU,OAAO,KAAK;AAClD,aAAO,WAAW,SAAS;AAAA,IAC7B;AACA,aAAS,KAAK,WAAW;AACvB,gBAAU,OAAO,KAAK,MAAM,UAAU,OAAO,KAAK;AAClD,gBAAU,OAAO,KAAK,MAAM,UAAU,OAAO,KAAK;AAClD,aAAO,WAAW,SAAS;AAAA,IAC7B;AACA,aAAS,WAAW,WAAW;AAC7B,YAAM,gBAAgB,OAAO,IAAI,CAAC,GAAG,OAAO,WAAW,IAAI,SAAS,CAAC;AACrE,YAAM,WAAW,cAAc,KAAK,GAAG;AACvC,YAAM,YAAY,cAAc,MAAM,EAAE,EAAE,KAAK,GAAG;AAClD,aAAO,mBAAmB,mBAAmB;AAAA,IAC/C;AACA,aAAS,WAAW,IAAI,WAAW;AACjC,UAAI,KAAK,QAAQ,EAAE,MAAM,MAAM,OAAO,QAAQ,GAAG;AAC/C,eAAO,GAAG,OAAO,SAAS,UAAU;AAAA,MACtC,OAAO;AACL,eAAO,GAAG,UAAU;AAAA,MACtB;AAAA,IACF;AAAA,EACF;AACF;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,aAAa,eAAe,MAAM,EAAE,KAAK;AACvD,MAAI,UAAU,GAAG;AACf,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD;AACA,QAAM,UAAU,IAAI,EAAE,QAAQ,6BAA6B,IAAI,IAAI,qBAAqB,EAAE,OAAO,KAAK,IAAI,IAAI,eAAe,EAAE,OAAO,KAAK;AAC3I,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACvD;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,YAAY,WAAW;AACjC,SAAK,gBAAgB,CAAC,OAAO;AAC7B,SAAK,cAAc,CAAC;AACpB,SAAK,iBAAiB,CAAC,EAAE,MAAM,UAAU,MAAM,OAAO,CAAC;AACvD,UAAM,cAAc,WAAW;AAC/B,UAAM,aAAa,WAAW;AAC9B,SAAK,cAAc;AACnB,QAAI,cAAc;AAClB,QAAI,OAAO,cAAc,UAAU;AACjC,oBAAc,uBAAuB,UAAU,QAAQ,CAAC;AAAA,IAC1D,OAAO;AACL,oBAAc;AAAA,2BACO,UAAU,KAAK,GAAG;AAAA;AAAA,IAEzC;AACA,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAWR;AAAA,uCAC2B,yCAAyC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAM9E;AACF;AAGA,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,UAAM,EAAE,SAAS,WAAW,OAAO,IAAI;AACvC,UAAM,eAAe;AACrB,UAAM,UAAU,IAAI,cAAc,OAAO,OAAO,SAAS;AACzD,UAAM,CAAC,SAAS,OAAO,IAAI,qBAAqB,eAAe,QAAQ,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE;AACvG,UAAM,eAAe,CAAC,CAAC,SAAS,SAAS,KAAK,IAAI,OAAO,GAAG,KAAK,IAAI,OAAO,CAAC,CAAC;AAC9E,UAAM,SAAS,aAAa,gBAAgB,SAAS,CAAC,MAAM,GAAG,OAAO,OAAO,YAAY;AACzF,WAAO;AAAA,EACT;AACF;AAGA,IAAI,QAAQ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAgBZ,IAAI,SAAS,iBAAiB,EAAE,WAAW,MAAM,CAAC;AAClD,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ;AACZ,IAAI,SAAS,iBAAiB,EAAE,WAAW,OAAO,eAAe,aAAa,CAAC;AAC/E,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,YAAY,UAAU,aAAa,aAAaY,UAAS,OAAO,mBAAmB,MAAM;AACnG,SAAK,gBAAgB,CAAC,WAAW,WAAW,cAAc;AAC1D,SAAK,cAAc;AACnB,UAAM,cAAc,kBAAkBA,SAAQ,MAAM;AACpD,UAAM,QAAQ,kBAAkB,MAAM,MAAM;AAC5C,QAAI,gBAAgB;AACpB,QAAI,gBAAgB,GAAG;AACrB,sBAAgB;AAAA,IAClB,WAAW,gBAAgB,GAAG;AAC5B,sBAAgB;AAAA,IAClB;AACA,UAAM,iBAAiB,cAAc;AACrC,QAAI,gBAAgB;AACpB,QAAI,gBAAgB,GAAG;AACrB,sBAAgB;AAAA,IAClB,WAAW,gBAAgB,GAAG;AAC5B,sBAAgB;AAAA,IAClB;AACA,UAAM,iBAAiB,cAAc;AACrC,UAAM,eAAe,WAAW,IAAI,eAAe;AACnD,SAAK,WAAW;AAAA,UACV,yBAAyB,eAAeA;AAAA;AAAA;AAAA,YAGtC;AAAA;AAAA;AAAA,gCAGoB;AAAA;AAAA,kCAEE;AAAA,kCACA;AAAA,0CACQ;AAAA;AAAA;AAAA,uBAGnB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAOrB;AACF;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,SAAS,QAAQ,IAAI;AAC7B,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,EAAE,WAAW,YAAY,WAAW,SAAAA,UAAS,YAAAQ,YAAW,IAAI,qBAAqB,gBAAgB,SAAS,SAAS,KAAK;AAC9H,QAAM,eAAe,CAACA,cAAa,WAAW,SAAS;AACvD,MAAIA,gBAAe,GAAG;AACpB,WAAO,SAAS,eAAe,OAAO,QAAQ,KAAK;AAAA,EACrD;AACA,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,YAAY,SAAS,EAAE,EAAE,CAAC;AACxH,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,YAAY,SAAS,EAAE,EAAE,CAAC;AAClH,QAAM,eAAe,SAAS,eAAe,CAAC,GAAG,WAAW,IAAI,aAAa,CAAC,CAAC,CAAC,CAAC;AACjF,QAAM,UAAU,IAAI,eAAe,YAAY,WAAW,eAAe,MAAM,QAAQ,SAAS,MAAM,QAAQR,UAAS,YAAY;AACnI,QAAM,MAAM,SAAS,gBAAgB,SAAS,CAAC,UAAU,gBAAgB,YAAY,GAAG,SAAS,KAAK;AACtG,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AACrF,WAAS,8BAA8B,cAAc;AACrD,WAAS,8BAA8B,QAAQ;AAC/C,WAAS,8BAA8B,GAAG;AAC1C,WAAS,8BAA8B,YAAY;AACnD,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,WAAW,WAAW,WAAW,MAAM;AACjD,SAAK,gBAAgB,CAAC,kBAAkB,QAAQ;AAChD,SAAK,iBAAiB,CAAC,EAAE,MAAM,aAAa,MAAM,MAAM,CAAC;AACzD,SAAK,cAAc,CAAC,WAAW,SAAS;AACxC,UAAM,iBAAiB;AACvB,UAAM,iBAAiB,uBAAuB,KAAK,KAAK,KAAK,KAAK,YAAY,CAAC,CAAC;AAChF,UAAM,WAAW,IAAI,EAAE,UAAU,eAAe,MAAM,IAAI,iBAAiB;AAC3E,UAAM,kBAAkB,SAAS,SAAS,MAAM;AAChD,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,WAKT;AAAA;AAAA,+CAEoC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAmB7C;AACF;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,gBAAgB,OAAO,IAAI;AACnC,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,UAAU,IAAI,oBAAoB,eAAe,MAAM,IAAI,eAAe,MAAM,IAAI,OAAO,MAAM,IAAI,IAAI;AAC/G,QAAM,eAAe,CAAC,CAAC,eAAe,MAAM,EAAE,CAAC;AAC/C,SAAO,SAAS,gBAAgB,SAAS,CAAC,gBAAgB,MAAM,GAAG,SAAS,YAAY;AAC1F;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,OAAO,OAAO,MAAM;AAC9B,SAAK,gBAAgB,CAAC,KAAK,KAAK,GAAG;AACnC,SAAK,cAAc;AACnB,QAAI;AACJ,QAAI;AACJ,QAAI,OAAO,GAAG;AACZ,YAAM,MAAM,kBAAkB,2BAA2B;AAAA,IAC3D;AACA,QAAI,SAAS,GAAG;AACd,iBAAW;AACX,gBAAU;AAAA,IACZ,OAAO;AACL,YAAM,gBAAgB,CAAC,WAAW,WAAW,WAAW,SAAS;AACjE,YAAM,aAAa,CAAC;AACpB,YAAM,cAAc,CAAC;AACrB,eAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,MAAM;AACxC,oBAAY,KAAK,GAAG,cAAc,KAAK;AACvC,YAAI,KAAK,OAAO;AACd,qBAAW,KAAK,GAAG,cAAc,KAAK;AAAA,QACxC;AAAA,MACF;AACA,gBAAU,WAAW,KAAK;AAC1B,iBAAW,YAAY,KAAK;AAAA,IAC9B;AACA,UAAM,QAAQ,kBAAkB,IAAI;AACpC,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA,4BACkB;AAAA;AAAA,2BAED;AAAA;AAAA,2BAEA;AAAA;AAAA;AAAA;AAAA,EAIzB;AACF;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,WAAW,GAAG,IAAI,GAAG,GAAG,IAAI;AACpC,QAAM,UAAU,IAAI,cAAc,UAAU,MAAM,QAAQ,GAAG,OAAO,GAAG,MAAM,MAAM;AACnF,SAAO,SAAS,gBAAgB,SAAS,CAAC,WAAW,IAAI,EAAE,GAAG,WAAW,GAAG,OAAO,GAAG,KAAK,CAAC;AAC9F;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AAAA;AAAA;AAAA,uBAGY,qBAAqB;AAAA,kBAC1B,qBAAqB;AAAA;AAAA;AAGvC,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW,0BAA0B;AAAA;AAAA;AAGzC,IAAI,iBAAiB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWrB,IAAI,WAAW,iBAAiB;AAAA,EAC9B,WAAW;AAAA,EACX,iBAAiB;AAAA,EACjB,eAAe;AACjB,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AAAA;AAAA;AAAA;AAIX,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM,0BAA0B;AAAA;AAAA;AAGpC,IAAI,OAAO,iBAAiB,EAAE,WAAW,IAAI,CAAC;AAC9C,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AAAA;AAAA;AAAA;AAIX,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAqBf,IAAI,YAAY,iBAAiB,EAAE,WAAW,SAAS,CAAC;AACxD,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kBAAkB,CAAC,SAAS;AAC9B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAS,IAAI;AACjC,eAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,sEAAsE;AACrH,QAAM,QAAQ,WAAW,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAC/C,QAAM,mBAAmB,CAAC,CAAC,GAAG,CAAC,CAAC;AAChC,mBAAiB,KAAK,GAAG,QAAQ;AACjC,WAAS,KAAK,IAAI,WAAW,QAAQ,KAAK,EAAE,MAAM,QAAQ,EAAE,IAAI;AAC9D,qBAAiB,KAAK,CAAC,GAAG,CAAC,CAAC;AAAA,EAC9B;AACA,QAAM,YAAY,CAAC;AACnB,QAAM,UAAU,OAAO;AAAA,IACrB,QAAQ,EAAE,EAAE;AAAA,IACZ,SAAS;AAAA,IACT,OAAO,EAAE,UAAU,kBAAkB,eAAe,EAAE;AAAA,EACxD,CAAC;AACD,QAAM,sBAAsB,qBAAqB,YAAY,QAAQ,OAAO,YAAY,OAAO,KAAK;AACpG,QAAM,oCAAoC,qBAAqB,YAAY,oBAAoB,QAAQ,WAAW,QAAQ,KAAK;AAC/H,QAAM,eAAe,qBAAqB,oBAAoB,QAAQ,OAAO,YAAY,OAAO,KAAK;AACrG,QAAM,kBAAkB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,oBAAoB,EAAE,CAAC;AACrH,QAAM,WAAW,WAAW;AAAA,IAC1B,QAAQ,EAAE,GAAG,gBAAgB;AAAA,IAC7B,SAAS;AAAA,IACT,OAAO,EAAE,MAAM,kCAAkC;AAAA,EACnD,CAAC;AACD,QAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,aAAa,EAAE,CAAC;AACtG,YAAU,KAAK,OAAO;AACtB,YAAU,KAAK,eAAe;AAC9B,YAAU,KAAK,QAAQ;AACvB,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,SAAO;AACT;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,SAAS,QAAQ,YAAY,aAAa,IAAI;AACtD,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,WACT,WAAW,OAAO;AAAA,EAC3B;AACA,MAAI,QAAQ,MAAM,WAAW,GAAG;AAC9B,UAAM,IAAI,MAAM;AAAA,WACT,QAAQ,OAAO;AAAA,EACxB;AACA,MAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,UAAM,IAAI,MAAM;AAAA,WACT,OAAO,OAAO;AAAA,EACvB;AACA,MAAI,aAAa,MAAM,WAAW,GAAG;AACnC,UAAM,IAAI,MAAM;AAAA,UACV,aAAa,OAAO;AAAA,EAC5B;AACA,QAAM,WAAW,SAAS,SAAS,QAAQ,MAAM;AACjD,QAAM,UAAU,SAAS,SAAS,OAAO,MAAM;AAC/C,QAAM,cAAc,SAAS,SAAS,WAAW,MAAM;AACvD,QAAM,gBAAgB,SAAS,SAAS,aAAa,MAAM,EAAE;AAC7D,QAAM,CAAC,eAAe,oBAAoB,cAAc,mBAAmB,eAAe,IAAI,2BAA2B,UAAU,QAAQ,OAAO,QAAQ,OAAO,SAAS,OAAO,OAAO,aAAa,aAAa;AAClN,SAAO;AAAA,IACL,SAAS,eAAe,oBAAoB,QAAQ,OAAO,aAAa;AAAA,IACxE,SAAS,eAAe,CAAC,mBAAmB,EAAE,GAAG,OAAO,OAAO,YAAY;AAAA,IAC3E,SAAS,eAAe,CAAC,kBAAkB,MAAM,GAAG,QAAQ,IAAI,WAAW,kBAAkB,IAAI,CAAC,UAAU,OAAO,KAAK,CAAC,CAAC,CAAC;AAAA,IAC3H,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,QAAQ,OAAO,IAAI,WAAW,eAAe,CAAC;AAAA,EAClG;AACF;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,cAAc,YAAY,SAAS,IAAI;AAC/C,MAAI,aAAa,MAAM,WAAW,GAAG;AACnC,UAAM,IAAI,MAAM,uDAAuD,aAAa,OAAO;AAAA,EAC7F;AACA,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM,qDAAqD,WAAW,OAAO;AAAA,EACzF;AACA,MAAI,SAAS,MAAM,WAAW,GAAG;AAC/B,UAAM,IAAI,MAAM,sDAAsD,SAAS,OAAO;AAAA,EACxF;AACA,QAAM,cAAc,MAAM,KAAK,SAAS,SAAS,WAAW,MAAM,CAAC;AACnE,QAAM,gBAAgB,SAAS,SAAS,aAAa,MAAM;AAC3D,QAAM,cAAc,MAAM,KAAK,SAAS,SAAS,SAAS,MAAM,CAAC;AACjE,QAAM,CAAC,YAAY,cAAc,WAAW,IAAI,qBAAqB,eAAe,aAAa,OAAO,aAAa,OAAO,aAAa,WAAW;AACpJ,SAAO;AAAA,IACL,SAAS,eAAe,cAAc,aAAa,OAAO,UAAU;AAAA,IACpE,SAAS,eAAe,CAAC,YAAY,MAAM,GAAG,SAAS,OAAO,IAAI,WAAW,WAAW,CAAC;AAAA,EAC3F;AACF;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,mBAAmB,MAAM;AAChC,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,MAAM,SAAS,WAAW,IAAI;AACtC,MAAI,KAAK,MAAM,SAAS,GAAG;AACzB,UAAM,IAAI,MAAM,2DAA2D;AAAA,EAC7E;AACA,MAAI,QAAQ,MAAM,WAAW,GAAG;AAC9B,UAAM,IAAI,MAAM;AAAA,gBACJ,QAAQ,OAAO;AAAA,EAC7B;AACA,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,gBACJ,WAAW,OAAO;AAAA,EAChC;AACA,QAAM,QAAQ,SAAS,SAAS,KAAK,MAAM;AAC3C,QAAM,WAAW,SAAS,SAAS,QAAQ,MAAM;AACjD,QAAM,cAAc,SAAS,SAAS,WAAW,MAAM;AACvD,QAAM,CAAC,YAAY,eAAe,IAAI,8BAA8B,OAAO,KAAK,OAAO,KAAK,OAAO,UAAU,aAAa,IAAI;AAC9H,SAAO,SAAS,eAAe,iBAAiB,KAAK,OAAO,UAAU;AACxE;AACA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,kBAAkB,MAAM;AAC/B,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,MAAM,SAAS,WAAW,IAAI;AACtC,MAAI,KAAK,MAAM,SAAS,GAAG;AACzB,UAAM,IAAI,MAAM,2DAA2D;AAAA,EAC7E;AACA,MAAI,QAAQ,MAAM,WAAW,GAAG;AAC9B,UAAM,IAAI,MAAM;AAAA,eACL,QAAQ,OAAO;AAAA,EAC5B;AACA,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,eACL,WAAW,OAAO;AAAA,EAC/B;AACA,QAAM,QAAQ,SAAS,SAAS,KAAK,MAAM;AAC3C,QAAM,WAAW,SAAS,SAAS,QAAQ,MAAM;AACjD,QAAM,cAAc,SAAS,SAAS,WAAW,MAAM;AACvD,QAAM,CAAC,YAAY,eAAe,IAAI,8BAA8B,OAAO,KAAK,OAAO,KAAK,OAAO,UAAU,WAAW;AACxH,SAAO,SAAS,eAAe,iBAAiB,KAAK,OAAO,UAAU;AACxE;AACA,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,eAAe,cAAc,aAAa,IAAI;AACtD,QAAM,EAAE,YAAY,IAAI;AACxB,QAAM,EAAE,WAAW,YAAY,WAAW,SAAAA,UAAS,YAAAQ,YAAW,IAAI,qBAAqB,gBAAgB,cAAc,eAAe,WAAW;AAC/I,QAAM,iBAAiB;AACvB,MAAI,aAAa,UAAU,UAAU;AACnC,UAAM,aAAa,SAAS,WAAW,aAAa;AACpD,UAAM,aAAa,SAAS,WAAW,YAAY;AACnD,UAAM,gBAAgB,aAAa,aAAa,SAAS,SAAS,aAAa,MAAM,EAAE,EAAE;AACzF,UAAM,SAAS,eAAe,YAAY,YAAY,aAAaA,aAAY,WAAW,YAAY,WAAWR,UAAS,eAAe,cAAc;AACvJ,WAAO,SAAS,eAAe,aAAa,OAAO,OAAO,OAAO,MAAM;AAAA,EACzE;AACA,QAAM,UAAU,IAAI,eAAe,YAAY,WAAW,cAAc,MAAM,QAAQ,aAAa,MAAM,QAAQA,UAAS,CAACQ,aAAY,CAAC,GAAG,cAAc;AACzJ,QAAM,MAAM,SAAS,gBAAgB,SAAS,CAAC,cAAc,eAAe,YAAY,GAAG,aAAa,KAAK;AAC7G,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAClG,WAAS,8BAA8B,GAAG;AAC1C,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,iBAAiB,KAAK,IAAI;AAClC,QAAM,QAAQ,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AACzD,QAAM,aAAa,qBAAqB,iBAAiB,GAAG,iBAAiB,KAAK;AAClF,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,IAAI,MAAM,KAAK,EAAE,KAAK,CAAC;AACrC,QAAMpB,QAAO,EAAE,MAAM,MAAM;AAC3B,SAAO,WAAW,IAAI,CAAC,OAAO;AAC5B,UAAM,YAAY,CAAC,GAAGA,KAAI;AAC1B,cAAU,SAAS;AACnB,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,MAAM,UAAU,EAAE,CAAC;AAC7F,UAAM,UAAU;AAChB,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AACX,IAAI,QAAQ,iBAAiB,EAAE,WAAW,MAAM,iBAAiB,MAAM,eAAe,YAAY,CAAC;AACnG,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS;AACb,IAAI,UAAU,iBAAiB,EAAE,WAAW,OAAO,CAAC;AACpD,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,qBAAqB;AACzB,IAAI,qBAAqB,kBAAkB,EAAE,WAAW,oBAAoB,iBAAiB,mBAAmB,CAAC;AACjH,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,GAAG;AACnD,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,YAAY,oBAAoB;AAAA,mCACL,MAAM;AAAA;AAEvC,QAAM,UAAU,IAAI,eAAe,EAAE,OAAO,SAAS;AACrD,SAAO,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACvD;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,OAAOY,UAASZ,OAAM;AAChC,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,cAAcA;AACnB,UAAM,OAAOA,MAAK;AAClB,UAAM,aAAa,kBAAkBA,MAAK,MAAM;AAChD,UAAM,QAAQ,kBAAkBA,MAAK,MAAM;AAC3C,QAAI,YAAY;AAChB,QAAI,SAAS,GAAG;AACd,kBAAY;AAAA,IACd,OAAO;AACL,UAAI,aAAa;AACjB,kBAAYA,MAAK,IAAI,CAAC,GAAG,OAAO;AAC9B;AACA,eAAOA,MAAK,WAAW,IAAI,oBAAoB,eAAe,QAAQ,UAAU,aAAa,gBAAgB,eAAe;AAAA,MAC9H,CAAC,EAAE,KAAK,GAAG;AAAA,IACb;AACA,SAAK,WAAW;AAAA,QACZ,sBAAsB,cAAc;AAAA,QACpC,wBAAwB,cAAcY;AAAA;AAAA;AAAA,UAGpC;AAAA,yBACe;AAAA;AAAA;AAAA,EAGvB;AACF;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAO,KAAK,SAAAA,UAAS,WAAW,SAAS,cAAc,aAAa,eAAe,IAAI;AAC/F,QAAM,EAAE,kBAAkB,YAAY,YAAY,WAAW,eAAe,OAAO,QAAQ,KAAK,MAAM,SAAS,SAAS,IAAI,mBAAmB,UAAU,EAAE,OAAO,OAAO,KAAKA,UAAS,WAAW,SAAS,cAAc,aAAa,cAAc;AACpP,MAAI;AACJ,MAAI,YAAY;AACd,aAAS,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAAA,EACtF,WAAW,aAAa,eAAe;AACrC,iBAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,yCAAyC,EAAE,MAAM,QAAQ;AACxG,UAAMZ,QAAO,mBAAmB,gBAAgB,QAAQ,MAAM,QAAQ;AACtE,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,QAAQ,MAAAA,MAAK,EAAE,CAAC;AAC1F,aAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAC5F,aAAS,8BAA8B,MAAM;AAAA,EAC/C,OAAO;AACL,UAAM,qBAAqB,SAAS,mBAAmB,CAAC,CAAC,CAAC;AAC1D,QAAI,oBAAoB;AACtB,YAAM,SAAS,SAAS,SAAS,EAAE,MAAM;AACzC,YAAM,OAAO,OAAO,EAAE,OAAO,EAAE,OAAO,MAAM;AAC5C,YAAM,eAAe,oBAAoB,kBAAkB,MAAM,UAAU,MAAM;AACjF,eAAS,SAAS,eAAe,YAAY,EAAE,OAAO,aAAa,MAAM;AAAA,IAC3E,OAAO;AACL,YAAM,UAAU,IAAI,oBAAoB,QAAQ,UAAU,gBAAgB;AAC1E,eAAS,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AAAA,IACzD;AAAA,EACF;AACA,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAC1G,WAAS,8BAA8B,MAAM;AAC7C,SAAO;AACT;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,WAAW,aAAa,SAAS,UAAU,WAAW,UAAU,uBAAuB,IAAI;AACnG,QAAM,EAAE,MAAM,WAAW,IAAI;AAC7B,QAAM,QAAQ,SAAS,SAAS,KAAK,MAAM;AAC3C,QAAM,cAAc,SAAS,SAAS,WAAW,MAAM;AACvD,QAAM,CAAC,QAAQ,YAAY,IAAI,oBAAoB,OAAO,aAAa,WAAW,aAAa,SAAS,WAAW,UAAU,sBAAsB;AACnJ,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,OAAO,MAAM,GAAG,UAAU,MAAM;AAAA,IACzD,SAAS,eAAe,WAAW,OAAO,SAAS,YAAY;AAAA,EACjE;AACF;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,UAAU,IAAI;AACtB,QAAM,EAAE,OAAO,QAAQ,UAAU,IAAI;AACrC,MAAI,OAAO,UAAU,UAAU;AAC7B,UAAM,IAAI,MAAM,kCAAkC;AAAA,EACpD;AACA,MAAI,OAAO,MAAM,WAAW,GAAG;AAC7B,UAAM,IAAI,MAAM,sCAAsC,OAAO,OAAO;AAAA,EACtE;AACA,MAAI,UAAU,MAAM,WAAW,GAAG;AAChC,UAAM,IAAI,MAAM,0CAA0C,UAAU,OAAO;AAAA,EAC7E;AACA,QAAM,SAAS,SAAS,SAAS,OAAO,MAAM;AAC9C,QAAM,aAAa,SAAS,SAAS,UAAU,MAAM,EAAE;AACvD,QAAM,CAAC,SAAS,QAAQ,KAAK,IAAI,mBAAmB,QAAQ,YAAY,SAAS;AACjF,QAAMoB,cAAa,OAAO;AAC1B,SAAO;AAAA,IACL,SAAS,eAAe,CAACA,aAAY,CAAC,GAAG,SAAS,OAAO;AAAA,IACzD,SAAS,eAAe,CAACA,WAAU,GAAG,UAAU,MAAM;AAAA,IACtD,SAAS,eAAe,CAAC,CAAC,GAAG,SAAS,IAAI,WAAW,KAAK,CAAC;AAAA,EAC7D;AACF;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,wBAAwB,MAAM;AACrC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,WAAW,IAAI;AACvB,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,MAAI,OAAO,UAAU,UAAU;AAC7B,UAAM,IAAI,MAAM,kCAAkC;AAAA,EACpD;AACA,MAAI,cAAc,GAAG;AACnB,UAAM,IAAI,MAAM,sCAAsC;AAAA,EACxD;AACA,QAAM,SAAS,SAAS,SAAS,OAAO,MAAM;AAC9C,QAAM,SAAS,8BAA8B,QAAQ,UAAU;AAC/D,SAAO,SAAS,eAAe,OAAO,OAAO,SAAS,MAAM;AAC9D;AACA,IAAI,gCAAgC;AAAA,EAClC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,MAAM;AACV,IAAI,OAAO,iBAAiB,EAAE,WAAW,IAAI,CAAC;AAC9C,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO;AAAA;AAAA;AAAA;AAIX,IAAI,QAAQ,iBAAiB,EAAE,WAAW,KAAK,CAAC;AAChD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,QAAQ,MAAM;AACxB,SAAK,gBAAgB,CAAC,GAAG;AACzB,UAAM,cAAc,IAAI,MAAM,OAAO,MAAM;AAC3C,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,MAAM;AAC9C,kBAAY,MAAM,OAAO,MAAM,KAAK;AAAA,IACtC;AACA,SAAK,cAAc;AACnB,SAAK,OAAO,YAAY;AACxB,UAAM,QAAQ,kBAAkB,KAAK,IAAI;AACzC,UAAM,eAAe,iBAAiB,MAAM;AAC5C,SAAK,WAAW;AAAA;AAAA,UAEV;AAAA,yBACe;AAAA;AAAA;AAAA,EAGvB;AACF;AACA,SAAS,iBAAiB,QAAQ;AAChC,QAAM,OAAO,OAAO;AACpB,MAAI,OAAO,GAAG;AACZ,UAAM,MAAM,iBAAiB,2BAA2B;AAAA,EAC1D;AACA,MAAI,SAAS,GAAG;AACd,WAAO,eAAe,OAAO;AAAA,EAC/B;AACA,QAAM,gBAAgB,CAAC,WAAW,WAAW,WAAW,WAAW,SAAS;AAC5E,QAAM,eAAe,CAAC;AACtB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,iBAAa,KAAK,QAAQ,cAAc,QAAQ,OAAO,MAAM;AAAA,EAC/D;AACA,SAAO,aAAa,KAAK;AAC3B;AAGA,SAAS,MAAM,QAAQ;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,EAAE,UAAU,YAAY,EAAE,MAAM,SAAS,GAAG;AAC9C,UAAM,OAAO,SAAS,SAAS,EAAE,MAAM;AACvC,UAAM,QAAQ,EAAE,UAAU,WAAW,KAAK,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC,IAAI;AACrF,UAAM,MAAM,OAAO,EAAE,OAAO,EAAE,OAAO,KAAK;AAC1C,UAAM,SAAS,YAAY,KAAK,IAAI;AACpC,WAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAAA,EAC1E;AACA,QAAM,UAAU,IAAI,YAAY,EAAE,OAAO,IAAI;AAC7C,QAAM,SAAS,SAAS,gBAAgB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AAC7D,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,OAAO;AACjB,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,iBAAiB;AAAA,MACpB,EAAE,MAAM,KAAK,MAAM,MAAM;AAAA,MACzB,EAAE,MAAM,aAAa,MAAM,MAAM;AAAA,MACjC,EAAE,MAAM,eAAe,MAAM,QAAQ;AAAA,MACrC,EAAE,MAAM,OAAO,MAAM,MAAM;AAAA,MAC3B,EAAE,MAAM,OAAO,MAAM,MAAM;AAAA,IAC7B;AACA,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAyClB;AACF;AACA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,OAAO;AACjB,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,iBAAiB;AAAA,MACpB,EAAE,MAAM,KAAK,MAAM,MAAM;AAAA,MACzB,EAAE,MAAM,aAAa,MAAM,MAAM;AAAA,MACjC,EAAE,MAAM,KAAK,MAAM,MAAM;AAAA,IAC3B;AACA,SAAK,cAAc;AACnB,SAAK,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAmClB;AACF;AAGA,SAAS,oCAAoC,UAAU,YAAY;AACjE,MAAI,eAAe,MAAM;AACvB,aAAS,8BAA8B,UAAU;AAAA,EACnD;AACF;AACA,SAAS,cAAc,KAAK;AAC1B,MAAI,QAAQ;AACZ,SAAO,QAAQ,KAAK;AAClB,aAAS;AAAA,EACX;AACA,SAAO;AACT;AACA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,2CAA2C,IAAI,EAAE,UAAU,0CAA0C;AAC3G,QAAM,+BAA+B,IAAI,EAAE,UAAU,8BAA8B;AACnF,QAAM,SAAS,EAAE;AACjB,QAAM,UAAU,OAAO,OAAO,SAAS;AACvC,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,KAAK,UAAU,4CAA4C,IAAI,8BAA8B;AAC9H,UAAM,QAAQ,SAAS,SAAS,EAAE,MAAM;AACxC,UAAM,CAAC,aAAa,cAAc,IAAI,YAAY,OAAO,QAAQ,EAAE,OAAO,GAAG,MAAM;AACnF,WAAO;AAAA,MACL,SAAS,eAAe,YAAY,OAAO,YAAY,OAAO,YAAY,MAAM;AAAA,MAChF,SAAS,eAAe,eAAe,OAAO,eAAe,OAAO,eAAe,MAAM;AAAA,IAC3F;AAAA,EACF;AACA,MAAI,MAAM,GAAG;AACX,WAAO,OAAO,SAAS,KAAK;AAC5B,WAAO;AAAA,MACL,SAAS,eAAe,QAAQ,EAAE,OAAO,CAAC,CAAC;AAAA,MAC3C,SAAS,eAAe,QAAQ,SAAS,CAAC,CAAC;AAAA,IAC7C;AAAA,EACF;AACA,MAAI,YAAY,GAAG;AACjB,WAAO;AAAA,MACL;AAAA,MACA,MAAM,EAAE,OAAO,EAAE,OAAO,QAAQ,OAAO,SAAS,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,IACjF;AAAA,EACF;AACA,QAAM,WAAW,SAAS,QAAQ,IAAI,EAAE,MAAM;AAC9C,QAAM,YAAY,aAAa,QAAQ,SAAS;AAChD,QAAM,YAAY,YAAY,SAAS,aAAa,CAAC,IAAI;AACzD,QAAM,QAAQ,aAAa,cAAc,MAAM;AAC/C,QAAM,QAAQ,QAAQ;AACtB,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,OAAO,EAAE,OAAO,CAAC,OAAO,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AACxG,MAAI,WAAW;AACb,wCAAoC,UAAU,SAAS;AAAA,EACzD;AACA,QAAM,QAAQ,cAAc,CAAC;AAC7B,QAAM,cAAc,cAAc,OAAO;AACzC,MAAI,UAAU;AACd,QAAM,YAAY,MAAM,YAAY,OAAO,CAAC,KAAK,GAAG,IAAI,CAAC,KAAK,OAAO;AACrE,QAAM,UAAU,CAAC,KAAK,KAAK,UAAU;AACnC,UAAM,UAAU,UAAU;AAC1B,UAAM,UAAU,IAAI,YAAY,KAAK;AACrC,UAAM,WAAW,YAAY,OAAO,IAAI;AACxC,UAAM,eAAe,CAAC,CAAC,OAAO,GAAG,CAAC,QAAQ,GAAG,CAAC,OAAO,iBAAiB,GAAG,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC;AACrF,UAAM,eAAe;AACrB,cAAU,SAAS,gBAAgB,SAAS,SAAS,SAAS,YAAY;AAC1E,wCAAoC,UAAU,YAAY;AAAA,EAC5D;AACA,WAAS,MAAM,GAAG,MAAM,OAAO,OAAO,GAAG;AACvC,UAAM,MAAM,MAAM;AAClB,aAAS,MAAM,KAAK,OAAO,GAAG,OAAO,GAAG;AACtC,cAAQ,KAAK,KAAK,CAAC,OAAO,WAAW,CAAC;AAAA,IACxC;AAAA,EACF;AACA,WAAS,cAAc,aAAa,cAAc,OAAO,eAAe,GAAG;AACzE,UAAM,UAAU,UAAU;AAC1B,UAAM,eAAe,IAAI,aAAa,CAAC,OAAO,cAAc,CAAC,CAAC;AAC9D,UAAM,YAAY,YAAY,OAAO,IAAI;AACzC,UAAM,eAAe,CAAC,CAAC,OAAO,GAAG,CAAC,SAAS,GAAG,CAAC,KAAK,CAAC;AACrD,UAAM,eAAe;AACrB,cAAU,SAAS,gBAAgB,cAAc,SAAS,SAAS,YAAY;AAC/E,wCAAoC,UAAU,YAAY;AAC1D,UAAM,MAAM,QAAQ;AACpB,UAAM,MAAM,MAAM;AAClB,aAAS,MAAM,KAAK,OAAO,GAAG,OAAO,GAAG;AACtC,cAAQ,KAAK,KAAK,QAAQ,KAAK;AAAA,IACjC;AAAA,EACF;AACA,MAAI,cAAc;AAClB,YAAU,OAAO,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,GAAG,MAAM,CAAC,OAAO,CAAC,EAAE,EAAE,CAAC;AACrG,sCAAoC,UAAU,WAAW;AACzD,MAAI,SAAS,UAAU,EAAE,QAAQ,EAAE,GAAG,KAAK,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,GAAG,WAAW,EAAE,EAAE,CAAC;AAC3G,sCAAoC,UAAU,GAAG;AACjD,QAAM,WAAW,OAAO,MAAM,GAAG,EAAE;AACnC,WAAS,KAAK,CAAC;AACf,gBAAc;AACd,YAAU,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AAC5F,sCAAoC,UAAU,WAAW;AACzD,QAAM,aAAa;AACnB,WAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AAC1F,sCAAoC,UAAU,UAAU;AACxD,SAAO,CAAC,QAAQ,OAAO;AACzB;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,aAAa,YAAY,eAAe,UAAU,WAAW,UAAU;AACjF,SAAK,gBAAgB,CAAC,SAAS,YAAY;AAC3C,SAAK,cAAc;AACnB,UAAM,sBAAsB,kBAAkB,YAAY,IAAI;AAC9D,QAAI;AACJ,YAAQ;AAAA,WACD;AACH,qBAAa;AACb;AAAA,WACG;AACH,qBAAa;AACb;AAAA,WACG;AACH,qBAAa;AACb;AAAA,WACG;AACH,qBAAa;AACb;AAAA;AAEA,qBAAa;AACb;AAAA;AAEJ,SAAK,WAAW;AAAA;AAAA;AAAA,mBAGD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,2BAwBQ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,2BAiBA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,4CAUiB,0CAA0C;AAAA;AAAA;AAAA,sCAGhD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,sCAwBA;AAAA;AAAA;AAAA;AAAA,mDAIa;AAAA,mDACA;AAAA;AAAA,sBAE7B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAyBpB;AACF;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,WAAW,IAAI;AACtC,QAAM,EAAE,eAAe,UAAU,WAAW,YAAY,IAAI;AAC5D,QAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,QAAM,CAAC,WAAW,QAAQ,IAAI,eAAe,OAAO,cAAc,CAAC,aAAa,UAAU;AAC1F,QAAM,WAAW;AAAA,IACf;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACA,QAAM,UAAU,IAAI,iBAAiB,aAAa,YAAY,eAAe,UAAU,WAAW,QAAQ;AAC1G,SAAO,SAAS,gBAAgB,SAAS,CAAC,QAAQ,UAAU,GAAG,SAAS;AAC1E;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,EAAE,EAAE,IAAI;AACd,oBAAkB,GAAG,QAAQ;AAC7B,UAAQ,KAAK,aAAa,4DAA4D;AACtF,QAAM,SAAS,SAAS,SAAS,EAAE,MAAM;AACzC,QAAM,EAAE,cAAc,aAAa,QAAQ,IAAI,cAAc,QAAQ,MAAM,EAAE,OAAO,EAAE,KAAK;AAC3F,SAAO;AAAA,IACL,SAAS,eAAe,aAAa,EAAE,OAAO,YAAY;AAAA,IAC1D,SAAS,eAAe,CAAC,QAAQ,MAAM,GAAG,SAAS,OAAO;AAAA,EAC5D;AACF;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,IAAI;AAClB,MAAI,EAAE,KAAK,IAAI;AACf,MAAI,OAAO,GAAG;AACZ,YAAQ,MAAM,MAAM;AAAA,EACtB;AACA,QAAM,IAAI;AACV,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,MAAM,MAAM,MAAM;AACxB,QAAM,WAAW,IAAI,MAAM,QAAQ,CAAC;AACpC,MAAI,WAAW;AACf,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM;AACjC,QAAI,OAAO,MAAM;AACf,eAAS,cAAc,EAAE,MAAM;AAAA,IACjC;AAAA,EACF;AACA,QAAM,YAAY,CAAC;AACnB,QAAM,QAAQ,IAAI,MAAM,KAAK,EAAE,KAAK,CAAC;AACrC,QAAMpB,QAAO,EAAE,MAAM,MAAM;AAC3B,EAAAA,MAAK,QAAQ;AACb,QAAM,MAAM,IAAI,MAAM,GAAG;AACzB,WAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,MAAM;AACtC,UAAM,QAAQ;AACd,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,MAAAA,MAAK,EAAE,CAAC;AAClF,UAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAClG,QAAI,MAAM;AACV,cAAU,KAAK,MAAM;AAAA,EACvB;AACA,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,WAAW,WAAW;AAChC,SAAK,gBAAgB,CAAC,KAAK,YAAY;AACvC,UAAM,aAAa,UAAU;AAC7B,UAAM,YAAY,UAAU;AAC5B,UAAM,SAAS,UAAU;AACzB,UAAM,cAAc,UAAU;AAC9B,UAAM,UAAU,cAAc,KAAK,KAAK,SAAS,UAAU;AAC3D,SAAK,cAAc,CAAC,WAAW,OAAO;AACtC,UAAM,sBAAsB;AAC5B,UAAM,cAAc;AACpB,UAAM,wBAAwB,KAAK,MAAM,aAAa,CAAC,IAAI;AAC3D,UAAM,0BAA0B,aAAa;AAC7C,UAAM,gBAAgB;AAAA;AAAA;AAGtB,QAAI,wBAAwB;AAC5B,QAAI,SAAS,aAAa,GAAG;AAC3B,8BAAwB;AAAA,oCACM;AAAA;AAAA;AAAA;AAAA,IAIhC;AACA,QAAI,4BAA4B;AAChC,QAAI,SAAS,aAAa,GAAG;AAC3B,kCAA4B;AAAA,oCACE;AAAA;AAAA;AAAA;AAAA,IAIhC;AACA,SAAK,WAAW;AAAA,0CACsB;AAAA;AAAA;AAAA,UAGhC;AAAA;AAAA;AAAA;AAAA;AAAA,UAKA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YASE,yBAAyB;AAAA,wDACmB;AAAA;AAAA;AAAA;AAAA,8BAI1B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAgBlB;AAAA;AAAA;AAAA,iCAGqB;AAAA,cACnB,4BAA4B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAiB9B;AAAA,qBACS,4BAA4B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAerC;AAAA,qBACS,4BAA4B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAerC;AAAA;AAAA,oBAEQ;AAAA;AAAA;AAAA,EAGlB;AACF;AAGA,SAAS,oBAAoB,MAAM;AACjC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,WAAW,IAAI;AAC1B,QAAM,EAAE,YAAY,IAAI;AACxB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,YAAY,CAAC;AACnB,MAAI,OAAO;AACX,QAAM,cAAc,qBAAqB,mBAAmB,CAAC,IAAI,GAAG,KAAK;AACzE,MAAI,YAAY;AAChB,MAAI,eAAe,MAAM;AACvB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,YAAY,EAAE,CAAC;AACzF,cAAU,KAAK,SAAS;AACxB,WAAO,qBAAqB,iBAAiB,GAAG,KAAK,EAAE;AAAA,EACzD;AACA,QAAM,WAAW,qBAAqB,aAAa,gBAAgB,UAAU,OAAO,MAAM,WAAW;AACrG,QAAM,SAAS,aAAa,cAAc,CAAC,UAAU,MAAM,KAAK,CAAC;AACjE,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,IAAI,MAAM,EAAE,EAAE,CAAC;AACpG,YAAU,KAAK,GAAG;AAClB,QAAM,cAAc,WAAW,EAAE,KAAK;AACtC,QAAM,eAAe,CAAC,IAAI,WAAW,aAAa,OAAO,iBAAiB;AACxE,UAAM,YAAY,GAAG,MAAM;AAC3B,UAAM,UAAU,GAAG,MAAM;AACzB,UAAM,aAAa,qBAAqB,aAAa,8BAA8B,SAAS,YAAY;AACxG,UAAM,YAAY,EAAE,YAAY,QAAQ,SAAS,WAAW,aAAa,aAAa;AACtF,UAAM,UAAU,IAAI,iBAAiB,WAAW,SAAS;AACzD,UAAM,SAAS,SAAS,cAAc,SAAS,CAAC,IAAI,WAAW,GAAG,KAAK;AACvE,cAAU,KAAK,MAAM;AACrB,QAAI,OAAO,MAAM,OAAO,cAAc;AACpC,aAAO;AAAA,IACT;AACA,UAAM,YAAY,OAAO;AAAA,MACvB,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,GAAG,MAAM,cAAc,MAAM,GAAG,OAAO,UAAU;AAAA,IACnE,CAAC;AACD,UAAM,WAAW,MAAM;AAAA,MACrB,QAAQ,EAAE,GAAG,UAAU;AAAA,MACvB,SAAS;AAAA,MACT,OAAO,EAAE,MAAM,CAAC,UAAU,UAAU,EAAE;AAAA,IACxC,CAAC;AACD,cAAU,KAAK,SAAS;AACxB,cAAU,KAAK,QAAQ;AACvB,UAAM,UAAU,aAAa,QAAQ,WAAW,UAAU,OAAO,YAAY;AAC7E,WAAO;AAAA,EACT;AACA,QAAM,cAAc,aAAa,KAAK,sBAAsB,YAAY,aAAa,WAAW;AAChG,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,YAAY,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACvG,MAAI,SAAS;AACb,MAAI,eAAe,MAAM;AACvB,cAAU,KAAK,QAAQ;AACvB,UAAM,OAAO,qBAAqB,uBAAuB,WAAW;AACpE,aAAS,WAAW,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AAAA,EACnF;AACA,YAAU,QAAQ,CAAC,OAAO,SAAS,8BAA8B,EAAE,CAAC;AACpE,SAAO;AACT;AACA,IAAI,4BAA4B;AAAA,EAC9B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB;AAAA,EACnB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,WAAW,gBAAgB,gBAAgB;AACzC,iBAAe,YAAY;AAC7B;AAGA,IAAI;AAAA,CACH,SAAS,WAAW;AACnB,YAAU,UAAU,aAAa,KAAK;AACtC,YAAU,UAAU,WAAW,KAAK;AACpC,YAAU,UAAU,UAAU,KAAK;AACnC,YAAU,UAAU,YAAY,KAAK;AACrC,YAAU,UAAU,eAAe,KAAK;AAC1C,GAAG,aAAa,WAAW,CAAC,EAAE;AAC9B,IAAI;AAAA,CACH,SAAS,oBAAoB;AAC5B,qBAAmB,mBAAmB,YAAY,KAAK;AACvD,qBAAmB,mBAAmB,UAAU,KAAK;AACrD,qBAAmB,mBAAmB,WAAW,KAAK;AACtD,qBAAmB,mBAAmB,WAAW,KAAK;AACtD,qBAAmB,mBAAmB,eAAe,KAAK;AAC1D,qBAAmB,mBAAmB,aAAa,KAAK;AACxD,qBAAmB,mBAAmB,SAAS,KAAK;AACtD,GAAG,sBAAsB,oBAAoB,CAAC,EAAE;AAGhD,IAAI;AACJ,SAAS,MAAM,UAAU;AACvB,oBAAkB,SAAS,KAAK,MAAM,cAAc,MAAM;AAAA,IACxD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,iBAAiB,MAAM;AAC9B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,MAAM,uBAAuB,IAAI;AAC/C,MAAI,EAAE,UAAU,aAAa,EAAE,UAAU,WAAW;AAClD,UAAM,IAAI,MAAM,6DAA6D;AAAA,EAC/E;AACA,QAAM,EAAE,YAAY,YAAY,YAAY,aAAa,eAAe,IAAI;AAC5E,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,SAAS;AACb,MAAI,QAAQ,MAAM;AAChB,UAAM,WAAW,SAAS,UAAU,IAAI,KAAK,MAAM;AACnD,QAAI,SAAS,MAAM,WAAW,GAAG;AAC/B,YAAM,IAAI,MAAM,uDAAuD,SAAS,MAAM,SAAS;AAAA,IACjG;AACA,aAAS,SAAS;AAAA,EACpB;AACA,QAAM,2BAA2B,0BAA0B,OAAO,IAAI,SAAS,UAAU,IAAI,uBAAuB,MAAM,EAAE;AAC5H,QAAM,kBAAkB,kBAAkB;AAC1C,MAAI,mBAAmB,MAAM;AAC3B,UAAM,IAAI,MAAM,GAAG,+EAA+E;AAAA,EACpG;AACA,QAAM,UAAU,aAAa,EAAE,MAAM,KAAK,EAAE,MAAM;AAClD,QAAM,WAAW,aAAa,EAAE,MAAM,KAAK,EAAE,MAAM;AACnD,QAAM,YAAY,uBAAuB,2BAA2B,EAAE,MAAM,MAAM,GAAG,EAAE,GAAG,EAAE,MAAM,MAAM,GAAG,EAAE,CAAC;AAC9G,QAAM,MAAM,SAAS,WAAW,CAAC,GAAG,WAAW,SAAS,QAAQ,GAAG,EAAE,KAAK;AAC1E,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,kBAAgB,KAAK,aAAa,EAAE,MAAM,QAAQ,KAAK,aAAa,EAAE,MAAM,QAAQ,YAAY,YAAY,iBAAiB,QAAQ,0BAA0B,kBAAkB,GAAG,KAAK;AACzL,SAAO;AACT;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,wBAAwB,YAAY,SAAS;AACpD,MAAI;AACJ,WAAS,WAAW,UAAU;AAC5B,gBAAY,SAAS,KAAK,MAAM,YAAY,MAAM;AAAA,MAChD;AAAA,MACA;AAAA,MACA;AAAA,IACF,CAAC;AAAA,EACH;AACA,WAAS,YAAY,MAAM;AACzB,UAAM,EAAE,SAAS,UAAU,QAAQ,EAAE,EAAE,EAAE,IAAI;AAC7C,UAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,MAAM,SAAS,WAAW,EAAE,OAAO,WAAW,EAAE,KAAK;AAC3D,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAI,aAAa,cAAc,IAAI,KAAK,MAAM,GAAG;AAC/C,aAAO;AAAA,IACT;AACA,cAAU,KAAK,SAAS,EAAE,QAAQ,KAAK;AACvC,WAAO;AAAA,EACT;AACA,SAAO,EAAE,YAAY,aAAa,QAAQ,WAAW,YAAY,YAAY,YAAY;AAC3F;AAGA,IAAI,aAAa,wBAAwB,GAAG;AAG5C,SAAS,yBAAyB,YAAY,yBAAyB,OAAO;AAC5E,MAAI;AACJ,WAAS,WAAW,UAAU;AAC5B,gBAAY,SAAS,KAAK,MAAM,YAAY,MAAM;AAAA,MAChD;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF,CAAC;AAAA,EACH;AACA,WAAS,YAAY,MAAM;AACzB,UAAM,EAAE,SAAS,UAAU,OAAO,IAAI;AACtC,UAAM,EAAE,GAAG,EAAE,IAAI;AACjB,UAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,aAAa,SAAS,OAAO,QAAQ,EAAE;AAC7C,UAAM,WAAW,qBAAqB,2BAA2B,EAAE,OAAO,EAAE,KAAK;AACjF,UAAM,MAAM,SAAS,WAAW,UAAU,UAAU;AACpD,QAAI,aAAa,cAAc,QAAQ,MAAM,GAAG;AAC9C,aAAO;AAAA,IACT;AACA,UAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,UAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,UAAM,cAAc,MAAM,UAAU,KAAK,aAAa,EAAE,MAAM,QAAQ,KAAK,aAAa,EAAE,MAAM,QAAQ,SAAS,EAAE,QAAQ,KAAK;AAChI,gBAAY;AACZ,WAAO;AAAA,EACT;AACA,SAAO,EAAE,YAAY,aAAa,QAAQ,WAAW,YAAY,YAAY,YAAY;AAC3F;AAGA,IAAI,wBAAwB;AAC5B,IAAI,aAAa,yBAAyB,KAAK,qBAAqB;AAGpE,IAAI;AACJ,SAAS,UAAU,UAAU;AAC3B,aAAW,SAAS,KAAK,MAAM,MAAM,MAAM;AAAA,IACzC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,MAAM,SAAS,WAAW,OAAO,GAAG,OAAO,OAAO,GAAG,KAAK;AAChE,MAAI,aAAa,cAAc,IAAI,KAAK,MAAM,GAAG;AAC/C,WAAO;AAAA,EACT;AACA,QAAM,WAAW,OAAO,IAAI,CAAC,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE,EAAE;AACtE,QAAM,gBAAgB,IAAI,WAAW,IAAI,WAAW,QAAQ,EAAE,MAAM;AACpE,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,WAAS,eAAe,SAAS,QAAQ,SAAS,IAAI,QAAQ,KAAK;AACnE,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb;AAAA,EACA,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,IAAI;AAC7C,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,SAAS,SAAS,mBAAmB,CAAC;AAC5C,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,UAAQ,IAAI,MAAM;AAClB,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,kBAAgB,SAAS,KAAK,MAAM,WAAW,MAAM;AAAA,IACnD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,CAAC,cAAc,IAAI,IAAI,kBAAkB,OAAO,EAAE,OAAO,MAAM,IAAI;AACzE,MAAI,aAAa;AACjB,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,QAAI,KAAK,QAAQ,IAAI;AACnB,mBAAa;AAAA,IACf;AAAA,EACF;AACA,QAAM,WAAW,iBAAiB,OAAO,EAAE,OAAO,MAAM,IAAI;AAC5D,QAAM,IAAI;AAAA,IACR,QAAQ,OAAO,EAAE;AAAA,IACjB,OAAO;AAAA,IACP,OAAO,OAAO,EAAE;AAAA,EAClB;AACA,MAAI,YAAY;AACd,UAAM,SAAS,UAAU,EAAE,QAAQ,SAAS,SAAS,CAAC;AACtD,WAAO,QAAQ;AACf,WAAO;AAAA,EACT;AACA,QAAM,MAAM,SAAS,WAAW,UAAU,EAAE,KAAK;AACjD,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,YAAY,IAAI,WAAW,IAAI,WAAW,IAAI,EAAE,MAAM;AAC5D,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,gBAAc,KAAK,aAAa,EAAE,MAAM,QAAQ,SAAS,EAAE,QAAQ,OAAO,WAAW,KAAK,MAAM;AAChG,SAAO;AACT;AACA,SAAS,iBAAiB,SAAS,MAAM;AACvC,QAAM,WAAW,IAAI,MAAM,QAAQ,MAAM;AACzC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,aAAS,MAAM,QAAQ,KAAK;AAAA,EAC9B;AACA,SAAO;AACT;AACA,SAAS,kBAAkB,OAAO,MAAM;AACtC,QAAM,WAAW,CAAC;AAClB,QAAM,UAAU,CAAC;AACjB,WAAS,KAAK,GAAG,KAAK,MAAM,QAAQ,EAAE,IAAI;AACxC,QAAI,MAAM,QAAQ,GAAG;AACnB,eAAS,KAAK,MAAM,GAAG;AAAA,IACzB;AACA,QAAI,MAAM,KAAK,SAAS,GAAG;AACzB,cAAQ,KAAK,KAAK,GAAG;AAAA,IACvB;AAAA,EACF;AACA,WAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,EAAE,IAAI;AAC1C,QAAI,YAAY;AAChB,aAAS,IAAI,GAAG,IAAI,QAAQ,QAAQ,EAAE,GAAG;AACvC,UAAI,QAAQ,MAAM,OAAO,cAAc,MAAM,QAAQ,aAAa,QAAQ,KAAK;AAC7E,oBAAY;AAAA,MACd;AAAA,IACF;AACA,YAAQ,aAAa;AAAA,EACvB;AACA,SAAO,CAAC,UAAU,OAAO;AAC3B;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,SAAS,wBAAwB,GAAG,MAAM,UAAU;AAClD,QAAM,SAAS,EAAE;AACjB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,eAAe,aAAa,eAAe,MAAM,MAAM;AAC7D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,cAAc;AAClB,MAAI,qBAAqB;AACzB,MAAI,gBAAgB,MAAM;AACxB,UAAM,WAAW,IAAI,MAAM,KAAK;AAChC,aAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,eAAS,MAAM,OAAO,aAAa;AAAA,IACrC;AACA,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAC/D,kBAAc,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,MAAM,aAAa,GAAG,SAAS,SAAS,CAAC;AAC5F,UAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,eAAe,SAAS,UAAU,IAAI,YAAY,MAAM,EAAE;AAChE,QAAI,iBAAiB,KAAK;AACxB,2BAAqB;AAAA,IACvB;AAAA,EACF;AACA,SAAO,EAAE,YAAY,aAAa,cAAc,MAAM,mBAAmB;AAC3E;AAGA,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,YAAU,SAAS,KAAK,MAAM,KAAK,MAAM,CAAC,wBAAwB,CAAC;AACrE;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,cAAc,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AACxG,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,aAAS;AACT,cAAU;AAAA,EACZ;AACA,QAAM,YAAY,OAAO,MAAM;AAC/B,uBAAqB,2BAA2B,OAAO,MAAM,SAAS;AACtE,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,IAAI;AACjG,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,MAAM,SAAS,WAAW,UAAU,EAAE,KAAK;AACjD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,YAAQ,SAAS,YAAY,KAAK;AAAA,EACpC;AACA,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,YAAY;AAClF,QAAI,QAAQ;AAAA,EACd;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,YAAU,SAAS,KAAK,MAAM,KAAK,MAAM,CAAC,wBAAwB,CAAC;AACrE;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,cAAc,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AACxG,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,aAAS;AACT,cAAU;AAAA,EACZ;AACA,QAAM,YAAY,OAAO,MAAM;AAC/B,uBAAqB,2BAA2B,OAAO,MAAM,SAAS;AACtE,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,IAAI;AACjG,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,MAAM,SAAS,WAAW,UAAU,EAAE,KAAK;AACjD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,YAAQ,SAAS,YAAY,KAAK;AAAA,EACpC;AACA,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,YAAY;AAClF,QAAI,QAAQ;AAAA,EACd;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,cAAY,SAAS,KAAK,MAAM,QAAQ,MAAM;AAAA,IAC5C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AAC1F,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAI,iBAAiB,KAAK;AACxB,eAAS;AACT,gBAAU;AAAA,IACZ;AAAA,EACF;AACA,QAAM,WAAW,OAAO,MAAM,MAAM,GAAG,EAAE;AACzC,QAAM,MAAM,SAAS,WAAW,UAAU,OAAO;AACjD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,YAAY,aAAa,cAAc,IAAI,KAAK;AACtD,QAAM,YAAY,OAAO,MAAM,KAAK;AACpC,YAAU,SAAS,SAAS,OAAO,QAAQ,WAAW,WAAW,KAAK;AACtE,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,gBAAc,SAAS,KAAK,MAAM,SAAS,MAAM;AAAA,IAC/C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,IAAI,OAAO;AACjB,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,EAAE,YAAY,SAAAY,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,MAAM,eAAe;AAC9G,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,YAAY,SAAS,QAAQ;AACnC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,WAAW,SAAS;AAC1B,MAAI,SAAS,eAAe,gBAAgB;AAC1C,UAAM,IAAI,MAAM,6CAA6C,SAAS,yCAAyC;AAAA,EACjH;AACA,MAAI,SAAS,kBAAkB,KAAK,SAAS,mBAAmB,GAAG;AACjE,UAAM,IAAI,MAAM,0EAA0E,SAAS,mBAAmB,SAAS,iBAAiB;AAAA,EAClJ;AACA,QAAM,MAAM,SAAS,WAAW,SAAS,UAAU,SAAS;AAC5D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,cAAY,KAAK,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,cAAc,aAAa,QAAQ,UAAU,WAAW,SAAS,cAAc,aAAa,UAAU,KAAK;AAChK,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,MAAM,IAAI;AAC1B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,SAAS,aAAa,uBAAuB,OAAO,KAAK;AAC/D,eAAa,OAAO,UAAU,aAAa,cAAc,MAAM,GAAG,MAAM,cAAc,sBAAsB,EAAE,uEAAuE;AACrL,OAAK,QAAQ,OAAO,EAAE,MAAM;AAC5B,SAAO,EAAE,QAAQ,EAAE,QAAQ,OAAO,QAAQ,OAAO,EAAE,MAAM;AAC3D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,oBAAkB,SAAS,KAAK,MAAM,aAAa,MAAM;AAAA,IACvD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,EAAE,IAAI;AACjB,QAAM,EAAE,YAAY,WAAW,IAAI;AACnC,MAAI,EAAE,UAAU,aAAa,EAAE,UAAU,WAAW;AAClD,UAAM,IAAI,MAAM,4DAA4D;AAAA,EAC9E;AACA,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,oBAAoB,uBAAuB,2BAA2B,EAAE,MAAM,MAAM,GAAG,EAAE,GAAG,EAAE,MAAM,MAAM,GAAG,EAAE,CAAC;AACtH,QAAM,WAAW,kBAAkB,OAAO,CAAC,aAAa,WAAW,CAAC;AACpE,eAAa,OAAO,gBAAgB,aAAa,MAAM,kCAAkC,qBAAqB,uCAAuC,EAAE,aAAa,EAAE,wBAAwB,6BAA6B,wBAAwB;AACnP,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,UAAU,aAAa,IAAI,MAAM,KAAK,IAAI,MAAM;AACtD,QAAM,WAAW,aAAa,IAAI,MAAM,KAAK,IAAI,MAAM;AACvD,QAAM,WAAW,KAAK,IAAI,WAAW,SAAS;AAC9C,QAAM,MAAM,SAAS,WAAW,CAAC,UAAU,SAAS,QAAQ,GAAG,IAAI,KAAK;AACxE,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,IAAI,KAAK,EAAE,MAAM;AACnE,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,IAAI,KAAK,EAAE,MAAM;AACnE,kBAAgB,OAAO,aAAa,IAAI,MAAM,QAAQ,OAAO,aAAa,IAAI,MAAM,QAAQ,YAAY,YAAY,KAAK;AACzH,WAAS,YAAY,IAAI,MAAM;AAC/B,WAAS,YAAY,IAAI,MAAM;AAC/B,MAAI,QAAQ;AACZ,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,OAAO,MAAAZ,MAAK,GAAG,SAAS,SAAS,IAAI;AACrE,QAAM,CAAC,QAAQ,KAAK,IAAI,mBAAmB,iBAAiB,GAAG,OAAOA,KAAI;AAC1E,QAAM,cAAc,mBAAmB,iBAAiB,EAAE,OAAO,QAAQ,KAAK;AAC9E,QAAM,QAAQ,SAAS,SAAS,EAAE,MAAM;AACxC,QAAM,MAAM,SAAS,WAAW,OAAO,EAAE,KAAK;AAC9C,QAAM,WAAW,aAAa,eAAe,EAAE,KAAK;AACpD,QAAM,UAAU,SAAS,UAAU,IAAI,IAAI,MAAM;AACjD,MAAI,aAAa;AACf,UAAM,aAAa,mBAAmB,kBAAkB,QAAQ,QAAQ;AACxE,QAAI,EAAE,UAAU,UAAU;AACxB,cAAQ,cAAc,MAAM,MAAM,YAAY,aAAa,aAAa,cAAc,KAAK,CAAC;AAAA,IAC9F,OAAO;AACL,YAAM,WAAW,SAAS,mBAAmB,GAAG;AAChD,eAAS,IAAI,MAAM,SAAS,YAAY,aAAa,aAAa,cAAc,KAAK,CAAC,CAAC;AAAA,IACzF;AACA,WAAO;AAAA,EACT;AACA,MAAI,EAAE,UAAU,UAAU;AACxB,UAAM,MAAM,UAAU,OAAO,QAAQ,OAAO,EAAE,OAAO,EAAE,KAAK;AAC5D,YAAQ,cAAc;AACtB,WAAO;AAAA,EACT;AACA,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,QAAM,OAAO,EAAE,MAAM;AACrB,MAAI,SAAS,GAAG;AACd,aAAS,OAAO,SAAS,IAAI,SAAS,QAAQ,KAAK;AAAA,EACrD,WAAW,SAAS,GAAG;AACrB,aAAS,OAAO,SAAS,IAAI,SAAS,IAAI,SAAS,QAAQ,KAAK;AAAA,EAClE,WAAW,SAAS,GAAG;AACrB,aAAS,OAAO,SAAS,IAAI,SAAS,IAAI,SAAS,IAAI,SAAS,QAAQ,KAAK;AAAA,EAC/E,OAAO;AACL,UAAM,MAAM,UAAU,OAAO,QAAQ,OAAO,EAAE,OAAO,EAAE,KAAK;AAC5D,YAAQ,IAAI,GAAG;AAAA,EACjB;AACA,SAAO;AACT;AACA,SAAS,SAAS,OAAO,SAAS,SAAS,OAAOA,OAAM;AACtD,MAAI,YAAY;AAChB,QAAM,SAAS,MAAM;AACrB,QAAM,SAAS,MAAM;AACrB,QAAM,OAAO,SAASA,MAAK;AAC3B,WAAS,KAAK,QAAQ,KAAK,MAAM,MAAM;AACrC,UAAM,UAAU,KAAK,UAAU;AAC/B,YAAQ,IAAI,MAAM,SAAS,SAAS,UAAUA,MAAK,EAAE,GAAG,SAAS;AACjE,iBAAaA,MAAK;AAAA,EACpB;AACF;AACA,SAAS,SAAS,OAAO,UAAU,UAAU,SAAS,OAAOA,OAAM;AACjE,MAAI,YAAY;AAChB,QAAM,SAAS,MAAM;AACrB,QAAM,SAAS,MAAM;AACrB,QAAM,SAAS,MAAM;AACrB,QAAM,OAAO,SAASA,MAAK;AAC3B,QAAM,OAAO,SAASA,MAAK;AAC3B,WAAS,KAAK,QAAQ,KAAK,MAAM,MAAM;AACrC,aAAS,IAAI,QAAQ,IAAI,MAAM,KAAK;AAClC,YAAM,UAAU,KAAK,WAAW,IAAI,WAAW;AAC/C,cAAQ,IAAI,MAAM,SAAS,SAAS,UAAUA,MAAK,EAAE,GAAG,SAAS;AACjE,mBAAaA,MAAK;AAAA,IACpB;AAAA,EACF;AACF;AACA,SAAS,SAAS,OAAO,UAAU,UAAU,UAAU,SAAS,OAAOA,OAAM;AAC3E,MAAI,YAAY;AAChB,QAAM,SAAS,MAAM;AACrB,QAAM,SAAS,MAAM;AACrB,QAAM,SAAS,MAAM;AACrB,QAAM,OAAO,SAASA,MAAK;AAC3B,QAAM,OAAO,SAASA,MAAK;AAC3B,QAAM,OAAO,SAASA,MAAK;AAC3B,QAAM,SAAS,MAAM;AACrB,WAAS,KAAK,QAAQ,KAAK,MAAM,MAAM;AACrC,aAAS,IAAI,QAAQ,IAAI,MAAM,KAAK;AAClC,eAAS,IAAI,QAAQ,IAAI,MAAM,KAAK;AAClC,cAAM,UAAU,KAAK,WAAW,IAAI,WAAW,IAAI,WAAW;AAC9D,gBAAQ,IAAI,MAAM,SAAS,SAAS,UAAUA,MAAK,EAAE,GAAG,SAAS;AACjE,qBAAaA,MAAK;AAAA,MACpB;AAAA,IACF;AAAA,EACF;AACF;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,MAAM,IAAI;AAC9B,QAAM,QAAQ,WAAW,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAC/C,QAAM,WAAW,qBAAqB,YAAY,EAAE,OAAO,YAAY,KAAK;AAC5E,QAAM,WAAW,qBAAqB,YAAY,SAAS,QAAQ,WAAW,MAAM;AACpF,QAAM,mBAAmB,qBAAqB,oBAAoB,EAAE,OAAO,YAAY,KAAK;AAC5F,QAAM,mBAAmB,qBAAqB,oBAAoB,OAAO,WAAW,MAAM;AAC1F,QAAM,YAAY,qBAAqB,aAAa,kBAAkB,OAAO,WAAW,MAAM;AAC9F,QAAM,YAAY,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC3F,QAAM,cAAc,WAAW,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,SAAS,EAAE,CAAC;AACzG,QAAM,sBAAsB,SAAS,EAAE,QAAQ,EAAE,GAAG,YAAY,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,iBAAiB,EAAE,CAAC;AAC1H,QAAM,SAAS,OAAO;AAAA,IACpB,QAAQ,EAAE,GAAG,oBAAoB;AAAA,IACjC,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,kBAAkB,MAAM,UAAU;AAAA,EACpD,CAAC;AACD,WAAS,YAAY,UAAU,MAAM;AACrC,WAAS,YAAY,YAAY,MAAM;AACvC,WAAS,YAAY,UAAU,MAAM;AACrC,SAAO;AACT;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,MAAM,GAAG,SAAS,SAAS,IAAI;AAC/D,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,KAAK;AAC9C,QAAM,SAAS,SAAS,mBAAmB,CAAC;AAC5C,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,UAAQ,IAAI,MAAM;AAClB,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,wBAAwB,IAAI;AAG9C,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,aAAW,SAAS,KAAK,MAAM,aAAa,MAAM;AAAA,IAChD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,cAAc,aAAa,IAAI;AACvC,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,WAAS,KAAK,cAAc,cAAc,KAAK;AAC/C,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,OAAO,aAAa,eAAe,KAAK,MAAM,MAAM,OAAO,GAAG,KAAK,EAAE;AAC3E,MAAI,WAAW,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,IAAI;AACtF,QAAM,UAAU,OAAO,OAAO,CAAC,OAAO,aAAa,cAAc,GAAG,KAAK,IAAI,CAAC;AAC9E,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,GAAG,SAAS,SAAS,CAAC;AAAA,EACnE;AACA,QAAM,MAAM,SAAS,WAAW,UAAU,OAAO,GAAG,KAAK;AACzD,MAAI,aAAa,cAAc,QAAQ,MAAM,GAAG;AAC9C,WAAO;AAAA,EACT;AACA,QAAM,SAAS,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK;AAC3C,uBAAqB,uBAAuB,QAAQ,IAAI;AACxD,MAAI,QAAQ,GAAG,UAAU,UAAU;AACjC,UAAM,WAAW,QAAQ,IAAI,CAAC,OAAO;AACnC,YAAM,YAAY,aAAa,cAAc,GAAG,MAAM,MAAM,IAAI,CAAC;AACjE,YAAM,QAAQ,CAAC,IAAI,SAAS;AAC5B,aAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AAAA,IAC5E,CAAC;AACD,UAAM,kBAAkB,SAAS,IAAI,CAAC,OAAO;AAC3C,aAAO,EAAE,MAAM,SAAS,SAAS,GAAG,MAAM,GAAG,OAAO,GAAG,MAAM;AAAA,IAC/D,CAAC;AACD,eAAW,qBAAqB,gBAAgB,SAAS,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,CAAC;AACjF,UAAM,eAAe,SAAS,GAAG,MAAM,OAAO;AAC9C,UAAM,WAAW,WAAW,iBAAiB,UAAU,OAAO,GAAG,OAAO,YAAY;AACpF,UAAM,gBAAgB,qBAAqB,gBAAgB,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,IAAI;AAC9F,QAAI,QAAQ;AACZ,UAAM,UAAU,SAAS,UAAU,IAAI,IAAI,MAAM;AACjD,YAAQ,cAAc,qBAAqB,uBAAuB,QAAQ;AAC1E,aAAS,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACxD,WAAO;AAAA,EACT;AACA,QAAM,WAAW,aAAa,cAAc,QAAQ,GAAG,MAAM,MAAM,GAAG,IAAI,CAAC;AAC3E,MAAI,eAAe;AACnB,QAAM,YAAY,QAAQ,IAAI,CAAC,WAAW;AACxC,UAAM,WAAW,aAAa,cAAc,OAAO,MAAM,MAAM,IAAI,CAAC;AACpE,oBAAgB;AAChB,WAAO;AAAA,EACT,CAAC;AACD,QAAM,SAAS,QAAQ,IAAI,CAAC,WAAW,SAAS,mBAAmB,MAAM,CAAC;AAC1E,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,WAAS,IAAI,GAAG,IAAI,UAAU,KAAK;AACjC,QAAI,YAAY,IAAI;AACpB,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,YAAM,WAAW,UAAU;AAC3B,YAAM,WAAW,IAAI;AACrB,YAAM,OAAO,OAAO,IAAI,SAAS,UAAU,WAAW,QAAQ;AAC9D,cAAQ,IAAI,MAAM,SAAS;AAC3B,mBAAa;AAAA,IACf;AAAA,EACF;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,OAAO,UAAU;AACxB,eAAa,SAAS,KAAK,MAAM,QAAQ,MAAM;AAAA,IAC7C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,EAAE,SAAAY,UAAS,WAAW,KAAK,MAAM,iBAAiB,WAAW,IAAI;AACvE,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,OAAO,WAAW;AAC5I,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,YAAY,SAAS,QAAQ;AACnC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,iBAAiB,SAAS;AAChC,QAAM,YAAY,SAAS,QAAQ,SAAS,SAAS,IAAI;AACzD,MAAI,SAAS,eAAe,gBAAgB;AAC1C,UAAM,IAAI,MAAM,oDAAoD,SAAS,yCAAyC;AAAA,EACxH;AACA,QAAM,MAAM,SAAS,WAAW,SAAS,UAAU,SAAS;AAC5D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,aAAW,KAAK,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,UAAU,cAAc,aAAa,QAAQ,UAAU,WAAW,SAAS,WAAW,gBAAgB,eAAe,cAAc,aAAa,eAAe,gBAAgB,KAAK;AACxO,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,4BAA0B,SAAS,KAAK,MAAM,qBAAqB,MAAM;AAAA,IACvE;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,YAAY,iBAAiB,WAAW,IAAI;AACxE,QAAM,YAAY;AAClB,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,OAAO,WAAW;AAC/I,QAAM,EAAE,WAAW,cAAc,aAAa,YAAY,UAAU,SAAS,aAAa,WAAW,UAAU,cAAc,YAAY,IAAI;AAC7I,QAAM,SAAS,eAAe,IAAI,SAAS,QAAQ;AACnD,QAAM,UAAU,cAAc,IAAI,SAAS,QAAQ;AACnD,QAAM,iBAAiB,SAAS,eAAe;AAC/C,QAAM,YAAY,aAAa,eAAe,SAAS,OAAO;AAC9D,QAAM,YAAY,aAAa,eAAe,GAAG,KAAK;AACtD,QAAM,CAAC,OAAO,OAAO,KAAK,IAAI,aAAa,eAAe,OAAO,KAAK;AACtE,QAAM,eAAe,UAAU;AAC/B,QAAM,aAAa,iBAAiB,UAAU,KAAK,UAAU;AAC7D,QAAM,aAAa,iBAAiB,UAAU,KAAK;AACnD,QAAM,iBAAiB,iBAAiB,IAAI,UAAU;AACtD,QAAM,eAAe,UAAU;AAC/B,QAAM,aAAa,iBAAiB,UAAU,KAAK,UAAU;AAC7D,QAAM,aAAa,iBAAiB,UAAU,KAAK;AACnD,QAAM,iBAAiB,iBAAiB,IAAI,UAAU;AACtD,QAAM,MAAM,SAAS,WAAW,SAAS,SAAS,SAAS;AAC3D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,OAAO,SAAS,UAAU,IAAI,GAAG,MAAM,EAAE;AAC/C,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,0BAAwB,MAAM,UAAU,WAAW,cAAc,aAAa,UAAU,SAAS,YAAY,WAAW,UAAU,aAAa,cAAc,aAAa,QAAQ,SAAS,OAAO,OAAO,OAAO,cAAc,YAAY,YAAY,gBAAgB,cAAc,YAAY,YAAY,gBAAgB,KAAK;AACjU,SAAO;AACT;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,aAAa,wBAAwB,GAAG;AAG5C,IAAI,cAAc,wBAAwB,IAAI;AAG9C,IAAI;AAAA,CACH,SAAS,sBAAsB;AAC9B,uBAAqB,qBAAqB,cAAc,KAAK;AAC7D,uBAAqB,qBAAqB,aAAa,KAAK;AAC9D,GAAG,wBAAwB,sBAAsB,CAAC,EAAE;AACpD,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,sBAAoB,SAAS,KAAK,MAAM,eAAe,MAAM;AAAA,IAC3D;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,oBAAoB,SAAS,IAAI;AACjD,QAAM,EAAE,OAAO,QAAQ,OAAO,OAAO,IAAI;AACzC,QAAM,WAAW,MAAM,MAAM;AAC7B,QAAM,CAAC,YAAY,SAAS,IAAI;AAChC,QAAM,WAAW,CAAC,UAAU,YAAY,WAAW,OAAO,MAAM,EAAE;AAClE,MAAI,aAAa,SAAS,UAAU,IAAI,OAAO,MAAM;AACrD,MAAI;AACJ,MAAI,OAAO,UAAU,WAAW;AAC9B,iBAAa,MAAM,EAAE,SAAS,UAAU,QAAQ,EAAE,GAAG,OAAO,GAAG,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AAC5F,iBAAa,SAAS,UAAU,IAAI,WAAW,MAAM;AAAA,EACvD;AACA,QAAM,WAAW,WAAW;AAC5B,QAAM,UAAU,SAAS,UAAU,IAAI,MAAM,MAAM,EAAE;AACrD,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,MAAM,SAAS,WAAW,UAAU,SAAS;AACnD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,mBAAmB,IAAI,WAAW,IAAI,WAAW,OAAO,KAAK,EAAE,MAAM;AAC3E,oBAAkB,UAAU,SAAS,UAAU,UAAU,kBAAkB,YAAY,WAAW,oBAAoB,SAAS,oBAAoB,KAAK;AACxJ,MAAI,cAAc,MAAM;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,gBAAc,SAAS,KAAK,MAAM,SAAS,MAAM;AAAA,IAC/C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,QAAM,QAAQ,EAAE,MAAM;AACtB,eAAa,OAAO,EAAE,UAAU,aAAa,EAAE,UAAU,SAAS,MAAM,4BAA4B,EAAE,mCAAmC;AACzI,QAAM,cAAc,qBAAqB,mBAAmB,CAAC,IAAI,GAAG,KAAK;AACzE,MAAI,YAAY;AAChB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,MAAM,YAAY,GAAG,SAAS,SAAS,CAAC;AAAA,EAC3F;AACA,QAAM,eAAe,qBAAqB,iBAAiB,GAAG,KAAK,EAAE;AACrE,uBAAqB,2BAA2B,WAAW,CAAC,YAAY,GAAG,KAAK;AAChF,QAAM,cAAc,SAAS,WAAW,UAAU,OAAO,UAAU,KAAK;AACxE,QAAM,WAAW,UAAU,MAAM;AACjC,QAAM,cAAc,SAAS,UAAU,IAAI,UAAU,MAAM,EAAE;AAC7D,QAAM,gBAAgB,SAAS,UAAU,IAAI,YAAY,MAAM,EAAE;AACjE,cAAY,aAAa,YAAY,IAAI,GAAG,WAAW,IAAI,GAAG,UAAU,eAAe,SAAS,EAAE,MAAM;AACxG,MAAI,MAAM;AACV,MAAI,gBAAgB,MAAM;AACxB,UAAM,kBAAkB,qBAAqB,uBAAuB,WAAW;AAC/E,UAAM,WAAW,EAAE,QAAQ,EAAE,GAAG,YAAY,GAAG,OAAO,EAAE,MAAM,gBAAgB,GAAG,SAAS,SAAS,CAAC;AACpG,aAAS,YAAY,UAAU,MAAM;AACrC,aAAS,YAAY,YAAY,MAAM;AAAA,EACzC;AACA,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,eAAa,SAAS,KAAK,MAAM,QAAQ,MAAM;AAAA,IAC7C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,QAAM,QAAQ,EAAE,MAAM;AACtB,eAAa,OAAO,EAAE,UAAU,aAAa,EAAE,UAAU,SAAS,MAAM,2BAA2B,EAAE,mCAAmC;AACxI,QAAM,cAAc,qBAAqB,mBAAmB,CAAC,IAAI,GAAG,KAAK;AACzE,MAAI,YAAY;AAChB,MAAI,gBAAgB,MAAM;AACxB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,MAAM,YAAY,GAAG,SAAS,SAAS,CAAC;AAAA,EAC3F;AACA,QAAM,eAAe,qBAAqB,iBAAiB,GAAG,KAAK,EAAE;AACrE,uBAAqB,2BAA2B,UAAU,CAAC,YAAY,GAAG,KAAK;AAC/E,QAAM,cAAc,SAAS,WAAW,UAAU,OAAO,UAAU,KAAK;AACxE,QAAM,WAAW,UAAU,MAAM;AACjC,QAAM,cAAc,SAAS,UAAU,IAAI,UAAU,MAAM,EAAE;AAC7D,QAAM,gBAAgB,SAAS,UAAU,IAAI,YAAY,MAAM,EAAE;AACjE,aAAW,aAAa,YAAY,IAAI,GAAG,WAAW,IAAI,GAAG,UAAU,eAAe,SAAS,EAAE,MAAM;AACvG,MAAI,MAAM;AACV,MAAI,gBAAgB,MAAM;AACxB,UAAM,kBAAkB,qBAAqB,uBAAuB,WAAW;AAC/E,UAAM,WAAW,EAAE,QAAQ,EAAE,GAAG,YAAY,GAAG,OAAO,EAAE,MAAM,gBAAgB,GAAG,SAAS,SAAS,CAAC;AACpG,aAAS,YAAY,UAAU,MAAM;AACrC,aAAS,YAAY,YAAY,MAAM;AAAA,EACzC;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,qBAAmB,SAAS,KAAK,MAAM,cAAc,MAAM;AAAA,IACzD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,WAAW,WAAW,IAAI;AAClC,QAAM,YAAY,EAAE,MAAM;AAC1B,QAAM,cAAc,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AACjE,QAAM,aAAa,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AAChE,QAAM,aAAa,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AAChE,QAAM,eAAe,cAAc;AACnC,QAAM,cAAc,aAAa;AACjC,QAAM,cAAc,cAAc,YAAY;AAC9C,QAAM,cAAc,eAAe,SAAS,CAAC,WAAW,cAAc,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,cAAc,WAAW;AACpJ,QAAM,MAAM,SAAS,WAAW,aAAa,SAAS;AACtD,QAAM,QAAQ,SAAS,UAAU,IAAI,EAAE,MAAM;AAC7C,QAAM,MAAM,MAAM;AAClB,QAAM,gBAAgB,IAAI,WAAW,IAAI,WAAW,aAAa,eAAe,EAAE,KAAK,CAAC,EAAE,MAAM;AAChG,QAAM,mBAAmB,IAAI,WAAW,IAAI,WAAW,WAAW,EAAE,MAAM;AAC1E,QAAM,kBAAkB,IAAI,WAAW,IAAI,WAAW,aAAa,eAAe,WAAW,CAAC,EAAE,MAAM;AACtG,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,eAAe,eAAe,SAAS,IAAI;AACjD,mBAAiB,KAAK,WAAW,cAAc,eAAe,EAAE,MAAM,SAAS,GAAG,kBAAkB,iBAAiB,YAAY,QAAQ,KAAK;AAC9I,SAAO;AACT;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,wBAAsB,SAAS,KAAK,MAAM,uBAAuB,MAAM;AAAA,IACrE;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,iBAAiB,MAAM;AAC9B,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,EAAE,SAAAA,UAAS,WAAW,KAAK,MAAM,gBAAgB,IAAI;AAC3D,QAAM,aAAa,aAAa,OAAO,CAAC,GAAG,CAAC,IAAI;AAChD,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,YAAY,MAAM,iBAAiB,IAAI;AAC/H,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,YAAY,SAAS,QAAQ;AACnC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,iBAAiB,SAAS;AAChC,QAAM,YAAY,SAAS,QAAQ,SAAS,SAAS,IAAI;AACzD,MAAI,SAAS,eAAe,gBAAgB;AAC1C,UAAM,IAAI,MAAM,mEAAmE,SAAS,yCAAyC;AAAA,EACvI;AACA,QAAM,MAAM,SAAS,WAAW,SAAS,UAAU,SAAS;AAC5D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,sBAAoB,KAAK,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,UAAU,cAAc,aAAa,QAAQ,UAAU,WAAW,SAAS,WAAW,gBAAgB,eAAe,cAAc,aAAa,eAAe,gBAAgB,KAAK;AACjP,SAAO;AACT;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,aAAa,wBAAwB,GAAG;AAG5C,IAAI,yBAAyB;AAC7B,IAAI,eAAe,yBAAyB,OAAO,wBAAwB,MAAM;AAGjF,IAAI,aAAa,wBAAwB,KAAK,SAAS;AAGvD,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,IAAI,IAAI;AAChB,QAAM,YAAY,OAAO,MAAM;AAC/B,QAAM,WAAW,OAAO,MAAM,MAAM;AACpC,MAAI,OAAO;AACX,MAAI,MAAM,GAAG;AACX,iBAAa,OAAO,EAAE,YAAY,MAAM,KAAK,MAAM,iCAAiC,EAAE,YAAY,OAAO,YAAY;AACrH,WAAO,YAAY,MAAM;AAAA,EAC3B;AACA,WAAS,OAAO,MAAM,GAAG,CAAC;AAC1B,SAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC1F;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,OAAO,EAAE,OAAO,OAAO,MAAM,GAAG,SAAS,SAAS,IAAI;AAC9D,QAAM,MAAM,SAAS,WAAW,OAAO,KAAK;AAC5C,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,UAAQ,KAAK,KAAK;AAClB,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,sBAAoB,SAAS,KAAK,MAAM,eAAe,MAAM;AAAA,IAC3D;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,MAAM,SAAS,WAAW,OAAO,OAAO,OAAO,KAAK;AAC1D,QAAM,UAAU,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACtD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,oBAAkB,SAAS,OAAO,aAAa,YAAY,aAAa,KAAK;AAC7E,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,IAAI,eAAe,wBAAwB,KAAK;AAGhD,IAAI,yBAAyB;AAC7B,IAAI,kBAAkB,yBAAyB,UAAU,sBAAsB;AAG/E,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,kBAAgB,SAAS,KAAK,MAAM,gBAAgB,MAAM,CAAC,UAAU,UAAU,UAAU,UAAU,UAAU,UAAU,QAAQ,CAAC;AAClI;AACA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,gBAAgB,IAAI;AAC5B,QAAM,EAAE,GAAG,MAAM,OAAO,UAAU,QAAQ,OAAOS,QAAO,IAAI;AAC5D,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,SAAS,SAAS,UAAU,IAAI,MAAM,MAAM,EAAE;AACpD,QAAM,aAAa,SAAS,UAAU,IAAI,SAAS,MAAM,EAAE;AAC3D,QAAM,WAAW,UAAU,OAAO,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE,KAAK;AAC7E,QAAM,UAAUA,WAAU,OAAO,SAAS,UAAU,IAAIA,QAAO,MAAM,EAAE,KAAK;AAC5E,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,MAAI,aAAa,cAAc,EAAE,KAAK,MAAM,GAAG;AAC7C,WAAO;AAAA,EACT;AACA,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,gBAAc,KAAK,QAAQ,YAAY,UAAU,SAAS,iBAAiB,KAAK;AAChF,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,oBAAkB,SAAS,KAAK,MAAM,aAAa,MAAM;AAAA,IACvD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAT,UAAS,KAAK,MAAM,WAAW,YAAY,iBAAiB,YAAY,aAAa,eAAe,IAAI;AAChH,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,eAAe;AACxH,QAAM,kBAAkB,kBAAkB;AAC1C,MAAI,mBAAmB,MAAM;AAC3B,UAAM,IAAI,MAAM,GAAG,+EAA+E;AAAA,EACpG;AACA,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,iBAAiB,SAAS;AAChC,MAAI,SAAS;AACb,MAAI,QAAQ,MAAM;AAChB,UAAM,WAAW,SAAS,UAAU,IAAI,KAAK,MAAM;AACnD,QAAI,SAAS,MAAM,WAAW,GAAG;AAC/B,YAAM,IAAI,MAAM,sDAAsD,SAAS,MAAM,SAAS;AAAA,IAChG;AACA,QAAI,SAAS,MAAM,OAAO,gBAAgB;AACxC,YAAM,IAAI,MAAM,2BAA2B,SAAS,wDAAwD,iBAAiB;AAAA,IAC/H;AACA,aAAS,SAAS;AAAA,EACpB;AACA,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,YAAY,SAAS,QAAQ;AACnC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,YAAY,SAAS,QAAQ,SAAS,SAAS,IAAI;AACzD,QAAM,YAAY,SAAS;AAC3B,QAAM,WAAW,SAAS;AAC1B,QAAM,UAAU,SAAS;AACzB,MAAI,eAAe,QAAQ;AACzB,UAAM,IAAI,MAAM,yDAAyD,iCAAiC;AAAA,EAC5G;AACA,QAAM,MAAM,SAAS,WAAW,SAAS,UAAU,SAAS;AAC5D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,2BAA2B,0BAA0B,OAAO,IAAI,SAAS,UAAU,IAAI,uBAAuB,MAAM,EAAE;AAC5H,kBAAgB,KAAK,WAAW,UAAU,SAAS,UAAU,cAAc,aAAa,QAAQ,QAAQ,UAAU,WAAW,SAAS,WAAW,gBAAgB,eAAe,cAAc,aAAa,eAAe,gBAAgB,iBAAiB,0BAA0B,kBAAkB,GAAG,KAAK;AAC/S,SAAO;AACT;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,6BAA2B,SAAS,KAAK,MAAM,sBAAsB,MAAM;AAAA,IACzE;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,WAAW,YAAY,iBAAiB,YAAY,aAAa,eAAe,IAAI;AAChH,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,IAAI;AAC9H,QAAM,kBAAkB,kBAAkB;AAC1C,MAAI,mBAAmB,MAAM;AAC3B,UAAM,IAAI,MAAM,GAAG,wFAAwF;AAAA,EAC7G;AACA,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,iBAAiB,SAAS;AAChC,MAAI,SAAS;AACb,MAAI,QAAQ,MAAM;AAChB,UAAM,WAAW,SAAS,UAAU,IAAI,KAAK,MAAM;AACnD,QAAI,SAAS,MAAM,WAAW,GAAG;AAC/B,YAAM,IAAI,MAAM,+DAA+D,SAAS,MAAM,SAAS;AAAA,IACzG;AACA,QAAI,SAAS,MAAM,OAAO,gBAAgB;AACxC,YAAM,IAAI,MAAM,oCAAoC,SAAS,wDAAwD,iBAAiB;AAAA,IACxI;AACA,aAAS,SAAS;AAAA,EACpB;AACA,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,YAAY,SAAS,QAAQ;AACnC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,YAAY,SAAS,QAAQ,SAAS,SAAS,IAAI;AACzD,QAAM,YAAY,SAAS;AAC3B,QAAM,WAAW,SAAS;AAC1B,QAAM,UAAU,SAAS;AACzB,MAAI,eAAe,QAAQ;AACzB,UAAM,IAAI,MAAM,kEAAkE,iCAAiC;AAAA,EACrH;AACA,QAAM,MAAM,SAAS,WAAW,SAAS,UAAU,SAAS;AAC5D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,2BAA2B,0BAA0B,OAAO,IAAI,SAAS,UAAU,IAAI,uBAAuB,MAAM,EAAE;AAC5H,2BAAyB,KAAK,WAAW,UAAU,SAAS,UAAU,cAAc,aAAa,QAAQ,QAAQ,UAAU,WAAW,SAAS,WAAW,gBAAgB,eAAe,cAAc,aAAa,eAAe,gBAAgB,iBAAiB,0BAA0B,kBAAkB,GAAG,KAAK;AACxT,SAAO;AACT;AACA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,iBAAe,SAAS,KAAK,MAAM,UAAU,MAAM;AAAA,IACjD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,SAAS,UAAU,OAAO,IAAI;AACtC,QAAM,EAAE,QAAQ,QAAQ,IAAI;AAC5B,QAAM,CAAC,aAAa,WAAW,WAAWA,QAAO,IAAI,uBAAuB,mBAAmB,QAAQ,OAAO;AAC9G,QAAM,MAAM,SAAS,WAAW,aAAa,OAAO,KAAK;AACzD,MAAI,cAAc,GAAG;AACnB,WAAO;AAAA,EACT;AACA,QAAM,eAAe,QAAQ;AAC7B,QAAM,YAAY,aAAa,aAAa,SAAS;AACrD,QAAM,QAAQ,SAAS,UAAU,IAAI,OAAO,MAAM;AAClD,QAAM,MAAM,MAAM;AAClB,QAAM,cAAc,SAAS,UAAU,IAAI,QAAQ,MAAM;AACzD,QAAM,YAAY,YAAY;AAC9B,QAAM,eAAe,IAAI,WAAW,IAAI,WAAWA,QAAO,EAAE,MAAM;AAClE,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,eAAa,KAAK,SAAS,OAAO,QAAQ,WAAW,WAAW,WAAW,WAAW,cAAc,KAAK;AACzG,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,eAAa,SAAS,KAAK,MAAM,UAAU,MAAM;AAAA,IAC/C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAM,UAAU,IAAI;AAC5B,QAAM,aAAa,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AAC9D,QAAM,cAAc,SAAS,SAAS,QAAQ,MAAM;AACpD,QAAM,UAAU,EAAE,MAAM;AACxB,WAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,EAAE,IAAI;AAC9C,UAAMH,SAAQ,YAAY;AAC1B,iBAAa,OAAOA,UAAS,UAAU,KAAKA,UAAS,GAAG,MAAM,6BAA6BA,wBAAuB,UAAU,IAAI;AAAA,EAClI;AACA,QAAM,YAAY,qBAAqB,aAAa,yBAAyB,GAAG,SAAS,YAAY,SAAS;AAC9G,QAAM,WAAW,SAAS;AAAA,IACxB,QAAQ,EAAE,EAAE;AAAA,IACZ,OAAO;AAAA,MACL,OAAO;AAAA,QACL,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,MACZ;AAAA,IACF;AAAA,IACA,SAAS;AAAA,EACX,CAAC;AACD,QAAM,cAAc,aAAa,cAAc,QAAQ,KAAK;AAC5D,QAAM,eAAe,SAAS;AAAA,IAC5B,QAAQ,EAAE,GAAG,QAAQ;AAAA,IACrB,OAAO,EAAE,OAAO,CAAC,UAAU,WAAW,cAAc,UAAU,SAAS,EAAE;AAAA,IACzE,SAAS;AAAA,EACX,CAAC;AACD,QAAM,qBAAqB;AAAA,IACzB,UAAU;AAAA,IACV,UAAU;AAAA,IACV,cAAc,UAAU;AAAA,IACxB,UAAU;AAAA,EACZ;AACA,QAAM,MAAM,SAAS,WAAW,oBAAoB,EAAE,KAAK;AAC3D,MAAI,aAAa,cAAc,EAAE,KAAK,MAAM,GAAG;AAC7C,WAAO;AAAA,EACT;AACA,QAAM,cAAc,SAAS,MAAM,SAAS;AAC5C,QAAM,QAAQ,SAAS,UAAU,IAAI,SAAS,MAAM;AACpD,QAAM,MAAM,MAAM;AAClB,QAAM,cAAc,SAAS,UAAU,IAAI,aAAa,MAAM;AAC9D,QAAM,YAAY,YAAY;AAC9B,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,gBAAgB,IAAI,WAAW,IAAI,WAAW,aAAa,eAAe,SAAS,KAAK,CAAC,EAAE,MAAM;AACvG,QAAM,kBAAkB,IAAI,WAAW,IAAI,WAAW,aAAa,eAAe,kBAAkB,CAAC,EAAE,MAAM;AAC7G,aAAW,KAAK,SAAS,EAAE,QAAQ,eAAe,aAAa,WAAW,UAAU,WAAW,iBAAiB,KAAK;AACrH,WAAS,YAAY,SAAS,MAAM;AACpC,WAAS,YAAY,aAAa,MAAM;AACxC,MAAI,QAAQ,UAAU;AACtB,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,yBAAyB;AAC7B,IAAI,iBAAiB,yBAAyB,SAAS,wBAAwB,MAAM;AAGrF,IAAI,yBAAyB;AAC7B,IAAI,sBAAsB,yBAAyB,cAAc,wBAAwB,MAAM;AAG/F,IAAI;AACJ,SAAS,WAAW,UAAU;AAC5B,cAAY,SAAS,KAAK,MAAM,WAAW,MAAM;AAAA,IAC/C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,OAAAa,OAAM,GAAG,SAAS,SAAS,IAAI;AAC/D,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,SAAS;AAClD,MAAI,aAAa,cAAc,EAAE,KAAK,MAAM,GAAG;AAC7C,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,cAAU,KAAK,SAAS,EAAE,QAAQA,QAAO,KAAK;AAAA,EAChD;AACA,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,yBAAyB;AAC7B,IAAI,cAAc,yBAAyB,MAAM,wBAAwB,MAAM;AAG/E,IAAI,yBAAyB;AAC7B,IAAI,mBAAmB,yBAAyB,WAAW,wBAAwB,MAAM;AAGzF,IAAI,aAAa,wBAAwB,GAAG;AAG5C,IAAI,yBAAyB;AAC7B,IAAI,oBAAoB,yBAAyB,YAAY,wBAAwB,MAAM;AAG3F,IAAI,oBAAoB,wBAAwB,UAAU;AAG1D,IAAI,yBAAyB;AAC7B,IAAI,mBAAmB,yBAAyB,WAAW,wBAAwB,MAAM;AAGzF,IAAI,0BAA0B;AAC9B,IAAI,mBAAmB,yBAAyB,YAAY,yBAAyB,MAAM;AAG3F,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,YAAU,SAAS,KAAK,MAAM,KAAK,MAAM;AAAA,IACvC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,kBAAkB,MAAM,SAAS,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,cAAc,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AACxG,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,aAAS;AACT,cAAU;AAAA,EACZ;AACA,QAAM,YAAY,OAAO,MAAM;AAC/B,uBAAqB,2BAA2B,OAAO,MAAM,SAAS;AACtE,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,IAAI;AACjG,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,MAAM,SAAS,WAAW,UAAU,EAAE,KAAK;AACjD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,YAAQ,SAAS,SAAS,EAAE,QAAQ,YAAY,KAAK;AAAA,EACvD;AACA,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,YAAY;AAClF,QAAI,QAAQ;AAAA,EACd;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,0BAA0B;AAC9B,IAAI,iBAAiB,yBAAyB,SAAS,uBAAuB;AAG9E,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,gBAAc,SAAS,KAAK,MAAM,SAAS,MAAM;AAAA,IAC/C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,IAAI,OAAO;AACjB,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,eAAa,OAAO,EAAE,UAAU,WAAW,MAAM,0DAA0D,EAAE,QAAQ;AACrH,QAAM,EAAE,YAAY,SAAAV,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,GAAG,MAAM,eAAe;AAC9G,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,SAAS,SAAS,QAAQ;AAChC,QAAM,WAAW,SAAS,QAAQ;AAClC,QAAM,YAAY,SAAS,QAAQ;AACnC,QAAM,UAAU,SAAS,QAAQ;AACjC,QAAM,iBAAiB,SAAS;AAChC,QAAM,gBAAgB,SAAS;AAC/B,QAAM,eAAe,SAAS;AAC9B,QAAM,cAAc,SAAS;AAC7B,QAAM,gBAAgB,SAAS;AAC/B,QAAM,iBAAiB,SAAS;AAChC,MAAI,SAAS,eAAe,gBAAgB;AAC1C,UAAM,IAAI,MAAM,6CAA6C,SAAS,yCAAyC;AAAA,EACjH;AACA,QAAM,MAAM,SAAS,WAAW,SAAS,UAAU,SAAS;AAC5D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,cAAY,KAAK,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,EAAE,MAAM,IAAI,cAAc,aAAa,QAAQ,UAAU,WAAW,SAAS,gBAAgB,eAAe,cAAc,aAAa,eAAe,gBAAgB,KAAK;AACpN,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,aAAW,SAAS,KAAK,MAAM,MAAM,MAAM,CAAC,wBAAwB,CAAC;AACvE;AACA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,cAAc,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AACxG,MAAI,gBAAgB;AACpB,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAI,iBAAiB,KAAK;AACxB,eAAS;AACT,gBAAU;AACV,sBAAgB,qBAAqB,iBAAiB,cAAc,QAAQ,OAAO,MAAM,MAAM;AAAA,IACjG;AAAA,EACF;AACA,uBAAqB,2BAA2B,QAAQ,eAAe,OAAO,MAAM,MAAM;AAC1F,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,aAAa;AAC1G,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,MAAI,cAAc;AAClB,MAAI,OAAO,UAAU,WAAW;AAC9B,kBAAc,MAAM,EAAE,SAAS,UAAU,QAAQ,EAAE,GAAG,OAAO,GAAG,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AAC7F,cAAU,SAAS,UAAU,IAAI,YAAY,MAAM,EAAE;AAAA,EACvD;AACA,QAAM,MAAM,SAAS,WAAW,UAAU,SAAS;AACnD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,aAAS,SAAS,YAAY,KAAK;AAAA,EACrC;AACA,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,YAAY;AAClF,QAAI,QAAQ;AAAA,EACd;AACA,MAAI,OAAO,UAAU,WAAW;AAC9B,aAAS,YAAY,YAAY,MAAM;AAAA,EACzC;AACA,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,YAAU,SAAS,KAAK,MAAM,KAAK,MAAM;AAAA,IACvC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,cAAc,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AACxG,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAI,iBAAiB,KAAK;AACxB,eAAS;AACT,gBAAU;AAAA,IACZ;AAAA,EACF;AACA,QAAM,YAAY,OAAO,MAAM;AAC/B,uBAAqB,2BAA2B,OAAO,MAAM,SAAS;AACtE,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,IAAI;AACjG,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,MAAM,SAAS,WAAW,UAAU,OAAO,KAAK;AACtD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,YAAQ,SAAS,SAAS,EAAE,QAAQ,YAAY,KAAK;AAAA,EACvD;AACA,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,YAAY;AAClF,QAAI,QAAQ;AAAA,EACd;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,0BAA0B;AAC9B,IAAI,iBAAiB,yBAAyB,SAAS,uBAAuB;AAG9E,IAAI;AAAA,CACH,SAAS,oBAAoB;AAC5B,qBAAmB,mBAAmB,aAAa,KAAK;AACxD,qBAAmB,mBAAmB,eAAe,KAAK;AAC5D,GAAG,sBAAsB,oBAAoB,CAAC,EAAE;AAChD,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,kBAAgB,SAAS,KAAK,MAAM,WAAW,MAAM;AAAA,IACnD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,UAAU,KAAK,EAAE,IAAI;AACxE,QAAM,WAAW,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,EAAE,MAAM,MAAM,GAAG,EAAE;AACrE,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,MAAM,SAAS,WAAW,UAAU,EAAE,KAAK;AACjD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,QAAM,kBAAkB,SAAS,IAAI,CAAC,aAAa,SAAS,EAAE;AAC9D,QAAM,mBAAmB,SAAS,IAAI,CAAC,aAAa,SAAS,EAAE;AAC/D,QAAM,mBAAmB,IAAI,WAAW,IAAI,WAAW,eAAe,EAAE,MAAM;AAC9E,QAAM,oBAAoB,IAAI,WAAW,IAAI,WAAW,gBAAgB,EAAE,MAAM;AAChF,gBAAc,KAAK,aAAa,EAAE,MAAM,QAAQ,SAAS,EAAE,QAAQ,kBAAkB,mBAAmB,kBAAkB,OAAO,KAAK;AACtI,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,IAAI,0BAA0B;AAC9B,IAAI,kBAAkB,yBAAyB,UAAU,uBAAuB;AAGhF,IAAI,aAAa,wBAAwB,GAAG;AAG5C,SAAS,kBAAkB,UAAU,WAAW;AAC9C,QAAM,SAAS,IAAI,WAAW,SAAS,KAAK,OAAO,QAAQ,WAAW,CAAC;AACvE,QAAM,mBAAmB,OAAO;AAChC,QAAM,eAAe,OAAO;AAC5B,QAAM,kBAAkB,OAAO;AAC/B,QAAM,gBAAgB,OAAO;AAC7B,WAAS,KAAK,MAAM,SAAS;AAC7B,SAAO,EAAE,kBAAkB,cAAc,iBAAiB,cAAc;AAC1E;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,cAAY,SAAS,KAAK;AAAA,IACxB;AAAA,IACA;AAAA,IACA;AAAA,MACE;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,cAAc,eAAe,eAAe,IAAI;AACxD,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,UAAU,SAAS,UAAU,IAAI,MAAM,MAAM,EAAE;AACrD,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,YAAY,UAAU,SAAS,UAAU,eAAe,cAAc,cAAc;AAC1F,QAAM,EAAE,kBAAkB,cAAc,iBAAiB,cAAc,IAAI,kBAAkB,UAAU,SAAS;AAChH,WAAS,KAAK,MAAM,eAAe;AACnC,WAAS,KAAK,MAAM,aAAa;AACjC,QAAM,wBAAwB,SAAS,WAAW,CAAC,YAAY,GAAG,SAAS,gBAAgB;AAC3F,SAAO;AACT;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX;AACF;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,cAAY,SAAS,KAAK;AAAA,IACxB;AAAA,IACA;AAAA,IACA;AAAA,MACE;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,cAAc,eAAe,gBAAgB,mBAAmB,IAAI;AAC5E,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,UAAU,SAAS,UAAU,IAAI,MAAM,MAAM,EAAE;AACrD,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,YAAY,UAAU,SAAS,UAAU,eAAe,cAAc,gBAAgB,kBAAkB;AAC9G,QAAM,EAAE,kBAAkB,cAAc,iBAAiB,cAAc,IAAI,kBAAkB,UAAU,SAAS;AAChH,WAAS,KAAK,MAAM,eAAe;AACnC,QAAM,wBAAwB,SAAS,WAAW,CAAC,YAAY,GAAG,SAAS,gBAAgB;AAC3F,QAAM,qBAAqB,SAAS,WAAW,CAAC,GAAG,SAAS,aAAa;AACzE,SAAO,CAAC,uBAAuB,kBAAkB;AACnD;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,cAAY,SAAS,KAAK;AAAA,IACxB;AAAA,IACA;AAAA,IACA;AAAA,MACE;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF;AAAA,EACF;AACF;AACA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,cAAc,eAAe,gBAAgB,aAAa,IAAI;AACtE,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,UAAU,SAAS,UAAU,IAAI,MAAM,MAAM,EAAE;AACrD,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,YAAY,UAAU,SAAS,UAAU,eAAe,cAAc,gBAAgB,YAAY;AACxG,QAAM,EAAE,kBAAkB,cAAc,iBAAiB,cAAc,IAAI,kBAAkB,UAAU,SAAS;AAChH,WAAS,KAAK,MAAM,aAAa;AACjC,QAAM,wBAAwB,SAAS,WAAW,CAAC,YAAY,GAAG,SAAS,gBAAgB;AAC3F,QAAM,uBAAuB,SAAS,WAAW,CAAC,YAAY,GAAG,WAAW,eAAe;AAC3F,SAAO,CAAC,uBAAuB,oBAAoB;AACrD;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,0BAA0B;AAC9B,IAAI,kBAAkB,yBAAyB,UAAU,yBAAyB,MAAM;AAGxF,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,eAAa,SAAS,KAAK,MAAM,QAAQ,MAAM;AAAA,IAC7C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,QAAQ,IAAI;AACpB,QAAM,EAAE,OAAO,SAAS,SAAS,IAAI;AACrC,QAAM,MAAM,SAAS,WAAW,CAAC,GAAG,QAAQ,OAAO,KAAK,GAAG,OAAO;AAClE,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,cAAc,SAAS,UAAU,IAAI,QAAQ,MAAM;AACzD,QAAM,YAAY,YAAY;AAC9B,aAAW,WAAW,OAAO,SAAS,UAAU,KAAK;AACrD,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,IAAI;AAC7C,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,UAAQ,KAAK,CAAC;AACd,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,YAAY,EAAE,QAAQ,EAAE,OAAO,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAAA,EAC9F;AACA,QAAM,QAAQ,OAAO,GAAG;AACxB,QAAM,QAAQ,OAAO,GAAG;AACxB,SAAO,QAAQ,CAAC,OAAO;AACrB,iBAAa,kBAAkB,OAAO,GAAG,OAAO,uDAAuD;AACvG,iBAAa,OAAO,UAAU,GAAG,OAAO,MAAM,uDAAuD;AAAA,EACvG,CAAC;AACD,QAAM,0BAA0B,CAAC;AACjC,QAAM,kBAAkB,OAAO,IAAI,CAAC,OAAO;AACzC,UAAM,YAAY,YAAY,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAChG,4BAAwB,KAAK,SAAS;AACtC,WAAO;AAAA,EACT,CAAC;AACD,QAAM,SAAS,QAAQ,EAAE,QAAQ,iBAAiB,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AACtF,0BAAwB,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACvE,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,cAAY,SAAS,KAAK,MAAM,OAAO,MAAM;AAAA,IAC3C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,UAAU,cAAc,EAAE,IAAI;AACjF,QAAM,WAAW,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,EAAE,MAAM,MAAM,GAAG,EAAE;AACrE,MAAI,aAAa,cAAc,EAAE,KAAK,MAAM,GAAG;AAC7C,WAAO,MAAM;AAAA,MACX,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,UAAU,OAAO,eAAe,OAAO,EAAE,MAAM;AAAA,IACjE,CAAC;AAAA,EACH;AACA,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,MAAM,SAAS,WAAW,UAAU,EAAE,KAAK;AACjD,QAAM,gBAAgB,SAAS,UAAU,IAAI,IAAI,MAAM;AACvD,QAAM,QAAQ,cAAc;AAC5B,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,QAAM,kBAAkB,SAAS,IAAI,CAAC,aAAa,SAAS,EAAE;AAC9D,QAAM,mBAAmB,SAAS,IAAI,CAAC,aAAa,SAAS,EAAE;AAC/D,QAAM,mBAAmB,IAAI,WAAW,IAAI,WAAW,eAAe,EAAE,MAAM;AAC9E,QAAM,oBAAoB,IAAI,WAAW,IAAI,WAAW,gBAAgB,EAAE,MAAM;AAChF,YAAU,KAAK,aAAa,EAAE,MAAM,QAAQ,SAAS,EAAE,QAAQ,kBAAkB,mBAAmB,eAAe,KAAK;AACxH,SAAO;AACT;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,IAAI,0BAA0B;AAC9B,IAAI,aAAa,yBAAyB,KAAK,uBAAuB;AAGtE,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,cAAY,SAAS,KAAK,MAAM,OAAO,MAAM;AAAA,IAC3C;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,GAAG,OAAAU,OAAM,IAAI;AACrB,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,YAAY,SAAS,UAAU,IAAIA,OAAM,MAAM,EAAE;AACvD,MAAI,UAAU;AACd,QAAM,SAAS;AACf,MAAI,cAAc;AAClB,MAAI,OAAO,UAAU,WAAW;AAC9B,kBAAc,MAAM,EAAE,SAAS,UAAU,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AACrF,cAAU,SAAS,UAAU,IAAI,YAAY,MAAM,EAAE;AAAA,EACvD;AACA,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,SAAS;AAClD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,YAAU,SAAS,WAAW,KAAK;AACnC,MAAI,OAAO,UAAU,WAAW;AAC9B,aAAS,YAAY,YAAY,MAAM;AAAA,EACzC;AACA,SAAO;AACT;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,aAAW,SAAS,KAAK,MAAM,MAAM,MAAM;AAAA,IACzC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,cAAc,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AACxG,MAAI,gBAAgB;AACpB,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAI,iBAAiB,KAAK;AACxB,eAAS;AACT,gBAAU;AACV,sBAAgB,qBAAqB,iBAAiB,cAAc,QAAQ,OAAO,MAAM,MAAM;AAAA,IACjG;AAAA,EACF;AACA,uBAAqB,2BAA2B,QAAQ,eAAe,OAAO,MAAM,MAAM;AAC1F,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,aAAa;AAC1G,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,MAAM,SAAS,WAAW,UAAU,OAAO,KAAK;AACtD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,aAAS,SAAS,YAAY,SAAS,IAAI,QAAQ,KAAK;AAAA,EAC1D;AACA,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,YAAY;AAClF,QAAI,QAAQ;AAAA,EACd;AACA,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,SAAS,CAAC,SAAS;AACrB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,MAAM,OAAO,MAAM,IAAI;AAC5C,QAAM,SAAS,UAAU,OAAO,MAAM,OAAO,KAAK;AAClD,QAAM,MAAM,SAAS,WAAW,CAAC,OAAO,MAAM,GAAG,KAAK;AACtD,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,UAAQ,IAAI,MAAM;AAClB,SAAO;AACT;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,0BAA0B;AAC9B,IAAI,iBAAiB,yBAAyB,SAAS,uBAAuB;AAG9E,IAAI,cAAc,wBAAwB,IAAI;AAG9C,IAAI,eAAe,wBAAwB,KAAK;AAGhD,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,uBAAqB,SAAS,KAAK,MAAM,gBAAgB,MAAM;AAAA,IAC7D;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,kBAAkB,MAAAtB,MAAK,IAAI;AACjD,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,CAAC,OAAO,WAAW,UAAU,WAAW,IAAI,OAAO;AACzD,QAAM,WAAW,CAAC,OAAO,WAAW,UAAU,WAAW;AACzD,MAAI,QAAQ,SAAS,UAAU,IAAI,OAAO,MAAM;AAChD,MAAI;AACJ,MAAI,MAAM,UAAU,WAAW;AAC7B,iBAAa,MAAM,EAAE,SAAS,UAAU,QAAQ,EAAE,GAAG,OAAO,GAAG,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AAC5F,YAAQ,SAAS,UAAU,IAAI,WAAW,MAAM;AAAA,EAClD;AACA,QAAM,MAAM,MAAM;AAClB,QAAM,MAAM,SAAS,WAAW,UAAU,SAAS;AACnD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,WAAO;AAAA,EACT;AACA,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,qBAAmB,KAAK,OAAO,WAAW,UAAU,aAAa,WAAW,UAAU,eAAe,IAAI,GAAG,mBAAmB,IAAI,GAAG,KAAK;AAC3I,MAAI,cAAc,MAAM;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,SAAO;AACT;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,8BAA4B,SAAS,KAAK,MAAM,uBAAuB,MAAM;AAAA,IAC3E;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,uBAAuB,MAAM;AACpC,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,kBAAkB,MAAAA,MAAK,IAAI;AACjD,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,CAAC,OAAO,WAAW,UAAU,WAAW,IAAI,OAAO;AACzD,QAAM,WAAW,CAAC,OAAO,WAAW,UAAU,WAAW;AACzD,QAAM,MAAM,SAAS,WAAW,UAAU,SAAS;AACnD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,WAAO;AAAA,EACT;AACA,MAAI,QAAQ,SAAS,UAAU,IAAI,OAAO,MAAM;AAChD,MAAI;AACJ,MAAI,MAAM,UAAU,WAAW;AAC7B,iBAAa,MAAM;AAAA,MACjB,SAAS;AAAA,MACT,QAAQ,EAAE,GAAG,OAAO;AAAA,MACpB,OAAO,EAAE,OAAO,UAAU;AAAA,IAC5B,CAAC;AACD,YAAQ,SAAS,UAAU,IAAI,WAAW,MAAM;AAAA,EAClD;AACA,QAAM,MAAM,MAAM;AAClB,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,4BAA0B,KAAK,OAAO,WAAW,UAAU,aAAa,WAAW,UAAU,eAAe,IAAI,GAAG,mBAAmB,IAAI,GAAG,KAAK;AAClJ,MAAI,cAAc,MAAM;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,SAAO;AACT;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,gBAAc,SAAS,KAAK,MAAM,SAAS,MAAM;AAAA,IAC/C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACtD,MAAI,EAAE,MAAM,WAAW,GAAG;AACxB,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD;AACA,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,YAAY,IAAI,WAAW,IAAI,WAAW,IAAI,EAAE,MAAM;AAC5D,QAAM,gBAAgB,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACnE,cAAY,KAAK,WAAW,KAAK,QAAQ,eAAe,EAAE,MAAM,QAAQ,KAAK;AAC7E,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,OAAO,EAAE,OAAO,EAAE,MAAM,GAAG,SAAS,SAAS,CAAC;AAC9F,WAAS,YAAY,IAAI,MAAM;AAC/B,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,eAAa,SAAS,KAAK,MAAM,kBAAkB,MAAM;AAAA,IACvD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,kBAAkB,MAAM;AAC/B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,SAAS,WAAW,OAAO,IAAI;AACvC,QAAM,MAAM,SAAS,WAAW,OAAO,OAAO,OAAO,KAAK;AAC1D,QAAM,UAAU,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACtD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,QAAM,CAAC,SAAS,OAAO,IAAI,qBAAqB,eAAe,QAAQ,aAAa,UAAU;AAC9F,QAAM,cAAc,cAAc;AAClC,QAAM,mBAAmB;AACzB,QAAM,cAAc,OAAO,cAAc,WAAW,CAAC,WAAW,WAAW,WAAW,cAAc,IAAI,gBAAgB,IAAI,CAAC,GAAG,WAAW,gBAAgB;AAC3J,QAAM,YAAY,IAAI,WAAW,IAAI,WAAW,WAAW,EAAE,MAAM;AACnE,aAAW,SAAS,OAAO,aAAa,YAAY,aAAa,SAAS,SAAS,SAAS,WAAW,YAAY,QAAQ,KAAK;AAChI,SAAO;AACT;AACA,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,IAAI,eAAe,wBAAwB,KAAK;AAGhD,IAAI,eAAe,wBAAwB,KAAK;AAGhD,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,kBAAgB,SAAS,KAAK,MAAM,WAAW,MAAM;AAAA,IACnD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,SAAS,QAAQ,IAAI;AAC7B,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,MAAM,SAAS,WAAW,OAAO,QAAQ,KAAK;AACpD,MAAI,aAAa,cAAc,KAAK,MAAM,GAAG;AAC3C,WAAO;AAAA,EACT;AACA,QAAM,EAAE,WAAW,YAAY,WAAW,SAAAY,UAAS,YAAAQ,YAAW,IAAI,wBAAwB,gBAAgB,SAAS,SAAS,KAAK;AACjI,QAAM,cAAc,SAAS,UAAU,IAAI,QAAQ,MAAM;AACzD,QAAM,YAAY,YAAY;AAC9B,QAAM,cAAc,SAAS,UAAU,IAAI,QAAQ,MAAM;AACzD,QAAM,YAAY,YAAY;AAC9B,QAAM,eAAe,IAAI,WAAW,IAAI,WAAWR,QAAO,EAAE,MAAM;AAClE,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,gBAAc,WAAW,WAAW,SAAS,QAAQ,QAAQ,WAAW,YAAY,WAAW,cAAcQ,aAAY,KAAK;AAC9H,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,eAAa,SAAS,KAAK,MAAM,YAAY,MAAM;AAAA,IACjD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,WAAW,GAAG,IAAI,GAAG,GAAG,IAAI;AACpC,QAAM,cAAc,SAAS,UAAU,IAAI,UAAU,MAAM,EAAE;AAC7D,QAAM,MAAM,SAAS,UAAU,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,MAAM,SAAS,UAAU,IAAI,GAAG,MAAM,EAAE;AAC9C,QAAM,MAAM,SAAS,WAAW,GAAG,OAAO,GAAG,KAAK;AAClD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,QAAQ,UAAU,MAAM;AAC9B,QAAM,QAAQ,GAAG,MAAM;AACvB,QAAM,SAAS,UAAU,KAAK,QAAQ,KAAK,UAAU,IAAI,IAAI,aAAa,cAAc,GAAG,MAAM,MAAM,CAAC,CAAC;AACzG,aAAW,aAAa,KAAK,KAAK,QAAQ,KAAK;AAC/C,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AAAA,EACZ,WAAW;AACb;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,cAAY,SAAS,KAAK,MAAM,SAAS,MAAM,CAAC,UAAU,QAAQ,CAAC;AACrE;AACA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,SAAS,UAAU,QAAQ,EAAE,EAAE,EAAE,IAAI;AAC7C,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,MAAI,aAAa,cAAc,IAAI,KAAK,MAAM,GAAG;AAC/C,WAAO;AAAA,EACT;AACA,YAAU,KAAK,KAAK;AACpB,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,aAAa,wBAAwB,GAAG;AAG5C,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,cAAY,SAAS,KAAK,MAAM,SAAS,MAAM;AAAA,IAC7C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,SAAS,UAAU,QAAQ,EAAE,OAAO,GAAG,OAAO,EAAE,IAAI,EAAE,IAAI;AAClE,QAAM,MAAM,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AAClD,QAAM,MAAM,SAAS,WAAW,OAAO,OAAO,OAAO,KAAK;AAC1D,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,WAAW,OAAO,MAAM;AAC9B,QAAM,QAAQ,aAAa,cAAc,OAAO,KAAK,IAAI;AACzD,MAAI,aAAa,cAAc,IAAI,KAAK,MAAM,GAAG;AAC/C,WAAO;AAAA,EACT;AACA,YAAU,KAAK,OAAO,UAAU,KAAK;AACrC,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAS,IAAI;AACjC,QAAM,QAAQ,aAAa,cAAc,UAAU;AACnD,QAAM,mBAAmB,CAAC,CAAC,GAAG,CAAC,CAAC;AAChC,mBAAiB,KAAK,GAAG,QAAQ;AACjC,WAAS,KAAK,IAAI,WAAW,QAAQ,KAAK,EAAE,MAAM,QAAQ,EAAE,IAAI;AAC9D,qBAAiB,KAAK,CAAC,GAAG,CAAC,CAAC;AAAA,EAC9B;AACA,QAAM,UAAU,aAAa,WAAW;AAAA,IACtC,QAAQ,EAAE,EAAE;AAAA,IACZ,SAAS;AAAA,IACT,OAAO,EAAE,UAAU,kBAAkB,eAAe,EAAE;AAAA,EACxD,CAAC;AACD,QAAM,sBAAsB,qBAAqB,YAAY,QAAQ,OAAO,YAAY,OAAO,KAAK;AACpG,QAAM,oCAAoC,qBAAqB,YAAY,oBAAoB,QAAQ,WAAW,QAAQ,KAAK;AAC/H,QAAM,eAAe,qBAAqB,oBAAoB,QAAQ,OAAO,YAAY,OAAO,KAAK;AACrG,QAAM,gBAAgB,EAAE,GAAG,QAAQ;AACnC,QAAM,eAAe,EAAE,OAAO,oBAAoB;AAClD,QAAM,kBAAkB,SAAS,EAAE,QAAQ,eAAe,SAAS,UAAU,OAAO,aAAa,CAAC;AAClG,QAAM,kBAAkB,EAAE,GAAG,gBAAgB;AAC7C,QAAM,iBAAiB,EAAE,MAAM,kCAAkC;AACjE,QAAM,WAAW,WAAW,EAAE,QAAQ,iBAAiB,SAAS,UAAU,OAAO,eAAe,CAAC;AACjG,QAAM,sBAAsB,EAAE,GAAG,SAAS;AAC1C,QAAM,qBAAqB,EAAE,OAAO,aAAa;AACjD,QAAM,SAAS,SAAS,EAAE,QAAQ,qBAAqB,SAAS,UAAU,OAAO,mBAAmB,CAAC;AACrG,WAAS,YAAY,QAAQ,MAAM;AACnC,WAAS,YAAY,gBAAgB,MAAM;AAC3C,WAAS,YAAY,SAAS,MAAM;AACpC,SAAO;AACT;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,4BAA0B,SAAS,KAAK,MAAM,uBAAuB,UAAU;AAAA,IAC7E;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,SAAS,UAAU,OAAO,IAAI;AACtC,QAAM,EAAE,SAAS,QAAQ,YAAY,aAAa,IAAI;AACtD,QAAM,eAAe,QAAQ,MAAM;AACnC,QAAM,OAAO,QAAQ,MAAM;AAC3B,QAAM,YAAY,SAAS,SAAS,WAAW,MAAM,EAAE;AACvD,QAAM,wBAAwB,CAAC,eAAe,WAAW,IAAI;AAC7D,QAAM,YAAY,SAAS,UAAU,IAAI,QAAQ,MAAM,EAAE;AACzD,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,iBAAiB,SAAS,UAAU,IAAI,aAAa,MAAM,EAAE;AACnE,QAAM,gBAAgB,SAAS,WAAW,uBAAuB,QAAQ,KAAK;AAC9E,QAAM,kBAAkB,SAAS,UAAU,IAAI,cAAc,MAAM,EAAE;AACrE,QAAM,eAAe,SAAS,WAAW,sBAAsB,MAAM,GAAG,CAAC,GAAG,OAAO,KAAK;AACxF,QAAM,iBAAiB,SAAS,UAAU,IAAI,aAAa,MAAM,EAAE;AACnE,QAAM,oBAAoB,SAAS,WAAW,CAAC,SAAS,GAAG,MAAM;AACjE,QAAM,sBAAsB,SAAS,UAAU,IAAI,kBAAkB,MAAM,EAAE;AAC7E,QAAM,kBAAkB,SAAS,WAAW,CAAC,YAAY,GAAG,QAAQ,KAAK;AACzE,QAAM,oBAAoB,SAAS,UAAU,IAAI,gBAAgB,MAAM,EAAE;AACzE,QAAM,kBAAkB,SAAS,WAAW,CAAC,CAAC,GAAG,OAAO;AACxD,QAAM,oBAAoB,SAAS,UAAU,IAAI,gBAAgB,MAAM,EAAE;AACzE,QAAM,aAAa,wBAAwB,WAAW,UAAU,SAAS,OAAO,QAAQ,cAAc,WAAW,MAAM,gBAAgB,iBAAiB,gBAAgB,qBAAqB,mBAAmB,iBAAiB;AACjO,QAAM,uBAAuB,SAAS,SAAS,gBAAgB,MAAM;AACrE,MAAI;AACJ,UAAQ,qBAAqB;AAAA,SACtB,GAAG;AACN,yBAAmB,qBAAqB,gDAAgD,qBAAqB,EAAE;AAC/G;AAAA,IACF;AAAA,SACK,GAAG;AACN,yBAAmB,qBAAqB,gDAAgD,qBAAqB,IAAI,qBAAqB,EAAE;AACxI;AAAA,IACF;AAAA,SACK;AACH,yBAAmB,qBAAqB,kDAAkD,qBAAqB,IAAI,qBAAqB,IAAI,qBAAqB,EAAE;AACnK;AAAA;AAEA,yBAAmB;AAAA;AAEvB,WAAS,YAAY,gBAAgB,MAAM;AAC3C,MAAI,kBAAkB;AACpB,aAAS,YAAY,cAAc,MAAM;AACzC,aAAS,YAAY,aAAa,MAAM;AACxC,aAAS,YAAY,kBAAkB,MAAM;AAC7C,aAAS,YAAY,gBAAgB,MAAM;AAC3C,UAAM,IAAI,MAAM,gBAAgB;AAAA,EAClC;AACA,MAAI,iBAAiB;AACrB,MAAI,gBAAgB;AACpB,MAAI,eAAe,sBAAsB,IAAI;AAC3C,qBAAiB,OAAO;AAAA,MACtB,QAAQ,EAAE,GAAG,cAAc;AAAA,MAC3B,OAAO,EAAE,OAAO,GAAG,MAAM,CAAC,YAAY,IAAI,EAAE;AAAA,MAC5C,SAAS;AAAA,IACX,CAAC;AACD,oBAAgB,OAAO;AAAA,MACrB,QAAQ,EAAE,GAAG,aAAa;AAAA,MAC1B,OAAO,EAAE,OAAO,GAAG,MAAM,WAAW;AAAA,MACpC,SAAS;AAAA,IACX,CAAC;AACD,aAAS,YAAY,cAAc,MAAM;AACzC,aAAS,YAAY,aAAa,MAAM;AAAA,EAC1C;AACA,SAAO,CAAC,gBAAgB,eAAe,mBAAmB,eAAe;AAC3E;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,sBAAoB,SAAS,KAAK,MAAM,eAAe,MAAM;AAAA,IAC3D;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,SAAS,UAAU,OAAO,IAAI;AACtC,QAAM,EAAE,cAAc,YAAY,SAAS,IAAI;AAC/C,MAAI,aAAa,MAAM,WAAW,GAAG;AACnC,UAAM,IAAI,MAAM;AAAA,UACV,aAAa,OAAO;AAAA,EAC5B;AACA,MAAI,WAAW,MAAM,WAAW,GAAG;AACjC,UAAM,IAAI,MAAM;AAAA,UACV,WAAW,OAAO;AAAA,EAC1B;AACA,MAAI,SAAS,MAAM,WAAW,GAAG;AAC/B,UAAM,IAAI,MAAM,sDAAsD,SAAS,OAAO;AAAA,EACxF;AACA,QAAM,iBAAiB,SAAS,UAAU,IAAI,aAAa,MAAM,EAAE;AACnE,QAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAM,aAAa,SAAS,UAAU,IAAI,SAAS,MAAM,EAAE;AAC3D,QAAM,MAAM,aAAa,MAAM;AAC/B,QAAM,aAAa,aAAa,cAAc,SAAS,KAAK;AAC5D,QAAM,aAAa,SAAS,WAAW,CAAC,KAAK,UAAU,GAAG,aAAa,KAAK;AAC5E,QAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAM,cAAc,SAAS,WAAW,CAAC,UAAU,GAAG,SAAS,KAAK;AACpE,QAAM,gBAAgB,SAAS,UAAU,IAAI,YAAY,MAAM,EAAE;AACjE,QAAM,kBAAkB,SAAS,WAAW,CAAC,CAAC,GAAG,OAAO;AACxD,QAAM,oBAAoB,SAAS,UAAU,IAAI,gBAAgB,MAAM,EAAE;AACzE,oBAAkB,gBAAgB,cAAc,YAAY,KAAK,cAAc,eAAe,iBAAiB;AAC/G,QAAM,uBAAuB,SAAS,SAAS,gBAAgB,MAAM;AACrE,MAAI;AACJ,UAAQ,qBAAqB;AAAA,SACtB,GAAG;AACN,yBAAmB,qBAAqB,yDAAyD,qBAAqB,IAAI,qBAAqB,EAAE;AACjJ;AAAA,IACF;AAAA,SACK,GAAG;AACN,yBAAmB,qBAAqB,8CAA8C,qBAAqB,IAAI,qBAAqB,EAAE;AACtI;AAAA,IACF;AAAA,SACK;AACH,yBAAmB,qBAAqB,qDAAqD;AAC7F;AAAA,SACG,GAAG;AACN,YAAM,mBAAmB,MAAM,KAAK,SAAS,SAAS,WAAW,MAAM,CAAC,GAAG,oBAAoB,MAAM,KAAK,SAAS,SAAS,YAAY,MAAM,CAAC;AAC/I,yBAAmB,qBAAqB,gDAAgD,kBAAkB,iBAAiB;AAC3H;AAAA,IACF;AAAA,SACK,GAAG;AACN,YAAM,mBAAmB,MAAM,KAAK,SAAS,SAAS,WAAW,MAAM,CAAC,GAAG,oBAAoB,MAAM,KAAK,SAAS,SAAS,YAAY,MAAM,CAAC;AAC/I,yBAAmB,qBAAqB,gDAAgD,kBAAkB,iBAAiB;AAC3H;AAAA,IACF;AAAA;AAEE,yBAAmB;AAAA;AAEvB,WAAS,YAAY,gBAAgB,MAAM;AAC3C,MAAI,kBAAkB;AACpB,aAAS,YAAY,WAAW,MAAM;AACtC,aAAS,YAAY,YAAY,MAAM;AACvC,UAAM,IAAI,MAAM,gBAAgB;AAAA,EAClC;AACA,SAAO,CAAC,YAAY,WAAW;AACjC;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,+BAA6B,SAAS,KAAK,MAAM,0BAA0B,MAAM;AAAA,IAC/E;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,uBAAuB,MAAM,QAAQ;AAC5C,QAAM,EAAE,SAAS,UAAU,OAAO,IAAI;AACtC,QAAM,EAAE,MAAM,SAAS,WAAW,IAAI;AACtC,QAAM,aAAa,QAAQ,MAAM;AACjC,QAAM,iBAAiB,SAAS,SAAS,WAAW,QAAQ,aAAa,GAAG,UAAU,EAAE;AACxF,QAAM,uBAAuB,aAAa,IAAI,iBAAiB,IAAI;AACnE,QAAM,aAAa;AACnB,MAAI,aAAa,GAAG;AAClB,UAAM,IAAI,MAAM,qBAAqB,wDAAwD,CAAC;AAAA,EAChG;AACA,QAAM,cAAc,KAAK,MAAM,MAAM;AACrC,cAAY,KAAK;AACjB,QAAM,SAAS,SAAS,UAAU,IAAI,KAAK,MAAM,EAAE;AACnD,QAAM,YAAY,SAAS,UAAU,IAAI,QAAQ,MAAM,EAAE;AACzD,QAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAM,SAAS,SAAS,WAAW,aAAa,KAAK,KAAK;AAC1D,QAAM,WAAW,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACvD,QAAM,kBAAkB,SAAS,WAAW,CAAC,CAAC,GAAG,OAAO;AACxD,QAAM,oBAAoB,SAAS,UAAU,IAAI,gBAAgB,MAAM,EAAE;AACzE,6BAA2B,QAAQ,SAAS,KAAK,QAAQ,KAAK,MAAM,IAAI,WAAW,cAAc,UAAU,mBAAmB,QAAQ,CAAC;AACvI,QAAM,uBAAuB,SAAS,SAAS,gBAAgB,MAAM;AACrE,MAAI;AACJ,UAAQ,qBAAqB;AAAA,SACtB,GAAG;AACN,yBAAmB,qBAAqB,wDAAwD;AAChG;AAAA,IACF;AAAA,SACK,GAAG;AACN,yBAAmB,qBAAqB,6DAA6D;AACrG;AAAA,IACF;AAAA,SACK;AACH,yBAAmB,qBAAqB,yDAAyD,qBAAqB,IAAI,qBAAqB,EAAE;AACjJ;AAAA,SACG;AACH,yBAAmB,qBAAqB,uDAAuD,qBAAqB,IAAI,qBAAqB,IAAI,qBAAqB,EAAE;AACxK;AAAA;AAEA,yBAAmB;AAAA;AAEvB,WAAS,YAAY,gBAAgB,MAAM;AAC3C,MAAI,kBAAkB;AACpB,aAAS,YAAY,OAAO,MAAM;AAClC,UAAM,IAAI,MAAM,gBAAgB;AAAA,EAClC;AACA,SAAO;AACT;AAGA,SAAS,mBAAmB,MAAM;AAChC,SAAO,uBAAuB,MAAM,IAAI;AAC1C;AACA,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,kBAAkB,MAAM;AAC/B,SAAO,uBAAuB,MAAM,KAAK;AAC3C;AACA,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,iBAAiB,KAAK,IAAI;AAClC,QAAM,QAAQ,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AACzD,QAAM,aAAa,qBAAqB,iBAAiB,GAAG,iBAAiB,KAAK;AAClF,QAAM,QAAQ,IAAI,MAAM,EAAE,MAAM,MAAM,EAAE,KAAK,CAAC;AAC9C,QAAMpB,QAAO,EAAE,MAAM,MAAM;AAC3B,SAAO,WAAW,IAAI,CAAC,OAAO;AAC5B,UAAM,aAAa,CAAC,GAAGA,KAAI;AAC3B,eAAW,SAAS;AACpB,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,OAAO,MAAM,WAAW,GAAG,SAAS,SAAS,CAAC;AAC9F,UAAM,UAAU;AAChB,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,wBAAwB,IAAI;AAG9C,IAAI,gBAAgB,wBAAwB,MAAM;AAGlD,IAAI,0BAA0B;AAC9B,IAAI,2BAA2B,yBAAyB,mBAAmB,uBAAuB;AAGlG,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,aAAW,SAAS,KAAK,MAAM,MAAM,MAAM;AAAA,IACzC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAAsB,OAAM,IAAI;AAClB,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,WAAS,KAAKA,QAAO,SAAS,EAAE,QAAQ,KAAK;AAC7C,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,qBAAmB,SAAS,KAAK,MAAM,cAAc,MAAM;AAAA,IACzD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAO,KAAK,SAAAV,UAAS,WAAW,SAAS,cAAc,aAAa,eAAe,IAAI;AAC/F,QAAM,EAAE,kBAAkB,YAAY,YAAY,WAAW,eAAe,OAAO,QAAQ,KAAK,MAAM,SAAS,SAAS,IAAI,mBAAmB,UAAU,EAAE,OAAO,OAAO,KAAKA,UAAS,WAAW,SAAS,cAAc,aAAa,cAAc;AACpP,MAAI;AACJ,MAAI,YAAY;AACd,aAAS,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAAA,EACtF,WAAW,aAAa,eAAe;AACrC,iBAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,yCAAyC,EAAE,MAAM,QAAQ;AACxG,UAAMZ,QAAO,mBAAmB,gBAAgB,QAAQ,MAAM,QAAQ;AACtE,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,QAAQ,MAAAA,MAAK,EAAE,CAAC;AAC1F,aAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAC5F,aAAS,YAAY,OAAO,MAAM;AAAA,EACpC,OAAO;AACL,UAAM,MAAM,SAAS,WAAW,kBAAkB,SAAS;AAC3D,UAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,UAAM,gBAAgB,IAAI,WAAW,IAAI,WAAW,aAAa,eAAe,EAAE,KAAK,CAAC,EAAE,MAAM;AAChG,UAAM,aAAa,IAAI,WAAW,IAAI,WAAW,MAAM,EAAE,MAAM;AAC/D,UAAM,WAAW,IAAI,WAAW,IAAI,WAAW,IAAI,EAAE,MAAM;AAC3D,UAAM,eAAe,IAAI,WAAW,IAAI,WAAW,QAAQ,EAAE,MAAM;AACnE,UAAM,mBAAmB,IAAI,WAAW,IAAI,WAAW,gBAAgB,EAAE,MAAM;AAC/E,UAAM,kBAAkB,IAAI,WAAW,IAAI,WAAW,aAAa,eAAe,gBAAgB,CAAC,EAAE,MAAM;AAC3G,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,qBAAiB,KAAK,eAAe,EAAE,MAAM,QAAQ,YAAY,UAAU,cAAc,kBAAkB,iBAAiB,iBAAiB,QAAQ,KAAK;AAC1J,aAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AACzF,aAAS,YAAY,IAAI,MAAM;AAAA,EACjC;AACA,SAAO;AACT;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,WAAW,IAAI;AAC7B,QAAM,EAAE,WAAW,aAAa,SAAS,UAAU,WAAW,UAAU,uBAAuB,IAAI;AACnG,QAAM,QAAQ,SAAS,SAAS,KAAK,MAAM;AAC3C,QAAM,cAAc,SAAS,SAAS,WAAW,MAAM;AACvD,QAAM,CAAC,QAAQ,YAAY,IAAI,iBAAiB,OAAO,aAAa,WAAW,aAAa,SAAS,WAAW,UAAU,sBAAsB;AAChJ,QAAM,YAAY,SAAS,WAAW,CAAC,OAAO,MAAM,GAAG,QAAQ;AAC/D,QAAM,gBAAgB,SAAS,UAAU,IAAI,UAAU,MAAM;AAC7D,gBAAc,cAAc;AAC5B,QAAM,kBAAkB,SAAS,WAAW,WAAW,OAAO,OAAO;AACrE,QAAM,sBAAsB,SAAS,mBAAmB,eAAe;AACvE,sBAAoB,IAAI,YAAY;AACpC,SAAO,CAAC,WAAW,eAAe;AACpC;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,UAAU,IAAI;AACrC,QAAM,EAAE,UAAU,IAAI;AACtB,QAAM,YAAY,SAAS,SAAS,OAAO,MAAM;AACjD,QAAM,gBAAgB,SAAS,SAAS,UAAU,MAAM;AACxD,QAAM,CAAC,SAAS,QAAQ,KAAK,IAAI,gBAAgB,WAAW,cAAc,IAAI,SAAS;AACvF,QAAMoB,cAAa,OAAO;AAC1B,QAAM,aAAa,SAAS,WAAW,CAACA,aAAY,CAAC,GAAG,OAAO;AAC/D,QAAM,iBAAiB,SAAS,mBAAmB,UAAU;AAC7D,iBAAe,IAAI,OAAO;AAC1B,QAAM,YAAY,SAAS,WAAW,CAACA,WAAU,GAAG,QAAQ;AAC5D,QAAM,gBAAgB,SAAS,UAAU,IAAI,UAAU,MAAM;AAC7D,gBAAc,cAAc;AAC5B,QAAM,WAAW,SAAS,WAAW,CAAC,CAAC,GAAG,OAAO;AACjD,QAAM,eAAe,SAAS,mBAAmB,QAAQ;AACzD,eAAa,IAAI,KAAK;AACtB,SAAO,CAAC,YAAY,WAAW,QAAQ;AACzC;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,wBAAwB,MAAM;AACrC,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,WAAW,IAAI;AACvB,QAAM,YAAY,SAAS,SAAS,OAAO,MAAM;AACjD,QAAM,SAAS,2BAA2B,WAAW,UAAU;AAC/D,QAAM,MAAM,SAAS,WAAW,OAAO,OAAO,OAAO;AACrD,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,UAAQ,IAAI,MAAM;AAClB,SAAO;AACT;AACA,IAAI,gCAAgC;AAAA,EAClC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,0BAA0B;AAC9B,IAAI,aAAa,yBAAyB,KAAK,uBAAuB;AAGtE,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,YAAU,SAAS,KAAK,MAAM,KAAK,MAAM;AAAA,IACvC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,MAAI,UAAU;AACd,MAAI,SAAS;AACb,QAAM,EAAE,YAAY,MAAM,cAAc,mBAAmB,IAAI,wBAAwB,GAAG,MAAM,QAAQ;AACxG,MAAI,gBAAgB;AACpB,MAAI,oBAAoB;AACtB,UAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,QAAI,iBAAiB,KAAK;AACxB,eAAS;AACT,gBAAU;AACV,sBAAgB,qBAAqB,iBAAiB,cAAc,QAAQ,OAAO,MAAM,MAAM;AAAA,IACjG;AAAA,EACF;AACA,uBAAqB,2BAA2B,OAAO,eAAe,OAAO,MAAM,MAAM;AACzF,QAAM,CAAC,UAAU,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,aAAa;AAC1G,QAAM,aAAa,aAAa,cAAc,WAAW;AACzD,QAAM,MAAM,SAAS,WAAW,UAAU,OAAO,KAAK;AACtD,MAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,UAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,YAAQ,SAAS,YAAY,SAAS,IAAI,QAAQ,KAAK;AAAA,EACzD;AACA,MAAI,oBAAoB;AACtB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,UAAU;AACZ,UAAM,WAAW,qBAAqB,qBAAqB,IAAI,OAAO,YAAY;AAClF,QAAI,QAAQ;AAAA,EACd;AACA,SAAO;AACT;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI,aAAa,wBAAwB,GAAG;AAG5C,IAAI,cAAc,wBAAwB,IAAI;AAG9C,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,aAAW,SAAS,KAAK,MAAM,MAAM,MAAM;AAAA,IACzC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,WAAW,IAAI,MAAM,EAAE,MAAM,MAAM;AACzC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,aAAS,MAAM,EAAE,MAAM,MAAM,KAAK;AAAA,EACpC;AACA,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,QAAM,gBAAgB,IAAI,WAAW,IAAI,WAAW,QAAQ,EAAE,MAAM;AACpE,QAAM,MAAM,SAAS,WAAW,UAAU,EAAE,KAAK;AACjD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,WAAS,KAAK,aAAa,EAAE,MAAM,QAAQ,eAAe,SAAS,QAAQ,SAAS,IAAI,QAAQ,KAAK;AACrG,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,aAAW,SAAS,KAAK,MAAM,MAAM,MAAM;AAAA,IACzC;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,IAAI,QAAQ,CAAC,EAAE,QAAQ,SAAS,UAAU,MAAM,MAAM;AACpD,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,MAAM,SAAS,UAAU,IAAI,EAAE,MAAM,EAAE;AAC7C,QAAM,cAAc,IAAI,WAAW,IAAI,WAAW,EAAE,KAAK,EAAE,MAAM;AACjE,QAAM,cAAc,EAAE,MAAM,MAAM;AAClC,cAAY,YAAY,SAAS,KAAK;AACtC,QAAM,YAAY,SAAS,WAAW,aAAa,EAAE,KAAK;AAC1D,QAAM,cAAc,SAAS,UAAU,IAAI,UAAU,MAAM,EAAE;AAC7D,QAAM,aAAa,SAAS,WAAW,aAAa,OAAO;AAC3D,QAAM,eAAe,SAAS,UAAU,IAAI,WAAW,MAAM,EAAE;AAC/D,WAAS,KAAK,aAAa,EAAE,MAAM,QAAQ,SAAS,EAAE,QAAQ,GAAG,QAAQ,aAAa,YAAY;AAClG,SAAO,CAAC,WAAW,UAAU;AAC/B;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,IAAI;AACJ,SAAS,QAAQ,UAAU;AACzB,kBAAgB,SAAS,KAAK,MAAM,WAAW,MAAM;AAAA,IACnD;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC;AACH;AACA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,SAAS,UAAU,QAAQ,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,WAAW,IAAI;AACtC,QAAM,EAAE,eAAe,UAAU,WAAW,YAAY,IAAI;AAC5D,QAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,QAAM,CAAC,WAAW,QAAQ,IAAI,eAAe,OAAO,cAAc,CAAC,aAAa,UAAU;AAC1F,QAAM,WAAW;AAAA,IACf;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACA,QAAMR,WAAU,IAAI,WAAW,IAAI,WAAW,aAAa,eAAe,OAAO,KAAK,CAAC,EAAE,MAAM;AAC/F,QAAM,MAAM,SAAS,WAAW,UAAU,OAAO,KAAK;AACtD,QAAM,QAAQ,SAAS,UAAU,IAAI,IAAI,MAAM,EAAE;AACjD,QAAM,YAAY,SAAS,UAAU,IAAI,OAAO,MAAM;AACtD,QAAM,UAAU,UAAU;AAC1B,QAAM,iBAAiB,SAAS,UAAU,IAAI,WAAW,MAAM;AAC/D,QAAM,eAAe,eAAe;AACpC,QAAM,sBAAsB,kBAAkB,YAAY,IAAI;AAC9D,MAAI;AACJ,UAAQ;AAAA,SACD;AACH,mBAAa;AACb;AAAA,SACG;AACH,mBAAa;AACb;AAAA,SACG;AACH,mBAAa;AACb;AAAA,SACG;AACH,mBAAa;AACb;AAAA;AAEA,mBAAa;AACb;AAAA;AAEJ,gBAAc,SAAS,cAAc,WAAW,MAAM,KAAK,GAAG,OAAO,WAAW,UAAU,aAAa,YAAY,aAAaA,UAAS,OAAO,MAAM,SAAS,GAAG,qBAAqB,YAAY,WAAW,KAAK;AACnN,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,WAAW;AAAA,EACX,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,IAAI;AAClB,MAAI,EAAE,KAAK,IAAI;AACf,MAAI,OAAO,GAAG;AACZ,YAAQ,MAAM,MAAM;AAAA,EACtB;AACA,QAAM,aAAa,MAAM,MAAM;AAC/B,QAAM,OAAO,MAAM,MAAM;AACzB,QAAM,WAAW,IAAI,MAAM,OAAO,CAAC;AACnC,MAAI,WAAW;AACf,WAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,QAAI,OAAO,MAAM;AACf,eAAS,cAAc,MAAM,MAAM;AAAA,IACrC;AAAA,EACF;AACA,QAAM,OAAO,IAAI,MAAM,UAAU;AACjC,QAAM,QAAQ,IAAI,MAAM,IAAI,EAAE,KAAK,CAAC;AACpC,QAAMZ,QAAO,MAAM,MAAM,MAAM;AAC/B,EAAAA,MAAK,QAAQ;AACb,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,UAAM,QAAQ;AACd,SAAK,MAAM,OAAO,EAAE,QAAQ,EAAE,GAAG,MAAM,GAAG,OAAO,EAAE,OAAO,MAAAA,MAAK,GAAG,SAAS,SAAS,CAAC;AAAA,EACvF;AACA,SAAO,KAAK,IAAI,CAAC,EAAE,QAAQ,MAAM,OAAO,EAAE,QAAQ,OAAO,OAAO,SAAS,EAAE;AAC7E;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,IAAI;AAC7C,QAAM,MAAM,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AAChD,QAAM,UAAU,SAAS,mBAAmB,GAAG;AAC/C,UAAQ,KAAK,CAAC;AACd,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB;AAAA,EACnB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,WAAW,gBAAgB,gBAAgB;AACzC,iBAAe,YAAY;AAC7B;AAGA,IAAI,OAAO,IAAI;AACf,KAAK;AAAA,EACH;AAAA,EACA,YAAY,YAAY,SAAS,IAAI,WAAW;AAAA,IAC9C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF,CAAC,CAAC;AACJ;AACA,KAAK,aAAa,gCAAgC,YAAY;AAC5D,MAAI,KAAK,IAAI,SAAS,GAAG;AACvB,WAAO;AAAA,EACT;AACA,MAAI;AACF,QAAI,eAAe,EAAE,MAAM,YAAY,IAAI,kBAAkB,CAAC,CAAC;AAC/D,WAAO,YAAY,SAAS,IAAI,WAAW;AAAA,MACzC;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,MACA;AAAA,IACF,CAAC,CAAC;AAAA,EACJ,SAAS,IAAP;AACA,WAAO;AAAA,EACT;AACF,CAAC;AAGD,IAAI,iCAAiC,QAAQ,wCAAwC,CAAC;AACtF,IAAI,gDAAgD,QAAQ,+CAA+C,CAAC;AAC5G,IAAI,qBAAqB,QAAQ,0BAA0B,CAAC;AAC5D,IAAI,0BAA0B,+BAA+B,WAAW;AACxE,IAAI,cAAc,mBAAmB,WAAW;AAChD,IAAI,cAAc,cAAc,cAAc;AAAA,EAC5C,YAAY,MAAM;AAChB,UAAM;AACN,SAAK,OAAO;AACZ,SAAK,mBAAmB;AACxB,SAAK,KAAK,KAAK,qBAAqB,YAAY;AAChD,yBAAqB,KAAK,KAAK,KAAK,gBAAgB;AACpD,SAAK,YAAY,IAAI,YAAY,MAAM,OAAO,CAAC;AAAA,EACjD;AAAA,EACA,MAAM,QAAQ,OAAO,OAAO;AAC1B,UAAM,SAAS,EAAE,IAAI,KAAK,mBAAmB;AAC7C,SAAK,KAAK,QAAQ,QAAQ,OAAO,OAAO,CAAC;AACzC,WAAO;AAAA,EACT;AAAA,EACA,aAAa;AACX,WAAO,KAAK,UAAU,WAAW;AAAA,EACnC;AAAA,EACA,MAAM,KAAK,GAAG;AACZ,UAAM,QAAQ,aAAa,IAAI;AAC/B,MAAE;AACF,UAAM,WAAW,aAAa,IAAI,IAAI;AACtC,WAAO,EAAE,SAAS;AAAA,EACpB;AAAA,EACA,KAAK,QAAQ,QAAQ,OAAO,OAAO,UAAU;AAC3C,UAAM,KAAK,KAAK;AAChB,QAAI,UAAU,UAAU;AACtB,YAAM,cAAc;AACpB,WAAK,UAAU,IAAI,QAAQ,EAAE,IAAI,aAAa,OAAO,OAAO,cAAc,MAAM,SAAS,CAAC;AAC1F;AAAA,IACF;AACA,UAAMA,QAAO,aAAa,cAAc,KAAK;AAC7C,UAAM,WAAWA,QAAO,aAAa,gBAAgB,KAAK;AAC1D,UAAM,eAAe,KAAK,KAAK,QAAQ,QAAQ;AAC/C,SAAK,UAAU,IAAI,QAAQ,EAAE,IAAI,cAAc,OAAO,OAAO,SAAS,CAAC;AACvE,SAAK,KAAK,KAAK,eAAe,IAAIA,OAAM,YAAY;AACpD,QAAI,UAAU,MAAM;AAClB,WAAK,KAAK,OAAO,IAAI,IAAI,WAAW,OAAO,QAAQ,OAAO,YAAY,QAAQ,GAAG,YAAY;AAAA,IAC/F;AAAA,EACF;AAAA,EACA,MAAM,KAAK,QAAQ;AACjB,WAAO,KAAK,SAAS,MAAM;AAAA,EAC7B;AAAA,EACA,SAAS,QAAQ,OAAO,KAAK;AAC3B,UAAM,EAAE,cAAc,OAAO,OAAO,YAAY,IAAI,KAAK,UAAU,IAAI,MAAM;AAC7E,QAAI,UAAU,UAAU;AACtB,WAAK,SAAS,QAAQ,UAAU,OAAO,OAAO,QAAQ,OAAO,YAAY,SAAS;AAChF,eAAO;AAAA,MACT;AACA,aAAO,YAAY,MAAM,OAAO,GAAG;AAAA,IACrC;AACA,YAAQ,SAAS;AACjB,UAAM,OAAO,aAAa,cAAc,KAAK;AAC7C,UAAM,mBAAmB,aAAa,gBAAgB,KAAK;AAC3D,UAAM,QAAQ,KAAK,KAAK,OAAO,MAAM,eAAe,QAAQ,kBAAkB,eAAe,MAAM,gBAAgB;AACnH,WAAO,qBAAqB,MAAM,QAAQ,KAAK;AAAA,EACjD;AAAA,EACA,YAAY,QAAQ,QAAQ,OAAO;AACjC,QAAI,KAAK,UAAU,IAAI,MAAM,GAAG;AAC9B,YAAM,OAAO,KAAK,UAAU,IAAI,MAAM;AACtC,WAAK;AACL,UAAI,CAAC,SAAS,KAAK,WAAW,GAAG;AAC/B,eAAO;AAAA,MACT;AACA,WAAK,KAAK,MAAM,KAAK,YAAY;AACjC,WAAK,KAAK,KAAK,YAAY,KAAK,EAAE;AAClC,WAAK,UAAU,OAAO,MAAM;AAAA,IAC9B;AACA,WAAO;AAAA,EACT;AAAA,EACA,SAAS,QAAQ;AACf,QAAI,KAAK,UAAU,IAAI,MAAM,GAAG;AAC9B,YAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,aAAO,WAAW;AAAA,IACpB;AACA,WAAO;AAAA,EACT;AAAA,EACA,OAAO,QAAQ;AACb,UAAM,OAAO,KAAK,UAAU,IAAI,MAAM;AACtC,QAAI,QAAQ,MAAM;AAChB,WAAK;AAAA,IACP;AAAA,EACF;AAAA,EACA,iBAAiB;AACf,WAAO;AAAA,EACT;AAAA,EACA,gBAAgB,QAAQ;AACtB,WAAO,KAAK,UAAU,IAAI,MAAM,EAAE;AAAA,EACpC;AAAA,EACA,UAAU;AACR,SAAK,KAAK,KAAK,QAAQ;AACvB,QAAI,aAAa,KAAK,MAAM;AAC1B,WAAK,KAAK,QAAQ,oBAAoB;AAAA,IACxC;AACA,SAAK,OAAO;AAAA,EACd;AAAA,EACA,SAAS;AACP,WAAO,EAAE,YAAY,MAAM;AAAA,EAC7B;AAAA,EACA,WAAW,OAAO,OAAO,cAAc;AACrC,QAAI;AACJ,QAAI,gBAAgB,MAAM;AACxB,eAAS,KAAK,MAAM,MAAM,OAAO,KAAK;AAAA,IACxC,OAAO;AACL,YAAM,KAAK,KAAK;AAChB,eAAS,EAAE,GAAG;AACd,WAAK,UAAU,IAAI,QAAQ,EAAE,IAAI,cAAc,OAAO,OAAO,UAAU,EAAE,CAAC;AAC1E,YAAMA,QAAO,aAAa,cAAc,KAAK;AAC7C,WAAK,KAAK,KAAK,eAAe,IAAIA,OAAM,YAAY;AAAA,IACtD;AACA,WAAO,EAAE,QAAQ,OAAO,MAAM;AAAA,EAChC;AAAA,EACA,mBAAmB,EAAE,OAAO,OAAO,OAAO,GAAG;AAC3C,UAAM,UAAU,KAAK,KAAK,OAAO;AACjC,UAAM,EAAE,aAAa,IAAI,KAAK,UAAU,IAAI,MAAM;AAClD,UAAMA,QAAO,aAAa,cAAc,KAAK;AAC7C,YAAQ;AAAA,WACD;AACH,eAAO,IAAI,aAAa,SAAS,cAAcA,KAAI;AAAA,WAChD;AACH,eAAO,IAAI,WAAW,SAAS,cAAcA,KAAI;AAAA,WAC9C;AACH,eAAO,IAAI,WAAW,SAAS,cAAcA,KAAI;AAAA;AAEjD,cAAM,IAAI,MAAM,iBAAiB,OAAO;AAAA;AAAA,EAE9C;AACF;AACA,SAAS,0BAA0B,MAAM;AACvC,SAAO,CAAC,SAAS,aAAa;AAC5B,iBAAa,MAAM,MAAM,EAAE,aAAa,cAAc,CAAC,EAAE,KAAK,CAAC,aAAa;AAC1E,UAAI,CAAC,SAAS,OAAO;AACnB,gBAAQ,IAAI,EAAE,uCAAuC,OAAO;AAAA,MAC9D;AACA,eAAS,YAAY,EAAE,KAAK,CAAC,WAAW;AACtC,oBAAY,YAAY,QAAQ,OAAO,EAAE,KAAK,CAAC,WAAW;AACxD,mBAAS,OAAO,UAAU,OAAO,MAAM;AAAA,QACzC,CAAC;AAAA,MACH,CAAC;AAAA,IACH,CAAC;AACD,WAAO,CAAC;AAAA,EACV;AACF;AACA,SAAS,oBAAoB,eAAe,kBAAkB,kBAAkB;AAC9E,MAAI,YAAY,MAAM;AACpB,WAAO;AAAA,EACT;AACA,MAAI,OAAO;AACX,MAAI,iBAAiB,kBAAkB;AACrC,WAAO;AAAA,EACT,WAAW,eAAe;AACxB,WAAO;AAAA,EACT;AACA,MAAI,eAAe,MAAM;AACvB,QAAI,YAAY,SAAS,MAAM;AAC7B,aAAO,YAAY;AAAA,IACrB;AAAA,EACF;AACA,SAAO,mBAAmB;AAC5B;AACA,eAAe,OAAO;AACpB,QAAM,CAAC,eAAe,gBAAgB,IAAI,MAAM,QAAQ,IAAI;AAAA,IAC1D,IAAI,EAAE,SAAS,uBAAuB;AAAA,IACtC,IAAI,EAAE,SAAS,8BAA8B;AAAA,EAC/C,CAAC;AACD,SAAO,IAAI,QAAQ,CAAC,SAAS,WAAW;AACtC,UAAM,gBAAgB,CAAC;AACvB,kBAAc,aAAa,CAAC,MAAM,WAAW;AAC3C,UAAI,KAAK,SAAS,YAAY,GAAG;AAC/B,cAAM,WAAW,8CAA8C,mBAAmB,QAAQ,OAAO,KAAK;AACtG,cAAM,OAAO,IAAI,KAAK,CAAC,QAAQ,GAAG,EAAE,MAAM,yBAAyB,CAAC;AACpE,eAAO,IAAI,gBAAgB,IAAI;AAAA,MACjC;AACA,UAAI,KAAK,SAAS,OAAO,GAAG;AAC1B,eAAO,oBAAoB,eAAe,kBAAkB,kBAAkB,OAAO,iBAAiB,MAAM;AAAA,MAC9G;AACA,aAAO,SAAS;AAAA,IAClB;AACA,QAAI,aAAa;AACf,oBAAc,kBAAkB,0BAA0B,oBAAoB,eAAe,kBAAkB,kBAAkB,OAAO,iBAAiB,EAAE,CAAC;AAAA,IAC9J;AACA,QAAI,cAAc;AAClB,kBAAc,UAAU,MAAM;AAC5B,UAAI,aAAa;AACf;AAAA,MACF;AACA,UAAI,aAAa;AACf;AAAA,MACF;AACA,oBAAc;AACd,YAAM,YAAY;AAClB,aAAO,EAAE,SAAS,UAAU,CAAC;AAAA,IAC/B;AACA,QAAI;AACJ,QAAI,oBAAoB,iBAAiB,YAAY,MAAM;AACzD,oBAAc,sBAAsB,IAAI,KAAK,CAAC,yCAAyC,wBAAwB,SAAS,CAAC,GAAG,EAAE,MAAM,kBAAkB,CAAC;AACvJ,aAAO,wBAAwB,aAAa;AAAA,IAC9C,OAAO;AACL,aAAO,YAAY,aAAa;AAAA,IAClC;AACA,SAAK,KAAK,CAAC,WAAW;AACpB,oBAAc;AACd,oBAAc;AACd,YAAM,iBAAiB;AACvB,aAAO,OAAO;AAAA,QACZ,MAAM,OAAO,MAAM,QAAQ,MAAM,CAAC,CAAC;AAAA,QACnC,sBAAsB,OAAO,MAAM,2BAA2B,MAAM,CAAC,QAAQ,CAAC;AAAA,QAC9E,iBAAiB,OAAO,MAAM,qBAAqB,UAAU,CAAC,CAAC;AAAA,QAC/D,gBAAgB,OAAO,MAAM,mBAAmB,MAAM;AAAA,UACpD;AAAA,UACA;AAAA,UACA;AAAA,QACF,CAAC;AAAA,QACD,aAAa,OAAO,MAAM,gBAAgB,gBAAgB,CAAC,QAAQ,CAAC;AAAA,QACpE,SAAS,OAAO,MAAM,WAAW,gBAAgB,CAAC,CAAC;AAAA,MACrD;AACA,cAAQ,EAAE,MAAM,OAAO,CAAC;AAAA,IAC1B,CAAC,EAAE,MAAM,MAAM;AAAA,EACjB,CAAC;AACH;AACA,SAAS,qBAAqB,SAAS,OAAO;AAC5C,UAAQ;AAAA,SACD;AACH,aAAO,IAAI,aAAa,OAAO;AAAA,SAC5B;AACH,aAAO,IAAI,WAAW,OAAO;AAAA,SAC1B;AACH,aAAO,IAAI,WAAW,OAAO;AAAA;AAE7B,YAAM,IAAI,MAAM,iBAAiB,OAAO;AAAA;AAE9C;AACA,IAAI,kBAAkB;AAAA,EACpB;AAAA,EACA;AAAA,EACA;AACF;AACA,IAAI,WAAW;AACf,IAAI,iBAAiB;AACrB,IAAI,cAAc,CAAC;AACnB,IAAI,cAAc;AAClB,IAAI,cAAc;AAClB,SAAS,YAAY,MAAM,mBAAmB,OAAO;AACnD,kBAAgB,mGAAmG;AACnH,MAAI,aAAa;AACf,UAAM,IAAI,MAAM,gIAAgI;AAAA,EAClJ;AACA,aAAW;AACX,gBAAc;AAChB;AACA,SAAS,aAAa,iBAAiB,mBAAmB,OAAO;AAC/D,MAAI,aAAa;AACf,UAAM,IAAI,MAAM,iIAAiI;AAAA,EACnJ;AACA,MAAI,OAAO,oBAAoB,UAAU;AACvC,qBAAiB;AAAA,EACnB,OAAO;AACL,kBAAc;AACd,UAAM,eAAe,gBAAgB,OAAO,CAAC,SAAS,YAAY,SAAS,IAAI;AAC/E,QAAI,aAAa,SAAS,GAAG;AAC3B,YAAM,IAAI,MAAM,2DAA2D,aAAa,KAAK,GAAG,gKAAgK;AAAA,IAClQ;AAAA,EACF;AACA,gBAAc;AAChB;AACA,IAAI,eAAe;AACnB,IAAI,qBAAqB;AACzB,SAAS,gBAAgB,YAAY;AACnC,iBAAe;AACjB;AACA,SAAS,kBAAkB;AACzB,MAAI,uBAAuB,IAAI;AAC7B,UAAM,IAAI,MAAM,+BAA+B;AAAA,EACjD;AACA,SAAO;AACT;AAGA,IAAI,WAAW;AAGf,IAAI,gBAAgB;AACpB,gBAAgB,QAAQ,YAAY;AAClC,QAAM,EAAE,KAAK,IAAI,MAAM,KAAK;AAC5B,SAAO,IAAI,YAAY,IAAI;AAC7B,GAAG,aAAa;AAGhB,IAAI,OAAO,IAAI;AACf,KAAK,aAAa,qCAAqC,MAAM,EAAE;AAC/D,KAAK,aAAa,sBAAsB,MAAM,IAAI;AAClD,KAAK,aAAa,iCAAiC,MAAM,CAAC;AAC1D,KAAK,aAAa,8BAA8B,MAAM,EAAE;AACxD,KAAK,aAAa,qCAAqC,MAAM,KAAK;AAClE,KAAK,aAAa,4BAA4B,MAAM,KAAK;AACzD,KAAK,aAAa,qCAAqC,MAAM,GAAG;AAChE,KAAK,aAAa,2BAA2B,MAAM,KAAK;AACxD,KAAK,aAAa,kCAAkC,MAAM,KAAK;AAG/D,IAAI;AAAA,CACH,SAAS,eAAe;AACvB,gBAAc,cAAc,SAAS,KAAK;AAC1C,gBAAc,cAAc,SAAS,KAAK;AAC1C,gBAAc,cAAc,SAAS,KAAK;AAC1C,gBAAc,cAAc,SAAS,KAAK;AAC1C,gBAAc,cAAc,WAAW,KAAK;AAC5C,gBAAc,cAAc,aAAa,KAAK;AAC9C,gBAAc,cAAc,mBAAmB,KAAK;AACpD,gBAAc,cAAc,UAAU,KAAK;AAC3C,gBAAc,cAAc,gBAAgB,KAAK;AACjD,gBAAc,cAAc,iBAAiB,KAAK;AAClD,gBAAc,cAAc,eAAe,MAAM;AACjD,gBAAc,cAAc,wBAAwB,MAAM;AAC1D,gBAAc,cAAc,aAAa,MAAM;AAC/C,gBAAc,cAAc,SAAS,MAAM;AAC3C,gBAAc,cAAc,WAAW,MAAM;AAC7C,gBAAc,cAAc,SAAS,MAAM;AAC3C,gBAAc,cAAc,SAAS,MAAM;AAC3C,gBAAc,cAAc,2BAA2B,MAAM;AAC7D,gBAAc,cAAc,2BAA2B,MAAM;AAC/D,GAAG,iBAAiB,eAAe,CAAC,EAAE;AACtC,IAAI,OAAO;AACX,IAAI,wBAAwB;AAC5B,IAAI,wBAAwB;AAC5B,IAAI,OAAO;AACX,IAAI,OAAO;AACX,IAAI,sBAAsB;AAC1B,IAAI,OAAO;AACX,IAAI,SAAS;AACb,IAAI,aAAa;AACjB,IAAI,WAAW;AACf,IAAI,eAAe;AACnB,IAAI,iBAAiB;AACrB,IAAI,qBAAqB;AACzB,IAAI,QAAQ;AACZ,IAAI,YAAY;AAChB,IAAI,cAAc;AAClB,IAAI,kBAAkB;AACtB,IAAI,eAAe;AACnB,IAAI,mBAAmB;AAAA;AAEvB,IAAI,qBAAqB;AAAA;AAAA;AAAA;AAIzB,IAAI,yBAAyB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAc7B,IAAI,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAMf,IAAI,eAAe;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAsBnB,IAAI,aAAa;AACjB,IAAI,iBAAiB;AACrB,IAAI,OAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAYX,IAAI,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAqBX;AAAA;AAAA;AAGJ,IAAI,SAAS;AACb,IAAI,aAAa;AAAA;AAAA;AAAA;AAIjB,SAAS,gBAAgB,KAAK,SAAS;AACrC,QAAM,kBAAkB,UAAU,yBAAyB;AAC3D,SAAO,UAAU;AAAA,iCACc;AAAA;AAAA,QAEzB,kBAAkB;AAAA;AAAA,MAEpB,kBAAkB;AAAA,aACX;AAAA;AAEb;AACA,SAAS,kBAAkB,MAAM,SAAS;AACxC,UAAQ;AAAA,SACD,aAAa;AAChB,aAAO;AAAA,SACJ,aAAa;AAChB,aAAO;AAAA,SACJ,aAAa;AAChB,aAAO;AAAA,SACJ,aAAa;AAChB,aAAO;AAAA,SACJ,aAAa;AAChB,aAAO,UAAU,aAAa;AAAA,SAC3B,aAAa;AAChB,aAAO,UAAU,eAAe;AAAA,SAC7B,aAAa;AAChB,aAAO,UAAU,qBAAqB;AAAA,SACnC,aAAa;AAChB,aAAO,UAAU,YAAY;AAAA,SAC1B,aAAa;AAChB,aAAO,UAAU,kBAAkB;AAAA,SAChC,aAAa;AAChB,aAAO,UAAU,mBAAmB;AAAA,SACjC,aAAa;AAChB,aAAO,UAAU,iBAAiB;AAAA,SAC/B,aAAa;AAChB,aAAO;AAAA,SACJ,aAAa;AAChB,aAAO,UAAU,eAAe;AAAA,SAC7B,aAAa;AAChB,aAAO,UAAU,aAAa;AAAA,SAC3B,aAAa;AAChB,aAAO,gBAAgB,OAAO,OAAO;AAAA,SAClC,aAAa;AAChB,aAAO,gBAAgB,OAAO,OAAO;AAAA,SAClC,aAAa;AAChB,aAAO,UAAU,WAAW;AAAA,SACzB,aAAa;AAChB,aAAO;AAAA,SACJ,aAAa;AAChB,aAAO;AAAA;AAEP,YAAM,IAAI,MAAM,cAAc,0BAA0B;AAAA;AAE9D;AAGA,IAAI;AAAA,CACH,SAAS,cAAc;AACtB,eAAa,aAAa,SAAS,KAAK;AACxC,eAAa,aAAa,UAAU,KAAK;AACzC,eAAa,aAAa,SAAS,KAAK;AACxC,eAAa,aAAa,UAAU,KAAK;AACzC,eAAa,aAAa,SAAS,KAAK;AACxC,eAAa,aAAa,SAAS,KAAK;AACxC,eAAa,aAAa,WAAW,KAAK;AAC1C,eAAa,aAAa,WAAW,KAAK;AAC1C,eAAa,aAAa,YAAY,KAAK;AAC3C,eAAa,aAAa,SAAS,KAAK;AACxC,eAAa,aAAa,iBAAiB,MAAM;AACjD,eAAa,aAAa,SAAS,MAAM;AACzC,eAAa,aAAa,UAAU,MAAM;AAC1C,eAAa,aAAa,WAAW,MAAM;AAC3C,eAAa,aAAa,eAAe,MAAM;AAC/C,eAAa,aAAa,WAAW,MAAM;AAC3C,eAAa,aAAa,SAAS,MAAM;AACzC,eAAa,aAAa,UAAU,MAAM;AAC1C,eAAa,aAAa,aAAa,MAAM;AAC7C,eAAa,aAAa,UAAU,MAAM;AAC1C,eAAa,aAAa,YAAY,MAAM;AAC5C,eAAa,aAAa,UAAU,MAAM;AAC1C,eAAa,aAAa,YAAY,MAAM;AAC9C,GAAG,gBAAgB,cAAc,CAAC,EAAE;AACpC,IAAI,OAAO;AACX,IAAI,QAAQ;AACZ,IAAI,OAAO;AACX,IAAI,QAAQ;AAAA;AAAA;AAAA;AAIZ,IAAI,SAAS;AACb,IAAI,OAAO;AACX,IAAI,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAgBf,IAAI,OAAO;AACX,IAAI,SAAS;AACb,IAAI,UAAU;AACd,IAAI,OAAO;AAAA;AAEX,IAAI,eAAe;AACnB,IAAI,OAAO;AACX,IAAI,aAAa;AACjB,IAAI,iBAAiB;AAAA;AAAA;AAAA;AAIrB,IAAI,QAAQ;AACZ,IAAI,SAAS;AACb,IAAI,aAAa;AACjB,IAAI,YAAY;AAAA;AAAA;AAGhB,IAAI,SAAS;AACb,IAAI,WAAW;AACf,IAAI,OAAO;AACX,IAAI,QAAQ;AAAA;AAAA;AAAA;AAIZ,IAAI,QAAQ;AACZ,IAAI,UAAU;AACd,IAAI,QAAQ;AAAA;AAAA;AAAA;AAIZ,IAAI,UAAU;AACd,SAAS,iBAAiB,MAAM,SAAS;AACvC,UAAQ;AAAA,SACD,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO,UAAU,WAAW;AAAA,SACzB,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO,UAAU,iBAAiB;AAAA,SAC/B,YAAY;AACf,aAAO,UAAU,YAAY;AAAA,SAC1B,YAAY;AACf,aAAO,UAAU,aAAa;AAAA,SAC3B,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA,SACJ,YAAY;AACf,aAAO;AAAA;AAEP,YAAM,IAAI,MAAM,cAAc,0BAA0B;AAAA;AAE9D;AAGA,IAAI,cAAc,CAAC,cAAc;AAC/B,UAAQ;AAAA,SACD;AACH,aAAO;AAAA,SACJ;AACH,aAAO;AAAA,SACJ;AACH,aAAO;AAAA,SACJ;AACH,aAAO;AAAA;AAEP,YAAM,IAAI,MAAM,GAAG,uCAAuC;AAAA;AAEhE;AACA,SAAS,oBAAoB,aAAa,4BAA4B,OAAO,SAAS,OAAO,eAAe,GAAG;AAC7G,MAAI,gBAAgB,MAAM;AACxB,WAAO;AAAA,EACT;AACA,MAAI,sBAAsB;AAC1B,MAAI,gBAAgB,UAAU;AAC5B,0BAAsB,iBAAiB,YAAY,MAAM;AAAA,EAC3D,WAAW,gBAAgB,QAAQ;AACjC,0BAAsB,iBAAiB,YAAY,MAAM,MAAM;AAAA,EACjE,WAAW,gBAAgB,OAAO;AAChC,0BAAsB,iBAAiB,YAAY,KAAK,MAAM;AAAA,EAChE,WAAW,gBAAgB,SAAS;AAClC,0BAAsB,iBAAiB,YAAY,OAAO,MAAM;AAAA,EAClE,WAAW,gBAAgB,SAAS;AAClC,0BAAsB,kBAAkB,aAAa,OAAO,MAAM;AAAA,EACpE,WAAW,gBAAgB,WAAW;AACpC,0BAAsB,iBAAiB,YAAY,SAAS,MAAM;AAAA,EACpE,WAAW,gBAAgB,aAAa;AACtC,0BAAsB,iBAAiB,YAAY,WAAW,MAAM;AAAA,EACtE,OAAO;AACL,UAAM,IAAI,MAAM,cAAc,8DAA8D;AAAA,EAC9F;AACA,QAAM,cAAc,SAAS,IAAI;AACjC,QAAM,WAAW,YAAY,WAAW;AACxC,MAAI,uBAAuB;AAC3B,MAAI,2BAA2B;AAC7B,2BAAuB;AAAA,0BACD,yBAAyB,yBAAyB;AAAA;AAAA,UAElE;AAAA;AAAA,EAER,OAAO;AACL,2BAAuB;AAAA,0BACD,yBAAyB,yBAAyB;AAAA,UAClE;AAAA;AAAA,EAER;AACA,SAAO;AACT;AACA,SAAS,sBAAsB,SAAS,aAAa;AACnD,SAAO;AAAA,QACD,UAAU,mDAAmD;AAAA,QAC7D,cAAc,uCAAuC;AAAA;AAE7D;AAGA,SAAS,4BAA4B,YAAY,cAAc;AAC7D,MAAI,KAAK,IAAI,GAAG,UAAU,IAAI,GAAG;AAC/B,UAAM,IAAI,MAAM,0DAA0D;AAAA,EAC5E;AACA,QAAM,YAAY,WAAW;AAC7B,QAAM,QAAQ,WAAW,IAAI,CAAC,MAAM,GAAG,gBAAgB,IAAI;AAC3D,QAAMY,WAAU,IAAI,MAAM,YAAY,CAAC;AACvC,EAAAA,SAAQ,YAAY,KAAK,MAAM,YAAY;AAC3C,WAAS,KAAK,YAAY,GAAG,MAAM,GAAG,EAAE,IAAI;AAC1C,IAAAA,SAAQ,MAAM,IAAIA,SAAQ,KAAK,QAAQ,MAAM,KAAK;AAAA,EACpD;AACA,SAAOA;AACT;AAGA,IAAI,kBAAkB,CAAC,QAAQ,SAAS,YAAY,WAAW;AAC7D,QAAM,aAAa,EAAE,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC9D,QAAM,SAAS,YAAY,YAAY,YAAY,OAAO;AAC1D,QAAM,SAAS,OAAO,mBAAmB,EAAE,MAAM,QAAQ,OAAO,QAAQ,YAAY,KAAK,CAAC;AAC1F,QAAM,WAAW,OAAO,sBAAsB;AAAA,IAC5C,SAAS,EAAE,QAAQ,YAAY,OAAO;AAAA,IACtC,OAAO,QAAQ,YAAY;AAAA,IAC3B,QAAQ;AAAA,EACV,CAAC;AACD,SAAO;AACT;AACA,SAAS,mBAAmB,MAAM;AAChC,MAAI,QAAQ,GAAG;AACb,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,WAAW,SAAS,GAAG;AACrB,WAAO;AAAA,EACT,OAAO;AACL,UAAM,MAAM,gBAAgB,2BAA2B;AAAA,EACzD;AACF;AACA,SAAS,aAAaH,QAAO;AAC3B,MAAIA,WAAU,GAAG;AACf,WAAO;AAAA,EACT,WAAWA,WAAU,GAAG;AACtB,WAAO;AAAA,EACT,WAAWA,WAAU,GAAG;AACtB,WAAO;AAAA,EACT,WAAWA,WAAU,GAAG;AACtB,WAAO;AAAA,EACT,WAAWA,WAAU,GAAG;AACtB,WAAO;AAAA,EACT,WAAWA,WAAU,GAAG;AACtB,WAAO;AAAA,EACT,OAAO;AACL,UAAM,MAAM,SAASA,6BAA4B;AAAA,EACnD;AACF;AACA,SAAS,oCAAoC;AAC3C,SAAO;AAAA,MACH,oBAAoB;AAAA;AAAA;AAG1B;AACA,SAAS,sBAAsB;AAC7B,SAAO;AAAA,IACL,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAQ3B;AACA,SAAS,yBAAyB;AAChC,SAAO;AAAA;AAAA;AAGT;AACA,SAAS,YAAY,WAAW,YAAY,SAAS;AACnD,QAAM,iBAAiB,CAAC;AACxB,iBAAe,KAAK;AAAA,+BACS,QAAQ,cAAc;AAAA,+BACtB,QAAQ,cAAc;AAAA,+BACtB,QAAQ,cAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAQ3C,eAAe,OAAO,IAAI,8BAA8B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,KAW7D;AACH,MAAI,QAAQ,cAAc;AACxB,mBAAe,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,uEAO+C,eAAe,WAAW,OAAO,QAAQ,MAAM;AAAA;AAAA,OAE/G;AACH,WAAO;AAAA,MACL;AAAA,MACA,eAAe,KAAK,IAAI;AAAA,MACxB,0BAA0B,WAAW,KAAK;AAAA,MAC1C,QAAQ,YAAY;AAAA,IACtB,EAAE,KAAK,IAAI;AAAA,EACb;AACA,MAAI,oBAAoB;AACxB,MAAI,wBAAwB;AAC5B,MAAI,qBAAqB;AACzB,UAAQ,cAAc,QAAQ,CAAC,GAAG,OAAO;AACvC,UAAM,cAAc,mBAAmB,UAAU,IAAI,MAAM,MAAM;AACjE,QAAI,gBAAgB,UAAU,gBAAgB,QAAQ;AACpD,8BAAwB;AAAA,IAC1B;AACA,QAAI,qBAAqB,uBAAuB;AAC9C,4BAAsB;AAAA,IACxB;AACA,wBAAoB;AACpB,0BAAsB,GAAG,EAAE,OAAO,CAAC,EAAE,YAAY,IAAI,EAAE,MAAM,CAAC,YAAY;AAAA,EAC5E,CAAC;AACD,QAAM,iBAAiB,mBAAmB,WAAW,MAAM,MAAM;AACjE,0BAAwB,mBAAmB,UAAU,mBAAmB;AACxE,MAAI,qBAAqB,uBAAuB;AAC9C,0BAAsB;AAAA,EACxB;AACA,sBAAoB;AACpB,wBAAsB,cAAc;AACpC,QAAM,gBAAgB,WAAW,MAAM,SAAS;AAChD,QAAM,kBAAkB,mBAAmB,aAAa;AACxD,0BAAwB,oBAAoB,UAAU,oBAAoB;AAC1E,MAAI,qBAAqB,uBAAuB;AAC9C,0BAAsB;AAAA,EACxB;AACA,sBAAoB;AACpB,wBAAsB;AAAA,4BACI;AAC1B,MAAI,QAAQ,MAAM;AAChB,QAAI,mBAAmB;AACrB,4BAAsB;AAAA,IACxB;AACA,wBAAoB;AACpB,0BAAsB;AAAA,EACxB;AACA,MAAI,QAAQ,UAAU;AACpB,QAAI,mBAAmB;AACrB,4BAAsB;AAAA,IACxB;AACA,0BAAsB,QAAQ;AAAA,EAChC;AACA,wBAAsB;AACtB,iBAAe,KAAK,kBAAkB;AACtC,MAAI,QAAQ,QAAQ;AAClB,mBAAe,KAAK;AAAA;AAAA,KAEnB;AAAA,EACH,OAAO;AACL,mBAAe,KAAK;AAAA,qEAC6C,eAAe,WAAW,OAAO,QAAQ,MAAM;AAAA,KAC/G;AAAA,EACH;AACA,UAAQ,cAAc,QAAQ,CAAC,GAAG,OAAO;AACvC,mBAAe,KAAK;AAAA,2BACG,IAAI,0BAA0B,YAAY,QAAQ,gBAAgB,QAAQ,cAAc,MAAM,eAAe,UAAU,IAAI,OAAO,QAAQ,MAAM;AAAA,SAClK;AAAA,EACP,CAAC;AACD,MAAI,uBAAuB,IAAI;AAC7B,mBAAe,KAAK;AAAA,2BACG,IAAI,QAAQ,cAAc;AAAA,OAC9C;AAAA,EACL;AACA,QAAM,gBAAgB,uBAAuB,WAAW,OAAO,QAAQ,cAAc;AACrF,QAAM,UAAU;AAAA,IACd;AAAA,IACA,eAAe,KAAK,IAAI;AAAA,IACxB,0BAA0B,WAAW,KAAK;AAAA,IAC1C;AAAA,IACA,gCAAgC,WAAW,MAAM,MAAM;AAAA,EACzD;AACA,MAAI,CAAC,QAAQ,QAAQ;AACnB,YAAQ,KAAK,iBAAiB,WAAW,OAAO,WAAW,OAAO,QAAQ,MAAM,CAAC;AAAA,EACnF;AACA,QAAM,eAAe,UAAU,IAAI,CAAC,GAAG,OAAO,gBAAgB,GAAG,WAAW,OAAO,QAAQ,gBAAgB,QAAQ,cAAc,QAAQ,cAAc,QAAQ,QAAQ,QAAQ,eAAe,EAAE,WAAW,WAAW,MAAM,MAAM,CAAC,EAAE,KAAK,IAAI;AAC9O,UAAQ,KAAK,YAAY;AACzB,UAAQ,KAAK,QAAQ,YAAY,CAAC;AAClC,QAAM,SAAS,QAAQ,KAAK,IAAI;AAChC,SAAO;AACT;AACA,SAAS,eAAe,SAAS,QAAQ,YAAY,QAAQ;AAC3D,MAAI,MAAM,QAAQ;AAClB,MAAI,QAAQ,cAAc;AACxB,WAAO;AAAA,EACT;AACA,QAAM,QAAQ,WAAW,IAAI,CAAC,MAAM,EAAE,KAAK,EAAE,OAAO,OAAO,KAAK;AAChE,QAAM,gBAAgB,WAAW,IAAI,CAAC,MAAM,qBAAqB,iBAAiB,EAAE,OAAO,OAAO,KAAK,CAAC;AACxG,QAAM,4BAA4B,WAAW,IAAI,CAAC,MAAM,aAAa,YAAY,EAAE,OAAO,OAAO,KAAK,CAAC,EAAE,KAAK,GAAG;AACjH,QAAM,mBAAmB,cAAc,IAAI,CAAC,MAAM,EAAE,KAAK,GAAG,CAAC,EAAE,KAAK,GAAG;AACvE,QAAM,qBAAqB,eAAe,OAAO,IAAI,iBAAiB;AACtE,SAAO,OAAO,QAAQ,gBAAgB,QAAQ,cAAc,KAAK,GAAG,IAAI,MAAM,OAAO,IAAI,CAAC,UAAU,MAAM,MAAM,EAAE,KAAK,GAAG,IAAI,MAAM,KAAK,GAAG,IAAI,QAAQ,cAAc,KAAK,GAAG,IAAI,mBAAmB,4BAA4B;AACjO,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AA2DpB,SAAS,0BAA0B,OAAO;AACxC,QAAM,OAAO,MAAM;AACnB,MAAI,QAAQ,GAAG;AACb,WAAO;AAAA,EACT;AACA,QAAMG,WAAU,aAAa,eAAe,KAAK;AACjD,QAAM,QAAQ,mBAAmB,IAAI;AACrC,QAAM,UAAU,CAAC;AACjB,WAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,YAAQ,KAAK,IAAI,IAAI;AAAA,EACvB;AACA,MAAIA,SAAQ,WAAW,GAAG;AACxB,WAAO;AAAA;AAAA;AAAA;AAAA,EAIT;AACA,MAAI;AACJ,YAAU,wBAAwBA,SAAQ,IAAI,CAAC,GAAG,OAAO;AACvD,UAAM,QAAQ,OAAO,QAAQ,2CAA2C,aAAa,EAAE;AACvF,UAAM,QAAQ,OAAOA,SAAQ,SAAS,IAAI,OAAO,QAAQ,KAAK,iBAAiB,QAAQ,kCAAkC,aAAa,EAAE,MAAM,qBAAqB,QAAQ,kCAAkC,aAAa,EAAE;AAC5N,WAAO,GAAG,UAAU;AAAA,EACtB,CAAC,EAAE,KAAK,EAAE;AACV,SAAO;AAAA,4CACmC;AAAA,QACpC;AAAA,eACO,SAAS,QAAQ,KAAK,GAAG;AAAA;AAAA;AAGxC;AACA,SAAS,wBAAwB,WAAW,QAAQ;AAClD,QAAM,UAAU,UAAU;AAC1B,QAAM,OAAO,UAAU,MAAM;AAC7B,QAAM,OAAO,mBAAmB,IAAI;AACpC,QAAM,WAAW,QAAQ,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC1E,QAAM,OAAO,CAAC,MAAM,MAAM,MAAM,MAAM,MAAM,IAAI,EAAE,MAAM,GAAG,IAAI;AAC/D,QAAM,SAAS,KAAK,IAAI,CAAC,MAAM,GAAG,SAAS,EAAE,KAAK,IAAI;AACtD,MAAI,OAAO,GAAG;AACZ,QAAI,QAAQ;AACV,aAAO;AAAA,aACA;AAAA,6BACgB;AAAA;AAAA;AAAA,IAGzB;AACA,WAAO;AAAA,WACA;AAAA,qBACU;AAAA;AAAA;AAAA,EAGnB;AACA,QAAM,WAAW,YAAY,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC9E,MAAI,UAAU,GAAG;AACjB,MAAI,SAAS,GAAG;AACd,cAAU;AAAA,EACZ;AACA,MAAI,QAAQ;AACV,WAAO;AAAA,WACA,YAAY;AAAA,2BACI,6BAA6B,WAAW,QAAQ,KAAK,KAAK,GAAG;AAAA,YAC5E;AAAA;AAAA;AAAA,EAGV;AACA,SAAO;AAAA,SACA,YAAY;AAAA,mBACF,6BAA6B,WAAW,QAAQ,KAAK,KAAK,GAAG;AAAA,UACtE;AAAA;AAAA;AAGV;AACA,SAAS,wBAAwB,WAAW,UAAU,QAAQ,sBAAsB;AAClF,QAAM,UAAU,UAAU;AAC1B,QAAM,iBAAiB,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AACxE,QAAM,WAAW,QAAQ,iBAAiB;AAC1C,QAAM,SAAS,UAAU,MAAM;AAC/B,QAAM,UAAU,SAAS;AACzB,QAAM,OAAO,mBAAmB,OAAO;AACvC,MAAI,aAAa,YAAY,UAAU,OAAO,QAAQ,KAAK,sBAAsB;AAC/E,QAAI,QAAQ;AACV,aAAO;AAAA,WACF;AAAA,2BACgB;AAAA;AAAA;AAAA,WAGhB,2BAA2B;AAAA,2BACX,WAAW,UAAU,IAAI,qCAAqC;AAAA;AAAA;AAAA,IAGrF,OAAO;AACL,aAAO;AAAA,SACJ;AAAA,mBACU;AAAA;AAAA;AAAA,SAGV,2BAA2B;AAAA,mBACjB,WAAW,UAAU,IAAI,qCAAqC;AAAA;AAAA;AAAA,IAG7E;AAAA,EACF;AACA,QAAM,gBAAgB,qBAAqB,iBAAiB,UAAU,OAAO,QAAQ;AACrF,QAAM,WAAW,UAAU;AAC3B,MAAI,gBAAgB;AACpB,MAAI,WAAW,GAAG;AAChB,QAAI,QAAQ;AACV,aAAO;AAAA,SACJ;AAAA,kBACS;AAAA;AAAA;AAAA,SAGT,2BAA2B;AAAA,kBAClB;AAAA;AAAA;AAAA,IAGd;AACA,WAAO;AAAA,SACF;AAAA,kBACS;AAAA;AAAA;AAAA,SAGT,2BAA2B;AAAA,kBAClB;AAAA;AAAA;AAAA,EAGhB,OAAO;AACL,QAAI,UAAU,KAAK,cAAc,UAAU,GAAG;AAC5C,sBAAgB;AAAA,IAClB,OAAO;AACL,sBAAgB,cAAc,IAAI,CAAC,MAAM,UAAU,aAAa,IAAI,QAAQ,QAAQ,EAAE,KAAK,IAAI;AAAA,IACjG;AAAA,EACF;AACA,MAAI,wBAAwB;AAC5B,MAAI,UAAU,KAAK,SAAS,GAAG;AAC7B,4BAAwB;AAAA,EAC1B,OAAO;AACL,QAAI,UAAU,GAAG;AACf,YAAM,aAAa,mBAAmB,MAAM;AAC5C,YAAM,eAAe,UAAU,MAAM,IAAI,CAAC,IAAI,OAAO,UAAU,aAAa,KAAK,QAAQ,GAAG,EAAE,KAAK,IAAI;AACvG,8BAAwB,GAAG,cAAc;AAAA,IAC3C,OAAO;AACL,8BAAwB;AAAA,IAC1B;AAAA,EACF;AACA,QAAM,WAAW,YAAY,QAAQ,OAAO,CAAC,EAAE,YAAY,IAAI,QAAQ,MAAM,CAAC;AAC9E,QAAM,UAAU,GAAG;AACnB,MAAI,QAAQ;AACV,WAAO;AAAA,SACF;AAAA;AAAA,QAED;AAAA,eACO,6BAA6B,WAAW,0BAA0B;AAAA;AAAA;AAAA,SAGxE,6BAA6B;AAAA;AAAA,QAE9B;AAAA,eACO,6BAA6B,WAAW,0BAA0B;AAAA;AAAA;AAAA,EAG/E;AACA,SAAO;AAAA,OACF;AAAA;AAAA,MAED;AAAA,iBACW,6BAA6B,WAAW,0BAA0B;AAAA;AAAA;AAAA,OAG5E,6BAA6B;AAAA;AAAA,MAE9B;AAAA,iBACW,6BAA6B,WAAW,0BAA0B;AAAA;AAAA;AAGnF;AACA,SAAS,gBAAgB,WAAW,UAAU,QAAQ,sBAAsB;AAC1E,MAAI,MAAM,wBAAwB,WAAW,MAAM;AACnD,QAAM,UAAU,UAAU;AAC1B,MAAI,QAAQ,UAAU,SAAS,QAAQ;AACrC,WAAO,wBAAwB,WAAW,UAAU,QAAQ,oBAAoB;AAAA,EAClF;AACA,SAAO;AACT;AACA,SAAS,uBAAuB,UAAU,gBAAgB;AACxD,QAAM,EAAE,GAAG,IAAI,CAAC,GAAG,IAAI,CAAC,EAAE,IAAI;AAC9B,QAAM,UAAU,SAAS;AACzB,MAAI,EAAE,WAAW,SAAS;AACxB,UAAM,SAAS,mBAAmB,OAAO;AACzC,UAAM,WAAW,2BAA2B;AAAA;AAAA;AAAA;AAAA;AAK5C,WAAO;AAAA,EACT;AACA,MAAI,sBAAsB;AAC1B,QAAM,OAAO,CAAC,GAAG,GAAG,CAAC;AACrB,MAAI,OAAO;AACX,WAAS,KAAK,GAAG,KAAK,KAAK,QAAQ,MAAM;AACvC,UAAM,MAAM,KAAK;AACjB,QAAI,IAAI,WAAW,GAAG;AACpB;AAAA,IACF;AACA,YAAQ,IAAI;AACZ,QAAI,IAAI,WAAW,GAAG;AACpB,6BAAuB,QAAQ,IAAI,qBAAqB;AAAA,IAC1D,OAAO;AACL,YAAMA,WAAU,4BAA4B,KAAK,mBAAmB;AACpE,6BAAuB,YAAY,qBAAqB;AACxD,eAAS,IAAI,GAAG,IAAIA,SAAQ,QAAQ,KAAK;AACvC,+BAAuB,QAAQ,IAAI,aAAa,QAAQA,SAAQ;AAChE,YAAI,MAAMA,SAAQ,SAAS,GAAG;AAC5B,iCAAuB,QAAQ,IAAI,IAAI,aAAa,SAAS,IAAI,QAAQA,SAAQ;AAAA,QACnF,OAAO;AACL,iCAAuB,QAAQ,aAAa,SAAS,IAAI,QAAQA,SAAQ;AAAA,QAC3E;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACA,QAAM,aAAa,CAAC;AACpB,WAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,eAAW,KAAK,IAAI,IAAI;AAAA,EAC1B;AACA,QAAM,QAAQ,mBAAmB,IAAI;AACrC,MAAI,UAAU,2BAA2B;AAAA,IACvC;AAAA;AAEF,MAAI,WAAW,WAAW,GAAG;AAC3B,eAAW,UAAU;AAAA,EACvB,OAAO;AACL,eAAW,UAAU,SAAS,WAAW,KAAK,GAAG;AAAA,EACnD;AACA,SAAO;AACT;AACA,SAAS,gCAAgC,SAAS;AAChD,MAAI,UAAU;AACd,UAAQ;AAAA,SACD;AAAA,SACA;AACH,iBAAW;AAAA;AAAA;AAAA;AAAA;AAKX;AAAA,SACG;AACH,iBAAW;AAAA;AAAA;AAAA;AAAA;AAKX;AAAA,SACG;AACH,iBAAW;AAAA;AAAA;AAAA;AAAA;AAKX;AAAA,SACG;AACH,iBAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAMX;AAAA,SACG;AACH,iBAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AASX;AAAA,SACG;AACH,iBAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUX;AAAA;AAEA,mBAAa,OAAO,OAAO,MAAM,eAAe,gBAAgB;AAChE;AAAA;AAEJ,SAAO;AACT;AACA,SAAS,eAAe,SAAS;AAC/B,SAAO,QAAQ,SAAS,OAAO,KAAK,QAAQ,SAAS,OAAO;AAC9D;AACA,SAAS,eAAe,MAAM,QAAQ;AACpC,MAAI,SAAS,WAAW;AACtB,WAAO,SAAS,cAAc;AAAA,EAChC,WAAW,SAAS,SAAS;AAC3B,WAAO,SAAS,cAAc;AAAA,EAChC,WAAW,SAAS,QAAQ;AAC1B,WAAO,SAAS,cAAc;AAAA,EAChC;AACA,SAAO;AACT;AACA,SAAS,iBAAiB,UAAU,eAAe,QAAQ;AACzD,QAAM,UAAU,SAAS;AACzB,QAAM,WAAW,eAAe,eAAe,MAAM;AACrD,MAAI;AACJ,MAAI,QAAQ;AACV,cAAU;AAAA,4BACc;AAAA;AAAA;AAAA,4BAGA;AAAA;AAAA,EAE1B,OAAO;AACL,cAAU;AAAA,4BACc;AAAA;AAAA;AAAA,4BAGA;AAAA;AAAA,EAE1B;AACA,MAAI,WAAW,GAAG;AAChB,UAAM,OAAO,CAAC,MAAM,MAAM,MAAM,MAAM,MAAM,IAAI,EAAE,MAAM,GAAG,OAAO;AAClE,UAAM,OAAO,mBAAmB,OAAO;AACvC,QAAI,QAAQ;AACV,iBAAW;AAAA,6BACY,KAAK,IAAI,CAAC,MAAM,GAAG,SAAS,EAAE,KAAK,IAAI;AAAA,mDACjB,QAAQ,KAAK,KAAK,IAAI;AAAA;AAAA;AAAA,gCAGzC,KAAK,IAAI,CAAC,MAAM,GAAG,SAAS,EAAE,KAAK,IAAI;AAAA,mDACpB,QAAQ,KAAK,KAAK,IAAI;AAAA;AAAA;AAAA;AAAA,IAIrE,OAAO;AACL,iBAAW;AAAA,6BACY,KAAK,IAAI,CAAC,MAAM,GAAG,SAAS,EAAE,KAAK,IAAI;AAAA,mDACjB,QAAQ,KAAK,KAAK,IAAI;AAAA;AAAA;AAAA,gCAGzC,KAAK,IAAI,CAAC,MAAM,GAAG,SAAS,EAAE,KAAK,IAAI;AAAA,mDACpB,QAAQ,KAAK,KAAK,IAAI;AAAA;AAAA;AAAA;AAAA,IAIrE;AAAA,EACF;AACA,SAAO;AACT;AAGA,IAAI,sBAAsB,CAAC;AAC3Bf,UAAS,qBAAqB;AAAA,EAC5B,yBAAyB,MAAM;AAAA,EAC/B,oBAAoB,MAAM;AAAA,EAC1B,mBAAmB,MAAM;AAAA,EACzB,iBAAiB,MAAM;AAAA,EACvB,+BAA+B,MAAM;AAAA,EACrC,+BAA+B,MAAM;AAAA,EACrC,+BAA+B,MAAM;AAAA,EACrC,oBAAoB,MAAM;AAAA,EAC1B,mBAAmB,MAAM;AAAA,EACzB,yBAAyB,MAAM;AACjC,CAAC;AACD,IAAI,eAAe,CAAC,QAAQ;AAC1B,MAAI,UAAU;AACd,WAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,MAAM;AACtC,eAAW,IAAI;AAAA,EACjB;AACA,SAAO;AACT;AACA,SAAS,wBAAwB,UAAU,OAAO;AAChD,MAAI,SAAS,WAAW,MAAM,QAAQ;AACpC,UAAM,IAAI,MAAM,+BAA+B,SAAS,qCAAqC,MAAM,kCAAkC;AAAA,EACvI;AACA,SAAO,MAAM,MAAM,CAAC,KAAK,WAAW,MAAM,SAAS,YAAY,CAAC;AAClE;AACA,SAAS,gBAAgB,QAAQ,aAAa,gBAAgB,CAAC,GAAG,GAAG,CAAC,GAAG,oBAAoB,CAAC,GAAG,GAAG,CAAC,GAAG;AACtG,QAAM,CAAC,WAAW,WAAW,SAAS,IAAI;AAAA,IACxC,KAAK,KAAK,aAAa,OAAO,EAAE,IAAI,CAAC,MAAM,YAAY,EAAE,CAAC,KAAK,cAAc,KAAK,kBAAkB,GAAG;AAAA,IACvG,OAAO,IAAI,KAAK,KAAK,aAAa,OAAO,EAAE,IAAI,CAAC,MAAM,YAAY,EAAE,CAAC,KAAK,cAAc,KAAK,kBAAkB,GAAG,IAAI;AAAA,IACtH,OAAO,IAAI,KAAK,KAAK,aAAa,OAAO,EAAE,IAAI,CAAC,MAAM,YAAY,EAAE,CAAC,KAAK,cAAc,KAAK,kBAAkB,GAAG,IAAI;AAAA,EACxH;AACA,SAAO,CAAC,WAAW,WAAW,SAAS;AACzC;AACA,SAAS,8BAA8B,QAAQ,aAAa,SAAS,OAAO;AAC1E,MAAI,QAAQ;AACV,WAAO,CAAC,GAAG,GAAG,CAAC;AAAA,EACjB;AACA,QAAM,OAAO,aAAa,OAAO,EAAE,IAAI,CAAC,MAAM,YAAY,EAAE,CAAC;AAC7D,QAAM,OAAO,aAAa,OAAO,EAAE,IAAI,CAAC,MAAM,YAAY,EAAE,CAAC;AAC7D,MAAI,QAAQ,GAAG;AACb,WAAO,CAAC,GAAG,IAAI,CAAC;AAAA,EAClB;AACA,MAAI,QAAQ,GAAG;AACb,WAAO,CAAC,IAAI,GAAG,CAAC;AAAA,EAClB;AACA,SAAO,CAAC,IAAI,IAAI,CAAC;AACnB;AACA,SAAS,8BAA8B,WAAW,UAAU,WAAW;AACrE,MAAI,cAAc,GAAG;AACnB,WAAO,CAAC,IAAI,GAAG,CAAC;AAAA,EAClB,WAAW,cAAc,GAAG;AAC1B,WAAO,CAAC,GAAG,IAAI,CAAC;AAAA,EAClB;AACA,SAAO,CAAC,GAAG,GAAG,CAAC;AACjB;AACA,SAAS,8BAA8B,QAAQ,aAAa,SAAS,OAAO;AAC1E,MAAI,QAAQ;AACV,WAAO,CAAC,GAAG,GAAG,CAAC;AAAA,EACjB;AACA,QAAM,OAAO,aAAa,OAAO,EAAE,IAAI,CAAC,MAAM,YAAY,EAAE,CAAC;AAC7D,QAAM,OAAO,aAAa,OAAO,EAAE,IAAI,CAAC,MAAM,YAAY,EAAE,CAAC;AAC7D,MAAI,QAAQ,GAAG;AACb,WAAO,CAAC,GAAG,GAAG,CAAC;AAAA,EACjB;AACA,MAAI,QAAQ,GAAG;AACb,WAAO,CAAC,GAAG,GAAG,CAAC;AAAA,EACjB;AACA,SAAO,CAAC,GAAG,GAAG,CAAC;AACjB;AACA,SAAS,mBAAmB,OAAO;AACjC,SAAO,EAAE,GAAG,MAAM,IAAI,CAAC,GAAG,OAAO,EAAE,EAAE;AACvC;AACA,SAAS,mBAAmB,OAAO;AACjC,MAAI,UAAU,aAAa,UAAU,WAAW,UAAU,UAAU,UAAU,UAAU;AACtF,WAAO;AAAA,EACT,WAAW,UAAU,aAAa;AAChC,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,iBAAiB,OAAO;AAAA,EAC1C;AACF;AACA,SAAS,wBAAwB,MAAM,OAAO;AAC5C,MAAI,UAAU,WAAW;AACvB,WAAO,IAAI,aAAa,IAAI;AAAA,EAC9B,WAAW,UAAU,SAAS;AAC5B,WAAO,IAAI,WAAW,IAAI;AAAA,EAC5B,WAAW,UAAU,UAAU,UAAU,UAAU;AACjD,WAAO,WAAW,KAAK,IAAI,WAAW,IAAI,CAAC;AAAA,EAC7C,OAAO;AACL,UAAM,IAAI,MAAM,iBAAiB,OAAO;AAAA,EAC1C;AACF;AACA,SAAS,oBAAoB;AAC3B,UAAQ,OAAO,WAAW,eAAe,OAAO,sBAAsB,gBAAgB,CAAC,CAAC,UAAU;AACpG;AACA,IAAI;AAAA,CACH,SAAS,oBAAoB;AAC5B,qBAAmB,mBAAmB,6BAA6B,KAAK;AACxE,qBAAmB,mBAAmB,yBAAyB,KAAK;AACpE,qBAAmB,mBAAmB,yBAAyB,KAAK;AACpE,qBAAmB,mBAAmB,kCAAkC,KAAK;AAC7E,qBAAmB,mBAAmB,yBAAyB,KAAK;AACpE,qBAAmB,mBAAmB,eAAe,KAAK;AAC5D,GAAG,sBAAsB,oBAAoB,CAAC,EAAE;AAGhD,SAAS,mBAAmB,gBAAgB,gBAAgB,YAAY,YAAY,YAAY,OAAO,YAAY,OAAO,WAAW,OAAO,YAAY,GAAG;AACzJ,eAAa,OAAO,cAAc,cAAc,KAAK,CAAC,YAAY,MAAM,cAAc,oDAAoD,WAAW;AACrJ,QAAM,UAAU;AAAA,oBACE,iBAAiB,MAAM;AAAA;AAAA,QAEnC,aAAa,qEAAqE,gBAAgB,qEAAqE;AAAA;AAAA;AAG7K,MAAI;AACJ,MAAI,eAAe,OAAO;AACxB,cAAU,qEAAqE;AAAA,EACjF,OAAO;AACL,cAAU,qEAAqE;AAAA,EACjF;AACA,SAAO;AAAA,uDAC8C,YAAY,SAAS;AAAA,kBAC1D,YAAY,SAAS;AAAA,wBACf;AAAA,MAClB,aAAa,WAAW,UAAU;AAAA,MAClC,aAAa,4DAA4D;AAAA;AAAA,QAEvE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,uDAM+C,YAAY,SAAS;AAAA,wBACpD;AAAA,kBACN,iBAAiB,MAAM;AAAA;AAAA,kBAEvB,YAAY,SAAS;AAAA,MACjC;AAAA;AAAA;AAAA;AAIN;AACA,SAAS,wBAAwB,SAAS,aAAa,gBAAgB,gBAAgB,YAAY,YAAY,YAAY,OAAO,YAAY,OAAO,WAAW,OAAO,YAAY,GAAG;AACpL,SAAO;AAAA,IACL,mBAAmB,gBAAgB,gBAAgB,YAAY,YAAY,WAAW,WAAW,UAAU,SAAS;AAAA,2DAC7D,YAAY,SAAS;AAAA,wBACxD;AAAA,MAClB,aAAa,YAAY,KAAK;AAAA;AAAA;AAAA;AAAA,QAI5B,sBAAsB,SAAS,WAAW;AAAA;AAAA;AAAA;AAAA;AAKlD;AACA,IAAI,yBAAyB,CAAC,eAAe;AAC3C,MAAI,YAAY;AACd,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA,EAKT,OAAO;AACL,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA,EAKT;AACF;AACA,IAAI,0BAA0B,CAAC,eAAe;AAC5C,SAAO,aAAa,kDAAkD;AACxE;AACA,SAAS,uBAAuB,eAAe,eAAe,aAAa,OAAO,YAAY,IAAI;AAChG,QAAM,aAAa,cAAc,KAAK,cAAc;AACpD,QAAM,aAAa,cAAc,KAAK,cAAc;AACpD,QAAM,aAAa,aAAa,aAAa;AAC7C,QAAM,aAAa,aAAa,YAAY;AAC5C,eAAa,OAAO,aAAa,cAAc,OAAO,KAAK,aAAa,cAAc,OAAO,KAAK,YAAY,cAAc,OAAO,GAAG,MAAM,cAAc,mDAAmD,cAAc,kBAAkB,mDAAmD,cAAc,iBAAiB,kDAAkD,cAAc,IAAI;AACnY,QAAM,gBAAgB,aAAa,cAAc;AACjD,QAAM,gBAAgB,aAAa,cAAc;AACjD,QAAM,gBAAgB,YAAY,cAAc;AAChD,SAAO;AAAA,gDACuC,gBAAgB;AAAA,gDAChB,gBAAgB;AAAA,2BACrC,cAAc;AAAA,2BACd,cAAc;AAAA,wBACjB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kDAiB0B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,wCAaV;AAAA,wCACA;AAAA,wCACA;AAAA;AAAA;AAAA;AAAA,4CAII;AAAA,8CACE;AAAA;AAAA;AAAA,cAGhC,uBAAuB,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA,4CAKH;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAoB9B,wBAAwB,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAkBhD;AACA,IAAI,qBAAqB,CAAC,eAAe;AACvC,SAAO,aAAa;AAAA;AAAA;AAAA;AAAA;AAAA,MAKhB;AAAA;AAAA;AAAA;AAAA;AAAA;AAMN;AACA,SAAS,8BAA8B,eAAe,aAAa,OAAO;AACxE,eAAa,OAAO,cAAc,OAAO,KAAK,cAAc,OAAO,GAAG,MAAM,iDAAiD,gBAAgB;AAC7I,SAAO;AAAA,uBACc,cAAc,KAAK;AAAA,gDACM,cAAc;AAAA;AAAA,MAExD,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,uCAca,mBAAmB,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAqBpE;AACA,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,QAAQ,aAAa,eAAe,gBAAgB,gBAAgB,aAAa,OAAO,aAAa,OAAO,OAAO,MAAM,cAAc,MAAM,yBAAyB,MAAM;AACtL,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,IAAI,CAAC;AAC/B,SAAK,cAAc;AACnB,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE;AAC/C,UAAM,WAAW,aAAa,OAAO,KAAK,OAAO;AACjD,SAAK,gBAAgB,8BAA8B,YAAY,IAAI,UAAU,YAAY,EAAE;AAC3F,QAAI,YAAY,OAAO,KAAK,YAAY,OAAO,GAAG;AAChD,sBAAgB;AAAA,IAClB;AACA,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,eAAe,eAAe,CAAC,CAAC;AAC5H,QAAI,aAAa,YAAY,KAAK,UAAU,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG;AACtD,sBAAgB;AAChB,WAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,eAAe,eAAe,CAAC,CAAC;AAAA,IAC9H;AACA,UAAM,UAAU,QAAQ;AACxB,UAAM,4BAA4B,0BAA0B;AAC5D,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,2BAA2B;AAC7B,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,gBAAgB;AACrB,SAAK,aAAa;AAClB,SAAK,aAAa;AAClB,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,4BAA4B;AACjC,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AACtB,KAAC,KAAK,WAAW,KAAK,WAAW,KAAK,QAAQ,IAAI,KAAK,YAAY,YAAY,IAAI,YAAY,IAAI,QAAQ;AAC3G,SAAK,YAAY,gBAAgB,KAAK,iBAAiB,cAAc,cAAc,KAAK,cAAc,KAAK,aAAa,KAAK,aAAa,KAAK,YAAY,KAAK,YAAY,KAAK,KAAK,KAAK,kBAAkB,KAAK;AAAA,EACpN;AAAA,EACA,YAAY,WAAW,WAAW,UAAU;AAC1C,UAAM,aAAa,KAAK,cAAc,KAAK,KAAK;AAChD,UAAM,aAAa,KAAK,cAAc,KAAK,KAAK;AAChD,SAAK,YAAY;AACjB,QAAI,KAAK,YAAY,OAAO,GAAG;AAC7B,WAAK,YAAY,KAAK,cAAc,KAAK;AAAA,IAC3C;AACA,UAAM,YAAY,YAAY,eAAe;AAC7C,UAAM,YAAY,YAAY,eAAe;AAC7C,UAAM,WAAW,WAAW,KAAK,cAAc;AAC/C,WAAO,CAAC,WAAW,WAAW,QAAQ;AAAA,EACxC;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,oBAAoB,KAAK,YAAY,KAAK,yBAAyB;AAAA,QACnE,wBAAwB,KAAK,SAAS,KAAK,YAAY,KAAK,gBAAgB,KAAK,gBAAgB,OAAO,KAAK,YAAY,KAAK,WAAW,KAAK,WAAW,KAAK,QAAQ;AAAA,QACtK,KAAK,YAAY,KAAK,IAAI,uBAAuB,CAAC,KAAK,eAAe,KAAK,eAAe,CAAC,GAAG,KAAK,eAAe,KAAK,YAAY,KAAK,SAAS,IAAI,8BAA8B,KAAK,eAAe,KAAK,UAAU;AAAA;AAE1N,WAAO;AAAA,EACT;AACF;AAGA,IAAI,0BAA0B,CAAC,YAAY,sBAAsB;AAC/D,MAAI,YAAY;AACd,WAAO;AAAA;AAAA;AAAA,6BAGkB;AAAA;AAAA,EAE3B,OAAO;AACL,WAAO;AAAA;AAAA;AAAA,4BAGiB;AAAA;AAAA,EAE1B;AACF;AACA,IAAI,yBAAyB,CAAC,YAAY,qBAAqB;AAC7D,MAAI,YAAY;AACd,WAAO;AAAA;AAAA;AAAA;AAAA,UAID,qBAAqB,IAAI,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA,YAK5B,qBAAqB,IAAI,KAAK;AAAA;AAAA,EAExC,OAAO;AACL,WAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAMC,qBAAqB,IAAI,KAAK;AAAA;AAAA,EAExC;AACF;AACA,SAAS,2BAA2B,eAAe,YAAY,YAAY,WAAW,mBAAmB,GAAG,aAAa,OAAO;AAC9H,QAAM,aAAa,aAAa,aAAa;AAC7C,QAAM,aAAa,aAAa,YAAY;AAC5C,QAAM,oBAAoB,aAAa,cAAc,KAAK;AAC1D,eAAa,QAAQ,cAAc,eAAe,eAAe,YAAY,MAAM,KAAK,YAAY,MAAM,OAAO,cAAc,OAAO,MAAM,qBAAqB,KAAK,qBAAqB,IAAI,MAAM,aAAa,oDAAoD,cAAc;AAAA,8BACxP,+BAA+B;AAC3D,SAAO;AAAA,4CACmC,2BAA2B,aAAa,uBAAuB;AAAA,oDACvD,aAAa,cAAc,QAAQ;AAAA;AAAA,yBAE9D,cAAc;AAAA,yBACd,cAAc;AAAA,6BACV;AAAA,sBACP;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oBAYF,eAAe,IAAI,MAAM;AAAA;AAAA;AAAA,sBAGvB,eAAe,IAAI,MAAM;AAAA;AAAA;AAAA,gDAGC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAelC,wBAAwB,YAAY,iBAAiB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAiBrD,qBAAqB,IAAI,KAAK;AAAA;AAAA,cAE9B,uBAAuB,YAAY,gBAAgB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUjE;AACA,IAAI,0BAA0B,MAAM;AAAA,EAClC,YAAY,QAAQ,aAAa,gBAAgB,gBAAgB,aAAa,OAAO,OAAO,MAAM,cAAc,MAAM,yBAAyB,MAAM;AACnJ,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,GAAG,GAAG,CAAC;AAC7B,SAAK,SAAS;AACd,SAAK,cAAc;AACnB,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE;AAC/C,QAAI,YAAY,OAAO,KAAK,CAAC,YAAY;AACvC,WAAK,oBAAoB,CAAC,GAAG,GAAG,CAAC;AAAA,IACnC,OAAO;AACL,WAAK,oBAAoB,CAAC,GAAG,GAAG,CAAC;AAAA,IACnC;AACA,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,KAAK,iBAAiB;AACjH,UAAM,UAAU,QAAQ;AACxB,UAAM,4BAA4B,0BAA0B;AAC5D,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,2BAA2B;AAC7B,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,aAAa,YAAY,OAAO,KAAK,CAAC,aAAa,IAAI,KAAK,cAAc,KAAK,KAAK,kBAAkB;AAC3G,SAAK,aAAa,KAAK,cAAc,KAAK,KAAK,kBAAkB;AACjE,SAAK,YAAY,KAAK;AACtB,SAAK,SAAS;AACd,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,4BAA4B;AACjC,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AACtB,SAAK,aAAa;AAClB,UAAM,WAAW,aAAa,OAAO,KAAK,OAAO;AACjD,SAAK,YAAY,YAAY,KAAK,KAAK,eAAe;AACtD,SAAK,YAAY,YAAY,KAAK,KAAK,eAAe;AACtD,SAAK,WAAW,WAAW,KAAK,cAAc;AAC9C,SAAK,YAAY,oBAAoB,KAAK,cAAc,KAAK,aAAa,KAAK,aAAa,KAAK,YAAY,KAAK,qBAAqB,KAAK,kBAAkB,KAAK,kBAAkB,KAAK;AAAA,EAC5L;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,oBAAoB,KAAK,YAAY,KAAK,2BAA2B,IAAI;AAAA,QACzE,wBAAwB,KAAK,SAAS,KAAK,YAAY,KAAK,gBAAgB,KAAK,gBAAgB,OAAO,OAAO,KAAK,WAAW,KAAK,WAAW,KAAK,UAAU,CAAC;AAAA,QAC/J,2BAA2B,KAAK,mBAAmB,KAAK,YAAY,KAAK,YAAY,KAAK,WAAW,GAAG,KAAK,UAAU;AAAA;AAE3H,WAAO;AAAA,EACT;AACF;AAGA,SAAS,yBAAyB;AAChC,SAAO;AAAA;AAAA,MAEH,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AA8B1B;AACA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,aAAa,gBAAgB,gBAAgB,aAAa,OAAO,aAAa,OAAO,OAAO,MAAM,cAAc,MAAM,yBAAyB,MAAM;AAC/J,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,cAAc;AACnB,SAAK,iBAAiB,EAAE,GAAG,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE;AACjD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,UAAM,UAAU,QAAQ;AACxB,UAAM,4BAA4B,0BAA0B;AAC5D,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,2BAA2B;AAC7B,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,aAAa;AAClB,SAAK,aAAa;AAClB,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,4BAA4B;AACjC,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AACtB,SAAK,YAAY,gBAAgB,KAAK,cAAc,cAAc,cAAc,KAAK,kBAAkB,KAAK;AAAA,EAC9G;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,oBAAoB,KAAK,YAAY,KAAK,yBAAyB;AAAA,QACnE,wBAAwB,KAAK,SAAS,KAAK,YAAY,KAAK,gBAAgB,KAAK,gBAAgB,KAAK,YAAY,KAAK,UAAU;AAAA,QACjI,uBAAuB;AAAA;AAE3B,WAAO;AAAA,EACT;AACF;AAGA,SAAS,gCAAgC,eAAe;AACtD,QAAM,aAAa,cAAc;AACjC,QAAM,aAAa,cAAc;AACjC,QAAM,YAAY,aAAa,aAAa,aAAa;AACzD,SAAO;AAAA,8CACqC,eAAe;AAAA,8CACf,gBAAgB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAQ1D,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,+CAQuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAQf;AAAA,gCACA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,kCAYE;AAAA,kCACA;AAAA;AAAA,4BAEN;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAS5B;AACA,IAAI,+BAA+B,MAAM;AAAA,EACvC,YAAY,QAAQ,QAAQ,aAAa,aAAa,OAAO,aAAa,OAAO,OAAO,MAAM,cAAc,MAAM,yBAAyB,MAAM;AAC/I,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,cAAc;AACnB,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE;AAC/C,SAAK,WAAW;AAAA,MACd,KAAK,KAAK,YAAY,KAAK,KAAK,cAAc,EAAE;AAAA,MAChD,KAAK,KAAK,YAAY,KAAK,KAAK,cAAc,EAAE;AAAA,MAChD,YAAY;AAAA,IACd;AACA,UAAM,UAAU,QAAQ;AACxB,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,UAAM,4BAA4B,0BAA0B;AAC5D,QAAI,2BAA2B;AAC7B,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,aAAa;AAClB,SAAK,aAAa;AAClB,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,4BAA4B;AACjC,SAAK,iBAAiB,OAAO,OAAO;AACpC,SAAK,iBAAiB,OAAO,OAAO;AACpC,SAAK,YAAY,yBAAyB,KAAK,cAAc,cAAc,cAAc,KAAK,kBAAkB,KAAK;AAAA,EACvH;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,oBAAoB,KAAK,YAAY,KAAK,yBAAyB;AAAA,QACnE,wBAAwB,KAAK,SAAS,KAAK,YAAY,KAAK,gBAAgB,KAAK,gBAAgB,KAAK,YAAY,KAAK,UAAU;AAAA,QACjI,gCAAgC,KAAK,aAAa;AAAA;AAEtD,WAAO;AAAA,EACT;AACF;AAGA,IAAI,sBAAsB,MAAM;AAAA,EAC9B,YAAY,aAAa,UAAU,gBAAgB,gBAAgB,aAAa,OAAO,aAAa,OAAO;AACzG,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,GAAG,GAAG,CAAC;AAC7B,SAAK,SAAS;AACd,SAAK,YAAY;AACjB,iBAAa,OAAO,YAAY,OAAO,GAAG,MAAM,8CAA8C;AAC9F,SAAK,cAAc;AACnB,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,EAAE;AAClD,SAAK,oBAAoB,CAAC,GAAG,GAAG,KAAK,SAAS;AAC9C,QAAI,KAAK,YAAY,KAAK,IAAI;AAC5B,WAAK,kBAAkB,KAAK;AAAA,IAC9B;AACA,QAAI,KAAK,YAAY,KAAK,IAAI;AAC5B,WAAK,kBAAkB,KAAK;AAAA,IAC9B;AACA,SAAK,WAAW,gBAAgB,KAAK,gBAAgB;AAAA,MACnD,KAAK,YAAY;AAAA,MACjB,KAAK,YAAY;AAAA,MACjB,KAAK,YAAY;AAAA,MACjB;AAAA,IACF,GAAG,KAAK,eAAe,KAAK,iBAAiB;AAC7C,SAAK,aAAa;AAClB,SAAK,aAAa;AAClB,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AACtB,SAAK,YAAY,gBAAgB,cAAc,cAAc,kBAAkB,kBAAkB,KAAK;AAAA,EACxG;AAAA,EACA,cAAc;AACZ,UAAM,mBAAmB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWzB,UAAM,WAAW;AAAA,QACb,mBAAmB,KAAK,gBAAgB,KAAK,gBAAgB,KAAK,YAAY,KAAK,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAQzF;AAAA;AAAA;AAAA;AAAA,QAIJ,KAAK,uBAAuB;AAAA;AAEhC,WAAO;AAAA,EACT;AAAA,EACA,yBAAyB;AACvB,UAAM,aAAa,KAAK,cAAc,KAAK,KAAK,kBAAkB;AAClE,UAAM,aAAa,KAAK,cAAc,KAAK,KAAK,kBAAkB;AAClE,UAAM,eAAe,KAAK,kBAAkB;AAC5C,UAAM,eAAe,KAAK,kBAAkB;AAC5C,UAAM,gBAAgB,KAAK,YAAY,KAAK,cAAc;AAC1D,UAAM,gBAAgB,KAAK,YAAY,KAAK,cAAc;AAC1D,iBAAa,OAAO,KAAK,YAAY,KAAK,cAAc,OAAO,KAAK,KAAK,YAAY,KAAK,cAAc,OAAO,GAAG,MAAM,aAAa,KAAK,kDAAkD,KAAK,cAAc,0BAA0B,KAAK,cAAc,IAAI;AAChQ,WAAO;AAAA,kDACuC,KAAK,eAAe;AAAA,kDACpB,gBAAgB,KAAK;AAAA,QAC/D,oBAAoB;AAAA,yCACa;AAAA,yCACA;AAAA;AAAA,4CAEG;AAAA,4CACA;AAAA;AAAA,yCAEH,KAAK;AAAA;AAAA;AAAA,0CAGJ;AAAA,4CACE;AAAA,8CACE;AAAA;AAAA;AAAA,qDAGO,KAAK,iBAAiB,IAAI;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0CAMrC;AAAA,4CACE;AAAA,8CACE;AAAA;AAAA;AAAA,qDAGO,KAAK,iBAAiB,IAAI;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,qCAQ1C,kBAAkB;AAAA;AAAA,8BAEzB,KAAK;AAAA,qCACE;AAAA,wCACG;AAAA;AAAA;AAAA;AAAA,8CAIM;AAAA;AAAA,gDAEE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,4CAMJ;AAAA,8CACE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAM5C;AACF;AACA,IAAI,wBAAwB,MAAM;AAAA,EAChC,YAAY,aAAa,OAAO,MAAM,cAAc,MAAM,yBAAyB,MAAM;AACvF,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,UAAU,QAAQ;AACvB,SAAK,4BAA4B,0BAA0B;AAC3D,SAAK,aAAa;AAClB,QAAI,KAAK,SAAS;AAChB,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,KAAK,2BAA2B;AAClC,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,YAAY,kBAAkB;AAAA,EACrC;AAAA,EACA,cAAc;AACZ,WAAO;AAAA,MACL,oBAAoB,KAAK,YAAY,KAAK,yBAAyB;AAAA,MACnE,kCAAkC;AAAA;AAAA;AAAA;AAAA,UAI9B,sBAAsB,KAAK,SAAS,KAAK,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA,EAK3D;AACF;AAGA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,OAAO;AACjB,SAAK,gBAAgB,CAAC;AACtB,SAAK,cAAc,CAAC;AACpB,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,MACf,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAMpC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,IAAI;AACzB,MAAI,EAAE,MAAM,IAAI;AAChB,UAAQ,SAAS,aAAa,WAAW,KAAK;AAC9C,MAAI,UAAU,UAAU;AACtB,UAAM,SAAS,aAAa,kBAAkB,OAAO,aAAa,cAAc,KAAK,CAAC;AACtF,WAAO,KAAK,KAAK;AACjB,WAAO,SAAS,eAAe,OAAO,OAAO,MAAM;AAAA,EACrD,OAAO;AACL,UAAM,UAAU,IAAI,aAAa,KAAK;AACtC,UAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,KAAK,EAAE,CAAC;AACvD,WAAO,SAAS,iBAAiB,SAAS,CAAC,GAAG,OAAO,WAAW;AAAA,EAClE;AACF;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,MAAM,IAAI;AAC1B,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,QAAQ,aAAa,cAAc,EAAE,KAAK;AAChD,QAAM,SAAS,aAAa,uBAAuB,OAAO,KAAK;AAC/D,QAAM,SAAS,aAAa,cAAc,MAAM;AAChD,eAAa,OAAO,UAAU,QAAQ,MAAM,kBAAkB,eAAe,sCAAsC,EAAE,cAAc,oFAAoF;AACvN,OAAK,QAAQ,OAAO,EAAE,MAAM;AAC5B,SAAO,EAAE,QAAQ,EAAE,QAAQ,OAAO,QAAQ,OAAO,EAAE,MAAM;AAC3D;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,iBAAiB,EAAE,GAAG,GAAG,YAAY,YAAY,SAAS,UAAU,OAAO,MAAM,yBAAyB,MAAM,iBAAiB,GAAG,YAAY,cAAc,KAAK,GAAG;AAC7K,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,cAAc,aAAa,EAAE,MAAM,QAAQ,KAAK,EAAE,MAAM,QAAQ;AACtE,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,aAAa,EAAE,MAAM,MAAM,GAAG,EAAE;AACtC,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,YAAY,aAAa,cAAc,UAAU;AACvD,QAAM,oBAAoB,uBAAuB,2BAA2B,EAAE,MAAM,MAAM,GAAG,EAAE,GAAG,EAAE,MAAM,MAAM,GAAG,EAAE,CAAC;AACtH,QAAM,WAAW,kBAAkB,OAAO,CAAC,aAAa,WAAW,CAAC;AACpE,eAAa,OAAO,gBAAgB,aAAa,MAAM,kCAAkC,qBAAqB,uCAAuC,EAAE,aAAa,EAAE,wBAAwB,6BAA6B,wBAAwB;AACnP,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,WAAW,aAAa,CAAC,WAAW,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,WAAW;AAC1G,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACxF,QAAM,gBAAgB,CAAC,KAAK,GAAG;AAC/B,QAAM,WAAW,KAAK,IAAI,WAAW,SAAS;AAC9C,QAAM,iBAAiB,cAAc;AACrC,QAAM,iBAAiB,cAAc;AACrC,QAAM,WAAW,cAAc,MAAM,KAAK,CAAC,cAAc,cAAc,MAAM,KAAK,eAAe,cAAc,MAAM,KAAK,CAAC;AAC3H,QAAM,SAAS,CAAC,KAAK,GAAG;AACxB,QAAM,aAAa;AAAA,IACjB,EAAE,MAAM,SAAS,MAAM,CAAC,WAAW,EAAE;AAAA,IACrC,EAAE,MAAM,SAAS,MAAM,CAAC,WAAW,EAAE;AAAA,IACrC,EAAE,MAAM,SAAS,MAAM,CAAC,WAAW,EAAE;AAAA,EACvC;AACA,MAAI;AACJ,MAAI;AACJ,QAAM,cAAc,CAAC,UAAU,aAAa,WAAW;AACvD,MAAI,oBAAoB,IAAI,EAAE,IAAI,4BAA4B;AAC9D,MAAI,oBAAoB,GAAG;AACzB,QAAI,cAAc,eAAe,KAAK;AACpC,0BAAoB,kBAAkB;AAAA,IACxC,WAAW,aAAa,KAAK,eAAe,OAAO,eAAe,MAAM,eAAe,KAAK;AAC1F,0BAAoB,kBAAkB;AAAA,IACxC,WAAW,eAAe,OAAO,eAAe,OAAO,eAAe,IAAI,gBAAgB,eAAe,OAAO,eAAe,OAAO,eAAe,IAAI,cAAc;AACrK,0BAAoB,kBAAkB;AAAA,IACxC,WAAW,SAAS;AAClB,0BAAoB,kBAAkB;AAAA,IACxC,OAAO;AACL,0BAAoB,kBAAkB;AAAA,IACxC;AAAA,EACF;AACA,UAAQ;AAAA,SACD,kBAAkB;AACrB,gBAAU,IAAI,wBAAwB,UAAU,aAAa,gBAAgB,gBAAgB,YAAY,MAAM,aAAa,sBAAsB;AAClJ;AAAA,SACG,kBAAkB;AACrB,gBAAU,IAAI,oBAAoB,aAAa,gBAAgB,gBAAgB,YAAY,YAAY,MAAM,aAAa,sBAAsB;AAChJ;AAAA,SACG,kBAAkB,qBAAqB;AAC1C,YAAM,MAAM,EAAE,SAAS,UAAU,OAAO,EAAE,OAAO,aAAa,OAAO,GAAG,OAAO,EAAE,MAAM,EAAE,CAAC;AAC1F,gBAAU,IAAI,oBAAoB,aAAa,aAAa,gBAAgB,gBAAgB,YAAY,UAAU;AAClH,UAAI,QAAQ,aAAa;AACvB,cAAM,SAAS,iBAAiB,SAAS,QAAQ,EAAE,OAAO,YAAY,GAAG;AACzE,cAAM,wBAAwB,IAAI,sBAAsB,IAAI,OAAO,MAAM,aAAa,sBAAsB;AAC5G,YAAI,cAAc;AAClB,cAAM,mBAAmB,CAAC,GAAG;AAC7B,YAAI,MAAM;AACR,2BAAiB,KAAK,IAAI;AAAA,QAC5B;AACA,YAAI,wBAAwB;AAC1B,2BAAiB,KAAK,sBAAsB;AAAA,QAC9C;AACA,YAAI,gBAAgB,aAAa;AAC/B,wBAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,cAAc,EAAE,CAAC;AAC1D,gCAAsB,YAAY;AAAA,QACpC;AACA,cAAM,eAAe,SAAS,iBAAiB,uBAAuB,kBAAkB,IAAI,OAAO,WAAW;AAC9G,sBAAc,KAAK,GAAG;AACtB,cAAM,eAAe,SAAS,EAAE,QAAQ,EAAE,GAAG,aAAa,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC5G,sBAAc,KAAK,YAAY;AAC/B,mBAAW,MAAM,eAAe;AAC9B,mBAAS,YAAY,GAAG,MAAM;AAAA,QAChC;AACA,eAAO;AAAA,MACT;AACA;AAAA,IACF;AAAA,SACK,kBAAkB;AACrB,gBAAU,IAAI,6BAA6B,UAAU,UAAU,aAAa,YAAY,YAAY,MAAM,aAAa,sBAAsB;AAC7I;AAAA,SACG,kBAAkB;AACrB,gBAAU,IAAI,qBAAqB,UAAU,aAAa,IAAI,EAAE,IAAI,+BAA+B,GAAG,gBAAgB,gBAAgB,YAAY,YAAY,MAAM,aAAa,sBAAsB;AACvM;AAAA;AAEA,YAAM,IAAI,MAAM,iCAAiC,oBAAoB;AAAA;AAEzE,MAAI,MAAM;AACR,WAAO,KAAK,IAAI;AAAA,EAClB;AACA,MAAI,wBAAwB;AAC1B,WAAO,KAAK,sBAAsB;AAAA,EACpC;AACA,MAAI,gBAAgB,aAAa;AAC/B,eAAW,KAAK,EAAE,MAAM,WAAW,MAAM,CAAC,cAAc,EAAE,CAAC;AAC3D,YAAQ,YAAY;AAAA,EACtB;AACA,QAAM,SAAS,iBAAiB,SAAS,QAAQ,EAAE,OAAO,YAAY,GAAG;AACzE,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAClG,gBAAc,KAAK,GAAG;AACtB,aAAW,MAAM,eAAe;AAC9B,aAAS,YAAY,GAAG,MAAM;AAAA,EAChC;AACA,SAAO;AACT;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,GAAG,MAAM,uBAAuB,IAAI;AAC/C,QAAM,EAAE,YAAY,YAAY,YAAY,aAAa,eAAe,IAAI;AAC5E,SAAO,iBAAiB;AAAA,IACtB;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA,SAAS;AAAA,IACT;AAAA,IACA;AAAA,IACA;AAAA,IACA,YAAY;AAAA,EACd,CAAC;AACH;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,0BAA0B,MAAM;AAAA,EAClC,YAAY,KAAK,QAAQ,QAAQ;AAC/B,SAAK,gBAAgB,CAAC,SAAS,SAAS,SAAS,OAAO;AACxD,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,OAAO;AACZ,SAAK,cAAc,qBAAqB,2BAA2B,QAAQ,MAAM;AACjF,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY,mBAAmB;AACpC,SAAK,KAAK;AAAA,EACZ;AAAA,EACA,cAAc;AACZ,UAAM,QAAQ,kBAAkB,KAAK,IAAI,KAAK;AAC9C,UAAM,WAAW;AAAA;AAAA;AAAA,UAGX;AAAA;AAAA;AAAA,QAGF,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAUtC,WAAO;AAAA,EACT;AACF;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,KAAK,QAAQ,QAAQ;AAC/B,SAAK,OAAO;AACZ,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,cAAc,qBAAqB,2BAA2B,QAAQ,MAAM;AACjF,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,KAAK;AACV,SAAK,uBAAuB,OAAO,WAAW,KAAK,OAAO,SAAS,KAAK,OAAO,KAAK;AACpF,SAAK,uBAAuB,OAAO,WAAW,KAAK,OAAO,SAAS,KAAK,OAAO,KAAK;AACpF,QAAI,KAAK,wBAAwB,KAAK,sBAAsB;AAC1D,WAAK,SAAS;AACd,WAAK,oBAAoB,KAAK,uBAAuB,OAAO,KAAK,OAAO;AACxE,WAAK,YAAY,UAAU,KAAK,QAAQ,OAAO,KAAK,qBAAqB,KAAK;AAC9E,WAAK,OAAO;AACZ,WAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,UAAI,KAAK,oBAAoB,KAAK;AAChC,aAAK,gBAAgB;AAAA,MACvB,WAAW,KAAK,oBAAoB,KAAK;AACvC,aAAK,gBAAgB;AAAA,MACvB,OAAO;AACL,aAAK,gBAAgB;AAAA,MACvB;AAAA,IACF,OAAO;AACL,UAAI,aAAa,YAAY,QAAQ,MAAM,KAAK,aAAa,cAAc,MAAM,IAAI,MAAM,GAAG;AAC5F,aAAK,SAAS;AACd,aAAK,OAAO;AACZ,aAAK,gBAAgB;AAAA,MACvB,OAAO;AACL,aAAK,SAAS;AACd,aAAK,OAAO;AACZ,aAAK,gBAAgB;AAAA,MACvB;AACA,WAAK,YAAY,UAAU,KAAK,QAAQ;AACxC,WAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAAA,IACjC;AACA,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,KAAK,eAAe,GAAG,CAAC,CAAC;AAAA,EACvH;AAAA,EACA,cAAc;AACZ,QAAI;AACJ,QAAI,KAAK,SAAS,UAAU;AAC1B,YAAM,qBAAqB,KAAK,oBAAoB,IAAI,UAAU,KAAK,YAAY,SAAS,OAAO;AACnG,YAAM,oBAAoB,KAAK,uBAAuB;AAAA,8BAC9B,yBAAyB,qBAAqB;AAAA;AAEtE,YAAM,QAAQ,kBAAkB,KAAK,IAAI,KAAK,MAAM;AACpD,iBAAW;AAAA;AAAA,YAEL;AAAA;AAAA,gDAEoC,KAAK;AAAA,UAC3C,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA,8DAKkB,KAAK,gDAAgD,KAAK,cAAc;AAAA,0CAC5F,KAAK,uBAAuB,MAAM;AAAA;AAAA;AAAA;AAAA,+BAI7C,KAAK;AAAA,sCACE,KAAK;AAAA;AAAA;AAAA;AAAA,gBAI3B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAMZ,OAAO;AACL,YAAM,QAAQ,KAAK,SAAS,SAAS,cAAc;AACnD,YAAM,QAAQ,kBAAkB,KAAK,IAAI,KAAK,MAAM;AACpD,iBAAW;AAAA,gCACe,cAAc,aAAa;AAAA,WAChD;AAAA;AAAA,SAEF,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAQvC;AACA,WAAO;AAAA,EACT;AACF;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,EAAE,IAAI;AACd,OAAK,QAAQ,OAAO,EAAE,MAAM;AAC5B,SAAO,EAAE,QAAQ,EAAE,QAAQ,OAAO,EAAE,OAAO,OAAO,EAAE,MAAM;AAC5D;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,MAAM,OAAO,MAAM,MAAM,IAAI;AACrC,QAAM,cAAc,SAAS,eAAe,MAAM,OAAO,WAAW;AACpE,QAAM,WAAW,SAAS,UAAU,IAAI,YAAY,MAAM;AAC1D,QAAM,iBAAiB,UAAU,EAAE,QAAQ,EAAE,GAAG,MAAM,GAAG,SAAS,SAAS,CAAC;AAC5E,QAAM,iBAAiB,UAAU,EAAE,QAAQ,EAAE,GAAG,MAAM,GAAG,SAAS,SAAS,CAAC;AAC5E,WAAS,qBAAqB,EAAE,MAAM,gBAAgB,MAAM,eAAe;AAC3E,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,YAAY,aAAa,KAAK;AAC5B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,OAAO;AACZ,UAAM,iBAAiB;AACvB,SAAK,gBAAgB,CAAC,gBAAgB,GAAG,CAAC;AAC1C,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,KAAK;AACV,SAAK,YAAY,SAAS;AAAA,EAC5B;AAAA,EACA,cAAc;AACZ,WAAO;AAAA;AAAA,UAED,iBAAiB,KAAK,IAAI,KAAK;AAAA;AAAA,QAEjC,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAOxC;AACF;AAGA,SAAS,iBAAiB,EAAE,QAAQ,eAAe,MAAM,GAAG;AAC1D,SAAO,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AACxC,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,gBAAgB;AACtB,UAAM,SAAS,SAAS,EAAE;AAC1B,QAAI,cAAc,mBAAmB,CAAC,CAAC,CAAC,KAAK,iBAAiB,MAAM;AAClE,YAAM,QAAQ,cAAc,UAAU,IAAI,EAAE,MAAM;AAClD,YAAM,YAAY,cAAc,MAAM,QAAQ,MAAM;AACpD,aAAO,cAAc,eAAe,EAAE,OAAO,QAAQ,SAAS;AAAA,IAChE;AACA,UAAM,UAAU,IAAI,gBAAgB,EAAE,OAAO,MAAM;AACnD,WAAO,cAAc,iBAAiB,SAAS,CAAC,CAAC,GAAG,MAAM;AAAA,EAC5D;AACF;AACA,SAAS,kBAAkB,EAAE,QAAQ,eAAe,kBAAkB,OAAO,MAAM,GAAG;AACpF,SAAO,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AACxC,UAAM,EAAE,GAAG,EAAE,IAAI;AACjB,UAAM,gBAAgB;AACtB,QAAI,mBAAmB,EAAE,UAAU,aAAa;AAC9C,YAAM,QAAQ,cAAc,UAAU,IAAI,EAAE,MAAM;AAClD,YAAM,QAAQ,cAAc,UAAU,IAAI,EAAE,MAAM;AAClD,UAAI,OAAO;AACX,UAAI,WAAW,aAAa,KAAK;AAC/B,SAAC,OAAO,KAAK,IAAI;AAAA,UACf,CAAC,MAAM,mBAAmB,MAAM,MAAM,mBAAmB,IAAI;AAAA,UAC7D,CAAC,MAAM,mBAAmB,MAAM,MAAM,mBAAmB,IAAI;AAAA,QAC/D,EAAE,IAAI,CAAC,iBAAiB;AACtB,gBAAM,CAAC,OAAO,KAAK,IAAI;AACvB,gBAAM,UAAU;AAAA,YACd,QAAQ,MAAM;AAAA,YACd,OAAO,MAAM;AAAA,YACb,OAAO,EAAE;AAAA,UACX;AACA,gBAAM,UAAU;AAAA,YACd,QAAQ,MAAM;AAAA,YACd,OAAO,MAAM;AAAA,YACb,OAAO,EAAE;AAAA,UACX;AACA,gBAAM,WAAW,IAAI,iBAAiB,QAAQ,EAAE,OAAO,EAAE,KAAK;AAC9D,iBAAO,cAAc,iBAAiB,UAAU,CAAC,SAAS,OAAO,GAAG,WAAW,MAAM,OAAO,MAAM,KAAK,CAAC;AAAA,QAC1G,CAAC;AAAA,MACH,OAAO;AACL,cAAM,cAAc,IAAI,wBAAwB,aAAa,uBAAuB,EAAE,OAAO,EAAE,KAAK;AACpG,cAAM,cAAc,IAAI,wBAAwB,aAAa,uBAAuB,EAAE,OAAO,EAAE,KAAK;AACpG,cAAM,UAAU;AAAA,UACd;AAAA,YACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,YACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,YACrC,OAAO,EAAE;AAAA,UACX;AAAA,UACA;AAAA,YACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,YACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,YACrC,OAAO,EAAE;AAAA,UACX;AAAA,UACA;AAAA,YACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,YACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,YACrC,OAAO,EAAE;AAAA,UACX;AAAA,UACA;AAAA,YACE,QAAQ,MAAM,mBAAmB,KAAK;AAAA,YACtC,OAAO,MAAM,mBAAmB,KAAK;AAAA,YACrC,OAAO,EAAE;AAAA,UACX;AAAA,QACF;AACA,gBAAQ,cAAc,iBAAiB,aAAa,SAAS,SAAS;AACtE,gBAAQ,cAAc,iBAAiB,aAAa,SAAS,SAAS;AAAA,MACxE;AACA,YAAM,gBAAgB,SAAS,EAAE,QAAQ,EAAE,MAAM,OAAO,MAAM,MAAM,GAAG,SAAS,cAAc,CAAC;AAC/F,oBAAc,YAAY,MAAM,MAAM;AACtC,oBAAc,YAAY,MAAM,MAAM;AACtC,aAAO;AAAA,IACT;AACA,UAAM,SAAS,SAAS,WAAW,EAAE,OAAO,EAAE,KAAK;AACnD,SAAK,EAAE,UAAU,YAAY,EAAE,UAAU,YAAY,cAAc,mBAAmB,CAAC,GAAG,CAAC,CAAC,MAAM,iBAAiB,MAAM;AACvH,YAAM,QAAQ,cAAc,UAAU,IAAI,EAAE,MAAM,EAAE;AACpD,YAAM,QAAQ,cAAc,UAAU,IAAI,EAAE,MAAM,EAAE;AACpD,YAAM,eAAe,EAAE,UAAU,WAAW,qBAAqB,uBAAuB,KAAK,IAAI;AACjG,YAAM,eAAe,EAAE,UAAU,WAAW,qBAAqB,uBAAuB,KAAK,IAAI;AACjG,YAAM,CAAC,WAAW,QAAQ,IAAI,cAAc,EAAE,OAAO,EAAE,OAAO,cAAc,cAAc,MAAM;AAChG,aAAO,cAAc,eAAe,UAAU,QAAQ,SAAS;AAAA,IACjE;AACA,UAAM,UAAU,IAAI,iBAAiB,QAAQ,EAAE,OAAO,EAAE,KAAK;AAC7D,WAAO,cAAc,iBAAiB,SAAS,CAAC,GAAG,CAAC,GAAG,MAAM;AAAA,EAC/D;AACF;AAGA,IAAI,EAAE,SAAS,aAAa,UAAU,cAAc,YAAY,gBAAgB,WAAW,eAAe,SAAS,aAAa,WAAW,eAAe,WAAW,eAAe,cAAc,kBAAkB,cAAc,kBAAkB,kBAAkB,sBAAsB,aAAa,iBAAiB,eAAe,mBAAmB,UAAU,cAAc,SAAS,aAAa,SAAS,aAAa,aAAa,iBAAiB,aAAa,iBAAiB,cAAc,kBAAkB,SAAS,aAAa,cAAc,kBAAkB,UAAU,cAAc,WAAW,eAAe,WAAW,eAAe,aAAa,iBAAiB,eAAe,mBAAmB,WAAW,eAAe,kBAAkB,sBAAsB,kBAAkB,sBAAsB,SAAS,aAAa,UAAU,cAAc,UAAU,cAAc,eAAe,mBAAmB,YAAY,eAAe,IAAI;AAG/6B,IAAI,OAAO,iBAAiB,EAAE,QAAQ,YAAY,KAAK,eAAe,kBAAkB,CAAC;AACzF,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,kBAAkB,EAAE,QAAQ,aAAa,KAAK,eAAe,aAAa,iBAAiB,KAAK,CAAC;AACtH,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,qBAAqB,MAAM;AAAA,EAC7B,YAAY,QAAQ;AAClB,SAAK,gBAAgB;AACrB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,OAAO;AAC1B,SAAK,gBAAgB,OAAO,IAAI,CAAC,GAAG,OAAO,IAAI,IAAI;AACnD,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,KAAK,eAAe,GAAG,CAAC,CAAC;AACrH,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW,CAAC;AAClB,SAAK,cAAc,QAAQ,CAAC,cAAc;AACxC,eAAS,KAAK,QAAQ,kBAAkB,kCAAkC;AAAA,IAC5E,CAAC;AACD,UAAM,YAAY,KAAK,cAAc,IAAI,CAAC,cAAc;AACtD,aAAO,IAAI;AAAA,IACb,CAAC,EAAE,KAAK,KAAK;AACb,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA,8BACZ,KAAK;AAAA,oCACC,KAAK;AAAA;AAAA;AAAA,cAG3B,SAAS,KAAK,YAAY;AAAA,0CACE;AAAA;AAAA;AAAA;AAAA;AAKtC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,UAAU;AAChB,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,GAAG,SAAS,SAAS,CAAC;AAAA,EACnE;AACA,QAAM,QAAQ,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK,EAAE,OAAO,CAAC,IAAI,OAAO,WAAW,IAAI,EAAE,CAAC;AACjF,QAAM,SAAS,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK;AAC3C,QAAM,UAAU,IAAI,mBAAmB,MAAM;AAC7C,SAAO,SAAS,iBAAiB,SAAS,SAAS,KAAK;AAC1D;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,YAAY,MAAM,YAAY;AACxC,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,OAAO;AACZ,UAAM,OAAO,CAAC,IAAI;AAClB,yBAAqB,2BAA2B,QAAQ,WAAW,OAAO,CAAC,EAAE,YAAY,IAAI,WAAW,MAAM,CAAC,GAAG,MAAM,WAAW,MAAM;AACzI,SAAK,KAAK,eAAe,QAAQ,MAAM;AACvC,UAAM,CAAC,WAAW,IAAI,qBAAqB,0BAA0B,YAAY,IAAI;AACrF,SAAK,cAAc,YAAY,WAAW,IAAI,CAAC,CAAC,IAAI;AACpD,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,CAAC,GAAG,GAAG,CAAC,CAAC;AAChF,SAAK,aAAa;AAClB,SAAK,YAAY,YAAY,KAAK;AAAA,EACpC;AAAA,EACA,cAAc;AACZ,UAAM,sBAAsB;AAAA,iDACiB,KAAK,cAAc;AAAA,gDACpB,KAAK,cAAc;AAAA;AAE/D,UAAM,uBAAuB,MAAM;AACjC,UAAI,KAAK,WAAW,WAAW,GAAG;AAChC,eAAO;AAAA,MACT,OAAO;AACL,eAAO,mBAAmB,aAAa,KAAK,WAAW,SAAS,CAAC;AAAA,MACnE;AAAA,IACF;AACA,UAAM,oBAAoB,MAAM;AAC9B,UAAI,UAAU;AACd,UAAI,KAAK,YAAY,WAAW,GAAG;AACjC,YAAI,KAAK,WAAW,WAAW,GAAG;AAChC,qBAAW;AAAA,QACb;AAAA,MACF,OAAO;AACL,iBAAS,KAAK,GAAG,KAAK,KAAK,YAAY,QAAQ,MAAM;AACnD,qBAAW,gBAAgB,aAAa,EAAE;AAAA,QAC5C;AAAA,MACF;AACA,aAAO;AAAA,IACT;AACA,UAAM,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,QAKb;AAAA;AAAA,QAEA,kCAAkC;AAAA;AAAA,6BAEb,qBAAqB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,iCAOjB,kBAAkB;AAAA,+CACJ,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,4BAexB,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAe7B,WAAO;AAAA,EACT;AACF;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,QAAQ,QAAQ;AAC1B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB,CAAC,IAAI,IAAI,CAAC;AAC/B,UAAM,cAAc,IAAI,MAAM,OAAO,MAAM;AAC3C,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,MAAM;AAC9C,kBAAY,MAAM,OAAO,OAAO;AAAA,IAClC;AACA,SAAK,cAAc;AACnB,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE;AACvC,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,GAAG,GAAG,CAAC,CAAC;AACpG,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,yBACI,KAAK,cAAc;AAAA,+CACG,KAAK,cAAc,KAAK,OAAO,KAAK,cAAc;AAAA,QACzF,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAoB3B,WAAO;AAAA,EACT;AACF;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,QAAQ,QAAQ;AAC1B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB;AACrB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,UAAM,cAAc,IAAI,MAAM,OAAO,MAAM;AAC3C,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,MAAM;AAC9C,kBAAY,MAAM,OAAO,OAAO;AAAA,IAClC;AACA,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,KAAK,eAAe,GAAG,CAAC,CAAC;AACrH,SAAK,SAAS;AACd,SAAK,YAAY,aAAa;AAAA,EAChC;AAAA,EACA,cAAc;AACZ,UAAM,QAAQ,mBAAmB,KAAK,YAAY,MAAM;AACxD,UAAM,WAAW,mBAAmB,KAAK,MAAM;AAC/C,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA,6BAEb,KAAK;AAAA,oCACE,KAAK;AAAA;AAAA;AAAA,8DAGqB,KAAK,YAAY;AAAA,gBAC/D,SAAS;AAAA;AAAA;AAAA;AAAA;AAKrB,WAAO;AAAA,EACT;AACF;AACA,SAAS,mBAAmB,QAAQ;AAClC,QAAM,OAAO,OAAO;AACpB,MAAI,OAAO,GAAG;AACZ,UAAM,MAAM,sBAAsB,2BAA2B;AAAA,EAC/D;AACA,QAAM,iBAAiB,IAAI,MAAM,IAAI;AACrC,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,mBAAe,OAAO,OAAO,SAAS,aAAa,EAAE;AAAA,EACvD;AACA,SAAO,eAAe,KAAK;AAC7B;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,gBAAgB;AACtB,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,WAAW,IAAI,MAAM,KAAK;AAChC,WAAS,KAAK,GAAG,KAAK,SAAS,QAAQ,MAAM;AAC3C,aAAS,MAAM,EAAE,MAAM,KAAK;AAAA,EAC9B;AACA,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,GAAG;AACpC,UAAM,QAAQ,cAAc,UAAU,IAAI,EAAE,MAAM;AAClD,UAAM,SAAS,MAAM;AACrB,UAAM,YAAY,kBAAkB,QAAQ,EAAE,OAAO,EAAE,OAAO,MAAM,QAAQ;AAC5E,WAAO,SAAS,eAAe,UAAU,EAAE,OAAO,SAAS;AAAA,EAC7D;AACA,MAAI,EAAE,MAAM,WAAW,KAAK,aAAa,YAAY,MAAM,CAAC,GAAG,CAAC,CAAC,GAAG;AAClE,UAAM,WAAW,IAAI,uBAAuB,EAAE,OAAO,IAAI;AACzD,WAAO,cAAc,iBAAiB,UAAU,CAAC,CAAC,GAAG,EAAE,KAAK;AAAA,EAC9D;AACA,QAAM,UAAU,IAAI,kBAAkB,EAAE,OAAO,IAAI;AACnD,SAAO,cAAc,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AAC7D;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACpD,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,QAAM,0BAA0B,CAAC;AACjC,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,4BAAwB,KAAK,EAAE;AAC/B,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,GAAG,MAAM,MAAM;AAAA,EAC3E;AACA,uBAAqB,2BAA2B,UAAU,CAAC,KAAK,EAAE,GAAG,GAAG,MAAM,MAAM;AACpF,QAAM,UAAU,IAAI,kBAAkB,GAAG,OAAO,KAAK,IAAI,KAAK;AAC9D,QAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,OAAO,iBAAiB,EAAE,CAAC;AAC1E,QAAM,MAAM,SAAS,iBAAiB,SAAS,CAAC,EAAE,GAAG,SAAS,WAAW;AACzE,0BAAwB,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACvE,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,aAAa,eAAe,MAAM,EAAE,KAAK;AACpD,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,EAAE,MAAM,MAAM;AACjF,MAAI,KAAK;AACT,QAAM,0BAA0B,CAAC;AACjC,MAAI,gBAAgB,MAAM;AACxB,SAAK,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AACnF,4BAAwB,KAAK,EAAE;AAC/B,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,GAAG,MAAM,MAAM;AAAA,EAC3E;AACA,uBAAqB,2BAA2B,UAAU,CAAC,KAAK,EAAE,GAAG,GAAG,MAAM,MAAM;AACpF,QAAM,UAAU,IAAI,kBAAkB,GAAG,OAAO,KAAK,IAAI,KAAK;AAC9D,QAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,OAAO,iBAAiB,EAAE,CAAC;AAC1E,QAAM,MAAM,SAAS,iBAAiB,SAAS,CAAC,EAAE,GAAG,SAAS,WAAW;AACzE,0BAAwB,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACvE,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,UAAU,UAAU;AAC9B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,OAAO;AACZ,SAAK,cAAc,SAAS;AAC5B,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY,UAAU;AAC3B,SAAK,WAAW;AAAA,EAClB;AAAA,EACA,cAAc;AACZ,QAAI,gBAAgB;AACpB,QAAI,KAAK,aAAa,OAAO;AAC3B,sBAAgB;AAAA,IAClB;AACA,QAAI,cAAc;AAClB,QAAI,KAAK,aAAa,OAAO;AAC3B,oBAAc;AAAA,IAChB;AACA,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAQZ,KAAK,aAAa,QAAQ,QAAQ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gBAiBhD;AAAA;AAAA;AAAA;AAAA,oCAIoB;AAAA;AAAA;AAAA;AAIhC,WAAO;AAAA,EACT;AACF;AAGA,IAAI,qCAAqC,MAAM;AAAA,EAC7C,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,OAAO;AACZ,SAAK,cAAc,SAAS;AAC5B,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAetC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAAe,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY;AAClB,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,MAAI,SAAS,gBAAgB,KAAK,SAAS,iBAAiB,KAAK,aAAa,YAAY,SAAS,SAAS,SAAS,QAAQ,GAAG;AAC9H,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD;AACA,MAAI;AACJ,QAAM,aAAa,CAAC,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE,CAAC;AAC1F,MAAI,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,GAAG;AAC7D,cAAU,IAAI,mCAAmC,QAAQ;AAAA,EAC3D,OAAO;AACL,cAAU,IAAI,eAAe,UAAU,KAAK;AAC5C,eAAW,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI,EAAE,GAAG;AAAA,MACtF,MAAM;AAAA,MACN,MAAM,CAAC,SAAS,gBAAgB,SAAS,aAAa;AAAA,IACxD,GAAG,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,UAAU,SAAS,OAAO,EAAE,GAAG;AAAA,MACjE,MAAM;AAAA,MACN,MAAM,CAAC,SAAS,uBAAuB,SAAS,oBAAoB;AAAA,IACtE,CAAC;AAAA,EACH;AACA,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,UAAU;AACpE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,EAAE,IAAI;AACjB,QAAM,EAAE,YAAY,WAAW,IAAI;AACnC,SAAO,iBAAiB,EAAE,GAAG,GAAG,YAAY,YAAY,SAAS,SAAS,CAAC;AAC7E;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,OAAO,UAAU;AAC3B,SAAK,gBAAgB,CAAC,QAAQ;AAC9B,SAAK,gBAAgB;AACrB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,OAAO,SAAS;AACrB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,KAAK,eAAe,GAAG,CAAC,CAAC;AACrH,SAAK,QAAQ;AACb,SAAK,WAAW,WAAW,mBAAmB,MAAM,MAAM;AAC1D,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,QAAQ,mBAAmB,KAAK,IAAI;AAC1C,UAAM,eAAe,WAAW,KAAK,IAAI;AACzC,QAAI;AACJ,QAAI,KAAK,MAAM,WAAW,GAAG;AAC3B,iBAAW,KAAK,YAAY,IAAI,CAAC,GAAG,OAAO;AACzC,eAAO;AAAA,MACT,CAAC;AAAA,IACH,OAAO;AACL,iBAAW,KAAK,YAAY,IAAI,CAAC,GAAG,OAAO;AACzC,eAAO,aAAa,QAAQ,wBAAwB,gBAAgB,QAAQ;AAAA,MAC9E,CAAC;AAAA,IACH;AACA,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA,4BAEd;AAAA;AAAA,YAEhB,SAAS,KAAK,IAAI;AAAA,8CACgB;AAAA;AAAA;AAAA;AAI1C,WAAO;AAAA,EACT;AACF;AACA,IAAI,UAAU,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAC3C,SAAS,WAAW,MAAM;AACxB,MAAI,SAAS,GAAG;AACd,WAAO;AAAA,EACT,WAAW,QAAQ,GAAG;AACpB,WAAO,QAAQ,MAAM,GAAG,IAAI,EAAE,IAAI,CAAC,UAAU,aAAa,OAAO,EAAE,KAAK,GAAG;AAAA,EAC7E,OAAO;AACL,UAAM,MAAM,oBAAoB,2BAA2B;AAAA,EAC7D;AACF;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAO,MAAAZ,MAAK,IAAI;AACxB,QAAM,CAAC,QAAQ,KAAK,IAAI,mBAAmB,iBAAiB,GAAG,OAAOA,KAAI;AAC1E,qBAAmB,kBAAkB,GAAG,QAAQ,KAAK;AACrD,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,KAAK,EAAE,UAAU,UAAU;AAC5D,UAAM,cAAc,SAAS,UAAU,IAAI,EAAE,MAAM;AACnD,UAAM,YAAY,cAAc,YAAY,QAAQ,QAAQ,OAAO,EAAE,OAAO,EAAE,KAAK;AACnF,WAAO,SAAS,eAAe,OAAO,EAAE,OAAO,SAAS;AAAA,EAC1D;AACA,MAAI,aAAa,cAAc,KAAK,MAAM,GAAG;AAC3C,WAAO,SAAS,eAAe,OAAO,EAAE,OAAO,CAAC,CAAC;AAAA,EACnD;AACA,QAAM,UAAU,IAAI,cAAc,QAAQ,KAAK;AAC/C,QAAM,cAAc,CAAC,EAAE,MAAM,SAAS,MAAM,OAAO,CAAC;AACpD,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,WAAW;AACrE;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kBAAkB,CAAC,SAAS;AAC9B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,MAAM,IAAI;AAC9B,eAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,uEAAuE;AACtH,QAAM,QAAQ,WAAW,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAC/C,QAAM,WAAW,qBAAqB,YAAY,EAAE,OAAO,YAAY,KAAK;AAC5E,QAAM,WAAW,qBAAqB,YAAY,SAAS,QAAQ,WAAW,MAAM;AACpF,QAAM,mBAAmB,qBAAqB,oBAAoB,EAAE,OAAO,YAAY,KAAK;AAC5F,QAAM,mBAAmB,qBAAqB,oBAAoB,OAAO,WAAW,MAAM;AAC1F,QAAM,YAAY,qBAAqB,aAAa,kBAAkB,OAAO,WAAW,MAAM;AAC9F,QAAM,YAAY,CAAC;AACnB,QAAM,uBAAuB,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACtG,QAAM,yBAAyB,WAAW,EAAE,QAAQ,EAAE,GAAG,qBAAqB,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,SAAS,EAAE,CAAC;AAC/H,QAAM,wBAAwB,SAAS;AAAA,IACrC,QAAQ,EAAE,GAAG,uBAAuB;AAAA,IACpC,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,iBAAiB;AAAA,EACnC,CAAC;AACD,QAAM,SAAS,OAAO;AAAA,IACpB,QAAQ,EAAE,GAAG,sBAAsB;AAAA,IACnC,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,kBAAkB,MAAM,UAAU;AAAA,EACpD,CAAC;AACD,YAAU,KAAK,oBAAoB;AACnC,YAAU,KAAK,sBAAsB;AACrC,YAAU,KAAK,qBAAqB;AACpC,YAAU,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACzD,SAAO;AACT;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY,kBAAkB;AAAA,EAChC,QAAQ,aAAa;AAAA,EACrB,OAAO;AAAA,EACP,eAAe;AACjB,CAAC;AACD,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,YAAY,SAAS,UAAU,IAAI,OAAO,MAAM;AACtD,SAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,UAAU,mBAAmB,KAAK,GAAG,SAAS,SAAS,CAAC;AAC1F;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,QAAQ,UAAU;AAC9B,QAAM,UAAU,IAAI,gBAAgB,OAAO,OAAO,YAAY,MAAM;AACpE,QAAM,SAAS,SAAS,iBAAiB,SAAS,CAAC,MAAM,GAAG,OAAO;AACnE,SAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAC3E;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,IAAI;AAClB,MAAI,UAAU,aAAa;AACzB,QAAI,EAAE,UAAU,aAAa;AAC3B,aAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,IACvD;AACA,UAAM,cAAc,MAAM,EAAE,KAAK;AACjC,UAAM,SAAS,MAAM,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,UAAU,EAAE,CAAC;AACtF,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,QAAQ,MAAM,YAAY,GAAG,SAAS,SAAS,CAAC;AAC1F,gBAAY,QAAQ;AACpB,aAAS,YAAY,OAAO,MAAM;AAClC,WAAO;AAAA,EACT;AACA,MAAI,EAAE,UAAU,aAAa;AAC3B,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,SAAS,MAAM,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AACrF,aAAS,YAAY,SAAS,MAAM;AACpC,WAAO;AAAA,EACT;AACA,MAAI,CAAC,aAAa,gBAAgB,EAAE,OAAO,KAAK,GAAG;AACjD,UAAM,SAAS,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAC7D,WAAO,EAAE,QAAQ,OAAO,QAAQ,OAAO,OAAO,OAAO,MAAM;AAAA,EAC7D;AACA,MAAI,UAAU,SAAS;AACrB,WAAO,KAAK,GAAG,QAAQ;AAAA,EACzB;AACA,MAAI,UAAU,QAAQ;AACpB,UAAM,kBAAkB,SAAS,eAAe,CAAC,GAAG,QAAQ,aAAa,uBAAuB,QAAQ,CAAC,CAAC;AAC1G,UAAM,eAAe,EAAE,GAAG,GAAG,GAAG,gBAAgB;AAChD,UAAM,SAAS,UAAU,EAAE,QAAQ,cAAc,SAAS,SAAS,CAAC;AACpE,aAAS,YAAY,gBAAgB,MAAM;AAC3C,WAAO;AAAA,EACT;AACA,QAAM,IAAI,MAAM,iCAAiC,EAAE,YAAY,OAAO;AACxE;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,iBAAiB,EAAE,QAAQ,YAAY,MAAM,eAAe,aAAa,CAAC;AACtF,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,gBAAgB;AACrB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,SAAS;AACd,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,KAAK,eAAe,GAAG,CAAC,CAAC;AACrH,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAgBtC,WAAO;AAAA,EACT;AACF;AAGA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,aAAa;AACvB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWtC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,cAAc,aAAa,IAAI;AACvC,MAAI;AACJ,QAAM,cAAc;AAAA,IAClB,EAAE,MAAM,WAAW,MAAM,CAAC,YAAY,EAAE;AAAA,IACxC,EAAE,MAAM,WAAW,MAAM,CAAC,YAAY,EAAE;AAAA,EAC1C;AACA,MAAI,aAAa,cAAc,EAAE,KAAK,IAAI,MAAM,GAAG;AACjD,cAAU,IAAI,gBAAgB,EAAE,KAAK;AAAA,EACvC,OAAO;AACL,cAAU,IAAI,aAAa,EAAE,KAAK;AAAA,EACpC;AACA,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,WAAW;AACrE;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,QAAQ;AAClB,SAAK,WAAW;AAChB,SAAK,gBAAgB;AACrB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,qBAAqB,gBAAgB,QAAQ,CAAC;AACjE,SAAK,gBAAgB,OAAO,IAAI,CAAC,GAAG,OAAO,IAAI,IAAI;AACnD,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,KAAK,eAAe,GAAG,CAAC,CAAC;AACrH,SAAK,eAAe,OAAO,SAAS;AACpC,aAAS,KAAK,GAAG,KAAK,KAAK,cAAc,MAAM;AAC7C,WAAK,YAAY,SAAS;AAAA,IAC5B;AACA,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW,CAAC;AAClB,QAAI,KAAK,eAAe,GAAG;AACzB,eAAS,KAAK,qFAAqF;AACnG,eAAS,KAAK,GAAG,KAAK,KAAK,cAAc,MAAM;AAC7C,iBAAS,KAAK,gCAAgC,CAAC,EAAE,iDAAiD,8BAA8B,KAAK,QAAQ;AAAA,MAC/I;AACA,YAAM,YAAY,KAAK;AACvB,YAAM,iBAAiB,KAAK,eAAe;AAC3C,eAAS,KAAK,oDAAoD,qCAAqC,qBAAqB;AAAA,IAC9H,OAAO;AACL,eAAS,KAAK,uDAAuD;AAAA,IACvE;AACA,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA,6BACb,KAAK;AAAA,oCACE,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAM3B,SAAS,KAAK,YAAY;AAAA;AAAA;AAAA;AAAA;AAKpC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,YAAY,SAAS,UAAU,IAAI,OAAO,MAAM;AACtD,SAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,UAAU,mBAAmB,KAAK,GAAG,SAAS,SAAS,CAAC;AAC1F;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,QAAQ,MAAM,UAAU;AAC3C,QAAM,QAAQ,OAAO,GAAG;AACxB,MAAI,UAAU,aAAa;AACzB,UAAM,QAAQ,OAAO,IAAI,CAAC,OAAO,MAAM,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,SAAS,CAAC,CAAC;AACpF,UAAM,QAAQ,OAAO,IAAI,CAAC,OAAO,MAAM,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,SAAS,CAAC,CAAC;AACpF,UAAM,eAAe,YAAY,OAAO,MAAM,QAAQ;AACtD,UAAM,eAAe,YAAY,OAAO,MAAM,QAAQ;AACtD,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,cAAc,MAAM,aAAa,GAAG,SAAS,SAAS,CAAC;AACjG,UAAM,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACrD,UAAM,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACrD,aAAS,YAAY,aAAa,MAAM;AACxC,aAAS,YAAY,aAAa,MAAM;AACxC,WAAO;AAAA,EACT;AACA,MAAI,WAAW,SAAS,mBAAmB,MAAM;AACjD,MAAI,UAAU,UAAU;AACtB,eAAW;AAAA,EACb;AACA,MAAI,UAAU;AACZ,UAAM,aAAa,OAAO,IAAI,CAAC,OAAO;AACpC,YAAM,YAAY,aAAa,cAAc,GAAG,MAAM,MAAM,IAAI,CAAC;AACjE,YAAM,QAAQ,CAAC,IAAI,SAAS;AAC5B,aAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AAAA,IAC5E,CAAC;AACD,UAAM,kBAAkB,WAAW,IAAI,CAAC,OAAO;AAC7C,aAAO,EAAE,MAAM,SAAS,SAAS,GAAG,MAAM,GAAG,OAAO,GAAG,MAAM;AAAA,IAC/D,CAAC;AACD,UAAM,YAAY,qBAAqB,gBAAgB,WAAW,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,CAAC;AAC1F,UAAM,eAAe,WAAW,GAAG,MAAM,OAAO;AAChD,UAAM,UAAU,eAAe,iBAAiB,WAAW,OAAO,YAAY;AAC9E,UAAM,gBAAgB,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,IAAI;AAC7F,UAAM,UAAU,SAAS,eAAe,eAAe,OAAO,OAAO;AACrE,eAAW,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AAC1D,WAAO;AAAA,EACT;AACA,QAAM,cAAc,SAAS,OAAO,OAAO,kCAAkC;AAC7E,MAAI,OAAO,SAAS,aAAa;AAC/B,UAAM,gBAAgB,CAAC;AACvB,aAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM,aAAa;AACtD,YAAM,WAAW,OAAO,MAAM,IAAI,KAAK,WAAW;AAClD,oBAAc,KAAK,YAAY,UAAU,MAAM,QAAQ,CAAC;AAAA,IAC1D;AACA,UAAM,SAAS,YAAY,eAAe,MAAM,QAAQ;AACxD,eAAW,MAAM,eAAe;AAC9B,eAAS,YAAY,GAAG,MAAM;AAAA,IAChC;AACA,WAAO;AAAA,EACT;AACA,QAAM,EAAE,WAAW,SAAS,IAAI,kBAAkB,QAAQ,MAAM,QAAQ;AACxE,QAAM,SAAS,UAAU,IAAI,CAAC,OAAO,GAAG,KAAK;AAC7C,QAAM,UAAU,IAAI,eAAe,MAAM;AACzC,QAAM,cAAc,CAAC;AACrB,QAAM,UAAU,IAAI,MAAM,OAAO,SAAS,CAAC;AAC3C,MAAI,QAAQ,SAAS,GAAG;AACtB,YAAQ,KAAK,OAAO,GAAG;AACvB,gBAAY,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,QAAQ,EAAE,EAAE,CAAC;AACtD,aAAS,KAAK,GAAG,KAAK,QAAQ,QAAQ,MAAM;AAC1C,cAAQ,MAAM,QAAQ,KAAK,KAAK,OAAO,IAAI;AAC3C,kBAAY,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,QAAQ,GAAG,EAAE,CAAC;AAAA,IACzD;AAAA,EACF;AACA,QAAM,MAAM,SAAS,iBAAiB,SAAS,WAAW,UAAU,GAAG,OAAO,WAAW;AACzF,YAAU,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACzD,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AACrG,WAAS,YAAY,IAAI,MAAM;AAC/B,SAAO;AACT;AACA,SAAS,kBAAkB,QAAQ,MAAM,UAAU;AACjD,QAAM,WAAW,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,IAAI;AACxF,QAAM,YAAY,OAAO,IAAI,CAAC,OAAO,SAAS;AAAA,IAC5C,QAAQ,EAAE,GAAG,GAAG;AAAA,IAChB,SAAS;AAAA,IACT,OAAO;AAAA,MACL,OAAO;AAAA,QACL,aAAa,cAAc,GAAG,MAAM,MAAM,GAAG,IAAI,CAAC;AAAA,QAClD,aAAa,cAAc,GAAG,MAAM,MAAM,IAAI,CAAC;AAAA,MACjD;AAAA,IACF;AAAA,EACF,CAAC,CAAC;AACF,SAAO,EAAE,WAAW,SAAS;AAC/B;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,QAAM,QAAQ,aAAa,eAAe,MAAM,OAAO,GAAG,KAAK,EAAE;AACjE,QAAM,WAAW,qBAAqB,gBAAgB,OAAO,IAAI,CAAC,OAAO,GAAG,KAAK,GAAG,KAAK;AACzF,MAAI,aAAa,cAAc,QAAQ,MAAM,GAAG;AAC9C,WAAO,SAAS,eAAe,UAAU,OAAO,GAAG,OAAO,CAAC,CAAC;AAAA,EAC9D;AACA,QAAM,UAAU,OAAO,OAAO,CAAC,OAAO,aAAa,cAAc,GAAG,KAAK,IAAI,CAAC;AAC9E,MAAI,QAAQ,WAAW,GAAG;AACxB,WAAO,UAAU,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,GAAG,SAAS,SAAS,CAAC;AAAA,EACnE;AACA,QAAM,SAAS,QAAQ,IAAI,CAAC,OAAO,GAAG,KAAK;AAC3C,uBAAqB,uBAAuB,QAAQ,KAAK;AACzD,SAAO,YAAY,SAAS,OAAO,QAAQ;AAC7C;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,oBAAoB,gBAAgB,WAAW,WAAW,UAAU,UAAU,OAAO,cAAc,MAAM,4BAA4B,OAAO,oBAAoB,GAAG,oBAAoB,GAAG,mBAAmB,GAAG;AACvN,QAAM,cAAc,CAAC,sBAAsB;AACzC,YAAQ;AAAA,WACD;AACH,eAAO;AAAA,WACJ;AACH,eAAO;AAAA,WACJ;AACH,eAAO;AAAA;AAEP,cAAM,IAAI,MAAM,oBAAoB,qCAAqC;AAAA;AAAA,EAE/E;AACA,QAAM,cAAc,CAAC,sBAAsB;AACzC,YAAQ;AAAA,WACD;AACH,eAAO;AAAA,WACJ;AACH,eAAO;AAAA;AAEP,cAAM,IAAI,MAAM,oBAAoB,qCAAqC;AAAA;AAAA,EAE/E;AACA,QAAM,gBAAgB,iBAAiB;AAAA;AAAA,UAE/B;AAAA;AAAA;AAGR,QAAM,kBAAkB,iBAAiB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAMjC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAOR,QAAM,SAAS,iBAAiB,uBAAuB;AACvD,QAAM,SAAS,iBAAiB,uBAAuB;AACvD,QAAM,MAAM,iBAAiB,QAAQ;AACrC,QAAM,MAAM,iBAAiB,QAAQ;AACrC,QAAM,eAAe;AAAA;AAAA,uBAEA,iBAAiB,yBAAyB;AAAA,qBAC5C;AAAA,qBACA;AAAA;AAAA,mBAEF;AAAA,mBACA;AAAA;AAAA;AAAA,kBAGD;AAAA,sBACI,YAAY,iBAAiB;AAAA;AAAA;AAAA,gCAGnB,iCAAiC;AAAA,UACvD;AAAA;AAAA,UAEA,YAAY,iBAAiB;AAAA;AAAA;AAGrC,QAAM,UAAU,iBAAiB,aAAa,WAAW;AAAA,0BACjC;AAAA,QAClB,iBAAiB;AAAA,0BACC;AAAA;AAAA,UAEhB;AAAA;AAAA,eAEK,YAAY,iBAAiB,YAAY,YAAY,YAAY;AAAA,0BACtD;AAAA,QAClB,iBAAiB;AAAA,0BACC;AAAA;AAAA,UAEhB;AAAA;AAAA,eAEK,YAAY,iBAAiB;AAC1C,QAAM,UAAU,GAAG,YAAY,iBAAiB;AAChD,QAAM,UAAU,YAAY,gBAAgB;AAC5C,QAAM,QAAQ,iBAAiB,YAAY,iBAAiB,IAAI,YAAY,iBAAiB;AAC7F,QAAM,QAAQ,iBAAiB,YAAY,iBAAiB,IAAI,YAAY,iBAAiB;AAC7F,QAAM,WAAW;AAAA,QACX,oBAAoB,aAAa,2BAA2B,qBAAqB,GAAG,CAAC;AAAA,2DAClC;AAAA,UACjD,iBAAiB,UAAU;AAAA;AAAA;AAAA,2DAGsB;AAAA,UACjD,iBAAiB,UAAU;AAAA;AAAA;AAAA,kEAG6B;AAAA,4BACtC;AAAA;AAAA;AAAA;AAAA,yBAIH,iBAAiB,yBAAyB;AAAA,UACzD;AAAA,UACA,sBAAsB,SAAS,WAAW;AAAA;AAAA;AAAA;AAIlD,SAAO;AACT;AACA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,YAAY,UAAU,WAAW,WAAW,UAAU,UAAU,OAAO,cAAc,MAAM,4BAA4B,OAAO;AAC5H,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,cAAc,SAAS;AAC5B,SAAK,iBAAiB,SAAS,eAAe;AAC9C,SAAK,WAAW,SAAS,aAAa,MAAM,KAAK,SAAS,aAAa,MAAM,MAAM,KAAK,kBAAkB,SAAS,WAAW,MAAM,KAAK,CAAC,KAAK,mBAAmB,SAAS,cAAc,MAAM;AAC/L,SAAK,iBAAiB,KAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE,IAAI,EAAE,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE;AACxG,SAAK,gBAAgB,8BAA8B,KAAK,gBAAgB,KAAK,aAAa,KAAK,MAAM;AACrG,SAAK,oBAAoB,8BAA8B,KAAK,gBAAgB,KAAK,aAAa,KAAK,MAAM;AACzG,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,KAAK,iBAAiB;AACjH,QAAI,KAAK,QAAQ;AACf,UAAI,KAAK,kBAAkB,SAAS,aAAa,MAAM,GAAG;AACxD,aAAK,mBAAmB;AACxB,aAAK,gBAAgB,CAAC,OAAO,WAAW;AAAA,MAC1C,OAAO;AACL,aAAK,mBAAmB;AACxB,aAAK,gBAAgB,CAAC,aAAa,WAAW;AAAA,MAChD;AACA,UAAI,SAAS;AACX,aAAK,cAAc,KAAK,MAAM;AAC9B,aAAK,cAAc,KAAK,WAAW;AAAA,MACrC;AACA,UAAI,2BAA2B;AAC7B,aAAK,cAAc,KAAK,wBAAwB;AAChD,aAAK,cAAc,KAAK,WAAW;AAAA,MACrC;AAAA,IACF,OAAO;AACL,WAAK,mBAAmB,KAAK,kBAAkB;AAC/C,UAAI,SAAS;AACX,aAAK,cAAc,KAAK,MAAM;AAAA,MAChC;AACA,UAAI,2BAA2B;AAC7B,aAAK,cAAc,KAAK,wBAAwB;AAAA,MAClD;AAAA,IACF;AACA,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,4BAA4B;AACjC,SAAK,aAAa,KAAK,cAAc,KAAK,KAAK,kBAAkB;AACjE,SAAK,aAAa,KAAK,cAAc,KAAK,KAAK,kBAAkB;AACjE,SAAK,YAAY,KAAK,IAAI,KAAK,cAAc,KAAK,KAAK,kBAAkB,KAAK,cAAc,EAAE;AAC9F,SAAK,YAAY,YAAY,KAAK,eAAe;AACjD,SAAK,YAAY,YAAY,KAAK,eAAe;AACjD,SAAK,WAAW,WAAW,KAAK,cAAc;AAC9C,SAAK,YAAY,YAAY,KAAK,qBAAqB,KAAK,eAAe,KAAK,aAAa,KAAK,aAAa,KAAK,YAAY,KAAK,UAAU,KAAK,oBAAoB,KAAK;AAAA,EAC/K;AAAA,EACA,cAAc;AACZ,UAAM,eAAe,KAAK,SAAS,2BAA2B,KAAK,mBAAmB,KAAK,YAAY,KAAK,YAAY,KAAK,WAAW,KAAK,kBAAkB,CAAC,KAAK,cAAc,IAAI,uBAAuB,KAAK,mBAAmB,KAAK,eAAe,CAAC,KAAK,gBAAgB,KAAK,SAAS;AAC9R,UAAM,eAAe,KAAK,SAAS,CAAC,KAAK,iBAAiB,KAAK,mBAAmB,GAAG,GAAG,CAAC,IAAI,CAAC,GAAG,GAAG,CAAC;AACrG,UAAM,WAAW;AAAA,MACf,oBAAoB,KAAK,gBAAgB,KAAK,WAAW,KAAK,WAAW,KAAK,UAAU,KAAK,SAAS,KAAK,YAAY,KAAK,2BAA2B,aAAa,IAAI,aAAa,IAAI,aAAa,EAAE;AAAA,MACxM;AAAA;AAEF,WAAO;AAAA,EACT;AACF;AAGA,SAAS,wBAAwB,OAAO,gBAAgB;AACtD,QAAM,SAAS,MAAM;AACrB,MAAI,UAAU,GAAG;AACf,WAAO,iBAAiB;AAAA,MACtB,GAAG,MAAM,MAAM,GAAG,EAAE;AAAA,MACpB,MAAM,SAAS,KAAK,MAAM,SAAS;AAAA,MACnC,MAAM,SAAS;AAAA,IACjB,IAAI;AAAA,MACF,GAAG,MAAM,MAAM,GAAG,EAAE;AAAA,MACpB,MAAM,SAAS;AAAA,MACf,MAAM,SAAS,KAAK,MAAM,SAAS;AAAA,IACrC;AAAA,EACF,WAAW,CAAC,kBAAkB,WAAW,KAAK,MAAM,KAAK,GAAG;AAC1D,WAAO,CAAC,MAAM,IAAI,CAAC;AAAA,EACrB,OAAO;AACL,WAAO;AAAA,EACT;AACF;AACA,SAAS,gBAAgB,EAAE,GAAG,QAAQ,UAAU,SAAS,UAAU,OAAO,MAAM,yBAAyB,MAAM,iBAAiB,GAAG,YAAY,cAAc,KAAK,GAAG;AACnK,QAAM,iBAAiB,SAAS,eAAe;AAC/C,QAAM,aAAa,iBAAiB,QAAQ;AAC5C,QAAM,aAAa;AACnB,QAAM,WAAW,kBAAkB,SAAS,iBAAiB,SAAS,YAAY,SAAS,gBAAgB,SAAS,WAAW,SAAS,QAAQ,SAAS;AACzJ,QAAM,gBAAgB,CAAC;AACvB,MAAI;AACJ,MAAI;AACJ,MAAI,UAAU;AACZ,UAAM,YAAY,SAAS,WAAW,SAAS,UAAU,SAAS;AAClE,gBAAY,SAAS;AAAA,MACnB,QAAQ,EAAE,EAAE;AAAA,MACZ,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,CAAC,GAAG,SAAS,WAAW,SAAS,EAAE;AAAA,IACrD,CAAC;AACD,qBAAiB,SAAS;AAAA,MACxB,QAAQ,EAAE,GAAG,OAAO;AAAA,MACpB,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,CAAC,GAAG,WAAW,SAAS,WAAW,EAAE;AAAA,IACvD,CAAC;AAAA,EACH,OAAO;AACL,gBAAY,SAAS;AAAA,MACnB,QAAQ,EAAE,EAAE;AAAA,MACZ,SAAS;AAAA,MACT,OAAO;AAAA,QACL,OAAO,iBAAiB;AAAA,UACtB,SAAS;AAAA,UACT,SAAS,WAAW,SAAS;AAAA,UAC7B,SAAS;AAAA,QACX,IAAI;AAAA,UACF,SAAS;AAAA,UACT,SAAS;AAAA,UACT,SAAS,WAAW,SAAS;AAAA,QAC/B;AAAA,MACF;AAAA,IACF,CAAC;AACD,qBAAiB,SAAS;AAAA,MACxB,QAAQ,EAAE,GAAG,OAAO;AAAA,MACpB,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,CAAC,GAAG,SAAS,YAAY,SAAS,WAAW,EAAE;AAAA,IACjE,CAAC;AAAA,EACH;AACA,gBAAc,KAAK,SAAS;AAC5B,gBAAc,KAAK,cAAc;AACjC,MAAI,0BAA0B,MAAM;AAClC,UAAM,cAAc,wBAAwB,uBAAuB,OAAO,cAAc;AACxF,QAAI,eAAe,MAAM;AACvB,+BAAyB,SAAS;AAAA,QAChC,QAAQ,EAAE,GAAG,uBAAuB;AAAA,QACpC,SAAS;AAAA,QACT,OAAO,EAAE,OAAO,YAAY;AAAA,MAC9B,CAAC;AACD,oBAAc,KAAK,sBAAsB;AAAA,IAC3C;AAAA,EACF;AACA,MAAI,QAAQ,MAAM;AAChB,UAAM,cAAc,wBAAwB,KAAK,OAAO,cAAc;AACtE,QAAI,eAAe,MAAM;AACvB,aAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,KAAK,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AACzF,oBAAc,KAAK,IAAI;AAAA,IACzB;AAAA,EACF;AACA,QAAM,SAAS,iBAAiB;AAAA,IAC9B,GAAG,iBAAiB,YAAY;AAAA,IAChC,GAAG,iBAAiB,iBAAiB;AAAA,IACrC;AAAA,IACA;AAAA,IACA,SAAS;AAAA,IACT;AAAA,IACA,YAAY;AAAA,IACZ;AAAA,IACA;AAAA,EACF,CAAC;AACD,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,SAAS,EAAE,CAAC;AACtG,gBAAc,KAAK,MAAM;AACzB,aAAW,MAAM,eAAe;AAC9B,aAAS,YAAY,GAAG,MAAM;AAAA,EAChC;AACA,SAAO;AACT;AACA,SAAS,WAAW,EAAE,GAAG,QAAQ,UAAU,SAAS,UAAU,OAAO,MAAM,yBAAyB,MAAM,iBAAiB,GAAG,YAAY,cAAc,KAAK,GAAG;AAC9J,QAAM,UAAU,QAAQ;AACxB,QAAM,4BAA4B,0BAA0B;AAC5D,QAAM,iBAAiB,SAAS,eAAe;AAC/C,QAAM,WAAW,kBAAkB,SAAS,iBAAiB,SAAS,YAAY,SAAS,gBAAgB,SAAS,WAAW,SAAS,QAAQ,SAAS;AACzJ,MAAI,YAAY,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,KAAK,SAAS,mBAAmB,KAAK,SAAS,kBAAkB,KAAK,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,MAAM,SAAS,QAAQ,SAAS,UAAU,SAAS,QAAQ,SAAS,UAAU;AAClR,WAAO,gBAAgB;AAAA,MACrB;AAAA,MACA;AAAA,MACA;AAAA,MACA,SAAS;AAAA,MACT;AAAA,MACA,YAAY;AAAA,MACZ;AAAA,MACA;AAAA,IACF,CAAC;AAAA,EACH;AACA,QAAM,YAAY,iBAAiB,SAAS,YAAY,SAAS,WAAW,SAAS;AACrF,QAAM,YAAY,iBAAiB,SAAS,cAAc,SAAS,YAAY,SAAS;AACxF,QAAM,WAAW,SAAS,eAAe,SAAS,cAAc,SAAS;AACzE,QAAM,UAAU,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI;AAC5D,QAAM,aAAa;AAAA,IACjB,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE;AAAA,IACrE,EAAE,MAAM,SAAS,MAAM,CAAC,GAAG,OAAO,EAAE;AAAA,IACpC,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE;AAAA,IACrE,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,gBAAgB,SAAS,aAAa,EAAE;AAAA,IACzE,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE;AAAA,IACnC,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE;AAAA,IACnC,EAAE,MAAM,SAAS,MAAM,CAAC,QAAQ,EAAE;AAAA,EACpC;AACA,QAAM,UAAU,IAAI,gBAAgB,UAAU,WAAW,WAAW,UAAU,SAAS,aAAa,yBAAyB;AAC7H,QAAM,gBAAgB,CAAC;AACvB,QAAM,WAAW,CAAC,GAAG,MAAM;AAC3B,MAAI,SAAS;AACX,QAAI,CAAC,kBAAkB,KAAK,MAAM,WAAW,GAAG;AAC9C,aAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,KAAK,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,KAAK,MAAM,IAAI,GAAG,CAAC,EAAE,EAAE,CAAC;AACnG,oBAAc,KAAK,IAAI;AAAA,IACzB;AACA,aAAS,KAAK,IAAI;AAAA,EACpB;AACA,MAAI,2BAA2B;AAC7B,QAAI,CAAC,kBAAkB,uBAAuB,MAAM,WAAW,GAAG;AAChE,+BAAyB,SAAS;AAAA,QAChC,QAAQ,EAAE,GAAG,uBAAuB;AAAA,QACpC,SAAS;AAAA,QACT,OAAO,EAAE,OAAO,CAAC,uBAAuB,MAAM,IAAI,GAAG,CAAC,EAAE;AAAA,MAC1D,CAAC;AACD,oBAAc,KAAK,sBAAsB;AAAA,IAC3C;AACA,aAAS,KAAK,sBAAsB;AAAA,EACtC;AACA,MAAI,gBAAgB,aAAa;AAC/B,eAAW,KAAK,EAAE,MAAM,WAAW,MAAM,CAAC,cAAc,EAAE,CAAC;AAC3D,YAAQ,YAAY;AAAA,EACtB;AACA,QAAM,MAAM,SAAS,iBAAiB,SAAS,UAAU,EAAE,OAAO,UAAU;AAC5E,aAAW,MAAM,eAAe;AAC9B,aAAS,YAAY,GAAG,MAAM;AAAA,EAChC;AACA,SAAO;AACT;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAY,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB,IAAI;AACvE,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,OAAO,WAAW;AAC5I,SAAO,WAAW,EAAE,GAAG,QAAQ,UAAU,SAAS,SAAS,CAAC;AAC9D;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,6BAA6B,mBAAmB,GAAG;AAC1D,QAAM,cAAc,CAAC,sBAAsB;AACzC,YAAQ;AAAA,WACD;AACH,eAAO;AAAA,WACJ;AACH,eAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAWP,cAAM,IAAI,MAAM,oBAAoB,qCAAqC;AAAA;AAAA,EAE/E;AACA,QAAM,eAAe;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,iBASN,YAAY,gBAAgB;AAAA;AAAA;AAAA,iBAG5B,YAAY,gBAAgB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8DAOiB;AAC5D,QAAM,UAAU;AAAA,UACR;AAAA;AAAA,eAEK,YAAY,gBAAgB;AACzC,QAAM,WAAW;AAAA,uDACoC,YAAY,gBAAgB;AAAA,wBAC3D;AAAA,MAClB;AAAA;AAAA;AAAA,uDAGiD,YAAY,gBAAgB;AAAA,wBAC3D;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,QAShB,YAAY,gBAAgB;AAAA;AAAA,aAEvB,YAAY,gBAAgB;AAAA;AAAA;AAAA,iEAGwB,YAAY,gBAAgB;AAAA,wBACrE;AAAA,6CACqB,mBAAmB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,iEAOC;AAAA;AAAA;AAG/D,SAAO;AACT;AACA,IAAI,0BAA0B,MAAM;AAAA,EAClC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,cAAc,SAAS;AAC5B,iBAAa,OAAO,SAAS,eAAe,gBAAgB,MAAM,6BAA6B;AAC/F,SAAK,SAAS,SAAS,aAAa,MAAM,KAAK,SAAS,cAAc,MAAM;AAC5E,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC,EAAE;AAClD,SAAK,gBAAgB,8BAA8B,KAAK,gBAAgB,KAAK,aAAa,KAAK,MAAM;AACrG,SAAK,oBAAoB,8BAA8B,KAAK,gBAAgB,KAAK,aAAa,KAAK,MAAM;AACzG,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,KAAK,iBAAiB;AACjH,QAAI,KAAK,QAAQ;AACf,WAAK,mBAAmB;AACxB,WAAK,gBAAgB,CAAC,aAAa,KAAK;AAAA,IAC1C,OAAO;AACL,WAAK,mBAAmB,KAAK,kBAAkB;AAAA,IACjD;AACA,SAAK,aAAa,KAAK,cAAc,KAAK,KAAK,kBAAkB;AACjE,SAAK,aAAa,KAAK,cAAc,KAAK,KAAK,kBAAkB;AACjE,SAAK,YAAY,KAAK,IAAI,KAAK,cAAc,KAAK,KAAK,kBAAkB,KAAK,cAAc,EAAE;AAC9F,SAAK,YAAY,oBAAoB,KAAK,UAAU,KAAK,qBAAqB,KAAK;AAAA,EACrF;AAAA,EACA,cAAc;AACZ,UAAM,eAAe,KAAK,SAAS,2BAA2B,KAAK,mBAAmB,KAAK,YAAY,KAAK,YAAY,KAAK,WAAW,KAAK,gBAAgB,IAAI,uBAAuB,KAAK,mBAAmB,KAAK,aAAa;AAClO,UAAM,WAAW;AAAA,MACf,6BAA6B,KAAK,SAAS,IAAI,CAAC;AAAA,MAChD;AAAA;AAEF,WAAO;AAAA,EACT;AACF;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,MAAM,GAAG;AAC/B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,SAAS;AAC5B,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,iBAAiB,SAAS,eAAe;AAC9C,SAAK,YAAY,kBAAkB,KAAK;AAAA,EAC1C;AAAA,EACA,cAAc;AACZ,UAAM,SAAS,KAAK,iBAAiB,IAAI;AACzC,UAAM,SAAS,KAAK,iBAAiB,IAAI;AACzC,UAAM,aAAa,KAAK,iBAAiB,IAAI;AAC7C,WAAO;AAAA,MACL,kCAAkC;AAAA;AAAA;AAAA;AAAA,0BAId;AAAA;AAAA,0CAEgB,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oBA0B1C,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAiBvB;AACF;AAGA,SAAS,qBAAqB,MAAM;AAClC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,IAAI,OAAO,IAAI;AACvB,QAAM,EAAE,YAAY,SAAAA,UAAS,KAAK,MAAM,YAAY,gBAAgB,IAAI;AACxE,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,YAAY,OAAO,OAAOA,UAAS,GAAG,MAAM,iBAAiB,OAAO,WAAW;AACvI,QAAM,aAAa;AAAA,IACjB,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE;AAAA,IACrE;AAAA,MACE,MAAM;AAAA,MACN,MAAM;AAAA,QACJ,SAAS,eAAe,IAAI,SAAS,QAAQ;AAAA,QAC7C,SAAS,cAAc,IAAI,SAAS,QAAQ;AAAA,MAC9C;AAAA,IACF;AAAA,IACA,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE;AAAA,IACrE;AAAA,MACE,MAAM;AAAA,MACN,MAAM;AAAA,QACJ,SAAS;AAAA,QACT,SAAS;AAAA,QACT,SAAS;AAAA,QACT,SAAS;AAAA,MACX;AAAA,IACF;AAAA,EACF;AACA,MAAI;AACJ,MAAI,IAAI,EAAE,QAAQ,mCAAmC,GAAG;AACtD,cAAU,IAAI,uBAAuB,QAAQ;AAAA,EAC/C,OAAO;AACL,cAAU,IAAI,wBAAwB,QAAQ;AAC9C,UAAM,YAAY,SAAS,QAAQ,KAAK,SAAS,QAAQ;AACzD,UAAM,YAAY,SAAS,QAAQ;AACnC,UAAM,WAAW,SAAS,eAAe,SAAS,cAAc,SAAS;AACzE,eAAW,KAAK,EAAE,MAAM,UAAU,MAAM,CAAC,SAAS,EAAE,GAAG,EAAE,MAAM,UAAU,MAAM,CAAC,SAAS,EAAE,GAAG,EAAE,MAAM,UAAU,MAAM,CAAC,QAAQ,EAAE,CAAC;AAAA,EACpI;AACA,SAAO,SAAS,iBAAiB,SAAS,CAAC,IAAI,MAAM,GAAG,WAAW,UAAU;AAC/E;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,iBAAiB,EAAE,QAAQ,YAAY,IAAI,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,iBAAiB,EAAE,QAAQ,YAAY,KAAK,CAAC;AACzD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,wBAAwB,MAAM;AAAA,EAChC,YAAY,UAAU,UAAU,UAAU,QAAQ;AAChD,SAAK,gBAAgB,CAAC,SAAS,SAAS,QAAQ;AAChD,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,UAAM,CAAC,QAAQ,IAAI;AACnB,SAAK,cAAc,CAAC,UAAU,SAAS,IAAI,SAAS,IAAI,QAAQ;AAChE,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,WAAW,WAAW,aAAa,IAAI;AAC5C,SAAK,wBAAwB,KAAK,YAAY,KAAK;AACnD,SAAK,uBAAuB,KAAK,YAAY,KAAK;AAClD,SAAK,YAAY,iBAAiB,KAAK,YAAY,KAAK,yBAAyB,KAAK;AAAA,EACxF;AAAA,EACA,cAAc;AACZ,UAAM,CAAC,kBAAkB,eAAe,IAAI,CAAC,mCAAmC,iCAAiC;AACjH,UAAM,CAAC,aAAa,aAAa,GAAG,IAAI,KAAK,wBAAwB;AAAA,MACnE,IAAI;AAAA,MACJ;AAAA,MACA,MAAM;AAAA,IACR,IAAI;AAAA,MACF;AAAA,MACA;AAAA,MACA,mBAAmB;AAAA,IACrB;AACA,UAAM,CAAC,YAAY,YAAY,GAAG,IAAI,KAAK,uBAAuB;AAAA,MAChE,IAAI;AAAA,MACJ;AAAA,MACA,MAAM;AAAA,IACR,IAAI;AAAA,MACF;AAAA,MACA;AAAA,MACA,mBAAmB;AAAA,IACrB;AACA,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA,iCAGT;AAAA,gCACD;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,6BAeH;AAAA,4BACD;AAAA,qBACP;AAAA,mCACc;AAAA;AAAA;AAAA;AAAA,qBAId;AAAA,mCACc;AAAA;AAAA;AAAA;AAAA;AAAA,aAKtB,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAwBd,WAAO;AAAA,EACT;AACF;AAGA,IAAI,iBAAiB,CAAC,SAAS;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,OAAO,OAAO,IAAI;AACzC,QAAM,EAAE,UAAU,QAAQ,mBAAmB,IAAI;AACjD,QAAM,UAAU,IAAI,sBAAsB,OAAO,MAAM,IAAI,MAAM,OAAO,UAAU,MAAM;AACxF,QAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,kBAAkB,EAAE,CAAC;AACpE,SAAO,SAAS,iBAAiB,SAAS,CAAC,QAAQ,OAAO,MAAM,GAAG,WAAW,WAAW;AAC3F;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI;AAAA,CACH,SAAS,YAAY;AACpB,aAAW,UAAU;AACrB,aAAW,SAAS;AACtB,GAAG,eAAe,aAAa,CAAC,EAAE;AAClC,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,KAAK,OAAO,WAAW,UAAU;AAC3C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,OAAO;AACZ,UAAM,iBAAiB;AACvB,SAAK,gBAAgB,CAAC,gBAAgB,GAAG,CAAC;AAC1C,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AACjB,SAAK,UAAU;AACf,SAAK,KAAK;AACV,SAAK,YAAY,OAAO,KAAK,MAAM,KAAK,aAAa,KAAK;AAAA,EAC5D;AAAA,EACA,cAAc;AACZ,UAAM,OAAO,KAAK,YAAY;AAC9B,UAAM,UAAU,KAAK,OAAO,WAAW,OAAO,QAAQ;AACtD,UAAM,MAAM,KAAK,YAAY,UAAU,QAAQ,WAAW,MAAM,UAAU,KAAK,EAAE;AACjF,UAAM,SAAS,KAAK,YAAY,KAAK,YAAY,SAAS;AAC1D,QAAI,YAAY;AAChB,QAAI,YAAY;AAChB,QAAI,KAAK,WAAW;AAClB,kBAAY,KAAK,UAAU,UAAU,SAAS,MAAM;AACpD,kBAAY,KAAK,UAAU,YAAY;AAAA,IACzC,OAAO;AACL,kBAAY,KAAK,UAAU,gBAAgB,WAAW;AACtD,kBAAY,KAAK,UAAU,eAAe;AAAA,IAC5C;AACA,WAAO;AAAA,QACH,kCAAkC;AAAA;AAAA;AAAA;AAAA,qBAIrB,eAAe,MAAM,UAAU,KAAK,EAAE;AAAA,qBACtC;AAAA;AAAA,eAEN;AAAA,uBACQ;AAAA,aACV,eAAe,MAAM,UAAU,KAAK,EAAE;AAAA,iBAClC,KAAK,YAAY,WAAW,MAAM,UAAU,KAAK,EAAE;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAMlE;AACF;AACA,SAAS,WAAW,MAAM,MAAM,KAAK;AACnC,MAAI,SAAS,GAAG;AACd,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG,WAAW;AAAA,EACvB,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG,WAAW,WAAW;AAAA,EAClC,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG,WAAW,WAAW,WAAW;AAAA,EAC7C,OAAO;AACL,UAAM,MAAM,cAAc,gBAAgB,2BAA2B;AAAA,EACvE;AACF;AACA,SAAS,eAAe,MAAM,MAAM,KAAK;AACvC,MAAI,SAAS,GAAG;AACd,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG;AAAA,EACZ,WAAW,SAAS,GAAG;AACrB,WAAO,GAAG;AAAA,EACZ,OAAO;AACL,UAAM,MAAM,cAAc,gBAAgB,2BAA2B;AAAA,EACvE;AACF;AAGA,SAAS,SAAS,KAAK,GAAG,UAAU,MAAM,WAAW,UAAU;AAC7D,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,cAAc,qBAAqB,mBAAmB,CAAC,IAAI,GAAG,KAAK;AACzE,MAAI,YAAY;AAChB,MAAI,eAAe,MAAM;AACvB,gBAAY,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,YAAY,EAAE,CAAC;AAAA,EAC3F;AACA,QAAM,eAAe,qBAAqB,iBAAiB,GAAG,KAAK,EAAE;AACrE,MAAI,iBAAiB,QAAQ,GAAG;AAC9B,UAAM,IAAI,MAAM,oDAAoD,EAAE,MAAM,SAAS,kBAAkB,MAAM;AAAA,EAC/G;AACA,QAAMZ,QAAO,UAAU,MAAM;AAC7B,MAAI,SAAS,UAAU,EAAE,QAAQ,EAAE,GAAG,UAAU,GAAG,SAAS,SAAS,CAAC;AACtE,WAAS,KAAK,GAAG,MAAM,KAAK,KAAK,KAAK,KAAKA,KAAI,CAAC,IAAI,GAAG,MAAM;AAC3D,UAAM,UAAU,IAAI,YAAY,KAAK,UAAU,OAAO,OAAO,QAAQ;AACrE,UAAM,aAAa;AACnB,UAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,EAAE,EAAE,CAAC;AACpD,aAAS,SAAS,iBAAiB,SAAS,CAAC,MAAM,GAAG,OAAO,OAAO,WAAW;AAC/E,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,WAAW;AACb,UAAM,UAAU,IAAI,YAAY,KAAK,UAAU,OAAO,WAAW,QAAQ;AACzE,UAAM,aAAa;AACnB,UAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,CAAC,EAAE,CAAC;AACnD,aAAS,SAAS,iBAAiB,SAAS,CAAC,MAAM,GAAG,OAAO,OAAO,WAAW;AAC/E,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,MAAI,eAAe,MAAM;AACvB,UAAM,qBAAqB,qBAAqB,uBAAuB,WAAW;AAClF,UAAM,0BAA0B,WAAW,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,mBAAmB,EAAE,CAAC;AAC5H,aAAS,YAAY,OAAO,MAAM;AAClC,aAAS,YAAY,UAAU,MAAM;AACrC,WAAO;AAAA,EACT;AACA,SAAO;AACT;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,SAAO,SAAS,WAAW,MAAM,GAAG,UAAU,MAAM,WAAW,QAAQ;AACzE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,WAAW,SAAS,SAAS,IAAI;AAC/C,SAAO,SAAS,WAAW,KAAK,GAAG,UAAU,MAAM,WAAW,QAAQ;AACxE;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,aAAa,YAAY;AACnC,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,WAAW;AAChB,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY,gBAAgB;AACjC,SAAK,aAAa;AAAA,EACpB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA,oBAItB,KAAK,qBAAqB;AAAA,oBAC1B,KAAK,oBAAoB;AAAA,oBACzB,KAAK,oBAAoB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAO/B,KAAK,mBAAmB;AAAA;AAAA;AAAA,sBAGhB,KAAK,uBAAuB;AAAA;AAAA;AAAA;AAI9C,WAAO;AAAA,EACT;AAAA,EACA,uBAAuB;AACrB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,sBAAsB;AACpB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,sBAAsB;AACpB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,qBAAqB;AACnB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,yBAAyB;AACvB,QAAI,KAAK,eAAe,QAAQ;AAC9B,aAAO;AAAA,IACT,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AACF;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,WAAW,WAAW,IAAI;AAClC,QAAM,YAAY,EAAE,MAAM;AAC1B,QAAM,cAAc,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AACjE,QAAM,aAAa,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AAChE,QAAM,aAAa,eAAe,SAAS,EAAE,MAAM,KAAK,EAAE,MAAM;AAChE,QAAM,eAAe,cAAc;AACnC,QAAM,cAAc,aAAa;AACjC,QAAM,cAAc,cAAc,YAAY;AAC9C,QAAM,cAAc,eAAe,SAAS,CAAC,WAAW,cAAc,aAAa,WAAW,IAAI,CAAC,WAAW,aAAa,cAAc,WAAW;AACpJ,QAAM,cAAc;AAAA,IAClB,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE;AAAA,EACrC;AACA,QAAM,UAAU,IAAI,qBAAqB,aAAa,UAAU;AAChE,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,WAAW;AACrE;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mCAAmC,MAAM;AAAA,EAC3C,YAAY,aAAa,cAAc,aAAa,UAAU,OAAO,cAAc,MAAM,qBAAqB,OAAO;AACnH,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,IAAI,CAAC;AAC/B,SAAK,cAAc;AACnB,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,EAAE;AAClD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,oBAAoB;AACtB,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,qBAAqB;AAC1B,SAAK,eAAe;AACpB,SAAK,cAAc;AACnB,SAAK,YAAY,iBAAiB,KAAK,cAAc,KAAK,gBAAgB,KAAK;AAAA,EACjF;AAAA,EACA,cAAc;AACZ,UAAM,aAAa,KAAK,cAAc,KAAK;AAC3C,UAAM,gBAAgB,KAAK,cAAc,KAAK,KAAK,cAAc,KAAK,KAAK,cAAc;AACzF,UAAM,cAAc,KAAK,cAAc,KAAK,KAAK,eAAe;AAChE,UAAM,aAAa,KAAK,cAAc,KAAK,KAAK,cAAc;AAC9D,UAAM,WAAW;AAAA,QACb,oBAAoB,KAAK,YAAY,KAAK,oBAAoB,OAAO,CAAC;AAAA;AAAA,kDAE5B,gBAAgB;AAAA,kDAChB,KAAK,iBAAiB,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,QAUrE,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,mDAuBoB,sCAAsC,KAAK,cAAc;AAAA,qDACvD,qCAAqC,KAAK,cAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UASnG,aAAa,gBAAgB,gBAAgB,gBAAgB,kBAAkB,iCAAiC;AAAA;AAAA;AAAA,gCAG1F,KAAK;AAAA,gCACL,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAOL,KAAK;AAAA,kCACH,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,UAM7B,sBAAsB,KAAK,SAAS,KAAK,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAMzD,WAAO;AAAA,EACT;AACF;AAGA,IAAI,6BAA6B,MAAM;AAAA,EACrC,YAAY,UAAU,UAAU,OAAO,cAAc,MAAM,qBAAqB,OAAO;AACrF,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,GAAG,GAAG,CAAC;AAC7B,SAAK,SAAS;AACd,SAAK,cAAc,SAAS;AAC5B,SAAK,iBAAiB,EAAE,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,EAAE;AAClD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,GAAG,GAAG,CAAC,CAAC;AACpG,iBAAa,OAAO,SAAS,eAAe,gBAAgB,MAAM,6BAA6B;AAC/F,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,oBAAoB;AACtB,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,WAAW;AAChB,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,qBAAqB;AAC1B,SAAK,YAAY,iBAAiB,eAAe,KAAK,SAAS,gBAAgB,KAAK,SAAS;AAAA,EAC/F;AAAA,EACA,cAAc;AACZ,UAAM,UAAU,IAAI,KAAK,SAAS,cAAc;AAChD,UAAM,WAAW;AAAA,QACb,oBAAoB,KAAK,YAAY,KAAK,oBAAoB,MAAM,CAAC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,QASrE,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,uCAUQ;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,gCAQP,KAAK,SAAS;AAAA;AAAA,gCAEd;AAAA;AAAA;AAAA;AAAA,kCAIE,KAAK,SAAS;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAalC,sBAAsB,KAAK,SAAS,KAAK,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAM7D,WAAO;AAAA,EACT;AACF;AAGA,IAAI,0BAA0B,MAAM;AAAA,EAClC,YAAY,UAAU,UAAU,OAAO,cAAc,MAAM,qBAAqB,OAAO;AACrF,SAAK,gBAAgB,CAAC,KAAK,GAAG;AAC9B,SAAK,WAAW;AAAA;AAEhB,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,cAAc,SAAS;AAC5B,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,iBAAiB,SAAS,eAAe;AAC9C,QAAI,SAAS;AACX,WAAK,cAAc,KAAK,MAAM;AAAA,IAChC;AACA,QAAI,oBAAoB;AACtB,WAAK,cAAc,KAAK,wBAAwB;AAAA,IAClD;AACA,SAAK,WAAW;AAChB,SAAK,UAAU;AACf,SAAK,aAAa;AAClB,SAAK,qBAAqB;AAC1B,SAAK,YAAY,aAAa,KAAK,cAAc,KAAK;AAAA,EACxD;AAAA,EACA,cAAc;AACZ,UAAM,cAAc,KAAK,iBAAiB,6BAA6B;AACvE,UAAM,WAAW;AAAA,QACb,oBAAoB,KAAK,YAAY,KAAK,oBAAoB,OAAO,CAAC;AAAA;AAAA,QAEtE,oBAAoB;AAAA;AAAA;AAAA,2CAGe,KAAK,iBAAiB,OAAO;AAAA,0BAC9C,KAAK,iBAAiB,IAAI;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,6BA4BvB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,6BAoBA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAMjB,sBAAsB,KAAK,SAAS,KAAK,UAAU;AAAA;AAAA;AAAA;AAAA;AAAA;AAM3D,WAAO;AAAA,EACT;AACF;AAGA,SAAS,uBAAuB,MAAM;AACpC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,EAAE,SAAAY,UAAS,KAAK,MAAM,YAAY,WAAW,gBAAgB,IAAI;AACvE,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,MAAI,aAAa;AACjB,MAAI,cAAc,MAAM;AACtB,iBAAa,CAAC,GAAG,CAAC;AAAA,EACpB;AACA,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,YAAY,MAAM,iBAAiB,MAAM,WAAW;AAC5I,QAAM,aAAa;AAAA,IACjB,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI,EAAE;AAAA,IACrE,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,UAAU,SAAS,OAAO,EAAE;AAAA,EAC/D;AACA,QAAM,iBAAiB,SAAS,eAAe;AAC/C,MAAI;AACJ,MAAI,CAAC,kBAAkB,SAAS,WAAW,MAAM,SAAS,UAAU,MAAM,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,KAAK,SAAS,kBAAkB,KAAK,SAAS,mBAAmB,KAAK,SAAS,eAAe,SAAS,aAAa;AACpP,cAAU,IAAI,iCAAiC,SAAS,UAAU,SAAS,cAAc,SAAS,WAAW;AAAA,EAC/G,WAAW,kBAAkB,SAAS,WAAW,KAAK,SAAS,UAAU,KAAK,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,KAAK,SAAS,eAAe,SAAS,eAAe,SAAS,mBAAmB,KAAK,SAAS,kBAAkB,KAAK,SAAS,aAAa,MAAM,GAAG;AACzR,cAAU,IAAI,2BAA2B,QAAQ;AAAA,EACnD,OAAO;AACL,cAAU,IAAI,wBAAwB,QAAQ;AAC9C,eAAW,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,YAAY,EAAE,GAAG,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,WAAW,EAAE,GAAG,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE,GAAG;AAAA,MACzL,MAAM;AAAA,MACN,MAAM,CAAC,SAAS,gBAAgB,SAAS,aAAa;AAAA,IACxD,CAAC;AAAA,EACH;AACA,SAAO,SAAS,iBAAiB,SAAS,CAAC,GAAG,MAAM,GAAG,EAAE,OAAO,UAAU;AAC5E;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,qBAAqB,kBAAkB;AAAA,EACzC,QAAQ,aAAa;AAAA,EACrB,eAAe;AAAA,EACf,iBAAiB;AACnB,CAAC;AACD,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,YAAY,YAAY;AAClC,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,OAAO;AACZ,SAAK,aAAa,CAAC,WAAW,WAAW,WAAW,MAAM;AAC1D,UAAM,CAAC,WAAW,IAAI,qBAAqB,0BAA0B,KAAK,YAAY,CAAC,CAAC,CAAC;AACzF,SAAK,cAAc,YAAY,WAAW,IAAI,CAAC,CAAC,IAAI;AACpD,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,CAAC,GAAG,GAAG,CAAC,CAAC;AAChF,SAAK,aAAa;AAClB,SAAK,YAAY,UAAU;AAAA,EAC7B;AAAA,EACA,cAAc;AACZ,QAAI,WAAW;AACf,QAAI,YAAY;AAChB,QAAI,KAAK,eAAe,SAAS,KAAK,eAAe,OAAO;AAC1D,iBAAW;AAAA;AAAA;AAAA,qDAGoC,KAAK,eAAe,QAAQ,MAAM;AAAA;AAEjF,kBAAY;AAAA,IACd,WAAW,KAAK,eAAe,SAAS,KAAK,eAAe,QAAQ;AAClE,iBAAW;AAAA,IACb,WAAW,KAAK,eAAe,QAAQ;AACrC,iBAAW;AACX,kBAAY;AAAA,IACd;AACA,UAAM,gBAAgB,KAAK,eAAe,SAAS,yEAAyE;AAC5H,UAAM,sBAAsB;AAAA,mDACmB,KAAK,cAAc;AAAA;AAElE,UAAM,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA,SAKZ;AAAA;AAAA;AAAA,wBAGe,KAAK,YAAY,WAAW,IAAI,iBAAiB;AAAA;AAAA;AAAA,SAGhE,kCAAkC;AAAA;AAAA;AAAA,2BAGhB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,aAMd;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAWC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAQF;AAAA;AAAA;AAAA;AAIR,WAAO;AAAA,EACT;AACF;AAGA,SAAS,QAAQ,GAAG,MAAM,UAAU,YAAY,UAAU;AACxD,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,YAAY,CAAC;AACnB,QAAM,WAAW,aAAa,eAAe,MAAM,EAAE,KAAK;AAC1D,MAAI,OAAO;AACX,QAAM,eAAe,qBAAqB,mBAAmB,MAAM,KAAK;AACxE,MAAI,SAAS;AACb,MAAI,gBAAgB,MAAM;AACxB,aAAS,WAAW,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,MAAM,aAAa,GAAG,SAAS,SAAS,CAAC;AACvF,WAAO,qBAAqB,iBAAiB,KAAK,QAAQ,KAAK;AAC/D,cAAU,KAAK,MAAM;AAAA,EACvB;AACA,uBAAqB,2BAA2B,YAAY,MAAM,KAAK;AACvE,QAAM,CAAC,gBAAgB,WAAW,IAAI,qBAAqB,0BAA0B,OAAO,OAAO,IAAI;AACvG,MAAI,cAAc;AAClB,MAAI,UAAU;AACZ,kBAAc,qBAAqB,qBAAqB,gBAAgB,QAAQ;AAAA,EAClF;AACA,MAAI;AACJ,OAAK,eAAe,SAAS,eAAe,WAAW,SAAS,mBAAmB,CAAC,MAAM,CAAC,GAAG;AAC5F,UAAM,QAAQ,SAAS,UAAU,IAAI,OAAO,MAAM,EAAE;AACpD,YAAQ;AAAA,WACD;AACH,cAAM,YAAY,YAAY,OAAO,aAAa,cAAc,WAAW,GAAG,aAAa,EAAE,KAAK;AAClG,cAAM,SAAS,eAAe,aAAa,EAAE,OAAO,SAAS;AAC7D;AAAA,WACG;AACH,cAAM,EAAE,SAAS,UAAU,SAAS,IAAI,aAAa,OAAO,OAAO,OAAO,OAAO,OAAO,IAAI;AAC5F,cAAM,SAAS,eAAe,UAAU,UAAU,OAAO;AACzD;AAAA;AAEA,cAAM,IAAI,MAAM,GAAG,qDAAqD;AAAA;AAAA,EAE9E,OAAO;AACL,UAAM,SAAS,aAAa,cAAc,WAAW;AACrD,UAAM,QAAQ,aAAa,cAAc,OAAO,KAAK;AACrD,UAAM,YAAY,QAAQ;AAC1B,UAAM,aAAa,EAAE,YAAY,QAAQ,QAAQ,WAAW,SAAS,EAAE;AACvE,UAAM,QAAQ,eAAe,SAAS,YAAY,WAAW,EAAE,KAAK;AACpE,UAAM,cAAc;AAAA,MAClB,EAAE,MAAM,SAAS,MAAM,CAAC,MAAM,EAAE;AAAA,IAClC;AACA,UAAM,UAAU,IAAI,eAAe,YAAY,UAAU;AACzD,UAAM,UAAU,SAAS,iBAAiB,SAAS,CAAC,MAAM,GAAG,OAAO,WAAW;AAC/E,cAAU,KAAK,OAAO;AACtB,UAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,OAAO,EAAE,OAAO,YAAY,GAAG,SAAS,SAAS,CAAC;AAAA,EAC7F;AACA,YAAU,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACzD,SAAO;AACT;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,SAAO,QAAQ,GAAG,MAAM,UAAU,OAAO,QAAQ;AACnD;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,SAAS,IAAI;AACrB,QAAM,UAAU;AAChB,QAAM,EAAE,SAAS,YAAY,OAAO,IAAI,qBAAqB,qBAAqB,UAAU,QAAQ,MAAM;AAC1G,uBAAqB,oBAAoB,QAAQ,QAAQ,QAAQ,OAAO;AACxE,QAAM,EAAE,MAAM,MAAM,IAAI,qBAAqB,qBAAqB,YAAY,MAAM;AACpF,QAAM,SAAS,MAAM;AACrB,MAAI,MAAM;AACV,MAAI,mBAAmB,QAAQ;AAC/B,QAAM,mBAAmB,CAAC;AAC1B,WAAS,KAAK,GAAG,KAAK,QAAQ,EAAE,IAAI;AAClC,eAAW,UAAU,MAAM,KAAK;AAC9B,YAAM,EAAE,oBAAoB,MAAM,YAAY,aAAa,IAAI,qBAAqB,qBAAqB,kBAAkB,OAAO,OAAO;AACzI,UAAI;AACJ,UAAI,qBAAqB,sBAAsB,IAAI,GAAG;AACpD,YAAI,QAAQ;AAAA,MACd,OAAO;AACL,YAAI,WAAW,EAAE,QAAQ,EAAE,GAAG,QAAQ,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AACrF,yBAAiB,KAAK,CAAC;AAAA,MACzB;AACA,YAAM,cAAc,EAAE,MAAM,MAAM;AAClC,eAAS,IAAI,GAAG,IAAI,aAAa,QAAQ,EAAE,GAAG;AAC5C,oBAAY,OAAO,aAAa,IAAI,GAAG,CAAC;AAAA,MAC1C;AACA,UAAI,CAAC,aAAa,YAAY,EAAE,OAAO,WAAW,GAAG;AACnD,YAAI,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAChF,yBAAiB,KAAK,CAAC;AAAA,MACzB;AACA,UAAI,QAAQ,MAAM;AAChB,cAAM;AAAA,MACR,OAAO;AACL,cAAM,mBAAmB,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,IAAI,GAAG,SAAS,SAAS,CAAC;AACxE,yBAAiB,KAAK,GAAG;AAAA,MAC3B;AAAA,IACF;AACA,QAAI,KAAK,SAAS,GAAG;AACnB,UAAI,KAAK,OAAO,GAAG;AACjB,cAAM,KAAK;AAAA,UACT,QAAQ,EAAE,GAAG,IAAI;AAAA,UACjB,SAAS;AAAA,UACT,OAAO;AAAA,YACL,MAAM,KAAK,OAAO,QAAQ,SAAS;AAAA,YACnC,UAAU;AAAA,UACZ;AAAA,QACF,CAAC;AACD,yBAAiB,KAAK,GAAG;AAAA,MAC3B;AACA;AAAA,IACF;AAAA,EACF;AACA,aAAW,cAAc,kBAAkB;AACzC,QAAI,eAAe,KAAK;AACtB;AAAA,IACF;AACA,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACA,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,iBAAiB,EAAE,QAAQ,YAAY,IAAI,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,kBAAkB,EAAE,QAAQ,aAAa,OAAO,OAAO,QAAQ,eAAe,cAAc,CAAC;AAC1G,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,iBAAiB;AAAA,EAC1B,QAAQ,YAAY;AAAA,EACpB,eAAe;AAAA,EACf,OAAO;AACT,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,OAAO,SAAS,SAAS,IAAI;AAC7C,QAAM,EAAE,IAAI,IAAI;AAChB,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,YAAY,OAAO,MAAM;AAC/B,QAAM,WAAW,OAAO,MAAM,MAAM;AACpC,MAAI,OAAO;AACX,MAAI,MAAM,GAAG;AACX,iBAAa,OAAO,EAAE,YAAY,MAAM,KAAK,MAAM,iCAAiC,EAAE,YAAY,OAAO,YAAY;AACrH,WAAO,YAAY,MAAM;AAAA,EAC3B;AACA,WAAS,OAAO,MAAM,GAAG,CAAC;AAC1B,SAAO,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAC1F;AACA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,iBAAiB,EAAE,QAAQ,YAAY,OAAO,eAAe,cAAc,CAAC;AACzF,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,wBAAwB,MAAM;AAAA,EAChC,YAAY,YAAY;AACtB,SAAK,cAAc,CAAC;AACpB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAStC,WAAO;AAAA,EACT;AACF;AAGA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AAC7C,UAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,UAAM,gBAAgB;AACtB,UAAM,UAAU,IAAI,sBAAsB,OAAO,KAAK;AACtD,UAAM,SAAS,cAAc,iBAAiB,SAAS,CAAC,MAAM,GAAG,OAAO,KAAK;AAC7E,WAAO;AAAA,EACT;AACF;AAGA,IAAI,SAAS,iBAAiB,EAAE,QAAQ,YAAY,OAAO,eAAe,cAAc,CAAC;AACzF,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,YAAY,kBAAkB,EAAE,QAAQ,aAAa,SAAS,OAAO,QAAQ,CAAC;AAClF,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,qBAAqB,MAAM;AAAA,EAC7B,YAAY,aAAa,aAAa,cAAc,OAAO;AACzD,SAAK,eAAe;AACpB,SAAK,cAAc,CAAC,CAAC;AACrB,SAAK,gBAAgB,CAAC;AACtB,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,aAAa,GAAG,CAAC,CAAC;AAC9G,SAAK,cAAc;AACnB,SAAK,YAAY,cAAc,KAAK;AAAA,EACtC;AAAA,EACA,cAAc;AACZ,UAAM,cAAc,KAAK,cAAc,4CAA4C;AACnF,UAAM,cAAc,KAAK,cAAc,qBAAqB;AAC5D,WAAO;AAAA,uCAC4B;AAAA,QAC/B,kCAAkC;AAAA;AAAA;AAAA;AAAA,yBAIjB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,EAOvB;AACF;AAGA,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AACA,IAAI;AACJ,IAAI,oBAAoC,oBAAI,IAAI;AAChD,SAAS,YAAY,MAAM;AACzB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,MAAI,EAAE,OAAO,IAAI;AACjB,QAAM,EAAE,YAAY,IAAI;AACxB,MAAI,UAAU,MAAM;AAClB,UAAM,IAAI,MAAM,0DAA0D;AAAA,EAC5E;AACA,QAAM,UAAU,OAAO,qBAAqB,eAAe,kBAAkB;AAC7E,QAAM,UAAU,OAAO,qBAAqB,eAAe,kBAAkB;AAC7E,QAAM,WAAW,OAAO,sBAAsB,eAAe,kBAAkB,qBAAqB,OAAO,oBAAoB,eAAe,kBAAkB;AAChK,QAAM,gBAAgB,OAAO,gBAAgB,eAAe,kBAAkB;AAC9E,QAAM,CAAC,OAAO,MAAM,IAAI,UAAU;AAAA,IAChC,OAAO;AAAA,IACP,OAAO;AAAA,EACT,IAAI,CAAC,OAAO,OAAO,OAAO,MAAM;AAChC,QAAM,cAAc,CAAC,QAAQ,OAAO,WAAW;AAC/C,QAAM,cAAc,IAAI,EAAE,QAAQ,gCAAgC,KAAK;AACvE,QAAM,iBAAiB,WAAW;AAClC,MAAI,iBAAiB,YAAY,gBAAgB;AAC/C,QAAI;AACJ,QAAI,aAAa;AACf,YAAM,eAAe;AACrB,UAAI,CAAC,kBAAkB,IAAI,YAAY,KAAK,kBAAkB,IAAI,YAAY,EAAE,SAAS;AACvF,cAAM,4BAA4B,EAAE,QAAQ,aAAa;AACzD,0BAAkB,IAAI,cAAc,SAAS,OAAO,sBAAsB,yBAAyB,CAAC;AAAA,MACtG;AACA,oBAAc;AAAA,QACZ;AAAA,QACA;AAAA,QACA,QAAQ;AAAA,QACR,OAAO;AAAA,QACP,SAAS,kBAAkB,IAAI,YAAY;AAAA,MAC7C;AAAA,IACF,OAAO;AACL,UAAI,gBAAgB;AAClB,YAAI,wBAAwB,MAAM;AAChC,iCAAuB,SAAS,cAAc,QAAQ,EAAE,WAAW,IAAI;AAAA,QACzE;AACA,6BAAqB,OAAO,QAAQ;AACpC,6BAAqB,OAAO,SAAS;AACrC,6BAAqB,UAAU,QAAQ,GAAG,GAAG,OAAO,MAAM;AAC1D,iBAAS,qBAAqB;AAAA,MAChC;AACA,YAAM,QAAQ,gBAAgB,WAAW,gBAAgB,oBAAoB,gBAAgB;AAC7F,YAAM,SAAS;AACf,YAAM,UAAU,SAAS,eAAe,eAAe,YAAY,IAAI,YAAY,IAAI,QAAQ,KAAK;AACpG,eAAS,MAAM,2BAA2B,EAAE,QAAQ,OAAO,GAAG,EAAE,QAAQ,GAAG,CAAC,YAAY,IAAI,YAAY,EAAE,CAAC;AAC3G,oBAAc,EAAE,OAAO,QAAQ,QAAQ,OAAO,QAAQ;AAAA,IACxD;AACA,UAAMZ,QAAO,aAAa,cAAc,WAAW;AACnD,UAAMY,WAAU,aAAa,eAAe,WAAW;AACvD,UAAM,UAAU,IAAI,mBAAmB,aAAa,aAAa,WAAW;AAC5E,UAAM,cAAc;AAAA,MAClB,EAAE,MAAM,UAAU,MAAM,CAACZ,KAAI,EAAE;AAAA,MAC/B,EAAE,MAAM,UAAU,MAAM,CAAC,WAAW,EAAE;AAAA,MACtC,EAAE,MAAM,UAAU,MAAM,CAAC,GAAGY,QAAO,EAAE;AAAA,IACvC;AACA,UAAM,SAAS,SAAS,eAAe,CAAC,QAAQ,KAAK,GAAG,OAAO;AAC/D,UAAM,OAAO,SAAS,UAAU,IAAI,OAAO,MAAM;AACjD,SAAK,eAAe;AACpB,UAAM,SAAS,SAAS,iBAAiB,SAAS,CAAC,MAAM,GAAG,SAAS,WAAW;AAChF,aAAS,YAAY,OAAO,MAAM;AAClC,WAAO;AAAA,EACT;AACA,QAAM,YAAY,OAAO;AACzB,MAAI,aAAa;AACjB,MAAI,eAAe,QAAQ,gBAAgB,GAAG;AAC5C,iBAAa,IAAI,WAAW,OAAO,QAAQ,OAAO,SAAS,WAAW;AACtE,UAAM,aAAa,UAAU;AAC7B,QAAI,IAAI;AACR,aAAS,KAAK,GAAG,KAAK,YAAY,MAAM;AACtC,UAAI,KAAK,IAAI,aAAa;AACxB,mBAAW,OAAO,UAAU;AAAA,MAC9B;AAAA,IACF;AAAA,EACF;AACA,QAAM,SAAS,SAAS,eAAe,aAAa,SAAS,IAAI,WAAW,UAAU,CAAC;AACvF,WAAS,YAAY,OAAO,MAAM;AAClC,SAAO;AACT;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,QAAQ,WAAW,eAAe,aAAa,YAAY;AACrE,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,OAAO;AACZ,SAAK,gBAAgB,CAAC,KAAK,QAAQ,UAAU;AAC7C,yBAAqB,2BAA2B,QAAQ,SAAS;AACjE,yBAAqB,2BAA2B,QAAQ,aAAa;AACrE,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,QAAI,eAAe,MAAM;AACvB,2BAAqB,2BAA2B,QAAQ,WAAW;AACnE,WAAK,cAAc,KAAK,QAAQ;AAAA,IAClC;AACA,QAAI,cAAc,MAAM;AACtB,2BAAqB,2BAA2B,QAAQ,UAAU;AAClE,WAAK,cAAc,KAAK,OAAO;AAAA,IACjC;AACA,SAAK,cAAc;AACnB,SAAK,aAAa;AAClB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,QAAI,gBAAgB;AACpB,QAAI,KAAK,eAAe,MAAM;AAC5B,sBAAgB;AAAA,IAClB;AACA,QAAI,eAAe;AACnB,QAAI,KAAK,cAAc,MAAM;AAC3B,qBAAe;AAAA,IACjB;AACA,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAMZ;AAAA,6BACD;AAAA;AAAA;AAAA;AAAA;AAAA;AAMzB,WAAO;AAAA,EACT;AACF;AAGA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,GAAG,OAAOS,SAAQ,QAAQ,MAAM,OAAO,SAAS,IAAI;AAC5D,UAAM,EAAE,gBAAgB,IAAI;AAC5B,UAAM,gBAAgB;AACtB,UAAM,kBAAkB,CAAC,GAAG,OAAO,QAAQ;AAC3C,QAAI,cAAc;AAClB,QAAI,UAAU,MAAM;AAClB,oBAAc,OAAO;AACrB,sBAAgB,KAAK,MAAM;AAAA,IAC7B;AACA,QAAI,aAAa;AACjB,QAAIA,WAAU,MAAM;AAClB,mBAAaA,QAAO;AACpB,sBAAgB,KAAKA,OAAM;AAAA,IAC7B;AACA,UAAM,UAAU,IAAI,kBAAkB,EAAE,OAAO,MAAM,OAAO,SAAS,OAAO,aAAa,UAAU;AACnG,UAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,eAAe,EAAE,CAAC;AACjE,WAAO,cAAc,iBAAiB,SAAS,iBAAiB,EAAE,OAAO,WAAW;AAAA,EACtF;AACF;AAGA,SAAS,aAAa,MAAM;AAC1B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAT,UAAS,KAAK,MAAM,YAAY,WAAW,iBAAiB,YAAY,aAAa,eAAe,IAAI;AAChH,QAAM,cAAc,qBAAqB,wBAAwB,UAAU;AAC3E,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,WAAW,MAAM,iBAAiB,OAAO,WAAW;AAC5I,SAAO,WAAW;AAAA,IAChB;AAAA,IACA;AAAA,IACA;AAAA,IACA,SAAS;AAAA,IACT;AAAA,IACA;AAAA,IACA;AAAA,IACA,YAAY;AAAA,EACd,CAAC;AACH;AACA,IAAI,qBAAqB;AAAA,EACvB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,sBAAsB,MAAM;AACnC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,MAAM,uBAAuB,IAAI;AACpD,QAAM,EAAE,SAAAA,UAAS,KAAK,MAAM,WAAW,iBAAiB,YAAY,aAAa,eAAe,IAAI;AACpG,MAAI,aAAa;AACjB,MAAI,cAAc,MAAM;AACtB,iBAAa,CAAC,GAAG,CAAC;AAAA,EACpB;AACA,eAAa,OAAO,qBAAqB,+BAA+BA,UAAS,UAAU,GAAG,MAAM,gFAAgFA,2BAA0B,aAAa;AAC3N,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,OAAO,OAAOA,UAAS,YAAY,MAAM,iBAAiB,IAAI;AAC/H,QAAM,gBAAgB,CAAC,GAAG,MAAM;AAChC,QAAM,UAAU,QAAQ;AACxB,QAAM,4BAA4B,0BAA0B;AAC5D,MAAI,SAAS;AACX,kBAAc,KAAK,IAAI;AAAA,EACzB;AACA,MAAI,2BAA2B;AAC7B,kBAAc,KAAK,sBAAsB;AAAA,EAC3C;AACA,QAAM,aAAa;AAAA,IACjB,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI,EAAE;AAAA,IACrE,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,UAAU,SAAS,OAAO,EAAE;AAAA,EAC/D;AACA,MAAI;AACJ,MAAI,SAAS,WAAW,KAAK,SAAS,UAAU,KAAK,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,KAAK,SAAS,eAAe,SAAS,eAAe,SAAS,mBAAmB,KAAK,SAAS,kBAAkB,KAAK,SAAS,aAAa,MAAM,GAAG;AAChQ,cAAU,IAAI,2BAA2B,UAAU,SAAS,aAAa,yBAAyB;AAAA,EACpG,OAAO;AACL,cAAU,IAAI,wBAAwB,UAAU,SAAS,aAAa,yBAAyB;AAC/F,eAAW,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,YAAY,EAAE,GAAG,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,WAAW,EAAE,GAAG,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE,GAAG;AAAA,MACzL,MAAM;AAAA,MACN,MAAM,CAAC,SAAS,gBAAgB,SAAS,aAAa;AAAA,IACxD,CAAC;AAAA,EACH;AACA,MAAI,gBAAgB,aAAa;AAC/B,eAAW,KAAK,EAAE,MAAM,WAAW,MAAM,CAAC,cAAc,EAAE,CAAC;AAC3D,YAAQ,YAAY;AAAA,EACtB;AACA,QAAM,SAAS,SAAS,iBAAiB,SAAS,eAAe,WAAW,UAAU;AACtF,SAAO;AACT;AACA,IAAI,8BAA8B;AAAA,EAChC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,mBAAmB,MAAM;AAAA,EAC3B,YAAY,UAAU,OAAO;AAC3B,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY,YAAY;AAC7B,SAAK,WAAW;AAChB,SAAK,WAAW,6BAA6B,mBAAmB,QAAQ;AAAA,EAC1E;AAAA,EACA,cAAc;AACZ,QAAI;AACJ,QAAI,KAAK,WAAW,GAAG;AACrB,qBAAe;AAAA,IACjB,OAAO;AACL,qBAAe;AAAA,IACjB;AACA,UAAM,WAAW;AAAA,UACX,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,8BAMd;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAQ1B,WAAO;AAAA,EACT;AACF;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,QAAQ,QAAQ,IAAI;AAC5B,QAAM,eAAe,QAAQ;AAC7B,QAAM,YAAY,aAAa,aAAa,SAAS;AACrD,QAAM,aAAa,aAAa,cAAc,OAAO,KAAK;AAC1D,QAAM,CAAC,aAAa,WAAW,WAAWA,QAAO,IAAI,qBAAqB,mBAAmB,QAAQ,OAAO;AAC5G,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,WAAW,SAAS,EAAE,EAAE,CAAC;AACvH,QAAM,WAAW,SAAS;AAAA,IACxB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,aAAa,cAAc,OAAO,KAAK,IAAI,WAAW,SAAS,EAAE;AAAA,EACpF,CAAC;AACD,MAAI,SAAS,mBAAmB,CAAC,QAAQ,OAAO,CAAC,KAAK,OAAO,UAAU,UAAU;AAC/E,UAAM,cAAc,SAAS,SAAS,QAAQ,MAAM;AACpD,UAAM,YAAY,SAAS,WAAW,MAAM;AAC5C,UAAM,WAAW,iBAAiB,aAAa,WAAW,OAAO,OAAO,WAAW,WAAW,WAAWA,UAAS,OAAO,OAAO,UAAU;AAC1I,WAAO,SAAS,eAAe,aAAa,OAAO,OAAO,SAAS,MAAM;AAAA,EAC3E;AACA,QAAM,UAAU,IAAI,iBAAiB,WAAW,CAAC,WAAW,SAAS,CAAC;AACtE,QAAM,cAAc,CAAC,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE,GAAG,EAAE,MAAM,SAAS,MAAMA,SAAQ,CAAC;AAC3F,QAAM,MAAM,SAAS,iBAAiB,SAAS,CAAC,UAAU,cAAc,GAAG,SAAS,OAAO,WAAW;AACtG,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAClG,WAAS,YAAY,eAAe,MAAM;AAC1C,WAAS,YAAY,SAAS,MAAM;AACpC,WAAS,YAAY,IAAI,MAAM;AAC/B,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,QAAQ,aAAa;AAC/B,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,OAAO,MAAM;AAChC,SAAK,SAAS;AACd,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,eAAe,iBAAiB,KAAK,MAAM;AACjD,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA,oDAKU;AAAA;AAAA;AAAA;AAIhD,WAAO;AAAA,EACT;AACF;AACA,SAAS,iBAAiB,QAAQ;AAChC,QAAM,gBAAgB,CAAC,WAAW,WAAW,WAAW,SAAS;AACjE,QAAM,eAAe,CAAC;AACtB,WAAS,KAAK,GAAG,KAAK,OAAO,QAAQ,MAAM;AACzC,QAAI,OAAO,GAAG;AACZ,mBAAa,KAAK,QAAQ;AAAA,IAC5B,OAAO;AACL,mBAAa,KAAK,GAAG,cAAc,KAAK;AAAA,IAC1C;AAAA,EACF;AACA,SAAO,aAAa,KAAK;AAC3B;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,GAAG,QAAQ,IAAI;AACvB,QAAM,EAAE,MAAM,UAAU,IAAI;AAC5B,QAAM,aAAa,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AAC9D,QAAM,YAAY,qBAAqB,aAAa,yBAAyB,GAAG,SAAS,YAAY,SAAS;AAC9G,QAAM,cAAc,aAAa,cAAc,QAAQ,KAAK;AAC5D,QAAM,YAAY,CAAC;AACnB,QAAM,WAAW,SAAS;AAAA,IACxB,QAAQ,EAAE,EAAE;AAAA,IACZ,SAAS;AAAA,IACT,OAAO;AAAA,MACL,OAAO;AAAA,QACL,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,QACV,UAAU;AAAA,MACZ;AAAA,IACF;AAAA,EACF,CAAC;AACD,QAAM,eAAe,SAAS;AAAA,IAC5B,QAAQ,EAAE,GAAG,QAAQ;AAAA,IACrB,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,UAAU,WAAW,cAAc,UAAU,SAAS,EAAE;AAAA,EAC3E,CAAC;AACD,YAAU,KAAK,QAAQ;AACvB,YAAU,KAAK,YAAY;AAC3B,QAAM,qBAAqB;AAAA,IACzB,UAAU;AAAA,IACV,UAAU;AAAA,IACV,cAAc,UAAU;AAAA,IACxB,UAAU;AAAA,EACZ;AACA,MAAI,SAAS,mBAAmB,CAAC,GAAG,OAAO,CAAC,GAAG;AAC7C,UAAM,oBAAoB,SAAS,UAAU,IAAI,aAAa,MAAM;AACpE,UAAM,gBAAgB,kBAAkB;AACxC,UAAM,aAAa,OAAO,aAAa,OAAO,aAAa,OAAO,aAAa;AAC/E,UAAM,cAAc,SAAS,UAAU,IAAI,SAAS,MAAM;AAC1D,UAAM,UAAU,YAAY;AAC5B,UAAM,OAAO,OAAO,SAAS,OAAO,SAAS,OAAO,OAAO;AAC3D,UAAM,SAAS,iBAAiB,MAAM,YAAY,kBAAkB;AACpE,cAAU,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACzD,WAAO,SAAS,eAAe,UAAU,aAAa,OAAO,OAAO,OAAO,MAAM;AAAA,EACnF;AACA,QAAM,UAAU,IAAI,eAAe,SAAS,OAAO,kBAAkB;AACrE,QAAM,MAAM,SAAS,iBAAiB,SAAS,CAAC,UAAU,YAAY,GAAG,SAAS,KAAK;AACvF,YAAU,KAAK,GAAG;AAClB,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,UAAU,YAAY,EAAE,CAAC;AAC5G,YAAU,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACzD,SAAO;AACT;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW,kBAAkB;AAAA,EAC/B,QAAQ,aAAa;AAAA,EACrB,eAAe;AAAA,EACf,OAAO;AACT,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB,kBAAkB;AAAA,EACpC,QAAQ,aAAa;AAAA,EACrB,OAAO;AAAA,EACP,eAAe;AACjB,CAAC;AACD,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAAU,OAAM,IAAI;AAClB,QAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAACA,MAAK,EAAE,CAAC;AACvD,QAAM,UAAU,IAAI,gBAAgB,EAAE,OAAO,YAAY,SAAS;AAClE,UAAQ,WAAW;AACnB,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,WAAW,WAAW;AACvE;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,kBAAkB,EAAE,QAAQ,aAAa,MAAM,OAAO,QAAQ,eAAe,aAAa,CAAC;AACvG,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,aAAa,kBAAkB;AAAA,EACjC,QAAQ,aAAa;AAAA,EACrB,OAAO;AAAA,EACP,eAAe;AACjB,CAAC;AACD,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,iBAAiB,EAAE,QAAQ,YAAY,KAAK,eAAe,YAAY,CAAC;AACnF,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,kBAAkB,EAAE,QAAQ,aAAa,aAAa,OAAO,OAAO,CAAC;AACvF,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,iBAAiB,EAAE,QAAQ,YAAY,YAAY,CAAC;AACtE,IAAI,oBAAoB;AAAA,EACtB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,kBAAkB,SAAS,IAAI;AACvC,SAAO,QAAQ,GAAG,kBAAkB,UAAU,OAAO,QAAQ;AAC/D;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW,kBAAkB;AAAA,EAC/B,QAAQ,aAAa;AAAA,EACrB,eAAe;AACjB,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAAV,UAAS,KAAK,MAAM,gBAAgB,IAAI;AAC5D,QAAM,YAAY;AAClB,QAAM,WAAW,qBAAqB,kBAAkB,EAAE,OAAO,YAAYA,UAAS,WAAW,MAAM,eAAe;AACtH,MAAI;AACJ,QAAM,aAAa,CAAC;AACpB,MAAI,SAAS,iBAAiB,KAAK,SAAS,gBAAgB,GAAG;AAC7D,QAAI,aAAa,YAAY,SAAS,SAAS,SAAS,QAAQ,GAAG;AACjE,aAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,IACvD;AACA,cAAU,IAAI,mCAAmC,QAAQ;AACzD,eAAW,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE,CAAC;AAAA,EACxF,OAAO;AACL,cAAU,IAAI,eAAe,UAAU,KAAK;AAC5C,eAAW,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,cAAc,SAAS,WAAW,EAAE,GAAG,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,QAAQ,KAAK,SAAS,QAAQ,IAAI,EAAE,GAAG;AAAA,MAC9J,MAAM;AAAA,MACN,MAAM,CAAC,SAAS,gBAAgB,SAAS,aAAa;AAAA,IACxD,GAAG,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,UAAU,SAAS,OAAO,EAAE,GAAG;AAAA,MACjE,MAAM;AAAA,MACN,MAAM,CAAC,SAAS,uBAAuB,SAAS,oBAAoB;AAAA,IACtE,CAAC;AAAA,EACH;AACA,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,UAAU;AACpE;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,UAAU,KAAK,IAAI;AAC3B,SAAO,QAAQ,GAAG,MAAM,UAAU,QAAQ,QAAQ;AACpD;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,SAAO,QAAQ,GAAG,MAAM,UAAU,OAAO,QAAQ;AACnD;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW,kBAAkB;AAAA,EAC/B,QAAQ,aAAa;AAAA,EACrB,eAAe;AACjB,CAAC;AACD,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,QAAQ,UAAU,MAAM;AAClC,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,MAAM,GAAG,EAAE;AACtE,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,SAAS;AACd,aAAS,IAAI,CAAC,GAAG,OAAO;AACtB,WAAK,YAAY,OAAO;AAAA,IAC1B,CAAC;AACD,SAAK,SAAS,SAAS,YAAY,IAAI;AACvC,SAAK,YAAY,aAAa;AAAA,EAChC;AAAA,EACA,cAAc;AACZ,UAAM,OAAO,KAAK,OAAO;AACzB,UAAM,QAAQ,KAAK,OAAO,IAAI,CAAC,GAAG,OAAO,eAAe,OAAO,EAAE,KAAK,GAAG;AACzE,UAAM,MAAM,KAAK,OAAO,IAAI,CAAC,GAAG,OAAO,eAAe,0BAA0B,OAAO,IAAI,IAAI,QAAQ,IAAI,EAAE,KAAK,GAAG;AACrH,UAAM,cAAc,SAAS,IAAI,UAAU;AAC3C,UAAM,YAAY,SAAS,IAAI,QAAQ;AACvC,UAAM,aAAa,SAAS,IAAI,SAAS;AACzC,UAAM,QAAQ,mBAAmB,IAAI;AACrC,UAAM,iBAAiB,OAAO,IAAI,CAAC,aAAa,aAAa,aAAa,WAAW,EAAE,MAAM,GAAG,IAAI,IAAI;AACxG,WAAO;AAAA,QACH,kCAAkC;AAAA;AAAA,wBAElB,SAAS;AAAA,sBACX,SAAS;AAAA;AAAA,gCAEC;AAAA,kBACd,gBAAgB;AAAA,gBAClB,gBAAgB,qBAAqB,gBAAgB,KAAK;AAAA,wBAClD,iBAAiB;AAAA,gBACzB,iBAAiB,wBAAwB,gBAAgB,KAAK;AAAA;AAAA;AAAA;AAAA,yCAIrC;AAAA;AAAA;AAAA;AAAA,EAIvC;AACF;AAGA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,EAAE,UAAU,KAAK,IAAI;AAC3B,UAAM,gBAAgB;AACtB,UAAM,cAAc,SAAS,IAAI,CAAC,OAAO;AACvC,aAAO,EAAE,MAAM,SAAS,MAAM,CAAC,GAAG,IAAI,GAAG,EAAE,EAAE;AAAA,IAC/C,CAAC;AACD,UAAM,UAAU,IAAI,kBAAkB,EAAE,OAAO,UAAU,IAAI;AAC7D,UAAM,SAAS,cAAc,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,WAAW;AAChF,WAAO;AAAA,EACT;AACF;AAGA,SAAS,KAAK,MAAM;AAClB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,GAAG;AACpC,UAAM,QAAQ,SAAS,UAAU,IAAI,EAAE,MAAM;AAC7C,UAAM,CAAC,WAAW,QAAQ,IAAI,YAAY,MAAM,QAAQ,EAAE,OAAO,EAAE,KAAK;AACxE,WAAO,SAAS,eAAe,UAAU,EAAE,OAAO,SAAS;AAAA,EAC7D;AACA,QAAM,UAAU,IAAI,gBAAgB,EAAE,OAAO,YAAY,GAAG;AAC5D,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AACxD;AACA,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,UAAQ,KAAK,gGAAgG;AAC7G,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,eAAe,IAAI;AACxD,QAAM,YAAY,SAAS,SAAS,MAAM,MAAM;AAChD,QAAM,aAAa,SAAS,SAAS,OAAO,MAAM;AAClD,QAAM,EAAE,gBAAgB,IAAI,qBAAqB,wBAAwB,WAAW,YAAY,eAAe,cAAc,cAAc;AAC3I,SAAO,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AACnG;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,qBAAqB,MAAM;AAClC,UAAQ,KAAK,gGAAgG;AAC7G,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,QAAM,EAAE,eAAe,cAAc,gBAAgB,aAAa,IAAI;AACtE,QAAM,YAAY,SAAS,SAAS,MAAM,MAAM;AAChD,QAAM,aAAa,SAAS,SAAS,OAAO,MAAM;AAClD,QAAM,mBAAmB;AACzB,QAAM,kBAAkB;AACxB,QAAM,oBAAoB;AAC1B,QAAM,kBAAkB;AACxB,QAAM,EAAE,iBAAiB,eAAe,IAAI,qBAAqB,wBAAwB,WAAW,YAAY,kBAAkB,iBAAiB,mBAAmB,eAAe;AACrL,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,gBAAgB,MAAM,GAAG,SAAS,IAAI,WAAW,eAAe,CAAC;AAAA,IAC1F,SAAS,eAAe,CAAC,eAAe,MAAM,GAAG,WAAW,IAAI,aAAa,cAAc,CAAC;AAAA,EAC9F;AACF;AACA,IAAI,6BAA6B;AAAA,EAC/B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,EAAE,UAAU,aAAa;AAC3B,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,IAAI,MAAM,GAAG,GAAG,SAAS,SAAS,CAAC;AAC7E,aAAS,YAAY,SAAS,MAAM;AACpC,aAAS,YAAY,GAAG,MAAM;AAC9B,aAAS,YAAY,SAAS,MAAM;AACpC,aAAS,YAAY,GAAG,MAAM;AAC9B,WAAO;AAAA,EACT,OAAO;AACL,WAAO,MAAM;AAAA,MACX,OAAO;AAAA,QACL,OAAO,EAAE;AAAA,QACT,OAAO,EAAE;AAAA,QACT,OAAO,EAAE,UAAU,WAAW,KAAK;AAAA,MACrC;AAAA,MACA,SAAS;AAAA,IACX,CAAC;AAAA,EACH;AACF;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,UAAU,MAAM;AACvB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,EAAE,IAAI;AACd,MAAI,EAAE,UAAU,UAAU;AACxB,UAAM,IAAI,MAAM,8CAA8C;AAAA,EAChE,WAAW,EAAE,UAAU,aAAa;AAClC,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,UAAU,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACnE,UAAM,WAAW,MAAM,EAAE,QAAQ,EAAE,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAClE,UAAM,KAAK,WAAW,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,SAAS,CAAC;AACpE,UAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,MAAM,IAAI,MAAM,GAAG,GAAG,SAAS,SAAS,CAAC;AAC7E,aAAS,YAAY,SAAS,MAAM;AACpC,aAAS,YAAY,GAAG,MAAM;AAC9B,aAAS,YAAY,SAAS,MAAM;AACpC,aAAS,YAAY,GAAG,MAAM;AAC9B,WAAO;AAAA,EACT,OAAO;AACL,WAAO,MAAM,EAAE,OAAO,EAAE,OAAO,EAAE,OAAO,OAAO,EAAE,OAAO,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACzF;AACF;AACA,IAAI,kBAAkB;AAAA,EACpB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,OAAO,WAAW,GAAG;AACvB,WAAO,YAAY,EAAE,QAAQ,EAAE,OAAO,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAAA,EAC9F;AACA,QAAM,QAAQ,OAAO,GAAG;AACxB,QAAM,QAAQ,OAAO,GAAG;AACxB,SAAO,QAAQ,CAAC,OAAO;AACrB,iBAAa,kBAAkB,OAAO,GAAG,OAAO,uDAAuD;AACvG,iBAAa,OAAO,UAAU,GAAG,OAAO,MAAM,uDAAuD;AAAA,EACvG,CAAC;AACD,QAAM,0BAA0B,CAAC;AACjC,QAAM,kBAAkB,OAAO,IAAI,CAAC,OAAO;AACzC,UAAM,YAAY,YAAY,EAAE,QAAQ,EAAE,OAAO,GAAG,GAAG,SAAS,UAAU,OAAO,EAAE,KAAK,KAAK,EAAE,CAAC;AAChG,4BAAwB,KAAK,SAAS;AACtC,WAAO;AAAA,EACT,CAAC;AACD,QAAM,SAAS,QAAQ,EAAE,QAAQ,iBAAiB,SAAS,UAAU,OAAO,EAAE,KAAK,EAAE,CAAC;AACtF,0BAAwB,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACvE,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,cAAc,MAAM;AAAA,EACtB,YAAY,QAAQ,UAAU;AAC5B,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,OAAO,MAAM,GAAG,EAAE;AACtE,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,aAAS,IAAI,CAAC,GAAG,OAAO;AACtB,WAAK,YAAY,OAAO;AAAA,IAC1B,CAAC;AACD,SAAK,SAAS;AACd,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,OAAO,KAAK,OAAO;AACzB,UAAM,OAAO,mBAAmB,IAAI;AACpC,UAAM,QAAQ,KAAK,OAAO,IAAI,CAAC,GAAG,OAAO,eAAe,OAAO,EAAE,KAAK,GAAG;AACzE,UAAM,MAAM,KAAK,OAAO,IAAI,CAAC,GAAG,OAAO,eAAe,0BAA0B,OAAO,IAAI,IAAI,QAAQ,IAAI,EAAE,KAAK,GAAG;AACrH,UAAM,aAAa,OAAO,IAAI,GAAG,QAAQ,WAAW,GAAG;AACvD,UAAM,WAAW,OAAO,IAAI,GAAG,QAAQ,SAAS,GAAG;AACnD,UAAM,mBAAmB,OAAO,IAAI,sBAAsB;AAC1D,UAAM,oBAAoB,OAAO,IAAI,qBAAqB;AAC1D,UAAM,iBAAiB,OAAO,IAAI,CAAC,aAAa,aAAa,aAAa,WAAW,EAAE,MAAM,GAAG,IAAI,IAAI;AACxG,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA,wBAElB;AAAA,sBACF;AAAA;AAAA;AAAA,gBAGN,uBAAuB;AAAA;AAAA;AAAA;AAAA,2CAII;AAAA;AAAA;AAAA;AAAA;AAKvC,WAAO;AAAA,EACT;AACF;AAGA,IAAI,SAAS,CAAC,SAAS;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,UAAU,cAAc,IAAI;AACpC,MAAI,SAAS,MAAM,CAAC,OAAO,aAAa,YAAY,IAAI,CAAC,GAAG,CAAC,CAAC,CAAC,GAAG;AAChE,WAAO,UAAU,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,EACvD;AACA,MAAI,aAAa,cAAc,EAAE,KAAK,MAAM,GAAG;AAC7C,UAAM,cAAc,SAAS,IAAI,CAAC,IAAI,OAAO,GAAG,KAAK,EAAE,MAAM,MAAM,GAAG,EAAE;AACxE,WAAO,MAAM;AAAA,MACX,SAAS;AAAA,MACT,OAAO,EAAE,OAAO,aAAa,OAAO,eAAe,OAAO,EAAE,MAAM;AAAA,IACpE,CAAC;AAAA,EACH;AACA,QAAM,cAAc,CAAC,EAAE,MAAM,WAAW,MAAM,CAAC,aAAa,EAAE,CAAC;AAC/D,WAAS,IAAI,CAAC,OAAO,YAAY,KAAK,EAAE,MAAM,SAAS,MAAM,CAAC,GAAG,IAAI,GAAG,EAAE,EAAE,CAAC,CAAC;AAC9E,QAAM,UAAU,IAAI,YAAY,EAAE,OAAO,QAAQ;AACjD,SAAO,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,WAAW;AACrE;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,kBAAkB;AAAA,EAC3B,QAAQ,aAAa;AACvB,CAAC;AACD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,OAAO,MAAM;AACpB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,GAAG,OAAAU,OAAM,IAAI;AACrB,QAAM,UAAU,IAAI,iBAAiB,aAAa,OAAO,EAAE,OAAOA,OAAM,KAAK;AAC7E,SAAO,SAAS,iBAAiB,SAAS,CAAC,GAAGA,MAAK,GAAG,SAAS;AACjE;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,MAAM,SAAS,IAAI;AAC3B,SAAO,QAAQ,GAAG,MAAM,UAAU,QAAQ,QAAQ;AACpD;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,CAAC,SAAS;AACrB,QAAM,EAAE,SAAS,UAAU,MAAM,IAAI;AACrC,QAAM,EAAE,OAAO,MAAM,MAAM,OAAO,MAAM,IAAI;AAC5C,QAAM,SAAS,cAAc,OAAO,MAAM,OAAO,KAAK;AACtD,SAAO,SAAS,eAAe,CAAC,OAAO,MAAM,GAAG,OAAO,MAAM;AAC/D;AACA,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW,kBAAkB,EAAE,QAAQ,aAAa,IAAI,CAAC;AAC7D,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,iBAAiB,EAAE,QAAQ,YAAY,KAAK,CAAC;AACzD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,SAAS,iBAAiB,EAAE,QAAQ,YAAY,MAAM,CAAC;AAC3D,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,yBAAyB,MAAM;AAAA,EACjC,YAAY,YAAY,WAAW,UAAU;AAC3C,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,CAAC,WAAW,IAAI,WAAW,UAAU,WAAW,EAAE;AACrE,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AA2CtC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,gBAAgB,MAAM;AAC7B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,MAAAtB,OAAM,iBAAiB,IAAI;AACjD,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,eAAe,gBAAgB,YAAY,IAAI,IAAI;AACzD,QAAM,cAAc,gBAAgB,WAAW,IAAI,IAAI;AACvD,QAAM,wBAAwB,mBAAmB,MAAM;AACvD,QAAM,cAAc;AAAA,IAClB,EAAE,MAAM,WAAW,MAAM,CAAC,cAAc,WAAW,EAAE;AAAA,IACrD,EAAE,MAAM,WAAW,MAAM,CAAC,qBAAqB,EAAE;AAAA,EACnD;AACA,QAAM,UAAU,IAAI,uBAAuB,OAAO,OAAO,WAAW,QAAQ;AAC5E,SAAO,SAAS,iBAAiB,SAAS,CAAC,MAAM,GAAG,WAAW,WAAW;AAC5E;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gCAAgC,MAAM;AAAA,EACxC,YAAY,YAAY,WAAW,UAAU,kBAAkB;AAC7D,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc,CAAC,WAAW,IAAI,WAAW,UAAU,WAAW,EAAE;AACrE,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,mBAAmB;AACxB,SAAK,YAAY,iBAAiB;AAAA,EACpC;AAAA,EACA,cAAc;AACZ,QAAI;AACJ,QAAI,KAAK,kBAAkB;AACzB,0BAAoB;AAAA,IACtB,OAAO;AACL,0BAAoB;AAAA,IACtB;AACA,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,oCAmBN;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAYhC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,uBAAuB,MAAM;AACpC,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,cAAc,kBAAkB,MAAAA,MAAK,IAAI;AACjD,QAAM,CAAC,WAAW,QAAQ,IAAIA;AAC9B,QAAM,eAAe,gBAAgB,YAAY,IAAI,IAAI;AACzD,QAAM,cAAc,gBAAgB,WAAW,IAAI,IAAI;AACvD,QAAM,YAAY,eAAe,MAAM;AACvC,QAAM,cAAc;AAAA,IAClB,EAAE,MAAM,WAAW,MAAM,CAAC,cAAc,WAAW,EAAE;AAAA,IACrD,EAAE,MAAM,WAAW,MAAM,CAAC,SAAS,EAAE;AAAA,EACvC;AACA,QAAM,UAAU,IAAI,8BAA8B,OAAO,OAAO,WAAW,UAAU,gBAAgB;AACrG,SAAO,SAAS,iBAAiB,SAAS,CAAC,MAAM,GAAG,OAAO,OAAO,WAAW;AAC/E;AACA,IAAI,+BAA+B;AAAA,EACjC,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,YAAY,WAAW;AACjC,SAAK,cAAc,CAAC;AACpB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,WAAW;AAAA;AAEhB,SAAK,YAAY;AACjB,SAAK,cAAc;AACnB,QAAI,OAAO,cAAc,UAAU;AACjC,WAAK,YAAY;AACjB,WAAK,cAAc;AACnB,WAAK,aAAa;AAAA,IACpB,OAAO;AACL,WAAK,YAAY;AACjB,WAAK,cAAc;AACnB,WAAK,aAAa;AAAA,IACpB;AAAA,EACF;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,UACX,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,cAY9B,KAAK;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AASf,WAAO;AAAA,EACT;AACF;AAGA,IAAI,0BAA0B;AAAA,EAC5B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,OAAO,SAAS,SAAS,MAAM;AACpD,UAAM,EAAE,OAAO,OAAO,IAAI;AAC1B,UAAM,EAAE,SAAS,WAAW,OAAO,IAAI;AACvC,UAAM,gBAAgB;AACtB,UAAM,UAAU,IAAI,eAAe,OAAO,OAAO,SAAS;AAC1D,UAAM,CAAC,SAAS,OAAO,IAAI,qBAAqB,eAAe,QAAQ,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE;AACvG,UAAM,cAAc;AAAA,MAClB,EAAE,MAAM,WAAW,MAAM,CAAC,OAAO,EAAE;AAAA,MACnC,EAAE,MAAM,WAAW,MAAM,CAAC,OAAO,EAAE;AAAA,MACnC,EAAE,MAAM,WAAW,MAAM,CAAC,KAAK,IAAI,OAAO,CAAC,EAAE;AAAA,MAC7C,EAAE,MAAM,WAAW,MAAM,CAAC,KAAK,IAAI,OAAO,CAAC,EAAE;AAAA,IAC/C;AACA,QAAI,OAAO,cAAc,UAAU;AACjC,kBAAY,KAAK,EAAE,MAAM,WAAW,MAAM,CAAC,OAAO,WAAW,UAAU,QAAQ,CAAC,CAAC,CAAC,EAAE,CAAC;AAAA,IACvF,OAAO;AACL,kBAAY,KAAK,EAAE,MAAM,WAAW,MAAM,UAAU,CAAC;AAAA,IACvD;AACA,UAAM,SAAS,cAAc,iBAAiB,SAAS,CAAC,MAAM,GAAG,OAAO,OAAO,WAAW;AAC1F,WAAO;AAAA,EACT;AACF;AAGA,IAAI,SAAS,iBAAiB,EAAE,QAAQ,YAAY,OAAO,eAAe,cAAc,CAAC;AACzF,IAAI,eAAe;AAAA,EACjB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,0BAA0B,MAAM;AAAA,EAClC,YAAY,eAAe,UAAU,aAAa,aAAaY,UAAS,OAAO,aAAa,iBAAiB,MAAM;AACjH,SAAK,gBAAgB,CAAC,WAAW,SAAS;AAC1C,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,SAAS;AACd,SAAK,cAAc;AACnB,SAAK,OAAO;AACZ,SAAK,iBAAiB;AACtB,SAAK,iBAAiB,mBAAmB,aAAa;AACtD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,eAAe,KAAK,aAAa;AACtF,SAAK,yBAAyB,WAAW;AACzC,SAAK,YAAY,WAAW,eAAe,eAAe,KAAK,0BAA0B,eAAe;AACxG,UAAM,cAAc,mBAAmBA,SAAQ,MAAM;AACrD,SAAK,WAAW,4BAA4B;AAC5C,SAAK,cAAc;AACnB,SAAK,cAAc;AAAA,EACrB;AAAA,EACA,cAAc;AACZ,QAAI,gBAAgB;AACpB,QAAI,KAAK,gBAAgB,GAAG;AAC1B,sBAAgB;AAAA,IAClB,WAAW,KAAK,gBAAgB,GAAG;AACjC,sBAAgB;AAAA,IAClB;AACA,UAAM,iBAAiB,cAAc;AACrC,UAAM,eAAe,KAAK,yBAAyB,wBAAwB;AAC3E,QAAI,kBAAkB;AACtB,QAAI,gCAAgC;AACpC,QAAI,KAAK,eAAe,EAAE,WAAW,GAAG;AACtC,wBAAkB;AAClB,sCAAgC;AAAA;AAAA;AAAA;AAAA;AAAA,IAKlC,WAAW,KAAK,eAAe,EAAE,WAAW,GAAG;AAC7C,wBAAkB;AAClB,sCAAgC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,IAYlC;AACA,UAAM,gBAAgB,MAAM,KAAK,EAAE,QAAQ,KAAK,YAAY,GAAG,CAAC,GAAG,QAAQ,UAAU,MAAM;AAC3F,UAAM,iBAAiB,cAAc,cAAc,KAAK,IAAI;AAC5D,UAAM,YAAY,CAAC,KAAK,QAAQ;AAC9B,UAAI,mBAAmB,aAAa,qBAAqB;AACzD,UAAI,KAAK,SAAS,WAAW;AAC3B,2BAAmB;AAAA;AAAA;AAAA,yCAGc;AAAA;AAAA,qDAEY;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,2CAMV;AAAA;AAAA;AAAA;AAAA;AAAA,MAKrC;AACA,YAAM,qBAAqB,eAAe,qBAAqB;AAC/D,aAAO,KAAK,iBAAiB,mBAAmB;AAAA,IAClD;AACA,UAAM,WAAW;AAAA,MACf;AAAA;AAAA,QAEE,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,0CAMA;AAAA,8DACoB;AAAA;AAAA;AAAA,gBAG9C,eAAe,KAAK,MAAM,KAAK,KAAK;AAAA,qDACC;AAAA;AAAA,YAEzC,UAAU,sBAAsB,aAAa;AAAA;AAAA;AAGrD,WAAO;AAAA,EACT;AACF;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,SAAS,QAAQ,IAAI;AAC7B,QAAM,EAAE,MAAM,IAAI;AAClB,QAAM,EAAE,WAAW,YAAY,WAAW,SAAAA,UAAS,YAAAQ,YAAW,IAAI,qBAAqB,gBAAgB,SAAS,SAAS,KAAK;AAC9H,QAAM,eAAe,CAACA,cAAa,WAAW,SAAS;AACvD,MAAIA,gBAAe,GAAG;AACpB,WAAO,SAAS,eAAe,OAAO,QAAQ,KAAK;AAAA,EACrD;AACA,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,YAAY,SAAS,EAAE,EAAE,CAAC;AACxH,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,CAAC,YAAY,SAAS,EAAE,EAAE,CAAC;AAClH,QAAM,OAAO,SAAS;AACtB,QAAM,SAAS,MAAM,EAAE,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,OAAO,GAAG,OAAO,KAAK,EAAE,CAAC;AACjG,QAAMpB,QAAO,aAAa,cAAc,SAAS,KAAK;AACtD,QAAM,cAAc;AAAA,IAClB,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE;AAAA,IACnC,EAAE,MAAM,SAAS,MAAMY,SAAQ;AAAA,IAC/B,EAAE,MAAM,SAAS,MAAM,CAACZ,KAAI,EAAE;AAAA,EAChC;AACA,QAAM,UAAU,IAAI,wBAAwB,SAAS,OAAO,WAAW,eAAe,MAAM,QAAQ,SAAS,MAAM,QAAQY,UAAS,cAAc,IAAI;AACtJ,QAAM,MAAM,SAAS,iBAAiB,SAAS,CAAC,UAAU,cAAc,GAAG,MAAM,aAAa,MAAM;AACpG,QAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,IAAI,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,EAAE,CAAC;AACrF,WAAS,YAAY,eAAe,MAAM;AAC1C,WAAS,YAAY,SAAS,MAAM;AACpC,WAAS,YAAY,IAAI,MAAM;AAC/B,SAAO;AACT;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB,MAAM;AAAA,EACzB,YAAY,OAAO,OAAO,MAAM;AAC9B,SAAK,gBAAgB,CAAC,KAAK,KAAK,GAAG;AACnC,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,QAAQ;AACb,SAAK,OAAO;AACZ,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,QAAI;AACJ,QAAI;AACJ,QAAI,KAAK,OAAO,GAAG;AACjB,YAAM,MAAM,kBAAkB,KAAK,2BAA2B;AAAA,IAChE;AACA,QAAI,KAAK,SAAS,GAAG;AACnB,iBAAW;AACX,gBAAU;AAAA,IACZ,OAAO;AACL,YAAM,gBAAgB,CAAC,WAAW,WAAW,WAAW,SAAS;AACjE,YAAM,aAAa,CAAC;AACpB,YAAM,cAAc,CAAC;AACrB,eAAS,KAAK,GAAG,KAAK,KAAK,YAAY,QAAQ,MAAM;AACnD,oBAAY,KAAK,GAAG,cAAc,KAAK;AACvC,YAAI,KAAK,KAAK,OAAO;AACnB,qBAAW,KAAK,GAAG,cAAc,KAAK;AAAA,QACxC;AAAA,MACF;AACA,gBAAU,WAAW,KAAK;AAC1B,iBAAW,YAAY,KAAK;AAAA,IAC9B;AACA,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA,4BAGd;AAAA;AAAA,2CAEe;AAAA;AAAA,2CAEA;AAAA;AAAA;AAAA;AAAA;AAKvC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,SAAS,IAAI;AACtC,QAAM,EAAE,WAAW,GAAG,IAAI,GAAG,GAAG,IAAI;AACpC,QAAM,UAAU,IAAI,eAAe,UAAU,MAAM,QAAQ,GAAG,OAAO,GAAG,MAAM,MAAM;AACpF,SAAO,SAAS,iBAAiB,SAAS,CAAC,WAAW,IAAI,EAAE,GAAG,WAAW,GAAG,OAAO,GAAG,KAAK,CAAC;AAC/F;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,WAAW,iBAAiB,EAAE,QAAQ,YAAY,QAAQ,CAAC;AAC/D,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,iBAAiB,EAAE,QAAQ,YAAY,IAAI,CAAC;AACvD,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,iBAAiB,EAAE,QAAQ,YAAY,KAAK,CAAC;AACzD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,OAAO,kBAAkB,EAAE,QAAQ,aAAa,KAAK,eAAe,aAAa,iBAAiB,KAAK,CAAC;AAC5G,IAAI,aAAa;AAAA,EACf,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,SAAS,MAAM;AACtB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,IAAI;AACnB,QAAM,EAAE,IAAI,IAAI;AAChB,QAAM,OAAO,aAAa,eAAe,CAAC,GAAG,GAAG,OAAO,KAAK;AAC5D,QAAM,WAAW,KAAK;AAAA,IACpB,QAAQ,EAAE,GAAG,OAAO;AAAA,IACpB,SAAS;AAAA,IACT,OAAO,EAAE,kBAAkB,MAAM,UAAU,MAAM;AAAA,EACnD,CAAC;AACD,QAAM,gBAAgB,qBAAqB,qBAAqB,SAAS,OAAO,IAAI;AACpF,QAAM,oBAAoB,SAAS,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAClH,QAAM,IAAI,KAAK,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,kBAAkB,GAAG,SAAS,SAAS,CAAC;AACjF,QAAM,IAAI,KAAK,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,SAAS,CAAC;AACtD,QAAM,SAAS,KAAK,EAAE,QAAQ,EAAE,GAAG,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,MAAM,UAAU,MAAM,EAAE,CAAC;AACnG,QAAM,iBAAiB,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,cAAc,EAAE,CAAC;AAC7G,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,GAAG,GAAG,GAAG,eAAe,GAAG,SAAS,SAAS,CAAC;AAC/E,WAAS,YAAY,SAAS,MAAM;AACpC,WAAS,YAAY,kBAAkB,MAAM;AAC7C,WAAS,YAAY,EAAE,MAAM;AAC7B,WAAS,YAAY,EAAE,MAAM;AAC7B,WAAS,YAAY,OAAO,MAAM;AAClC,WAAS,YAAY,eAAe,MAAM;AAC1C,SAAO;AACT;AACA,IAAI,iBAAiB;AAAA,EACnB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,kBAAkB,CAAC,SAAS;AAC9B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,YAAY,SAAS,IAAI;AACjC,eAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,uEAAuE;AACtH,QAAM,QAAQ,WAAW,OAAO,CAAC,GAAG,MAAM,IAAI,CAAC;AAC/C,QAAM,mBAAmB,CAAC,CAAC,GAAG,CAAC,CAAC;AAChC,mBAAiB,KAAK,GAAG,QAAQ;AACjC,WAAS,KAAK,IAAI,WAAW,QAAQ,KAAK,EAAE,MAAM,QAAQ,EAAE,IAAI;AAC9D,qBAAiB,KAAK,CAAC,GAAG,CAAC,CAAC;AAAA,EAC9B;AACA,QAAM,YAAY,CAAC;AACnB,QAAM,UAAU,OAAO;AAAA,IACrB,QAAQ,EAAE,EAAE;AAAA,IACZ,SAAS;AAAA,IACT,OAAO,EAAE,UAAU,kBAAkB,eAAe,EAAE;AAAA,EACxD,CAAC;AACD,QAAM,sBAAsB,qBAAqB,YAAY,QAAQ,OAAO,YAAY,OAAO,KAAK;AACpG,QAAM,oCAAoC,qBAAqB,YAAY,oBAAoB,QAAQ,WAAW,QAAQ,KAAK;AAC/H,QAAM,eAAe,qBAAqB,oBAAoB,QAAQ,OAAO,YAAY,OAAO,KAAK;AACrG,QAAM,kBAAkB,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,oBAAoB,EAAE,CAAC;AACrH,QAAM,WAAW,WAAW;AAAA,IAC1B,QAAQ,EAAE,GAAG,gBAAgB;AAAA,IAC7B,SAAS;AAAA,IACT,OAAO,EAAE,MAAM,kCAAkC;AAAA,EACnD,CAAC;AACD,QAAM,SAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,SAAS,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,aAAa,EAAE,CAAC;AACtG,YAAU,KAAK,OAAO;AACtB,YAAU,KAAK,eAAe;AAC9B,YAAU,KAAK,QAAQ;AACvB,YAAU,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACzD,SAAO;AACT;AACA,IAAI,wBAAwB;AAAA,EAC1B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,QAAQ,MAAM;AACxB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,UAAM,cAAc,IAAI,MAAM,OAAO,MAAM;AAC3C,aAAS,KAAK,GAAG,KAAK,YAAY,QAAQ,MAAM;AAC9C,kBAAY,MAAM,OAAO,MAAM,KAAK;AAAA,IACtC;AACA,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,OAAO,KAAK,YAAY;AAC7B,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,eAAe,iBAAiB,KAAK,MAAM,WAAW;AAC5D,UAAM,WAAW;AAAA,QACb,kCAAkC;AAAA;AAAA;AAAA,yCAGD;AAAA;AAAA;AAAA;AAIrC,WAAO;AAAA,EACT;AACF;AACA,SAAS,iBAAiB,MAAM,gBAAgB,IAAI;AAClD,MAAI,QAAQ,GAAG;AACb,UAAM,MAAM,iBAAiB,2BAA2B;AAAA,EAC1D;AACA,MAAI,SAAS,GAAG;AACd,WAAO,YAAY;AAAA,EACrB;AACA,QAAM,gBAAgB,CAAC,WAAW,WAAW,WAAW,SAAS;AACjE,QAAM,eAAe,CAAC;AACtB,WAAS,KAAK,GAAG,KAAK,MAAM,MAAM;AAChC,iBAAa,KAAK,IAAI,cAAc,SAAS,uBAAuB,MAAM;AAAA,EAC5E;AACA,SAAO,aAAa,KAAK;AAC3B;AAGA,SAAS,MAAM,QAAQ;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,KAAK,IAAI;AACjB,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,KAAK,EAAE,UAAU,YAAY,EAAE,MAAM,UAAU,GAAG;AACnF,UAAM,OAAO,SAAS,SAAS,EAAE,MAAM;AACvC,UAAM,QAAQ,EAAE,UAAU,WAAW,KAAK,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC,IAAI;AACrF,UAAM,MAAM,OAAO,EAAE,OAAO,EAAE,OAAO,KAAK;AAC1C,UAAM,SAAS,aAAa,KAAK,IAAI;AACrC,WAAO,SAAS,eAAe,OAAO,OAAO,OAAO,OAAO,OAAO,MAAM;AAAA,EAC1E;AACA,QAAM,UAAU,IAAI,aAAa,EAAE,OAAO,IAAI;AAC9C,QAAM,SAAS,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AAC9D,SAAO;AACT;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,eAAe,MAAM;AAC5B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,eAAe,cAAc,aAAa,IAAI;AACtD,QAAM,EAAE,YAAY,IAAI;AACxB,QAAM,EAAE,WAAW,YAAY,WAAW,SAAAA,UAAS,YAAAQ,YAAW,IAAI,qBAAqB,gBAAgB,cAAc,eAAe,WAAW;AAC/I,QAAM,iBAAiB;AACvB,MAAI,aAAa,UAAU,UAAU;AACnC,UAAM,aAAa,SAAS,WAAW,aAAa;AACpD,UAAM,aAAa,SAAS,WAAW,YAAY;AACnD,UAAM,iBAAiB,aAAa,aAAa,SAAS,SAAS,aAAa,MAAM,EAAE,EAAE;AAC1F,UAAM,SAAS,gBAAgB,YAAY,YAAY,aAAaA,aAAY,WAAW,YAAY,WAAWR,UAAS,gBAAgB,cAAc;AACzJ,WAAO,SAAS,eAAe,aAAa,OAAO,OAAO,OAAO,MAAM;AAAA,EACzE;AACA,QAAM,eAAe,CAACQ,cAAa,WAAW,SAAS;AACvD,QAAM,iBAAiB,SAAS;AAAA,IAC9B,QAAQ,EAAE,GAAG,cAAc;AAAA,IAC3B,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,YAAY,SAAS,EAAE;AAAA,EAC1C,CAAC;AACD,QAAM,gBAAgB,aAAa,MAAM,SAAS,SAAS;AAAA,IACzD,QAAQ,EAAE,GAAG,aAAa;AAAA,IAC1B,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,CAAC,YAAY,SAAS,EAAE;AAAA,EAC1C,CAAC,IAAI,UAAU,EAAE,QAAQ,EAAE,GAAG,aAAa,GAAG,SAAS,SAAS,CAAC;AACjE,QAAM,OAAO,cAAc;AAC3B,QAAM,OAAO,SAAS,eAAe,CAAC,GAAG,MAAM,aAAa,oBAAoB,GAAG,IAAI,CAAC;AACxF,QAAM,gBAAgB,SAAS;AAAA,IAC7B,QAAQ,EAAE,GAAG,aAAa;AAAA,IAC1B,SAAS;AAAA,IACT,OAAO,EAAE,OAAO,MAAM,aAAa,MAAM,EAAE,KAAK,CAAC,EAAE;AAAA,EACrD,CAAC;AACD,QAAM,eAAe,MAAM,EAAE,QAAQ,EAAE,GAAG,cAAc,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,aAAa,EAAE,CAAC;AAC7G,QAAMpB,QAAO,aAAa,cAAc,CAAC,YAAY,SAAS,CAAC;AAC/D,QAAM,cAAc;AAAA,IAClB,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE;AAAA,IACnC,EAAE,MAAM,SAAS,MAAMY,SAAQ;AAAA,IAC/B,EAAE,MAAM,SAAS,MAAM,CAACZ,KAAI,EAAE;AAAA,EAChC;AACA,UAAQ;AAAA,SACD;AACH;AAAA,SACG;AACH,UAAI,MAAM;AACR,cAAM,UAAU,IAAI,wBAAwB,CAAC,YAAY,SAAS,GAAG,WAAW,eAAe,MAAM,QAAQ,cAAc,MAAM,QAAQY,UAAS,cAAc,MAAM,cAAc;AACpL,iBAAS,iBAAiB,SAAS,CAAC,eAAe,cAAc,GAAG,MAAM,aAAa,YAAY;AAAA,MACrG;AACA;AAAA;AAEA,UAAI,MAAM;AACR,cAAM,UAAU,IAAI,wBAAwB,CAAC,YAAY,SAAS,GAAG,WAAW,eAAe,MAAM,QAAQ,KAAK,MAAM,QAAQA,UAAS,cAAc,MAAM,cAAc;AAC3K,iBAAS,iBAAiB,SAAS,CAAC,MAAM,cAAc,GAAG,MAAM,aAAa,YAAY;AAAA,MAC5F;AACA;AACE,cAAM,UAAU,IAAI,wBAAwB,CAAC,YAAY,SAAS,GAAG,WAAW,eAAe,MAAM,QAAQ,cAAc,MAAM,QAAQA,UAAS,cAAc,IAAI;AACpK,iBAAS,iBAAiB,SAAS,CAAC,eAAe,cAAc,GAAG,MAAM,aAAa,YAAY;AAAA,MACrG;AAAA;AAEJ,QAAM,cAAc,SAAS,EAAE,QAAQ,EAAE,GAAG,aAAa,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,YAAY,EAAE,CAAC;AAC9G,WAAS,YAAY,eAAe,MAAM;AAC1C,WAAS,YAAY,cAAc,MAAM;AACzC,WAAS,YAAY,cAAc,MAAM;AACzC,WAAS,YAAY,KAAK,MAAM;AAChC,WAAS,YAAY,aAAa,MAAM;AACxC,SAAO;AACT;AACA,IAAI,uBAAuB;AAAA,EACzB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,iBAAiB,KAAK,IAAI;AAClC,QAAM,QAAQ,aAAa,eAAe,MAAM,EAAE,KAAK,EAAE;AACzD,QAAM,aAAa,qBAAqB,iBAAiB,GAAG,iBAAiB,KAAK;AAClF,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,QAAQ,IAAI,MAAM,KAAK,EAAE,KAAK,CAAC;AACrC,QAAMZ,QAAO,EAAE,MAAM,MAAM;AAC3B,SAAO,WAAW,IAAI,CAAC,OAAO;AAC5B,UAAM,YAAY,CAAC,GAAGA,KAAI;AAC1B,cAAU,SAAS;AACnB,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,MAAM,UAAU,EAAE,CAAC;AAC7F,UAAM,UAAU;AAChB,WAAO;AAAA,EACT,CAAC;AACH;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,iBAAiB,EAAE,QAAQ,YAAY,KAAK,CAAC;AACzD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY,CAAC,EAAE,QAAQ,SAAS,SAAS,MAAM;AAC7C,UAAM,EAAE,EAAE,IAAI;AACd,UAAM,gBAAgB;AACtB,UAAM,UAAU,IAAI,gBAAgB,EAAE,OAAO,YAAY,MAAM;AAC/D,WAAO,cAAc,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,KAAK;AAAA,EAC7D;AACF;AAGA,IAAI,qBAAqB,kBAAkB;AAAA,EACzC,QAAQ,aAAa;AACvB,CAAC;AACD,IAAI,2BAA2B;AAAA,EAC7B,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,uBAAuB,MAAM;AAAA,EAC/B,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,GAAG;AACzB,SAAK,gBAAgB;AACrB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,eAAe,CAAC,KAAK,eAAe,GAAG,CAAC,CAAC;AACrH,UAAM,QAAQ,mBAAmB,KAAK,YAAY,MAAM;AACxD,SAAK,WAAW,WAAW,qBAAqB;AAChD,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,OAAO,KAAK,YAAY;AAC9B,QAAI,YAAY;AAChB,QAAI,SAAS,GAAG;AACd,kBAAY;AAAA,IACd,OAAO;AACL,UAAI,aAAa;AACjB,kBAAY,KAAK,YAAY,IAAI,CAAC,GAAG,OAAO;AAC1C;AACA,eAAO,KAAK,YAAY,WAAW,IAAI,6BAA6B,wBAAwB,QAAQ,UAAU,aAAa,yBAAyB,wBAAwB;AAAA,MAC9K,CAAC,EAAE,KAAK,GAAG;AAAA,IACb;AACA,UAAM,WAAW;AAAA,SACZ,kCAAkC;AAAA;AAAA;AAAA,0CAGD;AAAA;AAAA;AAAA;AAItC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,OAAO,KAAK,SAAAY,UAAS,WAAW,SAAS,cAAc,aAAa,eAAe,IAAI;AAC/F,QAAM,EAAE,kBAAkB,YAAY,YAAY,WAAW,eAAe,OAAO,QAAQ,KAAK,MAAM,SAAS,SAAS,IAAI,mBAAmB,UAAU,EAAE,OAAO,OAAO,KAAKA,UAAS,WAAW,SAAS,cAAc,aAAa,cAAc;AACpP,MAAI;AACJ,MAAI,YAAY;AACd,aAAS,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAAA,EACtF,WAAW,aAAa,eAAe;AACrC,iBAAa,OAAO,EAAE,MAAM,UAAU,GAAG,MAAM,yCAAyC,EAAE,MAAM,QAAQ;AACxG,UAAMZ,QAAO,mBAAmB,gBAAgB,QAAQ,MAAM,QAAQ;AACtE,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,QAAQ,MAAAA,MAAK,EAAE,CAAC;AAC1F,aAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAC5F,aAAS,YAAY,OAAO,MAAM;AAAA,EACpC,OAAO;AACL,UAAM,qBAAqB,SAAS,mBAAmB,CAAC,CAAC,CAAC;AAC1D,QAAI,oBAAoB;AACtB,YAAM,SAAS,SAAS,SAAS,EAAE,MAAM;AACzC,YAAM,OAAO,OAAO,EAAE,OAAO,EAAE,OAAO,MAAM;AAC5C,YAAM,eAAe,qBAAqB,kBAAkB,MAAM,UAAU,MAAM;AAClF,eAAS,SAAS,eAAe,YAAY,EAAE,OAAO,aAAa,MAAM;AAAA,IAC3E,OAAO;AACL,YAAM,UAAU,IAAI,qBAAqB,gBAAgB;AACzD,YAAM,cAAc,CAAC,EAAE,MAAM,SAAS,MAAM,OAAO,GAAG,EAAE,MAAM,SAAS,MAAM,SAAS,CAAC;AACvF,YAAM,eAAe,SAAS,iBAAiB,SAAS,CAAC,CAAC,GAAG,EAAE,OAAO,WAAW;AACjF,eAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,aAAa,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,WAAW,EAAE,CAAC;AAClG,eAAS,YAAY,aAAa,MAAM;AAAA,IAC1C;AAAA,EACF;AACA,SAAO;AACT;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,cAAc,MAAM;AAC3B,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,WAAW,aAAa,SAAS,UAAU,WAAW,UAAU,uBAAuB,IAAI;AACnG,QAAM,EAAE,MAAM,WAAW,IAAI;AAC7B,QAAM,QAAQ,SAAS,SAAS,KAAK,MAAM;AAC3C,QAAM,cAAc,SAAS,SAAS,WAAW,MAAM;AACvD,QAAM,CAAC,QAAQ,YAAY,IAAI,qBAAqB,OAAO,aAAa,WAAW,aAAa,SAAS,WAAW,UAAU,sBAAsB;AACpJ,SAAO;AAAA,IACL,SAAS,eAAe,CAAC,OAAO,MAAM,GAAG,UAAU,MAAM;AAAA,IACzD,SAAS,eAAe,WAAW,OAAO,SAAS,YAAY;AAAA,EACjE;AACF;AACA,IAAI,sBAAsB;AAAA,EACxB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,QAAQ,iBAAiB,EAAE,QAAQ,YAAY,KAAK,CAAC;AACzD,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,eAAe,MAAM;AAAA,EACvB,YAAY,OAAO;AACjB,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,WAAW;AAAA;AAEhB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,UACX,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAmExC,WAAO;AAAA,EACT;AACF;AACA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,OAAO;AACjB,SAAK,gBAAgB,CAAC,KAAK,SAAS;AACpC,SAAK,gBAAgB,CAAC,KAAK,GAAG,CAAC;AAC/B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,WAAW;AAChB,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA,UACX,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AA2DxC,WAAO;AAAA,EACT;AACF;AAGA,SAAS,qCAAqC,UAAU,YAAY;AAClE,MAAI,eAAe,MAAM;AACvB,aAAS,YAAY,WAAW,MAAM;AAAA,EACxC;AACF;AACA,SAAS,eAAe,KAAK;AAC3B,MAAI,QAAQ;AACZ,SAAO,QAAQ,KAAK;AAClB,aAAS;AAAA,EACX;AACA,SAAO;AACT;AACA,SAAS,MAAM,MAAM;AACnB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,EAAE,IAAI;AACd,QAAM,EAAE,GAAG,OAAO,IAAI;AACtB,QAAM,SAAS,EAAE;AACjB,QAAM,UAAU,OAAO,OAAO,SAAS;AACvC,MAAI,SAAS,mBAAmB,CAAC,CAAC,CAAC,GAAG;AACpC,UAAM,QAAQ,SAAS,SAAS,EAAE,MAAM;AACxC,UAAM,CAAC,aAAa,cAAc,IAAI,aAAa,OAAO,QAAQ,EAAE,OAAO,GAAG,MAAM;AACpF,WAAO;AAAA,MACL,SAAS,eAAe,YAAY,OAAO,YAAY,OAAO,YAAY,MAAM;AAAA,MAChF,SAAS,eAAe,eAAe,OAAO,eAAe,OAAO,eAAe,MAAM;AAAA,IAC3F;AAAA,EACF;AACA,MAAI,MAAM,GAAG;AACX,WAAO,OAAO,SAAS,KAAK;AAC5B,WAAO;AAAA,MACL,SAAS,eAAe,QAAQ,EAAE,OAAO,CAAC,CAAC;AAAA,MAC3C,SAAS,eAAe,QAAQ,SAAS,CAAC,CAAC;AAAA,IAC7C;AAAA,EACF;AACA,MAAI,YAAY,GAAG;AACjB,WAAO;AAAA,MACL;AAAA,MACA,MAAM,EAAE,OAAO,EAAE,OAAO,QAAQ,OAAO,SAAS,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAAA,IACjF;AAAA,EACF;AACA,QAAM,QAAQ,aAAa,cAAc,MAAM;AAC/C,QAAM,QAAQ,QAAQ;AACtB,QAAM,MAAM,SAAS,EAAE,QAAQ,EAAE,EAAE,GAAG,OAAO,EAAE,OAAO,CAAC,OAAO,OAAO,EAAE,GAAG,SAAS,SAAS,CAAC;AAC7F,QAAM,QAAQ,eAAe,CAAC;AAC9B,QAAM,cAAc,eAAe,OAAO;AAC1C,MAAI,UAAU;AACd,QAAM,YAAY,MAAM,YAAY,OAAO,CAAC,KAAK,GAAG,IAAI,CAAC,KAAK,OAAO;AACrE,QAAM,UAAU,CAAC,KAAK,KAAK,UAAU;AACnC,UAAM,UAAU,UAAU;AAC1B,UAAM,UAAU,IAAI,aAAa,KAAK;AACtC,UAAM,YAAY,YAAY,OAAO,IAAI;AACzC,UAAM,kBAAkB;AAAA,MACtB,EAAE,MAAM,SAAS,MAAM,CAAC,OAAO,EAAE;AAAA,MACjC,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE;AAAA,MACnC,EAAE,MAAM,WAAW,MAAM,CAAC,OAAO,iBAAiB,EAAE;AAAA,MACpD,EAAE,MAAM,SAAS,MAAM,CAAC,GAAG,EAAE;AAAA,MAC7B,EAAE,MAAM,SAAS,MAAM,CAAC,GAAG,EAAE;AAAA,IAC/B;AACA,UAAM,eAAe;AACrB,cAAU,SAAS,iBAAiB,SAAS,SAAS,SAAS,eAAe;AAC9E,yCAAqC,UAAU,YAAY;AAAA,EAC7D;AACA,WAAS,MAAM,GAAG,MAAM,OAAO,OAAO,GAAG;AACvC,UAAM,MAAM,MAAM;AAClB,aAAS,MAAM,KAAK,OAAO,GAAG,OAAO,GAAG;AACtC,cAAQ,KAAK,KAAK,CAAC,OAAO,WAAW,CAAC;AAAA,IACxC;AAAA,EACF;AACA,WAAS,cAAc,aAAa,cAAc,OAAO,eAAe,GAAG;AACzE,UAAM,UAAU,UAAU;AAC1B,UAAM,eAAe,IAAI,cAAc,CAAC,OAAO,cAAc,CAAC,CAAC;AAC/D,UAAM,YAAY,YAAY,OAAO,IAAI;AACzC,UAAM,mBAAmB;AAAA,MACvB,EAAE,MAAM,SAAS,MAAM,CAAC,OAAO,EAAE;AAAA,MACjC,EAAE,MAAM,SAAS,MAAM,CAAC,SAAS,EAAE;AAAA,MACnC,EAAE,MAAM,SAAS,MAAM,CAAC,KAAK,EAAE;AAAA,IACjC;AACA,UAAM,eAAe;AACrB,cAAU,SAAS,iBAAiB,cAAc,SAAS,SAAS,gBAAgB;AACpF,yCAAqC,UAAU,YAAY;AAC3D,UAAM,MAAM,QAAQ;AACpB,UAAM,MAAM,MAAM;AAClB,aAAS,MAAM,KAAK,OAAO,GAAG,OAAO,GAAG;AACtC,cAAQ,KAAK,KAAK,QAAQ,KAAK;AAAA,IACjC;AAAA,EACF;AACA,MAAI,cAAc;AAClB,YAAU,OAAO,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,GAAG,MAAM,CAAC,OAAO,CAAC,EAAE,EAAE,CAAC;AACrG,uCAAqC,UAAU,WAAW;AAC1D,MAAI,SAAS,UAAU,EAAE,QAAQ,EAAE,GAAG,KAAK,QAAQ,GAAG,SAAS,UAAU,OAAO,EAAE,MAAM,GAAG,WAAW,EAAE,EAAE,CAAC;AAC3G,uCAAqC,UAAU,GAAG;AAClD,QAAM,WAAW,OAAO,MAAM,GAAG,EAAE;AACnC,WAAS,KAAK,CAAC;AACf,gBAAc;AACd,YAAU,SAAS,EAAE,QAAQ,EAAE,GAAG,QAAQ,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AAC5F,uCAAqC,UAAU,WAAW;AAC1D,QAAM,aAAa;AACnB,WAAS,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,OAAO,EAAE,OAAO,SAAS,GAAG,SAAS,SAAS,CAAC;AAC1F,uCAAqC,UAAU,UAAU;AACzD,SAAO,CAAC,QAAQ,OAAO;AACzB;AACA,IAAI,cAAc;AAAA,EAChB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,oBAAoB,MAAM;AAAA,EAC5B,YAAY,UAAU;AACpB,SAAK,gBAAgB,CAAC,SAAS,YAAY;AAC3C,SAAK,WAAW;AAChB,SAAK,gBAAgB,CAAC,IAAI,GAAG,CAAC;AAC9B,SAAK,OAAO;AACZ,SAAK,cAAc;AACnB,SAAK,iBAAiB,mBAAmB,KAAK,WAAW;AACzD,SAAK,WAAW,gBAAgB,KAAK,gBAAgB,KAAK,aAAa,KAAK,aAAa;AACzF,SAAK,YAAY;AAAA,EACnB;AAAA,EACA,cAAc;AACZ,UAAM,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA,YAgET,kCAAkC;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAqD1C,WAAO;AAAA,EACT;AACF;AAGA,SAAS,WAAW,MAAM;AACxB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,OAAO,QAAQ,WAAW,IAAI;AACtC,QAAM,EAAE,eAAe,UAAU,WAAW,YAAY,IAAI;AAC5D,QAAM,CAAC,OAAO,aAAa,YAAY,WAAW,IAAI,OAAO;AAC7D,QAAM,CAAC,WAAW,QAAQ,IAAI,eAAe,OAAO,cAAc,CAAC,aAAa,UAAU;AAC1F,QAAM,WAAW;AAAA,IACf;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,EACF;AACA,QAAM,UAAU,IAAI,kBAAkB,QAAQ;AAC9C,QAAM,sBAAsB,kBAAkB,YAAY,IAAI;AAC9D,MAAI;AACJ,UAAQ;AAAA,SACD;AACH,mBAAa;AACb;AAAA,SACG;AACH,mBAAa;AACb;AAAA,SACG;AACH,mBAAa;AACb;AAAA,SACG;AACH,mBAAa;AACb;AAAA;AAEA,mBAAa;AACb;AAAA;AAEJ,QAAM,cAAc;AAAA,IAClB,EAAE,MAAM,SAAS,MAAM,CAAC,mBAAmB,EAAE;AAAA,IAC7C,EAAE,MAAM,SAAS,MAAM,CAAC,UAAU,EAAE;AAAA,IACpC,EAAE,MAAM,WAAW,MAAM,CAAC,SAAS,EAAE;AAAA,EACvC;AACA,SAAO,SAAS,iBAAiB,SAAS,CAAC,QAAQ,UAAU,GAAG,WAAW,WAAW;AACxF;AACA,IAAI,mBAAmB;AAAA,EACrB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,SAAS,QAAQ,MAAM;AACrB,QAAM,EAAE,QAAQ,SAAS,UAAU,MAAM,IAAI;AAC7C,QAAM,EAAE,MAAM,IAAI;AAClB,MAAI,EAAE,KAAK,IAAI;AACf,MAAI,OAAO,GAAG;AACZ,YAAQ,MAAM,MAAM;AAAA,EACtB;AACA,QAAM,IAAI;AACV,QAAM,QAAQ,EAAE,MAAM;AACtB,QAAM,MAAM,MAAM,MAAM;AACxB,QAAM,WAAW,IAAI,MAAM,QAAQ,CAAC;AACpC,MAAI,WAAW;AACf,WAAS,KAAK,GAAG,KAAK,OAAO,MAAM;AACjC,QAAI,OAAO,MAAM;AACf,eAAS,cAAc,EAAE,MAAM;AAAA,IACjC;AAAA,EACF;AACA,QAAM,YAAY,CAAC;AACnB,QAAM,QAAQ,IAAI,MAAM,KAAK,EAAE,KAAK,CAAC;AACrC,QAAMA,QAAO,EAAE,MAAM,MAAM;AAC3B,EAAAA,MAAK,QAAQ;AACb,QAAM,MAAM,IAAI,MAAM,GAAG;AACzB,WAAS,KAAK,GAAG,KAAK,IAAI,QAAQ,MAAM;AACtC,UAAM,QAAQ;AACd,UAAM,SAAS,OAAO,EAAE,QAAQ,EAAE,EAAE,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,MAAAA,MAAK,EAAE,CAAC;AAClF,UAAM,WAAW,SAAS,EAAE,QAAQ,EAAE,GAAG,OAAO,GAAG,SAAS,UAAU,OAAO,EAAE,OAAO,SAAS,EAAE,CAAC;AAClG,QAAI,MAAM;AACV,cAAU,KAAK,MAAM;AAAA,EACvB;AACA,YAAU,QAAQ,CAAC,OAAO,SAAS,YAAY,GAAG,MAAM,CAAC;AACzD,SAAO;AACT;AACA,IAAI,gBAAgB;AAAA,EAClB,YAAY;AAAA,EACZ,aAAa;AAAA,EACb,YAAY;AACd;AAGA,IAAI,iBAAiB;AAAA,EACnB;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AACA,WAAW,gBAAgB,gBAAgB;AACzC,iBAAe,YAAY;AAC7B;AAGA,IAAI,gBAAgB,MAAM;AAAA,EACxB,YAAY,QAAQ;AAClB,SAAK,SAAS;AACd,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AACtB,SAAK,cAA8B,oBAAI,IAAI;AAC3C,SAAK,cAA8B,oBAAI,IAAI;AAC3C,SAAK,eAAe;AACpB,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,oBAAoBA,OAAM,OAAO;AAC/B,WAAO,KAAK,cAAcA,OAAM,OAAO,IAAI;AAAA,EAC7C;AAAA,EACA,cAAcA,OAAM,OAAO,mBAAmB,OAAO;AACnD,UAAM,MAAM,aAAaA,OAAM,KAAK;AACpC,QAAI,CAAC,KAAK,YAAY,IAAI,GAAG,GAAG;AAC9B,WAAK,YAAY,IAAI,KAAK,CAAC,CAAC;AAAA,IAC9B;AACA,QAAI,CAAC,KAAK,YAAY,IAAI,GAAG,GAAG;AAC9B,WAAK,YAAY,IAAI,KAAK,CAAC,CAAC;AAAA,IAC9B;AACA,SAAK,gBAAgBA;AACrB,SAAK;AACL,QAAI,KAAK,YAAY,IAAI,GAAG,EAAE,SAAS,GAAG;AACxC,WAAK;AACL,YAAM,aAAa,KAAK,YAAY,IAAI,GAAG,EAAE,MAAM;AACnD,WAAK,YAAY,IAAI,GAAG,EAAE,KAAK,UAAU;AACzC,aAAO;AAAA,IACT;AACA,SAAK,qBAAqBA;AAC1B,UAAM,YAAY,KAAK,OAAO,aAAa,EAAE,MAAAA,OAAM,OAAO,iBAAiB,CAAC;AAC5E,SAAK,YAAY,IAAI,GAAG,EAAE,KAAK,SAAS;AACxC,WAAO;AAAA,EACT;AAAA,EACA,cAAc,SAASA,OAAM,OAAO;AAClC,QAAI,KAAK,YAAY,SAAS,GAAG;AAC/B;AAAA,IACF;AACA,UAAM,MAAM,aAAaA,OAAM,KAAK;AACpC,QAAI,CAAC,KAAK,YAAY,IAAI,GAAG,GAAG;AAC9B,WAAK,YAAY,IAAI,KAAK,CAAC,CAAC;AAAA,IAC9B;AACA,SAAK,YAAY,IAAI,GAAG,EAAE,KAAK,OAAO;AACtC,SAAK;AACL,SAAK;AACL,UAAM,aAAa,KAAK,YAAY,IAAI,GAAG;AAC3C,UAAM,cAAc,WAAW,QAAQ,OAAO;AAC9C,QAAI,cAAc,GAAG;AACnB,YAAM,IAAI,MAAM,wEAAwE;AAAA,IAC1F;AACA,eAAW,OAAO,aAAa,CAAC;AAChC,SAAK,gBAAgBA;AAAA,EACvB;AAAA,EACA,oBAAoB,SAASA,OAAM,OAAO;AACxC,YAAQ,SAAS,WAAW,KAAK,EAAE,KAAK,MAAM;AAC5C,WAAK,cAAc,SAASA,OAAM,KAAK;AAAA,IACzC,GAAG,CAAC,QAAQ;AAAA,IACZ,CAAC;AAAA,EACH;AAAA,EACA,oBAAoB;AAClB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,oBAAoB;AAClB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,UAAU;AACR,SAAK,YAAY,QAAQ,CAAC,SAAS,QAAQ;AACzC,cAAQ,QAAQ,CAAC,YAAY;AAC3B,gBAAQ,QAAQ;AAAA,MAClB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,YAAY,QAAQ,CAAC,SAAS,QAAQ;AACzC,cAAQ,QAAQ,CAAC,YAAY;AAC3B,gBAAQ,QAAQ;AAAA,MAClB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,cAA8B,oBAAI,IAAI;AAC3C,SAAK,cAA8B,oBAAI,IAAI;AAC3C,SAAK,iBAAiB;AACtB,SAAK,iBAAiB;AACtB,SAAK,eAAe;AACpB,SAAK,oBAAoB;AAAA,EAC3B;AACF;AACA,SAAS,aAAaA,OAAM,OAAO;AACjC,SAAO,GAAGA,SAAQ;AACpB;AAGA,IAAI,kBAAkB,MAAM;AAAA,EAC1B,YAAY,QAAQ;AAClB,SAAK,SAAS;AACd,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AACvB,SAAK,eAA+B,oBAAI,IAAI;AAC5C,SAAK,eAA+B,oBAAI,IAAI;AAC5C,SAAK,eAAe;AACpB,SAAK,oBAAoB;AAAA,EAC3B;AAAA,EACA,eAAe,OAAO,QAAQ,QAAQ,OAAO;AAC3C,UAAM,mBAAmB,mBAAmB,MAAM;AAClD,UAAM,WAAW,QAAQ,SAAS;AAClC,UAAM,MAAM,cAAc,OAAO,QAAQ,QAAQ,KAAK;AACtD,QAAI,CAAC,KAAK,aAAa,IAAI,GAAG,GAAG;AAC/B,WAAK,aAAa,IAAI,KAAK,CAAC,CAAC;AAAA,IAC/B;AACA,QAAI,CAAC,KAAK,aAAa,IAAI,GAAG,GAAG;AAC/B,WAAK,aAAa,IAAI,KAAK,CAAC,CAAC;AAAA,IAC/B;AACA,SAAK,gBAAgB;AACrB,SAAK;AACL,QAAI,KAAK,aAAa,IAAI,GAAG,EAAE,SAAS,GAAG;AACzC,WAAK;AACL,YAAM,cAAc,KAAK,aAAa,IAAI,GAAG,EAAE,MAAM;AACrD,WAAK,aAAa,IAAI,GAAG,EAAE,KAAK,WAAW;AAC3C,aAAO;AAAA,IACT;AACA,SAAK,qBAAqB;AAC1B,UAAM,aAAa,KAAK,OAAO,cAAc;AAAA,MAC3C,MAAM,CAAC,OAAO,MAAM;AAAA,MACpB;AAAA,MACA;AAAA,IACF,CAAC;AACD,SAAK,aAAa,IAAI,GAAG,EAAE,KAAK,UAAU;AAC1C,WAAO;AAAA,EACT;AAAA,EACA,eAAe,SAAS,OAAO,QAAQ,QAAQ,OAAO;AACpD,QAAI,KAAK,aAAa,SAAS,GAAG;AAChC;AAAA,IACF;AACA,UAAM,MAAM,cAAc,OAAO,QAAQ,QAAQ,KAAK;AACtD,QAAI,CAAC,KAAK,aAAa,IAAI,GAAG,GAAG;AAC/B,WAAK,aAAa,IAAI,KAAK,CAAC,CAAC;AAAA,IAC/B;AACA,SAAK,aAAa,IAAI,GAAG,EAAE,KAAK,OAAO;AACvC,SAAK;AACL,SAAK;AACL,UAAM,cAAc,KAAK,aAAa,IAAI,GAAG;AAC7C,UAAM,eAAe,YAAY,QAAQ,OAAO;AAChD,QAAI,eAAe,GAAG;AACpB,YAAM,IAAI,MAAM,0EAA0E;AAAA,IAC5F;AACA,gBAAY,OAAO,cAAc,CAAC;AAClC,UAAM,mBAAmB,mBAAmB,MAAM;AAClD,UAAM,WAAW,QAAQ,SAAS;AAClC,SAAK,gBAAgB;AAAA,EACvB;AAAA,EACA,qBAAqB;AACnB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,qBAAqB;AACnB,WAAO,KAAK;AAAA,EACd;AAAA,EACA,UAAU;AACR,SAAK,aAAa,QAAQ,CAAC,UAAU,QAAQ;AAC3C,eAAS,QAAQ,CAAC,YAAY;AAC5B,gBAAQ,QAAQ;AAAA,MAClB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,aAAa,QAAQ,CAAC,UAAU,QAAQ;AAC3C,eAAS,QAAQ,CAAC,YAAY;AAC5B,gBAAQ,QAAQ;AAAA,MAClB,CAAC;AAAA,IACH,CAAC;AACD,SAAK,eAA+B,oBAAI,IAAI;AAC5C,SAAK,eAA+B,oBAAI,IAAI;AAC5C,SAAK,kBAAkB;AACvB,SAAK,kBAAkB;AACvB,SAAK,eAAe;AACpB,SAAK,oBAAoB;AAAA,EAC3B;AACF;AACA,SAAS,cAAc,OAAO,QAAQ,QAAQ,OAAO;AACnD,SAAO,GAAG,SAAS,UAAU,UAAU;AACzC;AACA,SAAS,mBAAmB,QAAQ;AAClC,MAAI,WAAW,cAAc;AAC3B,WAAO;AAAA,EACT,OAAO;AACL,UAAM,IAAI,MAAM,GAAG,0BAA0B;AAAA,EAC/C;AACF;AAGA,IAAI,8BAA8B,IAAI,EAAE,UAAU,mCAAmC;AACrF,IAAI,kBAAkB,CAAC,QAAQ,YAAY;AACzC,QAAM,0CAA0C,OAAO,OAAO;AAC9D,QAAM,SAAS,QAAQ;AACvB,QAAM,WAAW,QAAQ;AACzB,MAAI,SAAS,MAAM,CAAC,MAAM,KAAK,uCAAuC,GAAG;AACvE,WAAO;AAAA,EACT;AACA,eAAa,OAAO,SAAS,KAAK,2CAA2C,OAAO,MAAM,UAAU,OAAO,MAAM,QAAQ,MAAM,0DAA0D;AACzL,MAAI,kBAAkB,KAAK,KAAK,KAAK,KAAK,SAAS,EAAE,CAAC;AACtD,MAAI,kBAAkB,yCAAyC;AAC7D,sBAAkB,KAAK,KAAK,KAAK,KAAK,SAAS,EAAE,CAAC;AAClD,iBAAa,OAAO,mBAAmB,yCAAyC,MAAM,6CAA6C;AACnI,WAAO,CAAC,iBAAiB,iBAAiB,eAAe;AAAA,EAC3D,OAAO;AACL,WAAO,CAAC,iBAAiB,iBAAiB,CAAC;AAAA,EAC7C;AACF;AACA,IAAI,gBAAgB,cAAc,cAAc;AAAA,EAC9C,YAAY,QAAQ,mBAAmB,OAAO;AAC5C,UAAM;AACN,SAAK,uBAAuC,oBAAI,QAAQ;AACxD,SAAK,0BAA0B;AAC/B,SAAK,WAAW;AAChB,SAAK,iBAAiB;AACtB,SAAK,4BAA4B,CAAC;AAClC,SAAK,yBAAyB,CAAC;AAC/B,SAAK,yBAAyB,CAAC;AAC/B,SAAK,eAAe;AACpB,QAAI,CAAC,kBAAkB,GAAG;AACxB,YAAM,IAAI,MAAM,wCAAwC;AAAA,IAC1D;AACA,SAAK,gBAAgB,CAAC;AACtB,SAAK,SAAS;AACd,SAAK,QAAQ,OAAO;AACpB,SAAK,wBAAwB;AAC7B,SAAK,qBAAqB;AAC1B,SAAK,mBAAmB;AACxB,SAAK,gBAAgB,IAAI,cAAc,KAAK,MAAM;AAClD,SAAK,iBAAiB,IAAI,gBAAgB,KAAK,MAAM;AACrD,SAAK,YAAY,IAAI,YAAY,MAAM,OAAO,CAAC;AAC/C,QAAI,KAAK,kBAAkB;AACzB,WAAK,WAAW,KAAK,OAAO,eAAe;AAAA,QACzC,MAAM;AAAA,QACN,OAAO;AAAA,MACT,CAAC;AAAA,IACH;AACA,QAAI,IAAI,EAAE,QAAQ,yBAAyB,GAAG;AAC5C,WAAK,cAAc,SAAS,cAAc,QAAQ;AAClD,WAAK,YAAY,QAAQ;AACzB,WAAK,YAAY,SAAS;AAC1B,WAAK,eAAe,KAAK,YAAY,WAAW,QAAQ;AACxD,WAAK,aAAa,UAAU;AAAA,QAC1B;AAAA,QACA,QAAQ;AAAA,MACV,CAAC;AACD,eAAS,KAAK,YAAY,KAAK,WAAW;AAAA,IAC5C;AAAA,EACF;AAAA,EACA,aAAa;AACX,WAAO,cAAc;AAAA,EACvB;AAAA,EACA,iBAAiB;AACf,WAAO;AAAA,EACT;AAAA,EACA,wBAAwB;AACtB,WAAO,eAAe,UAAU,eAAe,WAAW,eAAe;AAAA,EAC3E;AAAA,EACA,YAAY,QAAQ,QAAQ,OAAO;AACjC,QAAI,KAAK,0BAA0B,QAAQ,MAAM,KAAK,GAAG;AACvD,aAAO;AAAA,IACT;AACA,QAAI,CAAC,KAAK,UAAU,IAAI,MAAM,GAAG;AAC/B,aAAO;AAAA,IACT;AACA,UAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,SAAK,OAAO,MAAM;AAClB,QAAI,CAAC,SAAS,WAAW,WAAW,GAAG;AACrC,aAAO;AAAA,IACT;AACA,QAAI,KAAK,qBAAqB,IAAI,MAAM,GAAG;AACzC,WAAK,0BAA0B,KAAK,MAAM;AAC1C,aAAO;AAAA,IACT;AACA,UAAM,EAAE,mBAAmB,IAAI,KAAK,UAAU,IAAI,MAAM;AACxD,QAAI,sBAAsB,MAAM;AAC9B,WAAK,YAAY,mBAAmB,KAAK,QAAQ,KAAK;AACtD,WAAK,YAAY,mBAAmB,KAAK,QAAQ,KAAK;AAAA,IACxD;AACA,SAAK,gBAAgB,MAAM;AAC3B,SAAK,UAAU,OAAO,MAAM;AAC5B,WAAO;AAAA,EACT;AAAA,EACA,SAAS;AACP,WAAO;AAAA,MACL,eAAe,KAAK,cAAc;AAAA,MAClC,wBAAwB,KAAK,cAAc;AAAA,MAC3C,YAAY;AAAA,IACd;AAAA,EACF;AAAA,EACA,gBAAgB,QAAQ;AACtB,UAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,QAAI,CAAC,cAAc,CAAC,WAAW,cAAc;AAC3C;AAAA,IACF;AACA,QAAI,aAAa,WAAW,cAAc;AACxC,YAAM,cAAc,WAAW;AAC/B,UAAI,YAAY,mBAAmB,YAAY;AAC7C,aAAK,eAAe,eAAe,YAAY,SAAS,YAAY,OAAO,YAAY,QAAQ,YAAY,QAAQ,YAAY,KAAK;AAAA,MACtI;AACA,kBAAY,UAAU;AAAA,IACxB,OAAO;AACL,YAAM,aAAa,WAAW;AAC9B,WAAK,cAAc,cAAc,WAAW,QAAQ,WAAW,MAAM,WAAW,KAAK;AACrF,iBAAW,SAAS;AAAA,IACtB;AACA,eAAW,eAAe;AAAA,EAC5B;AAAA,EACA,SAAS,QAAQ;AACf,QAAI,KAAK,UAAU,IAAI,MAAM,GAAG;AAC9B,YAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,aAAO,WAAW;AAAA,IACpB;AACA,WAAO;AAAA,EACT;AAAA,EACA,OAAO,QAAQ;AACb,UAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,eAAW;AAAA,EACb;AAAA,EACA,OAAO,QAAQ;AACb,QAAI,KAAK,UAAU,IAAI,MAAM,GAAG;AAC9B,YAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,iBAAW;AAAA,IACb;AAAA,EACF;AAAA,EACA,MAAM,QAAQ,OAAO,OAAO;AAC1B,QAAI,UAAU,eAAe,UAAU,MAAM;AAC3C,YAAM,IAAI,MAAM,uEAAuE;AAAA,IACzF;AACA,UAAM,SAAS,EAAE,IAAI,KAAK,WAAW,EAAE;AACvC,SAAK,UAAU,IAAI,QAAQ,EAAE,OAAO,OAAO,QAAQ,UAAU,EAAE,CAAC;AAChE,WAAO;AAAA,EACT;AAAA,EACA,KAAK,QAAQ,QAAQ,OAAO,OAAO,UAAU;AAC3C,QAAI,UAAU,aAAa;AACzB,YAAM,IAAI,MAAM,uEAAuE;AAAA,IACzF;AACA,SAAK,UAAU,IAAI,QAAQ,EAAE,OAAO,OAAO,QAAQ,SAAS,CAAC;AAAA,EAC/D;AAAA,EACA,cAAc;AACZ,SAAK,uBAAuB;AAC5B,SAAK,MAAM,OAAO,CAAC,KAAK,sBAAsB,OAAO,CAAC,CAAC;AACvD,SAAK,wBAAwB;AAC7B,SAAK,0BAA0B;AAC/B,SAAK,uBAAuC,oBAAI,QAAQ;AACxD,SAAK,0BAA0B,QAAQ,CAAC,MAAM;AAC5C,WAAK,gBAAgB,CAAC;AACtB,WAAK,UAAU,OAAO,CAAC;AAAA,IACzB,CAAC;AACD,SAAK,uBAAuB,QAAQ,CAAC,MAAM,KAAK,cAAc,cAAc,EAAE,QAAQ,EAAE,MAAM,EAAE,KAAK,CAAC;AACtG,SAAK,uBAAuB,QAAQ,CAAC,MAAM,KAAK,cAAc,oBAAoB,EAAE,QAAQ,EAAE,MAAM,EAAE,KAAK,CAAC;AAC5G,SAAK,4BAA4B,CAAC;AAClC,SAAK,yBAAyB,CAAC;AAC/B,SAAK,yBAAyB,CAAC;AAAA,EACjC;AAAA,EACA,4BAA4B;AAC1B,QAAI,CAAC,KAAK,uBAAuB;AAC/B,WAAK,wBAAwB,KAAK,OAAO,qBAAqB;AAAA,IAChE;AAAA,EACF;AAAA,EACA,yBAAyB;AACvB,QAAI,KAAK,oBAAoB;AAC3B,WAAK,mBAAmB,IAAI;AAC5B,WAAK,qBAAqB;AAAA,IAC5B;AAAA,EACF;AAAA,EACA,iBAAiB;AACf,QAAI,CAAC,KAAK,oBAAoB;AAC5B,WAAK,qBAAqB,KAAK,sBAAsB,iBAAiB;AAAA,IACxE;AACA,WAAO,KAAK;AAAA,EACd;AAAA,EACA,MAAM,cAAc,SAASA,OAAM;AACjC,UAAM,UAAU,KAAK,cAAc,cAAcA,OAAM,eAAe,WAAW,eAAe,QAAQ;AACxG,SAAK,0BAA0B;AAC/B,SAAK,uBAAuB;AAC5B,SAAK,sBAAsB,mBAAmB,SAAS,GAAG,SAAS,GAAGA,KAAI;AAC1E,SAAK,YAAY;AACjB,UAAM,QAAQ,SAAS,WAAW,IAAI;AACtC,UAAM,SAAS,QAAQ,eAAe,EAAE,MAAM,CAAC;AAC/C,YAAQ,MAAM;AACd,QAAI,WAAW,MAAM;AACnB,WAAK,cAAc,cAAc,SAASA,OAAM,eAAe,WAAW,eAAe,QAAQ;AAAA,IACnG;AACA,QAAI,IAAI,EAAE,QAAQ,yBAAyB,GAAG;AAC5C,mBAAa,OAAO,KAAK,iBAAiB,QAAQ,MAAM,wCAAwC;AAChG,WAAK,aAAa,kBAAkB;AAAA,IACtC;AACA,WAAO;AAAA,EACT;AAAA,EACA,qBAAqB,QAAQ,MAAM;AACjC,UAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,SAAK,gBAAgB,MAAM;AAC3B,eAAW,SAAS;AACpB,WAAO,WAAW;AAAA,EACpB;AAAA,EACA,SAAS,QAAQ;AACf,UAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,UAAM,EAAE,OAAO,IAAI;AACnB,QAAI,UAAU,MAAM;AAClB,YAAM,IAAI,MAAM,6DAA6D;AAAA,IAC/E;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,KAAK,QAAQ;AACjB,QAAI,CAAC,KAAK,UAAU,IAAI,MAAM,GAAG;AAC/B,YAAM,IAAI,MAAM,UAAU,4BAA4B;AAAA,IACxD;AACA,UAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,UAAM,EAAE,OAAO,IAAI;AACnB,QAAI,UAAU,MAAM;AAClB,aAAO,KAAK,qBAAqB,QAAQ,MAAM;AAAA,IACjD;AACA,QAAI;AACJ,QAAI,WAAW,UAAU,aAAa;AACpC,YAAM,KAAK,MAAM,QAAQ,IAAI;AAAA,QAC3B,KAAK,KAAK,WAAW,mBAAmB,KAAK,MAAM;AAAA,QACnD,KAAK,KAAK,WAAW,mBAAmB,KAAK,MAAM;AAAA,MACrD,CAAC;AACD,YAAM,aAAa,GAAG;AACtB,YAAM,aAAa,GAAG;AACtB,aAAO,qBAAqB,uBAAuB,YAAY,UAAU;AAAA,IAC3E,OAAO;AACL,YAAM,aAAa,WAAW;AAC9B,YAAM,OAAO,MAAM,KAAK,cAAc,WAAW,QAAQ,WAAW,IAAI;AACxE,aAAO,wBAAwB,MAAM,WAAW,KAAK;AAAA,IACvD;AACA,SAAK,qBAAqB,QAAQ,IAAI;AACtC,WAAO;AAAA,EACT;AAAA,EACA,UAAU,QAAQ;AAChB,UAAM,gBAAgB,KAAK,UAAU,IAAI,MAAM;AAC/C,UAAM,EAAE,QAAQ,OAAO,OAAO,aAAa,IAAI;AAC/C,QAAI,UAAU,aAAa;AACzB,YAAM,IAAI,MAAM,sDAAsD;AAAA,IACxE;AACA,QAAI,gBAAgB,MAAM;AACxB,UAAI,UAAU,MAAM;AAClB,cAAM,IAAI,MAAM,gCAAgC;AAAA,MAClD,OAAO;AACL,cAAM,IAAI,MAAM,iCAAiC;AAAA,MACnD;AAAA,IACF;AACA,UAAMA,QAAO,aAAa;AAC1B,UAAM,UAAU,KAAK,cAAc,cAAcA,OAAM,aAAa,KAAK;AACzE,SAAK,0BAA0B;AAC/B,SAAK,uBAAuB;AAC5B,SAAK,sBAAsB,mBAAmB,aAAa,QAAQ,GAAG,SAAS,GAAGA,KAAI;AACtF,SAAK,YAAY;AACjB,UAAM,aAAa,KAAK,eAAe,OAAO,KAAK;AACnD,UAAM,YAAY,OAAO,EAAE,yBAAyB,UAAU;AAC9D,UAAM,aAAa,KAAK,UAAU,IAAI,WAAW,MAAM;AACvD,eAAW,eAAe,EAAE,MAAAA,OAAM,OAAO,KAAK,sBAAsB,GAAG,QAAQ,QAAQ;AACvF,WAAO,EAAE,WAAW,QAAQ,SAAS,SAASA,MAAK;AAAA,EACrD;AAAA,EACA,WAAW,IAAI;AACb,UAAM,OAAO,KAAK,SAAS,GAAG,MAAM;AACpC,QAAI,GAAG,UAAU,UAAU;AACzB,UAAI;AACF,cAAM,UAAU,KAAK,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC;AAC5D,eAAO,OAAO,GAAG,OAAO,GAAG,OAAO,OAAO;AAAA,MAC3C,SAAS,IAAP;AACA,cAAM,IAAI,MAAM,kDAAkD;AAAA,MACpE;AAAA,IACF;AACA,WAAO,OAAO,GAAG,OAAO,GAAG,OAAO,IAAI;AAAA,EACxC;AAAA,EACA,MAAM,KAAK,GAAG;AACZ,UAAM,kBAAkB,KAAK;AAC7B,UAAM,kBAAkB,CAAC;AACzB,QAAI,gBAAgB;AACpB,QAAI,KAAK,sBAAsB,MAAM;AACnC,WAAK,qBAAqB;AAC1B,sBAAgB;AAAA,IAClB,OAAO;AACL,WAAK,aAAa,KAAK,eAAe;AAAA,IACxC;AACA,SAAK,eAAe;AACpB,MAAE;AACF,UAAM,8BAA8B,aAAa,QAAQ,KAAK,aAAa,IAAI,CAAC,MAAM,EAAE,KAAK,CAAC,EAAE,OAAO,CAAC,MAAM,KAAK,IAAI;AACvH,UAAM,4BAA4B,aAAa,QAAQ,KAAK,aAAa,IAAI,CAAC,MAAM,EAAE,IAAI,CAAC,EAAE,OAAO,CAAC,MAAM,KAAK,IAAI;AACpH,SAAK,eAAe;AACpB,QAAI,eAAe;AACjB,WAAK,qBAAqB;AAAA,IAC5B;AACA,UAAM,MAAM;AAAA,MACV,cAAc,KAAK;AAAA,MACnB,gBAAgB,KAAK;AAAA,MACrB,UAAU;AAAA,MACV,QAAQ;AAAA,IACV;AACA,UAAM,WAAW,MAAM,QAAQ,IAAI,2BAA2B;AAC9D,QAAI,cAAc,aAAa,IAAI,QAAQ;AAC3C,QAAI,yBAAyB,MAAM,SAAS,IAAI,CAAC,GAAG,QAAQ,EAAE,MAAM,0BAA0B,KAAK,IAAI,EAAE,EAAE,EAAE,IAAI,CAAC,MAAM,GAAG,EAAE,SAAS,EAAE,IAAI,EAAE,KAAK,IAAI;AACvJ,SAAK,eAAe;AACpB,SAAK,iBAAiB;AACtB,WAAO;AAAA,EACT;AAAA,EACA,eAAe,OAAO,OAAO,QAAQ;AACnC,QAAI,UAAU,YAAY,UAAU,QAAQ,OAAO,SAAS,KAAK,aAAa,SAAS,OAAO,EAAE,GAAG;AACjG,eAAS,OAAO,IAAI,CAAC,MAAM,aAAa,aAAa,CAAC,CAAC;AAAA,IACzD;AACA,UAAM,SAAS,KAAK,MAAM,QAAQ,OAAO,KAAK;AAC9C,WAAO,EAAE,QAAQ,OAAO,MAAM;AAAA,EAChC;AAAA,EACA,gBAAgB,SAAS;AACvB,QAAI,CAAC,SAAS;AACZ,aAAO;AAAA,IACT;AACA,UAAM,aAAa,KAAK,UAAU,IAAI,QAAQ,MAAM;AACpD,QAAI,aAAa,WAAW,cAAc;AACxC,YAAM,OAAO,WAAW;AACxB,UAAI,KAAK,mBAAmB,oBAAoB;AAC9C,eAAO,KAAK;AAAA,MACd,OAAO;AACL,eAAO,KAAK,QAAQ,WAAW;AAAA,MACjC;AAAA,IACF;AACA,UAAM,aAAa,WAAW;AAC9B,WAAO,EAAE,QAAQ,GAAG,MAAM,WAAW,MAAM,QAAQ,WAAW,OAAO;AAAA,EACvE;AAAA,EACA,MAAM,aAAa,OAAO;AACxB,QAAI,KAAK,kBAAkB;AACzB,aAAO,KAAK,oBAAoB,KAAK;AAAA,IACvC,OAAO;AACL,aAAO;AAAA,IACT;AAAA,EACF;AAAA,EACA,YAAY,QAAQ;AAClB,UAAM,aAAa,KAAK,UAAU,IAAI,MAAM;AAC5C,QAAI,WAAW,cAAc;AAC3B;AAAA,IACF;AACA,UAAMA,QAAO,mBAAmB,WAAW,KAAK,IAAI,aAAa,cAAc,WAAW,KAAK;AAC/F,UAAM,UAAU,KAAK,cAAc,cAAcA,OAAM,KAAK,sBAAsB,CAAC;AACnF,eAAW,eAAe,EAAE,MAAAA,OAAM,OAAO,KAAK,sBAAsB,GAAG,QAAQ,QAAQ;AACvF,QAAI,WAAW,QAAQ;AACrB,YAAM,gBAAgB,KAAK,cAAc,oBAAoBA,OAAM,eAAe,YAAY,eAAe,QAAQ;AACrH,YAAM,cAAc,cAAc,eAAe;AACjD,UAAI,WAAW,UAAU,WAAW,WAAW,UAAU,QAAQ;AAC/D,YAAI,WAAW,WAAW,EAAE,IAAI,WAAW,MAAM;AAAA,MACnD,OAAO;AACL,YAAI,aAAa,WAAW,EAAE,IAAI,WAAW,MAAM;AAAA,MACrD;AACA,oBAAc,MAAM;AACpB,WAAK,0BAA0B;AAC/B,WAAK,uBAAuB;AAC5B,WAAK,sBAAsB,mBAAmB,eAAe,GAAG,SAAS,GAAGA,KAAI;AAChF,YAAM,cAAc;AAAA,QAClB,MAAAA;AAAA,QACA,OAAO,eAAe,YAAY,eAAe;AAAA,QACjD,QAAQ;AAAA,MACV;AACA,WAAK,uBAAuB,KAAK,WAAW;AAAA,IAC9C;AAAA,EACF;AAAA,EACA,aAAa,gBAAgB;AAC3B,QAAI,gBAAgB;AACpB,QAAI,YAAY;AAChB,UAAM,UAAU,CAAC;AACjB,mBAAe,QAAQ,CAAC,MAAM;AAC5B,UAAI,EAAE,KAAK,WAAW,GAAG;AACvB,UAAE,OAAO,CAAC,CAAC;AAAA,MACb;AACA,UAAI;AACJ,cAAQ,EAAE,KAAK;AAAA,aACR;AACH,0BAAgB;AAChB;AAAA,aACG;AACH,0BAAgB;AAChB;AAAA,aACG;AACH,0BAAgB;AAChB;AAAA,aACG;AACH,0BAAgB;AAChB;AAAA,aACG;AACH,0BAAgB;AAChB;AAAA,aACG;AACH,0BAAgB;AAChB;AAAA;AAEA,uBAAa,OAAO,OAAO,MAAM,eAAe,EAAE,KAAK,eAAe;AAAA;AAE1E,UAAI,cAAc,KAAK,cAAc,GAAG;AACtC,wBAAgB;AAAA,MAClB;AACA,sBAAgB,KAAK,KAAK,gBAAgB,aAAa,IAAI;AAC3D,kBAAY,EAAE,KAAK;AACnB,cAAQ,KAAK,aAAa;AAC1B,uBAAiB,EAAE,KAAK,SAAS;AAAA,IACnC,CAAC;AACD,UAAM,cAAc,IAAI,YAAY,aAAa;AACjD,mBAAe,QAAQ,CAAC,GAAG,OAAO;AAChC,YAAM,SAAS,QAAQ;AACvB,UAAI,EAAE,SAAS,SAAS;AACtB,YAAI,WAAW,aAAa,QAAQ,EAAE,KAAK,MAAM,EAAE,IAAI,EAAE,IAAI;AAAA,MAC/D,WAAW,EAAE,SAAS,UAAU;AAC9B,YAAI,YAAY,aAAa,QAAQ,EAAE,KAAK,MAAM,EAAE,IAAI,EAAE,IAAI;AAAA,MAChE,OAAO;AACL,YAAI,aAAa,aAAa,QAAQ,EAAE,KAAK,MAAM,EAAE,IAAI,EAAE,IAAI;AAAA,MACjE;AAAA,IACF,CAAC;AACD,UAAM,gBAAgB,KAAK,cAAc,cAAc,eAAe,eAAe,WAAW,eAAe,OAAO;AACtH,SAAK,MAAM,YAAY,eAAe,GAAG,aAAa,GAAG,aAAa;AACtE,UAAM,cAAc;AAAA,MAClB,MAAM;AAAA,MACN,OAAO,eAAe,WAAW,eAAe;AAAA,MAChD,QAAQ;AAAA,IACV;AACA,SAAK,uBAAuB,KAAK,WAAW;AAC5C,WAAO,EAAE,QAAQ,GAAG,MAAM,eAAe,QAAQ,cAAc;AAAA,EACjE;AAAA,EACA,iBAAiB,SAAS,QAAQ,aAAa,uBAAuB,QAAQ;AAC5E,QAAI,CAAC,QAAQ;AACX,eAAS,KAAK,eAAe,QAAQ,aAAa,WAAW;AAAA,IAC/D;AACA,QAAI,aAAa,cAAc,OAAO,KAAK,MAAM,GAAG;AAClD,WAAK,UAAU,IAAI,OAAO,MAAM,EAAE,SAAS,aAAa,uBAAuB,OAAO,OAAO,CAAC;AAC9F,aAAO;AAAA,IACT;AACA,SAAK,YAAY,OAAO,MAAM;AAC9B,YAAQ,WAAW,gBAAgB,KAAK,QAAQ,OAAO;AACvD,QAAI,iBAAiB,CAAC;AACtB,QAAI,eAAe,CAAC;AACpB,QAAI,CAAC,QAAQ,cAAc;AACzB,qBAAe,KAAK,EAAE,MAAM,WAAW,MAAM,CAAC,GAAG,EAAE,CAAC;AACpD,qBAAe,OAAO,OAAO,MAAM,EAAE,IAAI,CAAC,MAAM,EAAE,KAAK;AACvD,YAAM,eAAe;AACrB,mBAAa,IAAI,CAAC,MAAM;AACtB,uBAAe,KAAK,EAAE,MAAM,cAAc,MAAM,EAAE,CAAC;AAAA,MACrD,CAAC;AACD,YAAMY,WAAU,aAAa,eAAe,OAAO,KAAK;AACxD,qBAAe,KAAK,EAAE,MAAM,cAAc,MAAMA,SAAQ,CAAC;AACzD,UAAI,QAAQ,MAAM;AAChB,cAAMZ,QAAO,aAAa,cAAc,QAAQ,WAAW;AAC3D,uBAAe,KAAK,EAAE,MAAM,cAAc,MAAM,CAAC,QAAQ,SAASA,QAAO,IAAIA,KAAI,EAAE,CAAC;AAAA,MACtF;AAAA,IACF;AACA,UAAM,aAAa,OAAO,IAAI,CAAC,QAAQ,OAAO;AAC5C,UAAI,OAAO,UAAU,aAAa;AAChC,cAAM,IAAI,MAAM,iIAAiI;AAAA,MACnJ;AACA,WAAK,YAAY,OAAO,MAAM;AAC9B,aAAO;AAAA,QACL,OAAO,KAAK,UAAU,IAAI,OAAO,MAAM,EAAE;AAAA,QACzC,OAAO,OAAO;AAAA,QACd,MAAM,QAAQ,cAAc;AAAA,MAC9B;AAAA,IACF,CAAC;AACD,UAAM,MAAM,eAAe,SAAS,cAAc,YAAY,MAAM;AACpE,QAAI;AACJ,QAAI,OAAO,KAAK,eAAe;AAC7B,iBAAW,KAAK,cAAc;AAAA,IAChC,OAAO;AACL,iBAAW,gBAAgB,KAAK,QAAQ,SAAS,YAAY,MAAM;AACnE,WAAK,cAAc,OAAO;AAAA,IAC5B;AACA,QAAI,uBAAuB;AACzB,uBAAiB,CAAC,GAAG,gBAAgB,GAAG,qBAAqB;AAAA,IAC/D;AACA,UAAM,WAAW;AAAA,MACf,KAAK,gBAAgB,MAAM;AAAA,MAC3B,GAAG,OAAO,IAAI,CAAC,OAAO,KAAK,gBAAgB,EAAE,CAAC;AAAA,MAC9C,KAAK,aAAa,cAAc;AAAA,IAClC;AACA,UAAM,YAAY,KAAK,OAAO,gBAAgB;AAAA,MAC5C,QAAQ,SAAS,mBAAmB,CAAC;AAAA,MACrC,SAAS,SAAS,IAAI,CAAC,GAAG,QAAQ,EAAE,SAAS,IAAI,UAAU,EAAE,EAAE;AAAA,IACjE,CAAC;AACD,SAAK,0BAA0B;AAC/B,UAAM,OAAO,KAAK,eAAe;AACjC,UAAM,oBAAoB,KAAK,gBAAgB;AAC/C,QAAI,mBAAmB;AACrB,UAAI,KAAK,kBAAkB;AACzB,aAAK,eAAe,KAAK,UAAU,CAAC;AAAA,MACtC;AAAA,IACF;AACA,SAAK,YAAY,QAAQ;AACzB,SAAK,aAAa,GAAG,SAAS;AAC9B,SAAK,mBAAmB,QAAQ,SAAS,IAAI,QAAQ,SAAS,IAAI,QAAQ,SAAS,EAAE;AACrF,QAAI,mBAAmB;AACrB,UAAI,KAAK,kBAAkB;AACzB,aAAK,eAAe,KAAK,UAAU,CAAC;AAAA,MACtC;AAAA,IACF;AACA,SAAK;AACL,WAAO,QAAQ,CAAC,WAAW;AACzB,WAAK,qBAAqB,IAAI,OAAO,MAAM;AAAA,IAC7C,CAAC;AACD,SAAK,qBAAqB,IAAI,OAAO,MAAM;AAC3C,QAAI,IAAI,EAAE,IAAI,mCAAmC,KAAK,KAAK,yBAAyB;AAClF,WAAK,YAAY;AAAA,IACnB;AACA,QAAI,mBAAmB;AACrB,WAAK,aAAa,KAAK;AAAA,QACrB,MAAM,QAAQ,YAAY;AAAA,QAC1B,OAAO,KAAK,aAAa,KAAK,QAAQ;AAAA,MACxC,CAAC;AAAA,IACH;AACA,WAAO;AAAA,EACT;AAAA,EACA,MAAM,oBAAoB,UAAU;AAClC,UAAM,cAAc,KAAK,cAAc,cAAc,IAAI,eAAe,WAAW,eAAe,aAAa;AAC/G,UAAM,MAAM,KAAK,cAAc,cAAc,IAAI,eAAe,WAAW,eAAe,QAAQ;AAClG,SAAK,0BAA0B;AAC/B,SAAK,uBAAuB;AAC5B,SAAK,sBAAsB,gBAAgB,UAAU,GAAG,GAAG,aAAa,CAAC;AACzE,SAAK,sBAAsB,mBAAmB,aAAa,GAAG,KAAK,GAAG,EAAE;AACxE,SAAK,YAAY;AACjB,UAAM,IAAI,SAAS,WAAW,IAAI;AAClC,UAAM,WAAW,IAAI,eAAe,IAAI,eAAe,CAAC;AACxD,UAAM,mBAAmB,OAAO,SAAS,KAAK,SAAS,EAAE;AACzD,QAAI,MAAM;AACV,SAAK,cAAc,cAAc,KAAK,IAAI,eAAe,WAAW,eAAe,QAAQ;AAC3F,SAAK,cAAc,cAAc,aAAa,IAAI,eAAe,WAAW,eAAe,aAAa;AACxG,WAAO,mBAAmB;AAAA,EAC5B;AAAA,EACA,mBAAmB,QAAQ,gBAAgB,6BAA6B;AACtE,WAAO,IAAI,EAAE,QAAQ,oBAAoB,KAAK,OAAO,MAAM,CAAC,WAAW,KAAK,UAAU,IAAI,OAAO,MAAM,EAAE,gBAAgB,QAAQ,aAAa,cAAc,OAAO,KAAK,IAAI,aAAa;AAAA,EAC3L;AAAA,EACA,aAAa;AACX,WAAO,KAAK,UAAU,WAAW,IAAI,KAAK,0BAA0B;AAAA,EACtE;AAAA,EACA,UAAU;AACR,QAAI,KAAK,UAAU;AACjB;AAAA,IACF;AACA,SAAK,cAAc,QAAQ;AAC3B,SAAK,eAAe,QAAQ;AAC5B,SAAK,WAAW;AAAA,EAClB;AACF;AACA,cAAc,aAAa;AAG3B,IAAI,iBAAiB,CAAC;AACtBH,UAAS,gBAAgB;AAAA,EACvB,eAAe,MAAM;AAAA,EACrB,aAAa,MAAM;AACrB,CAAC;AAGD,IAAI,kBAAkB,GAAG;AACvB,kBAAgB,UAAU,YAAY;AACpC,QAAI,EAAE,IAAI,gCAAgC,KAAK;AAC/C,UAAM,gBAAgB;AAAA,MACpB,iBAAiB,IAAI,EAAE,IAAI,0BAA0B,IAAI,cAAc;AAAA,IACzE;AACA,UAAM,UAAU,MAAM,UAAU,IAAI,eAAe,aAAa;AAChE,UAAM,gBAAgB,QAAQ;AAC9B,UAAM,mBAAmB,CAAC;AAC1B,UAAM,mBAAmB,QAAQ,SAAS,IAAI,iBAAiB;AAC/D,qBAAiB,iBAAiB;AAAA,MAChC,kCAAkC,cAAc;AAAA,MAChD,oCAAoC,cAAc;AAAA,MAClD,+BAA+B,cAAc;AAAA,IAC/C;AACA,QAAI,kBAAkB;AACpB,uBAAiB,mBAAmB,CAAC,iBAAiB;AAAA,IACxD,OAAO;AACL,cAAQ,KAAK,wUAAwU;AAAA,IACvV;AACA,UAAM,SAAS,MAAM,QAAQ,cAAc,gBAAgB;AAC3D,WAAO,IAAI,cAAc,QAAQ,gBAAgB;AAAA,EACnD,GAAG,CAAC;AACN;AAGA,IAAI,IAAI;AACR,IAAI,IAAI;AACR,IAAI,IAAI;AACR,IAAI,IAAI;AACR,IAAI,IAAI;AACR,IAAI,IAAI;AACR,IAAI,IAAI;AACR,IAAI,IAAI,EAAE,MAAM,GAAG,aAAa,GAAG,aAAa,GAAG,eAAe,GAAG,kBAAkB,GAAG,sBAAsB,GAAG,qBAAqB,EAAE;;;AC79xEnI,IAAM,iBAAiB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAqBvB,IAAM,uBAAuB;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAc7B,IAAM,0BAA0B;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAchC,IAAM,WAAW;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAejB,IAAM,OAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAyBb,IAAM,cAAc;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;;;AChF3B,IAAM,UAAU,CAAC,QAAQ,QAAQ,eAAe;AAC9C,QAAMyC,KAAI,IAAI,OAAO,QAAQ,SAAS,gBAAgB,IAAI;AAC1D,SAAO,QAAQA,IAAG,CAACC,QAAO,SAAS;AACjC,eAAW,QAAQ;AACnB,WAAOA;AAAA,EACT,CAAC;AACH;AAEA,IAAM,YAAN,MAAgB;AAAA,EAMd,YAAY,IAAI,cAAc,gBAAgB;AAL9C,mCAAU,CAAC;AACX,qCAAY,CAAC;AACb;AACA;AA2BA,mCAAU,CAAC,QAAQ,SAA6B;AAC9C,YAAM,SAAS,KAAK,GAAG,aAAa,IAAI;AACxC,UAAI,CAAC,QAAQ;AACX,YAAI,iCAAiC;AACrC,eAAO;AAAA,MACT;AACA,WAAK,GAAG,aAAa,QAAQ,MAAM;AACnC,WAAK,GAAG,cAAc,MAAM;AAC5B,UAAI,CAAC,KAAK,GAAG,mBAAmB,QAAQ,KAAK,GAAG,cAAc,GAAG;AAC/D,YAAI,8BAA8B,KAAK,GAAG,iBAAiB,MAAM,GAAG;AACpE,eAAO;AAAA,MACT;AACA,aAAO;AAAA,IACT;AArCE,SAAK,KAAK;AACV,UAAM,eAAe,KAAK,QAAQ,cAAc,KAAK,GAAG,aAAa;AACrE,UAAM,iBAAiB,KAAK,QAAQ,gBAAgB,KAAK,GAAG,eAAe;AAC3E,SAAK,KAAK,KAAK,GAAG,cAAc;AAChC,QAAI,CAAC,gBAAgB,CAAC;AAAgB;AACtC,QAAI,CAAC,KAAK,IAAI;AACZ,UAAI,wCAAwC;AAC5C;AAAA,IACF;AACA,SAAK,GAAG,aAAa,KAAK,IAAI,YAAY;AAC1C,SAAK,GAAG,aAAa,KAAK,IAAI,cAAc;AAC5C,SAAK,GAAG,YAAY,KAAK,EAAE;AAC3B,QAAI,CAAC,KAAK,GAAG,oBAAoB,KAAK,IAAI,KAAK,GAAG,WAAW,GAAG;AAC9D,UAAI,2BAA2B,KAAK,GAAG,kBAAkB,KAAK,EAAE,GAAG;AACnE;AAAA,IACF;AACA,SAAK,GAAG,WAAW,KAAK,EAAE;AAC1B,YAAQ,cAAc,aAAa,KAAK,SAAS;AACjD,eAAW,KAAK,KAAK;AAAW,WAAK,UAAU,KAAK,KAAK,GAAG,kBAAkB,KAAK,IAAI,CAAC;AACxF,YAAQ,cAAc,WAAW,KAAK,OAAO;AAC7C,YAAQ,gBAAgB,WAAW,KAAK,OAAO;AAC/C,eAAW,KAAK,KAAK;AAAS,WAAK,QAAQ,KAAK,KAAK,GAAG,mBAAmB,KAAK,IAAI,CAAC;AAAA,EACvF;AAgBF;AAWO,SAAS,gBAAgB;AAC9B,MAAI,YAAY;AAChB,MAAI,gBAAqC;AACzC,MAAI,cAAc;AAClB,MAAI,0BAA0B;AAC9B,MAAI,mBAAoG,CAAC,MAAM,IAAI;AACnH,MAAI,cAAyC,CAAC;AAC9C,MAAI,eAAmC;AACvC,MAAI,iBAAmC;AACvC,QAAM,WAAW,OAAO,KAAK,GAAG;AAChC,QAAM,qBAAqB,CAAE;AAC7B,QAAM,OAAO,EAAE,cAAc,EAAE;AAC/B,QAAM,KAAK,SAAS,WAAW,OAAO;AACtC,MAAI,CAAC,IAAI;AACP,QAAI,kCAAkC;AACtC;AAAA,EACF;AAEA,OAAK,KAAK;AAEV,WAAS,OAAO,OAAO,QAAQ;AAC7B,QAAI,UAAU,SAAS,SAAS,WAAW,SAAS;AAAQ;AAC5D,aAAS,QAAQ;AACjB,aAAS,SAAS;AAClB,QAAI,CAAC,cAAc;AACjB,YAAM,WAAW,IAAI,aAAa,CAAC,IAAI,IAAI,GAAG,GAAG,GAAG,IAAI,GAAG,GAAG,IAAI,GAAG,GAAG,GAAG,IAAI,GAAG,GAAG,GAAG,GAAG,IAAI,GAAG,GAAG,GAAG,GAAG,GAAG,CAAC,CAAC;AAChH,qBAAe,GAAG,aAAa;AAC/B,SAAG,WAAW,GAAG,cAAc,YAAY;AAC3C,SAAG,WAAW,GAAG,cAAc,UAAU,GAAG,WAAW;AACvD,SAAG,YAAY,GAAG,gCAAgC,IAAI;AAAA,IACxD;AACA,OAAG,SAAS,GAAG,GAAG,SAAS,OAAO,SAAS,MAAM;AACjD,uBAAmB,CAAC,MAAM,IAAI;AAAA,EAChC;AAEA,WAAS,yBAAyB,OAAO,QAAQ;AAC/C,UAAM,MAAM,GAAG,kBAAkB;AACjC,OAAG,gBAAgB,GAAG,aAAa,GAAG;AACtC,UAAM,eAAe,GAAG,mBAAmB;AAC3C,OAAG,iBAAiB,GAAG,cAAc,YAAY;AACjD,UAAM,UAAU,GAAG,cAAc;AACjC,OAAG,YAAY,GAAG,YAAY,OAAO;AACrC,OAAG,WAAW,GAAG,YAAY,GAAG,GAAG,MAAM,OAAO,QAAQ,GAAG,GAAG,MAAM,GAAG,eAAe,IAAI;AAC1F,OAAG,cAAc,GAAG,YAAY,GAAG,oBAAoB,GAAG,MAAM;AAChE,OAAG,cAAc,GAAG,YAAY,GAAG,oBAAoB,GAAG,MAAM;AAChE,OAAG,cAAc,GAAG,YAAY,GAAG,gBAAgB,GAAG,aAAa;AACnE,OAAG,cAAc,GAAG,YAAY,GAAG,gBAAgB,GAAG,aAAa;AACnE,OAAG,qBAAqB,GAAG,aAAa,GAAG,mBAAmB,GAAG,YAAY,SAAS,CAAC;AACvF,OAAG,YAAY,GAAG,YAAY,IAAI;AAClC,OAAG,gBAAgB,GAAG,aAAa,IAAI;AACvC,WAAO,EAAE,KAAK,QAAQ;AAAA,EACxB;AAEA,WAAS,mBAAmBC,QAAuE;AACjG,qBAAiBA,UAAS,iBAAiBA,WAAU,yBAAyB,SAAS,OAAO,SAAS,MAAM;AAC7G,WAAO,iBAAiBA;AAAA,EAC1B;AAEA,WAAS,KAAK,QAAQ,GAAG;AACvB,QAAI,CAAC;AAAgB;AACrB,QAAI,SAA8B;AAClC,QAAI,SAAkC;AACtC,QAAI,QAAQ;AACZ,QAAI,cAAc;AAAG,eAAS;AAAA;AACzB,eAAS,mBAAmB,uBAAuB,EAAE,WAAW;AACrE;AACA,QAAI,eAAe,EAAE,QAAQ,KAAK,eAAe;AAC/C,eAAS;AACT,cAAQ,YAAY,MAAM;AAAA,IAC5B,OAAO;AACL,iCAA2B,0BAA0B,KAAK;AAC1D,eAAS,mBAAmB,uBAAuB,EAAE,OAAO;AAAA,IAC9D;AACA,OAAG,YAAY,GAAG,YAAY,MAAM;AACpC,OAAG,gBAAgB,GAAG,aAAa,MAAM;AACzC,OAAG,UAAU,eAAe,QAAQ,UAAW,QAAQ,KAAK,CAAE;AAC9D,OAAG,WAAW,GAAG,WAAW,GAAG,CAAC;AAAA,EAClC;AAEA,WAAS,cAAc,gBAAkC;AACvD,QAAI,mBAAmB,iBAAiB;AACtC,uBAAiB,mBAAmB;AACpC,SAAG,YAAY,iBAAiB,eAAe,KAAK,SAAS,IAAI;AACjE,aAAO;AAAA,IACT;AACA,qBAAiB,IAAI,UAAU,IAAY,gBAAgB,cAAc;AACzE,QAAI,CAAC,gBAAgB;AACnB,UAAI,qCAAqC;AACzC,aAAO;AAAA,IACT;AACA,UAAM,YAAY,aAAa;AAC/B,UAAM,WAAW,IAAI;AACrB,OAAG,wBAAwB,eAAe,UAAU,MAAM;AAC1D,OAAG,oBAAoB,eAAe,UAAU,QAAQ,GAAG,GAAG,OAAO,OAAO,UAAU,IAAI,SAAS;AACnG,OAAG,wBAAwB,eAAe,UAAU,KAAK;AACzD,OAAG,oBAAoB,eAAe,UAAU,OAAO,GAAG,GAAG,OAAO,OAAO,UAAU,IAAI,SAAS;AAClG,uBAAmB,kBAAkB;AACrC,WAAO;AAAA,EACT;AAEA,QAAM,SAAS;AAAA,IACb,aAAa,CAAC,WAAW;AACvB,YAAM,IAAI,IAAI,aAAa,MAAM;AACjC,QAAE,MAAM;AACR,QAAE,MAAM;AACR,QAAE,OAAO;AACT,QAAE,OAAO;AACT,YAAM,SAAU,EAAE,QAAQ,KAAK,EAAE,OAAO,KAAK,EAAE,OAAO,KAAK,EAAE,QAAQ,KAAK,EAAE,QAAQ,KAAK,EAAE,QAAQ,KAAK,EAAE,QAAQ,KAAK,EAAE,QAAQ,IACrH,0BACA;AACZ,YAAM,UAAU,cAAc,MAAM;AACpC,UAAI,CAAC;AAAS;AACd,SAAG,WAAW,QAAQ,QAAQ,MAAM,CAAC;AACrC,WAAK;AAAA,IACP;AAAA,IAEA,YAAY,CAAC,eAAe;AAC1B,YAAM,KAAK,cAAc,KAAK;AAC9B,aAAO,YAAY;AAAA,QACjB;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,YAAY,CAAC,WAAW;AACtB,YAAM,KAAK,UAAU,KAAK,IAAI,IAAI;AAClC,YAAM,KAAM,IAAI,KAAK;AACrB,aAAO,YAAY;AAAA,QACjB;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,YAAY,MAAM;AAChB,aAAO,WAAW,EAAE;AAAA,IACtB;AAAA,IAEA,UAAU,CAAC,WAAW;AACpB,YAAM,KAAK,UAAU,KAAK;AAC1B,YAAM,IAAI,QAAQ,IAAI;AACtB,aAAO,YAAY;AAAA,QACjB;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,UAAU,MAAM;AACd,aAAO,SAAS,EAAE;AAAA,IACpB;AAAA,IAEA,KAAK,CAAC,aAAa;AACjB,kBAAY,YAAY,KAAK,MAAM,KAAK;AACxC,YAAMC,OAAM,KAAK,IAAI,QAAQ;AAC7B,YAAMC,OAAM,KAAK,IAAI,QAAQ;AAC7B,YAAM,OAAO;AACb,YAAM,OAAO;AACb,YAAM,OAAO;AACb,aAAO,YAAY;AAAA,QACjB,OAAOD,QAAO,IAAI,QAAQC,OAAO,CAAC;AAAA,QAAO,OAAOD,OAAO,CAAC,OAAQC,OAAO,CAAC;AAAA,QAAO,OAAOD,OAAO,CAAC,OAAQC,QAAO,IAAI;AAAA,QAAO;AAAA,QAAG;AAAA,QAC3H,OAAOD,OAAO,CAAC,OAAQC,OAAO;AAAA,QAAQ,OAAOD,QAAO,IAAI,QAAQC,OAAO;AAAA,QAAQ,OAAOD,OAAO,CAAC,OAAQC,OAAO;AAAA,QAAS;AAAA,QAAG;AAAA,QACzH,OAAOD,OAAO,CAAC,OAAQC,OAAO,EAAE,IAAI;AAAA,QAAQ,OAAOD,OAAO,CAAC,OAAQC,OAAO;AAAA,QAAO,OAAOD,QAAO,IAAI,QAAQC,OAAO;AAAA,QAAO;AAAA,QAAG;AAAA,QAC5H;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,qBAAqB,MAAM;AACzB,aAAO,YAAY;AAAA,QACjB;AAAA,QAAW;AAAA,QAAW;AAAA,QAAW;AAAA,QAAG;AAAA,QACpC;AAAA,QAAW;AAAA,QAAW;AAAA,QAAW;AAAA,QAAG;AAAA,QACpC;AAAA,QAAW;AAAA,QAAW;AAAA,QAAW;AAAA,QAAG;AAAA,QACpC;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,OAAO,MAAM;AACX,aAAO,YAAY;AAAA,QACjB;AAAA,QAAO;AAAA,QAAW;AAAA,QAAY;AAAA,QAAG;AAAA,QACjC;AAAA,QAAO;AAAA,QAAW;AAAA,QAAY;AAAA,QAAG;AAAA,QACjC;AAAA,QAAO;AAAA,QAAW;AAAA,QAAY;AAAA,QAAG;AAAA,QACjC;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,SAAS,MAAM;AACb,aAAO,YAAY;AAAA,QACjB;AAAA,QAAoB;AAAA,QAAqB;AAAA,QAAqB;AAAA,QAAG;AAAA,QACjE;AAAA,QAAuB;AAAA,QAAoB;AAAA,QAAqB;AAAA,QAAG;AAAA,QACnE;AAAA,QAAqB;AAAA,QAAsB;AAAA,QAAqB;AAAA,QAAG;AAAA,QACnE;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,gBAAgB,MAAM;AACpB,aAAO,YAAY;AAAA,QACjB;AAAA,QAAoB;AAAA,QAAoB;AAAA,QAAsB;AAAA,QAAG;AAAA,QACjE;AAAA,QAAqB;AAAA,QAAoB;AAAA,QAAqB;AAAA,QAAG;AAAA,QACjE;AAAA,QAAoB;AAAA,QAAqB;AAAA,QAAoB;AAAA,QAAG;AAAA,QAChE;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,YAAY,MAAM;AAChB,aAAO,YAAY;AAAA,QACjB;AAAA,QAAoB;AAAA,QAAqB;AAAA,QAAsB;AAAA,QAAG;AAAA,QAClE;AAAA,QAAsB;AAAA,QAAoB;AAAA,QAAsB;AAAA,QAAG;AAAA,QACnE;AAAA,QAAsB;AAAA,QAAqB;AAAA,QAAoB;AAAA,QAAG;AAAA,QAClE;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,aAAa,MAAM;AACjB,aAAO,YAAY;AAAA,QACjB;AAAA,QAAoB;AAAA,QAAqB;AAAA,QAAsB;AAAA,QAAG;AAAA,QAClE;AAAA,QAAqB;AAAA,QAAoB;AAAA,QAAsB;AAAA,QAAG;AAAA,QAClE;AAAA,QAAoB;AAAA,QAAqB;AAAA,QAAmB;AAAA,QAAG;AAAA,QAC/D;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,UAAU,MAAM;AACd,aAAO,YAAY;AAAA,QACjB;AAAA,QAAO;AAAA,QAAQ;AAAA,QAAQ;AAAA,QAAG;AAAA,QAC1B;AAAA,QAAQ;AAAA,QAAO;AAAA,QAAQ;AAAA,QAAG;AAAA,QAC1B;AAAA,QAAQ;AAAA,QAAQ;AAAA,QAAO;AAAA,QAAG;AAAA,QAC1B;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,YAAY,MAAM;AAChB,aAAO,YAAY;AAAA,QACjB;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QACZ;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,QAAG;AAAA,MACd,CAAC;AAAA,IACH;AAAA,IAEA,aAAa,CAAC,WAAW;AACvB,YAAM,IAAI,IAAI,aAAa,MAAM;AACjC,YAAM,aAAa,IAAI,SAAS;AAChC,YAAM,aAAa,IAAI,SAAS;AAChC,YAAM,UAAU,cAAsB,WAAW;AACjD,UAAI,CAAC;AAAS;AACd,SAAG,WAAW,QAAQ,QAAQ,MAAM,CAAC;AACrC,SAAG,UAAU,QAAQ,QAAQ,OAAO,YAAY,UAAU;AAC1D,WAAK;AAAA,IACP;AAAA,IAEA,aAAa,MAAM;AAEjB,aAAO,YAAY,KAAK,MAAM;AAAA,QAC5B;AAAA,QAAG;AAAA,QAAG;AAAA,QACN;AAAA,QAAG;AAAA,QAAI;AAAA,QACP;AAAA,QAAG;AAAA,QAAG;AAAA,MACR,CAAC;AAAA,IACH;AAAA,IAEA,QAAQ,MAAM;AAEZ,aAAO,YAAY,KAAK,MAAM;AAAA,QAC5B;AAAA,QAAI;AAAA,QAAG;AAAA,QACP;AAAA,QAAI;AAAA,QAAG;AAAA,QACP;AAAA,QAAI;AAAA,QAAG;AAAA,MACT,CAAC;AAAA,IACH;AAAA,IAEA,QAAQ,MAAM;AAEZ,aAAO,YAAY,KAAK,MAAM;AAAA,QAC5B;AAAA,QAAI;AAAA,QAAI;AAAA,QACR;AAAA,QAAG;AAAA,QAAG;AAAA,QACN;AAAA,QAAG;AAAA,QAAG;AAAA,MACR,CAAC;AAAA,IACH;AAAA,IAEA,SAAS,CAAC,WAAW;AACnB,YAAM,IAAI,UAAU;AAEpB,aAAO,YAAY,KAAK,MAAM;AAAA,QAC5B;AAAA,QAAG,KAAK;AAAA,QAAG;AAAA,QACX,KAAK;AAAA,QAAG,IAAI,IAAI;AAAA,QAAG,KAAK;AAAA,QACxB;AAAA,QAAG,KAAK;AAAA,QAAG;AAAA,MACb,CAAC;AAAA,IACH;AAAA,IAEA,QAAQ,CAACC,UAAS;AAChB,YAAMC,KAAID,SAAQ;AAElB,aAAO,YAAY,KAAK,MAAM;AAAA,QAC5B,KAAKC;AAAA,QAAG,KAAKA;AAAA,QAAG;AAAA,QAChB,KAAKA;AAAA,QAAG;AAAA,QAAG,IAAIA;AAAA,QACf;AAAA,QAAG,IAAIA;AAAA,QAAG,IAAIA;AAAA,MAChB,CAAC;AAAA,IACH;AAAA,IAEA,MAAM,CAACD,UAAS;AACd,YAAM,YAAaA,QAAO,IAAK,SAAS;AACxC,YAAM,YAAaA,QAAO,IAAK,SAAS;AACxC,YAAM,UAAU,cAAsB,IAAI;AAC1C,UAAI,CAAC;AAAS;AAEd,SAAG,UAAU,QAAQ,QAAQ,OAAO,GAAG,SAAS;AAChD,WAAK,KAAK,YAAY;AAEtB,SAAG,UAAU,QAAQ,QAAQ,OAAO,WAAW,CAAC;AAChD,WAAK;AAAA,IACP;AAAA,IAEA,UAAU,CAACA,UAAS;AAClB,YAAM,YAAaA,QAAQ,SAAS;AACpC,YAAM,YAAaA,QAAQ,SAAS;AACpC,YAAM,UAAU,cAAsB,QAAQ;AAC9C,UAAI,CAAC;AAAS;AACd,SAAG,UAAU,QAAQ,QAAQ,SAAS,WAAW,SAAS;AAC1D,WAAK;AAAA,IACP;AAAA,EACF;AAGA,OAAK,MAAM,SAAU,MAAM;AAEzB,UAAM,OAAO,MAAM,UAAU,MAAM,KAAK,WAAW,CAAC;AACpD,UAAME,QAAO,OAAO;AACpB,gBAAY,KAAK,EAAE,MAAAA,OAAM,KAAK,CAAC;AAAA,EACjC;AAGA,OAAK,QAAQ,WAAY;AACvB,kBAAc,CAAC;AAAA,EACjB;AAGA,OAAK,MAAM,WAAY;AACrB,WAAO;AAAA,EACT;AAGA,OAAK,QAAQ,SAAUC,QAAO;AAC5B,WAAOA,OAAM,OAAOA,OAAM,MAAM;AAChC,gBAAY;AACZ,QAAI,CAAC;AAAe,sBAAgB,GAAG,cAAc;AACrD,OAAG,YAAY,GAAG,YAAY,aAAa;AAC3C,OAAG,cAAc,GAAG,YAAY,GAAG,gBAAgB,GAAG,aAAa;AACnE,OAAG,cAAc,GAAG,YAAY,GAAG,gBAAgB,GAAG,aAAa;AACnE,OAAG,cAAc,GAAG,YAAY,GAAG,oBAAoB,GAAG,OAAO;AACjE,OAAG,cAAc,GAAG,YAAY,GAAG,oBAAoB,GAAG,OAAO;AACjE,OAAG,WAAW,GAAG,YAAY,GAAG,GAAG,MAAM,GAAG,MAAM,GAAG,eAAeA,MAAK;AACzE,aAASC,KAAI,GAAGA,KAAI,YAAY,QAAQA,MAAK;AAC3C,oBAAeA,OAAM,YAAY,SAAS;AAC1C,YAAM,IAAI,YAAYA;AAEtB,QAAE,KAAK,MAAM,MAAM,EAAE,QAAQ,CAAC,CAAC;AAAA,IACjC;AACA,WAAO;AAAA,EACT;AAGA,OAAK,OAAO,SAAUD,QAAO;AAC3B,SAAK,IAAI,cAAc,CAAC;AACxB,WAAO,KAAK,MAAMA,MAAK;AAAA,EACzB;AACF;;;ACjbA,eAAsB,sBAAsB,YAAqC;AAE/E,QAAME,WAAU,WAAW,MAAM,WAAW,IAAO,QAAQ,UAAU,IAAI;AACzE,QAAM,WAAc,MAAMA,UAAS,GAAG,CAAC;AACvC,QAAMC,OAAgB,CAAI,IAAI,SAAS,EAAE,GAAM,IAAI,SAAS,EAAE,GAAM,IAAI,SAAS,EAAE,CAAC;AACpF,QAAMC,OAAgB,CAAI,IAAI,SAAS,EAAE,GAAM,IAAI,SAAS,EAAE,GAAM,IAAI,SAAS,EAAE,CAAC;AACpF,QAAM,SAAS,MAAM,QAAQ,IAAIA,KAAI,IAAI,CAAC,YAAY,QAAQ,KAAK,CAAC,CAAC;AACrE,QAAM,WAAW,OAAO,KAAK,IAAI,OAAO,GAAG,IAAI,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE;AACzE,QAAMC,OAAM,CAAI,IAAI,SAAS,IAAIF,KAAI,EAAE,GAAM,IAAI,SAAS,IAAIA,KAAI,EAAE,GAAM,IAAI,SAAS,IAAIA,KAAI,EAAE,CAAC;AAClG,QAAMG,SAAQ,CAAI,IAAIF,KAAI,IAAID,KAAI,EAAE,GAAM,IAAIC,KAAI,IAAID,KAAI,EAAE,GAAM,IAAIC,KAAI,IAAID,KAAI,EAAE,CAAC;AACrF,QAAM,OAAO,CAAI,IAAI,UAAUG,OAAM,EAAE,GAAM,IAAI,UAAUA,OAAM,EAAE,GAAM,IAAI,UAAUA,OAAM,EAAE,CAAC;AAChG,QAAM,MAAM,CAAI,IAAID,KAAI,IAAI,KAAK,EAAE,GAAM,IAAIA,KAAI,IAAI,KAAK,EAAE,GAAM,IAAIA,KAAI,IAAI,KAAK,EAAE,CAAC;AACtF,QAAME,OAAS,MAAM,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,GAAG,CAAC;AAChD,QAAMC,WAAa,QAAQD,MAAK,CAAC,GAAGL,SAAQ,MAAM,IAAIA,SAAQ,MAAM,IAAI,CAAC,CAAC;AAC1E,EAAG,QAAQ,CAAC,GAAG,UAAU,GAAGC,MAAK,GAAGC,MAAK,GAAGC,MAAK,GAAGC,QAAO,GAAG,MAAM,GAAG,KAAKC,MAAKL,QAAO,CAAC;AACzF,SAAOM;AACT;;;ACZA,IAAM,UAAU;AAEhB,IAAI,WAA6B;AACjC,IAAI,YAA8B;AAClC,IAAI,YAA8B;AAElC,IAAI;AAEJ,IAAM,OAAoG;AAAA,EACxG,UAAU;AAAA,EACV,WAAW;AAAA,EACX,WAAW;AAAA,EACX,aAAa;AACf;AAEO,SAAS,OAAO,OAAe,QAA2B;AAC/D,MAAI;AACJ,MAAIC,KAAI,SAAS;AACf,QAAIA,KAAI,QAAQ;AACd,UAAI,OAAO,oBAAoB;AAAa,cAAM,IAAI,MAAM,mFAAmF;AAC/I,UAAI,IAAI,gBAAgB,OAAO,MAAM;AAAA,IACvC,OAAO;AACL,UAAI,OAAO,aAAa;AAAa,cAAM,IAAI,MAAM,kEAAkE;AACvH,UAAI,SAAS,cAAc,QAAQ;AACnC,QAAE,QAAQ;AACV,QAAE,SAAS;AAAA,IACb;AAAA,EACF,OAAO;AAEL,QAAI,OAAOA,KAAI,WAAW;AAAa,UAAI,IAAIA,KAAI,OAAO,OAAO,MAAM;AAAA,aAC9D,OAAO,WAAW,WAAW;AAAa,UAAI,IAAI,WAAW,OAAO,OAAO,MAAM;AAAA,EAE5F;AACA,SAAO;AACT;AAGO,SAAS,KAAKC,QAAkB,QAAoB;AACzD,QAAM,eAAe,UAAU,OAAOA,OAAM,OAAOA,OAAM,MAAM;AAC/D,QAAM,MAAM,aAAa,WAAW,IAAI;AACxC,MAAI,UAAUA,QAAO,GAAG,CAAC;AACzB,SAAO;AACT;AAKA,eAAsBC,SAAQD,QAAcE,SAAgBC,aAAqB,MAAoE;AACnJ,MAAI,CAACH,QAAO;AAEV,QAAIE,QAAO;AAAO,UAAI,+BAA+B;AACrD,WAAO,EAAE,QAAQ,MAAM,QAAQ,KAAK;AAAA,EACtC;AAEA,MACE,EAAEF,kBAAoB,WACnB,EAAE,OAAO,UAAU,eAAeA,kBAAiB,UACnD,EAAE,OAAOD,KAAI,WAAW,eAAeC,kBAAiBD,KAAI,WAC5D,EAAE,OAAO,WAAW,WAAW,eAAeC,kBAAiB,WAAW,WAC1E,EAAE,OAAO,cAAc,eAAeA,kBAAiB,cACvD,EAAE,OAAO,gBAAgB,eAAeA,kBAAiB,gBACzD,EAAE,OAAO,qBAAqB,eAAeA,kBAAiB,qBAC9D,EAAE,OAAO,qBAAqB,eAAeA,kBAAiB,qBAC9D,EAAE,OAAO,qBAAqB,eAAeA,kBAAiB,qBAC9D,EAAE,OAAO,sBAAsB,eAAeA,kBAAiB,sBAC/D,EAAE,OAAO,oBAAoB,eAAeA,kBAAiB,kBAChE;AACA,UAAM,IAAI,MAAM,qCAAqC;AAAA,EACvD;AACA,MAAIA,kBAAoB,QAAQ;AAC9B,QAAII,UAAwB;AAC5B,QAAKJ,OAAiB;AAAuB,YAAM,IAAI,MAAM,yDAAyD;AACtH,QAAI,CAAEA,OAAiB;AAAU,YAAM,IAAI,MAAM,sDAAsD;AACvG,QAAKA,OAAiB,MAAM,WAAW,GAAG;AACxC,UAAKA,OAAiB,MAAM,OAAO,GAAG;AACpC,QAAAI,UAAY,WAAWJ,QAAO,CAAC;AAAA,MACjC,WAAYA,OAAiB,MAAM,OAAO,GAAG;AAC3C,cAAMK,OAAS,QAAQL,QAAO,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,IAAI,IAAI,CAAC,CAAC;AACpD,QAAAI,UAAY,WAAWC,MAAK,CAAC;AAC7B,QAAG,QAAQA,IAAG;AAAA,MAChB;AAAA,IACF,WAAYL,OAAiB,MAAM,WAAW,GAAG;AAC/C,UAAKA,OAAiB,MAAM,OAAO,GAAG;AACpC,QAAAI,UAAY,MAAMJ,MAAK;AAAA,MACzB,WAAYA,OAAiB,MAAM,OAAO,GAAG;AAC3C,QAAAI,UAAY,QAAQJ,QAAO,CAAC,GAAG,GAAG,GAAG,CAAC,GAAG,CAAC,IAAI,IAAI,IAAI,CAAC,CAAC;AAAA,MAC1D;AAAA,IACF;AAEA,QAAII,WAAU,QAAQA,QAAO,MAAM,WAAW,KAAKA,QAAO,MAAM,OAAO,KAAKA,QAAO,MAAM,OAAO;AAAG,YAAM,IAAI,MAAM,iEAAiEJ,OAAM,UAAU;AACpM,QAAKI,QAAkB,UAAU,SAAS;AACxC,YAAME,QAAU,KAAKF,SAAQ,SAAS;AACtC,MAAG,QAAQA,OAAM;AACjB,MAAAA,UAASE;AAAA,IACX;AACA,WAAO,EAAE,QAAAF,SAAQ,QAASF,QAAO,OAAO,SAAS,YAAY,KAAM;AAAA,EACrE,OAAO;AAEL,QAAI,OAAOF,OAAM,kBAAkB,eAAeA,OAAM,iBAAiB,GAAG;AAC1E,UAAIE,QAAO;AAAO,YAAI,2BAA2B;AACjD,aAAO,EAAE,QAAQ,MAAM,QAAQ,SAAS;AAAA,IAC1C;AACA,UAAM,gBAAgBF,OAAM,mBAAmBA,OAAM,iBAAiBA,OAAM,YAAaA,OAAM,YAAaA,OAAM,SAAS,KAAK;AAChI,UAAM,iBAAiBA,OAAM,oBAAoBA,OAAM,kBAAkBA,OAAM,aAAcA,OAAM,YAAaA,OAAM,SAAS,KAAK;AACpI,QAAI,CAAC,iBAAiB,CAAC,gBAAgB;AACrC,UAAIE,QAAO;AAAO,YAAI,mCAAmC;AACzD,aAAO,EAAE,QAAQ,MAAM,QAAQ,SAAS;AAAA,IAC1C;AACA,QAAI,cAAc;AAClB,QAAI,eAAe;AACnB,QAAI,cAAc,SAAS;AACzB,oBAAc;AACd,qBAAe,KAAK,MAAM,cAAc,iBAAiB,aAAa;AAAA,IACxE;AACA,QAAI,eAAe,SAAS;AAC1B,qBAAe;AACf,oBAAc,KAAK,MAAM,eAAe,gBAAgB,cAAc;AAAA,IACxE;AAGA,SAAKA,QAAO,OAAO,SAAS,KAAK;AAAG,oBAAcA,QAAO,OAAO;AAAA,cACtDA,QAAO,OAAO,UAAU,KAAK;AAAG,oBAAc,kBAAkBA,QAAO,OAAO,UAAU,KAAK;AACvG,SAAKA,QAAO,OAAO,UAAU,KAAK;AAAG,qBAAeA,QAAO,OAAO;AAAA,cACxDA,QAAO,OAAO,SAAS,KAAK;AAAG,qBAAe,mBAAmBA,QAAO,OAAO,SAAS,KAAK;AACvG,QAAI,CAAC,eAAe,CAAC;AAAc,YAAM,IAAI,MAAM,yCAAyC;AAC5F,QAAI,CAAC,aAAa,qCAAU,WAAU,gBAAiB,qCAAU,YAAW;AAAe,iBAAW,OAAO,aAAa,YAAY;AAGtI,UAAM,QAAQ,SAAS,WAAW,IAAI;AACtC,QAAK,OAAO,cAAc,eAAiBF,kBAAiB,WAAY;AACtE,YAAM,aAAaA,QAAO,GAAG,CAAC;AAAA,IAChC,OAAO;AACL,UAAIE,QAAO,OAAO,QAAQ,OAAO,MAAM,cAAc,aAAa;AAChE,cAAM,UAAU,eAAe,CAAC;AAChC,cAAM,MAAM,IAAI,CAAC;AACjB,cAAM,UAAUF,QAAoB,GAAG,GAAG,eAAe,gBAAgB,GAAG,GAAG,qCAAU,OAAO,qCAAU,MAAM;AAChH,cAAM,aAAa,GAAG,GAAG,GAAG,GAAG,GAAG,CAAC;AAAA,MACrC,OAAO;AACL,cAAM,UAAUA,QAAoB,GAAG,GAAG,eAAe,gBAAgB,GAAG,GAAG,qCAAU,OAAO,qCAAU,MAAM;AAAA,MAClH;AAAA,IACF;AAEA,QAAI,CAAC,aAAc,SAAS,UAAU,UAAU,UAAW,qCAAU,aAAW,uCAAW;AAAS,kBAAY,OAAO,SAAS,OAAO,SAAS,MAAM;AAGtJ,QAAIE,QAAO,OAAO,WAAWH,KAAI,MAAM,WAAW;AAChD,UAAI,CAAC;AAAI,aAAKA,KAAI,UAAU,IAAY,cAAc,IAAI;AAC1D,MAAAA,KAAI,SAAS,CAAC,CAAC;AACf,UAAI,CAAC,MAAM,CAAC,GAAG,KAAK;AAClB,YAAIG,QAAO;AAAO,cAAI,gDAAgD;AACtE,QAAAH,KAAI,MAAM,YAAY;AACtB,QAAAG,QAAO,OAAO,UAAU;AACxB,aAAK,UAAU,SAAS;AAAA,MAE1B,OAAO;AACL,WAAG,MAAM;AACT,YAAIA,QAAO,OAAO,eAAe;AAAG,aAAG,IAAI,cAAcA,QAAO,OAAO,UAAU;AACjF,YAAIA,QAAO,OAAO,aAAa;AAAG,aAAG,IAAI,YAAYA,QAAO,OAAO,QAAQ;AAC3E,YAAIA,QAAO,OAAO,cAAc;AAAG,aAAG,IAAI,WAAWA,QAAO,OAAO,SAAS;AAC5E,YAAIA,QAAO,OAAO,SAAS;AAAG,aAAG,IAAI,QAAQA,QAAO,OAAO,IAAI;AAC/D,YAAIA,QAAO,OAAO,eAAe;AAAG,aAAG,IAAI,cAAcA,QAAO,OAAO,UAAU;AACjF,YAAIA,QAAO,OAAO,QAAQ;AAAG,aAAG,IAAI,OAAOA,QAAO,OAAO,GAAG;AAC5D,YAAIA,QAAO,OAAO;AAAU,aAAG,IAAI,UAAU;AAC7C,YAAIA,QAAO,OAAO;AAAO,aAAG,IAAI,OAAO;AACvC,YAAIA,QAAO,OAAO;AAAS,aAAG,IAAI,SAAS;AAC3C,YAAIA,QAAO,OAAO;AAAO,aAAG,IAAI,OAAO;AACvC,YAAIA,QAAO,OAAO;AAAY,aAAG,IAAI,YAAY;AACjD,YAAIA,QAAO,OAAO;AAAa,aAAG,IAAI,aAAa;AACnD,YAAIA,QAAO,OAAO;AAAU,aAAG,IAAI,UAAU;AAC7C,YAAIA,QAAO,OAAO,aAAa;AAAG,aAAG,IAAI,YAAYA,QAAO,OAAO,QAAQ;AAC3E,YAAI,GAAG,IAAI,IAAI;AAAG,sBAAY,GAAG,MAAM,QAAQ;AAAA;AAC1C,sBAAY,GAAG,KAAK,QAAQ;AAAA,MACnC;AAAA,IACF,OAAO;AACL,WAAK,UAAU,SAAS;AACxB,UAAI;AAAI,aAAK;AACb,MAAAH,KAAI,SAAS,CAAC,CAAC;AAAA,IACjB;AAEA,QAAI,CAACI;AAAW,aAAO,EAAE,QAAQ,MAAM,QAAQ,UAAU;AACzD,QAAI,CAAC;AAAW,YAAM,IAAI,MAAM,oCAAoC;AAGpE,QAAI;AACJ,QAAI,QAAQ;AACZ,QAAK,OAAO,cAAc,eAAeH,kBAAiB,aAAeA,OAAM,WAAWA,OAAM,YAAYA,OAAM,WAAY;AAC5H,UAAID,KAAI,WAAc,iBAAS;AAC7B,iBAAY,kBAAa,gBAAQ,WAAWC,MAAK,IAAI;AAAA,MACvD,OAAO;AACL,gBAAQA,OAAM,QAAQ,SAASA,OAAM,YAAYA,OAAM;AAEvD,cAAM,MAAM,IAAI,WAAWA,OAAM,QAAQ,SAAS;AAClD,iBAAY,OAAO,KAAK,CAACA,OAAM,WAAWA,OAAM,UAAU,KAAK,GAAG,OAAO;AAAA,MAC3E;AAAA,IACF,OAAO;AACL,UAAI,CAAC,aAAc,UAAU,UAAU,UAAU,SAAW,UAAU,WAAW,UAAU;AAAS,oBAAY,OAAO,UAAU,OAAO,UAAU,MAAM;AACxJ,UAAO,mBAAWD,KAAI,SAAS;AAC7B,YAAIG,QAAO,YAAY,WAAWA,QAAO,YAAY,aAAaA,QAAO,YAAY,UAAU;AAC7F,mBAAY,gBAAQ,WAAW,SAAS;AAAA,QAC1C,OAAO;AACL,sBAAY,KAAK,SAAS;AAC1B,mBAAY,gBAAQ,WAAW,SAAS;AAAA,QAC1C;AAAA,MACF,OAAO;AACL,cAAM,aAAa,KAAK,SAAS;AACjC,cAAM,UAAU,WAAW,WAAW,IAAI;AAC1C,cAAM,WAAW,QAAQ,aAAa,GAAG,GAAG,aAAa,YAAY;AACrE,gBAAQ,SAAS,KAAK,SAAS,cAAc;AAC7C,cAAM,MAAM,IAAI,WAAW,SAAS,KAAK,MAAM;AAC/C,iBAAY,OAAO,KAAK,CAAC,aAAa,cAAc,KAAK,CAAC;AAAA,MAC5D;AAAA,IACF;AACA,QAAI,UAAU,GAAG;AACf,YAAMG,OAAS,QAAQ,QAAQ,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,IAAI,IAAI,CAAC,CAAC;AACrD,MAAG,QAAQ,MAAM;AACjB,eAASA;AAAA,IACX;AACA,QAAI,CAAC;AAAQ,YAAM,IAAI,MAAM,mCAAmC;AAChE,UAAM,SAAY,KAAK,QAAQ,SAAS;AACxC,UAAMD,UAASF,QAAO,OAAO,eAAe,MAAc,sBAAsB,MAAM,IAAO,WAAW,QAAQ,CAAC;AACjH,IAAG,QAAQ,CAAC,QAAQ,MAAM,CAAC;AAC3B,WAAO,EAAE,QAAAE,SAAQ,QAASF,QAAO,OAAO,SAAS,YAAY,KAAM;AAAA,EACrE;AACF;AAgCA,eAAsB,KAAKA,SAAyBF,QAAe;AACjE,MAAI,YAAY;AAChB,MAAIE,QAAO,qBAAqB,KAAK,CAACF,OAAM,SAASA,OAAM,MAAM,WAAW,KAAKA,OAAM,MAAM,KAAK,QAAQA,OAAM,MAAM,KAAK;AAAM,WAAO;AAcxI,MAAI,CAAC,KAAK,aAAa;AACrB,SAAK,cAAiB,MAAMA,MAAK;AAAA,EACnC,WAAW,KAAK,YAAY,MAAM,OAAOA,OAAM,MAAM,MAAM,KAAK,YAAY,MAAM,OAAOA,OAAM,MAAM,IAAI;AACvG,IAAG,QAAQ,KAAK,WAAW;AAC3B,SAAK,cAAiB,MAAMA,MAAK;AAAA,EACnC,OAAO;AACL,UAAMO,KAA4B,CAAC;AACnC,IAAAA,GAAE,OAAU,IAAIP,QAAO,KAAK,WAAW;AACvC,IAAAO,GAAE,UAAa,IAAIA,GAAE,MAAMA,GAAE,IAAI;AACjC,IAAAA,GAAE,MAAS,KAAIA,GAAE,OAAO;AACxB,UAAM,UAAU,MAAMA,GAAE,IAAI,KAAK;AACjC,UAAM,eAAe,QAAQ,MAAMP,OAAM,MAAM,MAAM,MAAMA,OAAM,MAAM,MAAM,KAAK,MAAM;AACxF,IAAG,QAAQ,CAAC,KAAK,aAAaO,GAAE,MAAMA,GAAE,SAASA,GAAE,GAAG,CAAC;AACvD,SAAK,cAAiB,MAAMP,MAAK;AACjC,gBAAY,iBAAiBE,QAAO,oBAAoB;AAAA,EAC1D;AACA,SAAO;AACT;AAEA,eAAsB,QAAQA,SAAyB,QAAgB,QAAiC;AACtG,QAAMK,KAA4B,CAAC;AACnC,MAAI,CAAC,UAAU,CAAC,UAAU,OAAO,MAAM,WAAW,KAAK,OAAO,MAAM,WAAW,OAAO,MAAM,QAAQ;AAClG,QAAI,CAACL,QAAO;AAAO,UAAI,uDAAuD,OAAO,OAAO,OAAO,KAAK;AACxG,WAAO;AAAA,EACT;AACA,MAAI,OAAO,MAAM,OAAO,KAAK,OAAO,MAAM,OAAO,KAAK,OAAO,MAAM,OAAO,KAAK,OAAO,MAAM,OAAO,GAAG;AACpG,QAAI,CAACA,QAAO;AAAO,UAAI,yDAAyD,OAAO,OAAO,OAAO,KAAK;AAC1G,WAAO;AAAA,EACT;AACA,EAAAK,GAAE,SAAY,MAAM,MAAM;AAC1B,EAAAA,GAAE,SAAU,OAAO,MAAM,OAAO,OAAO,MAAM,MAAM,OAAO,MAAM,OAAO,OAAO,MAAM,KAAS,MAAM,eAAe,QAAQ,CAAC,OAAO,MAAM,IAAI,OAAO,MAAM,EAAE,CAAC,IAAO,MAAM,MAAM;AAC/K,EAAAA,GAAE,OAAU,IAAIA,GAAE,QAAQA,GAAE,MAAM;AAClC,EAAAA,GAAE,UAAa,IAAIA,GAAE,MAAMA,GAAE,IAAI;AACjC,EAAAA,GAAE,MAAS,KAAIA,GAAE,OAAO;AACxB,QAAM,UAAU,MAAMA,GAAE,IAAI,KAAK;AACjC,QAAM,eAAe,QAAQ,MAAM,OAAO,MAAM,MAAM,MAAM,OAAO,MAAM,MAAM,KAAK,MAAM;AAC1F,EAAG,QAAQ,CAACA,GAAE,QAAQA,GAAE,QAAQA,GAAE,MAAMA,GAAE,SAASA,GAAE,GAAG,CAAC;AACzD,SAAO;AACT;;;AC5TO,IAAM,MAAN,MAAU;AAAA,EA4Ef,cAAc;AA1Ed;AAEA;AAEA;AAEA,oCAAmB;AAEnB,iCAAgB;AAEhB,oCAAqB,CAAC;AAEtB;AAEA;AAEA;AAIA;AAEA,mCAAmB;AAEnB,gCAKI;AAAA,MACA,WAAW;AAAA,MACX,SAAS;AAAA,MACT,MAAM;AAAA,MACN,aAAa;AAAA,IACf;AAEF,iCAKI;AAAA,MACA,WAAW;AAAA,MACX,SAAS;AAAA,MACT,SAAS;AAAA,MACT,UAAU;AAAA,IACZ;AAEF,kCAII;AAAA,MACA,WAAW;AAAA,MACX,SAAS;AAAA,MACT,SAAS;AAAA,IACX;AAEF,+BAGI;AAAA,MACA,OAAO;AAAA,MACP,OAAO,CAAC;AAAA,IACV;AAEF,mCAAoB,CAAC;AAErB;AAEA;AAEA;AAGE,SAAK,UAAU,OAAO,cAAc;AACpC,SAAK,OAAQ,OAAO,YAAY,eAAiB,OAAO,QAAQ,aAAa,eAAiB,OAAO,QAAQ,SAAS,SAAS;AAC/H,SAAK,OAAO,EAAE,SAAY,EAAQ,aAAa;AAC/C,SAAK,YAAY,OAAO,oBAAoB;AAC5C,SAAK,UAAU;AAEf,SAAK,SAAS,KAAK,WAAW,KAAK,YAAa,OAAO,sBAAsB,cAAe;AAC5F,QAAI,OAAO,cAAc,aAAa;AACpC,YAAM,MAAM,UAAU,UAAU,MAAM,eAAe;AACrD,UAAI,OAAO,IAAI,IAAI;AACjB,cAAM,gBAAgB,IAAI,GAAG,MAAM,eAAe;AAClD,aAAK,WAAY,iBAAiB,cAAc,KAAM,cAAc,GAAG,QAAQ,UAAU,EAAE,IAAI;AAC/F,aAAK,QAAQ,UAAU,UAAU,QAAQ,IAAI,IAAI,EAAE;AACnD,YAAI,KAAK,SAAS;AAAI,eAAK,QAAQ,KAAK,MAAM,QAAQ,IAAI,IAAI,EAAE;AAChE,aAAK,QAAQ,KAAK,MAAM,QAAQ,OAAO,GAAG;AAAA,MAU5C;AAAA,IACF,WAAW,OAAO,YAAY,aAAa;AACzC,WAAK,WAAW,GAAG,QAAQ,YAAY,QAAQ;AAC/C,WAAK,QAAQ,UAAU,QAAQ;AAAA,IACjC;AAAA,EACF;AAAA,EAGA,MAAM,gBAAgB;AAEpB,SAAK,WAAW,OAAO,KAAQ,OAAO,EAAE,eAAe;AACvD,SAAK,KAAK,YAAY,OAAO,gBAAgB;AAC7C,SAAK,KAAK,UAAU,KAAK,SAAS,SAAS,MAAM;AACjD,QAAI,KAAK,KAAK,aAAa,KAAK,KAAK,WAAc,WAAW,MAAM,QAAQ;AAC1E,WAAK,KAAK,OAAO,MAAS,IAAI,EAAE,SAAS,uBAAuB;AAChE,WAAK,KAAK,cAAc,MAAS,IAAI,EAAE,SAAS,8BAA8B;AAAA,IAChF;AACA,UAAM,IAAU,OAAO,KAAK,GAAG;AAC/B,UAAM,MAAM,IAAI,EAAE,WAAW,QAAQ,IAAI;AAEzC,SAAK,MAAM,YAAY,OAAO,QAAQ;AACtC,SAAK,MAAM,UAAU,KAAK,SAAS,SAAS,OAAO;AACnD,QAAI,KAAK,MAAM,aAAa,KAAK,MAAM,YAAe,WAAW,MAAM,WAAc,WAAW,MAAM,YAAY;AAEhH,YAAM,KAAQ,QAAQ,EAAE,UAAU,cAAc,MAAS,QAAQ,EAAE,gBAAgB,EAAE,KAAK;AAC1F,UAAI,IAAI;AACN,aAAK,MAAM,UAAU,GAAG,aAAa,GAAG,OAAO;AAC/C,aAAK,MAAM,WAAW,GAAG,aAAa,GAAG,QAAQ;AAAA,MACnD;AAAA,IACF;AAEA,SAAK,OAAO,YAAY,KAAK,WAAW,OAAO,UAAU,WAAW;AACpE,SAAK,OAAO,UAAU,KAAK,SAAS,SAAS,QAAQ;AACrD,QAAI;AAEF,UAAI,KAAK,OAAO;AAAW,aAAK,OAAO,WAAW,MAAM,UAAU,OAAO,eAAe,GAAG;AAAA,IAC7F,SAAQC,IAAN;AACA,WAAK,OAAO,YAAY;AAAA,IAC1B;AACA,QAAI;AACF,WAAK,UAAa,qBAAwB,WAAW,CAAC,EAAE,IAAI,CAAC,WAAW,OAAO,WAAW,YAAY,CAAC;AAAA,IACzG,SAAQA,IAAN;AAAA,IAAa;AAAA,EACjB;AAAA,EAGA,MAAM,YAAY;AAChB,UAAM,MAAM,EAAE,OAAO,IAAI,OAAO,CAAC,EAAE;AACnC,QAAI,KAAK,QAAQ,KAAK,SAAS,WAAW,OAAO,GAAG;AAAA,IAWpD;AACA,QAAI,CAAC,KAAK;AAAQ,aAAO,eAAe,MAAM,OAAO,EAAE,OAAO,IAAI,CAAC;AAAA;AAC9D,WAAK,SAAS;AAAA,EACrB;AACF;AAEO,IAAMC,OAAM,IAAI,IAAI;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;ACnK3B,IAAM,UAAU;AAAA,EACd,aAAa;AAAA,EACb,gBAAgB;AAAA,EAChB,SAAS;AAAA,EACT,OAAO;AAAA,EACP,eAAe;AACjB;AAUO,IAAM,aAAwC,CAAC;AAEtD,eAAe,YAAY,KAAKC,OAAiC;AAC/D,MAAI,QAAQ;AAAO,QAAI,qBAAqB,KAAKA,KAAI;AACrD,SAAO,MAAM,KAAKA,KAAI;AACxB;AAEO,SAAS,oBAAoBC,SAAgB;AAClD,UAAQ,cAAcA,QAAO;AAC7B,UAAQ,UAAUA,QAAO;AACzB,UAAQ,gBAAgBA,QAAO;AACjC;AAEA,eAAsB,UAAU,WAAoD;AAnCpF;AAoCE,MAAI,WAAW,KAAK,QAAQ,eAAe,aAAa,EAAE;AAC1D,MAAI,CAAC,SAAS,YAAY,EAAE,SAAS,OAAO;AAAG,gBAAY;AAC3D,QAAM,oBAAoB,SAAS,SAAS,GAAG,IAAI,SAAS,MAAM,GAAG,IAAI,SAAS,MAAM,IAAI;AAC5F,QAAM,iBAAiB,kBAAkB,kBAAkB,SAAS,GAAG,QAAQ,SAAS,EAAE;AAC1F,QAAM,kBAAkB,iBAAiB;AACzC,aAAW,kBAAkB;AAAA,IAC3B,MAAM;AAAA,IACN,kBAAkB;AAAA,IAClB,mBAAmB;AAAA,IACnB,aAAa,eAAW;AAAA,IACxB,SAAS;AAAA,EACX;AACA,UAAQ,iBAAkB,OAAO,WAAW,eAAiB,OAAO,OAAO,iBAAiB,eAAiB,OAAO,OAAO,cAAc;AACzI,MAAI,eAAe,CAAC;AACpB,MAAI;AACF,mBAAgB,QAAQ,kBAAkB,QAAQ,cAAe,MAAS,WAAG,WAAW,IAAI,CAAC;AAAA,EAC/F,SAAQC,IAAN;AACA,YAAQ,iBAAiB;AAAA,EAC3B;AACA,aAAW,gBAAgB,UAAW,QAAQ,kBAAkB,QAAQ,eAAgB,OAAO,KAAK,YAAY,EAAE,SAAS,eAAe;AAC1I,QAAM,gBAAgB,OAAO,UAAU,cAAc,CAAC,IAAI,EAAE,WAAW,CAAC,KAAKF,UAAU,YAAY,KAAKA,KAAI,EAAE;AAC9G,QAAMG,UAAoB,IAAO,WAAW,WAAW,gBAAgB,UAAU,kBAAkB,UAAU,aAAa;AAC1H,MAAI,SAAS;AACb,MAAI;AAEF,IAAAA,QAAM,cAAc;AACpB,QAAI,QAAQ;AAAO,UAAI,uBAAuBA,QAAM,UAAU;AAE9D,UAAM,YAAY,MAAMA,QAAM,QAAQ,KAAK;AAC3C,eAAW,gBAAgB,qBAAmB,4CAAW,eAAX,mBAAuB,eAAc;AACnF,IAAAA,QAAM,SAAS,SAAS;AAExB,eAAW,gBAAgB,sBAAoB,WAAAA,WAAA,gBAAAA,QAAO,cAAP,mBAAkB,eAAlB,mBAA8B,eAAc;AAC3F,QAAI,QAAQ;AAAS,UAAI,eAAeA,QAAM,aAAa,EAAE,OAAO,WAAW,gBAAgB,kBAAkB,GAAG,OAAO;AAC3H,aAAS;AAAA,EACX,SAAS,KAAP;AACA,QAAI,wBAAwB,UAAU,GAAG;AAAA,EAC3C;AACA,MAAI,UAAU,QAAQ,eAAe,QAAQ,kBAAkB,CAAC,WAAW,gBAAgB,SAAS;AAClG,QAAI;AACF,YAAM,aAAa,MAAMA,QAAM,KAAK,eAAe;AACnD,UAAI,gBAAgB,iBAAiB,UAAU;AAAA,IACjD,SAAS,KAAP;AACA,UAAI,uBAAuB,UAAU,GAAG;AAAA,IAC1C;AAAA,EACF;AACA,SAAOA;AACT;;;;;;ACnFA,IAAAC,kBAAA;AAAA,SAAAA,iBAAA;AAAA;AAAA;AAAA,cAAAC;AAAA,EAAA;AAAA,kBAAAC;AAAA;;;ACeA,IAAIC;AACJ,IAAMC,QAAwB,CAAC;AAC/B,IAAM,YAAY,CAAC,SAAS,SAAS,SAAS,UAAU,OAAO;AAC/D,IAAM,aAAa,CAAC,IAAI,IAAI,IAAI,MAAM,MAAM,MAAM,EAAE;AACpD,IAAI,YAAY;AAChB,IAAI,WAAW;AACf,IAAI,UAAU,OAAO;AAGrB,eAAsB,KAAKC,SAAgB;AAxB3C;AAyBE,MAAIC,KAAI;AAAS,IAAAH,SAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,SAAQ,MAAM,WAAU,KAAAE,QAAO,KAAK,YAAZ,mBAAqB,SAAS;AAAA,WACzDA,QAAO;AAAO,QAAI,iBAAiBF,OAAM,WAAW;AAC7D,SAAOA;AACT;AAGA,eAAsB,QAAQI,QAAeF,SAAgB,KAAaG,QAAkC;AAhC5G;AAiCE,MAAI,CAACL;AAAO,WAAO,EAAE,KAAK,GAAG,QAAQ,WAAW,aAAa,GAAG,MAAM,CAAC,EAAE;AACzE,QAAM,YAAY,aAAW,KAAAE,QAAO,KAAK,YAAZ,mBAAqB,eAAc;AAChE,QAAM,cAAY,KAAAA,QAAO,KAAK,YAAZ,mBAAqB,aAAY,KAAM,IAAI,IAAI;AACjE,MAAIA,QAAO,eAAe,YAAY,aAAc,cAAcG,UAAUJ,MAAK,MAAM;AACrF;AACA,WAAOA,MAAK;AAAA,EACd;AACA,YAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AAzCxC,QAAAK,KAAAC;AA0CI,QAAI,EAACP,UAAA,gBAAAA,OAAO,OAAO,GAAG;AAAO;AAC7B,UAAMQ,KAA4B,CAAC;AAEnC,UAAM,MAAM,CAAC,CAAC,GAAK,KAAM,KAAM,GAAI,CAAC;AACpC,IAAAA,GAAE,SAAY,MAAM,cAAcJ,QAAO,KAAK,CAAC,CAAC,GAAG,CAACJ,OAAM,OAAO,GAAG,MAAM,IAAIA,OAAM,OAAO,GAAG,MAAM,EAAE,CAAC;AACvG,UAAM,MAAgB,EAAE,KAAK,GAAG,QAAQ,WAAW,aAAa,GAAG,MAAM,CAAC,EAAE;AAC5E,SAAIM,MAAAJ,QAAO,KAAK,YAAZ,gBAAAI,IAAqB;AAAS,OAACE,GAAE,KAAKA,GAAE,QAAQA,GAAE,IAAI,IAAIR,OAAM,QAAQQ,GAAE,QAAQ,CAAC,cAAc,iBAAiB,aAAa,CAAC;AACpI,UAAMC,UAAS,MAAMD,GAAE,OAAO,KAAK;AACnC,QAAI,SAASC,QAAO,KAAKA,QAAO,KAAK,SAAS;AAC9C,QAAI,cAAc,KAAK,MAAM,OAAOA,QAAO,KAAKA,QAAO,KAAKA,QAAO,KAAKA,QAAO,GAAG,IAAI;AACtF,UAAM,OAAO,MAAMD,GAAE,KAAK,KAAK;AAC/B,aAASE,KAAI,GAAGA,KAAI,KAAK,QAAQA,MAAK;AACpC,UAAI,KAAKA,SAAMH,MAAAL,QAAO,KAAK,YAAZ,gBAAAK,IAAqB,kBAAiB;AAAM,YAAI,KAAK,KAAK,EAAE,OAAO,KAAK,MAAM,MAAM,KAAKG,GAAE,IAAI,KAAK,MAAM,UAAUA,IAAW,CAAC;AAAA,IACjJ;AACA,QAAI,KAAK,KAAK,CAAC,GAAG,MAAM,EAAE,QAAQ,EAAE,KAAK;AAEzC,UAAM,kBAAkB,MAAM,KAAK,MAAMF,GAAE,IAAI,KAAK,CAAC;AACrD,UAAM,YAAY,gBAAgB,IAAI,CAAC,GAAGE,OAAM,CAAC,WAAWA,KAAI,CAAC,CAAC,EAAE,KAAK,CAAC,GAAG,MAAM,EAAE,KAAK,EAAE,EAAE;AAC9F,QAAIC,OAAM,UAAU,GAAG;AACvB,aAASD,KAAI,GAAGA,KAAI,UAAU,QAAQA;AAAK,MAAAC,QAAO,UAAUD,IAAG,MAAM,UAAUA,IAAG,KAAKC;AACvF,QAAI,MAAM,KAAK,MAAM,KAAKA,IAAG,IAAI;AACjC,WAAO,KAAKH,EAAC,EAAE,QAAQ,CAACI,YAAc,QAAQJ,GAAEI,QAAO,CAAC;AACxD,IAAAX,MAAK,OAAO;AACZ,gBAAYI;AACZ,eAAW,IAAI;AACf,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;AClEO,IAAM,YAAwD;AAAA,EACnE,OAAO;AAAA,EACP,KAAK;AAAA,EACL,KAAK;AAAA,EACL,MAAM;AAAA,EACN,OAAO;AAAA,EACP,KAAK,CAAC,QAAQ,OAAQ,KAAM;AAC9B;AAEO,SAASQ,QAAO;AACrB,YAAU,QAAW,OAAO,KAAK,SAAS;AAC1C,YAAU,MAAS,OAAO,GAAG,SAAS;AACtC,YAAU,MAAS,OAAO,GAAG,SAAS;AACtC,YAAU,OAAU,OAAO,KAAK,SAAS;AACzC,YAAU,QAAW,OAAO,OAAO,SAAS;AAC5C,YAAU,MAAS,SAAS,CAAC,QAAQ,OAAQ,KAAM,GAAG,SAAS;AACjE;;;ACLA,IAAIC;AACJ,IAAMC,QAA+B,CAAC;AACtC,IAAIC,aAAY;AAChB,IAAIC,YAAW;AACf,IAAIC,WAAU,OAAO;AAGrB,eAAsBC,MAAKC,SAAgB;AACzC,MAAIC,KAAI;AAAS,IAAAP,SAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,SAAQ,MAAM,UAAUM,QAAO,KAAK,UAAU,YAAY;AAAA,WAC7DA,QAAO;AAAO,QAAI,iBAAiBN,OAAM,WAAW;AAC7D,SAAOA;AACT;AAGA,eAAsBQ,SAAQC,QAAeH,SAAgB,KAAaI,QAAyC;AA7BnH;AA8BE,MAAI,CAACV;AAAO,WAAO,EAAE,KAAK,EAAE;AAC5B,QAAM,YAAYI,cAAW,KAAAE,QAAO,KAAK,cAAZ,mBAAuB,eAAc;AAClE,QAAM,cAAY,KAAAA,QAAO,KAAK,cAAZ,mBAAuB,aAAY,KAAM,IAAI,IAAIH;AACnE,MAAIG,QAAO,eAAe,aAAa,YAAaJ,eAAcQ,YAAU,KAAAT,MAAK,SAAL,mBAAW,UAAQ,KAAAA,MAAK,SAAL,mBAAW,OAAM,GAAI;AAClH,IAAAG;AACA,WAAOH,MAAK;AAAA,EACd;AACA,EAAAG,WAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,QAAI,EAACJ,UAAA,gBAAAA,OAAO,WAAU,CAACA,OAAM,OAAO,MAAM,CAACA,OAAM,OAAO,GAAG;AAAO;AAClE,UAAMW,KAA4B,CAAC;AACnC,IAAAA,GAAE,SAAY,MAAM,eAAeF,QAAO,CAACT,OAAM,OAAO,GAAG,MAAM,IAAIA,OAAM,OAAO,GAAG,MAAM,EAAE,GAAG,KAAK;AACrG,IAAAW,GAAE,UAAa,IAAIA,GAAE,QAAQ,UAAU,KAAK;AAC5C,UAAM,MAAM,EAAE,KAAK,EAAE;AACrB,QAAIL,QAAO,KAAK,UAAU;AAAS,MAAAK,GAAE,MAAMX,OAAM,QAAQW,GAAE,OAAO;AAClE,QAAIA,GAAE,KAAK;AACT,YAAM,OAAO,MAAMA,GAAE,IAAI,KAAK;AAC9B,UAAI,MAAM,KAAK,MAAM,KAAK,KAAK,EAAE,IAAI;AAAA,IACvC;AACA,WAAO,KAAKA,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,IAAAX,MAAK,OAAO;AACZ,IAAAC,aAAYQ;AACZ,IAAAP,YAAW,IAAI;AACf,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;ACxCA,IAAIU;AACJ,IAAMC,QAAuD,CAAC;AAC9D,IAAIC,aAAY;AAChB,IAAIC,YAAW;AACf,IAAIC,WAAU,OAAO;AAGrB,IAAM,MAAM,CAAC,QAAQ,OAAQ,KAAM;AAGnC,eAAsBC,MAAKC,SAAsB;AAC/C,MAAIC,KAAI;AAAS,IAAAP,SAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,SAAQ,MAAM,UAAUM,QAAO,KAAK,UAAU,eAAe;AAAA,WAChEA,QAAO;AAAO,QAAI,iBAAiBN,OAAM,WAAW;AAC7D,SAAOA;AACT;AAGA,eAAsBQ,SAAQC,QAAeH,SAAgB,KAAKI,QAAyD;AAjC3H;AAkCE,MAAI,CAACV;AAAO,WAAO,EAAE,QAAQ,WAAW,aAAa,EAAE;AACvD,QAAM,YAAYI,cAAW,KAAAE,QAAO,KAAK,cAAZ,mBAAuB,eAAc;AAClE,QAAM,cAAY,KAAAA,QAAO,KAAK,cAAZ,mBAAuB,aAAY,KAAM,IAAI,IAAIH;AACnE,MAAIG,QAAO,eAAe,aAAa,YAAaJ,eAAcQ,YAAU,KAAAT,MAAK,SAAL,mBAAW,aAAW,KAAAA,MAAK,SAAL,mBAAW,eAAc,GAAI;AAC7H,IAAAG;AACA,WAAOH,MAAK;AAAA,EACd;AACA,EAAAG,WAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,QAAI,EAACJ,UAAA,gBAAAA,OAAO,OAAO,GAAG;AAAO;AAC7B,UAAMW,KAA4B,CAAC;AACnC,IAAAA,GAAE,SAAY,MAAM,eAAeF,QAAO,CAACT,OAAM,OAAO,GAAG,MAAM,IAAIA,OAAM,OAAO,GAAG,MAAM,EAAE,GAAG,KAAK;AACrG,IAAAW,GAAE,UAAa,KAAK,MAAM;AACxB,YAAM,CAAC,KAAK,OAAO,IAAI,IAAO,MAAMA,GAAE,QAAQ,GAAG,CAAC;AAClD,YAAM,UAAa,IAAI,KAAK,IAAI,EAAE;AAClC,YAAM,YAAe,IAAI,OAAO,IAAI,EAAE;AACtC,YAAM,WAAc,IAAI,MAAM,IAAI,EAAE;AACpC,YAAM,YAAe,KAAK,CAAC,SAAS,WAAW,QAAQ,CAAC;AACxD,YAAM,YAAe,IAAO,IAAI,WAAW,UAAU,IAAI,GAAG,CAAC;AAC7D,aAAO;AAAA,IACT,CAAC;AACD,UAAM,MAA+C,EAAE,QAAQ,WAAW,aAAa,EAAE;AACzF,QAAIL,QAAO,KAAK,UAAU;AAAS,MAAAK,GAAE,SAASX,OAAM,QAAQW,GAAE,OAAO;AACrE,UAAM,OAAO,MAAMA,GAAE,OAAO,KAAK;AACjC,QAAI,SAAS,KAAK,KAAK,KAAK,KAAK,WAAW;AAC5C,QAAI,cAAc,KAAK,KAAK,KAAK,KAAM,KAAK,MAAM,MAAM,KAAK,EAAE,IAAI,MAAQ,KAAK,MAAM,MAAM,KAAK,EAAE,IAAI;AACvG,WAAO,KAAKA,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,IAAAX,MAAK,OAAO;AACZ,IAAAC,aAAYQ;AACZ,IAAAP,YAAW,IAAI;AACf,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;ACvDA,IAAIU;AACJ,IAAM,SAAwB,CAAC;AAC/B,IAAIC,WAAU,OAAO;AACrB,IAAIC,aAAY;AAChB,IAAIC,YAAW;AAEf,eAAsBC,MAAKC,SAAqC;AAjBhE;AAkBE,MAAIC,KAAI;AAAS,IAAAN,SAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,SAAQ,MAAM,WAAU,KAAAK,QAAO,KAAK,cAAZ,mBAAuB,SAAS;AAAA,WAC3DA,QAAO;AAAO,QAAI,iBAAiBL,OAAM,WAAW;AAC7D,SAAOA;AACT;AAEA,eAAsBO,SAAQC,QAAeH,SAAgB,KAAaI,QAAgC;AAxB1G;AAyBE,MAAI,CAACT;AAAO,WAAO;AACnB,QAAM,cAAY,KAAAK,QAAO,KAAK,cAAZ,mBAAuB,aAAY,KAAM,IAAI,IAAIF;AACnE,QAAM,YAAYF,cAAW,KAAAI,QAAO,KAAK,cAAZ,mBAAuB,eAAc;AAClE,MAAIA,QAAO,eAAe,YAAY,aAAcH,eAAcO,UAAU,OAAO,MAAM;AACvF,IAAAR;AACA,WAAO,OAAO;AAAA,EAChB;AACA,EAAAA,WAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,UAAM,SAAY,MAAM,eAAeO,QAAO,EAACR,UAAA,gBAAAA,OAAO,OAAO,GAAG,SAAQA,OAAM,OAAO,GAAG,MAAM,KAAK,IAAGA,UAAA,gBAAAA,OAAO,OAAO,GAAG,SAAQA,OAAM,OAAO,GAAG,MAAM,KAAK,CAAC,GAAG,KAAK;AACnK,UAAM,MAAMA,UAAA,gBAAAA,OAAO,QAAQ;AAC3B,UAAM,OAAO,MAAM,IAAI,KAAK,GAAG;AAC/B,WAAO,OAAO,KAAK,MAAM,MAAM,GAAG,IAAI;AACtC,IAAAE,aAAYO;AACZ,IAAAN,YAAW,IAAI;AACf,IAAG,QAAQ,CAAC,QAAQ,GAAG,CAAC;AACxB,YAAQ,OAAO,IAAI;AAAA,EACrB,CAAC;AACH;;;ACtCO,IAAM,kBAA4C;AAAA,EACvD,YAAY;AAAA,IACV;AAAA,IAAI;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IACtD;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IACvD;AAAA,IAAK;AAAA,IAAI;AAAA,IAAK;AAAA,IAAI;AAAA,IAAK;AAAA,IAAK;AAAA,IAAK;AAAA,IAAI;AAAA,IAAI;AAAA,IAAK;AAAA,IAAI;AAAA,EACpD;AAAA,EAKA,gBAAgB,CAAC,KAAK,IAAI,IAAI,IAAI,GAAG,KAAK,KAAK,KAAK,GAAG;AAAA,EACvD,gBAAgB,CAAC,IAAI,KAAK,IAAI,KAAK,IAAI,IAAI,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAClE,gBAAgB,CAAC,KAAK,IAAI,IAAI,IAAI,IAAI,KAAK,KAAK,KAAK,GAAG;AAAA,EACxD,gBAAgB,CAAC,IAAI,IAAI,IAAI,KAAK,IAAI,IAAI,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACjE,oBAAoB,CAAC,IAAI,IAAI,IAAI,KAAK,IAAI,IAAI,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACrE,oBAAoB,CAAC,KAAK,IAAI,IAAI,IAAI,IAAI,KAAK,KAAK,KAAK,GAAG;AAAA,EAC5D,oBAAoB,CAAC,IAAI,IAAI,IAAI,KAAK,IAAI,IAAI,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACrE,oBAAoB,CAAC,KAAK,IAAI,IAAI,IAAI,IAAI,KAAK,KAAK,KAAK,GAAG;AAAA,EAC5D,gBAAgB,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAClD,gBAAgB,CAAC,IAAI,GAAG,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACzD,gBAAgB,CAAC,KAAK,IAAI,IAAI,IAAI,IAAI,IAAI,GAAG;AAAA,EAC7C,gBAAgB,CAAC,KAAK,IAAI,KAAK,IAAI,IAAI,IAAI,IAAI,KAAK,GAAG;AAAA,EACvD,gBAAgB,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAClD,gBAAgB,CAAC,KAAK,IAAI,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAC3D,gBAAgB,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAC5D,mBAAmB,CAAC,KAAK,IAAI,IAAI,KAAK,IAAI,KAAK,IAAI,GAAG;AAAA,EACtD,mBAAmB,CAAC,IAAI,KAAK,IAAI,IAAI,IAAI,EAAE;AAAA,EAC3C,cAAc,CAAC,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACtC,eAAe,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACjD,eAAe,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAC3D,eAAe,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACjD,eAAe,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAC3D,eAAe,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACjD,eAAe,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAC3D,eAAe,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAC3D,kBAAkB,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACzD,kBAAkB,CAAC,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EAC/C,aAAa,CAAC,KAAK,KAAK,KAAK,KAAK,GAAG;AAAA,EACrC,mBAAmB,CAAC,GAAG;AAAA,EACvB,SAAS,CAAC,CAAC;AAAA,EACX,YAAY,CAAC,CAAC;AAAA,EACd,iBAAiB,CAAC,EAAE;AAAA,EACpB,gBAAgB,CAAC,GAAG;AAAA,EACpB,YAAY,CAAC,GAAG;AAAA,EAChB,WAAW,CAAC,GAAG;AACjB;AAEO,IAAM,gBAAmD;AAAA,EAC9D,OAAO;AAAA,EACP,OAAO;AAAA,EACP,cAAc,CAAC,IAAI,gBAAgB,qBAAqB,EAAE;AAC5D;AAEO,IAAM,qBAAwD;AAAA,EACnE,SAAS;AAAA,EACT,UAAU;AAAA,EACV,MAAM;AAAA,EACN,OAAO;AAAA,EACP,SAAS;AAAA,EACT,UAAU;AAAA,EACV,cAAc,CAAC,GAAG,CAAC;AACrB;AAEO,IAAM,cAAyD;AAAA,EACpE,EAAE,KAAK,aAAa,SAAS,CAAC,GAAG,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAAA,EACzD,EAAE,KAAK,aAAa,SAAS,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAAA,EAC1D,EAAE,KAAK,aAAa,SAAS,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAAA,EAC1D,EAAE,KAAK,aAAa,SAAS,CAAC,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,CAAC,EAAE;AAAA,EACzD,EAAE,KAAK,aAAa,SAAS,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAAA,EAClE,EAAE,KAAK,aAAa,SAAS,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAAA,EAClE,EAAE,KAAK,aAAa,SAAS,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAAA,EAClE,EAAE,KAAK,gBAAgB,SAAS,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAAA,EACjE,EAAE,KAAK,gBAAgB,SAAS,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,EAAE;AAC3D;AAEO,IAAM,QAA4B;AAAA,EACvC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,gBAAgB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,iBAAiB,gBAAgB;AAAA,EAClC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,gBAAgB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,gBAAgB,iBAAiB;AAAA,EAClC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,kBAAkB,iBAAiB;AAAA,EACpC,CAAC,iBAAiB,iBAAiB;AAAA,EACnC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AAAA,EACrC,CAAC,mBAAmB,iBAAiB;AACvC;AAEO,IAAM,SAAwB;AAAA,EACnC;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAG;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EACtJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAClJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EACr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lJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EACrJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EACpJ;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAG;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACnJ;AAAA,EAAK;AAAA,EAAI;AAAA,EAAG;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACnJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAG;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAC9I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EACtJ;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAClJ;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAG;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACnJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACrJ;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACpJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAClJ;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACnJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACnJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EACnJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAChJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAChJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC7I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAClJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC7I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EACnJ;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACpJ;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAClJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAClJ;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAChJ;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EACpJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EACrJ;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACp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jJ;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAC9I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EACpJ;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACrJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EACpJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EACpJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAC9I;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAI;AAAA,EAClJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAChJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAChJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9I;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/I;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAChJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAClJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACpJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACjJ;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAG;AAwB1I,IAAM,QAAuB;AAAA,EACtB;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC/E;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC1C;AAAA,EAAK;AAAA,EAAG;AAAA,EAAK;AAAA,EAAG;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAChC;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACtD;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAChD;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAI;AAC7C;AAEO,IAAM,QAAuB,CAAC,IAAI,KAAK,KAAK,KAAK,GAAG,IAAI,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG,KAAK,KAAK,GAAG,IAAI,IAAI,IAAI,KAAK,KAAK,KAAK,KAAK,KAAK,IAAI,IAAI,KAAK,IAAI,KAAK,KAAK,KAAK,IAAI,KAAK,GAAG;AAElL,IAAM,OAAsB,CAAC,IAAI,KAAK,KAAK,KAAK,GAAG,IAAI,GAAG;AAE1D,IAAM,OAAO,MAAM,IAAI,CAAC,MAAM,MAAM,EAAE;AAEtC,IAAM,OAAO,MAAM,IAAI,CAAC,MAAM,MAAM,EAAE;AAEtC,IAAM,MAAM,KAAK,IAAI,CAAC,MAAM,MAAM,EAAE;AAO3C,SAAS,qBAAqB,aAAwB;AACpD,QAAM,UAAU,YAAY,IAAI,CAAC,eAAe,WAAW,EAAE;AAC7D,UAAQ,KAAK,YAAY,YAAY,SAAS,GAAG,EAAE;AACnD,SAAO;AACT;AAEO,IAAM,YAAuB;AAAA,EACl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eAA0B,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAE/N,IAAM,mBAA8B,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAEnI,IAAM,gBAA2B,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAEhF,IAAM,gBAA2B,CAAC,CAAC,IAAI,CAAC,GAAG,CAAC,GAAG,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,IAAI,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAE1N,IAAM,oBAA+B,CAAC,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,GAAG,GAAG,CAAC,KAAK,EAAE,GAAG,CAAC,IAAI,GAAG,CAAC;AAEvH,IAAM,iBAA4B,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAEjF,IAAM,mBAA8B;AAAA,EACzC,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EACpE,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EACrE,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EACrE,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EACrE,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EACjE,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAChE;AAEO,IAAM,mBAAmB;AAAA,EAC9B,MAAM,qBAAqB,SAAS;AAAA,EACpC,SAAS,qBAAqB,YAAY;AAAA,EAC1C,aAAa,qBAAqB,gBAAgB;AAAA,EAClD,UAAU,qBAAqB,aAAa;AAAA,EAC5C,UAAU,qBAAqB,aAAa;AAAA,EAC5C,cAAc,qBAAqB,iBAAiB;AAAA,EACpD,WAAW,qBAAqB,cAAc;AAAA,EAC9C,UAAU,qBAAqB,gBAAgB;AACjD;;;ACrsBO,IAAM,aAAa,CAAC,QAA0B,CAAC,KAAK,IAAI,IAAI,SAAS,KAAK,IAAI,WAAW,EAAE,GAAG,KAAK,IAAI,IAAI,SAAS,KAAK,IAAI,WAAW,EAAE,CAAC;AAE3I,IAAM,eAAe,CAAC,QAAkC,CAAC,IAAI,WAAW,MAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM,GAAG,IAAI,WAAW,MAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM,GAAG,CAAC;AAExL,IAAM,WAAW,CAAC,KAAKO,WAAgB,MAAM;AAAA,EAClD,KAAK,MAAM,KAAK,IAAI,GAAG,IAAI,WAAW,EAAE,CAAC;AAAA,EACzC,KAAK,MAAM,KAAK,IAAI,GAAG,IAAI,WAAW,EAAE,CAAC;AAAA,EACzC,KAAK,MAAM,KAAK,IAAKA,OAAM,MAAM,MAAM,GAAI,IAAI,SAAS,EAAE,IAAI,KAAK,IAAI,GAAG,IAAI,WAAW,EAAE,CAAC;AAAA,EAC5F,KAAK,MAAM,KAAK,IAAKA,OAAM,MAAM,MAAM,GAAI,IAAI,SAAS,EAAE,IAAI,KAAK,IAAI,GAAG,IAAI,WAAW,EAAE,CAAC;AAC9F,IAAI,CAAC,GAAG,GAAG,GAAG,CAAC;AAER,IAAM,YAAY,CAAC,KAAKA,WAAgB,MAAM;AAAA,EACnD,IAAI,WAAW,MAAMA,OAAM,MAAM,MAAM;AAAA,EACvC,IAAI,WAAW,MAAMA,OAAM,MAAM,MAAM;AAAA,GACtC,IAAI,SAAS,KAAK,IAAI,WAAW,OAAOA,OAAM,MAAM,MAAM;AAAA,GAC1D,IAAI,SAAS,KAAK,IAAI,WAAW,OAAOA,OAAM,MAAM,MAAM;AAC7D,IAAI,CAAC,GAAG,GAAG,GAAG,CAAC;AAER,IAAM,sBAAsB,CAAC,KAAK,WAAW;AAClD,QAAM,aAAoB,CAAC,IAAI,WAAW,KAAK,OAAO,IAAI,IAAI,WAAW,KAAK,OAAO,EAAE;AACvF,QAAM,WAAkB,CAAC,IAAI,SAAS,KAAK,OAAO,IAAI,IAAI,SAAS,KAAK,OAAO,EAAE;AACjF,SAAO,EAAE,YAAY,UAAU,WAAW,IAAI,WAAW,YAAY,IAAI,WAAW;AACtF;AAEO,IAAM,eAAe,CAAC,KAAKC,QAAO,aAAa;AACpD,QAAM,IAAIA,OAAM,MAAM;AACtB,QAAM,IAAIA,OAAM,MAAM;AACtB,QAAM,SAAS,CAAC,IAAI,WAAW,KAAK,GAAG,IAAI,WAAW,KAAK,GAAG,IAAI,SAAS,KAAK,GAAG,IAAI,SAAS,KAAK,CAAC;AACtG,QAAM,OAAU,MAAM,cAAcA,QAAO,CAAC,MAAM,GAAG,CAAC,CAAC,GAAG,QAAQ;AAClE,QAAMC,QAAU,IAAI,MAAM,UAAU,KAAK;AACzC,EAAG,QAAQ,IAAI;AACf,SAAOA;AACT;AAEO,IAAM,aAAa,CAAC,KAAK,WAAW;AACzC,QAAM,SAAS,aAAa,GAAG;AAC/B,QAAMC,QAAO,WAAW,GAAG;AAC3B,QAAM,WAA6B,CAAC,SAASA,MAAK,KAAK,GAAG,SAASA,MAAK,KAAK,CAAC;AAC9E,SAAO,EAAE,YAAY,CAAC,OAAO,KAAK,SAAS,IAAI,OAAO,KAAK,SAAS,EAAE,GAAY,UAAU,CAAC,OAAO,KAAK,SAAS,IAAI,OAAO,KAAK,SAAS,EAAE,GAAY,WAAW,IAAI,WAAW,YAAY,IAAI,WAAW;AAChN;AAEO,IAAM,cAAc,CAAC,QAAQ;AAClC,QAAM,UAAU,aAAa,GAAG;AAChC,QAAMA,QAAO,WAAW,GAAG;AAC3B,QAAM,WAAW,KAAK,IAAI,GAAGA,KAAI,IAAI;AACrC,SAAO,EAAE,YAAY,CAAC,KAAK,MAAM,QAAQ,KAAK,QAAQ,GAAG,KAAK,MAAM,QAAQ,KAAK,QAAQ,CAAC,GAAY,UAAU,CAAC,KAAK,MAAM,QAAQ,KAAK,QAAQ,GAAG,KAAK,MAAM,QAAQ,KAAK,QAAQ,CAAC,GAAY,WAAW,IAAI,WAAW,YAAY,IAAI,WAAW;AACxP;AAEO,IAAM,gCAAgC,CAAC,cAAc;AAC1D,QAAM,IAAI,UAAU,IAAI,CAAC,MAAM,EAAE,EAAE;AACnC,QAAM,IAAI,UAAU,IAAI,CAAC,MAAM,EAAE,EAAE;AACnC,SAAO,EAAE,YAAY,CAAC,KAAK,IAAI,GAAG,CAAC,GAAG,KAAK,IAAI,GAAG,CAAC,CAAC,GAAY,UAAU,CAAC,KAAK,IAAI,GAAG,CAAC,GAAG,KAAK,IAAI,GAAG,CAAC,CAAC,GAAY,UAAU;AACjI;AAEO,IAAM,sBAAsB,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC;AAE5D,IAAM,mBAAmB,CAAC,UAAU,QAAQ,IAAI,KAAK,KAAK,KAAK,OAAO,QAAQ,KAAK,OAAO,IAAI,KAAK,GAAG;AAEtG,IAAM,kBAAkB,CAAC,QAAQ,WAAW,iBAAiB,KAAK,KAAK,IAAI,KAAK,MAAM,EAAE,OAAO,KAAK,OAAO,KAAK,OAAO,KAAK,OAAO,EAAE,CAAC;AAItI,IAAM,yBAAyB,CAAC,GAAG,MAAM,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC;AAEzE,IAAMC,OAAM,CAAC,IAAc,OAAiB;AACjD,MAAI,UAAU;AACd,WAASC,KAAI,GAAGA,KAAI,GAAG,QAAQA;AAAK,eAAW,GAAGA,MAAK,GAAGA;AAC1D,SAAO;AACT;AAEO,IAAM,qBAAqB,CAAC,KAAK,gBAAgB;AACtD,QAAM,SAAwB,CAAC;AAC/B,WAASA,KAAI,GAAGA,KAAI,IAAI,QAAQA;AAAK,WAAO,KAAK,IAAIA,IAAG,YAAY;AACpE,SAAO;AACT;AAEO,IAAM,4BAA4B,CAAC,MAAM,SAAS;AACvD,QAAM,UAA2B,CAAC;AAClC,QAAMC,QAAO,KAAK;AAClB,WAAS,MAAM,GAAG,MAAMA,OAAM,OAAO;AACnC,YAAQ,KAAK,CAAC,CAAC;AACf,aAAS,MAAM,GAAG,MAAMA,OAAM;AAAO,cAAQ,KAAK,KAAKF,KAAI,KAAK,MAAM,mBAAmB,MAAM,GAAG,CAAC,CAAC;AAAA,EACtG;AACA,SAAO;AACT;AAEO,IAAM,sBAAsB,CAAC,UAAU,WAAW;AACvD,QAAM,OAAO,KAAK,IAAI,QAAQ;AAC9B,QAAM,OAAO,KAAK,IAAI,QAAQ;AAC9B,QAAM,iBAAiB,CAAC,CAAC,MAAM,CAAC,MAAM,CAAC,GAAG,CAAC,MAAM,MAAM,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC;AACpE,QAAM,oBAAoB,uBAAuB,OAAO,IAAI,OAAO,EAAE;AACrE,QAAM,2BAA2B,0BAA0B,mBAAmB,cAAc;AAC5F,QAAM,4BAA4B,uBAAuB,CAAC,OAAO,IAAI,CAAC,OAAO,EAAE;AAC/E,SAAO,0BAA0B,0BAA0B,yBAAyB;AACtF;AAEO,IAAM,wBAAwB,CAAC,WAAW;AAC/C,QAAM,oBAAoB,CAAC,CAAC,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE,GAAG,CAAC,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE,CAAC;AACrF,QAAM,uBAAuB,CAAC,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE;AACxD,QAAM,sBAAsB,CAAC,CAACA,KAAI,kBAAkB,IAAI,oBAAoB,GAAG,CAACA,KAAI,kBAAkB,IAAI,oBAAoB,CAAC;AAC/H,SAAO,CAAC,kBAAkB,GAAG,OAAO,oBAAoB,EAAE,GAAG,kBAAkB,GAAG,OAAO,oBAAoB,EAAE,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC;AAC7H;AAEO,IAAM,cAAc,CAAC,uBAAuB,mBAAmB,CAACA,KAAI,uBAAuB,eAAe,EAAE,GAAGA,KAAI,uBAAuB,eAAe,EAAE,CAAC;AAI5J,SAAS,gBAAgBG,aAAW;AACzC,QAAM,OAAOA,gBAAc,MACvB,EAAE,SAAS,CAAC,CAAC,GAAG,SAAS,CAAC,CAAC,EAAE,IAC7B,EAAE,SAAS,CAACA,cAAY,IAAIA,cAAY,CAAC,GAAG,SAAS,CAAC,GAAG,CAAC,EAAE;AAChE,QAAMC,WAAmC,CAAC;AAC1C,WAASC,KAAI,GAAGA,KAAI,KAAK,QAAQ,QAAQA,MAAK;AAC5C,UAAM,SAAS,KAAK,QAAQA;AAC5B,UAAM,WAAW,KAAK,OAAOF,cAAY,SAAS,KAAK,MAAM;AAC7D,UAAM,WAAW,KAAK,OAAOA,cAAY,SAAS,KAAK,MAAM;AAC7D,UAAM,aAAa,KAAK,QAAQE;AAChC,aAAS,QAAQ,GAAG,QAAQ,UAAU,SAAS;AAC7C,YAAM,UAAU,UAAU,QAAQ;AAClC,eAAS,QAAQ,GAAG,QAAQ,UAAU,SAAS;AAC7C,cAAM,UAAU,UAAU,QAAQ;AAClC,iBAASC,KAAI,GAAGA,KAAI,YAAYA;AAAK,UAAAF,SAAQ,KAAK,CAAC,SAAS,OAAO,CAAC;AAAA,MACtE;AAAA,IACF;AAAA,EACF;AACA,SAAOA;AACT;AAEO,SAAS,mBAAmB,WAAW,KAAK,OAAO,gBAAgBD,aAAW;AACnF,QAAM,UAAU,WAAW,GAAG;AAC9B,QAAM,eAAe,UAAU,IAAI,CAAC,UAAW;AAAA,IAC5C,QAAQ,KAAKA,eAAc,MAAM,KAAMA,cAAY;AAAA,IACnD,QAAQ,KAAKA,eAAc,MAAM,KAAMA,cAAY;AAAA,IACnD,MAAM,MAAM;AAAA,EACf,CAAE;AACF,QAAM,aAAa,SAAU,UAAU,KAAO,KAAK,IAAI,KAAK,IAAI;AAChE,QAAM,uBAAuB,aAAa,oBAAoB,OAAO,CAAC,GAAG,CAAC,CAAC,IAAI;AAC/E,QAAM,gBAAgB,aAAa,aAAa,IAAI,CAAC,UAAW,CAAC,GAAG,YAAY,OAAO,oBAAoB,GAAG,MAAM,EAAE,CAAE,IAAI;AAC5H,QAAM,wBAAwB,aAAa,sBAAsB,cAAc,IAAI;AACnF,QAAM,YAAY,aAAa,GAAG;AAClC,QAAM,UAAU,CAACI,KAAI,WAAW,sBAAsB,EAAE,GAAGA,KAAI,WAAW,sBAAsB,EAAE,CAAC;AACnG,SAAO,cAAc,IAAI,CAAC,UAAW;AAAA,IACnC,KAAK,MAAM,MAAM,KAAK,QAAQ,EAAE;AAAA,IAChC,KAAK,MAAM,MAAM,KAAK,QAAQ,EAAE;AAAA,IAChC,KAAK,MAAM,MAAM,MAAM,CAAC;AAAA,EAC1B,CAAE;AACJ;AAEO,SAAS,oBAAoB,QAAQ,KAAKC,QAAOL,aAAW;AACjE,QAAM,eAAgB,IAAI,UAAU,UAAiB,cAAc,QACxD,cAAc,eACd,mBAAmB;AAC9B,MAAI,QAAQ;AACZ,MAAI,iBAAiB;AACrB,MAAIM;AAEJ,MAAI,UAAUC,KAAI,QAAQ,SAAS,kBAAkB,GAAG;AACtD,YAAQ,gBAAgB,IAAI,UAAU,aAAa,KAAK,IAAI,UAAU,aAAa,GAAG;AACtF,UAAM,aAAa,SAAU,UAAU,KAAO,KAAK,IAAI,KAAK,IAAI;AAChE,QAAI,YAAY;AACd,YAAM,SAAgB,aAAa,GAAG;AACtC,YAAM,YAAmB,CAAC,OAAO,KAAKF,OAAM,MAAM,IAAI,OAAO,KAAKA,OAAM,MAAM,EAAE;AAChF,YAAM,UAAa,MAAM,iBAAiBA,QAAO,OAAO,GAAG,SAAS;AACpE,uBAAiB,oBAAoB,CAAC,OAAO,MAAM;AACnD,MAAAC,QAAO,aAAa,KAAK,SAAS,CAACN,aAAWA,WAAS,CAAC;AACxD,MAAG,QAAQ,OAAO;AAAA,IACpB,OAAO;AACL,MAAAM,QAAO,aAAa,KAAKD,QAAO,CAACL,aAAWA,WAAS,CAAC;AAAA,IACxD;AAAA,EACF,OAAO;AACL,IAAAM,QAAO,aAAa,KAAKD,QAAO,CAACL,aAAWA,WAAS,CAAC;AAAA,EACxD;AACA,SAAO,CAAC,OAAO,gBAAgBM,KAAI;AACrC;AAEO,IAAM,iBAAiB,CAAC,SAAS;AACtC,QAAM,IAAI,KAAK,IAAI,CAAC,MAAM,EAAE,EAAE;AAC9B,QAAM,IAAI,KAAK,IAAI,CAAC,MAAM,EAAE,EAAE;AAO9B,SAAO,CAAC,KAAK,IAAI,GAAG,CAAC,KAAK,KAAK,IAAI,GAAG,CAAC,IAAI,KAAK,IAAI,GAAG,CAAC,KAAK,GAAG,KAAK,IAAI,GAAG,CAAC,KAAK,KAAK,IAAI,GAAG,CAAC,IAAI,KAAK,IAAI,GAAG,CAAC,KAAK,CAAC;AACxH;AAEO,IAAM,mBAAmB,CAAC,MAAM,gBAAgB;AACrD,QAAM,SAAS,eAAe,IAAI;AAClC,QAAM,UAAU,WAAW,WAAW;AACtC,QAAM,gBAAgB;AAAA,IACpB,YAAY,CAAC,OAAO,KAAK,QAAQ,KAAK,GAAG,OAAO,KAAK,QAAQ,KAAK,CAAC;AAAA,IACnE,UAAU,CAAC,OAAO,KAAK,QAAQ,KAAK,GAAG,OAAO,KAAK,QAAQ,KAAK,CAAC;AAAA,EACnE;AACA,SAAO;AACT;;;ACnMA,IAAM,iBAAiB;AACvB,IAAM,qBAAqB;AAC3B,IAAIE;AACJ,IAAI,UAAyB;AAC7B,IAAI,YAAY;AAChB,IAAI,aAA4B;AAIzB,IAAM,OAAO,MAAM;AAE1B,eAAsBC,MAAKC,SAAqC;AA1BhE;AA2BE,MAAIC,KAAI;AAAS,IAAAH,SAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,SAAQ,MAAM,WAAU,KAAAE,QAAO,KAAK,aAAZ,mBAAsB,SAAS;AAAA,WAC1DA,QAAO;AAAO,QAAI,iBAAiBF,OAAM,WAAW;AAC7D,cAAYA,OAAM,OAAO,GAAG,QAAQA,OAAM,OAAO,GAAG,MAAM,KAAK;AAC/D,eAAgB,OAAO,WAAW,OAAO;AACzC,YAAa,SAAc,gBAAgB,SAAS,CAAC;AACrD,SAAOA;AACT;AAEA,SAAS,YAAY,YAAoB;AACvC,QAAMI,KAA4B,CAAC;AACnC,EAAAA,GAAE,YAAe,MAAM,YAAY,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,CAAC,CAAC;AAClD,EAAAA,GAAE,UAAa,KAAIA,GAAE,WAAW,OAAO;AACvC,EAAAA,GAAE,WAAc,MAAM,YAAY,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,CAAC,CAAC;AACjD,EAAAA,GAAE,qBAAwB,IAAIA,GAAE,UAAU,UAAU;AACpD,EAAAA,GAAE,oBAAuB,IAAIA,GAAE,SAAS,UAAU;AAClD,EAAAA,GAAE,cAAiB,IAAIA,GAAE,oBAAoB,UAAU,GAAG;AAC1D,EAAAA,GAAE,SAAY,IAAIA,GAAE,mBAAmBA,GAAE,WAAW;AACpD,EAAAA,GAAE,OAAU,KAAIA,GAAE,mBAAmBA,GAAE,WAAW;AAClD,EAAAA,GAAE,kBAAqB,IAAIA,GAAE,QAAQ,UAAU;AAC/C,EAAAA,GAAE,gBAAmB,IAAIA,GAAE,MAAM,UAAU;AAC3C,QAAM,QAAW,SAAS,CAACA,GAAE,iBAAiBA,GAAE,aAAa,GAAG,CAAC;AACjE,SAAO,KAAKA,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,SAAO;AACT;AAEA,eAAsB,SAAS,YAAoBH,SAAgB;AArDnE;AAuDE,MAAK,CAAC,cAAgB,WAAW,yBAA2B,WAAW,MAAM,WAAW,KAAO,WAAW,MAAM,KAAK,KAAO,WAAW,MAAM,KAAK;AAAI,WAAO,CAAC;AAC9J,QAAME,KAA4B,CAAC;AACnC,EAAAA,GAAE,UAAa,MAAM,eAAe,YAAY,CAAC,WAAW,SAAS,CAAC;AACtE,EAAAA,GAAE,MAAS,IAAIA,GAAE,SAAS,UAAU,KAAK;AACzC,EAAAA,GAAE,aAAgB,IAAIA,GAAE,KAAK,UAAU,IAAI;AAC3C,QAAM,MAAMJ,UAAA,gBAAAA,OAAO,QAAQI,GAAE;AAC7B,MAAI,MAAM,QAAQ,GAAG,KAAK,IAAI,SAAS,GAAG;AACxC,UAAM,SAAS,IAAI,KAAK,CAAC,GAAG,MAAM,EAAE,OAAO,EAAE,IAAI;AACjD,IAAAA,GAAE,YAAe,OAAO,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,CAAC;AACjD,IAAAA,GAAE,YAAe,OAAO,CAAC,OAAO,IAAI,OAAO,EAAE,GAAG,CAAC;AACjD,IAAAA,GAAE,SAAY,OAAO,CAACA,GAAE,WAAWA,GAAE,SAAS,GAAG,CAAC;AAClD,IAAAA,GAAE,QAAW,QAAQA,GAAE,QAAQ,CAAC;AAAA,EAClC,WAAW,MAAM,QAAQ,GAAG,GAAG;AAC7B,IAAAA,GAAE,QAAW,QAAQ,IAAI,EAAE;AAAA,EAC7B,OAAO;AACL,IAAAA,GAAE,QAAW,QAAQ,GAAG;AAAA,EAC1B;AACA,EAAG,QAAQ,GAAG;AACd,EAAAA,GAAE,QAAQ,YAAYA,GAAE,KAAK;AAC7B,EAAAA,GAAE,SAAY,MAAMA,GAAE,OAAO,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,CAAC,CAAC;AAC5C,EAAAA,GAAE,UAAa,QAAQA,GAAE,MAAM;AAC/B,EAAAA,GAAE,SAAY,QAAQA,GAAE,OAAO;AAC/B,EAAAA,GAAE,MAAM,MAAS,MAAM,uBAAuBA,GAAE,OAAOA,GAAE,UAAS,KAAAF,QAAO,KAAK,aAAZ,mBAAsB,gBAAe,KAAK,KAAAA,QAAO,KAAK,aAAZ,mBAAsB,iBAAgB,KAAK,KAAAA,QAAO,KAAK,aAAZ,mBAAsB,kBAAiB,CAAE;AAChM,QAAM,MAAM,MAAME,GAAE,IAAI,MAAM;AAC9B,QAAM,QAA0B,CAAC;AACjC,QAAM,SAAS,MAAMA,GAAE,OAAO,KAAK;AACnC,WAASE,KAAI,GAAGA,KAAI,IAAI,QAAQA,MAAK;AACnC,UAAM,aAAa,OAAO,IAAIA;AAC9B,QAAI,gBAAc,KAAAJ,QAAO,KAAK,aAAZ,mBAAsB,kBAAiB,IAAI;AAC3D,YAAM,IAA4B,CAAC;AACnC,QAAE,OAAU,MAAME,GAAE,OAAO,CAAC,IAAIE,KAAI,CAAC,GAAG,CAAC,GAAG,EAAE,CAAC;AAC/C,QAAE,QAAW,MAAMF,GAAE,OAAO,CAAC,IAAIE,KAAI,iBAAiB,CAAC,GAAG,CAAC,GAAG,EAAE,CAAC;AACjE,QAAE,UAAa,QAAQ,EAAE,KAAK;AAC9B,QAAE,YAAe,QAAQ,EAAE,SAAS,CAAC,gBAAgB,EAAE,CAAC;AACxD,YAAM,SAAS,MAAM,EAAE,KAAK,KAAK;AACjC,YAAM,SAAS;AAAA,QACb,YAAY,CAAC,OAAO,IAAI,OAAO,EAAE;AAAA,QACjC,UAAU,CAAC,OAAO,IAAI,OAAO,EAAE;AAAA,QAC/B,WAAY,MAAM,EAAE,UAAU,MAAM;AAAA,QACpC;AAAA,MACF;AACA,YAAM,YAAiB,oBAAoB,QAAQ,EAAE,WAAW,MAAM,MAAM,KAAK,YAAY,WAAW,MAAM,MAAM,KAAK,SAAS,CAAC;AACnI,YAAM,cAAmB,WAAW,WAAWJ,QAAO,KAAK,YAAY,kBAAkB;AACzF,YAAM,aAAkB,YAAY,WAAW;AAC/C,YAAM,KAAK,UAAU;AACrB,aAAO,KAAK,CAAC,EAAE,QAAQ,CAACG,YAAc,QAAQ,EAAEA,QAAO,CAAC;AAAA,IAC1D;AAAA,EACF;AACA,SAAO,KAAKD,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,SAAO;AACT;;;ACzGA;AAAA;AAAA;AAAA;AAAA;AAEO,IAAM,MAAqB;AAAA,EAChC;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AAEO,IAAM,YAAsC;AAAA,EACjD,WAAW,CAAC,gBAAgB,eAAe;AAAA,EAC3C,MAAM,CAAC,YAAY,SAAS;AAAA,EAC5B,OAAO,CAAC,aAAa,YAAY;AAAA,EACjC,cAAc,CAAC,WAAW,UAAU;AAAA,EACpC,cAAc,CAAC,YAAY,WAAW;AAAA,EACtC,UAAU,CAAC,aAAa,YAAY,UAAU;AAAA,EAC9C,WAAW,CAAC,gBAAgB,SAAS;AAAA,EACrC,cAAc,CAAC,gBAAgB,WAAW;AAAA,EAC1C,cAAc,CAAC,aAAa,WAAW;AAAA,EACvC,UAAU,CAAC,aAAa,UAAU;AAAA,EAClC,eAAe,CAAC,YAAY,WAAW;AAAA,EACvC,eAAe,CAAC,YAAY,WAAW;AAAA,EACvC,eAAe,CAAC,YAAY,WAAW;AAAA,EACvC,gBAAgB,CAAC,iBAAiB,gBAAgB;AAAA,EAClD,eAAe,CAAC,YAAY,WAAW;AAAA,EACvC,eAAe,CAAC,aAAa,YAAY;AAAA,EACzC,WAAW,CAAC,cAAc,aAAa,WAAW;AAAA,EAClD,YAAY,CAAC,iBAAiB,UAAU;AAAA,EACxC,eAAe,CAAC,iBAAiB,YAAY;AAAA,EAC7C,eAAe,CAAC,cAAc,YAAY;AAAA,EAC1C,WAAW,CAAC,cAAc,WAAW;AAAA,EACrC,gBAAgB,CAAC,aAAa,YAAY;AAAA,EAC1C,gBAAgB,CAAC,aAAa,YAAY;AAAA,EAC1C,gBAAgB,CAAC,aAAa,YAAY;AAAA,EAC1C,iBAAiB,CAAC,kBAAkB,iBAAiB;AACvD;;;AC/DA,IAAME,aAAY;AAClB,IAAI;AACJ,IAAM,YAAY;AAClB,IAAM,UAAU,CAAC,GAAG,IAAI,IAAI,IAAI,EAAE;AAElC,eAAsB,gBAAgB;AACpC,QAAMC,WAA2C,CAAC;AAClD,MAAI,UAAU;AACd,SAAO,UAAU,WAAW;AAC1B,QAAI,cAAc;AAClB,QAAI,sBAAsB;AAC1B,WAAO,sBAAsB,QAAQ,UAAU,QAAQ,yBAAyB,QAAQ,UAAU;AAChG,qBAAe;AACf;AAAA,IACF;AACA,UAAM,SAAS,QAAQ;AACvB,UAAM,mBAAmB,KAAK,KAAKD,aAAY,MAAM;AACrD,UAAM,kBAAkB,KAAK,KAAKA,aAAY,MAAM;AACpD,aAAS,IAAI,GAAG,IAAI,kBAAkB,EAAE,GAAG;AACzC,eAAS,IAAI,GAAG,IAAI,iBAAiB,EAAE,GAAG;AACxC,iBAAS,WAAW,GAAG,WAAW,aAAa,EAAE,UAAU;AACzD,UAAAC,SAAQ,KAAK,EAAE,IAAI,IAAI,OAAO,iBAAiB,IAAI,IAAI,OAAO,iBAAiB,CAAC;AAAA,QAClF;AAAA,MACF;AAAA,IACF;AACA,cAAU;AAAA,EACZ;AACA,iBAAe,EAAE,GAAM,SAASA,SAAQ,IAAI,CAAC,MAAM,EAAE,CAAC,CAAC,GAAG,GAAM,SAASA,SAAQ,IAAI,CAAC,MAAM,EAAE,CAAC,CAAC,EAAE;AACpG;;;ACjCO,SAAS,KAAK,WAAyBC,cAA+B,CAAC,GAAG,CAAC,GAAG;AACnF,QAAMC,UAAS,CAAC,UAAU,IAAI,CAAC,OAAO,GAAG,EAAE,GAAG,UAAU,IAAI,CAAC,OAAO,GAAG,EAAE,CAAC;AAC1E,QAAMC,OAAM,CAAC,KAAK,IAAI,GAAGD,QAAO,EAAE,GAAG,KAAK,IAAI,GAAGA,QAAO,EAAE,CAAC;AAC3D,QAAME,OAAM,CAAC,KAAK,IAAI,GAAGF,QAAO,EAAE,GAAG,KAAK,IAAI,GAAGA,QAAO,EAAE,CAAC;AAC3D,QAAM,MAAW,CAACC,KAAI,IAAIA,KAAI,IAAIC,KAAI,KAAKD,KAAI,IAAIC,KAAI,KAAKD,KAAI,EAAE;AAClE,QAAM,SAAc,CAAC,IAAI,KAAKF,YAAW,IAAI,IAAI,KAAKA,YAAW,IAAI,IAAI,KAAKA,YAAW,IAAI,IAAI,KAAKA,YAAW,EAAE;AACnH,SAAO,EAAE,KAAK,OAAO;AACvB;AAEO,SAASI,QAAO,WAAyBJ,cAA+B,CAAC,GAAG,CAAC,GAAG;AACrF,QAAMC,UAAS,CAAC,UAAU,IAAI,CAAC,OAAO,GAAG,EAAE,GAAG,UAAU,IAAI,CAAC,OAAO,GAAG,EAAE,CAAC;AAC1E,QAAMC,OAAM,CAAC,KAAK,IAAI,GAAGD,QAAO,EAAE,GAAG,KAAK,IAAI,GAAGA,QAAO,EAAE,CAAC;AAC3D,QAAME,OAAM,CAAC,KAAK,IAAI,GAAGF,QAAO,EAAE,GAAG,KAAK,IAAI,GAAGA,QAAO,EAAE,CAAC;AAC3D,QAAM,SAAS,EAAEC,KAAI,KAAKC,KAAI,MAAM,IAAID,KAAI,KAAKC,KAAI,MAAM,CAAC;AAC5D,QAAM,OAAO,KAAK,IAAI,OAAO,KAAKD,KAAI,IAAI,OAAO,KAAKA,KAAI,IAAI,CAAC,OAAO,KAAKC,KAAI,IAAI,CAAC,OAAO,KAAKA,KAAI,EAAE;AACtG,QAAM,MAAW,CAAC,KAAK,MAAM,OAAO,KAAK,IAAI,GAAG,KAAK,MAAM,OAAO,KAAK,IAAI,GAAG,KAAK,MAAM,IAAI,IAAI,GAAG,KAAK,MAAM,IAAI,IAAI,CAAC;AACxH,QAAM,SAAc,CAAC,IAAI,KAAKH,YAAW,IAAI,IAAI,KAAKA,YAAW,IAAI,IAAI,KAAKA,YAAW,IAAI,IAAI,KAAKA,YAAW,EAAE;AACnH,SAAO,EAAE,KAAK,OAAO;AACvB;AAEO,SAASK,OAAM,KAAU,WAAmB;AACjD,QAAM,OAAO,CAAC,IAAI,KAAK,WAAW,IAAI,KAAK,SAAS;AACpD,QAAM,SAAc;AAAA,IAClB,IAAI,MAAM,KAAK,KAAK,IAAI,MAAM;AAAA,IAC9B,IAAI,MAAM,KAAK,KAAK,IAAI,MAAM;AAAA,IAC9B,KAAK;AAAA,IACL,KAAK;AAAA,EACP;AACA,SAAO;AACT;;;AChBA,IAAMC,OAAM,EAAE,SAAS,KAAK;AAE5B,IAAM,SAAwE,EAAE,UAAU,MAAM,WAAW,KAAK;AAChH,IAAMC,aAAyE,EAAE,UAAU,CAAC,KAAK,GAAG,GAAG,WAAW,CAAC,KAAK,GAAG,EAAE;AAC7H,IAAIC,WAAU,OAAO;AACrB,IAAM,cAA2D;AAAA,EAC/D,WAAW,CAAC,SAAS,2BAA2B,sBAAsB,YAAY,iBAAiB;AAAA,EACnG,UAAU,CAAC;AACb;AAEA,IAAI,QAA2B;AAC/B,IAAI;AACJ,IAAI,UAA8B,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AACjE,IAAIC,YAAW;AAEf,IAAMC,WAAU,CAAC,MAAO,IAAK,KAAK,IAAI,KAAK,IAAI,CAAC;AAEhD,eAAsB,WAAWC,SAAqC;AACpE,MAAIL,KAAI;AAAS,WAAO,WAAW;AACnC,MAAI,CAAC,OAAO,YAAYK,QAAO,KAAK,eAAeA,QAAO,KAAK,YAAY,gBAAgB,IAAI;AAC7F,WAAO,WAAW,MAAM,UAAUA,QAAO,KAAK,YAAY,YAAY;AACtE,UAAM,SAAS,OAAO,OAAO,OAAO,SAAS,eAAe,SAAS;AACrE,IAAAJ,WAAU,SAAS,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAC9F,IAAAA,WAAU,SAAS,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAAA,EAChG,WAAWI,QAAO,SAAS,OAAO;AAAU,QAAI,iBAAiB,OAAO,SAAS,WAAW;AAC5F,QAAa,cAAc;AAC3B,SAAO,OAAO;AAChB;AAEA,eAAsB,SAASA,SAAqC;AAClE,MAAIL,KAAI;AAAS,WAAO,YAAY;AACpC,MAAI,CAAC,OAAO,WAAW;AACrB,WAAO,YAAY,MAAM,UAAUK,QAAO,KAAK,SAAS;AACxD,UAAM,SAAS,OAAO,OAAO,OAAO,UAAU,eAAe,SAAS;AACtE,IAAAJ,WAAU,UAAU,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAC/F,IAAAA,WAAU,UAAU,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAAA,EACjG,WAAWI,QAAO;AAAO,QAAI,iBAAiB,OAAO,UAAU,WAAW;AAC1E,SAAO,OAAO;AAChB;AAQA,eAAe,aAAaC,QAAeC,OAA+B;AACxE,QAAMC,KAA4B,CAAC;AACnC,MAAI,CAACF,OAAM,SAAS,CAACA,OAAM,MAAM,MAAM,CAACA,OAAM,MAAM;AAAI,WAAOA;AAC/D,MAAI;AACJ,MAAI,SAAS;AACX,IAAAE,GAAE,UAAa,MAAM,cAAcF,QAAO,CAAC,OAAO,GAAG,CAAC,CAAC,GAAG,CAACA,OAAM,MAAM,IAAIA,OAAM,MAAM,EAAE,CAAC;AAAA,EAC5F;AACA,MAAIA,OAAM,MAAM,OAAOA,OAAM,MAAM,IAAI;AACrC,UAAM,SAA2B;AAAA,MAC/BA,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI;AAAA,MACtFA,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI;AAAA,IACxF;AACA,UAAM,QAA0B;AAAA,MAC9BA,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI;AAAA,MACtFA,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI;AAAA,IACxF;AACA,cAAU;AAAA,MACR,CAAC,GAAG,CAAC;AAAA,MACL;AAAA,MACA;AAAA,MACA,CAAC,GAAG,CAAC;AAAA,IACP;AACA,IAAAE,GAAE,MAAS,IAAIA,GAAE,WAAWF,QAAO,OAAO;AAC1C,IAAAE,GAAE,SAAY,MAAM,eAAeA,GAAE,KAAK,CAACD,OAAMA,KAAI,CAAC;AACtD,YAAW,IAAIC,GAAE,QAAQ,UAAU,KAAK;AAAA,EAC1C,WAAWF,OAAM,MAAM,OAAOC,OAAM;AAClC,IAAAC,GAAE,SAAY,MAAM,eAAeA,GAAE,WAAWF,QAAO,CAACC,OAAMA,KAAI,CAAC;AACnE,YAAW,IAAIC,GAAE,QAAQ,UAAU,KAAK;AAAA,EAC1C,OAAO;AACL,YAAW,IAAIA,GAAE,WAAWF,QAAO,UAAU,KAAK;AAAA,EACpD;AACA,SAAO,KAAKE,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,SAAO;AACT;AAEA,SAAS,iBAAiB,WAAgCC,aAAmD;AAC3G,aAAWC,QAAO,WAAW;AAC3B,IAAAA,KAAI,WAAW;AAAA,MACb,KAAK,MAAMA,KAAI,SAAS,MAAMD,YAAW,KAAK,QAAQ,GAAG,KAAK,QAAQ,GAAG,MAAMA,YAAW,KAAK,QAAQ,GAAG,EAAE;AAAA,MAC5G,KAAK,MAAMC,KAAI,SAAS,MAAMD,YAAW,KAAK,QAAQ,GAAG,KAAK,QAAQ,GAAG,MAAMA,YAAW,KAAK,QAAQ,GAAG,EAAE;AAAA,MAC5GC,KAAI,SAAS;AAAA,IACf;AACA,IAAAA,KAAI,cAAc,CAACA,KAAI,SAAS,KAAKD,YAAW,IAAIC,KAAI,SAAS,KAAKD,YAAW,IAAI,IAAKC,KAAI,SAAS,MAAiBD,YAAW,KAAKA,YAAW,GAAG;AAAA,EACxJ;AACA,MAAI,SAAS;AACX,eAAWC,QAAO,WAAW;AAC3B,MAAAA,KAAI,cAAc;AAAA,QAChBA,KAAI,YAAY,KAAK,QAAQ;AAAA,QAC7BA,KAAI,YAAY,KAAK,QAAQ;AAAA,QAC7BA,KAAI,YAAY;AAAA,MAClB;AACA,MAAAA,KAAI,WAAW;AAAA,QACb,KAAK,MAAMA,KAAI,YAAY,KAAKD,YAAW,EAAE;AAAA,QAC7C,KAAK,MAAMC,KAAI,YAAY,KAAKD,YAAW,EAAE;AAAA,QAC7CC,KAAI,YAAY;AAAA,MAClB;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AAEA,eAAe,aAAa,WAAgC;AAE1D,QAAM,WAAW,UAAU,KAAK,CAAC,MAAM,EAAE,SAAS,UAAU;AAC5D,QAAM,YAAY,UAAU,KAAK,CAAC,MAAM,EAAE,SAAS,WAAW;AAC9D,QAAM,YAAY,UAAU,KAAK,CAAC,MAAM,EAAE,SAAS,WAAW;AAC9D,WAAS,SAAS,OAAO,UAAU,SAAS,MAAM,MAAM,UAAU,SAAS,MAAM,MAAM;AACvF,QAAM,YAAY,UAAU,KAAK,CAAC,MAAM,EAAE,SAAS,WAAW;AAC9D,QAAM,aAAa,UAAU,KAAK,CAAC,MAAM,EAAE,SAAS,YAAY;AAChE,QAAM,aAAa,UAAU,KAAK,CAAC,MAAM,EAAE,SAAS,YAAY;AAChE,YAAU,SAAS,OAAO,WAAW,SAAS,MAAM,MAAM,WAAW,SAAS,MAAM,MAAM;AAC5F;AAEA,eAAe,gBAAgBL,QAAeM,SAAgBF,aAA0D;AAtIxH;AA8IE,QAAMF,KAA4B,CAAC;AACnC,GAACA,GAAE,IAAqBA,GAAE,cAA+BA,GAAE,SAAyBA,GAAE,OAAwBA,GAAE,QAAiB,KAAI,YAAO,cAAP,mBAAkB,QAAQF,QAAO,YAAY;AAClL,QAAM,aAAa,MAAME,GAAE,SAAS,KAAK,GAAG;AAC5C,QAAM,SAAS,MAAMA,GAAE,GAAG,KAAK;AAC/B,QAAM,YAAY,MAAMA,GAAE,MAAM,KAAK;AACrC,SAAO,KAAKA,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,QAAM,oBAAyC,CAAC;AAChD,QAAM,QAAQ;AACd,WAASI,KAAI,GAAGA,KAAI,OAAO,SAAS,OAAOA,MAAK;AAC9C,UAAM,QAAQC,SAAQ,OAAO,QAAQD,KAAI,EAAE;AAC3C,UAAM,WAAWC,SAAQ,OAAO,QAAQD,KAAI,EAAE;AAC9C,UAAM,WAAW,KAAK,MAAM,MAAM,QAAQ,WAAW,SAAS,IAAI;AAClE,UAAM,cAAqB,CAAC,OAAO,QAAQA,KAAI,KAAKE,WAAU,UAAU,IAAI,OAAO,QAAQF,KAAI,KAAKE,WAAU,UAAU,IAAI,OAAO,QAAQF,KAAI,KAAK,CAAC;AACrJ,UAAM,WAAkB,CAAC,KAAK,MAAMH,YAAW,KAAK,YAAY,EAAE,GAAG,KAAK,MAAMA,YAAW,KAAK,YAAY,EAAE,GAAG,YAAY,EAAY;AACzI,UAAMM,YAAkB,CAAC,UAAU,QAAQH,KAAI,IAAI,UAAU,QAAQA,KAAI,IAAI,UAAU,QAAQA,KAAI,KAAK,CAAC;AACzG,sBAAkB,KAAK,EAAE,MAAa,IAAIA,KAAoB,aAAa,UAAU,UAAAG,WAAU,OAAO,SAAS,CAAC;AAAA,EAClH;AACA,MAAI,aAAaJ,QAAO,KAAK,iBAAiB;AAAI,WAAO;AACzD,eAAa,iBAAiB;AAC9B,QAAM,YAAiC,iBAAiB,mBAAmBF,WAAU;AACrF,QAAM,OAAO,UAAU,IAAI,CAAC,MAAM,EAAE,QAAQ;AAC5C,QAAM,QAAY,KAAK,MAAM,CAACA,YAAW,IAAIA,YAAW,EAAE,CAAC;AAC3D,QAAMO,eAAiD,CAAC;AACxD,aAAW,CAAC,MAAM,OAAO,KAAK,OAAO,QAAe,SAAS,GAAG;AAC9D,UAAM,KAAqB,CAAC;AAC5B,aAASJ,KAAI,GAAGA,KAAI,QAAQ,SAAS,GAAGA,MAAK;AAC3C,YAAM,MAAM,UAAU,KAAK,CAACF,SAAQA,KAAI,SAAS,QAAQE,GAAE;AAC3D,YAAM,MAAM,UAAU,KAAK,CAACF,SAAQA,KAAI,SAAS,QAAQE,KAAI,EAAE;AAC/D,UAAI,OAAO;AAAK,WAAG,KAAK,CAAC,IAAI,UAAU,IAAI,QAAQ,CAAC;AAAA,IACtD;AACA,IAAAI,aAAY,QAAQ;AAAA,EACtB;AACA,QAAMC,QAAO,EAAE,IAAI,GAAG,OAAO,KAAK,MAAM,MAAM,SAAS,IAAI,KAAK,KAAK,MAAM,KAAK,QAAQ,MAAM,QAAQ,WAAW,aAAAD,aAAY;AAC7H,SAAOC;AACT;AAgCA,eAAsBC,SAAQb,QAAeM,SAAuC;AAClF,QAAMF,cAA+B,CAACJ,OAAM,MAAM,MAAM,GAAGA,OAAM,MAAM,MAAM,CAAC;AAC9E,QAAM,YAAYM,QAAO,KAAK,YAAY,KAAM,IAAI,IAAIQ;AACxD,QAAM,YAAYC,YAAWT,QAAO,KAAK,cAAc;AACvD,MAAIA,QAAO,eAAe,YAAY,aAAa,UAAU,MAAM;AACjE,IAAAS;AAAA,EACF,OAAO;AACL,UAAMb,KAA4B,CAAC;AAOnC,IAAAA,GAAE,YAAY,MAAM,aAAaF,QAAO,GAAG;AAC3C,YAAQ,MAAM,gBAAgBE,GAAE,WAAWI,SAAQF,WAAU;AAe7D,WAAO,KAAKF,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,IAAAW,YAAW,IAAI;AACf,IAAAC,WAAU;AAAA,EACZ;AACA,SAAO,QAAQ,CAAC,KAAK,IAAI,CAAC;AAC5B;;;AChPO,IAAM,SAAS;AAAA,EACpB,EAAE,OAAO,GAAG,OAAO,SAAS;AAAA,EAC5B,EAAE,OAAO,GAAG,OAAO,UAAU;AAAA,EAC7B,EAAE,OAAO,GAAG,OAAO,MAAM;AAAA,EACzB,EAAE,OAAO,GAAG,OAAO,aAAa;AAAA,EAChC,EAAE,OAAO,GAAG,OAAO,WAAW;AAAA,EAC9B,EAAE,OAAO,GAAG,OAAO,MAAM;AAAA,EACzB,EAAE,OAAO,GAAG,OAAO,QAAQ;AAAA,EAC3B,EAAE,OAAO,GAAG,OAAO,QAAQ;AAAA,EAC3B,EAAE,OAAO,GAAG,OAAO,OAAO;AAAA,EAC1B,EAAE,OAAO,IAAI,OAAO,gBAAgB;AAAA,EACpC,EAAE,OAAO,IAAI,OAAO,eAAe;AAAA,EACnC,EAAE,OAAO,IAAI,OAAO,YAAY;AAAA,EAChC,EAAE,OAAO,IAAI,OAAO,gBAAgB;AAAA,EACpC,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,MAAM;AAAA,EAC1B,EAAE,OAAO,IAAI,OAAO,MAAM;AAAA,EAC1B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,MAAM;AAAA,EAC1B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,UAAU;AAAA,EAC9B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,UAAU;AAAA,EAC9B,EAAE,OAAO,IAAI,OAAO,MAAM;AAAA,EAC1B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,UAAU;AAAA,EAC9B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,YAAY;AAAA,EAChC,EAAE,OAAO,IAAI,OAAO,cAAc;AAAA,EAClC,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,eAAe;AAAA,EACnC,EAAE,OAAO,IAAI,OAAO,iBAAiB;AAAA,EACrC,EAAE,OAAO,IAAI,OAAO,aAAa;AAAA,EACjC,EAAE,OAAO,IAAI,OAAO,YAAY;AAAA,EAChC,EAAE,OAAO,IAAI,OAAO,gBAAgB;AAAA,EACpC,EAAE,OAAO,IAAI,OAAO,SAAS;AAAA,EAC7B,EAAE,OAAO,IAAI,OAAO,aAAa;AAAA,EACjC,EAAE,OAAO,IAAI,OAAO,MAAM;AAAA,EAC1B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,SAAS;AAAA,EAC7B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,SAAS;AAAA,EAC7B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,SAAS;AAAA,EAC7B,EAAE,OAAO,IAAI,OAAO,UAAU;AAAA,EAC9B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,eAAe;AAAA,EACnC,EAAE,OAAO,IAAI,OAAO,MAAM;AAAA,EAC1B,EAAE,OAAO,IAAI,OAAO,eAAe;AAAA,EACnC,EAAE,OAAO,IAAI,OAAO,SAAS;AAAA,EAC7B,EAAE,OAAO,IAAI,OAAO,KAAK;AAAA,EACzB,EAAE,OAAO,IAAI,OAAO,SAAS;AAAA,EAC7B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,SAAS;AAAA,EAC7B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,aAAa;AAAA,EACjC,EAAE,OAAO,IAAI,OAAO,YAAY;AAAA,EAChC,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,UAAU;AAAA,EAC9B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,eAAe;AAAA,EACnC,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,QAAQ;AAAA,EAC5B,EAAE,OAAO,IAAI,OAAO,OAAO;AAAA,EAC3B,EAAE,OAAO,IAAI,OAAO,WAAW;AAAA,EAC/B,EAAE,OAAO,IAAI,OAAO,aAAa;AAAA,EACjC,EAAE,OAAO,IAAI,OAAO,aAAa;AAAA,EACjC,EAAE,OAAO,IAAI,OAAO,aAAa;AACnC;;;ACrEA,IAAIC;AACJ,IAAIC,aAAY;AAChB,IAAIC,QAAuB,CAAC;AAC5B,IAAIC,YAAW;AACf,IAAIC,WAAU,OAAO;AAErB,eAAsBC,MAAKC,SAAqC;AAC9D,MAAIC,KAAI;AAAS,IAAAP,SAAQ;AACzB,MAAI,CAACA,QAAO;AAEV,IAAAA,SAAQ,MAAM,UAAUM,QAAO,OAAO,SAAS;AAC/C,UAAM,SAAS,OAAO,OAAON,OAAM,eAAe,SAAS;AAC3D,IAAAC,aAAY,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAAA,EACpF,WAAWK,QAAO;AAAO,QAAI,iBAAiBN,OAAM,WAAW;AAC/D,SAAOA;AACT;AAEA,eAAeQ,SAAQ,KAAoB,aAA+BF,SAAgB;AACxF,MAAI,CAAC;AAAK,WAAO,CAAC;AAClB,QAAMG,KAA4B,CAAC;AACnC,QAAM,UAA+B,CAAC;AACtC,QAAM,aAAa,MAAM,IAAI,MAAM;AACnC,EAAAA,GAAE,UAAa,QAAQ,GAAG;AAC1B,QAAM,MAAS,MAAMA,GAAE,SAAS,GAAG,CAAC;AACpC,EAAAA,GAAE,QAAW,MAAM,CAAC,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,IAAI,EAAE,GAAG,CAAC;AACtD,EAAAA,GAAE,QAAW,QAAQA,GAAE,KAAK;AAC5B,EAAAA,GAAE,SAAY,QAAQ,IAAI,EAAE;AAC5B,EAAAA,GAAE,UAAa,QAAQ,IAAI,EAAE;AAC7B,EAAG,QAAQ,CAAC,KAAK,GAAG,GAAG,CAAC;AACxB,EAAAA,GAAE,MAAM,MAAS,MAAM,uBAAuBA,GAAE,OAAOA,GAAE,QAAQH,QAAO,OAAO,aAAaA,QAAO,OAAO,cAAeA,QAAO,OAAO,iBAAiB,CAAE;AAC1J,QAAM,MAAM,MAAMG,GAAE,IAAI,KAAK;AAC7B,MAAIC,KAAI;AACR,aAAW,MAAM,MAAM,KAAK,GAAG,GAAG;AAChC,UAAM,QAAQ,KAAK,MAAM,MAAM,WAAW,GAAG,IAAI,EAAE,IAAI;AACvD,UAAM,WAAW,WAAW,GAAG,IAAI;AACnC,UAAM,QAAQ,OAAO,UAAU;AAC/B,UAAM,CAAC,GAAG,CAAC,IAAI;AAAA,MACb,WAAW,GAAG,IAAI,KAAKT;AAAA,MACvB,WAAW,GAAG,IAAI,KAAKA;AAAA,IACzB;AACA,UAAM,SAAc;AAAA,MAClB;AAAA,MACA;AAAA,MACA,WAAW,GAAG,IAAI,KAAKA,aAAY;AAAA,MACnC,WAAW,GAAG,IAAI,KAAKA,aAAY;AAAA,IACrC;AACA,UAAM,MAAW;AAAA,MACf,KAAK,MAAM,OAAO,KAAK,YAAY,EAAE;AAAA,MACrC,KAAK,MAAM,OAAO,KAAK,YAAY,EAAE;AAAA,MACrC,KAAK,MAAM,OAAO,KAAK,YAAY,EAAE;AAAA,MACrC,KAAK,MAAM,OAAO,KAAK,YAAY,EAAE;AAAA,IACvC;AACA,YAAQ,KAAK,EAAE,IAAIS,MAAK,OAAO,OAAO,UAAU,OAAO,KAAK,OAAO,CAAC;AAAA,EACtE;AACA,SAAO,KAAKD,EAAC,EAAE,QAAQ,CAACE,YAAc,QAAQF,GAAEE,QAAO,CAAC;AACxD,SAAO;AACT;AAEA,eAAsBC,SAAQC,QAAeP,SAAyC;AACpF,QAAM,YAAYA,QAAO,OAAO,YAAY,KAAM,IAAI,IAAIH;AAC1D,QAAM,YAAYC,YAAWE,QAAO,OAAO,cAAc;AACzD,MAAIA,QAAO,eAAe,YAAY,aAAcJ,MAAK,SAAS,GAAI;AACpE,IAAAE;AACA,WAAOF;AAAA,EACT;AACA,EAAAE,WAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,UAAMU,cAAa,CAACD,OAAM,MAAM,MAAM,GAAGA,OAAM,MAAM,MAAM,CAAC;AAC5D,UAAM,SAAY,MAAM,eAAeA,QAAO,CAACZ,YAAWA,UAAS,CAAC;AACpE,UAAM,UAAUK,QAAO,OAAO,UAAUN,UAAA,gBAAAA,OAAO,QAAQ,QAAQ,CAAC,oBAAoB,KAAe;AACnG,IAAAG,YAAW,IAAI;AACf,IAAG,QAAQ,MAAM;AAEjB,UAAM,MAAM,MAAMK,SAAQ,SAASM,aAAYR,OAAM;AACrD,IAAAJ,QAAO;AAEP,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;AC7FA;AAAA;AAAA,mBAAAa;AAAA,EAAA,WAAAC;AAAA;AAAO,IAAMA,OAAqB;AAAA,EAChC;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AAEO,IAAMD,aAAsC;AAAA,EACjD,SAAS,CAAC,WAAW,YAAY,WAAW;AAAA,EAC5C,UAAU,CAAC,YAAY,aAAa,YAAY;AAAA,EAChD,OAAO,CAAC,gBAAgB,iBAAiB,YAAY,WAAW,cAAc;AAAA,EAC9E,SAAS,CAAC,gBAAgB,aAAa,WAAW;AAAA,EAClD,UAAU,CAAC,iBAAiB,cAAc,YAAY;AAAA,EACtD,MAAM,CAAC;AACT;;;ACVA,IAAIE;AACJ,IAAIC,YAAW;AACf,IAAMC,SAAoB,EAAE,IAAI,GAAG,WAAW,CAAC,GAAG,KAAK,CAAC,GAAG,GAAG,GAAG,CAAC,GAAG,QAAQ,CAAC,GAAG,GAAG,GAAG,CAAC,GAAG,OAAO,GAAG,aAAa,CAAC,EAAuC;AAM1J,IAAIC,WAAU,OAAO;AAErB,eAAsBC,MAAKC,SAAqC;AAC9D,MAAIC,KAAI;AAAS,IAAAN,SAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,SAAQ,MAAM,UAAUK,QAAO,KAAK,SAAS;AAAA,WAChDA,QAAO;AAAO,QAAI,iBAAiBL,OAAM,WAAW;AAC7D,SAAOA;AACT;AAGA,eAAe,MAAM,QAAQ,UAAU;AACrC,QAAM,CAAC,OAAO,MAAM,IAAI,OAAO;AAC/B,QAAM,WAAc,QAAQ,QAAQ,CAAC,SAAS,KAAK,CAAC;AACpD,QAAMO,OAAS,IAAI,UAAU,CAAC;AAC9B,QAAM,YAAY,MAAMA,KAAI,KAAK,GAAG;AACpC,EAAG,QAAQ,CAAC,UAAUA,IAAG,CAAC;AAC1B,MAAI,WAAW,UAAU;AACvB,UAAM,cAAiB,OAAO,UAAU,CAAC;AACzC,UAAMC,OAAS,IAAI,aAAa,KAAK;AACrC,UAAM,KAAK,MAAMA,KAAI,KAAK,GAAG;AAC7B,UAAMC,OAAS,IAAI,aAAgB,OAAO,OAAO,OAAO,CAAC;AACzD,UAAM,KAAK,MAAMA,KAAI,KAAK,GAAG;AAC7B,IAAG,QAAQ,CAACD,MAAKC,IAAG,CAAC;AACrB,WAAO,CAAC,GAAG,GAAG,QAAQ;AAAA,EACxB;AACA,SAAO,CAAC,GAAG,GAAG,QAAQ;AACxB;AAEA,eAAsBC,SAAQC,QAAeN,SAAuC;AAClF,QAAM,YAAYA,QAAO,KAAK,YAAY,KAAM,IAAI,IAAIJ;AACxD,QAAM,YAAYE,YAAWE,QAAO,KAAK,cAAc;AACvD,MAAIA,QAAO,eAAe,YAAY,aAAa,OAAO,KAAKH,OAAM,SAAS,EAAE,SAAS,GAAG;AAC1F,IAAAC;AACA,WAAO,CAACD,MAAK;AAAA,EACf;AACA,EAAAC,WAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AA5DxC;AA6DI,UAAMS,UAAY,KAAK,MAAM;AAC3B,UAAI,EAACZ,UAAA,gBAAAA,OAAO,OAAO,GAAG;AAAO,eAAO;AACpC,YAAM,SAAY,MAAM,eAAeW,QAAO,CAACX,OAAM,OAAO,GAAG,MAAM,IAAIA,OAAM,OAAO,GAAG,MAAM,EAAE,GAAG,KAAK;AACzG,YAAMa,WAAa,IAAI,QAAQ,UAAU,GAAG;AAC5C,YAAMC,QAAU,IAAID,UAAS,UAAU,GAAG;AAC1C,aAAOC;AAAA,IACT,CAAC;AAED,QAAI;AACJ,QAAIT,QAAO,KAAK;AAAS,aAAOL,UAAA,gBAAAA,OAAO,QAAQY;AAC/C,IAAAX,YAAW,IAAI;AACf,IAAG,QAAQW,OAAM;AAEjB,QAAI,MAAM;AACR,MAAAV,OAAM,UAAU,SAAS;AACzB,YAAMa,WAAU,KAAK,QAAQ;AAC7B,MAAG,QAAQ,IAAI;AAEf,YAAMC,SAAQD,SAAQ,QAAQ,CAAC;AAC/B,MAAG,QAAQA,QAAO;AAElB,eAAS,KAAK,GAAG,KAAKC,OAAM,QAAQ,MAAM;AAExC,cAAM,CAACC,IAAGC,IAAG,SAAS,IAAI,MAAM,MAAMF,OAAM,KAAKX,QAAO,KAAK,aAAa;AAC1E,YAAI,eAAa,KAAAA,QAAO,SAAP,mBAAa,kBAAiB,IAAI;AACjD,UAAAH,OAAM,UAAU,KAAK;AAAA,YACnB,OAAO,KAAK,MAAM,MAAM,SAAS,IAAI;AAAA,YACrC,MAAaiB,KAAI;AAAA,YACjB,aAAa;AAAA,cAEXF,KAAIjB,OAAM,OAAO,GAAG,MAAM;AAAA,cAAIkB,KAAIlB,OAAM,OAAO,GAAG,MAAM;AAAA,YAC1D;AAAA,YACA,UAAU;AAAA,cAER,KAAK,MAAMW,OAAM,MAAM,KAAKM,KAAIjB,OAAM,OAAO,GAAG,MAAM,EAAE;AAAA,cAAG,KAAK,MAAMW,OAAM,MAAM,KAAKO,KAAIlB,OAAM,OAAO,GAAG,MAAM,EAAE;AAAA,YACrH;AAAA,UACF,CAAC;AAAA,QACH;AAAA,MACF;AACA,MAAAgB,OAAM,QAAQ,CAACI,OAAS,QAAQA,EAAC,CAAC;AAAA,IACpC;AACA,IAAAlB,OAAM,QAAQA,OAAM,UAAU,OAAO,CAAC,MAAM,SAAU,KAAK,QAAQ,OAAO,KAAK,QAAQ,MAAO,CAAC;AAC/F,UAAM,IAAIA,OAAM,UAAU,IAAI,CAAC,MAAM,EAAE,SAAS,EAAE;AAClD,UAAM,IAAIA,OAAM,UAAU,IAAI,CAAC,MAAM,EAAE,SAAS,EAAE;AAClD,IAAAA,OAAM,MAAM;AAAA,MACV,KAAK,IAAI,GAAG,CAAC;AAAA,MACb,KAAK,IAAI,GAAG,CAAC;AAAA,MACb,KAAK,IAAI,GAAG,CAAC,IAAI,KAAK,IAAI,GAAG,CAAC;AAAA,MAC9B,KAAK,IAAI,GAAG,CAAC,IAAI,KAAK,IAAI,GAAG,CAAC;AAAA,IAChC;AACA,UAAM,OAAOA,OAAM,UAAU,IAAI,CAAC,MAAM,EAAE,YAAY,EAAE;AACxD,UAAM,OAAOA,OAAM,UAAU,IAAI,CAAC,MAAM,EAAE,YAAY,EAAE;AACxD,IAAAA,OAAM,SAAS;AAAA,MACb,KAAK,IAAI,GAAG,IAAI;AAAA,MAChB,KAAK,IAAI,GAAG,IAAI;AAAA,MAChB,KAAK,IAAI,GAAG,IAAI,IAAI,KAAK,IAAI,GAAG,IAAI;AAAA,MACpC,KAAK,IAAI,GAAG,IAAI,IAAI,KAAK,IAAI,GAAG,IAAI;AAAA,IACtC;AACA,eAAW,CAAC,MAAM,OAAO,KAAK,OAAO,QAAemB,UAAS,GAAG;AAC9D,YAAM,KAAqB,CAAC;AAC5B,eAASC,KAAI,GAAGA,KAAI,QAAQ,SAAS,GAAGA,MAAK;AAC3C,cAAM,MAAMpB,OAAM,UAAU,KAAK,CAACiB,SAAQA,KAAI,SAAS,QAAQG,GAAE;AACjE,cAAM,MAAMpB,OAAM,UAAU,KAAK,CAACiB,SAAQA,KAAI,SAAS,QAAQG,KAAI,EAAE;AACrE,YAAI,OAAO,OAAO,IAAI,SAASjB,QAAO,KAAK,iBAAiB,MAAM,IAAI,SAASA,QAAO,KAAK,iBAAiB;AAAI,aAAG,KAAK,CAAC,IAAI,UAAU,IAAI,QAAQ,CAAC;AAAA,MACtJ;AACA,MAAAH,OAAM,YAAY,QAAQ;AAAA,IAC5B;AACA,YAAQ,CAACA,MAAK,CAAC;AAAA,EACjB,CAAC;AACH;;;ACnHA,IAAM,cAAc,CAAC,SAAS,WAAW,QAAQ,SAAS,OAAO,YAAY,SAAS;AACtF,IAAIqB;AACJ,IAAMC,QAA0D,CAAC;AACjE,IAAIC,aAAY;AAChB,IAAIC,YAAW;AACf,IAAIC,WAAU,OAAO;AAErB,eAAsBC,MAAKC,SAAqC;AAtBhE;AAuBE,MAAIC,KAAI;AAAS,IAAAP,SAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,SAAQ,MAAM,WAAU,KAAAM,QAAO,KAAK,YAAZ,mBAAqB,SAAS;AAAA,WACzDA,QAAO;AAAO,QAAI,iBAAiBN,OAAM,WAAW;AAC7D,SAAOA;AACT;AAEA,eAAsBQ,SAAQC,QAAeH,SAAgB,KAAaI,QAAoE;AA7B9I;AA8BE,MAAI,CAACV;AAAO,WAAO,CAAC;AACpB,QAAM,YAAYI,cAAW,KAAAE,QAAO,KAAK,YAAZ,mBAAqB,eAAc;AAChE,QAAM,cAAY,KAAAA,QAAO,KAAK,YAAZ,mBAAqB,aAAY,KAAM,IAAI,IAAIH;AACjE,MAAIG,QAAO,eAAe,YAAY,aAAcJ,eAAcQ,UAAUT,MAAK,QAASA,MAAK,KAAK,SAAS,GAAI;AAC/G,IAAAG;AACA,WAAOH,MAAK;AAAA,EACd;AACA,EAAAG,WAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AAtCxC,QAAAO,KAAAC;AAuCI,UAAM,MAAkD,CAAC;AACzD,SAAID,MAAAL,QAAO,KAAK,YAAZ,gBAAAK,IAAqB,SAAS;AAChC,YAAME,KAA4B,CAAC;AACnC,YAAMC,eAAYd,UAAA,gBAAAA,OAAO,OAAO,GAAG,SAAQA,OAAM,OAAO,GAAG,MAAM,KAAK;AACtE,MAAAa,GAAE,SAAY,MAAM,eAAeJ,QAAO,CAACK,aAAWA,WAAS,GAAG,KAAK;AASvE,MAAAD,GAAE,WAAc,IAAIA,GAAE,QAAQ,UAAU,GAAG;AAC3C,MAAAA,GAAE,YAAe,KAAIA,GAAE,UAAU,GAAG,IAAI;AACxC,MAAAA,GAAE,eAAkB,IAAIA,GAAE,WAAW,UAAU,IAAI;AACnD,MAAAA,GAAE,eAAkB,IAAIA,GAAE,cAAc,UAAU,GAAG;AACrD,MAAAA,GAAE,UAAUb,UAAA,gBAAAA,OAAO,QAAQa,GAAE;AAC7B,MAAAV,YAAW,IAAI;AACf,YAAM,OAAO,MAAMU,GAAE,QAAQ,KAAK;AAClC,eAASE,KAAI,GAAGA,KAAI,KAAK,QAAQA,MAAK;AACpC,YAAI,KAAKA,SAAMH,MAAAN,QAAO,KAAK,YAAZ,gBAAAM,IAAqB,kBAAiB;AAAI,cAAI,KAAK,EAAE,OAAO,KAAK,IAAI,MAAM,KAAK,MAAM,MAAM,KAAKG,GAAE,IAAI,GAAG,GAAG,SAAS,YAAYA,IAAc,CAAC;AAAA,MAClK;AACA,UAAI,KAAK,CAAC,GAAG,MAAM,EAAE,QAAQ,EAAE,KAAK;AACpC,aAAO,KAAKF,EAAC,EAAE,QAAQ,CAACG,YAAc,QAAQH,GAAEG,QAAO,CAAC;AAAA,IAC1D;AACA,IAAAf,MAAK,OAAO;AACZ,IAAAC,aAAYQ;AACZ,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;ACtDA,IAAIO;AACJ,IAAMC,QAAwB,CAAC;AAC/B,IAAIC,aAAY;AAChB,IAAIC,YAAW;AACf,IAAIC,WAAU,OAAO;AAErB,eAAsBC,MAAKC,SAAqC;AAC9D,MAAIC,KAAI;AAAS,IAAAP,UAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,UAAQ,MAAM,UAAUM,QAAO,KAAK,iBAAiB,SAAS;AAAA,WACjEA,QAAO;AAAO,QAAI,iBAAiBN,QAAM,WAAW;AAC7D,SAAOA;AACT;AAoBA,eAAsBQ,SAAQC,QAAeH,SAAgB,KAAKI,QAA0B;AA9C5F;AA+CE,MAAI,CAACV;AAAO,WAAO,CAAC;AACpB,QAAM,YAAYI,cAAW,KAAAE,QAAO,KAAK,iBAAZ,mBAA0B,eAAc;AACrE,QAAM,cAAY,KAAAA,QAAO,KAAK,iBAAZ,mBAA0B,aAAY,KAAM,IAAI,IAAIH;AACtE,MAAIG,QAAO,eAAe,YAAY,aAAcJ,eAAcQ,UAAUT,MAAK,MAAM;AACrF,IAAAG;AACA,WAAOH,MAAK;AAAA,EACd;AACA,SAAO,IAAI,QAAQ,OAAO,YAAY;AAtDxC,QAAAU;AAuDI,QAAI,OAAsB,CAAC;AAC3B,UAAIA,MAAAL,QAAO,KAAK,iBAAZ,gBAAAK,IAA0B,aAAWX,WAAA,gBAAAA,QAAO,OAAO,GAAG,QAAO;AAC/D,YAAMY,KAA4B,CAAC;AACnC,MAAAA,GAAE,OAAU,MAAM,eAAeH,QAAO,CAACT,QAAM,OAAO,GAAG,MAAM,IAAIA,QAAM,OAAO,GAAG,MAAM,EAAE,GAAG,KAAK;AAInG,MAAAY,GAAE,OAAOZ,WAAA,gBAAAA,QAAO,QAAQY,GAAE;AAa1B,YAAM,SAAS,MAAMA,GAAE,KAAK,KAAK;AACjC,aAAO,MAAM,KAAK,MAAM;AAAA,IAC1B;AACA,IAAAX,MAAK,OAAO;AACZ,IAAAC,aAAYQ;AACZ,IAAAP,YAAW,IAAI;AACf,YAAQ,IAAI;AAAA,EACd,CAAC;AACH;;;ACzEA,IAAIU;AACJ,IAAIC,aAAY;AAEhB,IAAM,cAAc;AAEpB,IAAM,cAAqB,gBAAgB;AAC3C,IAAM,eAAsB,gBAAgB;AAE5C,IAAM,eAAe;AAAA,EACnB,YAAY,CAAC,YAAY,IAAI,YAAY,YAAY,SAAS,EAAE;AAAA,EAChE,aAAa,CAAC,aAAa,IAAI,aAAa,aAAa,SAAS,EAAE;AACtE;AAEA,IAAM,gBAAgB;AAAA,EACpB,aAAa;AAAA,EACb,aAAa;AAAA,EACb,OAAO;AAAA,EACP,gBAAgB;AAClB;AAEA,eAAsBC,OAAKC,SAAqC;AA9BhE;AA+BE,MAAIC,KAAI;AAAS,IAAAJ,UAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,UAAQ,MAAM,WAAU,KAAAG,QAAO,KAAK,SAAZ,mBAAkB,SAAS;AAAA,WACtDA,QAAO;AAAO,QAAI,iBAAiBH,QAAM,WAAW;AAC7D,EAAAC,aAAYD,QAAM,OAAO,GAAG,QAAQA,QAAM,OAAO,GAAG,MAAM,KAAK;AAC/D,MAAIC,eAAc;AAAI,IAAAA,aAAY;AAClC,SAAOD;AACT;AAGO,SAAS,kBAAkB,WAAW,WAAW,QAAQ,MAAM;AACpE,WAASK,KAAI,GAAGA,KAAW,YAAY,QAAQA,MAAK;AAClD,UAAM,EAAE,KAAK,QAAQ,IAAW,YAAYA;AAC5C,UAAM,kBAAyB,gBAAgB,GAAG,SAAS;AAC3D,QAAI,CAAC,QAAQ,KAAK,SAAS,GAAG,GAAG;AAC/B,eAAS,IAAI,GAAG,IAAI,QAAQ,QAAQ,KAAK;AACvC,cAAMC,SAAQ,QAAQ;AACtB,kBAAU,gBAAgB,MAAM;AAAA,UAC9B,UAAUA,QAAO;AAAA,UACjB,UAAUA,QAAO;AAAA,WAChB,UAAUA,QAAO,KAAK,UAAU,gBAAgB,IAAI,MAAM;AAAA,QAC7D;AAAA,MACF;AAAA,IACF;AAAA,EACF;AACF;AAEO,IAAM,mCAAmC,CAAC,cAAc;AAC7D,QAAM,WAAW,UAAU,aAAa,WAAW,IAAI;AACvD,QAAM,YAAY,UAAU,aAAa,YAAY,IAAI;AACzD,SAAO,WAAW;AACpB;AAGO,IAAM,YAAY,CAAC,WAAWC,OAAM,qBAAqB,qBAAqB,UAAU,OAAO,UAAU;AAC9G,QAAM,MAAW,YAAiB,WAAgB,8BAA8B,CAAC,UAAU,sBAAsB,UAAU,oBAAoB,CAAC,GAAG,WAAW,CAAC;AAC/J,QAAM,UAAe,WAAW,GAAG;AACnC,MAAI,OAAU,MAAM,cAAcA,OAAM,CAAC;AAAA,IACvC,IAAI,WAAW,KAAK;AAAA,IACpB,IAAI,WAAW,KAAK;AAAA,IAAU,IAAI,SAAS,KAAK;AAAA,IAChD,IAAI,SAAS,KAAK;AAAA,EACpB,CAAC,GAAG,CAAC,CAAC,GAAG,CAACN,YAAWA,UAAS,CAAC;AAC/B,MAAI,QAAQG,KAAI,QAAQ,SAAS,eAAe,GAAG;AACjD,UAAM,UAAa,MAAM,cAAc,IAAI;AAC3C,IAAG,QAAQ,IAAI;AACf,WAAO;AAAA,EACT;AACA,SAAO,EAAE,KAAK,SAAS,KAAK;AAC9B;AAGO,IAAM,eAAe,CAAC,SAAS,QAAQ,YAAY,OAAO,UAAU;AACzE,QAAM,eAA6B,CAAC;AACpC,WAASC,KAAI,GAAGA,KAAI,cAAc,gBAAgBA,MAAK;AACrD,UAAM,IAAI,QAAQA,KAAI;AACtB,UAAM,IAAI,QAAQA,KAAI,IAAI;AAC1B,UAAM,IAAI,QAAQA,KAAI,IAAI;AAC1B,iBAAa,KAAK;AAAA,OACf,OAAQ,IAAK,IAAIJ,aAAe,IAAIA,cAAc,WAAW,KAAK,OAAO,WAAW;AAAA,MACpF,IAAIA,aAAa,WAAW,KAAK,OAAO,WAAW;AAAA,MAAI;AAAA,IAC1D,CAAC;AAAA,EACH;AACA,SAAO,EAAE,WAAW,cAAc,MAAM,aAAa,MAAM,cAAc,KAAK,EAAE;AAClF;AAGO,IAAM,wBAAwB,CAAC,WAAW,YAAY,cAAc;AACzE,QAAM,eAAe,UAAiB,gBAAgB,GAAG,sBAAsB,cAAc,cAAc;AAC3G,QAAM,eAAe,UAAiB,gBAAgB,GAAG,sBAAsB,cAAc,cAAc;AAC3G,QAAM,YAAY,eAAe,gBAAgB;AAEjD,SAAO,WAAW,IAAI,CAAC,OAAOI,OAAM;AAClC,QAAI,IAAI;AACR,QAAIA,OAAM,GAAG;AACX,UAAI;AAAA,IACN,WAAWA,OAAM,GAAG;AAClB,UAAI;AAAA,IACN;AACA,WAAO,CAAC,MAAM,IAAI,MAAM,IAAI,CAAC;AAAA,EAC/B,CAAC;AACH;AAEA,eAAsB,YAAY,WAAWE,OAAMJ,SAAQ,UAAU;AACnE,MAAI,CAACH,SAAO;AACV,QAAIG,QAAO;AAAO,UAAI,6DAA6D;AACnF,WAAO;AAAA,EACT;AACA,QAAM,EAAE,KAAK,YAAY,SAAS,gBAAgB,MAAM,YAAY,IAAI,UAAU,WAAWI,OAAM,aAAa,WAAW,IAAI,aAAa,WAAW,IAAI,UAAU,IAAI;AACzK,QAAM,EAAE,KAAK,aAAa,SAAS,iBAAiB,MAAM,aAAa,IAAI,UAAU,WAAWA,OAAM,aAAa,YAAY,IAAI,aAAa,YAAY,IAAI,UAAU,IAAI;AAC9K,QAAM,WAAc,OAAO,CAAC,aAAa,YAAY,CAAC;AACtD,EAAG,QAAQ,WAAW;AACtB,EAAG,QAAQ,YAAY;AACvB,QAAM,iBAAiBP,QAAM,QAAQ,QAAQ;AAC7C,EAAG,QAAQ,QAAQ;AACnB,QAAM,qBAAqB,MAAM,eAAe,KAAK;AACrD,EAAG,QAAQ,cAAc;AACzB,QAAM,cAAc,mBAAmB,MAAM,GAAG,cAAc,iBAAiB,CAAC;AAChF,QAAM,EAAE,WAAW,kBAAkB,MAAM,kBAAkB,IAAI,aAAa,aAAa,YAAY,gBAAgB,IAAI;AAC3H,QAAM,eAAe,mBAAmB,MAAM,cAAc,iBAAiB,CAAC;AAC9E,QAAM,EAAE,WAAW,mBAAmB,MAAM,mBAAmB,IAAI,aAAa,cAAc,aAAa,iBAAiB,KAAK;AACjI,QAAM,gCAAgC,iCAAiC,SAAS;AAChF,MAAI,KAAK,IAAI,6BAA6B,IAAI,IAAI;AAChD,sBAAkB,WAAW,kBAAkB,QAAQ,IAAI;AAC3D,sBAAkB,WAAW,mBAAmB,SAAS,IAAI;AAAA,EAE/D,WAAW,gCAAgC,GAAG;AAC5C,sBAAkB,WAAW,kBAAkB,QAAQ,CAAC,aAAa,WAAW,CAAC;AAAA,EACnF,OAAO;AACL,sBAAkB,WAAW,mBAAmB,SAAS,CAAC,aAAa,WAAW,CAAC;AAAA,EACrF;AACA,QAAM,yBAAyB,sBAAsB,WAAW,mBAAmB,MAAM;AACzF,QAAM,0BAA0B,sBAAsB,WAAW,oBAAoB,OAAO;AAC5F,QAAM,YAAY,UAAU,OAAO,sBAAsB,EAAE,OAAO,uBAAuB;AACzF,SAAO;AACT;;;AC3IA,IAAM,mBAA8B;AAAA,EACl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uBAAkC,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAEvO,IAAM,2BAAsC,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAE3I,IAAM,wBAAmC,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAExF,IAAM,wBAAmC,CAAC,CAAC,IAAI,CAAC,GAAG,CAAC,GAAG,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,IAAI,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAElO,IAAM,4BAAuC,CAAC,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,GAAG,GAAG,CAAC,KAAK,EAAE,GAAG,CAAC,IAAI,GAAG,CAAC;AAE/H,IAAM,yBAAoC,CAAC,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,GAAG,CAAC,KAAK,GAAG,CAAC;AAEzF,IAAM,wBAAmC;AAAA,EACvC,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EACpN,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAAA,EAAG,CAAC,IAAI,GAAG;AAAA,EAAG,CAAC,KAAK,EAAE;AAC5M;AAmJA,SAASQ,sBAAqB,aAAwB;AACpD,QAAM,UAAU,YAAY,IAAI,CAAC,eAAe,WAAW,EAAE;AAC7D,UAAQ,KAAK,YAAY,YAAY,SAAS,GAAG,EAAE;AACnD,SAAO;AACT;AAEO,IAAM,2CAA2C;AAAA,EACtD,MAAMA,sBAAqB,gBAAgB;AAAA,EAC3C,SAASA,sBAAqB,oBAAoB;AAAA,EAClD,aAAaA,sBAAqB,wBAAwB;AAAA,EAC1D,UAAUA,sBAAqB,qBAAqB;AAAA,EACpD,UAAUA,sBAAqB,qBAAqB;AAAA,EACpD,cAAcA,sBAAqB,yBAAyB;AAAA,EAC5D,WAAWA,sBAAqB,sBAAsB;AAAA,EACtD,UAAUA,sBAAqB,qBAAqB;AACtD;AAEA,IAAM,kBAA2C,OAAO,QAAQ,wCAAwC,EACrG,IAAI,CAAC,CAAC,OAAO,OAAO,MAAM,QAAQ,IAAI,CAACC,WAAU,CAACA,QAAO,KAAK,CAAqB,CAAC,EACpF,KAAK;AAED,IAAM,gCAAgC,IAAI,IAAI,eAAe;AAQ7D,IAAM,mCAAmC;AAAA,EAC9C;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9C;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACnC;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC7C;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACpC;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC7C;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACpC;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC7C;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AACtC;AAEO,IAAM,uCAAuC;AAAA,EAClD;AAAA,EAAI;AAAA,EAAG;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACrC;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9B;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EACnC;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EACzB;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACvC;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9B;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAI;AAAA,EACrB;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACxC;AAAA,EAAK;AAAA,EAAI;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AAAA,EAAK;AAAA,EAAI;AACjC;AAEO,IAAM,wCAAwC;AAAA,EACnD;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACxC;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9B;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACxC;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9B;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACxC;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAC9B;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACzB;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EACxC;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AAAA,EAAK;AACrC;;;ACvOA,eAAsB,QAAQ,WAAW,SAAmB;AAC1D,QAAMC,KAAkC;AAAA,IAGtC,MAAM,MAAM,QAAQ,OAAO,CAACC,OAAMA,GAAE,SAAS,GAAG,EAAE,GAAG,KAAK;AAAA,IAC1D,OAAO,MAAM,QAAQ,OAAO,CAACA,OAAMA,GAAE,SAAS,EAAE,EAAE,GAAG,KAAK;AAAA,IAC1D,MAAM,MAAM,QAAQ,OAAO,CAACA,OAAMA,GAAE,SAAS,GAAG,EAAE,GAAG,KAAK;AAAA,IAC1D,OAAO,MAAM,QAAQ,OAAO,CAACA,OAAMA,GAAE,SAAS,EAAE,EAAE,GAAG,KAAK;AAAA,IAC1D,MAAM,MAAM,QAAQ,OAAO,CAACA,OAAMA,GAAE,SAAS,GAAG,EAAE,GAAG,KAAK;AAAA,EAC5D;AAGA,QAAM,aAAuB,qCAAqC,OAAO,CAAC,MAAM,SAAS,QAAQ,UAAU,MAAM,IAAI,CAAC,IAAc,qCAAqC;AACzK,WAASC,KAAI,GAAGA,KAAIF,GAAE,MAAM,SAAS,GAAGE;AAAK,cAAU,KAAK,CAACF,GAAE,MAAM,IAAIE,KAAI,IAAIF,GAAE,MAAM,IAAIE,KAAI,IAAI,UAAU,CAAC;AAChH,QAAM,aAAuB,sCAAsC,OAAO,CAAC,MAAM,SAAS,QAAQ,UAAU,MAAM,IAAI,CAAC,IAAc,sCAAsC;AAC3K,WAASA,KAAI,GAAGA,KAAIF,GAAE,MAAM,SAAS,GAAGE;AAAK,cAAU,KAAK,CAACF,GAAE,MAAM,IAAIE,KAAI,IAAIF,GAAE,MAAM,IAAIE,KAAI,IAAI,UAAU,CAAC;AAGhH,WAASA,KAAI,GAAGA,KAAIF,GAAE,KAAK,SAAS,GAAGE;AAAK,cAAoB,qCAAqCA,OAAM,CAACF,GAAE,KAAK,IAAIE,KAAI,IAAIF,GAAE,KAAK,IAAIE,KAAI,IAAI,UAAoB,qCAAqCA,KAAI,EAAE;AACjN,WAASA,KAAI,GAAGA,KAAIF,GAAE,KAAK,SAAS,GAAGE;AAAK,cAAoB,sCAAsCA,OAAM,CAACF,GAAE,KAAK,IAAIE,KAAI,IAAIF,GAAE,KAAK,IAAIE,KAAI,IAAI,UAAoB,sCAAsCA,KAAI,EAAE;AAGnN,WAASA,KAAI,GAAGA,KAAIF,GAAE,KAAK,SAAS,GAAGE;AAAK,cAAoB,iCAAiCA,OAAM,CAACF,GAAE,KAAK,IAAIE,KAAI,IAAIF,GAAE,KAAK,IAAIE,KAAI,IAAI,UAAoB,iCAAiCA,KAAI,EAAE;AAEzM,SAAO;AACT;;;ACHA,IAAMC,SAAQ;AAAA,EACZ,OAAO,CAAC;AAAA,EACR,SAAS,OAAO;AAAA,EAChB,WAAW;AACb;AAEA,IAAIC,UAA2B;AAC/B,IAAIC,aAAY;AAEhB,eAAsBC,UAAQC,QAAeC,SAAuC;AAlCpF;AAoCE,QAAM,cAAY,KAAAA,QAAO,KAAK,aAAZ,mBAAsB,aAAY,KAAM,IAAI,IAAIL,OAAM;AACxE,QAAM,YAAYA,OAAM,aAAW,KAAAK,QAAO,KAAK,aAAZ,mBAAsB,eAAc;AACvE,MAAI,CAACA,QAAO,eAAe,CAAC,YAAY,CAAC,aAAaL,OAAM,MAAM,WAAW,GAAG;AAC9E,IAAAA,OAAM,QAAQ,MAAgB,SAASI,QAAOC,OAAM;AACpD,IAAAL,OAAM,YAAY,IAAI;AACtB,IAAAA,OAAM,UAAU;AAAA,EAClB,OAAO;AACL,IAAAA,OAAM;AAAA,EACR;AACA,QAAM,QAA2B,CAAC;AAClC,QAAM,WAA6B,CAAC;AACpC,MAAI,KAAK;AACT,WAASM,KAAI,GAAGA,KAAIN,OAAM,MAAM,QAAQM,MAAK;AAC3C,UAAM,MAAMN,OAAM,MAAMM;AACxB,QAAI,QAAQ;AACZ,QAAI;AACJ,UAAMC,QAAmB;AAAA,MACvB,IAAI;AAAA,MACJ,MAAM,CAAC;AAAA,MACP,SAAS,CAAC;AAAA,MACV,KAAK,CAAC,GAAG,GAAG,GAAG,CAAC;AAAA,MAChB,QAAQ,CAAC,GAAG,GAAG,GAAG,CAAC;AAAA,MACnB,OAAO;AAAA,MACP,UAAU;AAAA,MACV,WAAW;AAAA,MAGX,aAAa,CAAC;AAAA,IAChB;AAGA,KAAC,OAAO,gBAAgBA,MAAK,MAAM,IAAS,qBAAoB,KAAAF,QAAO,KAAK,aAAZ,mBAAsB,UAAU,KAAKD,UAAO,KAAAC,QAAO,KAAK,SAAZ,mBAAkB,WAAUH,aAAsB,KAAK,CAAC;AACpK,SAAI,KAAAG,WAAA,gBAAAA,QAAQ,WAAR,mBAAgB,cAAc;AAChC,YAAM,YAAY,MAAM,sBAAsBE,MAAK,MAAgB;AACnE,MAAG,QAAQA,MAAK,MAAM;AACtB,MAAAA,MAAK,SAAS;AAAA,IAChB;AACA,IAAAA,MAAK,WAAW,KAAK,MAAM,MAAM,IAAI,UAAU,IAAI;AACnD,QAAI,GAAC,KAAAF,QAAO,KAAK,SAAZ,mBAAkB,UAAS;AAC9B,MAAAE,MAAK,MAAW,SAAS,KAAKH,MAAK;AACnC,MAAAG,MAAK,SAAc,UAAU,KAAKH,MAAK;AACvC,MAAAG,MAAK,QAAQA,MAAK;AAClB,MAAAA,MAAK,OAAO,IAAI,UAAU,IAAI,CAAC,OAAO;AAAA,SAClC,IAAI,WAAW,KAAK,IAAI,SAAS,MAAO,KAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM,GAAG,KAAe,KAAK;AAAA,SAC5G,IAAI,WAAW,KAAK,IAAI,SAAS,MAAO,KAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM,GAAG,KAAe,KAAK;AAAA,MAChH,CAAC;AACD,MAAAA,MAAK,UAAUA,MAAK,KAAK,IAAI,CAAC,OAAO,CAAC,GAAG,MAAMH,OAAM,MAAM,MAAM,IAAI,GAAG,MAAMA,OAAM,MAAM,MAAM,KAAK,GAAG,MAAM,KAAKF,UAAS,CAAC;AAC7H,iBAAW,OAAO,OAAO,KAAY,kBAAkB,GAAG;AACxD,QAAAK,MAAK,YAAY,OAAO,CAACA,MAAK,KAAY,mBAAmB,KAAe;AAAA,MAC9E;AAAA,IACF,WAAW,CAACN,SAAO;AACjB,UAAII,QAAO;AAAO,YAAI,wDAAwD;AAAA,IAChF,OAAO;AACL,YAAM,UAAUJ,QAAM,QAAQM,MAAK,MAAgB;AACnD,YAAM,cAAc,QAAQ,KAAK,CAACC,OAAMA,GAAE,MAAMA,GAAE,MAAM,SAAS,OAAO,CAAC;AACzE,YAAM,iBAAiB,MAAM,YAAY,KAAK;AAC9C,MAAAD,MAAK,YAAY,KAAK,MAAM,MAAM,eAAe,EAAE,IAAI;AAEvD,UAAIA,MAAK,eAAa,KAAAF,QAAO,KAAK,aAAZ,mBAAsB,kBAAiB,IAAI;AAC/D,YAAI,aAAaE,MAAK;AACtB,aAAI,KAAAF,QAAO,KAAK,SAAZ,mBAAkB,aAAa;AACjC,UAAAE,MAAK,MAAW,SAAS,KAAKH,MAAK;AACnC,UAAAG,MAAK,SAAc,UAAU,KAAKH,MAAK;AACvC,UAAAG,MAAK,QAAQA,MAAK;AAClB,UAAAA,MAAK,OAAO,IAAI,UAAU,IAAI,CAAC,OAAO;AAAA,aAClC,IAAI,WAAW,KAAK,IAAI,SAAS,MAAO,KAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM,GAAG,KAAe,KAAK;AAAA,aAC5G,IAAI,WAAW,KAAK,IAAI,SAAS,MAAO,KAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM,GAAG,KAAe,KAAK;AAAA,UAChH,CAAC;AACD,UAAAA,MAAK,UAAUA,MAAK,KAAK,IAAI,CAAC,OAAO,CAAC,GAAG,MAAMH,OAAM,MAAM,MAAM,IAAI,GAAG,MAAMA,OAAM,MAAM,MAAM,KAAK,GAAG,MAAM,KAAKF,UAAS,CAAC;AAC7H,qBAAW,OAAO,OAAO,KAAY,kBAAkB,GAAG;AACxD,YAAAK,MAAK,YAAY,OAAO,CAACA,MAAK,KAAY,mBAAmB,KAAe;AAAA,UAC9E;AAAA,QACF;AAAA,MACF,OAAO;AACL,cAAM,QAAQ,QAAQ,KAAK,CAACC,OAAMA,GAAE,MAAMA,GAAE,MAAM,SAAS,OAAO,IAAI;AACtE,cAAM,iBAAoB,QAAQ,OAAO,CAAC,IAAI,CAAC,CAAC;AAChD,YAAI,YAAY,MAAM,eAAe,MAAM;AAC3C,QAAG,QAAQ,cAAc;AACzB,aAAI,KAAAH,QAAO,KAAK,cAAZ,mBAAuB,SAAS;AAClC,sBAAY,MAAgB,QAAQ,WAAW,OAAO;AAAA,QACxD,YAAW,KAAAA,QAAO,KAAK,SAAZ,mBAAkB,SAAS;AACpC,sBAAY,MAAW,YAAY,WAAWE,MAAK,QAAQF,SAAQH,UAAS;AAAA,QAC9E;AACA,QAAAK,MAAK,OAAY,mBAAmB,WAAW,KAAK,OAAO,gBAAgBL,UAAS;AACpF,QAAAK,MAAK,UAAUA,MAAK,KAAK,IAAI,CAAC,OAAO,CAAC,GAAG,MAAMH,OAAM,MAAM,MAAM,IAAI,GAAG,MAAMA,OAAM,MAAM,MAAM,KAAK,GAAG,MAAM,KAAKF,UAAS,CAAC;AAC7H,mBAAW,OAAO,OAAO,KAAY,eAAe;AAAG,UAAAK,MAAK,YAAY,OAAc,gBAAgB,KAAK,IAAI,CAACE,WAAUF,MAAK,KAAKE,OAAM;AAC1I,QAAAF,MAAK,QAAQA,MAAK;AAClB,cAAM,gBAAgB,EAAE,GAAQ,iBAAiBA,MAAK,MAAM,GAAG,GAAG,YAAY,IAAI,YAAY,WAAW,IAAI,UAAU;AACvH,QAAAA,MAAK,MAAW,SAAS,eAAeH,MAAK;AAC7C,QAAAG,MAAK,SAAc,UAAU,eAAeH,MAAK;AAQjD,iBAAS,KAAK,aAAa;AAAA,MAC7B;AACA,MAAG,QAAQ,OAAO;AAAA,IACpB;AACA,QAAIG,MAAK,WAAS,KAAAF,QAAO,KAAK,aAAZ,mBAAsB,kBAAiB;AAAI,YAAM,KAAKE,KAAI;AAAA;AACvE,MAAG,QAAQA,MAAK,MAAM;AAAA,EAC7B;AACA,EAAAP,OAAM,QAAQ;AACd,SAAO;AACT;AAEA,eAAsBU,OAAKL,SAAqC;AAhJhE;AAiJE,MAAIM,KAAI;AAAS,IAAAV,UAAQ;AAEzB,QAAI,WAAAI,WAAA,gBAAAA,QAAQ,SAAR,mBAAc,cAAd,mBAAyB,aAAWJ,WAAA,gBAAAA,QAAO,YAAW;AAExD,QAAI,OAAO,OAAK,KAAAA,WAAA,gBAAAA,QAAO,cAAP,mBAAkB,YAAW,CAAC,CAAC,EAAE,SAAS;AAAG,MAAAA,UAAQ;AAAA,EACvE;AACA,MAAI,CAACA,SAAO;AACV,SAAI,KAAAI,QAAO,KAAK,cAAZ,mBAAuB;AAAS,MAAAJ,UAAQ,MAAM,WAAU,KAAAI,QAAO,KAAK,cAAZ,mBAAuB,SAAS;AAAA;AACvF,MAAAJ,UAAQ,MAAM,WAAU,KAAAI,QAAO,KAAK,SAAZ,mBAAkB,SAAS;AAAA,EAC1D,WAAWA,QAAO,OAAO;AACvB,QAAI,iBAAiBJ,QAAM,WAAW;AAAA,EACxC;AACA,EAAAC,aAAYD,QAAM,OAAO,GAAG,QAAQA,QAAM,OAAO,GAAG,MAAM,KAAK;AAC/D,SAAOA;AACT;AAEO,IAAM,gBAAuB;AAC7B,IAAM,QAAe;;;AC9I5B,IAAIW;AACJ,IAAMC,QAKD,CAAC;AAEN,IAAIC,aAAW;AACf,IAAIC,aAAY;AAChB,IAAIC,YAAU,OAAO;AAErB,eAAsBC,OAAKC,SAAqC;AAhChE;AAiCE,MAAIC,KAAI;AAAS,IAAAP,UAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,UAAQ,MAAM,WAAU,KAAAM,QAAO,KAAK,gBAAZ,mBAAyB,SAAS;AAAA,WAC7DA,QAAO;AAAO,QAAI,iBAAiBN,QAAM,WAAW;AAC7D,SAAOA;AACT;AAEO,SAAS,QAAQQ,QAAe;AACrC,QAAMC,UAAUD,OAAM,SAASA,OAAM,UAAUA;AAC/C,MAAI,EAACR,WAAA,gBAAAA,QAAO,OAAO,GAAG;AAAO,WAAOS;AACpC,QAAM,OAAU,MAAM,eAAeA,SAAQ,CAACT,QAAM,OAAO,GAAG,MAAM,IAAIA,QAAM,OAAO,GAAG,MAAM,EAAE,GAAG,KAAK;AACxG,QAAMU,QAAU,IAAI,MAAM,UAAU,KAAK;AACzC,EAAG,QAAQ,IAAI;AACf,SAAOA;AAkBT;AAEA,eAAsBC,UAAQC,QAAeN,SAAgB,KAAaO,QAAiC;AAjE3G;AAkEE,MAAI,CAACb;AAAO,WAAO,EAAE,KAAK,GAAG,QAAQ,WAAW,aAAa,GAAG,YAAY,CAAC,EAAE;AAC/E,QAAM,YAAYI,eAAW,KAAAE,QAAO,KAAK,gBAAZ,mBAAyB,eAAc;AACpE,QAAM,cAAY,KAAAA,QAAO,KAAK,gBAAZ,mBAAyB,aAAY,KAAM,IAAI,IAAIJ;AACrE,MAAII,QAAO,eAAe,aAAa,YAAaH,eAAcU,YAAU,KAAAZ,MAAK,SAAL,mBAAW,UAAQ,KAAAA,MAAK,SAAL,mBAAW,OAAM,GAAI;AAClH,IAAAG;AACA,WAAOH,MAAK;AAAA,EACd;AACA,EAAAG,YAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AA1ExC,QAAAU,KAAAC;AA2EI,UAAM,MAAM;AAAA,MACV,KAAa;AAAA,MACb,QAAgB;AAAA,MAChB,aAAqB;AAAA,MACrB,YAAsB,CAAC;AAAA,IACzB;AAEA,SAAID,MAAAR,QAAO,KAAK,gBAAZ,gBAAAQ,IAAyB,SAAS;AACpC,YAAM,WAAW,QAAQF,MAAK;AAC9B,YAAM,OAAOZ,WAAA,gBAAAA,QAAO,QAAQ;AAC5B,MAAAE,aAAW,IAAI;AACf,MAAG,QAAQ,QAAQ;AACnB,YAAM,UAAU,MAAM,KAAK,KAAK,CAACc,OAAMA,GAAE,MAAM,OAAO,CAAC;AACvD,YAAMC,UAAS,MAAM,QAAQ,KAAK;AAClC,YAAM,aAAa,KAAK,MAAM,MAAM,KAAK,IAAKA,QAAO,KAAK,GAAI,CAAC,IAAI;AACnE,UAAI,gBAAcF,MAAAT,QAAO,KAAK,gBAAZ,gBAAAS,IAAyB,kBAAiB,IAAI;AAC9D,YAAI,SAASE,QAAO,MAAM,MAAM,WAAW;AAC3C,YAAI,cAAc,KAAK,IAAI,MAAM,UAAU;AAAA,MAC7C;AACA,YAAMC,UAAY,OAAO,KAAK,KAAK,CAACF,OAAMA,GAAE,MAAM,OAAO,GAAG,GAAG,CAAC;AAChE,YAAMG,QAAO,MAAMD,QAAO,KAAK,GAAG;AAClC,MAAG,QAAQA,OAAM;AACjB,YAAM,OAAO,KAAK,KAAK,CAACF,OAAMA,GAAE,MAAM,OAAO,GAAG;AAChD,YAAMI,OAAM,MAAM,KAAK,KAAK;AAC5B,UAAI,MAAM,KAAK,MAAMA,KAAID,OAAM,KAAKC,KAAID,OAAM,KAAK,KAAKA,OAAM,MAAMC,KAAID,OAAM,KAAK,KAAKA,OAAM,MAAMC,KAAID,OAAM,EAAE,IAAI;AAEpH,YAAM,OAAO,KAAK,KAAK,CAACH,OAAMA,GAAE,MAAM,OAAO,IAAI;AAGjD,YAAM,aAAa,OAAO,MAAM,KAAK,KAAK,IAAc,CAAC;AACzD,UAAI,aAAa,MAAM,KAAK,UAAU;AACtC,WAAK,QAAQ,CAACA,OAAS,QAAQA,EAAC,CAAC;AAAA,IACnC;AACA,IAAAf,MAAK,OAAO;AACZ,IAAAE,aAAYU;AACZ,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;AC7GO,SAASQ,YAAW,KAAK;AAC9B,SAAO;AAAA,IACL,KAAK,IAAI,IAAI,SAAS,KAAK,IAAI,WAAW,EAAE;AAAA,IAC5C,KAAK,IAAI,IAAI,SAAS,KAAK,IAAI,WAAW,EAAE;AAAA,EAC9C;AACF;AAEO,SAASC,cAAa,KAAK;AAChC,SAAO;AAAA,IACL,IAAI,WAAW,MAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM;AAAA,IAC5D,IAAI,WAAW,MAAM,IAAI,SAAS,KAAK,IAAI,WAAW,MAAM;AAAA,EAC9D;AACF;AAEO,SAAS,yBAAyB,KAAKC,QAAO,UAAU;AAC7D,QAAM,IAAIA,OAAM,MAAM;AACtB,QAAM,IAAIA,OAAM,MAAM;AACtB,QAAM,QAAQ,CAAC;AAAA,IACb,IAAI,WAAW,KAAK;AAAA,IACpB,IAAI,WAAW,KAAK;AAAA,IACpB,IAAI,SAAS,KAAK;AAAA,IAClB,IAAI,SAAS,KAAK;AAAA,EACpB,CAAC;AACD,SAAU,MAAM,cAAcA,QAAO,OAAO,CAAC,CAAC,GAAG,QAAQ;AAC3D;AAEO,SAASC,qBAAoB,KAAK,QAAQ;AAC/C,QAAM,aAAa,CAAC,IAAI,WAAW,KAAK,OAAO,IAAI,IAAI,WAAW,KAAK,OAAO,EAAE;AAChF,QAAM,WAAW,CAAC,IAAI,SAAS,KAAK,OAAO,IAAI,IAAI,SAAS,KAAK,OAAO,EAAE;AAC1E,QAAM,gBAAgB,IAAI,cAAc,IAAI,CAAC,UAAU;AACrD,UAAM,cAAc,CAAC,MAAM,KAAK,OAAO,IAAI,MAAM,KAAK,OAAO,EAAE;AAC/D,WAAO;AAAA,EACT,CAAC;AACD,SAAO,EAAE,YAAY,UAAU,eAAe,YAAY,IAAI,WAAW;AAC3E;AAEO,SAASC,YAAW,KAAK,SAAS,KAAK;AAC5C,QAAM,SAASH,cAAa,GAAG;AAC/B,QAAMI,QAAOL,YAAW,GAAG;AAC3B,QAAM,cAAc,CAAC,SAASK,MAAK,KAAK,GAAG,SAASA,MAAK,KAAK,CAAC;AAC/D,QAAM,aAAa,CAAC,OAAO,KAAK,YAAY,IAAI,OAAO,KAAK,YAAY,EAAE;AAC1E,QAAM,WAAW,CAAC,OAAO,KAAK,YAAY,IAAI,OAAO,KAAK,YAAY,EAAE;AACxE,SAAO,EAAE,YAAY,UAAU,eAAe,IAAI,cAAc;AAClE;AAEO,SAASC,aAAY,KAAK;AAC/B,QAAM,UAAUL,cAAa,GAAG;AAChC,QAAMI,QAAOL,YAAW,GAAG;AAC3B,QAAM,UAAU,KAAK,IAAI,GAAGK,KAAI;AAChC,QAAM,WAAW,UAAU;AAC3B,QAAM,aAAa,CAAC,QAAQ,KAAK,UAAU,QAAQ,KAAK,QAAQ;AAChE,QAAM,WAAW,CAAC,QAAQ,KAAK,UAAU,QAAQ,KAAK,QAAQ;AAC9D,SAAO,EAAE,YAAY,UAAU,eAAe,IAAI,cAAc;AAClE;AAaO,SAASE,kBAAiB,OAAO;AACtC,SAAO,QAAQ,IAAI,KAAK,KAAK,KAAK,OAAO,QAAQ,KAAK,OAAO,IAAI,KAAK,GAAG;AAC3E;AAEO,SAASC,iBAAgB,QAAQ,QAAQ;AAC9C,QAAM,UAAU,KAAK,KAAK,IAAI,KAAK,MAAM,EAAE,OAAO,KAAK,OAAO,KAAK,OAAO,KAAK,OAAO,EAAE;AACxF,SAAOD,kBAAiB,OAAO;AACjC;AAEO,IAAME,0BAAyB,CAAC,GAAG,MAAM,CAAC,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC;AAEzE,SAASC,KAAI,IAAI,IAAI;AAC1B,MAAI,UAAU;AACd,WAASC,KAAI,GAAGA,KAAI,GAAG,QAAQA,MAAK;AAClC,eAAW,GAAGA,MAAK,GAAGA;AAAA,EACxB;AACA,SAAO;AACT;AAEO,SAASC,oBAAmB,KAAK,aAAa;AACnD,QAAM,SAAwB,CAAC;AAC/B,WAASD,KAAI,GAAGA,KAAI,IAAI,QAAQA,MAAK;AACnC,WAAO,KAAK,IAAIA,IAAG,YAAY;AAAA,EACjC;AACA,SAAO;AACT;AAEO,SAASE,2BAA0B,MAAM,MAAM;AACpD,QAAM,UAA2B,CAAC;AAClC,QAAMC,QAAO,KAAK;AAClB,WAAS,MAAM,GAAG,MAAMA,OAAM,OAAO;AACnC,YAAQ,KAAK,CAAC,CAAC;AACf,aAAS,MAAM,GAAG,MAAMA,OAAM,OAAO;AACnC,cAAQ,KAAK,KAAKJ,KAAI,KAAK,MAAME,oBAAmB,MAAM,GAAG,CAAC,CAAC;AAAA,IACjE;AAAA,EACF;AACA,SAAO;AACT;AAEO,SAASG,qBAAoB,UAAU,QAAQ;AACpD,QAAM,OAAO,KAAK,IAAI,QAAQ;AAC9B,QAAM,OAAO,KAAK,IAAI,QAAQ;AAC9B,QAAM,iBAAiB,CAAC,CAAC,MAAM,CAAC,MAAM,CAAC,GAAG,CAAC,MAAM,MAAM,CAAC,GAAG,CAAC,GAAG,GAAG,CAAC,CAAC;AACpE,QAAM,oBAAoBN,wBAAuB,OAAO,IAAI,OAAO,EAAE;AACrE,QAAM,2BAA2BI,2BAA0B,mBAAmB,cAAc;AAC5F,QAAM,4BAA4BJ,wBAAuB,CAAC,OAAO,IAAI,CAAC,OAAO,EAAE;AAC/E,SAAOI,2BAA0B,0BAA0B,yBAAyB;AACtF;AAEO,SAASG,uBAAsB,QAAQ;AAC5C,QAAM,oBAAoB,CAAC,CAAC,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE,GAAG,CAAC,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE,CAAC;AACrF,QAAM,uBAAuB,CAAC,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE;AACxD,QAAM,sBAAsB;AAAA,IAC1B,CAACN,KAAI,kBAAkB,IAAI,oBAAoB;AAAA,IAC/C,CAACA,KAAI,kBAAkB,IAAI,oBAAoB;AAAA,EACjD;AACA,SAAO;AAAA,IACL,kBAAkB,GAAG,OAAO,oBAAoB,EAAE;AAAA,IAClD,kBAAkB,GAAG,OAAO,oBAAoB,EAAE;AAAA,IAClD,CAAC,GAAG,GAAG,CAAC;AAAA,EACV;AACF;AAEO,SAASO,aAAY,uBAAuB,gBAAgB;AACjE,SAAO;AAAA,IACLP,KAAI,uBAAuB,eAAe,EAAE;AAAA,IAC5CA,KAAI,uBAAuB,eAAe,EAAE;AAAA,EAC9C;AACF;;;ACpIO,IAAMQ,WAAU;AAAA,EACrB,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,UAAU,GAAG,SAAS;AAAA,EAC3B,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,SAAS,GAAG,QAAQ;AAAA,EACzB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AAAA,EACvB,EAAE,GAAG,QAAQ,GAAG,OAAO;AACzB;;;AC13FO,IAAM,eAAN,MAAmB;AAAA,EAQxB,YAAYC,SAAO;AAPnB;AACA;AACA;AACA;AACA;AACA;AAGE,SAAK,QAAQA;AACb,SAAK,UAAkBC,SAAQ,IAAI,CAAC,WAAW,CAAC,OAAO,GAAG,OAAO,CAAC,CAAC;AACnE,SAAK,gBAAmB,SAAS,KAAK,OAAO;AAC7C,SAAK,YAAa,KAAK,SAAS,KAAK,MAAM,UAAU,KAAK,MAAM,OAAO,GAAG,QAAS,KAAK,MAAM,OAAO,GAAG,MAAM,KAAK;AACnH,SAAK,kBAAqB,SAAS,CAAC,KAAK,WAAW,KAAK,SAAS,CAAC;AACnE,SAAK,wBAA2B,SAAS,CAAC,KAAK,YAAY,GAAG,KAAK,YAAY,CAAC,CAAC;AAAA,EACnF;AAAA,EAEA,eAAe,OAAO;AACpB,UAAMC,KAA4B,CAAC;AACnC,IAAAA,GAAE,aAAgB,MAAM,OAAO,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,CAAC,CAAC;AAC9C,IAAAA,GAAE,WAAc,MAAM,OAAO,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,CAAC,CAAC;AAC5C,IAAAA,GAAE,MAAS,IAAIA,GAAE,YAAY,KAAK,eAAe;AACjD,IAAAA,GAAE,kBAAqB,KAAIA,GAAE,KAAK,KAAK,aAAa;AACpD,IAAAA,GAAE,eAAkB,IAAIA,GAAE,UAAU,KAAK,qBAAqB;AAC9D,IAAAA,GAAE,MAAS,IAAIA,GAAE,iBAAiBA,GAAE,YAAY;AAChD,IAAAA,GAAE,cAAiB,IAAIA,GAAE,KAAK,KAAK,eAAe;AAClD,IAAAA,GAAE,MAAS,KAAIA,GAAE,iBAAiBA,GAAE,YAAY;AAChD,IAAAA,GAAE,YAAe,IAAIA,GAAE,KAAK,KAAK,eAAe;AAChD,UAAM,MAAS,SAAS,CAACA,GAAE,aAAaA,GAAE,SAAS,GAAG,CAAC;AACvD,WAAO,KAAKA,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,WAAO;AAAA,EACT;AAAA,EAEA,mBAAmB,kBAAkBC,QAAO;AAC1C,UAAMF,KAA4B,CAAC;AACnC,IAAAA,GAAE,UAAa,QAAQ,kBAAkB,CAAC,IAAI,GAAG,CAAC,CAAC;AACnD,IAAAA,GAAE,MAAS,IAAIA,GAAE,SAAS,KAAK,eAAe;AAC9C,IAAAA,GAAE,YAAe,KAAIA,GAAE,KAAK,KAAK,QAAQE,OAAM;AAC/C,UAAM,MAAS,IAAIF,GAAE,WAAW,KAAK,eAAe;AACpD,WAAO,KAAKA,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,WAAO;AAAA,EACT;AAAA,EAEA,MAAM,QAAQE,QAAOC,SAAuG;AAC1H,UAAMJ,KAA4B,CAAC;AACnC,IAAAA,GAAE,SAAY,MAAM,eAAeG,QAAO,CAAC,KAAK,WAAW,KAAK,SAAS,CAAC;AAC1E,IAAAH,GAAE,MAAS,IAAIA,GAAE,QAAQ,UAAU,KAAK;AACxC,IAAAA,GAAE,QAAW,IAAIA,GAAE,KAAK,UAAU,GAAG;AACrC,IAAAA,GAAE,UAAU,KAAK,MAAM,QAAQA,GAAE,KAAK;AACtC,IAAAA,GAAE,cAAiB,QAAQA,GAAE,OAAO;AACpC,IAAAA,GAAE,QAAW,MAAMA,GAAE,aAAa,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,CAAC,CAAC;AACjD,IAAAA,GAAE,UAAa,QAAQA,GAAE,KAAK;AAC9B,IAAAA,GAAE,SAAY,QAAQA,GAAE,OAAO;AAC/B,UAAM,SAAS,MAAMA,GAAE,OAAO,KAAK;AACnC,IAAAA,GAAE,QAAW,MAAMA,GAAE,aAAa,CAAC,GAAG,CAAC,GAAG,CAAC,IAAI,CAAC,CAAC;AACjD,IAAAA,GAAE,OAAO,KAAK,eAAeA,GAAE,KAAK;AAEpC,IAAAA,GAAE,MAAM,MAAS,MAAM,uBAAuBA,GAAE,MAAMA,GAAE,QAAQ,IAAII,QAAO,KAAK,aAAaA,QAAO,KAAK,cAAcA,QAAO,KAAK,aAAa;AAChJ,UAAM,MAAM,MAAMJ,GAAE,IAAI,MAAM;AAC9B,UAAM,QAAmG,CAAC;AAC1G,eAAWE,UAAS,KAAK;AACvB,YAAMG,KAA4B,CAAC;AACnC,MAAAA,GAAE,MAAS,MAAML,GAAE,MAAM,CAACE,QAAO,CAAC,GAAG,CAAC,GAAG,EAAE,CAAC;AAC5C,MAAAG,GAAE,QAAW,MAAML,GAAE,aAAa,CAACE,QAAO,CAAC,GAAG,CAAC,GAAG,EAAE,CAAC;AACrD,MAAAG,GAAE,OAAO,KAAK,mBAAmBA,GAAE,OAAOH,MAAK;AAC/C,MAAAG,GAAE,gBAAmB,QAAQA,GAAE,MAAM,CAAC,IAAI,CAAC,CAAC;AAC5C,YAAM,MAAM,MAAMA,GAAE,IAAI,KAAK;AAC7B,YAAM,aAAa,IAAI,MAAM,GAAG,CAAC;AACjC,YAAM,WAAW,IAAI,MAAM,GAAG,CAAC;AAC/B,YAAM,gBAAgB,MAAMA,GAAE,cAAc,MAAM;AAClD,YAAMC,QAAO,EAAE,YAAY,UAAU,eAAe,YAAY,OAAOJ,QAAO;AAC9E,YAAM,SAAcK,qBAAoBD,OAAM,CAACH,OAAM,MAAM,KAAK,KAAK,WAAWA,OAAM,MAAM,KAAK,KAAK,SAAS,CAAC;AAChH,YAAM,KAAK,MAAM;AACjB,aAAO,KAAKE,EAAC,EAAE,QAAQ,CAACJ,YAAc,QAAQI,GAAEJ,QAAO,CAAC;AAAA,IAC1D;AACA,WAAO,KAAKD,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,WAAO;AAAA,EACT;AACF;;;AC5EA,IAAM,uBAAuB;AAC7B,IAAM,uBAAuB;AAC7B,IAAM,kBAAkB,CAAC,GAAG,GAAG,GAAG,IAAI,IAAI,GAAG,CAAC;AAC9C,IAAM,wBAAwB;AAC9B,IAAM,gCAAgC;AACtC,IAAIO,aAAW;AAER,IAAM,eAAN,MAAmB;AAAA,EAQxB,YAAY,cAAcC,gBAAe;AAPzC;AACA;AACA;AACA;AACA;AACA;AAGE,SAAK,eAAe;AACpB,SAAK,gBAAgBA;AACrB,SAAK,YAAY,KAAK,iBAAiB,KAAK,cAAc,OAAO,GAAG,QAAQ,KAAK,cAAc,OAAO,GAAG,MAAM,KAAK;AACpH,SAAK,cAAc,CAAC;AACpB,SAAK,UAAU,OAAO;AACtB,SAAK,gBAAgB;AAAA,EACvB;AAAA,EAGA,8BAA8B,WAAW;AACvC,UAAM,KAAK,UAAU,IAAI,CAAC,MAAM,EAAE,EAAE;AACpC,UAAM,KAAK,UAAU,IAAI,CAAC,MAAM,EAAE,EAAE;AACpC,UAAM,aAAa,CAAC,KAAK,IAAI,GAAG,EAAE,GAAG,KAAK,IAAI,GAAG,EAAE,CAAC;AACpD,UAAM,WAAW,CAAC,KAAK,IAAI,GAAG,EAAE,GAAG,KAAK,IAAI,GAAG,EAAE,CAAC;AAClD,WAAO,EAAE,YAAY,SAAS;AAAA,EAChC;AAAA,EAEA,uBAAuB,eAAe,gBAAgB;AACpD,UAAM,uBAAuB,cAAc,IAAI,CAAC,UAAeC,aAAY,CAAC,GAAG,OAAO,CAAC,GAAG,cAAc,CAAC;AACzG,UAAM,gBAAgB,KAAK,8BAA8B,oBAAoB;AAC7E,WAAYC,YAAgBC,aAAY,aAAa,GAAG,oBAAoB;AAAA,EAC9E;AAAA,EAEA,uBAAuB,WAAW;AAChC,UAAM,cAAc,KAAK,8BAA8B,SAAS;AAChE,UAAM,gBAAqBD,YAAgBC,aAAY,WAAW,GAAG,oBAAoB;AACzF,kBAAc,gBAAgB,CAAC;AAC/B,aAASC,KAAI,GAAGA,KAAI,gBAAgB,QAAQA,MAAK;AAC/C,oBAAc,cAAc,KAAK,UAAU,gBAAgBA,KAAI,MAAM,GAAG,CAAC,CAAC;AAAA,IAC5E;AACA,WAAO;AAAA,EACT;AAAA,EAEA,mBAAmB,WAAW,MAAM,OAAO,gBAAgB;AACzD,UAAM,UAAeC,YAAW,IAAI;AACpC,UAAM,cAAc,CAAC,QAAQ,KAAK,KAAK,WAAW,QAAQ,KAAK,KAAK,YAAY,QAAQ,KAAK,QAAQ,MAAM,KAAK,YAAY,CAAC;AAC7H,UAAM,eAAe,UAAU,IAAI,CAAC,UAAU;AAAA,MAC5C,YAAY,MAAM,MAAM,KAAK,KAAK,YAAY;AAAA,MAC9C,YAAY,MAAM,MAAM,KAAK,KAAK,YAAY;AAAA,MAC9C,YAAY,KAAK,MAAM;AAAA,IACzB,CAAC;AACD,UAAM,uBAA4BC,qBAAoB,OAAO,CAAC,GAAG,CAAC,CAAC;AACnE,UAAM,gBAAgB,aAAa,IAAI,CAAC,UAAU;AAChD,YAAM,UAAeL,aAAY,OAAO,oBAAoB;AAC5D,aAAO,CAAC,GAAG,SAAS,MAAM,EAAE;AAAA,IAC9B,CAAC;AACD,UAAM,wBAA6BM,uBAAsB,cAAc;AACvE,UAAM,YAAY,CAAC,GAAQC,cAAa,IAAI,GAAG,CAAC;AAChD,UAAM,oBAAoB;AAAA,MACnBC,KAAI,WAAW,sBAAsB,EAAE;AAAA,MACvCA,KAAI,WAAW,sBAAsB,EAAE;AAAA,IAC9C;AACA,WAAO,cAAc,IAAI,CAAC,UAAU;AAAA,MAClC,KAAK,MAAM,MAAM,KAAK,kBAAkB,EAAE;AAAA,MAC1C,KAAK,MAAM,MAAM,KAAK,kBAAkB,EAAE;AAAA,MAC1C,KAAK,MAAM,MAAM,EAAE;AAAA,IACrB,CAAC;AAAA,EACH;AAAA,EAEA,MAAM,cAAcC,QAAOC,SAAQ;AACjC,QAAI,cAAc;AAGlB,QAAI;AACJ,UAAM,YAAYA,QAAO,KAAK,YAAY,KAAM,IAAI,IAAIZ;AACxD,UAAM,YAAY,KAAK,WAAWY,QAAO,KAAK,cAAc;AAC5D,QAAIA,QAAO,eAAe,YAAY,WAAW;AAC/C,cAAQ,MAAM,KAAK,aAAa,QAAQD,QAAOC,OAAM;AACrD,WAAK,UAAU;AAAA,IACjB;AACA,QAAIA,QAAO;AAAa,WAAK;AAG7B,QAAI,SAAU,MAAM,SAAS,MAAQ,MAAM,WAAW,KAAK,iBAAmB,KAAK,kBAAkBA,QAAO,KAAK,eAAgB,CAACA,QAAO,KAAK,YAAY;AACxJ,WAAK,gBAAgB;AACrB,WAAK,cAAc,CAAC,GAAG,KAAK;AAE5B,UAAI,KAAK,YAAY,SAAS;AAAG,sBAAc;AAAA,IACjD;AACA,UAAM,QAAyJ,CAAC;AAGhK,aAASP,KAAI,GAAGA,KAAI,KAAK,YAAY,QAAQA,MAAK;AAChD,YAAM,aAAa,KAAK,YAAYA;AACpC,UAAI,CAAC;AAAY;AACjB,UAAIO,QAAO,KAAK,WAAW;AACzB,cAAM,QAAQA,QAAO,KAAK,WAAgBC,iBAAgB,WAAW,cAAc,wBAAwB,WAAW,cAAc,8BAA8B,IAAI;AACtK,cAAM,aAAkBJ,cAAa,UAAU;AAC/C,cAAM,uBAAuB,CAAC,WAAW,KAAKE,OAAM,MAAM,IAAI,WAAW,KAAKA,OAAM,MAAM,EAAE;AAC5F,cAAM,eAAeC,QAAO,KAAK,YAAYE,KAAI,QAAQ,SAAS,kBAAkB,IAAO,MAAM,iBAAiBH,QAAO,OAAO,GAAG,oBAAoB,IAAIA,OAAM,MAAM;AACvK,cAAM,iBAAsBJ,qBAAoB,CAAC,OAAO,UAAU;AAClE,cAAM,SAAS,cAAc,KAAK,uBAAuB,WAAW,eAAe,cAAc,IAAI;AACrG,cAAM,eAAoB,yBAAyB,QAAQ,cAAc,CAAC,KAAK,WAAW,KAAK,SAAS,CAAC;AACzG,cAAM,YAAe,IAAI,cAAc,UAAU,KAAK;AACtD,QAAG,QAAQ,YAAY;AACvB,QAAG,QAAQ,YAAY;AACvB,cAAM,CAAC,aAAa,SAAS,IAAI,KAAK,cAAc,QAAQ,SAAS;AACrE,QAAAP,aAAW,IAAI;AACf,QAAG,QAAQ,SAAS;AACpB,cAAM,cAAc,MAAM,YAAY,KAAK,GAAG;AAC9C,QAAG,QAAQ,WAAW;AACtB,YAAI,cAAcY,QAAO,KAAK,gBAAgB,GAAG;AAC/C,gBAAM,oBAAuB,QAAQ,WAAW,CAAC,IAAI,CAAC,CAAC;AACvD,gBAAM,YAAY,MAAM,kBAAkB,MAAM;AAChD,UAAG,QAAQ,SAAS;AACpB,UAAG,QAAQ,iBAAiB;AAC5B,gBAAMG,UAAS,KAAK,mBAAmB,WAAW,QAAQ,OAAO,cAAc;AAC/E,gBAAM,kBAAkB,KAAK,uBAAuBA,OAAM;AAC1D,eAAK,YAAYV,MAAK,EAAE,GAAG,iBAAiB,WAAW;AACvD,gBAAM,SAAS;AAAA,YACb,WAAWU;AAAA,YACX;AAAA,YACA,eAAe,WAAW;AAAA,YAC1B,kBAAkB;AAAA,YAClB,KAAK,EAAE,SAAS,gBAAgB,YAAY,aAAa,gBAAgB,SAAS;AAAA,UACpF;AACA,gBAAM,KAAK,MAAM;AAAA,QACnB,OAAO;AACL,eAAK,YAAYV,MAAK;AAAA,QACxB;AACA,QAAG,QAAQ,SAAS;AAAA,MACtB,OAAO;AAEL,cAAM,WAAgBF,YAAgBC,aAAY,UAAU,GAAG,oBAAoB;AACnF,cAAM,SAAS;AAAA,UACb,YAAY,WAAW;AAAA,UACvB,eAAe,WAAW;AAAA,UAC1B,kBAAkB;AAAA,UAClB,KAAK,EAAE,SAAS,SAAS,YAAY,aAAa,SAAS,SAAS;AAAA,UACpE,WAAW,CAAC;AAAA,QACd;AACA,cAAM,KAAK,MAAM;AAAA,MACnB;AAAA,IACF;AACA,SAAK,cAAc,KAAK,YAAY,OAAO,CAAC,MAAM,MAAM,IAAI;AAC5D,SAAK,gBAAgB,MAAM;AAC3B,QAAI,MAAM,SAASQ,QAAO,KAAK;AAAa,YAAM,SAASA,QAAO,KAAK;AACvE,WAAO;AAAA,EACT;AACF;;;ACpKO,IAAM,SAAS;AAAA,EACpB,OAAO;AAAA,EACP,OAAO;AAAA,EACP,QAAQ;AAAA,EACR,MAAM;AAAA,EACN,OAAO;AAAA,EACP,KAAK,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC;AAAA,EACnB,aAAa,EAAE,GAAG,SAAS,GAAG,SAAS,GAAG,UAAU,GAAG,QAAQ,GAAG,QAAQ;AAAA,EAQ1E,eAAe;AAAA,IACb,GAAG,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAAA,IAClC,GAAG,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAAA,IAClC,GAAG,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,CAAC;AAAA,IACvC,GAAG,CAAC,CAAC,GAAG,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,CAAC;AAAA,IACzC,GAAG,CAAC,CAAC,GAAG,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,GAAG,CAAC,IAAI,EAAE,CAAC;AAAA,EAC3C;AAAA,EACA,SAAS,CAAC,UAAU,OAAO,YAAY;AAAA,EACvC,WAAW,CAAC,UAAU,OAAO,cAAc;AAC7C;AAEO,IAAM,aAAa;AAAA,EACxB,MAAM;AAAA,EACN,MAAM;AAAA,EACN,MAAM;AAAA,EACN,aAAa,EAAE,GAAG,QAAQ,GAAG,QAAQ,GAAG,OAAO;AAAA,EAC/C,SAAS,CAAC,UAAU,WAAW,YAAY;AAC7C;AAEO,IAAM,kBAAkB;AAAA,EAC7B,YAAY;AAAA,EACZ,cAAc;AAAA,EACd,gBAAgB;AAAA,EAChB,iBAAiB;AAAA,EACjB,iBAAiB;AAAA,EACjB,gBAAgB;AAAA,EAChB,mBAAmB;AAAA,EACnB,kBAAkB;AAAA,EAClB,aAAa,EAAE,GAAG,cAAc,GAAG,gBAAgB,GAAG,kBAAkB,GAAG,mBAAmB,GAAG,mBAAmB,GAAG,kBAAkB,GAAG,qBAAqB,GAAG,mBAAmB;AAAA,EACvL,SAAS,CAAC,UAAU,gBAAgB,YAAY;AAClD;AAEO,IAAM,gBAAN,MAAoB;AAAA,EAOzB,YAAY,MAAM;AANlB;AACA;AACA;AACA;AACA;AAIE,SAAK,OAAO;AACZ,SAAK,QAAQ,CAAC;AACd,SAAK,aAAa,CAAC;AACnB,SAAK,UAAU,CAAC,GAAK,GAAK,GAAK,GAAK,CAAG;AACvC,SAAK,kBAAkB,CAAC,GAAK,GAAK,GAAK,GAAK,CAAG;AAAA,EACjD;AAAA,EAEA,KAAK,QAAQ,MAAM,YAAY;AAC7B,QAAI,OAAO,KAAK,MAAM,YAAY;AAAa,WAAK,MAAM,UAAU,CAAC;AACrE,SAAK,MAAM,QAAQ,KAAK,CAAC,MAAM,UAAU,CAAC;AAAA,EAC5C;AAAA,EAEA,UAAU,QAAQ,UAAU,YAAY;AACtC,QAAI,CAAC,KAAK,WAAW;AAAS,WAAK,WAAW,UAAU,CAAC;AACzD,SAAK,WAAW,QAAQ,KAAK,CAAC,UAAU,UAAU,CAAC;AAAA,EACrD;AAAA,EAEA,OAAO,QAAQ,QAAQ;AACrB,SAAK,QAAQ,UAAU;AAEvB,UAAM,QAAQ,KAAK,QAAQ,OAAO,CAAC,GAAG,MAAM,IAAI,GAAG,CAAC;AACpD,SAAK,kBAAkB,KAAK,QAAQ,IAAI,CAAC,OAAO,KAAK,IAAI,KAAK;AAAA,EAChE;AAAA,EAEA,aAAa,eAAe,oBAAoB;AAC9C,QAAI,aAAa;AAGjB,eAAW,aAAa,eAAe;AACrC,YAAM,eAAe,cAAc;AACnC,YAAM,gBAAgB,KAAK,MAAM;AACjC,UAAI,OAAO,kBAAkB,aAAa;AAGxC,sBAAc,KAAK,gBAAgB;AACnC;AAAA,MACF;AAEA,iBAAW,CAAC,cAAc,KAAK,KAAK,eAAe;AACjD,YAAI,iBAAiB,cAAc;AACjC,wBAAc,QAAQ,KAAK,gBAAgB;AAC3C;AAAA,QACF;AAAA,MACF;AAAA,IACF;AAEA,eAAW,aAAa,oBAAoB;AAC1C,YAAM,oBAAoB,mBAAmB;AAC7C,YAAM,qBAAqB,KAAK,WAAW;AAC3C,UAAI,OAAO,uBAAuB,aAAa;AAG7C,sBAAc,KAAK,gBAAgB;AACnC;AAAA,MACF;AAEA,iBAAW,CAAC,mBAAmB,KAAK,KAAK,oBAAoB;AAC3D,YAAI,sBAAsB,mBAAmB;AAC3C,wBAAc,QAAQ,KAAK,gBAAgB;AAC3C;AAAA,QACF;AAAA,MACF;AAAA,IACF;AACA,WAAO,aAAa;AAAA,EACtB;AACF;;;ACtHO,IAAM,EAAE,OAAO,OAAO,QAAQ,MAAM,MAAM,IAAI;AAE9C,IAAM,EAAE,MAAM,MAAM,KAAK,IAAI;AAE7B,IAAM,EAAE,YAAY,cAAc,gBAAgB,iBAAiB,iBAAiB,gBAAgB,mBAAmB,iBAAiB,IAAI;AAGnJ,IAAM,WAAW,IAAI,cAAc,WAAW;AAC9C,SAAS,KAAK,OAAO,MAAM,CAAG;AAC9B,SAAS,UAAU,OAAO,YAAY,CAAG;AACzC,SAAS,UAAU,OAAO,gBAAgB,IAAI;AAC9C,SAAS,UAAU,OAAO,iBAAiB,IAAI;AAC/C,WAAW,UAAU,CAAC,OAAO,OAAO,OAAO,QAAQ,OAAO,MAAM,OAAO,KAAK,GAAG;AAC7E,WAAS,KAAK,QAAQ,MAAM,CAAG;AAC/B,WAAS,UAAU,QAAQ,gBAAgB,CAAG;AAC9C,WAAS,UAAU,QAAQ,iBAAiB,CAAG;AACjD;AAGA,IAAM,UAAU,IAAI,cAAc,SAAS;AAC3C,QAAQ,KAAK,OAAO,MAAM,GAAG;AAC7B,QAAQ,KAAK,OAAO,MAAM,GAAG;AAC7B,QAAQ,UAAU,OAAO,YAAY,CAAG;AACxC,QAAQ,UAAU,OAAO,gBAAgB,CAAG;AAC5C,QAAQ,KAAK,OAAO,MAAM,CAAG;AAC7B,QAAQ,UAAU,OAAO,YAAY,IAAI;AACzC,QAAQ,UAAU,OAAO,gBAAgB,CAAG;AAC5C,QAAQ,KAAK,QAAQ,MAAM,CAAG;AAC9B,QAAQ,UAAU,QAAQ,YAAY,CAAG;AACzC,QAAQ,UAAU,QAAQ,gBAAgB,IAAI;AAC9C,QAAQ,KAAK,MAAM,MAAM,CAAG;AAC5B,QAAQ,UAAU,MAAM,YAAY,GAAG;AACvC,QAAQ,UAAU,MAAM,gBAAgB,CAAG;AAC3C,QAAQ,UAAU,MAAM,gBAAgB,GAAG;AAC3C,QAAQ,KAAK,OAAO,MAAM,CAAG;AAC7B,QAAQ,UAAU,OAAO,YAAY,GAAG;AACxC,QAAQ,UAAU,OAAO,gBAAgB,CAAG;AAC5C,QAAQ,UAAU,OAAO,gBAAgB,GAAG;AAC5C,QAAQ,OAAO,OAAO,CAAC;AACvB,QAAQ,OAAO,QAAQ,CAAC;AAGxB,IAAM,QAAQ,IAAI,cAAc,OAAO;AACvC,MAAM,KAAK,OAAO,MAAM,CAAG;AAC3B,MAAM,KAAK,OAAO,MAAM,GAAG;AAC3B,MAAM,KAAK,QAAQ,MAAM,GAAG;AAC5B,MAAM,KAAK,MAAM,MAAM,GAAG;AAC1B,MAAM,KAAK,OAAO,MAAM,GAAG;AAC3B,MAAM,OAAO,OAAO,CAAC;AACrB,MAAM,OAAO,QAAQ,CAAC;AAGtB,IAAM,eAAe,IAAI,cAAc,eAAe;AACtD,aAAa,KAAK,OAAO,MAAM,CAAG;AAClC,aAAa,KAAK,OAAO,MAAM,GAAG;AAClC,aAAa,KAAK,QAAQ,MAAM,GAAG;AACnC,aAAa,KAAK,MAAM,MAAM,GAAG;AACjC,aAAa,KAAK,OAAO,MAAM,GAAG;AAClC,aAAa,OAAO,OAAO,CAAC;AAC5B,aAAa,OAAO,QAAQ,CAAC;AAG7B,IAAM,WAAW,IAAI,cAAc,WAAW;AAC9C,SAAS,KAAK,OAAO,MAAM,IAAI;AAC/B,SAAS,KAAK,OAAO,MAAM,IAAI;AAC/B,SAAS,KAAK,QAAQ,MAAM,IAAI;AAChC,SAAS,KAAK,MAAM,MAAM,IAAI;AAC9B,SAAS,KAAK,OAAO,MAAM,IAAI;AAE/B,IAAO,wBAAQ,CAAC,UAAU,SAAS,OAAO,cAAc,QAAQ;;;ACpEhE,IAAM,gBAAgB;AACtB,IAAMI,WAAU;AAAA,EAEd,uBAAuB;AAAA,EACvB,qBAAqB;AAAA,EAErB,qBAAqB;AAAA,EACrB,yBAAyB;AAAA,EACzB,wBAAwB;AAC1B;AAEA,SAAS,eAAe,SAAS,SAAS,SAAS,SAAS;AAC1D,QAAM,SAAS,UAAU,YAAY,UAAU;AAC/C,MAAI,QAAQ,KAAK,KAAK,KAAK,IAAI,MAAM,KAAK;AAC1C,MAAI,SAAS;AAAG,YAAQ,CAAC;AAAA,WAChB,QAAQ;AAAG,YAAQ,MAAM;AAClC,SAAO;AACT;AAIA,SAAS,UAAU,QAAQ,QAAQ;AACjC,MAAI,CAAC,UAAU,CAAC;AAAQ,WAAO,CAAC,GAAG,CAAC;AACpC,QAAM,UAAU,eAAe,OAAO,IAAI,OAAO,IAAI,OAAO,IAAI,OAAO,EAAE;AACzE,MAAI,OAAO,WAAW;AAAG,WAAO;AAChC,QAAM,UAAU,eAAe,OAAO,IAAI,OAAO,IAAI,OAAO,IAAI,OAAO,EAAE;AACzE,SAAO,CAAC,SAAS,OAAO;AAC1B;AAEA,SAAS,mBAAmB,OAAO,cAAc,GAAK;AACpD,MAAI,aAAa;AACjB,MAAI,aAAa;AACjB,MAAI,eAAe;AACnB,MAAI,SAAS,MAAQ,SAAS;AAAO,iBAAa,IAAI;AAAA,WAC7C,SAAS,MAAQ,SAAS;AAAO,iBAAa,IAAI;AAAA;AACtD,mBAAe,IAAI;AACxB,SAAO,CAAC,YAAY,YAAY,YAAY;AAC9C;AAEA,SAAS,mBAAmB,YAAY,UAAU,UAAU;AAC1D,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,iBAAiB,SAAS,KAAK,SAAS;AAC9C,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,iBAAiB,SAAS,KAAK,SAAS;AAC9C,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,iBAAiB,SAAS,KAAK,SAAS;AAC9C,QAAM,iBAAiB,KAAK,KAAK,mBAAmB,mBAAmB,mBAAmB,mBAAmB,mBAAmB,gBAAgB;AAChJ,QAAM,iBAAiB,KAAK,KAAK,mBAAmB,mBAAmB,mBAAmB,mBAAmB,mBAAmB,gBAAgB;AAChJ,QAAM,eAAe,KAAK,KAAK,iBAAiB,iBAAiB,iBAAiB,iBAAiB,iBAAiB,cAAc;AAClI,MAAI,UAAU,eAAe,eAAe,iBAAiB,iBAAiB,iBAAiB,mBAAmB,IAAI,eAAe;AACrI,MAAI,SAAS;AAAK,aAAS;AAAA,WAClB,SAAS;AAAM,aAAS;AACjC,MAAI,eAAe,KAAK,KAAK,MAAM;AACnC,iBAAgB,UAAU,eAAgB;AAC1C,MAAI;AACJ,MAAI,eAAeA,SAAQ;AAAqB,iBAAa,WAAW;AAAA,WAC/D,eAAeA,SAAQ;AAAuB,iBAAa,WAAW;AAAA;AAC1E,iBAAa,WAAW;AAC7B,SAAO;AACT;AAEA,SAAS,4BAA4B,kBAAkB,kBAAkB,gBAAgB,YAAY;AACnG,MAAI;AACJ,MAAI,eAAe,KAAK,IAAI,gBAAgB,GAAG;AAC7C,QAAI,mBAAmB;AAAG,2BAAqB,gBAAgB;AAAA;AAC1D,2BAAqB,gBAAgB;AAAA,EAC5C,WAAW,eAAe,KAAK,IAAI,gBAAgB,GAAG;AACpD,QAAI,mBAAmB;AAAG,2BAAqB,gBAAgB;AAAA;AAC1D,2BAAqB,gBAAgB;AAAA,EAC5C,OAAO;AACL,QAAI,iBAAiB;AAAG,2BAAqB,gBAAgB;AAAA;AACxD,2BAAqB,gBAAgB;AAAA,EAC5C;AACA,SAAO;AACT;AAEA,SAAS,0BAA0B,kBAAkB,kBAAkB,gBAAgB,YAAY;AACjG,MAAI;AACJ,MAAI,eAAe,KAAK,IAAI,gBAAgB,GAAG;AAC7C,QAAI,mBAAmB;AAAG,2BAAqB,gBAAgB;AAAA;AAC1D,2BAAqB,gBAAgB;AAAA,EAC5C,WAAW,eAAe,KAAK,IAAI,gBAAgB,GAAG;AACpD,QAAI,mBAAmB;AAAG,2BAAqB,gBAAgB;AAAA;AAC1D,2BAAqB,gBAAgB;AAAA,EAC5C,OAAO;AACL,QAAI,iBAAiB;AAAG,2BAAqB,gBAAgB;AAAA;AACxD,2BAAqB,gBAAgB;AAAA,EAC5C;AACA,SAAO;AACT;AAEA,SAAS,0BAA0B,kBAAkB,kBAAkB,gBAAgB,YAAY,kBAAkB,kBAAkB,gBAAgB,YAAY;AACjK,MAAI;AACJ,QAAM,0BAA0B,0BAA0B,kBAAkB,kBAAkB,gBAAgB,UAAU;AACxH,QAAM,4BAA4B,4BAA4B,kBAAkB,kBAAkB,gBAAgB,UAAU;AAC5H,MAAI,4BAA4B,gBAAgB,YAAY;AAC1D,QAAI,8BAA8B,gBAAgB;AAAgB,2BAAqB,gBAAgB;AAAA;AAClG,2BAAqB,gBAAgB;AAAA,EAC5C,OAAO;AACL,QAAI,8BAA8B,gBAAgB;AAAgB,2BAAqB,gBAAgB;AAAA;AAClG,2BAAqB,gBAAgB;AAAA,EAC5C;AACA,SAAO;AACT;AAEA,SAAS,yBAAyB,YAAY,UAAU,UAAU,cAAc;AAC9E,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,iBAAiB,SAAS,KAAK,SAAS;AAC9C,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,mBAAmB,WAAW,KAAK,SAAS;AAClD,QAAM,iBAAiB,SAAS,KAAK,SAAS;AAC9C,QAAM,aAAa,KAAK,IAAI,KAAK,IAAI,gBAAgB,GAAG,KAAK,IAAI,gBAAgB,GAAG,KAAK,IAAI,cAAc,CAAC;AAC5G,QAAM,aAAa,KAAK,IAAI,KAAK,IAAI,gBAAgB,GAAG,KAAK,IAAI,gBAAgB,GAAG,KAAK,IAAI,cAAc,CAAC;AAC5G,MAAI,eAAe;AACnB,MAAI,eAAe;AACnB,MAAI,iBAAiB;AACrB,QAAM,2BAA2B,cAAc,aAAa;AAC5D,MAAI,2BAA2B;AAAK,oBAAgBA,SAAQ;AAAA,WACnD,2BAA2B;AAAM,oBAAgBA,SAAQ;AAAA;AAC7D,sBAAkBA,SAAQ;AAC/B,QAAM,iBAAiB,KAAK,KAAK,mBAAmB,mBAAmB,mBAAmB,gBAAgB;AAC1G,QAAM,iBAAiB,KAAK,KAAK,mBAAmB,mBAAmB,mBAAmB,gBAAgB;AAC1G,QAAM,eAAe,KAAK,KAAK,iBAAiB,iBAAiB,iBAAiB,cAAc;AAChG,QAAM,WAAW,KAAK,IAAI,gBAAgB,gBAAgB,YAAY;AACtE,MAAI,qBAAqB,WAAW;AACpC,MAAI,qBAAqB,WAAW;AACpC,MAAI,mBAAmB,SAAS;AAChC,MAAI,mBAAmB,SAAS;AAChC,MAAI,aAAa,gBAAgB;AAC/B,uBAAmB,SAAS;AAC5B,uBAAmB,SAAS;AAAA,EAC9B,WAAW,aAAa,cAAc;AACpC,yBAAqB,SAAS;AAC9B,yBAAqB,SAAS;AAAA,EAChC;AACA,QAAM,iBAAiB,CAAC,oBAAoB,kBAAkB;AAC9D,QAAM,eAAe,CAAC,kBAAkB,gBAAgB;AACxD,QAAM,aAAa,UAAU,gBAAgB,YAAY;AACzD,QAAM,QAAQ,mBAAmB,YAAYA,SAAQ,sBAAsB;AAC3E,kBAAgB,MAAM;AACtB,kBAAgB,MAAM;AACtB,oBAAkB,MAAM;AACxB,aAAW,eAAe,cAAc;AACtC,UAAM,cAAc,mBAAmB,aAAaA,SAAQ,uBAAuB;AACnF,oBAAgB,YAAY;AAC5B,oBAAgB,YAAY;AAC5B,sBAAkB,YAAY;AAAA,EAChC;AAGA,MAAI;AACJ,MAAI,iBAAiB,KAAK,IAAI,cAAc,cAAc,cAAc,GAAG;AACzE,yBAAqB,0BAA0B,kBAAkB,kBAAkB,gBAAgB,UAAU;AAAA,EAC/G,WAAW,mBAAmB,KAAK,IAAI,cAAc,cAAc,GAAG;AACpE,yBAAqB,4BAA4B,kBAAkB,kBAAkB,gBAAgB,UAAU;AAAA,EACjH,OAAO;AACL,yBAAqB,0BAA0B,kBAAkB,kBAAkB,gBAAgB,YAAY,kBAAkB,kBAAkB,gBAAgB,UAAU;AAAA,EAC/K;AACA,SAAO;AACT;AAEA,SAAS,SAAS,WAAW;AAE3B,QAAM,WAA4B,CAAC;AACnC,QAAM,WAA4B,CAAC;AACnC,QAAM,cAA6B,CAAC;AACpC,QAAM,mBAAkC,CAAC;AACzC,MAAI,CAAC;AAAW,WAAO,EAAE,OAAO,aAAa,YAAY,iBAAiB;AAG1E,aAAW,UAAU,OAAO,KAAK;AAC/B,UAAM,SAAS,OAAO,UAAU,MAAM;AACtC,UAAM,YAA2B,CAAC;AAClC,UAAM,YAA2B,CAAC;AAClC,eAAWC,UAAS,QAAQ;AAC1B,YAAM,SAAS,UAAUA,OAAM;AAC/B,YAAMC,UAAS,UAAUD,OAAM;AAE/B,YAAM,SAAS,UAAU,QAAQC,OAAM;AACvC,YAAM,UAAU,OAAO;AACvB,YAAM,UAAU,OAAO;AACvB,gBAAU,KAAK,OAAO;AACtB,gBAAU,KAAK,OAAO;AAAA,IACxB;AACA,aAAS,KAAK,SAAS;AACvB,aAAS,KAAK,SAAS;AAAA,EACzB;AAGA,aAAW,UAAU,OAAO,KAAK;AAE/B,UAAM,eAAgB,WAAW,OAAO,QAAS,IAAI;AACrD,UAAM,iBAAiB,OAAO,UAAU,MAAM;AAC9C,UAAM,aAAa,UAAU,eAAe,cAAc;AAC1D,UAAM,WAAW,UAAU,eAAe,eAAe,GAAG;AAC5D,UAAM,WAAW,UAAU,eAAe,GAAG;AAE7C,UAAM,eAAe,mBAAmB,YAAY,UAAU,QAAQ;AACtE,UAAM,iBAAiB,yBAAyB,YAAY,UAAU,UAAU,SAAS,QAAQ,MAAM,YAAY,CAAC;AACpH,gBAAY,UAAU;AACtB,qBAAiB,UAAU;AAAA,EAC7B;AACA,SAAO,EAAE,OAAO,aAAa,YAAY,iBAAiB;AAC5D;AAEO,SAAS,QAAQ,WAAW;AACjC,MAAI,CAAC,aAAa,UAAU,WAAW;AAAG,WAAO;AACjD,QAAM,eAAe,SAAS,SAAS;AACvC,QAAM,YAAY,CAAC;AACnB,aAAW,aAAa,OAAO,KAAK;AAClC,cAAU,OAAO,QAAQ,SAAS,KAAK;AAAA,MACrC,MAAM,WAAW,QAAQ,aAAa,MAAM,UAAU;AAAA,MACtD,WAAW,gBAAgB,QAAQ,aAAa,WAAW,UAAU;AAAA,IACvE;AAAA,EACF;AACA,SAAO;AACT;AAEO,SAAS,MAAM,WAAW;AAC/B,QAAM,QAAqD,CAAC;AAC5D,MAAI,CAAC,aAAa,UAAU,WAAW;AAAG,WAAO;AACjD,QAAM,eAAe,SAAS,SAAS;AACvC,aAAWC,YAAW,uBAAU;AAC9B,UAAM,aAAaA,SAAQ,aAAa,aAAa,OAAO,aAAa,UAAU;AACnF,QAAI,cAAc;AAAe,YAAM,KAAK,EAAE,MAAMA,SAAQ,MAAM,WAAW,CAAC;AAAA,EAChF;AACA,SAAO;AACT;;;AChOA,IAAMC,mBAAkB;AAAA,EACtB,OAAO,CAAC,GAAG,GAAG,GAAG,CAAC;AAAA,EAClB,OAAO,CAAC,GAAG,GAAG,GAAG,CAAC;AAAA,EAClB,QAAQ,CAAC,GAAG,IAAI,IAAI,EAAE;AAAA,EACtB,MAAM,CAAC,IAAI,IAAI,IAAI,EAAE;AAAA,EACrB,OAAO,CAAC,IAAI,IAAI,IAAI,EAAE;AAAA,EACtB,MAAM,CAAC,CAAC;AACV;AAEA,IAAI;AACJ,IAAI;AACJ,IAAI;AAEJ,eAAsBC,UAAQC,QAAeC,SAAuC;AAClF,QAAM,cAAc,MAAM,aAAa,cAAcD,QAAOC,OAAM;AAClE,MAAI,CAAC;AAAa,WAAO,CAAC;AAC1B,QAAM,QAA2B,CAAC;AAClC,WAASC,KAAI,GAAGA,KAAI,YAAY,QAAQA,MAAK;AAC3C,UAAMC,eAAc,CAAC;AACrB,QAAI,YAAYD,IAAG,WAAW;AAC5B,iBAAW,OAAO,OAAO,KAAKJ,gBAAe,GAAG;AAC9C,QAAAK,aAAY,OAAOL,iBAAgB,KAAK,IAAI,CAACM,WAAU,YAAYF,IAAG,UAAUE,OAAM;AAAA,MACxF;AAAA,IACF;AACA,UAAM,YAAY,YAAYF,IAAG;AACjC,QAAI,MAAW,CAAC,OAAO,kBAAkB,OAAO,kBAAkB,GAAG,CAAC;AACtE,QAAI,SAAc,CAAC,GAAG,GAAG,GAAG,CAAC;AAC7B,QAAI,aAAa,UAAU,SAAS,GAAG;AACrC,iBAAW,MAAM,WAAW;AAC1B,YAAI,GAAG,KAAK,IAAI;AAAI,cAAI,KAAK,GAAG;AAChC,YAAI,GAAG,KAAK,IAAI;AAAI,cAAI,KAAK,GAAG;AAChC,YAAI,GAAG,KAAK,IAAI;AAAI,cAAI,KAAK,GAAG;AAChC,YAAI,GAAG,KAAK,IAAI;AAAI,cAAI,KAAK,GAAG;AAAA,MAClC;AACA,UAAI,MAAM,IAAI;AACd,UAAI,MAAM,IAAI;AACd,eAAS,CAAC,IAAI,MAAMF,OAAM,MAAM,MAAM,IAAI,IAAI,MAAMA,OAAM,MAAM,MAAM,IAAI,IAAI,MAAMA,OAAM,MAAM,MAAM,IAAI,IAAI,MAAMA,OAAM,MAAM,MAAM,EAAE;AAAA,IAC1I,OAAO;AACL,YAAM,YAAYE,IAAG,MAAM;AAAA,QACzB,KAAK,MAAM,KAAK,IAAI,GAAG,YAAYA,IAAG,IAAI,QAAQ,EAAE,CAAC;AAAA,QACrD,KAAK,MAAM,KAAK,IAAI,GAAG,YAAYA,IAAG,IAAI,QAAQ,EAAE,CAAC;AAAA,QACrD,KAAK,MAAM,KAAK,IAAKF,OAAM,MAAM,MAAM,GAAI,YAAYE,IAAG,IAAI,YAAY,EAAE,IAAI,KAAK,IAAI,GAAG,YAAYA,IAAG,IAAI,QAAQ,EAAE,CAAC;AAAA,QAC1H,KAAK,MAAM,KAAK,IAAKF,OAAM,MAAM,MAAM,GAAI,YAAYE,IAAG,IAAI,YAAY,EAAE,IAAI,KAAK,IAAI,GAAG,YAAYA,IAAG,IAAI,QAAQ,EAAE,CAAC;AAAA,MAC5H,IAAI,CAAC,GAAG,GAAG,GAAG,CAAC;AACf,eAAS;AAAA,QACN,YAAYA,IAAG,IAAI,QAAQ,MAAOF,OAAM,MAAM,MAAM;AAAA,QACpD,YAAYE,IAAG,IAAI,QAAQ,MAAOF,OAAM,MAAM,MAAM;AAAA,SACpD,YAAYE,IAAG,IAAI,YAAY,KAAK,YAAYA,IAAG,IAAI,QAAQ,OAAOF,OAAM,MAAM,MAAM;AAAA,SACxF,YAAYE,IAAG,IAAI,YAAY,KAAK,YAAYA,IAAG,IAAI,QAAQ,OAAOF,OAAM,MAAM,MAAM;AAAA,MAC3F;AAAA,IACF;AACA,UAAM,YAAuB,QAAQ,SAAS;AAC9C,UAAM,KAAK;AAAA,MACT,IAAIE;AAAA,MACJ,OAAO,KAAK,MAAM,MAAM,YAAYA,IAAG,UAAU,IAAI;AAAA,MACrD,UAAU,KAAK,MAAM,MAAM,YAAYA,IAAG,aAAa,IAAI;AAAA,MAC3D,aAAa,KAAK,MAAM,MAAM,YAAYA,IAAG,gBAAgB,IAAI;AAAA,MACjE,OAAO;AAAA,MACP;AAAA,MACA;AAAA,MACA;AAAA,MACA,aAAaC;AAAA,MACb;AAAA,IACF,CAAC;AAAA,EACH;AACA,SAAO;AACT;AAEA,eAAsBE,OAAKJ,SAAiE;AApF5F;AAqFE,MAAIK,KAAI,SAAS;AACf,wBAAoB;AACpB,oBAAgB;AAAA,EAClB;AACA,MAAI,CAAC,qBAAqB,CAAC,eAAe;AACxC,KAAC,mBAAmB,aAAa,IAAI,MAAM,QAAQ,IAAI;AAAA,MACrDL,QAAO,KAAK,UAAU,WAAU,KAAAA,QAAO,KAAK,aAAZ,mBAAsB,SAAS,IAAI;AAAA,MACnEA,QAAO,KAAK,YAAY,WAAU,KAAAA,QAAO,KAAK,aAAZ,mBAAsB,SAAS,IAAI;AAAA,IACvE,CAAC;AAAA,EACH,OAAO;AACL,QAAIA,QAAO;AAAO,UAAI,iBAAiB,kBAAkB,WAAW;AACpE,QAAIA,QAAO;AAAO,UAAI,iBAAiB,cAAc,WAAW;AAAA,EAClE;AACA,QAAM,eAAe,IAAiB,aAAa,iBAAiB;AACpE,iBAAe,IAAiB,aAAa,cAAc,aAAa;AACxE,SAAO,CAAC,mBAAmB,aAAa;AAC1C;;;ACjFA,IAAMM,UAAiD,CAAC,MAAM,IAAI;AAClE,IAAM,mBAAmB,CAAC,+CAA+C,oDAAoD;AAE7H,IAAMC,aAAY,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAEjC,IAAM,UAAU,CAAC,QAAQ,QAAQ,SAAS,SAAS,QAAQ,OAAO,UAAU;AAC5E,IAAM,YAAY;AAElB,IAAM,gBAAgB;AACtB,IAAM,wBAAwB;AAC9B,IAAM,qBAAqB;AAE3B,IAAIC,YAAU,OAAO;AACrB,IAAIC,aAAW;AACf,IAAI,aAA+B,CAAC,GAAG,CAAC;AAUxC,IAAMC,SAGF;AAAA,EACF,OAAO,CAAC;AAAA,EACR,OAAO,CAAC;AACV;AAEA,IAAM,YAAY;AAAA,EAShB,OAAO,CAAC,GAAG,GAAG,GAAG,CAAC;AAAA,EAClB,OAAO,CAAC,GAAG,GAAG,GAAG,CAAC;AAAA,EAClB,QAAQ,CAAC,GAAG,IAAI,IAAI,EAAE;AAAA,EACtB,MAAM,CAAC,IAAI,IAAI,IAAI,EAAE;AAAA,EACrB,OAAO,CAAC,IAAI,IAAI,IAAI,EAAE;AAAA,EACtB,MAAM,CAAC,CAAC;AAAA,EACR,MAAM,CAAC,GAAG,IAAI,IAAI,GAAG,GAAG,GAAG,CAAC;AAC9B;AAEA,eAAsBC,YAAWC,SAAqC;AAtEtE;AAwEE,MAAIC,KAAI;AAAS,IAAAP,QAAO,KAAK;AAC7B,MAAI,CAACA,QAAO,IAAI;AAGd,YAAQ,CAAC,qBAAqB,SAAS,wBAAwB,SAAS,YAAY,UAAU,QAAQ,mBAAmB,iBAAiB,qBAAqB,qBAAqB,cAAc,SAAS,SAAS,OAAO,GAAGM,OAAM;AACpO,IAAAN,QAAO,KAAK,MAAM,WAAU,KAAAM,QAAO,KAAK,aAAZ,mBAAsB,SAAS;AAC3D,UAAM,SAAS,OAAO,OAAON,QAAO,GAAG,eAAe,SAAS;AAC/D,IAAAC,WAAU,GAAG,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AACxF,IAAAA,WAAU,GAAG,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAAA,EAC1F,WAAWK,QAAO;AAAO,QAAI,iBAAiBN,QAAO,GAAG,WAAW;AACnE,SAAOA,QAAO;AAChB;AAEA,eAAsB,aAAaM,SAAqC;AArFxE;AAsFE,MAAIC,KAAI;AAAS,IAAAP,QAAO,KAAK;AAC7B,MAAI,CAACA,QAAO,IAAI;AACd,IAAAA,QAAO,KAAK,MAAM,WAAU,KAAAM,QAAO,KAAK,aAAZ,mBAAsB,SAAS;AAC3D,UAAM,SAAS,OAAO,OAAON,QAAO,GAAG,eAAe,SAAS;AAC/D,IAAAC,WAAU,GAAG,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AACxF,IAAAA,WAAU,GAAG,KAAK,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAAA,EAC1F,WAAWK,QAAO;AAAO,QAAI,iBAAiBN,QAAO,GAAG,WAAW;AACnE,SAAOA,QAAO;AAChB;AAQA,eAAe,YAAYQ,QAAeC,SAA6C;AACrF,QAAM,QAA4B,CAAC;AACnC,MAAI,CAACD,UAAS,CAACE,QAAO;AAAI,WAAO;AACjC,QAAMC,KAA4B,CAAC;AACnC,QAAM,SAASH,OAAM,MAAM,MAAM,MAAMA,OAAM,MAAM,MAAM;AACzD,QAAM,SAAS,KAAK,IAAI,KAAK,OAAOA,OAAM,MAAM,MAAM,KAAK,CAAC,IAAI,GAAG,qBAAqB;AACxF,QAAM,QAAQ,KAAK,MAAM,SAAS,QAAQ,CAAC,IAAI;AAC/C,EAAAG,GAAE,SAAY,MAAM,eAAeH,QAAO,CAAC,QAAQ,KAAK,CAAC;AACzD,EAAAG,GAAE,OAAU,KAAKA,GAAE,QAAQ,OAAO;AAClC,GAACA,GAAE,WAAWA,GAAE,QAAQ,IAAI,MAAMD,QAAO,GAAG,aAAaC,GAAE,MAAM,gBAAgB;AACjF,EAAAA,GAAE,QAAW,QAAQA,GAAE,UAAU,CAAC,GAAG,CAAC,CAAC;AACvC,EAAAA,GAAE,SAAY,QAAQA,GAAE,WAAW,CAAC,CAAC,CAAC;AACtC,QAAM,cAAgC,QAAQA,GAAE,QAAQ,CAAC;AACzD,EAAG,QAAQ,YAAY,UAAU;AACjC,cAAY,OAAO,WAAW,CAAC;AAC/B,EAAAA,GAAE,WAAc,MAAM,aAAa,CAAC;AACpC,EAAG,QAAQ,WAAW;AAEtB,EAAAA,GAAE,MAAS,IAAIA,GAAE,UAAU,CAAC;AAC5B,EAAAA,GAAE,SAAY,OAAOA,GAAE,UAAU,CAAC;AAClC,MAAI,KAAK;AACT,EAAAA,GAAE,MAAM,MAAS,MAAM,uBAAuBA,GAAE,OAAOA,GAAE,MAAMF,QAAO,KAAK,eAAe,KAAK,GAAGA,QAAO,KAAK,gBAAgB,GAAGA,QAAO,KAAK,iBAAiB,CAAC;AAC/J,QAAM,MAAM,MAAME,GAAE,IAAI,KAAK;AAC7B,QAAM,SAAS,MAAMA,GAAE,IAAI,KAAK;AAChC,QAAM,WAAW,MAAMA,GAAE,OAAO,KAAK;AACrC,aAAW,YAAY,MAAM,KAAK,GAAG,GAAG;AACtC,UAAM,WAAc,MAAMA,GAAE,OAAO,UAAU,CAAC;AAC9C,UAAM,QAAQ,MAAM,SAAS,KAAK;AAClC,IAAG,QAAQ,QAAQ;AACnB,UAAM,UAAe,CAAC,MAAM,IAAI,MAAM,IAAI,MAAM,KAAK,MAAM,IAAI,MAAM,KAAK,MAAM,EAAE;AAClF,UAAM,SAAkBC,OAAM,SAAS,kBAAkB;AACzD,UAAM,UAAe,CAAC,KAAK,MAAM,QAAQ,KAAK,WAAW,EAAE,GAAG,KAAK,MAAM,QAAQ,KAAK,WAAW,EAAE,GAAG,KAAK,MAAM,QAAQ,KAAK,WAAW,EAAE,GAAG,KAAK,MAAM,QAAQ,KAAK,WAAW,EAAE,CAAC;AACpL,UAAM,QAAQ,OAAO;AACrB,UAAM,QAAQ,QAAQ,SAAS;AAC/B,UAAMC,QAAyB,EAAE,IAAI,MAAM,OAAO,KAAK,SAAS,QAAQ,MAAM;AAC9E,UAAM,KAAKA,KAAI;AAAA,EACjB;AACA,SAAO,KAAKF,EAAC,EAAE,QAAQ,CAACG,YAAc,QAAQH,GAAEG,QAAO,CAAC;AACxD,QAAM,KAAK,CAAC,GAAG,MAAM,EAAE,QAAQ,EAAE,KAAK;AACtC,MAAI,MAAM,UAAUL,QAAO,KAAK,eAAe;AAAI,UAAM,SAAUA,QAAO,KAAK,eAAe;AAC9F,SAAO;AACT;AAEA,eAAe,cAAcD,QAAe,GAAqBC,SAAqC;AACpG,QAAMI,QAAmB;AAAA,IACvB,IAAI,EAAE;AAAA,IACN,OAAO,KAAK,MAAM,MAAM,EAAE,KAAK,IAAI;AAAA,IACnC,UAAU,KAAK,MAAM,MAAM,EAAE,KAAK,IAAI;AAAA,IACtC,aAAa;AAAA,IACb,KAAK,EAAE;AAAA,IACP,QAAQ,EAAE;AAAA,IACV,OAAO,EAAE;AAAA,IACT,WAAW,CAAC;AAAA,IACZ,WAAW,CAAC;AAAA,IACZ,aAAa,CAAC;AAAA,EAChB;AACA,MAAIL,UAASE,QAAO,MAAMD,QAAO,KAAK,aAAa,EAAE,SAASA,QAAO,KAAK,iBAAiB,IAAI;AAC7F,UAAME,KAA4B,CAAC;AACnC,UAAM,UAAU,CAAC,EAAE,OAAO,IAAI,EAAE,OAAO,IAAI,EAAE,OAAO,KAAK,EAAE,OAAO,IAAI,EAAE,OAAO,KAAK,EAAE,OAAO,EAAE;AAC/F,IAAAA,GAAE,OAAU,MAAM,cAAcH,QAAO,CAAC,OAAO,GAAG,CAAC,CAAC,GAAG,CAACO,WAAU,GAAG,IAAIA,WAAU,GAAG,EAAE,GAAG,UAAU;AACrG,IAAAJ,GAAE,MAAS,IAAIA,GAAE,MAAM,UAAU,KAAK;AACtC,KAACA,GAAE,OAAOA,GAAE,SAAS,IAAID,QAAO,GAAG,QAAQC,GAAE,KAAK,CAAC,cAAc,UAAU,CAAC;AAC5E,UAAM,YAAY,MAAMA,GAAE,MAAM,KAAK,GAAG;AACxC,UAAM,SAAS,MAAM,KAAK,MAAM,OAAO,IAAI,KAAK,IAAI,QAAQ,EAAE,KAAK;AACnE,QAAI,UAAUF,QAAO,KAAK,iBAAiB,IAAI;AAC7C,MAAAI,MAAK,cAAc;AACnB,MAAAF,GAAE,WAAc,QAAQA,GAAE,WAAW,CAAC,IAAI,CAAC,CAAC;AAC5C,YAAM,aAAsB,MAAMA,GAAE,SAAS,MAAM;AACnD,YAAM,YAAqB,WAAW,IAAI,CAACK,SAAQ,CAACA,KAAI,KAAKD,WAAU,GAAG,IAAIC,KAAI,KAAKD,WAAU,GAAG,IAAKC,KAAI,MAAM,CAAE,CAAC;AACtH,YAAM,aAAsB,UAAU,IAAI,CAACA,SAAQ,CAACA,KAAI,KAAK,EAAE,OAAO,IAAIA,KAAI,KAAK,EAAE,OAAO,IAAKA,KAAI,MAAM,CAAE,CAAC;AAC9G,MAAAH,MAAK,YAAa,WAAY,IAAI,CAACG,SAAQ,CAAC,WAAW,MAAMA,KAAI,KAAK,EAAE,OAAO,KAAK,WAAW,MAAMA,KAAI,KAAK,EAAE,OAAO,KAAMA,KAAI,MAAM,CAAE,CAAC;AAC1I,MAAAH,MAAK,YAAuB,QAAQA,MAAK,SAAS;AAClD,iBAAW,OAAO,OAAO,KAAK,SAAS,GAAG;AACxC,QAAAA,MAAK,YAAY,OAAO,UAAU,KAAK,IAAI,CAACI,WAAmBJ,MAAK,aAAaA,MAAK,UAAUI,UAASJ,MAAK,UAAUI,UAAS,IAAK;AAAA,MACxI;AAAA,IACF;AACA,WAAO,KAAKN,EAAC,EAAE,QAAQ,CAACG,YAAc,QAAQH,GAAEG,QAAO,CAAC;AAAA,EAC1D;AACA,SAAOD;AACT;AAEA,eAAsBK,UAAQV,QAAeC,SAAuC;AAvLpF;AAwLE,MAAI,CAACC,QAAO,MAAM,CAACA,QAAO,MAAM,GAAC,KAAAA,QAAO,OAAP,mBAAW,OAAO,GAAG,UAAS,GAAC,KAAAA,QAAO,OAAP,mBAAW,OAAO,GAAG;AAAO,WAAO,CAAC;AACpG,eAAa,CAACF,OAAM,MAAM,MAAM,GAAGA,OAAM,MAAM,MAAM,CAAC;AACtD,EAAAW;AACA,QAAM,YAAYV,QAAO,KAAK,YAAY,KAAM,IAAI,IAAIW;AACxD,QAAM,YAAYD,aAAWV,QAAO,KAAK,cAAc;AACvD,MAAIA,QAAO,eAAe,YAAY,WAAW;AAC/C,WAAOY,OAAM;AAAA,EACf;AACA,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,UAAM,mBAAmB,KAAKZ,QAAO,KAAK,YAAY,KAAM,IAAI,IAAIW;AACpE,UAAM,oBAAoBD,YAAU,KAAKV,QAAO,KAAK,cAAc;AACnE,QAAIA,QAAO,eAAeY,OAAM,MAAM,WAAWZ,QAAO,KAAK,aAAa;AACxE,MAAAY,OAAM,QAAQ,MAAM,QAAQ,IAAIA,OAAM,MAAM,IAAI,CAAC,YAAY,cAAcb,QAAO,SAASC,OAAM,CAAC,CAAC;AAAA,IACrG,WAAWA,QAAO,eAAe,oBAAoB,qBAAqBY,OAAM,MAAM,SAAS,GAAG;AAChG,MAAAA,OAAM,QAAQ,MAAM,QAAQ,IAAIA,OAAM,MAAM,IAAI,CAAC,YAAY,cAAcb,QAAO,SAASC,OAAM,CAAC,CAAC;AAAA,IACrG,OAAO;AACL,MAAAY,OAAM,QAAQ,MAAM,YAAYb,QAAOC,OAAM;AAC7C,MAAAW,aAAW,IAAI;AACf,MAAAC,OAAM,QAAQ,MAAM,QAAQ,IAAIA,OAAM,MAAM,IAAI,CAAC,YAAY,cAAcb,QAAO,SAASC,OAAM,CAAC,CAAC;AACnG,MAAAU,YAAU;AAAA,IACZ;AAEA,UAAM,WAAW,CAAC,GAAGE,OAAM,KAAK;AAChC,IAAAA,OAAM,MAAM,SAAS;AACrB,QAAIZ,QAAO,mBAAmB,GAAG;AAC/B,eAASa,KAAI,GAAGA,KAAID,OAAM,MAAM,QAAQC,MAAK;AAC3C,cAAM,SAAaC,QAAOF,OAAM,MAAMC,IAAG,WAAW,UAAU;AAC9D,YAAI,OAAO,IAAI,MAAMd,OAAM,MAAM,MAAM,KAAK,QAAQ,OAAO,IAAI,MAAMA,OAAM,MAAM,MAAM,KAAK,QAAQa,OAAM,MAAMC,IAAG,eAAeD,OAAM,MAAMC,IAAG,eAAeb,QAAO,KAAK,iBAAiB,IAAI;AAC/L,gBAAM,WAAeG,OAAM,OAAO,KAAK,aAAa;AACpD,gBAAM,cAAkBA,OAAM,OAAO,QAAQ,aAAa;AAE1D,UAAAS,OAAM,MAAM,KAAK,EAAE,GAAG,SAASC,KAAI,KAAK,UAAU,QAAQ,YAAY,CAAC;AAAA,QACzE;AAAA,MACF;AAAA,IACF;AACA,aAASA,KAAI,GAAGA,KAAID,OAAM,MAAM,QAAQC,MAAK;AAC3C,YAAM,OAAW,KAAKD,OAAM,MAAMC,IAAG,WAAW,UAAU;AAC1D,MAAAD,OAAM,MAAMC,IAAG,MAAM,KAAK;AAC1B,MAAAD,OAAM,MAAMC,IAAG,SAAS,KAAK;AAAA,IAC/B;AACA,YAAQD,OAAM,KAAK;AAAA,EACrB,CAAC;AACH;;;ACvNA,IAAIG;AACJ,IAAMC,UAAwB,CAAC;AAC/B,IAAIC,YAAU,OAAO;AACrB,IAAIC,aAAY;AAChB,IAAIC,aAAW;AAEf,eAAsBC,OAAKC,SAAqC;AAjBhE;AAkBE,MAAIC,KAAI;AAAS,IAAAP,UAAQ;AACzB,MAAI,CAACA;AAAO,IAAAA,UAAQ,MAAM,WAAU,KAAAM,QAAO,KAAK,aAAZ,mBAAsB,SAAS;AAAA,WAC1DA,QAAO;AAAO,QAAI,iBAAiBN,QAAM,WAAW;AAC7D,SAAOA;AACT;AAEA,eAAsBQ,UAAQC,QAAeH,SAAgB,KAAaI,QAAgC;AAxB1G;AAyBE,MAAI,CAACV;AAAO,WAAO;AACnB,QAAM,cAAY,KAAAM,QAAO,KAAK,aAAZ,mBAAsB,aAAY,KAAM,IAAI,IAAIF;AAClE,QAAM,YAAYF,eAAW,KAAAI,QAAO,KAAK,aAAZ,mBAAsB,eAAc;AACjE,MAAIA,QAAO,eAAe,YAAY,aAAcH,eAAcO,UAAUT,QAAO,MAAM;AACvF,IAAAC;AACA,WAAOD,QAAO;AAAA,EAChB;AACA,EAAAC,YAAU;AACV,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,UAAM,SAAY,MAAM,eAAeO,QAAO,EAACT,WAAA,gBAAAA,QAAO,OAAO,GAAG,SAAQA,QAAM,OAAO,GAAG,MAAM,KAAK,IAAGA,WAAA,gBAAAA,QAAO,OAAO,GAAG,SAAQA,QAAM,OAAO,GAAG,MAAM,KAAK,CAAC,GAAG,KAAK;AACnK,UAAM,MAAMA,WAAA,gBAAAA,QAAO,QAAQ;AAC3B,UAAM,OAAO,MAAM,IAAI,KAAK,GAAG;AAC/B,IAAAC,QAAO,OAAO,KAAK,MAAM,MAAM,GAAG,IAAI;AACtC,IAAAE,aAAYO;AACZ,IAAAN,aAAW,IAAI;AACf,IAAG,QAAQ,CAAC,QAAQ,GAAG,CAAC;AACxB,YAAQH,QAAO,IAAI;AAAA,EACrB,CAAC;AACH;;;AC3CA;AAAA;AAAA,mBAAAU;AAAA,EAAA;AAAA,aAAAC;AAAA,EAAA;AAAA;AAAA;AAAO,IAAMA,OAAqB;AAAA,EAChC;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AAAA,EACA;AACF;AAEO,IAAM,aAA8B;AAAA,EACzC,CAAC,WAAW,UAAU;AAAA,EACtB,CAAC,WAAW,UAAU;AAAA,EACtB,CAAC,gBAAgB,eAAe;AAAA,EAChC,CAAC,aAAa,YAAY;AAAA,EAC1B,CAAC,aAAa,YAAY;AAAA,EAC1B,CAAC,WAAW,UAAU;AAAA,EACtB,CAAC,YAAY,WAAW;AAAA,EACxB,CAAC,aAAa,YAAY;AAC5B;AAEO,IAAM,WAA4B;AAAA,EACvC,CAAC,YAAY,cAAc;AAAA,EAC3B,CAAC,aAAa,eAAe;AAAA,EAC7B,CAAC,aAAa,UAAU;AAAA,EACxB,CAAC,cAAc,WAAW;AAC5B;AAEO,IAAM,WAA8B;AAAA,EACzC,CAAC,CAAC,WAAW,UAAU,GAAG,CAAC,gBAAgB,eAAe,CAAC;AAAA,EAC3D,CAAC,CAAC,aAAa,YAAY,GAAG,CAAC,gBAAgB,eAAe,CAAC;AACjE;AAEO,IAAMD,aAAsC;AAAA,EACjD,SAAS,CAAC,WAAW,YAAY,WAAW;AAAA,EAC5C,UAAU,CAAC,YAAY,aAAa,YAAY;AAAA,EAChD,OAAO,CAAC,gBAAgB,iBAAiB,YAAY,WAAW,cAAc;AAAA,EAC9E,SAAS,CAAC,gBAAgB,aAAa,WAAW;AAAA,EAClD,UAAU,CAAC,iBAAiB,cAAc,YAAY;AAAA,EACtD,MAAM,CAAC;AACT;;;AC5CA,IAAM,YAAY;AAElB,IAAME,SAGF;AAAA,EACF,WAAW,CAAC;AAAA,EACZ,SAAS,CAAC,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,GAAG,CAAC,CAAC;AAC1C;AAEO,SAAS,UAAUC,OAAkB;AAC1C,aAAW,QAAe,YAAY;AACpC,UAAM,OAAOA,MAAK,UAAU,UAAU,CAAC,OAAO,GAAG,SAAS,KAAK,EAAE;AACjE,UAAM,QAAQA,MAAK,UAAU,UAAU,CAAC,OAAO,GAAG,SAAS,KAAK,EAAE;AAClE,QAAIA,MAAK,UAAU,SAASA,MAAK,UAAU,QAAQ;AACjD,UAAIA,MAAK,UAAU,MAAM,SAAS,KAAKA,MAAK,UAAU,OAAO,SAAS,IAAI;AACxE,cAAM,MAAMA,MAAK,UAAU;AAC3B,QAAAA,MAAK,UAAU,QAAQA,MAAK,UAAU;AACtC,QAAAA,MAAK,UAAU,SAAS;AAAA,MAC1B;AAAA,IACF;AAAA,EACF;AACA,aAAW,QAAe,UAAU;AAClC,UAAM,QAAQA,MAAK,UAAU,UAAU,CAAC,OAAQ,MAAM,GAAG,SAAS,KAAK,EAAG;AAC1E,UAAM,SAASA,MAAK,UAAU,UAAU,CAAC,OAAQ,MAAM,GAAG,SAAS,KAAK,EAAG;AAC3E,QAAIA,MAAK,UAAU,UAAUA,MAAK,UAAU,SAAS;AACnD,UAAIA,MAAK,UAAU,OAAO,SAAS,KAAKA,MAAK,UAAU,QAAQ,SAAS,IAAI;AAC1E,QAAAA,MAAK,UAAU,OAAO,OAAO,CAAC;AAAA,MAChC;AAAA,IACF;AAAA,EACF;AACA,aAAW,CAAC,MAAMC,QAAO,KAAY,UAAU;AAC7C,UAAM,OAAOD,MAAK,UAAU,UAAU,CAAC,OAAQ,MAAM,GAAG,SAAS,KAAK,EAAG;AACzE,UAAM,QAAQA,MAAK,UAAU,UAAU,CAAC,OAAQ,MAAM,GAAG,SAAS,KAAK,EAAG;AAC1E,UAAM,SAASA,MAAK,UAAU,UAAU,CAAC,OAAQ,MAAM,GAAG,SAASC,SAAQ,EAAG;AAC9E,UAAM,UAAUD,MAAK,UAAU,UAAU,CAAC,OAAQ,MAAM,GAAG,SAASC,SAAQ,EAAG;AAC/E,QAAI,CAACD,MAAK,UAAU,WAAW,CAACA,MAAK,UAAU;AAAU;AACzD,UAAM,eAAeA,MAAK,UAAU,QAAQ;AAAA,MAC1C,KAAK,IAAIA,MAAK,UAAU,QAAQ,SAAS,KAAKA,MAAK,UAAU,MAAM,SAAS,EAAE;AAAA,MAC9E,KAAK,IAAIA,MAAK,UAAU,SAAS,SAAS,KAAKA,MAAK,UAAU,MAAM,SAAS,EAAE;AAAA,IACjF,IAAI,CAAC,GAAG,CAAC;AACT,UAAM,gBAAgBA,MAAK,UAAU,SAAS;AAAA,MAC5C,KAAK,IAAIA,MAAK,UAAU,SAAS,SAAS,KAAKA,MAAK,UAAU,OAAO,SAAS,EAAE;AAAA,MAChF,KAAK,IAAIA,MAAK,UAAU,QAAQ,SAAS,KAAKA,MAAK,UAAU,OAAO,SAAS,EAAE;AAAA,IACjF,IAAI,CAAC,GAAG,CAAC;AACT,QAAI,aAAa,KAAK,aAAa,MAAM,cAAc,KAAK,cAAc,IAAI;AAC5E,YAAM,MAAMA,MAAK,UAAU;AAC3B,MAAAA,MAAK,UAAU,QAAQA,MAAK,UAAU;AACtC,MAAAA,MAAK,UAAU,SAAS;AAAA,IAC1B;AAAA,EACF;AACF;AAEO,SAAS,OAAO,WAAqD;AAC1E,WAASE,KAAI,GAAGA,KAAI,UAAU,QAAQA,MAAK;AACzC,QAAI,UAAUA,OAAMH,OAAM,UAAUG,KAAI;AACtC,YAAM,OAAO,CAAC,KAAK,IAAI,UAAUA,IAAG,YAAY,KAAKH,OAAM,UAAUG,IAAG,YAAY,EAAE,GAAG,KAAK,IAAI,UAAUA,IAAG,YAAY,KAAKH,OAAM,UAAUG,IAAG,YAAY,EAAE,CAAC;AAClK,UAAI,KAAK,KAAK,aAAa,KAAK,KAAK,WAAW;AAC9C,kBAAUA,MAAKH,OAAM,UAAUG;AAAA,MACjC,OAAO;AACL,QAAAH,OAAM,UAAUG,MAAK,UAAUA;AAAA,MACjC;AAAA,IACF,OAAO;AACL,MAAAH,OAAM,UAAUG,MAAK,UAAUA;AAAA,IACjC;AAAA,EACF;AACA,SAAO;AACT;AAEO,SAAS,SAASC,QAAeC,aAA2B;AACjE,QAAMC,KAA4B,CAAC;AACnC,MAAI,CAACF,OAAM,SAAS,CAACA,OAAM,MAAM,MAAM,CAACA,OAAM,MAAM;AAAI,WAAOA;AAC/D,EAAAJ,OAAM,UAAU;AAAA,IACd,CAAC,GAAG,CAAC;AAAA,IACL,CAACI,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI,GAAGA,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI,CAAC;AAAA,IACjL,CAACA,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI,GAAGA,OAAM,MAAM,KAAKA,OAAM,MAAM,KAAK,KAAK,OAAOA,OAAM,MAAM,KAAKA,OAAM,MAAM,MAAM,CAAC,IAAI,CAAC;AAAA,IACjL,CAAC,GAAG,CAAC;AAAA,EACP;AACA,EAAAE,GAAE,MAAS,IAAIF,QAAOJ,OAAM,OAAO;AACnC,EAAAM,GAAE,SAAY,MAAM,eAAeA,GAAE,KAAK,CAACD,aAAWA,WAAS,CAAC;AAChE,QAAM,QAAW,KAAKC,GAAE,QAAQ,OAAO;AACvC,SAAO,KAAKA,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,SAAO;AACT;AAEO,SAAS,YAAYN,OAAkBO,aAA0C;AACtF,EAAAP,MAAK,YAAYA,MAAK,UAAU,OAAO,CAACQ,SAAQA,QAAOA,KAAI,QAAQ;AACnE,aAAWA,QAAOR,MAAK,WAAW;AAChC,IAAAQ,KAAI,WAAW;AAAA,MACbA,KAAI,SAAS,MAAMD,YAAW,KAAKR,OAAM,QAAQ,GAAG,KAAKA,OAAM,QAAQ,GAAG,MAAMQ,YAAW,KAAKR,OAAM,QAAQ,GAAG;AAAA,MACjHS,KAAI,SAAS,MAAMD,YAAW,KAAKR,OAAM,QAAQ,GAAG,KAAKA,OAAM,QAAQ,GAAG,MAAMQ,YAAW,KAAKR,OAAM,QAAQ,GAAG;AAAA,IACnH;AACA,IAAAS,KAAI,cAAc;AAAA,MAChBA,KAAI,SAAS,KAAKD,YAAW;AAAA,MAAIC,KAAI,SAAS,KAAKD,YAAW;AAAA,IAChE;AAAA,EACF;AACA,QAAM,gBAAoB,KAAKP,MAAK,UAAU,IAAI,CAAC,OAAO,GAAG,QAAQ,GAAGO,WAAU;AAClF,EAAAP,MAAK,MAAM,cAAc;AACzB,EAAAA,MAAK,SAAS,cAAc;AAC5B,SAAOA;AACT;;;ACxFA,IAAIS;AACJ,IAAIC,aAAY;AAChB,IAAIC,YAAU,OAAO;AAGrB,IAAMC,SAIF;AAAA,EACF,OAAO,CAAC;AAAA,EACR,QAAQ,CAAC;AAAA,EACT,MAAM;AACR;AAEA,eAAsBC,OAAKC,SAAqC;AAC9D,MAAIC,KAAI;AAAS,IAAAN,UAAQ;AACzB,MAAI,CAACA,SAAO;AACV,YAAQ,CAAC,MAAM,GAAGK,OAAM;AACxB,IAAAL,UAAQ,MAAM,UAAUK,QAAO,KAAK,SAAS;AAAA,EAC/C,WAAWA,QAAO;AAAO,QAAI,iBAAiBL,QAAM,WAAW;AAC/D,EAAAC,aAAYD,QAAM,OAAO,GAAG,QAAQA,QAAM,OAAO,GAAG,MAAM,KAAK;AAC/D,MAAIC,aAAY;AAAI,IAAAA,aAAY;AAChC,SAAOD;AACT;AAEA,eAAe,gBAAgB,KAAKK,SAAQE,QAAO;AACjD,QAAMC,OAAM,IAAI,GAAG;AACnB,QAAM,YAAiC,CAAC;AACxC,MAAI,QAAQ;AACZ,WAAS,KAAK,GAAG,KAAKA,KAAI,QAAQ,MAAM;AACtC,YAAQA,KAAI,IAAI;AAChB,QAAI,QAAQH,QAAO,KAAK,eAAe;AACrC,YAAM,cAAqB,CAACG,KAAI,IAAI,IAAIA,KAAI,IAAI,EAAE;AAClD,gBAAU,KAAK;AAAA,QACb,OAAO,KAAK,MAAM,MAAM,KAAK,IAAI;AAAA,QACjC,MAAaA,KAAI;AAAA,QACjB;AAAA,QACA,UAAU;AAAA,UACR,KAAK,OAAOD,OAAM,MAAM,MAAM,KAAK,YAAY,EAAE;AAAA,UACjD,KAAK,OAAOA,OAAM,MAAM,MAAM,KAAK,YAAY,EAAE;AAAA,QACnD;AAAA,MACF,CAAC;AAAA,IACH;AAAA,EACF;AACA,UAAQ,UAAU,OAAO,CAAC,MAAM,SAAU,KAAK,QAAQ,OAAO,KAAK,QAAQ,MAAO,CAAC;AACnF,QAAM,SAA4B,CAAC;AACnC,QAAM,SAAa,KAAK,UAAU,IAAI,CAAC,OAAO,GAAG,QAAQ,GAAG,CAACA,OAAM,MAAM,IAAIA,OAAM,MAAM,EAAE,CAAC;AAC5F,QAAME,eAAyC,CAAC;AAChD,aAAW,CAAC,MAAM,OAAO,KAAK,OAAO,QAAeC,UAAS,GAAG;AAC9D,UAAM,KAAqB,CAAC;AAC5B,aAASC,KAAI,GAAGA,KAAI,QAAQ,SAAS,GAAGA,MAAK;AAC3C,YAAM,MAAM,UAAU,KAAK,CAAC,OAAO,GAAG,SAAS,QAAQA,GAAE;AACzD,YAAM,MAAM,UAAU,KAAK,CAAC,OAAO,GAAG,SAAS,QAAQA,KAAI,EAAE;AAC7D,UAAI,OAAO,OAAO,IAAI,SAASN,QAAO,KAAK,iBAAiB,MAAM,IAAI,SAASA,QAAO,KAAK,iBAAiB;AAAI,WAAG,KAAK,CAAC,IAAI,UAAU,IAAI,QAAQ,CAAC;AAAA,IACtJ;AACA,IAAAI,aAAY,QAAQ;AAAA,EACtB;AACA,QAAMG,QAAmB,EAAE,IAAI,GAAG,OAAO,KAAK,OAAO,KAAK,QAAQ,OAAO,QAAQ,WAAW,aAAAH,aAAY;AACxG,EAAI,UAAUG,KAAI;AAClB,SAAO,KAAKA,KAAI;AAChB,SAAO;AACT;AAEA,eAAe,eAAe,KAAKP,SAAQE,QAAO;AAChD,QAAM,SAA4B,CAAC;AACnC,WAAS,KAAK,GAAG,KAAK,IAAI,GAAG,QAAQ,MAAM;AACzC,UAAMC,OAAM,IAAI,GAAG;AACnB,UAAM,aAAa,KAAK,MAAM,MAAMA,KAAI,KAAK,EAAE,IAAI;AACnD,QAAI,aAAaH,QAAO,KAAK,eAAe;AAC1C,YAAM,YAAiC,CAAC;AACxC,eAASM,KAAI,GAAGA,KAAI,IAAIA,MAAK;AAC3B,cAAM,QAAQH,KAAI,IAAIG,KAAI;AAC1B,YAAI,QAAQN,QAAO,KAAK,eAAe;AACrC,gBAAM,cAAqB,CAACG,KAAI,IAAIG,KAAI,IAAIH,KAAI,IAAIG,KAAI,EAAE;AAC1D,oBAAU,KAAK;AAAA,YACb,MAAaH,KAAIG;AAAA,YACjB,OAAO,KAAK,MAAM,MAAM,KAAK,IAAI;AAAA,YACjC;AAAA,YACA,UAAU,CAAC,KAAK,OAAOJ,OAAM,MAAM,MAAM,KAAK,YAAY,EAAE,GAAG,KAAK,OAAOA,OAAM,MAAM,MAAM,KAAK,YAAY,EAAE,CAAC;AAAA,UACnH,CAAC;AAAA,QACH;AAAA,MACF;AACA,YAAM,SAAa,KAAK,UAAU,IAAI,CAAC,OAAO,GAAG,QAAQ,GAAG,CAACA,OAAM,MAAM,IAAIA,OAAM,MAAM,EAAE,CAAC;AAI5F,YAAME,eAAiD,CAAC;AACxD,iBAAW,CAAC,MAAM,OAAO,KAAK,OAAO,QAAeC,UAAS,GAAG;AAC9D,cAAM,KAAqB,CAAC;AAC5B,iBAASC,KAAI,GAAGA,KAAI,QAAQ,SAAS,GAAGA,MAAK;AAC3C,gBAAM,MAAM,UAAU,KAAK,CAAC,OAAO,GAAG,SAAS,QAAQA,GAAE;AACzD,gBAAM,MAAM,UAAU,KAAK,CAAC,OAAO,GAAG,SAAS,QAAQA,KAAI,EAAE;AAC7D,cAAI,OAAO,OAAO,IAAI,SAASN,QAAO,KAAK,iBAAiB,MAAM,IAAI,SAASA,QAAO,KAAK,iBAAiB;AAAI,eAAG,KAAK,CAAC,IAAI,UAAU,IAAI,QAAQ,CAAC;AAAA,QACtJ;AACA,QAAAI,aAAY,QAAQ;AAAA,MACtB;AACA,YAAMG,QAAmB,EAAE,IAAI,OAAO,YAAY,KAAK,OAAO,KAAK,QAAQ,OAAO,QAAQ,WAAW,CAAC,GAAG,SAAS,GAAG,aAAAH,aAAY;AACjI,MAAI,UAAUG,KAAI;AAClB,aAAO,KAAKA,KAAI;AAAA,IAClB;AAAA,EACF;AACA,SAAO,KAAK,CAAC,GAAG,MAAM,EAAE,QAAQ,EAAE,KAAK;AACvC,MAAI,OAAO,SAASP,QAAO,KAAK;AAAa,WAAO,SAASA,QAAO,KAAK;AACzE,SAAO;AACT;AAEA,eAAsBQ,UAAQC,QAAeT,SAAuC;AAClF,MAAI,CAACL,WAAS,EAACA,WAAA,gBAAAA,QAAO,OAAO,GAAG;AAAO,WAAO,CAAC;AAC/C,MAAI,CAACK,QAAO;AAAa,IAAAF,OAAM,MAAM,SAAS;AAC9C,EAAAD;AACA,QAAM,YAAYG,QAAO,KAAK,YAAY,KAAM,IAAI,IAAIF,OAAM;AAC9D,QAAM,YAAYD,aAAWG,QAAO,KAAK,cAAc;AACvD,MAAIA,QAAO,eAAe,YAAY,WAAW;AAC/C,WAAOF,OAAM;AAAA,EACf;AACA,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,UAAMY,KAA4B,CAAC;AACnC,IAAAb,YAAU;AAmCV,IAAAa,GAAE,QAAY,SAASD,QAAOb,UAAS;AACvC,IAAAc,GAAE,MAAMf,WAAA,gBAAAA,QAAO,QAAQe,GAAE;AACzB,IAAAZ,OAAM,OAAO,IAAI;AACjB,UAAM,MAAM,MAAMY,GAAE,IAAI,MAAM;AAC9B,IAAAZ,OAAM,SAAUY,GAAE,IAAI,MAAM,OAAO,KAC/B,MAAM,gBAAgB,KAAKV,SAAQS,MAAK,IACxC,MAAM,eAAe,KAAKT,SAAQS,MAAK;AAC3C,eAAWF,SAAQT,OAAM,QAAQ;AAC/B,MAAI,YAAYS,OAAM,CAACE,OAAM,MAAM,MAAM,GAAGA,OAAM,MAAM,MAAM,CAAC,CAAC;AAChE,MAAI,OAAOF,MAAK,SAAS;AAAA,IAC3B;AACA,WAAO,KAAKG,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AAExD,YAAQb,OAAM,MAAM;AAAA,EACtB,CAAC;AACH;;;AC1KA,IAAIc;AACJ,IAAIC,QAA4B,CAAC;AACjC,IAAIC,aAAW;AACf,IAAIC,YAAU,OAAO;AACrB,IAAIC,aAAY;AAEhB,IAAM,WAAW;AAEjB,eAAsBC,OAAKC,SAAqC;AAC9D,MAAI,CAACN,WAASO,KAAI,SAAS;AACzB,IAAAP,UAAQ,MAAM,UAAUM,QAAO,OAAO,SAAS;AAC/C,UAAM,SAAS,OAAO,OAAON,QAAM,eAAe,SAAS;AAC3D,IAAAI,aAAY,MAAM,QAAQ,MAAM,IAAI,SAAS,OAAO,GAAG,YAAY,IAAI,GAAG,IAAI,IAAI;AAAA,EACpF,WAAWE,QAAO;AAAO,QAAI,iBAAiBN,QAAM,WAAW;AAC/D,SAAOA;AACT;AAEA,eAAeQ,SAAQ,KAAe,aAA+BF,SAAgB;AACnF,MAAI,KAAK;AACT,MAAI,UAA+B,CAAC;AACpC,aAAW,cAAc,CAAC,GAAG,GAAG,CAAC,GAAG;AAElC,IAAG,KAAK,YAAY;AAClB,YAAM,WAAW,aAAa;AAE9B,YAAM,UAAa,QAAQ,IAAI,KAAK,CAAC,MAAe,EAAE,MAAM,OAAQ,YAAY,MAAO,EAAE,MAAM,MAAM,OAAO,OAAO,MAAO,CAAC;AAC3H,YAAM,YAAe,QAAQ,IAAI,KAAK,CAAC,MAAe,EAAE,MAAM,OAAQ,YAAY,MAAO,EAAE,MAAM,MAAM,KAAK,OAAO,MAAO,CAAC;AAC3H,YAAM,WAAW,UAAU,QAAQ,CAAC,IAAI,GAAG,UAAU,MAAM,KAAK,CAAC,CAAC;AAClE,YAAM,SAAS,MAAM,SAAS,OAAO,CAAC,EAAE,MAAM;AAC9C,YAAM,SAAS,MAAM,QAAQ,MAAM;AACnC,eAASG,KAAI,GAAGA,KAAI,QAAQ,MAAM,IAAIA,MAAK;AACzC,iBAAS,IAAI,GAAG,IAAI,QAAQ,MAAM,IAAI,KAAK;AACzC,gBAAM,QAAQ,OAAOA,IAAG;AACxB,cAAI,SAASH,QAAO,OAAO,iBAAiB,MAAM,MAAM,IAAI;AAC1D,kBAAM,MAAM,MAAM,KAAK,MAAMG,KAAI,QAAQ,KAAK;AAC9C,kBAAM,MAAM,MAAM,KAAK,MAAMA,KAAI,QAAQ,KAAK;AAC9C,kBAAM,YAAY,OAAOA,IAAG,IAAI,CAAC,MAAc,KAAK,WAAW,aAAaL,WAAU;AACtF,kBAAM,CAAC,GAAG,CAAC,IAAI;AAAA,cACb,KAAM,WAAW,aAAa,UAAU;AAAA,cACxC,KAAM,WAAW,aAAa,UAAU;AAAA,YAC1C;AACA,kBAAM,CAAC,GAAG,CAAC,IAAI;AAAA,cACb,KAAM,WAAW,aAAa,UAAU,KAAM;AAAA,cAC9C,KAAM,WAAW,aAAa,UAAU,KAAM;AAAA,YAChD;AACA,gBAAI,SAAc,CAAC,GAAG,GAAG,GAAG,CAAC;AAC7B,qBAAS,OAAO,IAAI,CAAC,MAAM,KAAK,IAAI,GAAG,KAAK,IAAI,GAAG,CAAC,CAAC,CAAC;AACtD,kBAAM,MAAM;AAAA,cACV,OAAO,KAAK,YAAY;AAAA,cACxB,OAAO,KAAK,YAAY;AAAA,cACxB,OAAO,KAAK,YAAY;AAAA,cACxB,OAAO,KAAK,YAAY;AAAA,YAC1B;AACA,kBAAM,SAAS;AAAA,cACb,IAAI;AAAA,cAEJ,OAAO,KAAK,MAAM,MAAM,KAAK,IAAI;AAAA,cACjC,OAAO,IAAI;AAAA,cACX,OAAO,OAAO,GAAG;AAAA,cAGjB,KAAK,IAAI,IAAI,CAAC,MAAM,KAAK,MAAM,CAAC,CAAC;AAAA,cACjC;AAAA,YACF;AACA,oBAAQ,KAAK,MAAM;AAAA,UACrB;AAAA,QACF;AAAA,MACF;AAAA,IACF,CAAC;AAAA,EACH;AAEA,MAAI,QAAQ,CAACM,OAAS,QAAQA,EAAC,CAAC;AAIhC,QAAM,WAAW,QAAQ,IAAI,CAAC,MAAM,CAAC,EAAE,OAAO,IAAI,EAAE,OAAO,IAAI,EAAE,OAAO,IAAI,EAAE,OAAO,EAAE,CAAC;AACxF,QAAM,YAAY,QAAQ,IAAI,CAAC,MAAM,EAAE,KAAK;AAC5C,MAAI,SAAwB,CAAC;AAC7B,MAAI,YAAY,SAAS,SAAS,GAAG;AACnC,UAAM,MAAM,MAAS,MAAM,uBAAuB,UAAU,WAAWJ,QAAO,OAAO,aAAaA,QAAO,OAAO,cAAcA,QAAO,OAAO,aAAa;AACzJ,aAAS,MAAM,IAAI,KAAK;AACxB,IAAG,QAAQ,GAAG;AAAA,EAChB;AAGA,YAAU,QACP,OAAO,CAAC,MAAM,QAAQ,OAAO,SAAS,GAAG,CAAC,EAC1C,KAAK,CAAC,GAAG,MAAO,EAAE,QAAQ,EAAE,KAAM;AAErC,SAAO;AACT;AAEA,eAAsBK,UAAQC,QAAeN,SAAyC;AACpF,QAAM,YAAYA,QAAO,OAAO,YAAY,KAAM,IAAI,IAAIJ;AAC1D,QAAM,YAAYC,aAAWG,QAAO,OAAO,cAAc;AACzD,MAAIA,QAAO,eAAe,YAAY,aAAcL,MAAK,SAAS,GAAI;AACpE,IAAAE;AACA,WAAOF;AAAA,EACT;AACA,EAAAE,YAAU;AACV,MAAI,CAACI,KAAI,QAAQ,SAAS,KAAK,KAAK,CAACA,KAAI,QAAQ,SAAS,eAAe;AAAG,WAAON;AACnF,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,UAAMY,cAAa,CAACD,OAAM,MAAM,MAAM,GAAGA,OAAM,MAAM,MAAM,CAAC;AAC5D,UAAM,SAAY,MAAM,eAAeA,QAAO,CAACR,YAAWA,UAAS,GAAG,KAAK;AAC3E,UAAMU,QAAU,IAAI,QAAQ,UAAU,KAAK;AAC3C,UAAMC,aAAYD,MAAK,UAAU,CAAC,GAAG,GAAG,GAAG,CAAC,CAAC;AAC7C,IAAG,QAAQA,KAAI;AACf,IAAG,QAAQ,MAAM;AAEjB,QAAI;AACJ,QAAIR,QAAO,OAAO;AAAS,gBAAUN,QAAM,QAAQe,UAAS;AAC5D,IAAAb,aAAW,IAAI;AACf,IAAG,QAAQa,UAAS;AAEpB,UAAM,MAAM,MAAMP,SAAQ,SAAqBK,aAAgCP,OAAM;AACrF,IAAAL,QAAO;AACP,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;AC/HO,IAAM,YAAY;AAAA,EACvB;AAAA,EAAQ;AAAA,EAAW;AAAA,EAAY;AAAA,EAAW;AAAA,EAAY;AAAA,EACtD;AAAA,EAAiB;AAAA,EAAa;AAAA,EAAc;AAAA,EAAa;AAAA,EACzD;AAAA,EAAW;AAAA,EAAY;AAAA,EAAY;AAAA,EAAa;AAAA,EAAa;AAC/D;AAEO,IAAMe,SAAQ,UAAU;AAExB,IAAM,UAAU,UAAU,OAAO,CAAC,QAAQ,WAAWC,OAAM;AAChE,SAAO,aAAaA;AACpB,SAAO;AACT,GAAG,CAAC,CAAC;AAEL,IAAM,qBAAqB;AAAA,EACzB,CAAC,WAAW,cAAc;AAAA,EAAG,CAAC,aAAa,cAAc;AAAA,EACzD,CAAC,aAAa,WAAW;AAAA,EAAG,CAAC,WAAW,UAAU;AAAA,EAClD,CAAC,YAAY,WAAW;AAAA,EAAG,CAAC,YAAY,eAAe;AAAA,EACvD,CAAC,cAAc,eAAe;AAAA,EAAG,CAAC,cAAc,YAAY;AAAA,EAC5D,CAAC,YAAY,WAAW;AAAA,EAAG,CAAC,aAAa,YAAY;AAAA,EACrD,CAAC,gBAAgB,eAAe;AAAA,EAAG,CAAC,WAAW,UAAU;AAC3D;AACO,IAAM,uBAAuB,mBAAmB,IAAI,CAAC,CAAC,YAAY,UAAU,MAAO,CAAC,QAAQ,aAAa,QAAQ,WAAW,CAAE;AAE9H,IAAM,YAAY;AAAA,EACvB,CAAC,QAAQ,SAAS;AAAA,EAAG,CAAC,WAAW,SAAS;AAAA,EAAG,CAAC,QAAQ,UAAU;AAAA,EAChE,CAAC,YAAY,UAAU;AAAA,EAAG,CAAC,QAAQ,cAAc;AAAA,EACjD,CAAC,gBAAgB,WAAW;AAAA,EAAG,CAAC,aAAa,WAAW;AAAA,EACxD,CAAC,gBAAgB,SAAS;AAAA,EAAG,CAAC,WAAW,UAAU;AAAA,EACnD,CAAC,YAAY,WAAW;AAAA,EAAG,CAAC,QAAQ,eAAe;AAAA,EACnD,CAAC,iBAAiB,YAAY;AAAA,EAAG,CAAC,cAAc,YAAY;AAAA,EAC5D,CAAC,iBAAiB,UAAU;AAAA,EAAG,CAAC,YAAY,WAAW;AAAA,EACvD,CAAC,aAAa,YAAY;AAC5B;AAgBO,SAAS,eAAe,WAA6C;AAC1E,QAAM,QAAQ,UAAU,OAAO,CAAC,EAAE,MAAM,MAAM,MAAM,KAAK,GAAG,EAAE,UAAU,EAAE,GAAG,EAAE,EAAE,OAAO;AAAA,IACtF,MAAM,KAAK,IAAI,MAAM,CAAC;AAAA,IACtB,MAAM,KAAK,IAAI,MAAM,CAAC;AAAA,IACtB,MAAM,KAAK,IAAI,MAAM,CAAC;AAAA,IACtB,MAAM,KAAK,IAAI,MAAM,CAAC;AAAA,EACxB,IAAI;AAAA,IACF,MAAM,OAAO;AAAA,IACb,MAAM,OAAO;AAAA,IACb,MAAM,OAAO;AAAA,IACb,MAAM,OAAO;AAAA,EACf,CAAC;AACD,SAAO,CAAC,MAAM,MAAM,MAAM,MAAM,MAAM,OAAO,MAAM,MAAM,MAAM,OAAO,MAAM,IAAI;AAClF;AAEO,SAAS,WAAW,OAAO,CAAC,QAAQ,KAAK,GAAG,CAAC,uBAAuB,oBAAoB,GAAsB;AACnH,QAAM,SAAS,SAAS;AACxB,QAAM,SAAS,QAAQ;AACvB,QAAM,YAAY,CAAC,MAAMC,QAAmB;AAAA,IAC1C,IAAIA;AAAA,IACJ,OAAO,KAAK;AAAA,IACZ,QAAQ,CAAC,KAAK,IAAI,KAAK,sBAAsB,KAAK,IAAI,KAAK,uBAAuB,KAAK,IAAI,KAAK,sBAAsB,KAAK,IAAI,KAAK,qBAAqB;AAAA,IACzJ,KAAK,CAAC,KAAK,MAAM,KAAK,IAAI,KAAK,MAAM,GAAG,KAAK,MAAM,KAAK,IAAI,KAAK,MAAM,GAAG,KAAK,MAAM,KAAK,IAAI,KAAK,MAAM,GAAG,KAAK,MAAM,KAAK,IAAI,KAAK,MAAM,CAAC;AAAA,IAC5I,WAAW,KAAK,UAAU,IAAI,CAAC,EAAE,OAAO,MAAM,SAAS,OAAO;AAAA,MAC5D;AAAA,MACA;AAAA,MACA,UAAU,CAAC,KAAK,MAAM,SAAS,IAAI,MAAM,GAAG,KAAK,MAAM,SAAS,IAAI,MAAM,CAAC;AAAA,MAC3E,aAAa,CAAC,SAAS,IAAI,uBAAuB,SAAS,IAAI,qBAAqB;AAAA,IACtF,EAAE;AAAA,IACF,aAAa,CAAC;AAAA,EAChB;AACA,QAAM,cAAc,MAAM,IAAI,CAAC,MAAMA,OAAM,UAAU,MAAMA,EAAC,CAAC;AAC7D,SAAO;AACT;AAGO,IAAM,UAAN,MAAc;AAAA,EAKnB,YAAYC,UAAS,iBAAiB;AAJtC;AACA;AACA;AAGE,SAAK,gBAAgB,IAAI,MAAMA,QAAO;AACtC,SAAK,mBAAmB;AACxB,SAAK,kBAAkB;AAAA,EACzB;AAAA,EAEA,QAAQ,GAAG;AACT,SAAK,cAAc,EAAE,KAAK,oBAAoB;AAC9C,SAAK,KAAK,KAAK,gBAAgB;AAAA,EACjC;AAAA,EAEA,UAAU;AACR,UAAMC,OAAM,KAAK,cAAc;AAC/B,SAAK,SAAS,GAAG,KAAK,kBAAkB;AACxC,SAAK,KAAK,CAAC;AACX,SAAK,cAAc,KAAK,mBAAmB,KAAK;AAChD,WAAOA;AAAA,EACT;AAAA,EAEA,QAAQ;AAAE,WAAO,KAAK,qBAAqB;AAAA,EAAI;AAAA,EAE/C,OAAO;AAAE,WAAO,KAAK,mBAAmB;AAAA,EAAG;AAAA,EAE3C,MAAM;AAAE,WAAO,KAAK,cAAc,MAAM,GAAG,KAAK,mBAAmB,CAAC;AAAA,EAAG;AAAA,EAEvE,MAAM;AAAE,WAAO,KAAK,cAAc;AAAA,EAAI;AAAA,EAEtC,KAAK,GAAG;AACN,WAAO,IAAI,KAAK,KAAK,KAAK,KAAK,MAAM,IAAI,CAAC,GAAG,CAAC,GAAG;AAC/C,WAAK,SAAS,GAAG,KAAK,MAAM,IAAI,CAAC,CAAC;AAClC,UAAI,KAAK,MAAM,IAAI,CAAC;AAAA,IACtB;AAAA,EACF;AAAA,EAEA,KAAK,GAAG;AACN,WAAO,IAAI,KAAK,KAAK,kBAAkB;AACrC,UAAI,IAAI,IAAI;AACZ,UAAI,IAAI,KAAK,oBAAoB,KAAK,KAAK,GAAG,IAAI,CAAC;AAAG;AACtD,UAAI,CAAC,KAAK,KAAK,GAAG,CAAC;AAAG;AACtB,WAAK,SAAS,GAAG,CAAC;AAClB,UAAI;AAAA,IACN;AAAA,EACF;AAAA,EAEA,WAAWF,IAAG;AAEZ,WAAO,KAAK,gBAAgB,KAAK,cAAcA,GAAE;AAAA,EACnD;AAAA,EAEA,KAAKA,IAAG,GAAG;AACT,WAAO,KAAK,WAAWA,EAAC,IAAI,KAAK,WAAW,CAAC;AAAA,EAC/C;AAAA,EAEA,SAASA,IAAG,GAAG;AACb,UAAMG,KAAI,KAAK,cAAcH;AAC7B,SAAK,cAAcA,MAAK,KAAK,cAAc;AAC3C,SAAK,cAAc,KAAKG;AAAA,EAC1B;AACF;AAEO,SAAS,eAAe,GAAG,GAAG,UAAU,SAAS;AACtD,SAAO;AAAA,IACL,GAAG,QAAQ,IAAI,GAAG,GAAG,QAAQ;AAAA,IAC7B,GAAG,QAAQ,IAAI,GAAG,GAAG,WAAWC,MAAK;AAAA,EACvC;AACF;AAEO,SAAS,eAAe,MAAMC,eAAc,SAAS;AAC1D,QAAM,EAAE,UAAU,UAAU,IAAI,SAAS,IAAI;AAC7C,QAAM,EAAE,GAAG,EAAE,IAAI,eAAe,UAAU,UAAU,UAAU,OAAO;AACrE,SAAO;AAAA,IACL,GAAG,KAAK,WAAWA,gBAAe;AAAA,IAClC,GAAG,KAAK,WAAWA,gBAAe;AAAA,EACpC;AACF;AAUO,SAASC,OAAM,GAAGC,MAAKC,MAAK;AACjC,MAAI,IAAID;AAAK,WAAOA;AACpB,MAAI,IAAIC;AAAK,WAAOA;AACpB,SAAO;AACT;AAEO,SAAS,gBAAgB,IAAI,IAAI,IAAI,IAAI;AAC9C,QAAM,KAAK,KAAK;AAChB,QAAM,KAAK,KAAK;AAChB,SAAO,KAAK,KAAK,KAAK;AACxB;AAEO,SAAS,WAAW,GAAG,GAAG;AAC/B,SAAO,EAAE,GAAG,EAAE,IAAI,EAAE,GAAG,GAAG,EAAE,IAAI,EAAE,EAAE;AACtC;;;ACnLA,IAAIC;AACJ,IAAM,iBAAiB,CAAC,gCAA6C,iCAAoD,0CAA+D,wCAA6D;AACrP,IAAM,qBAAqB;AAC3B,IAAM,eAAe;AACrB,IAAM,mBAAmB,MAAM;AAE/B,SAAS,SAAS,QAAQ,gBAAgB,UAAU,QAAQ,SAAS,eAAe,mBAAmB,GAAG;AACxG,QAAM,kBAAkB,CAACC,YAAW;AAAA,IAClC,GAAG,cAAc,IAAIA,OAAM,GAAGA,OAAM,GAAG,MAAM;AAAA,IAC7C,GAAG,cAAc,IAAIA,OAAM,GAAGA,OAAM,GAAI,cAAc,MAAM,KAAK,IAAK,MAAM;AAAA,EAC9E;AACA,QAAM,2BAA2B,CAACA,QAAOC,SAAQC,YAAW;AAAA,IAC1D,GAASC,OAAM,KAAK,MAAMH,OAAM,IAAI,YAAY,GAAG,GAAGC,UAAS,CAAC;AAAA,IAChE,GAASE,OAAM,KAAK,MAAMH,OAAM,IAAI,YAAY,GAAG,GAAGE,SAAQ,CAAC;AAAA,EACjE;AAEA,QAAM,CAAC,QAAQ,KAAK,IAAI,OAAO;AAE/B,QAAM,wBAAwB,yBAAyB,eAAe,UAAU,QAAQ,KAAK;AAC7F,QAAM,eAAe,gBAAgB,qBAAqB;AAC1D,QAAM,iBAAuB,WAAW,eAAe,UAAU,YAAY;AAC7E,MAAI,iBAAiB;AACrB,WAASE,KAAI,GAAGA,KAAI,kBAAkBA,MAAK;AACzC,UAAM,wBAAwB,yBAAyB,gBAAgB,QAAQ,KAAK;AACpF,UAAM,cAAoB,eAAe,sBAAsB,GAAG,sBAAsB,GAAG,UAAU,OAAO;AAC5G,qBAAuB;AAAA,MACrB,EAAE,GAAG,sBAAsB,IAAI,cAAc,GAAG,sBAAsB,IAAI,aAAa;AAAA,MACvF,EAAE,GAAG,YAAY,GAAG,GAAG,YAAY,EAAE;AAAA,IACvC;AAAA,EACF;AACA,QAAM,wBAAwB,yBAAyB,gBAAgB,QAAQ,KAAK;AACpF,QAAM,QAAQ,OAAO,IAAI,sBAAsB,GAAG,sBAAsB,GAAG,QAAQ;AACnF,SAAO,EAAE,UAAU,gBAAgB,MAAY,UAAU,WAAW,MAAM;AAC5E;AAEO,SAAS,WAAW,MAAM,QAAQ,SAAS,kBAAkB,kBAAkB;AACpF,QAAM,SAAe,UAAU,IAAI,CAAC,CAAC,gBAAgB,aAAa,MAAO,CAAO,QAAQ,iBAAuB,QAAQ,cAAc,CAAE;AACvI,QAAM,WAAW,OAAO,IAAI,CAAC,CAAC,EAAE,YAAY,MAAM,YAAY;AAC9D,QAAM,WAAW,OAAO,IAAI,CAAC,CAAC,aAAa,MAAM,aAAa;AAC9D,QAAM,WAAW,OAAO,MAAM;AAC9B,QAAM,WAAW,SAAS;AAC1B,QAAM,YAAY,IAAI,MAAM,QAAQ;AAEpC,QAAM,YAAkB,eAAe,KAAK,MAAM,cAAc,OAAO;AACvE,YAAU,KAAK,KAAK,MAAM;AAAA,IACxB,OAAO,KAAK;AAAA,IACZ,MAAY,UAAU,KAAK,KAAK;AAAA,IAChC,UAAU;AAAA,EACZ;AAEA,WAAS,OAAO,WAAW,GAAG,QAAQ,GAAG,EAAE,MAAM;AAC/C,UAAM,WAAW,SAAS;AAC1B,UAAM,WAAW,SAAS;AAC1B,QAAI,UAAU,aAAa,CAAC,UAAU,WAAW;AAC/C,gBAAU,YAAY,SAAS,MAAM,UAAU,WAAW,UAAU,QAAQ,SAAS,gBAAgB;AAAA,IACvG;AAAA,EACF;AAEA,WAAS,OAAO,GAAG,OAAO,UAAU,EAAE,MAAM;AAC1C,UAAM,WAAW,SAAS;AAC1B,UAAM,WAAW,SAAS;AAC1B,QAAI,UAAU,aAAa,CAAC,UAAU,WAAW;AAC/C,gBAAU,YAAY,SAAS,MAAM,UAAU,WAAW,UAAU,QAAQ,SAAS,gBAAgB;AAAA,IACvG;AAAA,EACF;AACA,SAAO;AACT;AAEA,SAAS,4BAA4B,YAAY,OAAO,UAAU,UAAU,QAAQ;AAClF,QAAM,CAAC,QAAQ,KAAK,IAAI,OAAO;AAC/B,MAAI,eAAe;AACnB,QAAM,SAAS,KAAK,IAAI,WAAW,oBAAoB,CAAC;AACxD,QAAM,OAAO,KAAK,IAAI,WAAW,qBAAqB,GAAG,MAAM;AAC/D,WAAS,WAAW,QAAQ,WAAW,MAAM,EAAE,UAAU;AACvD,UAAM,SAAS,KAAK,IAAI,WAAW,oBAAoB,CAAC;AACxD,UAAM,OAAO,KAAK,IAAI,WAAW,qBAAqB,GAAG,KAAK;AAC9D,aAAS,WAAW,QAAQ,WAAW,MAAM,EAAE,UAAU;AACvD,UAAI,OAAO,IAAI,UAAU,UAAU,UAAU,IAAI,OAAO;AACtD,uBAAe;AACf;AAAA,MACF;AAAA,IACF;AACA,QAAI,CAAC;AAAc;AAAA,EACrB;AACA,SAAO;AACT;AAEO,SAAS,wBAAwBC,gBAAe,QAAQ;AAC7D,QAAM,CAAC,QAAQ,OAAO,YAAY,IAAI,OAAO;AAC7C,QAAM,QAAQ,IAAU,QAAQ,SAAS,QAAQ,cAAc,CAAC,EAAE,MAAM,MAAM,KAAK;AACnF,WAAS,WAAW,GAAG,WAAW,QAAQ,EAAE,UAAU;AACpD,aAAS,WAAW,GAAG,WAAW,OAAO,EAAE,UAAU;AACnD,eAAS,aAAa,GAAG,aAAa,cAAc,EAAE,YAAY;AAChE,cAAM,QAAQ,OAAO,IAAI,UAAU,UAAU,UAAU;AAEvD,YAAI,QAAQA;AAAe;AAE3B,YAAI,4BAA4B,YAAY,OAAO,UAAU,UAAU,MAAM;AAAG,gBAAM,QAAQ,EAAE,OAAO,MAAM,EAAE,UAAU,UAAU,IAAI,WAAW,EAAE,CAAC;AAAA,MACvJ;AAAA,IACF;AAAA,EACF;AACA,SAAO;AACT;AAEA,SAAS,aAAa,OAAO,EAAE,GAAG,EAAE,GAAG,YAAY;AACjD,SAAO,MAAM,KAAK,CAAC,EAAE,UAAU,MAAM;AAxHvC;AAyHI,UAAM,yBAAwB,eAAU,gBAAV,mBAAuB;AACrD,QAAI,CAAC;AAAuB,aAAO;AACnC,WAAa,gBAAgB,GAAG,GAAG,sBAAsB,GAAG,sBAAsB,CAAC,KAAK;AAAA,EAC1F,CAAC;AACH;AAEA,SAAS,iBAAiB,eAAe,WAAW;AAClD,QAAM,8BAA8B,UAAU,OAAO,CAAC,QAAQ,EAAE,UAAU,MAAM,GAAG,eAAe;AAChG,QAAI,CAAC,aAAa,eAAe,UAAU,UAAU;AAAG,gBAAU;AAClE,WAAO;AAAA,EACT,GAAG,CAAG;AACN,SAAO,8BAA8B,UAAU;AACjD;AAEO,SAAS,OAAO,SAAS,QAAQ,kBAAkB,kBAAkB,aAAaA,gBAAe;AACtG,QAAM,QAAuD,CAAC;AAC9D,QAAM,QAAQ,wBAAwBA,gBAAe,MAAM;AAE3D,SAAO,MAAM,SAAS,eAAe,CAAC,MAAM,MAAM,GAAG;AAEnD,UAAM,OAAO,MAAM,QAAQ;AAG3B,UAAM,kBAAwB,eAAe,KAAK,MAAM,cAAc,OAAO;AAE7E,QAAI,aAAa,OAAO,iBAAiB,KAAK,KAAK,EAAE;AAAG;AAExD,QAAI,YAAY,WAAW,MAAM,QAAQ,SAAS,kBAAkB,gBAAgB;AACpF,gBAAY,UAAU,OAAO,CAAC,MAAM,EAAE,QAAQA,cAAa;AAC3D,UAAM,QAAQ,iBAAiB,OAAO,SAAS;AAC/C,UAAM,MAAY,eAAe,SAAS;AAC1C,QAAI,QAAQA;AAAe,YAAM,KAAK,EAAE,WAAW,KAAK,OAAO,KAAK,MAAM,MAAM,KAAK,IAAI,IAAI,CAAC;AAAA,EAChG;AACA,SAAO;AACT;AAEA,eAAsBC,UAAQC,QAAeC,SAAuC;AAIlF,QAAM,MAAS,KAAK,MAAM;AACxB,QAAI,CAACT,QAAM,OAAO,GAAG;AAAO,aAAO,CAAC;AACpC,UAAM,UAAa,MAAM,eAAeQ,QAAO,CAACR,QAAM,OAAO,GAAG,MAAM,IAAIA,QAAM,OAAO,GAAG,MAAM,EAAE,CAAC;AACnG,UAAM,aAAgB,IAAO,IAAO,KAAK,SAAS,SAAS,GAAG,KAAK,GAAG,CAAG;AACzE,UAAM,UAAyBA,QAAM,QAAQ,YAAY,cAAc;AACvE,UAAM,YAAY,QAAQ,IAAI,CAAC,MAAS,QAAQ,GAAG,CAAC,CAAC,CAAC,CAAC;AACvD,cAAU,KAAQ,QAAQ,UAAU,EAAE;AACtC,WAAO;AAAA,EACT,CAAC;AAED,QAAM,UAAU,MAAM,QAAQ,IAAI,IAAI,IAAI,CAACU,YAAmBA,QAAO,OAAO,CAAC,CAAC;AAC9E,aAAWC,MAAK;AAAK,IAAG,QAAQA,EAAC;AAEjC,QAAM,UAAU,MAAM,OAAO,QAAQ,IAAI,QAAQ,IAAI,QAAQ,IAAI,QAAQ,IAAIF,QAAO,KAAK,aAAaA,QAAO,KAAK,aAAa;AAC/H,MAAI,CAACT,QAAM,OAAO,GAAG;AAAO,WAAO,CAAC;AACpC,QAAM,SAAe,WAAW,SAAS,CAACQ,OAAM,MAAM,IAAIA,OAAM,MAAM,EAAE,GAAG,CAACR,QAAM,OAAO,GAAG,MAAM,IAAIA,QAAM,OAAO,GAAG,MAAM,EAAE,CAAC;AAC/H,SAAO;AACT;AAEA,eAAsBY,OAAKH,SAAqC;AAC9D,MAAI,CAACT,WAASa,KAAI;AAAS,IAAAb,UAAQ,MAAM,UAAUS,QAAO,KAAK,SAAS;AAAA,WAC/DA,QAAO;AAAO,QAAI,iBAAiBT,QAAM,WAAW;AAC7D,SAAOA;AACT;;;ACtKA,IAAIc;AACJ,IAAI,OAAO;AAEX,eAAsBC,OAAKC,SAAqC;AAC9D,MAAI,CAACF,WAASG,KAAI;AAAS,IAAAH,UAAQ,MAAM,UAAUE,QAAO,aAAa,SAAS;AAAA,WACvEA,QAAO;AAAO,QAAI,iBAAiBF,QAAM,WAAW;AAC7D,SAAOA;AACT;AAEA,eAAsBI,SAAQC,QAAc,YAA+BH,SACoB;AA5B/F;AA6BE,MAAI;AAAM,WAAO,EAAE,MAAM,CAAC,GAAG,QAAQ,MAAM,OAAO,KAAK;AACvD,SAAO;AACP,MAAI,CAACF;AAAO,UAAMC,OAAKC,OAAM;AAC7B,QAAM,aAAa,MAAYE,SAAQC,QAAOH,OAAM;AACpD,QAAM,UAAQ,gBAAW,WAAX,mBAAmB,MAAM,OAAM;AAC7C,QAAM,WAAS,gBAAW,WAAX,mBAAmB,MAAM,OAAM;AAC9C,MAAI,CAAC,WAAW;AAAQ,WAAO,EAAE,MAAM,CAAC,GAAG,QAAQ,MAAM,OAAO,KAAK;AACrE,QAAMI,KAA4B,CAAC;AAEnC,EAAAA,GAAE,SAAY,MAAM,eAAe,WAAW,QAAQ,CAACN,QAAM,OAAO,GAAG,QAAQA,QAAM,OAAO,GAAG,MAAM,KAAK,GAAGA,QAAM,OAAO,GAAG,QAAQA,QAAM,OAAO,GAAG,MAAM,KAAK,CAAC,GAAG,KAAK;AACzK,EAAG,QAAQ,WAAW,MAAM;AAC5B,EAAAM,GAAE,OAAU,IAAIA,GAAE,QAAQ,UAAU,KAAK;AACzC,EAAAA,GAAE,MAAMN,QAAM,QAAQM,GAAE,IAAI;AAE5B,EAAAA,GAAE,UAAa,QAAQA,GAAE,KAAK,CAAC;AAC/B,MAAIA,GAAE,QAAQ,MAAM,OAAO,GAAG;AAC5B,IAAAA,GAAE,UAAa,QAAQA,GAAE,OAAO;AAChC,KAACA,GAAE,IAAIA,GAAE,EAAE,IAAO,QAAQA,GAAE,SAAS,CAAC;AACtC,IAAAA,GAAE,SAAY,WAAWA,GAAE,IAAI,CAAC;AAChC,IAAAA,GAAE,MAAS,WAAWA,GAAE,QAAQ,CAAC;AACjC,IAAAA,GAAE,OAAU,MAAM,cAAcA,GAAE,KAAK,CAAC,CAAC,GAAG,GAAG,KAAK,GAAG,CAAC,GAAG,CAAC,CAAC,GAAG,CAAC,OAAO,MAAM,CAAC;AAI/E,IAAAA,GAAE,OAAU,QAAQA,GAAE,MAAM,CAAC;AAAA,EAC/B,OAAO;AACL,IAAAA,GAAE,OAAU,MAAM,eAAeA,GAAE,SAAS,CAAC,QAAQ,KAAK,CAAC;AAAA,EAC7D;AACA,QAAM,OAAO,MAAM,KAAK,MAAMA,GAAE,KAAK,KAAK,CAAC;AAE3C,MAAIH,KAAI,QAAQ,CAACA,KAAI,UAAW,OAAO,cAAc,aAAc;AACjE,QAAID,QAAO;AAAO,UAAI,wBAAwB;AAC9C,WAAO,KAAKI,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,WAAO,EAAE,MAAM,QAAQ,MAAM,OAAO,KAAK;AAAA,EAC3C;AAEA,QAAM,cAAoB,OAAO,OAAO,MAAM;AAE9C,MAAO;AAAS,UAAS,gBAAQ,SAASD,GAAE,MAAM,WAAW;AAC7D,QAAM,WAAW,YAAY,WAAW,IAAI;AAC5C,MAAIJ,QAAO,aAAa,QAAQA,QAAO,aAAa,OAAO;AAAG,aAAS,SAAS,QAAQA,QAAO,aAAa;AAC5G,QAAM,YAAY,SAAS,aAAa,GAAG,GAAG,OAAO,MAAM;AAE3D,QAAM,kBAAwB,OAAO,OAAO,MAAM;AAClD,QAAM,eAAe,gBAAgB,WAAW,IAAI;AACpD,MAAI,WAAW;AAAQ,iBAAa,UAAU,WAAW,QAAQ,GAAG,CAAC;AACrE,eAAa,2BAA2B;AACxC,MAAIA,QAAO,aAAa,QAAQA,QAAO,aAAa,OAAO;AAAG,iBAAa,SAAS,QAAQA,QAAO,aAAa;AAChH,eAAa,UAAU,aAAa,GAAG,CAAC;AACxC,eAAa,2BAA2B;AACxC,eAAa,SAAS;AACtB,QAAM,gBAAgB,aAAa,aAAa,GAAG,GAAG,OAAO,MAAM;AACnE,WAASM,KAAI,GAAGA,KAAI,QAAQ,QAAQA;AAAK,kBAAc,KAAK,IAAIA,KAAI,KAAK,UAAU,KAAK,IAAIA,KAAI;AAChG,eAAa,aAAa,eAAe,GAAG,CAAC;AAE7C,MAAI,eAAiC;AACrC,MAAI,cAAc,iBAAiB;AACjC,mBAAqB,OAAO,OAAO,MAAM;AACzC,UAAM,UAAU,MAAYJ,SAAQ,YAAYF,OAAM;AACtD,IAAG,QAAQ,QAAQ,MAAM;AACzB,UAAM,WAAW,aAAa,WAAW,IAAI;AAC7C,aAAS,UAAU,QAAQ,QAA6B,GAAG,GAAG,aAAa,OAAO,aAAa,MAAM;AACrG,aAAS,UAAU,iBAAiB,GAAG,CAAC;AAAA,EAC1C;AAEA,SAAO,KAAKI,EAAC,EAAE,QAAQ,CAACC,YAAc,QAAQD,GAAEC,QAAO,CAAC;AACxD,SAAO;AAEP,SAAO,EAAE,MAAM,QAAQ,iBAAiB,OAAO,YAAY;AAC7D;;;AxC9DO,IAAM,SAAN,MAAa;AAAA,EAAb;AACL,qCAAqD;AACrD,gCAAgD;AAChD,2CAA2D;AAC3D,qCAAqD;AACrD,qCAAqD;AACrD,yCAAyD;AACzD,yCAAyD;AACzD,mCAAmD;AACnD,sCAAsD;AACtD,oCAAoD;AACpD,oCAAoD;AACpD,mCAAmD;AACnD,wCAAwD;AACxD,oCAAoD;AACpD,wCAAwD;AACxD,qCAAqD;AACrD,oCAAoD;AACpD,mCAAmD;AACnD,mCAAmD;AACnD,mCAAmD;AACnD,wCAAwD;AACxD,qCAAqD;AAAA;AACvD;AAcO,IAAM,gBAAgB,CAAC,aAAgC;AAC5D,MAAI,wBAAwB;AAC5B,MAAI,mBAAmB;AACvB,MAAI,mBAAmB;AACvB,aAAW,KAAK,OAAO,OAAO,UAAU,GAAG;AACzC,6BAAyB,EAAE;AAC3B,wBAAoB,EAAE;AACtB,wBAAoB,EAAE;AAAA,EACxB;AACA,QAAM,mBAAmB,mBAAmB,IAAI,mBAAmB,mBAAmB;AACtF,SAAO;AAAA,IACL,iBAAiB,OAAO,OAAO,UAAU,EAAE;AAAA,IAC3C,kBAAkB;AAAA,IAClB,kBAAkB,OAAO,KAAK,SAAS,MAAM,EAAE;AAAA,IAC/C;AAAA,IACA;AAAA,IACA;AAAA,IACA;AAAA,IACA,kBAAkB;AAAA,IAClB,YAAY,OAAO,OAAO,UAAU;AAAA,EACtC;AACF;AAEO,SAAS,MAAM,UAAuB;AAE3C,aAAWE,WAAS,OAAO,KAAK,SAAS,MAAM;AAAG,aAAS,OAAOA,WAAyB;AAC7F;AAGA,eAAsBC,OAAK,UAAgC;AAtG3D;AAuGE,MAAIC,KAAI;AAAS,UAAM,QAAQ;AAC/B,MAAI,SAAS,OAAO,KAAK,SAAS;AAChC,QAAI,CAAC,SAAS,OAAO,cAAY,oBAAS,OAAO,KAAK,aAArB,mBAA+B,cAA/B,mBAA0C,SAAS,gBAAe;AACjG,OAAC,SAAS,OAAO,UAAU,SAAS,OAAO,YAAY,IAAI,MAAeD,OAAK,SAAS,MAAM;AAAA,IAChG;AACA,QAAI,CAAC,SAAS,OAAO,gBAAgB,SAAS,OAAO,KAAK,eAAa,oBAAS,OAAO,KAAK,aAArB,mBAA+B,cAA/B,mBAA0C,SAAS,gBAAe;AACvI,OAAC,SAAS,OAAO,UAAU,SAAS,OAAO,YAAY,IAAI,MAAeA,OAAK,SAAS,MAAM;AAAA,IAChG;AAAA,EACF;AACA,MAAI,SAAS,OAAO,KAAK,WAAW,CAAC,SAAS,OAAO,eAAa,oBAAS,OAAO,SAAhB,mBAAsB,cAAtB,mBAAiC,SAAS;AAAc,aAAS,OAAO,YAAsB,SAAS,SAAS,MAAM;AAExL,MAAI,SAAS,OAAO,KAAK,WAAW,CAAC,SAAS,OAAO,mBAAmB,SAAS,OAAO,KAAK,eAAe,SAAS,OAAO,KAAK,YAAY;AAAc,aAAS,OAAO,kBAA4B,WAAW,SAAS,MAAM;AACjO,MAAI,SAAS,OAAO,KAAK,WAAW,CAAC,SAAS,OAAO,mBAAiB,oBAAS,OAAO,SAAhB,mBAAsB,cAAtB,mBAAiC,SAAS;AAAkB,aAAS,OAAO,gBAA8BA,MAAK,SAAS,MAAM;AACpM,MAAI,SAAS,OAAO,KAAK,WAAW,CAAC,SAAS,OAAO,aAAW,oBAAS,OAAO,SAAhB,mBAAsB,cAAtB,mBAAiC,SAAS;AAAY,aAAS,OAAO,UAAkBA,OAAK,SAAS,MAAM;AAC5K,MAAI,SAAS,OAAO,KAAK,WAAW,CAAC,SAAS,OAAO,aAAW,oBAAS,OAAO,SAAhB,mBAAsB,cAAtB,mBAAiC,SAAS;AAAY,aAAS,OAAO,UAAkBA,OAAK,SAAS,MAAM;AAC5K,MAAI,SAAS,OAAO,KAAK,WAAW,CAAC,SAAS,OAAO;AAAY,aAAS,OAAO,aAAuBA,MAAK,SAAS,MAAM;AAC5H,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,cAArB,mBAAgC,YAAW,CAAC,SAAS,OAAO;AAAW,aAAS,OAAO,YAAsBA,MAAK,SAAS,MAAM;AACrK,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,aAArB,mBAA+B,YAAW,CAAC,SAAS,OAAO;AAAU,aAAS,OAAO,WAAoBA,OAAK,SAAS,MAAM;AACjK,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,gBAArB,mBAAkC,YAAW,CAAC,SAAS,OAAO;AAAS,aAAS,OAAO,UAAkBA,OAAK,SAAS,MAAM;AACjK,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,YAArB,mBAA8B,YAAW,CAAC,SAAS,OAAO;AAAS,aAAS,OAAO,UAAkBA,MAAK,SAAS,MAAM;AAC7J,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,SAArB,mBAA2B,YAAW,GAAC,cAAS,OAAO,KAAK,cAArB,mBAAgC,YAAW,CAAC,SAAS,OAAO;AAAU,aAAS,OAAO,WAAgBA,OAAK,SAAS,MAAM;AACrM,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,SAArB,mBAA2B,YAAW,CAAC,SAAS,OAAO;AAAU,aAAS,OAAO,WAAoBA,OAAK,SAAS,MAAM;AAE7J,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,YAArB,mBAA8B,YAAW,CAAC,SAAS,OAAO;AAAM,aAAS,OAAO,OAAY,KAAK,SAAS,MAAM;AAEpJ,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,cAArB,mBAAgC,YAAW,CAAC,SAAS,OAAO;AAAW,aAAS,OAAO,YAAsBA,MAAK,SAAS,MAAM;AAErK,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,cAArB,mBAAgC,YAAW,CAAC,SAAS,OAAO;AAAc,aAAS,OAAO,eAA4BA,MAAK,SAAS,MAAM;AAE9K,MAAI,SAAS,OAAO,KAAK,aAAW,cAAS,OAAO,KAAK,qBAArB,mBAAuC,YAAW,CAAC,SAAS,OAAO;AAAe,aAAS,OAAO,gBAA8BA,MAAK,SAAS,MAAM;AACxL,MAAI,SAAS,OAAO,KAAK,WAAW,CAAC,SAAS,OAAO,eAAa,oBAAS,OAAO,KAAK,aAArB,mBAA+B,cAA/B,mBAA0C,SAAS;AAAc,aAAS,OAAO,YAAsBE,YAAW,SAAS,MAAM;AACnM,MAAI,SAAS,OAAO,KAAK,WAAW,SAAS,OAAO,KAAK,aAAa,CAAC,SAAS,OAAO,kBAAgB,oBAAS,OAAO,KAAK,aAArB,mBAA+B,cAA/B,mBAA0C,SAAS;AAAc,aAAS,OAAO,eAAyB,aAAa,SAAS,MAAM;AAC7O,MAAI,SAAS,OAAO,OAAO,WAAW,CAAC,SAAS,OAAO,eAAa,oBAAS,OAAO,WAAhB,mBAAwB,cAAxB,mBAAmC,SAAS;AAAc,aAAS,OAAO,YAAsBF,MAAK,SAAS,MAAM;AACxL,MAAI,SAAS,OAAO,OAAO,WAAW,CAAC,SAAS,OAAO,aAAW,oBAAS,OAAO,WAAhB,mBAAwB,cAAxB,mBAAmC,SAAS;AAAY,aAAS,OAAO,UAAkBA,OAAK,SAAS,MAAM;AAChL,MAAI,SAAS,OAAO,aAAa,WAAW,CAAC,SAAS,OAAO;AAAc,aAAS,OAAO,eAA4BA,OAAK,SAAS,MAAM;AAG3I,mBAAiBD,WAAS,OAAO,KAAK,SAAS,MAAM,GAAG;AACtD,QAAI,SAAS,OAAOA,YAA0B,OAAO,SAAS,OAAOA,aAA2B,aAAa;AAC3G,eAAS,OAAOA,WAAyB,MAAM,SAAS,OAAOA;AAAA,IACjE;AAAA,EACF;AACF;AAEA,eAAsBI,UAAS,UAAgC;AAE7D,QAAM,YAAY,CAAC,SAAS,eAAe,QAAQ,OAAO,WAAW,OAAO,OAAO,OAAO,KAAK;AAC/F,aAAW,WAAW,OAAO,KAAK,SAAS,MAAM,GAAG;AAClD,UAAMJ,UAA2B,SAAS,OAAO;AACjD,QAAI,CAACA;AAAO;AACZ,UAAM,MAAgB,CAAC;AAEvB,UAAM,WAAWA,WAAA,gBAAAA,QAAO;AACxB,QAAI,YAAY,SAAS,MAAM,OAAO;AACpC,iBAAW,UAAU,OAAO,OAAO,SAAS,MAAM,KAAK,GAAG;AACxD,cAAMK,MAAM,OAAc,GAAG,YAAY;AACzC,YAAI,CAAC,IAAI,SAASA,GAAE;AAAG,cAAI,KAAKA,GAAE;AAAA,MACpC;AAAA,IACF,OAAO;AACL,UAAI,CAAC,YAAY,SAAS,OAAO;AAAO,YAAI,mCAAmC,OAAO;AAAA,IACxF;AACA,UAAM,UAAoB,CAAC;AAC3B,eAAWA,OAAM,KAAK;AACpB,UAAI,CAAC,UAAU,SAASA,GAAE,KACrB,CAAC,SAAS,IAAI,QAAQ,SAASA,GAAE,KACjC,CAAC,SAAS,IAAI,QAAQ,SAASA,IAAG,QAAQ,KAAK,EAAE,CAAC,KAClD,CAAC,SAAS,IAAI,QAAQ,SAASA,IAAG,QAAQ,UAAU,EAAE,CAAC,KACvD,CAAC,SAAS,IAAI,QAAQ,SAASA,IAAG,QAAQ,MAAM,EAAE,CAAC,GAAG;AACzD,gBAAQ,KAAKA,GAAE;AAAA,MACjB;AAAA,IACF;AAEA,QAAI,SAAS,OAAO,SAAS,QAAQ,SAAS;AAAG,UAAI,4BAA4B,SAAS,OAAO;AAAA,EACnG;AACF;;;AyCvKO,IAAMC,UAAS;AAAA,EACpB,MAAM;AAAA,EACN,UAAU;AAAA,EACV,QAA0B;AAAA,EAC1B,IAAmC;AAAA,EACnC,YAAuB,CAAC;AAAA,EACxB,WAAW;AAAA,IACT,OAAO;AAAA,IACP,WAAW;AAAA,IACX,oBAAoB;AAAA,IACpB,uBAAuB;AAAA,IACvB,OAAO;AAAA,IACP,SAAS;AAAA,IACT,8BAA8B;AAAA,IAC9B,gBAAgB;AAAA,EAClB;AACF;AAEA,SAAS,aAAmB;AAK1B,QAAM,KAAKA,QAAO;AAClB,MAAI,CAAC;AAAI;AACT,EAAAA,QAAO,aAAa,GAAG,uBAAuB;AAEhD;AAOA,eAAsB,SAAS,UAAgC;AA5C/D;AA8CE,MAAI,SAAS,OAAO,YAAY;AAAW;AAC3C,MAAKA,QAAO,QAAW,OAAO,EAAE,aAAc,CAACA,QAAO,MAAM,CAACA,QAAO,GAAG,aAAaA,QAAO,GAAG,OAAO,IAAI;AACvG,QAAI,wCAAwC;AAC5C,IAAO,MAAM,QAAQ;AAAA,EAMvB;AACA,MAAI,CAAI,YAAYA,QAAO,IAAI,GAAG;AAChC,QAAI;AACF,MAAAA,QAAO,SAAS,MAAY,OAAO,KAAK,GAAG;AAAA,IAC7C,SAAS,KAAP;AACA,UAAI,gCAAgC,GAAG;AACvC;AAAA,IACF;AACA,QAAI;AACF,MAAAA,QAAO,MAAK,KAAAA,QAAO,WAAP,mBAAe,WAAW,UAAUA,QAAO;AACvD,YAAM,OAAOA,QAAO,GAAG,aAAaA,QAAO,GAAG,OAAO,EAAE,SAAS,KAAK;AACrE,UAAI,CAAC,MAAM;AACT,YAAI,qEAAqE;AACzE,iBAAS,OAAO,UAAU;AAC1B;AAAA,MACF;AACA,UAAIA,QAAO,QAAQ;AACjB,QAAAA,QAAO,OAAO,iBAAiB,oBAAoB,OAAOC,OAAM;AAC9D,cAAI,mBAAmBA,GAAE,IAAI;AAC7B,cAAI,0FAA0F;AAC9F,mBAAS,KAAK,OAAO;AACrB,gBAAM,IAAI,MAAM,mCAAmC;AAAA,QAMrD,CAAC;AACD,QAAAD,QAAO,OAAO,iBAAiB,wBAAwB,CAACC,OAAM;AAC5D,cAAI,oCAAoCA,EAAC;AAAA,QAC3C,CAAC;AACD,QAAAD,QAAO,OAAO,iBAAiB,6BAA6B,CAACC,OAAM;AACjE,cAAI,kCAAkCA,EAAC;AAAA,QACzC,CAAC;AAAA,MACH;AAAA,IACF,SAAS,KAAP;AACA,UAAI,oCAAoC,GAAG;AAC3C;AAAA,IACF;AACA,QAAI;AACF,MAAG,gBAAgB,GAAGD,QAAO,EAAE;AAAA,IACjC,SAAS,KAAP;AACA,UAAI,oCAAoC,GAAG;AAC3C;AAAA,IACF;AACA,QAAI;AACF,YAAM,MAAM,IAAO,aAAaA,QAAO,EAAE;AACzC,MAAG,gBAAgBA,QAAO,MAAM,MAAM,IAAO,iBAAiB,GAAG,GAAGA,QAAO,QAAQ;AAAA,IACrF,SAAS,KAAP;AACA,UAAI,yCAAyC,GAAG;AAChD;AAAA,IACF;AACA,QAAI;AACF,YAAM,UAAa,qBAAqB,OAAO;AAC/C,cAAQ,QAAQ,CAAC,iBAAiB;AAChC,cAAM,kBAAkB,EAAE,GAAG,cAAc,aAAaA,QAAO,KAAK;AACpE,QAAG,eAAe,eAAe;AAAA,MACnC,CAAC;AAAA,IACH,SAAS,KAAP;AACA,UAAI,oDAAoD,GAAG;AAC3D;AAAA,IACF;AACA,UAAM,UAAa,QAAQ,EAAE,kBAAqB,QAAQ,EAAE,gBAAgB,EAAE,KAAK;AACnF,QAAI,SAAS;AACX,UAAI,yBAAyB,QAAQ,aAAa,QAAQ,OAAO,cAAc,QAAQ,aAAa,QAAQ,QAAQ,GAAG;AAAA,IACzH,OAAO;AACL,UAAI,iCAAiC,SAASA,QAAO,EAAE;AACvD;AAAA,IACF;AACA,QAAI;AACF,UAAO,IAAI,EAAE,aAAa;AAAkB,QAAG,IAAI,EAAE,IAAI,iBAAiB,CAAC;AAAA,IAC7E,SAAS,KAAP;AACA,UAAI,0CAA0C,GAAG;AACjD;AAAA,IACF;AACA,eAAW;AACX,QAAI,uBAAuBA,QAAO,IAAI;AAAA,EACxC;AACF;;;AC5HA,SAAS,oBAAoB;AAC3B,MAAI,CAACE,KAAI,QAAQ,SAAS,KAAK,GAAG;AAChC,UAAM,YAAY;AAAA,MAChB,YAAY;AAAA,MACZ,aAAgB,WAAW;AAAA,MAC3B,YAAY,CAACC,QAAU,KAAK,MAAS,IAAIA,IAAG,OAAO,GAAM,IAAO,IAAIA,IAAG,OAAO,GAAGA,IAAG,OAAO,CAAC,GAAGA,IAAG,OAAO,CAAC,CAAC,CAAC;AAAA,IAC9G;AACA,IAAG,eAAe,SAAS;AAC3B,IAAAD,KAAI,QAAQ,KAAK,KAAK;AAAA,EACxB;AACA,MAAI,CAACA,KAAI,QAAQ,SAAS,UAAU,GAAG;AACrC,UAAM,YAAY;AAAA,MAChB,YAAY;AAAA,MACZ,aAAgB,WAAW;AAAA,MAC3B,YAAY,CAACC,QAAU,KAAK,MAAS,SAASA,IAAG,OAAO,IAAIA,IAAG,OAAO,CAAC,IAAIA,IAAG,OAAO,IAAO,IAAIA,IAAG,OAAO,GAAGA,IAAG,OAAO,CAAC,CAAC;AAAA,IAC3H;AACA,IAAG,eAAe,SAAS;AAC3B,IAAAD,KAAI,QAAQ,KAAK,UAAU;AAAA,EAC7B;AACF;AAEA,eAAsB,MAAM,UAAiB,QAAQ,OAAO;AAC1D,WAAS,QAAQ;AACjB,MAAI,SAASA,KAAI,WAAY,SAAS,OAAO,WAAY,SAAS,OAAO,QAAQ,SAAS,KAAU,WAAW,MAAM,SAAS,OAAO,SAAW;AAC9I,UAAM,YAAY,IAAI;AAEtB,QAAI,SAAS,OAAO,WAAW,SAAS,OAAO,QAAQ,SAAS,GAAG;AAGjE,UAAI,OAAO,WAAW,eAAe,OAAO,sBAAsB,eAAe,SAAS,OAAO,OAAO;AACtG,YAAI,SAAS,OAAO;AAAO,cAAI,2BAA2B;AAAA,MAC5D;AAGA,UAAIA,KAAI,WAAW,SAAS,OAAO,YAAY,cAAc;AAC3D,YAAI,SAAS,OAAO;AAAO,cAAI,8DAA8D;AAC7F,iBAAS,OAAO,UAAU;AAAA,MAC5B;AACA,UAAIA,KAAI,SAAS,SAAS,OAAO,YAAY,WAAW,SAAS,OAAO,YAAY,YAAY;AAC9F,YAAI,SAAS,OAAO;AAAO,cAAI,4BAA4B,SAAS,OAAO,iCAAiC;AAC5G,iBAAS,OAAO,UAAU;AAAA,MAC5B;AAGA,UAAIA,KAAI,WAAW,SAAS,OAAO,YAAY,UAAU;AACvD,YAAI,OAAO,cAAc,eAAe,OAAO,UAAU,WAAW,aAAa;AAC/E,cAAI,qEAAqE;AACzE,mBAAS,OAAO,UAAU;AAAA,QAC5B,OAAO;AACL,gBAAM,UAAU,MAAM,UAAU,OAAO,eAAe;AACtD,cAAI,SAAS,OAAO;AAAO,gBAAI,8BAA8B,OAAO;AACpE,cAAI,CAAC,SAAS;AACZ,gBAAI,sEAAsE;AAC1E,qBAAS,OAAO,UAAU;AAAA,UAC5B,OAAO;AAGL,kBAAM,cAAc,wBAAwB,UAAU,MAAO,QAAuB,mBAAmB,IAAI;AAE3G,gBAAI,wBAAwB,WAAW;AAAA,UACzC;AAAA,QACF;AAAA,MACF;AAGA,UAAI,SAAS,OAAO,YAAY;AAAW,cAAc,SAAS,QAAQ;AAC1E,YAAM,YAAY,OAAO,KAAQ,OAAO,EAAE,eAAe;AACzD,UAAI,SAAS,OAAO;AAAO,YAAI,uBAAuB,SAAS;AAE/D,UAAI,CAAC,UAAU,SAAS,SAAS,OAAO,OAAO,GAAG;AAChD,YAAI,kBAAkB,SAAS,OAAO,+BAA+B;AACrE,iBAAS,OAAO,UAAUA,KAAI,OAAO,eAAe;AACpD,YAAI,SAAS,OAAO;AAAO,cAAI,6BAA6B,SAAS,OAAO,SAAS;AAAA,MACvF;AAEA,UAAI,SAAS,OAAO;AAAO,YAAI,oBAAoB,SAAS,OAAO,OAAO;AAG1E,UAAI,SAAS,OAAO,YAAY,QAAQ;AACtC,YAAO,IAAI,EAAE,aAAa;AAAkC,UAAG,IAAI,EAAE,IAAI,iCAAiC,IAAI;AAC9G,YAAI,SAAS,OAAO;AAAO,cAAI,cAAc,SAAS,OAAO,QAAQ;AACrE,YAAI,QAAO,qDAAI,kBAAiB;AAAa,gBAAS,aAAa,SAAS,OAAO,UAAU,SAAS,OAAO,iBAAiB;AAAA;AACzH,gBAAM,IAAI,MAAM,wEAAwE;AAC7F,cAAM,OAAO,MAAS,IAAI,EAAE,SAAS,uBAAuB;AAC5D,cAAM,KAAK,MAAS,IAAI,EAAE,SAAS,8BAA8B;AACjE,YAAI,SAAS,OAAO;AAAO,cAAI,mBAAmB,OAAO,SAAS,aAAa,KAAK,kBAAkB,kBAAkB;AACxH,YAAI,SAAS,OAAO,SAAS,CAAC;AAAM,cAAI,2CAA2C;AAAA,MACrF;AAEA,UAAI;AACF,cAAS,WAAW,SAAS,OAAO,OAAO;AAC3C,cAAS,MAAM;AACf,QAAUE,MAAK;AAAA,MACjB,SAAS,KAAP;AACA,YAAI,8BAA8B,SAAS,OAAO,SAAS,GAAG;AAC9D,eAAO;AAAA,MACT;AAAA,IACF;AAGA,QAAO,WAAW,MAAM,WAAW;AACjC,UAAO,IAAI,EAAE,aAAa;AAAiC,QAAG,IAAI,EAAE,IAAI,gCAAgC,KAAK;AAC7G,UAAO,IAAI,EAAE,aAAa;AAAsB,QAAG,IAAI,EAAE,IAAI,qBAAqB,IAAI;AACtF,UAAO,IAAI,EAAE,aAAa;AAA8B,QAAG,IAAI,EAAE,IAAI,6BAA6B,IAAI;AACtG,UAAO,IAAI,EAAE,aAAa;AAA+B,QAAG,IAAI,EAAE,IAAI,8BAA8B,GAAG;AACvG,UAAO,IAAI,EAAE,aAAa;AAAmB,QAAG,IAAI,EAAE,IAAI,kBAAkB,IAAI;AAChF,UAAO,IAAI,EAAE,aAAa;AAAsB,QAAG,IAAI,EAAE,IAAI,qBAAqB,IAAI;AAGtF,UAAI,OAAO,SAAS,OAAO,kBAAkB,eAAe,SAAS,OAAO,eAAe;AACzF,YAAI,mDAAmD,IAAI;AAC3D,QAAG,IAAI,EAAE,IAAI,kCAAkC,CAAC;AAAA,MAClD;AACA,UAAO,QAAQ,EAAE,iBAAiB;AAChC,cAAM,KAAK,MAAS,QAAQ,EAAE,gBAAgB,EAAE;AAChD,YAAI,SAAS,OAAO;AAAO,cAAI,cAAc,GAAG,aAAa,GAAG,OAAO,cAAc,GAAG,aAAa,GAAG,QAAQ,GAAG;AAAA,MACrH;AAAA,IACF;AAGA,QAAO,WAAW,MAAM,UAAU;AAAA,IAIlC;AAGA,IAAG,eAAe;AAClB,UAAS,MAAM;AAEf,aAAS,YAAY,cAAc,KAAK,MAAM,IAAI,IAAI,SAAS;AAC/D,aAAS,OAAO,UAAa,WAAW;AAExC,UAAMF,KAAI,cAAc;AACxB,sBAAkB;AAAA,EAEpB;AACA,SAAO;AACT;AAGO,SAAS,QAAQ,aAA4BG,SAAQ;AAE1D,aAAW,cAAc,aAAa;AACpC,UAAM,eAAe;AAAA,MACnB;AAAA,MACA,aAAaA,QAAO;AAAA,MACpB,YAAY,MAAM;AAAE,YAAIA,QAAO;AAAO,cAAI,cAAc,YAAYA,QAAO,OAAO;AAAA,MAAG;AAAA,IAGvF;AACA,IAAG,eAAe,YAAY;AAAA,EAChC;AACA,EAAAH,KAAI,UAAa,qBAAwB,WAAW,CAAC,EAAE,IAAI,CAAC,WAAW,OAAO,WAAW,YAAY,CAAC;AACxG;;;ACnKA;AAAA;AAAA,aAAAI;AAAA,EAAA;AAAA,gBAAAC;AAAA,EAAA;AAAA;AAAA;AAAA;AAAA,iBAAAC;AAAA,EAAA;AAAA;;;ACKO,IAAM,mBAAmB,CAACC,WAAqB;AACpD,MAAI,CAACA;AAAO,QAAI,4BAA4B;AAAA,WACnC,CAACA,OAAM;AAAY,QAAI,wCAAwC;AAAA,OACnE;AACH,UAAM,MAAMA,OAAM,WAAW,IAAI;AACjC,QAAI,CAAC;AAAK,UAAI,uCAAuC;AAAA;AAChD,aAAO;AAAA,EACd;AACA,SAAO;AACT;AAEO,IAAM,UAAU,CAAC,UAAkB,KAAK,MAAO,QAAQ,MAAO,KAAK,EAAE;AAErE,IAAM,aAAa,CAAC,GAAuBC,SAA6B;AAC7E,MAAI,CAACA,KAAI,YAAY,OAAO,MAAM;AAAa,WAAOA,KAAI;AAC1D,QAAMC,OAAM,kBAAkB,KAAK,CAAC,MAAO,IAAI,GAAI,MAAO,IAAI,GAAI,GAAG,CAAC;AACtE,QAAM,QAAQ,QAAQA,KAAI,OAAOA,KAAI,OAAOA,KAAI,OAAOD,KAAI;AAC3D,SAAO;AACT;AAEO,SAAS,MAAM,KAAmE,GAAW,GAAW,GAAuB,cAA2B;AAC/J,MAAI,YAAY,WAAW,GAAG,YAAY;AAC1C,MAAI,UAAU;AACd,MAAI,IAAI,GAAG,GAAG,aAAa,WAAW,GAAG,IAAI,KAAK,EAAE;AACpD,MAAI,KAAK;AACX;AAEO,SAAS,KAAK,KAAmE,GAAW,GAAW,OAAe,QAAgB,cAA2B;AACtK,MAAI,UAAU;AACd,MAAI,YAAY,aAAa;AAC7B,MAAI,aAAa,WAAW;AAC1B,UAAM,MAAM,IAAI,IAAI,SAAS;AAC7B,UAAM,MAAM,IAAI,IAAI,UAAU;AAC9B,QAAI,QAAQ,IAAI,IAAI,QAAQ,GAAG,SAAS,GAAG,GAAG,GAAG,IAAI,KAAK,EAAE;AAAA,EAC9D,OAAO;AACL,QAAI,OAAO,IAAI,aAAa,WAAW,CAAC;AACxC,QAAI,OAAO,IAAI,QAAQ,aAAa,WAAW,CAAC;AAChD,QAAI,iBAAiB,IAAI,OAAO,GAAG,IAAI,OAAO,IAAI,aAAa,SAAS;AACxE,QAAI,OAAO,IAAI,OAAO,IAAI,SAAS,aAAa,SAAS;AACzD,QAAI,iBAAiB,IAAI,OAAO,IAAI,QAAQ,IAAI,QAAQ,aAAa,WAAW,IAAI,MAAM;AAC1F,QAAI,OAAO,IAAI,aAAa,WAAW,IAAI,MAAM;AACjD,QAAI,iBAAiB,GAAG,IAAI,QAAQ,GAAG,IAAI,SAAS,aAAa,SAAS;AAC1E,QAAI,OAAO,GAAG,IAAI,aAAa,SAAS;AACxC,QAAI,iBAAiB,GAAG,GAAG,IAAI,aAAa,WAAW,CAAC;AACxD,QAAI,UAAU;AAAA,EAChB;AACA,MAAI,OAAO;AACb;AAEO,SAAS,MAAM,KAAmE,QAAiB,cAA2B;AACnI,MAAI,OAAO,SAAS;AAAG;AACvB,MAAI,UAAU;AACd,MAAI,OAAO,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE;AACrC,aAAW,MAAM,QAAQ;AACvB,QAAI,cAAc,WAAW,GAAG,MAAM,GAAG,YAAY;AACrD,QAAI,OAAO,KAAK,MAAM,GAAG,EAAE,GAAG,KAAK,MAAM,GAAG,EAAE,CAAC;AAAA,EACjD;AACA,MAAI,OAAO;AACX,MAAI,aAAa,cAAc;AAC7B,QAAI,UAAU;AACd,QAAI,KAAK;AAAA,EACX;AACF;AAEO,SAAS,OAAO,KAAmE,QAAiB,cAA2B;AACpI,MAAI,OAAO,SAAS;AAAG;AACvB,MAAI,YAAY,aAAa;AAC7B,MAAI,CAAC,aAAa,aAAa,OAAO,UAAU,GAAG;AACjD,UAAM,KAAK,QAAQ,YAAY;AAC/B;AAAA,EACF;AACA,MAAI,OAAO,OAAO,GAAG,IAAI,OAAO,GAAG,EAAE;AACrC,WAASE,KAAI,GAAGA,KAAI,OAAO,SAAS,GAAGA,MAAK;AAC1C,UAAM,MAAM,OAAOA,IAAG,KAAK,OAAOA,KAAI,GAAG,MAAM;AAC/C,UAAM,MAAM,OAAOA,IAAG,KAAK,OAAOA,KAAI,GAAG,MAAM;AAC/C,QAAI,iBAAiB,OAAOA,IAAG,IAAI,OAAOA,IAAG,IAAI,IAAI,EAAE;AAAA,EACzD;AACA,MAAI,iBAAiB,OAAO,OAAO,SAAS,GAAG,IAAI,OAAO,OAAO,SAAS,GAAG,IAAI,OAAO,OAAO,SAAS,GAAG,IAAI,OAAO,OAAO,SAAS,GAAG,EAAE;AAC3I,MAAI,OAAO;AACX,MAAI,aAAa,cAAc;AAC7B,QAAI,UAAU;AACd,QAAI,KAAK;AAAA,EACX;AACF;AAEO,SAAS,MAAM,KAAmE,MAAa,IAAW,SAAS,GAAG;AAC3H,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI,UAAU;AACd,MAAI,OAAO,KAAK,IAAI,KAAK,EAAE;AAC3B,MAAI,OAAO,GAAG,IAAI,GAAG,EAAE;AACvB,UAAQ,KAAK,MAAM,GAAG,KAAK,KAAK,IAAI,GAAG,KAAK,KAAK,EAAE;AACnD,MAAI,SAAS,KAAK,IAAI,KAAK,IAAI,GAAG;AAClC,MAAI,SAAS,KAAK,IAAI,KAAK,IAAI,GAAG;AAClC,MAAI,OAAO,GAAG,CAAC;AACf,WAAU,IAAM,KAAQ,IAAI,KAAK;AACjC,MAAI,SAAS,KAAK,IAAI,KAAK,IAAI,GAAG;AAClC,MAAI,SAAS,KAAK,IAAI,KAAK,IAAI,GAAG;AAClC,MAAI,OAAO,GAAG,CAAC;AACf,WAAU,IAAM,KAAQ,IAAI,KAAK;AACjC,MAAI,SAAS,KAAK,IAAI,KAAK,IAAI,GAAG;AAClC,MAAI,SAAS,KAAK,IAAI,KAAK,IAAI,GAAG;AAClC,MAAI,OAAO,GAAG,CAAC;AACf,MAAI,UAAU;AACd,MAAI,OAAO;AACX,MAAI,KAAK;AACX;;;ACnEO,IAAMC,WAAuB;AAAA,EAClC,OAAe;AAAA,EACf,YAAoB;AAAA,EACpB,aAAqB;AAAA,EACrB,OAAO;AAAA,EACP,MAAc;AAAA,EACd,YAAoB;AAAA,EACpB,WAAmB;AAAA,EACnB,WAAmB;AAAA,EACnB,WAAmB;AAAA,EACnB,YAAqB;AAAA,EACrB,YAAqB;AAAA,EACrB,WAAoB;AAAA,EACpB,eAAwB;AAAA,EACxB,cAAuB;AAAA,EACvB,cAAuB;AAAA,EACvB,UAAmB;AAAA,EACnB,cAAuB;AAAA,EACvB,UAAmB;AAAA,EACnB,WAAoB;AACtB;;;ACzDA,IAAI;AAEJ,SAAS,WAAW,GAAe,KAAmE;AACpG,MAAI,IAAI,YAAY;AAElB,UAAMC,UAAkB,CAAC;AACzB,IAAAA,QAAO,KAAK,SAAS,KAAK,MAAM,MAAM,EAAE,KAAK,IAAI;AACjD,QAAI,EAAE;AAAa,MAAAA,QAAO,KAAK,GAAG,EAAE,UAAU,MAAM,KAAK,MAAM,MAAM,EAAE,WAAW,IAAI;AACtF,QAAI,EAAE;AAAK,MAAAA,QAAO,KAAK,QAAQ,EAAE,OAAO,IAAI;AAC5C,QAAI,EAAE;AAAM,MAAAA,QAAO,KAAK,aAAa,EAAE,MAAM;AAC7C,QAAI,EAAE;AAAM,MAAAA,QAAO,KAAK,SAAS,KAAK,MAAM,MAAM,EAAE,IAAI,IAAI;AAC5D,QAAI,EAAE;AAAM,MAAAA,QAAO,KAAK,SAAS,KAAK,MAAM,MAAM,EAAE,IAAI,IAAI;AAC5D,QAAI,EAAE,WAAW,EAAE,QAAQ,SAAS,GAAG;AACrC,YAAMC,WAAU,EAAE,QAAQ,IAAI,CAAC,MAAM,GAAG,KAAK,MAAM,MAAM,EAAE,KAAK,MAAM,EAAE,SAAS;AACjF,UAAIA,SAAQ,SAAS;AAAG,QAAAA,SAAQ,SAAS;AACzC,MAAAD,QAAO,KAAKC,SAAQ,KAAK,GAAG,CAAC;AAAA,IAC/B;AACA,QAAI,EAAE,YAAY,EAAE,SAAS,SAAS,EAAE,SAAS,MAAM;AACrD,UAAI,EAAE,SAAS,MAAM;AAAM,QAAAD,QAAO,KAAK,SAAS,QAAQ,EAAE,SAAS,MAAM,IAAI,aAAU,QAAQ,EAAE,SAAS,MAAM,GAAG,eAAY,QAAQ,EAAE,SAAS,MAAM,KAAK,OAAI;AACjK,UAAI,EAAE,SAAS,KAAK;AAAS,QAAAA,QAAO,KAAK,SAAS,QAAQ,EAAE,SAAS,KAAK,OAAO,OAAI;AAAA,IACvF;AACA,QAAIA,QAAO,WAAW;AAAG,MAAAA,QAAO,KAAK,MAAM;AAC3C,QAAI,YAAY,IAAI;AACpB,aAASE,KAAIF,QAAO,SAAS,GAAGE,MAAK,GAAGA,MAAK;AAC3C,YAAM,IAAI,KAAK,IAAI,EAAE,IAAI,IAAI,CAAC;AAC9B,YAAM,IAAIA,KAAI,IAAI,aAAa,EAAE,IAAI;AACrC,UAAI,IAAI,eAAe,IAAI,gBAAgB,IAAI;AAC7C,YAAI,YAAY,IAAI;AACpB,YAAI,SAASF,QAAOE,KAAI,IAAI,GAAG,IAAI,EAAE;AAAA,MACvC;AACA,UAAI,YAAY,IAAI;AACpB,UAAI,SAASF,QAAOE,KAAI,IAAI,GAAG,IAAI,EAAE;AAAA,IACvC;AAAA,EACF;AACF;AAEA,SAAS,eAAe,GAAe,KAAmE;AAExG,MAAI,EAAE,eAAe,EAAE,YAAY,kBAAkB,EAAE,YAAY,eAAe,IAAI;AACpF,QAAI,cAAc,IAAI,WAAW,6BAA6B,IAAI;AAClE,QAAI,UAAU;AACd,UAAM,QAAQ,KAAK,IAAI,EAAE,YAAY,eAAe,GAAG,KAAK,EAAE,YAAY,eAAe,GAAG,EAAE,IAAI;AAClG,UAAM,QAAQ,KAAK,IAAI,EAAE,YAAY,eAAe,GAAG,KAAK,EAAE,YAAY,eAAe,GAAG,EAAE,IAAI;AAClG,QAAI,QAAQ,EAAE,YAAY,eAAe,GAAG,IAAI,EAAE,YAAY,eAAe,GAAG,IAAI,OAAO,OAAO,GAAG,GAAG,IAAI,KAAK,EAAE;AACnH,QAAI,OAAO;AACX,QAAI,IAAI,cAAc;AACpB,UAAI,YAAY,IAAI,WAAW,6BAA6B,IAAI;AAChE,UAAI,KAAK;AAAA,IACX;AAAA,EACF;AACA,MAAI,EAAE,eAAe,EAAE,YAAY,mBAAmB,EAAE,YAAY,gBAAgB,IAAI;AACtF,QAAI,cAAc,IAAI,WAAW,6BAA6B,IAAI;AAClE,QAAI,UAAU;AACd,UAAM,QAAQ,KAAK,IAAI,EAAE,YAAY,gBAAgB,GAAG,KAAK,EAAE,YAAY,gBAAgB,GAAG,EAAE,IAAI;AACpG,UAAM,QAAQ,KAAK,IAAI,EAAE,YAAY,gBAAgB,GAAG,KAAK,EAAE,YAAY,gBAAgB,GAAG,EAAE,IAAI;AACpG,QAAI,QAAQ,EAAE,YAAY,gBAAgB,GAAG,IAAI,EAAE,YAAY,gBAAgB,GAAG,IAAI,OAAO,OAAO,GAAG,GAAG,IAAI,KAAK,EAAE;AACrH,QAAI,OAAO;AACX,QAAI,IAAI,cAAc;AACpB,UAAI,YAAY,IAAI,WAAW,6BAA6B,IAAI;AAChE,UAAI,KAAK;AAAA,IACX;AAAA,EACF;AACF;AAEA,SAAS,gBAAgB,GAAe,KAAmE;AAxE3G;AAyEE,MAAI,IAAI,cAAY,OAAE,aAAF,mBAAY,UAAS,OAAO,WAAW,aAAa;AACtE,QAAI,cAAc;AAClB,UAAM,OAAQ,EAAE,IAAI,KAAK,EAAE,IAAI,KAAK,IAAM,EAAE,IAAI,KAAK,QAAQ,EAAE,SAAS,MAAM,GAAG,IAAI;AACrF,UAAM,OAAQ,EAAE,IAAI,KAAK,EAAE,IAAI,KAAK,IAAM,EAAE,IAAI,KAAK,QAAQ,EAAE,SAAS,MAAM,KAAK,IAAI;AACvF,UAAM,QAAQ,IAAI,OAAO;AAAA,UACnB,EAAE,IAAI,KAAK,EAAE,IAAI,KAAK,KAAK,EAAE,IAAI;AAAA;AAAA,UAEjC,QAAQ,EAAE,IAAI;AAAA,UACd,QAAQ,EAAE,IAAI,KAAK,EAAE,IAAI;AAAA,UACzB,EAAE,IAAI,KAAK,EAAE,IAAI,KAAK,KAAK,EAAE,IAAI,KAAK,EAAE,IAAI;AAAA,KACjD;AACD,UAAM,QAAQ,IAAI,OAAO;AAAA,UACnB,EAAE,IAAI,MAAM,EAAE,IAAI,KAAK,EAAE,IAAI,KAAK;AAAA;AAAA,UAElC,EAAE,IAAI,MAAM;AAAA,UACZ,EAAE,IAAI,KAAK,EAAE,IAAI,MAAM;AAAA,UACvB,EAAE,IAAI,KAAK,EAAE,IAAI,MAAM,EAAE,IAAI,KAAK,EAAE,IAAI,KAAK;AAAA,KAClD;AACD,QAAI,OAAO,KAAK;AAChB,QAAI,OAAO,KAAK;AAAA,EAClB;AACF;AAEA,SAAS,eAAe,GAAe,KAAmE;AAhG1G;AAiGE,MAAI,IAAI,cAAY,aAAE,aAAF,mBAAY,SAAZ,mBAAkB,eAAY,aAAE,aAAF,mBAAY,SAAZ,mBAAkB,YAAW,EAAE,YAAY,kBAAkB,EAAE,YAAY,mBAAmB,EAAE,YAAY,eAAe,MAAM,EAAE,YAAY,gBAAgB,IAAI;AACnN,QAAI,cAAc;AAClB,QAAI,YAAY;AAChB,UAAM,WAAW;AAAA,MACf,EAAE,YAAY,eAAe,GAAG,KAAM,KAAK,IAAI,EAAE,SAAS,KAAK,OAAO,IAAI,EAAE,SAAS,KAAK,WAAW,EAAE,IAAI;AAAA,MAC3G,EAAE,YAAY,eAAe,GAAG,KAAM,KAAK,IAAI,EAAE,SAAS,KAAK,OAAO,IAAI,EAAE,SAAS,KAAK,WAAW,EAAE,IAAI;AAAA,IAC7G;AACA,UAAM,KAAK,CAAC,EAAE,YAAY,eAAe,GAAG,IAAI,EAAE,YAAY,eAAe,GAAG,EAAE,GAAG,CAAC,SAAS,IAAI,SAAS,EAAE,GAAG,CAAC;AAClH,UAAM,YAAY;AAAA,MAChB,EAAE,YAAY,gBAAgB,GAAG,KAAM,KAAK,IAAI,EAAE,SAAS,KAAK,OAAO,IAAI,EAAE,SAAS,KAAK,WAAW,EAAE,IAAI;AAAA,MAC5G,EAAE,YAAY,gBAAgB,GAAG,KAAM,KAAK,IAAI,EAAE,SAAS,KAAK,OAAO,IAAI,EAAE,SAAS,KAAK,WAAW,EAAE,IAAI;AAAA,IAC9G;AACA,UAAM,KAAK,CAAC,EAAE,YAAY,gBAAgB,GAAG,IAAI,EAAE,YAAY,gBAAgB,GAAG,EAAE,GAAG,CAAC,UAAU,IAAI,UAAU,EAAE,GAAG,CAAC;AAAA,EACxH;AACF;AAEA,SAAS,iBAAiB,GAAe,KAAmE;AAC1G,MAAI,IAAI,gBAAgB,EAAE,KAAK,UAAU,KAAK;AAC5C,QAAI,YAAY;AAChB,aAASA,KAAI,GAAGA,KAAI,OAAc,SAAS,GAAGA,MAAK;AACjD,YAAM,SAAS,CAAC,OAAcA,KAAI,IAAI,IAAI,OAAcA,KAAI,IAAI,IAAI,OAAcA,KAAI,IAAI,EAAE,EAAE,IAAI,CAACC,WAAU,EAAE,KAAKA,OAAM;AAC1H,YAAM,KAAK,QAAQ,GAAG;AAAA,IACxB;AACA,mBAAe,GAAG,GAAG;AAAA,EACvB;AAQF;AAEA,SAAS,eAAe,GAAe,KAAmE;AACxG,MAAI,IAAI,cAAc,EAAE,KAAK,UAAU,KAAK;AAC1C,aAASD,KAAI,GAAGA,KAAI,EAAE,KAAK,QAAQA,MAAK;AACtC,YAAM,KAAK,EAAE,KAAKA,IAAG,IAAI,EAAE,KAAKA,IAAG,IAAI,EAAE,KAAKA,IAAG,IAAI,GAAG;AACxD,UAAI,IAAI,eAAe;AACrB,YAAsB,iCAAiC,SAASA,EAAC;AAAG,gBAAM,KAAK,EAAE,KAAKA,IAAG,IAAI,EAAE,KAAKA,IAAG,IAAK,EAAE,KAAKA,IAAG,KAAgB,KAAK,GAAG;AAC9I,YAAsB,qCAAqC,SAASA,EAAC;AAAG,gBAAM,KAAK,EAAE,KAAKA,IAAG,IAAI,EAAE,KAAKA,IAAG,IAAK,EAAE,KAAKA,IAAG,KAAgB,KAAK,GAAG;AAClJ,YAAsB,sCAAsC,SAASA,EAAC;AAAG,gBAAM,KAAK,EAAE,KAAKA,IAAG,IAAI,EAAE,KAAKA,IAAG,IAAK,EAAE,KAAKA,IAAG,KAAgB,KAAK,GAAG;AAAA,MACrJ;AAAA,IACF;AAAA,EACF;AACF;AAEA,SAAS,cAAc,GAAe,KAAK;AACzC,MAAI,IAAI,WAAW;AACjB,SAAK,KAAK,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,GAAG;AAAA,EACvD;AACF;AAGA,eAAsB,KAAKE,WAAqB,QAA2B,aAAoC;AAC7G,QAAM,UAAUC,UAAS,WAAW;AACpC,MAAI,CAAC,UAAU,CAACD;AAAU;AAC1B,QAAM,MAAM,iBAAiBA,SAAQ;AACrC,MAAI,CAAC;AAAK;AACV,MAAI,OAAO,IAAI;AACf,MAAI,cAAc,IAAI;AACtB,MAAI,YAAY,IAAI;AACpB,aAAW,KAAK,QAAQ;AACtB,kBAAc,GAAG,GAAG;AACpB,eAAW,GAAG,GAAG;AACjB,QAAI,EAAE,QAAQ,EAAE,KAAK,SAAS,GAAG;AAC/B,qBAAe,GAAG,GAAG;AACrB,uBAAiB,GAAG,GAAG;AACvB,sBAAgB,GAAG,GAAG;AACtB,qBAAe,GAAG,GAAG;AAAA,IACvB;AAAA,EACF;AACF;;;AClKA,eAAsB,KAAKE,WAAqB,QAA2B,aAAoC;AAP/G;AAQE,QAAM,eAAe,UAAUC,UAAS,WAAW;AACnD,MAAI,CAAC,UAAU,CAACD;AAAU;AAC1B,QAAM,MAAM,iBAAiBA,SAAQ;AACrC,MAAI,CAAC;AAAK;AACV,MAAI,WAAW;AACf,WAASE,KAAI,GAAGA,KAAI,OAAO,QAAQA,MAAK;AACtC,QAAI,cAAc,aAAa;AAC/B,QAAI,YAAY,aAAa;AAC7B,QAAI,YAAY,aAAa;AAC7B,QAAI,OAAO,aAAa;AACxB,QAAI,aAAa,aAAa,OAAOA,IAAG,SAAO,YAAOA,IAAG,QAAV,mBAAe,YAAW,GAAG;AAC1E,WAAK,KAAK,OAAOA,IAAG,IAAI,IAAI,OAAOA,IAAG,IAAI,IAAI,OAAOA,IAAG,IAAI,IAAI,OAAOA,IAAG,IAAI,IAAI,YAAY;AAC9F,UAAI,aAAa,YAAY;AAC3B,YAAI,aAAa,eAAe,aAAa,gBAAgB,IAAI;AAC/D,cAAI,YAAY,aAAa;AAC7B,cAAI,SAAS,QAAQ,MAAM,OAAOA,IAAG,UAAU,OAAOA,IAAG,IAAI,KAAK,GAAG,IAAI,OAAOA,IAAG,IAAI,KAAK,aAAa,YAAY,OAAOA,IAAG,IAAI,EAAE;AAAA,QACvI;AACA,YAAI,YAAY,aAAa;AAC7B,YAAI,SAAS,QAAQ,MAAM,OAAOA,IAAG,UAAU,OAAOA,IAAG,IAAI,KAAK,GAAG,IAAI,OAAOA,IAAG,IAAI,KAAK,aAAa,YAAY,OAAOA,IAAG,IAAI,EAAE;AAAA,MACvI;AAAA,IACF;AACA,QAAI,aAAa,cAAc,OAAOA,IAAG,WAAW;AAClD,eAAS,KAAK,GAAG,KAAK,OAAOA,IAAG,UAAU,QAAQ,MAAM;AACtD,YAAI,CAAC,OAAOA,IAAG,UAAU,IAAI,SAAU,OAAOA,IAAG,UAAU,IAAI,UAAU;AAAI;AAC7E,YAAI,YAAY,WAAW,OAAOA,IAAG,UAAU,IAAI,SAAS,IAAI,YAAY;AAC5E,cAAM,KAAK,OAAOA,IAAG,UAAU,IAAI,SAAS,IAAI,OAAOA,IAAG,UAAU,IAAI,SAAS,IAAI,GAAG,YAAY;AAAA,MACtG;AAAA,IACF;AACA,QAAI,aAAa,cAAc,OAAOA,IAAG,WAAW;AAClD,UAAI,OAAO,aAAa;AACxB,iBAAW,MAAM,OAAOA,IAAG,WAAW;AACpC,YAAI,CAAC,GAAG,SAAU,GAAG,UAAU;AAAI;AACnC,YAAI,YAAY,WAAW,GAAG,SAAS,IAAI,YAAY;AACvD,YAAI,SAAS,GAAG,GAAG,QAAQ,KAAK,MAAM,MAAM,GAAG,KAAK,MAAM,GAAG,SAAS,KAAK,GAAG,GAAG,SAAS,KAAK,CAAC;AAAA,MAClG;AAAA,IACF;AACA,QAAI,aAAa,gBAAgB,OAAOA,IAAG,aAAa,OAAOA,IAAG,aAAa;AAC7E,iBAAW,QAAQ,OAAO,OAAO,OAAOA,IAAG,WAAW,GAAG;AACvD,mBAAWC,cAAa;AAAM,iBAAO,KAAKA,YAAW,YAAY;AAAA,MACnE;AAAA,IACF;AAAA,EACF;AACF;;;AC3CA,eAAsB,KAAKC,WAAqB,QAA2B,aAAoC;AAC7G,QAAM,eAAe,UAAUC,UAAS,WAAW;AACnD,MAAI,CAAC,UAAU,CAACD;AAAU;AAC1B,QAAM,MAAM,iBAAiBA,SAAQ;AACrC,MAAI,CAAC;AAAK;AACV,MAAI,WAAW;AACf,MAAI,OAAO,aAAa;AACxB,aAAW,KAAK,QAAQ;AACtB,QAAI,aAAa,WAAW;AAC1B,UAAI,cAAc,aAAa;AAC/B,UAAI,YAAY,aAAa;AAC7B,WAAK,KAAK,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,YAAY;AAC9D,UAAI,aAAa,YAAY;AAC3B,YAAI,aAAa,eAAe,aAAa,gBAAgB,IAAI;AAC/D,cAAI,YAAY,aAAa;AAC7B,cAAI,SAAS,QAAQ,KAAK,MAAM,MAAM,EAAE,KAAK,MAAM,EAAE,IAAI,KAAK,GAAG,IAAI,EAAE,IAAI,KAAK,aAAa,YAAY,EAAE,IAAI,EAAE;AAAA,QACnH;AACA,YAAI,YAAY,aAAa;AAC7B,YAAI,SAAS,QAAQ,KAAK,MAAM,MAAM,EAAE,KAAK,MAAM,EAAE,IAAI,KAAK,GAAG,IAAI,EAAE,IAAI,KAAK,aAAa,YAAY,EAAE,IAAI,EAAE;AAAA,MACnH;AACA,UAAI,OAAO;AAAA,IACb;AACA,QAAI,aAAa,YAAY;AAC3B,UAAI,EAAE,aAAa,EAAE,UAAU,SAAS,GAAG;AACzC,mBAAW,MAAM,EAAE,WAAW;AAC5B,cAAI,YAAY,WAAW,GAAG,IAAI,YAAY;AAC9C,gBAAM,KAAK,GAAG,IAAI,GAAG,IAAI,GAAG,YAAY;AAAA,QAC1C;AAAA,MACF;AAAA,IACF;AACA,QAAI,aAAa,cAAc,EAAE,aAAa;AAC5C,YAAM,eAAe,CAAC,MAAoB,UAAkB;AAC1D,YAAI,CAAC,QAAQ,KAAK,WAAW,KAAK,CAAC,KAAK;AAAI;AAC5C,cAAM,IAAI,KAAK,KAAK,SAAS,GAAG,MAAM;AACtC,YAAI,YAAY,WAAW,GAAG,YAAY;AAC1C,YAAI,SAAS,OAAO,KAAK,KAAK,SAAS,GAAG,KAAK,GAAG,KAAK,KAAK,SAAS,GAAG,KAAK,CAAC;AAAA,MAChF;AACA,UAAI,OAAO,aAAa;AACxB,mBAAa,EAAE,YAAY,UAAU,OAAO;AAC5C,mBAAa,EAAE,YAAY,WAAW,QAAQ;AAC9C,mBAAa,EAAE,YAAY,SAAS,MAAM;AAC1C,mBAAa,EAAE,YAAY,UAAU,OAAO;AAC5C,mBAAa,EAAE,YAAY,UAAU,OAAO;AAC5C,mBAAa,EAAE,YAAY,SAAS,MAAM;AAAA,IAC5C;AACA,QAAI,aAAa,gBAAgB,EAAE,aAAa;AAC9C,YAAM,cAAc,CAAC,SAAuB;AAC1C,YAAI,CAAC,QAAQ,KAAK,WAAW,KAAK,CAAC,KAAK;AAAI;AAC5C,iBAASE,KAAI,GAAGA,KAAI,KAAK,QAAQA,MAAK;AACpC,cAAI,UAAU;AACd,gBAAM,IAAI,KAAKA,IAAG,MAAM;AACxB,cAAI,cAAc,WAAWA,KAAI,GAAG,YAAY;AAChD,cAAI,OAAO,KAAKA,KAAI,IAAIA,KAAI,IAAI,GAAG,IAAI,KAAKA,KAAI,IAAIA,KAAI,IAAI,GAAG,EAAE;AACjE,cAAI,OAAO,KAAKA,IAAG,IAAI,KAAKA,IAAG,EAAE;AACjC,cAAI,OAAO;AAAA,QACb;AAAA,MACF;AACA,UAAI,YAAY,aAAa;AAC7B,kBAAY,EAAE,YAAY,QAAQ;AAClC,kBAAY,EAAE,YAAY,SAAS;AACnC,kBAAY,EAAE,YAAY,OAAO;AACjC,kBAAY,EAAE,YAAY,QAAQ;AAClC,kBAAY,EAAE,YAAY,QAAQ;AAAA,IAEpC;AAAA,EACF;AACF;;;AClEA,eAAsB,OAAOC,WAAqB,QAA6B,aAAoC;AACjH,QAAM,eAAe,UAAUC,UAAS,WAAW;AACnD,MAAI,CAAC,UAAU,CAACD;AAAU;AAC1B,QAAM,MAAM,iBAAiBA,SAAQ;AACrC,MAAI,CAAC;AAAK;AACV,MAAI,WAAW;AACf,MAAI,OAAO,aAAa;AACxB,aAAW,KAAK,QAAQ;AACtB,QAAI,aAAa,WAAW;AAC1B,UAAI,cAAc,aAAa;AAC/B,UAAI,YAAY,aAAa;AAC7B,WAAK,KAAK,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,EAAE,IAAI,IAAI,YAAY;AAC9D,UAAI,aAAa,YAAY;AAC3B,cAAM,QAAQ,GAAG,EAAE,SAAS,KAAK,MAAM,MAAM,EAAE,KAAK;AACpD,YAAI,aAAa,eAAe,aAAa,gBAAgB,IAAI;AAC/D,cAAI,YAAY,aAAa;AAC7B,cAAI,SAAS,OAAO,EAAE,IAAI,KAAK,GAAG,IAAI,EAAE,IAAI,KAAK,aAAa,YAAY,EAAE,IAAI,EAAE;AAAA,QACpF;AACA,YAAI,YAAY,aAAa;AAC7B,YAAI,SAAS,OAAO,EAAE,IAAI,KAAK,GAAG,IAAI,EAAE,IAAI,KAAK,aAAa,YAAY,EAAE,IAAI,EAAE;AAAA,MACpF;AACA,UAAI,OAAO;AAAA,IACb;AAAA,EACF;AACF;;;ACxBA,eAAsB,QAAQE,WAAqB,QAA8B,aAAoC;AACnH,QAAM,eAAe,UAAUC,UAAS,WAAW;AACnD,MAAI,CAAC,UAAU,CAACD;AAAU;AAC1B,MAAI,aAAa,cAAc;AAC7B,UAAM,MAAM,iBAAiBA,SAAQ;AACrC,QAAI,CAAC;AAAK;AACV,QAAI,OAAO,aAAa;AACxB,QAAI,YAAY,aAAa;AAC7B,QAAIE,KAAI;AACR,aAAS,IAAI,GAAG,IAAI,OAAO,QAAQ,KAAK;AACtC,UAAIC,SAAmB,CAAC;AACxB,UAAI,OAAkB,CAAC;AACvB,OAACA,QAAO,IAAI,IAAI,OAAO,QAAQ,OAAO,EAAE;AACxC,UAAK,KAAK,SAAS,KAAQ,KAAK,GAAc,SAAS,GAAI;AACzD,cAAM,MAAMA,OAAM,KAAe,IAAI,IAAIA,OAAM,OAAO;AACtD,cAAM,QAAQ,GAAGA,OAAM,MAAM,QAAQ,KAAK;AAC1C,YAAI,aAAa,eAAe,aAAa,gBAAgB,IAAI;AAC/D,cAAI,YAAY,aAAa;AAC7B,cAAI,SAAS,OAAO,GAAG,IAAKD,KAAI,aAAa,UAAW;AAAA,QAC1D;AACA,YAAI,YAAY,aAAa;AAC7B,YAAI,SAAS,OAAO,GAAG,IAAKA,KAAI,aAAa,UAAW;AACxD,QAAAA,MAAK;AAAA,MACP;AAAA,IACF;AAAA,EACF;AACF;;;APjBA,IAAI,WAAW;AAUf,eAAsB,OAAOE,WAAqB,QAA6B,aAAoC;AACjH,QAAM,eAAe,UAAUC,UAAS,WAAW;AACnD,MAAI,CAAC,UAAU,CAACD;AAAU;AAC1B,QAAM,MAAM,iBAAiBA,SAAQ;AACrC,MAAI,CAAC;AAAK;AACV,MAAI,WAAW;AACf,MAAI,OAAO,aAAa;AAExB,WAASE,KAAI,GAAGA,KAAI,OAAO,QAAQA,MAAK;AACtC,QAAI,aAAa,WAAW;AAC1B,UAAI,cAAc,aAAa;AAC/B,UAAI,YAAY,aAAa;AAC7B,WAAK,KAAK,OAAOA,IAAG,IAAI,IAAI,OAAOA,IAAG,IAAI,IAAI,OAAOA,IAAG,IAAI,IAAI,OAAOA,IAAG,IAAI,IAAI,YAAY;AAC9F,UAAI,aAAa,YAAY;AAC3B,cAAM,QAAQ,WAAWA;AACzB,YAAI,aAAa,eAAe,aAAa,gBAAgB,IAAI;AAC/D,cAAI,YAAY,aAAa;AAC7B,cAAI,SAAS,OAAO,OAAOA,IAAG,IAAI,KAAK,GAAG,IAAI,OAAOA,IAAG,IAAI,KAAK,aAAa,YAAY,OAAOA,IAAG,IAAI,EAAE;AAAA,QAC5G;AACA,YAAI,YAAY,aAAa;AAC7B,YAAI,SAAS,OAAO,OAAOA,IAAG,IAAI,KAAK,GAAG,IAAI,OAAOA,IAAG,IAAI,KAAK,aAAa,YAAY,OAAOA,IAAG,IAAI,EAAE;AAAA,MAC5G;AACA,UAAI,OAAO;AAAA,IACb;AAAA,EACF;AACF;AAGA,eAAsBC,QAAOC,QAAwD,QAAmB;AACtG,MAAI,CAACA,UAAS,CAAC;AAAQ;AACvB,QAAM,MAAM,iBAAiB,MAAM;AACnC,MAAI,CAAC;AAAK;AACV,MAAI,UAAUA,QAAO,GAAG,CAAC;AAC3B;AAGA,eAAsBC,KAAIL,WAAqB,QAAgB,aAAoC;AACjG,MAAI,CAAC,UAAU,CAAC,OAAO,eAAe,CAAC,UAAU,CAACA;AAAU,WAAO;AACnE,QAAM,YAAY,IAAI;AACtB,QAAM,eAAe,UAAUC,UAAS,WAAW;AACnD,QAAM,UAAU,QAAQ,IAAI;AAAA,IAC1B,KAAKD,WAAU,OAAO,MAAM,YAAY;AAAA,IACxC,KAAKA,WAAU,OAAO,MAAM,YAAY;AAAA,IACxC,KAAKA,WAAU,OAAO,MAAM,YAAY;AAAA,IACxC,OAAOA,WAAU,OAAO,QAAQ,YAAY;AAAA,IAC5C,QAAQA,WAAU,OAAO,SAAS,YAAY;AAAA,EAEhD,CAAC;AACD,aAAWM,KAAI,UAAU,WAAW,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAChG,SAAO,YAAY,OAAO;AAC1B,SAAO;AACT;;;AQxEA,IAAM,aAAa;AACnB,IAAM,QAAQ;AAGd,SAAS,WAAW,GAAW,GAAW,SAAmD;AAC3F,MAAI,SAAS;AACb,MAAI,IAAI,QAAQ,SAAS;AACzB,WAASC,KAAI,GAAGA,KAAI,QAAQ,QAAQ,IAAIA,MAAK;AAC3C,QAAM,QAAQA,IAAG,IAAI,MAAQ,QAAQ,GAAG,IAAI,KAAQ,KAAK,QAAQ,GAAG,IAAI,QAAQA,IAAG,MAAM,IAAI,QAAQA,IAAG,MAAM,QAAQ,GAAG,IAAI,QAAQA,IAAG,KAAK,QAAQA,IAAG;AAAI,eAAS,CAAC;AAAA,EACxK;AACA,SAAO;AACT;AAEA,eAAsB,KAAKC,OAA+C;AACxE,MAAI,CAACA,MAAK;AAAQ,WAAOA,MAAK;AAC9B,MAAI,CAACA,MAAK,QAAQA,MAAK,KAAK,SAAS;AAAK,WAAOA,MAAK;AACtD,QAAM,QAAQA,MAAK,OAAO,MAAM,MAAM;AACtC,QAAM,SAASA,MAAK,OAAO,MAAM,MAAM;AACvC,QAAMC,UAAS,MAAMD,MAAK,OAAO,OAAO;AACxC,MAAI,aAA8C,CAAC;AACnD,aAAW,MAAM,gBAAgB;AAAY,eAAW,KAAK,EAAE,IAAIA,MAAK,KAAK,IAAI,KAAKA,MAAK,IAAI,MAAMA,MAAK,IAAI,IAAI,IAAIA,MAAK,KAAK,IAAI,KAAKA,MAAK,IAAI,MAAMA,MAAK,IAAI,GAAG,CAAC;AACrK,MAAI,cAAc,aAAa;AAAG,iBAAa,WAAW,IAAI,CAAC,QAAQ,EAAE,GAAG,GAAG,IAAI,MAAM,GAAG,IAAI,aAAa,GAAG,IAAI,YAAY,GAAG,GAAG,IAAI,MAAM,GAAG,IAAI,aAAa,GAAG,IAAI,WAAW,EAAE;AACxL,WAAS,IAAI,GAAG,IAAI,OAAO,KAAK;AAC9B,aAAS,IAAI,GAAG,IAAI,QAAQ,KAAK;AAC/B,YAAM,SAAS,WAAW,IAAI,OAAO,IAAI,OAAO,UAAU;AAC1D,UAAI,CAAC,QAAQ;AACX,QAAAC,QAAO,IAAI,QAAQA,QAAO,IAAI,GAAG,GAAG,GAAG,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC;AACrD,QAAAA,QAAO,IAAI,QAAQA,QAAO,IAAI,GAAG,GAAG,GAAG,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC;AACrD,QAAAA,QAAO,IAAI,QAAQA,QAAO,IAAI,GAAG,GAAG,GAAG,CAAC,GAAG,GAAG,GAAG,GAAG,CAAC;AAAA,MACvD;AAAA,IACF;AAAA,EACF;AACA,QAAM,SAASA,QAAO,SAAS;AAC/B,EAAG,QAAQA,OAAM;AACjB,SAAO;AACT;;;ACpCA,IAAM,gBAAgB,CAACC,UAA4D;AACjF,QAAM,UAAU,CAAC,KAAY,QAAe,KAAK,MAAM,IAAI,KAAK,IAAI,IAAI,IAAI,KAAK,IAAI,EAAE;AACvF,MAAI,CAACA,MAAK,YAAY,mBAAmB,CAACA,MAAK,YAAY;AAAgB,WAAO,EAAE,SAAS,GAAG,UAAU,EAAE;AAE5G,QAAM,aAAa,CAAC,GAAG,IAAI;AAC3B,QAAM,WAAW;AAEjB,QAAM,QAAQA,MAAK,KAAK,IAAI,MAAM,MAAMA,MAAK,KAAK,KAAK,MAAM;AAC7D,QAAM,aAAa,OAAOA,MAAK,KAAK,OAAOA,MAAK,KAAK;AACrD,QAAM,YAAY,OACd,EAAEA,MAAK,KAAK,KAAK,KAAKA,MAAK,KAAK,IAAI,MAAM,IAAIA,MAAK,KAAK,KAAK,KAAKA,MAAK,KAAK,IAAI,MAAM,CAAC,IACvF,EAAEA,MAAK,KAAK,KAAK,KAAKA,MAAK,KAAK,KAAK,MAAM,IAAIA,MAAK,KAAK,KAAK,KAAKA,MAAK,KAAK,KAAK,MAAM,CAAC;AAC7F,QAAM,UAAU,OACZ,CAACA,MAAK,KAAK,KAAK,KAAKA,MAAK,KAAK,IAAI,IAAIA,MAAK,KAAK,IAAI,KAAKA,MAAK,KAAK,IAAI,EAAE,IAC1E,CAACA,MAAK,KAAK,KAAK,KAAKA,MAAK,KAAK,KAAK,IAAIA,MAAK,KAAK,KAAK,KAAKA,MAAK,KAAK,KAAK,EAAE;AACjF,QAAM,UAAiB;AAAA,KACpB,UAAU,KAAK,WAAW,MAAM,QAAQ,KAAK,WAAW;AAAA,IACzD,YAAY,WAAW,KAAK,UAAU,MAAM,QAAQ,KAAK,WAAW;AAAA,EACtE;AACA,MAAI,WAAW,KAAK,KAAM,QAAQ,KAAK,QAAQ,KAAO,QAAQ,KAAK,QAAQ,EAAG;AAC9E,aAAW,KAAK,IAAI,UAAUA,MAAK,OAAO,KAAK,GAAGA,MAAK,OAAO,KAAK,CAAC;AACpE,QAAM,WAAW,QAAQ,CAAC,GAAG,CAAC,GAAG,OAAO,IAAK,KAAK,KAAK,KAAM,KAAK;AAClE,SAAO,EAAE,SAAS,SAAS;AAC7B;AAEO,IAAM,qBAAqB,CAACA,OAAkB,cAIhD;AAEH,QAAM,YAAY,CAAC,MAAsB;AACvC,UAAM,SAAS,KAAK,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE,EAAE;AAChE,MAAE,MAAM;AACR,MAAE,MAAM;AACR,MAAE,MAAM;AACR,WAAO;AAAA,EACT;AACA,QAAM,aAAa,CAAC,GAAW,MAAsB;AACnD,UAAM,IAAI,EAAE,KAAK,EAAE;AACnB,UAAM,IAAI,EAAE,KAAK,EAAE;AACnB,UAAM,IAAI,EAAE,KAAK,EAAE;AACnB,WAAO,CAAC,GAAG,GAAG,CAAC;AAAA,EACjB;AACA,QAAM,eAAe,CAAC,GAAW,MAAsB;AACrD,UAAM,IAAI,EAAE,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE;AACjC,UAAM,IAAI,EAAE,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE;AACjC,UAAM,IAAI,EAAE,KAAK,EAAE,KAAK,EAAE,KAAK,EAAE;AACjC,WAAO,CAAC,GAAG,GAAG,CAAC;AAAA,EACjB;AAEA,QAAM,6BAA6B,CAACC,OAA8D;AAEhG,UAAM,CAAC,KAAK,MAAM,MAAM,KAAK,KAAK,KAAK,KAAK,KAAK,GAAG,IAAIA;AACxD,QAAI;AACJ,QAAI;AACJ,QAAI;AACJ,QAAI,MAAM,GAAG;AACX,UAAI,MAAM,IAAI;AACZ,iBAAS,KAAK,KAAK,GAAG;AACtB,iBAAS,KAAK,MAAM,CAAC,KAAK,GAAG;AAC7B,iBAAS,KAAK,MAAM,CAAC,KAAK,GAAG;AAAA,MAC/B,OAAO;AACL,iBAAS,CAAC,KAAK,KAAK;AACpB,iBAAS,CAAC,KAAK,MAAM,KAAK,GAAG;AAC7B,iBAAS;AAAA,MACX;AAAA,IACF,OAAO;AACL,eAAS,KAAK,KAAK;AACnB,eAAS,KAAK,MAAM,KAAK,GAAG;AAC5B,eAAS;AAAA,IACX;AACA,QAAI,MAAM,MAAM;AAAG,eAAS;AAC5B,QAAI,MAAM,MAAM;AAAG,eAAS;AAC5B,QAAI,MAAM,MAAM;AAAG,eAAS;AAC5B,WAAO,EAAE,OAAO,IAAI,CAAC,QAAQ,KAAK,IAAI,CAAC,QAAQ,MAAM,IAAI,CAAC,OAAO;AAAA,EACnE;AAcA,QAAM,OAAOD,MAAK;AAClB,MAAI,CAAC,QAAQ,KAAK,SAAS;AAAK,WAAO,EAAE,OAAO,EAAE,OAAO,GAAG,KAAK,GAAG,MAAM,EAAE,GAAG,QAAQ,CAAC,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,CAAC,GAAG,MAAM,EAAE,SAAS,GAAG,UAAU,EAAE,EAAE;AAEtJ,QAAME,QAAO,KAAK,IAAIF,MAAK,OAAO,KAAK,UAAU,IAAIA,MAAK,OAAO,KAAK,UAAU,EAAE,IAAI;AAEtF,QAAM,MAAe,CAAC,KAAK,KAAK,KAAK,MAAM,KAAK,MAAM,KAAK,IAAI,EAAE,IAAI,CAAC,OAAO,CAAC,GAAG,KAAK,UAAU,KAAKE,OAAM,GAAG,KAAK,UAAU,KAAKA,OAAM,GAAG,EAAE,CAAU;AAEvJ,QAAM,SAAS,UAAU,WAAW,IAAI,IAAc,IAAI,EAAY,CAAC;AACvE,MAAI,SAAS,UAAU,WAAW,IAAI,IAAc,IAAI,EAAY,CAAC;AACrE,QAAM,SAAS,UAAU,aAAa,QAAQ,MAAM,CAAC;AAErD,WAAS,aAAa,QAAQ,MAAM;AAIpC,QAAM,SAAmF;AAAA,IACvF,OAAO;AAAA,IAAI,OAAO;AAAA,IAAI,OAAO;AAAA,IAC7B,OAAO;AAAA,IAAI,OAAO;AAAA,IAAI,OAAO;AAAA,IAC7B,OAAO;AAAA,IAAI,OAAO;AAAA,IAAI,OAAO;AAAA,EAC/B;AACA,QAAM,QAAQ,2BAA2B,MAAM;AAI/C,QAAM,OAAO,KAAK,WAAW,MAAM,cAAcF,KAAI,IAAI,EAAE,SAAS,GAAG,UAAU,EAAE;AAEnF,SAAO,EAAE,OAAO,QAAQ,KAAK;AAC/B;;;AChGO,IAAM,aAAa,OAAO,UAAyCG,WAAyC;AAzBnH;AA4BE,MAAI,YAAoB,IAAI;AAC5B,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AACJ,MAAI;AAEJ,QAAM,UAA6B,CAAC;AACpC,WAAS,QAAQ;AAEjB,QAAM,QAAQ,MAAeC,UAAQD,QAAO,SAAS,MAAM;AAC3D,WAAS,YAAY,OAAOE,KAAI,WAAW,SAAS,YAAY,QAAQ,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AACzI,MAAI,CAACF,OAAM,SAASA,OAAM,MAAM,WAAW;AAAG,WAAO,CAAC;AACtD,MAAI,CAAC;AAAO,WAAO,CAAC;AAEpB,WAASG,KAAI,GAAGA,KAAI,MAAM,QAAQA,MAAK;AACrC,aAAS,QAAQ,UAAU;AAI3B,QAAI,CAAC,MAAMA,IAAG,UAAU,MAAMA,IAAG,OAAO,uBAAuB;AAC7D,UAAI,4BAA4B,MAAMA,IAAG,MAAM;AAC/C;AAAA,IACF;AAGA,SAAI,cAAS,OAAO,KAAK,aAArB,mBAA+B,MAAM;AACvC,YAAM,SAAS,MAAW,KAAK,MAAMA,GAAE;AACvC,MAAG,QAAQ,MAAMA,IAAG,MAAM;AAC1B,YAAMA,IAAG,SAAS;AAAA,IACpB;AAGA,UAAM,WAAW,MAAMA,IAAG,QAAS,MAAMA,IAAG,KAAK,SAAS,MAAO,mBAAmB,MAAMA,KAAI,CAACH,OAAM,MAAM,IAAIA,OAAM,MAAM,EAAE,CAAC,IAAI;AAGlI,aAAS,QAAQ,gBAAgB;AACjC,QAAI,SAAS,OAAO,OAAO;AACzB,qBAAa,cAAS,OAAO,KAAK,YAArB,mBAA8B,WAAkBC,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI,CAAC;AAAA,IAC9I,OAAO;AACL,eAAS,QAAQ;AACjB,kBAAY,IAAI;AAChB,qBAAa,cAAS,OAAO,KAAK,YAArB,mBAA8B,WAAU,MAAcF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI,CAAC;AAClJ,eAAS,YAAY,UAAUD,KAAI,WAAW,SAAS,YAAY,WAAW,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,IACjJ;AACA,aAAS,QAAQ,cAAc;AAG/B,aAAS,QAAQ,kBAAkB;AACnC,QAAI,SAAS,OAAO,OAAO;AACzB,uBAAe,cAAS,OAAO,KAAK,cAArB,mBAAgC,WAAoBD,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAAA,IACnJ,OAAO;AACL,eAAS,QAAQ;AACjB,kBAAY,IAAI;AAChB,uBAAe,cAAS,OAAO,KAAK,cAArB,mBAAgC,WAAU,MAAgBF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AACvJ,eAAS,YAAY,YAAYD,KAAI,WAAW,SAAS,YAAY,aAAa,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,IACrJ;AACA,aAAS,QAAQ,gBAAgB;AAGjC,aAAS,QAAQ,iBAAiB;AAClC,QAAI,SAAS,OAAO,OAAO;AACzB,sBAAc,cAAS,OAAO,KAAK,aAArB,mBAA+B,WAAmBD,UAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAAA,IAChJ,OAAO;AACL,eAAS,QAAQ;AACjB,kBAAY,IAAI;AAChB,sBAAc,cAAS,OAAO,KAAK,aAArB,mBAA+B,WAAU,MAAeF,UAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AACpJ,eAAS,YAAY,WAAWD,KAAI,WAAW,SAAS,YAAY,aAAa,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,IACpJ;AACA,aAAS,QAAQ,eAAe;AAGhC,aAAS,QAAQ,aAAa;AAC9B,QAAI,SAAS,OAAO,OAAO;AACzB,kBAAU,cAAS,OAAO,KAAK,YAArB,mBAA8B,WAAe,QAAQ,MAAMC,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAAA,IACvI,OAAO;AACL,eAAS,QAAQ;AACjB,kBAAY,IAAI;AAChB,kBAAU,cAAS,OAAO,KAAK,YAArB,mBAA8B,WAAU,MAAW,QAAQ,MAAMA,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAC3I,eAAS,YAAY,OAAO,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,IAC1D;AACA,aAAS,QAAQ,WAAW;AAG5B,aAAS,QAAQ,eAAe;AAChC,QAAI,SAAS,OAAO,OAAO;AACzB,iBAAS,cAAS,OAAO,KAAK,cAArB,mBAAgC,WAAoBF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAC3I,oBAAY,cAAS,OAAO,KAAK,cAArB,mBAAgC,WAAuBF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAAA,IACnJ,OAAO;AACL,eAAS,QAAQ;AACjB,kBAAY,IAAI;AAChB,iBAAS,cAAS,OAAO,KAAK,cAArB,mBAAgC,WAAU,MAAgBF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AACjJ,oBAAY,cAAS,OAAO,KAAK,cAArB,mBAAgC,WAAU,MAAmBF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AACvJ,eAAS,YAAY,SAAS,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,IAC5D;AACA,aAAS,QAAQ,aAAa;AAG9B,aAAS,QAAQ,sBAAsB;AACvC,QAAI,SAAS,OAAO,OAAO;AACzB,2BAAmB,cAAS,OAAO,KAAK,qBAArB,mBAAuC,WAAwBF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAAA,IAClK,OAAO;AACL,eAAS,QAAQ;AACjB,kBAAY,IAAI;AAChB,2BAAmB,cAAS,OAAO,KAAK,qBAArB,mBAAuC,WAAU,MAAoBF,SAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AACtK,eAAS,YAAY,gBAAgB,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,IACnE;AACA,aAAS,QAAQ,oBAAoB;AAGrC,aAAS,QAAQ,oBAAoB;AACrC,QAAI,SAAS,OAAO,OAAO;AACzB,kBAAU,cAAS,OAAO,KAAK,gBAArB,mBAAkC,WAAkBF,UAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAAA,IAC9I,OAAO;AACL,eAAS,QAAQ;AACjB,kBAAY,IAAI;AAChB,kBAAU,cAAS,OAAO,KAAK,gBAArB,mBAAkC,WAAU,MAAcF,UAAQ,MAAME,IAAG,UAAa,OAAO,CAAC,CAAC,GAAG,SAAS,QAAQA,IAAG,MAAM,MAAM,IAAI;AAClJ,eAAS,YAAY,cAAcD,KAAI,WAAW,SAAS,YAAY,eAAe,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,IACzJ;AACA,aAAS,QAAQ,kBAAkB;AAGnC,QAAI,SAAS,OAAO,OAAO;AACzB,OAAC,QAAQ,WAAW,YAAY,kBAAkB,SAAS,SAAS,cAAc,WAAW,IAAI,MAAM,QAAQ,IAAI,CAAC,QAAQ,WAAW,YAAY,kBAAkB,SAAS,SAAS,cAAc,WAAW,CAAC;AAAA,IACnN;AACA,aAAS,QAAQ,cAAc;AAE/B,UAAI,cAAS,OAAO,KAAK,cAArB,mBAAgC,YAAW,UAAU,WAAW;AAClE,gBAAU;AAAA,QACR,GAAI;AAAA,QACJ,KAAM,OAA0B;AAAA,QAChC,QAAS,UAAsD;AAAA,QAC/D,aAAc,UAAsD;AAAA,MACtE;AAAA,IACF;AACA,UAAI,cAAS,OAAO,KAAK,YAArB,mBAA8B,YAAW,SAAS;AACpD,gBAAU;AAAA,QACR,GAAI;AAAA,QACJ,KAAM,QAA0B;AAAA,QAChC,QAAS,QAA0B;AAAA,QACnC,aAAc,QAA0B;AAAA,QACxC,MAAO,QAA0B;AAAA,MACnC;AAAA,IACF;AACA,UAAI,cAAS,OAAO,KAAK,qBAArB,mBAAuC,YAAW,kBAAkB;AACtE,MAAC,QAAoB,aAAa;AAAA,IACpC;AAIA,QAAI,GAAC,cAAS,OAAO,KAAK,SAArB,mBAA2B,UAAS;AAAA,IAGzC;AACA,UAAM,WAAY,MAAMC,IAAG,eAAe,MAAMA,IAAG,YAAY,eAAe,MAAMA,IAAG,YAAY,YAAY,MAAM,MAAMA,IAAG,YAAY,gBAAgB,MAAMA,IAAG,YAAY,aAAa,MACtL,MAAMA,IAAG,YAAY,YAAY,SAAS,KAAO,MAAMA,IAAG,YAAY,aAAa,SAAS,KAC5F,MAAMA,IAAG,YAAY,YAAY,OAAO,QAAU,MAAMA,IAAG,YAAY,aAAa,OAAO,OAC7F,KAAK,IAAI,KAAK,IAAI,MAAMA,IAAG,YAAY,YAAY,GAAG,KAAK,MAAMA,IAAG,YAAY,YAAY,GAAG,EAAE,GAAG,KAAK,IAAI,MAAMA,IAAG,YAAY,aAAa,GAAG,KAAK,MAAMA,IAAG,YAAY,aAAa,GAAG,EAAE,CAAC,IAAIH,OAAM,MAAM,KAC/M;AAGJ,UAAMI,YAAS,cAAS,OAAO,KAAK,aAArB,mBAA+B,UAAY,QAAQ,MAAMD,IAAG,MAAM,IAAI;AAErF,IAAG,QAAQ,MAAMA,IAAG,MAAM;AAE1B,QAAI,MAAMA,IAAG;AAAQ,aAAO,MAAMA,IAAG;AAErC,UAAM,MAAkB;AAAA,MACtB,GAAG,MAAMA;AAAA,MACT,IAAIA;AAAA,IACN;AACA,QAAK,mCAAqB;AAAK,UAAI,MAAO,QAAoB;AAC9D,QAAK,mCAAqB;AAAQ,UAAI,SAAU,QAAoB;AACpE,QAAK,mCAAqB;AAAa,UAAI,cAAe,mCAAqB;AAC/E,QAAK,mCAAqB;AAAY,UAAI,YAAa,mCAAqB;AAC5E,QAAK,mCAAqB;AAAM,UAAI,OAAQ,mCAAqB;AACjE,QAAI;AAAY,UAAI,UAAU;AAC9B,QAAI;AAAc,UAAI,OAAO;AAC7B,QAAI;AAAa,UAAI,OAAO;AAC5B,QAAI,YAAY,aAAa;AAAG,UAAI,OAAO,KAAK,MAAM,MAAM,WAAW,IAAI,IAAI;AAC/E,QAAI;AAAU,UAAI,WAAW;AAC7B,QAAIC;AAAQ,UAAI,SAASA;AACzB,YAAQ,KAAK,GAAG;AAChB,aAAS,QAAQ,UAAU;AAAA,EAC7B;AACA,WAAS,QAAQ,eAAe;AAChC,MAAI,SAAS,OAAO,OAAO;AACzB,QAAI,SAAS,YAAY;AAAM,aAAO,SAAS,YAAY;AAC3D,QAAI,SAAS,YAAY;AAAK,aAAO,SAAS,YAAY;AAC1D,QAAI,SAAS,YAAY;AAAQ,aAAO,SAAS,YAAY;AAC7D,QAAI,SAAS,YAAY;AAAS,aAAO,SAAS,YAAY;AAAA,EAChE;AACA,SAAO;AACT;;;AC/LO,IAAMC,QAAO,CAAC,QAAuC;AAC1D,MAAI,CAAC;AAAK,WAAO,CAAC;AAClB,QAAM,WAA0D,CAAC;AACjE,WAASC,KAAI,GAAGA,KAAI,IAAI,QAAQA,MAAK;AAEnC,UAAM,YAAY,IAAIA,IAAG,UAAU,KAAK,CAAC,MAAO,EAAE,SAAS,WAAY;AACvE,UAAM,aAAa,IAAIA,IAAG,UAAU,KAAK,CAAC,MAAO,EAAE,SAAS,YAAa;AACzE,UAAM,OAAO,IAAIA,IAAG,UAAU,KAAK,CAAC,MAAO,EAAE,SAAS,MAAO;AAC7D,QAAI,QAAQ,aAAa,cAAe,UAAU,SAAS,KAAK,KAAK,SAAS,MAAQ,WAAW,SAAS,KAAK,KAAK,SAAS;AAAK,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,YAAY,CAAC;AAAA,aACxK,QAAQ,aAAc,UAAU,SAAS,KAAK,KAAK,SAAS;AAAK,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,kBAAkB,CAAC;AAAA,aACtH,QAAQ,cAAe,WAAW,SAAS,KAAK,KAAK,SAAS;AAAK,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,mBAAmB,CAAC;AAGlI,UAAM,eAAe,IAAIA,IAAG,UAAU,KAAK,CAAC,MAAO,EAAE,SAAS,cAAe;AAC7E,UAAM,gBAAgB,IAAIA,IAAG,UAAU,KAAK,CAAC,MAAO,EAAE,SAAS,eAAgB;AAC/E,QAAI,gBAAgB,iBAAiB,KAAK,IAAI,aAAa,YAAY,KAAK,cAAc,YAAY,EAAE,IAAI,KAAK;AAC/G,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,WAAY,aAAa,SAAS,KAAK,cAAc,SAAS,KAAM,SAAS,UAAU,CAAC;AAAA,IAC5H;AAAA,EACF;AACA,SAAO;AACT;AAEO,IAAMC,QAAO,CAAC,QAAuC;AAC1D,MAAI,CAAC;AAAK,WAAO,CAAC;AAClB,QAAM,WAA0D,CAAC;AACjE,WAASD,KAAI,GAAGA,KAAI,IAAI,QAAQA,MAAK;AACnC,QAAI,IAAIA,IAAG,QAAQ,IAAIA,IAAG,KAAK,SAAS,KAAK;AAC3C,YAAM,SAAS,IAAIA,IAAG,KAAK,IAAI,MAAM,MAAM,IAAIA,IAAG,KAAK,KAAK,MAAM;AAClE,YAAM,QAAQ,IAAIA,IAAG,KAAK,IAAI,KAAK,IAAIA,IAAG,KAAK,KAAK;AACpD,UAAI,KAAK,IAAI,QAAQ,KAAK,KAAK;AAAM,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,gBAAgB,CAAC;AAAA;AACnF,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,UAAU,QAAQ,IAAI,SAAS,UAAU,CAAC;AACjF,YAAM,WAAW,KAAK,IAAI,IAAIA,IAAG,KAAK,KAAK,KAAK,IAAIA,IAAG,KAAK,KAAK,EAAE,IAAI,KAAK,IAAI,IAAIA,IAAG,KAAK,KAAK,KAAK,IAAIA,IAAG,KAAK,KAAK,EAAE;AACzH,UAAI,WAAW;AAAK,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,iBAAiB,CAAC;AACxE,YAAM,YAAY,KAAK,IAAI,IAAIA,IAAG,KAAK,KAAK,KAAK,IAAIA,IAAG,KAAK,KAAK,EAAE,IAAI,KAAK,IAAI,IAAIA,IAAG,KAAK,KAAK,KAAK,IAAIA,IAAG,KAAK,KAAK,EAAE;AAC1H,UAAI,YAAY;AAAK,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,kBAAkB,CAAC;AAC1E,YAAM,YAAY,KAAK,IAAI,KAAK,MAAM,KAAK,IAAI,IAAIA,IAAG,KAAK,IAAI,KAAK,IAAIA,IAAG,KAAK,IAAI,EAAE,IAAI,KAAK,IAAI,IAAIA,IAAG,KAAK,IAAI,KAAK,IAAIA,IAAG,KAAK,KAAK,EAAE,CAAC;AAC5I,UAAI,YAAY;AAAI,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,SAAS,KAAK,MAAM,SAAS,UAAU,CAAC;AAC9F,YAAM,YAAY,IAAIA,IAAG,KAAK,KAAK,MAAM;AACzC,UAAI,KAAK,IAAI,SAAS,IAAI;AAAI,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,QAAQ,YAAY,IAAI,OAAO,SAAS,CAAC;AAAA,IAC3G;AAAA,EACF;AACA,SAAO;AACT;AAEO,IAAME,QAAO,CAAC,QAAuC;AAC1D,MAAI,CAAC;AAAK,WAAO,CAAC;AAClB,QAAM,WAA0D,CAAC;AACjE,WAASF,KAAI,GAAGA,KAAI,IAAI,QAAQA,MAAK;AACnC,QAAI,CAAC,IAAIA,IAAG,eAAe,CAAC,IAAIA,IAAG,YAAY,eAAe,CAAC,IAAIA,IAAG,YAAY,YAAY,MAAM,CAAC,IAAIA,IAAG,YAAY,gBAAgB,CAAC,IAAIA,IAAG,YAAY,aAAa;AAAI;AAC7K,UAAM,YAAY,IAAIA,IAAG,YAAY,YAAY,GAAG,KAAK,IAAIA,IAAG,YAAY,YAAY,GAAG;AAC3F,UAAM,YAAY,IAAIA,IAAG,YAAY,YAAY,GAAG,KAAK,IAAIA,IAAG,YAAY,YAAY,GAAG;AAC3F,UAAM,WAAW,KAAK,IAAI,YAAY,SAAS;AAE/C,UAAM,aAAa,IAAIA,IAAG,YAAY,aAAa,GAAG,KAAK,IAAIA,IAAG,YAAY,aAAa,GAAG;AAC9F,UAAM,aAAa,IAAIA,IAAG,YAAY,aAAa,GAAG,KAAK,IAAIA,IAAG,YAAY,aAAa,GAAG;AAC9F,UAAM,YAAY,KAAK,IAAI,aAAa,UAAU;AAElD,QAAI,SAAS;AACb,UAAM,aAAa,KAAK,IAAI,WAAW,SAAS,IAAI,KAAK,IAAI,UAAU,SAAS;AAChF,QAAI,aAAa,MAAM;AACrB,eAAS;AACT,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,gBAAgB,CAAC;AAAA,IACrD;AAEA,UAAM,kBAAkB,KAAK,IAAI,IAAIA,IAAG,KAAK,KAAK,KAAK,IAAIA,IAAG,YAAY,YAAY,GAAG,EAAE,IAAI,IAAIA,IAAG,IAAI;AAC1G,UAAM,mBAAmB,KAAK,IAAI,IAAIA,IAAG,KAAK,IAAI,KAAK,IAAIA,IAAG,YAAY,aAAa,GAAG,EAAE,IAAI,IAAIA,IAAG,IAAI;AAC3G,QAAI,kBAAkB,QAAQ,mBAAmB;AAAM,eAAS;AAChE,QAAI,kBAAkB,kBAAkB;AACtC,UAAI,kBAAkB;AAAM,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,gBAAgB,CAAC;AAAA,IACjF,OAAO;AACL,UAAI,mBAAmB;AAAM,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,eAAe,CAAC;AAAA,IACjF;AAEA,UAAM,mBAAmB,KAAK,IAAI,IAAIA,IAAG,KAAK,KAAK,KAAK,IAAIA,IAAG,YAAY,aAAa,GAAG,EAAE,IAAI,IAAIA,IAAG,IAAI;AAC5G,UAAM,kBAAkB,KAAK,IAAI,IAAIA,IAAG,KAAK,KAAK,KAAK,IAAIA,IAAG,YAAY,YAAY,GAAG,EAAE,IAAI,IAAIA,IAAG,IAAI;AAC1G,QAAI,kBAAkB,QAAQ,mBAAmB,QAAQ,kBAAkB,SAAS,mBAAmB;AAAO,eAAS;AACvH,QAAI,kBAAkB,QAAQ,mBAAmB;AAAM,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,eAAe,CAAC;AACzG,QAAI,kBAAkB,SAAS,mBAAmB;AAAO,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,aAAa,CAAC;AAGzG,QAAI;AAAQ,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,iBAAiB,CAAC;AAAA,EAClE;AACA,SAAO;AACT;AAEO,IAAMG,QAAO,CAAC,QAAuC;AAC1D,MAAI,CAAC;AAAK,WAAO,CAAC;AAClB,QAAM,WAA0D,CAAC;AACjE,WAASH,KAAI,GAAGA,KAAI,IAAI,QAAQA,MAAK;AACnC,UAAM,UAAoD,CAAC;AAC3D,QAAI,IAAIA,IAAG,gBAAgB;AACzB,iBAAW,CAAC,QAAQ,GAAG,KAAK,OAAO,QAAQ,IAAIA,IAAG,cAAc,GAAG;AACjE,YAAI,WAAW,cAAc,MAAM,QAAQ,GAAG,KAAK,IAAI;AAAI,kBAAQ,KAAK,EAAE,MAAM,OAAO,YAAY,GAAG,UAAU,IAAI,GAAG,CAAC;AAAA,MAC1H;AAAA,IACF;AACA,QAAI,WAAW,QAAQ,SAAS,GAAG;AACjC,YAAM,UAAU,QAAQ,OAAO,CAAC,MAAM,OAAQ,KAAK,SAAS,MAAM,MAAM,EAAE,SAAS,MAAM,KAAK,OAAO,CAAE;AACvG,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,GAAG,QAAQ,eAA8B,CAAC;AAC5E,YAAM,UAAU,QAAQ,OAAO,CAAC,MAAM,MAAO,KAAK,SAAS,KAAK,EAAE,SAAS,KAAK,OAAO,CAAE;AACzF,eAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,GAAG,QAAQ,UAAyB,CAAC;AAAA,IACzE;AACA,QAAI,IAAIA,IAAG,cAAc;AACvB,YAAM,QAAmB,MAAM,IAAIA,IAAG,YAAY;AAClD,iBAAW,QAAQ;AAAO,iBAAS,KAAK,EAAE,MAAMA,IAAG,SAAS,KAAK,KAAoB,CAAC;AAAA,IACxF;AAAA,EACF;AACA,SAAO;AACT;;;AC/HA,IAAM,iBAAyB,EAAE,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,SAAS,CAAC,GAAG,QAAQ,CAAC,GAAG,SAAS,CAAC,GAAG,aAAa,CAAC,GAAG,WAAW,GAAG,OAAO,KAAK;AAChJ,IAAI,kBAAkB;AAEf,SAASI,MAAK,WAAmBC,SAAwB;AAhBhE;AAiBE,QAAM,KAAK,IAAI;AACf,MAAI,CAAC;AAAW,WAAO,EAAE,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,SAAS,CAAC,GAAG,QAAQ,CAAC,GAAG,SAAS,CAAC,GAAG,aAAa,CAAC,GAAG,WAAW,GAAG,OAAO,KAAK;AAKxI,QAAM,UAAU,KAAK,IAAI,IAAI,UAAU;AAQvC,QAAM,iBAAiB,UAAU,MAAO,IAAI,KAAK,IAAI,UAAU,CAAC,IAAI;AAEpE,MAAI,UAAU;AAAQ,mBAAe,SAAS,UAAU;AACxD,MAAI,UAAU;AAAO,mBAAe,QAAQ,UAAU;AAGtD,MAAI,CAAC,eAAe,QAAS,UAAU,KAAK,WAAW,eAAe,KAAK,QAAS;AAClF,mBAAe,OAAO,KAAK,MAAM,KAAK,UAAU,UAAU,IAAoB,CAAC;AAAA,EACjF,OAAO;AACL,aAASC,KAAI,GAAGA,KAAI,UAAU,KAAK,QAAQA,MAAK;AAC9C,YAAM,MAAM,UAAU,KAAKA,IAAG,IAC3B,IAAI,CAAC,aAAa,QAAQ,iBAAiB,KAAK,eAAe,KAAKA,IAAG,IAAI,KAAK,eAAe,cAAc;AAChH,YAAM,SAAS,UAAU,KAAKA,IAAG,OAC9B,IAAI,CAAC,aAAa,QAAQ,iBAAiB,KAAK,eAAe,KAAKA,IAAG,OAAO,KAAK,eAAe,cAAc;AACnH,YAAM,YAAa,UAAU,KAAKA,IAAG,UAClC,IAAI,CAAC,QAAQ,MAAG;AA9CzB,YAAAC,KAAAC,KAAAC,KAAAC,KAAAC,KAAAC,KAAAC,KAAAC,KAAAC;AA8C6B;AAAA,UACnB,OAAO,OAAO;AAAA,UACd,MAAM,OAAO;AAAA,UACb,UAAU;AAAA,YACR,eAAe,KAAKT,IAAG,UAAU,OAAO,iBAAiB,MAAM,eAAe,KAAKA,IAAG,UAAU,GAAG,SAAS,MAAM,MAAM,OAAO,SAAS,MAAM,MAAM,iBAAiB,OAAO,SAAS;AAAA,YACrL,eAAe,KAAKA,IAAG,UAAU,OAAO,iBAAiB,MAAM,eAAe,KAAKA,IAAG,UAAU,GAAG,SAAS,MAAM,MAAM,OAAO,SAAS,MAAM,MAAM,iBAAiB,OAAO,SAAS;AAAA,YACrL,eAAe,KAAKA,IAAG,UAAU,OAAO,iBAAiB,MAAM,eAAe,KAAKA,IAAG,UAAU,GAAG,SAAS,MAAM,MAAM,OAAO,SAAS,MAAM,MAAM,iBAAiB,OAAO,SAAS;AAAA,UACvL;AAAA,UACA,aAAa;AAAA,YACX,eAAe,KAAKA,IAAG,UAAU,OAAO,iBAAiB,MAAM,eAAe,KAAKA,IAAG,UAAU,GAAG,YAAY,MAAM,MAAM,OAAO,YAAY,MAAM,MAAM,iBAAiB,OAAO,YAAY;AAAA,YAC9L,eAAe,KAAKA,IAAG,UAAU,OAAO,iBAAiB,MAAM,eAAe,KAAKA,IAAG,UAAU,GAAG,YAAY,MAAM,MAAM,OAAO,YAAY,MAAM,MAAM,iBAAiB,OAAO,YAAY;AAAA,YAC9L,eAAe,KAAKA,IAAG,UAAU,OAAO,iBAAiB,MAAM,eAAe,KAAKA,IAAG,UAAU,GAAG,YAAY,MAAM,MAAM,OAAO,YAAY,MAAM,MAAM,iBAAiB,OAAO,YAAY;AAAA,UAChM;AAAA,UACA,UAAU;AAAA,YACR,eAAe,KAAKA,IAAG,UAAU,OAAO,iBAAiB,QAAMC,MAAA,eAAe,KAAKD,IAAG,UAAU,GAAG,aAApC,gBAAAC,IAA+C,OAAM,QAAMC,MAAA,OAAO,aAAP,gBAAAA,IAAkB,OAAM,MAAM,kBAAiBC,MAAA,OAAO,aAAP,gBAAAA,IAAkB;AAAA,YAC3L,eAAe,KAAKH,IAAG,UAAU,OAAO,iBAAiB,QAAMI,MAAA,eAAe,KAAKJ,IAAG,UAAU,GAAG,aAApC,gBAAAI,IAA+C,OAAM,QAAMC,MAAA,OAAO,aAAP,gBAAAA,IAAkB,OAAM,MAAM,kBAAiBC,MAAA,OAAO,aAAP,gBAAAA,IAAkB;AAAA,YAC3L,eAAe,KAAKN,IAAG,UAAU,OAAO,iBAAiB,QAAMO,MAAA,eAAe,KAAKP,IAAG,UAAU,GAAG,aAApC,gBAAAO,IAA+C,OAAM,QAAMC,MAAA,OAAO,aAAP,gBAAAA,IAAkB,OAAM,MAAM,kBAAiBC,MAAA,OAAO,aAAP,gBAAAA,IAAkB;AAAA,UAC7L;AAAA,QACF;AAAA,OAAE;AAEJ,YAAMC,eAAiD,CAAC;AACxD,UAAIC,UAAS,EAAE,WAAW,CAAC,EAAE;AAC7B,WAAI,WAAAZ,QAAO,SAAP,mBAAa,cAAb,mBAAwB,SAAS;AAAkB,QAAAY,UAAS;AAAA,gBACvD,WAAAZ,QAAO,SAAP,mBAAa,cAAb,mBAAwB,SAAS;AAAc,QAAAY,UAAS;AAAA,gBACxD,WAAAZ,QAAO,SAAP,mBAAa,cAAb,mBAAwB,SAAS;AAAY,QAAAY,UAAS;AAC/D,iBAAW,CAAC,MAAM,OAAO,KAAK,OAAO,QAAQA,QAAO,SAAqC,GAAG;AAC1F,cAAM,KAAqB,CAAC;AAC5B,iBAAS,IAAI,GAAG,IAAI,QAAQ,SAAS,GAAG,KAAK;AAC3C,gBAAM,MAAM,UAAU,KAAK,CAAC,OAAO,GAAG,SAAS,QAAQ,EAAE;AACzD,gBAAM,MAAM,UAAU,KAAK,CAAC,OAAO,GAAG,SAAS,QAAQ,IAAI,EAAE;AAE7D,cAAI,OAAO;AAAK,eAAG,KAAK,CAAC,IAAI,UAAU,IAAI,QAAQ,CAAC;AAAA,QACtD;AACA,QAAAD,aAAY,QAAQ;AAAA,MACtB;AACA,qBAAe,KAAKV,MAAK,EAAE,GAAG,UAAU,KAAKA,KAAI,KAAK,QAAQ,WAAW,aAAaU,aAAyC;AAAA,IACjI;AAAA,EACF;AAGA,MAAI,CAAC,eAAe,QAAS,UAAU,KAAK,WAAW,eAAe,KAAK,QAAS;AAClF,mBAAe,OAAO,KAAK,MAAM,KAAK,UAAU,UAAU,IAAoB,CAAC;AAAA,EACjF,OAAO;AACL,aAASV,KAAI,GAAGA,KAAI,UAAU,KAAK,QAAQA,MAAK;AAC9C,YAAM,MAAO,UAAU,KAAKA,IAAG,IAC5B,IAAI,CAAC,GAAG,QAAQ,iBAAiB,KAAK,eAAe,KAAKA,IAAG,IAAI,KAAK,KAAK,cAAc;AAC5F,YAAM,SAAU,UAAU,KAAKA,IAAG,OAC/B,IAAI,CAAC,GAAG,QAAQ,iBAAiB,KAAK,eAAe,KAAKA,IAAG,OAAO,KAAK,KAAK,cAAc;AAC/F,UAAI,eAAe,KAAKA,IAAG,UAAU,WAAW,UAAU,KAAKA,IAAG,UAAU;AAAQ,uBAAe,KAAKA,IAAG,YAAY,UAAU,KAAKA,IAAG;AACzI,YAAM,YAAY,UAAU,KAAKA,IAAG,aAAa,UAAU,KAAKA,IAAG,UAAU,SAAS,IAAI,UAAU,KAAKA,IAAG,UACzG,IAAI,CAAC,UAAU,MAAM,SACnB,IAAI,CAAC,OAAO,QAAS,iBAAiB,MAAM,eAAe,KAAKA,IAAG,UAAU,GAAG,MAAM,MAAM,SAAS,MAAM,cAAe,CAAU,IACrI,CAAC;AACL,UAAIU,eAAc,CAAC;AACnB,UAAI,OAAO,KAAK,eAAe,KAAKV,IAAG,WAAW,EAAE,WAAW,OAAO,KAAK,UAAU,KAAKA,IAAG,WAAW,EAAE,QAAQ;AAChH,uBAAe,KAAKA,IAAG,cAAc,UAAU,KAAKA,IAAG;AACvD,QAAAU,eAAc,eAAe,KAAKV,IAAG;AAAA,MACvC,WAAW,UAAU,KAAKA,IAAG,aAAa;AACxC,mBAAW,OAAO,OAAO,KAAK,UAAU,KAAKA,IAAG,WAAW,GAAG;AAC5D,UAAAU,aAAY,OAAO,UAAU,KAAKV,IAAG,YAAY,QAAQ,UAAU,KAAKA,IAAG,YAAY,KAAK,KACxF,UAAU,KAAKA,IAAG,YAAY,KAC7B,IAAI,CAAC,KAAK,MAAc,IACtB,IAAI,CAAC,OAAe,QAAgB,iBAAiB,KAAK,eAAe,KAAKA,IAAG,YAAY,KAAK,GAAG,KAAK,SAAS,cAAc,CAAC,IACrI;AAAA,QACN;AAAA,MACF;AACA,qBAAe,KAAKA,MAAK,EAAE,GAAG,UAAU,KAAKA,KAAI,KAAK,QAAQ,WAAW,aAAaU,aAAyC;AAAA,IACjI;AAAA,EACF;AAGA,MAAI,CAAC,eAAe,QAAS,UAAU,KAAK,WAAW,eAAe,KAAK,QAAS;AAClF,mBAAe,OAAO,KAAK,MAAM,KAAK,UAAU,UAAU,IAAoB,CAAC;AAAA,EACjF,OAAO;AACL,aAASV,KAAI,GAAGA,KAAI,UAAU,KAAK,QAAQA,MAAK;AAC9C,YAAM,MAAO,UAAU,KAAKA,IAAG,IAC5B,IAAI,CAAC,GAAG,QAAQ,iBAAiB,KAAK,eAAe,KAAKA,IAAG,IAAI,KAAK,KAAK,cAAc;AAC5F,YAAM,SAAU,UAAU,KAAKA,IAAG,OAC/B,IAAI,CAAC,GAAG,QAAQ,iBAAiB,KAAK,eAAe,KAAKA,IAAG,OAAO,KAAK,KAAK,cAAc;AAC/F,UAAI,UAAU,KAAKA,IAAG,UAAU;AAC9B,cAAM,WAIF,EAAE,QAAQ,CAAC,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,GAAG,CAAC,GAAG,OAAO,EAAE,MAAM,GAAG,KAAK,GAAG,OAAO,EAAE,GAAG,MAAM,EAAE,SAAS,GAAG,UAAU,EAAE,EAAE;AACnH,iBAAS,UAAS,eAAU,KAAKA,IAAG,aAAlB,mBAA4B;AAC9C,iBAAS,QAAQ;AAAA,UACf,QAAQ,iBAAiB,QAAM,0BAAe,KAAKA,IAAG,aAAvB,mBAAiC,UAAjC,mBAAwC,SAAQ,QAAM,qBAAU,KAAKA,IAAG,aAAlB,mBAA4B,UAA5B,mBAAmC,SAAQ,MAAM;AAAA,UACtI,OAAO,iBAAiB,QAAM,0BAAe,KAAKA,IAAG,aAAvB,mBAAiC,UAAjC,mBAAwC,QAAO,QAAM,qBAAU,KAAKA,IAAG,aAAlB,mBAA4B,UAA5B,mBAAmC,QAAO,MAAM;AAAA,UACnI,SAAS,iBAAiB,QAAM,0BAAe,KAAKA,IAAG,aAAvB,mBAAiC,UAAjC,mBAAwC,UAAS,QAAM,qBAAU,KAAKA,IAAG,aAAlB,mBAA4B,UAA5B,mBAAmC,UAAS,MAAM;AAAA,QAC3I;AACA,iBAAS,OAAO;AAAA,UAEd,WAAW,iBAAiB,QAAM,0BAAe,KAAKA,IAAG,aAAvB,mBAAiC,SAAjC,mBAAuC,YAAW,QAAM,qBAAU,KAAKA,IAAG,aAAlB,mBAA4B,SAA5B,mBAAkC,YAAW,MAAM;AAAA,UAC7I,YAAY,iBAAiB,QAAM,0BAAe,KAAKA,IAAG,aAAvB,mBAAiC,SAAjC,mBAAuC,aAAY,QAAM,qBAAU,KAAKA,IAAG,aAAlB,mBAA4B,SAA5B,mBAAkC,aAAY,MAAM;AAAA,QAClJ;AACA,uBAAe,KAAKA,MAAK,EAAE,GAAG,UAAU,KAAKA,KAAI,UAAU,KAAK,OAAO;AAAA,MACzE;AACA,qBAAe,KAAKA,MAAK,EAAE,GAAG,UAAU,KAAKA,KAAI,KAAK,OAAO;AAAA,IAC/D;AAAA,EACF;AAGA,MAAI,CAAC,eAAe,UAAW,UAAU,OAAO,WAAW,eAAe,OAAO,QAAS;AACxF,mBAAe,SAAS,KAAK,MAAM,KAAK,UAAU,UAAU,MAAwB,CAAC;AAAA,EACvF,OAAO;AACL,aAASA,KAAI,GAAGA,KAAI,UAAU,OAAO,QAAQA,MAAK;AAChD,YAAM,MAAO,UAAU,OAAOA,IAAG,IAC9B,IAAI,CAAC,GAAG,QAAQ,iBAAiB,KAAK,eAAe,OAAOA,IAAG,IAAI,KAAK,KAAK,cAAc;AAC9F,YAAM,SAAU,UAAU,OAAOA,IAAG,OACjC,IAAI,CAAC,GAAG,QAAQ,iBAAiB,KAAK,eAAe,OAAOA,IAAG,OAAO,KAAK,KAAK,cAAc;AACjG,qBAAe,OAAOA,MAAK,EAAE,GAAG,UAAU,OAAOA,KAAI,KAAK,OAAO;AAAA,IACnE;AAAA,EACF;AAGA,MAAI,UAAU,SAAS;AACrB,UAAM,aAAa,UAAU;AAC7B,QAAI,CAAC,eAAe,WAAY,WAAW,WAAW,eAAe,QAAQ,QAAS;AACpF,qBAAe,UAAU,KAAK,MAAM,KAAK,UAAU,UAA4B,CAAC;AAAA,IAClF,OAAO;AACL,eAASA,KAAI,GAAGA,KAAI,WAAW,QAAQA,MAAK;AAC1C,uBAAe,QAAQA,IAAG,MAAO,WAAWA,IAAG,IAC5C,IAAI,CAAC,KAAK,QAAQ,iBAAiB,KAAK,eAAe,QAAQA,IAAG,IAAI,KAAK,OAAO,cAAc;AAAA,MACrG;AAAA,IACF;AAAA,EACF;AAGA,MAAI,UAAU;AAAS,mBAAe,UAAU,UAAU;AAG1D,QAAM,KAAK,IAAI;AACf,oBAAkBY,KAAI,UAAU,kBAAkB,KAAK,MAAM,KAAK,EAAE,IAAI,KAAK,MAAM,KAAK,EAAE;AAC1F,MAAI,UAAU;AAAa,mBAAe,cAAc,EAAE,GAAG,UAAU,aAAa,aAAa,gBAAgB;AAEjH,SAAO;AACT;;;ACvLA;AAAA;AAAA;AAAA,eAAAC;AAAA,EAAA;AAAA;AAWO,SAAS,SAAS,aAAyB,aAAyBC,WAAwB,EAAE,OAAO,GAAG,YAAY,GAAG,GAAG;AAE/H,MAAIC,OAAM;AACV,WAASC,KAAI,GAAGA,KAAI,YAAY,QAAQA,MAAK;AAC3C,UAAM,OAAQ,CAACF,SAAQ,SAASA,SAAQ,UAAU,IAAM,YAAYE,MAAK,YAAYA,MAAO,KAAK,IAAI,YAAYA,MAAK,YAAYA,GAAE;AACpI,IAAAD,QAAQ,CAACD,SAAQ,SAASA,SAAQ,UAAU,IAAM,OAAO,OAAS,QAAQA,SAAQ;AAAA,EACpF;AACA,UAAQA,SAAQ,cAAc,MAAMC;AACtC;AAGA,IAAM,oBAAoB,CAAC,MAAM,OAAOE,MAAKC,SAAQ;AACnD,MAAI,SAAS;AAAG,WAAO;AACvB,QAAM,OAAO,UAAU,IAAI,KAAK,KAAK,IAAI,IAAI,SAAS,IAAI;AAC1D,QAAMC,SAAQ,IAAK,OAAO,MAAOF,SAAQC,OAAMD;AAC/C,QAAMG,SAAQ,KAAK,IAAI,KAAK,IAAID,OAAM,CAAC,GAAG,CAAC;AAC3C,SAAOC;AACT;AAaO,SAAS,WAAW,aAAyB,aAAyBN,WAAwB,EAAE,OAAO,GAAG,YAAY,IAAI,KAAK,KAAK,KAAK,IAAI,GAAG;AACrJ,QAAM,OAAO,SAAS,aAAa,aAAaA,QAAO;AACvD,SAAO,kBAAkB,MAAMA,SAAQ,SAAS,GAAGA,SAAQ,OAAO,GAAGA,SAAQ,OAAO,CAAC;AACvF;AAWO,SAASD,OAAM,YAAwB,aAAgCC,WAAwB,EAAE,OAAO,GAAG,YAAY,IAAI,WAAW,GAAG,KAAK,KAAK,KAAK,IAAI,GAAG;AACpK,MAAI,CAAC,MAAM,QAAQ,UAAU,KAAK,CAAC,MAAM,QAAQ,WAAW,KAAK,WAAW,SAAS,MAAM,YAAY,WAAW,KAAK,WAAW,WAAW,YAAY,GAAG,QAAQ;AAClK,WAAO,EAAE,OAAO,IAAI,UAAU,OAAO,mBAAmB,YAAY,EAAE;AAAA,EACxE;AACA,MAAI,iBAAiB,OAAO;AAC5B,MAAIO,SAAQ;AACZ,WAASL,KAAI,GAAGA,KAAI,YAAY,QAAQA,MAAK;AAC3C,UAAM,MAAM,SAAS,YAAY,YAAYA,KAAIF,QAAO;AACxD,QAAI,MAAM,gBAAgB;AACxB,uBAAiB;AACjB,MAAAO,SAAQL;AAAA,IACV;AACA,QAAI,kBAAkBF,SAAQ,aAAa;AAAI;AAAA,EACjD;AACA,QAAM,uBAAuB,kBAAkB,gBAAgBA,SAAQ,SAAS,GAAGA,SAAQ,OAAO,GAAGA,SAAQ,OAAO,CAAC;AACrH,SAAO,EAAE,OAAAO,QAAO,UAAU,gBAAgB,YAAY,qBAAqB;AAC7E;;;ACjEO,SAASC,MAAK,OAA0B,QAA2B,OAA0B,UAAgC,OAAuD;AAN3L;AAOE,MAAI,KAAK;AACT,QAAM,UAA+B,CAAC;AACtC,aAAWC,SAAQ,OAAO;AACxB,UAAMC,UAAuB,EAAE,IAAI,MAAM,MAAAD,OAAM,MAAM,MAAM,OAAO,EAAE,MAAM,MAAM,OAAO,KAAK,GAAG,UAAU,CAAC,GAAG,KAAK,CAAC,GAAG,GAAG,GAAG,CAAC,EAAE;AAC/H,eAAWE,SAAQ,QAAQ;AACzB,UAAIF,MAAK,IAAI,KAAKE,MAAK,IAAI,MACtBF,MAAK,IAAI,KAAKE,MAAK,IAAI,KAAKA,MAAK,IAAI,MACrCF,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKE,MAAK,IAAI,MACrCF,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKE,MAAK,IAAI,KAAKA,MAAK,IAAI,IAAI;AAC1D,QAAAD,QAAO,OAAOC;AAAA,MAChB;AAAA,IACF;AACA,QAAID,QAAO,MAAM;AACf,iBAAWE,SAAQ,OAAO;AACxB,YAAIA,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,MAC3CE,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,KAAKA,QAAO,KAAK,IAAI,MACjEE,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,MAC5CE,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,KAAKA,QAAO,KAAK,IAAI,IAAI;AACxE,cAAIA,QAAO;AAAO,YAAAA,QAAO,MAAM,OAAOE;AAAA,QACxC;AACA,YAAIA,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,KAAKA,QAAO,KAAK,IAAI,MAClDE,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,MAC9BE,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,MAC5CE,MAAK,IAAI,KAAKA,MAAK,IAAI,KAAKF,QAAO,KAAK,IAAI,KAAKA,QAAO,KAAK,IAAI,IAAI;AACxE,cAAIA,QAAO;AAAO,YAAAA,QAAO,MAAM,QAAQE;AAAA,QACzC;AAAA,MACF;AAAA,IACF;AACA,eAAWC,YAAW,UAAU;AAC9B,UAAIA,SAAQ,YAAY,UAAaA,SAAQ,YAAYJ,MAAK;AAAI,cAAAC,QAAO,aAAP,mBAAiB,KAAKG;AAAA,eAC/EA,SAAQ,YAAY,UAAaA,SAAQ,YAAYJ,MAAK;AAAI,cAAAC,QAAO,aAAP,mBAAiB,KAAKG;AAAA,eACpFA,SAAQ,YAAY,UAAaA,SAAQ,cAAY,KAAAH,QAAO,SAAP,mBAAa;AAAI,cAAAA,QAAO,aAAP,mBAAiB,KAAKG;AAAA,eAC5FA,SAAQ,YAAY,UAAaA,SAAQ,cAAY,WAAAH,QAAO,UAAP,mBAAc,SAAd,mBAAoB;AAAI,cAAAA,QAAO,aAAP,mBAAiB,KAAKG;AAAA,eACnGA,SAAQ,YAAY,UAAaA,SAAQ,cAAY,WAAAH,QAAO,UAAP,mBAAc,UAAd,mBAAqB;AAAI,cAAAA,QAAO,aAAP,mBAAiB,KAAKG;AAAA,IAC/G;AAGA,UAAM,IAAc,CAAC;AACrB,UAAM,IAAc,CAAC;AACrB,UAAM,YAAY,CAAC,QAAyB;AAC1C,UAAI,OAAO,IAAI,WAAW,GAAG;AAC3B,UAAE,KAAK,IAAI,IAAI,IAAI,KAAK,IAAI,EAAE;AAC9B,UAAE,KAAK,IAAI,IAAI,IAAI,KAAK,IAAI,EAAE;AAAA,MAChC;AAAA,IACF;AACA,eAAU,KAAAH,QAAO,SAAP,mBAAa,GAAG;AAC1B,eAAU,KAAAA,QAAO,SAAP,mBAAa,GAAG;AAC1B,eAAU,WAAAA,QAAO,UAAP,mBAAc,SAAd,mBAAoB,GAAG;AACjC,eAAU,WAAAA,QAAO,UAAP,mBAAc,UAAd,mBAAqB,GAAG;AAClC,UAAM,OAAO,KAAK,IAAI,GAAG,CAAC;AAC1B,UAAM,OAAO,KAAK,IAAI,GAAG,CAAC;AAC1B,IAAAA,QAAO,MAAM,CAAC,MAAM,MAAM,KAAK,IAAI,GAAG,CAAC,IAAI,MAAM,KAAK,IAAI,GAAG,CAAC,IAAI,IAAI;AAGtE,QAAI,SAAS,MAAM,MAAM,MAAM;AAAI,MAAAA,QAAO,SAAS,CAACA,QAAO,IAAI,KAAK,MAAM,IAAIA,QAAO,IAAI,KAAK,MAAM,IAAIA,QAAO,IAAI,KAAK,MAAM,IAAIA,QAAO,IAAI,KAAK,MAAM,EAAE;AAE1J,YAAQ,KAAKA,OAAM;AAAA,EACrB;AACA,SAAO;AACT;;;AC7DO,IAAMI,QAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AA0Jb,IAAMC,QAAO;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;AAAA;;;ACjJpB,eAAe,aAAa,UAA8C;AACxE,QAAM,YAAY,CAAC,QAAgB,OAAO,+BAA+B,MAAM,QAAQ,eAAe,QAAQ,EAAE,KAAK,CAACC,SAAQA,KAAI,KAAK,CAAC;AACxI,MAAI;AACJ,MAAI;AACJ,UAAQ,SAAS,OAAO;AAAA,SACjB;AAAQ,aAAO,MAAM,UAAiBC,KAAI;AAAG;AAAA,SAC7C;AAAA,SACA;AAAQ,aAAO,MAAM,UAAiBC,KAAI;AAAG;AAAA;AACzC,aAAO;AAAA;AAElB,MAAI,MAAM;AACR,UAAM,SAAS,MAAM,kBAAkB,IAAI;AAC3C,UAAM,MAAM,SAAS,OAAO,QAAQ,SAAS,MAAM;AACnD,WAAO,MAAM;AAAA,EACf;AACA,SAAO;AACT;AAEA,eAAe,aAAa,UAA8C;AACxE,SAAO,IAAI,QAAQ,CAAC,YAAY;AAC9B,QAAI;AAEJ,YAAQ,SAAS,OAAO;AAAA,WACjB;AAEH,cAAM,4BAAmCD;AACzC;AAAA,WACG;AAAA,WACA;AAEH,cAAM,4BAAmCC;AACzC;AAAA;AAEA,cAAM;AAAA;AAGV,QAAI;AACJ,QAAI,OAAO,UAAU;AAAa,YAAM,IAAI,MAAM;AAAA,aAEzCC,KAAI;AAAO,YAAM,IAAIA,KAAI,MAAM;AAAA;AACnC;AACL,QAAI,SAAS,YAAY;AACvB,YAAMC,UAAe,OAAO,IAAI,cAAc,IAAI,aAAa;AAC/D,UAAI,CAACA,SAAQ;AACX,YAAI,0BAA0B;AAC9B,gBAAQ,MAAS;AAAA,MACnB,OAAO;AACL,cAAM,MAAMA,QAAO,WAAW,IAAI;AAClC,YAAI;AAAK,cAAI,UAAU,KAAK,GAAG,CAAC;AAEhC,cAAMC,UAAS,MAAM,SAAS,MAAMD,OAAM;AAC1C,cAAM,MAAM,MAAM,SAAS,OAAOC,QAAO,QAAkB,SAAS,MAAM;AAC1E,gBAAQ,GAAG;AAAA,MACb;AAAA,IACF;AACA,QAAI;AAAK,UAAI,MAAM;AAAA;AACd,cAAQ,MAAS;AAAA,EACxB,CAAC;AACH;AAEA,eAAe,WAAW,UAA8C;AACtE,QAAMC,QAAO,CAAC,QAAgB,OAAO,KAAK,KAAK,QAAQ;AACvD,MAAI;AACJ,MAAI,SAAS,OAAO,WAAW;AAAQ,UAAMA,MAAYL,KAAI;AAAA;AACxD,UAAMK,MAAYJ,KAAI;AAC3B,MAAI;AACJ,MAAI,UAAU,kBAAI;AAEhB,UAAM,OAAU,SAAQ,WAAW,GAAG;AACtC,UAAM,WAAW,KAAK,WAAW,CAAC;AAClC,aAAS,GAAG,QAAQ,IAAI;AAExB,UAAM,MAAM,SAAS,OAAO,UAAU,SAAS,MAAM;AACrD,aAAS,GAAG,QAAQ,QAAQ;AAAA,EAC9B,OAAO;AACL,QAAI,SAAS,OAAO;AAAO,UAAI,6BAA6B;AAAA,EAQ9D;AACA,SAAO;AACT;AAEA,eAAe,aAAa,UAAiB;AAC3C,MAAI;AACJ,MAAI,OAAO,sBAAsB;AAAY,UAAM,MAAM,aAAa,QAAQ;AAAA,WACrE,OAAO,UAAU,eAAeC,KAAI,WAAW;AAAW,UAAM,MAAM,aAAa,QAAQ;AAAA;AAC/F,UAAM,MAAM,WAAW,QAAQ;AACpC,SAAO;AACT;AAGA,eAAsB,WAAW,WAAmB;AAClD,MAAI,CAAI,IAAI,EAAE,aAAa;AAAwB;AACnD,QAAM,cAAiB,WAAW;AAClC,QAAM,eAAkB,QAAQ;AAChC,MAAK,gBAAgB,WAAW,gBAAgB,cAAe,CAAC,gBAAgB,CAAC,aAAa,yBAAyB;AAErH;AAAA,EACF;AACA,EAAG,IAAI,EAAE,IAAI,uBAAuB,IAAI;AACxC,QAAM,kBAAqB,OAAO,EAAE,MAAM;AAC1C,QAAM,iBAA2B,CAAC;AAClC,aAAW,CAAC,WAAWI,OAAK,KAAK,OAAO,QAAQ,SAAS,EAAE,OAAO,CAAC,CAAC,KAAK,GAAG,MAAO,QAAQ,QAAQ,QAAQ,IAAK,GAAG;AACjH,UAAM,QAASA,QAAM,UAAUA,QAAM,OAAO,MAAMA,QAAM,OAAO,GAAG,QAAS,CAAC,GAAGA,QAAM,OAAO,GAAG,KAAK,IAAI,CAAC,GAAG,IAAI,IAAI,CAAC;AACrH,UAAM,QAASA,QAAM,UAAUA,QAAM,OAAO,MAAMA,QAAM,OAAO,GAAG,QAASA,QAAM,OAAO,GAAG,QAAQ;AACnG,aAAS,MAAM,GAAG,MAAM,MAAM,QAAQ,OAAO;AAC3C,UAAI,MAAM,SAAS;AAAI,cAAM,OAAO,QAAQ,IAAI,IAAI;AAAA,IACtD;AACA,UAAMF,UAAY,MAAM,OAAO,KAAK;AAEpC,QAAI;AACF,YAAM,MAAME,QAAM,QAAQF,OAAM;AAChC,qBAAe,KAAK,SAAS;AAC7B,UAAI,MAAM,QAAQ,GAAG;AAAG,YAAI,QAAQ,CAACG,OAAS,QAAQA,EAAC,CAAC;AAAA;AACnD,QAAG,QAAQ,GAAG;AAAA,IACrB,SAAQC,IAAN;AACA,UAAI,uBAAuB,SAAS;AAAA,IACtC;AACA,IAAG,QAAQJ,OAAM;AAAA,EACnB;AACA,QAAM,UAAU,MAAM,aAAa,4BAA4B;AAC/D,eAAa,oBAAoB;AACjC,MAAI,wBAAwB,cAAc;AAC1C,MAAI,yBAAyB,QAAQ,MAAM;AAC3C,EAAG,IAAI,EAAE,IAAI,uBAAuB,KAAK;AACzC,QAAM,gBAAmB,OAAO,EAAE,MAAM;AACxC,MAAK,gBAAgB,kBAAmB;AAAG,QAAI,gBAAgB,gBAAgB,eAAe;AAChG;AAOA,eAAsB,OAAO,UAAiB,YAA2D;AACvG,QAAM,KAAK,IAAI;AACf,WAAS,QAAQ;AACjB,MAAI;AAAY,aAAS,SAAS,UAAU,SAAS,QAAQ,UAAU;AACvE,MAAI,CAAC,SAAS,OAAO,UAAU,SAAS,OAAO,OAAO,WAAW,KAAK,SAAS,OAAO,WAAW,QAAQ;AACvG,WAAO,EAAE,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,SAAS,CAAC,GAAG,QAAQ,CAAC,GAAG,aAAa,SAAS,aAAa,WAAW,IAAI,GAAG,SAAS,CAAC,GAAG,OAAO,KAAK;AAAA,EAChJ;AACA,SAAO,IAAI,QAAQ,OAAO,YAAY;AACpC,UAAM,WAAW,SAAS,MAAM;AAChC,UAAM,MAAM,MAAM,aAAa,QAAQ;AACvC,UAAM,KAAK,IAAI;AACf,QAAI,SAAS,OAAO;AAAO,UAAI,UAAU,SAAS,OAAO,QAAQ,KAAK,MAAM,KAAK,EAAE,GAAG,IAAI;AAC1F,aAAS,KAAK,QAAQ;AACtB,YAAQ,GAAG;AAAA,EACb,CAAC;AACH;;;ACxKA;AAsDO,IAAM,QAAN,MAAY;AAAA,EAuEjB,YAAY,YAA8B;AArE1C;AAKA;AAKA;AAMA;AAGA;AAMA;AAGA;AAOA;AAMA;AAWA;AAEA;AAEA;AAEA;AACA;AACA;AACA;AAEA;AA2DA,mCAAU,IAAI,QAAkB;AAC9B,UAAI,CAAC,mBAAK;AAAqB;AAC/B,YAAM,iBAAiB,KAAK,GAAG,OAAO,EAAE,MAAM;AAC9C,YAAM,kBAAkB,mBAAK;AAC7B,yBAAK,aAAc;AACnB,YAAM,SAAS,iBAAiB;AAChC,UAAI,WAAW;AAAG,YAAI,GAAG,KAAK,MAAM;AAAA,IACtC;AAGA,gCAAU,CAACK,WAAgC;AACzC,UAAI,CAAC,mBAAK;AAAc,eAAO;AAC/B,UAAI,CAACA;AAAO,eAAO;AACnB,UAAI,KAAK,IAAI,QAAQ,EAAEA,kBAAoB;AAAS,eAAO;AAC3D,UAAI;AACF,aAAK,GAAG,WAAW;AAAA,MACrB,SAAQC,IAAN;AACA,eAAO;AAAA,MACT;AACA,aAAO;AAAA,IACT;AAeA,wBAAO,cAAmB;AAE1B,wBAAO,YAAiB;AAExB,wBAAO,SAAcC;AAoGrB,gCAAO,CAAC,UAAkB;AA7T5B;AA8TI,UAAI,KAAK,UAAU,KAAK,OAAO;AAAe,mBAAK,WAAL,mBAAa,cAAc,IAAI,MAAM,KAAK;AAAA,IAC1F;AA/TF;AA8HI,SAAK,MAAMC;AAMX,UAAM,eAAa,KAAG,MAAH,mBAAY,SAAW,SAAc,QAAQ,SAAS,EAAE;AAC3E,WAAS,WAAW,8DAA8D;AAClF,WAAS,gBAAgBA,KAAI,UAAU,eAAe;AACtD,WAAS,UAAUA,KAAI,UAAU,YAAY;AAC7C,SAAK,UAAcC;AACnB,WAAO,eAAe,MAAM,WAAW,EAAE,OAAWA,SAAQ,CAAC;AAC7D,SAAK,SAAS,KAAK,MAAM,KAAK,UAAU,MAAQ,CAAC;AACjD,WAAO,KAAK,KAAK,MAAM;AACvB,SAAK,OAAO,cAAc,OAAO,cAAc;AAC/C,QAAI;AAAY,WAAK,SAAS,UAAU,KAAK,QAAQ,UAAU;AAC/D,wBAAoB,KAAK,MAAM;AAC/B,SAAK,KAAK;AACV,SAAK,QAAQ;AACb,uBAAK,aAAc;AACnB,uBAAK,qBAAsB;AAC3B,uBAAK,cAAe;AACpB,SAAK,cAAc,CAAC;AACpB,SAAK,SAAU,OAAO,gBAAgB,cAAe,IAAI,YAAY,IAAI;AAEzE,SAAK,SAAS,IAAW,OAAO;AAEhC,SAAK,OAAO;AAAA,MACV,SAAcC;AAAA,MACd,QAAQ,CAACL,QAAwD,WAA2BM,QAAON,QAAO,MAAM;AAAA,MAChH,MAAM,CAAC,QAAmB,QAAsBK,aAAwC,KAAK,QAAQ,QAAQA,QAAO;AAAA,MACpH,MAAM,CAAC,QAAmB,QAAsBA,aAAwC,KAAK,QAAQ,QAAQA,QAAO;AAAA,MACpH,MAAM,CAAC,QAAmB,QAAsBA,aAAwC,KAAK,QAAQ,QAAQA,QAAO;AAAA,MACpH,SAAS,CAAC,QAAmB,QAAyBA,aAAwC,QAAQ,QAAQ,QAAQA,QAAO;AAAA,MAC7H,QAAQ,CAAC,QAAmB,QAAwBA,aAAwC,OAAO,QAAQ,QAAQA,QAAO;AAAA,MAC1H,QAAQ,CAAC,QAAmB,QAAwBA,aAAwC,OAAO,QAAQ,QAAQA,QAAO;AAAA,MAC1H,KAAK,CAAC,QAAmB,QAAgBA,aAAwCE,KAAI,QAAQ,QAAQF,QAAO;AAAA,IAC9G;AACA,SAAK,SAAS,EAAE,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,SAAS,CAAC,GAAG,QAAQ,CAAC,GAAG,aAAa,CAAC,GAAG,WAAW,GAAG,SAAS,CAAC,GAAG,OAAO,KAAK;AAG/H,SAAK,UAAU,EAAE,QAAQ,MAAM,QAAQ,KAAK;AAE5C,SAAK,oBAA6B;AAClC,SAAK,YAAqB;AAE1B,SAAK,KAAaG;AAElB,SAAK,KAAK,QAAQ;AAAA,EACpB;AAAA,EA0BA,QAAc;AACZ,UAAM,iBAAiB,KAAK,OAAO;AACnC,SAAK,SAAS,KAAK,MAAM,KAAK,UAAU,MAAQ,CAAC;AACjD,SAAK,OAAO,UAAU;AAAA,EACxB;AAAA,EAGA,SAAS,YAA8B;AACrC,WAAO,SAAS,QAAU,cAAc,KAAK,MAAM;AAAA,EACrD;AAAA,EAUA,MAAc;AACZ,WAAO,IAAI;AAAA,EACb;AAAA,EAQA,MAAMR,QAAcS,aAAqB,MAAM;AAC7C,WAAaC,SAAQV,QAAO,KAAK,QAAQS,UAAS;AAAA,EACpD;AAAA,EAYA,MAAM,aAAaT,QAAc,YAA6G;AAC5I,WAAoBU,SAAQV,QAAO,YAAY,KAAK,MAAM;AAAA,EAC5D;AAAA,EAQA,QAAQA,QAA8B;AACpC,WAAe,QAAQA,MAAK;AAAA,EAC9B;AAAA,EASA,QAAQ,kBAA0B,mBAA4C;AAC5E,WAAa,QAAQ,KAAK,QAAQ,kBAAkB,iBAAiB;AAAA,EACvE;AAAA,EAOA,MAAM,OAAsB;AAC1B,UAAc,MAAM,MAAM,IAAI;AAC9B,UAAM,KAAK,GAAG,MAAM;AAAA,EACtB;AAAA,EAOA,MAAM,KAAK,YAA6C;AACtD,SAAK,QAAQ;AACb,UAAM,YAAY,IAAI;AACtB,UAAMW,SAAQ,OAAO,OAAO,KAAK,MAAM,EAAE,OAAO,CAACC,YAAUA,OAAK,EAAE;AAClE,QAAI;AAAY,WAAK,SAAS,UAAU,KAAK,QAAQ,UAAU;AAE/D,QAAI,KAAK,IAAI,SAAS;AACpB,UAAI,KAAK,OAAO;AAAO,YAAI,YAAY,KAAK,SAAS;AACrD,UAAI,KAAK,OAAO;AAAO,YAAI,iBAAiB,KAAK,GAAG,QAAQ,cAAc;AAC1E,UAAI,CAAC,MAAc,MAAM,IAAI;AAAG,YAAI,6BAA6B;AACjE,YAAS,MAAM;AACf,UAAI,KAAK,IAAI,SAAS;AACpB,YAAI,KAAK,OAAO;AAAO,cAAI,kBAAkB,KAAK,MAAM;AACxD,YAAI,KAAK,OAAO;AAAO,cAAI,gBAAgB,KAAK,GAAG;AACnD,YAAI,KAAK,OAAO;AAAO,cAAI,aAAa,KAAK,GAAG,IAAI,QAAQ;AAAA,MAC9D;AAAA,IACF;AAEA,UAAaC,OAAK,IAAI;AACtB,QAAI,KAAK,IAAI,WAAW,KAAK,OAAO;AAAO,UAAI,oBAAoB,KAAK,GAAG,OAAO,EAAE,MAAM,UAAU,SAAS,KAAK,GAAG,OAAO,EAAE,MAAM,YAAY,SAAS;AACzJ,SAAK,IAAI,UAAU;AAEnB,UAAM,SAAS,OAAO,OAAO,KAAK,MAAM,EAAE,OAAO,CAACD,YAAUA,OAAK,EAAE;AACnE,QAAI,WAAWD,QAAO;AACpB,YAAaG,UAAS,IAAI;AAC1B,WAAK,KAAK,MAAM;AAAA,IAClB;AAEA,UAAM,UAAU,KAAK,MAAM,IAAI,IAAI,SAAS;AAC5C,QAAI,WAAW,KAAK,YAAY,cAAwB;AAAI,WAAK,YAAY,aAAa,KAAK,IAAI,WAAW,KAAK,YAAY,cAAc,KAAK,UAAU;AAAA,EAC9J;AAAA,EAaA,KAAK,SAAiB,KAAK,QAAgB;AACzC,WAAmBC,MAAK,QAAQ,KAAK,MAAM;AAAA,EAC7C;AAAA,EAGA,gBAA4B;AAAE,WAAc,cAAc,IAAI;AAAA,EAAG;AAAA,EAQjE,MAAM,OAAO,YAA8B;AACzC,UAAM,KAAK,IAAI;AACf,UAAM,MAAM,MAAc,OAAO,MAAM,UAAU;AACjD,UAAM,KAAK,IAAI;AACf,SAAK,YAAY,SAAS,KAAK,MAAM,KAAK,EAAE;AAC5C,WAAO;AAAA,EACT;AAAA,EAMA,MAAM,QAAQf,QAAc,YAA8F;AACxH,UAAMgB,WAAU,MAAM,KAAK,GAAG,QAAQ,MAAM,KAAK,OAAOhB,QAAO,UAAU,CAAC;AAC1E,UAAM,UAAkC,CAAC;AACzC,QAAI,QAAQ;AACZ,eAAW,UAAUgB,SAAQ,SAAS;AACpC,UAAI,QAAQ,OAAO;AAAO,gBAAQ,OAAO,SAAS,OAAO;AAAA;AACpD,gBAAQ,OAAO,QAAQ,OAAO;AACnC,eAAS,OAAO;AAAA,IAClB;AACA,UAAM,YAAmE,CAAC;AAC1E,WAAO,QAAQ,OAAO,EAAE,QAAQ,CAAC,QAAQ,UAAU,KAAK,EAAE,QAAQ,IAAI,IAAI,MAAM,IAAI,IAAyB,MAAM,EAAE,CAAC,CAAC;AACvH,eAAW,UAAU,WAAW;AAC9B,aAAO,OAAO,KAAK,MAAM,MAAO,OAAO,OAAO,KAAK,IAAI;AACvD,aAAO,OAAO,KAAK,MAAM,MAAO,OAAO,IAAI,IAAI;AAAA,IACjD;AACA,cAAU,KAAK,CAAC,GAAG,MAAM,EAAE,OAAO,EAAE,IAAI;AACxC,cAAU,SAAS;AAGnB,WAAO;AAAA,EACT;AAAA,EAYA,MAAM,OAAOhB,QAAc,YAA+C;AAExE,SAAK,QAAQ;AACb,WAAO,IAAI,QAAQ,OAAO,YAAY;AAnY1C;AAoYM,WAAK,QAAQ;AACb,UAAI;AAGJ,WAAK,SAAS,UAAU,KAAK,QAAQ,UAAU;AAG/C,WAAK,QAAQ;AACb,YAAM,QAAQ,mBAAK,SAAL,WAAaA;AAC3B,UAAI,OAAO;AACT,YAAI,OAAOA,MAAK;AAChB,aAAK,KAAK,OAAO;AACjB,gBAAQ,EAAE,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,SAAS,CAAC,GAAG,QAAQ,CAAC,GAAG,aAAa,KAAK,aAAa,WAAW,IAAI,GAAG,SAAS,CAAC,GAAG,MAAM,CAAC;AAAA,MACxI;AAEA,YAAM,YAAY,IAAI;AAGtB,YAAc,MAAM,IAAI;AAGxB,YAAM,KAAK,KAAK;AAEhB,kBAAY,IAAI;AAChB,WAAK,QAAQ;AACb,YAAM,MAAM,MAAYU,SAAQV,QAAO,KAAK,MAAM;AAClD,WAAK,UAAU;AACf,WAAK,YAAY,eAAe,KAAK,IAAI,WAAW,KAAK,YAAY,gBAAgB,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AACtJ,WAAK,QAAQ,YAAY;AAEzB,UAAI,CAAC,IAAI,QAAQ;AACf,YAAI,KAAK,OAAO;AAAO,cAAI,mCAAmC;AAC9D,aAAK,KAAK,OAAO;AACjB,gBAAQ,EAAE,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,MAAM,CAAC,GAAG,SAAS,CAAC,GAAG,QAAQ,CAAC,GAAG,aAAa,KAAK,aAAa,WAAW,IAAI,GAAG,SAAS,CAAC,GAAG,OAAO,oCAAoC,CAAC;AAC3K;AAAA,MACF;AACA,WAAK,KAAK,OAAO;AAEjB,kBAAY,IAAI;AAChB,WAAK,OAAO,cAAc,MAAY,KAAK,KAAK,QAAQ,IAAI,MAAM;AAClE,UAAI,CAAC,KAAK,YAAY;AAAa,aAAK,YAAY,cAAc;AAClE,UAAI,CAAC,KAAK,YAAY;AAAc,aAAK,YAAY,eAAe;AACpE,MAAC,KAAK,YAAY;AAClB,UAAI,KAAK,OAAO;AAAa,aAAK,YAAY;AAC9C,WAAK,YAAY,aAAa,KAAK,IAAI,WAAW,KAAK,YAAY,cAAc,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAClJ,WAAK,QAAQ,gBAAgB;AAI7B,UAAI,UAA0D,CAAC;AAC/D,UAAI,UAA0D,CAAC;AAC/D,UAAI,UAA0D,CAAC;AAC/D,UAAI,YAAgE,CAAC;AAGrE,WAAK,QAAQ;AACb,UAAI,KAAK,OAAO,OAAO;AACrB,kBAAU,KAAK,OAAO,KAAK,UAAe,WAAW,MAAM,IAAI,MAAM,IAAI,CAAC;AAC1E,YAAI,KAAK,YAAY;AAAM,iBAAO,KAAK,YAAY;AAAA,MACrD,OAAO;AACL,oBAAY,IAAI;AAChB,kBAAU,KAAK,OAAO,KAAK,UAAU,MAAW,WAAW,MAAM,IAAI,MAAM,IAAI,CAAC;AAChF,aAAK,YAAY,OAAO,KAAK,IAAI,WAAW,KAAK,YAAY,QAAQ,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,MACxI;AAEA,UAAI,KAAK,OAAO,UAAU,KAAK,OAAO,KAAK,gBAAgB,MAAM,KAAK,OAAO,KAAK,gBAAgB;AAAK,kBAAU,MAAM;AAGvH,WAAK,QAAQ,aAAa;AAC1B,WAAK,QAAQ;AACb,YAAM,aAAa,KAAK,OAAO,KAAK,gBAAgB,KAAK,UAAU,KAAK,QAAQ,EAAE,MAAM,EAAE,aAAa,KAAK,OAAO,KAAK,UAAU,IAAK,QAAyB,SAAS,EAAE,EAAE,CAAC,IAAI,KAAK;AACvL,UAAI,KAAK,OAAO,OAAO;AACrB,aAAI,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAY,oBAAU,KAAK,OAAO,KAAK,UAAkBiB,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBAC5H,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAc,oBAAU,KAAK,OAAO,KAAK,UAAoBA,SAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBACrI,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAkB,oBAAU,KAAK,OAAO,KAAK,UAAwBA,SAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBAC7I,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAY,oBAAU,KAAK,OAAO,KAAK,UAAkBA,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAC1I,YAAI,KAAK,YAAY;AAAM,iBAAO,KAAK,YAAY;AAAA,MACrD,OAAO;AACL,oBAAY,IAAI;AAChB,aAAI,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAY,oBAAU,KAAK,OAAO,KAAK,UAAU,MAAcA,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBAClI,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAc,oBAAU,KAAK,OAAO,KAAK,UAAU,MAAgBA,SAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBAC3I,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAkB,oBAAU,KAAK,OAAO,KAAK,UAAU,MAAoBA,SAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBACnJ,UAAK,OAAO,KAAK,cAAjB,mBAA4B,SAAS;AAAY,oBAAU,KAAK,OAAO,KAAK,UAAU,MAAcA,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAChJ,aAAK,YAAY,OAAO,KAAK,IAAI,WAAW,KAAK,YAAY,QAAQ,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,MACxI;AACA,WAAK,QAAQ,WAAW;AAGxB,WAAK,QAAQ,aAAa;AAC1B,WAAK,QAAQ;AACb,YAAM,aAAa,KAAK,OAAO,KAAK,gBAAgB,KAAK,UAAU,KAAK,QAAQ,EAAE,MAAM,EAAE,aAAa,KAAK,OAAO,KAAK,UAAU,IAAK,QAAyB,SAAS,EAAE,EAAE,CAAC,IAAI,KAAK;AACvL,UAAI,KAAK,OAAO,OAAO;AACrB,aAAI,gBAAK,OAAO,KAAK,aAAjB,mBAA2B,cAA3B,mBAAsC,SAAS;AAAe,oBAAU,KAAK,OAAO,KAAK,UAAmBA,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBAC1I,gBAAK,OAAO,KAAK,aAAjB,mBAA2B,cAA3B,mBAAsC,SAAS;AAAc,oBAAU,KAAK,OAAO,KAAK,UAAoBA,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AACxJ,YAAI,KAAK,YAAY;AAAM,iBAAO,KAAK,YAAY;AAAA,MACrD,OAAO;AACL,oBAAY,IAAI;AAChB,aAAI,gBAAK,OAAO,KAAK,aAAjB,mBAA2B,cAA3B,mBAAsC,SAAS;AAAe,oBAAU,KAAK,OAAO,KAAK,UAAU,MAAeA,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAAA,kBAChJ,gBAAK,OAAO,KAAK,aAAjB,mBAA2B,cAA3B,mBAAsC,SAAS;AAAc,oBAAU,KAAK,OAAO,KAAK,UAAU,MAAgBA,UAAQ,IAAI,QAAQ,UAAU,IAAI,CAAC;AAC9J,aAAK,YAAY,OAAO,KAAK,IAAI,WAAW,KAAK,YAAY,QAAQ,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,MACxI;AACA,WAAK,QAAQ,WAAW;AAGxB,WAAK,QAAQ,eAAe;AAC5B,WAAK,QAAQ;AACb,UAAI,KAAK,OAAO,OAAO;AACrB,aAAI,UAAK,OAAO,OAAO,cAAnB,mBAA8B,SAAS;AAAY,sBAAY,KAAK,OAAO,OAAO,UAAkBA,UAAQ,IAAI,QAAQ,KAAK,MAAM,IAAI,CAAC;AAAA,kBACnI,UAAK,OAAO,OAAO,cAAnB,mBAA8B,SAAS;AAAc,sBAAY,KAAK,OAAO,OAAO,UAAoBA,SAAQ,IAAI,QAAQ,KAAK,MAAM,IAAI,CAAC;AACrJ,YAAI,KAAK,YAAY;AAAQ,iBAAO,KAAK,YAAY;AAAA,MACvD,OAAO;AACL,oBAAY,IAAI;AAChB,aAAI,UAAK,OAAO,OAAO,cAAnB,mBAA8B,SAAS;AAAY,sBAAY,KAAK,OAAO,OAAO,UAAU,MAAcA,UAAQ,IAAI,QAAQ,KAAK,MAAM,IAAI,CAAC;AAAA,kBACzI,UAAK,OAAO,OAAO,cAAnB,mBAA8B,SAAS;AAAc,sBAAY,KAAK,OAAO,OAAO,UAAU,MAAgBA,SAAQ,IAAI,QAAQ,KAAK,MAAM,IAAI,CAAC;AAC3J,aAAK,YAAY,SAAS,KAAK,IAAI,WAAW,KAAK,YAAY,UAAU,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,MAC5I;AACA,WAAK,QAAQ,aAAa;AAG1B,WAAK,QAAQ;AACb,UAAI,KAAK,OAAO;AAAO,SAAC,SAAS,SAAS,SAAS,SAAS,IAAI,MAAM,QAAQ,IAAI,CAAC,SAAS,SAAS,SAAS,SAAS,CAAC;AAGxH,WAAK,QAAQ;AACb,UAAI,aAA8B,CAAC;AACnC,UAAI,KAAK,OAAO,QAAQ,SAAS;AAC/B,oBAAY,IAAI;AAChB,qBAAa,CAAC,GAAWC,MAAK,OAAuB,GAAG,GAAWC,MAAK,OAAuB,GAAG,GAAWC,MAAK,OAAuB,GAAG,GAAWC,MAAK,OAAuB,CAAC;AACpL,YAAI,CAAC,KAAK,OAAO;AAAO,eAAK,YAAY,UAAU,KAAK,IAAI,WAAW,KAAK,YAAY,WAAW,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AAAA,iBAC3J,KAAK,YAAY;AAAS,iBAAO,KAAK,YAAY;AAAA,MAC7D;AAEA,WAAK,YAAY,QAAQ,KAAK,IAAI,WAAW,KAAK,YAAY,SAAS,KAAK,KAAK,MAAM,IAAI,IAAI,SAAS,IAAI,KAAK,MAAM,IAAI,IAAI,SAAS;AACxI,YAAM,UAAQ,gBAAK,YAAL,mBAAc,WAAd,mBAAsB,UAAS,CAAC;AAC9C,WAAK,SAAS;AAAA,QACZ,MAAM;AAAA,QACN,MAAM;AAAA,QACN,MAAM;AAAA,QACN,SAAS;AAAA,QACT,QAAQ;AAAA,QACR,aAAa,KAAK;AAAA,QAClB,QAAQ,KAAK,QAAQ;AAAA,QACrB,WAAW,KAAK,IAAI;AAAA,QACpB,OAAO;AAAA,QACP,IAAI,UAAU;AAAE,iBAAeC,MAAK,SAAyB,SAAyB,SAAyB,YAAY,KAAK;AAAA,QAAG;AAAA,MACrI;AAGA,MAAG,QAAQ,IAAI,MAAM;AAGrB,WAAK,KAAK,QAAQ;AAClB,WAAK,QAAQ;AACb,cAAQ,KAAK,MAAM;AAAA,IACrB,CAAC;AAAA,EACH;AACF;AA7aE;AACA;AACA;AAuEA;",
+  "names": ["config", "log2", "__defProp", "__export", "all5", "cache", "size", "compare", "log22", "copy", "init2", "mask", "options", "count2", "now2", "index", "canvas", "object", "strides", "log", "config", "now", "node", "lines", "size2", "labels", "outputSize", "scale2", "alpha", "half", "middle", "labels2", "inputSize", "padding", "lastTime", "model2", "constants", "maxSize", "node2", "outputNodes", "match", "skipped", "strides2", "body", "r", "match", "index", "cos", "sin", "size", "s", "func", "image", "i", "squeeze", "min", "max", "sub", "range", "rgb", "reshape", "env", "input", "process", "config", "getTensor", "tensor", "rgb", "cast", "t", "e", "env", "init", "config", "e", "model", "models_exports", "load", "validate", "model", "last", "config", "env", "image", "count", "_a", "_b", "t", "gender", "i", "age", "tensor", "init", "model", "last", "lastCount", "lastTime", "skipped", "load", "config", "env", "predict", "image", "count", "t", "tensor", "model", "last", "lastCount", "lastTime", "skipped", "load", "config", "env", "predict", "image", "count", "t", "tensor", "model", "skipped", "lastCount", "lastTime", "load", "config", "env", "predict", "image", "count", "input", "image", "norm", "size", "dot", "i", "size", "inputSize", "anchors", "i", "n", "dot", "input", "face", "env", "model", "load", "config", "env", "t", "tensor", "i", "inputSize", "anchors", "outputSize", "coords", "min", "max", "square", "scale", "env", "inputSize", "skipped", "lastTime", "sigmoid", "config", "input", "size", "t", "tensor", "outputSize", "kpt", "config", "i", "sigmoid", "inputSize", "distance", "annotations", "body", "predict", "lastTime", "skipped", "model", "inputSize", "last", "lastTime", "skipped", "load", "config", "env", "process", "t", "i", "tensor", "predict", "input", "outputSize", "connected", "kpt", "model", "lastTime", "cache", "skipped", "load", "config", "env", "max", "mod", "div", "predict", "image", "tensor", "enhance", "norm", "squeeze", "stack", "x", "y", "kpt", "s", "connected", "i", "model", "last", "lastCount", "lastTime", "skipped", "load", "config", "env", "predict", "image", "count", "_a", "_b", "t", "inputSize", "i", "tensor", "model", "last", "lastCount", "lastTime", "skipped", "load", "config", "env", "predict", "input", "count", "_a", "t", "model", "inputSize", "load", "config", "env", "i", "index", "face", "connectionsToIndices", "index", "t", "r", "i", "cache", "model", "inputSize", "predict", "input", "config", "i", "face", "t", "index", "load", "env", "model", "last", "lastTime", "lastCount", "skipped", "load", "config", "env", "input", "tensor", "norm", "predict", "image", "count", "_a", "_b", "t", "gender", "argmax", "age", "all", "getBoxSize", "getBoxCenter", "image", "scaleBoxCoordinates", "enlargeBox", "size", "squarifyBox", "normalizeRadians", "computeRotation", "buildTranslationMatrix", "dot", "i", "getColumnFrom2DArr", "multiplyTransformMatrices", "size", "buildRotationMatrix", "invertTransformMatrix", "rotatePoint", "anchors", "model", "anchors", "t", "tensor", "index", "input", "config", "p", "hand", "scaleBoxCoordinates", "lastTime", "handPoseModel", "rotatePoint", "enlargeBox", "squarifyBox", "i", "getBoxSize", "buildRotationMatrix", "invertTransformMatrix", "getBoxCenter", "dot", "image", "config", "computeRotation", "env", "coords", "options", "point", "point2", "gesture", "meshAnnotations", "predict", "input", "config", "i", "annotations", "index", "load", "env", "models", "inputSize", "skipped", "lastTime", "cache", "loadDetect", "config", "env", "input", "config", "models", "t", "scale", "hand", "tensor", "inputSize", "kpt", "index", "predict", "skipped", "lastTime", "cache", "i", "square", "model", "cached", "skipped", "lastCount", "lastTime", "load", "config", "env", "predict", "image", "count", "connected", "kpt", "cache", "body", "compare", "i", "input", "inputSize", "t", "tensor", "outputSize", "kpt", "model", "inputSize", "skipped", "cache", "load", "config", "env", "image", "kpt", "annotations", "connected", "i", "body", "predict", "input", "t", "tensor", "model", "last", "lastTime", "skipped", "inputSize", "load", "config", "env", "process", "i", "t", "predict", "image", "outputSize", "norm", "transpose", "count", "i", "i", "maxSize", "max", "t", "count", "outputStride", "clamp", "min", "max", "model", "point", "height", "width", "clamp", "i", "minConfidence", "predict", "input", "config", "tensor", "t", "load", "env", "model", "load", "config", "env", "process", "input", "t", "tensor", "i", "model", "load", "env", "loadDetect", "validate", "op", "config", "e", "env", "op", "init", "config", "all", "canvas", "options", "input", "opt", "rgb", "i", "options", "labels", "emotion", "i", "index", "inCanvas", "options", "inCanvas", "options", "i", "connected", "inCanvas", "options", "i", "inCanvas", "options", "inCanvas", "options", "i", "where", "inCanvas", "options", "i", "canvas", "input", "all", "env", "i", "face", "buffer", "face", "r", "size", "input", "predict", "env", "i", "tensor", "body", "i", "face", "iris", "hand", "calc", "config", "i", "_a", "_b", "_c", "_d", "_e", "_f", "_g", "_h", "_i", "annotations", "coords", "env", "match", "options", "sum", "i", "min", "max", "norm", "clamp", "index", "join", "face", "person", "body", "hand", "gesture", "face", "body", "res", "face", "body", "env", "canvas", "tensor", "atob", "model", "t", "e", "input", "e", "match", "env", "version", "options", "canvas", "all", "config", "getTensor", "process", "count", "model", "load", "validate", "calc", "profile", "predict", "face", "body", "hand", "iris", "join"]
 }
diff --git a/dist/human.js b/dist/human.js
index 2828a0d8..2785e1e5 100644
--- a/dist/human.js
+++ b/dist/human.js
@@ -4,64 +4,64 @@
   author: <https://github.com/vladmandic>'
 */
 
-var Human=(()=>{var zf=Object.defineProperty;var GR=Object.getOwnPropertyDescriptor;var HR=Object.getOwnPropertyNames;var jR=Object.prototype.hasOwnProperty;var qR=(e,t,n)=>t in e?zf(e,t,{enumerable:!0,configurable:!0,writable:!0,value:n}):e[t]=n;var ia=(e,t)=>{for(var n in t)zf(e,n,{get:t[n],enumerable:!0})},XR=(e,t,n,s)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of HR(t))!jR.call(e,r)&&r!==n&&zf(e,r,{get:()=>t[r],enumerable:!(s=GR(t,r))||s.enumerable});return e};var KR=e=>XR(zf({},"__esModule",{value:!0}),e);var me=(e,t,n)=>(qR(e,typeof t!="symbol"?t+"":t,n),n),lv=(e,t,n)=>{if(!t.has(e))throw TypeError("Cannot "+n)};var Zd=(e,t,n)=>(lv(e,t,"read from private field"),n?n.call(e):t.get(e)),Yd=(e,t,n)=>{if(t.has(e))throw TypeError("Cannot add the same private member more than once");t instanceof WeakSet?t.add(e):t.set(e,n)},Jd=(e,t,n,s)=>(lv(e,t,"write to private field"),s?s.call(e,n):t.set(e,n),n);var Exe={};ia(Exe,{Human:()=>B4,default:()=>B4,defaults:()=>Ba,draw:()=>$4,env:()=>fe,match:()=>L4,models:()=>m1});function ie(...e){let t=new Date,n=`${t.getHours().toString().padStart(2,"0")}:${t.getMinutes().toString().padStart(2,"0")}:${t.getSeconds().toString().padStart(2,"0")}.${t.getMilliseconds().toString().padStart(3,"0")}`;e&&console.log(n,"Human:",...e)}function uv(e,t){let n=e.endsWith("/")?"":"/",r=t.startsWith(".")||t.startsWith("/")||t.startsWith("http:")||t.startsWith("https:")||t.startsWith("file:")?`${t}`:`${e}${n}${t}`;if(!r.toLocaleLowerCase().includes(".json"))throw new Error(`modelpath error: expecting json file: ${r}`);return r}var ue=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function t3(e,t,n="config",s=[]){for(let r of Object.keys(t))if(typeof t[r]=="object")t3(e[r],t[r],r,s);else{let a=e&&typeof e[r]!="undefined";a||s.push({reason:"unknown property",where:`${n}.${r} = ${t[r]}`});let o=e&&typeof e[r]==typeof t[r];a&&!o&&s.push({reason:"property type mismatch",where:`${n}.${r} = ${t[r]}`,expected:typeof e[r]})}return t.debug&&n==="config"&&s.length>0&&ie("invalid configuration",s),s}function Xt(...e){let t=n=>n&&typeof n=="object";return e.reduce((n,s)=>(Object.keys(s||{}).forEach(r=>{let a=n[r],o=s[r];Array.isArray(a)&&Array.isArray(o)?n[r]=a.concat(...o):t(a)&&t(o)?n[r]=Xt(a,o):n[r]=o}),n),{})}var Ba={backend:"",modelBasePath:"",cacheModels:!0,wasmPath:"",wasmPlatformFetch:!1,debug:!1,async:!0,warmup:"full",cacheSensitivity:.7,skipAllowed:!1,deallocate:!1,filter:{enabled:!0,equalization:!1,width:0,height:0,flip:!1,return:!0,brightness:0,contrast:0,sharpness:0,blur:0,saturation:0,hue:0,negative:!1,sepia:!1,vintage:!1,kodachrome:!1,technicolor:!1,polaroid:!1,pixelate:0},gesture:{enabled:!0},face:{enabled:!0,detector:{modelPath:"blazeface.json",rotation:!0,maxDetected:1,skipFrames:99,skipTime:2500,minConfidence:.2,iouThreshold:.1,mask:!1,return:!1},mesh:{enabled:!0,modelPath:"facemesh.json",keepInvalid:!1},attention:{enabled:!1,modelPath:"facemesh-attention.json"},iris:{enabled:!0,modelPath:"iris.json"},emotion:{enabled:!0,minConfidence:.1,skipFrames:99,skipTime:1500,modelPath:"emotion.json"},description:{enabled:!0,modelPath:"faceres.json",skipFrames:99,skipTime:3e3,minConfidence:.1},antispoof:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"antispoof.json"},liveness:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"liveness.json"}},body:{enabled:!0,modelPath:"movenet-lightning.json",maxDetected:-1,minConfidence:.3,skipFrames:1,skipTime:200},hand:{enabled:!0,rotation:!0,skipFrames:99,skipTime:1e3,minConfidence:.5,iouThreshold:.2,maxDetected:-1,landmarks:!0,detector:{modelPath:"handtrack.json"},skeleton:{modelPath:"handlandmark-full.json"}},object:{enabled:!1,modelPath:"mb3-centernet.json",minConfidence:.2,iouThreshold:.4,maxDetected:10,skipFrames:99,skipTime:2e3},segmentation:{enabled:!1,modelPath:"selfie.json",blur:8}};var je={};ia(je,{Abs:()=>il,Acos:()=>pc,Acosh:()=>hc,AdadeltaOptimizer:()=>j0,AdagradOptimizer:()=>q0,AdamOptimizer:()=>X0,AdamaxOptimizer:()=>K0,Add:()=>xa,AddN:()=>po,All:()=>fc,Any:()=>mc,ArgMax:()=>ho,ArgMin:()=>gc,Asin:()=>yc,Asinh:()=>Ac,Atan:()=>xc,Atan2:()=>vc,Atanh:()=>bc,AvgPool:()=>fo,AvgPool3D:()=>zp,AvgPool3DGrad:()=>Hm,AvgPoolGrad:()=>Gm,BackendWasm:()=>WC,BatchMatMul:()=>mo,BatchToSpaceND:()=>ll,Bincount:()=>jm,BroadcastArgs:()=>qm,BroadcastTo:()=>c6,Callback:()=>kk,CallbackList:()=>T8,Cast:()=>go,Ceil:()=>yo,ClipByValue:()=>ba,Complex:()=>Lp,ComplexAbs:()=>Bp,Concat:()=>ul,Conv2D:()=>Ao,Conv2DBackpropFilter:()=>Xm,Conv2DBackpropInput:()=>xo,Conv3D:()=>Wp,Conv3DBackpropFilterV2:()=>Km,Conv3DBackpropInputV2:()=>Zm,Cos:()=>bo,Cosh:()=>vo,CropAndResize:()=>dl,Cumprod:()=>cl,Cumsum:()=>wo,CustomCallback:()=>E8,DataStorage:()=>Mp,DenseBincount:()=>Ym,DepthToSpace:()=>pl,DepthwiseConv2dNative:()=>ko,DepthwiseConv2dNativeBackpropFilter:()=>Jm,DepthwiseConv2dNativeBackpropInput:()=>Qm,Diag:()=>e0,Dilation2D:()=>Vp,Dilation2DBackpropFilter:()=>hm,Dilation2DBackpropInput:()=>pm,ENV:()=>$r,EarlyStopping:()=>Ik,Einsum:()=>Up,Elu:()=>So,EluGrad:()=>t0,Environment:()=>l6,Equal:()=>hl,Erf:()=>wc,Exp:()=>Co,ExpandDims:()=>fl,Expm1:()=>ml,FFT:()=>n0,Fill:()=>kc,FlipLeftRight:()=>gl,Floor:()=>To,FloorDiv:()=>No,FromPixels:()=>bp,FusedBatchNorm:()=>Eo,FusedConv2D:()=>Qa,FusedDepthwiseConv2D:()=>eo,GPGPUContext:()=>ju,GatherNd:()=>Al,GatherV2:()=>yl,GraphModel:()=>$h,Greater:()=>xl,GreaterEqual:()=>Ro,History:()=>N8,IFFT:()=>s0,Identity:()=>_o,Imag:()=>Gp,InputSpec:()=>rn,IsFinite:()=>Ic,IsInf:()=>Sc,IsNan:()=>Cc,KernelBackend:()=>cc,LRN:()=>Hp,LRNGrad:()=>a0,LayerVariable:()=>b8,LayersModel:()=>ha,LeakyRelu:()=>Do,Less:()=>bl,LessEqual:()=>vl,LinSpace:()=>r0,Log:()=>$o,Log1p:()=>Tc,LogSoftmax:()=>p6,LogicalAnd:()=>wl,LogicalNot:()=>kl,LogicalOr:()=>Nc,LogicalXor:()=>d6,LowerBound:()=>B_,MathBackendWebGL:()=>id,Max:()=>Po,MaxPool:()=>Oo,MaxPool3D:()=>jp,MaxPool3DGrad:()=>i0,MaxPoolGrad:()=>o0,MaxPoolWithArgmax:()=>l0,Maximum:()=>Fo,Mean:()=>Mo,Min:()=>zo,Minimum:()=>Lo,MirrorPad:()=>Bo,Mod:()=>Ec,MomentumOptimizer:()=>Z0,Multinomial:()=>u0,Multiply:()=>Wo,Neg:()=>Il,NonMaxSuppressionV3:()=>Cl,NonMaxSuppressionV4:()=>Rc,NonMaxSuppressionV5:()=>Tl,NotEqual:()=>Sl,OP_SCOPE_SUFFIX:()=>Cy,OneHot:()=>El,OnesLike:()=>Nl,Optimizer:()=>ka,OptimizerConstructors:()=>Wa,Pack:()=>Rl,PadV2:()=>Vo,Pool:()=>W_,Pow:()=>Uo,Prelu:()=>Go,Prod:()=>Ho,RMSPropOptimizer:()=>Y0,RNN:()=>Qr,Range:()=>_c,Rank:()=>A3,Real:()=>qp,RealDiv:()=>Io,Reciprocal:()=>Dc,Reduction:()=>Yn,Relu:()=>jo,Relu6:()=>Ko,Reshape:()=>_l,ResizeBilinear:()=>Xo,ResizeBilinearGrad:()=>d0,ResizeNearestNeighbor:()=>qo,ResizeNearestNeighborGrad:()=>c0,Reverse:()=>Dl,RotateWithOffset:()=>jl,Round:()=>$l,Rsqrt:()=>Zo,SGDOptimizer:()=>vh,ScatterNd:()=>Pl,SearchSorted:()=>p0,Select:()=>Fl,Selu:()=>$c,Sequential:()=>sc,Sigmoid:()=>Jo,Sign:()=>Pc,Sin:()=>Yo,Sinh:()=>Ml,Slice:()=>Ol,Softmax:()=>ti,Softplus:()=>Fc,SpaceToBatchND:()=>zl,SparseFillEmptyRows:()=>Xp,SparseReshape:()=>Oc,SparseSegmentMean:()=>Kp,SparseSegmentSum:()=>Zp,SparseToDense:()=>Yp,SplitV:()=>Ll,Sqrt:()=>Qo,Square:()=>Mc,SquaredDifference:()=>ni,Step:()=>ai,StridedSlice:()=>Bl,StringNGrams:()=>zc,StringSplit:()=>Jp,StringToHashBucketFast:()=>Qp,Sub:()=>si,Sum:()=>ei,SymbolicTensor:()=>Cr,Tan:()=>Wl,Tanh:()=>ri,Tensor:()=>tt,TensorBuffer:()=>fn,Tile:()=>va,TopK:()=>Vl,Transform:()=>Ul,Transpose:()=>Hr,Unique:()=>h0,Unpack:()=>Gl,UnsortedSegmentSum:()=>eh,UpperBound:()=>V_,Variable:()=>kp,ZerosLike:()=>Hl,_FusedMatMul:()=>Ja,abs:()=>tn,acos:()=>Hy,acosh:()=>jy,add:()=>ce,addN:()=>m0,all:()=>g0,any:()=>Cp,argMax:()=>Es,argMin:()=>qy,asin:()=>Xy,asinh:()=>Ky,atan:()=>Zy,atan2:()=>Yy,atanh:()=>Jy,avgPool:()=>lh,avgPool3d:()=>eA,backend:()=>Zs,backend_util:()=>C,basicLSTMCell:()=>sw,batchNorm:()=>Wc,batchNorm2d:()=>tA,batchNorm3d:()=>nA,batchNorm4d:()=>sA,batchToSpaceND:()=>uh,bincount:()=>rA,booleanMaskAsync:()=>zw,broadcastArgs:()=>rw,broadcastTo:()=>Gu,broadcast_util:()=>Xl,browser:()=>Ys,buffer:()=>Le,callbacks:()=>jH,cast:()=>ge,ceil:()=>aA,clipByValue:()=>fs,clone:()=>Fn,complex:()=>fa,concat:()=>Ct,concat1d:()=>oA,concat2d:()=>Kl,concat3d:()=>iA,concat4d:()=>lA,constraints:()=>k8,conv1d:()=>y0,conv2d:()=>ma,conv2dTranspose:()=>A0,conv3d:()=>cA,conv3dTranspose:()=>dA,copyRegisteredKernels:()=>j_,cos:()=>ch,cosh:()=>x0,cosineWindow:()=>W0,cumprod:()=>Tp,cumsum:()=>b0,customGrad:()=>Kr,data:()=>Xk,denseBincount:()=>ow,deprecationWarn:()=>Py,depthToSpace:()=>pA,depthwiseConv2d:()=>Vc,deregisterOp:()=>KH,device_util:()=>rh,diag:()=>iw,dilation2d:()=>hA,disableDeprecationWarnings:()=>x$,dispose:()=>ne,disposeVariables:()=>b$,div:()=>pe,divNoNan:()=>fA,dot:()=>mA,dropout:()=>WA,einsum:()=>lw,elu:()=>Uc,enableDebugMode:()=>A$,enableProdMode:()=>$y,enclosingPowerOfTwo:()=>VA,engine:()=>sn,env:()=>Z,equal:()=>Rs,erf:()=>gA,euclideanNorm:()=>xA,exp:()=>_s,expandDims:()=>Kt,expm1:()=>bA,eye:()=>v0,fft:()=>xh,fill:()=>Hc,findBackend:()=>Oy,findBackendFactory:()=>I$,floor:()=>jc,floorDiv:()=>Bc,forceHalfFloat:()=>i9,fused:()=>ec,gather:()=>qc,gatherND:()=>Vw,gather_util:()=>zy,getBackend:()=>ss,getGradient:()=>g3,getKernel:()=>fm,getKernelsForBackend:()=>qr,getThreadsCount:()=>vme,gpgpu_util:()=>LS,grad:()=>HF,grads:()=>jF,greater:()=>ys,greaterEqual:()=>li,ifft:()=>Qu,imag:()=>oh,image:()=>Ne,inTopKAsync:()=>Uw,initializers:()=>I8,input:()=>U8,io:()=>Ts,irfft:()=>M0,isFinite:()=>vA,isInf:()=>wA,isNaN:()=>kA,keep:()=>bn,kernel_impls:()=>dr,layers:()=>S8,leakyRelu:()=>dh,less:()=>w0,lessEqual:()=>ui,linalg:()=>HA,linspace:()=>hw,loadGraphModel:()=>Jj,loadGraphModelSync:()=>Qj,loadLayersModel:()=>nG,localResponseNormalization:()=>IA,log:()=>Ds,log1p:()=>ph,logSigmoid:()=>SA,logSoftmax:()=>I0,logSumExp:()=>S0,logicalAnd:()=>lr,logicalNot:()=>hh,logicalOr:()=>C0,logicalXor:()=>CA,losses:()=>t8,lowerBound:()=>mw,matMul:()=>Qe,math:()=>O6,max:()=>mn,maxPool:()=>fh,maxPool3d:()=>TA,maxPoolWithArgmax:()=>gw,maximum:()=>Jr,mean:()=>Bt,memory:()=>ym,meshgrid:()=>yw,metrics:()=>bk,min:()=>ga,minimum:()=>Xc,mirrorPad:()=>NA,mod:()=>Yl,model:()=>eG,models:()=>vk,moments:()=>mh,movingAverage:()=>Lw,mul:()=>L,multiRNNCell:()=>Aw,multinomial:()=>xw,neg:()=>Dt,nextFrame:()=>jA,norm:()=>Gc,notEqual:()=>Qi,oneHot:()=>Zu,ones:()=>Ns,onesLike:()=>$s,op:()=>V,outerProduct:()=>bw,pad:()=>Js,pad1d:()=>vw,pad2d:()=>ww,pad3d:()=>kw,pad4d:()=>Iw,pool:()=>EA,pow:()=>ya,prelu:()=>yh,print:()=>Ry,prod:()=>RA,profile:()=>v$,rand:()=>Sw,randomGamma:()=>Cw,randomNormal:()=>N0,randomStandardNormal:()=>Tw,randomUniform:()=>Kc,range:()=>Ju,ready:()=>Lc,real:()=>Yu,reciprocal:()=>$A,registerBackend:()=>ql,registerCallbackConstructor:()=>sG,registerGradient:()=>h6,registerKernel:()=>cr,registerOp:()=>XH,regularizers:()=>wk,relu:()=>Pr,relu6:()=>E0,removeBackend:()=>k$,reshape:()=>U,reverse:()=>Ks,reverse1d:()=>Nw,reverse2d:()=>Ew,reverse3d:()=>Rw,reverse4d:()=>_w,rfft:()=>bh,round:()=>R0,rsqrt:()=>_0,scalar:()=>Se,scatterND:()=>Bw,scatter_util:()=>Ly,searchSorted:()=>T0,selu:()=>D0,separableConv2d:()=>$0,sequential:()=>tG,serialization:()=>de,setBackend:()=>Fy,setPlatform:()=>S$,setThreadsCount:()=>bme,setWasmPath:()=>xme,setWasmPaths:()=>tb,setWebGLContext:()=>x2,setdiff1dAsync:()=>Dw,sigmoid:()=>Cn,sign:()=>PA,signal:()=>e8,sin:()=>P0,sinh:()=>F0,slice:()=>Oe,slice1d:()=>Ah,slice2d:()=>O0,slice3d:()=>ci,slice4d:()=>no,slice_util:()=>Ut,softmax:()=>Jl,softplus:()=>Zl,spaceToBatchND:()=>gh,sparse:()=>n8,sparseToDense:()=>Ww,spectral:()=>Qw,split:()=>Zt,sqrt:()=>Nn,square:()=>vt,squaredDifference:()=>z0,squeeze:()=>rt,stack:()=>on,step:()=>Ql,stridedSlice:()=>FA,string:()=>s8,sub:()=>he,sum:()=>ke,sumOutType:()=>sh,tan:()=>OA,tanh:()=>Yi,tensor:()=>ft,tensor1d:()=>Ft,tensor2d:()=>or,tensor3d:()=>My,tensor4d:()=>$w,tensor5d:()=>Pw,tensor6d:()=>Fw,tensor_util:()=>Tr,test_util:()=>Y6,tidy:()=>J,tile:()=>js,time:()=>w$,topk:()=>MA,train:()=>Fi,transpose:()=>st,truncatedNormal:()=>L0,unique:()=>zA,unregisterGradient:()=>H_,unregisterKernel:()=>G_,unsortedSegmentSum:()=>B0,unstack:()=>es,upcastType:()=>On,upperBound:()=>Ow,util:()=>v,valueAndGrad:()=>qF,valueAndGrads:()=>XF,variable:()=>LA,variableGrads:()=>fw,version:()=>Uh,version_converter:()=>tq,version_core:()=>Gy,version_layers:()=>f5,version_wasm:()=>wme,version_webgl:()=>gne,webgl:()=>yne,webgl_util:()=>uS,webgpu:()=>fT,where:()=>Mn,whereAsync:()=>BA,zeros:()=>Wt,zerosLike:()=>it});var ZR=Object.create,Ay=Object.defineProperty,YR=Object.getOwnPropertyDescriptor,Z7=Object.getOwnPropertyNames,JR=Object.getPrototypeOf,QR=Object.prototype.hasOwnProperty,ln=(e,t)=>function(){return t||(0,e[Z7(e)[0]])((t={exports:{}}).exports,t),t.exports},Ve=(e,t)=>{for(var n in t)Ay(e,n,{get:t[n],enumerable:!0})},e_=(e,t,n,s)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of Z7(t))!QR.call(e,r)&&r!==n&&Ay(e,r,{get:()=>t[r],enumerable:!(s=YR(t,r))||s.enumerable});return e},uo=(e,t,n)=>(n=e!=null?ZR(JR(e)):{},e_(t||!e||!e.__esModule?Ay(n,"default",{value:e,enumerable:!0}):n,e)),t_=ln({"node_modules/.pnpm/long@4.0.0/node_modules/long/src/long.js"(e,t){t.exports=s;var n=null;try{n=new WebAssembly.Instance(new WebAssembly.Module(new Uint8Array([0,97,115,109,1,0,0,0,1,13,2,96,0,1,127,96,4,127,127,127,127,1,127,3,7,6,0,1,1,1,1,1,6,6,1,127,1,65,0,11,7,50,6,3,109,117,108,0,1,5,100,105,118,95,115,0,2,5,100,105,118,95,117,0,3,5,114,101,109,95,115,0,4,5,114,101,109,95,117,0,5,8,103,101,116,95,104,105,103,104,0,0,10,191,1,6,4,0,35,0,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,126,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,127,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,128,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,129,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,130,34,4,66,32,135,167,36,0,32,4,167,11])),{}).exports}catch($){}function s($,T,F){this.low=$|0,this.high=T|0,this.unsigned=!!F}s.prototype.__isLong__,Object.defineProperty(s.prototype,"__isLong__",{value:!0});function r($){return($&&$.__isLong__)===!0}s.isLong=r;var a={},o={};function i($,T){var F,G,q;return T?($>>>=0,(q=0<=$&&$<256)&&(G=o[$],G)?G:(F=u($,($|0)<0?-1:0,!0),q&&(o[$]=F),F)):($|=0,(q=-128<=$&&$<128)&&(G=a[$],G)?G:(F=u($,$<0?-1:0,!1),q&&(a[$]=F),F))}s.fromInt=i;function l($,T){if(isNaN($))return T?b:A;if(T){if($<0)return b;if($>=g)return R}else{if($<=-y)return P;if($+1>=y)return E}return $<0?l(-$,T).neg():u($%m|0,$/m|0,T)}s.fromNumber=l;function u($,T,F){return new s($,T,F)}s.fromBits=u;var c=Math.pow;function p($,T,F){if($.length===0)throw Error("empty string");if($==="NaN"||$==="Infinity"||$==="+Infinity"||$==="-Infinity")return A;if(typeof T=="number"?(F=T,T=!1):T=!!T,F=F||10,F<2||36<F)throw RangeError("radix");var G;if((G=$.indexOf("-"))>0)throw Error("interior hyphen");if(G===0)return p($.substring(1),T,F).neg();for(var q=l(c(F,8)),z=A,K=0;K<$.length;K+=8){var B=Math.min(8,$.length-K),ee=parseInt($.substring(K,K+B),F);if(B<8){var Q=l(c(F,B));z=z.mul(Q).add(l(ee))}else z=z.mul(q),z=z.add(l(ee))}return z.unsigned=T,z}s.fromString=p;function d($,T){return typeof $=="number"?l($,T):typeof $=="string"?p($,T):u($.low,$.high,typeof T=="boolean"?T:$.unsigned)}s.fromValue=d;var h=1<<16,f=1<<24,m=h*h,g=m*m,y=g/2,x=i(f),A=i(0);s.ZERO=A;var b=i(0,!0);s.UZERO=b;var w=i(1);s.ONE=w;var k=i(1,!0);s.UONE=k;var S=i(-1);s.NEG_ONE=S;var E=u(-1,2147483647,!1);s.MAX_VALUE=E;var R=u(-1,-1,!0);s.MAX_UNSIGNED_VALUE=R;var P=u(0,-2147483648,!1);s.MIN_VALUE=P;var _=s.prototype;_.toInt=function(){return this.unsigned?this.low>>>0:this.low},_.toNumber=function(){return this.unsigned?(this.high>>>0)*m+(this.low>>>0):this.high*m+(this.low>>>0)},_.toString=function(T){if(T=T||10,T<2||36<T)throw RangeError("radix");if(this.isZero())return"0";if(this.isNegative())if(this.eq(P)){var F=l(T),G=this.div(F),q=G.mul(F).sub(this);return G.toString(T)+q.toInt().toString(T)}else return"-"+this.neg().toString(T);for(var z=l(c(T,6),this.unsigned),K=this,B="";;){var ee=K.div(z),Q=K.sub(ee.mul(z)).toInt()>>>0,oe=Q.toString(T);if(K=ee,K.isZero())return oe+B;for(;oe.length<6;)oe="0"+oe;B=""+oe+B}},_.getHighBits=function(){return this.high},_.getHighBitsUnsigned=function(){return this.high>>>0},_.getLowBits=function(){return this.low},_.getLowBitsUnsigned=function(){return this.low>>>0},_.getNumBitsAbs=function(){if(this.isNegative())return this.eq(P)?64:this.neg().getNumBitsAbs();for(var T=this.high!=0?this.high:this.low,F=31;F>0&&(T&1<<F)==0;F--);return this.high!=0?F+33:F+1},_.isZero=function(){return this.high===0&&this.low===0},_.eqz=_.isZero,_.isNegative=function(){return!this.unsigned&&this.high<0},_.isPositive=function(){return this.unsigned||this.high>=0},_.isOdd=function(){return(this.low&1)===1},_.isEven=function(){return(this.low&1)===0},_.equals=function(T){return r(T)||(T=d(T)),this.unsigned!==T.unsigned&&this.high>>>31===1&&T.high>>>31===1?!1:this.high===T.high&&this.low===T.low},_.eq=_.equals,_.notEquals=function(T){return!this.eq(T)},_.neq=_.notEquals,_.ne=_.notEquals,_.lessThan=function(T){return this.comp(T)<0},_.lt=_.lessThan,_.lessThanOrEqual=function(T){return this.comp(T)<=0},_.lte=_.lessThanOrEqual,_.le=_.lessThanOrEqual,_.greaterThan=function(T){return this.comp(T)>0},_.gt=_.greaterThan,_.greaterThanOrEqual=function(T){return this.comp(T)>=0},_.gte=_.greaterThanOrEqual,_.ge=_.greaterThanOrEqual,_.compare=function(T){if(r(T)||(T=d(T)),this.eq(T))return 0;var F=this.isNegative(),G=T.isNegative();return F&&!G?-1:!F&&G?1:this.unsigned?T.high>>>0>this.high>>>0||T.high===this.high&&T.low>>>0>this.low>>>0?-1:1:this.sub(T).isNegative()?-1:1},_.comp=_.compare,_.negate=function(){return!this.unsigned&&this.eq(P)?P:this.not().add(w)},_.neg=_.negate,_.add=function(T){r(T)||(T=d(T));var F=this.high>>>16,G=this.high&65535,q=this.low>>>16,z=this.low&65535,K=T.high>>>16,B=T.high&65535,ee=T.low>>>16,Q=T.low&65535,oe=0,Y=0,ae=0,le=0;return le+=z+Q,ae+=le>>>16,le&=65535,ae+=q+ee,Y+=ae>>>16,ae&=65535,Y+=G+B,oe+=Y>>>16,Y&=65535,oe+=F+K,oe&=65535,u(ae<<16|le,oe<<16|Y,this.unsigned)},_.subtract=function(T){return r(T)||(T=d(T)),this.add(T.neg())},_.sub=_.subtract,_.multiply=function(T){if(this.isZero())return A;if(r(T)||(T=d(T)),n){var F=n.mul(this.low,this.high,T.low,T.high);return u(F,n.get_high(),this.unsigned)}if(T.isZero())return A;if(this.eq(P))return T.isOdd()?P:A;if(T.eq(P))return this.isOdd()?P:A;if(this.isNegative())return T.isNegative()?this.neg().mul(T.neg()):this.neg().mul(T).neg();if(T.isNegative())return this.mul(T.neg()).neg();if(this.lt(x)&&T.lt(x))return l(this.toNumber()*T.toNumber(),this.unsigned);var G=this.high>>>16,q=this.high&65535,z=this.low>>>16,K=this.low&65535,B=T.high>>>16,ee=T.high&65535,Q=T.low>>>16,oe=T.low&65535,Y=0,ae=0,le=0,ye=0;return ye+=K*oe,le+=ye>>>16,ye&=65535,le+=z*oe,ae+=le>>>16,le&=65535,le+=K*Q,ae+=le>>>16,le&=65535,ae+=q*oe,Y+=ae>>>16,ae&=65535,ae+=z*Q,Y+=ae>>>16,ae&=65535,ae+=K*ee,Y+=ae>>>16,ae&=65535,Y+=G*oe+q*Q+z*ee+K*B,Y&=65535,u(le<<16|ye,Y<<16|ae,this.unsigned)},_.mul=_.multiply,_.divide=function(T){if(r(T)||(T=d(T)),T.isZero())throw Error("division by zero");if(n){if(!this.unsigned&&this.high===-2147483648&&T.low===-1&&T.high===-1)return this;var F=(this.unsigned?n.div_u:n.div_s)(this.low,this.high,T.low,T.high);return u(F,n.get_high(),this.unsigned)}if(this.isZero())return this.unsigned?b:A;var G,q,z;if(this.unsigned){if(T.unsigned||(T=T.toUnsigned()),T.gt(this))return b;if(T.gt(this.shru(1)))return k;z=b}else{if(this.eq(P)){if(T.eq(w)||T.eq(S))return P;if(T.eq(P))return w;var K=this.shr(1);return G=K.div(T).shl(1),G.eq(A)?T.isNegative()?w:S:(q=this.sub(T.mul(G)),z=G.add(q.div(T)),z)}else if(T.eq(P))return this.unsigned?b:A;if(this.isNegative())return T.isNegative()?this.neg().div(T.neg()):this.neg().div(T).neg();if(T.isNegative())return this.div(T.neg()).neg();z=A}for(q=this;q.gte(T);){G=Math.max(1,Math.floor(q.toNumber()/T.toNumber()));for(var B=Math.ceil(Math.log(G)/Math.LN2),ee=B<=48?1:c(2,B-48),Q=l(G),oe=Q.mul(T);oe.isNegative()||oe.gt(q);)G-=ee,Q=l(G,this.unsigned),oe=Q.mul(T);Q.isZero()&&(Q=w),z=z.add(Q),q=q.sub(oe)}return z},_.div=_.divide,_.modulo=function(T){if(r(T)||(T=d(T)),n){var F=(this.unsigned?n.rem_u:n.rem_s)(this.low,this.high,T.low,T.high);return u(F,n.get_high(),this.unsigned)}return this.sub(this.div(T).mul(T))},_.mod=_.modulo,_.rem=_.modulo,_.not=function(){return u(~this.low,~this.high,this.unsigned)},_.and=function(T){return r(T)||(T=d(T)),u(this.low&T.low,this.high&T.high,this.unsigned)},_.or=function(T){return r(T)||(T=d(T)),u(this.low|T.low,this.high|T.high,this.unsigned)},_.xor=function(T){return r(T)||(T=d(T)),u(this.low^T.low,this.high^T.high,this.unsigned)},_.shiftLeft=function(T){return r(T)&&(T=T.toInt()),(T&=63)===0?this:T<32?u(this.low<<T,this.high<<T|this.low>>>32-T,this.unsigned):u(0,this.low<<T-32,this.unsigned)},_.shl=_.shiftLeft,_.shiftRight=function(T){return r(T)&&(T=T.toInt()),(T&=63)===0?this:T<32?u(this.low>>>T|this.high<<32-T,this.high>>T,this.unsigned):u(this.high>>T-32,this.high>=0?0:-1,this.unsigned)},_.shr=_.shiftRight,_.shiftRightUnsigned=function(T){if(r(T)&&(T=T.toInt()),T&=63,T===0)return this;var F=this.high;if(T<32){var G=this.low;return u(G>>>T|F<<32-T,F>>>T,this.unsigned)}else return T===32?u(F,0,this.unsigned):u(F>>>T-32,0,this.unsigned)},_.shru=_.shiftRightUnsigned,_.shr_u=_.shiftRightUnsigned,_.toSigned=function(){return this.unsigned?u(this.low,this.high,!1):this},_.toUnsigned=function(){return this.unsigned?this:u(this.low,this.high,!0)},_.toBytes=function(T){return T?this.toBytesLE():this.toBytesBE()},_.toBytesLE=function(){var T=this.high,F=this.low;return[F&255,F>>>8&255,F>>>16&255,F>>>24,T&255,T>>>8&255,T>>>16&255,T>>>24]},_.toBytesBE=function(){var T=this.high,F=this.low;return[T>>>24,T>>>16&255,T>>>8&255,T&255,F>>>24,F>>>16&255,F>>>8&255,F&255]},s.fromBytes=function(T,F,G){return G?s.fromBytesLE(T,F):s.fromBytesBE(T,F)},s.fromBytesLE=function(T,F){return new s(T[0]|T[1]<<8|T[2]<<16|T[3]<<24,T[4]|T[5]<<8|T[6]<<16|T[7]<<24,F)},s.fromBytesBE=function(T,F){return new s(T[4]<<24|T[5]<<16|T[6]<<8|T[7],T[0]<<24|T[1]<<16|T[2]<<8|T[3],F)}}}),n_=ln({"(disabled):node_modules/.pnpm/node-fetch@2.6.7/node_modules/node-fetch/browser.js"(){}}),s_=ln({"(disabled):util"(){}}),r_=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/alea.js"(e,t){(function(n,s,r){function a(u){var c=this,p=l();c.next=function(){var d=2091639*c.s0+c.c*23283064365386963e-26;return c.s0=c.s1,c.s1=c.s2,c.s2=d-(c.c=d|0)},c.c=1,c.s0=p(" "),c.s1=p(" "),c.s2=p(" "),c.s0-=p(u),c.s0<0&&(c.s0+=1),c.s1-=p(u),c.s1<0&&(c.s1+=1),c.s2-=p(u),c.s2<0&&(c.s2+=1),p=null}function o(u,c){return c.c=u.c,c.s0=u.s0,c.s1=u.s1,c.s2=u.s2,c}function i(u,c){var p=new a(u),d=c&&c.state,h=p.next;return h.int32=function(){return p.next()*4294967296|0},h.double=function(){return h()+(h()*2097152|0)*11102230246251565e-32},h.quick=h,d&&(typeof d=="object"&&o(d,p),h.state=function(){return o(p,{})}),h}function l(){var u=4022871197,c=function(p){p=String(p);for(var d=0;d<p.length;d++){u+=p.charCodeAt(d);var h=.02519603282416938*u;u=h>>>0,h-=u,h*=u,u=h>>>0,h-=u,u+=h*4294967296}return(u>>>0)*23283064365386963e-26};return c}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.alea=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),a_=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xor128.js"(e,t){(function(n,s,r){function a(l){var u=this,c="";u.x=0,u.y=0,u.z=0,u.w=0,u.next=function(){var d=u.x^u.x<<11;return u.x=u.y,u.y=u.z,u.z=u.w,u.w^=u.w>>>19^d^d>>>8},l===(l|0)?u.x=l:c+=l;for(var p=0;p<c.length+64;p++)u.x^=c.charCodeAt(p)|0,u.next()}function o(l,u){return u.x=l.x,u.y=l.y,u.z=l.z,u.w=l.w,u}function i(l,u){var c=new a(l),p=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var h=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,p&&(typeof p=="object"&&o(p,c),d.state=function(){return o(c,{})}),d}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xor128=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),o_=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xorwow.js"(e,t){(function(n,s,r){function a(l){var u=this,c="";u.next=function(){var d=u.x^u.x>>>2;return u.x=u.y,u.y=u.z,u.z=u.w,u.w=u.v,(u.d=u.d+362437|0)+(u.v=u.v^u.v<<4^(d^d<<1))|0},u.x=0,u.y=0,u.z=0,u.w=0,u.v=0,l===(l|0)?u.x=l:c+=l;for(var p=0;p<c.length+64;p++)u.x^=c.charCodeAt(p)|0,p==c.length&&(u.d=u.x<<10^u.x>>>4),u.next()}function o(l,u){return u.x=l.x,u.y=l.y,u.z=l.z,u.w=l.w,u.v=l.v,u.d=l.d,u}function i(l,u){var c=new a(l),p=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var h=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,p&&(typeof p=="object"&&o(p,c),d.state=function(){return o(c,{})}),d}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xorwow=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),i_=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xorshift7.js"(e,t){(function(n,s,r){function a(l){var u=this;u.next=function(){var p=u.x,d=u.i,h,f,m;return h=p[d],h^=h>>>7,f=h^h<<24,h=p[d+1&7],f^=h^h>>>10,h=p[d+3&7],f^=h^h>>>3,h=p[d+4&7],f^=h^h<<7,h=p[d+7&7],h=h^h<<13,f^=h^h<<9,p[d]=f,u.i=d+1&7,f};function c(p,d){var h,f,m=[];if(d===(d|0))f=m[0]=d;else for(d=""+d,h=0;h<d.length;++h)m[h&7]=m[h&7]<<15^d.charCodeAt(h)+m[h+1&7]<<13;for(;m.length<8;)m.push(0);for(h=0;h<8&&m[h]===0;++h);for(h==8?f=m[7]=-1:f=m[h],p.x=m,p.i=0,h=256;h>0;--h)p.next()}c(u,l)}function o(l,u){return u.x=l.x.slice(),u.i=l.i,u}function i(l,u){l==null&&(l=+new Date);var c=new a(l),p=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var h=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,p&&(p.x&&o(p,c),d.state=function(){return o(c,{})}),d}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xorshift7=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),l_=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xor4096.js"(e,t){(function(n,s,r){function a(l){var u=this;u.next=function(){var p=u.w,d=u.X,h=u.i,f,m;return u.w=p=p+1640531527|0,m=d[h+34&127],f=d[h=h+1&127],m^=m<<13,f^=f<<17,m^=m>>>15,f^=f>>>12,m=d[h]=m^f,u.i=h,m+(p^p>>>16)|0};function c(p,d){var h,f,m,g,y,x=[],A=128;for(d===(d|0)?(f=d,d=null):(d=d+"\0",f=0,A=Math.max(A,d.length)),m=0,g=-32;g<A;++g)d&&(f^=d.charCodeAt((g+32)%d.length)),g===0&&(y=f),f^=f<<10,f^=f>>>15,f^=f<<4,f^=f>>>13,g>=0&&(y=y+1640531527|0,h=x[g&127]^=f+y,m=h==0?m+1:0);for(m>=128&&(x[(d&&d.length||0)&127]=-1),m=127,g=4*128;g>0;--g)f=x[m+34&127],h=x[m=m+1&127],f^=f<<13,h^=h<<17,f^=f>>>15,h^=h>>>12,x[m]=f^h;p.w=y,p.X=x,p.i=m}c(u,l)}function o(l,u){return u.i=l.i,u.w=l.w,u.X=l.X.slice(),u}function i(l,u){l==null&&(l=+new Date);var c=new a(l),p=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var h=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,p&&(p.X&&o(p,c),d.state=function(){return o(c,{})}),d}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xor4096=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),u_=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/tychei.js"(e,t){(function(n,s,r){function a(l){var u=this,c="";u.next=function(){var d=u.b,h=u.c,f=u.d,m=u.a;return d=d<<25^d>>>7^h,h=h-f|0,f=f<<24^f>>>8^m,m=m-d|0,u.b=d=d<<20^d>>>12^h,u.c=h=h-f|0,u.d=f<<16^h>>>16^m,u.a=m-d|0},u.a=0,u.b=0,u.c=-1640531527,u.d=1367130551,l===Math.floor(l)?(u.a=l/4294967296|0,u.b=l|0):c+=l;for(var p=0;p<c.length+20;p++)u.b^=c.charCodeAt(p)|0,u.next()}function o(l,u){return u.a=l.a,u.b=l.b,u.c=l.c,u.d=l.d,u}function i(l,u){var c=new a(l),p=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var h=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,p&&(typeof p=="object"&&o(p,c),d.state=function(){return o(c,{})}),d}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.tychei=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),c_=ln({"(disabled):crypto"(){}}),d_=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/seedrandom.js"(e,t){(function(n,s,r){var a=256,o=6,i=52,l="random",u=r.pow(a,o),c=r.pow(2,i),p=c*2,d=a-1,h;function f(w,k,S){var E=[];k=k==!0?{entropy:!0}:k||{};var R=x(y(k.entropy?[w,b(s)]:w==null?A():w,3),E),P=new m(E),_=function(){for(var $=P.g(o),T=u,F=0;$<c;)$=($+F)*a,T*=a,F=P.g(1);for(;$>=p;)$/=2,T/=2,F>>>=1;return($+F)/T};return _.int32=function(){return P.g(4)|0},_.quick=function(){return P.g(4)/4294967296},_.double=_,x(b(P.S),s),(k.pass||S||function($,T,F,G){return G&&(G.S&&g(G,P),$.state=function(){return g(P,{})}),F?(r[l]=$,T):$})(_,R,"global"in k?k.global:this==r,k.state)}function m(w){var k,S=w.length,E=this,R=0,P=E.i=E.j=0,_=E.S=[];for(S||(w=[S++]);R<a;)_[R]=R++;for(R=0;R<a;R++)_[R]=_[P=d&P+w[R%S]+(k=_[R])],_[P]=k;(E.g=function($){for(var T,F=0,G=E.i,q=E.j,z=E.S;$--;)T=z[G=d&G+1],F=F*a+z[d&(z[G]=z[q=d&q+T])+(z[q]=T)];return E.i=G,E.j=q,F})(a)}function g(w,k){return k.i=w.i,k.j=w.j,k.S=w.S.slice(),k}function y(w,k){var S=[],E=typeof w,R;if(k&&E=="object")for(R in w)try{S.push(y(w[R],k-1))}catch(P){}return S.length?S:E=="string"?w:w+"\0"}function x(w,k){for(var S=w+"",E,R=0;R<S.length;)k[d&R]=d&(E^=k[d&R]*19)+S.charCodeAt(R++);return b(k)}function A(){try{var w;return h&&(w=h.randomBytes)?w=w(a):(w=new Uint8Array(a),(n.crypto||n.msCrypto).getRandomValues(w)),b(w)}catch(E){var k=n.navigator,S=k&&k.plugins;return[+new Date,n,S,n.screen,b(s)]}}function b(w){return String.fromCharCode.apply(0,w)}if(x(r.random(),s),typeof t=="object"&&t.exports){t.exports=f;try{h=c_()}catch(w){}}else typeof define=="function"&&define.amd?define(function(){return f}):r["seed"+l]=f})(typeof self!="undefined"?self:e,[],Math)}}),Wm=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/index.js"(e,t){var n=r_(),s=a_(),r=o_(),a=i_(),o=l_(),i=u_(),l=d_();l.alea=n,l.xor128=s,l.xorwow=r,l.xorshift7=a,l.xor4096=o,l.tychei=i,t.exports=l}}),Y7=ln({"(disabled):node_modules/.pnpm/string_decoder@1.3.0/node_modules/string_decoder/lib/string_decoder.js"(){}}),xy=ln({"(disabled):fs"(){}}),um=ln({"(disabled):path"(){}}),p_=ln({"(disabled):worker_threads"(){}}),h_=ln({"(disabled):perf_hooks"(){}}),f_=ln({"(disabled):os"(){}}),m_=ln({"node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.js"(e,t){var n=(()=>{var s=typeof document!="undefined"&&document.currentScript?document.currentScript.src:void 0;return typeof __filename!="undefined"&&(s=s||__filename),function(r){r=r||{};function a(){return $e.buffer!=jn&&yr($e.buffer),sf}function o(){return $e.buffer!=jn&&yr($e.buffer),rf}function i(){return $e.buffer!=jn&&yr($e.buffer),zd}function l(){return $e.buffer!=jn&&yr($e.buffer),af}function u(){return $e.buffer!=jn&&yr($e.buffer),of}function c(){return $e.buffer!=jn&&yr($e.buffer),lf}function p(){return $e.buffer!=jn&&yr($e.buffer),uf}var d=typeof r!="undefined"?r:{},h,f;d.ready=new Promise(function(N,O){h=N,f=O});var m;typeof process!="undefined"&&process.listeners&&(m={uncaughtException:process.listeners("uncaughtException"),unhandledRejection:process.listeners("unhandledRejection")});var g=Object.assign({},d),y=[],x="./this.program",A=(N,O)=>{throw O},b=typeof window=="object",w=typeof importScripts=="function",k=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string",S=d.ENVIRONMENT_IS_PTHREAD||!1,E="";function R(N){return d.locateFile?d.locateFile(N,E):E+N}var P,_,$,T;function F(N){if(N instanceof Xd)return;Q("exiting due to exception: "+N)}var G,q,z;if(k){w?E=um().dirname(E)+"/":E=__dirname+"/",z=()=>{q||(G=xy(),q=um())},P=function(H,te){return z(),H=q.normalize(H),G.readFileSync(H,te?void 0:"utf8")},$=O=>{var H=P(O,!0);return H.buffer||(H=new Uint8Array(H)),H},_=(O,H,te)=>{z(),O=q.normalize(O),G.readFile(O,function(Ae,ve){Ae?te(Ae):H(ve.buffer)})},process.argv.length>1&&(x=process.argv[1].replace(/\\/g,"/")),y=process.argv.slice(2),process.on("uncaughtException",function(O){if(!(O instanceof Xd))throw O}),process.on("unhandledRejection",function(O){throw O}),A=(O,H)=>{if(Ti())throw process.exitCode=O,H;F(H),process.exit(O)},d.inspect=function(){return"[Emscripten Module object]"};let N;try{N=p_()}catch(O){throw console.error('The "worker_threads" module is not supported in this node.js build - perhaps a newer version is needed?'),O}global.Worker=N.Worker}else(b||w)&&(w?E=self.location.href:typeof document!="undefined"&&document.currentScript&&(E=document.currentScript.src),typeof s!="undefined"&&s&&(E=s),E.indexOf("blob:")!==0?E=E.substr(0,E.replace(/[?#].*/,"").lastIndexOf("/")+1):E="",k||(P=N=>{var O=new XMLHttpRequest;return O.open("GET",N,!1),O.send(null),O.responseText},w&&($=N=>{var O=new XMLHttpRequest;return O.open("GET",N,!1),O.responseType="arraybuffer",O.send(null),new Uint8Array(O.response)}),_=(N,O,H)=>{var te=new XMLHttpRequest;te.open("GET",N,!0),te.responseType="arraybuffer",te.onload=()=>{if(te.status==200||te.status==0&&te.response){O(te.response);return}H()},te.onerror=H,te.send(null)}),T=N=>document.title=N);k&&typeof performance=="undefined"&&(global.performance=h_().performance);var K=console.log.bind(console),B=console.warn.bind(console);k&&(z(),K=N=>G.writeSync(1,N+`
+var Human=(()=>{var Mf=Object.defineProperty;var GR=Object.getOwnPropertyDescriptor;var HR=Object.getOwnPropertyNames;var jR=Object.prototype.hasOwnProperty;var qR=(e,t,n)=>t in e?Mf(e,t,{enumerable:!0,configurable:!0,writable:!0,value:n}):e[t]=n;var oa=(e,t)=>{for(var n in t)Mf(e,n,{get:t[n],enumerable:!0})},XR=(e,t,n,s)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of HR(t))!jR.call(e,r)&&r!==n&&Mf(e,r,{get:()=>t[r],enumerable:!(s=GR(t,r))||s.enumerable});return e};var KR=e=>XR(Mf({},"__esModule",{value:!0}),e);var me=(e,t,n)=>(qR(e,typeof t!="symbol"?t+"":t,n),n),lv=(e,t,n)=>{if(!t.has(e))throw TypeError("Cannot "+n)};var Kd=(e,t,n)=>(lv(e,t,"read from private field"),n?n.call(e):t.get(e)),Zd=(e,t,n)=>{if(t.has(e))throw TypeError("Cannot add the same private member more than once");t instanceof WeakSet?t.add(e):t.set(e,n)},Yd=(e,t,n,s)=>(lv(e,t,"write to private field"),s?s.call(e,n):t.set(e,n),n);var Exe={};oa(Exe,{Human:()=>B4,default:()=>B4,defaults:()=>La,draw:()=>$4,env:()=>fe,match:()=>L4,models:()=>f1});function ie(...e){let t=new Date,n=`${t.getHours().toString().padStart(2,"0")}:${t.getMinutes().toString().padStart(2,"0")}:${t.getSeconds().toString().padStart(2,"0")}.${t.getMilliseconds().toString().padStart(3,"0")}`;e&&console.log(n,"Human:",...e)}function uv(e,t){let n=e.endsWith("/")?"":"/",r=t.startsWith(".")||t.startsWith("/")||t.startsWith("http:")||t.startsWith("https:")||t.startsWith("file:")?`${t}`:`${e}${n}${t}`;if(!r.toLocaleLowerCase().includes(".json"))throw new Error(`modelpath error: expecting json file: ${r}`);return r}var ue=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function e3(e,t,n="config",s=[]){for(let r of Object.keys(t))if(typeof t[r]=="object")e3(e[r],t[r],r,s);else{let a=e&&typeof e[r]!="undefined";a||s.push({reason:"unknown property",where:`${n}.${r} = ${t[r]}`});let o=e&&typeof e[r]==typeof t[r];a&&!o&&s.push({reason:"property type mismatch",where:`${n}.${r} = ${t[r]}`,expected:typeof e[r]})}return t.debug&&n==="config"&&s.length>0&&ie("invalid configuration",s),s}function Xt(...e){let t=n=>n&&typeof n=="object";return e.reduce((n,s)=>(Object.keys(s||{}).forEach(r=>{let a=n[r],o=s[r];Array.isArray(a)&&Array.isArray(o)?n[r]=a.concat(...o):t(a)&&t(o)?n[r]=Xt(a,o):n[r]=o}),n),{})}var La={backend:"",modelBasePath:"",cacheModels:!0,wasmPath:"",wasmPlatformFetch:!1,debug:!1,async:!0,warmup:"full",cacheSensitivity:.7,skipAllowed:!1,deallocate:!1,filter:{enabled:!0,equalization:!1,width:0,height:0,flip:!1,return:!0,brightness:0,contrast:0,sharpness:0,blur:0,saturation:0,hue:0,negative:!1,sepia:!1,vintage:!1,kodachrome:!1,technicolor:!1,polaroid:!1,pixelate:0},gesture:{enabled:!0},face:{enabled:!0,detector:{modelPath:"blazeface.json",rotation:!0,maxDetected:1,skipFrames:99,skipTime:2500,minConfidence:.2,iouThreshold:.1,mask:!1,return:!1},mesh:{enabled:!0,modelPath:"facemesh.json",keepInvalid:!1},attention:{enabled:!1,modelPath:"facemesh-attention.json"},iris:{enabled:!0,modelPath:"iris.json"},emotion:{enabled:!0,minConfidence:.1,skipFrames:99,skipTime:1500,modelPath:"emotion.json"},description:{enabled:!0,modelPath:"faceres.json",skipFrames:99,skipTime:3e3,minConfidence:.1},antispoof:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"antispoof.json"},liveness:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"liveness.json"}},body:{enabled:!0,modelPath:"movenet-lightning.json",maxDetected:-1,minConfidence:.3,skipFrames:1,skipTime:200},hand:{enabled:!0,rotation:!0,skipFrames:99,skipTime:1e3,minConfidence:.5,iouThreshold:.2,maxDetected:-1,landmarks:!0,detector:{modelPath:"handtrack.json"},skeleton:{modelPath:"handlandmark-full.json"}},object:{enabled:!1,modelPath:"mb3-centernet.json",minConfidence:.2,iouThreshold:.4,maxDetected:10,skipFrames:99,skipTime:2e3},segmentation:{enabled:!1,modelPath:"selfie.json",blur:8}};var je={};oa(je,{Abs:()=>ol,Acos:()=>dc,Acosh:()=>pc,AdadeltaOptimizer:()=>H0,AdagradOptimizer:()=>j0,AdamOptimizer:()=>q0,AdamaxOptimizer:()=>X0,Add:()=>Aa,AddN:()=>co,All:()=>hc,Any:()=>fc,ArgMax:()=>po,ArgMin:()=>mc,Asin:()=>gc,Asinh:()=>yc,Atan:()=>Ac,Atan2:()=>bc,Atanh:()=>xc,AvgPool:()=>ho,AvgPool3D:()=>Mp,AvgPool3DGrad:()=>Gm,AvgPoolGrad:()=>Um,BackendWasm:()=>WC,BatchMatMul:()=>fo,BatchToSpaceND:()=>il,Bincount:()=>Hm,BroadcastArgs:()=>jm,BroadcastTo:()=>c6,Callback:()=>kk,CallbackList:()=>T8,Cast:()=>mo,Ceil:()=>go,ClipByValue:()=>xa,Complex:()=>zp,ComplexAbs:()=>Lp,Concat:()=>ll,Conv2D:()=>yo,Conv2DBackpropFilter:()=>qm,Conv2DBackpropInput:()=>Ao,Conv3D:()=>Bp,Conv3DBackpropFilterV2:()=>Xm,Conv3DBackpropInputV2:()=>Km,Cos:()=>xo,Cosh:()=>bo,CropAndResize:()=>cl,Cumprod:()=>ul,Cumsum:()=>vo,CustomCallback:()=>E8,DataStorage:()=>Op,DenseBincount:()=>Zm,DepthToSpace:()=>dl,DepthwiseConv2dNative:()=>wo,DepthwiseConv2dNativeBackpropFilter:()=>Ym,DepthwiseConv2dNativeBackpropInput:()=>Jm,Diag:()=>Qm,Dilation2D:()=>Wp,Dilation2DBackpropFilter:()=>pm,Dilation2DBackpropInput:()=>dm,ENV:()=>wy,EarlyStopping:()=>Ik,Einsum:()=>Vp,Elu:()=>Io,EluGrad:()=>e0,Environment:()=>l6,Equal:()=>pl,Erf:()=>vc,Exp:()=>So,ExpandDims:()=>hl,Expm1:()=>fl,FFT:()=>t0,Fill:()=>wc,FlipLeftRight:()=>ml,Floor:()=>Co,FloorDiv:()=>To,FromPixels:()=>xp,FusedBatchNorm:()=>No,FusedConv2D:()=>Ja,FusedDepthwiseConv2D:()=>Qa,GPGPUContext:()=>Hu,GatherNd:()=>yl,GatherV2:()=>gl,GraphModel:()=>Dh,Greater:()=>Al,GreaterEqual:()=>Eo,History:()=>N8,IFFT:()=>n0,Identity:()=>Ro,Imag:()=>Up,InputSpec:()=>rn,IsFinite:()=>kc,IsInf:()=>Ic,IsNan:()=>Sc,KernelBackend:()=>uc,LRN:()=>Gp,LRNGrad:()=>r0,LayerVariable:()=>b8,LayersModel:()=>pa,LeakyRelu:()=>_o,Less:()=>xl,LessEqual:()=>bl,LinSpace:()=>s0,Log:()=>Do,Log1p:()=>Cc,LogSoftmax:()=>p6,LogicalAnd:()=>vl,LogicalNot:()=>wl,LogicalOr:()=>Tc,LogicalXor:()=>d6,LowerBound:()=>B_,MathBackendWebGL:()=>od,Max:()=>$o,MaxPool:()=>Fo,MaxPool3D:()=>Hp,MaxPool3DGrad:()=>o0,MaxPoolGrad:()=>a0,MaxPoolWithArgmax:()=>i0,Maximum:()=>Po,Mean:()=>Oo,Min:()=>Mo,Minimum:()=>zo,MirrorPad:()=>Lo,Mod:()=>Nc,MomentumOptimizer:()=>K0,Multinomial:()=>l0,Multiply:()=>Bo,Neg:()=>kl,NonMaxSuppressionV3:()=>Sl,NonMaxSuppressionV4:()=>Ec,NonMaxSuppressionV5:()=>Cl,NotEqual:()=>Il,OP_SCOPE_SUFFIX:()=>Cy,OneHot:()=>Nl,OnesLike:()=>Tl,Optimizer:()=>wa,OptimizerConstructors:()=>Ba,Pack:()=>El,PadV2:()=>Wo,Pool:()=>W_,Pow:()=>Vo,Prelu:()=>Uo,Prod:()=>Go,RMSPropOptimizer:()=>Z0,RNN:()=>Jr,Range:()=>Rc,Rank:()=>y3,Real:()=>jp,RealDiv:()=>ko,Reciprocal:()=>_c,Reduction:()=>Yn,Relu:()=>Ho,Relu6:()=>Xo,Reshape:()=>Rl,ResizeBilinear:()=>qo,ResizeBilinearGrad:()=>c0,ResizeNearestNeighbor:()=>jo,ResizeNearestNeighborGrad:()=>u0,Reverse:()=>_l,RotateWithOffset:()=>Hl,Round:()=>Dl,Rsqrt:()=>Ko,SGDOptimizer:()=>bh,ScatterNd:()=>$l,SearchSorted:()=>d0,Select:()=>Pl,Selu:()=>Dc,Sequential:()=>nc,Sigmoid:()=>Yo,Sign:()=>$c,Sin:()=>Zo,Sinh:()=>Ol,Slice:()=>Fl,Softmax:()=>ei,Softplus:()=>Pc,SpaceToBatchND:()=>Ml,SparseFillEmptyRows:()=>qp,SparseReshape:()=>Fc,SparseSegmentMean:()=>Xp,SparseSegmentSum:()=>Kp,SparseToDense:()=>Zp,SplitV:()=>zl,Sqrt:()=>Jo,Square:()=>Oc,SquaredDifference:()=>ti,Step:()=>ri,StridedSlice:()=>Ll,StringNGrams:()=>Mc,StringSplit:()=>Yp,StringToHashBucketFast:()=>Jp,Sub:()=>ni,Sum:()=>Qo,SymbolicTensor:()=>Cr,Tan:()=>Bl,Tanh:()=>si,Tensor:()=>tt,TensorBuffer:()=>fn,Tile:()=>ba,TopK:()=>Wl,Transform:()=>Vl,Transpose:()=>Gr,Unique:()=>p0,Unpack:()=>Ul,UnsortedSegmentSum:()=>Qp,UpperBound:()=>V_,Variable:()=>wp,ZerosLike:()=>Gl,_FusedMatMul:()=>Ya,abs:()=>tn,acos:()=>Hy,acosh:()=>jy,add:()=>ce,addN:()=>f0,all:()=>m0,any:()=>Sp,argMax:()=>Es,argMin:()=>qy,asin:()=>Xy,asinh:()=>Ky,atan:()=>Zy,atan2:()=>Yy,atanh:()=>Jy,avgPool:()=>ih,avgPool3d:()=>eA,backend:()=>Zs,backend_util:()=>C,basicLSTMCell:()=>sw,batchNorm:()=>Bc,batchNorm2d:()=>tA,batchNorm3d:()=>nA,batchNorm4d:()=>sA,batchToSpaceND:()=>lh,bincount:()=>rA,booleanMaskAsync:()=>zw,broadcastArgs:()=>rw,broadcastTo:()=>Uu,broadcast_util:()=>ql,browser:()=>Ys,buffer:()=>Le,callbacks:()=>jH,cast:()=>ge,ceil:()=>aA,clipByValue:()=>fs,clone:()=>Fn,complex:()=>ha,concat:()=>Ct,concat1d:()=>oA,concat2d:()=>Xl,concat3d:()=>iA,concat4d:()=>lA,constraints:()=>k8,conv1d:()=>g0,conv2d:()=>fa,conv2dTranspose:()=>y0,conv3d:()=>cA,conv3dTranspose:()=>dA,copyRegisteredKernels:()=>j_,cos:()=>uh,cosh:()=>A0,cosineWindow:()=>B0,cumprod:()=>Cp,cumsum:()=>x0,customGrad:()=>Xr,data:()=>Xk,denseBincount:()=>ow,deprecationWarn:()=>Py,depthToSpace:()=>pA,depthwiseConv2d:()=>Wc,deregisterOp:()=>KH,device_util:()=>sh,diag:()=>iw,dilation2d:()=>hA,disableDeprecationWarnings:()=>x$,dispose:()=>ne,disposeVariables:()=>b$,div:()=>pe,divNoNan:()=>fA,dot:()=>mA,dropout:()=>WA,einsum:()=>lw,elu:()=>Vc,enableDebugMode:()=>A$,enableProdMode:()=>$y,enclosingPowerOfTwo:()=>VA,engine:()=>sn,env:()=>X,equal:()=>Rs,erf:()=>gA,euclideanNorm:()=>xA,exp:()=>_s,expandDims:()=>Kt,expm1:()=>bA,eye:()=>b0,fft:()=>Ah,fill:()=>Gc,findBackend:()=>Oy,findBackendFactory:()=>I$,floor:()=>Hc,floorDiv:()=>Lc,forceHalfFloat:()=>i9,fused:()=>Qu,gather:()=>jc,gatherND:()=>Vw,gather_util:()=>zy,getBackend:()=>ss,getGradient:()=>m3,getKernel:()=>hm,getKernelsForBackend:()=>jr,getThreadsCount:()=>vme,gpgpu_util:()=>LS,grad:()=>HF,grads:()=>jF,greater:()=>ys,greaterEqual:()=>ii,ifft:()=>Ju,imag:()=>ah,image:()=>Ne,inTopKAsync:()=>Uw,initializers:()=>I8,input:()=>U8,io:()=>Ts,irfft:()=>O0,isFinite:()=>vA,isInf:()=>wA,isNaN:()=>kA,keep:()=>bn,kernel_impls:()=>dr,layers:()=>S8,leakyRelu:()=>ch,less:()=>v0,lessEqual:()=>li,linalg:()=>HA,linspace:()=>hw,loadGraphModel:()=>Jj,loadGraphModelSync:()=>Qj,loadLayersModel:()=>nG,localResponseNormalization:()=>IA,log:()=>Ds,log1p:()=>dh,logSigmoid:()=>SA,logSoftmax:()=>k0,logSumExp:()=>I0,logicalAnd:()=>lr,logicalNot:()=>ph,logicalOr:()=>S0,logicalXor:()=>CA,losses:()=>t8,lowerBound:()=>mw,matMul:()=>Qe,math:()=>O6,max:()=>mn,maxPool:()=>hh,maxPool3d:()=>TA,maxPoolWithArgmax:()=>gw,maximum:()=>Yr,mean:()=>Bt,memory:()=>gm,meshgrid:()=>yw,metrics:()=>bk,min:()=>ma,minimum:()=>qc,mirrorPad:()=>NA,mod:()=>Zl,model:()=>eG,models:()=>vk,moments:()=>fh,movingAverage:()=>Lw,mul:()=>L,multiRNNCell:()=>Aw,multinomial:()=>xw,neg:()=>Dt,nextFrame:()=>jA,norm:()=>Uc,notEqual:()=>Ji,oneHot:()=>Ku,ones:()=>Ns,onesLike:()=>$s,op:()=>V,outerProduct:()=>bw,pad:()=>Js,pad1d:()=>vw,pad2d:()=>ww,pad3d:()=>kw,pad4d:()=>Iw,pool:()=>EA,pow:()=>ga,prelu:()=>gh,print:()=>Ry,prod:()=>RA,profile:()=>v$,rand:()=>Sw,randomGamma:()=>Cw,randomNormal:()=>T0,randomStandardNormal:()=>Tw,randomUniform:()=>Xc,range:()=>Yu,ready:()=>zc,real:()=>Zu,reciprocal:()=>$A,registerBackend:()=>jl,registerCallbackConstructor:()=>sG,registerGradient:()=>h6,registerKernel:()=>cr,registerOp:()=>XH,regularizers:()=>wk,relu:()=>$r,relu6:()=>N0,removeBackend:()=>k$,reshape:()=>U,reverse:()=>Ks,reverse1d:()=>Nw,reverse2d:()=>Ew,reverse3d:()=>Rw,reverse4d:()=>_w,rfft:()=>xh,round:()=>E0,rsqrt:()=>R0,scalar:()=>Se,scatterND:()=>Bw,scatter_util:()=>Ly,searchSorted:()=>C0,selu:()=>_0,separableConv2d:()=>D0,sequential:()=>tG,serialization:()=>de,setBackend:()=>Fy,setPlatform:()=>S$,setThreadsCount:()=>bme,setWasmPath:()=>xme,setWasmPaths:()=>tb,setWebGLContext:()=>A2,setdiff1dAsync:()=>Dw,sigmoid:()=>Cn,sign:()=>PA,signal:()=>e8,sin:()=>$0,sinh:()=>P0,slice:()=>Oe,slice1d:()=>yh,slice2d:()=>F0,slice3d:()=>ui,slice4d:()=>to,slice_util:()=>Ut,softmax:()=>Yl,softplus:()=>Kl,spaceToBatchND:()=>mh,sparse:()=>n8,sparseToDense:()=>Ww,spectral:()=>Qw,split:()=>Zt,sqrt:()=>Nn,square:()=>vt,squaredDifference:()=>M0,squeeze:()=>rt,stack:()=>on,step:()=>Jl,stridedSlice:()=>FA,string:()=>s8,sub:()=>he,sum:()=>ke,sumOutType:()=>nh,tan:()=>OA,tanh:()=>Zi,tensor:()=>ft,tensor1d:()=>Ft,tensor2d:()=>or,tensor3d:()=>My,tensor4d:()=>$w,tensor5d:()=>Pw,tensor6d:()=>Fw,tensor_util:()=>Tr,test_util:()=>Y6,tidy:()=>J,tile:()=>js,time:()=>w$,topk:()=>MA,train:()=>Pi,transpose:()=>st,truncatedNormal:()=>z0,unique:()=>zA,unregisterGradient:()=>H_,unregisterKernel:()=>G_,unsortedSegmentSum:()=>L0,unstack:()=>es,upcastType:()=>On,upperBound:()=>Ow,util:()=>v,valueAndGrad:()=>qF,valueAndGrads:()=>XF,variable:()=>LA,variableGrads:()=>fw,version:()=>Vh,version_converter:()=>tq,version_core:()=>Gy,version_layers:()=>f5,version_wasm:()=>wme,version_webgl:()=>gne,webgl:()=>yne,webgl_util:()=>uS,webgpu:()=>fT,where:()=>Mn,whereAsync:()=>BA,zeros:()=>Wt,zerosLike:()=>it});var ZR=Object.create,yy=Object.defineProperty,YR=Object.getOwnPropertyDescriptor,Z7=Object.getOwnPropertyNames,JR=Object.getPrototypeOf,QR=Object.prototype.hasOwnProperty,ln=(e,t)=>function(){return t||(0,e[Z7(e)[0]])((t={exports:{}}).exports,t),t.exports},Ve=(e,t)=>{for(var n in t)yy(e,n,{get:t[n],enumerable:!0})},e_=(e,t,n,s)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of Z7(t))!QR.call(e,r)&&r!==n&&yy(e,r,{get:()=>t[r],enumerable:!(s=YR(t,r))||s.enumerable});return e},lo=(e,t,n)=>(n=e!=null?ZR(JR(e)):{},e_(t||!e||!e.__esModule?yy(n,"default",{value:e,enumerable:!0}):n,e)),t_=ln({"node_modules/.pnpm/long@4.0.0/node_modules/long/src/long.js"(e,t){t.exports=s;var n=null;try{n=new WebAssembly.Instance(new WebAssembly.Module(new Uint8Array([0,97,115,109,1,0,0,0,1,13,2,96,0,1,127,96,4,127,127,127,127,1,127,3,7,6,0,1,1,1,1,1,6,6,1,127,1,65,0,11,7,50,6,3,109,117,108,0,1,5,100,105,118,95,115,0,2,5,100,105,118,95,117,0,3,5,114,101,109,95,115,0,4,5,114,101,109,95,117,0,5,8,103,101,116,95,104,105,103,104,0,0,10,191,1,6,4,0,35,0,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,126,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,127,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,128,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,129,34,4,66,32,135,167,36,0,32,4,167,11,36,1,1,126,32,0,173,32,1,173,66,32,134,132,32,2,173,32,3,173,66,32,134,132,130,34,4,66,32,135,167,36,0,32,4,167,11])),{}).exports}catch($){}function s($,T,F){this.low=$|0,this.high=T|0,this.unsigned=!!F}s.prototype.__isLong__,Object.defineProperty(s.prototype,"__isLong__",{value:!0});function r($){return($&&$.__isLong__)===!0}s.isLong=r;var a={},o={};function i($,T){var F,G,q;return T?($>>>=0,(q=0<=$&&$<256)&&(G=o[$],G)?G:(F=u($,($|0)<0?-1:0,!0),q&&(o[$]=F),F)):($|=0,(q=-128<=$&&$<128)&&(G=a[$],G)?G:(F=u($,$<0?-1:0,!1),q&&(a[$]=F),F))}s.fromInt=i;function l($,T){if(isNaN($))return T?b:A;if(T){if($<0)return b;if($>=g)return R}else{if($<=-y)return P;if($+1>=y)return E}return $<0?l(-$,T).neg():u($%m|0,$/m|0,T)}s.fromNumber=l;function u($,T,F){return new s($,T,F)}s.fromBits=u;var c=Math.pow;function p($,T,F){if($.length===0)throw Error("empty string");if($==="NaN"||$==="Infinity"||$==="+Infinity"||$==="-Infinity")return A;if(typeof T=="number"?(F=T,T=!1):T=!!T,F=F||10,F<2||36<F)throw RangeError("radix");var G;if((G=$.indexOf("-"))>0)throw Error("interior hyphen");if(G===0)return p($.substring(1),T,F).neg();for(var q=l(c(F,8)),z=A,Z=0;Z<$.length;Z+=8){var B=Math.min(8,$.length-Z),ee=parseInt($.substring(Z,Z+B),F);if(B<8){var Q=l(c(F,B));z=z.mul(Q).add(l(ee))}else z=z.mul(q),z=z.add(l(ee))}return z.unsigned=T,z}s.fromString=p;function d($,T){return typeof $=="number"?l($,T):typeof $=="string"?p($,T):u($.low,$.high,typeof T=="boolean"?T:$.unsigned)}s.fromValue=d;var h=1<<16,f=1<<24,m=h*h,g=m*m,y=g/2,x=i(f),A=i(0);s.ZERO=A;var b=i(0,!0);s.UZERO=b;var w=i(1);s.ONE=w;var k=i(1,!0);s.UONE=k;var S=i(-1);s.NEG_ONE=S;var E=u(-1,2147483647,!1);s.MAX_VALUE=E;var R=u(-1,-1,!0);s.MAX_UNSIGNED_VALUE=R;var P=u(0,-2147483648,!1);s.MIN_VALUE=P;var _=s.prototype;_.toInt=function(){return this.unsigned?this.low>>>0:this.low},_.toNumber=function(){return this.unsigned?(this.high>>>0)*m+(this.low>>>0):this.high*m+(this.low>>>0)},_.toString=function(T){if(T=T||10,T<2||36<T)throw RangeError("radix");if(this.isZero())return"0";if(this.isNegative())if(this.eq(P)){var F=l(T),G=this.div(F),q=G.mul(F).sub(this);return G.toString(T)+q.toInt().toString(T)}else return"-"+this.neg().toString(T);for(var z=l(c(T,6),this.unsigned),Z=this,B="";;){var ee=Z.div(z),Q=Z.sub(ee.mul(z)).toInt()>>>0,oe=Q.toString(T);if(Z=ee,Z.isZero())return oe+B;for(;oe.length<6;)oe="0"+oe;B=""+oe+B}},_.getHighBits=function(){return this.high},_.getHighBitsUnsigned=function(){return this.high>>>0},_.getLowBits=function(){return this.low},_.getLowBitsUnsigned=function(){return this.low>>>0},_.getNumBitsAbs=function(){if(this.isNegative())return this.eq(P)?64:this.neg().getNumBitsAbs();for(var T=this.high!=0?this.high:this.low,F=31;F>0&&(T&1<<F)==0;F--);return this.high!=0?F+33:F+1},_.isZero=function(){return this.high===0&&this.low===0},_.eqz=_.isZero,_.isNegative=function(){return!this.unsigned&&this.high<0},_.isPositive=function(){return this.unsigned||this.high>=0},_.isOdd=function(){return(this.low&1)===1},_.isEven=function(){return(this.low&1)===0},_.equals=function(T){return r(T)||(T=d(T)),this.unsigned!==T.unsigned&&this.high>>>31===1&&T.high>>>31===1?!1:this.high===T.high&&this.low===T.low},_.eq=_.equals,_.notEquals=function(T){return!this.eq(T)},_.neq=_.notEquals,_.ne=_.notEquals,_.lessThan=function(T){return this.comp(T)<0},_.lt=_.lessThan,_.lessThanOrEqual=function(T){return this.comp(T)<=0},_.lte=_.lessThanOrEqual,_.le=_.lessThanOrEqual,_.greaterThan=function(T){return this.comp(T)>0},_.gt=_.greaterThan,_.greaterThanOrEqual=function(T){return this.comp(T)>=0},_.gte=_.greaterThanOrEqual,_.ge=_.greaterThanOrEqual,_.compare=function(T){if(r(T)||(T=d(T)),this.eq(T))return 0;var F=this.isNegative(),G=T.isNegative();return F&&!G?-1:!F&&G?1:this.unsigned?T.high>>>0>this.high>>>0||T.high===this.high&&T.low>>>0>this.low>>>0?-1:1:this.sub(T).isNegative()?-1:1},_.comp=_.compare,_.negate=function(){return!this.unsigned&&this.eq(P)?P:this.not().add(w)},_.neg=_.negate,_.add=function(T){r(T)||(T=d(T));var F=this.high>>>16,G=this.high&65535,q=this.low>>>16,z=this.low&65535,Z=T.high>>>16,B=T.high&65535,ee=T.low>>>16,Q=T.low&65535,oe=0,Y=0,ae=0,le=0;return le+=z+Q,ae+=le>>>16,le&=65535,ae+=q+ee,Y+=ae>>>16,ae&=65535,Y+=G+B,oe+=Y>>>16,Y&=65535,oe+=F+Z,oe&=65535,u(ae<<16|le,oe<<16|Y,this.unsigned)},_.subtract=function(T){return r(T)||(T=d(T)),this.add(T.neg())},_.sub=_.subtract,_.multiply=function(T){if(this.isZero())return A;if(r(T)||(T=d(T)),n){var F=n.mul(this.low,this.high,T.low,T.high);return u(F,n.get_high(),this.unsigned)}if(T.isZero())return A;if(this.eq(P))return T.isOdd()?P:A;if(T.eq(P))return this.isOdd()?P:A;if(this.isNegative())return T.isNegative()?this.neg().mul(T.neg()):this.neg().mul(T).neg();if(T.isNegative())return this.mul(T.neg()).neg();if(this.lt(x)&&T.lt(x))return l(this.toNumber()*T.toNumber(),this.unsigned);var G=this.high>>>16,q=this.high&65535,z=this.low>>>16,Z=this.low&65535,B=T.high>>>16,ee=T.high&65535,Q=T.low>>>16,oe=T.low&65535,Y=0,ae=0,le=0,ye=0;return ye+=Z*oe,le+=ye>>>16,ye&=65535,le+=z*oe,ae+=le>>>16,le&=65535,le+=Z*Q,ae+=le>>>16,le&=65535,ae+=q*oe,Y+=ae>>>16,ae&=65535,ae+=z*Q,Y+=ae>>>16,ae&=65535,ae+=Z*ee,Y+=ae>>>16,ae&=65535,Y+=G*oe+q*Q+z*ee+Z*B,Y&=65535,u(le<<16|ye,Y<<16|ae,this.unsigned)},_.mul=_.multiply,_.divide=function(T){if(r(T)||(T=d(T)),T.isZero())throw Error("division by zero");if(n){if(!this.unsigned&&this.high===-2147483648&&T.low===-1&&T.high===-1)return this;var F=(this.unsigned?n.div_u:n.div_s)(this.low,this.high,T.low,T.high);return u(F,n.get_high(),this.unsigned)}if(this.isZero())return this.unsigned?b:A;var G,q,z;if(this.unsigned){if(T.unsigned||(T=T.toUnsigned()),T.gt(this))return b;if(T.gt(this.shru(1)))return k;z=b}else{if(this.eq(P)){if(T.eq(w)||T.eq(S))return P;if(T.eq(P))return w;var Z=this.shr(1);return G=Z.div(T).shl(1),G.eq(A)?T.isNegative()?w:S:(q=this.sub(T.mul(G)),z=G.add(q.div(T)),z)}else if(T.eq(P))return this.unsigned?b:A;if(this.isNegative())return T.isNegative()?this.neg().div(T.neg()):this.neg().div(T).neg();if(T.isNegative())return this.div(T.neg()).neg();z=A}for(q=this;q.gte(T);){G=Math.max(1,Math.floor(q.toNumber()/T.toNumber()));for(var B=Math.ceil(Math.log(G)/Math.LN2),ee=B<=48?1:c(2,B-48),Q=l(G),oe=Q.mul(T);oe.isNegative()||oe.gt(q);)G-=ee,Q=l(G,this.unsigned),oe=Q.mul(T);Q.isZero()&&(Q=w),z=z.add(Q),q=q.sub(oe)}return z},_.div=_.divide,_.modulo=function(T){if(r(T)||(T=d(T)),n){var F=(this.unsigned?n.rem_u:n.rem_s)(this.low,this.high,T.low,T.high);return u(F,n.get_high(),this.unsigned)}return this.sub(this.div(T).mul(T))},_.mod=_.modulo,_.rem=_.modulo,_.not=function(){return u(~this.low,~this.high,this.unsigned)},_.and=function(T){return r(T)||(T=d(T)),u(this.low&T.low,this.high&T.high,this.unsigned)},_.or=function(T){return r(T)||(T=d(T)),u(this.low|T.low,this.high|T.high,this.unsigned)},_.xor=function(T){return r(T)||(T=d(T)),u(this.low^T.low,this.high^T.high,this.unsigned)},_.shiftLeft=function(T){return r(T)&&(T=T.toInt()),(T&=63)===0?this:T<32?u(this.low<<T,this.high<<T|this.low>>>32-T,this.unsigned):u(0,this.low<<T-32,this.unsigned)},_.shl=_.shiftLeft,_.shiftRight=function(T){return r(T)&&(T=T.toInt()),(T&=63)===0?this:T<32?u(this.low>>>T|this.high<<32-T,this.high>>T,this.unsigned):u(this.high>>T-32,this.high>=0?0:-1,this.unsigned)},_.shr=_.shiftRight,_.shiftRightUnsigned=function(T){if(r(T)&&(T=T.toInt()),T&=63,T===0)return this;var F=this.high;if(T<32){var G=this.low;return u(G>>>T|F<<32-T,F>>>T,this.unsigned)}else return T===32?u(F,0,this.unsigned):u(F>>>T-32,0,this.unsigned)},_.shru=_.shiftRightUnsigned,_.shr_u=_.shiftRightUnsigned,_.toSigned=function(){return this.unsigned?u(this.low,this.high,!1):this},_.toUnsigned=function(){return this.unsigned?this:u(this.low,this.high,!0)},_.toBytes=function(T){return T?this.toBytesLE():this.toBytesBE()},_.toBytesLE=function(){var T=this.high,F=this.low;return[F&255,F>>>8&255,F>>>16&255,F>>>24,T&255,T>>>8&255,T>>>16&255,T>>>24]},_.toBytesBE=function(){var T=this.high,F=this.low;return[T>>>24,T>>>16&255,T>>>8&255,T&255,F>>>24,F>>>16&255,F>>>8&255,F&255]},s.fromBytes=function(T,F,G){return G?s.fromBytesLE(T,F):s.fromBytesBE(T,F)},s.fromBytesLE=function(T,F){return new s(T[0]|T[1]<<8|T[2]<<16|T[3]<<24,T[4]|T[5]<<8|T[6]<<16|T[7]<<24,F)},s.fromBytesBE=function(T,F){return new s(T[4]<<24|T[5]<<16|T[6]<<8|T[7],T[0]<<24|T[1]<<16|T[2]<<8|T[3],F)}}}),n_=ln({"(disabled):node_modules/.pnpm/node-fetch@2.6.7/node_modules/node-fetch/browser.js"(){}}),s_=ln({"(disabled):util"(){}}),r_=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/alea.js"(e,t){(function(n,s,r){function a(u){var c=this,p=l();c.next=function(){var d=2091639*c.s0+c.c*23283064365386963e-26;return c.s0=c.s1,c.s1=c.s2,c.s2=d-(c.c=d|0)},c.c=1,c.s0=p(" "),c.s1=p(" "),c.s2=p(" "),c.s0-=p(u),c.s0<0&&(c.s0+=1),c.s1-=p(u),c.s1<0&&(c.s1+=1),c.s2-=p(u),c.s2<0&&(c.s2+=1),p=null}function o(u,c){return c.c=u.c,c.s0=u.s0,c.s1=u.s1,c.s2=u.s2,c}function i(u,c){var p=new a(u),d=c&&c.state,h=p.next;return h.int32=function(){return p.next()*4294967296|0},h.double=function(){return h()+(h()*2097152|0)*11102230246251565e-32},h.quick=h,d&&(typeof d=="object"&&o(d,p),h.state=function(){return o(p,{})}),h}function l(){var u=4022871197,c=function(p){p=String(p);for(var d=0;d<p.length;d++){u+=p.charCodeAt(d);var h=.02519603282416938*u;u=h>>>0,h-=u,h*=u,u=h>>>0,h-=u,u+=h*4294967296}return(u>>>0)*23283064365386963e-26};return c}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.alea=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),a_=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xor128.js"(e,t){(function(n,s,r){function a(l){var u=this,c="";u.x=0,u.y=0,u.z=0,u.w=0,u.next=function(){var d=u.x^u.x<<11;return u.x=u.y,u.y=u.z,u.z=u.w,u.w^=u.w>>>19^d^d>>>8},l===(l|0)?u.x=l:c+=l;for(var p=0;p<c.length+64;p++)u.x^=c.charCodeAt(p)|0,u.next()}function o(l,u){return u.x=l.x,u.y=l.y,u.z=l.z,u.w=l.w,u}function i(l,u){var c=new a(l),p=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var h=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,p&&(typeof p=="object"&&o(p,c),d.state=function(){return o(c,{})}),d}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xor128=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),o_=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xorwow.js"(e,t){(function(n,s,r){function a(l){var u=this,c="";u.next=function(){var d=u.x^u.x>>>2;return u.x=u.y,u.y=u.z,u.z=u.w,u.w=u.v,(u.d=u.d+362437|0)+(u.v=u.v^u.v<<4^(d^d<<1))|0},u.x=0,u.y=0,u.z=0,u.w=0,u.v=0,l===(l|0)?u.x=l:c+=l;for(var p=0;p<c.length+64;p++)u.x^=c.charCodeAt(p)|0,p==c.length&&(u.d=u.x<<10^u.x>>>4),u.next()}function o(l,u){return u.x=l.x,u.y=l.y,u.z=l.z,u.w=l.w,u.v=l.v,u.d=l.d,u}function i(l,u){var c=new a(l),p=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var h=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,p&&(typeof p=="object"&&o(p,c),d.state=function(){return o(c,{})}),d}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xorwow=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),i_=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xorshift7.js"(e,t){(function(n,s,r){function a(l){var u=this;u.next=function(){var p=u.x,d=u.i,h,f,m;return h=p[d],h^=h>>>7,f=h^h<<24,h=p[d+1&7],f^=h^h>>>10,h=p[d+3&7],f^=h^h>>>3,h=p[d+4&7],f^=h^h<<7,h=p[d+7&7],h=h^h<<13,f^=h^h<<9,p[d]=f,u.i=d+1&7,f};function c(p,d){var h,f,m=[];if(d===(d|0))f=m[0]=d;else for(d=""+d,h=0;h<d.length;++h)m[h&7]=m[h&7]<<15^d.charCodeAt(h)+m[h+1&7]<<13;for(;m.length<8;)m.push(0);for(h=0;h<8&&m[h]===0;++h);for(h==8?f=m[7]=-1:f=m[h],p.x=m,p.i=0,h=256;h>0;--h)p.next()}c(u,l)}function o(l,u){return u.x=l.x.slice(),u.i=l.i,u}function i(l,u){l==null&&(l=+new Date);var c=new a(l),p=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var h=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,p&&(p.x&&o(p,c),d.state=function(){return o(c,{})}),d}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xorshift7=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),l_=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/xor4096.js"(e,t){(function(n,s,r){function a(l){var u=this;u.next=function(){var p=u.w,d=u.X,h=u.i,f,m;return u.w=p=p+1640531527|0,m=d[h+34&127],f=d[h=h+1&127],m^=m<<13,f^=f<<17,m^=m>>>15,f^=f>>>12,m=d[h]=m^f,u.i=h,m+(p^p>>>16)|0};function c(p,d){var h,f,m,g,y,x=[],A=128;for(d===(d|0)?(f=d,d=null):(d=d+"\0",f=0,A=Math.max(A,d.length)),m=0,g=-32;g<A;++g)d&&(f^=d.charCodeAt((g+32)%d.length)),g===0&&(y=f),f^=f<<10,f^=f>>>15,f^=f<<4,f^=f>>>13,g>=0&&(y=y+1640531527|0,h=x[g&127]^=f+y,m=h==0?m+1:0);for(m>=128&&(x[(d&&d.length||0)&127]=-1),m=127,g=4*128;g>0;--g)f=x[m+34&127],h=x[m=m+1&127],f^=f<<13,h^=h<<17,f^=f>>>15,h^=h>>>12,x[m]=f^h;p.w=y,p.X=x,p.i=m}c(u,l)}function o(l,u){return u.i=l.i,u.w=l.w,u.X=l.X.slice(),u}function i(l,u){l==null&&(l=+new Date);var c=new a(l),p=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var h=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,p&&(p.X&&o(p,c),d.state=function(){return o(c,{})}),d}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.xor4096=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),u_=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/lib/tychei.js"(e,t){(function(n,s,r){function a(l){var u=this,c="";u.next=function(){var d=u.b,h=u.c,f=u.d,m=u.a;return d=d<<25^d>>>7^h,h=h-f|0,f=f<<24^f>>>8^m,m=m-d|0,u.b=d=d<<20^d>>>12^h,u.c=h=h-f|0,u.d=f<<16^h>>>16^m,u.a=m-d|0},u.a=0,u.b=0,u.c=-1640531527,u.d=1367130551,l===Math.floor(l)?(u.a=l/4294967296|0,u.b=l|0):c+=l;for(var p=0;p<c.length+20;p++)u.b^=c.charCodeAt(p)|0,u.next()}function o(l,u){return u.a=l.a,u.b=l.b,u.c=l.c,u.d=l.d,u}function i(l,u){var c=new a(l),p=u&&u.state,d=function(){return(c.next()>>>0)/4294967296};return d.double=function(){do var h=c.next()>>>11,f=(c.next()>>>0)/4294967296,m=(h+f)/(1<<21);while(m===0);return m},d.int32=c.next,d.quick=d,p&&(typeof p=="object"&&o(p,c),d.state=function(){return o(c,{})}),d}s&&s.exports?s.exports=i:r&&r.amd?r(function(){return i}):this.tychei=i})(e,typeof t=="object"&&t,typeof define=="function"&&define)}}),c_=ln({"(disabled):crypto"(){}}),d_=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/seedrandom.js"(e,t){(function(n,s,r){var a=256,o=6,i=52,l="random",u=r.pow(a,o),c=r.pow(2,i),p=c*2,d=a-1,h;function f(w,k,S){var E=[];k=k==!0?{entropy:!0}:k||{};var R=x(y(k.entropy?[w,b(s)]:w==null?A():w,3),E),P=new m(E),_=function(){for(var $=P.g(o),T=u,F=0;$<c;)$=($+F)*a,T*=a,F=P.g(1);for(;$>=p;)$/=2,T/=2,F>>>=1;return($+F)/T};return _.int32=function(){return P.g(4)|0},_.quick=function(){return P.g(4)/4294967296},_.double=_,x(b(P.S),s),(k.pass||S||function($,T,F,G){return G&&(G.S&&g(G,P),$.state=function(){return g(P,{})}),F?(r[l]=$,T):$})(_,R,"global"in k?k.global:this==r,k.state)}function m(w){var k,S=w.length,E=this,R=0,P=E.i=E.j=0,_=E.S=[];for(S||(w=[S++]);R<a;)_[R]=R++;for(R=0;R<a;R++)_[R]=_[P=d&P+w[R%S]+(k=_[R])],_[P]=k;(E.g=function($){for(var T,F=0,G=E.i,q=E.j,z=E.S;$--;)T=z[G=d&G+1],F=F*a+z[d&(z[G]=z[q=d&q+T])+(z[q]=T)];return E.i=G,E.j=q,F})(a)}function g(w,k){return k.i=w.i,k.j=w.j,k.S=w.S.slice(),k}function y(w,k){var S=[],E=typeof w,R;if(k&&E=="object")for(R in w)try{S.push(y(w[R],k-1))}catch(P){}return S.length?S:E=="string"?w:w+"\0"}function x(w,k){for(var S=w+"",E,R=0;R<S.length;)k[d&R]=d&(E^=k[d&R]*19)+S.charCodeAt(R++);return b(k)}function A(){try{var w;return h&&(w=h.randomBytes)?w=w(a):(w=new Uint8Array(a),(n.crypto||n.msCrypto).getRandomValues(w)),b(w)}catch(E){var k=n.navigator,S=k&&k.plugins;return[+new Date,n,S,n.screen,b(s)]}}function b(w){return String.fromCharCode.apply(0,w)}if(x(r.random(),s),typeof t=="object"&&t.exports){t.exports=f;try{h=c_()}catch(w){}}else typeof define=="function"&&define.amd?define(function(){return f}):r["seed"+l]=f})(typeof self!="undefined"?self:e,[],Math)}}),Bm=ln({"node_modules/.pnpm/seedrandom@3.0.5/node_modules/seedrandom/index.js"(e,t){var n=r_(),s=a_(),r=o_(),a=i_(),o=l_(),i=u_(),l=d_();l.alea=n,l.xor128=s,l.xorwow=r,l.xorshift7=a,l.xor4096=o,l.tychei=i,t.exports=l}}),Y7=ln({"(disabled):node_modules/.pnpm/string_decoder@1.3.0/node_modules/string_decoder/lib/string_decoder.js"(){}}),Ay=ln({"(disabled):fs"(){}}),lm=ln({"(disabled):path"(){}}),p_=ln({"(disabled):worker_threads"(){}}),h_=ln({"(disabled):perf_hooks"(){}}),f_=ln({"(disabled):os"(){}}),m_=ln({"node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.js"(e,t){var n=(()=>{var s=typeof document!="undefined"&&document.currentScript?document.currentScript.src:void 0;return typeof __filename!="undefined"&&(s=s||__filename),function(r){r=r||{};function a(){return $e.buffer!=jn&&yr($e.buffer),nf}function o(){return $e.buffer!=jn&&yr($e.buffer),sf}function i(){return $e.buffer!=jn&&yr($e.buffer),Md}function l(){return $e.buffer!=jn&&yr($e.buffer),rf}function u(){return $e.buffer!=jn&&yr($e.buffer),af}function c(){return $e.buffer!=jn&&yr($e.buffer),of}function p(){return $e.buffer!=jn&&yr($e.buffer),lf}var d=typeof r!="undefined"?r:{},h,f;d.ready=new Promise(function(N,O){h=N,f=O});var m;typeof process!="undefined"&&process.listeners&&(m={uncaughtException:process.listeners("uncaughtException"),unhandledRejection:process.listeners("unhandledRejection")});var g=Object.assign({},d),y=[],x="./this.program",A=(N,O)=>{throw O},b=typeof window=="object",w=typeof importScripts=="function",k=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string",S=d.ENVIRONMENT_IS_PTHREAD||!1,E="";function R(N){return d.locateFile?d.locateFile(N,E):E+N}var P,_,$,T;function F(N){if(N instanceof qd)return;Q("exiting due to exception: "+N)}var G,q,z;if(k){w?E=lm().dirname(E)+"/":E=__dirname+"/",z=()=>{q||(G=Ay(),q=lm())},P=function(H,te){return z(),H=q.normalize(H),G.readFileSync(H,te?void 0:"utf8")},$=O=>{var H=P(O,!0);return H.buffer||(H=new Uint8Array(H)),H},_=(O,H,te)=>{z(),O=q.normalize(O),G.readFile(O,function(Ae,ve){Ae?te(Ae):H(ve.buffer)})},process.argv.length>1&&(x=process.argv[1].replace(/\\/g,"/")),y=process.argv.slice(2),process.on("uncaughtException",function(O){if(!(O instanceof qd))throw O}),process.on("unhandledRejection",function(O){throw O}),A=(O,H)=>{if(Ci())throw process.exitCode=O,H;F(H),process.exit(O)},d.inspect=function(){return"[Emscripten Module object]"};let N;try{N=p_()}catch(O){throw console.error('The "worker_threads" module is not supported in this node.js build - perhaps a newer version is needed?'),O}global.Worker=N.Worker}else(b||w)&&(w?E=self.location.href:typeof document!="undefined"&&document.currentScript&&(E=document.currentScript.src),typeof s!="undefined"&&s&&(E=s),E.indexOf("blob:")!==0?E=E.substr(0,E.replace(/[?#].*/,"").lastIndexOf("/")+1):E="",k||(P=N=>{var O=new XMLHttpRequest;return O.open("GET",N,!1),O.send(null),O.responseText},w&&($=N=>{var O=new XMLHttpRequest;return O.open("GET",N,!1),O.responseType="arraybuffer",O.send(null),new Uint8Array(O.response)}),_=(N,O,H)=>{var te=new XMLHttpRequest;te.open("GET",N,!0),te.responseType="arraybuffer",te.onload=()=>{if(te.status==200||te.status==0&&te.response){O(te.response);return}H()},te.onerror=H,te.send(null)}),T=N=>document.title=N);k&&typeof performance=="undefined"&&(global.performance=h_().performance);var Z=console.log.bind(console),B=console.warn.bind(console);k&&(z(),Z=N=>G.writeSync(1,N+`
 `),B=N=>G.writeSync(2,N+`
-`));var ee=d.print||K,Q=d.printErr||B;Object.assign(d,g),g=null,d.arguments&&(y=d.arguments),d.thisProgram&&(x=d.thisProgram),d.quit&&(A=d.quit);var oe=4;function Y(N){Y.shown||(Y.shown={}),Y.shown[N]||(Y.shown[N]=1,Q(N))}function ae(N,O){if(typeof WebAssembly.Function=="function"){for(var H={i:"i32",j:"i64",f:"f32",d:"f64"},te={parameters:[],results:O[0]=="v"?[]:[H[O[0]]]},Ae=1;Ae<O.length;++Ae)te.parameters.push(H[O[Ae]]);return new WebAssembly.Function(te,N)}var ve=[1,0,1,96],Te=O.slice(0,1),Me=O.slice(1),Lt={i:127,j:126,f:125,d:124};ve.push(Me.length);for(var Ae=0;Ae<Me.length;++Ae)ve.push(Lt[Me[Ae]]);Te=="v"?ve.push(0):ve=ve.concat([1,Lt[Te]]),ve[1]=ve.length-2;var vr=new Uint8Array([0,97,115,109,1,0,0,0].concat(ve,[2,7,1,1,101,1,102,0,0,7,5,1,1,102,0,0])),wr=new WebAssembly.Module(vr),Mf=new WebAssembly.Instance(wr,{e:{f:N}}),Kd=Mf.exports.f;return Kd}var le=[],ye;function we(){if(le.length)return le.pop();try{Us.grow(1)}catch(N){throw N instanceof RangeError?"Unable to grow wasm table. Set ALLOW_TABLE_GROWTH.":N}return Us.length-1}function Re(N,O){for(var H=N;H<N+O;H++){var te=Su(H);te&&ye.set(te,H)}}var _e=0,Be=N=>{_e=N},Ge=Atomics.load,ot=Atomics.store,dt=Atomics.compareExchange,pt;d.wasmBinary&&(pt=d.wasmBinary);var At=d.noExitRuntime||!0;typeof WebAssembly!="object"&&wu("no native wasm support detected");var $e,Tt,It=!1,Un;function Qt(N,O){N||wu(O)}function bs(N){var O=d["_"+N];return O}function pn(N,O,H,te,Ae){var ve={string:function(ks){var Du=0;if(ks!=null&&ks!==0){var iv=(ks.length<<2)+1;Du=_u(iv),aa(ks,Du,iv)}return Du},array:function(ks){var Du=_u(ks.length);return oa(ks,Du),Du}};function Te(ks){return O==="string"?Hn(ks):O==="boolean"?Boolean(ks):ks}var Me=bs(N),Lt=[],vr=0;if(te)for(var wr=0;wr<te.length;wr++){var Mf=ve[H[wr]];Mf?(vr===0&&(vr=Qg()),Lt[wr]=Mf(te[wr])):Lt[wr]=te[wr]}var Kd=Me.apply(null,Lt);function UR(ks){return vr!==0&&$f(vr),Te(ks)}return Kd=UR(Kd),Kd}function Gn(N,O,H,te){H=H||[];var Ae=H.every(function(Te){return Te==="number"}),ve=O!=="string";return ve&&Ae&&!te?bs(N):function(){return pn(N,O,H,arguments,te)}}var vs=1;function ws(N){var O=new TextDecoder(N);this.decode=H=>(H.buffer instanceof SharedArrayBuffer&&(H=new Uint8Array(H)),O.decode.call(O,H))}var $n=typeof TextDecoder!="undefined"?new ws("utf8"):void 0;function Vs(N,O,H){for(var te=O+H,Ae=O;N[Ae]&&!(Ae>=te);)++Ae;if(Ae-O>16&&N.subarray&&$n)return $n.decode(N.subarray(O,Ae));for(var ve="";O<Ae;){var Te=N[O++];if(!(Te&128)){ve+=String.fromCharCode(Te);continue}var Me=N[O++]&63;if((Te&224)==192){ve+=String.fromCharCode((Te&31)<<6|Me);continue}var Lt=N[O++]&63;if((Te&240)==224?Te=(Te&15)<<12|Me<<6|Lt:Te=(Te&7)<<18|Me<<12|Lt<<6|N[O++]&63,Te<65536)ve+=String.fromCharCode(Te);else{var vr=Te-65536;ve+=String.fromCharCode(55296|vr>>10,56320|vr&1023)}}return ve}function Hn(N,O){return N?Vs(o(),N,O):""}function ra(N,O,H,te){if(!(te>0))return 0;for(var Ae=H,ve=H+te-1,Te=0;Te<N.length;++Te){var Me=N.charCodeAt(Te);if(Me>=55296&&Me<=57343){var Lt=N.charCodeAt(++Te);Me=65536+((Me&1023)<<10)|Lt&1023}if(Me<=127){if(H>=ve)break;O[H++]=Me}else if(Me<=2047){if(H+1>=ve)break;O[H++]=192|Me>>6,O[H++]=128|Me&63}else if(Me<=65535){if(H+2>=ve)break;O[H++]=224|Me>>12,O[H++]=128|Me>>6&63,O[H++]=128|Me&63}else{if(H+3>=ve)break;O[H++]=240|Me>>18,O[H++]=128|Me>>12&63,O[H++]=128|Me>>6&63,O[H++]=128|Me&63}}return O[H]=0,H-Ae}function aa(N,O,H){return ra(N,o(),O,H)}function xu(N){for(var O=0,H=0;H<N.length;++H){var te=N.charCodeAt(H);te>=55296&&te<=57343&&(te=65536+((te&1023)<<10)|N.charCodeAt(++H)&1023),te<=127?++O:te<=2047?O+=2:te<=65535?O+=3:O+=4}return O}var Oa=typeof TextDecoder!="undefined"?new ws("utf-16le"):void 0;function oa(N,O){a().set(N,O)}function Md(N,O,H){for(var te=0;te<N.length;++te)a()[O++>>0]=N.charCodeAt(te);H||(a()[O>>0]=0)}function bu(N,O){return N%O>0&&(N+=O-N%O),N}var jn,sf,rf,zd,af,of,W4,lf,uf;S&&(jn=d.buffer);function yr(N){jn=N,d.HEAP8=sf=new Int8Array(N),d.HEAP16=zd=new Int16Array(N),d.HEAP32=of=new Int32Array(N),d.HEAPU8=rf=new Uint8Array(N),d.HEAPU16=af=new Uint16Array(N),d.HEAPU32=W4=new Uint32Array(N),d.HEAPF32=lf=new Float32Array(N),d.HEAPF64=uf=new Float64Array(N)}var cf=d.INITIAL_MEMORY||16777216;if(S)$e=d.wasmMemory,jn=d.buffer;else if(d.wasmMemory)$e=d.wasmMemory;else if($e=new WebAssembly.Memory({initial:cf/65536,maximum:32768,shared:!0}),!($e.buffer instanceof SharedArrayBuffer))throw Q("requested a shared WebAssembly.Memory but the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag"),k&&console.log("(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)"),Error("bad memory");$e&&(jn=$e.buffer),cf=jn.byteLength,yr(jn);var Us,vu=[],Ma=[],b1=[],df=[],Ci=!1,v1=!1,pf=0;function Ti(){return At||pf>0}function qn(){if(d.preRun)for(typeof d.preRun=="function"&&(d.preRun=[d.preRun]);d.preRun.length;)V4(d.preRun.shift());gf(vu)}function Ld(){Ci=!0,!S&&gf(Ma)}function w1(){S||(ze.terminateAllThreads(),v1=!0)}function k1(){if(!S){if(d.postRun)for(typeof d.postRun=="function"&&(d.postRun=[d.postRun]);d.postRun.length;)Bd(d.postRun.shift());gf(df)}}function V4(N){vu.unshift(N)}function U4(N){Ma.unshift(N)}function Bd(N){df.unshift(N)}var za=0,hf=null,Ar=null;function Wd(N){za++,d.monitorRunDependencies&&d.monitorRunDependencies(za)}function G4(N){if(za--,d.monitorRunDependencies&&d.monitorRunDependencies(za),za==0&&(hf!==null&&(clearInterval(hf),hf=null),Ar)){var O=Ar;Ar=null,O()}}d.preloadedImages={},d.preloadedAudios={};function wu(N){S?postMessage({cmd:"onAbort",arg:N}):d.onAbort&&d.onAbort(N),N="Aborted("+N+")",Q(N),It=!0,Un=1,N+=". Build with -s ASSERTIONS=1 for more info.";var O=new WebAssembly.RuntimeError(N);throw f(O),O}var I1="data:application/octet-stream;base64,";function Vd(N){return N.startsWith(I1)}function ff(N){return N.startsWith("file://")}var Xn;Xn="tfjs-backend-wasm-threaded-simd.wasm",Vd(Xn)||(Xn=R(Xn));function mf(N){try{if(N==Xn&&pt)return new Uint8Array(pt);if($)return $(N);throw"both async and sync fetching of the wasm failed"}catch(O){wu(O)}}function ku(){if(!pt&&(b||w)){if(typeof fetch=="function"&&!ff(Xn))return fetch(Xn,{credentials:"same-origin"}).then(function(N){if(!N.ok)throw"failed to load wasm binary file at '"+Xn+"'";return N.arrayBuffer()}).catch(function(){return mf(Xn)});if(_)return new Promise(function(N,O){_(Xn,function(H){N(new Uint8Array(H))},O)})}return Promise.resolve().then(function(){return mf(Xn)})}function S1(){var N={env:Nf,wasi_snapshot_preview1:Nf};function O(Te,Me){var Lt=Te.exports;if(d.asm=Lt,D1(d.asm.emscripten_tls_init),Us=d.asm.__indirect_function_table,U4(d.asm.__wasm_call_ctors),Tt=Me,!S){var vr=ze.unusedWorkers.length;ze.unusedWorkers.forEach(function(wr){ze.loadWasmModuleToWorker(wr,function(){--vr||G4("wasm-instantiate")})})}}S||Wd("wasm-instantiate");function H(Te){O(Te.instance,Te.module)}function te(Te){return ku().then(function(Me){return WebAssembly.instantiate(Me,N)}).then(function(Me){return Me}).then(Te,function(Me){Q("failed to asynchronously prepare wasm: "+Me),wu(Me)})}function Ae(){return!pt&&typeof WebAssembly.instantiateStreaming=="function"&&!Vd(Xn)&&!ff(Xn)&&typeof fetch=="function"?fetch(Xn,{credentials:"same-origin"}).then(function(Te){var Me=WebAssembly.instantiateStreaming(Te,N);return Me.then(H,function(Lt){return Q("wasm streaming compile failed: "+Lt),Q("falling back to ArrayBuffer instantiation"),te(H)})}):te(H)}if(d.instantiateWasm)try{var ve=d.instantiateWasm(N,O);return ve}catch(Te){return Q("Module.instantiateWasm callback failed with error: "+Te),!1}return Ae().catch(f),{}}var H4,j4,C1={};function gf(N){for(;N.length>0;){var O=N.shift();if(typeof O=="function"){O(d);continue}var H=O.func;typeof H=="number"?O.arg===void 0?Su(H)():Su(H)(O.arg):H(O.arg===void 0?null:O.arg)}}function Iu(N){var O=Qg(),H=N();return $f(O),H}function YE(N){return N}function q4(N){var O=/\b_Z[\w\d_]+/g;return N.replace(O,function(H){var te=H;return H===te?H:te+" ["+H+"]"})}function T1(N){u()[N>>2]=0;var O=ze.pthreads[N];delete ze.pthreads[N],O.worker.terminate(),Jg(N),ze.runningWorkers.splice(ze.runningWorkers.indexOf(O.worker),1),O.worker.pthread=void 0}function N1(N){var O=ze.pthreads[N];O.worker.postMessage({cmd:"cancel"})}function yf(N){var O=ze.pthreads[N];if(O){u()[N>>2]=0;var H=O.worker;ze.returnWorkerToPool(H)}}function Af(N){BR(N)}function E1(N){if(N instanceof Xd||N=="unwind")return Un;A(1,N)}var ze={unusedWorkers:[],runningWorkers:[],tlsInitFunctions:[],init:function(){S?ze.initWorker():ze.initMainThread()},initMainThread:function(){for(var N=8,O=0;O<N;++O)ze.allocateUnusedWorker()},initWorker:function(){At=!1},pthreads:{},setExitStatus:function(N){Un=N},terminateAllThreads:function(){for(var N in ze.pthreads){var O=ze.pthreads[N];O&&O.worker&&ze.returnWorkerToPool(O.worker)}for(var H=0;H<ze.unusedWorkers.length;++H){var te=ze.unusedWorkers[H];te.terminate()}ze.unusedWorkers=[]},returnWorkerToPool:function(N){ze.runWithoutMainThreadQueuedCalls(function(){delete ze.pthreads[N.pthread.threadInfoStruct],ze.unusedWorkers.push(N),ze.runningWorkers.splice(ze.runningWorkers.indexOf(N),1),Jg(N.pthread.threadInfoStruct),N.pthread=void 0})},runWithoutMainThreadQueuedCalls:function(N){u()[ov>>2]=0;try{N()}finally{u()[ov>>2]=1}},receiveObjectTransfer:function(N){},threadInit:function(){for(var N in ze.tlsInitFunctions)ze.tlsInitFunctions[N]()},loadWasmModuleToWorker:function(N,O){N.onmessage=H=>{var te=H.data,Ae=te.cmd;if(N.pthread&&(ze.currentProxiedOperationCallerThread=N.pthread.threadInfoStruct),te.targetThread&&te.targetThread!=Df()){var ve=ze.pthreads[te.targetThread];ve?ve.worker.postMessage(te,te.transferList):Q('Internal error! Worker sent a message "'+Ae+'" to target pthread '+te.targetThread+", but that thread no longer exists!"),ze.currentProxiedOperationCallerThread=void 0;return}Ae==="processQueuedMainThreadWork"?tv():Ae==="spawnThread"?bf(te):Ae==="cleanupThread"?yf(te.thread):Ae==="killThread"?T1(te.thread):Ae==="cancelThread"?N1(te.thread):Ae==="loaded"?(N.loaded=!0,O&&O(N),N.runPthread&&(N.runPthread(),delete N.runPthread)):Ae==="print"?ee("Thread "+te.threadId+": "+te.text):Ae==="printErr"?Q("Thread "+te.threadId+": "+te.text):Ae==="alert"?alert("Thread "+te.threadId+": "+te.text):te.target==="setimmediate"?N.postMessage(te):Ae==="onAbort"?d.onAbort&&d.onAbort(te.arg):Q("worker sent an unknown command "+Ae),ze.currentProxiedOperationCallerThread=void 0},N.onerror=H=>{var te="worker sent an error!";throw Q(te+" "+H.filename+":"+H.lineno+": "+H.message),H},k&&(N.on("message",function(H){N.onmessage({data:H})}),N.on("error",function(H){N.onerror(H)}),N.on("detachedExit",function(){})),N.postMessage({cmd:"load",urlOrBlob:d.mainScriptUrlOrBlob||s,wasmMemory:$e,wasmModule:Tt})},allocateUnusedWorker:function(){var N=R("tfjs-backend-wasm-threaded-simd.worker.js");ze.unusedWorkers.push(new Worker(N))},getNewWorker:function(){return ze.unusedWorkers.length==0&&(ze.allocateUnusedWorker(),ze.loadWasmModuleToWorker(ze.unusedWorkers[0])),ze.unusedWorkers.pop()}};function R1(){var N=Df(),O=u()[N+44>>2],H=u()[N+48>>2],te=O-H;av(O,te),$f(O)}d.establishStackSpace=R1;function xf(N){if(S)return Ri(1,0,N);try{Af(N)}catch(O){E1(O)}}var Ni=[];function Su(N){var O=Ni[N];return O||(N>=Ni.length&&(Ni.length=N+1),Ni[N]=O=Us.get(N)),O}function _1(N,O){return Su(N)(O)}d.invokeEntryPoint=_1;function X4(){var N=new Error;if(!N.stack){try{throw new Error}catch(O){N=O}if(!N.stack)return"(no stack trace available)"}return N.stack.toString()}function D1(N,O,H){ze.tlsInitFunctions.push(N)}function K4(N,O){Us.set(N,O),Ni[N]=O}var Ei;k?Ei=()=>{var N=process.hrtime();return N[0]*1e3+N[1]/1e6}:S?Ei=()=>performance.now()-d.__performance_now_clock_drift:Ei=()=>performance.now();var $1=!0;function P1(N){return u()[ev()>>2]=N,N}function F1(N,O){var H;if(N===0)H=Date.now();else if((N===1||N===4)&&$1)H=Ei();else return P1(28),-1;return u()[O>>2]=H/1e3|0,u()[O+4>>2]=H%1e3*1e3*1e3|0,0}function O1(N,O){return F1(N,O)}function M1(N){nv(N,!w,1,!b),ze.threadInit()}function z1(N){S?postMessage({cmd:"cleanupThread",thread:N}):yf(N)}function bf(N){var O=ze.getNewWorker();if(!O)return 6;ze.runningWorkers.push(O);var H=ze.pthreads[N.pthread_ptr]={worker:O,threadInfoStruct:N.pthread_ptr};O.pthread=H;var te={cmd:"run",start_routine:N.startRoutine,arg:N.arg,threadInfoStruct:N.pthread_ptr};return O.runPthread=()=>{te.time=performance.now(),O.postMessage(te,N.transferList)},O.loaded&&(O.runPthread(),delete O.runPthread),0}function L1(N,O,H,te){if(typeof SharedArrayBuffer=="undefined")return Q("Current environment does not support SharedArrayBuffer, pthreads are not available!"),6;var Ae=[],ve=0;if(S&&(Ae.length===0||ve))return sv(687865856,N,O,H,te);if(ve)return ve;var Te={startRoutine:H,pthread_ptr:N,arg:te,transferList:Ae};return S?(Te.cmd="spawnThread",postMessage(Te,Ae),0):bf(Te)}function B1(){return 2097152}function W1(N,O){if(N==O)postMessage({cmd:"processQueuedMainThreadWork"});else if(S)postMessage({targetThread:N,cmd:"processThreadQueue"});else{var H=ze.pthreads[N],te=H&&H.worker;if(!te)return;te.postMessage({cmd:"processThreadQueue"})}return 1}function V1(){wu("")}function U1(){k||w||Y("Blocking on the main thread is very dangerous, see https://emscripten.org/docs/porting/pthreads.html#blocking-on-the-main-browser-thread")}function vf(){return 2147483648}function G1(N,O,H){o().copyWithin(N,O,O+H)}function H1(){return k?f_().cpus().length:navigator.hardwareConcurrency}function Ri(N,O){var H=arguments.length-2,te=arguments;return Iu(function(){for(var Ae=H,ve=_u(Ae*8),Te=ve>>3,Me=0;Me<H;Me++){var Lt=te[2+Me];p()[Te+Me]=Lt}return rv(N,Ae,ve,O)})}var Ud=[];function j1(N,O,H){Ud.length=O;for(var te=H>>3,Ae=0;Ae<O;Ae++)Ud[Ae]=p()[te+Ae];var ve=N<0,Te=ve?C1[-N-1]:dg[N];return Te.apply(null,Ud)}function q1(N){try{return $e.grow(N-jn.byteLength+65535>>>16),yr($e.buffer),1}catch(O){}}function X1(N){var O=o().length;if(N=N>>>0,N<=O)return!1;var H=vf();if(N>H)return!1;for(var te=1;te<=4;te*=2){var Ae=O*(1+.2/te);Ae=Math.min(Ae,N+100663296);var ve=Math.min(H,bu(Math.max(N,Ae),65536)),Te=q1(ve);if(Te)return!0}return!1}var Je={inEventHandler:0,removeAllEventListeners:function(){for(var N=Je.eventHandlers.length-1;N>=0;--N)Je._removeHandler(N);Je.eventHandlers=[],Je.deferredCalls=[]},registerRemoveEventListeners:function(){Je.removeEventListenersRegistered||(b1.push(Je.removeAllEventListeners),Je.removeEventListenersRegistered=!0)},deferredCalls:[],deferCall:function(N,O,H){function te(Te,Me){if(Te.length!=Me.length)return!1;for(var Lt in Te)if(Te[Lt]!=Me[Lt])return!1;return!0}for(var Ae in Je.deferredCalls){var ve=Je.deferredCalls[Ae];if(ve.targetFunction==N&&te(ve.argsList,H))return}Je.deferredCalls.push({targetFunction:N,precedence:O,argsList:H}),Je.deferredCalls.sort(function(Te,Me){return Te.precedence<Me.precedence})},removeDeferredCalls:function(N){for(var O=0;O<Je.deferredCalls.length;++O)Je.deferredCalls[O].targetFunction==N&&(Je.deferredCalls.splice(O,1),--O)},canPerformEventHandlerRequests:function(){return Je.inEventHandler&&Je.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!!Je.canPerformEventHandlerRequests())for(var N=0;N<Je.deferredCalls.length;++N){var O=Je.deferredCalls[N];Je.deferredCalls.splice(N,1),--N,O.targetFunction.apply(null,O.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(N,O){for(var H=0;H<Je.eventHandlers.length;++H)Je.eventHandlers[H].target==N&&(!O||O==Je.eventHandlers[H].eventTypeString)&&Je._removeHandler(H--)},_removeHandler:function(N){var O=Je.eventHandlers[N];O.target.removeEventListener(O.eventTypeString,O.eventListenerFunc,O.useCapture),Je.eventHandlers.splice(N,1)},registerOrRemoveHandler:function(N){var O=function(Ae){++Je.inEventHandler,Je.currentEventHandler=N,Je.runDeferredCalls(),N.handlerFunc(Ae),Je.runDeferredCalls(),--Je.inEventHandler};if(N.callbackfunc)N.eventListenerFunc=O,N.target.addEventListener(N.eventTypeString,O,N.useCapture),Je.eventHandlers.push(N),Je.registerRemoveEventListeners();else for(var H=0;H<Je.eventHandlers.length;++H)Je.eventHandlers[H].target==N.target&&Je.eventHandlers[H].eventTypeString==N.eventTypeString&&Je._removeHandler(H--)},queueEventHandlerOnThread_iiii:function(N,O,H,te,Ae){Iu(function(){var ve=_u(12);u()[ve>>2]=H,u()[ve+4>>2]=te,u()[ve+8>>2]=Ae,Yg(N,637534208,O,te,ve)})},getTargetThreadForEventCallback:function(N){switch(N){case 1:return 0;case 2:return ze.currentProxiedOperationCallerThread;default:return N}},getNodeNameForTarget:function(N){return N?N==window?"#window":N==screen?"#screen":N&&N.nodeName?N.nodeName:"":""},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function K1(N){var O=xu(N)+1,H=Zg(O);return aa(N,H,O),H}function Z1(N,O,H,te){Iu(function(){var Ae=_u(12),ve=0;O&&(ve=K1(O)),u()[Ae>>2]=ve,u()[Ae+4>>2]=H,u()[Ae+8>>2]=te,Yg(N,657457152,0,ve,Ae)})}function Y1(N,O,H,te){O=O?Hn(O):"",Z1(N,O,H,te)}function J1(N){return N>2?Hn(N):N}var Q1=[0,typeof document!="undefined"?document:0,typeof window!="undefined"?window:0];function eg(N){N=J1(N);var O=Q1[N]||(typeof document!="undefined"?document.querySelector(N):void 0);return O}function Gd(N){return eg(N)}function wf(N,O,H){var te=Gd(N);if(!te)return-4;if(te.canvasSharedPtr&&(u()[te.canvasSharedPtr>>2]=O,u()[te.canvasSharedPtr+4>>2]=H),te.offscreenCanvas||!te.controlTransferredOffscreen){te.offscreenCanvas&&(te=te.offscreenCanvas);var Ae=!1;if(te.GLctxObject&&te.GLctxObject.GLctx){var ve=te.GLctxObject.GLctx.getParameter(2978);Ae=ve[0]===0&&ve[1]===0&&ve[2]===te.width&&ve[3]===te.height}te.width=O,te.height=H,Ae&&te.GLctxObject.GLctx.viewport(0,0,O,H)}else if(te.canvasSharedPtr){var Te=u()[te.canvasSharedPtr+8>>2];return Y1(Te,N,O,H),1}else return-4;return 0}function kf(N,O,H){return S?Ri(2,1,N,O,H):wf(N,O,H)}function tg(N,O,H){var te=Gd(N);return te?wf(N,O,H):kf(N,O,H)}function ng(){throw"unwind"}function sg(N){var O=N.getExtension("ANGLE_instanced_arrays");if(O)return N.vertexAttribDivisor=function(H,te){O.vertexAttribDivisorANGLE(H,te)},N.drawArraysInstanced=function(H,te,Ae,ve){O.drawArraysInstancedANGLE(H,te,Ae,ve)},N.drawElementsInstanced=function(H,te,Ae,ve,Te){O.drawElementsInstancedANGLE(H,te,Ae,ve,Te)},1}function rg(N){var O=N.getExtension("OES_vertex_array_object");if(O)return N.createVertexArray=function(){return O.createVertexArrayOES()},N.deleteVertexArray=function(H){O.deleteVertexArrayOES(H)},N.bindVertexArray=function(H){O.bindVertexArrayOES(H)},N.isVertexArray=function(H){return O.isVertexArrayOES(H)},1}function ag(N){var O=N.getExtension("WEBGL_draw_buffers");if(O)return N.drawBuffers=function(H,te){O.drawBuffersWEBGL(H,te)},1}function og(N){return!!(N.multiDrawWebgl=N.getExtension("WEBGL_multi_draw"))}var zt={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},queries:[],stringCache:{},unpackAlignment:4,recordError:function(O){zt.lastError||(zt.lastError=O)},getNewId:function(N){for(var O=zt.counter++,H=N.length;H<O;H++)N[H]=null;return O},getSource:function(N,O,H,te){for(var Ae="",ve=0;ve<O;++ve){var Te=te?u()[te+ve*4>>2]:-1;Ae+=Hn(u()[H+ve*4>>2],Te<0?void 0:Te)}return Ae},createContext:function(N,O){N.getContextSafariWebGL2Fixed||(N.getContextSafariWebGL2Fixed=N.getContext,N.getContext=function(Ae,ve){var Te=N.getContextSafariWebGL2Fixed(Ae,ve);return Ae=="webgl"==Te instanceof WebGLRenderingContext?Te:null});var H=N.getContext("webgl",O);if(!H)return 0;var te=zt.registerContext(H,O);return te},registerContext:function(N,O){var H=Zg(8);u()[H+4>>2]=Df();var te={handle:H,attributes:O,version:O.majorVersion,GLctx:N};return N.canvas&&(N.canvas.GLctxObject=te),zt.contexts[H]=te,(typeof O.enableExtensionsByDefault=="undefined"||O.enableExtensionsByDefault)&&zt.initExtensions(te),H},makeContextCurrent:function(N){return zt.currentContext=zt.contexts[N],d.ctx=Tf=zt.currentContext&&zt.currentContext.GLctx,!(N&&!Tf)},getContext:function(N){return zt.contexts[N]},deleteContext:function(N){zt.currentContext===zt.contexts[N]&&(zt.currentContext=null),typeof Je=="object"&&Je.removeAllHandlersOnTarget(zt.contexts[N].GLctx.canvas),zt.contexts[N]&&zt.contexts[N].GLctx.canvas&&(zt.contexts[N].GLctx.canvas.GLctxObject=void 0),Q4(zt.contexts[N].handle),zt.contexts[N]=null},initExtensions:function(N){if(N||(N=zt.currentContext),!N.initExtensionsDone){N.initExtensionsDone=!0;var O=N.GLctx;sg(O),rg(O),ag(O),O.disjointTimerQueryExt=O.getExtension("EXT_disjoint_timer_query"),og(O);var H=O.getSupportedExtensions()||[];H.forEach(function(te){!te.includes("lose_context")&&!te.includes("debug")&&O.getExtension(te)})}}},ig=["default","low-power","high-performance"];function lg(N,O){var H=O>>2,te=u()[H+6],Ae={alpha:!!u()[H+0],depth:!!u()[H+1],stencil:!!u()[H+2],antialias:!!u()[H+3],premultipliedAlpha:!!u()[H+4],preserveDrawingBuffer:!!u()[H+5],powerPreference:ig[te],failIfMajorPerformanceCaveat:!!u()[H+7],majorVersion:u()[H+8],minorVersion:u()[H+9],enableExtensionsByDefault:u()[H+10],explicitSwapControl:u()[H+11],proxyContextToMainThread:u()[H+12],renderViaOffscreenBackBuffer:u()[H+13]},ve=Gd(N);if(!ve||Ae.explicitSwapControl)return 0;var Te=zt.createContext(ve,Ae);return Te}function ug(N,O){return lg(N,O)}var Cu={mappings:{},buffers:[null,[],[]],printChar:function(N,O){var H=Cu.buffers[N];O===0||O===10?((N===1?ee:Q)(Vs(H,0)),H.length=0):H.push(O)},varargs:void 0,get:function(){Cu.varargs+=4;var N=u()[Cu.varargs-4>>2];return N},getStr:function(N){var O=Hn(N);return O},get64:function(N,O){return N}};function If(N){return S?Ri(3,1,N):0}function Sf(N,O,H,te,Ae){if(S)return Ri(4,1,N,O,H,te,Ae)}function Cf(N,O,H,te){if(S)return Ri(5,1,N,O,H,te);for(var Ae=0,ve=0;ve<H;ve++){var Te=u()[O>>2],Me=u()[O+4>>2];O+=8;for(var Lt=0;Lt<Me;Lt++)Cu.printChar(N,o()[Te+Lt]);Ae+=Me}return u()[te>>2]=Ae,0}function cg(N){Be(N)}ze.init();var Tf,dg=[null,xf,kf,If,Sf,Cf],Z4=!1,Nf={__clock_gettime:O1,__emscripten_init_main_thread_js:M1,__emscripten_thread_cleanup:z1,__pthread_create_js:L1,_emscripten_default_pthread_stack_size:B1,_emscripten_notify_thread_queue:W1,abort:V1,emscripten_check_blocking_allowed:U1,emscripten_get_heap_max:vf,emscripten_get_now:Ei,emscripten_memcpy_big:G1,emscripten_num_logical_cores:H1,emscripten_receive_on_main_thread_js:j1,emscripten_resize_heap:X1,emscripten_set_canvas_element_size:tg,emscripten_unwind_to_js_event_loop:ng,emscripten_webgl_create_context:ug,exit:Af,fd_close:If,fd_seek:Sf,fd_write:Cf,memory:$e||d.wasmMemory,setTempRet0:cg},Y4=S1(),pg=d.___wasm_call_ctors=function(){return(pg=d.___wasm_call_ctors=d.asm.__wasm_call_ctors).apply(null,arguments)},hg=d._init=function(){return(hg=d._init=d.asm.init).apply(null,arguments)},fg=d._init_with_threads_count=function(){return(fg=d._init_with_threads_count=d.asm.init_with_threads_count).apply(null,arguments)},mg=d._get_threads_count=function(){return(mg=d._get_threads_count=d.asm.get_threads_count).apply(null,arguments)},gg=d._register_tensor=function(){return(gg=d._register_tensor=d.asm.register_tensor).apply(null,arguments)},yg=d._dispose_data=function(){return(yg=d._dispose_data=d.asm.dispose_data).apply(null,arguments)},Ag=d._dispose=function(){return(Ag=d._dispose=d.asm.dispose).apply(null,arguments)},xg=d._Abs=function(){return(xg=d._Abs=d.asm.Abs).apply(null,arguments)},bg=d._Add=function(){return(bg=d._Add=d.asm.Add).apply(null,arguments)},vg=d._AddN=function(){return(vg=d._AddN=d.asm.AddN).apply(null,arguments)},wg=d._All=function(){return(wg=d._All=d.asm.All).apply(null,arguments)},kg=d._Any=function(){return(kg=d._Any=d.asm.Any).apply(null,arguments)},Ig=d._ArgMax=function(){return(Ig=d._ArgMax=d.asm.ArgMax).apply(null,arguments)},Sg=d._AvgPool=function(){return(Sg=d._AvgPool=d.asm.AvgPool).apply(null,arguments)},Cg=d._BatchMatMul=function(){return(Cg=d._BatchMatMul=d.asm.BatchMatMul).apply(null,arguments)},Tg=d._Ceil=function(){return(Tg=d._Ceil=d.asm.Ceil).apply(null,arguments)},Ng=d._ClipByValue=function(){return(Ng=d._ClipByValue=d.asm.ClipByValue).apply(null,arguments)},Eg=d._Conv2D=function(){return(Eg=d._Conv2D=d.asm.Conv2D).apply(null,arguments)},Rg=d._Conv2DBackpropInput=function(){return(Rg=d._Conv2DBackpropInput=d.asm.Conv2DBackpropInput).apply(null,arguments)},_g=d._Cos=function(){return(_g=d._Cos=d.asm.Cos).apply(null,arguments)},Dg=d._Cosh=function(){return(Dg=d._Cosh=d.asm.Cosh).apply(null,arguments)},$g=d._CropAndResize=function(){return($g=d._CropAndResize=d.asm.CropAndResize).apply(null,arguments)},Pg=d._Cumprod=function(){return(Pg=d._Cumprod=d.asm.Cumprod).apply(null,arguments)},Fg=d._Cumsum=function(){return(Fg=d._Cumsum=d.asm.Cumsum).apply(null,arguments)},Og=d._DepthToSpace=function(){return(Og=d._DepthToSpace=d.asm.DepthToSpace).apply(null,arguments)},Mg=d._DepthwiseConv2dNative=function(){return(Mg=d._DepthwiseConv2dNative=d.asm.DepthwiseConv2dNative).apply(null,arguments)},zg=d._Elu=function(){return(zg=d._Elu=d.asm.Elu).apply(null,arguments)},Lg=d._Equal=function(){return(Lg=d._Equal=d.asm.Equal).apply(null,arguments)},Bg=d._Exp=function(){return(Bg=d._Exp=d.asm.Exp).apply(null,arguments)},Wg=d._FlipLeftRight=function(){return(Wg=d._FlipLeftRight=d.asm.FlipLeftRight).apply(null,arguments)},Vg=d._Floor=function(){return(Vg=d._Floor=d.asm.Floor).apply(null,arguments)},Ug=d._FloorDiv=function(){return(Ug=d._FloorDiv=d.asm.FloorDiv).apply(null,arguments)},Gg=d._FusedBatchNorm=function(){return(Gg=d._FusedBatchNorm=d.asm.FusedBatchNorm).apply(null,arguments)},Hg=d._FusedConv2D=function(){return(Hg=d._FusedConv2D=d.asm.FusedConv2D).apply(null,arguments)},Ef=d._FusedDepthwiseConv2D=function(){return(Ef=d._FusedDepthwiseConv2D=d.asm.FusedDepthwiseConv2D).apply(null,arguments)},Rf=d._Gather=function(){return(Rf=d._Gather=d.asm.Gather).apply(null,arguments)},Hd=d._GatherNd=function(){return(Hd=d._GatherNd=d.asm.GatherNd).apply(null,arguments)},jg=d._Greater=function(){return(jg=d._Greater=d.asm.Greater).apply(null,arguments)},qg=d._GreaterEqual=function(){return(qg=d._GreaterEqual=d.asm.GreaterEqual).apply(null,arguments)},Tu=d._LeakyRelu=function(){return(Tu=d._LeakyRelu=d.asm.LeakyRelu).apply(null,arguments)},jd=d._Less=function(){return(jd=d._Less=d.asm.Less).apply(null,arguments)},qd=d._LessEqual=function(){return(qd=d._LessEqual=d.asm.LessEqual).apply(null,arguments)},J4=d._Log=function(){return(J4=d._Log=d.asm.Log).apply(null,arguments)},Nu=d._LogicalAnd=function(){return(Nu=d._LogicalAnd=d.asm.LogicalAnd).apply(null,arguments)},Eu=d._LogicalNot=function(){return(Eu=d._LogicalNot=d.asm.LogicalNot).apply(null,arguments)},Xg=d._LogicalOr=function(){return(Xg=d._LogicalOr=d.asm.LogicalOr).apply(null,arguments)},X=d._LogicalXor=function(){return(X=d._LogicalXor=d.asm.LogicalXor).apply(null,arguments)},se=d._Max=function(){return(se=d._Max=d.asm.Max).apply(null,arguments)},xe=d._MaxPool=function(){return(xe=d._MaxPool=d.asm.MaxPool).apply(null,arguments)},De=d._Maximum=function(){return(De=d._Maximum=d.asm.Maximum).apply(null,arguments)},ht=d._Mean=function(){return(ht=d._Mean=d.asm.Mean).apply(null,arguments)},yt=d._Min=function(){return(yt=d._Min=d.asm.Min).apply(null,arguments)},et=d._Minimum=function(){return(et=d._Minimum=d.asm.Minimum).apply(null,arguments)},Ze=d._MirrorPad=function(){return(Ze=d._MirrorPad=d.asm.MirrorPad).apply(null,arguments)},en=d._Multiply=function(){return(en=d._Multiply=d.asm.Multiply).apply(null,arguments)},xr=d._Neg=function(){return(xr=d._Neg=d.asm.Neg).apply(null,arguments)},br=d._NonMaxSuppressionV3=function(){return(br=d._NonMaxSuppressionV3=d.asm.NonMaxSuppressionV3).apply(null,arguments)},Ru=d._NonMaxSuppressionV4=function(){return(Ru=d._NonMaxSuppressionV4=d.asm.NonMaxSuppressionV4).apply(null,arguments)},_i=d._NonMaxSuppressionV5=function(){return(_i=d._NonMaxSuppressionV5=d.asm.NonMaxSuppressionV5).apply(null,arguments)},Kg=d._NotEqual=function(){return(Kg=d._NotEqual=d.asm.NotEqual).apply(null,arguments)},Kn=d._OneHot=function(){return(Kn=d._OneHot=d.asm.OneHot).apply(null,arguments)},La=d._PadV2=function(){return(La=d._PadV2=d.asm.PadV2).apply(null,arguments)},_f=d._Pow=function(){return(_f=d._Pow=d.asm.Pow).apply(null,arguments)},JE=d._Prelu=function(){return(JE=d._Prelu=d.asm.Prelu).apply(null,arguments)},QE=d._Prod=function(){return(QE=d._Prod=d.asm.Prod).apply(null,arguments)},eR=d._RealDiv=function(){return(eR=d._RealDiv=d.asm.RealDiv).apply(null,arguments)},tR=d._Relu=function(){return(tR=d._Relu=d.asm.Relu).apply(null,arguments)},nR=d._Relu6=function(){return(nR=d._Relu6=d.asm.Relu6).apply(null,arguments)},sR=d._ResizeBilinear=function(){return(sR=d._ResizeBilinear=d.asm.ResizeBilinear).apply(null,arguments)},rR=d._ResizeNearestNeighbor=function(){return(rR=d._ResizeNearestNeighbor=d.asm.ResizeNearestNeighbor).apply(null,arguments)},aR=d._Reverse=function(){return(aR=d._Reverse=d.asm.Reverse).apply(null,arguments)},oR=d._RotateWithOffset=function(){return(oR=d._RotateWithOffset=d.asm.RotateWithOffset).apply(null,arguments)},iR=d._Round=function(){return(iR=d._Round=d.asm.Round).apply(null,arguments)},lR=d._Rsqrt=function(){return(lR=d._Rsqrt=d.asm.Rsqrt).apply(null,arguments)},uR=d._ScatterNd=function(){return(uR=d._ScatterNd=d.asm.ScatterNd).apply(null,arguments)},cR=d._SelectV2=function(){return(cR=d._SelectV2=d.asm.SelectV2).apply(null,arguments)},dR=d._Sigmoid=function(){return(dR=d._Sigmoid=d.asm.Sigmoid).apply(null,arguments)},pR=d._Sin=function(){return(pR=d._Sin=d.asm.Sin).apply(null,arguments)},hR=d._Softmax=function(){return(hR=d._Softmax=d.asm.Softmax).apply(null,arguments)},fR=d._SparseFillEmptyRows=function(){return(fR=d._SparseFillEmptyRows=d.asm.SparseFillEmptyRows).apply(null,arguments)},mR=d._SparseReshape=function(){return(mR=d._SparseReshape=d.asm.SparseReshape).apply(null,arguments)},gR=d._SparseSegmentReduction=function(){return(gR=d._SparseSegmentReduction=d.asm.SparseSegmentReduction).apply(null,arguments)},yR=d._Sqrt=function(){return(yR=d._Sqrt=d.asm.Sqrt).apply(null,arguments)},AR=d._Square=function(){return(AR=d._Square=d.asm.Square).apply(null,arguments)},xR=d._SquaredDifference=function(){return(xR=d._SquaredDifference=d.asm.SquaredDifference).apply(null,arguments)},bR=d._Step=function(){return(bR=d._Step=d.asm.Step).apply(null,arguments)},vR=d._StridedSlice=function(){return(vR=d._StridedSlice=d.asm.StridedSlice).apply(null,arguments)},wR=d._Sub=function(){return(wR=d._Sub=d.asm.Sub).apply(null,arguments)},kR=d._Sum=function(){return(kR=d._Sum=d.asm.Sum).apply(null,arguments)},IR=d._Tan=function(){return(IR=d._Tan=d.asm.Tan).apply(null,arguments)},SR=d._Tanh=function(){return(SR=d._Tanh=d.asm.Tanh).apply(null,arguments)},CR=d._Tile=function(){return(CR=d._Tile=d.asm.Tile).apply(null,arguments)},TR=d._TopK=function(){return(TR=d._TopK=d.asm.TopK).apply(null,arguments)},NR=d._Transform=function(){return(NR=d._Transform=d.asm.Transform).apply(null,arguments)},ER=d._Transpose=function(){return(ER=d._Transpose=d.asm.Transpose).apply(null,arguments)},RR=d.__FusedMatMul=function(){return(RR=d.__FusedMatMul=d.asm._FusedMatMul).apply(null,arguments)},Zg=d._malloc=function(){return(Zg=d._malloc=d.asm.malloc).apply(null,arguments)},Q4=d._free=function(){return(Q4=d._free=d.asm.free).apply(null,arguments)},_R=d._emscripten_tls_init=function(){return(_R=d._emscripten_tls_init=d.asm.emscripten_tls_init).apply(null,arguments)},ev=d.___errno_location=function(){return(ev=d.___errno_location=d.asm.__errno_location).apply(null,arguments)},Df=d._pthread_self=function(){return(Df=d._pthread_self=d.asm.pthread_self).apply(null,arguments)},tv=d._emscripten_main_thread_process_queued_calls=function(){return(tv=d._emscripten_main_thread_process_queued_calls=d.asm.emscripten_main_thread_process_queued_calls).apply(null,arguments)},DR=d.__emscripten_thread_crashed=function(){return(DR=d.__emscripten_thread_crashed=d.asm._emscripten_thread_crashed).apply(null,arguments)},nv=d.__emscripten_thread_init=function(){return(nv=d.__emscripten_thread_init=d.asm._emscripten_thread_init).apply(null,arguments)},$R=d._emscripten_current_thread_process_queued_calls=function(){return($R=d._emscripten_current_thread_process_queued_calls=d.asm.emscripten_current_thread_process_queued_calls).apply(null,arguments)},PR=d._emscripten_main_browser_thread_id=function(){return(PR=d._emscripten_main_browser_thread_id=d.asm.emscripten_main_browser_thread_id).apply(null,arguments)},FR=d._emscripten_sync_run_in_main_thread_2=function(){return(FR=d._emscripten_sync_run_in_main_thread_2=d.asm.emscripten_sync_run_in_main_thread_2).apply(null,arguments)},sv=d._emscripten_sync_run_in_main_thread_4=function(){return(sv=d._emscripten_sync_run_in_main_thread_4=d.asm.emscripten_sync_run_in_main_thread_4).apply(null,arguments)},rv=d._emscripten_run_in_main_runtime_thread_js=function(){return(rv=d._emscripten_run_in_main_runtime_thread_js=d.asm.emscripten_run_in_main_runtime_thread_js).apply(null,arguments)},Yg=d._emscripten_dispatch_to_thread_=function(){return(Yg=d._emscripten_dispatch_to_thread_=d.asm.emscripten_dispatch_to_thread_).apply(null,arguments)},Jg=d.__emscripten_thread_free_data=function(){return(Jg=d.__emscripten_thread_free_data=d.asm._emscripten_thread_free_data).apply(null,arguments)},OR=d.__emscripten_thread_exit=function(){return(OR=d.__emscripten_thread_exit=d.asm._emscripten_thread_exit).apply(null,arguments)},MR=d._memalign=function(){return(MR=d._memalign=d.asm.memalign).apply(null,arguments)},av=d._emscripten_stack_set_limits=function(){return(av=d._emscripten_stack_set_limits=d.asm.emscripten_stack_set_limits).apply(null,arguments)},Qg=d.stackSave=function(){return(Qg=d.stackSave=d.asm.stackSave).apply(null,arguments)},$f=d.stackRestore=function(){return($f=d.stackRestore=d.asm.stackRestore).apply(null,arguments)},_u=d.stackAlloc=function(){return(_u=d.stackAlloc=d.asm.stackAlloc).apply(null,arguments)},zR=d.dynCall_iijjiiii=function(){return(zR=d.dynCall_iijjiiii=d.asm.dynCall_iijjiiii).apply(null,arguments)},LR=d.dynCall_jiji=function(){return(LR=d.dynCall_jiji=d.asm.dynCall_jiji).apply(null,arguments)},ov=d.__emscripten_allow_main_runtime_queued_calls=21672;d.cwrap=Gn,d.keepRuntimeAlive=Ti,d.PThread=ze,d.PThread=ze,d.wasmMemory=$e,d.ExitStatus=Xd;var Pf;function Xd(N){this.name="ExitStatus",this.message="Program terminated with exit("+N+")",this.status=N}Ar=function N(){Pf||e3(),Pf||(Ar=N)};function e3(N){if(N=N||y,za>0)return;if(S){h(d),Ld(),postMessage({cmd:"loaded"});return}if(qn(),za>0)return;function O(){Pf||(Pf=!0,d.calledRun=!0,!It&&(Ld(),h(d),d.onRuntimeInitialized&&d.onRuntimeInitialized(),k1()))}d.setStatus?(d.setStatus("Running..."),setTimeout(function(){setTimeout(function(){d.setStatus("")},1),O()},1)):O()}d.run=e3;function BR(N,O){if(Un=N,!O&&S)throw xf(N),"unwind";Ti()||w1(),WR(N)}function WR(N){Un=N,Ti()||(ze.terminateAllThreads(),d.onExit&&d.onExit(N),It=!0),A(N,new Xd(N))}if(d.preInit)for(typeof d.preInit=="function"&&(d.preInit=[d.preInit]);d.preInit.length>0;)d.preInit.pop()();e3();var Ff;m&&(Ff={uncaughtException:process.listeners("uncaughtException").filter(function(N){return!m.uncaughtException.indexOf(N)>-1}),unhandledRejection:process.listeners("unhandledRejection").filter(function(N){return!m.unhandledRejection.indexOf(N)>-1})});var Of;if(typeof WasmBackendModule!="undefined")Of=WasmBackendModule;else if(typeof r!="undefined")Of=r;else throw new Error("Could not find wasm module in post.js");if(Ff){var VR=Of._dispose;Of._dispose=function(){VR(),Ff.uncaughtException.forEach(function(N){process.removeListener("uncaughtException",N)}),Ff.unhandledRejection.forEach(function(N){process.removeListener("unhandledRejection",N)})}}return r.ready}})();typeof e=="object"&&typeof t=="object"?t.exports=n:typeof define=="function"&&define.amd?define([],function(){return n}):typeof e=="object"&&(e.WasmBackendModuleThreadedSimd=n)}}),g_=ln({"node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.worker.js"(e,t){t.exports.wasmWorkerContents=`"use strict";var Module={};var ENVIRONMENT_IS_NODE=typeof process==="object"&&typeof process.versions==="object"&&typeof process.versions.node==="string";if(ENVIRONMENT_IS_NODE){var nodeWorkerThreads=require("worker_threads");var parentPort=nodeWorkerThreads.parentPort;parentPort.on("message",function(data){onmessage({data:data})});var fs=require("fs");Object.assign(global,{self:global,require:require,Module:Module,location:{href:__filename},Worker:nodeWorkerThreads.Worker,importScripts:function(f){(0,eval)(fs.readFileSync(f,"utf8"))},postMessage:function(msg){parentPort.postMessage(msg)},performance:global.performance||{now:function(){return Date.now()}}})}function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(" ");if(ENVIRONMENT_IS_NODE){fs.writeSync(2,text+"
-");return}console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(" ");postMessage({cmd:"alert",text:text,threadId:Module["_pthread_self"]()})}var err=threadPrintErr;self.alert=threadAlert;Module["instantiateWasm"]=((info,receiveInstance)=>{var instance=new WebAssembly.Instance(Module["wasmModule"],info);receiveInstance(instance);Module["wasmModule"]=null;return instance.exports});self.onmessage=(e=>{try{if(e.data.cmd==="load"){Module["wasmModule"]=e.data.wasmModule;Module["wasmMemory"]=e.data.wasmMemory;Module["buffer"]=Module["wasmMemory"].buffer;Module["ENVIRONMENT_IS_PTHREAD"]=true;if(typeof e.data.urlOrBlob==="string"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module).then(function(instance){Module=instance})}else if(e.data.cmd==="run"){Module["__performance_now_clock_drift"]=performance.now()-e.data.time;Module["__emscripten_thread_init"](e.data.threadInfoStruct,0,0,1);Module["establishStackSpace"]();Module["PThread"].receiveObjectTransfer(e.data);Module["PThread"].threadInit();try{var result=Module["invokeEntryPoint"](e.data.start_routine,e.data.arg);if(Module["keepRuntimeAlive"]()){Module["PThread"].setExitStatus(result)}else{Module["__emscripten_thread_exit"](result)}}catch(ex){if(ex!="unwind"){if(ex instanceof Module["ExitStatus"]){if(Module["keepRuntimeAlive"]()){}else{Module["__emscripten_thread_exit"](ex.status)}}else{throw ex}}}}else if(e.data.cmd==="cancel"){if(Module["_pthread_self"]()){Module["__emscripten_thread_exit"](-1)}}else if(e.data.target==="setimmediate"){}else if(e.data.cmd==="processThreadQueue"){if(Module["_pthread_self"]()){Module["_emscripten_current_thread_process_queued_calls"]()}}else if(e.data.cmd==="processProxyingQueue"){if(Module["_pthread_self"]()){Module["_emscripten_proxy_execute_queue"](e.data.queue)}}else{err("worker.js received unknown command "+e.data.cmd);err(e.data)}}catch(ex){err("worker.js onmessage() captured an uncaught exception: "+ex);if(ex&&ex.stack)err(ex.stack);if(Module["__emscripten_thread_crashed"]){Module["__emscripten_thread_crashed"]()}throw ex}});`}}),y_=ln({"node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm.js"(e,t){var n=(()=>{var s=typeof document!="undefined"&&document.currentScript?document.currentScript.src:void 0;return typeof __filename!="undefined"&&(s=s||__filename),function(r){r=r||{};var a=typeof r!="undefined"?r:{},o,i;a.ready=new Promise(function(X,se){o=X,i=se});var l;typeof process!="undefined"&&process.listeners&&(l={uncaughtException:process.listeners("uncaughtException"),unhandledRejection:process.listeners("unhandledRejection")});var u=Object.assign({},a),c=[],p="./this.program",d=(X,se)=>{throw se},h=typeof window=="object",f=typeof importScripts=="function",m=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string",g="";function y(X){return a.locateFile?a.locateFile(X,g):g+X}var x,A,b,w;function k(X){if(X instanceof jd)return;_("exiting due to exception: "+X)}var S,E,R;m?(f?g=um().dirname(g)+"/":g=__dirname+"/",R=()=>{E||(S=xy(),E=um())},x=function(se,xe){return R(),se=E.normalize(se),S.readFileSync(se,xe?void 0:"utf8")},b=X=>{var se=x(X,!0);return se.buffer||(se=new Uint8Array(se)),se},A=(X,se,xe)=>{R(),X=E.normalize(X),S.readFile(X,function(De,ht){De?xe(De):se(ht.buffer)})},process.argv.length>1&&(p=process.argv[1].replace(/\\/g,"/")),c=process.argv.slice(2),process.on("uncaughtException",function(X){if(!(X instanceof jd))throw X}),process.on("unhandledRejection",function(X){throw X}),d=(X,se)=>{if(zd())throw process.exitCode=X,se;k(se),process.exit(X)},a.inspect=function(){return"[Emscripten Module object]"}):(h||f)&&(f?g=self.location.href:typeof document!="undefined"&&document.currentScript&&(g=document.currentScript.src),s&&(g=s),g.indexOf("blob:")!==0?g=g.substr(0,g.replace(/[?#].*/,"").lastIndexOf("/")+1):g="",x=X=>{var se=new XMLHttpRequest;return se.open("GET",X,!1),se.send(null),se.responseText},f&&(b=X=>{var se=new XMLHttpRequest;return se.open("GET",X,!1),se.responseType="arraybuffer",se.send(null),new Uint8Array(se.response)}),A=(X,se,xe)=>{var De=new XMLHttpRequest;De.open("GET",X,!0),De.responseType="arraybuffer",De.onload=()=>{if(De.status==200||De.status==0&&De.response){se(De.response);return}xe()},De.onerror=xe,De.send(null)},w=X=>document.title=X);var P=a.print||console.log.bind(console),_=a.printErr||console.warn.bind(console);Object.assign(a,u),u=null,a.arguments&&(c=a.arguments),a.thisProgram&&(p=a.thisProgram),a.quit&&(d=a.quit);var $=4;function T(X){T.shown||(T.shown={}),T.shown[X]||(T.shown[X]=1,_(X))}function F(X,se){if(typeof WebAssembly.Function=="function"){for(var xe={i:"i32",j:"i64",f:"f32",d:"f64"},De={parameters:[],results:se[0]=="v"?[]:[xe[se[0]]]},ht=1;ht<se.length;++ht)De.parameters.push(xe[se[ht]]);return new WebAssembly.Function(De,X)}var yt=[1,0,1,96],et=se.slice(0,1),Ze=se.slice(1),en={i:127,j:126,f:125,d:124};yt.push(Ze.length);for(var ht=0;ht<Ze.length;++ht)yt.push(en[Ze[ht]]);et=="v"?yt.push(0):yt=yt.concat([1,en[et]]),yt[1]=yt.length-2;var xr=new Uint8Array([0,97,115,109,1,0,0,0].concat(yt,[2,7,1,1,101,1,102,0,0,7,5,1,1,102,0,0])),br=new WebAssembly.Module(xr),Ru=new WebAssembly.Instance(br,{e:{f:X}}),_i=Ru.exports.f;return _i}var G=[],q;function z(){if(G.length)return G.pop();try{Oa.grow(1)}catch(X){throw X instanceof RangeError?"Unable to grow wasm table. Set ALLOW_TABLE_GROWTH.":X}return Oa.length-1}function K(X,se){for(var xe=X;xe<X+se;xe++){var De=Wd(xe);De&&q.set(De,xe)}}var B=0,ee=X=>{B=X},Q;a.wasmBinary&&(Q=a.wasmBinary);var oe=a.noExitRuntime||!0;typeof WebAssembly!="object"&&Ci("no native wasm support detected");var Y,ae=!1,le;function ye(X,se){X||Ci(se)}function we(X){var se=a["_"+X];return se}function Re(X,se,xe,De,ht){var yt={string:function(Kn){var La=0;if(Kn!=null&&Kn!==0){var _f=(Kn.length<<2)+1;La=Hd(_f),At(Kn,La,_f)}return La},array:function(Kn){var La=Hd(Kn.length);return It(Kn,La),La}};function et(Kn){return se==="string"?dt(Kn):se==="boolean"?Boolean(Kn):Kn}var Ze=we(X),en=[],xr=0;if(De)for(var br=0;br<De.length;br++){var Ru=yt[xe[br]];Ru?(xr===0&&(xr=Ef()),en[br]=Ru(De[br])):en[br]=De[br]}var _i=Ze.apply(null,en);function Kg(Kn){return xr!==0&&Rf(xr),et(Kn)}return _i=Kg(_i),_i}function _e(X,se,xe,De){xe=xe||[];var ht=xe.every(function(et){return et==="number"}),yt=se!=="string";return yt&&ht&&!De?we(X):function(){return Re(X,se,xe,arguments,De)}}var Be=1,Ge=typeof TextDecoder!="undefined"?new TextDecoder("utf8"):void 0;function ot(X,se,xe){for(var De=se+xe,ht=se;X[ht]&&!(ht>=De);)++ht;if(ht-se>16&&X.subarray&&Ge)return Ge.decode(X.subarray(se,ht));for(var yt="";se<ht;){var et=X[se++];if(!(et&128)){yt+=String.fromCharCode(et);continue}var Ze=X[se++]&63;if((et&224)==192){yt+=String.fromCharCode((et&31)<<6|Ze);continue}var en=X[se++]&63;if((et&240)==224?et=(et&15)<<12|Ze<<6|en:et=(et&7)<<18|Ze<<12|en<<6|X[se++]&63,et<65536)yt+=String.fromCharCode(et);else{var xr=et-65536;yt+=String.fromCharCode(55296|xr>>10,56320|xr&1023)}}return yt}function dt(X,se){return X?ot(Gn,X,se):""}function pt(X,se,xe,De){if(!(De>0))return 0;for(var ht=xe,yt=xe+De-1,et=0;et<X.length;++et){var Ze=X.charCodeAt(et);if(Ze>=55296&&Ze<=57343){var en=X.charCodeAt(++et);Ze=65536+((Ze&1023)<<10)|en&1023}if(Ze<=127){if(xe>=yt)break;se[xe++]=Ze}else if(Ze<=2047){if(xe+1>=yt)break;se[xe++]=192|Ze>>6,se[xe++]=128|Ze&63}else if(Ze<=65535){if(xe+2>=yt)break;se[xe++]=224|Ze>>12,se[xe++]=128|Ze>>6&63,se[xe++]=128|Ze&63}else{if(xe+3>=yt)break;se[xe++]=240|Ze>>18,se[xe++]=128|Ze>>12&63,se[xe++]=128|Ze>>6&63,se[xe++]=128|Ze&63}}return se[xe]=0,xe-ht}function At(X,se,xe){return pt(X,Gn,se,xe)}function $e(X){for(var se=0,xe=0;xe<X.length;++xe){var De=X.charCodeAt(xe);De>=55296&&De<=57343&&(De=65536+((De&1023)<<10)|X.charCodeAt(++xe)&1023),De<=127?++se:De<=2047?se+=2:De<=65535?se+=3:se+=4}return se}var Tt=typeof TextDecoder!="undefined"?new TextDecoder("utf-16le"):void 0;function It(X,se){pn.set(X,se)}function Un(X,se,xe){for(var De=0;De<X.length;++De)pn[se++>>0]=X.charCodeAt(De);xe||(pn[se>>0]=0)}function Qt(X,se){return X%se>0&&(X+=se-X%se),X}var bs,pn,Gn,vs,ws,$n,Vs,Hn,ra;function aa(X){bs=X,a.HEAP8=pn=new Int8Array(X),a.HEAP16=vs=new Int16Array(X),a.HEAP32=$n=new Int32Array(X),a.HEAPU8=Gn=new Uint8Array(X),a.HEAPU16=ws=new Uint16Array(X),a.HEAPU32=Vs=new Uint32Array(X),a.HEAPF32=Hn=new Float32Array(X),a.HEAPF64=ra=new Float64Array(X)}var xu=a.INITIAL_MEMORY||16777216,Oa,oa=[],Md=[],bu=[],jn=!1,sf=!1,rf=0;function zd(){return oe||rf>0}function af(){if(a.preRun)for(typeof a.preRun=="function"&&(a.preRun=[a.preRun]);a.preRun.length;)uf(a.preRun.shift());Bd(oa)}function of(){jn=!0,Bd(Md)}function W4(){sf=!0}function lf(){if(a.postRun)for(typeof a.postRun=="function"&&(a.postRun=[a.postRun]);a.postRun.length;)cf(a.postRun.shift());Bd(bu)}function uf(X){oa.unshift(X)}function yr(X){Md.unshift(X)}function cf(X){bu.unshift(X)}var Us=0,vu=null,Ma=null;function b1(X){Us++,a.monitorRunDependencies&&a.monitorRunDependencies(Us)}function df(X){if(Us--,a.monitorRunDependencies&&a.monitorRunDependencies(Us),Us==0&&(vu!==null&&(clearInterval(vu),vu=null),Ma)){var se=Ma;Ma=null,se()}}a.preloadedImages={},a.preloadedAudios={};function Ci(X){a.onAbort&&a.onAbort(X),X="Aborted("+X+")",_(X),ae=!0,le=1,X+=". Build with -s ASSERTIONS=1 for more info.";var se=new WebAssembly.RuntimeError(X);throw i(se),se}var v1="data:application/octet-stream;base64,";function pf(X){return X.startsWith(v1)}function Ti(X){return X.startsWith("file://")}var qn;qn="tfjs-backend-wasm.wasm",pf(qn)||(qn=y(qn));function Ld(X){try{if(X==qn&&Q)return new Uint8Array(Q);if(b)return b(X);throw"both async and sync fetching of the wasm failed"}catch(se){Ci(se)}}function w1(){if(!Q&&(h||f)){if(typeof fetch=="function"&&!Ti(qn))return fetch(qn,{credentials:"same-origin"}).then(function(X){if(!X.ok)throw"failed to load wasm binary file at '"+qn+"'";return X.arrayBuffer()}).catch(function(){return Ld(qn)});if(A)return new Promise(function(X,se){A(qn,function(xe){X(new Uint8Array(xe))},se)})}return Promise.resolve().then(function(){return Ld(qn)})}function k1(){var X={env:Iu,wasi_snapshot_preview1:Iu};function se(et,Ze){var en=et.exports;a.asm=en,Y=a.asm.memory,aa(Y.buffer),Oa=a.asm.__indirect_function_table,yr(a.asm.__wasm_call_ctors),df("wasm-instantiate")}b1("wasm-instantiate");function xe(et){se(et.instance)}function De(et){return w1().then(function(Ze){return WebAssembly.instantiate(Ze,X)}).then(function(Ze){return Ze}).then(et,function(Ze){_("failed to asynchronously prepare wasm: "+Ze),Ci(Ze)})}function ht(){return!Q&&typeof WebAssembly.instantiateStreaming=="function"&&!pf(qn)&&!Ti(qn)&&typeof fetch=="function"?fetch(qn,{credentials:"same-origin"}).then(function(et){var Ze=WebAssembly.instantiateStreaming(et,X);return Ze.then(xe,function(en){return _("wasm streaming compile failed: "+en),_("falling back to ArrayBuffer instantiation"),De(xe)})}):De(xe)}if(a.instantiateWasm)try{var yt=a.instantiateWasm(X,se);return yt}catch(et){return _("Module.instantiateWasm callback failed with error: "+et),!1}return ht().catch(i),{}}var V4,U4;function Bd(X){for(;X.length>0;){var se=X.shift();if(typeof se=="function"){se(a);continue}var xe=se.func;typeof xe=="number"?se.arg===void 0?Wd(xe)():Wd(xe)(se.arg):xe(se.arg===void 0?null:se.arg)}}function za(X){return X}function hf(X){var se=/\b_Z[\w\d_]+/g;return X.replace(se,function(xe){var De=xe;return xe===De?xe:De+" ["+xe+"]"})}var Ar=[];function Wd(X){var se=Ar[X];return se||(X>=Ar.length&&(Ar.length=X+1),Ar[X]=se=Oa.get(X)),se}function G4(){var X=new Error;if(!X.stack){try{throw new Error}catch(se){X=se}if(!X.stack)return"(no stack trace available)"}return X.stack.toString()}function wu(X,se){Oa.set(X,se),Ar[X]=se}function I1(){Ci("")}function Vd(){return 2147483648}function ff(X,se,xe){Gn.copyWithin(X,se,se+xe)}function Xn(X){try{return Y.grow(X-bs.byteLength+65535>>>16),aa(Y.buffer),1}catch(se){}}function mf(X){var se=Gn.length;X=X>>>0;var xe=Vd();if(X>xe)return!1;for(var De=1;De<=4;De*=2){var ht=se*(1+.2/De);ht=Math.min(ht,X+100663296);var yt=Math.min(xe,Qt(Math.max(X,ht),65536)),et=Xn(yt);if(et)return!0}return!1}var ku={mappings:{},buffers:[null,[],[]],printChar:function(X,se){var xe=ku.buffers[X];se===0||se===10?((X===1?P:_)(ot(xe,0)),xe.length=0):xe.push(se)},varargs:void 0,get:function(){ku.varargs+=4;var X=$n[ku.varargs-4>>2];return X},getStr:function(X){var se=dt(X);return se},get64:function(X,se){return X}};function S1(X){return 0}function H4(X,se,xe,De,ht){}function j4(X,se,xe,De){for(var ht=0,yt=0;yt<xe;yt++){var et=$n[se>>2],Ze=$n[se+4>>2];se+=8;for(var en=0;en<Ze;en++)ku.printChar(X,Gn[et+en]);ht+=Ze}return $n[De>>2]=ht,0}function C1(X){ee(X)}var gf=!1,Iu={abort:I1,emscripten_get_heap_max:Vd,emscripten_memcpy_big:ff,emscripten_resize_heap:mf,fd_close:S1,fd_seek:H4,fd_write:j4,setTempRet0:C1},YE=k1(),q4=a.___wasm_call_ctors=function(){return(q4=a.___wasm_call_ctors=a.asm.__wasm_call_ctors).apply(null,arguments)},T1=a._init=function(){return(T1=a._init=a.asm.init).apply(null,arguments)},N1=a._init_with_threads_count=function(){return(N1=a._init_with_threads_count=a.asm.init_with_threads_count).apply(null,arguments)},yf=a._get_threads_count=function(){return(yf=a._get_threads_count=a.asm.get_threads_count).apply(null,arguments)},Af=a._register_tensor=function(){return(Af=a._register_tensor=a.asm.register_tensor).apply(null,arguments)},E1=a._dispose_data=function(){return(E1=a._dispose_data=a.asm.dispose_data).apply(null,arguments)},ze=a._dispose=function(){return(ze=a._dispose=a.asm.dispose).apply(null,arguments)},R1=a._Abs=function(){return(R1=a._Abs=a.asm.Abs).apply(null,arguments)},xf=a._Add=function(){return(xf=a._Add=a.asm.Add).apply(null,arguments)},Ni=a._AddN=function(){return(Ni=a._AddN=a.asm.AddN).apply(null,arguments)},Su=a._All=function(){return(Su=a._All=a.asm.All).apply(null,arguments)},_1=a._Any=function(){return(_1=a._Any=a.asm.Any).apply(null,arguments)},X4=a._ArgMax=function(){return(X4=a._ArgMax=a.asm.ArgMax).apply(null,arguments)},D1=a._AvgPool=function(){return(D1=a._AvgPool=a.asm.AvgPool).apply(null,arguments)},K4=a._BatchMatMul=function(){return(K4=a._BatchMatMul=a.asm.BatchMatMul).apply(null,arguments)},Ei=a._Ceil=function(){return(Ei=a._Ceil=a.asm.Ceil).apply(null,arguments)},$1=a._ClipByValue=function(){return($1=a._ClipByValue=a.asm.ClipByValue).apply(null,arguments)},P1=a._Conv2D=function(){return(P1=a._Conv2D=a.asm.Conv2D).apply(null,arguments)},F1=a._Conv2DBackpropInput=function(){return(F1=a._Conv2DBackpropInput=a.asm.Conv2DBackpropInput).apply(null,arguments)},O1=a._Cos=function(){return(O1=a._Cos=a.asm.Cos).apply(null,arguments)},M1=a._Cosh=function(){return(M1=a._Cosh=a.asm.Cosh).apply(null,arguments)},z1=a._CropAndResize=function(){return(z1=a._CropAndResize=a.asm.CropAndResize).apply(null,arguments)},bf=a._Cumprod=function(){return(bf=a._Cumprod=a.asm.Cumprod).apply(null,arguments)},L1=a._Cumsum=function(){return(L1=a._Cumsum=a.asm.Cumsum).apply(null,arguments)},B1=a._DepthToSpace=function(){return(B1=a._DepthToSpace=a.asm.DepthToSpace).apply(null,arguments)},W1=a._DepthwiseConv2dNative=function(){return(W1=a._DepthwiseConv2dNative=a.asm.DepthwiseConv2dNative).apply(null,arguments)},V1=a._Elu=function(){return(V1=a._Elu=a.asm.Elu).apply(null,arguments)},U1=a._Equal=function(){return(U1=a._Equal=a.asm.Equal).apply(null,arguments)},vf=a._Exp=function(){return(vf=a._Exp=a.asm.Exp).apply(null,arguments)},G1=a._FlipLeftRight=function(){return(G1=a._FlipLeftRight=a.asm.FlipLeftRight).apply(null,arguments)},H1=a._Floor=function(){return(H1=a._Floor=a.asm.Floor).apply(null,arguments)},Ri=a._FloorDiv=function(){return(Ri=a._FloorDiv=a.asm.FloorDiv).apply(null,arguments)},Ud=a._FusedBatchNorm=function(){return(Ud=a._FusedBatchNorm=a.asm.FusedBatchNorm).apply(null,arguments)},j1=a._FusedConv2D=function(){return(j1=a._FusedConv2D=a.asm.FusedConv2D).apply(null,arguments)},q1=a._FusedDepthwiseConv2D=function(){return(q1=a._FusedDepthwiseConv2D=a.asm.FusedDepthwiseConv2D).apply(null,arguments)},X1=a._Gather=function(){return(X1=a._Gather=a.asm.Gather).apply(null,arguments)},Je=a._GatherNd=function(){return(Je=a._GatherNd=a.asm.GatherNd).apply(null,arguments)},K1=a._Greater=function(){return(K1=a._Greater=a.asm.Greater).apply(null,arguments)},Z1=a._GreaterEqual=function(){return(Z1=a._GreaterEqual=a.asm.GreaterEqual).apply(null,arguments)},Y1=a._LeakyRelu=function(){return(Y1=a._LeakyRelu=a.asm.LeakyRelu).apply(null,arguments)},J1=a._Less=function(){return(J1=a._Less=a.asm.Less).apply(null,arguments)},Q1=a._LessEqual=function(){return(Q1=a._LessEqual=a.asm.LessEqual).apply(null,arguments)},eg=a._Log=function(){return(eg=a._Log=a.asm.Log).apply(null,arguments)},Gd=a._LogicalAnd=function(){return(Gd=a._LogicalAnd=a.asm.LogicalAnd).apply(null,arguments)},wf=a._LogicalNot=function(){return(wf=a._LogicalNot=a.asm.LogicalNot).apply(null,arguments)},kf=a._LogicalOr=function(){return(kf=a._LogicalOr=a.asm.LogicalOr).apply(null,arguments)},tg=a._LogicalXor=function(){return(tg=a._LogicalXor=a.asm.LogicalXor).apply(null,arguments)},ng=a._Max=function(){return(ng=a._Max=a.asm.Max).apply(null,arguments)},sg=a._MaxPool=function(){return(sg=a._MaxPool=a.asm.MaxPool).apply(null,arguments)},rg=a._Maximum=function(){return(rg=a._Maximum=a.asm.Maximum).apply(null,arguments)},ag=a._Mean=function(){return(ag=a._Mean=a.asm.Mean).apply(null,arguments)},og=a._Min=function(){return(og=a._Min=a.asm.Min).apply(null,arguments)},zt=a._Minimum=function(){return(zt=a._Minimum=a.asm.Minimum).apply(null,arguments)},ig=a._MirrorPad=function(){return(ig=a._MirrorPad=a.asm.MirrorPad).apply(null,arguments)},lg=a._Multiply=function(){return(lg=a._Multiply=a.asm.Multiply).apply(null,arguments)},ug=a._Neg=function(){return(ug=a._Neg=a.asm.Neg).apply(null,arguments)},Cu=a._NonMaxSuppressionV3=function(){return(Cu=a._NonMaxSuppressionV3=a.asm.NonMaxSuppressionV3).apply(null,arguments)},If=a._NonMaxSuppressionV4=function(){return(If=a._NonMaxSuppressionV4=a.asm.NonMaxSuppressionV4).apply(null,arguments)},Sf=a._NonMaxSuppressionV5=function(){return(Sf=a._NonMaxSuppressionV5=a.asm.NonMaxSuppressionV5).apply(null,arguments)},Cf=a._NotEqual=function(){return(Cf=a._NotEqual=a.asm.NotEqual).apply(null,arguments)},cg=a._OneHot=function(){return(cg=a._OneHot=a.asm.OneHot).apply(null,arguments)},Tf=a._PadV2=function(){return(Tf=a._PadV2=a.asm.PadV2).apply(null,arguments)},dg=a._Pow=function(){return(dg=a._Pow=a.asm.Pow).apply(null,arguments)},Z4=a._Prelu=function(){return(Z4=a._Prelu=a.asm.Prelu).apply(null,arguments)},Nf=a._Prod=function(){return(Nf=a._Prod=a.asm.Prod).apply(null,arguments)},Y4=a._RealDiv=function(){return(Y4=a._RealDiv=a.asm.RealDiv).apply(null,arguments)},pg=a._Relu=function(){return(pg=a._Relu=a.asm.Relu).apply(null,arguments)},hg=a._Relu6=function(){return(hg=a._Relu6=a.asm.Relu6).apply(null,arguments)},fg=a._ResizeBilinear=function(){return(fg=a._ResizeBilinear=a.asm.ResizeBilinear).apply(null,arguments)},mg=a._ResizeNearestNeighbor=function(){return(mg=a._ResizeNearestNeighbor=a.asm.ResizeNearestNeighbor).apply(null,arguments)},gg=a._Reverse=function(){return(gg=a._Reverse=a.asm.Reverse).apply(null,arguments)},yg=a._RotateWithOffset=function(){return(yg=a._RotateWithOffset=a.asm.RotateWithOffset).apply(null,arguments)},Ag=a._Round=function(){return(Ag=a._Round=a.asm.Round).apply(null,arguments)},xg=a._Rsqrt=function(){return(xg=a._Rsqrt=a.asm.Rsqrt).apply(null,arguments)},bg=a._ScatterNd=function(){return(bg=a._ScatterNd=a.asm.ScatterNd).apply(null,arguments)},vg=a._SelectV2=function(){return(vg=a._SelectV2=a.asm.SelectV2).apply(null,arguments)},wg=a._Sigmoid=function(){return(wg=a._Sigmoid=a.asm.Sigmoid).apply(null,arguments)},kg=a._Sin=function(){return(kg=a._Sin=a.asm.Sin).apply(null,arguments)},Ig=a._Softmax=function(){return(Ig=a._Softmax=a.asm.Softmax).apply(null,arguments)},Sg=a._SparseFillEmptyRows=function(){return(Sg=a._SparseFillEmptyRows=a.asm.SparseFillEmptyRows).apply(null,arguments)},Cg=a._SparseReshape=function(){return(Cg=a._SparseReshape=a.asm.SparseReshape).apply(null,arguments)},Tg=a._SparseSegmentReduction=function(){return(Tg=a._SparseSegmentReduction=a.asm.SparseSegmentReduction).apply(null,arguments)},Ng=a._Sqrt=function(){return(Ng=a._Sqrt=a.asm.Sqrt).apply(null,arguments)},Eg=a._Square=function(){return(Eg=a._Square=a.asm.Square).apply(null,arguments)},Rg=a._SquaredDifference=function(){return(Rg=a._SquaredDifference=a.asm.SquaredDifference).apply(null,arguments)},_g=a._Step=function(){return(_g=a._Step=a.asm.Step).apply(null,arguments)},Dg=a._StridedSlice=function(){return(Dg=a._StridedSlice=a.asm.StridedSlice).apply(null,arguments)},$g=a._Sub=function(){return($g=a._Sub=a.asm.Sub).apply(null,arguments)},Pg=a._Sum=function(){return(Pg=a._Sum=a.asm.Sum).apply(null,arguments)},Fg=a._Tan=function(){return(Fg=a._Tan=a.asm.Tan).apply(null,arguments)},Og=a._Tanh=function(){return(Og=a._Tanh=a.asm.Tanh).apply(null,arguments)},Mg=a._Tile=function(){return(Mg=a._Tile=a.asm.Tile).apply(null,arguments)},zg=a._TopK=function(){return(zg=a._TopK=a.asm.TopK).apply(null,arguments)},Lg=a._Transform=function(){return(Lg=a._Transform=a.asm.Transform).apply(null,arguments)},Bg=a._Transpose=function(){return(Bg=a._Transpose=a.asm.Transpose).apply(null,arguments)},Wg=a.__FusedMatMul=function(){return(Wg=a.__FusedMatMul=a.asm._FusedMatMul).apply(null,arguments)},Vg=a._malloc=function(){return(Vg=a._malloc=a.asm.malloc).apply(null,arguments)},Ug=a._free=function(){return(Ug=a._free=a.asm.free).apply(null,arguments)},Gg=a.___errno_location=function(){return(Gg=a.___errno_location=a.asm.__errno_location).apply(null,arguments)},Hg=a._emscripten_main_thread_process_queued_calls=function(){return(Hg=a._emscripten_main_thread_process_queued_calls=a.asm.emscripten_main_thread_process_queued_calls).apply(null,arguments)},Ef=a.stackSave=function(){return(Ef=a.stackSave=a.asm.stackSave).apply(null,arguments)},Rf=a.stackRestore=function(){return(Rf=a.stackRestore=a.asm.stackRestore).apply(null,arguments)},Hd=a.stackAlloc=function(){return(Hd=a.stackAlloc=a.asm.stackAlloc).apply(null,arguments)},jg=a.dynCall_iijjiiii=function(){return(jg=a.dynCall_iijjiiii=a.asm.dynCall_iijjiiii).apply(null,arguments)},qg=a.dynCall_jiji=function(){return(qg=a.dynCall_jiji=a.asm.dynCall_jiji).apply(null,arguments)};a.cwrap=_e;var Tu;function jd(X){this.name="ExitStatus",this.message="Program terminated with exit("+X+")",this.status=X}Ma=function X(){Tu||qd(),Tu||(Ma=X)};function qd(X){if(X=X||c,Us>0||(af(),Us>0))return;function se(){Tu||(Tu=!0,a.calledRun=!0,!ae&&(of(),o(a),a.onRuntimeInitialized&&a.onRuntimeInitialized(),lf()))}a.setStatus?(a.setStatus("Running..."),setTimeout(function(){setTimeout(function(){a.setStatus("")},1),se()},1)):se()}a.run=qd;function J4(X){le=X,zd()||(a.onExit&&a.onExit(X),ae=!0),d(X,new jd(X))}if(a.preInit)for(typeof a.preInit=="function"&&(a.preInit=[a.preInit]);a.preInit.length>0;)a.preInit.pop()();qd();var Nu;l&&(Nu={uncaughtException:process.listeners("uncaughtException").filter(function(X){return!l.uncaughtException.indexOf(X)>-1}),unhandledRejection:process.listeners("unhandledRejection").filter(function(X){return!l.unhandledRejection.indexOf(X)>-1})});var Eu;if(typeof r!="undefined")Eu=r;else if(typeof WasmBackendModuleThreadedSimd!="undefined")Eu=WasmBackendModuleThreadedSimd;else throw new Error("Could not find wasm module in post.js");if(Nu){var Xg=Eu._dispose;Eu._dispose=function(){Xg(),Nu.uncaughtException.forEach(function(X){process.removeListener("uncaughtException",X)}),Nu.unhandledRejection.forEach(function(X){process.removeListener("unhandledRejection",X)})}}return r.ready}})();typeof e=="object"&&typeof t=="object"?t.exports=n:typeof define=="function"&&define.amd?define([],function(){return n}):typeof e=="object"&&(e.WasmBackendModule=n)}}),A_=1e-7,x_=1e-4,Mp=class{constructor(e,t){this.backend=e,this.dataMover=t,this.data=new WeakMap,this.dataIdsCount=0}get(e){return this.data.has(e)||this.dataMover.moveData(this.backend,e),this.data.get(e)}set(e,t){this.dataIdsCount++,this.data.set(e,t)}has(e){return this.data.has(e)}delete(e){return this.dataIdsCount--,this.data.delete(e)}numDataIds(){return this.dataIdsCount}},cc=class{refCount(e){return Gs("refCount")}incRef(e){return Gs("incRef")}timerAvailable(){return!0}time(e){return Gs("time")}read(e){return Gs("read")}readSync(e){return Gs("readSync")}readToGPU(e,t){return Gs("readToGPU")}numDataIds(){return Gs("numDataIds")}disposeData(e,t){return Gs("disposeData")}write(e,t,n){return Gs("write")}move(e,t,n,s,r){return Gs("move")}memory(){return Gs("memory")}floatPrecision(){return Gs("floatPrecision")}epsilon(){return this.floatPrecision()===32?A_:x_}dispose(){return Gs("dispose")}};function Gs(e){throw new Error(`'${e}' not yet implemented or not found in the registry. This kernel may not be supported by the tfjs backend you have chosen`)}function J7(e){let t=e.length,n=0;for(;t>0;)n=Math.random()*t|0,t--,cm(e,t,n)}function b_(e,t){if(e.length!==t.length)throw new Error(`Array sizes must match to be shuffled together First array length was ${e.length}Second array length was ${t.length}`);let n=e.length,s=0;for(;n>0;)s=Math.random()*n|0,n--,cm(e,n,s),cm(t,n,s)}function xp(e,t,n){return Math.max(e,Math.min(t,n))}function v_(e){return e%2===0?e:e+1}function cm(e,t,n){let s=e[t];e[t]=e[n],e[n]=s}function w_(e){let t=0;for(let n=0;n<e.length;n++)t+=e[n];return t}function k_(e,t){let n=Math.random();return t*n+(1-n)*e}function I_(e,t){let n=0;for(let s=0;s<e.length;s++){let r=Number(e[s])-Number(t[s]);n+=r*r}return n}function M(e,t){if(!e)throw new Error(typeof t=="string"?t:t())}function ns(e,t,n=""){M(co(e,t),()=>n+` Shapes ${e} and ${t} must match`)}function ol(e){M(e!=null,()=>"The input to the tensor constructor must be a non-null value.")}function Xi(e,t=[],n=!1){if(t==null&&(t=[]),Array.isArray(e)||Pn(e)&&!n)for(let s=0;s<e.length;++s)Xi(e[s],t,n);else t.push(e);return t}function Et(e){if(e.length===0)return 1;let t=e[0];for(let n=1;n<e.length;n++)t*=e[n];return t}function S_(e){return e.length===0}function co(e,t){if(e===t)return!0;if(e==null||t==null||e.length!==t.length)return!1;for(let n=0;n<e.length;n++)if(e[n]!==t[n])return!1;return!0}function qu(e){return e%1===0}function C_(e){if(Math.tanh!=null)return Math.tanh(e);if(e===1/0)return 1;if(e===-1/0)return-1;{let t=Math.exp(2*e);return(t-1)/(t+1)}}function T_(e){let t=Math.ceil(Math.sqrt(e));return[t,Math.ceil(e/t)]}function N_(e){let t=new Uint32Array(e);for(let n=0;n<e;++n)t[n]=n;return J7(t),t}function fp(e,t){return t<=e.length?e:e+" ".repeat(t-e.length)}function E_(e,t=s=>0,n){return new Promise((s,r)=>{let a=0,o=()=>{if(e()){s();return}a++;let i=t(a);if(n!=null&&a>=n){r();return}setTimeout(o,i)};o()})}function R_(e,t){let n=1,s=-1;for(let a=0;a<e.length;++a)if(e[a]>=0)n*=e[a];else if(e[a]===-1){if(s!==-1)throw Error(`Shapes can only have 1 implicit size. Found -1 at dim ${s} and dim ${a}`);s=a}else if(e[a]<0)throw Error(`Shapes can not be < 0. Found ${e[a]} at dim ${a}`);if(s===-1){if(t>0&&t!==n)throw Error(`Size(${t}) must match the product of shape ${e}`);return e}if(n===0)throw Error(`Cannot infer the missing size in [${e}] when there are 0 elements`);if(t%n!==0)throw Error(`The implicit shape can't be a fractional number. Got ${t} / ${n}`);let r=e.slice();return r[s]=t/n,r}function ur(e,t){let n=t.length;return e=e==null?t.map((s,r)=>r):[].concat(e),M(e.every(s=>s>=-n&&s<n),()=>`All values in axis param must be in range [-${n}, ${n}) but got axis ${e}`),M(e.every(s=>qu(s)),()=>`All values in axis param must be integers but got axis ${e}`),e.map(s=>s<0?n+s:s)}function Q7(e,t){let n=[],s=[],r=t!=null&&Array.isArray(t)&&t.length===0,a=t==null||r?null:ur(t,e).sort(),o=0;for(let i=0;i<e.length;++i){if(a!=null){if(a[o]===i&&e[i]!==1)throw new Error(`Can't squeeze axis ${i} since its dim '${e[i]}' is not 1`);(a[o]==null||a[o]>i)&&e[i]===1&&(n.push(e[i]),s.push(i)),a[o]<=i&&o++}e[i]!==1&&(n.push(e[i]),s.push(i))}return{newShape:n,keptDims:s}}function e6(e,t){let n=null;if(e==null||e==="float32")n=new Float32Array(t);else if(e==="int32")n=new Int32Array(t);else if(e==="bool")n=new Uint8Array(t);else throw new Error(`Unknown data type ${e}`);return n}function t6(e,t){let n=null;if(e==null||e==="float32")n=new Float32Array(t);else if(e==="int32")n=new Int32Array(t);else if(e==="bool")n=new Uint8Array(t);else if(e==="string")n=new Array(t);else throw new Error(`Unknown data type ${e}`);return n}function n6(e,t){for(let n=0;n<e.length;n++){let s=e[n];if(isNaN(s)||!isFinite(s))throw Error(`A tensor of type ${t} being uploaded contains ${s}.`)}}function s6(e){return e==="bool"||e==="complex64"||e==="float32"||e==="int32"||e==="string"}function __(e,t){return!(t==="complex64"||t==="float32"&&e!=="complex64"||t==="int32"&&e!=="float32"&&e!=="complex64"||t==="bool"&&e==="bool")}function Pn(e){return e instanceof Float32Array||e instanceof Int32Array||e instanceof Uint8Array||e instanceof Uint8ClampedArray}function m3(e){if(e==="float32"||e==="int32")return 4;if(e==="complex64")return 8;if(e==="bool")return 1;throw new Error(`Unknown dtype ${e}`)}function r6(e){if(e==null)return 0;let t=0;return e.forEach(n=>t+=n.length),t}function Ga(e){return typeof e=="string"||e instanceof String}function a6(e){return typeof e=="boolean"}function o6(e){return typeof e=="number"}function Vm(e){return Array.isArray(e)?Vm(e[0]):e instanceof Float32Array?"float32":e instanceof Int32Array||e instanceof Uint8Array||e instanceof Uint8ClampedArray?"int32":o6(e)?"float32":Ga(e)?"string":a6(e)?"bool":"float32"}function Ya(e){return!!(e&&e.constructor&&e.call&&e.apply)}function dm(e,t){for(let n=t;n<e;++n)if(e%n===0)return n;return e}function dc(e){let t=e.length;if(t<2)return[];let n=new Array(t-1);n[t-2]=e[t-1];for(let s=t-3;s>=0;--s)n[s]=n[s+1]*e[s+1];return n}function i6(e,t,n,s=!1){let r=new Array;if(t.length===1){let a=t[0]*(s?2:1);for(let o=0;o<a;o++)r[o]=n[e+o]}else{let a=t[0],o=t.slice(1),i=o.reduce((l,u)=>l*u)*(s?2:1);for(let l=0;l<a;l++)r[l]=i6(e+l*i,o,n,s)}return r}function Wu(e,t,n=!1){if(e.length===0)return t[0];let s=e.reduce((r,a)=>r*a)*(n?2:1);if(s===0)return[];if(s!==t.length)throw new Error(`[${e}] does not match the input size ${t.length}${n?" for a complex tensor":""}.`);return i6(0,e,t,n)}function by(e,t){let n=Um(e,t);for(let s=0;s<n.length;s++)n[s]=1;return n}function Um(e,t){if(t==null||t==="float32"||t==="complex64")return new Float32Array(e);if(t==="int32")return new Int32Array(e);if(t==="bool")return new Uint8Array(e);throw new Error(`Unknown data type ${t}`)}function D_(e,t){let n=e.reduce((s,r)=>s*r,1);if(t==null||t==="float32")return Wu(e,new Float32Array(n));if(t==="int32")return Wu(e,new Int32Array(n));if(t==="bool")return Wu(e,new Uint8Array(n));throw new Error(`Unknown data type ${t}`)}function vy(e){e.forEach(t=>{M(Number.isInteger(t)&&t>=0,()=>`Tensor must have a shape comprised of positive integers but got shape [${e}].`)})}function $_(e,t,n){if(t===0)return 0;if(t===1)return e[0];let s=e[e.length-1];for(let r=0;r<e.length-1;++r)s+=n[r]*e[r];return s}function P_(e,t,n){if(t===0)return[];if(t===1)return[e];let s=new Array(t);for(let r=0;r<s.length-1;++r)s[r]=Math.floor(e/n[r]),e-=s[r]*n[r];return s[s.length-1]=e,s}function wy(e){return e&&e.then&&typeof e.then=="function"}var cv="tfjsflags",l6=class{constructor(e){this.global=e,this.flags={},this.flagRegistry={},this.urlFlags={},this.getQueryParams=F_,this.populateURLFlags()}setPlatform(e,t){this.platform!=null&&(Z().getBool("IS_TEST")||Z().getBool("PROD")||console.warn(`Platform ${this.platformName} has already been set. Overwriting the platform with ${e}.`)),this.platformName=e,this.platform=t}registerFlag(e,t,n){if(this.flagRegistry[e]={evaluationFn:t,setHook:n},this.urlFlags[e]!=null){let s=this.urlFlags[e];Z().getBool("IS_TEST")||Z().getBool("PROD")||console.warn(`Setting feature override from URL ${e}: ${s}.`),this.set(e,s)}}async getAsync(e){return e in this.flags?this.flags[e]:(this.flags[e]=await this.evaluateFlag(e),this.flags[e])}get(e){if(e in this.flags)return this.flags[e];let t=this.evaluateFlag(e);if(wy(t))throw new Error(`Flag ${e} cannot be synchronously evaluated. Please use getAsync() instead.`);return this.flags[e]=t,this.flags[e]}getNumber(e){return this.get(e)}getBool(e){return this.get(e)}getFlags(){return this.flags}get features(){return this.flags}set(e,t){if(this.flagRegistry[e]==null)throw new Error(`Cannot set flag ${e} as it has not been registered.`);this.flags[e]=t,this.flagRegistry[e].setHook!=null&&this.flagRegistry[e].setHook(t)}evaluateFlag(e){if(this.flagRegistry[e]==null)throw new Error(`Cannot evaluate flag '${e}': no evaluation function found.`);return this.flagRegistry[e].evaluationFn()}setFlags(e){this.flags=Object.assign({},e)}reset(){this.flags={},this.urlFlags={},this.populateURLFlags()}populateURLFlags(){if(typeof this.global=="undefined"||typeof this.global.location=="undefined"||typeof this.global.location.search=="undefined")return;let e=this.getQueryParams(this.global.location.search);cv in e&&e[cv].split(",").forEach(n=>{let[s,r]=n.split(":");this.urlFlags[s]=M_(s,r)})}};function F_(e){let t={};return e.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g,(n,...s)=>(O_(t,s[0],s[1]),s.join("="))),t}function O_(e,t,n){e[decodeURIComponent(t)]=decodeURIComponent(n||"")}function M_(e,t){if(t=t.toLowerCase(),t==="true"||t==="false")return t==="true";if(`${+t}`===t)return+t;throw new Error(`Could not parse value flag value ${t} for flag ${e}.`)}function Z(){return $r}var $r=null;function z_(e){$r=e}var n3;function u6(){if(n3==null){let e;if(typeof window!="undefined")e=window;else if(typeof global!="undefined")e=global;else if(typeof process!="undefined")e=process;else if(typeof self!="undefined")e=self;else throw new Error("Could not find a global object");n3=e}return n3}function L_(){let e=u6();return e._tfGlobals==null&&(e._tfGlobals=new Map),e._tfGlobals}function ky(e,t){let n=L_();if(n.has(e))return n.get(e);{let s=t();return n.set(e,s),n.get(e)}}var il="Abs",pc="Acos",hc="Acosh",xa="Add",po="AddN",fc="All",mc="Any",ho="ArgMax",gc="ArgMin",yc="Asin",Ac="Asinh",xc="Atan",bc="Atanh",vc="Atan2",fo="AvgPool",Gm="AvgPoolGrad",zp="AvgPool3D",Hm="AvgPool3DGrad",mo="BatchMatMul",ll="BatchToSpaceND",jm="Bincount",c6="BroadcastTo",qm="BroadcastArgs",go="Cast",yo="Ceil",ba="ClipByValue",Lp="Complex",Bp="ComplexAbs",ul="Concat",Ao="Conv2D",Xm="Conv2DBackpropFilter",xo="Conv2DBackpropInput",Wp="Conv3D",Km="Conv3DBackpropFilterV2",Zm="Conv3DBackpropInputV2",bo="Cos",vo="Cosh",cl="Cumprod",wo="Cumsum",dl="CropAndResize",Ym="DenseBincount",pl="DepthToSpace",ko="DepthwiseConv2dNative",Jm="DepthwiseConv2dNativeBackpropFilter",Qm="DepthwiseConv2dNativeBackpropInput",e0="Diag",Vp="Dilation2D",pm="Dilation2DBackpropInput",hm="Dilation2DBackpropFilter",Io="RealDiv",Up="Einsum",So="Elu",t0="EluGrad",wc="Erf",hl="Equal",Co="Exp",fl="ExpandDims",ml="Expm1",n0="FFT",kc="Fill",gl="FlipLeftRight",To="Floor",No="FloorDiv",Eo="FusedBatchNorm",yl="GatherV2",Al="GatherNd",xl="Greater",Ro="GreaterEqual",_o="Identity",s0="IFFT",Gp="Imag",Ic="IsFinite",Sc="IsInf",Cc="IsNan",Do="LeakyRelu",bl="Less",vl="LessEqual",r0="LinSpace",$o="Log",Tc="Log1p",wl="LogicalAnd",kl="LogicalNot",Nc="LogicalOr",d6="LogicalXor",p6="LogSoftmax",B_="LowerBound",Hp="LRN",a0="LRNGrad",Po="Max",Fo="Maximum",Oo="MaxPool",o0="MaxPoolGrad",jp="MaxPool3D",i0="MaxPool3DGrad",l0="MaxPoolWithArgmax",Mo="Mean",zo="Min",Lo="Minimum",Bo="MirrorPad",Ec="Mod",u0="Multinomial",Wo="Multiply",Il="Neg",Sl="NotEqual",Cl="NonMaxSuppressionV3",Rc="NonMaxSuppressionV4",Tl="NonMaxSuppressionV5",Nl="OnesLike",El="OneHot",Rl="Pack",Vo="PadV2",W_="Pool",Uo="Pow",Go="Prelu",Ho="Prod",_c="Range",qp="Real",Dc="Reciprocal",jo="Relu",_l="Reshape",qo="ResizeNearestNeighbor",c0="ResizeNearestNeighborGrad",Xo="ResizeBilinear",d0="ResizeBilinearGrad",Ko="Relu6",Dl="Reverse",$l="Round",Zo="Rsqrt",Pl="ScatterNd",p0="SearchSorted",Fl="Select",$c="Selu",Ol="Slice",Yo="Sin",Ml="Sinh",Pc="Sign",Jo="Sigmoid",Fc="Softplus",Qo="Sqrt",ei="Sum",zl="SpaceToBatchND",Ll="SplitV",ti="Softmax",Xp="SparseFillEmptyRows",Oc="SparseReshape",Kp="SparseSegmentMean",Zp="SparseSegmentSum",Yp="SparseToDense",ni="SquaredDifference",Mc="Square",Bl="StridedSlice",zc="StringNGrams",Jp="StringSplit",Qp="StringToHashBucketFast",si="Sub",Wl="Tan",ri="Tanh",va="Tile",Vl="TopK",Ul="Transform",Hr="Transpose",h0="Unique",Gl="Unpack",eh="UnsortedSegmentSum",V_="UpperBound",Hl="ZerosLike",ai="Step",bp="FromPixels",jl="RotateWithOffset",Ja="_FusedMatMul",Qa="FusedConv2D",eo="FusedDepthwiseConv2D";function Ua(...e){Z().getBool("IS_TEST")||Z().getBool("PROD")||console.warn(...e)}function U_(...e){Z().getBool("IS_TEST")||Z().getBool("PROD")||console.log(...e)}var Xu=ky("kernelRegistry",()=>new Map),vp=ky("gradRegistry",()=>new Map);function fm(e,t){let n=Iy(e,t);return Xu.get(n)}function g3(e){return vp.get(e)}function qr(e){let t=Xu.entries(),n=[];for(;;){let{done:s,value:r}=t.next();if(s)break;let[a,o]=r,[i]=a.split("_");i===e&&n.push(o)}return n}function cr(e){let{kernelName:t,backendName:n}=e,s=Iy(t,n);Xu.has(s)&&Ua(`The kernel '${t}' for backend '${n}' is already registered`),Xu.set(s,e)}function h6(e){let{kernelName:t}=e;vp.has(t)&&Z().getBool("DEBUG")&&Ua(`Overriding the gradient for '${t}'`),vp.set(t,e)}function G_(e,t){let n=Iy(e,t);if(!Xu.has(n))throw new Error(`The kernel '${e}' for backend '${t}' is not registered`);Xu.delete(n)}function H_(e){if(!vp.has(e))throw new Error(`The gradient '${e}' for backend is not registered`);vp.delete(e)}function j_(e,t){qr(e).forEach(s=>{let r=Object.assign({},s,{backendName:t});cr(r)})}function Iy(e,t){return`${t}_${e}`}var v={};Ve(v,{arraysEqual:()=>co,assert:()=>M,assertNonNegativeIntegerDimensions:()=>vy,assertNonNull:()=>ol,assertShapesMatch:()=>ns,bytesFromStringArray:()=>r6,bytesPerElement:()=>m3,checkConversionForErrors:()=>n6,clamp:()=>xp,computeStrides:()=>dc,createScalarValue:()=>J_,createShuffledIndices:()=>N_,decodeString:()=>mm,distSquared:()=>I_,encodeString:()=>nh,fetch:()=>eD,fingerPrint64:()=>Y_,flatten:()=>Xi,getArrayFromDType:()=>t6,getTypedArrayFromDType:()=>e6,hasEncodingLoss:()=>__,hexToLong:()=>th,indexToLoc:()=>P_,inferDtype:()=>Vm,inferFromImplicitShape:()=>R_,isBoolean:()=>a6,isFunction:()=>Ya,isInt:()=>qu,isNumber:()=>o6,isPromise:()=>wy,isScalarShape:()=>S_,isString:()=>Ga,isTypedArray:()=>Pn,isValidDtype:()=>s6,locToIndex:()=>$_,makeOnesTypedArray:()=>by,makeZerosNestedTypedArray:()=>D_,makeZerosTypedArray:()=>Um,nearestDivisor:()=>dm,nearestLargerEven:()=>v_,now:()=>wp,parseAxisParam:()=>ur,randUniform:()=>k_,repeatedTry:()=>E_,rightPad:()=>fp,shuffle:()=>J7,shuffleCombo:()=>b_,sizeFromShape:()=>Et,sizeToSquarishShape:()=>T_,squeezeShape:()=>Q7,sum:()=>w_,swap:()=>cm,tanh:()=>C_,toNestedArray:()=>Wu,toTypedArray:()=>f0});var dv=uo(t_()),Mi=dv.default||dv;function th(e){return Mi.fromString(e,!0,16)}var f6=th("c3a5c85c97cb3127"),Pi=th("b492b66fbe98f273"),Zn=th("9ae16a3b2f90404f");function y3(e){return e.xor(e.shru(47))}function m6(e,t,n){let s=e.slice(t,t+n);return Mi.fromBytes(Array.from(s),!0,!0)}function Nt(e,t){return m6(e,t,8)}function pv(e,t){return m6(e,t,4)}function xn(e,t){return t===0?e:e.shru(t).or(e.shl(64-t))}function qa(e,t,n=th("9ddfea08eb382d69")){let s=e.xor(t).mul(n);s=s.xor(s.shru(47));let r=t.xor(s).mul(n);return r=r.xor(r.shru(47)),r=r.mul(n),r}function q_(e,t,n,s,r,a){r=r.add(e),a=xn(a.add(r).add(s),21);let o=r;return r=r.add(t),r=r.add(n),a=a.add(xn(r,44)),[r.add(s),a.add(o)]}function Lf(e,t,n,s){return q_(Nt(e,t),Nt(e,t+8),Nt(e,t+16),Nt(e,t+24),n,s)}function X_(e,t=e.length){if(t>=8){let n=Zn.add(t*2),s=Nt(e,0).add(Zn),r=Nt(e,t-8),a=xn(r,37).mul(n).add(s),o=xn(s,25).add(r).mul(n);return qa(a,o,n)}if(t>=4){let n=Zn.add(t*2),s=pv(e,0);return qa(s.shl(3).add(t),pv(e,t-4),n)}if(t>0){let n=e[0],s=e[t>>1],r=e[t-1],a=n+(s<<8),o=t+(r<<2);return y3(Zn.mul(a).xor(f6.mul(o))).mul(Zn)}return Zn}function K_(e,t=e.length){let n=Zn.add(t*2),s=Nt(e,0).mul(Pi),r=Nt(e,8),a=Nt(e,t-8).mul(n),o=Nt(e,t-16).mul(Zn);return qa(xn(s.add(r),43).add(xn(a,30)).add(o),s.add(xn(r.add(Zn),18)).add(a),n)}function Z_(e,t=e.length){let n=Zn.add(t*2),s=Nt(e,0).mul(Zn),r=Nt(e,8),a=Nt(e,t-8).mul(n),o=Nt(e,t-16).mul(Zn),i=xn(s.add(r),43).add(xn(a,30)).add(o),l=qa(i,s.add(xn(r.add(Zn),18)).add(a),n),u=Nt(e,16).mul(n),c=Nt(e,24),p=i.add(Nt(e,t-32)).mul(n),d=l.add(Nt(e,t-24)).mul(n);return qa(xn(u.add(c),43).add(xn(p,30)).add(d),u.add(xn(c.add(s),18)).add(p),n)}function Y_(e,t=e.length){let n=Mi.fromNumber(81,!0);if(t<=32)return t<=16?X_(e,t):K_(e,t);if(t<=64)return Z_(e,t);let s=n,r=n.mul(Pi).add(113),a=y3(r.mul(Zn).add(113)).mul(Zn),o=[Mi.UZERO,Mi.UZERO],i=[Mi.UZERO,Mi.UZERO];s=s.mul(Zn).add(Nt(e,0));let l=0,u=(t-1>>6)*64,c=u+(t-1&63)-63;do s=xn(s.add(r).add(o[0]).add(Nt(e,l+8)),37).mul(Pi),r=xn(r.add(o[1]).add(Nt(e,l+48)),42).mul(Pi),s=s.xor(i[1]),r=r.add(o[0]).add(Nt(e,l+40)),a=xn(a.add(i[0]),33).mul(Pi),o=Lf(e,l,o[1].mul(Pi),s.add(i[0])),i=Lf(e,l+32,a.add(i[1]),r.add(Nt(e,l+16))),[a,s]=[s,a],l+=64;while(l!==u);let p=Pi.add(a.and(255).shl(1));return l=c,i[0]=i[0].add(t-1&63),o[0]=o[0].add(i[0]),i[0]=i[0].add(o[0]),s=xn(s.add(r).add(o[0]).add(Nt(e,l+8)),37).mul(p),r=xn(r.add(o[1]).add(Nt(e,l+48)),42).mul(p),s=s.xor(i[1].mul(9)),r=r.add(o[0].mul(9).add(Nt(e,l+40))),a=xn(a.add(i[0]),33).mul(p),o=Lf(e,l,o[1].mul(p),s.add(i[0])),i=Lf(e,l+32,a.add(i[1]),r.add(Nt(e,l+16))),[a,s]=[s,a],qa(qa(o[0],i[0],p).add(y3(r).mul(f6)).add(a),qa(o[1],i[1],p).add(s),p)}function J_(e,t){return t==="string"?nh(e):f0([e],t)}function Q_(e,t){return e instanceof Float32Array&&t==="float32"||e instanceof Int32Array&&t==="int32"||e instanceof Uint8Array&&t==="bool"}function f0(e,t){if(t==="string")throw new Error("Cannot convert a string[] to a TypedArray");if(Array.isArray(e)&&(e=Xi(e)),Z().getBool("DEBUG")&&n6(e,t),Q_(e,t))return e;if(t==null||t==="float32"||t==="complex64")return new Float32Array(e);if(t==="int32")return new Int32Array(e);if(t==="bool"){let n=new Uint8Array(e.length);for(let s=0;s<n.length;++s)Math.round(e[s])!==0&&(n[s]=1);return n}else throw new Error(`Unknown data type ${t}`)}function wp(){return Z().platform.now()}function eD(e,t){return Z().platform.fetch(e,t)}function nh(e,t="utf-8"){return t=t||"utf-8",Z().platform.encode(e,t)}function mm(e,t="utf-8"){return t=t||"utf-8",Z().platform.decode(e,t)}var tD=class{constructor(e,t){this.backendTimer=e,this.logger=t,t==null&&(this.logger=new sD)}profileKernel(e,t,n){let s,r=()=>{s=n()},a,o=wp();if(this.backendTimer.timerAvailable())a=this.backendTimer.time(r);else{r();for(let l of s)l.dataSync();a=Promise.resolve({kernelMs:wp()-o})}if(Z().getBool("CHECK_COMPUTATION_FOR_ERRORS"))for(let l=0;l<s.length;l++){let u=s[l];u.data().then(c=>{nD(c,u.dtype,e)})}return{kernelName:e,outputs:s,inputs:t,timeMs:a.then(l=>l.kernelMs),extraInfo:a.then(l=>l.getExtraProfileInfo!=null?l.getExtraProfileInfo():"")}}logKernelProfile(e){let{kernelName:t,outputs:n,timeMs:s,inputs:r,extraInfo:a}=e;n.forEach(o=>{Promise.all([o.data(),s,a]).then(i=>{this.logger.logKernelProfile(t,o,i[0],i[1],r,i[2])})})}};function nD(e,t,n){if(t!=="float32")return!1;for(let s=0;s<e.length;s++){let r=e[s];if(isNaN(r)||!isFinite(r))return console.warn(`Found ${r} in the result of '${n}'`),!0}return!1}var sD=class{logKernelProfile(e,t,n,s,r,a){let o=typeof s=="number"?fp(`${s}ms`,9):s.error,i=fp(e,25),l=t.rank,u=t.size,c=fp(t.shape.toString(),14),p="";for(let d in r){let h=r[d];if(h!=null){let f=h.shape||t.shape,m=f.length;p+=`${d}: ${m}D ${m>0?f:""} `}}console.log(`%c${i}	%c${o}	%c${l}D ${c}	%c${u}	%c${p}	%c${a}`,"font-weight:bold","color:red","color:blue","color: orange","color: green","color: steelblue")}};function rD(e,t,n){let s={},r={};for(let l=0;l<t.length;l++)s[t[l].id]=!0;for(let l=0;l<e.length;l++){let u=e[l],c=u.inputs;for(let p in c){let d=c[p],h=!1;for(let f=0;f<t.length;f++)if(s[d.id]){u.outputs.forEach(m=>s[m.id]=!0),h=!0,r[u.id]=!0;break}if(h)break}}let a={};a[n.id]=!0;let o={};for(let l=e.length-1;l>=0;l--){let u=e[l],c=u.inputs;for(let p=0;p<u.outputs.length;p++)if(a[u.outputs[p].id]){for(let d in c)a[c[d].id]=!0,o[u.id]=!0;break}}let i=[];for(let l=0;l<e.length;l++){let u=e[l];if(r[u.id]&&o[u.id]){let c={};for(let d in u.inputs){let h=u.inputs[d];s[h.id]&&(c[d]=h)}let p=Object.assign({},u);p.inputs=c,p.outputs=u.outputs,i.push(p)}}return i}function aD(e,t,n,s){for(let r=t.length-1;r>=0;r--){let a=t[r],o=[];if(a.outputs.forEach(l=>{let u=e[l.id];u!=null?o.push(u):o.push(null)}),a.gradient==null)throw new Error(`Cannot compute gradient: gradient function not found for ${a.kernelName}.`);let i=a.gradient(o);for(let l in a.inputs){if(!(l in i))throw new Error(`Cannot backprop through input ${l}. Available gradients found: ${Object.keys(i)}.`);let u=n(()=>i[l]());if(u.dtype!=="float32")throw new Error(`Error in gradient for op ${a.kernelName}. The gradient of input ${l} must have 'float32' dtype, but has '${u.dtype}'`);let c=a.inputs[l];if(!co(u.shape,c.shape))throw new Error(`Error in gradient for op ${a.kernelName}. The gradient of input '${l}' has shape '${u.shape}', which does not match the shape of the input '${c.shape}'`);if(e[c.id]==null)e[c.id]=u;else{let p=e[c.id];e[c.id]=s(p,u),p.dispose()}}}}var hv=20,Qd=3,s3=7;function oD(e,t,n,s){let r=dc(t),a=iD(e,t,n,r),o=t.length,i=Qf(e,t,n,r,a),l=["Tensor"];return s&&(l.push(`  dtype: ${n}`),l.push(`  rank: ${o}`),l.push(`  shape: [${t}]`),l.push("  values:")),l.push(i.map(u=>"    "+u).join(`
+`));var ee=d.print||Z,Q=d.printErr||B;Object.assign(d,g),g=null,d.arguments&&(y=d.arguments),d.thisProgram&&(x=d.thisProgram),d.quit&&(A=d.quit);var oe=4;function Y(N){Y.shown||(Y.shown={}),Y.shown[N]||(Y.shown[N]=1,Q(N))}function ae(N,O){if(typeof WebAssembly.Function=="function"){for(var H={i:"i32",j:"i64",f:"f32",d:"f64"},te={parameters:[],results:O[0]=="v"?[]:[H[O[0]]]},Ae=1;Ae<O.length;++Ae)te.parameters.push(H[O[Ae]]);return new WebAssembly.Function(te,N)}var ve=[1,0,1,96],Te=O.slice(0,1),Me=O.slice(1),Lt={i:127,j:126,f:125,d:124};ve.push(Me.length);for(var Ae=0;Ae<Me.length;++Ae)ve.push(Lt[Me[Ae]]);Te=="v"?ve.push(0):ve=ve.concat([1,Lt[Te]]),ve[1]=ve.length-2;var vr=new Uint8Array([0,97,115,109,1,0,0,0].concat(ve,[2,7,1,1,101,1,102,0,0,7,5,1,1,102,0,0])),wr=new WebAssembly.Module(vr),Of=new WebAssembly.Instance(wr,{e:{f:N}}),Xd=Of.exports.f;return Xd}var le=[],ye;function we(){if(le.length)return le.pop();try{Us.grow(1)}catch(N){throw N instanceof RangeError?"Unable to grow wasm table. Set ALLOW_TABLE_GROWTH.":N}return Us.length-1}function Re(N,O){for(var H=N;H<N+O;H++){var te=Iu(H);te&&ye.set(te,H)}}var _e=0,Be=N=>{_e=N},Ge=Atomics.load,ot=Atomics.store,dt=Atomics.compareExchange,pt;d.wasmBinary&&(pt=d.wasmBinary);var At=d.noExitRuntime||!0;typeof WebAssembly!="object"&&vu("no native wasm support detected");var $e,Tt,It=!1,Un;function Qt(N,O){N||vu(O)}function bs(N){var O=d["_"+N];return O}function pn(N,O,H,te,Ae){var ve={string:function(ks){var _u=0;if(ks!=null&&ks!==0){var iv=(ks.length<<2)+1;_u=Ru(iv),ra(ks,_u,iv)}return _u},array:function(ks){var _u=Ru(ks.length);return aa(ks,_u),_u}};function Te(ks){return O==="string"?Hn(ks):O==="boolean"?Boolean(ks):ks}var Me=bs(N),Lt=[],vr=0;if(te)for(var wr=0;wr<te.length;wr++){var Of=ve[H[wr]];Of?(vr===0&&(vr=Jg()),Lt[wr]=Of(te[wr])):Lt[wr]=te[wr]}var Xd=Me.apply(null,Lt);function UR(ks){return vr!==0&&Df(vr),Te(ks)}return Xd=UR(Xd),Xd}function Gn(N,O,H,te){H=H||[];var Ae=H.every(function(Te){return Te==="number"}),ve=O!=="string";return ve&&Ae&&!te?bs(N):function(){return pn(N,O,H,arguments,te)}}var vs=1;function ws(N){var O=new TextDecoder(N);this.decode=H=>(H.buffer instanceof SharedArrayBuffer&&(H=new Uint8Array(H)),O.decode.call(O,H))}var $n=typeof TextDecoder!="undefined"?new ws("utf8"):void 0;function Vs(N,O,H){for(var te=O+H,Ae=O;N[Ae]&&!(Ae>=te);)++Ae;if(Ae-O>16&&N.subarray&&$n)return $n.decode(N.subarray(O,Ae));for(var ve="";O<Ae;){var Te=N[O++];if(!(Te&128)){ve+=String.fromCharCode(Te);continue}var Me=N[O++]&63;if((Te&224)==192){ve+=String.fromCharCode((Te&31)<<6|Me);continue}var Lt=N[O++]&63;if((Te&240)==224?Te=(Te&15)<<12|Me<<6|Lt:Te=(Te&7)<<18|Me<<12|Lt<<6|N[O++]&63,Te<65536)ve+=String.fromCharCode(Te);else{var vr=Te-65536;ve+=String.fromCharCode(55296|vr>>10,56320|vr&1023)}}return ve}function Hn(N,O){return N?Vs(o(),N,O):""}function sa(N,O,H,te){if(!(te>0))return 0;for(var Ae=H,ve=H+te-1,Te=0;Te<N.length;++Te){var Me=N.charCodeAt(Te);if(Me>=55296&&Me<=57343){var Lt=N.charCodeAt(++Te);Me=65536+((Me&1023)<<10)|Lt&1023}if(Me<=127){if(H>=ve)break;O[H++]=Me}else if(Me<=2047){if(H+1>=ve)break;O[H++]=192|Me>>6,O[H++]=128|Me&63}else if(Me<=65535){if(H+2>=ve)break;O[H++]=224|Me>>12,O[H++]=128|Me>>6&63,O[H++]=128|Me&63}else{if(H+3>=ve)break;O[H++]=240|Me>>18,O[H++]=128|Me>>12&63,O[H++]=128|Me>>6&63,O[H++]=128|Me&63}}return O[H]=0,H-Ae}function ra(N,O,H){return sa(N,o(),O,H)}function Au(N){for(var O=0,H=0;H<N.length;++H){var te=N.charCodeAt(H);te>=55296&&te<=57343&&(te=65536+((te&1023)<<10)|N.charCodeAt(++H)&1023),te<=127?++O:te<=2047?O+=2:te<=65535?O+=3:O+=4}return O}var Fa=typeof TextDecoder!="undefined"?new ws("utf-16le"):void 0;function aa(N,O){a().set(N,O)}function Od(N,O,H){for(var te=0;te<N.length;++te)a()[O++>>0]=N.charCodeAt(te);H||(a()[O>>0]=0)}function xu(N,O){return N%O>0&&(N+=O-N%O),N}var jn,nf,sf,Md,rf,af,W4,of,lf;S&&(jn=d.buffer);function yr(N){jn=N,d.HEAP8=nf=new Int8Array(N),d.HEAP16=Md=new Int16Array(N),d.HEAP32=af=new Int32Array(N),d.HEAPU8=sf=new Uint8Array(N),d.HEAPU16=rf=new Uint16Array(N),d.HEAPU32=W4=new Uint32Array(N),d.HEAPF32=of=new Float32Array(N),d.HEAPF64=lf=new Float64Array(N)}var uf=d.INITIAL_MEMORY||16777216;if(S)$e=d.wasmMemory,jn=d.buffer;else if(d.wasmMemory)$e=d.wasmMemory;else if($e=new WebAssembly.Memory({initial:uf/65536,maximum:32768,shared:!0}),!($e.buffer instanceof SharedArrayBuffer))throw Q("requested a shared WebAssembly.Memory but the returned buffer is not a SharedArrayBuffer, indicating that while the browser has SharedArrayBuffer it does not have WebAssembly threads support - you may need to set a flag"),k&&console.log("(on node you may need: --experimental-wasm-threads --experimental-wasm-bulk-memory and also use a recent version)"),Error("bad memory");$e&&(jn=$e.buffer),uf=jn.byteLength,yr(jn);var Us,bu=[],Oa=[],x1=[],cf=[],Si=!1,b1=!1,df=0;function Ci(){return At||df>0}function qn(){if(d.preRun)for(typeof d.preRun=="function"&&(d.preRun=[d.preRun]);d.preRun.length;)V4(d.preRun.shift());mf(bu)}function zd(){Si=!0,!S&&mf(Oa)}function v1(){S||(ze.terminateAllThreads(),b1=!0)}function w1(){if(!S){if(d.postRun)for(typeof d.postRun=="function"&&(d.postRun=[d.postRun]);d.postRun.length;)Ld(d.postRun.shift());mf(cf)}}function V4(N){bu.unshift(N)}function U4(N){Oa.unshift(N)}function Ld(N){cf.unshift(N)}var Ma=0,pf=null,Ar=null;function Bd(N){Ma++,d.monitorRunDependencies&&d.monitorRunDependencies(Ma)}function G4(N){if(Ma--,d.monitorRunDependencies&&d.monitorRunDependencies(Ma),Ma==0&&(pf!==null&&(clearInterval(pf),pf=null),Ar)){var O=Ar;Ar=null,O()}}d.preloadedImages={},d.preloadedAudios={};function vu(N){S?postMessage({cmd:"onAbort",arg:N}):d.onAbort&&d.onAbort(N),N="Aborted("+N+")",Q(N),It=!0,Un=1,N+=". Build with -s ASSERTIONS=1 for more info.";var O=new WebAssembly.RuntimeError(N);throw f(O),O}var k1="data:application/octet-stream;base64,";function Wd(N){return N.startsWith(k1)}function hf(N){return N.startsWith("file://")}var Xn;Xn="tfjs-backend-wasm-threaded-simd.wasm",Wd(Xn)||(Xn=R(Xn));function ff(N){try{if(N==Xn&&pt)return new Uint8Array(pt);if($)return $(N);throw"both async and sync fetching of the wasm failed"}catch(O){vu(O)}}function wu(){if(!pt&&(b||w)){if(typeof fetch=="function"&&!hf(Xn))return fetch(Xn,{credentials:"same-origin"}).then(function(N){if(!N.ok)throw"failed to load wasm binary file at '"+Xn+"'";return N.arrayBuffer()}).catch(function(){return ff(Xn)});if(_)return new Promise(function(N,O){_(Xn,function(H){N(new Uint8Array(H))},O)})}return Promise.resolve().then(function(){return ff(Xn)})}function I1(){var N={env:Tf,wasi_snapshot_preview1:Tf};function O(Te,Me){var Lt=Te.exports;if(d.asm=Lt,_1(d.asm.emscripten_tls_init),Us=d.asm.__indirect_function_table,U4(d.asm.__wasm_call_ctors),Tt=Me,!S){var vr=ze.unusedWorkers.length;ze.unusedWorkers.forEach(function(wr){ze.loadWasmModuleToWorker(wr,function(){--vr||G4("wasm-instantiate")})})}}S||Bd("wasm-instantiate");function H(Te){O(Te.instance,Te.module)}function te(Te){return wu().then(function(Me){return WebAssembly.instantiate(Me,N)}).then(function(Me){return Me}).then(Te,function(Me){Q("failed to asynchronously prepare wasm: "+Me),vu(Me)})}function Ae(){return!pt&&typeof WebAssembly.instantiateStreaming=="function"&&!Wd(Xn)&&!hf(Xn)&&typeof fetch=="function"?fetch(Xn,{credentials:"same-origin"}).then(function(Te){var Me=WebAssembly.instantiateStreaming(Te,N);return Me.then(H,function(Lt){return Q("wasm streaming compile failed: "+Lt),Q("falling back to ArrayBuffer instantiation"),te(H)})}):te(H)}if(d.instantiateWasm)try{var ve=d.instantiateWasm(N,O);return ve}catch(Te){return Q("Module.instantiateWasm callback failed with error: "+Te),!1}return Ae().catch(f),{}}var H4,j4,S1={};function mf(N){for(;N.length>0;){var O=N.shift();if(typeof O=="function"){O(d);continue}var H=O.func;typeof H=="number"?O.arg===void 0?Iu(H)():Iu(H)(O.arg):H(O.arg===void 0?null:O.arg)}}function ku(N){var O=Jg(),H=N();return Df(O),H}function YE(N){return N}function q4(N){var O=/\b_Z[\w\d_]+/g;return N.replace(O,function(H){var te=H;return H===te?H:te+" ["+H+"]"})}function C1(N){u()[N>>2]=0;var O=ze.pthreads[N];delete ze.pthreads[N],O.worker.terminate(),Yg(N),ze.runningWorkers.splice(ze.runningWorkers.indexOf(O.worker),1),O.worker.pthread=void 0}function T1(N){var O=ze.pthreads[N];O.worker.postMessage({cmd:"cancel"})}function gf(N){var O=ze.pthreads[N];if(O){u()[N>>2]=0;var H=O.worker;ze.returnWorkerToPool(H)}}function yf(N){BR(N)}function N1(N){if(N instanceof qd||N=="unwind")return Un;A(1,N)}var ze={unusedWorkers:[],runningWorkers:[],tlsInitFunctions:[],init:function(){S?ze.initWorker():ze.initMainThread()},initMainThread:function(){for(var N=8,O=0;O<N;++O)ze.allocateUnusedWorker()},initWorker:function(){At=!1},pthreads:{},setExitStatus:function(N){Un=N},terminateAllThreads:function(){for(var N in ze.pthreads){var O=ze.pthreads[N];O&&O.worker&&ze.returnWorkerToPool(O.worker)}for(var H=0;H<ze.unusedWorkers.length;++H){var te=ze.unusedWorkers[H];te.terminate()}ze.unusedWorkers=[]},returnWorkerToPool:function(N){ze.runWithoutMainThreadQueuedCalls(function(){delete ze.pthreads[N.pthread.threadInfoStruct],ze.unusedWorkers.push(N),ze.runningWorkers.splice(ze.runningWorkers.indexOf(N),1),Yg(N.pthread.threadInfoStruct),N.pthread=void 0})},runWithoutMainThreadQueuedCalls:function(N){u()[ov>>2]=0;try{N()}finally{u()[ov>>2]=1}},receiveObjectTransfer:function(N){},threadInit:function(){for(var N in ze.tlsInitFunctions)ze.tlsInitFunctions[N]()},loadWasmModuleToWorker:function(N,O){N.onmessage=H=>{var te=H.data,Ae=te.cmd;if(N.pthread&&(ze.currentProxiedOperationCallerThread=N.pthread.threadInfoStruct),te.targetThread&&te.targetThread!=_f()){var ve=ze.pthreads[te.targetThread];ve?ve.worker.postMessage(te,te.transferList):Q('Internal error! Worker sent a message "'+Ae+'" to target pthread '+te.targetThread+", but that thread no longer exists!"),ze.currentProxiedOperationCallerThread=void 0;return}Ae==="processQueuedMainThreadWork"?tv():Ae==="spawnThread"?xf(te):Ae==="cleanupThread"?gf(te.thread):Ae==="killThread"?C1(te.thread):Ae==="cancelThread"?T1(te.thread):Ae==="loaded"?(N.loaded=!0,O&&O(N),N.runPthread&&(N.runPthread(),delete N.runPthread)):Ae==="print"?ee("Thread "+te.threadId+": "+te.text):Ae==="printErr"?Q("Thread "+te.threadId+": "+te.text):Ae==="alert"?alert("Thread "+te.threadId+": "+te.text):te.target==="setimmediate"?N.postMessage(te):Ae==="onAbort"?d.onAbort&&d.onAbort(te.arg):Q("worker sent an unknown command "+Ae),ze.currentProxiedOperationCallerThread=void 0},N.onerror=H=>{var te="worker sent an error!";throw Q(te+" "+H.filename+":"+H.lineno+": "+H.message),H},k&&(N.on("message",function(H){N.onmessage({data:H})}),N.on("error",function(H){N.onerror(H)}),N.on("detachedExit",function(){})),N.postMessage({cmd:"load",urlOrBlob:d.mainScriptUrlOrBlob||s,wasmMemory:$e,wasmModule:Tt})},allocateUnusedWorker:function(){var N=R("tfjs-backend-wasm-threaded-simd.worker.js");ze.unusedWorkers.push(new Worker(N))},getNewWorker:function(){return ze.unusedWorkers.length==0&&(ze.allocateUnusedWorker(),ze.loadWasmModuleToWorker(ze.unusedWorkers[0])),ze.unusedWorkers.pop()}};function E1(){var N=_f(),O=u()[N+44>>2],H=u()[N+48>>2],te=O-H;av(O,te),Df(O)}d.establishStackSpace=E1;function Af(N){if(S)return Ei(1,0,N);try{yf(N)}catch(O){N1(O)}}var Ti=[];function Iu(N){var O=Ti[N];return O||(N>=Ti.length&&(Ti.length=N+1),Ti[N]=O=Us.get(N)),O}function R1(N,O){return Iu(N)(O)}d.invokeEntryPoint=R1;function X4(){var N=new Error;if(!N.stack){try{throw new Error}catch(O){N=O}if(!N.stack)return"(no stack trace available)"}return N.stack.toString()}function _1(N,O,H){ze.tlsInitFunctions.push(N)}function K4(N,O){Us.set(N,O),Ti[N]=O}var Ni;k?Ni=()=>{var N=process.hrtime();return N[0]*1e3+N[1]/1e6}:S?Ni=()=>performance.now()-d.__performance_now_clock_drift:Ni=()=>performance.now();var D1=!0;function $1(N){return u()[ev()>>2]=N,N}function P1(N,O){var H;if(N===0)H=Date.now();else if((N===1||N===4)&&D1)H=Ni();else return $1(28),-1;return u()[O>>2]=H/1e3|0,u()[O+4>>2]=H%1e3*1e3*1e3|0,0}function F1(N,O){return P1(N,O)}function O1(N){nv(N,!w,1,!b),ze.threadInit()}function M1(N){S?postMessage({cmd:"cleanupThread",thread:N}):gf(N)}function xf(N){var O=ze.getNewWorker();if(!O)return 6;ze.runningWorkers.push(O);var H=ze.pthreads[N.pthread_ptr]={worker:O,threadInfoStruct:N.pthread_ptr};O.pthread=H;var te={cmd:"run",start_routine:N.startRoutine,arg:N.arg,threadInfoStruct:N.pthread_ptr};return O.runPthread=()=>{te.time=performance.now(),O.postMessage(te,N.transferList)},O.loaded&&(O.runPthread(),delete O.runPthread),0}function z1(N,O,H,te){if(typeof SharedArrayBuffer=="undefined")return Q("Current environment does not support SharedArrayBuffer, pthreads are not available!"),6;var Ae=[],ve=0;if(S&&(Ae.length===0||ve))return sv(687865856,N,O,H,te);if(ve)return ve;var Te={startRoutine:H,pthread_ptr:N,arg:te,transferList:Ae};return S?(Te.cmd="spawnThread",postMessage(Te,Ae),0):xf(Te)}function L1(){return 2097152}function B1(N,O){if(N==O)postMessage({cmd:"processQueuedMainThreadWork"});else if(S)postMessage({targetThread:N,cmd:"processThreadQueue"});else{var H=ze.pthreads[N],te=H&&H.worker;if(!te)return;te.postMessage({cmd:"processThreadQueue"})}return 1}function W1(){vu("")}function V1(){k||w||Y("Blocking on the main thread is very dangerous, see https://emscripten.org/docs/porting/pthreads.html#blocking-on-the-main-browser-thread")}function bf(){return 2147483648}function U1(N,O,H){o().copyWithin(N,O,O+H)}function G1(){return k?f_().cpus().length:navigator.hardwareConcurrency}function Ei(N,O){var H=arguments.length-2,te=arguments;return ku(function(){for(var Ae=H,ve=Ru(Ae*8),Te=ve>>3,Me=0;Me<H;Me++){var Lt=te[2+Me];p()[Te+Me]=Lt}return rv(N,Ae,ve,O)})}var Vd=[];function H1(N,O,H){Vd.length=O;for(var te=H>>3,Ae=0;Ae<O;Ae++)Vd[Ae]=p()[te+Ae];var ve=N<0,Te=ve?S1[-N-1]:cg[N];return Te.apply(null,Vd)}function j1(N){try{return $e.grow(N-jn.byteLength+65535>>>16),yr($e.buffer),1}catch(O){}}function q1(N){var O=o().length;if(N=N>>>0,N<=O)return!1;var H=bf();if(N>H)return!1;for(var te=1;te<=4;te*=2){var Ae=O*(1+.2/te);Ae=Math.min(Ae,N+100663296);var ve=Math.min(H,xu(Math.max(N,Ae),65536)),Te=j1(ve);if(Te)return!0}return!1}var Je={inEventHandler:0,removeAllEventListeners:function(){for(var N=Je.eventHandlers.length-1;N>=0;--N)Je._removeHandler(N);Je.eventHandlers=[],Je.deferredCalls=[]},registerRemoveEventListeners:function(){Je.removeEventListenersRegistered||(x1.push(Je.removeAllEventListeners),Je.removeEventListenersRegistered=!0)},deferredCalls:[],deferCall:function(N,O,H){function te(Te,Me){if(Te.length!=Me.length)return!1;for(var Lt in Te)if(Te[Lt]!=Me[Lt])return!1;return!0}for(var Ae in Je.deferredCalls){var ve=Je.deferredCalls[Ae];if(ve.targetFunction==N&&te(ve.argsList,H))return}Je.deferredCalls.push({targetFunction:N,precedence:O,argsList:H}),Je.deferredCalls.sort(function(Te,Me){return Te.precedence<Me.precedence})},removeDeferredCalls:function(N){for(var O=0;O<Je.deferredCalls.length;++O)Je.deferredCalls[O].targetFunction==N&&(Je.deferredCalls.splice(O,1),--O)},canPerformEventHandlerRequests:function(){return Je.inEventHandler&&Je.currentEventHandler.allowsDeferredCalls},runDeferredCalls:function(){if(!!Je.canPerformEventHandlerRequests())for(var N=0;N<Je.deferredCalls.length;++N){var O=Je.deferredCalls[N];Je.deferredCalls.splice(N,1),--N,O.targetFunction.apply(null,O.argsList)}},eventHandlers:[],removeAllHandlersOnTarget:function(N,O){for(var H=0;H<Je.eventHandlers.length;++H)Je.eventHandlers[H].target==N&&(!O||O==Je.eventHandlers[H].eventTypeString)&&Je._removeHandler(H--)},_removeHandler:function(N){var O=Je.eventHandlers[N];O.target.removeEventListener(O.eventTypeString,O.eventListenerFunc,O.useCapture),Je.eventHandlers.splice(N,1)},registerOrRemoveHandler:function(N){var O=function(Ae){++Je.inEventHandler,Je.currentEventHandler=N,Je.runDeferredCalls(),N.handlerFunc(Ae),Je.runDeferredCalls(),--Je.inEventHandler};if(N.callbackfunc)N.eventListenerFunc=O,N.target.addEventListener(N.eventTypeString,O,N.useCapture),Je.eventHandlers.push(N),Je.registerRemoveEventListeners();else for(var H=0;H<Je.eventHandlers.length;++H)Je.eventHandlers[H].target==N.target&&Je.eventHandlers[H].eventTypeString==N.eventTypeString&&Je._removeHandler(H--)},queueEventHandlerOnThread_iiii:function(N,O,H,te,Ae){ku(function(){var ve=Ru(12);u()[ve>>2]=H,u()[ve+4>>2]=te,u()[ve+8>>2]=Ae,Zg(N,637534208,O,te,ve)})},getTargetThreadForEventCallback:function(N){switch(N){case 1:return 0;case 2:return ze.currentProxiedOperationCallerThread;default:return N}},getNodeNameForTarget:function(N){return N?N==window?"#window":N==screen?"#screen":N&&N.nodeName?N.nodeName:"":""},fullscreenEnabled:function(){return document.fullscreenEnabled||document.webkitFullscreenEnabled}};function X1(N){var O=Au(N)+1,H=Kg(O);return ra(N,H,O),H}function K1(N,O,H,te){ku(function(){var Ae=Ru(12),ve=0;O&&(ve=X1(O)),u()[Ae>>2]=ve,u()[Ae+4>>2]=H,u()[Ae+8>>2]=te,Zg(N,657457152,0,ve,Ae)})}function Z1(N,O,H,te){O=O?Hn(O):"",K1(N,O,H,te)}function Y1(N){return N>2?Hn(N):N}var J1=[0,typeof document!="undefined"?document:0,typeof window!="undefined"?window:0];function Q1(N){N=Y1(N);var O=J1[N]||(typeof document!="undefined"?document.querySelector(N):void 0);return O}function Ud(N){return Q1(N)}function vf(N,O,H){var te=Ud(N);if(!te)return-4;if(te.canvasSharedPtr&&(u()[te.canvasSharedPtr>>2]=O,u()[te.canvasSharedPtr+4>>2]=H),te.offscreenCanvas||!te.controlTransferredOffscreen){te.offscreenCanvas&&(te=te.offscreenCanvas);var Ae=!1;if(te.GLctxObject&&te.GLctxObject.GLctx){var ve=te.GLctxObject.GLctx.getParameter(2978);Ae=ve[0]===0&&ve[1]===0&&ve[2]===te.width&&ve[3]===te.height}te.width=O,te.height=H,Ae&&te.GLctxObject.GLctx.viewport(0,0,O,H)}else if(te.canvasSharedPtr){var Te=u()[te.canvasSharedPtr+8>>2];return Z1(Te,N,O,H),1}else return-4;return 0}function wf(N,O,H){return S?Ei(2,1,N,O,H):vf(N,O,H)}function eg(N,O,H){var te=Ud(N);return te?vf(N,O,H):wf(N,O,H)}function tg(){throw"unwind"}function ng(N){var O=N.getExtension("ANGLE_instanced_arrays");if(O)return N.vertexAttribDivisor=function(H,te){O.vertexAttribDivisorANGLE(H,te)},N.drawArraysInstanced=function(H,te,Ae,ve){O.drawArraysInstancedANGLE(H,te,Ae,ve)},N.drawElementsInstanced=function(H,te,Ae,ve,Te){O.drawElementsInstancedANGLE(H,te,Ae,ve,Te)},1}function sg(N){var O=N.getExtension("OES_vertex_array_object");if(O)return N.createVertexArray=function(){return O.createVertexArrayOES()},N.deleteVertexArray=function(H){O.deleteVertexArrayOES(H)},N.bindVertexArray=function(H){O.bindVertexArrayOES(H)},N.isVertexArray=function(H){return O.isVertexArrayOES(H)},1}function rg(N){var O=N.getExtension("WEBGL_draw_buffers");if(O)return N.drawBuffers=function(H,te){O.drawBuffersWEBGL(H,te)},1}function ag(N){return!!(N.multiDrawWebgl=N.getExtension("WEBGL_multi_draw"))}var zt={counter:1,buffers:[],programs:[],framebuffers:[],renderbuffers:[],textures:[],shaders:[],vaos:[],contexts:{},offscreenCanvases:{},queries:[],stringCache:{},unpackAlignment:4,recordError:function(O){zt.lastError||(zt.lastError=O)},getNewId:function(N){for(var O=zt.counter++,H=N.length;H<O;H++)N[H]=null;return O},getSource:function(N,O,H,te){for(var Ae="",ve=0;ve<O;++ve){var Te=te?u()[te+ve*4>>2]:-1;Ae+=Hn(u()[H+ve*4>>2],Te<0?void 0:Te)}return Ae},createContext:function(N,O){N.getContextSafariWebGL2Fixed||(N.getContextSafariWebGL2Fixed=N.getContext,N.getContext=function(Ae,ve){var Te=N.getContextSafariWebGL2Fixed(Ae,ve);return Ae=="webgl"==Te instanceof WebGLRenderingContext?Te:null});var H=N.getContext("webgl",O);if(!H)return 0;var te=zt.registerContext(H,O);return te},registerContext:function(N,O){var H=Kg(8);u()[H+4>>2]=_f();var te={handle:H,attributes:O,version:O.majorVersion,GLctx:N};return N.canvas&&(N.canvas.GLctxObject=te),zt.contexts[H]=te,(typeof O.enableExtensionsByDefault=="undefined"||O.enableExtensionsByDefault)&&zt.initExtensions(te),H},makeContextCurrent:function(N){return zt.currentContext=zt.contexts[N],d.ctx=Cf=zt.currentContext&&zt.currentContext.GLctx,!(N&&!Cf)},getContext:function(N){return zt.contexts[N]},deleteContext:function(N){zt.currentContext===zt.contexts[N]&&(zt.currentContext=null),typeof Je=="object"&&Je.removeAllHandlersOnTarget(zt.contexts[N].GLctx.canvas),zt.contexts[N]&&zt.contexts[N].GLctx.canvas&&(zt.contexts[N].GLctx.canvas.GLctxObject=void 0),Q4(zt.contexts[N].handle),zt.contexts[N]=null},initExtensions:function(N){if(N||(N=zt.currentContext),!N.initExtensionsDone){N.initExtensionsDone=!0;var O=N.GLctx;ng(O),sg(O),rg(O),O.disjointTimerQueryExt=O.getExtension("EXT_disjoint_timer_query"),ag(O);var H=O.getSupportedExtensions()||[];H.forEach(function(te){!te.includes("lose_context")&&!te.includes("debug")&&O.getExtension(te)})}}},og=["default","low-power","high-performance"];function ig(N,O){var H=O>>2,te=u()[H+6],Ae={alpha:!!u()[H+0],depth:!!u()[H+1],stencil:!!u()[H+2],antialias:!!u()[H+3],premultipliedAlpha:!!u()[H+4],preserveDrawingBuffer:!!u()[H+5],powerPreference:og[te],failIfMajorPerformanceCaveat:!!u()[H+7],majorVersion:u()[H+8],minorVersion:u()[H+9],enableExtensionsByDefault:u()[H+10],explicitSwapControl:u()[H+11],proxyContextToMainThread:u()[H+12],renderViaOffscreenBackBuffer:u()[H+13]},ve=Ud(N);if(!ve||Ae.explicitSwapControl)return 0;var Te=zt.createContext(ve,Ae);return Te}function lg(N,O){return ig(N,O)}var Su={mappings:{},buffers:[null,[],[]],printChar:function(N,O){var H=Su.buffers[N];O===0||O===10?((N===1?ee:Q)(Vs(H,0)),H.length=0):H.push(O)},varargs:void 0,get:function(){Su.varargs+=4;var N=u()[Su.varargs-4>>2];return N},getStr:function(N){var O=Hn(N);return O},get64:function(N,O){return N}};function kf(N){return S?Ei(3,1,N):0}function If(N,O,H,te,Ae){if(S)return Ei(4,1,N,O,H,te,Ae)}function Sf(N,O,H,te){if(S)return Ei(5,1,N,O,H,te);for(var Ae=0,ve=0;ve<H;ve++){var Te=u()[O>>2],Me=u()[O+4>>2];O+=8;for(var Lt=0;Lt<Me;Lt++)Su.printChar(N,o()[Te+Lt]);Ae+=Me}return u()[te>>2]=Ae,0}function ug(N){Be(N)}ze.init();var Cf,cg=[null,Af,wf,kf,If,Sf],Z4=!1,Tf={__clock_gettime:F1,__emscripten_init_main_thread_js:O1,__emscripten_thread_cleanup:M1,__pthread_create_js:z1,_emscripten_default_pthread_stack_size:L1,_emscripten_notify_thread_queue:B1,abort:W1,emscripten_check_blocking_allowed:V1,emscripten_get_heap_max:bf,emscripten_get_now:Ni,emscripten_memcpy_big:U1,emscripten_num_logical_cores:G1,emscripten_receive_on_main_thread_js:H1,emscripten_resize_heap:q1,emscripten_set_canvas_element_size:eg,emscripten_unwind_to_js_event_loop:tg,emscripten_webgl_create_context:lg,exit:yf,fd_close:kf,fd_seek:If,fd_write:Sf,memory:$e||d.wasmMemory,setTempRet0:ug},Y4=I1(),dg=d.___wasm_call_ctors=function(){return(dg=d.___wasm_call_ctors=d.asm.__wasm_call_ctors).apply(null,arguments)},pg=d._init=function(){return(pg=d._init=d.asm.init).apply(null,arguments)},hg=d._init_with_threads_count=function(){return(hg=d._init_with_threads_count=d.asm.init_with_threads_count).apply(null,arguments)},fg=d._get_threads_count=function(){return(fg=d._get_threads_count=d.asm.get_threads_count).apply(null,arguments)},mg=d._register_tensor=function(){return(mg=d._register_tensor=d.asm.register_tensor).apply(null,arguments)},gg=d._dispose_data=function(){return(gg=d._dispose_data=d.asm.dispose_data).apply(null,arguments)},yg=d._dispose=function(){return(yg=d._dispose=d.asm.dispose).apply(null,arguments)},Ag=d._Abs=function(){return(Ag=d._Abs=d.asm.Abs).apply(null,arguments)},xg=d._Add=function(){return(xg=d._Add=d.asm.Add).apply(null,arguments)},bg=d._AddN=function(){return(bg=d._AddN=d.asm.AddN).apply(null,arguments)},vg=d._All=function(){return(vg=d._All=d.asm.All).apply(null,arguments)},wg=d._Any=function(){return(wg=d._Any=d.asm.Any).apply(null,arguments)},kg=d._ArgMax=function(){return(kg=d._ArgMax=d.asm.ArgMax).apply(null,arguments)},Ig=d._AvgPool=function(){return(Ig=d._AvgPool=d.asm.AvgPool).apply(null,arguments)},Sg=d._BatchMatMul=function(){return(Sg=d._BatchMatMul=d.asm.BatchMatMul).apply(null,arguments)},Cg=d._Ceil=function(){return(Cg=d._Ceil=d.asm.Ceil).apply(null,arguments)},Tg=d._ClipByValue=function(){return(Tg=d._ClipByValue=d.asm.ClipByValue).apply(null,arguments)},Ng=d._Conv2D=function(){return(Ng=d._Conv2D=d.asm.Conv2D).apply(null,arguments)},Eg=d._Conv2DBackpropInput=function(){return(Eg=d._Conv2DBackpropInput=d.asm.Conv2DBackpropInput).apply(null,arguments)},Rg=d._Cos=function(){return(Rg=d._Cos=d.asm.Cos).apply(null,arguments)},_g=d._Cosh=function(){return(_g=d._Cosh=d.asm.Cosh).apply(null,arguments)},Dg=d._CropAndResize=function(){return(Dg=d._CropAndResize=d.asm.CropAndResize).apply(null,arguments)},$g=d._Cumprod=function(){return($g=d._Cumprod=d.asm.Cumprod).apply(null,arguments)},Pg=d._Cumsum=function(){return(Pg=d._Cumsum=d.asm.Cumsum).apply(null,arguments)},Fg=d._DepthToSpace=function(){return(Fg=d._DepthToSpace=d.asm.DepthToSpace).apply(null,arguments)},Og=d._DepthwiseConv2dNative=function(){return(Og=d._DepthwiseConv2dNative=d.asm.DepthwiseConv2dNative).apply(null,arguments)},Mg=d._Elu=function(){return(Mg=d._Elu=d.asm.Elu).apply(null,arguments)},zg=d._Equal=function(){return(zg=d._Equal=d.asm.Equal).apply(null,arguments)},Lg=d._Exp=function(){return(Lg=d._Exp=d.asm.Exp).apply(null,arguments)},Bg=d._FlipLeftRight=function(){return(Bg=d._FlipLeftRight=d.asm.FlipLeftRight).apply(null,arguments)},Wg=d._Floor=function(){return(Wg=d._Floor=d.asm.Floor).apply(null,arguments)},Vg=d._FloorDiv=function(){return(Vg=d._FloorDiv=d.asm.FloorDiv).apply(null,arguments)},Ug=d._FusedBatchNorm=function(){return(Ug=d._FusedBatchNorm=d.asm.FusedBatchNorm).apply(null,arguments)},Gg=d._FusedConv2D=function(){return(Gg=d._FusedConv2D=d.asm.FusedConv2D).apply(null,arguments)},Nf=d._FusedDepthwiseConv2D=function(){return(Nf=d._FusedDepthwiseConv2D=d.asm.FusedDepthwiseConv2D).apply(null,arguments)},Ef=d._Gather=function(){return(Ef=d._Gather=d.asm.Gather).apply(null,arguments)},Gd=d._GatherNd=function(){return(Gd=d._GatherNd=d.asm.GatherNd).apply(null,arguments)},Hg=d._Greater=function(){return(Hg=d._Greater=d.asm.Greater).apply(null,arguments)},jg=d._GreaterEqual=function(){return(jg=d._GreaterEqual=d.asm.GreaterEqual).apply(null,arguments)},Cu=d._LeakyRelu=function(){return(Cu=d._LeakyRelu=d.asm.LeakyRelu).apply(null,arguments)},Hd=d._Less=function(){return(Hd=d._Less=d.asm.Less).apply(null,arguments)},jd=d._LessEqual=function(){return(jd=d._LessEqual=d.asm.LessEqual).apply(null,arguments)},J4=d._Log=function(){return(J4=d._Log=d.asm.Log).apply(null,arguments)},Tu=d._LogicalAnd=function(){return(Tu=d._LogicalAnd=d.asm.LogicalAnd).apply(null,arguments)},Nu=d._LogicalNot=function(){return(Nu=d._LogicalNot=d.asm.LogicalNot).apply(null,arguments)},qg=d._LogicalOr=function(){return(qg=d._LogicalOr=d.asm.LogicalOr).apply(null,arguments)},K=d._LogicalXor=function(){return(K=d._LogicalXor=d.asm.LogicalXor).apply(null,arguments)},se=d._Max=function(){return(se=d._Max=d.asm.Max).apply(null,arguments)},xe=d._MaxPool=function(){return(xe=d._MaxPool=d.asm.MaxPool).apply(null,arguments)},De=d._Maximum=function(){return(De=d._Maximum=d.asm.Maximum).apply(null,arguments)},ht=d._Mean=function(){return(ht=d._Mean=d.asm.Mean).apply(null,arguments)},yt=d._Min=function(){return(yt=d._Min=d.asm.Min).apply(null,arguments)},et=d._Minimum=function(){return(et=d._Minimum=d.asm.Minimum).apply(null,arguments)},Ze=d._MirrorPad=function(){return(Ze=d._MirrorPad=d.asm.MirrorPad).apply(null,arguments)},en=d._Multiply=function(){return(en=d._Multiply=d.asm.Multiply).apply(null,arguments)},xr=d._Neg=function(){return(xr=d._Neg=d.asm.Neg).apply(null,arguments)},br=d._NonMaxSuppressionV3=function(){return(br=d._NonMaxSuppressionV3=d.asm.NonMaxSuppressionV3).apply(null,arguments)},Eu=d._NonMaxSuppressionV4=function(){return(Eu=d._NonMaxSuppressionV4=d.asm.NonMaxSuppressionV4).apply(null,arguments)},Ri=d._NonMaxSuppressionV5=function(){return(Ri=d._NonMaxSuppressionV5=d.asm.NonMaxSuppressionV5).apply(null,arguments)},Xg=d._NotEqual=function(){return(Xg=d._NotEqual=d.asm.NotEqual).apply(null,arguments)},Kn=d._OneHot=function(){return(Kn=d._OneHot=d.asm.OneHot).apply(null,arguments)},za=d._PadV2=function(){return(za=d._PadV2=d.asm.PadV2).apply(null,arguments)},Rf=d._Pow=function(){return(Rf=d._Pow=d.asm.Pow).apply(null,arguments)},JE=d._Prelu=function(){return(JE=d._Prelu=d.asm.Prelu).apply(null,arguments)},QE=d._Prod=function(){return(QE=d._Prod=d.asm.Prod).apply(null,arguments)},eR=d._RealDiv=function(){return(eR=d._RealDiv=d.asm.RealDiv).apply(null,arguments)},tR=d._Relu=function(){return(tR=d._Relu=d.asm.Relu).apply(null,arguments)},nR=d._Relu6=function(){return(nR=d._Relu6=d.asm.Relu6).apply(null,arguments)},sR=d._ResizeBilinear=function(){return(sR=d._ResizeBilinear=d.asm.ResizeBilinear).apply(null,arguments)},rR=d._ResizeNearestNeighbor=function(){return(rR=d._ResizeNearestNeighbor=d.asm.ResizeNearestNeighbor).apply(null,arguments)},aR=d._Reverse=function(){return(aR=d._Reverse=d.asm.Reverse).apply(null,arguments)},oR=d._RotateWithOffset=function(){return(oR=d._RotateWithOffset=d.asm.RotateWithOffset).apply(null,arguments)},iR=d._Round=function(){return(iR=d._Round=d.asm.Round).apply(null,arguments)},lR=d._Rsqrt=function(){return(lR=d._Rsqrt=d.asm.Rsqrt).apply(null,arguments)},uR=d._ScatterNd=function(){return(uR=d._ScatterNd=d.asm.ScatterNd).apply(null,arguments)},cR=d._SelectV2=function(){return(cR=d._SelectV2=d.asm.SelectV2).apply(null,arguments)},dR=d._Sigmoid=function(){return(dR=d._Sigmoid=d.asm.Sigmoid).apply(null,arguments)},pR=d._Sin=function(){return(pR=d._Sin=d.asm.Sin).apply(null,arguments)},hR=d._Softmax=function(){return(hR=d._Softmax=d.asm.Softmax).apply(null,arguments)},fR=d._SparseFillEmptyRows=function(){return(fR=d._SparseFillEmptyRows=d.asm.SparseFillEmptyRows).apply(null,arguments)},mR=d._SparseReshape=function(){return(mR=d._SparseReshape=d.asm.SparseReshape).apply(null,arguments)},gR=d._SparseSegmentReduction=function(){return(gR=d._SparseSegmentReduction=d.asm.SparseSegmentReduction).apply(null,arguments)},yR=d._Sqrt=function(){return(yR=d._Sqrt=d.asm.Sqrt).apply(null,arguments)},AR=d._Square=function(){return(AR=d._Square=d.asm.Square).apply(null,arguments)},xR=d._SquaredDifference=function(){return(xR=d._SquaredDifference=d.asm.SquaredDifference).apply(null,arguments)},bR=d._Step=function(){return(bR=d._Step=d.asm.Step).apply(null,arguments)},vR=d._StridedSlice=function(){return(vR=d._StridedSlice=d.asm.StridedSlice).apply(null,arguments)},wR=d._Sub=function(){return(wR=d._Sub=d.asm.Sub).apply(null,arguments)},kR=d._Sum=function(){return(kR=d._Sum=d.asm.Sum).apply(null,arguments)},IR=d._Tan=function(){return(IR=d._Tan=d.asm.Tan).apply(null,arguments)},SR=d._Tanh=function(){return(SR=d._Tanh=d.asm.Tanh).apply(null,arguments)},CR=d._Tile=function(){return(CR=d._Tile=d.asm.Tile).apply(null,arguments)},TR=d._TopK=function(){return(TR=d._TopK=d.asm.TopK).apply(null,arguments)},NR=d._Transform=function(){return(NR=d._Transform=d.asm.Transform).apply(null,arguments)},ER=d._Transpose=function(){return(ER=d._Transpose=d.asm.Transpose).apply(null,arguments)},RR=d.__FusedMatMul=function(){return(RR=d.__FusedMatMul=d.asm._FusedMatMul).apply(null,arguments)},Kg=d._malloc=function(){return(Kg=d._malloc=d.asm.malloc).apply(null,arguments)},Q4=d._free=function(){return(Q4=d._free=d.asm.free).apply(null,arguments)},_R=d._emscripten_tls_init=function(){return(_R=d._emscripten_tls_init=d.asm.emscripten_tls_init).apply(null,arguments)},ev=d.___errno_location=function(){return(ev=d.___errno_location=d.asm.__errno_location).apply(null,arguments)},_f=d._pthread_self=function(){return(_f=d._pthread_self=d.asm.pthread_self).apply(null,arguments)},tv=d._emscripten_main_thread_process_queued_calls=function(){return(tv=d._emscripten_main_thread_process_queued_calls=d.asm.emscripten_main_thread_process_queued_calls).apply(null,arguments)},DR=d.__emscripten_thread_crashed=function(){return(DR=d.__emscripten_thread_crashed=d.asm._emscripten_thread_crashed).apply(null,arguments)},nv=d.__emscripten_thread_init=function(){return(nv=d.__emscripten_thread_init=d.asm._emscripten_thread_init).apply(null,arguments)},$R=d._emscripten_current_thread_process_queued_calls=function(){return($R=d._emscripten_current_thread_process_queued_calls=d.asm.emscripten_current_thread_process_queued_calls).apply(null,arguments)},PR=d._emscripten_main_browser_thread_id=function(){return(PR=d._emscripten_main_browser_thread_id=d.asm.emscripten_main_browser_thread_id).apply(null,arguments)},FR=d._emscripten_sync_run_in_main_thread_2=function(){return(FR=d._emscripten_sync_run_in_main_thread_2=d.asm.emscripten_sync_run_in_main_thread_2).apply(null,arguments)},sv=d._emscripten_sync_run_in_main_thread_4=function(){return(sv=d._emscripten_sync_run_in_main_thread_4=d.asm.emscripten_sync_run_in_main_thread_4).apply(null,arguments)},rv=d._emscripten_run_in_main_runtime_thread_js=function(){return(rv=d._emscripten_run_in_main_runtime_thread_js=d.asm.emscripten_run_in_main_runtime_thread_js).apply(null,arguments)},Zg=d._emscripten_dispatch_to_thread_=function(){return(Zg=d._emscripten_dispatch_to_thread_=d.asm.emscripten_dispatch_to_thread_).apply(null,arguments)},Yg=d.__emscripten_thread_free_data=function(){return(Yg=d.__emscripten_thread_free_data=d.asm._emscripten_thread_free_data).apply(null,arguments)},OR=d.__emscripten_thread_exit=function(){return(OR=d.__emscripten_thread_exit=d.asm._emscripten_thread_exit).apply(null,arguments)},MR=d._memalign=function(){return(MR=d._memalign=d.asm.memalign).apply(null,arguments)},av=d._emscripten_stack_set_limits=function(){return(av=d._emscripten_stack_set_limits=d.asm.emscripten_stack_set_limits).apply(null,arguments)},Jg=d.stackSave=function(){return(Jg=d.stackSave=d.asm.stackSave).apply(null,arguments)},Df=d.stackRestore=function(){return(Df=d.stackRestore=d.asm.stackRestore).apply(null,arguments)},Ru=d.stackAlloc=function(){return(Ru=d.stackAlloc=d.asm.stackAlloc).apply(null,arguments)},zR=d.dynCall_iijjiiii=function(){return(zR=d.dynCall_iijjiiii=d.asm.dynCall_iijjiiii).apply(null,arguments)},LR=d.dynCall_jiji=function(){return(LR=d.dynCall_jiji=d.asm.dynCall_jiji).apply(null,arguments)},ov=d.__emscripten_allow_main_runtime_queued_calls=21672;d.cwrap=Gn,d.keepRuntimeAlive=Ci,d.PThread=ze,d.PThread=ze,d.wasmMemory=$e,d.ExitStatus=qd;var $f;function qd(N){this.name="ExitStatus",this.message="Program terminated with exit("+N+")",this.status=N}Ar=function N(){$f||Qg(),$f||(Ar=N)};function Qg(N){if(N=N||y,Ma>0)return;if(S){h(d),zd(),postMessage({cmd:"loaded"});return}if(qn(),Ma>0)return;function O(){$f||($f=!0,d.calledRun=!0,!It&&(zd(),h(d),d.onRuntimeInitialized&&d.onRuntimeInitialized(),w1()))}d.setStatus?(d.setStatus("Running..."),setTimeout(function(){setTimeout(function(){d.setStatus("")},1),O()},1)):O()}d.run=Qg;function BR(N,O){if(Un=N,!O&&S)throw Af(N),"unwind";Ci()||v1(),WR(N)}function WR(N){Un=N,Ci()||(ze.terminateAllThreads(),d.onExit&&d.onExit(N),It=!0),A(N,new qd(N))}if(d.preInit)for(typeof d.preInit=="function"&&(d.preInit=[d.preInit]);d.preInit.length>0;)d.preInit.pop()();Qg();var Pf;m&&(Pf={uncaughtException:process.listeners("uncaughtException").filter(function(N){return!m.uncaughtException.indexOf(N)>-1}),unhandledRejection:process.listeners("unhandledRejection").filter(function(N){return!m.unhandledRejection.indexOf(N)>-1})});var Ff;if(typeof WasmBackendModule!="undefined")Ff=WasmBackendModule;else if(typeof r!="undefined")Ff=r;else throw new Error("Could not find wasm module in post.js");if(Pf){var VR=Ff._dispose;Ff._dispose=function(){VR(),Pf.uncaughtException.forEach(function(N){process.removeListener("uncaughtException",N)}),Pf.unhandledRejection.forEach(function(N){process.removeListener("unhandledRejection",N)})}}return r.ready}})();typeof e=="object"&&typeof t=="object"?t.exports=n:typeof define=="function"&&define.amd?define([],function(){return n}):typeof e=="object"&&(e.WasmBackendModuleThreadedSimd=n)}}),g_=ln({"node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm-threaded-simd.worker.js"(e,t){t.exports.wasmWorkerContents=`"use strict";var Module={};var ENVIRONMENT_IS_NODE=typeof process==="object"&&typeof process.versions==="object"&&typeof process.versions.node==="string";if(ENVIRONMENT_IS_NODE){var nodeWorkerThreads=require("worker_threads");var parentPort=nodeWorkerThreads.parentPort;parentPort.on("message",function(data){onmessage({data:data})});var fs=require("fs");Object.assign(global,{self:global,require:require,Module:Module,location:{href:__filename},Worker:nodeWorkerThreads.Worker,importScripts:function(f){(0,eval)(fs.readFileSync(f,"utf8"))},postMessage:function(msg){parentPort.postMessage(msg)},performance:global.performance||{now:function(){return Date.now()}}})}function threadPrintErr(){var text=Array.prototype.slice.call(arguments).join(" ");if(ENVIRONMENT_IS_NODE){fs.writeSync(2,text+"
+");return}console.error(text)}function threadAlert(){var text=Array.prototype.slice.call(arguments).join(" ");postMessage({cmd:"alert",text:text,threadId:Module["_pthread_self"]()})}var err=threadPrintErr;self.alert=threadAlert;Module["instantiateWasm"]=((info,receiveInstance)=>{var instance=new WebAssembly.Instance(Module["wasmModule"],info);receiveInstance(instance);Module["wasmModule"]=null;return instance.exports});self.onmessage=(e=>{try{if(e.data.cmd==="load"){Module["wasmModule"]=e.data.wasmModule;Module["wasmMemory"]=e.data.wasmMemory;Module["buffer"]=Module["wasmMemory"].buffer;Module["ENVIRONMENT_IS_PTHREAD"]=true;if(typeof e.data.urlOrBlob==="string"){importScripts(e.data.urlOrBlob)}else{var objectUrl=URL.createObjectURL(e.data.urlOrBlob);importScripts(objectUrl);URL.revokeObjectURL(objectUrl)}WasmBackendModuleThreadedSimd(Module).then(function(instance){Module=instance})}else if(e.data.cmd==="run"){Module["__performance_now_clock_drift"]=performance.now()-e.data.time;Module["__emscripten_thread_init"](e.data.threadInfoStruct,0,0,1);Module["establishStackSpace"]();Module["PThread"].receiveObjectTransfer(e.data);Module["PThread"].threadInit();try{var result=Module["invokeEntryPoint"](e.data.start_routine,e.data.arg);if(Module["keepRuntimeAlive"]()){Module["PThread"].setExitStatus(result)}else{Module["__emscripten_thread_exit"](result)}}catch(ex){if(ex!="unwind"){if(ex instanceof Module["ExitStatus"]){if(Module["keepRuntimeAlive"]()){}else{Module["__emscripten_thread_exit"](ex.status)}}else{throw ex}}}}else if(e.data.cmd==="cancel"){if(Module["_pthread_self"]()){Module["__emscripten_thread_exit"](-1)}}else if(e.data.target==="setimmediate"){}else if(e.data.cmd==="processThreadQueue"){if(Module["_pthread_self"]()){Module["_emscripten_current_thread_process_queued_calls"]()}}else if(e.data.cmd==="processProxyingQueue"){if(Module["_pthread_self"]()){Module["_emscripten_proxy_execute_queue"](e.data.queue)}}else{err("worker.js received unknown command "+e.data.cmd);err(e.data)}}catch(ex){err("worker.js onmessage() captured an uncaught exception: "+ex);if(ex&&ex.stack)err(ex.stack);if(Module["__emscripten_thread_crashed"]){Module["__emscripten_thread_crashed"]()}throw ex}});`}}),y_=ln({"node_modules/.pnpm/@tensorflow+tfjs-backend-wasm@3.19.0_hek32lflchivueqv5i4vgonghu/node_modules/@tensorflow/tfjs-backend-wasm/wasm-out/tfjs-backend-wasm.js"(e,t){var n=(()=>{var s=typeof document!="undefined"&&document.currentScript?document.currentScript.src:void 0;return typeof __filename!="undefined"&&(s=s||__filename),function(r){r=r||{};var a=typeof r!="undefined"?r:{},o,i;a.ready=new Promise(function(K,se){o=K,i=se});var l;typeof process!="undefined"&&process.listeners&&(l={uncaughtException:process.listeners("uncaughtException"),unhandledRejection:process.listeners("unhandledRejection")});var u=Object.assign({},a),c=[],p="./this.program",d=(K,se)=>{throw se},h=typeof window=="object",f=typeof importScripts=="function",m=typeof process=="object"&&typeof process.versions=="object"&&typeof process.versions.node=="string",g="";function y(K){return a.locateFile?a.locateFile(K,g):g+K}var x,A,b,w;function k(K){if(K instanceof Hd)return;_("exiting due to exception: "+K)}var S,E,R;m?(f?g=lm().dirname(g)+"/":g=__dirname+"/",R=()=>{E||(S=Ay(),E=lm())},x=function(se,xe){return R(),se=E.normalize(se),S.readFileSync(se,xe?void 0:"utf8")},b=K=>{var se=x(K,!0);return se.buffer||(se=new Uint8Array(se)),se},A=(K,se,xe)=>{R(),K=E.normalize(K),S.readFile(K,function(De,ht){De?xe(De):se(ht.buffer)})},process.argv.length>1&&(p=process.argv[1].replace(/\\/g,"/")),c=process.argv.slice(2),process.on("uncaughtException",function(K){if(!(K instanceof Hd))throw K}),process.on("unhandledRejection",function(K){throw K}),d=(K,se)=>{if(Md())throw process.exitCode=K,se;k(se),process.exit(K)},a.inspect=function(){return"[Emscripten Module object]"}):(h||f)&&(f?g=self.location.href:typeof document!="undefined"&&document.currentScript&&(g=document.currentScript.src),s&&(g=s),g.indexOf("blob:")!==0?g=g.substr(0,g.replace(/[?#].*/,"").lastIndexOf("/")+1):g="",x=K=>{var se=new XMLHttpRequest;return se.open("GET",K,!1),se.send(null),se.responseText},f&&(b=K=>{var se=new XMLHttpRequest;return se.open("GET",K,!1),se.responseType="arraybuffer",se.send(null),new Uint8Array(se.response)}),A=(K,se,xe)=>{var De=new XMLHttpRequest;De.open("GET",K,!0),De.responseType="arraybuffer",De.onload=()=>{if(De.status==200||De.status==0&&De.response){se(De.response);return}xe()},De.onerror=xe,De.send(null)},w=K=>document.title=K);var P=a.print||console.log.bind(console),_=a.printErr||console.warn.bind(console);Object.assign(a,u),u=null,a.arguments&&(c=a.arguments),a.thisProgram&&(p=a.thisProgram),a.quit&&(d=a.quit);var $=4;function T(K){T.shown||(T.shown={}),T.shown[K]||(T.shown[K]=1,_(K))}function F(K,se){if(typeof WebAssembly.Function=="function"){for(var xe={i:"i32",j:"i64",f:"f32",d:"f64"},De={parameters:[],results:se[0]=="v"?[]:[xe[se[0]]]},ht=1;ht<se.length;++ht)De.parameters.push(xe[se[ht]]);return new WebAssembly.Function(De,K)}var yt=[1,0,1,96],et=se.slice(0,1),Ze=se.slice(1),en={i:127,j:126,f:125,d:124};yt.push(Ze.length);for(var ht=0;ht<Ze.length;++ht)yt.push(en[Ze[ht]]);et=="v"?yt.push(0):yt=yt.concat([1,en[et]]),yt[1]=yt.length-2;var xr=new Uint8Array([0,97,115,109,1,0,0,0].concat(yt,[2,7,1,1,101,1,102,0,0,7,5,1,1,102,0,0])),br=new WebAssembly.Module(xr),Eu=new WebAssembly.Instance(br,{e:{f:K}}),Ri=Eu.exports.f;return Ri}var G=[],q;function z(){if(G.length)return G.pop();try{Fa.grow(1)}catch(K){throw K instanceof RangeError?"Unable to grow wasm table. Set ALLOW_TABLE_GROWTH.":K}return Fa.length-1}function Z(K,se){for(var xe=K;xe<K+se;xe++){var De=Bd(xe);De&&q.set(De,xe)}}var B=0,ee=K=>{B=K},Q;a.wasmBinary&&(Q=a.wasmBinary);var oe=a.noExitRuntime||!0;typeof WebAssembly!="object"&&Si("no native wasm support detected");var Y,ae=!1,le;function ye(K,se){K||Si(se)}function we(K){var se=a["_"+K];return se}function Re(K,se,xe,De,ht){var yt={string:function(Kn){var za=0;if(Kn!=null&&Kn!==0){var Rf=(Kn.length<<2)+1;za=Gd(Rf),At(Kn,za,Rf)}return za},array:function(Kn){var za=Gd(Kn.length);return It(Kn,za),za}};function et(Kn){return se==="string"?dt(Kn):se==="boolean"?Boolean(Kn):Kn}var Ze=we(K),en=[],xr=0;if(De)for(var br=0;br<De.length;br++){var Eu=yt[xe[br]];Eu?(xr===0&&(xr=Nf()),en[br]=Eu(De[br])):en[br]=De[br]}var Ri=Ze.apply(null,en);function Xg(Kn){return xr!==0&&Ef(xr),et(Kn)}return Ri=Xg(Ri),Ri}function _e(K,se,xe,De){xe=xe||[];var ht=xe.every(function(et){return et==="number"}),yt=se!=="string";return yt&&ht&&!De?we(K):function(){return Re(K,se,xe,arguments,De)}}var Be=1,Ge=typeof TextDecoder!="undefined"?new TextDecoder("utf8"):void 0;function ot(K,se,xe){for(var De=se+xe,ht=se;K[ht]&&!(ht>=De);)++ht;if(ht-se>16&&K.subarray&&Ge)return Ge.decode(K.subarray(se,ht));for(var yt="";se<ht;){var et=K[se++];if(!(et&128)){yt+=String.fromCharCode(et);continue}var Ze=K[se++]&63;if((et&224)==192){yt+=String.fromCharCode((et&31)<<6|Ze);continue}var en=K[se++]&63;if((et&240)==224?et=(et&15)<<12|Ze<<6|en:et=(et&7)<<18|Ze<<12|en<<6|K[se++]&63,et<65536)yt+=String.fromCharCode(et);else{var xr=et-65536;yt+=String.fromCharCode(55296|xr>>10,56320|xr&1023)}}return yt}function dt(K,se){return K?ot(Gn,K,se):""}function pt(K,se,xe,De){if(!(De>0))return 0;for(var ht=xe,yt=xe+De-1,et=0;et<K.length;++et){var Ze=K.charCodeAt(et);if(Ze>=55296&&Ze<=57343){var en=K.charCodeAt(++et);Ze=65536+((Ze&1023)<<10)|en&1023}if(Ze<=127){if(xe>=yt)break;se[xe++]=Ze}else if(Ze<=2047){if(xe+1>=yt)break;se[xe++]=192|Ze>>6,se[xe++]=128|Ze&63}else if(Ze<=65535){if(xe+2>=yt)break;se[xe++]=224|Ze>>12,se[xe++]=128|Ze>>6&63,se[xe++]=128|Ze&63}else{if(xe+3>=yt)break;se[xe++]=240|Ze>>18,se[xe++]=128|Ze>>12&63,se[xe++]=128|Ze>>6&63,se[xe++]=128|Ze&63}}return se[xe]=0,xe-ht}function At(K,se,xe){return pt(K,Gn,se,xe)}function $e(K){for(var se=0,xe=0;xe<K.length;++xe){var De=K.charCodeAt(xe);De>=55296&&De<=57343&&(De=65536+((De&1023)<<10)|K.charCodeAt(++xe)&1023),De<=127?++se:De<=2047?se+=2:De<=65535?se+=3:se+=4}return se}var Tt=typeof TextDecoder!="undefined"?new TextDecoder("utf-16le"):void 0;function It(K,se){pn.set(K,se)}function Un(K,se,xe){for(var De=0;De<K.length;++De)pn[se++>>0]=K.charCodeAt(De);xe||(pn[se>>0]=0)}function Qt(K,se){return K%se>0&&(K+=se-K%se),K}var bs,pn,Gn,vs,ws,$n,Vs,Hn,sa;function ra(K){bs=K,a.HEAP8=pn=new Int8Array(K),a.HEAP16=vs=new Int16Array(K),a.HEAP32=$n=new Int32Array(K),a.HEAPU8=Gn=new Uint8Array(K),a.HEAPU16=ws=new Uint16Array(K),a.HEAPU32=Vs=new Uint32Array(K),a.HEAPF32=Hn=new Float32Array(K),a.HEAPF64=sa=new Float64Array(K)}var Au=a.INITIAL_MEMORY||16777216,Fa,aa=[],Od=[],xu=[],jn=!1,nf=!1,sf=0;function Md(){return oe||sf>0}function rf(){if(a.preRun)for(typeof a.preRun=="function"&&(a.preRun=[a.preRun]);a.preRun.length;)lf(a.preRun.shift());Ld(aa)}function af(){jn=!0,Ld(Od)}function W4(){nf=!0}function of(){if(a.postRun)for(typeof a.postRun=="function"&&(a.postRun=[a.postRun]);a.postRun.length;)uf(a.postRun.shift());Ld(xu)}function lf(K){aa.unshift(K)}function yr(K){Od.unshift(K)}function uf(K){xu.unshift(K)}var Us=0,bu=null,Oa=null;function x1(K){Us++,a.monitorRunDependencies&&a.monitorRunDependencies(Us)}function cf(K){if(Us--,a.monitorRunDependencies&&a.monitorRunDependencies(Us),Us==0&&(bu!==null&&(clearInterval(bu),bu=null),Oa)){var se=Oa;Oa=null,se()}}a.preloadedImages={},a.preloadedAudios={};function Si(K){a.onAbort&&a.onAbort(K),K="Aborted("+K+")",_(K),ae=!0,le=1,K+=". Build with -s ASSERTIONS=1 for more info.";var se=new WebAssembly.RuntimeError(K);throw i(se),se}var b1="data:application/octet-stream;base64,";function df(K){return K.startsWith(b1)}function Ci(K){return K.startsWith("file://")}var qn;qn="tfjs-backend-wasm.wasm",df(qn)||(qn=y(qn));function zd(K){try{if(K==qn&&Q)return new Uint8Array(Q);if(b)return b(K);throw"both async and sync fetching of the wasm failed"}catch(se){Si(se)}}function v1(){if(!Q&&(h||f)){if(typeof fetch=="function"&&!Ci(qn))return fetch(qn,{credentials:"same-origin"}).then(function(K){if(!K.ok)throw"failed to load wasm binary file at '"+qn+"'";return K.arrayBuffer()}).catch(function(){return zd(qn)});if(A)return new Promise(function(K,se){A(qn,function(xe){K(new Uint8Array(xe))},se)})}return Promise.resolve().then(function(){return zd(qn)})}function w1(){var K={env:ku,wasi_snapshot_preview1:ku};function se(et,Ze){var en=et.exports;a.asm=en,Y=a.asm.memory,ra(Y.buffer),Fa=a.asm.__indirect_function_table,yr(a.asm.__wasm_call_ctors),cf("wasm-instantiate")}x1("wasm-instantiate");function xe(et){se(et.instance)}function De(et){return v1().then(function(Ze){return WebAssembly.instantiate(Ze,K)}).then(function(Ze){return Ze}).then(et,function(Ze){_("failed to asynchronously prepare wasm: "+Ze),Si(Ze)})}function ht(){return!Q&&typeof WebAssembly.instantiateStreaming=="function"&&!df(qn)&&!Ci(qn)&&typeof fetch=="function"?fetch(qn,{credentials:"same-origin"}).then(function(et){var Ze=WebAssembly.instantiateStreaming(et,K);return Ze.then(xe,function(en){return _("wasm streaming compile failed: "+en),_("falling back to ArrayBuffer instantiation"),De(xe)})}):De(xe)}if(a.instantiateWasm)try{var yt=a.instantiateWasm(K,se);return yt}catch(et){return _("Module.instantiateWasm callback failed with error: "+et),!1}return ht().catch(i),{}}var V4,U4;function Ld(K){for(;K.length>0;){var se=K.shift();if(typeof se=="function"){se(a);continue}var xe=se.func;typeof xe=="number"?se.arg===void 0?Bd(xe)():Bd(xe)(se.arg):xe(se.arg===void 0?null:se.arg)}}function Ma(K){return K}function pf(K){var se=/\b_Z[\w\d_]+/g;return K.replace(se,function(xe){var De=xe;return xe===De?xe:De+" ["+xe+"]"})}var Ar=[];function Bd(K){var se=Ar[K];return se||(K>=Ar.length&&(Ar.length=K+1),Ar[K]=se=Fa.get(K)),se}function G4(){var K=new Error;if(!K.stack){try{throw new Error}catch(se){K=se}if(!K.stack)return"(no stack trace available)"}return K.stack.toString()}function vu(K,se){Fa.set(K,se),Ar[K]=se}function k1(){Si("")}function Wd(){return 2147483648}function hf(K,se,xe){Gn.copyWithin(K,se,se+xe)}function Xn(K){try{return Y.grow(K-bs.byteLength+65535>>>16),ra(Y.buffer),1}catch(se){}}function ff(K){var se=Gn.length;K=K>>>0;var xe=Wd();if(K>xe)return!1;for(var De=1;De<=4;De*=2){var ht=se*(1+.2/De);ht=Math.min(ht,K+100663296);var yt=Math.min(xe,Qt(Math.max(K,ht),65536)),et=Xn(yt);if(et)return!0}return!1}var wu={mappings:{},buffers:[null,[],[]],printChar:function(K,se){var xe=wu.buffers[K];se===0||se===10?((K===1?P:_)(ot(xe,0)),xe.length=0):xe.push(se)},varargs:void 0,get:function(){wu.varargs+=4;var K=$n[wu.varargs-4>>2];return K},getStr:function(K){var se=dt(K);return se},get64:function(K,se){return K}};function I1(K){return 0}function H4(K,se,xe,De,ht){}function j4(K,se,xe,De){for(var ht=0,yt=0;yt<xe;yt++){var et=$n[se>>2],Ze=$n[se+4>>2];se+=8;for(var en=0;en<Ze;en++)wu.printChar(K,Gn[et+en]);ht+=Ze}return $n[De>>2]=ht,0}function S1(K){ee(K)}var mf=!1,ku={abort:k1,emscripten_get_heap_max:Wd,emscripten_memcpy_big:hf,emscripten_resize_heap:ff,fd_close:I1,fd_seek:H4,fd_write:j4,setTempRet0:S1},YE=w1(),q4=a.___wasm_call_ctors=function(){return(q4=a.___wasm_call_ctors=a.asm.__wasm_call_ctors).apply(null,arguments)},C1=a._init=function(){return(C1=a._init=a.asm.init).apply(null,arguments)},T1=a._init_with_threads_count=function(){return(T1=a._init_with_threads_count=a.asm.init_with_threads_count).apply(null,arguments)},gf=a._get_threads_count=function(){return(gf=a._get_threads_count=a.asm.get_threads_count).apply(null,arguments)},yf=a._register_tensor=function(){return(yf=a._register_tensor=a.asm.register_tensor).apply(null,arguments)},N1=a._dispose_data=function(){return(N1=a._dispose_data=a.asm.dispose_data).apply(null,arguments)},ze=a._dispose=function(){return(ze=a._dispose=a.asm.dispose).apply(null,arguments)},E1=a._Abs=function(){return(E1=a._Abs=a.asm.Abs).apply(null,arguments)},Af=a._Add=function(){return(Af=a._Add=a.asm.Add).apply(null,arguments)},Ti=a._AddN=function(){return(Ti=a._AddN=a.asm.AddN).apply(null,arguments)},Iu=a._All=function(){return(Iu=a._All=a.asm.All).apply(null,arguments)},R1=a._Any=function(){return(R1=a._Any=a.asm.Any).apply(null,arguments)},X4=a._ArgMax=function(){return(X4=a._ArgMax=a.asm.ArgMax).apply(null,arguments)},_1=a._AvgPool=function(){return(_1=a._AvgPool=a.asm.AvgPool).apply(null,arguments)},K4=a._BatchMatMul=function(){return(K4=a._BatchMatMul=a.asm.BatchMatMul).apply(null,arguments)},Ni=a._Ceil=function(){return(Ni=a._Ceil=a.asm.Ceil).apply(null,arguments)},D1=a._ClipByValue=function(){return(D1=a._ClipByValue=a.asm.ClipByValue).apply(null,arguments)},$1=a._Conv2D=function(){return($1=a._Conv2D=a.asm.Conv2D).apply(null,arguments)},P1=a._Conv2DBackpropInput=function(){return(P1=a._Conv2DBackpropInput=a.asm.Conv2DBackpropInput).apply(null,arguments)},F1=a._Cos=function(){return(F1=a._Cos=a.asm.Cos).apply(null,arguments)},O1=a._Cosh=function(){return(O1=a._Cosh=a.asm.Cosh).apply(null,arguments)},M1=a._CropAndResize=function(){return(M1=a._CropAndResize=a.asm.CropAndResize).apply(null,arguments)},xf=a._Cumprod=function(){return(xf=a._Cumprod=a.asm.Cumprod).apply(null,arguments)},z1=a._Cumsum=function(){return(z1=a._Cumsum=a.asm.Cumsum).apply(null,arguments)},L1=a._DepthToSpace=function(){return(L1=a._DepthToSpace=a.asm.DepthToSpace).apply(null,arguments)},B1=a._DepthwiseConv2dNative=function(){return(B1=a._DepthwiseConv2dNative=a.asm.DepthwiseConv2dNative).apply(null,arguments)},W1=a._Elu=function(){return(W1=a._Elu=a.asm.Elu).apply(null,arguments)},V1=a._Equal=function(){return(V1=a._Equal=a.asm.Equal).apply(null,arguments)},bf=a._Exp=function(){return(bf=a._Exp=a.asm.Exp).apply(null,arguments)},U1=a._FlipLeftRight=function(){return(U1=a._FlipLeftRight=a.asm.FlipLeftRight).apply(null,arguments)},G1=a._Floor=function(){return(G1=a._Floor=a.asm.Floor).apply(null,arguments)},Ei=a._FloorDiv=function(){return(Ei=a._FloorDiv=a.asm.FloorDiv).apply(null,arguments)},Vd=a._FusedBatchNorm=function(){return(Vd=a._FusedBatchNorm=a.asm.FusedBatchNorm).apply(null,arguments)},H1=a._FusedConv2D=function(){return(H1=a._FusedConv2D=a.asm.FusedConv2D).apply(null,arguments)},j1=a._FusedDepthwiseConv2D=function(){return(j1=a._FusedDepthwiseConv2D=a.asm.FusedDepthwiseConv2D).apply(null,arguments)},q1=a._Gather=function(){return(q1=a._Gather=a.asm.Gather).apply(null,arguments)},Je=a._GatherNd=function(){return(Je=a._GatherNd=a.asm.GatherNd).apply(null,arguments)},X1=a._Greater=function(){return(X1=a._Greater=a.asm.Greater).apply(null,arguments)},K1=a._GreaterEqual=function(){return(K1=a._GreaterEqual=a.asm.GreaterEqual).apply(null,arguments)},Z1=a._LeakyRelu=function(){return(Z1=a._LeakyRelu=a.asm.LeakyRelu).apply(null,arguments)},Y1=a._Less=function(){return(Y1=a._Less=a.asm.Less).apply(null,arguments)},J1=a._LessEqual=function(){return(J1=a._LessEqual=a.asm.LessEqual).apply(null,arguments)},Q1=a._Log=function(){return(Q1=a._Log=a.asm.Log).apply(null,arguments)},Ud=a._LogicalAnd=function(){return(Ud=a._LogicalAnd=a.asm.LogicalAnd).apply(null,arguments)},vf=a._LogicalNot=function(){return(vf=a._LogicalNot=a.asm.LogicalNot).apply(null,arguments)},wf=a._LogicalOr=function(){return(wf=a._LogicalOr=a.asm.LogicalOr).apply(null,arguments)},eg=a._LogicalXor=function(){return(eg=a._LogicalXor=a.asm.LogicalXor).apply(null,arguments)},tg=a._Max=function(){return(tg=a._Max=a.asm.Max).apply(null,arguments)},ng=a._MaxPool=function(){return(ng=a._MaxPool=a.asm.MaxPool).apply(null,arguments)},sg=a._Maximum=function(){return(sg=a._Maximum=a.asm.Maximum).apply(null,arguments)},rg=a._Mean=function(){return(rg=a._Mean=a.asm.Mean).apply(null,arguments)},ag=a._Min=function(){return(ag=a._Min=a.asm.Min).apply(null,arguments)},zt=a._Minimum=function(){return(zt=a._Minimum=a.asm.Minimum).apply(null,arguments)},og=a._MirrorPad=function(){return(og=a._MirrorPad=a.asm.MirrorPad).apply(null,arguments)},ig=a._Multiply=function(){return(ig=a._Multiply=a.asm.Multiply).apply(null,arguments)},lg=a._Neg=function(){return(lg=a._Neg=a.asm.Neg).apply(null,arguments)},Su=a._NonMaxSuppressionV3=function(){return(Su=a._NonMaxSuppressionV3=a.asm.NonMaxSuppressionV3).apply(null,arguments)},kf=a._NonMaxSuppressionV4=function(){return(kf=a._NonMaxSuppressionV4=a.asm.NonMaxSuppressionV4).apply(null,arguments)},If=a._NonMaxSuppressionV5=function(){return(If=a._NonMaxSuppressionV5=a.asm.NonMaxSuppressionV5).apply(null,arguments)},Sf=a._NotEqual=function(){return(Sf=a._NotEqual=a.asm.NotEqual).apply(null,arguments)},ug=a._OneHot=function(){return(ug=a._OneHot=a.asm.OneHot).apply(null,arguments)},Cf=a._PadV2=function(){return(Cf=a._PadV2=a.asm.PadV2).apply(null,arguments)},cg=a._Pow=function(){return(cg=a._Pow=a.asm.Pow).apply(null,arguments)},Z4=a._Prelu=function(){return(Z4=a._Prelu=a.asm.Prelu).apply(null,arguments)},Tf=a._Prod=function(){return(Tf=a._Prod=a.asm.Prod).apply(null,arguments)},Y4=a._RealDiv=function(){return(Y4=a._RealDiv=a.asm.RealDiv).apply(null,arguments)},dg=a._Relu=function(){return(dg=a._Relu=a.asm.Relu).apply(null,arguments)},pg=a._Relu6=function(){return(pg=a._Relu6=a.asm.Relu6).apply(null,arguments)},hg=a._ResizeBilinear=function(){return(hg=a._ResizeBilinear=a.asm.ResizeBilinear).apply(null,arguments)},fg=a._ResizeNearestNeighbor=function(){return(fg=a._ResizeNearestNeighbor=a.asm.ResizeNearestNeighbor).apply(null,arguments)},mg=a._Reverse=function(){return(mg=a._Reverse=a.asm.Reverse).apply(null,arguments)},gg=a._RotateWithOffset=function(){return(gg=a._RotateWithOffset=a.asm.RotateWithOffset).apply(null,arguments)},yg=a._Round=function(){return(yg=a._Round=a.asm.Round).apply(null,arguments)},Ag=a._Rsqrt=function(){return(Ag=a._Rsqrt=a.asm.Rsqrt).apply(null,arguments)},xg=a._ScatterNd=function(){return(xg=a._ScatterNd=a.asm.ScatterNd).apply(null,arguments)},bg=a._SelectV2=function(){return(bg=a._SelectV2=a.asm.SelectV2).apply(null,arguments)},vg=a._Sigmoid=function(){return(vg=a._Sigmoid=a.asm.Sigmoid).apply(null,arguments)},wg=a._Sin=function(){return(wg=a._Sin=a.asm.Sin).apply(null,arguments)},kg=a._Softmax=function(){return(kg=a._Softmax=a.asm.Softmax).apply(null,arguments)},Ig=a._SparseFillEmptyRows=function(){return(Ig=a._SparseFillEmptyRows=a.asm.SparseFillEmptyRows).apply(null,arguments)},Sg=a._SparseReshape=function(){return(Sg=a._SparseReshape=a.asm.SparseReshape).apply(null,arguments)},Cg=a._SparseSegmentReduction=function(){return(Cg=a._SparseSegmentReduction=a.asm.SparseSegmentReduction).apply(null,arguments)},Tg=a._Sqrt=function(){return(Tg=a._Sqrt=a.asm.Sqrt).apply(null,arguments)},Ng=a._Square=function(){return(Ng=a._Square=a.asm.Square).apply(null,arguments)},Eg=a._SquaredDifference=function(){return(Eg=a._SquaredDifference=a.asm.SquaredDifference).apply(null,arguments)},Rg=a._Step=function(){return(Rg=a._Step=a.asm.Step).apply(null,arguments)},_g=a._StridedSlice=function(){return(_g=a._StridedSlice=a.asm.StridedSlice).apply(null,arguments)},Dg=a._Sub=function(){return(Dg=a._Sub=a.asm.Sub).apply(null,arguments)},$g=a._Sum=function(){return($g=a._Sum=a.asm.Sum).apply(null,arguments)},Pg=a._Tan=function(){return(Pg=a._Tan=a.asm.Tan).apply(null,arguments)},Fg=a._Tanh=function(){return(Fg=a._Tanh=a.asm.Tanh).apply(null,arguments)},Og=a._Tile=function(){return(Og=a._Tile=a.asm.Tile).apply(null,arguments)},Mg=a._TopK=function(){return(Mg=a._TopK=a.asm.TopK).apply(null,arguments)},zg=a._Transform=function(){return(zg=a._Transform=a.asm.Transform).apply(null,arguments)},Lg=a._Transpose=function(){return(Lg=a._Transpose=a.asm.Transpose).apply(null,arguments)},Bg=a.__FusedMatMul=function(){return(Bg=a.__FusedMatMul=a.asm._FusedMatMul).apply(null,arguments)},Wg=a._malloc=function(){return(Wg=a._malloc=a.asm.malloc).apply(null,arguments)},Vg=a._free=function(){return(Vg=a._free=a.asm.free).apply(null,arguments)},Ug=a.___errno_location=function(){return(Ug=a.___errno_location=a.asm.__errno_location).apply(null,arguments)},Gg=a._emscripten_main_thread_process_queued_calls=function(){return(Gg=a._emscripten_main_thread_process_queued_calls=a.asm.emscripten_main_thread_process_queued_calls).apply(null,arguments)},Nf=a.stackSave=function(){return(Nf=a.stackSave=a.asm.stackSave).apply(null,arguments)},Ef=a.stackRestore=function(){return(Ef=a.stackRestore=a.asm.stackRestore).apply(null,arguments)},Gd=a.stackAlloc=function(){return(Gd=a.stackAlloc=a.asm.stackAlloc).apply(null,arguments)},Hg=a.dynCall_iijjiiii=function(){return(Hg=a.dynCall_iijjiiii=a.asm.dynCall_iijjiiii).apply(null,arguments)},jg=a.dynCall_jiji=function(){return(jg=a.dynCall_jiji=a.asm.dynCall_jiji).apply(null,arguments)};a.cwrap=_e;var Cu;function Hd(K){this.name="ExitStatus",this.message="Program terminated with exit("+K+")",this.status=K}Oa=function K(){Cu||jd(),Cu||(Oa=K)};function jd(K){if(K=K||c,Us>0||(rf(),Us>0))return;function se(){Cu||(Cu=!0,a.calledRun=!0,!ae&&(af(),o(a),a.onRuntimeInitialized&&a.onRuntimeInitialized(),of()))}a.setStatus?(a.setStatus("Running..."),setTimeout(function(){setTimeout(function(){a.setStatus("")},1),se()},1)):se()}a.run=jd;function J4(K){le=K,Md()||(a.onExit&&a.onExit(K),ae=!0),d(K,new Hd(K))}if(a.preInit)for(typeof a.preInit=="function"&&(a.preInit=[a.preInit]);a.preInit.length>0;)a.preInit.pop()();jd();var Tu;l&&(Tu={uncaughtException:process.listeners("uncaughtException").filter(function(K){return!l.uncaughtException.indexOf(K)>-1}),unhandledRejection:process.listeners("unhandledRejection").filter(function(K){return!l.unhandledRejection.indexOf(K)>-1})});var Nu;if(typeof r!="undefined")Nu=r;else if(typeof WasmBackendModuleThreadedSimd!="undefined")Nu=WasmBackendModuleThreadedSimd;else throw new Error("Could not find wasm module in post.js");if(Tu){var qg=Nu._dispose;Nu._dispose=function(){qg(),Tu.uncaughtException.forEach(function(K){process.removeListener("uncaughtException",K)}),Tu.unhandledRejection.forEach(function(K){process.removeListener("unhandledRejection",K)})}}return r.ready}})();typeof e=="object"&&typeof t=="object"?t.exports=n:typeof define=="function"&&define.amd?define([],function(){return n}):typeof e=="object"&&(e.WasmBackendModule=n)}}),A_=1e-7,x_=1e-4,Op=class{constructor(e,t){this.backend=e,this.dataMover=t,this.data=new WeakMap,this.dataIdsCount=0}get(e){return this.data.has(e)||this.dataMover.moveData(this.backend,e),this.data.get(e)}set(e,t){this.dataIdsCount++,this.data.set(e,t)}has(e){return this.data.has(e)}delete(e){return this.dataIdsCount--,this.data.delete(e)}numDataIds(){return this.dataIdsCount}},uc=class{refCount(e){return Gs("refCount")}incRef(e){return Gs("incRef")}timerAvailable(){return!0}time(e){return Gs("time")}read(e){return Gs("read")}readSync(e){return Gs("readSync")}readToGPU(e,t){return Gs("readToGPU")}numDataIds(){return Gs("numDataIds")}disposeData(e,t){return Gs("disposeData")}write(e,t,n){return Gs("write")}move(e,t,n,s,r){return Gs("move")}memory(){return Gs("memory")}floatPrecision(){return Gs("floatPrecision")}epsilon(){return this.floatPrecision()===32?A_:x_}dispose(){return Gs("dispose")}};function Gs(e){throw new Error(`'${e}' not yet implemented or not found in the registry. This kernel may not be supported by the tfjs backend you have chosen`)}function J7(e){let t=e.length,n=0;for(;t>0;)n=Math.random()*t|0,t--,um(e,t,n)}function b_(e,t){if(e.length!==t.length)throw new Error(`Array sizes must match to be shuffled together First array length was ${e.length}Second array length was ${t.length}`);let n=e.length,s=0;for(;n>0;)s=Math.random()*n|0,n--,um(e,n,s),um(t,n,s)}function Ap(e,t,n){return Math.max(e,Math.min(t,n))}function v_(e){return e%2===0?e:e+1}function um(e,t,n){let s=e[t];e[t]=e[n],e[n]=s}function w_(e){let t=0;for(let n=0;n<e.length;n++)t+=e[n];return t}function k_(e,t){let n=Math.random();return t*n+(1-n)*e}function I_(e,t){let n=0;for(let s=0;s<e.length;s++){let r=Number(e[s])-Number(t[s]);n+=r*r}return n}function M(e,t){if(!e)throw new Error(typeof t=="string"?t:t())}function ns(e,t,n=""){M(uo(e,t),()=>n+` Shapes ${e} and ${t} must match`)}function al(e){M(e!=null,()=>"The input to the tensor constructor must be a non-null value.")}function qi(e,t=[],n=!1){if(t==null&&(t=[]),Array.isArray(e)||Pn(e)&&!n)for(let s=0;s<e.length;++s)qi(e[s],t,n);else t.push(e);return t}function Et(e){if(e.length===0)return 1;let t=e[0];for(let n=1;n<e.length;n++)t*=e[n];return t}function S_(e){return e.length===0}function uo(e,t){if(e===t)return!0;if(e==null||t==null||e.length!==t.length)return!1;for(let n=0;n<e.length;n++)if(e[n]!==t[n])return!1;return!0}function ju(e){return e%1===0}function C_(e){if(Math.tanh!=null)return Math.tanh(e);if(e===1/0)return 1;if(e===-1/0)return-1;{let t=Math.exp(2*e);return(t-1)/(t+1)}}function T_(e){let t=Math.ceil(Math.sqrt(e));return[t,Math.ceil(e/t)]}function N_(e){let t=new Uint32Array(e);for(let n=0;n<e;++n)t[n]=n;return J7(t),t}function hp(e,t){return t<=e.length?e:e+" ".repeat(t-e.length)}function E_(e,t=s=>0,n){return new Promise((s,r)=>{let a=0,o=()=>{if(e()){s();return}a++;let i=t(a);if(n!=null&&a>=n){r();return}setTimeout(o,i)};o()})}function R_(e,t){let n=1,s=-1;for(let a=0;a<e.length;++a)if(e[a]>=0)n*=e[a];else if(e[a]===-1){if(s!==-1)throw Error(`Shapes can only have 1 implicit size. Found -1 at dim ${s} and dim ${a}`);s=a}else if(e[a]<0)throw Error(`Shapes can not be < 0. Found ${e[a]} at dim ${a}`);if(s===-1){if(t>0&&t!==n)throw Error(`Size(${t}) must match the product of shape ${e}`);return e}if(n===0)throw Error(`Cannot infer the missing size in [${e}] when there are 0 elements`);if(t%n!==0)throw Error(`The implicit shape can't be a fractional number. Got ${t} / ${n}`);let r=e.slice();return r[s]=t/n,r}function ur(e,t){let n=t.length;return e=e==null?t.map((s,r)=>r):[].concat(e),M(e.every(s=>s>=-n&&s<n),()=>`All values in axis param must be in range [-${n}, ${n}) but got axis ${e}`),M(e.every(s=>ju(s)),()=>`All values in axis param must be integers but got axis ${e}`),e.map(s=>s<0?n+s:s)}function Q7(e,t){let n=[],s=[],r=t!=null&&Array.isArray(t)&&t.length===0,a=t==null||r?null:ur(t,e).sort(),o=0;for(let i=0;i<e.length;++i){if(a!=null){if(a[o]===i&&e[i]!==1)throw new Error(`Can't squeeze axis ${i} since its dim '${e[i]}' is not 1`);(a[o]==null||a[o]>i)&&e[i]===1&&(n.push(e[i]),s.push(i)),a[o]<=i&&o++}e[i]!==1&&(n.push(e[i]),s.push(i))}return{newShape:n,keptDims:s}}function e6(e,t){let n=null;if(e==null||e==="float32")n=new Float32Array(t);else if(e==="int32")n=new Int32Array(t);else if(e==="bool")n=new Uint8Array(t);else throw new Error(`Unknown data type ${e}`);return n}function t6(e,t){let n=null;if(e==null||e==="float32")n=new Float32Array(t);else if(e==="int32")n=new Int32Array(t);else if(e==="bool")n=new Uint8Array(t);else if(e==="string")n=new Array(t);else throw new Error(`Unknown data type ${e}`);return n}function n6(e,t){for(let n=0;n<e.length;n++){let s=e[n];if(isNaN(s)||!isFinite(s))throw Error(`A tensor of type ${t} being uploaded contains ${s}.`)}}function s6(e){return e==="bool"||e==="complex64"||e==="float32"||e==="int32"||e==="string"}function __(e,t){return!(t==="complex64"||t==="float32"&&e!=="complex64"||t==="int32"&&e!=="float32"&&e!=="complex64"||t==="bool"&&e==="bool")}function Pn(e){return e instanceof Float32Array||e instanceof Int32Array||e instanceof Uint8Array||e instanceof Uint8ClampedArray}function f3(e){if(e==="float32"||e==="int32")return 4;if(e==="complex64")return 8;if(e==="bool")return 1;throw new Error(`Unknown dtype ${e}`)}function r6(e){if(e==null)return 0;let t=0;return e.forEach(n=>t+=n.length),t}function Ua(e){return typeof e=="string"||e instanceof String}function a6(e){return typeof e=="boolean"}function o6(e){return typeof e=="number"}function Wm(e){return Array.isArray(e)?Wm(e[0]):e instanceof Float32Array?"float32":e instanceof Int32Array||e instanceof Uint8Array||e instanceof Uint8ClampedArray?"int32":o6(e)?"float32":Ua(e)?"string":a6(e)?"bool":"float32"}function Za(e){return!!(e&&e.constructor&&e.call&&e.apply)}function cm(e,t){for(let n=t;n<e;++n)if(e%n===0)return n;return e}function cc(e){let t=e.length;if(t<2)return[];let n=new Array(t-1);n[t-2]=e[t-1];for(let s=t-3;s>=0;--s)n[s]=n[s+1]*e[s+1];return n}function i6(e,t,n,s=!1){let r=new Array;if(t.length===1){let a=t[0]*(s?2:1);for(let o=0;o<a;o++)r[o]=n[e+o]}else{let a=t[0],o=t.slice(1),i=o.reduce((l,u)=>l*u)*(s?2:1);for(let l=0;l<a;l++)r[l]=i6(e+l*i,o,n,s)}return r}function Bu(e,t,n=!1){if(e.length===0)return t[0];let s=e.reduce((r,a)=>r*a)*(n?2:1);if(s===0)return[];if(s!==t.length)throw new Error(`[${e}] does not match the input size ${t.length}${n?" for a complex tensor":""}.`);return i6(0,e,t,n)}function xy(e,t){let n=Vm(e,t);for(let s=0;s<n.length;s++)n[s]=1;return n}function Vm(e,t){if(t==null||t==="float32"||t==="complex64")return new Float32Array(e);if(t==="int32")return new Int32Array(e);if(t==="bool")return new Uint8Array(e);throw new Error(`Unknown data type ${t}`)}function D_(e,t){let n=e.reduce((s,r)=>s*r,1);if(t==null||t==="float32")return Bu(e,new Float32Array(n));if(t==="int32")return Bu(e,new Int32Array(n));if(t==="bool")return Bu(e,new Uint8Array(n));throw new Error(`Unknown data type ${t}`)}function by(e){e.forEach(t=>{M(Number.isInteger(t)&&t>=0,()=>`Tensor must have a shape comprised of positive integers but got shape [${e}].`)})}function $_(e,t,n){if(t===0)return 0;if(t===1)return e[0];let s=e[e.length-1];for(let r=0;r<e.length-1;++r)s+=n[r]*e[r];return s}function P_(e,t,n){if(t===0)return[];if(t===1)return[e];let s=new Array(t);for(let r=0;r<s.length-1;++r)s[r]=Math.floor(e/n[r]),e-=s[r]*n[r];return s[s.length-1]=e,s}function vy(e){return e&&e.then&&typeof e.then=="function"}var cv="tfjsflags",l6=class{constructor(e){this.global=e,this.flags={},this.flagRegistry={},this.urlFlags={},this.getQueryParams=F_,this.populateURLFlags()}setPlatform(e,t){this.platform!=null&&(X().getBool("IS_TEST")||X().getBool("PROD")||console.warn(`Platform ${this.platformName} has already been set. Overwriting the platform with ${e}.`)),this.platformName=e,this.platform=t}registerFlag(e,t,n){if(this.flagRegistry[e]={evaluationFn:t,setHook:n},this.urlFlags[e]!=null){let s=this.urlFlags[e];X().getBool("IS_TEST")||X().getBool("PROD")||console.warn(`Setting feature override from URL ${e}: ${s}.`),this.set(e,s)}}async getAsync(e){return e in this.flags?this.flags[e]:(this.flags[e]=await this.evaluateFlag(e),this.flags[e])}get(e){if(e in this.flags)return this.flags[e];let t=this.evaluateFlag(e);if(vy(t))throw new Error(`Flag ${e} cannot be synchronously evaluated. Please use getAsync() instead.`);return this.flags[e]=t,this.flags[e]}getNumber(e){return this.get(e)}getBool(e){return this.get(e)}getFlags(){return this.flags}get features(){return this.flags}set(e,t){if(this.flagRegistry[e]==null)throw new Error(`Cannot set flag ${e} as it has not been registered.`);this.flags[e]=t,this.flagRegistry[e].setHook!=null&&this.flagRegistry[e].setHook(t)}evaluateFlag(e){if(this.flagRegistry[e]==null)throw new Error(`Cannot evaluate flag '${e}': no evaluation function found.`);return this.flagRegistry[e].evaluationFn()}setFlags(e){this.flags=Object.assign({},e)}reset(){this.flags={},this.urlFlags={},this.populateURLFlags()}populateURLFlags(){if(typeof this.global=="undefined"||typeof this.global.location=="undefined"||typeof this.global.location.search=="undefined")return;let e=this.getQueryParams(this.global.location.search);cv in e&&e[cv].split(",").forEach(n=>{let[s,r]=n.split(":");this.urlFlags[s]=M_(s,r)})}};function F_(e){let t={};return e.replace(/[?&]([^=?&]+)(?:=([^&]*))?/g,(n,...s)=>(O_(t,s[0],s[1]),s.join("="))),t}function O_(e,t,n){e[decodeURIComponent(t)]=decodeURIComponent(n||"")}function M_(e,t){if(t=t.toLowerCase(),t==="true"||t==="false")return t==="true";if(`${+t}`===t)return+t;throw new Error(`Could not parse value flag value ${t} for flag ${e}.`)}function X(){return wy}var wy=null;function z_(e){wy=e}var t3;function u6(){if(t3==null){let e;if(typeof window!="undefined")e=window;else if(typeof global!="undefined")e=global;else if(typeof process!="undefined")e=process;else if(typeof self!="undefined")e=self;else throw new Error("Could not find a global object");t3=e}return t3}function L_(){let e=u6();return e._tfGlobals==null&&(e._tfGlobals=new Map),e._tfGlobals}function ky(e,t){let n=L_();if(n.has(e))return n.get(e);{let s=t();return n.set(e,s),n.get(e)}}var ol="Abs",dc="Acos",pc="Acosh",Aa="Add",co="AddN",hc="All",fc="Any",po="ArgMax",mc="ArgMin",gc="Asin",yc="Asinh",Ac="Atan",xc="Atanh",bc="Atan2",ho="AvgPool",Um="AvgPoolGrad",Mp="AvgPool3D",Gm="AvgPool3DGrad",fo="BatchMatMul",il="BatchToSpaceND",Hm="Bincount",c6="BroadcastTo",jm="BroadcastArgs",mo="Cast",go="Ceil",xa="ClipByValue",zp="Complex",Lp="ComplexAbs",ll="Concat",yo="Conv2D",qm="Conv2DBackpropFilter",Ao="Conv2DBackpropInput",Bp="Conv3D",Xm="Conv3DBackpropFilterV2",Km="Conv3DBackpropInputV2",xo="Cos",bo="Cosh",ul="Cumprod",vo="Cumsum",cl="CropAndResize",Zm="DenseBincount",dl="DepthToSpace",wo="DepthwiseConv2dNative",Ym="DepthwiseConv2dNativeBackpropFilter",Jm="DepthwiseConv2dNativeBackpropInput",Qm="Diag",Wp="Dilation2D",dm="Dilation2DBackpropInput",pm="Dilation2DBackpropFilter",ko="RealDiv",Vp="Einsum",Io="Elu",e0="EluGrad",vc="Erf",pl="Equal",So="Exp",hl="ExpandDims",fl="Expm1",t0="FFT",wc="Fill",ml="FlipLeftRight",Co="Floor",To="FloorDiv",No="FusedBatchNorm",gl="GatherV2",yl="GatherNd",Al="Greater",Eo="GreaterEqual",Ro="Identity",n0="IFFT",Up="Imag",kc="IsFinite",Ic="IsInf",Sc="IsNan",_o="LeakyRelu",xl="Less",bl="LessEqual",s0="LinSpace",Do="Log",Cc="Log1p",vl="LogicalAnd",wl="LogicalNot",Tc="LogicalOr",d6="LogicalXor",p6="LogSoftmax",B_="LowerBound",Gp="LRN",r0="LRNGrad",$o="Max",Po="Maximum",Fo="MaxPool",a0="MaxPoolGrad",Hp="MaxPool3D",o0="MaxPool3DGrad",i0="MaxPoolWithArgmax",Oo="Mean",Mo="Min",zo="Minimum",Lo="MirrorPad",Nc="Mod",l0="Multinomial",Bo="Multiply",kl="Neg",Il="NotEqual",Sl="NonMaxSuppressionV3",Ec="NonMaxSuppressionV4",Cl="NonMaxSuppressionV5",Tl="OnesLike",Nl="OneHot",El="Pack",Wo="PadV2",W_="Pool",Vo="Pow",Uo="Prelu",Go="Prod",Rc="Range",jp="Real",_c="Reciprocal",Ho="Relu",Rl="Reshape",jo="ResizeNearestNeighbor",u0="ResizeNearestNeighborGrad",qo="ResizeBilinear",c0="ResizeBilinearGrad",Xo="Relu6",_l="Reverse",Dl="Round",Ko="Rsqrt",$l="ScatterNd",d0="SearchSorted",Pl="Select",Dc="Selu",Fl="Slice",Zo="Sin",Ol="Sinh",$c="Sign",Yo="Sigmoid",Pc="Softplus",Jo="Sqrt",Qo="Sum",Ml="SpaceToBatchND",zl="SplitV",ei="Softmax",qp="SparseFillEmptyRows",Fc="SparseReshape",Xp="SparseSegmentMean",Kp="SparseSegmentSum",Zp="SparseToDense",ti="SquaredDifference",Oc="Square",Ll="StridedSlice",Mc="StringNGrams",Yp="StringSplit",Jp="StringToHashBucketFast",ni="Sub",Bl="Tan",si="Tanh",ba="Tile",Wl="TopK",Vl="Transform",Gr="Transpose",p0="Unique",Ul="Unpack",Qp="UnsortedSegmentSum",V_="UpperBound",Gl="ZerosLike",ri="Step",xp="FromPixels",Hl="RotateWithOffset",Ya="_FusedMatMul",Ja="FusedConv2D",Qa="FusedDepthwiseConv2D";function Va(...e){X().getBool("IS_TEST")||X().getBool("PROD")||console.warn(...e)}function U_(...e){X().getBool("IS_TEST")||X().getBool("PROD")||console.log(...e)}var qu=ky("kernelRegistry",()=>new Map),bp=ky("gradRegistry",()=>new Map);function hm(e,t){let n=Iy(e,t);return qu.get(n)}function m3(e){return bp.get(e)}function jr(e){let t=qu.entries(),n=[];for(;;){let{done:s,value:r}=t.next();if(s)break;let[a,o]=r,[i]=a.split("_");i===e&&n.push(o)}return n}function cr(e){let{kernelName:t,backendName:n}=e,s=Iy(t,n);qu.has(s)&&Va(`The kernel '${t}' for backend '${n}' is already registered`),qu.set(s,e)}function h6(e){let{kernelName:t}=e;bp.has(t)&&X().getBool("DEBUG")&&Va(`Overriding the gradient for '${t}'`),bp.set(t,e)}function G_(e,t){let n=Iy(e,t);if(!qu.has(n))throw new Error(`The kernel '${e}' for backend '${t}' is not registered`);qu.delete(n)}function H_(e){if(!bp.has(e))throw new Error(`The gradient '${e}' for backend is not registered`);bp.delete(e)}function j_(e,t){jr(e).forEach(s=>{let r=Object.assign({},s,{backendName:t});cr(r)})}function Iy(e,t){return`${t}_${e}`}var v={};Ve(v,{arraysEqual:()=>uo,assert:()=>M,assertNonNegativeIntegerDimensions:()=>by,assertNonNull:()=>al,assertShapesMatch:()=>ns,bytesFromStringArray:()=>r6,bytesPerElement:()=>f3,checkConversionForErrors:()=>n6,clamp:()=>Ap,computeStrides:()=>cc,createScalarValue:()=>J_,createShuffledIndices:()=>N_,decodeString:()=>fm,distSquared:()=>I_,encodeString:()=>th,fetch:()=>eD,fingerPrint64:()=>Y_,flatten:()=>qi,getArrayFromDType:()=>t6,getTypedArrayFromDType:()=>e6,hasEncodingLoss:()=>__,hexToLong:()=>eh,indexToLoc:()=>P_,inferDtype:()=>Wm,inferFromImplicitShape:()=>R_,isBoolean:()=>a6,isFunction:()=>Za,isInt:()=>ju,isNumber:()=>o6,isPromise:()=>vy,isScalarShape:()=>S_,isString:()=>Ua,isTypedArray:()=>Pn,isValidDtype:()=>s6,locToIndex:()=>$_,makeOnesTypedArray:()=>xy,makeZerosNestedTypedArray:()=>D_,makeZerosTypedArray:()=>Vm,nearestDivisor:()=>cm,nearestLargerEven:()=>v_,now:()=>vp,parseAxisParam:()=>ur,randUniform:()=>k_,repeatedTry:()=>E_,rightPad:()=>hp,shuffle:()=>J7,shuffleCombo:()=>b_,sizeFromShape:()=>Et,sizeToSquarishShape:()=>T_,squeezeShape:()=>Q7,sum:()=>w_,swap:()=>um,tanh:()=>C_,toNestedArray:()=>Bu,toTypedArray:()=>h0});var dv=lo(t_()),Oi=dv.default||dv;function eh(e){return Oi.fromString(e,!0,16)}var f6=eh("c3a5c85c97cb3127"),$i=eh("b492b66fbe98f273"),Zn=eh("9ae16a3b2f90404f");function g3(e){return e.xor(e.shru(47))}function m6(e,t,n){let s=e.slice(t,t+n);return Oi.fromBytes(Array.from(s),!0,!0)}function Nt(e,t){return m6(e,t,8)}function pv(e,t){return m6(e,t,4)}function xn(e,t){return t===0?e:e.shru(t).or(e.shl(64-t))}function ja(e,t,n=eh("9ddfea08eb382d69")){let s=e.xor(t).mul(n);s=s.xor(s.shru(47));let r=t.xor(s).mul(n);return r=r.xor(r.shru(47)),r=r.mul(n),r}function q_(e,t,n,s,r,a){r=r.add(e),a=xn(a.add(r).add(s),21);let o=r;return r=r.add(t),r=r.add(n),a=a.add(xn(r,44)),[r.add(s),a.add(o)]}function zf(e,t,n,s){return q_(Nt(e,t),Nt(e,t+8),Nt(e,t+16),Nt(e,t+24),n,s)}function X_(e,t=e.length){if(t>=8){let n=Zn.add(t*2),s=Nt(e,0).add(Zn),r=Nt(e,t-8),a=xn(r,37).mul(n).add(s),o=xn(s,25).add(r).mul(n);return ja(a,o,n)}if(t>=4){let n=Zn.add(t*2),s=pv(e,0);return ja(s.shl(3).add(t),pv(e,t-4),n)}if(t>0){let n=e[0],s=e[t>>1],r=e[t-1],a=n+(s<<8),o=t+(r<<2);return g3(Zn.mul(a).xor(f6.mul(o))).mul(Zn)}return Zn}function K_(e,t=e.length){let n=Zn.add(t*2),s=Nt(e,0).mul($i),r=Nt(e,8),a=Nt(e,t-8).mul(n),o=Nt(e,t-16).mul(Zn);return ja(xn(s.add(r),43).add(xn(a,30)).add(o),s.add(xn(r.add(Zn),18)).add(a),n)}function Z_(e,t=e.length){let n=Zn.add(t*2),s=Nt(e,0).mul(Zn),r=Nt(e,8),a=Nt(e,t-8).mul(n),o=Nt(e,t-16).mul(Zn),i=xn(s.add(r),43).add(xn(a,30)).add(o),l=ja(i,s.add(xn(r.add(Zn),18)).add(a),n),u=Nt(e,16).mul(n),c=Nt(e,24),p=i.add(Nt(e,t-32)).mul(n),d=l.add(Nt(e,t-24)).mul(n);return ja(xn(u.add(c),43).add(xn(p,30)).add(d),u.add(xn(c.add(s),18)).add(p),n)}function Y_(e,t=e.length){let n=Oi.fromNumber(81,!0);if(t<=32)return t<=16?X_(e,t):K_(e,t);if(t<=64)return Z_(e,t);let s=n,r=n.mul($i).add(113),a=g3(r.mul(Zn).add(113)).mul(Zn),o=[Oi.UZERO,Oi.UZERO],i=[Oi.UZERO,Oi.UZERO];s=s.mul(Zn).add(Nt(e,0));let l=0,u=(t-1>>6)*64,c=u+(t-1&63)-63;do s=xn(s.add(r).add(o[0]).add(Nt(e,l+8)),37).mul($i),r=xn(r.add(o[1]).add(Nt(e,l+48)),42).mul($i),s=s.xor(i[1]),r=r.add(o[0]).add(Nt(e,l+40)),a=xn(a.add(i[0]),33).mul($i),o=zf(e,l,o[1].mul($i),s.add(i[0])),i=zf(e,l+32,a.add(i[1]),r.add(Nt(e,l+16))),[a,s]=[s,a],l+=64;while(l!==u);let p=$i.add(a.and(255).shl(1));return l=c,i[0]=i[0].add(t-1&63),o[0]=o[0].add(i[0]),i[0]=i[0].add(o[0]),s=xn(s.add(r).add(o[0]).add(Nt(e,l+8)),37).mul(p),r=xn(r.add(o[1]).add(Nt(e,l+48)),42).mul(p),s=s.xor(i[1].mul(9)),r=r.add(o[0].mul(9).add(Nt(e,l+40))),a=xn(a.add(i[0]),33).mul(p),o=zf(e,l,o[1].mul(p),s.add(i[0])),i=zf(e,l+32,a.add(i[1]),r.add(Nt(e,l+16))),[a,s]=[s,a],ja(ja(o[0],i[0],p).add(g3(r).mul(f6)).add(a),ja(o[1],i[1],p).add(s),p)}function J_(e,t){return t==="string"?th(e):h0([e],t)}function Q_(e,t){return e instanceof Float32Array&&t==="float32"||e instanceof Int32Array&&t==="int32"||e instanceof Uint8Array&&t==="bool"}function h0(e,t){if(t==="string")throw new Error("Cannot convert a string[] to a TypedArray");if(Array.isArray(e)&&(e=qi(e)),X().getBool("DEBUG")&&n6(e,t),Q_(e,t))return e;if(t==null||t==="float32"||t==="complex64")return new Float32Array(e);if(t==="int32")return new Int32Array(e);if(t==="bool"){let n=new Uint8Array(e.length);for(let s=0;s<n.length;++s)Math.round(e[s])!==0&&(n[s]=1);return n}else throw new Error(`Unknown data type ${t}`)}function vp(){return X().platform.now()}function eD(e,t){return X().platform.fetch(e,t)}function th(e,t="utf-8"){return t=t||"utf-8",X().platform.encode(e,t)}function fm(e,t="utf-8"){return t=t||"utf-8",X().platform.decode(e,t)}var tD=class{constructor(e,t){this.backendTimer=e,this.logger=t,t==null&&(this.logger=new sD)}profileKernel(e,t,n){let s,r=()=>{s=n()},a,o=vp();if(this.backendTimer.timerAvailable())a=this.backendTimer.time(r);else{r();for(let l of s)l.dataSync();a=Promise.resolve({kernelMs:vp()-o})}if(X().getBool("CHECK_COMPUTATION_FOR_ERRORS"))for(let l=0;l<s.length;l++){let u=s[l];u.data().then(c=>{nD(c,u.dtype,e)})}return{kernelName:e,outputs:s,inputs:t,timeMs:a.then(l=>l.kernelMs),extraInfo:a.then(l=>l.getExtraProfileInfo!=null?l.getExtraProfileInfo():"")}}logKernelProfile(e){let{kernelName:t,outputs:n,timeMs:s,inputs:r,extraInfo:a}=e;n.forEach(o=>{Promise.all([o.data(),s,a]).then(i=>{this.logger.logKernelProfile(t,o,i[0],i[1],r,i[2])})})}};function nD(e,t,n){if(t!=="float32")return!1;for(let s=0;s<e.length;s++){let r=e[s];if(isNaN(r)||!isFinite(r))return console.warn(`Found ${r} in the result of '${n}'`),!0}return!1}var sD=class{logKernelProfile(e,t,n,s,r,a){let o=typeof s=="number"?hp(`${s}ms`,9):s.error,i=hp(e,25),l=t.rank,u=t.size,c=hp(t.shape.toString(),14),p="";for(let d in r){let h=r[d];if(h!=null){let f=h.shape||t.shape,m=f.length;p+=`${d}: ${m}D ${m>0?f:""} `}}console.log(`%c${i}	%c${o}	%c${l}D ${c}	%c${u}	%c${p}	%c${a}`,"font-weight:bold","color:red","color:blue","color: orange","color: green","color: steelblue")}};function rD(e,t,n){let s={},r={};for(let l=0;l<t.length;l++)s[t[l].id]=!0;for(let l=0;l<e.length;l++){let u=e[l],c=u.inputs;for(let p in c){let d=c[p],h=!1;for(let f=0;f<t.length;f++)if(s[d.id]){u.outputs.forEach(m=>s[m.id]=!0),h=!0,r[u.id]=!0;break}if(h)break}}let a={};a[n.id]=!0;let o={};for(let l=e.length-1;l>=0;l--){let u=e[l],c=u.inputs;for(let p=0;p<u.outputs.length;p++)if(a[u.outputs[p].id]){for(let d in c)a[c[d].id]=!0,o[u.id]=!0;break}}let i=[];for(let l=0;l<e.length;l++){let u=e[l];if(r[u.id]&&o[u.id]){let c={};for(let d in u.inputs){let h=u.inputs[d];s[h.id]&&(c[d]=h)}let p=Object.assign({},u);p.inputs=c,p.outputs=u.outputs,i.push(p)}}return i}function aD(e,t,n,s){for(let r=t.length-1;r>=0;r--){let a=t[r],o=[];if(a.outputs.forEach(l=>{let u=e[l.id];u!=null?o.push(u):o.push(null)}),a.gradient==null)throw new Error(`Cannot compute gradient: gradient function not found for ${a.kernelName}.`);let i=a.gradient(o);for(let l in a.inputs){if(!(l in i))throw new Error(`Cannot backprop through input ${l}. Available gradients found: ${Object.keys(i)}.`);let u=n(()=>i[l]());if(u.dtype!=="float32")throw new Error(`Error in gradient for op ${a.kernelName}. The gradient of input ${l} must have 'float32' dtype, but has '${u.dtype}'`);let c=a.inputs[l];if(!uo(u.shape,c.shape))throw new Error(`Error in gradient for op ${a.kernelName}. The gradient of input '${l}' has shape '${u.shape}', which does not match the shape of the input '${c.shape}'`);if(e[c.id]==null)e[c.id]=u;else{let p=e[c.id];e[c.id]=s(p,u),p.dispose()}}}}var hv=20,Jd=3,n3=7;function oD(e,t,n,s){let r=cc(t),a=iD(e,t,n,r),o=t.length,i=Jf(e,t,n,r,a),l=["Tensor"];return s&&(l.push(`  dtype: ${n}`),l.push(`  rank: ${o}`),l.push(`  shape: [${t}]`),l.push("  values:")),l.push(i.map(u=>"    "+u).join(`
 `)),l.join(`
-`)}function iD(e,t,n,s){let r=Et(t),a=s[s.length-1],o=new Array(a).fill(0),i=t.length,l=n==="complex64"?rp(e):e;if(i>1)for(let u=0;u<r/a;u++){let c=u*a;for(let p=0;p<a;p++)o[p]=Math.max(o[p],sp(l[c+p],0,n).length)}return o}function sp(e,t,n){let s;return Array.isArray(e)?s=`${parseFloat(e[0].toFixed(s3))} + ${parseFloat(e[1].toFixed(s3))}j`:Ga(e)?s=`'${e}'`:n==="bool"?s=g6(e):s=parseFloat(e.toFixed(s3)).toString(),fp(s,t)}function g6(e){return e===0?"false":"true"}function Qf(e,t,n,s,r,a=!0){let o=n==="complex64"?2:1,i=t[0],l=t.length;if(l===0){if(n==="complex64"){let m=rp(e);return[sp(m[0],0,n)]}return n==="bool"?[g6(e[0])]:[e[0].toString()]}if(l===1){if(i>hv){let g=Qd*o,y=Array.from(e.slice(0,g)),x=Array.from(e.slice((i-Qd)*o,i*o));return n==="complex64"&&(y=rp(y),x=rp(x)),["["+y.map((A,b)=>sp(A,r[b],n)).join(", ")+", ..., "+x.map((A,b)=>sp(A,r[i-Qd+b],n)).join(", ")+"]"]}let m=n==="complex64"?rp(e):Array.from(e);return["["+m.map((g,y)=>sp(g,r[y],n)).join(", ")+"]"]}let u=t.slice(1),c=s.slice(1),p=s[0]*o,d=[];if(i>hv){for(let m=0;m<Qd;m++){let g=m*p,y=g+p;d.push(...Qf(e.slice(g,y),u,n,c,r,!1))}d.push("...");for(let m=i-Qd;m<i;m++){let g=m*p,y=g+p;d.push(...Qf(e.slice(g,y),u,n,c,r,m===i-1))}}else for(let m=0;m<i;m++){let g=m*p,y=g+p;d.push(...Qf(e.slice(g,y),u,n,c,r,m===i-1))}let h=l===2?",":"";d[0]="["+d[0]+h;for(let m=1;m<d.length-1;m++)d[m]=" "+d[m]+h;let f=`,
+`)}function iD(e,t,n,s){let r=Et(t),a=s[s.length-1],o=new Array(a).fill(0),i=t.length,l=n==="complex64"?sp(e):e;if(i>1)for(let u=0;u<r/a;u++){let c=u*a;for(let p=0;p<a;p++)o[p]=Math.max(o[p],np(l[c+p],0,n).length)}return o}function np(e,t,n){let s;return Array.isArray(e)?s=`${parseFloat(e[0].toFixed(n3))} + ${parseFloat(e[1].toFixed(n3))}j`:Ua(e)?s=`'${e}'`:n==="bool"?s=g6(e):s=parseFloat(e.toFixed(n3)).toString(),hp(s,t)}function g6(e){return e===0?"false":"true"}function Jf(e,t,n,s,r,a=!0){let o=n==="complex64"?2:1,i=t[0],l=t.length;if(l===0){if(n==="complex64"){let m=sp(e);return[np(m[0],0,n)]}return n==="bool"?[g6(e[0])]:[e[0].toString()]}if(l===1){if(i>hv){let g=Jd*o,y=Array.from(e.slice(0,g)),x=Array.from(e.slice((i-Jd)*o,i*o));return n==="complex64"&&(y=sp(y),x=sp(x)),["["+y.map((A,b)=>np(A,r[b],n)).join(", ")+", ..., "+x.map((A,b)=>np(A,r[i-Jd+b],n)).join(", ")+"]"]}let m=n==="complex64"?sp(e):Array.from(e);return["["+m.map((g,y)=>np(g,r[y],n)).join(", ")+"]"]}let u=t.slice(1),c=s.slice(1),p=s[0]*o,d=[];if(i>hv){for(let m=0;m<Jd;m++){let g=m*p,y=g+p;d.push(...Jf(e.slice(g,y),u,n,c,r,!1))}d.push("...");for(let m=i-Jd;m<i;m++){let g=m*p,y=g+p;d.push(...Jf(e.slice(g,y),u,n,c,r,m===i-1))}}else for(let m=0;m<i;m++){let g=m*p,y=g+p;d.push(...Jf(e.slice(g,y),u,n,c,r,m===i-1))}let h=l===2?",":"";d[0]="["+d[0]+h;for(let m=1;m<d.length-1;m++)d[m]=" "+d[m]+h;let f=`,
 `;for(let m=2;m<l;m++)f+=`
-`;return d[d.length-1]=" "+d[d.length-1]+"]"+(a?"":f),d}function rp(e){let t=[];for(let n=0;n<e.length;n+=2)t.push([e[n],e[n+1]]);return t}var fn=class{constructor(e,t,n){if(this.dtype=t,this.shape=e.slice(),this.size=Et(e),n!=null){let s=n.length;M(s===this.size,()=>`Length of values '${s}' does not match the size inferred by the shape '${this.size}'.`)}if(t==="complex64")throw new Error("complex64 dtype TensorBuffers are not supported. Please create a TensorBuffer for the real and imaginary parts separately and call tf.complex(real, imag).");this.values=n||t6(t,this.size),this.strides=dc(e)}set(e,...t){t.length===0&&(t=[0]),M(t.length===this.rank,()=>`The number of provided coordinates (${t.length}) must match the rank (${this.rank})`);let n=this.locToIndex(t);this.values[n]=e}get(...e){e.length===0&&(e=[0]);let t=0;for(let s of e){if(s<0||s>=this.shape[t]){let r=`Requested out of range element at ${e}.   Buffer shape=${this.shape}`;throw new Error(r)}t++}let n=e[e.length-1];for(let s=0;s<e.length-1;++s)n+=this.strides[s]*e[s];return this.values[n]}locToIndex(e){if(this.rank===0)return 0;if(this.rank===1)return e[0];let t=e[e.length-1];for(let n=0;n<e.length-1;++n)t+=this.strides[n]*e[n];return t}indexToLoc(e){if(this.rank===0)return[];if(this.rank===1)return[e];let t=new Array(this.shape.length);for(let n=0;n<t.length-1;++n)t[n]=Math.floor(e/this.strides[n]),e-=t[n]*this.strides[n];return t[t.length-1]=e,t}get rank(){return this.shape.length}toTensor(){return kr().makeTensor(this.values,this.shape,this.dtype)}},kr=null,zu=null,lD=null;function uD(e){kr=e}function cD(e){zu=e}function dD(e){lD=e}var tt=class{constructor(e,t,n,s){this.kept=!1,this.isDisposedInternal=!1,this.shape=e.slice(),this.dtype=t||"float32",this.size=Et(e),this.strides=dc(e),this.dataId=n,this.id=s,this.rankType=this.rank<5?this.rank.toString():"higher"}get rank(){return this.shape.length}async buffer(){let e=await this.data();return zu.buffer(this.shape,this.dtype,e)}bufferSync(){return zu.buffer(this.shape,this.dtype,this.dataSync())}async array(){let e=await this.data();return Wu(this.shape,e,this.dtype==="complex64")}arraySync(){return Wu(this.shape,this.dataSync(),this.dtype==="complex64")}async data(){this.throwIfDisposed();let e=kr().read(this.dataId);if(this.dtype==="string"){let t=await e;try{return t.map(n=>mm(n))}catch(n){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}}return e}dataToGPU(e){return this.throwIfDisposed(),kr().readToGPU(this.dataId,e)}dataSync(){this.throwIfDisposed();let e=kr().readSync(this.dataId);if(this.dtype==="string")try{return e.map(t=>mm(t))}catch(t){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}return e}async bytes(){this.throwIfDisposed();let e=await kr().read(this.dataId);return this.dtype==="string"?e:new Uint8Array(e.buffer)}dispose(){this.isDisposed||(kr().disposeTensor(this),this.isDisposedInternal=!0)}get isDisposed(){return this.isDisposedInternal}throwIfDisposed(){if(this.isDisposed)throw new Error("Tensor is disposed.")}print(e=!1){return zu.print(this,e)}clone(){return this.throwIfDisposed(),zu.clone(this)}toString(e=!1){let t=this.dataSync();return oD(t,this.shape,this.dtype,e)}cast(e){return this.throwIfDisposed(),zu.cast(this,e)}variable(e=!0,t,n){return this.throwIfDisposed(),kr().makeVariable(this,e,t,n)}};Object.defineProperty(tt,Symbol.hasInstance,{value:e=>!!e&&e.data!=null&&e.dataSync!=null&&e.throwIfDisposed!=null});function re(){return ky("Tensor",()=>tt)}re();var kp=class extends tt{constructor(e,t,n,s){super(e.shape,e.dtype,e.dataId,s),this.trainable=t,this.name=n}assign(e){if(e.dtype!==this.dtype)throw new Error(`dtype of the new value (${e.dtype}) and previous value (${this.dtype}) must match`);if(!co(e.shape,this.shape))throw new Error(`shape of the new value (${e.shape}) and previous value (${this.shape}) must match`);kr().disposeTensor(this),this.dataId=e.dataId,kr().incRef(this,null)}dispose(){kr().disposeVariable(this),this.isDisposedInternal=!0}};Object.defineProperty(kp,Symbol.hasInstance,{value:e=>e instanceof tt&&e.assign!=null&&e.assign instanceof Function});var Tr={};Ve(Tr,{assertTypesMatch:()=>y6,getTensorsInContainer:()=>Sy,isTensorInList:()=>hD,makeTypesMatch:()=>Gt});var A3;(function(e){e.R0="R0",e.R1="R1",e.R2="R2",e.R3="R3",e.R4="R4",e.R5="R5",e.R6="R6"})(A3||(A3={}));var x3;(function(e){e.float32="float32",e.int32="int32",e.bool="int32",e.complex64="complex64"})(x3||(x3={}));var b3;(function(e){e.float32="float32",e.int32="int32",e.bool="bool",e.complex64="complex64"})(b3||(b3={}));var v3;(function(e){e.float32="float32",e.int32="float32",e.bool="float32",e.complex64="complex64"})(v3||(v3={}));var w3;(function(e){e.float32="complex64",e.int32="complex64",e.bool="complex64",e.complex64="complex64"})(w3||(w3={}));var pD={float32:v3,int32:x3,bool:b3,complex64:w3};function On(e,t){if(e==="string"||t==="string"){if(e==="string"&&t==="string")return"string";throw new Error(`Can not upcast ${e} with ${t}`)}return pD[e][t]}function sh(e){return On(e,"int32")}function Gt(e,t){if(e.dtype===t.dtype)return[e,t];let n=On(e.dtype,t.dtype);return[e.cast(n),t.cast(n)]}function y6(e,t){M(e.dtype===t.dtype,()=>`The dtypes of the first(${e.dtype}) and second(${t.dtype}) input must match`)}function hD(e,t){return t.some(n=>n.id===e.id)}function Sy(e){let t=[];return A6(e,t,new Set),t}function A6(e,t,n){if(e==null)return;if(e instanceof tt){t.push(e);return}if(!fD(e))return;let s=e;for(let r in s){let a=s[r];n.has(a)||(n.add(a),A6(a,t,n))}}function fD(e){return Array.isArray(e)||typeof e=="object"}function r3(e){return e.kernelName!=null}var fv=class{constructor(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null,get kernelNames(){return Array.from(new Set(this.kernels.map(e=>e.name)))}}}dispose(){for(let e in this.registeredVariables)this.registeredVariables[e].dispose()}},Ip=class{constructor(e){this.ENV=e,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new fv}async ready(){if(this.pendingBackendInit!=null)return this.pendingBackendInit.then(()=>{});if(this.backendInstance!=null)return;let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let n=e[t];if(await this.initializeBackend(n).success){await this.setBackend(n);return}}throw new Error("Could not initialize any backends, all backend initializations failed.")}get backend(){if(this.pendingBackendInit!=null)throw new Error(`Backend '${this.backendName}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);if(this.backendInstance==null){let{name:e,asyncInit:t}=this.initializeBackendsAndReturnBest();if(t)throw new Error(`The highest priority backend '${e}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);this.setBackend(e)}return this.backendInstance}backendNames(){return Object.keys(this.registryFactory)}findBackend(e){if(!(e in this.registry))if(e in this.registryFactory){let{asyncInit:t}=this.initializeBackend(e);if(t)return null}else return null;return this.registry[e]}findBackendFactory(e){return e in this.registryFactory?this.registryFactory[e].factory:null}registerBackend(e,t,n=1){return e in this.registryFactory?(Ua(`${e} backend was already registered. Reusing existing backend factory.`),!1):(this.registryFactory[e]={factory:t,priority:n},!0)}async setBackend(e){if(this.registryFactory[e]==null)throw new Error(`Backend name '${e}' not found in registry`);if(this.backendName=e,this.registry[e]==null){this.backendInstance=null;let{success:t,asyncInit:n}=this.initializeBackend(e);if(!(n?await t:t))return!1}return this.backendInstance=this.registry[e],this.setupRegisteredKernels(),this.profiler=new tD(this.backendInstance),!0}setupRegisteredKernels(){qr(this.backendName).forEach(t=>{t.setupFunc!=null&&t.setupFunc(this.backendInstance)})}disposeRegisteredKernels(e){qr(e).forEach(n=>{n.disposeFunc!=null&&n.disposeFunc(this.registry[e])})}initializeBackend(e){let t=this.registryFactory[e];if(t==null)throw new Error(`Cannot initialize backend ${e}, no registration found.`);try{let n=t.factory();if(n&&!(n instanceof cc)&&typeof n.then=="function"){let s=++this.pendingBackendInitId,r=n.then(a=>s<this.pendingBackendInitId?!1:(this.registry[e]=a,this.pendingBackendInit=null,!0)).catch(a=>(s<this.pendingBackendInitId||(this.pendingBackendInit=null,Ua(`Initialization of backend ${e} failed`),Ua(a.stack||a.message)),!1));return this.pendingBackendInit=r,{success:r,asyncInit:!0}}else return this.registry[e]=n,{success:!0,asyncInit:!1}}catch(n){return Ua(`Initialization of backend ${e} failed`),Ua(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${e} backend not found in registry`);this.backendName===e&&this.pendingBackendInit!=null&&this.pendingBackendInitId++,e in this.registry&&(this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e]),delete this.registryFactory[e],this.backendName===e&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(Object.keys(this.registryFactory).length===0)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((e,t)=>this.registryFactory[t].priority-this.registryFactory[e].priority)}initializeBackendsAndReturnBest(){let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let n=e[t],{success:s,asyncInit:r}=this.initializeBackend(n);if(r||s)return{name:n,asyncInit:r}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let n=this.state.tensorInfo.get(t),s=n.backend,r=this.readSync(t),a=s.refCount(t);s.disposeData(t,!0),n.backend=e,e.move(t,r,n.shape,n.dtype,a),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let n=null;if(t==null){if(typeof e!="function")throw new Error("Please provide a function to tidy()");t=e}else{if(typeof e!="string"&&!(e instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof t!="function")throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");n=e}let s;return this.scopedRun(()=>this.startScope(n),()=>this.endScope(s),()=>(s=t(),s instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),s))}scopedRun(e,t,n){e();try{let s=n();return t(),s}catch(s){throw t(),s}}nextTensorId(){return Ip.nextTensorId++}nextVariableId(){return Ip.nextVariableId++}clone(e){let t=W.runKernel(_o,{x:e}),n={x:e},s=a=>({x:()=>{let o="float32",i={x:a},l={dtype:o};return W.runKernel(go,i,l)}}),r=[];return this.addTapeNode(this.state.activeScope.name,n,[t],s,r,{}),t}runKernel(e,t,n){if(this.backendName==null&&this.backend,!(fm(e,this.backendName)!=null))throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){let s=this.backend.numDataIds(),r=0;n.forEach(i=>{r+=i.dtype==="complex64"?3:1});let a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],o=s-t-r-a;if(o>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${o} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],s=this.isTapeOn(),r=this.state.numBytes,a=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let o;this.backendName==null&&this.backend;let i,l=r3(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(r3(e)){let{kernelName:h,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let g=fm(h,this.backendName);M(g!=null,()=>`Cannot find registered kernel '${h}' for backend '${this.backendName}'`),o=()=>{let y=this.backend.numDataIds();i=g.kernelFunc({inputs:f,attrs:m,backend:this.backend});let x=Array.isArray(i)?i:[i];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(h,y,x);let A=x.map(b=>b.rank!=null?b:this.makeTensorFromTensorInfo(b));if(s){let b=this.getTensorsForGradient(h,f,A);n=this.saveTensorsForBackwardMode(b)}return A}}else{let{forwardFunc:h}=e,f=m=>{!s||(n=m.map(g=>this.keep(this.clone(g))))};o=()=>{let m=this.backend.numDataIds();i=this.tidy(()=>h(this.backend,f));let g=Array.isArray(i)?i:[i];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,m,g),g}}let{inputs:u,attrs:c}=e,p=r3(e)?null:e.backwardsFunc,d;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=o():(d=this.profiler.profileKernel(l,u,()=>o()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),s&&this.addTapeNode(l,u,t,p,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-r,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-a,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(h=>u[h]!=null?u[h].shape:null),outputShapes:t.map(h=>h.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(i)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(n=>this.keep(this.clone(n)))}getTensorsForGradient(e,t,n){let s=g3(e);if(s!=null){let r=s.inputsToSave||[],a=s.outputsToSave||[],o;s.saveAllInputs?(M(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),o=Object.keys(t).map(l=>t[l])):o=r.map(l=>t[l]);let i=n.filter((l,u)=>a[u]);return o.concat(i)}return[]}makeTensor(e,t,n,s){if(e==null)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",s=s||this.backend;let r=e;n==="string"&&Ga(e[0])&&(r=e.map(i=>nh(i)));let a=s.write(r,t,n),o=new tt(t,n,a,this.nextTensorId());if(this.trackTensor(o,s),n==="string"){let i=this.state.tensorInfo.get(a),l=r6(r);this.state.numBytes+=l-i.bytes,i.bytes=l}return o}makeTensorFromDataId(e,t,n,s){n=n||"float32";let r={dataId:e,shape:t,dtype:n};return this.makeTensorFromTensorInfo(r,s)}makeTensorFromTensorInfo(e,t){let{dataId:n,shape:s,dtype:r}=e,a=new tt(s,r,n,this.nextTensorId());return this.trackTensor(a,t),a}makeVariable(e,t=!0,n,s){n=n||this.nextVariableId().toString(),s!=null&&s!==e.dtype&&(e=e.cast(s));let r=new kp(e,t,n,this.nextTensorId());if(this.state.registeredVariables[r.name]!=null)throw new Error(`Variable with name ${r.name} was already registered`);return this.state.registeredVariables[r.name]=r,this.incRef(r,this.backend),r}trackTensor(e,t){this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++;let n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*m3(e.dtype)),this.state.numBytes+=n,this.state.tensorInfo.has(e.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(e.dataId,{backend:t||this.backend,dtype:e.dtype,shape:e.shape,bytes:n})),e instanceof kp||this.track(e)}incRef(e,t){this.trackTensor(e,t),this.backend.incRef(e.dataId)}removeDataId(e,t){this.state.tensorInfo.has(e)&&this.state.tensorInfo.get(e).backend===t&&(this.state.tensorInfo.delete(e),this.state.numDataBuffers--)}disposeTensor(e){if(!this.state.tensorInfo.has(e.dataId))return;let t=this.state.tensorInfo.get(e.dataId);if(this.state.numTensors--,e.dtype==="string"&&(this.state.numStringTensors--,this.state.numBytes-=t.bytes),e.dtype!=="complex64"&&e.dtype!=="string"){let n=e.size*m3(e.dtype);this.state.numBytes-=n}t.backend.disposeData(e.dataId)&&this.removeDataId(e.dataId,t.backend)}disposeVariables(){for(let e in this.state.registeredVariables){let t=this.state.registeredVariables[e];this.disposeVariable(t)}}disposeVariable(e){this.disposeTensor(e),this.state.registeredVariables[e.name]!=null&&delete this.state.registeredVariables[e.name]}memory(){let e=this.backend.memory();return e.numTensors=this.state.numTensors,e.numDataBuffers=this.state.numDataBuffers,e.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(e.unreliable=!0,e.reasons==null&&(e.reasons=[]),e.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),e}async profile(e){this.state.profiling=!0;let t=this.state.numBytes,n=this.state.numTensors;this.state.activeProfile.kernels=[],this.state.activeProfile.result=await e(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max(...this.state.activeProfile.kernels.map(s=>s.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-n;for(let s of this.state.activeProfile.kernels)s.kernelTimeMs=await s.kernelTimeMs,s.extraInfo=await s.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(e,t,n,s,r,a){let o={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:r},i=g3(e);i!=null&&(s=i.gradFunc),s!=null&&(o.gradient=l=>(l=l.map((u,c)=>{if(u==null){let p=n[c],d=Um(p.size,p.dtype);return this.makeTensor(d,p.shape,p.dtype)}return u}),s(l.length>1?l:l[0],r,a))),this.state.activeTape.push(o)}keep(e){return e.kept=!0,e}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){let t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){let t=Sy(e),n=new Set(t.map(r=>r.id));for(let r=0;r<this.state.activeScope.track.length;r++){let a=this.state.activeScope.track[r];!a.kept&&!n.has(a.id)&&a.dispose()}let s=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(r=>{!r.kept&&r.scopeId===s.id&&this.track(r)})}gradients(e,t,n,s=!1){if(M(t.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let r=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));M(r instanceof tt,()=>"The result y returned by f() must be a tensor.");let a=rD(this.state.activeTape,t,r);if(!s&&a.length===0&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");return this.tidy("backward",()=>{let o={};o[r.id]=n==null?mD(r.shape):n,aD(o,a,l=>this.tidy(l),gD);let i=t.map(l=>o[l.id]);return this.state.gradientDepth===0&&(this.state.activeTape.forEach(l=>{for(let u of l.saved)u.dispose()}),this.state.activeTape=null),{value:r,grads:i}})}customGrad(e){return M(Ya(e),()=>"The f passed in customGrad(f) must be a function."),(...t)=>{M(t.every(o=>o instanceof tt),()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors");let n,s={};t.forEach((o,i)=>{s[i]=o});let r=(o,i)=>(n=e(...t,i),M(n.value instanceof tt,()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"),M(Ya(n.gradFunc),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."),n.value),a=(o,i)=>{let l=n.gradFunc(o,i),u=Array.isArray(l)?l:[l];M(u.length===t.length,()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...)."),M(u.every(p=>p instanceof tt),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors.");let c={};return u.forEach((p,d)=>{c[d]=()=>p}),c};return this.runKernelFunc({forwardFunc:r,backwardsFunc:a,inputs:s})}}readSync(e){return this.state.tensorInfo.get(e).backend.readSync(e)}read(e){return this.state.tensorInfo.get(e).backend.read(e)}readToGPU(e,t){return this.state.tensorInfo.get(e).backend.readToGPU(e,t)}async time(e){let t=wp(),n=await this.backend.time(e);return n.wallMs=wp()-t,n}track(e){return this.state.activeScope!=null&&(e.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(e)),e}get registeredVariables(){return this.state.registeredVariables}reset(){this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new fv;for(let e in this.registry)this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e];this.backendName=null,this.backendInstance=null,this.pendingBackendInit=null}};Ip.nextTensorId=0;Ip.nextVariableId=0;function mD(e){let t=by(Et(e),"float32");return W.makeTensor(t,e,"float32")}function x6(){let e=u6();if(e._tfengine==null){let t=new l6(e);e._tfengine=new Ip(t)}return z_(e._tfengine.ENV),uD(()=>e._tfengine),e._tfengine}var W=x6();function gD(e,t){let n={a:e,b:t};return W.runKernel(xa,n)}var rh={};Ve(rh,{isBrowser:()=>b6,isMobile:()=>xD,mockIsMobile:()=>AD});function yD(){return typeof navigator!="undefined"&&navigator!=null}var k3;function AD(e){k3=e}function xD(e){if(k3!==void 0)return k3;if(e||yD()){if(e||(e=navigator),e.product==="ReactNative")return!0;let t=e.userAgent||e.vendor||(typeof window!="undefined"?window.opera:"");if(!t){let n=e;return n.userAgentData&&n.userAgentData.mobile}return/(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i.test(t)||/1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\-(n|u)|c55\/|capi|ccwa|cdm\-|cell|chtm|cldc|cmd\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\-s|devi|dica|dmob|do(c|p)o|ds(12|\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\-|_)|g1 u|g560|gene|gf\-5|g\-mo|go(\.w|od)|gr(ad|un)|haie|hcit|hd\-(m|p|t)|hei\-|hi(pt|ta)|hp( i|ip)|hs\-c|ht(c(\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\-(20|go|ma)|i230|iac( |\-|\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\/)|klon|kpt |kwc\-|kyo(c|k)|le(no|xi)|lg( g|\/(k|l|u)|50|54|\-[a-w])|libw|lynx|m1\-w|m3ga|m50\/|ma(te|ui|xo)|mc(01|21|ca)|m\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\-2|po(ck|rt|se)|prox|psio|pt\-g|qa\-a|qc(07|12|21|32|60|\-[2-7]|i\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\-|oo|p\-)|sdk\/|se(c(\-|0|1)|47|mc|nd|ri)|sgh\-|shar|sie(\-|m)|sk\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\-|v\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\-|tdg\-|tel(i|m)|tim\-|t\-mo|to(pl|sh)|ts(70|m\-|m3|m5)|tx\-9|up(\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\-|your|zeto|zte\-/i.test(t.substr(0,4))}return!1}function b6(){return typeof window!="undefined"&&window.document!=null||typeof WorkerGlobalScope!="undefined"}var ir=Z();ir.registerFlag("DEBUG",()=>!1,e=>{e&&console.warn("Debugging mode is ON. The output of every math call will be downloaded to CPU and checked for NaNs. This significantly impacts performance.")});ir.registerFlag("IS_BROWSER",()=>b6());ir.registerFlag("IS_NODE",()=>typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined");ir.registerFlag("IS_CHROME",()=>typeof navigator!="undefined"&&navigator!=null&&navigator.userAgent!=null&&/Chrome/.test(navigator.userAgent)&&/Google Inc/.test(navigator.vendor));ir.registerFlag("PROD",()=>!1);ir.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY",()=>ir.getBool("DEBUG"));ir.registerFlag("DEPRECATION_WARNINGS_ENABLED",()=>!0);ir.registerFlag("IS_TEST",()=>!1);ir.registerFlag("CHECK_COMPUTATION_FOR_ERRORS",()=>!0);ir.registerFlag("WRAP_TO_IMAGEBITMAP",()=>!1);ir.registerFlag("ENGINE_COMPILE_ONLY",()=>!1);function Xr(e,t){let n=e;if(Pn(e))return t==="string"?[]:[e.length];if(!Array.isArray(e))return[];let s=[];for(;Array.isArray(n)||Pn(n)&&t!=="string";)s.push(n.length),n=n[0];return Array.isArray(e)&&Z().getBool("TENSORLIKE_CHECK_SHAPE_CONSISTENCY")&&v6(e,s,[]),s}function v6(e,t,n){if(n=n||[],!Array.isArray(e)&&!Pn(e)){M(t.length===0,()=>`Element arr[${n.join("][")}] is a primitive, but should be an array/TypedArray of ${t[0]} elements`);return}M(t.length>0,()=>`Element arr[${n.join("][")}] should be a primitive, but is an array of ${e.length} elements`),M(e.length===t[0],()=>`Element arr[${n.join("][")}] should have ${t[0]} elements, but has ${e.length} elements`);let s=t.slice(1);for(let r=0;r<e.length;++r)v6(e[r],s,n.concat(r))}function mv(e,t,n,s){if(e!=="string_or_numeric"){if(e==null)throw new Error("Expected dtype cannot be null.");if(e!=="numeric"&&e!==t||e==="numeric"&&t==="string")throw new Error(`Argument '${n}' passed to '${s}' must be ${e} tensor, but got ${t} tensor`)}}function D(e,t,n,s="numeric"){if(e instanceof tt)return mv(s,e.dtype,t,n),e;let r=Vm(e);if(r!=="string"&&["bool","int32","float32"].indexOf(s)>=0&&(r=s),mv(s,r,t,n),e==null||!Pn(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string"){let l=e==null?"null":e.constructor.name;throw new Error(`Argument '${t}' passed to '${n}' must be a Tensor or TensorLike, but got '${l}'`)}let a=Xr(e,r);!Pn(e)&&!Array.isArray(e)&&(e=[e]);let i=r!=="string"?f0(e,r):Xi(e,[],!0);return W.makeTensor(i,a,r)}function Sp(e,t,n,s="numeric"){if(!Array.isArray(e))throw new Error(`Argument ${t} passed to ${n} must be a \`Tensor[]\` or \`TensorLike[]\``);return e.map((a,o)=>D(a,`${t}[${o}]`,n,s))}var Cy="__op";function V(e){let t=Object.keys(e);if(t.length!==1)throw new Error(`Please provide an object with a single key (operation name) mapping to a function. Got an object with ${t.length} keys.`);let n=t[0],s=e[n];n.endsWith("_")&&(n=n.substring(0,n.length-1)),n=n+Cy;let r=(...a)=>{W.startScope(n);try{let o=s(...a);return wy(o)&&console.error("Cannot return a Promise inside of tidy."),W.endScope(o),o}catch(o){throw W.endScope(null),o}};return Object.defineProperty(r,"name",{value:n,configurable:!0}),r}function bD(e,t){let n=D(e,"real","complex"),s=D(t,"imag","complex");ns(n.shape,s.shape,`real and imag shapes, ${n.shape} and ${s.shape}, must match in call to tf.complex().`);let r={real:n,imag:s};return W.runKernel(Lp,r)}var fa=V({complex_:bD});function oi(e,t,n,s){if(s==null&&(s=Vm(e)),s==="complex64")throw new Error("Cannot construct a complex64 tensor directly. Please use tf.complex(real, imag).");if(!Pn(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string")throw new Error("values passed to tensor(values) must be a number/boolean/string or an array of numbers/booleans/strings, or a TypedArray");if(t!=null){vy(t);let r=Et(t),a=Et(n);M(r===a,()=>`Based on the provided shape, [${t}], the tensor should have ${r} values but has ${a}`);for(let o=0;o<n.length;++o){let i=n[o],l=o===n.length-1?i!==Et(t.slice(o)):!0;M(n[o]===t[o]||!l,()=>`Error creating a new Tensor. Inferred shape (${n}) does not match the provided shape (${t}). `)}}return!Pn(e)&&!Array.isArray(e)&&(e=[e]),t=t||n,e=s!=="string"?f0(e,s):Xi(e,[],!0),W.makeTensor(e,t,s)}function ft(e,t,n){let s=Xr(e,n);return oi(e,t,s,n)}var I3={float32:4,float16:2,int32:4,uint16:2,uint8:1,bool:1,complex64:8},gm=4;async function vD(e,t){let n=[],s=[],r=Array.isArray(e)?e.map(o=>o.name):Object.keys(e);for(let o=0;o<r.length;++o){let i=r[o],l=Array.isArray(e)?e[o].tensor:e[i];if(l.dtype!=="float32"&&l.dtype!=="int32"&&l.dtype!=="bool"&&l.dtype!=="string"&&l.dtype!=="complex64")throw new Error(`Unsupported dtype in weight '${i}': ${l.dtype}`);let u={name:i,shape:l.shape,dtype:l.dtype};if(l.dtype==="string"){let c=new Promise(async p=>{let d=await l.bytes(),h=d.reduce((g,y)=>g+y.length,0)+gm*d.length,f=new Uint8Array(h),m=0;for(let g=0;g<d.length;g++){let y=d[g],x=new Uint8Array(new Uint32Array([y.length]).buffer);f.set(x,m),m+=gm,f.set(y,m),m+=y.length}p(f)});s.push(c)}else s.push(l.data());t!=null&&(u.group=t),n.push(u)}let a=await Promise.all(s);return{data:wD(a),specs:n}}function w6(e,t){let n={},s,r=0;for(let a of t){let o=a.name,i=a.dtype,l=a.shape,u=Et(l),c;if("quantization"in a){let p=a.quantization;if(p.dtype==="uint8"||p.dtype==="uint16"){if(!("min"in p&&"scale"in p))throw new Error(`Weight ${a.name} with quantization ${p.dtype} doesn't have corresponding metadata min and scale.`)}else if(p.dtype==="float16"){if(i!=="float32")throw new Error(`Weight ${a.name} is quantized with ${p.dtype} which only supports weights of type float32 not ${i}.`)}else throw new Error(`Weight ${a.name} has unknown quantization dtype ${p.dtype}. Supported quantization dtypes are: 'uint8', 'uint16', and 'float16'.`);let d=I3[p.dtype],h=e.slice(r,r+u*d),f=p.dtype==="uint8"?new Uint8Array(h):new Uint16Array(h);if(i==="float32")if(p.dtype==="uint8"||p.dtype==="uint16"){c=new Float32Array(f.length);for(let m=0;m<f.length;m++){let g=f[m];c[m]=g*p.scale+p.min}}else if(p.dtype==="float16")s===void 0&&(s=ND()),c=s(f);else throw new Error(`Unsupported quantization type ${p.dtype} for weight type float32.`);else if(i==="int32"){if(p.dtype!=="uint8"&&p.dtype!=="uint16")throw new Error(`Unsupported quantization type ${p.dtype} for weight type int32.`);c=new Int32Array(f.length);for(let m=0;m<f.length;m++){let g=f[m];c[m]=Math.round(g*p.scale+p.min)}}else throw new Error(`Unsupported dtype in weight '${o}': ${i}`);r+=u*d}else if(i==="string"){let p=Et(a.shape);c=[];for(let d=0;d<p;d++){let h=new Uint32Array(e.slice(r,r+gm))[0];r+=gm;let f=new Uint8Array(e.slice(r,r+h));c.push(f),r+=h}}else{let p=I3[i],d=e.slice(r,r+u*p);if(i==="float32")c=new Float32Array(d);else if(i==="int32")c=new Int32Array(d);else if(i==="bool")c=new Uint8Array(d);else if(i==="complex64"){c=new Float32Array(d);let h=new Float32Array(c.length/2),f=new Float32Array(c.length/2);for(let y=0;y<h.length;y++)h[y]=c[y*2],f[y]=c[y*2+1];let m=ft(h,l,"float32"),g=ft(f,l,"float32");n[o]=fa(m,g),m.dispose(),g.dispose()}else throw new Error(`Unsupported dtype in weight '${o}': ${i}`);r+=u*p}i!=="complex64"&&(n[o]=ft(c,l,i))}return n}function wD(e){if(e===null)throw new Error(`Invalid input value: ${JSON.stringify(e)}`);let t=0,n=[];e.forEach(a=>{if(t+=a.byteLength,n.push(a.byteLength===a.buffer.byteLength?a:new a.constructor(a)),!(a instanceof Float32Array||a instanceof Int32Array||a instanceof Uint8Array))throw new Error(`Unsupported TypedArray subtype: ${a.constructor.name}`)});let s=new Uint8Array(t),r=0;return n.forEach(a=>{s.set(new Uint8Array(a.buffer),r),r+=a.byteLength}),s.buffer}var Ty=typeof Buffer!="undefined"&&(typeof Blob=="undefined"||typeof atob=="undefined"||typeof btoa=="undefined");function gv(e){return Ty?Buffer.byteLength(e):new Blob([e]).size}function kD(e){if(Ty)return Buffer.from(e).toString("base64");let t=new Uint8Array(e),n="";for(let s=0,r=t.length;s<r;s++)n+=String.fromCharCode(t[s]);return btoa(n)}function ID(e){if(Ty){let s=Buffer.from(e,"base64");return s.buffer.slice(s.byteOffset,s.byteOffset+s.byteLength)}let t=atob(e),n=new Uint8Array(t.length);for(let s=0;s<t.length;++s)n.set([t.charCodeAt(s)],s);return n.buffer}function Ny(e){if(e.length===1)return e[0];let t=0;e.forEach(r=>{t+=r.byteLength});let n=new Uint8Array(t),s=0;return e.forEach(r=>{n.set(new Uint8Array(r),s),s+=r.byteLength}),n.buffer}function yv(e){let t="/";for(e=e.trim();e.endsWith(t);)e=e.slice(0,e.length-1);let n=e.split(t);return n[n.length-1]}function k6(e,t){let n={modelTopology:e.modelTopology,format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy,weightsManifest:t};return e.signature!=null&&(n.signature=e.signature),e.userDefinedMetadata!=null&&(n.userDefinedMetadata=e.userDefinedMetadata),e.modelInitializer!=null&&(n.modelInitializer=e.modelInitializer),e.trainingConfig!=null&&(n.trainingConfig=e.trainingConfig),n}async function Ey(e,t){let n={modelTopology:e.modelTopology,format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy};if(e.trainingConfig!=null&&(n.trainingConfig=e.trainingConfig),e.weightsManifest!=null){let[s,r]=await t(e.weightsManifest);n.weightSpecs=s,n.weightData=r}return e.signature!=null&&(n.signature=e.signature),e.userDefinedMetadata!=null&&(n.userDefinedMetadata=e.userDefinedMetadata),e.modelInitializer!=null&&(n.modelInitializer=e.modelInitializer),n}function ah(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("Expected JSON model topology, received ArrayBuffer.");return{dateSaved:new Date,modelTopologyType:"JSON",modelTopologyBytes:e.modelTopology==null?0:gv(JSON.stringify(e.modelTopology)),weightSpecsBytes:e.weightSpecs==null?0:gv(JSON.stringify(e.weightSpecs)),weightDataBytes:e.weightData==null?0:e.weightData.byteLength}}function SD(){let e=n=>{let s=n<<13,r=0;for(;(s&8388608)===0;)r-=8388608,s<<=1;return s&=-8388609,r+=947912704,s|r},t=new Uint32Array(2048);t[0]=0;for(let n=1;n<1024;n++)t[n]=e(n);for(let n=1024;n<2048;n++)t[n]=939524096+(n-1024<<13);return t}function CD(){let e=new Uint32Array(64);e[0]=0,e[31]=1199570944,e[32]=2147483648,e[63]=3347054592;for(let t=1;t<31;t++)e[t]=t<<23;for(let t=33;t<63;t++)e[t]=2147483648+(t-32<<23);return e}function TD(){let e=new Uint32Array(64);for(let t=0;t<64;t++)e[t]=1024;return e[0]=e[32]=0,e}function ND(){let e=SD(),t=CD(),n=TD();return s=>{let r=new ArrayBuffer(4*s.length),a=new Uint32Array(r);for(let o=0;o<s.length;o++){let i=s[o],l=e[n[i>>10]+(i&1023)]+t[i>>10];a[o]=l}return new Float32Array(r)}}var qt=class{constructor(){this.saveRouters=[],this.loadRouters=[]}static getInstance(){return qt.instance==null&&(qt.instance=new qt),qt.instance}static registerSaveRouter(e){qt.getInstance().saveRouters.push(e)}static registerLoadRouter(e){qt.getInstance().loadRouters.push(e)}static getSaveHandlers(e){return qt.getHandlers(e,"save")}static getLoadHandlers(e,t){return qt.getHandlers(e,"load",t)}static getHandlers(e,t,n){let s=[];return(t==="load"?qt.getInstance().loadRouters:qt.getInstance().saveRouters).forEach(a=>{let o=a(e,n);o!==null&&s.push(o)}),s}},ED=e=>qt.registerSaveRouter(e),RD=e=>qt.registerLoadRouter(e),_D=e=>qt.getSaveHandlers(e),DD=(e,t)=>qt.getLoadHandlers(e,t),S3="tensorflowjs",C3=1,Wi="models_store",Ha="model_info_store";function I6(){if(!Z().getBool("IS_BROWSER"))throw new Error("Failed to obtain IndexedDB factory because the current environmentis not a web browser.");let e=typeof window=="undefined"?self:window,t=e.indexedDB||e.mozIndexedDB||e.webkitIndexedDB||e.msIndexedDB||e.shimIndexedDB;if(t==null)throw new Error("The current browser does not appear to support IndexedDB.");return t}function T3(e){let t=e.result;t.createObjectStore(Wi,{keyPath:"modelPath"}),t.createObjectStore(Ha,{keyPath:"modelPath"})}var Ki=class{constructor(e){if(this.indexedDB=I6(),e==null||!e)throw new Error("For IndexedDB, modelPath must not be null, undefined or empty.");this.modelPath=e}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");return this.databaseAction(this.modelPath,e)}async load(){return this.databaseAction(this.modelPath)}databaseAction(e,t){return new Promise((n,s)=>{let r=this.indexedDB.open(S3,C3);r.onupgradeneeded=()=>T3(r),r.onsuccess=()=>{let a=r.result;if(t==null){let o=a.transaction(Wi,"readonly"),l=o.objectStore(Wi).get(this.modelPath);l.onsuccess=()=>{if(l.result==null)return a.close(),s(new Error(`Cannot find model with path '${this.modelPath}' in IndexedDB.`));n(l.result.modelArtifacts)},l.onerror=u=>(a.close(),s(l.error)),o.oncomplete=()=>a.close()}else{let o=ah(t),i=a.transaction(Ha,"readwrite"),l=i.objectStore(Ha),u=l.put({modelPath:this.modelPath,modelArtifactsInfo:o}),c;u.onsuccess=()=>{c=a.transaction(Wi,"readwrite");let d=c.objectStore(Wi).put({modelPath:this.modelPath,modelArtifacts:t,modelArtifactsInfo:o});d.onsuccess=()=>n({modelArtifactsInfo:o}),d.onerror=h=>{l=i.objectStore(Ha);let f=l.delete(this.modelPath);f.onsuccess=()=>(a.close(),s(d.error)),f.onerror=m=>(a.close(),s(d.error))}},u.onerror=p=>(a.close(),s(u.error)),i.oncomplete=()=>{c==null?a.close():c.oncomplete=()=>a.close()}}},r.onerror=a=>s(r.error)})}};Ki.URL_SCHEME="indexeddb://";var S6=e=>Z().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Ki.URL_SCHEME)?$D(e.slice(Ki.URL_SCHEME.length)):null;qt.registerSaveRouter(S6);qt.registerLoadRouter(S6);function $D(e){return new Ki(e)}function PD(e){return e.startsWith(Ki.URL_SCHEME)?e.slice(Ki.URL_SCHEME.length):e}var FD=class{constructor(){this.indexedDB=I6()}async listModels(){return new Promise((e,t)=>{let n=this.indexedDB.open(S3,C3);n.onupgradeneeded=()=>T3(n),n.onsuccess=()=>{let s=n.result,r=s.transaction(Ha,"readonly"),o=r.objectStore(Ha).getAll();o.onsuccess=()=>{let i={};for(let l of o.result)i[l.modelPath]=l.modelArtifactsInfo;e(i)},o.onerror=i=>(s.close(),t(o.error)),r.oncomplete=()=>s.close()},n.onerror=s=>t(n.error)})}async removeModel(e){return e=PD(e),new Promise((t,n)=>{let s=this.indexedDB.open(S3,C3);s.onupgradeneeded=()=>T3(s),s.onsuccess=()=>{let r=s.result,a=r.transaction(Ha,"readwrite"),o=a.objectStore(Ha),i=o.get(e),l;i.onsuccess=()=>{if(i.result==null)return r.close(),n(new Error(`Cannot find model with path '${e}' in IndexedDB.`));{let u=o.delete(e),c=()=>{l=r.transaction(Wi,"readwrite");let d=l.objectStore(Wi).delete(e);d.onsuccess=()=>t(i.result.modelArtifactsInfo),d.onerror=h=>n(i.error)};u.onsuccess=c,u.onerror=p=>(c(),r.close(),n(i.error))}},i.onerror=u=>(r.close(),n(i.error)),a.oncomplete=()=>{l==null?r.close():l.oncomplete=()=>r.close()}},s.onerror=r=>n(s.error)})}},da="/",Lu="tensorflowjs_models",C6="info",OD="model_topology",MD="weight_specs",zD="weight_data",LD="model_metadata";function T6(e){return{info:[Lu,e,C6].join(da),topology:[Lu,e,OD].join(da),weightSpecs:[Lu,e,MD].join(da),weightData:[Lu,e,zD].join(da),modelMetadata:[Lu,e,LD].join(da)}}function N6(e){for(let t of Object.values(e))window.localStorage.removeItem(t)}function BD(e){let t=e.split(da);if(t.length<3)throw new Error(`Invalid key format: ${e}`);return t.slice(1,t.length-1).join(da)}function WD(e){return e.startsWith(Zi.URL_SCHEME)?e.slice(Zi.URL_SCHEME.length):e}var Zi=class{constructor(e){if(!Z().getBool("IS_BROWSER")||typeof window=="undefined"||typeof window.localStorage=="undefined")throw new Error("The current environment does not support local storage.");if(this.LS=window.localStorage,e==null||!e)throw new Error("For local storage, modelPath must not be null, undefined or empty.");this.modelPath=e,this.keys=T6(this.modelPath)}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");{let t=JSON.stringify(e.modelTopology),n=JSON.stringify(e.weightSpecs),s=ah(e);try{this.LS.setItem(this.keys.info,JSON.stringify(s)),this.LS.setItem(this.keys.topology,t),this.LS.setItem(this.keys.weightSpecs,n),this.LS.setItem(this.keys.weightData,kD(e.weightData));let r={format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy,signature:e.signature!=null?e.signature:void 0,userDefinedMetadata:e.userDefinedMetadata!=null?e.userDefinedMetadata:void 0,modelInitializer:e.modelInitializer!=null?e.modelInitializer:void 0,trainingConfig:e.trainingConfig!=null?e.trainingConfig:void 0};return this.LS.setItem(this.keys.modelMetadata,JSON.stringify(r)),{modelArtifactsInfo:s}}catch(r){throw N6(this.keys),new Error(`Failed to save model '${this.modelPath}' to local storage: size quota being exceeded is a possible cause of this failure: modelTopologyBytes=${s.modelTopologyBytes}, weightSpecsBytes=${s.weightSpecsBytes}, weightDataBytes=${s.weightDataBytes}.`)}}}async load(){let e=JSON.parse(this.LS.getItem(this.keys.info));if(e==null)throw new Error(`In local storage, there is no model with name '${this.modelPath}'`);if(e.modelTopologyType!=="JSON")throw new Error("BrowserLocalStorage does not support loading non-JSON model topology yet.");let t={},n=JSON.parse(this.LS.getItem(this.keys.topology));if(n==null)throw new Error(`In local storage, the topology of model '${this.modelPath}' is missing.`);t.modelTopology=n;let s=JSON.parse(this.LS.getItem(this.keys.weightSpecs));if(s==null)throw new Error(`In local storage, the weight specs of model '${this.modelPath}' are missing.`);t.weightSpecs=s;let r=this.LS.getItem(this.keys.modelMetadata);if(r!=null){let o=JSON.parse(r);t.format=o.format,t.generatedBy=o.generatedBy,t.convertedBy=o.convertedBy,o.signature!=null&&(t.signature=o.signature),o.userDefinedMetadata!=null&&(t.userDefinedMetadata=o.userDefinedMetadata),o.modelInitializer!=null&&(t.modelInitializer=o.modelInitializer),o.trainingConfig!=null&&(t.trainingConfig=o.trainingConfig)}let a=this.LS.getItem(this.keys.weightData);if(a==null)throw new Error(`In local storage, the binary weight values of model '${this.modelPath}' are missing.`);return t.weightData=ID(a),t}};Zi.URL_SCHEME="localstorage://";var E6=e=>Z().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Zi.URL_SCHEME)?VD(e.slice(Zi.URL_SCHEME.length)):null;qt.registerSaveRouter(E6);qt.registerLoadRouter(E6);function VD(e){return new Zi(e)}var UD=class{constructor(){M(Z().getBool("IS_BROWSER"),()=>"Current environment is not a web browser"),M(typeof window=="undefined"||typeof window.localStorage!="undefined",()=>"Current browser does not appear to support localStorage"),this.LS=window.localStorage}async listModels(){let e={},t=Lu+da,n=da+C6;for(let s=0;s<this.LS.length;++s){let r=this.LS.key(s);if(r.startsWith(t)&&r.endsWith(n)){let a=BD(r);e[a]=JSON.parse(this.LS.getItem(r))}}return e}async removeModel(e){e=WD(e);let t=T6(e);if(this.LS.getItem(t.info)==null)throw new Error(`Cannot find model at path '${e}'`);let n=JSON.parse(this.LS.getItem(t.info));return N6(t),n}},Vu="://",ds=class{constructor(){this.managers={}}static getInstance(){return ds.instance==null&&(ds.instance=new ds),ds.instance}static registerManager(e,t){M(e!=null,()=>"scheme must not be undefined or null."),e.endsWith(Vu)&&(e=e.slice(0,e.indexOf(Vu))),M(e.length>0,()=>"scheme must not be an empty string.");let n=ds.getInstance();M(n.managers[e]==null,()=>`A model store manager is already registered for scheme '${e}'.`),n.managers[e]=t}static getManager(e){let t=ds.getInstance().managers[e];if(t==null)throw new Error(`Cannot find model manager for scheme '${e}'`);return t}static getSchemes(){return Object.keys(ds.getInstance().managers)}};function em(e){if(e.indexOf(Vu)===-1)throw new Error(`The url string provided does not contain a scheme. Supported schemes are: ${ds.getSchemes().join(",")}`);return{scheme:e.split(Vu)[0],path:e.split(Vu)[1]}}async function R6(e,t,n=!1){M(e!==t,()=>`Old path and new path are the same: '${e}'`);let s=qt.getLoadHandlers(e);M(s.length>0,()=>`Copying failed because no load handler is found for source URL ${e}.`),M(s.length<2,()=>`Copying failed because more than one (${s.length}) load handlers for source URL ${e}.`);let r=s[0],a=qt.getSaveHandlers(t);M(a.length>0,()=>`Copying failed because no save handler is found for destination URL ${t}.`),M(a.length<2,()=>`Copying failed because more than one (${s.length}) save handlers for destination URL ${t}.`);let o=a[0],i=em(e).scheme,l=em(e).path,u=i===em(e).scheme,c=await r.load();n&&u&&await ds.getManager(i).removeModel(l);let p=await o.save(c);return n&&!u&&await ds.getManager(i).removeModel(l),p.modelArtifactsInfo}async function GD(){let e=ds.getSchemes(),t={};for(let n of e){let s=await ds.getManager(n).listModels();for(let r in s){let a=n+Vu+r;t[a]=s[r]}}return t}async function HD(e){let t=em(e);return ds.getManager(t.scheme).removeModel(t.path)}async function jD(e,t){return R6(e,t,!1)}async function qD(e,t){return R6(e,t,!0)}var XD=class{fetch(e,t){return fetch(e,t)}now(){return performance.now()}encode(e,t){if(t!=="utf-8"&&t!=="utf8")throw new Error(`Browser's encoder only supports utf-8, but got ${t}`);return this.textEncoder==null&&(this.textEncoder=new TextEncoder),this.textEncoder.encode(e)}decode(e,t){return new TextDecoder(t).decode(e)}};if(Z().get("IS_BROWSER")){Z().setPlatform("browser",new XD);try{ds.registerManager(Zi.URL_SCHEME,new UD)}catch(e){}try{ds.registerManager(Ki.URL_SCHEME,new FD)}catch(e){}}var KD={importFetch:()=>n_()},a3,ZD=class{constructor(){this.util=s_(),this.textEncoder=new this.util.TextEncoder}fetch(e,t){return Z().global.fetch!=null?Z().global.fetch(e,t):(a3==null&&(a3=KD.importFetch()),a3(e,t))}now(){let e=process.hrtime();return e[0]*1e3+e[1]/1e6}encode(e,t){if(t!=="utf-8"&&t!=="utf8")throw new Error(`Node built-in encoder only supports utf-8, but got ${t}`);return this.textEncoder.encode(e)}decode(e,t){return e.length===0?"":new this.util.TextDecoder(t).decode(e)}};Z().get("IS_NODE")&&!Z().get("IS_BROWSER")&&Z().setPlatform("node",new ZD);function Le(e,t="float32",n){return t=t||"float32",vy(e),new fn(e,t,n)}function YD(e,t){let n=D(e,"x","cast");if(!s6(t))throw new Error(`Failed to cast to unknown dtype ${t}`);if(t==="string"&&n.dtype!=="string"||t!=="string"&&n.dtype==="string")throw new Error("Only strings can be casted to strings");let s={x:n},r={dtype:t};return W.runKernel(go,s,r)}var ge=V({cast_:YD});function JD(e){let n={x:D(e,"x","clone","string_or_numeric")};return W.runKernel(_o,n)}var Fn=V({clone_:JD});function Ry(e,t=!1){console.log(e.toString(t))}x6();var QD={buffer:Le,cast:ge,clone:Fn,print:Ry};cD(QD);var Ts={};Ve(Ts,{browserFiles:()=>o$,browserHTTPRequest:()=>d$,concatenateArrayBuffers:()=>Ny,copyModel:()=>jD,decodeWeights:()=>w6,encodeWeights:()=>vD,fromMemory:()=>h$,fromMemorySync:()=>F6,getLoadHandlers:()=>DD,getModelArtifactsForJSON:()=>Ey,getModelArtifactsInfoForJSON:()=>ah,getSaveHandlers:()=>_D,http:()=>Dy,isHTTPScheme:()=>N3,listModels:()=>GD,loadWeights:()=>i$,moveModel:()=>qD,registerLoadRouter:()=>RD,registerSaveRouter:()=>ED,removeModel:()=>HD,weightsLoaderFactory:()=>D6,withSaveHandler:()=>f$,withSaveHandlerSync:()=>m$});var e$="model",t$=".json",n$=".weights.bin";function Av(e){return new Promise(t=>setTimeout(t)).then(e)}var Ku=class{constructor(e){if(!Z().getBool("IS_BROWSER"))throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");e.startsWith(Ku.URL_SCHEME)&&(e=e.slice(Ku.URL_SCHEME.length)),(e==null||e.length===0)&&(e=e$),this.modelJsonFileName=e+t$,this.weightDataFileName=e+n$}async save(e){if(typeof document=="undefined")throw new Error("Browser downloads are not supported in this environment since `document` is not present");let t=window.URL.createObjectURL(new Blob([e.weightData],{type:"application/octet-stream"}));if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserDownloads.save() does not support saving model topology in binary formats yet.");{let n=[{paths:["./"+this.weightDataFileName],weights:e.weightSpecs}],s=k6(e,n),r=window.URL.createObjectURL(new Blob([JSON.stringify(s)],{type:"application/json"})),a=this.modelJsonAnchor==null?document.createElement("a"):this.modelJsonAnchor;if(a.download=this.modelJsonFileName,a.href=r,await Av(()=>a.dispatchEvent(new MouseEvent("click"))),e.weightData!=null){let o=this.weightDataAnchor==null?document.createElement("a"):this.weightDataAnchor;o.download=this.weightDataFileName,o.href=t,await Av(()=>o.dispatchEvent(new MouseEvent("click")))}return{modelArtifactsInfo:ah(e)}}}};Ku.URL_SCHEME="downloads://";var s$=class{constructor(e){if(e==null||e.length<1)throw new Error(`When calling browserFiles, at least 1 file is required, but received ${e}`);this.jsonFile=e[0],this.weightsFiles=e.slice(1)}async load(){return new Promise((e,t)=>{let n=new FileReader;n.onload=s=>{let r=JSON.parse(s.target.result),a=r.modelTopology;if(a==null){t(new Error(`modelTopology field is missing from file ${this.jsonFile.name}`));return}if(r.weightsManifest==null){t(new Error(`weightManifest field is missing from file ${this.jsonFile.name}`));return}if(this.weightsFiles.length===0){e({modelTopology:a});return}let i=Ey(r,l=>this.loadWeights(l));e(i)},n.onerror=s=>t(`Failed to read model topology and weights manifest JSON from file '${this.jsonFile.name}'. BrowserFiles supports loading Keras-style tf.Model artifacts only.`),n.readAsText(this.jsonFile)})}loadWeights(e){let t=[],n=[];for(let a of e)t.push(...a.weights),n.push(...a.paths);let s=this.checkManifestAndWeightFiles(e),r=n.map(a=>this.loadWeightsFile(a,s[a]));return Promise.all(r).then(a=>[t,Ny(a)])}loadWeightsFile(e,t){return new Promise((n,s)=>{let r=new FileReader;r.onload=a=>{let o=a.target.result;n(o)},r.onerror=a=>s(`Failed to weights data from file of path '${e}'.`),r.readAsArrayBuffer(t)})}checkManifestAndWeightFiles(e){let t=[],n=this.weightsFiles.map(r=>yv(r.name)),s={};for(let r of e)r.paths.forEach(a=>{let o=yv(a);if(t.indexOf(o)!==-1)throw new Error(`Duplicate file basename found in weights manifest: '${o}'`);if(t.push(o),n.indexOf(o)===-1)throw new Error(`Weight file with basename '${o}' is not provided.`);s[a]=this.weightsFiles[n.indexOf(o)]});if(t.length!==this.weightsFiles.length)throw new Error(`Mismatch in the number of files in weights manifest (${t.length}) and the number of weight files provided (${this.weightsFiles.length}).`);return s}},r$=e=>Z().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Ku.URL_SCHEME)?a$(e.slice(Ku.URL_SCHEME.length)):null;qt.registerSaveRouter(r$);function a$(e="model"){return new Ku(e)}function o$(e){return new s$(e)}function xv(e,t,n,s){o(e),n=n==null?0:n,s=s==null?1:s,i(n,s);let r=0,a=l=>(l.then(u=>{let c=n+ ++r/e.length*(s-n);return t(c),u}),l);function o(l){M(l!=null&&Array.isArray(l)&&l.length>0,()=>"promises must be a none empty array")}function i(l,u){M(l>=0&&l<=1,()=>`Progress fraction must be in range [0, 1], but got startFraction ${l}`),M(u>=0&&u<=1,()=>`Progress fraction must be in range [0, 1], but got endFraction ${u}`),M(u>=l,()=>`startFraction must be no more than endFraction, but got startFraction ${l} and endFraction ${u}`)}return Promise.all(e.map(a))}async function _6(e,t){t==null&&(t={});let n=t.fetchFunc==null?Z().platform.fetch:t.fetchFunc,s=e.map(p=>n(p,t.requestInit,{isBinary:!0})),r=0,a=.5,i=(t.onProgress==null?await Promise.all(s):await xv(s,t.onProgress,r,a)).map(p=>p.arrayBuffer()),l=.5,u=1;return t.onProgress==null?await Promise.all(i):await xv(i,t.onProgress,l,u)}async function i$(e,t="",n,s){return D6(o=>_6(o,{requestInit:s}))(e,t,n)}function D6(e){return async(t,n="",s)=>{let r=t.map(()=>!1),a={},o=s!=null?s.map(()=>!1):[],i=[];if(t.forEach((h,f)=>{let m=0;h.weights.forEach(g=>{let y="quantization"in g?g.quantization.dtype:g.dtype,x=I3[y]*Et(g.shape),A=()=>{r[f]=!0,a[f]==null&&(a[f]=[]),a[f].push({manifestEntry:g,groupOffset:m,sizeBytes:x})};s!=null?s.forEach((b,w)=>{b===g.name&&(A(),o[w]=!0)}):A(),i.push(g.name),m+=x})}),!o.every(h=>h)){let h=s.filter((f,m)=>!o[m]);throw new Error(`Could not find weights in manifest with names: ${h.join(", ")}. 
-Manifest JSON has weights with names: ${i.join(", ")}.`)}let l=r.reduce((h,f,m)=>(f&&h.push(m),h),[]),u=[];l.forEach(h=>{t[h].paths.forEach(f=>{let m=n+(n.endsWith("/")?"":"/")+f;u.push(m)})});let c=await e(u),p={},d=0;return l.forEach(h=>{let f=t[h].paths.length,m=0;for(let b=0;b<f;b++)m+=c[d+b].byteLength;let g=new ArrayBuffer(m),y=new Uint8Array(g),x=0;for(let b=0;b<f;b++){let w=new Uint8Array(c[d+b]);y.set(w,x),x+=w.byteLength}a[h].forEach(b=>{let w=g.slice(b.groupOffset,b.groupOffset+b.sizeBytes),k=w6(w,[b.manifestEntry]);for(let S in k)p[S]=k[S]}),d+=f}),p}}var l$="application/octet-stream",u$="application/json",_y=class{constructor(e,t){if(this.DEFAULT_METHOD="POST",t==null&&(t={}),this.weightPathPrefix=t.weightPathPrefix,this.onProgress=t.onProgress,this.weightUrlConverter=t.weightUrlConverter,t.fetchFunc!=null?(M(typeof t.fetchFunc=="function",()=>"Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)"),this.fetch=t.fetchFunc):this.fetch=Z().platform.fetch,M(e!=null&&e.length>0,()=>"URL path for http must not be null, undefined or empty."),Array.isArray(e)&&M(e.length===2,()=>`URL paths for http must have a length of 2, (actual length is ${e.length}).`),this.path=e,t.requestInit!=null&&t.requestInit.body!=null)throw new Error("requestInit is expected to have no pre-existing body, but has one.");this.requestInit=t.requestInit||{}}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.");let t=Object.assign({method:this.DEFAULT_METHOD},this.requestInit);t.body=new FormData;let n=[{paths:["./model.weights.bin"],weights:e.weightSpecs}],s=k6(e,n);t.body.append("model.json",new Blob([JSON.stringify(s)],{type:u$}),"model.json"),e.weightData!=null&&t.body.append("model.weights.bin",new Blob([e.weightData],{type:l$}),"model.weights.bin");let r=await this.fetch(this.path,t);if(r.ok)return{modelArtifactsInfo:ah(e),responses:[r]};throw new Error(`BrowserHTTPRequest.save() failed due to HTTP response status ${r.status}.`)}async load(){let e=await this.fetch(this.path,this.requestInit);if(!e.ok)throw new Error(`Request to ${this.path} failed with status code ${e.status}. Please verify this URL points to the model JSON of the model to load.`);let t;try{t=await e.json()}catch(r){let a=`Failed to parse model JSON of response from ${this.path}.`;throw this.path.endsWith(".pb")?a+=" Your path contains a .pb file extension. Support for .pb models have been removed in TensorFlow.js 1.0 in favor of .json models. You can re-convert your Python TensorFlow model using the TensorFlow.js 1.0 conversion scripts or you can convert your.pb models with the 'pb2json'NPM script in the tensorflow/tfjs-converter repository.":a+=" Please make sure the server is serving valid JSON for this request.",new Error(a)}let n=t.modelTopology,s=t.weightsManifest;if(n==null&&s==null)throw new Error(`The JSON from HTTP path ${this.path} contains neither model topology or manifest for weights.`);return Ey(t,r=>this.loadWeights(r))}async loadWeights(e){let t=Array.isArray(this.path)?this.path[1]:this.path,[n,s]=c$(t),r=this.weightPathPrefix||n,a=[];for(let u of e)a.push(...u.weights);let o=[],i=[];for(let u of e)for(let c of u.paths)this.weightUrlConverter!=null?i.push(this.weightUrlConverter(c)):o.push(r+c+s);this.weightUrlConverter&&o.push(...await Promise.all(i));let l=await _6(o,{requestInit:this.requestInit,fetchFunc:this.fetch,onProgress:this.onProgress});return[a,Ny(l)]}};_y.URL_SCHEME_REGEX=/^https?:\/\//;function c$(e){let t=e.lastIndexOf("/"),n=e.lastIndexOf("?"),s=e.substring(0,t),r=n>t?e.substring(n):"";return[s+"/",r]}function N3(e){return e.match(_y.URL_SCHEME_REGEX)!=null}var $6=(e,t)=>{if(typeof fetch=="undefined"&&(t==null||t.fetchFunc==null))return null;{let n=!0;if(Array.isArray(e)?n=e.every(s=>N3(s)):n=N3(e),n)return Dy(e,t)}return null};qt.registerSaveRouter($6);qt.registerLoadRouter($6);function Dy(e,t){return new _y(e,t)}function d$(e,t){return Dy(e,t)}var o3=class{constructor(e){this.modelArtifacts=e}load(){return this.modelArtifacts}},P6=class{constructor(e){this.saveHandler=e}save(e){return this.saveHandler(e)}},p$=class{constructor(e){e.load&&(this.load=()=>Promise.resolve(e.load())),e.save&&(this.save=t=>Promise.resolve(e.save(t)))}};function h$(e,t,n,s){let r=arguments;return new p$(F6(...r))}function F6(e,t,n,s){return arguments.length===1?e.modelTopology!=null||e.weightSpecs!=null?new o3(e):(console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."),new o3({modelTopology:e})):(console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."),new o3({modelTopology:e,weightSpecs:t,weightData:n,trainingConfig:s}))}function f$(e){return new P6(e)}function m$(e){return new P6(e)}var O6={};Ve(O6,{confusionMatrix:()=>_$});function g$(e,t,n=!1,s=!1){let r=D(e,"a","matMul"),a=D(t,"b","matMul");[r,a]=Gt(r,a);let o={a:r,b:a},i={transposeA:n,transposeB:s};return W.runKernel(mo,o,i)}var Qe=V({matMul_:g$});function y$(e,t,n=1,s=0){if(t<2)throw new Error(`Error in oneHot: depth must be >=2, but it is ${t}`);let a={indices:D(e,"indices","oneHot","int32")},o={depth:t,onValue:n,offValue:s};return W.runKernel(El,a,o)}var Zu=V({oneHot_:y$});function $y(){Z().set("PROD",!0)}function A$(){Z().set("DEBUG",!0)}function x$(){Z().set("DEPRECATION_WARNINGS_ENABLED",!1),console.warn("TensorFlow.js deprecation warnings have been disabled.")}function Py(e){Z().getBool("DEPRECATION_WARNINGS_ENABLED")&&console.warn(e+" You can disable deprecation warnings with tf.disableDeprecationWarnings().")}dD(Py);function b$(){W.disposeVariables()}function sn(){return W}function ym(){return W.memory()}function v$(e){return W.profile(e)}function J(e,t){return W.tidy(e,t)}function ne(e){Sy(e).forEach(n=>n.dispose())}function bn(e){return W.keep(e)}function w$(e){return W.time(e)}function Fy(e){return W.setBackend(e)}function Lc(){return W.ready()}function ss(){return W.backendName}function k$(e){W.removeBackend(e)}function Oy(e){return W.findBackend(e)}function I$(e){return W.findBackendFactory(e)}function ql(e,t,n=1){return W.registerBackend(e,t,n)}function Zs(){return W.backend}function S$(e,t){Z().setPlatform(e,t)}function C$(e){let n={input:D(e,"input","imag")};return W.runKernel(Gp,n)}var oh=V({imag_:C$});function T$(e){let n={x:D(e,"x","neg")};return W.runKernel(Il,n)}var Dt=V({neg_:T$});function N$(e){let n={input:D(e,"input","real")};return W.runKernel(qp,n)}var Yu=V({real_:N$});function E$(e,t,n){let s=D(e,"x","transpose");if(t==null&&(t=s.shape.map((o,i)=>i).reverse()),M(s.rank===t.length,()=>`Error in transpose: rank of input ${s.rank} must match length of perm ${t}.`),t.forEach(o=>{M(o>=0&&o<s.rank,()=>`All entries in 'perm' must be between 0 and ${s.rank-1} but got ${t}`)}),s.rank<=1)return s.clone();let r={x:s},a={perm:t};return s.dtype==="complex64"?J(()=>{let o=Yu(s),i=oh(s);return o=W.runKernel(Hr,{x:o},a),i=W.runKernel(Hr,{x:i},a),n&&(i=Dt(i)),fa(o,i)}):W.runKernel(Hr,r,a)}var st=V({transpose_:E$});function R$(e,t,n){let s=D(e,"labels","confusionMatrix"),r=D(t,"predictions","confusionMatrix");M(n==null||n>0&&Number.isInteger(n),()=>`If provided, numClasses must be a positive integer, but got ${n}`),M(s.rank===1,()=>`Expected the rank of labels to be 1, but got ${s.rank}`),M(r.rank===1,()=>`Expected the rank of predictions to be 1, but got ${r.rank}`),M(s.shape[0]===r.shape[0],()=>`Mismatch in the number of examples: ${s.shape[0]} vs. ${r.shape[0]}. Labels and predictions should have the same number of elements.`),M(n>0&&Number.isInteger(n),()=>`numClasses is required to be a positive integer, but got ${n}`);let a=Zu(ge(s,"int32"),n),o=Zu(ge(r,"int32"),n),i=st(a),l=Qe(i,o);return ge(l,"int32")}var _$=V({confusionMatrix_:R$}),Xl={};Ve(Xl,{assertAndGetBroadcastShape:()=>kt,getBroadcastDims:()=>M6,getReductionAxes:()=>an});function M6(e,t){let n=e.length,s=[];for(let r=0;r<n;r++){let a=n-1-r,o=e[a]||1;(t[t.length-1-r]||1)>1&&o===1&&s.unshift(a)}return s}function an(e,t){let n=[];for(let s=0;s<t.length;s++){let r=e[e.length-s-1],a=t.length-s-1,o=t[a];(r==null||r===1&&o>1)&&n.unshift(a)}return n}function kt(e,t){let n=[],s=Math.max(e.length,t.length);for(let r=0;r<s;r++){let a=e[e.length-r-1];a==null&&(a=1);let o=t[t.length-r-1];if(o==null&&(o=1),a===1)n.unshift(o);else if(o===1)n.unshift(a);else if(a!==o){let i=`Operands could not be broadcast together with shapes ${e} and ${t}.`;throw Error(i)}else n.unshift(a)}return n}var Ys={};Ve(Ys,{fromPixels:()=>z$,fromPixelsAsync:()=>O$,toPixels:()=>M$});function My(e,t,n){if(ol(e),t!=null&&t.length!==3)throw new Error("tensor3d() requires shape to have three numbers");let s=Xr(e,n);if(s.length!==3&&s.length!==1)throw new Error("tensor3d() requires values to be number[][][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor3d() requires shape to be provided when `values` are a flat array");return oi(e,t,s,n)}var Di;function z6(e,t=3){if(t>4)throw new Error("Cannot construct Tensor with more than 4 channels from pixels.");if(e==null)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");let n=!1,s=!1,r=!1,a=!1,o=!1,i=!1;if(e.data instanceof Uint8Array)n=!0;else if(typeof ImageData!="undefined"&&e instanceof ImageData)s=!0;else if(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)r=!0;else if(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)a=!0;else if(e.getContext!=null)o=!0;else if(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)i=!0;else throw new Error(`pixels passed to tf.browser.fromPixels() must be either an HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData in browser, or OffscreenCanvas, ImageData in webworker or {data: Uint32Array, width: number, height: number}, but was ${e.constructor.name}`);if(r&&r&&e.readyState<2)throw new Error("The video element has not loaded data yet. Please wait for `loadeddata` event on the <video> element.");if(fm(bp,W.backendName)!=null){let f={pixels:e},m={numChannels:t};return W.runKernel(bp,f,m)}let[u,c]=r?[e.videoWidth,e.videoHeight]:[e.width,e.height],p;if(o)p=e.getContext("2d").getImageData(0,0,u,c).data;else if(s||n)p=e.data;else if(a||r||i){if(Di==null)if(typeof document=="undefined")if(typeof OffscreenCanvas!="undefined"&&typeof OffscreenCanvasRenderingContext2D!="undefined")Di=new OffscreenCanvas(1,1).getContext("2d");else throw new Error("Cannot parse input in current context. Reason: OffscreenCanvas Context2D rendering is not supported.");else Di=document.createElement("canvas").getContext("2d",{willReadFrequently:!0});Di.canvas.width=u,Di.canvas.height=c,Di.drawImage(e,0,0,u,c),p=Di.getImageData(0,0,u,c).data}let d;if(t===4)d=new Int32Array(p);else{let f=u*c;d=new Int32Array(f*t);for(let m=0;m<f;m++)for(let g=0;g<t;++g)d[m*t+g]=p[m*4+g]}return My(d,[c,u,t],"int32")}function D$(e){return e!=null&&e.data instanceof Uint8Array}function $$(){return typeof window!="undefined"&&typeof ImageBitmap!="undefined"&&window.hasOwnProperty("createImageBitmap")}function P$(e){return e!=null&&e.width!==0&&e.height!==0}function F$(e){return $$()&&!(e instanceof ImageBitmap)&&P$(e)&&!D$(e)}async function O$(e,t=3){let n=null;if(Z().getBool("WRAP_TO_IMAGEBITMAP")&&F$(e)){let s;try{s=await createImageBitmap(e,{premultiplyAlpha:"none"})}catch(r){s=null}s!=null&&s.width===e.width&&s.height===e.height?n=s:n=e}else n=e;return z6(n,t)}async function M$(e,t){let n=D(e,"img","toPixels");if(!(e instanceof tt)){let u=n;n=ge(u,"int32"),u.dispose()}if(n.rank!==2&&n.rank!==3)throw new Error(`toPixels only supports rank 2 or 3 tensors, got rank ${n.rank}.`);let[s,r]=n.shape.slice(0,2),a=n.rank===2?1:n.shape[2];if(a>4||a===2)throw new Error(`toPixels only supports depth of size 1, 3 or 4 but got ${a}`);if(n.dtype!=="float32"&&n.dtype!=="int32")throw new Error(`Unsupported type for toPixels: ${n.dtype}. Please use float32 or int32 tensors.`);let o=await n.data(),i=n.dtype==="float32"?255:1,l=new Uint8ClampedArray(r*s*4);for(let u=0;u<s*r;++u){let c=[0,0,0,255];for(let d=0;d<a;d++){let h=o[u*a+d];if(n.dtype==="float32"){if(h<0||h>1)throw new Error(`Tensor values for a float32 Tensor must be in the range [0 - 1] but encountered ${h}.`)}else if(n.dtype==="int32"&&(h<0||h>255))throw new Error(`Tensor values for a int32 Tensor must be in the range [0 - 255] but encountered ${h}.`);a===1?(c[0]=h*i,c[1]=h*i,c[2]=h*i):c[d]=h*i}let p=u*4;l[p+0]=Math.round(c[0]),l[p+1]=Math.round(c[1]),l[p+2]=Math.round(c[2]),l[p+3]=Math.round(c[3])}if(t!=null){t.width=r,t.height=s;let u=t.getContext("2d"),c=new ImageData(l,r,s);u.putImageData(c,0,0)}return n!==e&&n.dispose(),l}var z$=V({fromPixels_:z6}),zy={};Ve(zy,{prepareAndValidate:()=>L6});function L6(e,t){let n=e.shape.length,s=t.shape.length;if(n<1)throw new Error(`tf.gatherND() expects the input to be rank 1 or higher, but the rank was ${n}.`);if(s<1)throw new Error(`tf.gatherND() expects the indices to be rank 1 or higher, but the rank was ${s}.`);if(t.dtype!=="int32")throw new Error(`tf.gatherND() expects the indices to be int32 type, but the dtype was ${t.dtype}.`);if(t.shape[s-1]>n)throw new Error(`index innermost dimension length must be <= tensor rank; saw: ${t.shape[s-1]} vs. ${n}`);if(Et(e.shape)===0)throw new Error(`Requested more than 0 entries, but input is empty. Input shape: ${e.shape}.`);let r=t.shape,a=r[r.length-1],o=1;for(let p=0;p<r.length-1;++p)o*=r[p];let i=e.shape,l=r.slice();l.pop();let u=1;for(let p=a;p<n;++p)u*=i[p],l.push(i[p]);let c=[...dc(e.shape).map(p=>p/u),1].slice(0,a);return[l,o,u,c]}var Ly={};Ve(Ly,{calculateShapes:()=>B6,validateInput:()=>Wy,validateUpdateShape:()=>By});function By(e,t,n){let s=t.rank>1?t.shape[t.rank-1]:1,r=t.rank>1?t.rank-1:1,a=`Must have updates.shape = indices.shape[:batchDim] + shape[sliceDim:], got updates.shape: ${n.shape}, indices.shape: ${t.shape}, shape: ${e}, sliceDim: ${s}, and batchDim: ${r}.`;if(n.rank<r)throw new Error(a+` update.rank < ${r}. `);if(e.length<s+(n.rank-r))throw new Error(a+` Output shape length < ${s+(n.rank-r)}`);if(n.rank!==r+e.length-s)throw new Error(a+` update.rank != ${r+e.length-s}`);for(let o=0;o<r;++o)if(n.shape[o]!==t.shape[o])throw new Error(a+` updates.shape[${o}] (${n.shape[o]}) != indices.shape[${o}] (${t.shape[o]}).`);for(let o=0;o<n.rank-r;++o)if(n.shape[o+r]!==e[o+s])throw new Error(a+` updates.shape[${o+r}] (${n.shape[o+r]}) != shape[${o+r}] (${e[o+r]})`)}function Wy(e,t,n){if(t.rank<1)throw new Error(`tf.scatterND() expects the indices to be rank 1 or higher, but the rank was ${t.rank}.`);if(e.rank<1)throw new Error(`tf.scatterND() expects the updates to be rank 1 or higher, but the rank was ${e.rank}.`);if(t.dtype!=="int32")throw new Error(`The dtype of 'indices' should be int32, but got dtype: ${t.dtype}`);if(n.length<1)throw new Error(`Output rank must be greater or equal to 1, but got shape: ${n}`);if(n.length===0){if(t.size===0)throw new Error(`Indices specified for empty output. indices shape: ${t.shape}`);if(e.size===0)throw new Error(`Updates specified for empty output. updates shape: ${e.shape}`)}By(n,t,e)}function B6(e,t,n){let s=t.shape.length,r=s>1?t.shape[s-1]:1,a=n.length,o=1;for(let p=r;p<a;++p)o*=n[p];let i=r<1?1:r,l=Et(t.shape)/i,u=[...dc(n.slice(0,r)),1],c=Et(n);return{sliceRank:r,numUpdates:l,sliceSize:o,strides:u,outputSize:c}}var Ut={};Ve(Ut,{assertParamsValid:()=>B$,computeFlatOffset:()=>H$,computeOutShape:()=>V$,getNormalizedAxes:()=>U$,isSliceContinous:()=>G$,maskToAxes:()=>W$,parseSliceParams:()=>K6,sliceInfo:()=>j$,startForAxis:()=>q6,startIndicesWithElidedDims:()=>G6,stopForAxis:()=>X6,stopIndicesWithElidedDims:()=>H6,stridesForAxis:()=>j6,stridesWithElidedDims:()=>W6});var E3=-2,L$=-1;function B$(e,t,n){let s=e.shape.length;M(s===t.length,()=>`Error in slice${s}D: Length of begin ${t} must match the rank of the array (${s}).`),M(s===n.length,()=>`Error in slice${s}D: Length of size ${n} must match the rank of the array (${s}).`);for(let r=0;r<s;++r)M(t[r]+n[r]<=e.shape[r],()=>`Error in slice${s}D: begin[${r}] + size[${r}] (${t[r]+n[r]}) would overflow input.shape[${r}] (${e.shape[r]})`)}function W$(e){let t=[],n=0;for(;e>0;)e&1&&t.push(n),e/=2,n++;return t}function V$(e,t,n){let s=[];for(let r=0;r<e.length;r++)s[r]=Math.ceil((t[r]-e[r])/n[r]);return s}function W6(e,t,n,s){let r=[...e];for(let a=r.length;a<s.length;a++)r.push(1);for(let a=0;a<n;a++)a===0?r[t]=1:(r.splice(t,0,1),r.pop());return r}function V6(e,t,n){return n<=e?n:n-(t-1)}function U6(e,t){let n=[];for(let s=0;s<e;s++)n.push(t+s);return n}function U$(e,t,n,s,r,a,o,i,l){let u=e.length,c=new Array(u),p=new Array(u),d=new Array(u);if(t.length&&n>0){let h=t[0],f=n+1;c=G6(o,h,f,s,e),p=H6(i,h,f,r,e),d=W6(a,h,f,e)}else for(let h=0;h<u;h++)c[h]=q6(o,s,a,e,h,l),p[h]=X6(i,r,a,e,h,l),d[h]=j6(a,h,l);return{begin:c,end:p,strides:d}}function G6(e,t,n,s,r){let a=[...r],o=U6(n,t);for(let i=0;i<a.length;i++)if(o.indexOf(i)>-1)a[i]=0;else{let l=V6(t,n,i),u=s[l];e&1<<l&&(u=0),a[i]=u}return a}function H6(e,t,n,s,r){let a=[...r],o=U6(n,t);for(let i=0;i<a.length;i++)if(o.indexOf(i)>-1)a[i]=Number.MAX_SAFE_INTEGER;else{let l=V6(t,n,i),u=s[l];e&1<<l&&(u=Number.MAX_SAFE_INTEGER),a[i]=u}for(let i=0;i<a.length;i++){let l=r[i];a[i]<0&&(a[i]+=l),a[i]=xp(0,a[i],r[i])}return a}function j6(e,t,n){let s=e[t];return(n&1<<t||s==null)&&(s=1),s}function q6(e,t,n,s,r,a){let o=t[r],i=n[r]||1;(e&1<<r||a&1<<r||o==null)&&(i>0?o=Number.MIN_SAFE_INTEGER:o=Number.MAX_SAFE_INTEGER);let l=s[r];return o<0&&(o+=l),o=xp(0,o,l-1),o}function X6(e,t,n,s,r,a){let o=t[r],i=n[r]||1;(e&1<<r||a&1<<r||o==null)&&(i>0?o=Number.MAX_SAFE_INTEGER:o=Number.MIN_SAFE_INTEGER);let l=s[r];return o<0&&(o+=l),i>0?o=xp(0,o,l):o=xp(-1,o,l-1),o}function G$(e,t,n){let s=n.length;for(let r=0;r<n.length;r++)if(n[r]>1){s=r;break}for(let r=s+1;r<n.length;r++)if(t[r]>0||n[r]!==e[r])return!1;return!0}function H$(e,t){let n=e.length>0?e[e.length-1]:1;for(let s=0;s<e.length-1;s++)n+=e[s]*t[s];return n}function K6(e,t,n){let s,r=e.shape.length;typeof t=="number"?s=[t,...new Array(r-1).fill(0)]:t.length<r?s=t.concat(new Array(r-t.length).fill(0)):s=t.slice(),s.forEach(o=>{M(o!==-1,()=>"slice() does not support negative begin indexing.")});let a;return n==null?a=new Array(r).fill(-1):typeof n=="number"?a=[n,...new Array(r-1).fill(-1)]:n.length<r?a=n.concat(new Array(r-n.length).fill(-1)):a=n,a=a.map((o,i)=>o>=0?o:(M(o===-1,()=>`Negative size values should be exactly -1 but got ${o} for the slice() size at index ${i}.`),e.shape[i]-s[i])),[s,a]}function j$(e,t,n,s,r,a,o,i,l){let u;if(s==null?(u=new Array(t.length),u.fill(1)):u=s,o!=null&&(o&o-1)!==0)throw new Error("Multiple ellipses in slice is not allowed.");let c=!1,p={dims:u.length,numAddAxisAfterEllipsis:0,begin:t.slice(),end:n.slice(),strides:u.slice(),beginMask:r,endMask:a,ellipsisMask:o,newAxisMask:i,shrinkAxisMask:l};for(let A=0;A<p.dims;A++)c&&(1<<A&i)!==0&&p.numAddAxisAfterEllipsis++,1<<A&o&&(c=!0);c||(p.ellipsisMask|=1<<p.dims,p.dims++);let d={dims:e.length,beginMask:0,endMask:0,beginValid:!1,endValid:!1};q$(p,d);let h=!0,f=!0,m=!0,g=[],y=[];for(let A=0;A<e.length;++A){if(d.strides[A]===0)throw Error(`strides[${A}] must be non-zero`);let b=!!(d.shrinkAxisMask&1<<A),w=e[A];if(w===-1){g.push(b?1:-1);continue}let k=[d.beginMask&1<<A,d.endMask&1<<A],S=[d.strides[A]>0?0:-1,d.strides[A]>0?w:w-1];if(b&&d.strides[A]<=0)throw Error("only stride 1 allowed on non-range indexing.");m=m&&d.strides[A]===1;let E=!!(d.beginMask&1<<A&&d.endMask&1<<A);if(d.beginValid&&d.endValid){if(b){let $=d.begin[A]<0?w+d.begin[A]:d.begin[A];if(d.begin[A]=$,d.end[A]=d.begin[A]+1,$<0||$>=w)throw Error(`slice index ${d.begin[A]} of dimension ${A} out of bounds.`)}else d.begin[A]=bv(d.begin[A],0,d.strides[A],w,k,S),d.end[A]=bv(d.end[A],1,d.strides[A],w,k,S);let _=d.strides[A]===1&&d.begin[A]===0&&d.end[A]===w;h=h&&_,f=f&&(A===0&&d.strides[A]===1||_)}else h=h&&d.strides[A]===1&&E,f=f&&(A===0&&d.strides[A]===1||E);let R,P=!1;if(d.beginValid&&d.endValid?(R=d.end[A]-d.begin[A],P=!0):b?(R=1,P=!0):E&&w>=0&&(d.strides[A]<0?R=-w:R=w,P=!0),P){let _;R===0||R<0!=d.strides[A]<0?_=0:_=Math.trunc(R/d.strides[A])+(R%d.strides[A]!==0?1:0),g.push(_)}else g.push(-1)}for(let A=0;A<d.finalShapeGatherIndices.length;++A){let b=d.finalShapeGatherIndices[A];b>=0?y.push(g[b]):b===E3&&y.push(1)}return{finalShapeSparse:y.filter((A,b)=>d.finalShapeGatherIndices[b]!==E3),finalShape:y,isIdentity:h,sliceDim0:f,isSimpleSlice:m,begin:d.begin,end:d.end,strides:d.strides}}function q$(e,t){t.beginMask=0,t.endMask=0,t.shrinkAxisMask=0;let n=0;t.beginValid=e.begin!=null,t.endValid=e.end!=null,t.begin=new Array(t.dims),t.end=new Array(t.dims),t.strides=new Array(t.dims),t.finalShapeGatherIndices=[],t.finalShapeGatherIndicesSparse=[],t.inputShapeGatherIndicesSparse=new Array(t.dims);for(let s=0;s<e.dims;s++)if(1<<s&e.ellipsisMask){let r=Math.min(t.dims-(e.dims-s)+1+e.numAddAxisAfterEllipsis,t.dims);for(;n<r;n++)t.begin[n]=0,t.end[n]=0,t.strides[n]=1,t.beginMask|=1<<n,t.endMask|=1<<n,t.finalShapeGatherIndices.push(n),t.finalShapeGatherIndicesSparse.push(-1),t.inputShapeGatherIndicesSparse[n]=s}else if(1<<s&e.newAxisMask)t.finalShapeGatherIndices.push(E3),t.finalShapeGatherIndicesSparse.push(-1);else{if(n===t.begin.length)throw Error(`Index out of range using input dim ${n}; input has only ${t.dims} dims, ${t.begin.length}.`);e.begin!=null&&(t.begin[n]=e.begin[s]),e.end!=null&&(t.end[n]=e.end[s]),t.strides[n]=e.strides[s],e.beginMask&1<<s&&(t.beginMask|=1<<n),e.endMask&1<<s&&(t.endMask|=1<<n),e.shrinkAxisMask&1<<s?(t.finalShapeGatherIndices.push(L$),t.finalShapeGatherIndicesSparse.push(-1),t.shrinkAxisMask|=1<<n):(t.finalShapeGatherIndices.push(n),t.finalShapeGatherIndicesSparse.push(s)),t.inputShapeGatherIndicesSparse[n]=s,n++}}function bv(e,t,n,s,r,a){if(r[t])return n>0?a[t]:a[t+1&1];{let o=e<0?s+e:e;return o<a[0]?a[0]:o>a[1]?a[1]:o}}var de={};Ve(de,{Serializable:()=>Z6,SerializationMap:()=>zi,registerClass:()=>ii});var Z6=class{getClassName(){return this.constructor.className}static fromConfig(e,t){return new e(t)}},zi=class{constructor(){this.classNameMap={}}static getMap(){return zi.instance==null&&(zi.instance=new zi),zi.instance}static register(e){zi.getMap().classNameMap[e.className]=[e,e.fromConfig]}};function ii(e){M(e.className!=null,()=>"Class being registered does not have the static className property defined."),M(typeof e.className=="string",()=>"className is required to be a string, but got type "+typeof e.className),M(e.className.length>0,()=>"Class being registered has an empty-string as its className, which is disallowed."),zi.register(e)}var Y6={};Ve(Y6,{TEST_EPSILON_FLOAT16:()=>J6,encodeStrings:()=>Q6,expectArrayBuffersEqual:()=>eP,expectArraysClose:()=>K$,expectArraysEqual:()=>Y$,expectNumbersClose:()=>J$,expectPromiseToFail:()=>Z$,expectValuesInRange:()=>Q$,testEpsilon:()=>Vy});var X$=.001,J6=.1;function K$(e,t,n){return n==null&&(n=Vy()),R3(e,t,(s,r)=>Uy(s,r,n))}function Vy(){return W.backend.floatPrecision()===32?X$:J6}function R3(e,t,n){let s=!0;if((Pn(e)||Pn(t))&&(s=!1),Pn(e)&&Pn(t)&&(s=!0),s){let o=e.constructor.name,i=t.constructor.name;if(o!==i)throw new Error(`Arrays are of different type. Actual: ${o}. Expected: ${i}`)}if(Array.isArray(e)&&Array.isArray(t)){let o=Xr(e),i=Xr(t);if(!co(o,i))throw new Error(`Arrays have different shapes. Actual: [${o}]. Expected: [${i}]`)}let r=Pn(e)?e:Xi(e),a=Pn(t)?t:Xi(t);if(r.length!==a.length)throw new Error(`Arrays have different lengths actual: ${r.length} vs expected: ${a.length}.
+`;return d[d.length-1]=" "+d[d.length-1]+"]"+(a?"":f),d}function sp(e){let t=[];for(let n=0;n<e.length;n+=2)t.push([e[n],e[n+1]]);return t}var fn=class{constructor(e,t,n){if(this.dtype=t,this.shape=e.slice(),this.size=Et(e),n!=null){let s=n.length;M(s===this.size,()=>`Length of values '${s}' does not match the size inferred by the shape '${this.size}'.`)}if(t==="complex64")throw new Error("complex64 dtype TensorBuffers are not supported. Please create a TensorBuffer for the real and imaginary parts separately and call tf.complex(real, imag).");this.values=n||t6(t,this.size),this.strides=cc(e)}set(e,...t){t.length===0&&(t=[0]),M(t.length===this.rank,()=>`The number of provided coordinates (${t.length}) must match the rank (${this.rank})`);let n=this.locToIndex(t);this.values[n]=e}get(...e){e.length===0&&(e=[0]);let t=0;for(let s of e){if(s<0||s>=this.shape[t]){let r=`Requested out of range element at ${e}.   Buffer shape=${this.shape}`;throw new Error(r)}t++}let n=e[e.length-1];for(let s=0;s<e.length-1;++s)n+=this.strides[s]*e[s];return this.values[n]}locToIndex(e){if(this.rank===0)return 0;if(this.rank===1)return e[0];let t=e[e.length-1];for(let n=0;n<e.length-1;++n)t+=this.strides[n]*e[n];return t}indexToLoc(e){if(this.rank===0)return[];if(this.rank===1)return[e];let t=new Array(this.shape.length);for(let n=0;n<t.length-1;++n)t[n]=Math.floor(e/this.strides[n]),e-=t[n]*this.strides[n];return t[t.length-1]=e,t}get rank(){return this.shape.length}toTensor(){return kr().makeTensor(this.values,this.shape,this.dtype)}},kr=null,Mu=null,lD=null;function uD(e){kr=e}function cD(e){Mu=e}function dD(e){lD=e}var tt=class{constructor(e,t,n,s){this.kept=!1,this.isDisposedInternal=!1,this.shape=e.slice(),this.dtype=t||"float32",this.size=Et(e),this.strides=cc(e),this.dataId=n,this.id=s,this.rankType=this.rank<5?this.rank.toString():"higher"}get rank(){return this.shape.length}async buffer(){let e=await this.data();return Mu.buffer(this.shape,this.dtype,e)}bufferSync(){return Mu.buffer(this.shape,this.dtype,this.dataSync())}async array(){let e=await this.data();return Bu(this.shape,e,this.dtype==="complex64")}arraySync(){return Bu(this.shape,this.dataSync(),this.dtype==="complex64")}async data(){this.throwIfDisposed();let e=kr().read(this.dataId);if(this.dtype==="string"){let t=await e;try{return t.map(n=>fm(n))}catch(n){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}}return e}dataToGPU(e){return this.throwIfDisposed(),kr().readToGPU(this.dataId,e)}dataSync(){this.throwIfDisposed();let e=kr().readSync(this.dataId);if(this.dtype==="string")try{return e.map(t=>fm(t))}catch(t){throw new Error("Failed to decode the string bytes into utf-8. To get the original bytes, call tensor.bytes().")}return e}async bytes(){this.throwIfDisposed();let e=await kr().read(this.dataId);return this.dtype==="string"?e:new Uint8Array(e.buffer)}dispose(){this.isDisposed||(kr().disposeTensor(this),this.isDisposedInternal=!0)}get isDisposed(){return this.isDisposedInternal}throwIfDisposed(){if(this.isDisposed)throw new Error("Tensor is disposed.")}print(e=!1){return Mu.print(this,e)}clone(){return this.throwIfDisposed(),Mu.clone(this)}toString(e=!1){let t=this.dataSync();return oD(t,this.shape,this.dtype,e)}cast(e){return this.throwIfDisposed(),Mu.cast(this,e)}variable(e=!0,t,n){return this.throwIfDisposed(),kr().makeVariable(this,e,t,n)}};Object.defineProperty(tt,Symbol.hasInstance,{value:e=>!!e&&e.data!=null&&e.dataSync!=null&&e.throwIfDisposed!=null});function re(){return ky("Tensor",()=>tt)}re();var wp=class extends tt{constructor(e,t,n,s){super(e.shape,e.dtype,e.dataId,s),this.trainable=t,this.name=n}assign(e){if(e.dtype!==this.dtype)throw new Error(`dtype of the new value (${e.dtype}) and previous value (${this.dtype}) must match`);if(!uo(e.shape,this.shape))throw new Error(`shape of the new value (${e.shape}) and previous value (${this.shape}) must match`);kr().disposeTensor(this),this.dataId=e.dataId,kr().incRef(this,null)}dispose(){kr().disposeVariable(this),this.isDisposedInternal=!0}};Object.defineProperty(wp,Symbol.hasInstance,{value:e=>e instanceof tt&&e.assign!=null&&e.assign instanceof Function});var Tr={};Ve(Tr,{assertTypesMatch:()=>y6,getTensorsInContainer:()=>Sy,isTensorInList:()=>hD,makeTypesMatch:()=>Gt});var y3;(function(e){e.R0="R0",e.R1="R1",e.R2="R2",e.R3="R3",e.R4="R4",e.R5="R5",e.R6="R6"})(y3||(y3={}));var A3;(function(e){e.float32="float32",e.int32="int32",e.bool="int32",e.complex64="complex64"})(A3||(A3={}));var x3;(function(e){e.float32="float32",e.int32="int32",e.bool="bool",e.complex64="complex64"})(x3||(x3={}));var b3;(function(e){e.float32="float32",e.int32="float32",e.bool="float32",e.complex64="complex64"})(b3||(b3={}));var v3;(function(e){e.float32="complex64",e.int32="complex64",e.bool="complex64",e.complex64="complex64"})(v3||(v3={}));var pD={float32:b3,int32:A3,bool:x3,complex64:v3};function On(e,t){if(e==="string"||t==="string"){if(e==="string"&&t==="string")return"string";throw new Error(`Can not upcast ${e} with ${t}`)}return pD[e][t]}function nh(e){return On(e,"int32")}function Gt(e,t){if(e.dtype===t.dtype)return[e,t];let n=On(e.dtype,t.dtype);return[e.cast(n),t.cast(n)]}function y6(e,t){M(e.dtype===t.dtype,()=>`The dtypes of the first(${e.dtype}) and second(${t.dtype}) input must match`)}function hD(e,t){return t.some(n=>n.id===e.id)}function Sy(e){let t=[];return A6(e,t,new Set),t}function A6(e,t,n){if(e==null)return;if(e instanceof tt){t.push(e);return}if(!fD(e))return;let s=e;for(let r in s){let a=s[r];n.has(a)||(n.add(a),A6(a,t,n))}}function fD(e){return Array.isArray(e)||typeof e=="object"}function s3(e){return e.kernelName!=null}var fv=class{constructor(){this.registeredVariables={},this.nextTapeNodeId=0,this.numBytes=0,this.numTensors=0,this.numStringTensors=0,this.numDataBuffers=0,this.gradientDepth=0,this.kernelDepth=0,this.scopeStack=[],this.numDataMovesStack=[],this.nextScopeId=0,this.tensorInfo=new WeakMap,this.profiling=!1,this.activeProfile={newBytes:0,newTensors:0,peakBytes:0,kernels:[],result:null,get kernelNames(){return Array.from(new Set(this.kernels.map(e=>e.name)))}}}dispose(){for(let e in this.registeredVariables)this.registeredVariables[e].dispose()}},kp=class{constructor(e){this.ENV=e,this.registry={},this.registryFactory={},this.pendingBackendInitId=0,this.state=new fv}async ready(){if(this.pendingBackendInit!=null)return this.pendingBackendInit.then(()=>{});if(this.backendInstance!=null)return;let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let n=e[t];if(await this.initializeBackend(n).success){await this.setBackend(n);return}}throw new Error("Could not initialize any backends, all backend initializations failed.")}get backend(){if(this.pendingBackendInit!=null)throw new Error(`Backend '${this.backendName}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);if(this.backendInstance==null){let{name:e,asyncInit:t}=this.initializeBackendsAndReturnBest();if(t)throw new Error(`The highest priority backend '${e}' has not yet been initialized. Make sure to await tf.ready() or await tf.setBackend() before calling other methods`);this.setBackend(e)}return this.backendInstance}backendNames(){return Object.keys(this.registryFactory)}findBackend(e){if(!(e in this.registry))if(e in this.registryFactory){let{asyncInit:t}=this.initializeBackend(e);if(t)return null}else return null;return this.registry[e]}findBackendFactory(e){return e in this.registryFactory?this.registryFactory[e].factory:null}registerBackend(e,t,n=1){return e in this.registryFactory?(Va(`${e} backend was already registered. Reusing existing backend factory.`),!1):(this.registryFactory[e]={factory:t,priority:n},!0)}async setBackend(e){if(this.registryFactory[e]==null)throw new Error(`Backend name '${e}' not found in registry`);if(this.backendName=e,this.registry[e]==null){this.backendInstance=null;let{success:t,asyncInit:n}=this.initializeBackend(e);if(!(n?await t:t))return!1}return this.backendInstance=this.registry[e],this.setupRegisteredKernels(),this.profiler=new tD(this.backendInstance),!0}setupRegisteredKernels(){jr(this.backendName).forEach(t=>{t.setupFunc!=null&&t.setupFunc(this.backendInstance)})}disposeRegisteredKernels(e){jr(e).forEach(n=>{n.disposeFunc!=null&&n.disposeFunc(this.registry[e])})}initializeBackend(e){let t=this.registryFactory[e];if(t==null)throw new Error(`Cannot initialize backend ${e}, no registration found.`);try{let n=t.factory();if(n&&!(n instanceof uc)&&typeof n.then=="function"){let s=++this.pendingBackendInitId,r=n.then(a=>s<this.pendingBackendInitId?!1:(this.registry[e]=a,this.pendingBackendInit=null,!0)).catch(a=>(s<this.pendingBackendInitId||(this.pendingBackendInit=null,Va(`Initialization of backend ${e} failed`),Va(a.stack||a.message)),!1));return this.pendingBackendInit=r,{success:r,asyncInit:!0}}else return this.registry[e]=n,{success:!0,asyncInit:!1}}catch(n){return Va(`Initialization of backend ${e} failed`),Va(n.stack||n.message),{success:!1,asyncInit:!1}}}removeBackend(e){if(!(e in this.registryFactory))throw new Error(`${e} backend not found in registry`);this.backendName===e&&this.pendingBackendInit!=null&&this.pendingBackendInitId++,e in this.registry&&(this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e]),delete this.registryFactory[e],this.backendName===e&&(this.pendingBackendInit=null,this.backendName=null,this.backendInstance=null)}getSortedBackends(){if(Object.keys(this.registryFactory).length===0)throw new Error("No backend found in registry.");return Object.keys(this.registryFactory).sort((e,t)=>this.registryFactory[t].priority-this.registryFactory[e].priority)}initializeBackendsAndReturnBest(){let e=this.getSortedBackends();for(let t=0;t<e.length;t++){let n=e[t],{success:s,asyncInit:r}=this.initializeBackend(n);if(r||s)return{name:n,asyncInit:r}}throw new Error("Could not initialize any backends, all backend initializations failed.")}moveData(e,t){let n=this.state.tensorInfo.get(t),s=n.backend,r=this.readSync(t),a=s.refCount(t);s.disposeData(t,!0),n.backend=e,e.move(t,r,n.shape,n.dtype,a),this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack[this.state.numDataMovesStack.length-1]++}tidy(e,t){let n=null;if(t==null){if(typeof e!="function")throw new Error("Please provide a function to tidy()");t=e}else{if(typeof e!="string"&&!(e instanceof String))throw new Error("When calling with two arguments, the first argument to tidy() must be a string");if(typeof t!="function")throw new Error("When calling with two arguments, the 2nd argument to tidy() must be a function");n=e}let s;return this.scopedRun(()=>this.startScope(n),()=>this.endScope(s),()=>(s=t(),s instanceof Promise&&console.error("Cannot return a Promise inside of tidy."),s))}scopedRun(e,t,n){e();try{let s=n();return t(),s}catch(s){throw t(),s}}nextTensorId(){return kp.nextTensorId++}nextVariableId(){return kp.nextVariableId++}clone(e){let t=W.runKernel(Ro,{x:e}),n={x:e},s=a=>({x:()=>{let o="float32",i={x:a},l={dtype:o};return W.runKernel(mo,i,l)}}),r=[];return this.addTapeNode(this.state.activeScope.name,n,[t],s,r,{}),t}runKernel(e,t,n){if(this.backendName==null&&this.backend,!(hm(e,this.backendName)!=null))throw new Error(`Kernel '${e}' not registered for backend '${this.backendName}'`);return this.runKernelFunc({kernelName:e,inputs:t,attrs:n})}shouldCheckForMemLeaks(){return this.ENV.getBool("IS_TEST")}checkKernelForMemLeak(e,t,n){let s=this.backend.numDataIds(),r=0;n.forEach(i=>{r+=i.dtype==="complex64"?3:1});let a=this.state.numDataMovesStack[this.state.numDataMovesStack.length-1],o=s-t-r-a;if(o>0)throw new Error(`Backend '${this.backendName}' has an internal memory leak (${o} data ids) after running '${e}'`)}runKernelFunc(e){let t,n=[],s=this.isTapeOn(),r=this.state.numBytes,a=this.state.numTensors;this.shouldCheckForMemLeaks()&&this.state.numDataMovesStack.push(0);let o;this.backendName==null&&this.backend;let i,l=s3(e)?e.kernelName:this.state.activeScope!=null?this.state.activeScope.name:"";if(s3(e)){let{kernelName:h,inputs:f,attrs:m}=e;this.backendName==null&&this.backend;let g=hm(h,this.backendName);M(g!=null,()=>`Cannot find registered kernel '${h}' for backend '${this.backendName}'`),o=()=>{let y=this.backend.numDataIds();i=g.kernelFunc({inputs:f,attrs:m,backend:this.backend});let x=Array.isArray(i)?i:[i];this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(h,y,x);let A=x.map(b=>b.rank!=null?b:this.makeTensorFromTensorInfo(b));if(s){let b=this.getTensorsForGradient(h,f,A);n=this.saveTensorsForBackwardMode(b)}return A}}else{let{forwardFunc:h}=e,f=m=>{!s||(n=m.map(g=>this.keep(this.clone(g))))};o=()=>{let m=this.backend.numDataIds();i=this.tidy(()=>h(this.backend,f));let g=Array.isArray(i)?i:[i];return this.shouldCheckForMemLeaks()&&this.checkKernelForMemLeak(l,m,g),g}}let{inputs:u,attrs:c}=e,p=s3(e)?null:e.backwardsFunc,d;return this.scopedRun(()=>this.state.kernelDepth++,()=>this.state.kernelDepth--,()=>{!this.ENV.getBool("DEBUG")&&!this.state.profiling?t=o():(d=this.profiler.profileKernel(l,u,()=>o()),this.ENV.getBool("DEBUG")&&this.profiler.logKernelProfile(d),t=d.outputs)}),s&&this.addTapeNode(l,u,t,p,n,c),this.state.profiling&&this.state.activeProfile.kernels.push({name:l,bytesAdded:this.state.numBytes-r,totalBytesSnapshot:this.state.numBytes,tensorsAdded:this.state.numTensors-a,totalTensorsSnapshot:this.state.numTensors,inputShapes:Object.keys(u).map(h=>u[h]!=null?u[h].shape:null),outputShapes:t.map(h=>h.shape),kernelTimeMs:d.timeMs,extraInfo:d.extraInfo}),Array.isArray(i)?t:t[0]}saveTensorsForBackwardMode(e){return e.map(n=>this.keep(this.clone(n)))}getTensorsForGradient(e,t,n){let s=m3(e);if(s!=null){let r=s.inputsToSave||[],a=s.outputsToSave||[],o;s.saveAllInputs?(M(Array.isArray(t),()=>"saveAllInputs is true, expected inputs to be an array."),o=Object.keys(t).map(l=>t[l])):o=r.map(l=>t[l]);let i=n.filter((l,u)=>a[u]);return o.concat(i)}return[]}makeTensor(e,t,n,s){if(e==null)throw new Error("Values passed to engine.makeTensor() are null");n=n||"float32",s=s||this.backend;let r=e;n==="string"&&Ua(e[0])&&(r=e.map(i=>th(i)));let a=s.write(r,t,n),o=new tt(t,n,a,this.nextTensorId());if(this.trackTensor(o,s),n==="string"){let i=this.state.tensorInfo.get(a),l=r6(r);this.state.numBytes+=l-i.bytes,i.bytes=l}return o}makeTensorFromDataId(e,t,n,s){n=n||"float32";let r={dataId:e,shape:t,dtype:n};return this.makeTensorFromTensorInfo(r,s)}makeTensorFromTensorInfo(e,t){let{dataId:n,shape:s,dtype:r}=e,a=new tt(s,r,n,this.nextTensorId());return this.trackTensor(a,t),a}makeVariable(e,t=!0,n,s){n=n||this.nextVariableId().toString(),s!=null&&s!==e.dtype&&(e=e.cast(s));let r=new wp(e,t,n,this.nextTensorId());if(this.state.registeredVariables[r.name]!=null)throw new Error(`Variable with name ${r.name} was already registered`);return this.state.registeredVariables[r.name]=r,this.incRef(r,this.backend),r}trackTensor(e,t){this.state.numTensors++,e.dtype==="string"&&this.state.numStringTensors++;let n=0;e.dtype!=="complex64"&&e.dtype!=="string"&&(n=e.size*f3(e.dtype)),this.state.numBytes+=n,this.state.tensorInfo.has(e.dataId)||(this.state.numDataBuffers++,this.state.tensorInfo.set(e.dataId,{backend:t||this.backend,dtype:e.dtype,shape:e.shape,bytes:n})),e instanceof wp||this.track(e)}incRef(e,t){this.trackTensor(e,t),this.backend.incRef(e.dataId)}removeDataId(e,t){this.state.tensorInfo.has(e)&&this.state.tensorInfo.get(e).backend===t&&(this.state.tensorInfo.delete(e),this.state.numDataBuffers--)}disposeTensor(e){if(!this.state.tensorInfo.has(e.dataId))return;let t=this.state.tensorInfo.get(e.dataId);if(this.state.numTensors--,e.dtype==="string"&&(this.state.numStringTensors--,this.state.numBytes-=t.bytes),e.dtype!=="complex64"&&e.dtype!=="string"){let n=e.size*f3(e.dtype);this.state.numBytes-=n}t.backend.disposeData(e.dataId)&&this.removeDataId(e.dataId,t.backend)}disposeVariables(){for(let e in this.state.registeredVariables){let t=this.state.registeredVariables[e];this.disposeVariable(t)}}disposeVariable(e){this.disposeTensor(e),this.state.registeredVariables[e.name]!=null&&delete this.state.registeredVariables[e.name]}memory(){let e=this.backend.memory();return e.numTensors=this.state.numTensors,e.numDataBuffers=this.state.numDataBuffers,e.numBytes=this.state.numBytes,this.state.numStringTensors>0&&(e.unreliable=!0,e.reasons==null&&(e.reasons=[]),e.reasons.push("Memory usage by string tensors is approximate (2 bytes per character)")),e}async profile(e){this.state.profiling=!0;let t=this.state.numBytes,n=this.state.numTensors;this.state.activeProfile.kernels=[],this.state.activeProfile.result=await e(),this.state.profiling=!1,this.state.activeProfile.peakBytes=Math.max(...this.state.activeProfile.kernels.map(s=>s.totalBytesSnapshot)),this.state.activeProfile.newBytes=this.state.numBytes-t,this.state.activeProfile.newTensors=this.state.numTensors-n;for(let s of this.state.activeProfile.kernels)s.kernelTimeMs=await s.kernelTimeMs,s.extraInfo=await s.extraInfo;return this.state.activeProfile}isTapeOn(){return this.state.gradientDepth>0&&this.state.kernelDepth===0}addTapeNode(e,t,n,s,r,a){let o={id:this.state.nextTapeNodeId++,kernelName:e,inputs:t,outputs:n,saved:r},i=m3(e);i!=null&&(s=i.gradFunc),s!=null&&(o.gradient=l=>(l=l.map((u,c)=>{if(u==null){let p=n[c],d=Vm(p.size,p.dtype);return this.makeTensor(d,p.shape,p.dtype)}return u}),s(l.length>1?l:l[0],r,a))),this.state.activeTape.push(o)}keep(e){return e.kept=!0,e}startTape(){this.state.gradientDepth===0&&(this.state.activeTape=[]),this.state.gradientDepth++}endTape(){this.state.gradientDepth--}startScope(e){let t={track:[],name:"unnamed scope",id:this.state.nextScopeId++};e&&(t.name=e),this.state.scopeStack.push(t),this.state.activeScope=t}endScope(e){let t=Sy(e),n=new Set(t.map(r=>r.id));for(let r=0;r<this.state.activeScope.track.length;r++){let a=this.state.activeScope.track[r];!a.kept&&!n.has(a.id)&&a.dispose()}let s=this.state.scopeStack.pop();this.state.activeScope=this.state.scopeStack.length===0?null:this.state.scopeStack[this.state.scopeStack.length-1],t.forEach(r=>{!r.kept&&r.scopeId===s.id&&this.track(r)})}gradients(e,t,n,s=!1){if(M(t.length>0,()=>"gradients() received an empty list of xs."),n!=null&&n.dtype!=="float32")throw new Error(`dy must have 'float32' dtype, but has '${n.dtype}'`);let r=this.scopedRun(()=>this.startTape(),()=>this.endTape(),()=>this.tidy("forward",e));M(r instanceof tt,()=>"The result y returned by f() must be a tensor.");let a=rD(this.state.activeTape,t,r);if(!s&&a.length===0&&t.length>0)throw new Error("Cannot compute gradient of y=f(x) with respect to x. Make sure that the f you passed encloses all operations that lead from x to y.");return this.tidy("backward",()=>{let o={};o[r.id]=n==null?mD(r.shape):n,aD(o,a,l=>this.tidy(l),gD);let i=t.map(l=>o[l.id]);return this.state.gradientDepth===0&&(this.state.activeTape.forEach(l=>{for(let u of l.saved)u.dispose()}),this.state.activeTape=null),{value:r,grads:i}})}customGrad(e){return M(Za(e),()=>"The f passed in customGrad(f) must be a function."),(...t)=>{M(t.every(o=>o instanceof tt),()=>"The args passed in customGrad(f)(x1, x2,...) must all be tensors");let n,s={};t.forEach((o,i)=>{s[i]=o});let r=(o,i)=>(n=e(...t,i),M(n.value instanceof tt,()=>"The function f passed in customGrad(f) must return an object where `obj.value` is a tensor"),M(Za(n.gradFunc),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function."),n.value),a=(o,i)=>{let l=n.gradFunc(o,i),u=Array.isArray(l)?l:[l];M(u.length===t.length,()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns the same number of tensors as inputs passed to f(...)."),M(u.every(p=>p instanceof tt),()=>"The function f passed in customGrad(f) must return an object where `obj.gradFunc` is a function that returns a list of only tensors.");let c={};return u.forEach((p,d)=>{c[d]=()=>p}),c};return this.runKernelFunc({forwardFunc:r,backwardsFunc:a,inputs:s})}}readSync(e){return this.state.tensorInfo.get(e).backend.readSync(e)}read(e){return this.state.tensorInfo.get(e).backend.read(e)}readToGPU(e,t){return this.state.tensorInfo.get(e).backend.readToGPU(e,t)}async time(e){let t=vp(),n=await this.backend.time(e);return n.wallMs=vp()-t,n}track(e){return this.state.activeScope!=null&&(e.scopeId=this.state.activeScope.id,this.state.activeScope.track.push(e)),e}get registeredVariables(){return this.state.registeredVariables}reset(){this.pendingBackendInitId++,this.state.dispose(),this.ENV.reset(),this.state=new fv;for(let e in this.registry)this.disposeRegisteredKernels(e),this.registry[e].dispose(),delete this.registry[e];this.backendName=null,this.backendInstance=null,this.pendingBackendInit=null}};kp.nextTensorId=0;kp.nextVariableId=0;function mD(e){let t=xy(Et(e),"float32");return W.makeTensor(t,e,"float32")}function x6(){let e=u6();if(e._tfengine==null){let t=new l6(e);e._tfengine=new kp(t)}return z_(e._tfengine.ENV),uD(()=>e._tfengine),e._tfengine}var W=x6();function gD(e,t){let n={a:e,b:t};return W.runKernel(Aa,n)}var sh={};Ve(sh,{isBrowser:()=>b6,isMobile:()=>xD,mockIsMobile:()=>AD});function yD(){return typeof navigator!="undefined"&&navigator!=null}var w3;function AD(e){w3=e}function xD(e){if(w3!==void 0)return w3;if(e||yD()){if(e||(e=navigator),e.product==="ReactNative")return!0;let t=e.userAgent||e.vendor||(typeof window!="undefined"?window.opera:"");if(!t){let n=e;return n.userAgentData&&n.userAgentData.mobile}return/(android|bb\d+|meego).+mobile|avantgo|bada\/|blackberry|blazer|compal|elaine|fennec|hiptop|iemobile|ip(hone|od)|iris|kindle|lge |maemo|midp|mmp|mobile.+firefox|netfront|opera m(ob|in)i|palm( os)?|phone|p(ixi|re)\/|plucker|pocket|psp|series(4|6)0|symbian|treo|up\.(browser|link)|vodafone|wap|windows ce|xda|xiino/i.test(t)||/1207|6310|6590|3gso|4thp|50[1-6]i|770s|802s|a wa|abac|ac(er|oo|s\-)|ai(ko|rn)|al(av|ca|co)|amoi|an(ex|ny|yw)|aptu|ar(ch|go)|as(te|us)|attw|au(di|\-m|r |s )|avan|be(ck|ll|nq)|bi(lb|rd)|bl(ac|az)|br(e|v)w|bumb|bw\-(n|u)|c55\/|capi|ccwa|cdm\-|cell|chtm|cldc|cmd\-|co(mp|nd)|craw|da(it|ll|ng)|dbte|dc\-s|devi|dica|dmob|do(c|p)o|ds(12|\-d)|el(49|ai)|em(l2|ul)|er(ic|k0)|esl8|ez([4-7]0|os|wa|ze)|fetc|fly(\-|_)|g1 u|g560|gene|gf\-5|g\-mo|go(\.w|od)|gr(ad|un)|haie|hcit|hd\-(m|p|t)|hei\-|hi(pt|ta)|hp( i|ip)|hs\-c|ht(c(\-| |_|a|g|p|s|t)|tp)|hu(aw|tc)|i\-(20|go|ma)|i230|iac( |\-|\/)|ibro|idea|ig01|ikom|im1k|inno|ipaq|iris|ja(t|v)a|jbro|jemu|jigs|kddi|keji|kgt( |\/)|klon|kpt |kwc\-|kyo(c|k)|le(no|xi)|lg( g|\/(k|l|u)|50|54|\-[a-w])|libw|lynx|m1\-w|m3ga|m50\/|ma(te|ui|xo)|mc(01|21|ca)|m\-cr|me(rc|ri)|mi(o8|oa|ts)|mmef|mo(01|02|bi|de|do|t(\-| |o|v)|zz)|mt(50|p1|v )|mwbp|mywa|n10[0-2]|n20[2-3]|n30(0|2)|n50(0|2|5)|n7(0(0|1)|10)|ne((c|m)\-|on|tf|wf|wg|wt)|nok(6|i)|nzph|o2im|op(ti|wv)|oran|owg1|p800|pan(a|d|t)|pdxg|pg(13|\-([1-8]|c))|phil|pire|pl(ay|uc)|pn\-2|po(ck|rt|se)|prox|psio|pt\-g|qa\-a|qc(07|12|21|32|60|\-[2-7]|i\-)|qtek|r380|r600|raks|rim9|ro(ve|zo)|s55\/|sa(ge|ma|mm|ms|ny|va)|sc(01|h\-|oo|p\-)|sdk\/|se(c(\-|0|1)|47|mc|nd|ri)|sgh\-|shar|sie(\-|m)|sk\-0|sl(45|id)|sm(al|ar|b3|it|t5)|so(ft|ny)|sp(01|h\-|v\-|v )|sy(01|mb)|t2(18|50)|t6(00|10|18)|ta(gt|lk)|tcl\-|tdg\-|tel(i|m)|tim\-|t\-mo|to(pl|sh)|ts(70|m\-|m3|m5)|tx\-9|up(\.b|g1|si)|utst|v400|v750|veri|vi(rg|te)|vk(40|5[0-3]|\-v)|vm40|voda|vulc|vx(52|53|60|61|70|80|81|83|85|98)|w3c(\-| )|webc|whit|wi(g |nc|nw)|wmlb|wonu|x700|yas\-|your|zeto|zte\-/i.test(t.substr(0,4))}return!1}function b6(){return typeof window!="undefined"&&window.document!=null||typeof WorkerGlobalScope!="undefined"}var ir=X();ir.registerFlag("DEBUG",()=>!1,e=>{e&&console.warn("Debugging mode is ON. The output of every math call will be downloaded to CPU and checked for NaNs. This significantly impacts performance.")});ir.registerFlag("IS_BROWSER",()=>b6());ir.registerFlag("IS_NODE",()=>typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined");ir.registerFlag("IS_CHROME",()=>typeof navigator!="undefined"&&navigator!=null&&navigator.userAgent!=null&&/Chrome/.test(navigator.userAgent)&&/Google Inc/.test(navigator.vendor));ir.registerFlag("PROD",()=>!1);ir.registerFlag("TENSORLIKE_CHECK_SHAPE_CONSISTENCY",()=>ir.getBool("DEBUG"));ir.registerFlag("DEPRECATION_WARNINGS_ENABLED",()=>!0);ir.registerFlag("IS_TEST",()=>!1);ir.registerFlag("CHECK_COMPUTATION_FOR_ERRORS",()=>!0);ir.registerFlag("WRAP_TO_IMAGEBITMAP",()=>!1);ir.registerFlag("ENGINE_COMPILE_ONLY",()=>!1);function qr(e,t){let n=e;if(Pn(e))return t==="string"?[]:[e.length];if(!Array.isArray(e))return[];let s=[];for(;Array.isArray(n)||Pn(n)&&t!=="string";)s.push(n.length),n=n[0];return Array.isArray(e)&&X().getBool("TENSORLIKE_CHECK_SHAPE_CONSISTENCY")&&v6(e,s,[]),s}function v6(e,t,n){if(n=n||[],!Array.isArray(e)&&!Pn(e)){M(t.length===0,()=>`Element arr[${n.join("][")}] is a primitive, but should be an array/TypedArray of ${t[0]} elements`);return}M(t.length>0,()=>`Element arr[${n.join("][")}] should be a primitive, but is an array of ${e.length} elements`),M(e.length===t[0],()=>`Element arr[${n.join("][")}] should have ${t[0]} elements, but has ${e.length} elements`);let s=t.slice(1);for(let r=0;r<e.length;++r)v6(e[r],s,n.concat(r))}function mv(e,t,n,s){if(e!=="string_or_numeric"){if(e==null)throw new Error("Expected dtype cannot be null.");if(e!=="numeric"&&e!==t||e==="numeric"&&t==="string")throw new Error(`Argument '${n}' passed to '${s}' must be ${e} tensor, but got ${t} tensor`)}}function D(e,t,n,s="numeric"){if(e instanceof tt)return mv(s,e.dtype,t,n),e;let r=Wm(e);if(r!=="string"&&["bool","int32","float32"].indexOf(s)>=0&&(r=s),mv(s,r,t,n),e==null||!Pn(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string"){let l=e==null?"null":e.constructor.name;throw new Error(`Argument '${t}' passed to '${n}' must be a Tensor or TensorLike, but got '${l}'`)}let a=qr(e,r);!Pn(e)&&!Array.isArray(e)&&(e=[e]);let i=r!=="string"?h0(e,r):qi(e,[],!0);return W.makeTensor(i,a,r)}function Ip(e,t,n,s="numeric"){if(!Array.isArray(e))throw new Error(`Argument ${t} passed to ${n} must be a \`Tensor[]\` or \`TensorLike[]\``);return e.map((a,o)=>D(a,`${t}[${o}]`,n,s))}var Cy="__op";function V(e){let t=Object.keys(e);if(t.length!==1)throw new Error(`Please provide an object with a single key (operation name) mapping to a function. Got an object with ${t.length} keys.`);let n=t[0],s=e[n];n.endsWith("_")&&(n=n.substring(0,n.length-1)),n=n+Cy;let r=(...a)=>{W.startScope(n);try{let o=s(...a);return vy(o)&&console.error("Cannot return a Promise inside of tidy."),W.endScope(o),o}catch(o){throw W.endScope(null),o}};return Object.defineProperty(r,"name",{value:n,configurable:!0}),r}function bD(e,t){let n=D(e,"real","complex"),s=D(t,"imag","complex");ns(n.shape,s.shape,`real and imag shapes, ${n.shape} and ${s.shape}, must match in call to tf.complex().`);let r={real:n,imag:s};return W.runKernel(zp,r)}var ha=V({complex_:bD});function ai(e,t,n,s){if(s==null&&(s=Wm(e)),s==="complex64")throw new Error("Cannot construct a complex64 tensor directly. Please use tf.complex(real, imag).");if(!Pn(e)&&!Array.isArray(e)&&typeof e!="number"&&typeof e!="boolean"&&typeof e!="string")throw new Error("values passed to tensor(values) must be a number/boolean/string or an array of numbers/booleans/strings, or a TypedArray");if(t!=null){by(t);let r=Et(t),a=Et(n);M(r===a,()=>`Based on the provided shape, [${t}], the tensor should have ${r} values but has ${a}`);for(let o=0;o<n.length;++o){let i=n[o],l=o===n.length-1?i!==Et(t.slice(o)):!0;M(n[o]===t[o]||!l,()=>`Error creating a new Tensor. Inferred shape (${n}) does not match the provided shape (${t}). `)}}return!Pn(e)&&!Array.isArray(e)&&(e=[e]),t=t||n,e=s!=="string"?h0(e,s):qi(e,[],!0),W.makeTensor(e,t,s)}function ft(e,t,n){let s=qr(e,n);return ai(e,t,s,n)}var k3={float32:4,float16:2,int32:4,uint16:2,uint8:1,bool:1,complex64:8},mm=4;async function vD(e,t){let n=[],s=[],r=Array.isArray(e)?e.map(o=>o.name):Object.keys(e);for(let o=0;o<r.length;++o){let i=r[o],l=Array.isArray(e)?e[o].tensor:e[i];if(l.dtype!=="float32"&&l.dtype!=="int32"&&l.dtype!=="bool"&&l.dtype!=="string"&&l.dtype!=="complex64")throw new Error(`Unsupported dtype in weight '${i}': ${l.dtype}`);let u={name:i,shape:l.shape,dtype:l.dtype};if(l.dtype==="string"){let c=new Promise(async p=>{let d=await l.bytes(),h=d.reduce((g,y)=>g+y.length,0)+mm*d.length,f=new Uint8Array(h),m=0;for(let g=0;g<d.length;g++){let y=d[g],x=new Uint8Array(new Uint32Array([y.length]).buffer);f.set(x,m),m+=mm,f.set(y,m),m+=y.length}p(f)});s.push(c)}else s.push(l.data());t!=null&&(u.group=t),n.push(u)}let a=await Promise.all(s);return{data:wD(a),specs:n}}function w6(e,t){let n={},s,r=0;for(let a of t){let o=a.name,i=a.dtype,l=a.shape,u=Et(l),c;if("quantization"in a){let p=a.quantization;if(p.dtype==="uint8"||p.dtype==="uint16"){if(!("min"in p&&"scale"in p))throw new Error(`Weight ${a.name} with quantization ${p.dtype} doesn't have corresponding metadata min and scale.`)}else if(p.dtype==="float16"){if(i!=="float32")throw new Error(`Weight ${a.name} is quantized with ${p.dtype} which only supports weights of type float32 not ${i}.`)}else throw new Error(`Weight ${a.name} has unknown quantization dtype ${p.dtype}. Supported quantization dtypes are: 'uint8', 'uint16', and 'float16'.`);let d=k3[p.dtype],h=e.slice(r,r+u*d),f=p.dtype==="uint8"?new Uint8Array(h):new Uint16Array(h);if(i==="float32")if(p.dtype==="uint8"||p.dtype==="uint16"){c=new Float32Array(f.length);for(let m=0;m<f.length;m++){let g=f[m];c[m]=g*p.scale+p.min}}else if(p.dtype==="float16")s===void 0&&(s=ND()),c=s(f);else throw new Error(`Unsupported quantization type ${p.dtype} for weight type float32.`);else if(i==="int32"){if(p.dtype!=="uint8"&&p.dtype!=="uint16")throw new Error(`Unsupported quantization type ${p.dtype} for weight type int32.`);c=new Int32Array(f.length);for(let m=0;m<f.length;m++){let g=f[m];c[m]=Math.round(g*p.scale+p.min)}}else throw new Error(`Unsupported dtype in weight '${o}': ${i}`);r+=u*d}else if(i==="string"){let p=Et(a.shape);c=[];for(let d=0;d<p;d++){let h=new Uint32Array(e.slice(r,r+mm))[0];r+=mm;let f=new Uint8Array(e.slice(r,r+h));c.push(f),r+=h}}else{let p=k3[i],d=e.slice(r,r+u*p);if(i==="float32")c=new Float32Array(d);else if(i==="int32")c=new Int32Array(d);else if(i==="bool")c=new Uint8Array(d);else if(i==="complex64"){c=new Float32Array(d);let h=new Float32Array(c.length/2),f=new Float32Array(c.length/2);for(let y=0;y<h.length;y++)h[y]=c[y*2],f[y]=c[y*2+1];let m=ft(h,l,"float32"),g=ft(f,l,"float32");n[o]=ha(m,g),m.dispose(),g.dispose()}else throw new Error(`Unsupported dtype in weight '${o}': ${i}`);r+=u*p}i!=="complex64"&&(n[o]=ft(c,l,i))}return n}function wD(e){if(e===null)throw new Error(`Invalid input value: ${JSON.stringify(e)}`);let t=0,n=[];e.forEach(a=>{if(t+=a.byteLength,n.push(a.byteLength===a.buffer.byteLength?a:new a.constructor(a)),!(a instanceof Float32Array||a instanceof Int32Array||a instanceof Uint8Array))throw new Error(`Unsupported TypedArray subtype: ${a.constructor.name}`)});let s=new Uint8Array(t),r=0;return n.forEach(a=>{s.set(new Uint8Array(a.buffer),r),r+=a.byteLength}),s.buffer}var Ty=typeof Buffer!="undefined"&&(typeof Blob=="undefined"||typeof atob=="undefined"||typeof btoa=="undefined");function gv(e){return Ty?Buffer.byteLength(e):new Blob([e]).size}function kD(e){if(Ty)return Buffer.from(e).toString("base64");let t=new Uint8Array(e),n="";for(let s=0,r=t.length;s<r;s++)n+=String.fromCharCode(t[s]);return btoa(n)}function ID(e){if(Ty){let s=Buffer.from(e,"base64");return s.buffer.slice(s.byteOffset,s.byteOffset+s.byteLength)}let t=atob(e),n=new Uint8Array(t.length);for(let s=0;s<t.length;++s)n.set([t.charCodeAt(s)],s);return n.buffer}function Ny(e){if(e.length===1)return e[0];let t=0;e.forEach(r=>{t+=r.byteLength});let n=new Uint8Array(t),s=0;return e.forEach(r=>{n.set(new Uint8Array(r),s),s+=r.byteLength}),n.buffer}function yv(e){let t="/";for(e=e.trim();e.endsWith(t);)e=e.slice(0,e.length-1);let n=e.split(t);return n[n.length-1]}function k6(e,t){let n={modelTopology:e.modelTopology,format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy,weightsManifest:t};return e.signature!=null&&(n.signature=e.signature),e.userDefinedMetadata!=null&&(n.userDefinedMetadata=e.userDefinedMetadata),e.modelInitializer!=null&&(n.modelInitializer=e.modelInitializer),e.trainingConfig!=null&&(n.trainingConfig=e.trainingConfig),n}async function Ey(e,t){let n={modelTopology:e.modelTopology,format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy};if(e.trainingConfig!=null&&(n.trainingConfig=e.trainingConfig),e.weightsManifest!=null){let[s,r]=await t(e.weightsManifest);n.weightSpecs=s,n.weightData=r}return e.signature!=null&&(n.signature=e.signature),e.userDefinedMetadata!=null&&(n.userDefinedMetadata=e.userDefinedMetadata),e.modelInitializer!=null&&(n.modelInitializer=e.modelInitializer),n}function rh(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("Expected JSON model topology, received ArrayBuffer.");return{dateSaved:new Date,modelTopologyType:"JSON",modelTopologyBytes:e.modelTopology==null?0:gv(JSON.stringify(e.modelTopology)),weightSpecsBytes:e.weightSpecs==null?0:gv(JSON.stringify(e.weightSpecs)),weightDataBytes:e.weightData==null?0:e.weightData.byteLength}}function SD(){let e=n=>{let s=n<<13,r=0;for(;(s&8388608)===0;)r-=8388608,s<<=1;return s&=-8388609,r+=947912704,s|r},t=new Uint32Array(2048);t[0]=0;for(let n=1;n<1024;n++)t[n]=e(n);for(let n=1024;n<2048;n++)t[n]=939524096+(n-1024<<13);return t}function CD(){let e=new Uint32Array(64);e[0]=0,e[31]=1199570944,e[32]=2147483648,e[63]=3347054592;for(let t=1;t<31;t++)e[t]=t<<23;for(let t=33;t<63;t++)e[t]=2147483648+(t-32<<23);return e}function TD(){let e=new Uint32Array(64);for(let t=0;t<64;t++)e[t]=1024;return e[0]=e[32]=0,e}function ND(){let e=SD(),t=CD(),n=TD();return s=>{let r=new ArrayBuffer(4*s.length),a=new Uint32Array(r);for(let o=0;o<s.length;o++){let i=s[o],l=e[n[i>>10]+(i&1023)]+t[i>>10];a[o]=l}return new Float32Array(r)}}var qt=class{constructor(){this.saveRouters=[],this.loadRouters=[]}static getInstance(){return qt.instance==null&&(qt.instance=new qt),qt.instance}static registerSaveRouter(e){qt.getInstance().saveRouters.push(e)}static registerLoadRouter(e){qt.getInstance().loadRouters.push(e)}static getSaveHandlers(e){return qt.getHandlers(e,"save")}static getLoadHandlers(e,t){return qt.getHandlers(e,"load",t)}static getHandlers(e,t,n){let s=[];return(t==="load"?qt.getInstance().loadRouters:qt.getInstance().saveRouters).forEach(a=>{let o=a(e,n);o!==null&&s.push(o)}),s}},ED=e=>qt.registerSaveRouter(e),RD=e=>qt.registerLoadRouter(e),_D=e=>qt.getSaveHandlers(e),DD=(e,t)=>qt.getLoadHandlers(e,t),I3="tensorflowjs",S3=1,Bi="models_store",Ga="model_info_store";function I6(){if(!X().getBool("IS_BROWSER"))throw new Error("Failed to obtain IndexedDB factory because the current environmentis not a web browser.");let e=typeof window=="undefined"?self:window,t=e.indexedDB||e.mozIndexedDB||e.webkitIndexedDB||e.msIndexedDB||e.shimIndexedDB;if(t==null)throw new Error("The current browser does not appear to support IndexedDB.");return t}function C3(e){let t=e.result;t.createObjectStore(Bi,{keyPath:"modelPath"}),t.createObjectStore(Ga,{keyPath:"modelPath"})}var Xi=class{constructor(e){if(this.indexedDB=I6(),e==null||!e)throw new Error("For IndexedDB, modelPath must not be null, undefined or empty.");this.modelPath=e}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");return this.databaseAction(this.modelPath,e)}async load(){return this.databaseAction(this.modelPath)}databaseAction(e,t){return new Promise((n,s)=>{let r=this.indexedDB.open(I3,S3);r.onupgradeneeded=()=>C3(r),r.onsuccess=()=>{let a=r.result;if(t==null){let o=a.transaction(Bi,"readonly"),l=o.objectStore(Bi).get(this.modelPath);l.onsuccess=()=>{if(l.result==null)return a.close(),s(new Error(`Cannot find model with path '${this.modelPath}' in IndexedDB.`));n(l.result.modelArtifacts)},l.onerror=u=>(a.close(),s(l.error)),o.oncomplete=()=>a.close()}else{let o=rh(t),i=a.transaction(Ga,"readwrite"),l=i.objectStore(Ga),u=l.put({modelPath:this.modelPath,modelArtifactsInfo:o}),c;u.onsuccess=()=>{c=a.transaction(Bi,"readwrite");let d=c.objectStore(Bi).put({modelPath:this.modelPath,modelArtifacts:t,modelArtifactsInfo:o});d.onsuccess=()=>n({modelArtifactsInfo:o}),d.onerror=h=>{l=i.objectStore(Ga);let f=l.delete(this.modelPath);f.onsuccess=()=>(a.close(),s(d.error)),f.onerror=m=>(a.close(),s(d.error))}},u.onerror=p=>(a.close(),s(u.error)),i.oncomplete=()=>{c==null?a.close():c.oncomplete=()=>a.close()}}},r.onerror=a=>s(r.error)})}};Xi.URL_SCHEME="indexeddb://";var S6=e=>X().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Xi.URL_SCHEME)?$D(e.slice(Xi.URL_SCHEME.length)):null;qt.registerSaveRouter(S6);qt.registerLoadRouter(S6);function $D(e){return new Xi(e)}function PD(e){return e.startsWith(Xi.URL_SCHEME)?e.slice(Xi.URL_SCHEME.length):e}var FD=class{constructor(){this.indexedDB=I6()}async listModels(){return new Promise((e,t)=>{let n=this.indexedDB.open(I3,S3);n.onupgradeneeded=()=>C3(n),n.onsuccess=()=>{let s=n.result,r=s.transaction(Ga,"readonly"),o=r.objectStore(Ga).getAll();o.onsuccess=()=>{let i={};for(let l of o.result)i[l.modelPath]=l.modelArtifactsInfo;e(i)},o.onerror=i=>(s.close(),t(o.error)),r.oncomplete=()=>s.close()},n.onerror=s=>t(n.error)})}async removeModel(e){return e=PD(e),new Promise((t,n)=>{let s=this.indexedDB.open(I3,S3);s.onupgradeneeded=()=>C3(s),s.onsuccess=()=>{let r=s.result,a=r.transaction(Ga,"readwrite"),o=a.objectStore(Ga),i=o.get(e),l;i.onsuccess=()=>{if(i.result==null)return r.close(),n(new Error(`Cannot find model with path '${e}' in IndexedDB.`));{let u=o.delete(e),c=()=>{l=r.transaction(Bi,"readwrite");let d=l.objectStore(Bi).delete(e);d.onsuccess=()=>t(i.result.modelArtifactsInfo),d.onerror=h=>n(i.error)};u.onsuccess=c,u.onerror=p=>(c(),r.close(),n(i.error))}},i.onerror=u=>(r.close(),n(i.error)),a.oncomplete=()=>{l==null?r.close():l.oncomplete=()=>r.close()}},s.onerror=r=>n(s.error)})}},ca="/",zu="tensorflowjs_models",C6="info",OD="model_topology",MD="weight_specs",zD="weight_data",LD="model_metadata";function T6(e){return{info:[zu,e,C6].join(ca),topology:[zu,e,OD].join(ca),weightSpecs:[zu,e,MD].join(ca),weightData:[zu,e,zD].join(ca),modelMetadata:[zu,e,LD].join(ca)}}function N6(e){for(let t of Object.values(e))window.localStorage.removeItem(t)}function BD(e){let t=e.split(ca);if(t.length<3)throw new Error(`Invalid key format: ${e}`);return t.slice(1,t.length-1).join(ca)}function WD(e){return e.startsWith(Ki.URL_SCHEME)?e.slice(Ki.URL_SCHEME.length):e}var Ki=class{constructor(e){if(!X().getBool("IS_BROWSER")||typeof window=="undefined"||typeof window.localStorage=="undefined")throw new Error("The current environment does not support local storage.");if(this.LS=window.localStorage,e==null||!e)throw new Error("For local storage, modelPath must not be null, undefined or empty.");this.modelPath=e,this.keys=T6(this.modelPath)}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserLocalStorage.save() does not support saving model topology in binary formats yet.");{let t=JSON.stringify(e.modelTopology),n=JSON.stringify(e.weightSpecs),s=rh(e);try{this.LS.setItem(this.keys.info,JSON.stringify(s)),this.LS.setItem(this.keys.topology,t),this.LS.setItem(this.keys.weightSpecs,n),this.LS.setItem(this.keys.weightData,kD(e.weightData));let r={format:e.format,generatedBy:e.generatedBy,convertedBy:e.convertedBy,signature:e.signature!=null?e.signature:void 0,userDefinedMetadata:e.userDefinedMetadata!=null?e.userDefinedMetadata:void 0,modelInitializer:e.modelInitializer!=null?e.modelInitializer:void 0,trainingConfig:e.trainingConfig!=null?e.trainingConfig:void 0};return this.LS.setItem(this.keys.modelMetadata,JSON.stringify(r)),{modelArtifactsInfo:s}}catch(r){throw N6(this.keys),new Error(`Failed to save model '${this.modelPath}' to local storage: size quota being exceeded is a possible cause of this failure: modelTopologyBytes=${s.modelTopologyBytes}, weightSpecsBytes=${s.weightSpecsBytes}, weightDataBytes=${s.weightDataBytes}.`)}}}async load(){let e=JSON.parse(this.LS.getItem(this.keys.info));if(e==null)throw new Error(`In local storage, there is no model with name '${this.modelPath}'`);if(e.modelTopologyType!=="JSON")throw new Error("BrowserLocalStorage does not support loading non-JSON model topology yet.");let t={},n=JSON.parse(this.LS.getItem(this.keys.topology));if(n==null)throw new Error(`In local storage, the topology of model '${this.modelPath}' is missing.`);t.modelTopology=n;let s=JSON.parse(this.LS.getItem(this.keys.weightSpecs));if(s==null)throw new Error(`In local storage, the weight specs of model '${this.modelPath}' are missing.`);t.weightSpecs=s;let r=this.LS.getItem(this.keys.modelMetadata);if(r!=null){let o=JSON.parse(r);t.format=o.format,t.generatedBy=o.generatedBy,t.convertedBy=o.convertedBy,o.signature!=null&&(t.signature=o.signature),o.userDefinedMetadata!=null&&(t.userDefinedMetadata=o.userDefinedMetadata),o.modelInitializer!=null&&(t.modelInitializer=o.modelInitializer),o.trainingConfig!=null&&(t.trainingConfig=o.trainingConfig)}let a=this.LS.getItem(this.keys.weightData);if(a==null)throw new Error(`In local storage, the binary weight values of model '${this.modelPath}' are missing.`);return t.weightData=ID(a),t}};Ki.URL_SCHEME="localstorage://";var E6=e=>X().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Ki.URL_SCHEME)?VD(e.slice(Ki.URL_SCHEME.length)):null;qt.registerSaveRouter(E6);qt.registerLoadRouter(E6);function VD(e){return new Ki(e)}var UD=class{constructor(){M(X().getBool("IS_BROWSER"),()=>"Current environment is not a web browser"),M(typeof window=="undefined"||typeof window.localStorage!="undefined",()=>"Current browser does not appear to support localStorage"),this.LS=window.localStorage}async listModels(){let e={},t=zu+ca,n=ca+C6;for(let s=0;s<this.LS.length;++s){let r=this.LS.key(s);if(r.startsWith(t)&&r.endsWith(n)){let a=BD(r);e[a]=JSON.parse(this.LS.getItem(r))}}return e}async removeModel(e){e=WD(e);let t=T6(e);if(this.LS.getItem(t.info)==null)throw new Error(`Cannot find model at path '${e}'`);let n=JSON.parse(this.LS.getItem(t.info));return N6(t),n}},Wu="://",ds=class{constructor(){this.managers={}}static getInstance(){return ds.instance==null&&(ds.instance=new ds),ds.instance}static registerManager(e,t){M(e!=null,()=>"scheme must not be undefined or null."),e.endsWith(Wu)&&(e=e.slice(0,e.indexOf(Wu))),M(e.length>0,()=>"scheme must not be an empty string.");let n=ds.getInstance();M(n.managers[e]==null,()=>`A model store manager is already registered for scheme '${e}'.`),n.managers[e]=t}static getManager(e){let t=ds.getInstance().managers[e];if(t==null)throw new Error(`Cannot find model manager for scheme '${e}'`);return t}static getSchemes(){return Object.keys(ds.getInstance().managers)}};function Qf(e){if(e.indexOf(Wu)===-1)throw new Error(`The url string provided does not contain a scheme. Supported schemes are: ${ds.getSchemes().join(",")}`);return{scheme:e.split(Wu)[0],path:e.split(Wu)[1]}}async function R6(e,t,n=!1){M(e!==t,()=>`Old path and new path are the same: '${e}'`);let s=qt.getLoadHandlers(e);M(s.length>0,()=>`Copying failed because no load handler is found for source URL ${e}.`),M(s.length<2,()=>`Copying failed because more than one (${s.length}) load handlers for source URL ${e}.`);let r=s[0],a=qt.getSaveHandlers(t);M(a.length>0,()=>`Copying failed because no save handler is found for destination URL ${t}.`),M(a.length<2,()=>`Copying failed because more than one (${s.length}) save handlers for destination URL ${t}.`);let o=a[0],i=Qf(e).scheme,l=Qf(e).path,u=i===Qf(e).scheme,c=await r.load();n&&u&&await ds.getManager(i).removeModel(l);let p=await o.save(c);return n&&!u&&await ds.getManager(i).removeModel(l),p.modelArtifactsInfo}async function GD(){let e=ds.getSchemes(),t={};for(let n of e){let s=await ds.getManager(n).listModels();for(let r in s){let a=n+Wu+r;t[a]=s[r]}}return t}async function HD(e){let t=Qf(e);return ds.getManager(t.scheme).removeModel(t.path)}async function jD(e,t){return R6(e,t,!1)}async function qD(e,t){return R6(e,t,!0)}var XD=class{fetch(e,t){return fetch(e,t)}now(){return performance.now()}encode(e,t){if(t!=="utf-8"&&t!=="utf8")throw new Error(`Browser's encoder only supports utf-8, but got ${t}`);return this.textEncoder==null&&(this.textEncoder=new TextEncoder),this.textEncoder.encode(e)}decode(e,t){return new TextDecoder(t).decode(e)}};if(X().get("IS_BROWSER")){X().setPlatform("browser",new XD);try{ds.registerManager(Ki.URL_SCHEME,new UD)}catch(e){}try{ds.registerManager(Xi.URL_SCHEME,new FD)}catch(e){}}var KD={importFetch:()=>n_()},r3,ZD=class{constructor(){this.util=s_(),this.textEncoder=new this.util.TextEncoder}fetch(e,t){return X().global.fetch!=null?X().global.fetch(e,t):(r3==null&&(r3=KD.importFetch()),r3(e,t))}now(){let e=process.hrtime();return e[0]*1e3+e[1]/1e6}encode(e,t){if(t!=="utf-8"&&t!=="utf8")throw new Error(`Node built-in encoder only supports utf-8, but got ${t}`);return this.textEncoder.encode(e)}decode(e,t){return e.length===0?"":new this.util.TextDecoder(t).decode(e)}};X().get("IS_NODE")&&!X().get("IS_BROWSER")&&X().setPlatform("node",new ZD);function Le(e,t="float32",n){return t=t||"float32",by(e),new fn(e,t,n)}function YD(e,t){let n=D(e,"x","cast");if(!s6(t))throw new Error(`Failed to cast to unknown dtype ${t}`);if(t==="string"&&n.dtype!=="string"||t!=="string"&&n.dtype==="string")throw new Error("Only strings can be casted to strings");let s={x:n},r={dtype:t};return W.runKernel(mo,s,r)}var ge=V({cast_:YD});function JD(e){let n={x:D(e,"x","clone","string_or_numeric")};return W.runKernel(Ro,n)}var Fn=V({clone_:JD});function Ry(e,t=!1){console.log(e.toString(t))}x6();var QD={buffer:Le,cast:ge,clone:Fn,print:Ry};cD(QD);var Ts={};Ve(Ts,{browserFiles:()=>o$,browserHTTPRequest:()=>d$,concatenateArrayBuffers:()=>Ny,copyModel:()=>jD,decodeWeights:()=>w6,encodeWeights:()=>vD,fromMemory:()=>h$,fromMemorySync:()=>F6,getLoadHandlers:()=>DD,getModelArtifactsForJSON:()=>Ey,getModelArtifactsInfoForJSON:()=>rh,getSaveHandlers:()=>_D,http:()=>Dy,isHTTPScheme:()=>T3,listModels:()=>GD,loadWeights:()=>i$,moveModel:()=>qD,registerLoadRouter:()=>RD,registerSaveRouter:()=>ED,removeModel:()=>HD,weightsLoaderFactory:()=>D6,withSaveHandler:()=>f$,withSaveHandlerSync:()=>m$});var e$="model",t$=".json",n$=".weights.bin";function Av(e){return new Promise(t=>setTimeout(t)).then(e)}var Xu=class{constructor(e){if(!X().getBool("IS_BROWSER"))throw new Error("browserDownloads() cannot proceed because the current environment is not a browser.");e.startsWith(Xu.URL_SCHEME)&&(e=e.slice(Xu.URL_SCHEME.length)),(e==null||e.length===0)&&(e=e$),this.modelJsonFileName=e+t$,this.weightDataFileName=e+n$}async save(e){if(typeof document=="undefined")throw new Error("Browser downloads are not supported in this environment since `document` is not present");let t=window.URL.createObjectURL(new Blob([e.weightData],{type:"application/octet-stream"}));if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserDownloads.save() does not support saving model topology in binary formats yet.");{let n=[{paths:["./"+this.weightDataFileName],weights:e.weightSpecs}],s=k6(e,n),r=window.URL.createObjectURL(new Blob([JSON.stringify(s)],{type:"application/json"})),a=this.modelJsonAnchor==null?document.createElement("a"):this.modelJsonAnchor;if(a.download=this.modelJsonFileName,a.href=r,await Av(()=>a.dispatchEvent(new MouseEvent("click"))),e.weightData!=null){let o=this.weightDataAnchor==null?document.createElement("a"):this.weightDataAnchor;o.download=this.weightDataFileName,o.href=t,await Av(()=>o.dispatchEvent(new MouseEvent("click")))}return{modelArtifactsInfo:rh(e)}}}};Xu.URL_SCHEME="downloads://";var s$=class{constructor(e){if(e==null||e.length<1)throw new Error(`When calling browserFiles, at least 1 file is required, but received ${e}`);this.jsonFile=e[0],this.weightsFiles=e.slice(1)}async load(){return new Promise((e,t)=>{let n=new FileReader;n.onload=s=>{let r=JSON.parse(s.target.result),a=r.modelTopology;if(a==null){t(new Error(`modelTopology field is missing from file ${this.jsonFile.name}`));return}if(r.weightsManifest==null){t(new Error(`weightManifest field is missing from file ${this.jsonFile.name}`));return}if(this.weightsFiles.length===0){e({modelTopology:a});return}let i=Ey(r,l=>this.loadWeights(l));e(i)},n.onerror=s=>t(`Failed to read model topology and weights manifest JSON from file '${this.jsonFile.name}'. BrowserFiles supports loading Keras-style tf.Model artifacts only.`),n.readAsText(this.jsonFile)})}loadWeights(e){let t=[],n=[];for(let a of e)t.push(...a.weights),n.push(...a.paths);let s=this.checkManifestAndWeightFiles(e),r=n.map(a=>this.loadWeightsFile(a,s[a]));return Promise.all(r).then(a=>[t,Ny(a)])}loadWeightsFile(e,t){return new Promise((n,s)=>{let r=new FileReader;r.onload=a=>{let o=a.target.result;n(o)},r.onerror=a=>s(`Failed to weights data from file of path '${e}'.`),r.readAsArrayBuffer(t)})}checkManifestAndWeightFiles(e){let t=[],n=this.weightsFiles.map(r=>yv(r.name)),s={};for(let r of e)r.paths.forEach(a=>{let o=yv(a);if(t.indexOf(o)!==-1)throw new Error(`Duplicate file basename found in weights manifest: '${o}'`);if(t.push(o),n.indexOf(o)===-1)throw new Error(`Weight file with basename '${o}' is not provided.`);s[a]=this.weightsFiles[n.indexOf(o)]});if(t.length!==this.weightsFiles.length)throw new Error(`Mismatch in the number of files in weights manifest (${t.length}) and the number of weight files provided (${this.weightsFiles.length}).`);return s}},r$=e=>X().getBool("IS_BROWSER")&&!Array.isArray(e)&&e.startsWith(Xu.URL_SCHEME)?a$(e.slice(Xu.URL_SCHEME.length)):null;qt.registerSaveRouter(r$);function a$(e="model"){return new Xu(e)}function o$(e){return new s$(e)}function xv(e,t,n,s){o(e),n=n==null?0:n,s=s==null?1:s,i(n,s);let r=0,a=l=>(l.then(u=>{let c=n+ ++r/e.length*(s-n);return t(c),u}),l);function o(l){M(l!=null&&Array.isArray(l)&&l.length>0,()=>"promises must be a none empty array")}function i(l,u){M(l>=0&&l<=1,()=>`Progress fraction must be in range [0, 1], but got startFraction ${l}`),M(u>=0&&u<=1,()=>`Progress fraction must be in range [0, 1], but got endFraction ${u}`),M(u>=l,()=>`startFraction must be no more than endFraction, but got startFraction ${l} and endFraction ${u}`)}return Promise.all(e.map(a))}async function _6(e,t){t==null&&(t={});let n=t.fetchFunc==null?X().platform.fetch:t.fetchFunc,s=e.map(p=>n(p,t.requestInit,{isBinary:!0})),r=0,a=.5,i=(t.onProgress==null?await Promise.all(s):await xv(s,t.onProgress,r,a)).map(p=>p.arrayBuffer()),l=.5,u=1;return t.onProgress==null?await Promise.all(i):await xv(i,t.onProgress,l,u)}async function i$(e,t="",n,s){return D6(o=>_6(o,{requestInit:s}))(e,t,n)}function D6(e){return async(t,n="",s)=>{let r=t.map(()=>!1),a={},o=s!=null?s.map(()=>!1):[],i=[];if(t.forEach((h,f)=>{let m=0;h.weights.forEach(g=>{let y="quantization"in g?g.quantization.dtype:g.dtype,x=k3[y]*Et(g.shape),A=()=>{r[f]=!0,a[f]==null&&(a[f]=[]),a[f].push({manifestEntry:g,groupOffset:m,sizeBytes:x})};s!=null?s.forEach((b,w)=>{b===g.name&&(A(),o[w]=!0)}):A(),i.push(g.name),m+=x})}),!o.every(h=>h)){let h=s.filter((f,m)=>!o[m]);throw new Error(`Could not find weights in manifest with names: ${h.join(", ")}. 
+Manifest JSON has weights with names: ${i.join(", ")}.`)}let l=r.reduce((h,f,m)=>(f&&h.push(m),h),[]),u=[];l.forEach(h=>{t[h].paths.forEach(f=>{let m=n+(n.endsWith("/")?"":"/")+f;u.push(m)})});let c=await e(u),p={},d=0;return l.forEach(h=>{let f=t[h].paths.length,m=0;for(let b=0;b<f;b++)m+=c[d+b].byteLength;let g=new ArrayBuffer(m),y=new Uint8Array(g),x=0;for(let b=0;b<f;b++){let w=new Uint8Array(c[d+b]);y.set(w,x),x+=w.byteLength}a[h].forEach(b=>{let w=g.slice(b.groupOffset,b.groupOffset+b.sizeBytes),k=w6(w,[b.manifestEntry]);for(let S in k)p[S]=k[S]}),d+=f}),p}}var l$="application/octet-stream",u$="application/json",_y=class{constructor(e,t){if(this.DEFAULT_METHOD="POST",t==null&&(t={}),this.weightPathPrefix=t.weightPathPrefix,this.onProgress=t.onProgress,this.weightUrlConverter=t.weightUrlConverter,t.fetchFunc!=null?(M(typeof t.fetchFunc=="function",()=>"Must pass a function that matches the signature of `fetch` (see https://developer.mozilla.org/en-US/docs/Web/API/Fetch_API)"),this.fetch=t.fetchFunc):this.fetch=X().platform.fetch,M(e!=null&&e.length>0,()=>"URL path for http must not be null, undefined or empty."),Array.isArray(e)&&M(e.length===2,()=>`URL paths for http must have a length of 2, (actual length is ${e.length}).`),this.path=e,t.requestInit!=null&&t.requestInit.body!=null)throw new Error("requestInit is expected to have no pre-existing body, but has one.");this.requestInit=t.requestInit||{}}async save(e){if(e.modelTopology instanceof ArrayBuffer)throw new Error("BrowserHTTPRequest.save() does not support saving model topology in binary formats yet.");let t=Object.assign({method:this.DEFAULT_METHOD},this.requestInit);t.body=new FormData;let n=[{paths:["./model.weights.bin"],weights:e.weightSpecs}],s=k6(e,n);t.body.append("model.json",new Blob([JSON.stringify(s)],{type:u$}),"model.json"),e.weightData!=null&&t.body.append("model.weights.bin",new Blob([e.weightData],{type:l$}),"model.weights.bin");let r=await this.fetch(this.path,t);if(r.ok)return{modelArtifactsInfo:rh(e),responses:[r]};throw new Error(`BrowserHTTPRequest.save() failed due to HTTP response status ${r.status}.`)}async load(){let e=await this.fetch(this.path,this.requestInit);if(!e.ok)throw new Error(`Request to ${this.path} failed with status code ${e.status}. Please verify this URL points to the model JSON of the model to load.`);let t;try{t=await e.json()}catch(r){let a=`Failed to parse model JSON of response from ${this.path}.`;throw this.path.endsWith(".pb")?a+=" Your path contains a .pb file extension. Support for .pb models have been removed in TensorFlow.js 1.0 in favor of .json models. You can re-convert your Python TensorFlow model using the TensorFlow.js 1.0 conversion scripts or you can convert your.pb models with the 'pb2json'NPM script in the tensorflow/tfjs-converter repository.":a+=" Please make sure the server is serving valid JSON for this request.",new Error(a)}let n=t.modelTopology,s=t.weightsManifest;if(n==null&&s==null)throw new Error(`The JSON from HTTP path ${this.path} contains neither model topology or manifest for weights.`);return Ey(t,r=>this.loadWeights(r))}async loadWeights(e){let t=Array.isArray(this.path)?this.path[1]:this.path,[n,s]=c$(t),r=this.weightPathPrefix||n,a=[];for(let u of e)a.push(...u.weights);let o=[],i=[];for(let u of e)for(let c of u.paths)this.weightUrlConverter!=null?i.push(this.weightUrlConverter(c)):o.push(r+c+s);this.weightUrlConverter&&o.push(...await Promise.all(i));let l=await _6(o,{requestInit:this.requestInit,fetchFunc:this.fetch,onProgress:this.onProgress});return[a,Ny(l)]}};_y.URL_SCHEME_REGEX=/^https?:\/\//;function c$(e){let t=e.lastIndexOf("/"),n=e.lastIndexOf("?"),s=e.substring(0,t),r=n>t?e.substring(n):"";return[s+"/",r]}function T3(e){return e.match(_y.URL_SCHEME_REGEX)!=null}var $6=(e,t)=>{if(typeof fetch=="undefined"&&(t==null||t.fetchFunc==null))return null;{let n=!0;if(Array.isArray(e)?n=e.every(s=>T3(s)):n=T3(e),n)return Dy(e,t)}return null};qt.registerSaveRouter($6);qt.registerLoadRouter($6);function Dy(e,t){return new _y(e,t)}function d$(e,t){return Dy(e,t)}var a3=class{constructor(e){this.modelArtifacts=e}load(){return this.modelArtifacts}},P6=class{constructor(e){this.saveHandler=e}save(e){return this.saveHandler(e)}},p$=class{constructor(e){e.load&&(this.load=()=>Promise.resolve(e.load())),e.save&&(this.save=t=>Promise.resolve(e.save(t)))}};function h$(e,t,n,s){let r=arguments;return new p$(F6(...r))}function F6(e,t,n,s){return arguments.length===1?e.modelTopology!=null||e.weightSpecs!=null?new a3(e):(console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."),new a3({modelTopology:e})):(console.warn("Please call tf.io.fromMemory() with only one argument. The argument should be of type ModelArtifacts. The multi-argument signature of tf.io.fromMemory() has been deprecated and will be removed in a future release."),new a3({modelTopology:e,weightSpecs:t,weightData:n,trainingConfig:s}))}function f$(e){return new P6(e)}function m$(e){return new P6(e)}var O6={};Ve(O6,{confusionMatrix:()=>_$});function g$(e,t,n=!1,s=!1){let r=D(e,"a","matMul"),a=D(t,"b","matMul");[r,a]=Gt(r,a);let o={a:r,b:a},i={transposeA:n,transposeB:s};return W.runKernel(fo,o,i)}var Qe=V({matMul_:g$});function y$(e,t,n=1,s=0){if(t<2)throw new Error(`Error in oneHot: depth must be >=2, but it is ${t}`);let a={indices:D(e,"indices","oneHot","int32")},o={depth:t,onValue:n,offValue:s};return W.runKernel(Nl,a,o)}var Ku=V({oneHot_:y$});function $y(){X().set("PROD",!0)}function A$(){X().set("DEBUG",!0)}function x$(){X().set("DEPRECATION_WARNINGS_ENABLED",!1),console.warn("TensorFlow.js deprecation warnings have been disabled.")}function Py(e){X().getBool("DEPRECATION_WARNINGS_ENABLED")&&console.warn(e+" You can disable deprecation warnings with tf.disableDeprecationWarnings().")}dD(Py);function b$(){W.disposeVariables()}function sn(){return W}function gm(){return W.memory()}function v$(e){return W.profile(e)}function J(e,t){return W.tidy(e,t)}function ne(e){Sy(e).forEach(n=>n.dispose())}function bn(e){return W.keep(e)}function w$(e){return W.time(e)}function Fy(e){return W.setBackend(e)}function zc(){return W.ready()}function ss(){return W.backendName}function k$(e){W.removeBackend(e)}function Oy(e){return W.findBackend(e)}function I$(e){return W.findBackendFactory(e)}function jl(e,t,n=1){return W.registerBackend(e,t,n)}function Zs(){return W.backend}function S$(e,t){X().setPlatform(e,t)}function C$(e){let n={input:D(e,"input","imag")};return W.runKernel(Up,n)}var ah=V({imag_:C$});function T$(e){let n={x:D(e,"x","neg")};return W.runKernel(kl,n)}var Dt=V({neg_:T$});function N$(e){let n={input:D(e,"input","real")};return W.runKernel(jp,n)}var Zu=V({real_:N$});function E$(e,t,n){let s=D(e,"x","transpose");if(t==null&&(t=s.shape.map((o,i)=>i).reverse()),M(s.rank===t.length,()=>`Error in transpose: rank of input ${s.rank} must match length of perm ${t}.`),t.forEach(o=>{M(o>=0&&o<s.rank,()=>`All entries in 'perm' must be between 0 and ${s.rank-1} but got ${t}`)}),s.rank<=1)return s.clone();let r={x:s},a={perm:t};return s.dtype==="complex64"?J(()=>{let o=Zu(s),i=ah(s);return o=W.runKernel(Gr,{x:o},a),i=W.runKernel(Gr,{x:i},a),n&&(i=Dt(i)),ha(o,i)}):W.runKernel(Gr,r,a)}var st=V({transpose_:E$});function R$(e,t,n){let s=D(e,"labels","confusionMatrix"),r=D(t,"predictions","confusionMatrix");M(n==null||n>0&&Number.isInteger(n),()=>`If provided, numClasses must be a positive integer, but got ${n}`),M(s.rank===1,()=>`Expected the rank of labels to be 1, but got ${s.rank}`),M(r.rank===1,()=>`Expected the rank of predictions to be 1, but got ${r.rank}`),M(s.shape[0]===r.shape[0],()=>`Mismatch in the number of examples: ${s.shape[0]} vs. ${r.shape[0]}. Labels and predictions should have the same number of elements.`),M(n>0&&Number.isInteger(n),()=>`numClasses is required to be a positive integer, but got ${n}`);let a=Ku(ge(s,"int32"),n),o=Ku(ge(r,"int32"),n),i=st(a),l=Qe(i,o);return ge(l,"int32")}var _$=V({confusionMatrix_:R$}),ql={};Ve(ql,{assertAndGetBroadcastShape:()=>kt,getBroadcastDims:()=>M6,getReductionAxes:()=>an});function M6(e,t){let n=e.length,s=[];for(let r=0;r<n;r++){let a=n-1-r,o=e[a]||1;(t[t.length-1-r]||1)>1&&o===1&&s.unshift(a)}return s}function an(e,t){let n=[];for(let s=0;s<t.length;s++){let r=e[e.length-s-1],a=t.length-s-1,o=t[a];(r==null||r===1&&o>1)&&n.unshift(a)}return n}function kt(e,t){let n=[],s=Math.max(e.length,t.length);for(let r=0;r<s;r++){let a=e[e.length-r-1];a==null&&(a=1);let o=t[t.length-r-1];if(o==null&&(o=1),a===1)n.unshift(o);else if(o===1)n.unshift(a);else if(a!==o){let i=`Operands could not be broadcast together with shapes ${e} and ${t}.`;throw Error(i)}else n.unshift(a)}return n}var Ys={};Ve(Ys,{fromPixels:()=>z$,fromPixelsAsync:()=>O$,toPixels:()=>M$});function My(e,t,n){if(al(e),t!=null&&t.length!==3)throw new Error("tensor3d() requires shape to have three numbers");let s=qr(e,n);if(s.length!==3&&s.length!==1)throw new Error("tensor3d() requires values to be number[][][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor3d() requires shape to be provided when `values` are a flat array");return ai(e,t,s,n)}var _i;function z6(e,t=3){if(t>4)throw new Error("Cannot construct Tensor with more than 4 channels from pixels.");if(e==null)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");let n=!1,s=!1,r=!1,a=!1,o=!1,i=!1;if(e.data instanceof Uint8Array)n=!0;else if(typeof ImageData!="undefined"&&e instanceof ImageData)s=!0;else if(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)r=!0;else if(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)a=!0;else if(e.getContext!=null)o=!0;else if(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)i=!0;else throw new Error(`pixels passed to tf.browser.fromPixels() must be either an HTMLVideoElement, HTMLImageElement, HTMLCanvasElement, ImageData in browser, or OffscreenCanvas, ImageData in webworker or {data: Uint32Array, width: number, height: number}, but was ${e.constructor.name}`);if(r&&r&&e.readyState<2)throw new Error("The video element has not loaded data yet. Please wait for `loadeddata` event on the <video> element.");if(hm(xp,W.backendName)!=null){let f={pixels:e},m={numChannels:t};return W.runKernel(xp,f,m)}let[u,c]=r?[e.videoWidth,e.videoHeight]:[e.width,e.height],p;if(o)p=e.getContext("2d").getImageData(0,0,u,c).data;else if(s||n)p=e.data;else if(a||r||i){if(_i==null)if(typeof document=="undefined")if(typeof OffscreenCanvas!="undefined"&&typeof OffscreenCanvasRenderingContext2D!="undefined")_i=new OffscreenCanvas(1,1).getContext("2d");else throw new Error("Cannot parse input in current context. Reason: OffscreenCanvas Context2D rendering is not supported.");else _i=document.createElement("canvas").getContext("2d",{willReadFrequently:!0});_i.canvas.width=u,_i.canvas.height=c,_i.drawImage(e,0,0,u,c),p=_i.getImageData(0,0,u,c).data}let d;if(t===4)d=new Int32Array(p);else{let f=u*c;d=new Int32Array(f*t);for(let m=0;m<f;m++)for(let g=0;g<t;++g)d[m*t+g]=p[m*4+g]}return My(d,[c,u,t],"int32")}function D$(e){return e!=null&&e.data instanceof Uint8Array}function $$(){return typeof window!="undefined"&&typeof ImageBitmap!="undefined"&&window.hasOwnProperty("createImageBitmap")}function P$(e){return e!=null&&e.width!==0&&e.height!==0}function F$(e){return $$()&&!(e instanceof ImageBitmap)&&P$(e)&&!D$(e)}async function O$(e,t=3){let n=null;if(X().getBool("WRAP_TO_IMAGEBITMAP")&&F$(e)){let s;try{s=await createImageBitmap(e,{premultiplyAlpha:"none"})}catch(r){s=null}s!=null&&s.width===e.width&&s.height===e.height?n=s:n=e}else n=e;return z6(n,t)}async function M$(e,t){let n=D(e,"img","toPixels");if(!(e instanceof tt)){let u=n;n=ge(u,"int32"),u.dispose()}if(n.rank!==2&&n.rank!==3)throw new Error(`toPixels only supports rank 2 or 3 tensors, got rank ${n.rank}.`);let[s,r]=n.shape.slice(0,2),a=n.rank===2?1:n.shape[2];if(a>4||a===2)throw new Error(`toPixels only supports depth of size 1, 3 or 4 but got ${a}`);if(n.dtype!=="float32"&&n.dtype!=="int32")throw new Error(`Unsupported type for toPixels: ${n.dtype}. Please use float32 or int32 tensors.`);let o=await n.data(),i=n.dtype==="float32"?255:1,l=new Uint8ClampedArray(r*s*4);for(let u=0;u<s*r;++u){let c=[0,0,0,255];for(let d=0;d<a;d++){let h=o[u*a+d];if(n.dtype==="float32"){if(h<0||h>1)throw new Error(`Tensor values for a float32 Tensor must be in the range [0 - 1] but encountered ${h}.`)}else if(n.dtype==="int32"&&(h<0||h>255))throw new Error(`Tensor values for a int32 Tensor must be in the range [0 - 255] but encountered ${h}.`);a===1?(c[0]=h*i,c[1]=h*i,c[2]=h*i):c[d]=h*i}let p=u*4;l[p+0]=Math.round(c[0]),l[p+1]=Math.round(c[1]),l[p+2]=Math.round(c[2]),l[p+3]=Math.round(c[3])}if(t!=null){t.width=r,t.height=s;let u=t.getContext("2d"),c=new ImageData(l,r,s);u.putImageData(c,0,0)}return n!==e&&n.dispose(),l}var z$=V({fromPixels_:z6}),zy={};Ve(zy,{prepareAndValidate:()=>L6});function L6(e,t){let n=e.shape.length,s=t.shape.length;if(n<1)throw new Error(`tf.gatherND() expects the input to be rank 1 or higher, but the rank was ${n}.`);if(s<1)throw new Error(`tf.gatherND() expects the indices to be rank 1 or higher, but the rank was ${s}.`);if(t.dtype!=="int32")throw new Error(`tf.gatherND() expects the indices to be int32 type, but the dtype was ${t.dtype}.`);if(t.shape[s-1]>n)throw new Error(`index innermost dimension length must be <= tensor rank; saw: ${t.shape[s-1]} vs. ${n}`);if(Et(e.shape)===0)throw new Error(`Requested more than 0 entries, but input is empty. Input shape: ${e.shape}.`);let r=t.shape,a=r[r.length-1],o=1;for(let p=0;p<r.length-1;++p)o*=r[p];let i=e.shape,l=r.slice();l.pop();let u=1;for(let p=a;p<n;++p)u*=i[p],l.push(i[p]);let c=[...cc(e.shape).map(p=>p/u),1].slice(0,a);return[l,o,u,c]}var Ly={};Ve(Ly,{calculateShapes:()=>B6,validateInput:()=>Wy,validateUpdateShape:()=>By});function By(e,t,n){let s=t.rank>1?t.shape[t.rank-1]:1,r=t.rank>1?t.rank-1:1,a=`Must have updates.shape = indices.shape[:batchDim] + shape[sliceDim:], got updates.shape: ${n.shape}, indices.shape: ${t.shape}, shape: ${e}, sliceDim: ${s}, and batchDim: ${r}.`;if(n.rank<r)throw new Error(a+` update.rank < ${r}. `);if(e.length<s+(n.rank-r))throw new Error(a+` Output shape length < ${s+(n.rank-r)}`);if(n.rank!==r+e.length-s)throw new Error(a+` update.rank != ${r+e.length-s}`);for(let o=0;o<r;++o)if(n.shape[o]!==t.shape[o])throw new Error(a+` updates.shape[${o}] (${n.shape[o]}) != indices.shape[${o}] (${t.shape[o]}).`);for(let o=0;o<n.rank-r;++o)if(n.shape[o+r]!==e[o+s])throw new Error(a+` updates.shape[${o+r}] (${n.shape[o+r]}) != shape[${o+r}] (${e[o+r]})`)}function Wy(e,t,n){if(t.rank<1)throw new Error(`tf.scatterND() expects the indices to be rank 1 or higher, but the rank was ${t.rank}.`);if(e.rank<1)throw new Error(`tf.scatterND() expects the updates to be rank 1 or higher, but the rank was ${e.rank}.`);if(t.dtype!=="int32")throw new Error(`The dtype of 'indices' should be int32, but got dtype: ${t.dtype}`);if(n.length<1)throw new Error(`Output rank must be greater or equal to 1, but got shape: ${n}`);if(n.length===0){if(t.size===0)throw new Error(`Indices specified for empty output. indices shape: ${t.shape}`);if(e.size===0)throw new Error(`Updates specified for empty output. updates shape: ${e.shape}`)}By(n,t,e)}function B6(e,t,n){let s=t.shape.length,r=s>1?t.shape[s-1]:1,a=n.length,o=1;for(let p=r;p<a;++p)o*=n[p];let i=r<1?1:r,l=Et(t.shape)/i,u=[...cc(n.slice(0,r)),1],c=Et(n);return{sliceRank:r,numUpdates:l,sliceSize:o,strides:u,outputSize:c}}var Ut={};Ve(Ut,{assertParamsValid:()=>B$,computeFlatOffset:()=>H$,computeOutShape:()=>V$,getNormalizedAxes:()=>U$,isSliceContinous:()=>G$,maskToAxes:()=>W$,parseSliceParams:()=>K6,sliceInfo:()=>j$,startForAxis:()=>q6,startIndicesWithElidedDims:()=>G6,stopForAxis:()=>X6,stopIndicesWithElidedDims:()=>H6,stridesForAxis:()=>j6,stridesWithElidedDims:()=>W6});var N3=-2,L$=-1;function B$(e,t,n){let s=e.shape.length;M(s===t.length,()=>`Error in slice${s}D: Length of begin ${t} must match the rank of the array (${s}).`),M(s===n.length,()=>`Error in slice${s}D: Length of size ${n} must match the rank of the array (${s}).`);for(let r=0;r<s;++r)M(t[r]+n[r]<=e.shape[r],()=>`Error in slice${s}D: begin[${r}] + size[${r}] (${t[r]+n[r]}) would overflow input.shape[${r}] (${e.shape[r]})`)}function W$(e){let t=[],n=0;for(;e>0;)e&1&&t.push(n),e/=2,n++;return t}function V$(e,t,n){let s=[];for(let r=0;r<e.length;r++)s[r]=Math.ceil((t[r]-e[r])/n[r]);return s}function W6(e,t,n,s){let r=[...e];for(let a=r.length;a<s.length;a++)r.push(1);for(let a=0;a<n;a++)a===0?r[t]=1:(r.splice(t,0,1),r.pop());return r}function V6(e,t,n){return n<=e?n:n-(t-1)}function U6(e,t){let n=[];for(let s=0;s<e;s++)n.push(t+s);return n}function U$(e,t,n,s,r,a,o,i,l){let u=e.length,c=new Array(u),p=new Array(u),d=new Array(u);if(t.length&&n>0){let h=t[0],f=n+1;c=G6(o,h,f,s,e),p=H6(i,h,f,r,e),d=W6(a,h,f,e)}else for(let h=0;h<u;h++)c[h]=q6(o,s,a,e,h,l),p[h]=X6(i,r,a,e,h,l),d[h]=j6(a,h,l);return{begin:c,end:p,strides:d}}function G6(e,t,n,s,r){let a=[...r],o=U6(n,t);for(let i=0;i<a.length;i++)if(o.indexOf(i)>-1)a[i]=0;else{let l=V6(t,n,i),u=s[l];e&1<<l&&(u=0),a[i]=u}return a}function H6(e,t,n,s,r){let a=[...r],o=U6(n,t);for(let i=0;i<a.length;i++)if(o.indexOf(i)>-1)a[i]=Number.MAX_SAFE_INTEGER;else{let l=V6(t,n,i),u=s[l];e&1<<l&&(u=Number.MAX_SAFE_INTEGER),a[i]=u}for(let i=0;i<a.length;i++){let l=r[i];a[i]<0&&(a[i]+=l),a[i]=Ap(0,a[i],r[i])}return a}function j6(e,t,n){let s=e[t];return(n&1<<t||s==null)&&(s=1),s}function q6(e,t,n,s,r,a){let o=t[r],i=n[r]||1;(e&1<<r||a&1<<r||o==null)&&(i>0?o=Number.MIN_SAFE_INTEGER:o=Number.MAX_SAFE_INTEGER);let l=s[r];return o<0&&(o+=l),o=Ap(0,o,l-1),o}function X6(e,t,n,s,r,a){let o=t[r],i=n[r]||1;(e&1<<r||a&1<<r||o==null)&&(i>0?o=Number.MAX_SAFE_INTEGER:o=Number.MIN_SAFE_INTEGER);let l=s[r];return o<0&&(o+=l),i>0?o=Ap(0,o,l):o=Ap(-1,o,l-1),o}function G$(e,t,n){let s=n.length;for(let r=0;r<n.length;r++)if(n[r]>1){s=r;break}for(let r=s+1;r<n.length;r++)if(t[r]>0||n[r]!==e[r])return!1;return!0}function H$(e,t){let n=e.length>0?e[e.length-1]:1;for(let s=0;s<e.length-1;s++)n+=e[s]*t[s];return n}function K6(e,t,n){let s,r=e.shape.length;typeof t=="number"?s=[t,...new Array(r-1).fill(0)]:t.length<r?s=t.concat(new Array(r-t.length).fill(0)):s=t.slice(),s.forEach(o=>{M(o!==-1,()=>"slice() does not support negative begin indexing.")});let a;return n==null?a=new Array(r).fill(-1):typeof n=="number"?a=[n,...new Array(r-1).fill(-1)]:n.length<r?a=n.concat(new Array(r-n.length).fill(-1)):a=n,a=a.map((o,i)=>o>=0?o:(M(o===-1,()=>`Negative size values should be exactly -1 but got ${o} for the slice() size at index ${i}.`),e.shape[i]-s[i])),[s,a]}function j$(e,t,n,s,r,a,o,i,l){let u;if(s==null?(u=new Array(t.length),u.fill(1)):u=s,o!=null&&(o&o-1)!==0)throw new Error("Multiple ellipses in slice is not allowed.");let c=!1,p={dims:u.length,numAddAxisAfterEllipsis:0,begin:t.slice(),end:n.slice(),strides:u.slice(),beginMask:r,endMask:a,ellipsisMask:o,newAxisMask:i,shrinkAxisMask:l};for(let A=0;A<p.dims;A++)c&&(1<<A&i)!==0&&p.numAddAxisAfterEllipsis++,1<<A&o&&(c=!0);c||(p.ellipsisMask|=1<<p.dims,p.dims++);let d={dims:e.length,beginMask:0,endMask:0,beginValid:!1,endValid:!1};q$(p,d);let h=!0,f=!0,m=!0,g=[],y=[];for(let A=0;A<e.length;++A){if(d.strides[A]===0)throw Error(`strides[${A}] must be non-zero`);let b=!!(d.shrinkAxisMask&1<<A),w=e[A];if(w===-1){g.push(b?1:-1);continue}let k=[d.beginMask&1<<A,d.endMask&1<<A],S=[d.strides[A]>0?0:-1,d.strides[A]>0?w:w-1];if(b&&d.strides[A]<=0)throw Error("only stride 1 allowed on non-range indexing.");m=m&&d.strides[A]===1;let E=!!(d.beginMask&1<<A&&d.endMask&1<<A);if(d.beginValid&&d.endValid){if(b){let $=d.begin[A]<0?w+d.begin[A]:d.begin[A];if(d.begin[A]=$,d.end[A]=d.begin[A]+1,$<0||$>=w)throw Error(`slice index ${d.begin[A]} of dimension ${A} out of bounds.`)}else d.begin[A]=bv(d.begin[A],0,d.strides[A],w,k,S),d.end[A]=bv(d.end[A],1,d.strides[A],w,k,S);let _=d.strides[A]===1&&d.begin[A]===0&&d.end[A]===w;h=h&&_,f=f&&(A===0&&d.strides[A]===1||_)}else h=h&&d.strides[A]===1&&E,f=f&&(A===0&&d.strides[A]===1||E);let R,P=!1;if(d.beginValid&&d.endValid?(R=d.end[A]-d.begin[A],P=!0):b?(R=1,P=!0):E&&w>=0&&(d.strides[A]<0?R=-w:R=w,P=!0),P){let _;R===0||R<0!=d.strides[A]<0?_=0:_=Math.trunc(R/d.strides[A])+(R%d.strides[A]!==0?1:0),g.push(_)}else g.push(-1)}for(let A=0;A<d.finalShapeGatherIndices.length;++A){let b=d.finalShapeGatherIndices[A];b>=0?y.push(g[b]):b===N3&&y.push(1)}return{finalShapeSparse:y.filter((A,b)=>d.finalShapeGatherIndices[b]!==N3),finalShape:y,isIdentity:h,sliceDim0:f,isSimpleSlice:m,begin:d.begin,end:d.end,strides:d.strides}}function q$(e,t){t.beginMask=0,t.endMask=0,t.shrinkAxisMask=0;let n=0;t.beginValid=e.begin!=null,t.endValid=e.end!=null,t.begin=new Array(t.dims),t.end=new Array(t.dims),t.strides=new Array(t.dims),t.finalShapeGatherIndices=[],t.finalShapeGatherIndicesSparse=[],t.inputShapeGatherIndicesSparse=new Array(t.dims);for(let s=0;s<e.dims;s++)if(1<<s&e.ellipsisMask){let r=Math.min(t.dims-(e.dims-s)+1+e.numAddAxisAfterEllipsis,t.dims);for(;n<r;n++)t.begin[n]=0,t.end[n]=0,t.strides[n]=1,t.beginMask|=1<<n,t.endMask|=1<<n,t.finalShapeGatherIndices.push(n),t.finalShapeGatherIndicesSparse.push(-1),t.inputShapeGatherIndicesSparse[n]=s}else if(1<<s&e.newAxisMask)t.finalShapeGatherIndices.push(N3),t.finalShapeGatherIndicesSparse.push(-1);else{if(n===t.begin.length)throw Error(`Index out of range using input dim ${n}; input has only ${t.dims} dims, ${t.begin.length}.`);e.begin!=null&&(t.begin[n]=e.begin[s]),e.end!=null&&(t.end[n]=e.end[s]),t.strides[n]=e.strides[s],e.beginMask&1<<s&&(t.beginMask|=1<<n),e.endMask&1<<s&&(t.endMask|=1<<n),e.shrinkAxisMask&1<<s?(t.finalShapeGatherIndices.push(L$),t.finalShapeGatherIndicesSparse.push(-1),t.shrinkAxisMask|=1<<n):(t.finalShapeGatherIndices.push(n),t.finalShapeGatherIndicesSparse.push(s)),t.inputShapeGatherIndicesSparse[n]=s,n++}}function bv(e,t,n,s,r,a){if(r[t])return n>0?a[t]:a[t+1&1];{let o=e<0?s+e:e;return o<a[0]?a[0]:o>a[1]?a[1]:o}}var de={};Ve(de,{Serializable:()=>Z6,SerializationMap:()=>Mi,registerClass:()=>oi});var Z6=class{getClassName(){return this.constructor.className}static fromConfig(e,t){return new e(t)}},Mi=class{constructor(){this.classNameMap={}}static getMap(){return Mi.instance==null&&(Mi.instance=new Mi),Mi.instance}static register(e){Mi.getMap().classNameMap[e.className]=[e,e.fromConfig]}};function oi(e){M(e.className!=null,()=>"Class being registered does not have the static className property defined."),M(typeof e.className=="string",()=>"className is required to be a string, but got type "+typeof e.className),M(e.className.length>0,()=>"Class being registered has an empty-string as its className, which is disallowed."),Mi.register(e)}var Y6={};Ve(Y6,{TEST_EPSILON_FLOAT16:()=>J6,encodeStrings:()=>Q6,expectArrayBuffersEqual:()=>eP,expectArraysClose:()=>K$,expectArraysEqual:()=>Y$,expectNumbersClose:()=>J$,expectPromiseToFail:()=>Z$,expectValuesInRange:()=>Q$,testEpsilon:()=>Vy});var X$=.001,J6=.1;function K$(e,t,n){return n==null&&(n=Vy()),E3(e,t,(s,r)=>Uy(s,r,n))}function Vy(){return W.backend.floatPrecision()===32?X$:J6}function E3(e,t,n){let s=!0;if((Pn(e)||Pn(t))&&(s=!1),Pn(e)&&Pn(t)&&(s=!0),s){let o=e.constructor.name,i=t.constructor.name;if(o!==i)throw new Error(`Arrays are of different type. Actual: ${o}. Expected: ${i}`)}if(Array.isArray(e)&&Array.isArray(t)){let o=qr(e),i=qr(t);if(!uo(o,i))throw new Error(`Arrays have different shapes. Actual: [${o}]. Expected: [${i}]`)}let r=Pn(e)?e:qi(e),a=Pn(t)?t:qi(t);if(r.length!==a.length)throw new Error(`Arrays have different lengths actual: ${r.length} vs expected: ${a.length}.
 Actual:   ${r}.
 Expected: ${a}.`);for(let o=0;o<a.length;++o){let i=r[o],l=a[o];if(!n(i,l))throw new Error(`Arrays differ: actual[${o}] = ${i}, expected[${o}] = ${l}.
 Actual:   ${r}.
-Expected: ${a}.`)}}function Z$(e,t){e().then(()=>t.fail(),()=>t())}function Y$(e,t){let n=typeof t=="string"||typeof t=="number"||typeof t=="boolean"?[t]:t;return Ga(e)||Ga(e[0])||Ga(t)||Ga(t[0])?R3(e,n,(s,r)=>s==r):R3(e,t,(s,r)=>Uy(s,r,0))}function J$(e,t,n){if(n==null&&(n=Vy()),!Uy(e,t,n))throw new Error(`Numbers differ: actual === ${e}, expected === ${t}`)}function Uy(e,t,n){return!isFinite(e)&&!isFinite(t)?!0:!(isNaN(e)||isNaN(t)||Math.abs(e-t)>n)}function Q$(e,t,n){for(let s=0;s<e.length;s++)if(e[s]<t||e[s]>n)throw new Error(`Value out of range:${e[s]} low: ${t}, high: ${n}`)}function eP(e,t){let n=new Float32Array(e),s=new Float32Array(t);if(n.length!==s.length)throw new Error(`Expected ArrayBuffer to be of length ${s.length}, but it was ${n.length}`);for(let r=0;r<s.length;r++)if(n[r]!==s[r])throw new Error(`Expected ArrayBuffer value at ${r} to be ${s[r]} but got ${n[r]} instead`)}function Q6(e){for(let t=0;t<e.length;t++){let n=e[t];Array.isArray(n)?Q6(n):e[t]=nh(n)}return e}var Gy="3.19.0";function tP(e,t){let n=D(e,"a","add"),s=D(t,"b","add");[n,s]=Gt(n,s);let r={a:n,b:s};return W.runKernel(xa,r)}var ce=V({add_:tP});function nP(e,t){let n=D(e,"a","floorDiv"),s=D(t,"b","floorDiv");[n,s]=Gt(n,s);let r={a:n,b:s};return W.runKernel(No,r)}var Bc=V({floorDiv_:nP});function sP(e,t){let n=D(e,"a","div"),s=D(t,"b","div");if([n,s]=Gt(n,s),n.dtype==="int32"&&s.dtype==="int32")return Bc(n,s);let r={a:n,b:s},a={};return W.runKernel(Io,r,a)}var pe=V({div_:sP});function rP(e,t){let n=D(e,"a","mul"),s=D(t,"b","mul");[n,s]=Gt(n,s);let r={a:n,b:s};return W.runKernel(Wo,r)}var L=V({mul_:rP});function aP(e){let t=D(e,"x","abs");if(t.dtype==="complex64"){let n={x:t};return W.runKernel(Bp,n)}else{let n={x:t};return W.runKernel(il,n)}}var tn=V({abs_:aP});function oP(e){let n={x:D(e,"x","acos")};return W.runKernel(pc,n)}var Hy=V({acos_:oP});function iP(e){let n={x:D(e,"x","acosh")};return W.runKernel(hc,n)}var jy=V({acosh_:iP});function lP(e){M(Array.isArray(e),()=>"The argument passed to tf.addN() must be a list of tensors"),M(e.length>=1,()=>`Must pass at least one tensor to tf.addN(), but got ${e.length}`);let t=e.map((r,a)=>D(r,`tensors${a}`,"addN")),n=t[0];t.forEach(r=>{if(r.dtype!==n.dtype)throw new Error("All tensors passed to tf.addN() must have the same dtype")}),t.forEach(r=>{if(!co(r.shape,n.shape))throw new Error("All tensors passed to tf.addN() must have the same shape")});let s=t;return W.runKernel(po,s)}var m0=V({addN_:lP});function uP(e,t=null,n=!1){let r={x:D(e,"x","all","bool")},a={axis:t,keepDims:n};return W.runKernel(fc,r,a)}var g0=V({all_:uP});function cP(e,t=null,n=!1){let r={x:D(e,"x","any","bool")},a={axis:t,keepDims:n};return W.runKernel(mc,r,a)}var Cp=V({any_:cP});function dP(e,t=0){let s={x:D(e,"x","argMax")},r={axis:t};return W.runKernel(ho,s,r)}var Es=V({argMax_:dP});function pP(e,t=0){let s={x:D(e,"x","argMin")},r={axis:t};return W.runKernel(gc,s,r)}var qy=V({argMin_:pP});function hP(e){let n={x:D(e,"x","asin")};return W.runKernel(yc,n)}var Xy=V({asin_:hP});function fP(e){let n={x:D(e,"x","asinh")};return W.runKernel(Ac,n)}var Ky=V({asinh_:fP});function mP(e){let n={x:D(e,"x","atan")};return W.runKernel(xc,n)}var Zy=V({atan_:mP});function gP(e,t){let n=D(e,"a","atan2"),s=D(t,"b","atan2");[n,s]=Gt(n,s);let r={a:n,b:s};return W.runKernel(vc,r)}var Yy=V({atan2_:gP});function yP(e){let n={x:D(e,"x","atanh")};return W.runKernel(bc,n)}var Jy=V({atanh_:yP});function AP(e,t,n,s,r="NHWC",a){let o=e[3],i=[...t,o],l=nw(r);return ih(e,i,n,a,s,null,null,l)}function ew(e,t,n,s,r,a,o="channelsLast"){let[i,l]=Am(t),u;if(o==="channelsLast")u=[i,l,e[3],e[3]];else if(o==="channelsFirst")u=[i,l,e[1],e[1]];else throw new Error(`Unknown dataFormat ${o}`);return ih(e,u,n,s,r,a,!1,o)}function xP(e,t,n,s,r,a,o="NDHWC"){let[i,l,u]=_3(t),c,p;if(o==="NDHWC")p="channelsLast",c=[i,l,u,e[4],e[4]];else if(o==="NCDHW")p="channelsFirst",c=[i,l,u,e[1],e[1]];else throw new Error(`Unknown dataFormat ${o}`);return tw(e,c,n,s,r,!1,p,a)}function ih(e,t,n,s,r,a,o=!1,i="channelsLast"){let[l,u,c,p]=[-1,-1,-1,-1];if(i==="channelsLast")[l,u,c,p]=e;else if(i==="channelsFirst")[l,p,u,c]=e;else throw new Error(`Unknown dataFormat ${i}`);let[d,h,,f]=t,[m,g]=Am(n),[y,x]=Am(s),A=Uu(d,y),b=Uu(h,x),{padInfo:w,outHeight:k,outWidth:S}=wP(r,u,c,m,g,A,b,a,i),E=o?f*p:f,R;return i==="channelsFirst"?R=[l,E,k,S]:i==="channelsLast"&&(R=[l,k,S,E]),{batchSize:l,dataFormat:i,inHeight:u,inWidth:c,inChannels:p,outHeight:k,outWidth:S,outChannels:E,padInfo:w,strideHeight:m,strideWidth:g,filterHeight:d,filterWidth:h,effectiveFilterHeight:A,effectiveFilterWidth:b,dilationHeight:y,dilationWidth:x,inShape:e,outShape:R,filterShape:t}}function tw(e,t,n,s,r,a=!1,o="channelsLast",i){let[l,u,c,p,d]=[-1,-1,-1,-1,-1];if(o==="channelsLast")[l,u,c,p,d]=e;else if(o==="channelsFirst")[l,d,u,c,p]=e;else throw new Error(`Unknown dataFormat ${o}`);let[h,f,m,,g]=t,[y,x,A]=_3(n),[b,w,k]=_3(s),S=Uu(h,b),E=Uu(f,w),R=Uu(m,k),{padInfo:P,outDepth:_,outHeight:$,outWidth:T}=kP(r,u,c,p,y,x,A,S,E,R,i),F=a?g*d:g,G;return o==="channelsFirst"?G=[l,F,_,$,T]:o==="channelsLast"&&(G=[l,_,$,T,F]),{batchSize:l,dataFormat:o,inDepth:u,inHeight:c,inWidth:p,inChannels:d,outDepth:_,outHeight:$,outWidth:T,outChannels:F,padInfo:P,strideDepth:y,strideHeight:x,strideWidth:A,filterDepth:h,filterHeight:f,filterWidth:m,effectiveFilterDepth:S,effectiveFilterHeight:E,effectiveFilterWidth:R,dilationDepth:b,dilationHeight:w,dilationWidth:k,inShape:e,outShape:G,filterShape:t}}function bP(e,t,n,s,r){s==null&&(s=Qy(e,t,n));let a=e[0],o=e[1],i=Gi((a-t+2*s)/n+1,r),l=Gi((o-t+2*s)/n+1,r);return[i,l]}function vP(e,t,n,s,r,a){r==null&&(r=Qy(e,t,s));let o=e[0],i=e[1],l=e[2],u=Gi((o-t+2*r)/s+1,a),c=Gi((i-t+2*r)/s+1,a),p=Gi((l-t+2*r)/s+1,a);return[u,c,p,n]}function Qy(e,t,n,s=1){let r=Uu(t,s);return Math.floor((e[0]*(n-1)-n+r)/2)}function Am(e){return typeof e=="number"?[e,e,e]:e.length===2?[e[0],e[1],1]:e}function _3(e){return typeof e=="number"?[e,e,e]:e}function Uu(e,t){return t<=1?e:e+(e-1)*(t-1)}function wP(e,t,n,s,r,a,o,i,l){let u,c,p;if(typeof e=="number"){u={top:e,bottom:e,left:e,right:e,type:e===0?"VALID":"NUMBER"};let h=bP([t,n],a,s,e,i);c=h[0],p=h[1]}else if(e==="same"){c=Math.ceil(t/s),p=Math.ceil(n/r);let d=Math.max(0,(c-1)*s+a-t),h=Math.max(0,(p-1)*r+o-n),f=Math.floor(d/2),m=d-f,g=Math.floor(h/2),y=h-g;u={top:f,bottom:m,left:g,right:y,type:"SAME"}}else if(e==="valid")u={top:0,bottom:0,left:0,right:0,type:"VALID"},c=Math.ceil((t-a+1)/s),p=Math.ceil((n-o+1)/r);else if(typeof e=="object"){let d=l==="channelsLast"?e[1][0]:e[2][0],h=l==="channelsLast"?e[1][1]:e[2][1],f=l==="channelsLast"?e[2][0]:e[3][0],m=l==="channelsLast"?e[2][1]:e[3][1];u={top:d,bottom:h,left:f,right:m,type:d===0&&h===0&&f===0&&m===0?"VALID":"EXPLICIT"},c=Gi((t-a+d+h)/s+1,i),p=Gi((n-o+f+m)/r+1,i)}else throw Error(`Unknown padding parameter: ${e}`);return{padInfo:u,outHeight:c,outWidth:p}}function kP(e,t,n,s,r,a,o,i,l,u,c){let p,d,h,f;if(typeof e=="number"){p={top:e,bottom:e,left:e,right:e,front:e,back:e,type:e===0?"VALID":"NUMBER"};let g=vP([t,n,s,1],i,1,r,e,c);d=g[0],h=g[1],f=g[2]}else if(e==="same"){d=Math.ceil(t/r),h=Math.ceil(n/a),f=Math.ceil(s/o);let m=(d-1)*r+i-t,g=(h-1)*a+l-n,y=(f-1)*o+u-s,x=Math.floor(m/2),A=m-x,b=Math.floor(g/2),w=g-b,k=Math.floor(y/2),S=y-k;p={top:b,bottom:w,left:k,right:S,front:x,back:A,type:"SAME"}}else if(e==="valid")p={top:0,bottom:0,left:0,right:0,front:0,back:0,type:"VALID"},d=Math.ceil((t-i+1)/r),h=Math.ceil((n-l+1)/a),f=Math.ceil((s-u+1)/o);else throw Error(`Unknown padding parameter: ${e}`);return{padInfo:p,outDepth:d,outHeight:h,outWidth:f}}function Gi(e,t){if(!t)return Math.trunc(e);switch(t){case"round":return Math.round(e);case"ceil":return Math.ceil(e);case"floor":return Math.floor(e);default:throw new Error(`Unknown roundingMode ${t}`)}}function to(e){let[t,n,s]=Am(e);return t===1&&n===1&&s===1}function Yr(e,t){return to(e)||to(t)}function nw(e){if(e==="NHWC")return"channelsLast";if(e==="NCHW")return"channelsFirst";throw new Error(`Unknown dataFormat ${e}`)}function rs(e,t,n){if(n!=null){if(typeof t=="string")throw Error(`Error in ${e}: pad must be an integer when using dimRoundingMode ${n} but got pad ${t}.`);if(typeof t=="number")M(qu(t),()=>`Error in ${e}: pad must be an integer when using dimRoundingMode ${n} but got pad ${t}.`);else if(typeof t=="object")t.forEach(s=>{s.forEach(r=>{M(qu(r),()=>`Error in ${e}: pad must be an integer when using dimRoundingMode ${n} but got pad ${r}.`)})});else throw Error(`Error in ${e}: Unknown padding parameter: ${t}`)}}function IP(e,t){let s={x:D(e,"x","reshape","string_or_numeric")},r={shape:t};return W.runKernel(_l,s,r)}var U=V({reshape_:IP});function SP(e,t,n,s,r){let a=D(e,"x","avgPool","float32"),o=1;M(Yr(n,o),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${n} and dilations '${o}'`);let i=a,l=!1;a.rank===3&&(l=!0,i=U(a,[1,a.shape[0],a.shape[1],a.shape[2]])),M(i.rank===4,()=>`Error in avgPool: x must be rank 4 but got rank ${i.rank}.`),rs("avgPool",s,r);let u={x:i},c={filterSize:t,strides:n,pad:s,dimRoundingMode:r},p=W.runKernel(fo,u,c);return p=ge(p,a.dtype),l?U(p,[p.shape[1],p.shape[2],p.shape[3]]):p}var lh=V({avgPool_:SP});function CP(e,t,n,s,r,a="NDHWC"){let o=D(e,"x","avgPool3d","float32"),i=o,l=!1;o.rank===4&&(l=!0,i=U(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),M(i.rank===5,()=>`Error in avgPool3d: x must be rank 5 but got rank ${i.rank}.`),M(a==="NDHWC",()=>`Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of ${a}`),rs("avgPool3d",s,r);let u={x:i},c={filterSize:t,strides:n,pad:s,dimRoundingMode:r,dataFormat:a},p=W.runKernel(zp,u,c);return p=ge(p,i.dtype),l?U(p,[p.shape[1],p.shape[2],p.shape[3],p.shape[4]]):p}var eA=V({avgPool3d_:CP});function TP(e,t=0){M(e.length>=1,()=>"Pass at least one tensor to concat");let n=Sp(e,"tensors","concat","string_or_numeric");if(n[0].dtype==="complex64"&&n.forEach(a=>{if(a.dtype!=="complex64")throw new Error(`Cannot concatenate complex64 tensors with a tensor
-          with dtype ${a.dtype}. `)}),n.length===1)return Fn(n[0]);let s=n,r={axis:t};return W.runKernel(ul,s,r)}var Ct=V({concat_:TP});function NP(e){let n={x:D(e,"x","sigmoid","float32")};return W.runKernel(Jo,n)}var Cn=V({sigmoid_:NP});function EP(e,t,n){let s=D(e,"x","slice","string_or_numeric");if(s.rank===0)throw new Error("Slicing scalar is not possible");let r={x:s},a={begin:t,size:n};return W.runKernel(Ol,r,a)}var Oe=V({slice_:EP});function RP(e){let n={x:D(e,"x","tanh","float32")};return W.runKernel(ri,n)}var Yi=V({tanh_:RP});function _P(e,t,n,s,r,a){let o=D(e,"forgetBias","basicLSTMCell"),i=D(t,"lstmKernel","basicLSTMCell"),l=D(n,"lstmBias","basicLSTMCell"),u=D(s,"data","basicLSTMCell"),c=D(r,"c","basicLSTMCell"),p=D(a,"h","basicLSTMCell"),d=Ct([u,p],1),h=Qe(d,i),f=ce(h,l),m=f.shape[0],g=f.shape[1]/4,y=[m,g],x=Oe(f,[0,0],y),A=Oe(f,[0,g],y),b=Oe(f,[0,g*2],y),w=Oe(f,[0,g*3],y),k=ce(L(Cn(x),Yi(A)),L(c,Cn(ce(o,b)))),S=L(Yi(k),Cn(w));return[k,S]}var sw=V({basicLSTMCell_:_P});function DP(e,t,n){let s=D(e,"x","batchToSpaceND"),r=t.reduce((i,l)=>i*l);M(s.rank>=1+t.length,()=>`input rank is ${s.rank} but should be > than blockShape.length ${t.length}`),M(n.length===t.length,()=>`crops.length is ${n.length} but should be equal to blockShape.length  ${t.length}`),M(s.shape[0]%r===0,()=>`input tensor batch is ${s.shape[0]} but is not divisible by the product of the elements of blockShape ${t.join(" * ")} === ${r}`);let a={x:s},o={blockShape:t,crops:n};return W.runKernel(ll,a,o)}var uh=V({batchToSpaceND_:DP});function $P(e){let t;return e.rank===0||e.rank===1?t=U(e,[1,1,1,e.size]):e.rank===2?t=U(e,[1,1,e.shape[0],e.shape[1]]):e.rank===3?t=U(e,[1,e.shape[0],e.shape[1],e.shape[2]]):t=e,t}function PP(e,t,n,s,r,a){a==null&&(a=.001);let o=D(e,"x","batchNorm"),i=D(t,"mean","batchNorm"),l=D(n,"variance","batchNorm"),u;r!=null&&(u=D(r,"scale","batchNorm"));let c;s!=null&&(c=D(s,"offset","batchNorm")),M(i.rank===l.rank,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),M(c==null||i.rank===c.rank,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),M(u==null||i.rank===u.rank,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let d={x:$P(o),scale:u,offset:c,mean:i,variance:l},h={varianceEpsilon:a},f=W.runKernel(Eo,d,h);return U(f,o.shape)}var Wc=V({batchNorm_:PP});function FP(e,t,n,s,r,a){let o=D(e,"x","batchNorm"),i=D(t,"mean","batchNorm"),l=D(n,"variance","batchNorm"),u;r!=null&&(u=D(r,"scale","batchNorm"));let c;return s!=null&&(c=D(s,"offset","batchNorm")),M(o.rank===2,()=>`Error in batchNorm2D: x must be rank 2 but got rank ${o.rank}.`),M(i.rank===2||i.rank===1,()=>`Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank ${i.rank}.`),M(l.rank===2||l.rank===1,()=>`Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank ${l.rank}.`),u!=null&&M(u.rank===2||u.rank===1,()=>`Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank ${u.rank}.`),c!=null&&M(c.rank===2||c.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${c.rank}.`),Wc(o,i,l,c,u,a)}var tA=V({batchNorm2d_:FP});function OP(e,t,n,s,r,a){let o=D(e,"x","batchNorm"),i=D(t,"mean","batchNorm"),l=D(n,"variance","batchNorm"),u;r!=null&&(u=D(r,"scale","batchNorm"));let c;return s!=null&&(c=D(s,"offset","batchNorm")),M(o.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${o.rank}.`),M(i.rank===3||i.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${i.rank}.`),M(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${l.rank}.`),u!=null&&M(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${u.rank}.`),c!=null&&M(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${c.rank}.`),Wc(o,i,l,c,u,a)}var nA=V({batchNorm3d_:OP});function MP(e,t,n,s,r,a){let o=D(e,"x","batchNorm"),i=D(t,"mean","batchNorm"),l=D(n,"variance","batchNorm"),u;r!=null&&(u=D(r,"scale","batchNorm"));let c;return s!=null&&(c=D(s,"offset","batchNorm")),M(o.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${o.rank}.`),M(i.rank===4||i.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${i.rank}.`),M(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),u!=null&&M(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`),c!=null&&M(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`),Wc(o,i,l,c,u,a)}var sA=V({batchNorm4d_:MP});function zP(e,t,n){let s=D(e,"x","bincount"),r=D(t,"weights","bincount");M(s.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${s.dtype}`),M(n>=0,()=>`size must be non-negative, but got ${n}.`),M(r.size===s.size||r.size===0,()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${s.shape}, weights shape: ${r.shape}.`);let a={x:s,weights:r},o={size:n};return W.runKernel(jm,a,o)}var rA=V({bincount_:zP});function LP(e,t){let n=D(e,"s0","broadcastArgs","int32"),s=D(t,"s1","broadcastArgs","int32");if(n.rank!==1)throw new Error(`broadcastArgs(): first input must be a vector (rank=1). Has rank ${n.rank}`);if(s.rank!==1)throw new Error(`broadcastArgs(): second input must be a vector (rank=1). Has rank ${s.rank}`);let r={s0:n,s1:s};return W.runKernel(qm,r)}var rw=V({broadcastArgs_:LP});function BP(e,t){let n=D(e,"broadcastTo","x"),s=n.shape;if(t.some(u=>!(u>0)||u%1!==0))throw new Error(`broadcastTo(): Invalid broadcast shape [${t}].`);if(t.length<n.rank)throw new Error(`broadcastTo(): shape.length=${t.length} < input.rank=${n.rank}.`);if(t.length>n.rank){let u=n.shape.slice();for(;u.length<t.length;)u.unshift(1);n=U(n,u)}let r=n.shape,a=Array.from(t);for(let u=t.length-1;u>=0;u--)if(r[u]===t[u])a[u]=1;else if(n.shape[u]!==1)throw new Error(`broadcastTo(): [${s}] cannot be broadcast to [${t}].`);if(a.map((u,c)=>u>1?c:-1).filter(u=>u>=0).length===0)return Fn(n);let i={x:n},l={reps:a};return W.runKernel(va,i,l)}var Gu=V({broadcastTo_:BP});function WP(e){let n={x:D(e,"x","ceil","float32")};return W.runKernel(yo,n)}var aA=V({ceil_:WP});function VP(e,t,n){let s=D(e,"x","clipByValue");M(t<=n,()=>`Error in clip: min (${t}) must be less than or equal to max (${n}).`);let r={x:s},a={clipValueMin:t,clipValueMax:n};return W.runKernel(ba,r,a)}var fs=V({clipByValue_:VP});function UP(e){return Ct(e,0)}var oA=V({concat1d_:UP});function GP(e,t){return Ct(e,t)}var Kl=V({concat2d_:GP});function HP(e,t){return Ct(e,t)}var iA=V({concat3d_:HP});function jP(e,t){return Ct(e,t)}var lA=V({concat4d_:jP});function qP(e,t,n,s,r="NHWC",a=[1,1],o){let i=D(e,"x","conv2d","float32"),l=D(t,"filter","conv2d","float32"),u=i,c=!1;i.rank===3&&(c=!0,u=U(i,[1,i.shape[0],i.shape[1],i.shape[2]])),M(u.rank===4,()=>`Error in conv2d: input must be rank 4, but got rank ${u.rank}.`),M(l.rank===4,()=>`Error in conv2d: filter must be rank 4, but got rank ${l.rank}.`),rs("conv2d",s,o);let p=r==="NHWC"?u.shape[3]:u.shape[1];M(p===l.shape[2],()=>`Error in conv2d: depth of input (${p}) must match input depth for filter ${l.shape[2]}.`),M(Yr(n,a),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`);let d={x:u,filter:l},h={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:o},f=W.runKernel(Ao,d,h);return c?U(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var ma=V({conv2d_:qP});function XP(e,t,n,s,r="NWC",a=1,o){let i=D(e,"x","conv1d"),l=D(t,"filter","conv1d"),u=i,c=!1;i.rank===2&&(c=!0,u=U(i,[1,i.shape[0],i.shape[1]])),M(u.rank===3,()=>`Error in conv1d: input must be rank 3, but got rank ${u.rank}.`),M(l.rank===3,()=>`Error in conv1d: filter must be rank 3, but got rank ${l.rank}.`),rs("conv1d",s,o),M(u.shape[2]===l.shape[1],()=>`Error in conv1d: depth of input (${u.shape[2]}) must match input depth for filter ${l.shape[1]}.`),M(Yr(n,a),()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${n} and dilation '${a}'`),M(r==="NWC",()=>`Error in conv1d: got dataFormat of ${r} but only NWC is currently supported.`);let p=U(l,[1,l.shape[0],l.shape[1],l.shape[2]]),d=U(u,[u.shape[0],1,u.shape[1],u.shape[2]]),g=ma(d,p,[1,n],s,"NHWC",[1,a],o);return c?U(g,[g.shape[2],g.shape[3]]):U(g,[g.shape[0],g.shape[2],g.shape[3]])}var y0=V({conv1d_:XP});function KP(e,t,n,s,r,a="NHWC",o){M(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let i=e,l=t,u=!1;t.rank===3&&(u=!0,l=U(t,[1,t.shape[0],t.shape[1],t.shape[2]]),i=[1,e[0],e[1],e[2]]),M(i.length===4,()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${i.length}.`),M(l.rank===4,()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${l.rank}`),M(n.rank===4,()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${n.rank}`);let c=a==="NHWC"?i[3]:i[1],p=a==="NHWC"?l.shape[3]:l.shape[1];M(c===n.shape[2],()=>`Error in conv2dDerInput: depth of input (${c}) must match input depth for filter ${n.shape[2]}.`),M(p===n.shape[3],()=>`Error in conv2dDerInput: depth of output (${p}) must match output depth for filter ${n.shape[3]}.`),rs("conv2dDerInput",r,o);let d={dy:l,filter:n},h={strides:s,pad:r,dataFormat:a,dimRoundingMode:o,inputShape:i},f=W.runKernel(xo,d,h);return u?U(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var uA=V({conv2DBackpropInput_:KP});function ZP(e,t,n,s,r,a){let o=D(e,"x","conv2dTranspose"),i=D(t,"filter","conv2dTranspose");return uA(n,o,i,s,r,"NHWC",a)}var A0=V({conv2dTranspose_:ZP});function YP(e,t,n,s,r="NDHWC",a=[1,1,1]){let o=D(e,"x","conv3d"),i=D(t,"filter","conv3d"),l=o,u=!1;o.rank===4&&(u=!0,l=U(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),M(l.rank===5,()=>`Error in conv3d: input must be rank 5, but got rank ${l.rank}.`),M(i.rank===5,()=>`Error in conv3d: filter must be rank 5, but got rank ${i.rank}.`),M(l.shape[4]===i.shape[3],()=>`Error in conv3d: depth of input (${l.shape[4]}) must match input depth for filter ${i.shape[3]}.`),M(Yr(n,a),()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`),M(r==="NDHWC",()=>`Error in conv3d: got dataFormat of ${r} but only NDHWC is currently supported.`);let c={x:l,filter:i},p={strides:n,pad:s,dataFormat:r,dilations:a},d=W.runKernel(Wp,c,p);return u?U(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var cA=V({conv3d_:YP});function JP(e,t,n,s,r){M(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let a=e,o=t,i=!1;t.rank===4&&(i=!0,o=U(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]]),a=[1,e[0],e[1],e[2],e[3]]);let l=a[4],u=o.shape[4];M(a.length===5,()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${a.length}.`),M(o.rank===5,()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${o.rank}`),M(n.rank===5,()=>`Error in conv3dDerInput: filter must be rank 5, but got rank ${n.rank}`),M(l===n.shape[3],()=>`Error in conv3dDerInput: depth of input (${l}) must match input depth for filter ${n.shape[3]}.`),M(u===n.shape[4],()=>`Error in conv3dDerInput: depth of output (${u}) must match output depth for filter ${n.shape[4]}.`);let c={dy:o,filter:n},p={pad:r,strides:s,inputShape:a},d=W.runKernel(Zm,c,p);return i?U(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var aw=V({conv3DBackpropInput_:JP});function QP(e,t,n,s,r){let a=D(e,"x","conv3dTranspose"),o=D(t,"filter","conv3dTranspose");return aw(n,a,o,s,r)}var dA=V({conv3dTranspose_:QP});function eF(e){let n={x:D(e,"x","cos","float32")};return W.runKernel(bo,n)}var ch=V({cos_:eF});function tF(e){let n={x:D(e,"x","cosh","float32")};return W.runKernel(vo,n)}var x0=V({cosh_:tF});function nF(e,t=0,n=!1,s=!1){let a={x:D(e,"x","cumprod")},o={axis:t,exclusive:n,reverse:s};return W.runKernel(cl,a,o)}var Tp=V({cumprod_:nF});function sF(e,t=0,n=!1,s=!1){let a={x:D(e,"x","cumsum")},o={axis:t,exclusive:n,reverse:s};return W.runKernel(wo,a,o)}var b0=V({cumsum_:sF});function rF(e,t,n,s=!1){let r=D(e,"x","denseBincount"),a=D(t,"weights","denseBincount");M(r.dtype==="int32",()=>`Error in denseBincount: input dtype must be int32, but got ${r.dtype}`),M(r.rank<=2,()=>`Error in denseBincount: input must be at most rank 2, but got rank ${r.rank}.`),M(n>=0,()=>`size must be non-negative, but got ${n}.`),M(a.size===r.size||a.size===0,()=>`Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${r.shape}, weights shape: ${a.shape}.`);let o={x:r,weights:a},i={size:n,binaryOutput:s};return W.runKernel(Ym,o,i)}var ow=V({denseBincount_:rF});function aF(e,t,n="NHWC"){let s=D(e,"x","depthToSpace","float32"),r=n==="NHWC"?s.shape[1]:s.shape[2],a=n==="NHWC"?s.shape[2]:s.shape[3],o=n==="NHWC"?s.shape[3]:s.shape[1];M(t>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${t}`),M(r*t>=0,()=>`Negative dimension size caused by overflow when multiplying
+Expected: ${a}.`)}}function Z$(e,t){e().then(()=>t.fail(),()=>t())}function Y$(e,t){let n=typeof t=="string"||typeof t=="number"||typeof t=="boolean"?[t]:t;return Ua(e)||Ua(e[0])||Ua(t)||Ua(t[0])?E3(e,n,(s,r)=>s==r):E3(e,t,(s,r)=>Uy(s,r,0))}function J$(e,t,n){if(n==null&&(n=Vy()),!Uy(e,t,n))throw new Error(`Numbers differ: actual === ${e}, expected === ${t}`)}function Uy(e,t,n){return!isFinite(e)&&!isFinite(t)?!0:!(isNaN(e)||isNaN(t)||Math.abs(e-t)>n)}function Q$(e,t,n){for(let s=0;s<e.length;s++)if(e[s]<t||e[s]>n)throw new Error(`Value out of range:${e[s]} low: ${t}, high: ${n}`)}function eP(e,t){let n=new Float32Array(e),s=new Float32Array(t);if(n.length!==s.length)throw new Error(`Expected ArrayBuffer to be of length ${s.length}, but it was ${n.length}`);for(let r=0;r<s.length;r++)if(n[r]!==s[r])throw new Error(`Expected ArrayBuffer value at ${r} to be ${s[r]} but got ${n[r]} instead`)}function Q6(e){for(let t=0;t<e.length;t++){let n=e[t];Array.isArray(n)?Q6(n):e[t]=th(n)}return e}var Gy="3.19.0";function tP(e,t){let n=D(e,"a","add"),s=D(t,"b","add");[n,s]=Gt(n,s);let r={a:n,b:s};return W.runKernel(Aa,r)}var ce=V({add_:tP});function nP(e,t){let n=D(e,"a","floorDiv"),s=D(t,"b","floorDiv");[n,s]=Gt(n,s);let r={a:n,b:s};return W.runKernel(To,r)}var Lc=V({floorDiv_:nP});function sP(e,t){let n=D(e,"a","div"),s=D(t,"b","div");if([n,s]=Gt(n,s),n.dtype==="int32"&&s.dtype==="int32")return Lc(n,s);let r={a:n,b:s},a={};return W.runKernel(ko,r,a)}var pe=V({div_:sP});function rP(e,t){let n=D(e,"a","mul"),s=D(t,"b","mul");[n,s]=Gt(n,s);let r={a:n,b:s};return W.runKernel(Bo,r)}var L=V({mul_:rP});function aP(e){let t=D(e,"x","abs");if(t.dtype==="complex64"){let n={x:t};return W.runKernel(Lp,n)}else{let n={x:t};return W.runKernel(ol,n)}}var tn=V({abs_:aP});function oP(e){let n={x:D(e,"x","acos")};return W.runKernel(dc,n)}var Hy=V({acos_:oP});function iP(e){let n={x:D(e,"x","acosh")};return W.runKernel(pc,n)}var jy=V({acosh_:iP});function lP(e){M(Array.isArray(e),()=>"The argument passed to tf.addN() must be a list of tensors"),M(e.length>=1,()=>`Must pass at least one tensor to tf.addN(), but got ${e.length}`);let t=e.map((r,a)=>D(r,`tensors${a}`,"addN")),n=t[0];t.forEach(r=>{if(r.dtype!==n.dtype)throw new Error("All tensors passed to tf.addN() must have the same dtype")}),t.forEach(r=>{if(!uo(r.shape,n.shape))throw new Error("All tensors passed to tf.addN() must have the same shape")});let s=t;return W.runKernel(co,s)}var f0=V({addN_:lP});function uP(e,t=null,n=!1){let r={x:D(e,"x","all","bool")},a={axis:t,keepDims:n};return W.runKernel(hc,r,a)}var m0=V({all_:uP});function cP(e,t=null,n=!1){let r={x:D(e,"x","any","bool")},a={axis:t,keepDims:n};return W.runKernel(fc,r,a)}var Sp=V({any_:cP});function dP(e,t=0){let s={x:D(e,"x","argMax")},r={axis:t};return W.runKernel(po,s,r)}var Es=V({argMax_:dP});function pP(e,t=0){let s={x:D(e,"x","argMin")},r={axis:t};return W.runKernel(mc,s,r)}var qy=V({argMin_:pP});function hP(e){let n={x:D(e,"x","asin")};return W.runKernel(gc,n)}var Xy=V({asin_:hP});function fP(e){let n={x:D(e,"x","asinh")};return W.runKernel(yc,n)}var Ky=V({asinh_:fP});function mP(e){let n={x:D(e,"x","atan")};return W.runKernel(Ac,n)}var Zy=V({atan_:mP});function gP(e,t){let n=D(e,"a","atan2"),s=D(t,"b","atan2");[n,s]=Gt(n,s);let r={a:n,b:s};return W.runKernel(bc,r)}var Yy=V({atan2_:gP});function yP(e){let n={x:D(e,"x","atanh")};return W.runKernel(xc,n)}var Jy=V({atanh_:yP});function AP(e,t,n,s,r="NHWC",a){let o=e[3],i=[...t,o],l=nw(r);return oh(e,i,n,a,s,null,null,l)}function ew(e,t,n,s,r,a,o="channelsLast"){let[i,l]=ym(t),u;if(o==="channelsLast")u=[i,l,e[3],e[3]];else if(o==="channelsFirst")u=[i,l,e[1],e[1]];else throw new Error(`Unknown dataFormat ${o}`);return oh(e,u,n,s,r,a,!1,o)}function xP(e,t,n,s,r,a,o="NDHWC"){let[i,l,u]=R3(t),c,p;if(o==="NDHWC")p="channelsLast",c=[i,l,u,e[4],e[4]];else if(o==="NCDHW")p="channelsFirst",c=[i,l,u,e[1],e[1]];else throw new Error(`Unknown dataFormat ${o}`);return tw(e,c,n,s,r,!1,p,a)}function oh(e,t,n,s,r,a,o=!1,i="channelsLast"){let[l,u,c,p]=[-1,-1,-1,-1];if(i==="channelsLast")[l,u,c,p]=e;else if(i==="channelsFirst")[l,p,u,c]=e;else throw new Error(`Unknown dataFormat ${i}`);let[d,h,,f]=t,[m,g]=ym(n),[y,x]=ym(s),A=Vu(d,y),b=Vu(h,x),{padInfo:w,outHeight:k,outWidth:S}=wP(r,u,c,m,g,A,b,a,i),E=o?f*p:f,R;return i==="channelsFirst"?R=[l,E,k,S]:i==="channelsLast"&&(R=[l,k,S,E]),{batchSize:l,dataFormat:i,inHeight:u,inWidth:c,inChannels:p,outHeight:k,outWidth:S,outChannels:E,padInfo:w,strideHeight:m,strideWidth:g,filterHeight:d,filterWidth:h,effectiveFilterHeight:A,effectiveFilterWidth:b,dilationHeight:y,dilationWidth:x,inShape:e,outShape:R,filterShape:t}}function tw(e,t,n,s,r,a=!1,o="channelsLast",i){let[l,u,c,p,d]=[-1,-1,-1,-1,-1];if(o==="channelsLast")[l,u,c,p,d]=e;else if(o==="channelsFirst")[l,d,u,c,p]=e;else throw new Error(`Unknown dataFormat ${o}`);let[h,f,m,,g]=t,[y,x,A]=R3(n),[b,w,k]=R3(s),S=Vu(h,b),E=Vu(f,w),R=Vu(m,k),{padInfo:P,outDepth:_,outHeight:$,outWidth:T}=kP(r,u,c,p,y,x,A,S,E,R,i),F=a?g*d:g,G;return o==="channelsFirst"?G=[l,F,_,$,T]:o==="channelsLast"&&(G=[l,_,$,T,F]),{batchSize:l,dataFormat:o,inDepth:u,inHeight:c,inWidth:p,inChannels:d,outDepth:_,outHeight:$,outWidth:T,outChannels:F,padInfo:P,strideDepth:y,strideHeight:x,strideWidth:A,filterDepth:h,filterHeight:f,filterWidth:m,effectiveFilterDepth:S,effectiveFilterHeight:E,effectiveFilterWidth:R,dilationDepth:b,dilationHeight:w,dilationWidth:k,inShape:e,outShape:G,filterShape:t}}function bP(e,t,n,s,r){s==null&&(s=Qy(e,t,n));let a=e[0],o=e[1],i=Ui((a-t+2*s)/n+1,r),l=Ui((o-t+2*s)/n+1,r);return[i,l]}function vP(e,t,n,s,r,a){r==null&&(r=Qy(e,t,s));let o=e[0],i=e[1],l=e[2],u=Ui((o-t+2*r)/s+1,a),c=Ui((i-t+2*r)/s+1,a),p=Ui((l-t+2*r)/s+1,a);return[u,c,p,n]}function Qy(e,t,n,s=1){let r=Vu(t,s);return Math.floor((e[0]*(n-1)-n+r)/2)}function ym(e){return typeof e=="number"?[e,e,e]:e.length===2?[e[0],e[1],1]:e}function R3(e){return typeof e=="number"?[e,e,e]:e}function Vu(e,t){return t<=1?e:e+(e-1)*(t-1)}function wP(e,t,n,s,r,a,o,i,l){let u,c,p;if(typeof e=="number"){u={top:e,bottom:e,left:e,right:e,type:e===0?"VALID":"NUMBER"};let h=bP([t,n],a,s,e,i);c=h[0],p=h[1]}else if(e==="same"){c=Math.ceil(t/s),p=Math.ceil(n/r);let d=Math.max(0,(c-1)*s+a-t),h=Math.max(0,(p-1)*r+o-n),f=Math.floor(d/2),m=d-f,g=Math.floor(h/2),y=h-g;u={top:f,bottom:m,left:g,right:y,type:"SAME"}}else if(e==="valid")u={top:0,bottom:0,left:0,right:0,type:"VALID"},c=Math.ceil((t-a+1)/s),p=Math.ceil((n-o+1)/r);else if(typeof e=="object"){let d=l==="channelsLast"?e[1][0]:e[2][0],h=l==="channelsLast"?e[1][1]:e[2][1],f=l==="channelsLast"?e[2][0]:e[3][0],m=l==="channelsLast"?e[2][1]:e[3][1];u={top:d,bottom:h,left:f,right:m,type:d===0&&h===0&&f===0&&m===0?"VALID":"EXPLICIT"},c=Ui((t-a+d+h)/s+1,i),p=Ui((n-o+f+m)/r+1,i)}else throw Error(`Unknown padding parameter: ${e}`);return{padInfo:u,outHeight:c,outWidth:p}}function kP(e,t,n,s,r,a,o,i,l,u,c){let p,d,h,f;if(typeof e=="number"){p={top:e,bottom:e,left:e,right:e,front:e,back:e,type:e===0?"VALID":"NUMBER"};let g=vP([t,n,s,1],i,1,r,e,c);d=g[0],h=g[1],f=g[2]}else if(e==="same"){d=Math.ceil(t/r),h=Math.ceil(n/a),f=Math.ceil(s/o);let m=(d-1)*r+i-t,g=(h-1)*a+l-n,y=(f-1)*o+u-s,x=Math.floor(m/2),A=m-x,b=Math.floor(g/2),w=g-b,k=Math.floor(y/2),S=y-k;p={top:b,bottom:w,left:k,right:S,front:x,back:A,type:"SAME"}}else if(e==="valid")p={top:0,bottom:0,left:0,right:0,front:0,back:0,type:"VALID"},d=Math.ceil((t-i+1)/r),h=Math.ceil((n-l+1)/a),f=Math.ceil((s-u+1)/o);else throw Error(`Unknown padding parameter: ${e}`);return{padInfo:p,outDepth:d,outHeight:h,outWidth:f}}function Ui(e,t){if(!t)return Math.trunc(e);switch(t){case"round":return Math.round(e);case"ceil":return Math.ceil(e);case"floor":return Math.floor(e);default:throw new Error(`Unknown roundingMode ${t}`)}}function eo(e){let[t,n,s]=ym(e);return t===1&&n===1&&s===1}function Zr(e,t){return eo(e)||eo(t)}function nw(e){if(e==="NHWC")return"channelsLast";if(e==="NCHW")return"channelsFirst";throw new Error(`Unknown dataFormat ${e}`)}function rs(e,t,n){if(n!=null){if(typeof t=="string")throw Error(`Error in ${e}: pad must be an integer when using dimRoundingMode ${n} but got pad ${t}.`);if(typeof t=="number")M(ju(t),()=>`Error in ${e}: pad must be an integer when using dimRoundingMode ${n} but got pad ${t}.`);else if(typeof t=="object")t.forEach(s=>{s.forEach(r=>{M(ju(r),()=>`Error in ${e}: pad must be an integer when using dimRoundingMode ${n} but got pad ${r}.`)})});else throw Error(`Error in ${e}: Unknown padding parameter: ${t}`)}}function IP(e,t){let s={x:D(e,"x","reshape","string_or_numeric")},r={shape:t};return W.runKernel(Rl,s,r)}var U=V({reshape_:IP});function SP(e,t,n,s,r){let a=D(e,"x","avgPool","float32"),o=1;M(Zr(n,o),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${n} and dilations '${o}'`);let i=a,l=!1;a.rank===3&&(l=!0,i=U(a,[1,a.shape[0],a.shape[1],a.shape[2]])),M(i.rank===4,()=>`Error in avgPool: x must be rank 4 but got rank ${i.rank}.`),rs("avgPool",s,r);let u={x:i},c={filterSize:t,strides:n,pad:s,dimRoundingMode:r},p=W.runKernel(ho,u,c);return p=ge(p,a.dtype),l?U(p,[p.shape[1],p.shape[2],p.shape[3]]):p}var ih=V({avgPool_:SP});function CP(e,t,n,s,r,a="NDHWC"){let o=D(e,"x","avgPool3d","float32"),i=o,l=!1;o.rank===4&&(l=!0,i=U(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),M(i.rank===5,()=>`Error in avgPool3d: x must be rank 5 but got rank ${i.rank}.`),M(a==="NDHWC",()=>`Error in avgPool3d: Only NDHWC is currently supported, but got dataFormat of ${a}`),rs("avgPool3d",s,r);let u={x:i},c={filterSize:t,strides:n,pad:s,dimRoundingMode:r,dataFormat:a},p=W.runKernel(Mp,u,c);return p=ge(p,i.dtype),l?U(p,[p.shape[1],p.shape[2],p.shape[3],p.shape[4]]):p}var eA=V({avgPool3d_:CP});function TP(e,t=0){M(e.length>=1,()=>"Pass at least one tensor to concat");let n=Ip(e,"tensors","concat","string_or_numeric");if(n[0].dtype==="complex64"&&n.forEach(a=>{if(a.dtype!=="complex64")throw new Error(`Cannot concatenate complex64 tensors with a tensor
+          with dtype ${a.dtype}. `)}),n.length===1)return Fn(n[0]);let s=n,r={axis:t};return W.runKernel(ll,s,r)}var Ct=V({concat_:TP});function NP(e){let n={x:D(e,"x","sigmoid","float32")};return W.runKernel(Yo,n)}var Cn=V({sigmoid_:NP});function EP(e,t,n){let s=D(e,"x","slice","string_or_numeric");if(s.rank===0)throw new Error("Slicing scalar is not possible");let r={x:s},a={begin:t,size:n};return W.runKernel(Fl,r,a)}var Oe=V({slice_:EP});function RP(e){let n={x:D(e,"x","tanh","float32")};return W.runKernel(si,n)}var Zi=V({tanh_:RP});function _P(e,t,n,s,r,a){let o=D(e,"forgetBias","basicLSTMCell"),i=D(t,"lstmKernel","basicLSTMCell"),l=D(n,"lstmBias","basicLSTMCell"),u=D(s,"data","basicLSTMCell"),c=D(r,"c","basicLSTMCell"),p=D(a,"h","basicLSTMCell"),d=Ct([u,p],1),h=Qe(d,i),f=ce(h,l),m=f.shape[0],g=f.shape[1]/4,y=[m,g],x=Oe(f,[0,0],y),A=Oe(f,[0,g],y),b=Oe(f,[0,g*2],y),w=Oe(f,[0,g*3],y),k=ce(L(Cn(x),Zi(A)),L(c,Cn(ce(o,b)))),S=L(Zi(k),Cn(w));return[k,S]}var sw=V({basicLSTMCell_:_P});function DP(e,t,n){let s=D(e,"x","batchToSpaceND"),r=t.reduce((i,l)=>i*l);M(s.rank>=1+t.length,()=>`input rank is ${s.rank} but should be > than blockShape.length ${t.length}`),M(n.length===t.length,()=>`crops.length is ${n.length} but should be equal to blockShape.length  ${t.length}`),M(s.shape[0]%r===0,()=>`input tensor batch is ${s.shape[0]} but is not divisible by the product of the elements of blockShape ${t.join(" * ")} === ${r}`);let a={x:s},o={blockShape:t,crops:n};return W.runKernel(il,a,o)}var lh=V({batchToSpaceND_:DP});function $P(e){let t;return e.rank===0||e.rank===1?t=U(e,[1,1,1,e.size]):e.rank===2?t=U(e,[1,1,e.shape[0],e.shape[1]]):e.rank===3?t=U(e,[1,e.shape[0],e.shape[1],e.shape[2]]):t=e,t}function PP(e,t,n,s,r,a){a==null&&(a=.001);let o=D(e,"x","batchNorm"),i=D(t,"mean","batchNorm"),l=D(n,"variance","batchNorm"),u;r!=null&&(u=D(r,"scale","batchNorm"));let c;s!=null&&(c=D(s,"offset","batchNorm")),M(i.rank===l.rank,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),M(c==null||i.rank===c.rank,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),M(u==null||i.rank===u.rank,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let d={x:$P(o),scale:u,offset:c,mean:i,variance:l},h={varianceEpsilon:a},f=W.runKernel(No,d,h);return U(f,o.shape)}var Bc=V({batchNorm_:PP});function FP(e,t,n,s,r,a){let o=D(e,"x","batchNorm"),i=D(t,"mean","batchNorm"),l=D(n,"variance","batchNorm"),u;r!=null&&(u=D(r,"scale","batchNorm"));let c;return s!=null&&(c=D(s,"offset","batchNorm")),M(o.rank===2,()=>`Error in batchNorm2D: x must be rank 2 but got rank ${o.rank}.`),M(i.rank===2||i.rank===1,()=>`Error in batchNorm2D: mean must be rank 2 or rank 1 but got rank ${i.rank}.`),M(l.rank===2||l.rank===1,()=>`Error in batchNorm2D: variance must be rank 2 or rank 1 but got rank ${l.rank}.`),u!=null&&M(u.rank===2||u.rank===1,()=>`Error in batchNorm2D: scale must be rank 2 or rank 1 but got rank ${u.rank}.`),c!=null&&M(c.rank===2||c.rank===1,()=>`Error in batchNorm2D: offset must be rank 2 or rank 1 but got rank ${c.rank}.`),Bc(o,i,l,c,u,a)}var tA=V({batchNorm2d_:FP});function OP(e,t,n,s,r,a){let o=D(e,"x","batchNorm"),i=D(t,"mean","batchNorm"),l=D(n,"variance","batchNorm"),u;r!=null&&(u=D(r,"scale","batchNorm"));let c;return s!=null&&(c=D(s,"offset","batchNorm")),M(o.rank===3,()=>`Error in batchNorm3D: x must be rank 3 but got rank ${o.rank}.`),M(i.rank===3||i.rank===1,()=>`Error in batchNorm3D: mean must be rank 3 or rank 1 but got rank ${i.rank}.`),M(l.rank===3||l.rank===1,()=>`Error in batchNorm3D: variance must be rank 3 or rank 1 but got rank ${l.rank}.`),u!=null&&M(u.rank===3||u.rank===1,()=>`Error in batchNorm3D: scale must be rank 3 or rank 1 but got rank ${u.rank}.`),c!=null&&M(c.rank===3||c.rank===1,()=>`Error in batchNorm3D: offset must be rank 3 or rank 1 but got rank ${c.rank}.`),Bc(o,i,l,c,u,a)}var nA=V({batchNorm3d_:OP});function MP(e,t,n,s,r,a){let o=D(e,"x","batchNorm"),i=D(t,"mean","batchNorm"),l=D(n,"variance","batchNorm"),u;r!=null&&(u=D(r,"scale","batchNorm"));let c;return s!=null&&(c=D(s,"offset","batchNorm")),M(o.rank===4,()=>`Error in batchNorm4D: x must be rank 4 but got rank ${o.rank}.`),M(i.rank===4||i.rank===1,()=>`Error in batchNorm4D: mean must be rank 4 or rank 1 but got rank ${i.rank}.`),M(l.rank===4||l.rank===1,()=>`Error in batchNorm4D: variance must be rank 4 or rank 1 but got rank ${l.rank}.`),u!=null&&M(u.rank===4||u.rank===1,()=>`Error in batchNorm4D: scale must be rank 4 or rank 1 but got rank ${u.rank}.`),c!=null&&M(c.rank===4||c.rank===1,()=>`Error in batchNorm4D: offset must be rank 4 or rank 1 but got rank ${c.rank}.`),Bc(o,i,l,c,u,a)}var sA=V({batchNorm4d_:MP});function zP(e,t,n){let s=D(e,"x","bincount"),r=D(t,"weights","bincount");M(s.dtype==="int32",()=>`Error in bincount: input dtype must be int32, but got ${s.dtype}`),M(n>=0,()=>`size must be non-negative, but got ${n}.`),M(r.size===s.size||r.size===0,()=>`Error in bincount: weights must have the same size as input or0-length, but got input shape: ${s.shape}, weights shape: ${r.shape}.`);let a={x:s,weights:r},o={size:n};return W.runKernel(Hm,a,o)}var rA=V({bincount_:zP});function LP(e,t){let n=D(e,"s0","broadcastArgs","int32"),s=D(t,"s1","broadcastArgs","int32");if(n.rank!==1)throw new Error(`broadcastArgs(): first input must be a vector (rank=1). Has rank ${n.rank}`);if(s.rank!==1)throw new Error(`broadcastArgs(): second input must be a vector (rank=1). Has rank ${s.rank}`);let r={s0:n,s1:s};return W.runKernel(jm,r)}var rw=V({broadcastArgs_:LP});function BP(e,t){let n=D(e,"broadcastTo","x"),s=n.shape;if(t.some(u=>!(u>0)||u%1!==0))throw new Error(`broadcastTo(): Invalid broadcast shape [${t}].`);if(t.length<n.rank)throw new Error(`broadcastTo(): shape.length=${t.length} < input.rank=${n.rank}.`);if(t.length>n.rank){let u=n.shape.slice();for(;u.length<t.length;)u.unshift(1);n=U(n,u)}let r=n.shape,a=Array.from(t);for(let u=t.length-1;u>=0;u--)if(r[u]===t[u])a[u]=1;else if(n.shape[u]!==1)throw new Error(`broadcastTo(): [${s}] cannot be broadcast to [${t}].`);if(a.map((u,c)=>u>1?c:-1).filter(u=>u>=0).length===0)return Fn(n);let i={x:n},l={reps:a};return W.runKernel(ba,i,l)}var Uu=V({broadcastTo_:BP});function WP(e){let n={x:D(e,"x","ceil","float32")};return W.runKernel(go,n)}var aA=V({ceil_:WP});function VP(e,t,n){let s=D(e,"x","clipByValue");M(t<=n,()=>`Error in clip: min (${t}) must be less than or equal to max (${n}).`);let r={x:s},a={clipValueMin:t,clipValueMax:n};return W.runKernel(xa,r,a)}var fs=V({clipByValue_:VP});function UP(e){return Ct(e,0)}var oA=V({concat1d_:UP});function GP(e,t){return Ct(e,t)}var Xl=V({concat2d_:GP});function HP(e,t){return Ct(e,t)}var iA=V({concat3d_:HP});function jP(e,t){return Ct(e,t)}var lA=V({concat4d_:jP});function qP(e,t,n,s,r="NHWC",a=[1,1],o){let i=D(e,"x","conv2d","float32"),l=D(t,"filter","conv2d","float32"),u=i,c=!1;i.rank===3&&(c=!0,u=U(i,[1,i.shape[0],i.shape[1],i.shape[2]])),M(u.rank===4,()=>`Error in conv2d: input must be rank 4, but got rank ${u.rank}.`),M(l.rank===4,()=>`Error in conv2d: filter must be rank 4, but got rank ${l.rank}.`),rs("conv2d",s,o);let p=r==="NHWC"?u.shape[3]:u.shape[1];M(p===l.shape[2],()=>`Error in conv2d: depth of input (${p}) must match input depth for filter ${l.shape[2]}.`),M(Zr(n,a),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`);let d={x:u,filter:l},h={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:o},f=W.runKernel(yo,d,h);return c?U(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var fa=V({conv2d_:qP});function XP(e,t,n,s,r="NWC",a=1,o){let i=D(e,"x","conv1d"),l=D(t,"filter","conv1d"),u=i,c=!1;i.rank===2&&(c=!0,u=U(i,[1,i.shape[0],i.shape[1]])),M(u.rank===3,()=>`Error in conv1d: input must be rank 3, but got rank ${u.rank}.`),M(l.rank===3,()=>`Error in conv1d: filter must be rank 3, but got rank ${l.rank}.`),rs("conv1d",s,o),M(u.shape[2]===l.shape[1],()=>`Error in conv1d: depth of input (${u.shape[2]}) must match input depth for filter ${l.shape[1]}.`),M(Zr(n,a),()=>`Error in conv1D: Either stride or dilation must be 1. Got stride ${n} and dilation '${a}'`),M(r==="NWC",()=>`Error in conv1d: got dataFormat of ${r} but only NWC is currently supported.`);let p=U(l,[1,l.shape[0],l.shape[1],l.shape[2]]),d=U(u,[u.shape[0],1,u.shape[1],u.shape[2]]),g=fa(d,p,[1,n],s,"NHWC",[1,a],o);return c?U(g,[g.shape[2],g.shape[3]]):U(g,[g.shape[0],g.shape[2],g.shape[3]])}var g0=V({conv1d_:XP});function KP(e,t,n,s,r,a="NHWC",o){M(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let i=e,l=t,u=!1;t.rank===3&&(u=!0,l=U(t,[1,t.shape[0],t.shape[1],t.shape[2]]),i=[1,e[0],e[1],e[2]]),M(i.length===4,()=>`Error in conv2dDerInput: inShape must be length 4, but got length ${i.length}.`),M(l.rank===4,()=>`Error in conv2dDerInput: dy must be rank 4, but got rank ${l.rank}`),M(n.rank===4,()=>`Error in conv2dDerInput: filter must be rank 4, but got rank ${n.rank}`);let c=a==="NHWC"?i[3]:i[1],p=a==="NHWC"?l.shape[3]:l.shape[1];M(c===n.shape[2],()=>`Error in conv2dDerInput: depth of input (${c}) must match input depth for filter ${n.shape[2]}.`),M(p===n.shape[3],()=>`Error in conv2dDerInput: depth of output (${p}) must match output depth for filter ${n.shape[3]}.`),rs("conv2dDerInput",r,o);let d={dy:l,filter:n},h={strides:s,pad:r,dataFormat:a,dimRoundingMode:o,inputShape:i},f=W.runKernel(Ao,d,h);return u?U(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var uA=V({conv2DBackpropInput_:KP});function ZP(e,t,n,s,r,a){let o=D(e,"x","conv2dTranspose"),i=D(t,"filter","conv2dTranspose");return uA(n,o,i,s,r,"NHWC",a)}var y0=V({conv2dTranspose_:ZP});function YP(e,t,n,s,r="NDHWC",a=[1,1,1]){let o=D(e,"x","conv3d"),i=D(t,"filter","conv3d"),l=o,u=!1;o.rank===4&&(u=!0,l=U(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),M(l.rank===5,()=>`Error in conv3d: input must be rank 5, but got rank ${l.rank}.`),M(i.rank===5,()=>`Error in conv3d: filter must be rank 5, but got rank ${i.rank}.`),M(l.shape[4]===i.shape[3],()=>`Error in conv3d: depth of input (${l.shape[4]}) must match input depth for filter ${i.shape[3]}.`),M(Zr(n,a),()=>`Error in conv3D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`),M(r==="NDHWC",()=>`Error in conv3d: got dataFormat of ${r} but only NDHWC is currently supported.`);let c={x:l,filter:i},p={strides:n,pad:s,dataFormat:r,dilations:a},d=W.runKernel(Bp,c,p);return u?U(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var cA=V({conv3d_:YP});function JP(e,t,n,s,r){M(e.length===t.rank,()=>`Length of inShape (${e.length}) and rank of dy (${t.rank}) must match`);let a=e,o=t,i=!1;t.rank===4&&(i=!0,o=U(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]]),a=[1,e[0],e[1],e[2],e[3]]);let l=a[4],u=o.shape[4];M(a.length===5,()=>`Error in conv3dDerInput: inShape must be length 5, but got length ${a.length}.`),M(o.rank===5,()=>`Error in conv3dDerInput: dy must be rank 5, but got rank ${o.rank}`),M(n.rank===5,()=>`Error in conv3dDerInput: filter must be rank 5, but got rank ${n.rank}`),M(l===n.shape[3],()=>`Error in conv3dDerInput: depth of input (${l}) must match input depth for filter ${n.shape[3]}.`),M(u===n.shape[4],()=>`Error in conv3dDerInput: depth of output (${u}) must match output depth for filter ${n.shape[4]}.`);let c={dy:o,filter:n},p={pad:r,strides:s,inputShape:a},d=W.runKernel(Km,c,p);return i?U(d,[d.shape[1],d.shape[2],d.shape[3],d.shape[4]]):d}var aw=V({conv3DBackpropInput_:JP});function QP(e,t,n,s,r){let a=D(e,"x","conv3dTranspose"),o=D(t,"filter","conv3dTranspose");return aw(n,a,o,s,r)}var dA=V({conv3dTranspose_:QP});function eF(e){let n={x:D(e,"x","cos","float32")};return W.runKernel(xo,n)}var uh=V({cos_:eF});function tF(e){let n={x:D(e,"x","cosh","float32")};return W.runKernel(bo,n)}var A0=V({cosh_:tF});function nF(e,t=0,n=!1,s=!1){let a={x:D(e,"x","cumprod")},o={axis:t,exclusive:n,reverse:s};return W.runKernel(ul,a,o)}var Cp=V({cumprod_:nF});function sF(e,t=0,n=!1,s=!1){let a={x:D(e,"x","cumsum")},o={axis:t,exclusive:n,reverse:s};return W.runKernel(vo,a,o)}var x0=V({cumsum_:sF});function rF(e,t,n,s=!1){let r=D(e,"x","denseBincount"),a=D(t,"weights","denseBincount");M(r.dtype==="int32",()=>`Error in denseBincount: input dtype must be int32, but got ${r.dtype}`),M(r.rank<=2,()=>`Error in denseBincount: input must be at most rank 2, but got rank ${r.rank}.`),M(n>=0,()=>`size must be non-negative, but got ${n}.`),M(a.size===r.size||a.size===0,()=>`Error in denseBincount: weights must have the same shape as x or 0-length, but got x shape: ${r.shape}, weights shape: ${a.shape}.`);let o={x:r,weights:a},i={size:n,binaryOutput:s};return W.runKernel(Zm,o,i)}var ow=V({denseBincount_:rF});function aF(e,t,n="NHWC"){let s=D(e,"x","depthToSpace","float32"),r=n==="NHWC"?s.shape[1]:s.shape[2],a=n==="NHWC"?s.shape[2]:s.shape[3],o=n==="NHWC"?s.shape[3]:s.shape[1];M(t>1,()=>`blockSize should be > 1 for depthToSpace, but was: ${t}`),M(r*t>=0,()=>`Negative dimension size caused by overflow when multiplying
     ${r} and ${t}  for depthToSpace with input shape
     ${s.shape}`),M(a*t>=0,()=>`Negative dimension size caused by overflow when multiplying
     ${a} and ${t} for depthToSpace with input shape
-        ${s.shape}`),M(o%(t*t)===0,()=>`Dimension size must be evenly divisible by ${t*t} but is ${o} for depthToSpace with input shape ${s.shape}`);let i={x:s},l={blockSize:t,dataFormat:n};return W.runKernel(pl,i,l)}var pA=V({depthToSpace_:aF});function oF(e,t,n,s,r="NHWC",a=[1,1],o){let i=D(e,"x","depthwiseConv2d","float32"),l=D(t,"filter","depthwiseConv2d","float32"),u=i,c=!1;i.rank===3&&(c=!0,u=U(i,[1,i.shape[0],i.shape[1],i.shape[2]])),M(u.rank===4,()=>`Error in depthwiseConv2d: input must be rank 4, but got rank ${u.rank}.`),M(l.rank===4,()=>`Error in depthwiseConv2d: filter must be rank 4, but got rank ${l.rank}.`);let p=r==="NHWC"?u.shape[3]:u.shape[1];M(p===l.shape[2],()=>`Error in depthwiseConv2d: number of input channels (${p}) must match the inChannels dimension in filter ${l.shape[2]}.`),rs("depthwiseConv2d",s,o);let d={x:u,filter:l},h={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:o},f=W.runKernel(ko,d,h);return c?U(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var Vc=V({depthwiseConv2d_:oF});function iF(e){let n={x:D(e,"x","diag")};return W.runKernel(e0,n)}var iw=V({diag_:iF});function lF(e,t,n,s,r=[1,1],a="NHWC"){let o=D(e,"x","dilation2d"),i=D(t,"filter","dilation2d");M(o.rank===3||o.rank===4,()=>`Error in dilation2d: input must be rank 3 or 4, but got rank ${o.rank}.`),M(i.rank===3,()=>`Error in dilation2d: filter must be rank 3, but got rank ${i.rank}.`),M(a==="NHWC",()=>`Error in dilation2d: Only NHWC is currently supported, but got dataFormat of ${a}`);let l=o,u=!1;o.rank===3&&(l=U(o,[1,o.shape[0],o.shape[1],o.shape[2]]),u=!0);let c={x:l,filter:i},p={strides:n,pad:s,dilations:r},d=W.runKernel(Vp,c,p);return u?U(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var hA=V({dilation2d_:lF});function uF(e,t){let n=D(e,"a","equal","string_or_numeric"),s=D(t,"b","equal","string_or_numeric");[n,s]=Gt(n,s),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(hl,r)}var Rs=V({equal_:uF});function cF(e,t,n){let s=D(t,"a","where"),r=D(n,"b","where"),a=D(e,"condition","where","bool"),o=kt(kt(a.shape,s.shape),r.shape),i=Gu(a,o),l=Gu(s,o),u=Gu(r,o),c={condition:i,t:l,e:u};return W.runKernel(Fl,c)}var Mn=V({where_:cF});function dF(e){let n={x:D(e,"x","zerosLike")};return W.runKernel(Hl,n)}var it=V({zerosLike_:dF});function pF(e,t){let n=D(e,"a","div"),s=D(t,"b","div");[n,s]=Gt(n,s);let r=pe(n,s),a=it(r),o=Rs(s,a);return Mn(o,a,r)}var fA=V({divNoNan_:pF});function hF(e,t){let n=D(e,"t1","dot"),s=D(t,"t2","dot");M((n.rank===1||n.rank===2)&&(s.rank===1||s.rank===2),()=>`Error in dot: inputs must all be rank 1 or 2, but got ranks ${n.rank} and ${s.rank}.`);let r=n.rank===1?n.size:n.shape[1],a=s.rank===1?s.size:s.shape[0];if(M(r===a,()=>`Error in dot: inner dimensions of inputs must match, but got ${r} and ${a}.`),n.rank===1&&s.rank===1){let o=U(n,[1,-1]),i=U(s,[-1,1]),l=Qe(o,i);return U(l,[])}else if(n.rank===1&&s.rank===2){let o=U(n,[1,-1]),i=U(s,[s.shape[0],s.shape[1]]),l=Qe(o,i);return U(l,[l.size])}else if(n.rank===2&&s.rank===1){let o=U(s,[-1,1]),i=Qe(n,o);return U(i,[i.size])}else{let o=U(s,[s.shape[0],s.shape[1]]);return Qe(n,o)}}var mA=V({dot_:hF});function fF(e,...t){let n=t.map((r,a)=>D(r,`tensors${a}`,"einsum")),s={equation:e};return W.runKernel(Up,n,s)}var lw=V({einsum_:fF});function mF(e){let n={x:D(e,"x","elu","float32")};return W.runKernel(So,n)}var Uc=V({elu_:mF});function gF(e){let t=D(e,"x","erf");M(t.dtype==="int32"||t.dtype==="float32",()=>"Input dtype must be `int32` or `float32`."),t.dtype==="int32"&&(t=ge(t,"float32"));let n={x:t};return W.runKernel(wc,n)}var gA=V({erf_:gF});function yA(e,t){for(let n=0;n<e.length;++n)if(e[e.length-n-1]!==t-1-n)return!1;return!0}function uw(e,t,n){let s=e.length+t.length,r=[],a=0,o=0;for(let i=0;i<s;i++)n.indexOf(i)===-1?r.push(e[a++]):r.push(t[o++]);return r}function cw(e,t){let n=[],s=e.length;for(let a=0;a<s;a++)t.indexOf(a)===-1&&n.push(e[a]);let r=t.map(a=>e[a]);return[n,r]}function Ji(e,t){let n=t.map(s=>1);return uw(e,n,t)}function yF(e,t,n){M(yA(t,n),()=>`${e} supports only inner-most axes for now. Got axes ${t} and rank-${n} input.`)}function dw(e,t){if(yA(e,t))return null;let n=[];for(let s=0;s<t;++s)e.indexOf(s)===-1&&n.push(s);return e.forEach(s=>n.push(s)),n}function AA(e){return e.map((t,n)=>[n,t]).sort((t,n)=>t[1]-n[1]).map(t=>t[0])}function AF(e,t){let n=[];for(let s=t-e;s<t;++s)n.push(s);return n}function xF(e,t=null,n=!1){let r={x:D(e,"x","max")},a={reductionIndices:t,keepDims:n};return W.runKernel(Po,r,a)}var mn=V({max_:xF});function bF(e,t=null,n=!1){let r={x:D(e,"x","min")},a={axis:t,keepDims:n};return W.runKernel(zo,r,a)}var ga=V({min_:bF});function vF(e,t){let n=D(e,"base","pow"),s=D(t,"exp","pow");[n,s]=Gt(n,s);let r={a:n,b:s};return W.runKernel(Uo,r)}var ya=V({pow_:vF});function Se(e,t){if((Pn(e)&&t!=="string"||Array.isArray(e))&&t!=="complex64")throw new Error("Error creating a new Scalar: value must be a primitive (number|boolean|string)");if(t==="string"&&Pn(e)&&!(e instanceof Uint8Array))throw new Error("When making a scalar from encoded string, the value must be `Uint8Array`.");return oi(e,[],[],t)}function wF(e){let n={x:D(e,"x","sqrt","float32")};return W.runKernel(Qo,n)}var Nn=V({sqrt_:wF});function kF(e){let t=D(e,"x","square"),n={};return W.runKernel("Square",{x:t},n)}var vt=V({square_:kF});function IF(e,t=null,n=!1){let s=D(e,"x","sum");s.dtype==="bool"&&(s=ge(s,"int32"));let r={x:s},a={axis:t,keepDims:n};return W.runKernel(ei,r,a)}var ke=V({sum_:IF});function SF(e,t="euclidean",n=null,s=!1){e=D(e,"x","norm");let r=pw(e,t,n),a=r.shape;if(s){let o=ur(n,e.shape);a=Ji(r.shape,o)}return U(r,a)}function pw(e,t,n=null){if(e.rank===0)return tn(e);if(e.rank!==1&&n===null)return pw(U(e,[-1]),t,n);if(e.rank===1||typeof n=="number"||Array.isArray(n)&&n.length===1){if(t===1)return ke(tn(e),n);if(t===1/0)return mn(tn(e),n);if(t===-1/0)return ga(tn(e),n);if(t==="euclidean"||t===2)return Nn(ke(ya(tn(e),Se(2,"int32")),n));throw new Error(`Error in norm: invalid ord value: ${t}`)}if(Array.isArray(n)&&n.length===2){if(t===1)return mn(ke(tn(e),n[0]),n[1]-1);if(t===1/0)return mn(ke(tn(e),n[1]),n[0]);if(t===-1/0)return ga(ke(tn(e),n[1]),n[0]);if(t==="fro"||t==="euclidean")return Nn(ke(vt(e),n));throw new Error(`Error in norm: invalid ord value: ${t}`)}throw new Error(`Error in norm: invalid axis: ${n}`)}var Gc=V({norm_:SF});function CF(e,t=null,n=!1){return Gc(e,"euclidean",t,n)}var xA=V({euclideanNorm_:CF});function TF(e){let n={x:D(e,"x","exp")};return W.runKernel(Co,n)}var _s=V({exp_:TF});function NF(e,t=0){let n=D(e,"x","expandDims","string_or_numeric");M(t<=n.rank,()=>"Axis must be <= rank of the tensor");let s={input:n},r={dim:t};return W.runKernel(fl,s,r)}var Kt=V({expandDims_:NF});function EF(e){let n={x:D(e,"x","expm1")};return W.runKernel(ml,n)}var bA=V({expm1_:EF});function RF(e,t){let n=D(e,"x","tile","string_or_numeric");M(n.rank===t.length,()=>`Error in transpose: rank of input ${n.rank} must match length of reps ${t}.`);let s={x:n},r={reps:t};return W.runKernel(va,s,r)}var js=V({tile_:RF});function _F(e,t,n,s="float32"){t==null&&(t=e);let r=Le([e,t],s),a=e<=t?e:t;for(let i=0;i<a;++i)r.set(1,i,i);let o=U(r.toTensor(),[e,t]);if(n==null)return o;if(n.length===1)return js(Kt(o,0),[n[0],1,1]);if(n.length===2)return js(Kt(Kt(o,0),0),[n[0],n[1],1,1]);if(n.length===3)return js(Kt(Kt(Kt(o,0),0),0),[n[0],n[1],n[2],1,1]);throw new Error(`eye() currently supports only 1D and 2D batchShapes, but received ${n.length}D.`)}var v0=V({eye_:_F});function Hc(e,t,n){let s={shape:e,value:t,dtype:n};return W.runKernel(kc,{},s)}function DF(e){let n={x:D(e,"x","floor","float32")};return W.runKernel(To,n)}var jc=V({floor_:DF});function $F(e,t,n=0,s=0){let r=D(e,"x","gather"),a=D(t,"indices","gather","int32"),o={x:r,indices:a},i={axis:n,batchDims:s};return W.runKernel(yl,o,i)}var qc=V({gather_:$F});function PF(e,t){let n=D(e,"a","greater","string_or_numeric"),s=D(t,"b","greater","string_or_numeric");[n,s]=Gt(n,s),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(xl,r)}var ys=V({greater_:PF});function FF(e,t){let n=D(e,"a","greaterEqual","string_or_numeric"),s=D(t,"b","greaterEqual","string_or_numeric");[n,s]=Gt(n,s),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(Ro,r)}var li=V({greaterEqual_:FF});function OF(e){let n={x:D(e,"x","isFinite")};return W.runKernel(Ic,n)}var vA=V({isFinite_:OF});function MF(e){let n={x:D(e,"x","isInf")};return W.runKernel(Sc,n)}var wA=V({isInf_:MF});function zF(e){let n={x:D(e,"x","isNaN")};return W.runKernel(Cc,n)}var kA=V({isNaN_:zF});function LF(e,t=.2){let s={x:D(e,"x","leakyRelu")},r={alpha:t};return W.runKernel(Do,s,r)}var dh=V({leakyRelu_:LF});function BF(e,t){let n=D(e,"a","less","string_or_numeric"),s=D(t,"b","less","string_or_numeric");[n,s]=Gt(n,s),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(bl,r)}var w0=V({less_:BF});function WF(e,t){let n=D(e,"a","lessEqual","string_or_numeric"),s=D(t,"b","lessEqual","string_or_numeric");[n,s]=Gt(n,s),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(vl,r)}var ui=V({lessEqual_:WF});function hw(e,t,n){if(n<=0)throw new Error("The number of values should be positive.");let s={start:e,stop:t,num:n};return W.runKernel(r0,{},s)}function VF(e,t=5,n=1,s=1,r=.5){let a=D(e,"x","localResponseNormalization");M(a.rank===4||a.rank===3,()=>`Error in localResponseNormalization: x must be rank 3 or 4 but got
-               rank ${a.rank}.`),M(qu(t),()=>`Error in localResponseNormalization: depthRadius must be an integer but got depthRadius ${t}.`);let o=a,i=!1;a.rank===3&&(i=!0,o=U(a,[1,a.shape[0],a.shape[1],a.shape[2]]));let l={x:o},u={depthRadius:t,bias:n,alpha:s,beta:r},c=W.runKernel(Hp,l,u);return i?U(c,[c.shape[1],c.shape[2],c.shape[3]]):c}var IA=V({localResponseNormalization_:VF});function UF(e){let n={x:D(e,"x","log","float32")};return W.runKernel($o,n)}var Ds=V({log_:UF});function GF(e){let n={x:D(e,"x","log1p")};return W.runKernel(Tc,n)}var ph=V({log1p_:GF});function HF(e){return M(Ya(e),()=>"The f passed in grad(f) must be a function"),(t,n)=>{let s=D(t,"x","tf.grad","string_or_numeric"),r=n!=null?D(n,"dy","tf.grad"):null;return W.tidy(()=>{let{value:a,grads:o}=W.gradients(()=>e(s),[s],r);return r!=null&&ns(a.shape,r.shape,"The shape of dy passed in grad(f)(x, dy) must match the shape returned by f(x)"),k0(o),o[0]})}}function jF(e){return M(Ya(e),()=>"The f passed in grads(f) must be a function"),(t,n)=>{M(Array.isArray(t),()=>"The args passed in grads(f)(args) must be an array of `Tensor`s or `TensorLike`s");let s=Sp(t,"args","tf.grads","string_or_numeric"),r=n!=null?D(n,"dy","tf.grads"):null;return W.tidy(()=>{let{value:a,grads:o}=W.gradients(()=>e(...s),s,r);return r!=null&&ns(a.shape,r.shape,"The shape of dy passed in grads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),k0(o),o})}}function qF(e){return M(Ya(e),()=>"The f passed in valueAndGrad(f) must be a function"),(t,n)=>{M(t instanceof tt,()=>"The x passed in valueAndGrad(f)(x) must be a tensor"),M(n==null||n instanceof tt,()=>"The dy passed in valueAndGrad(f)(x, dy) must be a tensor");let{grads:s,value:r}=W.gradients(()=>e(t),[t],n);return k0(s),{grad:s[0],value:r}}}function XF(e){return M(Ya(e),()=>"The f passed in valueAndGrads(f) must be a function"),(t,n)=>{M(Array.isArray(t)&&t.every(r=>r instanceof tt),()=>"The args passed in valueAndGrads(f)(args) must be array of tensors"),M(n==null||n instanceof tt,()=>"The dy passed in valueAndGrads(f)(args, dy) must be a tensor");let s=W.gradients(()=>e(...t),t,n);return n!=null&&ns(s.value.shape,n.shape,"The shape of dy passed in valueAndGrads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),k0(s.grads),s}}function fw(e,t){M(Ya(e),()=>"The f passed in variableGrads(f) must be a function"),M(t==null||Array.isArray(t)&&t.every(u=>u instanceof kp),()=>"The varList passed in variableGrads(f, varList) must be an array of variables");let n=t!=null;if(!n){t=[];for(let u in W.registeredVariables)t.push(W.registeredVariables[u])}let s=n?t.filter(u=>!u.trainable):null,r=t.length;t=t.filter(u=>u.trainable),M(t.length>0,()=>`variableGrads() expects at least one of the input variables to be trainable, but none of the ${r} variables is trainable.`);let a=!0,{value:o,grads:i}=W.gradients(e,t,null,a);M(i.some(u=>u!=null),()=>"Cannot find a connection between any variable and the result of the loss function y=f(x). Please make sure the operations that use variables are inside the function f passed to minimize()."),M(o.rank===0,()=>`The f passed in variableGrads(f) must return a scalar, but it returned a rank-${o.rank} tensor`);let l={};return t.forEach((u,c)=>{i[c]!=null&&(l[u.name]=i[c])}),s!=null&&s.forEach(u=>l[u.name]=null),{value:o,grads:l}}function Kr(e){return W.customGrad(e)}function k0(e){if(e.filter(n=>n==null).length>0)throw new Error(`Cannot compute gradient of y=f(x) with respect to x. Make sure that
-    the f you passed encloses all operations that lead from x to y.`)}function KF(e){let n={x:D(e,"x","softplus")};return W.runKernel(Fc,n)}var Zl=V({softplus_:KF});function ZF(e){let t=D(e,"x","logSigmoid");return Kr(s=>({value:Dt(Zl(Dt(s))),gradFunc:o=>L(o,Cn(Dt(s)))}))(t)}var SA=V({logSigmoid_:ZF});function YF(e,t){let n=D(e,"a","sub"),s=D(t,"b","sub");[n,s]=Gt(n,s);let r={a:n,b:s};return W.runKernel(si,r)}var he=V({sub_:YF});function JF(e,t=-1){let n=D(e,"logits","logSoftmax");if(t===-1&&(t=n.rank-1),t!==n.rank-1)throw Error(`Log Softmax along a non-last dimension is not yet supported. Logits was rank ${n.rank} and axis was ${t}`);return Kr((r,a)=>{let i=mn(r,t,!0),l=he(r,i),u=he(ge(l,"float32"),Ds(ke(_s(l),t,!0)));return a([u]),{value:u,gradFunc:(p,d)=>{let[h]=d,f=!0,m=_s(h);return he(p,L(ke(p,t,f),m))}}})(n)}var I0=V({logSoftmax_:JF});function QF(e,t=null,n=!1){let s=D(e,"x","logSumExp"),r=ur(t,s.shape),a=mn(s,r,!0),o=he(s,a),i=_s(o),l=ke(i,r),u=Ds(l),c=ce(U(a,u.shape),u);if(n){let p=Ji(c.shape,r);return U(c,p)}return c}var S0=V({logSumExp_:QF});function eO(e,t){let n=D(e,"a","logicalAnd","bool"),s=D(t,"b","logicalAnd","bool");kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(wl,r)}var lr=V({logicalAnd_:eO});function tO(e){let n={x:D(e,"x","logicalNot","bool")};return W.runKernel(kl,n)}var hh=V({logicalNot_:tO});function nO(e,t){let n=D(e,"a","logicalOr","bool"),s=D(t,"b","logicalOr","bool");kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(Nc,r)}var C0=V({logicalOr_:nO});function sO(e,t){let n=D(e,"a","logicalXor","bool"),s=D(t,"b","logicalXor","bool");return kt(n.shape,s.shape),lr(C0(e,t),hh(lr(e,t)))}var CA=V({logicalXor_:sO}),Bf=2147483648;function rO(e,t,n="left"){let s=D(e,"sortedSequence","searchSorted"),r=D(t,"values","searchSorted"),a=s.shape[s.shape.length-1],o=r.shape[r.shape.length-1],i=U(s,[-1,a]),l=U(r,[-1,o]);if(i.rank<2)throw new Error("Sorted input argument must be at least 2-dimensional");if(i.shape[0]!==l.shape[0])throw new Error("Leading dimension of 'sortedSequence' and 'values' must match.");if(Et(l.shape)>=Bf)throw new Error(`values tensor size must less than ${Bf}`);if(i.shape[1]>=Bf)throw new Error(`trailing dim_size must less than ${Bf} for int32 output type, was ${i.shape[1]}`);let u={sortedSequence:i,values:l},c={side:n};return W.runKernel(p0,u,c)}var T0=V({searchSorted_:rO});function mw(e,t){return T0(e,t,"left")}function aO(e,t,n,s,r){let a=D(e,"x","maxPool"),o=1,i=a,l=!1;a.rank===3&&(l=!0,i=U(a,[1,a.shape[0],a.shape[1],a.shape[2]])),M(i.rank===4,()=>`Error in maxPool: input must be rank 4 but got rank ${i.rank}.`),M(Yr(n,o),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${n} and dilations '${o}'`),rs("maxPool",s,r);let u={x:i},c={filterSize:t,strides:n,pad:s,dimRoundingMode:r},p=W.runKernel(Oo,u,c);return l?U(p,[p.shape[1],p.shape[2],p.shape[3]]):p}var fh=V({maxPool_:aO});function oO(e,t=[1,1,1],n,s,r,a="NDHWC"){let o=D(e,"x","maxPool3d"),i=o,l=!1;o.rank===4&&(l=!0,i=U(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),M(i.rank===5,()=>`Error in maxPool3d: x must be rank 5 but got rank ${i.rank}.`),M(a==="NDHWC",()=>`Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of ${a}`),rs("maxPool3d",s,r);let u={x:i},c={filterSize:t,strides:n,pad:s,dimRoundingMode:r,dataFormat:a},p=W.runKernel(jp,u,c);return l?U(p,[p.shape[1],p.shape[2],p.shape[3],p.shape[4]]):p}var TA=V({maxPool3d_:oO});function iO(e,t,n,s,r=!1){let o={x:D(e,"x","maxPoolWithArgmax")},i={filterSize:t,strides:n,pad:s,includeBatchInIndex:r},l=W.runKernel(l0,o,i);return{result:l[0],indexes:l[1]}}var gw=V({maxPoolWithArgmax_:iO});function lO(e,t){let n=D(e,"a","maximum"),s=D(t,"b","maximum");[n,s]=Gt(n,s),n.dtype==="bool"&&(n=ge(n,"int32"),s=ge(s,"int32")),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(Fo,r)}var Jr=V({maximum_:lO});function uO(e,t=null,n=!1){let r={x:D(e,"x","mean")},a={axis:t,keepDims:n};return W.runKernel(Mo,r,a)}var Bt=V({mean_:uO});function Wt(e,t="float32"){if(t==="complex64"){let s=Wt(e,"float32"),r=Wt(e,"float32");return fa(s,r)}let n=Um(Et(e),t);return W.makeTensor(n,e,t)}function Ns(e,t="float32"){if(t==="complex64"){let s=Ns(e,"float32"),r=Wt(e,"float32");return fa(s,r)}let n=by(Et(e),t);return W.makeTensor(n,e,t)}function yw(e,t,{indexing:n="xy"}={}){if(n!=="xy"&&n!=="ij")throw new TypeError(`${n} is not a valid third argument to meshgrid`);if(e===void 0)return[];let s=D(e,"x","meshgrid",e instanceof tt?e.dtype:"float32");if(t===void 0)return[s];let r=D(t,"y","meshgrid",t instanceof tt?t.dtype:"float32"),a=Et(s.shape),o=Et(r.shape);return n==="xy"?(s=U(s,[1,-1]),r=U(r,[-1,1]),[Qe(Ns([o,1],s.dtype),s),Qe(r,Ns([1,a],r.dtype))]):(s=U(s,[-1,1]),r=U(r,[1,-1]),[Qe(s,Ns([1,o],s.dtype)),Qe(Ns([a,1],r.dtype),r)])}function cO(e,t){let n=D(e,"a","minimum"),s=D(t,"b","minimum");[n,s]=Gt(n,s),n.dtype==="bool"&&(n=ge(n,"int32"),s=ge(s,"int32")),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(Lo,r)}var Xc=V({minimum_:cO});function dO(e,t,n){M(n==="reflect"||n==="symmetric",()=>`Invalid mode. Mode must be either reflect or symmetric. Got ${n}.`);let s=D(e,"x","mirrorPad");if(s.rank===0)throw new Error("mirrorPad(scalar) is not defined. Pass non-scalar to mirrorPad");M(t.length===s.rank,()=>`Padding doesn't match input. Must be ${s.rank}. Got ${t.length}.`);let r=n==="reflect"?1:0;for(let i=0;i<s.rank;i++)M(t[i].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),M(t[i][0]>=0&&t[i][0]<=s.shape[i]-r&&t[i][1]>=0&&t[i][1]<=s.shape[i]-r,()=>`Padding in dimension ${i} cannot be greater than or equal to ${s.shape[i]-r} or less than 0 for input of shape ${s.shape}`);let a={paddings:t,mode:n},o={x:s};return W.runKernel(Bo,o,a)}var NA=V({mirrorPad_:dO});function pO(e,t){let n=D(e,"a","mod"),s=D(t,"b","mod");[n,s]=Gt(n,s);let r={a:n,b:s};return W.runKernel(Ec,r)}var Yl=V({mod_:pO});function hO(e,t=null,n=!1){e=D(e,"x","moments");let s=ur(t,e.shape),r=Bt(e,s,n),a=r.shape;n||(a=Ji(r.shape,s));let o=vt(he(ge(e,"float32"),U(r,a))),i=Bt(o,s,n);return{mean:r,variance:i}}var mh=V({moments_:hO});function fO(e,t,n,s){let r=D(t,"data","multiRNNCell"),a=Sp(n,"c","multiRNNCell"),o=Sp(s,"h","multiRNNCell"),i=r,l=[];for(let p=0;p<e.length;p++){let d=e[p](i,a[p],o[p]);l.push(d[0]),l.push(d[1]),i=d[1]}let u=[],c=[];for(let p=0;p<l.length;p+=2)u.push(l[p]),c.push(l[p+1]);return[u,c]}var Aw=V({multiRNNCell_:fO});function mO(e,t,n,s=!1){let r=D(e,"logits","multinomial"),a=r.size,o=r.rank;if(a<2)throw new Error(`Error in multinomial: you need at least 2 outcomes, but got ${a}.`);if(o>2)throw new Error(`Rank of probabilities must be 1 or 2, but is ${o}`);n=n||Math.random();let l={logits:o===1?U(r,[1,-1]):r},u={numSamples:t,seed:n,normalized:s},c=W.runKernel(u0,l,u);return o===1?U(c,[c.size]):c}var xw=V({multinomial_:mO});function gO(e,t){let n=D(e,"a","notEqual","string_or_numeric"),s=D(t,"b","notEqual","string_or_numeric");[n,s]=Gt(n,s),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(Sl,r)}var Qi=V({notEqual_:gO});function yO(e){let n={x:D(e,"x","onesLike")};return W.runKernel(Nl,n)}var $s=V({onesLike_:yO});function AO(e,t){let n=D(e,"v1","outerProduct"),s=D(t,"v2","outerProduct");M(n.rank===1&&s.rank===1,()=>`Error in outerProduct: inputs must be rank 1, but got ranks ${n.rank} and ${s.rank}.`);let r=U(n,[-1,1]),a=U(s,[1,-1]);return Qe(r,a)}var bw=V({outerProduct_:AO});function xO(e,t,n=0){let s=D(e,"x","pad");if(s.rank===0)throw new Error("pad(scalar) is not defined. Pass non-scalar to pad");let r={paddings:t,constantValue:n},a={x:s};return W.runKernel(Vo,a,r)}var Js=V({pad_:xO});function bO(e,t,n=0){return M(t.length===2,()=>"Invalid number of paddings. Must be length of 2."),Js(e,[t],n)}var vw=V({pad1d_:bO});function vO(e,t,n=0){return M(t.length===2&&t[0].length===2&&t[1].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),Js(e,t,n)}var ww=V({pad2d_:vO});function wO(e,t,n=0){return M(t.length===3&&t[0].length===2&&t[1].length===2&&t[2].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),Js(e,t,n)}var kw=V({pad3d_:wO});function kO(e,t,n=0){return M(t.length===4&&t[0].length===2&&t[1].length===2&&t[2].length===2&&t[3].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),Js(e,t,n)}var Iw=V({pad4d_:kO});function IO(e,t,n){let s=D(e,"x","spaceToBatchND");M(s.rank>=1+t.length,()=>`input rank ${s.rank} should be > than [blockShape] ${t.length}`),M(n.length===t.length,()=>`paddings.shape[0] ${n.length} must be equal to [blockShape] ${t.length}`),M(s.shape.reduce((o,i,l)=>l>0&&l<=t.length?o&&(i+n[l-1][0]+n[l-1][1])%t[l-1]===0:o,!0),()=>`input spatial dimensions ${s.shape.slice(1)} with paddings ${n.toString()} must be divisible by blockShapes ${t.toString()}`);let r={x:s},a={blockShape:t,paddings:n};return W.runKernel(zl,r,a)}var gh=V({spaceToBatchND_:IO});function SO(e,t,n,s,r,a,o){r==null&&(r=[1,1]),a==null&&(a=1),s===0&&(s="valid");let i=D(e,"x","maxPool"),l=i,u=!1;i.rank===3&&(u=!0,l=U(i,[1,i.shape[0],i.shape[1],i.shape[2]])),M(Yr(a,r),()=>`Error in pool: Either strides or dilations must be 1. Got strides ${a} and dilations '${r}'`);let c=ew(l.shape,t,a,r,s),p=[c.dilationHeight,c.dilationWidth],d;s==="same"?d=TO([c.filterHeight,c.filterWidth],p):d=[[0,0],[0,0]];let h=p[0]===1&&p[1]===1,[f,m]=CO([c.inHeight,c.inWidth],p,d),g=h?s:"valid",y=h?l:gh(l,p,f),A=(n==="avg"?()=>lh(y,t,a,g,o):()=>fh(y,t,a,g,o))(),b=h?A:uh(A,p,m);return u?U(b,[b.shape[1],b.shape[2],b.shape[3]]):b}function CO(e,t,n){let s=n.map(c=>c[0]),r=n.map(c=>c[1]),a=e.concat(s,r),o=t.map((c,p)=>(c-a[p]%c)%c),i=r.map((c,p)=>c+o[p]),l=t.map((c,p)=>[s[p],i[p]]),u=t.map((c,p)=>[0,o[p]]);return[l,u]}function TO(e,t){let s=e.map((o,i)=>o+(o-1)*(t[i]-1)).map(o=>o-1),r=s.map(o=>Math.floor(o/2)),a=s.map((o,i)=>o-r[i]);return s.map((o,i)=>[r[i],a[i]])}var EA=V({pool_:SO});function NO(e,t){let n=D(e,"x","prelu"),s=D(t,"alpha","prelu"),r={x:n,alpha:s};return W.runKernel(Go,r)}var yh=V({prelu_:NO});function EO(e,t=null,n=!1){let s=D(e,"x","prod");s.dtype==="bool"&&(s=ge(s,"int32"));let r={x:s},a={axis:t,keepDims:n};return W.runKernel(Ho,r,a)}var RA=V({prod_:EO});function RO(e,t,n){let s=Et(e),r=null;if(n==null||n==="float32")r=new Float32Array(s);else if(n==="int32")r=new Int32Array(s);else if(n==="bool")r=new Uint8Array(s);else throw new Error(`Unknown data type ${n}`);for(let a=0;a<s;a++)r[a]=t();return W.makeTensor(r,e,n)}var Sw=V({rand_:RO}),_A=uo(Wm()),DA=class{constructor(e,t,n,s,r){this.mean=e,this.stdDev=t,this.dtype=n,this.nextVal=NaN,this.truncated=s,this.truncated&&(this.upper=this.mean+this.stdDev*2,this.lower=this.mean-this.stdDev*2);let a=r||Math.random();this.random=_A.alea(a.toString())}nextValue(){if(!isNaN(this.nextVal)){let s=this.nextVal;return this.nextVal=NaN,s}let e,t,n=!1;for(;!n;){let s,r,a;do s=2*this.random()-1,r=2*this.random()-1,a=s*s+r*r;while(a>=1||a===0);let o=Math.sqrt(-2*Math.log(a)/a);e=this.mean+this.stdDev*s*o,t=this.mean+this.stdDev*r*o,(!this.truncated||this.isValidTruncated(e))&&(n=!0)}return(!this.truncated||this.isValidTruncated(t))&&(this.nextVal=this.convertValue(t)),this.convertValue(e)}convertValue(e){return this.dtype==null||this.dtype==="float32"?e:Math.round(e)}isValidTruncated(e){return e<=this.upper&&e>=this.lower}},_O=class{constructor(e,t,n,s){this.alpha=e,this.beta=1/t,this.dtype=n;let r=s||Math.random();this.randu=_A.alea(r.toString()),this.randn=new DA(0,1,n,!1,this.randu()),e<1?this.d=e+2/3:this.d=e-1/3,this.c=1/Math.sqrt(9*this.d)}nextValue(){let e,t,n,s,r,a;for(;;){do s=this.randn.nextValue(),a=1+this.c*s;while(a<=0);if(a*=a*a,e=s*s,t=1-.331*e*e,n=.5*e+this.d*(1-a+Math.log(a)),r=this.randu(),r<t||Math.log(r)<n)break}return a=1/this.beta*this.d*a,this.alpha<1&&(a*=Math.pow(this.randu(),1/this.alpha)),this.convertValue(a)}convertValue(e){return this.dtype==="float32"?e:Math.round(e)}},DO=class{constructor(e=0,t=1,n,s){if(this.canReturnFloat=()=>this.dtype==null||this.dtype==="float32",this.min=e,this.range=t-e,this.dtype=n,s==null&&(s=Math.random()),typeof s=="number"&&(s=s.toString()),!this.canReturnFloat()&&this.range<=1)throw new Error(`The difference between ${e} - ${t} <= 1 and dtype is not float`);this.random=_A.alea(s)}convertValue(e){return this.canReturnFloat()?e:Math.round(e)}nextValue(){return this.convertValue(this.min+this.range*this.random())}};function $O(e,t,n=1,s="float32",r){if(n==null&&(n=1),s==null&&(s="float32"),s!=="float32"&&s!=="int32")throw new Error(`Unsupported data type ${s}`);let a=new _O(t,n,s,r),o=Le(e,s);for(let i=0;i<o.values.length;i++)o.values[i]=a.nextValue();return o.toTensor()}var Cw=V({randomGamma_:$O});function PO(e,t=0,n=1,s,r){if(s!=null&&s==="bool")throw new Error(`Unsupported data type ${s}`);let a=new DA(t,n,s,!1,r),o=Le(e,s);for(let i=0;i<o.values.length;i++)o.values[i]=a.nextValue();return o.toTensor()}var N0=V({randomNormal_:PO});function FO(e,t,n){if(t!=null&&t==="bool")throw new Error(`Unsupported data type ${t}`);return N0(e,0,1,t,n)}var Tw=V({randomStandardNormal_:FO});function OO(e,t=0,n=1,s="float32",r){let a=Le(e,s),o=new DO(t,n,null,r);for(let i=0;i<a.values.length;i++)a.values[i]=o.nextValue();return a.toTensor()}var Kc=V({randomUniform_:OO});function Ju(e,t,n=1,s="float32"){if(n===0)throw new Error("Cannot have a step of zero");let r={start:e,stop:t,step:n,dtype:s};return W.runKernel(_c,{},r)}function MO(e){let n={x:D(e,"x","reciprocal")};return W.runKernel(Dc,n)}var $A=V({reciprocal_:MO});function zO(e){let n={x:D(e,"x","relu")};return W.runKernel(jo,n)}var Pr=V({relu_:zO});function LO(e){let n={x:D(e,"x","relu6")};return W.runKernel(Ko,n)}var E0=V({relu6_:LO});function BO(e,t){let s={x:D(e,"x","reverse")},r={dims:t};return W.runKernel(Dl,s,r)}var Ks=V({reverse_:BO});function WO(e){let t=D(e,"x","reverse");return M(t.rank===1,()=>`Error in reverse1D: x must be rank 1 but got rank ${t.rank}.`),Ks(t,0)}var Nw=V({reverse1d_:WO});function VO(e,t){let n=D(e,"x","reverse");return M(n.rank===2,()=>`Error in reverse2D: x must be rank 2 but got rank ${n.rank}.`),Ks(n,t)}var Ew=V({reverse2d_:VO});function UO(e,t){let n=D(e,"x","reverse");return M(n.rank===3,()=>`Error in reverse3D: x must be rank 3 but got rank ${n.rank}.`),Ks(n,t)}var Rw=V({reverse3d_:UO});function GO(e,t){let n=D(e,"x","reverse");return M(n.rank===4,()=>`Error in reverse4D: x must be rank 4 but got rank ${n.rank}.`),Ks(n,t)}var _w=V({reverse4d_:GO});function HO(e){let n={x:D(e,"x","round")};return W.runKernel($l,n)}var R0=V({round_:HO});function jO(e){let n={x:D(e,"x","rsqrt","float32")};return W.runKernel(Zo,n)}var _0=V({rsqrt_:jO});function qO(e){let n={x:D(e,"x","selu")};return W.runKernel($c,n)}var D0=V({selu_:qO});function XO(e,t,n,s,r,a=[1,1],o="NHWC"){let i=D(e,"x","separableConv2d"),l=D(t,"depthwiseFilter","separableConv2d"),u=D(n,"pointwiseFilter","separableConv2d"),c=i,p=!1;if(i.rank===3&&(p=!0,c=U(i,[1,i.shape[0],i.shape[1],i.shape[2]])),o==="NCHW")throw new Error("separableConv2d currently does not support dataFormat NCHW; only NHWC is supported");M(c.rank===4,()=>`Error in separableConv2d: input must be rank 4, but got rank ${c.rank}.`),M(l.rank===4,()=>`Error in separableConv2d: depthwise filter must be rank 4, but got rank ${l.rank}.`),M(u.rank===4,()=>`Error in separableConv2d: pointwise filter must be rank 4, but got rank ${l.rank}.`),M(u.shape[0]===1,()=>`Error in separableConv2d: the first dimension of pointwise filter  must be 1, but got ${u.shape[0]}.`),M(u.shape[1]===1,()=>`Error in separableConv2d: the second dimension of pointwise filter must be 1, but got ${u.shape[1]}.`);let d=l.shape[2],h=l.shape[3];M(u.shape[2]===d*h,()=>`Error in separableConv2d: the third dimension of pointwise filter must be ${d*h}, but got ${u.shape[2]}.`);let f=Vc(c,l,s,r,o,a),g=ma(f,u,1,"valid",o);return p?U(g,[g.shape[1],g.shape[2],g.shape[3]]):g}var $0=V({separableConv2d_:XO});async function KO(e,t){let n=D(e,"x","setdiff1d"),s=D(t,"y","setdiff1d");M(n.dtype===s.dtype,()=>`x and y should have the same dtype, but got x (${n.dtype}) and y (${s.dtype}).`),M(n.rank===1,()=>`x should be 1D tensor, but got x (${n.shape}).`),M(s.rank===1,()=>`y should be 1D tensor, but got y (${s.shape}).`);let r=await n.data(),a=await s.data(),o=new Set(a),i=0;for(let c=0;c<r.length;c++)o.has(r[c])||i++;let l=new fn([i],n.dtype),u=new fn([i],"int32");for(let c=0,p=0;c<r.length;c++)o.has(r[c])||(l.values[p]=r[c],u.values[p]=c,p++);return[l.toTensor(),u.toTensor()]}var Dw=KO;function ZO(e){let n={x:D(e,"x","sign")};return W.runKernel(Pc,n)}var PA=V({sign_:ZO});function YO(e){let n={x:D(e,"x","sin","float32")};return W.runKernel(Yo,n)}var P0=V({sin_:YO});function JO(e){let n={x:D(e,"x","sinh")};return W.runKernel(Ml,n)}var F0=V({sinh_:JO});function QO(e,t,n){let s=D(e,"x","slice1d");return M(s.rank===1,()=>`slice1d expects a rank-1 tensor, but got a rank-${s.rank} tensor`),Oe(s,[t],[n])}var Ah=V({slice1d_:QO});function eM(e,t,n){let s=D(e,"x","slice2d");return M(s.rank===2,()=>`slice2d expects a rank-2 tensor, but got a rank-${s.rank} tensor`),Oe(s,t,n)}var O0=V({slice2d_:eM});function tM(e,t,n){let s=D(e,"x","slice3d");return M(s.rank===3,()=>`slice3d expects a rank-3 tensor, but got a rank-${s.rank} tensor`),Oe(s,t,n)}var ci=V({slice3d_:tM});function nM(e,t,n){let s=D(e,"x","slice4d");return M(s.rank===4,()=>`slice4d expects a rank-4 tensor, but got a rank-${s.rank} tensor`),Oe(s,t,n)}var no=V({slice4d_:nM});function sM(e,t=-1){let n=D(e,"logits","softmax","float32");if(t===-1&&(t=n.rank-1),t!==n.rank-1)throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${n.rank} and dim was ${t}`);let s={logits:n},r={dim:t};return W.runKernel(ti,s,r)}var Jl=V({softmax_:sM});function rM(e){M(e.dtype==="complex64",()=>`The dtype for tf.spectral.fft() must be complex64 but got ${e.dtype}.`);let t={input:e};return W.runKernel(n0,t)}var xh=V({fft_:rM});function aM(e){M(e.dtype==="complex64",()=>`The dtype for tf.spectral.ifft() must be complex64 but got ${e.dtype}.`);let t={input:e};return W.runKernel(s0,t)}var Qu=V({ifft_:aM});function oM(e){let t=e.shape[e.shape.length-1],n=e.size/t,s;if(t<=2){let r=U(e,[n,t]);s=Qu(r)}else{let r=[n,2*(t-1)],a=U(Yu(e),[n,t]),o=U(oh(e),[n,t]),i=Ks(Oe(a,[0,1],[n,t-2]),1),l=L(Ks(Oe(o,[0,1],[n,t-2]),1),Se(-1)),u=Ct([a,i],1),c=Ct([o,l],1),p=U(fa(u,c),[r[0],r[1]]);s=Qu(p)}if(s=Yu(s),e.rank===3&&e.shape[0]!==0){let r=s,a=e.shape[0];s=U(s,[a,s.shape[0]/a,s.shape[1]]),r.dispose()}return s}var M0=V({irfft_:oM});function iM(e,t,n=0){let r={x:D(e,"x","split")},a={numOrSizeSplits:t,axis:n};return W.runKernel(Ll,r,a)}var Zt=V({split_:iM});function lM(e,t){M(e.dtype==="float32",()=>`The dtype for rfft() must be real value but got ${e.dtype}`);let n=e.shape[e.shape.length-1],s=e.size/n,r;if(t!=null&&t<n){let f=e.shape.map(g=>0),m=e.shape.map(g=>g);m[e.shape.length-1]=t,r=Oe(e,f,m),n=t}else if(t!=null&&t>n){let f=e.shape.map(m=>m);f[e.shape.length-1]=t-n,r=Ct([e,Wt(f)],e.shape.length-1),n=t}else r=e;let a=it(r),o=U(fa(r,a),[s,n]),i=xh(o),l=Math.floor(n/2)+1,u=Yu(i),c=oh(i),p=Zt(u,[l,n-l],u.shape.length-1),d=Zt(c,[l,n-l],c.shape.length-1),h=r.shape.slice();return h[r.shape.length-1]=l,U(fa(p[0],d[0]),h)}var bh=V({rfft_:lM});function uM(e,t){let n=D(e,"a","squaredDifference"),s=D(t,"b","squaredDifference");[n,s]=Gt(n,s),kt(n.shape,s.shape);let r={a:n,b:s},a={};return W.runKernel(ni,r,a)}var z0=V({squaredDifference_:uM});function cM(e,t){let n=D(e,"x","squeeze","string_or_numeric");return U(n,Q7(n.shape,t).newShape)}var rt=V({squeeze_:cM});function dM(e,t=0){let n=Sp(e,"tensors","stack","string_or_numeric");M(n.length>=1,()=>"Pass at least one tensor to tf.stack"),n.length>0&&M(t<=n[0].rank,()=>"Axis must be <= rank of the tensor");let s=n,r={axis:t};return W.runKernel(Rl,s,r)}var on=V({stack_:dM});function pM(e,t=0){let s={x:D(e,"x","step")},r={alpha:t};return W.runKernel(ai,s,r)}var Ql=V({step_:pM});function hM(e,t,n,s,r=0,a=0,o=0,i=0,l=0){let c={x:D(e,"x","stridedSlice","string_or_numeric")},p={begin:t,end:n,strides:s,beginMask:r,endMask:a,ellipsisMask:o,newAxisMask:i,shrinkAxisMask:l};return W.runKernel(Bl,c,p)}var FA=V({stridedSlice_:hM});function fM(e){let n={x:D(e,"x","tan","float32")};return W.runKernel(Wl,n)}var OA=V({tan_:fM});function Ft(e,t){ol(e);let n=Xr(e,t);if(n.length!==1)throw new Error("tensor1d() requires values to be a flat/TypedArray");return oi(e,null,n,t)}function or(e,t,n){if(ol(e),t!=null&&t.length!==2)throw new Error("tensor2d() requires shape to have two numbers");let s=Xr(e,n);if(s.length!==2&&s.length!==1)throw new Error("tensor2d() requires values to be number[][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor2d() requires shape to be provided when `values` are a flat/TypedArray");return oi(e,t,s,n)}function $w(e,t,n){if(ol(e),t!=null&&t.length!==4)throw new Error("tensor4d() requires shape to have four numbers");let s=Xr(e,n);if(s.length!==4&&s.length!==1)throw new Error("tensor4d() requires values to be number[][][][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor4d() requires shape to be provided when `values` are a flat array");return oi(e,t,s,n)}function Pw(e,t,n){if(ol(e),t!=null&&t.length!==5)throw new Error("tensor5d() requires shape to have five numbers");let s=Xr(e,n);if(s.length!==5&&s.length!==1)throw new Error("tensor5d() requires values to be number[][][][][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor5d() requires shape to be provided when `values` are a flat array");return oi(e,t,s,n)}function Fw(e,t,n){if(ol(e),t!=null&&t.length!==6)throw new Error("tensor6d() requires shape to have six numbers");let s=Xr(e,n);if(s.length!==6&&s.length!==1)throw new Error("tensor6d() requires values to be number[][][][][][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor6d() requires shape to be provided when `values` are a flat array");return t=t||s,oi(e,t,s,n)}function mM(e,t=1,n=!0){let s=D(e,"x","topk");if(s.rank===0)throw new Error("topk() expects the input to be of rank 1 or higher");let r=s.shape[s.shape.length-1];if(t<0)throw new Error(`'k' passed to topk() must be >= 0 but got ${t}`);if(t>r)throw new Error(`'k' passed to topk() must be <= the last dimension (${r}) but got ${t}`);let a={x:s},o={k:t,sorted:n},[i,l]=W.runKernel(Vl,a,o);return{values:i,indices:l}}var MA=V({topk_:mM});function gM(e,t=0,n=1,s,r){if(s!=null&&s==="bool")throw new Error("Unsupported data type $ { dtype }");let a=new DA(t,n,s,!0,r),o=Le(e,s);for(let i=0;i<o.values.length;i++)o.values[i]=a.nextValue();return o.toTensor()}var L0=V({truncatedNormal_:gM});function yM(e,t=0){let n=D(e,"x","unique","string_or_numeric");M(n.rank>0,()=>"The input tensor must be at least 1D");let s={x:n},r={axis:t},[a,o]=W.runKernel(h0,s,r);return{values:a,indices:o}}var zA=V({unique_:yM});function AM(e,t,n){let s=D(e,"x","unsortedSegmentSum"),r=D(t,"segmentIds","unsortedSegmentSum","int32");M(qu(n),()=>"numSegments must be of dtype int");let a={x:s,segmentIds:r},o={numSegments:n};return W.runKernel(eh,a,o)}var B0=V({unsortedSegmentSum_:AM});function xM(e,t=0){let n=D(e,"x","unstack","string_or_numeric");M(t>=-n.shape.length&&t<n.shape.length,()=>`Axis = ${t} is not in [-${n.shape.length}, ${n.shape.length})`);let s={value:n},r={axis:t};return W.runKernel(Gl,s,r)}var es=V({unstack_:xM});function Ow(e,t){return T0(e,t,"right")}function LA(e,t=!0,n,s){return W.makeVariable(e,t,n,s)}function Mw(e,t){let n=[];for(let a=0;a<t.length;a++)t[a]&&n.push(a);let s=Le(e,"int32"),r=Le([n.length,e.length],"int32");for(let a=0;a<n.length;a++){let o=s.indexToLoc(n[a]),i=a*e.length;r.values.set(o,i)}return r.toTensor()}async function bM(e){let t=D(e,"condition","whereAsync","bool"),n=await t.data(),s=Mw(t.shape,n);return e!==t&&t.dispose(),s}var BA=bM;async function vM(e,t,n){let s=D(e,"tensor","boolMask"),r=D(t,"mask","boolMask","bool"),a=n==null?0:n,o=r.rank,i=s.shape;M(o>0,()=>"mask cannot be scalar"),ns(i.slice(a,a+o),r.shape,"mask's shape must match the first K dimensions of tensor's shape,");let l=1;for(let m=a;m<a+o;m++)l*=i[m];let u=i.slice(0,a).concat([l],i.slice(a+o)),c=U(s,u),p=U(r,[-1]),d=await BA(p),h=rt(d,[1]),f=qc(c,h,a);return e!==s&&s.dispose(),t!==r&&r.dispose(),h.dispose(),c.dispose(),p.dispose(),d.dispose(),f}var zw=vM;function wM(e,t,n,s,r=!0){let a=D(e,"v","movingAverage"),o=D(t,"x","movingAverage"),i=D(n,"decay","movingAverage");y6(a,o),M(co(a.shape,o.shape),()=>"Shape mismatch in v and x");let l=Se(1),u=he(l,i),c=L(he(o,a),u);if(r){M(s!=null,()=>"When using zeroDebias: true, step is required.");let p=D(s,"step","movingAverage");c=pe(c,he(l,ya(i,p)))}return ce(a,c)}var Lw=V({movingAverage_:wM});function kM(e,t,n){let s=D(e,"indices","scatterND","int32"),r=D(t,"updates","scatterND");Wy(r,s,n);let a={indices:s,updates:r},o={shape:n};return W.runKernel(Pl,a,o)}var Bw=V({scatterND_:kM});function IM(e,t,n,s){if(e.dtype!=="int32")throw new Error(`tf.sparseToDense() expects the indices to be int32 type, but the dtype was ${e.dtype}.`);if(e.rank>2)throw new Error(`sparseIndices should be a scalar, vector, or matrix, but got shape ${e.shape}.`);let r=e.rank>0?e.shape[0]:1,a=e.rank>1?e.shape[1]:1;if(n.length!==a)throw new Error(`outputShape has incorrect number of elements:, ${n.length}, should be: ${a}.`);let o=t.size;if(!(t.rank===0||t.rank===1&&o===r))throw new Error(`sparseValues has incorrect shape ${t.shape}, should be [] or [${r}]`);if(t.dtype!==s.dtype)throw new Error("sparseValues.dtype must match defaultValues.dtype")}function SM(e,t,n,s=0){let r=D(e,"sparseIndices","sparseToDense","int32"),a=D(t,"sparseValues","sparseToDense","string_or_numeric"),o=D(s,"defaultValue","sparseToDense",a.dtype);IM(r,a,n,o);let i={sparseIndices:r,sparseValues:a,defaultValue:o},l={outputShape:n};return W.runKernel(Yp,i,l)}var Ww=V({sparseToDense_:SM});function CM(e,t){let n=D(t,"indices","gatherND","int32"),r={params:D(e,"x","gatherND","string_or_numeric"),indices:n};return W.runKernel(Al,r)}var Vw=V({gatherND_:CM});function TM(e,t){if(t==null)return e.shape.slice();if(co(e.shape,t))return t;if(e.shape.length===t.length){let n=[];for(let s=0;s<e.shape.length;s++)t[s]==null&&e.shape[s]!=null?n.push(e.shape[s]):n.push(t[s]);return n}return t}function NM(e,t,n,s){let r=D(e,"x","dropout");if(M(r.dtype==="float32",()=>`x has to be a floating point tensor since it's going to be scaled, but got a ${r.dtype} tensor instead.`),M(t>=0&&t<1,()=>`rate must be a float in the range [0, 1), but got ${t}.`),t===0)return e instanceof tt?r.clone():r;let a=TM(r,n),o=1-t,i=pe(jc(ce(Kc(a,0,1,"float32",s),o)),o);return L(r,i)}var WA=V({dropout_:NM});function VA(e){return Math.floor(Math.pow(2,Math.ceil(Math.log(e)/Math.log(2))))}function W0(e,t,n){let s=1-e%2,r=new Float32Array(e);for(let a=0;a<e;++a){let o=2*Math.PI*a/(e+s-1);r[a]=t-n*Math.cos(o)}return Ft(r,"float32")}async function EM(e,t,n=1){let s=D(e,"predictions","inTopK"),r=D(t,"targets","inTopK");M(s.rank>1,()=>`inTopK() expects the predictions to be of rank 2 or higher, but got ${s.rank}`),M(s.rank-1===r.rank,()=>`predictions rank should be 1 larger than targets rank, but got predictions rank ${s.rank} and targets rank ${r.rank}`),ns(s.shape.slice(0,s.shape.length-1),r.shape,"predictions's shape should be align with the targets' shape, except the last dimension.");let a=s.shape[s.shape.length-1];M(n>0&&n<=a,()=>`'k' passed to inTopK() must be > 0 && <= the predictions last dimension (${a}), but got ${n}`);let o=await s.data(),i=await r.data(),[l,u]=[o.length/a,a],c=e6("bool",l);for(let p=0;p<l;p++){let d=p*u,h=o.subarray(d,d+u),f=[];for(let m=0;m<h.length;m++)f.push({value:h[m],index:m});f.sort((m,g)=>g.value-m.value),c[p]=0;for(let m=0;m<n;m++)if(f[m].index===i[p]){c[p]=1;break}}return e!==s&&s.dispose(),t!==r&&r.dispose(),ft(c,r.shape,"bool")}var Uw=EM,ec={};Ve(ec,{conv2d:()=>DM,depthwiseConv2d:()=>OM,matMul:()=>zM});function RM(e,t,n,s,r,a="NHWC",o){let i=e;e.rank===3&&(i=U(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let l=t;l.rank===3&&(l=U(t,[1,t.shape[0],t.shape[1],t.shape[2]])),M(i.rank===4,()=>`Error in conv2dDerFilter: input must be rank 4, but got shape ${i.shape}.`),M(l.rank===4,()=>`Error in conv2dDerFilter: dy must be rank 4, but got shape ${l.shape}.`),M(n.length===4,()=>`Error in conv2dDerFilter: filterShape must be length 4, but got ${n}.`);let u=a==="NHWC"?i.shape[3]:i.shape[1],c=a==="NHWC"?l.shape[3]:l.shape[1];M(u===n[2],()=>`Error in conv2dDerFilter: depth of input ${u}) must match input depth in filter (${n[2]}.`),M(c===n[3],()=>`Error in conv2dDerFilter: depth of dy (${c}) must match output depth for filter (${n[3]}).`),rs("conv2dDerFilter",r,o);let p={x:i,dy:l},d={strides:s,pad:r,dataFormat:a,dimRoundingMode:o,filterShape:n};return W.runKernel(Xm,p,d)}var UA=V({conv2DBackpropFilter_:RM});function V0(e,t,n){if(n==null||n==="linear")return e;if(n==="relu")return L(e,Ql(t));throw new Error(`Cannot compute gradient for fused activation ${n}.`)}function U0(e,t){let n=t,s=an(e.shape,t.shape);return s.length>0&&(n=ke(n,s)),U(n,e.shape)}function G0(e,t,n,s){if(t==="linear")return e;if(t==="relu")return Pr(e);if(t==="elu")return Uc(e);if(t==="relu6")return E0(e);if(t==="prelu")return yh(e,n);if(t==="leakyrelu")return dh(e,s);if(t==="sigmoid")return Cn(e);throw new Error(`Unknown fused activation ${t}.`)}var H0=(e,t)=>!(e>0)||t==="linear";function _M({x:e,filter:t,strides:n,pad:s,dataFormat:r="NHWC",dilations:a=[1,1],dimRoundingMode:o,bias:i,activation:l="linear",preluActivationWeights:u,leakyreluAlpha:c}){if(l=l||"linear",H0(W.state.gradientDepth,l)===!1){M(r==="NHWC",()=>`Error in fused conv2d: got dataFormat of ${r} but only NHWC is currently supported for the case of gradient depth is 0 and the activation is not linear.`);let k=ma(e,t,n,s,r,a,o);return i!=null&&(k=ce(k,i)),G0(k,l,u,c)}let p=D(e,"x","conv2d","float32"),d=D(t,"filter","conv2d","float32"),h=p,f=!1;p.rank===3&&(f=!0,h=U(p,[1,p.shape[0],p.shape[1],p.shape[2]])),M(h.rank===4,()=>`Error in fused conv2d: input must be rank 4, but got rank ${h.rank}.`),M(d.rank===4,()=>`Error in fused conv2d: filter must be rank 4, but got rank ${d.rank}.`),rs("fused conv2d",s,o);let m=r==="NHWC"?h.shape[3]:h.shape[1];M(d.shape[2]===m,()=>`Error in conv2d: depth of input (${m}) must match input depth for filter ${d.shape[2]}.`),M(Yr(n,a),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`);let g=ih(h.shape,d.shape,n,a,s,o),y;i!=null&&(y=D(i,"bias","fused conv2d"),[y]=Gt(y,p),r==="NHWC"?kt(g.outShape,y.shape):(M(y.shape.length<=1,()=>`Error in fused conv2d: only supports scalar or 1-D Tensor bias for NCHW format but got the bias of rank-${y.shape.length}.`),M(y.shape.length===0||y.shape[0]===g.outChannels||y.shape[0]===1,()=>`Error in fused conv2d: bias shape (${y.shape}) is not compatible with the number of output channels (${g.outChannels})`)));let x;if(u!=null){let k=u.shape;if(M(k.length<=1||k.length===3,()=>`Error in fused conv2d: only supports scalar, 1-D Tensor or 3-D Tensor PReLU activation weights but got a tensor of rank-${k.length}.`),k.length===1)M(k[0]===1||k[0]===g.outChannels,()=>`Error in fused conv2d: PReLU activation weights (${k}) is not compatible with the number of output channels (${g.outChannels}).`);else if(k.length===3)try{kt(k,g.outShape)}catch(S){let E=`Error in fused conv2d: PReLU activation weights (${k}) is not compatible with the output shape of the conv2d (${g.outShape}).`;throw Error(E)}x=D(u,"prelu weights","fused conv2d")}let A=(k,S)=>{M(r==="NHWC",()=>`Error in gradient of fused conv2D: got dataFormat of ${r} but only NHWC is currently supported.`);let[E,R,P,_]=S,$=V0(k,P,l);M(to(a),()=>`Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${a}'`);let T=uA(R.shape,$,E,n,s),F=UA(R,$,E.shape,n,s),G=[T,F];if(_!=null){let q=U0(_,$);G.push(q)}return G},b={x:h,filter:d,bias:y,preluActivationWeights:x},w={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:o,activation:l,leakyreluAlpha:c};return i==null?Kr((S,E,R)=>{let P=W.runKernel(Qa,b,w);return R([E,S,P]),f&&(P=U(P,[P.shape[1],P.shape[2],P.shape[3]])),{value:P,gradFunc:A}})(h,d):Kr((S,E,R,P)=>{let _=W.runKernel(Qa,b,w);return P([E,S,_,R]),f&&(_=U(_,[_.shape[1],_.shape[2],_.shape[3]])),{value:_,gradFunc:A}})(h,d,y)}var DM=V({fusedConv2d_:_M});function $M(e,t,n,s,r,a=[1,1],o){let i=e;e.rank===3&&(i=U(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let l=t;l.rank===3&&(l=U(t,[1,t.shape[0],t.shape[1],t.shape[2]]));let u={x:i,dy:l},c={strides:s,pad:r,dimRoundingMode:o,dilations:a,filterShape:n};return W.runKernel(Jm,u,c)}var Gw=V({depthwiseConv2dNativeBackpropFilter_:$M});function PM(e,t,n,s,r,a=[1,1],o){let i=t,l=!1;t.rank===3&&(l=!0,i=U(t,[1,t.shape[0],t.shape[1],t.shape[2]]));let u={dy:i,filter:n},c={strides:s,pad:r,dimRoundingMode:o,dilations:a,inputShape:e},p=W.runKernel(Qm,u,c);return l?U(p,[p.shape[1],p.shape[2],p.shape[3]]):p}var Hw=V({depthwiseConv2dNativeBackpropInput_:PM});function FM({x:e,filter:t,strides:n,pad:s,dataFormat:r="NHWC",dilations:a=[1,1],dimRoundingMode:o,bias:i,activation:l="linear",preluActivationWeights:u,leakyreluAlpha:c}){if(H0(W.state.gradientDepth,l)===!1){let w=Vc(e,t,n,s,r,a,o);return i!=null&&(w=ce(w,i)),G0(w,l,u,c)}let p=D(e,"x","depthwiseConv2d","float32"),d=D(t,"filter","depthwiseConv2d","float32"),h=p,f=!1;p.rank===3&&(f=!0,h=U(p,[1,p.shape[0],p.shape[1],p.shape[2]])),M(h.rank===4,()=>`Error in fused depthwiseConv2d: input must be rank 4, but got rank ${h.rank}.`),M(d.rank===4,()=>`Error in fused depthwiseConv2d: filter must be rank 4, but got rank ${d.rank}.`),M(h.shape[3]===d.shape[2],()=>`Error in fused depthwiseConv2d: number of input channels (${h.shape[3]}) must match the inChannels dimension in filter ${d.shape[2]}.`),a==null&&(a=[1,1]),M(Yr(n,a),()=>`Error in fused depthwiseConv2d: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`),rs("fused depthwiseConv2d",s,o);let m=ih(h.shape,d.shape,n,a,s,o,!0),g;i!=null&&(g=D(i,"bias","fused conv2d"),[g]=Gt(g,p),kt(m.outShape,g.shape));let y;u!=null&&(y=D(u,"prelu weights","fused depthwiseConv2d"));let x=(w,k)=>{M(to(a),()=>`Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '${a}'`);let[S,E,R,P]=k,_=V0(w,R,l),$=Hw(E.shape,_,S,n,s,a,o),T=Gw(E,_,S.shape,n,s,a,o);if(P!=null){let F=U0(g,_);return[$,T,F]}return[$,T]},A={x:h,filter:d,bias:g,preluActivationWeights:y},b={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:o,activation:l,leakyreluAlpha:c};return i==null?Kr((k,S,E)=>{let R=W.runKernel(eo,A,b);return E([S,k,R]),f&&(R=U(R,[R.shape[1],R.shape[2],R.shape[3]])),{value:R,gradFunc:x}})(h,d):Kr((k,S,E,R)=>{let P=W.runKernel(eo,A,b);return R([S,k,P,E]),f&&(P=U(P,[P.shape[1],P.shape[2],P.shape[3]])),{value:P,gradFunc:x}})(h,d,g)}var OM=V({fusedDepthwiseConv2d_:FM});function MM({a:e,b:t,transposeA:n=!1,transposeB:s=!1,bias:r,activation:a="linear",preluActivationWeights:o,leakyreluAlpha:i=.2}){if(H0(W.state.gradientDepth,a)===!1){let _=Qe(e,t,n,s);return r!=null&&(_=ce(_,r)),G0(_,a,o,i)}let l=D(e,"a","fused matMul"),u=D(t,"b","fused matMul");[l,u]=Gt(l,u);let c=n?l.shape[l.rank-2]:l.shape[l.rank-1],p=s?u.shape[u.rank-1]:u.shape[u.rank-2],d=n?l.shape[l.rank-1]:l.shape[l.rank-2],h=s?u.shape[u.rank-2]:u.shape[u.rank-1],f=l.shape.slice(0,-2),m=u.shape.slice(0,-2),g=Et(f),y=Et(m);M(c===p,()=>`Error in fused matMul: inner shapes (${c}) and (${p}) of Tensors with shapes ${l.shape} and ${u.shape} and transposeA=${n} and transposeB=${s} must match.`);let A=kt(l.shape.slice(0,-2),u.shape.slice(0,-2)).concat([d,h]),b=n?U(l,[g,c,d]):U(l,[g,d,c]),w=s?U(u,[y,h,p]):U(u,[y,p,h]),k;r!=null&&(k=D(r,"bias","fused matMul"),[k]=Gt(k,l),kt(A,k.shape));let S;o!=null&&(S=D(o,"prelu weights","fused matMul"));let E=(_,$)=>{let[T,F,G,q]=$,z=V0(U(_,G.shape),G,a),K,B;if(!n&&!s?(K=Qe(z,F,!1,!0),B=Qe(T,z,!0,!1)):!n&&s?(K=Qe(z,F,!1,!1),B=Qe(z,T,!0,!1)):n&&!s?(K=Qe(F,z,!1,!0),B=Qe(T,z,!1,!1)):(K=Qe(F,z,!0,!0),B=Qe(z,T,!0,!0)),r!=null){let ee=U0(q,z);return[K,B,ee]}else return[K,B]},R={a:b,b:w,bias:k,preluActivationWeights:S},P={transposeA:n,transposeB:s,activation:a,leakyreluAlpha:i};return r==null?Kr(($,T,F)=>{let G=W.runKernel(Ja,R,P);return F([$,T,G]),{value:U(G,A),gradFunc:E}})(b,w):Kr(($,T,F,G)=>{let q=W.runKernel(Ja,R,P);return G([$,T,q,F]),{value:U(q,A),gradFunc:E}})(b,w,k)}var zM=V({fusedMatMul_:MM});function LM(e){return W0(e,.54,.46)}var BM=V({hammingWindow_:LM});function WM(e){return W0(e,.5,.5)}var jw=V({hannWindow_:WM});function VM(e,t,n,s=!1,r=0){let a=0,o=[];for(;a+t<=e.size;)o.push(Oe(e,a,t)),a+=n;if(s)for(;a<e.size;){let i=a+t-e.size,l=Ct([Oe(e,a,t-i),Hc([i],r)]);o.push(l),a+=n}return o.length===0?or([],[0,t]):U(Ct(o),[o.length,t])}var qw=V({frame_:VM});function UM(e,t,n,s,r=jw){s==null&&(s=VA(t));let a=qw(e,t,n),o=L(a,r(t));return bh(o,s)}var GM=V({stft_:UM});function HM(e,t,n,s,r="bilinear",a=0){let o=D(e,"image","cropAndResize"),i=D(t,"boxes","cropAndResize","float32"),l=D(n,"boxInd","cropAndResize","int32"),u=i.shape[0];M(o.rank===4,()=>`Error in cropAndResize: image must be rank 4,but got rank ${o.rank}.`),M(i.rank===2&&i.shape[1]===4,()=>`Error in cropAndResize: boxes must be have size [${u},4] but had shape ${i.shape}.`),M(l.rank===1&&l.shape[0]===u,()=>`Error in cropAndResize: boxInd must be have size [${u}] but had shape ${i.shape}.`),M(s.length===2,()=>`Error in cropAndResize: cropSize must be of length 2, but got length ${s.length}.`),M(s[0]>=1&&s[1]>=1,()=>`cropSize must be atleast [1,1], but was ${s}`),M(r==="bilinear"||r==="nearest",()=>`method must be bilinear or nearest, but was ${r}`);let c={image:o,boxes:i,boxInd:l},p={method:r,extrapolationValue:a,cropSize:s};return W.runKernel(dl,c,p)}var jM=V({cropAndResize_:HM});function qM(e){let t=D(e,"image","flipLeftRight","float32");M(t.rank===4,()=>`Error in flipLeftRight: image must be rank 4,but got rank ${t.rank}.`);let n={image:t};return W.runKernel(gl,n,{})}var XM=V({flipLeftRight_:qM});function KM(e){let t=D(e,"image","grayscaleToRGB"),n=t.rank-1,s=t.shape[n];M(t.rank>=2,()=>`Error in grayscaleToRGB: images must be at least rank 2, but got rank ${t.rank}.`),M(s===1,()=>`Error in grayscaleToRGB: last dimension of a grayscale image should be size 1, but got size ${s}.`);let r=new Array(t.rank);return r.fill(1,0,n),r[n]=3,js(t,r)}var ZM=V({grayscaleToRGB_:KM});function YM(e,t,n=0,s=.5){let r=D(e,"image","rotateWithOffset","float32");M(r.rank===4,()=>`Error in rotateWithOffset: image must be rank 4,but got rank ${r.rank}.`);let a={image:r},o={radians:t,fillValue:n,center:s};return W.runKernel(jl,a,o)}var JM=V({rotateWithOffset_:YM});function Zc(e,t,n,s,r,a){s==null&&(s=.5),r==null&&(r=Number.NEGATIVE_INFINITY),a==null&&(a=0);let o=e.shape[0];return n=Math.min(n,o),M(0<=s&&s<=1,()=>`iouThreshold must be in [0, 1], but was '${s}'`),M(e.rank===2,()=>`boxes must be a 2D tensor, but was of rank '${e.rank}'`),M(e.shape[1]===4,()=>`boxes must have 4 columns, but 2nd dimension was ${e.shape[1]}`),M(t.rank===1,()=>"scores must be a 1D tensor"),M(t.shape[0]===o,()=>`scores has incompatible shape with boxes. Expected ${o}, but was ${t.shape[0]}`),M(0<=a&&a<=1,()=>`softNmsSigma must be in [0, 1], but was '${a}'`),{maxOutputSize:n,iouThreshold:s,scoreThreshold:r,softNmsSigma:a}}function QM(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY){let a=D(e,"boxes","nonMaxSuppression","float32"),o=D(t,"scores","nonMaxSuppression","float32"),i=Zc(a,o,n,s,r);n=i.maxOutputSize,s=i.iouThreshold,r=i.scoreThreshold;let l={maxOutputSize:n,iouThreshold:s,scoreThreshold:r};return W.runKernel(Cl,{boxes:a,scores:o},l)}var ez=V({nonMaxSuppression_:QM});function tz(e,t,n){let s=nz(e,t,n),r=s<0?-(s+1):s;e.splice(r,0,t)}function nz(e,t,n){return rz(e,t,n||sz)}function sz(e,t){return e>t?1:e<t?-1:0}function rz(e,t,n){let s=0,r=e.length,a=0,o=!1;for(;s<r;){a=s+(r-s>>>1);let i=n(t,e[a]);i>0?s=a+1:(r=a,o=!i)}return o?s:-s-1}function Xw(e,t,n,s,r){return GA(e,t,n,s,r,0)}function Kw(e,t,n,s,r,a){return GA(e,t,n,s,r,0,!1,a,!0)}function Zw(e,t,n,s,r,a){return GA(e,t,n,s,r,a,!0)}function GA(e,t,n,s,r,a,o=!1,i=!1,l=!1){let u=[];for(let g=0;g<t.length;g++)t[g]>r&&u.push({score:t[g],boxIndex:g,suppressBeginIndex:0});u.sort(vv);let c=a>0?-.5/a:0,p=[],d=[];for(;p.length<n&&u.length>0;){let g=u.pop(),{score:y,boxIndex:x,suppressBeginIndex:A}=g;if(y<r)break;let b=!1;for(let w=p.length-1;w>=A;--w){let k=az(e,x,p[w]);if(k>=s){b=!0;break}if(g.score=g.score*oz(s,c,k),g.score<=r)break}g.suppressBeginIndex=p.length,b||(g.score===y?(p.push(x),d.push(g.score)):g.score>r&&tz(u,g,vv))}let h=p.length,f=n-h;i&&f>0&&(p.push(...new Array(f).fill(0)),d.push(...new Array(f).fill(0)));let m={selectedIndices:p};return o&&(m.selectedScores=d),l&&(m.validOutputs=h),m}function az(e,t,n){let s=e.subarray(t*4,t*4+4),r=e.subarray(n*4,n*4+4),a=Math.min(s[0],s[2]),o=Math.min(s[1],s[3]),i=Math.max(s[0],s[2]),l=Math.max(s[1],s[3]),u=Math.min(r[0],r[2]),c=Math.min(r[1],r[3]),p=Math.max(r[0],r[2]),d=Math.max(r[1],r[3]),h=(i-a)*(l-o),f=(p-u)*(d-c);if(h<=0||f<=0)return 0;let m=Math.max(a,u),g=Math.max(o,c),y=Math.min(i,p),x=Math.min(l,d),A=Math.max(y-m,0)*Math.max(x-g,0);return A/(h+f-A)}function oz(e,t,n){let s=Math.exp(t*n*n);return n<=e?s:0}function vv(e,t){return e.score-t.score||e.score===t.score&&t.boxIndex-e.boxIndex}async function iz(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY){let a=D(e,"boxes","nonMaxSuppressionAsync"),o=D(t,"scores","nonMaxSuppressionAsync"),i=Zc(a,o,n,s,r);n=i.maxOutputSize,s=i.iouThreshold,r=i.scoreThreshold;let l=await Promise.all([a.data(),o.data()]),u=l[0],c=l[1],{selectedIndices:p}=Xw(u,c,n,s,r);return a!==e&&a.dispose(),o!==t&&o.dispose(),Ft(p,"int32")}var lz=iz;function uz(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY,a=0){let o=D(e,"boxes","nonMaxSuppression"),i=D(t,"scores","nonMaxSuppression"),l=Zc(o,i,n,s,r,a);n=l.maxOutputSize,s=l.iouThreshold,r=l.scoreThreshold,a=l.softNmsSigma;let u={boxes:o,scores:i},c={maxOutputSize:n,iouThreshold:s,scoreThreshold:r,softNmsSigma:a},p=W.runKernel(Tl,u,c);return{selectedIndices:p[0],selectedScores:p[1]}}var cz=V({nonMaxSuppressionWithScore_:uz});async function dz(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY,a=0){let o=D(e,"boxes","nonMaxSuppressionAsync"),i=D(t,"scores","nonMaxSuppressionAsync"),l=Zc(o,i,n,s,r,a);n=l.maxOutputSize,s=l.iouThreshold,r=l.scoreThreshold,a=l.softNmsSigma;let u=await Promise.all([o.data(),i.data()]),c=u[0],p=u[1],{selectedIndices:d,selectedScores:h}=Zw(c,p,n,s,r,a);return o!==e&&o.dispose(),i!==t&&i.dispose(),{selectedIndices:Ft(d,"int32"),selectedScores:Ft(h)}}var pz=dz;function hz(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY,a=!1){let o=D(e,"boxes","nonMaxSuppression"),i=D(t,"scores","nonMaxSuppression"),l=Zc(o,i,n,s,r,null),u=l.maxOutputSize,c=l.iouThreshold,p=l.scoreThreshold,d={boxes:o,scores:i},h={maxOutputSize:u,iouThreshold:c,scoreThreshold:p,padToMaxOutputSize:a},f=W.runKernel(Rc,d,h);return{selectedIndices:f[0],validOutputs:f[1]}}var fz=V({nonMaxSuppressionPadded_:hz});async function mz(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY,a=!1){let o=D(e,"boxes","nonMaxSuppressionAsync"),i=D(t,"scores","nonMaxSuppressionAsync"),l=Zc(o,i,n,s,r,null),u=l.maxOutputSize,c=l.iouThreshold,p=l.scoreThreshold,[d,h]=await Promise.all([o.data(),i.data()]),{selectedIndices:f,validOutputs:m}=Kw(d,h,u,c,p,a);return o!==e&&o.dispose(),i!==t&&i.dispose(),{selectedIndices:Ft(f,"int32"),validOutputs:Se(m,"int32")}}var gz=mz;function yz(e,t,n=!1,s=!1){let r=D(e,"images","resizeBilinear");M(r.rank===3||r.rank===4,()=>`Error in resizeBilinear: x must be rank 3 or 4, but got rank ${r.rank}.`),M(t.length===2,()=>`Error in resizeBilinear: new shape must 2D, but got shape ${t}.`),M(s===!1||n===!1,()=>"Error in resizeBilinear: If halfPixelCenters is true, alignCorners must be false.");let a=r,o=!1;r.rank===3&&(o=!0,a=U(r,[1,r.shape[0],r.shape[1],r.shape[2]]));let[]=t,i={images:a},l={alignCorners:n,halfPixelCenters:s,size:t},u=W.runKernel(Xo,i,l);return o?U(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var Yw=V({resizeBilinear_:yz});function Az(e,t,n=!1,s=!1){let r=D(e,"images","resizeNearestNeighbor");M(r.rank===3||r.rank===4,()=>`Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank ${r.rank}.`),M(t.length===2,()=>`Error in resizeNearestNeighbor: new shape must 2D, but got shape ${t}.`),M(r.dtype==="float32"||r.dtype==="int32",()=>"`images` must have `int32` or `float32` as dtype"),M(s===!1||n===!1,()=>"Error in resizeNearestNeighbor: If halfPixelCenters is true, alignCorners must be false.");let a=r,o=!1;r.rank===3&&(o=!0,a=U(r,[1,r.shape[0],r.shape[1],r.shape[2]]));let[]=t,i={images:a},l={alignCorners:n,halfPixelCenters:s,size:t},u=W.runKernel(qo,i,l);return o?U(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var Jw=V({resizeNearestNeighbor_:Az});function xz(e,t="binary",n=!1,s=.5){let r=D(e,"image","threshold"),a=.2989,o=.587,i=.114,l=r.shape[0]*r.shape[1],u=L(Ft([s]),255),c,p,d,h;if(M(r.rank===3,()=>`Error in threshold: image must be rank 3,but got rank ${r.rank}.`),M(r.shape[2]===3||r.shape[2]===1,()=>`Error in threshold: image color channel must be equal to 3 or 1but got ${r.shape[2]}.`),M(r.dtype==="int32"||r.dtype==="float32",()=>`Error in dtype: image dtype must be int32 or float32,but got dtype ${r.dtype}.`),M(t==="otsu"||t==="binary",()=>`Method must be binary or otsu, but was ${t}`),r.shape[2]===3){[c,p,d]=Zt(r,[1,1,1],-1);let g=L(c,a),y=L(p,o),x=L(d,i);h=ce(ce(g,y),x)}else h=e;if(t==="otsu"){let g=rA(ge(R0(h),"int32"),ft([]),256);u=bz(g,l)}let f=n?ui(h,u):ys(h,u);return ge(L(f,255),"int32")}function bz(e,t){let n=Ft([-1]),s=Ft([0]),r=Ft([0]),a,o,i,l,u,c;for(let p=0;p<e.size-1;p++){a=Oe(e,0,p+1),o=Oe(e,p+1),u=pe(ke(a),t),c=pe(ke(o),t);let d=ke(L(a,Ju(0,a.size)));i=pe(d,ke(a));let h=Hc(o.shape,a.size),f=ce(Ju(0,o.size),h),m=L(o,f);l=pe(ke(m),ke(o));let g=he(i,l),y=he(i,l),x=L(u,c);r=L(L(x,g),y);let A=ys(r,s);s=Mn(A,r,s),n=Mn(A,Ft([p]),n)}return n}var vz=V({threshold_:xz});function wz(e,t,n="nearest",s="constant",r=0,a){let o=D(e,"image","transform","float32"),i=D(t,"transforms","transform","float32");M(o.rank===4,()=>`Error in transform: image must be rank 4,but got rank ${o.rank}.`),M(i.rank===2&&(i.shape[0]===o.shape[0]||i.shape[0]===1)&&i.shape[1]===8,()=>"Error in transform: Input transform should be batch x 8 or 1 x 8"),M(a==null||a.length===2,()=>`Error in transform: outputShape must be [height, width] or null, but got ${a}.`);let l={image:o,transforms:i},u={interpolation:n,fillMode:s,fillValue:r,outputShape:a};return W.runKernel(Ul,l,u)}var kz=V({transform_:wz});function Iz(e,t,n){M(t%1===0,()=>`bandPart(): numLower must be an integer, got ${t}.`),M(n%1===0,()=>`bandPart(): numUpper must be an integer, got ${n}.`);let s=D(e,"a","bandPart");M(s.rank>=2,()=>`bandPart(): Rank must be at least 2, got ${s.rank}.`);let r=s.shape,[a,o]=s.shape.slice(-2);if(!(t<=a))throw new Error(`bandPart(): numLower (${t}) must not be greater than the number of rows (${a}).`);if(!(n<=o))throw new Error(`bandPart(): numUpper (${n}) must not be greater than the number of columns (${o}).`);t<0&&(t=a),n<0&&(n=o);let i=U(Ju(0,a,1,"int32"),[-1,1]),l=Ju(0,o,1,"int32"),u=he(i,l),c=lr(ui(u,Se(+t,"int32")),li(u,Se(-n,"int32"))),p=Wt([a,o],s.dtype);return U(on(es(U(s,[-1,a,o])).map(d=>Mn(c,d,p))),r)}var Sz=V({bandPart_:Iz});function Cz(e){let t;if(Array.isArray(e)){t=!1,M(e!=null&&e.length>0,()=>"Gram-Schmidt process: input must not be null, undefined, or empty");let r=e[0].shape[0];for(let a=1;a<e.length;++a)M(e[a].shape[0]===r,()=>`Gram-Schmidt: Non-unique lengths found in the input vectors: (${e[a].shape[0]} vs. ${r})`)}else t=!0,e=Zt(e,e.shape[0],0).map(r=>rt(r,[0]));M(e.length<=e[0].shape[0],()=>`Gram-Schmidt: Number of vectors (${e.length}) exceeds number of dimensions (${e[0].shape[0]}).`);let n=[],s=e;for(let r=0;r<e.length;++r)n.push(W.tidy(()=>{let a=s[r];if(r>0)for(let o=0;o<r;++o){let i=L(ke(L(n[o],a)),n[o]);a=he(a,i)}return pe(a,Gc(a,"euclidean"))}));return t?on(n,0):n}var Tz=V({gramSchmidt_:Cz});function Nz(e,t=!1){if(M(e.rank>=2,()=>`qr() requires input tensor to have a rank >= 2, but got rank ${e.rank}`),e.rank===2)return wv(e,t);{let n=e.shape.slice(0,e.shape.length-2).reduce((l,u)=>l*u),s=es(U(e,[n,e.shape[e.shape.length-2],e.shape[e.shape.length-1]]),0),r=[],a=[];s.forEach(l=>{let[u,c]=wv(l,t);r.push(u),a.push(c)});let o=U(on(r,0),e.shape),i=U(on(a,0),e.shape);return[o,i]}}function wv(e,t=!1){return W.tidy(()=>{M(e.shape.length===2,()=>`qr2d() requires a 2D Tensor, but got a ${e.shape.length}D Tensor.`);let n=e.shape[0],s=e.shape[1],r=v0(n),a=Fn(e),o=or([[1]],[1,1]),i=Fn(o),l=n>=s?s:n;for(let u=0;u<l;++u){let c=a,p=i,d=r;[i,a,r]=W.tidy(()=>{let h=Oe(a,[u,u],[n-u,1]),f=Gc(h),m=Oe(a,[u,u],[1,1]),g=Mn(ys(m,0),or([[-1]]),or([[1]])),y=he(m,L(g,f)),x=pe(h,y);x.shape[0]===1?i=Fn(o):i=Ct([o,Oe(x,[1,0],[x.shape[0]-1,x.shape[1]])],0);let A=Dt(pe(Qe(g,y),f)),b=Oe(a,[u,0],[n-u,s]),w=L(A,i),k=st(i);if(u===0)a=he(b,Qe(w,Qe(k,b)));else{let R=he(b,Qe(w,Qe(k,b)));a=Ct([Oe(a,[0,0],[u,s]),R],0)}let S=st(w),E=Oe(r,[0,u],[n,r.shape[1]-u]);if(u===0)r=he(E,Qe(Qe(E,i),S));else{let R=he(E,Qe(Qe(E,i),S));r=Ct([Oe(r,[0,0],[n,u]),R],1)}return[i,a,r]}),ne([c,p,d])}return!t&&n>s&&(r=Oe(r,[0,0],[n,s]),a=Oe(a,[0,0],[s,s])),[r,a]})}var Ez=V({qr_:Nz}),Yn;(function(e){e[e.NONE=0]="NONE",e[e.MEAN=1]="MEAN",e[e.SUM=2]="SUM",e[e.SUM_BY_NONZERO_WEIGHTS=3]="SUM_BY_NONZERO_WEIGHTS"})(Yn||(Yn={}));function Rz(e,t,n=Yn.SUM_BY_NONZERO_WEIGHTS){let s=D(e,"losses","computeWeightedLoss"),r=null;t!=null&&(r=D(t,"weights","computeWeightedLoss"));let a=r==null?s:L(s,r);if(n===Yn.NONE)return a;if(n===Yn.SUM)return ke(a);if(n===Yn.MEAN){if(r==null)return Bt(a);{let o=s.size/r.size,i=pe(ke(a),ke(r));return o>1?pe(i,Se(o)):i}}if(n===Yn.SUM_BY_NONZERO_WEIGHTS){if(r==null)return pe(ke(a),Se(s.size));{let o=L(r,Ns(s.shape)),i=ge(ke(Qi(o,Se(0))),"float32");return pe(ke(a),i)}}throw Error(`Unknown reduction: ${n}`)}var wa=V({computeWeightedLoss_:Rz});function _z(e,t,n,s=Yn.SUM_BY_NONZERO_WEIGHTS){let r=D(e,"labels","absoluteDifference"),a=D(t,"predictions","absoluteDifference"),o=null;n!=null&&(o=D(n,"weights","absoluteDifference")),ns(r.shape,a.shape,"Error in absoluteDifference: ");let i=tn(he(r,a));return wa(i,o,s)}var Dz=V({absoluteDifference_:_z});function $z(e,t,n,s,r=Yn.SUM_BY_NONZERO_WEIGHTS){let a=D(e,"labels","cosineDistance"),o=D(t,"predictions","cosineDistance"),i=null;s!=null&&(i=D(s,"weights","cosineDistance")),ns(a.shape,o.shape,"Error in cosineDistance: ");let l=Se(1),u=he(l,ke(L(a,o),n,!0));return wa(u,i,r)}var Pz=V({cosineDistance_:$z});function Fz(e,t,n,s=Yn.SUM_BY_NONZERO_WEIGHTS){let r=D(e,"labels","hingeLoss"),a=D(t,"predictions","hingeLoss"),o=null;n!=null&&(o=D(n,"weights","hingeLoss")),ns(r.shape,a.shape,"Error in hingeLoss: ");let i=Se(1);r=he(L(Se(2),r),i);let l=Pr(he(i,L(r,a)));return wa(l,o,s)}var Oz=V({hingeLoss_:Fz});function Mz(e,t,n,s=1,r=Yn.SUM_BY_NONZERO_WEIGHTS){let a=D(e,"labels","huberLoss"),o=D(t,"predictions","huberLoss"),i=null;n!=null&&(i=D(n,"weights","huberLoss")),ns(a.shape,o.shape,"Error in huberLoss: ");let l=Se(s),u=tn(he(o,a)),c=Xc(u,l),p=he(u,c),d=ce(L(Se(.5),vt(c)),L(l,p));return wa(d,i,r)}var zz=V({huberLoss_:Mz});function Lz(e,t,n,s=1e-7,r=Yn.SUM_BY_NONZERO_WEIGHTS){let a=D(e,"labels","logLoss"),o=D(t,"predictions","logLoss"),i=null;n!=null&&(i=D(n,"weights","logLoss")),ns(a.shape,o.shape,"Error in logLoss: ");let l=Se(1),u=Se(s),c=Dt(L(a,Ds(ce(o,u)))),p=L(he(l,a),Ds(ce(he(l,o),u))),d=he(c,p);return wa(d,i,r)}var Bz=V({logLoss_:Lz});function Wz(e,t,n,s=Yn.SUM_BY_NONZERO_WEIGHTS){let r=D(e,"labels","meanSquaredError"),a=D(t,"predictions","meanSquaredError"),o=null;n!=null&&(o=D(n,"weights","meanSquaredError")),ns(r.shape,a.shape,"Error in meanSquaredError: ");let i=z0(r,a);return wa(i,o,s)}var Vz=V({meanSquaredError_:Wz});function Uz(e,t){let n=D(e,"labels","sigmoidCrossEntropyWithLogits"),s=D(t,"logits","sigmoidCrossEntropyWithLogits");ns(n.shape,s.shape,"Error in sigmoidCrossEntropyWithLogits: ");let r=Pr(s),a=L(s,n),o=ph(_s(Dt(tn(s))));return ce(he(r,a),o)}function Gz(e,t,n,s=0,r=Yn.SUM_BY_NONZERO_WEIGHTS){let a=D(e,"multiClassLabels","sigmoidCrossEntropy"),o=D(t,"logits","sigmoidCrossEntropy"),i=null;if(n!=null&&(i=D(n,"weights","sigmoidCrossEntropy")),ns(a.shape,o.shape,"Error in sigmoidCrossEntropy: "),s>0){let u=Se(s),c=Se(1),p=Se(.5);a=ce(L(a,he(c,u)),L(p,u))}let l=Uz(a,o);return wa(l,i,r)}var Hz=V({sigmoidCrossEntropy_:Gz});function jz(e,t,n=-1){if(n===-1&&(n=t.rank-1),n!==t.rank-1)throw Error(`Softmax cross entropy along a non-last dimension is not yet supported. Labels / logits was rank ${t.rank} and dim was ${n}`);return Kr((r,a,o)=>{let l=S0(a,[n],!0),u=he(ge(a,"float32"),l);o([r,u]);let c=Dt(L(u,r));return{value:ke(c,[n]),gradFunc:(h,f)=>{let[m,g]=f,y=Ji(h.shape,[n]);return[L(U(h,y),he(ge(m,"float32"),_s(g))),L(U(h,y),he(_s(g),ge(m,"float32")))]}}})(e,t)}function qz(e,t,n,s=0,r=Yn.SUM_BY_NONZERO_WEIGHTS){let a=D(e,"onehotLabels","softmaxCrossEntropy"),o=D(t,"logits","softmaxCrossEntropy"),i=null;if(n!=null&&(i=D(n,"weights","softmaxCrossEntropy")),ns(a.shape,o.shape,"Error in softmaxCrossEntropy: "),s>0){let u=Se(s),c=Se(1),p=Se(a.shape[1]);a=ce(L(a,he(c,u)),pe(u,p))}let l=jz(a,o);return wa(l,i,r)}var Xz=V({softmaxCrossEntropy_:qz});function Kz(e,t,n,s){let r=D(e,"indices","sparseFillEmptyRows","int32"),a=D(t,"values","sparseFillEmptyRows"),o=D(n,"denseShape","sparseFillEmptyRows","int32"),i=D(s,"defaultValue","sparseFillEmptyRows",a.dtype);if(r.rank!==2)throw new Error(`Indices should be Tensor2D but received shape
-        ${r.shape}`);if(a.rank!==1)throw new Error(`Values should be Tensor1D but received shape ${a.shape}`);if(o.rank!==1)throw new Error(`Dense shape should be Tensor1D but received shape ${o.shape}`);if(i.rank!==0)throw new Error(`Default value should be a scalar but received shape ${i.shape}`);let l={indices:r,values:a,denseShape:o,defaultValue:i},u=W.runKernel(Xp,l);return{outputIndices:u[0],outputValues:u[1],emptyRowIndicator:u[2],reverseIndexMap:u[3]}}var Zz=V({sparseFillEmptyRows_:Kz});function Yz(e,t,n){let s=D(e,"inputIndices","sparseReshape","int32"),r=D(t,"inputShape","sparseReshape","int32"),a=D(n,"newShape","sparseReshape","int32");if(s.rank!==2)throw new Error(`Input indices should be Tensor2D but received shape
-        ${s.shape}`);if(r.rank!==1)throw new Error(`Input shape should be Tensor1D but received shape ${r.shape}`);if(a.rank!==1)throw new Error(`New shape should be Tensor1D but received shape ${a.shape}`);let o={inputIndices:s,inputShape:r,newShape:a},i=W.runKernel(Oc,o);return{outputIndices:i[0],outputShape:i[1]}}var Jz=V({sparseReshape_:Yz});function Qz(e,t,n){let s=D(e,"data","sparseSegmentMean"),r=D(t,"indices","sparseSegmentMean","int32"),a=D(n,"segmentIds","sparseSegmentMean","int32");if(s.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.rank!==1)throw new Error(`Indices should be Tensor1D but received shape
+        ${s.shape}`),M(o%(t*t)===0,()=>`Dimension size must be evenly divisible by ${t*t} but is ${o} for depthToSpace with input shape ${s.shape}`);let i={x:s},l={blockSize:t,dataFormat:n};return W.runKernel(dl,i,l)}var pA=V({depthToSpace_:aF});function oF(e,t,n,s,r="NHWC",a=[1,1],o){let i=D(e,"x","depthwiseConv2d","float32"),l=D(t,"filter","depthwiseConv2d","float32"),u=i,c=!1;i.rank===3&&(c=!0,u=U(i,[1,i.shape[0],i.shape[1],i.shape[2]])),M(u.rank===4,()=>`Error in depthwiseConv2d: input must be rank 4, but got rank ${u.rank}.`),M(l.rank===4,()=>`Error in depthwiseConv2d: filter must be rank 4, but got rank ${l.rank}.`);let p=r==="NHWC"?u.shape[3]:u.shape[1];M(p===l.shape[2],()=>`Error in depthwiseConv2d: number of input channels (${p}) must match the inChannels dimension in filter ${l.shape[2]}.`),rs("depthwiseConv2d",s,o);let d={x:u,filter:l},h={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:o},f=W.runKernel(wo,d,h);return c?U(f,[f.shape[1],f.shape[2],f.shape[3]]):f}var Wc=V({depthwiseConv2d_:oF});function iF(e){let n={x:D(e,"x","diag")};return W.runKernel(Qm,n)}var iw=V({diag_:iF});function lF(e,t,n,s,r=[1,1],a="NHWC"){let o=D(e,"x","dilation2d"),i=D(t,"filter","dilation2d");M(o.rank===3||o.rank===4,()=>`Error in dilation2d: input must be rank 3 or 4, but got rank ${o.rank}.`),M(i.rank===3,()=>`Error in dilation2d: filter must be rank 3, but got rank ${i.rank}.`),M(a==="NHWC",()=>`Error in dilation2d: Only NHWC is currently supported, but got dataFormat of ${a}`);let l=o,u=!1;o.rank===3&&(l=U(o,[1,o.shape[0],o.shape[1],o.shape[2]]),u=!0);let c={x:l,filter:i},p={strides:n,pad:s,dilations:r},d=W.runKernel(Wp,c,p);return u?U(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var hA=V({dilation2d_:lF});function uF(e,t){let n=D(e,"a","equal","string_or_numeric"),s=D(t,"b","equal","string_or_numeric");[n,s]=Gt(n,s),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(pl,r)}var Rs=V({equal_:uF});function cF(e,t,n){let s=D(t,"a","where"),r=D(n,"b","where"),a=D(e,"condition","where","bool"),o=kt(kt(a.shape,s.shape),r.shape),i=Uu(a,o),l=Uu(s,o),u=Uu(r,o),c={condition:i,t:l,e:u};return W.runKernel(Pl,c)}var Mn=V({where_:cF});function dF(e){let n={x:D(e,"x","zerosLike")};return W.runKernel(Gl,n)}var it=V({zerosLike_:dF});function pF(e,t){let n=D(e,"a","div"),s=D(t,"b","div");[n,s]=Gt(n,s);let r=pe(n,s),a=it(r),o=Rs(s,a);return Mn(o,a,r)}var fA=V({divNoNan_:pF});function hF(e,t){let n=D(e,"t1","dot"),s=D(t,"t2","dot");M((n.rank===1||n.rank===2)&&(s.rank===1||s.rank===2),()=>`Error in dot: inputs must all be rank 1 or 2, but got ranks ${n.rank} and ${s.rank}.`);let r=n.rank===1?n.size:n.shape[1],a=s.rank===1?s.size:s.shape[0];if(M(r===a,()=>`Error in dot: inner dimensions of inputs must match, but got ${r} and ${a}.`),n.rank===1&&s.rank===1){let o=U(n,[1,-1]),i=U(s,[-1,1]),l=Qe(o,i);return U(l,[])}else if(n.rank===1&&s.rank===2){let o=U(n,[1,-1]),i=U(s,[s.shape[0],s.shape[1]]),l=Qe(o,i);return U(l,[l.size])}else if(n.rank===2&&s.rank===1){let o=U(s,[-1,1]),i=Qe(n,o);return U(i,[i.size])}else{let o=U(s,[s.shape[0],s.shape[1]]);return Qe(n,o)}}var mA=V({dot_:hF});function fF(e,...t){let n=t.map((r,a)=>D(r,`tensors${a}`,"einsum")),s={equation:e};return W.runKernel(Vp,n,s)}var lw=V({einsum_:fF});function mF(e){let n={x:D(e,"x","elu","float32")};return W.runKernel(Io,n)}var Vc=V({elu_:mF});function gF(e){let t=D(e,"x","erf");M(t.dtype==="int32"||t.dtype==="float32",()=>"Input dtype must be `int32` or `float32`."),t.dtype==="int32"&&(t=ge(t,"float32"));let n={x:t};return W.runKernel(vc,n)}var gA=V({erf_:gF});function yA(e,t){for(let n=0;n<e.length;++n)if(e[e.length-n-1]!==t-1-n)return!1;return!0}function uw(e,t,n){let s=e.length+t.length,r=[],a=0,o=0;for(let i=0;i<s;i++)n.indexOf(i)===-1?r.push(e[a++]):r.push(t[o++]);return r}function cw(e,t){let n=[],s=e.length;for(let a=0;a<s;a++)t.indexOf(a)===-1&&n.push(e[a]);let r=t.map(a=>e[a]);return[n,r]}function Yi(e,t){let n=t.map(s=>1);return uw(e,n,t)}function yF(e,t,n){M(yA(t,n),()=>`${e} supports only inner-most axes for now. Got axes ${t} and rank-${n} input.`)}function dw(e,t){if(yA(e,t))return null;let n=[];for(let s=0;s<t;++s)e.indexOf(s)===-1&&n.push(s);return e.forEach(s=>n.push(s)),n}function AA(e){return e.map((t,n)=>[n,t]).sort((t,n)=>t[1]-n[1]).map(t=>t[0])}function AF(e,t){let n=[];for(let s=t-e;s<t;++s)n.push(s);return n}function xF(e,t=null,n=!1){let r={x:D(e,"x","max")},a={reductionIndices:t,keepDims:n};return W.runKernel($o,r,a)}var mn=V({max_:xF});function bF(e,t=null,n=!1){let r={x:D(e,"x","min")},a={axis:t,keepDims:n};return W.runKernel(Mo,r,a)}var ma=V({min_:bF});function vF(e,t){let n=D(e,"base","pow"),s=D(t,"exp","pow");[n,s]=Gt(n,s);let r={a:n,b:s};return W.runKernel(Vo,r)}var ga=V({pow_:vF});function Se(e,t){if((Pn(e)&&t!=="string"||Array.isArray(e))&&t!=="complex64")throw new Error("Error creating a new Scalar: value must be a primitive (number|boolean|string)");if(t==="string"&&Pn(e)&&!(e instanceof Uint8Array))throw new Error("When making a scalar from encoded string, the value must be `Uint8Array`.");return ai(e,[],[],t)}function wF(e){let n={x:D(e,"x","sqrt","float32")};return W.runKernel(Jo,n)}var Nn=V({sqrt_:wF});function kF(e){let t=D(e,"x","square"),n={};return W.runKernel("Square",{x:t},n)}var vt=V({square_:kF});function IF(e,t=null,n=!1){let s=D(e,"x","sum");s.dtype==="bool"&&(s=ge(s,"int32"));let r={x:s},a={axis:t,keepDims:n};return W.runKernel(Qo,r,a)}var ke=V({sum_:IF});function SF(e,t="euclidean",n=null,s=!1){e=D(e,"x","norm");let r=pw(e,t,n),a=r.shape;if(s){let o=ur(n,e.shape);a=Yi(r.shape,o)}return U(r,a)}function pw(e,t,n=null){if(e.rank===0)return tn(e);if(e.rank!==1&&n===null)return pw(U(e,[-1]),t,n);if(e.rank===1||typeof n=="number"||Array.isArray(n)&&n.length===1){if(t===1)return ke(tn(e),n);if(t===1/0)return mn(tn(e),n);if(t===-1/0)return ma(tn(e),n);if(t==="euclidean"||t===2)return Nn(ke(ga(tn(e),Se(2,"int32")),n));throw new Error(`Error in norm: invalid ord value: ${t}`)}if(Array.isArray(n)&&n.length===2){if(t===1)return mn(ke(tn(e),n[0]),n[1]-1);if(t===1/0)return mn(ke(tn(e),n[1]),n[0]);if(t===-1/0)return ma(ke(tn(e),n[1]),n[0]);if(t==="fro"||t==="euclidean")return Nn(ke(vt(e),n));throw new Error(`Error in norm: invalid ord value: ${t}`)}throw new Error(`Error in norm: invalid axis: ${n}`)}var Uc=V({norm_:SF});function CF(e,t=null,n=!1){return Uc(e,"euclidean",t,n)}var xA=V({euclideanNorm_:CF});function TF(e){let n={x:D(e,"x","exp")};return W.runKernel(So,n)}var _s=V({exp_:TF});function NF(e,t=0){let n=D(e,"x","expandDims","string_or_numeric");M(t<=n.rank,()=>"Axis must be <= rank of the tensor");let s={input:n},r={dim:t};return W.runKernel(hl,s,r)}var Kt=V({expandDims_:NF});function EF(e){let n={x:D(e,"x","expm1")};return W.runKernel(fl,n)}var bA=V({expm1_:EF});function RF(e,t){let n=D(e,"x","tile","string_or_numeric");M(n.rank===t.length,()=>`Error in transpose: rank of input ${n.rank} must match length of reps ${t}.`);let s={x:n},r={reps:t};return W.runKernel(ba,s,r)}var js=V({tile_:RF});function _F(e,t,n,s="float32"){t==null&&(t=e);let r=Le([e,t],s),a=e<=t?e:t;for(let i=0;i<a;++i)r.set(1,i,i);let o=U(r.toTensor(),[e,t]);if(n==null)return o;if(n.length===1)return js(Kt(o,0),[n[0],1,1]);if(n.length===2)return js(Kt(Kt(o,0),0),[n[0],n[1],1,1]);if(n.length===3)return js(Kt(Kt(Kt(o,0),0),0),[n[0],n[1],n[2],1,1]);throw new Error(`eye() currently supports only 1D and 2D batchShapes, but received ${n.length}D.`)}var b0=V({eye_:_F});function Gc(e,t,n){let s={shape:e,value:t,dtype:n};return W.runKernel(wc,{},s)}function DF(e){let n={x:D(e,"x","floor","float32")};return W.runKernel(Co,n)}var Hc=V({floor_:DF});function $F(e,t,n=0,s=0){let r=D(e,"x","gather"),a=D(t,"indices","gather","int32"),o={x:r,indices:a},i={axis:n,batchDims:s};return W.runKernel(gl,o,i)}var jc=V({gather_:$F});function PF(e,t){let n=D(e,"a","greater","string_or_numeric"),s=D(t,"b","greater","string_or_numeric");[n,s]=Gt(n,s),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(Al,r)}var ys=V({greater_:PF});function FF(e,t){let n=D(e,"a","greaterEqual","string_or_numeric"),s=D(t,"b","greaterEqual","string_or_numeric");[n,s]=Gt(n,s),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(Eo,r)}var ii=V({greaterEqual_:FF});function OF(e){let n={x:D(e,"x","isFinite")};return W.runKernel(kc,n)}var vA=V({isFinite_:OF});function MF(e){let n={x:D(e,"x","isInf")};return W.runKernel(Ic,n)}var wA=V({isInf_:MF});function zF(e){let n={x:D(e,"x","isNaN")};return W.runKernel(Sc,n)}var kA=V({isNaN_:zF});function LF(e,t=.2){let s={x:D(e,"x","leakyRelu")},r={alpha:t};return W.runKernel(_o,s,r)}var ch=V({leakyRelu_:LF});function BF(e,t){let n=D(e,"a","less","string_or_numeric"),s=D(t,"b","less","string_or_numeric");[n,s]=Gt(n,s),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(xl,r)}var v0=V({less_:BF});function WF(e,t){let n=D(e,"a","lessEqual","string_or_numeric"),s=D(t,"b","lessEqual","string_or_numeric");[n,s]=Gt(n,s),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(bl,r)}var li=V({lessEqual_:WF});function hw(e,t,n){if(n<=0)throw new Error("The number of values should be positive.");let s={start:e,stop:t,num:n};return W.runKernel(s0,{},s)}function VF(e,t=5,n=1,s=1,r=.5){let a=D(e,"x","localResponseNormalization");M(a.rank===4||a.rank===3,()=>`Error in localResponseNormalization: x must be rank 3 or 4 but got
+               rank ${a.rank}.`),M(ju(t),()=>`Error in localResponseNormalization: depthRadius must be an integer but got depthRadius ${t}.`);let o=a,i=!1;a.rank===3&&(i=!0,o=U(a,[1,a.shape[0],a.shape[1],a.shape[2]]));let l={x:o},u={depthRadius:t,bias:n,alpha:s,beta:r},c=W.runKernel(Gp,l,u);return i?U(c,[c.shape[1],c.shape[2],c.shape[3]]):c}var IA=V({localResponseNormalization_:VF});function UF(e){let n={x:D(e,"x","log","float32")};return W.runKernel(Do,n)}var Ds=V({log_:UF});function GF(e){let n={x:D(e,"x","log1p")};return W.runKernel(Cc,n)}var dh=V({log1p_:GF});function HF(e){return M(Za(e),()=>"The f passed in grad(f) must be a function"),(t,n)=>{let s=D(t,"x","tf.grad","string_or_numeric"),r=n!=null?D(n,"dy","tf.grad"):null;return W.tidy(()=>{let{value:a,grads:o}=W.gradients(()=>e(s),[s],r);return r!=null&&ns(a.shape,r.shape,"The shape of dy passed in grad(f)(x, dy) must match the shape returned by f(x)"),w0(o),o[0]})}}function jF(e){return M(Za(e),()=>"The f passed in grads(f) must be a function"),(t,n)=>{M(Array.isArray(t),()=>"The args passed in grads(f)(args) must be an array of `Tensor`s or `TensorLike`s");let s=Ip(t,"args","tf.grads","string_or_numeric"),r=n!=null?D(n,"dy","tf.grads"):null;return W.tidy(()=>{let{value:a,grads:o}=W.gradients(()=>e(...s),s,r);return r!=null&&ns(a.shape,r.shape,"The shape of dy passed in grads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),w0(o),o})}}function qF(e){return M(Za(e),()=>"The f passed in valueAndGrad(f) must be a function"),(t,n)=>{M(t instanceof tt,()=>"The x passed in valueAndGrad(f)(x) must be a tensor"),M(n==null||n instanceof tt,()=>"The dy passed in valueAndGrad(f)(x, dy) must be a tensor");let{grads:s,value:r}=W.gradients(()=>e(t),[t],n);return w0(s),{grad:s[0],value:r}}}function XF(e){return M(Za(e),()=>"The f passed in valueAndGrads(f) must be a function"),(t,n)=>{M(Array.isArray(t)&&t.every(r=>r instanceof tt),()=>"The args passed in valueAndGrads(f)(args) must be array of tensors"),M(n==null||n instanceof tt,()=>"The dy passed in valueAndGrads(f)(args, dy) must be a tensor");let s=W.gradients(()=>e(...t),t,n);return n!=null&&ns(s.value.shape,n.shape,"The shape of dy passed in valueAndGrads(f)([x1,...], dy) must match the shape returned by f([x1,...])"),w0(s.grads),s}}function fw(e,t){M(Za(e),()=>"The f passed in variableGrads(f) must be a function"),M(t==null||Array.isArray(t)&&t.every(u=>u instanceof wp),()=>"The varList passed in variableGrads(f, varList) must be an array of variables");let n=t!=null;if(!n){t=[];for(let u in W.registeredVariables)t.push(W.registeredVariables[u])}let s=n?t.filter(u=>!u.trainable):null,r=t.length;t=t.filter(u=>u.trainable),M(t.length>0,()=>`variableGrads() expects at least one of the input variables to be trainable, but none of the ${r} variables is trainable.`);let a=!0,{value:o,grads:i}=W.gradients(e,t,null,a);M(i.some(u=>u!=null),()=>"Cannot find a connection between any variable and the result of the loss function y=f(x). Please make sure the operations that use variables are inside the function f passed to minimize()."),M(o.rank===0,()=>`The f passed in variableGrads(f) must return a scalar, but it returned a rank-${o.rank} tensor`);let l={};return t.forEach((u,c)=>{i[c]!=null&&(l[u.name]=i[c])}),s!=null&&s.forEach(u=>l[u.name]=null),{value:o,grads:l}}function Xr(e){return W.customGrad(e)}function w0(e){if(e.filter(n=>n==null).length>0)throw new Error(`Cannot compute gradient of y=f(x) with respect to x. Make sure that
+    the f you passed encloses all operations that lead from x to y.`)}function KF(e){let n={x:D(e,"x","softplus")};return W.runKernel(Pc,n)}var Kl=V({softplus_:KF});function ZF(e){let t=D(e,"x","logSigmoid");return Xr(s=>({value:Dt(Kl(Dt(s))),gradFunc:o=>L(o,Cn(Dt(s)))}))(t)}var SA=V({logSigmoid_:ZF});function YF(e,t){let n=D(e,"a","sub"),s=D(t,"b","sub");[n,s]=Gt(n,s);let r={a:n,b:s};return W.runKernel(ni,r)}var he=V({sub_:YF});function JF(e,t=-1){let n=D(e,"logits","logSoftmax");if(t===-1&&(t=n.rank-1),t!==n.rank-1)throw Error(`Log Softmax along a non-last dimension is not yet supported. Logits was rank ${n.rank} and axis was ${t}`);return Xr((r,a)=>{let i=mn(r,t,!0),l=he(r,i),u=he(ge(l,"float32"),Ds(ke(_s(l),t,!0)));return a([u]),{value:u,gradFunc:(p,d)=>{let[h]=d,f=!0,m=_s(h);return he(p,L(ke(p,t,f),m))}}})(n)}var k0=V({logSoftmax_:JF});function QF(e,t=null,n=!1){let s=D(e,"x","logSumExp"),r=ur(t,s.shape),a=mn(s,r,!0),o=he(s,a),i=_s(o),l=ke(i,r),u=Ds(l),c=ce(U(a,u.shape),u);if(n){let p=Yi(c.shape,r);return U(c,p)}return c}var I0=V({logSumExp_:QF});function eO(e,t){let n=D(e,"a","logicalAnd","bool"),s=D(t,"b","logicalAnd","bool");kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(vl,r)}var lr=V({logicalAnd_:eO});function tO(e){let n={x:D(e,"x","logicalNot","bool")};return W.runKernel(wl,n)}var ph=V({logicalNot_:tO});function nO(e,t){let n=D(e,"a","logicalOr","bool"),s=D(t,"b","logicalOr","bool");kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(Tc,r)}var S0=V({logicalOr_:nO});function sO(e,t){let n=D(e,"a","logicalXor","bool"),s=D(t,"b","logicalXor","bool");return kt(n.shape,s.shape),lr(S0(e,t),ph(lr(e,t)))}var CA=V({logicalXor_:sO}),Lf=2147483648;function rO(e,t,n="left"){let s=D(e,"sortedSequence","searchSorted"),r=D(t,"values","searchSorted"),a=s.shape[s.shape.length-1],o=r.shape[r.shape.length-1],i=U(s,[-1,a]),l=U(r,[-1,o]);if(i.rank<2)throw new Error("Sorted input argument must be at least 2-dimensional");if(i.shape[0]!==l.shape[0])throw new Error("Leading dimension of 'sortedSequence' and 'values' must match.");if(Et(l.shape)>=Lf)throw new Error(`values tensor size must less than ${Lf}`);if(i.shape[1]>=Lf)throw new Error(`trailing dim_size must less than ${Lf} for int32 output type, was ${i.shape[1]}`);let u={sortedSequence:i,values:l},c={side:n};return W.runKernel(d0,u,c)}var C0=V({searchSorted_:rO});function mw(e,t){return C0(e,t,"left")}function aO(e,t,n,s,r){let a=D(e,"x","maxPool"),o=1,i=a,l=!1;a.rank===3&&(l=!0,i=U(a,[1,a.shape[0],a.shape[1],a.shape[2]])),M(i.rank===4,()=>`Error in maxPool: input must be rank 4 but got rank ${i.rank}.`),M(Zr(n,o),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${n} and dilations '${o}'`),rs("maxPool",s,r);let u={x:i},c={filterSize:t,strides:n,pad:s,dimRoundingMode:r},p=W.runKernel(Fo,u,c);return l?U(p,[p.shape[1],p.shape[2],p.shape[3]]):p}var hh=V({maxPool_:aO});function oO(e,t=[1,1,1],n,s,r,a="NDHWC"){let o=D(e,"x","maxPool3d"),i=o,l=!1;o.rank===4&&(l=!0,i=U(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]])),M(i.rank===5,()=>`Error in maxPool3d: x must be rank 5 but got rank ${i.rank}.`),M(a==="NDHWC",()=>`Error in maxPool3d: Only NDHWC is currently supported, but got dataFormat of ${a}`),rs("maxPool3d",s,r);let u={x:i},c={filterSize:t,strides:n,pad:s,dimRoundingMode:r,dataFormat:a},p=W.runKernel(Hp,u,c);return l?U(p,[p.shape[1],p.shape[2],p.shape[3],p.shape[4]]):p}var TA=V({maxPool3d_:oO});function iO(e,t,n,s,r=!1){let o={x:D(e,"x","maxPoolWithArgmax")},i={filterSize:t,strides:n,pad:s,includeBatchInIndex:r},l=W.runKernel(i0,o,i);return{result:l[0],indexes:l[1]}}var gw=V({maxPoolWithArgmax_:iO});function lO(e,t){let n=D(e,"a","maximum"),s=D(t,"b","maximum");[n,s]=Gt(n,s),n.dtype==="bool"&&(n=ge(n,"int32"),s=ge(s,"int32")),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(Po,r)}var Yr=V({maximum_:lO});function uO(e,t=null,n=!1){let r={x:D(e,"x","mean")},a={axis:t,keepDims:n};return W.runKernel(Oo,r,a)}var Bt=V({mean_:uO});function Wt(e,t="float32"){if(t==="complex64"){let s=Wt(e,"float32"),r=Wt(e,"float32");return ha(s,r)}let n=Vm(Et(e),t);return W.makeTensor(n,e,t)}function Ns(e,t="float32"){if(t==="complex64"){let s=Ns(e,"float32"),r=Wt(e,"float32");return ha(s,r)}let n=xy(Et(e),t);return W.makeTensor(n,e,t)}function yw(e,t,{indexing:n="xy"}={}){if(n!=="xy"&&n!=="ij")throw new TypeError(`${n} is not a valid third argument to meshgrid`);if(e===void 0)return[];let s=D(e,"x","meshgrid",e instanceof tt?e.dtype:"float32");if(t===void 0)return[s];let r=D(t,"y","meshgrid",t instanceof tt?t.dtype:"float32"),a=Et(s.shape),o=Et(r.shape);return n==="xy"?(s=U(s,[1,-1]),r=U(r,[-1,1]),[Qe(Ns([o,1],s.dtype),s),Qe(r,Ns([1,a],r.dtype))]):(s=U(s,[-1,1]),r=U(r,[1,-1]),[Qe(s,Ns([1,o],s.dtype)),Qe(Ns([a,1],r.dtype),r)])}function cO(e,t){let n=D(e,"a","minimum"),s=D(t,"b","minimum");[n,s]=Gt(n,s),n.dtype==="bool"&&(n=ge(n,"int32"),s=ge(s,"int32")),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(zo,r)}var qc=V({minimum_:cO});function dO(e,t,n){M(n==="reflect"||n==="symmetric",()=>`Invalid mode. Mode must be either reflect or symmetric. Got ${n}.`);let s=D(e,"x","mirrorPad");if(s.rank===0)throw new Error("mirrorPad(scalar) is not defined. Pass non-scalar to mirrorPad");M(t.length===s.rank,()=>`Padding doesn't match input. Must be ${s.rank}. Got ${t.length}.`);let r=n==="reflect"?1:0;for(let i=0;i<s.rank;i++)M(t[i].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),M(t[i][0]>=0&&t[i][0]<=s.shape[i]-r&&t[i][1]>=0&&t[i][1]<=s.shape[i]-r,()=>`Padding in dimension ${i} cannot be greater than or equal to ${s.shape[i]-r} or less than 0 for input of shape ${s.shape}`);let a={paddings:t,mode:n},o={x:s};return W.runKernel(Lo,o,a)}var NA=V({mirrorPad_:dO});function pO(e,t){let n=D(e,"a","mod"),s=D(t,"b","mod");[n,s]=Gt(n,s);let r={a:n,b:s};return W.runKernel(Nc,r)}var Zl=V({mod_:pO});function hO(e,t=null,n=!1){e=D(e,"x","moments");let s=ur(t,e.shape),r=Bt(e,s,n),a=r.shape;n||(a=Yi(r.shape,s));let o=vt(he(ge(e,"float32"),U(r,a))),i=Bt(o,s,n);return{mean:r,variance:i}}var fh=V({moments_:hO});function fO(e,t,n,s){let r=D(t,"data","multiRNNCell"),a=Ip(n,"c","multiRNNCell"),o=Ip(s,"h","multiRNNCell"),i=r,l=[];for(let p=0;p<e.length;p++){let d=e[p](i,a[p],o[p]);l.push(d[0]),l.push(d[1]),i=d[1]}let u=[],c=[];for(let p=0;p<l.length;p+=2)u.push(l[p]),c.push(l[p+1]);return[u,c]}var Aw=V({multiRNNCell_:fO});function mO(e,t,n,s=!1){let r=D(e,"logits","multinomial"),a=r.size,o=r.rank;if(a<2)throw new Error(`Error in multinomial: you need at least 2 outcomes, but got ${a}.`);if(o>2)throw new Error(`Rank of probabilities must be 1 or 2, but is ${o}`);n=n||Math.random();let l={logits:o===1?U(r,[1,-1]):r},u={numSamples:t,seed:n,normalized:s},c=W.runKernel(l0,l,u);return o===1?U(c,[c.size]):c}var xw=V({multinomial_:mO});function gO(e,t){let n=D(e,"a","notEqual","string_or_numeric"),s=D(t,"b","notEqual","string_or_numeric");[n,s]=Gt(n,s),kt(n.shape,s.shape);let r={a:n,b:s};return W.runKernel(Il,r)}var Ji=V({notEqual_:gO});function yO(e){let n={x:D(e,"x","onesLike")};return W.runKernel(Tl,n)}var $s=V({onesLike_:yO});function AO(e,t){let n=D(e,"v1","outerProduct"),s=D(t,"v2","outerProduct");M(n.rank===1&&s.rank===1,()=>`Error in outerProduct: inputs must be rank 1, but got ranks ${n.rank} and ${s.rank}.`);let r=U(n,[-1,1]),a=U(s,[1,-1]);return Qe(r,a)}var bw=V({outerProduct_:AO});function xO(e,t,n=0){let s=D(e,"x","pad");if(s.rank===0)throw new Error("pad(scalar) is not defined. Pass non-scalar to pad");let r={paddings:t,constantValue:n},a={x:s};return W.runKernel(Wo,a,r)}var Js=V({pad_:xO});function bO(e,t,n=0){return M(t.length===2,()=>"Invalid number of paddings. Must be length of 2."),Js(e,[t],n)}var vw=V({pad1d_:bO});function vO(e,t,n=0){return M(t.length===2&&t[0].length===2&&t[1].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),Js(e,t,n)}var ww=V({pad2d_:vO});function wO(e,t,n=0){return M(t.length===3&&t[0].length===2&&t[1].length===2&&t[2].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),Js(e,t,n)}var kw=V({pad3d_:wO});function kO(e,t,n=0){return M(t.length===4&&t[0].length===2&&t[1].length===2&&t[2].length===2&&t[3].length===2,()=>"Invalid number of paddings. Must be length of 2 each."),Js(e,t,n)}var Iw=V({pad4d_:kO});function IO(e,t,n){let s=D(e,"x","spaceToBatchND");M(s.rank>=1+t.length,()=>`input rank ${s.rank} should be > than [blockShape] ${t.length}`),M(n.length===t.length,()=>`paddings.shape[0] ${n.length} must be equal to [blockShape] ${t.length}`),M(s.shape.reduce((o,i,l)=>l>0&&l<=t.length?o&&(i+n[l-1][0]+n[l-1][1])%t[l-1]===0:o,!0),()=>`input spatial dimensions ${s.shape.slice(1)} with paddings ${n.toString()} must be divisible by blockShapes ${t.toString()}`);let r={x:s},a={blockShape:t,paddings:n};return W.runKernel(Ml,r,a)}var mh=V({spaceToBatchND_:IO});function SO(e,t,n,s,r,a,o){r==null&&(r=[1,1]),a==null&&(a=1),s===0&&(s="valid");let i=D(e,"x","maxPool"),l=i,u=!1;i.rank===3&&(u=!0,l=U(i,[1,i.shape[0],i.shape[1],i.shape[2]])),M(Zr(a,r),()=>`Error in pool: Either strides or dilations must be 1. Got strides ${a} and dilations '${r}'`);let c=ew(l.shape,t,a,r,s),p=[c.dilationHeight,c.dilationWidth],d;s==="same"?d=TO([c.filterHeight,c.filterWidth],p):d=[[0,0],[0,0]];let h=p[0]===1&&p[1]===1,[f,m]=CO([c.inHeight,c.inWidth],p,d),g=h?s:"valid",y=h?l:mh(l,p,f),A=(n==="avg"?()=>ih(y,t,a,g,o):()=>hh(y,t,a,g,o))(),b=h?A:lh(A,p,m);return u?U(b,[b.shape[1],b.shape[2],b.shape[3]]):b}function CO(e,t,n){let s=n.map(c=>c[0]),r=n.map(c=>c[1]),a=e.concat(s,r),o=t.map((c,p)=>(c-a[p]%c)%c),i=r.map((c,p)=>c+o[p]),l=t.map((c,p)=>[s[p],i[p]]),u=t.map((c,p)=>[0,o[p]]);return[l,u]}function TO(e,t){let s=e.map((o,i)=>o+(o-1)*(t[i]-1)).map(o=>o-1),r=s.map(o=>Math.floor(o/2)),a=s.map((o,i)=>o-r[i]);return s.map((o,i)=>[r[i],a[i]])}var EA=V({pool_:SO});function NO(e,t){let n=D(e,"x","prelu"),s=D(t,"alpha","prelu"),r={x:n,alpha:s};return W.runKernel(Uo,r)}var gh=V({prelu_:NO});function EO(e,t=null,n=!1){let s=D(e,"x","prod");s.dtype==="bool"&&(s=ge(s,"int32"));let r={x:s},a={axis:t,keepDims:n};return W.runKernel(Go,r,a)}var RA=V({prod_:EO});function RO(e,t,n){let s=Et(e),r=null;if(n==null||n==="float32")r=new Float32Array(s);else if(n==="int32")r=new Int32Array(s);else if(n==="bool")r=new Uint8Array(s);else throw new Error(`Unknown data type ${n}`);for(let a=0;a<s;a++)r[a]=t();return W.makeTensor(r,e,n)}var Sw=V({rand_:RO}),_A=lo(Bm()),DA=class{constructor(e,t,n,s,r){this.mean=e,this.stdDev=t,this.dtype=n,this.nextVal=NaN,this.truncated=s,this.truncated&&(this.upper=this.mean+this.stdDev*2,this.lower=this.mean-this.stdDev*2);let a=r||Math.random();this.random=_A.alea(a.toString())}nextValue(){if(!isNaN(this.nextVal)){let s=this.nextVal;return this.nextVal=NaN,s}let e,t,n=!1;for(;!n;){let s,r,a;do s=2*this.random()-1,r=2*this.random()-1,a=s*s+r*r;while(a>=1||a===0);let o=Math.sqrt(-2*Math.log(a)/a);e=this.mean+this.stdDev*s*o,t=this.mean+this.stdDev*r*o,(!this.truncated||this.isValidTruncated(e))&&(n=!0)}return(!this.truncated||this.isValidTruncated(t))&&(this.nextVal=this.convertValue(t)),this.convertValue(e)}convertValue(e){return this.dtype==null||this.dtype==="float32"?e:Math.round(e)}isValidTruncated(e){return e<=this.upper&&e>=this.lower}},_O=class{constructor(e,t,n,s){this.alpha=e,this.beta=1/t,this.dtype=n;let r=s||Math.random();this.randu=_A.alea(r.toString()),this.randn=new DA(0,1,n,!1,this.randu()),e<1?this.d=e+2/3:this.d=e-1/3,this.c=1/Math.sqrt(9*this.d)}nextValue(){let e,t,n,s,r,a;for(;;){do s=this.randn.nextValue(),a=1+this.c*s;while(a<=0);if(a*=a*a,e=s*s,t=1-.331*e*e,n=.5*e+this.d*(1-a+Math.log(a)),r=this.randu(),r<t||Math.log(r)<n)break}return a=1/this.beta*this.d*a,this.alpha<1&&(a*=Math.pow(this.randu(),1/this.alpha)),this.convertValue(a)}convertValue(e){return this.dtype==="float32"?e:Math.round(e)}},DO=class{constructor(e=0,t=1,n,s){if(this.canReturnFloat=()=>this.dtype==null||this.dtype==="float32",this.min=e,this.range=t-e,this.dtype=n,s==null&&(s=Math.random()),typeof s=="number"&&(s=s.toString()),!this.canReturnFloat()&&this.range<=1)throw new Error(`The difference between ${e} - ${t} <= 1 and dtype is not float`);this.random=_A.alea(s)}convertValue(e){return this.canReturnFloat()?e:Math.round(e)}nextValue(){return this.convertValue(this.min+this.range*this.random())}};function $O(e,t,n=1,s="float32",r){if(n==null&&(n=1),s==null&&(s="float32"),s!=="float32"&&s!=="int32")throw new Error(`Unsupported data type ${s}`);let a=new _O(t,n,s,r),o=Le(e,s);for(let i=0;i<o.values.length;i++)o.values[i]=a.nextValue();return o.toTensor()}var Cw=V({randomGamma_:$O});function PO(e,t=0,n=1,s,r){if(s!=null&&s==="bool")throw new Error(`Unsupported data type ${s}`);let a=new DA(t,n,s,!1,r),o=Le(e,s);for(let i=0;i<o.values.length;i++)o.values[i]=a.nextValue();return o.toTensor()}var T0=V({randomNormal_:PO});function FO(e,t,n){if(t!=null&&t==="bool")throw new Error(`Unsupported data type ${t}`);return T0(e,0,1,t,n)}var Tw=V({randomStandardNormal_:FO});function OO(e,t=0,n=1,s="float32",r){let a=Le(e,s),o=new DO(t,n,null,r);for(let i=0;i<a.values.length;i++)a.values[i]=o.nextValue();return a.toTensor()}var Xc=V({randomUniform_:OO});function Yu(e,t,n=1,s="float32"){if(n===0)throw new Error("Cannot have a step of zero");let r={start:e,stop:t,step:n,dtype:s};return W.runKernel(Rc,{},r)}function MO(e){let n={x:D(e,"x","reciprocal")};return W.runKernel(_c,n)}var $A=V({reciprocal_:MO});function zO(e){let n={x:D(e,"x","relu")};return W.runKernel(Ho,n)}var $r=V({relu_:zO});function LO(e){let n={x:D(e,"x","relu6")};return W.runKernel(Xo,n)}var N0=V({relu6_:LO});function BO(e,t){let s={x:D(e,"x","reverse")},r={dims:t};return W.runKernel(_l,s,r)}var Ks=V({reverse_:BO});function WO(e){let t=D(e,"x","reverse");return M(t.rank===1,()=>`Error in reverse1D: x must be rank 1 but got rank ${t.rank}.`),Ks(t,0)}var Nw=V({reverse1d_:WO});function VO(e,t){let n=D(e,"x","reverse");return M(n.rank===2,()=>`Error in reverse2D: x must be rank 2 but got rank ${n.rank}.`),Ks(n,t)}var Ew=V({reverse2d_:VO});function UO(e,t){let n=D(e,"x","reverse");return M(n.rank===3,()=>`Error in reverse3D: x must be rank 3 but got rank ${n.rank}.`),Ks(n,t)}var Rw=V({reverse3d_:UO});function GO(e,t){let n=D(e,"x","reverse");return M(n.rank===4,()=>`Error in reverse4D: x must be rank 4 but got rank ${n.rank}.`),Ks(n,t)}var _w=V({reverse4d_:GO});function HO(e){let n={x:D(e,"x","round")};return W.runKernel(Dl,n)}var E0=V({round_:HO});function jO(e){let n={x:D(e,"x","rsqrt","float32")};return W.runKernel(Ko,n)}var R0=V({rsqrt_:jO});function qO(e){let n={x:D(e,"x","selu")};return W.runKernel(Dc,n)}var _0=V({selu_:qO});function XO(e,t,n,s,r,a=[1,1],o="NHWC"){let i=D(e,"x","separableConv2d"),l=D(t,"depthwiseFilter","separableConv2d"),u=D(n,"pointwiseFilter","separableConv2d"),c=i,p=!1;if(i.rank===3&&(p=!0,c=U(i,[1,i.shape[0],i.shape[1],i.shape[2]])),o==="NCHW")throw new Error("separableConv2d currently does not support dataFormat NCHW; only NHWC is supported");M(c.rank===4,()=>`Error in separableConv2d: input must be rank 4, but got rank ${c.rank}.`),M(l.rank===4,()=>`Error in separableConv2d: depthwise filter must be rank 4, but got rank ${l.rank}.`),M(u.rank===4,()=>`Error in separableConv2d: pointwise filter must be rank 4, but got rank ${l.rank}.`),M(u.shape[0]===1,()=>`Error in separableConv2d: the first dimension of pointwise filter  must be 1, but got ${u.shape[0]}.`),M(u.shape[1]===1,()=>`Error in separableConv2d: the second dimension of pointwise filter must be 1, but got ${u.shape[1]}.`);let d=l.shape[2],h=l.shape[3];M(u.shape[2]===d*h,()=>`Error in separableConv2d: the third dimension of pointwise filter must be ${d*h}, but got ${u.shape[2]}.`);let f=Wc(c,l,s,r,o,a),g=fa(f,u,1,"valid",o);return p?U(g,[g.shape[1],g.shape[2],g.shape[3]]):g}var D0=V({separableConv2d_:XO});async function KO(e,t){let n=D(e,"x","setdiff1d"),s=D(t,"y","setdiff1d");M(n.dtype===s.dtype,()=>`x and y should have the same dtype, but got x (${n.dtype}) and y (${s.dtype}).`),M(n.rank===1,()=>`x should be 1D tensor, but got x (${n.shape}).`),M(s.rank===1,()=>`y should be 1D tensor, but got y (${s.shape}).`);let r=await n.data(),a=await s.data(),o=new Set(a),i=0;for(let c=0;c<r.length;c++)o.has(r[c])||i++;let l=new fn([i],n.dtype),u=new fn([i],"int32");for(let c=0,p=0;c<r.length;c++)o.has(r[c])||(l.values[p]=r[c],u.values[p]=c,p++);return[l.toTensor(),u.toTensor()]}var Dw=KO;function ZO(e){let n={x:D(e,"x","sign")};return W.runKernel($c,n)}var PA=V({sign_:ZO});function YO(e){let n={x:D(e,"x","sin","float32")};return W.runKernel(Zo,n)}var $0=V({sin_:YO});function JO(e){let n={x:D(e,"x","sinh")};return W.runKernel(Ol,n)}var P0=V({sinh_:JO});function QO(e,t,n){let s=D(e,"x","slice1d");return M(s.rank===1,()=>`slice1d expects a rank-1 tensor, but got a rank-${s.rank} tensor`),Oe(s,[t],[n])}var yh=V({slice1d_:QO});function eM(e,t,n){let s=D(e,"x","slice2d");return M(s.rank===2,()=>`slice2d expects a rank-2 tensor, but got a rank-${s.rank} tensor`),Oe(s,t,n)}var F0=V({slice2d_:eM});function tM(e,t,n){let s=D(e,"x","slice3d");return M(s.rank===3,()=>`slice3d expects a rank-3 tensor, but got a rank-${s.rank} tensor`),Oe(s,t,n)}var ui=V({slice3d_:tM});function nM(e,t,n){let s=D(e,"x","slice4d");return M(s.rank===4,()=>`slice4d expects a rank-4 tensor, but got a rank-${s.rank} tensor`),Oe(s,t,n)}var to=V({slice4d_:nM});function sM(e,t=-1){let n=D(e,"logits","softmax","float32");if(t===-1&&(t=n.rank-1),t!==n.rank-1)throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${n.rank} and dim was ${t}`);let s={logits:n},r={dim:t};return W.runKernel(ei,s,r)}var Yl=V({softmax_:sM});function rM(e){M(e.dtype==="complex64",()=>`The dtype for tf.spectral.fft() must be complex64 but got ${e.dtype}.`);let t={input:e};return W.runKernel(t0,t)}var Ah=V({fft_:rM});function aM(e){M(e.dtype==="complex64",()=>`The dtype for tf.spectral.ifft() must be complex64 but got ${e.dtype}.`);let t={input:e};return W.runKernel(n0,t)}var Ju=V({ifft_:aM});function oM(e){let t=e.shape[e.shape.length-1],n=e.size/t,s;if(t<=2){let r=U(e,[n,t]);s=Ju(r)}else{let r=[n,2*(t-1)],a=U(Zu(e),[n,t]),o=U(ah(e),[n,t]),i=Ks(Oe(a,[0,1],[n,t-2]),1),l=L(Ks(Oe(o,[0,1],[n,t-2]),1),Se(-1)),u=Ct([a,i],1),c=Ct([o,l],1),p=U(ha(u,c),[r[0],r[1]]);s=Ju(p)}if(s=Zu(s),e.rank===3&&e.shape[0]!==0){let r=s,a=e.shape[0];s=U(s,[a,s.shape[0]/a,s.shape[1]]),r.dispose()}return s}var O0=V({irfft_:oM});function iM(e,t,n=0){let r={x:D(e,"x","split")},a={numOrSizeSplits:t,axis:n};return W.runKernel(zl,r,a)}var Zt=V({split_:iM});function lM(e,t){M(e.dtype==="float32",()=>`The dtype for rfft() must be real value but got ${e.dtype}`);let n=e.shape[e.shape.length-1],s=e.size/n,r;if(t!=null&&t<n){let f=e.shape.map(g=>0),m=e.shape.map(g=>g);m[e.shape.length-1]=t,r=Oe(e,f,m),n=t}else if(t!=null&&t>n){let f=e.shape.map(m=>m);f[e.shape.length-1]=t-n,r=Ct([e,Wt(f)],e.shape.length-1),n=t}else r=e;let a=it(r),o=U(ha(r,a),[s,n]),i=Ah(o),l=Math.floor(n/2)+1,u=Zu(i),c=ah(i),p=Zt(u,[l,n-l],u.shape.length-1),d=Zt(c,[l,n-l],c.shape.length-1),h=r.shape.slice();return h[r.shape.length-1]=l,U(ha(p[0],d[0]),h)}var xh=V({rfft_:lM});function uM(e,t){let n=D(e,"a","squaredDifference"),s=D(t,"b","squaredDifference");[n,s]=Gt(n,s),kt(n.shape,s.shape);let r={a:n,b:s},a={};return W.runKernel(ti,r,a)}var M0=V({squaredDifference_:uM});function cM(e,t){let n=D(e,"x","squeeze","string_or_numeric");return U(n,Q7(n.shape,t).newShape)}var rt=V({squeeze_:cM});function dM(e,t=0){let n=Ip(e,"tensors","stack","string_or_numeric");M(n.length>=1,()=>"Pass at least one tensor to tf.stack"),n.length>0&&M(t<=n[0].rank,()=>"Axis must be <= rank of the tensor");let s=n,r={axis:t};return W.runKernel(El,s,r)}var on=V({stack_:dM});function pM(e,t=0){let s={x:D(e,"x","step")},r={alpha:t};return W.runKernel(ri,s,r)}var Jl=V({step_:pM});function hM(e,t,n,s,r=0,a=0,o=0,i=0,l=0){let c={x:D(e,"x","stridedSlice","string_or_numeric")},p={begin:t,end:n,strides:s,beginMask:r,endMask:a,ellipsisMask:o,newAxisMask:i,shrinkAxisMask:l};return W.runKernel(Ll,c,p)}var FA=V({stridedSlice_:hM});function fM(e){let n={x:D(e,"x","tan","float32")};return W.runKernel(Bl,n)}var OA=V({tan_:fM});function Ft(e,t){al(e);let n=qr(e,t);if(n.length!==1)throw new Error("tensor1d() requires values to be a flat/TypedArray");return ai(e,null,n,t)}function or(e,t,n){if(al(e),t!=null&&t.length!==2)throw new Error("tensor2d() requires shape to have two numbers");let s=qr(e,n);if(s.length!==2&&s.length!==1)throw new Error("tensor2d() requires values to be number[][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor2d() requires shape to be provided when `values` are a flat/TypedArray");return ai(e,t,s,n)}function $w(e,t,n){if(al(e),t!=null&&t.length!==4)throw new Error("tensor4d() requires shape to have four numbers");let s=qr(e,n);if(s.length!==4&&s.length!==1)throw new Error("tensor4d() requires values to be number[][][][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor4d() requires shape to be provided when `values` are a flat array");return ai(e,t,s,n)}function Pw(e,t,n){if(al(e),t!=null&&t.length!==5)throw new Error("tensor5d() requires shape to have five numbers");let s=qr(e,n);if(s.length!==5&&s.length!==1)throw new Error("tensor5d() requires values to be number[][][][][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor5d() requires shape to be provided when `values` are a flat array");return ai(e,t,s,n)}function Fw(e,t,n){if(al(e),t!=null&&t.length!==6)throw new Error("tensor6d() requires shape to have six numbers");let s=qr(e,n);if(s.length!==6&&s.length!==1)throw new Error("tensor6d() requires values to be number[][][][][][] or flat/TypedArray");if(s.length===1&&t==null)throw new Error("tensor6d() requires shape to be provided when `values` are a flat array");return t=t||s,ai(e,t,s,n)}function mM(e,t=1,n=!0){let s=D(e,"x","topk");if(s.rank===0)throw new Error("topk() expects the input to be of rank 1 or higher");let r=s.shape[s.shape.length-1];if(t<0)throw new Error(`'k' passed to topk() must be >= 0 but got ${t}`);if(t>r)throw new Error(`'k' passed to topk() must be <= the last dimension (${r}) but got ${t}`);let a={x:s},o={k:t,sorted:n},[i,l]=W.runKernel(Wl,a,o);return{values:i,indices:l}}var MA=V({topk_:mM});function gM(e,t=0,n=1,s,r){if(s!=null&&s==="bool")throw new Error("Unsupported data type $ { dtype }");let a=new DA(t,n,s,!0,r),o=Le(e,s);for(let i=0;i<o.values.length;i++)o.values[i]=a.nextValue();return o.toTensor()}var z0=V({truncatedNormal_:gM});function yM(e,t=0){let n=D(e,"x","unique","string_or_numeric");M(n.rank>0,()=>"The input tensor must be at least 1D");let s={x:n},r={axis:t},[a,o]=W.runKernel(p0,s,r);return{values:a,indices:o}}var zA=V({unique_:yM});function AM(e,t,n){let s=D(e,"x","unsortedSegmentSum"),r=D(t,"segmentIds","unsortedSegmentSum","int32");M(ju(n),()=>"numSegments must be of dtype int");let a={x:s,segmentIds:r},o={numSegments:n};return W.runKernel(Qp,a,o)}var L0=V({unsortedSegmentSum_:AM});function xM(e,t=0){let n=D(e,"x","unstack","string_or_numeric");M(t>=-n.shape.length&&t<n.shape.length,()=>`Axis = ${t} is not in [-${n.shape.length}, ${n.shape.length})`);let s={value:n},r={axis:t};return W.runKernel(Ul,s,r)}var es=V({unstack_:xM});function Ow(e,t){return C0(e,t,"right")}function LA(e,t=!0,n,s){return W.makeVariable(e,t,n,s)}function Mw(e,t){let n=[];for(let a=0;a<t.length;a++)t[a]&&n.push(a);let s=Le(e,"int32"),r=Le([n.length,e.length],"int32");for(let a=0;a<n.length;a++){let o=s.indexToLoc(n[a]),i=a*e.length;r.values.set(o,i)}return r.toTensor()}async function bM(e){let t=D(e,"condition","whereAsync","bool"),n=await t.data(),s=Mw(t.shape,n);return e!==t&&t.dispose(),s}var BA=bM;async function vM(e,t,n){let s=D(e,"tensor","boolMask"),r=D(t,"mask","boolMask","bool"),a=n==null?0:n,o=r.rank,i=s.shape;M(o>0,()=>"mask cannot be scalar"),ns(i.slice(a,a+o),r.shape,"mask's shape must match the first K dimensions of tensor's shape,");let l=1;for(let m=a;m<a+o;m++)l*=i[m];let u=i.slice(0,a).concat([l],i.slice(a+o)),c=U(s,u),p=U(r,[-1]),d=await BA(p),h=rt(d,[1]),f=jc(c,h,a);return e!==s&&s.dispose(),t!==r&&r.dispose(),h.dispose(),c.dispose(),p.dispose(),d.dispose(),f}var zw=vM;function wM(e,t,n,s,r=!0){let a=D(e,"v","movingAverage"),o=D(t,"x","movingAverage"),i=D(n,"decay","movingAverage");y6(a,o),M(uo(a.shape,o.shape),()=>"Shape mismatch in v and x");let l=Se(1),u=he(l,i),c=L(he(o,a),u);if(r){M(s!=null,()=>"When using zeroDebias: true, step is required.");let p=D(s,"step","movingAverage");c=pe(c,he(l,ga(i,p)))}return ce(a,c)}var Lw=V({movingAverage_:wM});function kM(e,t,n){let s=D(e,"indices","scatterND","int32"),r=D(t,"updates","scatterND");Wy(r,s,n);let a={indices:s,updates:r},o={shape:n};return W.runKernel($l,a,o)}var Bw=V({scatterND_:kM});function IM(e,t,n,s){if(e.dtype!=="int32")throw new Error(`tf.sparseToDense() expects the indices to be int32 type, but the dtype was ${e.dtype}.`);if(e.rank>2)throw new Error(`sparseIndices should be a scalar, vector, or matrix, but got shape ${e.shape}.`);let r=e.rank>0?e.shape[0]:1,a=e.rank>1?e.shape[1]:1;if(n.length!==a)throw new Error(`outputShape has incorrect number of elements:, ${n.length}, should be: ${a}.`);let o=t.size;if(!(t.rank===0||t.rank===1&&o===r))throw new Error(`sparseValues has incorrect shape ${t.shape}, should be [] or [${r}]`);if(t.dtype!==s.dtype)throw new Error("sparseValues.dtype must match defaultValues.dtype")}function SM(e,t,n,s=0){let r=D(e,"sparseIndices","sparseToDense","int32"),a=D(t,"sparseValues","sparseToDense","string_or_numeric"),o=D(s,"defaultValue","sparseToDense",a.dtype);IM(r,a,n,o);let i={sparseIndices:r,sparseValues:a,defaultValue:o},l={outputShape:n};return W.runKernel(Zp,i,l)}var Ww=V({sparseToDense_:SM});function CM(e,t){let n=D(t,"indices","gatherND","int32"),r={params:D(e,"x","gatherND","string_or_numeric"),indices:n};return W.runKernel(yl,r)}var Vw=V({gatherND_:CM});function TM(e,t){if(t==null)return e.shape.slice();if(uo(e.shape,t))return t;if(e.shape.length===t.length){let n=[];for(let s=0;s<e.shape.length;s++)t[s]==null&&e.shape[s]!=null?n.push(e.shape[s]):n.push(t[s]);return n}return t}function NM(e,t,n,s){let r=D(e,"x","dropout");if(M(r.dtype==="float32",()=>`x has to be a floating point tensor since it's going to be scaled, but got a ${r.dtype} tensor instead.`),M(t>=0&&t<1,()=>`rate must be a float in the range [0, 1), but got ${t}.`),t===0)return e instanceof tt?r.clone():r;let a=TM(r,n),o=1-t,i=pe(Hc(ce(Xc(a,0,1,"float32",s),o)),o);return L(r,i)}var WA=V({dropout_:NM});function VA(e){return Math.floor(Math.pow(2,Math.ceil(Math.log(e)/Math.log(2))))}function B0(e,t,n){let s=1-e%2,r=new Float32Array(e);for(let a=0;a<e;++a){let o=2*Math.PI*a/(e+s-1);r[a]=t-n*Math.cos(o)}return Ft(r,"float32")}async function EM(e,t,n=1){let s=D(e,"predictions","inTopK"),r=D(t,"targets","inTopK");M(s.rank>1,()=>`inTopK() expects the predictions to be of rank 2 or higher, but got ${s.rank}`),M(s.rank-1===r.rank,()=>`predictions rank should be 1 larger than targets rank, but got predictions rank ${s.rank} and targets rank ${r.rank}`),ns(s.shape.slice(0,s.shape.length-1),r.shape,"predictions's shape should be align with the targets' shape, except the last dimension.");let a=s.shape[s.shape.length-1];M(n>0&&n<=a,()=>`'k' passed to inTopK() must be > 0 && <= the predictions last dimension (${a}), but got ${n}`);let o=await s.data(),i=await r.data(),[l,u]=[o.length/a,a],c=e6("bool",l);for(let p=0;p<l;p++){let d=p*u,h=o.subarray(d,d+u),f=[];for(let m=0;m<h.length;m++)f.push({value:h[m],index:m});f.sort((m,g)=>g.value-m.value),c[p]=0;for(let m=0;m<n;m++)if(f[m].index===i[p]){c[p]=1;break}}return e!==s&&s.dispose(),t!==r&&r.dispose(),ft(c,r.shape,"bool")}var Uw=EM,Qu={};Ve(Qu,{conv2d:()=>DM,depthwiseConv2d:()=>OM,matMul:()=>zM});function RM(e,t,n,s,r,a="NHWC",o){let i=e;e.rank===3&&(i=U(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let l=t;l.rank===3&&(l=U(t,[1,t.shape[0],t.shape[1],t.shape[2]])),M(i.rank===4,()=>`Error in conv2dDerFilter: input must be rank 4, but got shape ${i.shape}.`),M(l.rank===4,()=>`Error in conv2dDerFilter: dy must be rank 4, but got shape ${l.shape}.`),M(n.length===4,()=>`Error in conv2dDerFilter: filterShape must be length 4, but got ${n}.`);let u=a==="NHWC"?i.shape[3]:i.shape[1],c=a==="NHWC"?l.shape[3]:l.shape[1];M(u===n[2],()=>`Error in conv2dDerFilter: depth of input ${u}) must match input depth in filter (${n[2]}.`),M(c===n[3],()=>`Error in conv2dDerFilter: depth of dy (${c}) must match output depth for filter (${n[3]}).`),rs("conv2dDerFilter",r,o);let p={x:i,dy:l},d={strides:s,pad:r,dataFormat:a,dimRoundingMode:o,filterShape:n};return W.runKernel(qm,p,d)}var UA=V({conv2DBackpropFilter_:RM});function W0(e,t,n){if(n==null||n==="linear")return e;if(n==="relu")return L(e,Jl(t));throw new Error(`Cannot compute gradient for fused activation ${n}.`)}function V0(e,t){let n=t,s=an(e.shape,t.shape);return s.length>0&&(n=ke(n,s)),U(n,e.shape)}function U0(e,t,n,s){if(t==="linear")return e;if(t==="relu")return $r(e);if(t==="elu")return Vc(e);if(t==="relu6")return N0(e);if(t==="prelu")return gh(e,n);if(t==="leakyrelu")return ch(e,s);if(t==="sigmoid")return Cn(e);throw new Error(`Unknown fused activation ${t}.`)}var G0=(e,t)=>!(e>0)||t==="linear";function _M({x:e,filter:t,strides:n,pad:s,dataFormat:r="NHWC",dilations:a=[1,1],dimRoundingMode:o,bias:i,activation:l="linear",preluActivationWeights:u,leakyreluAlpha:c}){if(l=l||"linear",G0(W.state.gradientDepth,l)===!1){M(r==="NHWC",()=>`Error in fused conv2d: got dataFormat of ${r} but only NHWC is currently supported for the case of gradient depth is 0 and the activation is not linear.`);let k=fa(e,t,n,s,r,a,o);return i!=null&&(k=ce(k,i)),U0(k,l,u,c)}let p=D(e,"x","conv2d","float32"),d=D(t,"filter","conv2d","float32"),h=p,f=!1;p.rank===3&&(f=!0,h=U(p,[1,p.shape[0],p.shape[1],p.shape[2]])),M(h.rank===4,()=>`Error in fused conv2d: input must be rank 4, but got rank ${h.rank}.`),M(d.rank===4,()=>`Error in fused conv2d: filter must be rank 4, but got rank ${d.rank}.`),rs("fused conv2d",s,o);let m=r==="NHWC"?h.shape[3]:h.shape[1];M(d.shape[2]===m,()=>`Error in conv2d: depth of input (${m}) must match input depth for filter ${d.shape[2]}.`),M(Zr(n,a),()=>`Error in conv2D: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`);let g=oh(h.shape,d.shape,n,a,s,o),y;i!=null&&(y=D(i,"bias","fused conv2d"),[y]=Gt(y,p),r==="NHWC"?kt(g.outShape,y.shape):(M(y.shape.length<=1,()=>`Error in fused conv2d: only supports scalar or 1-D Tensor bias for NCHW format but got the bias of rank-${y.shape.length}.`),M(y.shape.length===0||y.shape[0]===g.outChannels||y.shape[0]===1,()=>`Error in fused conv2d: bias shape (${y.shape}) is not compatible with the number of output channels (${g.outChannels})`)));let x;if(u!=null){let k=u.shape;if(M(k.length<=1||k.length===3,()=>`Error in fused conv2d: only supports scalar, 1-D Tensor or 3-D Tensor PReLU activation weights but got a tensor of rank-${k.length}.`),k.length===1)M(k[0]===1||k[0]===g.outChannels,()=>`Error in fused conv2d: PReLU activation weights (${k}) is not compatible with the number of output channels (${g.outChannels}).`);else if(k.length===3)try{kt(k,g.outShape)}catch(S){let E=`Error in fused conv2d: PReLU activation weights (${k}) is not compatible with the output shape of the conv2d (${g.outShape}).`;throw Error(E)}x=D(u,"prelu weights","fused conv2d")}let A=(k,S)=>{M(r==="NHWC",()=>`Error in gradient of fused conv2D: got dataFormat of ${r} but only NHWC is currently supported.`);let[E,R,P,_]=S,$=W0(k,P,l);M(eo(a),()=>`Error in gradient of fused conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${a}'`);let T=uA(R.shape,$,E,n,s),F=UA(R,$,E.shape,n,s),G=[T,F];if(_!=null){let q=V0(_,$);G.push(q)}return G},b={x:h,filter:d,bias:y,preluActivationWeights:x},w={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:o,activation:l,leakyreluAlpha:c};return i==null?Xr((S,E,R)=>{let P=W.runKernel(Ja,b,w);return R([E,S,P]),f&&(P=U(P,[P.shape[1],P.shape[2],P.shape[3]])),{value:P,gradFunc:A}})(h,d):Xr((S,E,R,P)=>{let _=W.runKernel(Ja,b,w);return P([E,S,_,R]),f&&(_=U(_,[_.shape[1],_.shape[2],_.shape[3]])),{value:_,gradFunc:A}})(h,d,y)}var DM=V({fusedConv2d_:_M});function $M(e,t,n,s,r,a=[1,1],o){let i=e;e.rank===3&&(i=U(e,[1,e.shape[0],e.shape[1],e.shape[2]]));let l=t;l.rank===3&&(l=U(t,[1,t.shape[0],t.shape[1],t.shape[2]]));let u={x:i,dy:l},c={strides:s,pad:r,dimRoundingMode:o,dilations:a,filterShape:n};return W.runKernel(Ym,u,c)}var Gw=V({depthwiseConv2dNativeBackpropFilter_:$M});function PM(e,t,n,s,r,a=[1,1],o){let i=t,l=!1;t.rank===3&&(l=!0,i=U(t,[1,t.shape[0],t.shape[1],t.shape[2]]));let u={dy:i,filter:n},c={strides:s,pad:r,dimRoundingMode:o,dilations:a,inputShape:e},p=W.runKernel(Jm,u,c);return l?U(p,[p.shape[1],p.shape[2],p.shape[3]]):p}var Hw=V({depthwiseConv2dNativeBackpropInput_:PM});function FM({x:e,filter:t,strides:n,pad:s,dataFormat:r="NHWC",dilations:a=[1,1],dimRoundingMode:o,bias:i,activation:l="linear",preluActivationWeights:u,leakyreluAlpha:c}){if(G0(W.state.gradientDepth,l)===!1){let w=Wc(e,t,n,s,r,a,o);return i!=null&&(w=ce(w,i)),U0(w,l,u,c)}let p=D(e,"x","depthwiseConv2d","float32"),d=D(t,"filter","depthwiseConv2d","float32"),h=p,f=!1;p.rank===3&&(f=!0,h=U(p,[1,p.shape[0],p.shape[1],p.shape[2]])),M(h.rank===4,()=>`Error in fused depthwiseConv2d: input must be rank 4, but got rank ${h.rank}.`),M(d.rank===4,()=>`Error in fused depthwiseConv2d: filter must be rank 4, but got rank ${d.rank}.`),M(h.shape[3]===d.shape[2],()=>`Error in fused depthwiseConv2d: number of input channels (${h.shape[3]}) must match the inChannels dimension in filter ${d.shape[2]}.`),a==null&&(a=[1,1]),M(Zr(n,a),()=>`Error in fused depthwiseConv2d: Either strides or dilations must be 1. Got strides ${n} and dilations '${a}'`),rs("fused depthwiseConv2d",s,o);let m=oh(h.shape,d.shape,n,a,s,o,!0),g;i!=null&&(g=D(i,"bias","fused conv2d"),[g]=Gt(g,p),kt(m.outShape,g.shape));let y;u!=null&&(y=D(u,"prelu weights","fused depthwiseConv2d"));let x=(w,k)=>{M(eo(a),()=>`Error in gradient of fused depthwiseConv2d: dilation rates greater than 1 are not yet supported. Got dilations '${a}'`);let[S,E,R,P]=k,_=W0(w,R,l),$=Hw(E.shape,_,S,n,s,a,o),T=Gw(E,_,S.shape,n,s,a,o);if(P!=null){let F=V0(g,_);return[$,T,F]}return[$,T]},A={x:h,filter:d,bias:g,preluActivationWeights:y},b={strides:n,pad:s,dataFormat:r,dilations:a,dimRoundingMode:o,activation:l,leakyreluAlpha:c};return i==null?Xr((k,S,E)=>{let R=W.runKernel(Qa,A,b);return E([S,k,R]),f&&(R=U(R,[R.shape[1],R.shape[2],R.shape[3]])),{value:R,gradFunc:x}})(h,d):Xr((k,S,E,R)=>{let P=W.runKernel(Qa,A,b);return R([S,k,P,E]),f&&(P=U(P,[P.shape[1],P.shape[2],P.shape[3]])),{value:P,gradFunc:x}})(h,d,g)}var OM=V({fusedDepthwiseConv2d_:FM});function MM({a:e,b:t,transposeA:n=!1,transposeB:s=!1,bias:r,activation:a="linear",preluActivationWeights:o,leakyreluAlpha:i=.2}){if(G0(W.state.gradientDepth,a)===!1){let _=Qe(e,t,n,s);return r!=null&&(_=ce(_,r)),U0(_,a,o,i)}let l=D(e,"a","fused matMul"),u=D(t,"b","fused matMul");[l,u]=Gt(l,u);let c=n?l.shape[l.rank-2]:l.shape[l.rank-1],p=s?u.shape[u.rank-1]:u.shape[u.rank-2],d=n?l.shape[l.rank-1]:l.shape[l.rank-2],h=s?u.shape[u.rank-2]:u.shape[u.rank-1],f=l.shape.slice(0,-2),m=u.shape.slice(0,-2),g=Et(f),y=Et(m);M(c===p,()=>`Error in fused matMul: inner shapes (${c}) and (${p}) of Tensors with shapes ${l.shape} and ${u.shape} and transposeA=${n} and transposeB=${s} must match.`);let A=kt(l.shape.slice(0,-2),u.shape.slice(0,-2)).concat([d,h]),b=n?U(l,[g,c,d]):U(l,[g,d,c]),w=s?U(u,[y,h,p]):U(u,[y,p,h]),k;r!=null&&(k=D(r,"bias","fused matMul"),[k]=Gt(k,l),kt(A,k.shape));let S;o!=null&&(S=D(o,"prelu weights","fused matMul"));let E=(_,$)=>{let[T,F,G,q]=$,z=W0(U(_,G.shape),G,a),Z,B;if(!n&&!s?(Z=Qe(z,F,!1,!0),B=Qe(T,z,!0,!1)):!n&&s?(Z=Qe(z,F,!1,!1),B=Qe(z,T,!0,!1)):n&&!s?(Z=Qe(F,z,!1,!0),B=Qe(T,z,!1,!1)):(Z=Qe(F,z,!0,!0),B=Qe(z,T,!0,!0)),r!=null){let ee=V0(q,z);return[Z,B,ee]}else return[Z,B]},R={a:b,b:w,bias:k,preluActivationWeights:S},P={transposeA:n,transposeB:s,activation:a,leakyreluAlpha:i};return r==null?Xr(($,T,F)=>{let G=W.runKernel(Ya,R,P);return F([$,T,G]),{value:U(G,A),gradFunc:E}})(b,w):Xr(($,T,F,G)=>{let q=W.runKernel(Ya,R,P);return G([$,T,q,F]),{value:U(q,A),gradFunc:E}})(b,w,k)}var zM=V({fusedMatMul_:MM});function LM(e){return B0(e,.54,.46)}var BM=V({hammingWindow_:LM});function WM(e){return B0(e,.5,.5)}var jw=V({hannWindow_:WM});function VM(e,t,n,s=!1,r=0){let a=0,o=[];for(;a+t<=e.size;)o.push(Oe(e,a,t)),a+=n;if(s)for(;a<e.size;){let i=a+t-e.size,l=Ct([Oe(e,a,t-i),Gc([i],r)]);o.push(l),a+=n}return o.length===0?or([],[0,t]):U(Ct(o),[o.length,t])}var qw=V({frame_:VM});function UM(e,t,n,s,r=jw){s==null&&(s=VA(t));let a=qw(e,t,n),o=L(a,r(t));return xh(o,s)}var GM=V({stft_:UM});function HM(e,t,n,s,r="bilinear",a=0){let o=D(e,"image","cropAndResize"),i=D(t,"boxes","cropAndResize","float32"),l=D(n,"boxInd","cropAndResize","int32"),u=i.shape[0];M(o.rank===4,()=>`Error in cropAndResize: image must be rank 4,but got rank ${o.rank}.`),M(i.rank===2&&i.shape[1]===4,()=>`Error in cropAndResize: boxes must be have size [${u},4] but had shape ${i.shape}.`),M(l.rank===1&&l.shape[0]===u,()=>`Error in cropAndResize: boxInd must be have size [${u}] but had shape ${i.shape}.`),M(s.length===2,()=>`Error in cropAndResize: cropSize must be of length 2, but got length ${s.length}.`),M(s[0]>=1&&s[1]>=1,()=>`cropSize must be atleast [1,1], but was ${s}`),M(r==="bilinear"||r==="nearest",()=>`method must be bilinear or nearest, but was ${r}`);let c={image:o,boxes:i,boxInd:l},p={method:r,extrapolationValue:a,cropSize:s};return W.runKernel(cl,c,p)}var jM=V({cropAndResize_:HM});function qM(e){let t=D(e,"image","flipLeftRight","float32");M(t.rank===4,()=>`Error in flipLeftRight: image must be rank 4,but got rank ${t.rank}.`);let n={image:t};return W.runKernel(ml,n,{})}var XM=V({flipLeftRight_:qM});function KM(e){let t=D(e,"image","grayscaleToRGB"),n=t.rank-1,s=t.shape[n];M(t.rank>=2,()=>`Error in grayscaleToRGB: images must be at least rank 2, but got rank ${t.rank}.`),M(s===1,()=>`Error in grayscaleToRGB: last dimension of a grayscale image should be size 1, but got size ${s}.`);let r=new Array(t.rank);return r.fill(1,0,n),r[n]=3,js(t,r)}var ZM=V({grayscaleToRGB_:KM});function YM(e,t,n=0,s=.5){let r=D(e,"image","rotateWithOffset","float32");M(r.rank===4,()=>`Error in rotateWithOffset: image must be rank 4,but got rank ${r.rank}.`);let a={image:r},o={radians:t,fillValue:n,center:s};return W.runKernel(Hl,a,o)}var JM=V({rotateWithOffset_:YM});function Kc(e,t,n,s,r,a){s==null&&(s=.5),r==null&&(r=Number.NEGATIVE_INFINITY),a==null&&(a=0);let o=e.shape[0];return n=Math.min(n,o),M(0<=s&&s<=1,()=>`iouThreshold must be in [0, 1], but was '${s}'`),M(e.rank===2,()=>`boxes must be a 2D tensor, but was of rank '${e.rank}'`),M(e.shape[1]===4,()=>`boxes must have 4 columns, but 2nd dimension was ${e.shape[1]}`),M(t.rank===1,()=>"scores must be a 1D tensor"),M(t.shape[0]===o,()=>`scores has incompatible shape with boxes. Expected ${o}, but was ${t.shape[0]}`),M(0<=a&&a<=1,()=>`softNmsSigma must be in [0, 1], but was '${a}'`),{maxOutputSize:n,iouThreshold:s,scoreThreshold:r,softNmsSigma:a}}function QM(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY){let a=D(e,"boxes","nonMaxSuppression","float32"),o=D(t,"scores","nonMaxSuppression","float32"),i=Kc(a,o,n,s,r);n=i.maxOutputSize,s=i.iouThreshold,r=i.scoreThreshold;let l={maxOutputSize:n,iouThreshold:s,scoreThreshold:r};return W.runKernel(Sl,{boxes:a,scores:o},l)}var ez=V({nonMaxSuppression_:QM});function tz(e,t,n){let s=nz(e,t,n),r=s<0?-(s+1):s;e.splice(r,0,t)}function nz(e,t,n){return rz(e,t,n||sz)}function sz(e,t){return e>t?1:e<t?-1:0}function rz(e,t,n){let s=0,r=e.length,a=0,o=!1;for(;s<r;){a=s+(r-s>>>1);let i=n(t,e[a]);i>0?s=a+1:(r=a,o=!i)}return o?s:-s-1}function Xw(e,t,n,s,r){return GA(e,t,n,s,r,0)}function Kw(e,t,n,s,r,a){return GA(e,t,n,s,r,0,!1,a,!0)}function Zw(e,t,n,s,r,a){return GA(e,t,n,s,r,a,!0)}function GA(e,t,n,s,r,a,o=!1,i=!1,l=!1){let u=[];for(let g=0;g<t.length;g++)t[g]>r&&u.push({score:t[g],boxIndex:g,suppressBeginIndex:0});u.sort(vv);let c=a>0?-.5/a:0,p=[],d=[];for(;p.length<n&&u.length>0;){let g=u.pop(),{score:y,boxIndex:x,suppressBeginIndex:A}=g;if(y<r)break;let b=!1;for(let w=p.length-1;w>=A;--w){let k=az(e,x,p[w]);if(k>=s){b=!0;break}if(g.score=g.score*oz(s,c,k),g.score<=r)break}g.suppressBeginIndex=p.length,b||(g.score===y?(p.push(x),d.push(g.score)):g.score>r&&tz(u,g,vv))}let h=p.length,f=n-h;i&&f>0&&(p.push(...new Array(f).fill(0)),d.push(...new Array(f).fill(0)));let m={selectedIndices:p};return o&&(m.selectedScores=d),l&&(m.validOutputs=h),m}function az(e,t,n){let s=e.subarray(t*4,t*4+4),r=e.subarray(n*4,n*4+4),a=Math.min(s[0],s[2]),o=Math.min(s[1],s[3]),i=Math.max(s[0],s[2]),l=Math.max(s[1],s[3]),u=Math.min(r[0],r[2]),c=Math.min(r[1],r[3]),p=Math.max(r[0],r[2]),d=Math.max(r[1],r[3]),h=(i-a)*(l-o),f=(p-u)*(d-c);if(h<=0||f<=0)return 0;let m=Math.max(a,u),g=Math.max(o,c),y=Math.min(i,p),x=Math.min(l,d),A=Math.max(y-m,0)*Math.max(x-g,0);return A/(h+f-A)}function oz(e,t,n){let s=Math.exp(t*n*n);return n<=e?s:0}function vv(e,t){return e.score-t.score||e.score===t.score&&t.boxIndex-e.boxIndex}async function iz(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY){let a=D(e,"boxes","nonMaxSuppressionAsync"),o=D(t,"scores","nonMaxSuppressionAsync"),i=Kc(a,o,n,s,r);n=i.maxOutputSize,s=i.iouThreshold,r=i.scoreThreshold;let l=await Promise.all([a.data(),o.data()]),u=l[0],c=l[1],{selectedIndices:p}=Xw(u,c,n,s,r);return a!==e&&a.dispose(),o!==t&&o.dispose(),Ft(p,"int32")}var lz=iz;function uz(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY,a=0){let o=D(e,"boxes","nonMaxSuppression"),i=D(t,"scores","nonMaxSuppression"),l=Kc(o,i,n,s,r,a);n=l.maxOutputSize,s=l.iouThreshold,r=l.scoreThreshold,a=l.softNmsSigma;let u={boxes:o,scores:i},c={maxOutputSize:n,iouThreshold:s,scoreThreshold:r,softNmsSigma:a},p=W.runKernel(Cl,u,c);return{selectedIndices:p[0],selectedScores:p[1]}}var cz=V({nonMaxSuppressionWithScore_:uz});async function dz(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY,a=0){let o=D(e,"boxes","nonMaxSuppressionAsync"),i=D(t,"scores","nonMaxSuppressionAsync"),l=Kc(o,i,n,s,r,a);n=l.maxOutputSize,s=l.iouThreshold,r=l.scoreThreshold,a=l.softNmsSigma;let u=await Promise.all([o.data(),i.data()]),c=u[0],p=u[1],{selectedIndices:d,selectedScores:h}=Zw(c,p,n,s,r,a);return o!==e&&o.dispose(),i!==t&&i.dispose(),{selectedIndices:Ft(d,"int32"),selectedScores:Ft(h)}}var pz=dz;function hz(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY,a=!1){let o=D(e,"boxes","nonMaxSuppression"),i=D(t,"scores","nonMaxSuppression"),l=Kc(o,i,n,s,r,null),u=l.maxOutputSize,c=l.iouThreshold,p=l.scoreThreshold,d={boxes:o,scores:i},h={maxOutputSize:u,iouThreshold:c,scoreThreshold:p,padToMaxOutputSize:a},f=W.runKernel(Ec,d,h);return{selectedIndices:f[0],validOutputs:f[1]}}var fz=V({nonMaxSuppressionPadded_:hz});async function mz(e,t,n,s=.5,r=Number.NEGATIVE_INFINITY,a=!1){let o=D(e,"boxes","nonMaxSuppressionAsync"),i=D(t,"scores","nonMaxSuppressionAsync"),l=Kc(o,i,n,s,r,null),u=l.maxOutputSize,c=l.iouThreshold,p=l.scoreThreshold,[d,h]=await Promise.all([o.data(),i.data()]),{selectedIndices:f,validOutputs:m}=Kw(d,h,u,c,p,a);return o!==e&&o.dispose(),i!==t&&i.dispose(),{selectedIndices:Ft(f,"int32"),validOutputs:Se(m,"int32")}}var gz=mz;function yz(e,t,n=!1,s=!1){let r=D(e,"images","resizeBilinear");M(r.rank===3||r.rank===4,()=>`Error in resizeBilinear: x must be rank 3 or 4, but got rank ${r.rank}.`),M(t.length===2,()=>`Error in resizeBilinear: new shape must 2D, but got shape ${t}.`),M(s===!1||n===!1,()=>"Error in resizeBilinear: If halfPixelCenters is true, alignCorners must be false.");let a=r,o=!1;r.rank===3&&(o=!0,a=U(r,[1,r.shape[0],r.shape[1],r.shape[2]]));let[]=t,i={images:a},l={alignCorners:n,halfPixelCenters:s,size:t},u=W.runKernel(qo,i,l);return o?U(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var Yw=V({resizeBilinear_:yz});function Az(e,t,n=!1,s=!1){let r=D(e,"images","resizeNearestNeighbor");M(r.rank===3||r.rank===4,()=>`Error in resizeNearestNeighbor: x must be rank 3 or 4, but got rank ${r.rank}.`),M(t.length===2,()=>`Error in resizeNearestNeighbor: new shape must 2D, but got shape ${t}.`),M(r.dtype==="float32"||r.dtype==="int32",()=>"`images` must have `int32` or `float32` as dtype"),M(s===!1||n===!1,()=>"Error in resizeNearestNeighbor: If halfPixelCenters is true, alignCorners must be false.");let a=r,o=!1;r.rank===3&&(o=!0,a=U(r,[1,r.shape[0],r.shape[1],r.shape[2]]));let[]=t,i={images:a},l={alignCorners:n,halfPixelCenters:s,size:t},u=W.runKernel(jo,i,l);return o?U(u,[u.shape[1],u.shape[2],u.shape[3]]):u}var Jw=V({resizeNearestNeighbor_:Az});function xz(e,t="binary",n=!1,s=.5){let r=D(e,"image","threshold"),a=.2989,o=.587,i=.114,l=r.shape[0]*r.shape[1],u=L(Ft([s]),255),c,p,d,h;if(M(r.rank===3,()=>`Error in threshold: image must be rank 3,but got rank ${r.rank}.`),M(r.shape[2]===3||r.shape[2]===1,()=>`Error in threshold: image color channel must be equal to 3 or 1but got ${r.shape[2]}.`),M(r.dtype==="int32"||r.dtype==="float32",()=>`Error in dtype: image dtype must be int32 or float32,but got dtype ${r.dtype}.`),M(t==="otsu"||t==="binary",()=>`Method must be binary or otsu, but was ${t}`),r.shape[2]===3){[c,p,d]=Zt(r,[1,1,1],-1);let g=L(c,a),y=L(p,o),x=L(d,i);h=ce(ce(g,y),x)}else h=e;if(t==="otsu"){let g=rA(ge(E0(h),"int32"),ft([]),256);u=bz(g,l)}let f=n?li(h,u):ys(h,u);return ge(L(f,255),"int32")}function bz(e,t){let n=Ft([-1]),s=Ft([0]),r=Ft([0]),a,o,i,l,u,c;for(let p=0;p<e.size-1;p++){a=Oe(e,0,p+1),o=Oe(e,p+1),u=pe(ke(a),t),c=pe(ke(o),t);let d=ke(L(a,Yu(0,a.size)));i=pe(d,ke(a));let h=Gc(o.shape,a.size),f=ce(Yu(0,o.size),h),m=L(o,f);l=pe(ke(m),ke(o));let g=he(i,l),y=he(i,l),x=L(u,c);r=L(L(x,g),y);let A=ys(r,s);s=Mn(A,r,s),n=Mn(A,Ft([p]),n)}return n}var vz=V({threshold_:xz});function wz(e,t,n="nearest",s="constant",r=0,a){let o=D(e,"image","transform","float32"),i=D(t,"transforms","transform","float32");M(o.rank===4,()=>`Error in transform: image must be rank 4,but got rank ${o.rank}.`),M(i.rank===2&&(i.shape[0]===o.shape[0]||i.shape[0]===1)&&i.shape[1]===8,()=>"Error in transform: Input transform should be batch x 8 or 1 x 8"),M(a==null||a.length===2,()=>`Error in transform: outputShape must be [height, width] or null, but got ${a}.`);let l={image:o,transforms:i},u={interpolation:n,fillMode:s,fillValue:r,outputShape:a};return W.runKernel(Vl,l,u)}var kz=V({transform_:wz});function Iz(e,t,n){M(t%1===0,()=>`bandPart(): numLower must be an integer, got ${t}.`),M(n%1===0,()=>`bandPart(): numUpper must be an integer, got ${n}.`);let s=D(e,"a","bandPart");M(s.rank>=2,()=>`bandPart(): Rank must be at least 2, got ${s.rank}.`);let r=s.shape,[a,o]=s.shape.slice(-2);if(!(t<=a))throw new Error(`bandPart(): numLower (${t}) must not be greater than the number of rows (${a}).`);if(!(n<=o))throw new Error(`bandPart(): numUpper (${n}) must not be greater than the number of columns (${o}).`);t<0&&(t=a),n<0&&(n=o);let i=U(Yu(0,a,1,"int32"),[-1,1]),l=Yu(0,o,1,"int32"),u=he(i,l),c=lr(li(u,Se(+t,"int32")),ii(u,Se(-n,"int32"))),p=Wt([a,o],s.dtype);return U(on(es(U(s,[-1,a,o])).map(d=>Mn(c,d,p))),r)}var Sz=V({bandPart_:Iz});function Cz(e){let t;if(Array.isArray(e)){t=!1,M(e!=null&&e.length>0,()=>"Gram-Schmidt process: input must not be null, undefined, or empty");let r=e[0].shape[0];for(let a=1;a<e.length;++a)M(e[a].shape[0]===r,()=>`Gram-Schmidt: Non-unique lengths found in the input vectors: (${e[a].shape[0]} vs. ${r})`)}else t=!0,e=Zt(e,e.shape[0],0).map(r=>rt(r,[0]));M(e.length<=e[0].shape[0],()=>`Gram-Schmidt: Number of vectors (${e.length}) exceeds number of dimensions (${e[0].shape[0]}).`);let n=[],s=e;for(let r=0;r<e.length;++r)n.push(W.tidy(()=>{let a=s[r];if(r>0)for(let o=0;o<r;++o){let i=L(ke(L(n[o],a)),n[o]);a=he(a,i)}return pe(a,Uc(a,"euclidean"))}));return t?on(n,0):n}var Tz=V({gramSchmidt_:Cz});function Nz(e,t=!1){if(M(e.rank>=2,()=>`qr() requires input tensor to have a rank >= 2, but got rank ${e.rank}`),e.rank===2)return wv(e,t);{let n=e.shape.slice(0,e.shape.length-2).reduce((l,u)=>l*u),s=es(U(e,[n,e.shape[e.shape.length-2],e.shape[e.shape.length-1]]),0),r=[],a=[];s.forEach(l=>{let[u,c]=wv(l,t);r.push(u),a.push(c)});let o=U(on(r,0),e.shape),i=U(on(a,0),e.shape);return[o,i]}}function wv(e,t=!1){return W.tidy(()=>{M(e.shape.length===2,()=>`qr2d() requires a 2D Tensor, but got a ${e.shape.length}D Tensor.`);let n=e.shape[0],s=e.shape[1],r=b0(n),a=Fn(e),o=or([[1]],[1,1]),i=Fn(o),l=n>=s?s:n;for(let u=0;u<l;++u){let c=a,p=i,d=r;[i,a,r]=W.tidy(()=>{let h=Oe(a,[u,u],[n-u,1]),f=Uc(h),m=Oe(a,[u,u],[1,1]),g=Mn(ys(m,0),or([[-1]]),or([[1]])),y=he(m,L(g,f)),x=pe(h,y);x.shape[0]===1?i=Fn(o):i=Ct([o,Oe(x,[1,0],[x.shape[0]-1,x.shape[1]])],0);let A=Dt(pe(Qe(g,y),f)),b=Oe(a,[u,0],[n-u,s]),w=L(A,i),k=st(i);if(u===0)a=he(b,Qe(w,Qe(k,b)));else{let R=he(b,Qe(w,Qe(k,b)));a=Ct([Oe(a,[0,0],[u,s]),R],0)}let S=st(w),E=Oe(r,[0,u],[n,r.shape[1]-u]);if(u===0)r=he(E,Qe(Qe(E,i),S));else{let R=he(E,Qe(Qe(E,i),S));r=Ct([Oe(r,[0,0],[n,u]),R],1)}return[i,a,r]}),ne([c,p,d])}return!t&&n>s&&(r=Oe(r,[0,0],[n,s]),a=Oe(a,[0,0],[s,s])),[r,a]})}var Ez=V({qr_:Nz}),Yn;(function(e){e[e.NONE=0]="NONE",e[e.MEAN=1]="MEAN",e[e.SUM=2]="SUM",e[e.SUM_BY_NONZERO_WEIGHTS=3]="SUM_BY_NONZERO_WEIGHTS"})(Yn||(Yn={}));function Rz(e,t,n=Yn.SUM_BY_NONZERO_WEIGHTS){let s=D(e,"losses","computeWeightedLoss"),r=null;t!=null&&(r=D(t,"weights","computeWeightedLoss"));let a=r==null?s:L(s,r);if(n===Yn.NONE)return a;if(n===Yn.SUM)return ke(a);if(n===Yn.MEAN){if(r==null)return Bt(a);{let o=s.size/r.size,i=pe(ke(a),ke(r));return o>1?pe(i,Se(o)):i}}if(n===Yn.SUM_BY_NONZERO_WEIGHTS){if(r==null)return pe(ke(a),Se(s.size));{let o=L(r,Ns(s.shape)),i=ge(ke(Ji(o,Se(0))),"float32");return pe(ke(a),i)}}throw Error(`Unknown reduction: ${n}`)}var va=V({computeWeightedLoss_:Rz});function _z(e,t,n,s=Yn.SUM_BY_NONZERO_WEIGHTS){let r=D(e,"labels","absoluteDifference"),a=D(t,"predictions","absoluteDifference"),o=null;n!=null&&(o=D(n,"weights","absoluteDifference")),ns(r.shape,a.shape,"Error in absoluteDifference: ");let i=tn(he(r,a));return va(i,o,s)}var Dz=V({absoluteDifference_:_z});function $z(e,t,n,s,r=Yn.SUM_BY_NONZERO_WEIGHTS){let a=D(e,"labels","cosineDistance"),o=D(t,"predictions","cosineDistance"),i=null;s!=null&&(i=D(s,"weights","cosineDistance")),ns(a.shape,o.shape,"Error in cosineDistance: ");let l=Se(1),u=he(l,ke(L(a,o),n,!0));return va(u,i,r)}var Pz=V({cosineDistance_:$z});function Fz(e,t,n,s=Yn.SUM_BY_NONZERO_WEIGHTS){let r=D(e,"labels","hingeLoss"),a=D(t,"predictions","hingeLoss"),o=null;n!=null&&(o=D(n,"weights","hingeLoss")),ns(r.shape,a.shape,"Error in hingeLoss: ");let i=Se(1);r=he(L(Se(2),r),i);let l=$r(he(i,L(r,a)));return va(l,o,s)}var Oz=V({hingeLoss_:Fz});function Mz(e,t,n,s=1,r=Yn.SUM_BY_NONZERO_WEIGHTS){let a=D(e,"labels","huberLoss"),o=D(t,"predictions","huberLoss"),i=null;n!=null&&(i=D(n,"weights","huberLoss")),ns(a.shape,o.shape,"Error in huberLoss: ");let l=Se(s),u=tn(he(o,a)),c=qc(u,l),p=he(u,c),d=ce(L(Se(.5),vt(c)),L(l,p));return va(d,i,r)}var zz=V({huberLoss_:Mz});function Lz(e,t,n,s=1e-7,r=Yn.SUM_BY_NONZERO_WEIGHTS){let a=D(e,"labels","logLoss"),o=D(t,"predictions","logLoss"),i=null;n!=null&&(i=D(n,"weights","logLoss")),ns(a.shape,o.shape,"Error in logLoss: ");let l=Se(1),u=Se(s),c=Dt(L(a,Ds(ce(o,u)))),p=L(he(l,a),Ds(ce(he(l,o),u))),d=he(c,p);return va(d,i,r)}var Bz=V({logLoss_:Lz});function Wz(e,t,n,s=Yn.SUM_BY_NONZERO_WEIGHTS){let r=D(e,"labels","meanSquaredError"),a=D(t,"predictions","meanSquaredError"),o=null;n!=null&&(o=D(n,"weights","meanSquaredError")),ns(r.shape,a.shape,"Error in meanSquaredError: ");let i=M0(r,a);return va(i,o,s)}var Vz=V({meanSquaredError_:Wz});function Uz(e,t){let n=D(e,"labels","sigmoidCrossEntropyWithLogits"),s=D(t,"logits","sigmoidCrossEntropyWithLogits");ns(n.shape,s.shape,"Error in sigmoidCrossEntropyWithLogits: ");let r=$r(s),a=L(s,n),o=dh(_s(Dt(tn(s))));return ce(he(r,a),o)}function Gz(e,t,n,s=0,r=Yn.SUM_BY_NONZERO_WEIGHTS){let a=D(e,"multiClassLabels","sigmoidCrossEntropy"),o=D(t,"logits","sigmoidCrossEntropy"),i=null;if(n!=null&&(i=D(n,"weights","sigmoidCrossEntropy")),ns(a.shape,o.shape,"Error in sigmoidCrossEntropy: "),s>0){let u=Se(s),c=Se(1),p=Se(.5);a=ce(L(a,he(c,u)),L(p,u))}let l=Uz(a,o);return va(l,i,r)}var Hz=V({sigmoidCrossEntropy_:Gz});function jz(e,t,n=-1){if(n===-1&&(n=t.rank-1),n!==t.rank-1)throw Error(`Softmax cross entropy along a non-last dimension is not yet supported. Labels / logits was rank ${t.rank} and dim was ${n}`);return Xr((r,a,o)=>{let l=I0(a,[n],!0),u=he(ge(a,"float32"),l);o([r,u]);let c=Dt(L(u,r));return{value:ke(c,[n]),gradFunc:(h,f)=>{let[m,g]=f,y=Yi(h.shape,[n]);return[L(U(h,y),he(ge(m,"float32"),_s(g))),L(U(h,y),he(_s(g),ge(m,"float32")))]}}})(e,t)}function qz(e,t,n,s=0,r=Yn.SUM_BY_NONZERO_WEIGHTS){let a=D(e,"onehotLabels","softmaxCrossEntropy"),o=D(t,"logits","softmaxCrossEntropy"),i=null;if(n!=null&&(i=D(n,"weights","softmaxCrossEntropy")),ns(a.shape,o.shape,"Error in softmaxCrossEntropy: "),s>0){let u=Se(s),c=Se(1),p=Se(a.shape[1]);a=ce(L(a,he(c,u)),pe(u,p))}let l=jz(a,o);return va(l,i,r)}var Xz=V({softmaxCrossEntropy_:qz});function Kz(e,t,n,s){let r=D(e,"indices","sparseFillEmptyRows","int32"),a=D(t,"values","sparseFillEmptyRows"),o=D(n,"denseShape","sparseFillEmptyRows","int32"),i=D(s,"defaultValue","sparseFillEmptyRows",a.dtype);if(r.rank!==2)throw new Error(`Indices should be Tensor2D but received shape
+        ${r.shape}`);if(a.rank!==1)throw new Error(`Values should be Tensor1D but received shape ${a.shape}`);if(o.rank!==1)throw new Error(`Dense shape should be Tensor1D but received shape ${o.shape}`);if(i.rank!==0)throw new Error(`Default value should be a scalar but received shape ${i.shape}`);let l={indices:r,values:a,denseShape:o,defaultValue:i},u=W.runKernel(qp,l);return{outputIndices:u[0],outputValues:u[1],emptyRowIndicator:u[2],reverseIndexMap:u[3]}}var Zz=V({sparseFillEmptyRows_:Kz});function Yz(e,t,n){let s=D(e,"inputIndices","sparseReshape","int32"),r=D(t,"inputShape","sparseReshape","int32"),a=D(n,"newShape","sparseReshape","int32");if(s.rank!==2)throw new Error(`Input indices should be Tensor2D but received shape
+        ${s.shape}`);if(r.rank!==1)throw new Error(`Input shape should be Tensor1D but received shape ${r.shape}`);if(a.rank!==1)throw new Error(`New shape should be Tensor1D but received shape ${a.shape}`);let o={inputIndices:s,inputShape:r,newShape:a},i=W.runKernel(Fc,o);return{outputIndices:i[0],outputShape:i[1]}}var Jz=V({sparseReshape_:Yz});function Qz(e,t,n){let s=D(e,"data","sparseSegmentMean"),r=D(t,"indices","sparseSegmentMean","int32"),a=D(n,"segmentIds","sparseSegmentMean","int32");if(s.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.rank!==1)throw new Error(`Indices should be Tensor1D but received shape
           ${r.shape}`);if(a.rank!==1)throw new Error(`Segment ids should be Tensor1D but received shape
-          ${a.shape}`);let o={data:s,indices:r,segmentIds:a};return W.runKernel(Kp,o)}var eL=V({sparseSegmentMean_:Qz});function tL(e,t,n){let s=D(e,"data","sparseSegmentSum"),r=D(t,"indices","sparseSegmentSum","int32"),a=D(n,"segmentIds","sparseSegmentSum","int32");if(s.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.rank!==1)throw new Error(`Indices should be Tensor1D but received shape
+          ${a.shape}`);let o={data:s,indices:r,segmentIds:a};return W.runKernel(Xp,o)}var eL=V({sparseSegmentMean_:Qz});function tL(e,t,n){let s=D(e,"data","sparseSegmentSum"),r=D(t,"indices","sparseSegmentSum","int32"),a=D(n,"segmentIds","sparseSegmentSum","int32");if(s.rank<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.rank!==1)throw new Error(`Indices should be Tensor1D but received shape
          ${r.shape}`);if(a.rank!==1)throw new Error(`Segment ids should be Tensor1D but received shape
-         ${a.shape}`);let o={data:s,indices:r,segmentIds:a};return W.runKernel(Zp,o)}var nL=V({sparseSegmentSum_:tL});function sL(e,t,n,s,r,a,o,i){let l=D(e,"data","stringNGrams","string");if(l.dtype!=="string")throw new Error("Data must be of datatype string");if(l.shape.length!==1)throw new Error(`Data must be a vector, saw: ${l.shape}`);let u=D(t,"dataSplits","stringNGrams");if(u.dtype!=="int32")throw new Error("Data splits must be of datatype int32");let c={separator:n,nGramWidths:s,leftPad:r,rightPad:a,padWidth:o,preserveShortSequences:i},p={data:l,dataSplits:u},d=W.runKernel(zc,p,c);return{nGrams:d[0],nGramsSplits:d[1]}}var rL=V({stringNGrams_:sL});function aL(e,t,n=!0){let s=D(e,"input","stringSplit","string"),r=D(t,"delimiter","stringSplit","string");if(s.rank!==1)throw new Error(`Input should be Tensor1D but received shape ${s.shape}`);if(r.rank!==0)throw new Error(`Delimiter should be a scalar but received shape ${r.shape}`);let a={skipEmpty:n},o={input:s,delimiter:r},i=W.runKernel(Jp,o,a);return{indices:i[0],values:i[1],shape:i[2]}}var oL=V({stringSplit_:aL});function iL(e,t){let n=D(e,"input","stringToHashBucketFast","string"),s={numBuckets:t};if(t<=0)throw new Error("Number of buckets must be at least 1");let r={input:n};return W.runKernel(Qp,r,s)}var lL=V({stringToHashBucketFast_:iL}),Qw={fft:xh,ifft:Qu,rfft:bh,irfft:M0},e8={hammingWindow:BM,hannWindow:jw,frame:qw,stft:GM},Ne={flipLeftRight:XM,grayscaleToRGB:ZM,resizeNearestNeighbor:Jw,resizeBilinear:Yw,rotateWithOffset:JM,cropAndResize:jM,nonMaxSuppression:ez,nonMaxSuppressionAsync:lz,nonMaxSuppressionWithScore:cz,nonMaxSuppressionWithScoreAsync:pz,nonMaxSuppressionPadded:fz,nonMaxSuppressionPaddedAsync:gz,threshold:vz,transform:kz},HA={bandPart:Sz,gramSchmidt:Tz,qr:Ez},t8={absoluteDifference:Dz,computeWeightedLoss:wa,cosineDistance:Pz,hingeLoss:Oz,huberLoss:zz,logLoss:Bz,meanSquaredError:Vz,sigmoidCrossEntropy:Hz,softmaxCrossEntropy:Xz},n8={sparseFillEmptyRows:Zz,sparseReshape:Jz,sparseSegmentMean:eL,sparseSegmentSum:nL},s8={stringNGrams:rL,stringSplit:oL,stringToHashBucketFast:lL},ka=class extends Z6{minimize(e,t=!1,n){let{value:s,grads:r}=this.computeGradients(e,n);if(n!=null){let a=n.map(o=>({name:o.name,tensor:r[o.name]}));this.applyGradients(a)}else this.applyGradients(r);return ne(r),t?s:(s.dispose(),null)}get iterations(){return this.iterations_==null&&(this.iterations_=0),this.iterations_}incrementIterations(){this.iterations_=this.iterations+1}computeGradients(e,t){return fw(e,t)}dispose(){this.iterations_!=null&&ne(this.iterations_)}async saveIterations(){return this.iterations_==null&&(this.iterations_=0),{name:"iter",tensor:Se(this.iterations_,"int32")}}async getWeights(){throw new Error("getWeights() is not implemented for this optimizer yet.")}async setWeights(e){throw new Error(`setWeights() is not implemented for this optimizer class ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}};Object.defineProperty(ka,Symbol.hasInstance,{value:e=>e.minimize!=null&&e.computeGradients!=null&&e.applyGradients!=null});var j0=class extends ka{constructor(e,t,n=null){super(),this.learningRate=e,this.rho=t,this.epsilon=n,this.accumulatedGrads=[],this.accumulatedUpdates=[],n==null&&(this.epsilon=W.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=W.registeredVariables[n],a=!1;this.accumulatedGrads[s]==null&&(this.accumulatedGrads[s]={originalName:`${n}/accum_grad`,variable:J(()=>it(r).variable(a))}),this.accumulatedUpdates[s]==null&&(this.accumulatedUpdates[s]={originalName:`${n}/accum_var`,variable:J(()=>it(r).variable(a))});let o=Array.isArray(e)?e[s].tensor:e[n];if(o==null)return;let i=this.accumulatedGrads[s].variable,l=this.accumulatedUpdates[s].variable;J(()=>{let u=ce(L(i,this.rho),L(vt(o),1-this.rho)),c=L(pe(Nn(ce(l,this.epsilon)),Nn(ce(i,this.epsilon))),o),p=ce(L(l,this.rho),L(vt(c),1-this.rho));i.assign(u),l.assign(p);let d=ce(L(c,-this.learningRate),r);r.assign(d)})}),this.incrementIterations()}dispose(){this.accumulatedUpdates!=null&&(ne(this.accumulatedGrads.map(e=>e.variable)),ne(this.accumulatedUpdates.map(e=>e.variable)))}async getWeights(){let e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=e.length/2,n=!1;this.accumulatedGrads=e.slice(0,t).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})),this.accumulatedUpdates=e.slice(t,t*2).map(s=>({originalName:s.name,variable:s.tensor.variable(n)}))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}};j0.className="Adadelta";ii(j0);var q0=class extends ka{constructor(e,t=.1){super(),this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=W.registeredVariables[n];this.accumulatedGrads[s]==null&&(this.accumulatedGrads[s]={originalName:`${n}/accumulator`,variable:J(()=>Hc(r.shape,this.initialAccumulatorValue).variable(!1))});let a=Array.isArray(e)?e[s].tensor:e[n];if(a==null)return;let o=this.accumulatedGrads[s].variable;J(()=>{let i=ce(o,vt(a));o.assign(i);let l=ce(L(pe(a,Nn(ce(i,W.backend.epsilon()))),-this.learningRate),r);r.assign(l)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&ne(this.accumulatedGrads.map(e=>e.variable))}async getWeights(){return[await this.saveIterations()].concat(this.accumulatedGrads.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulatedGrads=e.map(n=>({originalName:n.name,variable:n.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}};q0.className="Adagrad";ii(q0);var X0=class extends ka{constructor(e,t,n,s=null){super(),this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=s,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],J(()=>{this.accBeta1=Se(t).variable(),this.accBeta2=Se(n).variable()}),s==null&&(this.epsilon=W.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);J(()=>{let n=he(1,this.accBeta1),s=he(1,this.accBeta2);t.forEach((r,a)=>{let o=W.registeredVariables[r],i=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${r}/m`,variable:J(()=>it(o).variable(i))}),this.accumulatedSecondMoment[a]==null&&(this.accumulatedSecondMoment[a]={originalName:`${r}/v`,variable:J(()=>it(o).variable(i))});let l=Array.isArray(e)?e[a].tensor:e[r];if(l==null)return;let u=this.accumulatedFirstMoment[a].variable,c=this.accumulatedSecondMoment[a].variable,p=ce(L(u,this.beta1),L(l,1-this.beta1)),d=ce(L(c,this.beta2),L(vt(l),1-this.beta2)),h=pe(p,n),f=pe(d,s);u.assign(p),c.assign(d);let m=ce(L(pe(h,ce(Nn(f),this.epsilon)),-this.learningRate),o);o.assign(m)}),this.accBeta1.assign(L(this.accBeta1,this.beta1)),this.accBeta2.assign(L(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&ne(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&ne(this.accumulatedSecondMoment.map(e=>e.variable))}async getWeights(){let e=[...this.accumulatedFirstMoment,...this.accumulatedSecondMoment];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e),J(()=>{this.accBeta1.assign(ya(this.beta1,this.iterations_+1)),this.accBeta2.assign(ya(this.beta2,this.iterations_+1))});let t=e.length/2,n=!1;this.accumulatedFirstMoment=e.slice(0,t).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(s=>({originalName:s.name,variable:s.tensor.variable(n)}))}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon)}};X0.className="Adam";ii(X0);var K0=class extends ka{constructor(e,t,n,s=null,r=0){super(),this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=s,this.decay=r,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],J(()=>{this.iteration=Se(0).variable(),this.accBeta1=Se(t).variable()}),s==null&&(this.epsilon=W.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);J(()=>{let n=he(1,this.accBeta1),s=pe(-this.learningRate,ce(L(this.iteration,this.decay),1));t.forEach((r,a)=>{let o=W.registeredVariables[r],i=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${r}/m`,variable:it(o).variable(i)}),this.accumulatedWeightedInfNorm[a]==null&&(this.accumulatedWeightedInfNorm[a]={originalName:`${r}/v`,variable:it(o).variable(i)});let l=Array.isArray(e)?e[a].tensor:e[r];if(l==null)return;let u=this.accumulatedFirstMoment[a].variable,c=this.accumulatedWeightedInfNorm[a].variable,p=ce(L(u,this.beta1),L(l,1-this.beta1)),d=L(c,this.beta2),h=tn(l),f=Jr(d,h);u.assign(p),c.assign(f);let m=ce(L(pe(s,n),pe(p,ce(f,this.epsilon))),o);o.assign(m)}),this.iteration.assign(ce(this.iteration,1)),this.accBeta1.assign(L(this.accBeta1,this.beta1))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),this.accumulatedFirstMoment!=null&&ne(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedWeightedInfNorm!=null&&ne(this.accumulatedWeightedInfNorm.map(e=>e.variable))}async getWeights(){throw new Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}};K0.className="Adamax";ii(K0);var vh=class extends ka{constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=Array.isArray(e)?e[s].tensor:e[n];if(r==null)return;let a=W.registeredVariables[n];J(()=>{let o=ce(L(this.c,r),a);a.assign(o)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=bn(Se(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(e=await this.extractIterations(e),e.length!==0)throw new Error("SGD optimizer does not have settable weights.")}getConfig(){return{learningRate:this.learningRate}}static fromConfig(e,t){return new e(t.learningRate)}};vh.className="SGD";ii(vh);var Z0=class extends vh{constructor(e,t,n=!1){super(e),this.learningRate=e,this.momentum=t,this.useNesterov=n,this.accumulations=[],this.m=Se(this.momentum)}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=W.registeredVariables[n];this.accumulations[s]==null&&(this.accumulations[s]={originalName:`${n}/momentum`,variable:J(()=>it(r).variable(!1))});let a=this.accumulations[s].variable,o=Array.isArray(e)?e[s].tensor:e[n];o!=null&&J(()=>{let i,l=ce(L(this.m,a),o);this.useNesterov?i=ce(L(this.c,ce(o,L(l,this.m))),r):i=ce(L(this.c,l),r),a.assign(l),r.assign(i)})}),this.incrementIterations()}dispose(){this.m.dispose(),this.accumulations!=null&&ne(this.accumulations.map(e=>e.variable))}setMomentum(e){this.momentum=e}async getWeights(){return[await this.saveIterations()].concat(this.accumulations.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulations=e.map(n=>({originalName:n.name,variable:n.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}}static fromConfig(e,t){return new e(t.learningRate,t.momentum,t.useNesterov)}};Z0.className="Momentum";ii(Z0);var Y0=class extends ka{constructor(e,t=.9,n=0,s=null,r=!1){if(super(),this.learningRate=e,this.decay=t,this.momentum=n,this.epsilon=s,this.accumulatedMeanSquares=[],this.accumulatedMoments=[],this.accumulatedMeanGrads=[],this.centered=r,s==null&&(this.epsilon=W.backend.epsilon()),e==null)throw new Error("learningRate for RMSPropOptimizer must be defined.")}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=W.registeredVariables[n],a=!1;this.accumulatedMeanSquares[s]==null&&(this.accumulatedMeanSquares[s]={originalName:`${n}/rms`,variable:J(()=>it(r).variable(a))}),this.accumulatedMoments[s]==null&&(this.accumulatedMoments[s]={originalName:`${n}/momentum`,variable:J(()=>it(r).variable(a))}),this.accumulatedMeanGrads[s]==null&&this.centered&&(this.accumulatedMeanGrads[s]={originalName:`${n}/mg`,variable:J(()=>it(r).variable(a))});let o=Array.isArray(e)?e[s].tensor:e[n];if(o==null)return;let i=this.accumulatedMeanSquares[s].variable,l=this.accumulatedMoments[s].variable;J(()=>{let u=ce(L(i,this.decay),L(vt(o),1-this.decay));if(this.centered){let c=this.accumulatedMeanGrads[s].variable,p=ce(L(c,this.decay),L(o,1-this.decay)),d=pe(L(o,this.learningRate),Nn(he(u,ce(vt(p),this.epsilon)))),h=ce(L(l,this.momentum),d);i.assign(u),c.assign(p),l.assign(h);let f=he(r,h);r.assign(f)}else{let c=ce(L(i,this.decay),L(vt(o),1-this.decay)),p=ce(L(l,this.momentum),pe(L(o,this.learningRate),Nn(ce(c,this.epsilon))));i.assign(c),l.assign(p);let d=he(r,p);r.assign(d)}})}),this.incrementIterations()}dispose(){this.accumulatedMeanSquares!=null&&ne(this.accumulatedMeanSquares.map(e=>e.variable)),this.accumulatedMeanGrads!=null&&this.centered&&ne(this.accumulatedMeanGrads.map(e=>e.variable)),this.accumulatedMoments!=null&&ne(this.accumulatedMoments.map(e=>e.variable))}async getWeights(){let e=[...this.accumulatedMeanSquares,...this.accumulatedMoments];return this.centered&&e.push(...this.accumulatedMeanGrads),[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=this.centered?e.length/3:e.length/2,n=!1;this.accumulatedMeanSquares=e.slice(0,t).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})),this.accumulatedMoments=e.slice(t,t*2).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})),this.centered&&(this.accumulatedMeanGrads=e.slice(t*2,t*3).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})))}getConfig(){return{learningRate:this.learningRate,decay:this.decay,momentum:this.momentum,epsilon:this.epsilon,centered:this.centered}}static fromConfig(e,t){return new e(t.learningRate,t.decay,t.momentum,t.epsilon,t.centered)}};Y0.className="RMSProp";ii(Y0);var Wa=class{static sgd(e){return new vh(e)}static momentum(e,t,n=!1){return new Z0(e,t,n)}static rmsprop(e,t=.9,n=0,s=null,r=!1){return new Y0(e,t,n,s,r)}static adam(e=.001,t=.9,n=.999,s=null){return new X0(e,t,n,s)}static adadelta(e=.001,t=.95,n=null){return new j0(e,t,n)}static adamax(e=.002,t=.9,n=.999,s=null,r=0){return new K0(e,t,n,s,r)}static adagrad(e,t=.1){return new q0(e,t)}},Fi={sgd:Wa.sgd,momentum:Wa.momentum,adadelta:Wa.adadelta,adagrad:Wa.adagrad,rmsprop:Wa.rmsprop,adamax:Wa.adamax,adam:Wa.adam},uL=(()=>typeof requestAnimationFrame!="undefined"?requestAnimationFrame:typeof setImmediate!="undefined"?setImmediate:e=>e())();function jA(){return new Promise(e=>uL(()=>e()))}var C={};Ve(C,{ERF_A1:()=>bL,ERF_A2:()=>vL,ERF_A3:()=>wL,ERF_A4:()=>kL,ERF_A5:()=>IL,ERF_P:()=>xL,PARALLELIZE_THRESHOLD:()=>qA,SELU_SCALE:()=>a8,SELU_SCALEALPHA:()=>r8,applyActivation:()=>G0,assertAndGetBroadcastShape:()=>kt,assertAxesAreInnerMostDims:()=>yF,assertParamsConsistent:()=>cL,assignToTypedArray:()=>RL,axesAreInnerMostDims:()=>yA,calculateShapes:()=>B6,checkEinsumDimSizes:()=>OL,checkPadOnDimRoundingMode:()=>rs,combineLocations:()=>uw,complexWithEvenIndex:()=>TL,complexWithOddIndex:()=>NL,computeConv2DInfo:()=>ih,computeConv3DInfo:()=>tw,computeDefaultPad:()=>Qy,computeDilation2DInfo:()=>AP,computeOptimalWindowSize:()=>pL,computeOutAndReduceShapes:()=>cw,computeOutShape:()=>dL,computePool2DInfo:()=>ew,computePool3DInfo:()=>xP,convertConv2DDataFormat:()=>nw,decodeEinsumEquation:()=>PL,eitherStridesOrDilationsAreOne:()=>Yr,expandShapeToKeepDim:()=>Ji,exponent:()=>DL,exponents:()=>_L,fromStringArrayToUint8:()=>sB,fromUint8ToStringArray:()=>nB,getAxesPermutation:()=>dw,getBroadcastDims:()=>M6,getComplexWithIndex:()=>EL,getEinsumComputePath:()=>ML,getEinsumPermutation:()=>FL,getFusedBiasGradient:()=>U0,getFusedDyActivation:()=>V0,getImageCenter:()=>hL,getInnerMostAxes:()=>AF,getPermuted:()=>mL,getReductionAxes:()=>an,getReshaped:()=>fL,getReshapedPermuted:()=>gL,getSliceBeginCoords:()=>yL,getSliceSize:()=>AL,getSparseFillEmptyRowsIndicesDenseShapeMismatch:()=>WL,getSparseFillEmptyRowsNegativeIndexErrorMessage:()=>VL,getSparseFillEmptyRowsOutOfRangeIndexErrorMessage:()=>UL,getSparseReshapeEmptyTensorZeroOutputDimErrorMessage:()=>jL,getSparseReshapeInputOutputMismatchErrorMessage:()=>XL,getSparseReshapeInputOutputMultipleErrorMessage:()=>qL,getSparseReshapeMultipleNegativeOneOutputDimErrorMessage:()=>GL,getSparseReshapeNegativeOutputDimErrorMessage:()=>HL,getSparseSegmentReductionIndicesOutOfRangeErrorMessage:()=>JL,getSparseSegmentReductionNegativeSegmentIdsErrorMessage:()=>KL,getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage:()=>ZL,getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage:()=>YL,getUndoAxesPermutation:()=>AA,isIdentityPermutation:()=>zL,log:()=>U_,mergeRealAndImagArrays:()=>SL,prepareAndValidate:()=>L6,prepareSplitSize:()=>BL,segment_util:()=>o8,shouldFuse:()=>H0,slice_util:()=>Ut,splitRealAndImagArrays:()=>CL,tupleValuesAreOne:()=>to,upcastType:()=>On,validateInput:()=>Wy,validateUpdateShape:()=>By,warn:()=>Ua});function cL(e,t){let n=e[0].length;e.forEach((r,a)=>{M(r.length===n,()=>`Error in concat${n}D: rank of tensors[${a}] must be the same as the rank of the rest (${n})`)}),M(t>=0&&t<n,()=>`Error in concat${n}D: axis must be between 0 and ${n-1}.`);let s=e[0];e.forEach((r,a)=>{for(let o=0;o<n;o++)M(o===t||r[o]===s[o],()=>`Error in concat${n}D: Shape of tensors[${a}] (${r}) does not match the shape of the rest (${s}) along the non-concatenated axis ${a}.`)})}function dL(e,t){let n=e[0].slice();for(let s=1;s<e.length;s++)n[t]+=e[s][t];return n}var qA=30;function pL(e){return e<=qA?e:dm(e,Math.floor(Math.sqrt(e)))}function hL(e,t,n){let s=n*(typeof e=="number"?e:e[0]),r=t*(typeof e=="number"?e:e[1]);return[s,r]}function fL(e,t,n,s=!0){let r=[];if(s)r=r.concat(t.slice(0)),r.push(e[0]/n),r=r.concat(e.slice(1));else{r=r.concat(e[0]);let a=t.length;for(let o=0;o<a;++o)r=r.concat([e[o+1]/t[o],t[o]]);r=r.concat(e.slice(a+1))}return r}function mL(e,t,n=!0){let s=[];if(n){s.push(t);for(let r=t+1;r<e;++r)r<=2*t?(s.push(r),s.push(r-(t+1))):s.push(r)}else{let r=[],a=[];for(let o=1;o<e;++o)o>=t*2+1||o%2===1?a.push(o):r.push(o);s.push(...r),s.push(0),s.push(...a)}return s}function gL(e,t,n,s=!0){let r=[];s?r.push(e[0]/n):r.push(e[0]*n);for(let a=1;a<e.length;++a)a<=t.length?s?r.push(t[a-1]*e[a]):r.push(e[a]/t[a-1]):r.push(e[a]);return r}function yL(e,t){let n=[0];for(let s=0;s<t;++s)n.push(e[s][0]);return n}function AL(e,t,n){let s=e.slice(0,1);for(let r=0;r<n;++r)s.push(e[r+1]-t[r][0]-t[r][1]);return s}var r8=1.7580993408473768,a8=1.0507009873554805,xL=.3275911,bL=.254829592,vL=-.284496736,wL=1.421413741,kL=-1.453152027,IL=1.061405429;function SL(e,t){if(e.length!==t.length)throw new Error(`Cannot merge real and imag arrays of different lengths. real:${e.length}, imag: ${t.length}.`);let n=new Float32Array(e.length*2);for(let s=0;s<n.length;s+=2)n[s]=e[s/2],n[s+1]=t[s/2];return n}function CL(e){let t=new Float32Array(e.length/2),n=new Float32Array(e.length/2);for(let s=0;s<e.length;s+=2)t[s/2]=e[s],n[s/2]=e[s+1];return{real:t,imag:n}}function TL(e){let t=Math.ceil(e.length/4),n=new Float32Array(t),s=new Float32Array(t);for(let r=0;r<e.length;r+=4)n[Math.floor(r/4)]=e[r],s[Math.floor(r/4)]=e[r+1];return{real:n,imag:s}}function NL(e){let t=Math.floor(e.length/4),n=new Float32Array(t),s=new Float32Array(t);for(let r=2;r<e.length;r+=4)n[Math.floor(r/4)]=e[r],s[Math.floor(r/4)]=e[r+1];return{real:n,imag:s}}function EL(e,t){let n=e[t*2],s=e[t*2+1];return{real:n,imag:s}}function RL(e,t,n,s){e[s*2]=t,e[s*2+1]=n}function _L(e,t){let n=new Float32Array(e/2),s=new Float32Array(e/2);for(let r=0;r<Math.ceil(e/2);r++){let a=(t?2:-2)*Math.PI*(r/e);n[r]=Math.cos(a),s[r]=Math.sin(a)}return{real:n,imag:s}}function DL(e,t,n){let s=(n?2:-2)*Math.PI*(e/t),r=Math.cos(s),a=Math.sin(s);return{real:r,imag:a}}var i3="->",$L=/->/g,kv=",",Iv="...";function PL(e,t){e=e.replace(/\s/g,"");let n=(e.length-e.replace($L,"").length)/i3.length;if(n<1)throw new Error("Equations without an arrow are not supported.");if(n>1)throw new Error(`Equation must contain exactly one arrow ("${i3}").`);let[s,r]=e.split(i3);M(s.indexOf(Iv)===-1,()=>`The ellipsis notation ("${Iv}") is not supported yet.`);let a=s.split(kv),o=a.length;if(t!==o)throw new Error(`Expected ${o} input tensors, received ${t}`);if(o>2)throw new Error("Support for more than 2 input tensors is not implemented yet.");let i=[];for(let d=0;d<r.length;++d){let h=r[d];if(!a.some(f=>f.indexOf(h)!==-1))throw new Error(`Output subscripts contain the label ${h} not present in the input subscripts.`);i.indexOf(h)===-1&&i.push(h)}for(let d=0;d<s.length;++d){let h=s[d];i.indexOf(h)===-1&&h!==kv&&i.push(h)}let l=new Array(a.length);for(let d=0;d<o;++d){if(new Set(a[d].split("")).size!==a[d].length)throw new Error(`Found duplicate axes in input component ${a[d]}. Support for duplicate axes in input is not implemented yet.`);l[d]=[];for(let h=0;h<a[d].length;++h)l[d].push(i.indexOf(a[d][h]))}let u=i.length,c=r.length,p=[];for(let d=c;d<u;++d)p.push(d);return{allDims:i,summedDims:p,idDims:l}}function FL(e,t){let n=new Array(e);n.fill(-1);for(let r=0;r<t.length;++r)n[t[r]]=r;let s=[];for(let r=0;r<e;++r)n[r]===-1&&s.push(r);return n=n.filter(r=>r!==-1),{permutationIndices:n,expandDims:s}}function OL(e,t,n){let s=new Array(e);for(let r=0;r<n.length;++r){let a=n[r].shape;for(let o=0;o<t[r].length;++o)s[t[r][o]]===void 0?s[t[r][o]]=a[o]:M(s[t[r][o]]===a[o],()=>`Expected dimension ${s[t[r][o]]} at axis ${o} of input shaped ${JSON.stringify(a)}, but got dimension ${a[o]}`)}}function ML(e,t){let n=e,s=[],r=0;e.length===0&&n.push(-1),r=e.length+1;for(let o=0;o<r;++o)s.push([]);let a=[];for(let o=0;o<n.length;++o){let i=n[o],l=LL(t,i);for(let u of l)a.indexOf(u)===-1&&(s[o].push(u),a.push(u))}return{path:n,steps:s}}function zL(e){return e.every((t,n)=>t===n)}function LL(e,t){let n=[];for(let s=0;s<e.length;++s)(e[s].length===0||e[s].indexOf(t)!==-1||t===-1)&&n.push(s);return n}function BL(e,t,n=0){let s=[];if(typeof t=="number")M(e.shape[n]%t===0,()=>"Number of splits must evenly divide the axis."),s=new Array(t).fill(e.shape[n]/t);else{let r=t.reduce((o,i)=>(i===-1&&(o+=1),o),0);M(r<=1,()=>"There should be only one negative value in split array.");let a=t.indexOf(-1);if(a!==-1){let o=t.reduce((i,l)=>l>0?i+l:i);t[a]=e.shape[n]-o}M(e.shape[n]===t.reduce((o,i)=>o+i),()=>"The sum of sizes must match the size of the axis dimension."),s=t}return s}function WL(e){return`Received SparseTensor with denseShape[0] = 0 but
+         ${a.shape}`);let o={data:s,indices:r,segmentIds:a};return W.runKernel(Kp,o)}var nL=V({sparseSegmentSum_:tL});function sL(e,t,n,s,r,a,o,i){let l=D(e,"data","stringNGrams","string");if(l.dtype!=="string")throw new Error("Data must be of datatype string");if(l.shape.length!==1)throw new Error(`Data must be a vector, saw: ${l.shape}`);let u=D(t,"dataSplits","stringNGrams");if(u.dtype!=="int32")throw new Error("Data splits must be of datatype int32");let c={separator:n,nGramWidths:s,leftPad:r,rightPad:a,padWidth:o,preserveShortSequences:i},p={data:l,dataSplits:u},d=W.runKernel(Mc,p,c);return{nGrams:d[0],nGramsSplits:d[1]}}var rL=V({stringNGrams_:sL});function aL(e,t,n=!0){let s=D(e,"input","stringSplit","string"),r=D(t,"delimiter","stringSplit","string");if(s.rank!==1)throw new Error(`Input should be Tensor1D but received shape ${s.shape}`);if(r.rank!==0)throw new Error(`Delimiter should be a scalar but received shape ${r.shape}`);let a={skipEmpty:n},o={input:s,delimiter:r},i=W.runKernel(Yp,o,a);return{indices:i[0],values:i[1],shape:i[2]}}var oL=V({stringSplit_:aL});function iL(e,t){let n=D(e,"input","stringToHashBucketFast","string"),s={numBuckets:t};if(t<=0)throw new Error("Number of buckets must be at least 1");let r={input:n};return W.runKernel(Jp,r,s)}var lL=V({stringToHashBucketFast_:iL}),Qw={fft:Ah,ifft:Ju,rfft:xh,irfft:O0},e8={hammingWindow:BM,hannWindow:jw,frame:qw,stft:GM},Ne={flipLeftRight:XM,grayscaleToRGB:ZM,resizeNearestNeighbor:Jw,resizeBilinear:Yw,rotateWithOffset:JM,cropAndResize:jM,nonMaxSuppression:ez,nonMaxSuppressionAsync:lz,nonMaxSuppressionWithScore:cz,nonMaxSuppressionWithScoreAsync:pz,nonMaxSuppressionPadded:fz,nonMaxSuppressionPaddedAsync:gz,threshold:vz,transform:kz},HA={bandPart:Sz,gramSchmidt:Tz,qr:Ez},t8={absoluteDifference:Dz,computeWeightedLoss:va,cosineDistance:Pz,hingeLoss:Oz,huberLoss:zz,logLoss:Bz,meanSquaredError:Vz,sigmoidCrossEntropy:Hz,softmaxCrossEntropy:Xz},n8={sparseFillEmptyRows:Zz,sparseReshape:Jz,sparseSegmentMean:eL,sparseSegmentSum:nL},s8={stringNGrams:rL,stringSplit:oL,stringToHashBucketFast:lL},wa=class extends Z6{minimize(e,t=!1,n){let{value:s,grads:r}=this.computeGradients(e,n);if(n!=null){let a=n.map(o=>({name:o.name,tensor:r[o.name]}));this.applyGradients(a)}else this.applyGradients(r);return ne(r),t?s:(s.dispose(),null)}get iterations(){return this.iterations_==null&&(this.iterations_=0),this.iterations_}incrementIterations(){this.iterations_=this.iterations+1}computeGradients(e,t){return fw(e,t)}dispose(){this.iterations_!=null&&ne(this.iterations_)}async saveIterations(){return this.iterations_==null&&(this.iterations_=0),{name:"iter",tensor:Se(this.iterations_,"int32")}}async getWeights(){throw new Error("getWeights() is not implemented for this optimizer yet.")}async setWeights(e){throw new Error(`setWeights() is not implemented for this optimizer class ${this.getClassName()}`)}async extractIterations(e){return this.iterations_=(await e[0].tensor.data())[0],e.slice(1)}};Object.defineProperty(wa,Symbol.hasInstance,{value:e=>e.minimize!=null&&e.computeGradients!=null&&e.applyGradients!=null});var H0=class extends wa{constructor(e,t,n=null){super(),this.learningRate=e,this.rho=t,this.epsilon=n,this.accumulatedGrads=[],this.accumulatedUpdates=[],n==null&&(this.epsilon=W.backend.epsilon())}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=W.registeredVariables[n],a=!1;this.accumulatedGrads[s]==null&&(this.accumulatedGrads[s]={originalName:`${n}/accum_grad`,variable:J(()=>it(r).variable(a))}),this.accumulatedUpdates[s]==null&&(this.accumulatedUpdates[s]={originalName:`${n}/accum_var`,variable:J(()=>it(r).variable(a))});let o=Array.isArray(e)?e[s].tensor:e[n];if(o==null)return;let i=this.accumulatedGrads[s].variable,l=this.accumulatedUpdates[s].variable;J(()=>{let u=ce(L(i,this.rho),L(vt(o),1-this.rho)),c=L(pe(Nn(ce(l,this.epsilon)),Nn(ce(i,this.epsilon))),o),p=ce(L(l,this.rho),L(vt(c),1-this.rho));i.assign(u),l.assign(p);let d=ce(L(c,-this.learningRate),r);r.assign(d)})}),this.incrementIterations()}dispose(){this.accumulatedUpdates!=null&&(ne(this.accumulatedGrads.map(e=>e.variable)),ne(this.accumulatedUpdates.map(e=>e.variable)))}async getWeights(){let e=[...this.accumulatedGrads,...this.accumulatedUpdates];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=e.length/2,n=!1;this.accumulatedGrads=e.slice(0,t).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})),this.accumulatedUpdates=e.slice(t,t*2).map(s=>({originalName:s.name,variable:s.tensor.variable(n)}))}getConfig(){return{learningRate:this.learningRate,rho:this.rho,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.rho,t.epsilon)}};H0.className="Adadelta";oi(H0);var j0=class extends wa{constructor(e,t=.1){super(),this.learningRate=e,this.initialAccumulatorValue=t,this.accumulatedGrads=[]}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=W.registeredVariables[n];this.accumulatedGrads[s]==null&&(this.accumulatedGrads[s]={originalName:`${n}/accumulator`,variable:J(()=>Gc(r.shape,this.initialAccumulatorValue).variable(!1))});let a=Array.isArray(e)?e[s].tensor:e[n];if(a==null)return;let o=this.accumulatedGrads[s].variable;J(()=>{let i=ce(o,vt(a));o.assign(i);let l=ce(L(pe(a,Nn(ce(i,W.backend.epsilon()))),-this.learningRate),r);r.assign(l)})}),this.incrementIterations()}dispose(){this.accumulatedGrads!=null&&ne(this.accumulatedGrads.map(e=>e.variable))}async getWeights(){return[await this.saveIterations()].concat(this.accumulatedGrads.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulatedGrads=e.map(n=>({originalName:n.name,variable:n.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,initialAccumulatorValue:this.initialAccumulatorValue}}static fromConfig(e,t){return new e(t.learningRate,t.initialAccumulatorValue)}};j0.className="Adagrad";oi(j0);var q0=class extends wa{constructor(e,t,n,s=null){super(),this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=s,this.accumulatedFirstMoment=[],this.accumulatedSecondMoment=[],J(()=>{this.accBeta1=Se(t).variable(),this.accBeta2=Se(n).variable()}),s==null&&(this.epsilon=W.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);J(()=>{let n=he(1,this.accBeta1),s=he(1,this.accBeta2);t.forEach((r,a)=>{let o=W.registeredVariables[r],i=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${r}/m`,variable:J(()=>it(o).variable(i))}),this.accumulatedSecondMoment[a]==null&&(this.accumulatedSecondMoment[a]={originalName:`${r}/v`,variable:J(()=>it(o).variable(i))});let l=Array.isArray(e)?e[a].tensor:e[r];if(l==null)return;let u=this.accumulatedFirstMoment[a].variable,c=this.accumulatedSecondMoment[a].variable,p=ce(L(u,this.beta1),L(l,1-this.beta1)),d=ce(L(c,this.beta2),L(vt(l),1-this.beta2)),h=pe(p,n),f=pe(d,s);u.assign(p),c.assign(d);let m=ce(L(pe(h,ce(Nn(f),this.epsilon)),-this.learningRate),o);o.assign(m)}),this.accBeta1.assign(L(this.accBeta1,this.beta1)),this.accBeta2.assign(L(this.accBeta2,this.beta2))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.accBeta2.dispose(),this.accumulatedFirstMoment!=null&&ne(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedSecondMoment!=null&&ne(this.accumulatedSecondMoment.map(e=>e.variable))}async getWeights(){let e=[...this.accumulatedFirstMoment,...this.accumulatedSecondMoment];return[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e),J(()=>{this.accBeta1.assign(ga(this.beta1,this.iterations_+1)),this.accBeta2.assign(ga(this.beta2,this.iterations_+1))});let t=e.length/2,n=!1;this.accumulatedFirstMoment=e.slice(0,t).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})),this.accumulatedSecondMoment=e.slice(t,t*2).map(s=>({originalName:s.name,variable:s.tensor.variable(n)}))}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon)}};q0.className="Adam";oi(q0);var X0=class extends wa{constructor(e,t,n,s=null,r=0){super(),this.learningRate=e,this.beta1=t,this.beta2=n,this.epsilon=s,this.decay=r,this.accumulatedFirstMoment=[],this.accumulatedWeightedInfNorm=[],J(()=>{this.iteration=Se(0).variable(),this.accBeta1=Se(t).variable()}),s==null&&(this.epsilon=W.backend.epsilon())}applyGradients(e){let t=Array.isArray(e)?e.map(n=>n.name):Object.keys(e);J(()=>{let n=he(1,this.accBeta1),s=pe(-this.learningRate,ce(L(this.iteration,this.decay),1));t.forEach((r,a)=>{let o=W.registeredVariables[r],i=!1;this.accumulatedFirstMoment[a]==null&&(this.accumulatedFirstMoment[a]={originalName:`${r}/m`,variable:it(o).variable(i)}),this.accumulatedWeightedInfNorm[a]==null&&(this.accumulatedWeightedInfNorm[a]={originalName:`${r}/v`,variable:it(o).variable(i)});let l=Array.isArray(e)?e[a].tensor:e[r];if(l==null)return;let u=this.accumulatedFirstMoment[a].variable,c=this.accumulatedWeightedInfNorm[a].variable,p=ce(L(u,this.beta1),L(l,1-this.beta1)),d=L(c,this.beta2),h=tn(l),f=Yr(d,h);u.assign(p),c.assign(f);let m=ce(L(pe(s,n),pe(p,ce(f,this.epsilon))),o);o.assign(m)}),this.iteration.assign(ce(this.iteration,1)),this.accBeta1.assign(L(this.accBeta1,this.beta1))}),this.incrementIterations()}dispose(){this.accBeta1.dispose(),this.iteration.dispose(),this.accumulatedFirstMoment!=null&&ne(this.accumulatedFirstMoment.map(e=>e.variable)),this.accumulatedWeightedInfNorm!=null&&ne(this.accumulatedWeightedInfNorm.map(e=>e.variable))}async getWeights(){throw new Error("getWeights() is not implemented for Adamax yet.")}async setWeights(e){throw new Error("setWeights() is not implemented for Adamax yet.")}getConfig(){return{learningRate:this.learningRate,beta1:this.beta1,beta2:this.beta2,epsilon:this.epsilon,decay:this.decay}}static fromConfig(e,t){return new e(t.learningRate,t.beta1,t.beta2,t.epsilon,t.decay)}};X0.className="Adamax";oi(X0);var bh=class extends wa{constructor(e){super(),this.learningRate=e,this.setLearningRate(e)}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=Array.isArray(e)?e[s].tensor:e[n];if(r==null)return;let a=W.registeredVariables[n];J(()=>{let o=ce(L(this.c,r),a);a.assign(o)})}),this.incrementIterations()}setLearningRate(e){this.learningRate=e,this.c!=null&&this.c.dispose(),this.c=bn(Se(-e))}dispose(){this.c.dispose()}async getWeights(){return[await this.saveIterations()]}async setWeights(e){if(e=await this.extractIterations(e),e.length!==0)throw new Error("SGD optimizer does not have settable weights.")}getConfig(){return{learningRate:this.learningRate}}static fromConfig(e,t){return new e(t.learningRate)}};bh.className="SGD";oi(bh);var K0=class extends bh{constructor(e,t,n=!1){super(e),this.learningRate=e,this.momentum=t,this.useNesterov=n,this.accumulations=[],this.m=Se(this.momentum)}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=W.registeredVariables[n];this.accumulations[s]==null&&(this.accumulations[s]={originalName:`${n}/momentum`,variable:J(()=>it(r).variable(!1))});let a=this.accumulations[s].variable,o=Array.isArray(e)?e[s].tensor:e[n];o!=null&&J(()=>{let i,l=ce(L(this.m,a),o);this.useNesterov?i=ce(L(this.c,ce(o,L(l,this.m))),r):i=ce(L(this.c,l),r),a.assign(l),r.assign(i)})}),this.incrementIterations()}dispose(){this.m.dispose(),this.accumulations!=null&&ne(this.accumulations.map(e=>e.variable))}setMomentum(e){this.momentum=e}async getWeights(){return[await this.saveIterations()].concat(this.accumulations.map(e=>({name:e.originalName,tensor:e.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=!1;this.accumulations=e.map(n=>({originalName:n.name,variable:n.tensor.variable(t)}))}getConfig(){return{learningRate:this.learningRate,momentum:this.momentum,useNesterov:this.useNesterov}}static fromConfig(e,t){return new e(t.learningRate,t.momentum,t.useNesterov)}};K0.className="Momentum";oi(K0);var Z0=class extends wa{constructor(e,t=.9,n=0,s=null,r=!1){if(super(),this.learningRate=e,this.decay=t,this.momentum=n,this.epsilon=s,this.accumulatedMeanSquares=[],this.accumulatedMoments=[],this.accumulatedMeanGrads=[],this.centered=r,s==null&&(this.epsilon=W.backend.epsilon()),e==null)throw new Error("learningRate for RMSPropOptimizer must be defined.")}applyGradients(e){(Array.isArray(e)?e.map(n=>n.name):Object.keys(e)).forEach((n,s)=>{let r=W.registeredVariables[n],a=!1;this.accumulatedMeanSquares[s]==null&&(this.accumulatedMeanSquares[s]={originalName:`${n}/rms`,variable:J(()=>it(r).variable(a))}),this.accumulatedMoments[s]==null&&(this.accumulatedMoments[s]={originalName:`${n}/momentum`,variable:J(()=>it(r).variable(a))}),this.accumulatedMeanGrads[s]==null&&this.centered&&(this.accumulatedMeanGrads[s]={originalName:`${n}/mg`,variable:J(()=>it(r).variable(a))});let o=Array.isArray(e)?e[s].tensor:e[n];if(o==null)return;let i=this.accumulatedMeanSquares[s].variable,l=this.accumulatedMoments[s].variable;J(()=>{let u=ce(L(i,this.decay),L(vt(o),1-this.decay));if(this.centered){let c=this.accumulatedMeanGrads[s].variable,p=ce(L(c,this.decay),L(o,1-this.decay)),d=pe(L(o,this.learningRate),Nn(he(u,ce(vt(p),this.epsilon)))),h=ce(L(l,this.momentum),d);i.assign(u),c.assign(p),l.assign(h);let f=he(r,h);r.assign(f)}else{let c=ce(L(i,this.decay),L(vt(o),1-this.decay)),p=ce(L(l,this.momentum),pe(L(o,this.learningRate),Nn(ce(c,this.epsilon))));i.assign(c),l.assign(p);let d=he(r,p);r.assign(d)}})}),this.incrementIterations()}dispose(){this.accumulatedMeanSquares!=null&&ne(this.accumulatedMeanSquares.map(e=>e.variable)),this.accumulatedMeanGrads!=null&&this.centered&&ne(this.accumulatedMeanGrads.map(e=>e.variable)),this.accumulatedMoments!=null&&ne(this.accumulatedMoments.map(e=>e.variable))}async getWeights(){let e=[...this.accumulatedMeanSquares,...this.accumulatedMoments];return this.centered&&e.push(...this.accumulatedMeanGrads),[await this.saveIterations()].concat(e.map(t=>({name:t.originalName,tensor:t.variable})))}async setWeights(e){e=await this.extractIterations(e);let t=this.centered?e.length/3:e.length/2,n=!1;this.accumulatedMeanSquares=e.slice(0,t).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})),this.accumulatedMoments=e.slice(t,t*2).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})),this.centered&&(this.accumulatedMeanGrads=e.slice(t*2,t*3).map(s=>({originalName:s.name,variable:s.tensor.variable(n)})))}getConfig(){return{learningRate:this.learningRate,decay:this.decay,momentum:this.momentum,epsilon:this.epsilon,centered:this.centered}}static fromConfig(e,t){return new e(t.learningRate,t.decay,t.momentum,t.epsilon,t.centered)}};Z0.className="RMSProp";oi(Z0);var Ba=class{static sgd(e){return new bh(e)}static momentum(e,t,n=!1){return new K0(e,t,n)}static rmsprop(e,t=.9,n=0,s=null,r=!1){return new Z0(e,t,n,s,r)}static adam(e=.001,t=.9,n=.999,s=null){return new q0(e,t,n,s)}static adadelta(e=.001,t=.95,n=null){return new H0(e,t,n)}static adamax(e=.002,t=.9,n=.999,s=null,r=0){return new X0(e,t,n,s,r)}static adagrad(e,t=.1){return new j0(e,t)}},Pi={sgd:Ba.sgd,momentum:Ba.momentum,adadelta:Ba.adadelta,adagrad:Ba.adagrad,rmsprop:Ba.rmsprop,adamax:Ba.adamax,adam:Ba.adam},uL=(()=>typeof requestAnimationFrame!="undefined"?requestAnimationFrame:typeof setImmediate!="undefined"?setImmediate:e=>e())();function jA(){return new Promise(e=>uL(()=>e()))}var C={};Ve(C,{ERF_A1:()=>bL,ERF_A2:()=>vL,ERF_A3:()=>wL,ERF_A4:()=>kL,ERF_A5:()=>IL,ERF_P:()=>xL,PARALLELIZE_THRESHOLD:()=>qA,SELU_SCALE:()=>a8,SELU_SCALEALPHA:()=>r8,applyActivation:()=>U0,assertAndGetBroadcastShape:()=>kt,assertAxesAreInnerMostDims:()=>yF,assertParamsConsistent:()=>cL,assignToTypedArray:()=>RL,axesAreInnerMostDims:()=>yA,calculateShapes:()=>B6,checkEinsumDimSizes:()=>OL,checkPadOnDimRoundingMode:()=>rs,combineLocations:()=>uw,complexWithEvenIndex:()=>TL,complexWithOddIndex:()=>NL,computeConv2DInfo:()=>oh,computeConv3DInfo:()=>tw,computeDefaultPad:()=>Qy,computeDilation2DInfo:()=>AP,computeOptimalWindowSize:()=>pL,computeOutAndReduceShapes:()=>cw,computeOutShape:()=>dL,computePool2DInfo:()=>ew,computePool3DInfo:()=>xP,convertConv2DDataFormat:()=>nw,decodeEinsumEquation:()=>PL,eitherStridesOrDilationsAreOne:()=>Zr,expandShapeToKeepDim:()=>Yi,exponent:()=>DL,exponents:()=>_L,fromStringArrayToUint8:()=>sB,fromUint8ToStringArray:()=>nB,getAxesPermutation:()=>dw,getBroadcastDims:()=>M6,getComplexWithIndex:()=>EL,getEinsumComputePath:()=>ML,getEinsumPermutation:()=>FL,getFusedBiasGradient:()=>V0,getFusedDyActivation:()=>W0,getImageCenter:()=>hL,getInnerMostAxes:()=>AF,getPermuted:()=>mL,getReductionAxes:()=>an,getReshaped:()=>fL,getReshapedPermuted:()=>gL,getSliceBeginCoords:()=>yL,getSliceSize:()=>AL,getSparseFillEmptyRowsIndicesDenseShapeMismatch:()=>WL,getSparseFillEmptyRowsNegativeIndexErrorMessage:()=>VL,getSparseFillEmptyRowsOutOfRangeIndexErrorMessage:()=>UL,getSparseReshapeEmptyTensorZeroOutputDimErrorMessage:()=>jL,getSparseReshapeInputOutputMismatchErrorMessage:()=>XL,getSparseReshapeInputOutputMultipleErrorMessage:()=>qL,getSparseReshapeMultipleNegativeOneOutputDimErrorMessage:()=>GL,getSparseReshapeNegativeOutputDimErrorMessage:()=>HL,getSparseSegmentReductionIndicesOutOfRangeErrorMessage:()=>JL,getSparseSegmentReductionNegativeSegmentIdsErrorMessage:()=>KL,getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage:()=>ZL,getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage:()=>YL,getUndoAxesPermutation:()=>AA,isIdentityPermutation:()=>zL,log:()=>U_,mergeRealAndImagArrays:()=>SL,prepareAndValidate:()=>L6,prepareSplitSize:()=>BL,segment_util:()=>o8,shouldFuse:()=>G0,slice_util:()=>Ut,splitRealAndImagArrays:()=>CL,tupleValuesAreOne:()=>eo,upcastType:()=>On,validateInput:()=>Wy,validateUpdateShape:()=>By,warn:()=>Va});function cL(e,t){let n=e[0].length;e.forEach((r,a)=>{M(r.length===n,()=>`Error in concat${n}D: rank of tensors[${a}] must be the same as the rank of the rest (${n})`)}),M(t>=0&&t<n,()=>`Error in concat${n}D: axis must be between 0 and ${n-1}.`);let s=e[0];e.forEach((r,a)=>{for(let o=0;o<n;o++)M(o===t||r[o]===s[o],()=>`Error in concat${n}D: Shape of tensors[${a}] (${r}) does not match the shape of the rest (${s}) along the non-concatenated axis ${a}.`)})}function dL(e,t){let n=e[0].slice();for(let s=1;s<e.length;s++)n[t]+=e[s][t];return n}var qA=30;function pL(e){return e<=qA?e:cm(e,Math.floor(Math.sqrt(e)))}function hL(e,t,n){let s=n*(typeof e=="number"?e:e[0]),r=t*(typeof e=="number"?e:e[1]);return[s,r]}function fL(e,t,n,s=!0){let r=[];if(s)r=r.concat(t.slice(0)),r.push(e[0]/n),r=r.concat(e.slice(1));else{r=r.concat(e[0]);let a=t.length;for(let o=0;o<a;++o)r=r.concat([e[o+1]/t[o],t[o]]);r=r.concat(e.slice(a+1))}return r}function mL(e,t,n=!0){let s=[];if(n){s.push(t);for(let r=t+1;r<e;++r)r<=2*t?(s.push(r),s.push(r-(t+1))):s.push(r)}else{let r=[],a=[];for(let o=1;o<e;++o)o>=t*2+1||o%2===1?a.push(o):r.push(o);s.push(...r),s.push(0),s.push(...a)}return s}function gL(e,t,n,s=!0){let r=[];s?r.push(e[0]/n):r.push(e[0]*n);for(let a=1;a<e.length;++a)a<=t.length?s?r.push(t[a-1]*e[a]):r.push(e[a]/t[a-1]):r.push(e[a]);return r}function yL(e,t){let n=[0];for(let s=0;s<t;++s)n.push(e[s][0]);return n}function AL(e,t,n){let s=e.slice(0,1);for(let r=0;r<n;++r)s.push(e[r+1]-t[r][0]-t[r][1]);return s}var r8=1.7580993408473768,a8=1.0507009873554805,xL=.3275911,bL=.254829592,vL=-.284496736,wL=1.421413741,kL=-1.453152027,IL=1.061405429;function SL(e,t){if(e.length!==t.length)throw new Error(`Cannot merge real and imag arrays of different lengths. real:${e.length}, imag: ${t.length}.`);let n=new Float32Array(e.length*2);for(let s=0;s<n.length;s+=2)n[s]=e[s/2],n[s+1]=t[s/2];return n}function CL(e){let t=new Float32Array(e.length/2),n=new Float32Array(e.length/2);for(let s=0;s<e.length;s+=2)t[s/2]=e[s],n[s/2]=e[s+1];return{real:t,imag:n}}function TL(e){let t=Math.ceil(e.length/4),n=new Float32Array(t),s=new Float32Array(t);for(let r=0;r<e.length;r+=4)n[Math.floor(r/4)]=e[r],s[Math.floor(r/4)]=e[r+1];return{real:n,imag:s}}function NL(e){let t=Math.floor(e.length/4),n=new Float32Array(t),s=new Float32Array(t);for(let r=2;r<e.length;r+=4)n[Math.floor(r/4)]=e[r],s[Math.floor(r/4)]=e[r+1];return{real:n,imag:s}}function EL(e,t){let n=e[t*2],s=e[t*2+1];return{real:n,imag:s}}function RL(e,t,n,s){e[s*2]=t,e[s*2+1]=n}function _L(e,t){let n=new Float32Array(e/2),s=new Float32Array(e/2);for(let r=0;r<Math.ceil(e/2);r++){let a=(t?2:-2)*Math.PI*(r/e);n[r]=Math.cos(a),s[r]=Math.sin(a)}return{real:n,imag:s}}function DL(e,t,n){let s=(n?2:-2)*Math.PI*(e/t),r=Math.cos(s),a=Math.sin(s);return{real:r,imag:a}}var o3="->",$L=/->/g,kv=",",Iv="...";function PL(e,t){e=e.replace(/\s/g,"");let n=(e.length-e.replace($L,"").length)/o3.length;if(n<1)throw new Error("Equations without an arrow are not supported.");if(n>1)throw new Error(`Equation must contain exactly one arrow ("${o3}").`);let[s,r]=e.split(o3);M(s.indexOf(Iv)===-1,()=>`The ellipsis notation ("${Iv}") is not supported yet.`);let a=s.split(kv),o=a.length;if(t!==o)throw new Error(`Expected ${o} input tensors, received ${t}`);if(o>2)throw new Error("Support for more than 2 input tensors is not implemented yet.");let i=[];for(let d=0;d<r.length;++d){let h=r[d];if(!a.some(f=>f.indexOf(h)!==-1))throw new Error(`Output subscripts contain the label ${h} not present in the input subscripts.`);i.indexOf(h)===-1&&i.push(h)}for(let d=0;d<s.length;++d){let h=s[d];i.indexOf(h)===-1&&h!==kv&&i.push(h)}let l=new Array(a.length);for(let d=0;d<o;++d){if(new Set(a[d].split("")).size!==a[d].length)throw new Error(`Found duplicate axes in input component ${a[d]}. Support for duplicate axes in input is not implemented yet.`);l[d]=[];for(let h=0;h<a[d].length;++h)l[d].push(i.indexOf(a[d][h]))}let u=i.length,c=r.length,p=[];for(let d=c;d<u;++d)p.push(d);return{allDims:i,summedDims:p,idDims:l}}function FL(e,t){let n=new Array(e);n.fill(-1);for(let r=0;r<t.length;++r)n[t[r]]=r;let s=[];for(let r=0;r<e;++r)n[r]===-1&&s.push(r);return n=n.filter(r=>r!==-1),{permutationIndices:n,expandDims:s}}function OL(e,t,n){let s=new Array(e);for(let r=0;r<n.length;++r){let a=n[r].shape;for(let o=0;o<t[r].length;++o)s[t[r][o]]===void 0?s[t[r][o]]=a[o]:M(s[t[r][o]]===a[o],()=>`Expected dimension ${s[t[r][o]]} at axis ${o} of input shaped ${JSON.stringify(a)}, but got dimension ${a[o]}`)}}function ML(e,t){let n=e,s=[],r=0;e.length===0&&n.push(-1),r=e.length+1;for(let o=0;o<r;++o)s.push([]);let a=[];for(let o=0;o<n.length;++o){let i=n[o],l=LL(t,i);for(let u of l)a.indexOf(u)===-1&&(s[o].push(u),a.push(u))}return{path:n,steps:s}}function zL(e){return e.every((t,n)=>t===n)}function LL(e,t){let n=[];for(let s=0;s<e.length;++s)(e[s].length===0||e[s].indexOf(t)!==-1||t===-1)&&n.push(s);return n}function BL(e,t,n=0){let s=[];if(typeof t=="number")M(e.shape[n]%t===0,()=>"Number of splits must evenly divide the axis."),s=new Array(t).fill(e.shape[n]/t);else{let r=t.reduce((o,i)=>(i===-1&&(o+=1),o),0);M(r<=1,()=>"There should be only one negative value in split array.");let a=t.indexOf(-1);if(a!==-1){let o=t.reduce((i,l)=>l>0?i+l:i);t[a]=e.shape[n]-o}M(e.shape[n]===t.reduce((o,i)=>o+i),()=>"The sum of sizes must match the size of the axis dimension."),s=t}return s}function WL(e){return`Received SparseTensor with denseShape[0] = 0 but
   indices.shape[0] = ${e}`}function VL(e,t){return`indices(${e}, 0) is invalid: ${t} < 0`}function UL(e,t,n){return`indices(${e}, 0) is invalid: ${t} >= ${n}`}function GL(e,t){return`only one output dimension may be -1, not both ${e} and ${t}`}function HL(e,t){return`size ${e} must be non-negative, not ${t}`}function jL(){return"reshape cannot infer the missing input size for an empty tensor unless all specified input sizes are non-zero"}function qL(e,t){let n=Et(e),s=Et(t);return`Input to reshape is a SparseTensor with ${n}
-  dense values, but the requested shape requires a multiple of ${s}. inputShape=${e} outputShape= ${t}`}function XL(e,t){let n=Et(e),s=Et(t);return`Input to reshape is a tensor with ${n} dense values, but the requested shape has ${s}. inputShape=${e} outputShape=${t}`}function KL(){return"segment ids must be >= 0"}function ZL(){return"segment ids are not increasing"}function YL(e,t){return`Segment id ${e} out of range [0, ${t}), possibly because segmentIds input is not sorted.`}function JL(e,t,n){return`Bad: indices[${e}] == ${t} out of range [0, ${n})`}var o8={};Ve(o8,{collectGatherOpShapeInfo:()=>tB,computeOutShape:()=>eB,segOpComputeOptimalWindowSize:()=>QL});function QL(e,t){let n=!1,s;for(e<=qA?(s=e,n=!0):s=dm(e,Math.floor(Math.sqrt(e)));!n;)s>t||s===e?n=!0:s=dm(e,s+1);return s}function eB(e,t,n){let s=[],r=e.length;for(let a=0;a<r;a++)a!==t?s.push(e[a]):s.push(n);return s}function tB(e,t,n,s){let r=t.shape.length,a=e.shape.length;if(s!==0&&(s<-r||s>r))throw new Error(`Expect batchDims in the range of [-${r}, ${r}], but got ${s}`);if(s<0&&(s+=r),s>a)throw new Error(`batchDims (${s}) must be less than rank(x) (
-    ${a}).`);if(n<s)throw new Error(`batchDims (${s}) must be less than or equal to axis (${n}).`);for(let p=0;p<s;++p)if(e.shape[p]!==t.shape[p])throw new Error(`x.shape[${p}]: ${e.shape[p]} should be equal to indices.shape[${p}]: ${t.shape[p]}.`);let o=e.shape[n],i=[],l=1,u=1,c=1;for(let p=0;p<s;++p)i.push(e.shape[p]),l*=e.shape[p];for(let p=s;p<n;p++)i.push(e.shape[p]),u*=e.shape[p];for(let p=s;p<r;p++)i.push(t.shape[p]);for(let p=n+1;p<a;p++)i.push(e.shape[p]),c*=e.shape[p];return{batchSize:l,sliceSize:c,outerSize:u,dimSize:o,outputShape:i}}function nB(e){try{return e.map(t=>mm(t))}catch(t){throw new Error(`Failed to decode encoded string bytes into utf-8, error: ${t}`)}}function sB(e){return e.map(t=>nh(t))}var dr={};Ve(dr,{nonMaxSuppressionV3Impl:()=>Xw,nonMaxSuppressionV4Impl:()=>Kw,nonMaxSuppressionV5Impl:()=>Zw,whereImpl:()=>Mw});var i8={kernelName:il,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,Ql(ge(n,"float32"),-1))}}},rB={kernelName:pc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let s=vt(ge(n,"float32")),r=Nn(he(Se(1),s));return Dt(pe(e,r))}}}},aB={kernelName:hc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let s=Nn(he(vt(ge(n,"float32")),1));return pe(e,s)}}}},oB={kernelName:xa,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=kt(n.shape,s.shape);return{a:()=>{let i=e,l=an(n.shape,r);return l.length>0&&(i=ke(i,l)),U(i,n.shape)},b:()=>{let i=e,l=an(s.shape,r);return l.length>0&&(i=ke(i,l)),U(i,s.shape)}}}},iB={kernelName:po,saveAllInputs:!0,gradFunc:(e,t)=>{let n={};return t.forEach((s,r)=>{n[r]=()=>e.clone()}),n}},lB={kernelName:ho,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>it(n)}}},uB={kernelName:gc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>it(n)}}},cB={kernelName:yc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,Nn(he(Se(1),vt(ge(n,"float32")))))}}},dB={kernelName:Ac,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let s=Nn(ce(Se(1),vt(ge(n,"float32"))));return pe(e,s)}}}},pB={kernelName:vc,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=kt(n.shape,s.shape);return{a:()=>{let i=ce(vt(n),vt(s)),l=L(e,pe(s,i)),u=an(n.shape,r);return u.length>0&&(l=ke(l,u)),U(l,n.shape)},b:()=>{let i=ce(vt(n),vt(s)),l=Dt(L(e,pe(n,i))),u=an(s.shape,r);return u.length>0&&(l=ke(l,u)),U(l,s.shape)}}}},hB={kernelName:xc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,ce(vt(ge(n,"float32")),1))}}},fB={kernelName:bc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,he(Se(1),vt(ge(n,"float32"))))}}};function mB(e,t,n,s,r,a){let o=D(e,"dy","avgPool3dGrad"),i=D(t,"input","avgPool3dGrad"),l=o,u=i,c=!1;i.rank===4&&(c=!0,l=U(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]]),u=U(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),M(l.rank===5,()=>`Error in avgPool3dGrad: dy must be rank 5 but got rank ${l.rank}.`),M(u.rank===5,()=>`Error in avgPool3dGrad: input must be rank 5 but got rank ${u.rank}.`),rs("avgPool3dGrad",r,a);let p={dy:l,input:u},d={filterSize:n,strides:s,pad:r,dimRoundingMode:a},h=W.runKernel(Hm,p,d);return c?U(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}var gB=V({avgPool3dGrad_:mB}),yB={kernelName:zp,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{filterSize:r,strides:a,pad:o,dimRoundingMode:i}=n;return{x:()=>gB(e,s,r,a,o,i)}}};function AB(e,t,n,s,r){let a=D(e,"dy","avgPoolGrad"),o=D(t,"input","avgPoolGrad");M(o.rank===a.rank,()=>`Rank of input (${o.rank}) does not match rank of dy (${a.rank})`);let i=o,l=a,u=!1;o.rank===3&&(u=!0,i=U(o,[1,o.shape[0],o.shape[1],o.shape[2]]),l=U(a,[1,a.shape[0],a.shape[1],a.shape[2]])),M(l.rank===4,()=>`Error in avgPoolGrad: dy must be rank 4 but got rank ${l.rank}.`),M(i.rank===4,()=>`Error in avgPoolGrad: input must be rank 4 but got rank ${i.rank}.`);let c={dy:l,input:i},p={filterSize:n,strides:s,pad:r},d=W.runKernel(Gm,c,p);return u?U(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var xB=V({avgPoolGrad_:AB}),bB={kernelName:fo,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{filterSize:r,strides:a,pad:o}=n;return{x:()=>xB(e,s,r,a,o)}}},vB={kernelName:mo,inputsToSave:["a","b"],gradFunc:(e,t,n)=>{let[s,r]=t,{transposeA:a,transposeB:o}=n;return!a&&!o?{a:()=>Qe(e,r,!1,!0),b:()=>Qe(s,e,!0,!1)}:!a&&o?{a:()=>Qe(e,r,!1,!1),b:()=>Qe(e,s,!0,!1)}:a&&!o?{a:()=>Qe(r,e,!1,!0),b:()=>Qe(s,e,!1,!1)}:{a:()=>Qe(r,e,!0,!0),b:()=>Qe(e,s,!0,!0)}}},wB={kernelName:ll,gradFunc:(e,t,n)=>{let{blockShape:s,crops:r}=n;return{x:()=>gh(e,s,r)}}},kB={kernelName:c6,gradFunc:(e,t,n)=>{let s=n,r=s.inputShape,a=s.shape,o=Array.from(a);for(let l=r.length-1;l>=0;l--)if(r[l]===a[l])o[l]=1;else if(r[l]!==1)throw new Error(`broadcastTo(): [${r}] cannot be broadcast to [${a}].`);let i=[];for(let l=0;l<o.length;l++)o[l]>1&&i.push(l);return{x:()=>ke(e,i,!0)}}},IB={kernelName:go,gradFunc:e=>({x:()=>e.clone()})},SB={kernelName:yo,gradFunc:e=>({x:()=>it(e)})},CB={kernelName:ba,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{clipValueMin:r,clipValueMax:a}=n;return{x:()=>Mn(lr(li(s,r),ui(s,a)),e,it(e))}}},TB={kernelName:Bp,inputsToSave:["x"],gradFunc:i8.gradFunc},NB={kernelName:ul,saveAllInputs:!0,gradFunc:(e,t,n)=>{let s=t.map(l=>l.shape),{axis:r}=n,a=ur(r,t[0].shape)[0],o=s.map(l=>l[a]);return Zt(e,o,a).map(l=>()=>l)}},EB={kernelName:Ao,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let[s,r]=t,{dilations:a,strides:o,pad:i,dataFormat:l}=n;return M(to(a),()=>`Error in gradient of conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${a}'`),{x:()=>uA(s.shape,e,r,o,i,l),filter:()=>UA(s,e,r.shape,o,i,l)}}},RB={kernelName:xo,inputsToSave:["dy","filter"],gradFunc:(e,t,n)=>{let[s,r]=t,{strides:a,pad:o,dataFormat:i,dimRoundingMode:l}=n;return{dy:()=>ma(e,r,a,o,i,1,l),filter:()=>UA(e,s,r.shape,a,o,i,l)}}};function _B(e,t,n,s,r){let a=e;e.rank===4&&(a=U(e,[1,e.shape[0],e.shape[1],e.shape[2],e.shape[3]]));let o=t;o.rank===4&&(o=U(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]])),M(a.rank===5,()=>`Error in conv3dDerFilter: input must be rank 5, but got shape ${a.shape}.`),M(o.rank===5,()=>`Error in conv3dDerFilter: dy must be rank 5, but got shape ${o.shape}.`),M(n.length===5,()=>`Error in conv3dDerFilter: filterShape must be length 5, but got ${n}.`),M(a.shape[4]===n[3],()=>`Error in conv3dDerFilter: depth of input ${a.shape[4]}) must match input depth in filter (${n[3]}.`),M(o.shape[4]===n[4],()=>`Error in conv3dDerFilter: depth of dy (${o.shape[4]}) must match output depth for filter (${n[4]}).`);let i={x:a,dy:o},l={strides:s,pad:r,filterShape:n};return W.runKernel(Km,i,l)}var DB=V({conv3DBackpropFilter_:_B}),$B={kernelName:Wp,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let{dilations:s,strides:r,pad:a}=n;M(to(s),()=>`Error in gradient of conv3D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${s}'`);let[o,i]=t;return{x:()=>aw(o.shape,e,i,r,a),filter:()=>DB(o,e,i.shape,r,a)}}},PB={kernelName:bo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(Dt(P0(ge(n,"float32"))),e)}}},FB={kernelName:vo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(F0(ge(n,"float32")),e)}}},OB={kernelName:wo,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{axis:r,exclusive:a,reverse:o}=n;return{x:()=>{let i=dw([r],s.rank),l=b0(e,r,a,!o);return i!=null&&(l=st(l,i)),l}}}},MB={kernelName:ko,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let{dilations:s,strides:r,pad:a,dimRoundingMode:o}=n,i=s==null?[1,1]:s;M(to(i),()=>`Error in gradient of depthwiseConv2dNative: dilation rates greater than 1 are not yet supported. Got dilations '${i}'`);let[l,u]=t;return M(l.rank===4,()=>`Error in gradient of depthwiseConv2dNative: input must be rank 4, but got rank ${l.rank}.`),M(u.rank===4,()=>`Error in gradient of depthwiseConv2dNative: filter must be rank 4, but got rank ${u.rank}.`),M(l.shape[3]===u.shape[2],()=>`Error in gradient of depthwiseConv2d: number of input channels (${l.shape[3]}) must match the inChannels dimension in filter ${u.shape[2]}.`),M(Yr(r,i),()=>`Error in gradient of depthwiseConv2d: Either strides or dilations must be  1. Got strides ${r} and dilations '${i}'.`),rs("depthwiseConv2d",a,o),{x:()=>Hw(l.shape,e,u,r,a,i,o),filter:()=>Gw(l,e,u.shape,r,a,i,o)}}},zB={kernelName:Vp,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let[s,r]=t,a={x:s,filter:r,dy:e},o={x:s,filter:r,dy:e};return{x:()=>W.runKernel(pm,a,n),filter:()=>W.runKernel(hm,o,n)}}},LB={kernelName:So,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t,s={dy:e,y:n};return{x:()=>W.runKernel(t0,s)}}},BB={kernelName:wc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t,s=L(_s(Dt(vt(n))),2/Math.sqrt(Math.PI));return{x:()=>L(e,s)}}},WB={kernelName:Co,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,n)}}},VB={kernelName:fl,inputsToSave:["input"],gradFunc:(e,t)=>{let[n]=t;return{input:()=>U(e,n.shape)}}},UB={kernelName:ml,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,_s(n))}}},GB={kernelName:To,gradFunc:e=>({x:()=>it(e)})},HB={kernelName:No,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=kt(n.shape,s.shape);return{a:()=>{let i=pe(e,ge(s,"float32")),l=an(n.shape,r);return l.length>0?U(ke(i,l),n.shape):i},b:()=>{let i=L(e,ge(n,"float32")),l=an(s.shape,r);l.length>0&&(i=U(ke(i,l),s.shape));let u=vt(s);return Dt(pe(i,ge(u,"float32")))}}}},jB={kernelName:Eo,inputsToSave:["x","mean","variance","scale"],gradFunc:(e,t,n)=>{let{varianceEpsilon:s}=n,[r,a,o,i]=t,l=i==null?Se(1):i,u=an(a.shape,r.shape),c=[];if(a.rank===1){for(let b=0;b<r.shape.length-1;++b)c.push(r.shape[b]);c.push(1)}let p=he(r,a),d=L(e,l),h=_0(ce(o,Se(s))),f=L(L(L(h,h),h),Se(-.5));return{x:()=>a.rank===1?U(L(L(e,js(U(h,[1,1,1,a.shape[0]]),c)),l),r.shape):U(L(L(e,h),l),r.shape),mean:()=>{let b=L(L(h,Se(-1)),d);return a.rank===1&&(b=ke(b,u)),U(b,a.shape)},variance:()=>{let b=L(L(f,p),d);return a.rank===1&&(b=ke(b,u)),U(b,a.shape)},scale:()=>{let b=L(p,h),w=L(e,b);return a.rank===1&&(w=ke(w,u)),U(w,a.shape)},offset:()=>{let b=e;return a.rank===1&&(b=ke(b,u)),U(b,a.shape)}}}},qB={kernelName:yl,inputsToSave:["x","indices"],gradFunc:(e,t,n)=>{let[s,r]=t,{axis:a}=n,o=ur(a,s.shape)[0];return{x:()=>{let l=s.shape,u=r.size,c=l.slice(0,o),p=c.length,d=l.slice(a,l.length).slice(1),h=d.length,f=Sv(0,p),m=Sv(p+1,p+1+h),g=Cv([c,[u],d]),y=U(e,g),x=U(r,[u]),A=Cv([[p],f,m]),b=st(y,A),w=B0(b,x,s.shape[o]),k=AA(A);return w=st(w,k),w},indices:()=>r}}};function Sv(e,t){let n=[];for(let s=e;s<t;++s)n.push(s);return n}function Cv(e){let t=[];for(let n=0;n<e.length;++n)for(let s=0;s<e[n].length;++s)t.push(e[n][s]);return t}var XB={kernelName:Ro,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t;return{a:()=>it(n),b:()=>it(s)}}},KB={kernelName:_o,gradFunc:e=>({x:()=>ge(e,"float32")})},ZB={kernelName:Ic,gradFunc:e=>({x:()=>it(e)})},YB={kernelName:Sc,gradFunc:e=>({x:()=>it(e)})},JB={kernelName:Cc,gradFunc:e=>({x:()=>it(e)})},QB={kernelName:Do,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{alpha:r}=n,a=ys(s,0);return{x:()=>Mn(a,e,L(e,r))}}},eW={kernelName:Tc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,ce(n,1))}}},tW={kernelName:$o,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,ge(n,"float32"))}}},nW={kernelName:p6,inputsToSave:[],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s]=t,{axis:r}=n;return{logits:()=>{let o=_s(s);return he(e,L(ke(e,r,!0),o))}}}};function sW(e,t,n,s=5,r=1,a=1,o=.5){let i={x:e,y:t,dy:n},l={depthRadius:s,bias:r,alpha:a,beta:o};return W.runKernel(a0,i,l)}var rW=V({localResponseNormalizationBackprop_:sW}),aW={kernelName:Hp,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s,r]=t,{depthRadius:a,bias:o,alpha:i,beta:l}=n;return{x:()=>rW(s,r,e,a,o,i,l)}}};function l8(e,t,n,s){return t.rank<n.rank&&(t=U(t,Ji(t.shape,s))),e.rank<n.rank&&(e=U(e,Ji(e.shape,s))),{x:()=>L(e,ge(Rs(n,t),e.dtype))}}var Tv={kernelName:Po,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let s=n,{reductionIndices:r}=s,a=t[0],o=t[1],i=ur(r,a.shape),l=l8(e,o,a,i);return{x:()=>l.x()}}},oW={kernelName:Fo,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t;return{a:()=>L(e,ge(li(n,s),"float32")),b:()=>L(e,ge(w0(n,s),"float32"))}}};function iW(e,t,n,s,r,a,o){let i=D(e,"dy","maxPool3dGrad"),l=D(t,"input","maxPool3dGrad"),u=D(n,"output","maxPool3dGrad"),c=i,p=l,d=u,h=!1;l.rank===4&&(h=!0,c=U(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]]),p=U(l,[1,l.shape[0],l.shape[1],l.shape[2],l.shape[3]]),d=U(u,[1,u.shape[0],u.shape[1],u.shape[2],u.shape[3]])),M(c.rank===5,()=>`Error in maxPool3dGrad: dy must be rank 5 but got rank ${c.rank}.`),M(p.rank===5,()=>`Error in maxPool3dGrad: input must be rank 5 but got rank ${p.rank}.`),M(d.rank===5,()=>`Error in maxPool3dGrad: output must be rank 5 but got rank ${d.rank}.`),rs("maxPool3dGrad",a,o);let f={dy:c,input:p,output:d},m={filterSize:s,strides:r,pad:a,dimRoundingMode:o},g=W.runKernel(i0,f,m);return h?U(g,[g.shape[1],g.shape[2],g.shape[3],g.shape[4]]):g}var lW=V({maxPool3dGrad_:iW}),uW={kernelName:jp,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s,r]=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=n;return{x:()=>lW(e,s,r,a,o,i,l)}}};function cW(e,t,n,s,r,a,o){let i=D(e,"dy","maxPoolGrad"),l=D(t,"input","maxPoolGrad"),u=D(n,"output","maxPoolGrad");M(l.rank===i.rank,()=>`Rank of input (${l.rank}) does not match rank of dy (${i.rank})`),M(i.rank===4,()=>`Error in maxPoolGrad: dy must be rank 4 but got rank ${i.rank}.`),M(l.rank===4,()=>`Error in maxPoolGrad: input must be rank 4 but got rank ${l.rank}.`),rs("maxPoolGrad",a,o);let c={dy:i,input:l,output:u},p={filterSize:s,strides:r,pad:a,dimRoundingMode:o};return W.runKernel(o0,c,p)}var dW=V({maxPoolGrad_:cW}),pW={kernelName:Oo,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s,r]=t,{filterSize:a,strides:o,pad:i}=n;return{x:()=>dW(e,s,r,a,o,i)}}},hW={kernelName:Mo,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{axis:r}=n,a=ur(r,s.shape),i=cw(s.shape,a)[1],l=Et(i);return{x:()=>{let c=s.shape.slice();a.forEach(h=>{c[h]=1});let p=U(e,c);return pe(L(p,Ns(s.shape,"float32")),l)}}}},fW={kernelName:zo,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let s=n,{axis:r}=s,[a,o]=t,i=ur(r,a.shape),l=l8(e,o,a,i);return{x:()=>l.x()}}},mW={kernelName:Lo,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t;return{a:()=>L(e,ge(ui(n,s),"float32")),b:()=>L(e,ge(ys(n,s),"float32"))}}},gW={kernelName:Bo,inputsToSave:["x"],gradFunc:(e,t,n)=>{let s=t[0],{paddings:r}=n,a=r.map(o=>o[0]);return{x:()=>Oe(e,a,s.shape)}}},yW={kernelName:Ec,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=kt(n.shape,s.shape);return{a:()=>{let i=an(n.shape,r);return i.length>0?U(ke(e,i),n.shape):e},b:()=>{let i=L(e,Dt(jc(pe(n,s)))),l=an(s.shape,r);return l.length>0?U(ke(i,l),s.shape):i}}}},AW={kernelName:Wo,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=kt(n.shape,s.shape);return{a:()=>{let i=L(e,ge(s,"float32")),l=an(n.shape,r);return l.length>0?U(ke(i,l),n.shape):i},b:()=>{let i=L(e,ge(n,"float32")),l=an(s.shape,r);return l.length>0?U(ke(i,l),s.shape):i}}}},xW={kernelName:Il,gradFunc:e=>({x:()=>Dt(e)})},bW={kernelName:El,inputsToSave:["indices"],gradFunc:(e,t)=>{let n=t[0];return{indices:()=>Wt(n.shape,"float32")}}},vW={kernelName:Nl,gradFunc:e=>({x:()=>it(e)})},wW={kernelName:Rl,saveAllInputs:!0,gradFunc:(e,t,n)=>{let{axis:s}=n;return es(e,s).map(a=>()=>a)}},Nv={kernelName:Vo,inputsToSave:["x"],gradFunc:(e,t,n)=>{let s=t[0],{paddings:r}=n,a=r.map(o=>o[0]);return{x:()=>Oe(e,a,s.shape)}}},kW={kernelName:Uo,inputsToSave:["a","b"],outputsToSave:[!0],gradFunc:(e,t)=>{let[n,s,r]=t,a=n,o=s,i=kt(a.shape,o.shape);return{a:()=>{let c=ge(o,"float32"),p=L(e,L(c,ya(a,he(c,Se(1))))),d=an(a.shape,i);return d.length>0&&(p=ke(p,d)),U(p,a.shape)},b:()=>{let c=ys(a,0),p=Mn(c,Ds(a),it(a)),d=L(e,L(r,p)),h=an(o.shape,i);return h.length>0&&(d=ke(d,h)),U(d,o.shape)}}}},IW={kernelName:Go,inputsToSave:["x","alpha"],gradFunc:(e,t)=>{let[n,s]=t,r=ys(n,0);return{x:()=>Mn(r,e,L(e,s)),alpha:()=>{let a=Mn(r,it(e),L(e,n)),o=an(s.shape,e.shape);return o.length>0&&(a=ke(a,o)),U(a,s.shape)}}}};function SW(e,t,n){let s=e.shape.slice();s[n]=1;let r=U(t,s),a=Tp(e,n,!0,!1),o=Tp(e,n,!0,!0),i=L(a,o);return L(r,i)}function CW(e,t,n){let s=e.shape.length,r=s-n.length,a=C.getAxesPermutation(n,s),o=e;a!=null&&(o=st(e,a));let i=o.shape.slice(),u=i.splice(s-n.length,n.length).reduce((d,h)=>d*h,1);i.push(u);let c=o.reshape(i),p=SW(c,t,r);if(p=p.reshape(o.shape),a!=null){let d=C.getUndoAxesPermutation(a);p=st(p,d)}return p}var TW={kernelName:Ho,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{axis:r}=n,a=[];return r==null?a=s.shape.map((o,i)=>i):typeof r=="number"?a=[r]:a=r,{x:()=>CW(s,e,a)}}},NW={kernelName:Io,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=kt(n.shape,s.shape);return{a:()=>{let i=pe(e,ge(s,"float32")),l=an(n.shape,r);return l.length>0?U(ke(i,l),n.shape):i},b:()=>{let i=L(e,ge(n,"float32")),l=an(s.shape,r);l.length>0&&(i=U(ke(i,l),s.shape));let u=vt(s);return Dt(pe(i,ge(u,"float32")))}}}},EW={kernelName:Dc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,Dt(vt(n)))}}},RW={kernelName:Ko,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t,s=L(ui(n,6),Ql(n));return{x:()=>L(e,ge(s,"float32"))}}},_W={kernelName:jo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,ge(Ql(n),"float32"))}}},DW={kernelName:_l,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>U(e,n.shape)}}},$W={kernelName:Xo,inputsToSave:["images"],gradFunc:(e,t,n)=>{let[s]=t,r={dy:e,images:s};return{images:()=>W.runKernel(d0,r,n)}}},PW={kernelName:qo,inputsToSave:["images"],gradFunc:(e,t,n)=>{let[s]=t,r={dy:e,images:s};return{images:()=>W.runKernel(c0,r,n)}}},FW={kernelName:Dl,gradFunc:(e,t,n)=>{let{dims:s}=n,r=ur(s,e.shape);return{x:()=>Ks(e,r)}}},OW={kernelName:$l,gradFunc:e=>({x:()=>it(e)})},MW={kernelName:Zo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>Dt(pe(e,L(ya(n,1.5),2)))}}},zW={kernelName:Fl,inputsToSave:["condition"],gradFunc:(e,t)=>{let[n]=t;return{condition:()=>ge(it(n),"float32"),t:()=>L(e,ge(n,e.dtype)),e:()=>L(e,ge(hh(n),e.dtype))}}},LW={kernelName:$c,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let s=ys(n,Se(0)),r=Se(r8),a=Se(a8),o=L(e,a),i=L(L(e,r),_s(ge(n,"float32")));return Mn(s,o,i)}}}},BW={kernelName:Jo,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,L(n,he(Se(1),n)))}}},WW={kernelName:Pc,gradFunc:e=>({x:()=>it(e)})},VW={kernelName:Yo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(ch(ge(n,"float32")),e)}}},UW={kernelName:Ml,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(x0(ge(n,"float32")),e)}}},GW={kernelName:Ol,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{begin:r,size:a}=n,o=s.shape,[i,l]=K6(s,r,a),u=[];for(let c=0;c<e.rank;c++)u.push([i[c],o[c]-i[c]-l[c]]);return{x:()=>Js(e,u)}}},HW={kernelName:ti,outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s]=t,{dim:r}=n,a=!0,o=L(e,s);return{logits:()=>he(o,L(ke(o,[r],a),s))}}},jW={kernelName:Fc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,Cn(n))}}},Ev={kernelName:zl,gradFunc:(e,t,n)=>{let{blockShape:s,paddings:r}=n;return{x:()=>uh(e,s,r)}}},Rv={kernelName:Ll,gradFunc:(e,t,n)=>{let{axis:s}=n;return{x:()=>Ct(e,s)}}},qW={kernelName:Qo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,L(Nn(ge(n,"float32")),2))}}},XW={kernelName:Mc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,L(ge(n,"float32"),2))}}},KW={kernelName:ni,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=Se(2);return{a:()=>L(e,L(r,he(n,s))),b:()=>L(e,L(r,he(s,n)))}}},ZW={kernelName:ai,gradFunc:e=>({x:()=>it(e)})},YW={kernelName:si,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=kt(n.shape,s.shape);return{a:()=>{let i=e,l=an(n.shape,r);return l.length>0&&(i=ke(i,l)),U(i,n.shape)},b:()=>{let i=e,l=an(s.shape,r);return l.length>0&&(i=ke(i,l)),U(Dt(i),s.shape)}}}},JW={kernelName:ei,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,r=s.shape.slice(),{axis:a}=n;ur(a,s.shape).forEach(u=>{r[u]=1});let i=U(e,r),l=L(i,Ns(s.shape,"float32"));return{x:()=>l}}},QW={kernelName:Wl,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,vt(ch(n)))}}},eV={kernelName:ri,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(he(Se(1),vt(n)),e)}}},tV={kernelName:va,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{reps:r}=n;return{x:()=>{let o=it(s);if(s.rank===1)for(let i=0;i<r[0];++i)o=ce(o,Oe(e,[i*s.shape[0]],[s.shape[0]]));else if(s.rank===2)for(let i=0;i<r[0];++i)for(let l=0;l<r[1];++l)o=ce(o,Oe(e,[i*s.shape[0],l*s.shape[1]],[s.shape[0],s.shape[1]]));else if(s.rank===3)for(let i=0;i<r[0];++i)for(let l=0;l<r[1];++l)for(let u=0;u<r[2];++u)o=ce(o,Oe(e,[i*s.shape[0],l*s.shape[1],u*s.shape[2]],[s.shape[0],s.shape[1],s.shape[2]]));else if(s.rank===4)for(let i=0;i<r[0];++i)for(let l=0;l<r[1];++l)for(let u=0;u<r[2];++u)for(let c=0;c<r[3];++c)o=ce(o,Oe(e,[i*s.shape[0],l*s.shape[1],u*s.shape[2],c*s.shape[3]],[s.shape[0],s.shape[1],s.shape[2],s.shape[3]]));else throw new Error(`Gradient for tile operation is not implemented for rank-${s.rank} tensors yet.`);return o}}}},nV={kernelName:Hr,gradFunc:(e,t,n)=>{let s=n,{perm:r}=s,a=AA(r);return{x:()=>st(e,a)}}},sV={kernelName:Gl,gradFunc:(e,t,n)=>{let s=n,{axis:r}=s;return{value:()=>on(e,r)}}},rV={kernelName:eh,inputsToSave:["segmentIds"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>aV(e,n)}}};function aV(e,t){let n=Jr(t,it(t)),s=qc(e,n),r=li(t,Se(0,"int32")),a=s.rank-r.rank;for(let i=0;i<a;++i)r=Kt(r,i+1);r=lr(r,Ns(s.shape,"bool"));let o=it(s);return Mn(r,s,o)}var oV={kernelName:Hl,gradFunc:e=>({x:()=>it(e)})},iV=[i8,rB,aB,oB,iB,lB,uB,cB,dB,pB,hB,fB,yB,bB,vB,wB,kB,IB,SB,CB,TB,NB,RB,EB,$B,PB,FB,OB,MB,zB,NW,LB,BB,WB,VB,UB,HB,GB,jB,qB,XB,KB,ZB,YB,JB,QB,eW,tW,nW,aW,Tv,Tv,oW,uW,pW,hW,fW,mW,gW,yW,AW,xW,bW,vW,wW,Nv,Nv,kW,IW,TW,EW,RW,_W,DW,$W,PW,FW,OW,MW,zW,LW,BW,WW,VW,UW,GW,HW,jW,Ev,Ev,Rv,Rv,qW,KW,XW,ZW,YW,JW,QW,eV,tV,nV,sV,rV,oV];for(let e of iV)h6(e);re().prototype.abs=function(){return this.throwIfDisposed(),tn(this)};re().prototype.acos=function(){return this.throwIfDisposed(),Hy(this)};re().prototype.acosh=function(){return this.throwIfDisposed(),jy(this)};re().prototype.add=function(e){return this.throwIfDisposed(),ce(this,e)};re().prototype.all=function(e,t){return this.throwIfDisposed(),g0(this,e,t)};re().prototype.any=function(e,t){return this.throwIfDisposed(),Cp(this,e,t)};re().prototype.argMax=function(e){return this.throwIfDisposed(),Es(this,e)};re().prototype.argMin=function(e){return this.throwIfDisposed(),qy(this,e)};re().prototype.asScalar=function(){return this.throwIfDisposed(),M(this.size===1,()=>"The array must have only 1 element."),U(this,[])};re().prototype.asType=function(e){return this.throwIfDisposed(),ge(this,e)};re().prototype.as1D=function(){return this.throwIfDisposed(),U(this,[this.size])};re().prototype.as2D=function(e,t){return this.throwIfDisposed(),U(this,[e,t])};re().prototype.as3D=function(e,t,n){return this.throwIfDisposed(),U(this,[e,t,n])};re().prototype.as4D=function(e,t,n,s){return this.throwIfDisposed(),U(this,[e,t,n,s])};re().prototype.as5D=function(e,t,n,s,r){return this.throwIfDisposed(),U(this,[e,t,n,s,r])};re().prototype.asin=function(){return this.throwIfDisposed(),Xy(this)};re().prototype.asinh=function(){return this.throwIfDisposed(),Ky(this)};re().prototype.atan=function(){return this.throwIfDisposed(),Zy(this)};re().prototype.atan2=function(e){return this.throwIfDisposed(),Yy(this,e)};re().prototype.atanh=function(){return this.throwIfDisposed(),Jy(this)};re().prototype.avgPool=function(e,t,n,s){return this.throwIfDisposed(),lh(this,e,t,n,s)};re().prototype.batchToSpaceND=function(e,t){return this.throwIfDisposed(),uh(this,e,t)};re().prototype.batchNorm=function(e,t,n,s,r){return this.throwIfDisposed(),Wc(this,e,t,n,s,r)};re().prototype.broadcastTo=function(e){return this.throwIfDisposed(),Gu(this,e)};re().prototype.cast=function(e){return this.throwIfDisposed(),ge(this,e)};re().prototype.ceil=function(){return this.throwIfDisposed(),aA(this)};re().prototype.clipByValue=function(e,t){return this.throwIfDisposed(),fs(this,e,t)};re().prototype.concat=function(e,t){return this.throwIfDisposed(),e instanceof tt&&(e=[e]),Ct([this,...e],t)};re().prototype.conv1d=function(e,t,n,s,r,a){return this.throwIfDisposed(),y0(this,e,t,n,s,r,a)};re().prototype.conv2dTranspose=function(e,t,n,s,r){return this.throwIfDisposed(),A0(this,e,t,n,s,r)};re().prototype.conv2d=function(e,t,n,s,r,a){return this.throwIfDisposed(),ma(this,e,t,n,s,r,a)};re().prototype.cos=function(){return this.throwIfDisposed(),ch(this)};re().prototype.cosh=function(){return this.throwIfDisposed(),x0(this)};re().prototype.cumprod=function(e,t,n){return this.throwIfDisposed(),Tp(this,e,t,n)};re().prototype.cumsum=function(e,t,n){return this.throwIfDisposed(),b0(this,e,t,n)};re().prototype.depthToSpace=function(e,t){return this.throwIfDisposed(),pA(this,e,t)};re().prototype.depthwiseConv2d=function(e,t,n,s,r,a){return this.throwIfDisposed(),Vc(this,e,t,n,s,r,a)};re().prototype.dilation2d=function(e,t,n,s,r){return this.throwIfDisposed(),hA(this,e,t,n,s,r)};re().prototype.divNoNan=function(e){return this.throwIfDisposed(),fA(this,e)};re().prototype.div=function(e){return this.throwIfDisposed(),pe(this,e)};re().prototype.dot=function(e){return this.throwIfDisposed(),mA(this,e)};re().prototype.elu=function(){return this.throwIfDisposed(),Uc(this)};re().prototype.equal=function(e){return this.throwIfDisposed(),Rs(this,e)};re().prototype.erf=function(){return this.throwIfDisposed(),gA(this)};re().prototype.euclideanNorm=function(e,t){return this.throwIfDisposed(),xA(this,e,t)};re().prototype.exp=function(){return this.throwIfDisposed(),_s(this)};re().prototype.expandDims=function(e){return this.throwIfDisposed(),Kt(this,e)};re().prototype.expm1=function(){return this.throwIfDisposed(),bA(this)};re().prototype.fft=function(){return this.throwIfDisposed(),xh(this)};re().prototype.flatten=function(){return this.throwIfDisposed(),U(this,[this.size])};re().prototype.floor=function(){return this.throwIfDisposed(),jc(this)};re().prototype.floorDiv=function(e){return this.throwIfDisposed(),Bc(this,e)};re().prototype.gather=function(e,t){return this.throwIfDisposed(),qc(this,e,t)};re().prototype.greaterEqual=function(e){return this.throwIfDisposed(),li(this,e)};re().prototype.greater=function(e){return this.throwIfDisposed(),ys(this,e)};re().prototype.ifft=function(){return this.throwIfDisposed(),Qu(this)};re().prototype.irfft=function(){return this.throwIfDisposed(),M0(this)};re().prototype.isFinite=function(){return this.throwIfDisposed(),vA(this)};re().prototype.isInf=function(){return this.throwIfDisposed(),wA(this)};re().prototype.isNaN=function(){return this.throwIfDisposed(),kA(this)};re().prototype.leakyRelu=function(e){return this.throwIfDisposed(),dh(this,e)};re().prototype.lessEqual=function(e){return this.throwIfDisposed(),ui(this,e)};re().prototype.less=function(e){return this.throwIfDisposed(),w0(this,e)};re().prototype.localResponseNormalization=function(e,t,n,s){return this.throwIfDisposed(),IA(this,e,t,n,s)};re().prototype.logSigmoid=function(){return this.throwIfDisposed(),SA(this)};re().prototype.logSoftmax=function(e){return this.throwIfDisposed(),I0(this,e)};re().prototype.logSumExp=function(e,t){return this.throwIfDisposed(),S0(this,e,t)};re().prototype.log=function(){return this.throwIfDisposed(),Ds(this)};re().prototype.log1p=function(){return this.throwIfDisposed(),ph(this)};re().prototype.logicalAnd=function(e){return this.throwIfDisposed(),lr(this,e)};re().prototype.logicalNot=function(){return this.throwIfDisposed(),hh(this)};re().prototype.logicalOr=function(e){return this.throwIfDisposed(),C0(this,e)};re().prototype.logicalXor=function(e){return this.throwIfDisposed(),CA(this,e)};re().prototype.matMul=function(e,t,n){return this.throwIfDisposed(),Qe(this,e,t,n)};re().prototype.maxPool=function(e,t,n,s){return this.throwIfDisposed(),fh(this,e,t,n,s)};re().prototype.max=function(e,t){return this.throwIfDisposed(),mn(this,e,t)};re().prototype.maximum=function(e){return this.throwIfDisposed(),Jr(this,e)};re().prototype.mean=function(e,t){return this.throwIfDisposed(),Bt(this,e,t)};re().prototype.min=function(e,t){return this.throwIfDisposed(),ga(this,e,t)};re().prototype.minimum=function(e){return this.throwIfDisposed(),Xc(this,e)};re().prototype.mirrorPad=function(e,t){return this.throwIfDisposed(),NA(this,e,t)};re().prototype.mod=function(e){return this.throwIfDisposed(),Yl(this,e)};re().prototype.mul=function(e){return this.throwIfDisposed(),L(this,e)};re().prototype.neg=function(){return this.throwIfDisposed(),Dt(this)};re().prototype.norm=function(e,t,n){return this.throwIfDisposed(),Gc(this,e,t,n)};re().prototype.notEqual=function(e){return this.throwIfDisposed(),Qi(this,e)};re().prototype.oneHot=function(e,t=1,n=0){return this.throwIfDisposed(),Zu(this,e,t,n)};re().prototype.onesLike=function(){return this.throwIfDisposed(),$s(this)};re().prototype.pad=function(e,t){return this.throwIfDisposed(),Js(this,e,t)};re().prototype.pool=function(e,t,n,s,r,a){return this.throwIfDisposed(),EA(this,e,t,n,s,r,a)};re().prototype.pow=function(e){return this.throwIfDisposed(),ya(this,e)};re().prototype.prelu=function(e){return this.throwIfDisposed(),yh(this,e)};re().prototype.prod=function(e,t){return this.throwIfDisposed(),RA(this,e,t)};re().prototype.reciprocal=function(){return this.throwIfDisposed(),$A(this)};re().prototype.relu=function(){return this.throwIfDisposed(),Pr(this)};re().prototype.relu6=function(){return this.throwIfDisposed(),E0(this)};re().prototype.reshapeAs=function(e){return this.throwIfDisposed(),U(this,e.shape)};re().prototype.reshape=function(e){return this.throwIfDisposed(),U(this,e)};re().prototype.resizeBilinear=function(e,t,n){return this.throwIfDisposed(),Yw(this,e,t,n)};re().prototype.resizeNearestNeighbor=function(e,t,n){return this.throwIfDisposed(),Jw(this,e,t,n)};re().prototype.reverse=function(e){return this.throwIfDisposed(),Ks(this,e)};re().prototype.rfft=function(){return this.throwIfDisposed(),bh(this)};re().prototype.round=function(){return this.throwIfDisposed(),R0(this)};re().prototype.rsqrt=function(){return this.throwIfDisposed(),_0(this)};re().prototype.selu=function(){return this.throwIfDisposed(),D0(this)};re().prototype.separableConv2d=function(e,t,n,s,r,a){return this.throwIfDisposed(),$0(this,e,t,n,s,r,a)};re().prototype.sigmoid=function(){return this.throwIfDisposed(),Cn(this)};re().prototype.sign=function(){return this.throwIfDisposed(),PA(this)};re().prototype.sin=function(){return this.throwIfDisposed(),P0(this)};re().prototype.sinh=function(){return this.throwIfDisposed(),F0(this)};re().prototype.slice=function(e,t){return this.throwIfDisposed(),Oe(this,e,t)};re().prototype.softmax=function(e){return this.throwIfDisposed(),Jl(this,e)};re().prototype.softplus=function(){return this.throwIfDisposed(),Zl(this)};re().prototype.spaceToBatchND=function(e,t){return this.throwIfDisposed(),gh(this,e,t)};re().prototype.split=function(e,t){return this.throwIfDisposed(),Zt(this,e,t)};re().prototype.sqrt=function(){return this.throwIfDisposed(),Nn(this)};re().prototype.square=function(){return this.throwIfDisposed(),vt(this)};re().prototype.squaredDifference=function(e){return this.throwIfDisposed(),z0(this,e)};re().prototype.squeeze=function(e){return this.throwIfDisposed(),rt(this,e)};re().prototype.stack=function(e,t){this.throwIfDisposed();let n=e instanceof tt?[this,e]:[this,...e];return on(n,t)};re().prototype.step=function(e){return this.throwIfDisposed(),Ql(this,e)};re().prototype.stridedSlice=function(e,t,n,s,r,a,o,i){return this.throwIfDisposed(),FA(this,e,t,n,s,r,a,o,i)};re().prototype.sub=function(e){return this.throwIfDisposed(),he(this,e)};re().prototype.sum=function(e,t){return this.throwIfDisposed(),ke(this,e,t)};re().prototype.tan=function(){return this.throwIfDisposed(),OA(this)};re().prototype.tanh=function(){return this.throwIfDisposed(),Yi(this)};re().prototype.tile=function(e){return this.throwIfDisposed(),js(this,e)};re().prototype.toBool=function(){return this.throwIfDisposed(),ge(this,"bool")};re().prototype.toFloat=function(){return this.throwIfDisposed(),ge(this,"float32")};re().prototype.toInt=function(){return this.throwIfDisposed(),ge(this,"int32")};re().prototype.topk=function(e,t){return this.throwIfDisposed(),MA(this,e,t)};re().prototype.transpose=function(e){return this.throwIfDisposed(),st(this,e)};re().prototype.unique=function(e){return this.throwIfDisposed(),zA(this,e)};re().prototype.unsortedSegmentSum=function(e,t){return this.throwIfDisposed(),B0(this,e,t)};re().prototype.unstack=function(e){return this.throwIfDisposed(),es(this,e)};re().prototype.where=function(e,t){return this.throwIfDisposed(),Mn(e,this,t)};re().prototype.zerosLike=function(){return this.throwIfDisposed(),it(this)};var la=class extends Error{constructor(e){super(e),Object.setPrototypeOf(this,la.prototype)}},Sr=class extends Error{constructor(e){super(e),Object.setPrototypeOf(this,Sr.prototype)}},j=class extends Error{constructor(e){super(e),Object.setPrototypeOf(this,j.prototype)}},He=class extends Error{constructor(e){super(e),Object.setPrototypeOf(this,He.prototype)}},u8=class extends Error{constructor(e){super(e),Object.setPrototypeOf(this,u8.prototype)}},c8=class{constructor(e){this.maxEntries=e||100,this.cache=new Map}get(e){let t;return this.cache.has(e)&&(t=this.cache.get(e),this.cache.delete(e),this.cache.set(e,t)),t}put(e,t){if(this.cache.has(e))this.cache.delete(e);else if(this.cache.size>=this.maxEntries){let n=this.cache.keys().next().value;this.cache.delete(n)}this.cache.set(e,t)}getMaxEntries(){return this.maxEntries}setMaxEntries(e){if(e<0)throw new Error(`The maxEntries of LRU caches must be at least 0, but got ${e}.`);if(this.maxEntries>e)for(let t=0;t<this.maxEntries-e;t++){let n=this.cache.keys().next().value;this.cache.delete(n)}this.maxEntries=e}};function el(e,t){if(Array.isArray(e)){let n=[];for(let s=0;s<t;s++)n=n.concat(e);return n}else{let n=new Array(t);return n.fill(e),n}}function Vr(e,t){if(!e)throw new u8(t)}function _v(e,t){let n=0;for(let s of e)s===t&&n++;return n}function ps(e){return e.length===1?e[0]:e}function _t(e){return Array.isArray(e)?e:[e]}function ua(e){let n=e.replace(/(.)([A-Z][a-z0-9]+)/g,"$1_$2").replace(/([a-z])([A-Z])/g,"$1_$2").toLowerCase();return n[0]!=="_"?n:"private"+n}function Li(e){return e.length<=1||e.indexOf("_")===-1?e:e.replace(/[_]+(\w|$)/g,(t,n)=>n.toUpperCase())}var nr={};function XA(e){if(e==null)return null;let t={};return t.className=e.getClassName(),t.config=e.getConfig(),t}function D3(e){if(!(e==null||typeof e!="object"))if(Array.isArray(e))e.forEach(t=>D3(t));else{let t=Object.keys(e);for(let n of t){let s=e[n];s!=null&&typeof s=="object"&&(!Array.isArray(s)&&s.type==="ndarray"&&typeof s.value=="number"?e[n]=s.value:D3(s))}}}function wh(e,t={},n={},s="object",r=!1){if(typeof e=="string"){let a=e,o;if(a in n)o=n[a];else if(a in nr)o=nr[a];else if(o=t[a],o==null)throw new j(`Unknown ${s}: ${e}. This may be due to one of the following reasons:
+  dense values, but the requested shape requires a multiple of ${s}. inputShape=${e} outputShape= ${t}`}function XL(e,t){let n=Et(e),s=Et(t);return`Input to reshape is a tensor with ${n} dense values, but the requested shape has ${s}. inputShape=${e} outputShape=${t}`}function KL(){return"segment ids must be >= 0"}function ZL(){return"segment ids are not increasing"}function YL(e,t){return`Segment id ${e} out of range [0, ${t}), possibly because segmentIds input is not sorted.`}function JL(e,t,n){return`Bad: indices[${e}] == ${t} out of range [0, ${n})`}var o8={};Ve(o8,{collectGatherOpShapeInfo:()=>tB,computeOutShape:()=>eB,segOpComputeOptimalWindowSize:()=>QL});function QL(e,t){let n=!1,s;for(e<=qA?(s=e,n=!0):s=cm(e,Math.floor(Math.sqrt(e)));!n;)s>t||s===e?n=!0:s=cm(e,s+1);return s}function eB(e,t,n){let s=[],r=e.length;for(let a=0;a<r;a++)a!==t?s.push(e[a]):s.push(n);return s}function tB(e,t,n,s){let r=t.shape.length,a=e.shape.length;if(s!==0&&(s<-r||s>r))throw new Error(`Expect batchDims in the range of [-${r}, ${r}], but got ${s}`);if(s<0&&(s+=r),s>a)throw new Error(`batchDims (${s}) must be less than rank(x) (
+    ${a}).`);if(n<s)throw new Error(`batchDims (${s}) must be less than or equal to axis (${n}).`);for(let p=0;p<s;++p)if(e.shape[p]!==t.shape[p])throw new Error(`x.shape[${p}]: ${e.shape[p]} should be equal to indices.shape[${p}]: ${t.shape[p]}.`);let o=e.shape[n],i=[],l=1,u=1,c=1;for(let p=0;p<s;++p)i.push(e.shape[p]),l*=e.shape[p];for(let p=s;p<n;p++)i.push(e.shape[p]),u*=e.shape[p];for(let p=s;p<r;p++)i.push(t.shape[p]);for(let p=n+1;p<a;p++)i.push(e.shape[p]),c*=e.shape[p];return{batchSize:l,sliceSize:c,outerSize:u,dimSize:o,outputShape:i}}function nB(e){try{return e.map(t=>fm(t))}catch(t){throw new Error(`Failed to decode encoded string bytes into utf-8, error: ${t}`)}}function sB(e){return e.map(t=>th(t))}var dr={};Ve(dr,{nonMaxSuppressionV3Impl:()=>Xw,nonMaxSuppressionV4Impl:()=>Kw,nonMaxSuppressionV5Impl:()=>Zw,whereImpl:()=>Mw});var i8={kernelName:ol,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,Jl(ge(n,"float32"),-1))}}},rB={kernelName:dc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let s=vt(ge(n,"float32")),r=Nn(he(Se(1),s));return Dt(pe(e,r))}}}},aB={kernelName:pc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let s=Nn(he(vt(ge(n,"float32")),1));return pe(e,s)}}}},oB={kernelName:Aa,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=kt(n.shape,s.shape);return{a:()=>{let i=e,l=an(n.shape,r);return l.length>0&&(i=ke(i,l)),U(i,n.shape)},b:()=>{let i=e,l=an(s.shape,r);return l.length>0&&(i=ke(i,l)),U(i,s.shape)}}}},iB={kernelName:co,saveAllInputs:!0,gradFunc:(e,t)=>{let n={};return t.forEach((s,r)=>{n[r]=()=>e.clone()}),n}},lB={kernelName:po,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>it(n)}}},uB={kernelName:mc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>it(n)}}},cB={kernelName:gc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,Nn(he(Se(1),vt(ge(n,"float32")))))}}},dB={kernelName:yc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let s=Nn(ce(Se(1),vt(ge(n,"float32"))));return pe(e,s)}}}},pB={kernelName:bc,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=kt(n.shape,s.shape);return{a:()=>{let i=ce(vt(n),vt(s)),l=L(e,pe(s,i)),u=an(n.shape,r);return u.length>0&&(l=ke(l,u)),U(l,n.shape)},b:()=>{let i=ce(vt(n),vt(s)),l=Dt(L(e,pe(n,i))),u=an(s.shape,r);return u.length>0&&(l=ke(l,u)),U(l,s.shape)}}}},hB={kernelName:Ac,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,ce(vt(ge(n,"float32")),1))}}},fB={kernelName:xc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,he(Se(1),vt(ge(n,"float32"))))}}};function mB(e,t,n,s,r,a){let o=D(e,"dy","avgPool3dGrad"),i=D(t,"input","avgPool3dGrad"),l=o,u=i,c=!1;i.rank===4&&(c=!0,l=U(o,[1,o.shape[0],o.shape[1],o.shape[2],o.shape[3]]),u=U(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]])),M(l.rank===5,()=>`Error in avgPool3dGrad: dy must be rank 5 but got rank ${l.rank}.`),M(u.rank===5,()=>`Error in avgPool3dGrad: input must be rank 5 but got rank ${u.rank}.`),rs("avgPool3dGrad",r,a);let p={dy:l,input:u},d={filterSize:n,strides:s,pad:r,dimRoundingMode:a},h=W.runKernel(Gm,p,d);return c?U(h,[h.shape[1],h.shape[2],h.shape[3],h.shape[4]]):h}var gB=V({avgPool3dGrad_:mB}),yB={kernelName:Mp,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{filterSize:r,strides:a,pad:o,dimRoundingMode:i}=n;return{x:()=>gB(e,s,r,a,o,i)}}};function AB(e,t,n,s,r){let a=D(e,"dy","avgPoolGrad"),o=D(t,"input","avgPoolGrad");M(o.rank===a.rank,()=>`Rank of input (${o.rank}) does not match rank of dy (${a.rank})`);let i=o,l=a,u=!1;o.rank===3&&(u=!0,i=U(o,[1,o.shape[0],o.shape[1],o.shape[2]]),l=U(a,[1,a.shape[0],a.shape[1],a.shape[2]])),M(l.rank===4,()=>`Error in avgPoolGrad: dy must be rank 4 but got rank ${l.rank}.`),M(i.rank===4,()=>`Error in avgPoolGrad: input must be rank 4 but got rank ${i.rank}.`);let c={dy:l,input:i},p={filterSize:n,strides:s,pad:r},d=W.runKernel(Um,c,p);return u?U(d,[d.shape[1],d.shape[2],d.shape[3]]):d}var xB=V({avgPoolGrad_:AB}),bB={kernelName:ho,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{filterSize:r,strides:a,pad:o}=n;return{x:()=>xB(e,s,r,a,o)}}},vB={kernelName:fo,inputsToSave:["a","b"],gradFunc:(e,t,n)=>{let[s,r]=t,{transposeA:a,transposeB:o}=n;return!a&&!o?{a:()=>Qe(e,r,!1,!0),b:()=>Qe(s,e,!0,!1)}:!a&&o?{a:()=>Qe(e,r,!1,!1),b:()=>Qe(e,s,!0,!1)}:a&&!o?{a:()=>Qe(r,e,!1,!0),b:()=>Qe(s,e,!1,!1)}:{a:()=>Qe(r,e,!0,!0),b:()=>Qe(e,s,!0,!0)}}},wB={kernelName:il,gradFunc:(e,t,n)=>{let{blockShape:s,crops:r}=n;return{x:()=>mh(e,s,r)}}},kB={kernelName:c6,gradFunc:(e,t,n)=>{let s=n,r=s.inputShape,a=s.shape,o=Array.from(a);for(let l=r.length-1;l>=0;l--)if(r[l]===a[l])o[l]=1;else if(r[l]!==1)throw new Error(`broadcastTo(): [${r}] cannot be broadcast to [${a}].`);let i=[];for(let l=0;l<o.length;l++)o[l]>1&&i.push(l);return{x:()=>ke(e,i,!0)}}},IB={kernelName:mo,gradFunc:e=>({x:()=>e.clone()})},SB={kernelName:go,gradFunc:e=>({x:()=>it(e)})},CB={kernelName:xa,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{clipValueMin:r,clipValueMax:a}=n;return{x:()=>Mn(lr(ii(s,r),li(s,a)),e,it(e))}}},TB={kernelName:Lp,inputsToSave:["x"],gradFunc:i8.gradFunc},NB={kernelName:ll,saveAllInputs:!0,gradFunc:(e,t,n)=>{let s=t.map(l=>l.shape),{axis:r}=n,a=ur(r,t[0].shape)[0],o=s.map(l=>l[a]);return Zt(e,o,a).map(l=>()=>l)}},EB={kernelName:yo,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let[s,r]=t,{dilations:a,strides:o,pad:i,dataFormat:l}=n;return M(eo(a),()=>`Error in gradient of conv2D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${a}'`),{x:()=>uA(s.shape,e,r,o,i,l),filter:()=>UA(s,e,r.shape,o,i,l)}}},RB={kernelName:Ao,inputsToSave:["dy","filter"],gradFunc:(e,t,n)=>{let[s,r]=t,{strides:a,pad:o,dataFormat:i,dimRoundingMode:l}=n;return{dy:()=>fa(e,r,a,o,i,1,l),filter:()=>UA(e,s,r.shape,a,o,i,l)}}};function _B(e,t,n,s,r){let a=e;e.rank===4&&(a=U(e,[1,e.shape[0],e.shape[1],e.shape[2],e.shape[3]]));let o=t;o.rank===4&&(o=U(t,[1,t.shape[0],t.shape[1],t.shape[2],t.shape[3]])),M(a.rank===5,()=>`Error in conv3dDerFilter: input must be rank 5, but got shape ${a.shape}.`),M(o.rank===5,()=>`Error in conv3dDerFilter: dy must be rank 5, but got shape ${o.shape}.`),M(n.length===5,()=>`Error in conv3dDerFilter: filterShape must be length 5, but got ${n}.`),M(a.shape[4]===n[3],()=>`Error in conv3dDerFilter: depth of input ${a.shape[4]}) must match input depth in filter (${n[3]}.`),M(o.shape[4]===n[4],()=>`Error in conv3dDerFilter: depth of dy (${o.shape[4]}) must match output depth for filter (${n[4]}).`);let i={x:a,dy:o},l={strides:s,pad:r,filterShape:n};return W.runKernel(Xm,i,l)}var DB=V({conv3DBackpropFilter_:_B}),$B={kernelName:Bp,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let{dilations:s,strides:r,pad:a}=n;M(eo(s),()=>`Error in gradient of conv3D: dilation rates greater than 1 are not yet supported in gradients. Got dilations '${s}'`);let[o,i]=t;return{x:()=>aw(o.shape,e,i,r,a),filter:()=>DB(o,e,i.shape,r,a)}}},PB={kernelName:xo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(Dt($0(ge(n,"float32"))),e)}}},FB={kernelName:bo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(P0(ge(n,"float32")),e)}}},OB={kernelName:vo,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{axis:r,exclusive:a,reverse:o}=n;return{x:()=>{let i=dw([r],s.rank),l=x0(e,r,a,!o);return i!=null&&(l=st(l,i)),l}}}},MB={kernelName:wo,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let{dilations:s,strides:r,pad:a,dimRoundingMode:o}=n,i=s==null?[1,1]:s;M(eo(i),()=>`Error in gradient of depthwiseConv2dNative: dilation rates greater than 1 are not yet supported. Got dilations '${i}'`);let[l,u]=t;return M(l.rank===4,()=>`Error in gradient of depthwiseConv2dNative: input must be rank 4, but got rank ${l.rank}.`),M(u.rank===4,()=>`Error in gradient of depthwiseConv2dNative: filter must be rank 4, but got rank ${u.rank}.`),M(l.shape[3]===u.shape[2],()=>`Error in gradient of depthwiseConv2d: number of input channels (${l.shape[3]}) must match the inChannels dimension in filter ${u.shape[2]}.`),M(Zr(r,i),()=>`Error in gradient of depthwiseConv2d: Either strides or dilations must be  1. Got strides ${r} and dilations '${i}'.`),rs("depthwiseConv2d",a,o),{x:()=>Hw(l.shape,e,u,r,a,i,o),filter:()=>Gw(l,e,u.shape,r,a,i,o)}}},zB={kernelName:Wp,inputsToSave:["x","filter"],gradFunc:(e,t,n)=>{let[s,r]=t,a={x:s,filter:r,dy:e},o={x:s,filter:r,dy:e};return{x:()=>W.runKernel(dm,a,n),filter:()=>W.runKernel(pm,o,n)}}},LB={kernelName:Io,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t,s={dy:e,y:n};return{x:()=>W.runKernel(e0,s)}}},BB={kernelName:vc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t,s=L(_s(Dt(vt(n))),2/Math.sqrt(Math.PI));return{x:()=>L(e,s)}}},WB={kernelName:So,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,n)}}},VB={kernelName:hl,inputsToSave:["input"],gradFunc:(e,t)=>{let[n]=t;return{input:()=>U(e,n.shape)}}},UB={kernelName:fl,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,_s(n))}}},GB={kernelName:Co,gradFunc:e=>({x:()=>it(e)})},HB={kernelName:To,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=kt(n.shape,s.shape);return{a:()=>{let i=pe(e,ge(s,"float32")),l=an(n.shape,r);return l.length>0?U(ke(i,l),n.shape):i},b:()=>{let i=L(e,ge(n,"float32")),l=an(s.shape,r);l.length>0&&(i=U(ke(i,l),s.shape));let u=vt(s);return Dt(pe(i,ge(u,"float32")))}}}},jB={kernelName:No,inputsToSave:["x","mean","variance","scale"],gradFunc:(e,t,n)=>{let{varianceEpsilon:s}=n,[r,a,o,i]=t,l=i==null?Se(1):i,u=an(a.shape,r.shape),c=[];if(a.rank===1){for(let b=0;b<r.shape.length-1;++b)c.push(r.shape[b]);c.push(1)}let p=he(r,a),d=L(e,l),h=R0(ce(o,Se(s))),f=L(L(L(h,h),h),Se(-.5));return{x:()=>a.rank===1?U(L(L(e,js(U(h,[1,1,1,a.shape[0]]),c)),l),r.shape):U(L(L(e,h),l),r.shape),mean:()=>{let b=L(L(h,Se(-1)),d);return a.rank===1&&(b=ke(b,u)),U(b,a.shape)},variance:()=>{let b=L(L(f,p),d);return a.rank===1&&(b=ke(b,u)),U(b,a.shape)},scale:()=>{let b=L(p,h),w=L(e,b);return a.rank===1&&(w=ke(w,u)),U(w,a.shape)},offset:()=>{let b=e;return a.rank===1&&(b=ke(b,u)),U(b,a.shape)}}}},qB={kernelName:gl,inputsToSave:["x","indices"],gradFunc:(e,t,n)=>{let[s,r]=t,{axis:a}=n,o=ur(a,s.shape)[0];return{x:()=>{let l=s.shape,u=r.size,c=l.slice(0,o),p=c.length,d=l.slice(a,l.length).slice(1),h=d.length,f=Sv(0,p),m=Sv(p+1,p+1+h),g=Cv([c,[u],d]),y=U(e,g),x=U(r,[u]),A=Cv([[p],f,m]),b=st(y,A),w=L0(b,x,s.shape[o]),k=AA(A);return w=st(w,k),w},indices:()=>r}}};function Sv(e,t){let n=[];for(let s=e;s<t;++s)n.push(s);return n}function Cv(e){let t=[];for(let n=0;n<e.length;++n)for(let s=0;s<e[n].length;++s)t.push(e[n][s]);return t}var XB={kernelName:Eo,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t;return{a:()=>it(n),b:()=>it(s)}}},KB={kernelName:Ro,gradFunc:e=>({x:()=>ge(e,"float32")})},ZB={kernelName:kc,gradFunc:e=>({x:()=>it(e)})},YB={kernelName:Ic,gradFunc:e=>({x:()=>it(e)})},JB={kernelName:Sc,gradFunc:e=>({x:()=>it(e)})},QB={kernelName:_o,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{alpha:r}=n,a=ys(s,0);return{x:()=>Mn(a,e,L(e,r))}}},eW={kernelName:Cc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,ce(n,1))}}},tW={kernelName:Do,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,ge(n,"float32"))}}},nW={kernelName:p6,inputsToSave:[],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s]=t,{axis:r}=n;return{logits:()=>{let o=_s(s);return he(e,L(ke(e,r,!0),o))}}}};function sW(e,t,n,s=5,r=1,a=1,o=.5){let i={x:e,y:t,dy:n},l={depthRadius:s,bias:r,alpha:a,beta:o};return W.runKernel(r0,i,l)}var rW=V({localResponseNormalizationBackprop_:sW}),aW={kernelName:Gp,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s,r]=t,{depthRadius:a,bias:o,alpha:i,beta:l}=n;return{x:()=>rW(s,r,e,a,o,i,l)}}};function l8(e,t,n,s){return t.rank<n.rank&&(t=U(t,Yi(t.shape,s))),e.rank<n.rank&&(e=U(e,Yi(e.shape,s))),{x:()=>L(e,ge(Rs(n,t),e.dtype))}}var Tv={kernelName:$o,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let s=n,{reductionIndices:r}=s,a=t[0],o=t[1],i=ur(r,a.shape),l=l8(e,o,a,i);return{x:()=>l.x()}}},oW={kernelName:Po,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t;return{a:()=>L(e,ge(ii(n,s),"float32")),b:()=>L(e,ge(v0(n,s),"float32"))}}};function iW(e,t,n,s,r,a,o){let i=D(e,"dy","maxPool3dGrad"),l=D(t,"input","maxPool3dGrad"),u=D(n,"output","maxPool3dGrad"),c=i,p=l,d=u,h=!1;l.rank===4&&(h=!0,c=U(i,[1,i.shape[0],i.shape[1],i.shape[2],i.shape[3]]),p=U(l,[1,l.shape[0],l.shape[1],l.shape[2],l.shape[3]]),d=U(u,[1,u.shape[0],u.shape[1],u.shape[2],u.shape[3]])),M(c.rank===5,()=>`Error in maxPool3dGrad: dy must be rank 5 but got rank ${c.rank}.`),M(p.rank===5,()=>`Error in maxPool3dGrad: input must be rank 5 but got rank ${p.rank}.`),M(d.rank===5,()=>`Error in maxPool3dGrad: output must be rank 5 but got rank ${d.rank}.`),rs("maxPool3dGrad",a,o);let f={dy:c,input:p,output:d},m={filterSize:s,strides:r,pad:a,dimRoundingMode:o},g=W.runKernel(o0,f,m);return h?U(g,[g.shape[1],g.shape[2],g.shape[3],g.shape[4]]):g}var lW=V({maxPool3dGrad_:iW}),uW={kernelName:Hp,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s,r]=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=n;return{x:()=>lW(e,s,r,a,o,i,l)}}};function cW(e,t,n,s,r,a,o){let i=D(e,"dy","maxPoolGrad"),l=D(t,"input","maxPoolGrad"),u=D(n,"output","maxPoolGrad");M(l.rank===i.rank,()=>`Rank of input (${l.rank}) does not match rank of dy (${i.rank})`),M(i.rank===4,()=>`Error in maxPoolGrad: dy must be rank 4 but got rank ${i.rank}.`),M(l.rank===4,()=>`Error in maxPoolGrad: input must be rank 4 but got rank ${l.rank}.`),rs("maxPoolGrad",a,o);let c={dy:i,input:l,output:u},p={filterSize:s,strides:r,pad:a,dimRoundingMode:o};return W.runKernel(a0,c,p)}var dW=V({maxPoolGrad_:cW}),pW={kernelName:Fo,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s,r]=t,{filterSize:a,strides:o,pad:i}=n;return{x:()=>dW(e,s,r,a,o,i)}}},hW={kernelName:Oo,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{axis:r}=n,a=ur(r,s.shape),i=cw(s.shape,a)[1],l=Et(i);return{x:()=>{let c=s.shape.slice();a.forEach(h=>{c[h]=1});let p=U(e,c);return pe(L(p,Ns(s.shape,"float32")),l)}}}},fW={kernelName:Mo,inputsToSave:["x"],outputsToSave:[!0],gradFunc:(e,t,n)=>{let s=n,{axis:r}=s,[a,o]=t,i=ur(r,a.shape),l=l8(e,o,a,i);return{x:()=>l.x()}}},mW={kernelName:zo,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t;return{a:()=>L(e,ge(li(n,s),"float32")),b:()=>L(e,ge(ys(n,s),"float32"))}}},gW={kernelName:Lo,inputsToSave:["x"],gradFunc:(e,t,n)=>{let s=t[0],{paddings:r}=n,a=r.map(o=>o[0]);return{x:()=>Oe(e,a,s.shape)}}},yW={kernelName:Nc,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=kt(n.shape,s.shape);return{a:()=>{let i=an(n.shape,r);return i.length>0?U(ke(e,i),n.shape):e},b:()=>{let i=L(e,Dt(Hc(pe(n,s)))),l=an(s.shape,r);return l.length>0?U(ke(i,l),s.shape):i}}}},AW={kernelName:Bo,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=kt(n.shape,s.shape);return{a:()=>{let i=L(e,ge(s,"float32")),l=an(n.shape,r);return l.length>0?U(ke(i,l),n.shape):i},b:()=>{let i=L(e,ge(n,"float32")),l=an(s.shape,r);return l.length>0?U(ke(i,l),s.shape):i}}}},xW={kernelName:kl,gradFunc:e=>({x:()=>Dt(e)})},bW={kernelName:Nl,inputsToSave:["indices"],gradFunc:(e,t)=>{let n=t[0];return{indices:()=>Wt(n.shape,"float32")}}},vW={kernelName:Tl,gradFunc:e=>({x:()=>it(e)})},wW={kernelName:El,saveAllInputs:!0,gradFunc:(e,t,n)=>{let{axis:s}=n;return es(e,s).map(a=>()=>a)}},Nv={kernelName:Wo,inputsToSave:["x"],gradFunc:(e,t,n)=>{let s=t[0],{paddings:r}=n,a=r.map(o=>o[0]);return{x:()=>Oe(e,a,s.shape)}}},kW={kernelName:Vo,inputsToSave:["a","b"],outputsToSave:[!0],gradFunc:(e,t)=>{let[n,s,r]=t,a=n,o=s,i=kt(a.shape,o.shape);return{a:()=>{let c=ge(o,"float32"),p=L(e,L(c,ga(a,he(c,Se(1))))),d=an(a.shape,i);return d.length>0&&(p=ke(p,d)),U(p,a.shape)},b:()=>{let c=ys(a,0),p=Mn(c,Ds(a),it(a)),d=L(e,L(r,p)),h=an(o.shape,i);return h.length>0&&(d=ke(d,h)),U(d,o.shape)}}}},IW={kernelName:Uo,inputsToSave:["x","alpha"],gradFunc:(e,t)=>{let[n,s]=t,r=ys(n,0);return{x:()=>Mn(r,e,L(e,s)),alpha:()=>{let a=Mn(r,it(e),L(e,n)),o=an(s.shape,e.shape);return o.length>0&&(a=ke(a,o)),U(a,s.shape)}}}};function SW(e,t,n){let s=e.shape.slice();s[n]=1;let r=U(t,s),a=Cp(e,n,!0,!1),o=Cp(e,n,!0,!0),i=L(a,o);return L(r,i)}function CW(e,t,n){let s=e.shape.length,r=s-n.length,a=C.getAxesPermutation(n,s),o=e;a!=null&&(o=st(e,a));let i=o.shape.slice(),u=i.splice(s-n.length,n.length).reduce((d,h)=>d*h,1);i.push(u);let c=o.reshape(i),p=SW(c,t,r);if(p=p.reshape(o.shape),a!=null){let d=C.getUndoAxesPermutation(a);p=st(p,d)}return p}var TW={kernelName:Go,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{axis:r}=n,a=[];return r==null?a=s.shape.map((o,i)=>i):typeof r=="number"?a=[r]:a=r,{x:()=>CW(s,e,a)}}},NW={kernelName:ko,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=kt(n.shape,s.shape);return{a:()=>{let i=pe(e,ge(s,"float32")),l=an(n.shape,r);return l.length>0?U(ke(i,l),n.shape):i},b:()=>{let i=L(e,ge(n,"float32")),l=an(s.shape,r);l.length>0&&(i=U(ke(i,l),s.shape));let u=vt(s);return Dt(pe(i,ge(u,"float32")))}}}},EW={kernelName:_c,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,Dt(vt(n)))}}},RW={kernelName:Xo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t,s=L(li(n,6),Jl(n));return{x:()=>L(e,ge(s,"float32"))}}},_W={kernelName:Ho,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,ge(Jl(n),"float32"))}}},DW={kernelName:Rl,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>U(e,n.shape)}}},$W={kernelName:qo,inputsToSave:["images"],gradFunc:(e,t,n)=>{let[s]=t,r={dy:e,images:s};return{images:()=>W.runKernel(c0,r,n)}}},PW={kernelName:jo,inputsToSave:["images"],gradFunc:(e,t,n)=>{let[s]=t,r={dy:e,images:s};return{images:()=>W.runKernel(u0,r,n)}}},FW={kernelName:_l,gradFunc:(e,t,n)=>{let{dims:s}=n,r=ur(s,e.shape);return{x:()=>Ks(e,r)}}},OW={kernelName:Dl,gradFunc:e=>({x:()=>it(e)})},MW={kernelName:Ko,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>Dt(pe(e,L(ga(n,1.5),2)))}}},zW={kernelName:Pl,inputsToSave:["condition"],gradFunc:(e,t)=>{let[n]=t;return{condition:()=>ge(it(n),"float32"),t:()=>L(e,ge(n,e.dtype)),e:()=>L(e,ge(ph(n),e.dtype))}}},LW={kernelName:Dc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>{let s=ys(n,Se(0)),r=Se(r8),a=Se(a8),o=L(e,a),i=L(L(e,r),_s(ge(n,"float32")));return Mn(s,o,i)}}}},BW={kernelName:Yo,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,L(n,he(Se(1),n)))}}},WW={kernelName:$c,gradFunc:e=>({x:()=>it(e)})},VW={kernelName:Zo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(uh(ge(n,"float32")),e)}}},UW={kernelName:Ol,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(A0(ge(n,"float32")),e)}}},GW={kernelName:Fl,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{begin:r,size:a}=n,o=s.shape,[i,l]=K6(s,r,a),u=[];for(let c=0;c<e.rank;c++)u.push([i[c],o[c]-i[c]-l[c]]);return{x:()=>Js(e,u)}}},HW={kernelName:ei,outputsToSave:[!0],gradFunc:(e,t,n)=>{let[s]=t,{dim:r}=n,a=!0,o=L(e,s);return{logits:()=>he(o,L(ke(o,[r],a),s))}}},jW={kernelName:Pc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,Cn(n))}}},Ev={kernelName:Ml,gradFunc:(e,t,n)=>{let{blockShape:s,paddings:r}=n;return{x:()=>lh(e,s,r)}}},Rv={kernelName:zl,gradFunc:(e,t,n)=>{let{axis:s}=n;return{x:()=>Ct(e,s)}}},qW={kernelName:Jo,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,L(Nn(ge(n,"float32")),2))}}},XW={kernelName:Oc,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(e,L(ge(n,"float32"),2))}}},KW={kernelName:ti,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=Se(2);return{a:()=>L(e,L(r,he(n,s))),b:()=>L(e,L(r,he(s,n)))}}},ZW={kernelName:ri,gradFunc:e=>({x:()=>it(e)})},YW={kernelName:ni,inputsToSave:["a","b"],gradFunc:(e,t)=>{let[n,s]=t,r=kt(n.shape,s.shape);return{a:()=>{let i=e,l=an(n.shape,r);return l.length>0&&(i=ke(i,l)),U(i,n.shape)},b:()=>{let i=e,l=an(s.shape,r);return l.length>0&&(i=ke(i,l)),U(Dt(i),s.shape)}}}},JW={kernelName:Qo,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,r=s.shape.slice(),{axis:a}=n;ur(a,s.shape).forEach(u=>{r[u]=1});let i=U(e,r),l=L(i,Ns(s.shape,"float32"));return{x:()=>l}}},QW={kernelName:Bl,inputsToSave:["x"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>pe(e,vt(uh(n)))}}},eV={kernelName:si,outputsToSave:[!0],gradFunc:(e,t)=>{let[n]=t;return{x:()=>L(he(Se(1),vt(n)),e)}}},tV={kernelName:ba,inputsToSave:["x"],gradFunc:(e,t,n)=>{let[s]=t,{reps:r}=n;return{x:()=>{let o=it(s);if(s.rank===1)for(let i=0;i<r[0];++i)o=ce(o,Oe(e,[i*s.shape[0]],[s.shape[0]]));else if(s.rank===2)for(let i=0;i<r[0];++i)for(let l=0;l<r[1];++l)o=ce(o,Oe(e,[i*s.shape[0],l*s.shape[1]],[s.shape[0],s.shape[1]]));else if(s.rank===3)for(let i=0;i<r[0];++i)for(let l=0;l<r[1];++l)for(let u=0;u<r[2];++u)o=ce(o,Oe(e,[i*s.shape[0],l*s.shape[1],u*s.shape[2]],[s.shape[0],s.shape[1],s.shape[2]]));else if(s.rank===4)for(let i=0;i<r[0];++i)for(let l=0;l<r[1];++l)for(let u=0;u<r[2];++u)for(let c=0;c<r[3];++c)o=ce(o,Oe(e,[i*s.shape[0],l*s.shape[1],u*s.shape[2],c*s.shape[3]],[s.shape[0],s.shape[1],s.shape[2],s.shape[3]]));else throw new Error(`Gradient for tile operation is not implemented for rank-${s.rank} tensors yet.`);return o}}}},nV={kernelName:Gr,gradFunc:(e,t,n)=>{let s=n,{perm:r}=s,a=AA(r);return{x:()=>st(e,a)}}},sV={kernelName:Ul,gradFunc:(e,t,n)=>{let s=n,{axis:r}=s;return{value:()=>on(e,r)}}},rV={kernelName:Qp,inputsToSave:["segmentIds"],gradFunc:(e,t)=>{let[n]=t;return{x:()=>aV(e,n)}}};function aV(e,t){let n=Yr(t,it(t)),s=jc(e,n),r=ii(t,Se(0,"int32")),a=s.rank-r.rank;for(let i=0;i<a;++i)r=Kt(r,i+1);r=lr(r,Ns(s.shape,"bool"));let o=it(s);return Mn(r,s,o)}var oV={kernelName:Gl,gradFunc:e=>({x:()=>it(e)})},iV=[i8,rB,aB,oB,iB,lB,uB,cB,dB,pB,hB,fB,yB,bB,vB,wB,kB,IB,SB,CB,TB,NB,RB,EB,$B,PB,FB,OB,MB,zB,NW,LB,BB,WB,VB,UB,HB,GB,jB,qB,XB,KB,ZB,YB,JB,QB,eW,tW,nW,aW,Tv,Tv,oW,uW,pW,hW,fW,mW,gW,yW,AW,xW,bW,vW,wW,Nv,Nv,kW,IW,TW,EW,RW,_W,DW,$W,PW,FW,OW,MW,zW,LW,BW,WW,VW,UW,GW,HW,jW,Ev,Ev,Rv,Rv,qW,KW,XW,ZW,YW,JW,QW,eV,tV,nV,sV,rV,oV];for(let e of iV)h6(e);re().prototype.abs=function(){return this.throwIfDisposed(),tn(this)};re().prototype.acos=function(){return this.throwIfDisposed(),Hy(this)};re().prototype.acosh=function(){return this.throwIfDisposed(),jy(this)};re().prototype.add=function(e){return this.throwIfDisposed(),ce(this,e)};re().prototype.all=function(e,t){return this.throwIfDisposed(),m0(this,e,t)};re().prototype.any=function(e,t){return this.throwIfDisposed(),Sp(this,e,t)};re().prototype.argMax=function(e){return this.throwIfDisposed(),Es(this,e)};re().prototype.argMin=function(e){return this.throwIfDisposed(),qy(this,e)};re().prototype.asScalar=function(){return this.throwIfDisposed(),M(this.size===1,()=>"The array must have only 1 element."),U(this,[])};re().prototype.asType=function(e){return this.throwIfDisposed(),ge(this,e)};re().prototype.as1D=function(){return this.throwIfDisposed(),U(this,[this.size])};re().prototype.as2D=function(e,t){return this.throwIfDisposed(),U(this,[e,t])};re().prototype.as3D=function(e,t,n){return this.throwIfDisposed(),U(this,[e,t,n])};re().prototype.as4D=function(e,t,n,s){return this.throwIfDisposed(),U(this,[e,t,n,s])};re().prototype.as5D=function(e,t,n,s,r){return this.throwIfDisposed(),U(this,[e,t,n,s,r])};re().prototype.asin=function(){return this.throwIfDisposed(),Xy(this)};re().prototype.asinh=function(){return this.throwIfDisposed(),Ky(this)};re().prototype.atan=function(){return this.throwIfDisposed(),Zy(this)};re().prototype.atan2=function(e){return this.throwIfDisposed(),Yy(this,e)};re().prototype.atanh=function(){return this.throwIfDisposed(),Jy(this)};re().prototype.avgPool=function(e,t,n,s){return this.throwIfDisposed(),ih(this,e,t,n,s)};re().prototype.batchToSpaceND=function(e,t){return this.throwIfDisposed(),lh(this,e,t)};re().prototype.batchNorm=function(e,t,n,s,r){return this.throwIfDisposed(),Bc(this,e,t,n,s,r)};re().prototype.broadcastTo=function(e){return this.throwIfDisposed(),Uu(this,e)};re().prototype.cast=function(e){return this.throwIfDisposed(),ge(this,e)};re().prototype.ceil=function(){return this.throwIfDisposed(),aA(this)};re().prototype.clipByValue=function(e,t){return this.throwIfDisposed(),fs(this,e,t)};re().prototype.concat=function(e,t){return this.throwIfDisposed(),e instanceof tt&&(e=[e]),Ct([this,...e],t)};re().prototype.conv1d=function(e,t,n,s,r,a){return this.throwIfDisposed(),g0(this,e,t,n,s,r,a)};re().prototype.conv2dTranspose=function(e,t,n,s,r){return this.throwIfDisposed(),y0(this,e,t,n,s,r)};re().prototype.conv2d=function(e,t,n,s,r,a){return this.throwIfDisposed(),fa(this,e,t,n,s,r,a)};re().prototype.cos=function(){return this.throwIfDisposed(),uh(this)};re().prototype.cosh=function(){return this.throwIfDisposed(),A0(this)};re().prototype.cumprod=function(e,t,n){return this.throwIfDisposed(),Cp(this,e,t,n)};re().prototype.cumsum=function(e,t,n){return this.throwIfDisposed(),x0(this,e,t,n)};re().prototype.depthToSpace=function(e,t){return this.throwIfDisposed(),pA(this,e,t)};re().prototype.depthwiseConv2d=function(e,t,n,s,r,a){return this.throwIfDisposed(),Wc(this,e,t,n,s,r,a)};re().prototype.dilation2d=function(e,t,n,s,r){return this.throwIfDisposed(),hA(this,e,t,n,s,r)};re().prototype.divNoNan=function(e){return this.throwIfDisposed(),fA(this,e)};re().prototype.div=function(e){return this.throwIfDisposed(),pe(this,e)};re().prototype.dot=function(e){return this.throwIfDisposed(),mA(this,e)};re().prototype.elu=function(){return this.throwIfDisposed(),Vc(this)};re().prototype.equal=function(e){return this.throwIfDisposed(),Rs(this,e)};re().prototype.erf=function(){return this.throwIfDisposed(),gA(this)};re().prototype.euclideanNorm=function(e,t){return this.throwIfDisposed(),xA(this,e,t)};re().prototype.exp=function(){return this.throwIfDisposed(),_s(this)};re().prototype.expandDims=function(e){return this.throwIfDisposed(),Kt(this,e)};re().prototype.expm1=function(){return this.throwIfDisposed(),bA(this)};re().prototype.fft=function(){return this.throwIfDisposed(),Ah(this)};re().prototype.flatten=function(){return this.throwIfDisposed(),U(this,[this.size])};re().prototype.floor=function(){return this.throwIfDisposed(),Hc(this)};re().prototype.floorDiv=function(e){return this.throwIfDisposed(),Lc(this,e)};re().prototype.gather=function(e,t){return this.throwIfDisposed(),jc(this,e,t)};re().prototype.greaterEqual=function(e){return this.throwIfDisposed(),ii(this,e)};re().prototype.greater=function(e){return this.throwIfDisposed(),ys(this,e)};re().prototype.ifft=function(){return this.throwIfDisposed(),Ju(this)};re().prototype.irfft=function(){return this.throwIfDisposed(),O0(this)};re().prototype.isFinite=function(){return this.throwIfDisposed(),vA(this)};re().prototype.isInf=function(){return this.throwIfDisposed(),wA(this)};re().prototype.isNaN=function(){return this.throwIfDisposed(),kA(this)};re().prototype.leakyRelu=function(e){return this.throwIfDisposed(),ch(this,e)};re().prototype.lessEqual=function(e){return this.throwIfDisposed(),li(this,e)};re().prototype.less=function(e){return this.throwIfDisposed(),v0(this,e)};re().prototype.localResponseNormalization=function(e,t,n,s){return this.throwIfDisposed(),IA(this,e,t,n,s)};re().prototype.logSigmoid=function(){return this.throwIfDisposed(),SA(this)};re().prototype.logSoftmax=function(e){return this.throwIfDisposed(),k0(this,e)};re().prototype.logSumExp=function(e,t){return this.throwIfDisposed(),I0(this,e,t)};re().prototype.log=function(){return this.throwIfDisposed(),Ds(this)};re().prototype.log1p=function(){return this.throwIfDisposed(),dh(this)};re().prototype.logicalAnd=function(e){return this.throwIfDisposed(),lr(this,e)};re().prototype.logicalNot=function(){return this.throwIfDisposed(),ph(this)};re().prototype.logicalOr=function(e){return this.throwIfDisposed(),S0(this,e)};re().prototype.logicalXor=function(e){return this.throwIfDisposed(),CA(this,e)};re().prototype.matMul=function(e,t,n){return this.throwIfDisposed(),Qe(this,e,t,n)};re().prototype.maxPool=function(e,t,n,s){return this.throwIfDisposed(),hh(this,e,t,n,s)};re().prototype.max=function(e,t){return this.throwIfDisposed(),mn(this,e,t)};re().prototype.maximum=function(e){return this.throwIfDisposed(),Yr(this,e)};re().prototype.mean=function(e,t){return this.throwIfDisposed(),Bt(this,e,t)};re().prototype.min=function(e,t){return this.throwIfDisposed(),ma(this,e,t)};re().prototype.minimum=function(e){return this.throwIfDisposed(),qc(this,e)};re().prototype.mirrorPad=function(e,t){return this.throwIfDisposed(),NA(this,e,t)};re().prototype.mod=function(e){return this.throwIfDisposed(),Zl(this,e)};re().prototype.mul=function(e){return this.throwIfDisposed(),L(this,e)};re().prototype.neg=function(){return this.throwIfDisposed(),Dt(this)};re().prototype.norm=function(e,t,n){return this.throwIfDisposed(),Uc(this,e,t,n)};re().prototype.notEqual=function(e){return this.throwIfDisposed(),Ji(this,e)};re().prototype.oneHot=function(e,t=1,n=0){return this.throwIfDisposed(),Ku(this,e,t,n)};re().prototype.onesLike=function(){return this.throwIfDisposed(),$s(this)};re().prototype.pad=function(e,t){return this.throwIfDisposed(),Js(this,e,t)};re().prototype.pool=function(e,t,n,s,r,a){return this.throwIfDisposed(),EA(this,e,t,n,s,r,a)};re().prototype.pow=function(e){return this.throwIfDisposed(),ga(this,e)};re().prototype.prelu=function(e){return this.throwIfDisposed(),gh(this,e)};re().prototype.prod=function(e,t){return this.throwIfDisposed(),RA(this,e,t)};re().prototype.reciprocal=function(){return this.throwIfDisposed(),$A(this)};re().prototype.relu=function(){return this.throwIfDisposed(),$r(this)};re().prototype.relu6=function(){return this.throwIfDisposed(),N0(this)};re().prototype.reshapeAs=function(e){return this.throwIfDisposed(),U(this,e.shape)};re().prototype.reshape=function(e){return this.throwIfDisposed(),U(this,e)};re().prototype.resizeBilinear=function(e,t,n){return this.throwIfDisposed(),Yw(this,e,t,n)};re().prototype.resizeNearestNeighbor=function(e,t,n){return this.throwIfDisposed(),Jw(this,e,t,n)};re().prototype.reverse=function(e){return this.throwIfDisposed(),Ks(this,e)};re().prototype.rfft=function(){return this.throwIfDisposed(),xh(this)};re().prototype.round=function(){return this.throwIfDisposed(),E0(this)};re().prototype.rsqrt=function(){return this.throwIfDisposed(),R0(this)};re().prototype.selu=function(){return this.throwIfDisposed(),_0(this)};re().prototype.separableConv2d=function(e,t,n,s,r,a){return this.throwIfDisposed(),D0(this,e,t,n,s,r,a)};re().prototype.sigmoid=function(){return this.throwIfDisposed(),Cn(this)};re().prototype.sign=function(){return this.throwIfDisposed(),PA(this)};re().prototype.sin=function(){return this.throwIfDisposed(),$0(this)};re().prototype.sinh=function(){return this.throwIfDisposed(),P0(this)};re().prototype.slice=function(e,t){return this.throwIfDisposed(),Oe(this,e,t)};re().prototype.softmax=function(e){return this.throwIfDisposed(),Yl(this,e)};re().prototype.softplus=function(){return this.throwIfDisposed(),Kl(this)};re().prototype.spaceToBatchND=function(e,t){return this.throwIfDisposed(),mh(this,e,t)};re().prototype.split=function(e,t){return this.throwIfDisposed(),Zt(this,e,t)};re().prototype.sqrt=function(){return this.throwIfDisposed(),Nn(this)};re().prototype.square=function(){return this.throwIfDisposed(),vt(this)};re().prototype.squaredDifference=function(e){return this.throwIfDisposed(),M0(this,e)};re().prototype.squeeze=function(e){return this.throwIfDisposed(),rt(this,e)};re().prototype.stack=function(e,t){this.throwIfDisposed();let n=e instanceof tt?[this,e]:[this,...e];return on(n,t)};re().prototype.step=function(e){return this.throwIfDisposed(),Jl(this,e)};re().prototype.stridedSlice=function(e,t,n,s,r,a,o,i){return this.throwIfDisposed(),FA(this,e,t,n,s,r,a,o,i)};re().prototype.sub=function(e){return this.throwIfDisposed(),he(this,e)};re().prototype.sum=function(e,t){return this.throwIfDisposed(),ke(this,e,t)};re().prototype.tan=function(){return this.throwIfDisposed(),OA(this)};re().prototype.tanh=function(){return this.throwIfDisposed(),Zi(this)};re().prototype.tile=function(e){return this.throwIfDisposed(),js(this,e)};re().prototype.toBool=function(){return this.throwIfDisposed(),ge(this,"bool")};re().prototype.toFloat=function(){return this.throwIfDisposed(),ge(this,"float32")};re().prototype.toInt=function(){return this.throwIfDisposed(),ge(this,"int32")};re().prototype.topk=function(e,t){return this.throwIfDisposed(),MA(this,e,t)};re().prototype.transpose=function(e){return this.throwIfDisposed(),st(this,e)};re().prototype.unique=function(e){return this.throwIfDisposed(),zA(this,e)};re().prototype.unsortedSegmentSum=function(e,t){return this.throwIfDisposed(),L0(this,e,t)};re().prototype.unstack=function(e){return this.throwIfDisposed(),es(this,e)};re().prototype.where=function(e,t){return this.throwIfDisposed(),Mn(e,this,t)};re().prototype.zerosLike=function(){return this.throwIfDisposed(),it(this)};var ia=class extends Error{constructor(e){super(e),Object.setPrototypeOf(this,ia.prototype)}},Sr=class extends Error{constructor(e){super(e),Object.setPrototypeOf(this,Sr.prototype)}},j=class extends Error{constructor(e){super(e),Object.setPrototypeOf(this,j.prototype)}},He=class extends Error{constructor(e){super(e),Object.setPrototypeOf(this,He.prototype)}},u8=class extends Error{constructor(e){super(e),Object.setPrototypeOf(this,u8.prototype)}},c8=class{constructor(e){this.maxEntries=e||100,this.cache=new Map}get(e){let t;return this.cache.has(e)&&(t=this.cache.get(e),this.cache.delete(e),this.cache.set(e,t)),t}put(e,t){if(this.cache.has(e))this.cache.delete(e);else if(this.cache.size>=this.maxEntries){let n=this.cache.keys().next().value;this.cache.delete(n)}this.cache.set(e,t)}getMaxEntries(){return this.maxEntries}setMaxEntries(e){if(e<0)throw new Error(`The maxEntries of LRU caches must be at least 0, but got ${e}.`);if(this.maxEntries>e)for(let t=0;t<this.maxEntries-e;t++){let n=this.cache.keys().next().value;this.cache.delete(n)}this.maxEntries=e}};function Qi(e,t){if(Array.isArray(e)){let n=[];for(let s=0;s<t;s++)n=n.concat(e);return n}else{let n=new Array(t);return n.fill(e),n}}function Wr(e,t){if(!e)throw new u8(t)}function _v(e,t){let n=0;for(let s of e)s===t&&n++;return n}function ps(e){return e.length===1?e[0]:e}function _t(e){return Array.isArray(e)?e:[e]}function la(e){let n=e.replace(/(.)([A-Z][a-z0-9]+)/g,"$1_$2").replace(/([a-z])([A-Z])/g,"$1_$2").toLowerCase();return n[0]!=="_"?n:"private"+n}function zi(e){return e.length<=1||e.indexOf("_")===-1?e:e.replace(/[_]+(\w|$)/g,(t,n)=>n.toUpperCase())}var nr={};function XA(e){if(e==null)return null;let t={};return t.className=e.getClassName(),t.config=e.getConfig(),t}function _3(e){if(!(e==null||typeof e!="object"))if(Array.isArray(e))e.forEach(t=>_3(t));else{let t=Object.keys(e);for(let n of t){let s=e[n];s!=null&&typeof s=="object"&&(!Array.isArray(s)&&s.type==="ndarray"&&typeof s.value=="number"?e[n]=s.value:_3(s))}}}function vh(e,t={},n={},s="object",r=!1){if(typeof e=="string"){let a=e,o;if(a in n)o=n[a];else if(a in nr)o=nr[a];else if(o=t[a],o==null)throw new j(`Unknown ${s}: ${e}. This may be due to one of the following reasons:
 1. The ${s} is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.
 2. The custom ${s} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);return o}else{let a=e;if(a.className==null||a.config==null)throw new j(`${s}: Improper config format: ${JSON.stringify(a)}.
 'className' and 'config' must set.`);let o=a.className,i,l;if(o in n?[i,l]=n[o]:o in nr?[i,l]=nr.className:o in t&&([i,l]=t[o]),i==null)throw new j(`Unknown ${s}: ${o}. This may be due to one of the following reasons:
 1. The ${s} is defined in Python, in which case it needs to be ported to TensorFlow.js or your JavaScript code.
-2. The custom ${s} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);if(l!=null){let u={};for(let h of Object.keys(nr))u[h]=nr[h];for(let h of Object.keys(n))u[h]=n[h];let c=a.config;c.customObjects=u;let p=Object.assign({},nr);for(let h of Object.keys(n))nr[h]=n[h];D3(a.config);let d=l(i,a.config,n,r);return nr=Object.assign({},p),d}else{let u=Object.assign({},nr);for(let p of Object.keys(n))nr[p]=n[p];let c=new i(a.config);return nr=Object.assign({},u),c}}}function lV(e,t){return e<t?-1:e>t?1:0}function Wf(e,t){return-1*lV(e,t)}function Xa(e){if(e==null)return e;let t=[];for(let n of e)t.indexOf(n)===-1&&t.push(n);return t}function uV(e){if(e==null)throw new j(`Invalid value in obj: ${JSON.stringify(e)}`);for(let t in e)if(e.hasOwnProperty(t))return!1;return!0}function eu(e,t,n){if(n!=null&&e.indexOf(n)<0)throw new j(`${n} is not a valid ${t}.  Valid values are ${e} or null/undefined.`)}function KA(e,t,n=0,s=1/0){return Vr(n>=0),Vr(s>=n),Array.isArray(e)&&e.length>=n&&e.length<=s&&e.every(r=>typeof r===t)}function vn(e,t){Array.isArray(e)?(v.assert(e.length>0,()=>`${t} is unexpectedly an empty array.`),e.forEach((n,s)=>vn(n,`element ${s+1} of ${t}`))):v.assert(Number.isInteger(e)&&e>0,()=>`Expected ${t} to be a positive integer, but got ${d8(e)}.`)}function d8(e){return e===null?"null":Array.isArray(e)?"["+e.map(t=>d8(t)).join(",")+"]":typeof e=="string"?`"${e}"`:`${e}`}function cV(e,t,n){let s=n!=null?n():v.now(),r;return(...o)=>{let i=n!=null?n():v.now();return i-s<t||(s=i,r=e(...o)),r}}function p8(e){return e==="relu"?"relu":e==="linear"?"linear":e==="elu"?"elu":null}var dV=0;function h8(){return dV++}var Vf={};function J0(e=""){return e in Vf||(Vf[e]=0),Vf[e]+=1,e+Vf[e].toString()}var pV=["channelsFirst","channelsLast"],hV=["nearest","bilinear"],fV=["valid","same","causal"],mV=["max","avg"],gV=["sum","mul","concat","ave"],$u=new Map;function Yt(e){eu(pV,"DataFormat",e)}function yV(e){eu(hV,"InterpolationFormat",e)}function Qs(e){eu(fV,"PaddingMode",e)}function f8(e){eu(mV,"PoolMode",e)}var mp=[],Dv="/";function Hi(e,t){mp.push(e);try{let n=t();return mp.pop(),n}catch(n){throw mp.pop(),n}}function AV(){return mp.length===0?"":mp.join(Dv)+Dv}function m8(e){if(!y8(e))throw new Error("Not a valid tensor name: '"+e+"'");return AV()+e}function g8(e){if(!y8(e))throw new Error("Not a valid tensor name: '"+e+"'");$u.has(e)||$u.set(e,0);let t=$u.get(e);if($u.set(e,$u.get(e)+1),t>0){let n=`${e}_${t}`;return $u.set(n,1),n}else return e}var xV=new RegExp(/^[A-Za-z0-9][-A-Za-z0-9\._\/]*$/);function y8(e){return!!e.match(xV)}function bV(e){return e===parseInt(e.toString(),10)}function Ka(e,t,n){t==null&&(t=0),n==null&&(n=e.length);let s=1;for(let r=t;r<n;++r)s*=e[r];return s}function tc(e){if(e.length===0)return Number.NaN;let t=Number.POSITIVE_INFINITY;for(let n=0;n<e.length;n++){let s=e[n];s<t&&(t=s)}return t}function so(e){if(e.length===0)return Number.NaN;let t=Number.NEGATIVE_INFINITY;for(let n=0;n<e.length;n++){let s=e[n];s>t&&(t=s)}return t}function Rr(e,t){if(t<e)throw new j(`end (${t}) < begin (${e}) is forbidden.`);let n=[];for(let s=e;s<t;++s)n.push(s);return n}var l3;function hn(){return l3==null&&(l3=Zs().epsilon()),l3}function _r(){return"channelsLast"}function Q0(e,t){return ge(e,t)}function kh(e,t=-1){let n=e.shape.slice();return t<0&&(t=n.length+t+1),n.splice(t,0,1),U(e,n)}function vV(e,t){return J(()=>{if(e.shape.length!==2)throw new j(`repeat() expects a rank-2 tensor, but received a rank-${e.shape.length} tensor.`);let n=kh(e,1);return $3(n,[1,t,1])})}function wV(e){let t=[Ka(e.shape)];return U(e,t)}function kV(e){if(e.rank<=1)throw new j(`batchFlatten requires a minimum rank of 2. Got rank: ${e.rank}.`);let t=[e.shape[0],Ka(e.shape,1)];return U(e,t)}function ji(e,t,n){return J(()=>{switch(e.rank){case 1:return Ah(e,t,n);case 2:return O0(e,[t,0],[n,e.shape[1]]);case 3:return ci(e,[t,0,0],[n,e.shape[1],e.shape[2]]);case 4:return no(e,[t,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3]]);case 5:return Oe(e,[t,0,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3],e.shape[4]]);case 6:return Oe(e,[t,0,0,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3],e.shape[4],e.shape[5]]);default:throw new j(`sliceAlongFirstAxis() received an unsupported tensor rank: ${e.rank}`)}})}function u3(e,t,n){return J(()=>{switch(e.rank){case 1:return Ah(e,t,n);case 2:return O0(e,[0,t],[e.shape[0],n]);case 3:return ci(e,[0,0,t],[e.shape[0],e.shape[1],n]);case 4:return no(e,[0,0,0,t],[e.shape[0],e.shape[1],e.shape[2],n]);default:throw new j(`sliceAlongLastAxis() received an unsupported tensor rank: ${e.rank}`)}})}function Uf(e,t,n,s){return J(()=>{switch(e.rank){case 1:return Ah(e,t,n);case 2:switch(s){case 1:return ji(e,t,n);case 2:return u3(e,t,n);default:throw new j(`The axis is not within the rank of the tensor ${s}`)}case 3:switch(s){case 1:return ji(e,t,n);case 2:return ci(e,[0,t,0],[e.shape[0],n,e.shape[2]]);case 3:return u3(e,t,n);default:throw new j(`The axis is not within the rank of the tensor ${s}`)}case 4:switch(s){case 1:return ji(e,t,n);case 2:return no(e,[0,t,0,0],[e.shape[0],n,e.shape[2],e.shape[3]]);case 3:return no(e,[0,0,t,0],[e.shape[0],e.shape[1],n,e.shape[3]]);case 4:return u3(e,t,n);default:throw new j(`The axis is not within the rank of the tensor ${s}`)}default:throw new j(`sliceAlongLastAxis() received an unsupported tensor rank: ${e.rank}`)}})}function ZA(e,t=-1){let n;return t<0&&(n=e[0].rank,n!==0?t=n:t=0),t===e[0].rank&&(t=-1),Ct(e,t)}function $v(e,t){switch(e.rank){case 1:return oA([e,t]);case 2:return Kl([e,t],0);case 3:return iA([e,t],0);case 4:return lA([e,t],0);default:throw new j(`concatAlongFirstAxis() received an unsupported tensor rank: ${e.rank}`)}}function $3(e,t){if(Array.isArray(t)||(t=[t]),e.rank!==t.length)throw new j(`The length of input n (${t.length}) does not match the number of dimensions in input x (${e.rank})`);return js(e,t)}function e2(e,t=0,n=1,s,r){return N0(e,t,n,s,r)}function jr(e,t,n,s){if(e.rank<2||t.rank<2)throw new He(`dot requires both inputs to be rank >= 2 but got x shape = ${e.shape} and y shape = ${t.shape}`);if(t.rank>=3){let r=e.shape.slice(-1)[0],a=t.shape.slice(-2)[0];if(r!==a)throw new He(`If rank y >= 3, then the second last dim of y must equal the last dim of x but got x shape = ${e.shape} and  y shape = ${t.shape}`)}if(e.rank===2&&t.rank===2)return ec.matMul({a:e,b:t,transposeA:!1,transposeB:!1,bias:s?P3(e.rank,s,_r()):null,activation:n});{let r=e.shape.slice(),a=r.pop();e=U(e,[-1,a]);let o=t.shape.slice(),i=o.pop(),l=o.pop(),u=[...o,i],c=Array.from({length:t.rank},(f,m)=>m===0?t.rank-2:m<=t.rank-2?m-1:m);t=U(st(t,c),[l,-1]);let p=[...r,...u],d=!1,h=!1;return U(ec.matMul({a:e,b:t,transposeA:d,transposeB:h,bias:s?P3(e.rank,s,_r()):null,activation:n}),p)}}function A8(e,t,n){return J(()=>(Array.isArray(t)?t=Ft(t,"int32"):t=ge(t,"int32"),qc(e,t,n)))}function Ih(e){return L(e,e)}function P3(e,t,n){let s=t.shape;if(t.rank!==1&&t.rank!==e)throw new j(`Unexpected bias dimensions: ${t.rank}; expected it to be 1 or ${e}`);if(e===5){if(n==="channelsFirst")return s.length===1?U(t,[1,s[0],1,1,1]):U(t,[1,s[3],s[0],s[1],s[2]]);if(n==="channelsLast")return s.length===1?U(t,[1,1,1,1,s[0]]):U(t,[1].concat(s))}else if(e===4){if(n==="channelsFirst")return s.length===1?U(t,[1,s[0],1,1]):U(t,[1,s[2],s[0],s[1]]);if(n==="channelsLast")return s.length===1?U(t,[1,1,1,s[0]]):U(t,[1].concat(s))}else if(e===3){if(n==="channelsFirst")return s.length===1?U(t,[1,s[0],1]):U(t,[1,s[1],s[0]]);if(n==="channelsLast")return s.length===1?U(t,[1,1,s[0]]):U(t,[1].concat(s))}else if(e<3)return t;throw new j(`Unsupported input rank by biasAdd: ${t.rank}`)}function Fr(e,t,n){return J(()=>(n==null&&(n=_r()),Yt(n),ce(e,P3(e.rank,t,n))))}function IV(e,t=1){if(t!==1)throw new He(`Support for alpha values other than 1 (${t}) is not implemented yet.`);return Uc(e)}function SV(e){return J(()=>pe(e,ce(tn(e),1)))}function x8(e,t,n,s){return J(()=>WA(e,t,n,s))}function CV(e){return J(()=>{let t=ce(.5,L(.2,e));return fs(t,0,1)})}function Sh(e,t,n=!1){return n?e():t()}var TV=["fanIn","fanOut","fanAvg"],NV=["normal","uniform","truncatedNormal"];function EV(e){eu(TV,"FanMode",e)}function RV(e){eu(NV,"Distribution",e)}var pr=class extends de.Serializable{fromConfigUsesCustomObjects(){return!1}getConfig(){return{}}},YA=class extends pr{apply(e,t){return Wt(e,t)}};YA.className="Zeros";de.registerClass(YA);var t2=class extends pr{apply(e,t){return Ns(e,t)}};t2.className="Ones";de.registerClass(t2);var JA=class extends pr{constructor(e){if(super(),typeof e!="object")throw new j(`Expected argument of type ConstantConfig but got ${e}`);if(e.value===void 0)throw new j(`config must have value set but got ${e}`);this.value=e.value}apply(e,t){return J(()=>L(Se(this.value),Ns(e,t)))}getConfig(){return{value:this.value}}};JA.className="Constant";de.registerClass(JA);var QA=class extends pr{constructor(e){super(),this.DEFAULT_MINVAL=-.05,this.DEFAULT_MAXVAL=.05,this.minval=e.minval||this.DEFAULT_MINVAL,this.maxval=e.maxval||this.DEFAULT_MAXVAL,this.seed=e.seed}apply(e,t){return Kc(e,this.minval,this.maxval,t)}getConfig(){return{minval:this.minval,maxval:this.maxval,seed:this.seed}}};QA.className="RandomUniform";de.registerClass(QA);var e5=class extends pr{constructor(e){super(),this.DEFAULT_MEAN=0,this.DEFAULT_STDDEV=.05,this.mean=e.mean||this.DEFAULT_MEAN,this.stddev=e.stddev||this.DEFAULT_STDDEV,this.seed=e.seed}apply(e,t){if(t=t||"float32",t!=="float32"&&t!=="int32")throw new He(`randomNormal does not support dType ${t}.`);return e2(e,this.mean,this.stddev,t,this.seed)}getConfig(){return{mean:this.mean,stddev:this.stddev,seed:this.seed}}};e5.className="RandomNormal";de.registerClass(e5);var t5=class extends pr{constructor(e){super(),this.DEFAULT_MEAN=0,this.DEFAULT_STDDEV=.05,this.mean=e.mean||this.DEFAULT_MEAN,this.stddev=e.stddev||this.DEFAULT_STDDEV,this.seed=e.seed}apply(e,t){if(t=t||"float32",t!=="float32"&&t!=="int32")throw new He(`truncatedNormal does not support dType ${t}.`);return L0(e,this.mean,this.stddev,t,this.seed)}getConfig(){return{mean:this.mean,stddev:this.stddev,seed:this.seed}}};t5.className="TruncatedNormal";de.registerClass(t5);var n5=class extends pr{constructor(e){super(),this.gain=e.gain!=null?e.gain:1}apply(e,t){return J(()=>{if(e.length!==2||e[0]!==e[1])throw new j("Identity matrix initializer can only be used for 2D square matrices.");return L(this.gain,v0(e[0]))})}getConfig(){return{gain:this.gain}}};n5.className="Identity";de.registerClass(n5);function _V(e,t="channelsLast"){let n,s;if(Yt(t),e.length===2)n=e[0],s=e[1];else if([3,4,5].indexOf(e.length)!==-1){if(t==="channelsFirst"){let r=Ka(e,2);n=e[1]*r,s=e[0]*r}else if(t==="channelsLast"){let r=Ka(e,0,e.length-2);n=e[e.length-2]*r,s=e[e.length-1]*r}}else{let r=Ka(e);n=Math.sqrt(r),s=Math.sqrt(r)}return[n,s]}var ms=class extends pr{constructor(e){if(super(),e.scale<0)throw new j(`scale must be a positive float. Got: ${e.scale}`);this.scale=e.scale==null?1:e.scale,this.mode=e.mode==null?"fanIn":e.mode,EV(this.mode),this.distribution=e.distribution==null?"normal":e.distribution,RV(this.distribution),this.seed=e.seed}apply(e,t){let n=_V(e),s=n[0],r=n[1],a=this.scale;if(this.mode==="fanIn"?a/=Math.max(1,s):this.mode==="fanOut"?a/=Math.max(1,r):a/=Math.max(1,(s+r)/2),this.distribution==="normal"){let o=Math.sqrt(a);if(t=t||"float32",t!=="float32"&&t!=="int32")throw new He(`${this.getClassName()} does not support dType ${t}.`);return L0(e,0,o,t,this.seed)}else{let o=Math.sqrt(3*a);return Kc(e,-o,o,t)}}getConfig(){return{scale:this.scale,mode:this.mode,distribution:this.distribution,seed:this.seed}}};ms.className="VarianceScaling";de.registerClass(ms);var n2=class extends ms{constructor(e){super({scale:1,mode:"fanAvg",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return ms.className}};n2.className="GlorotUniform";de.registerClass(n2);var s2=class extends ms{constructor(e){super({scale:1,mode:"fanAvg",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return ms.className}};s2.className="GlorotNormal";de.registerClass(s2);var r2=class extends ms{constructor(e){super({scale:2,mode:"fanIn",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return ms.className}};r2.className="HeNormal";de.registerClass(r2);var a2=class extends ms{constructor(e){super({scale:2,mode:"fanIn",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return ms.className}};a2.className="HeUniform";de.registerClass(a2);var o2=class extends ms{constructor(e){super({scale:1,mode:"fanIn",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return ms.className}};o2.className="LeCunNormal";de.registerClass(o2);var i2=class extends ms{constructor(e){super({scale:1,mode:"fanIn",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return ms.className}};i2.className="LeCunNormal";de.registerClass(i2);var s5=class extends pr{constructor(e){if(super(),this.DEFAULT_GAIN=1,this.gain=e.gain==null?this.DEFAULT_GAIN:e.gain,this.seed=e.seed,this.seed!=null)throw new He("Random seed is not implemented for Orthogonal Initializer yet.")}apply(e,t){return J(()=>{if(e.length<2)throw new He("Shape must be at least 2D.");e[0]*e[1]>2e3&&console.warn(`Orthogonal initializer is being called on a matrix with more than 2000 (${e[0]*e[1]}) elements: Slowness may result.`);let n=e[0]>e[1]?[e[1],e[0]]:e,s=e2(n,0,1,"float32"),r=HA.gramSchmidt(s);return e[0]>e[1]&&(r=st(r)),L(this.gain,r)})}getConfig(){return{gain:this.gain,seed:this.seed}}};s5.className="Orthogonal";de.registerClass(s5);var Pv={constant:"Constant",glorotNormal:"GlorotNormal",glorotUniform:"GlorotUniform",heNormal:"HeNormal",heUniform:"HeUniform",identity:"Identity",leCunNormal:"LeCunNormal",leCunUniform:"LeCunUniform",ones:"Ones",orthogonal:"Orthogonal",randomNormal:"RandomNormal",randomUniform:"RandomUniform",truncatedNormal:"TruncatedNormal",varianceScaling:"VarianceScaling",zeros:"Zeros"};function Fv(e,t={}){return wh(e,de.SerializationMap.getMap().classNameMap,t,"initializer")}function Vt(e){return XA(e)}function Ot(e){if(typeof e=="string"){let t=e in Pv?Pv[e]:e;if(t==="GlorotNormal")return new s2;if(t==="GlorotUniform")return new n2;if(t==="HeNormal")return new r2;if(t==="HeUniform")return new a2;if(t==="LeCunNormal")return new o2;if(t==="LeCunUniform")return new i2;{let n={};return n.className=t,n.config={},Fv(n)}}else return e instanceof pr?e:Fv(e)}function F3(e){return Array.isArray(e)&&Array.isArray(e[0])}function xm(e){return e.length===0?[]:Array.isArray(e[0])?e:[e]}function Xe(e){let t;if(Array.isArray(e)){if(e.length!==1)throw new j(`Expected Tensor length to be 1; got ${e.length}`);t=e[0]}else t=e;return t}function xt(e){if(Array.isArray(e)&&Array.isArray(e[0])){if(e.length===1)return e=e,e[0];throw new j(`Expected exactly 1 Shape; got ${e.length}`)}else return e}function bm(e){let t=0;for(let n of e)n.shape.length===0?t+=1:t+=n.shape.reduce((s,r)=>s*r);return t}var Ov="Variable",b8=class{constructor(e,t="float32",n=Ov,s=!0,r=null){this.dtype=t==null?"float32":t,this.shape=e.shape,this.id=h8(),n=n==null?Ov:n,this.originalName=m8(n),this.name=g8(this.originalName),this.trainable_=s,this.constraint=r,this.val=LA(e,this.trainable_,this.name,this.dtype)}read(){return this.assertNotDisposed(),this.val}write(e){return this.assertNotDisposed(),DV(this.val,e),this.val.id!==e.id&&(this.val.assign(e),this.constraint!=null&&this.val.assign(this.constraint.apply(this.val))),this}dispose(){this.assertNotDisposed(),this.val.dispose()}assertNotDisposed(){if(this.val.isDisposed)throw new Error(`LayersVariable ${this.name} is already disposed.`)}get trainable(){return this.trainable_}set trainable(e){this.trainable_=e,this.val.trainable=e}};function DV(e,t){if(e.shape.toString()!==t.shape.toString())throw new Error("Shape mismatch: "+JSON.stringify(e.shape)+" vs. "+JSON.stringify(t.shape))}function O3(e){return e.map(t=>t.read())}function r5(e){e.forEach(t=>{t[0].write(t[1])})}var rn=class{constructor(e){this.dtype=e.dtype,this.shape=e.shape,e.shape!=null?this.ndim=e.shape.length:this.ndim=e.ndim,this.maxNDim=e.maxNDim,this.minNDim=e.minNDim,this.axes=e.axes||{}}},Cr=class{constructor(e,t,n,s,r,a,o){this.dtype=e,this.shape=t,this.sourceLayer=n,this.inputs=s,this.callArgs=r,this.outputTensorIndex=o,this.id=h8(),a!=null&&(this.originalName=m8(a),this.name=g8(this.originalName)),this.rank=t.length}},$V=0,l2=class{constructor(e,t){this.callArgs=t,this.id=$V++,this.outboundLayer=e.outboundLayer,this.inboundLayers=e.inboundLayers,this.nodeIndices=e.nodeIndices,this.tensorIndices=e.tensorIndices,this.inputTensors=e.inputTensors,this.outputTensors=e.outputTensors,this.inputMasks=e.inputMasks,this.outputMasks=e.outputMasks,this.inputShapes=e.inputShapes,this.outputShapes=e.outputShapes;for(let n of e.inboundLayers)n!=null&&n.outboundNodes.push(this);e.outboundLayer.inboundNodes.push(this)}getConfig(){let e=[];for(let t of this.inboundLayers)t!=null?e.push(t.name):e.push(null);return{outboundLayer:this.outboundLayer?this.outboundLayer.name:null,inboundLayers:e,nodeIndices:this.nodeIndices,tensorIndices:this.tensorIndices}}},PV=0,ut=class extends de.Serializable{constructor(e={}){super(),this._callHook=null,this._addedWeightNames=[],this._stateful=!1,this.id=PV++,this.activityRegularizer=null,this.inputSpec=null,this.supportsMasking=!1,this._trainableWeights=[],this._nonTrainableWeights=[],this._losses=[],this._updates=[],this._built=!1,this.inboundNodes=[],this.outboundNodes=[];let t=e.name;if(!t){let n=this.getClassName();t=ua(n)+"_"+J0(n)}if(this.name=t,this.trainable_=e.trainable==null?!0:e.trainable,e.inputShape!=null||e.batchInputShape!=null){let n;if(e.batchInputShape!=null)n=e.batchInputShape;else if(e.inputShape!=null){let r=null;e.batchSize!=null&&(r=e.batchSize),n=[r].concat(e.inputShape)}this.batchInputShape=n;let s=e.dtype;s==null&&(s=e.inputDType),s==null&&(s="float32"),this.dtype=s}e.weights!=null?this.initialWeights=e.weights:this.initialWeights=null,this._refCount=null,this.fastWeightInitDuringBuild=!1}static nodeKey(e,t){return e.name+"_ib-"+t.toString()}getNodeAtIndex(e,t){if(this.inboundNodes.length===0)throw new Sr(`The layer has never been called and thus has no defined ${t}.`);if(this.inboundNodes.length<=e)throw new j(`Asked to get ${t} at node ${e}, but the layer has only ${this.inboundNodes.length} inbound nodes.`);return this.inboundNodes[e]}getInputAt(e){return ps(this.getNodeAtIndex(e,"input").inputTensors)}getOutputAt(e){return ps(this.getNodeAtIndex(e,"output").outputTensors)}get input(){if(this.inboundNodes.length>1)throw new la(`Layer ${this.name} has multiple inbound nodes, hence the notion of "layer input" is ill-defined. Use \`getInputAt(nodeIndex)\` instead.`);if(this.inboundNodes.length===0)throw new la(`Layer ${this.name} is not connected, no input to return.`);return ps(this.getNodeAtIndex(0,"input").inputTensors)}get output(){if(this.inboundNodes.length===0)throw new la(`Layer ${this.name} has no inbound nodes.`);if(this.inboundNodes.length>1)throw new la(`Layer ${this.name} has multiple inbound nodes, hence the notion of "layer output" is ill-defined. Use \`getOutputAt(nodeIndex)\` instead.`);return ps(this.getNodeAtIndex(0,"output").outputTensors)}get losses(){return this._losses}calculateLosses(){return this.losses.map(e=>e())}get updates(){return this._updates}get built(){return this._built}set built(e){this._built=e}get trainable(){return this.trainable_}set trainable(e){this._trainableWeights.forEach(t=>t.trainable=e),this.trainable_=e}get trainableWeights(){return this.trainable_?this._trainableWeights.filter(e=>e.trainable):[]}set trainableWeights(e){this._trainableWeights=e}get nonTrainableWeights(){return this.trainable?this._trainableWeights.filter(e=>!e.trainable).concat(this._nonTrainableWeights):this._trainableWeights.concat(this._nonTrainableWeights)}set nonTrainableWeights(e){this._nonTrainableWeights=e}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}get stateful(){return this._stateful}resetStates(){if(!this.stateful)throw new Error("Cannot call the resetStates() method of a non-stateful Layer object.")}assertInputCompatibility(e){if(e=_t(e),this.inputSpec==null||this.inputSpec.length===0)return;let t=_t(this.inputSpec);if(e.length!==t.length)throw new j(`Layer ${this.name} expects ${t.length} inputs, but it received ${e.length} input tensors. Input received: ${e}`);for(let n=0;n<e.length;n++){let s=e[n],r=t[n];if(r==null)continue;let a=s.rank;if(r.ndim!=null&&a!==r.ndim)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected ndim=${r.ndim}, found ndim=${a}`);if(r.maxNDim!=null&&a>r.maxNDim)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected max_ndim=${r.maxNDim}, found ndim=${a}`);if(r.minNDim!=null&&a<r.minNDim)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected min_ndim=${r.minNDim}, found ndim=${a}.`);if(r.dtype!=null&&s.dtype!==r.dtype)throw new j(`Input ${n} is incompatible with layer ${this.name} : expected dtype=${r.dtype}, found dtype=${s.dtype}.`);if(r.axes){let o=s.shape;for(let i in r.axes){let l=Number(i),u=r.axes[i],c=l>=0?o[l]:o[o.length+l];if(u!=null&&[u,null].indexOf(c)===-1)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected axis ${l} of input shape to have value ${u} but got shape ${o}.`)}}if(r.shape!=null)for(let o=0;o<r.shape.length;++o){let i=r.shape[o],l=s.shape[o];if(i!=null&&l!=null&&i!==l)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected shape=${r.shape}, found shape=${s.shape}.`)}}}call(e,t){return e}invokeCallHook(e,t){this._callHook!=null&&this._callHook(e,t)}setCallHook(e){this._callHook=e}clearCallHook(){this._callHook=null}apply(e,t){t=t||{},this.assertNotDisposed();let n=_t(e),s=!0;for(let a of n)if(!(a instanceof Cr)){s=!1;break}let r=!0;for(let a of n)if(a instanceof Cr){r=!1;break}if(s===r)throw new j("Arguments to apply() must be all SymbolicTensors or all Tensors");return Hi(this.name,()=>{if(!this.built){this.assertInputCompatibility(e);let a=[];for(let o of _t(e))a.push(o.shape);this.build(ps(a)),this.built=!0,this.initialWeights&&this.setWeights(this.initialWeights),this._refCount===null&&r&&(this._refCount=1)}if(this.assertInputCompatibility(e),r){let a=this.call(e,t),o=_t(a),i=[];for(let l of o)n.indexOf(l)!==-1&&(l=l.clone()),i.push(l);if(a=ps(i),this.activityRegularizer!=null)throw new He("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return a}else{let a=FV(e),o=this.computeOutputShape(a),i,l=OV(e);if(this.warnOnIncompatibleInputShape(Array.isArray(e)?a[0]:a),o!=null&&o.length>0&&Array.isArray(o[0])?i=o.map((u,c)=>new Cr(l,u,this,_t(e),t,this.name,c)):i=new Cr(l,o,this,_t(e),t,this.name),this.addInboundNode(e,i,null,null,a,o,t),this._refCount++,this.activityRegularizer!=null)throw new He("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return i}})}warnOnIncompatibleInputShape(e){if(this.batchInputShape!=null)if(e.length!==this.batchInputShape.length)console.warn(`The rank of the input tensor provided (shape: ${JSON.stringify(e)}) does not match that of the batchInputShape (${JSON.stringify(this.batchInputShape)}) of the layer ${this.name}`);else{let t=!1;this.batchInputShape.forEach((n,s)=>{n!=null&&e[s]!=null&&e[s]!==n&&(t=!0)}),t&&console.warn(`The shape of the input tensor (${JSON.stringify(e)}) does not match the expectation of layer ${this.name}: ${JSON.stringify(this.batchInputShape)}`)}}get outputShape(){if(this.inboundNodes==null||this.inboundNodes.length===0)throw new la(`The layer ${this.name} has never been called and thus has no defined output shape.`);let e=[];for(let t of this.inboundNodes){let n=JSON.stringify(t.outputShapes);e.indexOf(n)===-1&&e.push(n)}if(e.length===1){let t=this.inboundNodes[0].outputShapes;return Array.isArray(t)&&Array.isArray(t[0])&&t.length===1?t[0]:t}else throw new la(`The layer ${this.name} has multiple inbound nodes with different output shapes. Hence the notion of "output shape" is ill-defined for the layer.`)}countParams(){if(!this.built)throw new Sr(`You tried to call countParams() on ${this.name}, but the layer is not built yet. Build it first by calling build(batchInputShape).`);return bm(this.weights)}build(e){this.built=!0}getWeights(e=!1){return O3(e?this.trainableWeights:this.weights)}setWeights(e){J(()=>{let t=this.weights;if(t.length!==e.length)throw new j(`You called setWeights(weights) on layer "${this.name}" with a weight list of length ${e.length}, but the layer was expecting ${t.length} weights. Provided weights: ${e}...`);if(t.length===0)return;let n=[],s=O3(t);for(let r=0;r<s.length;++r){let a=s[r],o=t[r],i=e[r];if(!v.arraysEqual(a.shape,i.shape))throw new j(`Layer weight shape ${a.shape} not compatible with provided weight shape ${i.shape}`);n.push([o,i])}r5(n)})}addWeight(e,t,n,s,r,a,o,i){if(this._addedWeightNames.indexOf(e)!==-1)throw new j(`Duplicate weight name ${e} for layer ${this.name}`);this._addedWeightNames.push(e),n==null&&(n="float32"),this.fastWeightInitDuringBuild&&(s=i!=null?i():Ot("zeros"));let l=s.apply(t,n),u=new b8(l,n,e,a,o);return l.dispose(),r!=null&&this.addLoss(()=>r.apply(u.read())),a==null&&(a=!0),a?this._trainableWeights.push(u):this._nonTrainableWeights.push(u),u}setFastWeightInitDuringBuild(e){this.fastWeightInitDuringBuild=e}addLoss(e){e==null||Array.isArray(e)&&e.length===0||(e=_t(e),this._losses!==void 0&&this._losses!==null&&this.losses.push(...e))}computeOutputShape(e){return e}computeMask(e,t){if(!this.supportsMasking){if(t!=null)if(Array.isArray(t))t.forEach(n=>{if(n!=null)throw new TypeError(`Layer ${this.name} does not support masking, but was passed an inputMask.`)});else throw new TypeError(`Layer ${this.name} does not support masking, but was passed an inputMask.`);return null}return t}addInboundNode(e,t,n,s,r,a,o=null){let i=_t(e);t=_t(t),n=_t(n),s=_t(s),r=xm(r),a=xm(a);let l=[],u=[],c=[];for(let p of i)l.push(p.sourceLayer),u.push(p.nodeIndex),c.push(p.tensorIndex);new l2({outboundLayer:this,inboundLayers:l,nodeIndices:u,tensorIndices:c,inputTensors:i,outputTensors:t,inputMasks:n,outputMasks:s,inputShapes:r,outputShapes:a},o);for(let p=0;p<t.length;p++)t[p].sourceLayer=this,t[p].nodeIndex=this.inboundNodes.length-1,t[p].tensorIndex=p}getConfig(){let e={name:this.name,trainable:this.trainable};return this.batchInputShape!=null&&(e.batchInputShape=this.batchInputShape),this.dtype!=null&&(e.dtype=this.dtype),e}disposeWeights(){return this.weights.forEach(e=>e.dispose()),this.weights.length}assertNotDisposed(){if(this._refCount===0)throw new Error(`Layer '${this.name}' is already disposed.`)}dispose(){if(!this.built)throw new Error(`Cannot dispose Layer ${this.name} because it has not been built yet.`);if(this._refCount===null)throw new Error(`Cannot dispose Layer ${this.name} because it has not been used yet.`);this.assertNotDisposed();let e=0;return--this._refCount===0&&(e=this.disposeWeights()),{refCountAfterDispose:this._refCount,numDisposedVariables:e}}};function FV(e){e=_t(e);let t=[];for(let n of e)t.push(n.shape);return ps(t)}function OV(e){return"float32"}function v8(e,t,n){if((t==null||n!=null&&n>0)&&(t=e.sourceLayer,n=e.nodeIndex),t.inboundNodes.length===0)return[e];{let s=t.inboundNodes[n];if(s.inboundLayers.length===0)return s.inputTensors;{let r=[];for(let a=0;a<s.inboundLayers.length;a++){let o=s.inputTensors[a],i=s.inboundLayers[a],l=s.nodeIndices[a],u=v8(o,i,l);for(let c of u)r.indexOf(c)===-1&&r.push(c)}return r}}}var Yc=class extends ut{constructor(e){if(super({dtype:e.dtype,name:e.name!=null?e.name:J0("input").toString()}),e.batchSize==null&&(e.batchSize=null),e.sparse==null&&(e.sparse=!1),this.trainable=!1,this.built=!0,this.sparse=e.sparse,e.inputShape!=null&&e.batchInputShape!=null)throw new j("Only provide the inputShape OR batchInputShape argument to inputLayer, not both at the same time.");let t=e.batchInputShape;if(t==null){if(e.inputShape==null)throw new j("An InputLayer should be passed either a `batchInputShape` or an `inputShape`.");t=[e.batchSize].concat(e.inputShape)}else if(e.batchSize!=null)throw new j("Cannot specify batchSize if batchInputShape is specified when creating an InputLayer.");let n=e.dtype||"float32";this.batchInputShape=t,this.dtype=n,this.inputSpec=[{shape:t}];let s=new Cr(this.dtype,this.batchInputShape,this,[],{},this.name);s.nodeIndex=0,s.tensorIndex=0,new l2({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:[s],outputTensors:[s],inputMasks:[null],outputMasks:[null],inputShapes:[t],outputShapes:[t]})}apply(e,t){throw new j(`Cannot pass any input to an InputLayer's apply() method. InputLayer name: ${this.name}`)}dispose(){return{refCountAfterDispose:this._refCount,numDisposedVariables:0}}getConfig(){return{batchInputShape:this.batchInputShape,dtype:this.dtype,sparse:this.sparse,name:this.name}}};Yc.className="InputLayer";de.registerClass(Yc);function w8(e){if(e.batchShape==null&&e.shape==null)throw new Error("Please provide to Input either a `shape` or a `batchShape` argument. Note that `shape` does not include the batch dimension.");if(e.batchShape!=null&&e.shape!=null)throw new j("Please provide either a `shape` or `batchShape` argument to Input, but not both.");let t=e.batchShape;e.shape!=null&&t==null&&(t=[null].concat(e.shape));let n=e.dtype;return n==null&&(n="float32"),new Yc({batchInputShape:t,name:e.name,dtype:n,sparse:e.sparse}).inboundNodes[0].outputTensors[0]}function MV(e,t){if(e.dtype==null||e.dtype===t.dtype)return t;try{return ge(t,e.dtype)}catch(n){throw new j(`The dtype of the feed (${t.dtype}) can not be cast to the dtype of the key '${e.name}' (${e.dtype}).`)}}var Vi=class{constructor(e){if(this.id2Value={},this.id2Mask={},this.name2Id={},e instanceof Vi)for(let t in e.id2Value)this.id2Value[t]=e.id2Value[t],t in e.id2Mask&&(this.id2Mask[t]=e.id2Mask[t]);else{if(e==null)return;for(let t of e)this.add(t.key,t.value)}}add(e,t,n){if(this.id2Value[e.id]==null)this.id2Value[e.id]=MV(e,t),this.name2Id[e.name]=e.id,n!=null&&(this.id2Mask[e.id]=n);else throw new j(`Duplicate key: name=${e.name}, id=${e.id}`);return this}addFeed(e){this.add(e.key,e.value)}hasKey(e){return this.id2Value[e.id]!=null}names(){return Object.keys(this.name2Id)}getValue(e){if(e instanceof Cr){if(this.id2Value[e.id]==null)throw new j(`Nonexistent key: ${e.name}`);return this.id2Value[e.id]}else{let t=this.name2Id[e];if(t==null)throw new j(`Feed dict has no SymbolicTensor name: ${e}`);return this.id2Value[t]}}getMask(e){if(e instanceof Cr){if(this.id2Value[e.id]==null)throw new j(`Nonexistent key: ${e.name}`);return this.id2Mask[e.id]}else{let t=this.name2Id[e];if(t==null)throw new j(`Feed dict has no SymbolicTensor name: ${e}`);return this.id2Mask[t]}}disposeMasks(){this.id2Mask!=null&&ne(this.id2Mask)}},vm=new c8,wm=new c8;function zV(e){vm!=null&&vm.setMaxEntries(e),wm!=null&&wm.setMaxEntries(e)}function ap(e,t,n,s){let r=n==null?!1:n.training,a=Array.isArray(e),o=a?e:[e],i=o.map(f=>f.name),l=[],u=t.names();for(let f of i)u.indexOf(f)!==-1?l.push(t.getValue(f)):l.push(null);s!=null&&(s.maxNumTensors=-1/0,s.minNumTensors=1/0);let c=i.join(",")+"|"+t.names().sort().join(","),p=vm.get(c),d;if(p==null){let f=LV(o,t);p=f.sorted,d=f.recipientCounts,vm.put(c,p),wm.put(c,d)}d={},r||Object.assign(d,wm.get(c));let h=new Vi(t);for(let f=0;f<p.length;++f){if(s!=null){let R=ym().numTensors;R>s.maxNumTensors&&(s.maxNumTensors=R),R<s.minNumTensors&&(s.minNumTensors=R)}let m=p[f],g=m.sourceLayer;if(g instanceof Yc)continue;let y=[],x=[],A=[],b=!1;for(let R of m.inputs){let P=h.getValue(R),_=h.getMask(R);y.push(P),x.push(_),_!=null&&(b=!0),r||(d[R.name]--,d[R.name]===0&&!t.hasKey(R)&&i.indexOf(R.name)===-1&&!P.isDisposed&&R.sourceLayer.stateful!==!0&&A.push(P))}b&&(n=n||{},n.mask=x[0]);let w=_t(g.apply(y,n)),k=null;g.supportsMasking&&(k=g.computeMask(y,x));let S=WV(m),E=Array.isArray(S)?S:[S];for(let R=0;R<E.length;++R){h.hasKey(E[R])||h.add(E[R],w[R],Array.isArray(k)?k[0]:k);let P=i.indexOf(E[R].name);P!==-1&&(l[P]=w[R])}r||ne(A)}return h.disposeMasks(),a?l:l[0]}function LV(e,t){v.assert(e!=null&&e.length>0,()=>"Expected at least one fetch, got none");let n=[],s={};if(e.length===1){let r=Mv(e[0],t);n=r.sorted,s=r.recipientMap}else{let r=new Set;for(let a of e){let{sorted:o,recipientMap:i}=Mv(a,t);for(let l of o)r.has(l.name)||(n.push(l),r.add(l.name));for(let l in i)s[l]==null&&(s[l]=new Set),i[l].forEach(u=>s[l].add(u))}}return{sorted:n,recipientCounts:BV(s)}}function BV(e){let t={};for(let n in e)t[n]=e[n].size;return t}function Mv(e,t){let n=new Set,s=[],r={};for(let i of t.names())n.add(i);let a=[],o=[];for(a.push(e);a.length>0;){let i=a[a.length-1];if(n.has(i.name)){a.pop();continue}let l=o[o.length-1]===a.length-1;if(i.inputs.length===0||l)a.pop(),s.push(i),n.add(i.name),l&&o.pop();else{o.push(a.length-1);for(let u of i.inputs)r[u.name]==null&&(r[u.name]=new Set),r[u.name].add(i.name),!n.has(u.name)&&a.push(u)}}return{sorted:s,recipientMap:r}}function WV(e){let t;if(e.sourceLayer.inboundNodes.length===1)t=e.sourceLayer.output;else{let n=null;for(let s=0;s<e.sourceLayer.inboundNodes.length;++s)for(let r of e.sourceLayer.inboundNodes[s].outputTensors)if(r.id===e.id){n=s;break}t=e.sourceLayer.getOutputAt(n)}return t}var VV=Z();VV.registerFlag("TOPOLOGICAL_SORT_CACHE_MAX_ENTRIES",()=>100,zV);var k8={};Ve(k8,{maxNorm:()=>UV,minMaxNorm:()=>jV,nonNeg:()=>HV,unitNorm:()=>GV});function a5(e,t){return J(()=>Nn(ke(L(e,e),t,!0)))}var Ch=class extends de.Serializable{getConfig(){return{}}},o5=class extends Ch{constructor(e){super(),this.defaultMaxValue=2,this.defaultAxis=0,this.maxValue=e.maxValue!=null?e.maxValue:this.defaultMaxValue,this.axis=e.axis!=null?e.axis:this.defaultAxis}apply(e){return J(()=>{let t=a5(e,this.axis),n=fs(t,0,this.maxValue);return L(e,pe(n,ce(hn(),t)))})}getConfig(){return{maxValue:this.maxValue,axis:this.axis}}};o5.className="MaxNorm";de.registerClass(o5);var i5=class extends Ch{constructor(e){super(),this.defaultAxis=0,this.axis=e.axis!=null?e.axis:this.defaultAxis}apply(e){return J(()=>pe(e,ce(hn(),a5(e,this.axis))))}getConfig(){return{axis:this.axis}}};i5.className="UnitNorm";de.registerClass(i5);var l5=class extends Ch{apply(e){return Pr(e)}};l5.className="NonNeg";de.registerClass(l5);var u5=class extends Ch{constructor(e){super(),this.defaultMinValue=0,this.defaultMaxValue=1,this.defaultRate=1,this.defaultAxis=0,this.minValue=e.minValue!=null?e.minValue:this.defaultMinValue,this.maxValue=e.maxValue!=null?e.maxValue:this.defaultMaxValue,this.rate=e.rate!=null?e.rate:this.defaultRate,this.axis=e.axis!=null?e.axis:this.defaultAxis}apply(e){return J(()=>{let t=a5(e,this.axis),n=ce(L(this.rate,fs(t,this.minValue,this.maxValue)),L(1-this.rate,t));return L(e,pe(n,ce(hn(),t)))})}getConfig(){return{minValue:this.minValue,maxValue:this.maxValue,rate:this.rate,axis:this.axis}}};u5.className="MinMaxNorm";de.registerClass(u5);var zv={maxNorm:"MaxNorm",minMaxNorm:"MinMaxNorm",nonNeg:"NonNeg",unitNorm:"UnitNorm"};function gn(e){return XA(e)}function Lv(e,t={}){return wh(e,de.SerializationMap.getMap().classNameMap,t,"constraint")}function yn(e){if(e==null)return null;if(typeof e=="string"){let n={className:e in zv?zv[e]:e,config:{}};return Lv(n)}else return e instanceof Ch?e:Lv(e)}function UV(e){return new o5(e)}function GV(e){return new i5(e)}function HV(){return new l5}function jV(e){return new u5(e)}var I8={};Ve(I8,{constant:()=>KV,glorotNormal:()=>nU,glorotUniform:()=>tU,heNormal:()=>sU,heUniform:()=>rU,identity:()=>QV,leCunNormal:()=>aU,leCunUniform:()=>oU,ones:()=>XV,orthogonal:()=>iU,randomNormal:()=>YV,randomUniform:()=>ZV,truncatedNormal:()=>JV,varianceScaling:()=>eU,zeros:()=>qV});function qV(){return new YA}function XV(){return new t2}function KV(e){return new JA(e)}function ZV(e){return new QA(e)}function YV(e){return new e5(e)}function JV(e){return new t5(e)}function QV(e){return new n5(e)}function eU(e){return new ms(e)}function tU(e){return new n2(e)}function nU(e){return new s2(e)}function sU(e){return new r2(e)}function rU(e){return new a2(e)}function aU(e){return new o2(e)}function oU(e){return new i2(e)}function iU(e){return new s5(e)}var S8={};Ve(S8,{Layer:()=>ut,RNN:()=>Qr,RNNCell:()=>_h,activation:()=>$G,add:()=>VG,alphaDropout:()=>SH,average:()=>UG,averagePooling1d:()=>gx,averagePooling2d:()=>yx,averagePooling3d:()=>Ax,avgPool1d:()=>JG,avgPool2d:()=>eH,avgPool3d:()=>nH,avgPooling1d:()=>QG,avgPooling2d:()=>tH,avgPooling3d:()=>sH,batchNormalization:()=>KG,bidirectional:()=>yH,concatenate:()=>GG,conv1d:()=>IG,conv2d:()=>SG,conv2dTranspose:()=>CG,conv3d:()=>TG,conv3dTranspose:()=>NG,convLstm2d:()=>hH,convLstm2dCell:()=>fH,cropping2D:()=>RG,dense:()=>PG,depthwiseConv2d:()=>DG,dot:()=>XG,dropout:()=>FG,elu:()=>AG,embedding:()=>WG,flatten:()=>MG,gaussianDropout:()=>IH,gaussianNoise:()=>kH,globalAveragePooling1d:()=>rH,globalAveragePooling2d:()=>aH,globalMaxPool1d:()=>xH,globalMaxPool2d:()=>bH,globalMaxPooling1d:()=>gk,globalMaxPooling2d:()=>yk,gru:()=>iH,gruCell:()=>lH,input:()=>U8,inputLayer:()=>yG,layerNormalization:()=>ZG,leakyReLU:()=>bG,lstm:()=>uH,lstmCell:()=>cH,masking:()=>CH,maxPool1d:()=>vH,maxPool2d:()=>wH,maxPooling1d:()=>Ak,maxPooling2d:()=>xk,maxPooling3d:()=>oH,maximum:()=>HG,minimum:()=>jG,multiply:()=>qG,permute:()=>BG,prelu:()=>vG,reLU:()=>xG,repeatVector:()=>zG,reshape:()=>LG,rnn:()=>mH,separableConv2d:()=>EG,simpleRNN:()=>dH,simpleRNNCell:()=>pH,softmax:()=>wG,spatialDropout1d:()=>OG,stackedRNNCells:()=>gH,thresholdedReLU:()=>kG,timeDistributed:()=>AH,upSampling2d:()=>_G,zeroPadding2d:()=>YG});async function Va(e){if(e==null)return;let t=[],n=[],s=[];for(let r in e){let a=e[r];if(typeof a!="number"){let o=a;t.push(o.data()),n.push(r),s.push(o)}}if(t.length>0){let r=await Promise.all(t);for(let a=0;a<r.length;++a)e[n[a]]=r[a][0];ne(s)}}function C8(e){if(e!=null)for(let t in e){let n=e[t];typeof n!="number"&&n.dispose()}}var Bv;(function(e){e[e.SILENT=0]="SILENT",e[e.VERBOSE=1]="VERBOSE"})(Bv||(Bv={}));var lU=125,nc=class{constructor(){this.validationData=null}setParams(e){this.params=e}async onEpochBegin(e,t){}async onEpochEnd(e,t){}async onBatchBegin(e,t){}async onBatchEnd(e,t){}async onTrainBegin(e){}async onTrainEnd(e){}setModel(e){}},T8=class{constructor(e,t=10){e==null&&(e=[]),this.callbacks=e,this.queueLength=t}append(e){this.callbacks.push(e)}setParams(e){for(let t of this.callbacks)t.setParams(e)}setModel(e){for(let t of this.callbacks)t.setModel(e)}async onEpochBegin(e,t){t==null&&(t={});for(let n of this.callbacks)await n.onEpochBegin(e,t)}async onEpochEnd(e,t){t==null&&(t={});for(let n of this.callbacks)await n.onEpochEnd(e,t)}async onBatchBegin(e,t){t==null&&(t={});for(let n of this.callbacks)await n.onBatchBegin(e,t)}async onBatchEnd(e,t){t==null&&(t={});for(let n of this.callbacks)await n.onBatchEnd(e,t)}async onTrainBegin(e){e==null&&(e={});for(let t of this.callbacks)await t.onTrainBegin(e)}async onTrainEnd(e){e==null&&(e={});for(let t of this.callbacks)await t.onTrainEnd(e)}},uU=class extends nc{constructor(){super()}async onEpochBegin(e){this.seen=0,this.totals={}}async onBatchEnd(e,t){t==null&&(t={});let n=t.size==null?0:t.size;this.seen+=n;for(let s in t){let r=t[s];if(typeof r=="number")this.totals.hasOwnProperty(s)||(this.totals[s]=0),this.totals[s]=this.totals[s]+r*n;else{let a;s in this.totals?a=this.totals[s]:this.totals[s]=0;let o=J(()=>ce(this.totals[s],L(r,n)));this.totals[s]=o,a!=null&&a.dispose()}}}async onEpochEnd(e,t){if(t!=null)for(let n of this.params.metrics)this.totals[n]!=null&&(typeof this.totals[n]=="number"?t[n]=this.totals[n]/this.seen:J(()=>{let s=L(pe(1,this.seen),this.totals[n]);t[n]=s,this.totals[n].dispose(),bn(t[n])}))}},N8=class extends nc{async onTrainBegin(e){this.epoch=[],this.history={}}async onEpochEnd(e,t){t==null&&(t={}),this.epoch.push(e);for(let n in t)this.history[n]==null&&(this.history[n]=[]),this.history[n].push(t[n])}async syncData(){let e=[],t=[],n=[];for(let r in this.history){let a=this.history[r];for(let o=0;o<a.length;++o)if(typeof a[o]!="number"){let i=a[o];e.push(i.data()),t.push(r),n.push(o)}}let s=await Promise.all(e);for(let r=0;r<s.length;++r)this.history[t[r]][n[r]].dispose(),this.history[t[r]][n[r]]=s[r][0]}},E8=class extends nc{constructor(e,t){if(super(),this.currentEpoch=0,this.nowFunc=e.nowFunc,this.nextFrameFunc=e.nextFrameFunc||jA,this.yieldEvery=t||"auto",this.yieldEvery==="auto"&&(this.yieldEvery=lU),this.yieldEvery==="never"&&e.onYield!=null)throw new Error("yieldEvery is `never` but you provided an `onYield` callback. Either change `yieldEvery` or remove the callback");v.isNumber(this.yieldEvery)&&(this.maybeWait=cV(this.maybeWait.bind(this),this.yieldEvery,this.nowFunc)),this.trainBegin=e.onTrainBegin,this.trainEnd=e.onTrainEnd,this.epochBegin=e.onEpochBegin,this.epochEnd=e.onEpochEnd,this.batchBegin=e.onBatchBegin,this.batchEnd=e.onBatchEnd,this.yield=e.onYield}async maybeWait(e,t,n){let s=[];this.yield!=null&&(await Va(n),s.push(this.yield(e,t,n))),s.push(this.nextFrameFunc()),await Promise.all(s)}async onEpochBegin(e,t){this.currentEpoch=e,this.epochBegin!=null&&(await Va(t),await this.epochBegin(e,t))}async onEpochEnd(e,t){let n=[];this.epochEnd!=null&&(await Va(t),n.push(this.epochEnd(e,t))),this.yieldEvery==="epoch"&&n.push(this.nextFrameFunc()),await Promise.all(n)}async onBatchBegin(e,t){this.batchBegin!=null&&(await Va(t),await this.batchBegin(e,t))}async onBatchEnd(e,t){let n=[];this.batchEnd!=null&&(await Va(t),n.push(this.batchEnd(e,t))),this.yieldEvery==="batch"?n.push(this.nextFrameFunc()):v.isNumber(this.yieldEvery)&&n.push(this.maybeWait(this.currentEpoch,e,t)),await Promise.all(n)}async onTrainBegin(e){this.trainBegin!=null&&(await Va(e),await this.trainBegin(e))}async onTrainEnd(e){this.trainEnd!=null&&(await Va(e),await this.trainEnd(e))}};function R8(e,t){return e==null&&(e={}),e instanceof nc?[e]:Array.isArray(e)&&e[0]instanceof nc?e:_t(e).map(s=>new E8(s,t))}var rr=class{constructor(){}static registerCallbackConstructor(e,t){v.assert(e>=0&&Number.isInteger(e),()=>`Verbosity level is expected to be an integer >= 0, but got ${e}`),rr.checkForDuplicate(t),rr.constructors[e]==null&&(rr.constructors[e]=[]),rr.constructors[e].push(t)}static checkForDuplicate(e){for(let t in rr.constructors)rr.constructors[+t].forEach(s=>{if(s===e)throw new j("Duplicate callback constructor.")})}static clear(){rr.constructors={}}static createCallbacks(e){let t=[];for(let n in rr.constructors){let s=+n;e>=s&&t.push(...rr.constructors[s])}return t.map(n=>new n)}};rr.constructors={};function _8(e,t,n,s,r,a,o,i,l){let u=new N8,c=[new uU,...rr.createCallbacks(t)];e!=null&&c.push(...e),c.push(u);let p=new T8(c);return p.setParams({epochs:n,initialEpoch:s,samples:r,steps:a,batchSize:o,verbose:t,doValidation:i,metrics:l}),{callbackList:p,history:u}}function Nr(e,t={},n=!1){return wh(e,de.SerializationMap.getMap().classNameMap,t,"layer",n)}function km(e,t){return J(()=>{e.dtype!=="float32"&&(e=ge(e,"float32"));let n=ke(Ih(e),t,!0),s=Hc(n.shape,hn()),r=Nn(Jr(n,s));return pe(e,r)})}function tu(e,t){return J(()=>Bt(Ih(he(t,e)),-1))}function u2(e,t){return J(()=>Bt(tn(he(t,e)),-1))}function Jc(e,t){return J(()=>{let n=he(e,t),s=fs(tn(e),hn(),Number.MAX_VALUE),r=tn(pe(n,s));return L(100,Bt(r,-1))})}function cU(e,t){return J(()=>{let n=fs(t,hn(),Number.MAX_VALUE),s=Ds(ce(1,n)),r=fs(e,hn(),Number.MAX_VALUE),a=Ds(ce(1,r));return Bt(Ih(he(s,a)),-1)})}function dU(e,t){return J(()=>{let n=Jr(0,he(1,L(e,t)));return Bt(Ih(n),-1)})}function pU(e,t){return J(()=>{let n=Jr(0,he(1,L(e,t)));return Bt(n,-1)})}function hU(e,t){return J(()=>{let n=ke(L(e,t),-1),s=mn(L(he(1,e),t),-1);return Jr(0,ce(1,he(s,n)))})}function fU(e,t){return J(()=>{let n=Math.log(2),s=he(t,e),r=he(ce(s,Zl(L(-2,s))),n);return Bt(r,-1)})}function Np(e,t,n=!1){return J(()=>{if(n)t=Jl(t);else{let s=ke(t,t.shape.length-1,!0);t=pe(t,s)}return t=fs(t,hn(),1-hn()),Dt(ke(L(ge(e,"float32"),Ds(t)),t.shape.length-1))})}function Im(e,t,n=!1){return J(()=>{let s=ge(jc(wV(e)),"int32");t=fs(t,hn(),1-hn());let r=t.shape,a=U(Zu(s,r[r.length-1]),r);return Np(a,t,n)})}function mU(e,t){if(!v.arraysEqual(e.shape,t.shape))throw new j(`logits and labels must have the same shape, but got shapes ${JSON.stringify(e.shape)} and ${JSON.stringify(t.shape)}`);return J(()=>{let n=Pr(t),s=Dt(tn(t));return ce(he(n,L(t,e)),ph(_s(s)))})}function c2(e,t){return J(()=>{let n;return n=fs(t,hn(),1-hn()),n=Ds(pe(n,he(1,n))),Bt(mU(e,n),-1)})}function gU(e,t){return J(()=>{let n=fs(e,hn(),1),s=fs(t,hn(),1);return ke(L(e,Ds(pe(n,s))),-1)})}function yU(e,t){return J(()=>{let n=Ds(ce(hn(),t));return Bt(he(t,L(e,n)),-1)})}function c5(e,t){return J(()=>{let n=km(e,-1),s=km(t,-1),r=L(n,s);return Dt(ke(r,-1))})}var Sm={meanSquaredError:tu,meanAbsoluteError:u2,meanAbsolutePercentageError:Jc,meanSquaredLogarithmicError:cU,squaredHinge:dU,hinge:pU,categoricalHinge:hU,logcosh:fU,categoricalCrossentropy:Np,sparseCategoricalCrossentropy:Im,binaryCrossentropy:c2,kullbackLeiblerDivergence:gU,poisson:yU,cosineProximity:c5};function c3(e){if(typeof e=="string"){if(e in Sm)return Sm[e];let t=`Unknown loss ${e}`;throw e.toLowerCase().includes("softmaxcrossentropy")&&(t=`Unknown loss ${e}. Use "categoricalCrossentropy" as the string name for tf.losses.softmaxCrossEntropy`),new j(t)}else return e}function d5(e,t){return J(()=>{let n=L(.5,$s(t)),s=Q0(ys(t,n),e.dtype);return Bt(Rs(e,s),-1)})}function p5(e,t){return J(()=>Q0(Rs(Es(e,-1),Es(t,-1)),"float32"))}function D8(e,t){return J(()=>ge(ke(lr(Rs(e,1),Rs(t,1))),"float32"))}function AU(e,t){return J(()=>ge(ke(lr(Rs(e,1),Rs(t,0))),"float32"))}function xU(e,t){return J(()=>ge(ke(lr(Rs(e,0),Rs(t,1))),"float32"))}function $8(e,t){return J(()=>{let n=D8(e,t),s=xU(e,t),r=ce(n,s);return ge(Mn(ys(r,0),pe(n,r),0),"float32")})}function bU(e,t){return J(()=>{let n=D8(e,t),s=AU(e,t),r=ce(n,s);return ge(Mn(ys(r,0),pe(n,r),0),"float32")})}function P8(e,t){return c2(e,t)}function F8(e,t){return e.rank===t.rank&&(e=rt(e,[e.rank-1])),t=Es(t,-1),t.dtype!==e.dtype&&(t=ge(t,e.dtype)),ge(Rs(e,t),"float32")}var vU=tu,wU=tu,kU=u2,IU=u2,SU=Jc,CU=Jc,h5=Np,TU=c5,O8=Im,Cm={binaryAccuracy:d5,categoricalAccuracy:p5,precision:$8,categoricalCrossentropy:h5,sparseCategoricalCrossentropy:O8,mse:vU,MSE:wU,mae:kU,MAE:IU,mape:SU,MAPE:CU,cosine:TU};function NU(e){if(typeof e=="string"&&e in Cm)return Cm[e];if(typeof e!="string"&&e!=null)return e;throw new j(`Unknown metric ${e}`)}function Gf(e){if(Vr(e!==null,`Unknown LossOrMetricFn ${e}`),typeof e=="string")return e;{let t;for(let n of Object.keys(Sm))if(Sm[n]===e){t=n;break}if(t!==void 0)return t;for(let n of Object.keys(Cm))if(Cm[n]===e){t=n;break}return t!==void 0?t:e.name}}function EU(e){let t={Adagrad:()=>Fi.adagrad(.01),Adadelta:()=>Fi.adadelta(1,.95,hn()),Adam:()=>Fi.adam(.001,.9,.999,hn()),Adamax:()=>Fi.adamax(.002,.9,.999,hn(),0),RMSProp:()=>Fi.rmsprop(.001,.9,0,hn()),SGD:()=>Fi.sgd(.01)};if(t.adagrad=t.Adagrad,t.adadelta=t.Adadelta,t.adam=t.Adam,t.adamax=t.Adamax,t.rmsprop=t.RMSProp,t.sgd=t.SGD,e in t)return t[e]();throw new j(`Unknown Optimizer ${e}`)}var Wv=1*1024*1024;function Vv(e,t,n=!1){if(e==null||typeof e!="object"||Object.getPrototypeOf(e)!==Object.prototype||!M3(e))throw new Error("User-defined metadata is expected to be a JSON object, but is not.");if(n){let s=JSON.stringify(e);s.length>Wv&&console.warn(`User-defined metadata of model "${t}" is too large in size (length=${s.length} when serialized). It is not recommended to store such large objects in user-defined metadata. Please make sure its serialized length is <= ${Wv}.`)}}function M3(e){if(e===null)return!0;if(typeof e=="object")if(Object.getPrototypeOf(e)===Object.prototype){let t=Object.keys(e);for(let n of t)if(typeof n!="string"||!M3(e[n]))return!1;return!0}else if(Array.isArray(e)){for(let t of e)if(!M3(t))return!1;return!0}else return!1;else{let t=typeof e;return t==="string"||t==="number"||t==="boolean"}}function RU(e,t,n,s=console.log){let r=DU(e),a=["Layer (type)","Input Shape","Output shape","Param #"];r?(t=t||90,n=n||[.32,.61,.89,1]):(t=t||115,n=n||[.24,.48,.7,.8,1]),n[n.length-1]<=1&&(n=n.map(c=>Math.floor(t*c)));let o;if(!r){a.push("Receives inputs"),o=[];for(let c in e.nodesByDepth)o.push(...e.nodesByDepth[c])}s("_".repeat(t)),Tm(a,n,s),s("=".repeat(t));let i=e.layers;for(let c=0;c<i.length;++c)r?$U(i[c],n,s):PU(i[c],n,o,s),s((c===i.length-1?"=":"_").repeat(t));e.checkTrainableWeightsConsistency();let l=_U(e),u=bm(e.nonTrainableWeights);s(`Total params: ${l+u}`),s(`Trainable params: ${l}`),s(`Non-trainable params: ${u}`),s("_".repeat(t))}function _U(e){let t;return e.collectedTrainableWeights!=null?t=bm(e.collectedTrainableWeights):t=bm(e.trainableWeights),t}function DU(e){let t=!0,n=[],s=[];for(let r in e.nodesByDepth)n.push(e.nodesByDepth[r]);for(let r of n){if(r.length>1||r.length===1&&r[0].inboundLayers.length>1){t=!1;break}s.push(...r)}if(t)for(let r of e.layers){let a=!1;for(let o of r.inboundNodes)if(s.indexOf(o)!==-1)if(a){t=!1;break}else a=!0;if(!t)break}return t}function Tm(e,t,n=console.log){let s="";for(let r=0;r<e.length;++r)r>0&&(s=s.slice(0,s.length-1)+" "),s+=e[r],s=s.slice(0,t[r]),s+=" ".repeat(t[r]-s.length);n(s)}function $U(e,t,n){let s,r;try{r=e.inboundNodes.map(l=>JSON.stringify(l.inputShapes)).join(",")}catch(l){r="multiple"}try{s=JSON.stringify(e.outputShape)}catch(l){s="multiple"}let a=e.name,o=e.getClassName(),i=[`${a} (${o})`,r,s,e.countParams().toString()];Tm(i,t,n)}function PU(e,t,n,s){let r,a;try{a=e.inboundNodes.map(p=>JSON.stringify(p.inputShapes)).join(",")}catch(p){a="multiple"}try{r=JSON.stringify(e.outputShape)}catch(p){r="multiple"}let o=[];for(let p of e.inboundNodes)if(!(n!=null&&n.length>0&&n.indexOf(p)===-1))for(let d=0;d<p.inboundLayers.length;++d){let h=p.inboundLayers[d].name,f=p.nodeIndices[d],m=p.tensorIndices[d];o.push(`${h}[${f}][${m}]`)}let i=e.name,l=e.getClassName(),u=o.length===0?"":o[0],c=[`${i} (${l})`,a,r,e.countParams().toString(),u];Tm(c,t,s);for(let p=1;p<o.length;++p)Tm(["","","","",o[p]],t,s)}function M8(e,t,n){return(e==="inboundNodes"||e==="outputLayers"||e==="inputLayers")&&t===0&&typeof n=="string"}function Ep(e,t){if(e===null)return null;if(typeof e=="string")return Li(e);if(typeof e=="number"||typeof e=="boolean")return e;if(e instanceof Array){let n=[],s=e.length;for(let r=0;r<s;++r){let a=e[r];M8(t,r,a)?n.push(a):n.push(Ep(a,t))}return n}else{let n={};for(let s of Object.keys(e)){let r=e[s];if(s==="name"&&typeof r=="string")n[s]=r;else{let a=Li(s);n[a]=Ep(r,a)}}return n}}function z3(e,t){if(e==null)return null;if(typeof e=="string")return ua(e);if(typeof e=="number"||typeof e=="boolean")return e;if(e instanceof Array){let n=[],s=e.length;for(let r=0;r<s;++r){let a=e[r];M8(t,r,a)?n.push(a):n.push(z3(a,t))}return n}else{let n={};for(let s of Object.keys(e)){let r=e[s],a=ua(s);(s==="name"||s==="className")&&typeof r=="string"?n[a]=r:n[a]=z3(r,s)}return n}}var f5="3.19.0",Wr=class extends ut{constructor(e){if(super({}),this.containerNodes=new Set,this.name=e.name,this.name==null){let y=this.getClassName().toLowerCase();this.name=J0(y)}if(this.supportsMasking=!1,this.trainable_=!0,Array.isArray(e.inputs)?this.inputs=e.inputs.slice():this.inputs=[e.inputs],Array.isArray(e.outputs)?this.outputs=e.outputs.slice():this.outputs=[e.outputs],Xa(this.inputs).length!==this.inputs.length)throw new j(`The list of inputs passed to the model is redundant. All inputs should only appear once. Found: ${this.inputs.map(y=>y.name)}`);Xa(this.outputs).length!==this.outputs.length&&console.warn(`The list of outputs passed to the model is redundant. All outputs should only appear once. Found: ${this.outputs.map(y=>y.name)}`),this.inputLayers=[],this.inputLayersNodeIndices=[],this.inputLayersTensorIndices=[],this.outputLayers=[],this.outputLayersNodeIndices=[],this.outputLayersTensorIndices=[],this.layers=[],this.internalContainerRefs=[];for(let y of this.outputs){let x=y.sourceLayer,A=y.nodeIndex,b=y.tensorIndex;this.outputLayers.push(x),this.outputLayersNodeIndices.push(A),this.outputLayersTensorIndices.push(b)}for(let y of this.inputs){let x=y.sourceLayer,A=y.nodeIndex,b=y.tensorIndex;Vr(A===0,"input layer has >1 nodes"),Vr(b===0,"input layer has >1 tensors"),this.inputLayers.push(x),this.inputLayersNodeIndices.push(A),this.inputLayersTensorIndices.push(b)}this.inputNames=[],this.outputNames=[],this.feedInputShapes=[],this.feedInputNames=[],this.feedOutputNames=[];for(let y=0;y<this.inputLayers.length;y++){let x=this.inputLayers[y];if(!(x instanceof Yc))throw new TypeError(`Input layers to a LayersModel must be InputLayer objects. Received inputs: ${e.inputs}. Input ${y} (0-based) originates from layer type ${x.getClassName()}.`);this.inputNames.push(x.name),this.feedInputShapes.push(x.batchInputShape),this.feedInputNames.push(x.name)}for(let y of this.outputLayers)this.outputNames.push(y.name);this.internalInputShapes=this.inputs.map(y=>y.shape),this.internalOutputShapes=this.outputs.map(y=>y.shape);let t={},n={},s={},r={},a={},o=[],i=(y,x,A,b,w,k)=>{(b==null||w==null||k==null)&&(b=y.sourceLayer,w=y.nodeIndex,k=y.tensorIndex);let S=b.inboundNodes[w];if(A.indexOf(S)!==-1)throw new Sr(`The tensor ${y.name} at layer "${b.name}" is part of a cycle.`);if(x.indexOf(S)!==-1)return;this.containerNodes.add(Wr.nodeKey(b,w)),b.id in a||(a[b.id]=Object.keys(a).length),A.indexOf(S)===-1&&A.push(S);let E=S.inboundLayers.length;for(let R=0;R<E;R++){let P=S.inputTensors[R],_=S.inboundLayers[R],$=S.nodeIndices[R],T=S.tensorIndices[R];i(P,x,A,_,$,T)}for(x.push(S);A.indexOf(S)>=0;)A.splice(A.indexOf(S),1);o.push(S)},l=[],u=[];for(let y of this.outputs)i(y,l,u);let c=o.slice().reverse();for(let y of c){n[y.id]=y,y.id in t||(t[y.id]=0);let x=t[y.id],A=s[y.outboundLayer.id]==null?0:s[y.outboundLayer.id];x=Math.max(x,A),s[y.outboundLayer.id]=x,r[y.outboundLayer.id]=y.outboundLayer,t[y.id]=x;for(let b=0;b<y.inboundLayers.length;b++){let w=y.inboundLayers[b],k=y.nodeIndices[b],S=w.inboundNodes[k],E=t[S.id]==null?0:t[S.id];t[S.id]=Math.max(x+1,E),n[S.id]=S}}let p={};for(let y in t){let x=t[y];x in p||(p[x]=[]),p[x].push(n[y])}let d={};for(let y in s){let x=s[y];x in d||(d[x]=[]),d[x].push(r[y])}let h=Object.keys(d).map(y=>parseInt(y,10)).sort(Wf);this.layers=[];for(let y of h){let x=d[y];x.sort((A,b)=>{let w=a[A.id],k=a[b.id];return w<k?-1:w>k?1:0});for(let A of x)A instanceof Wr&&this.internalContainerRefs.push(A),this.layers.push(A)}this.layersByDepth=d,h=Object.keys(p).map(y=>parseInt(y,10)).sort(Wf);let f=this.inputs.slice(),m=[];for(let y of h)for(let x of p[y]){let A=x.outboundLayer;if(A!=null){for(let b of x.inputTensors)if(f.indexOf(b)===-1)throw new Sr(`Graph disconnected: cannot obtain value for tensor ${b} at layer "${A.name}". The following previous layers were accessed without issue: ${m}`);for(let b of x.outputTensors)f.push(b);m.push(A.name)}}this.nodesByDepth=p;let g=this.layers.map(y=>y.name);for(let y of g){let x=g.filter(A=>A===y).length;if(x!==1)throw new Sr(`The name "${y}" is used ${x} times in the model. All layer names should be unique. Layer names: `+JSON.stringify(g))}this.outboundNodes=[],this.inboundNodes=[],new l2({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:this.inputs.map(y=>null),outputMasks:this.outputs.map(y=>null),inputShapes:this.inputs.map(y=>y.shape),outputShapes:this.outputs.map(y=>y.shape)}),this.built=!0,this._refCount=1}assertNotDisposed(){if(this._refCount===0)throw new Error(`Container '${this.name}' is already disposed.`)}dispose(){this.assertNotDisposed();let e={refCountAfterDispose:null,numDisposedVariables:0};if(--this._refCount===0){for(let t of this.layers)e.numDisposedVariables+=t.dispose().numDisposedVariables;for(let t of this.internalContainerRefs)e.numDisposedVariables+=t.dispose().numDisposedVariables}return e.refCountAfterDispose=this._refCount,e}get trainable(){return this.trainable_}set trainable(e){this.layers.forEach(t=>{t._trainableWeights.forEach(n=>n.trainable=e)}),this.trainable_=e}get trainableWeights(){if(this._trainableWeights.length>0)throw new j("Container instance unexpectedly contains _trainableWeights.The trainable weights of a Container are a union of the trainable weights of its consituent Layers. Its own _trainableWeights must remain an empty Array.");if(!this.trainable)return[];let e=[];for(let t of this.layers)e=e.concat(t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.layers)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.layers)t.push(...n.trainableWeights);return t.concat(e)}return e}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}loadWeights(e,t=!0){let n={},s=0;for(let a of this.layers)for(let o of a.weights){if(n[o.originalName]!=null)throw new j(`Duplicate weight name: ${o.originalName}`);n[o.originalName]=o,s++}let r=[];for(let a in e){let o=a;if(n[a]==null){let i=a.split("/");o=i.slice(0,-2).concat([i[i.length-1]]).join("/")}if(n[o]!=null)r.push([n[o],e[a]]);else if(t)throw new j(`Provided weight data has no target variable: ${a}`);delete n[o]}if(t){let a=[];for(let o in n)a.push(o);if(a.length>0)throw new j(`${a.length} of ${s} weights are not set: ${a}`)}r5(r)}updatedConfig(){let e=this.getConfig(),t={};return t.className=this.getClassName(),t.config=e,t.kerasVersion=`tfjs-layers ${f5}`,t.backend="TensorFlow.js",t}toJSON(e,t=!0){let n=z3(this.updatedConfig());return t?JSON.stringify(n):n}call(e,t){return J(()=>{e=_t(e);let n=new Vi;for(let s=0;s<this.inputs.length;++s)n.add(this.inputs[s],e[s]);return ap(this.outputs,n,t)})}computeMask(e,t){return J(()=>{e=_t(e);let n;return t==null?n=el(null,e.length):n=_t(t),this.runInternalGraph(e,n)[1]})}computeOutputShape(e){let t=xm(e);if(t.length!==this.inputLayers.length)throw new j(`Invalid inputShape argument ${e}: model has ${this.inputLayers.length} tensor inputs.`);let n={};for(let o=0;o<t.length;o++){let i=this.inputLayers[o],l=t[o],u=i.name+"_0_0";n[u]=l}let s=Object.keys(this.nodesByDepth).map(o=>parseInt(o,10)).sort(Wf);if(s.length>1)for(let o of s){let i=this.nodesByDepth[o];for(let l of i){let u=l.outboundLayer;if(this.inputLayers.map(f=>f.id).indexOf(u.id)!==-1)continue;let c=[];for(let f=0;f<l.inboundLayers.length;f++){let m=l.inboundLayers[f],g=l.nodeIndices[f],y=l.tensorIndices[f],x=`${m.name}_${g}_${y}`,A=n[x];c.push(A)}let p=u.computeOutputShape(ps(c)),d=xm(p),h=u.inboundNodes.indexOf(l);for(let f=0;f<d.length;f++){let m=`${u.name}_${h}_${f}`;n[m]=d[f]}}}let r=[],a=[];for(let o=0;o<this.outputLayers.length;o++){let i=this.outputLayers[o],l=this.outputLayersNodeIndices[o],u=this.outputLayersTensorIndices[o],c=`${i.name}_${l}_${u}`;a.push(c)}for(let o=0;o<a.length;o++){let i=a[o];Vr(i in n),r.push(n[i])}return ps(r)}runInternalGraph(e,t){t==null&&(t=el(null,e.length));let n={};for(let i=0;i<this.inputs.length;++i){let l=this.inputs[i],u=e[i],c=t[i];n[l.id]=[u,c]}let s=Object.keys(this.nodesByDepth).map(i=>parseInt(i,10)).sort(Wf);for(let i of s){let l=this.nodesByDepth[i];for(let u of l){let c=u.outboundLayer,p=u.inputTensors,d=u.outputTensors,h=new Array;for(let f of p)f.id in n&&h.push(n[f.id]);if(h.length===p.length){let f={},m,g,y,x;if(u.callArgs!=null&&(f=u.callArgs),h.length===1){let[A,b]=h[0];f.mask==null&&(f.mask=b),y=_t(c.call(A,f)),x=_t(c.computeMask(A,b)),m=[A],g=[b]}else m=h.map(A=>A[0]),g=h.map(A=>A[1]),f.mask==null&&(f.mask=g),y=_t(c.call(m,f)),x=_t(c.computeMask(m,g));if(c.activityRegularizer)throw new He("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let A=0;A<d.length;++A){let b=d[A],w=y[A],k=x[A];n[b.id]=[w,k]}}}}let r=[],a=[],o=[];for(let i of this.outputs){Vr(i.id in n,`Could not compute output ${i.name} : ${i.id}`);let[l,u]=n[i.id];o.push(l.shape),r.push(l),a.push(u)}return[r,a,o]}buildNodeConversionMap(e){let t={},n;for(let s of this.layers){n=s instanceof Wr?1:0;for(let r=0;r<s.inboundNodes.length;r++){let a=Wr.nodeKey(s,r);this.containerNodes.has(a)&&(t[a]=n,n+=1)}}return t}getLayer(e,t){if(t!=null){if(this.layers.length<=t)throw new j(`Was asked to retrieve layer at index ${t}, but model only has ${this.layers.length} layer(s).`);return this.layers[t]}else if(e==null)throw new j("Provide either a layer name or layer index");for(let n of this.layers)if(n.name===e)return n;throw new j(`No such layer: ${e}`)}calculateLosses(){return J(()=>{let e=[];for(let t of this.layers)for(let n=0;n<t.inboundNodes.length;++n){let s=Wr.nodeKey(t,n);this.containerNodes.has(s)&&e.push(...t.calculateLosses())}return e})}getConfig(){let e={name:this.name},t=this.buildNodeConversionMap(this.layers),n=[];for(let a of this.layers){let o=a.getClassName(),i=a.getConfig(),l=[];for(let c=0;c<a.inboundNodes.length;c++){let p=a.inboundNodes[c],d=Wr.nodeKey(a,c),h={};if(this.containerNodes.has(d)){if(p.callArgs)try{JSON.stringify(p.callArgs),h=p.callArgs}catch(f){console.warn(`Layer ${a.name} was passed non-serializable keyword arguments: ${p.callArgs}. They will not be included in the serialized model (and thus will be missing at deserialization time).`),h={}}if(p.inboundLayers.length>0){let f=[];for(let m=0;m<p.inboundLayers.length;m++){let g=p.inboundLayers[m],y=p.nodeIndices[m],x=p.tensorIndices[m],A=Wr.nodeKey(g,y),b=t[A];b==null&&(b=0),f.push([g.name,b,x,h])}l.push(f)}}}let u={};u.name=a.name,u.className=o,u.config=i,u.inboundNodes=l,n.push(u)}e.layers=n;let s=[];for(let a=0;a<this.inputLayers.length;a++){let o=this.inputLayers[a],i=this.inputLayersNodeIndices[a],l=Wr.nodeKey(o,i);if(!this.containerNodes.has(l))continue;let u=t[l];u==null&&(u=0);let c=this.inputLayersTensorIndices[a];s.push([o.name,u,c])}e.inputLayers=s;let r=[];for(let a=0;a<this.outputLayers.length;a++){let o=this.outputLayers[a],i=this.outputLayersNodeIndices[a],l=Wr.nodeKey(o,i);if(!this.containerNodes.has(l))continue;let u=t[l];u==null&&(u=0);let c=this.outputLayersTensorIndices[a];r.push([o.name,u,c])}return e.outputLayers=r,e}static fromConfig(e,t,n={},s=!1){let r={},a={};function o(m,g){m.name in a?a[m.name].push(g):a[m.name]=[g]}function i(m,g){let y=[],x;for(let A of g){let b=A[0],w=A[1],k=A[2];if(x=A[3]==null?{}:A[3],!(b in r)){o(m,g);return}let S=r[b];if(S.inboundNodes.length<=w){o(m,g);return}let E=S.inboundNodes[w];y.push(E.outputTensors[k])}y.length>0&&m.apply(ps(y),x)}function l(m){let g=m.name,y=Nr(m,t.customObjects!=null?t.customObjects:{});y.setFastWeightInitDuringBuild(s),r[g]=y,m.inboundNodes.forEach(A=>{if(!(A instanceof Array))throw new j(`Corrupted configuration, expected array for nodeData: ${A}`);o(y,A)})}let u=t.name,c=t.layers;for(let m of c)l(m);for(;!uV(a);)for(let m of c){let g=r[m.name];if(g.name in a){let y=a[g.name];delete a[g.name];for(let x of y)i(g,x)}}let p=[],d=[],h=t.inputLayers;for(let m of h){let g=m[0],y=m[1],x=m[2];Vr(g in r);let b=r[g].inboundNodes[y].outputTensors;p.push(b[x])}let f=t.outputLayers;for(let m of f){let g=m[0],y=m[1],x=m[2];Vr(g in r);let b=r[g].inboundNodes[y].outputTensors;d.push(b[x])}return new e({inputs:p,outputs:d,name:u})}get stateful(){if(this._stateful)throw new j("Container instance unexpectedly has _stateful = true. The statefulness of a Container is determined by the Layers it contains. Its _stateful property must remain the default false.");for(let e of this.layers)if(e.stateful)return!0;return!1}resetStates(){J(()=>{this.layers.forEach(e=>{e.stateful&&e.resetStates()})})}};function FU(e,t,n){let s=t.length;if(e==null||Array.isArray(e)&&e.length===0)return t.map(r=>null);if(s===1)return Array.isArray(e)&&e.length===1?e:typeof e=="object"&&t[0]in e?[e[t[0]]]:[e];if(Array.isArray(e)){if(e.length!==s)throw new Error(`Provided ${n} is an array of ${e.length} element(s), but the model has ${s} outputs. Make sure a set of weights is provided for each model output.`);return e}else if(typeof e=="object"&&Object.keys(e).length>0&&typeof e[Object.keys(e)[0]]=="object"){let r=[];return t.forEach(a=>{a in e?r.push(e[a]):r.push(null)}),r}else throw new Error(`The model has multiple (${s}) outputs, so ${n} must be either an array with ${s} elements or an object with ${t} keys. Provided ${n} not understood: ${JSON.stringify(e)}`)}function z8(e,t){return FU(e,t,"classWeight")}async function L8(e,t,n,s){if(t!=null||s!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let r=J(()=>{if(e.shape.length===1)return Fn(e);if(e.shape.length===2){if(e.shape[1]>1)return Es(e,1);if(e.shape[1]===1)return U(e,[e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${e.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${e.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),a=Array.from(await r.data());ne(r);let o=[];return a.forEach(i=>{if(n[i]==null)throw new Error(`classWeight must contain all classes in the training data. The class ${i} exists in the data but not in classWeight`);o.push(n[i])}),Ft(o,"float32")}else return null}function OU(e,t){return L(e,t)}var MU=32;function B8(e,t){let n,s,r=t;n=r.xs,s=r.ys,v.assert(n!=null&&s!=null,()=>`A Dataset iterator for fitDataset() is expected to generate objects of the form \`{xs: xVal, ys: yVal}\`, where the two values may be \`tf.Tensor\`, an array of Tensors, or a map of string to Tensor.  The provided Dataset instead generates ${t}`);let a=Uv("input",e.inputNames,n),o=Uv("output",e.outputNames,s),i=a[0].shape[0];v.assert(a.length===e.inputs.length,()=>`LayersModel has ${e.inputs.length} inputs, but the dataset provides ${a.length} inputs.  (Expected input keys: ${JSON.stringify(e.inputNames)})`),v.assert(o.length===e.outputs.length,()=>`LayersModel has ${e.outputs.length} outputs, but the dataset provides ${o.length} outputs.  (Expected output keys: ${JSON.stringify(e.outputNames)})`);for(let l=0;l<a.length;l++)v.assert(a[l].shape[0]===i,()=>`Batch size mismatch: input ${e.inputNames[l]} has ${a[l].shape[0]}; expected  ${i} based on input ${e.inputNames[0]}.`);for(let l=0;l<o.length;l++)v.assert(o[l].shape[0]===i,()=>`Batch size mismatch: output ${e.outputNames[l]} has ${o[l].shape[0]}; expected  ${i} based on input ${e.inputNames[0]}.`);return{xs:a,ys:o}}function Uv(e,t,n){if(n instanceof tt)return[n];if(Array.isArray(n))return v.assert(n.length===t.length,()=>`Received an array of ${n.length} Tensors, but expected ${t.length} to match the ${e} keys ${t}.`),n;{let s=[];for(let r of t){if(n[r]==null)throw new j(`The feature data generated by the dataset lacks the required ${e} key '${r}'.`);s.push(n[r])}return s}}function zU(e){if(e.length===3)throw new He("Validation with sample weights is not implemented yet.");return{xs:e[0],ys:e[1]}}async function LU(e,t,n){let s=n.batchesPerEpoch!=null;if(v.assert(e.optimizer!=null,()=>"You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig)."),v.assert(n!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),v.assert(n.epochs!=null&&n.epochs>0&&Number.isInteger(n.epochs),()=>`For fitDataset(), config.epochs is expected to be a positive integer, but got ${n.epochs}`),v.assert(!s||n.batchesPerEpoch>0&&Number.isInteger(n.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${n.batchesPerEpoch}`),v.assert(n.validationSplit==null,()=>"`validationSplit` is not supported by `fitDataset()`. Use validationData instead."),e.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");e.isTraining=!0;try{let r=n.validationData!=null,a,o;if(r)if(Gv(n.validationData))v.assert(n.validationBatches==null||n.validationBatches>0&&Number.isInteger(n.validationBatches),()=>`For fitDataset() with dataset-based validation, config.validationBatches is expected not to be provided, or to be a positive integer, but got ${n.validationBatches}`);else{let g=zU(n.validationData);a=g.xs,o=g.ys}let i=e.makeTrainFunction(),l=e.getDedupedMetricsNames(),u;r?u=l.slice().concat(l.map(g=>"val_"+g)):u=l.slice();let c=R8(n.callbacks,n.yieldEvery),p=n.verbose==null?1:n.verbose,{callbackList:d,history:h}=_8(c,p,n.epochs,null,null,BU(t,n),null,r,u);d.setModel(e),e.history=h,await d.onTrainBegin(),e.stopTraining_=!1;let f=n.initialEpoch==null?0:n.initialEpoch,m=await t.iterator();for(;f<n.epochs;){let g={};await d.onEpochBegin(f);let y=0,x=0;for(s||(m=await t.iterator());!s||y<n.batchesPerEpoch;){let A=await m.next();if(s&&A.done){console.warn(`You provided \`batchesPerEpoch\` as ${n.batchesPerEpoch}, but your dataset iterator ran out of data after ${y} batches; interrupting training. Make sure that your dataset can generate at least \`batchesPerEpoch * epochs\` batches (in this case, ${n.batchesPerEpoch*n.epochs} batches). You may need to use the repeat() function when building your dataset.`);break}if(A.value!=null){let{xs:b,ys:w}=B8(e,A.value),k={};k.batch=x,k.size=b[0].shape[0],await d.onBatchBegin(x,k);let S=[];if(n.classWeight!=null){let P=z8(n.classWeight,e.outputNames);for(let _=0;_<P.length;++_)S.push(await L8(w[_],null,P[_]))}let E=b.concat(w).concat(S),R=i(E);ne(E);for(let P=0;P<l.length;++P){let _=l[P],$=R[P];k[_]=$,bn($)}await d.onBatchEnd(x,k),C8(k),x++,y++}if(s?y>=n.batchesPerEpoch:A.done){if(r){let b;Gv(n.validationData)?b=_t(await e.evaluateDataset(n.validationData,{batches:n.validationBatches})):b=_t(e.evaluate(a,o,{batchSize:n.validationBatchSize==null?MU:n.validationBatchSize,verbose:0}));for(let w=0;w<e.metricsNames.length;++w)g[`val_${e.metricsNames[w]}`]=b[w]}break}if(e.stopTraining_)break}if(await d.onEpochEnd(f,g),f++,e.stopTraining_)break}return await d.onTrainEnd(),await e.history.syncData(),e.history}finally{e.isTraining=!1}}function BU(e,t){let n=null;return t.batchesPerEpoch!=null?n=t.batchesPerEpoch:Number.isFinite(e.size)&&(n=e.size),n}function Gv(e){return typeof e.iterator=="function"}function WU(e){return typeof e.next=="function"}async function VU(e,t,n){n=n||{};let s=n.batches!=null,r=e.testFunction,a=[];if(n.verbose>0)throw new He("Verbose mode is not implemented yet.");v.assert(!s||n.batches>0&&Number.isInteger(n.batches),()=>`Test loop expects \`batches\` to be a positive integer, but received ${JSON.stringify(n.batches)}`);let o=WU(t)?t:await t.iterator(),i=0,l=0;for(;!s||l<n.batches;){let u=await o.next();if(a=J(()=>{if(u.value){let{xs:c,ys:p}=B8(e,u.value),d=c.concat(p),h=J(()=>r(d));if(ne(d),l===0)for(let m=0;m<h.length;++m)a.push(Se(0));let f=d[0].shape[0];for(let m=0;m<h.length;++m){let g=h[m],y=a[m];a[m]=J(()=>ce(a[m],L(f,g))),l>0&&ne(y)}ne(h),i+=f,++l}return a}),u.done){s&&console.warn(`Your dataset iterator ran out of data during evaluateDataset(). Interrupting evalution. Make sure that your dataset can generate at least \`batches\` batches (in this case, ${n.batches} batches). You may need to use the repeat() function when building your dataset.`);break}}for(let u=0;u<a.length;++u){let c=a[u];a[u]=pe(a[u],i),ne(c)}return ps(a)}function L3(e){v.assert(e>0&&Number.isInteger(e),()=>`batchSize is required to be a positive integer, but got ${e}`)}function op(e,t,n){return e==null?[null]:Array.isArray(e)?e.map(s=>ji(s,t,n-t)):ji(e,t,n-t)}function m5(e,t){return J(()=>e==null?null:Array.isArray(e)?e.map(n=>m5(n,t)):A8(e,t.dtype==="int32"?t:ge(t,"int32")))}function B3(e,t){let n=[],s=0,r=null;for(;s<e;)r=s+t,r>=e&&(r=e),n.push([s,r]),s=r;return n}async function UU(e,t,n,s,r,a,o,i,l,u,c,p,d,h,f){r==null&&(r=32),a==null&&(a=1),c==null&&(c=!0),d==null&&(d=0);let m=!1;if(l!=null&&u!=null&&(m=!0),f!=null&&(m=!0,h==null))throw new j("Can only use `validationSteps` when doing step-wise training, i.e., `stepsPerEpoch` must be set.");let g=e.checkNumSamples(n,r,h,"steps_per_epoch"),y;g!=null&&(y=Rr(0,g)),o==null&&(o=1);let{callbackList:x,history:A}=_8(i,o,a,d,g,h,r,m,p);x.setModel(e),e.history=A,await x.onTrainBegin(),e.stopTraining_=!1;for(let b=d;b<a;++b){await x.onEpochBegin(b);let w={};if(h!=null)throw new He("stepsPerEpoch mode is not implemented yet.");{if(c==="batch")throw new He("batch shuffling is not implemneted yet");c&&v.shuffle(y);let k=Ft(y),S=B3(g,r);for(let E=0;E<S.length;++E){let R={};if(await x.onBatchBegin(E,R),J(()=>{let P=S[E][0],_=S[E][1],$=ji(k,P,_-P);R.batch=E,R.size=_-P;let T=m5(n,$),F=t(T);for(let G=0;G<s.length;++G){let q=s[G],z=F[G];R[q]=z,bn(z)}if(E===S.length-1&&m){let G=e.testLoop(l,u,r);for(let q=0;q<s.length;++q){let z=s[q],K=G[q];bn(K),w["val_"+z]=K}}}),await x.onBatchEnd(E,R),C8(R),e.stopTraining_)break}k.dispose()}if(await x.onEpochEnd(b,w),e.stopTraining_)break}return await x.onTrainEnd(),await e.history.syncData(),e.history}async function GU(e,t,n,s={}){if(e.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");e.isTraining=!0;let r,a,o,i,l,u,c,p,d;try{let h=s.batchSize==null?32:s.batchSize;L3(h);let f=!1,m=await e.standardizeUserData(t,n,s.sampleWeight,s.classWeight,f,h);r=m[0],a=m[1],d=m[2];let g=!1,y;if(s.validationData!=null&&s.validationData.length>0){if(g=!0,s.validationData.length===2)l=s.validationData[0],u=s.validationData[1];else throw s.validationData.length===3?new He("validationData including sample weights is not supported yet."):new j(`When passing validation data, it must contain 2 (valX, valY) or 3 (valX, valY, valSampleWeight) items; ${s.validationData} is invalid.`);let R=!0,P=await e.standardizeUserData(l,u,null,null,R,h);c=P[0],p=P[1],y=c.concat(p)}else if(s.validationSplit!=null&&s.validationSplit>0&&s.validationSplit<1){g=!0;let R=Math.floor(r[0].shape[0]*(1-s.validationSplit)),P=r[0].shape[0];c=op(r,R,P),o=r,r=op(r,0,R),p=op(a,R,P),i=a,a=op(a,0,R),y=c.concat(p)}else s.validationSteps!=null&&(g=!0);let x=r.concat(a).concat(d);e.checkTrainableWeightsConsistency();let A=e.makeTrainFunction(),b=e.getDedupedMetricsNames(),w,k;g?(e.makeTestFunction(),w=e.testFunction,k=b.slice().concat(b.map(R=>"val_"+R))):(w=null,y=[],k=b.slice());let S=R8(s.callbacks,s.yieldEvery);return await UU(e,A,x,b,h,s.epochs,s.verbose,S,w,y,s.shuffle,k,s.initialEpoch,null,null)}finally{e.isTraining=!1,Ir(r,t),Ir(a,n),Ir(o,t),Ir(i,n),Ir(c,l),Ir(p,u),d!=null&&ne(d)}}function W8(e){let t=[];e instanceof tt&&(e=[e]);for(let n=0;n<e.length;++n){let s=e[n];if(s.rank===1)t.push(kh(s,1));else{if(s.rank===0)throw new Error("Expected tensor to be at least 1D, but received a 0D tensor (scalar).");t.push(s)}}return t}function Ir(e,t){if(e==null)return;let n=[];if(t instanceof tt)n.push(t.id);else if(Array.isArray(t))t.forEach(r=>n.push(r.id));else if(t!=null)for(let r in t){let a=t[r];n.push(a.id)}let s=[];if(e instanceof tt)n.indexOf(e.id)===-1&&s.push(e);else if(Array.isArray(e))e.forEach(r=>{n.indexOf(r.id)===-1&&s.push(r)});else if(e!=null)for(let r in e){let a=e[r];n.indexOf(a.id)===-1&&s.push(a)}s.forEach(r=>{r.isDisposed||r.dispose()})}function HU(e){return e instanceof tt}function W3(e){return Array.isArray(e)}function Hv(e){return!HU(e)&&!W3(e)}function jv(e,t,n,s=!0,r=""){if(t==null||t.length===0){if(e!=null){let o=!1;if(W3(e)&&e.length>0)o=!0;else if(Hv(e)){for(let i in e)if(e.hasOwnProperty(i)){o=!0;break}}else o=!0;if(o)throw new j(`Error when checking model ${r} expected no data, but got ${e}`)}return[]}if(e==null)return t.map(o=>null);let a;if(Hv(e)){e=e,a=[];for(let o of t){if(e[o]==null)throw new j(`No data provided for "${o}". Need data for each key in: ${t}`);a.push(e[o])}}else if(W3(e)){if(e=e,e.length!==t.length)throw new j(`Error when checking model ${r}: the Array of Tensors that you are passing to your model is not the size the model expected. Expected to see ${t.length} Tensor(s), but instead got the following list of Tensor(s): ${e}`);a=e}else{if(e=e,t.length>1)throw new j(`The model ${r} expects ${t.length} Tensor(s), but only received one Tensor. Found: Tensor with shape ${e.shape}`);a=[e]}if(a=W8(a),n!=null)for(let o=0;o<t.length;++o){if(n[o]==null)continue;let i=a[o];if(i.shape.length!==n[o].length)throw new j(`Error when checking ${r}: expected ${t[o]} to have ${n[o].length} dimension(s). but got array with shape ${i.shape}`);for(let l=0;l<n[o].length;++l){if(l===0&&!s)continue;let u=i.shape[l],c=n[o][l];if(c!=null&&c>=0&&u!==c)throw new j(`${r} expected a batch of elements where each example has shape [${n[o].slice(1,n[o].length)}] (i.e.,tensor shape [*,${n[o].slice(1,n[o].length)}]) but the ${r} received an input with ${i.shape[0]} examples, each with shape [${i.shape.slice(1,i.shape.length)}] (tensor shape [${i.shape}])`)}}return a}function jU(e,t,n){let s=Xa(e.map(a=>a.shape[0]));s.sort();let r=Xa(t.map(a=>a.shape[0]));if(r.sort(),s.length>1)throw new j(`All input Tensors (x) should have the same number of samples. Got array shapes: ${JSON.stringify(e.map(a=>a.shape))}`);if(r.length>1)throw new j(`All target Tensors (y) should have the same number of samples. Got array shapes: ${JSON.stringify(t.map(a=>a.shape))}`);if(s.length>0&&r.length>0&&!v.arraysEqual(s,r))throw new j(`Input Tensors should have the same number of samples as target Tensors. Found ${s[0]} input sample(s) and ${r[0]} target sample(s).`)}function qU(e,t,n){let s=[tu,c2,Np];for(let r=0;r<e.length;++r){let a=e[r],o=t[r],i=n[r];if(o!=null){if(o===Np&&a.shape[a.shape.length-1]===1)throw new j(`You are passing a target array of shape ${a.shape} while using a loss 'categorical_crossentropy'. 'categorical_crossentropy'expects targets to be binary matrices (1s and 0s) of shape [samples, classes].`);if(s.indexOf(o)!==-1){let l=a.shape.slice(1),u=i.slice(1);for(let c=0;c<l.length;++c){let p=l[c],d=u[c];if(d!=null&&p!==d)throw new j(`A target Tensor with shape ${a.shape} was passed for an output of shape ${i}, while using a loss function that expects targets to have the same shape as the output.`)}}}}}function qv(e,t,n,s=!0,r=""){let a;if(Array.isArray(e)){if(e.length!==t.length)throw new j(`Error when checking model ${r}: the Array of Tensors that you are passing to your model is not the size the the model expected. Expected to see ${t.length} Tensor(s), but instead got ${e.length} Tensors(s).`);a=e}else{if(t.length>1)throw new j(`The model expects ${t.length} ${r} Tensors, but only received one Tensor. Found: array with shape ${JSON.stringify(e.shape)}.`);a=[e]}if(n!=null)for(let o=0;o<t.length;++o){if(n[o]==null)continue;let i=a[o];if(i.shape.length!==n[o].length)throw new j(`Error when checking ${r}: expected ${t[o]} to have ${n[o].length} dimension(s), but got array with shape ${JSON.stringify(i.shape)}`);for(let l=0;l<n[o].length;++l){if(l===0&&!s)continue;let u=i.shape[l],c=n[o][l];if(c!=null&&c!==u)throw new j(`Error when checking ${r}: expected ${t[o]} to have shape ${JSON.stringify(n[o])} but got array with shape ${JSON.stringify(i.shape)}.`)}}}function XU(e,t){if(e==null||Array.isArray(e)&&e.length===0)return t.map(s=>[]);let n;if(typeof e=="string"||typeof e=="function")n=[e];else if(Array.isArray(e)||typeof e=="object")n=e;else throw new TypeError(`Type of metrics argument not understood. Expected an string,function, Array, or Object, found: ${e}`);if(Array.isArray(n))return t.map(s=>n);{let s=[];for(let r of t){let a=n.hasOwnProperty(r)?n[r]:[];Array.isArray(a)||(a=[a]),s.push(a)}return s}}var KU="layers-model",ha=class extends Wr{constructor(e){super(e),this.isTraining=!1}summary(e,t,n=console.log){if(!this.built)throw new j("This model has never been called, thus its weights have not been created yet. So no summary can be displayed. Build the model first (e.g., by calling it on some test data).");RU(this,e,t,n)}compile(e){if(e.loss==null&&(e.loss=[]),this.loss=e.loss,typeof e.optimizer=="string")this.optimizer_=EU(e.optimizer),this.isOptimizerOwned=!0;else{if(!(e.optimizer instanceof ka))throw new j("User-defined optimizer must be an instance of tf.Optimizer.");this.optimizer_=e.optimizer,this.isOptimizerOwned=!1}let t=[];if(!Array.isArray(e.loss)&&typeof e.loss!="string"&&typeof e.loss!="function"){e.loss=e.loss;for(let a in e.loss)if(this.outputNames.indexOf(a)===-1)throw new j(`Unknown entry in loss dictionary: "${a}". Only expected the following keys: ${this.outputNames}`);for(let a of this.outputNames)e.loss[a]==null&&console.warn(`Output "${a}" is missing from loss dictionary. We assume this was done on purpose, and we will not be expecting data to be passed to ${a} during training`),t.push(c3(e.loss[a]))}else if(Array.isArray(e.loss)){if(e.loss.length!==this.outputs.length)throw new j(`When passing an Array as loss, it should have one entry per model output. The model has ${this.outputs.length} output(s), but you passed loss=${e.loss}.`);t=e.loss.map(o=>c3(o))}else{let a=c3(e.loss);this.outputs.forEach(o=>{t.push(a)})}this.lossFunctions=t,this.feedOutputNames=[],this.feedOutputShapes=[],this.feedLossFns=[];for(let a=0;a<this.outputs.length;++a){let o=this.internalOutputShapes[a],i=this.outputNames[a];this.feedOutputNames.push(i),this.feedOutputShapes.push(o),this.feedLossFns.push(this.lossFunctions[a])}let n=[];this.metrics=e.metrics,this.metricsNames=["loss"],this.metricsTensors=[],Hi("loss",()=>{for(let a=0;a<this.outputs.length;++a){if(n.indexOf(a)!==-1)continue;let o=this.lossFunctions[a];this.outputs.length>1&&(this.metricsTensors.push([o,a]),this.metricsNames.push(this.outputNames[a]+"_loss"))}});let s=XU(e.metrics,this.outputNames),r=(a,o,i)=>{this.outputNames.length>1&&(o=this.outputNames[a]+"_"+o),this.metricsNames.push(o),this.metricsTensors.push([i,a])};Hi("metric",()=>{for(let a=0;a<this.outputs.length;++a){if(n.indexOf(a)!==-1)continue;let o=s[a];(l=>{let u="",c,p,d;for(let h of l){if(typeof h=="string"&&["accuracy","acc","crossentropy","ce"].indexOf(h)!==-1){let m=this.internalOutputShapes[a];m[m.length-1]===1||this.lossFunctions[a]===c2?["accuracy","acc"].indexOf(h)!==-1?p=d5:["crossentropy","ce"].indexOf(h)!==-1&&(p=P8):this.lossFunctions[a]===Im?["accuracy","acc"].indexOf(h)!==-1?p=F8:["crossentropy","ce"].indexOf(h)!==-1&&(p=O8):["accuracy","acc"].indexOf(h)!==-1?p=p5:["crossentropy","ce"].indexOf(h)!==-1&&(p=h5);let g;["accuracy","acc"].indexOf(h)!==-1?g="acc":["crossentropy","ce"].indexOf(h)!==-1&&(g="ce"),d=p,c=u+g}else d=NU(h),c=u+Gf(h);let f;Hi(c,()=>{f=d}),r(a,c,f)}})(o)}}),this.collectedTrainableWeights=this.trainableWeights}checkTrainableWeightsConsistency(){this.collectedTrainableWeights!=null&&this.trainableWeights.length!==this.collectedTrainableWeights.length&&console.warn("Discrepancy between trainableweights and collected trainable weights. Did you set `model.trainable` without calling `model.compile()` afterwards?")}evaluate(e,t,n={}){let s=n.batchSize==null?32:n.batchSize;L3(s);let r=!0,a=this.standardizeUserDataXY(e,t,r,s);try{let o=a[0].concat(a[1]);this.makeTestFunction();let i=this.testFunction,l=this.testLoop(i,o,s,n.verbose,n.steps);return ps(l)}finally{Ir(a[0],e),Ir(a[1],t)}}async evaluateDataset(e,t){return this.makeTestFunction(),VU(this,e,t)}checkNumSamples(e,t,n,s="steps"){let r;if(n!=null){if(r=null,t!=null)throw new j(`If ${s} is set, batchSize must be null or undefined.Got batchSize = ${t}`)}else if(e!=null)Array.isArray(e)?r=e[0].shape[0]:r=e.shape[0];else throw new j(`Either the input data should have a defined shape, or ${s} shoud be specified.`);return r}execute(e,t){if(Array.isArray(t)&&t.length===0)throw new j("`outputs` is an empty Array, which is not allowed.");let n=Array.isArray(t),s=n?t:[t],r=this.retrieveSymbolicTensors(s),a=new Vi;if(e instanceof tt&&(e=[e]),Array.isArray(e)){if(e.length!==this.inputs.length)throw new j(`The number of inputs provided (${e.length}) does not match the number of inputs of this model (${this.inputs.length}).`);for(let i=0;i<this.inputs.length;++i)a.add(this.inputs[i],e[i])}else for(let i of this.inputs){let l=e[i.name];if(l==null)throw new j(`No value is provided for the model's input ${i.name}`);a.add(i,l)}let o=ap(r,a);return n?o:o[0]}retrieveSymbolicTensors(e){let t=el(null,e.length),n=e.length;for(let s of this.layers){let r=Array.isArray(s.output)?s.output:[s.output],a=r.map(o=>o.name);for(let o=0;o<e.length;++o){let i=a.indexOf(e[o]);if(i!==-1&&(t[o]=r[i],n--),n===0)break}if(n===0)break}if(n>0){let s=[];throw t.forEach((r,a)=>{r==null&&s.push(e[a])}),new j(`Cannot find SymbolicTensors for output name(s): ${JSON.stringify(s)}`)}return t}predictLoop(e,t=32,n=!1){return J(()=>{let s=this.checkNumSamples(e);if(n)throw new He("Verbose predictLoop() is not implemented yet.");let r=B3(s,t),a=this.outputs.map(o=>[]);for(let o=0;o<r.length;++o)J(()=>{let l=r[o][0],u=r[o][1],c=op(e,l,u),p=[];if(Array.isArray(c))for(let h=0;h<c.length;++h)p.push({key:this.inputs[h],value:c[h]});else p.push({key:this.inputs[0],value:c});let d=new Vi(p);return ap(this.outputs,d)}).forEach((l,u)=>a[u].push(l));return ps(a.map(o=>Ct(o,0)))})}predict(e,t={}){let n=W8(e);qv(n,this.inputNames,this.feedInputShapes,!1);try{let s=t.batchSize==null?32:t.batchSize;return L3(s),this.predictLoop(n,s)}finally{Ir(n,e)}}predictOnBatch(e){qv(e,this.inputNames,this.feedInputShapes,!0);let t=(Array.isArray(e)?e[0]:e).shape[0];return this.predictLoop(e,t)}standardizeUserDataXY(e,t,n=!0,s){if(this.optimizer_==null)throw new Sr("You must compile a model before training/testing. Use LayersModel.compile(modelCompileArgs).");let r=[];for(let a=0;a<this.feedOutputShapes.length;++a){let o=this.feedOutputShapes[a];this.feedLossFns[a]===Im?r.push(o.slice(0,o.length-1).concat([1])):r.push(o)}if(e=jv(e,this.feedInputNames,this.feedInputShapes,!1,"input"),t=jv(t,this.feedOutputNames,r,!1,"target"),jU(e,t,null),qU(t,this.feedLossFns,this.feedOutputShapes),this.stateful&&s!=null&&s>0&&e[0].shape[0]%s!==0)throw new j(`In a stateful network, you should only pass inputs with a number of samples that is divisible by the batch size ${s}. Found: ${e[0].shape[0]} sample(s).`);return[e,t]}async standardizeUserData(e,t,n,s,r=!0,a){let[o,i]=this.standardizeUserDataXY(e,t,r,a);if(n!=null)throw new Error("sample weight is not supported yet.");let l=null;if(s!=null){let u=z8(s,this.outputNames);l=[];for(let c=0;c<u.length;++c)l.push(await L8(i[c],null,u[c]))}return[o,i,l]}testLoop(e,t,n,s=0,r){return J(()=>{let a=this.checkNumSamples(t,n,r,"steps"),o=[];if(s>0)throw new He("Verbose mode is not implemented yet.");if(r!=null)throw new He("steps mode in testLoop() is not implemented yet");{let i=B3(a,n),l=Ft(Rr(0,a));for(let u=0;u<i.length;++u){let c=i[u][0],p=i[u][1],d=ji(l,c,p-c),h=m5(t,d),f=e(h);if(u===0)for(let m=0;m<f.length;++m)o.push(Se(0));for(let m=0;m<f.length;++m){let g=f[m];o[m]=ce(o[m],L(p-c,g))}}for(let u=0;u<o.length;++u)o[u]=pe(o[u],a)}return o})}getDedupedMetricsNames(){let e=this.metricsNames,t=[];for(let n=0;n<e.length;++n){let s=e[n],r=s;_v(e,s)>1&&(r+=`_${_v(e.slice(0,n),s)}`),t.push(r)}return t}makeTrainFunction(){return e=>{let t=[],n=e.slice(0,this.inputs.length),s=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),r=e.slice(this.inputs.length+this.outputs.length,this.inputs.length+this.outputs.length*2),a=[],o=()=>{let c=[];for(let f=0;f<this.inputs.length;++f)c.push({key:this.inputs[f],value:n[f]});let p=new Vi(c),d=ap(this.outputs,p,{training:!0}),h;for(let f=0;f<this.lossFunctions.length;++f){let m=this.lossFunctions[f],g=m(s[f],d[f]);r[f]!=null&&(g=OU(g,r[f]));let y=Bt(g);t.push(y),f===0?h=g:h=ce(h,g)}for(let f=0;f<this.metricsTensors.length;++f){let m;if(this.outputs.length>1&&f<this.outputs.length)m=t[f];else{let g=this.metricsTensors[f][0],y=this.metricsTensors[f][1];m=Bt(g(s[y],d[y]))}bn(m),a.push(m)}return h=Bt(h),this.calculateLosses().forEach(f=>{h=ce(h,f)}),h},i=this.collectedTrainableWeights.map(c=>c.read()),l=!0;return[this.optimizer_.minimize(o,l,i)].concat(a)}}makeTestFunction(){this.testFunction=e=>J(()=>{let t=[],n,s=e.slice(0,this.inputs.length),r=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),a=[];for(let l=0;l<this.inputs.length;++l)a.push({key:this.inputs[l],value:s[l]});let o=new Vi(a),i=ap(this.outputs,o);for(let l=0;l<this.lossFunctions.length;++l){let u=this.lossFunctions[l],c=Bt(u(r[l],i[l]));l===0?n=c:n=ce(n,c),t.push(n)}for(let l=0;l<this.metricsTensors.length;++l){let u=this.metricsTensors[l][0],c=this.metricsTensors[l][1],p=Bt(u(r[c],i[c]));t.push(p)}return t})}async fit(e,t,n={}){return GU(this,e,t,n)}async fitDataset(e,t){return LU(this,e,t)}async trainOnBatch(e,t){let n=await this.standardizeUserData(e,t),s=n[0],r=n[1],o=this.makeTrainFunction()(s.concat(r)),i=[];for(let l of o){let u=await l.data();i.push(u[0])}return ne(o),Ir(n[0],e),Ir(n[1],t),ps(i)}getNamedWeights(e){let t=[],n=e!=null&&e.trainableOnly,s=n?this.trainableWeights:this.weights,r=this.getWeights(n);for(let a=0;a<s.length;++a)n&&!s[a].trainable||t.push({name:s[a].originalName,tensor:r[a]});return t}set stopTraining(e){this.stopTraining_=e}get stopTraining(){return this.stopTraining_}get optimizer(){return this.optimizer_}set optimizer(e){this.optimizer_!==e&&(this.optimizer_=e,this.isOptimizerOwned=!1)}dispose(){let e=super.dispose();if(e.refCountAfterDispose===0&&this.optimizer!=null&&this.isOptimizerOwned){let t=ym().numTensors;this.optimizer_.dispose(),e.numDisposedVariables+=t-ym().numTensors}return e}getLossIdentifiers(){let e;if(typeof this.loss=="string")e=ua(this.loss);else if(Array.isArray(this.loss)){for(let t of this.loss)if(typeof t!="string")throw new Error("Serialization of non-string loss is not supported.");e=this.loss.map(t=>ua(t))}else{let t=Object.keys(this.loss);e={};let n=this.loss;for(let s of t)if(typeof n[s]=="string")e[s]=ua(n[s]);else throw new Error("Serialization of non-string loss is not supported.")}return e}getMetricIdentifiers(){if(typeof this.metrics=="string"||typeof this.metrics=="function")return[ua(Gf(this.metrics))];if(Array.isArray(this.metrics))return this.metrics.map(e=>ua(Gf(e)));{let e={};for(let t in this.metrics)e[t]=ua(Gf(this.metrics[t]));return e}}getTrainingConfig(){return{loss:this.getLossIdentifiers(),metrics:this.getMetricIdentifiers(),optimizer_config:{class_name:this.optimizer.getClassName(),config:this.optimizer.getConfig()}}}loadTrainingConfig(e){if(e.weighted_metrics!=null)throw new Error("Loading weight_metrics is not supported yet.");if(e.loss_weights!=null)throw new Error("Loading loss_weights is not supported yet.");if(e.sample_weight_mode!=null)throw new Error("Loading sample_weight_mode is not supported yet.");let t=Ep(e.optimizer_config),n=Nr(t),s;if(typeof e.loss=="string")s=Li(e.loss);else if(Array.isArray(e.loss))s=e.loss.map(a=>Li(a));else if(e.loss!=null){s={};for(let a in e.loss)s[a]=Li(e.loss[a])}let r;if(Array.isArray(e.metrics))r=e.metrics.map(a=>Li(a));else if(e.metrics!=null){r={};for(let a in e.metrics)r[a]=Li(e.metrics[a])}this.compile({loss:s,metrics:r,optimizer:n})}async save(e,t){if(typeof e=="string"){let l=Ts.getSaveHandlers(e);if(l.length===0)throw new j(`Cannot find any save handlers for URL '${e}'`);if(l.length>1)throw new j(`Found more than one (${l.length}) save handlers for URL '${e}'`);e=l[0]}if(e.save==null)throw new j("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let n=await Ts.encodeWeights(this.getNamedWeights(t)),s=!1,r=null,o={modelTopology:this.toJSON(r,s),format:KU,generatedBy:`TensorFlow.js tfjs-layers v${f5}`,convertedBy:null};if((t==null?!1:t.includeOptimizer)&&this.optimizer!=null){o.trainingConfig=this.getTrainingConfig();let l="optimizer",{data:u,specs:c}=await Ts.encodeWeights(await this.optimizer.getWeights(),l);n.specs.push(...c),n.data=Ts.concatenateArrayBuffers([n.data,u])}return this.userDefinedMetadata!=null&&(Vv(this.userDefinedMetadata,this.name,!0),o.userDefinedMetadata=this.userDefinedMetadata),o.weightData=n.data,o.weightSpecs=n.specs,e.save(o)}setUserDefinedMetadata(e){Vv(e,this.name),this.userDefinedMetadata=e}getUserDefinedMetadata(){return this.userDefinedMetadata}};ha.className="Model";de.registerClass(ha);var V8=class extends ha{};V8.className="Functional";de.registerClass(V8);async function ZU(e,t){"modelTopology"in e||(e={modelTopology:e}),e=e;let n=e.modelTopology;n.model_config!=null&&(n=n.model_config);let s=Ep(n),r=Nr(s,t);if(e.weightsManifest!=null){let a=await Ts.loadWeights(e.weightsManifest,e.pathPrefix,r.weights.map(i=>i.originalName)),o={};for(let i of r.weights)o[i.originalName]=a[i.originalName];r.loadWeights(o),ne(a)}return r}async function YU(e,t){if(t==null&&(t={}),typeof e=="string"){let n=Ts.getLoadHandlers(e,t);if(n.length===0)n.push(Ts.browserHTTPRequest(e,t));else if(n.length>1)throw new j(`Found more than one (${n.length}) load handlers for URL '${e}'`);e=n[0]}return JU(e,void 0,t)}async function JU(e,t,n){if(n==null&&(n={}),e.load==null)throw new j("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let s=await e.load(),r=s.modelTopology;r.model_config!=null&&(r=r.model_config);let a=n.strict==null?!0:n.strict,o=s.weightData!=null&&s.weightSpecs!=null&&a,i=Nr(Ep(r),t,o),l=s.trainingConfig;if(l!=null&&i.loadTrainingConfig(l),s.userDefinedMetadata!=null&&i.setUserDefinedMetadata(s.userDefinedMetadata),s.weightData!=null){if(s.weightSpecs==null)throw new j("LayersModel artifacts contains weight data, but not weight specs. Therefore loading of weights cannot proceed.");let{modelWeights:u,optimizerWeights:c}=QU(s.weightData,s.weightSpecs);i.loadWeights(u,a),i.optimizer!=null&&c.length>0&&await i.optimizer.setWeights(c),ne(u),ne(c.map(p=>p.tensor))}return i}function QU(e,t){let n=Ts.decodeWeights(e,t),s={},r=[];return t.forEach(a=>{a.group==="optimizer"?r.push({name:a.name,tensor:n[a.name]}):s[a.name]=n[a.name]}),{modelWeights:s,optimizerWeights:r}}var sc=class extends ha{constructor(e){if(super({inputs:[],outputs:[]}),e=e||{},this.trainable=!0,this.built=!1,this.name=e.name!=null?e.name:J0("sequential_"),e.layers!=null)for(let t of e.layers)this.add(t)}checkShape(e){if(e.inboundNodes[0].outputTensors[0].shape.some(n=>n<0))throw new j(`Negative dimension size caused by adding layer ${e.name} with input shape [${e.inboundNodes[0].inputTensors[0].shape}]`)}add(e){let t=e instanceof sc||e instanceof ha,n;if(t){if(n=e,n.outputs.length!==1)throw new j("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");if(n.inputs.length!==1)throw new j("All layers in a Sequential model should have a single input tensor. For multi-input layers, use the functional API.")}if(this.outputs.length===0){if(e.inboundNodes.length===0){if(e.batchInputShape==null)throw new j("The first layer in a Sequential model must get an `inputShape` or `batchInputShape` argument.");let s=w8({batchShape:e.batchInputShape,dtype:e.dtype,name:e.name+"_input"});e.apply(s)}if(t)this.outputs=n.outputs,this.inputs=n.inputs;else{if(e.inboundNodes.length!==1)throw new j(`A layer added to a Sequential model must not already be connected somewhere else. LayersModel received layer ${e.name} which has ${e.inboundNodes.length} pre-existing inbound connections.`);if(e.inboundNodes[0].outputTensors.length!==1)throw new j("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");this.checkShape(e),this.outputs=[e.inboundNodes[0].outputTensors[0]],this.inputs=v8(this.outputs[0])}this.inboundNodes=[],new l2({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:el(null,this.inputs.length),outputMasks:[null],inputShapes:this.inputs.map(s=>s.shape),outputShapes:this.outputs[0].shape})}else{let s=e.apply(this.outputs[0]);if(Array.isArray(s))throw new TypeError("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");this.checkShape(e),this.outputs=[s],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}this.layers.push(e),this.built=!1}pop(){if(this.layers.length===0)throw new TypeError("There are no layers in the model.");if(this.layers.pop(),this.layers.length===0)this.outputs=[],this.inboundNodes=[],this.outboundNodes=[];else{let e=this.layers.length-1;this.layers[e].outboundNodes=[],this.outputs=[this.layers[e].output],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}}call(e,t){return this.model==null&&this.build(),this.model.call(e,t)}build(e){if(xt(e),this.inputs.length===0||this.outputs.length===0)throw new TypeError("Sequential model cannot be built: model is empty. Add some layers first.");this.model=new ha({inputs:this.inputs,outputs:this.outputs[0],name:this.name+"_model"}),this.model.trainable=this.trainable,this.supportsMasking=this.model.supportsMasking,this.inputLayers=this.model.inputLayers,this.inputLayersNodeIndices=this.model.inputLayersNodeIndices,this.inputLayersTensorIndices=this.model.inputLayersTensorIndices,this.outputLayers=this.model.outputLayers,this.outputLayersNodeIndices=this.model.outputLayersNodeIndices,this.outputLayersTensorIndices=this.model.outputLayersTensorIndices,this.nodesByDepth=this.model.nodesByDepth,this.containerNodes=this.model.containerNodes,this.outputNames=this.model.outputNames,this.inputNames=this.model.inputNames,this.built=!0}countParams(){return this.built||this.build(),super.countParams()}summary(e,t,n=console.log){this.built||this.build(),super.summary(e,t,n)}setWeights(e){this.model==null&&this.build(),this.model.setWeights(e)}evaluate(e,t,n={}){if(!this.built)throw new Sr("The model needs to be compiled before being used.");return this.model.evaluate(e,t,n)}async evaluateDataset(e,t){if(!this.built)throw new Sr("The model needs to be compiled before being used.");return this.model.evaluateDataset(e,t)}predict(e,t={}){return this.model==null&&this.build(),this.model.predict(e,t)}predictOnBatch(e){return this.model==null&&this.build(),this.model.predictOnBatch(e)}compile(e){this.build(),this.model.compile(e),this.optimizer_=this.model.optimizer,this.isOptimizerOwned=this.model.isOptimizerOwned,this.loss=this.model.loss,this.metrics=this.model.metrics,this.metricsTensors=this.model.metricsTensors,this.metricsNames=this.model.metricsNames}get optimizer(){return this.model==null?void 0:this.model.optimizer}set optimizer(e){this.model.optimizer=e}async fit(e,t,n={}){if(!this.built)throw new Sr("The model needs to be compiled before being used.");return this.model.fit(e,t,n)}async fitDataset(e,t){if(!this.built)throw new Sr("The model needs to be compiled before being used.");return this.model.fitDataset(e,t)}async trainOnBatch(e,t){return this.model.trainOnBatch(e,t)}static fromConfig(e,t,n={},s=!1){let r,a={};if(t instanceof Array){if(t[0].className==null||t[0].className==="Merge")throw new j("Legacy serialization format not supported yet.");r=t}else v.assert(t.layers!=null,()=>"When the config data for a Sequential model is not an Array, it must be an Object that contains the 'layers' field."),r=t.layers,delete t.layers,a=t;let o=new e(a);if(!(o instanceof sc))throw new He(`Sequential.fromConfig called on non-Sequential input: ${o}`);for(let i of r){let u=Nr(i,void 0,s);s&&u.setFastWeightInitDuringBuild(!0),o.add(u)}return o}set stopTraining(e){if(this.model==null)throw new j("Cannot set the stopTraining property of a sequential model before it is compiled.");this.model.stopTraining=e}get stopTraining(){if(this.model==null)throw new j("Cannot get the stopTraining property of a sequential model before it is compiled.");return this.model.stopTraining}getConfig(){let e=[];for(let t of this.layers){let n={};n.className=t.getClassName(),n.config=t.getConfig(),e.push(n)}return{name:this.name,layers:e}}};sc.className="Sequential";de.registerClass(sc);function eG(e){return new ha(e)}function tG(e){return new sc(e)}function nG(e,t){return t==null&&(t={}),YU(e,t)}function U8(e){return w8(e)}function sG(e,t){rr.registerCallbackConstructor(e,t)}var As=class extends de.Serializable{getConfig(){return{}}},G8=class extends As{apply(e,t=1){return IV(e,t)}};G8.className="elu";de.registerClass(G8);var H8=class extends As{apply(e){return D0(e)}};H8.className="selu";de.registerClass(H8);var j8=class extends As{apply(e){return Pr(e)}};j8.className="relu";de.registerClass(j8);var q8=class extends As{apply(e){return J(()=>Xc(6,Pr(e)))}};q8.className="relu6";de.registerClass(q8);var X8=class extends As{apply(e){return e}};X8.className="linear";de.registerClass(X8);var K8=class extends As{apply(e){return Cn(e)}};K8.className="sigmoid";de.registerClass(K8);var Z8=class extends As{apply(e){return CV(e)}};Z8.className="hardSigmoid";de.registerClass(Z8);var Y8=class extends As{apply(e){return Zl(e)}};Y8.className="softplus";de.registerClass(Y8);var J8=class extends As{apply(e){return SV(e)}};J8.className="softsign";de.registerClass(J8);var Q8=class extends As{apply(e){return Yi(e)}};Q8.className="tanh";de.registerClass(Q8);var g5=class extends As{apply(e,t=-1){return Jl(e,t)}};g5.className="softmax";de.registerClass(g5);var ek=class extends As{apply(e,t=-1){return I0(e,t)}};ek.className="logSoftmax";de.registerClass(ek);var tk=class extends As{apply(e,t=1){return J(()=>L(Cn(L(e,t)),e))}};tk.className="swish";de.registerClass(tk);var nk=class extends As{apply(e){return J(()=>L(e,Yi(Zl(e))))}};nk.className="mish";de.registerClass(nk);function ro(e){return e.getClassName()}function d3(e,t={}){return wh(e,de.SerializationMap.getMap().classNameMap,t,"activation")}function ao(e){if(e==null){let t={};return t.className="linear",t.config={},d3(t)}if(typeof e=="string"){let t={};return t.className=e,t.config={},d3(t)}else return e instanceof As?e:d3(e)}function y5(e){if(e!=null&&typeof e!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}var sk=class extends de.Serializable{},Th=class extends sk{constructor(e){super(),y5(e),this.l1=e==null||e.l1==null?.01:e.l1,this.l2=e==null||e.l2==null?.01:e.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(e){return J(()=>{let t=Wt([1]);return this.hasL1&&(t=ce(t,ke(L(this.l1,tn(e))))),this.hasL2&&(t=ce(t,ke(L(this.l2,Ih(e))))),U(t,[])})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};Th.className="L1L2";de.registerClass(Th);function rG(e){return y5(e),new Th({l1:e!=null?e.l1:null,l2:0})}function aG(e){return y5(e),new Th({l2:e!=null?e.l2:null,l1:0})}var Xv={l1l2:"L1L2"};function St(e){return XA(e)}function Kv(e,t={}){return wh(e,de.SerializationMap.getMap().classNameMap,t,"regularizer")}function Mt(e){if(e==null)return null;if(typeof e=="string"){let n={className:e in Xv?Xv[e]:e,config:{}};return Kv(n)}else return e instanceof sk?e:Kv(e)}var A5=class extends ut{constructor(e){super(e==null?{}:e),this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=Xe(e);let n=Pr(e);return this.maxValue!=null&&(n=fs(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};A5.className="ReLU";de.registerClass(A5);var x5=class extends ut{constructor(e){super(e==null?{}:e),this.DEFAULT_ALPHA=.3,e==null&&(e={}),this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Xe(e);return dh(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};x5.className="LeakyReLU";de.registerClass(x5);var b5=class extends ut{constructor(e){if(super(e==null?{}:e),this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=Ot(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=Mt(e.alphaRegularizer),this.alphaConstraint=yn(e.alphaConstraint),e.sharedAxes==null)this.sharedAxes=null;else if(Array.isArray(e.sharedAxes))this.sharedAxes=e.sharedAxes;else if(typeof e.sharedAxes=="number")this.sharedAxes=[e.sharedAxes];else throw new j(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=xt(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let s of this.sharedAxes)t[s-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let s=1;s<e.length;++s)n[s]=e[s];this.inputSpec=[new rn({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=Xe(e),yh(e,this.alpha.read())}getConfig(){let e={alphaInitializer:Vt(this.alphaInitializer),alphaRegularizer:St(this.alphaRegularizer),alphaConstraint:gn(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};b5.className="PReLU";de.registerClass(b5);var v5=class extends ut{constructor(e){if(super(e==null?{}:e),this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new He(`Non-default alpha value (${e.alpha}) is not supported by the ELU layer yet.`);this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Xe(e);return Uc(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};v5.className="ELU";de.registerClass(v5);var w5=class extends ut{constructor(e){super(e==null?{}:e),this.DEFAULT_THETA=1,e==null&&(e={}),this.theta=e.theta==null?this.DEFAULT_THETA:e.theta}call(e,t){let n=Xe(e);return L(n,ge(ys(n,this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};w5.className="ThresholdedReLU";de.registerClass(w5);var k5=class extends ut{constructor(e){super(e==null?{}:e),this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new g5().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Xe(e);return this.softmax(n,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};k5.className="Softmax";de.registerClass(k5);function Hu(e,t,n){if(typeof e=="number")return el(e,t);if(e.length!==t)throw new j(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${e.length} elements.`);for(let s=0;s<t;++s){let r=e[s];if(!bV(r))throw new j(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${JSON.stringify(e)} including a non-integer number ${r}`)}return e}function Er(e,t,n,s,r=1){if(e==null)return e;let a=t+(t-1)*(r-1),o;return n==="same"?o=e:o=e-a+1,Math.floor((o+s-1)/s)}function Ur(e,t,n,s){if(e==null)return null;if(s==="valid")e=e*t+so([n-t,0]);else if(s==="same")e=e*t;else throw new j(`Unsupport padding mode: ${s}.`);return e}function I5(e,t){return J(()=>(Yt(t),t==="channelsFirst"?st(e,[0,2,3,1]):e))}function rk(e,t){return J(()=>(Yt(t),t==="channelsFirst"?st(e,[0,2,3,4,1]):e))}function oG(e,t,n,s=1,r="valid",a,o=1){return J(()=>{if(a==null&&(a=_r()),Yt(a),e.shape.length!==3)throw new j(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new j(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new j(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(a==="channelsFirst"&&(e=st(e,[0,2,1])),r==="causal")throw new He("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let i=y0(e,t,s,r==="same"?"same":"valid","NWC",o);return n!=null&&(i=Fr(i,n)),i})}function Zv(e,t,n,s=[1,1],r="valid",a,o,i=null){return J(()=>{if(a==null&&(a=_r()),Yt(a),e.rank!==3&&e.rank!==4)throw new j(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new j(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=I5(e,a);if(r==="causal")throw new He("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=ec.conv2d({x:l,filter:t,strides:s,pad:r==="same"?"same":"valid",dilations:o,dataFormat:"NHWC",bias:n,activation:i}),a==="channelsFirst"&&(l=st(l,[0,3,1,2])),l})}function iG(e,t,n,s=[1,1,1],r="valid",a,o){return J(()=>{if(a==null&&(a=_r()),Yt(a),e.rank!==4&&e.rank!==5)throw new j(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new j(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let i=rk(e,a);if(r==="causal")throw new He("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return i=cA(i,t,s,r==="same"?"same":"valid","NDHWC",o),n!=null&&(i=Fr(i,n)),a==="channelsFirst"&&(i=st(i,[0,4,1,2,3])),i})}var S5=class extends ut{constructor(e,t){if(super(t),this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",S5.verifyArgs(t),this.rank=e,vn(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new He(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Hu(t.kernelSize,e,"kernelSize"),this.strides=Hu(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Qs(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Yt(this.dataFormat),this.activation=ao(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=Ot(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=yn(t.biasConstraint),this.biasRegularizer=Mt(t.biasRegularizer),this.activityRegularizer=Mt(t.activityRegularizer),this.dilationRate=Hu(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new j(`dilationRate must be a number or an array of a single number for 1D convolution, but received ${JSON.stringify(this.dilationRate)}`);if(this.rank===2){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==2)throw new j(`dilationRate must be a number or array of two numbers for 2D convolution, but received ${JSON.stringify(this.dilationRate)}`)}else if(this.rank===3){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==3)throw new j(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Vr("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!KA(e.kernelSize,"number",1,3))throw new j(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(e.kernelSize)}.`)}getConfig(){let e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:ro(this.activation),useBias:this.useBias,biasInitializer:Vt(this.biasInitializer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),biasConstraint:gn(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Nh=class extends S5{constructor(e,t){super(e,t),this.kernel=null,Nh.verifyArgs(t),this.filters=t.filters,vn(this.filters,"filters"),this.kernelInitializer=Ot(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=yn(t.kernelConstraint),this.kernelRegularizer=Mt(t.kernelRegularizer)}build(e){e=xt(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new j(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],s=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:{[t]:n}}],this.built=!0}call(e,t){return J(()=>{e=Xe(e);let n,s=this.bias==null?null:this.bias.read(),r=p8(this.activation.getClassName());if(r!=null&&this.rank===2)n=Zv(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate,r);else{if(this.rank===1)n=oG(e,this.kernel.read(),s,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=Zv(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=iG(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new He("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=xt(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let r=0;r<n.length;++r){let a=Er(n[r],this.kernelSize[r],this.padding,this.strides[r],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[r]);t.push(a)}let s=[e[0]];return this.dataFormat==="channelsLast"?(s=s.concat(t),s.push(this.filters)):(s.push(this.filters),s=s.concat(t)),s}getConfig(){let e={filters:this.filters,kernelInitializer:Vt(this.kernelInitializer),kernelRegularizer:St(this.kernelRegularizer),kernelConstraint:gn(this.kernelConstraint)},t=super.getConfig();return Object.assign(e,t),e}static verifyArgs(e){if(!("filters"in e)||typeof e.filters!="number"||e.filters<1)throw new j(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Eh=class extends Nh{constructor(e){super(2,e),Eh.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!KA(e.kernelSize,"number",1,2))throw new j(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Eh.className="Conv2D";de.registerClass(Eh);var Rh=class extends Nh{constructor(e){super(3,e),Rh.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!(Array.isArray(e.kernelSize)&&(e.kernelSize.length===1||e.kernelSize.length===3)))throw new j(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};Rh.className="Conv3D";de.registerClass(Rh);var C5=class extends Eh{constructor(e){if(super(e),this.inputSpec=[new rn({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new j(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=xt(e),e.length!==4)throw new j("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new j("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],s=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",s,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new rn({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return J(()=>{let n=Xe(e);if(n.shape.length!==4)throw new j(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let s=n.shape,r=s[0],a,o;this.dataFormat==="channelsFirst"?(a=2,o=3):(a=1,o=2);let i=s[a],l=s[o],u=this.kernelSize[0],c=this.kernelSize[1],p=this.strides[0],d=this.strides[1],h=Ur(i,p,u,this.padding),f=Ur(l,d,c,this.padding),m=[r,h,f,this.filters];this.dataFormat!=="channelsLast"&&(n=st(n,[0,2,3,1]));let g=A0(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(g=st(g,[0,3,1,2])),this.bias!=null&&(g=Fr(g,this.bias.read(),this.dataFormat)),this.activation!=null&&(g=this.activation.apply(g)),g})}computeOutputShape(e){e=xt(e);let t=e.slice(),n,s,r;this.dataFormat==="channelsFirst"?(n=1,s=2,r=3):(n=3,s=1,r=2);let a=this.kernelSize[0],o=this.kernelSize[1],i=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[s]=Ur(t[s],i,a,this.padding),t[r]=Ur(t[r],l,o,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};C5.className="Conv2DTranspose";de.registerClass(C5);var T5=class extends Rh{constructor(e){if(super(e),this.inputSpec=[new rn({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new j(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=xt(e),e.length!==5)throw new j("Input should have rank 5; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new j("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],s=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",s,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new rn({ndim:5,axes:{[t]:n}})],this.built=!0}call(e,t){return J(()=>{let n=Xe(e);if(n.shape.length!==5)throw new j(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let s=n.shape,r=s[0],a,o,i;this.dataFormat==="channelsFirst"?(i=2,a=3,o=4):(i=1,a=2,o=3);let l=s[i],u=s[a],c=s[o],p=this.kernelSize[0],d=this.kernelSize[1],h=this.kernelSize[2],f=this.strides[0],m=this.strides[1],g=this.strides[2],y=Ur(l,f,p,this.padding),x=Ur(u,m,d,this.padding),A=Ur(c,g,h,this.padding),b=[r,y,x,A,this.filters];this.dataFormat!=="channelsLast"&&(n=st(n,[0,2,3,4,1]));let w=dA(n,this.kernel.read(),b,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(w=st(w,[0,4,1,2,3])),this.bias!==null&&(w=Fr(w,this.bias.read(),this.dataFormat)),this.activation!==null&&(w=this.activation.apply(w)),w})}computeOutputShape(e){e=xt(e);let t=e.slice(),n,s,r,a;this.dataFormat==="channelsFirst"?(n=1,s=2,r=3,a=4):(n=4,s=1,r=2,a=3);let o=this.kernelSize[0],i=this.kernelSize[1],l=this.kernelSize[2],u=this.strides[0],c=this.strides[1],p=this.strides[2];return t[n]=this.filters,t[s]=Ur(t[s],u,o,this.padding),t[r]=Ur(t[r],c,i,this.padding),t[a]=Ur(t[a],p,l,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};T5.className="Conv3DTranspose";de.registerClass(T5);var ak=class extends Nh{constructor(e,t){if(super(e,t),this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new j("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new j("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(t.padding!=null&&t.padding!=="same"&&t.padding!=="valid")throw new j(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=Ot(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=Mt(t.depthwiseRegularizer),this.depthwiseConstraint=yn(t.depthwiseConstraint),this.pointwiseInitializer=Ot(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=Mt(t.pointwiseRegularizer),this.pointwiseConstraint=yn(t.pointwiseConstraint)}build(e){if(e=xt(e),e.length<this.rank+2)throw new j(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank+2}, but received input shape: ${JSON.stringify(e)}`);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null||e[t]<0)throw new j(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],s=this.kernelSize.concat([n,this.depthMultiplier]),r=[];for(let o=0;o<this.rank;++o)r.push(1);r.push(n*this.depthMultiplier,this.filters);let a=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",s,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,a,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",r,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,a,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,a,this.biasConstraint):this.bias=null,this.inputSpec=[new rn({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return J(()=>{e=Xe(e);let n;if(this.rank===1)throw new He("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=st(e,[0,2,3,1])),n=$0(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Fr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=st(n,[0,3,1,2])),n})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=Vt(this.depthwiseInitializer),e.pointwiseInitializer=Vt(this.pointwiseInitializer),e.depthwiseRegularizer=St(this.depthwiseRegularizer),e.pointwiseRegularizer=St(this.pointwiseRegularizer),e.depthwiseConstraint=gn(this.depthwiseConstraint),e.pointwiseConstraint=gn(this.pointwiseConstraint),e}};ak.className="SeparableConv";var N5=class extends ak{constructor(e){super(2,e)}};N5.className="SeparableConv2D";de.registerClass(N5);var d2=class extends Nh{constructor(e){super(1,e),d2.verifyArgs(e),this.inputSpec=[{ndim:3}]}getConfig(){let e=super.getConfig();return delete e.rank,delete e.dataFormat,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!KA(e.kernelSize,"number",1,1))throw new j(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};d2.className="Conv1D";de.registerClass(d2);var E5=class extends ut{constructor(e){super(e),typeof e.cropping=="number"?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:typeof e.cropping[0]=="number"?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=e.dataFormat===void 0?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(e){return this.dataFormat==="channelsFirst"?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]}call(e,t){return J(()=>{if(e=Xe(e),this.dataFormat==="channelsLast"){let n=Uf(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Uf(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Uf(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Uf(n,this.cropping[1][0],e.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let e={cropping:this.cropping,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};E5.className="Cropping2D";de.registerClass(E5);var R5=class extends ut{constructor(e){super(e),this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=e.size==null?this.DEFAULT_SIZE:e.size,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Yt(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,yV(this.interpolation)}computeOutputShape(e){if(this.dataFormat==="channelsFirst"){let t=e[2]==null?null:this.size[0]*e[2],n=e[3]==null?null:this.size[1]*e[3];return[e[0],e[1],t,n]}else{let t=e[1]==null?null:this.size[0]*e[1],n=e[2]==null?null:this.size[1]*e[2];return[e[0],t,n,e[3]]}}call(e,t){return J(()=>{let n=Xe(e),s=n.shape;if(this.dataFormat==="channelsFirst"){n=st(n,[0,2,3,1]);let r=this.size[0]*s[2],a=this.size[1]*s[3],o=this.interpolation==="nearest"?Ne.resizeNearestNeighbor(n,[r,a]):Ne.resizeBilinear(n,[r,a]);return st(o,[0,3,1,2])}else{let r=this.size[0]*s[1],a=this.size[1]*s[2];return this.interpolation==="nearest"?Ne.resizeNearestNeighbor(n,[r,a]):Ne.resizeBilinear(n,[r,a])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat,interpolation:this.interpolation},t=super.getConfig();return Object.assign(e,t),e}};R5.className="UpSampling2D";de.registerClass(R5);function lG(e,t,n=[1,1],s="valid",r,a){return J(()=>{r==null&&(r=_r()),Yt(r);let o=I5(e,r);if(e.rank!==4)throw new j(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new j(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return o=Vc(o,t,n,s==="same"?"same":"valid","NHWC",a),r==="channelsFirst"&&(o=st(o,[0,3,1,2])),o})}var _5=class extends S5{constructor(e){super(2,e),this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=Ot(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=yn(e.depthwiseConstraint),this.depthwiseRegularizer=Mt(e.depthwiseRegularizer)}build(e){if(e=xt(e),e.length<4)throw new j(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new j(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],s=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",s,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return J(()=>{e=Xe(e);let n=lG(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Fr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=xt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],s=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,r=Er(t,this.kernelSize[0],this.padding,this.strides[0]),a=Er(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],s,r,a]:[e[0],r,a,s]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Vt(this.depthwiseInitializer),e.depthwiseRegularizer=St(this.depthwiseRegularizer),e.depthwiseConstraint=gn(this.depthwiseRegularizer),e}};_5.className="DepthwiseConv2D";de.registerClass(_5);function ok(e,t,n,s){if(Array.isArray(e)){if(t!=null||n!=null)throw new j("When inputs is an array, neither initialState or constants should be provided");s!=null&&(n=e.slice(e.length-s,e.length),e=e.slice(0,e.length-s)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function r(a){return a==null||Array.isArray(a)?a:[a]}return t=r(t),n=r(n),{inputs:e,initialState:t,constants:n}}function ik(e,t,n,s=!1,r,a,o=!1,i=!1){return J(()=>{let l=t.shape.length;if(l<3)throw new j(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(Rr(2,l));if(t=st(t,u),a!=null)throw new He("The rnn() functoin of the deeplearn.js backend does not support constants yet.");o&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),r!=null&&(r=ge(ge(r,"bool"),"float32"),r.rank===l-1&&(r=Kt(r,-1)),r=st(r,u)),s&&(t=Ks(t,0),r!=null&&(r=Ks(r,0)));let c=[],p,d=n,h=t.shape[0],f=es(t),m;r!=null&&(m=es(r));for(let y=0;y<h;++y){let x=f[y],A=J(()=>e(x,d));if(r==null)p=A[0],d=A[1];else{let b=J(()=>{let w=m[y],k=he($s(w),w),S=ce(L(A[0],w),L(d[0],k)),E=d.map((R,P)=>ce(L(A[1][P],w),L(R,k)));return{output:S,newStates:E}});p=b.output,d=b.newStates}i&&c.push(p)}let g;return i&&(g=on(c,1)),[p,g,d]})}var Qr=class extends ut{constructor(e){super(e);let t;if(e.cell==null)throw new j("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new f2({cells:e.cell}):t=e.cell,t.stateSize==null)throw new j("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=t,this.returnSequences=e.returnSequences==null?!1:e.returnSequences,this.returnState=e.returnState==null?!1:e.returnState,this.goBackwards=e.goBackwards==null?!1:e.goBackwards,this._stateful=e.stateful==null?!1:e.stateful,this.unroll=e.unroll==null?!1:e.unroll,this.supportsMasking=!0,this.inputSpec=[new rn({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return Rr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){F3(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],s;if(this.returnSequences?s=[e[0],e[1],n]:s=[e[0],n],this.returnState){let r=[];for(let a of t)r.push([e[0],a]);return[s].concat(r)}else return s}computeMask(e,t){return J(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let s=this.states.map(r=>null);return[n].concat(s)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){if(this.numConstants!=null)throw new He("Constants support is not implemented in RNN yet.");F3(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,s=e.slice(2);this.inputSpec[0]=new rn({shape:[n,null,...s]});let r=[e[0]].concat(e.slice(2));this.cell.build(r);let a;if(Array.isArray(this.cell.stateSize)?a=this.cell.stateSize:a=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(o=>o.shape[o.shape.length-1]),a))throw new j(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=a.map(o=>new rn({shape:[null,o]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){J(()=>{if(!this.stateful)throw new la("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new j("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.states_==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(s=>Wt([n,s])):this.states_=[Wt([n,this.cell.stateSize])];else if(e==null)ne(this.states_),this.keptStates!=null&&(ne(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(s=>Wt([n,s])):this.states_[0]=Wt([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new j(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t===!0?this.keptStates.push(this.states_.slice()):ne(this.states_);for(let s=0;s<this.states_.length;++s){let r=e[s],a=Array.isArray(this.cell.stateSize)?this.cell.stateSize[s]:this.cell.stateSize,o=[n,a];if(!v.arraysEqual(r.shape,o))throw new j(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${r.shape}`);this.states_[s]=r}}this.states_=this.states_.map(s=>bn(s.clone()))})}apply(e,t){let n=t==null?null:t.initialState,s=t==null?null:t.constants;t==null&&(t={});let r=ok(e,n,s,this.numConstants);e=r.inputs,n=r.initialState,s=r.constants;let a=[],o=[];if(n!=null){t.initialState=n,a=a.concat(n),this.stateSpec=[];for(let l of n)this.stateSpec.push(new rn({shape:l.shape}));o=o.concat(this.stateSpec)}if(s!=null&&(t.constants=s,a=a.concat(s),this.numConstants=s.length),a[0]instanceof Cr){let l=[e].concat(a),u=this.inputSpec.concat(o),c=this.inputSpec;this.inputSpec=u;let p=super.apply(l,t);return this.inputSpec=c,p}else return super.apply(e,t)}call(e,t){return J(()=>{let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;e=Xe(e),r==null&&(this.stateful?r=this.states_:r=this.getInitialState(e));let a=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(r.length!==a)throw new j(`RNN Layer has ${a} state(s) but was passed ${r.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let o={training:s},l=ik((h,f)=>{let m=this.cell.call([h].concat(f),o);return[m[0],m.slice(1)]},e,r,this.goBackwards,n,null,this.unroll,this.returnSequences),u=l[0],c=l[1],p=l[2];this.stateful&&this.resetStates(p,s);let d=this.returnSequences?c:u;return this.returnState?[d].concat(p):d})}getInitialState(e){return J(()=>{let t=Wt(e.shape);return t=ke(t,[1,2]),t=kh(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?$3(t,[1,n]):t):this.cell.stateSize>1?[$3(t,[1,this.cell.stateSize])]:[t]})}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.cell!=null&&this.cell.setFastWeightInitDuringBuild(e)}getConfig(){let e=super.getConfig(),t={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(t.numConstants=this.numConstants);let n=this.cell.getConfig();return this.getClassName()===Qr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let s=t.cell,r=Nr(s,n);return new e(Object.assign(t,{cell:r}))}};Qr.className="RNN";de.registerClass(Qr);var _h=class extends ut{},p2=class extends _h{constructor(e){super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,vn(this.units,"units"),this.activation=ao(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Ot(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Ot(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Ot(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Mt(e.kernelRegularizer),this.recurrentRegularizer=Mt(e.recurrentRegularizer),this.biasRegularizer=Mt(e.biasRegularizer),this.kernelConstraint=yn(e.kernelConstraint),this.recurrentConstraint=yn(e.recurrentConstraint),this.biasConstraint=yn(e.biasConstraint),this.dropout=tc([1,so([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=tc([1,so([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=xt(e),this.kernel=this.addWeight("kernel",[e[e.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return J(()=>{if(e=e,e.length!==2)throw new j(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let s=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=oo({ones:()=>$s(e),rate:this.dropout,training:s,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=oo({ones:()=>$s(n),rate:this.recurrentDropout,training:s,dropoutFunc:this.dropoutFunc}));let r,a=this.dropoutMask,o=this.recurrentDropoutMask;a!=null?r=jr(L(e,a),this.kernel.read()):r=jr(e,this.kernel.read()),this.bias!=null&&(r=Fr(r,this.bias.read())),o!=null&&(n=L(n,o));let i=ce(r,jr(n,this.recurrentKernel.read()));return this.activation!=null&&(i=this.activation.apply(i)),[i,i]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:ro(this.activation),useBias:this.useBias,kernelInitializer:Vt(this.kernelInitializer),recurrentInitializer:Vt(this.recurrentInitializer),biasInitializer:Vt(this.biasInitializer),kernelRegularizer:St(this.kernelRegularizer),recurrentRegularizer:St(this.recurrentRegularizer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),kernelConstraint:gn(this.kernelConstraint),recurrentConstraint:gn(this.recurrentConstraint),biasConstraint:gn(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};p2.className="SimpleRNNCell";de.registerClass(p2);var D5=class extends Qr{constructor(e){e.cell=new p2(e),super(e)}call(e,t){return J(()=>{this.cell.dropoutMask!=null&&(ne(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ne(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return new e(t)}};D5.className="SimpleRNN";de.registerClass(D5);var h2=class extends _h{constructor(e){if(super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new j("GRUCell does not support reset_after parameter set to true.");this.units=e.units,vn(this.units,"units"),this.activation=ao(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ao(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Ot(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Ot(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Ot(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Mt(e.kernelRegularizer),this.recurrentRegularizer=Mt(e.recurrentRegularizer),this.biasRegularizer=Mt(e.biasRegularizer),this.kernelConstraint=yn(e.kernelConstraint),this.recurrentConstraint=yn(e.recurrentConstraint),this.biasConstraint=yn(e.biasConstraint),this.dropout=tc([1,so([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=tc([1,so([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=xt(e);let t=e[e.length-1];this.kernel=this.addWeight("kernel",[t,this.units*3],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*3],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units*3],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return J(()=>{if(e=e,e.length!==2)throw new j(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,s=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=oo({ones:()=>$s(e),rate:this.dropout,training:n,count:3,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=oo({ones:()=>$s(s),rate:this.recurrentDropout,training:n,count:3,dropoutFunc:this.dropoutFunc}));let r=this.dropoutMask,a=this.recurrentDropoutMask,o,i,l;0<this.dropout&&this.dropout<1&&(e=L(e,r[0]));let u=jr(e,this.kernel.read());this.useBias&&(u=Fr(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(s=L(s,a[0]));let c=this.recurrentKernel.read(),[p,d]=Zt(c,[2*this.units,this.units],c.rank-1),h=jr(s,p),[f,m,g]=Zt(u,3,u.rank-1),[y,x]=Zt(h,2,h.rank-1);o=this.recurrentActivation.apply(ce(f,y)),i=this.recurrentActivation.apply(ce(m,x));let A=jr(L(i,s),d);l=this.activation.apply(ce(g,A));let b=ce(L(o,s),L(ce(1,Dt(o)),l));return[b,b]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:ro(this.activation),recurrentActivation:ro(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Vt(this.kernelInitializer),recurrentInitializer:Vt(this.recurrentInitializer),biasInitializer:Vt(this.biasInitializer),kernelRegularizer:St(this.kernelRegularizer),recurrentRegularizer:St(this.recurrentRegularizer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),kernelConstraint:gn(this.kernelConstraint),recurrentConstraint:gn(this.recurrentConstraint),biasConstraint:gn(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};h2.className="GRUCell";de.registerClass(h2);var $5=class extends Qr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new h2(e),super(e)}call(e,t){return J(()=>{this.cell.dropoutMask!=null&&(ne(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ne(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};$5.className="GRU";de.registerClass($5);var Dh=class extends _h{constructor(e){super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,vn(this.units,"units"),this.activation=ao(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ao(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Ot(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Ot(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Ot(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=Mt(e.kernelRegularizer),this.recurrentRegularizer=Mt(e.recurrentRegularizer),this.biasRegularizer=Mt(e.biasRegularizer),this.kernelConstraint=yn(e.kernelConstraint),this.recurrentConstraint=yn(e.recurrentConstraint),this.biasConstraint=yn(e.biasConstraint),this.dropout=tc([1,so([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=tc([1,so([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=xt(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let s;if(this.useBias){if(this.unitForgetBias){let r=this.biasInitializer,a=this.units;s=new(t=class extends pr{apply(i,l){let u=r.apply([a]),c=new t2().apply([a]),p=r.apply([a*2]);return $v($v(u,c),p)}},t.className="CustomInit",t)}else s=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,s,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return J(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new j(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let s=e[1],r=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=oo({ones:()=>$s(e),rate:this.dropout,training:n,count:4,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=oo({ones:()=>$s(s),rate:this.recurrentDropout,training:n,count:4,dropoutFunc:this.dropoutFunc}));let a=this.dropoutMask,o=this.recurrentDropoutMask,i,l,u,c;0<this.dropout&&this.dropout<1&&(e=L(e,a[0]));let p=jr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(s=L(s,o[0])),p=ce(p,jr(s,this.recurrentKernel.read())),this.useBias&&(p=Fr(p,this.bias.read()));let[d,h,f,m]=Zt(p,4,p.rank-1);i=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(h),u=ce(L(l,r),L(i,this.activation.apply(f))),c=this.recurrentActivation.apply(m);let g=L(c,this.activation.apply(u));return[g,g,u]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:ro(this.activation),recurrentActivation:ro(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Vt(this.kernelInitializer),recurrentInitializer:Vt(this.recurrentInitializer),biasInitializer:Vt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:St(this.kernelRegularizer),recurrentRegularizer:St(this.recurrentRegularizer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),kernelConstraint:gn(this.kernelConstraint),recurrentConstraint:gn(this.recurrentConstraint),biasConstraint:gn(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};Dh.className="LSTMCell";de.registerClass(Dh);var P5=class extends Qr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new Dh(e),super(e)}call(e,t){return J(()=>{this.cell.dropoutMask!=null&&(ne(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ne(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};P5.className="LSTM";de.registerClass(P5);var f2=class extends _h{constructor(e){super(e),this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return J(()=>{e=e;let n=e.slice(1),s=[];for(let o of this.cells.slice().reverse())Array.isArray(o.stateSize)?s.push(n.splice(0,o.stateSize.length)):s.push(n.splice(0,1));s.reverse();let r=[],a;for(let o=0;o<this.cells.length;++o){let i=this.cells[o];n=s[o],o===0?a=[e[0]].concat(n):a=[a[0]].concat(n),a=i.call(a,t),r.push(a.slice(1))}n=[];for(let o of r.slice().reverse())n.push(...o);return[a[0]].concat(n)})}build(e){F3(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,s)=>{Hi(`RNNCell_${s}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=r=>({className:r.getClassName(),config:r.getConfig()}),s={cells:this.cells.map(t)};return Object.assign({},e,s)}static fromConfig(e,t,n={}){let s=[];for(let r of t.cells)s.push(Nr(r,n));return new e({cells:s})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return O3(e)}setWeights(e){let t=[];for(let n of this.cells){let s=n.weights.length,r=e.splice(s);for(let a=0;a<n.weights.length;++a)t.push([n.weights[a],r[a]])}r5(t)}};f2.className="StackedRNNCells";de.registerClass(f2);function oo(e){let{ones:t,rate:n,training:s=!1,count:r=1,dropoutFunc:a}=e,o=()=>a!=null?a(t(),n):x8(t(),n),i=()=>Sh(o,t,s);return!r||r<=1?bn(i().clone()):Array(r).fill(void 0).map(i).map(u=>bn(u.clone()))}var uG=function(e,t){var n={};for(var s in e)Object.prototype.hasOwnProperty.call(e,s)&&t.indexOf(s)<0&&(n[s]=e[s]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var r=0,s=Object.getOwnPropertySymbols(e);r<s.length;r++)t.indexOf(s[r])<0&&Object.prototype.propertyIsEnumerable.call(e,s[r])&&(n[s[r]]=e[s[r]]);return n},lk=class extends Qr{constructor(e){if(e.unroll)throw new He("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new He("It is not possible at the moment to stack convolutional cells.");super(e),this.inputSpec=[new rn({ndim:5})]}call(e,t){return J(()=>{if(this.cell.dropoutMask!=null&&(ne(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ne(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new j("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return J(()=>{let{stateSize:t}=this.cell,n=e.shape,s=this.computeSingleOutputShape(n),r=[s[0],...s.slice(2)],a=Wt(r);return Array.isArray(t)?Array(t.length).fill(a):[a]})}resetStates(e,t=!1){J(()=>{if(!this.stateful)throw new la("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,s=this.computeSingleOutputShape(n),r=[s[0],...s.slice(2)];if(n[0]==null)throw new j("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Wt(r)):this.states_=[Wt(r)];else if(e==null)ne(this.states_),this.keptStates!=null&&(ne(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Wt(r)):this.states_[0]=Wt(r);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new j(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t?this.keptStates.push(this.states_.slice()):ne(this.states_);for(let o=0;o<this.states_.length;++o){let i=e[o],l=r;if(!v.arraysEqual(i.shape,l))throw new j(`State ${o} is incompatible with layer ${this.name}: expected shape=${l}, received shape=${i.shape}`);this.states_[o]=i}}this.states_=this.states_.map(o=>bn(o.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:s,padding:r,strides:a,dilationRate:o}=this.cell,i=t==="channelsFirst",l=e[i?3:2],u=e[i?4:3],c=Er(l,s[0],r,a[0],o[0]),p=Er(u,s[1],r,a[1],o[1]);return[...e.slice(0,2),...i?[n,c,p]:[c,p,n]]}};lk.className="ConvRNN2D";var m2=class extends Dh{constructor(e){let{filters:t,kernelSize:n,strides:s,padding:r,dataFormat:a,dilationRate:o}=e;super(Object.assign({},e,{units:t})),this.filters=t,vn(this.filters,"filters"),this.kernelSize=Hu(n,2,"kernelSize"),this.kernelSize.forEach(i=>vn(i,"kernelSize")),this.strides=Hu(s||1,2,"strides"),this.strides.forEach(i=>vn(i,"strides")),this.padding=r||"valid",Qs(this.padding),this.dataFormat=a||"channelsLast",Yt(this.dataFormat),this.dilationRate=Hu(o||1,2,"dilationRate"),this.dilationRate.forEach(i=>vn(i,"dilationRate"))}build(e){var t;e=xt(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new j(`The channel dimension of the input should be defined. Found ${e[n]}`);let s=e[n],r=4,a=this.kernelSize.concat([s,this.filters*r]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let o=this.kernelSize.concat([this.filters,this.filters*r]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",o,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let i;if(this.unitForgetBias){let l=this.biasInitializer,u=this.filters;i=new(t=class extends pr{apply(p,d){let h=l.apply([u]),f=Ns([u]),m=l.apply([u*2]);return ZA([h,f,m])}},t.className="CustomInit",t)}else i=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*r],null,i,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return J(()=>{if(e.length!==3)throw new j(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,s=e[0],r=e[1],a=e[2],o=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=oo({ones:()=>$s(s),rate:this.dropout,training:n,count:o,dropoutFunc:this.dropoutFunc}));let i=this.dropoutMask,l=(B,ee,Q)=>!ee||!ee[Q]?B:L(ee[Q],B),u=l(s,i,0),c=l(s,i,1),p=l(s,i,2),d=l(s,i,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=oo({ones:()=>$s(r),rate:this.recurrentDropout,training:n,count:o,dropoutFunc:this.dropoutFunc}));let h=this.recurrentDropoutMask,f=l(r,h,0),m=l(r,h,1),g=l(r,h,2),y=l(r,h,3),x=3,[A,b,w,k]=Zt(this.kernel.read(),o,x),[S,E,R,P]=this.useBias?Zt(this.bias.read(),o):[null,null,null,null];u=this.inputConv(u,A,S,this.padding),c=this.inputConv(c,b,E,this.padding),p=this.inputConv(p,w,R,this.padding),d=this.inputConv(d,k,P,this.padding);let[_,$,T,F]=Zt(this.recurrentKernel.read(),o,x);f=this.recurrentConv(f,_),m=this.recurrentConv(m,$),g=this.recurrentConv(g,T),y=this.recurrentConv(y,F);let G=this.recurrentActivation.apply(ce(u,f)),q=this.recurrentActivation.apply(ce(c,m)),z=ce(L(q,a),L(G,this.activation.apply(ce(p,g)))),K=L(this.recurrentActivation.apply(ce(d,y)),this.activation.apply(z));return[K,K,z]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=uG(e,["units"]),s={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,s)}inputConv(e,t,n,s){let r=ma(e,t,this.strides,s||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Fr(r,n,this.dataFormat):r}recurrentConv(e,t){return ma(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};m2.className="ConvLSTM2DCell";de.registerClass(m2);var F5=class extends lk{constructor(e){let t=new m2(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};F5.className="ConvLSTM2D";de.registerClass(F5);var g2=class extends ut{constructor(e){super(e),this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(this.noiseShape==null)return this.noiseShape;let t=e.shape,n=[];for(let s=0;s<this.noiseShape.length;++s)n.push(this.noiseShape[s]==null?t[s]:this.noiseShape[s]);return n}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);if(0<this.rate&&this.rate<1){let s=t.training==null?!1:t.training,r=this.getNoiseShape(n);return Sh(()=>x8(n,this.rate,r,this.seed),()=>n,s)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};g2.className="Dropout";de.registerClass(g2);var O5=class extends g2{constructor(e){super(e),this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};O5.className="SpatialDropout1D";de.registerClass(O5);var M5=class extends ut{constructor(e){if(super(e),this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.batchInputShape==null&&e.inputShape==null&&e.inputDim!=null){let t=null;e.batchSize!=null&&(t=e.batchSize),this.batchInputShape=[t,e.inputDim]}this.units=e.units,vn(this.units,"units"),this.activation=ao(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=Ot(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=Ot(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=yn(e.kernelConstraint),this.biasConstraint=yn(e.biasConstraint),this.kernelRegularizer=Mt(e.kernelRegularizer),this.biasRegularizer=Mt(e.biasRegularizer),this.activityRegularizer=Mt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=xt(e);let t=e[e.length-1];this.kernel==null&&(this.kernel=this.addWeight("kernel",[t,this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint))),this.inputSpec=[{minNDim:2,axes:{[-1]:t}}],this.built=!0}computeOutputShape(e){e=xt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e),s=p8(this.activation.getClassName()),r;return s!=null?r=jr(n,this.kernel.read(),s,this.bias?this.bias.read():null):(r=jr(n,this.kernel.read()),this.bias!=null&&(r=Fr(r,this.bias.read())),this.activation!=null&&(r=this.activation.apply(r))),r})}getConfig(){let e={units:this.units,activation:ro(this.activation),useBias:this.useBias,kernelInitializer:Vt(this.kernelInitializer),biasInitializer:Vt(this.biasInitializer),kernelRegularizer:St(this.kernelRegularizer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),kernelConstraint:gn(this.kernelConstraint),biasConstraint:gn(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};M5.className="Dense";de.registerClass(M5);var z5=class extends ut{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=xt(e);for(let t of e.slice(1))if(t==null)throw new j(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],Ka(e,1)]}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let s=[0];for(let r=2;r<n.rank;++r)s.push(r);s.push(1),n=st(n,s)}return kV(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};z5.className="Flatten";de.registerClass(z5);var L5=class extends ut{constructor(e){super(e),this.supportsMasking=!0,this.activation=ao(e.activation)}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);return this.activation.apply(n)})}getConfig(){let e={activation:ro(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};L5.className="Activation";de.registerClass(L5);var B5=class extends ut{constructor(e){super(e),this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return J(()=>(e=Xe(e),vV(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};B5.className="RepeatVector";de.registerClass(B5);var W5=class extends ut{constructor(e){super(e),this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let n="Total size of new array must be unchanged.",s=t.slice(),r=1,a=null;for(let i=0;i<s.length;++i){let l=s[i];if(this.isUnknown(l))if(a===null)a=i;else throw new j("Can only specifiy one unknown dimension.");else r*=l}let o=Ka(e);if(a!==null){if(r===0||o%r!==0)throw new j(n);s[a]=o/r}else if(o!==r)throw new j(n);return s}computeOutputShape(e){let t=!1;for(let n=0;n<e.length;++n)if(this.isUnknown(e[n])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e),s=n.shape,r=s.slice(0,1).concat(this.fixUnknownDimension(s.slice(1),this.targetShape));return U(n,r)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};W5.className="Reshape";de.registerClass(W5);var V5=class extends ut{constructor(e){if(super(e),e.dims==null)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(e.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${e.dims} instead.`);let t=Rr(1,e.dims.length+1);if(!v.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new rn({ndim:this.dims.length+1})]}computeOutputShape(e){e=xt(e);let t=e.slice();return this.dims.forEach((n,s)=>{t[s+1]=e[n]}),t}call(e,t){return st(Xe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};V5.className="Permute";de.registerClass(V5);var U5=class extends ut{constructor(e){super(e==null?{}:e),this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Xe(e),s=-1;return Cp(Qi(n,this.maskValue),s)}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e),s=-1,r=!0,a=Cp(Qi(n,this.maskValue),s,r);return L(n,ge(a,n.dtype))})}};U5.className="Masking";de.registerClass(U5);var G5=class extends ut{constructor(e){if(super(e),this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(_t(e.inputLength))}this.inputDim=e.inputDim,vn(this.inputDim,"inputDim"),this.outputDim=e.outputDim,vn(this.outputDim,"outputDim"),this.embeddingsInitializer=Ot(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=Mt(e.embeddingsRegularizer),this.activityRegularizer=Mt(e.activityRegularizer),this.embeddingsConstraint=yn(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return J(()=>this.maskZero?(e=Xe(e),Qi(e,it(e))):null)}computeOutputShape(e){if(e=xt(e),this.inputLength==null)return[...e,this.outputDim];let t=_t(this.inputLength);if(t.length!==e.length-1)throw new j(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let s=0;s<t.length;++s){let r=t[s],a=e[s+1];if(r!=null&&a!=null&&r!==a)throw new j(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);r==null&&(t[n]=a),n++}}return[e[0],...t,this.outputDim]}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);n.dtype!=="int32"&&(n=Q0(n,"int32"));let s=A8(this.embeddings.read(),U(n,[n.size]));return U(s,xt(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Vt(this.embeddingsInitializer),embeddingsRegularizer:St(this.embeddingsRegularizer),activityRegularizer:St(this.activityRegularizer),embeddingsConstraint:gn(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};G5.className="Embedding";de.registerClass(G5);var nu=class extends ut{constructor(e){super(e||{}),this.supportsMasking=!0}mergeFunction(e){throw new He}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let s=0;s<t.length;++s){let r=e[e.length-t.length+s],a=t[s];if(r==null||a==null||r<0||a<0)n.push(null);else if(r===1)n.push(a);else if(a===1)n.push(r);else{if(r!==a)throw new j("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(r)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[xt(e)]),e=e,e.length<2)throw new j(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let r of e)r!=null&&r[0]!==null&&t.push(r[0]);if(t=Xa(t),t.length>1)throw new j(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=e[0]==null?null:e[0].slice(1);for(let r=1;r<e.length;++r){let a=e[r]==null?null:e[r].slice(1);n=this.computeElementwiseOpOutputShape(n,a)}let s=e.map(r=>r.length);e.indexOf(null)===-1&&Xa(s).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return J(()=>{if(e=e,this.reshapeRequired){let n=[],s=e.map(r=>r.rank);if(s.indexOf(null)===-1){let r=so(s);for(let a of e){let o=a.rank;for(let i=0;i<r-o;++i)a=kh(a,1);n.push(a)}return this.mergeFunction(n)}else{let r=!1;for(let i of e){let l=i.rank;if(l==null){let u=i.shape,c=u[0],p=u.slice(1).concat([c]),d=U(i,[c].concat(Ka(u.slice(1))));d=st(d,[1,0]),d=U(d,p),n.push(d),r=!0}else if(l>1){let u=Rr(1,l).concat([0]);n.push(st(i,u)),r=!0}else n.push(i)}let a=this.mergeFunction(n),o=a.rank;if(r){if(o==null){let i=a.shape,l=i.length,u=i[l-1],c=[u].concat(i.slice(0,i.length-1));a=U(st(U(a,[-1,u]),[1,0]),c)}else if(o>1){let i=[o-1].concat(Rr(0,o-1));a=st(a,i)}}return a}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let s=1;s<e.length;++s){let r=e[s]==null?null:e[s].slice(1);t=this.computeElementwiseOpOutputShape(t,r)}let n=[];for(let s of e)s!=null&&s[0]!==null&&n.push(s[0]);return n=Xa(n),n.length===1?t=n.concat(t):t=[null].concat(t),t}computeMask(e,t){return J(()=>{if(t==null)return null;if(!Array.isArray(t))throw new j("`mask` should be an Array");if(!Array.isArray(e))throw new j("`inputs` should be an Array");if(t.length!==e.length)throw new j(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(s=>s==null))return null;t=t.map(s=>s==null?s:Kt(s,0));let n=t[0];for(let s=1;s<t.length-1;++s)n=lr(n,t[s]);return n})}},H5=class extends nu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ce(t,e[n]);return t})}};H5.className="Add";de.registerClass(H5);var j5=class extends nu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=L(t,e[n]);return t})}};j5.className="Multiply";de.registerClass(j5);var q5=class extends nu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ce(t,e[n]);return L(1/e.length,t)})}};q5.className="Average";de.registerClass(q5);var X5=class extends nu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=Jr(t,e[n]);return t})}};X5.className="Maximum";de.registerClass(X5);var K5=class extends nu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=Xc(t,e[n]);return t})}};K5.className="Minimum";de.registerClass(K5);var Z5=class extends nu{constructor(e){super(e),this.DEFAULT_AXIS=-1,e==null&&(e={}),this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){if(!(Array.isArray(e)&&Array.isArray(e[0]))||e.length===1)throw new j("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;let t=!0;for(let s of e)if(s!=null){t=!1;break}if(t)return;let n=[];for(let s=0;s<e.length;++s){let r=e[s].slice();r.splice(this.axis,1);let a=!1;for(let o of n)if(v.arraysEqual(o,r)){a=!0;break}a||n.push(r)}if(n.length>1)throw new j("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return J(()=>ZA(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new j("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),s=this.axis<0?n.length+this.axis:this.axis;for(let r of t.slice(1)){if(n[s]==null||r[s]==null){n[s]=null;break}n[s]+=r[s]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new j("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new j("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new j(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return J(()=>{let n=!0;if(t.forEach(a=>{if(a!=null){n=!1;return}}),n)return null;let s=[];for(let a=0;a<e.length;++a)t[a]==null?s.push(ge($s(e[a]),"bool")):t[a].rank<e[a].rank?s.push(Kt(t[a],-1)):s.push(t[a]);let r=Ct(s,this.axis);return g0(r,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Z5.className="Concatenate";de.registerClass(Z5);function ep(e,t){for(;e<0;)e+=t;return e}function cG(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new He("batchDot is not implemented for tensors of 4D or higher rank yet");if(v.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),v.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof n=="number"&&(n=[n,n]),e.dtype==="complex64"||t.dtype==="complex64")throw new He("batchDot is not implemented for complex64-type Tensors yet.");let s=e.shape.length,r=t.shape.length;n==null&&(n=[s-1,r-2]);let a=n;return J(()=>{let o;if(s>r){o=s-r;let l=[];for(let u=0;u<o;++u)l.push(1);t=U(t,t.shape.concat(l))}else if(r>s){o=r-s;let l=[];for(let u=0;u<o;++u)l.push(1);e=U(e,e.shape.concat(l))}else o=0;let i;if(e.shape.length===2&&t.shape.length===2)a[0]===a[1]?i=ke(L(e,t),a[0]):i=ke(L(st(e,[1,0]),t),a[1]);else{let l=a[0]!==e.shape.length-1,u=a[1]===t.shape.length-1;i=Qe(e,t,l,u)}if(o>0){let l;s>r?l=s+r-3:l=s-1;let u=[];for(let c=l;c<l+o;++c)u.push(c);i=rt(i,u)}return i.shape.length===1&&(i=Kt(i,1)),i})}var Y5=class extends nu{constructor(e){super(e),this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new He("Dot layer does not support tensors of 4D or higher rank yet.");let s=this.interpretAxes(t,n);if(t[s[0]]!==n[s[1]])throw new j(`Dimension incompatibility: ${t[s[0]]} !== ${n[s[1]]}`)}mergeFunction(e){if(e.length!==2)throw new j(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],n=e[1],s;return Array.isArray(this.axes)?s=this.axes.map((r,a)=>ep(r,e[a].shape.length)):s=[ep(this.axes,t.shape.length),ep(this.axes,n.shape.length)],this.normalize&&(t=km(t,s[0]),n=km(n,s[1])),cG(t,n,s)}interpretAxes(e,t){let n;return Array.isArray(this.axes)?n=this.axes:n=[ep(this.axes,e.length),ep(this.axes,t.length)],n}computeOutputShape(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new He("Dot layer does not support tensors of 4D or higher rank yet.");let s=this.interpretAxes(t,n);t.splice(s[0],1),n.splice(s[1],1),n.splice(0,1);let r=t.concat(n);return r.length===1&&r.push(1),r}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};Y5.className="Dot";de.registerClass(Y5);var J5=class extends ut{constructor(e){super(e),this.supportsMasking=!0,this.stddev=e.stddev}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={stddev:this.stddev};return Object.assign(t,e),t}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);return Sh(()=>ce(e2(n.shape,0,this.stddev),n),()=>n,t.training||!1)})}};J5.className="GaussianNoise";de.registerClass(J5);var Q5=class extends ut{constructor(e){super(e),this.supportsMasking=!0,this.rate=e.rate}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);return this.rate>0&&this.rate<1?Sh(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return L(n,e2(n.shape,1,r))},()=>n,t.training||!1):n})}};Q5.className="GaussianDropout";de.registerClass(Q5);var ex=class extends ut{constructor(e){super(e),this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Xe(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return J(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return Sh(()=>{let r=Xe(e),a=1.6732632423543772,o=1.0507009873554805,i=-a*o,l=li(Kc(n),this.rate);l=Q0(l,"float32");let u=((1-this.rate)*(1+this.rate*i**2))**-.5,c=-u*i*this.rate,p=ce(L(r,l),L(ce(l,-1),i));return ce(L(p,u),c)},()=>Xe(e),t.training||!1)}return e})}};ex.className="AlphaDropout";de.registerClass(ex);function Rp(e,t,n,s,r,a=.001){let o;if(e.rank===2)o=tA(e,t,n,s,r,a);else if(e.rank===3)o=nA(e,t,n,s,r,a);else if(e.rank===4)o=sA(e,t,n,s,r,a);else throw new He(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return o}function dG(e,t,n,s,r=.001){return J(()=>{let a=mh(e,s),o=a.mean,i=a.variance;return[Rp(e,o,i,n,t,r),o,i]})}function pG(e,t,n,s,r=.001){return J(()=>{let a=mh(e,s),o=a.mean,i=a.variance,l=[];for(let f of Rr(0,e.rank))s.indexOf(f)!==-1?l.push(1):l.push(e.shape[f]);let u=U(o,l),c=U(i,l),p=t==null?null:U(t,l),d=n==null?null:U(n,l);return[Rp(e,u,c,d,p,r),o,i]})}function hG(e,t,n,s,r=.001){return v.arraysEqual(s.slice().sort(),Rr(0,e.rank-1))?dG(e,t,n,s,r):pG(e,t,n,s,r)}var tx=class extends ut{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=Ot(e.betaInitializer||"zeros"),this.gammaInitializer=Ot(e.gammaInitializer||"ones"),this.movingMeanInitializer=Ot(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=Ot(e.movingVarianceInitializer||"ones"),this.betaConstraint=yn(e.betaConstraint),this.gammaConstraint=yn(e.gammaConstraint),this.betaRegularizer=Mt(e.betaRegularizer),this.gammaRegularizer=Mt(e.gammaRegularizer)}build(e){e=xt(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new j(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new rn({ndim:e.length,axes:{[t]:n}})];let s=[n];this.scale&&(this.gamma=this.addWeight("gamma",s,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",s,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",s,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",s,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return J(()=>{let n=t.training==null?!1:t.training,s=Xe(e),r=s.shape,a=r.length,o=Rr(0,a),i=this.axis>=0?this.axis:this.axis+a;o.splice(i,1);let l=el(1,a);l[i]=r[i];let u=o.slice();u.sort();let c=!v.arraysEqual(u,Rr(0,a).slice(0,a-1)),p=()=>{if(c){let y=U(this.movingMean.read(),l),x=U(this.movingVariance.read(),l),A=this.center?U(this.beta.read(),l):null,b=this.scale?U(this.gamma.read(),l):null;return Rp(s,y,x,A,b,this.epsilon)}else return Rp(s,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return p();let[d,h,f]=hG(s,this.gamma.read(),this.beta.read(),o,this.epsilon),m=(y,x,A)=>{J(()=>{let b=1-A,w=y.read(),k=L(he(w,x),b);y.write(he(w,k))})};return(()=>{m(this.movingMean,h,this.momentum),m(this.movingVariance,f,this.momentum)})(),d})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Vt(this.betaInitializer),gammaInitializer:Vt(this.gammaInitializer),movingMeanInitializer:Vt(this.movingMeanInitializer),movingVarianceInitializer:Vt(this.movingVarianceInitializer),betaRegularizer:St(this.betaRegularizer),gammaRegularizer:St(this.gammaRegularizer),betaConstraint:gn(this.betaConstraint),gammaConstraint:gn(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};tx.className="BatchNormalization";de.registerClass(tx);var nx=class extends ut{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=Ot(e.betaInitializer||"zeros"),this.gammaInitializer=Ot(e.gammaInitializer||"ones"),this.betaRegularizer=Mt(e.betaRegularizer),this.gammaRegularizer=Mt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=xt(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let r=0;r<this.axis.length;++r)this.axis[r]<0&&(this.axis[r]+=t);for(let r of this.axis)if(r<0||r>=t)throw new Error(`Invalid axis: ${r}`);if(this.axis.length!==Xa(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(r=>e[r]),s=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,s):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,s):this.beta=null,this.built=!0}call(e,t){let n=Xe(e),s=n.shape,r=s.length;return J(()=>{let{mean:o,variance:i}=mh(n,this.axis,!0),l=el(1,r);for(let f of this.axis)l[f]=s[f];let u=f=>f!=null&&f.shape.length!==r?U(f,l):f,c=this.scale?u(this.gamma.read()):null,p=this.center?u(this.beta.read()):null,d=[],h=[];for(let f=0;f<r;++f)this.axis.indexOf(f)!==-1?(d.push(s[f]),h.push(1)):(d.push(1),h.push(s[f]));return o=js(o,d),i=js(i,d),c!=null&&(c=js(c,h)),p!=null&&(p=js(p,h)),Rp(n,o,i,p,c,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Vt(this.betaInitializer),gammaInitializer:Vt(this.gammaInitializer),betaRegularizer:St(this.betaRegularizer),gammaRegularizer:St(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};nx.className="LayerNormalization";de.registerClass(nx);function fG(e,t,n){return J(()=>{if(e.rank!==4)throw new j(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new j("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=_r()),n!=="channelsLast"&&n!=="channelsFirst")throw new j(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let s;return n==="channelsFirst"?s=[[0,0],[0,0],t[0],t[1]]:s=[[0,0],t[0],t[1],[0,0]],Js(e,s)})}var sx=class extends ut{constructor(e){if(e==null&&(e={}),super(e),this.dataFormat=e.dataFormat==null?_r():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new j(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${e.padding.length} array.`);let t,n;if(typeof e.padding[0]=="number")t=[e.padding[0],e.padding[0]],n=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,e.padding[0].length!==2)throw new j(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new j(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new rn({ndim:4})]}computeOutputShape(e){e=xt(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return J(()=>fG(Xe(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};sx.className="ZeroPadding2D";de.registerClass(sx);function y2(e,t,n,s,r,a){return J(()=>{Yt(r),f8(a),Qs(s),n==null&&(n=[1,1]),s==null&&(s="valid"),r==null&&(r=_r()),a==null&&(a="max"),e=I5(e,r);let o,i=s==="same"?"same":"valid";return a==="max"?o=fh(e,t,n,i):o=lh(e,t,n,i),r==="channelsFirst"&&(o=st(o,[0,3,1,2])),o})}function uk(e,t,n,s,r,a){return J(()=>{Yt(r),f8(a),Qs(s),n==null&&(n=[1,1,1]),s==null&&(s="valid"),r==null&&(r=_r()),a==null&&(a="max"),e=rk(e,r);let o,i=s==="same"?"same":"valid";return a==="max"?o=TA(e,t,n,i):o=eA(e,t,n,i),r==="channelsFirst"&&(o=st(o,[0,4,1,2,3])),o})}var ck=class extends ut{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new j(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(vn(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new j(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);vn(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,Qs(this.padding),this.inputSpec=[new rn({ndim:3})]}computeOutputShape(e){e=xt(e);let t=Er(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return J(()=>{this.invokeCallHook(e,t),e=kh(Xe(e),2);let n=this.poolingFunction(Xe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return rt(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},rx=class extends ck{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),y2(e,t,n,s,r,"max")}};rx.className="MaxPooling1D";de.registerClass(rx);var ax=class extends ck{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),y2(e,t,n,s,r,"avg")}};ax.className="AveragePooling1D";de.registerClass(ax);var dk=class extends ut{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new j(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];vn(this.poolSize,"poolSize"),vn(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Yt(this.dataFormat),Qs(this.padding),this.inputSpec=[new rn({ndim:4})]}computeOutputShape(e){e=xt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Er(t,this.poolSize[0],this.padding,this.strides[0]),n=Er(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return J(()=>(this.invokeCallHook(e,t),this.poolingFunction(Xe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},ox=class extends dk{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),y2(e,t,n,s,r,"max")}};ox.className="MaxPooling2D";de.registerClass(ox);var ix=class extends dk{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),y2(e,t,n,s,r,"avg")}};ix.className="AveragePooling2D";de.registerClass(ix);var pk=class extends ut{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new j(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];vn(this.poolSize,"poolSize"),vn(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Yt(this.dataFormat),Qs(this.padding),this.inputSpec=[new rn({ndim:5})]}computeOutputShape(e){e=xt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],s=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Er(t,this.poolSize[0],this.padding,this.strides[0]),n=Er(n,this.poolSize[1],this.padding,this.strides[1]),s=Er(s,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,s]:[e[0],t,n,s,e[4]]}call(e,t){return J(()=>(this.invokeCallHook(e,t),this.poolingFunction(Xe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},lx=class extends pk{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),uk(e,t,n,s,r,"max")}};lx.className="MaxPooling3D";de.registerClass(lx);var ux=class extends pk{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),uk(e,t,n,s,r,"avg")}};ux.className="AveragePooling3D";de.registerClass(ux);var hk=class extends ut{constructor(e){super(e),this.inputSpec=[new rn({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new He}},cx=class extends hk{constructor(e){super(e||{})}call(e,t){return J(()=>{let n=Xe(e);return Bt(n,1)})}};cx.className="GlobalAveragePooling1D";de.registerClass(cx);var dx=class extends hk{constructor(e){super(e||{})}call(e,t){return J(()=>{let n=Xe(e);return mn(n,1)})}};dx.className="GlobalMaxPooling1D";de.registerClass(dx);var fk=class extends ut{constructor(e){super(e),this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Yt(this.dataFormat),this.inputSpec=[new rn({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new He}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},px=class extends fk{call(e,t){return J(()=>{let n=Xe(e);return this.dataFormat==="channelsLast"?Bt(n,[1,2]):Bt(n,[2,3])})}};px.className="GlobalAveragePooling2D";de.registerClass(px);var hx=class extends fk{call(e,t){return J(()=>{let n=Xe(e);return this.dataFormat==="channelsLast"?mn(n,[1,2]):mn(n,[2,3])})}};hx.className="GlobalMaxPooling2D";de.registerClass(hx);var mk=class extends ut{constructor(e){super(e),this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let s=t.layer,r=Nr(s,n);delete t.layer;let a={layer:r};return Object.assign(a,t),new e(a)}},fx=class extends mk{constructor(e){super(e),this.supportsMasking=!0}build(e){if(e=xt(e),e.length<3)throw new j(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=xt(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),s=e[1];return[n[0],s].concat(n.slice(1))}call(e,t){return J(()=>(e=Xe(e),ik((a,o)=>[Xe(this.layer.call(a,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};fx.className="TimeDistributed";de.registerClass(fx);function mG(e){eu(gV,"BidirectionalMergeMode",e)}var gG="concat",mx=class extends mk{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Nr(n),t.goBackwards=t.goBackwards!==!0;let s={};if(s.className=e.layer.getClassName(),s.config=t,this.backwardLayer=Nr(s),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?gG:e.mergeMode,mG(this.mergeMode),e.weights)throw new He("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,s,r;return this.returnState&&(r=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,s=[n]):this.mergeMode==null?s=[n,n.slice()]:s=[n],this.returnState?this.mergeMode==null?s.concat(r).concat(r.slice()):[n].concat(r).concat(r.slice()):ps(s)}apply(e,t){let n=t==null?null:t.initialState,s=t==null?null:t.constants;t==null&&(t={});let r=ok(e,n,s,this.numConstants);if(e=r.inputs,n=r.initialState,s=r.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&s==null)return super.apply(e,t);let a=[],o=[];if(n!=null){let l=n.length;if(l%2>0)throw new j("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,a.push(...n);let u=n.map(c=>new rn({shape:c.shape}));this.forwardLayer.stateSpec=u.slice(0,l/2),this.backwardLayer.stateSpec=u.slice(l/2),o.push(...u)}if(s!=null)throw new He("Support for constants in Bidirectional layers is not implemented yet.");let i=a[0]instanceof Cr;for(let l of a)if(l instanceof Cr!==i)throw new j("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(i){let l=[e].concat(a),u=this.inputSpec.concat(o),c=this.inputSpec;this.inputSpec=u;let p=super.apply(l,t);return this.inputSpec=c,p}else return super.apply(e,t)}call(e,t){return J(()=>{let n=t.initialState,s,r;if(n==null)s=this.forwardLayer.call(e,t),r=this.backwardLayer.call(e,t);else{let i=n.slice(0,n.length/2),l=n.slice(n.length/2);s=this.forwardLayer.call(e,Object.assign(t,{initialState:i})),r=this.backwardLayer.call(e,Object.assign(t,{initialState:l}))}let a;this.returnState&&(Array.isArray(s)&&(a=s.slice(1).concat(r.slice(1))),s=s[0],r=r[0]),this.returnSequences&&(r=Ks(r,1));let o;return this.mergeMode==="concat"?o=ZA([s,r]):this.mergeMode==="sum"?o=ce(s,r):this.mergeMode==="ave"?o=L(.5,ce(s,r)):this.mergeMode==="mul"?o=L(s,r):this.mergeMode==null&&(o=[s,r]),this.returnState?this.mergeMode==null?o.concat(a):[o].concat(a):o})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){Hi(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),Hi(this.backwardLayer.name,()=>{this.backwardLayer.build(e)}),this.built=!0}computeMask(e,t){Array.isArray(t)&&(t=t[0]);let n;if(this.returnSequences?this.mergeMode==null?n=[t,t]:n=t:this.mergeMode==null?n=[null,null]:n=null,this.returnState){let r=this.forwardLayer.states.map(a=>null);return Array.isArray(n)?n.concat(r).concat(r):[n].concat(r).concat(r)}else return n}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return this.forwardLayer.nonTrainableWeights.concat(this.backwardLayer.nonTrainableWeights)}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.forwardLayer!=null&&this.forwardLayer.setFastWeightInitDuringBuild(e),this.backwardLayer!=null&&this.backwardLayer.setFastWeightInitDuringBuild(e)}getConfig(){let e={mergeMode:this.mergeMode},t=super.getConfig();return Object.assign(e,t),e}static fromConfig(e,t){let n=Nr(t.layer);if(delete t.layer,t.numConstants!=null)throw new He("Deserialization of a Bidirectional layer with numConstants present is not supported yet.");let s=t;return s.layer=n,new e(s)}};mx.className="Bidirectional";de.registerClass(mx);function yG(e){return new Yc(e)}function AG(e){return new v5(e)}function xG(e){return new A5(e)}function bG(e){return new x5(e)}function vG(e){return new b5(e)}function wG(e){return new k5(e)}function kG(e){return new w5(e)}function IG(e){return new d2(e)}function SG(e){return new Eh(e)}function CG(e){return new C5(e)}function TG(e){return new Rh(e)}function NG(e){return new T5(e)}function EG(e){return new N5(e)}function RG(e){return new E5(e)}function _G(e){return new R5(e)}function DG(e){return new _5(e)}function $G(e){return new L5(e)}function PG(e){return new M5(e)}function FG(e){return new g2(e)}function OG(e){return new O5(e)}function MG(e){return new z5(e)}function zG(e){return new B5(e)}function LG(e){return new W5(e)}function BG(e){return new V5(e)}function WG(e){return new G5(e)}function VG(e){return new H5(e)}function UG(e){return new q5(e)}function GG(e){return new Z5(e)}function HG(e){return new X5(e)}function jG(e){return new K5(e)}function qG(e){return new j5(e)}function XG(e){return new Y5(e)}function KG(e){return new tx(e)}function ZG(e){return new nx(e)}function YG(e){return new sx(e)}function gx(e){return new ax(e)}function JG(e){return gx(e)}function QG(e){return gx(e)}function yx(e){return new ix(e)}function eH(e){return yx(e)}function tH(e){return yx(e)}function Ax(e){return new ux(e)}function nH(e){return Ax(e)}function sH(e){return Ax(e)}function rH(e){return new cx(e)}function aH(e){return new px(e)}function gk(e){return new dx(e)}function yk(e){return new hx(e)}function Ak(e){return new rx(e)}function xk(e){return new ox(e)}function oH(e){return new lx(e)}function iH(e){return new $5(e)}function lH(e){return new h2(e)}function uH(e){return new P5(e)}function cH(e){return new Dh(e)}function dH(e){return new D5(e)}function pH(e){return new p2(e)}function hH(e){return new F5(e)}function fH(e){return new m2(e)}function mH(e){return new Qr(e)}function gH(e){return new f2(e)}function yH(e){return new mx(e)}function AH(e){return new fx(e)}var xH=gk,bH=yk,vH=Ak,wH=xk;function kH(e){return new J5(e)}function IH(e){return new Q5(e)}function SH(e){return new ex(e)}function CH(e){return new U5(e)}var bk={};Ve(bk,{MAPE:()=>MH,MSE:()=>BH,binaryAccuracy:()=>TH,binaryCrossentropy:()=>NH,categoricalAccuracy:()=>RH,categoricalCrossentropy:()=>_H,cosineProximity:()=>PH,mape:()=>zH,meanAbsoluteError:()=>FH,meanAbsolutePercentageError:()=>OH,meanSquaredError:()=>LH,mse:()=>WH,precision:()=>DH,recall:()=>$H,sparseCategoricalAccuracy:()=>EH});function TH(e,t){return d5(e,t)}function NH(e,t){return P8(e,t)}function EH(e,t){return F8(e,t)}function RH(e,t){return p5(e,t)}function _H(e,t){return h5(e,t)}function DH(e,t){return $8(e,t)}function $H(e,t){return bU(e,t)}function PH(e,t){return c5(e,t)}function FH(e,t){return u2(e,t)}function OH(e,t){return Jc(e,t)}function MH(e,t){return Jc(e,t)}function zH(e,t){return Jc(e,t)}function LH(e,t){return tu(e,t)}function BH(e,t){return tu(e,t)}function WH(e,t){return tu(e,t)}var vk={};Ve(vk,{modelFromJSON:()=>ZU});var wk={};Ve(wk,{l1:()=>UH,l1l2:()=>VH,l2:()=>GH});function VH(e){return new Th(e)}function UH(e){return rG(e)}function GH(e){return aG(e)}var kk=class extends nc{constructor(){super(...arguments),this.model=null}setModel(e){if(!(e instanceof ha))throw new Error("model must be a LayersModel, not some other Container");this.model=e}};function Hf(e,t){return e<t}function Yv(e,t){return e>t}var Ik=class extends kk{constructor(e){if(super(),e==null&&(e={}),e.restoreBestWeights)throw new He("restoreBestWeights = True is not implemented in EarlyStopping yet.");this.monitor=e.monitor||"val_loss",this.minDelta=Math.abs(e.minDelta||0),this.patience=e.patience||0,this.verbose=e.verbose||0,this.mode=e.mode||"auto",this.baseline=e.baseline,["auto","min","max"].indexOf(this.mode)===-1&&(console.warn(`EarlyStopping mode '${this.mode}' is invalid. Falling back to mode 'auto'.`),this.mode="auto"),this.mode==="min"?this.monitorFunc=Hf:this.mode==="max"?this.monitorFunc=Yv:this.monitor.indexOf("acc")!==-1?this.monitorFunc=Yv:this.monitorFunc=Hf,this.monitorFunc===Hf&&(this.minDelta*=-1)}async onTrainBegin(e){this.wait=0,this.stoppedEpoch=0,this.baseline!=null?this.best=this.baseline:this.best=this.monitorFunc===Hf?1/0:-1/0}async onEpochEnd(e,t){await Va(t);let n=this.getMonitorValue(t);n!=null&&(this.monitorFunc(n-this.minDelta,this.best)?(this.best=n,this.wait=0):(this.wait++,this.wait>=this.patience&&(this.stoppedEpoch=e,this.model.stopTraining=!0)))}async onTrainEnd(e){this.stoppedEpoch>0&&this.verbose&&console.log(`Epoch ${this.stoppedEpoch}: early stopping.`)}getMonitorValue(e){e==null&&(e={});let t=e[this.monitor];return t==null&&console.warn(`Metric for EarlyStopping ${this.monitor} is not available. Available metrics are: ${Object.keys(e)}`),t}};function HH(e){return new Ik(e)}var jH={earlyStopping:HH},qH=Z();qH.registerFlag("KEEP_INTERMEDIATE_TENSORS",()=>!1,e=>{e&&console.warn("Keep intermediate tensors is ON. This will print the values of all intermediate tensors during model inference. Not all models support this mode. For details, check e2e/benchmarks/ model_config.js. This significantly impacts performance.")});var sr;(function(e){e[e.DT_INVALID=0]="DT_INVALID",e[e.DT_FLOAT=1]="DT_FLOAT",e[e.DT_DOUBLE=2]="DT_DOUBLE",e[e.DT_INT32=3]="DT_INT32",e[e.DT_UINT8=4]="DT_UINT8",e[e.DT_INT16=5]="DT_INT16",e[e.DT_INT8=6]="DT_INT8",e[e.DT_STRING=7]="DT_STRING",e[e.DT_COMPLEX64=8]="DT_COMPLEX64",e[e.DT_INT64=9]="DT_INT64",e[e.DT_BOOL=10]="DT_BOOL",e[e.DT_QINT8=11]="DT_QINT8",e[e.DT_QUINT8=12]="DT_QUINT8",e[e.DT_QINT32=13]="DT_QINT32",e[e.DT_BFLOAT16=14]="DT_BFLOAT16",e[e.DT_QINT16=15]="DT_QINT16",e[e.DT_QUINT16=16]="DT_QUINT16",e[e.DT_UINT16=17]="DT_UINT16",e[e.DT_COMPLEX128=18]="DT_COMPLEX128",e[e.DT_HALF=19]="DT_HALF",e[e.DT_RESOURCE=20]="DT_RESOURCE",e[e.DT_VARIANT=21]="DT_VARIANT",e[e.DT_UINT32=22]="DT_UINT32",e[e.DT_UINT64=23]="DT_UINT64",e[e.DT_FLOAT_REF=101]="DT_FLOAT_REF",e[e.DT_DOUBLE_REF=102]="DT_DOUBLE_REF",e[e.DT_INT32_REF=103]="DT_INT32_REF",e[e.DT_UINT8_REF=104]="DT_UINT8_REF",e[e.DT_INT16_REF=105]="DT_INT16_REF",e[e.DT_INT8_REF=106]="DT_INT8_REF",e[e.DT_STRING_REF=107]="DT_STRING_REF",e[e.DT_COMPLEX64_REF=108]="DT_COMPLEX64_REF",e[e.DT_INT64_REF=109]="DT_INT64_REF",e[e.DT_BOOL_REF=110]="DT_BOOL_REF",e[e.DT_QINT8_REF=111]="DT_QINT8_REF",e[e.DT_QUINT8_REF=112]="DT_QUINT8_REF",e[e.DT_QINT32_REF=113]="DT_QINT32_REF",e[e.DT_BFLOAT16_REF=114]="DT_BFLOAT16_REF",e[e.DT_QINT16_REF=115]="DT_QINT16_REF",e[e.DT_QUINT16_REF=116]="DT_QUINT16_REF",e[e.DT_UINT16_REF=117]="DT_UINT16_REF",e[e.DT_COMPLEX128_REF=118]="DT_COMPLEX128_REF",e[e.DT_HALF_REF=119]="DT_HALF_REF",e[e.DT_RESOURCE_REF=120]="DT_RESOURCE_REF",e[e.DT_VARIANT_REF=121]="DT_VARIANT_REF",e[e.DT_UINT32_REF=122]="DT_UINT32_REF",e[e.DT_UINT64_REF=123]="DT_UINT64_REF"})(sr||(sr={}));var Jv;(function(e){let t;(function(n){n[n.LEGACY=0]="LEGACY",n[n.V1=1]="V1",n[n.V2=2]="V2"})(t=e.CheckpointFormatVersion||(e.CheckpointFormatVersion={}))})(Jv||(Jv={}));var xx={};function XH(e,t){let n={tfOpName:e,category:"custom",inputs:[],attrs:[],customExecutor:t};xx[e]=n}function Sk(e){return xx[e]}function KH(e){delete xx[e]}function I(e,t,n,s,r){let a=t.inputParams[e];if(a&&a.inputIndexStart!==void 0){let i=a.inputIndexStart,l=a.inputIndexEnd===0?void 0:a.inputIndexEnd===void 0?i+1:a.inputIndexEnd;if(a.type==="tensor")return Jn(t.inputNames[a.inputIndexStart],n,s,r);if(a.type==="tensors")return t.inputNames.slice(i,l).map(d=>Jn(d,n,s,r));let u=Jn(t.inputNames.slice(i)[0],n,s,r),c=u.dataSync();return a.type==="number"?c[0]:v.toNestedArray(u.shape,c)}let o=t.attrParams[e];return o&&o.value}function Jn(e,t,n,s){let[r,a]=Ss(e);if(s!=null){let i=s.getHashTableHandleByName(r);if(i!=null)return i}let o=n.currentContextIds.find(i=>!!t[Nm(r,i)]);return o!==void 0?t[Nm(r,o)][a]:void 0}function ZH(e,t,n){return t[Nm(e,n.currentContextId)]}function Gr(e,t){let[n,s,r]=Ss(e);return[Nm(n,t&&t.currentContextId),s,r]}function Nm(e,t){return t?`${e}-${t}`:e}function Ss(e){let t=e.split(":");if(t.length===1)return[e,0,void 0];let n=t[0],s=t.length===3?t[1]:void 0,r=Number(t[t.length-1]);return[n,r,s]}function tm(e,t,n){let s=I("pad",e,t,n);if(s==="explicit"){s=I("explicitPaddings",e,t,n);let r=[[0,0],[0,0],[0,0],[0,0]];for(let a=0;a<4;a++)r[a][0]=s[a*2],r[a][1]=s[a*2+1];return r}return s}function ca(e){return e.kept?e:Fn(e)}var Ck={};Ve(Ck,{json:()=>YH});var YH=[{tfOpName:"Add",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"AddV2",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"AddN",category:"arithmetic",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}]},{tfOpName:"BiasAdd",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"Sub",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"RealDiv",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Div",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"DivNoNan",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"FloorDiv",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Mul",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Maximum",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Minimum",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Pow",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"SquaredDifference",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Mod",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"FloorMod",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],Tk={};Ve(Tk,{json:()=>JH});var JH=[{tfOpName:"Abs",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Acos",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Asin",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Atan",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Atan2",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"y",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Ceil",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ClipByValue",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"clipValueMin",type:"number"},{start:2,name:"clipValueMax",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Complex",category:"basic_math",inputs:[{start:0,name:"real",type:"tensor"},{start:1,name:"imag",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ComplexAbs",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Cos",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Cosh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Elu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Exp",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Floor",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Log",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Imag",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"Tout",name:"outputType",type:"dtype",notSupported:!0}]},{tfOpName:"Neg",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Real",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"Tout",name:"outputType",type:"dtype",notSupported:!0}]},{tfOpName:"Prelu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"alpha",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Relu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Relu6",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Selu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sigmoid",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sin",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sinh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sqrt",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Rsqrt",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Square",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Tan",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Tanh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sign",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Round",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Expm1",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Log1p",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Reciprocal",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Softplus",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Asinh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Acosh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Atanh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Erf",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Prod",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axes",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool",notSupported:!0},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LeakyRelu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"alpha",name:"alpha",type:"number",defaultValue:.2},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"IsNan",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],Nk={};Ve(Nk,{json:()=>QH});var QH=[{tfOpName:"EmptyTensorList",category:"control",inputs:[{start:0,name:"elementShape",type:"shape"},{start:1,name:"maxNumElements",type:"number"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"LoopCond",category:"control",inputs:[{start:0,name:"pred",type:"tensor"}]},{tfOpName:"Switch",category:"control",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"pred",type:"tensor"}]},{tfOpName:"Merge",category:"control",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}]},{tfOpName:"Enter",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"frame_name",name:"frameName",type:"string"},{tfName:"is_constant",name:"isConstant",type:"bool"}]},{tfOpName:"Exit",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"NextIteration",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"TensorArrayV3",category:"control",inputs:[{start:0,name:"size",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"element_shape",name:"elementShape",type:"shape"},{tfName:"dynamic_size",name:"dynamicSize",type:"bool"},{tfName:"clear_after_read",name:"clearAfterRead",type:"bool"},{tfName:"identical_element_shapes",name:"identicalElementShapes",type:"bool"},{tfName:"tensor_array_name",name:"name",type:"string"}]},{tfOpName:"TensorArrayWriteV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"tensor",type:"tensor"},{start:3,name:"flowIn",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"TensorArrayReadV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"flowIn",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"TensorArrayGatherV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"flowIn",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"element_shape",name:"elementShape",type:"shape"}]},{tfOpName:"TensorArrayScatterV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"tensor",type:"tensor"},{start:3,name:"flowIn",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"TensorArrayConcatV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"flowIn",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"element_shape_except0",name:"elementShapeExcept0",type:"shape",notSupported:!0}]},{tfOpName:"TensorArraySplitV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"tensor",type:"tensor"},{start:2,name:"lengths",type:"number[]"},{start:3,name:"flowIn",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"TensorArraySizeV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"flowIn",type:"number"}]},{tfOpName:"TensorArrayCloseV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"}]},{tfOpName:"StatelessIf",category:"control",inputs:[{start:0,name:"cond",type:"tensor"},{start:1,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"then_branch",name:"thenBranch",type:"func"},{tfName:"else_branch",name:"elseBranch",type:"func"}]},{tfOpName:"If",category:"control",inputs:[{start:0,name:"cond",type:"tensor"},{start:1,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"then_branch",name:"thenBranch",type:"func"},{tfName:"else_branch",name:"elseBranch",type:"func"}]},{tfOpName:"StatelessWhile",category:"control",inputs:[{start:0,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"cond",name:"cond",type:"func"},{tfName:"body",name:"body",type:"func"}]},{tfOpName:"While",category:"control",inputs:[{start:0,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"cond",name:"cond",type:"func"},{tfName:"body",name:"body",type:"func"}]},{tfOpName:"TensorListScatter",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListScatterV2",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"elementShape",type:"shape"},{start:3,name:"numElements",type:"number"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListGather",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListGetItem",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListSetItem",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"tensor",type:"tensor"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListReserve",category:"control",inputs:[{start:0,name:"elementShape",type:"shape"},{start:1,name:"numElements",type:"number"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListFromTensor",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListStack",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"},{tfName:"num_elements",name:"numElements",type:"dtype"}]},{tfOpName:"TensorListSplit",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"elementShape",type:"shape"},{start:2,name:"lengths",type:"number[]"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListConcat",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"}],attrs:[{tfName:"element_shape",name:"elementShape",type:"shape"},{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListConcatV2",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"}],attrs:[{tfName:"element_shape",name:"elementShape",type:"shape"},{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListPopBack",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListPushBack",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"tensor",type:"tensor"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListLength",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"}]},{tfOpName:"TensorListResize",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"size",type:"number"}]}],Ek={};Ve(Ek,{json:()=>ej});var ej=[{tfOpName:"AvgPool",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MaxPool",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[],notSupported:!0},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MaxPoolWithArgmax",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"include_batch_in_index",name:"includeBatchInIndex",type:"bool"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"AvgPool3D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MaxPool3D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Conv1D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"stride",name:"stride",type:"number"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NWC"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"dilation",name:"dilation",type:"number",defaultValue:1}]},{tfOpName:"Conv2D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"useCudnnOnGpu",name:"useCudnnOnGpu",type:"bool"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"_FusedConv2D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"},{start:2,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"num_args",name:"numArgs",type:"number"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"use_cudnn_on_gpu",name:"useCudnnOnGpu",type:"bool",defaultValue:!0},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"dilations",name:"dilations",type:"number[]",defaultValue:[1,1,1,1]},{tfName:"fused_ops",name:"fusedOps",type:"string[]",defaultValue:[]},{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:1e-4},{tfName:"leakyrelu_alpha",name:"leakyreluAlpha",type:"number",defaultValue:.2}]},{tfOpName:"Conv2DBackpropInput",category:"convolution",inputs:[{start:2,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"},{start:0,name:"outputShape",type:"number[]"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]",notSupported:!0}]},{tfOpName:"DepthwiseConv2d",category:"convolution",inputs:[{start:0,name:"input",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"DepthwiseConv2dNative",category:"convolution",inputs:[{start:0,name:"input",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"FusedDepthwiseConv2dNative",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"},{start:2,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"num_args",name:"numArgs",type:"number"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"dilations",name:"dilations",type:"number[]",defaultValue:[1,1,1,1]},{tfName:"fused_ops",name:"fusedOps",type:"string[]",defaultValue:[]},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]}]},{tfOpName:"Conv3D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"Dilation2D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"rates",name:"dilations",type:"number[]"},{tfName:"padding",name:"pad",type:"string"}]}],Rk={};Ve(Rk,{json:()=>tj});var tj=[{tfOpName:"Fill",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"},{start:1,name:"value",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"LinSpace",category:"creation",inputs:[{start:0,name:"start",type:"number"},{start:1,name:"stop",type:"number"},{start:2,name:"num",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"OneHot",category:"creation",inputs:[{start:0,name:"indices",type:"tensor"},{start:1,name:"depth",type:"number"},{start:2,name:"onValue",type:"number",defaultValue:1},{start:3,name:"offValue",type:"number",defaultValue:0}],attrs:[{tfName:"axis",name:"axis",type:"number",notSupported:!0},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Ones",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"OnesLike",category:"creation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"}]},{tfOpName:"RandomStandardNormal",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"seed",name:"seed",type:"number",defaultValue:0},{tfName:"seed2",name:"seed2",type:"number",defaultValue:0,notSupported:!0},{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"T",name:"T",type:"number",notSupported:!0}]},{tfOpName:"RandomUniform",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"minval",name:"minval",type:"number",defaultValue:0},{tfName:"maxval",name:"maxval",type:"number",defaultValue:1},{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"seed",name:"seed",type:"number",defaultValue:0},{tfName:"seed2",name:"seed2",type:"number",defaultValue:0,notSupported:!0},{tfName:"T",name:"T",type:"number",notSupported:!0}]},{tfOpName:"Range",category:"creation",inputs:[{start:0,name:"start",type:"number"},{start:1,name:"stop",type:"number"},{start:2,name:"step",type:"number",defaultValue:0}],attrs:[{tfName:"Tidx",name:"dtype",type:"dtype"}]},{tfOpName:"TruncatedNormal",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"means",name:"mean",type:"number",defaultValue:0},{tfName:"stddev",name:"stdDev",type:"number",defaultValue:1},{tfName:"seed",name:"seed",type:"number"},{tfName:"seed2",name:"seed2",type:"number",defaultValue:0,notSupported:!0},{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"T",name:"T",type:"number",notSupported:!0}]},{tfOpName:"Zeros",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"ZerosLike",category:"creation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"Multinomial",category:"creation",inputs:[{start:0,name:"logits",type:"tensor"},{start:1,name:"numSamples",type:"number"}],attrs:[{tfName:"seed",name:"seed",type:"number"},{tfName:"seed2",name:"seed2",type:"number"},{tfName:"T",name:"dtype",type:"dtype"},{tfName:"output_dtype",name:"output_dtype",type:"dtype"}]}],_k={};Ve(_k,{json:()=>nj});var nj=[{tfOpName:"NonMaxSuppressionV2",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"}]},{tfOpName:"NonMaxSuppressionV3",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"},{start:4,name:"scoreThreshold",type:"number"}]},{tfOpName:"NonMaxSuppressionV4",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"},{start:4,name:"scoreThreshold",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"T_threshold",name:"threshold",type:"dtype",notSupported:!0},{tfName:"pad_to_max_output_size",name:"padToMaxOutputSize",type:"bool"}]},{tfOpName:"NonMaxSuppressionV5",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"},{start:4,name:"scoreThreshold",type:"number"},{start:5,name:"softNmsSigma",type:"number"}]},{tfOpName:"Where",category:"dynamic",inputs:[{start:0,name:"condition",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ListDiff",category:"dynamic",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"y",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],Dk={};Ve(Dk,{json:()=>sj});var sj=[{tfOpName:"LowerBound",category:"evaluation",inputs:[{start:0,name:"sortedSequence",type:"tensor"},{start:1,name:"values",type:"tensor"}]},{tfOpName:"TopKV2",category:"evaluation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"k",type:"number"}],attrs:[{tfName:"sorted",name:"sorted",type:"bool"}]},{tfOpName:"UpperBound",category:"evaluation",inputs:[{start:0,name:"sortedSequence",type:"tensor"},{start:1,name:"values",type:"tensor"}]},{tfOpName:"Unique",category:"evaluation",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"UniqueV2",category:"evaluation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]}],$k={};Ve($k,{json:()=>rj});var rj=[{tfOpName:"PlaceholderWithDefault",category:"graph",inputs:[{start:0,name:"default",type:"tensor"}],attrs:[{tfName:"shape",name:"shape",type:"shape"},{tfName:"dtype",name:"dtype",type:"dtype"}]},{tfOpName:"Placeholder",category:"graph",attrs:[{tfName:"shape",name:"shape",type:"shape"},{tfName:"dtype",name:"dtype",type:"dtype"}]},{tfOpName:"Const",category:"graph"},{tfOpName:"Identity",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"IdentityN",category:"graph",inputs:[{start:0,end:0,name:"x",type:"tensors"}]},{tfOpName:"Snapshot",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"Rank",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"Size",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"Shape",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"ShapeN",category:"graph",inputs:[{start:0,end:0,name:"x",type:"tensors"}]},{tfOpName:"Print",category:"graph",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"data",type:"tensors"}],attrs:[{tfName:"message",name:"message",type:"string"},{tfName:"first_n",name:"firstN",type:"number",notSupported:!0},{tfName:"summarize",name:"summarize",type:"number",defaultValue:3}]},{tfOpName:"NoOp",category:"graph",inputs:[]},{tfOpName:"StopGradient",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"FakeQuantWithMinMaxVars",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"min",name:"min",type:"number"},{tfName:"max",name:"max",type:"number"}]}],Pk={};Ve(Pk,{json:()=>aj});var aj=[{tfOpName:"HashTable",category:"hash_table",inputs:[],attrs:[{tfName:"shared_name",name:"sharedName",type:"string"},{tfName:"use_node_name_sharing",name:"useNodeNameSharing",type:"bool"},{tfName:"key_dtype",name:"keyDType",type:"dtype"},{tfName:"value_dtype",name:"valueDType",type:"dtype"}]},{tfOpName:"HashTableV2",category:"hash_table",inputs:[],attrs:[{tfName:"shared_name",name:"sharedName",type:"string"},{tfName:"use_node_name_sharing",name:"useNodeNameSharing",type:"bool"},{tfName:"key_dtype",name:"keyDType",type:"dtype"},{tfName:"value_dtype",name:"valueDType",type:"dtype"}]},{tfOpName:"LookupTableImport",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"values",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableImportV2",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"values",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableFind",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableFindV2",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableSize",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"}]},{tfOpName:"LookupTableSizeV2",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"}]}],Fk={};Ve(Fk,{json:()=>oj});var oj=[{tfOpName:"ResizeBilinear",category:"image",inputs:[{start:0,name:"images",type:"tensor"},{start:1,name:"size",type:"number[]"}],attrs:[{tfName:"align_corners",name:"alignCorners",type:"bool"},{tfName:"half_pixel_centers",name:"halfPixelCenters",type:"bool"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ResizeNearestNeighbor",category:"image",inputs:[{start:0,name:"images",type:"tensor"},{start:1,name:"size",type:"number[]"}],attrs:[{tfName:"align_corners",name:"alignCorners",type:"bool"},{tfName:"half_pixel_centers",name:"halfPixelCenters",type:"bool"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"CropAndResize",category:"image",inputs:[{start:0,name:"image",type:"tensor"},{start:1,name:"boxes",type:"tensor"},{start:2,name:"boxInd",type:"tensor"},{start:3,name:"cropSize",type:"number[]"}],attrs:[{tfName:"method",name:"method",type:"string"},{tfName:"extrapolation_value",name:"extrapolationValue",type:"number"}]},{tfOpName:"ImageProjectiveTransformV3",category:"image",inputs:[{start:0,name:"images",type:"tensor"},{start:1,name:"transforms",type:"tensor"},{start:2,name:"outputShape",type:"number[]"},{start:3,name:"fillValue",type:"number"}],attrs:[{tfName:"interpolation",name:"interpolation",type:"string"},{tfName:"fill_mode",name:"fillMode",type:"string"}]}],Ok={};Ve(Ok,{json:()=>ij});var ij=[{tfOpName:"Equal",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"NotEqual",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Greater",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"GreaterEqual",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Less",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LessEqual",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalAnd",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalNot",category:"logical",inputs:[{start:0,name:"a",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalOr",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Select",category:"logical",inputs:[{start:0,name:"condition",type:"tensor"},{start:1,name:"a",type:"tensor"},{start:2,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"SelectV2",category:"logical",inputs:[{start:0,name:"condition",type:"tensor"},{start:1,name:"a",type:"tensor"},{start:2,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],Mk={};Ve(Mk,{json:()=>lj});var lj=[{tfOpName:"_FusedMatMul",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"},{start:2,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"num_args",name:"numArgs",type:"number"},{tfName:"fused_ops",name:"fusedOps",type:"string[]",defaultValue:[]},{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:1e-4},{tfName:"transpose_a",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"transpose_b",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"leakyrelu_alpha",name:"leakyreluAlpha",type:"number",defaultValue:.2},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MatMul",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"transpose_a",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"transpose_b",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"BatchMatMul",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"adj_x",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"adj_y",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"BatchMatMulV2",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"adj_x",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"adj_y",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Transpose",category:"matrices",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"perm",type:"number[]"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Einsum",category:"matrices",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}],attrs:[{tfName:"equation",name:"equation",type:"string"},{tfName:"N",name:"n",type:"number",defaultValue:2},{tfName:"T",name:"dtype",type:"dtype"}]}],zk={};Ve(zk,{json:()=>uj});var uj=[{tfOpName:"EuclideanNorm",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool",defaultValue:!1}]},{tfOpName:"FusedBatchNorm",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"scale",type:"tensor"},{start:2,name:"offset",type:"tensor"},{start:3,name:"mean",type:"tensor"},{start:4,name:"variance",type:"tensor"}],attrs:[{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:.001},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"FusedBatchNormV2",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"scale",type:"tensor"},{start:2,name:"offset",type:"tensor"},{start:3,name:"mean",type:"tensor"},{start:4,name:"variance",type:"tensor"}],attrs:[{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:.001},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"FusedBatchNormV3",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"scale",type:"tensor"},{start:2,name:"offset",type:"tensor"},{start:3,name:"mean",type:"tensor"},{start:4,name:"variance",type:"tensor"}],attrs:[{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:.001},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"LRN",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"depth_radius",name:"radius",type:"number",defaultValue:5},{tfName:"bias",name:"bias",type:"number",defaultValue:1},{tfName:"alpha",name:"alpha",type:"number",defaultValue:1},{tfName:"beta",name:"beta",type:"number",defaultValue:.5}]},{tfOpName:"Softmax",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"LogSoftmax",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"SparseToDense",category:"normalization",inputs:[{start:0,name:"sparseIndices",type:"tensor"},{start:1,name:"outputShape",type:"number[]"},{start:2,name:"sparseValues",type:"tensor"},{start:3,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"validate_indices",name:"validateIndices",type:"bool",defaultValue:!0,notSupported:!0}]}],Lk={};Ve(Lk,{json:()=>cj});var cj=[{tfOpName:"Bincount",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"size",type:"number"},{start:2,name:"weights",type:"tensor"}]},{tfOpName:"DenseBincount",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"size",type:"number"},{start:2,name:"weights",type:"tensor"}],attrs:[{tfName:"binary_output",name:"binaryOutput",type:"bool"}]},{tfOpName:"Max",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Mean",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Min",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Sum",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"All",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Any",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"ArgMax",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]},{tfOpName:"ArgMin",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]},{tfOpName:"Prod",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Cumprod",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}],attrs:[{tfName:"exclusive",name:"exclusive",type:"bool"},{tfName:"reverse",name:"reverse",type:"bool"}]},{tfOpName:"Cumsum",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}],attrs:[{tfName:"exclusive",name:"exclusive",type:"bool"},{tfName:"reverse",name:"reverse",type:"bool"}]}],Bk={};Ve(Bk,{json:()=>dj});var dj=[{tfOpName:"ConcatV2",category:"slice_join",inputs:[{start:0,end:-1,name:"tensors",type:"tensors"},{start:-1,name:"axis",type:"number"}],attrs:[{tfName:"N",name:"n",type:"number",defaultValue:2}]},{tfOpName:"Concat",category:"slice_join",inputs:[{start:1,end:0,name:"tensors",type:"tensors"},{start:0,name:"axis",type:"number"}],attrs:[{tfName:"N",name:"n",type:"number",defaultValue:2}]},{tfOpName:"GatherV2",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"indices",type:"tensor"},{start:2,name:"axis",type:"number",defaultValue:0}],attrs:[{tfName:"batch_dims",name:"batchDims",type:"number",defaultValue:0}]},{tfOpName:"Gather",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"indices",type:"tensor"}],attrs:[{tfName:"validate_indices",name:"validateIndices",type:"bool",notSupported:!0}]},{tfOpName:"Reverse",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"dims",type:"bool[]"}]},{tfOpName:"ReverseV2",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}]},{tfOpName:"Slice",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"begin",type:"number[]"},{start:2,name:"size",type:"number[]"}]},{tfOpName:"StridedSlice",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"begin",type:"number[]"},{start:2,name:"end",type:"number[]"},{start:3,name:"strides",type:"number[]"}],attrs:[{tfName:"begin_mask",name:"beginMask",type:"number",defaultValue:0},{tfName:"end_mask",name:"endMask",type:"number",defaultValue:0},{tfName:"new_axis_mask",name:"newAxisMask",type:"number",defaultValue:0},{tfName:"ellipsis_mask",name:"ellipsisMask",type:"number",defaultValue:0},{tfName:"shrink_axis_mask",name:"shrinkAxisMask",type:"number",defaultValue:0}]},{tfOpName:"Pack",category:"slice_join",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}],attrs:[{tfName:"axis",name:"axis",type:"number",defaultValue:0}]},{tfOpName:"Unpack",category:"slice_join",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"axis",name:"axis",type:"number",defaultValue:0},{tfName:"num",name:"num",type:"number",defaultValue:0,notSupported:!0}]},{tfOpName:"Tile",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"reps",type:"number[]"}]},{tfOpName:"Split",category:"slice_join",inputs:[{start:0,name:"axis",type:"number",defaultValue:0},{start:1,name:"x",type:"tensor"}],attrs:[{tfName:"num_split",name:"numOrSizeSplits",type:"number",defaultValue:1}]},{tfOpName:"SplitV",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"numOrSizeSplits",type:"number[]"},{start:2,name:"axis",type:"number",defaultValue:0}]},{tfOpName:"ScatterNd",category:"slice_join",inputs:[{start:0,name:"indices",type:"tensor"},{start:1,name:"values",type:"tensor"},{start:2,name:"shape",type:"number[]"}]},{tfOpName:"GatherNd",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"indices",type:"tensor"}]},{tfOpName:"SparseToDense",category:"slice_join",inputs:[{start:0,name:"sparseIndices",type:"tensor"},{start:1,name:"outputShape",type:"number[]"},{start:2,name:"sparseValues",type:"tensor"},{start:3,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"validate_indices",name:"validateIndices",type:"bool",defaultValue:!1,notSupported:!0}]}],Wk={};Ve(Wk,{json:()=>pj});var pj=[{tfOpName:"SparseFillEmptyRows",category:"sparse",inputs:[{start:0,name:"indices",type:"tensor"},{start:1,name:"values",type:"tensor"},{start:2,name:"denseShape",type:"tensor"},{start:3,name:"defaultValue",type:"tensor"}]},{tfOpName:"SparseReshape",category:"sparse",inputs:[{start:0,name:"inputIndices",type:"tensor"},{start:1,name:"inputShape",type:"tensor"},{start:2,name:"newShape",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"SparseSegmentMean",category:"sparse",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"indices",type:"tensor"},{start:2,name:"segmentIds",type:"tensor"}]},{tfOpName:"SparseSegmentSum",category:"sparse",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"indices",type:"tensor"},{start:2,name:"segmentIds",type:"tensor"}]}],Vk={};Ve(Vk,{json:()=>hj});var hj=[{tfOpName:"FFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"IFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"RFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"fft_length",type:"number",notSupported:!0}]},{tfOpName:"IRFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"fft_length",type:"number",notSupported:!0}]}],Uk={};Ve(Uk,{json:()=>fj});var fj=[{tfOpName:"StringNGrams",category:"string",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"dataSplits",type:"tensor"}],attrs:[{tfName:"separator",name:"separator",type:"string"},{tfName:"ngram_widths",name:"nGramWidths",type:"number[]"},{tfName:"left_pad",name:"leftPad",type:"string"},{tfName:"right_pad",name:"rightPad",type:"string"},{tfName:"pad_width",name:"padWidth",type:"number"},{tfName:"preserve_short_sequences",name:"preserveShortSequences",type:"bool"}],outputs:["ngrams","ngrams_splits"]},{tfOpName:"StringSplit",category:"string",inputs:[{start:0,name:"input",type:"tensor"},{start:1,name:"delimiter",type:"tensor"}],attrs:[{tfName:"skip_empty",name:"skipEmpty",type:"bool"}],outputs:["indices","values","shape"]},{tfOpName:"StringToHashBucketFast",category:"string",inputs:[{start:0,name:"input",type:"tensor"}],attrs:[{tfName:"num_buckets",name:"numBuckets",type:"number"}]}],Gk={};Ve(Gk,{json:()=>mj});var mj=[{tfOpName:"Cast",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"SrcT",name:"sdtype",type:"dtype",notSupported:!0},{tfName:"DstT",name:"dtype",type:"dtype"}]},{tfOpName:"ExpandDims",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]},{tfOpName:"MirrorPad",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"}],attrs:[{tfName:"mode",name:"mode",type:"string"}]},{tfOpName:"Pad",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"}],attrs:[{tfName:"constant_value",name:"constantValue",type:"number",defaultValue:0}]},{tfOpName:"PadV2",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"},{start:2,name:"constantValue",type:"number",defaultValue:0}]},{tfOpName:"Reshape",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"shape",type:"number[]"}]},{tfOpName:"Squeeze",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"axis",tfDeprecatedName:"squeeze_dims",name:"axis",type:"number[]"}]},{tfOpName:"SpaceToBatchND",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"blockShape",type:"number[]"},{start:2,name:"paddings",type:"number[]"}]},{tfOpName:"BatchToSpaceND",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"blockShape",type:"number[]"},{start:2,name:"crops",type:"number[]"}]},{tfOpName:"DepthToSpace",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"block_size",name:"blockSize",type:"number"},{tfName:"data_format",name:"dataFormat",type:"string"}]},{tfOpName:"BroadcastTo",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"shape",type:"number[]"}],attrs:[]},{tfOpName:"BroadcastArgs",category:"transformation",inputs:[{start:0,name:"s0",type:"tensor"},{start:1,name:"s1",type:"tensor"}],attrs:[]}],Qv=class{static get Instance(){return this._instance||(this._instance=new this)}constructor(){let e=[Ck,Tk,Nk,Ek,Rk,_k,Dk,$k,Pk,Fk,Ok,Mk,zk,Lk,Bk,Wk,Vk,Uk,Gk],t=[].concat(...e.map(n=>n.json));this.opMappers=t.reduce((n,s)=>(n[s.tfOpName]=s,n),{})}transformGraph(e,t={}){let n=e.node,s=[],r=[],a=[],o=n.reduce((f,m)=>(f[m.name]=this.mapNode(m),m.op.startsWith("Placeholder")?s.push(f[m.name]):m.op==="Const"?r.push(f[m.name]):(m.input==null||m.input.length===0)&&a.push(f[m.name]),f),{}),i=[],l=[],u={},c={};t!=null&&(u=this.mapSignatureEntries(t.inputs),c=this.mapSignatureEntries(t.outputs));let p=Object.keys(o);p.forEach(f=>{let m=o[f];m.inputNames.forEach((g,y)=>{let[x,,A]=Gr(g),b=o[x];if(b.outputs!=null){let w=b.outputs.indexOf(A);if(w!==-1){let k=`${x}:${w}`;m.inputNames[y]=k}}m.inputs.push(b),b.children.push(m)})}),Object.keys(c).length===0?p.forEach(f=>{let m=o[f];m.children.length===0&&l.push(m)}):Object.keys(c).forEach(f=>{let[m]=Gr(f),g=o[m];g!=null&&(g.signatureKey=c[f],l.push(g))}),Object.keys(u).length>0?Object.keys(u).forEach(f=>{let[m]=Gr(f),g=o[m];g&&(g.signatureKey=u[f],i.push(g))}):i=s;let d={};e.library!=null&&e.library.function!=null&&(d=e.library.function.reduce((f,m)=>(f[m.signature.name]=this.mapFunction(m),f),{}));let h={nodes:o,inputs:i,outputs:l,weights:r,placeholders:s,signature:t,functions:d};return a.length>0&&(h.initNodes=a),h}mapSignatureEntries(e){return Object.keys(e||{}).reduce((t,n)=>(t[e[n].name]=n,t),{})}mapNode(e){let t=Sk(e.op)||this.opMappers[e.op]||{};e.attr==null&&(e.attr={});let n={name:e.name,op:e.op,category:t.category,inputNames:(e.input||[]).map(s=>s.startsWith("^")?s.slice(1):s),inputs:[],children:[],inputParams:{},attrParams:{},rawAttrs:e.attr,outputs:t.outputs};return t.inputs!=null&&(n.inputParams=t.inputs.reduce((s,r)=>(s[r.name]={type:r.type,inputIndexStart:r.start,inputIndexEnd:r.end},s),{})),t.attrs!=null&&(n.attrParams=t.attrs.reduce((s,r)=>{let a=r.type,o;switch(r.type){case"string":o=V3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=V3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"string[]":o=K3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=K3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"number":o=G3(e.attr,r.tfName,r.defaultValue||0),o===void 0&&!!r.tfDeprecatedName&&(o=G3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"number[]":o=X3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=X3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"bool":o=U3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=U3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"bool[]":o=Y3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=Y3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"shape":o=q3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=q3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"shape[]":o=Z3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=Z3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"dtype":o=H3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=H3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"dtype[]":o=j3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=j3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"func":o=e7(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=e7(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"tensor":case"tensors":break;default:throw new Error(`Unsupported param type: ${r.type} for op: ${e.op}`)}return s[r.name]={value:o,type:a},s},{})),n}mapFunction(e){let t=e.nodeDef,n=[],s=[],r={};t!=null&&(r=t.reduce((c,p)=>(c[p.name]=this.mapNode(p),p.op==="Const"&&s.push(c[p.name]),c),{}));let a=[],o=[];e.signature.inputArg.forEach(c=>{let[p]=Gr(c.name),d={name:p,op:"Placeholder",inputs:[],inputNames:[],category:"graph",inputParams:{},attrParams:{dtype:{value:bx(c.type),type:"dtype"}},children:[]};d.signatureKey=c.name,a.push(d),r[p]=d}),Object.keys(r).forEach(c=>{let p=r[c];p.inputNames.forEach((d,h)=>{let[f,,m]=Gr(d),g=r[f];if(g.outputs!=null){let y=g.outputs.indexOf(m);if(y!==-1){let x=`${f}:${y}`;p.inputNames[h]=x}}p.inputs.push(g),g.children.push(p)})});let l=e.ret;e.signature.outputArg.forEach(c=>{let[p,d]=Gr(l[c.name]),h=r[p];h!=null&&(h.defaultOutput=d,o.push(h))});let u=this.mapArgsToSignature(e);return{nodes:r,inputs:a,outputs:o,weights:s,placeholders:n,signature:u}}mapArgsToSignature(e){return{methodName:e.signature.name,inputs:e.signature.inputArg.reduce((t,n)=>(t[n.name]=this.mapArgToTensorInfo(n),t),{}),outputs:e.signature.outputArg.reduce((t,n)=>(t[n.name]=this.mapArgToTensorInfo(n,e.ret),t),{})}}mapArgToTensorInfo(e,t){let n=e.name;return t!=null&&(n=t[n]),{name:n,dtype:e.type}}};function gj(e){let t=Z().global;if(typeof t.atob!="undefined")return t.atob(e);if(typeof Buffer!="undefined")return new Buffer(e,"base64").toString();throw new Error("Unable to decode base64 in this environment. Missing built-in atob() or Buffer()")}function Hk(e,t){let n=Array.isArray(e)?String.fromCharCode.apply(null,e):gj(e);return t?n:n.toLowerCase()}function V3(e,t,n,s=!1){let r=e[t];return r!=null?Hk(r.s,s):n}function U3(e,t,n){let s=e[t];return s?s.b:n}function G3(e,t,n){let s=e[t]||{},r=s.i!=null?s.i:s.f!=null?s.f:n;return typeof r=="number"?r:parseInt(r,10)}function bx(e){switch(typeof e=="string"&&(e=sr[e]),e){case sr.DT_FLOAT:case sr.DT_HALF:return"float32";case sr.DT_INT32:case sr.DT_INT64:case sr.DT_INT8:case sr.DT_UINT8:return"int32";case sr.DT_BOOL:return"bool";case sr.DT_DOUBLE:return"float32";case sr.DT_STRING:return"string";default:return null}}function e7(e,t,n){let s=e[t];return s&&s.func?s.func.name:n}function H3(e,t,n){let s=e[t];return s&&s.type?bx(s.type):n}function j3(e,t,n){let s=e[t];return s&&s.list&&s.list.type?s.list.type.map(r=>bx(r)):n}function jk(e){if(!e.unknownRank)return e.dim!=null?e.dim.map(t=>typeof t.size=="number"?t.size:parseInt(t.size,10)):[]}function q3(e,t,n){let s=e[t];return s&&s.shape?jk(s.shape):n}function X3(e,t,n){let s=e[t];return s?((s.list.f&&s.list.f.length?s.list.f:s.list.i)||[]).map(r=>typeof r=="number"?r:parseInt(r,10)):n}function K3(e,t,n,s=!1){let r=e[t];return r&&r.list&&r.list.s?r.list.s.map(a=>Hk(a,s)):n}function Z3(e,t,n){let s=e[t];return s&&s.list&&s.list.shape?s.list.shape.map(r=>jk(r)):n}function Y3(e,t,n){let s=e[t];return s&&s.list&&s.list.b?s.list.b:n}var yj=class{constructor(e,t,n){this.node=e,this.tensorMap=t,this.context=n,this.inputs=[],this.attrs={},this.inputs=e.inputNames.map(s=>this.getInput(s)),e.rawAttrs!=null&&(this.attrs=Object.keys(e.rawAttrs).reduce((s,r)=>(s[r]=this.getAttr(r),s),{}))}getInput(e){return Jn(e,this.tensorMap,this.context)}getAttr(e,t){let n=this.node.rawAttrs[e];if(n.tensor!=null)return Jn(e,this.tensorMap,this.context);if(n.i!=null||n.f!=null)return G3(this.node.rawAttrs,e,t);if(n.s!=null)return V3(this.node.rawAttrs,e,t);if(n.b!=null)return U3(this.node.rawAttrs,e,t);if(n.shape!=null)return q3(this.node.rawAttrs,e,t);if(n.type!=null)return H3(this.node.rawAttrs,e,t);if(n.list!=null){if(n.list.i!=null||n.list.f!=null)return X3(this.node.rawAttrs,e,t);if(n.list.s!=null)return K3(this.node.rawAttrs,e,t);if(n.list.shape!=null)return Z3(this.node.rawAttrs,e,t);if(n.list.b!=null)return Y3(this.node.rawAttrs,e,t);if(n.list.type!=null)return j3(this.node.rawAttrs,e,t)}return t}},En={};Ve(En,{OP_SCOPE_SUFFIX:()=>Cy,abs:()=>tn,acos:()=>Hy,acosh:()=>jy,add:()=>ce,addN:()=>m0,all:()=>g0,any:()=>Cp,argMax:()=>Es,argMin:()=>qy,asin:()=>Xy,asinh:()=>Ky,atan:()=>Zy,atan2:()=>Yy,atanh:()=>Jy,avgPool:()=>lh,avgPool3d:()=>eA,basicLSTMCell:()=>sw,batchNorm:()=>Wc,batchNorm2d:()=>tA,batchNorm3d:()=>nA,batchNorm4d:()=>sA,batchToSpaceND:()=>uh,bincount:()=>rA,booleanMaskAsync:()=>zw,broadcastArgs:()=>rw,broadcastTo:()=>Gu,buffer:()=>Le,cast:()=>ge,ceil:()=>aA,clipByValue:()=>fs,clone:()=>Fn,complex:()=>fa,concat:()=>Ct,concat1d:()=>oA,concat2d:()=>Kl,concat3d:()=>iA,concat4d:()=>lA,conv1d:()=>y0,conv2d:()=>ma,conv2dTranspose:()=>A0,conv3d:()=>cA,conv3dTranspose:()=>dA,cos:()=>ch,cosh:()=>x0,cosineWindow:()=>W0,cumprod:()=>Tp,cumsum:()=>b0,denseBincount:()=>ow,depthToSpace:()=>pA,depthwiseConv2d:()=>Vc,diag:()=>iw,dilation2d:()=>hA,div:()=>pe,divNoNan:()=>fA,dot:()=>mA,dropout:()=>WA,einsum:()=>lw,elu:()=>Uc,enclosingPowerOfTwo:()=>VA,equal:()=>Rs,erf:()=>gA,euclideanNorm:()=>xA,exp:()=>_s,expandDims:()=>Kt,expm1:()=>bA,eye:()=>v0,fft:()=>xh,fill:()=>Hc,floor:()=>jc,floorDiv:()=>Bc,fused:()=>ec,gather:()=>qc,gatherND:()=>Vw,greater:()=>ys,greaterEqual:()=>li,ifft:()=>Qu,imag:()=>oh,image:()=>Ne,inTopKAsync:()=>Uw,irfft:()=>M0,isFinite:()=>vA,isInf:()=>wA,isNaN:()=>kA,leakyRelu:()=>dh,less:()=>w0,lessEqual:()=>ui,linalg:()=>HA,linspace:()=>hw,localResponseNormalization:()=>IA,log:()=>Ds,log1p:()=>ph,logSigmoid:()=>SA,logSoftmax:()=>I0,logSumExp:()=>S0,logicalAnd:()=>lr,logicalNot:()=>hh,logicalOr:()=>C0,logicalXor:()=>CA,losses:()=>t8,lowerBound:()=>mw,matMul:()=>Qe,max:()=>mn,maxPool:()=>fh,maxPool3d:()=>TA,maxPoolWithArgmax:()=>gw,maximum:()=>Jr,mean:()=>Bt,meshgrid:()=>yw,min:()=>ga,minimum:()=>Xc,mirrorPad:()=>NA,mod:()=>Yl,moments:()=>mh,movingAverage:()=>Lw,mul:()=>L,multiRNNCell:()=>Aw,multinomial:()=>xw,neg:()=>Dt,norm:()=>Gc,notEqual:()=>Qi,oneHot:()=>Zu,ones:()=>Ns,onesLike:()=>$s,op:()=>V,outerProduct:()=>bw,pad:()=>Js,pad1d:()=>vw,pad2d:()=>ww,pad3d:()=>kw,pad4d:()=>Iw,pool:()=>EA,pow:()=>ya,prelu:()=>yh,print:()=>Ry,prod:()=>RA,rand:()=>Sw,randomGamma:()=>Cw,randomNormal:()=>N0,randomStandardNormal:()=>Tw,randomUniform:()=>Kc,range:()=>Ju,real:()=>Yu,reciprocal:()=>$A,relu:()=>Pr,relu6:()=>E0,reshape:()=>U,reverse:()=>Ks,reverse1d:()=>Nw,reverse2d:()=>Ew,reverse3d:()=>Rw,reverse4d:()=>_w,rfft:()=>bh,round:()=>R0,rsqrt:()=>_0,scalar:()=>Se,scatterND:()=>Bw,searchSorted:()=>T0,selu:()=>D0,separableConv2d:()=>$0,setdiff1dAsync:()=>Dw,sigmoid:()=>Cn,sign:()=>PA,signal:()=>e8,sin:()=>P0,sinh:()=>F0,slice:()=>Oe,slice1d:()=>Ah,slice2d:()=>O0,slice3d:()=>ci,slice4d:()=>no,softmax:()=>Jl,softplus:()=>Zl,spaceToBatchND:()=>gh,sparse:()=>n8,sparseToDense:()=>Ww,spectral:()=>Qw,split:()=>Zt,sqrt:()=>Nn,square:()=>vt,squaredDifference:()=>z0,squeeze:()=>rt,stack:()=>on,step:()=>Ql,stridedSlice:()=>FA,string:()=>s8,sub:()=>he,sum:()=>ke,tan:()=>OA,tanh:()=>Yi,tensor:()=>ft,tensor1d:()=>Ft,tensor2d:()=>or,tensor3d:()=>My,tensor4d:()=>$w,tensor5d:()=>Pw,tensor6d:()=>Fw,tile:()=>js,topk:()=>MA,transpose:()=>st,truncatedNormal:()=>L0,unique:()=>zA,unsortedSegmentSum:()=>B0,unstack:()=>es,upperBound:()=>Ow,variable:()=>LA,where:()=>Mn,whereAsync:()=>BA,zeros:()=>Wt,zerosLike:()=>it});var Aj=(e,t,n,s=En)=>{switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[s.add(I("a",e,t,n),I("b",e,t,n))];case"AddN":return[s.addN(I("tensors",e,t,n))];case"FloorMod":case"Mod":return[s.mod(I("a",e,t,n),I("b",e,t,n))];case"Mul":return[s.mul(I("a",e,t,n),I("b",e,t,n))];case"RealDiv":case"Div":return[s.div(I("a",e,t,n),I("b",e,t,n))];case"DivNoNan":return[s.divNoNan(I("a",e,t,n),I("b",e,t,n))];case"FloorDiv":return[s.floorDiv(I("a",e,t,n),I("b",e,t,n))];case"Sub":return[s.sub(I("a",e,t,n),I("b",e,t,n))];case"Minimum":return[s.minimum(I("a",e,t,n),I("b",e,t,n))];case"Maximum":return[s.maximum(I("a",e,t,n),I("b",e,t,n))];case"Pow":return[s.pow(I("a",e,t,n),I("b",e,t,n))];case"SquaredDifference":return[s.squaredDifference(I("a",e,t,n),I("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},xj=(e,t,n,s=En)=>{switch(e.op){case"Abs":case"ComplexAbs":return[s.abs(I("x",e,t,n))];case"Acos":return[s.acos(I("x",e,t,n))];case"Acosh":return[s.acosh(I("x",e,t,n))];case"Asin":return[s.asin(I("x",e,t,n))];case"Asinh":return[s.asinh(I("x",e,t,n))];case"Atan":return[s.atan(I("x",e,t,n))];case"Atan2":return[s.atan2(I("x",e,t,n),I("y",e,t,n))];case"Atanh":return[s.atanh(I("x",e,t,n))];case"Ceil":return[s.ceil(I("x",e,t,n))];case"Complex":return[s.complex(I("real",e,t,n),I("imag",e,t,n))];case"Cos":return[s.cos(I("x",e,t,n))];case"Cosh":return[s.cosh(I("x",e,t,n))];case"Elu":return[s.elu(I("x",e,t,n))];case"Erf":return[s.erf(I("x",e,t,n))];case"Exp":return[s.exp(I("x",e,t,n))];case"Expm1":return[s.expm1(I("x",e,t,n))];case"Floor":return[s.floor(I("x",e,t,n))];case"Log":return[s.log(I("x",e,t,n))];case"Log1p":return[s.log1p(I("x",e,t,n))];case"Imag":return[s.imag(I("x",e,t,n))];case"Neg":return[s.neg(I("x",e,t,n))];case"Reciprocal":return[s.reciprocal(I("x",e,t,n))];case"Real":return[s.real(I("x",e,t,n))];case"Relu":return[s.relu(I("x",e,t,n))];case"Round":return[s.round(I("x",e,t,n))];case"Selu":return[s.selu(I("x",e,t,n))];case"Sigmoid":return[s.sigmoid(I("x",e,t,n))];case"Sin":return[s.sin(I("x",e,t,n))];case"Sign":return[s.sign(I("x",e,t,n))];case"Sinh":return[s.sinh(I("x",e,t,n))];case"Softplus":return[s.softplus(I("x",e,t,n))];case"Sqrt":return[s.sqrt(I("x",e,t,n))];case"Square":return[s.square(I("x",e,t,n))];case"Tanh":return[s.tanh(I("x",e,t,n))];case"Tan":return[s.tan(I("x",e,t,n))];case"ClipByValue":return[s.clipByValue(I("x",e,t,n),I("clipValueMin",e,t,n),I("clipValueMax",e,t,n))];case"Relu6":return[s.relu6(I("x",e,t,n))];case"Rsqrt":return[s.rsqrt(Jn(e.inputNames[0],t,n))];case"Prod":return[s.prod(I("x",e,t,n),I("axes",e,t,n))];case"LeakyRelu":return[s.leakyRelu(I("x",e,t,n),I("alpha",e,t,n))];case"Prelu":return[s.prelu(I("x",e,t,n),I("alpha",e,t,n))];case"IsNan":return[s.isNaN(Jn(e.inputNames[0],t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function ar(e,t,n=""){if(!(typeof e=="number"||typeof t=="number")){v.assert(e.length===t.length,()=>n+` Shapes ${e} and ${t} must match`);for(let s=0;s<e.length;s++){let r=e[s],a=t[s];v.assert(r<0||a<0||r===a,()=>n+` Shapes ${e} and ${t} must match`)}}}function t7(e){return!(typeof e=="number"||e.some(t=>t<0))}function tp(e,t,n){let s=J3(e,n),r=!t7(s);if(r&&t.length===0)throw new Error(`Tried to calculate elements of an empty list with non-fully-defined elementShape: ${s}`);if(r&&t.forEach(a=>{s=J3(a.shape,s)}),!t7(s))throw new Error(`Non-fully-defined elementShape: ${s}`);return s}function J3(e,t){if(typeof e=="number")return t;if(typeof t=="number")return e;if(e.length!==t.length)throw new Error(`Incompatible ranks during merge: ${e} vs. ${t}`);let n=[];for(let s=0;s<e.length;++s){let r=e[s],a=t[s];if(r>=0&&a>=0&&r!==a)throw new Error(`Incompatible shape during merge: ${e} vs. ${t}`);n[s]=r>=0?r:a}return n}var bj=class{constructor(e,t,n,s,r,a,o){this.name=e,this.dtype=t,this.maxSize=n,this.elementShape=s,this.identicalElementShapes=r,this.dynamicSize=a,this.clearAfterRead=o,this.tensors=[],this.closed_=!1,this.idTensor=Se(0),bn(this.idTensor)}get id(){return this.idTensor.id}get closed(){return this.closed_}clearAndClose(e){this.tensors.forEach(t=>{(e==null||!e.has(t.tensor.id))&&t.tensor.dispose()}),this.tensors=[],this.closed_=!0,this.idTensor.dispose()}size(){return this.tensors.length}read(e){if(this.closed_)throw new Error(`TensorArray ${this.name} has already been closed.`);if(e<0||e>=this.size())throw new Error(`Tried to read from index ${e}, but array size is: ${this.size()}`);let t=this.tensors[e];if(t.cleared)throw new Error(`TensorArray ${this.name}: Could not read index ${e} twice because it was cleared after a previous read (perhaps try setting clear_after_read = false?).`);return this.clearAfterRead&&(t.cleared=!0),t.read=!0,t.tensor}readMany(e){return e.map(t=>this.read(t))}write(e,t){if(this.closed_)throw new Error(`TensorArray ${this.name} has already been closed.`);if(e<0||!this.dynamicSize&&e>=this.maxSize)throw new Error(`Tried to write to index ${e}, but array is not resizeable and size is: ${this.maxSize}`);let n=this.tensors[e]||{};if(t.dtype!==this.dtype)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e},
+2. The custom ${s} is defined in JavaScript, but is not registered properly with tf.serialization.registerClass().`);if(l!=null){let u={};for(let h of Object.keys(nr))u[h]=nr[h];for(let h of Object.keys(n))u[h]=n[h];let c=a.config;c.customObjects=u;let p=Object.assign({},nr);for(let h of Object.keys(n))nr[h]=n[h];_3(a.config);let d=l(i,a.config,n,r);return nr=Object.assign({},p),d}else{let u=Object.assign({},nr);for(let p of Object.keys(n))nr[p]=n[p];let c=new i(a.config);return nr=Object.assign({},u),c}}}function lV(e,t){return e<t?-1:e>t?1:0}function Bf(e,t){return-1*lV(e,t)}function qa(e){if(e==null)return e;let t=[];for(let n of e)t.indexOf(n)===-1&&t.push(n);return t}function uV(e){if(e==null)throw new j(`Invalid value in obj: ${JSON.stringify(e)}`);for(let t in e)if(e.hasOwnProperty(t))return!1;return!0}function Ql(e,t,n){if(n!=null&&e.indexOf(n)<0)throw new j(`${n} is not a valid ${t}.  Valid values are ${e} or null/undefined.`)}function KA(e,t,n=0,s=1/0){return Wr(n>=0),Wr(s>=n),Array.isArray(e)&&e.length>=n&&e.length<=s&&e.every(r=>typeof r===t)}function vn(e,t){Array.isArray(e)?(v.assert(e.length>0,()=>`${t} is unexpectedly an empty array.`),e.forEach((n,s)=>vn(n,`element ${s+1} of ${t}`))):v.assert(Number.isInteger(e)&&e>0,()=>`Expected ${t} to be a positive integer, but got ${d8(e)}.`)}function d8(e){return e===null?"null":Array.isArray(e)?"["+e.map(t=>d8(t)).join(",")+"]":typeof e=="string"?`"${e}"`:`${e}`}function cV(e,t,n){let s=n!=null?n():v.now(),r;return(...o)=>{let i=n!=null?n():v.now();return i-s<t||(s=i,r=e(...o)),r}}function p8(e){return e==="relu"?"relu":e==="linear"?"linear":e==="elu"?"elu":null}var dV=0;function h8(){return dV++}var Wf={};function Y0(e=""){return e in Wf||(Wf[e]=0),Wf[e]+=1,e+Wf[e].toString()}var pV=["channelsFirst","channelsLast"],hV=["nearest","bilinear"],fV=["valid","same","causal"],mV=["max","avg"],gV=["sum","mul","concat","ave"],Du=new Map;function Yt(e){Ql(pV,"DataFormat",e)}function yV(e){Ql(hV,"InterpolationFormat",e)}function Qs(e){Ql(fV,"PaddingMode",e)}function f8(e){Ql(mV,"PoolMode",e)}var fp=[],Dv="/";function Gi(e,t){fp.push(e);try{let n=t();return fp.pop(),n}catch(n){throw fp.pop(),n}}function AV(){return fp.length===0?"":fp.join(Dv)+Dv}function m8(e){if(!y8(e))throw new Error("Not a valid tensor name: '"+e+"'");return AV()+e}function g8(e){if(!y8(e))throw new Error("Not a valid tensor name: '"+e+"'");Du.has(e)||Du.set(e,0);let t=Du.get(e);if(Du.set(e,Du.get(e)+1),t>0){let n=`${e}_${t}`;return Du.set(n,1),n}else return e}var xV=new RegExp(/^[A-Za-z0-9][-A-Za-z0-9\._\/]*$/);function y8(e){return!!e.match(xV)}function bV(e){return e===parseInt(e.toString(),10)}function Xa(e,t,n){t==null&&(t=0),n==null&&(n=e.length);let s=1;for(let r=t;r<n;++r)s*=e[r];return s}function ec(e){if(e.length===0)return Number.NaN;let t=Number.POSITIVE_INFINITY;for(let n=0;n<e.length;n++){let s=e[n];s<t&&(t=s)}return t}function no(e){if(e.length===0)return Number.NaN;let t=Number.NEGATIVE_INFINITY;for(let n=0;n<e.length;n++){let s=e[n];s>t&&(t=s)}return t}function Rr(e,t){if(t<e)throw new j(`end (${t}) < begin (${e}) is forbidden.`);let n=[];for(let s=e;s<t;++s)n.push(s);return n}var i3;function hn(){return i3==null&&(i3=Zs().epsilon()),i3}function _r(){return"channelsLast"}function J0(e,t){return ge(e,t)}function wh(e,t=-1){let n=e.shape.slice();return t<0&&(t=n.length+t+1),n.splice(t,0,1),U(e,n)}function vV(e,t){return J(()=>{if(e.shape.length!==2)throw new j(`repeat() expects a rank-2 tensor, but received a rank-${e.shape.length} tensor.`);let n=wh(e,1);return D3(n,[1,t,1])})}function wV(e){let t=[Xa(e.shape)];return U(e,t)}function kV(e){if(e.rank<=1)throw new j(`batchFlatten requires a minimum rank of 2. Got rank: ${e.rank}.`);let t=[e.shape[0],Xa(e.shape,1)];return U(e,t)}function Hi(e,t,n){return J(()=>{switch(e.rank){case 1:return yh(e,t,n);case 2:return F0(e,[t,0],[n,e.shape[1]]);case 3:return ui(e,[t,0,0],[n,e.shape[1],e.shape[2]]);case 4:return to(e,[t,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3]]);case 5:return Oe(e,[t,0,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3],e.shape[4]]);case 6:return Oe(e,[t,0,0,0,0,0],[n,e.shape[1],e.shape[2],e.shape[3],e.shape[4],e.shape[5]]);default:throw new j(`sliceAlongFirstAxis() received an unsupported tensor rank: ${e.rank}`)}})}function l3(e,t,n){return J(()=>{switch(e.rank){case 1:return yh(e,t,n);case 2:return F0(e,[0,t],[e.shape[0],n]);case 3:return ui(e,[0,0,t],[e.shape[0],e.shape[1],n]);case 4:return to(e,[0,0,0,t],[e.shape[0],e.shape[1],e.shape[2],n]);default:throw new j(`sliceAlongLastAxis() received an unsupported tensor rank: ${e.rank}`)}})}function Vf(e,t,n,s){return J(()=>{switch(e.rank){case 1:return yh(e,t,n);case 2:switch(s){case 1:return Hi(e,t,n);case 2:return l3(e,t,n);default:throw new j(`The axis is not within the rank of the tensor ${s}`)}case 3:switch(s){case 1:return Hi(e,t,n);case 2:return ui(e,[0,t,0],[e.shape[0],n,e.shape[2]]);case 3:return l3(e,t,n);default:throw new j(`The axis is not within the rank of the tensor ${s}`)}case 4:switch(s){case 1:return Hi(e,t,n);case 2:return to(e,[0,t,0,0],[e.shape[0],n,e.shape[2],e.shape[3]]);case 3:return to(e,[0,0,t,0],[e.shape[0],e.shape[1],n,e.shape[3]]);case 4:return l3(e,t,n);default:throw new j(`The axis is not within the rank of the tensor ${s}`)}default:throw new j(`sliceAlongLastAxis() received an unsupported tensor rank: ${e.rank}`)}})}function ZA(e,t=-1){let n;return t<0&&(n=e[0].rank,n!==0?t=n:t=0),t===e[0].rank&&(t=-1),Ct(e,t)}function $v(e,t){switch(e.rank){case 1:return oA([e,t]);case 2:return Xl([e,t],0);case 3:return iA([e,t],0);case 4:return lA([e,t],0);default:throw new j(`concatAlongFirstAxis() received an unsupported tensor rank: ${e.rank}`)}}function D3(e,t){if(Array.isArray(t)||(t=[t]),e.rank!==t.length)throw new j(`The length of input n (${t.length}) does not match the number of dimensions in input x (${e.rank})`);return js(e,t)}function Q0(e,t=0,n=1,s,r){return T0(e,t,n,s,r)}function Hr(e,t,n,s){if(e.rank<2||t.rank<2)throw new He(`dot requires both inputs to be rank >= 2 but got x shape = ${e.shape} and y shape = ${t.shape}`);if(t.rank>=3){let r=e.shape.slice(-1)[0],a=t.shape.slice(-2)[0];if(r!==a)throw new He(`If rank y >= 3, then the second last dim of y must equal the last dim of x but got x shape = ${e.shape} and  y shape = ${t.shape}`)}if(e.rank===2&&t.rank===2)return Qu.matMul({a:e,b:t,transposeA:!1,transposeB:!1,bias:s?$3(e.rank,s,_r()):null,activation:n});{let r=e.shape.slice(),a=r.pop();e=U(e,[-1,a]);let o=t.shape.slice(),i=o.pop(),l=o.pop(),u=[...o,i],c=Array.from({length:t.rank},(f,m)=>m===0?t.rank-2:m<=t.rank-2?m-1:m);t=U(st(t,c),[l,-1]);let p=[...r,...u],d=!1,h=!1;return U(Qu.matMul({a:e,b:t,transposeA:d,transposeB:h,bias:s?$3(e.rank,s,_r()):null,activation:n}),p)}}function A8(e,t,n){return J(()=>(Array.isArray(t)?t=Ft(t,"int32"):t=ge(t,"int32"),jc(e,t,n)))}function kh(e){return L(e,e)}function $3(e,t,n){let s=t.shape;if(t.rank!==1&&t.rank!==e)throw new j(`Unexpected bias dimensions: ${t.rank}; expected it to be 1 or ${e}`);if(e===5){if(n==="channelsFirst")return s.length===1?U(t,[1,s[0],1,1,1]):U(t,[1,s[3],s[0],s[1],s[2]]);if(n==="channelsLast")return s.length===1?U(t,[1,1,1,1,s[0]]):U(t,[1].concat(s))}else if(e===4){if(n==="channelsFirst")return s.length===1?U(t,[1,s[0],1,1]):U(t,[1,s[2],s[0],s[1]]);if(n==="channelsLast")return s.length===1?U(t,[1,1,1,s[0]]):U(t,[1].concat(s))}else if(e===3){if(n==="channelsFirst")return s.length===1?U(t,[1,s[0],1]):U(t,[1,s[1],s[0]]);if(n==="channelsLast")return s.length===1?U(t,[1,1,s[0]]):U(t,[1].concat(s))}else if(e<3)return t;throw new j(`Unsupported input rank by biasAdd: ${t.rank}`)}function Pr(e,t,n){return J(()=>(n==null&&(n=_r()),Yt(n),ce(e,$3(e.rank,t,n))))}function IV(e,t=1){if(t!==1)throw new He(`Support for alpha values other than 1 (${t}) is not implemented yet.`);return Vc(e)}function SV(e){return J(()=>pe(e,ce(tn(e),1)))}function x8(e,t,n,s){return J(()=>WA(e,t,n,s))}function CV(e){return J(()=>{let t=ce(.5,L(.2,e));return fs(t,0,1)})}function Ih(e,t,n=!1){return n?e():t()}var TV=["fanIn","fanOut","fanAvg"],NV=["normal","uniform","truncatedNormal"];function EV(e){Ql(TV,"FanMode",e)}function RV(e){Ql(NV,"Distribution",e)}var pr=class extends de.Serializable{fromConfigUsesCustomObjects(){return!1}getConfig(){return{}}},YA=class extends pr{apply(e,t){return Wt(e,t)}};YA.className="Zeros";de.registerClass(YA);var e2=class extends pr{apply(e,t){return Ns(e,t)}};e2.className="Ones";de.registerClass(e2);var JA=class extends pr{constructor(e){if(super(),typeof e!="object")throw new j(`Expected argument of type ConstantConfig but got ${e}`);if(e.value===void 0)throw new j(`config must have value set but got ${e}`);this.value=e.value}apply(e,t){return J(()=>L(Se(this.value),Ns(e,t)))}getConfig(){return{value:this.value}}};JA.className="Constant";de.registerClass(JA);var QA=class extends pr{constructor(e){super(),this.DEFAULT_MINVAL=-.05,this.DEFAULT_MAXVAL=.05,this.minval=e.minval||this.DEFAULT_MINVAL,this.maxval=e.maxval||this.DEFAULT_MAXVAL,this.seed=e.seed}apply(e,t){return Xc(e,this.minval,this.maxval,t)}getConfig(){return{minval:this.minval,maxval:this.maxval,seed:this.seed}}};QA.className="RandomUniform";de.registerClass(QA);var e5=class extends pr{constructor(e){super(),this.DEFAULT_MEAN=0,this.DEFAULT_STDDEV=.05,this.mean=e.mean||this.DEFAULT_MEAN,this.stddev=e.stddev||this.DEFAULT_STDDEV,this.seed=e.seed}apply(e,t){if(t=t||"float32",t!=="float32"&&t!=="int32")throw new He(`randomNormal does not support dType ${t}.`);return Q0(e,this.mean,this.stddev,t,this.seed)}getConfig(){return{mean:this.mean,stddev:this.stddev,seed:this.seed}}};e5.className="RandomNormal";de.registerClass(e5);var t5=class extends pr{constructor(e){super(),this.DEFAULT_MEAN=0,this.DEFAULT_STDDEV=.05,this.mean=e.mean||this.DEFAULT_MEAN,this.stddev=e.stddev||this.DEFAULT_STDDEV,this.seed=e.seed}apply(e,t){if(t=t||"float32",t!=="float32"&&t!=="int32")throw new He(`truncatedNormal does not support dType ${t}.`);return z0(e,this.mean,this.stddev,t,this.seed)}getConfig(){return{mean:this.mean,stddev:this.stddev,seed:this.seed}}};t5.className="TruncatedNormal";de.registerClass(t5);var n5=class extends pr{constructor(e){super(),this.gain=e.gain!=null?e.gain:1}apply(e,t){return J(()=>{if(e.length!==2||e[0]!==e[1])throw new j("Identity matrix initializer can only be used for 2D square matrices.");return L(this.gain,b0(e[0]))})}getConfig(){return{gain:this.gain}}};n5.className="Identity";de.registerClass(n5);function _V(e,t="channelsLast"){let n,s;if(Yt(t),e.length===2)n=e[0],s=e[1];else if([3,4,5].indexOf(e.length)!==-1){if(t==="channelsFirst"){let r=Xa(e,2);n=e[1]*r,s=e[0]*r}else if(t==="channelsLast"){let r=Xa(e,0,e.length-2);n=e[e.length-2]*r,s=e[e.length-1]*r}}else{let r=Xa(e);n=Math.sqrt(r),s=Math.sqrt(r)}return[n,s]}var ms=class extends pr{constructor(e){if(super(),e.scale<0)throw new j(`scale must be a positive float. Got: ${e.scale}`);this.scale=e.scale==null?1:e.scale,this.mode=e.mode==null?"fanIn":e.mode,EV(this.mode),this.distribution=e.distribution==null?"normal":e.distribution,RV(this.distribution),this.seed=e.seed}apply(e,t){let n=_V(e),s=n[0],r=n[1],a=this.scale;if(this.mode==="fanIn"?a/=Math.max(1,s):this.mode==="fanOut"?a/=Math.max(1,r):a/=Math.max(1,(s+r)/2),this.distribution==="normal"){let o=Math.sqrt(a);if(t=t||"float32",t!=="float32"&&t!=="int32")throw new He(`${this.getClassName()} does not support dType ${t}.`);return z0(e,0,o,t,this.seed)}else{let o=Math.sqrt(3*a);return Xc(e,-o,o,t)}}getConfig(){return{scale:this.scale,mode:this.mode,distribution:this.distribution,seed:this.seed}}};ms.className="VarianceScaling";de.registerClass(ms);var t2=class extends ms{constructor(e){super({scale:1,mode:"fanAvg",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return ms.className}};t2.className="GlorotUniform";de.registerClass(t2);var n2=class extends ms{constructor(e){super({scale:1,mode:"fanAvg",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return ms.className}};n2.className="GlorotNormal";de.registerClass(n2);var s2=class extends ms{constructor(e){super({scale:2,mode:"fanIn",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return ms.className}};s2.className="HeNormal";de.registerClass(s2);var r2=class extends ms{constructor(e){super({scale:2,mode:"fanIn",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return ms.className}};r2.className="HeUniform";de.registerClass(r2);var a2=class extends ms{constructor(e){super({scale:1,mode:"fanIn",distribution:"normal",seed:e==null?null:e.seed})}getClassName(){return ms.className}};a2.className="LeCunNormal";de.registerClass(a2);var o2=class extends ms{constructor(e){super({scale:1,mode:"fanIn",distribution:"uniform",seed:e==null?null:e.seed})}getClassName(){return ms.className}};o2.className="LeCunNormal";de.registerClass(o2);var s5=class extends pr{constructor(e){if(super(),this.DEFAULT_GAIN=1,this.gain=e.gain==null?this.DEFAULT_GAIN:e.gain,this.seed=e.seed,this.seed!=null)throw new He("Random seed is not implemented for Orthogonal Initializer yet.")}apply(e,t){return J(()=>{if(e.length<2)throw new He("Shape must be at least 2D.");e[0]*e[1]>2e3&&console.warn(`Orthogonal initializer is being called on a matrix with more than 2000 (${e[0]*e[1]}) elements: Slowness may result.`);let n=e[0]>e[1]?[e[1],e[0]]:e,s=Q0(n,0,1,"float32"),r=HA.gramSchmidt(s);return e[0]>e[1]&&(r=st(r)),L(this.gain,r)})}getConfig(){return{gain:this.gain,seed:this.seed}}};s5.className="Orthogonal";de.registerClass(s5);var Pv={constant:"Constant",glorotNormal:"GlorotNormal",glorotUniform:"GlorotUniform",heNormal:"HeNormal",heUniform:"HeUniform",identity:"Identity",leCunNormal:"LeCunNormal",leCunUniform:"LeCunUniform",ones:"Ones",orthogonal:"Orthogonal",randomNormal:"RandomNormal",randomUniform:"RandomUniform",truncatedNormal:"TruncatedNormal",varianceScaling:"VarianceScaling",zeros:"Zeros"};function Fv(e,t={}){return vh(e,de.SerializationMap.getMap().classNameMap,t,"initializer")}function Vt(e){return XA(e)}function Ot(e){if(typeof e=="string"){let t=e in Pv?Pv[e]:e;if(t==="GlorotNormal")return new n2;if(t==="GlorotUniform")return new t2;if(t==="HeNormal")return new s2;if(t==="HeUniform")return new r2;if(t==="LeCunNormal")return new a2;if(t==="LeCunUniform")return new o2;{let n={};return n.className=t,n.config={},Fv(n)}}else return e instanceof pr?e:Fv(e)}function P3(e){return Array.isArray(e)&&Array.isArray(e[0])}function Am(e){return e.length===0?[]:Array.isArray(e[0])?e:[e]}function Xe(e){let t;if(Array.isArray(e)){if(e.length!==1)throw new j(`Expected Tensor length to be 1; got ${e.length}`);t=e[0]}else t=e;return t}function xt(e){if(Array.isArray(e)&&Array.isArray(e[0])){if(e.length===1)return e=e,e[0];throw new j(`Expected exactly 1 Shape; got ${e.length}`)}else return e}function xm(e){let t=0;for(let n of e)n.shape.length===0?t+=1:t+=n.shape.reduce((s,r)=>s*r);return t}var Ov="Variable",b8=class{constructor(e,t="float32",n=Ov,s=!0,r=null){this.dtype=t==null?"float32":t,this.shape=e.shape,this.id=h8(),n=n==null?Ov:n,this.originalName=m8(n),this.name=g8(this.originalName),this.trainable_=s,this.constraint=r,this.val=LA(e,this.trainable_,this.name,this.dtype)}read(){return this.assertNotDisposed(),this.val}write(e){return this.assertNotDisposed(),DV(this.val,e),this.val.id!==e.id&&(this.val.assign(e),this.constraint!=null&&this.val.assign(this.constraint.apply(this.val))),this}dispose(){this.assertNotDisposed(),this.val.dispose()}assertNotDisposed(){if(this.val.isDisposed)throw new Error(`LayersVariable ${this.name} is already disposed.`)}get trainable(){return this.trainable_}set trainable(e){this.trainable_=e,this.val.trainable=e}};function DV(e,t){if(e.shape.toString()!==t.shape.toString())throw new Error("Shape mismatch: "+JSON.stringify(e.shape)+" vs. "+JSON.stringify(t.shape))}function F3(e){return e.map(t=>t.read())}function r5(e){e.forEach(t=>{t[0].write(t[1])})}var rn=class{constructor(e){this.dtype=e.dtype,this.shape=e.shape,e.shape!=null?this.ndim=e.shape.length:this.ndim=e.ndim,this.maxNDim=e.maxNDim,this.minNDim=e.minNDim,this.axes=e.axes||{}}},Cr=class{constructor(e,t,n,s,r,a,o){this.dtype=e,this.shape=t,this.sourceLayer=n,this.inputs=s,this.callArgs=r,this.outputTensorIndex=o,this.id=h8(),a!=null&&(this.originalName=m8(a),this.name=g8(this.originalName)),this.rank=t.length}},$V=0,i2=class{constructor(e,t){this.callArgs=t,this.id=$V++,this.outboundLayer=e.outboundLayer,this.inboundLayers=e.inboundLayers,this.nodeIndices=e.nodeIndices,this.tensorIndices=e.tensorIndices,this.inputTensors=e.inputTensors,this.outputTensors=e.outputTensors,this.inputMasks=e.inputMasks,this.outputMasks=e.outputMasks,this.inputShapes=e.inputShapes,this.outputShapes=e.outputShapes;for(let n of e.inboundLayers)n!=null&&n.outboundNodes.push(this);e.outboundLayer.inboundNodes.push(this)}getConfig(){let e=[];for(let t of this.inboundLayers)t!=null?e.push(t.name):e.push(null);return{outboundLayer:this.outboundLayer?this.outboundLayer.name:null,inboundLayers:e,nodeIndices:this.nodeIndices,tensorIndices:this.tensorIndices}}},PV=0,ut=class extends de.Serializable{constructor(e={}){super(),this._callHook=null,this._addedWeightNames=[],this._stateful=!1,this.id=PV++,this.activityRegularizer=null,this.inputSpec=null,this.supportsMasking=!1,this._trainableWeights=[],this._nonTrainableWeights=[],this._losses=[],this._updates=[],this._built=!1,this.inboundNodes=[],this.outboundNodes=[];let t=e.name;if(!t){let n=this.getClassName();t=la(n)+"_"+Y0(n)}if(this.name=t,this.trainable_=e.trainable==null?!0:e.trainable,e.inputShape!=null||e.batchInputShape!=null){let n;if(e.batchInputShape!=null)n=e.batchInputShape;else if(e.inputShape!=null){let r=null;e.batchSize!=null&&(r=e.batchSize),n=[r].concat(e.inputShape)}this.batchInputShape=n;let s=e.dtype;s==null&&(s=e.inputDType),s==null&&(s="float32"),this.dtype=s}e.weights!=null?this.initialWeights=e.weights:this.initialWeights=null,this._refCount=null,this.fastWeightInitDuringBuild=!1}static nodeKey(e,t){return e.name+"_ib-"+t.toString()}getNodeAtIndex(e,t){if(this.inboundNodes.length===0)throw new Sr(`The layer has never been called and thus has no defined ${t}.`);if(this.inboundNodes.length<=e)throw new j(`Asked to get ${t} at node ${e}, but the layer has only ${this.inboundNodes.length} inbound nodes.`);return this.inboundNodes[e]}getInputAt(e){return ps(this.getNodeAtIndex(e,"input").inputTensors)}getOutputAt(e){return ps(this.getNodeAtIndex(e,"output").outputTensors)}get input(){if(this.inboundNodes.length>1)throw new ia(`Layer ${this.name} has multiple inbound nodes, hence the notion of "layer input" is ill-defined. Use \`getInputAt(nodeIndex)\` instead.`);if(this.inboundNodes.length===0)throw new ia(`Layer ${this.name} is not connected, no input to return.`);return ps(this.getNodeAtIndex(0,"input").inputTensors)}get output(){if(this.inboundNodes.length===0)throw new ia(`Layer ${this.name} has no inbound nodes.`);if(this.inboundNodes.length>1)throw new ia(`Layer ${this.name} has multiple inbound nodes, hence the notion of "layer output" is ill-defined. Use \`getOutputAt(nodeIndex)\` instead.`);return ps(this.getNodeAtIndex(0,"output").outputTensors)}get losses(){return this._losses}calculateLosses(){return this.losses.map(e=>e())}get updates(){return this._updates}get built(){return this._built}set built(e){this._built=e}get trainable(){return this.trainable_}set trainable(e){this._trainableWeights.forEach(t=>t.trainable=e),this.trainable_=e}get trainableWeights(){return this.trainable_?this._trainableWeights.filter(e=>e.trainable):[]}set trainableWeights(e){this._trainableWeights=e}get nonTrainableWeights(){return this.trainable?this._trainableWeights.filter(e=>!e.trainable).concat(this._nonTrainableWeights):this._trainableWeights.concat(this._nonTrainableWeights)}set nonTrainableWeights(e){this._nonTrainableWeights=e}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}get stateful(){return this._stateful}resetStates(){if(!this.stateful)throw new Error("Cannot call the resetStates() method of a non-stateful Layer object.")}assertInputCompatibility(e){if(e=_t(e),this.inputSpec==null||this.inputSpec.length===0)return;let t=_t(this.inputSpec);if(e.length!==t.length)throw new j(`Layer ${this.name} expects ${t.length} inputs, but it received ${e.length} input tensors. Input received: ${e}`);for(let n=0;n<e.length;n++){let s=e[n],r=t[n];if(r==null)continue;let a=s.rank;if(r.ndim!=null&&a!==r.ndim)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected ndim=${r.ndim}, found ndim=${a}`);if(r.maxNDim!=null&&a>r.maxNDim)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected max_ndim=${r.maxNDim}, found ndim=${a}`);if(r.minNDim!=null&&a<r.minNDim)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected min_ndim=${r.minNDim}, found ndim=${a}.`);if(r.dtype!=null&&s.dtype!==r.dtype)throw new j(`Input ${n} is incompatible with layer ${this.name} : expected dtype=${r.dtype}, found dtype=${s.dtype}.`);if(r.axes){let o=s.shape;for(let i in r.axes){let l=Number(i),u=r.axes[i],c=l>=0?o[l]:o[o.length+l];if(u!=null&&[u,null].indexOf(c)===-1)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected axis ${l} of input shape to have value ${u} but got shape ${o}.`)}}if(r.shape!=null)for(let o=0;o<r.shape.length;++o){let i=r.shape[o],l=s.shape[o];if(i!=null&&l!=null&&i!==l)throw new j(`Input ${n} is incompatible with layer ${this.name}: expected shape=${r.shape}, found shape=${s.shape}.`)}}}call(e,t){return e}invokeCallHook(e,t){this._callHook!=null&&this._callHook(e,t)}setCallHook(e){this._callHook=e}clearCallHook(){this._callHook=null}apply(e,t){t=t||{},this.assertNotDisposed();let n=_t(e),s=!0;for(let a of n)if(!(a instanceof Cr)){s=!1;break}let r=!0;for(let a of n)if(a instanceof Cr){r=!1;break}if(s===r)throw new j("Arguments to apply() must be all SymbolicTensors or all Tensors");return Gi(this.name,()=>{if(!this.built){this.assertInputCompatibility(e);let a=[];for(let o of _t(e))a.push(o.shape);this.build(ps(a)),this.built=!0,this.initialWeights&&this.setWeights(this.initialWeights),this._refCount===null&&r&&(this._refCount=1)}if(this.assertInputCompatibility(e),r){let a=this.call(e,t),o=_t(a),i=[];for(let l of o)n.indexOf(l)!==-1&&(l=l.clone()),i.push(l);if(a=ps(i),this.activityRegularizer!=null)throw new He("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return a}else{let a=FV(e),o=this.computeOutputShape(a),i,l=OV(e);if(this.warnOnIncompatibleInputShape(Array.isArray(e)?a[0]:a),o!=null&&o.length>0&&Array.isArray(o[0])?i=o.map((u,c)=>new Cr(l,u,this,_t(e),t,this.name,c)):i=new Cr(l,o,this,_t(e),t,this.name),this.addInboundNode(e,i,null,null,a,o,t),this._refCount++,this.activityRegularizer!=null)throw new He("Layer invocation in the presence of activity regularizer(s) is not supported yet.");return i}})}warnOnIncompatibleInputShape(e){if(this.batchInputShape!=null)if(e.length!==this.batchInputShape.length)console.warn(`The rank of the input tensor provided (shape: ${JSON.stringify(e)}) does not match that of the batchInputShape (${JSON.stringify(this.batchInputShape)}) of the layer ${this.name}`);else{let t=!1;this.batchInputShape.forEach((n,s)=>{n!=null&&e[s]!=null&&e[s]!==n&&(t=!0)}),t&&console.warn(`The shape of the input tensor (${JSON.stringify(e)}) does not match the expectation of layer ${this.name}: ${JSON.stringify(this.batchInputShape)}`)}}get outputShape(){if(this.inboundNodes==null||this.inboundNodes.length===0)throw new ia(`The layer ${this.name} has never been called and thus has no defined output shape.`);let e=[];for(let t of this.inboundNodes){let n=JSON.stringify(t.outputShapes);e.indexOf(n)===-1&&e.push(n)}if(e.length===1){let t=this.inboundNodes[0].outputShapes;return Array.isArray(t)&&Array.isArray(t[0])&&t.length===1?t[0]:t}else throw new ia(`The layer ${this.name} has multiple inbound nodes with different output shapes. Hence the notion of "output shape" is ill-defined for the layer.`)}countParams(){if(!this.built)throw new Sr(`You tried to call countParams() on ${this.name}, but the layer is not built yet. Build it first by calling build(batchInputShape).`);return xm(this.weights)}build(e){this.built=!0}getWeights(e=!1){return F3(e?this.trainableWeights:this.weights)}setWeights(e){J(()=>{let t=this.weights;if(t.length!==e.length)throw new j(`You called setWeights(weights) on layer "${this.name}" with a weight list of length ${e.length}, but the layer was expecting ${t.length} weights. Provided weights: ${e}...`);if(t.length===0)return;let n=[],s=F3(t);for(let r=0;r<s.length;++r){let a=s[r],o=t[r],i=e[r];if(!v.arraysEqual(a.shape,i.shape))throw new j(`Layer weight shape ${a.shape} not compatible with provided weight shape ${i.shape}`);n.push([o,i])}r5(n)})}addWeight(e,t,n,s,r,a,o,i){if(this._addedWeightNames.indexOf(e)!==-1)throw new j(`Duplicate weight name ${e} for layer ${this.name}`);this._addedWeightNames.push(e),n==null&&(n="float32"),this.fastWeightInitDuringBuild&&(s=i!=null?i():Ot("zeros"));let l=s.apply(t,n),u=new b8(l,n,e,a,o);return l.dispose(),r!=null&&this.addLoss(()=>r.apply(u.read())),a==null&&(a=!0),a?this._trainableWeights.push(u):this._nonTrainableWeights.push(u),u}setFastWeightInitDuringBuild(e){this.fastWeightInitDuringBuild=e}addLoss(e){e==null||Array.isArray(e)&&e.length===0||(e=_t(e),this._losses!==void 0&&this._losses!==null&&this.losses.push(...e))}computeOutputShape(e){return e}computeMask(e,t){if(!this.supportsMasking){if(t!=null)if(Array.isArray(t))t.forEach(n=>{if(n!=null)throw new TypeError(`Layer ${this.name} does not support masking, but was passed an inputMask.`)});else throw new TypeError(`Layer ${this.name} does not support masking, but was passed an inputMask.`);return null}return t}addInboundNode(e,t,n,s,r,a,o=null){let i=_t(e);t=_t(t),n=_t(n),s=_t(s),r=Am(r),a=Am(a);let l=[],u=[],c=[];for(let p of i)l.push(p.sourceLayer),u.push(p.nodeIndex),c.push(p.tensorIndex);new i2({outboundLayer:this,inboundLayers:l,nodeIndices:u,tensorIndices:c,inputTensors:i,outputTensors:t,inputMasks:n,outputMasks:s,inputShapes:r,outputShapes:a},o);for(let p=0;p<t.length;p++)t[p].sourceLayer=this,t[p].nodeIndex=this.inboundNodes.length-1,t[p].tensorIndex=p}getConfig(){let e={name:this.name,trainable:this.trainable};return this.batchInputShape!=null&&(e.batchInputShape=this.batchInputShape),this.dtype!=null&&(e.dtype=this.dtype),e}disposeWeights(){return this.weights.forEach(e=>e.dispose()),this.weights.length}assertNotDisposed(){if(this._refCount===0)throw new Error(`Layer '${this.name}' is already disposed.`)}dispose(){if(!this.built)throw new Error(`Cannot dispose Layer ${this.name} because it has not been built yet.`);if(this._refCount===null)throw new Error(`Cannot dispose Layer ${this.name} because it has not been used yet.`);this.assertNotDisposed();let e=0;return--this._refCount===0&&(e=this.disposeWeights()),{refCountAfterDispose:this._refCount,numDisposedVariables:e}}};function FV(e){e=_t(e);let t=[];for(let n of e)t.push(n.shape);return ps(t)}function OV(e){return"float32"}function v8(e,t,n){if((t==null||n!=null&&n>0)&&(t=e.sourceLayer,n=e.nodeIndex),t.inboundNodes.length===0)return[e];{let s=t.inboundNodes[n];if(s.inboundLayers.length===0)return s.inputTensors;{let r=[];for(let a=0;a<s.inboundLayers.length;a++){let o=s.inputTensors[a],i=s.inboundLayers[a],l=s.nodeIndices[a],u=v8(o,i,l);for(let c of u)r.indexOf(c)===-1&&r.push(c)}return r}}}var Zc=class extends ut{constructor(e){if(super({dtype:e.dtype,name:e.name!=null?e.name:Y0("input").toString()}),e.batchSize==null&&(e.batchSize=null),e.sparse==null&&(e.sparse=!1),this.trainable=!1,this.built=!0,this.sparse=e.sparse,e.inputShape!=null&&e.batchInputShape!=null)throw new j("Only provide the inputShape OR batchInputShape argument to inputLayer, not both at the same time.");let t=e.batchInputShape;if(t==null){if(e.inputShape==null)throw new j("An InputLayer should be passed either a `batchInputShape` or an `inputShape`.");t=[e.batchSize].concat(e.inputShape)}else if(e.batchSize!=null)throw new j("Cannot specify batchSize if batchInputShape is specified when creating an InputLayer.");let n=e.dtype||"float32";this.batchInputShape=t,this.dtype=n,this.inputSpec=[{shape:t}];let s=new Cr(this.dtype,this.batchInputShape,this,[],{},this.name);s.nodeIndex=0,s.tensorIndex=0,new i2({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:[s],outputTensors:[s],inputMasks:[null],outputMasks:[null],inputShapes:[t],outputShapes:[t]})}apply(e,t){throw new j(`Cannot pass any input to an InputLayer's apply() method. InputLayer name: ${this.name}`)}dispose(){return{refCountAfterDispose:this._refCount,numDisposedVariables:0}}getConfig(){return{batchInputShape:this.batchInputShape,dtype:this.dtype,sparse:this.sparse,name:this.name}}};Zc.className="InputLayer";de.registerClass(Zc);function w8(e){if(e.batchShape==null&&e.shape==null)throw new Error("Please provide to Input either a `shape` or a `batchShape` argument. Note that `shape` does not include the batch dimension.");if(e.batchShape!=null&&e.shape!=null)throw new j("Please provide either a `shape` or `batchShape` argument to Input, but not both.");let t=e.batchShape;e.shape!=null&&t==null&&(t=[null].concat(e.shape));let n=e.dtype;return n==null&&(n="float32"),new Zc({batchInputShape:t,name:e.name,dtype:n,sparse:e.sparse}).inboundNodes[0].outputTensors[0]}function MV(e,t){if(e.dtype==null||e.dtype===t.dtype)return t;try{return ge(t,e.dtype)}catch(n){throw new j(`The dtype of the feed (${t.dtype}) can not be cast to the dtype of the key '${e.name}' (${e.dtype}).`)}}var Wi=class{constructor(e){if(this.id2Value={},this.id2Mask={},this.name2Id={},e instanceof Wi)for(let t in e.id2Value)this.id2Value[t]=e.id2Value[t],t in e.id2Mask&&(this.id2Mask[t]=e.id2Mask[t]);else{if(e==null)return;for(let t of e)this.add(t.key,t.value)}}add(e,t,n){if(this.id2Value[e.id]==null)this.id2Value[e.id]=MV(e,t),this.name2Id[e.name]=e.id,n!=null&&(this.id2Mask[e.id]=n);else throw new j(`Duplicate key: name=${e.name}, id=${e.id}`);return this}addFeed(e){this.add(e.key,e.value)}hasKey(e){return this.id2Value[e.id]!=null}names(){return Object.keys(this.name2Id)}getValue(e){if(e instanceof Cr){if(this.id2Value[e.id]==null)throw new j(`Nonexistent key: ${e.name}`);return this.id2Value[e.id]}else{let t=this.name2Id[e];if(t==null)throw new j(`Feed dict has no SymbolicTensor name: ${e}`);return this.id2Value[t]}}getMask(e){if(e instanceof Cr){if(this.id2Value[e.id]==null)throw new j(`Nonexistent key: ${e.name}`);return this.id2Mask[e.id]}else{let t=this.name2Id[e];if(t==null)throw new j(`Feed dict has no SymbolicTensor name: ${e}`);return this.id2Mask[t]}}disposeMasks(){this.id2Mask!=null&&ne(this.id2Mask)}},bm=new c8,vm=new c8;function zV(e){bm!=null&&bm.setMaxEntries(e),vm!=null&&vm.setMaxEntries(e)}function rp(e,t,n,s){let r=n==null?!1:n.training,a=Array.isArray(e),o=a?e:[e],i=o.map(f=>f.name),l=[],u=t.names();for(let f of i)u.indexOf(f)!==-1?l.push(t.getValue(f)):l.push(null);s!=null&&(s.maxNumTensors=-1/0,s.minNumTensors=1/0);let c=i.join(",")+"|"+t.names().sort().join(","),p=bm.get(c),d;if(p==null){let f=LV(o,t);p=f.sorted,d=f.recipientCounts,bm.put(c,p),vm.put(c,d)}d={},r||Object.assign(d,vm.get(c));let h=new Wi(t);for(let f=0;f<p.length;++f){if(s!=null){let R=gm().numTensors;R>s.maxNumTensors&&(s.maxNumTensors=R),R<s.minNumTensors&&(s.minNumTensors=R)}let m=p[f],g=m.sourceLayer;if(g instanceof Zc)continue;let y=[],x=[],A=[],b=!1;for(let R of m.inputs){let P=h.getValue(R),_=h.getMask(R);y.push(P),x.push(_),_!=null&&(b=!0),r||(d[R.name]--,d[R.name]===0&&!t.hasKey(R)&&i.indexOf(R.name)===-1&&!P.isDisposed&&R.sourceLayer.stateful!==!0&&A.push(P))}b&&(n=n||{},n.mask=x[0]);let w=_t(g.apply(y,n)),k=null;g.supportsMasking&&(k=g.computeMask(y,x));let S=WV(m),E=Array.isArray(S)?S:[S];for(let R=0;R<E.length;++R){h.hasKey(E[R])||h.add(E[R],w[R],Array.isArray(k)?k[0]:k);let P=i.indexOf(E[R].name);P!==-1&&(l[P]=w[R])}r||ne(A)}return h.disposeMasks(),a?l:l[0]}function LV(e,t){v.assert(e!=null&&e.length>0,()=>"Expected at least one fetch, got none");let n=[],s={};if(e.length===1){let r=Mv(e[0],t);n=r.sorted,s=r.recipientMap}else{let r=new Set;for(let a of e){let{sorted:o,recipientMap:i}=Mv(a,t);for(let l of o)r.has(l.name)||(n.push(l),r.add(l.name));for(let l in i)s[l]==null&&(s[l]=new Set),i[l].forEach(u=>s[l].add(u))}}return{sorted:n,recipientCounts:BV(s)}}function BV(e){let t={};for(let n in e)t[n]=e[n].size;return t}function Mv(e,t){let n=new Set,s=[],r={};for(let i of t.names())n.add(i);let a=[],o=[];for(a.push(e);a.length>0;){let i=a[a.length-1];if(n.has(i.name)){a.pop();continue}let l=o[o.length-1]===a.length-1;if(i.inputs.length===0||l)a.pop(),s.push(i),n.add(i.name),l&&o.pop();else{o.push(a.length-1);for(let u of i.inputs)r[u.name]==null&&(r[u.name]=new Set),r[u.name].add(i.name),!n.has(u.name)&&a.push(u)}}return{sorted:s,recipientMap:r}}function WV(e){let t;if(e.sourceLayer.inboundNodes.length===1)t=e.sourceLayer.output;else{let n=null;for(let s=0;s<e.sourceLayer.inboundNodes.length;++s)for(let r of e.sourceLayer.inboundNodes[s].outputTensors)if(r.id===e.id){n=s;break}t=e.sourceLayer.getOutputAt(n)}return t}var VV=X();VV.registerFlag("TOPOLOGICAL_SORT_CACHE_MAX_ENTRIES",()=>100,zV);var k8={};Ve(k8,{maxNorm:()=>UV,minMaxNorm:()=>jV,nonNeg:()=>HV,unitNorm:()=>GV});function a5(e,t){return J(()=>Nn(ke(L(e,e),t,!0)))}var Sh=class extends de.Serializable{getConfig(){return{}}},o5=class extends Sh{constructor(e){super(),this.defaultMaxValue=2,this.defaultAxis=0,this.maxValue=e.maxValue!=null?e.maxValue:this.defaultMaxValue,this.axis=e.axis!=null?e.axis:this.defaultAxis}apply(e){return J(()=>{let t=a5(e,this.axis),n=fs(t,0,this.maxValue);return L(e,pe(n,ce(hn(),t)))})}getConfig(){return{maxValue:this.maxValue,axis:this.axis}}};o5.className="MaxNorm";de.registerClass(o5);var i5=class extends Sh{constructor(e){super(),this.defaultAxis=0,this.axis=e.axis!=null?e.axis:this.defaultAxis}apply(e){return J(()=>pe(e,ce(hn(),a5(e,this.axis))))}getConfig(){return{axis:this.axis}}};i5.className="UnitNorm";de.registerClass(i5);var l5=class extends Sh{apply(e){return $r(e)}};l5.className="NonNeg";de.registerClass(l5);var u5=class extends Sh{constructor(e){super(),this.defaultMinValue=0,this.defaultMaxValue=1,this.defaultRate=1,this.defaultAxis=0,this.minValue=e.minValue!=null?e.minValue:this.defaultMinValue,this.maxValue=e.maxValue!=null?e.maxValue:this.defaultMaxValue,this.rate=e.rate!=null?e.rate:this.defaultRate,this.axis=e.axis!=null?e.axis:this.defaultAxis}apply(e){return J(()=>{let t=a5(e,this.axis),n=ce(L(this.rate,fs(t,this.minValue,this.maxValue)),L(1-this.rate,t));return L(e,pe(n,ce(hn(),t)))})}getConfig(){return{minValue:this.minValue,maxValue:this.maxValue,rate:this.rate,axis:this.axis}}};u5.className="MinMaxNorm";de.registerClass(u5);var zv={maxNorm:"MaxNorm",minMaxNorm:"MinMaxNorm",nonNeg:"NonNeg",unitNorm:"UnitNorm"};function gn(e){return XA(e)}function Lv(e,t={}){return vh(e,de.SerializationMap.getMap().classNameMap,t,"constraint")}function yn(e){if(e==null)return null;if(typeof e=="string"){let n={className:e in zv?zv[e]:e,config:{}};return Lv(n)}else return e instanceof Sh?e:Lv(e)}function UV(e){return new o5(e)}function GV(e){return new i5(e)}function HV(){return new l5}function jV(e){return new u5(e)}var I8={};Ve(I8,{constant:()=>KV,glorotNormal:()=>nU,glorotUniform:()=>tU,heNormal:()=>sU,heUniform:()=>rU,identity:()=>QV,leCunNormal:()=>aU,leCunUniform:()=>oU,ones:()=>XV,orthogonal:()=>iU,randomNormal:()=>YV,randomUniform:()=>ZV,truncatedNormal:()=>JV,varianceScaling:()=>eU,zeros:()=>qV});function qV(){return new YA}function XV(){return new e2}function KV(e){return new JA(e)}function ZV(e){return new QA(e)}function YV(e){return new e5(e)}function JV(e){return new t5(e)}function QV(e){return new n5(e)}function eU(e){return new ms(e)}function tU(e){return new t2(e)}function nU(e){return new n2(e)}function sU(e){return new s2(e)}function rU(e){return new r2(e)}function aU(e){return new a2(e)}function oU(e){return new o2(e)}function iU(e){return new s5(e)}var S8={};Ve(S8,{Layer:()=>ut,RNN:()=>Jr,RNNCell:()=>Rh,activation:()=>$G,add:()=>VG,alphaDropout:()=>SH,average:()=>UG,averagePooling1d:()=>gx,averagePooling2d:()=>yx,averagePooling3d:()=>Ax,avgPool1d:()=>JG,avgPool2d:()=>eH,avgPool3d:()=>nH,avgPooling1d:()=>QG,avgPooling2d:()=>tH,avgPooling3d:()=>sH,batchNormalization:()=>KG,bidirectional:()=>yH,concatenate:()=>GG,conv1d:()=>IG,conv2d:()=>SG,conv2dTranspose:()=>CG,conv3d:()=>TG,conv3dTranspose:()=>NG,convLstm2d:()=>hH,convLstm2dCell:()=>fH,cropping2D:()=>RG,dense:()=>PG,depthwiseConv2d:()=>DG,dot:()=>XG,dropout:()=>FG,elu:()=>AG,embedding:()=>WG,flatten:()=>MG,gaussianDropout:()=>IH,gaussianNoise:()=>kH,globalAveragePooling1d:()=>rH,globalAveragePooling2d:()=>aH,globalMaxPool1d:()=>xH,globalMaxPool2d:()=>bH,globalMaxPooling1d:()=>gk,globalMaxPooling2d:()=>yk,gru:()=>iH,gruCell:()=>lH,input:()=>U8,inputLayer:()=>yG,layerNormalization:()=>ZG,leakyReLU:()=>bG,lstm:()=>uH,lstmCell:()=>cH,masking:()=>CH,maxPool1d:()=>vH,maxPool2d:()=>wH,maxPooling1d:()=>Ak,maxPooling2d:()=>xk,maxPooling3d:()=>oH,maximum:()=>HG,minimum:()=>jG,multiply:()=>qG,permute:()=>BG,prelu:()=>vG,reLU:()=>xG,repeatVector:()=>zG,reshape:()=>LG,rnn:()=>mH,separableConv2d:()=>EG,simpleRNN:()=>dH,simpleRNNCell:()=>pH,softmax:()=>wG,spatialDropout1d:()=>OG,stackedRNNCells:()=>gH,thresholdedReLU:()=>kG,timeDistributed:()=>AH,upSampling2d:()=>_G,zeroPadding2d:()=>YG});async function Wa(e){if(e==null)return;let t=[],n=[],s=[];for(let r in e){let a=e[r];if(typeof a!="number"){let o=a;t.push(o.data()),n.push(r),s.push(o)}}if(t.length>0){let r=await Promise.all(t);for(let a=0;a<r.length;++a)e[n[a]]=r[a][0];ne(s)}}function C8(e){if(e!=null)for(let t in e){let n=e[t];typeof n!="number"&&n.dispose()}}var Bv;(function(e){e[e.SILENT=0]="SILENT",e[e.VERBOSE=1]="VERBOSE"})(Bv||(Bv={}));var lU=125,tc=class{constructor(){this.validationData=null}setParams(e){this.params=e}async onEpochBegin(e,t){}async onEpochEnd(e,t){}async onBatchBegin(e,t){}async onBatchEnd(e,t){}async onTrainBegin(e){}async onTrainEnd(e){}setModel(e){}},T8=class{constructor(e,t=10){e==null&&(e=[]),this.callbacks=e,this.queueLength=t}append(e){this.callbacks.push(e)}setParams(e){for(let t of this.callbacks)t.setParams(e)}setModel(e){for(let t of this.callbacks)t.setModel(e)}async onEpochBegin(e,t){t==null&&(t={});for(let n of this.callbacks)await n.onEpochBegin(e,t)}async onEpochEnd(e,t){t==null&&(t={});for(let n of this.callbacks)await n.onEpochEnd(e,t)}async onBatchBegin(e,t){t==null&&(t={});for(let n of this.callbacks)await n.onBatchBegin(e,t)}async onBatchEnd(e,t){t==null&&(t={});for(let n of this.callbacks)await n.onBatchEnd(e,t)}async onTrainBegin(e){e==null&&(e={});for(let t of this.callbacks)await t.onTrainBegin(e)}async onTrainEnd(e){e==null&&(e={});for(let t of this.callbacks)await t.onTrainEnd(e)}},uU=class extends tc{constructor(){super()}async onEpochBegin(e){this.seen=0,this.totals={}}async onBatchEnd(e,t){t==null&&(t={});let n=t.size==null?0:t.size;this.seen+=n;for(let s in t){let r=t[s];if(typeof r=="number")this.totals.hasOwnProperty(s)||(this.totals[s]=0),this.totals[s]=this.totals[s]+r*n;else{let a;s in this.totals?a=this.totals[s]:this.totals[s]=0;let o=J(()=>ce(this.totals[s],L(r,n)));this.totals[s]=o,a!=null&&a.dispose()}}}async onEpochEnd(e,t){if(t!=null)for(let n of this.params.metrics)this.totals[n]!=null&&(typeof this.totals[n]=="number"?t[n]=this.totals[n]/this.seen:J(()=>{let s=L(pe(1,this.seen),this.totals[n]);t[n]=s,this.totals[n].dispose(),bn(t[n])}))}},N8=class extends tc{async onTrainBegin(e){this.epoch=[],this.history={}}async onEpochEnd(e,t){t==null&&(t={}),this.epoch.push(e);for(let n in t)this.history[n]==null&&(this.history[n]=[]),this.history[n].push(t[n])}async syncData(){let e=[],t=[],n=[];for(let r in this.history){let a=this.history[r];for(let o=0;o<a.length;++o)if(typeof a[o]!="number"){let i=a[o];e.push(i.data()),t.push(r),n.push(o)}}let s=await Promise.all(e);for(let r=0;r<s.length;++r)this.history[t[r]][n[r]].dispose(),this.history[t[r]][n[r]]=s[r][0]}},E8=class extends tc{constructor(e,t){if(super(),this.currentEpoch=0,this.nowFunc=e.nowFunc,this.nextFrameFunc=e.nextFrameFunc||jA,this.yieldEvery=t||"auto",this.yieldEvery==="auto"&&(this.yieldEvery=lU),this.yieldEvery==="never"&&e.onYield!=null)throw new Error("yieldEvery is `never` but you provided an `onYield` callback. Either change `yieldEvery` or remove the callback");v.isNumber(this.yieldEvery)&&(this.maybeWait=cV(this.maybeWait.bind(this),this.yieldEvery,this.nowFunc)),this.trainBegin=e.onTrainBegin,this.trainEnd=e.onTrainEnd,this.epochBegin=e.onEpochBegin,this.epochEnd=e.onEpochEnd,this.batchBegin=e.onBatchBegin,this.batchEnd=e.onBatchEnd,this.yield=e.onYield}async maybeWait(e,t,n){let s=[];this.yield!=null&&(await Wa(n),s.push(this.yield(e,t,n))),s.push(this.nextFrameFunc()),await Promise.all(s)}async onEpochBegin(e,t){this.currentEpoch=e,this.epochBegin!=null&&(await Wa(t),await this.epochBegin(e,t))}async onEpochEnd(e,t){let n=[];this.epochEnd!=null&&(await Wa(t),n.push(this.epochEnd(e,t))),this.yieldEvery==="epoch"&&n.push(this.nextFrameFunc()),await Promise.all(n)}async onBatchBegin(e,t){this.batchBegin!=null&&(await Wa(t),await this.batchBegin(e,t))}async onBatchEnd(e,t){let n=[];this.batchEnd!=null&&(await Wa(t),n.push(this.batchEnd(e,t))),this.yieldEvery==="batch"?n.push(this.nextFrameFunc()):v.isNumber(this.yieldEvery)&&n.push(this.maybeWait(this.currentEpoch,e,t)),await Promise.all(n)}async onTrainBegin(e){this.trainBegin!=null&&(await Wa(e),await this.trainBegin(e))}async onTrainEnd(e){this.trainEnd!=null&&(await Wa(e),await this.trainEnd(e))}};function R8(e,t){return e==null&&(e={}),e instanceof tc?[e]:Array.isArray(e)&&e[0]instanceof tc?e:_t(e).map(s=>new E8(s,t))}var rr=class{constructor(){}static registerCallbackConstructor(e,t){v.assert(e>=0&&Number.isInteger(e),()=>`Verbosity level is expected to be an integer >= 0, but got ${e}`),rr.checkForDuplicate(t),rr.constructors[e]==null&&(rr.constructors[e]=[]),rr.constructors[e].push(t)}static checkForDuplicate(e){for(let t in rr.constructors)rr.constructors[+t].forEach(s=>{if(s===e)throw new j("Duplicate callback constructor.")})}static clear(){rr.constructors={}}static createCallbacks(e){let t=[];for(let n in rr.constructors){let s=+n;e>=s&&t.push(...rr.constructors[s])}return t.map(n=>new n)}};rr.constructors={};function _8(e,t,n,s,r,a,o,i,l){let u=new N8,c=[new uU,...rr.createCallbacks(t)];e!=null&&c.push(...e),c.push(u);let p=new T8(c);return p.setParams({epochs:n,initialEpoch:s,samples:r,steps:a,batchSize:o,verbose:t,doValidation:i,metrics:l}),{callbackList:p,history:u}}function Nr(e,t={},n=!1){return vh(e,de.SerializationMap.getMap().classNameMap,t,"layer",n)}function wm(e,t){return J(()=>{e.dtype!=="float32"&&(e=ge(e,"float32"));let n=ke(kh(e),t,!0),s=Gc(n.shape,hn()),r=Nn(Yr(n,s));return pe(e,r)})}function eu(e,t){return J(()=>Bt(kh(he(t,e)),-1))}function l2(e,t){return J(()=>Bt(tn(he(t,e)),-1))}function Yc(e,t){return J(()=>{let n=he(e,t),s=fs(tn(e),hn(),Number.MAX_VALUE),r=tn(pe(n,s));return L(100,Bt(r,-1))})}function cU(e,t){return J(()=>{let n=fs(t,hn(),Number.MAX_VALUE),s=Ds(ce(1,n)),r=fs(e,hn(),Number.MAX_VALUE),a=Ds(ce(1,r));return Bt(kh(he(s,a)),-1)})}function dU(e,t){return J(()=>{let n=Yr(0,he(1,L(e,t)));return Bt(kh(n),-1)})}function pU(e,t){return J(()=>{let n=Yr(0,he(1,L(e,t)));return Bt(n,-1)})}function hU(e,t){return J(()=>{let n=ke(L(e,t),-1),s=mn(L(he(1,e),t),-1);return Yr(0,ce(1,he(s,n)))})}function fU(e,t){return J(()=>{let n=Math.log(2),s=he(t,e),r=he(ce(s,Kl(L(-2,s))),n);return Bt(r,-1)})}function Tp(e,t,n=!1){return J(()=>{if(n)t=Yl(t);else{let s=ke(t,t.shape.length-1,!0);t=pe(t,s)}return t=fs(t,hn(),1-hn()),Dt(ke(L(ge(e,"float32"),Ds(t)),t.shape.length-1))})}function km(e,t,n=!1){return J(()=>{let s=ge(Hc(wV(e)),"int32");t=fs(t,hn(),1-hn());let r=t.shape,a=U(Ku(s,r[r.length-1]),r);return Tp(a,t,n)})}function mU(e,t){if(!v.arraysEqual(e.shape,t.shape))throw new j(`logits and labels must have the same shape, but got shapes ${JSON.stringify(e.shape)} and ${JSON.stringify(t.shape)}`);return J(()=>{let n=$r(t),s=Dt(tn(t));return ce(he(n,L(t,e)),dh(_s(s)))})}function u2(e,t){return J(()=>{let n;return n=fs(t,hn(),1-hn()),n=Ds(pe(n,he(1,n))),Bt(mU(e,n),-1)})}function gU(e,t){return J(()=>{let n=fs(e,hn(),1),s=fs(t,hn(),1);return ke(L(e,Ds(pe(n,s))),-1)})}function yU(e,t){return J(()=>{let n=Ds(ce(hn(),t));return Bt(he(t,L(e,n)),-1)})}function c5(e,t){return J(()=>{let n=wm(e,-1),s=wm(t,-1),r=L(n,s);return Dt(ke(r,-1))})}var Im={meanSquaredError:eu,meanAbsoluteError:l2,meanAbsolutePercentageError:Yc,meanSquaredLogarithmicError:cU,squaredHinge:dU,hinge:pU,categoricalHinge:hU,logcosh:fU,categoricalCrossentropy:Tp,sparseCategoricalCrossentropy:km,binaryCrossentropy:u2,kullbackLeiblerDivergence:gU,poisson:yU,cosineProximity:c5};function u3(e){if(typeof e=="string"){if(e in Im)return Im[e];let t=`Unknown loss ${e}`;throw e.toLowerCase().includes("softmaxcrossentropy")&&(t=`Unknown loss ${e}. Use "categoricalCrossentropy" as the string name for tf.losses.softmaxCrossEntropy`),new j(t)}else return e}function d5(e,t){return J(()=>{let n=L(.5,$s(t)),s=J0(ys(t,n),e.dtype);return Bt(Rs(e,s),-1)})}function p5(e,t){return J(()=>J0(Rs(Es(e,-1),Es(t,-1)),"float32"))}function D8(e,t){return J(()=>ge(ke(lr(Rs(e,1),Rs(t,1))),"float32"))}function AU(e,t){return J(()=>ge(ke(lr(Rs(e,1),Rs(t,0))),"float32"))}function xU(e,t){return J(()=>ge(ke(lr(Rs(e,0),Rs(t,1))),"float32"))}function $8(e,t){return J(()=>{let n=D8(e,t),s=xU(e,t),r=ce(n,s);return ge(Mn(ys(r,0),pe(n,r),0),"float32")})}function bU(e,t){return J(()=>{let n=D8(e,t),s=AU(e,t),r=ce(n,s);return ge(Mn(ys(r,0),pe(n,r),0),"float32")})}function P8(e,t){return u2(e,t)}function F8(e,t){return e.rank===t.rank&&(e=rt(e,[e.rank-1])),t=Es(t,-1),t.dtype!==e.dtype&&(t=ge(t,e.dtype)),ge(Rs(e,t),"float32")}var vU=eu,wU=eu,kU=l2,IU=l2,SU=Yc,CU=Yc,h5=Tp,TU=c5,O8=km,Sm={binaryAccuracy:d5,categoricalAccuracy:p5,precision:$8,categoricalCrossentropy:h5,sparseCategoricalCrossentropy:O8,mse:vU,MSE:wU,mae:kU,MAE:IU,mape:SU,MAPE:CU,cosine:TU};function NU(e){if(typeof e=="string"&&e in Sm)return Sm[e];if(typeof e!="string"&&e!=null)return e;throw new j(`Unknown metric ${e}`)}function Uf(e){if(Wr(e!==null,`Unknown LossOrMetricFn ${e}`),typeof e=="string")return e;{let t;for(let n of Object.keys(Im))if(Im[n]===e){t=n;break}if(t!==void 0)return t;for(let n of Object.keys(Sm))if(Sm[n]===e){t=n;break}return t!==void 0?t:e.name}}function EU(e){let t={Adagrad:()=>Pi.adagrad(.01),Adadelta:()=>Pi.adadelta(1,.95,hn()),Adam:()=>Pi.adam(.001,.9,.999,hn()),Adamax:()=>Pi.adamax(.002,.9,.999,hn(),0),RMSProp:()=>Pi.rmsprop(.001,.9,0,hn()),SGD:()=>Pi.sgd(.01)};if(t.adagrad=t.Adagrad,t.adadelta=t.Adadelta,t.adam=t.Adam,t.adamax=t.Adamax,t.rmsprop=t.RMSProp,t.sgd=t.SGD,e in t)return t[e]();throw new j(`Unknown Optimizer ${e}`)}var Wv=1*1024*1024;function Vv(e,t,n=!1){if(e==null||typeof e!="object"||Object.getPrototypeOf(e)!==Object.prototype||!O3(e))throw new Error("User-defined metadata is expected to be a JSON object, but is not.");if(n){let s=JSON.stringify(e);s.length>Wv&&console.warn(`User-defined metadata of model "${t}" is too large in size (length=${s.length} when serialized). It is not recommended to store such large objects in user-defined metadata. Please make sure its serialized length is <= ${Wv}.`)}}function O3(e){if(e===null)return!0;if(typeof e=="object")if(Object.getPrototypeOf(e)===Object.prototype){let t=Object.keys(e);for(let n of t)if(typeof n!="string"||!O3(e[n]))return!1;return!0}else if(Array.isArray(e)){for(let t of e)if(!O3(t))return!1;return!0}else return!1;else{let t=typeof e;return t==="string"||t==="number"||t==="boolean"}}function RU(e,t,n,s=console.log){let r=DU(e),a=["Layer (type)","Input Shape","Output shape","Param #"];r?(t=t||90,n=n||[.32,.61,.89,1]):(t=t||115,n=n||[.24,.48,.7,.8,1]),n[n.length-1]<=1&&(n=n.map(c=>Math.floor(t*c)));let o;if(!r){a.push("Receives inputs"),o=[];for(let c in e.nodesByDepth)o.push(...e.nodesByDepth[c])}s("_".repeat(t)),Cm(a,n,s),s("=".repeat(t));let i=e.layers;for(let c=0;c<i.length;++c)r?$U(i[c],n,s):PU(i[c],n,o,s),s((c===i.length-1?"=":"_").repeat(t));e.checkTrainableWeightsConsistency();let l=_U(e),u=xm(e.nonTrainableWeights);s(`Total params: ${l+u}`),s(`Trainable params: ${l}`),s(`Non-trainable params: ${u}`),s("_".repeat(t))}function _U(e){let t;return e.collectedTrainableWeights!=null?t=xm(e.collectedTrainableWeights):t=xm(e.trainableWeights),t}function DU(e){let t=!0,n=[],s=[];for(let r in e.nodesByDepth)n.push(e.nodesByDepth[r]);for(let r of n){if(r.length>1||r.length===1&&r[0].inboundLayers.length>1){t=!1;break}s.push(...r)}if(t)for(let r of e.layers){let a=!1;for(let o of r.inboundNodes)if(s.indexOf(o)!==-1)if(a){t=!1;break}else a=!0;if(!t)break}return t}function Cm(e,t,n=console.log){let s="";for(let r=0;r<e.length;++r)r>0&&(s=s.slice(0,s.length-1)+" "),s+=e[r],s=s.slice(0,t[r]),s+=" ".repeat(t[r]-s.length);n(s)}function $U(e,t,n){let s,r;try{r=e.inboundNodes.map(l=>JSON.stringify(l.inputShapes)).join(",")}catch(l){r="multiple"}try{s=JSON.stringify(e.outputShape)}catch(l){s="multiple"}let a=e.name,o=e.getClassName(),i=[`${a} (${o})`,r,s,e.countParams().toString()];Cm(i,t,n)}function PU(e,t,n,s){let r,a;try{a=e.inboundNodes.map(p=>JSON.stringify(p.inputShapes)).join(",")}catch(p){a="multiple"}try{r=JSON.stringify(e.outputShape)}catch(p){r="multiple"}let o=[];for(let p of e.inboundNodes)if(!(n!=null&&n.length>0&&n.indexOf(p)===-1))for(let d=0;d<p.inboundLayers.length;++d){let h=p.inboundLayers[d].name,f=p.nodeIndices[d],m=p.tensorIndices[d];o.push(`${h}[${f}][${m}]`)}let i=e.name,l=e.getClassName(),u=o.length===0?"":o[0],c=[`${i} (${l})`,a,r,e.countParams().toString(),u];Cm(c,t,s);for(let p=1;p<o.length;++p)Cm(["","","","",o[p]],t,s)}function M8(e,t,n){return(e==="inboundNodes"||e==="outputLayers"||e==="inputLayers")&&t===0&&typeof n=="string"}function Np(e,t){if(e===null)return null;if(typeof e=="string")return zi(e);if(typeof e=="number"||typeof e=="boolean")return e;if(e instanceof Array){let n=[],s=e.length;for(let r=0;r<s;++r){let a=e[r];M8(t,r,a)?n.push(a):n.push(Np(a,t))}return n}else{let n={};for(let s of Object.keys(e)){let r=e[s];if(s==="name"&&typeof r=="string")n[s]=r;else{let a=zi(s);n[a]=Np(r,a)}}return n}}function M3(e,t){if(e==null)return null;if(typeof e=="string")return la(e);if(typeof e=="number"||typeof e=="boolean")return e;if(e instanceof Array){let n=[],s=e.length;for(let r=0;r<s;++r){let a=e[r];M8(t,r,a)?n.push(a):n.push(M3(a,t))}return n}else{let n={};for(let s of Object.keys(e)){let r=e[s],a=la(s);(s==="name"||s==="className")&&typeof r=="string"?n[a]=r:n[a]=M3(r,s)}return n}}var f5="3.19.0",Br=class extends ut{constructor(e){if(super({}),this.containerNodes=new Set,this.name=e.name,this.name==null){let y=this.getClassName().toLowerCase();this.name=Y0(y)}if(this.supportsMasking=!1,this.trainable_=!0,Array.isArray(e.inputs)?this.inputs=e.inputs.slice():this.inputs=[e.inputs],Array.isArray(e.outputs)?this.outputs=e.outputs.slice():this.outputs=[e.outputs],qa(this.inputs).length!==this.inputs.length)throw new j(`The list of inputs passed to the model is redundant. All inputs should only appear once. Found: ${this.inputs.map(y=>y.name)}`);qa(this.outputs).length!==this.outputs.length&&console.warn(`The list of outputs passed to the model is redundant. All outputs should only appear once. Found: ${this.outputs.map(y=>y.name)}`),this.inputLayers=[],this.inputLayersNodeIndices=[],this.inputLayersTensorIndices=[],this.outputLayers=[],this.outputLayersNodeIndices=[],this.outputLayersTensorIndices=[],this.layers=[],this.internalContainerRefs=[];for(let y of this.outputs){let x=y.sourceLayer,A=y.nodeIndex,b=y.tensorIndex;this.outputLayers.push(x),this.outputLayersNodeIndices.push(A),this.outputLayersTensorIndices.push(b)}for(let y of this.inputs){let x=y.sourceLayer,A=y.nodeIndex,b=y.tensorIndex;Wr(A===0,"input layer has >1 nodes"),Wr(b===0,"input layer has >1 tensors"),this.inputLayers.push(x),this.inputLayersNodeIndices.push(A),this.inputLayersTensorIndices.push(b)}this.inputNames=[],this.outputNames=[],this.feedInputShapes=[],this.feedInputNames=[],this.feedOutputNames=[];for(let y=0;y<this.inputLayers.length;y++){let x=this.inputLayers[y];if(!(x instanceof Zc))throw new TypeError(`Input layers to a LayersModel must be InputLayer objects. Received inputs: ${e.inputs}. Input ${y} (0-based) originates from layer type ${x.getClassName()}.`);this.inputNames.push(x.name),this.feedInputShapes.push(x.batchInputShape),this.feedInputNames.push(x.name)}for(let y of this.outputLayers)this.outputNames.push(y.name);this.internalInputShapes=this.inputs.map(y=>y.shape),this.internalOutputShapes=this.outputs.map(y=>y.shape);let t={},n={},s={},r={},a={},o=[],i=(y,x,A,b,w,k)=>{(b==null||w==null||k==null)&&(b=y.sourceLayer,w=y.nodeIndex,k=y.tensorIndex);let S=b.inboundNodes[w];if(A.indexOf(S)!==-1)throw new Sr(`The tensor ${y.name} at layer "${b.name}" is part of a cycle.`);if(x.indexOf(S)!==-1)return;this.containerNodes.add(Br.nodeKey(b,w)),b.id in a||(a[b.id]=Object.keys(a).length),A.indexOf(S)===-1&&A.push(S);let E=S.inboundLayers.length;for(let R=0;R<E;R++){let P=S.inputTensors[R],_=S.inboundLayers[R],$=S.nodeIndices[R],T=S.tensorIndices[R];i(P,x,A,_,$,T)}for(x.push(S);A.indexOf(S)>=0;)A.splice(A.indexOf(S),1);o.push(S)},l=[],u=[];for(let y of this.outputs)i(y,l,u);let c=o.slice().reverse();for(let y of c){n[y.id]=y,y.id in t||(t[y.id]=0);let x=t[y.id],A=s[y.outboundLayer.id]==null?0:s[y.outboundLayer.id];x=Math.max(x,A),s[y.outboundLayer.id]=x,r[y.outboundLayer.id]=y.outboundLayer,t[y.id]=x;for(let b=0;b<y.inboundLayers.length;b++){let w=y.inboundLayers[b],k=y.nodeIndices[b],S=w.inboundNodes[k],E=t[S.id]==null?0:t[S.id];t[S.id]=Math.max(x+1,E),n[S.id]=S}}let p={};for(let y in t){let x=t[y];x in p||(p[x]=[]),p[x].push(n[y])}let d={};for(let y in s){let x=s[y];x in d||(d[x]=[]),d[x].push(r[y])}let h=Object.keys(d).map(y=>parseInt(y,10)).sort(Bf);this.layers=[];for(let y of h){let x=d[y];x.sort((A,b)=>{let w=a[A.id],k=a[b.id];return w<k?-1:w>k?1:0});for(let A of x)A instanceof Br&&this.internalContainerRefs.push(A),this.layers.push(A)}this.layersByDepth=d,h=Object.keys(p).map(y=>parseInt(y,10)).sort(Bf);let f=this.inputs.slice(),m=[];for(let y of h)for(let x of p[y]){let A=x.outboundLayer;if(A!=null){for(let b of x.inputTensors)if(f.indexOf(b)===-1)throw new Sr(`Graph disconnected: cannot obtain value for tensor ${b} at layer "${A.name}". The following previous layers were accessed without issue: ${m}`);for(let b of x.outputTensors)f.push(b);m.push(A.name)}}this.nodesByDepth=p;let g=this.layers.map(y=>y.name);for(let y of g){let x=g.filter(A=>A===y).length;if(x!==1)throw new Sr(`The name "${y}" is used ${x} times in the model. All layer names should be unique. Layer names: `+JSON.stringify(g))}this.outboundNodes=[],this.inboundNodes=[],new i2({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:this.inputs.map(y=>null),outputMasks:this.outputs.map(y=>null),inputShapes:this.inputs.map(y=>y.shape),outputShapes:this.outputs.map(y=>y.shape)}),this.built=!0,this._refCount=1}assertNotDisposed(){if(this._refCount===0)throw new Error(`Container '${this.name}' is already disposed.`)}dispose(){this.assertNotDisposed();let e={refCountAfterDispose:null,numDisposedVariables:0};if(--this._refCount===0){for(let t of this.layers)e.numDisposedVariables+=t.dispose().numDisposedVariables;for(let t of this.internalContainerRefs)e.numDisposedVariables+=t.dispose().numDisposedVariables}return e.refCountAfterDispose=this._refCount,e}get trainable(){return this.trainable_}set trainable(e){this.layers.forEach(t=>{t._trainableWeights.forEach(n=>n.trainable=e)}),this.trainable_=e}get trainableWeights(){if(this._trainableWeights.length>0)throw new j("Container instance unexpectedly contains _trainableWeights.The trainable weights of a Container are a union of the trainable weights of its consituent Layers. Its own _trainableWeights must remain an empty Array.");if(!this.trainable)return[];let e=[];for(let t of this.layers)e=e.concat(t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.layers)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.layers)t.push(...n.trainableWeights);return t.concat(e)}return e}get weights(){return this.trainableWeights.concat(this.nonTrainableWeights)}loadWeights(e,t=!0){let n={},s=0;for(let a of this.layers)for(let o of a.weights){if(n[o.originalName]!=null)throw new j(`Duplicate weight name: ${o.originalName}`);n[o.originalName]=o,s++}let r=[];for(let a in e){let o=a;if(n[a]==null){let i=a.split("/");o=i.slice(0,-2).concat([i[i.length-1]]).join("/")}if(n[o]!=null)r.push([n[o],e[a]]);else if(t)throw new j(`Provided weight data has no target variable: ${a}`);delete n[o]}if(t){let a=[];for(let o in n)a.push(o);if(a.length>0)throw new j(`${a.length} of ${s} weights are not set: ${a}`)}r5(r)}updatedConfig(){let e=this.getConfig(),t={};return t.className=this.getClassName(),t.config=e,t.kerasVersion=`tfjs-layers ${f5}`,t.backend="TensorFlow.js",t}toJSON(e,t=!0){let n=M3(this.updatedConfig());return t?JSON.stringify(n):n}call(e,t){return J(()=>{e=_t(e);let n=new Wi;for(let s=0;s<this.inputs.length;++s)n.add(this.inputs[s],e[s]);return rp(this.outputs,n,t)})}computeMask(e,t){return J(()=>{e=_t(e);let n;return t==null?n=Qi(null,e.length):n=_t(t),this.runInternalGraph(e,n)[1]})}computeOutputShape(e){let t=Am(e);if(t.length!==this.inputLayers.length)throw new j(`Invalid inputShape argument ${e}: model has ${this.inputLayers.length} tensor inputs.`);let n={};for(let o=0;o<t.length;o++){let i=this.inputLayers[o],l=t[o],u=i.name+"_0_0";n[u]=l}let s=Object.keys(this.nodesByDepth).map(o=>parseInt(o,10)).sort(Bf);if(s.length>1)for(let o of s){let i=this.nodesByDepth[o];for(let l of i){let u=l.outboundLayer;if(this.inputLayers.map(f=>f.id).indexOf(u.id)!==-1)continue;let c=[];for(let f=0;f<l.inboundLayers.length;f++){let m=l.inboundLayers[f],g=l.nodeIndices[f],y=l.tensorIndices[f],x=`${m.name}_${g}_${y}`,A=n[x];c.push(A)}let p=u.computeOutputShape(ps(c)),d=Am(p),h=u.inboundNodes.indexOf(l);for(let f=0;f<d.length;f++){let m=`${u.name}_${h}_${f}`;n[m]=d[f]}}}let r=[],a=[];for(let o=0;o<this.outputLayers.length;o++){let i=this.outputLayers[o],l=this.outputLayersNodeIndices[o],u=this.outputLayersTensorIndices[o],c=`${i.name}_${l}_${u}`;a.push(c)}for(let o=0;o<a.length;o++){let i=a[o];Wr(i in n),r.push(n[i])}return ps(r)}runInternalGraph(e,t){t==null&&(t=Qi(null,e.length));let n={};for(let i=0;i<this.inputs.length;++i){let l=this.inputs[i],u=e[i],c=t[i];n[l.id]=[u,c]}let s=Object.keys(this.nodesByDepth).map(i=>parseInt(i,10)).sort(Bf);for(let i of s){let l=this.nodesByDepth[i];for(let u of l){let c=u.outboundLayer,p=u.inputTensors,d=u.outputTensors,h=new Array;for(let f of p)f.id in n&&h.push(n[f.id]);if(h.length===p.length){let f={},m,g,y,x;if(u.callArgs!=null&&(f=u.callArgs),h.length===1){let[A,b]=h[0];f.mask==null&&(f.mask=b),y=_t(c.call(A,f)),x=_t(c.computeMask(A,b)),m=[A],g=[b]}else m=h.map(A=>A[0]),g=h.map(A=>A[1]),f.mask==null&&(f.mask=g),y=_t(c.call(m,f)),x=_t(c.computeMask(m,g));if(c.activityRegularizer)throw new He("LayersModel invocation with concrete Tensor value(s) in the presence of activity regularizer(s) is not supported yet.");for(let A=0;A<d.length;++A){let b=d[A],w=y[A],k=x[A];n[b.id]=[w,k]}}}}let r=[],a=[],o=[];for(let i of this.outputs){Wr(i.id in n,`Could not compute output ${i.name} : ${i.id}`);let[l,u]=n[i.id];o.push(l.shape),r.push(l),a.push(u)}return[r,a,o]}buildNodeConversionMap(e){let t={},n;for(let s of this.layers){n=s instanceof Br?1:0;for(let r=0;r<s.inboundNodes.length;r++){let a=Br.nodeKey(s,r);this.containerNodes.has(a)&&(t[a]=n,n+=1)}}return t}getLayer(e,t){if(t!=null){if(this.layers.length<=t)throw new j(`Was asked to retrieve layer at index ${t}, but model only has ${this.layers.length} layer(s).`);return this.layers[t]}else if(e==null)throw new j("Provide either a layer name or layer index");for(let n of this.layers)if(n.name===e)return n;throw new j(`No such layer: ${e}`)}calculateLosses(){return J(()=>{let e=[];for(let t of this.layers)for(let n=0;n<t.inboundNodes.length;++n){let s=Br.nodeKey(t,n);this.containerNodes.has(s)&&e.push(...t.calculateLosses())}return e})}getConfig(){let e={name:this.name},t=this.buildNodeConversionMap(this.layers),n=[];for(let a of this.layers){let o=a.getClassName(),i=a.getConfig(),l=[];for(let c=0;c<a.inboundNodes.length;c++){let p=a.inboundNodes[c],d=Br.nodeKey(a,c),h={};if(this.containerNodes.has(d)){if(p.callArgs)try{JSON.stringify(p.callArgs),h=p.callArgs}catch(f){console.warn(`Layer ${a.name} was passed non-serializable keyword arguments: ${p.callArgs}. They will not be included in the serialized model (and thus will be missing at deserialization time).`),h={}}if(p.inboundLayers.length>0){let f=[];for(let m=0;m<p.inboundLayers.length;m++){let g=p.inboundLayers[m],y=p.nodeIndices[m],x=p.tensorIndices[m],A=Br.nodeKey(g,y),b=t[A];b==null&&(b=0),f.push([g.name,b,x,h])}l.push(f)}}}let u={};u.name=a.name,u.className=o,u.config=i,u.inboundNodes=l,n.push(u)}e.layers=n;let s=[];for(let a=0;a<this.inputLayers.length;a++){let o=this.inputLayers[a],i=this.inputLayersNodeIndices[a],l=Br.nodeKey(o,i);if(!this.containerNodes.has(l))continue;let u=t[l];u==null&&(u=0);let c=this.inputLayersTensorIndices[a];s.push([o.name,u,c])}e.inputLayers=s;let r=[];for(let a=0;a<this.outputLayers.length;a++){let o=this.outputLayers[a],i=this.outputLayersNodeIndices[a],l=Br.nodeKey(o,i);if(!this.containerNodes.has(l))continue;let u=t[l];u==null&&(u=0);let c=this.outputLayersTensorIndices[a];r.push([o.name,u,c])}return e.outputLayers=r,e}static fromConfig(e,t,n={},s=!1){let r={},a={};function o(m,g){m.name in a?a[m.name].push(g):a[m.name]=[g]}function i(m,g){let y=[],x;for(let A of g){let b=A[0],w=A[1],k=A[2];if(x=A[3]==null?{}:A[3],!(b in r)){o(m,g);return}let S=r[b];if(S.inboundNodes.length<=w){o(m,g);return}let E=S.inboundNodes[w];y.push(E.outputTensors[k])}y.length>0&&m.apply(ps(y),x)}function l(m){let g=m.name,y=Nr(m,t.customObjects!=null?t.customObjects:{});y.setFastWeightInitDuringBuild(s),r[g]=y,m.inboundNodes.forEach(A=>{if(!(A instanceof Array))throw new j(`Corrupted configuration, expected array for nodeData: ${A}`);o(y,A)})}let u=t.name,c=t.layers;for(let m of c)l(m);for(;!uV(a);)for(let m of c){let g=r[m.name];if(g.name in a){let y=a[g.name];delete a[g.name];for(let x of y)i(g,x)}}let p=[],d=[],h=t.inputLayers;for(let m of h){let g=m[0],y=m[1],x=m[2];Wr(g in r);let b=r[g].inboundNodes[y].outputTensors;p.push(b[x])}let f=t.outputLayers;for(let m of f){let g=m[0],y=m[1],x=m[2];Wr(g in r);let b=r[g].inboundNodes[y].outputTensors;d.push(b[x])}return new e({inputs:p,outputs:d,name:u})}get stateful(){if(this._stateful)throw new j("Container instance unexpectedly has _stateful = true. The statefulness of a Container is determined by the Layers it contains. Its _stateful property must remain the default false.");for(let e of this.layers)if(e.stateful)return!0;return!1}resetStates(){J(()=>{this.layers.forEach(e=>{e.stateful&&e.resetStates()})})}};function FU(e,t,n){let s=t.length;if(e==null||Array.isArray(e)&&e.length===0)return t.map(r=>null);if(s===1)return Array.isArray(e)&&e.length===1?e:typeof e=="object"&&t[0]in e?[e[t[0]]]:[e];if(Array.isArray(e)){if(e.length!==s)throw new Error(`Provided ${n} is an array of ${e.length} element(s), but the model has ${s} outputs. Make sure a set of weights is provided for each model output.`);return e}else if(typeof e=="object"&&Object.keys(e).length>0&&typeof e[Object.keys(e)[0]]=="object"){let r=[];return t.forEach(a=>{a in e?r.push(e[a]):r.push(null)}),r}else throw new Error(`The model has multiple (${s}) outputs, so ${n} must be either an array with ${s} elements or an object with ${t} keys. Provided ${n} not understood: ${JSON.stringify(e)}`)}function z8(e,t){return FU(e,t,"classWeight")}async function L8(e,t,n,s){if(t!=null||s!=null)throw new Error("Support sampleWeight is not implemented yet");if(n!=null){let r=J(()=>{if(e.shape.length===1)return Fn(e);if(e.shape.length===2){if(e.shape[1]>1)return Es(e,1);if(e.shape[1]===1)return U(e,[e.shape[0]]);throw new Error(`Encountered unexpected last-dimension size (${e.shape[1]}) during handling of class weights. The size is expected to be >= 1.`)}else throw new Error(`Unexpected rank of target (y) tensor (${e.rank}) during handling of class weights. The rank is expected to be 1 or 2.`)}),a=Array.from(await r.data());ne(r);let o=[];return a.forEach(i=>{if(n[i]==null)throw new Error(`classWeight must contain all classes in the training data. The class ${i} exists in the data but not in classWeight`);o.push(n[i])}),Ft(o,"float32")}else return null}function OU(e,t){return L(e,t)}var MU=32;function B8(e,t){let n,s,r=t;n=r.xs,s=r.ys,v.assert(n!=null&&s!=null,()=>`A Dataset iterator for fitDataset() is expected to generate objects of the form \`{xs: xVal, ys: yVal}\`, where the two values may be \`tf.Tensor\`, an array of Tensors, or a map of string to Tensor.  The provided Dataset instead generates ${t}`);let a=Uv("input",e.inputNames,n),o=Uv("output",e.outputNames,s),i=a[0].shape[0];v.assert(a.length===e.inputs.length,()=>`LayersModel has ${e.inputs.length} inputs, but the dataset provides ${a.length} inputs.  (Expected input keys: ${JSON.stringify(e.inputNames)})`),v.assert(o.length===e.outputs.length,()=>`LayersModel has ${e.outputs.length} outputs, but the dataset provides ${o.length} outputs.  (Expected output keys: ${JSON.stringify(e.outputNames)})`);for(let l=0;l<a.length;l++)v.assert(a[l].shape[0]===i,()=>`Batch size mismatch: input ${e.inputNames[l]} has ${a[l].shape[0]}; expected  ${i} based on input ${e.inputNames[0]}.`);for(let l=0;l<o.length;l++)v.assert(o[l].shape[0]===i,()=>`Batch size mismatch: output ${e.outputNames[l]} has ${o[l].shape[0]}; expected  ${i} based on input ${e.inputNames[0]}.`);return{xs:a,ys:o}}function Uv(e,t,n){if(n instanceof tt)return[n];if(Array.isArray(n))return v.assert(n.length===t.length,()=>`Received an array of ${n.length} Tensors, but expected ${t.length} to match the ${e} keys ${t}.`),n;{let s=[];for(let r of t){if(n[r]==null)throw new j(`The feature data generated by the dataset lacks the required ${e} key '${r}'.`);s.push(n[r])}return s}}function zU(e){if(e.length===3)throw new He("Validation with sample weights is not implemented yet.");return{xs:e[0],ys:e[1]}}async function LU(e,t,n){let s=n.batchesPerEpoch!=null;if(v.assert(e.optimizer!=null,()=>"You must compile a model before training/testing. Use LayersModel.compile(modelCompileConfig)."),v.assert(n!=null,()=>"For fitDataset(), the 2nd argument (config) is required, but it is not provided in this call."),v.assert(n.epochs!=null&&n.epochs>0&&Number.isInteger(n.epochs),()=>`For fitDataset(), config.epochs is expected to be a positive integer, but got ${n.epochs}`),v.assert(!s||n.batchesPerEpoch>0&&Number.isInteger(n.batchesPerEpoch),()=>`For fitDataset(), config.batchesPerEpoch is expected to be a positive integer if specified, but got ${n.batchesPerEpoch}`),v.assert(n.validationSplit==null,()=>"`validationSplit` is not supported by `fitDataset()`. Use validationData instead."),e.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");e.isTraining=!0;try{let r=n.validationData!=null,a,o;if(r)if(Gv(n.validationData))v.assert(n.validationBatches==null||n.validationBatches>0&&Number.isInteger(n.validationBatches),()=>`For fitDataset() with dataset-based validation, config.validationBatches is expected not to be provided, or to be a positive integer, but got ${n.validationBatches}`);else{let g=zU(n.validationData);a=g.xs,o=g.ys}let i=e.makeTrainFunction(),l=e.getDedupedMetricsNames(),u;r?u=l.slice().concat(l.map(g=>"val_"+g)):u=l.slice();let c=R8(n.callbacks,n.yieldEvery),p=n.verbose==null?1:n.verbose,{callbackList:d,history:h}=_8(c,p,n.epochs,null,null,BU(t,n),null,r,u);d.setModel(e),e.history=h,await d.onTrainBegin(),e.stopTraining_=!1;let f=n.initialEpoch==null?0:n.initialEpoch,m=await t.iterator();for(;f<n.epochs;){let g={};await d.onEpochBegin(f);let y=0,x=0;for(s||(m=await t.iterator());!s||y<n.batchesPerEpoch;){let A=await m.next();if(s&&A.done){console.warn(`You provided \`batchesPerEpoch\` as ${n.batchesPerEpoch}, but your dataset iterator ran out of data after ${y} batches; interrupting training. Make sure that your dataset can generate at least \`batchesPerEpoch * epochs\` batches (in this case, ${n.batchesPerEpoch*n.epochs} batches). You may need to use the repeat() function when building your dataset.`);break}if(A.value!=null){let{xs:b,ys:w}=B8(e,A.value),k={};k.batch=x,k.size=b[0].shape[0],await d.onBatchBegin(x,k);let S=[];if(n.classWeight!=null){let P=z8(n.classWeight,e.outputNames);for(let _=0;_<P.length;++_)S.push(await L8(w[_],null,P[_]))}let E=b.concat(w).concat(S),R=i(E);ne(E);for(let P=0;P<l.length;++P){let _=l[P],$=R[P];k[_]=$,bn($)}await d.onBatchEnd(x,k),C8(k),x++,y++}if(s?y>=n.batchesPerEpoch:A.done){if(r){let b;Gv(n.validationData)?b=_t(await e.evaluateDataset(n.validationData,{batches:n.validationBatches})):b=_t(e.evaluate(a,o,{batchSize:n.validationBatchSize==null?MU:n.validationBatchSize,verbose:0}));for(let w=0;w<e.metricsNames.length;++w)g[`val_${e.metricsNames[w]}`]=b[w]}break}if(e.stopTraining_)break}if(await d.onEpochEnd(f,g),f++,e.stopTraining_)break}return await d.onTrainEnd(),await e.history.syncData(),e.history}finally{e.isTraining=!1}}function BU(e,t){let n=null;return t.batchesPerEpoch!=null?n=t.batchesPerEpoch:Number.isFinite(e.size)&&(n=e.size),n}function Gv(e){return typeof e.iterator=="function"}function WU(e){return typeof e.next=="function"}async function VU(e,t,n){n=n||{};let s=n.batches!=null,r=e.testFunction,a=[];if(n.verbose>0)throw new He("Verbose mode is not implemented yet.");v.assert(!s||n.batches>0&&Number.isInteger(n.batches),()=>`Test loop expects \`batches\` to be a positive integer, but received ${JSON.stringify(n.batches)}`);let o=WU(t)?t:await t.iterator(),i=0,l=0;for(;!s||l<n.batches;){let u=await o.next();if(a=J(()=>{if(u.value){let{xs:c,ys:p}=B8(e,u.value),d=c.concat(p),h=J(()=>r(d));if(ne(d),l===0)for(let m=0;m<h.length;++m)a.push(Se(0));let f=d[0].shape[0];for(let m=0;m<h.length;++m){let g=h[m],y=a[m];a[m]=J(()=>ce(a[m],L(f,g))),l>0&&ne(y)}ne(h),i+=f,++l}return a}),u.done){s&&console.warn(`Your dataset iterator ran out of data during evaluateDataset(). Interrupting evalution. Make sure that your dataset can generate at least \`batches\` batches (in this case, ${n.batches} batches). You may need to use the repeat() function when building your dataset.`);break}}for(let u=0;u<a.length;++u){let c=a[u];a[u]=pe(a[u],i),ne(c)}return ps(a)}function z3(e){v.assert(e>0&&Number.isInteger(e),()=>`batchSize is required to be a positive integer, but got ${e}`)}function ap(e,t,n){return e==null?[null]:Array.isArray(e)?e.map(s=>Hi(s,t,n-t)):Hi(e,t,n-t)}function m5(e,t){return J(()=>e==null?null:Array.isArray(e)?e.map(n=>m5(n,t)):A8(e,t.dtype==="int32"?t:ge(t,"int32")))}function L3(e,t){let n=[],s=0,r=null;for(;s<e;)r=s+t,r>=e&&(r=e),n.push([s,r]),s=r;return n}async function UU(e,t,n,s,r,a,o,i,l,u,c,p,d,h,f){r==null&&(r=32),a==null&&(a=1),c==null&&(c=!0),d==null&&(d=0);let m=!1;if(l!=null&&u!=null&&(m=!0),f!=null&&(m=!0,h==null))throw new j("Can only use `validationSteps` when doing step-wise training, i.e., `stepsPerEpoch` must be set.");let g=e.checkNumSamples(n,r,h,"steps_per_epoch"),y;g!=null&&(y=Rr(0,g)),o==null&&(o=1);let{callbackList:x,history:A}=_8(i,o,a,d,g,h,r,m,p);x.setModel(e),e.history=A,await x.onTrainBegin(),e.stopTraining_=!1;for(let b=d;b<a;++b){await x.onEpochBegin(b);let w={};if(h!=null)throw new He("stepsPerEpoch mode is not implemented yet.");{if(c==="batch")throw new He("batch shuffling is not implemneted yet");c&&v.shuffle(y);let k=Ft(y),S=L3(g,r);for(let E=0;E<S.length;++E){let R={};if(await x.onBatchBegin(E,R),J(()=>{let P=S[E][0],_=S[E][1],$=Hi(k,P,_-P);R.batch=E,R.size=_-P;let T=m5(n,$),F=t(T);for(let G=0;G<s.length;++G){let q=s[G],z=F[G];R[q]=z,bn(z)}if(E===S.length-1&&m){let G=e.testLoop(l,u,r);for(let q=0;q<s.length;++q){let z=s[q],Z=G[q];bn(Z),w["val_"+z]=Z}}}),await x.onBatchEnd(E,R),C8(R),e.stopTraining_)break}k.dispose()}if(await x.onEpochEnd(b,w),e.stopTraining_)break}return await x.onTrainEnd(),await e.history.syncData(),e.history}async function GU(e,t,n,s={}){if(e.isTraining)throw new Error("Cannot start training because another fit() call is ongoing.");e.isTraining=!0;let r,a,o,i,l,u,c,p,d;try{let h=s.batchSize==null?32:s.batchSize;z3(h);let f=!1,m=await e.standardizeUserData(t,n,s.sampleWeight,s.classWeight,f,h);r=m[0],a=m[1],d=m[2];let g=!1,y;if(s.validationData!=null&&s.validationData.length>0){if(g=!0,s.validationData.length===2)l=s.validationData[0],u=s.validationData[1];else throw s.validationData.length===3?new He("validationData including sample weights is not supported yet."):new j(`When passing validation data, it must contain 2 (valX, valY) or 3 (valX, valY, valSampleWeight) items; ${s.validationData} is invalid.`);let R=!0,P=await e.standardizeUserData(l,u,null,null,R,h);c=P[0],p=P[1],y=c.concat(p)}else if(s.validationSplit!=null&&s.validationSplit>0&&s.validationSplit<1){g=!0;let R=Math.floor(r[0].shape[0]*(1-s.validationSplit)),P=r[0].shape[0];c=ap(r,R,P),o=r,r=ap(r,0,R),p=ap(a,R,P),i=a,a=ap(a,0,R),y=c.concat(p)}else s.validationSteps!=null&&(g=!0);let x=r.concat(a).concat(d);e.checkTrainableWeightsConsistency();let A=e.makeTrainFunction(),b=e.getDedupedMetricsNames(),w,k;g?(e.makeTestFunction(),w=e.testFunction,k=b.slice().concat(b.map(R=>"val_"+R))):(w=null,y=[],k=b.slice());let S=R8(s.callbacks,s.yieldEvery);return await UU(e,A,x,b,h,s.epochs,s.verbose,S,w,y,s.shuffle,k,s.initialEpoch,null,null)}finally{e.isTraining=!1,Ir(r,t),Ir(a,n),Ir(o,t),Ir(i,n),Ir(c,l),Ir(p,u),d!=null&&ne(d)}}function W8(e){let t=[];e instanceof tt&&(e=[e]);for(let n=0;n<e.length;++n){let s=e[n];if(s.rank===1)t.push(wh(s,1));else{if(s.rank===0)throw new Error("Expected tensor to be at least 1D, but received a 0D tensor (scalar).");t.push(s)}}return t}function Ir(e,t){if(e==null)return;let n=[];if(t instanceof tt)n.push(t.id);else if(Array.isArray(t))t.forEach(r=>n.push(r.id));else if(t!=null)for(let r in t){let a=t[r];n.push(a.id)}let s=[];if(e instanceof tt)n.indexOf(e.id)===-1&&s.push(e);else if(Array.isArray(e))e.forEach(r=>{n.indexOf(r.id)===-1&&s.push(r)});else if(e!=null)for(let r in e){let a=e[r];n.indexOf(a.id)===-1&&s.push(a)}s.forEach(r=>{r.isDisposed||r.dispose()})}function HU(e){return e instanceof tt}function B3(e){return Array.isArray(e)}function Hv(e){return!HU(e)&&!B3(e)}function jv(e,t,n,s=!0,r=""){if(t==null||t.length===0){if(e!=null){let o=!1;if(B3(e)&&e.length>0)o=!0;else if(Hv(e)){for(let i in e)if(e.hasOwnProperty(i)){o=!0;break}}else o=!0;if(o)throw new j(`Error when checking model ${r} expected no data, but got ${e}`)}return[]}if(e==null)return t.map(o=>null);let a;if(Hv(e)){e=e,a=[];for(let o of t){if(e[o]==null)throw new j(`No data provided for "${o}". Need data for each key in: ${t}`);a.push(e[o])}}else if(B3(e)){if(e=e,e.length!==t.length)throw new j(`Error when checking model ${r}: the Array of Tensors that you are passing to your model is not the size the model expected. Expected to see ${t.length} Tensor(s), but instead got the following list of Tensor(s): ${e}`);a=e}else{if(e=e,t.length>1)throw new j(`The model ${r} expects ${t.length} Tensor(s), but only received one Tensor. Found: Tensor with shape ${e.shape}`);a=[e]}if(a=W8(a),n!=null)for(let o=0;o<t.length;++o){if(n[o]==null)continue;let i=a[o];if(i.shape.length!==n[o].length)throw new j(`Error when checking ${r}: expected ${t[o]} to have ${n[o].length} dimension(s). but got array with shape ${i.shape}`);for(let l=0;l<n[o].length;++l){if(l===0&&!s)continue;let u=i.shape[l],c=n[o][l];if(c!=null&&c>=0&&u!==c)throw new j(`${r} expected a batch of elements where each example has shape [${n[o].slice(1,n[o].length)}] (i.e.,tensor shape [*,${n[o].slice(1,n[o].length)}]) but the ${r} received an input with ${i.shape[0]} examples, each with shape [${i.shape.slice(1,i.shape.length)}] (tensor shape [${i.shape}])`)}}return a}function jU(e,t,n){let s=qa(e.map(a=>a.shape[0]));s.sort();let r=qa(t.map(a=>a.shape[0]));if(r.sort(),s.length>1)throw new j(`All input Tensors (x) should have the same number of samples. Got array shapes: ${JSON.stringify(e.map(a=>a.shape))}`);if(r.length>1)throw new j(`All target Tensors (y) should have the same number of samples. Got array shapes: ${JSON.stringify(t.map(a=>a.shape))}`);if(s.length>0&&r.length>0&&!v.arraysEqual(s,r))throw new j(`Input Tensors should have the same number of samples as target Tensors. Found ${s[0]} input sample(s) and ${r[0]} target sample(s).`)}function qU(e,t,n){let s=[eu,u2,Tp];for(let r=0;r<e.length;++r){let a=e[r],o=t[r],i=n[r];if(o!=null){if(o===Tp&&a.shape[a.shape.length-1]===1)throw new j(`You are passing a target array of shape ${a.shape} while using a loss 'categorical_crossentropy'. 'categorical_crossentropy'expects targets to be binary matrices (1s and 0s) of shape [samples, classes].`);if(s.indexOf(o)!==-1){let l=a.shape.slice(1),u=i.slice(1);for(let c=0;c<l.length;++c){let p=l[c],d=u[c];if(d!=null&&p!==d)throw new j(`A target Tensor with shape ${a.shape} was passed for an output of shape ${i}, while using a loss function that expects targets to have the same shape as the output.`)}}}}}function qv(e,t,n,s=!0,r=""){let a;if(Array.isArray(e)){if(e.length!==t.length)throw new j(`Error when checking model ${r}: the Array of Tensors that you are passing to your model is not the size the the model expected. Expected to see ${t.length} Tensor(s), but instead got ${e.length} Tensors(s).`);a=e}else{if(t.length>1)throw new j(`The model expects ${t.length} ${r} Tensors, but only received one Tensor. Found: array with shape ${JSON.stringify(e.shape)}.`);a=[e]}if(n!=null)for(let o=0;o<t.length;++o){if(n[o]==null)continue;let i=a[o];if(i.shape.length!==n[o].length)throw new j(`Error when checking ${r}: expected ${t[o]} to have ${n[o].length} dimension(s), but got array with shape ${JSON.stringify(i.shape)}`);for(let l=0;l<n[o].length;++l){if(l===0&&!s)continue;let u=i.shape[l],c=n[o][l];if(c!=null&&c!==u)throw new j(`Error when checking ${r}: expected ${t[o]} to have shape ${JSON.stringify(n[o])} but got array with shape ${JSON.stringify(i.shape)}.`)}}}function XU(e,t){if(e==null||Array.isArray(e)&&e.length===0)return t.map(s=>[]);let n;if(typeof e=="string"||typeof e=="function")n=[e];else if(Array.isArray(e)||typeof e=="object")n=e;else throw new TypeError(`Type of metrics argument not understood. Expected an string,function, Array, or Object, found: ${e}`);if(Array.isArray(n))return t.map(s=>n);{let s=[];for(let r of t){let a=n.hasOwnProperty(r)?n[r]:[];Array.isArray(a)||(a=[a]),s.push(a)}return s}}var KU="layers-model",pa=class extends Br{constructor(e){super(e),this.isTraining=!1}summary(e,t,n=console.log){if(!this.built)throw new j("This model has never been called, thus its weights have not been created yet. So no summary can be displayed. Build the model first (e.g., by calling it on some test data).");RU(this,e,t,n)}compile(e){if(e.loss==null&&(e.loss=[]),this.loss=e.loss,typeof e.optimizer=="string")this.optimizer_=EU(e.optimizer),this.isOptimizerOwned=!0;else{if(!(e.optimizer instanceof wa))throw new j("User-defined optimizer must be an instance of tf.Optimizer.");this.optimizer_=e.optimizer,this.isOptimizerOwned=!1}let t=[];if(!Array.isArray(e.loss)&&typeof e.loss!="string"&&typeof e.loss!="function"){e.loss=e.loss;for(let a in e.loss)if(this.outputNames.indexOf(a)===-1)throw new j(`Unknown entry in loss dictionary: "${a}". Only expected the following keys: ${this.outputNames}`);for(let a of this.outputNames)e.loss[a]==null&&console.warn(`Output "${a}" is missing from loss dictionary. We assume this was done on purpose, and we will not be expecting data to be passed to ${a} during training`),t.push(u3(e.loss[a]))}else if(Array.isArray(e.loss)){if(e.loss.length!==this.outputs.length)throw new j(`When passing an Array as loss, it should have one entry per model output. The model has ${this.outputs.length} output(s), but you passed loss=${e.loss}.`);t=e.loss.map(o=>u3(o))}else{let a=u3(e.loss);this.outputs.forEach(o=>{t.push(a)})}this.lossFunctions=t,this.feedOutputNames=[],this.feedOutputShapes=[],this.feedLossFns=[];for(let a=0;a<this.outputs.length;++a){let o=this.internalOutputShapes[a],i=this.outputNames[a];this.feedOutputNames.push(i),this.feedOutputShapes.push(o),this.feedLossFns.push(this.lossFunctions[a])}let n=[];this.metrics=e.metrics,this.metricsNames=["loss"],this.metricsTensors=[],Gi("loss",()=>{for(let a=0;a<this.outputs.length;++a){if(n.indexOf(a)!==-1)continue;let o=this.lossFunctions[a];this.outputs.length>1&&(this.metricsTensors.push([o,a]),this.metricsNames.push(this.outputNames[a]+"_loss"))}});let s=XU(e.metrics,this.outputNames),r=(a,o,i)=>{this.outputNames.length>1&&(o=this.outputNames[a]+"_"+o),this.metricsNames.push(o),this.metricsTensors.push([i,a])};Gi("metric",()=>{for(let a=0;a<this.outputs.length;++a){if(n.indexOf(a)!==-1)continue;let o=s[a];(l=>{let u="",c,p,d;for(let h of l){if(typeof h=="string"&&["accuracy","acc","crossentropy","ce"].indexOf(h)!==-1){let m=this.internalOutputShapes[a];m[m.length-1]===1||this.lossFunctions[a]===u2?["accuracy","acc"].indexOf(h)!==-1?p=d5:["crossentropy","ce"].indexOf(h)!==-1&&(p=P8):this.lossFunctions[a]===km?["accuracy","acc"].indexOf(h)!==-1?p=F8:["crossentropy","ce"].indexOf(h)!==-1&&(p=O8):["accuracy","acc"].indexOf(h)!==-1?p=p5:["crossentropy","ce"].indexOf(h)!==-1&&(p=h5);let g;["accuracy","acc"].indexOf(h)!==-1?g="acc":["crossentropy","ce"].indexOf(h)!==-1&&(g="ce"),d=p,c=u+g}else d=NU(h),c=u+Uf(h);let f;Gi(c,()=>{f=d}),r(a,c,f)}})(o)}}),this.collectedTrainableWeights=this.trainableWeights}checkTrainableWeightsConsistency(){this.collectedTrainableWeights!=null&&this.trainableWeights.length!==this.collectedTrainableWeights.length&&console.warn("Discrepancy between trainableweights and collected trainable weights. Did you set `model.trainable` without calling `model.compile()` afterwards?")}evaluate(e,t,n={}){let s=n.batchSize==null?32:n.batchSize;z3(s);let r=!0,a=this.standardizeUserDataXY(e,t,r,s);try{let o=a[0].concat(a[1]);this.makeTestFunction();let i=this.testFunction,l=this.testLoop(i,o,s,n.verbose,n.steps);return ps(l)}finally{Ir(a[0],e),Ir(a[1],t)}}async evaluateDataset(e,t){return this.makeTestFunction(),VU(this,e,t)}checkNumSamples(e,t,n,s="steps"){let r;if(n!=null){if(r=null,t!=null)throw new j(`If ${s} is set, batchSize must be null or undefined.Got batchSize = ${t}`)}else if(e!=null)Array.isArray(e)?r=e[0].shape[0]:r=e.shape[0];else throw new j(`Either the input data should have a defined shape, or ${s} shoud be specified.`);return r}execute(e,t){if(Array.isArray(t)&&t.length===0)throw new j("`outputs` is an empty Array, which is not allowed.");let n=Array.isArray(t),s=n?t:[t],r=this.retrieveSymbolicTensors(s),a=new Wi;if(e instanceof tt&&(e=[e]),Array.isArray(e)){if(e.length!==this.inputs.length)throw new j(`The number of inputs provided (${e.length}) does not match the number of inputs of this model (${this.inputs.length}).`);for(let i=0;i<this.inputs.length;++i)a.add(this.inputs[i],e[i])}else for(let i of this.inputs){let l=e[i.name];if(l==null)throw new j(`No value is provided for the model's input ${i.name}`);a.add(i,l)}let o=rp(r,a);return n?o:o[0]}retrieveSymbolicTensors(e){let t=Qi(null,e.length),n=e.length;for(let s of this.layers){let r=Array.isArray(s.output)?s.output:[s.output],a=r.map(o=>o.name);for(let o=0;o<e.length;++o){let i=a.indexOf(e[o]);if(i!==-1&&(t[o]=r[i],n--),n===0)break}if(n===0)break}if(n>0){let s=[];throw t.forEach((r,a)=>{r==null&&s.push(e[a])}),new j(`Cannot find SymbolicTensors for output name(s): ${JSON.stringify(s)}`)}return t}predictLoop(e,t=32,n=!1){return J(()=>{let s=this.checkNumSamples(e);if(n)throw new He("Verbose predictLoop() is not implemented yet.");let r=L3(s,t),a=this.outputs.map(o=>[]);for(let o=0;o<r.length;++o)J(()=>{let l=r[o][0],u=r[o][1],c=ap(e,l,u),p=[];if(Array.isArray(c))for(let h=0;h<c.length;++h)p.push({key:this.inputs[h],value:c[h]});else p.push({key:this.inputs[0],value:c});let d=new Wi(p);return rp(this.outputs,d)}).forEach((l,u)=>a[u].push(l));return ps(a.map(o=>Ct(o,0)))})}predict(e,t={}){let n=W8(e);qv(n,this.inputNames,this.feedInputShapes,!1);try{let s=t.batchSize==null?32:t.batchSize;return z3(s),this.predictLoop(n,s)}finally{Ir(n,e)}}predictOnBatch(e){qv(e,this.inputNames,this.feedInputShapes,!0);let t=(Array.isArray(e)?e[0]:e).shape[0];return this.predictLoop(e,t)}standardizeUserDataXY(e,t,n=!0,s){if(this.optimizer_==null)throw new Sr("You must compile a model before training/testing. Use LayersModel.compile(modelCompileArgs).");let r=[];for(let a=0;a<this.feedOutputShapes.length;++a){let o=this.feedOutputShapes[a];this.feedLossFns[a]===km?r.push(o.slice(0,o.length-1).concat([1])):r.push(o)}if(e=jv(e,this.feedInputNames,this.feedInputShapes,!1,"input"),t=jv(t,this.feedOutputNames,r,!1,"target"),jU(e,t,null),qU(t,this.feedLossFns,this.feedOutputShapes),this.stateful&&s!=null&&s>0&&e[0].shape[0]%s!==0)throw new j(`In a stateful network, you should only pass inputs with a number of samples that is divisible by the batch size ${s}. Found: ${e[0].shape[0]} sample(s).`);return[e,t]}async standardizeUserData(e,t,n,s,r=!0,a){let[o,i]=this.standardizeUserDataXY(e,t,r,a);if(n!=null)throw new Error("sample weight is not supported yet.");let l=null;if(s!=null){let u=z8(s,this.outputNames);l=[];for(let c=0;c<u.length;++c)l.push(await L8(i[c],null,u[c]))}return[o,i,l]}testLoop(e,t,n,s=0,r){return J(()=>{let a=this.checkNumSamples(t,n,r,"steps"),o=[];if(s>0)throw new He("Verbose mode is not implemented yet.");if(r!=null)throw new He("steps mode in testLoop() is not implemented yet");{let i=L3(a,n),l=Ft(Rr(0,a));for(let u=0;u<i.length;++u){let c=i[u][0],p=i[u][1],d=Hi(l,c,p-c),h=m5(t,d),f=e(h);if(u===0)for(let m=0;m<f.length;++m)o.push(Se(0));for(let m=0;m<f.length;++m){let g=f[m];o[m]=ce(o[m],L(p-c,g))}}for(let u=0;u<o.length;++u)o[u]=pe(o[u],a)}return o})}getDedupedMetricsNames(){let e=this.metricsNames,t=[];for(let n=0;n<e.length;++n){let s=e[n],r=s;_v(e,s)>1&&(r+=`_${_v(e.slice(0,n),s)}`),t.push(r)}return t}makeTrainFunction(){return e=>{let t=[],n=e.slice(0,this.inputs.length),s=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),r=e.slice(this.inputs.length+this.outputs.length,this.inputs.length+this.outputs.length*2),a=[],o=()=>{let c=[];for(let f=0;f<this.inputs.length;++f)c.push({key:this.inputs[f],value:n[f]});let p=new Wi(c),d=rp(this.outputs,p,{training:!0}),h;for(let f=0;f<this.lossFunctions.length;++f){let m=this.lossFunctions[f],g=m(s[f],d[f]);r[f]!=null&&(g=OU(g,r[f]));let y=Bt(g);t.push(y),f===0?h=g:h=ce(h,g)}for(let f=0;f<this.metricsTensors.length;++f){let m;if(this.outputs.length>1&&f<this.outputs.length)m=t[f];else{let g=this.metricsTensors[f][0],y=this.metricsTensors[f][1];m=Bt(g(s[y],d[y]))}bn(m),a.push(m)}return h=Bt(h),this.calculateLosses().forEach(f=>{h=ce(h,f)}),h},i=this.collectedTrainableWeights.map(c=>c.read()),l=!0;return[this.optimizer_.minimize(o,l,i)].concat(a)}}makeTestFunction(){this.testFunction=e=>J(()=>{let t=[],n,s=e.slice(0,this.inputs.length),r=e.slice(this.inputs.length,this.inputs.length+this.outputs.length),a=[];for(let l=0;l<this.inputs.length;++l)a.push({key:this.inputs[l],value:s[l]});let o=new Wi(a),i=rp(this.outputs,o);for(let l=0;l<this.lossFunctions.length;++l){let u=this.lossFunctions[l],c=Bt(u(r[l],i[l]));l===0?n=c:n=ce(n,c),t.push(n)}for(let l=0;l<this.metricsTensors.length;++l){let u=this.metricsTensors[l][0],c=this.metricsTensors[l][1],p=Bt(u(r[c],i[c]));t.push(p)}return t})}async fit(e,t,n={}){return GU(this,e,t,n)}async fitDataset(e,t){return LU(this,e,t)}async trainOnBatch(e,t){let n=await this.standardizeUserData(e,t),s=n[0],r=n[1],o=this.makeTrainFunction()(s.concat(r)),i=[];for(let l of o){let u=await l.data();i.push(u[0])}return ne(o),Ir(n[0],e),Ir(n[1],t),ps(i)}getNamedWeights(e){let t=[],n=e!=null&&e.trainableOnly,s=n?this.trainableWeights:this.weights,r=this.getWeights(n);for(let a=0;a<s.length;++a)n&&!s[a].trainable||t.push({name:s[a].originalName,tensor:r[a]});return t}set stopTraining(e){this.stopTraining_=e}get stopTraining(){return this.stopTraining_}get optimizer(){return this.optimizer_}set optimizer(e){this.optimizer_!==e&&(this.optimizer_=e,this.isOptimizerOwned=!1)}dispose(){let e=super.dispose();if(e.refCountAfterDispose===0&&this.optimizer!=null&&this.isOptimizerOwned){let t=gm().numTensors;this.optimizer_.dispose(),e.numDisposedVariables+=t-gm().numTensors}return e}getLossIdentifiers(){let e;if(typeof this.loss=="string")e=la(this.loss);else if(Array.isArray(this.loss)){for(let t of this.loss)if(typeof t!="string")throw new Error("Serialization of non-string loss is not supported.");e=this.loss.map(t=>la(t))}else{let t=Object.keys(this.loss);e={};let n=this.loss;for(let s of t)if(typeof n[s]=="string")e[s]=la(n[s]);else throw new Error("Serialization of non-string loss is not supported.")}return e}getMetricIdentifiers(){if(typeof this.metrics=="string"||typeof this.metrics=="function")return[la(Uf(this.metrics))];if(Array.isArray(this.metrics))return this.metrics.map(e=>la(Uf(e)));{let e={};for(let t in this.metrics)e[t]=la(Uf(this.metrics[t]));return e}}getTrainingConfig(){return{loss:this.getLossIdentifiers(),metrics:this.getMetricIdentifiers(),optimizer_config:{class_name:this.optimizer.getClassName(),config:this.optimizer.getConfig()}}}loadTrainingConfig(e){if(e.weighted_metrics!=null)throw new Error("Loading weight_metrics is not supported yet.");if(e.loss_weights!=null)throw new Error("Loading loss_weights is not supported yet.");if(e.sample_weight_mode!=null)throw new Error("Loading sample_weight_mode is not supported yet.");let t=Np(e.optimizer_config),n=Nr(t),s;if(typeof e.loss=="string")s=zi(e.loss);else if(Array.isArray(e.loss))s=e.loss.map(a=>zi(a));else if(e.loss!=null){s={};for(let a in e.loss)s[a]=zi(e.loss[a])}let r;if(Array.isArray(e.metrics))r=e.metrics.map(a=>zi(a));else if(e.metrics!=null){r={};for(let a in e.metrics)r[a]=zi(e.metrics[a])}this.compile({loss:s,metrics:r,optimizer:n})}async save(e,t){if(typeof e=="string"){let l=Ts.getSaveHandlers(e);if(l.length===0)throw new j(`Cannot find any save handlers for URL '${e}'`);if(l.length>1)throw new j(`Found more than one (${l.length}) save handlers for URL '${e}'`);e=l[0]}if(e.save==null)throw new j("LayersModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");let n=await Ts.encodeWeights(this.getNamedWeights(t)),s=!1,r=null,o={modelTopology:this.toJSON(r,s),format:KU,generatedBy:`TensorFlow.js tfjs-layers v${f5}`,convertedBy:null};if((t==null?!1:t.includeOptimizer)&&this.optimizer!=null){o.trainingConfig=this.getTrainingConfig();let l="optimizer",{data:u,specs:c}=await Ts.encodeWeights(await this.optimizer.getWeights(),l);n.specs.push(...c),n.data=Ts.concatenateArrayBuffers([n.data,u])}return this.userDefinedMetadata!=null&&(Vv(this.userDefinedMetadata,this.name,!0),o.userDefinedMetadata=this.userDefinedMetadata),o.weightData=n.data,o.weightSpecs=n.specs,e.save(o)}setUserDefinedMetadata(e){Vv(e,this.name),this.userDefinedMetadata=e}getUserDefinedMetadata(){return this.userDefinedMetadata}};pa.className="Model";de.registerClass(pa);var V8=class extends pa{};V8.className="Functional";de.registerClass(V8);async function ZU(e,t){"modelTopology"in e||(e={modelTopology:e}),e=e;let n=e.modelTopology;n.model_config!=null&&(n=n.model_config);let s=Np(n),r=Nr(s,t);if(e.weightsManifest!=null){let a=await Ts.loadWeights(e.weightsManifest,e.pathPrefix,r.weights.map(i=>i.originalName)),o={};for(let i of r.weights)o[i.originalName]=a[i.originalName];r.loadWeights(o),ne(a)}return r}async function YU(e,t){if(t==null&&(t={}),typeof e=="string"){let n=Ts.getLoadHandlers(e,t);if(n.length===0)n.push(Ts.browserHTTPRequest(e,t));else if(n.length>1)throw new j(`Found more than one (${n.length}) load handlers for URL '${e}'`);e=n[0]}return JU(e,void 0,t)}async function JU(e,t,n){if(n==null&&(n={}),e.load==null)throw new j("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let s=await e.load(),r=s.modelTopology;r.model_config!=null&&(r=r.model_config);let a=n.strict==null?!0:n.strict,o=s.weightData!=null&&s.weightSpecs!=null&&a,i=Nr(Np(r),t,o),l=s.trainingConfig;if(l!=null&&i.loadTrainingConfig(l),s.userDefinedMetadata!=null&&i.setUserDefinedMetadata(s.userDefinedMetadata),s.weightData!=null){if(s.weightSpecs==null)throw new j("LayersModel artifacts contains weight data, but not weight specs. Therefore loading of weights cannot proceed.");let{modelWeights:u,optimizerWeights:c}=QU(s.weightData,s.weightSpecs);i.loadWeights(u,a),i.optimizer!=null&&c.length>0&&await i.optimizer.setWeights(c),ne(u),ne(c.map(p=>p.tensor))}return i}function QU(e,t){let n=Ts.decodeWeights(e,t),s={},r=[];return t.forEach(a=>{a.group==="optimizer"?r.push({name:a.name,tensor:n[a.name]}):s[a.name]=n[a.name]}),{modelWeights:s,optimizerWeights:r}}var nc=class extends pa{constructor(e){if(super({inputs:[],outputs:[]}),e=e||{},this.trainable=!0,this.built=!1,this.name=e.name!=null?e.name:Y0("sequential_"),e.layers!=null)for(let t of e.layers)this.add(t)}checkShape(e){if(e.inboundNodes[0].outputTensors[0].shape.some(n=>n<0))throw new j(`Negative dimension size caused by adding layer ${e.name} with input shape [${e.inboundNodes[0].inputTensors[0].shape}]`)}add(e){let t=e instanceof nc||e instanceof pa,n;if(t){if(n=e,n.outputs.length!==1)throw new j("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");if(n.inputs.length!==1)throw new j("All layers in a Sequential model should have a single input tensor. For multi-input layers, use the functional API.")}if(this.outputs.length===0){if(e.inboundNodes.length===0){if(e.batchInputShape==null)throw new j("The first layer in a Sequential model must get an `inputShape` or `batchInputShape` argument.");let s=w8({batchShape:e.batchInputShape,dtype:e.dtype,name:e.name+"_input"});e.apply(s)}if(t)this.outputs=n.outputs,this.inputs=n.inputs;else{if(e.inboundNodes.length!==1)throw new j(`A layer added to a Sequential model must not already be connected somewhere else. LayersModel received layer ${e.name} which has ${e.inboundNodes.length} pre-existing inbound connections.`);if(e.inboundNodes[0].outputTensors.length!==1)throw new j("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");this.checkShape(e),this.outputs=[e.inboundNodes[0].outputTensors[0]],this.inputs=v8(this.outputs[0])}this.inboundNodes=[],new i2({outboundLayer:this,inboundLayers:[],nodeIndices:[],tensorIndices:[],inputTensors:this.inputs,outputTensors:this.outputs,inputMasks:Qi(null,this.inputs.length),outputMasks:[null],inputShapes:this.inputs.map(s=>s.shape),outputShapes:this.outputs[0].shape})}else{let s=e.apply(this.outputs[0]);if(Array.isArray(s))throw new TypeError("All layers in a Sequential model should have a single output tensor. For multi-output layers, use the functional API.");this.checkShape(e),this.outputs=[s],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}this.layers.push(e),this.built=!1}pop(){if(this.layers.length===0)throw new TypeError("There are no layers in the model.");if(this.layers.pop(),this.layers.length===0)this.outputs=[],this.inboundNodes=[],this.outboundNodes=[];else{let e=this.layers.length-1;this.layers[e].outboundNodes=[],this.outputs=[this.layers[e].output],this.inboundNodes[0].outputTensors=this.outputs,this.inboundNodes[0].outputShapes=[this.outputs[0].shape]}}call(e,t){return this.model==null&&this.build(),this.model.call(e,t)}build(e){if(xt(e),this.inputs.length===0||this.outputs.length===0)throw new TypeError("Sequential model cannot be built: model is empty. Add some layers first.");this.model=new pa({inputs:this.inputs,outputs:this.outputs[0],name:this.name+"_model"}),this.model.trainable=this.trainable,this.supportsMasking=this.model.supportsMasking,this.inputLayers=this.model.inputLayers,this.inputLayersNodeIndices=this.model.inputLayersNodeIndices,this.inputLayersTensorIndices=this.model.inputLayersTensorIndices,this.outputLayers=this.model.outputLayers,this.outputLayersNodeIndices=this.model.outputLayersNodeIndices,this.outputLayersTensorIndices=this.model.outputLayersTensorIndices,this.nodesByDepth=this.model.nodesByDepth,this.containerNodes=this.model.containerNodes,this.outputNames=this.model.outputNames,this.inputNames=this.model.inputNames,this.built=!0}countParams(){return this.built||this.build(),super.countParams()}summary(e,t,n=console.log){this.built||this.build(),super.summary(e,t,n)}setWeights(e){this.model==null&&this.build(),this.model.setWeights(e)}evaluate(e,t,n={}){if(!this.built)throw new Sr("The model needs to be compiled before being used.");return this.model.evaluate(e,t,n)}async evaluateDataset(e,t){if(!this.built)throw new Sr("The model needs to be compiled before being used.");return this.model.evaluateDataset(e,t)}predict(e,t={}){return this.model==null&&this.build(),this.model.predict(e,t)}predictOnBatch(e){return this.model==null&&this.build(),this.model.predictOnBatch(e)}compile(e){this.build(),this.model.compile(e),this.optimizer_=this.model.optimizer,this.isOptimizerOwned=this.model.isOptimizerOwned,this.loss=this.model.loss,this.metrics=this.model.metrics,this.metricsTensors=this.model.metricsTensors,this.metricsNames=this.model.metricsNames}get optimizer(){return this.model==null?void 0:this.model.optimizer}set optimizer(e){this.model.optimizer=e}async fit(e,t,n={}){if(!this.built)throw new Sr("The model needs to be compiled before being used.");return this.model.fit(e,t,n)}async fitDataset(e,t){if(!this.built)throw new Sr("The model needs to be compiled before being used.");return this.model.fitDataset(e,t)}async trainOnBatch(e,t){return this.model.trainOnBatch(e,t)}static fromConfig(e,t,n={},s=!1){let r,a={};if(t instanceof Array){if(t[0].className==null||t[0].className==="Merge")throw new j("Legacy serialization format not supported yet.");r=t}else v.assert(t.layers!=null,()=>"When the config data for a Sequential model is not an Array, it must be an Object that contains the 'layers' field."),r=t.layers,delete t.layers,a=t;let o=new e(a);if(!(o instanceof nc))throw new He(`Sequential.fromConfig called on non-Sequential input: ${o}`);for(let i of r){let u=Nr(i,void 0,s);s&&u.setFastWeightInitDuringBuild(!0),o.add(u)}return o}set stopTraining(e){if(this.model==null)throw new j("Cannot set the stopTraining property of a sequential model before it is compiled.");this.model.stopTraining=e}get stopTraining(){if(this.model==null)throw new j("Cannot get the stopTraining property of a sequential model before it is compiled.");return this.model.stopTraining}getConfig(){let e=[];for(let t of this.layers){let n={};n.className=t.getClassName(),n.config=t.getConfig(),e.push(n)}return{name:this.name,layers:e}}};nc.className="Sequential";de.registerClass(nc);function eG(e){return new pa(e)}function tG(e){return new nc(e)}function nG(e,t){return t==null&&(t={}),YU(e,t)}function U8(e){return w8(e)}function sG(e,t){rr.registerCallbackConstructor(e,t)}var As=class extends de.Serializable{getConfig(){return{}}},G8=class extends As{apply(e,t=1){return IV(e,t)}};G8.className="elu";de.registerClass(G8);var H8=class extends As{apply(e){return _0(e)}};H8.className="selu";de.registerClass(H8);var j8=class extends As{apply(e){return $r(e)}};j8.className="relu";de.registerClass(j8);var q8=class extends As{apply(e){return J(()=>qc(6,$r(e)))}};q8.className="relu6";de.registerClass(q8);var X8=class extends As{apply(e){return e}};X8.className="linear";de.registerClass(X8);var K8=class extends As{apply(e){return Cn(e)}};K8.className="sigmoid";de.registerClass(K8);var Z8=class extends As{apply(e){return CV(e)}};Z8.className="hardSigmoid";de.registerClass(Z8);var Y8=class extends As{apply(e){return Kl(e)}};Y8.className="softplus";de.registerClass(Y8);var J8=class extends As{apply(e){return SV(e)}};J8.className="softsign";de.registerClass(J8);var Q8=class extends As{apply(e){return Zi(e)}};Q8.className="tanh";de.registerClass(Q8);var g5=class extends As{apply(e,t=-1){return Yl(e,t)}};g5.className="softmax";de.registerClass(g5);var ek=class extends As{apply(e,t=-1){return k0(e,t)}};ek.className="logSoftmax";de.registerClass(ek);var tk=class extends As{apply(e,t=1){return J(()=>L(Cn(L(e,t)),e))}};tk.className="swish";de.registerClass(tk);var nk=class extends As{apply(e){return J(()=>L(e,Zi(Kl(e))))}};nk.className="mish";de.registerClass(nk);function so(e){return e.getClassName()}function c3(e,t={}){return vh(e,de.SerializationMap.getMap().classNameMap,t,"activation")}function ro(e){if(e==null){let t={};return t.className="linear",t.config={},c3(t)}if(typeof e=="string"){let t={};return t.className=e,t.config={},c3(t)}else return e instanceof As?e:c3(e)}function y5(e){if(e!=null&&typeof e!="object")throw new Error(`Argument to L1L2 regularizer's constructor is expected to be an object, but received: ${e}`)}var sk=class extends de.Serializable{},Ch=class extends sk{constructor(e){super(),y5(e),this.l1=e==null||e.l1==null?.01:e.l1,this.l2=e==null||e.l2==null?.01:e.l2,this.hasL1=this.l1!==0,this.hasL2=this.l2!==0}apply(e){return J(()=>{let t=Wt([1]);return this.hasL1&&(t=ce(t,ke(L(this.l1,tn(e))))),this.hasL2&&(t=ce(t,ke(L(this.l2,kh(e))))),U(t,[])})}getConfig(){return{l1:this.l1,l2:this.l2}}static fromConfig(e,t){return new e({l1:t.l1,l2:t.l2})}};Ch.className="L1L2";de.registerClass(Ch);function rG(e){return y5(e),new Ch({l1:e!=null?e.l1:null,l2:0})}function aG(e){return y5(e),new Ch({l2:e!=null?e.l2:null,l1:0})}var Xv={l1l2:"L1L2"};function St(e){return XA(e)}function Kv(e,t={}){return vh(e,de.SerializationMap.getMap().classNameMap,t,"regularizer")}function Mt(e){if(e==null)return null;if(typeof e=="string"){let n={className:e in Xv?Xv[e]:e,config:{}};return Kv(n)}else return e instanceof sk?e:Kv(e)}var A5=class extends ut{constructor(e){super(e==null?{}:e),this.supportsMasking=!0,e!=null&&(this.maxValue=e.maxValue)}call(e,t){e=Xe(e);let n=$r(e);return this.maxValue!=null&&(n=fs(n,0,this.maxValue)),n}computeOutputShape(e){return e}getConfig(){let e={maxValue:this.maxValue},t=super.getConfig();return Object.assign(e,t),e}};A5.className="ReLU";de.registerClass(A5);var x5=class extends ut{constructor(e){super(e==null?{}:e),this.DEFAULT_ALPHA=.3,e==null&&(e={}),this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Xe(e);return ch(n,this.alpha)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};x5.className="LeakyReLU";de.registerClass(x5);var b5=class extends ut{constructor(e){if(super(e==null?{}:e),this.DEFAULT_ALPHA_INITIALIZER="zeros",e==null&&(e={}),this.supportsMasking=!0,this.alphaInitializer=Ot(e.alphaInitializer||this.DEFAULT_ALPHA_INITIALIZER),this.alphaRegularizer=Mt(e.alphaRegularizer),this.alphaConstraint=yn(e.alphaConstraint),e.sharedAxes==null)this.sharedAxes=null;else if(Array.isArray(e.sharedAxes))this.sharedAxes=e.sharedAxes;else if(typeof e.sharedAxes=="number")this.sharedAxes=[e.sharedAxes];else throw new j(`Expected sharedAxes to be a number or an array of numbers, but got ${e.sharedAxes}`)}build(e){e=xt(e);let t=e.slice(1);if(this.sharedAxes!=null)for(let s of this.sharedAxes)t[s-1]=1;this.alpha=this.addWeight("alpha",t,"float32",this.alphaInitializer,this.alphaRegularizer,!0,this.alphaConstraint);let n={};if(this.sharedAxes!=null)for(let s=1;s<e.length;++s)n[s]=e[s];this.inputSpec=[new rn({ndim:e.length,axes:n})],this.built=!0}call(e,t){return e=Xe(e),gh(e,this.alpha.read())}getConfig(){let e={alphaInitializer:Vt(this.alphaInitializer),alphaRegularizer:St(this.alphaRegularizer),alphaConstraint:gn(this.alphaConstraint),sharedAxes:this.sharedAxes},t=super.getConfig();return Object.assign(e,t),e}};b5.className="PReLU";de.registerClass(b5);var v5=class extends ut{constructor(e){if(super(e==null?{}:e),this.DEFAULT_ALPHA=1,e==null&&(e={}),e.alpha!=null&&e.alpha!==this.DEFAULT_ALPHA)throw new He(`Non-default alpha value (${e.alpha}) is not supported by the ELU layer yet.`);this.alpha=e.alpha==null?this.DEFAULT_ALPHA:e.alpha}call(e,t){let n=Xe(e);return Vc(n)}computeOutputShape(e){return e}getConfig(){let e={alpha:this.alpha},t=super.getConfig();return Object.assign(e,t),e}};v5.className="ELU";de.registerClass(v5);var w5=class extends ut{constructor(e){super(e==null?{}:e),this.DEFAULT_THETA=1,e==null&&(e={}),this.theta=e.theta==null?this.DEFAULT_THETA:e.theta}call(e,t){let n=Xe(e);return L(n,ge(ys(n,this.theta),"float32"))}computeOutputShape(e){return e}getConfig(){let e={theta:this.theta},t=super.getConfig();return Object.assign(e,t),e}};w5.className="ThresholdedReLU";de.registerClass(w5);var k5=class extends ut{constructor(e){super(e==null?{}:e),this.DEFAULT_AXIS=1,e==null&&(e={}),this.softmax=new g5().apply,this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis}call(e,t){let n=Xe(e);return this.softmax(n,this.axis)}computeOutputShape(e){return e}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};k5.className="Softmax";de.registerClass(k5);function Gu(e,t,n){if(typeof e=="number")return Qi(e,t);if(e.length!==t)throw new j(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${e.length} elements.`);for(let s=0;s<t;++s){let r=e[s];if(!bV(r))throw new j(`The ${n} argument must be an integer or tuple of ${t} integers. Received: ${JSON.stringify(e)} including a non-integer number ${r}`)}return e}function Er(e,t,n,s,r=1){if(e==null)return e;let a=t+(t-1)*(r-1),o;return n==="same"?o=e:o=e-a+1,Math.floor((o+s-1)/s)}function Vr(e,t,n,s){if(e==null)return null;if(s==="valid")e=e*t+no([n-t,0]);else if(s==="same")e=e*t;else throw new j(`Unsupport padding mode: ${s}.`);return e}function I5(e,t){return J(()=>(Yt(t),t==="channelsFirst"?st(e,[0,2,3,1]):e))}function rk(e,t){return J(()=>(Yt(t),t==="channelsFirst"?st(e,[0,2,3,4,1]):e))}function oG(e,t,n,s=1,r="valid",a,o=1){return J(()=>{if(a==null&&(a=_r()),Yt(a),e.shape.length!==3)throw new j(`The input of a conv1dWithBias operation should be 3, but is ${e.shape.length} instead.`);if(t.shape.length!==3)throw new j(`The kernel for a conv1dWithBias operation should be 3, but is ${t.shape.length} instead`);if(n!=null&&n.shape.length!==1)throw new j(`The bias for a conv1dWithBias operation should be 1, but is ${t.shape.length} instead`);if(a==="channelsFirst"&&(e=st(e,[0,2,1])),r==="causal")throw new He("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");let i=g0(e,t,s,r==="same"?"same":"valid","NWC",o);return n!=null&&(i=Pr(i,n)),i})}function Zv(e,t,n,s=[1,1],r="valid",a,o,i=null){return J(()=>{if(a==null&&(a=_r()),Yt(a),e.rank!==3&&e.rank!==4)throw new j(`conv2dWithBiasActivation expects input to be of rank 3 or 4, but received ${e.rank}.`);if(t.rank!==3&&t.rank!==4)throw new j(`conv2dWithBiasActivation expects kernel to be of rank 3 or 4, but received ${e.rank}.`);let l=I5(e,a);if(r==="causal")throw new He("The support for CAUSAL padding mode in conv1dWithBias is not implemented yet.");return l=Qu.conv2d({x:l,filter:t,strides:s,pad:r==="same"?"same":"valid",dilations:o,dataFormat:"NHWC",bias:n,activation:i}),a==="channelsFirst"&&(l=st(l,[0,3,1,2])),l})}function iG(e,t,n,s=[1,1,1],r="valid",a,o){return J(()=>{if(a==null&&(a=_r()),Yt(a),e.rank!==4&&e.rank!==5)throw new j(`conv3dWithBias expects input to be of rank 4 or 5, but received ${e.rank}.`);if(t.rank!==4&&t.rank!==5)throw new j(`conv3dWithBias expects kernel to be of rank 4 or 5, but received ${e.rank}.`);let i=rk(e,a);if(r==="causal")throw new He("The support for CAUSAL padding mode in conv3dWithBias is not implemented yet.");return i=cA(i,t,s,r==="same"?"same":"valid","NDHWC",o),n!=null&&(i=Pr(i,n)),a==="channelsFirst"&&(i=st(i,[0,4,1,2,3])),i})}var S5=class extends ut{constructor(e,t){if(super(t),this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",S5.verifyArgs(t),this.rank=e,vn(this.rank,"rank"),this.rank!==1&&this.rank!==2&&this.rank!==3)throw new He(`Convolution layer for rank other than 1, 2, or 3 (${this.rank}) is not implemented yet.`);if(this.kernelSize=Gu(t.kernelSize,e,"kernelSize"),this.strides=Gu(t.strides==null?1:t.strides,e,"strides"),this.padding=t.padding==null?"valid":t.padding,Qs(this.padding),this.dataFormat=t.dataFormat==null?"channelsLast":t.dataFormat,Yt(this.dataFormat),this.activation=ro(t.activation),this.useBias=t.useBias==null?!0:t.useBias,this.biasInitializer=Ot(t.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.biasConstraint=yn(t.biasConstraint),this.biasRegularizer=Mt(t.biasRegularizer),this.activityRegularizer=Mt(t.activityRegularizer),this.dilationRate=Gu(t.dilationRate==null?1:t.dilationRate,e,"dilationRate"),this.rank===1&&Array.isArray(this.dilationRate)&&this.dilationRate.length!==1)throw new j(`dilationRate must be a number or an array of a single number for 1D convolution, but received ${JSON.stringify(this.dilationRate)}`);if(this.rank===2){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==2)throw new j(`dilationRate must be a number or array of two numbers for 2D convolution, but received ${JSON.stringify(this.dilationRate)}`)}else if(this.rank===3){if(typeof this.dilationRate=="number")this.dilationRate=[this.dilationRate,this.dilationRate,this.dilationRate];else if(this.dilationRate.length!==3)throw new j(`dilationRate must be a number or array of three numbers for 3D convolution, but received ${JSON.stringify(this.dilationRate)}`)}}static verifyArgs(e){if(Wr("kernelSize"in e,"required key 'kernelSize' not in config"),typeof e.kernelSize!="number"&&!KA(e.kernelSize,"number",1,3))throw new j(`BaseConv expects config.kernelSize to be number or number[] with length 1, 2, or 3, but received ${JSON.stringify(e.kernelSize)}.`)}getConfig(){let e={kernelSize:this.kernelSize,strides:this.strides,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,activation:so(this.activation),useBias:this.useBias,biasInitializer:Vt(this.biasInitializer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),biasConstraint:gn(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}},Th=class extends S5{constructor(e,t){super(e,t),this.kernel=null,Th.verifyArgs(t),this.filters=t.filters,vn(this.filters,"filters"),this.kernelInitializer=Ot(t.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.kernelConstraint=yn(t.kernelConstraint),this.kernelRegularizer=Mt(t.kernelRegularizer)}build(e){e=xt(e);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new j(`The channel dimension of the input should be defined. Found ${e[t]}`);let n=e[t],s=this.kernelSize.concat([n,this.filters]);this.kernel=this.addWeight("kernel",s,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[{ndim:this.rank+2,axes:{[t]:n}}],this.built=!0}call(e,t){return J(()=>{e=Xe(e);let n,s=this.bias==null?null:this.bias.read(),r=p8(this.activation.getClassName());if(r!=null&&this.rank===2)n=Zv(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate,r);else{if(this.rank===1)n=oG(e,this.kernel.read(),s,this.strides[0],this.padding,this.dataFormat,this.dilationRate[0]);else if(this.rank===2)n=Zv(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate);else if(this.rank===3)n=iG(e,this.kernel.read(),s,this.strides,this.padding,this.dataFormat,this.dilationRate);else throw new He("convolutions greater than 3D are not implemented yet.");this.activation!=null&&(n=this.activation.apply(n))}return n})}computeOutputShape(e){e=xt(e);let t=[],n=this.dataFormat==="channelsLast"?e.slice(1,e.length-1):e.slice(2);for(let r=0;r<n.length;++r){let a=Er(n[r],this.kernelSize[r],this.padding,this.strides[r],typeof this.dilationRate=="number"?this.dilationRate:this.dilationRate[r]);t.push(a)}let s=[e[0]];return this.dataFormat==="channelsLast"?(s=s.concat(t),s.push(this.filters)):(s.push(this.filters),s=s.concat(t)),s}getConfig(){let e={filters:this.filters,kernelInitializer:Vt(this.kernelInitializer),kernelRegularizer:St(this.kernelRegularizer),kernelConstraint:gn(this.kernelConstraint)},t=super.getConfig();return Object.assign(e,t),e}static verifyArgs(e){if(!("filters"in e)||typeof e.filters!="number"||e.filters<1)throw new j(`Convolution layer expected config.filters to be a 'number' > 0 but got ${JSON.stringify(e.filters)}`)}},Nh=class extends Th{constructor(e){super(2,e),Nh.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!KA(e.kernelSize,"number",1,2))throw new j(`Conv2D expects config.kernelSize to be number or number[] with length 1 or 2, but received ${JSON.stringify(e.kernelSize)}.`)}};Nh.className="Conv2D";de.registerClass(Nh);var Eh=class extends Th{constructor(e){super(3,e),Eh.verifyArgs(e)}getConfig(){let e=super.getConfig();return delete e.rank,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!(Array.isArray(e.kernelSize)&&(e.kernelSize.length===1||e.kernelSize.length===3)))throw new j(`Conv3D expects config.kernelSize to be number or [number, number, number], but received ${JSON.stringify(e.kernelSize)}.`)}};Eh.className="Conv3D";de.registerClass(Eh);var C5=class extends Nh{constructor(e){if(super(e),this.inputSpec=[new rn({ndim:4})],this.padding!=="same"&&this.padding!=="valid")throw new j(`Conv2DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=xt(e),e.length!==4)throw new j("Input should have rank 4; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new j("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],s=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",s,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new rn({ndim:4,axes:{[t]:n}})],this.built=!0}call(e,t){return J(()=>{let n=Xe(e);if(n.shape.length!==4)throw new j(`Conv2DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let s=n.shape,r=s[0],a,o;this.dataFormat==="channelsFirst"?(a=2,o=3):(a=1,o=2);let i=s[a],l=s[o],u=this.kernelSize[0],c=this.kernelSize[1],p=this.strides[0],d=this.strides[1],h=Vr(i,p,u,this.padding),f=Vr(l,d,c,this.padding),m=[r,h,f,this.filters];this.dataFormat!=="channelsLast"&&(n=st(n,[0,2,3,1]));let g=y0(n,this.kernel.read(),m,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(g=st(g,[0,3,1,2])),this.bias!=null&&(g=Pr(g,this.bias.read(),this.dataFormat)),this.activation!=null&&(g=this.activation.apply(g)),g})}computeOutputShape(e){e=xt(e);let t=e.slice(),n,s,r;this.dataFormat==="channelsFirst"?(n=1,s=2,r=3):(n=3,s=1,r=2);let a=this.kernelSize[0],o=this.kernelSize[1],i=this.strides[0],l=this.strides[1];return t[n]=this.filters,t[s]=Vr(t[s],i,a,this.padding),t[r]=Vr(t[r],l,o,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};C5.className="Conv2DTranspose";de.registerClass(C5);var T5=class extends Eh{constructor(e){if(super(e),this.inputSpec=[new rn({ndim:5})],this.padding!=="same"&&this.padding!=="valid")throw new j(`Conv3DTranspose currently supports only padding modes 'same' and 'valid', but received padding mode ${this.padding}`)}build(e){if(e=xt(e),e.length!==5)throw new j("Input should have rank 5; Received input shape: "+JSON.stringify(e));let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null)throw new j("The channel dimension of the inputs should be defined. Found `None`.");let n=e[t],s=this.kernelSize.concat([this.filters,n]);this.kernel=this.addWeight("kernel",s,"float32",this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint)),this.inputSpec=[new rn({ndim:5,axes:{[t]:n}})],this.built=!0}call(e,t){return J(()=>{let n=Xe(e);if(n.shape.length!==5)throw new j(`Conv3DTranspose.call() expects input tensor to be rank-4, but received a tensor of rank-${n.shape.length}`);let s=n.shape,r=s[0],a,o,i;this.dataFormat==="channelsFirst"?(i=2,a=3,o=4):(i=1,a=2,o=3);let l=s[i],u=s[a],c=s[o],p=this.kernelSize[0],d=this.kernelSize[1],h=this.kernelSize[2],f=this.strides[0],m=this.strides[1],g=this.strides[2],y=Vr(l,f,p,this.padding),x=Vr(u,m,d,this.padding),A=Vr(c,g,h,this.padding),b=[r,y,x,A,this.filters];this.dataFormat!=="channelsLast"&&(n=st(n,[0,2,3,4,1]));let w=dA(n,this.kernel.read(),b,this.strides,this.padding);return this.dataFormat!=="channelsLast"&&(w=st(w,[0,4,1,2,3])),this.bias!==null&&(w=Pr(w,this.bias.read(),this.dataFormat)),this.activation!==null&&(w=this.activation.apply(w)),w})}computeOutputShape(e){e=xt(e);let t=e.slice(),n,s,r,a;this.dataFormat==="channelsFirst"?(n=1,s=2,r=3,a=4):(n=4,s=1,r=2,a=3);let o=this.kernelSize[0],i=this.kernelSize[1],l=this.kernelSize[2],u=this.strides[0],c=this.strides[1],p=this.strides[2];return t[n]=this.filters,t[s]=Vr(t[s],u,o,this.padding),t[r]=Vr(t[r],c,i,this.padding),t[a]=Vr(t[a],p,l,this.padding),t}getConfig(){let e=super.getConfig();return delete e.dilationRate,e}};T5.className="Conv3DTranspose";de.registerClass(T5);var ak=class extends Th{constructor(e,t){if(super(e,t),this.DEFAULT_DEPTHWISE_INITIALIZER="glorotUniform",this.DEFAULT_POINTWISE_INITIALIZER="glorotUniform",this.depthwiseKernel=null,this.pointwiseKernel=null,t.filters==null)throw new j("The `filters` configuration field is required by SeparableConv, but is unspecified.");if(t.kernelInitializer!=null||t.kernelRegularizer!=null||t.kernelConstraint!=null)throw new j("Fields kernelInitializer, kernelRegularizer and kernelConstraint are invalid for SeparableConv2D. Use depthwiseInitializer, depthwiseRegularizer, depthwiseConstraint, pointwiseInitializer, pointwiseRegularizer and pointwiseConstraint instead.");if(t.padding!=null&&t.padding!=="same"&&t.padding!=="valid")throw new j(`SeparableConv${this.rank}D supports only padding modes: 'same' and 'valid', but received ${JSON.stringify(t.padding)}`);this.depthMultiplier=t.depthMultiplier==null?1:t.depthMultiplier,this.depthwiseInitializer=Ot(t.depthwiseInitializer||this.DEFAULT_DEPTHWISE_INITIALIZER),this.depthwiseRegularizer=Mt(t.depthwiseRegularizer),this.depthwiseConstraint=yn(t.depthwiseConstraint),this.pointwiseInitializer=Ot(t.depthwiseInitializer||this.DEFAULT_POINTWISE_INITIALIZER),this.pointwiseRegularizer=Mt(t.pointwiseRegularizer),this.pointwiseConstraint=yn(t.pointwiseConstraint)}build(e){if(e=xt(e),e.length<this.rank+2)throw new j(`Inputs to SeparableConv${this.rank}D should have rank ${this.rank+2}, but received input shape: ${JSON.stringify(e)}`);let t=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[t]==null||e[t]<0)throw new j(`The channel dimension of the inputs should be defined, but found ${JSON.stringify(e[t])}`);let n=e[t],s=this.kernelSize.concat([n,this.depthMultiplier]),r=[];for(let o=0;o<this.rank;++o)r.push(1);r.push(n*this.depthMultiplier,this.filters);let a=!0;this.depthwiseKernel=this.addWeight("depthwise_kernel",s,"float32",this.depthwiseInitializer,this.depthwiseRegularizer,a,this.depthwiseConstraint),this.pointwiseKernel=this.addWeight("pointwise_kernel",r,"float32",this.pointwiseInitializer,this.pointwiseRegularizer,a,this.pointwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[this.filters],"float32",this.biasInitializer,this.biasRegularizer,a,this.biasConstraint):this.bias=null,this.inputSpec=[new rn({ndim:this.rank+2,axes:{[t]:n}})],this.built=!0}call(e,t){return J(()=>{e=Xe(e);let n;if(this.rank===1)throw new He("1D separable convolution is not implemented yet.");return this.rank===2&&(this.dataFormat==="channelsFirst"&&(e=st(e,[0,2,3,1])),n=D0(e,this.depthwiseKernel.read(),this.pointwiseKernel.read(),this.strides,this.padding,this.dilationRate,"NHWC")),this.useBias&&(n=Pr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),this.dataFormat==="channelsFirst"&&(n=st(n,[0,3,1,2])),n})}getConfig(){let e=super.getConfig();return delete e.rank,delete e.kernelInitializer,delete e.kernelRegularizer,delete e.kernelConstraint,e.depthwiseInitializer=Vt(this.depthwiseInitializer),e.pointwiseInitializer=Vt(this.pointwiseInitializer),e.depthwiseRegularizer=St(this.depthwiseRegularizer),e.pointwiseRegularizer=St(this.pointwiseRegularizer),e.depthwiseConstraint=gn(this.depthwiseConstraint),e.pointwiseConstraint=gn(this.pointwiseConstraint),e}};ak.className="SeparableConv";var N5=class extends ak{constructor(e){super(2,e)}};N5.className="SeparableConv2D";de.registerClass(N5);var c2=class extends Th{constructor(e){super(1,e),c2.verifyArgs(e),this.inputSpec=[{ndim:3}]}getConfig(){let e=super.getConfig();return delete e.rank,delete e.dataFormat,e}static verifyArgs(e){if(typeof e.kernelSize!="number"&&!KA(e.kernelSize,"number",1,1))throw new j(`Conv1D expects config.kernelSize to be number or number[] with length 1, but received ${JSON.stringify(e.kernelSize)}.`)}};c2.className="Conv1D";de.registerClass(c2);var E5=class extends ut{constructor(e){super(e),typeof e.cropping=="number"?this.cropping=[[e.cropping,e.cropping],[e.cropping,e.cropping]]:typeof e.cropping[0]=="number"?this.cropping=[[e.cropping[0],e.cropping[0]],[e.cropping[1],e.cropping[1]]]:this.cropping=e.cropping,this.dataFormat=e.dataFormat===void 0?"channelsLast":e.dataFormat,this.inputSpec=[{ndim:4}]}computeOutputShape(e){return this.dataFormat==="channelsFirst"?[e[0],e[1],e[2]-this.cropping[0][0]-this.cropping[0][1],e[3]-this.cropping[1][0]-this.cropping[1][1]]:[e[0],e[1]-this.cropping[0][0]-this.cropping[0][1],e[2]-this.cropping[1][0]-this.cropping[1][1],e[3]]}call(e,t){return J(()=>{if(e=Xe(e),this.dataFormat==="channelsLast"){let n=Vf(e,this.cropping[0][0],e.shape[1]-this.cropping[0][0]-this.cropping[0][1],2);return Vf(n,this.cropping[1][0],e.shape[2]-this.cropping[1][1]-this.cropping[1][0],3)}else{let n=Vf(e,this.cropping[0][0],e.shape[2]-this.cropping[0][0]-this.cropping[0][1],3);return Vf(n,this.cropping[1][0],e.shape[3]-this.cropping[1][1]-this.cropping[1][0],4)}})}getConfig(){let e={cropping:this.cropping,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};E5.className="Cropping2D";de.registerClass(E5);var R5=class extends ut{constructor(e){super(e),this.DEFAULT_SIZE=[2,2],this.inputSpec=[{ndim:4}],this.size=e.size==null?this.DEFAULT_SIZE:e.size,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Yt(this.dataFormat),this.interpolation=e.interpolation==null?"nearest":e.interpolation,yV(this.interpolation)}computeOutputShape(e){if(this.dataFormat==="channelsFirst"){let t=e[2]==null?null:this.size[0]*e[2],n=e[3]==null?null:this.size[1]*e[3];return[e[0],e[1],t,n]}else{let t=e[1]==null?null:this.size[0]*e[1],n=e[2]==null?null:this.size[1]*e[2];return[e[0],t,n,e[3]]}}call(e,t){return J(()=>{let n=Xe(e),s=n.shape;if(this.dataFormat==="channelsFirst"){n=st(n,[0,2,3,1]);let r=this.size[0]*s[2],a=this.size[1]*s[3],o=this.interpolation==="nearest"?Ne.resizeNearestNeighbor(n,[r,a]):Ne.resizeBilinear(n,[r,a]);return st(o,[0,3,1,2])}else{let r=this.size[0]*s[1],a=this.size[1]*s[2];return this.interpolation==="nearest"?Ne.resizeNearestNeighbor(n,[r,a]):Ne.resizeBilinear(n,[r,a])}})}getConfig(){let e={size:this.size,dataFormat:this.dataFormat,interpolation:this.interpolation},t=super.getConfig();return Object.assign(e,t),e}};R5.className="UpSampling2D";de.registerClass(R5);function lG(e,t,n=[1,1],s="valid",r,a){return J(()=>{r==null&&(r=_r()),Yt(r);let o=I5(e,r);if(e.rank!==4)throw new j(`Input for depthwiseConv2d is required to be 4-D, but is instead ${e.rank}-D`);if(t.rank!==4)throw new j(`depthwiseKernel is required to be 4-D, but is instead ${t.rank}-D`);return o=Wc(o,t,n,s==="same"?"same":"valid","NHWC",a),r==="channelsFirst"&&(o=st(o,[0,3,1,2])),o})}var _5=class extends S5{constructor(e){super(2,e),this.depthwiseKernel=null,this.depthMultiplier=e.depthMultiplier==null?1:e.depthMultiplier,this.depthwiseInitializer=Ot(e.depthwiseInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.depthwiseConstraint=yn(e.depthwiseConstraint),this.depthwiseRegularizer=Mt(e.depthwiseRegularizer)}build(e){if(e=xt(e),e.length<4)throw new j(`Inputs to DepthwiseConv2D should have rank 4. Received input shape: ${JSON.stringify(e)}.`);let t=this.dataFormat==="channelsFirst"?1:3;if(e[t]==null||e[t]<0)throw new j(`The channel dimension of the inputs to DepthwiseConv2D should be defined, but is not (${e[t]}).`);let n=e[t],s=[this.kernelSize[0],this.kernelSize[1],n,this.depthMultiplier];this.depthwiseKernel=this.addWeight("depthwise_kernel",s,null,this.depthwiseInitializer,this.depthwiseRegularizer,!0,this.depthwiseConstraint),this.useBias?this.bias=this.addWeight("bias",[n*this.depthMultiplier],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return J(()=>{e=Xe(e);let n=lG(e,this.depthwiseKernel.read(),this.strides,this.padding,this.dataFormat,null);return this.useBias&&(n=Pr(n,this.bias.read(),this.dataFormat)),this.activation!=null&&(n=this.activation.apply(n)),n})}computeOutputShape(e){e=xt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],s=this.dataFormat==="channelsFirst"?e[1]*this.depthMultiplier:e[3]*this.depthMultiplier,r=Er(t,this.kernelSize[0],this.padding,this.strides[0]),a=Er(n,this.kernelSize[1],this.padding,this.strides[1]);return this.dataFormat==="channelsFirst"?[e[0],s,r,a]:[e[0],r,a,s]}getConfig(){let e=super.getConfig();return e.depthMultiplier=this.depthMultiplier,e.depthwiseInitializer=Vt(this.depthwiseInitializer),e.depthwiseRegularizer=St(this.depthwiseRegularizer),e.depthwiseConstraint=gn(this.depthwiseRegularizer),e}};_5.className="DepthwiseConv2D";de.registerClass(_5);function ok(e,t,n,s){if(Array.isArray(e)){if(t!=null||n!=null)throw new j("When inputs is an array, neither initialState or constants should be provided");s!=null&&(n=e.slice(e.length-s,e.length),e=e.slice(0,e.length-s)),e.length>1&&(t=e.slice(1,e.length)),e=e[0]}function r(a){return a==null||Array.isArray(a)?a:[a]}return t=r(t),n=r(n),{inputs:e,initialState:t,constants:n}}function ik(e,t,n,s=!1,r,a,o=!1,i=!1){return J(()=>{let l=t.shape.length;if(l<3)throw new j(`Input should be at least 3D, but is ${l}D.`);let u=[1,0].concat(Rr(2,l));if(t=st(t,u),a!=null)throw new He("The rnn() functoin of the deeplearn.js backend does not support constants yet.");o&&console.warn("Backend rnn(): the unroll = true option is not applicable to the imperative deeplearn.js backend."),r!=null&&(r=ge(ge(r,"bool"),"float32"),r.rank===l-1&&(r=Kt(r,-1)),r=st(r,u)),s&&(t=Ks(t,0),r!=null&&(r=Ks(r,0)));let c=[],p,d=n,h=t.shape[0],f=es(t),m;r!=null&&(m=es(r));for(let y=0;y<h;++y){let x=f[y],A=J(()=>e(x,d));if(r==null)p=A[0],d=A[1];else{let b=J(()=>{let w=m[y],k=he($s(w),w),S=ce(L(A[0],w),L(d[0],k)),E=d.map((R,P)=>ce(L(A[1][P],w),L(R,k)));return{output:S,newStates:E}});p=b.output,d=b.newStates}i&&c.push(p)}let g;return i&&(g=on(c,1)),[p,g,d]})}var Jr=class extends ut{constructor(e){super(e);let t;if(e.cell==null)throw new j("cell property is missing for the constructor of RNN.");if(Array.isArray(e.cell)?t=new h2({cells:e.cell}):t=e.cell,t.stateSize==null)throw new j("The RNN cell should have an attribute `stateSize` (tuple of integers, one integer per RNN state).");this.cell=t,this.returnSequences=e.returnSequences==null?!1:e.returnSequences,this.returnState=e.returnState==null?!1:e.returnState,this.goBackwards=e.goBackwards==null?!1:e.goBackwards,this._stateful=e.stateful==null?!1:e.stateful,this.unroll=e.unroll==null?!1:e.unroll,this.supportsMasking=!0,this.inputSpec=[new rn({ndim:3})],this.stateSpec=null,this.states_=null,this.numConstants=null,this.keptStates=[]}getStates(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;return Rr(0,e).map(t=>null)}else return this.states_}setStates(e){this.states_=e}computeOutputShape(e){P3(e)&&(e=e[0]),e=e;let t=this.cell.stateSize;Array.isArray(t)||(t=[t]);let n=t[0],s;if(this.returnSequences?s=[e[0],e[1],n]:s=[e[0],n],this.returnState){let r=[];for(let a of t)r.push([e[0],a]);return[s].concat(r)}else return s}computeMask(e,t){return J(()=>{Array.isArray(t)&&(t=t[0]);let n=this.returnSequences?t:null;if(this.returnState){let s=this.states.map(r=>null);return[n].concat(s)}else return n})}get states(){if(this.states_==null){let e=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1,t=[];for(let n=0;n<e;++n)t.push(null);return t}else return this.states_}set states(e){this.states_=e}build(e){if(this.numConstants!=null)throw new He("Constants support is not implemented in RNN yet.");P3(e)&&(e=e[0]),e=e;let n=this.stateful?e[0]:null,s=e.slice(2);this.inputSpec[0]=new rn({shape:[n,null,...s]});let r=[e[0]].concat(e.slice(2));this.cell.build(r);let a;if(Array.isArray(this.cell.stateSize)?a=this.cell.stateSize:a=[this.cell.stateSize],this.stateSpec!=null){if(!v.arraysEqual(this.stateSpec.map(o=>o.shape[o.shape.length-1]),a))throw new j(`An initialState was passed that is not compatible with cell.stateSize. Received stateSpec=${this.stateSpec}; However cell.stateSize is ${this.cell.stateSize}`)}else this.stateSpec=a.map(o=>new rn({shape:[null,o]}));this.stateful&&this.resetStates()}resetStates(e,t=!1){J(()=>{if(!this.stateful)throw new ia("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape[0];if(n==null)throw new j("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.states_==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(s=>Wt([n,s])):this.states_=[Wt([n,this.cell.stateSize])];else if(e==null)ne(this.states_),this.keptStates!=null&&(ne(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(s=>Wt([n,s])):this.states_[0]=Wt([n,this.cell.stateSize]);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new j(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t===!0?this.keptStates.push(this.states_.slice()):ne(this.states_);for(let s=0;s<this.states_.length;++s){let r=e[s],a=Array.isArray(this.cell.stateSize)?this.cell.stateSize[s]:this.cell.stateSize,o=[n,a];if(!v.arraysEqual(r.shape,o))throw new j(`State ${s} is incompatible with layer ${this.name}: expected shape=${o}, received shape=${r.shape}`);this.states_[s]=r}}this.states_=this.states_.map(s=>bn(s.clone()))})}apply(e,t){let n=t==null?null:t.initialState,s=t==null?null:t.constants;t==null&&(t={});let r=ok(e,n,s,this.numConstants);e=r.inputs,n=r.initialState,s=r.constants;let a=[],o=[];if(n!=null){t.initialState=n,a=a.concat(n),this.stateSpec=[];for(let l of n)this.stateSpec.push(new rn({shape:l.shape}));o=o.concat(this.stateSpec)}if(s!=null&&(t.constants=s,a=a.concat(s),this.numConstants=s.length),a[0]instanceof Cr){let l=[e].concat(a),u=this.inputSpec.concat(o),c=this.inputSpec;this.inputSpec=u;let p=super.apply(l,t);return this.inputSpec=c,p}else return super.apply(e,t)}call(e,t){return J(()=>{let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;e=Xe(e),r==null&&(this.stateful?r=this.states_:r=this.getInitialState(e));let a=Array.isArray(this.cell.stateSize)?this.cell.stateSize.length:1;if(r.length!==a)throw new j(`RNN Layer has ${a} state(s) but was passed ${r.length} initial state(s).`);this.unroll&&console.warn("Ignoring unroll = true for RNN layer, due to imperative backend.");let o={training:s},l=ik((h,f)=>{let m=this.cell.call([h].concat(f),o);return[m[0],m.slice(1)]},e,r,this.goBackwards,n,null,this.unroll,this.returnSequences),u=l[0],c=l[1],p=l[2];this.stateful&&this.resetStates(p,s);let d=this.returnSequences?c:u;return this.returnState?[d].concat(p):d})}getInitialState(e){return J(()=>{let t=Wt(e.shape);return t=ke(t,[1,2]),t=wh(t),Array.isArray(this.cell.stateSize)?this.cell.stateSize.map(n=>n>1?D3(t,[1,n]):t):this.cell.stateSize>1?[D3(t,[1,this.cell.stateSize])]:[t]})}get trainableWeights(){return this.trainable?this.cell.trainableWeights:[]}get nonTrainableWeights(){return this.trainable?this.cell.nonTrainableWeights:this.cell.weights}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.cell!=null&&this.cell.setFastWeightInitDuringBuild(e)}getConfig(){let e=super.getConfig(),t={returnSequences:this.returnSequences,returnState:this.returnState,goBackwards:this.goBackwards,stateful:this.stateful,unroll:this.unroll};this.numConstants!=null&&(t.numConstants=this.numConstants);let n=this.cell.getConfig();return this.getClassName()===Jr.className&&(t.cell={className:this.cell.getClassName(),config:n}),Object.assign({},n,e,t)}static fromConfig(e,t,n={}){let s=t.cell,r=Nr(s,n);return new e(Object.assign(t,{cell:r}))}};Jr.className="RNN";de.registerClass(Jr);var Rh=class extends ut{},d2=class extends Rh{constructor(e){super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,vn(this.units,"units"),this.activation=ro(e.activation==null?this.DEFAULT_ACTIVATION:e.activation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Ot(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Ot(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Ot(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Mt(e.kernelRegularizer),this.recurrentRegularizer=Mt(e.recurrentRegularizer),this.biasRegularizer=Mt(e.biasRegularizer),this.kernelConstraint=yn(e.kernelConstraint),this.recurrentConstraint=yn(e.recurrentConstraint),this.biasConstraint=yn(e.biasConstraint),this.dropout=ec([1,no([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=ec([1,no([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=xt(e),this.kernel=this.addWeight("kernel",[e[e.length-1],this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return J(()=>{if(e=e,e.length!==2)throw new j(`SimpleRNNCell expects 2 input Tensors, got ${e.length}.`);let n=e[1];e=e[0];let s=t.training==null?!1:t.training;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ao({ones:()=>$s(e),rate:this.dropout,training:s,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ao({ones:()=>$s(n),rate:this.recurrentDropout,training:s,dropoutFunc:this.dropoutFunc}));let r,a=this.dropoutMask,o=this.recurrentDropoutMask;a!=null?r=Hr(L(e,a),this.kernel.read()):r=Hr(e,this.kernel.read()),this.bias!=null&&(r=Pr(r,this.bias.read())),o!=null&&(n=L(n,o));let i=ce(r,Hr(n,this.recurrentKernel.read()));return this.activation!=null&&(i=this.activation.apply(i)),[i,i]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:so(this.activation),useBias:this.useBias,kernelInitializer:Vt(this.kernelInitializer),recurrentInitializer:Vt(this.recurrentInitializer),biasInitializer:Vt(this.biasInitializer),kernelRegularizer:St(this.kernelRegularizer),recurrentRegularizer:St(this.recurrentRegularizer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),kernelConstraint:gn(this.kernelConstraint),recurrentConstraint:gn(this.recurrentConstraint),biasConstraint:gn(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout};return Object.assign({},e,t)}};d2.className="SimpleRNNCell";de.registerClass(d2);var D5=class extends Jr{constructor(e){e.cell=new d2(e),super(e)}call(e,t){return J(()=>{this.cell.dropoutMask!=null&&(ne(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ne(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return new e(t)}};D5.className="SimpleRNN";de.registerClass(D5);var p2=class extends Rh{constructor(e){if(super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.resetAfter)throw new j("GRUCell does not support reset_after parameter set to true.");this.units=e.units,vn(this.units,"units"),this.activation=ro(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ro(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Ot(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Ot(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Ot(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelRegularizer=Mt(e.kernelRegularizer),this.recurrentRegularizer=Mt(e.recurrentRegularizer),this.biasRegularizer=Mt(e.biasRegularizer),this.kernelConstraint=yn(e.kernelConstraint),this.recurrentConstraint=yn(e.recurrentConstraint),this.biasConstraint=yn(e.biasConstraint),this.dropout=ec([1,no([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=ec([1,no([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=this.units,this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){e=xt(e);let t=e[e.length-1];this.kernel=this.addWeight("kernel",[t,this.units*3],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*3],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias?this.bias=this.addWeight("bias",[this.units*3],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint):this.bias=null,this.built=!0}call(e,t){return J(()=>{if(e=e,e.length!==2)throw new j(`GRUCell expects 2 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training==null?!1:t.training,s=e[1];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ao({ones:()=>$s(e),rate:this.dropout,training:n,count:3,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ao({ones:()=>$s(s),rate:this.recurrentDropout,training:n,count:3,dropoutFunc:this.dropoutFunc}));let r=this.dropoutMask,a=this.recurrentDropoutMask,o,i,l;0<this.dropout&&this.dropout<1&&(e=L(e,r[0]));let u=Hr(e,this.kernel.read());this.useBias&&(u=Pr(u,this.bias.read())),0<this.recurrentDropout&&this.recurrentDropout<1&&(s=L(s,a[0]));let c=this.recurrentKernel.read(),[p,d]=Zt(c,[2*this.units,this.units],c.rank-1),h=Hr(s,p),[f,m,g]=Zt(u,3,u.rank-1),[y,x]=Zt(h,2,h.rank-1);o=this.recurrentActivation.apply(ce(f,y)),i=this.recurrentActivation.apply(ce(m,x));let A=Hr(L(i,s),d);l=this.activation.apply(ce(g,A));let b=ce(L(o,s),L(ce(1,Dt(o)),l));return[b,b]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:so(this.activation),recurrentActivation:so(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Vt(this.kernelInitializer),recurrentInitializer:Vt(this.recurrentInitializer),biasInitializer:Vt(this.biasInitializer),kernelRegularizer:St(this.kernelRegularizer),recurrentRegularizer:St(this.recurrentRegularizer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),kernelConstraint:gn(this.kernelConstraint),recurrentConstraint:gn(this.recurrentConstraint),biasConstraint:gn(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation,resetAfter:!1};return Object.assign({},e,t)}};p2.className="GRUCell";de.registerClass(p2);var $5=class extends Jr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new p2(e),super(e)}call(e,t){return J(()=>{this.cell.dropoutMask!=null&&(ne(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ne(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};$5.className="GRU";de.registerClass($5);var _h=class extends Rh{constructor(e){super(e),this.DEFAULT_ACTIVATION="tanh",this.DEFAULT_RECURRENT_ACTIVATION="hardSigmoid",this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_RECURRENT_INITIALIZER="orthogonal",this.DEFAULT_BIAS_INITIALIZER="zeros",this.units=e.units,vn(this.units,"units"),this.activation=ro(e.activation===void 0?this.DEFAULT_ACTIVATION:e.activation),this.recurrentActivation=ro(e.recurrentActivation===void 0?this.DEFAULT_RECURRENT_ACTIVATION:e.recurrentActivation),this.useBias=e.useBias==null?!0:e.useBias,this.kernelInitializer=Ot(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.recurrentInitializer=Ot(e.recurrentInitializer||this.DEFAULT_RECURRENT_INITIALIZER),this.biasInitializer=Ot(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.unitForgetBias=e.unitForgetBias,this.kernelRegularizer=Mt(e.kernelRegularizer),this.recurrentRegularizer=Mt(e.recurrentRegularizer),this.biasRegularizer=Mt(e.biasRegularizer),this.kernelConstraint=yn(e.kernelConstraint),this.recurrentConstraint=yn(e.recurrentConstraint),this.biasConstraint=yn(e.biasConstraint),this.dropout=ec([1,no([0,e.dropout==null?0:e.dropout])]),this.recurrentDropout=ec([1,no([0,e.recurrentDropout==null?0:e.recurrentDropout])]),this.dropoutFunc=e.dropoutFunc,this.implementation=e.implementation,this.stateSize=[this.units,this.units],this.dropoutMask=null,this.recurrentDropoutMask=null}build(e){var t;e=xt(e);let n=e[e.length-1];this.kernel=this.addWeight("kernel",[n,this.units*4],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.recurrentKernel=this.addWeight("recurrent_kernel",[this.units,this.units*4],null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint);let s;if(this.useBias){if(this.unitForgetBias){let r=this.biasInitializer,a=this.units;s=new(t=class extends pr{apply(i,l){let u=r.apply([a]),c=new e2().apply([a]),p=r.apply([a*2]);return $v($v(u,c),p)}},t.className="CustomInit",t)}else s=this.biasInitializer;this.bias=this.addWeight("bias",[this.units*4],null,s,this.biasRegularizer,!0,this.biasConstraint)}else this.bias=null;this.built=!0}call(e,t){return J(()=>{let n=t.training==null?!1:t.training;if(e=e,e.length!==3)throw new j(`LSTMCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let s=e[1],r=e[2];e=e[0],0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ao({ones:()=>$s(e),rate:this.dropout,training:n,count:4,dropoutFunc:this.dropoutFunc})),0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ao({ones:()=>$s(s),rate:this.recurrentDropout,training:n,count:4,dropoutFunc:this.dropoutFunc}));let a=this.dropoutMask,o=this.recurrentDropoutMask,i,l,u,c;0<this.dropout&&this.dropout<1&&(e=L(e,a[0]));let p=Hr(e,this.kernel.read());0<this.recurrentDropout&&this.recurrentDropout<1&&(s=L(s,o[0])),p=ce(p,Hr(s,this.recurrentKernel.read())),this.useBias&&(p=Pr(p,this.bias.read()));let[d,h,f,m]=Zt(p,4,p.rank-1);i=this.recurrentActivation.apply(d),l=this.recurrentActivation.apply(h),u=ce(L(l,r),L(i,this.activation.apply(f))),c=this.recurrentActivation.apply(m);let g=L(c,this.activation.apply(u));return[g,g,u]})}getConfig(){let e=super.getConfig(),t={units:this.units,activation:so(this.activation),recurrentActivation:so(this.recurrentActivation),useBias:this.useBias,kernelInitializer:Vt(this.kernelInitializer),recurrentInitializer:Vt(this.recurrentInitializer),biasInitializer:Vt(this.biasInitializer),unitForgetBias:this.unitForgetBias,kernelRegularizer:St(this.kernelRegularizer),recurrentRegularizer:St(this.recurrentRegularizer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),kernelConstraint:gn(this.kernelConstraint),recurrentConstraint:gn(this.recurrentConstraint),biasConstraint:gn(this.biasConstraint),dropout:this.dropout,recurrentDropout:this.recurrentDropout,implementation:this.implementation};return Object.assign({},e,t)}};_h.className="LSTMCell";de.registerClass(_h);var P5=class extends Jr{constructor(e){e.implementation===0&&console.warn("`implementation=0` has been deprecated, and now defaults to `implementation=1`. Please update your layer call."),e.cell=new _h(e),super(e)}call(e,t){return J(()=>{this.cell.dropoutMask!=null&&(ne(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ne(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null);let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}static fromConfig(e,t){return t.implmentation===0&&(t.implementation=1),new e(t)}};P5.className="LSTM";de.registerClass(P5);var h2=class extends Rh{constructor(e){super(e),this.cells=e.cells}get stateSize(){let e=[];for(let t of this.cells.slice().reverse())Array.isArray(t.stateSize)?e.push(...t.stateSize):e.push(t.stateSize);return e}call(e,t){return J(()=>{e=e;let n=e.slice(1),s=[];for(let o of this.cells.slice().reverse())Array.isArray(o.stateSize)?s.push(n.splice(0,o.stateSize.length)):s.push(n.splice(0,1));s.reverse();let r=[],a;for(let o=0;o<this.cells.length;++o){let i=this.cells[o];n=s[o],o===0?a=[e[0]].concat(n):a=[a[0]].concat(n),a=i.call(a,t),r.push(a.slice(1))}n=[];for(let o of r.slice().reverse())n.push(...o);return[a[0]].concat(n)})}build(e){P3(e)&&(e=e[0]),e=e;let t;this.cells.forEach((n,s)=>{Gi(`RNNCell_${s}`,()=>{n.build(e),Array.isArray(n.stateSize)?t=n.stateSize[0]:t=n.stateSize,e=[e[0],t]})}),this.built=!0}getConfig(){let e=super.getConfig(),t=r=>({className:r.getClassName(),config:r.getConfig()}),s={cells:this.cells.map(t)};return Object.assign({},e,s)}static fromConfig(e,t,n={}){let s=[];for(let r of t.cells)s.push(Nr(r,n));return new e({cells:s})}get trainableWeights(){if(!this.trainable)return[];let e=[];for(let t of this.cells)e.push(...t.trainableWeights);return e}get nonTrainableWeights(){let e=[];for(let t of this.cells)e.push(...t.nonTrainableWeights);if(!this.trainable){let t=[];for(let n of this.cells)t.push(...n.trainableWeights);return t.concat(e)}return e}getWeights(){let e=[];for(let t of this.cells)e.push(...t.weights);return F3(e)}setWeights(e){let t=[];for(let n of this.cells){let s=n.weights.length,r=e.splice(s);for(let a=0;a<n.weights.length;++a)t.push([n.weights[a],r[a]])}r5(t)}};h2.className="StackedRNNCells";de.registerClass(h2);function ao(e){let{ones:t,rate:n,training:s=!1,count:r=1,dropoutFunc:a}=e,o=()=>a!=null?a(t(),n):x8(t(),n),i=()=>Ih(o,t,s);return!r||r<=1?bn(i().clone()):Array(r).fill(void 0).map(i).map(u=>bn(u.clone()))}var uG=function(e,t){var n={};for(var s in e)Object.prototype.hasOwnProperty.call(e,s)&&t.indexOf(s)<0&&(n[s]=e[s]);if(e!=null&&typeof Object.getOwnPropertySymbols=="function")for(var r=0,s=Object.getOwnPropertySymbols(e);r<s.length;r++)t.indexOf(s[r])<0&&Object.prototype.propertyIsEnumerable.call(e,s[r])&&(n[s[r]]=e[s[r]]);return n},lk=class extends Jr{constructor(e){if(e.unroll)throw new He("Unrolling is not possible with convolutional RNNs.");if(Array.isArray(e.cell))throw new He("It is not possible at the moment to stack convolutional cells.");super(e),this.inputSpec=[new rn({ndim:5})]}call(e,t){return J(()=>{if(this.cell.dropoutMask!=null&&(ne(this.cell.dropoutMask),this.cell.dropoutMask=null),this.cell.recurrentDropoutMask!=null&&(ne(this.cell.recurrentDropoutMask),this.cell.recurrentDropoutMask=null),t&&t.constants)throw new j("ConvRNN2D cell does not support constants");let n=t==null?null:t.mask,s=t==null?null:t.training,r=t==null?null:t.initialState;return super.call(e,{mask:n,training:s,initialState:r})})}computeOutputShape(e){let t=this.computeSingleOutputShape(e);return this.returnSequences||(t=[t[0],...t.slice(2)]),this.returnState&&(t=[t,...Array(2).fill([e[0],...t.slice(-3)])]),t}getInitialState(e){return J(()=>{let{stateSize:t}=this.cell,n=e.shape,s=this.computeSingleOutputShape(n),r=[s[0],...s.slice(2)],a=Wt(r);return Array.isArray(t)?Array(t.length).fill(a):[a]})}resetStates(e,t=!1){J(()=>{if(!this.stateful)throw new ia("Cannot call resetStates() on an RNN Layer that is not stateful.");let n=this.inputSpec[0].shape,s=this.computeSingleOutputShape(n),r=[s[0],...s.slice(2)];if(n[0]==null)throw new j("If an RNN is stateful, it needs to know its batch size. Specify the batch size of your input tensors: \n- If using a Sequential model, specify the batch size by passing a `batchInputShape` option to your first layer.\n- If using the functional API, specify the batch size by passing a `batchShape` option to your Input layer.");if(this.getStates()==null)Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Wt(r)):this.states_=[Wt(r)];else if(e==null)ne(this.states_),this.keptStates!=null&&(ne(this.keptStates),this.keptStates=[]),Array.isArray(this.cell.stateSize)?this.states_=this.cell.stateSize.map(()=>Wt(r)):this.states_[0]=Wt(r);else{if(Array.isArray(e)||(e=[e]),e.length!==this.states_.length)throw new j(`Layer ${this.name} expects ${this.states_.length} state(s), but it received ${e.length} state value(s). Input received: ${e}`);t?this.keptStates.push(this.states_.slice()):ne(this.states_);for(let o=0;o<this.states_.length;++o){let i=e[o],l=r;if(!v.arraysEqual(i.shape,l))throw new j(`State ${o} is incompatible with layer ${this.name}: expected shape=${l}, received shape=${i.shape}`);this.states_[o]=i}}this.states_=this.states_.map(o=>bn(o.clone()))})}computeSingleOutputShape(e){let{dataFormat:t,filters:n,kernelSize:s,padding:r,strides:a,dilationRate:o}=this.cell,i=t==="channelsFirst",l=e[i?3:2],u=e[i?4:3],c=Er(l,s[0],r,a[0],o[0]),p=Er(u,s[1],r,a[1],o[1]);return[...e.slice(0,2),...i?[n,c,p]:[c,p,n]]}};lk.className="ConvRNN2D";var f2=class extends _h{constructor(e){let{filters:t,kernelSize:n,strides:s,padding:r,dataFormat:a,dilationRate:o}=e;super(Object.assign({},e,{units:t})),this.filters=t,vn(this.filters,"filters"),this.kernelSize=Gu(n,2,"kernelSize"),this.kernelSize.forEach(i=>vn(i,"kernelSize")),this.strides=Gu(s||1,2,"strides"),this.strides.forEach(i=>vn(i,"strides")),this.padding=r||"valid",Qs(this.padding),this.dataFormat=a||"channelsLast",Yt(this.dataFormat),this.dilationRate=Gu(o||1,2,"dilationRate"),this.dilationRate.forEach(i=>vn(i,"dilationRate"))}build(e){var t;e=xt(e);let n=this.dataFormat==="channelsFirst"?1:e.length-1;if(e[n]==null)throw new j(`The channel dimension of the input should be defined. Found ${e[n]}`);let s=e[n],r=4,a=this.kernelSize.concat([s,this.filters*r]);this.kernel=this.addWeight("kernel",a,null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint);let o=this.kernelSize.concat([this.filters,this.filters*r]);if(this.recurrentKernel=this.addWeight("recurrent_kernel",o,null,this.recurrentInitializer,this.recurrentRegularizer,!0,this.recurrentConstraint),this.useBias){let i;if(this.unitForgetBias){let l=this.biasInitializer,u=this.filters;i=new(t=class extends pr{apply(p,d){let h=l.apply([u]),f=Ns([u]),m=l.apply([u*2]);return ZA([h,f,m])}},t.className="CustomInit",t)}else i=this.biasInitializer;this.bias=this.addWeight("bias",[this.filters*r],null,i,this.biasRegularizer,!0,this.biasConstraint)}this.built=!0}call(e,t){return J(()=>{if(e.length!==3)throw new j(`ConvLSTM2DCell expects 3 input Tensors (inputs, h, c), got ${e.length}.`);let n=t.training||!1,s=e[0],r=e[1],a=e[2],o=4;0<this.dropout&&this.dropout<1&&this.dropoutMask==null&&(this.dropoutMask=ao({ones:()=>$s(s),rate:this.dropout,training:n,count:o,dropoutFunc:this.dropoutFunc}));let i=this.dropoutMask,l=(B,ee,Q)=>!ee||!ee[Q]?B:L(ee[Q],B),u=l(s,i,0),c=l(s,i,1),p=l(s,i,2),d=l(s,i,3);0<this.recurrentDropout&&this.recurrentDropout<1&&this.recurrentDropoutMask==null&&(this.recurrentDropoutMask=ao({ones:()=>$s(r),rate:this.recurrentDropout,training:n,count:o,dropoutFunc:this.dropoutFunc}));let h=this.recurrentDropoutMask,f=l(r,h,0),m=l(r,h,1),g=l(r,h,2),y=l(r,h,3),x=3,[A,b,w,k]=Zt(this.kernel.read(),o,x),[S,E,R,P]=this.useBias?Zt(this.bias.read(),o):[null,null,null,null];u=this.inputConv(u,A,S,this.padding),c=this.inputConv(c,b,E,this.padding),p=this.inputConv(p,w,R,this.padding),d=this.inputConv(d,k,P,this.padding);let[_,$,T,F]=Zt(this.recurrentKernel.read(),o,x);f=this.recurrentConv(f,_),m=this.recurrentConv(m,$),g=this.recurrentConv(g,T),y=this.recurrentConv(y,F);let G=this.recurrentActivation.apply(ce(u,f)),q=this.recurrentActivation.apply(ce(c,m)),z=ce(L(q,a),L(G,this.activation.apply(ce(p,g)))),Z=L(this.recurrentActivation.apply(ce(d,y)),this.activation.apply(z));return[Z,Z,z]})}getConfig(){let e=super.getConfig(),{units:t}=e,n=uG(e,["units"]),s={filters:this.filters,kernelSize:this.kernelSize,padding:this.padding,dataFormat:this.dataFormat,dilationRate:this.dilationRate,strides:this.strides};return Object.assign({},n,s)}inputConv(e,t,n,s){let r=fa(e,t,this.strides,s||"valid",this.dataFormat==="channelsFirst"?"NCHW":"NHWC",this.dilationRate);return n?Pr(r,n,this.dataFormat):r}recurrentConv(e,t){return fa(e,t,1,"same",this.dataFormat==="channelsFirst"?"NCHW":"NHWC")}};f2.className="ConvLSTM2DCell";de.registerClass(f2);var F5=class extends lk{constructor(e){let t=new f2(e);super(Object.assign({},e,{cell:t}))}static fromConfig(e,t){return new e(t)}};F5.className="ConvLSTM2D";de.registerClass(F5);var m2=class extends ut{constructor(e){super(e),this.rate=Math.max(Math.min(e.rate,1),0),this.noiseShape=e.noiseShape,this.seed=e.seed,this.supportsMasking=!0}getNoiseShape(e){if(this.noiseShape==null)return this.noiseShape;let t=e.shape,n=[];for(let s=0;s<this.noiseShape.length;++s)n.push(this.noiseShape[s]==null?t[s]:this.noiseShape[s]);return n}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);if(0<this.rate&&this.rate<1){let s=t.training==null?!1:t.training,r=this.getNoiseShape(n);return Ih(()=>x8(n,this.rate,r,this.seed),()=>n,s)}return e})}getConfig(){let e={rate:this.rate,noiseShape:this.noiseShape,seed:this.seed},t=super.getConfig();return Object.assign(e,t),e}dispose(){return super.dispose()}};m2.className="Dropout";de.registerClass(m2);var O5=class extends m2{constructor(e){super(e),this.inputSpec=[{ndim:3}]}getNoiseShape(e){let t=e.shape;return[t[0],1,t[2]]}};O5.className="SpatialDropout1D";de.registerClass(O5);var M5=class extends ut{constructor(e){if(super(e),this.activation=null,this.useBias=!0,this.kernel=null,this.bias=null,this.DEFAULT_KERNEL_INITIALIZER="glorotNormal",this.DEFAULT_BIAS_INITIALIZER="zeros",e.batchInputShape==null&&e.inputShape==null&&e.inputDim!=null){let t=null;e.batchSize!=null&&(t=e.batchSize),this.batchInputShape=[t,e.inputDim]}this.units=e.units,vn(this.units,"units"),this.activation=ro(e.activation),e.useBias!=null&&(this.useBias=e.useBias),this.kernelInitializer=Ot(e.kernelInitializer||this.DEFAULT_KERNEL_INITIALIZER),this.biasInitializer=Ot(e.biasInitializer||this.DEFAULT_BIAS_INITIALIZER),this.kernelConstraint=yn(e.kernelConstraint),this.biasConstraint=yn(e.biasConstraint),this.kernelRegularizer=Mt(e.kernelRegularizer),this.biasRegularizer=Mt(e.biasRegularizer),this.activityRegularizer=Mt(e.activityRegularizer),this.supportsMasking=!0,this.inputSpec=[{minNDim:2}]}build(e){e=xt(e);let t=e[e.length-1];this.kernel==null&&(this.kernel=this.addWeight("kernel",[t,this.units],null,this.kernelInitializer,this.kernelRegularizer,!0,this.kernelConstraint),this.useBias&&(this.bias=this.addWeight("bias",[this.units],null,this.biasInitializer,this.biasRegularizer,!0,this.biasConstraint))),this.inputSpec=[{minNDim:2,axes:{[-1]:t}}],this.built=!0}computeOutputShape(e){e=xt(e);let t=e.slice();return t[t.length-1]=this.units,t}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e),s=p8(this.activation.getClassName()),r;return s!=null?r=Hr(n,this.kernel.read(),s,this.bias?this.bias.read():null):(r=Hr(n,this.kernel.read()),this.bias!=null&&(r=Pr(r,this.bias.read())),this.activation!=null&&(r=this.activation.apply(r))),r})}getConfig(){let e={units:this.units,activation:so(this.activation),useBias:this.useBias,kernelInitializer:Vt(this.kernelInitializer),biasInitializer:Vt(this.biasInitializer),kernelRegularizer:St(this.kernelRegularizer),biasRegularizer:St(this.biasRegularizer),activityRegularizer:St(this.activityRegularizer),kernelConstraint:gn(this.kernelConstraint),biasConstraint:gn(this.biasConstraint)},t=super.getConfig();return Object.assign(e,t),e}};M5.className="Dense";de.registerClass(M5);var z5=class extends ut{constructor(e){e=e||{},super(e),this.inputSpec=[{minNDim:3}],this.dataFormat=e.dataFormat}computeOutputShape(e){e=xt(e);for(let t of e.slice(1))if(t==null)throw new j(`The shape of the input to "Flatten" is not fully defined (got ${e.slice(1)}). Make sure to pass a complete "input_shape" or "batch_input_shape" argument to the first layer in your model.`);return[e[0],Xa(e,1)]}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);if(this.dataFormat==="channelsFirst"&&n.rank>1){let s=[0];for(let r=2;r<n.rank;++r)s.push(r);s.push(1),n=st(n,s)}return kV(n)})}getConfig(){let e={};this.dataFormat!=null&&(e.dataFormat=this.dataFormat);let t=super.getConfig();return Object.assign(e,t),e}};z5.className="Flatten";de.registerClass(z5);var L5=class extends ut{constructor(e){super(e),this.supportsMasking=!0,this.activation=ro(e.activation)}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);return this.activation.apply(n)})}getConfig(){let e={activation:so(this.activation)},t=super.getConfig();return Object.assign(e,t),e}};L5.className="Activation";de.registerClass(L5);var B5=class extends ut{constructor(e){super(e),this.n=e.n,this.inputSpec=[{ndim:2}]}computeOutputShape(e){return[e[0],this.n,e[1]]}call(e,t){return J(()=>(e=Xe(e),vV(e,this.n)))}getConfig(){let e={n:this.n},t=super.getConfig();return Object.assign(e,t),e}};B5.className="RepeatVector";de.registerClass(B5);var W5=class extends ut{constructor(e){super(e),this.targetShape=e.targetShape;for(let t=0;t<this.targetShape.length;++t)this.isUnknown(this.targetShape[t])&&(this.targetShape[t]=null)}isUnknown(e){return e<0||e==null}fixUnknownDimension(e,t){let n="Total size of new array must be unchanged.",s=t.slice(),r=1,a=null;for(let i=0;i<s.length;++i){let l=s[i];if(this.isUnknown(l))if(a===null)a=i;else throw new j("Can only specifiy one unknown dimension.");else r*=l}let o=Xa(e);if(a!==null){if(r===0||o%r!==0)throw new j(n);s[a]=o/r}else if(o!==r)throw new j(n);return s}computeOutputShape(e){let t=!1;for(let n=0;n<e.length;++n)if(this.isUnknown(e[n])){t=!0;break}return t?e.slice(0,1).concat(this.targetShape):e.slice(0,1).concat(this.fixUnknownDimension(e.slice(1),this.targetShape))}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e),s=n.shape,r=s.slice(0,1).concat(this.fixUnknownDimension(s.slice(1),this.targetShape));return U(n,r)})}getConfig(){let e={targetShape:this.targetShape},t=super.getConfig();return Object.assign(e,t),e}};W5.className="Reshape";de.registerClass(W5);var V5=class extends ut{constructor(e){if(super(e),e.dims==null)throw new Error("Required configuration field `dims` is missing during Permute constructor call.");if(!Array.isArray(e.dims))throw new Error(`Permute constructor requires \`dims\` to be an Array, but received ${e.dims} instead.`);let t=Rr(1,e.dims.length+1);if(!v.arraysEqual(e.dims.slice().sort(),t))throw new Error("Invalid permutation `dims`: "+JSON.stringify(e.dims)+" `dims` must contain consecutive integers starting from 1.");this.dims=e.dims,this.dimsIncludingBatch=[0].concat(this.dims),this.inputSpec=[new rn({ndim:this.dims.length+1})]}computeOutputShape(e){e=xt(e);let t=e.slice();return this.dims.forEach((n,s)=>{t[s+1]=e[n]}),t}call(e,t){return st(Xe(e),this.dimsIncludingBatch)}getConfig(){let e={dims:this.dims},t=super.getConfig();return Object.assign(e,t),e}};V5.className="Permute";de.registerClass(V5);var U5=class extends ut{constructor(e){super(e==null?{}:e),this.supportsMasking=!0,e!=null?this.maskValue=e.maskValue==null?0:e.maskValue:this.maskValue=0}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={maskValue:this.maskValue};return Object.assign(t,e),t}computeMask(e,t){let n=Xe(e),s=-1;return Sp(Ji(n,this.maskValue),s)}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e),s=-1,r=!0,a=Sp(Ji(n,this.maskValue),s,r);return L(n,ge(a,n.dtype))})}};U5.className="Masking";de.registerClass(U5);var G5=class extends ut{constructor(e){if(super(e),this.embeddings=null,this.DEFAULT_EMBEDDINGS_INITIALIZER="randomUniform",e.batchInputShape==null&&e.inputShape==null){let t=null;e.batchSize!=null&&(t=e.batchSize),e.inputLength==null?this.batchInputShape=[t,null]:this.batchInputShape=[t].concat(_t(e.inputLength))}this.inputDim=e.inputDim,vn(this.inputDim,"inputDim"),this.outputDim=e.outputDim,vn(this.outputDim,"outputDim"),this.embeddingsInitializer=Ot(e.embeddingsInitializer||this.DEFAULT_EMBEDDINGS_INITIALIZER),this.embeddingsRegularizer=Mt(e.embeddingsRegularizer),this.activityRegularizer=Mt(e.activityRegularizer),this.embeddingsConstraint=yn(e.embeddingsConstraint),this.maskZero=e.maskZero,this.supportsMasking=e.maskZero,this.inputLength=e.inputLength}build(e){this.embeddings=this.addWeight("embeddings",[this.inputDim,this.outputDim],this.dtype,this.embeddingsInitializer,this.embeddingsRegularizer,!0,this.embeddingsConstraint),this.built=!0}warnOnIncompatibleInputShape(e){}computeMask(e,t){return J(()=>this.maskZero?(e=Xe(e),Ji(e,it(e))):null)}computeOutputShape(e){if(e=xt(e),this.inputLength==null)return[...e,this.outputDim];let t=_t(this.inputLength);if(t.length!==e.length-1)throw new j(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);{let n=0;for(let s=0;s<t.length;++s){let r=t[s],a=e[s+1];if(r!=null&&a!=null&&r!==a)throw new j(`"inputLength" is ${this.inputLength}, but received input shape has shape ${e}`);r==null&&(t[n]=a),n++}}return[e[0],...t,this.outputDim]}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);n.dtype!=="int32"&&(n=J0(n,"int32"));let s=A8(this.embeddings.read(),U(n,[n.size]));return U(s,xt(this.computeOutputShape(n.shape)))})}getConfig(){let e={inputDim:this.inputDim,outputDim:this.outputDim,embeddingsInitializer:Vt(this.embeddingsInitializer),embeddingsRegularizer:St(this.embeddingsRegularizer),activityRegularizer:St(this.activityRegularizer),embeddingsConstraint:gn(this.embeddingsConstraint),maskZero:this.maskZero,inputLength:this.inputLength},t=super.getConfig();return Object.assign(e,t),e}};G5.className="Embedding";de.registerClass(G5);var tu=class extends ut{constructor(e){super(e||{}),this.supportsMasking=!0}mergeFunction(e){throw new He}computeElementwiseOpOutputShape(e,t){if(e==null||t==null)return null;if(e.length<t.length)return this.computeElementwiseOpOutputShape(t,e);if(t.length===0)return e;let n=e.slice(0,e.length-t.length);for(let s=0;s<t.length;++s){let r=e[e.length-t.length+s],a=t[s];if(r==null||a==null||r<0||a<0)n.push(null);else if(r===1)n.push(a);else if(a===1)n.push(r);else{if(r!==a)throw new j("Operands could not be broadcast together with shapes "+JSON.stringify(e)+" "+JSON.stringify(t));n.push(r)}}return n}build(e){if(Array.isArray(e)&&!Array.isArray(e[0])&&(e=[xt(e)]),e=e,e.length<2)throw new j(`A merge layer should be called on an Array of at least 2 inputs. Got ${e.length} input(s).`);let t=[];for(let r of e)r!=null&&r[0]!==null&&t.push(r[0]);if(t=qa(t),t.length>1)throw new j(`Can not merge tensors with different batch sizes. Got tensors with shapes: ${JSON.stringify(e)}.`);let n=e[0]==null?null:e[0].slice(1);for(let r=1;r<e.length;++r){let a=e[r]==null?null:e[r].slice(1);n=this.computeElementwiseOpOutputShape(n,a)}let s=e.map(r=>r.length);e.indexOf(null)===-1&&qa(s).length===1?this.reshapeRequired=!1:this.reshapeRequired=!0}call(e,t){return J(()=>{if(e=e,this.reshapeRequired){let n=[],s=e.map(r=>r.rank);if(s.indexOf(null)===-1){let r=no(s);for(let a of e){let o=a.rank;for(let i=0;i<r-o;++i)a=wh(a,1);n.push(a)}return this.mergeFunction(n)}else{let r=!1;for(let i of e){let l=i.rank;if(l==null){let u=i.shape,c=u[0],p=u.slice(1).concat([c]),d=U(i,[c].concat(Xa(u.slice(1))));d=st(d,[1,0]),d=U(d,p),n.push(d),r=!0}else if(l>1){let u=Rr(1,l).concat([0]);n.push(st(i,u)),r=!0}else n.push(i)}let a=this.mergeFunction(n),o=a.rank;if(r){if(o==null){let i=a.shape,l=i.length,u=i[l-1],c=[u].concat(i.slice(0,i.length-1));a=U(st(U(a,[-1,u]),[1,0]),c)}else if(o>1){let i=[o-1].concat(Rr(0,o-1));a=st(a,i)}}return a}}else return this.mergeFunction(e)})}computeOutputShape(e){e=e;let t;e[0]==null?t=null:t=e[0].slice(1);for(let s=1;s<e.length;++s){let r=e[s]==null?null:e[s].slice(1);t=this.computeElementwiseOpOutputShape(t,r)}let n=[];for(let s of e)s!=null&&s[0]!==null&&n.push(s[0]);return n=qa(n),n.length===1?t=n.concat(t):t=[null].concat(t),t}computeMask(e,t){return J(()=>{if(t==null)return null;if(!Array.isArray(t))throw new j("`mask` should be an Array");if(!Array.isArray(e))throw new j("`inputs` should be an Array");if(t.length!==e.length)throw new j(`The Array 'inputs' and 'mask' are expected to have the same length, but have different lengths (${e.length} vs ${t.length})`);if(t.every(s=>s==null))return null;t=t.map(s=>s==null?s:Kt(s,0));let n=t[0];for(let s=1;s<t.length-1;++s)n=lr(n,t[s]);return n})}},H5=class extends tu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ce(t,e[n]);return t})}};H5.className="Add";de.registerClass(H5);var j5=class extends tu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=L(t,e[n]);return t})}};j5.className="Multiply";de.registerClass(j5);var q5=class extends tu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0].clone();for(let n=1;n<e.length;++n)t=ce(t,e[n]);return L(1/e.length,t)})}};q5.className="Average";de.registerClass(q5);var X5=class extends tu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=Yr(t,e[n]);return t})}};X5.className="Maximum";de.registerClass(X5);var K5=class extends tu{constructor(e){super(e)}mergeFunction(e){return J(()=>{let t=e[0];for(let n=1;n<e.length;++n)t=qc(t,e[n]);return t})}};K5.className="Minimum";de.registerClass(K5);var Z5=class extends tu{constructor(e){super(e),this.DEFAULT_AXIS=-1,e==null&&(e={}),this.axis=e.axis==null?this.DEFAULT_AXIS:e.axis,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){if(!(Array.isArray(e)&&Array.isArray(e[0]))||e.length===1)throw new j("A `Concatenate` layer should be called on a list of at least 2 inputs");e=e;let t=!0;for(let s of e)if(s!=null){t=!1;break}if(t)return;let n=[];for(let s=0;s<e.length;++s){let r=e[s].slice();r.splice(this.axis,1);let a=!1;for(let o of n)if(v.arraysEqual(o,r)){a=!0;break}a||n.push(r)}if(n.length>1)throw new j("A `Concatenate` layer requires inputs with matching shapes except for the concat axis. Got input shapes: "+JSON.stringify(e))}mergeFunction(e){return J(()=>ZA(e,this.axis))}computeOutputShape(e){if(!(Array.isArray(e)&&Array.isArray(e[0])))throw new j("A `Concatenate` layer should be called on a list of inputs.");let t=e,n=t[0].slice(),s=this.axis<0?n.length+this.axis:this.axis;for(let r of t.slice(1)){if(n[s]==null||r[s]==null){n[s]=null;break}n[s]+=r[s]}return n}computeMask(e,t){if(t==null)return null;if(!Array.isArray(t))throw new j("`mask` should be an array for Concatenate");if(!Array.isArray(e))throw new j("`inputs` should be an array for Concatenate");if(t.length!==e.length)throw new j(`Mismatch in the length of mask (${t.length}) and the legnth of inputs (${e.length})`);return J(()=>{let n=!0;if(t.forEach(a=>{if(a!=null){n=!1;return}}),n)return null;let s=[];for(let a=0;a<e.length;++a)t[a]==null?s.push(ge($s(e[a]),"bool")):t[a].rank<e[a].rank?s.push(Kt(t[a],-1)):s.push(t[a]);let r=Ct(s,this.axis);return m0(r,-1,!1)})}getConfig(){let e={axis:this.axis},t=super.getConfig();return Object.assign(e,t),e}};Z5.className="Concatenate";de.registerClass(Z5);function Qd(e,t){for(;e<0;)e+=t;return e}function cG(e,t,n){if(e.shape.length>3||t.shape.length>3)throw new He("batchDot is not implemented for tensors of 4D or higher rank yet");if(v.assert(e.shape.length>=2,()=>`batchDot requires the rank of x to be >= 2, but got ${e.shape.length}`),v.assert(e.shape.length>=2,()=>`batchDot requires the rank of y to be >= 2, but got ${t.shape.length}`),typeof n=="number"&&(n=[n,n]),e.dtype==="complex64"||t.dtype==="complex64")throw new He("batchDot is not implemented for complex64-type Tensors yet.");let s=e.shape.length,r=t.shape.length;n==null&&(n=[s-1,r-2]);let a=n;return J(()=>{let o;if(s>r){o=s-r;let l=[];for(let u=0;u<o;++u)l.push(1);t=U(t,t.shape.concat(l))}else if(r>s){o=r-s;let l=[];for(let u=0;u<o;++u)l.push(1);e=U(e,e.shape.concat(l))}else o=0;let i;if(e.shape.length===2&&t.shape.length===2)a[0]===a[1]?i=ke(L(e,t),a[0]):i=ke(L(st(e,[1,0]),t),a[1]);else{let l=a[0]!==e.shape.length-1,u=a[1]===t.shape.length-1;i=Qe(e,t,l,u)}if(o>0){let l;s>r?l=s+r-3:l=s-1;let u=[];for(let c=l;c<l+o;++c)u.push(c);i=rt(i,u)}return i.shape.length===1&&(i=Kt(i,1)),i})}var Y5=class extends tu{constructor(e){super(e),this.axes=e.axes,this.normalize=e.normalize==null?!1:e.normalize,this.supportsMasking=!0,this.reshapeRequired=!1}build(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0],n=e[1];if(t.length>3||n.length>3)throw new He("Dot layer does not support tensors of 4D or higher rank yet.");let s=this.interpretAxes(t,n);if(t[s[0]]!==n[s[1]])throw new j(`Dimension incompatibility: ${t[s[0]]} !== ${n[s[1]]}`)}mergeFunction(e){if(e.length!==2)throw new j(`A \`Dot\` layer must be called on exactly 2 inputs, but received ${e.length} input(s).`);let t=e[0],n=e[1],s;return Array.isArray(this.axes)?s=this.axes.map((r,a)=>Qd(r,e[a].shape.length)):s=[Qd(this.axes,t.shape.length),Qd(this.axes,n.shape.length)],this.normalize&&(t=wm(t,s[0]),n=wm(n,s[1])),cG(t,n,s)}interpretAxes(e,t){let n;return Array.isArray(this.axes)?n=this.axes:n=[Qd(this.axes,e.length),Qd(this.axes,t.length)],n}computeOutputShape(e){v.assert(Array.isArray(e)&&e.length===2&&Array.isArray(e[0])&&Array.isArray(e[1]),()=>"A `Dot` layer should be called on a list of exactly 2 inputs.");let t=e[0].slice(),n=e[1].slice();if(t.length>3||n.length>3)throw new He("Dot layer does not support tensors of 4D or higher rank yet.");let s=this.interpretAxes(t,n);t.splice(s[0],1),n.splice(s[1],1),n.splice(0,1);let r=t.concat(n);return r.length===1&&r.push(1),r}computeMask(e,t){return null}getConfig(){let e={axes:this.axes,normalize:this.normalize},t=super.getConfig();return Object.assign(e,t),e}};Y5.className="Dot";de.registerClass(Y5);var J5=class extends ut{constructor(e){super(e),this.supportsMasking=!0,this.stddev=e.stddev}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={stddev:this.stddev};return Object.assign(t,e),t}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);return Ih(()=>ce(Q0(n.shape,0,this.stddev),n),()=>n,t.training||!1)})}};J5.className="GaussianNoise";de.registerClass(J5);var Q5=class extends ut{constructor(e){super(e),this.supportsMasking=!0,this.rate=e.rate}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return J(()=>{this.invokeCallHook(e,t);let n=Xe(e);return this.rate>0&&this.rate<1?Ih(()=>{let r=Math.sqrt(this.rate/(1-this.rate));return L(n,Q0(n.shape,1,r))},()=>n,t.training||!1):n})}};Q5.className="GaussianDropout";de.registerClass(Q5);var ex=class extends ut{constructor(e){super(e),this.supportsMasking=!0,this.rate=e.rate,this.noiseShape=e.noiseShape}_getNoiseShape(e){return this.noiseShape||Xe(e).shape}computeOutputShape(e){return e}getConfig(){let e=super.getConfig(),t={rate:this.rate};return Object.assign(t,e),t}call(e,t){return J(()=>{if(this.rate<1&&this.rate>0){let n=this._getNoiseShape(e);return Ih(()=>{let r=Xe(e),a=1.6732632423543772,o=1.0507009873554805,i=-a*o,l=ii(Xc(n),this.rate);l=J0(l,"float32");let u=((1-this.rate)*(1+this.rate*i**2))**-.5,c=-u*i*this.rate,p=ce(L(r,l),L(ce(l,-1),i));return ce(L(p,u),c)},()=>Xe(e),t.training||!1)}return e})}};ex.className="AlphaDropout";de.registerClass(ex);function Ep(e,t,n,s,r,a=.001){let o;if(e.rank===2)o=tA(e,t,n,s,r,a);else if(e.rank===3)o=nA(e,t,n,s,r,a);else if(e.rank===4)o=sA(e,t,n,s,r,a);else throw new He(`batchNormalization is not implemented for array of rank ${e.rank} yet`);return o}function dG(e,t,n,s,r=.001){return J(()=>{let a=fh(e,s),o=a.mean,i=a.variance;return[Ep(e,o,i,n,t,r),o,i]})}function pG(e,t,n,s,r=.001){return J(()=>{let a=fh(e,s),o=a.mean,i=a.variance,l=[];for(let f of Rr(0,e.rank))s.indexOf(f)!==-1?l.push(1):l.push(e.shape[f]);let u=U(o,l),c=U(i,l),p=t==null?null:U(t,l),d=n==null?null:U(n,l);return[Ep(e,u,c,d,p,r),o,i]})}function hG(e,t,n,s,r=.001){return v.arraysEqual(s.slice().sort(),Rr(0,e.rank-1))?dG(e,t,n,s,r):pG(e,t,n,s,r)}var tx=class extends ut{constructor(e){e==null&&(e={}),super(e),this.supportsMasking=!0,this.axis=e.axis==null?-1:e.axis,this.momentum=e.momentum==null?.99:e.momentum,this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=Ot(e.betaInitializer||"zeros"),this.gammaInitializer=Ot(e.gammaInitializer||"ones"),this.movingMeanInitializer=Ot(e.movingMeanInitializer||"zeros"),this.movingVarianceInitializer=Ot(e.movingVarianceInitializer||"ones"),this.betaConstraint=yn(e.betaConstraint),this.gammaConstraint=yn(e.gammaConstraint),this.betaRegularizer=Mt(e.betaRegularizer),this.gammaRegularizer=Mt(e.gammaRegularizer)}build(e){e=xt(e);let t=this.axis>=0?this.axis:this.axis+e.length,n=e[t];if(n==null)throw new j(`Axis ${t} of input tensor should have a defined dimension but the layer received an input with shape ${JSON.stringify(e)}.`);this.inputSpec=[new rn({ndim:e.length,axes:{[t]:n}})];let s=[n];this.scale&&(this.gamma=this.addWeight("gamma",s,null,this.gammaInitializer,this.gammaRegularizer,!0,this.gammaConstraint)),this.center&&(this.beta=this.addWeight("beta",s,null,this.betaInitializer,this.betaRegularizer,!0,this.betaConstraint)),this.movingMean=this.addWeight("moving_mean",s,null,this.movingMeanInitializer,null,!1),this.movingVariance=this.addWeight("moving_variance",s,null,this.movingVarianceInitializer,null,!1),this.built=!0}call(e,t){return J(()=>{let n=t.training==null?!1:t.training,s=Xe(e),r=s.shape,a=r.length,o=Rr(0,a),i=this.axis>=0?this.axis:this.axis+a;o.splice(i,1);let l=Qi(1,a);l[i]=r[i];let u=o.slice();u.sort();let c=!v.arraysEqual(u,Rr(0,a).slice(0,a-1)),p=()=>{if(c){let y=U(this.movingMean.read(),l),x=U(this.movingVariance.read(),l),A=this.center?U(this.beta.read(),l):null,b=this.scale?U(this.gamma.read(),l):null;return Ep(s,y,x,A,b,this.epsilon)}else return Ep(s,this.movingMean.read(),this.movingVariance.read(),this.beta==null?null:this.beta.read(),this.gamma==null?null:this.gamma.read(),this.epsilon)};if(!n)return p();let[d,h,f]=hG(s,this.gamma.read(),this.beta.read(),o,this.epsilon),m=(y,x,A)=>{J(()=>{let b=1-A,w=y.read(),k=L(he(w,x),b);y.write(he(w,k))})};return(()=>{m(this.movingMean,h,this.momentum),m(this.movingVariance,f,this.momentum)})(),d})}getConfig(){let e={axis:this.axis,momentum:this.momentum,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Vt(this.betaInitializer),gammaInitializer:Vt(this.gammaInitializer),movingMeanInitializer:Vt(this.movingMeanInitializer),movingVarianceInitializer:Vt(this.movingVarianceInitializer),betaRegularizer:St(this.betaRegularizer),gammaRegularizer:St(this.gammaRegularizer),betaConstraint:gn(this.betaConstraint),gammaConstraint:gn(this.gammaConstraint)},t=super.getConfig();return Object.assign(e,t),e}};tx.className="BatchNormalization";de.registerClass(tx);var nx=class extends ut{constructor(e){if(e==null&&(e={}),super(e),this.axis=e.axis==null?-1:e.axis,typeof this.axis=="number"){if(!Number.isInteger(this.axis))throw new Error(`Expected axis to be an integer, but received ${this.axis}`)}else if(Array.isArray(this.axis)){for(let t of this.axis)if(!Number.isInteger(t))throw new Error(`Expected axis to be an array of integers, but received ${JSON.stringify(this.axis)}`)}else throw new Error(`Expected axis to be an integer or an array of integers, but received ${JSON.stringify(this.axis)}`);this.epsilon=e.epsilon==null?.001:e.epsilon,this.center=e.center==null?!0:e.center,this.scale=e.scale==null?!0:e.scale,this.betaInitializer=Ot(e.betaInitializer||"zeros"),this.gammaInitializer=Ot(e.gammaInitializer||"ones"),this.betaRegularizer=Mt(e.betaRegularizer),this.gammaRegularizer=Mt(e.gammaRegularizer),this.supportsMasking=!0}build(e){e=xt(e);let t=e.length;typeof this.axis=="number"&&(this.axis=[this.axis]);for(let r=0;r<this.axis.length;++r)this.axis[r]<0&&(this.axis[r]+=t);for(let r of this.axis)if(r<0||r>=t)throw new Error(`Invalid axis: ${r}`);if(this.axis.length!==qa(this.axis).length)throw new Error(`Found duplicate axes in: ${this.axis}`);let n=this.axis.map(r=>e[r]),s=!0;this.scale?this.gamma=this.addWeight("gamma",n,"float32",this.gammaInitializer,this.gammaRegularizer,s):this.gamma=null,this.center?this.beta=this.addWeight("beta",n,"float32",this.betaInitializer,this.betaRegularizer,s):this.beta=null,this.built=!0}call(e,t){let n=Xe(e),s=n.shape,r=s.length;return J(()=>{let{mean:o,variance:i}=fh(n,this.axis,!0),l=Qi(1,r);for(let f of this.axis)l[f]=s[f];let u=f=>f!=null&&f.shape.length!==r?U(f,l):f,c=this.scale?u(this.gamma.read()):null,p=this.center?u(this.beta.read()):null,d=[],h=[];for(let f=0;f<r;++f)this.axis.indexOf(f)!==-1?(d.push(s[f]),h.push(1)):(d.push(1),h.push(s[f]));return o=js(o,d),i=js(i,d),c!=null&&(c=js(c,h)),p!=null&&(p=js(p,h)),Ep(n,o,i,p,c,this.epsilon)})}getConfig(){let e={axis:this.axis,epsilon:this.epsilon,center:this.center,scale:this.scale,betaInitializer:Vt(this.betaInitializer),gammaInitializer:Vt(this.gammaInitializer),betaRegularizer:St(this.betaRegularizer),gammaRegularizer:St(this.gammaRegularizer)},t=super.getConfig();return Object.assign(e,t),e}};nx.className="LayerNormalization";de.registerClass(nx);function fG(e,t,n){return J(()=>{if(e.rank!==4)throw new j(`temporalPadding expects input tensor to be 4-D, but received a ${e.rank}-D tensor.`);if(t==null&&(t=[[1,1],[1,1]]),t.length!==2||t[0].length!==2||t[1].length!==2)throw new j("spatial2dPadding expects `padding` to be an Array of two Arrays, each of which is an Array of two integers.");if(n==null&&(n=_r()),n!=="channelsLast"&&n!=="channelsFirst")throw new j(`Unknown data format: ${n}. Supported data formats are 'channelsLast' and 'channelsFirst.`);let s;return n==="channelsFirst"?s=[[0,0],[0,0],t[0],t[1]]:s=[[0,0],t[0],t[1],[0,0]],Js(e,s)})}var sx=class extends ut{constructor(e){if(e==null&&(e={}),super(e),this.dataFormat=e.dataFormat==null?_r():e.dataFormat,e.padding==null)this.padding=[[1,1],[1,1]];else if(typeof e.padding=="number")this.padding=[[e.padding,e.padding],[e.padding,e.padding]];else{if(e.padding=e.padding,e.padding.length!==2)throw new j(`ZeroPadding2D expects padding to be a length-2 array, but received a length-${e.padding.length} array.`);let t,n;if(typeof e.padding[0]=="number")t=[e.padding[0],e.padding[0]],n=[e.padding[1],e.padding[1]];else{if(e.padding=e.padding,e.padding[0].length!==2)throw new j(`ZeroPadding2D expects height padding to be a length-2 array, but received a length-${e.padding[0].length} array.`);if(t=e.padding[0],e.padding[1].length!==2)throw new j(`ZeroPadding2D expects width padding to be a length-2 array, but received a length-${e.padding[1].length} array.`);n=e.padding[1]}this.padding=[t,n]}this.inputSpec=[new rn({ndim:4})]}computeOutputShape(e){e=xt(e);let t,n;return this.dataFormat==="channelsFirst"?(e[2]!=null&&e[2]>=0?t=e[2]+this.padding[0][0]+this.padding[0][1]:t=null,e[3]!=null&&e[3]>=0?n=e[3]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],e[1],t,n]):(e[1]!=null&&e[1]>=0?t=e[1]+this.padding[0][0]+this.padding[0][1]:t=null,e[2]!=null&&e[2]>=0?n=e[2]+this.padding[1][0]+this.padding[1][1]:n=null,[e[0],t,n,e[3]])}call(e,t){return J(()=>fG(Xe(e),this.padding,this.dataFormat))}getConfig(){let e={padding:this.padding,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}};sx.className="ZeroPadding2D";de.registerClass(sx);function g2(e,t,n,s,r,a){return J(()=>{Yt(r),f8(a),Qs(s),n==null&&(n=[1,1]),s==null&&(s="valid"),r==null&&(r=_r()),a==null&&(a="max"),e=I5(e,r);let o,i=s==="same"?"same":"valid";return a==="max"?o=hh(e,t,n,i):o=ih(e,t,n,i),r==="channelsFirst"&&(o=st(o,[0,3,1,2])),o})}function uk(e,t,n,s,r,a){return J(()=>{Yt(r),f8(a),Qs(s),n==null&&(n=[1,1,1]),s==null&&(s="valid"),r==null&&(r=_r()),a==null&&(a="max"),e=rk(e,r);let o,i=s==="same"?"same":"valid";return a==="max"?o=TA(e,t,n,i):o=eA(e,t,n,i),r==="channelsFirst"&&(o=st(o,[0,4,1,2,3])),o})}var ck=class extends ut{constructor(e){if(e.poolSize==null&&(e.poolSize=2),super(e),typeof e.poolSize=="number")this.poolSize=[e.poolSize];else if(Array.isArray(e.poolSize)&&e.poolSize.length===1&&typeof e.poolSize[0]=="number")this.poolSize=e.poolSize;else throw new j(`poolSize for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.poolSize)}`);if(vn(this.poolSize,"poolSize"),e.strides==null)this.strides=this.poolSize;else if(typeof e.strides=="number")this.strides=[e.strides];else if(Array.isArray(e.strides)&&e.strides.length===1&&typeof e.strides[0]=="number")this.strides=e.strides;else throw new j(`strides for 1D convolutional layer must be a number or an Array of a single number, but received ${JSON.stringify(e.strides)}`);vn(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,Qs(this.padding),this.inputSpec=[new rn({ndim:3})]}computeOutputShape(e){e=xt(e);let t=Er(e[1],this.poolSize[0],this.padding,this.strides[0]);return[e[0],t,e[2]]}call(e,t){return J(()=>{this.invokeCallHook(e,t),e=wh(Xe(e),2);let n=this.poolingFunction(Xe(e),[this.poolSize[0],1],[this.strides[0],1],this.padding,"channelsLast");return rt(n,[2])})}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides},t=super.getConfig();return Object.assign(e,t),e}},rx=class extends ck{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),g2(e,t,n,s,r,"max")}};rx.className="MaxPooling1D";de.registerClass(rx);var ax=class extends ck{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),g2(e,t,n,s,r,"avg")}};ax.className="AveragePooling1D";de.registerClass(ax);var dk=class extends ut{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==2)throw new j(`If the strides property of a 2D pooling layer is an Array, it is expected to have a length of 2, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides];vn(this.poolSize,"poolSize"),vn(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Yt(this.dataFormat),Qs(this.padding),this.inputSpec=[new rn({ndim:4})]}computeOutputShape(e){e=xt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2];return t=Er(t,this.poolSize[0],this.padding,this.strides[0]),n=Er(n,this.poolSize[1],this.padding,this.strides[1]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n]:[e[0],t,n,e[3]]}call(e,t){return J(()=>(this.invokeCallHook(e,t),this.poolingFunction(Xe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},ox=class extends dk{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),g2(e,t,n,s,r,"max")}};ox.className="MaxPooling2D";de.registerClass(ox);var ix=class extends dk{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),g2(e,t,n,s,r,"avg")}};ix.className="AveragePooling2D";de.registerClass(ix);var pk=class extends ut{constructor(e){if(e.poolSize==null&&(e.poolSize=[2,2,2]),super(e),this.poolSize=Array.isArray(e.poolSize)?e.poolSize:[e.poolSize,e.poolSize,e.poolSize],e.strides==null)this.strides=this.poolSize;else if(Array.isArray(e.strides)){if(e.strides.length!==3)throw new j(`If the strides property of a 3D pooling layer is an Array, it is expected to have a length of 3, but received length ${e.strides.length}.`);this.strides=e.strides}else this.strides=[e.strides,e.strides,e.strides];vn(this.poolSize,"poolSize"),vn(this.strides,"strides"),this.padding=e.padding==null?"valid":e.padding,this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Yt(this.dataFormat),Qs(this.padding),this.inputSpec=[new rn({ndim:5})]}computeOutputShape(e){e=xt(e);let t=this.dataFormat==="channelsFirst"?e[2]:e[1],n=this.dataFormat==="channelsFirst"?e[3]:e[2],s=this.dataFormat==="channelsFirst"?e[4]:e[3];return t=Er(t,this.poolSize[0],this.padding,this.strides[0]),n=Er(n,this.poolSize[1],this.padding,this.strides[1]),s=Er(s,this.poolSize[2],this.padding,this.strides[2]),this.dataFormat==="channelsFirst"?[e[0],e[1],t,n,s]:[e[0],t,n,s,e[4]]}call(e,t){return J(()=>(this.invokeCallHook(e,t),this.poolingFunction(Xe(e),this.poolSize,this.strides,this.padding,this.dataFormat)))}getConfig(){let e={poolSize:this.poolSize,padding:this.padding,strides:this.strides,dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},lx=class extends pk{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),uk(e,t,n,s,r,"max")}};lx.className="MaxPooling3D";de.registerClass(lx);var ux=class extends pk{constructor(e){super(e)}poolingFunction(e,t,n,s,r){return Yt(r),Qs(s),uk(e,t,n,s,r,"avg")}};ux.className="AveragePooling3D";de.registerClass(ux);var hk=class extends ut{constructor(e){super(e),this.inputSpec=[new rn({ndim:3})]}computeOutputShape(e){return[e[0],e[2]]}call(e,t){throw new He}},cx=class extends hk{constructor(e){super(e||{})}call(e,t){return J(()=>{let n=Xe(e);return Bt(n,1)})}};cx.className="GlobalAveragePooling1D";de.registerClass(cx);var dx=class extends hk{constructor(e){super(e||{})}call(e,t){return J(()=>{let n=Xe(e);return mn(n,1)})}};dx.className="GlobalMaxPooling1D";de.registerClass(dx);var fk=class extends ut{constructor(e){super(e),this.dataFormat=e.dataFormat==null?"channelsLast":e.dataFormat,Yt(this.dataFormat),this.inputSpec=[new rn({ndim:4})]}computeOutputShape(e){return e=e,this.dataFormat==="channelsLast"?[e[0],e[3]]:[e[0],e[1]]}call(e,t){throw new He}getConfig(){let e={dataFormat:this.dataFormat},t=super.getConfig();return Object.assign(e,t),e}},px=class extends fk{call(e,t){return J(()=>{let n=Xe(e);return this.dataFormat==="channelsLast"?Bt(n,[1,2]):Bt(n,[2,3])})}};px.className="GlobalAveragePooling2D";de.registerClass(px);var hx=class extends fk{call(e,t){return J(()=>{let n=Xe(e);return this.dataFormat==="channelsLast"?mn(n,[1,2]):mn(n,[2,3])})}};hx.className="GlobalMaxPooling2D";de.registerClass(hx);var mk=class extends ut{constructor(e){super(e),this.layer=e.layer}build(e){this.built=!0}get trainable(){return this.layer!=null?this.layer.trainable:!1}set trainable(e){this.layer!=null&&(this.layer.trainable=e)}get trainableWeights(){return this.layer.trainableWeights}get nonTrainableWeights(){return this.layer.nonTrainableWeights}get updates(){return this.layer._updates}get losses(){return this.layer.losses}getWeights(){return this.layer.getWeights()}setWeights(e){this.layer.setWeights(e)}getConfig(){let e={layer:{className:this.layer.getClassName(),config:this.layer.getConfig()}},t=super.getConfig();return Object.assign(e,t),e}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.layer!=null&&this.layer.setFastWeightInitDuringBuild(e)}static fromConfig(e,t,n={}){let s=t.layer,r=Nr(s,n);delete t.layer;let a={layer:r};return Object.assign(a,t),new e(a)}},fx=class extends mk{constructor(e){super(e),this.supportsMasking=!0}build(e){if(e=xt(e),e.length<3)throw new j(`TimeDistributed layer expects an input shape >= 3D, but received input shape ${JSON.stringify(e)}`);this.inputSpec=[{shape:e}];let t=[e[0]].concat(e.slice(2));this.layer.built||(this.layer.build(t),this.layer.built=!0),super.build(e)}computeOutputShape(e){e=xt(e);let t=[e[0]].concat(e.slice(2)),n=this.layer.computeOutputShape(t),s=e[1];return[n[0],s].concat(n.slice(1))}call(e,t){return J(()=>(e=Xe(e),ik((a,o)=>[Xe(this.layer.call(a,t)),[]],e,[],!1,null,null,!1,!0)[1]))}};fx.className="TimeDistributed";de.registerClass(fx);function mG(e){Ql(gV,"BidirectionalMergeMode",e)}var gG="concat",mx=class extends mk{constructor(e){super(e);let t=e.layer.getConfig(),n={};n.className=e.layer.getClassName(),n.config=t,this.forwardLayer=Nr(n),t.goBackwards=t.goBackwards!==!0;let s={};if(s.className=e.layer.getClassName(),s.config=t,this.backwardLayer=Nr(s),this.forwardLayer.name="forward_"+this.forwardLayer.name,this.backwardLayer.name="backward_"+this.backwardLayer.name,this.mergeMode=e.mergeMode===void 0?gG:e.mergeMode,mG(this.mergeMode),e.weights)throw new He("weights support is not implemented for Bidirectional layer yet.");this._stateful=e.layer.stateful,this.returnSequences=e.layer.returnSequences,this.returnState=e.layer.returnState,this.supportsMasking=!0,this._trainable=!0,this.inputSpec=e.layer.inputSpec,this.numConstants=null}get trainable(){return this._trainable}set trainable(e){this._trainable=e,this.forwardLayer!=null&&(this.forwardLayer.trainable=e),this.backwardLayer!=null&&(this.backwardLayer.trainable=e)}getWeights(){return this.forwardLayer.getWeights().concat(this.backwardLayer.getWeights())}setWeights(e){let t=e.length,n=Math.floor(t/2);this.forwardLayer.setWeights(e.slice(0,n)),this.backwardLayer.setWeights(e.slice(n))}computeOutputShape(e){let t=this.forwardLayer.computeOutputShape(e);Array.isArray(t)&&Array.isArray(t[0])||(t=[t]),t=t;let n,s,r;return this.returnState&&(r=t.slice(1)),n=t[0],n=n,this.mergeMode==="concat"?(n[n.length-1]*=2,s=[n]):this.mergeMode==null?s=[n,n.slice()]:s=[n],this.returnState?this.mergeMode==null?s.concat(r).concat(r.slice()):[n].concat(r).concat(r.slice()):ps(s)}apply(e,t){let n=t==null?null:t.initialState,s=t==null?null:t.constants;t==null&&(t={});let r=ok(e,n,s,this.numConstants);if(e=r.inputs,n=r.initialState,s=r.constants,Array.isArray(e)&&(n=e.slice(1),e=e[0]),(n==null||n.length===0)&&s==null)return super.apply(e,t);let a=[],o=[];if(n!=null){let l=n.length;if(l%2>0)throw new j("When passing `initialState` to a Bidrectional RNN, the state should be an Array containing the states of the underlying RNNs.");t.initialState=n,a.push(...n);let u=n.map(c=>new rn({shape:c.shape}));this.forwardLayer.stateSpec=u.slice(0,l/2),this.backwardLayer.stateSpec=u.slice(l/2),o.push(...u)}if(s!=null)throw new He("Support for constants in Bidirectional layers is not implemented yet.");let i=a[0]instanceof Cr;for(let l of a)if(l instanceof Cr!==i)throw new j("The initial state of a Bidirectional layer cannot be specified as a mix of symbolic and non-symbolic tensors");if(i){let l=[e].concat(a),u=this.inputSpec.concat(o),c=this.inputSpec;this.inputSpec=u;let p=super.apply(l,t);return this.inputSpec=c,p}else return super.apply(e,t)}call(e,t){return J(()=>{let n=t.initialState,s,r;if(n==null)s=this.forwardLayer.call(e,t),r=this.backwardLayer.call(e,t);else{let i=n.slice(0,n.length/2),l=n.slice(n.length/2);s=this.forwardLayer.call(e,Object.assign(t,{initialState:i})),r=this.backwardLayer.call(e,Object.assign(t,{initialState:l}))}let a;this.returnState&&(Array.isArray(s)&&(a=s.slice(1).concat(r.slice(1))),s=s[0],r=r[0]),this.returnSequences&&(r=Ks(r,1));let o;return this.mergeMode==="concat"?o=ZA([s,r]):this.mergeMode==="sum"?o=ce(s,r):this.mergeMode==="ave"?o=L(.5,ce(s,r)):this.mergeMode==="mul"?o=L(s,r):this.mergeMode==null&&(o=[s,r]),this.returnState?this.mergeMode==null?o.concat(a):[o].concat(a):o})}resetStates(e){this.forwardLayer.resetStates(),this.backwardLayer.resetStates()}build(e){Gi(this.forwardLayer.name,()=>{this.forwardLayer.build(e)}),Gi(this.backwardLayer.name,()=>{this.backwardLayer.build(e)}),this.built=!0}computeMask(e,t){Array.isArray(t)&&(t=t[0]);let n;if(this.returnSequences?this.mergeMode==null?n=[t,t]:n=t:this.mergeMode==null?n=[null,null]:n=null,this.returnState){let r=this.forwardLayer.states.map(a=>null);return Array.isArray(n)?n.concat(r).concat(r):[n].concat(r).concat(r)}else return n}get trainableWeights(){return this.forwardLayer.trainableWeights.concat(this.backwardLayer.trainableWeights)}get nonTrainableWeights(){return this.forwardLayer.nonTrainableWeights.concat(this.backwardLayer.nonTrainableWeights)}setFastWeightInitDuringBuild(e){super.setFastWeightInitDuringBuild(e),this.forwardLayer!=null&&this.forwardLayer.setFastWeightInitDuringBuild(e),this.backwardLayer!=null&&this.backwardLayer.setFastWeightInitDuringBuild(e)}getConfig(){let e={mergeMode:this.mergeMode},t=super.getConfig();return Object.assign(e,t),e}static fromConfig(e,t){let n=Nr(t.layer);if(delete t.layer,t.numConstants!=null)throw new He("Deserialization of a Bidirectional layer with numConstants present is not supported yet.");let s=t;return s.layer=n,new e(s)}};mx.className="Bidirectional";de.registerClass(mx);function yG(e){return new Zc(e)}function AG(e){return new v5(e)}function xG(e){return new A5(e)}function bG(e){return new x5(e)}function vG(e){return new b5(e)}function wG(e){return new k5(e)}function kG(e){return new w5(e)}function IG(e){return new c2(e)}function SG(e){return new Nh(e)}function CG(e){return new C5(e)}function TG(e){return new Eh(e)}function NG(e){return new T5(e)}function EG(e){return new N5(e)}function RG(e){return new E5(e)}function _G(e){return new R5(e)}function DG(e){return new _5(e)}function $G(e){return new L5(e)}function PG(e){return new M5(e)}function FG(e){return new m2(e)}function OG(e){return new O5(e)}function MG(e){return new z5(e)}function zG(e){return new B5(e)}function LG(e){return new W5(e)}function BG(e){return new V5(e)}function WG(e){return new G5(e)}function VG(e){return new H5(e)}function UG(e){return new q5(e)}function GG(e){return new Z5(e)}function HG(e){return new X5(e)}function jG(e){return new K5(e)}function qG(e){return new j5(e)}function XG(e){return new Y5(e)}function KG(e){return new tx(e)}function ZG(e){return new nx(e)}function YG(e){return new sx(e)}function gx(e){return new ax(e)}function JG(e){return gx(e)}function QG(e){return gx(e)}function yx(e){return new ix(e)}function eH(e){return yx(e)}function tH(e){return yx(e)}function Ax(e){return new ux(e)}function nH(e){return Ax(e)}function sH(e){return Ax(e)}function rH(e){return new cx(e)}function aH(e){return new px(e)}function gk(e){return new dx(e)}function yk(e){return new hx(e)}function Ak(e){return new rx(e)}function xk(e){return new ox(e)}function oH(e){return new lx(e)}function iH(e){return new $5(e)}function lH(e){return new p2(e)}function uH(e){return new P5(e)}function cH(e){return new _h(e)}function dH(e){return new D5(e)}function pH(e){return new d2(e)}function hH(e){return new F5(e)}function fH(e){return new f2(e)}function mH(e){return new Jr(e)}function gH(e){return new h2(e)}function yH(e){return new mx(e)}function AH(e){return new fx(e)}var xH=gk,bH=yk,vH=Ak,wH=xk;function kH(e){return new J5(e)}function IH(e){return new Q5(e)}function SH(e){return new ex(e)}function CH(e){return new U5(e)}var bk={};Ve(bk,{MAPE:()=>MH,MSE:()=>BH,binaryAccuracy:()=>TH,binaryCrossentropy:()=>NH,categoricalAccuracy:()=>RH,categoricalCrossentropy:()=>_H,cosineProximity:()=>PH,mape:()=>zH,meanAbsoluteError:()=>FH,meanAbsolutePercentageError:()=>OH,meanSquaredError:()=>LH,mse:()=>WH,precision:()=>DH,recall:()=>$H,sparseCategoricalAccuracy:()=>EH});function TH(e,t){return d5(e,t)}function NH(e,t){return P8(e,t)}function EH(e,t){return F8(e,t)}function RH(e,t){return p5(e,t)}function _H(e,t){return h5(e,t)}function DH(e,t){return $8(e,t)}function $H(e,t){return bU(e,t)}function PH(e,t){return c5(e,t)}function FH(e,t){return l2(e,t)}function OH(e,t){return Yc(e,t)}function MH(e,t){return Yc(e,t)}function zH(e,t){return Yc(e,t)}function LH(e,t){return eu(e,t)}function BH(e,t){return eu(e,t)}function WH(e,t){return eu(e,t)}var vk={};Ve(vk,{modelFromJSON:()=>ZU});var wk={};Ve(wk,{l1:()=>UH,l1l2:()=>VH,l2:()=>GH});function VH(e){return new Ch(e)}function UH(e){return rG(e)}function GH(e){return aG(e)}var kk=class extends tc{constructor(){super(...arguments),this.model=null}setModel(e){if(!(e instanceof pa))throw new Error("model must be a LayersModel, not some other Container");this.model=e}};function Gf(e,t){return e<t}function Yv(e,t){return e>t}var Ik=class extends kk{constructor(e){if(super(),e==null&&(e={}),e.restoreBestWeights)throw new He("restoreBestWeights = True is not implemented in EarlyStopping yet.");this.monitor=e.monitor||"val_loss",this.minDelta=Math.abs(e.minDelta||0),this.patience=e.patience||0,this.verbose=e.verbose||0,this.mode=e.mode||"auto",this.baseline=e.baseline,["auto","min","max"].indexOf(this.mode)===-1&&(console.warn(`EarlyStopping mode '${this.mode}' is invalid. Falling back to mode 'auto'.`),this.mode="auto"),this.mode==="min"?this.monitorFunc=Gf:this.mode==="max"?this.monitorFunc=Yv:this.monitor.indexOf("acc")!==-1?this.monitorFunc=Yv:this.monitorFunc=Gf,this.monitorFunc===Gf&&(this.minDelta*=-1)}async onTrainBegin(e){this.wait=0,this.stoppedEpoch=0,this.baseline!=null?this.best=this.baseline:this.best=this.monitorFunc===Gf?1/0:-1/0}async onEpochEnd(e,t){await Wa(t);let n=this.getMonitorValue(t);n!=null&&(this.monitorFunc(n-this.minDelta,this.best)?(this.best=n,this.wait=0):(this.wait++,this.wait>=this.patience&&(this.stoppedEpoch=e,this.model.stopTraining=!0)))}async onTrainEnd(e){this.stoppedEpoch>0&&this.verbose&&console.log(`Epoch ${this.stoppedEpoch}: early stopping.`)}getMonitorValue(e){e==null&&(e={});let t=e[this.monitor];return t==null&&console.warn(`Metric for EarlyStopping ${this.monitor} is not available. Available metrics are: ${Object.keys(e)}`),t}};function HH(e){return new Ik(e)}var jH={earlyStopping:HH},qH=X();qH.registerFlag("KEEP_INTERMEDIATE_TENSORS",()=>!1,e=>{e&&console.warn("Keep intermediate tensors is ON. This will print the values of all intermediate tensors during model inference. Not all models support this mode. For details, check e2e/benchmarks/ model_config.js. This significantly impacts performance.")});var sr;(function(e){e[e.DT_INVALID=0]="DT_INVALID",e[e.DT_FLOAT=1]="DT_FLOAT",e[e.DT_DOUBLE=2]="DT_DOUBLE",e[e.DT_INT32=3]="DT_INT32",e[e.DT_UINT8=4]="DT_UINT8",e[e.DT_INT16=5]="DT_INT16",e[e.DT_INT8=6]="DT_INT8",e[e.DT_STRING=7]="DT_STRING",e[e.DT_COMPLEX64=8]="DT_COMPLEX64",e[e.DT_INT64=9]="DT_INT64",e[e.DT_BOOL=10]="DT_BOOL",e[e.DT_QINT8=11]="DT_QINT8",e[e.DT_QUINT8=12]="DT_QUINT8",e[e.DT_QINT32=13]="DT_QINT32",e[e.DT_BFLOAT16=14]="DT_BFLOAT16",e[e.DT_QINT16=15]="DT_QINT16",e[e.DT_QUINT16=16]="DT_QUINT16",e[e.DT_UINT16=17]="DT_UINT16",e[e.DT_COMPLEX128=18]="DT_COMPLEX128",e[e.DT_HALF=19]="DT_HALF",e[e.DT_RESOURCE=20]="DT_RESOURCE",e[e.DT_VARIANT=21]="DT_VARIANT",e[e.DT_UINT32=22]="DT_UINT32",e[e.DT_UINT64=23]="DT_UINT64",e[e.DT_FLOAT_REF=101]="DT_FLOAT_REF",e[e.DT_DOUBLE_REF=102]="DT_DOUBLE_REF",e[e.DT_INT32_REF=103]="DT_INT32_REF",e[e.DT_UINT8_REF=104]="DT_UINT8_REF",e[e.DT_INT16_REF=105]="DT_INT16_REF",e[e.DT_INT8_REF=106]="DT_INT8_REF",e[e.DT_STRING_REF=107]="DT_STRING_REF",e[e.DT_COMPLEX64_REF=108]="DT_COMPLEX64_REF",e[e.DT_INT64_REF=109]="DT_INT64_REF",e[e.DT_BOOL_REF=110]="DT_BOOL_REF",e[e.DT_QINT8_REF=111]="DT_QINT8_REF",e[e.DT_QUINT8_REF=112]="DT_QUINT8_REF",e[e.DT_QINT32_REF=113]="DT_QINT32_REF",e[e.DT_BFLOAT16_REF=114]="DT_BFLOAT16_REF",e[e.DT_QINT16_REF=115]="DT_QINT16_REF",e[e.DT_QUINT16_REF=116]="DT_QUINT16_REF",e[e.DT_UINT16_REF=117]="DT_UINT16_REF",e[e.DT_COMPLEX128_REF=118]="DT_COMPLEX128_REF",e[e.DT_HALF_REF=119]="DT_HALF_REF",e[e.DT_RESOURCE_REF=120]="DT_RESOURCE_REF",e[e.DT_VARIANT_REF=121]="DT_VARIANT_REF",e[e.DT_UINT32_REF=122]="DT_UINT32_REF",e[e.DT_UINT64_REF=123]="DT_UINT64_REF"})(sr||(sr={}));var Jv;(function(e){let t;(function(n){n[n.LEGACY=0]="LEGACY",n[n.V1=1]="V1",n[n.V2=2]="V2"})(t=e.CheckpointFormatVersion||(e.CheckpointFormatVersion={}))})(Jv||(Jv={}));var xx={};function XH(e,t){let n={tfOpName:e,category:"custom",inputs:[],attrs:[],customExecutor:t};xx[e]=n}function Sk(e){return xx[e]}function KH(e){delete xx[e]}function I(e,t,n,s,r){let a=t.inputParams[e];if(a&&a.inputIndexStart!==void 0){let i=a.inputIndexStart,l=a.inputIndexEnd===0?void 0:a.inputIndexEnd===void 0?i+1:a.inputIndexEnd;if(a.type==="tensor")return Jn(t.inputNames[a.inputIndexStart],n,s,r);if(a.type==="tensors")return t.inputNames.slice(i,l).map(d=>Jn(d,n,s,r));let u=Jn(t.inputNames.slice(i)[0],n,s,r),c=u.dataSync();return a.type==="number"?c[0]:v.toNestedArray(u.shape,c)}let o=t.attrParams[e];return o&&o.value}function Jn(e,t,n,s){let[r,a]=Ss(e);if(s!=null){let i=s.getHashTableHandleByName(r);if(i!=null)return i}let o=n.currentContextIds.find(i=>!!t[Tm(r,i)]);return o!==void 0?t[Tm(r,o)][a]:void 0}function ZH(e,t,n){return t[Tm(e,n.currentContextId)]}function Ur(e,t){let[n,s,r]=Ss(e);return[Tm(n,t&&t.currentContextId),s,r]}function Tm(e,t){return t?`${e}-${t}`:e}function Ss(e){let t=e.split(":");if(t.length===1)return[e,0,void 0];let n=t[0],s=t.length===3?t[1]:void 0,r=Number(t[t.length-1]);return[n,r,s]}function em(e,t,n){let s=I("pad",e,t,n);if(s==="explicit"){s=I("explicitPaddings",e,t,n);let r=[[0,0],[0,0],[0,0],[0,0]];for(let a=0;a<4;a++)r[a][0]=s[a*2],r[a][1]=s[a*2+1];return r}return s}function ua(e){return e.kept?e:Fn(e)}var Ck={};Ve(Ck,{json:()=>YH});var YH=[{tfOpName:"Add",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"AddV2",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"AddN",category:"arithmetic",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}]},{tfOpName:"BiasAdd",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"Sub",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"RealDiv",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Div",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"DivNoNan",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"FloorDiv",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Mul",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Maximum",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Minimum",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Pow",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"SquaredDifference",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Mod",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"FloorMod",category:"arithmetic",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],Tk={};Ve(Tk,{json:()=>JH});var JH=[{tfOpName:"Abs",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Acos",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Asin",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Atan",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Atan2",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"y",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Ceil",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ClipByValue",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"clipValueMin",type:"number"},{start:2,name:"clipValueMax",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Complex",category:"basic_math",inputs:[{start:0,name:"real",type:"tensor"},{start:1,name:"imag",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ComplexAbs",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Cos",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Cosh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Elu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Exp",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Floor",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Log",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Imag",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"Tout",name:"outputType",type:"dtype",notSupported:!0}]},{tfOpName:"Neg",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Real",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"Tout",name:"outputType",type:"dtype",notSupported:!0}]},{tfOpName:"Prelu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"alpha",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Relu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Relu6",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Selu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sigmoid",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sin",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sinh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sqrt",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Rsqrt",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Square",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Tan",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Tanh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Sign",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Round",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Expm1",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Log1p",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Reciprocal",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Softplus",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Asinh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Acosh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Atanh",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Erf",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Prod",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axes",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool",notSupported:!0},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LeakyRelu",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"alpha",name:"alpha",type:"number",defaultValue:.2},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"IsNan",category:"basic_math",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],Nk={};Ve(Nk,{json:()=>QH});var QH=[{tfOpName:"EmptyTensorList",category:"control",inputs:[{start:0,name:"elementShape",type:"shape"},{start:1,name:"maxNumElements",type:"number"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"LoopCond",category:"control",inputs:[{start:0,name:"pred",type:"tensor"}]},{tfOpName:"Switch",category:"control",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"pred",type:"tensor"}]},{tfOpName:"Merge",category:"control",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}]},{tfOpName:"Enter",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"frame_name",name:"frameName",type:"string"},{tfName:"is_constant",name:"isConstant",type:"bool"}]},{tfOpName:"Exit",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"NextIteration",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"TensorArrayV3",category:"control",inputs:[{start:0,name:"size",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"element_shape",name:"elementShape",type:"shape"},{tfName:"dynamic_size",name:"dynamicSize",type:"bool"},{tfName:"clear_after_read",name:"clearAfterRead",type:"bool"},{tfName:"identical_element_shapes",name:"identicalElementShapes",type:"bool"},{tfName:"tensor_array_name",name:"name",type:"string"}]},{tfOpName:"TensorArrayWriteV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"tensor",type:"tensor"},{start:3,name:"flowIn",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"TensorArrayReadV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"flowIn",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"TensorArrayGatherV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"flowIn",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"element_shape",name:"elementShape",type:"shape"}]},{tfOpName:"TensorArrayScatterV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"tensor",type:"tensor"},{start:3,name:"flowIn",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"TensorArrayConcatV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"flowIn",type:"number"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"element_shape_except0",name:"elementShapeExcept0",type:"shape",notSupported:!0}]},{tfOpName:"TensorArraySplitV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"tensor",type:"tensor"},{start:2,name:"lengths",type:"number[]"},{start:3,name:"flowIn",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"TensorArraySizeV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"},{start:1,name:"flowIn",type:"number"}]},{tfOpName:"TensorArrayCloseV3",category:"control",inputs:[{start:0,name:"tensorArrayId",type:"tensor"}]},{tfOpName:"StatelessIf",category:"control",inputs:[{start:0,name:"cond",type:"tensor"},{start:1,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"then_branch",name:"thenBranch",type:"func"},{tfName:"else_branch",name:"elseBranch",type:"func"}]},{tfOpName:"If",category:"control",inputs:[{start:0,name:"cond",type:"tensor"},{start:1,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"then_branch",name:"thenBranch",type:"func"},{tfName:"else_branch",name:"elseBranch",type:"func"}]},{tfOpName:"StatelessWhile",category:"control",inputs:[{start:0,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"cond",name:"cond",type:"func"},{tfName:"body",name:"body",type:"func"}]},{tfOpName:"While",category:"control",inputs:[{start:0,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"cond",name:"cond",type:"func"},{tfName:"body",name:"body",type:"func"}]},{tfOpName:"TensorListScatter",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListScatterV2",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"elementShape",type:"shape"},{start:3,name:"numElements",type:"number"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListGather",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"indices",type:"number[]"},{start:2,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListGetItem",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListSetItem",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"index",type:"number"},{start:2,name:"tensor",type:"tensor"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListReserve",category:"control",inputs:[{start:0,name:"elementShape",type:"shape"},{start:1,name:"numElements",type:"number"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListFromTensor",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListStack",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"},{tfName:"num_elements",name:"numElements",type:"dtype"}]},{tfOpName:"TensorListSplit",category:"control",inputs:[{start:0,name:"tensor",type:"tensor"},{start:1,name:"elementShape",type:"shape"},{start:2,name:"lengths",type:"number[]"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListConcat",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"}],attrs:[{tfName:"element_shape",name:"elementShape",type:"shape"},{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListConcatV2",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"}],attrs:[{tfName:"element_shape",name:"elementShape",type:"shape"},{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListPopBack",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"elementShape",type:"shape"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListPushBack",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"tensor",type:"tensor"}],attrs:[{tfName:"element_dtype",name:"elementDType",type:"dtype"}]},{tfOpName:"TensorListLength",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"}]},{tfOpName:"TensorListResize",category:"control",inputs:[{start:0,name:"tensorListId",type:"tensor"},{start:1,name:"size",type:"number"}]}],Ek={};Ve(Ek,{json:()=>ej});var ej=[{tfOpName:"AvgPool",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MaxPool",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[],notSupported:!0},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MaxPoolWithArgmax",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"include_batch_in_index",name:"includeBatchInIndex",type:"bool"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"AvgPool3D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MaxPool3D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"ksize",name:"kernelSize",type:"number[]"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Conv1D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"stride",name:"stride",type:"number"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NWC"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"dilation",name:"dilation",type:"number",defaultValue:1}]},{tfOpName:"Conv2D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"useCudnnOnGpu",name:"useCudnnOnGpu",type:"bool"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"_FusedConv2D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"},{start:2,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"num_args",name:"numArgs",type:"number"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"use_cudnn_on_gpu",name:"useCudnnOnGpu",type:"bool",defaultValue:!0},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"dilations",name:"dilations",type:"number[]",defaultValue:[1,1,1,1]},{tfName:"fused_ops",name:"fusedOps",type:"string[]",defaultValue:[]},{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:1e-4},{tfName:"leakyrelu_alpha",name:"leakyreluAlpha",type:"number",defaultValue:.2}]},{tfOpName:"Conv2DBackpropInput",category:"convolution",inputs:[{start:2,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"},{start:0,name:"outputShape",type:"number[]"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]",notSupported:!0}]},{tfOpName:"DepthwiseConv2d",category:"convolution",inputs:[{start:0,name:"input",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"DepthwiseConv2dNative",category:"convolution",inputs:[{start:0,name:"input",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"FusedDepthwiseConv2dNative",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"},{start:2,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"num_args",name:"numArgs",type:"number"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"dilations",name:"dilations",type:"number[]",defaultValue:[1,1,1,1]},{tfName:"fused_ops",name:"fusedOps",type:"string[]",defaultValue:[]},{tfName:"explicit_paddings",name:"explicitPaddings",type:"number[]",defaultValue:[]}]},{tfOpName:"Conv3D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"padding",name:"pad",type:"string"},{tfName:"data_format",name:"dataFormat",type:"string",defaultValue:"NHWC"},{tfName:"dilations",name:"dilations",type:"number[]"}]},{tfOpName:"Dilation2D",category:"convolution",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"filter",type:"tensor"}],attrs:[{tfName:"strides",name:"strides",type:"number[]"},{tfName:"rates",name:"dilations",type:"number[]"},{tfName:"padding",name:"pad",type:"string"}]}],Rk={};Ve(Rk,{json:()=>tj});var tj=[{tfOpName:"Fill",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"},{start:1,name:"value",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"LinSpace",category:"creation",inputs:[{start:0,name:"start",type:"number"},{start:1,name:"stop",type:"number"},{start:2,name:"num",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"OneHot",category:"creation",inputs:[{start:0,name:"indices",type:"tensor"},{start:1,name:"depth",type:"number"},{start:2,name:"onValue",type:"number",defaultValue:1},{start:3,name:"offValue",type:"number",defaultValue:0}],attrs:[{tfName:"axis",name:"axis",type:"number",notSupported:!0},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Ones",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"OnesLike",category:"creation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"dtype",name:"dtype",type:"dtype"}]},{tfOpName:"RandomStandardNormal",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"seed",name:"seed",type:"number",defaultValue:0},{tfName:"seed2",name:"seed2",type:"number",defaultValue:0,notSupported:!0},{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"T",name:"T",type:"number",notSupported:!0}]},{tfOpName:"RandomUniform",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"minval",name:"minval",type:"number",defaultValue:0},{tfName:"maxval",name:"maxval",type:"number",defaultValue:1},{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"seed",name:"seed",type:"number",defaultValue:0},{tfName:"seed2",name:"seed2",type:"number",defaultValue:0,notSupported:!0},{tfName:"T",name:"T",type:"number",notSupported:!0}]},{tfOpName:"Range",category:"creation",inputs:[{start:0,name:"start",type:"number"},{start:1,name:"stop",type:"number"},{start:2,name:"step",type:"number",defaultValue:0}],attrs:[{tfName:"Tidx",name:"dtype",type:"dtype"}]},{tfOpName:"TruncatedNormal",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"means",name:"mean",type:"number",defaultValue:0},{tfName:"stddev",name:"stdDev",type:"number",defaultValue:1},{tfName:"seed",name:"seed",type:"number"},{tfName:"seed2",name:"seed2",type:"number",defaultValue:0,notSupported:!0},{tfName:"dtype",name:"dtype",type:"dtype"},{tfName:"T",name:"T",type:"number",notSupported:!0}]},{tfOpName:"Zeros",category:"creation",inputs:[{start:0,name:"shape",type:"number[]"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"ZerosLike",category:"creation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype"}]},{tfOpName:"Multinomial",category:"creation",inputs:[{start:0,name:"logits",type:"tensor"},{start:1,name:"numSamples",type:"number"}],attrs:[{tfName:"seed",name:"seed",type:"number"},{tfName:"seed2",name:"seed2",type:"number"},{tfName:"T",name:"dtype",type:"dtype"},{tfName:"output_dtype",name:"output_dtype",type:"dtype"}]}],_k={};Ve(_k,{json:()=>nj});var nj=[{tfOpName:"NonMaxSuppressionV2",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"}]},{tfOpName:"NonMaxSuppressionV3",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"},{start:4,name:"scoreThreshold",type:"number"}]},{tfOpName:"NonMaxSuppressionV4",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"},{start:4,name:"scoreThreshold",type:"number"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0},{tfName:"T_threshold",name:"threshold",type:"dtype",notSupported:!0},{tfName:"pad_to_max_output_size",name:"padToMaxOutputSize",type:"bool"}]},{tfOpName:"NonMaxSuppressionV5",category:"dynamic",inputs:[{start:0,name:"boxes",type:"tensor"},{start:1,name:"scores",type:"tensor"},{start:2,name:"maxOutputSize",type:"number"},{start:3,name:"iouThreshold",type:"number"},{start:4,name:"scoreThreshold",type:"number"},{start:5,name:"softNmsSigma",type:"number"}]},{tfOpName:"Where",category:"dynamic",inputs:[{start:0,name:"condition",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ListDiff",category:"dynamic",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"y",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],Dk={};Ve(Dk,{json:()=>sj});var sj=[{tfOpName:"LowerBound",category:"evaluation",inputs:[{start:0,name:"sortedSequence",type:"tensor"},{start:1,name:"values",type:"tensor"}]},{tfOpName:"TopKV2",category:"evaluation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"k",type:"number"}],attrs:[{tfName:"sorted",name:"sorted",type:"bool"}]},{tfOpName:"UpperBound",category:"evaluation",inputs:[{start:0,name:"sortedSequence",type:"tensor"},{start:1,name:"values",type:"tensor"}]},{tfOpName:"Unique",category:"evaluation",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"UniqueV2",category:"evaluation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]}],$k={};Ve($k,{json:()=>rj});var rj=[{tfOpName:"PlaceholderWithDefault",category:"graph",inputs:[{start:0,name:"default",type:"tensor"}],attrs:[{tfName:"shape",name:"shape",type:"shape"},{tfName:"dtype",name:"dtype",type:"dtype"}]},{tfOpName:"Placeholder",category:"graph",attrs:[{tfName:"shape",name:"shape",type:"shape"},{tfName:"dtype",name:"dtype",type:"dtype"}]},{tfOpName:"Const",category:"graph"},{tfOpName:"Identity",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"IdentityN",category:"graph",inputs:[{start:0,end:0,name:"x",type:"tensors"}]},{tfOpName:"Snapshot",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"Rank",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"Size",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"Shape",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"ShapeN",category:"graph",inputs:[{start:0,end:0,name:"x",type:"tensors"}]},{tfOpName:"Print",category:"graph",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"data",type:"tensors"}],attrs:[{tfName:"message",name:"message",type:"string"},{tfName:"first_n",name:"firstN",type:"number",notSupported:!0},{tfName:"summarize",name:"summarize",type:"number",defaultValue:3}]},{tfOpName:"NoOp",category:"graph",inputs:[]},{tfOpName:"StopGradient",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"FakeQuantWithMinMaxVars",category:"graph",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"min",name:"min",type:"number"},{tfName:"max",name:"max",type:"number"}]}],Pk={};Ve(Pk,{json:()=>aj});var aj=[{tfOpName:"HashTable",category:"hash_table",inputs:[],attrs:[{tfName:"shared_name",name:"sharedName",type:"string"},{tfName:"use_node_name_sharing",name:"useNodeNameSharing",type:"bool"},{tfName:"key_dtype",name:"keyDType",type:"dtype"},{tfName:"value_dtype",name:"valueDType",type:"dtype"}]},{tfOpName:"HashTableV2",category:"hash_table",inputs:[],attrs:[{tfName:"shared_name",name:"sharedName",type:"string"},{tfName:"use_node_name_sharing",name:"useNodeNameSharing",type:"bool"},{tfName:"key_dtype",name:"keyDType",type:"dtype"},{tfName:"value_dtype",name:"valueDType",type:"dtype"}]},{tfOpName:"LookupTableImport",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"values",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableImportV2",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"values",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableFind",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableFindV2",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"},{start:1,name:"keys",type:"tensor"},{start:2,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"Tin",name:"tIn",type:"dtype",notSupported:!0},{tfName:"Tout",name:"tOut",type:"dtype",notSupported:!0}]},{tfOpName:"LookupTableSize",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"}]},{tfOpName:"LookupTableSizeV2",category:"hash_table",inputs:[{start:0,name:"tableHandle",type:"tensor"}]}],Fk={};Ve(Fk,{json:()=>oj});var oj=[{tfOpName:"ResizeBilinear",category:"image",inputs:[{start:0,name:"images",type:"tensor"},{start:1,name:"size",type:"number[]"}],attrs:[{tfName:"align_corners",name:"alignCorners",type:"bool"},{tfName:"half_pixel_centers",name:"halfPixelCenters",type:"bool"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"ResizeNearestNeighbor",category:"image",inputs:[{start:0,name:"images",type:"tensor"},{start:1,name:"size",type:"number[]"}],attrs:[{tfName:"align_corners",name:"alignCorners",type:"bool"},{tfName:"half_pixel_centers",name:"halfPixelCenters",type:"bool"},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"CropAndResize",category:"image",inputs:[{start:0,name:"image",type:"tensor"},{start:1,name:"boxes",type:"tensor"},{start:2,name:"boxInd",type:"tensor"},{start:3,name:"cropSize",type:"number[]"}],attrs:[{tfName:"method",name:"method",type:"string"},{tfName:"extrapolation_value",name:"extrapolationValue",type:"number"}]},{tfOpName:"ImageProjectiveTransformV3",category:"image",inputs:[{start:0,name:"images",type:"tensor"},{start:1,name:"transforms",type:"tensor"},{start:2,name:"outputShape",type:"number[]"},{start:3,name:"fillValue",type:"number"}],attrs:[{tfName:"interpolation",name:"interpolation",type:"string"},{tfName:"fill_mode",name:"fillMode",type:"string"}]}],Ok={};Ve(Ok,{json:()=>ij});var ij=[{tfOpName:"Equal",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"NotEqual",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Greater",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"GreaterEqual",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Less",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LessEqual",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalAnd",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalNot",category:"logical",inputs:[{start:0,name:"a",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"LogicalOr",category:"logical",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Select",category:"logical",inputs:[{start:0,name:"condition",type:"tensor"},{start:1,name:"a",type:"tensor"},{start:2,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"SelectV2",category:"logical",inputs:[{start:0,name:"condition",type:"tensor"},{start:1,name:"a",type:"tensor"},{start:2,name:"b",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]}],Mk={};Ve(Mk,{json:()=>lj});var lj=[{tfOpName:"_FusedMatMul",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"},{start:2,end:0,name:"args",type:"tensors"}],attrs:[{tfName:"num_args",name:"numArgs",type:"number"},{tfName:"fused_ops",name:"fusedOps",type:"string[]",defaultValue:[]},{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:1e-4},{tfName:"transpose_a",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"transpose_b",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"leakyrelu_alpha",name:"leakyreluAlpha",type:"number",defaultValue:.2},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"MatMul",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"transpose_a",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"transpose_b",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"BatchMatMul",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"adj_x",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"adj_y",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"BatchMatMulV2",category:"matrices",inputs:[{start:0,name:"a",type:"tensor"},{start:1,name:"b",type:"tensor"}],attrs:[{tfName:"adj_x",name:"transposeA",type:"bool",defaultValue:!1},{tfName:"adj_y",name:"transposeB",type:"bool",defaultValue:!1},{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Transpose",category:"matrices",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"perm",type:"number[]"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"Einsum",category:"matrices",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}],attrs:[{tfName:"equation",name:"equation",type:"string"},{tfName:"N",name:"n",type:"number",defaultValue:2},{tfName:"T",name:"dtype",type:"dtype"}]}],zk={};Ve(zk,{json:()=>uj});var uj=[{tfOpName:"EuclideanNorm",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool",defaultValue:!1}]},{tfOpName:"FusedBatchNorm",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"scale",type:"tensor"},{start:2,name:"offset",type:"tensor"},{start:3,name:"mean",type:"tensor"},{start:4,name:"variance",type:"tensor"}],attrs:[{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:.001},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"FusedBatchNormV2",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"scale",type:"tensor"},{start:2,name:"offset",type:"tensor"},{start:3,name:"mean",type:"tensor"},{start:4,name:"variance",type:"tensor"}],attrs:[{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:.001},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"FusedBatchNormV3",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"scale",type:"tensor"},{start:2,name:"offset",type:"tensor"},{start:3,name:"mean",type:"tensor"},{start:4,name:"variance",type:"tensor"}],attrs:[{tfName:"epsilon",name:"epsilon",type:"number",defaultValue:.001},{tfName:"data_format",name:"dataFormat",type:"string",notSupported:!0}]},{tfOpName:"LRN",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"depth_radius",name:"radius",type:"number",defaultValue:5},{tfName:"bias",name:"bias",type:"number",defaultValue:1},{tfName:"alpha",name:"alpha",type:"number",defaultValue:1},{tfName:"beta",name:"beta",type:"number",defaultValue:.5}]},{tfOpName:"Softmax",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"LogSoftmax",category:"normalization",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"SparseToDense",category:"normalization",inputs:[{start:0,name:"sparseIndices",type:"tensor"},{start:1,name:"outputShape",type:"number[]"},{start:2,name:"sparseValues",type:"tensor"},{start:3,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"validate_indices",name:"validateIndices",type:"bool",defaultValue:!0,notSupported:!0}]}],Lk={};Ve(Lk,{json:()=>cj});var cj=[{tfOpName:"Bincount",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"size",type:"number"},{start:2,name:"weights",type:"tensor"}]},{tfOpName:"DenseBincount",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"size",type:"number"},{start:2,name:"weights",type:"tensor"}],attrs:[{tfName:"binary_output",name:"binaryOutput",type:"bool"}]},{tfOpName:"Max",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Mean",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Min",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Sum",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"All",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Any",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"ArgMax",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]},{tfOpName:"ArgMin",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]},{tfOpName:"Prod",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}],attrs:[{tfName:"keep_dims",name:"keepDims",type:"bool"}]},{tfOpName:"Cumprod",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}],attrs:[{tfName:"exclusive",name:"exclusive",type:"bool"},{tfName:"reverse",name:"reverse",type:"bool"}]},{tfOpName:"Cumsum",category:"reduction",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}],attrs:[{tfName:"exclusive",name:"exclusive",type:"bool"},{tfName:"reverse",name:"reverse",type:"bool"}]}],Bk={};Ve(Bk,{json:()=>dj});var dj=[{tfOpName:"ConcatV2",category:"slice_join",inputs:[{start:0,end:-1,name:"tensors",type:"tensors"},{start:-1,name:"axis",type:"number"}],attrs:[{tfName:"N",name:"n",type:"number",defaultValue:2}]},{tfOpName:"Concat",category:"slice_join",inputs:[{start:1,end:0,name:"tensors",type:"tensors"},{start:0,name:"axis",type:"number"}],attrs:[{tfName:"N",name:"n",type:"number",defaultValue:2}]},{tfOpName:"GatherV2",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"indices",type:"tensor"},{start:2,name:"axis",type:"number",defaultValue:0}],attrs:[{tfName:"batch_dims",name:"batchDims",type:"number",defaultValue:0}]},{tfOpName:"Gather",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"indices",type:"tensor"}],attrs:[{tfName:"validate_indices",name:"validateIndices",type:"bool",notSupported:!0}]},{tfOpName:"Reverse",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"dims",type:"bool[]"}]},{tfOpName:"ReverseV2",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number[]"}]},{tfOpName:"Slice",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"begin",type:"number[]"},{start:2,name:"size",type:"number[]"}]},{tfOpName:"StridedSlice",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"begin",type:"number[]"},{start:2,name:"end",type:"number[]"},{start:3,name:"strides",type:"number[]"}],attrs:[{tfName:"begin_mask",name:"beginMask",type:"number",defaultValue:0},{tfName:"end_mask",name:"endMask",type:"number",defaultValue:0},{tfName:"new_axis_mask",name:"newAxisMask",type:"number",defaultValue:0},{tfName:"ellipsis_mask",name:"ellipsisMask",type:"number",defaultValue:0},{tfName:"shrink_axis_mask",name:"shrinkAxisMask",type:"number",defaultValue:0}]},{tfOpName:"Pack",category:"slice_join",inputs:[{start:0,end:0,name:"tensors",type:"tensors"}],attrs:[{tfName:"axis",name:"axis",type:"number",defaultValue:0}]},{tfOpName:"Unpack",category:"slice_join",inputs:[{start:0,name:"tensor",type:"tensor"}],attrs:[{tfName:"axis",name:"axis",type:"number",defaultValue:0},{tfName:"num",name:"num",type:"number",defaultValue:0,notSupported:!0}]},{tfOpName:"Tile",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"reps",type:"number[]"}]},{tfOpName:"Split",category:"slice_join",inputs:[{start:0,name:"axis",type:"number",defaultValue:0},{start:1,name:"x",type:"tensor"}],attrs:[{tfName:"num_split",name:"numOrSizeSplits",type:"number",defaultValue:1}]},{tfOpName:"SplitV",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"numOrSizeSplits",type:"number[]"},{start:2,name:"axis",type:"number",defaultValue:0}]},{tfOpName:"ScatterNd",category:"slice_join",inputs:[{start:0,name:"indices",type:"tensor"},{start:1,name:"values",type:"tensor"},{start:2,name:"shape",type:"number[]"}]},{tfOpName:"GatherNd",category:"slice_join",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"indices",type:"tensor"}]},{tfOpName:"SparseToDense",category:"slice_join",inputs:[{start:0,name:"sparseIndices",type:"tensor"},{start:1,name:"outputShape",type:"number[]"},{start:2,name:"sparseValues",type:"tensor"},{start:3,name:"defaultValue",type:"tensor"}],attrs:[{tfName:"validate_indices",name:"validateIndices",type:"bool",defaultValue:!1,notSupported:!0}]}],Wk={};Ve(Wk,{json:()=>pj});var pj=[{tfOpName:"SparseFillEmptyRows",category:"sparse",inputs:[{start:0,name:"indices",type:"tensor"},{start:1,name:"values",type:"tensor"},{start:2,name:"denseShape",type:"tensor"},{start:3,name:"defaultValue",type:"tensor"}]},{tfOpName:"SparseReshape",category:"sparse",inputs:[{start:0,name:"inputIndices",type:"tensor"},{start:1,name:"inputShape",type:"tensor"},{start:2,name:"newShape",type:"tensor"}],attrs:[{tfName:"T",name:"dtype",type:"dtype",notSupported:!0}]},{tfOpName:"SparseSegmentMean",category:"sparse",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"indices",type:"tensor"},{start:2,name:"segmentIds",type:"tensor"}]},{tfOpName:"SparseSegmentSum",category:"sparse",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"indices",type:"tensor"},{start:2,name:"segmentIds",type:"tensor"}]}],Vk={};Ve(Vk,{json:()=>hj});var hj=[{tfOpName:"FFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"IFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"}]},{tfOpName:"RFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"fft_length",type:"number",notSupported:!0}]},{tfOpName:"IRFFT",category:"spectral",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"fft_length",type:"number",notSupported:!0}]}],Uk={};Ve(Uk,{json:()=>fj});var fj=[{tfOpName:"StringNGrams",category:"string",inputs:[{start:0,name:"data",type:"tensor"},{start:1,name:"dataSplits",type:"tensor"}],attrs:[{tfName:"separator",name:"separator",type:"string"},{tfName:"ngram_widths",name:"nGramWidths",type:"number[]"},{tfName:"left_pad",name:"leftPad",type:"string"},{tfName:"right_pad",name:"rightPad",type:"string"},{tfName:"pad_width",name:"padWidth",type:"number"},{tfName:"preserve_short_sequences",name:"preserveShortSequences",type:"bool"}],outputs:["ngrams","ngrams_splits"]},{tfOpName:"StringSplit",category:"string",inputs:[{start:0,name:"input",type:"tensor"},{start:1,name:"delimiter",type:"tensor"}],attrs:[{tfName:"skip_empty",name:"skipEmpty",type:"bool"}],outputs:["indices","values","shape"]},{tfOpName:"StringToHashBucketFast",category:"string",inputs:[{start:0,name:"input",type:"tensor"}],attrs:[{tfName:"num_buckets",name:"numBuckets",type:"number"}]}],Gk={};Ve(Gk,{json:()=>mj});var mj=[{tfOpName:"Cast",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"SrcT",name:"sdtype",type:"dtype",notSupported:!0},{tfName:"DstT",name:"dtype",type:"dtype"}]},{tfOpName:"ExpandDims",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"axis",type:"number"}]},{tfOpName:"MirrorPad",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"}],attrs:[{tfName:"mode",name:"mode",type:"string"}]},{tfOpName:"Pad",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"}],attrs:[{tfName:"constant_value",name:"constantValue",type:"number",defaultValue:0}]},{tfOpName:"PadV2",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"padding",type:"number[]"},{start:2,name:"constantValue",type:"number",defaultValue:0}]},{tfOpName:"Reshape",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"shape",type:"number[]"}]},{tfOpName:"Squeeze",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"axis",tfDeprecatedName:"squeeze_dims",name:"axis",type:"number[]"}]},{tfOpName:"SpaceToBatchND",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"blockShape",type:"number[]"},{start:2,name:"paddings",type:"number[]"}]},{tfOpName:"BatchToSpaceND",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"blockShape",type:"number[]"},{start:2,name:"crops",type:"number[]"}]},{tfOpName:"DepthToSpace",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"}],attrs:[{tfName:"block_size",name:"blockSize",type:"number"},{tfName:"data_format",name:"dataFormat",type:"string"}]},{tfOpName:"BroadcastTo",category:"transformation",inputs:[{start:0,name:"x",type:"tensor"},{start:1,name:"shape",type:"number[]"}],attrs:[]},{tfOpName:"BroadcastArgs",category:"transformation",inputs:[{start:0,name:"s0",type:"tensor"},{start:1,name:"s1",type:"tensor"}],attrs:[]}],Qv=class{static get Instance(){return this._instance||(this._instance=new this)}constructor(){let e=[Ck,Tk,Nk,Ek,Rk,_k,Dk,$k,Pk,Fk,Ok,Mk,zk,Lk,Bk,Wk,Vk,Uk,Gk],t=[].concat(...e.map(n=>n.json));this.opMappers=t.reduce((n,s)=>(n[s.tfOpName]=s,n),{})}transformGraph(e,t={}){let n=e.node,s=[],r=[],a=[],o=n.reduce((f,m)=>(f[m.name]=this.mapNode(m),m.op.startsWith("Placeholder")?s.push(f[m.name]):m.op==="Const"?r.push(f[m.name]):(m.input==null||m.input.length===0)&&a.push(f[m.name]),f),{}),i=[],l=[],u={},c={};t!=null&&(u=this.mapSignatureEntries(t.inputs),c=this.mapSignatureEntries(t.outputs));let p=Object.keys(o);p.forEach(f=>{let m=o[f];m.inputNames.forEach((g,y)=>{let[x,,A]=Ur(g),b=o[x];if(b.outputs!=null){let w=b.outputs.indexOf(A);if(w!==-1){let k=`${x}:${w}`;m.inputNames[y]=k}}m.inputs.push(b),b.children.push(m)})}),Object.keys(c).length===0?p.forEach(f=>{let m=o[f];m.children.length===0&&l.push(m)}):Object.keys(c).forEach(f=>{let[m]=Ur(f),g=o[m];g!=null&&(g.signatureKey=c[f],l.push(g))}),Object.keys(u).length>0?Object.keys(u).forEach(f=>{let[m]=Ur(f),g=o[m];g&&(g.signatureKey=u[f],i.push(g))}):i=s;let d={};e.library!=null&&e.library.function!=null&&(d=e.library.function.reduce((f,m)=>(f[m.signature.name]=this.mapFunction(m),f),{}));let h={nodes:o,inputs:i,outputs:l,weights:r,placeholders:s,signature:t,functions:d};return a.length>0&&(h.initNodes=a),h}mapSignatureEntries(e){return Object.keys(e||{}).reduce((t,n)=>(t[e[n].name]=n,t),{})}mapNode(e){let t=Sk(e.op)||this.opMappers[e.op]||{};e.attr==null&&(e.attr={});let n={name:e.name,op:e.op,category:t.category,inputNames:(e.input||[]).map(s=>s.startsWith("^")?s.slice(1):s),inputs:[],children:[],inputParams:{},attrParams:{},rawAttrs:e.attr,outputs:t.outputs};return t.inputs!=null&&(n.inputParams=t.inputs.reduce((s,r)=>(s[r.name]={type:r.type,inputIndexStart:r.start,inputIndexEnd:r.end},s),{})),t.attrs!=null&&(n.attrParams=t.attrs.reduce((s,r)=>{let a=r.type,o;switch(r.type){case"string":o=W3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=W3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"string[]":o=X3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=X3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"number":o=U3(e.attr,r.tfName,r.defaultValue||0),o===void 0&&!!r.tfDeprecatedName&&(o=U3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"number[]":o=q3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=q3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"bool":o=V3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=V3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"bool[]":o=Z3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=Z3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"shape":o=j3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=j3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"shape[]":o=K3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=K3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"dtype":o=G3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=G3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"dtype[]":o=H3(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=H3(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"func":o=e7(e.attr,r.tfName,r.defaultValue),o===void 0&&!!r.tfDeprecatedName&&(o=e7(e.attr,r.tfDeprecatedName,r.defaultValue));break;case"tensor":case"tensors":break;default:throw new Error(`Unsupported param type: ${r.type} for op: ${e.op}`)}return s[r.name]={value:o,type:a},s},{})),n}mapFunction(e){let t=e.nodeDef,n=[],s=[],r={};t!=null&&(r=t.reduce((c,p)=>(c[p.name]=this.mapNode(p),p.op==="Const"&&s.push(c[p.name]),c),{}));let a=[],o=[];e.signature.inputArg.forEach(c=>{let[p]=Ur(c.name),d={name:p,op:"Placeholder",inputs:[],inputNames:[],category:"graph",inputParams:{},attrParams:{dtype:{value:bx(c.type),type:"dtype"}},children:[]};d.signatureKey=c.name,a.push(d),r[p]=d}),Object.keys(r).forEach(c=>{let p=r[c];p.inputNames.forEach((d,h)=>{let[f,,m]=Ur(d),g=r[f];if(g.outputs!=null){let y=g.outputs.indexOf(m);if(y!==-1){let x=`${f}:${y}`;p.inputNames[h]=x}}p.inputs.push(g),g.children.push(p)})});let l=e.ret;e.signature.outputArg.forEach(c=>{let[p,d]=Ur(l[c.name]),h=r[p];h!=null&&(h.defaultOutput=d,o.push(h))});let u=this.mapArgsToSignature(e);return{nodes:r,inputs:a,outputs:o,weights:s,placeholders:n,signature:u}}mapArgsToSignature(e){return{methodName:e.signature.name,inputs:e.signature.inputArg.reduce((t,n)=>(t[n.name]=this.mapArgToTensorInfo(n),t),{}),outputs:e.signature.outputArg.reduce((t,n)=>(t[n.name]=this.mapArgToTensorInfo(n,e.ret),t),{})}}mapArgToTensorInfo(e,t){let n=e.name;return t!=null&&(n=t[n]),{name:n,dtype:e.type}}};function gj(e){let t=X().global;if(typeof t.atob!="undefined")return t.atob(e);if(typeof Buffer!="undefined")return new Buffer(e,"base64").toString();throw new Error("Unable to decode base64 in this environment. Missing built-in atob() or Buffer()")}function Hk(e,t){let n=Array.isArray(e)?String.fromCharCode.apply(null,e):gj(e);return t?n:n.toLowerCase()}function W3(e,t,n,s=!1){let r=e[t];return r!=null?Hk(r.s,s):n}function V3(e,t,n){let s=e[t];return s?s.b:n}function U3(e,t,n){let s=e[t]||{},r=s.i!=null?s.i:s.f!=null?s.f:n;return typeof r=="number"?r:parseInt(r,10)}function bx(e){switch(typeof e=="string"&&(e=sr[e]),e){case sr.DT_FLOAT:case sr.DT_HALF:return"float32";case sr.DT_INT32:case sr.DT_INT64:case sr.DT_INT8:case sr.DT_UINT8:return"int32";case sr.DT_BOOL:return"bool";case sr.DT_DOUBLE:return"float32";case sr.DT_STRING:return"string";default:return null}}function e7(e,t,n){let s=e[t];return s&&s.func?s.func.name:n}function G3(e,t,n){let s=e[t];return s&&s.type?bx(s.type):n}function H3(e,t,n){let s=e[t];return s&&s.list&&s.list.type?s.list.type.map(r=>bx(r)):n}function jk(e){if(!e.unknownRank)return e.dim!=null?e.dim.map(t=>typeof t.size=="number"?t.size:parseInt(t.size,10)):[]}function j3(e,t,n){let s=e[t];return s&&s.shape?jk(s.shape):n}function q3(e,t,n){let s=e[t];return s?((s.list.f&&s.list.f.length?s.list.f:s.list.i)||[]).map(r=>typeof r=="number"?r:parseInt(r,10)):n}function X3(e,t,n,s=!1){let r=e[t];return r&&r.list&&r.list.s?r.list.s.map(a=>Hk(a,s)):n}function K3(e,t,n){let s=e[t];return s&&s.list&&s.list.shape?s.list.shape.map(r=>jk(r)):n}function Z3(e,t,n){let s=e[t];return s&&s.list&&s.list.b?s.list.b:n}var yj=class{constructor(e,t,n){this.node=e,this.tensorMap=t,this.context=n,this.inputs=[],this.attrs={},this.inputs=e.inputNames.map(s=>this.getInput(s)),e.rawAttrs!=null&&(this.attrs=Object.keys(e.rawAttrs).reduce((s,r)=>(s[r]=this.getAttr(r),s),{}))}getInput(e){return Jn(e,this.tensorMap,this.context)}getAttr(e,t){let n=this.node.rawAttrs[e];if(n.tensor!=null)return Jn(e,this.tensorMap,this.context);if(n.i!=null||n.f!=null)return U3(this.node.rawAttrs,e,t);if(n.s!=null)return W3(this.node.rawAttrs,e,t);if(n.b!=null)return V3(this.node.rawAttrs,e,t);if(n.shape!=null)return j3(this.node.rawAttrs,e,t);if(n.type!=null)return G3(this.node.rawAttrs,e,t);if(n.list!=null){if(n.list.i!=null||n.list.f!=null)return q3(this.node.rawAttrs,e,t);if(n.list.s!=null)return X3(this.node.rawAttrs,e,t);if(n.list.shape!=null)return K3(this.node.rawAttrs,e,t);if(n.list.b!=null)return Z3(this.node.rawAttrs,e,t);if(n.list.type!=null)return H3(this.node.rawAttrs,e,t)}return t}},En={};Ve(En,{OP_SCOPE_SUFFIX:()=>Cy,abs:()=>tn,acos:()=>Hy,acosh:()=>jy,add:()=>ce,addN:()=>f0,all:()=>m0,any:()=>Sp,argMax:()=>Es,argMin:()=>qy,asin:()=>Xy,asinh:()=>Ky,atan:()=>Zy,atan2:()=>Yy,atanh:()=>Jy,avgPool:()=>ih,avgPool3d:()=>eA,basicLSTMCell:()=>sw,batchNorm:()=>Bc,batchNorm2d:()=>tA,batchNorm3d:()=>nA,batchNorm4d:()=>sA,batchToSpaceND:()=>lh,bincount:()=>rA,booleanMaskAsync:()=>zw,broadcastArgs:()=>rw,broadcastTo:()=>Uu,buffer:()=>Le,cast:()=>ge,ceil:()=>aA,clipByValue:()=>fs,clone:()=>Fn,complex:()=>ha,concat:()=>Ct,concat1d:()=>oA,concat2d:()=>Xl,concat3d:()=>iA,concat4d:()=>lA,conv1d:()=>g0,conv2d:()=>fa,conv2dTranspose:()=>y0,conv3d:()=>cA,conv3dTranspose:()=>dA,cos:()=>uh,cosh:()=>A0,cosineWindow:()=>B0,cumprod:()=>Cp,cumsum:()=>x0,denseBincount:()=>ow,depthToSpace:()=>pA,depthwiseConv2d:()=>Wc,diag:()=>iw,dilation2d:()=>hA,div:()=>pe,divNoNan:()=>fA,dot:()=>mA,dropout:()=>WA,einsum:()=>lw,elu:()=>Vc,enclosingPowerOfTwo:()=>VA,equal:()=>Rs,erf:()=>gA,euclideanNorm:()=>xA,exp:()=>_s,expandDims:()=>Kt,expm1:()=>bA,eye:()=>b0,fft:()=>Ah,fill:()=>Gc,floor:()=>Hc,floorDiv:()=>Lc,fused:()=>Qu,gather:()=>jc,gatherND:()=>Vw,greater:()=>ys,greaterEqual:()=>ii,ifft:()=>Ju,imag:()=>ah,image:()=>Ne,inTopKAsync:()=>Uw,irfft:()=>O0,isFinite:()=>vA,isInf:()=>wA,isNaN:()=>kA,leakyRelu:()=>ch,less:()=>v0,lessEqual:()=>li,linalg:()=>HA,linspace:()=>hw,localResponseNormalization:()=>IA,log:()=>Ds,log1p:()=>dh,logSigmoid:()=>SA,logSoftmax:()=>k0,logSumExp:()=>I0,logicalAnd:()=>lr,logicalNot:()=>ph,logicalOr:()=>S0,logicalXor:()=>CA,losses:()=>t8,lowerBound:()=>mw,matMul:()=>Qe,max:()=>mn,maxPool:()=>hh,maxPool3d:()=>TA,maxPoolWithArgmax:()=>gw,maximum:()=>Yr,mean:()=>Bt,meshgrid:()=>yw,min:()=>ma,minimum:()=>qc,mirrorPad:()=>NA,mod:()=>Zl,moments:()=>fh,movingAverage:()=>Lw,mul:()=>L,multiRNNCell:()=>Aw,multinomial:()=>xw,neg:()=>Dt,norm:()=>Uc,notEqual:()=>Ji,oneHot:()=>Ku,ones:()=>Ns,onesLike:()=>$s,op:()=>V,outerProduct:()=>bw,pad:()=>Js,pad1d:()=>vw,pad2d:()=>ww,pad3d:()=>kw,pad4d:()=>Iw,pool:()=>EA,pow:()=>ga,prelu:()=>gh,print:()=>Ry,prod:()=>RA,rand:()=>Sw,randomGamma:()=>Cw,randomNormal:()=>T0,randomStandardNormal:()=>Tw,randomUniform:()=>Xc,range:()=>Yu,real:()=>Zu,reciprocal:()=>$A,relu:()=>$r,relu6:()=>N0,reshape:()=>U,reverse:()=>Ks,reverse1d:()=>Nw,reverse2d:()=>Ew,reverse3d:()=>Rw,reverse4d:()=>_w,rfft:()=>xh,round:()=>E0,rsqrt:()=>R0,scalar:()=>Se,scatterND:()=>Bw,searchSorted:()=>C0,selu:()=>_0,separableConv2d:()=>D0,setdiff1dAsync:()=>Dw,sigmoid:()=>Cn,sign:()=>PA,signal:()=>e8,sin:()=>$0,sinh:()=>P0,slice:()=>Oe,slice1d:()=>yh,slice2d:()=>F0,slice3d:()=>ui,slice4d:()=>to,softmax:()=>Yl,softplus:()=>Kl,spaceToBatchND:()=>mh,sparse:()=>n8,sparseToDense:()=>Ww,spectral:()=>Qw,split:()=>Zt,sqrt:()=>Nn,square:()=>vt,squaredDifference:()=>M0,squeeze:()=>rt,stack:()=>on,step:()=>Jl,stridedSlice:()=>FA,string:()=>s8,sub:()=>he,sum:()=>ke,tan:()=>OA,tanh:()=>Zi,tensor:()=>ft,tensor1d:()=>Ft,tensor2d:()=>or,tensor3d:()=>My,tensor4d:()=>$w,tensor5d:()=>Pw,tensor6d:()=>Fw,tile:()=>js,topk:()=>MA,transpose:()=>st,truncatedNormal:()=>z0,unique:()=>zA,unsortedSegmentSum:()=>L0,unstack:()=>es,upperBound:()=>Ow,variable:()=>LA,where:()=>Mn,whereAsync:()=>BA,zeros:()=>Wt,zerosLike:()=>it});var Aj=(e,t,n,s=En)=>{switch(e.op){case"BiasAdd":case"AddV2":case"Add":return[s.add(I("a",e,t,n),I("b",e,t,n))];case"AddN":return[s.addN(I("tensors",e,t,n))];case"FloorMod":case"Mod":return[s.mod(I("a",e,t,n),I("b",e,t,n))];case"Mul":return[s.mul(I("a",e,t,n),I("b",e,t,n))];case"RealDiv":case"Div":return[s.div(I("a",e,t,n),I("b",e,t,n))];case"DivNoNan":return[s.divNoNan(I("a",e,t,n),I("b",e,t,n))];case"FloorDiv":return[s.floorDiv(I("a",e,t,n),I("b",e,t,n))];case"Sub":return[s.sub(I("a",e,t,n),I("b",e,t,n))];case"Minimum":return[s.minimum(I("a",e,t,n),I("b",e,t,n))];case"Maximum":return[s.maximum(I("a",e,t,n),I("b",e,t,n))];case"Pow":return[s.pow(I("a",e,t,n),I("b",e,t,n))];case"SquaredDifference":return[s.squaredDifference(I("a",e,t,n),I("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},xj=(e,t,n,s=En)=>{switch(e.op){case"Abs":case"ComplexAbs":return[s.abs(I("x",e,t,n))];case"Acos":return[s.acos(I("x",e,t,n))];case"Acosh":return[s.acosh(I("x",e,t,n))];case"Asin":return[s.asin(I("x",e,t,n))];case"Asinh":return[s.asinh(I("x",e,t,n))];case"Atan":return[s.atan(I("x",e,t,n))];case"Atan2":return[s.atan2(I("x",e,t,n),I("y",e,t,n))];case"Atanh":return[s.atanh(I("x",e,t,n))];case"Ceil":return[s.ceil(I("x",e,t,n))];case"Complex":return[s.complex(I("real",e,t,n),I("imag",e,t,n))];case"Cos":return[s.cos(I("x",e,t,n))];case"Cosh":return[s.cosh(I("x",e,t,n))];case"Elu":return[s.elu(I("x",e,t,n))];case"Erf":return[s.erf(I("x",e,t,n))];case"Exp":return[s.exp(I("x",e,t,n))];case"Expm1":return[s.expm1(I("x",e,t,n))];case"Floor":return[s.floor(I("x",e,t,n))];case"Log":return[s.log(I("x",e,t,n))];case"Log1p":return[s.log1p(I("x",e,t,n))];case"Imag":return[s.imag(I("x",e,t,n))];case"Neg":return[s.neg(I("x",e,t,n))];case"Reciprocal":return[s.reciprocal(I("x",e,t,n))];case"Real":return[s.real(I("x",e,t,n))];case"Relu":return[s.relu(I("x",e,t,n))];case"Round":return[s.round(I("x",e,t,n))];case"Selu":return[s.selu(I("x",e,t,n))];case"Sigmoid":return[s.sigmoid(I("x",e,t,n))];case"Sin":return[s.sin(I("x",e,t,n))];case"Sign":return[s.sign(I("x",e,t,n))];case"Sinh":return[s.sinh(I("x",e,t,n))];case"Softplus":return[s.softplus(I("x",e,t,n))];case"Sqrt":return[s.sqrt(I("x",e,t,n))];case"Square":return[s.square(I("x",e,t,n))];case"Tanh":return[s.tanh(I("x",e,t,n))];case"Tan":return[s.tan(I("x",e,t,n))];case"ClipByValue":return[s.clipByValue(I("x",e,t,n),I("clipValueMin",e,t,n),I("clipValueMax",e,t,n))];case"Relu6":return[s.relu6(I("x",e,t,n))];case"Rsqrt":return[s.rsqrt(Jn(e.inputNames[0],t,n))];case"Prod":return[s.prod(I("x",e,t,n),I("axes",e,t,n))];case"LeakyRelu":return[s.leakyRelu(I("x",e,t,n),I("alpha",e,t,n))];case"Prelu":return[s.prelu(I("x",e,t,n),I("alpha",e,t,n))];case"IsNan":return[s.isNaN(Jn(e.inputNames[0],t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function ar(e,t,n=""){if(!(typeof e=="number"||typeof t=="number")){v.assert(e.length===t.length,()=>n+` Shapes ${e} and ${t} must match`);for(let s=0;s<e.length;s++){let r=e[s],a=t[s];v.assert(r<0||a<0||r===a,()=>n+` Shapes ${e} and ${t} must match`)}}}function t7(e){return!(typeof e=="number"||e.some(t=>t<0))}function ep(e,t,n){let s=Y3(e,n),r=!t7(s);if(r&&t.length===0)throw new Error(`Tried to calculate elements of an empty list with non-fully-defined elementShape: ${s}`);if(r&&t.forEach(a=>{s=Y3(a.shape,s)}),!t7(s))throw new Error(`Non-fully-defined elementShape: ${s}`);return s}function Y3(e,t){if(typeof e=="number")return t;if(typeof t=="number")return e;if(e.length!==t.length)throw new Error(`Incompatible ranks during merge: ${e} vs. ${t}`);let n=[];for(let s=0;s<e.length;++s){let r=e[s],a=t[s];if(r>=0&&a>=0&&r!==a)throw new Error(`Incompatible shape during merge: ${e} vs. ${t}`);n[s]=r>=0?r:a}return n}var bj=class{constructor(e,t,n,s,r,a,o){this.name=e,this.dtype=t,this.maxSize=n,this.elementShape=s,this.identicalElementShapes=r,this.dynamicSize=a,this.clearAfterRead=o,this.tensors=[],this.closed_=!1,this.idTensor=Se(0),bn(this.idTensor)}get id(){return this.idTensor.id}get closed(){return this.closed_}clearAndClose(e){this.tensors.forEach(t=>{(e==null||!e.has(t.tensor.id))&&t.tensor.dispose()}),this.tensors=[],this.closed_=!0,this.idTensor.dispose()}size(){return this.tensors.length}read(e){if(this.closed_)throw new Error(`TensorArray ${this.name} has already been closed.`);if(e<0||e>=this.size())throw new Error(`Tried to read from index ${e}, but array size is: ${this.size()}`);let t=this.tensors[e];if(t.cleared)throw new Error(`TensorArray ${this.name}: Could not read index ${e} twice because it was cleared after a previous read (perhaps try setting clear_after_read = false?).`);return this.clearAfterRead&&(t.cleared=!0),t.read=!0,t.tensor}readMany(e){return e.map(t=>this.read(t))}write(e,t){if(this.closed_)throw new Error(`TensorArray ${this.name} has already been closed.`);if(e<0||!this.dynamicSize&&e>=this.maxSize)throw new Error(`Tried to write to index ${e}, but array is not resizeable and size is: ${this.maxSize}`);let n=this.tensors[e]||{};if(t.dtype!==this.dtype)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e},
           because the value dtype is ${t.dtype}, but TensorArray dtype is ${this.dtype}.`);if(this.size()===0&&(this.elementShape==null||this.elementShape.length===0)&&(this.elementShape=t.shape),ar(this.elementShape,t.shape,`TensorArray ${this.name}: Could not write to TensorArray index ${e}.`),n.read)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e}, because it has already been read.`);if(n.written)throw new Error(`TensorArray ${this.name}: Could not write to TensorArray index ${e}, because it has already been written.`);n.tensor=t,bn(t),n.written=!0,this.tensors[e]=n}writeMany(e,t){if(e.length!==t.length)throw new Error(`TensorArray ${this.name}: could not write multiple tensors,because the index size: ${e.length} is not the same as tensors size: ${t.length}.`);e.forEach((n,s)=>this.write(n,t[s]))}gather(e,t){if(!!t&&t!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but gather requested dtype ${t}`);if(e)e=e.slice(0,this.size());else{e=[];for(let s=0;s<this.size();s++)e.push(s)}if(e.length===0)return ft([],[0].concat(this.elementShape));let n=this.readMany(e);return ar(this.elementShape,n[0].shape,"TensorArray shape mismatch: "),on(n,0)}concat(e){if(!!e&&e!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but concat requested dtype ${e}`);if(this.size()===0)return ft([],[0].concat(this.elementShape));let t=[];for(let s=0;s<this.size();s++)t.push(s);let n=this.readMany(t);return ar(this.elementShape,n[0].shape,`TensorArray shape mismatch: tensor array shape (${this.elementShape}) vs first tensor shape (${n[0].shape})`),Ct(n,0)}scatter(e,t){if(t.dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${t.dtype}`);if(e.length!==t.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${e.length} vs. ${t.shape[0]}`);let n=Math.max(...e);if(!this.dynamicSize&&n>=this.maxSize)throw new Error(`Max index must be < array size (${n}  vs. ${this.maxSize})`);this.writeMany(e,es(t,0))}split(e,t){if(t.dtype!==this.dtype)throw new Error(`TensorArray dtype is ${this.dtype} but tensor has dtype ${t.dtype}`);let n=0,s=e.map(i=>(n+=i,n));if(n!==t.shape[0])throw new Error(`Expected sum of lengths to be equal to
           tensor.shape[0], but sum of lengths is
-        ${n}, and tensor's shape is: ${t.shape}`);if(!this.dynamicSize&&e.length!==this.maxSize)throw new Error(`TensorArray's size is not equal to the size of lengths (${this.maxSize} vs. ${e.length}), and the TensorArray is not marked as dynamically resizeable`);let r=n===0?0:t.size/n,a=[];J(()=>{t=U(t,[1,n,r]);for(let i=0;i<e.length;++i){let l=i===0?0:s[i-1],u=[0,l,0],c=[1,e[i],r];a[i]=U(Oe(t,u,c),this.elementShape)}return a});let o=[];for(let i=0;i<e.length;i++)o[i]=i;this.writeMany(o,a)}},rc=class{constructor(e,t,n,s=-1){this.tensors=e,this.elementShape=t,this.elementDtype=n,e!=null&&e.forEach(r=>{if(n!==r.dtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${r.dtype}`);ar(t,r.shape,"TensorList shape mismatch: "),bn(r)}),this.idTensor=Se(0),this.maxNumElements=s,bn(this.idTensor)}get id(){return this.idTensor.id}copy(){return new rc([...this.tensors],this.elementShape,this.elementDtype)}clearAndClose(e){this.tensors.forEach(t=>{(e==null||!e.has(t.id))&&t.dispose()}),this.tensors.length=0,this.idTensor.dispose()}size(){return this.tensors.length}stack(e,t,n=-1){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(n!==-1&&this.tensors.length!==n)throw new Error(`Operation expected a list with ${n} elements but got a list with ${this.tensors.length} elements.`);ar(e,this.elementShape,"TensorList shape mismatch: ");let s=tp(this.elementShape,this.tensors,e);return J(()=>{let r=this.tensors.map(a=>U(a,s));return on(r,0)})}popBack(e,t){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(this.size()===0)throw new Error("Trying to pop from an empty list.");let n=tp(this.elementShape,this.tensors,e),s=this.tensors.pop();return ar(s.shape,e,"TensorList shape mismatch: "),U(s,n)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if(ar(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");bn(e),this.tensors.push(e)}resize(e){if(e<0)throw new Error(`TensorListResize expects size to be non-negative. Got: ${e}`);if(this.maxNumElements!==-1&&e>this.maxNumElements)throw new Error(`TensorListResize input size ${e} is greater maxNumElement ${this.maxNumElements}.`);let t=new rc([],this.elementShape,this.elementDtype,this.maxNumElements);t.tensors.length=e;for(let n=0;n<Math.min(this.tensors.length,e);++n)t.tensors[n]=this.tensors[n];return t}getItem(e,t,n){if(n!==this.elementDtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${this.elementDtype}`);if(e<0||e>this.tensors.length)throw new Error(`Trying to access element ${e} in a list with ${this.tensors.length} elements.`);if(this.tensors[e]==null)throw new Error(`element at index ${e} is null.`);ar(this.tensors[e].shape,t,"TensorList shape mismatch: ");let s=tp(this.elementShape,this.tensors,t);return U(this.tensors[e],s)}setItem(e,t){if(t.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t.dtype}, but list elements ${this.elementDtype}`);if(e<0||this.maxNumElements!==-1&&e>=this.maxNumElements)throw new Error(`Trying to set element ${e} in a list with max ${this.maxNumElements} elements.`);ar(this.elementShape,t.shape,"TensorList shape mismatch: "),bn(t),this.tensors[e]=t}gather(e,t,n){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);ar(this.elementShape,n,"TensorList shape mismatch: "),e=e.slice(0,this.size());let s=tp(this.elementShape,this.tensors,n);return e.length===0?ft([],[0].concat(s)):J(()=>{let r=e.map(a=>U(this.tensors[a],s));return on(r,0)})}concat(e,t){if(!!e&&e!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${e}`);ar(this.elementShape,t,"TensorList shape mismatch: ");let n=tp(this.elementShape,this.tensors,t);return this.size()===0?ft([],[0].concat(n)):J(()=>{let s=this.tensors.map(r=>U(r,n));return Ct(s,0)})}};function vj(e,t,n){let s=e.dtype;if(e.shape.length<1)throw new Error(`Tensor must be at least a vector, but saw shape: ${e.shape}`);if(e.dtype!==n)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${n}`);let r=e.shape.slice(1);ar(r,t,"TensorList shape mismatch: ");let a=es(e);return new rc(a,t,s)}function wj(e,t,n,s){return new rc([],e,t,s)}function kj(e,t,n,s){if(t.length!==e.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${t.length} vs. ${e.shape[0]}`);let r=Math.max(...t);if(s!=null&&s!==-1&&r>=s)throw new Error(`Max index must be < array size (${r}  vs. ${s})`);let a=new rc([],n,e.dtype,s),o=es(e,0);return t.forEach((i,l)=>{a.setItem(i,o[l])}),a}function Ij(e,t,n){let s=0,r=t.map(c=>(s+=c,s));if(s!==e.shape[0])throw new Error(`Expected sum of lengths to be equal to
+        ${n}, and tensor's shape is: ${t.shape}`);if(!this.dynamicSize&&e.length!==this.maxSize)throw new Error(`TensorArray's size is not equal to the size of lengths (${this.maxSize} vs. ${e.length}), and the TensorArray is not marked as dynamically resizeable`);let r=n===0?0:t.size/n,a=[];J(()=>{t=U(t,[1,n,r]);for(let i=0;i<e.length;++i){let l=i===0?0:s[i-1],u=[0,l,0],c=[1,e[i],r];a[i]=U(Oe(t,u,c),this.elementShape)}return a});let o=[];for(let i=0;i<e.length;i++)o[i]=i;this.writeMany(o,a)}},sc=class{constructor(e,t,n,s=-1){this.tensors=e,this.elementShape=t,this.elementDtype=n,e!=null&&e.forEach(r=>{if(n!==r.dtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${r.dtype}`);ar(t,r.shape,"TensorList shape mismatch: "),bn(r)}),this.idTensor=Se(0),this.maxNumElements=s,bn(this.idTensor)}get id(){return this.idTensor.id}copy(){return new sc([...this.tensors],this.elementShape,this.elementDtype)}clearAndClose(e){this.tensors.forEach(t=>{(e==null||!e.has(t.id))&&t.dispose()}),this.tensors.length=0,this.idTensor.dispose()}size(){return this.tensors.length}stack(e,t,n=-1){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(n!==-1&&this.tensors.length!==n)throw new Error(`Operation expected a list with ${n} elements but got a list with ${this.tensors.length} elements.`);ar(e,this.elementShape,"TensorList shape mismatch: ");let s=ep(this.elementShape,this.tensors,e);return J(()=>{let r=this.tensors.map(a=>U(a,s));return on(r,0)})}popBack(e,t){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);if(this.size()===0)throw new Error("Trying to pop from an empty list.");let n=ep(this.elementShape,this.tensors,e),s=this.tensors.pop();return ar(s.shape,e,"TensorList shape mismatch: "),U(s,n)}pushBack(e){if(e.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${this.elementDtype}`);if(ar(e.shape,this.elementShape,"TensorList shape mismatch: "),this.maxNumElements===this.size())throw new Error("Trying to push element into a full list.");bn(e),this.tensors.push(e)}resize(e){if(e<0)throw new Error(`TensorListResize expects size to be non-negative. Got: ${e}`);if(this.maxNumElements!==-1&&e>this.maxNumElements)throw new Error(`TensorListResize input size ${e} is greater maxNumElement ${this.maxNumElements}.`);let t=new sc([],this.elementShape,this.elementDtype,this.maxNumElements);t.tensors.length=e;for(let n=0;n<Math.min(this.tensors.length,e);++n)t.tensors[n]=this.tensors[n];return t}getItem(e,t,n){if(n!==this.elementDtype)throw new Error(`Invalid data types; op elements ${n}, but list elements ${this.elementDtype}`);if(e<0||e>this.tensors.length)throw new Error(`Trying to access element ${e} in a list with ${this.tensors.length} elements.`);if(this.tensors[e]==null)throw new Error(`element at index ${e} is null.`);ar(this.tensors[e].shape,t,"TensorList shape mismatch: ");let s=ep(this.elementShape,this.tensors,t);return U(this.tensors[e],s)}setItem(e,t){if(t.dtype!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t.dtype}, but list elements ${this.elementDtype}`);if(e<0||this.maxNumElements!==-1&&e>=this.maxNumElements)throw new Error(`Trying to set element ${e} in a list with max ${this.maxNumElements} elements.`);ar(this.elementShape,t.shape,"TensorList shape mismatch: "),bn(t),this.tensors[e]=t}gather(e,t,n){if(t!==this.elementDtype)throw new Error(`Invalid data types; op elements ${t}, but list elements ${this.elementDtype}`);ar(this.elementShape,n,"TensorList shape mismatch: "),e=e.slice(0,this.size());let s=ep(this.elementShape,this.tensors,n);return e.length===0?ft([],[0].concat(s)):J(()=>{let r=e.map(a=>U(this.tensors[a],s));return on(r,0)})}concat(e,t){if(!!e&&e!==this.elementDtype)throw new Error(`TensorList dtype is ${this.elementDtype} but concat requested dtype ${e}`);ar(this.elementShape,t,"TensorList shape mismatch: ");let n=ep(this.elementShape,this.tensors,t);return this.size()===0?ft([],[0].concat(n)):J(()=>{let s=this.tensors.map(r=>U(r,n));return Ct(s,0)})}};function vj(e,t,n){let s=e.dtype;if(e.shape.length<1)throw new Error(`Tensor must be at least a vector, but saw shape: ${e.shape}`);if(e.dtype!==n)throw new Error(`Invalid data types; op elements ${e.dtype}, but list elements ${n}`);let r=e.shape.slice(1);ar(r,t,"TensorList shape mismatch: ");let a=es(e);return new sc(a,t,s)}function wj(e,t,n,s){return new sc([],e,t,s)}function kj(e,t,n,s){if(t.length!==e.shape[0])throw new Error(`Expected len(indices) == tensor.shape[0], but saw: ${t.length} vs. ${e.shape[0]}`);let r=Math.max(...t);if(s!=null&&s!==-1&&r>=s)throw new Error(`Max index must be < array size (${r}  vs. ${s})`);let a=new sc([],n,e.dtype,s),o=es(e,0);return t.forEach((i,l)=>{a.setItem(i,o[l])}),a}function Ij(e,t,n){let s=0,r=t.map(c=>(s+=c,s));if(s!==e.shape[0])throw new Error(`Expected sum of lengths to be equal to
           tensor.shape[0], but sum of lengths is
-        ${s}, and tensor's shape is: ${e.shape}`);let a=e.shape.slice(1),o=J3(a,n),i=s===0?0:e.size/s,l=J(()=>{let c=[];e=U(e,[1,s,i]);for(let p=0;p<t.length;++p){let d=p===0?0:r[p-1],h=[0,d,0],f=[1,t[p],i];c[p]=U(Oe(e,h,f),o)}return e.dispose(),c}),u=new rc([],n,e.dtype,t.length);for(let c=0;c<l.length;c++)u.setItem(c,l[c]);return u}var Sj=async(e,t,n)=>{switch(e.op){case"If":case"StatelessIf":{let s=I("thenBranch",e,t,n),r=I("elseBranch",e,t,n),a=I("cond",e,t,n),o=I("args",e,t,n);return(await a.data())[0]?n.functionMap[s].executeFunctionAsync(o,n.tensorArrayMap,n.tensorListMap):n.functionMap[r].executeFunctionAsync(o,n.tensorArrayMap,n.tensorListMap)}case"While":case"StatelessWhile":{let s=I("body",e,t,n),r=I("cond",e,t,n),a=I("args",e,t,n),o=await n.functionMap[r].executeFunctionAsync(a,n.tensorArrayMap,n.tensorListMap),i=a.map(c=>c.id),l=await o[0].data();o.forEach(c=>{!c.kept&&i.indexOf(c.id)===-1&&c.dispose()});let u=a;for(;l[0];){let c=u;u=await n.functionMap[s].executeFunctionAsync(u,n.tensorArrayMap,n.tensorListMap);let p=u.map(h=>h.id);c.forEach(h=>{!h.kept&&i.indexOf(h.id)===-1&&p.indexOf(h.id)===-1&&h.dispose()});let d=await n.functionMap[r].executeFunctionAsync(u,n.tensorArrayMap,n.tensorListMap);l=await d[0].data(),d.forEach(h=>{!h.kept&&i.indexOf(h.id)===-1&&p.indexOf(h.id)===-1&&h.dispose()})}return u}case"LoopCond":{let s=I("pred",e,t,n);return[ca(s)]}case"Switch":{let s=I("pred",e,t,n),r=I("data",e,t,n);return r.kept||(r=ca(r)),(await s.data())[0]?[void 0,r]:[r,void 0]}case"Merge":{let s=e.inputNames.find(r=>Jn(r,t,n)!==void 0);if(s){let r=Jn(s,t,n);return[ca(r)]}return}case"Enter":{let s=I("frameName",e,t,n),r=I("tensor",e,t,n);return n.enterFrame(s),[ca(r)]}case"Exit":{let s=I("tensor",e,t,n);return n.exitFrame(),[ca(s)]}case"NextIteration":{let s=I("tensor",e,t,n);return n.nextIteration(),[ca(s)]}case"TensorArrayV3":{let s=I("size",e,t,n),r=I("dtype",e,t,n),a=I("elementShape",e,t,n),o=I("dynamicSize",e,t,n),i=I("clearAfterRead",e,t,n),l=I("identicalElementShapes",e,t,n),u=I("name",e,t,n),c=new bj(u,r,s,a,l,o,i);return n.addTensorArray(c),[c.idTensor,Se(1)]}case"TensorArrayWriteV3":{let s=I("tensorArrayId",e,t,n),r=I("index",e,t,n),a=I("tensor",e,t,n),o=n.getTensorArray(s.id);return o.write(r,a),[o.idTensor]}case"TensorArrayReadV3":{let s=I("tensorArrayId",e,t,n),r=I("index",e,t,n);return[n.getTensorArray(s.id).read(r)]}case"TensorArrayGatherV3":{let s=I("tensorArrayId",e,t,n),r=I("indices",e,t,n),a=I("dtype",e,t,n);return[n.getTensorArray(s.id).gather(r,a)]}case"TensorArrayScatterV3":{let s=I("tensorArrayId",e,t,n),r=I("indices",e,t,n),a=I("tensor",e,t,n),o=n.getTensorArray(s.id);return o.scatter(r,a),[o.idTensor]}case"TensorArrayConcatV3":{let s=I("tensorArrayId",e,t,n),r=n.getTensorArray(s.id),a=I("dtype",e,t,n);return[r.concat(a)]}case"TensorArraySplitV3":{let s=I("tensorArrayId",e,t,n),r=I("tensor",e,t,n),a=I("lengths",e,t,n),o=n.getTensorArray(s.id);return o.split(a,r),[o.idTensor]}case"TensorArraySizeV3":{let s=I("tensorArrayId",e,t,n),r=n.getTensorArray(s.id);return[Se(r.size(),"int32")]}case"TensorArrayCloseV3":{let s=I("tensorArrayId",e,t,n),r=n.getTensorArray(s.id);return r.clearAndClose(),[r.idTensor]}case"TensorListSetItem":{let s=I("tensorListId",e,t,n),r=I("index",e,t,n),a=I("tensor",e,t,n),o=n.getTensorList(s.id);return o.setItem(r,a),[o.idTensor]}case"TensorListGetItem":{let s=I("tensorListId",e,t,n),r=I("index",e,t,n),a=I("elementShape",e,t,n),o=I("elementDType",e,t,n);return[n.getTensorList(s.id).getItem(r,a,o)]}case"TensorListScatterV2":case"TensorListScatter":{let s=I("indices",e,t,n),r=I("tensor",e,t,n),a=I("elementShape",e,t,n),o=I("numElements",e,t,n),i=kj(r,s,a,o);return n.addTensorList(i),[i.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let s=I("elementShape",e,t,n),r=I("elementDType",e,t,n),a;e.op==="TensorListReserve"?a="numElements":a="maxNumElements";let o=I(a,e,t,n),i=e.op==="TensorListReserve"?-1:o,l=wj(s,r,o,i);return n.addTensorList(l),[l.idTensor]}case"TensorListGather":{let s=I("tensorListId",e,t,n),r=I("indices",e,t,n),a=I("elementShape",e,t,n),o=I("elementDType",e,t,n);return[n.getTensorList(s.id).gather(r,o,a)]}case"TensorListStack":{let s=I("tensorListId",e,t,n),r=I("elementShape",e,t,n),a=I("elementDType",e,t,n),o=I("numElements",e,t,n);return[n.getTensorList(s.id).stack(r,a,o)]}case"TensorListFromTensor":{let s=I("tensor",e,t,n),r=I("elementShape",e,t,n),a=I("elementDType",e,t,n),o=vj(s,r,a);return n.addTensorList(o),[o.idTensor]}case"TensorListConcat":case"TensorListConcatV2":{let s=I("tensorListId",e,t,n),r=n.getTensorList(s.id),a=I("dtype",e,t,n),o=I("elementShape",e,t,n);return[r.concat(a,o)]}case"TensorListPushBack":{let s=I("tensorListId",e,t,n),r=I("tensor",e,t,n),a=n.getTensorList(s.id);return a.pushBack(r),[a.idTensor]}case"TensorListPopBack":{let s=I("tensorListId",e,t,n),r=I("elementShape",e,t,n),a=I("elementDType",e,t,n);return[n.getTensorList(s.id).popBack(r,a)]}case"TensorListSplit":{let s=I("tensor",e,t,n),r=I("elementShape",e,t,n),a=I("lengths",e,t,n),o=Ij(s,a,r);return n.addTensorList(o),[o.idTensor]}case"TensorListLength":{let s=I("tensorListId",e,t,n),r=n.getTensorList(s.id);return[Se(r.size(),"int32")]}case"TensorListResize":{let s=I("tensorListId",e,t,n),r=I("size",e,t,n),o=n.getTensorList(s.id).resize(r);return n.addTensorList(o),[o.idTensor]}default:throw TypeError(`Node type ${e.op} is not implemented`)}};function n7(e,t,n){let[s,r]=I("fusedOps",e,t,n),a=s==="biasadd",o=!a,i=r==="prelu",l=s==="fusedbatchnorm",u=I("numArgs",e,t,n);if(a){if(i&&u!==2)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&a&&u!==1)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd must have one extra argument: bias.")}if(l)throw new Error("FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported");let c=I("strides",e,t,n),p=tm(e,t,n),d=I("dataFormat",e,t,n).toUpperCase(),h=I("dilations",e,t,n),[f,m]=I("args",e,t,n);o&&(m=f,f=void 0);let g=I("leakyreluAlpha",e,t,n);return{stride:c,pad:p,dataFormat:d,dilations:h,biasArg:f,preluArg:m,activationFunc:r,leakyreluAlpha:g}}var Cj=(e,t,n,s=En)=>{switch(e.op){case"Conv1D":{let r=I("stride",e,t,n),a=I("pad",e,t,n),o=I("dataFormat",e,t,n).toUpperCase(),i=I("dilation",e,t,n);return[s.conv1d(I("x",e,t,n),I("filter",e,t,n),r,a,o,i)]}case"Conv2D":{let r=I("strides",e,t,n),a=tm(e,t,n),o=I("dataFormat",e,t,n).toUpperCase(),i=I("dilations",e,t,n);return[s.conv2d(I("x",e,t,n),I("filter",e,t,n),[r[1],r[2]],a,o,[i[1],i[2]])]}case"_FusedConv2D":{let{stride:r,pad:a,dataFormat:o,dilations:i,biasArg:l,preluArg:u,activationFunc:c,leakyreluAlpha:p}=n7(e,t,n);return[s.fused.conv2d({x:I("x",e,t,n),filter:I("filter",e,t,n),strides:[r[1],r[2]],pad:a,dataFormat:o,dilations:[i[1],i[2]],bias:l,activation:c,preluActivationWeights:u,leakyreluAlpha:p})]}case"FusedDepthwiseConv2dNative":{let{stride:r,pad:a,dataFormat:o,dilations:i,biasArg:l,preluArg:u,activationFunc:c,leakyreluAlpha:p}=n7(e,t,n);return[s.fused.depthwiseConv2d({x:I("x",e,t,n),filter:I("filter",e,t,n),strides:[r[1],r[2]],pad:a,dataFormat:o,dilations:[i[1],i[2]],bias:l,activation:c,preluActivationWeights:u,leakyreluAlpha:p})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{let r=I("outputShape",e,t,n),a=I("strides",e,t,n),o=tm(e,t,n);return[s.conv2dTranspose(I("x",e,t,n),I("filter",e,t,n),r,[a[1],a[2]],o)]}case"DepthwiseConv2dNative":case"DepthwiseConv2d":{let r=I("strides",e,t,n),a=tm(e,t,n),o=I("dilations",e,t,n),i=I("dataFormat",e,t,n).toUpperCase();return[s.depthwiseConv2d(I("input",e,t,n),I("filter",e,t,n),[r[1],r[2]],a,i,[o[1],o[2]])]}case"Conv3D":{let r=I("strides",e,t,n),a=I("pad",e,t,n),o=I("dataFormat",e,t,n).toUpperCase(),i=I("dilations",e,t,n);return[s.conv3d(I("x",e,t,n),I("filter",e,t,n),[r[1],r[2],r[3]],a,o,[i[1],i[2],i[3]])]}case"AvgPool":{let r=I("strides",e,t,n),a=I("pad",e,t,n),o=I("kernelSize",e,t,n);return[s.avgPool(I("x",e,t,n),[o[1],o[2]],[r[1],r[2]],a)]}case"MaxPool":{let r=I("strides",e,t,n),a=I("pad",e,t,n),o=I("kernelSize",e,t,n);return[s.maxPool(I("x",e,t,n),[o[1],o[2]],[r[1],r[2]],a)]}case"MaxPoolWithArgmax":{let r=I("strides",e,t,n),a=I("pad",e,t,n),o=I("kernelSize",e,t,n),i=I("includeBatchInIndex",e,t,n),{result:l,indexes:u}=s.maxPoolWithArgmax(I("x",e,t,n),[o[1],o[2]],[r[1],r[2]],a,i);return[l,u]}case"AvgPool3D":{let r=I("strides",e,t,n),a=I("pad",e,t,n),o=I("kernelSize",e,t,n);return[s.avgPool3d(I("x",e,t,n),[o[1],o[2],o[3]],[r[1],r[2],r[3]],a)]}case"MaxPool3D":{let r=I("strides",e,t,n),a=I("pad",e,t,n),o=I("kernelSize",e,t,n);return[s.maxPool3d(I("x",e,t,n),[o[1],o[2],o[3]],[r[1],r[2],r[3]],a)]}case"Dilation2D":{let r=I("strides",e,t,n),a=I("pad",e,t,n),o=I("dilations",e,t,n),i=r[1],l=r[2],u=o[1],c=o[2];return[s.dilation2d(I("x",e,t,n),I("filter",e,t,n),[i,l],a,[u,c],"NHWC")]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Tj=(e,t,n,s=En)=>{switch(e.op){case"Fill":{let r=I("shape",e,t,n),a=I("dtype",e,t,n),o=I("value",e,t,n);return[s.fill(r,o,a)]}case"LinSpace":{let r=I("start",e,t,n),a=I("stop",e,t,n),o=I("num",e,t,n);return[s.linspace(r,a,o)]}case"Multinomial":{let r=I("logits",e,t,n),a=I("numSamples",e,t,n),o=I("seed",e,t,n);return[s.multinomial(r,a,o)]}case"OneHot":{let r=I("indices",e,t,n),a=I("depth",e,t,n),o=I("onValue",e,t,n),i=I("offValue",e,t,n);return[s.oneHot(r,a,o,i)]}case"Ones":return[s.ones(I("shape",e,t,n),I("dtype",e,t,n))];case"OnesLike":return[s.onesLike(I("x",e,t,n))];case"RandomStandardNormal":return[s.randomStandardNormal(I("shape",e,t,n),I("dtype",e,t,n),I("seed",e,t,n))];case"RandomUniform":return[s.randomUniform(I("shape",e,t,n),I("minval",e,t,n),I("maxval",e,t,n),I("dtype",e,t,n))];case"Range":{let r=I("start",e,t,n),a=I("stop",e,t,n),o=I("step",e,t,n);return[s.range(r,a,o,I("dtype",e,t,n))]}case"TruncatedNormal":{let r=I("shape",e,t,n),a=I("mean",e,t,n),o=I("stdDev",e,t,n),i=I("seed",e,t,n);return[s.truncatedNormal(r,a,o,I("dtype",e,t,n),i)]}case"Zeros":return[s.zeros(I("shape",e,t,n),I("dtype",e,t,n))];case"ZerosLike":return[s.zerosLike(I("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function p3(e,t,n){let s=I("boxes",e,t,n),r=I("scores",e,t,n),a=I("maxOutputSize",e,t,n),o=I("iouThreshold",e,t,n),i=I("scoreThreshold",e,t,n),l=I("softNmsSigma",e,t,n);return{boxes:s,scores:r,maxOutputSize:a,iouThreshold:o,scoreThreshold:i,softNmsSigma:l}}var Nj=async(e,t,n,s,r=En)=>{switch(e.op){case"NonMaxSuppressionV5":{let{boxes:a,scores:o,maxOutputSize:i,iouThreshold:l,scoreThreshold:u,softNmsSigma:c}=p3(e,t,n),p=await r.image.nonMaxSuppressionWithScoreAsync(a,o,i,l,u,c);return[p.selectedIndices,p.selectedScores]}case"NonMaxSuppressionV4":{let{boxes:a,scores:o,maxOutputSize:i,iouThreshold:l,scoreThreshold:u}=p3(e,t,n),c=I("padToMaxOutputSize",e,t,n),p=await r.image.nonMaxSuppressionPaddedAsync(a,o,i,l,u,c);return[p.selectedIndices,p.validOutputs]}case"NonMaxSuppressionV3":case"NonMaxSuppressionV2":{let{boxes:a,scores:o,maxOutputSize:i,iouThreshold:l,scoreThreshold:u}=p3(e,t,n);return[await r.image.nonMaxSuppressionAsync(a,o,i,l,u)]}case"Where":{let a=r.cast(I("condition",e,t,n),"bool"),o=[await r.whereAsync(a)];return a.dispose(),o}case"ListDiff":return r.setdiff1dAsync(I("x",e,t,n),I("y",e,t,n));default:throw TypeError(`Node type ${e.op} is not implemented`)}},Ej=(e,t,n,s=En)=>{switch(e.op){case"LowerBound":{let r=I("sortedSequence",e,t,n),a=I("values",e,t,n);return[s.lowerBound(r,a)]}case"TopKV2":{let r=I("x",e,t,n),a=I("k",e,t,n),o=I("sorted",e,t,n),i=s.topk(r,a,o);return[i.values,i.indices]}case"UpperBound":{let r=I("sortedSequence",e,t,n),a=I("values",e,t,n);return[s.upperBound(r,a)]}case"Unique":{let r=I("x",e,t,n),a=s.unique(r);return[a.values,a.indices]}case"UniqueV2":{let r=I("x",e,t,n),a=I("axis",e,t,n),o=s.unique(r,a);return[o.values,o.indices]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Rj=(e,t,n,s=En)=>{switch(e.op){case"Const":return t[e.name];case"PlaceholderWithDefault":let r=I("default",e,t,n);return[Jn(e.name,t,n)||r];case"Placeholder":return[Jn(e.name,t,n)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":{let c=I("x",e,t,n);return[ca(c)]}case"IdentityN":return I("x",e,t,n).map(c=>ca(c));case"Snapshot":let a=I("x",e,t,n);return[ca(a)];case"Shape":return[s.tensor1d(I("x",e,t,n).shape,"int32")];case"ShapeN":return I("x",e,t,n).map(c=>s.tensor1d(c.shape));case"Size":return[s.scalar(I("x",e,t,n).size,"int32")];case"Rank":return[s.scalar(I("x",e,t,n).rank,"int32")];case"NoOp":return[s.scalar(1)];case"Print":let o=I("x",e,t,n),i=I("data",e,t,n),l=I("message",e,t,n),u=I("summarize",e,t,n);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(l);for(let c=0;c<i.length;c++)console.log(Array.prototype.slice.call(i[c].dataSync()).slice(0,u));return[o];default:throw TypeError(`Node type ${e.op} is not implemented`)}},_j=class{constructor(e,t){this.keyDType=e,this.valueDType=t,this.handle=Se(0),this.tensorMap=new Map,bn(this.handle)}get id(){return this.handle.id}clearAndClose(){this.tensorMap.forEach(e=>e.dispose()),this.tensorMap.clear(),this.handle.dispose()}size(){return this.tensorMap.size}tensorSize(){return Se(this.size(),"int32")}async import(e,t){this.checkKeyAndValueTensor(e,t);let n=await e.data();return this.tensorMap.forEach(s=>s.dispose()),this.tensorMap.clear(),J(()=>{let s=es(t),r=n.length,a=s.length;v.assert(r===a,()=>`The number of elements doesn't match, keys has ${r} elements, the values has ${a} elements.`);for(let o=0;o<r;o++){let i=n[o],l=s[o];bn(l),this.tensorMap.set(i,l)}return this.handle})}async find(e,t){this.checkKeyAndValueTensor(e,t);let n=await e.data();return J(()=>{let s=[];for(let r=0;r<n.length;r++){let a=n[r],o=this.findWithDefault(a,t);s.push(o)}return on(s)})}findWithDefault(e,t){let n=this.tensorMap.get(e);return n!=null?n:t}checkKeyAndValueTensor(e,t){if(e.dtype!==this.keyDType)throw new Error(`Expect key dtype ${this.keyDType}, but got ${e.dtype}`);if(t.dtype!==this.valueDType)throw new Error(`Expect value dtype ${this.valueDType}, but got ${t.dtype}`)}},Dj=async(e,t,n,s)=>{switch(e.op){case"HashTable":case"HashTableV2":{let r=I("keyDType",e,t,n),a=I("valueDType",e,t,n),o=new _j(r,a);return s.addHashTable(e.name,o),[o.handle]}case"LookupTableImport":case"LookupTableImportV2":{let r=I("tableHandle",e,t,n,s),a=I("keys",e,t,n),o=I("values",e,t,n);return[await s.getHashTableById(r.id).import(a,o)]}case"LookupTableFind":case"LookupTableFindV2":{let r=I("tableHandle",e,t,n,s),a=I("keys",e,t,n),o=I("defaultValue",e,t,n);return[await s.getHashTableById(r.id).find(a,o)]}case"LookupTableSize":case"LookupTableSizeV2":{let r=I("tableHandle",e,t,n,s);return[s.getHashTableById(r.id).tensorSize()]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},$j=(e,t,n,s=En)=>{switch(e.op){case"ResizeBilinear":{let r=I("images",e,t,n),a=I("size",e,t,n),o=I("alignCorners",e,t,n),i=I("halfPixelCenters",e,t,n);return[s.image.resizeBilinear(r,[a[0],a[1]],o,i)]}case"ResizeNearestNeighbor":{let r=I("images",e,t,n),a=I("size",e,t,n),o=I("alignCorners",e,t,n),i=I("halfPixelCenters",e,t,n);return[s.image.resizeNearestNeighbor(r,[a[0],a[1]],o,i)]}case"CropAndResize":{let r=I("image",e,t,n),a=I("boxes",e,t,n),o=I("boxInd",e,t,n),i=I("cropSize",e,t,n),l=I("method",e,t,n),u=I("extrapolationValue",e,t,n);return[s.image.cropAndResize(r,a,o,i,l,u)]}case"ImageProjectiveTransformV3":{let r=I("images",e,t,n),a=I("transforms",e,t,n),o=I("outputShape",e,t,n),i=I("fillValue",e,t,n),l=I("interpolation",e,t,n),u=I("fillMode",e,t,n);return[s.image.transform(r,a,l.toLowerCase(),u.toLowerCase(),i,o)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Pj=(e,t,n,s=En)=>{switch(e.op){case"Equal":return[s.equal(I("a",e,t,n),I("b",e,t,n))];case"NotEqual":return[s.notEqual(I("a",e,t,n),I("b",e,t,n))];case"Greater":return[s.greater(I("a",e,t,n),I("b",e,t,n))];case"GreaterEqual":return[s.greaterEqual(I("a",e,t,n),I("b",e,t,n))];case"Less":return[s.less(I("a",e,t,n),I("b",e,t,n))];case"LessEqual":return[s.lessEqual(I("a",e,t,n),I("b",e,t,n))];case"LogicalAnd":return[s.logicalAnd(I("a",e,t,n),I("b",e,t,n))];case"LogicalNot":return[s.logicalNot(I("a",e,t,n))];case"LogicalOr":return[s.logicalOr(I("a",e,t,n),I("b",e,t,n))];case"Select":case"SelectV2":return[s.where(I("condition",e,t,n),I("a",e,t,n),I("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Fj=(e,t,n,s=En)=>{switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[s.matMul(I("a",e,t,n),I("b",e,t,n),I("transposeA",e,t,n),I("transposeB",e,t,n))];case"Einsum":return[s.einsum(I("equation",e,t,n),...I("tensors",e,t,n))];case"Transpose":return[s.transpose(I("x",e,t,n),I("perm",e,t,n))];case"_FusedMatMul":let[r,a]=I("fusedOps",e,t,n),o=r==="biasadd",i=a==="prelu",l=I("numArgs",e,t,n),u=I("leakyreluAlpha",e,t,n);if(o){if(i&&l!==2)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&l!==1)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}let[c,p]=I("args",e,t,n);return[s.fused.matMul({a:I("a",e,t,n),b:I("b",e,t,n),transposeA:I("transposeA",e,t,n),transposeB:I("transposeB",e,t,n),bias:c,activation:a,preluActivationWeights:p,leakyreluAlpha:u})];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Oj=(e,t,n,s=En)=>{switch(e.op){case"EuclideanNorm":return[s.euclideanNorm(I("x",e,t,n),I("axis",e,t,n),I("keepDims",e,t,n))];case"FusedBatchNorm":case"FusedBatchNormV2":return[s.batchNorm(I("x",e,t,n),I("mean",e,t,n),I("variance",e,t,n),I("offset",e,t,n),I("scale",e,t,n),I("epsilon",e,t,n))];case"FusedBatchNormV3":return[s.batchNorm(I("x",e,t,n),I("mean",e,t,n),I("variance",e,t,n),I("offset",e,t,n),I("scale",e,t,n),I("epsilon",e,t,n))];case"LRN":return[s.localResponseNormalization(I("x",e,t,n),I("radius",e,t,n),I("bias",e,t,n),I("alpha",e,t,n),I("beta",e,t,n))];case"Softmax":return[s.softmax(I("x",e,t,n))];case"LogSoftmax":return[s.logSoftmax(I("x",e,t,n))];case"SparseToDense":return[s.sparseToDense(I("sparseIndices",e,t,n),I("outputShape",e,t,n),I("sparseValues",e,t,n),I("defaultValue",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Mj=(e,t,n,s=En)=>{switch(e.op){case"Max":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.max(I("x",e,t,n),i,l)]}case"Mean":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.mean(I("x",e,t,n),i,l)]}case"Min":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.min(I("x",e,t,n),i,l)]}case"Sum":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.sum(I("x",e,t,n),i,l)]}case"All":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.all(I("x",e,t,n),i,l)]}case"Any":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.any(I("x",e,t,n),i,l)]}case"ArgMax":{let i=I("axis",e,t,n);return[s.argMax(I("x",e,t,n),i)]}case"ArgMin":{let i=I("axis",e,t,n);return[s.argMin(I("x",e,t,n),i)]}case"Prod":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.prod(I("x",e,t,n),i,l)]}case"Cumprod":{let i=I("axis",e,t,n),l=I("exclusive",e,t,n),u=I("reverse",e,t,n);return[s.cumprod(I("x",e,t,n),i,l,u)]}case"Cumsum":{let i=I("axis",e,t,n),l=I("exclusive",e,t,n),u=I("reverse",e,t,n);return[s.cumsum(I("x",e,t,n),i,l,u)]}case"Bincount":let r=I("x",e,t,n),a=I("weights",e,t,n),o=I("size",e,t,n);return[s.bincount(r,a,o)];case"DenseBincount":{let i=I("x",e,t,n),l=I("weights",e,t,n),u=I("size",e,t,n),c=I("binaryOutput",e,t,n);return[s.denseBincount(i,l,u,c)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},zj=(e,t,n,s=En)=>{switch(e.op){case"ConcatV2":case"Concat":{let r=I("n",e,t,n),a=I("axis",e,t,n),o=I("tensors",e,t,n);return o=o.slice(0,r),[s.concat(o,a)]}case"Gather":{let r=I("x",e,t,n),a=I("indices",e,t,n);return[s.gather(r,s.cast(a,"int32"),0)]}case"GatherV2":{let r=I("axis",e,t,n),a=I("batchDims",e,t,n),o=I("x",e,t,n),i=I("indices",e,t,n);return[s.gather(o,s.cast(i,"int32"),r,a)]}case"Reverse":{let r=I("dims",e,t,n),a=[];for(let i=0;i<r.length;i++)r[i]&&a.push(i);let o=I("x",e,t,n);return[s.reverse(o,a)]}case"ReverseV2":{let r=I("axis",e,t,n),a=I("x",e,t,n);return[s.reverse(a,r)]}case"Slice":{let r=I("begin",e,t,n),a=I("size",e,t,n);return[s.slice(I("x",e,t,n),r,a)]}case"StridedSlice":{let r=I("begin",e,t,n),a=I("end",e,t,n),o=I("strides",e,t,n),i=I("beginMask",e,t,n),l=I("endMask",e,t,n),u=I("ellipsisMask",e,t,n),c=I("newAxisMask",e,t,n),p=I("shrinkAxisMask",e,t,n),d=I("x",e,t,n);return[s.stridedSlice(d,r,a,o,i,l,u,c,p)]}case"Pack":return J(()=>{let r=I("axis",e,t,n),a=I("tensors",e,t,n),o=a[0].shape,i=s.squeeze(a[0]).shape,l=a.map(u=>{let c=v.arraysEqual(u.shape,o);if(!c&&!v.arraysEqual(s.squeeze(u).shape,i))throw new Error("the input tensors shape does not match");return c?u:s.reshape(u,o)});return[s.stack(l,r)]});case"Unpack":{let r=I("axis",e,t,n),a=I("tensor",e,t,n);return s.unstack(a,r)}case"Tile":{let r=I("reps",e,t,n);return[s.tile(I("x",e,t,n),r)]}case"Split":case"SplitV":{let r=I("axis",e,t,n),a=I("numOrSizeSplits",e,t,n),o=I("x",e,t,n);return s.split(o,a,r)}case"ScatterNd":{let r=I("indices",e,t,n),a=I("values",e,t,n),o=I("shape",e,t,n);return[s.scatterND(r,a,o)]}case"GatherNd":{let r=I("x",e,t,n),a=I("indices",e,t,n);return[s.gatherND(r,a)]}case"SparseToDense":{let r=I("sparseIndices",e,t,n),a=I("outputShape",e,t,n),o=I("sparseValues",e,t,n),i=I("defaultValue",e,t,n);return[s.sparseToDense(r,o,a,o.dtype===i.dtype?i:s.cast(i,o.dtype))]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Lj=(e,t,n,s=En)=>{switch(e.op){case"SparseFillEmptyRows":{let{outputIndices:r,outputValues:a,emptyRowIndicator:o,reverseIndexMap:i}=s.sparse.sparseFillEmptyRows(I("indices",e,t,n),I("values",e,t,n),I("denseShape",e,t,n),I("defaultValue",e,t,n));return[r,a,o,i]}case"SparseReshape":{let{outputIndices:r,outputShape:a}=s.sparse.sparseReshape(I("inputIndices",e,t,n),I("inputShape",e,t,n),I("newShape",e,t,n));return[r,a]}case"SparseSegmentMean":return[s.sparse.sparseSegmentMean(I("data",e,t,n),I("indices",e,t,n),I("segmentIds",e,t,n))];case"SparseSegmentSum":return[s.sparse.sparseSegmentSum(I("data",e,t,n),I("indices",e,t,n),I("segmentIds",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Bj=(e,t,n,s=En)=>{switch(e.op){case"FFT":return[s.fft(I("x",e,t,n))];case"IFFT":return[s.ifft(I("x",e,t,n))];case"RFFT":return[s.rfft(I("x",e,t,n))];case"IRFFT":return[s.irfft(I("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Wj=(e,t,n,s=En)=>{switch(e.op){case"StringNGrams":{let{nGrams:r,nGramsSplits:a}=s.string.stringNGrams(I("data",e,t,n),I("dataSplits",e,t,n),I("separator",e,t,n),I("nGramWidths",e,t,n),I("leftPad",e,t,n),I("rightPad",e,t,n),I("padWidth",e,t,n),I("preserveShortSequences",e,t,n));return[r,a]}case"StringSplit":{let{indices:r,values:a,shape:o}=s.string.stringSplit(I("input",e,t,n),I("delimiter",e,t,n),I("skipEmpty",e,t,n));return[r,a,o]}case"StringToHashBucketFast":return[s.string.stringToHashBucketFast(I("input",e,t,n),I("numBuckets",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Vj=(e,t,n,s=En)=>{switch(e.op){case"Cast":return[s.cast(I("x",e,t,n),I("dtype",e,t,n))];case"ExpandDims":{let r=I("axis",e,t,n);return[s.expandDims(I("x",e,t,n),r)]}case"Squeeze":{let r=I("axis",e,t,n);return[s.squeeze(I("x",e,t,n),r)]}case"Reshape":return[s.reshape(I("x",e,t,n),I("shape",e,t,n))];case"MirrorPad":return[s.mirrorPad(I("x",e,t,n),I("padding",e,t,n),I("mode",e,t,n))];case"PadV2":case"Pad":return[s.pad(I("x",e,t,n),I("padding",e,t,n),I("constantValue",e,t,n))];case"SpaceToBatchND":{let r=I("blockShape",e,t,n),a=I("paddings",e,t,n);return[s.spaceToBatchND(I("x",e,t,n),r,a)]}case"BatchToSpaceND":{let r=I("blockShape",e,t,n),a=I("crops",e,t,n);return[s.batchToSpaceND(I("x",e,t,n),r,a)]}case"DepthToSpace":{let r=I("blockSize",e,t,n),a=I("dataFormat",e,t,n).toUpperCase();return[s.depthToSpace(I("x",e,t,n),r,a)]}case"BroadcastTo":return[s.broadcastTo(I("x",e,t,n),I("shape",e,t,n))];case"BroadcastArgs":return[s.broadcastArgs(I("s0",e,t,n),I("s1",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function s7(e,t,n,s,r=J){let a=((o,i,l)=>{switch(o.category){case"arithmetic":return r(()=>Aj(o,i,l));case"basic_math":return r(()=>xj(o,i,l));case"control":return Sj(o,i,l);case"convolution":return r(()=>Cj(o,i,l));case"creation":return r(()=>Tj(o,i,l));case"dynamic":return Nj(o,i,l);case"evaluation":return r(()=>Ej(o,i,l));case"image":return r(()=>$j(o,i,l));case"graph":return r(()=>Rj(o,i,l));case"logical":return r(()=>Pj(o,i,l));case"matrices":return r(()=>Fj(o,i,l));case"normalization":return r(()=>Oj(o,i,l));case"reduction":return r(()=>Mj(o,i,l));case"slice_join":return r(()=>zj(o,i,l));case"sparse":return r(()=>Lj(o,i,l));case"spectral":return r(()=>Bj(o,i,l));case"string":return r(()=>Wj(o,i,l));case"transformation":return r(()=>Vj(o,i,l));case"hash_table":return Dj(o,i,l,s);case"custom":let u=Sk(o.op);if(u&&u.customExecutor)return u.customExecutor(new yj(o,i,l));throw TypeError(`Custom op ${o.op} is not registered.`);default:throw TypeError(`Unknown op '${o.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`)}})(e,t,n);return v.isPromise(a)?a.then(o=>[].concat(o)):[].concat(a)}var r7=class{constructor(e={},t={},n={},s={}){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=n,this.functionMap=s,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}newFrame(e,t){return{id:e,frameName:t,iterationId:0}}set currentContext(e){this.contexts!==e&&(this.contexts=e,this.generateCurrentContextIds())}get currentContext(){return this.contexts}get currentContextId(){return this._currentContextIds[0]}get currentContextIds(){return this._currentContextIds}generateCurrentContextIds(){let e=[];for(let t=0;t<this.contexts.length-1;t++){let n=this.contexts.slice(0,this.contexts.length-t);e.push(this.contextIdforContexts(n))}e.push(""),this._currentContextIds=e}contextIdforContexts(e){return e?e.map(t=>t.id===0&&t.iterationId===0?"":`${t.frameName}-${t.iterationId}`).join("/"):""}enterFrame(e){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,e)),this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)))}exitFrame(){if(this.contexts&&this.contexts.length>1)this.contexts=this.contexts.slice(),this.contexts.splice(-1),this.currentContextIds.shift();else throw new Error("Cannot exit frame, the context is empty")}nextIteration(){if(this.contexts&&this.contexts.length>0){this.contexts=this.contexts.slice(),this.lastId++;let e=Object.assign({},this.contexts[this.contexts.length-1]);e.iterationId+=1,e.id=this.lastId,this.contexts.splice(-1,1,e),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}else throw new Error("Cannot increase frame iteration, the context is empty")}getWeight(e){return this.weightMap[e]}addTensorArray(e){this.tensorArrayMap[e.id]=e}getTensorArray(e){return this.tensorArrayMap[e]}addTensorList(e){this.tensorListMap[e.id]=e}getTensorList(e){return this.tensorListMap[e]}dispose(e){for(let t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(let t in this.tensorListMap)this.tensorListMap[t].clearAndClose(e)}};function a7(e,t,n,s){let r=new Set,a=[],o=null,i=null,l=new Set,u=Object.keys(e).map(d=>Ss(d)[0]),c=[];s!=null&&(c=s.map(d=>Ss(d.name)[0]));let p=[...t];for(;p.length>0;){let d=p.pop();if((qk(d)||qj(d)||Xj(d))&&o==null&&(o=d,i=o.children.map(h=>h.name).filter(h=>r.has(h))),r.add(d.name),n[d.name]==null&&u.indexOf(d.name)===-1&&c.indexOf(d.name)===-1){if(d.inputs.length===0){a.push(d.name);continue}d.inputs.forEach(h=>{l.has(h.name)||(l.add(h.name),p.push(h))})}}return{inputs:e,outputs:t,usedNodes:r,missingInputs:a,dynamicNode:o,syncInputs:i}}function Uj(e,t,n){let{usedNodes:s,inputs:r}=n,a=[],o=Object.keys(r).map(c=>Ss(c)[0]).map(c=>e.nodes[c]),i=e.initNodes;o.forEach(c=>{s.has(c.name)&&a.push(c)}),e.weights.forEach(c=>{s.has(c.name)&&a.push(c)}),i!=null&&i.forEach(c=>{s.has(c.name)&&a.push(c)});let l=new Set,u=[];for(;a.length>0;){let c=a.pop();l.add(c.name),t[c.name]||u.push(c),c.children.forEach(p=>{!l.has(p.name)&&s.has(p.name)&&p.inputs.every(d=>l.has(d.name))&&a.push(p)})}return u}var Gj=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],Hj=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],jj=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function qk(e){return Gj.indexOf(e.op)>=0}function qj(e){return Hj.indexOf(e.op)>=0}function Xj(e){return jj.indexOf(e.op)>=0}var Q3=class{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this.intermediateTensors={},this.keepTensorForDebug=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,e.functions!=null&&Object.keys(e.functions).forEach(n=>{this._functionExecutorMap[n]=new Q3(e.functions[n],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){let t=Object.keys(e).map(n=>e[n].map(s=>s.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(e=>e.signatureKey||e.name)}get outputNodes(){return this._outputs.map(e=>{let t=e.signatureKey||e.name;return e.defaultOutput?`${t}:${e.defaultOutput}`:t})}get functions(){return Object.keys(this._functions).reduce((e,t)=>(e[t]=this._functions[t].signature,e),{})}getCompilationKey(e,t){let n=e.map(r=>r.name).sort(),s=t.map(r=>r.name).sort();return n.join(this.SEPERATOR)+"--"+s.join(this.SEPERATOR)}compile(e,t){let n=a7(e,t,this.weightMap,this._initNodes),{missingInputs:s,dynamicNode:r,syncInputs:a}=n;if(r!=null)throw new Error(`This execution contains the node '${r.name}', which has the dynamic op '${r.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${a}]`);if(s.length>0){let o=t.map(l=>l.name),i=Object.keys(e);throw new Error(`Cannot compute the outputs [${o}] from the provided inputs [${i}]. Missing the following inputs: [${s}]`)}return Uj(this.graph,this.weightMap,n)}execute(e,t){e=this.mapInputs(e);let n=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let s=n.map(c=>this.graph.nodes[Ss(c)[0]]),r=t.map(c=>Ss(c)[0]),a=r.map(c=>this.graph.nodes[c]);this.resetIntermediateTensors(),a.length===0&&(a=this._outputs);let o=this.getCompilationKey(s,a),i=this.compiledMap.get(o);i==null&&(i=this.compile(e,a),this.compiledMap.set(o,i));let l={},u={};return J(()=>{let c=new r7(this.weightMap,l,u,this.functionExecutorMap),p=Object.assign({},this.weightMap);Object.keys(e).forEach(f=>{let[m,g]=Ss(f),y=[];y[g]=e[f],p[m]=y});let d=this.getFrozenTensorIds(p),h={};for(let f=0;f<i.length;f++){let m=i[f];if(!p[m.name]){let g=s7(m,p,c,this._resourceManager);if(v.isPromise(g))throw new Error(`The execution of the op '${m.op}' returned a promise. Please use model.executeAsync() instead.`);p[m.name]=g,this.checkTensorForDisposal(m.name,m,p,c,d,r,h)}}return this.parent==null&&c.dispose(d),t.map(f=>Jn(f,p,c))})}getFrozenTensorIds(e){let t=[].concat.apply([],Object.keys(e).map(n=>e[n]).map(n=>n.map(s=>s.id)));return new Set(t)}checkTensorForDisposal(e,t,n,s,r,a,o){t.category==="control"||a.indexOf(e)!==-1||(n[e].forEach(i=>{i!=null&&(o[i.id]=(o[i.id]||0)+t.children.length)}),t.inputs.forEach(i=>{if(i.category!=="control"){let l=ZH(i.name,n,s);l!=null&&l.forEach(u=>{if(u&&!u.kept&&!r.has(u.id)){let c=o[u.id];if(c===1){if(!this.keepTensorForDebug)u.dispose();else{let[p,d]=Gr(t.name,s);this.intermediateTensors[p]?this.intermediateTensors[p][d]=u:(this.intermediateTensors[p]=[],this.intermediateTensors[p][d]=u)}delete o[u.id]}else c!=null&&o[u.id]--}})}}))}async executeAsync(e,t){return this._executeAsync(e,t)}disposeIntermediateTensors(){!this.intermediateTensors||(Object.keys(this.intermediateTensors).forEach(e=>this.intermediateTensors[e].forEach(t=>t.dispose())),this.disposeTensorsMap())}disposeTensorsMap(){!this.tensorsMap||Object.keys(this.tensorsMap).forEach(e=>{this.tensorsMap[e].forEach(n=>{n&&!n.kept&&!n.isDisposed&&!this.keepIds.has(n.id)&&n.dispose()})})}getIntermediateTensors(){return this.tensorsMap}resetIntermediateTensors(){for(let e in this.intermediateTensors)this.intermediateTensors[e].forEach(t=>t.dispose()),delete this.intermediateTensors[e]}async _executeAsync(e,t,n=!1,s={},r={}){n||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));try{this.keepTensorForDebug=Z().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(u){console.warn(u.message)}this.resetIntermediateTensors();let a=new r7(this.weightMap,s,r,this.functionExecutorMap);this.tensorsMap=await this.executeWithControlFlow(e,a,t,n);let o=t.map(u=>Jn(u,this.tensorsMap,a)),i=o.map(u=>u.id),l=Object.keys(e).map(u=>e[u].id);return this.keepIds=new Set([...i,...l,...this.weightIds]),this.keepTensorForDebug||this.disposeTensorsMap(),this.parent==null&&a.dispose(this.keepIds),o}async executeFunctionAsync(e,t,n){let s=e.reduce((r,a,o)=>(r[this.inputs[o].name]=a,r),{});return this._executeAsync(s,this.outputNodes,!0,t,n)}async executeWithControlFlow(e,t,n,s){let r=Object.keys(e),a=r.map(x=>this.graph.nodes[Ss(x)[0]]),o=n.map(x=>Ss(x)[0]),i=o.map(x=>this.graph.nodes[x]);i.length===0&&(i=this._outputs);let{usedNodes:l,missingInputs:u,dynamicNode:c,syncInputs:p}=a7(e,i,this.weightMap,this._initNodes),d=[...a,...this.graph.weights,...this._initNodes||[]].map(x=>({node:x,contexts:t.currentContext})),h=Object.assign({},this.weightMap);Object.keys(e).forEach(x=>{let[A,b]=Ss(x),w=[];w[b]=e[x],h[A]=w});let f={},m=this.getFrozenTensorIds(h),g={};for(;d.length>0;){let x=this.processStack(a,d,t,h,g,m,o,f,l);await Promise.all(x)}c==null&&!s&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let y=i.filter(x=>!qk(x)&&!Jn(x.name,h,t)).map(x=>x.name);if(y.length>0){let x="";throw c!=null&&(x=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${p}]`),new Error(`Cannot compute the outputs [${y}] from the provided inputs [${r}]. Consider providing the following inputs: [${u}]. ${x}`)}return h}processStack(e,t,n,s,r,a,o,i,l){let u=[];for(;t.length>0;){let c=t.pop();n.currentContext=c.contexts;let p="";if(c.node.op==="Enter"&&I("isConstant",c.node,s,n)&&([p]=Gr(c.node.name,n)),s[c.node.name]==null){let d=s7(c.node,s,n,this._resourceManager);p||([p]=Gr(c.node.name,n));let h=n.currentContext;v.isPromise(d)?u.push(d.then(f=>(s[p]=f,n.currentContext=h,this.checkTensorForDisposal(p,c.node,s,n,a,o,i),this.processChildNodes(c.node,t,n,s,r,l),f))):(s[p]=d,this.checkTensorForDisposal(p,c.node,s,n,a,o,i),this.processChildNodes(c.node,t,n,s,r,l))}else this.processChildNodes(c.node,t,n,s,r,l)}return u}processChildNodes(e,t,n,s,r,a){e.children.forEach(o=>{let[i]=Gr(o.name,n);r[i]||!a.has(o.name)||(o.op==="Merge"?o.inputNames.some(l=>!!Jn(l,s,n))&&(r[i]=!0,t.push({contexts:n.currentContext,node:o})):o.inputNames.every(l=>!!Jn(l,s,n))&&(r[i]=!0,t.push({contexts:n.currentContext,node:o})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[s]=Ss(t),r=this.graph.nodes[s];if(r.attrParams.shape&&r.attrParams.shape.value){let a=r.attrParams.shape.value,o=a.length===n.shape.length&&n.shape.every((i,l)=>a[l]===-1||a[l]===i);v.assert(o,()=>`The shape of dict['${r.name}'] provided in model.execute(dict) must be [${a}], but was [${n.shape}]`)}r.attrParams.dtype&&r.attrParams.dtype.value&&v.assert(n.dtype===r.attrParams.dtype.value,()=>`The dtype of dict['${r.name}'] provided in model.execute(dict) must be ${r.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let s=this._signature.inputs[n];t[s.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[s]=Ss(n);return this.graph.nodes[s]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map(t=>this._signature!=null&&this._signature.outputs!=null&&this._signature.outputs[t]!=null?this._signature.outputs[t].name:t,{})}checkOutputs(e){e.forEach(t=>{let[n]=Ss(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},Kj=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},Zj="?tfjs-format=file",Yj="model.json",$h=class{constructor(e,t={},n=Ts){this.modelUrl=e,this.loadOptions=t,this.version="n/a",this.io=n,t==null&&(this.loadOptions={}),this.resourceManager=new Kj}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=this.io.browserHTTPRequest(e,this.loadOptions);else{let t=this.io.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(this.io.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=this.handler.load();return v.isPromise(e)?e.then(t=>this.loadSync(t)):this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,n=this.artifacts.signature;if(this.artifacts.userDefinedMetadata!=null){let r=this.artifacts.userDefinedMetadata;r.signature!=null&&(n=r.signature),r.structuredOutputKeys!=null&&(this.structuredOutputKeys=r.structuredOutputKeys)}this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let s=this.io.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new Q3(Qv.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(s),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let r=Qv.Instance.transformGraph(e.modelInitializer);this.initializer=new Q3(r),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=this.io.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(n.length>1)throw new Error(`Found more than one (${n.length}) save handlers for URL '${e}'`);e=n[0]}if(e.save==null)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return e.save(this.artifacts)}predict(e,t){let n=this.execute(e,this.outputNodes);if(this.structuredOutputKeys){let s=n instanceof tt?[n]:n,r={};return s.forEach((a,o)=>r[this.structuredOutputKeys[o]]=a),r}return n}normalizeInputs(e){if(!(e instanceof tt)&&!Array.isArray(e))return e;if(e=Array.isArray(e)?e:[e],e.length!==this.inputNodes.length)throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,s)=>(t[n]=e[s],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}getIntermediateTensors(){return this.executor.getIntermediateTensors()}disposeIntermediateTensors(){this.executor.disposeIntermediateTensors()}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}};async function Jj(e,t={},n=Ts){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");t==null&&(t={}),t.fromTFHub&&typeof e=="string"&&(e=eq(e));let s=new $h(e,t,n);return await s.load(),s}function Qj(e){if(e==null)throw new Error("modelUrl in loadGraphModelSync() cannot be null. Please provide a url or an IOHandler that loads the model");if(!e.load)throw new Error(`modelUrl IO Handler ${e} has no load function`);let t=new $h(e);return t.load(),t}function eq(e){return e.endsWith("/")||(e=e+"/"),`${e}${Yj}${Zj}`}var tq="3.19.0",Xk={};Ve(Xk,{CSVDataset:()=>sI,Dataset:()=>Qc,FileDataSource:()=>cI,TextLineDataset:()=>nI,URLDataSource:()=>dI,array:()=>Iq,csv:()=>Fq,func:()=>Oq,generator:()=>Mq,microphone:()=>Lq,version_data:()=>Bq,webcam:()=>zq,zip:()=>Sq});var nq=uo(Wm()),sq=uo(Wm());function rq(e,t){return Em(e,t)}function Em(e,t,n=new Map,s=new Set){if(e==null)return null;if(typeof Blob=="function"&&e instanceof Blob)return e.slice();if(s.has(e))throw new Error("Circular references are not supported.");if(n.has(e))return n.get(e);let r=t(e);if(r.recurse&&r.value!==null)throw new Error("A deep map function may not return both a value and recurse=true.");if(r.recurse)if(ac(e)){let a=Array.isArray(e)?[]:{};s.add(e);for(let o in e){let i=e[o],l=Em(i,t,n,s);a[o]=l}return s.delete(e),e.__proto__&&(a.__proto__=e.__proto__),a}else throw new Error(`Can't recurse into non-iterable type: ${e}`);else return n.set(e,r.value),r.value}function aq(e,t=Zk){return Kk(e,t)}function Kk(e,t,n=new Set){let s=e[0];if(n.has(s))throw new Error("Circular references are not supported.");let r=t(e);if(r.recurse&&r.value!==null)throw new Error("A deep zip function may not return both a value and recurse=true.");if(r.recurse)if(ac(s)){let a=Array.isArray(s)?[]:{};n.add(s);for(let o in s){let i=e.map(u=>u[o]),l=Kk(i,t,n);a[o]=l}return n.delete(s),a}else throw new Error(`Can't recurse into non-iterable type: ${s}`);else return r.value}function Zk(e){return e===null?null:ac(e[0])?{value:null,recurse:!0}:{value:e,recurse:!1}}async function Yk(e,t){let n=new Map;Em(e,t,n);for(let r of Array.from(n.keys())){let a=n.get(r);if(v.isPromise(a)){let o=await a;n.set(r,o)}}return Em(e,t,n)}function ac(e){let t=!1;if(Z().get("IS_BROWSER"))t=e instanceof TextDecoder;else{let{StringDecoder:n}=Y7();t=e instanceof n}return e!=null&&!ArrayBuffer.isView(e)&&(Array.isArray(e)||typeof e=="object"&&!(e instanceof tt)&&!(e instanceof Promise)&&!t)}function oq(e){return e==null||iq(e)||Array.isArray(e)||typeof e=="object"&&e instanceof tt||v.isTypedArray(e)}function iq(e){return e===null||typeof e!="object"&&typeof e!="function"}function lq(e){return rq(e,uq)}function uq(e){return e instanceof tt?{value:e.clone(),recurse:!1}:ac(e)?{value:null,recurse:!0}:{value:e,recurse:!1}}var Jk=class{constructor(e){if(this.capacity=e,this.begin=0,this.end=0,e==null)throw new RangeError("Can't create a ring buffer of unknown capacity.");if(e<1)throw new RangeError("Can't create ring buffer of capacity < 1.");this.data=new Array(e),this.doubledCapacity=2*e}wrap(e){for(;e<0;)e+=this.doubledCapacity;return e%this.doubledCapacity}get(e){if(e<0)throw new RangeError("Can't get item at a negative index.");return this.data[e%this.capacity]}set(e,t){if(e<0)throw new RangeError("Can't set item at a negative index.");this.data[e%this.capacity]=t}length(){let e=this.end-this.begin;return e<0&&(e=this.doubledCapacity+e),e}isFull(){return this.length()===this.capacity}isEmpty(){return this.length()===0}push(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.set(this.end,e),this.end=this.wrap(this.end+1)}pushAll(e){for(let t of e)this.push(t)}pop(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");this.end=this.wrap(this.end-1);let e=this.get(this.end);return this.set(this.end,void 0),e}unshift(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.begin=this.wrap(this.begin-1),this.set(this.begin,e)}shift(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let e=this.get(this.begin);return this.set(this.begin,void 0),this.begin=this.wrap(this.begin+1),e}shuffleExcise(e){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let t=this.wrap(this.begin+e),n=this.get(t);return this.set(t,this.pop()),n}},vx=class extends Jk{constructor(){super(vx.INITIAL_CAPACITY)}isFull(){return!1}push(e){super.isFull()&&this.expand(),super.push(e)}unshift(e){super.isFull()&&this.expand(),super.unshift(e)}expand(){let e=this.capacity*2,t=new Array(e),n=this.length();for(let s=0;s<n;s++)t[s]=this.get(this.wrap(this.begin+s));this.data=t,this.capacity=e,this.doubledCapacity=2*this.capacity,this.begin=0,this.end=n}};vx.INITIAL_CAPACITY=32;function Qk(e){return new pq(e)}function wx(e){return new hq(e)}function cq(e,t){return new eI(e,t)}function dq(e,t=ja.FAIL){return new wq(e,t)}var wn=class{async toArray(){let e=[],t=await this.next();for(;!t.done;)e.push(t.value),t=await this.next();return e}async toArrayForTest(){let e=this.prefetch(100),t=[],n=await e.next();for(;!n.done;)t.push(n.value),n=await e.next();return t}async resolveFully(){let e=await this.next();for(;!e.done;)e=await this.next()}async resolveWhile(e){let t=await this.next(),n=e(t.value);for(;!t.done&&n;)t=await this.next(),n=e(t.value)}handleErrors(e){return new bq(this,e)}filter(e){return new Aq(this,e)}map(e){return new xq(this,e)}mapAsync(e){return new o7(this,e)}serialMapAsync(e){return new o7(this,e).serial()}flatmap(e){return new vq(this,e)}async forEachAsync(e){return this.map(e).resolveFully()}async serialForEach(e){return this.serialMapAsync(e).resolveWhile(t=>t===!0)}rowMajorBatch(e,t=!0){return new yq(this,e,t)}columnMajorBatch(e,t=!0,n=Zk){return this.rowMajorBatch(e,t).map(r=>aq(r,n))}concatenate(e,t){return new eI(Qk([this,e]),t)}take(e){return e<0||e==null?this:new gq(this,e)}skip(e){return e<0||e==null?this:new mq(this,e)}prefetch(e){return new tI(this,e)}shuffle(e,t){return new kq(this,e,t)}serial(){return new fq(this)}},pq=class extends wn{constructor(e){super(),this.items=e,this.trav=0}summary(){return`Array of ${this.items.length} items`}async next(){if(this.trav>=this.items.length)return{value:null,done:!0};let e=this.items[this.trav];return this.trav++,{value:lq(e),done:!1}}},hq=class extends wn{constructor(e){super(),this.nextFn=e}summary(){return"Function call"}async next(){try{return this.nextFn()}catch(e){throw e.message=`Error thrown while iterating through a dataset: ${e.message}`,e}}},fq=class extends wn{constructor(e){super(),this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},mq=class extends wn{constructor(e,t){super(),this.upstream=e,this.maxCount=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++<this.maxCount;){let e=await this.upstream.next();if(e.done)return e;ne(e.value)}return this.upstream.next()}},gq=class extends wn{constructor(e,t){super(),this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},yq=class extends wn{constructor(e,t,n=!0){super(),this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},Aq=class extends wn{constructor(e,t){super(),this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;ne(e.value)}}},xq=class extends wn{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Tr.getTensorsInContainer(e.value),n=this.transform(e.value),s=Tr.getTensorsInContainer(n);for(let r of t)Tr.isTensorInList(r,s)||r.dispose();return{value:n,done:!1}}},bq=class extends wn{constructor(e,t){super(),this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},o7=class extends wn{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Tr.getTensorsInContainer(e.value),n=await this.transform(e.value),s=Tr.getTensorsInContainer(n);for(let r of t)Tr.isTensorInList(r,s)||r.dispose();return{value:n,done:!1}}},kx=class extends wn{constructor(){super(),this.outputQueue=new vx,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},vq=class extends kx{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=Tr.getTensorsInContainer(e.value),n=this.transform(e.value),s=Tr.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let r of t)Tr.isTensorInList(r,s)||r.dispose();return!0}},eI=class extends wn{constructor(e,t){super(),this.baseErrorHandler=t,this.lastRead=null,this.iterator=null,this.moreIterators=e}summary(){return"TODO: fill in upstream of chained summaries -> Chained"}async next(){return this.lastRead=this.readFromChain(this.lastRead),this.lastRead}async readFromChain(e){if(await e,this.iterator==null){let n=await this.moreIterators.next();if(n.done)return{value:null,done:!0};this.iterator=n.value,this.baseErrorHandler!=null&&(this.iterator=this.iterator.handleErrors(this.baseErrorHandler))}let t=await this.iterator.next();return t.done?(this.iterator=null,this.readFromChain(e)):t}},ja;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(ja||(ja={}));var wq=class extends wn{constructor(e,t=ja.FAIL){super(),this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,n=0;function s(a){return a instanceof wn?{value:a.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let r=await Yk(this.iterators,s);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case ja.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case ja.SHORTEST:return{value:null,done:!0};case ja.LONGEST:default:}return this.count++,{value:r,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},tI=class extends wn{constructor(e,t){super(),this.upstream=e,this.bufferSize=t,this.buffer=new Jk(t)}summary(){return`${this.upstream.summary()} -> Prefetch`}refill(){for(;!this.buffer.isFull();){let e=this.upstream.next();this.buffer.push(e)}}next(){return this.refill(),this.buffer.shift()}},kq=class extends tI{constructor(e,t,n){super(e,t),this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=sq.alea(n||v.now().toString()),this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}randomInt(e){return Math.floor(this.random()*e)}chooseIndex(){return this.randomInt(this.buffer.length())}async serialNext(){for(this.upstreamExhausted||this.refill();!this.buffer.isEmpty();){let e=this.chooseIndex(),t=await this.buffer.shuffleExcise(e);if(t.done)this.upstreamExhausted=!0;else return this.refill(),t}return{value:null,done:!0}}},Qc=class{constructor(){this.size=null}batch(e,t=!0){let n=this;v.assert(e>0,()=>`batchSize needs to be positive, but it is
-      ${e}`);let s;return this.size===1/0||this.size==null?s=this.size:t?s=Math.ceil(this.size/e):s=Math.floor(this.size/e),Is(async()=>(await n.iterator()).columnMajorBatch(e,t,Cq),s)}concatenate(e){let t=this,n;return this.size===1/0||e.size===1/0?n=1/0:this.size!=null&&e.size!=null?n=this.size+e.size:n=null,Is(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===1/0?n=1/0:n=null,Is(async()=>(await t.iterator()).filter(s=>J(()=>e(s))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return Is(async()=>(await t.iterator()).map(n=>J(()=>e(n))),this.size)}mapAsync(e){let t=this;return Is(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return Is(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,n;return this.size!=null&&e>0?n=this.size*e:e===0?n=0:this.size!=null&&(e===void 0||e<0)?n=1/0:n=null,Is(async()=>{let s=wx(async()=>({value:await t.iterator(),done:!1}));return cq(s.take(e))},n)}skip(e){let t=this,n;return this.size!=null&&e>=0&&this.size>=e?n=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?n=0:n=null,Is(async()=>(await t.iterator()).skip(e),n)}shuffle(e,t,n=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified.  If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let s=this,r=nq.alea(t||v.now().toString());return Is(async()=>{let a=r.int32();return n&&(a+=r.int32()),(await s.iterator()).shuffle(e,a.toString())},this.size)}take(e){let t=this,n;return this.size!=null&&this.size>e?n=e:this.size!=null&&this.size<=e?n=this.size:n=null,Is(async()=>(await t.iterator()).take(e),n)}async toArray(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};Qc.MAX_BUFFER_SIZE=1e4;function Is(e,t=null){return new class extends Qc{constructor(){super(...arguments),this.size=t}async iterator(){return e()}}}function Iq(e){return Is(async()=>Qk(e),e.length)}function Sq(e){if(!ac(e))throw new Error("The argument to zip() must be an object or array.");let t;if(Array.isArray(e))for(let n=0;n<e.length;n++)t=t==null?e[n].size:Math.min(t,e[n].size);else if(e instanceof Object)for(let n in e)t=t==null?e[n].size:Math.min(t,e[n].size);return Is(async()=>{let n=await Yk(e,s=>{if(s instanceof Qc)return{value:s.iterator(),recurse:!1};if(ac(s))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return dq(n,ja.SHORTEST)},t)}function Cq(e){if(e===null)return null;let t=e[0];return oq(t)?{value:Tq(e),recurse:!1}:{value:null,recurse:!0}}function Tq(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof tt?on(e):ft(e)}var nI=class extends Qc{constructor(e){super(),this.input=e}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
-`).map(s=>(s.endsWith("\r")&&(s=s.slice(0,-1)),s))}},jf='"',np=Symbol("out"),i7=Symbol("field"),qf=Symbol("quote"),h3=Symbol("quoteafterquote"),l7=Symbol("quoteinquote"),sI=class extends Qc{constructor(e,t){super(),this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new nI(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(v.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let e=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!e)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&e&&v.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((s,r)=>(s[r]=s[r]+1||1,s),{}),n=Object.keys(t).filter(s=>t[s]>1);if(v.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let s of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(s)===-1)throw new Error('The key "'+s+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let t=await(await this.base.iterator()).next();if(t.done)throw new Error("No data was found for CSV parsing.");let n=t.value;return this.parseRow(n,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),n={},s={};for(let r=0;r<this.fullColumnNames.length;r++){let a=this.fullColumnNames[r],o=this.columnConfigs?this.columnConfigs[a]:null;if(!(this.configuredColumnsOnly&&!o)){let i=t[r],l=null;if(i==="")if(o&&o.default!==void 0)l=o.default;else{if(o&&(o.required||o.isLabel))throw new Error(`Required column ${a} is empty in this line: ${e}`);l=void 0}else{let u=Number(i);if(isNaN(u))o&&o.dtype==="bool"?l=this.getBoolean(i):l=i;else if(!o||!o.dtype)l=u;else switch(o.dtype){case"float32":l=u;break;case"int32":l=Math.floor(u);break;case"bool":l=this.getBoolean(i);break;default:l=u}}o&&o.isLabel?s[a]=l:n[a]=l}}return Object.keys(s).length===0?n:{xs:n,ys:s}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let n=[],s=0,r=e.length,a=np;for(let o=0;o<r;o++)switch(a){case np:switch(e.charAt(o)){case jf:s=o+1,a=qf;break;case this.delimiter:if(s=o+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),a=np;break;default:a=i7,s=o;break}break;case i7:switch(e.charAt(o)){case this.delimiter:n.push(e.substring(s,o)),a=np,s=o+1;break;default:}break;case qf:switch(e.charAt(o)){case jf:a=h3;break;default:}break;case h3:switch(e.charAt(o)){case this.delimiter:n.push(e.substring(s,o-1)),a=np,s=o+1;break;case jf:a=qf;break;default:a=l7;break}break;case l7:switch(e.charAt(o)){case jf:a=qf;break;default:}break;default:}if(a===h3?n.push(e.substring(s,r-1)):n.push(e.substring(s)),t&&n.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},rI=class extends wn{constructor(e){super(),this.microphoneConfig=e,this.isClosed=!1,this.fftSize=e.fftSize||1024;let t=Math.log2(this.fftSize);if(this.fftSize<0||t<4||t>14||!Number.isInteger(t))throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);if(this.numFrames=e.numFramesPerSpectrogram||43,this.sampleRateHz=e.sampleRateHz,this.columnTruncateLength=e.columnTruncateLength||this.fftSize,this.audioTrackConstraints=e.audioTrackConstraints,this.smoothingTimeConstant=e.smoothingTimeConstant||0,this.includeSpectrogram=e.includeSpectrogram!==!1,this.includeWaveform=e.includeWaveform===!0,!this.includeSpectrogram&&!this.includeWaveform)throw new Error("Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.")}summary(){return"microphone"}static async create(e={}){if(!Z().get("IS_BROWSER"))throw new Error("microphone API is only supported in browser environment.");let t=new rI(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,n=await this.getAudioData();if(this.includeSpectrogram){let s=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(s,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let s=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(s,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],n=0;return new Promise(s=>{let r=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-1/0&&s({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(r),s({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,n=new Float32Array(e.length*t);return e.forEach((s,r)=>n.set(s,r*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),ft(n,t)}},aI=class extends wn{constructor(e,t){if(super(),this.webcamVideoElement=e,this.webcamConfig=t,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=Ft([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,s=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,r=(1-n)/2,a=(1-s)/2,o=r+n,i=s+a;this.cropBox=or([a,r,i,o],[1,4])}else this.cropBox=or([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(!Z().get("IS_BROWSER"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new aI(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&v.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(e){throw e.message=`Error thrown while initializing video stream: ${e.message}`,e}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(e){console.log(e),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(e=>{this.webcamVideoElement.onloadedmetadata=()=>{e()}})}async next(){if(this.isClosed)return{value:null,done:!0};let e;try{e=Ys.fromPixels(this.webcamVideoElement)}catch(t){throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(t)}`)}if(this.resize)try{return{value:this.cropAndResizeFrame(e),done:!1}}catch(t){throw new Error(`Error thrown cropping the video: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return J(()=>{let t=Kt(ge(e,"float32"),0),n;n=Ne.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let s=n.shape;return U(n,s.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(t=>t.stop());try{this.webcamVideoElement.srcObject=null}catch(t){console.log(t),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},oI=class{},iI=class extends wn{split(e){return new Nq(this,e)}},Nq=class extends iI{constructor(e,t){super(),this.upstream=e,this.impl=new Eq(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Eq=class extends kx{constructor(e,t){super(),this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},Rq=class extends wn{decodeUTF8(){return new _q(this)}},_q=class extends iI{constructor(e){super(),this.upstream=e,this.impl=new Dq(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Dq=class extends kx{constructor(e){if(super(),this.upstream=e,Z().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=Y7();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return Z().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},lI=class extends Rq{constructor(e,t={}){super(),this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(Z().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((t,n)=>{let s=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)t(new Uint8Array(this.file.slice(this.offset,s)));else{let r=new FileReader;r.onload=o=>{let i=r.result;if(i instanceof ArrayBuffer&&(i=new Uint8Array(i)),!(i instanceof Uint8Array))return n(new TypeError("FileReader returned unknown type."));t(i)},r.onabort=o=>n(new Error("Aborted")),r.onerror=o=>n(new Error(o.type));let a=this.file.slice(this.offset,s);r.readAsArrayBuffer(a)}this.offset=s}),done:!1}}};async function $q(e,t={},n){let s,r;typeof e=="string"?s=e:(s=e.url,r=Pq(e));let a=await(n||v.fetch)(s,r);if(a.ok){let o=new Uint8Array(await a.arrayBuffer());return new lI(o,t)}else throw new Error(a.statusText)}var Pq=e=>({method:e.method,headers:e.headers,body:e.body,mode:e.mode,credentials:e.credentials,cache:e.cache,redirect:e.redirect,referrer:e.referrer,integrity:e.integrity});function uI(e){return typeof e=="string"&&e.slice(0,7)==="file://"}var cI=class extends oI{constructor(e,t={}){super(),this.input=e,this.options=t}async iterator(){if(uI(this.input)&&Z().get("IS_NODE")){let e=xy();this.input=e.readFileSync(this.input.slice(7))}return new lI(this.input,this.options)}},dI=class extends oI{constructor(e,t={}){super(),this.url=e,this.fileOptions=t}async iterator(){return uI(this.url)?new cI(this.url,this.fileOptions).iterator():$q(this.url,this.fileOptions)}};function Fq(e,t={}){return new sI(new dI(e),t)}function Oq(e){let t=wx(e);return Is(async()=>t)}function Mq(e){return Is(async()=>{let t=await e();return wx(()=>t.next())})}async function zq(e,t){return aI.create(e,t)}async function Lq(e){return rI.create(e)}var Bq="3.19.0";function Ce(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&v.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the CPU backend.`)})}var Wq=dr.whereImpl,Ix=class extends cc{constructor(){super(),this.blockSize=48,this.firstUse=!0,this.data=new Mp(this,sn())}nextDataId(){return Ix.nextDataId++}write(e,t,n){this.firstUse&&(this.firstUse=!1,Z().get("IS_NODE")&&C.warn(`
+        ${s}, and tensor's shape is: ${e.shape}`);let a=e.shape.slice(1),o=Y3(a,n),i=s===0?0:e.size/s,l=J(()=>{let c=[];e=U(e,[1,s,i]);for(let p=0;p<t.length;++p){let d=p===0?0:r[p-1],h=[0,d,0],f=[1,t[p],i];c[p]=U(Oe(e,h,f),o)}return e.dispose(),c}),u=new sc([],n,e.dtype,t.length);for(let c=0;c<l.length;c++)u.setItem(c,l[c]);return u}var Sj=async(e,t,n)=>{switch(e.op){case"If":case"StatelessIf":{let s=I("thenBranch",e,t,n),r=I("elseBranch",e,t,n),a=I("cond",e,t,n),o=I("args",e,t,n);return(await a.data())[0]?n.functionMap[s].executeFunctionAsync(o,n.tensorArrayMap,n.tensorListMap):n.functionMap[r].executeFunctionAsync(o,n.tensorArrayMap,n.tensorListMap)}case"While":case"StatelessWhile":{let s=I("body",e,t,n),r=I("cond",e,t,n),a=I("args",e,t,n),o=await n.functionMap[r].executeFunctionAsync(a,n.tensorArrayMap,n.tensorListMap),i=a.map(c=>c.id),l=await o[0].data();o.forEach(c=>{!c.kept&&i.indexOf(c.id)===-1&&c.dispose()});let u=a;for(;l[0];){let c=u;u=await n.functionMap[s].executeFunctionAsync(u,n.tensorArrayMap,n.tensorListMap);let p=u.map(h=>h.id);c.forEach(h=>{!h.kept&&i.indexOf(h.id)===-1&&p.indexOf(h.id)===-1&&h.dispose()});let d=await n.functionMap[r].executeFunctionAsync(u,n.tensorArrayMap,n.tensorListMap);l=await d[0].data(),d.forEach(h=>{!h.kept&&i.indexOf(h.id)===-1&&p.indexOf(h.id)===-1&&h.dispose()})}return u}case"LoopCond":{let s=I("pred",e,t,n);return[ua(s)]}case"Switch":{let s=I("pred",e,t,n),r=I("data",e,t,n);return r.kept||(r=ua(r)),(await s.data())[0]?[void 0,r]:[r,void 0]}case"Merge":{let s=e.inputNames.find(r=>Jn(r,t,n)!==void 0);if(s){let r=Jn(s,t,n);return[ua(r)]}return}case"Enter":{let s=I("frameName",e,t,n),r=I("tensor",e,t,n);return n.enterFrame(s),[ua(r)]}case"Exit":{let s=I("tensor",e,t,n);return n.exitFrame(),[ua(s)]}case"NextIteration":{let s=I("tensor",e,t,n);return n.nextIteration(),[ua(s)]}case"TensorArrayV3":{let s=I("size",e,t,n),r=I("dtype",e,t,n),a=I("elementShape",e,t,n),o=I("dynamicSize",e,t,n),i=I("clearAfterRead",e,t,n),l=I("identicalElementShapes",e,t,n),u=I("name",e,t,n),c=new bj(u,r,s,a,l,o,i);return n.addTensorArray(c),[c.idTensor,Se(1)]}case"TensorArrayWriteV3":{let s=I("tensorArrayId",e,t,n),r=I("index",e,t,n),a=I("tensor",e,t,n),o=n.getTensorArray(s.id);return o.write(r,a),[o.idTensor]}case"TensorArrayReadV3":{let s=I("tensorArrayId",e,t,n),r=I("index",e,t,n);return[n.getTensorArray(s.id).read(r)]}case"TensorArrayGatherV3":{let s=I("tensorArrayId",e,t,n),r=I("indices",e,t,n),a=I("dtype",e,t,n);return[n.getTensorArray(s.id).gather(r,a)]}case"TensorArrayScatterV3":{let s=I("tensorArrayId",e,t,n),r=I("indices",e,t,n),a=I("tensor",e,t,n),o=n.getTensorArray(s.id);return o.scatter(r,a),[o.idTensor]}case"TensorArrayConcatV3":{let s=I("tensorArrayId",e,t,n),r=n.getTensorArray(s.id),a=I("dtype",e,t,n);return[r.concat(a)]}case"TensorArraySplitV3":{let s=I("tensorArrayId",e,t,n),r=I("tensor",e,t,n),a=I("lengths",e,t,n),o=n.getTensorArray(s.id);return o.split(a,r),[o.idTensor]}case"TensorArraySizeV3":{let s=I("tensorArrayId",e,t,n),r=n.getTensorArray(s.id);return[Se(r.size(),"int32")]}case"TensorArrayCloseV3":{let s=I("tensorArrayId",e,t,n),r=n.getTensorArray(s.id);return r.clearAndClose(),[r.idTensor]}case"TensorListSetItem":{let s=I("tensorListId",e,t,n),r=I("index",e,t,n),a=I("tensor",e,t,n),o=n.getTensorList(s.id);return o.setItem(r,a),[o.idTensor]}case"TensorListGetItem":{let s=I("tensorListId",e,t,n),r=I("index",e,t,n),a=I("elementShape",e,t,n),o=I("elementDType",e,t,n);return[n.getTensorList(s.id).getItem(r,a,o)]}case"TensorListScatterV2":case"TensorListScatter":{let s=I("indices",e,t,n),r=I("tensor",e,t,n),a=I("elementShape",e,t,n),o=I("numElements",e,t,n),i=kj(r,s,a,o);return n.addTensorList(i),[i.idTensor]}case"TensorListReserve":case"EmptyTensorList":{let s=I("elementShape",e,t,n),r=I("elementDType",e,t,n),a;e.op==="TensorListReserve"?a="numElements":a="maxNumElements";let o=I(a,e,t,n),i=e.op==="TensorListReserve"?-1:o,l=wj(s,r,o,i);return n.addTensorList(l),[l.idTensor]}case"TensorListGather":{let s=I("tensorListId",e,t,n),r=I("indices",e,t,n),a=I("elementShape",e,t,n),o=I("elementDType",e,t,n);return[n.getTensorList(s.id).gather(r,o,a)]}case"TensorListStack":{let s=I("tensorListId",e,t,n),r=I("elementShape",e,t,n),a=I("elementDType",e,t,n),o=I("numElements",e,t,n);return[n.getTensorList(s.id).stack(r,a,o)]}case"TensorListFromTensor":{let s=I("tensor",e,t,n),r=I("elementShape",e,t,n),a=I("elementDType",e,t,n),o=vj(s,r,a);return n.addTensorList(o),[o.idTensor]}case"TensorListConcat":case"TensorListConcatV2":{let s=I("tensorListId",e,t,n),r=n.getTensorList(s.id),a=I("dtype",e,t,n),o=I("elementShape",e,t,n);return[r.concat(a,o)]}case"TensorListPushBack":{let s=I("tensorListId",e,t,n),r=I("tensor",e,t,n),a=n.getTensorList(s.id);return a.pushBack(r),[a.idTensor]}case"TensorListPopBack":{let s=I("tensorListId",e,t,n),r=I("elementShape",e,t,n),a=I("elementDType",e,t,n);return[n.getTensorList(s.id).popBack(r,a)]}case"TensorListSplit":{let s=I("tensor",e,t,n),r=I("elementShape",e,t,n),a=I("lengths",e,t,n),o=Ij(s,a,r);return n.addTensorList(o),[o.idTensor]}case"TensorListLength":{let s=I("tensorListId",e,t,n),r=n.getTensorList(s.id);return[Se(r.size(),"int32")]}case"TensorListResize":{let s=I("tensorListId",e,t,n),r=I("size",e,t,n),o=n.getTensorList(s.id).resize(r);return n.addTensorList(o),[o.idTensor]}default:throw TypeError(`Node type ${e.op} is not implemented`)}};function n7(e,t,n){let[s,r]=I("fusedOps",e,t,n),a=s==="biasadd",o=!a,i=r==="prelu",l=s==="fusedbatchnorm",u=I("numArgs",e,t,n);if(a){if(i&&u!==2)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&a&&u!==1)throw new Error("FusedConv2d and DepthwiseConv2d with BiasAdd must have one extra argument: bias.")}if(l)throw new Error("FusedConv2d and DepthwiseConv2d with FusedBatchNorm is not supported");let c=I("strides",e,t,n),p=em(e,t,n),d=I("dataFormat",e,t,n).toUpperCase(),h=I("dilations",e,t,n),[f,m]=I("args",e,t,n);o&&(m=f,f=void 0);let g=I("leakyreluAlpha",e,t,n);return{stride:c,pad:p,dataFormat:d,dilations:h,biasArg:f,preluArg:m,activationFunc:r,leakyreluAlpha:g}}var Cj=(e,t,n,s=En)=>{switch(e.op){case"Conv1D":{let r=I("stride",e,t,n),a=I("pad",e,t,n),o=I("dataFormat",e,t,n).toUpperCase(),i=I("dilation",e,t,n);return[s.conv1d(I("x",e,t,n),I("filter",e,t,n),r,a,o,i)]}case"Conv2D":{let r=I("strides",e,t,n),a=em(e,t,n),o=I("dataFormat",e,t,n).toUpperCase(),i=I("dilations",e,t,n);return[s.conv2d(I("x",e,t,n),I("filter",e,t,n),[r[1],r[2]],a,o,[i[1],i[2]])]}case"_FusedConv2D":{let{stride:r,pad:a,dataFormat:o,dilations:i,biasArg:l,preluArg:u,activationFunc:c,leakyreluAlpha:p}=n7(e,t,n);return[s.fused.conv2d({x:I("x",e,t,n),filter:I("filter",e,t,n),strides:[r[1],r[2]],pad:a,dataFormat:o,dilations:[i[1],i[2]],bias:l,activation:c,preluActivationWeights:u,leakyreluAlpha:p})]}case"FusedDepthwiseConv2dNative":{let{stride:r,pad:a,dataFormat:o,dilations:i,biasArg:l,preluArg:u,activationFunc:c,leakyreluAlpha:p}=n7(e,t,n);return[s.fused.depthwiseConv2d({x:I("x",e,t,n),filter:I("filter",e,t,n),strides:[r[1],r[2]],pad:a,dataFormat:o,dilations:[i[1],i[2]],bias:l,activation:c,preluActivationWeights:u,leakyreluAlpha:p})]}case"Conv2DBackpropInput":case"Conv2dTranspose":{let r=I("outputShape",e,t,n),a=I("strides",e,t,n),o=em(e,t,n);return[s.conv2dTranspose(I("x",e,t,n),I("filter",e,t,n),r,[a[1],a[2]],o)]}case"DepthwiseConv2dNative":case"DepthwiseConv2d":{let r=I("strides",e,t,n),a=em(e,t,n),o=I("dilations",e,t,n),i=I("dataFormat",e,t,n).toUpperCase();return[s.depthwiseConv2d(I("input",e,t,n),I("filter",e,t,n),[r[1],r[2]],a,i,[o[1],o[2]])]}case"Conv3D":{let r=I("strides",e,t,n),a=I("pad",e,t,n),o=I("dataFormat",e,t,n).toUpperCase(),i=I("dilations",e,t,n);return[s.conv3d(I("x",e,t,n),I("filter",e,t,n),[r[1],r[2],r[3]],a,o,[i[1],i[2],i[3]])]}case"AvgPool":{let r=I("strides",e,t,n),a=I("pad",e,t,n),o=I("kernelSize",e,t,n);return[s.avgPool(I("x",e,t,n),[o[1],o[2]],[r[1],r[2]],a)]}case"MaxPool":{let r=I("strides",e,t,n),a=I("pad",e,t,n),o=I("kernelSize",e,t,n);return[s.maxPool(I("x",e,t,n),[o[1],o[2]],[r[1],r[2]],a)]}case"MaxPoolWithArgmax":{let r=I("strides",e,t,n),a=I("pad",e,t,n),o=I("kernelSize",e,t,n),i=I("includeBatchInIndex",e,t,n),{result:l,indexes:u}=s.maxPoolWithArgmax(I("x",e,t,n),[o[1],o[2]],[r[1],r[2]],a,i);return[l,u]}case"AvgPool3D":{let r=I("strides",e,t,n),a=I("pad",e,t,n),o=I("kernelSize",e,t,n);return[s.avgPool3d(I("x",e,t,n),[o[1],o[2],o[3]],[r[1],r[2],r[3]],a)]}case"MaxPool3D":{let r=I("strides",e,t,n),a=I("pad",e,t,n),o=I("kernelSize",e,t,n);return[s.maxPool3d(I("x",e,t,n),[o[1],o[2],o[3]],[r[1],r[2],r[3]],a)]}case"Dilation2D":{let r=I("strides",e,t,n),a=I("pad",e,t,n),o=I("dilations",e,t,n),i=r[1],l=r[2],u=o[1],c=o[2];return[s.dilation2d(I("x",e,t,n),I("filter",e,t,n),[i,l],a,[u,c],"NHWC")]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Tj=(e,t,n,s=En)=>{switch(e.op){case"Fill":{let r=I("shape",e,t,n),a=I("dtype",e,t,n),o=I("value",e,t,n);return[s.fill(r,o,a)]}case"LinSpace":{let r=I("start",e,t,n),a=I("stop",e,t,n),o=I("num",e,t,n);return[s.linspace(r,a,o)]}case"Multinomial":{let r=I("logits",e,t,n),a=I("numSamples",e,t,n),o=I("seed",e,t,n);return[s.multinomial(r,a,o)]}case"OneHot":{let r=I("indices",e,t,n),a=I("depth",e,t,n),o=I("onValue",e,t,n),i=I("offValue",e,t,n);return[s.oneHot(r,a,o,i)]}case"Ones":return[s.ones(I("shape",e,t,n),I("dtype",e,t,n))];case"OnesLike":return[s.onesLike(I("x",e,t,n))];case"RandomStandardNormal":return[s.randomStandardNormal(I("shape",e,t,n),I("dtype",e,t,n),I("seed",e,t,n))];case"RandomUniform":return[s.randomUniform(I("shape",e,t,n),I("minval",e,t,n),I("maxval",e,t,n),I("dtype",e,t,n))];case"Range":{let r=I("start",e,t,n),a=I("stop",e,t,n),o=I("step",e,t,n);return[s.range(r,a,o,I("dtype",e,t,n))]}case"TruncatedNormal":{let r=I("shape",e,t,n),a=I("mean",e,t,n),o=I("stdDev",e,t,n),i=I("seed",e,t,n);return[s.truncatedNormal(r,a,o,I("dtype",e,t,n),i)]}case"Zeros":return[s.zeros(I("shape",e,t,n),I("dtype",e,t,n))];case"ZerosLike":return[s.zerosLike(I("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function d3(e,t,n){let s=I("boxes",e,t,n),r=I("scores",e,t,n),a=I("maxOutputSize",e,t,n),o=I("iouThreshold",e,t,n),i=I("scoreThreshold",e,t,n),l=I("softNmsSigma",e,t,n);return{boxes:s,scores:r,maxOutputSize:a,iouThreshold:o,scoreThreshold:i,softNmsSigma:l}}var Nj=async(e,t,n,s,r=En)=>{switch(e.op){case"NonMaxSuppressionV5":{let{boxes:a,scores:o,maxOutputSize:i,iouThreshold:l,scoreThreshold:u,softNmsSigma:c}=d3(e,t,n),p=await r.image.nonMaxSuppressionWithScoreAsync(a,o,i,l,u,c);return[p.selectedIndices,p.selectedScores]}case"NonMaxSuppressionV4":{let{boxes:a,scores:o,maxOutputSize:i,iouThreshold:l,scoreThreshold:u}=d3(e,t,n),c=I("padToMaxOutputSize",e,t,n),p=await r.image.nonMaxSuppressionPaddedAsync(a,o,i,l,u,c);return[p.selectedIndices,p.validOutputs]}case"NonMaxSuppressionV3":case"NonMaxSuppressionV2":{let{boxes:a,scores:o,maxOutputSize:i,iouThreshold:l,scoreThreshold:u}=d3(e,t,n);return[await r.image.nonMaxSuppressionAsync(a,o,i,l,u)]}case"Where":{let a=r.cast(I("condition",e,t,n),"bool"),o=[await r.whereAsync(a)];return a.dispose(),o}case"ListDiff":return r.setdiff1dAsync(I("x",e,t,n),I("y",e,t,n));default:throw TypeError(`Node type ${e.op} is not implemented`)}},Ej=(e,t,n,s=En)=>{switch(e.op){case"LowerBound":{let r=I("sortedSequence",e,t,n),a=I("values",e,t,n);return[s.lowerBound(r,a)]}case"TopKV2":{let r=I("x",e,t,n),a=I("k",e,t,n),o=I("sorted",e,t,n),i=s.topk(r,a,o);return[i.values,i.indices]}case"UpperBound":{let r=I("sortedSequence",e,t,n),a=I("values",e,t,n);return[s.upperBound(r,a)]}case"Unique":{let r=I("x",e,t,n),a=s.unique(r);return[a.values,a.indices]}case"UniqueV2":{let r=I("x",e,t,n),a=I("axis",e,t,n),o=s.unique(r,a);return[o.values,o.indices]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Rj=(e,t,n,s=En)=>{switch(e.op){case"Const":return t[e.name];case"PlaceholderWithDefault":let r=I("default",e,t,n);return[Jn(e.name,t,n)||r];case"Placeholder":return[Jn(e.name,t,n)];case"Identity":case"StopGradient":case"FakeQuantWithMinMaxVars":{let c=I("x",e,t,n);return[ua(c)]}case"IdentityN":return I("x",e,t,n).map(c=>ua(c));case"Snapshot":let a=I("x",e,t,n);return[ua(a)];case"Shape":return[s.tensor1d(I("x",e,t,n).shape,"int32")];case"ShapeN":return I("x",e,t,n).map(c=>s.tensor1d(c.shape));case"Size":return[s.scalar(I("x",e,t,n).size,"int32")];case"Rank":return[s.scalar(I("x",e,t,n).rank,"int32")];case"NoOp":return[s.scalar(1)];case"Print":let o=I("x",e,t,n),i=I("data",e,t,n),l=I("message",e,t,n),u=I("summarize",e,t,n);console.warn("The graph has a tf.print() operation,usually used for debugging, which slows down performance."),console.log(l);for(let c=0;c<i.length;c++)console.log(Array.prototype.slice.call(i[c].dataSync()).slice(0,u));return[o];default:throw TypeError(`Node type ${e.op} is not implemented`)}},_j=class{constructor(e,t){this.keyDType=e,this.valueDType=t,this.handle=Se(0),this.tensorMap=new Map,bn(this.handle)}get id(){return this.handle.id}clearAndClose(){this.tensorMap.forEach(e=>e.dispose()),this.tensorMap.clear(),this.handle.dispose()}size(){return this.tensorMap.size}tensorSize(){return Se(this.size(),"int32")}async import(e,t){this.checkKeyAndValueTensor(e,t);let n=await e.data();return this.tensorMap.forEach(s=>s.dispose()),this.tensorMap.clear(),J(()=>{let s=es(t),r=n.length,a=s.length;v.assert(r===a,()=>`The number of elements doesn't match, keys has ${r} elements, the values has ${a} elements.`);for(let o=0;o<r;o++){let i=n[o],l=s[o];bn(l),this.tensorMap.set(i,l)}return this.handle})}async find(e,t){this.checkKeyAndValueTensor(e,t);let n=await e.data();return J(()=>{let s=[];for(let r=0;r<n.length;r++){let a=n[r],o=this.findWithDefault(a,t);s.push(o)}return on(s)})}findWithDefault(e,t){let n=this.tensorMap.get(e);return n!=null?n:t}checkKeyAndValueTensor(e,t){if(e.dtype!==this.keyDType)throw new Error(`Expect key dtype ${this.keyDType}, but got ${e.dtype}`);if(t.dtype!==this.valueDType)throw new Error(`Expect value dtype ${this.valueDType}, but got ${t.dtype}`)}},Dj=async(e,t,n,s)=>{switch(e.op){case"HashTable":case"HashTableV2":{let r=I("keyDType",e,t,n),a=I("valueDType",e,t,n),o=new _j(r,a);return s.addHashTable(e.name,o),[o.handle]}case"LookupTableImport":case"LookupTableImportV2":{let r=I("tableHandle",e,t,n,s),a=I("keys",e,t,n),o=I("values",e,t,n);return[await s.getHashTableById(r.id).import(a,o)]}case"LookupTableFind":case"LookupTableFindV2":{let r=I("tableHandle",e,t,n,s),a=I("keys",e,t,n),o=I("defaultValue",e,t,n);return[await s.getHashTableById(r.id).find(a,o)]}case"LookupTableSize":case"LookupTableSizeV2":{let r=I("tableHandle",e,t,n,s);return[s.getHashTableById(r.id).tensorSize()]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},$j=(e,t,n,s=En)=>{switch(e.op){case"ResizeBilinear":{let r=I("images",e,t,n),a=I("size",e,t,n),o=I("alignCorners",e,t,n),i=I("halfPixelCenters",e,t,n);return[s.image.resizeBilinear(r,[a[0],a[1]],o,i)]}case"ResizeNearestNeighbor":{let r=I("images",e,t,n),a=I("size",e,t,n),o=I("alignCorners",e,t,n),i=I("halfPixelCenters",e,t,n);return[s.image.resizeNearestNeighbor(r,[a[0],a[1]],o,i)]}case"CropAndResize":{let r=I("image",e,t,n),a=I("boxes",e,t,n),o=I("boxInd",e,t,n),i=I("cropSize",e,t,n),l=I("method",e,t,n),u=I("extrapolationValue",e,t,n);return[s.image.cropAndResize(r,a,o,i,l,u)]}case"ImageProjectiveTransformV3":{let r=I("images",e,t,n),a=I("transforms",e,t,n),o=I("outputShape",e,t,n),i=I("fillValue",e,t,n),l=I("interpolation",e,t,n),u=I("fillMode",e,t,n);return[s.image.transform(r,a,l.toLowerCase(),u.toLowerCase(),i,o)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Pj=(e,t,n,s=En)=>{switch(e.op){case"Equal":return[s.equal(I("a",e,t,n),I("b",e,t,n))];case"NotEqual":return[s.notEqual(I("a",e,t,n),I("b",e,t,n))];case"Greater":return[s.greater(I("a",e,t,n),I("b",e,t,n))];case"GreaterEqual":return[s.greaterEqual(I("a",e,t,n),I("b",e,t,n))];case"Less":return[s.less(I("a",e,t,n),I("b",e,t,n))];case"LessEqual":return[s.lessEqual(I("a",e,t,n),I("b",e,t,n))];case"LogicalAnd":return[s.logicalAnd(I("a",e,t,n),I("b",e,t,n))];case"LogicalNot":return[s.logicalNot(I("a",e,t,n))];case"LogicalOr":return[s.logicalOr(I("a",e,t,n),I("b",e,t,n))];case"Select":case"SelectV2":return[s.where(I("condition",e,t,n),I("a",e,t,n),I("b",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Fj=(e,t,n,s=En)=>{switch(e.op){case"BatchMatMul":case"BatchMatMulV2":case"MatMul":return[s.matMul(I("a",e,t,n),I("b",e,t,n),I("transposeA",e,t,n),I("transposeB",e,t,n))];case"Einsum":return[s.einsum(I("equation",e,t,n),...I("tensors",e,t,n))];case"Transpose":return[s.transpose(I("x",e,t,n),I("perm",e,t,n))];case"_FusedMatMul":let[r,a]=I("fusedOps",e,t,n),o=r==="biasadd",i=a==="prelu",l=I("numArgs",e,t,n),u=I("leakyreluAlpha",e,t,n);if(o){if(i&&l!==2)throw new Error("Fused MatMul with BiasAdd and Prelu must have two extra arguments: bias and alpha.");if(!i&&l!==1)throw new Error("Fused MatMul with BiasAdd must have one extra argument: bias.")}let[c,p]=I("args",e,t,n);return[s.fused.matMul({a:I("a",e,t,n),b:I("b",e,t,n),transposeA:I("transposeA",e,t,n),transposeB:I("transposeB",e,t,n),bias:c,activation:a,preluActivationWeights:p,leakyreluAlpha:u})];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Oj=(e,t,n,s=En)=>{switch(e.op){case"EuclideanNorm":return[s.euclideanNorm(I("x",e,t,n),I("axis",e,t,n),I("keepDims",e,t,n))];case"FusedBatchNorm":case"FusedBatchNormV2":return[s.batchNorm(I("x",e,t,n),I("mean",e,t,n),I("variance",e,t,n),I("offset",e,t,n),I("scale",e,t,n),I("epsilon",e,t,n))];case"FusedBatchNormV3":return[s.batchNorm(I("x",e,t,n),I("mean",e,t,n),I("variance",e,t,n),I("offset",e,t,n),I("scale",e,t,n),I("epsilon",e,t,n))];case"LRN":return[s.localResponseNormalization(I("x",e,t,n),I("radius",e,t,n),I("bias",e,t,n),I("alpha",e,t,n),I("beta",e,t,n))];case"Softmax":return[s.softmax(I("x",e,t,n))];case"LogSoftmax":return[s.logSoftmax(I("x",e,t,n))];case"SparseToDense":return[s.sparseToDense(I("sparseIndices",e,t,n),I("outputShape",e,t,n),I("sparseValues",e,t,n),I("defaultValue",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Mj=(e,t,n,s=En)=>{switch(e.op){case"Max":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.max(I("x",e,t,n),i,l)]}case"Mean":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.mean(I("x",e,t,n),i,l)]}case"Min":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.min(I("x",e,t,n),i,l)]}case"Sum":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.sum(I("x",e,t,n),i,l)]}case"All":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.all(I("x",e,t,n),i,l)]}case"Any":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.any(I("x",e,t,n),i,l)]}case"ArgMax":{let i=I("axis",e,t,n);return[s.argMax(I("x",e,t,n),i)]}case"ArgMin":{let i=I("axis",e,t,n);return[s.argMin(I("x",e,t,n),i)]}case"Prod":{let i=I("axis",e,t,n),l=I("keepDims",e,t,n);return[s.prod(I("x",e,t,n),i,l)]}case"Cumprod":{let i=I("axis",e,t,n),l=I("exclusive",e,t,n),u=I("reverse",e,t,n);return[s.cumprod(I("x",e,t,n),i,l,u)]}case"Cumsum":{let i=I("axis",e,t,n),l=I("exclusive",e,t,n),u=I("reverse",e,t,n);return[s.cumsum(I("x",e,t,n),i,l,u)]}case"Bincount":let r=I("x",e,t,n),a=I("weights",e,t,n),o=I("size",e,t,n);return[s.bincount(r,a,o)];case"DenseBincount":{let i=I("x",e,t,n),l=I("weights",e,t,n),u=I("size",e,t,n),c=I("binaryOutput",e,t,n);return[s.denseBincount(i,l,u,c)]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},zj=(e,t,n,s=En)=>{switch(e.op){case"ConcatV2":case"Concat":{let r=I("n",e,t,n),a=I("axis",e,t,n),o=I("tensors",e,t,n);return o=o.slice(0,r),[s.concat(o,a)]}case"Gather":{let r=I("x",e,t,n),a=I("indices",e,t,n);return[s.gather(r,s.cast(a,"int32"),0)]}case"GatherV2":{let r=I("axis",e,t,n),a=I("batchDims",e,t,n),o=I("x",e,t,n),i=I("indices",e,t,n);return[s.gather(o,s.cast(i,"int32"),r,a)]}case"Reverse":{let r=I("dims",e,t,n),a=[];for(let i=0;i<r.length;i++)r[i]&&a.push(i);let o=I("x",e,t,n);return[s.reverse(o,a)]}case"ReverseV2":{let r=I("axis",e,t,n),a=I("x",e,t,n);return[s.reverse(a,r)]}case"Slice":{let r=I("begin",e,t,n),a=I("size",e,t,n);return[s.slice(I("x",e,t,n),r,a)]}case"StridedSlice":{let r=I("begin",e,t,n),a=I("end",e,t,n),o=I("strides",e,t,n),i=I("beginMask",e,t,n),l=I("endMask",e,t,n),u=I("ellipsisMask",e,t,n),c=I("newAxisMask",e,t,n),p=I("shrinkAxisMask",e,t,n),d=I("x",e,t,n);return[s.stridedSlice(d,r,a,o,i,l,u,c,p)]}case"Pack":return J(()=>{let r=I("axis",e,t,n),a=I("tensors",e,t,n),o=a[0].shape,i=s.squeeze(a[0]).shape,l=a.map(u=>{let c=v.arraysEqual(u.shape,o);if(!c&&!v.arraysEqual(s.squeeze(u).shape,i))throw new Error("the input tensors shape does not match");return c?u:s.reshape(u,o)});return[s.stack(l,r)]});case"Unpack":{let r=I("axis",e,t,n),a=I("tensor",e,t,n);return s.unstack(a,r)}case"Tile":{let r=I("reps",e,t,n);return[s.tile(I("x",e,t,n),r)]}case"Split":case"SplitV":{let r=I("axis",e,t,n),a=I("numOrSizeSplits",e,t,n),o=I("x",e,t,n);return s.split(o,a,r)}case"ScatterNd":{let r=I("indices",e,t,n),a=I("values",e,t,n),o=I("shape",e,t,n);return[s.scatterND(r,a,o)]}case"GatherNd":{let r=I("x",e,t,n),a=I("indices",e,t,n);return[s.gatherND(r,a)]}case"SparseToDense":{let r=I("sparseIndices",e,t,n),a=I("outputShape",e,t,n),o=I("sparseValues",e,t,n),i=I("defaultValue",e,t,n);return[s.sparseToDense(r,o,a,o.dtype===i.dtype?i:s.cast(i,o.dtype))]}default:throw TypeError(`Node type ${e.op} is not implemented`)}},Lj=(e,t,n,s=En)=>{switch(e.op){case"SparseFillEmptyRows":{let{outputIndices:r,outputValues:a,emptyRowIndicator:o,reverseIndexMap:i}=s.sparse.sparseFillEmptyRows(I("indices",e,t,n),I("values",e,t,n),I("denseShape",e,t,n),I("defaultValue",e,t,n));return[r,a,o,i]}case"SparseReshape":{let{outputIndices:r,outputShape:a}=s.sparse.sparseReshape(I("inputIndices",e,t,n),I("inputShape",e,t,n),I("newShape",e,t,n));return[r,a]}case"SparseSegmentMean":return[s.sparse.sparseSegmentMean(I("data",e,t,n),I("indices",e,t,n),I("segmentIds",e,t,n))];case"SparseSegmentSum":return[s.sparse.sparseSegmentSum(I("data",e,t,n),I("indices",e,t,n),I("segmentIds",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Bj=(e,t,n,s=En)=>{switch(e.op){case"FFT":return[s.fft(I("x",e,t,n))];case"IFFT":return[s.ifft(I("x",e,t,n))];case"RFFT":return[s.rfft(I("x",e,t,n))];case"IRFFT":return[s.irfft(I("x",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Wj=(e,t,n,s=En)=>{switch(e.op){case"StringNGrams":{let{nGrams:r,nGramsSplits:a}=s.string.stringNGrams(I("data",e,t,n),I("dataSplits",e,t,n),I("separator",e,t,n),I("nGramWidths",e,t,n),I("leftPad",e,t,n),I("rightPad",e,t,n),I("padWidth",e,t,n),I("preserveShortSequences",e,t,n));return[r,a]}case"StringSplit":{let{indices:r,values:a,shape:o}=s.string.stringSplit(I("input",e,t,n),I("delimiter",e,t,n),I("skipEmpty",e,t,n));return[r,a,o]}case"StringToHashBucketFast":return[s.string.stringToHashBucketFast(I("input",e,t,n),I("numBuckets",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}},Vj=(e,t,n,s=En)=>{switch(e.op){case"Cast":return[s.cast(I("x",e,t,n),I("dtype",e,t,n))];case"ExpandDims":{let r=I("axis",e,t,n);return[s.expandDims(I("x",e,t,n),r)]}case"Squeeze":{let r=I("axis",e,t,n);return[s.squeeze(I("x",e,t,n),r)]}case"Reshape":return[s.reshape(I("x",e,t,n),I("shape",e,t,n))];case"MirrorPad":return[s.mirrorPad(I("x",e,t,n),I("padding",e,t,n),I("mode",e,t,n))];case"PadV2":case"Pad":return[s.pad(I("x",e,t,n),I("padding",e,t,n),I("constantValue",e,t,n))];case"SpaceToBatchND":{let r=I("blockShape",e,t,n),a=I("paddings",e,t,n);return[s.spaceToBatchND(I("x",e,t,n),r,a)]}case"BatchToSpaceND":{let r=I("blockShape",e,t,n),a=I("crops",e,t,n);return[s.batchToSpaceND(I("x",e,t,n),r,a)]}case"DepthToSpace":{let r=I("blockSize",e,t,n),a=I("dataFormat",e,t,n).toUpperCase();return[s.depthToSpace(I("x",e,t,n),r,a)]}case"BroadcastTo":return[s.broadcastTo(I("x",e,t,n),I("shape",e,t,n))];case"BroadcastArgs":return[s.broadcastArgs(I("s0",e,t,n),I("s1",e,t,n))];default:throw TypeError(`Node type ${e.op} is not implemented`)}};function s7(e,t,n,s,r=J){let a=((o,i,l)=>{switch(o.category){case"arithmetic":return r(()=>Aj(o,i,l));case"basic_math":return r(()=>xj(o,i,l));case"control":return Sj(o,i,l);case"convolution":return r(()=>Cj(o,i,l));case"creation":return r(()=>Tj(o,i,l));case"dynamic":return Nj(o,i,l);case"evaluation":return r(()=>Ej(o,i,l));case"image":return r(()=>$j(o,i,l));case"graph":return r(()=>Rj(o,i,l));case"logical":return r(()=>Pj(o,i,l));case"matrices":return r(()=>Fj(o,i,l));case"normalization":return r(()=>Oj(o,i,l));case"reduction":return r(()=>Mj(o,i,l));case"slice_join":return r(()=>zj(o,i,l));case"sparse":return r(()=>Lj(o,i,l));case"spectral":return r(()=>Bj(o,i,l));case"string":return r(()=>Wj(o,i,l));case"transformation":return r(()=>Vj(o,i,l));case"hash_table":return Dj(o,i,l,s);case"custom":let u=Sk(o.op);if(u&&u.customExecutor)return u.customExecutor(new yj(o,i,l));throw TypeError(`Custom op ${o.op} is not registered.`);default:throw TypeError(`Unknown op '${o.op}'. File an issue at https://github.com/tensorflow/tfjs/issues so we can add it, or register a custom execution with tf.registerOp()`)}})(e,t,n);return v.isPromise(a)?a.then(o=>[].concat(o)):[].concat(a)}var r7=class{constructor(e={},t={},n={},s={}){this.weightMap=e,this.tensorArrayMap=t,this.tensorListMap=n,this.functionMap=s,this.rootContext={id:0,frameName:"",iterationId:0},this.contexts=[this.rootContext],this.lastId=0,this.generateCurrentContextIds()}newFrame(e,t){return{id:e,frameName:t,iterationId:0}}set currentContext(e){this.contexts!==e&&(this.contexts=e,this.generateCurrentContextIds())}get currentContext(){return this.contexts}get currentContextId(){return this._currentContextIds[0]}get currentContextIds(){return this._currentContextIds}generateCurrentContextIds(){let e=[];for(let t=0;t<this.contexts.length-1;t++){let n=this.contexts.slice(0,this.contexts.length-t);e.push(this.contextIdforContexts(n))}e.push(""),this._currentContextIds=e}contextIdforContexts(e){return e?e.map(t=>t.id===0&&t.iterationId===0?"":`${t.frameName}-${t.iterationId}`).join("/"):""}enterFrame(e){this.contexts&&(this.lastId++,this.contexts=this.contexts.slice(),this.contexts.push(this.newFrame(this.lastId,e)),this._currentContextIds.unshift(this.contextIdforContexts(this.contexts)))}exitFrame(){if(this.contexts&&this.contexts.length>1)this.contexts=this.contexts.slice(),this.contexts.splice(-1),this.currentContextIds.shift();else throw new Error("Cannot exit frame, the context is empty")}nextIteration(){if(this.contexts&&this.contexts.length>0){this.contexts=this.contexts.slice(),this.lastId++;let e=Object.assign({},this.contexts[this.contexts.length-1]);e.iterationId+=1,e.id=this.lastId,this.contexts.splice(-1,1,e),this._currentContextIds.splice(0,1,this.contextIdforContexts(this.contexts))}else throw new Error("Cannot increase frame iteration, the context is empty")}getWeight(e){return this.weightMap[e]}addTensorArray(e){this.tensorArrayMap[e.id]=e}getTensorArray(e){return this.tensorArrayMap[e]}addTensorList(e){this.tensorListMap[e.id]=e}getTensorList(e){return this.tensorListMap[e]}dispose(e){for(let t in this.tensorArrayMap)this.tensorArrayMap[t].clearAndClose(e);for(let t in this.tensorListMap)this.tensorListMap[t].clearAndClose(e)}};function a7(e,t,n,s){let r=new Set,a=[],o=null,i=null,l=new Set,u=Object.keys(e).map(d=>Ss(d)[0]),c=[];s!=null&&(c=s.map(d=>Ss(d.name)[0]));let p=[...t];for(;p.length>0;){let d=p.pop();if((qk(d)||qj(d)||Xj(d))&&o==null&&(o=d,i=o.children.map(h=>h.name).filter(h=>r.has(h))),r.add(d.name),n[d.name]==null&&u.indexOf(d.name)===-1&&c.indexOf(d.name)===-1){if(d.inputs.length===0){a.push(d.name);continue}d.inputs.forEach(h=>{l.has(h.name)||(l.add(h.name),p.push(h))})}}return{inputs:e,outputs:t,usedNodes:r,missingInputs:a,dynamicNode:o,syncInputs:i}}function Uj(e,t,n){let{usedNodes:s,inputs:r}=n,a=[],o=Object.keys(r).map(c=>Ss(c)[0]).map(c=>e.nodes[c]),i=e.initNodes;o.forEach(c=>{s.has(c.name)&&a.push(c)}),e.weights.forEach(c=>{s.has(c.name)&&a.push(c)}),i!=null&&i.forEach(c=>{s.has(c.name)&&a.push(c)});let l=new Set,u=[];for(;a.length>0;){let c=a.pop();l.add(c.name),t[c.name]||u.push(c),c.children.forEach(p=>{!l.has(p.name)&&s.has(p.name)&&p.inputs.every(d=>l.has(d.name))&&a.push(p)})}return u}var Gj=["Switch","Merge","Enter","Exit","NextIteration","StatelessIf","StatelessWhile","if","While"],Hj=["NonMaxSuppressionV2","NonMaxSuppressionV3","NonMaxSuppressionV5","Where"],jj=["HashTable","HashTableV2","LookupTableImport","LookupTableImportV2","LookupTableFind","LookupTableFindV2","LookupTableSize","LookupTableSizeV2"];function qk(e){return Gj.indexOf(e.op)>=0}function qj(e){return Hj.indexOf(e.op)>=0}function Xj(e){return jj.indexOf(e.op)>=0}var J3=class{constructor(e,t){this.graph=e,this.parent=t,this.compiledMap=new Map,this._weightMap={},this.SEPERATOR=",",this._functions={},this._functionExecutorMap={},this.intermediateTensors={},this.keepTensorForDebug=!1,this._outputs=e.outputs,this._inputs=e.inputs,this._initNodes=e.initNodes,this._signature=e.signature,this._functions=e.functions,e.functions!=null&&Object.keys(e.functions).forEach(n=>{this._functionExecutorMap[n]=new J3(e.functions[n],this)})}get weightIds(){return this.parent?this.parent.weightIds:this._weightIds}get functionExecutorMap(){return this.parent?this.parent.functionExecutorMap:this._functionExecutorMap}get weightMap(){return this.parent?this.parent.weightMap:this._weightMap}set weightMap(e){let t=Object.keys(e).map(n=>e[n].map(s=>s.id));this._weightIds=[].concat(...t),this._weightMap=e}set resourceManager(e){this._resourceManager=e}get inputs(){return this._inputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get outputs(){return this._outputs.map(e=>({name:e.name,shape:e.attrParams.shape?e.attrParams.shape.value:void 0,dtype:e.attrParams.dtype?e.attrParams.dtype.value:void 0}))}get inputNodes(){return this._inputs.map(e=>e.signatureKey||e.name)}get outputNodes(){return this._outputs.map(e=>{let t=e.signatureKey||e.name;return e.defaultOutput?`${t}:${e.defaultOutput}`:t})}get functions(){return Object.keys(this._functions).reduce((e,t)=>(e[t]=this._functions[t].signature,e),{})}getCompilationKey(e,t){let n=e.map(r=>r.name).sort(),s=t.map(r=>r.name).sort();return n.join(this.SEPERATOR)+"--"+s.join(this.SEPERATOR)}compile(e,t){let n=a7(e,t,this.weightMap,this._initNodes),{missingInputs:s,dynamicNode:r,syncInputs:a}=n;if(r!=null)throw new Error(`This execution contains the node '${r.name}', which has the dynamic op '${r.op}'. Please use model.executeAsync() instead. Alternatively, to avoid the dynamic ops, specify the inputs [${a}]`);if(s.length>0){let o=t.map(l=>l.name),i=Object.keys(e);throw new Error(`Cannot compute the outputs [${o}] from the provided inputs [${i}]. Missing the following inputs: [${s}]`)}return Uj(this.graph,this.weightMap,n)}execute(e,t){e=this.mapInputs(e);let n=Object.keys(e).sort();this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t);let s=n.map(c=>this.graph.nodes[Ss(c)[0]]),r=t.map(c=>Ss(c)[0]),a=r.map(c=>this.graph.nodes[c]);this.resetIntermediateTensors(),a.length===0&&(a=this._outputs);let o=this.getCompilationKey(s,a),i=this.compiledMap.get(o);i==null&&(i=this.compile(e,a),this.compiledMap.set(o,i));let l={},u={};return J(()=>{let c=new r7(this.weightMap,l,u,this.functionExecutorMap),p=Object.assign({},this.weightMap);Object.keys(e).forEach(f=>{let[m,g]=Ss(f),y=[];y[g]=e[f],p[m]=y});let d=this.getFrozenTensorIds(p),h={};for(let f=0;f<i.length;f++){let m=i[f];if(!p[m.name]){let g=s7(m,p,c,this._resourceManager);if(v.isPromise(g))throw new Error(`The execution of the op '${m.op}' returned a promise. Please use model.executeAsync() instead.`);p[m.name]=g,this.checkTensorForDisposal(m.name,m,p,c,d,r,h)}}return this.parent==null&&c.dispose(d),t.map(f=>Jn(f,p,c))})}getFrozenTensorIds(e){let t=[].concat.apply([],Object.keys(e).map(n=>e[n]).map(n=>n.map(s=>s.id)));return new Set(t)}checkTensorForDisposal(e,t,n,s,r,a,o){t.category==="control"||a.indexOf(e)!==-1||(n[e].forEach(i=>{i!=null&&(o[i.id]=(o[i.id]||0)+t.children.length)}),t.inputs.forEach(i=>{if(i.category!=="control"){let l=ZH(i.name,n,s);l!=null&&l.forEach(u=>{if(u&&!u.kept&&!r.has(u.id)){let c=o[u.id];if(c===1){if(!this.keepTensorForDebug)u.dispose();else{let[p,d]=Ur(t.name,s);this.intermediateTensors[p]?this.intermediateTensors[p][d]=u:(this.intermediateTensors[p]=[],this.intermediateTensors[p][d]=u)}delete o[u.id]}else c!=null&&o[u.id]--}})}}))}async executeAsync(e,t){return this._executeAsync(e,t)}disposeIntermediateTensors(){!this.intermediateTensors||(Object.keys(this.intermediateTensors).forEach(e=>this.intermediateTensors[e].forEach(t=>t.dispose())),this.disposeTensorsMap())}disposeTensorsMap(){!this.tensorsMap||Object.keys(this.tensorsMap).forEach(e=>{this.tensorsMap[e].forEach(n=>{n&&!n.kept&&!n.isDisposed&&!this.keepIds.has(n.id)&&n.dispose()})})}getIntermediateTensors(){return this.tensorsMap}resetIntermediateTensors(){for(let e in this.intermediateTensors)this.intermediateTensors[e].forEach(t=>t.dispose()),delete this.intermediateTensors[e]}async _executeAsync(e,t,n=!1,s={},r={}){n||(e=this.mapInputs(e),this.checkInputs(e),this.checkInputShapeAndType(e),t=this.mapOutputs(t),this.checkOutputs(t));try{this.keepTensorForDebug=X().getBool("KEEP_INTERMEDIATE_TENSORS")}catch(u){console.warn(u.message)}this.resetIntermediateTensors();let a=new r7(this.weightMap,s,r,this.functionExecutorMap);this.tensorsMap=await this.executeWithControlFlow(e,a,t,n);let o=t.map(u=>Jn(u,this.tensorsMap,a)),i=o.map(u=>u.id),l=Object.keys(e).map(u=>e[u].id);return this.keepIds=new Set([...i,...l,...this.weightIds]),this.keepTensorForDebug||this.disposeTensorsMap(),this.parent==null&&a.dispose(this.keepIds),o}async executeFunctionAsync(e,t,n){let s=e.reduce((r,a,o)=>(r[this.inputs[o].name]=a,r),{});return this._executeAsync(s,this.outputNodes,!0,t,n)}async executeWithControlFlow(e,t,n,s){let r=Object.keys(e),a=r.map(x=>this.graph.nodes[Ss(x)[0]]),o=n.map(x=>Ss(x)[0]),i=o.map(x=>this.graph.nodes[x]);i.length===0&&(i=this._outputs);let{usedNodes:l,missingInputs:u,dynamicNode:c,syncInputs:p}=a7(e,i,this.weightMap,this._initNodes),d=[...a,...this.graph.weights,...this._initNodes||[]].map(x=>({node:x,contexts:t.currentContext})),h=Object.assign({},this.weightMap);Object.keys(e).forEach(x=>{let[A,b]=Ss(x),w=[];w[b]=e[x],h[A]=w});let f={},m=this.getFrozenTensorIds(h),g={};for(;d.length>0;){let x=this.processStack(a,d,t,h,g,m,o,f,l);await Promise.all(x)}c==null&&!s&&console.warn("This model execution did not contain any nodes with control flow or dynamic output shapes. You can use model.execute() instead.");let y=i.filter(x=>!qk(x)&&!Jn(x.name,h,t)).map(x=>x.name);if(y.length>0){let x="";throw c!=null&&(x=`Alternatively, to avoid the dynamic ops, use model.execute() and specify the inputs [${p}]`),new Error(`Cannot compute the outputs [${y}] from the provided inputs [${r}]. Consider providing the following inputs: [${u}]. ${x}`)}return h}processStack(e,t,n,s,r,a,o,i,l){let u=[];for(;t.length>0;){let c=t.pop();n.currentContext=c.contexts;let p="";if(c.node.op==="Enter"&&I("isConstant",c.node,s,n)&&([p]=Ur(c.node.name,n)),s[c.node.name]==null){let d=s7(c.node,s,n,this._resourceManager);p||([p]=Ur(c.node.name,n));let h=n.currentContext;v.isPromise(d)?u.push(d.then(f=>(s[p]=f,n.currentContext=h,this.checkTensorForDisposal(p,c.node,s,n,a,o,i),this.processChildNodes(c.node,t,n,s,r,l),f))):(s[p]=d,this.checkTensorForDisposal(p,c.node,s,n,a,o,i),this.processChildNodes(c.node,t,n,s,r,l))}else this.processChildNodes(c.node,t,n,s,r,l)}return u}processChildNodes(e,t,n,s,r,a){e.children.forEach(o=>{let[i]=Ur(o.name,n);r[i]||!a.has(o.name)||(o.op==="Merge"?o.inputNames.some(l=>!!Jn(l,s,n))&&(r[i]=!0,t.push({contexts:n.currentContext,node:o})):o.inputNames.every(l=>!!Jn(l,s,n))&&(r[i]=!0,t.push({contexts:n.currentContext,node:o})))})}dispose(){Object.keys(this.weightMap).forEach(e=>this.weightMap[e].forEach(t=>t.dispose()))}checkInputShapeAndType(e){Object.keys(e).forEach(t=>{let n=e[t],[s]=Ss(t),r=this.graph.nodes[s];if(r.attrParams.shape&&r.attrParams.shape.value){let a=r.attrParams.shape.value,o=a.length===n.shape.length&&n.shape.every((i,l)=>a[l]===-1||a[l]===i);v.assert(o,()=>`The shape of dict['${r.name}'] provided in model.execute(dict) must be [${a}], but was [${n.shape}]`)}r.attrParams.dtype&&r.attrParams.dtype.value&&v.assert(n.dtype===r.attrParams.dtype.value,()=>`The dtype of dict['${r.name}'] provided in model.execute(dict) must be ${r.attrParams.dtype.value}, but was ${n.dtype}`)})}mapInputs(e){let t={};for(let n in e)if(this._signature!=null&&this._signature.inputs!=null&&this._signature.inputs[n]!=null){let s=this._signature.inputs[n];t[s.name]=e[n]}else t[n]=e[n];return t}checkInputs(e){let t=Object.keys(e).filter(n=>{let[s]=Ss(n);return this.graph.nodes[s]==null});if(t.length>0)throw new Error(`The dict provided in model.execute(dict) has keys: [${t}] that are not part of graph`)}mapOutputs(e){return e.map(t=>this._signature!=null&&this._signature.outputs!=null&&this._signature.outputs[t]!=null?this._signature.outputs[t].name:t,{})}checkOutputs(e){e.forEach(t=>{let[n]=Ss(t);if(!this.graph.nodes[n])throw new Error(`The output '${t}' is not found in the graph`)})}},Kj=class{constructor(e={},t={}){this.hashTableNameToHandle=e,this.hashTableMap=t}addHashTable(e,t){this.hashTableNameToHandle[e]=t.handle,this.hashTableMap[t.id]=t}getHashTableHandleByName(e){return this.hashTableNameToHandle[e]}getHashTableById(e){return this.hashTableMap[e]}dispose(){for(let e in this.hashTableMap)this.hashTableMap[e].clearAndClose(),delete this.hashTableMap[e];for(let e in this.hashTableNameToHandle)this.hashTableNameToHandle[e].dispose(),delete this.hashTableNameToHandle[e]}},Zj="?tfjs-format=file",Yj="model.json",Dh=class{constructor(e,t={},n=Ts){this.modelUrl=e,this.loadOptions=t,this.version="n/a",this.io=n,t==null&&(this.loadOptions={}),this.resourceManager=new Kj}get modelVersion(){return this.version}get inputNodes(){return this.executor.inputNodes}get outputNodes(){return this.executor.outputNodes}get inputs(){return this.executor.inputs}get outputs(){return this.executor.outputs}get weights(){return this.executor.weightMap}get metadata(){return this.artifacts.userDefinedMetadata}get modelSignature(){return this.signature}get modelStructuredOutputKeys(){return this.structuredOutputKeys}findIOHandler(){let e=this.modelUrl;if(e.load!=null)this.handler=e;else if(this.loadOptions.requestInit!=null)this.handler=this.io.browserHTTPRequest(e,this.loadOptions);else{let t=this.io.getLoadHandlers(e,this.loadOptions);if(t.length===0)t.push(this.io.browserHTTPRequest(e,this.loadOptions));else if(t.length>1)throw new Error(`Found more than one (${t.length}) load handlers for URL '${[e]}'`);this.handler=t[0]}}load(){if(this.findIOHandler(),this.handler.load==null)throw new Error("Cannot proceed with model loading because the IOHandler provided does not have the `load` method implemented.");let e=this.handler.load();return v.isPromise(e)?e.then(t=>this.loadSync(t)):this.loadSync(e)}loadSync(e){this.artifacts=e;let t=this.artifacts.modelTopology,n=this.artifacts.signature;if(this.artifacts.userDefinedMetadata!=null){let r=this.artifacts.userDefinedMetadata;r.signature!=null&&(n=r.signature),r.structuredOutputKeys!=null&&(this.structuredOutputKeys=r.structuredOutputKeys)}this.signature=n,this.version=`${t.versions.producer}.${t.versions.minConsumer}`;let s=this.io.decodeWeights(this.artifacts.weightData,this.artifacts.weightSpecs);if(this.executor=new J3(Qv.Instance.transformGraph(t,this.signature)),this.executor.weightMap=this.convertTensorMapToTensorsMap(s),this.executor.resourceManager=this.resourceManager,e.modelInitializer!=null&&e.modelInitializer.node!=null){let r=Qv.Instance.transformGraph(e.modelInitializer);this.initializer=new J3(r),this.initializer.weightMap=this.executor.weightMap,this.initializer.resourceManager=this.resourceManager,this.initializer.executeAsync({},[])}return!0}async save(e,t){if(typeof e=="string"){let n=this.io.getSaveHandlers(e);if(n.length===0)throw new Error(`Cannot find any save handlers for URL '${e}'`);if(n.length>1)throw new Error(`Found more than one (${n.length}) save handlers for URL '${e}'`);e=n[0]}if(e.save==null)throw new Error("GraphModel.save() cannot proceed because the IOHandler provided does not have the `save` attribute defined.");return e.save(this.artifacts)}predict(e,t){let n=this.execute(e,this.outputNodes);if(this.structuredOutputKeys){let s=n instanceof tt?[n]:n,r={};return s.forEach((a,o)=>r[this.structuredOutputKeys[o]]=a),r}return n}normalizeInputs(e){if(!(e instanceof tt)&&!Array.isArray(e))return e;if(e=Array.isArray(e)?e:[e],e.length!==this.inputNodes.length)throw new Error(`Input tensor count mismatch,the graph model has ${this.inputNodes.length} placeholders, while there are ${e.length} input tensors.`);return this.inputNodes.reduce((t,n,s)=>(t[n]=e[s],t),{})}normalizeOutputs(e){return e=e||this.outputNodes,Array.isArray(e)?e:[e]}execute(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=this.executor.execute(e,t);return n.length>1?n:n[0]}async executeAsync(e,t){e=this.normalizeInputs(e),t=this.normalizeOutputs(t);let n=await this.executor.executeAsync(e,t);return n.length>1?n:n[0]}getIntermediateTensors(){return this.executor.getIntermediateTensors()}disposeIntermediateTensors(){this.executor.disposeIntermediateTensors()}convertTensorMapToTensorsMap(e){return Object.keys(e).reduce((t,n)=>(t[n]=[e[n]],t),{})}dispose(){this.executor.dispose(),this.initializer&&this.initializer.dispose(),this.resourceManager.dispose()}};async function Jj(e,t={},n=Ts){if(e==null)throw new Error("modelUrl in loadGraphModel() cannot be null. Please provide a url or an IOHandler that loads the model");t==null&&(t={}),t.fromTFHub&&typeof e=="string"&&(e=eq(e));let s=new Dh(e,t,n);return await s.load(),s}function Qj(e){if(e==null)throw new Error("modelUrl in loadGraphModelSync() cannot be null. Please provide a url or an IOHandler that loads the model");if(!e.load)throw new Error(`modelUrl IO Handler ${e} has no load function`);let t=new Dh(e);return t.load(),t}function eq(e){return e.endsWith("/")||(e=e+"/"),`${e}${Yj}${Zj}`}var tq="3.19.0",Xk={};Ve(Xk,{CSVDataset:()=>sI,Dataset:()=>Jc,FileDataSource:()=>cI,TextLineDataset:()=>nI,URLDataSource:()=>dI,array:()=>Iq,csv:()=>Fq,func:()=>Oq,generator:()=>Mq,microphone:()=>Lq,version_data:()=>Bq,webcam:()=>zq,zip:()=>Sq});var nq=lo(Bm()),sq=lo(Bm());function rq(e,t){return Nm(e,t)}function Nm(e,t,n=new Map,s=new Set){if(e==null)return null;if(typeof Blob=="function"&&e instanceof Blob)return e.slice();if(s.has(e))throw new Error("Circular references are not supported.");if(n.has(e))return n.get(e);let r=t(e);if(r.recurse&&r.value!==null)throw new Error("A deep map function may not return both a value and recurse=true.");if(r.recurse)if(rc(e)){let a=Array.isArray(e)?[]:{};s.add(e);for(let o in e){let i=e[o],l=Nm(i,t,n,s);a[o]=l}return s.delete(e),e.__proto__&&(a.__proto__=e.__proto__),a}else throw new Error(`Can't recurse into non-iterable type: ${e}`);else return n.set(e,r.value),r.value}function aq(e,t=Zk){return Kk(e,t)}function Kk(e,t,n=new Set){let s=e[0];if(n.has(s))throw new Error("Circular references are not supported.");let r=t(e);if(r.recurse&&r.value!==null)throw new Error("A deep zip function may not return both a value and recurse=true.");if(r.recurse)if(rc(s)){let a=Array.isArray(s)?[]:{};n.add(s);for(let o in s){let i=e.map(u=>u[o]),l=Kk(i,t,n);a[o]=l}return n.delete(s),a}else throw new Error(`Can't recurse into non-iterable type: ${s}`);else return r.value}function Zk(e){return e===null?null:rc(e[0])?{value:null,recurse:!0}:{value:e,recurse:!1}}async function Yk(e,t){let n=new Map;Nm(e,t,n);for(let r of Array.from(n.keys())){let a=n.get(r);if(v.isPromise(a)){let o=await a;n.set(r,o)}}return Nm(e,t,n)}function rc(e){let t=!1;if(X().get("IS_BROWSER"))t=e instanceof TextDecoder;else{let{StringDecoder:n}=Y7();t=e instanceof n}return e!=null&&!ArrayBuffer.isView(e)&&(Array.isArray(e)||typeof e=="object"&&!(e instanceof tt)&&!(e instanceof Promise)&&!t)}function oq(e){return e==null||iq(e)||Array.isArray(e)||typeof e=="object"&&e instanceof tt||v.isTypedArray(e)}function iq(e){return e===null||typeof e!="object"&&typeof e!="function"}function lq(e){return rq(e,uq)}function uq(e){return e instanceof tt?{value:e.clone(),recurse:!1}:rc(e)?{value:null,recurse:!0}:{value:e,recurse:!1}}var Jk=class{constructor(e){if(this.capacity=e,this.begin=0,this.end=0,e==null)throw new RangeError("Can't create a ring buffer of unknown capacity.");if(e<1)throw new RangeError("Can't create ring buffer of capacity < 1.");this.data=new Array(e),this.doubledCapacity=2*e}wrap(e){for(;e<0;)e+=this.doubledCapacity;return e%this.doubledCapacity}get(e){if(e<0)throw new RangeError("Can't get item at a negative index.");return this.data[e%this.capacity]}set(e,t){if(e<0)throw new RangeError("Can't set item at a negative index.");this.data[e%this.capacity]=t}length(){let e=this.end-this.begin;return e<0&&(e=this.doubledCapacity+e),e}isFull(){return this.length()===this.capacity}isEmpty(){return this.length()===0}push(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.set(this.end,e),this.end=this.wrap(this.end+1)}pushAll(e){for(let t of e)this.push(t)}pop(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");this.end=this.wrap(this.end-1);let e=this.get(this.end);return this.set(this.end,void 0),e}unshift(e){if(this.isFull())throw new RangeError("Ring buffer is full.");this.begin=this.wrap(this.begin-1),this.set(this.begin,e)}shift(){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let e=this.get(this.begin);return this.set(this.begin,void 0),this.begin=this.wrap(this.begin+1),e}shuffleExcise(e){if(this.isEmpty())throw new RangeError("Ring buffer is empty.");let t=this.wrap(this.begin+e),n=this.get(t);return this.set(t,this.pop()),n}},vx=class extends Jk{constructor(){super(vx.INITIAL_CAPACITY)}isFull(){return!1}push(e){super.isFull()&&this.expand(),super.push(e)}unshift(e){super.isFull()&&this.expand(),super.unshift(e)}expand(){let e=this.capacity*2,t=new Array(e),n=this.length();for(let s=0;s<n;s++)t[s]=this.get(this.wrap(this.begin+s));this.data=t,this.capacity=e,this.doubledCapacity=2*this.capacity,this.begin=0,this.end=n}};vx.INITIAL_CAPACITY=32;function Qk(e){return new pq(e)}function wx(e){return new hq(e)}function cq(e,t){return new eI(e,t)}function dq(e,t=Ha.FAIL){return new wq(e,t)}var wn=class{async toArray(){let e=[],t=await this.next();for(;!t.done;)e.push(t.value),t=await this.next();return e}async toArrayForTest(){let e=this.prefetch(100),t=[],n=await e.next();for(;!n.done;)t.push(n.value),n=await e.next();return t}async resolveFully(){let e=await this.next();for(;!e.done;)e=await this.next()}async resolveWhile(e){let t=await this.next(),n=e(t.value);for(;!t.done&&n;)t=await this.next(),n=e(t.value)}handleErrors(e){return new bq(this,e)}filter(e){return new Aq(this,e)}map(e){return new xq(this,e)}mapAsync(e){return new o7(this,e)}serialMapAsync(e){return new o7(this,e).serial()}flatmap(e){return new vq(this,e)}async forEachAsync(e){return this.map(e).resolveFully()}async serialForEach(e){return this.serialMapAsync(e).resolveWhile(t=>t===!0)}rowMajorBatch(e,t=!0){return new yq(this,e,t)}columnMajorBatch(e,t=!0,n=Zk){return this.rowMajorBatch(e,t).map(r=>aq(r,n))}concatenate(e,t){return new eI(Qk([this,e]),t)}take(e){return e<0||e==null?this:new gq(this,e)}skip(e){return e<0||e==null?this:new mq(this,e)}prefetch(e){return new tI(this,e)}shuffle(e,t){return new kq(this,e,t)}serial(){return new fq(this)}},pq=class extends wn{constructor(e){super(),this.items=e,this.trav=0}summary(){return`Array of ${this.items.length} items`}async next(){if(this.trav>=this.items.length)return{value:null,done:!0};let e=this.items[this.trav];return this.trav++,{value:lq(e),done:!1}}},hq=class extends wn{constructor(e){super(),this.nextFn=e}summary(){return"Function call"}async next(){try{return this.nextFn()}catch(e){throw e.message=`Error thrown while iterating through a dataset: ${e.message}`,e}}},fq=class extends wn{constructor(e){super(),this.upstream=e,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Serial`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){return this.upstream.next()}},mq=class extends wn{constructor(e,t){super(),this.upstream=e,this.maxCount=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Skip`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.count++<this.maxCount;){let e=await this.upstream.next();if(e.done)return e;ne(e.value)}return this.upstream.next()}},gq=class extends wn{constructor(e,t){super(),this.upstream=e,this.maxCount=t,this.count=0}summary(){return`${this.upstream.summary()} -> Take`}async next(){return this.count++>=this.maxCount?{value:null,done:!0}:this.upstream.next()}},yq=class extends wn{constructor(e,t,n=!0){super(),this.upstream=e,this.batchSize=t,this.enableSmallLastBatch=n,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> RowMajorBatch`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){let e=[];for(;e.length<this.batchSize;){let t=await this.upstream.next();if(t.done)return this.enableSmallLastBatch&&e.length>0?{value:e,done:!1}:{value:null,done:!0};e.push(t.value)}return{value:e,done:!1}}},Aq=class extends wn{constructor(e,t){super(),this.upstream=e,this.predicate=t,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> Filter`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;){let e=await this.upstream.next();if(e.done||this.predicate(e.value))return e;ne(e.value)}}},xq=class extends wn{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Map`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Tr.getTensorsInContainer(e.value),n=this.transform(e.value),s=Tr.getTensorsInContainer(n);for(let r of t)Tr.isTensorInList(r,s)||r.dispose();return{value:n,done:!1}}},bq=class extends wn{constructor(e,t){super(),this.upstream=e,this.handler=t,this.count=0,this.lastRead=Promise.resolve({value:null,done:!1})}summary(){return`${this.upstream.summary()} -> handleErrors`}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;;)try{return await this.upstream.next()}catch(e){if(!this.handler(e))return{value:null,done:!0}}}},o7=class extends wn{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> AsyncMap`}async next(){let e=await this.upstream.next();if(e.done)return{value:null,done:!0};let t=Tr.getTensorsInContainer(e.value),n=await this.transform(e.value),s=Tr.getTensorsInContainer(n);for(let r of t)Tr.isTensorInList(r,s)||r.dispose();return{value:n,done:!1}}},kx=class extends wn{constructor(){super(),this.outputQueue=new vx,this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}async serialNext(){for(;this.outputQueue.length()===0;)if(!await this.pump())return{value:null,done:!0};return{value:this.outputQueue.shift(),done:!1}}},vq=class extends kx{constructor(e,t){super(),this.upstream=e,this.transform=t}summary(){return`${this.upstream.summary()} -> Flatmap`}async pump(){let e=await this.upstream.next();if(e.done)return!1;let t=Tr.getTensorsInContainer(e.value),n=this.transform(e.value),s=Tr.getTensorsInContainer(n);this.outputQueue.pushAll(n);for(let r of t)Tr.isTensorInList(r,s)||r.dispose();return!0}},eI=class extends wn{constructor(e,t){super(),this.baseErrorHandler=t,this.lastRead=null,this.iterator=null,this.moreIterators=e}summary(){return"TODO: fill in upstream of chained summaries -> Chained"}async next(){return this.lastRead=this.readFromChain(this.lastRead),this.lastRead}async readFromChain(e){if(await e,this.iterator==null){let n=await this.moreIterators.next();if(n.done)return{value:null,done:!0};this.iterator=n.value,this.baseErrorHandler!=null&&(this.iterator=this.iterator.handleErrors(this.baseErrorHandler))}let t=await this.iterator.next();return t.done?(this.iterator=null,this.readFromChain(e)):t}},Ha;(function(e){e[e.FAIL=0]="FAIL",e[e.SHORTEST=1]="SHORTEST",e[e.LONGEST=2]="LONGEST"})(Ha||(Ha={}));var wq=class extends wn{constructor(e,t=Ha.FAIL){super(),this.iterators=e,this.mismatchMode=t,this.count=0,this.currentPromise=null}summary(){return"{TODO: fill in upstream of zip summaries} -> Zip"}async nextState(e){await e;let t=0,n=0;function s(a){return a instanceof wn?{value:a.next().then(i=>(t++,i.done&&n++,i.value)),recurse:!1}:{value:null,recurse:!0}}let r=await Yk(this.iterators,s);if(t===n)return{value:null,done:!0};if(n>0)switch(this.mismatchMode){case Ha.FAIL:throw new Error(`Zipped streams should have the same length. Mismatched at element ${this.count}.`);case Ha.SHORTEST:return{value:null,done:!0};case Ha.LONGEST:default:}return this.count++,{value:r,done:!1}}async next(){return this.currentPromise=this.nextState(this.currentPromise),this.currentPromise}},tI=class extends wn{constructor(e,t){super(),this.upstream=e,this.bufferSize=t,this.buffer=new Jk(t)}summary(){return`${this.upstream.summary()} -> Prefetch`}refill(){for(;!this.buffer.isFull();){let e=this.upstream.next();this.buffer.push(e)}}next(){return this.refill(),this.buffer.shift()}},kq=class extends tI{constructor(e,t,n){super(e,t),this.upstream=e,this.windowSize=t,this.upstreamExhausted=!1,this.random=sq.alea(n||v.now().toString()),this.lastRead=Promise.resolve({value:null,done:!1})}async next(){return this.lastRead=this.lastRead.then(()=>this.serialNext()),this.lastRead}randomInt(e){return Math.floor(this.random()*e)}chooseIndex(){return this.randomInt(this.buffer.length())}async serialNext(){for(this.upstreamExhausted||this.refill();!this.buffer.isEmpty();){let e=this.chooseIndex(),t=await this.buffer.shuffleExcise(e);if(t.done)this.upstreamExhausted=!0;else return this.refill(),t}return{value:null,done:!0}}},Jc=class{constructor(){this.size=null}batch(e,t=!0){let n=this;v.assert(e>0,()=>`batchSize needs to be positive, but it is
+      ${e}`);let s;return this.size===1/0||this.size==null?s=this.size:t?s=Math.ceil(this.size/e):s=Math.floor(this.size/e),Is(async()=>(await n.iterator()).columnMajorBatch(e,t,Cq),s)}concatenate(e){let t=this,n;return this.size===1/0||e.size===1/0?n=1/0:this.size!=null&&e.size!=null?n=this.size+e.size:n=null,Is(async()=>(await t.iterator()).concatenate(await e.iterator()),n)}filter(e){let t=this,n;return this.size===1/0?n=1/0:n=null,Is(async()=>(await t.iterator()).filter(s=>J(()=>e(s))),n)}async forEachAsync(e){return(await this.iterator()).forEachAsync(e)}map(e){let t=this;return Is(async()=>(await t.iterator()).map(n=>J(()=>e(n))),this.size)}mapAsync(e){let t=this;return Is(async()=>(await t.iterator()).mapAsync(e),this.size)}prefetch(e){if(e==null)throw new RangeError("`Dataset.prefetch()` requires bufferSize to be specified.");let t=this;return Is(async()=>(await t.iterator()).prefetch(e),this.size)}repeat(e){let t=this,n;return this.size!=null&&e>0?n=this.size*e:e===0?n=0:this.size!=null&&(e===void 0||e<0)?n=1/0:n=null,Is(async()=>{let s=wx(async()=>({value:await t.iterator(),done:!1}));return cq(s.take(e))},n)}skip(e){let t=this,n;return this.size!=null&&e>=0&&this.size>=e?n=this.size-e:this.size!=null&&(this.size<e||e===void 0||e<0)?n=0:n=null,Is(async()=>(await t.iterator()).skip(e),n)}shuffle(e,t,n=!0){if(e==null||e<0)throw this.size==null?new RangeError("`Dataset.shuffle()` requires bufferSize to be specified."):new RangeError(`\`Dataset.shuffle()\` requires bufferSize to be specified.  If your data fits in main memory (for regular JS objects), and/or GPU memory (for \`tf.Tensor\`s), consider setting bufferSize to the dataset size (${this.size} elements)`);let s=this,r=nq.alea(t||v.now().toString());return Is(async()=>{let a=r.int32();return n&&(a+=r.int32()),(await s.iterator()).shuffle(e,a.toString())},this.size)}take(e){let t=this,n;return this.size!=null&&this.size>e?n=e:this.size!=null&&this.size<=e?n=this.size:n=null,Is(async()=>(await t.iterator()).take(e),n)}async toArray(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArray()}async toArrayForTest(){if(this.size===1/0)throw new Error("Can not convert infinite data stream to array.");return(await this.iterator()).toArrayForTest()}};Jc.MAX_BUFFER_SIZE=1e4;function Is(e,t=null){return new class extends Jc{constructor(){super(...arguments),this.size=t}async iterator(){return e()}}}function Iq(e){return Is(async()=>Qk(e),e.length)}function Sq(e){if(!rc(e))throw new Error("The argument to zip() must be an object or array.");let t;if(Array.isArray(e))for(let n=0;n<e.length;n++)t=t==null?e[n].size:Math.min(t,e[n].size);else if(e instanceof Object)for(let n in e)t=t==null?e[n].size:Math.min(t,e[n].size);return Is(async()=>{let n=await Yk(e,s=>{if(s instanceof Jc)return{value:s.iterator(),recurse:!1};if(rc(s))return{value:null,recurse:!0};throw new Error("Leaves of the structure passed to zip() must be Datasets, not primitives.")});return dq(n,Ha.SHORTEST)},t)}function Cq(e){if(e===null)return null;let t=e[0];return oq(t)?{value:Tq(e),recurse:!1}:{value:null,recurse:!0}}function Tq(e){if(e.length===0)throw new Error("Can't make a batch of zero elements.");return e[0]instanceof tt?on(e):ft(e)}var nI=class extends Jc{constructor(e){super(),this.input=e}async iterator(){return(await this.input.iterator()).decodeUTF8().split(`
+`).map(s=>(s.endsWith("\r")&&(s=s.slice(0,-1)),s))}},Hf='"',tp=Symbol("out"),i7=Symbol("field"),jf=Symbol("quote"),p3=Symbol("quoteafterquote"),l7=Symbol("quoteinquote"),sI=class extends Jc{constructor(e,t){super(),this.input=e,this.hasHeader=!0,this.fullColumnNames=null,this.columnNamesValidated=!1,this.columnConfigs=null,this.configuredColumnsOnly=!1,this.delimiter=",",this.delimWhitespace=!1,this.base=new nI(e),t||(t={}),this.hasHeader=t.hasHeader!==!1,this.fullColumnNames=t.columnNames,this.columnConfigs=t.columnConfigs,this.configuredColumnsOnly=t.configuredColumnsOnly,t.delimWhitespace?(v.assert(t.delimiter==null,()=>"Delimiter should not be provided when delimWhitespace is true."),this.delimWhitespace=!0,this.delimiter=" "):this.delimiter=t.delimiter?t.delimiter:","}async columnNames(){return this.columnNamesValidated||await this.setColumnNames(),this.configuredColumnsOnly?Object.keys(this.columnConfigs):this.fullColumnNames}async setColumnNames(){let e=await this.maybeReadHeaderLine();if(!this.fullColumnNames&&!e)throw new Error("Column names must be provided if there is no header line.");this.fullColumnNames&&e&&v.assert(e.length===this.fullColumnNames.length,()=>"The length of provided columnNames ("+this.fullColumnNames.length.toString()+") does not match the length of the header line read from file ("+e.length.toString()+")."),this.fullColumnNames||(this.fullColumnNames=e);let t=this.fullColumnNames.reduce((s,r)=>(s[r]=s[r]+1||1,s),{}),n=Object.keys(t).filter(s=>t[s]>1);if(v.assert(n.length===0,()=>"Duplicate column names found: "+n.toString()),this.columnConfigs){for(let s of Object.keys(this.columnConfigs))if(this.fullColumnNames.indexOf(s)===-1)throw new Error('The key "'+s+'" provided in columnConfigs does not match any of the column names ('+this.fullColumnNames.toString()+").")}this.columnNamesValidated=!0}async maybeReadHeaderLine(){if(this.hasHeader){let t=await(await this.base.iterator()).next();if(t.done)throw new Error("No data was found for CSV parsing.");let n=t.value;return this.parseRow(n,!1)}else return null}async iterator(){this.columnNamesValidated||await this.setColumnNames();let e=await this.base.iterator();return this.hasHeader&&(e=e.skip(1)),e.map(t=>this.makeDataElement(t))}makeDataElement(e){let t=this.parseRow(e),n={},s={};for(let r=0;r<this.fullColumnNames.length;r++){let a=this.fullColumnNames[r],o=this.columnConfigs?this.columnConfigs[a]:null;if(!(this.configuredColumnsOnly&&!o)){let i=t[r],l=null;if(i==="")if(o&&o.default!==void 0)l=o.default;else{if(o&&(o.required||o.isLabel))throw new Error(`Required column ${a} is empty in this line: ${e}`);l=void 0}else{let u=Number(i);if(isNaN(u))o&&o.dtype==="bool"?l=this.getBoolean(i):l=i;else if(!o||!o.dtype)l=u;else switch(o.dtype){case"float32":l=u;break;case"int32":l=Math.floor(u);break;case"bool":l=this.getBoolean(i);break;default:l=u}}o&&o.isLabel?s[a]=l:n[a]=l}}return Object.keys(s).length===0?n:{xs:n,ys:s}}getBoolean(e){return e==="1"||e.toLowerCase()==="true"?1:0}parseRow(e,t=!0){let n=[],s=0,r=e.length,a=tp;for(let o=0;o<r;o++)switch(a){case tp:switch(e.charAt(o)){case Hf:s=o+1,a=jf;break;case this.delimiter:if(s=o+1,this.delimiter===" "&&this.delimWhitespace)break;n.push(""),a=tp;break;default:a=i7,s=o;break}break;case i7:switch(e.charAt(o)){case this.delimiter:n.push(e.substring(s,o)),a=tp,s=o+1;break;default:}break;case jf:switch(e.charAt(o)){case Hf:a=p3;break;default:}break;case p3:switch(e.charAt(o)){case this.delimiter:n.push(e.substring(s,o-1)),a=tp,s=o+1;break;case Hf:a=jf;break;default:a=l7;break}break;case l7:switch(e.charAt(o)){case Hf:a=jf;break;default:}break;default:}if(a===p3?n.push(e.substring(s,r-1)):n.push(e.substring(s)),t&&n.length!==this.fullColumnNames.length)throw new Error(`Invalid row in csv file. Should have ${this.fullColumnNames.length} elements in a row, but got ${n}`);return n}},rI=class extends wn{constructor(e){super(),this.microphoneConfig=e,this.isClosed=!1,this.fftSize=e.fftSize||1024;let t=Math.log2(this.fftSize);if(this.fftSize<0||t<4||t>14||!Number.isInteger(t))throw new Error(`Invalid fftSize: it must be a power of 2 between 2 to 4 and 2 to 14, but got ${this.fftSize}`);if(this.numFrames=e.numFramesPerSpectrogram||43,this.sampleRateHz=e.sampleRateHz,this.columnTruncateLength=e.columnTruncateLength||this.fftSize,this.audioTrackConstraints=e.audioTrackConstraints,this.smoothingTimeConstant=e.smoothingTimeConstant||0,this.includeSpectrogram=e.includeSpectrogram!==!1,this.includeWaveform=e.includeWaveform===!0,!this.includeSpectrogram&&!this.includeWaveform)throw new Error("Both includeSpectrogram and includeWaveform are false. At least one type of data should be returned.")}summary(){return"microphone"}static async create(e={}){if(!X().get("IS_BROWSER"))throw new Error("microphone API is only supported in browser environment.");let t=new rI(e);return await t.start(),t}async start(){try{this.stream=await navigator.mediaDevices.getUserMedia({audio:this.audioTrackConstraints==null?!0:this.audioTrackConstraints,video:!1})}catch(n){throw new Error(`Error thrown while initializing video stream: ${n.message}`)}if(!this.stream)throw new Error("Could not obtain audio from microphone.");let e=window.AudioContext||window.webkitAudioContext;if(this.audioContext=new e,!this.sampleRateHz)this.sampleRateHz=this.audioContext.sampleRate;else if(this.audioContext.sampleRate!==this.sampleRateHz)throw new Error(`Mismatch in sampling rate: Expected: ${this.sampleRateHz}; Actual: ${this.audioContext.sampleRate}`);let t=this.audioContext.createMediaStreamSource(this.stream);this.analyser=this.audioContext.createAnalyser(),this.analyser.fftSize=this.fftSize*2,this.analyser.smoothingTimeConstant=this.smoothingTimeConstant,t.connect(this.analyser),this.freqData=new Float32Array(this.fftSize),this.timeData=new Float32Array(this.fftSize)}async next(){if(this.isClosed)return{value:null,done:!0};let e,t,n=await this.getAudioData();if(this.includeSpectrogram){let s=this.flattenQueue(n.freqDataQueue);e=this.getTensorFromAudioDataArray(s,[this.numFrames,this.columnTruncateLength,1])}if(this.includeWaveform){let s=this.flattenQueue(n.timeDataQueue);t=this.getTensorFromAudioDataArray(s,[this.numFrames*this.fftSize,1])}return{value:{spectrogram:e,waveform:t},done:!1}}async capture(){return(await this.next()).value}async getAudioData(){let e=[],t=[],n=0;return new Promise(s=>{let r=setInterval(()=>{this.includeSpectrogram&&(this.analyser.getFloatFrequencyData(this.freqData),this.freqData[0]===-1/0&&s({freqDataQueue:e,timeDataQueue:t}),e.push(this.freqData.slice(0,this.columnTruncateLength))),this.includeWaveform&&(this.analyser.getFloatTimeDomainData(this.timeData),t.push(this.timeData.slice())),++n===this.numFrames&&(clearInterval(r),s({freqDataQueue:e,timeDataQueue:t}))},this.fftSize/this.sampleRateHz*1e3)})}stop(){this.isClosed||(this.isClosed=!0,this.analyser.disconnect(),this.audioContext.close(),this.stream!=null&&this.stream.getTracks().length>0&&this.stream.getTracks()[0].stop())}toArray(){throw new Error("Can not convert infinite audio stream to array.")}getSampleRate(){return this.sampleRateHz}flattenQueue(e){let t=e[0].length,n=new Float32Array(e.length*t);return e.forEach((s,r)=>n.set(s,r*t)),n}getTensorFromAudioDataArray(e,t){let n=new Float32Array(v.sizeFromShape(t));return n.set(e,n.length-e.length),ft(n,t)}},aI=class extends wn{constructor(e,t){if(super(),this.webcamVideoElement=e,this.webcamConfig=t,this.isClosed=!0,this.resize=!1,this.needToResize())if(this.resize=!0,this.cropSize=[this.webcamConfig.resizeHeight,this.webcamConfig.resizeWidth],this.cropBoxInd=Ft([0],"int32"),this.webcamConfig.centerCrop){let n=this.webcamConfig.resizeWidth*1/this.webcamVideoElement.width,s=this.webcamConfig.resizeHeight*1/this.webcamVideoElement.height,r=(1-n)/2,a=(1-s)/2,o=r+n,i=s+a;this.cropBox=or([a,r,i,o],[1,4])}else this.cropBox=or([0,0,1,1],[1,4])}summary(){return"webcam"}static async create(e,t={}){if(!X().get("IS_BROWSER"))throw new Error("tf.data.webcam is only supported in browser environment.");if(!e){if(e=document.createElement("video"),!t.resizeWidth||!t.resizeHeight)throw new Error("Please provide webcam video element, or resizeWidth and resizeHeight to create a hidden video element.");e.width=t.resizeWidth,e.height=t.resizeHeight}let n=new aI(e,t);return await n.start(),n}async start(){this.webcamConfig.facingMode&&v.assert(this.webcamConfig.facingMode==="user"||this.webcamConfig.facingMode==="environment",()=>`Invalid webcam facing mode: ${this.webcamConfig.facingMode}. Please provide 'user' or 'environment'`);try{this.stream=await navigator.mediaDevices.getUserMedia({video:{deviceId:this.webcamConfig.deviceId,facingMode:this.webcamConfig.facingMode?this.webcamConfig.facingMode:"user",width:this.webcamVideoElement.width,height:this.webcamVideoElement.height}})}catch(e){throw e.message=`Error thrown while initializing video stream: ${e.message}`,e}if(!this.stream)throw new Error("Could not obtain video from webcam.");try{this.webcamVideoElement.srcObject=this.stream}catch(e){console.log(e),this.webcamVideoElement.src=window.URL.createObjectURL(this.stream)}return this.webcamVideoElement.play(),this.isClosed=!1,new Promise(e=>{this.webcamVideoElement.onloadedmetadata=()=>{e()}})}async next(){if(this.isClosed)return{value:null,done:!0};let e;try{e=Ys.fromPixels(this.webcamVideoElement)}catch(t){throw new Error(`Error thrown converting video to pixels: ${JSON.stringify(t)}`)}if(this.resize)try{return{value:this.cropAndResizeFrame(e),done:!1}}catch(t){throw new Error(`Error thrown cropping the video: ${t.message}`)}finally{e.dispose()}else return{value:e,done:!1}}needToResize(){return!!(this.webcamConfig.resizeWidth&&this.webcamConfig.resizeHeight&&(this.webcamVideoElement.width!==this.webcamConfig.resizeWidth||this.webcamVideoElement.height!==this.webcamConfig.resizeHeight))}cropAndResizeFrame(e){return J(()=>{let t=Kt(ge(e,"float32"),0),n;n=Ne.cropAndResize(t,this.cropBox,this.cropBoxInd,this.cropSize,"bilinear");let s=n.shape;return U(n,s.slice(1))})}async capture(){return(await this.next()).value}stop(){this.stream.getTracks().forEach(t=>t.stop());try{this.webcamVideoElement.srcObject=null}catch(t){console.log(t),this.webcamVideoElement.src=null}this.isClosed=!0}toArray(){throw new Error("Can not convert infinite video stream to array.")}},oI=class{},iI=class extends wn{split(e){return new Nq(this,e)}},Nq=class extends iI{constructor(e,t){super(),this.upstream=e,this.impl=new Eq(e,t)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Eq=class extends kx{constructor(e,t){super(),this.upstream=e,this.separator=t,this.carryover=""}summary(){return`${this.upstream.summary()} -> Split('${this.separator}')`}async pump(){let e=await this.upstream.next();if(e.done)return this.carryover===""?!1:(this.outputQueue.push(this.carryover),this.carryover="",!0);let t=e.value.split(this.separator);t[0]=this.carryover+t[0];for(let n of t.slice(0,-1))this.outputQueue.push(n);return this.carryover=t[t.length-1],!0}},Rq=class extends wn{decodeUTF8(){return new _q(this)}},_q=class extends iI{constructor(e){super(),this.upstream=e,this.impl=new Dq(e)}summary(){return this.impl.summary()}async next(){return this.impl.next()}},Dq=class extends kx{constructor(e){if(super(),this.upstream=e,X().get("IS_BROWSER"))this.decoder=new TextDecoder("utf-8");else{let{StringDecoder:t}=Y7();this.decoder=new t("utf8")}}summary(){return`${this.upstream.summary()} -> Utf8`}async pump(){let e=await this.upstream.next(),t;if(e.done)return!1;t=e.value;let n;return X().get("IS_BROWSER")?n=this.decoder.decode(t,{stream:!0}):n=this.decoder.write(Buffer.from(t.buffer)),this.outputQueue.push(n),!0}},lI=class extends Rq{constructor(e,t={}){super(),this.file=e,this.options=t,v.assert(e instanceof Uint8Array||(X().get("IS_BROWSER")?e instanceof File||e instanceof Blob:!1),()=>"FileChunkIterator only supports File, Blob and Uint8Array right now."),this.offset=t.offset||0,this.chunkSize=t.chunkSize||1024*1024}summary(){return`FileChunks ${this.file}`}async next(){return this.offset>=(this.file instanceof Uint8Array?this.file.byteLength:this.file.size)?{value:null,done:!0}:{value:await new Promise((t,n)=>{let s=this.offset+this.chunkSize;if(this.file instanceof Uint8Array)t(new Uint8Array(this.file.slice(this.offset,s)));else{let r=new FileReader;r.onload=o=>{let i=r.result;if(i instanceof ArrayBuffer&&(i=new Uint8Array(i)),!(i instanceof Uint8Array))return n(new TypeError("FileReader returned unknown type."));t(i)},r.onabort=o=>n(new Error("Aborted")),r.onerror=o=>n(new Error(o.type));let a=this.file.slice(this.offset,s);r.readAsArrayBuffer(a)}this.offset=s}),done:!1}}};async function $q(e,t={},n){let s,r;typeof e=="string"?s=e:(s=e.url,r=Pq(e));let a=await(n||v.fetch)(s,r);if(a.ok){let o=new Uint8Array(await a.arrayBuffer());return new lI(o,t)}else throw new Error(a.statusText)}var Pq=e=>({method:e.method,headers:e.headers,body:e.body,mode:e.mode,credentials:e.credentials,cache:e.cache,redirect:e.redirect,referrer:e.referrer,integrity:e.integrity});function uI(e){return typeof e=="string"&&e.slice(0,7)==="file://"}var cI=class extends oI{constructor(e,t={}){super(),this.input=e,this.options=t}async iterator(){if(uI(this.input)&&X().get("IS_NODE")){let e=Ay();this.input=e.readFileSync(this.input.slice(7))}return new lI(this.input,this.options)}},dI=class extends oI{constructor(e,t={}){super(),this.url=e,this.fileOptions=t}async iterator(){return uI(this.url)?new cI(this.url,this.fileOptions).iterator():$q(this.url,this.fileOptions)}};function Fq(e,t={}){return new sI(new dI(e),t)}function Oq(e){let t=wx(e);return Is(async()=>t)}function Mq(e){return Is(async()=>{let t=await e();return wx(()=>t.next())})}async function zq(e,t){return aI.create(e,t)}async function Lq(e){return rI.create(e)}var Bq="3.19.0";function Ce(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&v.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the CPU backend.`)})}var Wq=dr.whereImpl,Ix=class extends uc{constructor(){super(),this.blockSize=48,this.firstUse=!0,this.data=new Op(this,sn())}nextDataId(){return Ix.nextDataId++}write(e,t,n){this.firstUse&&(this.firstUse=!1,X().get("IS_NODE")&&C.warn(`
 ============================
 Hi, looks like you are running TensorFlow.js in Node.js. To speed things up dramatically, install our node backend, visit https://github.com/tensorflow/tfjs-node for more details. 
-============================`));let s={id:this.nextDataId()};return this.data.set(s,{values:e,dtype:n,refCount:1}),s}makeTensorInfo(e,t,n){let s;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let r=n.map(a=>v.encodeString(a));s=this.write(r,e,t)}else s=this.write(n,e,t);return{dataId:s,shape:e,dtype:t}}refCount(e){return this.data.has(e)?this.data.get(e).refCount:0}incRef(e){let t=this.data.get(e);t.refCount++}decRef(e){if(this.data.has(e)){let t=this.data.get(e);t.refCount--}}move(e,t,n,s,r){this.data.set(e,{values:t,dtype:s,refCount:r})}numDataIds(){return this.data.numDataIds()}async read(e){return this.readSync(e)}readSync(e){let{dtype:t,complexTensorInfos:n}=this.data.get(e);if(t==="complex64"){let s=this.readSync(n.real.dataId),r=this.readSync(n.imag.dataId);return C.mergeRealAndImagArrays(s,r)}return this.data.get(e).values}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let n=t.map(s=>v.decodeString(s));return Le(e.shape,e.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Le(e.shape,e.dtype,t)}makeOutput(e,t,n){return sn().makeTensorFromTensorInfo(this.makeTensorInfo(t,n,e),this)}disposeData(e,t=!1){if(this.data.has(e)){if(this.data.get(e).refCount--,!t&&this.data.get(e).refCount>0)return!1;let{complexTensorInfos:n}=this.data.get(e);n!=null&&(this.disposeData(n.real.dataId,!0),this.disposeData(n.imag.dataId,!0)),this.data.delete(e)}return!0}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}async time(e){let t=v.now();return e(),{kernelMs:v.now()-t}}memory(){return{unreliable:!0,reasons:["The reported memory is an upper bound. Due to automatic garbage collection, the true allocated memory may be less."]}}where(e){Ce([e],"where");let t=this.readSync(e.dataId);return Wq(e.shape,t)}dispose(){}floatPrecision(){return 32}epsilon(){return super.epsilon()}};Ix.nextDataId=0;var Sx={};Ve(Sx,{addImpl:()=>hI,bincountImpl:()=>Tx,bincountReduceImpl:()=>fI,ceilImpl:()=>mI,concatImpl:()=>Nx,equalImpl:()=>gI,expImpl:()=>AI,expm1Impl:()=>bI,floorImpl:()=>vI,gatherNdImpl:()=>wI,gatherV2Impl:()=>kI,greaterEqualImpl:()=>SI,greaterImpl:()=>II,lessEqualImpl:()=>TI,lessImpl:()=>CI,linSpaceImpl:()=>NI,logImpl:()=>EI,maxImpl:()=>RI,maximumImpl:()=>_I,minimumImpl:()=>DI,multiplyImpl:()=>Ex,negImpl:()=>$I,notEqualImpl:()=>PI,prodImpl:()=>FI,rangeImpl:()=>_x,rsqrtImpl:()=>OI,scatterImpl:()=>Bu,sigmoidImpl:()=>EX,simpleAbsImpl:()=>pI,sliceImpl:()=>_m,sparseFillEmptyRowsImpl:()=>zI,sparseReshapeImpl:()=>LI,sparseSegmentReductionImpl:()=>Dx,sqrtImpl:()=>DX,squaredDifferenceImpl:()=>BI,stridedSliceImpl:()=>WI,stringNGramsImpl:()=>$x,stringSplitImpl:()=>Px,stringToHashBucketFastImpl:()=>Fx,subImpl:()=>VI,tileImpl:()=>UI,topKImpl:()=>HI,transposeImpl:()=>Rx,uniqueImpl:()=>jI});function pI(e){let t=new Float32Array(e.length);for(let n=0;n<e.length;++n)t[n]=Math.abs(e[n]);return t}var Vq=e=>{let{x:t}=e.inputs,n=e.backend;Ce(t,"abs");let s=new Float32Array(v.sizeFromShape(t.shape)),r=n.data.get(t.dataId).values;return s=pI(r),n.makeOutput(s,t.shape,t.dtype)},Uq={kernelName:il,backendName:"cpu",kernelFunc:Vq};function un(e){return(t,n,s,r,a)=>{let o=C.assertAndGetBroadcastShape(t,n),i=o.length,l=v.computeStrides(o),u=v.sizeFromShape(o),c=v.getTypedArrayFromDType(a,u),p=t.length,d=n.length,h=v.computeStrides(t),f=v.computeStrides(n),m=C.getBroadcastDims(t,o),g=C.getBroadcastDims(n,o);if(m.length+g.length===0)for(let y=0;y<c.length;++y)c[y]=e(s[y%s.length],r[y%r.length]);else for(let y=0;y<c.length;++y){let x=v.indexToLoc(y,i,l),A=x.slice(-p);m.forEach(S=>A[S]=0);let b=v.locToIndex(A,p,h),w=x.slice(-d);g.forEach(S=>w[S]=0);let k=v.locToIndex(w,d,f);c[y]=e(s[b],r[k])}return[c,o]}}function Cs(e){let{inputs:t,backend:n}=e,{real:s,imag:r}=t,a=n.data.get(s.dataId).values,o=n.data.get(r.dataId).values,i=n.makeTensorInfo(s.shape,"complex64"),l=n.data.get(i.dataId);return l.complexTensorInfos={real:n.makeTensorInfo(s.shape,"float32",a),imag:n.makeTensorInfo(r.shape,"float32",o)},i}var Gq={kernelName:Lp,backendName:"cpu",kernelFunc:Cs};function Rm(e,t,n="float32"){if(n==="complex64"){let r=Rm(e,t,"float32"),a=Rm(e,t,"float32");return Cs({inputs:{real:r,imag:a},backend:e})}let s=v.makeZerosTypedArray(v.sizeFromShape(t),n);return e.makeTensorInfo(t,n,s)}function Zr(e){let{inputs:t,backend:n}=e,{x:s}=t;return n.incRef(s.dataId),{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}var Hq={kernelName:_o,backendName:"cpu",kernelFunc:Zr};function tl(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.data.get(s.dataId).complexTensorInfos.real,a=n.data.get(r.dataId).values;return n.makeTensorInfo(r.shape,r.dtype,a)}var jq={kernelName:qp,backendName:"cpu",kernelFunc:tl};function io(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dtype:a}=s;if(a==="complex64"){if(r.dtype==="complex64")return Zr({inputs:{x:r},backend:n});let o=Rm(n,r.shape,r.dtype),i=io({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=Cs({inputs:{real:i,imag:o},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}if(r.dtype==="complex64"){let o=tl({inputs:{input:r},backend:n}),i=io({inputs:{x:o},backend:n,attrs:{dtype:a}});return n.disposeIntermediateTensorInfo(o),i}if(!v.hasEncodingLoss(r.dtype,a)){let o=Zr({inputs:{x:r},backend:n});return{dataId:o.dataId,shape:o.shape,dtype:a}}if(a==="int32"){let o=n.data.get(r.dataId).values,i=Int32Array.from(o);return n.makeTensorInfo(r.shape,"int32",i)}if(a==="bool"){let o=n.data.get(r.dataId).values,i=v.toTypedArray([0],r.dtype),[l,u]=un((c,p)=>c!==p?1:0)(r.shape,[],o,i,"bool");return n.makeTensorInfo(u,"bool",l)}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${a}`)}var qq={kernelName:go,backendName:"cpu",kernelFunc:io};function kn(e,t,n,s){return n==null?({inputs:r,backend:a})=>{let{a:o,b:i}=r,l=a;Ce([o,i],e);let u=l.data.get(o.dataId).values,c=l.data.get(i.dataId).values,p=o.dtype==="string"?C.fromUint8ToStringArray(u):u,d=o.dtype==="string"?C.fromUint8ToStringArray(c):c,h=s||o.dtype,[f,m]=t(o.shape,i.shape,p,d,h);return l.makeTensorInfo(m,h,f)}:({inputs:r,backend:a})=>{let{a:o,b:i}=r,l=a;if(o.dtype==="complex64"||i.dtype==="complex64"){let u=io({inputs:{x:o},backend:l,attrs:{dtype:"complex64"}}),c=l.data.get(u.dataId),p=c.complexTensorInfos.real,d=c.complexTensorInfos.imag,h=l.data.get(p.dataId).values,f=l.data.get(d.dataId).values,m=io({inputs:{x:i},backend:l,attrs:{dtype:"complex64"}}),g=l.data.get(m.dataId),y=g.complexTensorInfos.real,x=g.complexTensorInfos.imag,A=l.data.get(y.dataId).values,b=l.data.get(x.dataId).values,[w,k,S]=n(o.shape,i.shape,h,f,A,b),E=l.makeTensorInfo(S,"float32",w),R=l.makeTensorInfo(S,"float32",k),P=Cs({inputs:{real:E,imag:R},backend:l});return l.disposeIntermediateTensorInfo(u),l.disposeIntermediateTensorInfo(m),l.disposeIntermediateTensorInfo(E),l.disposeIntermediateTensorInfo(R),P}else{let u=l.data.get(o.dataId).values,c=l.data.get(i.dataId).values,p=s||o.dtype,[d,h]=t(o.shape,i.shape,u,c,p);return l.makeTensorInfo(h,p,d)}}}function Cx(e){return(t,n,s,r,a,o)=>{let i=C.assertAndGetBroadcastShape(t,n),l=v.sizeFromShape(i),u=i.length,c=v.computeStrides(i),p=v.getTypedArrayFromDType("float32",l),d=v.getTypedArrayFromDType("float32",l),h=C.getBroadcastDims(t,i),f=C.getBroadcastDims(n,i),m=C.mergeRealAndImagArrays(s,r),g=C.mergeRealAndImagArrays(a,o),y=t.length,x=v.computeStrides(t),A=n.length,b=v.computeStrides(n);if(h.length+f.length===0)for(let w=0;w<p.length;w++){let k=w%m.length,S=w%g.length,E=e(m[k*2],m[k*2+1],g[S*2],g[S*2+1]);p[w]=E.real,d[w]=E.imag}else for(let w=0;w<p.length;w++){let k=v.indexToLoc(w,u,c),S=k.slice(-y);h.forEach($=>S[$]=0);let E=v.locToIndex(S,y,x),R=k.slice(-A);f.forEach($=>R[$]=0);let P=v.locToIndex(R,A,b),_=e(m[E*2],m[E*2+1],g[P*2],g[P*2+1]);p[w]=_.real,d[w]=_.imag}return[p,d,i]}}var hI=un((e,t)=>e+t),Xq=Cx((e,t,n,s)=>({real:e+n,imag:t+s})),oc=kn(xa,hI,Xq),Kq={kernelName:xa,backendName:"cpu",kernelFunc:oc};function Tx(e,t,n,s,r){let a=v.sizeFromShape(s),o=v.makeZerosTypedArray(r,n);for(let i=0;i<e.length;i++){let l=e[i];if(l<0)throw new Error("Input x must be non-negative!");l>=r||(a>0?o[l]+=t[i]:o[l]+=1)}return o}function fI(e,t,n,s=!1){let r=e.shape[0],a=e.shape[1],o=Le([r,n],t.dtype);for(let i=0;i<r;i++)for(let l=0;l<a;l++){let u=e.get(i,l);if(u<0)throw new Error("Input x must be non-negative!");u>=n||(s?o.set(1,i,u):t.size>0?o.set(o.get(i,u)+t.get(i,l),i,u):o.set(o.get(i,u)+1,i,u))}return o}function di(e){return(t,n,s)=>{let r=v.getTypedArrayFromDType(n,t.length);for(let a=0;a<t.length;++a)r[a]=e(t[a],s);return r}}function bt(e,t,n){return({inputs:s,attrs:r,backend:a})=>{let{x:o}=s;if(Ce(o,e),o.dtype==="string"||n==="string")throw new Error("unaryKernelFunc does not support string input/output");let i=a,l=i.data.get(o.dataId).values,u=v.sizeFromShape(o.shape),c=n||o.dtype,p=v.getArrayFromDType(c,u);for(let d=0;d<u;++d)p[d]=t(l[d],r);return i.makeTensorInfo(o.shape,c,p)}}function ed(e,t,n){return({inputs:s,attrs:r,backend:a})=>{let{x:o}=s;if(Ce(o,e),o.dtype==="string"||n==="string")throw new Error("unaryKernelFunc does not support string input/output");let i=a,l=i.data.get(o.dataId).values,u=n||o.dtype,c=t(l,u,r);return i.makeTensorInfo(o.shape,u,c)}}var mI=di(e=>Math.ceil(e)),Zq=ed(yo,mI),Yq={kernelName:yo,backendName:"cpu",kernelFunc:Zq};function Nx(e,t,n,s){let r=v.getArrayFromDType(n,v.sizeFromShape(t));if(s&&n!=="string"){let a=0;e.forEach(o=>{let i=v.sizeFromShape(o.shape);r.set(o.vals,a),a+=i})}else{let a=0;e.forEach(o=>{let i=n==="string"?C.fromUint8ToStringArray(o.vals):o.vals,l=0;for(let u=0;u<o.shape[0];++u){let c=u*t[1]+a;for(let p=0;p<o.shape[1];++p)r[c+p]=i[l++]}a+=o.shape[1]})}return r}var gI=un((e,t)=>e===t?1:0),yI=kn(hl,gI,null,"bool"),Jq={kernelName:hl,backendName:"cpu",kernelFunc:yI},AI=di(e=>Math.exp(e)),xI=ed(Co,AI,"float32"),Qq={kernelName:Co,backendName:"cpu",kernelFunc:xI},bI=di(e=>Math.expm1(e)),eX=ed(ml,bI),tX={kernelName:ml,backendName:"cpu",kernelFunc:eX},vI=di(e=>Math.floor(e)),nX=ed(To,vI),sX={kernelName:To,backendName:"cpu",kernelFunc:nX};function wI(e,t,n,s,r,a,o,i,l){let u=Le([s,a],n);for(let c=0;c<s;c++){let p=[],d=0;for(let h=0;h<r;h++){let f=e[c*r+h];d+=f*o[h],p.push(f)}if(d<0||d>=l/a)throw new Error(`Invalid indices: ${p} does not index into ${i}`);for(let h=0;h<a;h++)u.values[c*a+h]=t.get(...t.indexToLoc(d*a+h))}return u}function kI(e,t,n){let s=Le(n,e.dtype);for(let r=0;r<s.size;++r){let o=s.indexToLoc(r).slice(),i=o[0],l=o[2],u=t.locToIndex([i,l]);o[2]=t.values[u];let c=e.locToIndex(o);0<=c&&c<e.values.length&&(s.values[r]=e.values[c])}return s}var II=un((e,t)=>e>t?1:0),rX=kn(xl,II,null,"bool"),aX={kernelName:xl,backendName:"cpu",kernelFunc:rX},SI=un((e,t)=>e>=t?1:0),oX=kn(Ro,SI,null,"bool"),iX={kernelName:Ro,backendName:"cpu",kernelFunc:oX},CI=un((e,t)=>e<t?1:0),lX=kn(bl,CI,null,"bool"),uX={kernelName:bl,backendName:"cpu",kernelFunc:lX},TI=un((e,t)=>e<=t?1:0),cX=kn(vl,TI,null,"bool"),dX={kernelName:vl,backendName:"cpu",kernelFunc:cX};function NI(e,t,n){let s=(t-e)/(n-1),r=v.makeZerosTypedArray(n,"float32");r[0]=e;for(let a=1;a<r.length;a++)r[a]=r[a-1]+s;return r}var EI=di(e=>Math.log(e)),pX=ed($o,EI),hX={kernelName:$o,backendName:"cpu",kernelFunc:pX};function RI(e,t,n,s){let r=v.getTypedArrayFromDType(s,v.sizeFromShape(n));for(let a=0;a<r.length;++a){let o=a*t,i=e[o];for(let l=0;l<t;++l){let u=e[o+l];(Number.isNaN(u)||u>i)&&(i=u)}r[a]=i}return r}var _I=un((e,t)=>Math.max(e,t)),fX=kn(Fo,_I),mX={kernelName:Fo,backendName:"cpu",kernelFunc:fX},DI=un((e,t)=>Math.min(e,t)),gX=kn(Lo,DI),yX={kernelName:Lo,backendName:"cpu",kernelFunc:gX},Ex=un((e,t)=>e*t),AX=Cx((e,t,n,s)=>({real:e*n-t*s,imag:e*s+t*n})),A2=kn(Wo,Ex,AX),xX={kernelName:Wo,backendName:"cpu",kernelFunc:A2};function $I(e,t,n){let s=v.createScalarValue(-1,n);return Ex([],t,s,e,n)}function bX(e){let{inputs:t,backend:n}=e,{x:s}=t;Ce(s,"neg");let r=n.data.get(s.dataId).values,[a,o]=$I(r,s.shape,s.dtype);return n.makeTensorInfo(o,s.dtype,a)}var vX={kernelName:Il,backendName:"cpu",kernelFunc:bX},PI=un((e,t)=>e!==t?1:0),wX=kn(Sl,PI,null,"bool"),kX={kernelName:Sl,backendName:"cpu",kernelFunc:wX};function Rx(e,t,n,s,r){let a=t.length,o=v.sizeFromShape(t),i=v.computeStrides(t),l=v.computeStrides(r),u=v.getTypedArrayFromDType(n,v.sizeFromShape(r));for(let c=0;c<o;++c){let p=v.indexToLoc(c,a,i),d=new Array(p.length);for(let f=0;f<d.length;f++)d[f]=p[s[f]];let h=v.locToIndex(d,a,l);u[h]=e[c]}return u}function gs(e){let{inputs:t,attrs:n,backend:s}=e,{x:r}=t,{perm:a}=n;Ce(r,"transpose");let o=r.shape.length,i=new Array(o);for(let p=0;p<i.length;p++)i[p]=r.shape[a[p]];let l=s.data.get(r.dataId).values,u=Rx(l,r.shape,r.dtype,a,i);return{dataId:s.write(u,i,r.dtype),shape:i,dtype:r.dtype}}var IX={kernelName:Hr,backendName:"cpu",kernelFunc:gs};function FI(e,t,n,s){let[r,a]=C.computeOutAndReduceShapes(e,s),o=On(t,"int32"),i=v.makeZerosTypedArray(v.sizeFromShape(r),o),l=v.sizeFromShape(a);for(let u=0;u<i.length;++u){let c=u*l,p=1;for(let d=0;d<l;++d)p*=n[c+d];i[u]=p}return{outVals:i,outShape:r,outDtype:o}}function SX(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;Ce(r,"prod");let i=r.shape.length,l=v.parseAxisParam(a,r.shape),u=C.getAxesPermutation(l,i),c=l,p=r,d=[];u!=null&&(p=gs({inputs:{x:r},backend:n,attrs:{perm:u}}),d.push(p),c=C.getInnerMostAxes(c.length,i));let h=n.data.get(p.dataId).values,{outVals:f,outShape:m,outDtype:g}=FI(p.shape,p.dtype,h,c),y=m;return o&&(y=C.expandShapeToKeepDim(m,l)),d.forEach(x=>n.disposeIntermediateTensorInfo(x)),n.makeTensorInfo(y,g,f)}var CX={kernelName:Ho,backendName:"cpu",kernelFunc:SX};function _x(e,t,n,s){let r=e===t,a=e<t&&n<0,o=t<e&&n>1;if(r||a||o)return v.makeZerosTypedArray(0,s);let i=Math.abs(Math.ceil((t-e)/n)),l=v.makeZerosTypedArray(i,s);t<e&&n===1&&(n=-1),l[0]=e;for(let u=1;u<l.length;u++)l[u]=l[u-1]+n;return l}var OI=di(e=>1/Math.sqrt(e)),TX=ed(Zo,OI),NX={kernelName:Zo,backendName:"cpu",kernelFunc:TX};function Bu(e,t,n,s,r,a,o,i,l,u){let c=[s/r,r],p=e.values,d=t.values;if(s===0)return Le(n,t.dtype);let h=Le(c,t.dtype);typeof l=="string"||typeof l=="number"?h.values.fill(l):typeof l=="boolean"&&h.values.fill(+l);for(let f=0;f<a;f++){let m=[],g=0;for(let y=0;y<o;y++){let x=p[f*o+y];m.push(x),g+=x*i[y]}if(g<0||g>=s/r)throw new Error(`Invalid indices: ${m} does not index into ${n}`);for(let y=0;y<r;y++)u?h.values[g*r+y]+=d[f*r+y]:h.values[g*r+y]=t.rank===0?d[0]:d[f*r+y]}return h}var EX=di(e=>1/(1+Math.exp(-e))),MI=bt(Jo,e=>1/(1+Math.exp(-e))),RX={kernelName:Jo,backendName:"cpu",kernelFunc:MI};function _m(e,t,n,s,r){let a=Ut.isSliceContinous(s,t,n),o=v.sizeFromShape(n),i=v.computeStrides(s);if(a){let p=Ut.computeFlatOffset(t,i);return r==="string"?e.slice(p,p+o):e.subarray(p,p+o)}let l=r==="string"?C.fromUint8ToStringArray(e):e,u=Le(s,r,l),c=Le(n,r);for(let p=0;p<c.size;++p){let d=c.indexToLoc(p),h=d.map((f,m)=>f+t[m]);c.set(u.get(...h),...d)}return r==="string"?C.fromStringArrayToUint8(c.values):c.values}function nl(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,size:o}=s;Ce(r,"slice");let[i,l]=Ut.parseSliceParams(r,a,o);Ut.assertParamsValid(r,i,l);let u=n.data.get(r.dataId).values,c=_m(u,i,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,c)}var _X={kernelName:Ol,backendName:"cpu",kernelFunc:nl};function zI(e,t,n,s,r,a,o){let i=t[0],l=a[0],u=new Array(l),c=new Array(i),p=t[1];if(l===0){if(i!==0)throw new Error(C.getSparseFillEmptyRowsIndicesDenseShapeMismatch(i));let g=v.getArrayFromDType(n,0),y=v.getArrayFromDType(r,0);return[g,[0,p],y,u,c]}let d=!0,h=0,f=new Array(l).fill(0);for(let g=0;g<i;++g){let y=e[g*p];if(y<0)throw new Error(C.getSparseFillEmptyRowsNegativeIndexErrorMessage(g,y));if(y>=l)throw new Error(C.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(g,y,l));++f[y],d=d&&y>=h,h=y}let m=!0;for(let g=0;g<l;++g){let y=f[g]===0;u[g]=y,m=m&&!y,f[g]=Math.max(f[g],1),g>0&&(f[g]+=f[g-1])}if(m&&d){let g=e,y=s;for(let x=0;x<i;++x)c[x]=x;return[g,[i,p],y,u,c]}else{let g=f[l-1],y=v.getArrayFromDType(n,g*p),x=v.getArrayFromDType(r,g),A=new Array(l).fill(0);for(let b=0;b<i;++b){let w=e[b*p],k=A[w],S=(w===0?0:f[w-1])+k;A[w]++;for(let E=0;E<p;++E)y[S*p+E]=e[b*p+E];x[S]=s[b],c[b]=S}for(let b=0;b<l;++b)if(A[b]===0){let k=b===0?0:f[b-1];y[k*p+0]=b;for(let S=1;S<p;++S)y[k*p+S]=0;x[k]=o}return[y,[g,p],x,u,c]}}function LI(e,t,n,s,r){let a=v.sizeFromShape(s),o=t[0],i=r.length,l=[],u=1,c=-1;for(let g=0;g<i;++g){let y=r[g];if(y===-1){if(c!==-1)throw new Error(C.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(c,g));c=g,l.push(1)}else{if(y<0)throw new Error(C.getSparseReshapeNegativeOutputDimErrorMessage(g,y));u*=y,l.push(y)}}if(c!==-1){if(u<=0)throw new Error(C.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage());let g=Math.trunc(a/u);if(u*g!==a)throw new Error(C.getSparseReshapeInputOutputMultipleErrorMessage(s,l));l[c]=g}if(v.sizeFromShape(l)!==a)throw new Error(C.getSparseReshapeInputOutputMismatchErrorMessage(s,l));let d=s.length,h=[];if(d>0){h[d-1]=1;for(let g=d-2;g>=0;--g)h[g]=h[g+1]*s[g+1]}let f=[];if(i>0){f[i-1]=1;for(let g=i-2;g>=0;--g)f[g]=f[g+1]*l[g+1]}let m=v.getArrayFromDType(n,o*i);for(let g=0;g<o;++g){let y=0;for(let x=0;x<d;++x)y+=e[g*d+x]*h[x];for(let x=0;x<i;++x)m[g*i+x]=Math.trunc(y/f[x]),y%=f[x]}return[m,[o,i],l]}function Dx(e,t,n,s,r,a=!1,o=0){let i=s.length,l=[t[0],e.length/t[0]],u=l[1],p=i>0?r[i-1]+1:0;if(p<0)throw new Error(C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let d=t.slice();d[0]=p;let h=d.reduce((A,b)=>A*b,1),f=v.getArrayFromDType(n,h);if(i===0)return p>0&&f.fill(o),[f,d];if(p<=0)throw new Error(C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let m=0,g=1,y=0,x=r[m];for(;;){let A=0;if(g<i){if(A=r[g],x===A){++g;continue}if(x>=A)throw new Error(C.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage())}if(x<0||x>=p)throw new Error(C.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(x,p));x>y&&f.fill(o,y*u,x*u);for(let b=m;b<g;++b){let w=s[b];if(w<0||w>=l[0])throw new Error(C.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(b,s[b],l[0]));for(let k=0;k<u;k++)f[x*u+k]+=e[w*u+k]}if(a)for(let b=0;b<u;b++)f[x*u+b]/=g-m;if(m=g,++g,y=x+1,x=A,g>i)break}return y<p&&f.fill(o,y*u,p*u),[f,d]}var DX=di(e=>Math.sqrt(e)),$X=bt(Qo,e=>Math.sqrt(e)),PX={kernelName:Qo,backendName:"cpu",kernelFunc:$X},BI=un((e,t)=>{let n=e-t;return n*n}),FX=kn(ni,BI),OX={kernelName:ni,backendName:"cpu",kernelFunc:FX};function WI(e,t,n,s){let r=Le(e,t.dtype);for(let a=0;a<r.size;a++){let o=r.indexToLoc(a),i=new Array(o.length);for(let l=0;l<i.length;l++)i[l]=o[l]*n[l]+s[l];r.set(t.get(...i),...o)}return r}var MX=class{constructor(e,t,n,s,r,a){this.separator=v.encodeString(e),this.nGramWidths=t,this.leftPad=v.encodeString(n),this.rightPad=v.encodeString(s),this.padWidth=r,this.preserveShort=a}getPadWidth(e){return Math.min(this.padWidth<0?e-1:this.padWidth,e-1)}getNumNGrams(e,t){let n=this.getPadWidth(t);return Math.max(0,e+2*n-t+1)}createNGrams(e,t,n,s,r,a){for(let o=0;o<r;++o){let i=this.getPadWidth(a),l=Math.max(0,i-o),u=Math.max(0,i-(r-(o+1))),c=a-(l+u),p=t+(l>0?0:o-i),d=0;d+=l*this.leftPad.length;for(let y=0;y<c;++y)d+=e[p+y].length;d+=u*this.rightPad.length,d+=(l+u+c-1)*this.separator.length,n[s+o]=new Uint8Array(d);let f=n[s+o],m=0,g=y=>y.forEach(x=>f[m++]=x);for(let y=0;y<l;++y)g(this.leftPad),g(this.separator);for(let y=0;y<c-1;++y)g(e[p+y]),g(this.separator);if(c>0){g(e[p+c-1]);for(let y=0;y<u;++y)g(this.separator),g(this.rightPad)}else{for(let y=0;y<u-1;++y)g(this.rightPad),g(this.separator);g(this.rightPad)}}}compute(e,t){let n=e.length,s=t.length;if(s>0){let i=t[0];if(i!==0)throw new Error(`First split value must be 0, got ${i}`);for(let l=1;l<s;++l){let u=t[l]>=i;if(u=u&&t[l]<=n,!u)throw new Error(`Invalid split value ${t[l]}, must be in [${i}, ${n}]`);i=t[l]}if(i!==n)throw new Error(`Last split value must be data size. Expected ${n}, got ${i}`)}let r=s-1,a=v.getArrayFromDType("int32",s);if(n===0||s===0){let i=new Array(n);for(let l=0;l<=r;++l)a[l]=0;return[i,a]}a[0]=0;for(let i=1;i<=r;++i){let l=t[i]-t[i-1],u=0;this.nGramWidths.forEach(c=>{u+=this.getNumNGrams(l,c)}),this.preserveShort&&l>0&&u===0&&(u=1),a[i]=a[i-1]+u}let o=new Array(a[r]);for(let i=0;i<r;++i){let l=t[i],u=a[i];if(this.nGramWidths.forEach(c=>{let p=t[i+1]-t[i],d=this.getNumNGrams(p,c);this.createNGrams(e,l,o,u,d,c),u+=d}),this.preserveShort&&u===a[i]){let c=t[i+1]-t[i];if(c===0)continue;let p=c+2*this.padWidth,d=1;this.createNGrams(e,l,o,u,d,p)}}return[o,a]}};function $x(e,t,n,s,r,a,o,i){return new MX(n,s,r,a,o,i).compute(e,t)}function zX(e,t,n,s){if(!e.length)return;if(t.length===0){for(let a=0;a<e.length;++a)s.push(e.subarray(a,a+1));return}if(t.length===1){let a=t[0],o=e.indexOf(a);for(;o!==-1;){let i=e.subarray(0,o);(!n||i.length!==0)&&s.push(i),e=e.subarray(o+1),o=e.indexOf(a)}(!n||e.length!==0)&&s.push(e);return}let r=0;for(let a=0;a<e.length+1;a++)if(a===e.length||t.indexOf(e[a])!==-1){let o=e.subarray(r,a);(!n||o.length!==0)&&s.push(o),r=a+1}}function Px(e,t,n){let s=e.length,r=[],a=0,o=0,i=new Array(s);for(let d=0;d<s;++d){let h=r.length;zX(e[d],t,n,r);let f=r.length-h;i[d]=f,a+=f,o=Math.max(o,f)}let l=v.getArrayFromDType("int32",a*2),u=new Array(a),c=[s,o],p=0;for(let d=0;d<s;++d)for(let h=0;h<i[d];++h)l[p*2]=d,l[p*2+1]=h,u[p]=r[p],++p;return[l,u,c]}function Fx(e,t){let n=v.getArrayFromDType("int32",e.length);for(let s=0;s<e.length;++s)n[s]=v.fingerPrint64(e[s]).modulo(t).getLowBitsUnsigned();return n}var VI=un((e,t)=>e-t),LX=Cx((e,t,n,s)=>({real:e-n,imag:t-s})),Ox=kn(si,VI,LX),BX={kernelName:si,backendName:"cpu",kernelFunc:Ox};function UI(e,t){let n=new Array(e.rank);for(let r=0;r<n.length;r++)n[r]=e.shape[r]*t[r];let s=Le(n,e.dtype);for(let r=0;r<s.values.length;++r){let a=s.indexToLoc(r),o=new Array(e.rank);for(let l=0;l<o.length;l++)o[l]=a[l]%e.shape[l];let i=e.locToIndex(o);s.values[r]=e.values[i]}return s}var ip=(e,t)=>{let n=t.value-e.value;return n===0?e.index-t.index:n};function GI(e,t,n=0,s=e.length-1){for(;s>n;){if(s-n>600){let i=s-n+1,l=t-n+1,u=Math.log(i),c=.5*Math.exp(2*u/3),p=.5*Math.sqrt(u*c*(i-c)/i)*Math.sign(l-i/2),d=Math.max(n,Math.floor(t-l*c/i+p)),h=Math.min(s,Math.floor(t+(i-l)*c/i+p));GI(e,t,d,h)}let r=e[t],a=n,o=s;for(v.swap(e,n,t),ip(e[s],r)>0&&v.swap(e,n,s);a<o;){for(v.swap(e,a,o),a++,o--;ip(e[a],r)<0;)a=a+1;for(;ip(e[o],r)>0;)o=o-1}ip(e[n],r)===0?v.swap(e,n,o):(o=o+1,v.swap(e,o,s)),o<=t&&(n=o+1),t<=o&&(s=o-1)}}function HI(e,t,n,s,r){let a=t[t.length-1],[o,i]=[e.length/a,a],l=v.getTypedArrayFromDType(n,o*s),u=v.getTypedArrayFromDType("int32",o*s);for(let p=0;p<o;p++){let d=p*i,h=e.subarray(d,d+i),f=new Array(h.length);h.forEach((x,A)=>f[A]={value:x,index:A}),s<f.length&&(GI(f,s),f=f.slice(0,s)),r&&f.sort(ip);let m=p*s,g=l.subarray(m,m+s),y=u.subarray(m,m+s);for(let x=0;x<s;x++)g[x]=f[x].value,y[x]=f[x].index}let c=t.slice();return c[c.length-1]=s,[Le(c,n,l),Le(c,"int32",u)]}function jI(e,t,n,s){let r=v.parseAxisParam(t,n)[0],a=[1,n[0],1];for(let f=0;f<r;f++)a[0]*=n[f];a[1]=n[r];for(let f=r+1;f<n.length;f++)a[2]*=n[f];let o={},i=new Int32Array(n[r]),l=new fn(a,s,e),u=[],c=a[0]===1&&a[2]===1;for(let f=0;f<n[r];f++){let m;if(c)m=e[f].toString();else{let g=[];for(let y=0;y<a[0];y++)for(let x=0;x<a[2];x++)g.push(l.get(y,f,x));m=g.join(",")}if(o[m]!==void 0)i[f]=o[m];else{let g=Object.keys(o).length;o[m]=g,i[f]=g,u.push(f)}}let p=a.slice();p[1]=Object.keys(o).length;let d=new fn(p,s);u.forEach((f,m)=>{for(let g=0;g<a[0];g++)for(let y=0;y<a[2];y++)d.set(l.get(g,f,y),g,m,y)});let h=n.slice();return h[r]=p[1],{outputValues:d.values,outputShape:h,indices:i}}ql("cpu",()=>new Ix,1);var qI=bt(So,e=>e>=0?e:Math.exp(e)-1),WX={kernelName:So,backendName:"cpu",kernelFunc:qI};function XI(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s;Ce([r],"leakyRelu");let o=v.sizeFromShape(r.shape),i=n.data.get(r.dataId).values,l=v.getTypedArrayFromDType("float32",o);for(let u=0;u<i.length;u++)l[u]=i[u]<0?a*i[u]:i[u];return n.makeTensorInfo(r.shape,"float32",l)}var VX={kernelName:Do,backendName:"cpu",kernelFunc:XI},UX=un((e,t)=>e<0?t*e:e);function KI(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t;Ce([s,r],"prelu");let a=n.data.get(s.dataId).values,o=n.data.get(r.dataId).values,[i,l]=UX(s.shape,r.shape,a,o,"float32");return n.makeTensorInfo(l,"float32",i)}var GX={kernelName:Go,backendName:"cpu",kernelFunc:KI},ZI=bt(jo,e=>Math.max(0,e)),HX={kernelName:jo,backendName:"cpu",kernelFunc:ZI},YI=bt(Ko,e=>Math.min(Math.max(0,e),6)),jX={kernelName:Ko,backendName:"cpu",kernelFunc:YI};function Dm(e,t,n,s,r){if(n==="linear")return Zr({inputs:{x:t},backend:e});if(n==="relu")return ZI({inputs:{x:t},backend:e});if(n==="elu")return qI({inputs:{x:t},backend:e});if(n==="relu6")return YI({inputs:{x:t},backend:e});if(n==="prelu")return KI({inputs:{x:t,alpha:s},backend:e});if(n==="leakyrelu")return XI({inputs:{x:t},backend:e,attrs:{alpha:r}});if(n==="sigmoid")return MI({inputs:{x:t},backend:e});throw new Error(`Activation ${n} has not been implemented for the CPU backend.`)}function Rt(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{shape:a}=s,o=v.sizeFromShape(r.shape),i=v.inferFromImplicitShape(a,o),l=v.sizeFromShape(i);v.assert(o===l,()=>`The new shape (${i}) has ${l} elements and the old shape (${r.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`),n.incRef(r.dataId);let u=n.data.get(r.dataId);if(u.complexTensorInfos!=null){let c=u.complexTensorInfos.real,p=u.complexTensorInfos.imag;c.shape=i,p.shape=i}return{dataId:r.dataId,shape:i,dtype:r.dtype}}var qX={kernelName:_l,backendName:"cpu",kernelFunc:Rt};function JI(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;Ce([r,a],"matMul");let l=r.shape.length,u=a.shape.length,c=o?r.shape[l-2]:r.shape[l-1],p=i?a.shape[u-1]:a.shape[u-2],d=o?r.shape[l-1]:r.shape[l-2],h=i?a.shape[u-2]:a.shape[u-1],f=r.shape.slice(0,-2),m=a.shape.slice(0,-2),g=v.sizeFromShape(f),y=v.sizeFromShape(m),A=Xl.assertAndGetBroadcastShape(r.shape.slice(0,-2),a.shape.slice(0,-2)).concat([d,h]);v.assert(c===p,()=>`Error in matMul: inner shapes (${c}) and (${p}) of Tensors with shapes ${r.shape} and ${a.shape} and transposeA=${o} and transposeB=${i} must match.`);let b=o?[g,c,d]:[g,d,c],w=i?[y,h,p]:[y,p,h],k=Rt({inputs:{x:r},backend:n,attrs:{shape:b}}),S=Rt({inputs:{x:a},backend:n,attrs:{shape:w}}),E=o?k.shape[1]:k.shape[2],R=o?k.shape[2]:k.shape[1],P=i?S.shape[1]:S.shape[2],_=Math.max(g,y),$=n.data.get(k.dataId).values,T=n.data.get(S.dataId).values,F=v.computeStrides(k.shape),G=v.computeStrides(S.shape),[q,z,K]=o?[F[0],1,F[1]]:[F[0],F[1],1],[B,ee,Q]=i?[1,G[1],G[0]]:[G[1],1,G[0]],oe=R*P,Y=Le([_,R,P],k.dtype),ae=Y.values,le=n.blockSize;for(let ye=0;ye<_;ye++)for(let we=0;we<R;we+=le)for(let Re=0;Re<P;Re+=le)for(let _e=0;_e<E;_e+=le){let Be=Math.min(we+le,R),Ge=Math.min(Re+le,P),ot=Math.min(_e+le,E);for(let dt=we;dt<Be;dt++)for(let pt=Re;pt<Ge;pt++){let At=0;for(let $e=_e;$e<ot;$e++){let Tt=Math.min(ye,g-1)*q,It=Math.min(ye,y-1)*Q,Un=$[Tt+dt*z+$e*K],Qt=T[$e*B+pt*ee+It];At+=Un*Qt}ae[ye*oe+(dt*P+pt)]+=At}}return n.disposeIntermediateTensorInfo(k),n.disposeIntermediateTensorInfo(S),n.makeTensorInfo(A,Y.dtype,Y.values)}var XX={kernelName:mo,backendName:"cpu",kernelFunc:JI};function KX(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=s,d,h,f,m=[];d=JI({inputs:{a:r,b:a},attrs:{transposeA:l,transposeB:u},backend:n}),o&&(h=oc({inputs:{a:d,b:o},backend:n}),m.push(d),d=h),c&&(f=Dm(n,d,c,i,p),m.push(d),d=f);for(let y of m)n.disposeIntermediateTensorInfo(y);return d}var ZX={kernelName:Ja,backendName:"cpu",kernelFunc:KX},YX=bt(pc,e=>Math.acos(e)),JX={kernelName:pc,backendName:"cpu",kernelFunc:YX},QX=bt(hc,e=>Math.acosh(e)),eK={kernelName:hc,backendName:"cpu",kernelFunc:QX};function tK(e){let{inputs:t,backend:n}=e,s=t;Ce(t,"addN");let r=s.map(i=>n.data.get(i.dataId).values),a=Le(s[0].shape,s[0].dtype),o=a.values;for(let i=0;i<s.length;i++){let l=r[i];for(let u=0;u<o.length;u++)o[u]+=l[u]}return n.makeTensorInfo(a.shape,a.dtype,a.values)}var nK={kernelName:po,backendName:"cpu",kernelFunc:tK};function sK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;Ce(r,"all");let i=v.parseAxisParam(a,r.shape),l=i,u=C.getAxesPermutation(l,r.shape.length),c=r;u!=null&&(c=gs({inputs:{x:r},backend:n,attrs:{perm:u}}),l=C.getInnerMostAxes(l.length,r.shape.length)),C.assertAxesAreInnerMostDims("all",l,c.shape.length);let[p,d]=C.computeOutAndReduceShapes(c.shape,l),h=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(p),c.dtype),m=n.data.get(c.dataId).values;for(let y=0;y<f.length;++y){let x=y*h,A=m[x];for(let b=0;b<h;++b){let w=m[x+b];A=A&&w}f[y]=A}u!=null&&n.disposeIntermediateTensorInfo(c);let g=n.makeTensorInfo(p,c.dtype,f);if(o){let y=C.expandShapeToKeepDim(p,i),x=Rt({inputs:{x:g},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(g),x}return g}var rK={kernelName:fc,backendName:"cpu",kernelFunc:sK};function aK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;Ce(r,"any");let i=v.parseAxisParam(a,r.shape),l=i,u=C.getAxesPermutation(l,r.shape.length),c=r;u!=null&&(c=gs({inputs:{x:r},backend:n,attrs:{perm:u}}),l=C.getInnerMostAxes(l.length,r.shape.length)),C.assertAxesAreInnerMostDims("any",l,c.shape.length);let[p,d]=C.computeOutAndReduceShapes(c.shape,l),h=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(p),c.dtype),m=n.data.get(c.dataId).values;for(let y=0;y<f.length;++y){let x=y*h,A=m[x];for(let b=0;b<h;++b){let w=m[x+b];A=A||w}f[y]=A}u!=null&&n.disposeIntermediateTensorInfo(c);let g=n.makeTensorInfo(p,c.dtype,f);if(o){let y=C.expandShapeToKeepDim(p,i),x=Rt({inputs:{x:g},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(g),x}return g}var oK={kernelName:mc,backendName:"cpu",kernelFunc:aK};function iK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s;Ce(r,"argMax");let o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=gs({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),o=[o[0]],C.assertAxesAreInnerMostDims("argMax",o,l.shape.length);let[c,p]=C.computeOutAndReduceShapes(l.shape,o),d=v.sizeFromShape(c),h=v.makeZerosTypedArray(d,"int32"),f=v.sizeFromShape(p),m=n.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let y=g*f,x=m[y],A=0;for(let b=0;b<f;++b){let w=m[y+b];w>x&&(x=w,A=b)}h[g]=A}return u.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(c,"int32",h)}var lK={kernelName:ho,backendName:"cpu",kernelFunc:iK};function uK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s;Ce(r,"argMin");let o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=gs({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),o=[o[0]],C.assertAxesAreInnerMostDims("argMin",o,l.shape.length);let[c,p]=C.computeOutAndReduceShapes(l.shape,o),d=v.sizeFromShape(c),h=v.makeZerosTypedArray(d,"int32"),f=v.sizeFromShape(p),m=n.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let y=g*f,x=m[y],A=0;for(let b=0;b<f;++b){let w=m[y+b];w<x&&(x=w,A=b)}h[g]=A}return u.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(c,"int32",h)}var cK={kernelName:gc,backendName:"cpu",kernelFunc:uK},dK=bt(yc,e=>Math.asin(e)),pK={kernelName:yc,backendName:"cpu",kernelFunc:dK},hK=bt(Ac,e=>Math.asinh(e)),fK={kernelName:Ac,backendName:"cpu",kernelFunc:hK},mK=bt(xc,e=>Math.atan(e)),gK={kernelName:xc,backendName:"cpu",kernelFunc:mK},yK=un((e,t)=>Math.atan2(e,t)),AK=kn(vc,yK),xK={kernelName:vc,backendName:"cpu",kernelFunc:AK},bK=bt(bc,e=>Math.atanh(e)),vK={kernelName:bc,backendName:"cpu",kernelFunc:bK};function Mx(e,t,n,s,r,a){let o=r.strideHeight,i=r.strideWidth,l=r.dilationHeight,u=r.dilationWidth,c=r.effectiveFilterHeight,p=r.effectiveFilterWidth,d=r.padInfo.top,h=r.padInfo.left,f=a==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=Le(r.outShape,n),g=m.values,y=r.outShape[1]*r.outShape[2]*r.outShape[3],x=r.outShape[2]*r.outShape[3],A=r.outShape[3];for(let b=0;b<r.batchSize;++b){let w=b*y,k=b*s[0];for(let S=0;S<r.inChannels;++S)for(let E=0;E<r.outHeight;++E){let R=E*o-d,P=Math.max(0,R),_=Math.min(r.inHeight,c+R),$=w+E*x;for(let T=0;T<r.outWidth;++T){let F=T*i-h,G=Math.max(0,F),q=Math.min(r.inWidth,p+F),z=f,K=0,B=0;for(let Q=P;Q<_;Q+=l){let oe=k+Q*s[1];for(let Y=G;Y<q;Y+=u){let ae=oe+Y*s[2],le=e[ae+S];a==="max"&&le>z?z=le:a==="avg"&&(K+=le,B++)}if(isNaN(z))break}let ee=$+T*A+S;g[ee]=a==="avg"?K/B:z}}}return m}function QI(e,t,n,s,r=!1,a=!1){let o=Le(s.outShape,"int32"),i=s.strideHeight,l=s.strideWidth,u=s.dilationHeight,c=s.dilationWidth,p=s.effectiveFilterHeight,d=s.effectiveFilterWidth,h=s.padInfo.top,f=s.padInfo.left,m=Le(t,n,e);for(let g=0;g<s.batchSize;++g)for(let y=0;y<s.inChannels;++y)for(let x=0;x<s.outHeight;++x){let A=x*i-h,b=A;for(;b<0;)b+=u;let w=Math.min(s.inHeight,p+A);for(let k=0;k<s.outWidth;++k){let S=k*l-f,E=S;for(;E<0;)E+=c;let R=Math.min(s.inWidth,d+S),P=Number.NEGATIVE_INFINITY,_=-1;for(let $=b;$<w;$+=u){let T=$-A;for(let F=E;F<R;F+=c){let G=F-S,q=m.get(g,$,F,y);q>P&&(P=q,r?_=a?((g*s.inHeight+$)*s.inWidth+F)*s.inChannels+y:($*s.inWidth+F)*s.inChannels+y:_=T*d+G)}}o.set(_,g,x,k,y)}}return o}function eS(e,t,n,s,r,a){let o=r.strideDepth,i=r.strideHeight,l=r.strideWidth,u=r.dilationDepth,c=r.dilationHeight,p=r.dilationWidth,d=r.effectiveFilterDepth,h=r.effectiveFilterHeight,f=r.effectiveFilterWidth,m=r.padInfo.front,g=r.padInfo.top,y=r.padInfo.left,x=a==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,A=Le(r.outShape,n),b=A.values,w=r.outShape[1]*r.outShape[2]*r.outShape[3]*r.outShape[4],k=r.outShape[2]*r.outShape[3]*r.outShape[4],S=r.outShape[3]*r.outShape[4],E=r.outShape[4];for(let R=0;R<r.batchSize;++R){let P=R*w,_=R*s[0];for(let $=0;$<r.inChannels;++$)for(let T=0;T<r.outDepth;++T){let F=T*o-m,G=F;for(;G<0;)G+=u;let q=Math.min(r.inDepth,d+F),z=P+T*k;for(let K=0;K<r.outHeight;++K){let B=K*i-g,ee=B;for(;ee<0;)ee+=c;let Q=Math.min(r.inHeight,h+B),oe=z+K*S;for(let Y=0;Y<r.outWidth;++Y){let ae=Y*l-y,le=ae;for(;le<0;)le+=p;let ye=Math.min(r.inWidth,f+ae),we=oe+Y*E,Re=x,_e=0,Be=0;for(let ot=G;ot<q;ot+=u){let dt=_+ot*s[1];for(let pt=ee;pt<Q;pt+=c){let At=dt+pt*s[2];for(let $e=le;$e<ye;$e+=p){let Tt=At+$e*s[3],It=e[Tt+$];if(a==="max"&&It>Re?Re=It:a==="avg"&&(_e+=It,Be++),isNaN(Re))break}if(isNaN(Re))break}if(isNaN(Re))break}let Ge=we+$;b[Ge]=a==="avg"?_e/Be:Re}}}}return A}function wK(e,t){let n=Le(t.outShape,"int32"),s=t.strideDepth,r=t.strideHeight,a=t.strideWidth,o=t.dilationDepth,i=t.dilationHeight,l=t.dilationWidth,u=t.effectiveFilterDepth,c=t.effectiveFilterHeight,p=t.effectiveFilterWidth,d=t.padInfo.front,h=t.padInfo.top,f=t.padInfo.left;for(let m=0;m<t.batchSize;++m)for(let g=0;g<t.inChannels;++g)for(let y=0;y<t.outDepth;++y){let x=y*s-d,A=x;for(;A<0;)A+=o;let b=Math.min(t.inDepth,u+x);for(let w=0;w<t.outHeight;++w){let k=w*r-h,S=k;for(;S<0;)S+=i;let E=Math.min(t.inHeight,c+k);for(let R=0;R<t.outWidth;++R){let P=R*a-f,_=P;for(;_<0;)_+=l;let $=Math.min(t.inWidth,p+P),T=Number.NEGATIVE_INFINITY,F=-1;for(let G=A;G<b;G+=o){let q=G-x;for(let z=S;z<E;z+=i){let K=z-k;for(let B=_;B<$;B+=l){let ee=B-P,Q=e.get(m,G,z,B,g);Q>=T&&(T=Q,F=q*c*p+K*c+ee)}}}n.set(F,m,y,w,R,g)}}}return n}function kK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;Ce(r,"avgPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;v.assert(C.eitherStridesOrDilationsAreOne(o,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=C.computePool2DInfo(r.shape,a,o,u,i,l),p;if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))p=Zr({inputs:{x:r},backend:n});else{let d=n.data.get(r.dataId).values,h=v.computeStrides(r.shape),f=Mx(d,r.shape,r.dtype,h,c,"avg");p=n.makeTensorInfo(c.outShape,r.dtype,f.values)}return p}var IK={kernelName:fo,backendName:"cpu",kernelFunc:kK};function SK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l,dataFormat:u}=s;Ce(r,"avgPool3d");let c=C.computePool3DInfo(r.shape,a,o,1,i,l,u),p=n.data.get(r.dataId).values,d=eS(p,r.shape,r.dtype,v.computeStrides(r.shape),c,"avg");return n.makeTensorInfo(d.shape,"float32",d.values)}var CK={kernelName:zp,backendName:"cpu",kernelFunc:SK};function TK(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=s;Ce([r,a],"avgPool3DGrad");let c=C.computePool3DInfo(a.shape,o,i,1,l,u),p=c.strideDepth,d=c.strideHeight,h=c.strideWidth,f=c.filterDepth,m=c.filterHeight,g=c.filterWidth,y=c.dilationDepth,x=c.dilationHeight,A=c.dilationWidth,b=c.effectiveFilterDepth,w=c.effectiveFilterHeight,k=c.effectiveFilterWidth,S=b-1-c.padInfo.front,E=k-1-c.padInfo.left,R=w-1-c.padInfo.top,P=Le(a.shape,"float32"),_=1/(f*m*g),$=n.bufferSync(r);for(let T=0;T<c.batchSize;++T)for(let F=0;F<c.inChannels;++F)for(let G=0;G<c.inDepth;++G)for(let q=0;q<c.inHeight;++q)for(let z=0;z<c.inWidth;++z){let K=G-S,B=q-R,ee=z-E,Q=0;for(let oe=0;oe<b;oe+=y){let Y=(K+oe)/p;if(!(Y<0||Y>=c.outDepth||Math.floor(Y)!==Y))for(let ae=0;ae<w;ae+=x){let le=(B+ae)/d;if(!(le<0||le>=c.outHeight||Math.floor(le)!==le))for(let ye=0;ye<k;ye+=A){let we=(ee+ye)/h;if(we<0||we>=c.outWidth||Math.floor(we)!==we)continue;Q+=$.get(T,Y,le,we,F)}}}P.set(Q*_,T,G,q,z,F)}return n.makeTensorInfo(P.shape,P.dtype,P.values)}var NK={kernelName:Hm,backendName:"cpu",kernelFunc:TK};function EK(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a;Ce([r,a],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=s,c=C.computePool2DInfo(o.shape,i,l,1,u),p=c.strideHeight,d=c.strideWidth,h=c.filterHeight,f=c.filterWidth,m=c.dilationHeight,g=c.dilationWidth,y=c.effectiveFilterHeight,x=c.effectiveFilterWidth,A=x-1-c.padInfo.left,b=y-1-c.padInfo.top,w=Le(o.shape,"float32"),k=1/(h*f),S=n.data.get(r.dataId).values,E=Le(r.shape,"float32",S);for(let R=0;R<c.batchSize;++R)for(let P=0;P<c.inChannels;++P)for(let _=0;_<c.inHeight;++_)for(let $=0;$<c.inWidth;++$){let T=_-b,F=$-A,G=0;for(let q=0;q<y;q+=m){let z=(T+q)/p;if(!(z<0||z>=c.outHeight||Math.floor(z)!==z))for(let K=0;K<x;K+=g){let B=(F+K)/d;if(B<0||B>=c.outWidth||Math.floor(B)!==B)continue;G+=E.get(R,z,B,P)}}w.set(G*k,R,_,$,P)}return n.makeTensorInfo(w.shape,w.dtype,w.values)}var RK={kernelName:Gm,backendName:"cpu",kernelFunc:EK};function _K(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,scale:a,offset:o,mean:i,variance:l}=t;v.assert(i.shape.length===l.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(o==null||i.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(a==null||i.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks."),Ce([r,i,l,a,o],"batchNorm");let{varianceEpsilon:u}=s;u==null&&(u=.001);let c=n.data.get(r.dataId).values,p=n.data.get(i.dataId).values,d=n.data.get(l.dataId).values,h=a?n.data.get(a.dataId).values:new Float32Array([1]),f=o?n.data.get(o.dataId).values:new Float32Array([0]),m=new Float32Array(c.length),g=f.length,y=h.length,x=d.length,A=p.length,b=0,w=0,k=0,S=0;for(let E=0;E<c.length;++E)m[E]=f[b++]+(c[E]-p[w++])*h[k++]/Math.sqrt(d[S++]+u),b>=g&&(b=0),w>=A&&(w=0),k>=y&&(k=0),S>=x&&(S=0);return n.makeTensorInfo(r.shape,r.dtype,m)}var DK={kernelName:Eo,backendName:"cpu",kernelFunc:_K};function $K(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s;Ce([r],"batchToSpaceND");let i=a.reduce((y,x)=>y*x),l=C.getReshaped(r.shape,a,i),u=C.getPermuted(l.length,a.length),c=C.getReshapedPermuted(r.shape,a,i),p=C.getSliceBeginCoords(o,a.length),d=C.getSliceSize(c,o,a.length),h=Rt({inputs:{x:r},backend:n,attrs:{shape:l}}),f=gs({inputs:{x:h},backend:n,attrs:{perm:u}}),m=Rt({inputs:{x:f},backend:n,attrs:{shape:c}}),g=nl({inputs:{x:m},backend:n,attrs:{begin:p,size:d}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),g}var PK={kernelName:ll,backendName:"cpu",kernelFunc:$K};function FK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o}=s,i=n.data.get(r.dataId).values,l=n.data.get(a.dataId).values,u=Tx(i,l,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,u)}var OK={kernelName:jm,backendName:"cpu",kernelFunc:FK};function MK(e){let{inputs:t,backend:n}=e,{s0:s,s1:r}=t,a=n.data.get(s.dataId).values,o=n.data.get(r.dataId).values,i=C.assertAndGetBroadcastShape(Array.from(a),Array.from(o));return n.makeTensorInfo([i.length],"int32",Int32Array.from(i))}var zK={kernelName:qm,backendName:"cpu",kernelFunc:MK},LK=bt(ba,(e,t)=>{let n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e}),BK={kernelName:ba,backendName:"cpu",kernelFunc:LK},WK=e=>{let{x:t}=e.inputs,n=e.backend,s=new Float32Array(v.sizeFromShape(t.shape)),r=n.data.get(t.dataId),a=r.complexTensorInfos.real,o=r.complexTensorInfos.imag,i=n.data.get(a.dataId).values,l=n.data.get(o.dataId).values;for(let u=0;u<i.length;u++){let c=i[u],p=l[u];s[u]=Math.hypot(c,p)}return n.makeOutput(s,t.shape,"float32")},VK={kernelName:Bp,backendName:"cpu",kernelFunc:WK};function ic(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.data.get(s.dataId).complexTensorInfos.imag,a=n.data.get(r.dataId).values;return n.makeTensorInfo(r.shape,r.dtype,a)}var UK={kernelName:Gp,backendName:"cpu",kernelFunc:ic};function lc(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s,a=v.parseAxisParam(r,t[0].shape)[0],o=C.computeOutShape(t.map(m=>m.shape),a);if(v.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let i=t.filter(m=>v.sizeFromShape(m.shape)>0);if(i.length===1)return Zr({inputs:{x:i[0]},backend:n});let l=i.map(m=>m.shape);if(C.assertParamsConsistent(l,a),i[0].dtype==="complex64"){let m=i.map(b=>tl({inputs:{input:b},backend:n})),g=i.map(b=>ic({inputs:{input:b},backend:n})),y=lc({inputs:m,backend:n,attrs:{axis:a}}),x=lc({inputs:g,backend:n,attrs:{axis:a}}),A=Cs({inputs:{real:y,imag:x},backend:n});return m.forEach(b=>n.disposeIntermediateTensorInfo(b)),g.forEach(b=>n.disposeIntermediateTensorInfo(b)),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(x),A}let u=i.map(m=>{let g=v.sizeFromShape(m.shape.slice(a));return Rt({inputs:{x:m},backend:n,attrs:{shape:[-1,g]}})}),c=u.map(m=>({vals:n.data.get(m.dataId).values,shape:m.shape}));o=C.computeOutShape(u.map(m=>m.shape),1);let p=u[0].shape[0]===1,d=Nx(c,o,t[0].dtype,p),h=C.computeOutShape(i.map(m=>m.shape),a),f=n.makeTensorInfo(h,t[0].dtype,d);return u.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var GK={kernelName:ul,backendName:"cpu",kernelFunc:lc};function tS(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=s;Ce([r,a],"conv2d");let p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,a.shape,o,u,i,c,!1,p),h=d.filterHeight,f=d.filterWidth,m=d.dilationHeight,g=d.dilationWidth,y=d.padInfo.left,x=d.padInfo.top,A=d.dataFormat==="channelsLast",b=new fn(d.outShape,r.dtype),w=v.computeStrides(r.shape),k=v.computeStrides(a.shape),S=w[0],E=A?w[1]:w[2],R=A?w[2]:1,P=A?1:w[1],_=b.strides[0],$=A?b.strides[1]:b.strides[2],T=A?b.strides[2]:1,F=A?1:b.strides[1],G=n.data.get(r.dataId).values,q=n.data.get(a.dataId).values,z=b.values;for(let K=0;K<d.batchSize;++K){let B=K*S,ee=K*_;for(let Q=0;Q<d.outHeight;++Q){let oe=ee+Q*$,Y=Q*d.strideHeight-x;for(let ae=0;ae<h;++ae){let le=Y+ae*m;if(le<0||le>=d.inHeight)continue;let ye=ae*k[0],we=B+le*E;for(let Re=0;Re<d.outWidth;++Re){let _e=oe+Re*T,Be=Re*d.strideWidth-y;for(let Ge=0;Ge<f;++Ge){let ot=Be+Ge*g;if(ot<0||ot>=d.inWidth)continue;let dt=ye+Ge*k[1],pt=we+ot*R,At=dt;for(let $e=0;$e<d.inChannels;++$e){let Tt=G[pt+$e*P];for(let It=0;It<d.outChannels;++It)z[_e+It*F]+=Tt*q[At+It];At+=d.outChannels}}}}}}return n.makeTensorInfo(b.shape,b.dtype,z)}var HK={kernelName:Ao,backendName:"cpu",kernelFunc:tS};function jK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=s;Ce([r,a],"conv2dBackpropFilter");let p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,c,o,1,i,u,!1,p),{strideHeight:h,strideWidth:f,filterHeight:m,filterWidth:g}=d,y=d.dataFormat==="channelsLast",x=new fn(d.filterShape,"float32"),A=d.padInfo.left,b=d.padInfo.top,w=n.data.get(r.dataId).values,k=n.data.get(a.dataId).values,S=new fn(r.shape,r.dtype,w),E=new fn(a.shape,a.dtype,k);for(let R=0;R<m;++R){let P=Math.max(0,Math.ceil((b-R)/h)),_=Math.min(d.outHeight,(d.inHeight+b-R)/h);for(let $=0;$<g;++$){let T=Math.max(0,Math.ceil((A-$)/f)),F=Math.min(d.outWidth,(d.inWidth+A-$)/f);for(let G=0;G<d.inChannels;++G)for(let q=0;q<d.outChannels;++q){let z=0;for(let K=0;K<d.batchSize;++K)for(let B=P;B<_;++B){let ee=R+B*h-b;for(let Q=T;Q<F;++Q){let oe=$+Q*f-A;y?z+=S.get(K,ee,oe,G)*E.get(K,B,Q,q):z+=S.get(K,G,ee,oe)*E.get(K,q,B,Q)}}x.set(z,R,$,G,q)}}}return n.makeTensorInfo(x.shape,x.dtype,x.values)}var qK={kernelName:Xm,backendName:"cpu",kernelFunc:jK};function XK(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=s;Ce([r,a],"conv2dBackpropInput");let p=v.computeStrides(a.shape),d=v.computeStrides(r.shape),h=C.convertConv2DDataFormat(u),f=C.computeConv2DInfo(o,a.shape,i,1,l,c,!1,h),m=new fn(f.inShape,"float32"),g=m.values,y=n.data.get(r.dataId).values,x=n.data.get(a.dataId).values,[A,b,w]=p,{batchSize:k,filterHeight:S,filterWidth:E,inChannels:R,inHeight:P,inWidth:_,outChannels:$,outHeight:T,outWidth:F,strideHeight:G,strideWidth:q}=f;h=f.dataFormat;let z=S-1-f.padInfo.top,K=E-1-f.padInfo.left,B=h==="channelsLast",ee=m.strides[0],Q=B?m.strides[1]:m.strides[2],oe=B?m.strides[2]:1,Y=B?1:m.strides[1],ae=d[0],le=B?d[1]:d[2],ye=B?d[2]:1,we=B?1:d[1];for(let Re=0;Re<k;++Re)for(let _e=0;_e<R;++_e)for(let Be=0;Be<P;++Be){let Ge=Be-z,ot=Math.max(0,Math.ceil(Ge/G)),dt=Math.min(T,(S+Ge)/G);for(let pt=0;pt<_;++pt){let At=pt-K,$e=Math.max(0,Math.ceil(At/q)),Tt=Math.min(F,(E+At)/q),It=0;for(let Qt=ot;Qt<dt;++Qt){let bs=Qt*G-Ge;for(let pn=$e;pn<Tt;++pn){let Gn=pn*q-At,vs=ae*Re+le*Qt+ye*pn,ws=A*(S-1-bs)+b*(E-1-Gn)+w*_e;for(let $n=0;$n<$;++$n){let Vs=y[vs+we*$n],Hn=x[ws+$n];It+=Vs*Hn}}}let Un=ee*Re+Q*Be+oe*pt+Y*_e;g[Un]=It}}return n.makeTensorInfo(m.shape,m.dtype,m.values)}var KK={kernelName:xo,backendName:"cpu",kernelFunc:XK};function ZK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s;Ce([r,a],"conv3d");let u=C.computeConv3DInfo(r.shape,a.shape,o,l,i),{filterDepth:c,filterHeight:p,filterWidth:d,dilationDepth:h,dilationHeight:f,dilationWidth:m,padInfo:g}=u,y=g.front,x=g.left,A=g.top,b=new fn(u.outShape,r.dtype),w=n.data.get(r.dataId).values,k=n.data.get(a.dataId).values,S=b.values,E=v.computeStrides(r.shape),R=v.computeStrides(a.shape);for(let P=0;P<u.batchSize;++P){let _=P*E[0],$=P*b.strides[0];for(let T=0;T<u.outDepth;++T){let F=$+T*b.strides[1],G=T*u.strideDepth-y;for(let q=0;q<c;++q){let z=G+q*h;if(z<0||z>=u.inDepth)continue;let K=q*R[0],B=_+z*E[1];for(let ee=0;ee<u.outHeight;++ee){let Q=F+ee*b.strides[2],oe=ee*u.strideHeight-A;for(let Y=0;Y<p;++Y){let ae=oe+Y*f;if(ae<0||ae>=u.inHeight)continue;let le=K+Y*R[1],ye=B+ae*E[2];for(let we=0;we<u.outWidth;++we){let Re=Q+we*u.outChannels,_e=we*u.strideWidth-x;for(let Be=0;Be<d;++Be){let Ge=_e+Be*m;if(Ge<0||Ge>=u.inWidth)continue;let ot=le+Be*R[2],dt=ye+Ge*u.inChannels,pt=ot;for(let At=0;At<u.inChannels;++At){let $e=w[dt+At];for(let Tt=0;Tt<u.outChannels;++Tt)S[Re+Tt]+=$e*k[pt+Tt];pt+=u.outChannels}}}}}}}}return n.makeTensorInfo(b.shape,b.dtype,b.values)}var YK={kernelName:Wp,backendName:"cpu",kernelFunc:ZK};function JK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,filterShape:l}=s;Ce([r,a],"conv3dBackpropFilterV2");let u=v.computeStrides(r.shape),c=v.computeStrides(a.shape),p=C.computeConv3DInfo(r.shape,l,o,1,i),d=p.strideDepth,h=p.strideHeight,f=p.strideWidth,m=p.filterDepth,g=p.filterHeight,y=p.filterWidth,x=new fn(p.filterShape,"float32"),A=x.values,[b,w,k,S]=x.strides,E=n.data.get(a.dataId).values,[R,P,_,$]=c,T=n.data.get(r.dataId).values,[F,G,q,z]=u,K=p.padInfo.front,B=p.padInfo.left,ee=p.padInfo.top;for(let Q=0;Q<m;++Q){let oe=Math.max(0,Math.ceil((K-Q)/d)),Y=Math.min(p.outDepth,(p.inDepth+K-Q)/d),ae=Q*b;for(let le=0;le<g;++le){let ye=Math.max(0,Math.ceil((ee-le)/h)),we=Math.min(p.outHeight,(p.inHeight+ee-le)/h),Re=le*w+ae;for(let _e=0;_e<y;++_e){let Be=Math.max(0,Math.ceil((B-_e)/f)),Ge=Math.min(p.outWidth,(p.inWidth+B-_e)/f),ot=_e*k+Re;for(let dt=0;dt<p.inChannels;++dt){let pt=dt*S+ot;for(let At=0;At<p.outChannels;++At){let $e=0;for(let Tt=0;Tt<p.batchSize;++Tt){let It=Tt*F,Un=Tt*R;for(let Qt=oe;Qt<Y;++Qt){let pn=(Q+Qt*d-K)*G+It,Gn=Qt*P+Un;for(let vs=ye;vs<we;++vs){let $n=(le+vs*h-ee)*q+pn,Vs=vs*_+Gn;for(let Hn=Be;Hn<Ge;++Hn){let aa=(_e+Hn*f-B)*z+$n,xu=Hn*$+Vs;$e+=T[aa+dt]*E[xu+At]}}}}A[pt+At]=$e}}}}}return n.makeTensorInfo(x.shape,x.dtype,x.values)}var QK={kernelName:Km,backendName:"cpu",kernelFunc:JK};function eZ(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{pad:o,strides:i,inputShape:l}=s;Ce([r],"conv3dBackpropInputV2");let u=v.computeStrides(r.shape),c=v.computeStrides(a.shape),p=C.computeConv3DInfo(l,a.shape,i,1,o),d=new fn(p.inShape,"float32"),h=d.values,[f,m,g,y]=d.strides,x=n.data.get(r.dataId).values,[A,b,w,k]=u,S=n.data.get(a.dataId).values,[E,R,P,_]=c,{batchSize:$,filterDepth:T,filterHeight:F,filterWidth:G,inChannels:q,inDepth:z,inHeight:K,inWidth:B,outChannels:ee,outDepth:Q,outHeight:oe,outWidth:Y,strideDepth:ae,strideHeight:le,strideWidth:ye}=p,we=T-1-p.padInfo.front,Re=F-1-p.padInfo.top,_e=G-1-p.padInfo.left;for(let Be=0;Be<$;++Be)for(let Ge=0;Ge<q;++Ge)for(let ot=0;ot<z;++ot){let dt=ot-we,pt=Math.max(0,Math.ceil(dt/ae)),At=Math.min(Q,(T+dt)/ae);for(let $e=0;$e<K;++$e){let Tt=$e-Re,It=Math.max(0,Math.ceil(Tt/le)),Un=Math.min(oe,(F+Tt)/le);for(let Qt=0;Qt<B;++Qt){let bs=Qt-_e,pn=Math.max(0,Math.ceil(bs/ye)),Gn=Math.min(Y,(G+bs)/ye),vs=0;for(let ws=pt;ws<At;++ws){let $n=ws*ae-dt;for(let Vs=It;Vs<Un;++Vs){let Hn=Vs*le-Tt;for(let ra=pn;ra<Gn;++ra){let aa=ra*ye-bs,xu=A*Be+b*ws+w*Vs+k*ra,Oa=E*(T-1-$n)+R*(F-1-Hn)+P*(G-1-aa)+_*Ge;for(let oa=0;oa<ee;++oa){let Md=x[xu+oa],bu=S[Oa+oa];vs+=Md*bu}}}}h[f*Be+m*ot+g*$e+y*Qt+Ge]=vs}}}return n.makeTensorInfo(d.shape,d.dtype,d.values)}var tZ={kernelName:Zm,backendName:"cpu",kernelFunc:eZ},nZ=bt(bo,e=>Math.cos(e)),sZ={kernelName:bo,backendName:"cpu",kernelFunc:nZ},rZ=bt(vo,e=>Math.cosh(e)),aZ={kernelName:vo,backendName:"cpu",kernelFunc:rZ};function oZ(e){let{inputs:t,backend:n,attrs:s}=e,{image:r,boxes:a,boxInd:o}=t,{cropSize:i,method:l,extrapolationValue:u}=s,[c,p,d,h]=r.shape,f=a.shape[0],[m,g]=i,y=Le([f,m,g,h],"float32"),x=n.data.get(a.dataId).values,A=n.data.get(o.dataId).values,b=n.data.get(r.dataId).values,w=v.computeStrides(r.shape),k=v.computeStrides(y.shape);for(let S=0;S<f;S++){let E=S*4,R=x[E],P=x[E+1],_=x[E+2],$=x[E+3],T=A[S];if(T>=c)continue;let F=m>1?(_-R)*(p-1)/(m-1):0,G=g>1?($-P)*(d-1)/(g-1):0;for(let q=0;q<m;q++){let z=m>1?R*(p-1)+q*F:.5*(R+_)*(p-1);if(z<0||z>p-1){for(let K=0;K<g;K++)for(let B=0;B<h;B++){let ee=B+K*k[2]+q*k[1]+S*k[0];y.values[ee]=u}continue}if(l==="bilinear"){let K=Math.floor(z),B=Math.ceil(z),ee=z-K;for(let Q=0;Q<g;Q++){let oe=g>1?P*(d-1)+Q*G:.5*(P+$)*(d-1);if(oe<0||oe>d-1){for(let ye=0;ye<h;ye++){let we=ye+Q*k[2]+q*k[1]+S*k[0];y.values[we]=u}continue}let Y=Math.floor(oe),ae=Math.ceil(oe),le=oe-Y;for(let ye=0;ye<h;ye++){let we=ye+Y*w[2]+K*w[1]+T*w[0],Re=b[we];we=ye+ae*w[2]+K*w[1]+T*w[0];let _e=b[we];we=ye+Y*w[2]+B*w[1]+T*w[0];let Be=b[we];we=ye+ae*w[2]+B*w[1]+T*w[0];let Ge=b[we],ot=Re+(_e-Re)*le,dt=Be+(Ge-Be)*le;we=ye+Q*k[2]+q*k[1]+S*k[0],y.values[we]=ot+(dt-ot)*ee}}}else for(let K=0;K<g;++K){let B=g>1?P*(d-1)+K*G:.5*(P+$)*(d-1);if(B<0||B>d-1){for(let oe=0;oe<h;oe++){let Y=oe+K*k[2]+q*k[1]+S*k[0];y.values[Y]=u}continue}let ee=Math.round(B),Q=Math.round(z);for(let oe=0;oe<h;oe++){let Y=oe+ee*w[2]+Q*w[1]+T*w[0],ae=oe+K*k[2]+q*k[1]+S*k[0];y.values[ae]=b[Y]}}}}return n.makeTensorInfo(y.shape,y.dtype,y.values)}var iZ={kernelName:dl,backendName:"cpu",kernelFunc:oZ};function lZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;Ce(r,"cumprod");let l=C.getAxesPermutation([a],r.shape.length),u=r;l!=null&&(u=gs({inputs:{x:r},backend:n,attrs:{perm:l}}));let c=C.getInnerMostAxes(1,r.shape.length)[0];if(c!==u.shape.length-1)throw new Error(`backend.cumprod in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${c}`);let p=On(u.dtype,"int32"),d=v.makeOnesTypedArray(v.sizeFromShape(u.shape),p),h=n.data.get(u.dataId).values,f=u.shape[u.shape.length-1],m=i?(y,x)=>y+f-x-1:(y,x)=>y+x;for(let y=0;y<h.length;y+=f)for(let x=0;x<f;x++){let A=m(y,x);if(x===0)d[A]=o?1:h[A];else{let b=m(y,x-1);d[A]=o?h[b]*d[b]:h[A]*d[b]}}let g=n.makeTensorInfo(u.shape,p,d);if(l!=null){let y=C.getUndoAxesPermutation(l),x=gs({inputs:{x:g},backend:n,attrs:{perm:y}});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(u),x}return g}var uZ={kernelName:cl,backendName:"cpu",kernelFunc:lZ};function cZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;Ce(r,"cumsum");let l=C.getAxesPermutation([a],r.shape.length),u=r;l!=null&&(u=gs({inputs:{x:r},backend:n,attrs:{perm:l}}));let c=C.getInnerMostAxes(1,r.shape.length)[0];if(c!==u.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${c}`);let p=On(u.dtype,"int32"),d=v.makeZerosTypedArray(v.sizeFromShape(u.shape),p),h=n.data.get(u.dataId).values,f=u.shape[u.shape.length-1],m=i?(y,x)=>y+f-x-1:(y,x)=>y+x;for(let y=0;y<h.length;y+=f)for(let x=0;x<f;x++){let A=m(y,x);if(x===0)d[A]=o?0:h[A];else{let b=m(y,x-1);d[A]=o?h[b]+d[b]:h[A]+d[b]}}let g=n.makeTensorInfo(u.shape,p,d);if(l!=null){let y=C.getUndoAxesPermutation(l),x=gs({inputs:{x:g},backend:n,attrs:{perm:y}});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(u),x}return g}var dZ={kernelName:wo,backendName:"cpu",kernelFunc:cZ};function pZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o,binaryOutput:i}=s;if(r.shape.length===1){let l=n.data.get(r.dataId).values,u=n.data.get(a.dataId).values,c=Tx(l,u,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,c)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(a),c=fI(l,u,o,i);return n.makeTensorInfo(c.shape,a.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var hZ={kernelName:Ym,backendName:"cpu",kernelFunc:pZ};function fZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockSize:a,dataFormat:o}=s;v.assert(o==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. Got ${o}`);let i=r.shape[0],l=r.shape[1],u=r.shape[2],c=r.shape[3],p=l*a,d=u*a,h=c/(a*a),f=n.data.get(r.dataId).values,m=new Float32Array(i*p*d*h),g=0;for(let y=0;y<i;++y)for(let x=0;x<p;++x){let A=Math.floor(x/a),b=x%a;for(let w=0;w<d;++w){let k=Math.floor(w/a),S=w%a,E=(b*a+S)*h;for(let R=0;R<h;++R){let _=R+E+c*(k+u*(A+l*y));m[g++]=f[_]}}}return n.makeTensorInfo([i,p,d,h],r.dtype,m)}var mZ={kernelName:pl,backendName:"cpu",kernelFunc:fZ};function nS(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l,dimRoundingMode:u}=s;Ce([r,a],"depthwiseConv2DNative");let c=v.computeStrides(r.shape),p=v.computeStrides(a.shape),d=l;d==null&&(d=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(o,d),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${o} and dilations '${d}'`);let h=C.computeConv2DInfo(r.shape,a.shape,o,d,i,u,!0),{filterHeight:f,filterWidth:m,dilationHeight:g,dilationWidth:y,padInfo:x}=h,A=x.left,b=x.top,w=h.outChannels/h.inChannels,k=new fn(h.outShape,r.dtype),S=n.data.get(r.dataId).values,E=n.data.get(a.dataId).values,R=k.values;for(let P=0;P<h.batchSize;++P){let _=P*c[0],$=P*k.strides[0];for(let T=0;T<h.outHeight;++T){let F=$+T*k.strides[1],G=T*h.strideHeight-b;for(let q=0;q<f;++q){let z=G+q*g;if(z<0||z>=h.inHeight)continue;let K=q*p[0],B=_+z*c[1];for(let ee=0;ee<h.outWidth;++ee){let Q=F+ee*k.strides[2],oe=ee*h.strideWidth-A;for(let Y=0;Y<m;++Y){let ae=oe+Y*y;if(ae<0||ae>=h.inWidth)continue;let le=K+Y*p[1],ye=B+ae*h.inChannels,we=Q,Re=le;for(let _e=0;_e<h.inChannels;++_e){let Be=S[ye+_e];for(let Ge=0;Ge<w;++Ge)R[we+Ge]+=Be*E[Re+Ge];we+=w,Re+=w}}}}}}return n.makeTensorInfo(k.shape,k.dtype,k.values)}var gZ={kernelName:ko,backendName:"cpu",kernelFunc:nS};function yZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=s;Ce([r,a],"depthwiseConv2dNativeBackpropFilter");let p=C.computeConv2DInfo(r.shape,c,o,i,l,u,!0),{strideHeight:d,strideWidth:h,filterHeight:f,filterWidth:m}=p,g=new fn(p.filterShape,"float32"),y=p.padInfo.left,x=p.padInfo.top,A=p.outChannels/p.inChannels,b=n.data.get(r.dataId).values,w=new fn(r.shape,r.dtype,b),k=n.data.get(a.dataId).values,S=new fn(a.shape,a.dtype,k);for(let E=0;E<f;++E){let R=Math.max(0,Math.ceil((x-E)/d)),P=Math.min(p.outHeight,(p.inHeight+x-E)/d);for(let _=0;_<m;++_){let $=Math.max(0,Math.ceil((y-_)/h)),T=Math.min(p.outWidth,(p.inWidth+y-_)/h);for(let F=0;F<p.outChannels;++F){let G=Math.trunc(F/A),q=F%A,z=0;for(let K=0;K<p.batchSize;++K)for(let B=R;B<P;++B){let ee=E+B*d-x;for(let Q=$;Q<T;++Q){let oe=_+Q*h-y;z+=w.get(K,ee,oe,G)*S.get(K,B,Q,F)}}g.set(z,E,_,G,q)}}}return n.makeTensorInfo(g.shape,g.dtype,g.values)}var AZ={kernelName:Jm,backendName:"cpu",kernelFunc:yZ};function xZ(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=s;Ce([r,a],"depthwiseConv2DNativeBackpropInput");let p=v.computeStrides(r.shape),d=v.computeStrides(a.shape),h=C.computeConv2DInfo(c,a.shape,o,i,l,u,!0),f=new fn(h.inShape,"float32"),m=f.values,[g,y,x]=f.strides,A=n.data.get(r.dataId).values,[b,w,k]=p,S=n.data.get(a.dataId).values,[E,R,P]=d,{batchSize:_,filterHeight:$,filterWidth:T,inChannels:F,inHeight:G,inWidth:q,outChannels:z,outHeight:K,outWidth:B,strideHeight:ee,strideWidth:Q}=h,oe=$-1-h.padInfo.top,Y=T-1-h.padInfo.left,ae=z/F;for(let le=0;le<_;++le)for(let ye=0;ye<F;++ye)for(let we=0;we<G;++we){let Re=we-oe,_e=Math.max(0,Math.ceil(Re/ee)),Be=Math.min(K,($+Re)/ee);for(let Ge=0;Ge<q;++Ge){let ot=Ge-Y,dt=Math.max(0,Math.ceil(ot/Q)),pt=Math.min(B,(T+ot)/Q),At=0;for(let $e=_e;$e<Be;++$e){let Tt=$e*ee-Re;for(let It=dt;It<pt;++It){let Un=It*Q-ot,Qt=b*le+w*$e+k*It,bs=E*($-1-Tt)+R*(T-1-Un)+P*ye;for(let pn=0;pn<ae;++pn){let Gn=ye*ae+pn,vs=A[Qt+Gn],ws=S[bs+pn];At+=vs*ws}}}m[g*le+y*we+x*Ge+ye]=At}}return n.makeTensorInfo(f.shape,f.dtype,f.values)}var bZ={kernelName:Qm,backendName:"cpu",kernelFunc:xZ};function vZ(e){let{inputs:t,backend:n}=e,{x:s}=t,r=v.sizeFromShape(s.shape),a=n.data.get(s.dataId).values,o=Le([r,r],s.dtype),i=o.values;for(let u=0;u<a.length;u++)i[u*r+u]=a[u];let l=[...s.shape,...s.shape];return n.makeTensorInfo(l,o.dtype,o.values)}var wZ={kernelName:e0,backendName:"cpu",kernelFunc:vZ},kZ={kernelName:Vp,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:s,filter:r}=e,{strides:a,pad:o,dilations:i}=n,l=t,u=l.data.get(s.dataId).values,c=s.shape.length,p=l.data.get(r.dataId).values,d=r.shape.length,{batchSize:h,inHeight:f,inWidth:m,inChannels:g,outHeight:y,outWidth:x,padInfo:A,strideHeight:b,strideWidth:w,filterHeight:k,filterWidth:S,dilationHeight:E,dilationWidth:R,outShape:P}=C.computeDilation2DInfo(s.shape,r.shape,a,o,"NHWC",i),_=v.sizeFromShape(P),$=P.length,T=v.getArrayFromDType(s.dtype,_);for(let G=0;G<h;++G)for(let q=0;q<y;++q){let z=q*b-A.top;for(let K=0;K<x;++K){let B=K*w-A.left;for(let ee=0;ee<g;++ee){let Q=Number.MIN_SAFE_INTEGER;for(let Y=0;Y<k;++Y){let ae=z+Y*E;if(ae>=0&&ae<f)for(let le=0;le<S;++le){let ye=B+le*R;if(ye>=0&&ye<m){let we=v.locToIndex([G,ae,ye,ee],c,v.computeStrides(s.shape)),Re=v.locToIndex([Y,le,ee],d,v.computeStrides(r.shape)),_e=u[we]+p[Re];_e>Q&&(Q=_e)}}}let oe=v.locToIndex([G,q,K,ee],$,v.computeStrides(P));T[oe]=Q}}}return{dataId:l.write(v.toTypedArray(T,s.dtype),P,s.dtype),shape:P,dtype:s.dtype}}},IZ={kernelName:hm,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:s,filter:r,dy:a}=e,{strides:o,pad:i,dilations:l}=n,u=t,c=v.toNestedArray(s.shape,u.data.get(s.dataId).values),p=v.toNestedArray(r.shape,u.data.get(r.dataId).values),{batchSize:d,inHeight:h,inWidth:f,inChannels:m,outHeight:g,outWidth:y,padInfo:x,strideHeight:A,strideWidth:b,filterHeight:w,filterWidth:k,dilationHeight:S,dilationWidth:E,outShape:R}=C.computeDilation2DInfo(s.shape,r.shape,o,i,"NHWC",l);v.assert(a.rank===R.length,()=>`Error in ${hm}, dy must have the same rank as output ${R.length}, but got ${a.rank}`);let P=v.toNestedArray(R,u.data.get(a.dataId).values),_=v.makeZerosNestedTypedArray(r.shape,r.dtype);for(let T=0;T<d;++T)for(let F=0;F<g;++F){let G=F*A-x.top;for(let q=0;q<y;++q){let z=q*b-x.left;for(let K=0;K<m;++K){let B=Number.MIN_SAFE_INTEGER,ee=0,Q=0;for(let oe=0;oe<w;++oe){let Y=G+oe*S;if(Y>=0&&Y<h)for(let ae=0;ae<k;++ae){let le=z+ae*E;if(le>=0&&le<f){let ye=c[T][Y][le][K]+p[oe][ae][K];ye>B&&(B=ye,ee=oe,Q=ae)}}}_[ee][Q][K]+=P[T][F][q][K]}}}return{dataId:u.write(v.toTypedArray(_,s.dtype),r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},SZ={kernelName:pm,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:s,filter:r,dy:a}=e,{strides:o,pad:i,dilations:l}=n,u=t,c=v.toNestedArray(s.shape,u.data.get(s.dataId).values),p=v.toNestedArray(r.shape,u.data.get(r.dataId).values),{batchSize:d,inHeight:h,inWidth:f,inChannels:m,outHeight:g,outWidth:y,padInfo:x,strideHeight:A,strideWidth:b,filterHeight:w,filterWidth:k,dilationHeight:S,dilationWidth:E,outShape:R}=C.computeDilation2DInfo(s.shape,r.shape,o,i,"NHWC",l);v.assert(a.rank===R.length,()=>`Error in ${pm}, dy must have the same rank as output ${R.length}, but got ${a.rank}`);let P=v.toNestedArray(R,u.data.get(a.dataId).values),_=v.makeZerosNestedTypedArray(s.shape,s.dtype);for(let T=0;T<d;++T)for(let F=0;F<g;++F){let G=F*A-x.top;for(let q=0;q<y;++q){let z=q*b-x.left;for(let K=0;K<m;++K){let B=Number.MIN_SAFE_INTEGER,ee=G<0?0:G,Q=z<0?0:z;for(let oe=0;oe<w;++oe){let Y=G+oe*S;if(Y>=0&&Y<h)for(let ae=0;ae<k;++ae){let le=z+ae*E;if(le>=0&&le<f){let ye=c[T][Y][le][K]+p[oe][ae][K];ye>B&&(B=ye,ee=Y,Q=le)}}}_[T][ee][Q][K]+=P[T][F][q][K]}}}return{dataId:u.write(v.toTypedArray(_,s.dtype),s.shape,s.dtype),shape:s.shape,dtype:s.dtype}}};function Ph(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;Ce(r,"sum");let i;r.dtype==="bool"?i=io({inputs:{x:r},backend:n,attrs:{dtype:"int32"}}):i=Zr({inputs:{x:r},backend:n});let l=i.shape.length,u=v.parseAxisParam(a,i.shape),c=C.getAxesPermutation(u,l),p=u,d=i;c!=null&&(d=gs({inputs:{x:i},backend:n,attrs:{perm:c}}),p=C.getInnerMostAxes(p.length,l)),C.assertAxesAreInnerMostDims("sum",p,d.shape.length);let[h,f]=C.computeOutAndReduceShapes(d.shape,p),m=C.upcastType(d.dtype,"int32"),g=Rm(n,h,m),y=v.sizeFromShape(f),x=n.data.get(g.dataId).values,A=n.data.get(d.dataId).values;for(let b=0;b<x.length;++b){let w=b*y,k=0;for(let S=0;S<y;++S)k+=A[w+S];x[b]=k}if(o){let b=C.expandShapeToKeepDim(g.shape,u),w=g;g=Rt({inputs:{x:g},backend:n,attrs:{shape:b}}),n.disposeIntermediateTensorInfo(w)}return n.disposeIntermediateTensorInfo(i),c!=null&&n.disposeIntermediateTensorInfo(d),g}var CZ={kernelName:ei,backendName:"cpu",kernelFunc:Ph};function TZ(e){let{inputs:t,backend:n,attrs:s}=e,{equation:r}=s,a=t,{allDims:o,summedDims:i,idDims:l}=C.decodeEinsumEquation(r,a.length);C.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=C.getEinsumComputePath(i,l),p=c.length,d=null,h=o.length,f=[];for(let m=0;m<p;++m){for(let g of c[m]){let{permutationIndices:y,expandDims:x}=C.getEinsumPermutation(h,l[g]),A;C.isIdentityPermutation(y)?A=a[g]:(A=gs({inputs:{x:a[g]},backend:n,attrs:{perm:y}}),f.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=Rt({inputs:{x:A},backend:n,attrs:{shape:b}}),f.push(A)),d===null?d=A:(d=A2({inputs:{a:A,b:d},backend:n}),f.push(d))}m<p-1&&(u[m]>=0&&(d=Ph({inputs:{x:d},backend:n,attrs:{axis:u[m]-(o.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&n.disposeIntermediateTensorInfo(m);return d}var NZ={kernelName:Up,backendName:"cpu",kernelFunc:TZ};function EZ(e){let{inputs:t,backend:n}=e,{dy:s,y:r}=t;Ce([s,r],"eluGrad");let a=new Float32Array(v.sizeFromShape(r.shape)),o=n.data.get(r.dataId).values,i=n.data.get(s.dataId).values;for(let l=0;l<o.length;++l){let u=o[l];u>=1?a[l]=i[l]:a[l]=i[l]*(u+1)}return n.makeTensorInfo(r.shape,"float32",a)}var RZ={kernelName:t0,backendName:"cpu",kernelFunc:EZ},_Z=C.ERF_P,DZ=C.ERF_A1,$Z=C.ERF_A2,PZ=C.ERF_A3,FZ=C.ERF_A4,OZ=C.ERF_A5,MZ=bt(wc,e=>{let t=Math.sign(e),n=Math.abs(e),s=1/(1+_Z*n);return t*(1-((((OZ*s+FZ)*s+PZ)*s+$Z)*s+DZ)*s*Math.exp(-n*n))}),zZ={kernelName:wc,backendName:"cpu",kernelFunc:MZ};function $m(e){let{inputs:t,backend:n,attrs:s}=e,{input:r}=t,{dim:a}=s,o=r.shape.length,i=r.shape.slice(),l=a;return a<0&&(v.assert(-(o+1)<=a,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+a+1),i.splice(l,0,1),Rt({inputs:{x:r},backend:n,attrs:{shape:i}})}var LZ={kernelName:fl,backendName:"cpu",kernelFunc:$m},BZ=un((e,t)=>e/t),zx=kn(Io,BZ),ey={kernelName:Io,backendName:"cpu",kernelFunc:zx};function sS(e,t,n){let s=e.shape,r=s[0],a=s[1],o=n.data.get(e.dataId),i=o.complexTensorInfos.real,l=o.complexTensorInfos.imag,u=[r,a],c=v.sizeFromShape(u),p=v.getTypedArrayFromDType("float32",c),d=v.getTypedArrayFromDType("float32",c);for(let g=0;g<r;g++){let y=nl({inputs:{x:i},backend:n,attrs:{begin:[g,0],size:[1,a]}}),x=nl({inputs:{x:l},backend:n,attrs:{begin:[g,0],size:[1,a]}}),A=Cs({inputs:{real:y,imag:x},backend:n}),{real:b,imag:w}=WZ(A,t,n),k=C.mergeRealAndImagArrays(b,w);for(let S=0;S<a;S++){let E=C.getComplexWithIndex(k,S);p[g*a+S]=E.real,d[g*a+S]=E.imag}n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(A)}let h=n.makeTensorInfo(u,"float32",p),f=n.makeTensorInfo(u,"float32",d),m=Cs({inputs:{real:h,imag:f},backend:n});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),m}function WZ(e,t,n){let s=v.sizeFromShape(e.shape),r=n.data.get(e.dataId),a=n.data.get(r.complexTensorInfos.real.dataId).values,o=n.data.get(r.complexTensorInfos.imag.dataId).values;if(VZ(s)){let i=ty(a,o,s,t,n),l=[e.shape[0],e.shape[1]];if(t){let u=n.makeTensorInfo(l,"float32",i.real),c=n.makeTensorInfo(l,"float32",i.imag),p=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),d=Zr({inputs:{x:p},backend:n}),h=ey.kernelFunc({inputs:{a:u,b:p},backend:n}),f=ey.kernelFunc({inputs:{a:c,b:d},backend:n}),m=n.data.get(h.dataId).values,g=n.data.get(f.dataId).values;return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),{real:m,imag:g}}return i}else{let i=C.mergeRealAndImagArrays(a,o),l=UZ(i,s,t);return C.splitRealAndImagArrays(l)}}function VZ(e){return(e&e-1)===0}function ty(e,t,n,s,r){if(n===1)return{real:e,imag:t};let a=C.mergeRealAndImagArrays(e,t),o=n/2,i=C.complexWithEvenIndex(a),l=i.real,u=i.imag,c=[l.length],p=r.makeTensorInfo(c,"float32",l),d=r.makeTensorInfo(c,"float32",u),h=Cs({inputs:{real:p,imag:d},backend:r}),f=C.complexWithOddIndex(a),m=f.real,g=f.imag,y=[m.length],x=r.makeTensorInfo(y,"float32",m),A=r.makeTensorInfo(y,"float32",g),b=Cs({inputs:{real:x,imag:A},backend:r}),w=ty(l,u,o,s,r),k=w.real,S=w.imag,E=[k.length],R=r.makeTensorInfo(E,"float32",k),P=r.makeTensorInfo(E,"float32",S),_=Cs({inputs:{real:R,imag:P},backend:r}),$=ty(m,g,o,s,r),T=$.real,F=$.imag,G=[T.length],q=r.makeTensorInfo(G,"float32",T),z=r.makeTensorInfo(G,"float32",F),K=Cs({inputs:{real:q,imag:z},backend:r}),B=C.exponents(n,s),ee=[B.real.length],Q=r.makeTensorInfo(ee,"float32",B.real),oe=r.makeTensorInfo(ee,"float32",B.imag),Y=Cs({inputs:{real:Q,imag:oe},backend:r}),ae=A2({inputs:{a:Y,b:K},backend:r}),le=oc({inputs:{a:_,b:ae},backend:r}),ye=Ox({inputs:{a:_,b:ae},backend:r}),we=tl({inputs:{input:le},backend:r}),Re=tl({inputs:{input:ye},backend:r}),_e=ic({inputs:{input:le},backend:r}),Be=ic({inputs:{input:ye},backend:r}),Ge=lc({inputs:[we,Re],backend:r,attrs:{axis:0}}),ot=lc({inputs:[_e,Be],backend:r,attrs:{axis:0}}),dt=r.data.get(Ge.dataId).values,pt=r.data.get(ot.dataId).values;return r.disposeIntermediateTensorInfo(p),r.disposeIntermediateTensorInfo(d),r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(x),r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(b),r.disposeIntermediateTensorInfo(R),r.disposeIntermediateTensorInfo(P),r.disposeIntermediateTensorInfo(_),r.disposeIntermediateTensorInfo(q),r.disposeIntermediateTensorInfo(z),r.disposeIntermediateTensorInfo(K),r.disposeIntermediateTensorInfo(Q),r.disposeIntermediateTensorInfo(oe),r.disposeIntermediateTensorInfo(Y),r.disposeIntermediateTensorInfo(ae),r.disposeIntermediateTensorInfo(le),r.disposeIntermediateTensorInfo(ye),r.disposeIntermediateTensorInfo(we),r.disposeIntermediateTensorInfo(_e),r.disposeIntermediateTensorInfo(Re),r.disposeIntermediateTensorInfo(Be),r.disposeIntermediateTensorInfo(Ge),r.disposeIntermediateTensorInfo(ot),{real:dt,imag:pt}}function UZ(e,t,n){let s=new Float32Array(t*2);for(let r=0;r<t;r++){let a=0,o=0;for(let i=0;i<t;i++){let l=C.exponent(r*i,t,n),u=C.getComplexWithIndex(e,i);a+=u.real*l.real-u.imag*l.imag,o+=u.real*l.imag+u.imag*l.real}n&&(a/=t,o/=t),C.assignToTypedArray(s,a,o,r)}return s}function GZ(e){let{inputs:t,backend:n}=e,{input:s}=t,r=v.sizeFromShape(s.shape),a=s.shape[s.shape.length-1],o=r/a,i=Rt({inputs:{x:s},backend:n,attrs:{shape:[o,a]}}),l=sS(i,!1,n),u=Rt({inputs:{x:l},backend:n,attrs:{shape:s.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var HZ={kernelName:n0,backendName:"cpu",kernelFunc:GZ};function Lx(e){let{backend:t,attrs:n}=e,{shape:s,value:r,dtype:a}=n,o=a||v.inferDtype(r),i=v.getArrayFromDType(o,v.sizeFromShape(s));return qZ(i,r,o),t.makeTensorInfo(s,o,i)}var jZ={kernelName:kc,backendName:"cpu",kernelFunc:Lx};function qZ(e,t,n){e.fill(t)}var XZ={kernelName:gl,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,r=n,a=v.getTypedArrayFromDType(s.dtype,v.sizeFromShape(s.shape)),[o,i,l,u]=s.shape,c=r.data.get(s.dataId).values;for(let d=0;d<o;d++){let h=d*l*i*u;for(let f=0;f<i;f++){let m=f*(l*u);for(let g=0;g<l;g++){let y=g*u;for(let x=0;x<u;x++){let A=Math.round(l-g-1),b=h+m+y+x,w=c[b];if(A>=0&&A<l){let k=A*u,S=h+m+k+x;w=c[S]}a[b]=w}}}}return{dataId:r.write(a,s.shape,s.dtype),shape:s.shape,dtype:s.dtype}}},KZ=un((e,t)=>Math.floor(e/t)),ZZ=kn(No,KZ,null,"int32"),YZ={kernelName:No,backendName:"cpu",kernelFunc:ZZ};function JZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=s,m=tS({inputs:{x:r,filter:a},backend:n,attrs:{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d}});if(o){let g=m;if(c==="NCHW"&&o.shape.length===1&&o.shape[0]!==1){let y=Rt({inputs:{x:o},backend:n,attrs:{shape:[o.shape[0],1,1]}});m=oc({inputs:{a:m,b:y},backend:n}),n.disposeIntermediateTensorInfo(y)}else m=oc({inputs:{a:m,b:o},backend:n});n.disposeIntermediateTensorInfo(g)}if(h){let g=m;if(c==="NCHW"&&h==="prelu"&&i.shape.length===1&&i.shape[0]!==1){let y=Rt({inputs:{x:i},backend:n,attrs:{shape:[i.shape[0],1,1]}});m=Dm(n,m,h,y,f),n.disposeIntermediateTensorInfo(y)}else m=Dm(n,m,h,i,f);n.disposeIntermediateTensorInfo(g)}return m}var QZ={kernelName:Qa,backendName:"cpu",kernelFunc:JZ};function eY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=s,m=nS({inputs:{x:r,filter:a},backend:n,attrs:{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d}});if(o){let g=m;m=oc({inputs:{a:m,b:o},backend:n}),n.disposeIntermediateTensorInfo(g)}if(h){let g=m;m=Dm(n,m,h,i,f),n.disposeIntermediateTensorInfo(g)}return m}var tY={kernelName:eo,backendName:"cpu",kernelFunc:eY};function nY(e){let{inputs:t,backend:n}=e,{params:s,indices:r}=t,a=v.sizeFromShape(s.shape),o=r.shape,i=o[o.length-1],[l,u,c,p]=C.prepareAndValidate(s,r);if(u===0)return n.makeTensorInfo(l,s.dtype,[]);let d=n.data.get(r.dataId).values,h=n.bufferSync(s),f=wI(d,h,s.dtype,u,i,c,p,s.shape,a);return n.makeTensorInfo(l,s.dtype,f.values)}var sY={kernelName:Al,backendName:"cpu",kernelFunc:nY};function rY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,indices:a}=t,{axis:o,batchDims:i}=s;Ce([r,a],"gatherV2");let l=v.parseAxisParam(o,r.shape)[0],u=n.data.get(a.dataId).values,c=r.shape[l];for(let b=0;b<u.length;++b){let w=u[b];v.assert(w<=c-1&&w>=0,()=>`GatherV2: the index value ${w} is not in [0, ${c-1}]`)}let p=i;i==null&&(p=0);let d=v.sizeFromShape(a.shape),h=C.segment_util.collectGatherOpShapeInfo(r,a,l,p),f=Rt({inputs:{x:r},backend:n,attrs:{shape:[h.batchSize,h.outerSize,h.dimSize,h.sliceSize]}}),m=Rt({inputs:{x:a},backend:n,attrs:{shape:[h.batchSize,d/h.batchSize]}}),g=[h.batchSize,h.outerSize,d/h.batchSize,h.sliceSize],y=n.bufferSync(m),x=n.bufferSync(f),A=kI(x,y,g);return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),n.makeTensorInfo(h.outputShape,A.dtype,A.values)}var aY={kernelName:yl,backendName:"cpu",kernelFunc:rY};function oY(e){let{inputs:t,backend:n}=e,{input:s}=t,r=v.sizeFromShape(s.shape),a=s.shape[s.shape.length-1],o=r/a,i=Rt({inputs:{x:s},backend:n,attrs:{shape:[o,a]}}),l=sS(i,!0,n),u=Rt({inputs:{x:l},backend:n,attrs:{shape:s.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var iY={kernelName:s0,backendName:"cpu",kernelFunc:oY},lY=bt(Ic,e=>Number.isFinite(e)?1:0,"bool"),uY={kernelName:Ic,backendName:"cpu",kernelFunc:lY},cY=bt(Sc,e=>Math.abs(e)===1/0?1:0,"bool"),dY={kernelName:Sc,backendName:"cpu",kernelFunc:cY},pY=bt(Cc,e=>Number.isNaN(e)?1:0,"bool"),hY={kernelName:Cc,backendName:"cpu",kernelFunc:pY};function fY(e){let{backend:t,attrs:n}=e,{start:s,stop:r,num:a}=n,o=NI(s,r,a);return t.makeTensorInfo([o.length],"float32",o)}var mY={kernelName:r0,backendName:"cpu",kernelFunc:fY},gY=bt(Tc,e=>Math.log1p(e)),yY={kernelName:Tc,backendName:"cpu",kernelFunc:gY},AY=un((e,t)=>e&&t),xY=kn(wl,AY,null,"bool"),bY={kernelName:wl,backendName:"cpu",kernelFunc:xY},vY=bt(kl,e=>e?0:1,"bool"),wY={kernelName:kl,backendName:"cpu",kernelFunc:vY},kY=un((e,t)=>e||t),IY=kn(Nc,kY,null,"bool"),SY={kernelName:Nc,backendName:"cpu",kernelFunc:IY};function CY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{depthRadius:a,bias:o,alpha:i,beta:l}=s;Ce(r,"LRN");let u=r.shape[3],c=u-1,p=n.data.get(r.dataId).values,d=v.sizeFromShape(r.shape),h=new Float32Array(d);function f(m){let g=m%u,y=m-g+Math.max(0,g-a),x=m-g+Math.min(g+a,c),A=0;for(;y<=x;y++){let b=p[y];A+=b*b}return A}for(let m=0;m<d;m++){let g=f(m),y=p[m]*Math.pow(o+i*g,-l);h[m]=y}return n.makeTensorInfo(r.shape,r.dtype,h)}var TY={kernelName:Hp,backendName:"cpu",kernelFunc:CY};function NY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,y:a,dy:o}=t,{depthRadius:i,bias:l,alpha:u,beta:c}=s;Ce(o,"LRNGrad");let p=v.sizeFromShape(o.shape),d=o.shape[3],h=n.data.get(o.dataId).values,f=n.data.get(r.dataId).values,m=n.data.get(a.dataId).values,g=new Float32Array(p),y=p;for(let x=0;x<y;x++){let A=x%d,b=x-A+Math.max(0,A-i),w=x-A+Math.min(d,A+i+1),k=0;for(let S=b;S<w;S++)k+=Math.pow(f[S],2);k=u*k+l;for(let S=b;S<w;S++){let E=-2*u*c*f[S]*m[x]/k;x===S&&(E+=Math.pow(k,-c)),E*=h[x],g[S]+=E}}return n.makeTensorInfo(o.shape,r.dtype,g)}var EY={kernelName:a0,backendName:"cpu",kernelFunc:NY};function rS(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reductionIndices:a,keepDims:o}=s,i=n,l=r.shape,u=l.length,c=v.parseAxisParam(a,l),p=c,d=C.getAxesPermutation(p,u),h=i.data.get(r.dataId).values;if(d!=null){let b=new Array(u);for(let w=0;w<b.length;w++)b[w]=l[d[w]];h=Rx(h,l,r.dtype,d,b),p=C.getInnerMostAxes(p.length,u),l=b}Ce(r,"max"),C.assertAxesAreInnerMostDims("max",p,u);let[f,m]=C.computeOutAndReduceShapes(l,p),g=v.sizeFromShape(m),y=RI(h,g,f,r.dtype),x=i.write(y,f,r.dtype),A=f;return o&&(A=C.expandShapeToKeepDim(f,c)),{dataId:x,shape:A,dtype:r.dtype}}var RY={kernelName:Po,backendName:"cpu",kernelFunc:rS};function _Y(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;Ce(r,"maxPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;v.assert(C.eitherStridesOrDilationsAreOne(o,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=C.computePool2DInfo(r.shape,a,o,u,i,l),p;if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))p=Zr({inputs:{x:r},backend:n});else{let d=n.data.get(r.dataId).values,h=v.computeStrides(r.shape),f=Mx(d,r.shape,r.dtype,h,c,"max");p=n.makeTensorInfo(c.outShape,r.dtype,f.values)}return p}var DY={kernelName:Oo,backendName:"cpu",kernelFunc:_Y};function $Y(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l,dataFormat:u}=s;Ce(r,"maxPool3d");let c=C.computePool3DInfo(r.shape,a,o,1,i,l,u),p=n.data.get(r.dataId).values,d=eS(p,r.shape,r.dtype,v.computeStrides(r.shape),c,"max");return n.makeTensorInfo(d.shape,"float32",d.values)}var PY={kernelName:jp,backendName:"cpu",kernelFunc:$Y};function FY(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=s;Ce([r,a],"maxPool3DGrad");let c=C.computePool3DInfo(a.shape,o,i,1,l,u),p=n.bufferSync(a),d=wK(p,c),h=c.strideDepth,f=c.strideHeight,m=c.strideWidth,g=c.dilationDepth,y=c.dilationHeight,x=c.dilationWidth,A=c.effectiveFilterDepth,b=c.effectiveFilterHeight,w=c.effectiveFilterWidth,k=A-1-c.padInfo.front,S=w-1-c.padInfo.left,E=b-1-c.padInfo.top,R=Le(a.shape,"float32"),P=n.bufferSync(r);for(let _=0;_<c.batchSize;++_)for(let $=0;$<c.inChannels;++$)for(let T=0;T<c.inDepth;++T)for(let F=0;F<c.inHeight;++F)for(let G=0;G<c.inWidth;++G){let q=T-k,z=F-E,K=G-S,B=0;for(let ee=0;ee<A;ee+=g){let Q=(q+ee)/h;if(!(Q<0||Q>=c.outDepth||Math.floor(Q)!==Q))for(let oe=0;oe<b;oe+=y){let Y=(z+oe)/f;if(!(Y<0||Y>=c.outHeight||Math.floor(Y)!==Y))for(let ae=0;ae<w;ae+=x){let le=(K+ae)/m;if(le<0||le>=c.outWidth||Math.floor(le)!==le)continue;let ye=A*b*w-1-d.get(_,Q,Y,le,$),we=ee*b*w+oe*w+ae,Re=ye===we?1:0;if(Re===0)continue;B+=P.get(_,Q,Y,le,$)*Re}}}R.set(B,_,T,F,G,$)}return n.makeTensorInfo(R.shape,R.dtype,R.values)}var OY={kernelName:i0,backendName:"cpu",kernelFunc:FY};function MY(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a,output:o}=t,i=a;Ce([a,o],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:p}=s,d=C.computePool2DInfo(i.shape,l,u,1,c,p),h=n.data.get(i.dataId).values,f=Le(d.outShape,i.dtype,QI(h,i.shape,i.dtype,d).values),m=d.strideHeight,g=d.strideWidth,y=d.dilationHeight,x=d.dilationWidth,A=d.effectiveFilterHeight,b=d.effectiveFilterWidth,w=b-1-d.padInfo.left,k=A-1-d.padInfo.top,S=Le(i.shape,"float32"),E=n.data.get(r.dataId).values,R=Le(r.shape,"float32",E);for(let P=0;P<d.batchSize;++P)for(let _=0;_<d.inChannels;++_)for(let $=0;$<d.inHeight;++$)for(let T=0;T<d.inWidth;++T){let F=$-k,G=T-w,q=0;for(let z=0;z<A;z+=y){let K=(F+z)/m;if(!(K<0||K>=d.outHeight||Math.floor(K)!==K))for(let B=0;B<b;B+=x){let ee=(G+B)/g;if(ee<0||ee>=d.outWidth||Math.floor(ee)!==ee)continue;let Q=A*b-1-f.get(P,K,ee,_),oe=z*b+B,Y=Q===oe?1:0;if(Y===0)continue;q+=R.get(P,K,ee,_)*Y}}S.set(q,P,$,T,_)}return n.makeTensorInfo(S.shape,S.dtype,S.values)}var zY={kernelName:o0,backendName:"cpu",kernelFunc:MY};function LY(e,t,n,s,r){let a=v.computeStrides(t),o=Mx(e,t,n,a,r,"max"),i=QI(e,t,n,r,!0,s);return[o.values,i.values]}var BY={kernelName:l0,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{filterSize:r,strides:a,pad:o,includeBatchInIndex:i}=t,l=n;Ce(s,"MaxPoolWithArgmax");let u=l.data.get(s.dataId).values,c=C.computePool2DInfo(s.shape,r,a,[1,1],o),[p,d]=LY(u,s.shape,s.dtype,i,c),h=l.write(p,c.outShape,s.dtype),f=l.write(d,c.outShape,s.dtype);return[{dataId:h,shape:c.outShape,dtype:s.dtype},{dataId:f,shape:c.outShape,dtype:"int32"}]}};function WY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=v.parseAxisParam(a,r.shape),u=C.computeOutAndReduceShapes(r.shape,i)[1],c=v.sizeFromShape(u),p=[],d=n.makeTensorInfo([],"float32",new Float32Array([c]));p.push(d);let h=io({inputs:{x:r},backend:n,attrs:{dtype:"float32"}});p.push(h);let f=zx({inputs:{a:h,b:d},backend:n});p.push(f);let m=Ph({inputs:{x:f},backend:n,attrs:{axis:a,keepDims:o}});return p.forEach(g=>n.disposeIntermediateTensorInfo(g)),m}var VY={kernelName:Mo,backendName:"cpu",kernelFunc:WY};function UY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;Ce(r,"min");let i=v.parseAxisParam(a,r.shape),l=i,u=C.getAxesPermutation(l,r.shape.length),c=r;u!=null&&(c=gs({inputs:{x:r},backend:n,attrs:{perm:u}}),l=C.getInnerMostAxes(l.length,r.shape.length)),C.assertAxesAreInnerMostDims("min",l,c.shape.length);let[p,d]=C.computeOutAndReduceShapes(c.shape,l),h=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(p),c.dtype),m=n.data.get(c.dataId).values;for(let y=0;y<f.length;++y){let x=y*h,A=m[x];for(let b=0;b<h;++b){let w=m[x+b];(Number.isNaN(w)||w<A)&&(A=w)}f[y]=A}u!=null&&n.disposeIntermediateTensorInfo(c);let g=n.makeTensorInfo(p,c.dtype,f);if(o){let y=C.expandShapeToKeepDim(p,i),x=Rt({inputs:{x:g},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(g),x}return g}var GY={kernelName:zo,backendName:"cpu",kernelFunc:UY};function HY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{paddings:a,mode:o}=s;Ce(r,"mirrorPad");let i=a.map((A,b)=>A[0]+r.shape[b]+A[1]),l=a.map(A=>A[0]),u=a.map((A,b)=>A[0]+r.shape[b]),c=o==="reflect"?0:1,p=n.data.get(r.dataId).values,d=r.shape.length,h=v.computeStrides(r.shape),f=v.sizeFromShape(i),m=i.length,g=v.computeStrides(i),y=v.getTypedArrayFromDType(r.dtype,f);for(let A=0;A<f;A++){let b=v.indexToLoc(A,m,g);for(let k=0;k<m;k++)b[k]<l[k]?b[k]=l[k]*2-b[k]-c:b[k]>=u[k]&&(b[k]=(u[k]-1)*2-b[k]+c);b=b.map((k,S)=>k-l[S]);let w=v.locToIndex(b,d,h);y[A]=p[w]}return{dataId:n.write(y,i,r.dtype),shape:i,dtype:r.dtype}}var jY={kernelName:Bo,backendName:"cpu",kernelFunc:HY},qY=un((e,t)=>{let n=e%t;return e<0&&t<0||e>=0&&t>=0?n:(n+t)%t}),XY=kn(Ec,qY),KY={kernelName:Ec,backendName:"cpu",kernelFunc:XY},ZY=uo(Wm());function aS(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{dim:a}=s,o=r.shape.length,i=a;if(i===-1&&(i=o-1),i!==o-1)throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${o} and dim was ${i}`);let l=v.parseAxisParam([i],r.shape),u=rS({inputs:{x:r},backend:n,attrs:{reductionIndices:l,keepDims:!1}}),c=C.expandShapeToKeepDim(u.shape,l),p=Rt({inputs:{x:u},backend:n,attrs:{shape:c}}),d=Ox({inputs:{a:r,b:p},backend:n}),h=xI({inputs:{x:d},backend:n}),f=Ph({inputs:{x:h},backend:n,attrs:{axis:l,keepDims:!1}}),m=Rt({inputs:{x:f},backend:n,attrs:{shape:c}}),g=zx({inputs:{a:h,b:m},backend:n});return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),g}var YY={kernelName:ti,backendName:"cpu",kernelFunc:aS};function JY(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{numSamples:a,seed:o,normalized:i}=s;Ce(r,"multinomial");let l=i?r:aS({inputs:{logits:r},backend:n,attrs:{dim:-1}}),u=l.shape[0],c=l.shape[1],p=n.data.get(l.dataId).values,d=[u,a],h=v.makeZerosTypedArray(v.sizeFromShape(d),"int32");for(let f=0;f<u;++f){let m=f*c,g=new Float32Array(c-1);g[0]=p[m];for(let A=1;A<g.length;++A)g[A]=g[A-1]+p[m+A];let y=ZY.alea(o.toString()),x=f*a;for(let A=0;A<a;++A){let b=y();h[x+A]=g.length;for(let w=0;w<g.length;w++)if(b<g[w]){h[x+A]=w;break}}}return i||n.disposeIntermediateTensorInfo(l),n.makeTensorInfo(d,"int32",h)}var QY={kernelName:u0,backendName:"cpu",kernelFunc:JY},eJ=dr.nonMaxSuppressionV3Impl;function tJ(e){let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l}=s;Ce(r,"NonMaxSuppression");let u=n.data.get(r.dataId).values,c=n.data.get(a.dataId).values,{selectedIndices:p}=eJ(u,c,o,i,l);return n.makeTensorInfo([p.length],"int32",new Int32Array(p))}var nJ={kernelName:Cl,backendName:"cpu",kernelFunc:tJ},sJ=dr.nonMaxSuppressionV4Impl;function rJ(e){let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,padToMaxOutputSize:u}=s;Ce(r,"NonMaxSuppressionPadded");let c=n.data.get(r.dataId).values,p=n.data.get(a.dataId).values,{selectedIndices:d,validOutputs:h}=sJ(c,p,o,i,l,u);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([h]))]}var aJ={kernelName:Rc,backendName:"cpu",kernelFunc:rJ},oJ=dr.nonMaxSuppressionV5Impl;function iJ(e){let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=s;Ce(r,"NonMaxSuppressionWithScore");let c=n.data.get(r.dataId).values,p=n.data.get(a.dataId).values,d=o,h=i,f=l,m=u,{selectedIndices:g,selectedScores:y}=oJ(c,p,d,h,f,m);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var lJ={kernelName:Tl,backendName:"cpu",kernelFunc:iJ};function uJ(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r}=t,{depth:a,onValue:o,offValue:i}=s;Ce(r,"oneHot");let l=v.sizeFromShape(r.shape),u=new Float32Array(l*a);u.fill(i);let c=n.data.get(r.dataId).values;for(let p=0;p<l;++p)c[p]>=0&&c[p]<a&&(u[p*a+c[p]]=o);return n.makeTensorInfo([...r.shape,a],"int32",u)}var cJ={kernelName:El,backendName:"cpu",kernelFunc:uJ};function Pm(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="string")throw new Error("zerosLike is not supported for string tensors");if(s.dtype==="complex64"){let r=tl({inputs:{input:s},backend:n}),a=Pm({inputs:{x:r},backend:n}),o=ic({inputs:{input:s},backend:n}),i=Pm({inputs:{x:o},backend:n}),l=Cs({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return Lx({backend:n,attrs:{shape:s.shape,value:0,dtype:s.dtype}})}var dJ={kernelName:Hl,backendName:"cpu",kernelFunc:Pm};function oS(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="string")throw new Error("onesLike is not supported for string tensors");if(s.dtype==="complex64"){let r=tl({inputs:{input:s},backend:n}),a=oS({inputs:{x:r},backend:n}),o=ic({inputs:{input:s},backend:n}),i=Pm({inputs:{x:o},backend:n}),l=Cs({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return Lx({backend:n,attrs:{shape:s.shape,value:1,dtype:s.dtype}})}var pJ={kernelName:Nl,backendName:"cpu",kernelFunc:oS};function iS(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return $m({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let p=$m({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(p),p}),u=lc({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var hJ={kernelName:Rl,backendName:"cpu",kernelFunc:iS};function fJ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{paddings:a,constantValue:o}=s;Ce(r,"pad");let i=a.map((x,A)=>x[0]+r.shape[A]+x[1]),l=a.map(x=>x[0]),u=n.data.get(r.dataId).values,c=v.sizeFromShape(r.shape),p=r.shape.length,d=v.computeStrides(r.shape),h=v.sizeFromShape(i),f=i.length,m=v.computeStrides(i),g=v.getTypedArrayFromDType(r.dtype,h);o!==0&&g.fill(o);for(let x=0;x<c;x++){let b=v.indexToLoc(x,p,d).map((k,S)=>k+l[S]),w=v.locToIndex(b,f,m);g[w]=u[x]}return{dataId:n.write(g,i,r.dtype),shape:i,dtype:r.dtype}}var lS={kernelName:Vo,backendName:"cpu",kernelFunc:fJ},mJ=un((e,t)=>Math.pow(e,t)),gJ=kn(Uo,mJ),yJ={kernelName:Uo,backendName:"cpu",kernelFunc:gJ};function AJ(e){let{backend:t,attrs:n}=e,{start:s,stop:r,dtype:a,step:o}=n,i=_x(s,r,o,a);return t.makeTensorInfo([i.length],a,i)}var xJ={kernelName:_c,backendName:"cpu",kernelFunc:AJ},bJ=bt(Dc,e=>1/e),vJ={kernelName:Dc,backendName:"cpu",kernelFunc:bJ};function wJ(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s;Ce(r,"resizeBilinear");let l=v.computeStrides(r.shape),[u,c]=i,[p,d,h,f]=r.shape,m=n.data.get(r.dataId).values,g=new Float32Array(v.sizeFromShape([p,u,c,f])),y=[a&&u>1?d-1:d,a&&c>1?h-1:h],x=[a&&u>1?u-1:u,a&&c>1?c-1:c],A=0,b=y[0]/x[0],w=y[1]/x[1];for(let k=0;k<p;k++)for(let S=0;S<u;S++){let E;o?E=b*(S+.5)-.5:E=b*S;let R=Math.max(0,Math.floor(E)),P=E-R,_=Math.min(d-1,Math.ceil(E)),$=k*l[0]+R*l[1],T=k*l[0]+_*l[1];for(let F=0;F<c;F++){let G;o?G=w*(F+.5)-.5:G=w*F;let q=Math.max(0,Math.floor(G)),z=G-q,K=Math.min(h-1,Math.ceil(G)),B=$+q*l[2],ee=T+q*l[2],Q=$+K*l[2],oe=T+K*l[2];for(let Y=0;Y<f;Y++){let ae=m[B+Y],le=m[ee+Y],ye=m[Q+Y],we=m[oe+Y],Re=ae+(ye-ae)*z,_e=le+(we-le)*z,Be=Re+(_e-Re)*P;g[A++]=Be}}}return n.makeTensorInfo([p,u,c,f],"float32",g)}var kJ={kernelName:Xo,backendName:"cpu",kernelFunc:wJ};function IJ(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s;Ce([a,r],"resizeBilinearGrad");let i=v.computeStrides(r.shape),[l,u,c,p]=r.shape,[,d,h]=a.shape,f=new Float32Array(l*u*c*p),m=[o&&d>1?u-1:u,o&&h>1?c-1:c],g=[o&&d>1?d-1:d,o&&h>1?h-1:h],y=m[0]/g[0],x=m[1]/g[1],A=n.data.get(a.dataId).values,b=0;for(let w=0;w<l;w++){let k=w*i[0];for(let S=0;S<d;S++){let E=S*y,R=Math.floor(E),P=Math.min(Math.ceil(E),u-1),_=k+R*i[1],$=k+P*i[1],T=E-R,F=1-T;for(let G=0;G<h;G++){let q=G*x,z=Math.floor(q),K=Math.min(Math.ceil(q),c-1),B=q-z,ee=1-B,Q=_+z*i[2],oe=_+K*i[2],Y=$+z*i[2],ae=$+K*i[2],le=F*ee,ye=F*B,we=T*ee,Re=T*B;for(let _e=0;_e<p;_e++){let Be=A[b++];f[Q+_e]+=Be*le,f[oe+_e]+=Be*ye,f[Y+_e]+=Be*we,f[ae+_e]+=Be*Re}}}}return n.makeTensorInfo([l,c,u,p],"float32",f)}var SJ={kernelName:d0,backendName:"cpu",kernelFunc:IJ};function CJ(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s;Ce(r,"resizeNearestNeighbor");let l=v.computeStrides(r.shape),[u,c]=i,[p,d,h,f]=r.shape,m=n.data.get(r.dataId).values,g=new Float32Array(p*u*c*f),y=[a&&u>1?d-1:d,a&&c>1?h-1:h],x=[a&&u>1?u-1:u,a&&c>1?c-1:c],A=y[0]/x[0],b=y[1]/x[1],w=0;for(let k=0;k<p;k++){let S=k*l[0];for(let E=0;E<u;E++){let R=o?A*(E+.5):A*E,P=Math.min(d-1,a?Math.round(R):Math.floor(R));o&&(P=Math.max(0,P));let _=S+P*l[1];for(let $=0;$<c;$++){let T=o?b*($+.5):b*$,F=Math.min(h-1,a?Math.round(T):Math.floor(T));o&&(F=Math.max(0,F));let G=_+F*l[2];for(let q=0;q<f;q++){let z=m[G+q];g[w++]=z}}}}return n.makeTensorInfo([p,u,c,f],r.dtype,g)}var TJ={kernelName:qo,backendName:"cpu",kernelFunc:CJ};function NJ(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s;Ce([a,r],"resizeNearestNeighborGrad");let i=v.computeStrides(r.shape),l=v.computeStrides(a.shape),[u,c,p,d]=r.shape,[,h,f]=a.shape,m=new Float32Array(u*c*p*d),g=n.data.get(a.dataId).values,y=[o&&h>1?c-1:c,o&&f>1?p-1:p],x=[o&&h>1?h-1:h,o&&f>1?f-1:f],A=y[0]/x[0],b=y[1]/x[1],w=1/A,k=1/b,S=Math.ceil(w)*2+2,E=Math.ceil(k)*2+2;for(let R=0;R<u;R++){let P=R*i[0];for(let _=0;_<c;_++){let $=P+_*i[1],T=Math.floor(_*w),F=Math.floor(T-S/2);for(let G=0;G<p;G++){let q=$+G*i[2],z=Math.floor(G*k),K=Math.floor(z-E/2);for(let B=0;B<d;B++){let ee=0;for(let Q=0;Q<S;Q++){let oe=Q+F;if(oe<0||oe>=h)continue;let Y=P+oe*l[1],ae=oe*A,le=Math.min(c-1,o?Math.round(ae):Math.floor(ae));if(_===le)for(let ye=0;ye<E;ye++){let we=ye+K;if(we<0||we>=f)continue;let Re=Y+we*l[2],_e=we*b,Be=Math.min(p-1,o?Math.round(_e):Math.floor(_e));G===Be&&(ee+=g[Re+B])}}m[q+B]=ee}}}}return n.makeTensorInfo(r.shape,r.dtype,m)}var EJ={kernelName:c0,backendName:"cpu",kernelFunc:NJ};function RJ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dims:a}=s;Ce(r,"reverse");let o=r.shape.length,i=v.parseAxisParam(a,r.shape);if(o===0)return Zr({inputs:{x:r},backend:n});let l=new fn(r.shape,r.dtype),u=n.bufferSync(r);for(let c=0;c<l.size;c++){let p=l.indexToLoc(c),d=p.slice();i.forEach(h=>d[h]=r.shape[h]-1-d[h]),l.set(u.get(...d),...p)}return n.makeTensorInfo(l.shape,l.dtype,l.values)}var _J={kernelName:Dl,backendName:"cpu",kernelFunc:RJ},DJ={kernelName:jl,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,{radians:r,fillValue:a,center:o}=t,i=n,l=v.getTypedArrayFromDType(s.dtype,v.sizeFromShape(s.shape)),[u,c,p,d]=s.shape,[h,f]=C.getImageCenter(o,c,p),m=255,g=Math.sin(r),y=Math.cos(r),x=i.data.get(s.dataId).values;for(let b=0;b<u;b++){let w=b*p*c*d;for(let k=0;k<c;k++){let S=k*(p*d);for(let E=0;E<p;E++){let R=E*d;for(let P=0;P<d;P++){let _=[u,k,E,P],$=_[2],T=_[1],F=($-h)*y-(T-f)*g,G=($-h)*g+(T-f)*y;F=Math.round(F+h),G=Math.round(G+f);let q=a;if(typeof a!="number"&&(P===3?q=m:q=a[P]),F>=0&&F<p&&G>=0&&G<c){let K=G*(p*d),B=F*d,ee=w+K+B+P;q=x[ee]}let z=w+S+R+P;l[z]=q}}}}return{dataId:i.write(l,s.shape,s.dtype),shape:s.shape,dtype:s.dtype}}},$J=bt($l,e=>{let t=Math.floor(e);return e-t<.5?Math.floor(e):e-t>.5?Math.ceil(e):t%2===0?t:t+1}),PJ={kernelName:$l,backendName:"cpu",kernelFunc:$J};function FJ(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r,updates:a}=t,{shape:o}=s,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:p}=C.calculateShapes(a,r,o),d=!0,h=n.bufferSync(r),f=n.bufferSync(a),m=Bu(h,f,o,p,u,l,i,c,0,d);return n.makeTensorInfo(o,m.dtype,m.values)}var OJ={kernelName:Pl,backendName:"cpu",kernelFunc:FJ};function MJ(e,t){let n=0,s=e.length,r=0;for(;n<s;)r=Math.floor((n+s)/2),e[r]<t?n=r+1:s=r;return s}function zJ(e,t){let n=0,s=e.length,r=0;for(;n<s;)r=Math.floor((n+s)/2),e[r]<=t?n=r+1:s=r;return s}function LJ(e,t,n,s,r,a){let o=v.getArrayFromDType("int32",n*r);for(let i=0;i<n;++i){let l=e.slice(i*s,(i+1)*s),u=i*r;for(let c=0;c<r;++c)o[u+c]=a==="left"?MJ(l,t[c+u]):zJ(l,t[c+u])}return o}function BJ(e){let{inputs:t,backend:n,attrs:s}=e,{sortedSequence:r,values:a}=t,{side:o}=s,i=n.data.get(r.dataId).values,l=n.data.get(a.dataId).values,u=LJ(i,l,r.shape[0],r.shape[1],a.shape[1],o);return n.makeTensorInfo(a.shape,"int32",u)}var WJ={kernelName:p0,backendName:"cpu",kernelFunc:BJ};function VJ(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t;Ce([s,r,a],"select");let o=s.shape.length,i=n.data.get(s.dataId).values,l=n.data.get(r.dataId).values,u=n.data.get(a.dataId).values,c=On(r.dtype,a.dtype),p=v.makeZerosTypedArray(v.sizeFromShape(r.shape),c),d=0,h=o===0||o>1||r.shape.length===1?1:v.sizeFromShape(r.shape.slice(1));for(let f=0;f<i.length;f++)for(let m=0;m<h;m++)i[f]===1?p[d++]=l[f]:p[d++]=u[f];return n.makeTensorInfo(r.shape,c,p)}var UJ={kernelName:Fl,backendName:"cpu",kernelFunc:VJ},GJ=C.SELU_SCALEALPHA,HJ=C.SELU_SCALE,jJ=bt($c,e=>e>=0?HJ*e:GJ*(Math.exp(e)-1)),qJ={kernelName:$c,backendName:"cpu",kernelFunc:jJ},XJ=bt(Pc,e=>e<0?-1:e>0?1:0),KJ={kernelName:Pc,backendName:"cpu",kernelFunc:XJ},ZJ=bt(Yo,e=>Math.sin(e)),YJ={kernelName:Yo,backendName:"cpu",kernelFunc:ZJ},JJ=bt(Ml,e=>Math.sinh(e)),QJ={kernelName:Ml,backendName:"cpu",kernelFunc:JJ},eQ=11920928955078125e-23,u7=Math.log(eQ)+2,tQ=bt(Fc,e=>{let t=e>-u7,n=e<u7,s=Math.exp(e),r;return n?r=s:t?r=e:r=Math.log(1+s),r}),nQ={kernelName:Fc,backendName:"cpu",kernelFunc:tQ};function sQ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,paddings:o}=s;Ce([r],"spaceToBatchND");let i=v.sizeFromShape(a),l=[[0,0]];l.push(...o);for(let k=1+a.length;k<r.shape.length;++k)l.push([0,0]);let u=lS.kernelFunc({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),c=C.getReshaped(u.shape,a,i,!1),p=C.getPermuted(c.length,a.length,!1),d=C.getReshapedPermuted(u.shape,a,i,!1),m=Rt({inputs:{x:u},backend:n,attrs:{shape:c}}),x=gs({inputs:{x:m},backend:n,attrs:{perm:p}}),w=Rt({inputs:{x},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(x),w}var rQ={kernelName:zl,backendName:"cpu",kernelFunc:sQ};function aQ(e){let{inputs:t,backend:n}=e,{indices:s,values:r,denseShape:a,defaultValue:o}=t;if(a.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
+============================`));let s={id:this.nextDataId()};return this.data.set(s,{values:e,dtype:n,refCount:1}),s}makeTensorInfo(e,t,n){let s;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let r=n.map(a=>v.encodeString(a));s=this.write(r,e,t)}else s=this.write(n,e,t);return{dataId:s,shape:e,dtype:t}}refCount(e){return this.data.has(e)?this.data.get(e).refCount:0}incRef(e){let t=this.data.get(e);t.refCount++}decRef(e){if(this.data.has(e)){let t=this.data.get(e);t.refCount--}}move(e,t,n,s,r){this.data.set(e,{values:t,dtype:s,refCount:r})}numDataIds(){return this.data.numDataIds()}async read(e){return this.readSync(e)}readSync(e){let{dtype:t,complexTensorInfos:n}=this.data.get(e);if(t==="complex64"){let s=this.readSync(n.real.dataId),r=this.readSync(n.imag.dataId);return C.mergeRealAndImagArrays(s,r)}return this.data.get(e).values}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let n=t.map(s=>v.decodeString(s));return Le(e.shape,e.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Le(e.shape,e.dtype,t)}makeOutput(e,t,n){return sn().makeTensorFromTensorInfo(this.makeTensorInfo(t,n,e),this)}disposeData(e,t=!1){if(this.data.has(e)){if(this.data.get(e).refCount--,!t&&this.data.get(e).refCount>0)return!1;let{complexTensorInfos:n}=this.data.get(e);n!=null&&(this.disposeData(n.real.dataId,!0),this.disposeData(n.imag.dataId,!0)),this.data.delete(e)}return!0}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}async time(e){let t=v.now();return e(),{kernelMs:v.now()-t}}memory(){return{unreliable:!0,reasons:["The reported memory is an upper bound. Due to automatic garbage collection, the true allocated memory may be less."]}}where(e){Ce([e],"where");let t=this.readSync(e.dataId);return Wq(e.shape,t)}dispose(){}floatPrecision(){return 32}epsilon(){return super.epsilon()}};Ix.nextDataId=0;var Sx={};Ve(Sx,{addImpl:()=>hI,bincountImpl:()=>Tx,bincountReduceImpl:()=>fI,ceilImpl:()=>mI,concatImpl:()=>Nx,equalImpl:()=>gI,expImpl:()=>AI,expm1Impl:()=>bI,floorImpl:()=>vI,gatherNdImpl:()=>wI,gatherV2Impl:()=>kI,greaterEqualImpl:()=>SI,greaterImpl:()=>II,lessEqualImpl:()=>TI,lessImpl:()=>CI,linSpaceImpl:()=>NI,logImpl:()=>EI,maxImpl:()=>RI,maximumImpl:()=>_I,minimumImpl:()=>DI,multiplyImpl:()=>Ex,negImpl:()=>$I,notEqualImpl:()=>PI,prodImpl:()=>FI,rangeImpl:()=>_x,rsqrtImpl:()=>OI,scatterImpl:()=>Lu,sigmoidImpl:()=>EX,simpleAbsImpl:()=>pI,sliceImpl:()=>Rm,sparseFillEmptyRowsImpl:()=>zI,sparseReshapeImpl:()=>LI,sparseSegmentReductionImpl:()=>Dx,sqrtImpl:()=>DX,squaredDifferenceImpl:()=>BI,stridedSliceImpl:()=>WI,stringNGramsImpl:()=>$x,stringSplitImpl:()=>Px,stringToHashBucketFastImpl:()=>Fx,subImpl:()=>VI,tileImpl:()=>UI,topKImpl:()=>HI,transposeImpl:()=>Rx,uniqueImpl:()=>jI});function pI(e){let t=new Float32Array(e.length);for(let n=0;n<e.length;++n)t[n]=Math.abs(e[n]);return t}var Vq=e=>{let{x:t}=e.inputs,n=e.backend;Ce(t,"abs");let s=new Float32Array(v.sizeFromShape(t.shape)),r=n.data.get(t.dataId).values;return s=pI(r),n.makeOutput(s,t.shape,t.dtype)},Uq={kernelName:ol,backendName:"cpu",kernelFunc:Vq};function un(e){return(t,n,s,r,a)=>{let o=C.assertAndGetBroadcastShape(t,n),i=o.length,l=v.computeStrides(o),u=v.sizeFromShape(o),c=v.getTypedArrayFromDType(a,u),p=t.length,d=n.length,h=v.computeStrides(t),f=v.computeStrides(n),m=C.getBroadcastDims(t,o),g=C.getBroadcastDims(n,o);if(m.length+g.length===0)for(let y=0;y<c.length;++y)c[y]=e(s[y%s.length],r[y%r.length]);else for(let y=0;y<c.length;++y){let x=v.indexToLoc(y,i,l),A=x.slice(-p);m.forEach(S=>A[S]=0);let b=v.locToIndex(A,p,h),w=x.slice(-d);g.forEach(S=>w[S]=0);let k=v.locToIndex(w,d,f);c[y]=e(s[b],r[k])}return[c,o]}}function Cs(e){let{inputs:t,backend:n}=e,{real:s,imag:r}=t,a=n.data.get(s.dataId).values,o=n.data.get(r.dataId).values,i=n.makeTensorInfo(s.shape,"complex64"),l=n.data.get(i.dataId);return l.complexTensorInfos={real:n.makeTensorInfo(s.shape,"float32",a),imag:n.makeTensorInfo(r.shape,"float32",o)},i}var Gq={kernelName:zp,backendName:"cpu",kernelFunc:Cs};function Em(e,t,n="float32"){if(n==="complex64"){let r=Em(e,t,"float32"),a=Em(e,t,"float32");return Cs({inputs:{real:r,imag:a},backend:e})}let s=v.makeZerosTypedArray(v.sizeFromShape(t),n);return e.makeTensorInfo(t,n,s)}function Kr(e){let{inputs:t,backend:n}=e,{x:s}=t;return n.incRef(s.dataId),{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}var Hq={kernelName:Ro,backendName:"cpu",kernelFunc:Kr};function el(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.data.get(s.dataId).complexTensorInfos.real,a=n.data.get(r.dataId).values;return n.makeTensorInfo(r.shape,r.dtype,a)}var jq={kernelName:jp,backendName:"cpu",kernelFunc:el};function oo(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dtype:a}=s;if(a==="complex64"){if(r.dtype==="complex64")return Kr({inputs:{x:r},backend:n});let o=Em(n,r.shape,r.dtype),i=oo({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=Cs({inputs:{real:i,imag:o},backend:n});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}if(r.dtype==="complex64"){let o=el({inputs:{input:r},backend:n}),i=oo({inputs:{x:o},backend:n,attrs:{dtype:a}});return n.disposeIntermediateTensorInfo(o),i}if(!v.hasEncodingLoss(r.dtype,a)){let o=Kr({inputs:{x:r},backend:n});return{dataId:o.dataId,shape:o.shape,dtype:a}}if(a==="int32"){let o=n.data.get(r.dataId).values,i=Int32Array.from(o);return n.makeTensorInfo(r.shape,"int32",i)}if(a==="bool"){let o=n.data.get(r.dataId).values,i=v.toTypedArray([0],r.dtype),[l,u]=un((c,p)=>c!==p?1:0)(r.shape,[],o,i,"bool");return n.makeTensorInfo(u,"bool",l)}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${a}`)}var qq={kernelName:mo,backendName:"cpu",kernelFunc:oo};function kn(e,t,n,s){return n==null?({inputs:r,backend:a})=>{let{a:o,b:i}=r,l=a;Ce([o,i],e);let u=l.data.get(o.dataId).values,c=l.data.get(i.dataId).values,p=o.dtype==="string"?C.fromUint8ToStringArray(u):u,d=o.dtype==="string"?C.fromUint8ToStringArray(c):c,h=s||o.dtype,[f,m]=t(o.shape,i.shape,p,d,h);return l.makeTensorInfo(m,h,f)}:({inputs:r,backend:a})=>{let{a:o,b:i}=r,l=a;if(o.dtype==="complex64"||i.dtype==="complex64"){let u=oo({inputs:{x:o},backend:l,attrs:{dtype:"complex64"}}),c=l.data.get(u.dataId),p=c.complexTensorInfos.real,d=c.complexTensorInfos.imag,h=l.data.get(p.dataId).values,f=l.data.get(d.dataId).values,m=oo({inputs:{x:i},backend:l,attrs:{dtype:"complex64"}}),g=l.data.get(m.dataId),y=g.complexTensorInfos.real,x=g.complexTensorInfos.imag,A=l.data.get(y.dataId).values,b=l.data.get(x.dataId).values,[w,k,S]=n(o.shape,i.shape,h,f,A,b),E=l.makeTensorInfo(S,"float32",w),R=l.makeTensorInfo(S,"float32",k),P=Cs({inputs:{real:E,imag:R},backend:l});return l.disposeIntermediateTensorInfo(u),l.disposeIntermediateTensorInfo(m),l.disposeIntermediateTensorInfo(E),l.disposeIntermediateTensorInfo(R),P}else{let u=l.data.get(o.dataId).values,c=l.data.get(i.dataId).values,p=s||o.dtype,[d,h]=t(o.shape,i.shape,u,c,p);return l.makeTensorInfo(h,p,d)}}}function Cx(e){return(t,n,s,r,a,o)=>{let i=C.assertAndGetBroadcastShape(t,n),l=v.sizeFromShape(i),u=i.length,c=v.computeStrides(i),p=v.getTypedArrayFromDType("float32",l),d=v.getTypedArrayFromDType("float32",l),h=C.getBroadcastDims(t,i),f=C.getBroadcastDims(n,i),m=C.mergeRealAndImagArrays(s,r),g=C.mergeRealAndImagArrays(a,o),y=t.length,x=v.computeStrides(t),A=n.length,b=v.computeStrides(n);if(h.length+f.length===0)for(let w=0;w<p.length;w++){let k=w%m.length,S=w%g.length,E=e(m[k*2],m[k*2+1],g[S*2],g[S*2+1]);p[w]=E.real,d[w]=E.imag}else for(let w=0;w<p.length;w++){let k=v.indexToLoc(w,u,c),S=k.slice(-y);h.forEach($=>S[$]=0);let E=v.locToIndex(S,y,x),R=k.slice(-A);f.forEach($=>R[$]=0);let P=v.locToIndex(R,A,b),_=e(m[E*2],m[E*2+1],g[P*2],g[P*2+1]);p[w]=_.real,d[w]=_.imag}return[p,d,i]}}var hI=un((e,t)=>e+t),Xq=Cx((e,t,n,s)=>({real:e+n,imag:t+s})),ac=kn(Aa,hI,Xq),Kq={kernelName:Aa,backendName:"cpu",kernelFunc:ac};function Tx(e,t,n,s,r){let a=v.sizeFromShape(s),o=v.makeZerosTypedArray(r,n);for(let i=0;i<e.length;i++){let l=e[i];if(l<0)throw new Error("Input x must be non-negative!");l>=r||(a>0?o[l]+=t[i]:o[l]+=1)}return o}function fI(e,t,n,s=!1){let r=e.shape[0],a=e.shape[1],o=Le([r,n],t.dtype);for(let i=0;i<r;i++)for(let l=0;l<a;l++){let u=e.get(i,l);if(u<0)throw new Error("Input x must be non-negative!");u>=n||(s?o.set(1,i,u):t.size>0?o.set(o.get(i,u)+t.get(i,l),i,u):o.set(o.get(i,u)+1,i,u))}return o}function ci(e){return(t,n,s)=>{let r=v.getTypedArrayFromDType(n,t.length);for(let a=0;a<t.length;++a)r[a]=e(t[a],s);return r}}function bt(e,t,n){return({inputs:s,attrs:r,backend:a})=>{let{x:o}=s;if(Ce(o,e),o.dtype==="string"||n==="string")throw new Error("unaryKernelFunc does not support string input/output");let i=a,l=i.data.get(o.dataId).values,u=v.sizeFromShape(o.shape),c=n||o.dtype,p=v.getArrayFromDType(c,u);for(let d=0;d<u;++d)p[d]=t(l[d],r);return i.makeTensorInfo(o.shape,c,p)}}function Qc(e,t,n){return({inputs:s,attrs:r,backend:a})=>{let{x:o}=s;if(Ce(o,e),o.dtype==="string"||n==="string")throw new Error("unaryKernelFunc does not support string input/output");let i=a,l=i.data.get(o.dataId).values,u=n||o.dtype,c=t(l,u,r);return i.makeTensorInfo(o.shape,u,c)}}var mI=ci(e=>Math.ceil(e)),Zq=Qc(go,mI),Yq={kernelName:go,backendName:"cpu",kernelFunc:Zq};function Nx(e,t,n,s){let r=v.getArrayFromDType(n,v.sizeFromShape(t));if(s&&n!=="string"){let a=0;e.forEach(o=>{let i=v.sizeFromShape(o.shape);r.set(o.vals,a),a+=i})}else{let a=0;e.forEach(o=>{let i=n==="string"?C.fromUint8ToStringArray(o.vals):o.vals,l=0;for(let u=0;u<o.shape[0];++u){let c=u*t[1]+a;for(let p=0;p<o.shape[1];++p)r[c+p]=i[l++]}a+=o.shape[1]})}return r}var gI=un((e,t)=>e===t?1:0),yI=kn(pl,gI,null,"bool"),Jq={kernelName:pl,backendName:"cpu",kernelFunc:yI},AI=ci(e=>Math.exp(e)),xI=Qc(So,AI,"float32"),Qq={kernelName:So,backendName:"cpu",kernelFunc:xI},bI=ci(e=>Math.expm1(e)),eX=Qc(fl,bI),tX={kernelName:fl,backendName:"cpu",kernelFunc:eX},vI=ci(e=>Math.floor(e)),nX=Qc(Co,vI),sX={kernelName:Co,backendName:"cpu",kernelFunc:nX};function wI(e,t,n,s,r,a,o,i,l){let u=Le([s,a],n);for(let c=0;c<s;c++){let p=[],d=0;for(let h=0;h<r;h++){let f=e[c*r+h];d+=f*o[h],p.push(f)}if(d<0||d>=l/a)throw new Error(`Invalid indices: ${p} does not index into ${i}`);for(let h=0;h<a;h++)u.values[c*a+h]=t.get(...t.indexToLoc(d*a+h))}return u}function kI(e,t,n){let s=Le(n,e.dtype);for(let r=0;r<s.size;++r){let o=s.indexToLoc(r).slice(),i=o[0],l=o[2],u=t.locToIndex([i,l]);o[2]=t.values[u];let c=e.locToIndex(o);0<=c&&c<e.values.length&&(s.values[r]=e.values[c])}return s}var II=un((e,t)=>e>t?1:0),rX=kn(Al,II,null,"bool"),aX={kernelName:Al,backendName:"cpu",kernelFunc:rX},SI=un((e,t)=>e>=t?1:0),oX=kn(Eo,SI,null,"bool"),iX={kernelName:Eo,backendName:"cpu",kernelFunc:oX},CI=un((e,t)=>e<t?1:0),lX=kn(xl,CI,null,"bool"),uX={kernelName:xl,backendName:"cpu",kernelFunc:lX},TI=un((e,t)=>e<=t?1:0),cX=kn(bl,TI,null,"bool"),dX={kernelName:bl,backendName:"cpu",kernelFunc:cX};function NI(e,t,n){let s=(t-e)/(n-1),r=v.makeZerosTypedArray(n,"float32");r[0]=e;for(let a=1;a<r.length;a++)r[a]=r[a-1]+s;return r}var EI=ci(e=>Math.log(e)),pX=Qc(Do,EI),hX={kernelName:Do,backendName:"cpu",kernelFunc:pX};function RI(e,t,n,s){let r=v.getTypedArrayFromDType(s,v.sizeFromShape(n));for(let a=0;a<r.length;++a){let o=a*t,i=e[o];for(let l=0;l<t;++l){let u=e[o+l];(Number.isNaN(u)||u>i)&&(i=u)}r[a]=i}return r}var _I=un((e,t)=>Math.max(e,t)),fX=kn(Po,_I),mX={kernelName:Po,backendName:"cpu",kernelFunc:fX},DI=un((e,t)=>Math.min(e,t)),gX=kn(zo,DI),yX={kernelName:zo,backendName:"cpu",kernelFunc:gX},Ex=un((e,t)=>e*t),AX=Cx((e,t,n,s)=>({real:e*n-t*s,imag:e*s+t*n})),y2=kn(Bo,Ex,AX),xX={kernelName:Bo,backendName:"cpu",kernelFunc:y2};function $I(e,t,n){let s=v.createScalarValue(-1,n);return Ex([],t,s,e,n)}function bX(e){let{inputs:t,backend:n}=e,{x:s}=t;Ce(s,"neg");let r=n.data.get(s.dataId).values,[a,o]=$I(r,s.shape,s.dtype);return n.makeTensorInfo(o,s.dtype,a)}var vX={kernelName:kl,backendName:"cpu",kernelFunc:bX},PI=un((e,t)=>e!==t?1:0),wX=kn(Il,PI,null,"bool"),kX={kernelName:Il,backendName:"cpu",kernelFunc:wX};function Rx(e,t,n,s,r){let a=t.length,o=v.sizeFromShape(t),i=v.computeStrides(t),l=v.computeStrides(r),u=v.getTypedArrayFromDType(n,v.sizeFromShape(r));for(let c=0;c<o;++c){let p=v.indexToLoc(c,a,i),d=new Array(p.length);for(let f=0;f<d.length;f++)d[f]=p[s[f]];let h=v.locToIndex(d,a,l);u[h]=e[c]}return u}function gs(e){let{inputs:t,attrs:n,backend:s}=e,{x:r}=t,{perm:a}=n;Ce(r,"transpose");let o=r.shape.length,i=new Array(o);for(let p=0;p<i.length;p++)i[p]=r.shape[a[p]];let l=s.data.get(r.dataId).values,u=Rx(l,r.shape,r.dtype,a,i);return{dataId:s.write(u,i,r.dtype),shape:i,dtype:r.dtype}}var IX={kernelName:Gr,backendName:"cpu",kernelFunc:gs};function FI(e,t,n,s){let[r,a]=C.computeOutAndReduceShapes(e,s),o=On(t,"int32"),i=v.makeZerosTypedArray(v.sizeFromShape(r),o),l=v.sizeFromShape(a);for(let u=0;u<i.length;++u){let c=u*l,p=1;for(let d=0;d<l;++d)p*=n[c+d];i[u]=p}return{outVals:i,outShape:r,outDtype:o}}function SX(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;Ce(r,"prod");let i=r.shape.length,l=v.parseAxisParam(a,r.shape),u=C.getAxesPermutation(l,i),c=l,p=r,d=[];u!=null&&(p=gs({inputs:{x:r},backend:n,attrs:{perm:u}}),d.push(p),c=C.getInnerMostAxes(c.length,i));let h=n.data.get(p.dataId).values,{outVals:f,outShape:m,outDtype:g}=FI(p.shape,p.dtype,h,c),y=m;return o&&(y=C.expandShapeToKeepDim(m,l)),d.forEach(x=>n.disposeIntermediateTensorInfo(x)),n.makeTensorInfo(y,g,f)}var CX={kernelName:Go,backendName:"cpu",kernelFunc:SX};function _x(e,t,n,s){let r=e===t,a=e<t&&n<0,o=t<e&&n>1;if(r||a||o)return v.makeZerosTypedArray(0,s);let i=Math.abs(Math.ceil((t-e)/n)),l=v.makeZerosTypedArray(i,s);t<e&&n===1&&(n=-1),l[0]=e;for(let u=1;u<l.length;u++)l[u]=l[u-1]+n;return l}var OI=ci(e=>1/Math.sqrt(e)),TX=Qc(Ko,OI),NX={kernelName:Ko,backendName:"cpu",kernelFunc:TX};function Lu(e,t,n,s,r,a,o,i,l,u){let c=[s/r,r],p=e.values,d=t.values;if(s===0)return Le(n,t.dtype);let h=Le(c,t.dtype);typeof l=="string"||typeof l=="number"?h.values.fill(l):typeof l=="boolean"&&h.values.fill(+l);for(let f=0;f<a;f++){let m=[],g=0;for(let y=0;y<o;y++){let x=p[f*o+y];m.push(x),g+=x*i[y]}if(g<0||g>=s/r)throw new Error(`Invalid indices: ${m} does not index into ${n}`);for(let y=0;y<r;y++)u?h.values[g*r+y]+=d[f*r+y]:h.values[g*r+y]=t.rank===0?d[0]:d[f*r+y]}return h}var EX=ci(e=>1/(1+Math.exp(-e))),MI=bt(Yo,e=>1/(1+Math.exp(-e))),RX={kernelName:Yo,backendName:"cpu",kernelFunc:MI};function Rm(e,t,n,s,r){let a=Ut.isSliceContinous(s,t,n),o=v.sizeFromShape(n),i=v.computeStrides(s);if(a){let p=Ut.computeFlatOffset(t,i);return r==="string"?e.slice(p,p+o):e.subarray(p,p+o)}let l=r==="string"?C.fromUint8ToStringArray(e):e,u=Le(s,r,l),c=Le(n,r);for(let p=0;p<c.size;++p){let d=c.indexToLoc(p),h=d.map((f,m)=>f+t[m]);c.set(u.get(...h),...d)}return r==="string"?C.fromStringArrayToUint8(c.values):c.values}function tl(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,size:o}=s;Ce(r,"slice");let[i,l]=Ut.parseSliceParams(r,a,o);Ut.assertParamsValid(r,i,l);let u=n.data.get(r.dataId).values,c=Rm(u,i,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,c)}var _X={kernelName:Fl,backendName:"cpu",kernelFunc:tl};function zI(e,t,n,s,r,a,o){let i=t[0],l=a[0],u=new Array(l),c=new Array(i),p=t[1];if(l===0){if(i!==0)throw new Error(C.getSparseFillEmptyRowsIndicesDenseShapeMismatch(i));let g=v.getArrayFromDType(n,0),y=v.getArrayFromDType(r,0);return[g,[0,p],y,u,c]}let d=!0,h=0,f=new Array(l).fill(0);for(let g=0;g<i;++g){let y=e[g*p];if(y<0)throw new Error(C.getSparseFillEmptyRowsNegativeIndexErrorMessage(g,y));if(y>=l)throw new Error(C.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(g,y,l));++f[y],d=d&&y>=h,h=y}let m=!0;for(let g=0;g<l;++g){let y=f[g]===0;u[g]=y,m=m&&!y,f[g]=Math.max(f[g],1),g>0&&(f[g]+=f[g-1])}if(m&&d){let g=e,y=s;for(let x=0;x<i;++x)c[x]=x;return[g,[i,p],y,u,c]}else{let g=f[l-1],y=v.getArrayFromDType(n,g*p),x=v.getArrayFromDType(r,g),A=new Array(l).fill(0);for(let b=0;b<i;++b){let w=e[b*p],k=A[w],S=(w===0?0:f[w-1])+k;A[w]++;for(let E=0;E<p;++E)y[S*p+E]=e[b*p+E];x[S]=s[b],c[b]=S}for(let b=0;b<l;++b)if(A[b]===0){let k=b===0?0:f[b-1];y[k*p+0]=b;for(let S=1;S<p;++S)y[k*p+S]=0;x[k]=o}return[y,[g,p],x,u,c]}}function LI(e,t,n,s,r){let a=v.sizeFromShape(s),o=t[0],i=r.length,l=[],u=1,c=-1;for(let g=0;g<i;++g){let y=r[g];if(y===-1){if(c!==-1)throw new Error(C.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(c,g));c=g,l.push(1)}else{if(y<0)throw new Error(C.getSparseReshapeNegativeOutputDimErrorMessage(g,y));u*=y,l.push(y)}}if(c!==-1){if(u<=0)throw new Error(C.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage());let g=Math.trunc(a/u);if(u*g!==a)throw new Error(C.getSparseReshapeInputOutputMultipleErrorMessage(s,l));l[c]=g}if(v.sizeFromShape(l)!==a)throw new Error(C.getSparseReshapeInputOutputMismatchErrorMessage(s,l));let d=s.length,h=[];if(d>0){h[d-1]=1;for(let g=d-2;g>=0;--g)h[g]=h[g+1]*s[g+1]}let f=[];if(i>0){f[i-1]=1;for(let g=i-2;g>=0;--g)f[g]=f[g+1]*l[g+1]}let m=v.getArrayFromDType(n,o*i);for(let g=0;g<o;++g){let y=0;for(let x=0;x<d;++x)y+=e[g*d+x]*h[x];for(let x=0;x<i;++x)m[g*i+x]=Math.trunc(y/f[x]),y%=f[x]}return[m,[o,i],l]}function Dx(e,t,n,s,r,a=!1,o=0){let i=s.length,l=[t[0],e.length/t[0]],u=l[1],p=i>0?r[i-1]+1:0;if(p<0)throw new Error(C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let d=t.slice();d[0]=p;let h=d.reduce((A,b)=>A*b,1),f=v.getArrayFromDType(n,h);if(i===0)return p>0&&f.fill(o),[f,d];if(p<=0)throw new Error(C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let m=0,g=1,y=0,x=r[m];for(;;){let A=0;if(g<i){if(A=r[g],x===A){++g;continue}if(x>=A)throw new Error(C.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage())}if(x<0||x>=p)throw new Error(C.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(x,p));x>y&&f.fill(o,y*u,x*u);for(let b=m;b<g;++b){let w=s[b];if(w<0||w>=l[0])throw new Error(C.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(b,s[b],l[0]));for(let k=0;k<u;k++)f[x*u+k]+=e[w*u+k]}if(a)for(let b=0;b<u;b++)f[x*u+b]/=g-m;if(m=g,++g,y=x+1,x=A,g>i)break}return y<p&&f.fill(o,y*u,p*u),[f,d]}var DX=ci(e=>Math.sqrt(e)),$X=bt(Jo,e=>Math.sqrt(e)),PX={kernelName:Jo,backendName:"cpu",kernelFunc:$X},BI=un((e,t)=>{let n=e-t;return n*n}),FX=kn(ti,BI),OX={kernelName:ti,backendName:"cpu",kernelFunc:FX};function WI(e,t,n,s){let r=Le(e,t.dtype);for(let a=0;a<r.size;a++){let o=r.indexToLoc(a),i=new Array(o.length);for(let l=0;l<i.length;l++)i[l]=o[l]*n[l]+s[l];r.set(t.get(...i),...o)}return r}var MX=class{constructor(e,t,n,s,r,a){this.separator=v.encodeString(e),this.nGramWidths=t,this.leftPad=v.encodeString(n),this.rightPad=v.encodeString(s),this.padWidth=r,this.preserveShort=a}getPadWidth(e){return Math.min(this.padWidth<0?e-1:this.padWidth,e-1)}getNumNGrams(e,t){let n=this.getPadWidth(t);return Math.max(0,e+2*n-t+1)}createNGrams(e,t,n,s,r,a){for(let o=0;o<r;++o){let i=this.getPadWidth(a),l=Math.max(0,i-o),u=Math.max(0,i-(r-(o+1))),c=a-(l+u),p=t+(l>0?0:o-i),d=0;d+=l*this.leftPad.length;for(let y=0;y<c;++y)d+=e[p+y].length;d+=u*this.rightPad.length,d+=(l+u+c-1)*this.separator.length,n[s+o]=new Uint8Array(d);let f=n[s+o],m=0,g=y=>y.forEach(x=>f[m++]=x);for(let y=0;y<l;++y)g(this.leftPad),g(this.separator);for(let y=0;y<c-1;++y)g(e[p+y]),g(this.separator);if(c>0){g(e[p+c-1]);for(let y=0;y<u;++y)g(this.separator),g(this.rightPad)}else{for(let y=0;y<u-1;++y)g(this.rightPad),g(this.separator);g(this.rightPad)}}}compute(e,t){let n=e.length,s=t.length;if(s>0){let i=t[0];if(i!==0)throw new Error(`First split value must be 0, got ${i}`);for(let l=1;l<s;++l){let u=t[l]>=i;if(u=u&&t[l]<=n,!u)throw new Error(`Invalid split value ${t[l]}, must be in [${i}, ${n}]`);i=t[l]}if(i!==n)throw new Error(`Last split value must be data size. Expected ${n}, got ${i}`)}let r=s-1,a=v.getArrayFromDType("int32",s);if(n===0||s===0){let i=new Array(n);for(let l=0;l<=r;++l)a[l]=0;return[i,a]}a[0]=0;for(let i=1;i<=r;++i){let l=t[i]-t[i-1],u=0;this.nGramWidths.forEach(c=>{u+=this.getNumNGrams(l,c)}),this.preserveShort&&l>0&&u===0&&(u=1),a[i]=a[i-1]+u}let o=new Array(a[r]);for(let i=0;i<r;++i){let l=t[i],u=a[i];if(this.nGramWidths.forEach(c=>{let p=t[i+1]-t[i],d=this.getNumNGrams(p,c);this.createNGrams(e,l,o,u,d,c),u+=d}),this.preserveShort&&u===a[i]){let c=t[i+1]-t[i];if(c===0)continue;let p=c+2*this.padWidth,d=1;this.createNGrams(e,l,o,u,d,p)}}return[o,a]}};function $x(e,t,n,s,r,a,o,i){return new MX(n,s,r,a,o,i).compute(e,t)}function zX(e,t,n,s){if(!e.length)return;if(t.length===0){for(let a=0;a<e.length;++a)s.push(e.subarray(a,a+1));return}if(t.length===1){let a=t[0],o=e.indexOf(a);for(;o!==-1;){let i=e.subarray(0,o);(!n||i.length!==0)&&s.push(i),e=e.subarray(o+1),o=e.indexOf(a)}(!n||e.length!==0)&&s.push(e);return}let r=0;for(let a=0;a<e.length+1;a++)if(a===e.length||t.indexOf(e[a])!==-1){let o=e.subarray(r,a);(!n||o.length!==0)&&s.push(o),r=a+1}}function Px(e,t,n){let s=e.length,r=[],a=0,o=0,i=new Array(s);for(let d=0;d<s;++d){let h=r.length;zX(e[d],t,n,r);let f=r.length-h;i[d]=f,a+=f,o=Math.max(o,f)}let l=v.getArrayFromDType("int32",a*2),u=new Array(a),c=[s,o],p=0;for(let d=0;d<s;++d)for(let h=0;h<i[d];++h)l[p*2]=d,l[p*2+1]=h,u[p]=r[p],++p;return[l,u,c]}function Fx(e,t){let n=v.getArrayFromDType("int32",e.length);for(let s=0;s<e.length;++s)n[s]=v.fingerPrint64(e[s]).modulo(t).getLowBitsUnsigned();return n}var VI=un((e,t)=>e-t),LX=Cx((e,t,n,s)=>({real:e-n,imag:t-s})),Ox=kn(ni,VI,LX),BX={kernelName:ni,backendName:"cpu",kernelFunc:Ox};function UI(e,t){let n=new Array(e.rank);for(let r=0;r<n.length;r++)n[r]=e.shape[r]*t[r];let s=Le(n,e.dtype);for(let r=0;r<s.values.length;++r){let a=s.indexToLoc(r),o=new Array(e.rank);for(let l=0;l<o.length;l++)o[l]=a[l]%e.shape[l];let i=e.locToIndex(o);s.values[r]=e.values[i]}return s}var op=(e,t)=>{let n=t.value-e.value;return n===0?e.index-t.index:n};function GI(e,t,n=0,s=e.length-1){for(;s>n;){if(s-n>600){let i=s-n+1,l=t-n+1,u=Math.log(i),c=.5*Math.exp(2*u/3),p=.5*Math.sqrt(u*c*(i-c)/i)*Math.sign(l-i/2),d=Math.max(n,Math.floor(t-l*c/i+p)),h=Math.min(s,Math.floor(t+(i-l)*c/i+p));GI(e,t,d,h)}let r=e[t],a=n,o=s;for(v.swap(e,n,t),op(e[s],r)>0&&v.swap(e,n,s);a<o;){for(v.swap(e,a,o),a++,o--;op(e[a],r)<0;)a=a+1;for(;op(e[o],r)>0;)o=o-1}op(e[n],r)===0?v.swap(e,n,o):(o=o+1,v.swap(e,o,s)),o<=t&&(n=o+1),t<=o&&(s=o-1)}}function HI(e,t,n,s,r){let a=t[t.length-1],[o,i]=[e.length/a,a],l=v.getTypedArrayFromDType(n,o*s),u=v.getTypedArrayFromDType("int32",o*s);for(let p=0;p<o;p++){let d=p*i,h=e.subarray(d,d+i),f=new Array(h.length);h.forEach((x,A)=>f[A]={value:x,index:A}),s<f.length&&(GI(f,s),f=f.slice(0,s)),r&&f.sort(op);let m=p*s,g=l.subarray(m,m+s),y=u.subarray(m,m+s);for(let x=0;x<s;x++)g[x]=f[x].value,y[x]=f[x].index}let c=t.slice();return c[c.length-1]=s,[Le(c,n,l),Le(c,"int32",u)]}function jI(e,t,n,s){let r=v.parseAxisParam(t,n)[0],a=[1,n[0],1];for(let f=0;f<r;f++)a[0]*=n[f];a[1]=n[r];for(let f=r+1;f<n.length;f++)a[2]*=n[f];let o={},i=new Int32Array(n[r]),l=new fn(a,s,e),u=[],c=a[0]===1&&a[2]===1;for(let f=0;f<n[r];f++){let m;if(c)m=e[f].toString();else{let g=[];for(let y=0;y<a[0];y++)for(let x=0;x<a[2];x++)g.push(l.get(y,f,x));m=g.join(",")}if(o[m]!==void 0)i[f]=o[m];else{let g=Object.keys(o).length;o[m]=g,i[f]=g,u.push(f)}}let p=a.slice();p[1]=Object.keys(o).length;let d=new fn(p,s);u.forEach((f,m)=>{for(let g=0;g<a[0];g++)for(let y=0;y<a[2];y++)d.set(l.get(g,f,y),g,m,y)});let h=n.slice();return h[r]=p[1],{outputValues:d.values,outputShape:h,indices:i}}jl("cpu",()=>new Ix,1);var qI=bt(Io,e=>e>=0?e:Math.exp(e)-1),WX={kernelName:Io,backendName:"cpu",kernelFunc:qI};function XI(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s;Ce([r],"leakyRelu");let o=v.sizeFromShape(r.shape),i=n.data.get(r.dataId).values,l=v.getTypedArrayFromDType("float32",o);for(let u=0;u<i.length;u++)l[u]=i[u]<0?a*i[u]:i[u];return n.makeTensorInfo(r.shape,"float32",l)}var VX={kernelName:_o,backendName:"cpu",kernelFunc:XI},UX=un((e,t)=>e<0?t*e:e);function KI(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t;Ce([s,r],"prelu");let a=n.data.get(s.dataId).values,o=n.data.get(r.dataId).values,[i,l]=UX(s.shape,r.shape,a,o,"float32");return n.makeTensorInfo(l,"float32",i)}var GX={kernelName:Uo,backendName:"cpu",kernelFunc:KI},ZI=bt(Ho,e=>Math.max(0,e)),HX={kernelName:Ho,backendName:"cpu",kernelFunc:ZI},YI=bt(Xo,e=>Math.min(Math.max(0,e),6)),jX={kernelName:Xo,backendName:"cpu",kernelFunc:YI};function _m(e,t,n,s,r){if(n==="linear")return Kr({inputs:{x:t},backend:e});if(n==="relu")return ZI({inputs:{x:t},backend:e});if(n==="elu")return qI({inputs:{x:t},backend:e});if(n==="relu6")return YI({inputs:{x:t},backend:e});if(n==="prelu")return KI({inputs:{x:t,alpha:s},backend:e});if(n==="leakyrelu")return XI({inputs:{x:t},backend:e,attrs:{alpha:r}});if(n==="sigmoid")return MI({inputs:{x:t},backend:e});throw new Error(`Activation ${n} has not been implemented for the CPU backend.`)}function Rt(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{shape:a}=s,o=v.sizeFromShape(r.shape),i=v.inferFromImplicitShape(a,o),l=v.sizeFromShape(i);v.assert(o===l,()=>`The new shape (${i}) has ${l} elements and the old shape (${r.shape}) has ${o} elements. The new shape and old shape must have the same number of elements.`),n.incRef(r.dataId);let u=n.data.get(r.dataId);if(u.complexTensorInfos!=null){let c=u.complexTensorInfos.real,p=u.complexTensorInfos.imag;c.shape=i,p.shape=i}return{dataId:r.dataId,shape:i,dtype:r.dtype}}var qX={kernelName:Rl,backendName:"cpu",kernelFunc:Rt};function JI(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;Ce([r,a],"matMul");let l=r.shape.length,u=a.shape.length,c=o?r.shape[l-2]:r.shape[l-1],p=i?a.shape[u-1]:a.shape[u-2],d=o?r.shape[l-1]:r.shape[l-2],h=i?a.shape[u-2]:a.shape[u-1],f=r.shape.slice(0,-2),m=a.shape.slice(0,-2),g=v.sizeFromShape(f),y=v.sizeFromShape(m),A=ql.assertAndGetBroadcastShape(r.shape.slice(0,-2),a.shape.slice(0,-2)).concat([d,h]);v.assert(c===p,()=>`Error in matMul: inner shapes (${c}) and (${p}) of Tensors with shapes ${r.shape} and ${a.shape} and transposeA=${o} and transposeB=${i} must match.`);let b=o?[g,c,d]:[g,d,c],w=i?[y,h,p]:[y,p,h],k=Rt({inputs:{x:r},backend:n,attrs:{shape:b}}),S=Rt({inputs:{x:a},backend:n,attrs:{shape:w}}),E=o?k.shape[1]:k.shape[2],R=o?k.shape[2]:k.shape[1],P=i?S.shape[1]:S.shape[2],_=Math.max(g,y),$=n.data.get(k.dataId).values,T=n.data.get(S.dataId).values,F=v.computeStrides(k.shape),G=v.computeStrides(S.shape),[q,z,Z]=o?[F[0],1,F[1]]:[F[0],F[1],1],[B,ee,Q]=i?[1,G[1],G[0]]:[G[1],1,G[0]],oe=R*P,Y=Le([_,R,P],k.dtype),ae=Y.values,le=n.blockSize;for(let ye=0;ye<_;ye++)for(let we=0;we<R;we+=le)for(let Re=0;Re<P;Re+=le)for(let _e=0;_e<E;_e+=le){let Be=Math.min(we+le,R),Ge=Math.min(Re+le,P),ot=Math.min(_e+le,E);for(let dt=we;dt<Be;dt++)for(let pt=Re;pt<Ge;pt++){let At=0;for(let $e=_e;$e<ot;$e++){let Tt=Math.min(ye,g-1)*q,It=Math.min(ye,y-1)*Q,Un=$[Tt+dt*z+$e*Z],Qt=T[$e*B+pt*ee+It];At+=Un*Qt}ae[ye*oe+(dt*P+pt)]+=At}}return n.disposeIntermediateTensorInfo(k),n.disposeIntermediateTensorInfo(S),n.makeTensorInfo(A,Y.dtype,Y.values)}var XX={kernelName:fo,backendName:"cpu",kernelFunc:JI};function KX(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=s,d,h,f,m=[];d=JI({inputs:{a:r,b:a},attrs:{transposeA:l,transposeB:u},backend:n}),o&&(h=ac({inputs:{a:d,b:o},backend:n}),m.push(d),d=h),c&&(f=_m(n,d,c,i,p),m.push(d),d=f);for(let y of m)n.disposeIntermediateTensorInfo(y);return d}var ZX={kernelName:Ya,backendName:"cpu",kernelFunc:KX},YX=bt(dc,e=>Math.acos(e)),JX={kernelName:dc,backendName:"cpu",kernelFunc:YX},QX=bt(pc,e=>Math.acosh(e)),eK={kernelName:pc,backendName:"cpu",kernelFunc:QX};function tK(e){let{inputs:t,backend:n}=e,s=t;Ce(t,"addN");let r=s.map(i=>n.data.get(i.dataId).values),a=Le(s[0].shape,s[0].dtype),o=a.values;for(let i=0;i<s.length;i++){let l=r[i];for(let u=0;u<o.length;u++)o[u]+=l[u]}return n.makeTensorInfo(a.shape,a.dtype,a.values)}var nK={kernelName:co,backendName:"cpu",kernelFunc:tK};function sK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;Ce(r,"all");let i=v.parseAxisParam(a,r.shape),l=i,u=C.getAxesPermutation(l,r.shape.length),c=r;u!=null&&(c=gs({inputs:{x:r},backend:n,attrs:{perm:u}}),l=C.getInnerMostAxes(l.length,r.shape.length)),C.assertAxesAreInnerMostDims("all",l,c.shape.length);let[p,d]=C.computeOutAndReduceShapes(c.shape,l),h=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(p),c.dtype),m=n.data.get(c.dataId).values;for(let y=0;y<f.length;++y){let x=y*h,A=m[x];for(let b=0;b<h;++b){let w=m[x+b];A=A&&w}f[y]=A}u!=null&&n.disposeIntermediateTensorInfo(c);let g=n.makeTensorInfo(p,c.dtype,f);if(o){let y=C.expandShapeToKeepDim(p,i),x=Rt({inputs:{x:g},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(g),x}return g}var rK={kernelName:hc,backendName:"cpu",kernelFunc:sK};function aK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;Ce(r,"any");let i=v.parseAxisParam(a,r.shape),l=i,u=C.getAxesPermutation(l,r.shape.length),c=r;u!=null&&(c=gs({inputs:{x:r},backend:n,attrs:{perm:u}}),l=C.getInnerMostAxes(l.length,r.shape.length)),C.assertAxesAreInnerMostDims("any",l,c.shape.length);let[p,d]=C.computeOutAndReduceShapes(c.shape,l),h=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(p),c.dtype),m=n.data.get(c.dataId).values;for(let y=0;y<f.length;++y){let x=y*h,A=m[x];for(let b=0;b<h;++b){let w=m[x+b];A=A||w}f[y]=A}u!=null&&n.disposeIntermediateTensorInfo(c);let g=n.makeTensorInfo(p,c.dtype,f);if(o){let y=C.expandShapeToKeepDim(p,i),x=Rt({inputs:{x:g},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(g),x}return g}var oK={kernelName:fc,backendName:"cpu",kernelFunc:aK};function iK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s;Ce(r,"argMax");let o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=gs({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),o=[o[0]],C.assertAxesAreInnerMostDims("argMax",o,l.shape.length);let[c,p]=C.computeOutAndReduceShapes(l.shape,o),d=v.sizeFromShape(c),h=v.makeZerosTypedArray(d,"int32"),f=v.sizeFromShape(p),m=n.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let y=g*f,x=m[y],A=0;for(let b=0;b<f;++b){let w=m[y+b];w>x&&(x=w,A=b)}h[g]=A}return u.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(c,"int32",h)}var lK={kernelName:po,backendName:"cpu",kernelFunc:iK};function uK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s;Ce(r,"argMin");let o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=gs({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),o=[o[0]],C.assertAxesAreInnerMostDims("argMin",o,l.shape.length);let[c,p]=C.computeOutAndReduceShapes(l.shape,o),d=v.sizeFromShape(c),h=v.makeZerosTypedArray(d,"int32"),f=v.sizeFromShape(p),m=n.data.get(l.dataId).values;for(let g=0;g<h.length;++g){let y=g*f,x=m[y],A=0;for(let b=0;b<f;++b){let w=m[y+b];w<x&&(x=w,A=b)}h[g]=A}return u.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.makeTensorInfo(c,"int32",h)}var cK={kernelName:mc,backendName:"cpu",kernelFunc:uK},dK=bt(gc,e=>Math.asin(e)),pK={kernelName:gc,backendName:"cpu",kernelFunc:dK},hK=bt(yc,e=>Math.asinh(e)),fK={kernelName:yc,backendName:"cpu",kernelFunc:hK},mK=bt(Ac,e=>Math.atan(e)),gK={kernelName:Ac,backendName:"cpu",kernelFunc:mK},yK=un((e,t)=>Math.atan2(e,t)),AK=kn(bc,yK),xK={kernelName:bc,backendName:"cpu",kernelFunc:AK},bK=bt(xc,e=>Math.atanh(e)),vK={kernelName:xc,backendName:"cpu",kernelFunc:bK};function Mx(e,t,n,s,r,a){let o=r.strideHeight,i=r.strideWidth,l=r.dilationHeight,u=r.dilationWidth,c=r.effectiveFilterHeight,p=r.effectiveFilterWidth,d=r.padInfo.top,h=r.padInfo.left,f=a==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,m=Le(r.outShape,n),g=m.values,y=r.outShape[1]*r.outShape[2]*r.outShape[3],x=r.outShape[2]*r.outShape[3],A=r.outShape[3];for(let b=0;b<r.batchSize;++b){let w=b*y,k=b*s[0];for(let S=0;S<r.inChannels;++S)for(let E=0;E<r.outHeight;++E){let R=E*o-d,P=Math.max(0,R),_=Math.min(r.inHeight,c+R),$=w+E*x;for(let T=0;T<r.outWidth;++T){let F=T*i-h,G=Math.max(0,F),q=Math.min(r.inWidth,p+F),z=f,Z=0,B=0;for(let Q=P;Q<_;Q+=l){let oe=k+Q*s[1];for(let Y=G;Y<q;Y+=u){let ae=oe+Y*s[2],le=e[ae+S];a==="max"&&le>z?z=le:a==="avg"&&(Z+=le,B++)}if(isNaN(z))break}let ee=$+T*A+S;g[ee]=a==="avg"?Z/B:z}}}return m}function QI(e,t,n,s,r=!1,a=!1){let o=Le(s.outShape,"int32"),i=s.strideHeight,l=s.strideWidth,u=s.dilationHeight,c=s.dilationWidth,p=s.effectiveFilterHeight,d=s.effectiveFilterWidth,h=s.padInfo.top,f=s.padInfo.left,m=Le(t,n,e);for(let g=0;g<s.batchSize;++g)for(let y=0;y<s.inChannels;++y)for(let x=0;x<s.outHeight;++x){let A=x*i-h,b=A;for(;b<0;)b+=u;let w=Math.min(s.inHeight,p+A);for(let k=0;k<s.outWidth;++k){let S=k*l-f,E=S;for(;E<0;)E+=c;let R=Math.min(s.inWidth,d+S),P=Number.NEGATIVE_INFINITY,_=-1;for(let $=b;$<w;$+=u){let T=$-A;for(let F=E;F<R;F+=c){let G=F-S,q=m.get(g,$,F,y);q>P&&(P=q,r?_=a?((g*s.inHeight+$)*s.inWidth+F)*s.inChannels+y:($*s.inWidth+F)*s.inChannels+y:_=T*d+G)}}o.set(_,g,x,k,y)}}return o}function eS(e,t,n,s,r,a){let o=r.strideDepth,i=r.strideHeight,l=r.strideWidth,u=r.dilationDepth,c=r.dilationHeight,p=r.dilationWidth,d=r.effectiveFilterDepth,h=r.effectiveFilterHeight,f=r.effectiveFilterWidth,m=r.padInfo.front,g=r.padInfo.top,y=r.padInfo.left,x=a==="max"?Number.NEGATIVE_INFINITY:Number.POSITIVE_INFINITY,A=Le(r.outShape,n),b=A.values,w=r.outShape[1]*r.outShape[2]*r.outShape[3]*r.outShape[4],k=r.outShape[2]*r.outShape[3]*r.outShape[4],S=r.outShape[3]*r.outShape[4],E=r.outShape[4];for(let R=0;R<r.batchSize;++R){let P=R*w,_=R*s[0];for(let $=0;$<r.inChannels;++$)for(let T=0;T<r.outDepth;++T){let F=T*o-m,G=F;for(;G<0;)G+=u;let q=Math.min(r.inDepth,d+F),z=P+T*k;for(let Z=0;Z<r.outHeight;++Z){let B=Z*i-g,ee=B;for(;ee<0;)ee+=c;let Q=Math.min(r.inHeight,h+B),oe=z+Z*S;for(let Y=0;Y<r.outWidth;++Y){let ae=Y*l-y,le=ae;for(;le<0;)le+=p;let ye=Math.min(r.inWidth,f+ae),we=oe+Y*E,Re=x,_e=0,Be=0;for(let ot=G;ot<q;ot+=u){let dt=_+ot*s[1];for(let pt=ee;pt<Q;pt+=c){let At=dt+pt*s[2];for(let $e=le;$e<ye;$e+=p){let Tt=At+$e*s[3],It=e[Tt+$];if(a==="max"&&It>Re?Re=It:a==="avg"&&(_e+=It,Be++),isNaN(Re))break}if(isNaN(Re))break}if(isNaN(Re))break}let Ge=we+$;b[Ge]=a==="avg"?_e/Be:Re}}}}return A}function wK(e,t){let n=Le(t.outShape,"int32"),s=t.strideDepth,r=t.strideHeight,a=t.strideWidth,o=t.dilationDepth,i=t.dilationHeight,l=t.dilationWidth,u=t.effectiveFilterDepth,c=t.effectiveFilterHeight,p=t.effectiveFilterWidth,d=t.padInfo.front,h=t.padInfo.top,f=t.padInfo.left;for(let m=0;m<t.batchSize;++m)for(let g=0;g<t.inChannels;++g)for(let y=0;y<t.outDepth;++y){let x=y*s-d,A=x;for(;A<0;)A+=o;let b=Math.min(t.inDepth,u+x);for(let w=0;w<t.outHeight;++w){let k=w*r-h,S=k;for(;S<0;)S+=i;let E=Math.min(t.inHeight,c+k);for(let R=0;R<t.outWidth;++R){let P=R*a-f,_=P;for(;_<0;)_+=l;let $=Math.min(t.inWidth,p+P),T=Number.NEGATIVE_INFINITY,F=-1;for(let G=A;G<b;G+=o){let q=G-x;for(let z=S;z<E;z+=i){let Z=z-k;for(let B=_;B<$;B+=l){let ee=B-P,Q=e.get(m,G,z,B,g);Q>=T&&(T=Q,F=q*c*p+Z*c+ee)}}}n.set(F,m,y,w,R,g)}}}return n}function kK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;Ce(r,"avgPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;v.assert(C.eitherStridesOrDilationsAreOne(o,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=C.computePool2DInfo(r.shape,a,o,u,i,l),p;if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))p=Kr({inputs:{x:r},backend:n});else{let d=n.data.get(r.dataId).values,h=v.computeStrides(r.shape),f=Mx(d,r.shape,r.dtype,h,c,"avg");p=n.makeTensorInfo(c.outShape,r.dtype,f.values)}return p}var IK={kernelName:ho,backendName:"cpu",kernelFunc:kK};function SK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l,dataFormat:u}=s;Ce(r,"avgPool3d");let c=C.computePool3DInfo(r.shape,a,o,1,i,l,u),p=n.data.get(r.dataId).values,d=eS(p,r.shape,r.dtype,v.computeStrides(r.shape),c,"avg");return n.makeTensorInfo(d.shape,"float32",d.values)}var CK={kernelName:Mp,backendName:"cpu",kernelFunc:SK};function TK(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=s;Ce([r,a],"avgPool3DGrad");let c=C.computePool3DInfo(a.shape,o,i,1,l,u),p=c.strideDepth,d=c.strideHeight,h=c.strideWidth,f=c.filterDepth,m=c.filterHeight,g=c.filterWidth,y=c.dilationDepth,x=c.dilationHeight,A=c.dilationWidth,b=c.effectiveFilterDepth,w=c.effectiveFilterHeight,k=c.effectiveFilterWidth,S=b-1-c.padInfo.front,E=k-1-c.padInfo.left,R=w-1-c.padInfo.top,P=Le(a.shape,"float32"),_=1/(f*m*g),$=n.bufferSync(r);for(let T=0;T<c.batchSize;++T)for(let F=0;F<c.inChannels;++F)for(let G=0;G<c.inDepth;++G)for(let q=0;q<c.inHeight;++q)for(let z=0;z<c.inWidth;++z){let Z=G-S,B=q-R,ee=z-E,Q=0;for(let oe=0;oe<b;oe+=y){let Y=(Z+oe)/p;if(!(Y<0||Y>=c.outDepth||Math.floor(Y)!==Y))for(let ae=0;ae<w;ae+=x){let le=(B+ae)/d;if(!(le<0||le>=c.outHeight||Math.floor(le)!==le))for(let ye=0;ye<k;ye+=A){let we=(ee+ye)/h;if(we<0||we>=c.outWidth||Math.floor(we)!==we)continue;Q+=$.get(T,Y,le,we,F)}}}P.set(Q*_,T,G,q,z,F)}return n.makeTensorInfo(P.shape,P.dtype,P.values)}var NK={kernelName:Gm,backendName:"cpu",kernelFunc:TK};function EK(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a;Ce([r,a],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=s,c=C.computePool2DInfo(o.shape,i,l,1,u),p=c.strideHeight,d=c.strideWidth,h=c.filterHeight,f=c.filterWidth,m=c.dilationHeight,g=c.dilationWidth,y=c.effectiveFilterHeight,x=c.effectiveFilterWidth,A=x-1-c.padInfo.left,b=y-1-c.padInfo.top,w=Le(o.shape,"float32"),k=1/(h*f),S=n.data.get(r.dataId).values,E=Le(r.shape,"float32",S);for(let R=0;R<c.batchSize;++R)for(let P=0;P<c.inChannels;++P)for(let _=0;_<c.inHeight;++_)for(let $=0;$<c.inWidth;++$){let T=_-b,F=$-A,G=0;for(let q=0;q<y;q+=m){let z=(T+q)/p;if(!(z<0||z>=c.outHeight||Math.floor(z)!==z))for(let Z=0;Z<x;Z+=g){let B=(F+Z)/d;if(B<0||B>=c.outWidth||Math.floor(B)!==B)continue;G+=E.get(R,z,B,P)}}w.set(G*k,R,_,$,P)}return n.makeTensorInfo(w.shape,w.dtype,w.values)}var RK={kernelName:Um,backendName:"cpu",kernelFunc:EK};function _K(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,scale:a,offset:o,mean:i,variance:l}=t;v.assert(i.shape.length===l.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(o==null||i.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(a==null||i.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks."),Ce([r,i,l,a,o],"batchNorm");let{varianceEpsilon:u}=s;u==null&&(u=.001);let c=n.data.get(r.dataId).values,p=n.data.get(i.dataId).values,d=n.data.get(l.dataId).values,h=a?n.data.get(a.dataId).values:new Float32Array([1]),f=o?n.data.get(o.dataId).values:new Float32Array([0]),m=new Float32Array(c.length),g=f.length,y=h.length,x=d.length,A=p.length,b=0,w=0,k=0,S=0;for(let E=0;E<c.length;++E)m[E]=f[b++]+(c[E]-p[w++])*h[k++]/Math.sqrt(d[S++]+u),b>=g&&(b=0),w>=A&&(w=0),k>=y&&(k=0),S>=x&&(S=0);return n.makeTensorInfo(r.shape,r.dtype,m)}var DK={kernelName:No,backendName:"cpu",kernelFunc:_K};function $K(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s;Ce([r],"batchToSpaceND");let i=a.reduce((y,x)=>y*x),l=C.getReshaped(r.shape,a,i),u=C.getPermuted(l.length,a.length),c=C.getReshapedPermuted(r.shape,a,i),p=C.getSliceBeginCoords(o,a.length),d=C.getSliceSize(c,o,a.length),h=Rt({inputs:{x:r},backend:n,attrs:{shape:l}}),f=gs({inputs:{x:h},backend:n,attrs:{perm:u}}),m=Rt({inputs:{x:f},backend:n,attrs:{shape:c}}),g=tl({inputs:{x:m},backend:n,attrs:{begin:p,size:d}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),g}var PK={kernelName:il,backendName:"cpu",kernelFunc:$K};function FK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o}=s,i=n.data.get(r.dataId).values,l=n.data.get(a.dataId).values,u=Tx(i,l,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,u)}var OK={kernelName:Hm,backendName:"cpu",kernelFunc:FK};function MK(e){let{inputs:t,backend:n}=e,{s0:s,s1:r}=t,a=n.data.get(s.dataId).values,o=n.data.get(r.dataId).values,i=C.assertAndGetBroadcastShape(Array.from(a),Array.from(o));return n.makeTensorInfo([i.length],"int32",Int32Array.from(i))}var zK={kernelName:jm,backendName:"cpu",kernelFunc:MK},LK=bt(xa,(e,t)=>{let n=t;return e>n.clipValueMax?n.clipValueMax:e<n.clipValueMin?n.clipValueMin:e}),BK={kernelName:xa,backendName:"cpu",kernelFunc:LK},WK=e=>{let{x:t}=e.inputs,n=e.backend,s=new Float32Array(v.sizeFromShape(t.shape)),r=n.data.get(t.dataId),a=r.complexTensorInfos.real,o=r.complexTensorInfos.imag,i=n.data.get(a.dataId).values,l=n.data.get(o.dataId).values;for(let u=0;u<i.length;u++){let c=i[u],p=l[u];s[u]=Math.hypot(c,p)}return n.makeOutput(s,t.shape,"float32")},VK={kernelName:Lp,backendName:"cpu",kernelFunc:WK};function oc(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.data.get(s.dataId).complexTensorInfos.imag,a=n.data.get(r.dataId).values;return n.makeTensorInfo(r.shape,r.dtype,a)}var UK={kernelName:Up,backendName:"cpu",kernelFunc:oc};function ic(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s,a=v.parseAxisParam(r,t[0].shape)[0],o=C.computeOutShape(t.map(m=>m.shape),a);if(v.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let i=t.filter(m=>v.sizeFromShape(m.shape)>0);if(i.length===1)return Kr({inputs:{x:i[0]},backend:n});let l=i.map(m=>m.shape);if(C.assertParamsConsistent(l,a),i[0].dtype==="complex64"){let m=i.map(b=>el({inputs:{input:b},backend:n})),g=i.map(b=>oc({inputs:{input:b},backend:n})),y=ic({inputs:m,backend:n,attrs:{axis:a}}),x=ic({inputs:g,backend:n,attrs:{axis:a}}),A=Cs({inputs:{real:y,imag:x},backend:n});return m.forEach(b=>n.disposeIntermediateTensorInfo(b)),g.forEach(b=>n.disposeIntermediateTensorInfo(b)),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(x),A}let u=i.map(m=>{let g=v.sizeFromShape(m.shape.slice(a));return Rt({inputs:{x:m},backend:n,attrs:{shape:[-1,g]}})}),c=u.map(m=>({vals:n.data.get(m.dataId).values,shape:m.shape}));o=C.computeOutShape(u.map(m=>m.shape),1);let p=u[0].shape[0]===1,d=Nx(c,o,t[0].dtype,p),h=C.computeOutShape(i.map(m=>m.shape),a),f=n.makeTensorInfo(h,t[0].dtype,d);return u.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var GK={kernelName:ll,backendName:"cpu",kernelFunc:ic};function tS(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=s;Ce([r,a],"conv2d");let p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,a.shape,o,u,i,c,!1,p),h=d.filterHeight,f=d.filterWidth,m=d.dilationHeight,g=d.dilationWidth,y=d.padInfo.left,x=d.padInfo.top,A=d.dataFormat==="channelsLast",b=new fn(d.outShape,r.dtype),w=v.computeStrides(r.shape),k=v.computeStrides(a.shape),S=w[0],E=A?w[1]:w[2],R=A?w[2]:1,P=A?1:w[1],_=b.strides[0],$=A?b.strides[1]:b.strides[2],T=A?b.strides[2]:1,F=A?1:b.strides[1],G=n.data.get(r.dataId).values,q=n.data.get(a.dataId).values,z=b.values;for(let Z=0;Z<d.batchSize;++Z){let B=Z*S,ee=Z*_;for(let Q=0;Q<d.outHeight;++Q){let oe=ee+Q*$,Y=Q*d.strideHeight-x;for(let ae=0;ae<h;++ae){let le=Y+ae*m;if(le<0||le>=d.inHeight)continue;let ye=ae*k[0],we=B+le*E;for(let Re=0;Re<d.outWidth;++Re){let _e=oe+Re*T,Be=Re*d.strideWidth-y;for(let Ge=0;Ge<f;++Ge){let ot=Be+Ge*g;if(ot<0||ot>=d.inWidth)continue;let dt=ye+Ge*k[1],pt=we+ot*R,At=dt;for(let $e=0;$e<d.inChannels;++$e){let Tt=G[pt+$e*P];for(let It=0;It<d.outChannels;++It)z[_e+It*F]+=Tt*q[At+It];At+=d.outChannels}}}}}}return n.makeTensorInfo(b.shape,b.dtype,z)}var HK={kernelName:yo,backendName:"cpu",kernelFunc:tS};function jK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=s;Ce([r,a],"conv2dBackpropFilter");let p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,c,o,1,i,u,!1,p),{strideHeight:h,strideWidth:f,filterHeight:m,filterWidth:g}=d,y=d.dataFormat==="channelsLast",x=new fn(d.filterShape,"float32"),A=d.padInfo.left,b=d.padInfo.top,w=n.data.get(r.dataId).values,k=n.data.get(a.dataId).values,S=new fn(r.shape,r.dtype,w),E=new fn(a.shape,a.dtype,k);for(let R=0;R<m;++R){let P=Math.max(0,Math.ceil((b-R)/h)),_=Math.min(d.outHeight,(d.inHeight+b-R)/h);for(let $=0;$<g;++$){let T=Math.max(0,Math.ceil((A-$)/f)),F=Math.min(d.outWidth,(d.inWidth+A-$)/f);for(let G=0;G<d.inChannels;++G)for(let q=0;q<d.outChannels;++q){let z=0;for(let Z=0;Z<d.batchSize;++Z)for(let B=P;B<_;++B){let ee=R+B*h-b;for(let Q=T;Q<F;++Q){let oe=$+Q*f-A;y?z+=S.get(Z,ee,oe,G)*E.get(Z,B,Q,q):z+=S.get(Z,G,ee,oe)*E.get(Z,q,B,Q)}}x.set(z,R,$,G,q)}}}return n.makeTensorInfo(x.shape,x.dtype,x.values)}var qK={kernelName:qm,backendName:"cpu",kernelFunc:jK};function XK(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=s;Ce([r,a],"conv2dBackpropInput");let p=v.computeStrides(a.shape),d=v.computeStrides(r.shape),h=C.convertConv2DDataFormat(u),f=C.computeConv2DInfo(o,a.shape,i,1,l,c,!1,h),m=new fn(f.inShape,"float32"),g=m.values,y=n.data.get(r.dataId).values,x=n.data.get(a.dataId).values,[A,b,w]=p,{batchSize:k,filterHeight:S,filterWidth:E,inChannels:R,inHeight:P,inWidth:_,outChannels:$,outHeight:T,outWidth:F,strideHeight:G,strideWidth:q}=f;h=f.dataFormat;let z=S-1-f.padInfo.top,Z=E-1-f.padInfo.left,B=h==="channelsLast",ee=m.strides[0],Q=B?m.strides[1]:m.strides[2],oe=B?m.strides[2]:1,Y=B?1:m.strides[1],ae=d[0],le=B?d[1]:d[2],ye=B?d[2]:1,we=B?1:d[1];for(let Re=0;Re<k;++Re)for(let _e=0;_e<R;++_e)for(let Be=0;Be<P;++Be){let Ge=Be-z,ot=Math.max(0,Math.ceil(Ge/G)),dt=Math.min(T,(S+Ge)/G);for(let pt=0;pt<_;++pt){let At=pt-Z,$e=Math.max(0,Math.ceil(At/q)),Tt=Math.min(F,(E+At)/q),It=0;for(let Qt=ot;Qt<dt;++Qt){let bs=Qt*G-Ge;for(let pn=$e;pn<Tt;++pn){let Gn=pn*q-At,vs=ae*Re+le*Qt+ye*pn,ws=A*(S-1-bs)+b*(E-1-Gn)+w*_e;for(let $n=0;$n<$;++$n){let Vs=y[vs+we*$n],Hn=x[ws+$n];It+=Vs*Hn}}}let Un=ee*Re+Q*Be+oe*pt+Y*_e;g[Un]=It}}return n.makeTensorInfo(m.shape,m.dtype,m.values)}var KK={kernelName:Ao,backendName:"cpu",kernelFunc:XK};function ZK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s;Ce([r,a],"conv3d");let u=C.computeConv3DInfo(r.shape,a.shape,o,l,i),{filterDepth:c,filterHeight:p,filterWidth:d,dilationDepth:h,dilationHeight:f,dilationWidth:m,padInfo:g}=u,y=g.front,x=g.left,A=g.top,b=new fn(u.outShape,r.dtype),w=n.data.get(r.dataId).values,k=n.data.get(a.dataId).values,S=b.values,E=v.computeStrides(r.shape),R=v.computeStrides(a.shape);for(let P=0;P<u.batchSize;++P){let _=P*E[0],$=P*b.strides[0];for(let T=0;T<u.outDepth;++T){let F=$+T*b.strides[1],G=T*u.strideDepth-y;for(let q=0;q<c;++q){let z=G+q*h;if(z<0||z>=u.inDepth)continue;let Z=q*R[0],B=_+z*E[1];for(let ee=0;ee<u.outHeight;++ee){let Q=F+ee*b.strides[2],oe=ee*u.strideHeight-A;for(let Y=0;Y<p;++Y){let ae=oe+Y*f;if(ae<0||ae>=u.inHeight)continue;let le=Z+Y*R[1],ye=B+ae*E[2];for(let we=0;we<u.outWidth;++we){let Re=Q+we*u.outChannels,_e=we*u.strideWidth-x;for(let Be=0;Be<d;++Be){let Ge=_e+Be*m;if(Ge<0||Ge>=u.inWidth)continue;let ot=le+Be*R[2],dt=ye+Ge*u.inChannels,pt=ot;for(let At=0;At<u.inChannels;++At){let $e=w[dt+At];for(let Tt=0;Tt<u.outChannels;++Tt)S[Re+Tt]+=$e*k[pt+Tt];pt+=u.outChannels}}}}}}}}return n.makeTensorInfo(b.shape,b.dtype,b.values)}var YK={kernelName:Bp,backendName:"cpu",kernelFunc:ZK};function JK(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,filterShape:l}=s;Ce([r,a],"conv3dBackpropFilterV2");let u=v.computeStrides(r.shape),c=v.computeStrides(a.shape),p=C.computeConv3DInfo(r.shape,l,o,1,i),d=p.strideDepth,h=p.strideHeight,f=p.strideWidth,m=p.filterDepth,g=p.filterHeight,y=p.filterWidth,x=new fn(p.filterShape,"float32"),A=x.values,[b,w,k,S]=x.strides,E=n.data.get(a.dataId).values,[R,P,_,$]=c,T=n.data.get(r.dataId).values,[F,G,q,z]=u,Z=p.padInfo.front,B=p.padInfo.left,ee=p.padInfo.top;for(let Q=0;Q<m;++Q){let oe=Math.max(0,Math.ceil((Z-Q)/d)),Y=Math.min(p.outDepth,(p.inDepth+Z-Q)/d),ae=Q*b;for(let le=0;le<g;++le){let ye=Math.max(0,Math.ceil((ee-le)/h)),we=Math.min(p.outHeight,(p.inHeight+ee-le)/h),Re=le*w+ae;for(let _e=0;_e<y;++_e){let Be=Math.max(0,Math.ceil((B-_e)/f)),Ge=Math.min(p.outWidth,(p.inWidth+B-_e)/f),ot=_e*k+Re;for(let dt=0;dt<p.inChannels;++dt){let pt=dt*S+ot;for(let At=0;At<p.outChannels;++At){let $e=0;for(let Tt=0;Tt<p.batchSize;++Tt){let It=Tt*F,Un=Tt*R;for(let Qt=oe;Qt<Y;++Qt){let pn=(Q+Qt*d-Z)*G+It,Gn=Qt*P+Un;for(let vs=ye;vs<we;++vs){let $n=(le+vs*h-ee)*q+pn,Vs=vs*_+Gn;for(let Hn=Be;Hn<Ge;++Hn){let ra=(_e+Hn*f-B)*z+$n,Au=Hn*$+Vs;$e+=T[ra+dt]*E[Au+At]}}}}A[pt+At]=$e}}}}}return n.makeTensorInfo(x.shape,x.dtype,x.values)}var QK={kernelName:Xm,backendName:"cpu",kernelFunc:JK};function eZ(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{pad:o,strides:i,inputShape:l}=s;Ce([r],"conv3dBackpropInputV2");let u=v.computeStrides(r.shape),c=v.computeStrides(a.shape),p=C.computeConv3DInfo(l,a.shape,i,1,o),d=new fn(p.inShape,"float32"),h=d.values,[f,m,g,y]=d.strides,x=n.data.get(r.dataId).values,[A,b,w,k]=u,S=n.data.get(a.dataId).values,[E,R,P,_]=c,{batchSize:$,filterDepth:T,filterHeight:F,filterWidth:G,inChannels:q,inDepth:z,inHeight:Z,inWidth:B,outChannels:ee,outDepth:Q,outHeight:oe,outWidth:Y,strideDepth:ae,strideHeight:le,strideWidth:ye}=p,we=T-1-p.padInfo.front,Re=F-1-p.padInfo.top,_e=G-1-p.padInfo.left;for(let Be=0;Be<$;++Be)for(let Ge=0;Ge<q;++Ge)for(let ot=0;ot<z;++ot){let dt=ot-we,pt=Math.max(0,Math.ceil(dt/ae)),At=Math.min(Q,(T+dt)/ae);for(let $e=0;$e<Z;++$e){let Tt=$e-Re,It=Math.max(0,Math.ceil(Tt/le)),Un=Math.min(oe,(F+Tt)/le);for(let Qt=0;Qt<B;++Qt){let bs=Qt-_e,pn=Math.max(0,Math.ceil(bs/ye)),Gn=Math.min(Y,(G+bs)/ye),vs=0;for(let ws=pt;ws<At;++ws){let $n=ws*ae-dt;for(let Vs=It;Vs<Un;++Vs){let Hn=Vs*le-Tt;for(let sa=pn;sa<Gn;++sa){let ra=sa*ye-bs,Au=A*Be+b*ws+w*Vs+k*sa,Fa=E*(T-1-$n)+R*(F-1-Hn)+P*(G-1-ra)+_*Ge;for(let aa=0;aa<ee;++aa){let Od=x[Au+aa],xu=S[Fa+aa];vs+=Od*xu}}}}h[f*Be+m*ot+g*$e+y*Qt+Ge]=vs}}}return n.makeTensorInfo(d.shape,d.dtype,d.values)}var tZ={kernelName:Km,backendName:"cpu",kernelFunc:eZ},nZ=bt(xo,e=>Math.cos(e)),sZ={kernelName:xo,backendName:"cpu",kernelFunc:nZ},rZ=bt(bo,e=>Math.cosh(e)),aZ={kernelName:bo,backendName:"cpu",kernelFunc:rZ};function oZ(e){let{inputs:t,backend:n,attrs:s}=e,{image:r,boxes:a,boxInd:o}=t,{cropSize:i,method:l,extrapolationValue:u}=s,[c,p,d,h]=r.shape,f=a.shape[0],[m,g]=i,y=Le([f,m,g,h],"float32"),x=n.data.get(a.dataId).values,A=n.data.get(o.dataId).values,b=n.data.get(r.dataId).values,w=v.computeStrides(r.shape),k=v.computeStrides(y.shape);for(let S=0;S<f;S++){let E=S*4,R=x[E],P=x[E+1],_=x[E+2],$=x[E+3],T=A[S];if(T>=c)continue;let F=m>1?(_-R)*(p-1)/(m-1):0,G=g>1?($-P)*(d-1)/(g-1):0;for(let q=0;q<m;q++){let z=m>1?R*(p-1)+q*F:.5*(R+_)*(p-1);if(z<0||z>p-1){for(let Z=0;Z<g;Z++)for(let B=0;B<h;B++){let ee=B+Z*k[2]+q*k[1]+S*k[0];y.values[ee]=u}continue}if(l==="bilinear"){let Z=Math.floor(z),B=Math.ceil(z),ee=z-Z;for(let Q=0;Q<g;Q++){let oe=g>1?P*(d-1)+Q*G:.5*(P+$)*(d-1);if(oe<0||oe>d-1){for(let ye=0;ye<h;ye++){let we=ye+Q*k[2]+q*k[1]+S*k[0];y.values[we]=u}continue}let Y=Math.floor(oe),ae=Math.ceil(oe),le=oe-Y;for(let ye=0;ye<h;ye++){let we=ye+Y*w[2]+Z*w[1]+T*w[0],Re=b[we];we=ye+ae*w[2]+Z*w[1]+T*w[0];let _e=b[we];we=ye+Y*w[2]+B*w[1]+T*w[0];let Be=b[we];we=ye+ae*w[2]+B*w[1]+T*w[0];let Ge=b[we],ot=Re+(_e-Re)*le,dt=Be+(Ge-Be)*le;we=ye+Q*k[2]+q*k[1]+S*k[0],y.values[we]=ot+(dt-ot)*ee}}}else for(let Z=0;Z<g;++Z){let B=g>1?P*(d-1)+Z*G:.5*(P+$)*(d-1);if(B<0||B>d-1){for(let oe=0;oe<h;oe++){let Y=oe+Z*k[2]+q*k[1]+S*k[0];y.values[Y]=u}continue}let ee=Math.round(B),Q=Math.round(z);for(let oe=0;oe<h;oe++){let Y=oe+ee*w[2]+Q*w[1]+T*w[0],ae=oe+Z*k[2]+q*k[1]+S*k[0];y.values[ae]=b[Y]}}}}return n.makeTensorInfo(y.shape,y.dtype,y.values)}var iZ={kernelName:cl,backendName:"cpu",kernelFunc:oZ};function lZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;Ce(r,"cumprod");let l=C.getAxesPermutation([a],r.shape.length),u=r;l!=null&&(u=gs({inputs:{x:r},backend:n,attrs:{perm:l}}));let c=C.getInnerMostAxes(1,r.shape.length)[0];if(c!==u.shape.length-1)throw new Error(`backend.cumprod in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${c}`);let p=On(u.dtype,"int32"),d=v.makeOnesTypedArray(v.sizeFromShape(u.shape),p),h=n.data.get(u.dataId).values,f=u.shape[u.shape.length-1],m=i?(y,x)=>y+f-x-1:(y,x)=>y+x;for(let y=0;y<h.length;y+=f)for(let x=0;x<f;x++){let A=m(y,x);if(x===0)d[A]=o?1:h[A];else{let b=m(y,x-1);d[A]=o?h[b]*d[b]:h[A]*d[b]}}let g=n.makeTensorInfo(u.shape,p,d);if(l!=null){let y=C.getUndoAxesPermutation(l),x=gs({inputs:{x:g},backend:n,attrs:{perm:y}});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(u),x}return g}var uZ={kernelName:ul,backendName:"cpu",kernelFunc:lZ};function cZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;Ce(r,"cumsum");let l=C.getAxesPermutation([a],r.shape.length),u=r;l!=null&&(u=gs({inputs:{x:r},backend:n,attrs:{perm:l}}));let c=C.getInnerMostAxes(1,r.shape.length)[0];if(c!==u.shape.length-1)throw new Error(`backend.cumsum in CPU expects an inner-most axis=${u.shape.length-1} but got axis=${c}`);let p=On(u.dtype,"int32"),d=v.makeZerosTypedArray(v.sizeFromShape(u.shape),p),h=n.data.get(u.dataId).values,f=u.shape[u.shape.length-1],m=i?(y,x)=>y+f-x-1:(y,x)=>y+x;for(let y=0;y<h.length;y+=f)for(let x=0;x<f;x++){let A=m(y,x);if(x===0)d[A]=o?0:h[A];else{let b=m(y,x-1);d[A]=o?h[b]+d[b]:h[A]+d[b]}}let g=n.makeTensorInfo(u.shape,p,d);if(l!=null){let y=C.getUndoAxesPermutation(l),x=gs({inputs:{x:g},backend:n,attrs:{perm:y}});return n.disposeIntermediateTensorInfo(g),n.disposeIntermediateTensorInfo(u),x}return g}var dZ={kernelName:vo,backendName:"cpu",kernelFunc:cZ};function pZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o,binaryOutput:i}=s;if(r.shape.length===1){let l=n.data.get(r.dataId).values,u=n.data.get(a.dataId).values,c=Tx(l,u,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,c)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(a),c=fI(l,u,o,i);return n.makeTensorInfo(c.shape,a.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var hZ={kernelName:Zm,backendName:"cpu",kernelFunc:pZ};function fZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockSize:a,dataFormat:o}=s;v.assert(o==="NHWC",()=>`Only NHWC dataFormat supported on CPU for depthToSpace. Got ${o}`);let i=r.shape[0],l=r.shape[1],u=r.shape[2],c=r.shape[3],p=l*a,d=u*a,h=c/(a*a),f=n.data.get(r.dataId).values,m=new Float32Array(i*p*d*h),g=0;for(let y=0;y<i;++y)for(let x=0;x<p;++x){let A=Math.floor(x/a),b=x%a;for(let w=0;w<d;++w){let k=Math.floor(w/a),S=w%a,E=(b*a+S)*h;for(let R=0;R<h;++R){let _=R+E+c*(k+u*(A+l*y));m[g++]=f[_]}}}return n.makeTensorInfo([i,p,d,h],r.dtype,m)}var mZ={kernelName:dl,backendName:"cpu",kernelFunc:fZ};function nS(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l,dimRoundingMode:u}=s;Ce([r,a],"depthwiseConv2DNative");let c=v.computeStrides(r.shape),p=v.computeStrides(a.shape),d=l;d==null&&(d=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(o,d),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${o} and dilations '${d}'`);let h=C.computeConv2DInfo(r.shape,a.shape,o,d,i,u,!0),{filterHeight:f,filterWidth:m,dilationHeight:g,dilationWidth:y,padInfo:x}=h,A=x.left,b=x.top,w=h.outChannels/h.inChannels,k=new fn(h.outShape,r.dtype),S=n.data.get(r.dataId).values,E=n.data.get(a.dataId).values,R=k.values;for(let P=0;P<h.batchSize;++P){let _=P*c[0],$=P*k.strides[0];for(let T=0;T<h.outHeight;++T){let F=$+T*k.strides[1],G=T*h.strideHeight-b;for(let q=0;q<f;++q){let z=G+q*g;if(z<0||z>=h.inHeight)continue;let Z=q*p[0],B=_+z*c[1];for(let ee=0;ee<h.outWidth;++ee){let Q=F+ee*k.strides[2],oe=ee*h.strideWidth-A;for(let Y=0;Y<m;++Y){let ae=oe+Y*y;if(ae<0||ae>=h.inWidth)continue;let le=Z+Y*p[1],ye=B+ae*h.inChannels,we=Q,Re=le;for(let _e=0;_e<h.inChannels;++_e){let Be=S[ye+_e];for(let Ge=0;Ge<w;++Ge)R[we+Ge]+=Be*E[Re+Ge];we+=w,Re+=w}}}}}}return n.makeTensorInfo(k.shape,k.dtype,k.values)}var gZ={kernelName:wo,backendName:"cpu",kernelFunc:nS};function yZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=s;Ce([r,a],"depthwiseConv2dNativeBackpropFilter");let p=C.computeConv2DInfo(r.shape,c,o,i,l,u,!0),{strideHeight:d,strideWidth:h,filterHeight:f,filterWidth:m}=p,g=new fn(p.filterShape,"float32"),y=p.padInfo.left,x=p.padInfo.top,A=p.outChannels/p.inChannels,b=n.data.get(r.dataId).values,w=new fn(r.shape,r.dtype,b),k=n.data.get(a.dataId).values,S=new fn(a.shape,a.dtype,k);for(let E=0;E<f;++E){let R=Math.max(0,Math.ceil((x-E)/d)),P=Math.min(p.outHeight,(p.inHeight+x-E)/d);for(let _=0;_<m;++_){let $=Math.max(0,Math.ceil((y-_)/h)),T=Math.min(p.outWidth,(p.inWidth+y-_)/h);for(let F=0;F<p.outChannels;++F){let G=Math.trunc(F/A),q=F%A,z=0;for(let Z=0;Z<p.batchSize;++Z)for(let B=R;B<P;++B){let ee=E+B*d-x;for(let Q=$;Q<T;++Q){let oe=_+Q*h-y;z+=w.get(Z,ee,oe,G)*S.get(Z,B,Q,F)}}g.set(z,E,_,G,q)}}}return n.makeTensorInfo(g.shape,g.dtype,g.values)}var AZ={kernelName:Ym,backendName:"cpu",kernelFunc:yZ};function xZ(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=s;Ce([r,a],"depthwiseConv2DNativeBackpropInput");let p=v.computeStrides(r.shape),d=v.computeStrides(a.shape),h=C.computeConv2DInfo(c,a.shape,o,i,l,u,!0),f=new fn(h.inShape,"float32"),m=f.values,[g,y,x]=f.strides,A=n.data.get(r.dataId).values,[b,w,k]=p,S=n.data.get(a.dataId).values,[E,R,P]=d,{batchSize:_,filterHeight:$,filterWidth:T,inChannels:F,inHeight:G,inWidth:q,outChannels:z,outHeight:Z,outWidth:B,strideHeight:ee,strideWidth:Q}=h,oe=$-1-h.padInfo.top,Y=T-1-h.padInfo.left,ae=z/F;for(let le=0;le<_;++le)for(let ye=0;ye<F;++ye)for(let we=0;we<G;++we){let Re=we-oe,_e=Math.max(0,Math.ceil(Re/ee)),Be=Math.min(Z,($+Re)/ee);for(let Ge=0;Ge<q;++Ge){let ot=Ge-Y,dt=Math.max(0,Math.ceil(ot/Q)),pt=Math.min(B,(T+ot)/Q),At=0;for(let $e=_e;$e<Be;++$e){let Tt=$e*ee-Re;for(let It=dt;It<pt;++It){let Un=It*Q-ot,Qt=b*le+w*$e+k*It,bs=E*($-1-Tt)+R*(T-1-Un)+P*ye;for(let pn=0;pn<ae;++pn){let Gn=ye*ae+pn,vs=A[Qt+Gn],ws=S[bs+pn];At+=vs*ws}}}m[g*le+y*we+x*Ge+ye]=At}}return n.makeTensorInfo(f.shape,f.dtype,f.values)}var bZ={kernelName:Jm,backendName:"cpu",kernelFunc:xZ};function vZ(e){let{inputs:t,backend:n}=e,{x:s}=t,r=v.sizeFromShape(s.shape),a=n.data.get(s.dataId).values,o=Le([r,r],s.dtype),i=o.values;for(let u=0;u<a.length;u++)i[u*r+u]=a[u];let l=[...s.shape,...s.shape];return n.makeTensorInfo(l,o.dtype,o.values)}var wZ={kernelName:Qm,backendName:"cpu",kernelFunc:vZ},kZ={kernelName:Wp,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:s,filter:r}=e,{strides:a,pad:o,dilations:i}=n,l=t,u=l.data.get(s.dataId).values,c=s.shape.length,p=l.data.get(r.dataId).values,d=r.shape.length,{batchSize:h,inHeight:f,inWidth:m,inChannels:g,outHeight:y,outWidth:x,padInfo:A,strideHeight:b,strideWidth:w,filterHeight:k,filterWidth:S,dilationHeight:E,dilationWidth:R,outShape:P}=C.computeDilation2DInfo(s.shape,r.shape,a,o,"NHWC",i),_=v.sizeFromShape(P),$=P.length,T=v.getArrayFromDType(s.dtype,_);for(let G=0;G<h;++G)for(let q=0;q<y;++q){let z=q*b-A.top;for(let Z=0;Z<x;++Z){let B=Z*w-A.left;for(let ee=0;ee<g;++ee){let Q=Number.MIN_SAFE_INTEGER;for(let Y=0;Y<k;++Y){let ae=z+Y*E;if(ae>=0&&ae<f)for(let le=0;le<S;++le){let ye=B+le*R;if(ye>=0&&ye<m){let we=v.locToIndex([G,ae,ye,ee],c,v.computeStrides(s.shape)),Re=v.locToIndex([Y,le,ee],d,v.computeStrides(r.shape)),_e=u[we]+p[Re];_e>Q&&(Q=_e)}}}let oe=v.locToIndex([G,q,Z,ee],$,v.computeStrides(P));T[oe]=Q}}}return{dataId:l.write(v.toTypedArray(T,s.dtype),P,s.dtype),shape:P,dtype:s.dtype}}},IZ={kernelName:pm,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:s,filter:r,dy:a}=e,{strides:o,pad:i,dilations:l}=n,u=t,c=v.toNestedArray(s.shape,u.data.get(s.dataId).values),p=v.toNestedArray(r.shape,u.data.get(r.dataId).values),{batchSize:d,inHeight:h,inWidth:f,inChannels:m,outHeight:g,outWidth:y,padInfo:x,strideHeight:A,strideWidth:b,filterHeight:w,filterWidth:k,dilationHeight:S,dilationWidth:E,outShape:R}=C.computeDilation2DInfo(s.shape,r.shape,o,i,"NHWC",l);v.assert(a.rank===R.length,()=>`Error in ${pm}, dy must have the same rank as output ${R.length}, but got ${a.rank}`);let P=v.toNestedArray(R,u.data.get(a.dataId).values),_=v.makeZerosNestedTypedArray(r.shape,r.dtype);for(let T=0;T<d;++T)for(let F=0;F<g;++F){let G=F*A-x.top;for(let q=0;q<y;++q){let z=q*b-x.left;for(let Z=0;Z<m;++Z){let B=Number.MIN_SAFE_INTEGER,ee=0,Q=0;for(let oe=0;oe<w;++oe){let Y=G+oe*S;if(Y>=0&&Y<h)for(let ae=0;ae<k;++ae){let le=z+ae*E;if(le>=0&&le<f){let ye=c[T][Y][le][Z]+p[oe][ae][Z];ye>B&&(B=ye,ee=oe,Q=ae)}}}_[ee][Q][Z]+=P[T][F][q][Z]}}}return{dataId:u.write(v.toTypedArray(_,s.dtype),r.shape,r.dtype),shape:r.shape,dtype:r.dtype}}},SZ={kernelName:dm,backendName:"cpu",kernelFunc:({inputs:e,backend:t,attrs:n})=>{let{x:s,filter:r,dy:a}=e,{strides:o,pad:i,dilations:l}=n,u=t,c=v.toNestedArray(s.shape,u.data.get(s.dataId).values),p=v.toNestedArray(r.shape,u.data.get(r.dataId).values),{batchSize:d,inHeight:h,inWidth:f,inChannels:m,outHeight:g,outWidth:y,padInfo:x,strideHeight:A,strideWidth:b,filterHeight:w,filterWidth:k,dilationHeight:S,dilationWidth:E,outShape:R}=C.computeDilation2DInfo(s.shape,r.shape,o,i,"NHWC",l);v.assert(a.rank===R.length,()=>`Error in ${dm}, dy must have the same rank as output ${R.length}, but got ${a.rank}`);let P=v.toNestedArray(R,u.data.get(a.dataId).values),_=v.makeZerosNestedTypedArray(s.shape,s.dtype);for(let T=0;T<d;++T)for(let F=0;F<g;++F){let G=F*A-x.top;for(let q=0;q<y;++q){let z=q*b-x.left;for(let Z=0;Z<m;++Z){let B=Number.MIN_SAFE_INTEGER,ee=G<0?0:G,Q=z<0?0:z;for(let oe=0;oe<w;++oe){let Y=G+oe*S;if(Y>=0&&Y<h)for(let ae=0;ae<k;++ae){let le=z+ae*E;if(le>=0&&le<f){let ye=c[T][Y][le][Z]+p[oe][ae][Z];ye>B&&(B=ye,ee=Y,Q=le)}}}_[T][ee][Q][Z]+=P[T][F][q][Z]}}}return{dataId:u.write(v.toTypedArray(_,s.dtype),s.shape,s.dtype),shape:s.shape,dtype:s.dtype}}};function $h(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;Ce(r,"sum");let i;r.dtype==="bool"?i=oo({inputs:{x:r},backend:n,attrs:{dtype:"int32"}}):i=Kr({inputs:{x:r},backend:n});let l=i.shape.length,u=v.parseAxisParam(a,i.shape),c=C.getAxesPermutation(u,l),p=u,d=i;c!=null&&(d=gs({inputs:{x:i},backend:n,attrs:{perm:c}}),p=C.getInnerMostAxes(p.length,l)),C.assertAxesAreInnerMostDims("sum",p,d.shape.length);let[h,f]=C.computeOutAndReduceShapes(d.shape,p),m=C.upcastType(d.dtype,"int32"),g=Em(n,h,m),y=v.sizeFromShape(f),x=n.data.get(g.dataId).values,A=n.data.get(d.dataId).values;for(let b=0;b<x.length;++b){let w=b*y,k=0;for(let S=0;S<y;++S)k+=A[w+S];x[b]=k}if(o){let b=C.expandShapeToKeepDim(g.shape,u),w=g;g=Rt({inputs:{x:g},backend:n,attrs:{shape:b}}),n.disposeIntermediateTensorInfo(w)}return n.disposeIntermediateTensorInfo(i),c!=null&&n.disposeIntermediateTensorInfo(d),g}var CZ={kernelName:Qo,backendName:"cpu",kernelFunc:$h};function TZ(e){let{inputs:t,backend:n,attrs:s}=e,{equation:r}=s,a=t,{allDims:o,summedDims:i,idDims:l}=C.decodeEinsumEquation(r,a.length);C.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=C.getEinsumComputePath(i,l),p=c.length,d=null,h=o.length,f=[];for(let m=0;m<p;++m){for(let g of c[m]){let{permutationIndices:y,expandDims:x}=C.getEinsumPermutation(h,l[g]),A;C.isIdentityPermutation(y)?A=a[g]:(A=gs({inputs:{x:a[g]},backend:n,attrs:{perm:y}}),f.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=Rt({inputs:{x:A},backend:n,attrs:{shape:b}}),f.push(A)),d===null?d=A:(d=y2({inputs:{a:A,b:d},backend:n}),f.push(d))}m<p-1&&(u[m]>=0&&(d=$h({inputs:{x:d},backend:n,attrs:{axis:u[m]-(o.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&n.disposeIntermediateTensorInfo(m);return d}var NZ={kernelName:Vp,backendName:"cpu",kernelFunc:TZ};function EZ(e){let{inputs:t,backend:n}=e,{dy:s,y:r}=t;Ce([s,r],"eluGrad");let a=new Float32Array(v.sizeFromShape(r.shape)),o=n.data.get(r.dataId).values,i=n.data.get(s.dataId).values;for(let l=0;l<o.length;++l){let u=o[l];u>=1?a[l]=i[l]:a[l]=i[l]*(u+1)}return n.makeTensorInfo(r.shape,"float32",a)}var RZ={kernelName:e0,backendName:"cpu",kernelFunc:EZ},_Z=C.ERF_P,DZ=C.ERF_A1,$Z=C.ERF_A2,PZ=C.ERF_A3,FZ=C.ERF_A4,OZ=C.ERF_A5,MZ=bt(vc,e=>{let t=Math.sign(e),n=Math.abs(e),s=1/(1+_Z*n);return t*(1-((((OZ*s+FZ)*s+PZ)*s+$Z)*s+DZ)*s*Math.exp(-n*n))}),zZ={kernelName:vc,backendName:"cpu",kernelFunc:MZ};function Dm(e){let{inputs:t,backend:n,attrs:s}=e,{input:r}=t,{dim:a}=s,o=r.shape.length,i=r.shape.slice(),l=a;return a<0&&(v.assert(-(o+1)<=a,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+a+1),i.splice(l,0,1),Rt({inputs:{x:r},backend:n,attrs:{shape:i}})}var LZ={kernelName:hl,backendName:"cpu",kernelFunc:Dm},BZ=un((e,t)=>e/t),zx=kn(ko,BZ),Q3={kernelName:ko,backendName:"cpu",kernelFunc:zx};function sS(e,t,n){let s=e.shape,r=s[0],a=s[1],o=n.data.get(e.dataId),i=o.complexTensorInfos.real,l=o.complexTensorInfos.imag,u=[r,a],c=v.sizeFromShape(u),p=v.getTypedArrayFromDType("float32",c),d=v.getTypedArrayFromDType("float32",c);for(let g=0;g<r;g++){let y=tl({inputs:{x:i},backend:n,attrs:{begin:[g,0],size:[1,a]}}),x=tl({inputs:{x:l},backend:n,attrs:{begin:[g,0],size:[1,a]}}),A=Cs({inputs:{real:y,imag:x},backend:n}),{real:b,imag:w}=WZ(A,t,n),k=C.mergeRealAndImagArrays(b,w);for(let S=0;S<a;S++){let E=C.getComplexWithIndex(k,S);p[g*a+S]=E.real,d[g*a+S]=E.imag}n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(x),n.disposeIntermediateTensorInfo(A)}let h=n.makeTensorInfo(u,"float32",p),f=n.makeTensorInfo(u,"float32",d),m=Cs({inputs:{real:h,imag:f},backend:n});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),m}function WZ(e,t,n){let s=v.sizeFromShape(e.shape),r=n.data.get(e.dataId),a=n.data.get(r.complexTensorInfos.real.dataId).values,o=n.data.get(r.complexTensorInfos.imag.dataId).values;if(VZ(s)){let i=ey(a,o,s,t,n),l=[e.shape[0],e.shape[1]];if(t){let u=n.makeTensorInfo(l,"float32",i.real),c=n.makeTensorInfo(l,"float32",i.imag),p=n.makeTensorInfo([],"float32",v.createScalarValue(s,"float32")),d=Kr({inputs:{x:p},backend:n}),h=Q3.kernelFunc({inputs:{a:u,b:p},backend:n}),f=Q3.kernelFunc({inputs:{a:c,b:d},backend:n}),m=n.data.get(h.dataId).values,g=n.data.get(f.dataId).values;return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),{real:m,imag:g}}return i}else{let i=C.mergeRealAndImagArrays(a,o),l=UZ(i,s,t);return C.splitRealAndImagArrays(l)}}function VZ(e){return(e&e-1)===0}function ey(e,t,n,s,r){if(n===1)return{real:e,imag:t};let a=C.mergeRealAndImagArrays(e,t),o=n/2,i=C.complexWithEvenIndex(a),l=i.real,u=i.imag,c=[l.length],p=r.makeTensorInfo(c,"float32",l),d=r.makeTensorInfo(c,"float32",u),h=Cs({inputs:{real:p,imag:d},backend:r}),f=C.complexWithOddIndex(a),m=f.real,g=f.imag,y=[m.length],x=r.makeTensorInfo(y,"float32",m),A=r.makeTensorInfo(y,"float32",g),b=Cs({inputs:{real:x,imag:A},backend:r}),w=ey(l,u,o,s,r),k=w.real,S=w.imag,E=[k.length],R=r.makeTensorInfo(E,"float32",k),P=r.makeTensorInfo(E,"float32",S),_=Cs({inputs:{real:R,imag:P},backend:r}),$=ey(m,g,o,s,r),T=$.real,F=$.imag,G=[T.length],q=r.makeTensorInfo(G,"float32",T),z=r.makeTensorInfo(G,"float32",F),Z=Cs({inputs:{real:q,imag:z},backend:r}),B=C.exponents(n,s),ee=[B.real.length],Q=r.makeTensorInfo(ee,"float32",B.real),oe=r.makeTensorInfo(ee,"float32",B.imag),Y=Cs({inputs:{real:Q,imag:oe},backend:r}),ae=y2({inputs:{a:Y,b:Z},backend:r}),le=ac({inputs:{a:_,b:ae},backend:r}),ye=Ox({inputs:{a:_,b:ae},backend:r}),we=el({inputs:{input:le},backend:r}),Re=el({inputs:{input:ye},backend:r}),_e=oc({inputs:{input:le},backend:r}),Be=oc({inputs:{input:ye},backend:r}),Ge=ic({inputs:[we,Re],backend:r,attrs:{axis:0}}),ot=ic({inputs:[_e,Be],backend:r,attrs:{axis:0}}),dt=r.data.get(Ge.dataId).values,pt=r.data.get(ot.dataId).values;return r.disposeIntermediateTensorInfo(p),r.disposeIntermediateTensorInfo(d),r.disposeIntermediateTensorInfo(h),r.disposeIntermediateTensorInfo(x),r.disposeIntermediateTensorInfo(A),r.disposeIntermediateTensorInfo(b),r.disposeIntermediateTensorInfo(R),r.disposeIntermediateTensorInfo(P),r.disposeIntermediateTensorInfo(_),r.disposeIntermediateTensorInfo(q),r.disposeIntermediateTensorInfo(z),r.disposeIntermediateTensorInfo(Z),r.disposeIntermediateTensorInfo(Q),r.disposeIntermediateTensorInfo(oe),r.disposeIntermediateTensorInfo(Y),r.disposeIntermediateTensorInfo(ae),r.disposeIntermediateTensorInfo(le),r.disposeIntermediateTensorInfo(ye),r.disposeIntermediateTensorInfo(we),r.disposeIntermediateTensorInfo(_e),r.disposeIntermediateTensorInfo(Re),r.disposeIntermediateTensorInfo(Be),r.disposeIntermediateTensorInfo(Ge),r.disposeIntermediateTensorInfo(ot),{real:dt,imag:pt}}function UZ(e,t,n){let s=new Float32Array(t*2);for(let r=0;r<t;r++){let a=0,o=0;for(let i=0;i<t;i++){let l=C.exponent(r*i,t,n),u=C.getComplexWithIndex(e,i);a+=u.real*l.real-u.imag*l.imag,o+=u.real*l.imag+u.imag*l.real}n&&(a/=t,o/=t),C.assignToTypedArray(s,a,o,r)}return s}function GZ(e){let{inputs:t,backend:n}=e,{input:s}=t,r=v.sizeFromShape(s.shape),a=s.shape[s.shape.length-1],o=r/a,i=Rt({inputs:{x:s},backend:n,attrs:{shape:[o,a]}}),l=sS(i,!1,n),u=Rt({inputs:{x:l},backend:n,attrs:{shape:s.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var HZ={kernelName:t0,backendName:"cpu",kernelFunc:GZ};function Lx(e){let{backend:t,attrs:n}=e,{shape:s,value:r,dtype:a}=n,o=a||v.inferDtype(r),i=v.getArrayFromDType(o,v.sizeFromShape(s));return qZ(i,r,o),t.makeTensorInfo(s,o,i)}var jZ={kernelName:wc,backendName:"cpu",kernelFunc:Lx};function qZ(e,t,n){e.fill(t)}var XZ={kernelName:ml,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,r=n,a=v.getTypedArrayFromDType(s.dtype,v.sizeFromShape(s.shape)),[o,i,l,u]=s.shape,c=r.data.get(s.dataId).values;for(let d=0;d<o;d++){let h=d*l*i*u;for(let f=0;f<i;f++){let m=f*(l*u);for(let g=0;g<l;g++){let y=g*u;for(let x=0;x<u;x++){let A=Math.round(l-g-1),b=h+m+y+x,w=c[b];if(A>=0&&A<l){let k=A*u,S=h+m+k+x;w=c[S]}a[b]=w}}}}return{dataId:r.write(a,s.shape,s.dtype),shape:s.shape,dtype:s.dtype}}},KZ=un((e,t)=>Math.floor(e/t)),ZZ=kn(To,KZ,null,"int32"),YZ={kernelName:To,backendName:"cpu",kernelFunc:ZZ};function JZ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=s,m=tS({inputs:{x:r,filter:a},backend:n,attrs:{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d}});if(o){let g=m;if(c==="NCHW"&&o.shape.length===1&&o.shape[0]!==1){let y=Rt({inputs:{x:o},backend:n,attrs:{shape:[o.shape[0],1,1]}});m=ac({inputs:{a:m,b:y},backend:n}),n.disposeIntermediateTensorInfo(y)}else m=ac({inputs:{a:m,b:o},backend:n});n.disposeIntermediateTensorInfo(g)}if(h){let g=m;if(c==="NCHW"&&h==="prelu"&&i.shape.length===1&&i.shape[0]!==1){let y=Rt({inputs:{x:i},backend:n,attrs:{shape:[i.shape[0],1,1]}});m=_m(n,m,h,y,f),n.disposeIntermediateTensorInfo(y)}else m=_m(n,m,h,i,f);n.disposeIntermediateTensorInfo(g)}return m}var QZ={kernelName:Ja,backendName:"cpu",kernelFunc:JZ};function eY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=s,m=nS({inputs:{x:r,filter:a},backend:n,attrs:{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d}});if(o){let g=m;m=ac({inputs:{a:m,b:o},backend:n}),n.disposeIntermediateTensorInfo(g)}if(h){let g=m;m=_m(n,m,h,i,f),n.disposeIntermediateTensorInfo(g)}return m}var tY={kernelName:Qa,backendName:"cpu",kernelFunc:eY};function nY(e){let{inputs:t,backend:n}=e,{params:s,indices:r}=t,a=v.sizeFromShape(s.shape),o=r.shape,i=o[o.length-1],[l,u,c,p]=C.prepareAndValidate(s,r);if(u===0)return n.makeTensorInfo(l,s.dtype,[]);let d=n.data.get(r.dataId).values,h=n.bufferSync(s),f=wI(d,h,s.dtype,u,i,c,p,s.shape,a);return n.makeTensorInfo(l,s.dtype,f.values)}var sY={kernelName:yl,backendName:"cpu",kernelFunc:nY};function rY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,indices:a}=t,{axis:o,batchDims:i}=s;Ce([r,a],"gatherV2");let l=v.parseAxisParam(o,r.shape)[0],u=n.data.get(a.dataId).values,c=r.shape[l];for(let b=0;b<u.length;++b){let w=u[b];v.assert(w<=c-1&&w>=0,()=>`GatherV2: the index value ${w} is not in [0, ${c-1}]`)}let p=i;i==null&&(p=0);let d=v.sizeFromShape(a.shape),h=C.segment_util.collectGatherOpShapeInfo(r,a,l,p),f=Rt({inputs:{x:r},backend:n,attrs:{shape:[h.batchSize,h.outerSize,h.dimSize,h.sliceSize]}}),m=Rt({inputs:{x:a},backend:n,attrs:{shape:[h.batchSize,d/h.batchSize]}}),g=[h.batchSize,h.outerSize,d/h.batchSize,h.sliceSize],y=n.bufferSync(m),x=n.bufferSync(f),A=kI(x,y,g);return n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),n.makeTensorInfo(h.outputShape,A.dtype,A.values)}var aY={kernelName:gl,backendName:"cpu",kernelFunc:rY};function oY(e){let{inputs:t,backend:n}=e,{input:s}=t,r=v.sizeFromShape(s.shape),a=s.shape[s.shape.length-1],o=r/a,i=Rt({inputs:{x:s},backend:n,attrs:{shape:[o,a]}}),l=sS(i,!0,n),u=Rt({inputs:{x:l},backend:n,attrs:{shape:s.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(l),u}var iY={kernelName:n0,backendName:"cpu",kernelFunc:oY},lY=bt(kc,e=>Number.isFinite(e)?1:0,"bool"),uY={kernelName:kc,backendName:"cpu",kernelFunc:lY},cY=bt(Ic,e=>Math.abs(e)===1/0?1:0,"bool"),dY={kernelName:Ic,backendName:"cpu",kernelFunc:cY},pY=bt(Sc,e=>Number.isNaN(e)?1:0,"bool"),hY={kernelName:Sc,backendName:"cpu",kernelFunc:pY};function fY(e){let{backend:t,attrs:n}=e,{start:s,stop:r,num:a}=n,o=NI(s,r,a);return t.makeTensorInfo([o.length],"float32",o)}var mY={kernelName:s0,backendName:"cpu",kernelFunc:fY},gY=bt(Cc,e=>Math.log1p(e)),yY={kernelName:Cc,backendName:"cpu",kernelFunc:gY},AY=un((e,t)=>e&&t),xY=kn(vl,AY,null,"bool"),bY={kernelName:vl,backendName:"cpu",kernelFunc:xY},vY=bt(wl,e=>e?0:1,"bool"),wY={kernelName:wl,backendName:"cpu",kernelFunc:vY},kY=un((e,t)=>e||t),IY=kn(Tc,kY,null,"bool"),SY={kernelName:Tc,backendName:"cpu",kernelFunc:IY};function CY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{depthRadius:a,bias:o,alpha:i,beta:l}=s;Ce(r,"LRN");let u=r.shape[3],c=u-1,p=n.data.get(r.dataId).values,d=v.sizeFromShape(r.shape),h=new Float32Array(d);function f(m){let g=m%u,y=m-g+Math.max(0,g-a),x=m-g+Math.min(g+a,c),A=0;for(;y<=x;y++){let b=p[y];A+=b*b}return A}for(let m=0;m<d;m++){let g=f(m),y=p[m]*Math.pow(o+i*g,-l);h[m]=y}return n.makeTensorInfo(r.shape,r.dtype,h)}var TY={kernelName:Gp,backendName:"cpu",kernelFunc:CY};function NY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,y:a,dy:o}=t,{depthRadius:i,bias:l,alpha:u,beta:c}=s;Ce(o,"LRNGrad");let p=v.sizeFromShape(o.shape),d=o.shape[3],h=n.data.get(o.dataId).values,f=n.data.get(r.dataId).values,m=n.data.get(a.dataId).values,g=new Float32Array(p),y=p;for(let x=0;x<y;x++){let A=x%d,b=x-A+Math.max(0,A-i),w=x-A+Math.min(d,A+i+1),k=0;for(let S=b;S<w;S++)k+=Math.pow(f[S],2);k=u*k+l;for(let S=b;S<w;S++){let E=-2*u*c*f[S]*m[x]/k;x===S&&(E+=Math.pow(k,-c)),E*=h[x],g[S]+=E}}return n.makeTensorInfo(o.shape,r.dtype,g)}var EY={kernelName:r0,backendName:"cpu",kernelFunc:NY};function rS(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reductionIndices:a,keepDims:o}=s,i=n,l=r.shape,u=l.length,c=v.parseAxisParam(a,l),p=c,d=C.getAxesPermutation(p,u),h=i.data.get(r.dataId).values;if(d!=null){let b=new Array(u);for(let w=0;w<b.length;w++)b[w]=l[d[w]];h=Rx(h,l,r.dtype,d,b),p=C.getInnerMostAxes(p.length,u),l=b}Ce(r,"max"),C.assertAxesAreInnerMostDims("max",p,u);let[f,m]=C.computeOutAndReduceShapes(l,p),g=v.sizeFromShape(m),y=RI(h,g,f,r.dtype),x=i.write(y,f,r.dtype),A=f;return o&&(A=C.expandShapeToKeepDim(f,c)),{dataId:x,shape:A,dtype:r.dtype}}var RY={kernelName:$o,backendName:"cpu",kernelFunc:rS};function _Y(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;Ce(r,"maxPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;v.assert(C.eitherStridesOrDilationsAreOne(o,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=C.computePool2DInfo(r.shape,a,o,u,i,l),p;if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))p=Kr({inputs:{x:r},backend:n});else{let d=n.data.get(r.dataId).values,h=v.computeStrides(r.shape),f=Mx(d,r.shape,r.dtype,h,c,"max");p=n.makeTensorInfo(c.outShape,r.dtype,f.values)}return p}var DY={kernelName:Fo,backendName:"cpu",kernelFunc:_Y};function $Y(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l,dataFormat:u}=s;Ce(r,"maxPool3d");let c=C.computePool3DInfo(r.shape,a,o,1,i,l,u),p=n.data.get(r.dataId).values,d=eS(p,r.shape,r.dtype,v.computeStrides(r.shape),c,"max");return n.makeTensorInfo(d.shape,"float32",d.values)}var PY={kernelName:Hp,backendName:"cpu",kernelFunc:$Y};function FY(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=s;Ce([r,a],"maxPool3DGrad");let c=C.computePool3DInfo(a.shape,o,i,1,l,u),p=n.bufferSync(a),d=wK(p,c),h=c.strideDepth,f=c.strideHeight,m=c.strideWidth,g=c.dilationDepth,y=c.dilationHeight,x=c.dilationWidth,A=c.effectiveFilterDepth,b=c.effectiveFilterHeight,w=c.effectiveFilterWidth,k=A-1-c.padInfo.front,S=w-1-c.padInfo.left,E=b-1-c.padInfo.top,R=Le(a.shape,"float32"),P=n.bufferSync(r);for(let _=0;_<c.batchSize;++_)for(let $=0;$<c.inChannels;++$)for(let T=0;T<c.inDepth;++T)for(let F=0;F<c.inHeight;++F)for(let G=0;G<c.inWidth;++G){let q=T-k,z=F-E,Z=G-S,B=0;for(let ee=0;ee<A;ee+=g){let Q=(q+ee)/h;if(!(Q<0||Q>=c.outDepth||Math.floor(Q)!==Q))for(let oe=0;oe<b;oe+=y){let Y=(z+oe)/f;if(!(Y<0||Y>=c.outHeight||Math.floor(Y)!==Y))for(let ae=0;ae<w;ae+=x){let le=(Z+ae)/m;if(le<0||le>=c.outWidth||Math.floor(le)!==le)continue;let ye=A*b*w-1-d.get(_,Q,Y,le,$),we=ee*b*w+oe*w+ae,Re=ye===we?1:0;if(Re===0)continue;B+=P.get(_,Q,Y,le,$)*Re}}}R.set(B,_,T,F,G,$)}return n.makeTensorInfo(R.shape,R.dtype,R.values)}var OY={kernelName:o0,backendName:"cpu",kernelFunc:FY};function MY(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a,output:o}=t,i=a;Ce([a,o],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:p}=s,d=C.computePool2DInfo(i.shape,l,u,1,c,p),h=n.data.get(i.dataId).values,f=Le(d.outShape,i.dtype,QI(h,i.shape,i.dtype,d).values),m=d.strideHeight,g=d.strideWidth,y=d.dilationHeight,x=d.dilationWidth,A=d.effectiveFilterHeight,b=d.effectiveFilterWidth,w=b-1-d.padInfo.left,k=A-1-d.padInfo.top,S=Le(i.shape,"float32"),E=n.data.get(r.dataId).values,R=Le(r.shape,"float32",E);for(let P=0;P<d.batchSize;++P)for(let _=0;_<d.inChannels;++_)for(let $=0;$<d.inHeight;++$)for(let T=0;T<d.inWidth;++T){let F=$-k,G=T-w,q=0;for(let z=0;z<A;z+=y){let Z=(F+z)/m;if(!(Z<0||Z>=d.outHeight||Math.floor(Z)!==Z))for(let B=0;B<b;B+=x){let ee=(G+B)/g;if(ee<0||ee>=d.outWidth||Math.floor(ee)!==ee)continue;let Q=A*b-1-f.get(P,Z,ee,_),oe=z*b+B,Y=Q===oe?1:0;if(Y===0)continue;q+=R.get(P,Z,ee,_)*Y}}S.set(q,P,$,T,_)}return n.makeTensorInfo(S.shape,S.dtype,S.values)}var zY={kernelName:a0,backendName:"cpu",kernelFunc:MY};function LY(e,t,n,s,r){let a=v.computeStrides(t),o=Mx(e,t,n,a,r,"max"),i=QI(e,t,n,r,!0,s);return[o.values,i.values]}var BY={kernelName:i0,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{filterSize:r,strides:a,pad:o,includeBatchInIndex:i}=t,l=n;Ce(s,"MaxPoolWithArgmax");let u=l.data.get(s.dataId).values,c=C.computePool2DInfo(s.shape,r,a,[1,1],o),[p,d]=LY(u,s.shape,s.dtype,i,c),h=l.write(p,c.outShape,s.dtype),f=l.write(d,c.outShape,s.dtype);return[{dataId:h,shape:c.outShape,dtype:s.dtype},{dataId:f,shape:c.outShape,dtype:"int32"}]}};function WY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=v.parseAxisParam(a,r.shape),u=C.computeOutAndReduceShapes(r.shape,i)[1],c=v.sizeFromShape(u),p=[],d=n.makeTensorInfo([],"float32",new Float32Array([c]));p.push(d);let h=oo({inputs:{x:r},backend:n,attrs:{dtype:"float32"}});p.push(h);let f=zx({inputs:{a:h,b:d},backend:n});p.push(f);let m=$h({inputs:{x:f},backend:n,attrs:{axis:a,keepDims:o}});return p.forEach(g=>n.disposeIntermediateTensorInfo(g)),m}var VY={kernelName:Oo,backendName:"cpu",kernelFunc:WY};function UY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;Ce(r,"min");let i=v.parseAxisParam(a,r.shape),l=i,u=C.getAxesPermutation(l,r.shape.length),c=r;u!=null&&(c=gs({inputs:{x:r},backend:n,attrs:{perm:u}}),l=C.getInnerMostAxes(l.length,r.shape.length)),C.assertAxesAreInnerMostDims("min",l,c.shape.length);let[p,d]=C.computeOutAndReduceShapes(c.shape,l),h=v.sizeFromShape(d),f=v.makeZerosTypedArray(v.sizeFromShape(p),c.dtype),m=n.data.get(c.dataId).values;for(let y=0;y<f.length;++y){let x=y*h,A=m[x];for(let b=0;b<h;++b){let w=m[x+b];(Number.isNaN(w)||w<A)&&(A=w)}f[y]=A}u!=null&&n.disposeIntermediateTensorInfo(c);let g=n.makeTensorInfo(p,c.dtype,f);if(o){let y=C.expandShapeToKeepDim(p,i),x=Rt({inputs:{x:g},backend:n,attrs:{shape:y}});return n.disposeIntermediateTensorInfo(g),x}return g}var GY={kernelName:Mo,backendName:"cpu",kernelFunc:UY};function HY(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{paddings:a,mode:o}=s;Ce(r,"mirrorPad");let i=a.map((A,b)=>A[0]+r.shape[b]+A[1]),l=a.map(A=>A[0]),u=a.map((A,b)=>A[0]+r.shape[b]),c=o==="reflect"?0:1,p=n.data.get(r.dataId).values,d=r.shape.length,h=v.computeStrides(r.shape),f=v.sizeFromShape(i),m=i.length,g=v.computeStrides(i),y=v.getTypedArrayFromDType(r.dtype,f);for(let A=0;A<f;A++){let b=v.indexToLoc(A,m,g);for(let k=0;k<m;k++)b[k]<l[k]?b[k]=l[k]*2-b[k]-c:b[k]>=u[k]&&(b[k]=(u[k]-1)*2-b[k]+c);b=b.map((k,S)=>k-l[S]);let w=v.locToIndex(b,d,h);y[A]=p[w]}return{dataId:n.write(y,i,r.dtype),shape:i,dtype:r.dtype}}var jY={kernelName:Lo,backendName:"cpu",kernelFunc:HY},qY=un((e,t)=>{let n=e%t;return e<0&&t<0||e>=0&&t>=0?n:(n+t)%t}),XY=kn(Nc,qY),KY={kernelName:Nc,backendName:"cpu",kernelFunc:XY},ZY=lo(Bm());function aS(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{dim:a}=s,o=r.shape.length,i=a;if(i===-1&&(i=o-1),i!==o-1)throw Error(`Softmax along a non-last dimension is not yet supported. Logits was rank ${o} and dim was ${i}`);let l=v.parseAxisParam([i],r.shape),u=rS({inputs:{x:r},backend:n,attrs:{reductionIndices:l,keepDims:!1}}),c=C.expandShapeToKeepDim(u.shape,l),p=Rt({inputs:{x:u},backend:n,attrs:{shape:c}}),d=Ox({inputs:{a:r,b:p},backend:n}),h=xI({inputs:{x:d},backend:n}),f=$h({inputs:{x:h},backend:n,attrs:{axis:l,keepDims:!1}}),m=Rt({inputs:{x:f},backend:n,attrs:{shape:c}}),g=zx({inputs:{a:h,b:m},backend:n});return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(m),g}var YY={kernelName:ei,backendName:"cpu",kernelFunc:aS};function JY(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{numSamples:a,seed:o,normalized:i}=s;Ce(r,"multinomial");let l=i?r:aS({inputs:{logits:r},backend:n,attrs:{dim:-1}}),u=l.shape[0],c=l.shape[1],p=n.data.get(l.dataId).values,d=[u,a],h=v.makeZerosTypedArray(v.sizeFromShape(d),"int32");for(let f=0;f<u;++f){let m=f*c,g=new Float32Array(c-1);g[0]=p[m];for(let A=1;A<g.length;++A)g[A]=g[A-1]+p[m+A];let y=ZY.alea(o.toString()),x=f*a;for(let A=0;A<a;++A){let b=y();h[x+A]=g.length;for(let w=0;w<g.length;w++)if(b<g[w]){h[x+A]=w;break}}}return i||n.disposeIntermediateTensorInfo(l),n.makeTensorInfo(d,"int32",h)}var QY={kernelName:l0,backendName:"cpu",kernelFunc:JY},eJ=dr.nonMaxSuppressionV3Impl;function tJ(e){let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l}=s;Ce(r,"NonMaxSuppression");let u=n.data.get(r.dataId).values,c=n.data.get(a.dataId).values,{selectedIndices:p}=eJ(u,c,o,i,l);return n.makeTensorInfo([p.length],"int32",new Int32Array(p))}var nJ={kernelName:Sl,backendName:"cpu",kernelFunc:tJ},sJ=dr.nonMaxSuppressionV4Impl;function rJ(e){let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,padToMaxOutputSize:u}=s;Ce(r,"NonMaxSuppressionPadded");let c=n.data.get(r.dataId).values,p=n.data.get(a.dataId).values,{selectedIndices:d,validOutputs:h}=sJ(c,p,o,i,l,u);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([h]))]}var aJ={kernelName:Ec,backendName:"cpu",kernelFunc:rJ},oJ=dr.nonMaxSuppressionV5Impl;function iJ(e){let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=s;Ce(r,"NonMaxSuppressionWithScore");let c=n.data.get(r.dataId).values,p=n.data.get(a.dataId).values,d=o,h=i,f=l,m=u,{selectedIndices:g,selectedScores:y}=oJ(c,p,d,h,f,m);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var lJ={kernelName:Cl,backendName:"cpu",kernelFunc:iJ};function uJ(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r}=t,{depth:a,onValue:o,offValue:i}=s;Ce(r,"oneHot");let l=v.sizeFromShape(r.shape),u=new Float32Array(l*a);u.fill(i);let c=n.data.get(r.dataId).values;for(let p=0;p<l;++p)c[p]>=0&&c[p]<a&&(u[p*a+c[p]]=o);return n.makeTensorInfo([...r.shape,a],"int32",u)}var cJ={kernelName:Nl,backendName:"cpu",kernelFunc:uJ};function $m(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="string")throw new Error("zerosLike is not supported for string tensors");if(s.dtype==="complex64"){let r=el({inputs:{input:s},backend:n}),a=$m({inputs:{x:r},backend:n}),o=oc({inputs:{input:s},backend:n}),i=$m({inputs:{x:o},backend:n}),l=Cs({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return Lx({backend:n,attrs:{shape:s.shape,value:0,dtype:s.dtype}})}var dJ={kernelName:Gl,backendName:"cpu",kernelFunc:$m};function oS(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="string")throw new Error("onesLike is not supported for string tensors");if(s.dtype==="complex64"){let r=el({inputs:{input:s},backend:n}),a=oS({inputs:{x:r},backend:n}),o=oc({inputs:{input:s},backend:n}),i=$m({inputs:{x:o},backend:n}),l=Cs({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return Lx({backend:n,attrs:{shape:s.shape,value:1,dtype:s.dtype}})}var pJ={kernelName:Tl,backendName:"cpu",kernelFunc:oS};function iS(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return Dm({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let p=Dm({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(p),p}),u=ic({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var hJ={kernelName:El,backendName:"cpu",kernelFunc:iS};function fJ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{paddings:a,constantValue:o}=s;Ce(r,"pad");let i=a.map((x,A)=>x[0]+r.shape[A]+x[1]),l=a.map(x=>x[0]),u=n.data.get(r.dataId).values,c=v.sizeFromShape(r.shape),p=r.shape.length,d=v.computeStrides(r.shape),h=v.sizeFromShape(i),f=i.length,m=v.computeStrides(i),g=v.getTypedArrayFromDType(r.dtype,h);o!==0&&g.fill(o);for(let x=0;x<c;x++){let b=v.indexToLoc(x,p,d).map((k,S)=>k+l[S]),w=v.locToIndex(b,f,m);g[w]=u[x]}return{dataId:n.write(g,i,r.dtype),shape:i,dtype:r.dtype}}var lS={kernelName:Wo,backendName:"cpu",kernelFunc:fJ},mJ=un((e,t)=>Math.pow(e,t)),gJ=kn(Vo,mJ),yJ={kernelName:Vo,backendName:"cpu",kernelFunc:gJ};function AJ(e){let{backend:t,attrs:n}=e,{start:s,stop:r,dtype:a,step:o}=n,i=_x(s,r,o,a);return t.makeTensorInfo([i.length],a,i)}var xJ={kernelName:Rc,backendName:"cpu",kernelFunc:AJ},bJ=bt(_c,e=>1/e),vJ={kernelName:_c,backendName:"cpu",kernelFunc:bJ};function wJ(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s;Ce(r,"resizeBilinear");let l=v.computeStrides(r.shape),[u,c]=i,[p,d,h,f]=r.shape,m=n.data.get(r.dataId).values,g=new Float32Array(v.sizeFromShape([p,u,c,f])),y=[a&&u>1?d-1:d,a&&c>1?h-1:h],x=[a&&u>1?u-1:u,a&&c>1?c-1:c],A=0,b=y[0]/x[0],w=y[1]/x[1];for(let k=0;k<p;k++)for(let S=0;S<u;S++){let E;o?E=b*(S+.5)-.5:E=b*S;let R=Math.max(0,Math.floor(E)),P=E-R,_=Math.min(d-1,Math.ceil(E)),$=k*l[0]+R*l[1],T=k*l[0]+_*l[1];for(let F=0;F<c;F++){let G;o?G=w*(F+.5)-.5:G=w*F;let q=Math.max(0,Math.floor(G)),z=G-q,Z=Math.min(h-1,Math.ceil(G)),B=$+q*l[2],ee=T+q*l[2],Q=$+Z*l[2],oe=T+Z*l[2];for(let Y=0;Y<f;Y++){let ae=m[B+Y],le=m[ee+Y],ye=m[Q+Y],we=m[oe+Y],Re=ae+(ye-ae)*z,_e=le+(we-le)*z,Be=Re+(_e-Re)*P;g[A++]=Be}}}return n.makeTensorInfo([p,u,c,f],"float32",g)}var kJ={kernelName:qo,backendName:"cpu",kernelFunc:wJ};function IJ(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s;Ce([a,r],"resizeBilinearGrad");let i=v.computeStrides(r.shape),[l,u,c,p]=r.shape,[,d,h]=a.shape,f=new Float32Array(l*u*c*p),m=[o&&d>1?u-1:u,o&&h>1?c-1:c],g=[o&&d>1?d-1:d,o&&h>1?h-1:h],y=m[0]/g[0],x=m[1]/g[1],A=n.data.get(a.dataId).values,b=0;for(let w=0;w<l;w++){let k=w*i[0];for(let S=0;S<d;S++){let E=S*y,R=Math.floor(E),P=Math.min(Math.ceil(E),u-1),_=k+R*i[1],$=k+P*i[1],T=E-R,F=1-T;for(let G=0;G<h;G++){let q=G*x,z=Math.floor(q),Z=Math.min(Math.ceil(q),c-1),B=q-z,ee=1-B,Q=_+z*i[2],oe=_+Z*i[2],Y=$+z*i[2],ae=$+Z*i[2],le=F*ee,ye=F*B,we=T*ee,Re=T*B;for(let _e=0;_e<p;_e++){let Be=A[b++];f[Q+_e]+=Be*le,f[oe+_e]+=Be*ye,f[Y+_e]+=Be*we,f[ae+_e]+=Be*Re}}}}return n.makeTensorInfo([l,c,u,p],"float32",f)}var SJ={kernelName:c0,backendName:"cpu",kernelFunc:IJ};function CJ(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s;Ce(r,"resizeNearestNeighbor");let l=v.computeStrides(r.shape),[u,c]=i,[p,d,h,f]=r.shape,m=n.data.get(r.dataId).values,g=new Float32Array(p*u*c*f),y=[a&&u>1?d-1:d,a&&c>1?h-1:h],x=[a&&u>1?u-1:u,a&&c>1?c-1:c],A=y[0]/x[0],b=y[1]/x[1],w=0;for(let k=0;k<p;k++){let S=k*l[0];for(let E=0;E<u;E++){let R=o?A*(E+.5):A*E,P=Math.min(d-1,a?Math.round(R):Math.floor(R));o&&(P=Math.max(0,P));let _=S+P*l[1];for(let $=0;$<c;$++){let T=o?b*($+.5):b*$,F=Math.min(h-1,a?Math.round(T):Math.floor(T));o&&(F=Math.max(0,F));let G=_+F*l[2];for(let q=0;q<f;q++){let z=m[G+q];g[w++]=z}}}}return n.makeTensorInfo([p,u,c,f],r.dtype,g)}var TJ={kernelName:jo,backendName:"cpu",kernelFunc:CJ};function NJ(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s;Ce([a,r],"resizeNearestNeighborGrad");let i=v.computeStrides(r.shape),l=v.computeStrides(a.shape),[u,c,p,d]=r.shape,[,h,f]=a.shape,m=new Float32Array(u*c*p*d),g=n.data.get(a.dataId).values,y=[o&&h>1?c-1:c,o&&f>1?p-1:p],x=[o&&h>1?h-1:h,o&&f>1?f-1:f],A=y[0]/x[0],b=y[1]/x[1],w=1/A,k=1/b,S=Math.ceil(w)*2+2,E=Math.ceil(k)*2+2;for(let R=0;R<u;R++){let P=R*i[0];for(let _=0;_<c;_++){let $=P+_*i[1],T=Math.floor(_*w),F=Math.floor(T-S/2);for(let G=0;G<p;G++){let q=$+G*i[2],z=Math.floor(G*k),Z=Math.floor(z-E/2);for(let B=0;B<d;B++){let ee=0;for(let Q=0;Q<S;Q++){let oe=Q+F;if(oe<0||oe>=h)continue;let Y=P+oe*l[1],ae=oe*A,le=Math.min(c-1,o?Math.round(ae):Math.floor(ae));if(_===le)for(let ye=0;ye<E;ye++){let we=ye+Z;if(we<0||we>=f)continue;let Re=Y+we*l[2],_e=we*b,Be=Math.min(p-1,o?Math.round(_e):Math.floor(_e));G===Be&&(ee+=g[Re+B])}}m[q+B]=ee}}}}return n.makeTensorInfo(r.shape,r.dtype,m)}var EJ={kernelName:u0,backendName:"cpu",kernelFunc:NJ};function RJ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dims:a}=s;Ce(r,"reverse");let o=r.shape.length,i=v.parseAxisParam(a,r.shape);if(o===0)return Kr({inputs:{x:r},backend:n});let l=new fn(r.shape,r.dtype),u=n.bufferSync(r);for(let c=0;c<l.size;c++){let p=l.indexToLoc(c),d=p.slice();i.forEach(h=>d[h]=r.shape[h]-1-d[h]),l.set(u.get(...d),...p)}return n.makeTensorInfo(l.shape,l.dtype,l.values)}var _J={kernelName:_l,backendName:"cpu",kernelFunc:RJ},DJ={kernelName:Hl,backendName:"cpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,{radians:r,fillValue:a,center:o}=t,i=n,l=v.getTypedArrayFromDType(s.dtype,v.sizeFromShape(s.shape)),[u,c,p,d]=s.shape,[h,f]=C.getImageCenter(o,c,p),m=255,g=Math.sin(r),y=Math.cos(r),x=i.data.get(s.dataId).values;for(let b=0;b<u;b++){let w=b*p*c*d;for(let k=0;k<c;k++){let S=k*(p*d);for(let E=0;E<p;E++){let R=E*d;for(let P=0;P<d;P++){let _=[u,k,E,P],$=_[2],T=_[1],F=($-h)*y-(T-f)*g,G=($-h)*g+(T-f)*y;F=Math.round(F+h),G=Math.round(G+f);let q=a;if(typeof a!="number"&&(P===3?q=m:q=a[P]),F>=0&&F<p&&G>=0&&G<c){let Z=G*(p*d),B=F*d,ee=w+Z+B+P;q=x[ee]}let z=w+S+R+P;l[z]=q}}}}return{dataId:i.write(l,s.shape,s.dtype),shape:s.shape,dtype:s.dtype}}},$J=bt(Dl,e=>{let t=Math.floor(e);return e-t<.5?Math.floor(e):e-t>.5?Math.ceil(e):t%2===0?t:t+1}),PJ={kernelName:Dl,backendName:"cpu",kernelFunc:$J};function FJ(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r,updates:a}=t,{shape:o}=s,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:p}=C.calculateShapes(a,r,o),d=!0,h=n.bufferSync(r),f=n.bufferSync(a),m=Lu(h,f,o,p,u,l,i,c,0,d);return n.makeTensorInfo(o,m.dtype,m.values)}var OJ={kernelName:$l,backendName:"cpu",kernelFunc:FJ};function MJ(e,t){let n=0,s=e.length,r=0;for(;n<s;)r=Math.floor((n+s)/2),e[r]<t?n=r+1:s=r;return s}function zJ(e,t){let n=0,s=e.length,r=0;for(;n<s;)r=Math.floor((n+s)/2),e[r]<=t?n=r+1:s=r;return s}function LJ(e,t,n,s,r,a){let o=v.getArrayFromDType("int32",n*r);for(let i=0;i<n;++i){let l=e.slice(i*s,(i+1)*s),u=i*r;for(let c=0;c<r;++c)o[u+c]=a==="left"?MJ(l,t[c+u]):zJ(l,t[c+u])}return o}function BJ(e){let{inputs:t,backend:n,attrs:s}=e,{sortedSequence:r,values:a}=t,{side:o}=s,i=n.data.get(r.dataId).values,l=n.data.get(a.dataId).values,u=LJ(i,l,r.shape[0],r.shape[1],a.shape[1],o);return n.makeTensorInfo(a.shape,"int32",u)}var WJ={kernelName:d0,backendName:"cpu",kernelFunc:BJ};function VJ(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t;Ce([s,r,a],"select");let o=s.shape.length,i=n.data.get(s.dataId).values,l=n.data.get(r.dataId).values,u=n.data.get(a.dataId).values,c=On(r.dtype,a.dtype),p=v.makeZerosTypedArray(v.sizeFromShape(r.shape),c),d=0,h=o===0||o>1||r.shape.length===1?1:v.sizeFromShape(r.shape.slice(1));for(let f=0;f<i.length;f++)for(let m=0;m<h;m++)i[f]===1?p[d++]=l[f]:p[d++]=u[f];return n.makeTensorInfo(r.shape,c,p)}var UJ={kernelName:Pl,backendName:"cpu",kernelFunc:VJ},GJ=C.SELU_SCALEALPHA,HJ=C.SELU_SCALE,jJ=bt(Dc,e=>e>=0?HJ*e:GJ*(Math.exp(e)-1)),qJ={kernelName:Dc,backendName:"cpu",kernelFunc:jJ},XJ=bt($c,e=>e<0?-1:e>0?1:0),KJ={kernelName:$c,backendName:"cpu",kernelFunc:XJ},ZJ=bt(Zo,e=>Math.sin(e)),YJ={kernelName:Zo,backendName:"cpu",kernelFunc:ZJ},JJ=bt(Ol,e=>Math.sinh(e)),QJ={kernelName:Ol,backendName:"cpu",kernelFunc:JJ},eQ=11920928955078125e-23,u7=Math.log(eQ)+2,tQ=bt(Pc,e=>{let t=e>-u7,n=e<u7,s=Math.exp(e),r;return n?r=s:t?r=e:r=Math.log(1+s),r}),nQ={kernelName:Pc,backendName:"cpu",kernelFunc:tQ};function sQ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,paddings:o}=s;Ce([r],"spaceToBatchND");let i=v.sizeFromShape(a),l=[[0,0]];l.push(...o);for(let k=1+a.length;k<r.shape.length;++k)l.push([0,0]);let u=lS.kernelFunc({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),c=C.getReshaped(u.shape,a,i,!1),p=C.getPermuted(c.length,a.length,!1),d=C.getReshapedPermuted(u.shape,a,i,!1),m=Rt({inputs:{x:u},backend:n,attrs:{shape:c}}),x=gs({inputs:{x:m},backend:n,attrs:{perm:p}}),w=Rt({inputs:{x},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(x),w}var rQ={kernelName:Ml,backendName:"cpu",kernelFunc:sQ};function aQ(e){let{inputs:t,backend:n}=e,{indices:s,values:r,denseShape:a,defaultValue:o}=t;if(a.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
         ${a.shape}`);if(s.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
         ${s.shape}`);if(r.shape.length!==1)throw new Error(`Values must be a vector, saw:
         ${r.shape}`);if(o.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
-        ${o.shape}`);let i=n.data.get(s.dataId).values,l=n.data.get(r.dataId).values,u=n.data.get(a.dataId).values,c=n.data.get(o.dataId).values[0],[p,d,h,f,m]=zI(i,s.shape,s.dtype,l,r.dtype,u,c);return[n.makeTensorInfo(d,s.dtype,p),n.makeTensorInfo([d[0]],r.dtype,h),n.makeTensorInfo([f.length],"bool",new Uint8Array(f.map(g=>Number(g)))),n.makeTensorInfo([m.length],s.dtype,new Int32Array(m))]}var oQ={kernelName:Xp,backendName:"cpu",kernelFunc:aQ};function iQ(e){let{inputs:t,backend:n}=e,{inputIndices:s,inputShape:r,newShape:a}=t;if(s.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape
+        ${o.shape}`);let i=n.data.get(s.dataId).values,l=n.data.get(r.dataId).values,u=n.data.get(a.dataId).values,c=n.data.get(o.dataId).values[0],[p,d,h,f,m]=zI(i,s.shape,s.dtype,l,r.dtype,u,c);return[n.makeTensorInfo(d,s.dtype,p),n.makeTensorInfo([d[0]],r.dtype,h),n.makeTensorInfo([f.length],"bool",new Uint8Array(f.map(g=>Number(g)))),n.makeTensorInfo([m.length],s.dtype,new Int32Array(m))]}var oQ={kernelName:qp,backendName:"cpu",kernelFunc:aQ};function iQ(e){let{inputs:t,backend:n}=e,{inputIndices:s,inputShape:r,newShape:a}=t;if(s.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape
         ${s.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape
-        ${r.shape}`);if(a.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${a.shape}`);let o=Array.from(n.data.get(r.dataId).values),i=n.data.get(s.dataId).values,l=Array.from(n.data.get(a.dataId).values),[u,c,p]=LI(i,s.shape,s.dtype,o,l);return[n.makeTensorInfo(c,s.dtype,u),n.makeTensorInfo([p.length],a.dtype,new Int32Array(p))]}var lQ={kernelName:Oc,backendName:"cpu",kernelFunc:iQ};function uQ(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
+        ${r.shape}`);if(a.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${a.shape}`);let o=Array.from(n.data.get(r.dataId).values),i=n.data.get(s.dataId).values,l=Array.from(n.data.get(a.dataId).values),[u,c,p]=LI(i,s.shape,s.dtype,o,l);return[n.makeTensorInfo(c,s.dtype,u),n.makeTensorInfo([p.length],a.dtype,new Int32Array(p))]}var lQ={kernelName:Fc,backendName:"cpu",kernelFunc:iQ};function uQ(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
           ${r.shape}`);if(a.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
-          ${a.shape}`);if(r.shape[0]!==a.shape[0])throw new Error("segmentIds and indices should have same size.");let o=n.data.get(s.dataId).values,i=n.data.get(r.dataId).values,l=n.data.get(a.dataId).values,[u,c]=Dx(o,s.shape,s.dtype,i,l,!0);return n.makeTensorInfo(c,s.dtype,u)}var cQ={kernelName:Kp,backendName:"cpu",kernelFunc:uQ};function dQ(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
+          ${a.shape}`);if(r.shape[0]!==a.shape[0])throw new Error("segmentIds and indices should have same size.");let o=n.data.get(s.dataId).values,i=n.data.get(r.dataId).values,l=n.data.get(a.dataId).values,[u,c]=Dx(o,s.shape,s.dtype,i,l,!0);return n.makeTensorInfo(c,s.dtype,u)}var cQ={kernelName:Xp,backendName:"cpu",kernelFunc:uQ};function dQ(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
          ${r.shape}`);if(a.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
-         ${a.shape}`);if(r.shape[0]!==a.shape[0])throw new Error("segmentIds and indices should have same size.");let o=n.data.get(s.dataId).values,i=n.data.get(r.dataId).values,l=n.data.get(a.dataId).values,[u,c]=Dx(o,s.shape,s.dtype,i,l);return n.makeTensorInfo(c,s.dtype,u)}var pQ={kernelName:Zp,backendName:"cpu",kernelFunc:dQ};function hQ(e){let{inputs:t,backend:n,attrs:s}=e,{sparseIndices:r,sparseValues:a,defaultValue:o}=t,{outputShape:i}=s,{sliceRank:l,numUpdates:u,sliceSize:c,strides:p,outputSize:d}=C.calculateShapes(a,r,i),h=!1,f=n.bufferSync(r),m;switch(a.dtype){case"bool":{let g=n.bufferSync(a),y=Boolean(n.data.get(o.dataId).values[0]);m=Bu(f,g,i,d,c,u,l,p,y,h);break}case"float32":{let g=n.bufferSync(a),y=n.data.get(o.dataId).values[0];m=Bu(f,g,i,d,c,u,l,p,y,h);break}case"int32":{let g=n.bufferSync(a),y=n.data.get(o.dataId).values[0];m=Bu(f,g,i,d,c,u,l,p,y,h);break}case"string":{let g=n.bufferSync(a),y=v.decodeString(n.data.get(o.dataId).values[0]);m=Bu(f,g,i,d,c,u,l,p,y,h);break}default:throw new Error(`Unsupported type ${a.dtype}`)}return n.makeTensorInfo(i,m.dtype,m.values)}var fQ={kernelName:Yp,backendName:"cpu",kernelFunc:hQ};function mQ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=s,i=v.parseAxisParam(o,r.shape)[0],l=C.prepareSplitSize(r,a,i),u=new Array(r.shape.length).fill(0),c=r.shape.slice();return l.map(p=>{let d=[...c];d[i]=p;let h=nl({inputs:{x:r},backend:n,attrs:{begin:u,size:d}});return u[i]+=p,h})}var gQ={kernelName:Ll,backendName:"cpu",kernelFunc:mQ},yQ={kernelName:Mc,backendName:"cpu",kernelFunc:({inputs:e,backend:t})=>{let{x:n}=e,s=t;Ce(n,"square");let r=s.data.get(n.dataId).values,a=new Float32Array(r.length);for(let i=0;i<r.length;++i){let l=r[i];a[i]=l*l}return{dataId:s.write(a,n.shape,n.dtype),shape:n.shape,dtype:n.dtype}}},AQ=bt(ai,(e,t)=>{let n=t;return isNaN(e)?NaN:e>0?1:n.alpha}),xQ={kernelName:ai,backendName:"cpu",kernelFunc:AQ};function bQ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,end:o,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:d}=s;Ce(r,"stridedSlice");let{finalShapeSparse:h,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Ut.sliceInfo(r.shape,a,o,i,l,u,c,p,d),w;if(m)w=Rt({inputs:{x:r},backend:n,attrs:{shape:f}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let k=Ut.computeOutShape(x,A,b),S=nl({inputs:{x:r},backend:n,attrs:{begin:x,size:k}});w=Rt({inputs:{x:S},backend:n,attrs:{shape:f}}),n.disposeIntermediateTensorInfo(S)}else{let k=n.bufferSync(r),S=WI(h,k,b,x);w=n.makeTensorInfo(f,S.dtype,S.values)}return w}var vQ={kernelName:Bl,backendName:"cpu",kernelFunc:bQ};function wQ(e){let{inputs:t,backend:n,attrs:s}=e,{separator:r,nGramWidths:a,leftPad:o,rightPad:i,padWidth:l,preserveShortSequences:u}=s,{data:c,dataSplits:p}=t,d=n.data.get(c.dataId).values,h=n.data.get(p.dataId).values,[f,m]=$x(d,h,r,a,o,i,l,u);return[n.makeTensorInfo([f.length],"string",f),n.makeTensorInfo(p.shape,"int32",m)]}var kQ={kernelName:zc,backendName:"cpu",kernelFunc:wQ};function IQ(e){let{inputs:t,backend:n,attrs:s}=e,{skipEmpty:r}=s,{input:a,delimiter:o}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(a.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${a.shape}`);if(o.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${o.shape}`);let i=n.data.get(a.dataId).values,l=n.data.get(o.dataId).values[0],[u,c,p]=Px(i,l,r),d=c.length;return[n.makeTensorInfo([d,2],"int32",u),n.makeTensorInfo([d],"string",c),n.makeTensorInfo([2],"int32",new Int32Array(p))]}var SQ={kernelName:Jp,backendName:"cpu",kernelFunc:IQ};function CQ(e){let{inputs:t,backend:n,attrs:s}=e,{numBuckets:r}=s,{input:a}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");let o=n.data.get(a.dataId).values,i=Fx(o,r);return n.makeTensorInfo(a.shape,"int32",i)}var TQ={kernelName:Qp,backendName:"cpu",kernelFunc:CQ},NQ=bt(Wl,e=>Math.tan(e)),EQ={kernelName:Wl,backendName:"cpu",kernelFunc:NQ},RQ=bt(ri,e=>Math.tanh(e)),_Q={kernelName:ri,backendName:"cpu",kernelFunc:RQ};function DQ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reps:a}=s;Ce(r,"tile");let o=UI(n.bufferSync(r),a);return n.makeTensorInfo(o.shape,o.dtype,o.values)}var $Q={kernelName:va,backendName:"cpu",kernelFunc:DQ};function PQ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{k:a,sorted:o}=s;Ce(r,"topk");let i=n.data.get(r.dataId).values,[l,u]=HI(i,r.shape,r.dtype,a,o);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(u.shape,u.dtype,u.values)]}var FQ={kernelName:Vl,backendName:"cpu",kernelFunc:PQ};function OQ(e){let{inputs:t,attrs:n,backend:s}=e,{image:r,transforms:a}=t,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=n,[c,p,d,h]=r.shape,[f,m]=u!=null?u:[p,d],g=[c,f,m,h],y=v.computeStrides(r.shape),x=y[0],A=y[1],b=y[2],w=v.getTypedArrayFromDType(r.dtype,v.sizeFromShape(g));w.fill(l);let k=s.data.get(r.dataId).values,S=s.data.get(a.dataId).values;for(let R=0;R<c;++R){let P=a.shape[0]===1?S:S.subarray(R*8,R*8+8);for(let _=0;_<f;++_)for(let $=0;$<m;++$)for(let T=0;T<h;++T){let F,G=P[6]*$+P[7]*_+1;if(G===0)continue;let q=(P[0]*$+P[1]*_+P[2])/G,z=(P[3]*$+P[4]*_+P[5])/G,K=c7(q,d,i),B=c7(z,p,i);switch(o){case"nearest":F=VQ(k,p,d,x,A,b,R,B,K,T,l);break;case"bilinear":F=UQ(k,p,d,x,A,b,R,B,K,T,l);break;default:throw new Error(`Error in Transform: Expect 'nearest' or 'bilinear', but got ${o}`)}let ee=R*x+_*A+$*b+T;w[ee]=F}return s.makeTensorInfo(g,r.dtype,w)}return{dataId:s.write(w,g,r.dtype),shape:r.shape,dtype:r.dtype}}var MQ={kernelName:Ul,backendName:"cpu",kernelFunc:OQ};function c7(e,t,n){switch(n){case"reflect":return zQ(e,t);case"wrap":return LQ(e,t);case"nearest":return WQ(e,t);case"constant":default:return BQ(e,t)}}function zQ(e,t){let n=e;if(n<0)if(t<=1)n=0;else{let s=2*t;n<s&&(n=s*Math.trunc(-n/s)+n),n=n<-t?n+s:-n-1}else if(n>t-1)if(t<=1)n=0;else{let s=2*t;n-=s*Math.trunc(n/s),n>=t&&(n=s-n-1)}return v.clamp(0,n,t-1)}function LQ(e,t){let n=e;if(n<0)if(t<=1)n=0;else{let s=t-1;n+=t*(Math.trunc(-n/s)+1)}else if(n>t-1)if(t<=1)n=0;else{let s=t-1;n-=t*Math.trunc(n/s)}return v.clamp(0,n,t-1)}function BQ(e,t){return e}function WQ(e,t){return v.clamp(0,e,t-1)}function lp(e,t,n,s,r,a,o,i,l,u,c){let p=o*s+i*r+l*a+u;return 0<=i&&i<t&&0<=l&&l<n?e[p]:c}function VQ(e,t,n,s,r,a,o,i,l,u,c){let p=Math.round(i),d=Math.round(l);return lp(e,t,n,s,r,a,o,p,d,u,c)}function UQ(e,t,n,s,r,a,o,i,l,u,c){let p=Math.floor(i),d=Math.floor(l),h=p+1,f=d+1,m=(f-l)*lp(e,t,n,s,r,a,o,p,d,u,c)+(l-d)*lp(e,t,n,s,r,a,o,p,f,u,c),g=(f-l)*lp(e,t,n,s,r,a,o,h,d,u,c)+(l-d)*lp(e,t,n,s,r,a,o,h,f,u,c);return(h-i)*m+(i-p)*g}function GQ(e){let{inputs:t,attrs:n,backend:s}=e,{axis:r}=n,{x:a}=t;Ce(a,"unique");let o=s.data.get(a.dataId).values,{outputValues:i,outputShape:l,indices:u}=jI(o,r,a.shape,a.dtype);return[s.makeTensorInfo(l,a.dtype,i),s.makeTensorInfo([u.length],"int32",u)]}var HQ={kernelName:h0,backendName:"cpu",kernelFunc:GQ};function jQ(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r.shape.length,i=r.shape[a],l=new Array(o-1),u=0;for(let h=0;h<o;h++)h!==a&&(l[u++]=r.shape[h]);let c=new Array(o).fill(0),p=r.shape.slice();p[a]=1;let d=new Array(i);for(let h=0;h<d.length;h++){c[a]=h;let f=nl({inputs:{x:r},backend:n,attrs:{begin:c,size:p}});d[h]=Rt({inputs:{x:f},backend:n,attrs:{shape:l}}),n.disposeIntermediateTensorInfo(f)}return d}var qQ={kernelName:Gl,backendName:"cpu",kernelFunc:jQ};function XQ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,segmentIds:a}=t,{numSegments:o}=s;Ce(r,"unsortedSegmentSum");let i=r.shape.length,l=a.shape.length,u=[],c=[],p=i-l,d=a;for(let f=0;f<p;++f){let m=$m({inputs:{input:d},backend:n,attrs:{dim:f+1}});d=m,c.push(m)}for(let f=0;f<o;++f){let m=v.createScalarValue(f,"int32"),g=n.makeTensorInfo([],"int32",m),y=yI({inputs:{a:g,b:d},backend:n}),x=io({inputs:{x:y},backend:n,attrs:{dtype:"float32"}}),A=A2({inputs:{a:x,b:r},backend:n}),b=Ph({inputs:{x:A},backend:n,attrs:{axis:0,keepDims:!1}});u.push(b),c.push(g),c.push(y),c.push(x),c.push(A),c.push(b)}let h=iS({inputs:u,backend:n,attrs:{axis:0}});return c.forEach(f=>n.disposeIntermediateTensorInfo(f)),h}var KQ={kernelName:eh,backendName:"cpu",kernelFunc:XQ},ZQ=[ZX,Uq,JX,eK,Kq,nK,rK,oK,lK,cK,pK,fK,gK,xK,vK,IK,CK,NK,RK,XX,DK,PK,OK,zK,qq,Yq,BK,Gq,VK,GK,HK,qK,KK,YK,QK,tZ,sZ,aZ,iZ,uZ,dZ,hZ,mZ,gZ,AZ,bZ,wZ,kZ,IZ,SZ,NZ,WX,RZ,Jq,zZ,Qq,LZ,tX,HZ,jZ,XZ,sX,YZ,QZ,tY,sY,aY,aX,iX,Hq,iY,UK,uY,dY,hY,VX,uX,dX,mY,hX,yY,bY,wY,SY,TY,EY,RY,mX,DY,PY,OY,zY,BY,VY,GY,yX,jY,KY,QY,xX,vX,nJ,aJ,lJ,kX,cJ,pJ,hJ,lS,yJ,GX,CX,xJ,jq,ey,vJ,HX,jX,qX,kJ,SJ,TJ,EJ,_J,DJ,PJ,NX,OJ,WJ,UJ,qJ,RX,KJ,YJ,QJ,_X,YY,nQ,rQ,oQ,lQ,cQ,pQ,fQ,gQ,PX,yQ,OX,xQ,vQ,kQ,SQ,TQ,BX,CZ,EQ,_Q,$Q,FQ,MQ,IX,HQ,qQ,KQ,dJ];for(let e of ZQ)cr(e);var uS={};Ve(uS,{assertNotComplex:()=>nd,bindCanvasToFramebuffer:()=>iee,bindColorTextureToFramebuffer:()=>sm,bindTextureToProgramUniformSampler:()=>IS,bindTextureUnit:()=>vS,bindVertexBufferToProgramAttribute:()=>ny,callAndCheck:()=>Ie,canBeRepresented:()=>cS,createFragmentShader:()=>hS,createFramebuffer:()=>bS,createProgram:()=>fS,createStaticIndexBuffer:()=>yS,createStaticVertexBuffer:()=>gS,createTexture:()=>AS,createVertexShader:()=>pS,getBatchDim:()=>sl,getExtensionOrThrow:()=>up,getFramebufferErrorMessage:()=>SS,getMaxTexturesInShader:()=>ES,getNumChannels:()=>aee,getProgramUniformLocation:()=>kS,getProgramUniformLocationOrThrow:()=>wS,getRowsCols:()=>rl,getShapeAs3D:()=>rm,getTextureShapeFromLogicalShape:()=>TS,getWebGLDisjointQueryTimerVersion:()=>RS,getWebGLErrorMessage:()=>dS,getWebGLMaxTextureSize:()=>NS,hasExtension:()=>Xs,isCapableOfRenderingToFloatTexture:()=>_S,isDownloadFloatTextureEnabled:()=>DS,isReshapeFree:()=>Dp,isWebGLFenceEnabled:()=>$S,isWebGLVersionEnabled:()=>ry,linkProgram:()=>mS,logShaderSourceAndInfoLog:()=>Wx,resetMaxTextureSize:()=>lee,resetMaxTexturesInShader:()=>uee,unbindColorTextureFromFramebuffer:()=>sy,unbindTextureUnit:()=>oee,validateFramebuffer:()=>cp,validateProgram:()=>nm,validateTextureSize:()=>xS});var Bi={},f3={alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!0};function x2(e,t){Bi[e]=t}function Dr(e,t){if(!(e in Bi)||t!=null){let s=JQ(e,t);if(s!==null)Bi[e]=s;else return console.log("Could not get context for WebGL version",e),null}let n=Bi[e];return n==null||n.isContextLost()?(delete Bi[e],Dr(e)):(n.disable(n.DEPTH_TEST),n.disable(n.STENCIL_TEST),n.disable(n.BLEND),n.disable(n.DITHER),n.disable(n.POLYGON_OFFSET_FILL),n.disable(n.SAMPLE_COVERAGE),n.enable(n.SCISSOR_TEST),n.enable(n.CULL_FACE),n.cullFace(n.BACK),Bi[e])}function YQ(e){if(typeof OffscreenCanvas!="undefined"&&e===2)return new OffscreenCanvas(300,150);if(typeof document!="undefined")return document.createElement("canvas");throw new Error("Cannot create a canvas in this context")}function JQ(e,t){if(e!==1&&e!==2)throw new Error("Cannot get WebGL rendering context, WebGL is disabled.");let n=t==null?YQ(e):t;return n.addEventListener("webglcontextlost",s=>{s.preventDefault(),delete Bi[e]},!1),e===1?n.getContext("webgl",f3)||n.getContext("experimental-webgl",f3):n.getContext("webgl2",f3)}var _p;(function(e){e[e.DENSE=0]="DENSE",e[e.SHARED_BATCH=1]="SHARED_BATCH"})(_p||(_p={}));var qs;(function(e){e[e.RENDER=0]="RENDER",e[e.UPLOAD=1]="UPLOAD",e[e.PIXELS=2]="PIXELS",e[e.DOWNLOAD=3]="DOWNLOAD"})(qs||(qs={}));var Sn;(function(e){e[e.UNPACKED_FLOAT16=0]="UNPACKED_FLOAT16",e[e.UNPACKED_FLOAT32=1]="UNPACKED_FLOAT32",e[e.PACKED_4X1_UNSIGNED_BYTE=2]="PACKED_4X1_UNSIGNED_BYTE",e[e.PACKED_2X2_FLOAT32=3]="PACKED_2X2_FLOAT32",e[e.PACKED_2X2_FLOAT16=4]="PACKED_2X2_FLOAT16"})(Sn||(Sn={}));function Fh(e,t){return[t,e]}function QQ(e,t){return e*t}function Xf(e){let t=v.sizeFromShape(e),n=Math.ceil(t/4);return v.sizeToSquarishShape(n)}function td(e,t){return[Math.max(1,Math.ceil(t/2)),Math.max(1,Math.ceil(e/2))]}function eee(e,t){let[n,s]=td(e,t);return n*s*4}function Bx(e,t){let n=e,s,r,a,o,i,l,u,c,p,d;return Z().getNumber("WEBGL_VERSION")===2?(s=n.R32F,r=n.R16F,a=n.RGBA16F,o=n.RGBA32F,i=n.RED,u=4,c=1,p=n.HALF_FLOAT,d=n.FLOAT,l=n.RGBA8):(s=e.RGBA,r=e.RGBA,a=e.RGBA,o=n.RGBA,i=e.RGBA,u=4,c=4,p=t!=null?t.HALF_FLOAT_OES:null,d=e.FLOAT,l=e.RGBA),{internalFormatFloat:s,internalFormatHalfFloat:r,internalFormatPackedHalfFloat:a,internalFormatPackedFloat:o,textureFormatFloat:i,downloadTextureFormat:l,downloadUnpackNumChannels:u,defaultNumChannels:c,textureTypeHalfFloat:p,textureTypeFloat:d}}function Ie(e,t){let n=t();return Z().getBool("DEBUG")&&tee(e),n}function tee(e){let t=e.getError();if(t!==e.NO_ERROR)throw new Error("WebGL Error: "+dS(e,t))}var nee=596e-10,see=65504;function cS(e){return!!(Z().getBool("WEBGL_RENDER_FLOAT32_ENABLED")||e===0||nee<Math.abs(e)&&Math.abs(e)<see)}function dS(e,t){switch(t){case e.NO_ERROR:return"NO_ERROR";case e.INVALID_ENUM:return"INVALID_ENUM";case e.INVALID_VALUE:return"INVALID_VALUE";case e.INVALID_OPERATION:return"INVALID_OPERATION";case e.INVALID_FRAMEBUFFER_OPERATION:return"INVALID_FRAMEBUFFER_OPERATION";case e.OUT_OF_MEMORY:return"OUT_OF_MEMORY";case e.CONTEXT_LOST_WEBGL:return"CONTEXT_LOST_WEBGL";default:return`Unknown error code ${t}`}}function up(e,t){return Ia(e,()=>e.getExtension(t),'Extension "'+t+'" not supported on this browser.')}function pS(e,t){let n=Ia(e,()=>e.createShader(e.VERTEX_SHADER),"Unable to create vertex WebGLShader.");if(Ie(e,()=>e.shaderSource(n,t)),Ie(e,()=>e.compileShader(n)),e.getShaderParameter(n,e.COMPILE_STATUS)===!1)throw console.log(e.getShaderInfoLog(n)),new Error("Failed to compile vertex shader.");return n}function hS(e,t){let n=Ia(e,()=>e.createShader(e.FRAGMENT_SHADER),"Unable to create fragment WebGLShader.");if(Ie(e,()=>e.shaderSource(n,t)),Ie(e,()=>e.compileShader(n)),Z().get("ENGINE_COMPILE_ONLY"))return n;if(e.getShaderParameter(n,e.COMPILE_STATUS)===!1)throw Wx(t,e.getShaderInfoLog(n)),new Error("Failed to compile fragment shader.");return n}var ree=/ERROR: [0-9]+:([0-9]+):/g;function Wx(e,t){let n=ree.exec(t);if(n==null){console.log(`Couldn't parse line number in error: ${t}`),console.log(e);return}let s=+n[1],r=e.split(`
+         ${a.shape}`);if(r.shape[0]!==a.shape[0])throw new Error("segmentIds and indices should have same size.");let o=n.data.get(s.dataId).values,i=n.data.get(r.dataId).values,l=n.data.get(a.dataId).values,[u,c]=Dx(o,s.shape,s.dtype,i,l);return n.makeTensorInfo(c,s.dtype,u)}var pQ={kernelName:Kp,backendName:"cpu",kernelFunc:dQ};function hQ(e){let{inputs:t,backend:n,attrs:s}=e,{sparseIndices:r,sparseValues:a,defaultValue:o}=t,{outputShape:i}=s,{sliceRank:l,numUpdates:u,sliceSize:c,strides:p,outputSize:d}=C.calculateShapes(a,r,i),h=!1,f=n.bufferSync(r),m;switch(a.dtype){case"bool":{let g=n.bufferSync(a),y=Boolean(n.data.get(o.dataId).values[0]);m=Lu(f,g,i,d,c,u,l,p,y,h);break}case"float32":{let g=n.bufferSync(a),y=n.data.get(o.dataId).values[0];m=Lu(f,g,i,d,c,u,l,p,y,h);break}case"int32":{let g=n.bufferSync(a),y=n.data.get(o.dataId).values[0];m=Lu(f,g,i,d,c,u,l,p,y,h);break}case"string":{let g=n.bufferSync(a),y=v.decodeString(n.data.get(o.dataId).values[0]);m=Lu(f,g,i,d,c,u,l,p,y,h);break}default:throw new Error(`Unsupported type ${a.dtype}`)}return n.makeTensorInfo(i,m.dtype,m.values)}var fQ={kernelName:Zp,backendName:"cpu",kernelFunc:hQ};function mQ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=s,i=v.parseAxisParam(o,r.shape)[0],l=C.prepareSplitSize(r,a,i),u=new Array(r.shape.length).fill(0),c=r.shape.slice();return l.map(p=>{let d=[...c];d[i]=p;let h=tl({inputs:{x:r},backend:n,attrs:{begin:u,size:d}});return u[i]+=p,h})}var gQ={kernelName:zl,backendName:"cpu",kernelFunc:mQ},yQ={kernelName:Oc,backendName:"cpu",kernelFunc:({inputs:e,backend:t})=>{let{x:n}=e,s=t;Ce(n,"square");let r=s.data.get(n.dataId).values,a=new Float32Array(r.length);for(let i=0;i<r.length;++i){let l=r[i];a[i]=l*l}return{dataId:s.write(a,n.shape,n.dtype),shape:n.shape,dtype:n.dtype}}},AQ=bt(ri,(e,t)=>{let n=t;return isNaN(e)?NaN:e>0?1:n.alpha}),xQ={kernelName:ri,backendName:"cpu",kernelFunc:AQ};function bQ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,end:o,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:d}=s;Ce(r,"stridedSlice");let{finalShapeSparse:h,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Ut.sliceInfo(r.shape,a,o,i,l,u,c,p,d),w;if(m)w=Rt({inputs:{x:r},backend:n,attrs:{shape:f}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let k=Ut.computeOutShape(x,A,b),S=tl({inputs:{x:r},backend:n,attrs:{begin:x,size:k}});w=Rt({inputs:{x:S},backend:n,attrs:{shape:f}}),n.disposeIntermediateTensorInfo(S)}else{let k=n.bufferSync(r),S=WI(h,k,b,x);w=n.makeTensorInfo(f,S.dtype,S.values)}return w}var vQ={kernelName:Ll,backendName:"cpu",kernelFunc:bQ};function wQ(e){let{inputs:t,backend:n,attrs:s}=e,{separator:r,nGramWidths:a,leftPad:o,rightPad:i,padWidth:l,preserveShortSequences:u}=s,{data:c,dataSplits:p}=t,d=n.data.get(c.dataId).values,h=n.data.get(p.dataId).values,[f,m]=$x(d,h,r,a,o,i,l,u);return[n.makeTensorInfo([f.length],"string",f),n.makeTensorInfo(p.shape,"int32",m)]}var kQ={kernelName:Mc,backendName:"cpu",kernelFunc:wQ};function IQ(e){let{inputs:t,backend:n,attrs:s}=e,{skipEmpty:r}=s,{input:a,delimiter:o}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(a.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${a.shape}`);if(o.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${o.shape}`);let i=n.data.get(a.dataId).values,l=n.data.get(o.dataId).values[0],[u,c,p]=Px(i,l,r),d=c.length;return[n.makeTensorInfo([d,2],"int32",u),n.makeTensorInfo([d],"string",c),n.makeTensorInfo([2],"int32",new Int32Array(p))]}var SQ={kernelName:Yp,backendName:"cpu",kernelFunc:IQ};function CQ(e){let{inputs:t,backend:n,attrs:s}=e,{numBuckets:r}=s,{input:a}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");let o=n.data.get(a.dataId).values,i=Fx(o,r);return n.makeTensorInfo(a.shape,"int32",i)}var TQ={kernelName:Jp,backendName:"cpu",kernelFunc:CQ},NQ=bt(Bl,e=>Math.tan(e)),EQ={kernelName:Bl,backendName:"cpu",kernelFunc:NQ},RQ=bt(si,e=>Math.tanh(e)),_Q={kernelName:si,backendName:"cpu",kernelFunc:RQ};function DQ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reps:a}=s;Ce(r,"tile");let o=UI(n.bufferSync(r),a);return n.makeTensorInfo(o.shape,o.dtype,o.values)}var $Q={kernelName:ba,backendName:"cpu",kernelFunc:DQ};function PQ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{k:a,sorted:o}=s;Ce(r,"topk");let i=n.data.get(r.dataId).values,[l,u]=HI(i,r.shape,r.dtype,a,o);return[n.makeTensorInfo(l.shape,l.dtype,l.values),n.makeTensorInfo(u.shape,u.dtype,u.values)]}var FQ={kernelName:Wl,backendName:"cpu",kernelFunc:PQ};function OQ(e){let{inputs:t,attrs:n,backend:s}=e,{image:r,transforms:a}=t,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=n,[c,p,d,h]=r.shape,[f,m]=u!=null?u:[p,d],g=[c,f,m,h],y=v.computeStrides(r.shape),x=y[0],A=y[1],b=y[2],w=v.getTypedArrayFromDType(r.dtype,v.sizeFromShape(g));w.fill(l);let k=s.data.get(r.dataId).values,S=s.data.get(a.dataId).values;for(let R=0;R<c;++R){let P=a.shape[0]===1?S:S.subarray(R*8,R*8+8);for(let _=0;_<f;++_)for(let $=0;$<m;++$)for(let T=0;T<h;++T){let F,G=P[6]*$+P[7]*_+1;if(G===0)continue;let q=(P[0]*$+P[1]*_+P[2])/G,z=(P[3]*$+P[4]*_+P[5])/G,Z=c7(q,d,i),B=c7(z,p,i);switch(o){case"nearest":F=VQ(k,p,d,x,A,b,R,B,Z,T,l);break;case"bilinear":F=UQ(k,p,d,x,A,b,R,B,Z,T,l);break;default:throw new Error(`Error in Transform: Expect 'nearest' or 'bilinear', but got ${o}`)}let ee=R*x+_*A+$*b+T;w[ee]=F}return s.makeTensorInfo(g,r.dtype,w)}return{dataId:s.write(w,g,r.dtype),shape:r.shape,dtype:r.dtype}}var MQ={kernelName:Vl,backendName:"cpu",kernelFunc:OQ};function c7(e,t,n){switch(n){case"reflect":return zQ(e,t);case"wrap":return LQ(e,t);case"nearest":return WQ(e,t);case"constant":default:return BQ(e,t)}}function zQ(e,t){let n=e;if(n<0)if(t<=1)n=0;else{let s=2*t;n<s&&(n=s*Math.trunc(-n/s)+n),n=n<-t?n+s:-n-1}else if(n>t-1)if(t<=1)n=0;else{let s=2*t;n-=s*Math.trunc(n/s),n>=t&&(n=s-n-1)}return v.clamp(0,n,t-1)}function LQ(e,t){let n=e;if(n<0)if(t<=1)n=0;else{let s=t-1;n+=t*(Math.trunc(-n/s)+1)}else if(n>t-1)if(t<=1)n=0;else{let s=t-1;n-=t*Math.trunc(n/s)}return v.clamp(0,n,t-1)}function BQ(e,t){return e}function WQ(e,t){return v.clamp(0,e,t-1)}function ip(e,t,n,s,r,a,o,i,l,u,c){let p=o*s+i*r+l*a+u;return 0<=i&&i<t&&0<=l&&l<n?e[p]:c}function VQ(e,t,n,s,r,a,o,i,l,u,c){let p=Math.round(i),d=Math.round(l);return ip(e,t,n,s,r,a,o,p,d,u,c)}function UQ(e,t,n,s,r,a,o,i,l,u,c){let p=Math.floor(i),d=Math.floor(l),h=p+1,f=d+1,m=(f-l)*ip(e,t,n,s,r,a,o,p,d,u,c)+(l-d)*ip(e,t,n,s,r,a,o,p,f,u,c),g=(f-l)*ip(e,t,n,s,r,a,o,h,d,u,c)+(l-d)*ip(e,t,n,s,r,a,o,h,f,u,c);return(h-i)*m+(i-p)*g}function GQ(e){let{inputs:t,attrs:n,backend:s}=e,{axis:r}=n,{x:a}=t;Ce(a,"unique");let o=s.data.get(a.dataId).values,{outputValues:i,outputShape:l,indices:u}=jI(o,r,a.shape,a.dtype);return[s.makeTensorInfo(l,a.dtype,i),s.makeTensorInfo([u.length],"int32",u)]}var HQ={kernelName:p0,backendName:"cpu",kernelFunc:GQ};function jQ(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r.shape.length,i=r.shape[a],l=new Array(o-1),u=0;for(let h=0;h<o;h++)h!==a&&(l[u++]=r.shape[h]);let c=new Array(o).fill(0),p=r.shape.slice();p[a]=1;let d=new Array(i);for(let h=0;h<d.length;h++){c[a]=h;let f=tl({inputs:{x:r},backend:n,attrs:{begin:c,size:p}});d[h]=Rt({inputs:{x:f},backend:n,attrs:{shape:l}}),n.disposeIntermediateTensorInfo(f)}return d}var qQ={kernelName:Ul,backendName:"cpu",kernelFunc:jQ};function XQ(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,segmentIds:a}=t,{numSegments:o}=s;Ce(r,"unsortedSegmentSum");let i=r.shape.length,l=a.shape.length,u=[],c=[],p=i-l,d=a;for(let f=0;f<p;++f){let m=Dm({inputs:{input:d},backend:n,attrs:{dim:f+1}});d=m,c.push(m)}for(let f=0;f<o;++f){let m=v.createScalarValue(f,"int32"),g=n.makeTensorInfo([],"int32",m),y=yI({inputs:{a:g,b:d},backend:n}),x=oo({inputs:{x:y},backend:n,attrs:{dtype:"float32"}}),A=y2({inputs:{a:x,b:r},backend:n}),b=$h({inputs:{x:A},backend:n,attrs:{axis:0,keepDims:!1}});u.push(b),c.push(g),c.push(y),c.push(x),c.push(A),c.push(b)}let h=iS({inputs:u,backend:n,attrs:{axis:0}});return c.forEach(f=>n.disposeIntermediateTensorInfo(f)),h}var KQ={kernelName:Qp,backendName:"cpu",kernelFunc:XQ},ZQ=[ZX,Uq,JX,eK,Kq,nK,rK,oK,lK,cK,pK,fK,gK,xK,vK,IK,CK,NK,RK,XX,DK,PK,OK,zK,qq,Yq,BK,Gq,VK,GK,HK,qK,KK,YK,QK,tZ,sZ,aZ,iZ,uZ,dZ,hZ,mZ,gZ,AZ,bZ,wZ,kZ,IZ,SZ,NZ,WX,RZ,Jq,zZ,Qq,LZ,tX,HZ,jZ,XZ,sX,YZ,QZ,tY,sY,aY,aX,iX,Hq,iY,UK,uY,dY,hY,VX,uX,dX,mY,hX,yY,bY,wY,SY,TY,EY,RY,mX,DY,PY,OY,zY,BY,VY,GY,yX,jY,KY,QY,xX,vX,nJ,aJ,lJ,kX,cJ,pJ,hJ,lS,yJ,GX,CX,xJ,jq,Q3,vJ,HX,jX,qX,kJ,SJ,TJ,EJ,_J,DJ,PJ,NX,OJ,WJ,UJ,qJ,RX,KJ,YJ,QJ,_X,YY,nQ,rQ,oQ,lQ,cQ,pQ,fQ,gQ,PX,yQ,OX,xQ,vQ,kQ,SQ,TQ,BX,CZ,EQ,_Q,$Q,FQ,MQ,IX,HQ,qQ,KQ,dJ];for(let e of ZQ)cr(e);var uS={};Ve(uS,{assertNotComplex:()=>td,bindCanvasToFramebuffer:()=>iee,bindColorTextureToFramebuffer:()=>nm,bindTextureToProgramUniformSampler:()=>IS,bindTextureUnit:()=>vS,bindVertexBufferToProgramAttribute:()=>ty,callAndCheck:()=>Ie,canBeRepresented:()=>cS,createFragmentShader:()=>hS,createFramebuffer:()=>bS,createProgram:()=>fS,createStaticIndexBuffer:()=>yS,createStaticVertexBuffer:()=>gS,createTexture:()=>AS,createVertexShader:()=>pS,getBatchDim:()=>nl,getExtensionOrThrow:()=>lp,getFramebufferErrorMessage:()=>SS,getMaxTexturesInShader:()=>ES,getNumChannels:()=>aee,getProgramUniformLocation:()=>kS,getProgramUniformLocationOrThrow:()=>wS,getRowsCols:()=>sl,getShapeAs3D:()=>sm,getTextureShapeFromLogicalShape:()=>TS,getWebGLDisjointQueryTimerVersion:()=>RS,getWebGLErrorMessage:()=>dS,getWebGLMaxTextureSize:()=>NS,hasExtension:()=>Xs,isCapableOfRenderingToFloatTexture:()=>_S,isDownloadFloatTextureEnabled:()=>DS,isReshapeFree:()=>_p,isWebGLFenceEnabled:()=>$S,isWebGLVersionEnabled:()=>sy,linkProgram:()=>mS,logShaderSourceAndInfoLog:()=>Wx,resetMaxTextureSize:()=>lee,resetMaxTexturesInShader:()=>uee,unbindColorTextureFromFramebuffer:()=>ny,unbindTextureUnit:()=>oee,validateFramebuffer:()=>up,validateProgram:()=>tm,validateTextureSize:()=>xS});var Li={},h3={alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!0};function A2(e,t){Li[e]=t}function Dr(e,t){if(!(e in Li)||t!=null){let s=JQ(e,t);if(s!==null)Li[e]=s;else return console.log("Could not get context for WebGL version",e),null}let n=Li[e];return n==null||n.isContextLost()?(delete Li[e],Dr(e)):(n.disable(n.DEPTH_TEST),n.disable(n.STENCIL_TEST),n.disable(n.BLEND),n.disable(n.DITHER),n.disable(n.POLYGON_OFFSET_FILL),n.disable(n.SAMPLE_COVERAGE),n.enable(n.SCISSOR_TEST),n.enable(n.CULL_FACE),n.cullFace(n.BACK),Li[e])}function YQ(e){if(typeof OffscreenCanvas!="undefined"&&e===2)return new OffscreenCanvas(300,150);if(typeof document!="undefined")return document.createElement("canvas");throw new Error("Cannot create a canvas in this context")}function JQ(e,t){if(e!==1&&e!==2)throw new Error("Cannot get WebGL rendering context, WebGL is disabled.");let n=t==null?YQ(e):t;return n.addEventListener("webglcontextlost",s=>{s.preventDefault(),delete Li[e]},!1),e===1?n.getContext("webgl",h3)||n.getContext("experimental-webgl",h3):n.getContext("webgl2",h3)}var Rp;(function(e){e[e.DENSE=0]="DENSE",e[e.SHARED_BATCH=1]="SHARED_BATCH"})(Rp||(Rp={}));var qs;(function(e){e[e.RENDER=0]="RENDER",e[e.UPLOAD=1]="UPLOAD",e[e.PIXELS=2]="PIXELS",e[e.DOWNLOAD=3]="DOWNLOAD"})(qs||(qs={}));var Sn;(function(e){e[e.UNPACKED_FLOAT16=0]="UNPACKED_FLOAT16",e[e.UNPACKED_FLOAT32=1]="UNPACKED_FLOAT32",e[e.PACKED_4X1_UNSIGNED_BYTE=2]="PACKED_4X1_UNSIGNED_BYTE",e[e.PACKED_2X2_FLOAT32=3]="PACKED_2X2_FLOAT32",e[e.PACKED_2X2_FLOAT16=4]="PACKED_2X2_FLOAT16"})(Sn||(Sn={}));function Ph(e,t){return[t,e]}function QQ(e,t){return e*t}function qf(e){let t=v.sizeFromShape(e),n=Math.ceil(t/4);return v.sizeToSquarishShape(n)}function ed(e,t){return[Math.max(1,Math.ceil(t/2)),Math.max(1,Math.ceil(e/2))]}function eee(e,t){let[n,s]=ed(e,t);return n*s*4}function Bx(e,t){let n=e,s,r,a,o,i,l,u,c,p,d;return X().getNumber("WEBGL_VERSION")===2?(s=n.R32F,r=n.R16F,a=n.RGBA16F,o=n.RGBA32F,i=n.RED,u=4,c=1,p=n.HALF_FLOAT,d=n.FLOAT,l=n.RGBA8):(s=e.RGBA,r=e.RGBA,a=e.RGBA,o=n.RGBA,i=e.RGBA,u=4,c=4,p=t!=null?t.HALF_FLOAT_OES:null,d=e.FLOAT,l=e.RGBA),{internalFormatFloat:s,internalFormatHalfFloat:r,internalFormatPackedHalfFloat:a,internalFormatPackedFloat:o,textureFormatFloat:i,downloadTextureFormat:l,downloadUnpackNumChannels:u,defaultNumChannels:c,textureTypeHalfFloat:p,textureTypeFloat:d}}function Ie(e,t){let n=t();return X().getBool("DEBUG")&&tee(e),n}function tee(e){let t=e.getError();if(t!==e.NO_ERROR)throw new Error("WebGL Error: "+dS(e,t))}var nee=596e-10,see=65504;function cS(e){return!!(X().getBool("WEBGL_RENDER_FLOAT32_ENABLED")||e===0||nee<Math.abs(e)&&Math.abs(e)<see)}function dS(e,t){switch(t){case e.NO_ERROR:return"NO_ERROR";case e.INVALID_ENUM:return"INVALID_ENUM";case e.INVALID_VALUE:return"INVALID_VALUE";case e.INVALID_OPERATION:return"INVALID_OPERATION";case e.INVALID_FRAMEBUFFER_OPERATION:return"INVALID_FRAMEBUFFER_OPERATION";case e.OUT_OF_MEMORY:return"OUT_OF_MEMORY";case e.CONTEXT_LOST_WEBGL:return"CONTEXT_LOST_WEBGL";default:return`Unknown error code ${t}`}}function lp(e,t){return ka(e,()=>e.getExtension(t),'Extension "'+t+'" not supported on this browser.')}function pS(e,t){let n=ka(e,()=>e.createShader(e.VERTEX_SHADER),"Unable to create vertex WebGLShader.");if(Ie(e,()=>e.shaderSource(n,t)),Ie(e,()=>e.compileShader(n)),e.getShaderParameter(n,e.COMPILE_STATUS)===!1)throw console.log(e.getShaderInfoLog(n)),new Error("Failed to compile vertex shader.");return n}function hS(e,t){let n=ka(e,()=>e.createShader(e.FRAGMENT_SHADER),"Unable to create fragment WebGLShader.");if(Ie(e,()=>e.shaderSource(n,t)),Ie(e,()=>e.compileShader(n)),X().get("ENGINE_COMPILE_ONLY"))return n;if(e.getShaderParameter(n,e.COMPILE_STATUS)===!1)throw Wx(t,e.getShaderInfoLog(n)),new Error("Failed to compile fragment shader.");return n}var ree=/ERROR: [0-9]+:([0-9]+):/g;function Wx(e,t){let n=ree.exec(t);if(n==null){console.log(`Couldn't parse line number in error: ${t}`),console.log(e);return}let s=+n[1],r=e.split(`
 `),a=r.length.toString().length+2,o=r.map((p,d)=>v.rightPad((d+1).toString(),a)+p),i=0;for(let p=0;p<o.length;p++)i=Math.max(o[p].length,i);let l=o.slice(0,s-1),u=o.slice(s-1,s),c=o.slice(s);console.log(l.join(`
 `)),console.log(t.split(`
 `)[0]),console.log(`%c ${v.rightPad(u[0],i)}`,"border:1px solid red; background-color:#e3d2d2; color:#a61717"),console.log(c.join(`
-`))}function fS(e){return Ia(e,()=>e.createProgram(),"Unable to create WebGLProgram.")}function mS(e,t){if(Ie(e,()=>e.linkProgram(t)),!Z().get("ENGINE_COMPILE_ONLY")&&e.getProgramParameter(t,e.LINK_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Failed to link vertex and fragment shaders.")}function nm(e,t){if(Ie(e,()=>e.validateProgram(t)),e.getProgramParameter(t,e.VALIDATE_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Shader program validation failed.")}function gS(e,t){let n=Ia(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return Ie(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),Ie(e,()=>e.bufferData(e.ARRAY_BUFFER,t,e.STATIC_DRAW)),n}function yS(e,t){let n=Ia(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return Ie(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,n)),Ie(e,()=>e.bufferData(e.ELEMENT_ARRAY_BUFFER,t,e.STATIC_DRAW)),n}function aee(){return Z().getNumber("WEBGL_VERSION")===2?1:4}function AS(e){return Ia(e,()=>e.createTexture(),"Unable to create WebGLTexture.")}function xS(e,t){let n=Z().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(e<=0||t<=0){let s=`[${e}x${t}]`;throw new Error("Requested texture size "+s+" is invalid.")}if(e>n||t>n){let s=`[${e}x${t}]`,r=`[${n}x${n}]`;throw new Error("Requested texture size "+s+" greater than WebGL maximum on this browser / GPU "+r+".")}}function bS(e){return Ia(e,()=>e.createFramebuffer(),"Unable to create WebGLFramebuffer.")}function ny(e,t,n,s,r,a,o){let i=e.getAttribLocation(t,n);return i===-1?!1:(Ie(e,()=>e.bindBuffer(e.ARRAY_BUFFER,s)),Ie(e,()=>e.vertexAttribPointer(i,r,e.FLOAT,!1,a,o)),Ie(e,()=>e.enableVertexAttribArray(i)),!0)}function vS(e,t,n){CS(e,n),Ie(e,()=>e.activeTexture(e.TEXTURE0+n)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,t))}function oee(e,t){CS(e,t),Ie(e,()=>e.activeTexture(e.TEXTURE0+t)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function wS(e,t,n){return Ia(e,()=>e.getUniformLocation(t,n),'uniform "'+n+'" not present in program.')}function kS(e,t,n){return e.getUniformLocation(t,n)}function IS(e,t,n,s){Ie(e,()=>vS(e,t,s)),Ie(e,()=>e.uniform1i(n,s))}function iee(e){Ie(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),Ie(e,()=>e.viewport(0,0,e.canvas.width,e.canvas.height)),Ie(e,()=>e.scissor(0,0,e.canvas.width,e.canvas.height))}function sm(e,t,n){Ie(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,n)),Ie(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0))}function sy(e,t){Ie(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,t)),Ie(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,null,0))}function cp(e){let t=e.checkFramebufferStatus(e.FRAMEBUFFER);if(t!==e.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+SS(e,t))}function SS(e,t){switch(t){case e.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case e.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return`unknown error ${t}`}}function Ia(e,t,n){let s=Ie(e,()=>t());if(s==null)throw new Error(n);return s}function CS(e,t){let n=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,s=t+e.TEXTURE0;if(s<e.TEXTURE0||s>n){let r=`[gl.TEXTURE0, gl.TEXTURE${n}]`;throw new Error(`textureUnit must be in ${r}.`)}}function sl(e,t=2){return v.sizeFromShape(e.slice(0,e.length-t))}function rl(e){if(e.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[e.length>1?e[e.length-2]:1,e[e.length-1]]}function rm(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[sl(e),...rl(e)]),t}function TS(e,t=!1){let n=Z().getNumber("WEBGL_MAX_TEXTURE_SIZE");t&&(n=n*2,e=e.map((r,a)=>a>=e.length-2?v.nearestLargerEven(e[a]):e[a]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=v.squeezeShape(e).newShape);let s=v.sizeFromShape(e);if(e.length<=1&&s<=n)return[1,s];if(e.length===2&&e[0]<=n&&e[1]<=n)return e;if(e.length===3&&e[0]*e[1]<=n&&e[2]<=n)return[e[0]*e[1],e[2]];if(e.length===3&&e[0]<=n&&e[1]*e[2]<=n)return[e[0],e[1]*e[2]];if(e.length===4&&e[0]*e[1]*e[2]<=n&&e[3]<=n)return[e[0]*e[1]*e[2],e[3]];if(e.length===4&&e[0]<=n&&e[1]*e[2]*e[3]<=n)return[e[0],e[1]*e[2]*e[3]];if(t){let r=sl(e),a=2,o=2;return e.length&&([a,o]=rl(e)),s=r*(a/2)*(o/2),v.sizeToSquarishShape(s).map(i=>i*2)}return v.sizeToSquarishShape(s)}function Kf(e){return e%2===0}function Dp(e,t){if(e=e.slice(-2),t=t.slice(-2),v.arraysEqual(e,t)||!e.length||!t.length||e[0]===0||e[1]===0||t[0]===0||t[1]===0)return!0;if(e.length!==t.length){let n=e.slice(-1)[0],s=t.slice(-1)[0];if(n===s||Kf(n)&&Kf(s)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&Kf(e[0])&&Kf(t[0])}var am,om;function NS(e){if(am==null){let t=Dr(e);am=t.getParameter(t.MAX_TEXTURE_SIZE)}return am}function lee(){am=null}function uee(){om=null}function ES(e){if(om==null){let t=Dr(e);om=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,om)}function RS(e){if(e===0)return 0;let t,n=Dr(e);return Xs(n,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:Xs(n,"EXT_disjoint_timer_query")?t=1:t=0,t}function Xs(e,t){return e.getExtension(t)!=null}function ry(e){try{if(Dr(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function _S(e){if(e===0)return!1;let t=Dr(e);if(e===1){if(!Xs(t,"OES_texture_float"))return!1}else if(!Xs(t,"EXT_color_buffer_float"))return!1;return ay(t)}function DS(e){if(e===0)return!1;let t=Dr(e);if(e===1){if(!Xs(t,"OES_texture_float")||!Xs(t,"WEBGL_color_buffer_float"))return!1}else{if(Xs(t,"EXT_color_buffer_float"))return ay(t);let s="EXT_color_buffer_half_float";if(Xs(t,s)){let r=t.getExtension(s);return cee(t,r)}return!1}return ay(t)}function ay(e){let t=Bx(e),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let s=1,r=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,s,r,0,t.textureFormatFloat,t.textureTypeFloat,null);let a=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,a),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let o=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(a),o}function cee(e,t){let n=Bx(e,t),s=e.createTexture();e.bindTexture(e.TEXTURE_2D,s);let r=1,a=1;e.texImage2D(e.TEXTURE_2D,0,n.internalFormatHalfFloat,r,a,0,n.textureFormatFloat,n.textureTypeHalfFloat,null);let o=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,o),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,s,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(s),e.deleteFramebuffer(o),i}function $S(e){return e!==2?!1:Dr(e).fenceSync!=null}function nd(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&v.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var Pe=Z();Pe.registerFlag("HAS_WEBGL",()=>Pe.getNumber("WEBGL_VERSION")>0);Pe.registerFlag("WEBGL_VERSION",()=>ry(2)?2:ry(1)?1:0);Pe.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Pe.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Pe.get("WEBGL_VERSION")===2);Pe.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Pe.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Pe.registerFlag("WEBGL_PACK",()=>Pe.getBool("HAS_WEBGL"));Pe.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_CLIP",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_REDUCE",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_LAZILY_UNPACK",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_CONV_IM2COL",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>NS(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>ES(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=Pe.getNumber("WEBGL_VERSION");return e===0?0:RS(e)});Pe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Pe.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!rh.isMobile());Pe.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>_S(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Pe.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Pe.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Pe.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>DS(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_FENCE_API_ENABLED",()=>$S(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Pe.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Pe.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",()=>-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${e}.`)});Pe.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>rh.isMobile()?1:-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${e}.`)});Pe.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);Pe.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);Pe.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);Pe.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);function as(){let e,t,n,s,r,a,o,i,l,u;return Z().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",s="in",r="texture",a="outputColor",o="out vec4 outputColor;",i=`
+`))}function fS(e){return ka(e,()=>e.createProgram(),"Unable to create WebGLProgram.")}function mS(e,t){if(Ie(e,()=>e.linkProgram(t)),!X().get("ENGINE_COMPILE_ONLY")&&e.getProgramParameter(t,e.LINK_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Failed to link vertex and fragment shaders.")}function tm(e,t){if(Ie(e,()=>e.validateProgram(t)),e.getProgramParameter(t,e.VALIDATE_STATUS)===!1)throw console.log(e.getProgramInfoLog(t)),new Error("Shader program validation failed.")}function gS(e,t){let n=ka(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return Ie(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),Ie(e,()=>e.bufferData(e.ARRAY_BUFFER,t,e.STATIC_DRAW)),n}function yS(e,t){let n=ka(e,()=>e.createBuffer(),"Unable to create WebGLBuffer");return Ie(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,n)),Ie(e,()=>e.bufferData(e.ELEMENT_ARRAY_BUFFER,t,e.STATIC_DRAW)),n}function aee(){return X().getNumber("WEBGL_VERSION")===2?1:4}function AS(e){return ka(e,()=>e.createTexture(),"Unable to create WebGLTexture.")}function xS(e,t){let n=X().getNumber("WEBGL_MAX_TEXTURE_SIZE");if(e<=0||t<=0){let s=`[${e}x${t}]`;throw new Error("Requested texture size "+s+" is invalid.")}if(e>n||t>n){let s=`[${e}x${t}]`,r=`[${n}x${n}]`;throw new Error("Requested texture size "+s+" greater than WebGL maximum on this browser / GPU "+r+".")}}function bS(e){return ka(e,()=>e.createFramebuffer(),"Unable to create WebGLFramebuffer.")}function ty(e,t,n,s,r,a,o){let i=e.getAttribLocation(t,n);return i===-1?!1:(Ie(e,()=>e.bindBuffer(e.ARRAY_BUFFER,s)),Ie(e,()=>e.vertexAttribPointer(i,r,e.FLOAT,!1,a,o)),Ie(e,()=>e.enableVertexAttribArray(i)),!0)}function vS(e,t,n){CS(e,n),Ie(e,()=>e.activeTexture(e.TEXTURE0+n)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,t))}function oee(e,t){CS(e,t),Ie(e,()=>e.activeTexture(e.TEXTURE0+t)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function wS(e,t,n){return ka(e,()=>e.getUniformLocation(t,n),'uniform "'+n+'" not present in program.')}function kS(e,t,n){return e.getUniformLocation(t,n)}function IS(e,t,n,s){Ie(e,()=>vS(e,t,s)),Ie(e,()=>e.uniform1i(n,s))}function iee(e){Ie(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),Ie(e,()=>e.viewport(0,0,e.canvas.width,e.canvas.height)),Ie(e,()=>e.scissor(0,0,e.canvas.width,e.canvas.height))}function nm(e,t,n){Ie(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,n)),Ie(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,t,0))}function ny(e,t){Ie(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,t)),Ie(e,()=>e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,null,0))}function up(e){let t=e.checkFramebufferStatus(e.FRAMEBUFFER);if(t!==e.FRAMEBUFFER_COMPLETE)throw new Error("Error binding framebuffer: "+SS(e,t))}function SS(e,t){switch(t){case e.FRAMEBUFFER_INCOMPLETE_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT:return"FRAMEBUFFER_INCOMPLETE_MISSING_ATTACHMENT";case e.FRAMEBUFFER_INCOMPLETE_DIMENSIONS:return"FRAMEBUFFER_INCOMPLETE_DIMENSIONS";case e.FRAMEBUFFER_UNSUPPORTED:return"FRAMEBUFFER_UNSUPPORTED";default:return`unknown error ${t}`}}function ka(e,t,n){let s=Ie(e,()=>t());if(s==null)throw new Error(n);return s}function CS(e,t){let n=e.MAX_COMBINED_TEXTURE_IMAGE_UNITS-1,s=t+e.TEXTURE0;if(s<e.TEXTURE0||s>n){let r=`[gl.TEXTURE0, gl.TEXTURE${n}]`;throw new Error(`textureUnit must be in ${r}.`)}}function nl(e,t=2){return v.sizeFromShape(e.slice(0,e.length-t))}function sl(e){if(e.length===0)throw Error("Cannot get rows and columns of an empty shape array.");return[e.length>1?e[e.length-2]:1,e[e.length-1]]}function sm(e){let t=[1,1,1];return e.length===0||e.length===1&&e[0]===1||(t=[nl(e),...sl(e)]),t}function TS(e,t=!1){let n=X().getNumber("WEBGL_MAX_TEXTURE_SIZE");t&&(n=n*2,e=e.map((r,a)=>a>=e.length-2?v.nearestLargerEven(e[a]):e[a]),e.length===1&&(e=[2,e[0]])),e.length!==2&&(e=v.squeezeShape(e).newShape);let s=v.sizeFromShape(e);if(e.length<=1&&s<=n)return[1,s];if(e.length===2&&e[0]<=n&&e[1]<=n)return e;if(e.length===3&&e[0]*e[1]<=n&&e[2]<=n)return[e[0]*e[1],e[2]];if(e.length===3&&e[0]<=n&&e[1]*e[2]<=n)return[e[0],e[1]*e[2]];if(e.length===4&&e[0]*e[1]*e[2]<=n&&e[3]<=n)return[e[0]*e[1]*e[2],e[3]];if(e.length===4&&e[0]<=n&&e[1]*e[2]*e[3]<=n)return[e[0],e[1]*e[2]*e[3]];if(t){let r=nl(e),a=2,o=2;return e.length&&([a,o]=sl(e)),s=r*(a/2)*(o/2),v.sizeToSquarishShape(s).map(i=>i*2)}return v.sizeToSquarishShape(s)}function Xf(e){return e%2===0}function _p(e,t){if(e=e.slice(-2),t=t.slice(-2),v.arraysEqual(e,t)||!e.length||!t.length||e[0]===0||e[1]===0||t[0]===0||t[1]===0)return!0;if(e.length!==t.length){let n=e.slice(-1)[0],s=t.slice(-1)[0];if(n===s||Xf(n)&&Xf(s)&&(e[0]===1||t[0]===1))return!0}return e[1]===t[1]&&Xf(e[0])&&Xf(t[0])}var rm,am;function NS(e){if(rm==null){let t=Dr(e);rm=t.getParameter(t.MAX_TEXTURE_SIZE)}return rm}function lee(){rm=null}function uee(){am=null}function ES(e){if(am==null){let t=Dr(e);am=t.getParameter(t.MAX_TEXTURE_IMAGE_UNITS)}return Math.min(16,am)}function RS(e){if(e===0)return 0;let t,n=Dr(e);return Xs(n,"EXT_disjoint_timer_query_webgl2")&&e===2?t=2:Xs(n,"EXT_disjoint_timer_query")?t=1:t=0,t}function Xs(e,t){return e.getExtension(t)!=null}function sy(e){try{if(Dr(e)!=null)return!0}catch(t){return console.log("Error when getting WebGL context: ",t),!1}return!1}function _S(e){if(e===0)return!1;let t=Dr(e);if(e===1){if(!Xs(t,"OES_texture_float"))return!1}else if(!Xs(t,"EXT_color_buffer_float"))return!1;return ry(t)}function DS(e){if(e===0)return!1;let t=Dr(e);if(e===1){if(!Xs(t,"OES_texture_float")||!Xs(t,"WEBGL_color_buffer_float"))return!1}else{if(Xs(t,"EXT_color_buffer_float"))return ry(t);let s="EXT_color_buffer_half_float";if(Xs(t,s)){let r=t.getExtension(s);return cee(t,r)}return!1}return ry(t)}function ry(e){let t=Bx(e),n=e.createTexture();e.bindTexture(e.TEXTURE_2D,n);let s=1,r=1;e.texImage2D(e.TEXTURE_2D,0,t.internalFormatFloat,s,r,0,t.textureFormatFloat,t.textureTypeFloat,null);let a=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,a),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,n,0);let o=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(n),e.deleteFramebuffer(a),o}function cee(e,t){let n=Bx(e,t),s=e.createTexture();e.bindTexture(e.TEXTURE_2D,s);let r=1,a=1;e.texImage2D(e.TEXTURE_2D,0,n.internalFormatHalfFloat,r,a,0,n.textureFormatFloat,n.textureTypeHalfFloat,null);let o=e.createFramebuffer();e.bindFramebuffer(e.FRAMEBUFFER,o),e.framebufferTexture2D(e.FRAMEBUFFER,e.COLOR_ATTACHMENT0,e.TEXTURE_2D,s,0);let i=e.checkFramebufferStatus(e.FRAMEBUFFER)===e.FRAMEBUFFER_COMPLETE;return e.bindTexture(e.TEXTURE_2D,null),e.bindFramebuffer(e.FRAMEBUFFER,null),e.deleteTexture(s),e.deleteFramebuffer(o),i}function $S(e){return e!==2?!1:Dr(e).fenceSync!=null}function td(e,t){Array.isArray(e)||(e=[e]),e.forEach(n=>{n!=null&&v.assert(n.dtype!=="complex64",()=>`${t} does not support complex64 tensors in the WebGL backend.`)})}var Pe=X();Pe.registerFlag("HAS_WEBGL",()=>Pe.getNumber("WEBGL_VERSION")>0);Pe.registerFlag("WEBGL_VERSION",()=>sy(2)?2:sy(1)?1:0);Pe.registerFlag("WEBGL_CHECK_NUMERICAL_PROBLEMS",()=>!1);Pe.registerFlag("WEBGL_BUFFER_SUPPORTED",()=>Pe.get("WEBGL_VERSION")===2);Pe.registerFlag("WEBGL_CPU_FORWARD",()=>!0);Pe.registerFlag("WEBGL_FORCE_F16_TEXTURES",()=>!1);Pe.registerFlag("WEBGL_PACK",()=>Pe.getBool("HAS_WEBGL"));Pe.registerFlag("WEBGL_PACK_NORMALIZATION",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_CLIP",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_DEPTHWISECONV",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_BINARY_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_UNARY_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_ARRAY_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_IMAGE_OPERATIONS",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_PACK_REDUCE",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_LAZILY_UNPACK",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_CONV_IM2COL",()=>Pe.getBool("WEBGL_PACK"));Pe.registerFlag("WEBGL_MAX_TEXTURE_SIZE",()=>NS(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_MAX_TEXTURES_IN_SHADER",()=>ES(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION",()=>{let e=Pe.getNumber("WEBGL_VERSION");return e===0?0:RS(e)});Pe.registerFlag("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE",()=>Pe.getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0&&!sh.isMobile());Pe.registerFlag("WEBGL_RENDER_FLOAT32_CAPABLE",()=>_S(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_RENDER_FLOAT32_ENABLED",()=>Pe.getBool("WEBGL_FORCE_F16_TEXTURES")?!1:Pe.getBool("WEBGL_RENDER_FLOAT32_CAPABLE"));Pe.registerFlag("WEBGL_DOWNLOAD_FLOAT_ENABLED",()=>DS(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_FENCE_API_ENABLED",()=>$S(Pe.getNumber("WEBGL_VERSION")));Pe.registerFlag("WEBGL_SIZE_UPLOAD_UNIFORM",()=>Pe.getBool("WEBGL_RENDER_FLOAT32_ENABLED")?4:0);Pe.registerFlag("WEBGL_DELETE_TEXTURE_THRESHOLD",()=>-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_DELETE_TEXTURE_THRESHOLD must be -1 (indicating never delete) or at least 0, but got ${e}.`)});Pe.registerFlag("WEBGL_FLUSH_THRESHOLD",()=>sh.isMobile()?1:-1,e=>{if(e<0&&e!==-1)throw new Error(`WEBGL_FLUSH_THRESHOLD must be -1 (indicating never manual flush) or at least 0, but got ${e}.`)});Pe.registerFlag("CPU_HANDOFF_SIZE_THRESHOLD",()=>128);Pe.registerFlag("WEBGL_USE_SHAPES_UNIFORMS",()=>!1);Pe.registerFlag("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e5);Pe.registerFlag("TOPK_K_CPU_HANDOFF_THRESHOLD",()=>128);function as(){let e,t,n,s,r,a,o,i,l,u;return X().getNumber("WEBGL_VERSION")===2?(e="#version 300 es",t="in",n="out",s="in",r="texture",a="outputColor",o="out vec4 outputColor;",i=`
       bool isnan_custom(float val) {
         uint floatToUint = floatBitsToUint(val);
         return (floatToUint & 0x7fffffffu) > 0x7f800000u;
@@ -107,7 +107,7 @@ Hi, looks like you are running TensorFlow.js in Node.js. To speed things up dram
       ivec4 round(vec4 value) {
         return ivec4(floor(value + vec4(0.5)));
       }
-    `),{version:e,attribute:t,varyingVs:n,varyingFs:s,texture2D:r,output:a,defineOutput:o,defineSpecialNaN:i,defineSpecialInf:l,defineRound:u}}function su(e,t,n="index"){let s=v.computeStrides(t);return s.map((r,a)=>{let o=`int ${e[a]} = ${n} / ${r}`,i=a===s.length-1?`int ${e[a+1]} = ${n} - ${e[a]} * ${r}`:`index -= ${e[a]} * ${r}`;return`${o}; ${i};`}).join("")}function b2(e,t,n="index"){let s=v.computeStrides(t);return s.map((r,a)=>{let o=`int ${e[a]} = ${n} / outShapeStrides[${a}]`,i=a===s.length-1?`int ${e[a+1]} = ${n} - ${e[a]} * outShapeStrides[${a}]`:`index -= ${e[a]} * outShapeStrides[${a}]`;return`${o}; ${i};`}).join("")}function dee(e,t){let n=e.length,s=e.map(a=>`${t}[${a}]`),r=new Array(n-1);r[n-2]=s[n-1];for(let a=n-3;a>=0;--a)r[a]=`(${r[a+1]} * ${s[a+1]})`;return r}function pee(e,t,n="index"){let s=e.map((a,o)=>o),r=dee(s,t);return r.map((a,o)=>{let i=`int ${e[o]} = ${n} / ${r[o]}`,l=o===r.length-1?`int ${e[o+1]} = ${n} - ${e[o]} * ${r[o]}`:`index -= ${e[o]} * ${r[o]}`;return`${i}; ${l};`}).join("")}function Vx(e){let t=v.computeStrides(e).map(n=>n.toString());return`
+    `),{version:e,attribute:t,varyingVs:n,varyingFs:s,texture2D:r,output:a,defineOutput:o,defineSpecialNaN:i,defineSpecialInf:l,defineRound:u}}function nu(e,t,n="index"){let s=v.computeStrides(t);return s.map((r,a)=>{let o=`int ${e[a]} = ${n} / ${r}`,i=a===s.length-1?`int ${e[a+1]} = ${n} - ${e[a]} * ${r}`:`index -= ${e[a]} * ${r}`;return`${o}; ${i};`}).join("")}function x2(e,t,n="index"){let s=v.computeStrides(t);return s.map((r,a)=>{let o=`int ${e[a]} = ${n} / outShapeStrides[${a}]`,i=a===s.length-1?`int ${e[a+1]} = ${n} - ${e[a]} * outShapeStrides[${a}]`:`index -= ${e[a]} * outShapeStrides[${a}]`;return`${o}; ${i};`}).join("")}function dee(e,t){let n=e.length,s=e.map(a=>`${t}[${a}]`),r=new Array(n-1);r[n-2]=s[n-1];for(let a=n-3;a>=0;--a)r[a]=`(${r[a+1]} * ${s[a+1]})`;return r}function pee(e,t,n="index"){let s=e.map((a,o)=>o),r=dee(s,t);return r.map((a,o)=>{let i=`int ${e[o]} = ${n} / ${r[o]}`,l=o===r.length-1?`int ${e[o+1]} = ${n} - ${e[o]} * ${r[o]}`:`index -= ${e[o]} * ${r[o]}`;return`${i}; ${l};`}).join("")}function Vx(e){let t=v.computeStrides(e).map(n=>n.toString());return`
   int getFlatIndex(ivec3 coords) {
     return coords.x * ${t[0]} + coords.y * ${t[1]} + coords.z;
   }
@@ -157,7 +157,7 @@ Hi, looks like you are running TensorFlow.js in Node.js. To speed things up dram
 `,{getBroadcastDims:FS}=C;function hee(e,t,n){let s=[];if(e.forEach(h=>{let f=v.sizeFromShape(h.shapeInfo.logicalShape);if(h.shapeInfo.isUniform?s.push(`uniform float ${h.name}${f>1?`[${f}]`:""};`):(s.push(`uniform sampler2D ${h.name};`),s.push(`uniform int offset${h.name};`)),n.enableShapeUniforms){let{uniformShape:m}=Gx(n.packedInputs,h.shapeInfo.logicalShape,h.shapeInfo.texShape);switch(m.length){case 1:s.push(`uniform int ${h.name}Shape;`);break;case 2:s.push(`uniform ivec2 ${h.name}Shape;`);break;case 3:s.push(`uniform ivec3 ${h.name}Shape;`);break;case 4:s.push(`uniform ivec4 ${h.name}Shape;`);break;default:break}s.push(`uniform ivec2 ${h.name}TexShape;`)}}),n.enableShapeUniforms){switch(t.logicalShape.length){case 1:s.push("uniform int outShape;");break;case 2:s.push("uniform ivec2 outShape;"),s.push("uniform int outShapeStrides;");break;case 3:s.push("uniform ivec3 outShape;"),s.push("uniform ivec2 outShapeStrides;");break;case 4:s.push("uniform ivec4 outShape;"),s.push("uniform ivec3 outShapeStrides;");break;default:break}s.push("uniform ivec2 outTexShape;")}n.customUniforms&&n.customUniforms.forEach(h=>{s.push(`uniform ${h.type} ${h.name}${h.arrayIndex?`[${h.arrayIndex}]`:""};`)});let r=s.join(`
 `),a=e.map(h=>fee(h,t,n.packedInputs,n.enableShapeUniforms)).join(`
 `),o=t.texShape,i=as(),l=yee(i),u,c,p=bee(i);return t.isPacked?(u=mee(t.logicalShape,o,n.enableShapeUniforms),c=xee(i)):(u=gee(t.logicalShape,o,n.enableShapeUniforms),c=Aee(i)),n.packedInputs&&(p+=Iee),[p,l,c,r,u,a,n.userCode].join(`
-`)}function sd(e,t=!1){let n=e.shapeInfo.logicalShape;switch(n.length){case 0:return Oee(e,t);case 1:return zee(e,t);case 2:return Bee(e,t);case 3:return Vee(e,t);case 4:return Gee(e,t);case 5:return Hee(e);case 6:return jee(e);default:throw new Error(`${n.length}-D input sampling is not yet supported`)}}function OS(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return Fee(e);case 1:return Mee(e,t);case 2:return Lee(e,t);case 3:return Wee(e,t);default:return Uee(e,t)}}function fee(e,t,n=!1,s){let r="";n?r+=OS(e,s):r+=sd(e,s);let a=e.shapeInfo.logicalShape,o=t.logicalShape;return a.length<=o.length&&(n?r+=qee(e,t):r+=Xee(e,t)),r}function mee(e,t,n){switch(e.length){case 0:return MS();case 1:return See(e,t,n);case 2:return $ee(e,t,n);case 3:return Tee(e,t,n);default:return Eee(e,t,n)}}function gee(e,t,n){switch(e.length){case 0:return MS();case 1:return Cee(e,t,n);case 2:return Pee(e,t,n);case 3:return Nee(e,t,n);case 4:return Ree(e,t,n);case 5:return _ee(e,t);case 6:return Dee(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function yee(e){return`
+`)}function nd(e,t=!1){let n=e.shapeInfo.logicalShape;switch(n.length){case 0:return Oee(e,t);case 1:return zee(e,t);case 2:return Bee(e,t);case 3:return Vee(e,t);case 4:return Gee(e,t);case 5:return Hee(e);case 6:return jee(e);default:throw new Error(`${n.length}-D input sampling is not yet supported`)}}function OS(e,t){switch(e.shapeInfo.logicalShape.length){case 0:return Fee(e);case 1:return Mee(e,t);case 2:return Lee(e,t);case 3:return Wee(e,t);default:return Uee(e,t)}}function fee(e,t,n=!1,s){let r="";n?r+=OS(e,s):r+=nd(e,s);let a=e.shapeInfo.logicalShape,o=t.logicalShape;return a.length<=o.length&&(n?r+=qee(e,t):r+=Xee(e,t)),r}function mee(e,t,n){switch(e.length){case 0:return MS();case 1:return See(e,t,n);case 2:return $ee(e,t,n);case 3:return Tee(e,t,n);default:return Eee(e,t,n)}}function gee(e,t,n){switch(e.length){case 0:return MS();case 1:return Cee(e,t,n);case 2:return Pee(e,t,n);case 3:return Nee(e,t,n);case 4:return Ree(e,t,n);case 5:return _ee(e,t);case 6:return Dee(e,t);default:throw new Error(`${e.length}-D output sampling is not yet supported`)}}function yee(e){return`
     float sampleTexture(sampler2D textureSampler, vec2 uv) {
       return ${e.texture2D}(textureSampler, uv).r;
     }
@@ -364,10 +364,10 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     ivec2 resTexRC = ivec2(resultUV.yx *
                            vec2(outTexShape[0], outTexShape[1]));
     int index = resTexRC.x * outTexShape[1] + resTexRC.y;
-    ${b2(["r","c","d"],e)}
+    ${x2(["r","c","d"],e)}
     return ivec3(r, c, d);
   }
-`;let s=su(["r","c","d"],e);return`
+`;let s=nu(["r","c","d"],e);return`
     ivec3 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
                              vec2(${t[0]}, ${t[1]}));
@@ -421,10 +421,10 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(outTexShape[0], outTexShape[1]));
       int index = resTexRC.x * outTexShape[1] + resTexRC.y;
-      ${b2(["r","c","d","d2"],e)}
+      ${x2(["r","c","d","d2"],e)}
       return ivec4(r, c, d, d2);
     }
-  `;let s=su(["r","c","d","d2"],e);return`
+  `;let s=nu(["r","c","d","d2"],e);return`
     ivec4 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${t[0]}, ${t[1]}));
@@ -432,7 +432,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${s}
       return ivec4(r, c, d, d2);
     }
-  `}function _ee(e,t){let n=su(["r","c","d","d2","d3"],e);return`
+  `}function _ee(e,t){let n=nu(["r","c","d","d2","d3"],e);return`
     ivec5 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx * vec2(${t[0]},
                              ${t[1]}));
@@ -444,7 +444,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ivec5 outShape = ivec5(r, c, d, d2, d3);
       return outShape;
     }
-  `}function Dee(e,t){let n=su(["r","c","d","d2","d3","d4"],e);return`
+  `}function Dee(e,t){let n=nu(["r","c","d","d2","d3","d4"],e);return`
     ivec6 getOutputCoords() {
       ivec2 resTexRC = ivec2(resultUV.yx *
         vec2(${t[0]}, ${t[1]}));
@@ -542,7 +542,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       int c = index - r * ${e[1]};
       return ivec2(r, c);
     }
-  `}function ru(e){return`offset${e}`}function Fee(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),s=as();return`
+  `}function su(e){return`offset${e}`}function Fee(e){let t=e.name,n="get"+t.charAt(0).toUpperCase()+t.slice(1),s=as();return`
     vec4 ${n}() {
       return ${s.texture2D}(${t}, halfCR);
     }
@@ -550,7 +550,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       float ${s}() {
         return sampleTexture(${n}, halfCR);
       }
-    `;let o=ru(n);if(t)return`
+    `;let o=su(n);if(t)return`
     float ${s}() {
       vec2 uv = uvFromFlat(${n}TexShape[0], ${n}TexShape[1], ${o});
       return sampleTexture(${n}, uv);
@@ -575,13 +575,13 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     }
   `}function zee(e,t){let n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1);if(e.shapeInfo.isUniform)return`
       float ${s}(int index) {
-        ${rd(e)}
+        ${sd(e)}
       }
     `;let r=e.shapeInfo.texShape,a=r[0],o=r[1];if(o===1&&a===1)return`
       float ${s}(int index) {
         return sampleTexture(${n}, halfCR);
       }
-    `;let i=ru(n);return o===1?t?`
+    `;let i=su(n);return o===1?t?`
       float ${s}(int index) {
         vec2 uv = vec2(0.5, (float(index + ${i}) + 0.5) / float(${n}TexShape[0]));
         return sampleTexture(${n}, uv);
@@ -645,17 +645,17 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = (vec2(col, row) + halfCR) / vec2(${h}.0, ${d}.0);
       return sampleTexture(${s}, uv);
     }
-  `}let{newShape:o,keptDims:i}=v.squeezeShape(n),l=o;if(l.length<n.length){let d=ad(e,l),h=["row","col"];return`
-      ${sd(d,t)}
+  `}let{newShape:o,keptDims:i}=v.squeezeShape(n),l=o;if(l.length<n.length){let d=rd(e,l),h=["row","col"];return`
+      ${nd(d,t)}
       float ${r}(int row, int col) {
-        return ${r}(${od(h,i)});
+        return ${r}(${ad(h,i)});
       }
     `}if(e.shapeInfo.isUniform)return`
       float ${r}(int row, int col) {
         int index = round(dot(vec2(row, col), vec2(${n[1]}, 1)));
-        ${rd(e)}
+        ${sd(e)}
       }
-    `;let u=a[0],c=a[1],p=ru(s);return c===1?t?`
+    `;let u=a[0],c=a[1],p=su(s);return c===1?t?`
       float ${r}(int row, int col) {
         float index = dot(vec3(row, col, ${p}), vec3(${s}Shape[1], 1, 1));
         vec2 uv = vec2(0.5, (index + 0.5) / float(${s}TexShape[0]));
@@ -693,10 +693,10 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     vec2 uv = uvFromFlat(${u}, ${c}, index);
     return sampleTexture(${s}, uv);
   }
-`}function Wee(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=e.shapeInfo.texShape,o=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(n[0]===1){let d=n.slice(1),h=[1,2],f=ad(e,d),m=["b","row","col"];return`
+`}function Wee(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=e.shapeInfo.texShape,o=[Math.ceil(a[0]/2),Math.ceil(a[1]/2)];if(n[0]===1){let d=n.slice(1),h=[1,2],f=rd(e,d),m=["b","row","col"];return`
         ${OS(f,t)}
         vec4 ${r}(int b, int row, int col) {
-          return ${r}(${od(m,h)});
+          return ${r}(${ad(m,h)});
         }
       `}let i=as();if(t)return`
     vec4 ${r}(int b, int row, int col) {
@@ -713,16 +713,16 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         ${l}, ${u}, ${p}, ${c}, b, row, col);
       return ${i.texture2D}(${s}, uv);
     }
-  `}function Vee(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=n[1]*n[2],o=n[2],{newShape:i,keptDims:l}=v.squeezeShape(n),u=i;if(u.length<n.length){let m=ad(e,u),g=["row","col","depth"];return`
-        ${sd(m,t)}
+  `}function Vee(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=n[1]*n[2],o=n[2],{newShape:i,keptDims:l}=v.squeezeShape(n),u=i;if(u.length<n.length){let m=rd(e,u),g=["row","col","depth"];return`
+        ${nd(m,t)}
         float ${r}(int row, int col, int depth) {
-          return ${r}(${od(g,l)});
+          return ${r}(${ad(g,l)});
         }
       `}if(e.shapeInfo.isUniform)return`
       float ${r}(int row, int col, int depth) {
         int index = round(dot(vec3(row, col, depth),
                           vec3(${a}, ${o}, 1)));
-        ${rd(e)}
+        ${sd(e)}
       }
     `;let c=e.shapeInfo.texShape,p=c[0],d=c[1],h=e.shapeInfo.flatOffset;if(d===a&&h==null)return t?`
       float ${r}(int row, int col, int depth) {
@@ -755,7 +755,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${d}.0, ${p}.0);
       return sampleTexture(${s}, uv);
     }
-  `;let f=ru(s);return t?`
+  `;let f=su(s);return t?`
     float ${r}(int row, int col, int depth) {
       // Explicitly use integer operations as dot() only works on floats.
       int stride0 = ${s}Shape[1] * ${s}Shape[2];
@@ -791,16 +791,16 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = (vec2(texC, texR) + halfCR) / vec2(${c}, ${u});
       return ${r.texture2D}(${n}, uv);
     }
-  `}function Gee(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=n[3],o=n[2]*a,i=n[1]*o,{newShape:l,keptDims:u}=v.squeezeShape(n);if(l.length<n.length){let x=ad(e,l),A=["row","col","depth","depth2"];return`
-      ${sd(x,t)}
+  `}function Gee(e,t){let n=e.shapeInfo.logicalShape,s=e.name,r="get"+s.charAt(0).toUpperCase()+s.slice(1),a=n[3],o=n[2]*a,i=n[1]*o,{newShape:l,keptDims:u}=v.squeezeShape(n);if(l.length<n.length){let x=rd(e,l),A=["row","col","depth","depth2"];return`
+      ${nd(x,t)}
       float ${r}(int row, int col, int depth, int depth2) {
-        return ${r}(${od(A,u)});
+        return ${r}(${ad(A,u)});
       }
     `}if(e.shapeInfo.isUniform)return`
       float ${r}(int row, int col, int depth, int depth2) {
         int index = round(dot(vec4(row, col, depth, depth2),
                           vec4(${i}, ${o}, ${a}, 1)));
-        ${rd(e)}
+        ${sd(e)}
       }
     `;let c=e.shapeInfo.flatOffset,p=e.shapeInfo.texShape,d=p[0],h=p[1],f=`int stride2 = ${s}Shape[3];`,m=`int stride1 = ${s}Shape[2] * stride2;`,g=`int stride0 = ${s}Shape[1] * stride1;`;if(h===i&&c==null)return t?`
       float ${r}(int row, int col, int depth, int depth2) {
@@ -842,7 +842,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${h}.0, ${d}.0);
         return sampleTexture(${s}, uv);
       }
-    `;let y=ru(s);return t?`
+    `;let y=su(s);return t?`
     float ${r}(int row, int col, int depth, int depth2) {
       // Explicitly use integer operations as dot() only works on floats.
       ${f}
@@ -861,10 +861,10 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${d}, ${h}, index + ${y});
       return sampleTexture(${s}, uv);
     }
-  `}function Hee(e){let t=e.shapeInfo.logicalShape,n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),r=t[4],a=t[3]*r,o=t[2]*a,i=t[1]*o,{newShape:l,keptDims:u}=v.squeezeShape(t);if(l.length<t.length){let m=ad(e,l),g=["row","col","depth","depth2","depth3"];return`
-      ${sd(m)}
+  `}function Hee(e){let t=e.shapeInfo.logicalShape,n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),r=t[4],a=t[3]*r,o=t[2]*a,i=t[1]*o,{newShape:l,keptDims:u}=v.squeezeShape(t);if(l.length<t.length){let m=rd(e,l),g=["row","col","depth","depth2","depth3"];return`
+      ${nd(m)}
       float ${s}(int row, int col, int depth, int depth2, int depth3) {
-        return ${s}(${od(g,u)});
+        return ${s}(${ad(g,u)});
       }
     `}if(e.shapeInfo.isUniform)return`
       float ${s}(int row, int col, int depth, int depth2, int depth3) {
@@ -872,7 +872,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           vec4(row, col, depth, depth2),
           vec4(${i}, ${o}, ${a}, ${r})) +
           depth3;
-        ${rd(e)}
+        ${sd(e)}
       }
     `;let c=e.shapeInfo.flatOffset,p=e.shapeInfo.texShape,d=p[0],h=p[1];if(h===i&&c==null)return`
       float ${s}(int row, int col, int depth, int depth2, int depth3) {
@@ -894,7 +894,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${h}.0, ${d}.0);
         return sampleTexture(${n}, uv);
       }
-    `;let f=ru(n);return`
+    `;let f=su(n);return`
     float ${s}(int row, int col, int depth, int depth2, int depth3) {
       // Explicitly use integer operations as dot() only works on floats.
       int index = row * ${i} + col * ${o} + depth * ${a} +
@@ -902,11 +902,11 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${d}, ${h}, index);
       return sampleTexture(${n}, uv);
     }
-  `}function jee(e){let t=e.shapeInfo.logicalShape,n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:r,keptDims:a}=v.squeezeShape(t);if(r.length<t.length){let g=ad(e,r),y=["row","col","depth","depth2","depth3","depth4"];return`
-      ${sd(g)}
+  `}function jee(e){let t=e.shapeInfo.logicalShape,n=e.name,s="get"+n.charAt(0).toUpperCase()+n.slice(1),{newShape:r,keptDims:a}=v.squeezeShape(t);if(r.length<t.length){let g=rd(e,r),y=["row","col","depth","depth2","depth3","depth4"];return`
+      ${nd(g)}
       float ${s}(int row, int col, int depth,
                     int depth2, int depth3, int depth4) {
-        return ${s}(${od(y,a)});
+        return ${s}(${ad(y,a)});
       }
     `}let o=t[5],i=t[4]*o,l=t[3]*i,u=t[2]*l,c=t[1]*u;if(e.shapeInfo.isUniform)return`
       float ${s}(int row, int col, int depth,
@@ -917,7 +917,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
           dot(
             vec2(depth3, depth4),
             vec2(${o}, 1)));
-        ${rd(e)}
+        ${sd(e)}
       }
     `;let p=e.shapeInfo.flatOffset,d=e.shapeInfo.texShape,h=d[0],f=d[1];if(f===c&&p==null)return`
       float ${s}(int row, int col, int depth,
@@ -943,7 +943,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
                   vec2(${f}.0, ${h}.0);
         return sampleTexture(${n}, uv);
       }
-    `;let m=ru(n);return`
+    `;let m=su(n);return`
     float ${s}(int row, int col, int depth,
                   int depth2, int depth3, int depth4) {
       // Explicitly use integer operations as dot() only works on floats.
@@ -952,7 +952,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       vec2 uv = uvFromFlat(${h}, ${f}, index);
       return sampleTexture(${n}, uv);
     }
-  `}function rd(e){let t=e.name,n=v.sizeFromShape(e.shapeInfo.logicalShape);return n<2?`return ${t};`:`
+  `}function sd(e){let t=e.name,n=v.sizeFromShape(e.shapeInfo.logicalShape);return n<2?`return ${t};`:`
     for (int i = 0; i < ${n}; i++) {
       if (i == index) {
         return ${t}[i];
@@ -983,9 +983,9 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       ${d}
       return get${s}(${f});
     }
-  `}function wt(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function Gx(e,t,n){let{newShape:s,keptDims:r}=v.squeezeShape(t),a=t.length,o=e&&a===3&&t[0]===1,i=o?t.slice(1):s,l=!e&&a>1&&!v.arraysEqual(t,n)&&s.length<a||o;return{useSqueezeShape:l,uniformShape:l?i:t,keptDims:r}}function ad(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function od(e,t){return t.map(n=>e[n]).join(", ")}function Kee(e,t,n,s){let r=n.map((c,p)=>{let d={logicalShape:c.shape,texShape:c.isUniform?null:c.texData.texShape,isUniform:c.isUniform,isPacked:c.isUniform?!1:c.texData.isPacked,flatOffset:null};return c.texData!=null&&c.texData.slice!=null&&c.texData.slice.flatOffset>0&&(d.flatOffset=c.texData.slice.flatOffset),{name:t.variableNames[p],shapeInfo:d}}),a=r.map(c=>c.shapeInfo),o={logicalShape:s.shape,texShape:s.texData.texShape,isUniform:!1,isPacked:s.texData.isPacked,flatOffset:null},i=hee(r,o,t),l=hS(e.gl,i),u=e.createProgram(l);return Z().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:l,source:i,webGLProgram:u,inShapeInfos:a,outShapeInfo:o,uniformLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,inShapesLocations:null,inTexShapesLocations:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:Object.assign({program:t,fragmentShader:l,source:i,webGLProgram:u,inShapeInfos:a,outShapeInfo:o},zS(e,t,u))}function zS(e,t,n){let s={},r={},a={},o=[],i,l,u,c=null,p=null;p=e.getUniformLocation(n,"NAN",!1),Z().getNumber("WEBGL_VERSION")===1&&(c=e.getUniformLocation(n,"INFINITY",!1));let d=!1;for(let h=0;h<t.variableNames.length;h++){let f=t.variableNames[h];s[f]=e.getUniformLocation(n,f,d),s[`offset${f}`]=e.getUniformLocation(n,`offset${f}`,d),t.enableShapeUniforms&&(r[`${f}Shape`]=e.getUniformLocation(n,`${f}Shape`,d),a[`${f}TexShape`]=e.getUniformLocation(n,`${f}TexShape`,d))}return t.enableShapeUniforms&&(i=e.getUniformLocation(n,"outShape",d),u=e.getUniformLocation(n,"outShapeStrides",d),l=e.getUniformLocation(n,"outTexShape",d)),t.customUniforms&&t.customUniforms.forEach((h,f)=>{o[f]=e.getUniformLocation(n,h.name,d)}),{uniformLocations:s,customUniformLocations:o,infLoc:c,nanLoc:p,inShapesLocations:r,inTexShapesLocations:a,outShapeLocation:i,outShapeStridesLocation:u,outTexShapeLocation:l}}function d7(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((n,s)=>{let r=n.logicalShape,a=t[s],o=a.shape;if(!v.arraysEqual(r,o))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${r} and ${o} must match`);if(n.isUniform&&a.isUniform)return;let i=n.texShape,l=a.isUniform?null:a.texData.texShape;if(!v.arraysEqual(i,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${i} and ${l} must match`)})}function Zee(e,t,n,s,r){t.program.enableShapeUniforms||(d7(t.inShapeInfos,n),d7([t.outShapeInfo],[s]));let a=s.texData.texture,o=s.texData.texShape;s.texData.isPacked?e.setOutputPackedMatrixTexture(a.texture,o[0],o[1]):e.setOutputMatrixTexture(a.texture,o[0],o[1]),e.setProgram(t.webGLProgram),Z().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((l,u)=>{let c=t.program.variableNames[u],p=t.uniformLocations[c],d=t.uniformLocations[`offset${c}`],h=t.inShapesLocations[`${c}Shape`],f=t.inTexShapesLocations[`${c}TexShape`];if(h){let{uniformShape:m}=Gx(t.program.packedInputs,l.shape,l.texData.texShape);switch(m.length){case 1:e.gl.uniform1iv(h,new Int32Array(m));break;case 2:e.gl.uniform2iv(h,new Int32Array(m));break;case 3:e.gl.uniform3iv(h,new Int32Array(m));break;case 4:e.gl.uniform4iv(h,new Int32Array(m));break;default:break}}if(f&&e.gl.uniform2i(f,l.texData.texShape[0],l.texData.texShape[1]),p!=null){if(l.isUniform){if(v.sizeFromShape(l.shape)<2)e.gl.uniform1f(p,l.uniformValues[0]);else{let m=l.uniformValues;m instanceof Float32Array||(m=new Float32Array(m)),e.gl.uniform1fv(p,m)}return}l.texData.slice!=null&&d!=null&&e.gl.uniform1i(d,l.texData.slice.flatOffset),e.setInputMatrixTexture(l.texData.texture.texture,p,u)}});let i=t.outShapeLocation;if(i)switch(s.shape.length){case 1:e.gl.uniform1iv(i,new Int32Array(s.shape));break;case 2:e.gl.uniform2iv(i,new Int32Array(s.shape));break;case 3:e.gl.uniform3iv(i,new Int32Array(s.shape));break;case 4:e.gl.uniform4iv(i,new Int32Array(s.shape));break;default:break}if(t.outShapeStridesLocation){let l=v.computeStrides(s.shape);switch(s.shape.length){case 2:e.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(l));break;case 3:e.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(l));break;case 4:e.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(l));break;default:break}}t.outTexShapeLocation&&e.gl.uniform2i(t.outTexShapeLocation,s.texData.texShape[0],s.texData.texShape[1]),t.program.customUniforms&&r&&t.program.customUniforms.forEach((l,u)=>{let c=t.customUniformLocations[u],p=r[u];if(l.type==="float")e.gl.uniform1fv(c,p);else if(l.type==="vec2")e.gl.uniform2fv(c,p);else if(l.type==="vec3")e.gl.uniform3fv(c,p);else if(l.type==="vec4")e.gl.uniform4fv(c,p);else if(l.type==="int")e.gl.uniform1iv(c,p);else if(l.type==="ivec2")e.gl.uniform2iv(c,p);else if(l.type==="ivec3")e.gl.uniform3iv(c,p);else if(l.type==="ivec4")e.gl.uniform4iv(c,p);else throw Error(`uniform type ${l.type} is not supported yet.`)}),e.executeProgram()}function Yee(e,t,n){let s="";t.concat(n).forEach(o=>{let i=o.texData!=null&&o.texData.slice!=null&&o.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!o.isUniform){let l=o.texData.texShape,{useSqueezeShape:u,uniformShape:c,keptDims:p}=Gx(e.packedInputs,o.shape,l),d="",h="",f="";if(c.length===1&&e.packedInputs){let w=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];d=`${w[0]>1}_${w[1]>1}`}else if(c.length===2&&!e.packedInputs)h=`${c[0]>1}_${c[1]>1}`;else if(c.length>2&&!e.packedInputs){let w=v.computeStrides(c);f=`${w[0]===l[1]}_${w[w.length-1]===l[1]}`}let m=o.shape.length,g=c.length===2&&v.arraysEqual(o.shape,l),y=v.sizeFromShape(o.shape)===1,x=C.getBroadcastDims(o.shape,n.shape),A=!e.packedInputs&&m===n.shape.length&&v.arraysEqual(l,n.texData.texShape),b=e.packedInputs||c.length>2?"":`${l[0]>1}_${l[1]>1}`;s+=`${m}_${A}_${u?p:""}_${c.length}_${y}_${x}_${g}_${d}_${h}_${f}_${b}_${i}`}else{let l=o.isUniform?"uniform":o.texData.texShape;s+=`${o.shape}_${l}_${i}`}});let r=e.userCode,a=e.constructor.name;return a+="_"+s+"_"+r+`${Z().getNumber("WEBGL_VERSION")}`,a}function xs(e){return Z().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var Jee=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=_p.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=as();this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
+  `}function wt(e){if(e<=1)return"int";if(e===2)return"ivec2";if(e===3)return"ivec3";if(e===4)return"ivec4";if(e===5)return"ivec5";if(e===6)return"ivec6";throw Error(`GPU for rank ${e} is not yet supported`)}function Gx(e,t,n){let{newShape:s,keptDims:r}=v.squeezeShape(t),a=t.length,o=e&&a===3&&t[0]===1,i=o?t.slice(1):s,l=!e&&a>1&&!v.arraysEqual(t,n)&&s.length<a||o;return{useSqueezeShape:l,uniformShape:l?i:t,keptDims:r}}function rd(e,t){let n=JSON.parse(JSON.stringify(e));return n.shapeInfo.logicalShape=t,n}function ad(e,t){return t.map(n=>e[n]).join(", ")}function Kee(e,t,n,s){let r=n.map((c,p)=>{let d={logicalShape:c.shape,texShape:c.isUniform?null:c.texData.texShape,isUniform:c.isUniform,isPacked:c.isUniform?!1:c.texData.isPacked,flatOffset:null};return c.texData!=null&&c.texData.slice!=null&&c.texData.slice.flatOffset>0&&(d.flatOffset=c.texData.slice.flatOffset),{name:t.variableNames[p],shapeInfo:d}}),a=r.map(c=>c.shapeInfo),o={logicalShape:s.shape,texShape:s.texData.texShape,isUniform:!1,isPacked:s.texData.isPacked,flatOffset:null},i=hee(r,o,t),l=hS(e.gl,i),u=e.createProgram(l);return X().get("ENGINE_COMPILE_ONLY")?{program:t,fragmentShader:l,source:i,webGLProgram:u,inShapeInfos:a,outShapeInfo:o,uniformLocations:null,customUniformLocations:null,infLoc:null,nanLoc:null,inShapesLocations:null,inTexShapesLocations:null,outShapeLocation:null,outShapeStridesLocation:null,outTexShapeLocation:null}:Object.assign({program:t,fragmentShader:l,source:i,webGLProgram:u,inShapeInfos:a,outShapeInfo:o},zS(e,t,u))}function zS(e,t,n){let s={},r={},a={},o=[],i,l,u,c=null,p=null;p=e.getUniformLocation(n,"NAN",!1),X().getNumber("WEBGL_VERSION")===1&&(c=e.getUniformLocation(n,"INFINITY",!1));let d=!1;for(let h=0;h<t.variableNames.length;h++){let f=t.variableNames[h];s[f]=e.getUniformLocation(n,f,d),s[`offset${f}`]=e.getUniformLocation(n,`offset${f}`,d),t.enableShapeUniforms&&(r[`${f}Shape`]=e.getUniformLocation(n,`${f}Shape`,d),a[`${f}TexShape`]=e.getUniformLocation(n,`${f}TexShape`,d))}return t.enableShapeUniforms&&(i=e.getUniformLocation(n,"outShape",d),u=e.getUniformLocation(n,"outShapeStrides",d),l=e.getUniformLocation(n,"outTexShape",d)),t.customUniforms&&t.customUniforms.forEach((h,f)=>{o[f]=e.getUniformLocation(n,h.name,d)}),{uniformLocations:s,customUniformLocations:o,infLoc:c,nanLoc:p,inShapesLocations:r,inTexShapesLocations:a,outShapeLocation:i,outShapeStridesLocation:u,outTexShapeLocation:l}}function d7(e,t){if(e.length!==t.length)throw Error(`Binary was compiled with ${e.length} inputs, but was executed with ${t.length} inputs`);e.forEach((n,s)=>{let r=n.logicalShape,a=t[s],o=a.shape;if(!v.arraysEqual(r,o))throw Error(`Binary was compiled with different shapes than the current args. Shapes ${r} and ${o} must match`);if(n.isUniform&&a.isUniform)return;let i=n.texShape,l=a.isUniform?null:a.texData.texShape;if(!v.arraysEqual(i,l))throw Error(`Binary was compiled with different texture shapes than the current args. Shape ${i} and ${l} must match`)})}function Zee(e,t,n,s,r){t.program.enableShapeUniforms||(d7(t.inShapeInfos,n),d7([t.outShapeInfo],[s]));let a=s.texData.texture,o=s.texData.texShape;s.texData.isPacked?e.setOutputPackedMatrixTexture(a.texture,o[0],o[1]):e.setOutputMatrixTexture(a.texture,o[0],o[1]),e.setProgram(t.webGLProgram),X().getNumber("WEBGL_VERSION")===1&&t.infLoc!==null&&e.gl.uniform1f(t.infLoc,1/0),t.nanLoc!==null&&e.gl.uniform1f(t.nanLoc,NaN),n.forEach((l,u)=>{let c=t.program.variableNames[u],p=t.uniformLocations[c],d=t.uniformLocations[`offset${c}`],h=t.inShapesLocations[`${c}Shape`],f=t.inTexShapesLocations[`${c}TexShape`];if(h){let{uniformShape:m}=Gx(t.program.packedInputs,l.shape,l.texData.texShape);switch(m.length){case 1:e.gl.uniform1iv(h,new Int32Array(m));break;case 2:e.gl.uniform2iv(h,new Int32Array(m));break;case 3:e.gl.uniform3iv(h,new Int32Array(m));break;case 4:e.gl.uniform4iv(h,new Int32Array(m));break;default:break}}if(f&&e.gl.uniform2i(f,l.texData.texShape[0],l.texData.texShape[1]),p!=null){if(l.isUniform){if(v.sizeFromShape(l.shape)<2)e.gl.uniform1f(p,l.uniformValues[0]);else{let m=l.uniformValues;m instanceof Float32Array||(m=new Float32Array(m)),e.gl.uniform1fv(p,m)}return}l.texData.slice!=null&&d!=null&&e.gl.uniform1i(d,l.texData.slice.flatOffset),e.setInputMatrixTexture(l.texData.texture.texture,p,u)}});let i=t.outShapeLocation;if(i)switch(s.shape.length){case 1:e.gl.uniform1iv(i,new Int32Array(s.shape));break;case 2:e.gl.uniform2iv(i,new Int32Array(s.shape));break;case 3:e.gl.uniform3iv(i,new Int32Array(s.shape));break;case 4:e.gl.uniform4iv(i,new Int32Array(s.shape));break;default:break}if(t.outShapeStridesLocation){let l=v.computeStrides(s.shape);switch(s.shape.length){case 2:e.gl.uniform1iv(t.outShapeStridesLocation,new Int32Array(l));break;case 3:e.gl.uniform2iv(t.outShapeStridesLocation,new Int32Array(l));break;case 4:e.gl.uniform3iv(t.outShapeStridesLocation,new Int32Array(l));break;default:break}}t.outTexShapeLocation&&e.gl.uniform2i(t.outTexShapeLocation,s.texData.texShape[0],s.texData.texShape[1]),t.program.customUniforms&&r&&t.program.customUniforms.forEach((l,u)=>{let c=t.customUniformLocations[u],p=r[u];if(l.type==="float")e.gl.uniform1fv(c,p);else if(l.type==="vec2")e.gl.uniform2fv(c,p);else if(l.type==="vec3")e.gl.uniform3fv(c,p);else if(l.type==="vec4")e.gl.uniform4fv(c,p);else if(l.type==="int")e.gl.uniform1iv(c,p);else if(l.type==="ivec2")e.gl.uniform2iv(c,p);else if(l.type==="ivec3")e.gl.uniform3iv(c,p);else if(l.type==="ivec4")e.gl.uniform4iv(c,p);else throw Error(`uniform type ${l.type} is not supported yet.`)}),e.executeProgram()}function Yee(e,t,n){let s="";t.concat(n).forEach(o=>{let i=o.texData!=null&&o.texData.slice!=null&&o.texData.slice.flatOffset>0;if(e.enableShapeUniforms&&!o.isUniform){let l=o.texData.texShape,{useSqueezeShape:u,uniformShape:c,keptDims:p}=Gx(e.packedInputs,o.shape,l),d="",h="",f="";if(c.length===1&&e.packedInputs){let w=[Math.ceil(l[0]/2),Math.ceil(l[1]/2)];d=`${w[0]>1}_${w[1]>1}`}else if(c.length===2&&!e.packedInputs)h=`${c[0]>1}_${c[1]>1}`;else if(c.length>2&&!e.packedInputs){let w=v.computeStrides(c);f=`${w[0]===l[1]}_${w[w.length-1]===l[1]}`}let m=o.shape.length,g=c.length===2&&v.arraysEqual(o.shape,l),y=v.sizeFromShape(o.shape)===1,x=C.getBroadcastDims(o.shape,n.shape),A=!e.packedInputs&&m===n.shape.length&&v.arraysEqual(l,n.texData.texShape),b=e.packedInputs||c.length>2?"":`${l[0]>1}_${l[1]>1}`;s+=`${m}_${A}_${u?p:""}_${c.length}_${y}_${x}_${g}_${d}_${h}_${f}_${b}_${i}`}else{let l=o.isUniform?"uniform":o.texData.texShape;s+=`${o.shape}_${l}_${i}`}});let r=e.userCode,a=e.constructor.name;return a+="_"+s+"_"+r+`${X().getNumber("WEBGL_VERSION")}`,a}function xs(e){return X().getBool("WEBGL_USE_SHAPES_UNIFORMS")&&e<=4}var Jee=class{constructor(e){this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outPackingScheme=Rp.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=as();this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
-        ${this.enableShapeUniforms?b2(["r","c","d"],e):su(["r","c","d"],e)}
+        ${this.enableShapeUniforms?x2(["r","c","d"],e):nu(["r","c","d"],e)}
         return ivec3(r, c, d);
       }
 
@@ -1003,9 +1003,9 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         ${t.output} = result;
       }
-    `}},Qee=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=_p.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=as();this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
+    `}},Qee=class{constructor(e){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outPackingScheme=Rp.DENSE,this.customUniforms=[{name:"texShape",type:"ivec2"}];let t=as();this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
       ivec3 outCoordsFromFlatIndex(int index) {
-        ${this.enableShapeUniforms?b2(["r","c","d"],e):su(["r","c","d"],e)}
+        ${this.enableShapeUniforms?x2(["r","c","d"],e):nu(["r","c","d"],e)}
         return ivec3(r, c, d);
       }
 
@@ -1121,7 +1121,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
     void main() {
       gl_Position = vec4(clipSpacePos, 1);
       resultUV = uv;
-    }`;return pS(e,n)}function WS(e){let t=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return gS(e,t)}function VS(e){let t=new Uint16Array([0,1,2,2,1,3]);return yS(e,t)}function Oh(e,t,n,s,r,a){xS(t,n);let o=AS(e),i=e.TEXTURE_2D;return Ie(e,()=>e.bindTexture(i,o)),Ie(e,()=>e.texParameteri(i,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),Ie(e,()=>e.texParameteri(i,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),Ie(e,()=>e.texParameteri(i,e.TEXTURE_MIN_FILTER,e.NEAREST)),Ie(e,()=>e.texParameteri(i,e.TEXTURE_MAG_FILTER,e.NEAREST)),Z().getNumber("WEBGL_VERSION")===1?Ie(e,()=>e.texImage2D(i,0,s,t,n,0,r,a,null)):Ie(e,()=>e.texStorage2D(i,1,s,t,n)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,null)),{texture:o,texShape:[n,t]}}function Hx(e){return e.internalFormatFloat}function US(e,t,n,s){let[r,a]=Fh(t,n);return Oh(e,r,a,Hx(s),s.textureFormatFloat,e.FLOAT)}function jx(e){return e.internalFormatHalfFloat}function GS(e,t,n,s){let[r,a]=Fh(t,n);return Oh(e,r,a,jx(s),s.textureFormatFloat,s.textureTypeHalfFloat)}function qx(e){return e.downloadTextureFormat}function HS(e,t,n,s){let[r,a]=Fh(t,n);return Oh(e,r,a,qx(s),e.RGBA,e.UNSIGNED_BYTE)}function Xx(e){return e.internalFormatPackedFloat}function jS(e,t,n,s){let[r,a]=td(t,n);return Oh(e,r,a,Xx(s),e.RGBA,e.FLOAT)}function Kx(e){return e.internalFormatPackedHalfFloat}function qS(e,t,n,s){let[r,a]=td(t,n);return Oh(e,r,a,Kx(s),e.RGBA,s.textureTypeHalfFloat)}function XS(e,t,n){return Ie(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),ny(e,t,"clipSpacePos",n,3,20,0)&&ny(e,t,"uv",n,2,20,12)}function KS(e,t,n,s,r,a){Ie(e,()=>e.bindTexture(e.TEXTURE_2D,t));let o,i,l;r instanceof Uint8Array?(o=new Uint8Array(n*s*4),i=e.UNSIGNED_BYTE,l=e.RGBA):(o=new Float32Array(n*s*4),i=e.FLOAT,l=a.internalFormatPackedFloat),o.set(r),Z().getNumber("WEBGL_VERSION")===2?Ie(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,n,s,e.RGBA,i,o)):Ie(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,s,0,e.RGBA,i,o)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function ZS(e,t,n){Ie(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?Z().getNumber("WEBGL_VERSION")===2?Ie(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,n.width,n.height,e.RGBA,e.UNSIGNED_BYTE,n.data)):Ie(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):Z().getNumber("WEBGL_VERSION")===2?Ie(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,e.RGBA,e.UNSIGNED_BYTE,n)):Ie(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function YS(e,t,n,s){let r=e.createBuffer();Ie(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,r));let i=4*4*t*n;return Ie(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,i,e.STREAM_READ)),Ie(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),Ie(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),r}function JS(e,t,n){let s=e,r=new Float32Array(n);return s.bindBuffer(s.PIXEL_PACK_BUFFER,t),s.getBufferSubData(s.PIXEL_PACK_BUFFER,0,r),s.bindBuffer(s.PIXEL_PACK_BUFFER,null),r}function QS(e,t,n,s){let[r,a]=Fh(t,n),o=4,i=new Uint8Array(QQ(t*n,o));return Ie(e,()=>e.readPixels(0,0,r,a,s.downloadTextureFormat,e.UNSIGNED_BYTE,i)),new Float32Array(i.buffer)}function e9(e,t,n,s,r,a,o,i){let l=e,u=new Float32Array(eee(a,o));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,u),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),u}function t9(e,t,n){let s=new Float32Array(t*n*4);return Ie(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,s)),s}var ju=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=Z().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,x2(t,e)):this.gl=Dr(t);let n="WEBGL_color_buffer_float",s="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),Z().getNumber("WEBGL_VERSION")===1){let r="OES_texture_float",a="OES_texture_half_float";if(this.textureFloatExtension=up(this.gl,r),Xs(this.gl,a))this.textureHalfFloatExtension=up(this.gl,a);else if(Z().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(n),Xs(this.gl,s))this.colorBufferHalfFloatExtension=up(this.gl,s);else if(Z().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",Xs(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(Xs(this.gl,s))this.colorBufferHalfFloatExtension=this.gl.getExtension(s);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=WS(this.gl),this.indexBuffer=VS(this.gl),this.framebuffer=bS(this.gl),this.textureConfig=Bx(this.gl,this.textureHalfFloatExtension)}get debug(){return Z().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),this.outputTexture!=null&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let e=this.gl;Ie(e,()=>e.finish()),Ie(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),Ie(e,()=>e.deleteFramebuffer(this.framebuffer)),Ie(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),Ie(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),Ie(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),US(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),GS(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),HS(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),ZS(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,s){this.throwIfDisposed(),KS(this.gl,e,t,n,s,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),qS(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),jS(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(sy(this.gl,this.framebuffer),this.outputTexture=null),Ie(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>QS(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,s,r,a){return e9(this.gl,e,t,n,s,r,a,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return JS(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let s=YS(this.gl,t,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),s}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,n;if(Z().getBool("WEBGL_FENCE_API_ENABLED")){let s=e,r=s.fenceSync(s.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let a=s.clientWaitSync(r,0,0);return a===s.ALREADY_SIGNALED||a===s.CONDITION_SATISFIED},t=r}else Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>t9(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl;this.vertexShader==null&&(this.vertexShader=BS(t));let n=fS(t);return Ie(t,()=>t.attachShader(n,this.vertexShader)),Ie(t,()=>t.attachShader(n,e)),mS(t,n),this.debug&&nm(t,n),this.vertexAttrsAreBound||(this.setProgram(n),this.vertexAttrsAreBound=XS(t,this.program,this.vertexBuffer)),n}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&Ie(this.gl,()=>this.gl.deleteProgram(e))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&nm(this.gl,this.program),Ie(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?wS(this.gl,e,t):kS(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),Ie(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,n){this.throwIfDisposed(),this.throwIfNoProgram(),IS(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[s,r]=td(t,n);this.setOutputMatrixTextureDriver(e,s,r)}setOutputMatrixWriteRegion(e,t,n,s){this.setOutputMatrixWriteRegionDriver(n,e,s,t)}setOutputPackedMatrixWriteRegion(e,t,n,s){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&nm(this.gl,this.program),cp(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&this.debugValidate(),Ie(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),Ie(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=up(this.gl,Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension}getQueryTimerExtensionWebGL2(){return this.getQueryTimerExtension()}getQueryTimerExtensionWebGL1(){return this.getQueryTimerExtension()}beginQuery(){if(Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,s=this.getQueryTimerExtensionWebGL2(),r=n.createQuery();return n.beginQuery(s.TIME_ELAPSED_EXT,r),r}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,n=this.getQueryTimerExtensionWebGL2();t.endQuery(n.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await v.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let n=this.gl;return n.getQueryParameter(e,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(e,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let n=this.gl,s=this.getQueryTimerExtensionWebGL2(),r=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(s.GPU_DISJOINT_EXT)),r&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),s=n.getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),s&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=rte(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:n}=this.itemsToPoll[t];n()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),!(this.itemsToPoll.length>1)&&v.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0))}bindTextureToFrameBuffer(e){this.throwIfDisposed(),sm(this.gl,e,this.framebuffer),this.debug&&cp(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(sm(this.gl,this.outputTexture,this.framebuffer),this.debug&&cp(this.gl)):sy(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let n=t();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(e,t,n){this.throwIfDisposed();let s=this.gl;sm(s,e,this.framebuffer),this.debug&&cp(s),this.outputTexture=e,Ie(s,()=>s.viewport(0,0,t,n)),Ie(s,()=>s.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,s){this.throwIfDisposed(),Ie(this.gl,()=>this.gl.scissor(e,t,n,s))}throwIfDisposed(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")}throwIfNoProgram(){if(this.program==null)throw new Error("No GPU program is currently set.")}};function rte(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{addImpl:ate,bincountImpl:n9,bincountReduceImpl:ote,ceilImpl:ite,concatImpl:lte,equalImpl:ute,expImpl:cte,expm1Impl:dte,floorImpl:pte,gatherNdImpl:hte,gatherV2Impl:fte,greaterImpl:mte,greaterEqualImpl:gte,lessImpl:yte,lessEqualImpl:Ate,linSpaceImpl:xte,logImpl:bte,maxImpl:vte,maximumImpl:wte,minimumImpl:kte,multiplyImpl:Ite,negImpl:Ste,notEqualImpl:Cte,prodImpl:Tte,rangeImpl:Nte,rsqrtImpl:Ete,scatterImpl:Rte,sigmoidImpl:_te,simpleAbsImpl:s9,sliceImpl:Dte,sparseFillEmptyRowsImpl:$te,sparseReshapeImpl:Pte,sparseSegmentReductionImpl:r9,sqrtImpl:Fte,stridedSliceImpl:Ote,stringNGramsImpl:Mte,stringSplitImpl:zte,stringToHashBucketFastImpl:Lte,subImpl:Bte,tileImpl:Wte,topKImpl:Vte,transposeImpl:Zx,uniqueImpl:Ute}=Sx;function a9(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function Qn(e,t){return t===1?[e]:a9(e,t)}function Gte(e,t){if(e===1)return"rc";let n="";for(let s=0;s<e;s++)n+=t[s],s<e-1&&(n+=",");return n}var Hte=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=xs(this.outputShape.length),this.rank===0)this.userCode=`
+    }`;return pS(e,n)}function WS(e){let t=new Float32Array([-1,1,0,0,1,-1,-1,0,0,0,1,1,0,1,1,1,-1,0,1,0]);return gS(e,t)}function VS(e){let t=new Uint16Array([0,1,2,2,1,3]);return yS(e,t)}function Fh(e,t,n,s,r,a){xS(t,n);let o=AS(e),i=e.TEXTURE_2D;return Ie(e,()=>e.bindTexture(i,o)),Ie(e,()=>e.texParameteri(i,e.TEXTURE_WRAP_S,e.CLAMP_TO_EDGE)),Ie(e,()=>e.texParameteri(i,e.TEXTURE_WRAP_T,e.CLAMP_TO_EDGE)),Ie(e,()=>e.texParameteri(i,e.TEXTURE_MIN_FILTER,e.NEAREST)),Ie(e,()=>e.texParameteri(i,e.TEXTURE_MAG_FILTER,e.NEAREST)),X().getNumber("WEBGL_VERSION")===1?Ie(e,()=>e.texImage2D(i,0,s,t,n,0,r,a,null)):Ie(e,()=>e.texStorage2D(i,1,s,t,n)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,null)),{texture:o,texShape:[n,t]}}function Hx(e){return e.internalFormatFloat}function US(e,t,n,s){let[r,a]=Ph(t,n);return Fh(e,r,a,Hx(s),s.textureFormatFloat,e.FLOAT)}function jx(e){return e.internalFormatHalfFloat}function GS(e,t,n,s){let[r,a]=Ph(t,n);return Fh(e,r,a,jx(s),s.textureFormatFloat,s.textureTypeHalfFloat)}function qx(e){return e.downloadTextureFormat}function HS(e,t,n,s){let[r,a]=Ph(t,n);return Fh(e,r,a,qx(s),e.RGBA,e.UNSIGNED_BYTE)}function Xx(e){return e.internalFormatPackedFloat}function jS(e,t,n,s){let[r,a]=ed(t,n);return Fh(e,r,a,Xx(s),e.RGBA,e.FLOAT)}function Kx(e){return e.internalFormatPackedHalfFloat}function qS(e,t,n,s){let[r,a]=ed(t,n);return Fh(e,r,a,Kx(s),e.RGBA,s.textureTypeHalfFloat)}function XS(e,t,n){return Ie(e,()=>e.bindBuffer(e.ARRAY_BUFFER,n)),ty(e,t,"clipSpacePos",n,3,20,0)&&ty(e,t,"uv",n,2,20,12)}function KS(e,t,n,s,r,a){Ie(e,()=>e.bindTexture(e.TEXTURE_2D,t));let o,i,l;r instanceof Uint8Array?(o=new Uint8Array(n*s*4),i=e.UNSIGNED_BYTE,l=e.RGBA):(o=new Float32Array(n*s*4),i=e.FLOAT,l=a.internalFormatPackedFloat),o.set(r),X().getNumber("WEBGL_VERSION")===2?Ie(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,n,s,e.RGBA,i,o)):Ie(e,()=>e.texImage2D(e.TEXTURE_2D,0,l,n,s,0,e.RGBA,i,o)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function ZS(e,t,n){Ie(e,()=>e.bindTexture(e.TEXTURE_2D,t)),n.data instanceof Uint8Array?X().getNumber("WEBGL_VERSION")===2?Ie(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,n.width,n.height,e.RGBA,e.UNSIGNED_BYTE,n.data)):Ie(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,n.width,n.height,0,e.RGBA,e.UNSIGNED_BYTE,n.data)):X().getNumber("WEBGL_VERSION")===2?Ie(e,()=>e.texSubImage2D(e.TEXTURE_2D,0,0,0,e.RGBA,e.UNSIGNED_BYTE,n)):Ie(e,()=>e.texImage2D(e.TEXTURE_2D,0,e.RGBA,e.RGBA,e.UNSIGNED_BYTE,n)),Ie(e,()=>e.bindTexture(e.TEXTURE_2D,null))}function YS(e,t,n,s){let r=e.createBuffer();Ie(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,r));let i=4*4*t*n;return Ie(e,()=>e.bufferData(e.PIXEL_PACK_BUFFER,i,e.STREAM_READ)),Ie(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,0)),Ie(e,()=>e.bindBuffer(e.PIXEL_PACK_BUFFER,null)),r}function JS(e,t,n){let s=e,r=new Float32Array(n);return s.bindBuffer(s.PIXEL_PACK_BUFFER,t),s.getBufferSubData(s.PIXEL_PACK_BUFFER,0,r),s.bindBuffer(s.PIXEL_PACK_BUFFER,null),r}function QS(e,t,n,s){let[r,a]=Ph(t,n),o=4,i=new Uint8Array(QQ(t*n,o));return Ie(e,()=>e.readPixels(0,0,r,a,s.downloadTextureFormat,e.UNSIGNED_BYTE,i)),new Float32Array(i.buffer)}function e9(e,t,n,s,r,a,o,i){let l=e,u=new Float32Array(eee(a,o));return l.bindBuffer(l.PIXEL_PACK_BUFFER,t),l.getBufferSubData(l.PIXEL_PACK_BUFFER,0,u),l.bindBuffer(l.PIXEL_PACK_BUFFER,null),u}function t9(e,t,n){let s=new Float32Array(t*n*4);return Ie(e,()=>e.readPixels(0,0,n,t,e.RGBA,e.FLOAT,s)),s}var Hu=class{constructor(e){this.outputTexture=null,this.program=null,this.disposed=!1,this.vertexAttrsAreBound=!1,this.itemsToPoll=[];let t=X().getNumber("WEBGL_VERSION");e!=null?(this.gl=e,A2(t,e)):this.gl=Dr(t);let n="WEBGL_color_buffer_float",s="EXT_color_buffer_half_float";if(this.parallelCompilationExtension=this.gl.getExtension("KHR_parallel_shader_compile"),X().getNumber("WEBGL_VERSION")===1){let r="OES_texture_float",a="OES_texture_half_float";if(this.textureFloatExtension=lp(this.gl,r),Xs(this.gl,a))this.textureHalfFloatExtension=lp(this.gl,a);else if(X().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support half float textures, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.");if(this.colorBufferFloatExtension=this.gl.getExtension(n),Xs(this.gl,s))this.colorBufferHalfFloatExtension=lp(this.gl,s);else if(X().get("WEBGL_FORCE_F16_TEXTURES"))throw new Error("GL context does not support color renderable half floats, yet the environment flag WEBGL_FORCE_F16_TEXTURES is set to true.")}else if(n="EXT_color_buffer_float",Xs(this.gl,n))this.colorBufferFloatExtension=this.gl.getExtension(n);else if(Xs(this.gl,s))this.colorBufferHalfFloatExtension=this.gl.getExtension(s);else throw new Error("GL context does not support color renderable floats");this.vertexBuffer=WS(this.gl),this.indexBuffer=VS(this.gl),this.framebuffer=bS(this.gl),this.textureConfig=Bx(this.gl,this.textureHalfFloatExtension)}get debug(){return X().getBool("DEBUG")}dispose(){if(this.disposed)return;this.program!=null&&console.warn("Disposing a GPGPUContext that still has a bound WebGLProgram. This is probably a resource leak, delete the program with GPGPUContext.deleteProgram before disposing."),this.outputTexture!=null&&console.warn("Disposing a GPGPUContext that still has a bound output matrix texture.  This is probably a resource leak, delete the output matrix texture with GPGPUContext.deleteMatrixTexture before disposing.");let e=this.gl;Ie(e,()=>e.finish()),Ie(e,()=>e.bindFramebuffer(e.FRAMEBUFFER,null)),Ie(e,()=>e.deleteFramebuffer(this.framebuffer)),Ie(e,()=>e.bindBuffer(e.ARRAY_BUFFER,null)),Ie(e,()=>e.bindBuffer(e.ELEMENT_ARRAY_BUFFER,null)),Ie(e,()=>e.deleteBuffer(this.indexBuffer)),this.disposed=!0}createFloat32MatrixTexture(e,t){return this.throwIfDisposed(),US(this.gl,e,t,this.textureConfig)}createFloat16MatrixTexture(e,t){return this.throwIfDisposed(),GS(this.gl,e,t,this.textureConfig)}createUnsignedBytesMatrixTexture(e,t){return this.throwIfDisposed(),HS(this.gl,e,t,this.textureConfig)}uploadPixelDataToTexture(e,t){this.throwIfDisposed(),ZS(this.gl,e,t)}uploadDenseMatrixToTexture(e,t,n,s){this.throwIfDisposed(),KS(this.gl,e,t,n,s,this.textureConfig)}createFloat16PackedMatrixTexture(e,t){return this.throwIfDisposed(),qS(this.gl,e,t,this.textureConfig)}createPackedMatrixTexture(e,t){return this.throwIfDisposed(),jS(this.gl,e,t,this.textureConfig)}deleteMatrixTexture(e){this.throwIfDisposed(),this.outputTexture===e&&(ny(this.gl,this.framebuffer),this.outputTexture=null),Ie(this.gl,()=>this.gl.deleteTexture(e))}downloadByteEncodedFloatMatrixFromOutputTexture(e,t,n){return this.downloadMatrixDriver(e,()=>QS(this.gl,t,n,this.textureConfig))}downloadPackedMatrixFromBuffer(e,t,n,s,r,a){return e9(this.gl,e,t,n,s,r,a,this.textureConfig)}downloadFloat32MatrixFromBuffer(e,t){return JS(this.gl,e,t)}createBufferFromTexture(e,t,n){this.bindTextureToFrameBuffer(e);let s=YS(this.gl,t,n,this.textureConfig);return this.unbindTextureToFrameBuffer(),s}createAndWaitForFence(){let e=this.createFence(this.gl);return this.pollFence(e)}createFence(e){let t,n;if(X().getBool("WEBGL_FENCE_API_ENABLED")){let s=e,r=s.fenceSync(s.SYNC_GPU_COMMANDS_COMPLETE,0);e.flush(),n=()=>{let a=s.clientWaitSync(r,0,0);return a===s.ALREADY_SIGNALED||a===s.CONDITION_SATISFIED},t=r}else X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")>0?(t=this.beginQuery(),this.endQuery(),n=()=>this.isQueryAvailable(t,X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))):n=()=>!0;return{query:t,isFencePassed:n}}downloadMatrixFromPackedTexture(e,t,n){return this.downloadMatrixDriver(e,()=>t9(this.gl,t,n))}createProgram(e){this.throwIfDisposed();let t=this.gl;this.vertexShader==null&&(this.vertexShader=BS(t));let n=fS(t);return Ie(t,()=>t.attachShader(n,this.vertexShader)),Ie(t,()=>t.attachShader(n,e)),mS(t,n),this.debug&&tm(t,n),this.vertexAttrsAreBound||(this.setProgram(n),this.vertexAttrsAreBound=XS(t,this.program,this.vertexBuffer)),n}deleteProgram(e){this.throwIfDisposed(),e===this.program&&(this.program=null),e!=null&&Ie(this.gl,()=>this.gl.deleteProgram(e))}setProgram(e){this.throwIfDisposed(),this.program=e,this.program!=null&&this.debug&&tm(this.gl,this.program),Ie(this.gl,()=>this.gl.useProgram(e))}getUniformLocation(e,t,n=!0){return this.throwIfDisposed(),n?wS(this.gl,e,t):kS(this.gl,e,t)}getAttributeLocation(e,t){return this.throwIfDisposed(),Ie(this.gl,()=>this.gl.getAttribLocation(e,t))}getUniformLocationNoThrow(e,t){return this.throwIfDisposed(),this.gl.getUniformLocation(e,t)}setInputMatrixTexture(e,t,n){this.throwIfDisposed(),this.throwIfNoProgram(),IS(this.gl,e,t,n)}setOutputMatrixTexture(e,t,n){this.setOutputMatrixTextureDriver(e,n,t)}setOutputPackedMatrixTexture(e,t,n){this.throwIfDisposed();let[s,r]=ed(t,n);this.setOutputMatrixTextureDriver(e,s,r)}setOutputMatrixWriteRegion(e,t,n,s){this.setOutputMatrixWriteRegionDriver(n,e,s,t)}setOutputPackedMatrixWriteRegion(e,t,n,s){throw new Error("setOutputPackedMatrixWriteRegion not implemented.")}debugValidate(){this.program!=null&&tm(this.gl,this.program),up(this.gl)}executeProgram(){this.throwIfDisposed(),this.throwIfNoProgram();let e=this.gl;this.debug&&this.debugValidate(),Ie(e,()=>e.drawElements(e.TRIANGLES,6,e.UNSIGNED_SHORT,0))}blockUntilAllProgramsCompleted(){this.throwIfDisposed(),Ie(this.gl,()=>this.gl.finish())}getQueryTimerExtension(){return this.disjointQueryTimerExtension==null&&(this.disjointQueryTimerExtension=lp(this.gl,X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2?"EXT_disjoint_timer_query_webgl2":"EXT_disjoint_timer_query")),this.disjointQueryTimerExtension}getQueryTimerExtensionWebGL2(){return this.getQueryTimerExtension()}getQueryTimerExtensionWebGL1(){return this.getQueryTimerExtension()}beginQuery(){if(X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let n=this.gl,s=this.getQueryTimerExtensionWebGL2(),r=n.createQuery();return n.beginQuery(s.TIME_ELAPSED_EXT,r),r}let e=this.getQueryTimerExtensionWebGL1(),t=e.createQueryEXT();return e.beginQueryEXT(e.TIME_ELAPSED_EXT,t),t}endQuery(){if(X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION")===2){let t=this.gl,n=this.getQueryTimerExtensionWebGL2();t.endQuery(n.TIME_ELAPSED_EXT);return}let e=this.getQueryTimerExtensionWebGL1();e.endQueryEXT(e.TIME_ELAPSED_EXT)}async waitForQueryAndGetTime(e){return await v.repeatedTry(()=>this.disposed||this.isQueryAvailable(e,X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))),this.getQueryTime(e,X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_VERSION"))}getQueryTime(e,t){if(t===0)return null;if(t===2){let n=this.gl;return n.getQueryParameter(e,n.QUERY_RESULT)/1e6}else{let n=this.getQueryTimerExtensionWebGL1();return n.getQueryObjectEXT(e,n.QUERY_RESULT_EXT)/1e6}}isQueryAvailable(e,t){if(t===0)return!0;if(t===2){let n=this.gl,s=this.getQueryTimerExtensionWebGL2(),r=n.getQueryParameter(e,n.QUERY_RESULT_AVAILABLE);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(s.GPU_DISJOINT_EXT)),r&&!this.disjoint}else{let n=this.getQueryTimerExtensionWebGL1(),s=n.getQueryObjectEXT(e,n.QUERY_RESULT_AVAILABLE_EXT);return this.disjoint==null&&(this.disjoint=this.gl.getParameter(n.GPU_DISJOINT_EXT)),s&&!this.disjoint}}pollFence(e){return new Promise(t=>{this.addItemToPoll(()=>e.isFencePassed(),()=>t())})}pollItems(){let e=rte(this.itemsToPoll.map(t=>t.isDoneFn));for(let t=0;t<=e;++t){let{resolveFn:n}=this.itemsToPoll[t];n()}this.itemsToPoll=this.itemsToPoll.slice(e+1)}addItemToPoll(e,t){this.itemsToPoll.push({isDoneFn:e,resolveFn:t}),!(this.itemsToPoll.length>1)&&v.repeatedTry(()=>(this.pollItems(),this.itemsToPoll.length===0))}bindTextureToFrameBuffer(e){this.throwIfDisposed(),nm(this.gl,e,this.framebuffer),this.debug&&up(this.gl)}unbindTextureToFrameBuffer(){this.outputTexture!=null?(nm(this.gl,this.outputTexture,this.framebuffer),this.debug&&up(this.gl)):ny(this.gl,this.framebuffer)}downloadMatrixDriver(e,t){this.bindTextureToFrameBuffer(e);let n=t();return this.unbindTextureToFrameBuffer(),n}setOutputMatrixTextureDriver(e,t,n){this.throwIfDisposed();let s=this.gl;nm(s,e,this.framebuffer),this.debug&&up(s),this.outputTexture=e,Ie(s,()=>s.viewport(0,0,t,n)),Ie(s,()=>s.scissor(0,0,t,n))}setOutputMatrixWriteRegionDriver(e,t,n,s){this.throwIfDisposed(),Ie(this.gl,()=>this.gl.scissor(e,t,n,s))}throwIfDisposed(){if(this.disposed)throw new Error("Attempted to use disposed GPGPUContext.")}throwIfNoProgram(){if(this.program==null)throw new Error("No GPU program is currently set.")}};function rte(e){let t=0;for(;t<e.length&&e[t]();++t);return t-1}var{addImpl:ate,bincountImpl:n9,bincountReduceImpl:ote,ceilImpl:ite,concatImpl:lte,equalImpl:ute,expImpl:cte,expm1Impl:dte,floorImpl:pte,gatherNdImpl:hte,gatherV2Impl:fte,greaterImpl:mte,greaterEqualImpl:gte,lessImpl:yte,lessEqualImpl:Ate,linSpaceImpl:xte,logImpl:bte,maxImpl:vte,maximumImpl:wte,minimumImpl:kte,multiplyImpl:Ite,negImpl:Ste,notEqualImpl:Cte,prodImpl:Tte,rangeImpl:Nte,rsqrtImpl:Ete,scatterImpl:Rte,sigmoidImpl:_te,simpleAbsImpl:s9,sliceImpl:Dte,sparseFillEmptyRowsImpl:$te,sparseReshapeImpl:Pte,sparseSegmentReductionImpl:r9,sqrtImpl:Fte,stridedSliceImpl:Ote,stringNGramsImpl:Mte,stringSplitImpl:zte,stringToHashBucketFastImpl:Lte,subImpl:Bte,tileImpl:Wte,topKImpl:Vte,transposeImpl:Zx,uniqueImpl:Ute}=Sx;function a9(e,t){return["x","y","z","w","u","v"].slice(0,t).map(n=>`${e}.${n}`)}function Qn(e,t){return t===1?[e]:a9(e,t)}function Gte(e,t){if(e===1)return"rc";let n="";for(let s=0;s<e;s++)n+=t[s],s<e-1&&(n+=",");return n}var Hte=class{constructor(e){if(this.variableNames=["A"],this.packedInputs=!1,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.enableShapeUniforms=xs(this.outputShape.length),this.rank===0)this.userCode=`
         void main() {
           setOutput(vec4(getA(), 0., 0., 0.));
         }
@@ -1178,10 +1178,10 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       }
     `}};function jte(e,t){return`
     ivec3 inputCoordsFromReshapedOutCoords(int index) {
-      ${t?pee(["r","c","d"],"inputShape"):su(["r","c","d"],e)}
+      ${t?pee(["r","c","d"],"inputShape"):nu(["r","c","d"],e)}
       return ivec3(r, c, d);
     }
-  `}var qte=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let s=h7(t,n),r=f7(e,s,n);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let a=p7(e,s,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=a,this.log();let i=this.freeTextures[r].shift();return this.usedTextures[r].push(i),i}let o;return s===Sn.PACKED_2X2_FLOAT32?o=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):s===Sn.PACKED_2X2_FLOAT16?o=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):s===Sn.UNPACKED_FLOAT32?o=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):s===Sn.UNPACKED_FLOAT16?o=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):s===Sn.PACKED_4X1_UNSIGNED_BYTE&&(o=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(o),this.numUsedTextures++,this._numBytesAllocated+=a,this.log(),o}releaseTexture(e,t,n,s){if(this.freeTextures==null)return;let r=h7(n,s),a=f7(t,r,s);a in this.freeTextures||(this.freeTextures[a]=[]);let o=p7(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,s),i=Z().get("WEBGL_DELETE_TEXTURE_THRESHOLD");i!==-1&&this._numBytesAllocated>i?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=o):(this.freeTextures[a].push(e),this.numFreeTextures++,this._numBytesFree+=o),this.numUsedTextures--;let l=this.usedTextures[a],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function Xte(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F)return 16;if(t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;if(t===n.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function p7(e,t,n,s,r){let a=Kte(t,s),o;if(r){let[l,u]=td(e[0],e[1]);o=l*u}else{let[l,u]=Fh(e[0],e[1]);o=l*u}let i=Xte(n,a);return o*i}function Kte(e,t){switch(e){case Sn.PACKED_2X2_FLOAT32:return Xx(t);case Sn.PACKED_2X2_FLOAT16:return Kx(t);case Sn.UNPACKED_FLOAT32:return Hx(t);case Sn.UNPACKED_FLOAT16:return jx(t);case Sn.PACKED_4X1_UNSIGNED_BYTE:return qx(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function Zte(e){return Z().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?Sn.PACKED_2X2_FLOAT32:Sn.UNPACKED_FLOAT32:e?Sn.PACKED_2X2_FLOAT16:Sn.UNPACKED_FLOAT16}function h7(e,t){if(e===qs.UPLOAD)return Sn.PACKED_2X2_FLOAT32;if(e===qs.RENDER||e==null)return Zte(t);if(e===qs.DOWNLOAD||e===qs.PIXELS)return Sn.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function f7(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var pa=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
+  `}var qte=class{constructor(e){this.gpgpu=e,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0,this.freeTextures={},this.logEnabled=!1,this.usedTextures={}}acquireTexture(e,t,n){let s=h7(t,n),r=f7(e,s,n);r in this.freeTextures||(this.freeTextures[r]=[]),r in this.usedTextures||(this.usedTextures[r]=[]);let a=p7(e,s,this.gpgpu.gl,this.gpgpu.textureConfig,n);if(this.freeTextures[r].length>0){this.numFreeTextures--,this.numUsedTextures++,this._numBytesFree-=a,this.log();let i=this.freeTextures[r].shift();return this.usedTextures[r].push(i),i}let o;return s===Sn.PACKED_2X2_FLOAT32?o=this.gpgpu.createPackedMatrixTexture(e[0],e[1]):s===Sn.PACKED_2X2_FLOAT16?o=this.gpgpu.createFloat16PackedMatrixTexture(e[0],e[1]):s===Sn.UNPACKED_FLOAT32?o=this.gpgpu.createFloat32MatrixTexture(e[0],e[1]):s===Sn.UNPACKED_FLOAT16?o=this.gpgpu.createFloat16MatrixTexture(e[0],e[1]):s===Sn.PACKED_4X1_UNSIGNED_BYTE&&(o=this.gpgpu.createUnsignedBytesMatrixTexture(e[0],e[1])),this.usedTextures[r].push(o),this.numUsedTextures++,this._numBytesAllocated+=a,this.log(),o}releaseTexture(e,t,n,s){if(this.freeTextures==null)return;let r=h7(n,s),a=f7(t,r,s);a in this.freeTextures||(this.freeTextures[a]=[]);let o=p7(t,r,this.gpgpu.gl,this.gpgpu.textureConfig,s),i=X().get("WEBGL_DELETE_TEXTURE_THRESHOLD");i!==-1&&this._numBytesAllocated>i?(this.gpgpu.deleteMatrixTexture(e.texture),this._numBytesAllocated-=o):(this.freeTextures[a].push(e),this.numFreeTextures++,this._numBytesFree+=o),this.numUsedTextures--;let l=this.usedTextures[a],u=l.indexOf(e);if(u<0)throw new Error("Cannot release a texture that was never provided by this texture manager");l.splice(u,1),this.log()}log(){if(!this.logEnabled)return;let e=this.numFreeTextures+this.numUsedTextures;console.log("Free/Used",`${this.numFreeTextures} / ${this.numUsedTextures}`,`(${e})`);let t=this._numBytesFree/this._numBytesAllocated;console.log(`Bytes allocated: ${this._numBytesAllocated}`),console.log(`Bytes unused: ${this._numBytesFree} (${Math.round(100*t)}%)`)}get numBytesAllocated(){return this._numBytesAllocated}get numBytesFree(){return this._numBytesFree}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){if(this.freeTextures!=null){for(let e in this.freeTextures)this.freeTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});for(let e in this.usedTextures)this.usedTextures[e].forEach(t=>{this.gpgpu.deleteMatrixTexture(t.texture)});this.freeTextures=null,this.usedTextures=null,this.numUsedTextures=0,this.numFreeTextures=0,this._numBytesAllocated=0,this._numBytesFree=0}}};function Xte(e,t){let n=e;if(t===n.R32F)return 4;if(t===n.R16F)return 2;if(t===n.RGBA32F)return 16;if(t===e.RGBA)return 16;if(t===n.RGBA16F)return 8;if(t===n.RGBA8)return 4;throw new Error(`Unknown internal format ${t}`)}function p7(e,t,n,s,r){let a=Kte(t,s),o;if(r){let[l,u]=ed(e[0],e[1]);o=l*u}else{let[l,u]=Ph(e[0],e[1]);o=l*u}let i=Xte(n,a);return o*i}function Kte(e,t){switch(e){case Sn.PACKED_2X2_FLOAT32:return Xx(t);case Sn.PACKED_2X2_FLOAT16:return Kx(t);case Sn.UNPACKED_FLOAT32:return Hx(t);case Sn.UNPACKED_FLOAT16:return jx(t);case Sn.PACKED_4X1_UNSIGNED_BYTE:return qx(t);default:throw new Error(`Unknown physical texture type ${e}`)}}function Zte(e){return X().getBool("WEBGL_RENDER_FLOAT32_ENABLED")?e?Sn.PACKED_2X2_FLOAT32:Sn.UNPACKED_FLOAT32:e?Sn.PACKED_2X2_FLOAT16:Sn.UNPACKED_FLOAT16}function h7(e,t){if(e===qs.UPLOAD)return Sn.PACKED_2X2_FLOAT32;if(e===qs.RENDER||e==null)return Zte(t);if(e===qs.DOWNLOAD||e===qs.PIXELS)return Sn.PACKED_4X1_UNSIGNED_BYTE;throw new Error(`Unknown logical texture type ${e}`)}function f7(e,t,n){return`${e[0]}_${e[1]}_${t}_${n}`}var da=class{constructor(e,t){this.variableNames=["A"],this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
       float unaryOperation(float x) {
         ${t}
       }
@@ -1196,7 +1196,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   return (x < 0.0) ? 0.0 : x;
 `,ene=hr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
-`,Pu="return x;",tne="return 1.0 / (1.0 + exp(-1.0 * x));",nne="return x;",sne=`
+`,$u="return x;",tne="return 1.0 / (1.0 + exp(-1.0 * x));",nne="return x;",sne=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -1225,7 +1225,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,one="return 1.0 / (1.0 + exp(-1.0 * x));",Ui=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
+`,one="return 1.0 / (1.0 + exp(-1.0 * x));",Vi=class{constructor(e,t){this.variableNames=["A"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
       vec4 unaryOperation(vec4 x) {
         ${t}
       }
@@ -1243,10 +1243,10 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(getChannel(packedInput, ${o}));
       }
-    `}},lne=dr.whereImpl,une=1e-7,cne=1e-4,Zf={};function dne(e){return e in Zf||(Zf[e]={}),Zf[e]}var pne=Z().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),hne=600;function fne(){return Z().global.screen==null?1024:Z().global.screen.height*Z().global.screen.width*window.devicePixelRatio*hne/1024/1024}var id=class extends cc{constructor(e){if(super(),this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!Z().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let t;if(e!=null){if(e instanceof ju)t=e;else{let n=Dr(Z().getNumber("WEBGL_VERSION"),e);t=new ju(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=Dr(Z().getNumber("WEBGL_VERSION"));t=new ju(n),this.binaryCache=dne(Z().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=t,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new qte(this.gpgpu),this.numMBBeforeWarning=fne(),this.texData=new Mp(this,sn())}nextDataId(){return id.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}write(e,t,n){if((Z().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||Z().getBool("DEBUG"))&&this.checkNumericalProblems(e),n==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let s={id:this.nextDataId()};return this.texData.set(s,{shape:t,dtype:n,values:e,usage:qs.UPLOAD,refCount:1}),s}refCount(e){return this.texData.has(e)?this.texData.get(e).refCount:0}incRef(e){let t=this.texData.get(e);t.refCount++}decRef(e){if(this.texData.has(e)){let t=this.texData.get(e);t.refCount--}}move(e,t,n,s,r){if(Z().getBool("DEBUG")&&this.checkNumericalProblems(t),s==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:s,values:t,usage:qs.UPLOAD,refCount:r})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:s,complexTensorInfos:r,slice:a,shape:o,isPacked:i}=t;if(a!=null){let p;i?p=new Ui(o,Pu):p=new pa(o,Pu);let d=this.runWebGLProgram(p,[{dataId:e,shape:o,dtype:s}],s),h=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),h}if(n!=null)return this.convertAndCacheOnCPU(e);if(s==="string")return n;let l=this.activeTimers!=null,u;l&&(u=v.now());let c;if(s==="complex64"){let p=this.readSync(r.real.dataId),d=this.readSync(r.imag.dataId);c=C.mergeRealAndImagArrays(p,d)}else c=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-u),this.convertAndCacheOnCPU(e,c)}async read(e){if(this.pendingRead.has(e)){let h=this.pendingRead.get(e);return new Promise(f=>h.push(f))}let t=this.texData.get(e),{values:n,shape:s,slice:r,dtype:a,complexTensorInfos:o,isPacked:i}=t;if(r!=null){let h;i?h=new Ui(s,Pu):h=new pa(s,Pu);let f=this.runWebGLProgram(h,[{dataId:e,shape:s,dtype:a}],a),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(Z().getBool("DEBUG")&&!Z().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&Z().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,u;if(a!=="complex64"&&Z().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let h=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(h.texture.texture,...Xf(s))}this.pendingRead.set(e,[]),a!=="complex64"&&await this.gpgpu.createAndWaitForFence();let c;if(a==="complex64"){let h=await Promise.all([this.read(o.real.dataId),this.read(o.imag.dataId)]),f=h[0],m=h[1];c=C.mergeRealAndImagArrays(f,m)}else if(l==null)c=this.getValuesFromTexture(e);else{let h=v.sizeFromShape(s);c=this.gpgpu.downloadFloat32MatrixFromBuffer(l,h)}if(u!=null&&this.disposeIntermediateTensorInfo(u),l!=null){let h=this.gpgpu.gl;Ie(h,()=>h.deleteBuffer(l))}let p=this.convertAndCacheOnCPU(e,c),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(h=>h(p)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&sn().removeDataId(e,this),this.pendingDeletes--),p}readToGPU(e,t={}){let n=this.texData.get(e),{values:s,shape:r,slice:a,dtype:o,isPacked:i,texture:l}=n;if(o==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(a!=null){let d;i?d=new Ui(r,Pu):d=new pa(r,Pu);let h=this.runWebGLProgram(d,[{dataId:e,shape:r,dtype:o}],o),f=this.readToGPU(h,t);return this.disposeIntermediateTensorInfo(h),f}if(l==null)throw s!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let u=this.decode(e,t.customTexShape),c=sn().makeTensorFromTensorInfo(u),p=this.texData.get(u.dataId);return Object.assign({tensorRef:c},p.texture)}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let n=t.map(s=>v.decodeString(s));return Le(e.shape,e.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Le(e.shape,e.dtype,t)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!cS(n))throw Z().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:s}=this.texData.get(e),r=v.sizeFromShape(t);if(Z().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let p=this.decode(e),d=this.texData.get(p.dataId),h=this.gpgpu.downloadMatrixFromPackedTexture(d.texture.texture,...Xf(t)).subarray(0,r);return this.disposeIntermediateTensorInfo(p),h}let a=Z().getBool("WEBGL_PACK")&&s===!0,o=a?rm(t):t,i=a?new tte(o):new ete(o),l=this.runWebGLProgram(i,[{shape:o,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),c=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture.texture,u.texShape[0],u.texShape[1]).subarray(0,r);return this.disposeIntermediateTensorInfo(l),c}timerAvailable(){return Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(e){let t=this.activeTimers,n=[],s=!1;this.programTimersStack==null?(this.programTimersStack=n,s=!0):this.activeTimers.push(n),this.activeTimers=n,e();let r=v.flatten(this.activeTimers.map(i=>i.query)).filter(i=>i!=null),a=v.flatten(this.activeTimers.map(i=>i.name)).filter(i=>i!=null);this.activeTimers=t,s&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let i=await Promise.all(r);o.kernelMs=v.sum(i),o.getExtraProfileInfo=()=>i.map((l,u)=>({name:a[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else o.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,o})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(Z().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:s,usage:r,isPacked:a,slice:o}=this.texData.get(e),i=o&&o.origDataId||e,l=this.dataRefCount.get(i);l>1?this.dataRefCount.set(i,l-1):(this.dataRefCount.delete(i),t!=null&&(this.numBytesInGPU-=this.computeBytes(s,n),this.textureManager.releaseTexture(t,s,r,a)));let u=this.texData.get(e);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture.texture}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=pne){return Z().getBool("WEBGL_CPU_FORWARD")&&e.every(n=>this.texData.get(n.dataId).texture==null&&v.sizeFromShape(n.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){C.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return lne(e.shape,t)}packedUnaryOp(e,t,n){let s=new Ui(e.shape,t),r=this.compileAndRun(s,[e],n);return sn().makeTensorFromTensorInfo(r)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let s=s9(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,s)}if(Z().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,m7,e.dtype);let t=new pa(e.shape,m7),n=this.compileAndRun(t,[e]);return sn().makeTensorFromTensorInfo(n)}makeTensorInfo(e,t,n){let s;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let r=n.map(a=>v.encodeString(a));s=this.write(r,e,t)}else s=this.write(n,e,t);return this.texData.get(s).usage=null,{dataId:s,shape:e,dtype:t}}makeOutput(e,t,n){return sn().makeTensorFromTensorInfo(this.makeTensorInfo(e,t,n),this)}unpackTensor(e){let t=new ine(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new Hte(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[sl(e.shape),...rl(e.shape)],s={dtype:e.dtype,shape:n,dataId:e.dataId},r=[sl(t),...rl(t)],a=new o9(r,n),o=!0,i=[n],l=this.runWebGLProgram(a,[s],e.dtype,i,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}decode(e,t){let n=this.texData.get(e),{isPacked:s,shape:r,dtype:a}=n;if(t!=null){let p=v.sizeFromShape(r),d=t[0]*t[1]*4;v.assert(p<=d,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let o=rm(r),i;s?i=new Qee(o):i=new Jee(o);let l=!0,u=[t!=null?t:Xf(o)],c=this.runWebGLProgram(i,[{shape:o,dtype:a,dataId:e}],a,u,l,t);return{dtype:a,shape:r,dataId:c.dataId}}runWebGLProgram(e,t,n,s,r=!1,a){let o=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(o.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===_p.DENSE){let g=a!=null?a:Xf(e.outputShape);i.texShape=g.map(y=>y*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(o.shape)===0)return i.values=v.getTypedArrayFromDType(o.dtype,0),o;let l=[],u=t.map(g=>{if(g.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let y=this.texData.get(g.dataId);if(y.texture==null){if(!e.packedInputs&&v.sizeFromShape(g.shape)<=Z().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:g.shape,texData:null,isUniform:!0,uniformValues:y.values};e.packedInputs&&(y.isPacked=!0,y.shape=g.shape)}if(this.uploadToGPU(g.dataId),!!y.isPacked!=!!e.packedInputs)g=y.isPacked?this.unpackTensor(g):this.packTensor(g),l.push(g),y=this.texData.get(g.dataId);else if(y.isPacked&&!Dp(y.shape,g.shape)){let x=g,A=g.shape;g.shape=y.shape,g=this.packedReshape(g,A),l.push(g),y=this.texData.get(g.dataId),x.shape=A}return{shape:g.shape,texData:y,isUniform:!1}});this.uploadToGPU(o.dataId);let c={shape:o.shape,texData:i,isUniform:!1},p=Yee(e,u,c),d=this.getAndSaveBinary(p,()=>Kee(this.gpgpu,e,u,c)),h=this.activeTimers!=null,f;h&&(f=this.startTimer()),Z().get("ENGINE_COMPILE_ONLY")||Zee(this.gpgpu,d,u,c,s),l.forEach(g=>this.disposeIntermediateTensorInfo(g)),h&&(f=this.endTimer(f),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(f)}));let m=Z().get("WEBGL_FLUSH_THRESHOLD");if(m>0){let g=v.now();g-this.lastGlFlushTime>m&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!Z().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&r===!1){let g=this.unpackTensor(o);return this.disposeIntermediateTensorInfo(o),g}return o}compileAndRun(e,t,n,s,r=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,s,r)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(Z().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(t=>{this.gpgpu.deleteProgram(this.binaryCache[t].webGLProgram),delete this.binaryCache[t]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=J(()=>{if(!Z().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=Z().getBool("DEBUG");Z().set("DEBUG",!1);let t=this.abs(Se(1e-8)).dataSync()[0];if(Z().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?une:cne}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:s,values:r,texture:a,usage:o,isPacked:i}=t;if(a!=null)return;let l=this.activeTimers!=null,u;l&&(u=v.now());let c=t.texShape;if(c==null&&(c=TS(n,i),t.texShape=c),r!=null){let p=rm(n),d,h=c[1],f=c[0],m=r instanceof Uint8Array||r instanceof Uint8ClampedArray;(i||!m)&&([h,f]=td(c[0],c[1])),i?d=new ste(p,m):d=new nte(p,m);let g=m?[f,h]:c,y=this.makeTensorInfo(g,s),x=this.texData.get(y.dataId);m?x.usage=qs.PIXELS:x.usage=qs.UPLOAD,x.texShape=g,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(y.dataId),h,f,r);let A=[[f,h]],b=!0,w=this.runWebGLProgram(d,[y],s,A,b),k=this.texData.get(w.dataId);t.texShape=k.texShape,t.isPacked=k.isPacked,t.usage=k.usage,Z().get("ENGINE_COMPILE_ONLY")?this.disposeData(w.dataId):(t.texture=k.texture,t.values=null,this.texData.delete(w.dataId)),this.disposeIntermediateTensorInfo(y),l&&(this.uploadWaitMs+=v.now()-u)}else{let p=this.acquireTexture(c,o,s,i);t.texture=p}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:s}=n;return this.releaseGPUData(e),t!=null&&(n.values=mne(t,s)),n.values}acquireTexture(e,t,n,s){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let r=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${r} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,s)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}checkCompileCompletion(){for(let[,e]of Object.entries(this.binaryCache))this.checkCompletion_(e)}async checkCompileCompletionAsync(){let e=[];if(this.gpgpu.parallelCompilationExtension){for(let[,t]of Object.entries(this.binaryCache))e.push(this.checkCompletionAsync_(t));return Promise.all(e)}else{for(let[,t]of Object.entries(this.binaryCache)){let n=new Promise(s=>{try{this.checkCompletion_(t),s(!0)}catch(r){throw r}});e.push(n)}return Promise.all(e)}}async checkCompletionAsync_(e){return this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(e):(await jA(),this.checkCompletionAsync_(e))}checkCompletion_(e){if(this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(e.webGLProgram)),this.gpgpu.gl.getShaderParameter(e.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?(Wx(e.source,this.gpgpu.gl.getShaderInfoLog(e.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let[,e]of Object.entries(this.binaryCache)){let{uniformLocations:t,customUniformLocations:n,infLoc:s,nanLoc:r,inShapesLocations:a,inTexShapesLocations:o,outShapeLocation:i,outShapeStridesLocation:l,outTexShapeLocation:u}=zS(this.gpgpu,e.program,e.webGLProgram);e.uniformLocations=t,e.customUniformLocations=n,e.infLoc=s,e.nanLoc=r,e.inShapesLocations=a,e.inTexShapesLocations=o,e.outShapeLocation=i,e.outShapeStridesLocation=l,e.outTexShapeLocation=u}}};id.nextDataId=0;function mne(e,t){if(t==="float32"||t==="complex64")return e;if(t==="int32"||t==="bool"){let n=t==="int32"?new Int32Array(e.length):new Uint8Array(e.length);for(let s=0;s<n.length;++s)n[s]=Math.round(e[s]);return n}else throw new Error(`Unknown dtype ${t}`)}var gne="3.19.0";function i9(){Z().set("WEBGL_FORCE_F16_TEXTURES",!0)}rh.isBrowser()&&ql("webgl",()=>new id,2);var yne={forceHalfFloat:i9},l9=`
+    `}},lne=dr.whereImpl,une=1e-7,cne=1e-4,Kf={};function dne(e){return e in Kf||(Kf[e]={}),Kf[e]}var pne=X().getNumber("CPU_HANDOFF_SIZE_THRESHOLD"),hne=600;function fne(){return X().global.screen==null?1024:X().global.screen.height*X().global.screen.width*window.devicePixelRatio*hne/1024/1024}var od=class extends uc{constructor(e){if(super(),this.pendingRead=new WeakMap,this.pendingDisposal=new WeakSet,this.dataRefCount=new WeakMap,this.numBytesInGPU=0,this.uploadWaitMs=0,this.downloadWaitMs=0,this.lastGlFlushTime=0,this.warnedAboutMemory=!1,this.pendingDeletes=0,this.disposed=!1,!X().getBool("HAS_WEBGL"))throw new Error("WebGL is not supported on this device");let t;if(e!=null){if(e instanceof Hu)t=e;else{let n=Dr(X().getNumber("WEBGL_VERSION"),e);t=new Hu(n)}this.binaryCache={},this.gpgpuCreatedLocally=!1}else{let n=Dr(X().getNumber("WEBGL_VERSION"));t=new Hu(n),this.binaryCache=dne(X().getNumber("WEBGL_VERSION")),this.gpgpuCreatedLocally=!0}this.gpgpu=t,this.canvas=this.gpgpu.gl.canvas,this.textureManager=new qte(this.gpgpu),this.numMBBeforeWarning=fne(),this.texData=new Op(this,sn())}nextDataId(){return od.nextDataId++}numDataIds(){return this.texData.numDataIds()-this.pendingDeletes}write(e,t,n){if((X().getBool("WEBGL_CHECK_NUMERICAL_PROBLEMS")||X().getBool("DEBUG"))&&this.checkNumericalProblems(e),n==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let s={id:this.nextDataId()};return this.texData.set(s,{shape:t,dtype:n,values:e,usage:qs.UPLOAD,refCount:1}),s}refCount(e){return this.texData.has(e)?this.texData.get(e).refCount:0}incRef(e){let t=this.texData.get(e);t.refCount++}decRef(e){if(this.texData.has(e)){let t=this.texData.get(e);t.refCount--}}move(e,t,n,s,r){if(X().getBool("DEBUG")&&this.checkNumericalProblems(t),s==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.texData.set(e,{shape:n,dtype:s,values:t,usage:qs.UPLOAD,refCount:r})}disposeIntermediateTensorInfo(e){this.disposeData(e.dataId)}readSync(e){let t=this.texData.get(e),{values:n,dtype:s,complexTensorInfos:r,slice:a,shape:o,isPacked:i}=t;if(a!=null){let p;i?p=new Vi(o,$u):p=new da(o,$u);let d=this.runWebGLProgram(p,[{dataId:e,shape:o,dtype:s}],s),h=this.readSync(d.dataId);return this.disposeIntermediateTensorInfo(d),h}if(n!=null)return this.convertAndCacheOnCPU(e);if(s==="string")return n;let l=this.activeTimers!=null,u;l&&(u=v.now());let c;if(s==="complex64"){let p=this.readSync(r.real.dataId),d=this.readSync(r.imag.dataId);c=C.mergeRealAndImagArrays(p,d)}else c=this.getValuesFromTexture(e);return l&&(this.downloadWaitMs+=v.now()-u),this.convertAndCacheOnCPU(e,c)}async read(e){if(this.pendingRead.has(e)){let h=this.pendingRead.get(e);return new Promise(f=>h.push(f))}let t=this.texData.get(e),{values:n,shape:s,slice:r,dtype:a,complexTensorInfos:o,isPacked:i}=t;if(r!=null){let h;i?h=new Vi(s,$u):h=new da(s,$u);let f=this.runWebGLProgram(h,[{dataId:e,shape:s,dtype:a}],a),m=this.read(f.dataId);return this.disposeIntermediateTensorInfo(f),m}if(n!=null)return this.convertAndCacheOnCPU(e);if(X().getBool("DEBUG")&&!X().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")&&X().getNumber("WEBGL_VERSION")===2)throw new Error("tensor.data() with WEBGL_DOWNLOAD_FLOAT_ENABLED=false and WEBGL_VERSION=2 not yet supported.");let l=null,u;if(a!=="complex64"&&X().get("WEBGL_BUFFER_SUPPORTED")){u=this.decode(e);let h=this.texData.get(u.dataId);l=this.gpgpu.createBufferFromTexture(h.texture.texture,...qf(s))}this.pendingRead.set(e,[]),a!=="complex64"&&await this.gpgpu.createAndWaitForFence();let c;if(a==="complex64"){let h=await Promise.all([this.read(o.real.dataId),this.read(o.imag.dataId)]),f=h[0],m=h[1];c=C.mergeRealAndImagArrays(f,m)}else if(l==null)c=this.getValuesFromTexture(e);else{let h=v.sizeFromShape(s);c=this.gpgpu.downloadFloat32MatrixFromBuffer(l,h)}if(u!=null&&this.disposeIntermediateTensorInfo(u),l!=null){let h=this.gpgpu.gl;Ie(h,()=>h.deleteBuffer(l))}let p=this.convertAndCacheOnCPU(e,c),d=this.pendingRead.get(e);return this.pendingRead.delete(e),d.forEach(h=>h(p)),this.pendingDisposal.has(e)&&(this.pendingDisposal.delete(e),this.disposeData(e)&&sn().removeDataId(e,this),this.pendingDeletes--),p}readToGPU(e,t={}){let n=this.texData.get(e),{values:s,shape:r,slice:a,dtype:o,isPacked:i,texture:l}=n;if(o==="complex64")throw new Error("Does not support reading texture for complex64 dtype.");if(a!=null){let d;i?d=new Vi(r,$u):d=new da(r,$u);let h=this.runWebGLProgram(d,[{dataId:e,shape:r,dtype:o}],o),f=this.readToGPU(h,t);return this.disposeIntermediateTensorInfo(h),f}if(l==null)throw s!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let u=this.decode(e,t.customTexShape),c=sn().makeTensorFromTensorInfo(u),p=this.texData.get(u.dataId);return Object.assign({tensorRef:c},p.texture)}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let n=t.map(s=>v.decodeString(s));return Le(e.shape,e.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Le(e.shape,e.dtype,t)}checkNumericalProblems(e){if(e!=null)for(let t=0;t<e.length;t++){let n=e[t];if(!cS(n))throw X().getBool("WEBGL_RENDER_FLOAT32_CAPABLE")?Error(`The value ${n} cannot be represented with your current settings. Consider enabling float32 rendering: 'tf.env().set('WEBGL_RENDER_FLOAT32_ENABLED', true);'`):Error(`The value ${n} cannot be represented on this device.`)}}getValuesFromTexture(e){let{shape:t,dtype:n,isPacked:s}=this.texData.get(e),r=v.sizeFromShape(t);if(X().getBool("WEBGL_DOWNLOAD_FLOAT_ENABLED")){let p=this.decode(e),d=this.texData.get(p.dataId),h=this.gpgpu.downloadMatrixFromPackedTexture(d.texture.texture,...qf(t)).subarray(0,r);return this.disposeIntermediateTensorInfo(p),h}let a=X().getBool("WEBGL_PACK")&&s===!0,o=a?sm(t):t,i=a?new tte(o):new ete(o),l=this.runWebGLProgram(i,[{shape:o,dtype:n,dataId:e}],"float32"),u=this.texData.get(l.dataId),c=this.gpgpu.downloadByteEncodedFloatMatrixFromOutputTexture(u.texture.texture,u.texShape[0],u.texShape[1]).subarray(0,r);return this.disposeIntermediateTensorInfo(l),c}timerAvailable(){return X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0}time(e){let t=this.activeTimers,n=[],s=!1;this.programTimersStack==null?(this.programTimersStack=n,s=!0):this.activeTimers.push(n),this.activeTimers=n,e();let r=v.flatten(this.activeTimers.map(i=>i.query)).filter(i=>i!=null),a=v.flatten(this.activeTimers.map(i=>i.name)).filter(i=>i!=null);this.activeTimers=t,s&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null};return(async()=>{if(X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0){let i=await Promise.all(r);o.kernelMs=v.sum(i),o.getExtraProfileInfo=()=>i.map((l,u)=>({name:a[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", ")}else o.kernelMs={error:"WebGL query timers are not supported in this environment."};return this.uploadWaitMs=0,this.downloadWaitMs=0,o})()}memory(){return{unreliable:!1,numBytesInGPU:this.numBytesInGPU,numBytesInGPUAllocated:this.textureManager.numBytesAllocated,numBytesInGPUFree:this.textureManager.numBytesFree}}startTimer(){return X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?this.gpgpu.beginQuery():{startMs:v.now(),endMs:null}}endTimer(e){return X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0?(this.gpgpu.endQuery(),e):(e.endMs=v.now(),e)}async getQueryTime(e){if(X().getNumber("WEBGL_DISJOINT_QUERY_TIMER_EXTENSION_RELIABLE")>0)return this.gpgpu.waitForQueryAndGetTime(e);let t=e;return t.endMs-t.startMs}disposeData(e,t=!1){if(this.pendingDisposal.has(e))return!1;if(!this.texData.has(e))return!0;if(t?this.texData.get(e).refCount=0:this.texData.get(e).refCount--,!t&&this.texData.get(e).refCount>0)return!1;if(this.pendingRead.has(e))return this.pendingDisposal.add(e),this.pendingDeletes++,!1;this.releaseGPUData(e);let{complexTensorInfos:n}=this.texData.get(e);return n!=null&&(this.disposeData(n.real.dataId,t),this.disposeData(n.imag.dataId,t)),this.texData.delete(e),!0}releaseGPUData(e){let{texture:t,dtype:n,texShape:s,usage:r,isPacked:a,slice:o}=this.texData.get(e),i=o&&o.origDataId||e,l=this.dataRefCount.get(i);l>1?this.dataRefCount.set(i,l-1):(this.dataRefCount.delete(i),t!=null&&(this.numBytesInGPU-=this.computeBytes(s,n),this.textureManager.releaseTexture(t,s,r,a)));let u=this.texData.get(e);u.texture=null,u.texShape=null,u.isPacked=!1,u.slice=null}getTexture(e){return this.uploadToGPU(e),this.texData.get(e).texture.texture}getDataInfo(e){return this.texData.get(e)}shouldExecuteOnCPU(e,t=pne){return X().getBool("WEBGL_CPU_FORWARD")&&e.every(n=>this.texData.get(n.dataId).texture==null&&v.sizeFromShape(n.shape)<t)}getGPGPUContext(){return this.gpgpu}where(e){C.warn("tf.where() in webgl locks the UI thread. Call tf.whereAsync() instead");let t=e.dataSync();return lne(e.shape,t)}packedUnaryOp(e,t,n){let s=new Vi(e.shape,t),r=this.compileAndRun(s,[e],n);return sn().makeTensorFromTensorInfo(r)}abs(e){if(this.shouldExecuteOnCPU([e])&&e.dtype!=="complex64"){let s=s9(this.texData.get(e.dataId).values);return this.makeOutput(e.shape,e.dtype,s)}if(X().getBool("WEBGL_PACK_UNARY_OPERATIONS"))return this.packedUnaryOp(e,m7,e.dtype);let t=new da(e.shape,m7),n=this.compileAndRun(t,[e]);return sn().makeTensorFromTensorInfo(n)}makeTensorInfo(e,t,n){let s;if(t==="string"&&n!=null&&n.length>0&&v.isString(n[0])){let r=n.map(a=>v.encodeString(a));s=this.write(r,e,t)}else s=this.write(n,e,t);return this.texData.get(s).usage=null,{dataId:s,shape:e,dtype:t}}makeOutput(e,t,n){return sn().makeTensorFromTensorInfo(this.makeTensorInfo(e,t,n),this)}unpackTensor(e){let t=new ine(e.shape);return this.runWebGLProgram(t,[e],e.dtype)}packTensor(e){let t=new Hte(e.shape),n=!0;return this.runWebGLProgram(t,[e],e.dtype,null,n)}packedReshape(e,t){let n=[nl(e.shape),...sl(e.shape)],s={dtype:e.dtype,shape:n,dataId:e.dataId},r=[nl(t),...sl(t)],a=new o9(r,n),o=!0,i=[n],l=this.runWebGLProgram(a,[s],e.dtype,i,o);return{dataId:l.dataId,shape:t,dtype:l.dtype}}decode(e,t){let n=this.texData.get(e),{isPacked:s,shape:r,dtype:a}=n;if(t!=null){let p=v.sizeFromShape(r),d=t[0]*t[1]*4;v.assert(p<=d,()=>"customTexShape is too small. Row * Column * 4 should be equal or larger than the size of the tensor data.")}let o=sm(r),i;s?i=new Qee(o):i=new Jee(o);let l=!0,u=[t!=null?t:qf(o)],c=this.runWebGLProgram(i,[{shape:o,dtype:a,dataId:e}],a,u,l,t);return{dtype:a,shape:r,dataId:c.dataId}}runWebGLProgram(e,t,n,s,r=!1,a){let o=this.makeTensorInfo(e.outputShape,n),i=this.texData.get(o.dataId);if(e.packedOutput&&(i.isPacked=!0),e.outPackingScheme===Rp.DENSE){let g=a!=null?a:qf(e.outputShape);i.texShape=g.map(y=>y*2)}if(e.outTexUsage!=null&&(i.usage=e.outTexUsage),v.sizeFromShape(o.shape)===0)return i.values=v.getTypedArrayFromDType(o.dtype,0),o;let l=[],u=t.map(g=>{if(g.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");let y=this.texData.get(g.dataId);if(y.texture==null){if(!e.packedInputs&&v.sizeFromShape(g.shape)<=X().getNumber("WEBGL_SIZE_UPLOAD_UNIFORM"))return{shape:g.shape,texData:null,isUniform:!0,uniformValues:y.values};e.packedInputs&&(y.isPacked=!0,y.shape=g.shape)}if(this.uploadToGPU(g.dataId),!!y.isPacked!=!!e.packedInputs)g=y.isPacked?this.unpackTensor(g):this.packTensor(g),l.push(g),y=this.texData.get(g.dataId);else if(y.isPacked&&!_p(y.shape,g.shape)){let x=g,A=g.shape;g.shape=y.shape,g=this.packedReshape(g,A),l.push(g),y=this.texData.get(g.dataId),x.shape=A}return{shape:g.shape,texData:y,isUniform:!1}});this.uploadToGPU(o.dataId);let c={shape:o.shape,texData:i,isUniform:!1},p=Yee(e,u,c),d=this.getAndSaveBinary(p,()=>Kee(this.gpgpu,e,u,c)),h=this.activeTimers!=null,f;h&&(f=this.startTimer()),X().get("ENGINE_COMPILE_ONLY")||Zee(this.gpgpu,d,u,c,s),l.forEach(g=>this.disposeIntermediateTensorInfo(g)),h&&(f=this.endTimer(f),this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(f)}));let m=X().get("WEBGL_FLUSH_THRESHOLD");if(m>0){let g=v.now();g-this.lastGlFlushTime>m&&(this.gpgpu.gl.flush(),this.lastGlFlushTime=g)}if(!X().getBool("WEBGL_LAZILY_UNPACK")&&i.isPacked&&r===!1){let g=this.unpackTensor(o);return this.disposeIntermediateTensorInfo(o),g}return o}compileAndRun(e,t,n,s,r=!1){return n=n||t[0].dtype,this.runWebGLProgram(e,t,n,s,r)}getAndSaveBinary(e,t){return e in this.binaryCache||(this.binaryCache[e]=t()),this.binaryCache[e]}getTextureManager(){return this.textureManager}dispose(){this.disposed||(X().getBool("IS_TEST")||Object.keys(this.binaryCache).forEach(t=>{this.gpgpu.deleteProgram(this.binaryCache[t].webGLProgram),delete this.binaryCache[t]}),this.textureManager.dispose(),this.canvas!=null&&typeof HTMLCanvasElement!="undefined"&&this.canvas instanceof HTMLCanvasElement?this.canvas.remove():this.canvas=null,this.gpgpuCreatedLocally&&(this.gpgpu.program=null,this.gpgpu.dispose()),this.disposed=!0)}floatPrecision(){return this.floatPrecisionValue==null&&(this.floatPrecisionValue=J(()=>{if(!X().get("WEBGL_RENDER_FLOAT32_ENABLED")){let e=X().getBool("DEBUG");X().set("DEBUG",!1);let t=this.abs(Se(1e-8)).dataSync()[0];if(X().set("DEBUG",e),t>0)return 32}return 16})),this.floatPrecisionValue}epsilon(){return this.floatPrecision()===32?une:cne}uploadToGPU(e){let t=this.texData.get(e),{shape:n,dtype:s,values:r,texture:a,usage:o,isPacked:i}=t;if(a!=null)return;let l=this.activeTimers!=null,u;l&&(u=v.now());let c=t.texShape;if(c==null&&(c=TS(n,i),t.texShape=c),r!=null){let p=sm(n),d,h=c[1],f=c[0],m=r instanceof Uint8Array||r instanceof Uint8ClampedArray;(i||!m)&&([h,f]=ed(c[0],c[1])),i?d=new ste(p,m):d=new nte(p,m);let g=m?[f,h]:c,y=this.makeTensorInfo(g,s),x=this.texData.get(y.dataId);m?x.usage=qs.PIXELS:x.usage=qs.UPLOAD,x.texShape=g,this.gpgpu.uploadDenseMatrixToTexture(this.getTexture(y.dataId),h,f,r);let A=[[f,h]],b=!0,w=this.runWebGLProgram(d,[y],s,A,b),k=this.texData.get(w.dataId);t.texShape=k.texShape,t.isPacked=k.isPacked,t.usage=k.usage,X().get("ENGINE_COMPILE_ONLY")?this.disposeData(w.dataId):(t.texture=k.texture,t.values=null,this.texData.delete(w.dataId)),this.disposeIntermediateTensorInfo(y),l&&(this.uploadWaitMs+=v.now()-u)}else{let p=this.acquireTexture(c,o,s,i);t.texture=p}}convertAndCacheOnCPU(e,t){let n=this.texData.get(e),{dtype:s}=n;return this.releaseGPUData(e),t!=null&&(n.values=mne(t,s)),n.values}acquireTexture(e,t,n,s){if(this.numBytesInGPU+=this.computeBytes(e,n),!this.warnedAboutMemory&&this.numBytesInGPU>this.numMBBeforeWarning*1024*1024){let r=(this.numBytesInGPU/1024/1024).toFixed(2);this.warnedAboutMemory=!0,console.warn(`High memory usage in GPU: ${r} MB, most likely due to a memory leak`)}return this.textureManager.acquireTexture(e,t,s)}computeBytes(e,t){return e[0]*e[1]*v.bytesPerElement(t)}checkCompileCompletion(){for(let[,e]of Object.entries(this.binaryCache))this.checkCompletion_(e)}async checkCompileCompletionAsync(){let e=[];if(this.gpgpu.parallelCompilationExtension){for(let[,t]of Object.entries(this.binaryCache))e.push(this.checkCompletionAsync_(t));return Promise.all(e)}else{for(let[,t]of Object.entries(this.binaryCache)){let n=new Promise(s=>{try{this.checkCompletion_(t),s(!0)}catch(r){throw r}});e.push(n)}return Promise.all(e)}}async checkCompletionAsync_(e){return this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.parallelCompilationExtension.COMPLETION_STATUS_KHR)?this.checkCompletion_(e):(await jA(),this.checkCompletionAsync_(e))}checkCompletion_(e){if(this.gpgpu.gl.getProgramParameter(e.webGLProgram,this.gpgpu.gl.LINK_STATUS)===!1)throw console.log(this.gpgpu.gl.getProgramInfoLog(e.webGLProgram)),this.gpgpu.gl.getShaderParameter(e.fragmentShader,this.gpgpu.gl.COMPILE_STATUS)===!1?(Wx(e.source,this.gpgpu.gl.getShaderInfoLog(e.fragmentShader)),new Error("Failed to compile fragment shader.")):new Error("Failed to link vertex and fragment shaders.");return!0}getUniformLocations(){for(let[,e]of Object.entries(this.binaryCache)){let{uniformLocations:t,customUniformLocations:n,infLoc:s,nanLoc:r,inShapesLocations:a,inTexShapesLocations:o,outShapeLocation:i,outShapeStridesLocation:l,outTexShapeLocation:u}=zS(this.gpgpu,e.program,e.webGLProgram);e.uniformLocations=t,e.customUniformLocations=n,e.infLoc=s,e.nanLoc=r,e.inShapesLocations=a,e.inTexShapesLocations=o,e.outShapeLocation=i,e.outShapeStridesLocation=l,e.outTexShapeLocation=u}}};od.nextDataId=0;function mne(e,t){if(t==="float32"||t==="complex64")return e;if(t==="int32"||t==="bool"){let n=t==="int32"?new Int32Array(e.length):new Uint8Array(e.length);for(let s=0;s<n.length;++s)n[s]=Math.round(e[s]);return n}else throw new Error(`Unknown dtype ${t}`)}var gne="3.19.0";function i9(){X().set("WEBGL_FORCE_F16_TEXTURES",!0)}sh.isBrowser()&&jl("webgl",()=>new od,2);var yne={forceHalfFloat:i9},l9=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
-`,uc=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=C.assertAndGetBroadcastShape(t,n),this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
+`,lc=class{constructor(e,t,n){this.variableNames=["A","B"],this.outputShape=C.assertAndGetBroadcastShape(t,n),this.enableShapeUniforms=xs(this.outputShape.length),this.userCode=`
       float binaryOperation(float a, float b) {
         ${e}
       }
@@ -1256,12 +1256,12 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float b = getBAtOutCoords();
         setOutput(binaryOperation(a, b));
       }
-    `}},v2=`
+    `}},b2=`
   result.r = isNaN.r > 0. ? NAN : result.r;
   result.g = isNaN.g > 0. ? NAN : result.g;
   result.b = isNaN.b > 0. ? NAN : result.b;
   result.a = isNaN.a > 0. ? NAN : result.a;
-`,Mh=class{constructor(e,t,n,s=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=C.assertAndGetBroadcastShape(t,n);let r=this.outputShape.length;this.enableShapeUniforms=xs(r);let a="";if(s)if(r===0||v.sizeFromShape(this.outputShape)===1)a=`
+`,Oh=class{constructor(e,t,n,s=!1){this.variableNames=["A","B"],this.supportsBroadcasting=!0,this.packedInputs=!0,this.packedOutput=!0,this.outputShape=C.assertAndGetBroadcastShape(t,n);let r=this.outputShape.length;this.enableShapeUniforms=xs(r);let a="";if(s)if(r===0||v.sizeFromShape(this.outputShape)===1)a=`
           result.y = 0.;
           result.z = 0.;
           result.w = 0.;
@@ -1305,13 +1305,13 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
 
         setOutput(result);
       }
-    `}};function Ps(e){let{inputs:t,backend:n}=e,{x:s}=t;return n.incRef(s.dataId),{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}var Ane={kernelName:_o,backendName:"webgl",kernelFunc:Ps};function pi(e){let{inputs:t,backend:n}=e,{real:s,imag:r}=t,a=n.makeTensorInfo(s.shape,"complex64"),o=n.texData.get(a.dataId),i=Ps({inputs:{x:s},backend:n}),l=Ps({inputs:{x:r},backend:n});return o.complexTensorInfos={real:i,imag:l},a}var xne={kernelName:Lp,backendName:"webgl",kernelFunc:pi},u9="return (a < 0.) ? b * a : a;",c9=`
+    `}};function Ps(e){let{inputs:t,backend:n}=e,{x:s}=t;return n.incRef(s.dataId),{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}var Ane={kernelName:Ro,backendName:"webgl",kernelFunc:Ps};function di(e){let{inputs:t,backend:n}=e,{real:s,imag:r}=t,a=n.makeTensorInfo(s.shape,"complex64"),o=n.texData.get(a.dataId),i=Ps({inputs:{x:s},backend:n}),l=Ps({inputs:{x:r},backend:n});return o.complexTensorInfos={real:i,imag:l},a}var xne={kernelName:zp,backendName:"webgl",kernelFunc:di},u9="return (a < 0.) ? b * a : a;",c9=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function bne(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s,o=n.makeTensorInfo([],"float32",v.createScalarValue(a,"float32")),i=Z().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Mh(c9,r.shape,o.shape):new uc(u9,r.shape,o.shape),l=n.runWebGLProgram(i,[r,o],"float32");return n.disposeIntermediateTensorInfo(o),l}var vne={kernelName:Do,backendName:"webgl",kernelFunc:bne},d9="return (a < 0.) ? b * a : a;",p9=`
+`;function bne(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s,o=n.makeTensorInfo([],"float32",v.createScalarValue(a,"float32")),i=X().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Oh(c9,r.shape,o.shape):new lc(u9,r.shape,o.shape),l=n.runWebGLProgram(i,[r,o],"float32");return n.disposeIntermediateTensorInfo(o),l}var vne={kernelName:_o,backendName:"webgl",kernelFunc:bne},d9="return (a < 0.) ? b * a : a;",p9=`
   vec4 aLessThanZero = vec4(lessThan(a, vec4(0.)));
   return (aLessThanZero * (b * a)) + ((vec4(1.0) - aLessThanZero) * a);
-`;function wne(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t,a=Z().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Mh(p9,s.shape,r.shape):new uc(d9,s.shape,r.shape);return n.runWebGLProgram(a,[s,r],"float32")}var kne={kernelName:Go,backendName:"webgl",kernelFunc:wne},ld="if (isnan(x)) return x;",Ine=`
+`;function wne(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t,a=X().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Oh(p9,s.shape,r.shape):new lc(d9,s.shape,r.shape);return n.runWebGLProgram(a,[s,r],"float32")}var kne={kernelName:Uo,backendName:"webgl",kernelFunc:wne},id="if (isnan(x)) return x;",Ine=`
   if (isnan(a)) return a;
   if (isnan(b)) return b;
 `,Sne=`
@@ -1319,7 +1319,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
   result.g = isNaN.g > 0. ? NAN : result.g;
   result.b = isNaN.b > 0. ? NAN : result.b;
   result.a = isNaN.a > 0. ? NAN : result.a;
-`;function ct({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:s}){return({inputs:r,backend:a})=>{let{x:o}=r,i=a,l=s||o.dtype;if(i.shouldExecuteOnCPU([o])&&n!=null){let p=i.texData.get(o.dataId),d=n(p.values,l);return i.makeTensorInfo(o.shape,l,d)}let u=Z().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return u?c=new Ui(o.shape,t):c=new pa(o.shape,e),i.runWebGLProgram(c,[o],l)}}function Rn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:s=!1,cpuKernelImpl:r,dtype:a}){return({inputs:o,backend:i})=>{let{a:l,b:u}=o,c=i;if(s&&l.dtype==="complex64"){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[g,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(A=>{let[b,w]=A,k={dataId:b.dataId,dtype:b.dtype,shape:l.shape},S={dataId:w.dataId,dtype:w.dtype,shape:u.shape},E=new uc(e,l.shape,u.shape);return c.runWebGLProgram(E,[k,S],On(b.dtype,w.dtype))}),x=pi({inputs:{real:g,imag:y},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(y),x}let p=a||On(l.dtype,u.dtype);if((l.dtype==="string"||u.dtype==="string"||c.shouldExecuteOnCPU([l,u]))&&r!=null){let f=c.texData.get(l.dataId).values,m=c.texData.get(u.dataId).values,g=l.dtype==="string"?C.fromUint8ToStringArray(f):f,y=l.dtype==="string"?C.fromUint8ToStringArray(m):m,[x,A]=r(l.shape,u.shape,g,y,p),b=c.makeTensorInfo(A,p),w=c.texData.get(b.dataId);return w.values=x,b}let d=Z().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,h;return d?h=new Mh(t,l.shape,u.shape,n):h=new uc(e,l.shape,u.shape),c.runWebGLProgram(h,[l,u],p)}}function w2(e,t=!1){if(e==="linear")return t?nne:Yte;if(e==="relu")return t?rne:Qte;if(e==="elu")return t?sne:Jte;if(e==="relu6")return t?ane:ene;if(e==="prelu")return t?p9:d9;if(e==="leakyrelu")return t?c9:u9;if(e==="sigmoid")return t?one:tne;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var h9=class{constructor(e,t,n,s=!1,r=!1,a=!1,o=null,i=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n,this.enableShapeUniforms=xs(this.outputShape.length);let u=s?e[1]:e[2],c=Math.ceil(u/2),p=s?"i * 2, rc.y":"rc.y, i * 2",d=r?"rc.z, i * 2":"i * 2, rc.z",h=s?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",g="";o&&(i?m=`vec4 activation(vec4 a) {
+`;function ct({opSnippet:e,packedOpSnippet:t,cpuKernelImpl:n,dtype:s}){return({inputs:r,backend:a})=>{let{x:o}=r,i=a,l=s||o.dtype;if(i.shouldExecuteOnCPU([o])&&n!=null){let p=i.texData.get(o.dataId),d=n(p.values,l);return i.makeTensorInfo(o.shape,l,d)}let u=X().getBool("WEBGL_PACK_UNARY_OPERATIONS")&&t!=null,c;return u?c=new Vi(o.shape,t):c=new da(o.shape,e),i.runWebGLProgram(c,[o],l)}}function Rn({opSnippet:e,packedOpSnippet:t,checkOutOfBounds:n=!1,supportsComplex:s=!1,cpuKernelImpl:r,dtype:a}){return({inputs:o,backend:i})=>{let{a:l,b:u}=o,c=i;if(s&&l.dtype==="complex64"){let f=c.texData.get(l.dataId),m=c.texData.get(u.dataId),[g,y]=[[f.complexTensorInfos.real,m.complexTensorInfos.real],[f.complexTensorInfos.imag,m.complexTensorInfos.imag]].map(A=>{let[b,w]=A,k={dataId:b.dataId,dtype:b.dtype,shape:l.shape},S={dataId:w.dataId,dtype:w.dtype,shape:u.shape},E=new lc(e,l.shape,u.shape);return c.runWebGLProgram(E,[k,S],On(b.dtype,w.dtype))}),x=di({inputs:{real:g,imag:y},backend:c});return c.disposeIntermediateTensorInfo(g),c.disposeIntermediateTensorInfo(y),x}let p=a||On(l.dtype,u.dtype);if((l.dtype==="string"||u.dtype==="string"||c.shouldExecuteOnCPU([l,u]))&&r!=null){let f=c.texData.get(l.dataId).values,m=c.texData.get(u.dataId).values,g=l.dtype==="string"?C.fromUint8ToStringArray(f):f,y=l.dtype==="string"?C.fromUint8ToStringArray(m):m,[x,A]=r(l.shape,u.shape,g,y,p),b=c.makeTensorInfo(A,p),w=c.texData.get(b.dataId);return w.values=x,b}let d=X().getBool("WEBGL_PACK_BINARY_OPERATIONS")&&t!=null,h;return d?h=new Oh(t,l.shape,u.shape,n):h=new lc(e,l.shape,u.shape),c.runWebGLProgram(h,[l,u],p)}}function v2(e,t=!1){if(e==="linear")return t?nne:Yte;if(e==="relu")return t?rne:Qte;if(e==="elu")return t?sne:Jte;if(e==="relu6")return t?ane:ene;if(e==="prelu")return t?p9:d9;if(e==="leakyrelu")return t?c9:u9;if(e==="sigmoid")return t?one:tne;throw new Error(`Activation ${e} has not been implemented for the WebGL backend.`)}var h9=class{constructor(e,t,n,s=!1,r=!1,a=!1,o=null,i=!1,l=!1){this.variableNames=["matrixA","matrixB"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=n,this.enableShapeUniforms=xs(this.outputShape.length);let u=s?e[1]:e[2],c=Math.ceil(u/2),p=s?"i * 2, rc.y":"rc.y, i * 2",d=r?"rc.z, i * 2":"i * 2, rc.z",h=s?["a.xxyy","a.zzww"]:["a.xxzz","a.yyww"],f=r?["b.xzxz","b.ywyw"]:["b.xyxy","b.zwzw"],m="",g="";o&&(i?m=`vec4 activation(vec4 a) {
           vec4 b = getPreluActivationWeightsAtOutCoords();
           ${o}
         }`:l?m=`vec4 activation(vec4 a) {
@@ -1371,7 +1371,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         float bimag = getBImagAtOutCoords();
         setOutput(binaryOpComplex(areal, aimag, breal, bimag));
       }
-    `}},A7="return a * b;";function Yx(e){let{inputs:t,backend:n}=e,{a:s,b:r}=t,a=C.upcastType(s.dtype,r.dtype);if(s.dtype==="complex64"){let i=n.texData.get(s.dataId),l=n.texData.get(r.dataId),u=new y7(g7.REAL,s.shape,r.shape),c=new y7(g7.IMAG,s.shape,r.shape),p=[{dataId:i.complexTensorInfos.real.dataId,dtype:i.complexTensorInfos.real.dtype,shape:s.shape},{dataId:i.complexTensorInfos.imag.dataId,dtype:i.complexTensorInfos.imag.dtype,shape:s.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:r.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:r.shape}],d=n.runWebGLProgram(u,p,"float32"),h=n.runWebGLProgram(c,p,"float32"),f=pi({inputs:{real:d,imag:h},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),f}if(n.shouldExecuteOnCPU([s,r])){let i=n.texData.get(s.dataId),l=n.texData.get(r.dataId),[u,c]=Ite(s.shape,r.shape,i.values,l.values,a),p=n.makeTensorInfo(c,a),d=n.texData.get(p.dataId);return d.values=u,p}let o;return Z().getBool("WEBGL_PACK_BINARY_OPERATIONS")?o=new Mh(A7,s.shape,r.shape):o=new uc(A7,s.shape,r.shape),n.runWebGLProgram(o,[s,r],a)}var Cne={kernelName:Wo,backendName:"webgl",kernelFunc:Yx};function Tne(e,t,n){let s=[sl(e.shape),...rl(e.shape)],r={dtype:e.dtype,shape:s,dataId:e.dataId},a=[sl(t),...rl(t)],o=new o9(a,s),i=!0,l=[s],u=n.runWebGLProgram(o,[r],e.dtype,l,i);return{dataId:u.dataId,shape:t,dtype:u.dtype}}function be(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{shape:a}=s,o=n,i=v.sizeFromShape(r.shape),l=v.inferFromImplicitShape(a,i),u=v.sizeFromShape(l);v.assert(i===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${r.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`);let c=o.texData.get(r.dataId);return c.isPacked&&!Dp(r.shape,l)&&!(c.texture!==null&&Dp(c.shape,l))?Tne(r,l,o):(o.incRef(r.dataId),{dataId:r.dataId,shape:l,dtype:r.dtype})}var Nne={kernelName:_l,backendName:"webgl",kernelFunc:be},x7=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:s,inSize:r,outSize:a}=e;this.outputShape=[s,a];let o=Math.floor(n/4)*4,i=n%4,l="sumValue += dot(values, ones);";if(t!=null){let c=1/t;l=`sumValue += dot(values * ${v.isInt(c)?c.toPrecision(2):c}, ones);`}let u="";r%n>0&&(u=`
+    `}},A7="return a * b;";function Yx(e){let{inputs:t,backend:n}=e,{a:s,b:r}=t,a=C.upcastType(s.dtype,r.dtype);if(s.dtype==="complex64"){let i=n.texData.get(s.dataId),l=n.texData.get(r.dataId),u=new y7(g7.REAL,s.shape,r.shape),c=new y7(g7.IMAG,s.shape,r.shape),p=[{dataId:i.complexTensorInfos.real.dataId,dtype:i.complexTensorInfos.real.dtype,shape:s.shape},{dataId:i.complexTensorInfos.imag.dataId,dtype:i.complexTensorInfos.imag.dtype,shape:s.shape},{dataId:l.complexTensorInfos.real.dataId,dtype:l.complexTensorInfos.real.dtype,shape:r.shape},{dataId:l.complexTensorInfos.imag.dataId,dtype:l.complexTensorInfos.imag.dtype,shape:r.shape}],d=n.runWebGLProgram(u,p,"float32"),h=n.runWebGLProgram(c,p,"float32"),f=di({inputs:{real:d,imag:h},backend:n});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),f}if(n.shouldExecuteOnCPU([s,r])){let i=n.texData.get(s.dataId),l=n.texData.get(r.dataId),[u,c]=Ite(s.shape,r.shape,i.values,l.values,a),p=n.makeTensorInfo(c,a),d=n.texData.get(p.dataId);return d.values=u,p}let o;return X().getBool("WEBGL_PACK_BINARY_OPERATIONS")?o=new Oh(A7,s.shape,r.shape):o=new lc(A7,s.shape,r.shape),n.runWebGLProgram(o,[s,r],a)}var Cne={kernelName:Bo,backendName:"webgl",kernelFunc:Yx};function Tne(e,t,n){let s=[nl(e.shape),...sl(e.shape)],r={dtype:e.dtype,shape:s,dataId:e.dataId},a=[nl(t),...sl(t)],o=new o9(a,s),i=!0,l=[s],u=n.runWebGLProgram(o,[r],e.dtype,l,i);return{dataId:u.dataId,shape:t,dtype:u.dtype}}function be(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{shape:a}=s,o=n,i=v.sizeFromShape(r.shape),l=v.inferFromImplicitShape(a,i),u=v.sizeFromShape(l);v.assert(i===u,()=>`The new shape (${l}) has ${u} elements and the old shape (${r.shape}) has ${i} elements. The new shape and old shape must have the same number of elements.`);let c=o.texData.get(r.dataId);return c.isPacked&&!_p(r.shape,l)&&!(c.texture!==null&&_p(c.shape,l))?Tne(r,l,o):(o.incRef(r.dataId),{dataId:r.dataId,shape:l,dtype:r.dtype})}var Nne={kernelName:Rl,backendName:"webgl",kernelFunc:be},x7=class{constructor(e,t){this.variableNames=["x"];let{windowSize:n,batchSize:s,inSize:r,outSize:a}=e;this.outputShape=[s,a];let o=Math.floor(n/4)*4,i=n%4,l="sumValue += dot(values, ones);";if(t!=null){let c=1/t;l=`sumValue += dot(values * ${v.isInt(c)?c.toPrecision(2):c}, ones);`}let u="";r%n>0&&(u=`
         if (inIdx < 0 || inIdx >= ${r}) {
           return 0.0;
         }
@@ -1516,7 +1516,7 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
         }
         setOutput(${l});
       }
-    `}};function Rne(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],s=C.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:s,outSize:Math.ceil(n/s)})}return t}function au(e,t,n,s){let r=Rne(e.shape),a=e;for(let o=0;o<r.length;o++){let{inSize:i,windowSize:l,outSize:u}=r[o],c,p;n==="mean"?c=o===0?new x7({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u},i):new x7({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u}):c=new Ene({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u},n),p=a,a=s.runWebGLProgram(c,[a],t),p.dataId!==e.dataId&&s.disposeIntermediateTensorInfo(p)}return a}var _ne=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let a=0;a<n.length;a++)n[a]=e[t[a]];this.outputShape=n,this.rank=n.length;let s=wt(this.rank),r=Dne(t);this.userCode=`
+    `}};function Rne(e){let t=[];for(;t.length===0||t[t.length-1].outSize!==1;){let n=t.length?t[t.length-1].outSize:e[1],s=C.computeOptimalWindowSize(n);t.push({inSize:n,windowSize:s,outSize:Math.ceil(n/s)})}return t}function ru(e,t,n,s){let r=Rne(e.shape),a=e;for(let o=0;o<r.length;o++){let{inSize:i,windowSize:l,outSize:u}=r[o],c,p;n==="mean"?c=o===0?new x7({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u},i):new x7({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u}):c=new Ene({windowSize:l,inSize:i,batchSize:e.shape[0],outSize:u},n),p=a,a=s.runWebGLProgram(c,[a],t),p.dataId!==e.dataId&&s.disposeIntermediateTensorInfo(p)}return a}var _ne=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let a=0;a<n.length;a++)n[a]=e[t[a]];this.outputShape=n,this.rank=n.length;let s=wt(this.rank),r=Dne(t);this.userCode=`
     void main() {
       ${s} resRC = getOutputCoords();
       setOutput(getA(${r}));
@@ -1538,14 +1538,14 @@ vec2 packedUVfrom3D(int texNumR, int texNumC,
       }
       setOutput(result);
     }
-    `}};function k2(e,t,n){let s=Z().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new $ne(e.shape,t):new _ne(e.shape,t);return n.runWebGLProgram(s,[e],e.dtype)}function Pne(e,t,n,s){let r=t,a=e.shape.length,o=v.parseAxisParam(r,e.shape),i=o,l=C.getAxesPermutation(i,a),u=l!=null,c=e;u&&(c=k2(e,l,s),i=C.getInnerMostAxes(i.length,a)),C.assertAxesAreInnerMostDims("sum",i,a);let[p,d]=C.computeOutAndReduceShapes(c.shape,i),h=p;n&&(h=C.expandShapeToKeepDim(p,o));let f=v.sizeFromShape(d),g=v.sizeFromShape(e.shape)/f,y=be({inputs:{x:c},attrs:{shape:[g,f]},backend:s}),x=sh(e.dtype),A=au(y,x,"sum",s),b=be({inputs:{x:A},attrs:{shape:h},backend:s});return s.disposeIntermediateTensorInfo(y),s.disposeIntermediateTensorInfo(A),u&&s.disposeIntermediateTensorInfo(c),b}function I2(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Pne(r,a,o,n)}var Fne={kernelName:ei,backendName:"webgl",kernelFunc:I2};function ts(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{perm:a}=s,o=n,i=r.shape.length,l=new Array(i);for(let c=0;c<l.length;c++)l[c]=r.shape[a[c]];let u;if(o.shouldExecuteOnCPU([r])){let p=o.texData.get(r.dataId).values,d=Zx(p,r.shape,r.dtype,a,l);u=o.makeTensorInfo(l,r.dtype);let h=o.texData.get(u.dataId);h.values=d}else u=k2(r,a,o);return u}var One={kernelName:Hr,backendName:"webgl",kernelFunc:ts},f9=1e3;function Fm({a:e,b:t,transposeA:n,transposeB:s,backend:r,bias:a=null,preluActivationWeights:o=null,leakyreluAlpha:i=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,p=n?e.shape[u-2]:e.shape[u-1],d=s?t.shape[c-1]:t.shape[c-2],h=n?e.shape[u-1]:e.shape[u-2],f=s?t.shape[c-2]:t.shape[c-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(m),x=v.sizeFromShape(g),b=Xl.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,f]);v.assert(p===d,()=>`Error in matMul: inner shapes (${p}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${s} must match.`);let w=n?[y,p,h]:[y,h,p],k=s?[x,f,d]:[x,d,f],S=be({inputs:{x:e},backend:r,attrs:{shape:w}}),E=be({inputs:{x:t},backend:r,attrs:{shape:k}}),R=[S,E],P=Math.max(y,x),_=n?S.shape[1]:S.shape[2],$=a!=null,T=o!=null,F=l==="leakyrelu",G=l!=null?w2(l,!0):null,q=$||T||F||G!=null,z;if((h===1||f===1)&&_>f9&&q===!1){let B=S,ee=E;n&&(B=ts({inputs:{x:S},backend:r,attrs:{perm:[0,2,1]}}),R.push(B)),s&&(ee=ts({inputs:{x:E},backend:r,attrs:{perm:[0,2,1]}}),R.push(ee));let Q=f!==1,oe=f===1,Y=B;Q&&(Y=be({inputs:{x:B},backend:r,attrs:{shape:[P,_,1]}}),R.push(Y));let ae=f===1?2:1,le=ee;oe&&(le=be({inputs:{x:ee},backend:r,attrs:{shape:[P,1,_]}}),R.push(le));let ye=Yx({inputs:{a:Y,b:le},backend:r});z=I2({inputs:{x:ye},backend:r,attrs:{axis:ae,keepDims:!0}}),R.push(ye)}else{let B=On(e.dtype,t.dtype),ee=new h9(w,k,[P,h,f],n,s,$,G,T,F),Q=[S,E];if(a!=null&&Q.push(a),T&&Q.push(o),F){let oe=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));Q.push(oe),R.push(oe)}z=r.runWebGLProgram(ee,Q,B)}let K=be({inputs:{x:z},backend:r,attrs:{shape:b}});R.push(z);for(let B of R)r.disposeIntermediateTensorInfo(B);return K}function Mne(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=s;return Fm({a:r,b:a,transposeA:l,transposeB:u,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:p,activation:c})}var zne={kernelName:Ja,backendName:"webgl",kernelFunc:Mne},b7="return abs(x);";function Lne(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])&&s.dtype!=="complex64"){let a=n.texData.get(s.dataId),o=s9(a.values);return n.makeTensorInfo(s.shape,s.dtype,o)}let r;return Z().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new Ui(s.shape,b7):r=new pa(s.shape,b7),n.runWebGLProgram(r,[s],s.dtype)}var Bne={kernelName:il,backendName:"webgl",kernelFunc:Lne},Wne=hr+`
+    `}};function w2(e,t,n){let s=X().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new $ne(e.shape,t):new _ne(e.shape,t);return n.runWebGLProgram(s,[e],e.dtype)}function Pne(e,t,n,s){let r=t,a=e.shape.length,o=v.parseAxisParam(r,e.shape),i=o,l=C.getAxesPermutation(i,a),u=l!=null,c=e;u&&(c=w2(e,l,s),i=C.getInnerMostAxes(i.length,a)),C.assertAxesAreInnerMostDims("sum",i,a);let[p,d]=C.computeOutAndReduceShapes(c.shape,i),h=p;n&&(h=C.expandShapeToKeepDim(p,o));let f=v.sizeFromShape(d),g=v.sizeFromShape(e.shape)/f,y=be({inputs:{x:c},attrs:{shape:[g,f]},backend:s}),x=nh(e.dtype),A=ru(y,x,"sum",s),b=be({inputs:{x:A},attrs:{shape:h},backend:s});return s.disposeIntermediateTensorInfo(y),s.disposeIntermediateTensorInfo(A),u&&s.disposeIntermediateTensorInfo(c),b}function k2(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Pne(r,a,o,n)}var Fne={kernelName:Qo,backendName:"webgl",kernelFunc:k2};function ts(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{perm:a}=s,o=n,i=r.shape.length,l=new Array(i);for(let c=0;c<l.length;c++)l[c]=r.shape[a[c]];let u;if(o.shouldExecuteOnCPU([r])){let p=o.texData.get(r.dataId).values,d=Zx(p,r.shape,r.dtype,a,l);u=o.makeTensorInfo(l,r.dtype);let h=o.texData.get(u.dataId);h.values=d}else u=w2(r,a,o);return u}var One={kernelName:Gr,backendName:"webgl",kernelFunc:ts},f9=1e3;function Pm({a:e,b:t,transposeA:n,transposeB:s,backend:r,bias:a=null,preluActivationWeights:o=null,leakyreluAlpha:i=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,p=n?e.shape[u-2]:e.shape[u-1],d=s?t.shape[c-1]:t.shape[c-2],h=n?e.shape[u-1]:e.shape[u-2],f=s?t.shape[c-2]:t.shape[c-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(m),x=v.sizeFromShape(g),b=ql.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,f]);v.assert(p===d,()=>`Error in matMul: inner shapes (${p}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${s} must match.`);let w=n?[y,p,h]:[y,h,p],k=s?[x,f,d]:[x,d,f],S=be({inputs:{x:e},backend:r,attrs:{shape:w}}),E=be({inputs:{x:t},backend:r,attrs:{shape:k}}),R=[S,E],P=Math.max(y,x),_=n?S.shape[1]:S.shape[2],$=a!=null,T=o!=null,F=l==="leakyrelu",G=l!=null?v2(l,!0):null,q=$||T||F||G!=null,z;if((h===1||f===1)&&_>f9&&q===!1){let B=S,ee=E;n&&(B=ts({inputs:{x:S},backend:r,attrs:{perm:[0,2,1]}}),R.push(B)),s&&(ee=ts({inputs:{x:E},backend:r,attrs:{perm:[0,2,1]}}),R.push(ee));let Q=f!==1,oe=f===1,Y=B;Q&&(Y=be({inputs:{x:B},backend:r,attrs:{shape:[P,_,1]}}),R.push(Y));let ae=f===1?2:1,le=ee;oe&&(le=be({inputs:{x:ee},backend:r,attrs:{shape:[P,1,_]}}),R.push(le));let ye=Yx({inputs:{a:Y,b:le},backend:r});z=k2({inputs:{x:ye},backend:r,attrs:{axis:ae,keepDims:!0}}),R.push(ye)}else{let B=On(e.dtype,t.dtype),ee=new h9(w,k,[P,h,f],n,s,$,G,T,F),Q=[S,E];if(a!=null&&Q.push(a),T&&Q.push(o),F){let oe=r.makeTensorInfo([],"float32",v.createScalarValue(i,"float32"));Q.push(oe),R.push(oe)}z=r.runWebGLProgram(ee,Q,B)}let Z=be({inputs:{x:z},backend:r,attrs:{shape:b}});R.push(z);for(let B of R)r.disposeIntermediateTensorInfo(B);return Z}function Mne(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=s;return Pm({a:r,b:a,transposeA:l,transposeB:u,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:p,activation:c})}var zne={kernelName:Ya,backendName:"webgl",kernelFunc:Mne},b7="return abs(x);";function Lne(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])&&s.dtype!=="complex64"){let a=n.texData.get(s.dataId),o=s9(a.values);return n.makeTensorInfo(s.shape,s.dtype,o)}let r;return X().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new Vi(s.shape,b7):r=new da(s.shape,b7),n.runWebGLProgram(r,[s],s.dtype)}var Bne={kernelName:ol,backendName:"webgl",kernelFunc:Lne},Wne=hr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return acos(x);
-`,Vne=ct({opSnippet:Wne}),Une={kernelName:pc,backendName:"webgl",kernelFunc:Vne},Gne=hr+`
+`,Vne=ct({opSnippet:Wne}),Une={kernelName:dc,backendName:"webgl",kernelFunc:Vne},Gne=hr+`
   if (x < 1.0) return NAN;
-return log(x + sqrt(x * x - 1.0));`,Hne=ct({opSnippet:Gne}),jne={kernelName:hc,backendName:"webgl",kernelFunc:Hne},v7="return a + b;",qne=Rn({opSnippet:v7,packedOpSnippet:v7,supportsComplex:!0,cpuKernelImpl:ate}),Xne={kernelName:xa,backendName:"webgl",kernelFunc:qne},Kne=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((r,a)=>`T${a}`);let n=[];this.variableNames.forEach(r=>{n.push(`float v${r} = get${r}AtOutCoords();`)});let s=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
+return log(x + sqrt(x * x - 1.0));`,Hne=ct({opSnippet:Gne}),jne={kernelName:pc,backendName:"webgl",kernelFunc:Hne},v7="return a + b;",qne=Rn({opSnippet:v7,packedOpSnippet:v7,supportsComplex:!0,cpuKernelImpl:ate}),Xne={kernelName:Aa,backendName:"webgl",kernelFunc:qne},Kne=class{constructor(e,t){this.outputShape=[],this.outputShape=e,this.variableNames=t.map((r,a)=>`T${a}`);let n=[];this.variableNames.forEach(r=>{n.push(`float v${r} = get${r}AtOutCoords();`)});let s=this.variableNames.map(r=>`v${r}`).join(" + ");this.userCode=`
       void main() {
         ${n.join(`
         `)}
@@ -1561,7 +1561,7 @@ return log(x + sqrt(x * x - 1.0));`,Hne=ct({opSnippet:Gne}),jne={kernelName:hc,b
         vec4 result = ${s};
         setOutput(result);
       }
-    `}};function im(e){let{inputs:t,backend:n}=e,s=t;if(s.length===1)return Ps({inputs:{x:s[0]},backend:n});if(s.length>Z().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let l=Math.floor(s.length/2),u=im({inputs:s.slice(0,l),backend:n}),c=im({inputs:s.slice(l),backend:n});return im({inputs:[u,c],backend:n})}let r=s.map(l=>l.dtype).reduce((l,u)=>On(l,u)),a=s.map(l=>l.shape),i=Z().getBool("WEBGL_PACK")?new Zne(s[0].shape,a):new Kne(s[0].shape,a);return n.runWebGLProgram(i,s,r)}var Yne={kernelName:po,backendName:"webgl",kernelFunc:im};function Jne(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=v.parseAxisParam(a,r.shape),u=l,c=C.getAxesPermutation(u,i),p=r;c!=null&&(p=ts({inputs:{x:r},backend:n,attrs:{perm:c}}),u=C.getInnerMostAxes(u.length,i)),C.assertAxesAreInnerMostDims("all",u,i);let[d,h]=C.computeOutAndReduceShapes(p.shape,u),f=v.sizeFromShape(h),m=be({inputs:{x:p},backend:n,attrs:{shape:[-1,f]}}),g=au(m,m.dtype,"all",n),y;if(o){let x=C.expandShapeToKeepDim(d,l);y=be({inputs:{x:g},backend:n,attrs:{shape:x}})}else y=be({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(p),y}var Qne={kernelName:fc,backendName:"webgl",kernelFunc:Jne};function ese(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=v.parseAxisParam(a,r.shape),u=l,c=C.getAxesPermutation(u,i),p=r;c!=null&&(p=ts({inputs:{x:r},backend:n,attrs:{perm:c}}),u=C.getInnerMostAxes(u.length,i)),C.assertAxesAreInnerMostDims("any",u,i);let[d,h]=C.computeOutAndReduceShapes(p.shape,u),f=v.sizeFromShape(h),m=be({inputs:{x:p},backend:n,attrs:{shape:[-1,f]}}),g=au(m,m.dtype,"any",n),y;if(o){let x=C.expandShapeToKeepDim(d,l);y=be({inputs:{x:g},backend:n,attrs:{shape:x}})}else y=be({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(p),y}var tse={kernelName:mc,backendName:"webgl",kernelFunc:ese},nse=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:s,batchSize:r,outSize:a}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[r,a];let o=t==="max"?">":"<",i=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
+    `}};function om(e){let{inputs:t,backend:n}=e,s=t;if(s.length===1)return Ps({inputs:{x:s[0]},backend:n});if(s.length>X().get("WEBGL_MAX_TEXTURES_IN_SHADER")){let l=Math.floor(s.length/2),u=om({inputs:s.slice(0,l),backend:n}),c=om({inputs:s.slice(l),backend:n});return om({inputs:[u,c],backend:n})}let r=s.map(l=>l.dtype).reduce((l,u)=>On(l,u)),a=s.map(l=>l.shape),i=X().getBool("WEBGL_PACK")?new Zne(s[0].shape,a):new Kne(s[0].shape,a);return n.runWebGLProgram(i,s,r)}var Yne={kernelName:co,backendName:"webgl",kernelFunc:om};function Jne(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=v.parseAxisParam(a,r.shape),u=l,c=C.getAxesPermutation(u,i),p=r;c!=null&&(p=ts({inputs:{x:r},backend:n,attrs:{perm:c}}),u=C.getInnerMostAxes(u.length,i)),C.assertAxesAreInnerMostDims("all",u,i);let[d,h]=C.computeOutAndReduceShapes(p.shape,u),f=v.sizeFromShape(h),m=be({inputs:{x:p},backend:n,attrs:{shape:[-1,f]}}),g=ru(m,m.dtype,"all",n),y;if(o){let x=C.expandShapeToKeepDim(d,l);y=be({inputs:{x:g},backend:n,attrs:{shape:x}})}else y=be({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(p),y}var Qne={kernelName:hc,backendName:"webgl",kernelFunc:Jne};function ese(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=v.parseAxisParam(a,r.shape),u=l,c=C.getAxesPermutation(u,i),p=r;c!=null&&(p=ts({inputs:{x:r},backend:n,attrs:{perm:c}}),u=C.getInnerMostAxes(u.length,i)),C.assertAxesAreInnerMostDims("any",u,i);let[d,h]=C.computeOutAndReduceShapes(p.shape,u),f=v.sizeFromShape(h),m=be({inputs:{x:p},backend:n,attrs:{shape:[-1,f]}}),g=ru(m,m.dtype,"any",n),y;if(o){let x=C.expandShapeToKeepDim(d,l);y=be({inputs:{x:g},backend:n,attrs:{shape:x}})}else y=be({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(p),y}var tse={kernelName:fc,backendName:"webgl",kernelFunc:ese},nse=class{constructor(e,t,n){this.variableNames=["A"];let{windowSize:s,batchSize:r,outSize:a}=e;n||this.variableNames.push("bestIndicesA"),this.outputShape=[r,a];let o=t==="max"?">":"<",i=n?"inOffset + i;":"round(getBestIndicesA(batch, inOffset + i));";this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
@@ -1643,23 +1643,23 @@ return log(x + sqrt(x * x - 1.0));`,Hne=ct({opSnippet:Gne}),jne={kernelName:hc,b
         }
         setOutput(bestIndex);
       }
-    `}};function m9(e,t,n,s=null){let r=t.shape[0],a=t.shape[1];s!=null&&(r=s.shape[0],a=s.shape[1]);let o=C.computeOptimalWindowSize(a),i={windowSize:o,inSize:a,batchSize:r,outSize:Math.ceil(a/o)},l=new nse(i,n,s==null),u=[t];s!=null&&u.push(s);let c=e.runWebGLProgram(l,u,"int32");if(c.shape[1]===1)return c;let p=m9(e,t,n,c);return e.disposeIntermediateTensorInfo(c),p}function g9(e,t,n,s=null){let r=s!=null?s.shape:t.shape,a=r[r.length-1],o=C.computeOptimalWindowSize(a),i=new sse(r,o,n,s==null),l=s==null?[t]:[t,s],u=e.runWebGLProgram(i,l,"int32");if(u.shape.length===t.shape.length){let c=g9(e,t,n,u);return e.disposeIntermediateTensorInfo(u),c}return u}function y9(e,t,n,s){let r=[n];if(C.assertAxesAreInnerMostDims("arg"+s.charAt(0).toUpperCase()+s.slice(1),r,t.shape.length),!Z().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let a=[],o=e.texData.get(t.dataId),i=o!==null&&o.isPacked,l=t;i&&(l=e.unpackTensor(t),a.push(l));let[u,c]=C.computeOutAndReduceShapes(l.shape,r),p=v.sizeFromShape(c),d=be({inputs:{x:l},backend:e,attrs:{shape:[-1,p]}});a.push(d);let h=m9(e,d,s);a.push(h);let f=be({inputs:{x:h},backend:e,attrs:{shape:u}});return a.forEach(m=>e.disposeIntermediateTensorInfo(m)),f}return g9(e,t,s)}function rse(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=ts({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMax",[o[0]],l.shape.length);let c=y9(n,l,o[0],"max");return u.forEach(p=>n.disposeIntermediateTensorInfo(p)),c}var ase={kernelName:ho,backendName:"webgl",kernelFunc:rse};function ose(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=ts({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMin",[o[0]],l.shape.length);let c=y9(n,l,o[0],"min");return u.forEach(p=>n.disposeIntermediateTensorInfo(p)),c}var ise={kernelName:gc,backendName:"webgl",kernelFunc:ose},lse=hr+`
+    `}};function m9(e,t,n,s=null){let r=t.shape[0],a=t.shape[1];s!=null&&(r=s.shape[0],a=s.shape[1]);let o=C.computeOptimalWindowSize(a),i={windowSize:o,inSize:a,batchSize:r,outSize:Math.ceil(a/o)},l=new nse(i,n,s==null),u=[t];s!=null&&u.push(s);let c=e.runWebGLProgram(l,u,"int32");if(c.shape[1]===1)return c;let p=m9(e,t,n,c);return e.disposeIntermediateTensorInfo(c),p}function g9(e,t,n,s=null){let r=s!=null?s.shape:t.shape,a=r[r.length-1],o=C.computeOptimalWindowSize(a),i=new sse(r,o,n,s==null),l=s==null?[t]:[t,s],u=e.runWebGLProgram(i,l,"int32");if(u.shape.length===t.shape.length){let c=g9(e,t,n,u);return e.disposeIntermediateTensorInfo(u),c}return u}function y9(e,t,n,s){let r=[n];if(C.assertAxesAreInnerMostDims("arg"+s.charAt(0).toUpperCase()+s.slice(1),r,t.shape.length),!X().getBool("WEBGL_PACK_REDUCE")||t.shape.length<=2){let a=[],o=e.texData.get(t.dataId),i=o!==null&&o.isPacked,l=t;i&&(l=e.unpackTensor(t),a.push(l));let[u,c]=C.computeOutAndReduceShapes(l.shape,r),p=v.sizeFromShape(c),d=be({inputs:{x:l},backend:e,attrs:{shape:[-1,p]}});a.push(d);let h=m9(e,d,s);a.push(h);let f=be({inputs:{x:h},backend:e,attrs:{shape:u}});return a.forEach(m=>e.disposeIntermediateTensorInfo(m)),f}return g9(e,t,s)}function rse(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=ts({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMax",[o[0]],l.shape.length);let c=y9(n,l,o[0],"max");return u.forEach(p=>n.disposeIntermediateTensorInfo(p)),c}var ase={kernelName:po,backendName:"webgl",kernelFunc:rse};function ose(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=ts({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMin",[o[0]],l.shape.length);let c=y9(n,l,o[0],"min");return u.forEach(p=>n.disposeIntermediateTensorInfo(p)),c}var ise={kernelName:mc,backendName:"webgl",kernelFunc:ose},lse=hr+`
   if (abs(x) > 1.) {
     return NAN;
   }
   return asin(x);
-`,use=ct({opSnippet:lse}),cse={kernelName:yc,backendName:"webgl",kernelFunc:use},dse=hr+"return log(x + sqrt(x * x + 1.0));",pse=ct({opSnippet:dse}),hse={kernelName:Ac,backendName:"webgl",kernelFunc:pse},fse=hr+`
+`,use=ct({opSnippet:lse}),cse={kernelName:gc,backendName:"webgl",kernelFunc:use},dse=hr+"return log(x + sqrt(x * x + 1.0));",pse=ct({opSnippet:dse}),hse={kernelName:yc,backendName:"webgl",kernelFunc:pse},fse=hr+`
   return atan(x);
-`,mse=ct({opSnippet:fse}),gse={kernelName:xc,backendName:"webgl",kernelFunc:mse},yse=Ine+`
+`,mse=ct({opSnippet:fse}),gse={kernelName:Ac,backendName:"webgl",kernelFunc:mse},yse=Ine+`
   return atan(a, b);
 `,Ase=`
   vec4 result = atan(a, b);
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
   `+Sne+`
   return result;
-`,xse=Rn({opSnippet:yse,packedOpSnippet:Ase}),bse={kernelName:vc,backendName:"webgl",kernelFunc:xse},vse=hr+`
+`,xse=Rn({opSnippet:yse,packedOpSnippet:Ase}),bse={kernelName:bc,backendName:"webgl",kernelFunc:xse},vse=hr+`
   if ((x < -1.0) || (x > 1.0)) return NAN;
-return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernelName:bc,backendName:"webgl",kernelFunc:wse},$p=class{constructor(e,t,n,s=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,o=e.strideHeight,i=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterHeight,p=e.effectiveFilterWidth,d=e.padInfo.top,h=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let S=">=";this.userCode=`
+return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernelName:xc,backendName:"webgl",kernelFunc:wse},Dp=class{constructor(e,t,n,s=!1,r=!1){if(this.variableNames=["x"],t==="avg"&&n)throw new Error("Cannot compute positions for average pool.");let a=e.filterWidth,o=e.strideHeight,i=e.strideWidth,l=e.dilationHeight,u=e.dilationWidth,c=e.effectiveFilterHeight,p=e.effectiveFilterWidth,d=e.padInfo.top,h=e.padInfo.left;this.outputShape=e.outShape;let f=t==="avg",m=`((batch  * ${e.inHeight} + xR) * ${e.inWidth} + xC) * ${e.inChannels} + d`,g=`(xR * ${e.inWidth} + xC) * ${e.inChannels} + d`,y="0.0";if(f||(y="-1.0 / 1e-20"),n){let S=">=";this.userCode=`
         const ivec2 strides = ivec2(${o}, ${i});
         const ivec2 pads = ivec2(${d}, ${h});
 
@@ -1963,7 +1963,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
           setOutput(${w});
         }
       }
-    `}};function Ise(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;nd(r,"avgPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;v.assert(C.eitherStridesOrDilationsAreOne(o,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=C.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Ps({inputs:{x:r},backend:n});let p=new $p(c,"avg",!1);return n.runWebGLProgram(p,[r],"float32")}var Sse={kernelName:fo,backendName:"webgl",kernelFunc:Ise};function Cse(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l,dataFormat:u}=s,c=[1,1,1],p=C.computePool3DInfo(r.shape,a,o,c,i,l,u),d=new Jx(p,"avg",!1);return n.runWebGLProgram(d,[r],"float32")}var Tse={kernelName:zp,backendName:"webgl",kernelFunc:Cse},Nse=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,s=e.strideHeight,r=e.strideWidth,a=e.dilationHeight,o=e.dilationWidth,i=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=i-1-e.padInfo.top,c=l-1-e.padInfo.left,p=1/(t*n);this.userCode=`
+    `}};function Ise(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;td(r,"avgPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;v.assert(C.eitherStridesOrDilationsAreOne(o,u),()=>`Error in avgPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=C.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Ps({inputs:{x:r},backend:n});let p=new Dp(c,"avg",!1);return n.runWebGLProgram(p,[r],"float32")}var Sse={kernelName:ho,backendName:"webgl",kernelFunc:Ise};function Cse(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l,dataFormat:u}=s,c=[1,1,1],p=C.computePool3DInfo(r.shape,a,o,c,i,l,u),d=new Jx(p,"avg",!1);return n.runWebGLProgram(d,[r],"float32")}var Tse={kernelName:Mp,backendName:"webgl",kernelFunc:Cse},Nse=class{constructor(e){this.variableNames=["dy"],this.outputShape=e.inShape;let t=e.filterHeight,n=e.filterWidth,s=e.strideHeight,r=e.strideWidth,a=e.dilationHeight,o=e.dilationWidth,i=e.effectiveFilterHeight,l=e.effectiveFilterWidth,u=i-1-e.padInfo.top,c=l-1-e.padInfo.left,p=1/(t*n);this.userCode=`
       const ivec2 pads = ivec2(${u}, ${c});
       const float avgMultiplier = float(${p});
 
@@ -2061,7 +2061,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
         }
         setOutput(dotProd);
       }
-    `}};function Rse(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=s,p=[1,1,1],d=C.computePool3DInfo(o.shape,i,l,p,u,c),h=new Ese(d);return n.runWebGLProgram(h,[r],o.dtype)}var _se={kernelName:Hm,backendName:"webgl",kernelFunc:Rse};function Dse(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a;nd([r,a],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=s,c=C.computePool2DInfo(o.shape,i,l,1,u),p=new Nse(c);return n.runWebGLProgram(p,[r],o.dtype)}var $se={kernelName:Gm,backendName:"webgl",kernelFunc:Dse};function Pse(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;return Fm({a:r,b:a,transposeA:o,transposeB:i,backend:n})}var Fse={kernelName:mo,backendName:"webgl",kernelFunc:Pse},Ose=class{constructor(e,t,n,s,r,a){this.outputShape=[],this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,n);let o="0.0";s!=null&&(C.assertAndGetBroadcastShape(e,s),this.variableNames.push("offset"),o="getOffsetAtOutCoords()");let i="1.0";r!=null&&(C.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),i="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
+    `}};function Rse(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=s,p=[1,1,1],d=C.computePool3DInfo(o.shape,i,l,p,u,c),h=new Ese(d);return n.runWebGLProgram(h,[r],o.dtype)}var _se={kernelName:Gm,backendName:"webgl",kernelFunc:Rse};function Dse(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a;td([r,a],"avgPoolGrad");let{filterSize:i,strides:l,pad:u}=s,c=C.computePool2DInfo(o.shape,i,l,1,u),p=new Nse(c);return n.runWebGLProgram(p,[r],o.dtype)}var $se={kernelName:Um,backendName:"webgl",kernelFunc:Dse};function Pse(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;return Pm({a:r,b:a,transposeA:o,transposeB:i,backend:n})}var Fse={kernelName:fo,backendName:"webgl",kernelFunc:Pse},Ose=class{constructor(e,t,n,s,r,a){this.outputShape=[],this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,n);let o="0.0";s!=null&&(C.assertAndGetBroadcastShape(e,s),this.variableNames.push("offset"),o="getOffsetAtOutCoords()");let i="1.0";r!=null&&(C.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale"),i="getScaleAtOutCoords()"),this.outputShape=e,this.userCode=`
       void main() {
         float x = getXAtOutCoords();
         float mean = getMeanAtOutCoords();
@@ -2084,7 +2084,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
 
         setOutput((x - mean) * inv + offset);
       }
-    `}},zse=({inputs:e,backend:t,attrs:n})=>{let{x:s,mean:r,variance:a,offset:o,scale:i}=e;v.assert(r.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(o==null||r.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(i==null||r.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let u=[s,r,a],c=null;o!=null&&(c=o.shape,u.push(o));let p=null;i!=null&&(p=i.shape,u.push(i));let d=Z().getBool("WEBGL_PACK_NORMALIZATION")?new Mse(s.shape,r.shape,a.shape,c,p,l):new Ose(s.shape,r.shape,a.shape,c,p,l);return t.runWebGLProgram(d,u,u[0].dtype)},Lse={kernelName:Eo,backendName:"webgl",kernelFunc:zse},Bse=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=wt(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let n=Wse(this.rank),s,r=e.map((a,o)=>`sourceLoc.${oy[o]} = start[${o}] + coords.${oy[o]};`);s=`
+    `}},zse=({inputs:e,backend:t,attrs:n})=>{let{x:s,mean:r,variance:a,offset:o,scale:i}=e;v.assert(r.shape.length===a.shape.length,()=>"Batch normalization gradient requires mean and variance to have equal ranks."),v.assert(o==null||r.shape.length===o.shape.length,()=>"Batch normalization gradient requires mean and offset to have equal ranks."),v.assert(i==null||r.shape.length===i.shape.length,()=>"Batch normalization gradient requires mean and scale to have equal ranks.");let{varianceEpsilon:l}=n;l==null&&(l=.001);let u=[s,r,a],c=null;o!=null&&(c=o.shape,u.push(o));let p=null;i!=null&&(p=i.shape,u.push(i));let d=X().getBool("WEBGL_PACK_NORMALIZATION")?new Mse(s.shape,r.shape,a.shape,c,p,l):new Ose(s.shape,r.shape,a.shape,c,p,l);return t.runWebGLProgram(d,u,u[0].dtype)},Lse={kernelName:No,backendName:"webgl",kernelFunc:zse},Bse=class{constructor(e){this.variableNames=["source"],this.outputShape=e,this.rank=e.length;let t=wt(this.rank);this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let n=Wse(this.rank),s,r=e.map((a,o)=>`sourceLoc.${ay[o]} = start[${o}] + coords.${ay[o]};`);s=`
         ${t} sourceLoc;
         ${t} coords = getOutputCoords();
         ${r.join(`
@@ -2094,7 +2094,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
         ${s}
         setOutput(getSource(${n}));
       }
-    `}},oy=["x","y","z","w","u","v"];function Wse(e){if(e===1)return"sourceLoc";if(e<=6)return oy.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var Vse=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=wt(this.rank),n=Qn("coords",this.rank),s=Qn("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${s.slice(-2).join()})`,a=`getChannel(getSource(${s.join()}), ${r})`,o=`
+    `}},ay=["x","y","z","w","u","v"];function Wse(e){if(e===1)return"sourceLoc";if(e<=6)return ay.slice(0,e).map(t=>"sourceLoc."+t).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}var Vse=class{constructor(e){this.variableNames=["source"],this.packedInputs=!0,this.packedOutput=!0,this.outputShape=e,this.rank=e.length,this.customUniforms=[{name:"start",arrayIndex:this.rank,type:"int"}];let t=wt(this.rank),n=Qn("coords",this.rank),s=Qn("sourceLoc",this.rank),r=this.rank===1?"sourceLoc":`vec2(${s.slice(-2).join()})`,a=`getChannel(getSource(${s.join()}), ${r})`,o=`
       result.x = ${a};
       if (++${n[this.rank-1]} < ${e[this.rank-1]}) {
         ++${s[this.rank-1]};
@@ -2123,7 +2123,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
         ${i}
         setOutput(result);
       }
-    `}};function Use(e,t,n,s){let r=s.texData.get(e.dataId),a=s.makeTensorInfo(n,e.dtype),o=s.texData.get(a.dataId);Object.assign(o,r),o.refCount=1,o.shape=n,o.dtype=e.dtype;let i=Ut.computeFlatOffset(t,v.computeStrides(e.shape));r.slice&&(i+=r.slice.flatOffset),o.slice={flatOffset:i,origDataId:r.slice&&r.slice.origDataId||e.dataId};let l=s.dataRefCount.get(o.slice.origDataId)||1;return s.dataRefCount.set(o.slice.origDataId,l+1),a}function ud(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,size:o}=s,[i,l]=Ut.parseSliceParams(r,a,o);if(Ut.assertParamsValid(r,i,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,r.dtype,[]);if(n.shouldExecuteOnCPU([r])||r.dtype==="string"){let p=n.texData.get(r.dataId),d=Dte(p.values,i,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,d)}let{isPacked:u}=n.texData.get(r.dataId),c=Ut.isSliceContinous(r.shape,i,l);if(u||!c){let p=Z().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Vse(l):new Bse(l),d=[i];return n.runWebGLProgram(p,[r],r.dtype,d)}return n.uploadToGPU(r.dataId),Use(r,i,l,n)}var Gse={kernelName:Ol,backendName:"webgl",kernelFunc:ud},Hse=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s;v.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let i=a.reduce((x,A)=>x*A),l=C.getReshaped(r.shape,a,i),u=C.getPermuted(l.length,a.length),c=C.getReshapedPermuted(r.shape,a,i),p=C.getSliceBeginCoords(o,a.length),d=C.getSliceSize(c,o,a.length),h=[],f=be({inputs:{x:r},backend:n,attrs:{shape:l}}),m=ts({inputs:{x:f},backend:n,attrs:{perm:u}}),g=be({inputs:{x:m},backend:n,attrs:{shape:c}}),y=ud({inputs:{x:g},backend:n,attrs:{begin:p,size:d}});return h.push(f),h.push(m),h.push(g),h.forEach(x=>n.disposeIntermediateTensorInfo(x)),y},jse={kernelName:ll,backendName:"webgl",kernelFunc:Hse};function qse(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o}=s,i=n.readSync(r.dataId),l=n.readSync(a.dataId),u=n9(i,l,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,u)}var Xse={kernelName:jm,backendName:"webgl",kernelFunc:qse};function Kse(e){let{inputs:t,backend:n}=e,{s0:s,s1:r}=t,a=n.readSync(s.dataId),o=n.readSync(r.dataId),i=C.assertAndGetBroadcastShape(Array.from(a),Array.from(o));return n.makeTensorInfo([i.length],"int32",Int32Array.from(i))}var Zse={kernelName:qm,backendName:"webgl",kernelFunc:Kse},Yse="return float(a != b);",A9=Rn({opSnippet:Yse,cpuKernelImpl:Cte,dtype:"bool"}),Jse={kernelName:Sl,backendName:"webgl",kernelFunc:A9};function zh(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.texData.get(s.dataId);return Ps({inputs:{x:r.complexTensorInfos.real},backend:n})}var Qse={kernelName:qp,backendName:"webgl",kernelFunc:zh},ere="return float(int(x));";function tre(e,t){let n=new pa(e.shape,ere),s=t.runWebGLProgram(n,[e],"int32");return{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}function iy(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dtype:a}=s;if(a==="complex64"){if(r.dtype==="complex64")return Ps({inputs:{x:r},backend:n});let o=Wt(r.shape),i=iy({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=pi({inputs:{real:i,imag:o},backend:n});return o.dispose(),n.disposeIntermediateTensorInfo(i),l}if(r.dtype==="complex64"){let o=zh({inputs:{input:r},backend:n}),i=iy({inputs:{x:o},backend:n,attrs:{dtype:a}});return n.disposeIntermediateTensorInfo(o),i}if(!v.hasEncodingLoss(r.dtype,a)){let o=Ps({inputs:{x:r},backend:n});return{dataId:o.dataId,shape:o.shape,dtype:a}}if(a==="int32")return tre(r,n);if(a==="bool"){let o=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),l=A9({inputs:{a:r,b:o},backend:n});return n.disposeIntermediateTensorInfo(o),l}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${a}`)}var nre={kernelName:go,backendName:"webgl",kernelFunc:iy},w7="return ceil(x);",sre=ct({opSnippet:w7,packedOpSnippet:w7,cpuKernelImpl:ite}),rre={kernelName:yo,backendName:"webgl",kernelFunc:sre},are=class{constructor(e){this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=`
+    `}};function Use(e,t,n,s){let r=s.texData.get(e.dataId),a=s.makeTensorInfo(n,e.dtype),o=s.texData.get(a.dataId);Object.assign(o,r),o.refCount=1,o.shape=n,o.dtype=e.dtype;let i=Ut.computeFlatOffset(t,v.computeStrides(e.shape));r.slice&&(i+=r.slice.flatOffset),o.slice={flatOffset:i,origDataId:r.slice&&r.slice.origDataId||e.dataId};let l=s.dataRefCount.get(o.slice.origDataId)||1;return s.dataRefCount.set(o.slice.origDataId,l+1),a}function ld(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,size:o}=s,[i,l]=Ut.parseSliceParams(r,a,o);if(Ut.assertParamsValid(r,i,l),v.sizeFromShape(l)===0)return n.makeTensorInfo(l,r.dtype,[]);if(n.shouldExecuteOnCPU([r])||r.dtype==="string"){let p=n.texData.get(r.dataId),d=Dte(p.values,i,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,d)}let{isPacked:u}=n.texData.get(r.dataId),c=Ut.isSliceContinous(r.shape,i,l);if(u||!c){let p=X().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Vse(l):new Bse(l),d=[i];return n.runWebGLProgram(p,[r],r.dtype,d)}return n.uploadToGPU(r.dataId),Use(r,i,l,n)}var Gse={kernelName:Fl,backendName:"webgl",kernelFunc:ld},Hse=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s;v.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGL backend not implemented yet");let i=a.reduce((x,A)=>x*A),l=C.getReshaped(r.shape,a,i),u=C.getPermuted(l.length,a.length),c=C.getReshapedPermuted(r.shape,a,i),p=C.getSliceBeginCoords(o,a.length),d=C.getSliceSize(c,o,a.length),h=[],f=be({inputs:{x:r},backend:n,attrs:{shape:l}}),m=ts({inputs:{x:f},backend:n,attrs:{perm:u}}),g=be({inputs:{x:m},backend:n,attrs:{shape:c}}),y=ld({inputs:{x:g},backend:n,attrs:{begin:p,size:d}});return h.push(f),h.push(m),h.push(g),h.forEach(x=>n.disposeIntermediateTensorInfo(x)),y},jse={kernelName:il,backendName:"webgl",kernelFunc:Hse};function qse(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o}=s,i=n.readSync(r.dataId),l=n.readSync(a.dataId),u=n9(i,l,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,u)}var Xse={kernelName:Hm,backendName:"webgl",kernelFunc:qse};function Kse(e){let{inputs:t,backend:n}=e,{s0:s,s1:r}=t,a=n.readSync(s.dataId),o=n.readSync(r.dataId),i=C.assertAndGetBroadcastShape(Array.from(a),Array.from(o));return n.makeTensorInfo([i.length],"int32",Int32Array.from(i))}var Zse={kernelName:jm,backendName:"webgl",kernelFunc:Kse},Yse="return float(a != b);",A9=Rn({opSnippet:Yse,cpuKernelImpl:Cte,dtype:"bool"}),Jse={kernelName:Il,backendName:"webgl",kernelFunc:A9};function Mh(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.texData.get(s.dataId);return Ps({inputs:{x:r.complexTensorInfos.real},backend:n})}var Qse={kernelName:jp,backendName:"webgl",kernelFunc:Mh},ere="return float(int(x));";function tre(e,t){let n=new da(e.shape,ere),s=t.runWebGLProgram(n,[e],"int32");return{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}function oy(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dtype:a}=s;if(a==="complex64"){if(r.dtype==="complex64")return Ps({inputs:{x:r},backend:n});let o=Wt(r.shape),i=oy({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=di({inputs:{real:i,imag:o},backend:n});return o.dispose(),n.disposeIntermediateTensorInfo(i),l}if(r.dtype==="complex64"){let o=Mh({inputs:{input:r},backend:n}),i=oy({inputs:{x:o},backend:n,attrs:{dtype:a}});return n.disposeIntermediateTensorInfo(o),i}if(!v.hasEncodingLoss(r.dtype,a)){let o=Ps({inputs:{x:r},backend:n});return{dataId:o.dataId,shape:o.shape,dtype:a}}if(a==="int32")return tre(r,n);if(a==="bool"){let o=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),l=A9({inputs:{a:r,b:o},backend:n});return n.disposeIntermediateTensorInfo(o),l}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${a}`)}var nre={kernelName:mo,backendName:"webgl",kernelFunc:oy},w7="return ceil(x);",sre=ct({opSnippet:w7,packedOpSnippet:w7,cpuKernelImpl:ite}),rre={kernelName:go,backendName:"webgl",kernelFunc:sre},are=class{constructor(e){this.variableNames=["A"],this.customUniforms=[{name:"minVal",type:"float"},{name:"maxVal",type:"float"}],this.outputShape=e,this.userCode=`
 
       void main() {
         float value = getAAtOutCoords();
@@ -2145,7 +2145,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
 
         setOutput(clamp(value, vec4(minVal), vec4(maxVal)));
       }
-    `}};function ire(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i;Z().getBool("WEBGL_PACK_CLIP")?i=new ore(r.shape):i=new are(r.shape);let l=[[a],[o]];return n.runWebGLProgram(i,[r],r.dtype,l)}var lre={kernelName:ba,backendName:"webgl",kernelFunc:ire},ure=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
+    `}};function ire(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i;X().getBool("WEBGL_PACK_CLIP")?i=new ore(r.shape):i=new are(r.shape);let l=[[a],[o]];return n.runWebGLProgram(i,[r],r.dtype,l)}var lre={kernelName:xa,backendName:"webgl",kernelFunc:ire},ure=class{constructor(e){this.variableNames=["real","imag"],this.outputShape=e,this.userCode=`
       void main() {
         float re = abs(getRealAtOutCoords());
         float im = abs(getImagAtOutCoords());
@@ -2158,7 +2158,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
           mx == 0.0 ? 0.0 : mx * length(vec2(1, min(re, im)/mx))
         );
       }
-    `}};function k7(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function cre(e){let{inputs:t,backend:n}=e,{x:s}=t,r=n.texData.get(s.dataId),a=new ure(s.shape),o=[k7(s,r.complexTensorInfos.real),k7(s,r.complexTensorInfos.imag)];return n.runWebGLProgram(a,o,o[0].dtype)}var dre={kernelName:Bp,backendName:"webgl",kernelFunc:cre},pre=class{constructor(e){this.outputShape=[],this.outputShape=C.computeOutShape(e,1),this.variableNames=e.map((a,o)=>`T${o}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let a=1;a<t.length;a++)t[a]=t[a-1]+e[a][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let a=1;a<t.length;a++){let o=t[a-1];n.push(`else if (yC < ${t[a]}) setOutput(getT${a}(yR, yC-${o}));`)}let s=t.length,r=t[t.length-1];n.push(`else setOutput(getT${s}(yR, yC-${r}));`),this.userCode=`
+    `}};function k7(e,t){return{dataId:t.dataId,dtype:t.dtype,shape:e.shape}}function cre(e){let{inputs:t,backend:n}=e,{x:s}=t,r=n.texData.get(s.dataId),a=new ure(s.shape),o=[k7(s,r.complexTensorInfos.real),k7(s,r.complexTensorInfos.imag)];return n.runWebGLProgram(a,o,o[0].dtype)}var dre={kernelName:Lp,backendName:"webgl",kernelFunc:cre},pre=class{constructor(e){this.outputShape=[],this.outputShape=C.computeOutShape(e,1),this.variableNames=e.map((a,o)=>`T${o}`);let t=new Array(e.length-1);t[0]=e[0][1];for(let a=1;a<t.length;a++)t[a]=t[a-1]+e[a][1];let n=[`if (yC < ${t[0]}) setOutput(getT0(yR, yC));`];for(let a=1;a<t.length;a++){let o=t[a-1];n.push(`else if (yC < ${t[a]}) setOutput(getT${a}(yR, yC-${o}));`)}let s=t.length,r=t[t.length-1];n.push(`else setOutput(getT${s}(yR, yC-${r}));`),this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int yR = coords.x;
@@ -2173,12 +2173,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
         }`;for(let f=1;f<i.length;f++){let m=i[f-1];p+=`
         if (${l} < ${i[f]}  && ${l} >= ${i[f-1]}) {
           return getChannel(
-            getT${f}(${Yf(o,l,m)}),
-            vec2(${Yf(u,l,m)}));
+            getT${f}(${Zf(o,l,m)}),
+            vec2(${Zf(u,l,m)}));
         }`}let d=i.length,h=i[i.length-1];p+=`
         return getChannel(
-          getT${d}(${Yf(o,l,h)}),
-          vec2(${Yf(u,l,h)}));`,this.userCode=`
+          getT${d}(${Zf(o,l,h)}),
+          vec2(${Zf(u,l,h)}));`,this.userCode=`
       float getValue(${o.map(f=>"int "+f)}) {
         ${p}
       }
@@ -2204,7 +2204,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
         }
         setOutput(result);
       }
-    `}};function Yf(e,t,n){let s=e.indexOf(t);return e.map((a,o)=>o===s?`${a} - ${n}`:a).join()}function S2(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.texData.get(s.dataId);return Ps({inputs:{x:r.complexTensorInfos.imag},backend:n})}var fre={kernelName:Gp,backendName:"webgl",kernelFunc:S2};function dp(e,t,n){let s=e[0].dtype;if(s==="complex64"){let p=e.map(g=>zh({inputs:{input:g},backend:n})),d=e.map(g=>S2({inputs:{input:g},backend:n})),h=dp(p,t,n),f=dp(d,t,n),m=pi({inputs:{real:h,imag:f},backend:n});return p.forEach(g=>n.disposeIntermediateTensorInfo(g)),d.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),m}let r=n.shouldExecuteOnCPU(e);if(s==="string"&&(r=!0),r){let p=e.map(x=>{let A=v.sizeFromShape(x.shape.slice(t));return be({inputs:{x},backend:n,attrs:{shape:[-1,A]}})}),d=p.map(x=>({vals:n.readSync(x.dataId),shape:x.shape})),h=C.computeOutShape(p.map(x=>x.shape),1),f=p[0].shape[0]===1,m=lte(d,h,s,f),g=C.computeOutShape(e.map(x=>x.shape),t),y=n.makeTensorInfo(g,s,m);return p.forEach(x=>n.disposeIntermediateTensorInfo(x)),y}let a=Z().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(e.length>a){let p=[];for(let h=0;h<e.length;h+=a){let f=e.slice(h,h+a);p.push(dp(f,t,n))}let d=dp(p,t,n);for(let h of p)n.disposeIntermediateTensorInfo(h);return d}if(Z().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let p=new hre(e.map(d=>d.shape),t);return n.runWebGLProgram(p,e,s)}let{tensors2D:o,outShape:i}=mre(e,t,n),l=new pre(o.map(p=>p.shape)),u=n.runWebGLProgram(l,o,s);o.forEach(p=>n.disposeIntermediateTensorInfo(p));let c=be({inputs:{x:u},attrs:{shape:i},backend:n});return n.disposeIntermediateTensorInfo(u),c}function mre(e,t,n){let s=C.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>be({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:s}}function x9(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s,a=v.parseAxisParam(r,t[0].shape)[0],o=C.computeOutShape(t.map(u=>u.shape),a);if(v.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let i=t.filter(u=>v.sizeFromShape(u.shape)>0);if(i.length===1)return Ps({inputs:{x:i[0]},backend:n});let l=i.map(u=>u.shape);return C.assertParamsConsistent(l,a),dp(i,a,n)}var gre={kernelName:ul,backendName:"webgl",kernelFunc:x9},b9=class{constructor(e,t=!1,n=null,s=!1,r=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.padInfo.top,o=e.padInfo.left,i=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,p=e.filterHeight,d=e.filterWidth,h=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",g=m?1:2,y=m?2:3,x=m?3:1,A="",b="";n&&(s?A=`float activation(float a) {
+    `}};function Zf(e,t,n){let s=e.indexOf(t);return e.map((a,o)=>o===s?`${a} - ${n}`:a).join()}function I2(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.texData.get(s.dataId);return Ps({inputs:{x:r.complexTensorInfos.imag},backend:n})}var fre={kernelName:Up,backendName:"webgl",kernelFunc:I2};function cp(e,t,n){let s=e[0].dtype;if(s==="complex64"){let p=e.map(g=>Mh({inputs:{input:g},backend:n})),d=e.map(g=>I2({inputs:{input:g},backend:n})),h=cp(p,t,n),f=cp(d,t,n),m=di({inputs:{real:h,imag:f},backend:n});return p.forEach(g=>n.disposeIntermediateTensorInfo(g)),d.forEach(g=>n.disposeIntermediateTensorInfo(g)),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),m}let r=n.shouldExecuteOnCPU(e);if(s==="string"&&(r=!0),r){let p=e.map(x=>{let A=v.sizeFromShape(x.shape.slice(t));return be({inputs:{x},backend:n,attrs:{shape:[-1,A]}})}),d=p.map(x=>({vals:n.readSync(x.dataId),shape:x.shape})),h=C.computeOutShape(p.map(x=>x.shape),1),f=p[0].shape[0]===1,m=lte(d,h,s,f),g=C.computeOutShape(e.map(x=>x.shape),t),y=n.makeTensorInfo(g,s,m);return p.forEach(x=>n.disposeIntermediateTensorInfo(x)),y}let a=X().getNumber("WEBGL_MAX_TEXTURES_IN_SHADER");if(e.length>a){let p=[];for(let h=0;h<e.length;h+=a){let f=e.slice(h,h+a);p.push(cp(f,t,n))}let d=cp(p,t,n);for(let h of p)n.disposeIntermediateTensorInfo(h);return d}if(X().getBool("WEBGL_PACK_ARRAY_OPERATIONS")&&e[0].shape.length>1){let p=new hre(e.map(d=>d.shape),t);return n.runWebGLProgram(p,e,s)}let{tensors2D:o,outShape:i}=mre(e,t,n),l=new pre(o.map(p=>p.shape)),u=n.runWebGLProgram(l,o,s);o.forEach(p=>n.disposeIntermediateTensorInfo(p));let c=be({inputs:{x:u},attrs:{shape:i},backend:n});return n.disposeIntermediateTensorInfo(u),c}function mre(e,t,n){let s=C.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>be({inputs:{x:a},attrs:{shape:[-1,v.sizeFromShape(a.shape.slice(t))]},backend:n})),outShape:s}}function x9(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s,a=v.parseAxisParam(r,t[0].shape)[0],o=C.computeOutShape(t.map(u=>u.shape),a);if(v.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let i=t.filter(u=>v.sizeFromShape(u.shape)>0);if(i.length===1)return Ps({inputs:{x:i[0]},backend:n});let l=i.map(u=>u.shape);return C.assertParamsConsistent(l,a),cp(i,a,n)}var gre={kernelName:ll,backendName:"webgl",kernelFunc:x9},b9=class{constructor(e,t=!1,n=null,s=!1,r=!1){this.variableNames=["x","W"],this.outputShape=e.outShape;let a=e.padInfo.top,o=e.padInfo.left,i=e.strideHeight,l=e.strideWidth,u=e.dilationHeight,c=e.dilationWidth,p=e.filterHeight,d=e.filterWidth,h=Math.floor(e.inChannels/4)*4,f=e.inChannels%4,m=e.dataFormat==="channelsLast",g=m?1:2,y=m?2:3,x=m?3:1,A="",b="";n&&(s?A=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:r?A=`float activation(float a) {
@@ -2473,7 +2473,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
 
         ${s.output} = result;
       }
-    `}};function Om(e,t){let n=e.length;return n>=3?t?[...e.slice(0,-3),e[n-3]*e[n-2],e[n-1]]:[...e.slice(0,-3),e[n-3],e[n-2]*e[n-1]]:!t&&n===1&&e[0]>1?[e[0],1]:null}function v9({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let l=e.shape,u=s.texData.get(e.dataId),c=n.inChannels,p=l[0]*l[1]*l[2],d=n.outChannels,h=n.dataFormat==="channelsLast",f=!1,m=!1,g,y=[];if(a!=null){let b=Om(a.shape,h);b!=null&&(a=be({inputs:{x:a},backend:s,attrs:{shape:b}}),y.push(a))}if(r!=null){let b=Om(r.shape,h);b!=null&&(r=be({inputs:{x:r},backend:s,attrs:{shape:b}}),y.push(r))}if(!((p===1||d===1)&&c>f9)&&u.isPacked&&h&&u.texture!=null&&l[2]%2!==0&&v.arraysEqual(u.shape.slice(-3),l.slice(-3))){let b=l[0]*l[1]*(l[2]+1),w={dataId:e.dataId,shape:[1,b,n.inChannels],dtype:e.dtype},k=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(Dp(u.shape,w.shape),()=>`packed reshape ${u.shape} to ${w.shape} isn't free`);let S=be({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(S);let E=Fm({a:w,b:S,backend:s,transposeA:f,transposeB:m,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o}),R=s.texData.get(E.dataId);v.assert(R.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=k,R.shape=n.outShape,g=Ps({inputs:{x:E},backend:s}),g.shape=n.outShape,y.push(E)}else{let b=n.outHeight*n.outWidth,w=be({inputs:{x:e},backend:s,attrs:{shape:h?[n.batchSize,b,n.inChannels]:[n.batchSize,n.inChannels,b]}}),k=be({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}}),S=Fm({a:h?w:k,b:h?k:w,transposeA:!h,transposeB:m,backend:s,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o});g=be({inputs:{x:S},backend:s,attrs:{shape:n.outShape}}),y.push(w),y.push(k),y.push(S)}for(let b of y)s.disposeIntermediateTensorInfo(b);return g}function w9({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:p,outHeight:d,dataFormat:h}=n,f=h==="channelsLast",m=l*u*c,g=d*p,y=[n.batchSize,m,g],x=!0,A=!1,b=[];if(a!=null){let K=Om(a.shape,f);K!=null&&(a=be({inputs:{x:a},backend:s,attrs:{shape:K}}),b.push(a))}if(r!=null){let K=Om(r.shape,f);K!=null&&(r=be({inputs:{x:r},backend:s,attrs:{shape:K}}),b.push(r))}let w=be({inputs:{x:t},backend:s,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});b.push(w);let k=new Are(y,n),S=[e.shape,[n.padInfo.top,n.padInfo.left],[n.strideHeight,n.strideWidth],[n.dilationHeight,n.dilationWidth],[n.inChannels],[n.filterWidth*n.inChannels],[n.outWidth]],E=s.runWebGLProgram(k,[e],"float32",S),R=be({inputs:{x:E},backend:s,attrs:{shape:y}});b.push(E),b.push(R);let P=r!=null,_=a!=null,$=i==="leakyrelu",T=i?w2(i,!0):null,F=new h9(f?R.shape:w.shape,f?w.shape:R.shape,f?[n.batchSize,g,n.outChannels]:[n.batchSize,n.outChannels,g],x,A,P,T,_,$),G=f?[R,w]:[w,R];if(r&&G.push(r),_&&G.push(a),$){let K=s.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));G.push(K),b.push(K)}let q=s.runWebGLProgram(F,G,"float32"),z=be({inputs:{x:q},backend:s,attrs:{shape:n.outShape}});b.push(q);for(let K of b)s.disposeIntermediateTensorInfo(K);return z}function xre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=s,p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,a.shape,o,u,i,c,!1,p),h;if(d.filterHeight===1&&d.filterWidth===1&&d.dilationHeight===1&&d.dilationWidth===1&&d.strideHeight===1&&d.strideWidth===1&&(d.padInfo.type==="SAME"||d.padInfo.type==="VALID"))h=v9({x:r,filter:a,convInfo:d,backend:n});else if(Z().getBool("WEBGL_CONV_IM2COL"))h=w9({x:r,filter:a,convInfo:d,backend:n});else{let m=new b9(d);h=n.runWebGLProgram(m,[r,a],"float32")}let f=be({inputs:{x:h},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(h),f}var bre={kernelName:Ao,backendName:"webgl",kernelFunc:xre},vre=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,s=e.padInfo.top,r=e.padInfo.left,a=e.dataFormat==="channelsLast";this.userCode=`
+    `}};function Fm(e,t){let n=e.length;return n>=3?t?[...e.slice(0,-3),e[n-3]*e[n-2],e[n-1]]:[...e.slice(0,-3),e[n-3],e[n-2]*e[n-1]]:!t&&n===1&&e[0]>1?[e[0],1]:null}function v9({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let l=e.shape,u=s.texData.get(e.dataId),c=n.inChannels,p=l[0]*l[1]*l[2],d=n.outChannels,h=n.dataFormat==="channelsLast",f=!1,m=!1,g,y=[];if(a!=null){let b=Fm(a.shape,h);b!=null&&(a=be({inputs:{x:a},backend:s,attrs:{shape:b}}),y.push(a))}if(r!=null){let b=Fm(r.shape,h);b!=null&&(r=be({inputs:{x:r},backend:s,attrs:{shape:b}}),y.push(r))}if(!((p===1||d===1)&&c>f9)&&u.isPacked&&h&&u.texture!=null&&l[2]%2!==0&&v.arraysEqual(u.shape.slice(-3),l.slice(-3))){let b=l[0]*l[1]*(l[2]+1),w={dataId:e.dataId,shape:[1,b,n.inChannels],dtype:e.dtype},k=u.shape;u.shape=u.shape.slice(),u.shape[u.shape.length-2]++,v.assert(_p(u.shape,w.shape),()=>`packed reshape ${u.shape} to ${w.shape} isn't free`);let S=be({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}});y.push(S);let E=Pm({a:w,b:S,backend:s,transposeA:f,transposeB:m,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o}),R=s.texData.get(E.dataId);v.assert(R.isPacked,()=>"batchMatMul result is expected to be packed"),u.shape=k,R.shape=n.outShape,g=Ps({inputs:{x:E},backend:s}),g.shape=n.outShape,y.push(E)}else{let b=n.outHeight*n.outWidth,w=be({inputs:{x:e},backend:s,attrs:{shape:h?[n.batchSize,b,n.inChannels]:[n.batchSize,n.inChannels,b]}}),k=be({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}}),S=Pm({a:h?w:k,b:h?k:w,transposeA:!h,transposeB:m,backend:s,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o});g=be({inputs:{x:S},backend:s,attrs:{shape:n.outShape}}),y.push(w),y.push(k),y.push(S)}for(let b of y)s.disposeIntermediateTensorInfo(b);return g}function w9({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let{filterWidth:l,filterHeight:u,inChannels:c,outWidth:p,outHeight:d,dataFormat:h}=n,f=h==="channelsLast",m=l*u*c,g=d*p,y=[n.batchSize,m,g],x=!0,A=!1,b=[];if(a!=null){let Z=Fm(a.shape,f);Z!=null&&(a=be({inputs:{x:a},backend:s,attrs:{shape:Z}}),b.push(a))}if(r!=null){let Z=Fm(r.shape,f);Z!=null&&(r=be({inputs:{x:r},backend:s,attrs:{shape:Z}}),b.push(r))}let w=be({inputs:{x:t},backend:s,attrs:{shape:[1,m,v.sizeFromShape(t.shape)/m]}});b.push(w);let k=new Are(y,n),S=[e.shape,[n.padInfo.top,n.padInfo.left],[n.strideHeight,n.strideWidth],[n.dilationHeight,n.dilationWidth],[n.inChannels],[n.filterWidth*n.inChannels],[n.outWidth]],E=s.runWebGLProgram(k,[e],"float32",S),R=be({inputs:{x:E},backend:s,attrs:{shape:y}});b.push(E),b.push(R);let P=r!=null,_=a!=null,$=i==="leakyrelu",T=i?v2(i,!0):null,F=new h9(f?R.shape:w.shape,f?w.shape:R.shape,f?[n.batchSize,g,n.outChannels]:[n.batchSize,n.outChannels,g],x,A,P,T,_,$),G=f?[R,w]:[w,R];if(r&&G.push(r),_&&G.push(a),$){let Z=s.makeTensorInfo([],"float32",v.createScalarValue(o,"float32"));G.push(Z),b.push(Z)}let q=s.runWebGLProgram(F,G,"float32"),z=be({inputs:{x:q},backend:s,attrs:{shape:n.outShape}});b.push(q);for(let Z of b)s.disposeIntermediateTensorInfo(Z);return z}function xre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=s,p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,a.shape,o,u,i,c,!1,p),h;if(d.filterHeight===1&&d.filterWidth===1&&d.dilationHeight===1&&d.dilationWidth===1&&d.strideHeight===1&&d.strideWidth===1&&(d.padInfo.type==="SAME"||d.padInfo.type==="VALID"))h=v9({x:r,filter:a,convInfo:d,backend:n});else if(X().getBool("WEBGL_CONV_IM2COL"))h=w9({x:r,filter:a,convInfo:d,backend:n});else{let m=new b9(d);h=n.runWebGLProgram(m,[r,a],"float32")}let f=be({inputs:{x:h},backend:n,attrs:{shape:d.outShape}});return n.disposeIntermediateTensorInfo(h),f}var bre={kernelName:yo,backendName:"webgl",kernelFunc:xre},vre=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,s=e.padInfo.top,r=e.padInfo.left,a=e.dataFormat==="channelsLast";this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -2667,12 +2667,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
         }
         setOutput(dotProd);
       }
-    `}};function Sre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=s,p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,c,o,1,i,u,!1,p),h=new vre(d);return n.runWebGLProgram(h,[r,a],"float32")}var Cre={kernelName:Xm,backendName:"webgl",kernelFunc:Sre};function Tre(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=s,p=C.convertConv2DDataFormat(u),d=C.computeConv2DInfo(o,a.shape,i,1,l,c,!1,p),h=new wre(d);return n.runWebGLProgram(h,[r,a],"float32")}var Nre={kernelName:xo,backendName:"webgl",kernelFunc:Tre};function Ere(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s,u=C.computeConv3DInfo(r.shape,a.shape,o,l,i),c=new yre(u);return n.runWebGLProgram(c,[r,a],"float32")}var Rre={kernelName:Wp,backendName:"webgl",kernelFunc:Ere};function _re(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,filterShape:l}=s,u=C.computeConv3DInfo(r.shape,l,o,1,i),c=new kre(u);return n.runWebGLProgram(c,[r,a],"float32")}var Dre={kernelName:Km,backendName:"webgl",kernelFunc:_re};function $re(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{pad:o,strides:i,inputShape:l}=s,u=C.computeConv3DInfo(l,a.shape,i,1,o),c=new Ire(u);return n.runWebGLProgram(c,[r,a],"float32")}var Pre={kernelName:Zm,backendName:"webgl",kernelFunc:$re},Fre=ld+`
+    `}};function Sre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,filterShape:c}=s,p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,c,o,1,i,u,!1,p),h=new vre(d);return n.runWebGLProgram(h,[r,a],"float32")}var Cre={kernelName:qm,backendName:"webgl",kernelFunc:Sre};function Tre(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=s,p=C.convertConv2DDataFormat(u),d=C.computeConv2DInfo(o,a.shape,i,1,l,c,!1,p),h=new wre(d);return n.runWebGLProgram(h,[r,a],"float32")}var Nre={kernelName:Ao,backendName:"webgl",kernelFunc:Tre};function Ere(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s,u=C.computeConv3DInfo(r.shape,a.shape,o,l,i),c=new yre(u);return n.runWebGLProgram(c,[r,a],"float32")}var Rre={kernelName:Bp,backendName:"webgl",kernelFunc:Ere};function _re(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,pad:i,filterShape:l}=s,u=C.computeConv3DInfo(r.shape,l,o,1,i),c=new kre(u);return n.runWebGLProgram(c,[r,a],"float32")}var Dre={kernelName:Xm,backendName:"webgl",kernelFunc:_re};function $re(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{pad:o,strides:i,inputShape:l}=s,u=C.computeConv3DInfo(l,a.shape,i,1,o),c=new Ire(u);return n.runWebGLProgram(c,[r,a],"float32")}var Pre={kernelName:Km,backendName:"webgl",kernelFunc:$re},Fre=id+`
   return cos(x);
-`,Ore=ct({opSnippet:Fre}),Mre={kernelName:bo,backendName:"webgl",kernelFunc:Ore},zre=`
+`,Ore=ct({opSnippet:Fre}),Mre={kernelName:xo,backendName:"webgl",kernelFunc:Ore},zre=`
   float e2x = exp(-x);
   return (e2x + 1.0 / e2x) / 2.0;
-`,Lre=ct({opSnippet:zre}),Bre={kernelName:vo,backendName:"webgl",kernelFunc:Lre},Wre=class{constructor(e,t,n,s,r){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[a,o,i,l]=e,[u]=t,[c,p]=n;this.outputShape=[u,c,p,l];let d=s==="bilinear"?1:0,[h,f]=[`${o-1}.0`,`${i-1}.0`],[m,g,y]=c>1?[`${(o-1)/(c-1)}`,"(y2-y1) * height_ratio",`y1*${h} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${h}`],[x,A,b]=p>1?[`${(i-1)/(p-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
+`,Lre=ct({opSnippet:zre}),Bre={kernelName:bo,backendName:"webgl",kernelFunc:Lre},Wre=class{constructor(e,t,n,s,r){this.variableNames=["Image","Boxes","BoxInd"],this.outputShape=[];let[a,o,i,l]=e,[u]=t,[c,p]=n;this.outputShape=[u,c,p,l];let d=s==="bilinear"?1:0,[h,f]=[`${o-1}.0`,`${i-1}.0`],[m,g,y]=c>1?[`${(o-1)/(c-1)}`,"(y2-y1) * height_ratio",`y1*${h} + float(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${h}`],[x,A,b]=p>1?[`${(i-1)/(p-1)}`,"(x2-x1) * width_ratio",`x1*${f} + float(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${f}`];this.userCode=`
       const float height_ratio = float(${m});
       const float width_ratio = float(${x});
       void main() {
@@ -2733,7 +2733,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
           setOutput(newValue);
         }
       }
-    `}},Vre=e=>{let{inputs:t,backend:n,attrs:s}=e,{image:r,boxes:a,boxInd:o}=t,{cropSize:i,method:l,extrapolationValue:u}=s,c=new Wre(r.shape,a.shape,i,l,u);return n.runWebGLProgram(c,[r,a,o],"float32")},Ure={kernelName:dl,backendName:"webgl",kernelFunc:Vre},Pp;(function(e){e.Prod="*",e.Sum="+"})(Pp||(Pp={}));var I7=class{constructor(e,t,n,s){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let r=this.outputShape.length,a=this.op===Pp.Prod?"1.0":"0.0",o=n?a:`getX(${S7(r,"coords",this.op)})`,i=this.outputShape[this.outputShape.length-1],l="",u="";n?(l=s?`end != ${i-1}`:"end != 0",u=s?"end + 1":"end - 1"):(l=s?`end + pow2 < ${i}`:"end >= pow2",u=s?"end + pow2":"end - pow2"),this.userCode=`
+    `}},Vre=e=>{let{inputs:t,backend:n,attrs:s}=e,{image:r,boxes:a,boxInd:o}=t,{cropSize:i,method:l,extrapolationValue:u}=s,c=new Wre(r.shape,a.shape,i,l,u);return n.runWebGLProgram(c,[r,a,o],"float32")},Ure={kernelName:cl,backendName:"webgl",kernelFunc:Vre},$p;(function(e){e.Prod="*",e.Sum="+"})($p||($p={}));var I7=class{constructor(e,t,n,s){this.op=e,this.outputShape=t,this.variableNames=["x"],this.customUniforms=[{name:"index",type:"float"}];let r=this.outputShape.length,a=this.op===$p.Prod?"1.0":"0.0",o=n?a:`getX(${S7(r,"coords",this.op)})`,i=this.outputShape[this.outputShape.length-1],l="",u="";n?(l=s?`end != ${i-1}`:"end != 0",u=s?"end + 1":"end - 1"):(l=s?`end + pow2 < ${i}`:"end >= pow2",u=s?"end + pow2":"end - pow2"),this.userCode=`
       void main() {
         ${wt(r)} coords = getOutputCoords();
         int end = ${C7(r,"coords",this.op)};
@@ -2746,7 +2746,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
         }
         setOutput(val);
       }
-    `}};function S7(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw new Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function C7(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw new Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function k9(e,t,n,s,r,a){let o=t.shape.length,i=C.getAxesPermutation([s],o),l=t;i!=null&&(l=ts({inputs:{x:t},backend:n,attrs:{perm:i}}));let u=C.getInnerMostAxes(1,o)[0];if(u!==o-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${s}`);let c=l.shape[u],p=Ps({inputs:{x:l},backend:n});for(let d=0;d<=Math.ceil(Math.log2(c))-1;d++){let h=new I7(e,l.shape,!1,a),f=[[d]],m=p;p=n.runWebGLProgram(h,[p],p.dtype,f),n.disposeIntermediateTensorInfo(m)}if(r){let d=new I7(e,l.shape,r,a),h=p;p=n.runWebGLProgram(d,[p],p.dtype),n.disposeIntermediateTensorInfo(h)}if(i!=null){let d=C.getUndoAxesPermutation(i),h=ts({inputs:{x:p},backend:n,attrs:{perm:d}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(l),h}return p}function Gre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return k9(Pp.Prod,r,n,a,o,i)}var Hre={kernelName:cl,backendName:"webgl",kernelFunc:Gre};function jre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return k9(Pp.Sum,r,n,a,o,i)}var qre={kernelName:wo,backendName:"webgl",kernelFunc:jre};function Xre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o,binaryOutput:i}=s;if(r.shape.length===1){let l=n.readSync(r.dataId),u=n.readSync(a.dataId),c=n9(l,u,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,c)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(a),c=ote(l,u,o,i);return n.makeTensorInfo(c.shape,a.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var Kre={kernelName:Ym,backendName:"webgl",kernelFunc:Xre},Zre=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=n,this.userCode=`
+    `}};function S7(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw new Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function C7(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw new Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function k9(e,t,n,s,r,a){let o=t.shape.length,i=C.getAxesPermutation([s],o),l=t;i!=null&&(l=ts({inputs:{x:t},backend:n,attrs:{perm:i}}));let u=C.getInnerMostAxes(1,o)[0];if(u!==o-1)throw new Error(`WebGL cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${s}`);let c=l.shape[u],p=Ps({inputs:{x:l},backend:n});for(let d=0;d<=Math.ceil(Math.log2(c))-1;d++){let h=new I7(e,l.shape,!1,a),f=[[d]],m=p;p=n.runWebGLProgram(h,[p],p.dtype,f),n.disposeIntermediateTensorInfo(m)}if(r){let d=new I7(e,l.shape,r,a),h=p;p=n.runWebGLProgram(d,[p],p.dtype),n.disposeIntermediateTensorInfo(h)}if(i!=null){let d=C.getUndoAxesPermutation(i),h=ts({inputs:{x:p},backend:n,attrs:{perm:d}});return n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(l),h}return p}function Gre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return k9($p.Prod,r,n,a,o,i)}var Hre={kernelName:ul,backendName:"webgl",kernelFunc:Gre};function jre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return k9($p.Sum,r,n,a,o,i)}var qre={kernelName:vo,backendName:"webgl",kernelFunc:jre};function Xre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,weights:a}=t,{size:o,binaryOutput:i}=s;if(r.shape.length===1){let l=n.readSync(r.dataId),u=n.readSync(a.dataId),c=n9(l,u,a.dtype,a.shape,o);return n.makeTensorInfo([o],a.dtype,c)}else if(r.shape.length===2){let l=n.bufferSync(r),u=n.bufferSync(a),c=ote(l,u,o,i);return n.makeTensorInfo(c.shape,a.dtype,c.values)}throw new Error(`Error in denseBincount: input must be at most rank 2, but got rank${r.shape.length}.`)}var Kre={kernelName:Zm,backendName:"webgl",kernelFunc:Xre},Zre=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=[],this.outputShape=e,this.blockSize=t,this.dataFormat=n,this.userCode=`
     void main() {
       ivec4 coords = getOutputCoords();
       int b = coords[0];
@@ -2765,7 +2765,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
       float result = ${this.getInputSamplingString()};
       setOutput(result);
     }
-  `}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?this.outputShape[3]:this.outputShape[1]}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function Yre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockSize:a,dataFormat:o}=s,i=r.shape[0],l=o==="NHWC"?r.shape[1]:r.shape[2],u=o==="NHWC"?r.shape[2]:r.shape[3],c=o==="NHWC"?r.shape[3]:r.shape[1],p=l*a,d=u*a,h=c/(a*a),f=o==="NHWC"?[i,p,d,h]:[i,h,p,d],m=new Zre(f,a,o);return n.runWebGLProgram(m,[r],r.dtype)}var Jre={kernelName:pl,backendName:"webgl",kernelFunc:Yre},I9=class{constructor(e,t=!1,n=null,s=!1,r=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=xs(this.outputShape.length);let a=e.filterHeight,o=e.filterWidth,i=e.outChannels/e.inChannels,l="",u="";n&&(s?l=`float activation(float a) {
+  `}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?this.outputShape[3]:this.outputShape[1]}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function Yre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockSize:a,dataFormat:o}=s,i=r.shape[0],l=o==="NHWC"?r.shape[1]:r.shape[2],u=o==="NHWC"?r.shape[2]:r.shape[3],c=o==="NHWC"?r.shape[3]:r.shape[1],p=l*a,d=u*a,h=c/(a*a),f=o==="NHWC"?[i,p,d,h]:[i,h,p,d],m=new Zre(f,a,o);return n.runWebGLProgram(m,[r],r.dtype)}var Jre={kernelName:dl,backendName:"webgl",kernelFunc:Yre},I9=class{constructor(e,t=!1,n=null,s=!1,r=!1){this.variableNames=["x","W"],this.customUniforms=[{name:"pads",type:"ivec2"},{name:"strides",type:"ivec2"},{name:"dilations",type:"ivec2"},{name:"inDims",type:"ivec2"}],this.outputShape=e.outShape,this.enableShapeUniforms=xs(this.outputShape.length);let a=e.filterHeight,o=e.filterWidth,i=e.outChannels/e.inChannels,l="",u="";n&&(s?l=`float activation(float a) {
           float b = getPreluActivationWeightsAtOutCoords();
           ${n}
         }`:r?l=`float activation(float a) {
@@ -3005,7 +3005,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
         ${f}
         setOutput(result);
       }
-    `}};function Qre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l,dimRoundingMode:u}=s,c=l;c==null&&(c=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(o,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${o} and dilations '${c}'`);let p=C.computeConv2DInfo(r.shape,a.shape,o,c,i,u,!0),d;Z().getBool("WEBGL_PACK_DEPTHWISECONV")&&p.strideWidth<=2&&p.outChannels/p.inChannels===1?d=new S9(p):d=new I9(p);let h=[[p.padInfo.top,p.padInfo.left],[p.strideHeight,p.strideWidth],[p.dilationHeight,p.dilationWidth],[p.inHeight,p.inWidth]];return n.runWebGLProgram(d,[r,a],"float32",h)}var eae={kernelName:ko,backendName:"webgl",kernelFunc:Qre},tae=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,s=e.padInfo.top,r=e.padInfo.left,a=e.outChannels/e.inChannels;this.userCode=`
+    `}};function Qre(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l,dimRoundingMode:u}=s,c=l;c==null&&(c=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(o,c),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${o} and dilations '${c}'`);let p=C.computeConv2DInfo(r.shape,a.shape,o,c,i,u,!0),d;X().getBool("WEBGL_PACK_DEPTHWISECONV")&&p.strideWidth<=2&&p.outChannels/p.inChannels===1?d=new S9(p):d=new I9(p);let h=[[p.padInfo.top,p.padInfo.left],[p.strideHeight,p.strideWidth],[p.dilationHeight,p.dilationWidth],[p.inHeight,p.inWidth]];return n.runWebGLProgram(d,[r,a],"float32",h)}var eae={kernelName:wo,backendName:"webgl",kernelFunc:Qre},tae=class{constructor(e){this.variableNames=["x","dy"],this.outputShape=e.filterShape;let t=e.strideHeight,n=e.strideWidth,s=e.padInfo.top,r=e.padInfo.left,a=e.outChannels/e.inChannels;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int wR = coords.x;
@@ -3085,13 +3085,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
         }
         setOutput(dotProd);
       }
-    `}};function sae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=s,p=C.computeConv2DInfo(r.shape,c,o,i,l,u,!0),d=new tae(p);return n.runWebGLProgram(d,[r,a],"float32")}var rae={kernelName:Jm,backendName:"webgl",kernelFunc:sae};function aae(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=s,p=C.computeConv2DInfo(c,a.shape,o,i,l,u,!0),d=new nae(p);return n.runWebGLProgram(d,[r,a],"float32")}var oae={kernelName:Qm,backendName:"webgl",kernelFunc:aae},iae=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
+    `}};function sae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,dy:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,filterShape:c}=s,p=C.computeConv2DInfo(r.shape,c,o,i,l,u,!0),d=new tae(p);return n.runWebGLProgram(d,[r,a],"float32")}var rae={kernelName:Ym,backendName:"webgl",kernelFunc:sae};function aae(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{strides:o,dilations:i,pad:l,dimRoundingMode:u,inputShape:c}=s,p=C.computeConv2DInfo(c,a.shape,o,i,l,u,!0),d=new nae(p);return n.runWebGLProgram(d,[r,a],"float32")}var oae={kernelName:Jm,backendName:"webgl",kernelFunc:aae},iae=class{constructor(e){this.variableNames=["X"],this.outputShape=[e,e],this.userCode=`
       void main() {
           ivec2 coords = getOutputCoords();
           float val = coords[0] == coords[1] ? getX(coords[0]) : 0.0;
           setOutput(val);
       }
-    `}};function lae(e){let{inputs:t,backend:n}=e,{x:s}=t,r=[...s.shape,...s.shape],a=v.sizeFromShape(s.shape),o=be({inputs:{x:s},backend:n,attrs:{shape:[a]}}),i=new iae(a),l=n.runWebGLProgram(i,[o],o.dtype),u=be({inputs:{x:l},backend:n,attrs:{shape:r}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(l),u}var uae={kernelName:e0,backendName:"webgl",kernelFunc:lae},cae=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:s,strideHeight:r,strideWidth:a,filterHeight:o,filterWidth:i,dilationHeight:l,dilationWidth:u}=e,{top:c,left:p}=s;this.userCode=`
+    `}};function lae(e){let{inputs:t,backend:n}=e,{x:s}=t,r=[...s.shape,...s.shape],a=v.sizeFromShape(s.shape),o=be({inputs:{x:s},backend:n,attrs:{shape:[a]}}),i=new iae(a),l=n.runWebGLProgram(i,[o],o.dtype),u=be({inputs:{x:l},backend:n,attrs:{shape:r}});return n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(l),u}var uae={kernelName:Qm,backendName:"webgl",kernelFunc:lae},cae=class{constructor(e){this.variableNames=["x","W"],this.outputShape=e.outShape;let{inHeight:t,inWidth:n,padInfo:s,strideHeight:r,strideWidth:a,filterHeight:o,filterWidth:i,dilationHeight:l,dilationWidth:u}=e,{top:c,left:p}=s;this.userCode=`
       const ivec2 strides = ivec2(${r}, ${a});
       const ivec2 pads = ivec2(${c}, ${p});
       const float neg_infinity = -3.4e38;
@@ -3129,7 +3129,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
         float result = curVal;
         setOutput(result);
       }
-    `}};function dae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s,u=C.computeDilation2DInfo(r.shape,a.shape,o,i,"NHWC",l),c,p=new cae(u);c=n.runWebGLProgram(p,[r,a],"float32");let d=be({inputs:{x:c},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(c),d}var pae={kernelName:Vp,backendName:"webgl",kernelFunc:dae};function hae(e){let{inputs:t,backend:n,attrs:s}=e,{equation:r}=s,a=t,{allDims:o,summedDims:i,idDims:l}=C.decodeEinsumEquation(r,a.length);C.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=C.getEinsumComputePath(i,l),p=c.length,d=null,h=o.length,f=[];for(let m=0;m<p;++m){for(let g of c[m]){let{permutationIndices:y,expandDims:x}=C.getEinsumPermutation(h,l[g]),A;C.isIdentityPermutation(y)?A=a[g]:(A=ts({inputs:{x:a[g]},backend:n,attrs:{perm:y}}),f.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=be({inputs:{x:A},backend:n,attrs:{shape:b}}),f.push(A)),d===null?d=A:(d=Yx({inputs:{a:A,b:d},backend:n}),f.push(d))}m<p-1&&(u[m]>=0&&(d=I2({inputs:{x:d},backend:n,attrs:{axis:u[m]-(o.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&n.disposeIntermediateTensorInfo(m);return d}var fae={kernelName:Up,backendName:"webgl",kernelFunc:hae},mae="return (x >= 0.0) ? x : (exp(x) - 1.0);",gae=`
+    `}};function dae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dilations:l}=s,u=C.computeDilation2DInfo(r.shape,a.shape,o,i,"NHWC",l),c,p=new cae(u);c=n.runWebGLProgram(p,[r,a],"float32");let d=be({inputs:{x:c},backend:n,attrs:{shape:u.outShape}});return n.disposeIntermediateTensorInfo(c),d}var pae={kernelName:Wp,backendName:"webgl",kernelFunc:dae};function hae(e){let{inputs:t,backend:n,attrs:s}=e,{equation:r}=s,a=t,{allDims:o,summedDims:i,idDims:l}=C.decodeEinsumEquation(r,a.length);C.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=C.getEinsumComputePath(i,l),p=c.length,d=null,h=o.length,f=[];for(let m=0;m<p;++m){for(let g of c[m]){let{permutationIndices:y,expandDims:x}=C.getEinsumPermutation(h,l[g]),A;C.isIdentityPermutation(y)?A=a[g]:(A=ts({inputs:{x:a[g]},backend:n,attrs:{perm:y}}),f.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=be({inputs:{x:A},backend:n,attrs:{shape:b}}),f.push(A)),d===null?d=A:(d=Yx({inputs:{a:A,b:d},backend:n}),f.push(d))}m<p-1&&(u[m]>=0&&(d=k2({inputs:{x:d},backend:n,attrs:{axis:u[m]-(o.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&n.disposeIntermediateTensorInfo(m);return d}var fae={kernelName:Vp,backendName:"webgl",kernelFunc:hae},mae="return (x >= 0.0) ? x : (exp(x) - 1.0);",gae=`
   vec4 result;
 
   result.r = (x.r >= 0.0) ? x.r : (exp(x.r) - 1.0);
@@ -3138,12 +3138,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
   result.a = (x.a >= 0.0) ? x.a : (exp(x.a) - 1.0);
 
   return result;
-`,yae=ct({opSnippet:mae,packedOpSnippet:gae}),Aae={kernelName:So,backendName:"webgl",kernelFunc:yae},xae="return (b >= 1.0) ? a : a * (b + 1.0);",bae=`
+`,yae=ct({opSnippet:mae,packedOpSnippet:gae}),Aae={kernelName:Io,backendName:"webgl",kernelFunc:yae},xae="return (b >= 1.0) ? a : a * (b + 1.0);",bae=`
   vec4 bGTEZero = vec4(greaterThanEqual(b, vec4(0.)));
   return (bGTEZero * a) + ((vec4(1.0) - bGTEZero) * (a * (b + vec4(1.0))));
-`,vae=e=>{let{inputs:t,backend:n}=e,{dy:s,y:r}=t,a=Z().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Mh(bae,s.shape,r.shape):new uc(xae,s.shape,r.shape);return n.runWebGLProgram(a,[s,r],s.dtype)},wae={kernelName:t0,backendName:"webgl",kernelFunc:vae},kae=`
+`,vae=e=>{let{inputs:t,backend:n}=e,{dy:s,y:r}=t,a=X().getBool("WEBGL_PACK_BINARY_OPERATIONS")?new Oh(bae,s.shape,r.shape):new lc(xae,s.shape,r.shape);return n.runWebGLProgram(a,[s,r],s.dtype)},wae={kernelName:e0,backendName:"webgl",kernelFunc:vae},kae=`
   return vec4(equal(a, b));
-`,Iae="return float(a == b);",Sae=Rn({opSnippet:Iae,packedOpSnippet:kae,dtype:"bool",cpuKernelImpl:ute}),Cae={kernelName:hl,backendName:"webgl",kernelFunc:Sae},Tae=`
+`,Iae="return float(a == b);",Sae=Rn({opSnippet:Iae,packedOpSnippet:kae,dtype:"bool",cpuKernelImpl:ute}),Cae={kernelName:pl,backendName:"webgl",kernelFunc:Sae},Tae=`
   // Error function is calculated approximately with elementary function.
   // See "Handbook of Mathematical Functions with Formulas,
   // Graphs, and Mathematical Tables", Abramowitz and Stegun.
@@ -3158,7 +3158,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
   x = abs(x);
   float t = 1.0 / (1.0 + p * x);
   return sign * (1.0 - (((((a5*t + a4)*t) + a3)*t + a2)*t + a1)*t*exp(-x*x));
-`,Nae=ct({opSnippet:Tae}),Eae={kernelName:wc,backendName:"webgl",kernelFunc:Nae},Rae=ld+`
+`,Nae=ct({opSnippet:Tae}),Eae={kernelName:vc,backendName:"webgl",kernelFunc:Nae},Rae=id+`
   return exp(x);
 `,_ae=`
   vec4 result = exp(x);
@@ -3169,7 +3169,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,C9=ct({opSnippet:Rae,packedOpSnippet:_ae,cpuKernelImpl:cte,dtype:"float32"}),Dae={kernelName:Co,backendName:"webgl",kernelFunc:C9};function ly(e){let{inputs:t,attrs:n,backend:s}=e,{dim:r}=n,{input:a}=t,o=a.shape.length,i=a.shape.slice(),l=r;return r<0&&(v.assert(-(o+1)<=r,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+r+1),i.splice(l,0,1),be({inputs:{x:a},backend:s,attrs:{shape:i}})}var $ae={kernelName:fl,backendName:"webgl",kernelFunc:ly},T7="return exp(x) - 1.0;",Pae=ct({opSnippet:T7,packedOpSnippet:T7,cpuKernelImpl:dte}),Fae={kernelName:ml,backendName:"webgl",kernelFunc:Pae},N7=class{constructor(e,t,n){this.variableNames=["real","imag"];let s=t[1];this.outputShape=t;let r=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,a=n?`${s}.0`:"1.0",o;if(e==="real")o="return real * expR - imag * expI;";else if(e==="imag")o="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
+`,C9=ct({opSnippet:Rae,packedOpSnippet:_ae,cpuKernelImpl:cte,dtype:"float32"}),Dae={kernelName:So,backendName:"webgl",kernelFunc:C9};function iy(e){let{inputs:t,attrs:n,backend:s}=e,{dim:r}=n,{input:a}=t,o=a.shape.length,i=a.shape.slice(),l=r;return r<0&&(v.assert(-(o+1)<=r,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+r+1),i.splice(l,0,1),be({inputs:{x:a},backend:s,attrs:{shape:i}})}var $ae={kernelName:hl,backendName:"webgl",kernelFunc:iy},T7="return exp(x) - 1.0;",Pae=ct({opSnippet:T7,packedOpSnippet:T7,cpuKernelImpl:dte}),Fae={kernelName:fl,backendName:"webgl",kernelFunc:Pae},N7=class{constructor(e,t,n){this.variableNames=["real","imag"];let s=t[1];this.outputShape=t;let r=n?`2.0 * ${Math.PI}`:`-2.0 * ${Math.PI}`,a=n?`${s}.0`:"1.0",o;if(e==="real")o="return real * expR - imag * expI;";else if(e==="imag")o="return real * expI + imag * expR;";else throw new Error(`FFT component must be either "real" or "imag", got ${e}.`);this.userCode=`
       const float exponentMultiplier = ${r};
 
       float unaryOpComplex(float real, float expR, float imag, float expI) {
@@ -3202,12 +3202,12 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
         ivec2 coords = getOutputCoords();
         setOutput(mulMatDFT(coords[0], coords[1]));
       }
-    `}};function T9(e,t,n){let s=n.texData.get(e.dataId),r=v.sizeFromShape(e.shape),a=e.shape[e.shape.length-1],o=r/a,i=be({inputs:{x:e},backend:n,attrs:{shape:[o,a]}}),l=i.shape,u=new N7("real",l,t),c=new N7("imag",l,t),p=[{dataId:s.complexTensorInfos.real.dataId,dtype:s.complexTensorInfos.real.dtype,shape:l},{dataId:s.complexTensorInfos.imag.dataId,dtype:s.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(u,p,"float32"),h=n.runWebGLProgram(c,p,"float32"),f=pi({inputs:{real:d,imag:h},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h);let m=be({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(f),m}function Oae(e){let{inputs:t,backend:n}=e,{input:s}=t;return T9(s,!1,n)}var Mae={kernelName:n0,backendName:"webgl",kernelFunc:Oae},zae=class{constructor(e,t){this.outputShape=[],this.customUniforms=[{name:"value",type:"float"}],this.variableNames=["x"],this.outputShape=e,this.userCode=`
+    `}};function T9(e,t,n){let s=n.texData.get(e.dataId),r=v.sizeFromShape(e.shape),a=e.shape[e.shape.length-1],o=r/a,i=be({inputs:{x:e},backend:n,attrs:{shape:[o,a]}}),l=i.shape,u=new N7("real",l,t),c=new N7("imag",l,t),p=[{dataId:s.complexTensorInfos.real.dataId,dtype:s.complexTensorInfos.real.dtype,shape:l},{dataId:s.complexTensorInfos.imag.dataId,dtype:s.complexTensorInfos.imag.dtype,shape:l}],d=n.runWebGLProgram(u,p,"float32"),h=n.runWebGLProgram(c,p,"float32"),f=di({inputs:{real:d,imag:h},backend:n});n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h);let m=be({inputs:{x:f},backend:n,attrs:{shape:e.shape}});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(f),m}function Oae(e){let{inputs:t,backend:n}=e,{input:s}=t;return T9(s,!1,n)}var Mae={kernelName:t0,backendName:"webgl",kernelFunc:Oae},zae=class{constructor(e,t){this.outputShape=[],this.customUniforms=[{name:"value",type:"float"}],this.variableNames=["x"],this.outputShape=e,this.userCode=`
       void main() {
         // Input can be obtained from uniform value.
         setOutput(value);
       }
-    `}};function Lh(e){let{backend:t,attrs:n}=e,{shape:s,value:r}=n,{dtype:a}=n;if(a=a||v.inferDtype(r),a==="string"){let o=v.getArrayFromDType(a,v.sizeFromShape(s));return o.fill(r),t.makeTensorInfo(s,a,o)}else{let o=new zae(s,r),i=[[r]];return t.runWebGLProgram(o,[],a,i)}}var Lae={kernelName:kc,backendName:"webgl",kernelFunc:Lh},Bae=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
+    `}};function zh(e){let{backend:t,attrs:n}=e,{shape:s,value:r}=n,{dtype:a}=n;if(a=a||v.inferDtype(r),a==="string"){let o=v.getArrayFromDType(a,v.sizeFromShape(s));return o.fill(r),t.makeTensorInfo(s,a,o)}else{let o=new zae(s,r),i=[[r]];return t.runWebGLProgram(o,[],a,i)}}var Lae={kernelName:wc,backendName:"webgl",kernelFunc:zh},Bae=class{constructor(e){this.variableNames=["Image"],this.outputShape=[];let t=e[2];this.outputShape=e,this.userCode=`
         void main() {
           ivec4 coords = getOutputCoords();
           int x = coords[2];
@@ -3221,7 +3221,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
           }
           setOutput(outputValue);
         }
-    `}},Wae={kernelName:gl,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,s=t,r=new Bae(n.shape);return s.runWebGLProgram(r,[n],n.dtype)}},E7="return floor(x);",Vae=ct({opSnippet:E7,packedOpSnippet:E7,cpuKernelImpl:pte}),Uae={kernelName:To,backendName:"webgl",kernelFunc:Vae},Gae=`
+    `}},Wae={kernelName:ml,backendName:"webgl",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,s=t,r=new Bae(n.shape);return s.runWebGLProgram(r,[n],n.dtype)}},E7="return floor(x);",Vae=ct({opSnippet:E7,packedOpSnippet:E7,cpuKernelImpl:pte}),Uae={kernelName:Co,backendName:"webgl",kernelFunc:Vae},Gae=`
   float s = sign(a) * sign(b);
   int ia = round(a);
   int ib = round(b);
@@ -3252,7 +3252,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
     result[3] = idiv(ia[3], ib[3], s[3]);
   }
   return vec4(result);
-`,jae=Rn({opSnippet:Gae,packedOpSnippet:Hae,dtype:"int32"}),qae={kernelName:No,backendName:"webgl",kernelFunc:jae},Xae=class{constructor(e){this.variableNames=["A"];let t=as(),[n,s]=e;this.outputShape=e,this.userCode=`
+`,jae=Rn({opSnippet:Gae,packedOpSnippet:Hae,dtype:"int32"}),qae={kernelName:To,backendName:"webgl",kernelFunc:jae},Xae=class{constructor(e){this.variableNames=["A"];let t=as(),[n,s]=e;this.outputShape=e,this.userCode=`
       void main() {
         ivec3 coords = getOutputCoords();
         int texR = coords[0];
@@ -3308,7 +3308,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
 
         ${t.output} = result;
       }
-    `}},Zae={kernelName:bp,backendName:"webgl",kernelFunc:Yae},Fu;function Yae(e){let{inputs:t,backend:n,attrs:s}=e,{pixels:r}=t,{numChannels:a}=s,o=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,[l,u]=o?[r.videoWidth,r.videoHeight]:[r.width,r.height],c=[u,l],p=[u,l,a];(i||o)&&(Fu==null&&(Fu=document.createElement("canvas").getContext("2d")),Fu.canvas.width=l,Fu.canvas.height=u,Fu.drawImage(r,0,0,l,u),r=Fu.canvas);let d=n.makeTensorInfo(c,"int32");n.texData.get(d.dataId).usage=qs.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),r);let h=Z().getBool("WEBGL_PACK")?new Kae(p):new Xae(p),f=n.runWebGLProgram(h,[d],"int32");return n.disposeData(d.dataId),f}function Jae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=s,m=C.convertConv2DDataFormat(c),g=C.computeConv2DInfo(r.shape,a.shape,l,p,u,d,!1,m),y,x=[];if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))y=v9({x:r,filter:a,convInfo:g,backend:n,bias:o,activation:h,preluActivationWeights:i,leakyreluAlpha:f});else if(Z().getBool("WEBGL_CONV_IM2COL"))y=w9({x:r,filter:a,convInfo:g,backend:n,bias:o,activation:h,preluActivationWeights:i,leakyreluAlpha:f});else{let b=o!=null,w=i!=null,k=h==="leakyrelu",S=h?w2(h,!1):null,E=new b9(g,b,S,w,k),R=[r,a],P=(_,$)=>{if($==="NCHW"&&_.shape.length===1&&_.shape[0]!==1){let T=be({inputs:{x:_},backend:n,attrs:{shape:[_.shape[0],1,1]}});return x.push(T),T}return _};if(b&&R.push(P(o,c)),w&&R.push(P(i,c)),k){let _=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));R.push(_),x.push(_)}y=n.runWebGLProgram(E,R,"float32")}let A=be({inputs:{x:y},backend:n,attrs:{shape:g.outShape}});return x.push(y),x.forEach(b=>n.disposeIntermediateTensorInfo(b)),A}var Qae={kernelName:Qa,backendName:"webgl",kernelFunc:Jae};function eoe(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dimRoundingMode:p,activation:d,leakyreluAlpha:h}=s,f=[],m=c;m==null&&(m=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let g=C.computeConv2DInfo(r.shape,a.shape,l,m,u,p,!0),y=Z().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,x=d?w2(d,y):null,A=[r,a],b=o!=null,w=i!=null,k=d==="leakyrelu";if(b&&A.push(o),w&&A.push(i),k){let P=n.makeTensorInfo([],"float32",v.createScalarValue(h,"float32"));A.push(P),f.push(P)}let S;y?S=new S9(g,b,x,w,k):S=new I9(g,b,x,w,k);let E=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],R=n.runWebGLProgram(S,A,"float32",E);return f.forEach(P=>n.disposeIntermediateTensorInfo(P)),R}var toe={kernelName:eo,backendName:"webgl",kernelFunc:eoe},noe=class{constructor(e,t,n,s){this.sliceDim=e,this.strides=t,this.paramsShape=s,this.variableNames=["x","indices"],this.outputShape=n;let r=wt(t.length),a=wt(n.length),o=this.sliceDim>1?"strides[j]":"strides",i=wt(s.length),l=s.length>1?"paramsShape[j]":"paramsShape";this.userCode=`
+    `}},Zae={kernelName:xp,backendName:"webgl",kernelFunc:Yae},Pu;function Yae(e){let{inputs:t,backend:n,attrs:s}=e,{pixels:r}=t,{numChannels:a}=s,o=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,[l,u]=o?[r.videoWidth,r.videoHeight]:[r.width,r.height],c=[u,l],p=[u,l,a];(i||o)&&(Pu==null&&(Pu=document.createElement("canvas").getContext("2d")),Pu.canvas.width=l,Pu.canvas.height=u,Pu.drawImage(r,0,0,l,u),r=Pu.canvas);let d=n.makeTensorInfo(c,"int32");n.texData.get(d.dataId).usage=qs.PIXELS,n.gpgpu.uploadPixelDataToTexture(n.getTexture(d.dataId),r);let h=X().getBool("WEBGL_PACK")?new Kae(p):new Xae(p),f=n.runWebGLProgram(h,[d],"int32");return n.disposeData(d.dataId),f}function Jae(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=s,m=C.convertConv2DDataFormat(c),g=C.computeConv2DInfo(r.shape,a.shape,l,p,u,d,!1,m),y,x=[];if(g.filterHeight===1&&g.filterWidth===1&&g.dilationHeight===1&&g.dilationWidth===1&&g.strideHeight===1&&g.strideWidth===1&&(g.padInfo.type==="SAME"||g.padInfo.type==="VALID"))y=v9({x:r,filter:a,convInfo:g,backend:n,bias:o,activation:h,preluActivationWeights:i,leakyreluAlpha:f});else if(X().getBool("WEBGL_CONV_IM2COL"))y=w9({x:r,filter:a,convInfo:g,backend:n,bias:o,activation:h,preluActivationWeights:i,leakyreluAlpha:f});else{let b=o!=null,w=i!=null,k=h==="leakyrelu",S=h?v2(h,!1):null,E=new b9(g,b,S,w,k),R=[r,a],P=(_,$)=>{if($==="NCHW"&&_.shape.length===1&&_.shape[0]!==1){let T=be({inputs:{x:_},backend:n,attrs:{shape:[_.shape[0],1,1]}});return x.push(T),T}return _};if(b&&R.push(P(o,c)),w&&R.push(P(i,c)),k){let _=n.makeTensorInfo([],"float32",v.createScalarValue(f,"float32"));R.push(_),x.push(_)}y=n.runWebGLProgram(E,R,"float32")}let A=be({inputs:{x:y},backend:n,attrs:{shape:g.outShape}});return x.push(y),x.forEach(b=>n.disposeIntermediateTensorInfo(b)),A}var Qae={kernelName:Ja,backendName:"webgl",kernelFunc:Jae};function eoe(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dimRoundingMode:p,activation:d,leakyreluAlpha:h}=s,f=[],m=c;m==null&&(m=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(l,m),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${m}'`);let g=C.computeConv2DInfo(r.shape,a.shape,l,m,u,p,!0),y=X().getBool("WEBGL_PACK_DEPTHWISECONV")&&g.strideWidth<=2&&g.outChannels/g.inChannels===1,x=d?v2(d,y):null,A=[r,a],b=o!=null,w=i!=null,k=d==="leakyrelu";if(b&&A.push(o),w&&A.push(i),k){let P=n.makeTensorInfo([],"float32",v.createScalarValue(h,"float32"));A.push(P),f.push(P)}let S;y?S=new S9(g,b,x,w,k):S=new I9(g,b,x,w,k);let E=[[g.padInfo.top,g.padInfo.left],[g.strideHeight,g.strideWidth],[g.dilationHeight,g.dilationWidth],[g.inHeight,g.inWidth]],R=n.runWebGLProgram(S,A,"float32",E);return f.forEach(P=>n.disposeIntermediateTensorInfo(P)),R}var toe={kernelName:Qa,backendName:"webgl",kernelFunc:eoe},noe=class{constructor(e,t,n,s){this.sliceDim=e,this.strides=t,this.paramsShape=s,this.variableNames=["x","indices"],this.outputShape=n;let r=wt(t.length),a=wt(n.length),o=this.sliceDim>1?"strides[j]":"strides",i=wt(s.length),l=s.length>1?"paramsShape[j]":"paramsShape";this.userCode=`
         ${r} strides = ${r}(${this.strides});
         ${i} paramsShape = ${i}(${this.paramsShape});
          void main() {
@@ -3323,22 +3323,22 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
           }
           setOutput(out_of_bounds ? 0.0 : getX(flattenIndex, coords[1]));
         }
-      `}};function soe(e){let{inputs:t,backend:n}=e,{params:s,indices:r}=t,a=r.shape,o=a[a.length-1],i=v.sizeFromShape(s.shape),[l,u,c,p]=C.prepareAndValidate(s,r),d=be({inputs:{x:r},backend:n,attrs:{shape:[u,o]}}),h=be({inputs:{x:s},backend:n,attrs:{shape:[v.sizeFromShape(s.shape)/c,c]}});if(n.shouldExecuteOnCPU([s,r])||s.dtype==="string"){let y=n.readSync(r.dataId),x=n.bufferSync(s),A=hte(y,x,s.dtype,u,o,c,p,s.shape,i);return n.makeTensorInfo(l,s.dtype,A.values)}let f=new noe(o,p,[u,c],s.shape),m=n.runWebGLProgram(f,[h,d],h.dtype),g=be({inputs:{x:m},backend:n,attrs:{shape:l}});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(m),g}var roe={kernelName:Al,backendName:"webgl",kernelFunc:soe},aoe=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=wt(this.rank),s=ooe(e,2);this.userCode=`
+      `}};function soe(e){let{inputs:t,backend:n}=e,{params:s,indices:r}=t,a=r.shape,o=a[a.length-1],i=v.sizeFromShape(s.shape),[l,u,c,p]=C.prepareAndValidate(s,r),d=be({inputs:{x:r},backend:n,attrs:{shape:[u,o]}}),h=be({inputs:{x:s},backend:n,attrs:{shape:[v.sizeFromShape(s.shape)/c,c]}});if(n.shouldExecuteOnCPU([s,r])||s.dtype==="string"){let y=n.readSync(r.dataId),x=n.bufferSync(s),A=hte(y,x,s.dtype,u,o,c,p,s.shape,i);return n.makeTensorInfo(l,s.dtype,A.values)}let f=new noe(o,p,[u,c],s.shape),m=n.runWebGLProgram(f,[h,d],h.dtype),g=be({inputs:{x:m},backend:n,attrs:{shape:l}});return n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(m),g}var roe={kernelName:yl,backendName:"webgl",kernelFunc:soe},aoe=class{constructor(e,t){this.variableNames=["A","indices"],this.outputShape=t,this.rank=t.length;let n=wt(this.rank),s=ooe(e,2);this.userCode=`
       void main() {
         ${n} resRC = getOutputCoords();
         int index = int(getIndices(resRC.x, resRC.z));
         float inBounds = (index >= 0) && (index < ${e[2]}) ? 1.0 : 0.0;
         setOutput(inBounds * getA(${s}));
       }
-    `}};function ooe(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],s=[];for(let r=0;r<e.length;r++)r===2?s.push("index"):s.push(`${n[r]}`);return s.join()}function N9(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,indices:a}=t,{axis:o,batchDims:i}=s,l=v.parseAxisParam(o,r.shape)[0];if(Z().get("DEBUG")){let x=n.readSync(a.dataId),A=r.shape[l];for(let b=0;b<x.length;++b){let w=x[b];v.assert(w<=A-1&&w>=0,()=>`GatherV2: the index value ${w} is not in [0, ${A-1}]`)}}let u=C.segment_util.collectGatherOpShapeInfo(r,a,l,i),c=v.sizeFromShape(a.shape),p=[],d=be({inputs:{x:r},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=be({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});p.push(d),p.push(h);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([r,a])||r.dtype==="string"){let x=n.bufferSync(h),A=n.bufferSync(d),b=fte(A,x,f);return p.forEach(w=>n.disposeIntermediateTensorInfo(w)),n.makeTensorInfo(u.outputShape,b.dtype,b.values)}let m=new aoe(d.shape,f),g=n.runWebGLProgram(m,[d,h],d.dtype);p.push(g);let y=be({inputs:{x:g},backend:n,attrs:{shape:u.outputShape}});return p.forEach(x=>n.disposeIntermediateTensorInfo(x)),y}var ioe={kernelName:yl,backendName:"webgl",kernelFunc:N9},loe="return float(a > b);",uoe=`
+    `}};function ooe(e,t){let n=["resRC.x","resRC.y","resRC.z","resRC.w"],s=[];for(let r=0;r<e.length;r++)r===2?s.push("index"):s.push(`${n[r]}`);return s.join()}function N9(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,indices:a}=t,{axis:o,batchDims:i}=s,l=v.parseAxisParam(o,r.shape)[0];if(X().get("DEBUG")){let x=n.readSync(a.dataId),A=r.shape[l];for(let b=0;b<x.length;++b){let w=x[b];v.assert(w<=A-1&&w>=0,()=>`GatherV2: the index value ${w} is not in [0, ${A-1}]`)}}let u=C.segment_util.collectGatherOpShapeInfo(r,a,l,i),c=v.sizeFromShape(a.shape),p=[],d=be({inputs:{x:r},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=be({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});p.push(d),p.push(h);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([r,a])||r.dtype==="string"){let x=n.bufferSync(h),A=n.bufferSync(d),b=fte(A,x,f);return p.forEach(w=>n.disposeIntermediateTensorInfo(w)),n.makeTensorInfo(u.outputShape,b.dtype,b.values)}let m=new aoe(d.shape,f),g=n.runWebGLProgram(m,[d,h],d.dtype);p.push(g);let y=be({inputs:{x:g},backend:n,attrs:{shape:u.outputShape}});return p.forEach(x=>n.disposeIntermediateTensorInfo(x)),y}var ioe={kernelName:gl,backendName:"webgl",kernelFunc:N9},loe="return float(a > b);",uoe=`
   return vec4(greaterThan(a, b));
-`,coe=Rn({opSnippet:loe,packedOpSnippet:uoe,cpuKernelImpl:mte,dtype:"bool"}),doe={kernelName:xl,backendName:"webgl",kernelFunc:coe},poe="return float(a >= b);",hoe=`
+`,coe=Rn({opSnippet:loe,packedOpSnippet:uoe,cpuKernelImpl:mte,dtype:"bool"}),doe={kernelName:Al,backendName:"webgl",kernelFunc:coe},poe="return float(a >= b);",hoe=`
   return vec4(greaterThanEqual(a, b));
-`,foe=Rn({opSnippet:poe,packedOpSnippet:hoe,dtype:"bool",cpuKernelImpl:gte}),moe={kernelName:Ro,backendName:"webgl",kernelFunc:foe};function goe(e){let{inputs:t,backend:n}=e,{input:s}=t;return T9(s,!0,n)}var yoe={kernelName:s0,backendName:"webgl",kernelFunc:goe},Aoe="return float(!isnan(x) && !isinf(x));",xoe=ct({opSnippet:Aoe,dtype:"bool"}),boe={kernelName:Ic,backendName:"webgl",kernelFunc:xoe},voe="return float(isinf(x));",woe=ct({opSnippet:voe,dtype:"bool"}),koe={kernelName:Sc,backendName:"webgl",kernelFunc:woe},Ioe="return float(isnan(x));",Soe=ct({opSnippet:Ioe,dtype:"bool"}),Coe={kernelName:Cc,backendName:"webgl",kernelFunc:Soe},Toe="return float(a < b);",Noe=`
+`,foe=Rn({opSnippet:poe,packedOpSnippet:hoe,dtype:"bool",cpuKernelImpl:gte}),moe={kernelName:Eo,backendName:"webgl",kernelFunc:foe};function goe(e){let{inputs:t,backend:n}=e,{input:s}=t;return T9(s,!0,n)}var yoe={kernelName:n0,backendName:"webgl",kernelFunc:goe},Aoe="return float(!isnan(x) && !isinf(x));",xoe=ct({opSnippet:Aoe,dtype:"bool"}),boe={kernelName:kc,backendName:"webgl",kernelFunc:xoe},voe="return float(isinf(x));",woe=ct({opSnippet:voe,dtype:"bool"}),koe={kernelName:Ic,backendName:"webgl",kernelFunc:woe},Ioe="return float(isnan(x));",Soe=ct({opSnippet:Ioe,dtype:"bool"}),Coe={kernelName:Sc,backendName:"webgl",kernelFunc:Soe},Toe="return float(a < b);",Noe=`
   return vec4(lessThan(a, b));
-`,Eoe=Rn({opSnippet:Toe,packedOpSnippet:Noe,cpuKernelImpl:yte,dtype:"bool"}),Roe={kernelName:bl,backendName:"webgl",kernelFunc:Eoe},_oe="return float(a <= b);",Doe=`
+`,Eoe=Rn({opSnippet:Toe,packedOpSnippet:Noe,cpuKernelImpl:yte,dtype:"bool"}),Roe={kernelName:xl,backendName:"webgl",kernelFunc:Eoe},_oe="return float(a <= b);",Doe=`
   return vec4(lessThanEqual(a, b));
-`,$oe=Rn({opSnippet:_oe,packedOpSnippet:Doe,cpuKernelImpl:Ate,dtype:"bool"}),Poe={kernelName:vl,backendName:"webgl",kernelFunc:$oe};function Foe(e){let{backend:t,attrs:n}=e,{start:s,stop:r,num:a}=n,o=xte(s,r,a);return t.makeTensorInfo([o.length],"float32",o)}var Ooe={kernelName:r0,backendName:"webgl",kernelFunc:Foe},Moe=ld+`
+`,$oe=Rn({opSnippet:_oe,packedOpSnippet:Doe,cpuKernelImpl:Ate,dtype:"bool"}),Poe={kernelName:bl,backendName:"webgl",kernelFunc:$oe};function Foe(e){let{backend:t,attrs:n}=e,{start:s,stop:r,num:a}=n,o=xte(s,r,a);return t.makeTensorInfo([o.length],"float32",o)}var Ooe={kernelName:s0,backendName:"webgl",kernelFunc:Foe},Moe=id+`
   return x < 0.0 ? 0./0. : log(x);
 `,zoe=`
   vec4 result = log(x);
@@ -3348,18 +3348,18 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
   result.b = isNaN.b ? x.b : (x.b < 0.0 ? 0./0. : result.b);
   result.a = isNaN.a ? x.a : (x.a < 0.0 ? 0./0. : result.a);
   return result;
-`,Loe=ct({opSnippet:Moe,packedOpSnippet:zoe,cpuKernelImpl:bte}),Boe={kernelName:$o,backendName:"webgl",kernelFunc:Loe},Woe=ld+`
+`,Loe=ct({opSnippet:Moe,packedOpSnippet:zoe,cpuKernelImpl:bte}),Boe={kernelName:Do,backendName:"webgl",kernelFunc:Loe},Woe=id+`
   return log(1.0 + x);
-`,Voe=ct({opSnippet:Woe}),Uoe={kernelName:Tc,backendName:"webgl",kernelFunc:Voe},Goe="return float(a >= 1.0 && b >= 1.0);",Hoe=`
+`,Voe=ct({opSnippet:Woe}),Uoe={kernelName:Cc,backendName:"webgl",kernelFunc:Voe},Goe="return float(a >= 1.0 && b >= 1.0);",Hoe=`
   return vec4(
     vec4(greaterThanEqual(a, vec4(1.0))) *
     vec4(greaterThanEqual(b, vec4(1.0))));
-`,joe=Rn({opSnippet:Goe,packedOpSnippet:Hoe,dtype:"bool"}),qoe={kernelName:wl,backendName:"webgl",kernelFunc:joe},Xoe="return float(!(x >= 1.0));",Koe=ct({opSnippet:Xoe}),Zoe={kernelName:kl,backendName:"webgl",kernelFunc:Koe},Yoe="return float(a >= 1.0 || b >= 1.0);",Joe=`
+`,joe=Rn({opSnippet:Goe,packedOpSnippet:Hoe,dtype:"bool"}),qoe={kernelName:vl,backendName:"webgl",kernelFunc:joe},Xoe="return float(!(x >= 1.0));",Koe=ct({opSnippet:Xoe}),Zoe={kernelName:wl,backendName:"webgl",kernelFunc:Koe},Yoe="return float(a >= 1.0 || b >= 1.0);",Joe=`
   return min(
     vec4(greaterThanEqual(a, vec4(1.0))) +
     vec4(greaterThanEqual(b, vec4(1.0))),
     vec4(1.0));
-`,Qoe=Rn({opSnippet:Yoe,packedOpSnippet:Joe,dtype:"bool"}),eie={kernelName:Nc,backendName:"webgl",kernelFunc:Qoe},tie=class{constructor(e,t,n,s,r){this.variableNames=["x"],this.outputShape=[];let a=t,o=e[3]-1;this.outputShape=e;let i,l=`float(${n}) + float(${s}) * sum`;r===.5?i=`inversesqrt(${l})`:r===1?i=`1.0/(${l})`:i=`exp(log(${l}) * float(-${r}));`,this.userCode=`
+`,Qoe=Rn({opSnippet:Yoe,packedOpSnippet:Joe,dtype:"bool"}),eie={kernelName:Tc,backendName:"webgl",kernelFunc:Qoe},tie=class{constructor(e,t,n,s,r){this.variableNames=["x"],this.outputShape=[];let a=t,o=e[3]-1;this.outputShape=e;let i,l=`float(${n}) + float(${s}) * sum`;r===.5?i=`inversesqrt(${l})`:r===1?i=`1.0/(${l})`:i=`exp(log(${l}) * float(-${r}));`,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3440,7 +3440,7 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
         vec4 result = xAtOutputCoords * ${i};
         setOutput(result);
       }
-    `}},sie=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{depthRadius:a,bias:o,alpha:i,beta:l}=s,u=Z().getBool("WEBGL_PACK_NORMALIZATION")?new nie(r.shape,a,o,i,l):new tie(r.shape,a,o,i,l);return n.runWebGLProgram(u,[r],r.dtype)},rie={kernelName:Hp,backendName:"webgl",kernelFunc:sie},aie=class{constructor(e,t,n,s,r){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=s,this.beta=r,this.userCode=`
+    `}},sie=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{depthRadius:a,bias:o,alpha:i,beta:l}=s,u=X().getBool("WEBGL_PACK_NORMALIZATION")?new nie(r.shape,a,o,i,l):new tie(r.shape,a,o,i,l);return n.runWebGLProgram(u,[r],r.dtype)},rie={kernelName:Gp,backendName:"webgl",kernelFunc:sie},aie=class{constructor(e,t,n,s,r){this.variableNames=["inputImage","outputImage","dy"],this.outputShape=[],this.outputShape=e,this.depth=e[3],this.depthRadius=t,this.bias=n,this.alpha=s,this.beta=r,this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -3495,14 +3495,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
       }
       setOutput(result);
       }
-    `}},oie=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r,y:a,dy:o}=t,{depthRadius:i,bias:l,alpha:u,beta:c}=s,p=new aie(r.shape,i,l,u,c);return n.runWebGLProgram(p,[r,a,o],r.dtype)},iie={kernelName:a0,backendName:"webgl",kernelFunc:oie};function lie(e,t,n,s){let r=v.sizeFromShape(t),o=v.sizeFromShape(e.shape)/r,i=be({inputs:{x:e},attrs:{shape:[o,r]},backend:s}),l=au(i,e.dtype,"max",s),u=be({inputs:{x:l},attrs:{shape:n},backend:s});return s.disposeIntermediateTensorInfo(i),s.disposeIntermediateTensorInfo(l),u}function E9(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reductionIndices:a,keepDims:o}=s,i=r.shape.length,l=v.parseAxisParam(a,r.shape),u=l,c=C.getAxesPermutation(u,i),p=c!=null,d=n.shouldExecuteOnCPU([r]),h=r;if(p){if(d){let A=n.texData.get(h.dataId).values,b=new Array(i);for(let S=0;S<b.length;S++)b[S]=r.shape[c[S]];let w=Zx(A,r.shape,r.dtype,c,b);h=n.makeTensorInfo(b,r.dtype);let k=n.texData.get(h.dataId);k.values=w}else h=k2(r,c,n);u=C.getInnerMostAxes(u.length,i)}C.assertAxesAreInnerMostDims("max",u,i);let[f,m]=C.computeOutAndReduceShapes(h.shape,u),g=f;o&&(g=C.expandShapeToKeepDim(f,l));let y;if(d){let A=n.texData.get(h.dataId).values,b=vte(A,v.sizeFromShape(m),g,r.dtype);y=n.makeTensorInfo(g,r.dtype);let w=n.texData.get(y.dataId);w.values=b}else y=lie(h,m,g,n);return p&&n.disposeIntermediateTensorInfo(h),y}var uie={kernelName:Po,backendName:"webgl",kernelFunc:E9},cie=l9+`
+    `}},oie=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r,y:a,dy:o}=t,{depthRadius:i,bias:l,alpha:u,beta:c}=s,p=new aie(r.shape,i,l,u,c);return n.runWebGLProgram(p,[r,a,o],r.dtype)},iie={kernelName:r0,backendName:"webgl",kernelFunc:oie};function lie(e,t,n,s){let r=v.sizeFromShape(t),o=v.sizeFromShape(e.shape)/r,i=be({inputs:{x:e},attrs:{shape:[o,r]},backend:s}),l=ru(i,e.dtype,"max",s),u=be({inputs:{x:l},attrs:{shape:n},backend:s});return s.disposeIntermediateTensorInfo(i),s.disposeIntermediateTensorInfo(l),u}function E9(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reductionIndices:a,keepDims:o}=s,i=r.shape.length,l=v.parseAxisParam(a,r.shape),u=l,c=C.getAxesPermutation(u,i),p=c!=null,d=n.shouldExecuteOnCPU([r]),h=r;if(p){if(d){let A=n.texData.get(h.dataId).values,b=new Array(i);for(let S=0;S<b.length;S++)b[S]=r.shape[c[S]];let w=Zx(A,r.shape,r.dtype,c,b);h=n.makeTensorInfo(b,r.dtype);let k=n.texData.get(h.dataId);k.values=w}else h=w2(r,c,n);u=C.getInnerMostAxes(u.length,i)}C.assertAxesAreInnerMostDims("max",u,i);let[f,m]=C.computeOutAndReduceShapes(h.shape,u),g=f;o&&(g=C.expandShapeToKeepDim(f,l));let y;if(d){let A=n.texData.get(h.dataId).values,b=vte(A,v.sizeFromShape(m),g,r.dtype);y=n.makeTensorInfo(g,r.dtype);let w=n.texData.get(y.dataId);w.values=b}else y=lie(h,m,g,n);return p&&n.disposeIntermediateTensorInfo(h),y}var uie={kernelName:$o,backendName:"webgl",kernelFunc:E9},cie=l9+`
   return max(a, b);
 `,die=`
   vec4 result = vec4(max(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+v2+`
+  `+b2+`
   return result;
-`,pie=Rn({opSnippet:cie,packedOpSnippet:die,cpuKernelImpl:wte}),hie={kernelName:Fo,backendName:"webgl",kernelFunc:pie};function fie(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;nd(r,"maxPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;v.assert(C.eitherStridesOrDilationsAreOne(o,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=C.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Ps({inputs:{x:r},backend:n});let p=new $p(c,"max",!1);return n.runWebGLProgram(p,[r],r.dtype)}var mie={kernelName:Oo,backendName:"webgl",kernelFunc:fie};function gie(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dataFormat:l,dimRoundingMode:u}=s,c=[1,1,1],p=C.computePool3DInfo(r.shape,a,o,c,i,u,l),d=new Jx(p,"max",!1);return n.runWebGLProgram(d,[r],r.dtype)}var yie={kernelName:jp,backendName:"webgl",kernelFunc:gie},Aie=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,s=e.dilationHeight,r=e.effectiveFilterHeight,a=e.effectiveFilterWidth,o=r-1-e.padInfo.top,i=a-1-e.padInfo.left,l=r*a-1;this.userCode=`
+`,pie=Rn({opSnippet:cie,packedOpSnippet:die,cpuKernelImpl:wte}),hie={kernelName:Po,backendName:"webgl",kernelFunc:pie};function fie(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t;td(r,"maxPool");let{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1;v.assert(C.eitherStridesOrDilationsAreOne(o,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${o} and dilations '${u}'`);let c=C.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Ps({inputs:{x:r},backend:n});let p=new Dp(c,"max",!1);return n.runWebGLProgram(p,[r],r.dtype)}var mie={kernelName:Fo,backendName:"webgl",kernelFunc:fie};function gie(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dataFormat:l,dimRoundingMode:u}=s,c=[1,1,1],p=C.computePool3DInfo(r.shape,a,o,c,i,u,l),d=new Jx(p,"max",!1);return n.runWebGLProgram(d,[r],r.dtype)}var yie={kernelName:Hp,backendName:"webgl",kernelFunc:gie},Aie=class{constructor(e){this.variableNames=["dy","maxPos"],this.outputShape=e.inShape;let t=e.strideHeight,n=e.strideWidth,s=e.dilationHeight,r=e.effectiveFilterHeight,a=e.effectiveFilterWidth,o=r-1-e.padInfo.top,i=a-1-e.padInfo.left,l=r*a-1;this.userCode=`
       const ivec2 pads = ivec2(${o}, ${i});
 
       void main() {
@@ -3612,14 +3612,14 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
         }
         setOutput(dotProd);
       }
-    `}};function bie(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=s,p=[1,1,1],d=C.computePool3DInfo(o.shape,i,l,p,u,c),h=new Jx(d,"max",!0),f=n.runWebGLProgram(h,[o],o.dtype),m=new xie(d),g=n.runWebGLProgram(m,[r,f],o.dtype);return n.disposeIntermediateTensorInfo(f),g}var vie={kernelName:i0,backendName:"webgl",kernelFunc:bie};function wie(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a,output:o}=t,i=a;nd([a,o],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:p}=s,d=C.computePool2DInfo(i.shape,l,u,1,c,p),h=!0,f=new $p(d,"max",h),m=n.runWebGLProgram(f,[i],i.dtype),g=new Aie(d),y=n.runWebGLProgram(g,[r,m],i.dtype);return n.disposeIntermediateTensorInfo(m),y}var kie={kernelName:o0,backendName:"webgl",kernelFunc:wie};function Iie(e,t,n,s){let r=new $p(n,"max",!1),a=s.runWebGLProgram(r,[e],"float32");r=new $p(n,"max",!0,!0,t);let o=s.runWebGLProgram(r,[e],"float32");return[a,o]}var Sie={kernelName:l0,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{filterSize:r,strides:a,pad:o,includeBatchInIndex:i}=t,l=n;v.assert(s.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${s.shape.length}.`);let u=[1,1];v.assert(C.eitherStridesOrDilationsAreOne(a,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=C.computePool2DInfo(s.shape,r,a,u,o),[p,d]=Iie(s,i,c,l);return[p,d]}};function Cie(e,t,n,s){let r=v.sizeFromShape(t),o=v.sizeFromShape(e.shape)/r,i=be({inputs:{x:e},attrs:{shape:[o,r]},backend:s}),l=au(i,"float32","mean",s),u=be({inputs:{x:l},attrs:{shape:n},backend:s});return s.disposeIntermediateTensorInfo(i),s.disposeIntermediateTensorInfo(l),u}var Tie={kernelName:Mo,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{keepDims:r,axis:a}=t,o=n,i=s.shape.length,l=v.parseAxisParam(a,s.shape),u=l,c=C.getAxesPermutation(u,i),p=c!=null,d=o.shouldExecuteOnCPU([s]),h=[],f=s;if(p){if(d){let b=o.texData.get(f.dataId).values,w=new Array(i);for(let E=0;E<w.length;E++)w[E]=s.shape[c[E]];let k=Zx(b,s.shape,s.dtype,c,w);f=o.makeTensorInfo(w,s.dtype);let S=o.texData.get(f.dataId);S.values=k}else f=k2(s,c,o);h.push(f),u=C.getInnerMostAxes(u.length,i)}C.assertAxesAreInnerMostDims("sum",u,i);let[m,g]=C.computeOutAndReduceShapes(f.shape,u),y=m;r&&(y=C.expandShapeToKeepDim(m,l));let x=Cie(f,g,y,o);for(let A of h)o.disposeIntermediateTensorInfo(A);return x}};function Nie(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=v.parseAxisParam(a,r.shape),u=l,c=C.getAxesPermutation(u,i),p=r;c!=null&&(p=ts({inputs:{x:r},backend:n,attrs:{perm:c}}),u=C.getInnerMostAxes(u.length,r.shape.length)),C.assertAxesAreInnerMostDims("min",u,i);let[d,h]=C.computeOutAndReduceShapes(p.shape,u),f=v.sizeFromShape(h),m=be({inputs:{x:p},backend:n,attrs:{shape:[-1,f]}}),g=au(m,m.dtype,"min",n),y;if(o){let x=C.expandShapeToKeepDim(d,l);y=be({inputs:{x:g},backend:n,attrs:{shape:x}})}else y=be({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(p),y}var Eie={kernelName:zo,backendName:"webgl",kernelFunc:Nie},Rie=l9+`
+    `}};function bie(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a}=t,o=a,{filterSize:i,strides:l,pad:u,dimRoundingMode:c}=s,p=[1,1,1],d=C.computePool3DInfo(o.shape,i,l,p,u,c),h=new Jx(d,"max",!0),f=n.runWebGLProgram(h,[o],o.dtype),m=new xie(d),g=n.runWebGLProgram(m,[r,f],o.dtype);return n.disposeIntermediateTensorInfo(f),g}var vie={kernelName:o0,backendName:"webgl",kernelFunc:bie};function wie(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,input:a,output:o}=t,i=a;td([a,o],"maxPoolGrad");let{filterSize:l,strides:u,pad:c,dimRoundingMode:p}=s,d=C.computePool2DInfo(i.shape,l,u,1,c,p),h=!0,f=new Dp(d,"max",h),m=n.runWebGLProgram(f,[i],i.dtype),g=new Aie(d),y=n.runWebGLProgram(g,[r,m],i.dtype);return n.disposeIntermediateTensorInfo(m),y}var kie={kernelName:a0,backendName:"webgl",kernelFunc:wie};function Iie(e,t,n,s){let r=new Dp(n,"max",!1),a=s.runWebGLProgram(r,[e],"float32");r=new Dp(n,"max",!0,!0,t);let o=s.runWebGLProgram(r,[e],"float32");return[a,o]}var Sie={kernelName:i0,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{filterSize:r,strides:a,pad:o,includeBatchInIndex:i}=t,l=n;v.assert(s.shape.length===4,()=>`Error in maxPool: input must be rank 4 but got rank ${s.shape.length}.`);let u=[1,1];v.assert(C.eitherStridesOrDilationsAreOne(a,u),()=>`Error in maxPool: Either strides or dilations must be 1. Got strides ${a} and dilations '${u}'`);let c=C.computePool2DInfo(s.shape,r,a,u,o),[p,d]=Iie(s,i,c,l);return[p,d]}};function Cie(e,t,n,s){let r=v.sizeFromShape(t),o=v.sizeFromShape(e.shape)/r,i=be({inputs:{x:e},attrs:{shape:[o,r]},backend:s}),l=ru(i,"float32","mean",s),u=be({inputs:{x:l},attrs:{shape:n},backend:s});return s.disposeIntermediateTensorInfo(i),s.disposeIntermediateTensorInfo(l),u}var Tie={kernelName:Oo,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{keepDims:r,axis:a}=t,o=n,i=s.shape.length,l=v.parseAxisParam(a,s.shape),u=l,c=C.getAxesPermutation(u,i),p=c!=null,d=o.shouldExecuteOnCPU([s]),h=[],f=s;if(p){if(d){let b=o.texData.get(f.dataId).values,w=new Array(i);for(let E=0;E<w.length;E++)w[E]=s.shape[c[E]];let k=Zx(b,s.shape,s.dtype,c,w);f=o.makeTensorInfo(w,s.dtype);let S=o.texData.get(f.dataId);S.values=k}else f=w2(s,c,o);h.push(f),u=C.getInnerMostAxes(u.length,i)}C.assertAxesAreInnerMostDims("sum",u,i);let[m,g]=C.computeOutAndReduceShapes(f.shape,u),y=m;r&&(y=C.expandShapeToKeepDim(m,l));let x=Cie(f,g,y,o);for(let A of h)o.disposeIntermediateTensorInfo(A);return x}};function Nie(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=v.parseAxisParam(a,r.shape),u=l,c=C.getAxesPermutation(u,i),p=r;c!=null&&(p=ts({inputs:{x:r},backend:n,attrs:{perm:c}}),u=C.getInnerMostAxes(u.length,r.shape.length)),C.assertAxesAreInnerMostDims("min",u,i);let[d,h]=C.computeOutAndReduceShapes(p.shape,u),f=v.sizeFromShape(h),m=be({inputs:{x:p},backend:n,attrs:{shape:[-1,f]}}),g=ru(m,m.dtype,"min",n),y;if(o){let x=C.expandShapeToKeepDim(d,l);y=be({inputs:{x:g},backend:n,attrs:{shape:x}})}else y=be({inputs:{x:g},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(m),n.disposeIntermediateTensorInfo(g),c!=null&&n.disposeIntermediateTensorInfo(p),y}var Eie={kernelName:Mo,backendName:"webgl",kernelFunc:Nie},Rie=l9+`
   return min(a, b);
 `,_ie=`
   vec4 result = vec4(min(a, b));
   vec4 isNaN = min(vec4(isnan(a)) + vec4(isnan(b)), vec4(1.0));
-  `+v2+`
+  `+b2+`
   return result;
-`,Die=Rn({opSnippet:Rie,packedOpSnippet:_ie,cpuKernelImpl:kte}),$ie={kernelName:Lo,backendName:"webgl",kernelFunc:Die},Pie=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let s=e.length,r=wt(s),a=t.map(u=>u[0]).join(","),o=t.map((u,c)=>u[0]+e[c]).join(","),i=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,s),l=n==="reflect"?0:1;if(s===1){this.userCode=`
+`,Die=Rn({opSnippet:Rie,packedOpSnippet:_ie,cpuKernelImpl:kte}),$ie={kernelName:zo,backendName:"webgl",kernelFunc:Die},Pie=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=t.map((u,c)=>u[0]+e[c]+u[1]);let s=e.length,r=wt(s),a=t.map(u=>u[0]).join(","),o=t.map((u,c)=>u[0]+e[c]).join(","),i=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,s),l=n==="reflect"?0:1;if(s===1){this.userCode=`
         int start = ${a};
         int end = ${o};
 
@@ -3704,13 +3704,13 @@ return (log(1.0 + x) - log(1.0 - x)) / 2.0;`,wse=ct({opSnippet:vse}),kse={kernel
         ${d}
         setOutput(result);
       }
-    `}},Oie=({inputs:e,backend:t,attrs:n})=>{let{x:s}=e,{paddings:r,mode:a}=n,o=Z().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Fie(s.shape,r,a):new Pie(s.shape,r,a);return t.runWebGLProgram(o,[s],s.dtype)},Mie={kernelName:Bo,backendName:"webgl",kernelFunc:Oie},zie=`if (b == 0.0) return NAN;
+    `}},Oie=({inputs:e,backend:t,attrs:n})=>{let{x:s}=e,{paddings:r,mode:a}=n,o=X().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Fie(s.shape,r,a):new Pie(s.shape,r,a);return t.runWebGLProgram(o,[s],s.dtype)},Mie={kernelName:Lo,backendName:"webgl",kernelFunc:Oie},zie=`if (b == 0.0) return NAN;
   return mod(a, b);`,Lie=`
   vec4 result = mod(a, b);
   vec4 isNaN = vec4(equal(b, vec4(0.0)));
-  `+v2+`
+  `+b2+`
   return result;
-`,Bie=Rn({opSnippet:zie,packedOpSnippet:Lie}),Wie={kernelName:Ec,backendName:"webgl",kernelFunc:Bie},Vie=class{constructor(e,t,n){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,n],this.userCode=`
+`,Bie=Rn({opSnippet:zie,packedOpSnippet:Lie}),Wie={kernelName:Nc,backendName:"webgl",kernelFunc:Bie},Vie=class{constructor(e,t,n){this.variableNames=["probs"],this.customUniforms=[{name:"seed",type:"float"}],this.outputShape=[e,n],this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int batch = coords[0];
@@ -3752,7 +3752,7 @@ return a / b;`,Gie=`
   }
 
   return result;
-`,R9=Rn({opSnippet:Uie,packedOpSnippet:Gie,checkOutOfBounds:!0}),Hie={kernelName:Io,backendName:"webgl",kernelFunc:R9},R7="return a - b;",_9=Rn({opSnippet:R7,packedOpSnippet:R7,supportsComplex:!0,cpuKernelImpl:Bte}),jie={kernelName:si,backendName:"webgl",kernelFunc:_9};function D9(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{dim:a}=s,o=v.parseAxisParam([a],r.shape),i=E9({inputs:{x:r},backend:n,attrs:{reductionIndices:o,keepDims:!1}}),l=C.expandShapeToKeepDim(i.shape,o),u=be({inputs:{x:i},backend:n,attrs:{shape:l}}),c=_9({inputs:{a:r,b:u},backend:n}),p=C9({inputs:{x:c},backend:n}),d=I2({inputs:{x:p},backend:n,attrs:{axis:o,keepDims:!1}}),h=be({inputs:{x:d},backend:n,attrs:{shape:l}}),f=R9({inputs:{a:p,b:h},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),f}var qie={kernelName:ti,backendName:"webgl",kernelFunc:D9};function Xie(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{numSamples:a,seed:o,normalized:i}=s,l=i?r:D9({inputs:{logits:r},backend:n,attrs:{dim:r.shape.length-1}}),u=l.shape[0],c=l.shape[1],p=new Vie(u,c,a),d=[[o]],h=n.runWebGLProgram(p,[l],"int32",d);return i||n.disposeIntermediateTensorInfo(l),h}var Kie={kernelName:u0,backendName:"webgl",kernelFunc:Xie},Zie=hr+`
+`,R9=Rn({opSnippet:Uie,packedOpSnippet:Gie,checkOutOfBounds:!0}),Hie={kernelName:ko,backendName:"webgl",kernelFunc:R9},R7="return a - b;",_9=Rn({opSnippet:R7,packedOpSnippet:R7,supportsComplex:!0,cpuKernelImpl:Bte}),jie={kernelName:ni,backendName:"webgl",kernelFunc:_9};function D9(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{dim:a}=s,o=v.parseAxisParam([a],r.shape),i=E9({inputs:{x:r},backend:n,attrs:{reductionIndices:o,keepDims:!1}}),l=C.expandShapeToKeepDim(i.shape,o),u=be({inputs:{x:i},backend:n,attrs:{shape:l}}),c=_9({inputs:{a:r,b:u},backend:n}),p=C9({inputs:{x:c},backend:n}),d=k2({inputs:{x:p},backend:n,attrs:{axis:o,keepDims:!1}}),h=be({inputs:{x:d},backend:n,attrs:{shape:l}}),f=R9({inputs:{a:p,b:h},backend:n});return n.disposeIntermediateTensorInfo(i),n.disposeIntermediateTensorInfo(u),n.disposeIntermediateTensorInfo(c),n.disposeIntermediateTensorInfo(p),n.disposeIntermediateTensorInfo(d),n.disposeIntermediateTensorInfo(h),f}var qie={kernelName:ei,backendName:"webgl",kernelFunc:D9};function Xie(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{numSamples:a,seed:o,normalized:i}=s,l=i?r:D9({inputs:{logits:r},backend:n,attrs:{dim:r.shape.length-1}}),u=l.shape[0],c=l.shape[1],p=new Vie(u,c,a),d=[[o]],h=n.runWebGLProgram(p,[l],"int32",d);return i||n.disposeIntermediateTensorInfo(l),h}var Kie={kernelName:l0,backendName:"webgl",kernelFunc:Xie},Zie=hr+`
   return -x;
 `,Yie=`
   vec4 result = -x;
@@ -3764,14 +3764,14 @@ return a / b;`,Gie=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`;function Jie(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])){let a=n.texData.get(s.dataId),[o,i]=Ste(a.values,s.shape,s.dtype);return n.makeTensorInfo(i,s.dtype,o)}let r;return Z().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new Ui(s.shape,Yie):r=new pa(s.shape,Zie),n.runWebGLProgram(r,[s],s.dtype)}var Qie={kernelName:Il,backendName:"webgl",kernelFunc:Jie},ele=dr.nonMaxSuppressionV3Impl;function tle(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l}=s,u=n.readSync(r.dataId),c=n.readSync(a.dataId),{selectedIndices:p}=ele(u,c,o,i,l);return n.makeTensorInfo([p.length],"int32",new Int32Array(p))}var nle={kernelName:Cl,backendName:"webgl",kernelFunc:tle},sle=dr.nonMaxSuppressionV4Impl;function rle(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,padToMaxOutputSize:u}=s,c=n.readSync(r.dataId),p=n.readSync(a.dataId),{selectedIndices:d,validOutputs:h}=sle(c,p,o,i,l,u);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([h]))]}var ale={kernelName:Rc,backendName:"webgl",kernelFunc:rle},ole=dr.nonMaxSuppressionV5Impl;function ile(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=s,c=n.readSync(r.dataId),p=n.readSync(a.dataId),d=o,h=i,f=l,m=u,{selectedIndices:g,selectedScores:y}=ole(c,p,d,h,f,m);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var lle={kernelName:Tl,backendName:"webgl",kernelFunc:ile},ule=class{constructor(e,t,n,s){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
+`;function Jie(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])){let a=n.texData.get(s.dataId),[o,i]=Ste(a.values,s.shape,s.dtype);return n.makeTensorInfo(i,s.dtype,o)}let r;return X().getBool("WEBGL_PACK_UNARY_OPERATIONS")?r=new Vi(s.shape,Yie):r=new da(s.shape,Zie),n.runWebGLProgram(r,[s],s.dtype)}var Qie={kernelName:kl,backendName:"webgl",kernelFunc:Jie},ele=dr.nonMaxSuppressionV3Impl;function tle(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l}=s,u=n.readSync(r.dataId),c=n.readSync(a.dataId),{selectedIndices:p}=ele(u,c,o,i,l);return n.makeTensorInfo([p.length],"int32",new Int32Array(p))}var nle={kernelName:Sl,backendName:"webgl",kernelFunc:tle},sle=dr.nonMaxSuppressionV4Impl;function rle(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,padToMaxOutputSize:u}=s,c=n.readSync(r.dataId),p=n.readSync(a.dataId),{selectedIndices:d,validOutputs:h}=sle(c,p,o,i,l,u);return[n.makeTensorInfo([d.length],"int32",new Int32Array(d)),n.makeTensorInfo([],"int32",new Int32Array([h]))]}var ale={kernelName:Ec,backendName:"webgl",kernelFunc:rle},ole=dr.nonMaxSuppressionV5Impl;function ile(e){C.warn("tf.nonMaxSuppression() in webgl locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=s,c=n.readSync(r.dataId),p=n.readSync(a.dataId),d=o,h=i,f=l,m=u,{selectedIndices:g,selectedScores:y}=ole(c,p,d,h,f,m);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var lle={kernelName:Cl,backendName:"webgl",kernelFunc:ile},ule=class{constructor(e,t,n,s){this.variableNames=["indices"],this.outputShape=[e,t],this.userCode=`
       void main() {
         ivec2 coords = getOutputCoords();
         int index = round(getIndices(coords.x));
         setOutput(mix(float(${s}), float(${n}),
                       float(index == coords.y)));
       }
-    `}},cle=e=>{let{inputs:t,backend:n,attrs:s}=e,{indices:r}=t,{depth:a,onValue:o,offValue:i}=s,l=v.sizeFromShape(r.shape),u=new ule(l,a,o,i),c=be({inputs:{x:r},backend:n,attrs:{shape:[l]}}),p=n.runWebGLProgram(u,[c],r.dtype);n.disposeIntermediateTensorInfo(c);let d=[...r.shape,a],h=be({inputs:{x:p},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(p),h},dle={kernelName:El,backendName:"webgl",kernelFunc:cle};function Mm(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="complex64"){let r=zh({inputs:{input:s},backend:n}),a=Mm({inputs:{x:r},backend:n}),o=S2({inputs:{input:s},backend:n}),i=Mm({inputs:{x:o},backend:n}),l=pi({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return Lh({attrs:{shape:s.shape,dtype:s.dtype,value:s.dtype==="string"?"":0},backend:n})}var ple={kernelName:Hl,backendName:"webgl",kernelFunc:Mm};function $9(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(s.dtype==="complex64"){let r=zh({inputs:{input:s},backend:n}),a=$9({inputs:{x:r},backend:n}),o=S2({inputs:{input:s},backend:n}),i=Mm({inputs:{x:o},backend:n}),l=pi({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return Lh({attrs:{shape:s.shape,dtype:s.dtype,value:1},backend:n})}var hle={kernelName:Nl,backendName:"webgl",kernelFunc:$9};function fle(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return ly({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let p=ly({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(p),p}),u=x9({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var mle={kernelName:Rl,backendName:"webgl",kernelFunc:fle},gle=class{constructor(e,t,n){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let s=e.length,r=wt(s),a=t.map(l=>l[0]).join(","),o=t.map((l,u)=>l[0]+e[u]).join(","),i=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,s);if(s===1){this.userCode=`
+    `}},cle=e=>{let{inputs:t,backend:n,attrs:s}=e,{indices:r}=t,{depth:a,onValue:o,offValue:i}=s,l=v.sizeFromShape(r.shape),u=new ule(l,a,o,i),c=be({inputs:{x:r},backend:n,attrs:{shape:[l]}}),p=n.runWebGLProgram(u,[c],r.dtype);n.disposeIntermediateTensorInfo(c);let d=[...r.shape,a],h=be({inputs:{x:p},backend:n,attrs:{shape:d}});return n.disposeIntermediateTensorInfo(p),h},dle={kernelName:Nl,backendName:"webgl",kernelFunc:cle};function Om(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="complex64"){let r=Mh({inputs:{input:s},backend:n}),a=Om({inputs:{x:r},backend:n}),o=I2({inputs:{input:s},backend:n}),i=Om({inputs:{x:o},backend:n}),l=di({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return zh({attrs:{shape:s.shape,dtype:s.dtype,value:s.dtype==="string"?"":0},backend:n})}var ple={kernelName:Gl,backendName:"webgl",kernelFunc:Om};function $9(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(s.dtype==="complex64"){let r=Mh({inputs:{input:s},backend:n}),a=$9({inputs:{x:r},backend:n}),o=I2({inputs:{input:s},backend:n}),i=Om({inputs:{x:o},backend:n}),l=di({inputs:{real:a,imag:i},backend:n});return n.disposeIntermediateTensorInfo(r),n.disposeIntermediateTensorInfo(a),n.disposeIntermediateTensorInfo(o),n.disposeIntermediateTensorInfo(i),l}else return zh({attrs:{shape:s.shape,dtype:s.dtype,value:1},backend:n})}var hle={kernelName:Tl,backendName:"webgl",kernelFunc:$9};function fle(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return iy({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let p=iy({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(p),p}),u=x9({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeIntermediateTensorInfo(c)),u}var mle={kernelName:El,backendName:"webgl",kernelFunc:fle},gle=class{constructor(e,t,n){this.variableNames=["x"],this.customUniforms=[{name:"value",type:"float"}],this.outputShape=t.map((l,u)=>l[0]+e[u]+l[1]);let s=e.length,r=wt(s),a=t.map(l=>l[0]).join(","),o=t.map((l,u)=>l[0]+e[u]).join(","),i=["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,s);if(s===1){this.userCode=`
         int start = ${a};
         int end = ${o};
 
@@ -3820,7 +3820,7 @@ return a / b;`,Gie=`
         ${h}
         setOutput(result);
       }
-    `}},P9=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{paddings:a,constantValue:o}=s;if(v.sizeFromShape(r.shape)===0){let u=a.map((c,p)=>c[0]+r.shape[p]+c[1]);return Lh({backend:n,attrs:{shape:u,value:o,dtype:r.dtype}})}let i=Z().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new yle(r.shape,a,o):new gle(r.shape,a,o),l=[[o]];return n.runWebGLProgram(i,[r],r.dtype,l)},Ale={kernelName:Vo,backendName:"webgl",kernelFunc:P9},xle=`
+    `}},P9=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{paddings:a,constantValue:o}=s;if(v.sizeFromShape(r.shape)===0){let u=a.map((c,p)=>c[0]+r.shape[p]+c[1]);return zh({backend:n,attrs:{shape:u,value:o,dtype:r.dtype}})}let i=X().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new yle(r.shape,a,o):new gle(r.shape,a,o),l=[[o]];return n.runWebGLProgram(i,[r],r.dtype,l)},Ale={kernelName:Wo,backendName:"webgl",kernelFunc:P9},xle=`
   if(a < 0.0 && floor(b) < b){
     return NAN;
   }
@@ -3843,9 +3843,9 @@ return a / b;`,Gie=`
   result.a = isExpZero.a ? 1.0 : result.a;
 
   vec4 isNaN = vec4(lessThan(a, vec4(0.0))) * vec4(lessThan(floor(b), b));
-  `+v2+`
+  `+b2+`
   return result;
-`,vle=Rn({opSnippet:xle,packedOpSnippet:ble}),wle={kernelName:Uo,backendName:"webgl",kernelFunc:vle};function kle(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=[],u=v.parseAxisParam(a,r.shape),c=u,p=C.getAxesPermutation(c,i),d=r;p!=null&&(d=ts({inputs:{x:r},backend:n,attrs:{perm:p}}),c=C.getInnerMostAxes(c.length,i),l.push(d)),C.assertAxesAreInnerMostDims("prod",c,i);let h;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:g,outDtype:y}=Tte(d.shape,d.dtype,f,c);h=n.makeTensorInfo(g,y,m)}else{let[f,m]=C.computeOutAndReduceShapes(d.shape,c),g=v.sizeFromShape(m),y=be({inputs:{x:d},backend:n,attrs:{shape:[-1,g]}}),x=sh(r.dtype),A=au(y,x,"prod",n);h=be({inputs:{x:A},backend:n,attrs:{shape:f}}),l.push(y),l.push(A)}if(o){l.push(h);let f=C.expandShapeToKeepDim(h.shape,u);h=be({inputs:{x:h},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),h}var Ile={kernelName:Ho,backendName:"webgl",kernelFunc:kle},F9=e=>{let{backend:t,attrs:n}=e,{start:s,stop:r,step:a,dtype:o}=n,i=Nte(s,r,a,o);return t.makeTensorInfo([i.length],o,i)},Sle={kernelName:_c,backendName:"webgl",kernelFunc:F9},Cle="return 1.0 / x;",Tle=ct({opSnippet:Cle}),Nle={kernelName:Dc,backendName:"webgl",kernelFunc:Tle},Ele=hr+`
+`,vle=Rn({opSnippet:xle,packedOpSnippet:ble}),wle={kernelName:Vo,backendName:"webgl",kernelFunc:vle};function kle(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s,i=r.shape.length,l=[],u=v.parseAxisParam(a,r.shape),c=u,p=C.getAxesPermutation(c,i),d=r;p!=null&&(d=ts({inputs:{x:r},backend:n,attrs:{perm:p}}),c=C.getInnerMostAxes(c.length,i),l.push(d)),C.assertAxesAreInnerMostDims("prod",c,i);let h;if(n.shouldExecuteOnCPU([d])){let f=n.texData.get(d.dataId).values,{outVals:m,outShape:g,outDtype:y}=Tte(d.shape,d.dtype,f,c);h=n.makeTensorInfo(g,y,m)}else{let[f,m]=C.computeOutAndReduceShapes(d.shape,c),g=v.sizeFromShape(m),y=be({inputs:{x:d},backend:n,attrs:{shape:[-1,g]}}),x=nh(r.dtype),A=ru(y,x,"prod",n);h=be({inputs:{x:A},backend:n,attrs:{shape:f}}),l.push(y),l.push(A)}if(o){l.push(h);let f=C.expandShapeToKeepDim(h.shape,u);h=be({inputs:{x:h},backend:n,attrs:{shape:f}})}return l.forEach(f=>n.disposeIntermediateTensorInfo(f)),h}var Ile={kernelName:Go,backendName:"webgl",kernelFunc:kle},F9=e=>{let{backend:t,attrs:n}=e,{start:s,stop:r,step:a,dtype:o}=n,i=Nte(s,r,a,o);return t.makeTensorInfo([i.length],o,i)},Sle={kernelName:Rc,backendName:"webgl",kernelFunc:F9},Cle="return 1.0 / x;",Tle=ct({opSnippet:Cle}),Nle={kernelName:_c,backendName:"webgl",kernelFunc:Tle},Ele=hr+`
   return (x < 0.0) ? 0.0 : x;
 `,Rle=`
   vec4 result = x * vec4(greaterThanEqual(x, vec4(0.0)));
@@ -3857,7 +3857,7 @@ return a / b;`,Gie=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,_le=ct({opSnippet:Ele,packedOpSnippet:Rle}),Dle={kernelName:jo,backendName:"webgl",kernelFunc:_le},$le=hr+`
+`,_le=ct({opSnippet:Ele,packedOpSnippet:Rle}),Dle={kernelName:Ho,backendName:"webgl",kernelFunc:_le},$le=hr+`
   return (x < 0.0) ? 0.0 : min(6.0, x);
 `,Ple=`
   vec4 result = min(x, vec4(6.)) * vec4(greaterThanEqual(x, vec4(0.0)));
@@ -3869,7 +3869,7 @@ return a / b;`,Gie=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,Fle=ct({opSnippet:$le,packedOpSnippet:Ple}),Ole={kernelName:Ko,backendName:"webgl",kernelFunc:Fle},Mle=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&n>1?n-1:n],p;r?p="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":p="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+`,Fle=ct({opSnippet:$le,packedOpSnippet:Ple}),Ole={kernelName:Xo,backendName:"webgl",kernelFunc:Fle},Mle=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&n>1?n-1:n],p;r?p="(vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC - vec2(0.5)":p="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
           ${u[0]/c[0]},
           ${u[1]/c[1]});
@@ -3979,7 +3979,7 @@ return a / b;`,Gie=`
 
         setOutput(newValue);
       }
-    `}};function Lle(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=Z().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new zle(r.shape,l,u,a,o):new Mle(r.shape,l,u,a,o);return n.runWebGLProgram(c,[r],"float32")}var Ble={kernelName:Xo,backendName:"webgl",kernelFunc:Lle},Wle=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,s,r]=t,[,a,o]=e,i=[n&&a>1?s-1:s,n&&o>1?r-1:r],l=[n&&a>1?a-1:a,n&&o>1?o-1:o],u=i[0]/l[0],c=i[1]/l[1],p=1/u,d=1/c,h=Math.ceil(p)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
+    `}};function Lle(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=X().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new zle(r.shape,l,u,a,o):new Mle(r.shape,l,u,a,o);return n.runWebGLProgram(c,[r],"float32")}var Ble={kernelName:qo,backendName:"webgl",kernelFunc:Lle},Wle=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,s,r]=t,[,a,o]=e,i=[n&&a>1?s-1:s,n&&o>1?r-1:r],l=[n&&a>1?a-1:a,n&&o>1?o-1:o],u=i[0]/l[0],c=i[1]/l[1],p=1/u,d=1/c,h=Math.ceil(p)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -4060,7 +4060,7 @@ return a / b;`,Gie=`
 
         setOutput(accumulator);
       }
-    `}};function Vle(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s,i=new Wle(a.shape,r.shape,o);return n.runWebGLProgram(i,[a],a.dtype)}var Ule={kernelName:d0,backendName:"webgl",kernelFunc:Vle},Gle=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&n>1?n-1:n],p=s?"0.5":"0.0",d;r?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
+    `}};function Vle(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s,i=new Wle(a.shape,r.shape,o);return n.runWebGLProgram(i,[a],a.dtype)}var Ule={kernelName:c0,backendName:"webgl",kernelFunc:Vle},Gle=class{constructor(e,t,n,s,r){this.variableNames=["A"],this.outputShape=[];let[a,o,i,l]=e;this.outputShape=[a,t,n,l];let u=[s&&t>1?o-1:o,s&&n>1?i-1:i],c=[s&&t>1?t-1:t,s&&n>1?n-1:n],p=s?"0.5":"0.0",d;r?d="max((vec2(yRC) + vec2(0.5)) * effectiveInputOverOutputRatioRC, vec2(0.0))":d="vec2(yRC) * effectiveInputOverOutputRatioRC",this.userCode=`
       const vec2 effectiveInputOverOutputRatioRC = vec2(
           ${u[0]/c[0]},
           ${u[1]/c[1]});
@@ -4123,7 +4123,7 @@ return a / b;`,Gie=`
 
         setOutput(newValue);
       }
-    `}};function jle(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=Z().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Hle(r.shape,l,u,a,o):new Gle(r.shape,l,u,a,o);return n.runWebGLProgram(c,[r],r.dtype)}var qle={kernelName:qo,backendName:"webgl",kernelFunc:jle},Xle=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,s,r]=t,[,a,o]=e,i=[n&&a>1?s-1:s,n&&o>1?r-1:r],l=[n&&a>1?a-1:a,n&&o>1?o-1:o],u=i[0]/l[0],c=i[1]/l[1],p=1/u,d=1/c,h=Math.ceil(p)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
+    `}};function jle(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=X().getBool("WEBGL_PACK_IMAGE_OPERATIONS")?new Hle(r.shape,l,u,a,o):new Gle(r.shape,l,u,a,o);return n.runWebGLProgram(c,[r],r.dtype)}var qle={kernelName:jo,backendName:"webgl",kernelFunc:jle},Xle=class{constructor(e,t,n){this.variableNames=["dy"],this.outputShape=[],this.outputShape=t;let[,s,r]=t,[,a,o]=e,i=[n&&a>1?s-1:s,n&&o>1?r-1:r],l=[n&&a>1?a-1:a,n&&o>1?o-1:o],u=i[0]/l[0],c=i[1]/l[1],p=1/u,d=1/c,h=Math.ceil(p)*2+2,f=Math.ceil(d)*2+2;this.userCode=`
       void main() {
         ivec4 coords = getOutputCoords();
         int b = coords[0];
@@ -4193,7 +4193,7 @@ return a / b;`,Gie=`
 
         setOutput(accumulator);
       }
-    `}};function Kle(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s,i=new Xle(a.shape,r.shape,o);return n.runWebGLProgram(i,[a],a.dtype)}var Zle={kernelName:c0,backendName:"webgl",kernelFunc:Kle},Yle=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
+    `}};function Kle(e){let{inputs:t,backend:n,attrs:s}=e,{images:r,dy:a}=t,{alignCorners:o}=s,i=new Xle(a.shape,r.shape,o);return n.runWebGLProgram(i,[a],a.dtype)}var Zle={kernelName:u0,backendName:"webgl",kernelFunc:Kle},Yle=class{constructor(e,t){this.variableNames=["x"];let n=e.length;if(n>4)throw new Error(`WebGL backend: Reverse of rank-${n} tensor is not yet supported`);if(this.outputShape=e,n===1){this.userCode=`
         void main() {
           int coord = getOutputCoords();
           setOutput(getX(${e[0]} - coord - 1));
@@ -4231,7 +4231,7 @@ return a / b;`,Gie=`
           }
           setOutput(result);
         }
-    `;function i(h){return p(h)}function l(h){return h[n-1]="("+h[n-1]+" + 1)",p(h)}function u(h){return h[n-2]="("+h[n-2]+" + 1)",p(h)}function c(h){return h[n-1]="("+h[n-1]+" + 1)",h[n-2]="("+h[n-2]+" + 1)",p(h)}function p(h){let f=e.map((y,x)=>d(x,h)),m=f.join(","),g=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${g}))`}function d(h,f){return t.indexOf(h)!==-1&&e[h]!==1?`${e[h]} - ${f[h]} - 1`:`${f[h]}`}}};function Qle(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dims:a}=s,o=r.shape.length,i=v.parseAxisParam(a,r.shape);if(o===0)return Ps({inputs:{x:r},backend:n});let l=Z().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Jle(r.shape,i):new Yle(r.shape,i);return n.runWebGLProgram(l,[r],r.dtype)}var eue={kernelName:Dl,backendName:"webgl",kernelFunc:Qle},tue=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let n=e[1],s=e[2];this.outputShape=e;let r="";typeof t=="number"?r=`float outputValue = ${t.toFixed(2)};`:r=`
+    `;function i(h){return p(h)}function l(h){return h[n-1]="("+h[n-1]+" + 1)",p(h)}function u(h){return h[n-2]="("+h[n-2]+" + 1)",p(h)}function c(h){return h[n-1]="("+h[n-1]+" + 1)",h[n-2]="("+h[n-2]+" + 1)",p(h)}function p(h){let f=e.map((y,x)=>d(x,h)),m=f.join(","),g=f.slice(-2).join(",");return`getChannel(getX(${m}), vec2(${g}))`}function d(h,f){return t.indexOf(h)!==-1&&e[h]!==1?`${e[h]} - ${f[h]} - 1`:`${f[h]}`}}};function Qle(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dims:a}=s,o=r.shape.length,i=v.parseAxisParam(a,r.shape);if(o===0)return Ps({inputs:{x:r},backend:n});let l=X().getBool("WEBGL_PACK_ARRAY_OPERATIONS")?new Jle(r.shape,i):new Yle(r.shape,i);return n.runWebGLProgram(l,[r],r.dtype)}var eue={kernelName:_l,backendName:"webgl",kernelFunc:Qle},tue=class{constructor(e,t){this.variableNames=["Image"],this.outputShape=[],this.customUniforms=[{name:"params",type:"vec4"}];let n=e[1],s=e[2];this.outputShape=e;let r="";typeof t=="number"?r=`float outputValue = ${t.toFixed(2)};`:r=`
         vec3 fill = vec3(${t.join(",")});
         float outputValue = fill[coords[3]];`,this.userCode=`
         void main() {
@@ -4250,7 +4250,7 @@ return a / b;`,Gie=`
           }
           setOutput(outputValue);
         }
-    `}},nue={kernelName:jl,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,{radians:r,fillValue:a,center:o}=t,i=n,l=new tue(s.shape,a),[u,c]=C.getImageCenter(o,s.shape[1],s.shape[2]),p=[[u,c,Math.sin(r),Math.cos(r)]];return i.runWebGLProgram(l,[s],s.dtype,p)}},sue=`
+    `}},nue={kernelName:Hl,backendName:"webgl",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,{radians:r,fillValue:a,center:o}=t,i=n,l=new tue(s.shape,a),[u,c]=C.getImageCenter(o,s.shape[1],s.shape[2]),p=[[u,c,Math.sin(r),Math.cos(r)]];return i.runWebGLProgram(l,[s],s.dtype,p)}},sue=`
   // OpenGL ES does not support round function.
   // The algorithm is based on banker's rounding.
   float base = floor(x);
@@ -4265,7 +4265,7 @@ return a / b;`,Gie=`
       return base + 1.0;
     }
   }
-`,rue=ct({opSnippet:sue}),aue={kernelName:$l,backendName:"webgl",kernelFunc:rue},oue="return inversesqrt(x);",iue=ct({opSnippet:oue,cpuKernelImpl:Ete}),lue={kernelName:Zo,backendName:"webgl",kernelFunc:iue},O9=class{constructor(e,t,n,s,r,a,o=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;let i=wt(r.length),l=wt(a.length),u="";n===1?u="i":n===2&&(u="i, j");let c=`getIndices(${u})`,p="";s===1?p="i":s===2&&(p="i, coords[1]");let d=`getUpdates(${p})`,h=t>1?"strides[j]":"strides";this.userCode=`
+`,rue=ct({opSnippet:sue}),aue={kernelName:Dl,backendName:"webgl",kernelFunc:rue},oue="return inversesqrt(x);",iue=ct({opSnippet:oue,cpuKernelImpl:Ete}),lue={kernelName:Ko,backendName:"webgl",kernelFunc:iue},O9=class{constructor(e,t,n,s,r,a,o=!0){this.variableNames=["updates","indices","defaultValue"],this.outputShape=a;let i=wt(r.length),l=wt(a.length),u="";n===1?u="i":n===2&&(u="i, j");let c=`getIndices(${u})`,p="";s===1?p="i":s===2&&(p="i, coords[1]");let d=`getUpdates(${p})`,h=t>1?"strides[j]":"strides";this.userCode=`
         ${i} strides = ${i}(${r});
 
         void main() {
@@ -4285,7 +4285,7 @@ return a / b;`,Gie=`
           }
           setOutput(mix(getDefaultValue(), sum, float(found)));
         }
-      `}};function uue(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r,updates:a}=t,{shape:o}=s,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:p}=C.calculateShapes(a,r,o),d=[p/u,u];if(p===0)return n.makeTensorInfo(o,r.dtype);let h=be({inputs:{x:r},backend:n,attrs:{shape:[l,i]}}),f=be({inputs:{x:a},backend:n,attrs:{shape:[l,u]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),g=new O9(l,i,h.shape.length,f.shape.length,c,d),y=n.runWebGLProgram(g,[f,h,m],f.dtype),x=be({inputs:{x:y},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),x}var cue={kernelName:Pl,backendName:"webgl",kernelFunc:uue},due=class{constructor(e,t,n,s){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[e,n];let r="while (left < right) {",a=`for (int i = 0; i < ${Math.ceil(Math.log2(t+1))}; ++i) { if (left >= right) break;`,o=Z().getNumber("WEBGL_VERSION")===2?r:a,i=s==="left"?"<":"<=";this.userCode=`
+      `}};function uue(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r,updates:a}=t,{shape:o}=s,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:p}=C.calculateShapes(a,r,o),d=[p/u,u];if(p===0)return n.makeTensorInfo(o,r.dtype);let h=be({inputs:{x:r},backend:n,attrs:{shape:[l,i]}}),f=be({inputs:{x:a},backend:n,attrs:{shape:[l,u]}}),m=n.makeTensorInfo([],"float32",new Float32Array([0])),g=new O9(l,i,h.shape.length,f.shape.length,c,d),y=n.runWebGLProgram(g,[f,h,m],f.dtype),x=be({inputs:{x:y},backend:n,attrs:{shape:o}});return n.disposeIntermediateTensorInfo(h),n.disposeIntermediateTensorInfo(f),n.disposeIntermediateTensorInfo(y),n.disposeIntermediateTensorInfo(m),x}var cue={kernelName:$l,backendName:"webgl",kernelFunc:uue},due=class{constructor(e,t,n,s){this.variableNames=["sortedSequence","values"],this.customUniforms=[{name:"numInputs",type:"int"}],this.outputShape=[e,n];let r="while (left < right) {",a=`for (int i = 0; i < ${Math.ceil(Math.log2(t+1))}; ++i) { if (left >= right) break;`,o=X().getNumber("WEBGL_VERSION")===2?r:a,i=s==="left"?"<":"<=";this.userCode=`
        int findBound(int batch, float value) {
          int left = 0;
          int right = numInputs;
@@ -4310,7 +4310,7 @@ return a / b;`,Gie=`
 
          setOutput(float(findBound(batch, value)));
        }
-     `}};function pue(e){let{inputs:t,backend:n,attrs:s}=e,{sortedSequence:r,values:a}=t,{side:o}=s,i=new due(r.shape[0],r.shape[1],a.shape[1],o),l=[[r.shape[1]]];return n.runWebGLProgram(i,[r,a],"int32",l)}var hue={kernelName:p0,backendName:"webgl",kernelFunc:pue},fue=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let s,r;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)r="resRC",s="resRC";else{let o=["resRC.x","resRC.y","resRC.z","resRC.w"],i=[],l=[];for(let u=0;u<t.length;u++)l.push(`${o[u]}`),u<e&&i.push(`${o[u]}`);s=i.join(),r=l.join()}let a=wt(n);this.userCode=`
+     `}};function pue(e){let{inputs:t,backend:n,attrs:s}=e,{sortedSequence:r,values:a}=t,{side:o}=s,i=new due(r.shape[0],r.shape[1],a.shape[1],o),l=[[r.shape[1]]];return n.runWebGLProgram(i,[r,a],"int32",l)}var hue={kernelName:d0,backendName:"webgl",kernelFunc:pue},fue=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.outputShape=t;let s,r;if(n>4)throw Error(`Where for rank ${n} is not yet supported`);if(n===1)r="resRC",s="resRC";else{let o=["resRC.x","resRC.y","resRC.z","resRC.w"],i=[],l=[];for(let u=0;u<t.length;u++)l.push(`${o[u]}`),u<e&&i.push(`${o[u]}`);s=i.join(),r=l.join()}let a=wt(n);this.userCode=`
       void main() {
         ${a} resRC = getOutputCoords();
         float cVal = getC(${s});
@@ -4320,13 +4320,13 @@ return a / b;`,Gie=`
           setOutput(getB(${r}));
         }
       }
-    `}};function mue(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t,o=new fue(s.shape.length,r.shape,r.shape.length);return n.runWebGLProgram(o,[s,r,a],On(r.dtype,a.dtype))}var gue={kernelName:Fl,backendName:"webgl",kernelFunc:mue},yue=`
+    `}};function mue(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t,o=new fue(s.shape.length,r.shape,r.shape.length);return n.runWebGLProgram(o,[s,r,a],On(r.dtype,a.dtype))}var gue={kernelName:Pl,backendName:"webgl",kernelFunc:mue},yue=`
   // Stable and Attracting Fixed Point (0, 1) for Normalized Weights.
   // see: https://arxiv.org/abs/1706.02515
   float scaleAlpha = ${C.SELU_SCALEALPHA};
   float scale = ${C.SELU_SCALE};
   return (x >= 0.0) ? scale * x : scaleAlpha * (exp(x) - 1.0);
-`,Aue=ct({opSnippet:yue}),xue={kernelName:$c,backendName:"webgl",kernelFunc:Aue},bue=ld+`
+`,Aue=ct({opSnippet:yue}),xue={kernelName:Dc,backendName:"webgl",kernelFunc:Aue},bue=id+`
   return 1.0 / (1.0 + exp(-1.0 * x));
 `,vue=`
   vec4 result = 1.0 / (1.0 + exp(-1.0 * x));
@@ -4338,15 +4338,15 @@ return a / b;`,Gie=`
   result.a = isNaN.a ? x.a : result.a;
 
   return result;
-`,wue=ct({opSnippet:bue,packedOpSnippet:vue,cpuKernelImpl:_te}),kue={kernelName:Jo,backendName:"webgl",kernelFunc:wue},Iue=`
+`,wue=ct({opSnippet:bue,packedOpSnippet:vue,cpuKernelImpl:_te}),kue={kernelName:Yo,backendName:"webgl",kernelFunc:wue},Iue=`
   if (isnan(x)) { return 0.0; }
   return sign(x);
-`,Sue=ct({opSnippet:Iue}),Cue={kernelName:Pc,backendName:"webgl",kernelFunc:Sue},Tue=ld+`
+`,Sue=ct({opSnippet:Iue}),Cue={kernelName:$c,backendName:"webgl",kernelFunc:Sue},Tue=id+`
   return sin(x);
-`,Nue=ct({opSnippet:Tue}),Eue={kernelName:Yo,backendName:"webgl",kernelFunc:Nue},Rue=`
+`,Nue=ct({opSnippet:Tue}),Eue={kernelName:Zo,backendName:"webgl",kernelFunc:Nue},Rue=`
   float e2x = exp(x);
   return (e2x - 1.0 / e2x) / 2.0;
-`,_ue=ct({opSnippet:Rue}),Due={kernelName:Ml,backendName:"webgl",kernelFunc:_ue},$ue=`
+`,_ue=ct({opSnippet:Rue}),Due={kernelName:Ol,backendName:"webgl",kernelFunc:_ue},$ue=`
   float epsilon = 1.1920928955078125e-7;
   float threshold = log(epsilon) + 2.0;
 
@@ -4366,17 +4366,17 @@ return a / b;`,Gie=`
     result = log(exp_x + 1.0);
   }
   return result;
-`,Pue=ct({opSnippet:$ue}),Fue={kernelName:Fc,backendName:"webgl",kernelFunc:Pue},Oue=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,paddings:o}=s;v.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let i=a.reduce((y,x)=>y*x),l=[[0,0]];l.push(...o);for(let y=1+a.length;y<r.shape.length;++y)l.push([0,0]);let u=[],c=P9({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),p=C.getReshaped(c.shape,a,i,!1),d=C.getPermuted(p.length,a.length,!1),h=C.getReshapedPermuted(c.shape,a,i,!1),f=be({inputs:{x:c},backend:n,attrs:{shape:p}}),m=ts({inputs:{x:f},backend:n,attrs:{perm:d}}),g=be({inputs:{x:m},backend:n,attrs:{shape:h}});return u.push(c),u.push(f),u.push(m),u.forEach(y=>n.disposeIntermediateTensorInfo(y)),g},Mue={kernelName:zl,backendName:"webgl",kernelFunc:Oue};function zue(e){let{inputs:t,backend:n}=e,{indices:s,values:r,denseShape:a,defaultValue:o}=t;if(a.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
+`,Pue=ct({opSnippet:$ue}),Fue={kernelName:Pc,backendName:"webgl",kernelFunc:Pue},Oue=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,paddings:o}=s;v.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGL backend not implemented yet");let i=a.reduce((y,x)=>y*x),l=[[0,0]];l.push(...o);for(let y=1+a.length;y<r.shape.length;++y)l.push([0,0]);let u=[],c=P9({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),p=C.getReshaped(c.shape,a,i,!1),d=C.getPermuted(p.length,a.length,!1),h=C.getReshapedPermuted(c.shape,a,i,!1),f=be({inputs:{x:c},backend:n,attrs:{shape:p}}),m=ts({inputs:{x:f},backend:n,attrs:{perm:d}}),g=be({inputs:{x:m},backend:n,attrs:{shape:h}});return u.push(c),u.push(f),u.push(m),u.forEach(y=>n.disposeIntermediateTensorInfo(y)),g},Mue={kernelName:Ml,backendName:"webgl",kernelFunc:Oue};function zue(e){let{inputs:t,backend:n}=e,{indices:s,values:r,denseShape:a,defaultValue:o}=t;if(a.shape.length!==1)throw new Error(`Dense shape must be a vector, saw:
          ${a.shape}`);if(s.shape.length!==2)throw new Error(`Indices must be a matrix, saw:
          ${s.shape}`);if(r.shape.length!==1)throw new Error(`Values must be a vector, saw:
          ${r.shape}`);if(o.shape.length!==0)throw new Error(`Default value must be a scalar, saw:
-        ${o.shape}`);let i=n.readSync(s.dataId),l=n.readSync(r.dataId),u=n.readSync(a.dataId),c=n.readSync(o.dataId)[0],[p,d,h,f,m]=$te(i,s.shape,s.dtype,l,r.dtype,u,c);return[n.makeTensorInfo(d,s.dtype,p),n.makeTensorInfo([d[0]],r.dtype,h),n.makeTensorInfo([f.length],"bool",new Uint8Array(f.map(g=>Number(g)))),n.makeTensorInfo([m.length],s.dtype,new Int32Array(m))]}var Lue={kernelName:Xp,backendName:"webgl",kernelFunc:zue};function Bue(e){let{inputs:t,backend:n}=e,{inputIndices:s,inputShape:r,newShape:a}=t;if(s.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${s.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${r.shape}`);if(a.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${a.shape}`);let o=Array.from(n.readSync(r.dataId)),i=n.readSync(s.dataId),l=Array.from(n.readSync(a.dataId)),[u,c,p]=Pte(i,s.shape,s.dtype,o,l);return[n.makeTensorInfo(c,s.dtype,u),n.makeTensorInfo([p.length],a.dtype,new Int32Array(p))]}var Wue={kernelName:Oc,backendName:"webgl",kernelFunc:Bue};function Vue(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
+        ${o.shape}`);let i=n.readSync(s.dataId),l=n.readSync(r.dataId),u=n.readSync(a.dataId),c=n.readSync(o.dataId)[0],[p,d,h,f,m]=$te(i,s.shape,s.dtype,l,r.dtype,u,c);return[n.makeTensorInfo(d,s.dtype,p),n.makeTensorInfo([d[0]],r.dtype,h),n.makeTensorInfo([f.length],"bool",new Uint8Array(f.map(g=>Number(g)))),n.makeTensorInfo([m.length],s.dtype,new Int32Array(m))]}var Lue={kernelName:qp,backendName:"webgl",kernelFunc:zue};function Bue(e){let{inputs:t,backend:n}=e,{inputIndices:s,inputShape:r,newShape:a}=t;if(s.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape ${s.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape ${r.shape}`);if(a.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${a.shape}`);let o=Array.from(n.readSync(r.dataId)),i=n.readSync(s.dataId),l=Array.from(n.readSync(a.dataId)),[u,c,p]=Pte(i,s.shape,s.dtype,o,l);return[n.makeTensorInfo(c,s.dtype,u),n.makeTensorInfo([p.length],a.dtype,new Int32Array(p))]}var Wue={kernelName:Fc,backendName:"webgl",kernelFunc:Bue};function Vue(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
               ${r.shape}`);if(a.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
-              ${a.shape}`);let o=n.readSync(s.dataId),i=n.readSync(r.dataId),l=n.readSync(a.dataId),[u,c]=r9(o,s.shape,s.dtype,i,l,!0);return n.makeTensorInfo(c,s.dtype,u)}var Uue={kernelName:Kp,backendName:"webgl",kernelFunc:Vue};function Gue(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
+              ${a.shape}`);let o=n.readSync(s.dataId),i=n.readSync(r.dataId),l=n.readSync(a.dataId),[u,c]=r9(o,s.shape,s.dtype,i,l,!0);return n.makeTensorInfo(c,s.dtype,u)}var Uue={kernelName:Xp,backendName:"webgl",kernelFunc:Vue};function Gue(e){let{inputs:t,backend:n}=e,{data:s,indices:r,segmentIds:a}=t;if(s.shape.length<1)throw new Error("Data should be at least 1 dimensional but received scalar");if(r.shape.length!==1)throw new Error(`Indices should be a vector but received shape
              ${r.shape}`);if(a.shape.length!==1)throw new Error(`Segment ids should be a vector but received shape
-             ${a.shape}`);let o=n.readSync(s.dataId),i=n.readSync(r.dataId),l=n.readSync(a.dataId),[u,c]=r9(o,s.shape,s.dtype,i,l);return n.makeTensorInfo(c,s.dtype,u)}var Hue={kernelName:Zp,backendName:"webgl",kernelFunc:Gue};function jue(e){let{inputs:t,backend:n,attrs:s}=e,{sparseIndices:r,sparseValues:a,defaultValue:o}=t,{outputShape:i}=s,{sliceRank:l,numUpdates:u,sliceSize:c,strides:p,outputSize:d}=C.calculateShapes(a,r,i),h=!1;if(a.dtype==="string"){let y=n.bufferSync(r),x=n.bufferSync(a),A=v.decodeString(n.readSync(o.dataId)[0]),b=Rte(y,x,i,d,c,u,l,p,A,h);return n.makeTensorInfo(i,b.dtype,b.values)}let f=new O9(u,l,r.shape.length,a.shape.length,p,[d,1],h),m=n.runWebGLProgram(f,[a,r,o],a.dtype),g=be({inputs:{x:m},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(m),g}var que={kernelName:Yp,backendName:"webgl",kernelFunc:jue};function Xue(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=s,i=v.parseAxisParam(o,r.shape)[0],l=C.prepareSplitSize(r,a,i),u=r.shape.length,c=new Array(u).fill(0),p=r.shape.slice();return l.map(d=>{let h=[...p];h[i]=d;let f=ud({inputs:{x:r},backend:n,attrs:{begin:c,size:h}});return c[i]+=d,f})}var Kue={kernelName:Ll,backendName:"webgl",kernelFunc:Xue},_7="return sqrt(x);",Zue=ct({opSnippet:_7,packedOpSnippet:_7,cpuKernelImpl:Fte}),Yue={kernelName:Qo,backendName:"webgl",kernelFunc:Zue},Jue="return x * x;",Que=ct({opSnippet:Jue}),ece={kernelName:Mc,backendName:"webgl",kernelFunc:Que},D7="return (a - b) * (a - b);",tce=Rn({opSnippet:D7,packedOpSnippet:D7}),nce={kernelName:ni,backendName:"webgl",kernelFunc:tce};function sce({inputs:e,attrs:t,backend:n}){let{x:s}=e,r=hr+`
+             ${a.shape}`);let o=n.readSync(s.dataId),i=n.readSync(r.dataId),l=n.readSync(a.dataId),[u,c]=r9(o,s.shape,s.dtype,i,l);return n.makeTensorInfo(c,s.dtype,u)}var Hue={kernelName:Kp,backendName:"webgl",kernelFunc:Gue};function jue(e){let{inputs:t,backend:n,attrs:s}=e,{sparseIndices:r,sparseValues:a,defaultValue:o}=t,{outputShape:i}=s,{sliceRank:l,numUpdates:u,sliceSize:c,strides:p,outputSize:d}=C.calculateShapes(a,r,i),h=!1;if(a.dtype==="string"){let y=n.bufferSync(r),x=n.bufferSync(a),A=v.decodeString(n.readSync(o.dataId)[0]),b=Rte(y,x,i,d,c,u,l,p,A,h);return n.makeTensorInfo(i,b.dtype,b.values)}let f=new O9(u,l,r.shape.length,a.shape.length,p,[d,1],h),m=n.runWebGLProgram(f,[a,r,o],a.dtype),g=be({inputs:{x:m},backend:n,attrs:{shape:i}});return n.disposeIntermediateTensorInfo(m),g}var que={kernelName:Zp,backendName:"webgl",kernelFunc:jue};function Xue(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=s,i=v.parseAxisParam(o,r.shape)[0],l=C.prepareSplitSize(r,a,i),u=r.shape.length,c=new Array(u).fill(0),p=r.shape.slice();return l.map(d=>{let h=[...p];h[i]=d;let f=ld({inputs:{x:r},backend:n,attrs:{begin:c,size:h}});return c[i]+=d,f})}var Kue={kernelName:zl,backendName:"webgl",kernelFunc:Xue},_7="return sqrt(x);",Zue=ct({opSnippet:_7,packedOpSnippet:_7,cpuKernelImpl:Fte}),Yue={kernelName:Jo,backendName:"webgl",kernelFunc:Zue},Jue="return x * x;",Que=ct({opSnippet:Jue}),ece={kernelName:Oc,backendName:"webgl",kernelFunc:Que},D7="return (a - b) * (a - b);",tce=Rn({opSnippet:D7,packedOpSnippet:D7}),nce={kernelName:ti,backendName:"webgl",kernelFunc:tce};function sce({inputs:e,attrs:t,backend:n}){let{x:s}=e,r=hr+`
     return x > 0.0 ? 1.0 : float(${t.alpha});
-  `,a=new pa(s.shape,r);return n.runWebGLProgram(a,[s],s.dtype)}var rce={kernelName:ai,backendName:"webgl",kernelFunc:sce},ace=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let s=n.length,r=wt(n.length),a=wt(n.length),o="";if(s===1)o="coords * strides + begin";else{let i=0;o=n.map((l,u)=>(i++,n.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${i-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=`
+  `,a=new da(s.shape,r);return n.runWebGLProgram(a,[s],s.dtype)}var rce={kernelName:ri,backendName:"webgl",kernelFunc:sce},ace=class{constructor(e,t,n){this.variableNames=["x"],this.outputShape=n;let s=n.length,r=wt(n.length),a=wt(n.length),o="";if(s===1)o="coords * strides + begin";else{let i=0;o=n.map((l,u)=>(i++,n.length===1?`coords * strides[${u}] + begin[${u}]`:`coords[${i-1}] * strides[${u}] + begin[${u}]`)).join(",")}this.userCode=`
       ${r} begin = ${r}(${e});
       ${r} strides = ${r}(${t});
 
@@ -4384,15 +4384,15 @@ return a / b;`,Gie=`
         ${a} coords = getOutputCoords();
         setOutput(getX(${o}));
       }
-    `}};function oce(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,end:o,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:d}=s,{finalShapeSparse:h,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Ut.sliceInfo(r.shape,a,o,i,l,u,c,p,d),w;if(m)w=be({inputs:{x:r},backend:n,attrs:{shape:f}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let S=Ut.computeOutShape(x,A,b),E=ud({inputs:{x:r},backend:n,attrs:{begin:x,size:S}});w=be({inputs:{x:E},backend:n,attrs:{shape:f}}),n.disposeIntermediateTensorInfo(E)}else if(n.shouldExecuteOnCPU([r])){let E=n.readSync(r.dataId),R=Le(r.shape,r.dtype,E),P=Ote(h,R,b,x);w=n.makeTensorInfo(f,r.dtype,P.values)}else{let E=new ace(x,b,h);w=n.runWebGLProgram(E,[r],r.dtype)}let k=be({inputs:{x:w},backend:n,attrs:{shape:f}});return n.disposeIntermediateTensorInfo(w),k}var ice={kernelName:Bl,backendName:"webgl",kernelFunc:oce};function lce(e){let{inputs:t,backend:n,attrs:s}=e,{separator:r,nGramWidths:a,leftPad:o,rightPad:i,padWidth:l,preserveShortSequences:u}=s,{data:c,dataSplits:p}=t,d=n.readSync(c.dataId),h=n.readSync(p.dataId),[f,m]=Mte(d,h,r,a,o,i,l,u);return[n.makeTensorInfo([f.length],"string",f),n.makeTensorInfo(p.shape,"int32",m)]}var uce={kernelName:zc,backendName:"webgl",kernelFunc:lce};function cce(e){let{inputs:t,backend:n,attrs:s}=e,{skipEmpty:r}=s,{input:a,delimiter:o}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(a.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${a.shape}`);if(o.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${o.shape}`);let i=n.readSync(a.dataId),l=n.readSync(o.dataId)[0],[u,c,p]=zte(i,l,r),d=c.length;return[n.makeTensorInfo([d,2],"int32",u),n.makeTensorInfo([d],"string",c),n.makeTensorInfo([2],"int32",new Int32Array(p))]}var dce={kernelName:Jp,backendName:"webgl",kernelFunc:cce};function pce(e){let{inputs:t,backend:n,attrs:s}=e,{numBuckets:r}=s,{input:a}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");let o=n.readSync(a.dataId),i=Lte(o,r);return n.makeTensorInfo(a.shape,"int32",i)}var hce={kernelName:Qp,backendName:"webgl",kernelFunc:pce},fce="return tan(x);",mce=ct({opSnippet:fce}),gce={kernelName:Wl,backendName:"webgl",kernelFunc:mce},yce=`
+    `}};function oce(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,end:o,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:d}=s,{finalShapeSparse:h,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Ut.sliceInfo(r.shape,a,o,i,l,u,c,p,d),w;if(m)w=be({inputs:{x:r},backend:n,attrs:{shape:f}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let S=Ut.computeOutShape(x,A,b),E=ld({inputs:{x:r},backend:n,attrs:{begin:x,size:S}});w=be({inputs:{x:E},backend:n,attrs:{shape:f}}),n.disposeIntermediateTensorInfo(E)}else if(n.shouldExecuteOnCPU([r])){let E=n.readSync(r.dataId),R=Le(r.shape,r.dtype,E),P=Ote(h,R,b,x);w=n.makeTensorInfo(f,r.dtype,P.values)}else{let E=new ace(x,b,h);w=n.runWebGLProgram(E,[r],r.dtype)}let k=be({inputs:{x:w},backend:n,attrs:{shape:f}});return n.disposeIntermediateTensorInfo(w),k}var ice={kernelName:Ll,backendName:"webgl",kernelFunc:oce};function lce(e){let{inputs:t,backend:n,attrs:s}=e,{separator:r,nGramWidths:a,leftPad:o,rightPad:i,padWidth:l,preserveShortSequences:u}=s,{data:c,dataSplits:p}=t,d=n.readSync(c.dataId),h=n.readSync(p.dataId),[f,m]=Mte(d,h,r,a,o,i,l,u);return[n.makeTensorInfo([f.length],"string",f),n.makeTensorInfo(p.shape,"int32",m)]}var uce={kernelName:Mc,backendName:"webgl",kernelFunc:lce};function cce(e){let{inputs:t,backend:n,attrs:s}=e,{skipEmpty:r}=s,{input:a,delimiter:o}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(a.shape.length!==1)throw new Error(`Input must be a vector, got shape: ${a.shape}`);if(o.shape.length!==0)throw new Error(`Delimiter must be a scalar, got shape: ${o.shape}`);let i=n.readSync(a.dataId),l=n.readSync(o.dataId)[0],[u,c,p]=zte(i,l,r),d=c.length;return[n.makeTensorInfo([d,2],"int32",u),n.makeTensorInfo([d],"string",c),n.makeTensorInfo([2],"int32",new Int32Array(p))]}var dce={kernelName:Yp,backendName:"webgl",kernelFunc:cce};function pce(e){let{inputs:t,backend:n,attrs:s}=e,{numBuckets:r}=s,{input:a}=t;if(a.dtype!=="string")throw new Error("Input must be of datatype string");if(r<=0)throw new Error("Number of buckets must be at least 1");let o=n.readSync(a.dataId),i=Lte(o,r);return n.makeTensorInfo(a.shape,"int32",i)}var hce={kernelName:Jp,backendName:"webgl",kernelFunc:pce},fce="return tan(x);",mce=ct({opSnippet:fce}),gce={kernelName:Bl,backendName:"webgl",kernelFunc:mce},yce=`
   float e2x = exp(-2.0 * abs(x));
   return sign(x) * (1.0 - e2x) / (1.0 + e2x);
-`,Ace=ct({opSnippet:yce}),xce={kernelName:ri,backendName:"webgl",kernelFunc:Ace},bce=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let a=0;a<n.length;a++)n[a]=e[a]*t[a];this.outputShape=n,this.rank=n.length;let s=wt(this.rank),r=vce(e);this.userCode=`
+`,Ace=ct({opSnippet:yce}),xce={kernelName:si,backendName:"webgl",kernelFunc:Ace},bce=class{constructor(e,t){this.variableNames=["A"];let n=new Array(e.length);for(let a=0;a<n.length;a++)n[a]=e[a]*t[a];this.outputShape=n,this.rank=n.length;let s=wt(this.rank),r=vce(e);this.userCode=`
       void main() {
         ${s} resRC = getOutputCoords();
         setOutput(getA(${r}));
       }
-    `}};function vce(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],s=[];for(let r=0;r<e.length;r++)s.push(`imod(${n[r]}, ${e[r]})`);return s.join()}function M9(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reps:a}=s;if(r.dtype==="string"||r.shape.length>5){let l=n.readSync(r.dataId),u=r.dtype==="string"?l.map(d=>v.decodeString(d)):l,c=Le(r.shape,r.dtype,u),p=Wte(c,a);return n.makeTensorInfo(p.shape,p.dtype,p.values)}let o=new bce(r.shape,a);return n.runWebGLProgram(o,[r],r.dtype)}var wce={kernelName:va,backendName:"webgl",kernelFunc:M9},kce=class{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"negativeInf",type:"float"},{name:"dir",type:"int"},{name:"inc",type:"int"}],this.outputShape=e,this.userCode=`
+    `}};function vce(e){let t=e.length;if(t>5)throw Error(`Tile for rank ${t} is not yet supported`);if(t===1)return`imod(resRC, ${e[0]})`;let n=["resRC.x","resRC.y","resRC.z","resRC.w","resRC.u"],s=[];for(let r=0;r<e.length;r++)s.push(`imod(${n[r]}, ${e[r]})`);return s.join()}function M9(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reps:a}=s;if(r.dtype==="string"||r.shape.length>5){let l=n.readSync(r.dataId),u=r.dtype==="string"?l.map(d=>v.decodeString(d)):l,c=Le(r.shape,r.dtype,u),p=Wte(c,a);return n.makeTensorInfo(p.shape,p.dtype,p.values)}let o=new bce(r.shape,a);return n.runWebGLProgram(o,[r],r.dtype)}var wce={kernelName:ba,backendName:"webgl",kernelFunc:M9},kce=class{constructor(e){this.variableNames=["x","indices"],this.customUniforms=[{name:"n",type:"int"},{name:"firstPass",type:"int"},{name:"negativeInf",type:"float"},{name:"dir",type:"int"},{name:"inc",type:"int"}],this.outputShape=e,this.userCode=`
        void main() {
          ivec2 coords = getOutputCoords();
          int batch = coords[0];
@@ -4466,7 +4466,7 @@ return a / b;`,Gie=`
 
          setOutput(x0 >= x1 ? float(i0) : float(i1));
        }
-     `}};function $i(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function $7(e){let t=1;for(;t<e;)t*=2;return t}function Sce(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{k:a,sorted:o}=s,i=Z().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=Z().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=r.shape,c=u[u.length-1];if(n.shouldExecuteOnCPU([r])||c<i||a>l){let P=n.readSync(r.dataId),[_,$]=Vte(P,u,r.dtype,a,o);return[n.makeTensorInfo(_.shape,_.dtype,_.values),n.makeTensorInfo($.shape,$.dtype,$.values)]}if(a===0)return u[u.length-1]=0,[n.makeTensorInfo(u,r.dtype,[]),n.makeTensorInfo(u,"int32",[])];if(c===1)return[r,Lh({attrs:{shape:u,dtype:"int32",value:0},backend:n})];let p=n.texData.get(r.dataId),d=p!==null&&p.isPacked,h=d?n.unpackTensor(r):r,m=v.sizeFromShape(u)/c,g=be({inputs:{x:h},attrs:{shape:[m,c]},backend:n});d&&$i(n,h);let y=$7(a),x=$7(c),A=null,b=()=>A===null?[g,g]:[g,A],w=(P,_,$)=>{let T=b(),F=new kce($),q=[[c],[A===null?1:0],[Number.NEGATIVE_INFINITY],[P],[_]],z=A;A=n.runWebGLProgram(F,T,"int32",q),$i(n,z)};for(let P=1;P<y;P*=2){let _=P*2;for(let $=P;$>=1;$/=2)w(_,$,[m,x])}for(let P=x;P>y;P/=2){let _=b(),$=new Ice([m,P/2]),F=[[c],[A===null?1:0],[y]],G=A;A=n.runWebGLProgram($,_,"int32",F),$i(n,G);let q=y/2,z=q*2;for(let K=q;K>=1;K/=2)w(z,K,A.shape)}let k=A;A=ud({inputs:{x:A},backend:n,attrs:{begin:0,size:[m,a]}}),$i(n,k);let S=N9({inputs:{x:g,indices:A},backend:n,attrs:{axis:1,batchDims:1}});$i(n,g);let E=u.slice(0,-1);E.push(a),k=A,A=be({inputs:{x:A},attrs:{shape:E},backend:n}),$i(n,k);let R=S;return S=be({inputs:{x:S},attrs:{shape:E},backend:n}),$i(n,R),[S,A]}var Cce={kernelName:Vl,backendName:"webgl",kernelFunc:Sce},Tce=class{constructor(e,t,n,s,r,a){this.variableNames=["Image","Transforms"],this.outputShape=a;let o=n==="nearest"?1:2,i;switch(s){case"constant":i=1;break;case"reflect":i=2;break;case"wrap":i=3;break;case"nearest":i=4;break;default:i=1;break}this.userCode=`
+     `}};function Di(e,t){t!==null&&e.disposeIntermediateTensorInfo(t)}function $7(e){let t=1;for(;t<e;)t*=2;return t}function Sce(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{k:a,sorted:o}=s,i=X().getNumber("TOPK_LAST_DIM_CPU_HANDOFF_SIZE_THRESHOLD"),l=X().getNumber("TOPK_K_CPU_HANDOFF_THRESHOLD"),u=r.shape,c=u[u.length-1];if(n.shouldExecuteOnCPU([r])||c<i||a>l){let P=n.readSync(r.dataId),[_,$]=Vte(P,u,r.dtype,a,o);return[n.makeTensorInfo(_.shape,_.dtype,_.values),n.makeTensorInfo($.shape,$.dtype,$.values)]}if(a===0)return u[u.length-1]=0,[n.makeTensorInfo(u,r.dtype,[]),n.makeTensorInfo(u,"int32",[])];if(c===1)return[r,zh({attrs:{shape:u,dtype:"int32",value:0},backend:n})];let p=n.texData.get(r.dataId),d=p!==null&&p.isPacked,h=d?n.unpackTensor(r):r,m=v.sizeFromShape(u)/c,g=be({inputs:{x:h},attrs:{shape:[m,c]},backend:n});d&&Di(n,h);let y=$7(a),x=$7(c),A=null,b=()=>A===null?[g,g]:[g,A],w=(P,_,$)=>{let T=b(),F=new kce($),q=[[c],[A===null?1:0],[Number.NEGATIVE_INFINITY],[P],[_]],z=A;A=n.runWebGLProgram(F,T,"int32",q),Di(n,z)};for(let P=1;P<y;P*=2){let _=P*2;for(let $=P;$>=1;$/=2)w(_,$,[m,x])}for(let P=x;P>y;P/=2){let _=b(),$=new Ice([m,P/2]),F=[[c],[A===null?1:0],[y]],G=A;A=n.runWebGLProgram($,_,"int32",F),Di(n,G);let q=y/2,z=q*2;for(let Z=q;Z>=1;Z/=2)w(z,Z,A.shape)}let k=A;A=ld({inputs:{x:A},backend:n,attrs:{begin:0,size:[m,a]}}),Di(n,k);let S=N9({inputs:{x:g,indices:A},backend:n,attrs:{axis:1,batchDims:1}});Di(n,g);let E=u.slice(0,-1);E.push(a),k=A,A=be({inputs:{x:A},attrs:{shape:E},backend:n}),Di(n,k);let R=S;return S=be({inputs:{x:S},attrs:{shape:E},backend:n}),Di(n,R),[S,A]}var Cce={kernelName:Wl,backendName:"webgl",kernelFunc:Sce},Tce=class{constructor(e,t,n,s,r,a){this.variableNames=["Image","Transforms"],this.outputShape=a;let o=n==="nearest"?1:2,i;switch(s){case"constant":i=1;break;case"reflect":i=2;break;case"wrap":i=3;break;case"nearest":i=4;break;default:i=1;break}this.userCode=`
             float mapCoord(float outCoord, float len) {
               float inCoord = outCoord;
               if(${i} == 2) {
@@ -4578,7 +4578,7 @@ return a / b;`,Gie=`
               }
               setOutput(outputValue);
             }
-        `}};function Nce(e){let{inputs:t,backend:n,attrs:s}=e,{image:r,transforms:a}=t,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=s,[c,p,d,h]=r.shape,[f,m]=u!=null?u:[p,d],g=[c,f,m,h],y=new Tce(p,d,o,i,l,g);return n.runWebGLProgram(y,[r,a],"float32")}var Ece={kernelName:Ul,backendName:"webgl",kernelFunc:Nce};function Rce(e){let{inputs:t,attrs:n,backend:s}=e,{axis:r}=n,{x:a}=t;nd(a,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let o=s.readSync(a.dataId),{outputValues:i,outputShape:l,indices:u}=Ute(o,r,a.shape,a.dtype);return[s.makeTensorInfo(l,a.dtype,i),s.makeTensorInfo([u.length],"int32",u)]}var _ce={kernelName:h0,backendName:"webgl",kernelFunc:Rce};function Dce(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r,i=o.shape.length,l=r.shape[a],u=new Array(i-1),c=0;for(let m=0;m<i;m++)m!==a&&(u[c++]=o.shape[m]);let p=[],d=new Array(i).fill(0),h=o.shape.slice();h[a]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[a]=m;let g=ud({inputs:{x:o},backend:n,attrs:{begin:d,size:h}}),y=be({inputs:{x:g},backend:n,attrs:{shape:u}});f[m]=y,p.push(g)}return p.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var $ce={kernelName:Gl,backendName:"webgl",kernelFunc:Dce},Pce=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,s=e.batchSize,r=e.inSize,a=e.numSegments,o=a*Math.ceil(r/n);this.outputShape=[s,o];let i="0.0",l="sumValue",u=Math.floor(n/4)*4,c=n%4,p=`
+        `}};function Nce(e){let{inputs:t,backend:n,attrs:s}=e,{image:r,transforms:a}=t,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=s,[c,p,d,h]=r.shape,[f,m]=u!=null?u:[p,d],g=[c,f,m,h],y=new Tce(p,d,o,i,l,g);return n.runWebGLProgram(y,[r,a],"float32")}var Ece={kernelName:Vl,backendName:"webgl",kernelFunc:Nce};function Rce(e){let{inputs:t,attrs:n,backend:s}=e,{axis:r}=n,{x:a}=t;td(a,"unique"),console.warn("WARNING: ","UI might be locked temporarily as data is being downloaded");let o=s.readSync(a.dataId),{outputValues:i,outputShape:l,indices:u}=Ute(o,r,a.shape,a.dtype);return[s.makeTensorInfo(l,a.dtype,i),s.makeTensorInfo([u.length],"int32",u)]}var _ce={kernelName:p0,backendName:"webgl",kernelFunc:Rce};function Dce(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r,i=o.shape.length,l=r.shape[a],u=new Array(i-1),c=0;for(let m=0;m<i;m++)m!==a&&(u[c++]=o.shape[m]);let p=[],d=new Array(i).fill(0),h=o.shape.slice();h[a]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[a]=m;let g=ld({inputs:{x:o},backend:n,attrs:{begin:d,size:h}}),y=be({inputs:{x:g},backend:n,attrs:{shape:u}});f[m]=y,p.push(g)}return p.forEach(m=>n.disposeIntermediateTensorInfo(m)),f}var $ce={kernelName:Ul,backendName:"webgl",kernelFunc:Dce},Pce=class{constructor(e,t){this.variableNames=["x","segmentIds"];let n=e.windowSize,s=e.batchSize,r=e.inSize,a=e.numSegments,o=a*Math.ceil(r/n);this.outputShape=[s,o];let i="0.0",l="sumValue",u=Math.floor(n/4)*4,c=n%4,p=`
         sumValue += dot(values, segFilter);
     `,d="";r%n>0&&(d=`
         if (inIdx < 0 || inIdx >= ${r}) {
@@ -4684,9 +4684,9 @@ return a / b;`,Gie=`
         }
         setOutput(${l});
       }
-    `}};function Fce(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,segmentIds:a}=t,{numSegments:o}=s,i=r.shape.length,l=[],u=0,c=C.getAxesPermutation([u],i),p=r;c!=null&&(p=ts({inputs:{x:r},backend:n,attrs:{perm:c}}),l.push(p),u=C.getInnerMostAxes(1,i)[0]);let d=C.segment_util.computeOutShape(p.shape,u,o),h=v.sizeFromShape([p.shape[u]]),f=be({inputs:{x:p},backend:n,attrs:{shape:[-1,h]}});l.push(f);let m=sh(r.dtype),g=(b,w,k,S,E)=>{let R=b.shape[0],P=b.shape[1],_=C.segment_util.segOpComputeOptimalWindowSize(P,E),$={windowSize:_,inSize:P,batchSize:R,numSegments:E},T=new Pce($,w),F=n.compileAndRun(T,[b,k],S);if(l.push(F),F.shape[1]===E)return F;let G=F9({backend:n,attrs:{start:0,stop:E,step:1,dtype:"float32"}}),q=M9({inputs:{x:G},backend:n,attrs:{reps:[P/_]}});return l.push(G),l.push(q),g(F,w,q,S,E)},y=g(f,"unsortedSegmentSum",a,m,o),x=be({inputs:{x:y},backend:n,attrs:{shape:d}}),A=x;if(c!=null){l.push(x);let b=C.getUndoAxesPermutation(c);A=ts({inputs:{x:A},backend:n,attrs:{perm:b}})}return l.forEach(b=>n.disposeIntermediateTensorInfo(b)),A}var Oce={kernelName:eh,backendName:"webgl",kernelFunc:Fce},Mce=[zne,Bne,Une,jne,Xne,Yne,Qne,tse,ase,ise,cse,hse,gse,bse,kse,Sse,Tse,_se,$se,Fse,Lse,jse,Xse,Zse,nre,rre,lre,xne,dre,gre,bre,Cre,Nre,Rre,Dre,Pre,Mre,Bre,Ure,Hre,qre,Kre,Jre,eae,rae,oae,uae,pae,fae,Aae,wae,Cae,Eae,Dae,$ae,Fae,Mae,Lae,Wae,Uae,qae,Zae,Qae,toe,roe,ioe,doe,moe,Ane,yoe,fre,boe,koe,Coe,vne,Roe,Poe,Ooe,Boe,Uoe,qoe,Zoe,eie,rie,iie,uie,hie,mie,yie,vie,kie,Sie,Tie,Eie,$ie,Mie,Wie,Kie,Cne,Qie,nle,ale,lle,Jse,dle,hle,mle,Ale,wle,kne,Ile,Sle,Qse,Hie,Nle,Dle,Ole,Nne,Ble,Ule,qle,Zle,eue,nue,aue,lue,cue,hue,gue,xue,kue,Cue,Eue,Due,Gse,qie,Fue,Mue,Lue,Wue,Uue,Hue,que,Kue,Yue,ece,nce,rce,ice,uce,dce,hce,jie,Fne,gce,xce,wce,Cce,Ece,One,_ce,$ce,Oce,ple];for(let e of Mce)cr(e);var Ht;(function(e){e[e.float32=0]="float32",e[e.int32=1]="int32",e[e.bool=2]="bool",e[e.string=3]="string",e[e.complex64=4]="complex64"})(Ht||(Ht={}));var Fp;(function(e){e[e.linear=0]="linear",e[e.relu=1]="relu",e[e.relu6=2]="relu6",e[e.prelu=3]="prelu",e[e.leakyrelu=4]="leakyrelu",e[e.sigmoid=5]="sigmoid",e[e.elu=6]="elu"})(Fp||(Fp={}));var z9;function zce(e){z9=e.wasm.cwrap(Ja,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function Lce(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t;if(r.dtype!=="float32"||a.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=s,d=n.dataIdMap.get(r.dataId).id,h=n.dataIdMap.get(a.dataId).id,f=0;if(o!=null){let E=n.dataIdMap.get(o.dataId);if(E.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${E.shape.length}.`);f=E.id}let m=i==null?0:n.dataIdMap.get(i.dataId).id,g=Fp[c];if(g==null)throw new Error(`${c} activation not yet supported for FusedConv2D in the wasm backend.`);let y=l?r.shape[2]:r.shape[1],x=u?a.shape[1]:a.shape[2],A=Xl.assertAndGetBroadcastShape(r.shape.slice(0,-2),a.shape.slice(0,-2)),b=n.makeOutput([...A,y,x],r.dtype),w=n.dataIdMap.get(b.dataId).id,k=new Uint8Array(new Int32Array(r.shape).buffer),S=new Uint8Array(new Int32Array(a.shape).buffer);return z9(d,k,r.shape.length,h,S,a.shape.length,l,u,g,f,m,p||0,w),b}var Bce={kernelName:Ja,backendName:"wasm",setupFunc:zce,kernelFunc:Lce};function In(e,t){let n;function s(a){n=a.wasm.cwrap(e,null,["number","number","number"])}function r(a){let{backend:o,inputs:{x:i}}=a,l=o.dataIdMap.get(i.dataId).id,u=o.makeOutput(i.shape,t||i.dtype),c=o.dataIdMap.get(u.dataId).id;return v.sizeFromShape(u.shape)===0||n(l,Ht[i.dtype],c),u}return{kernelName:e,backendName:"wasm",setupFunc:s,kernelFunc:r}}var Wce=In(il);function _n(e,t,n){let s;function r(o){s=o.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function a(o){let{backend:i,inputs:l}=o,{a:u,b:c}=l,p=i.dataIdMap.get(u.dataId).id,d=i.dataIdMap.get(c.dataId).id,h=n!=null?n:u.dtype,f=C.assertAndGetBroadcastShape(u.shape,c.shape),m=i.makeOutput(f,h);if(v.sizeFromShape(f)===0)return m;let g=new Uint8Array(new Int32Array(u.shape).buffer),y=new Uint8Array(new Int32Array(c.shape).buffer),x=i.dataIdMap.get(m.dataId).id;return(()=>s(p,g,u.shape.length,d,y,c.shape.length,Ht[u.dtype],x))(),m}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:a}}var Vce=!0,Uce=_n(xa,Vce),L9;function Gce(e){L9=e.wasm.cwrap(po,null,["array","number","number","number"])}function Hce(e){let{inputs:t,backend:n}=e,s=n.makeOutput(t[0].shape,t[0].dtype);if(v.sizeFromShape(s.shape)===0)return s;let r=t.map(i=>n.dataIdMap.get(i.dataId).id),a=new Uint8Array(new Int32Array(r).buffer),o=n.dataIdMap.get(s.dataId).id;return L9(a,r.length,Ht[s.dtype],o),s}var jce={kernelName:po,backendName:"wasm",setupFunc:Gce,kernelFunc:Hce};function C2(e){let{inputs:{x:t},backend:n}=e,s=n.makeOutput(t.shape,t.dtype),r=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(s).set(r),s}var qce={kernelName:_o,backendName:"wasm",kernelFunc:C2},B9;function Xce(e){B9=e.wasm.cwrap(Hr,null,["number","array","number","number","number","array","number"])}function lo(e){let{inputs:t,backend:n,attrs:s}=e,[r,a]=Zce(t.x.shape,s.perm),o=!0;for(let f=0;f<a.length;f++)a[f]!==f&&(o=!1);let i=Kce(t.x.shape,s.perm),l={dataId:t.x.dataId,shape:r,dtype:t.x.dtype};if(o){let f=C2({inputs:t,backend:n});return f.shape=i,f}let u=n.makeOutput(i,l.dtype),c=n.dataIdMap.get(l.dataId).id,p=n.dataIdMap.get(u.dataId).id,d=new Uint8Array(new Int32Array(a).buffer),h=new Uint8Array(new Int32Array(l.shape).buffer);return B9(c,h,l.shape.length,Ht[l.dtype],p,d,a.length),u}function Kce(e,t){let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];return n}function Zce(e,t){let n=[],s=[];for(let r=0;r<e.length;++r)e[r]!==1&&n.push(e[r]),e[t[r]]!==1&&s.push(t[r]);for(let r=0;r<s.length;++r){let a=-1;for(let o=0;o<s.length;++o)s[o]>=r&&(a===-1||s[a]>s[o])&&(a=o);s[a]=r}return[n,s]}var Yce={kernelName:Hr,backendName:"wasm",kernelFunc:lo,setupFunc:Xce};function hi(e,t,n){let s=e.shape,r=e.shape.length,a=v.parseAxisParam(t,s),o=a,i=C.getAxesPermutation(o,r),l=null,u=!1;if(i!=null){let c=new Array(r);for(let h=0;h<c.length;h++)c[h]=s[i[h]];o=C.getInnerMostAxes(o.length,r),l=lo({inputs:{x:e},attrs:{perm:i},backend:n});let p=n.dataIdMap.get(e.dataId).id;n.dataIdMap.get(l.dataId).id!==p&&(u=!0)}return{transposed:l,originalAxes:a,axes:o,inputWasTransposed:u}}var W9;function Jce(e){W9=e.wasm.cwrap(fc,null,["number, number, number"])}function Qce(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=hi(o,r,t);if(h){let A=t.dataIdMap.get(c.dataId).id;u=c,l=A}let f=u.shape.length;C.assertAxesAreInnerMostDims("all",p,f);let[m,g]=C.computeOutAndReduceShapes(u.shape,p),y=v.sizeFromShape(g),x=t.makeOutput(m,o.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;W9(l,y,A)}if(h&&t.disposeData(c.dataId),a){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var ede={kernelName:fc,backendName:"wasm",setupFunc:Jce,kernelFunc:Qce},V9;function tde(e){V9=e.wasm.cwrap(mc,null,["number, number, number"])}function nde(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=hi(o,r,t);if(h){let A=t.dataIdMap.get(c.dataId).id;u=c,l=A}let f=u.shape.length;C.assertAxesAreInnerMostDims("any",p,f);let[m,g]=C.computeOutAndReduceShapes(u.shape,p),y=v.sizeFromShape(g),x=t.makeOutput(m,o.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;V9(l,y,A)}if(h&&t.disposeData(c.dataId),a){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var sde={kernelName:mc,backendName:"wasm",setupFunc:tde,kernelFunc:nde},U9;function rde(e){U9=e.wasm.cwrap(ho,null,["number","number","number","number","number"])}function ade(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r}=s,{x:a}=n,o=t.dataIdMap.get(a.dataId).id,i=o,l=a,{transposed:u,axes:c,inputWasTransposed:p}=hi(a,r,t);if(p){let y=t.dataIdMap.get(u.dataId).id;y!==o&&(l=u,i=y)}let d=l.shape.slice(0,-1),h=t.makeOutput(d,"int32"),f=t.dataIdMap.get(h.dataId).id,m=v.sizeFromShape(h.shape),g=l.shape[c[0]];return U9(i,Ht[l.dtype],m,g,f),p&&t.disposeData(u.dataId),h}var ode={kernelName:ho,backendName:"wasm",kernelFunc:ade,setupFunc:rde},G9;function ide(e){G9=e.wasm.cwrap(fo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function lde(e){let{inputs:t,attrs:n,backend:s}=e,r=t.x,a=s.dataIdMap.get(r.dataId).id,{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=n,c=C.computePool2DInfo(r.shape,o,i,1,l,u),p=c.filterHeight,d=c.filterWidth,h=c.padInfo.top,f=c.padInfo.right,m=c.padInfo.bottom,g=c.padInfo.left,y=c.strideHeight,x=c.strideWidth,A=c.inChannels;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${c.dataFormat}'. Please use 'channelsLast'.`);if(c.dilationWidth!==1||c.dilationHeight!==1)throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${c.dilationHeight}, ${c.dilationWidth}].`);let b=s.makeOutput(c.outShape,"float32"),w=s.dataIdMap.get(b.dataId).id;return G9(a,r.shape[0],r.shape[1],r.shape[2],p,d,h,f,m,g,y,x,A,w),b}var ude={kernelName:fo,backendName:"wasm",setupFunc:ide,kernelFunc:lde};function hs(e){let{inputs:t,attrs:n}=e,{x:s}=t,{shape:r}=n,a=v.sizeFromShape(s.shape),o=v.inferFromImplicitShape(r,a);return v.assert(a===v.sizeFromShape(o),()=>`new shape: ${o}, old shape: ${s.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(s.dataId),{dataId:s.dataId,shape:o,dtype:s.dtype}}var cde={kernelName:_l,backendName:"wasm",kernelFunc:hs},H9;function dde(e){H9=e.wasm.cwrap(mo,null,["number","array","number","number","array","number","number","number","number"])}function pde(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;if(r.dtype!=="float32"||a.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=r.shape.length,u=a.shape.length,c=o?r.shape[l-2]:r.shape[l-1],p=i?a.shape[u-1]:a.shape[u-2],d=o?r.shape[l-1]:r.shape[l-2],h=i?a.shape[u-2]:a.shape[u-1],f=r.shape.slice(0,-2),m=a.shape.slice(0,-2),g=v.sizeFromShape(f),y=v.sizeFromShape(m),A=Xl.assertAndGetBroadcastShape(r.shape.slice(0,-2),a.shape.slice(0,-2)).concat([d,h]);v.assert(c===p,()=>`Error in matMul: inner shapes (${c}) and (${p}) of Tensors with shapes ${r.shape} and ${a.shape} and transposeA=${o} and transposeB=${i} must match.`);let b=o?[g,c,d]:[g,d,c],w=i?[y,h,p]:[y,p,h],k=hs({inputs:{x:r},backend:n,attrs:{shape:b}}),S=hs({inputs:{x:a},backend:n,attrs:{shape:w}}),E=n.dataIdMap.get(k.dataId).id,R=n.dataIdMap.get(S.dataId).id,P=o?k.shape[2]:k.shape[1],_=i?S.shape[1]:S.shape[2],$=Math.max(g,y),T=n.makeOutput([$,P,_],k.dtype),F=n.dataIdMap.get(T.dataId).id,G=new Uint8Array(new Int32Array(k.shape).buffer),q=new Uint8Array(new Int32Array(S.shape).buffer);return H9(E,G,k.shape.length,R,q,S.shape.length,o,i,F),n.disposeData(k.dataId),n.disposeData(S.dataId),T.shape=A,T}var hde={kernelName:mo,backendName:"wasm",setupFunc:dde,kernelFunc:pde};function al(e){let{inputs:{x:t},attrs:{begin:n,size:s},backend:r}=e,[a,o]=Ut.parseSliceParams(t,n,s),i=Ut.isSliceContinous(t.shape,a,o),l=r.readSync(t.dataId),u=r.makeOutput(o,t.dtype),c=v.computeStrides(t.shape),p=r.dataIdMap.get(u.dataId);if(i){let f=Ut.computeFlatOffset(a,c);return t.dtype==="string"?p.stringBytes=l.slice(f,f+v.sizeFromShape(o)):r.typedArrayFromHeap(u).set(l.subarray(f,f+v.sizeFromShape(o))),u}if(t.dtype==="string"){let f=_m(l,a,o,t.shape,t.dtype);return p.stringBytes=f,u}let d=r.typedArrayFromHeap(u),h=t.shape.length;if(h===2)fde(l,c[0],d,a,o);else if(h===3)mde(l,c[0],c[1],d,a,o);else if(h===4)gde(l,c[0],c[1],c[2],d,a,o);else{let f=_m(l,a,o,t.shape,t.dtype);d.set(f)}return u}function fde(e,t,n,s,r){let a=0,o=s[0],i=s[1],l=o+r[0];for(let u=o;u<l;u++){let c=u*t+i;n.set(e.subarray(c,c+r[1]),a),a+=r[1]}}function mde(e,t,n,s,r,a){let o=0,i=r[0],l=r[1],u=r[2],c=i+a[0],p=l+a[1];for(let d=i;d<c;d++)for(let h=l;h<p;h++){let f=d*t+h*n+u;s.set(e.subarray(f,f+a[2]),o),o+=a[2]}}function gde(e,t,n,s,r,a,o){let i=0,l=a[0],u=a[1],c=a[2],p=l+o[0],d=u+o[1],h=c+o[2],f=a[3];for(let m=l;m<p;m++)for(let g=u;g<d;g++)for(let y=c;y<h;y++){let x=m*t+g*n+y*s+f;r.set(e.subarray(x,x+o[3]),i),i+=o[3]}}var yde={kernelName:Ol,backendName:"wasm",kernelFunc:al};function Ade(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s,i=a.reduce((y,x)=>y*x),l=C.getReshaped(r.shape,a,i),u=C.getPermuted(l.length,a.length),c=C.getReshapedPermuted(r.shape,a,i),p=C.getSliceBeginCoords(o,a.length),d=C.getSliceSize(c,o,a.length),h=hs({inputs:{x:r},backend:n,attrs:{shape:l}}),f=lo({inputs:{x:h},backend:n,attrs:{perm:u}}),m=hs({inputs:{x:f},backend:n,attrs:{shape:c}}),g=al({inputs:{x:m},backend:n,attrs:{begin:p,size:d}});return n.disposeData(h.dataId),n.disposeData(f.dataId),n.disposeData(h.dataId),g}var xde={kernelName:ll,backendName:"wasm",kernelFunc:Ade};function cd(e){let{inputs:{x:t},attrs:{dtype:n},backend:s}=e,r=s.makeOutput(t.shape,n),a=s.typedArrayFromHeap(t);return s.typedArrayFromHeap(r).set(a),r}var bde={kernelName:go,backendName:"wasm",kernelFunc:cd},vde=In(yo),j9;function wde(e){j9=e.wasm.cwrap(ba,null,["number","number","number","number"])}function kde(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i=n.dataIdMap.get(r.dataId).id,l=n.makeOutput(r.shape,r.dtype),u=n.dataIdMap.get(l.dataId).id;return j9(i,a,o,u),l}var Ide={kernelName:ba,backendName:"wasm",setupFunc:wde,kernelFunc:kde};function q9(e){let{inputs:t,backend:n}=e,s=v.parseAxisParam(e.attrs.axis,t[0].shape)[0],r=C.computeOutShape(t.map(h=>h.shape),s),a=t.filter(h=>v.sizeFromShape(h.shape)>0);if(a.length===1)return C2({inputs:{x:a[0]},backend:n});let o=n.makeOutput(r,t[0].dtype);if(v.sizeFromShape(r)===0)return o;let i=a.map(h=>h.shape);if(C.assertParamsConsistent(i,s),a[0].dtype==="string"){let h=a.map(A=>{let b=v.sizeFromShape(A.shape.slice(s));return hs({inputs:{x:A},backend:n,attrs:{shape:[-1,b]}})}),f=h.map(A=>({vals:n.readSync(A.dataId),shape:A.shape}));r=C.computeOutShape(h.map(A=>A.shape),1);let m=h[0].shape[0]===1,g=Nx(f,r,t[0].dtype,m),y=C.computeOutShape(a.map(A=>A.shape),s);o.shape=y;let x=n.dataIdMap.get(o.dataId);return x.stringBytes=C.fromStringArrayToUint8(g),h.forEach(A=>n.disposeData(A.dataId)),o}let l=v.sizeFromShape(a[0].shape.slice(0,s)),u=0,c=a.map(h=>{let f=v.sizeFromShape(h.shape.slice(s));return u+=f,f}),p=a.map(h=>n.typedArrayFromHeap(h)),d=n.typedArrayFromHeap(o);for(let h=0;h<l;h++){let f=h*u;for(let m=0;m<p.length;m++){let g=c[m],y=h*g,x=p[m].subarray(y,y+g);d.set(x,f),f+=g}}return o}var Sde={kernelName:ul,backendName:"wasm",kernelFunc:q9},X9;function Cde(e){X9=e.wasm.cwrap(Ao,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Tde(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a}=t,o=s.dataIdMap.get(r.dataId).id,i=s.dataIdMap.get(a.dataId).id,{strides:l,dilations:u,pad:c,dimRoundingMode:p,dataFormat:d}=n,h=C.convertConv2DDataFormat(d),f=C.computeConv2DInfo(r.shape,a.shape,l,u,c,p,!1,h),m=f.filterHeight,g=f.filterWidth,y=f.padInfo.top,x=f.padInfo.right,A=f.padInfo.bottom,b=f.padInfo.left,w=f.dilationHeight,k=f.dilationWidth,S=f.strideHeight,E=f.strideWidth,R=f.inChannels,P=f.outChannels,_=f.padInfo.type==="SAME"?1:0;if(f.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${f.dataFormat}'. Please use 'channelsLast'.`);let $=s.makeOutput(f.outShape,"float32"),T=s.dataIdMap.get($.dataId).id;return X9(o,r.shape[0],r.shape[1],r.shape[2],i,m,g,y,x,A,b,_,w,k,S,E,R,P,T),$}var Nde={kernelName:Ao,backendName:"wasm",setupFunc:Cde,kernelFunc:Tde},K9;function Ede(e){K9=e.wasm.cwrap(xo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Rde(e){let{backend:t,inputs:n,attrs:s}=e,{dy:r,filter:a}=n,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,inputShape:c}=s,p=1,d=C.convertConv2DDataFormat(l),h=C.computeConv2DInfo(c,a.shape,o,p,i,u,!1,d),{batchSize:f,filterHeight:m,filterWidth:g,inChannels:y,inHeight:x,inWidth:A,outChannels:b,outHeight:w,outWidth:k,strideHeight:S,strideWidth:E}=h,R=m-1-h.padInfo.top,P=g-1-h.padInfo.left,_=h.dataFormat==="channelsLast",$=v.computeStrides(h.inShape),T=v.computeStrides(r.shape),[F,G,q]=v.computeStrides(a.shape),z=$[0],K=_?$[1]:$[2],B=_?$[2]:1,ee=_?1:$[1],Q=T[0],oe=_?T[1]:T[2],Y=_?T[2]:1,ae=_?1:T[1],le=t.makeOutput(h.inShape,"float32"),ye=t.dataIdMap.get(le.dataId).id,we=t.dataIdMap.get(r.dataId).id,Re=t.dataIdMap.get(a.dataId).id;return K9(we,Re,f,m,g,x,A,y,w,k,b,S,E,R,P,F,G,q,z,K,B,ee,Q,oe,Y,ae,ye),le}var _de={kernelName:xo,backendName:"wasm",setupFunc:Ede,kernelFunc:Rde},Dde=In(bo),$de=In(vo),uy;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})(uy||(uy={}));var Z9;function Pde(e){Z9=e.wasm.cwrap(dl,null,["number","number","number","number","array","number","number","number","number","number"])}function Fde(e){let{backend:t,inputs:n,attrs:s}=e,{method:r,extrapolationValue:a,cropSize:o}=s,{image:i,boxes:l,boxInd:u}=n,c=l.shape[0],[p,d]=o,h=[c,p,d,i.shape[3]],f=t.dataIdMap.get(i.dataId),m;i.dtype!=="float32"&&(m=cd({backend:t,inputs:{x:i},attrs:{dtype:"float32"}}),f=t.dataIdMap.get(m.dataId));let g=f.id,y=t.dataIdMap.get(l.dataId).id,x=t.dataIdMap.get(u.dataId).id,A=t.makeOutput(h,"float32"),b=t.dataIdMap.get(A.dataId).id,w=new Uint8Array(new Int32Array(i.shape).buffer);return Z9(g,y,x,c,w,p,d,uy[r],a,b),m!=null&&t.disposeData(m.dataId),A}var Ode={kernelName:dl,backendName:"wasm",setupFunc:Pde,kernelFunc:Fde},Y9;function Mde(e){Y9=e.wasm.cwrap(cl,null,["number","number","number","number","number","number"])}function zde(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumprod does not support ${r.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([a],l),c=r;u!==null&&(c=lo({inputs:{x:r},attrs:{perm:u},backend:n}));let p=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumprod",[p],l);let d=n.makeOutput(c.shape,c.dtype),h=c.shape[p],f=n.dataIdMap.get(c.dataId).id,m=n.dataIdMap.get(d.dataId).id;Y9(f,o?1:0,i?1:0,h,m,Ht[r.dtype]);let g=d;if(u!==null){let y=C.getUndoAxesPermutation(u);g=lo({inputs:{x:d},attrs:{perm:y},backend:n}),n.disposeData(c.dataId),n.disposeData(d.dataId)}return g}var Lde={kernelName:cl,backendName:"wasm",setupFunc:Mde,kernelFunc:zde},J9;function Bde(e){J9=e.wasm.cwrap(wo,null,["number","number","number","number","number","number"])}function Wde(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumsum does not support ${r.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([a],l),c=r;u!==null&&(c=lo({inputs:{x:r},attrs:{perm:u},backend:n}));let p=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumsum",[p],l);let d=n.makeOutput(c.shape,c.dtype),h=c.shape[p],f=n.dataIdMap.get(c.dataId).id,m=n.dataIdMap.get(d.dataId).id;J9(f,o?1:0,i?1:0,h,m,Ht[r.dtype]);let g=d;if(u!==null){let y=C.getUndoAxesPermutation(u);g=lo({inputs:{x:d},attrs:{perm:y},backend:n}),n.disposeData(c.dataId),n.disposeData(d.dataId)}return g}var Vde={kernelName:wo,backendName:"wasm",setupFunc:Bde,kernelFunc:Wde},Q9;function Ude(e){Q9=e.wasm.cwrap(pl,null,["number","number","number","array","number","array","array","number","number"])}function Gde(e){let{backend:t,inputs:n,attrs:s}=e,{x:r}=n,{blockSize:a,dataFormat:o}=s,i=r.shape[0],l=o==="NHWC"?r.shape[1]:r.shape[2],u=o==="NHWC"?r.shape[2]:r.shape[3],c=o==="NHWC"?r.shape[3]:r.shape[1],p=l*a,d=u*a,h=c/(a*a),f=o==="NHWC"?[i,p,d,h]:[i,h,p,d],m=t.makeOutput(f,"float32"),y=t.dataIdMap.get(r.dataId).id,x=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),A=new Uint8Array(new Int32Array(f).buffer),b=new Uint8Array(new Int32Array(v.computeStrides(f)).buffer),w=t.dataIdMap.get(m.dataId).id;return Q9(y,a,o==="NHWC"?1:0,x,r.shape.length-1,A,b,f.length,w),m}var Hde={kernelName:pl,backendName:"wasm",setupFunc:Ude,kernelFunc:Gde},eC;function jde(e){eC=e.wasm.cwrap(ko,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function qde(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a}=t,o=s.dataIdMap.get(r.dataId).id,i=s.dataIdMap.get(a.dataId).id,{strides:l,dilations:u,pad:c,dimRoundingMode:p}=n,d=u==null?[1,1]:u,h=C.computeConv2DInfo(r.shape,a.shape,l,d,c,p,!0),f=h.filterHeight,m=h.filterWidth,g=h.padInfo.top,y=h.padInfo.right,x=h.padInfo.bottom,A=h.padInfo.left,b=h.dilationHeight,w=h.dilationWidth,k=h.strideHeight,S=h.strideWidth,E=h.inChannels,R=h.outChannels,P=h.padInfo.type==="SAME"?1:0;if(h.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${h.dataFormat}'. Please use 'channelsLast'.`);let _=s.makeOutput(h.outShape,"float32"),$=s.dataIdMap.get(_.dataId).id;return eC(o,r.shape[0],r.shape[1],r.shape[2],i,f,m,g,y,x,A,P,b,w,k,S,E,R,$),_}var Xde={kernelName:ko,backendName:"wasm",setupFunc:jde,kernelFunc:qde},Kde=In(So),Zde=!1,Yde=_n(hl,Zde,"bool"),Jde=In(Co,"float32");function cy(e){let{inputs:t,attrs:n,backend:s}=e,{input:r}=t,{dim:a}=n,o=r.shape.length,i=r.shape.slice(),l=a;return a<0&&(v.assert(-(o+1)<=a,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+a+1),i.splice(l,0,1),hs({inputs:{x:r},backend:s,attrs:{shape:i}})}var Qde={kernelName:fl,backendName:"wasm",kernelFunc:cy};function tC(e){let{attrs:{shape:t,value:n,dtype:s},backend:r}=e,a=r.makeOutput(t,s);return r.typedArrayFromHeap(a).fill(n),a}var epe={kernelName:kc,backendName:"wasm",kernelFunc:tC},nC;function tpe(e){nC=e.wasm.cwrap(gl,null,["number","number","number","number","number","number"])}function npe(e){let{inputs:t,backend:n}=e,{image:s}=t,r=n.makeOutput(s.shape,s.dtype),a=n.dataIdMap.get(s.dataId).id,o=n.dataIdMap.get(r.dataId).id,[i,l,u,c]=s.shape;return nC(a,i,l,u,c,o),r}var spe={kernelName:gl,backendName:"wasm",kernelFunc:npe,setupFunc:tpe},rpe=In(To),ape=!1,ope=_n(No,ape),sC;function ipe(e){sC=e.wasm.cwrap(Eo,null,["number","number","number","number","number","number","number"])}function lpe(e){let{backend:t,inputs:n,attrs:s}=e,{varianceEpsilon:r}=s,{x:a,mean:o,variance:i,offset:l,scale:u}=n,c=t.dataIdMap.get(a.dataId).id,p=t.dataIdMap.get(o.dataId).id,d=t.dataIdMap.get(i.dataId).id,h=l!=null?t.dataIdMap.get(l.dataId).id:0,f=u!=null?t.dataIdMap.get(u.dataId).id:0,m=t.makeOutput(a.shape,a.dtype);if(v.sizeFromShape(a.shape)===0)return m;let g=t.dataIdMap.get(m.dataId).id;return sC(c,p,d,h,f,r,g),m}var upe={kernelName:Eo,backendName:"wasm",setupFunc:ipe,kernelFunc:lpe},rC;function cpe(e){rC=e.wasm.cwrap(Qa,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function dpe(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dataFormat:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=n,m=C.computeConv2DInfo(r.shape,a.shape,l,c,u,d),g=Fp[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedConv2D in the wasm backend.`);let y=s.dataIdMap.get(r.dataId).id,x=s.dataIdMap.get(a.dataId).id,A=m.outChannels,b=0;if(o!=null){let Y=s.dataIdMap.get(o.dataId);if(Y.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${Y.shape.length}.`);if(Y.shape[0]!==A)throw new Error(`FusedConv2D bias shape (${Y.shape}) does not match the number of output channels (${A})`);b=Y.id}let w=m.filterHeight,k=m.filterWidth,S=m.padInfo.top,E=m.padInfo.right,R=m.padInfo.bottom,P=m.padInfo.left,_=m.dilationHeight,$=m.dilationWidth,T=m.strideHeight,F=m.strideWidth,G=m.inChannels,q=m.padInfo.type==="SAME"?1:0,z=m.batchSize,K=m.inHeight,B=m.inWidth;if(p!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${p}'. Please use 'NHWC'.`);let ee=s.makeOutput(m.outShape,"float32"),Q=s.dataIdMap.get(ee.dataId).id,oe=i==null?0:s.dataIdMap.get(i.dataId).id;return rC(y,z,K,B,x,w,k,b,S,E,R,P,q,_,$,T,F,G,A,g,oe,f||0,Q),ee}var ppe={kernelName:Qa,backendName:"wasm",setupFunc:cpe,kernelFunc:dpe},aC;function hpe(e){aC=e.wasm.cwrap(eo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function fpe(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dataFormat:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=n,m=C.computeConv2DInfo(r.shape,a.shape,l,c,u,d,!0),g=Fp[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let y=s.dataIdMap.get(r.dataId).id,x=s.dataIdMap.get(a.dataId).id,A=m.outChannels,b=0;if(o!=null){let Y=s.dataIdMap.get(o.dataId);if(Y.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${Y.shape.length}.`);if(Y.shape[0]!==A)throw new Error(`FusedDepthwiseConv2D bias shape (${Y.shape}) does not match the number of output channels (${A})`);b=Y.id}let w=m.filterHeight,k=m.filterWidth,S=m.padInfo.top,E=m.padInfo.right,R=m.padInfo.bottom,P=m.padInfo.left,_=m.dilationHeight,$=m.dilationWidth,T=m.strideHeight,F=m.strideWidth,G=m.inChannels,q=m.padInfo.type==="SAME"?1:0,z=m.batchSize,K=m.inHeight,B=m.inWidth;if(p!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${p}'. Please use 'NHWC'.`);let ee=s.makeOutput(m.outShape,"float32"),Q=s.dataIdMap.get(ee.dataId).id,oe=i==null?0:s.dataIdMap.get(i.dataId).id;return aC(y,z,K,B,x,w,k,b,S,E,R,P,q,_,$,T,F,G,A,g,oe,f||0,Q),ee}var mpe={kernelName:eo,backendName:"wasm",setupFunc:hpe,kernelFunc:fpe},oC;function gpe(e){oC=e.wasm.cwrap(Al,null,["number","number","number","number","number","number","array","number"])}function ype(e){let{backend:t,inputs:n}=e,{params:s,indices:r}=n,[a,o,i,l]=zy.prepareAndValidate(s,r),u=t.makeOutput(a,s.dtype);if(o===0)return u;let c=r.shape,p=c[c.length-1],h=t.dataIdMap.get(s.dataId).id,m=t.dataIdMap.get(r.dataId).id,g=new Uint8Array(new Int32Array(l).buffer),y=t.dataIdMap.get(u.dataId).id;return oC(h,Ht[s.dtype],m,o,p,i,g,y),u}var Ape={kernelName:Al,backendName:"wasm",setupFunc:gpe,kernelFunc:ype},iC;function xpe(e){iC=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function bpe(e){let{backend:t,inputs:n,attrs:s}=e,{x:r,indices:a}=n,{axis:o,batchDims:i}=s,l=v.parseAxisParam(o,r.shape)[0],u=t.readSync(a.dataId),c=r.shape[l];for(let R=0;R<u.length;++R){let P=u[R];v.assert(P<=c-1&&P>=0,()=>`GatherV2: the index value ${P} is not in [0, ${c-1}]`)}let p=C.segment_util.collectGatherOpShapeInfo(r,a,l,i),d=hs({inputs:{x:r},attrs:{shape:[p.batchSize,p.outerSize,p.dimSize,p.sliceSize]},backend:t}),h=v.sizeFromShape(a.shape),f=hs({inputs:{x:a},attrs:{shape:[p.batchSize,h/p.batchSize]},backend:t}),m=[p.batchSize,p.outerSize,h/p.batchSize,p.sliceSize],g=t.makeOutput(m,r.dtype);if(v.sizeFromShape(r.shape)===0)return g;let y=d.shape.length-1,A=t.dataIdMap.get(d.dataId).id,w=t.dataIdMap.get(f.dataId).id,k=t.dataIdMap.get(g.dataId).id,S=new Uint8Array(new Int32Array(v.computeStrides(d.shape)).buffer),E=new Uint8Array(new Int32Array(v.computeStrides(m)).buffer);return iC(A,Ht[r.dtype],S,y,w,p.batchSize,E,k),t.disposeData(d.dataId),t.disposeData(f.dataId),g.shape=p.outputShape,g}var vpe={kernelName:yl,backendName:"wasm",setupFunc:xpe,kernelFunc:bpe},wpe=!1,kpe=_n(xl,wpe,"bool"),Ipe=!1,Spe=_n(Ro,Ipe,"bool"),lC;function Cpe(e){lC=e.wasm.cwrap(Do,null,["number","number","number","number"])}function Tpe(e){let{inputs:{x:t},attrs:{alpha:n},backend:s}=e,r=s.dataIdMap.get(t.dataId).id,a=s.makeOutput(t.shape,"float32");if(v.sizeFromShape(t.shape)!==0){let o=s.dataIdMap.get(a.dataId).id;lC(r,Ht[t.dtype],n,o)}return a}var Npe={kernelName:Do,backendName:"wasm",setupFunc:Cpe,kernelFunc:Tpe},Epe=!1,Rpe=_n(bl,Epe,"bool"),_pe=!1,Dpe=_n(vl,_pe,"bool"),$pe=In($o),Ppe=!1,Fpe=_n(wl,Ppe,"bool"),Ope=In(kl),Mpe=!1,zpe=_n(Nc,Mpe,"bool"),Lpe=!1,Bpe=_n(d6,Lpe,"bool"),uC;function Wpe(e){uC=e.wasm.cwrap(Po,null,["number","number","number","number"])}function Vpe(e){let{backend:t,inputs:n,attrs:s}=e,{reductionIndices:r,keepDims:a}=s,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=hi(o,r,t);if(h){let A=t.dataIdMap.get(c.dataId).id;u=c,l=A}let f=u.shape.length;C.assertAxesAreInnerMostDims("max",p,f);let[m,g]=C.computeOutAndReduceShapes(u.shape,p),y=v.sizeFromShape(g),x=t.makeOutput(m,o.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;uC(l,Ht[o.dtype],y,A)}if(h&&t.disposeData(c.dataId),a){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var Upe={kernelName:Po,backendName:"wasm",setupFunc:Wpe,kernelFunc:Vpe},Gpe=!1,Hpe=_n(Fo,Gpe),cC;function jpe(e){cC=e.wasm.cwrap(Oo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function qpe(e){let{inputs:t,attrs:n,backend:s}=e,r=t.x,a=s.dataIdMap.get(r.dataId).id;v.assert(r.dtype==="float32",()=>`Error in MaxPool: only float32 input is supported. Got ${r.dtype}.`);let{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=n,c=C.computePool2DInfo(r.shape,o,i,1,l,u),p=c.filterHeight,d=c.filterWidth,h=c.padInfo.top,f=c.padInfo.right,m=c.padInfo.bottom,g=c.padInfo.left,y=c.dilationHeight,x=c.dilationWidth,A=c.strideHeight,b=c.strideWidth,w=c.inChannels,k=c.outChannels;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${c.dataFormat}'. Please use 'channelsLast'.`);let S=s.makeOutput(c.outShape,"float32"),E=s.dataIdMap.get(S.dataId).id;return cC(a,r.shape[0],r.shape[1],r.shape[2],p,d,h,f,m,g,y,x,A,b,w,k,E),S}var Xpe={kernelName:Oo,backendName:"wasm",setupFunc:jpe,kernelFunc:qpe},dC;function Kpe(e){dC=e.wasm.cwrap(Mo,null,["number, number, number"])}function Zpe(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,i=t.dataIdMap.get(o.dataId).id,l=i,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=hi(o,r,t),f=p;if(h){let b=t.dataIdMap.get(c.dataId).id;b!==i&&(u=c,l=b,f=C.getInnerMostAxes(f.length,u.shape.length))}C.assertAxesAreInnerMostDims("mean",f,u.shape.length);let[m,g]=C.computeOutAndReduceShapes(u.shape,f),y=v.sizeFromShape(g),x=u;u.dtype!=="float32"&&(x=cd({backend:t,inputs:{x:u},attrs:{dtype:"float32"}}),l=t.dataIdMap.get(x.dataId).id);let A=t.makeOutput(m,"float32");if(v.sizeFromShape(u.shape)!==0){let b=t.dataIdMap.get(A.dataId).id;dC(l,y,b)}if(h&&t.disposeData(c.dataId),a){let b=C.expandShapeToKeepDim(A.shape,d);A.shape=b}return u.dtype!=="float32"&&t.disposeData(x.dataId),A}var Ype={kernelName:Mo,backendName:"wasm",setupFunc:Kpe,kernelFunc:Zpe},pC;function Jpe(e){pC=e.wasm.cwrap(zo,null,["number","number","number","number"])}function Qpe(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,i=t.dataIdMap.get(o.dataId).id,l=i,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=hi(o,r,t);if(h){let A=t.dataIdMap.get(c.dataId).id;A!==i&&(u=c,l=A)}let f=u.shape.length;C.assertAxesAreInnerMostDims("min",p,f);let[m,g]=C.computeOutAndReduceShapes(u.shape,p),y=v.sizeFromShape(g),x=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;pC(l,Ht[o.dtype],y,A)}if(h&&t.disposeData(c.dataId),a){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var ehe={kernelName:zo,backendName:"wasm",setupFunc:Jpe,kernelFunc:Qpe},the=!1,nhe=_n(Lo,the),dy;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(dy||(dy={}));var hC;function she(e){hC=e.wasm.cwrap(Bo,null,["number","array","number","number","array","array","number","number"])}function rhe(e){let{inputs:{x:t},backend:n,attrs:{paddings:s,mode:r}}=e,a=s.map((f,m)=>f[0]+t.shape[m]+f[1]),o=n.dataIdMap.get(t.dataId).id,i=n.makeOutput(a,t.dtype),l=n.dataIdMap.get(i.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),c=s.map(f=>f[0]),p=s.map(f=>f[1]),d=new Uint8Array(new Int32Array(c).buffer),h=new Uint8Array(new Int32Array(p).buffer);return hC(o,u,t.shape.length,Ht[t.dtype],d,h,dy[r],l),i}var ahe={kernelName:Bo,backendName:"wasm",kernelFunc:rhe,setupFunc:she},ohe=!0,ihe=_n(Wo,ohe),lhe=In(Il);function Qx(e,t){let n=new Int32Array(e.wasm.HEAPU8.buffer,t,4),s=n[0],r=n[1],a=n[2],o=n[3];return e.wasm._free(t),{pSelectedIndices:s,selectedSize:r,pSelectedScores:a,pValidOutputs:o}}var fC;function uhe(e){fC=e.wasm.cwrap(Cl,"number",["number","number","number","number","number"])}function che(e){let{backend:t,inputs:n,attrs:s}=e,{iouThreshold:r,maxOutputSize:a,scoreThreshold:o}=s,{boxes:i,scores:l}=n,u=t.dataIdMap.get(i.dataId).id,c=t.dataIdMap.get(l.dataId).id,p=fC(u,c,a,r,o),{pSelectedIndices:d,selectedSize:h,pSelectedScores:f,pValidOutputs:m}=Qx(t,p);return t.wasm._free(f),t.wasm._free(m),t.makeOutput([h],"int32",d)}var dhe={kernelName:Cl,backendName:"wasm",setupFunc:uhe,kernelFunc:che},mC;function phe(e){mC=e.wasm.cwrap(Rc,"number",["number","number","number","number","number","bool"])}function hhe(e){let{backend:t,inputs:n,attrs:s}=e,{iouThreshold:r,maxOutputSize:a,scoreThreshold:o,padToMaxOutputSize:i}=s,{boxes:l,scores:u}=n,c=t.dataIdMap.get(l.dataId).id,p=t.dataIdMap.get(u.dataId).id,d=mC(c,p,a,r,o,i),{pSelectedIndices:h,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=Qx(t,d);t.wasm._free(m);let y=t.makeOutput([f],"int32",h),x=t.makeOutput([],"int32",g);return[y,x]}var fhe={kernelName:Rc,backendName:"wasm",setupFunc:phe,kernelFunc:hhe},gC;function mhe(e){gC=e.wasm.cwrap(Tl,"number",["number","number","number","number","number","number"])}function ghe(e){let{backend:t,inputs:n,attrs:s}=e,{iouThreshold:r,maxOutputSize:a,scoreThreshold:o,softNmsSigma:i}=s,{boxes:l,scores:u}=n,c=t.dataIdMap.get(l.dataId).id,p=t.dataIdMap.get(u.dataId).id,d=gC(c,p,a,r,o,i),{pSelectedIndices:h,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=Qx(t,d);t.wasm._free(g);let y=t.makeOutput([f],"int32",h),x=t.makeOutput([f],"float32",m);return[y,x]}var yhe={kernelName:Tl,backendName:"wasm",setupFunc:mhe,kernelFunc:ghe},Ahe=!1,xhe=_n(Sl,Ahe,"bool"),yC;function bhe(e){yC=e.wasm.cwrap(El,null,["number","number","number","number","number"])}function vhe(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r}=t,{depth:a,onValue:o,offValue:i}=s,l=n.makeOutput([...r.shape,a],"int32"),u=n.dataIdMap.get(l.dataId).id,p=n.dataIdMap.get(r.dataId).id;return yC(p,a,o,i,u),l}var whe={kernelName:El,backendName:"wasm",setupFunc:bhe,kernelFunc:vhe};function khe(e){let{inputs:{x:t},backend:n}=e,s=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(s).fill(1),s}var Ihe={kernelName:Nl,backendName:"wasm",kernelFunc:khe};function She(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return cy({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let p=cy({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(p),p}),u=q9({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeData(c.dataId)),u}var Che={kernelName:Rl,backendName:"wasm",kernelFunc:She},AC;function The(e){AC=e.wasm.cwrap(Vo,null,["number","array","number","number","array","array","number","number"])}function Nhe(e){let{inputs:{x:t},backend:n,attrs:{paddings:s,constantValue:r}}=e,a=s.map((m,g)=>m[0]+t.shape[g]+m[1]);if(v.sizeFromShape(t.shape)===0)return tC({backend:n,attrs:{shape:a,value:r,dtype:t.dtype}});let o=n.dataIdMap.get(t.dataId).id,i=n.makeOutput(a,t.dtype),u=n.dataIdMap.get(i.dataId).id,c=new Uint8Array(new Int32Array(t.shape).buffer),p=s.map(m=>m[0]),d=s.map(m=>m[1]),h=new Uint8Array(new Int32Array(p).buffer),f=new Uint8Array(new Int32Array(d).buffer);return AC(o,c,t.shape.length,Ht[t.dtype],h,f,r,u),i}var xC={kernelName:Vo,backendName:"wasm",kernelFunc:Nhe,setupFunc:The},Ehe=!1,Rhe=_n(Uo,Ehe),bC;function _he(e){bC=e.wasm.cwrap(Go,null,["number","number","number"])}function Dhe(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t,a=n.dataIdMap.get(s.dataId).id,o=n.dataIdMap.get(r.dataId).id,i=a,l=s,u=l;l.dtype!=="float32"&&(u=cd({backend:n,inputs:{x:s},attrs:{dtype:"float32"}}),i=n.dataIdMap.get(u.dataId).id);let c=n.makeOutput(s.shape,"float32"),p=n.dataIdMap.get(c.dataId).id;return bC(i,o,p),l.dtype!=="float32"&&n.disposeData(u.dataId),c}var $he={kernelName:Go,backendName:"wasm",setupFunc:_he,kernelFunc:Dhe},vC;function Phe(e){vC=e.wasm.cwrap(Ho,null,["number","number","number","number"])}function Fhe(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,i=t.dataIdMap.get(o.dataId).id,l=i,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=hi(o,r,t),f=p;if(h){let A=t.dataIdMap.get(c.dataId).id;A!==i&&(u=c,l=A,f=C.getInnerMostAxes(f.length,u.shape.length))}C.assertAxesAreInnerMostDims("prod",f,u.shape.length);let[m,g]=C.computeOutAndReduceShapes(u.shape,f),y=v.sizeFromShape(g),x=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;vC(l,y,Ht[x.dtype],A)}if(h&&t.disposeData(c.dataId),a){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var Ohe={kernelName:Ho,backendName:"wasm",setupFunc:Phe,kernelFunc:Fhe},Mhe=e=>{let{backend:t,attrs:n}=e,{start:s,stop:r,step:a,dtype:o}=n,i=_x(s,r,a,o),l=t.makeOutput([i.length],o);return t.typedArrayFromHeap(l).set(i),l},zhe={kernelName:_c,backendName:"wasm",kernelFunc:Mhe},Lhe=!0,Bhe=_n(Io,Lhe),Whe=In(jo),Vhe=In(Ko),wC;function Uhe(e){wC=e.wasm.cwrap(Xo,null,["number","number","number","number","number","number","number","number","number","number"])}function Ghe(e){let{backend:t,inputs:n,attrs:s}=e,{images:r}=n,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,[c,p,d,h]=r.shape,f=[c,l,u,h],m=t.dataIdMap.get(r.dataId),g;m.dtype!=="float32"&&(g=cd({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),m=t.dataIdMap.get(g.dataId));let y=m.id,x=t.makeOutput(f,"float32");if(v.sizeFromShape(r.shape)===0)return x;let A=t.dataIdMap.get(x.dataId).id;return wC(y,c,p,d,h,l,u,a?1:0,o?1:0,A),g!=null&&t.disposeData(g.dataId),x}var Hhe={kernelName:Xo,backendName:"wasm",setupFunc:Uhe,kernelFunc:Ghe},kC;function jhe(e){kC=e.wasm.cwrap(qo,null,["number","number","number","number","number","number","number","number","number","number"])}function qhe(e){let{backend:t,inputs:n,attrs:s}=e,{images:r}=n,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,[c,p,d,h]=r.shape,f=[c,l,u,h],m=t.makeOutput(f,"float32");if(v.sizeFromShape(r.shape)===0)return m;let g=t.dataIdMap.get(r.dataId),y;g.dtype!=="float32"&&(y=cd({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),g=t.dataIdMap.get(y.dataId));let x=g.id,A=t.dataIdMap.get(m.dataId).id;return kC(x,c,p,d,h,l,u,a?1:0,o?1:0,A),y!=null&&t.disposeData(y.dataId),m}var Xhe={kernelName:qo,backendName:"wasm",setupFunc:jhe,kernelFunc:qhe},IC;function Khe(e){IC=e.wasm.cwrap(Dl,null,["number","array","number","array","number","number"])}function Zhe(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dims:a}=s,o=v.parseAxisParam(a,r.shape);if(r.shape.length===0)return C2({inputs:{x:r},backend:n});let i=n.makeOutput(r.shape,r.dtype),l=n.dataIdMap.get(r.dataId).id,u=n.dataIdMap.get(i.dataId).id,c=new Uint8Array(new Int32Array(o).buffer),p=new Uint8Array(new Int32Array(r.shape).buffer);IC(l,c,o.length,p,r.shape.length,u);let d=hs({inputs:{x:i},attrs:{shape:r.shape},backend:n});return n.disposeData(i.dataId),d}var Yhe={kernelName:Dl,backendName:"wasm",kernelFunc:Zhe,setupFunc:Khe},SC;function Jhe(e){SC=e.wasm.cwrap(jl,null,["number","number","number","number","number","number","number","number","array","number","number"])}function Qhe(e){let{inputs:t,backend:n,attrs:s}=e,{image:r}=t,{radians:a,fillValue:o,center:i}=s,l=n.makeOutput(r.shape,r.dtype),u=n.dataIdMap.get(r.dataId).id,c=n.dataIdMap.get(l.dataId).id,[p,d,h,f]=r.shape,[m,g]=C.getImageCenter(i,d,h),y=o===0,x=255,A=typeof o=="number"?[o,o,o,y?0:x]:[...o,x],b=new Uint8Array(new Int32Array(A).buffer);return SC(u,p,d,h,f,a,m,g,b,A.length,c),l}var efe={kernelName:jl,backendName:"wasm",kernelFunc:Qhe,setupFunc:Jhe},tfe=In($l),nfe=In(Zo),CC;function sfe(e){CC=e.wasm.cwrap(Pl,null,["number","number","number","number","number","number","array","number","number"])}function rfe(e){let{backend:t,inputs:n,attrs:s}=e,{indices:r,updates:a}=n,{shape:o}=s,i=t.makeOutput(o,a.dtype);if(v.sizeFromShape(o)===0)return i;let{sliceRank:l,numUpdates:u,sliceSize:c,strides:p,outputSize:d}=Ly.calculateShapes(a,r,o),f=t.dataIdMap.get(r.dataId).id,g=t.dataIdMap.get(a.dataId).id,y=new Uint8Array(new Int32Array(p).buffer),x=t.dataIdMap.get(i.dataId).id;return CC(f,g,Ht[a.dtype],l,u,c,y,d,x),i}var afe={kernelName:Pl,backendName:"wasm",setupFunc:sfe,kernelFunc:rfe},TC;function ofe(e){TC=e.wasm.cwrap("SelectV2",null,["number","number","number","number","number"])}function ife(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t,o=n.dataIdMap.get(s.dataId).id,i=n.dataIdMap.get(r.dataId).id,l=n.dataIdMap.get(a.dataId).id,u=n.makeOutput(r.shape,r.dtype),c=n.dataIdMap.get(u.dataId).id,p=s.shape.length,d=r.shape.length,h=p===0||p>1||d===1?1:v.sizeFromShape(r.shape.slice(1));return TC(o,i,l,h,c),u}var lfe={kernelName:Fl,backendName:"wasm",kernelFunc:ife,setupFunc:ofe},NC;function ufe(e){NC=e.wasm.cwrap(Jo,null,["number","number"])}function cfe(e){let{backend:t,inputs:{x:n}}=e,s=t.dataIdMap.get(n.dataId).id,r=t.makeOutput(n.shape,n.dtype),a=t.dataIdMap.get(r.dataId).id;return v.sizeFromShape(r.shape)===0||NC(s,a),r}var dfe={kernelName:"Sigmoid",backendName:"wasm",setupFunc:ufe,kernelFunc:cfe},pfe=In(Yo),EC;function hfe(e){EC=e.wasm.cwrap(ti,null,["number","number","number","number"])}function ffe(e){let{backend:t,inputs:{logits:n},attrs:{dim:s}}=e,r=t.dataIdMap.get(n.dataId).id,a=t.makeOutput(n.shape,n.dtype),o=t.dataIdMap.get(a.dataId).id,i=n.shape[s],l=v.sizeFromShape(n.shape)/i;return v.sizeFromShape(a.shape)===0||EC(r,o,i,l),a}var mfe={kernelName:ti,backendName:"wasm",setupFunc:hfe,kernelFunc:ffe};function gfe(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,paddings:o}=s,i=v.sizeFromShape(a),l=[[0,0]];l.push(...o);for(let k=1+a.length;k<r.shape.length;++k)l.push([0,0]);let u=xC.kernelFunc({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),c=C.getReshaped(u.shape,a,i,!1),p=C.getPermuted(c.length,a.length,!1),d=C.getReshapedPermuted(u.shape,a,i,!1),m=hs({inputs:{x:u},backend:n,attrs:{shape:c}}),x=lo({inputs:{x:m},backend:n,attrs:{perm:p}}),w=hs({inputs:{x},backend:n,attrs:{shape:d}});return n.disposeData(u.dataId),n.disposeData(m.dataId),n.disposeData(x.dataId),w}var yfe={kernelName:zl,backendName:"wasm",kernelFunc:gfe},RC;function Afe(e){RC=e.wasm.cwrap("SparseFillEmptyRows","number",["number","number","number","number","number","number","number","number","number","number","number","number"])}function xfe(e){let{backend:t,inputs:n}=e,{indices:s,values:r,denseShape:a,defaultValue:o}=n,i=s.shape[0],l=s.shape[1],u=t.readSync(a.dataId)[0],c=[i+u,l],p=t.dataIdMap.get(s.dataId).id,d=t.dataIdMap.get(r.dataId).id,h=t.dataIdMap.get(o.dataId).id,f=t.makeOutput(c,s.dtype),m=t.dataIdMap.get(f.dataId).id,g=t.makeOutput(c.slice(0,1),r.dtype),y=t.dataIdMap.get(g.dataId).id,x=t.makeOutput([u],"bool"),A=t.dataIdMap.get(x.dataId).id,b=t.makeOutput([i],s.dtype),w=t.dataIdMap.get(b.dataId).id,k=t.makeOutput([4],"int32"),S=t.dataIdMap.get(k.dataId).id,E=RC(p,d,Ht[r.dtype],i,u,l,h,m,y,A,w,S),R=t.readSync(k.dataId),P;switch(R[0]){case 1:{P=C.getSparseFillEmptyRowsIndicesDenseShapeMismatch(R[1]);break}case 2:{P=C.getSparseFillEmptyRowsNegativeIndexErrorMessage(R[1],R[2]);break}case 3:P=C.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(R[1],R[2],R[3]);break;default:P=""}if(t.disposeData(k.dataId),P)throw t.disposeData(f.dataId),t.disposeData(g.dataId),t.disposeData(x.dataId),t.disposeData(b.dataId),new Error(P);let _=f,$=g;return E!==c[0]&&(_=al({inputs:{x:f},attrs:{begin:0,size:[E,l]},backend:t}),$=al({inputs:{x:g},attrs:{begin:0,size:E},backend:t}),t.disposeData(f.dataId),t.disposeData(g.dataId)),[_,$,x,b]}var bfe={kernelName:Xp,backendName:"wasm",setupFunc:Afe,kernelFunc:xfe},_C;function vfe(e){_C=e.wasm.cwrap(Oc,null,["number","number","number","number","number","number","number"])}function wfe(e){let{backend:t,inputs:n}=e,{inputIndices:s,inputShape:r,newShape:a}=n;if(s.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape
+    `}};function Fce(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,segmentIds:a}=t,{numSegments:o}=s,i=r.shape.length,l=[],u=0,c=C.getAxesPermutation([u],i),p=r;c!=null&&(p=ts({inputs:{x:r},backend:n,attrs:{perm:c}}),l.push(p),u=C.getInnerMostAxes(1,i)[0]);let d=C.segment_util.computeOutShape(p.shape,u,o),h=v.sizeFromShape([p.shape[u]]),f=be({inputs:{x:p},backend:n,attrs:{shape:[-1,h]}});l.push(f);let m=nh(r.dtype),g=(b,w,k,S,E)=>{let R=b.shape[0],P=b.shape[1],_=C.segment_util.segOpComputeOptimalWindowSize(P,E),$={windowSize:_,inSize:P,batchSize:R,numSegments:E},T=new Pce($,w),F=n.compileAndRun(T,[b,k],S);if(l.push(F),F.shape[1]===E)return F;let G=F9({backend:n,attrs:{start:0,stop:E,step:1,dtype:"float32"}}),q=M9({inputs:{x:G},backend:n,attrs:{reps:[P/_]}});return l.push(G),l.push(q),g(F,w,q,S,E)},y=g(f,"unsortedSegmentSum",a,m,o),x=be({inputs:{x:y},backend:n,attrs:{shape:d}}),A=x;if(c!=null){l.push(x);let b=C.getUndoAxesPermutation(c);A=ts({inputs:{x:A},backend:n,attrs:{perm:b}})}return l.forEach(b=>n.disposeIntermediateTensorInfo(b)),A}var Oce={kernelName:Qp,backendName:"webgl",kernelFunc:Fce},Mce=[zne,Bne,Une,jne,Xne,Yne,Qne,tse,ase,ise,cse,hse,gse,bse,kse,Sse,Tse,_se,$se,Fse,Lse,jse,Xse,Zse,nre,rre,lre,xne,dre,gre,bre,Cre,Nre,Rre,Dre,Pre,Mre,Bre,Ure,Hre,qre,Kre,Jre,eae,rae,oae,uae,pae,fae,Aae,wae,Cae,Eae,Dae,$ae,Fae,Mae,Lae,Wae,Uae,qae,Zae,Qae,toe,roe,ioe,doe,moe,Ane,yoe,fre,boe,koe,Coe,vne,Roe,Poe,Ooe,Boe,Uoe,qoe,Zoe,eie,rie,iie,uie,hie,mie,yie,vie,kie,Sie,Tie,Eie,$ie,Mie,Wie,Kie,Cne,Qie,nle,ale,lle,Jse,dle,hle,mle,Ale,wle,kne,Ile,Sle,Qse,Hie,Nle,Dle,Ole,Nne,Ble,Ule,qle,Zle,eue,nue,aue,lue,cue,hue,gue,xue,kue,Cue,Eue,Due,Gse,qie,Fue,Mue,Lue,Wue,Uue,Hue,que,Kue,Yue,ece,nce,rce,ice,uce,dce,hce,jie,Fne,gce,xce,wce,Cce,Ece,One,_ce,$ce,Oce,ple];for(let e of Mce)cr(e);var Ht;(function(e){e[e.float32=0]="float32",e[e.int32=1]="int32",e[e.bool=2]="bool",e[e.string=3]="string",e[e.complex64=4]="complex64"})(Ht||(Ht={}));var Pp;(function(e){e[e.linear=0]="linear",e[e.relu=1]="relu",e[e.relu6=2]="relu6",e[e.prelu=3]="prelu",e[e.leakyrelu=4]="leakyrelu",e[e.sigmoid=5]="sigmoid",e[e.elu=6]="elu"})(Pp||(Pp={}));var z9;function zce(e){z9=e.wasm.cwrap(Ya,null,["number","array","number","number","array","number","number","number","number","number","number","number","number"])}function Lce(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t;if(r.dtype!=="float32"||a.dtype!=="float32")throw new Error("_FusedMatMul for non non-float32 tensors not yet supported.");let{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=s,d=n.dataIdMap.get(r.dataId).id,h=n.dataIdMap.get(a.dataId).id,f=0;if(o!=null){let E=n.dataIdMap.get(o.dataId);if(E.shape.length!==1)throw new Error(`_FusedMatMul only supports rank-1 bias but got rank ${E.shape.length}.`);f=E.id}let m=i==null?0:n.dataIdMap.get(i.dataId).id,g=Pp[c];if(g==null)throw new Error(`${c} activation not yet supported for FusedConv2D in the wasm backend.`);let y=l?r.shape[2]:r.shape[1],x=u?a.shape[1]:a.shape[2],A=ql.assertAndGetBroadcastShape(r.shape.slice(0,-2),a.shape.slice(0,-2)),b=n.makeOutput([...A,y,x],r.dtype),w=n.dataIdMap.get(b.dataId).id,k=new Uint8Array(new Int32Array(r.shape).buffer),S=new Uint8Array(new Int32Array(a.shape).buffer);return z9(d,k,r.shape.length,h,S,a.shape.length,l,u,g,f,m,p||0,w),b}var Bce={kernelName:Ya,backendName:"wasm",setupFunc:zce,kernelFunc:Lce};function In(e,t){let n;function s(a){n=a.wasm.cwrap(e,null,["number","number","number"])}function r(a){let{backend:o,inputs:{x:i}}=a,l=o.dataIdMap.get(i.dataId).id,u=o.makeOutput(i.shape,t||i.dtype),c=o.dataIdMap.get(u.dataId).id;return v.sizeFromShape(u.shape)===0||n(l,Ht[i.dtype],c),u}return{kernelName:e,backendName:"wasm",setupFunc:s,kernelFunc:r}}var Wce=In(ol);function _n(e,t,n){let s;function r(o){s=o.wasm.cwrap(e,null,["number","array","number","number","array","number","number","number"])}function a(o){let{backend:i,inputs:l}=o,{a:u,b:c}=l,p=i.dataIdMap.get(u.dataId).id,d=i.dataIdMap.get(c.dataId).id,h=n!=null?n:u.dtype,f=C.assertAndGetBroadcastShape(u.shape,c.shape),m=i.makeOutput(f,h);if(v.sizeFromShape(f)===0)return m;let g=new Uint8Array(new Int32Array(u.shape).buffer),y=new Uint8Array(new Int32Array(c.shape).buffer),x=i.dataIdMap.get(m.dataId).id;return(()=>s(p,g,u.shape.length,d,y,c.shape.length,Ht[u.dtype],x))(),m}return{kernelName:e,backendName:"wasm",setupFunc:r,kernelFunc:a}}var Vce=!0,Uce=_n(Aa,Vce),L9;function Gce(e){L9=e.wasm.cwrap(co,null,["array","number","number","number"])}function Hce(e){let{inputs:t,backend:n}=e,s=n.makeOutput(t[0].shape,t[0].dtype);if(v.sizeFromShape(s.shape)===0)return s;let r=t.map(i=>n.dataIdMap.get(i.dataId).id),a=new Uint8Array(new Int32Array(r).buffer),o=n.dataIdMap.get(s.dataId).id;return L9(a,r.length,Ht[s.dtype],o),s}var jce={kernelName:co,backendName:"wasm",setupFunc:Gce,kernelFunc:Hce};function S2(e){let{inputs:{x:t},backend:n}=e,s=n.makeOutput(t.shape,t.dtype),r=n.typedArrayFromHeap(t);return n.typedArrayFromHeap(s).set(r),s}var qce={kernelName:Ro,backendName:"wasm",kernelFunc:S2},B9;function Xce(e){B9=e.wasm.cwrap(Gr,null,["number","array","number","number","number","array","number"])}function io(e){let{inputs:t,backend:n,attrs:s}=e,[r,a]=Zce(t.x.shape,s.perm),o=!0;for(let f=0;f<a.length;f++)a[f]!==f&&(o=!1);let i=Kce(t.x.shape,s.perm),l={dataId:t.x.dataId,shape:r,dtype:t.x.dtype};if(o){let f=S2({inputs:t,backend:n});return f.shape=i,f}let u=n.makeOutput(i,l.dtype),c=n.dataIdMap.get(l.dataId).id,p=n.dataIdMap.get(u.dataId).id,d=new Uint8Array(new Int32Array(a).buffer),h=new Uint8Array(new Int32Array(l.shape).buffer);return B9(c,h,l.shape.length,Ht[l.dtype],p,d,a.length),u}function Kce(e,t){let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];return n}function Zce(e,t){let n=[],s=[];for(let r=0;r<e.length;++r)e[r]!==1&&n.push(e[r]),e[t[r]]!==1&&s.push(t[r]);for(let r=0;r<s.length;++r){let a=-1;for(let o=0;o<s.length;++o)s[o]>=r&&(a===-1||s[a]>s[o])&&(a=o);s[a]=r}return[n,s]}var Yce={kernelName:Gr,backendName:"wasm",kernelFunc:io,setupFunc:Xce};function pi(e,t,n){let s=e.shape,r=e.shape.length,a=v.parseAxisParam(t,s),o=a,i=C.getAxesPermutation(o,r),l=null,u=!1;if(i!=null){let c=new Array(r);for(let h=0;h<c.length;h++)c[h]=s[i[h]];o=C.getInnerMostAxes(o.length,r),l=io({inputs:{x:e},attrs:{perm:i},backend:n});let p=n.dataIdMap.get(e.dataId).id;n.dataIdMap.get(l.dataId).id!==p&&(u=!0)}return{transposed:l,originalAxes:a,axes:o,inputWasTransposed:u}}var W9;function Jce(e){W9=e.wasm.cwrap(hc,null,["number, number, number"])}function Qce(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=pi(o,r,t);if(h){let A=t.dataIdMap.get(c.dataId).id;u=c,l=A}let f=u.shape.length;C.assertAxesAreInnerMostDims("all",p,f);let[m,g]=C.computeOutAndReduceShapes(u.shape,p),y=v.sizeFromShape(g),x=t.makeOutput(m,o.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;W9(l,y,A)}if(h&&t.disposeData(c.dataId),a){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var ede={kernelName:hc,backendName:"wasm",setupFunc:Jce,kernelFunc:Qce},V9;function tde(e){V9=e.wasm.cwrap(fc,null,["number, number, number"])}function nde(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=pi(o,r,t);if(h){let A=t.dataIdMap.get(c.dataId).id;u=c,l=A}let f=u.shape.length;C.assertAxesAreInnerMostDims("any",p,f);let[m,g]=C.computeOutAndReduceShapes(u.shape,p),y=v.sizeFromShape(g),x=t.makeOutput(m,o.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;V9(l,y,A)}if(h&&t.disposeData(c.dataId),a){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var sde={kernelName:fc,backendName:"wasm",setupFunc:tde,kernelFunc:nde},U9;function rde(e){U9=e.wasm.cwrap(po,null,["number","number","number","number","number"])}function ade(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r}=s,{x:a}=n,o=t.dataIdMap.get(a.dataId).id,i=o,l=a,{transposed:u,axes:c,inputWasTransposed:p}=pi(a,r,t);if(p){let y=t.dataIdMap.get(u.dataId).id;y!==o&&(l=u,i=y)}let d=l.shape.slice(0,-1),h=t.makeOutput(d,"int32"),f=t.dataIdMap.get(h.dataId).id,m=v.sizeFromShape(h.shape),g=l.shape[c[0]];return U9(i,Ht[l.dtype],m,g,f),p&&t.disposeData(u.dataId),h}var ode={kernelName:po,backendName:"wasm",kernelFunc:ade,setupFunc:rde},G9;function ide(e){G9=e.wasm.cwrap(ho,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function lde(e){let{inputs:t,attrs:n,backend:s}=e,r=t.x,a=s.dataIdMap.get(r.dataId).id,{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=n,c=C.computePool2DInfo(r.shape,o,i,1,l,u),p=c.filterHeight,d=c.filterWidth,h=c.padInfo.top,f=c.padInfo.right,m=c.padInfo.bottom,g=c.padInfo.left,y=c.strideHeight,x=c.strideWidth,A=c.inChannels;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${c.dataFormat}'. Please use 'channelsLast'.`);if(c.dilationWidth!==1||c.dilationHeight!==1)throw new Error(`was backend only supports average pooling with dilation = [1, 1], got [${c.dilationHeight}, ${c.dilationWidth}].`);let b=s.makeOutput(c.outShape,"float32"),w=s.dataIdMap.get(b.dataId).id;return G9(a,r.shape[0],r.shape[1],r.shape[2],p,d,h,f,m,g,y,x,A,w),b}var ude={kernelName:ho,backendName:"wasm",setupFunc:ide,kernelFunc:lde};function hs(e){let{inputs:t,attrs:n}=e,{x:s}=t,{shape:r}=n,a=v.sizeFromShape(s.shape),o=v.inferFromImplicitShape(r,a);return v.assert(a===v.sizeFromShape(o),()=>`new shape: ${o}, old shape: ${s.shape}. New shape and old shape must have the same number of elements.`),e.backend.incRef(s.dataId),{dataId:s.dataId,shape:o,dtype:s.dtype}}var cde={kernelName:Rl,backendName:"wasm",kernelFunc:hs},H9;function dde(e){H9=e.wasm.cwrap(fo,null,["number","array","number","number","array","number","number","number","number"])}function pde(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;if(r.dtype!=="float32"||a.dtype!=="float32")throw new Error("BatchMatMul for non non-float32 tensors not yet supported.");let l=r.shape.length,u=a.shape.length,c=o?r.shape[l-2]:r.shape[l-1],p=i?a.shape[u-1]:a.shape[u-2],d=o?r.shape[l-1]:r.shape[l-2],h=i?a.shape[u-2]:a.shape[u-1],f=r.shape.slice(0,-2),m=a.shape.slice(0,-2),g=v.sizeFromShape(f),y=v.sizeFromShape(m),A=ql.assertAndGetBroadcastShape(r.shape.slice(0,-2),a.shape.slice(0,-2)).concat([d,h]);v.assert(c===p,()=>`Error in matMul: inner shapes (${c}) and (${p}) of Tensors with shapes ${r.shape} and ${a.shape} and transposeA=${o} and transposeB=${i} must match.`);let b=o?[g,c,d]:[g,d,c],w=i?[y,h,p]:[y,p,h],k=hs({inputs:{x:r},backend:n,attrs:{shape:b}}),S=hs({inputs:{x:a},backend:n,attrs:{shape:w}}),E=n.dataIdMap.get(k.dataId).id,R=n.dataIdMap.get(S.dataId).id,P=o?k.shape[2]:k.shape[1],_=i?S.shape[1]:S.shape[2],$=Math.max(g,y),T=n.makeOutput([$,P,_],k.dtype),F=n.dataIdMap.get(T.dataId).id,G=new Uint8Array(new Int32Array(k.shape).buffer),q=new Uint8Array(new Int32Array(S.shape).buffer);return H9(E,G,k.shape.length,R,q,S.shape.length,o,i,F),n.disposeData(k.dataId),n.disposeData(S.dataId),T.shape=A,T}var hde={kernelName:fo,backendName:"wasm",setupFunc:dde,kernelFunc:pde};function rl(e){let{inputs:{x:t},attrs:{begin:n,size:s},backend:r}=e,[a,o]=Ut.parseSliceParams(t,n,s),i=Ut.isSliceContinous(t.shape,a,o),l=r.readSync(t.dataId),u=r.makeOutput(o,t.dtype),c=v.computeStrides(t.shape),p=r.dataIdMap.get(u.dataId);if(i){let f=Ut.computeFlatOffset(a,c);return t.dtype==="string"?p.stringBytes=l.slice(f,f+v.sizeFromShape(o)):r.typedArrayFromHeap(u).set(l.subarray(f,f+v.sizeFromShape(o))),u}if(t.dtype==="string"){let f=Rm(l,a,o,t.shape,t.dtype);return p.stringBytes=f,u}let d=r.typedArrayFromHeap(u),h=t.shape.length;if(h===2)fde(l,c[0],d,a,o);else if(h===3)mde(l,c[0],c[1],d,a,o);else if(h===4)gde(l,c[0],c[1],c[2],d,a,o);else{let f=Rm(l,a,o,t.shape,t.dtype);d.set(f)}return u}function fde(e,t,n,s,r){let a=0,o=s[0],i=s[1],l=o+r[0];for(let u=o;u<l;u++){let c=u*t+i;n.set(e.subarray(c,c+r[1]),a),a+=r[1]}}function mde(e,t,n,s,r,a){let o=0,i=r[0],l=r[1],u=r[2],c=i+a[0],p=l+a[1];for(let d=i;d<c;d++)for(let h=l;h<p;h++){let f=d*t+h*n+u;s.set(e.subarray(f,f+a[2]),o),o+=a[2]}}function gde(e,t,n,s,r,a,o){let i=0,l=a[0],u=a[1],c=a[2],p=l+o[0],d=u+o[1],h=c+o[2],f=a[3];for(let m=l;m<p;m++)for(let g=u;g<d;g++)for(let y=c;y<h;y++){let x=m*t+g*n+y*s+f;r.set(e.subarray(x,x+o[3]),i),i+=o[3]}}var yde={kernelName:Fl,backendName:"wasm",kernelFunc:rl};function Ade(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s,i=a.reduce((y,x)=>y*x),l=C.getReshaped(r.shape,a,i),u=C.getPermuted(l.length,a.length),c=C.getReshapedPermuted(r.shape,a,i),p=C.getSliceBeginCoords(o,a.length),d=C.getSliceSize(c,o,a.length),h=hs({inputs:{x:r},backend:n,attrs:{shape:l}}),f=io({inputs:{x:h},backend:n,attrs:{perm:u}}),m=hs({inputs:{x:f},backend:n,attrs:{shape:c}}),g=rl({inputs:{x:m},backend:n,attrs:{begin:p,size:d}});return n.disposeData(h.dataId),n.disposeData(f.dataId),n.disposeData(h.dataId),g}var xde={kernelName:il,backendName:"wasm",kernelFunc:Ade};function ud(e){let{inputs:{x:t},attrs:{dtype:n},backend:s}=e,r=s.makeOutput(t.shape,n),a=s.typedArrayFromHeap(t);return s.typedArrayFromHeap(r).set(a),r}var bde={kernelName:mo,backendName:"wasm",kernelFunc:ud},vde=In(go),j9;function wde(e){j9=e.wasm.cwrap(xa,null,["number","number","number","number"])}function kde(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i=n.dataIdMap.get(r.dataId).id,l=n.makeOutput(r.shape,r.dtype),u=n.dataIdMap.get(l.dataId).id;return j9(i,a,o,u),l}var Ide={kernelName:xa,backendName:"wasm",setupFunc:wde,kernelFunc:kde};function q9(e){let{inputs:t,backend:n}=e,s=v.parseAxisParam(e.attrs.axis,t[0].shape)[0],r=C.computeOutShape(t.map(h=>h.shape),s),a=t.filter(h=>v.sizeFromShape(h.shape)>0);if(a.length===1)return S2({inputs:{x:a[0]},backend:n});let o=n.makeOutput(r,t[0].dtype);if(v.sizeFromShape(r)===0)return o;let i=a.map(h=>h.shape);if(C.assertParamsConsistent(i,s),a[0].dtype==="string"){let h=a.map(A=>{let b=v.sizeFromShape(A.shape.slice(s));return hs({inputs:{x:A},backend:n,attrs:{shape:[-1,b]}})}),f=h.map(A=>({vals:n.readSync(A.dataId),shape:A.shape}));r=C.computeOutShape(h.map(A=>A.shape),1);let m=h[0].shape[0]===1,g=Nx(f,r,t[0].dtype,m),y=C.computeOutShape(a.map(A=>A.shape),s);o.shape=y;let x=n.dataIdMap.get(o.dataId);return x.stringBytes=C.fromStringArrayToUint8(g),h.forEach(A=>n.disposeData(A.dataId)),o}let l=v.sizeFromShape(a[0].shape.slice(0,s)),u=0,c=a.map(h=>{let f=v.sizeFromShape(h.shape.slice(s));return u+=f,f}),p=a.map(h=>n.typedArrayFromHeap(h)),d=n.typedArrayFromHeap(o);for(let h=0;h<l;h++){let f=h*u;for(let m=0;m<p.length;m++){let g=c[m],y=h*g,x=p[m].subarray(y,y+g);d.set(x,f),f+=g}}return o}var Sde={kernelName:ll,backendName:"wasm",kernelFunc:q9},X9;function Cde(e){X9=e.wasm.cwrap(yo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Tde(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a}=t,o=s.dataIdMap.get(r.dataId).id,i=s.dataIdMap.get(a.dataId).id,{strides:l,dilations:u,pad:c,dimRoundingMode:p,dataFormat:d}=n,h=C.convertConv2DDataFormat(d),f=C.computeConv2DInfo(r.shape,a.shape,l,u,c,p,!1,h),m=f.filterHeight,g=f.filterWidth,y=f.padInfo.top,x=f.padInfo.right,A=f.padInfo.bottom,b=f.padInfo.left,w=f.dilationHeight,k=f.dilationWidth,S=f.strideHeight,E=f.strideWidth,R=f.inChannels,P=f.outChannels,_=f.padInfo.type==="SAME"?1:0;if(f.dataFormat!=="channelsLast")throw new Error(`wasm backend Conv2D does not support dataFormat:'${f.dataFormat}'. Please use 'channelsLast'.`);let $=s.makeOutput(f.outShape,"float32"),T=s.dataIdMap.get($.dataId).id;return X9(o,r.shape[0],r.shape[1],r.shape[2],i,m,g,y,x,A,b,_,w,k,S,E,R,P,T),$}var Nde={kernelName:yo,backendName:"wasm",setupFunc:Cde,kernelFunc:Tde},K9;function Ede(e){K9=e.wasm.cwrap(Ao,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function Rde(e){let{backend:t,inputs:n,attrs:s}=e,{dy:r,filter:a}=n,{strides:o,pad:i,dataFormat:l,dimRoundingMode:u,inputShape:c}=s,p=1,d=C.convertConv2DDataFormat(l),h=C.computeConv2DInfo(c,a.shape,o,p,i,u,!1,d),{batchSize:f,filterHeight:m,filterWidth:g,inChannels:y,inHeight:x,inWidth:A,outChannels:b,outHeight:w,outWidth:k,strideHeight:S,strideWidth:E}=h,R=m-1-h.padInfo.top,P=g-1-h.padInfo.left,_=h.dataFormat==="channelsLast",$=v.computeStrides(h.inShape),T=v.computeStrides(r.shape),[F,G,q]=v.computeStrides(a.shape),z=$[0],Z=_?$[1]:$[2],B=_?$[2]:1,ee=_?1:$[1],Q=T[0],oe=_?T[1]:T[2],Y=_?T[2]:1,ae=_?1:T[1],le=t.makeOutput(h.inShape,"float32"),ye=t.dataIdMap.get(le.dataId).id,we=t.dataIdMap.get(r.dataId).id,Re=t.dataIdMap.get(a.dataId).id;return K9(we,Re,f,m,g,x,A,y,w,k,b,S,E,R,P,F,G,q,z,Z,B,ee,Q,oe,Y,ae,ye),le}var _de={kernelName:Ao,backendName:"wasm",setupFunc:Ede,kernelFunc:Rde},Dde=In(xo),$de=In(bo),ly;(function(e){e[e.bilinear=0]="bilinear",e[e.nearest=1]="nearest"})(ly||(ly={}));var Z9;function Pde(e){Z9=e.wasm.cwrap(cl,null,["number","number","number","number","array","number","number","number","number","number"])}function Fde(e){let{backend:t,inputs:n,attrs:s}=e,{method:r,extrapolationValue:a,cropSize:o}=s,{image:i,boxes:l,boxInd:u}=n,c=l.shape[0],[p,d]=o,h=[c,p,d,i.shape[3]],f=t.dataIdMap.get(i.dataId),m;i.dtype!=="float32"&&(m=ud({backend:t,inputs:{x:i},attrs:{dtype:"float32"}}),f=t.dataIdMap.get(m.dataId));let g=f.id,y=t.dataIdMap.get(l.dataId).id,x=t.dataIdMap.get(u.dataId).id,A=t.makeOutput(h,"float32"),b=t.dataIdMap.get(A.dataId).id,w=new Uint8Array(new Int32Array(i.shape).buffer);return Z9(g,y,x,c,w,p,d,ly[r],a,b),m!=null&&t.disposeData(m.dataId),A}var Ode={kernelName:cl,backendName:"wasm",setupFunc:Pde,kernelFunc:Fde},Y9;function Mde(e){Y9=e.wasm.cwrap(ul,null,["number","number","number","number","number","number"])}function zde(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumprod does not support ${r.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([a],l),c=r;u!==null&&(c=io({inputs:{x:r},attrs:{perm:u},backend:n}));let p=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumprod",[p],l);let d=n.makeOutput(c.shape,c.dtype),h=c.shape[p],f=n.dataIdMap.get(c.dataId).id,m=n.dataIdMap.get(d.dataId).id;Y9(f,o?1:0,i?1:0,h,m,Ht[r.dtype]);let g=d;if(u!==null){let y=C.getUndoAxesPermutation(u);g=io({inputs:{x:d},attrs:{perm:y},backend:n}),n.disposeData(c.dataId),n.disposeData(d.dataId)}return g}var Lde={kernelName:ul,backendName:"wasm",setupFunc:Mde,kernelFunc:zde},J9;function Bde(e){J9=e.wasm.cwrap(vo,null,["number","number","number","number","number","number"])}function Wde(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s,l=r.shape.length;v.assert(r.dtype==="float32"||r.dtype==="int32",()=>`cumsum does not support ${r.dtype} tensors in the WASM backend`);let u=C.getAxesPermutation([a],l),c=r;u!==null&&(c=io({inputs:{x:r},attrs:{perm:u},backend:n}));let p=C.getInnerMostAxes(1,l)[0];C.assertAxesAreInnerMostDims("cumsum",[p],l);let d=n.makeOutput(c.shape,c.dtype),h=c.shape[p],f=n.dataIdMap.get(c.dataId).id,m=n.dataIdMap.get(d.dataId).id;J9(f,o?1:0,i?1:0,h,m,Ht[r.dtype]);let g=d;if(u!==null){let y=C.getUndoAxesPermutation(u);g=io({inputs:{x:d},attrs:{perm:y},backend:n}),n.disposeData(c.dataId),n.disposeData(d.dataId)}return g}var Vde={kernelName:vo,backendName:"wasm",setupFunc:Bde,kernelFunc:Wde},Q9;function Ude(e){Q9=e.wasm.cwrap(dl,null,["number","number","number","array","number","array","array","number","number"])}function Gde(e){let{backend:t,inputs:n,attrs:s}=e,{x:r}=n,{blockSize:a,dataFormat:o}=s,i=r.shape[0],l=o==="NHWC"?r.shape[1]:r.shape[2],u=o==="NHWC"?r.shape[2]:r.shape[3],c=o==="NHWC"?r.shape[3]:r.shape[1],p=l*a,d=u*a,h=c/(a*a),f=o==="NHWC"?[i,p,d,h]:[i,h,p,d],m=t.makeOutput(f,"float32"),y=t.dataIdMap.get(r.dataId).id,x=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),A=new Uint8Array(new Int32Array(f).buffer),b=new Uint8Array(new Int32Array(v.computeStrides(f)).buffer),w=t.dataIdMap.get(m.dataId).id;return Q9(y,a,o==="NHWC"?1:0,x,r.shape.length-1,A,b,f.length,w),m}var Hde={kernelName:dl,backendName:"wasm",setupFunc:Ude,kernelFunc:Gde},eC;function jde(e){eC=e.wasm.cwrap(wo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function qde(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a}=t,o=s.dataIdMap.get(r.dataId).id,i=s.dataIdMap.get(a.dataId).id,{strides:l,dilations:u,pad:c,dimRoundingMode:p}=n,d=u==null?[1,1]:u,h=C.computeConv2DInfo(r.shape,a.shape,l,d,c,p,!0),f=h.filterHeight,m=h.filterWidth,g=h.padInfo.top,y=h.padInfo.right,x=h.padInfo.bottom,A=h.padInfo.left,b=h.dilationHeight,w=h.dilationWidth,k=h.strideHeight,S=h.strideWidth,E=h.inChannels,R=h.outChannels,P=h.padInfo.type==="SAME"?1:0;if(h.dataFormat!=="channelsLast")throw new Error(`wasm backend DepthwiseConv2dNative does not support dataFormat:'${h.dataFormat}'. Please use 'channelsLast'.`);let _=s.makeOutput(h.outShape,"float32"),$=s.dataIdMap.get(_.dataId).id;return eC(o,r.shape[0],r.shape[1],r.shape[2],i,f,m,g,y,x,A,P,b,w,k,S,E,R,$),_}var Xde={kernelName:wo,backendName:"wasm",setupFunc:jde,kernelFunc:qde},Kde=In(Io),Zde=!1,Yde=_n(pl,Zde,"bool"),Jde=In(So,"float32");function uy(e){let{inputs:t,attrs:n,backend:s}=e,{input:r}=t,{dim:a}=n,o=r.shape.length,i=r.shape.slice(),l=a;return a<0&&(v.assert(-(o+1)<=a,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+a+1),i.splice(l,0,1),hs({inputs:{x:r},backend:s,attrs:{shape:i}})}var Qde={kernelName:hl,backendName:"wasm",kernelFunc:uy};function tC(e){let{attrs:{shape:t,value:n,dtype:s},backend:r}=e,a=r.makeOutput(t,s);return r.typedArrayFromHeap(a).fill(n),a}var epe={kernelName:wc,backendName:"wasm",kernelFunc:tC},nC;function tpe(e){nC=e.wasm.cwrap(ml,null,["number","number","number","number","number","number"])}function npe(e){let{inputs:t,backend:n}=e,{image:s}=t,r=n.makeOutput(s.shape,s.dtype),a=n.dataIdMap.get(s.dataId).id,o=n.dataIdMap.get(r.dataId).id,[i,l,u,c]=s.shape;return nC(a,i,l,u,c,o),r}var spe={kernelName:ml,backendName:"wasm",kernelFunc:npe,setupFunc:tpe},rpe=In(Co),ape=!1,ope=_n(To,ape),sC;function ipe(e){sC=e.wasm.cwrap(No,null,["number","number","number","number","number","number","number"])}function lpe(e){let{backend:t,inputs:n,attrs:s}=e,{varianceEpsilon:r}=s,{x:a,mean:o,variance:i,offset:l,scale:u}=n,c=t.dataIdMap.get(a.dataId).id,p=t.dataIdMap.get(o.dataId).id,d=t.dataIdMap.get(i.dataId).id,h=l!=null?t.dataIdMap.get(l.dataId).id:0,f=u!=null?t.dataIdMap.get(u.dataId).id:0,m=t.makeOutput(a.shape,a.dtype);if(v.sizeFromShape(a.shape)===0)return m;let g=t.dataIdMap.get(m.dataId).id;return sC(c,p,d,h,f,r,g),m}var upe={kernelName:No,backendName:"wasm",setupFunc:ipe,kernelFunc:lpe},rC;function cpe(e){rC=e.wasm.cwrap(Ja,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function dpe(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dataFormat:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=n,m=C.computeConv2DInfo(r.shape,a.shape,l,c,u,d),g=Pp[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedConv2D in the wasm backend.`);let y=s.dataIdMap.get(r.dataId).id,x=s.dataIdMap.get(a.dataId).id,A=m.outChannels,b=0;if(o!=null){let Y=s.dataIdMap.get(o.dataId);if(Y.shape.length!==1)throw new Error(`FusedConv2D only supports rank-1 bias but got rank ${Y.shape.length}.`);if(Y.shape[0]!==A)throw new Error(`FusedConv2D bias shape (${Y.shape}) does not match the number of output channels (${A})`);b=Y.id}let w=m.filterHeight,k=m.filterWidth,S=m.padInfo.top,E=m.padInfo.right,R=m.padInfo.bottom,P=m.padInfo.left,_=m.dilationHeight,$=m.dilationWidth,T=m.strideHeight,F=m.strideWidth,G=m.inChannels,q=m.padInfo.type==="SAME"?1:0,z=m.batchSize,Z=m.inHeight,B=m.inWidth;if(p!=="NHWC")throw new Error(`wasm backend FusedConv2D does not support dataFormat:'${p}'. Please use 'NHWC'.`);let ee=s.makeOutput(m.outShape,"float32"),Q=s.dataIdMap.get(ee.dataId).id,oe=i==null?0:s.dataIdMap.get(i.dataId).id;return rC(y,z,Z,B,x,w,k,b,S,E,R,P,q,_,$,T,F,G,A,g,oe,f||0,Q),ee}var ppe={kernelName:Ja,backendName:"wasm",setupFunc:cpe,kernelFunc:dpe},aC;function hpe(e){aC=e.wasm.cwrap(Qa,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function fpe(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dataFormat:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=n,m=C.computeConv2DInfo(r.shape,a.shape,l,c,u,d,!0),g=Pp[h];if(g==null)throw new Error(`${h} activation not yet supported for FusedDepthwiseConv2D in the wasm backend.`);let y=s.dataIdMap.get(r.dataId).id,x=s.dataIdMap.get(a.dataId).id,A=m.outChannels,b=0;if(o!=null){let Y=s.dataIdMap.get(o.dataId);if(Y.shape.length!==1)throw new Error(`FusedDepthwiseConv2D only supports rank-1 bias but got rank ${Y.shape.length}.`);if(Y.shape[0]!==A)throw new Error(`FusedDepthwiseConv2D bias shape (${Y.shape}) does not match the number of output channels (${A})`);b=Y.id}let w=m.filterHeight,k=m.filterWidth,S=m.padInfo.top,E=m.padInfo.right,R=m.padInfo.bottom,P=m.padInfo.left,_=m.dilationHeight,$=m.dilationWidth,T=m.strideHeight,F=m.strideWidth,G=m.inChannels,q=m.padInfo.type==="SAME"?1:0,z=m.batchSize,Z=m.inHeight,B=m.inWidth;if(p!=="NHWC")throw new Error(`wasm backend FusedDepthwiseConv2D does not support dataFormat:'${p}'. Please use 'NHWC'.`);let ee=s.makeOutput(m.outShape,"float32"),Q=s.dataIdMap.get(ee.dataId).id,oe=i==null?0:s.dataIdMap.get(i.dataId).id;return aC(y,z,Z,B,x,w,k,b,S,E,R,P,q,_,$,T,F,G,A,g,oe,f||0,Q),ee}var mpe={kernelName:Qa,backendName:"wasm",setupFunc:hpe,kernelFunc:fpe},oC;function gpe(e){oC=e.wasm.cwrap(yl,null,["number","number","number","number","number","number","array","number"])}function ype(e){let{backend:t,inputs:n}=e,{params:s,indices:r}=n,[a,o,i,l]=zy.prepareAndValidate(s,r),u=t.makeOutput(a,s.dtype);if(o===0)return u;let c=r.shape,p=c[c.length-1],h=t.dataIdMap.get(s.dataId).id,m=t.dataIdMap.get(r.dataId).id,g=new Uint8Array(new Int32Array(l).buffer),y=t.dataIdMap.get(u.dataId).id;return oC(h,Ht[s.dtype],m,o,p,i,g,y),u}var Ape={kernelName:yl,backendName:"wasm",setupFunc:gpe,kernelFunc:ype},iC;function xpe(e){iC=e.wasm.cwrap("Gather",null,["number","number","array","number","number","number","array","number"])}function bpe(e){let{backend:t,inputs:n,attrs:s}=e,{x:r,indices:a}=n,{axis:o,batchDims:i}=s,l=v.parseAxisParam(o,r.shape)[0],u=t.readSync(a.dataId),c=r.shape[l];for(let R=0;R<u.length;++R){let P=u[R];v.assert(P<=c-1&&P>=0,()=>`GatherV2: the index value ${P} is not in [0, ${c-1}]`)}let p=C.segment_util.collectGatherOpShapeInfo(r,a,l,i),d=hs({inputs:{x:r},attrs:{shape:[p.batchSize,p.outerSize,p.dimSize,p.sliceSize]},backend:t}),h=v.sizeFromShape(a.shape),f=hs({inputs:{x:a},attrs:{shape:[p.batchSize,h/p.batchSize]},backend:t}),m=[p.batchSize,p.outerSize,h/p.batchSize,p.sliceSize],g=t.makeOutput(m,r.dtype);if(v.sizeFromShape(r.shape)===0)return g;let y=d.shape.length-1,A=t.dataIdMap.get(d.dataId).id,w=t.dataIdMap.get(f.dataId).id,k=t.dataIdMap.get(g.dataId).id,S=new Uint8Array(new Int32Array(v.computeStrides(d.shape)).buffer),E=new Uint8Array(new Int32Array(v.computeStrides(m)).buffer);return iC(A,Ht[r.dtype],S,y,w,p.batchSize,E,k),t.disposeData(d.dataId),t.disposeData(f.dataId),g.shape=p.outputShape,g}var vpe={kernelName:gl,backendName:"wasm",setupFunc:xpe,kernelFunc:bpe},wpe=!1,kpe=_n(Al,wpe,"bool"),Ipe=!1,Spe=_n(Eo,Ipe,"bool"),lC;function Cpe(e){lC=e.wasm.cwrap(_o,null,["number","number","number","number"])}function Tpe(e){let{inputs:{x:t},attrs:{alpha:n},backend:s}=e,r=s.dataIdMap.get(t.dataId).id,a=s.makeOutput(t.shape,"float32");if(v.sizeFromShape(t.shape)!==0){let o=s.dataIdMap.get(a.dataId).id;lC(r,Ht[t.dtype],n,o)}return a}var Npe={kernelName:_o,backendName:"wasm",setupFunc:Cpe,kernelFunc:Tpe},Epe=!1,Rpe=_n(xl,Epe,"bool"),_pe=!1,Dpe=_n(bl,_pe,"bool"),$pe=In(Do),Ppe=!1,Fpe=_n(vl,Ppe,"bool"),Ope=In(wl),Mpe=!1,zpe=_n(Tc,Mpe,"bool"),Lpe=!1,Bpe=_n(d6,Lpe,"bool"),uC;function Wpe(e){uC=e.wasm.cwrap($o,null,["number","number","number","number"])}function Vpe(e){let{backend:t,inputs:n,attrs:s}=e,{reductionIndices:r,keepDims:a}=s,{x:o}=n,l=t.dataIdMap.get(o.dataId).id,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=pi(o,r,t);if(h){let A=t.dataIdMap.get(c.dataId).id;u=c,l=A}let f=u.shape.length;C.assertAxesAreInnerMostDims("max",p,f);let[m,g]=C.computeOutAndReduceShapes(u.shape,p),y=v.sizeFromShape(g),x=t.makeOutput(m,o.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;uC(l,Ht[o.dtype],y,A)}if(h&&t.disposeData(c.dataId),a){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var Upe={kernelName:$o,backendName:"wasm",setupFunc:Wpe,kernelFunc:Vpe},Gpe=!1,Hpe=_n(Po,Gpe),cC;function jpe(e){cC=e.wasm.cwrap(Fo,null,["number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number","number"])}function qpe(e){let{inputs:t,attrs:n,backend:s}=e,r=t.x,a=s.dataIdMap.get(r.dataId).id;v.assert(r.dtype==="float32",()=>`Error in MaxPool: only float32 input is supported. Got ${r.dtype}.`);let{filterSize:o,strides:i,pad:l,dimRoundingMode:u}=n,c=C.computePool2DInfo(r.shape,o,i,1,l,u),p=c.filterHeight,d=c.filterWidth,h=c.padInfo.top,f=c.padInfo.right,m=c.padInfo.bottom,g=c.padInfo.left,y=c.dilationHeight,x=c.dilationWidth,A=c.strideHeight,b=c.strideWidth,w=c.inChannels,k=c.outChannels;if(c.dataFormat!=="channelsLast")throw new Error(`wasm backend does not support dataFormat:'${c.dataFormat}'. Please use 'channelsLast'.`);let S=s.makeOutput(c.outShape,"float32"),E=s.dataIdMap.get(S.dataId).id;return cC(a,r.shape[0],r.shape[1],r.shape[2],p,d,h,f,m,g,y,x,A,b,w,k,E),S}var Xpe={kernelName:Fo,backendName:"wasm",setupFunc:jpe,kernelFunc:qpe},dC;function Kpe(e){dC=e.wasm.cwrap(Oo,null,["number, number, number"])}function Zpe(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,i=t.dataIdMap.get(o.dataId).id,l=i,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=pi(o,r,t),f=p;if(h){let b=t.dataIdMap.get(c.dataId).id;b!==i&&(u=c,l=b,f=C.getInnerMostAxes(f.length,u.shape.length))}C.assertAxesAreInnerMostDims("mean",f,u.shape.length);let[m,g]=C.computeOutAndReduceShapes(u.shape,f),y=v.sizeFromShape(g),x=u;u.dtype!=="float32"&&(x=ud({backend:t,inputs:{x:u},attrs:{dtype:"float32"}}),l=t.dataIdMap.get(x.dataId).id);let A=t.makeOutput(m,"float32");if(v.sizeFromShape(u.shape)!==0){let b=t.dataIdMap.get(A.dataId).id;dC(l,y,b)}if(h&&t.disposeData(c.dataId),a){let b=C.expandShapeToKeepDim(A.shape,d);A.shape=b}return u.dtype!=="float32"&&t.disposeData(x.dataId),A}var Ype={kernelName:Oo,backendName:"wasm",setupFunc:Kpe,kernelFunc:Zpe},pC;function Jpe(e){pC=e.wasm.cwrap(Mo,null,["number","number","number","number"])}function Qpe(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,i=t.dataIdMap.get(o.dataId).id,l=i,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=pi(o,r,t);if(h){let A=t.dataIdMap.get(c.dataId).id;A!==i&&(u=c,l=A)}let f=u.shape.length;C.assertAxesAreInnerMostDims("min",p,f);let[m,g]=C.computeOutAndReduceShapes(u.shape,p),y=v.sizeFromShape(g),x=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;pC(l,Ht[o.dtype],y,A)}if(h&&t.disposeData(c.dataId),a){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var ehe={kernelName:Mo,backendName:"wasm",setupFunc:Jpe,kernelFunc:Qpe},the=!1,nhe=_n(zo,the),cy;(function(e){e[e.reflect=0]="reflect",e[e.symmetric=1]="symmetric"})(cy||(cy={}));var hC;function she(e){hC=e.wasm.cwrap(Lo,null,["number","array","number","number","array","array","number","number"])}function rhe(e){let{inputs:{x:t},backend:n,attrs:{paddings:s,mode:r}}=e,a=s.map((f,m)=>f[0]+t.shape[m]+f[1]),o=n.dataIdMap.get(t.dataId).id,i=n.makeOutput(a,t.dtype),l=n.dataIdMap.get(i.dataId).id,u=new Uint8Array(new Int32Array(t.shape).buffer),c=s.map(f=>f[0]),p=s.map(f=>f[1]),d=new Uint8Array(new Int32Array(c).buffer),h=new Uint8Array(new Int32Array(p).buffer);return hC(o,u,t.shape.length,Ht[t.dtype],d,h,cy[r],l),i}var ahe={kernelName:Lo,backendName:"wasm",kernelFunc:rhe,setupFunc:she},ohe=!0,ihe=_n(Bo,ohe),lhe=In(kl);function Qx(e,t){let n=new Int32Array(e.wasm.HEAPU8.buffer,t,4),s=n[0],r=n[1],a=n[2],o=n[3];return e.wasm._free(t),{pSelectedIndices:s,selectedSize:r,pSelectedScores:a,pValidOutputs:o}}var fC;function uhe(e){fC=e.wasm.cwrap(Sl,"number",["number","number","number","number","number"])}function che(e){let{backend:t,inputs:n,attrs:s}=e,{iouThreshold:r,maxOutputSize:a,scoreThreshold:o}=s,{boxes:i,scores:l}=n,u=t.dataIdMap.get(i.dataId).id,c=t.dataIdMap.get(l.dataId).id,p=fC(u,c,a,r,o),{pSelectedIndices:d,selectedSize:h,pSelectedScores:f,pValidOutputs:m}=Qx(t,p);return t.wasm._free(f),t.wasm._free(m),t.makeOutput([h],"int32",d)}var dhe={kernelName:Sl,backendName:"wasm",setupFunc:uhe,kernelFunc:che},mC;function phe(e){mC=e.wasm.cwrap(Ec,"number",["number","number","number","number","number","bool"])}function hhe(e){let{backend:t,inputs:n,attrs:s}=e,{iouThreshold:r,maxOutputSize:a,scoreThreshold:o,padToMaxOutputSize:i}=s,{boxes:l,scores:u}=n,c=t.dataIdMap.get(l.dataId).id,p=t.dataIdMap.get(u.dataId).id,d=mC(c,p,a,r,o,i),{pSelectedIndices:h,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=Qx(t,d);t.wasm._free(m);let y=t.makeOutput([f],"int32",h),x=t.makeOutput([],"int32",g);return[y,x]}var fhe={kernelName:Ec,backendName:"wasm",setupFunc:phe,kernelFunc:hhe},gC;function mhe(e){gC=e.wasm.cwrap(Cl,"number",["number","number","number","number","number","number"])}function ghe(e){let{backend:t,inputs:n,attrs:s}=e,{iouThreshold:r,maxOutputSize:a,scoreThreshold:o,softNmsSigma:i}=s,{boxes:l,scores:u}=n,c=t.dataIdMap.get(l.dataId).id,p=t.dataIdMap.get(u.dataId).id,d=gC(c,p,a,r,o,i),{pSelectedIndices:h,selectedSize:f,pSelectedScores:m,pValidOutputs:g}=Qx(t,d);t.wasm._free(g);let y=t.makeOutput([f],"int32",h),x=t.makeOutput([f],"float32",m);return[y,x]}var yhe={kernelName:Cl,backendName:"wasm",setupFunc:mhe,kernelFunc:ghe},Ahe=!1,xhe=_n(Il,Ahe,"bool"),yC;function bhe(e){yC=e.wasm.cwrap(Nl,null,["number","number","number","number","number"])}function vhe(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r}=t,{depth:a,onValue:o,offValue:i}=s,l=n.makeOutput([...r.shape,a],"int32"),u=n.dataIdMap.get(l.dataId).id,p=n.dataIdMap.get(r.dataId).id;return yC(p,a,o,i,u),l}var whe={kernelName:Nl,backendName:"wasm",setupFunc:bhe,kernelFunc:vhe};function khe(e){let{inputs:{x:t},backend:n}=e,s=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(s).fill(1),s}var Ihe={kernelName:Tl,backendName:"wasm",kernelFunc:khe};function She(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return uy({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let p=uy({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(p),p}),u=q9({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeData(c.dataId)),u}var Che={kernelName:El,backendName:"wasm",kernelFunc:She},AC;function The(e){AC=e.wasm.cwrap(Wo,null,["number","array","number","number","array","array","number","number"])}function Nhe(e){let{inputs:{x:t},backend:n,attrs:{paddings:s,constantValue:r}}=e,a=s.map((m,g)=>m[0]+t.shape[g]+m[1]);if(v.sizeFromShape(t.shape)===0)return tC({backend:n,attrs:{shape:a,value:r,dtype:t.dtype}});let o=n.dataIdMap.get(t.dataId).id,i=n.makeOutput(a,t.dtype),u=n.dataIdMap.get(i.dataId).id,c=new Uint8Array(new Int32Array(t.shape).buffer),p=s.map(m=>m[0]),d=s.map(m=>m[1]),h=new Uint8Array(new Int32Array(p).buffer),f=new Uint8Array(new Int32Array(d).buffer);return AC(o,c,t.shape.length,Ht[t.dtype],h,f,r,u),i}var xC={kernelName:Wo,backendName:"wasm",kernelFunc:Nhe,setupFunc:The},Ehe=!1,Rhe=_n(Vo,Ehe),bC;function _he(e){bC=e.wasm.cwrap(Uo,null,["number","number","number"])}function Dhe(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t,a=n.dataIdMap.get(s.dataId).id,o=n.dataIdMap.get(r.dataId).id,i=a,l=s,u=l;l.dtype!=="float32"&&(u=ud({backend:n,inputs:{x:s},attrs:{dtype:"float32"}}),i=n.dataIdMap.get(u.dataId).id);let c=n.makeOutput(s.shape,"float32"),p=n.dataIdMap.get(c.dataId).id;return bC(i,o,p),l.dtype!=="float32"&&n.disposeData(u.dataId),c}var $he={kernelName:Uo,backendName:"wasm",setupFunc:_he,kernelFunc:Dhe},vC;function Phe(e){vC=e.wasm.cwrap(Go,null,["number","number","number","number"])}function Fhe(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,i=t.dataIdMap.get(o.dataId).id,l=i,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=pi(o,r,t),f=p;if(h){let A=t.dataIdMap.get(c.dataId).id;A!==i&&(u=c,l=A,f=C.getInnerMostAxes(f.length,u.shape.length))}C.assertAxesAreInnerMostDims("prod",f,u.shape.length);let[m,g]=C.computeOutAndReduceShapes(u.shape,f),y=v.sizeFromShape(g),x=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;vC(l,y,Ht[x.dtype],A)}if(h&&t.disposeData(c.dataId),a){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var Ohe={kernelName:Go,backendName:"wasm",setupFunc:Phe,kernelFunc:Fhe},Mhe=e=>{let{backend:t,attrs:n}=e,{start:s,stop:r,step:a,dtype:o}=n,i=_x(s,r,a,o),l=t.makeOutput([i.length],o);return t.typedArrayFromHeap(l).set(i),l},zhe={kernelName:Rc,backendName:"wasm",kernelFunc:Mhe},Lhe=!0,Bhe=_n(ko,Lhe),Whe=In(Ho),Vhe=In(Xo),wC;function Uhe(e){wC=e.wasm.cwrap(qo,null,["number","number","number","number","number","number","number","number","number","number"])}function Ghe(e){let{backend:t,inputs:n,attrs:s}=e,{images:r}=n,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,[c,p,d,h]=r.shape,f=[c,l,u,h],m=t.dataIdMap.get(r.dataId),g;m.dtype!=="float32"&&(g=ud({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),m=t.dataIdMap.get(g.dataId));let y=m.id,x=t.makeOutput(f,"float32");if(v.sizeFromShape(r.shape)===0)return x;let A=t.dataIdMap.get(x.dataId).id;return wC(y,c,p,d,h,l,u,a?1:0,o?1:0,A),g!=null&&t.disposeData(g.dataId),x}var Hhe={kernelName:qo,backendName:"wasm",setupFunc:Uhe,kernelFunc:Ghe},kC;function jhe(e){kC=e.wasm.cwrap(jo,null,["number","number","number","number","number","number","number","number","number","number"])}function qhe(e){let{backend:t,inputs:n,attrs:s}=e,{images:r}=n,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,[c,p,d,h]=r.shape,f=[c,l,u,h],m=t.makeOutput(f,"float32");if(v.sizeFromShape(r.shape)===0)return m;let g=t.dataIdMap.get(r.dataId),y;g.dtype!=="float32"&&(y=ud({backend:t,inputs:{x:r},attrs:{dtype:"float32"}}),g=t.dataIdMap.get(y.dataId));let x=g.id,A=t.dataIdMap.get(m.dataId).id;return kC(x,c,p,d,h,l,u,a?1:0,o?1:0,A),y!=null&&t.disposeData(y.dataId),m}var Xhe={kernelName:jo,backendName:"wasm",setupFunc:jhe,kernelFunc:qhe},IC;function Khe(e){IC=e.wasm.cwrap(_l,null,["number","array","number","array","number","number"])}function Zhe(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dims:a}=s,o=v.parseAxisParam(a,r.shape);if(r.shape.length===0)return S2({inputs:{x:r},backend:n});let i=n.makeOutput(r.shape,r.dtype),l=n.dataIdMap.get(r.dataId).id,u=n.dataIdMap.get(i.dataId).id,c=new Uint8Array(new Int32Array(o).buffer),p=new Uint8Array(new Int32Array(r.shape).buffer);IC(l,c,o.length,p,r.shape.length,u);let d=hs({inputs:{x:i},attrs:{shape:r.shape},backend:n});return n.disposeData(i.dataId),d}var Yhe={kernelName:_l,backendName:"wasm",kernelFunc:Zhe,setupFunc:Khe},SC;function Jhe(e){SC=e.wasm.cwrap(Hl,null,["number","number","number","number","number","number","number","number","array","number","number"])}function Qhe(e){let{inputs:t,backend:n,attrs:s}=e,{image:r}=t,{radians:a,fillValue:o,center:i}=s,l=n.makeOutput(r.shape,r.dtype),u=n.dataIdMap.get(r.dataId).id,c=n.dataIdMap.get(l.dataId).id,[p,d,h,f]=r.shape,[m,g]=C.getImageCenter(i,d,h),y=o===0,x=255,A=typeof o=="number"?[o,o,o,y?0:x]:[...o,x],b=new Uint8Array(new Int32Array(A).buffer);return SC(u,p,d,h,f,a,m,g,b,A.length,c),l}var efe={kernelName:Hl,backendName:"wasm",kernelFunc:Qhe,setupFunc:Jhe},tfe=In(Dl),nfe=In(Ko),CC;function sfe(e){CC=e.wasm.cwrap($l,null,["number","number","number","number","number","number","array","number","number"])}function rfe(e){let{backend:t,inputs:n,attrs:s}=e,{indices:r,updates:a}=n,{shape:o}=s,i=t.makeOutput(o,a.dtype);if(v.sizeFromShape(o)===0)return i;let{sliceRank:l,numUpdates:u,sliceSize:c,strides:p,outputSize:d}=Ly.calculateShapes(a,r,o),f=t.dataIdMap.get(r.dataId).id,g=t.dataIdMap.get(a.dataId).id,y=new Uint8Array(new Int32Array(p).buffer),x=t.dataIdMap.get(i.dataId).id;return CC(f,g,Ht[a.dtype],l,u,c,y,d,x),i}var afe={kernelName:$l,backendName:"wasm",setupFunc:sfe,kernelFunc:rfe},TC;function ofe(e){TC=e.wasm.cwrap("SelectV2",null,["number","number","number","number","number"])}function ife(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t,o=n.dataIdMap.get(s.dataId).id,i=n.dataIdMap.get(r.dataId).id,l=n.dataIdMap.get(a.dataId).id,u=n.makeOutput(r.shape,r.dtype),c=n.dataIdMap.get(u.dataId).id,p=s.shape.length,d=r.shape.length,h=p===0||p>1||d===1?1:v.sizeFromShape(r.shape.slice(1));return TC(o,i,l,h,c),u}var lfe={kernelName:Pl,backendName:"wasm",kernelFunc:ife,setupFunc:ofe},NC;function ufe(e){NC=e.wasm.cwrap(Yo,null,["number","number"])}function cfe(e){let{backend:t,inputs:{x:n}}=e,s=t.dataIdMap.get(n.dataId).id,r=t.makeOutput(n.shape,n.dtype),a=t.dataIdMap.get(r.dataId).id;return v.sizeFromShape(r.shape)===0||NC(s,a),r}var dfe={kernelName:"Sigmoid",backendName:"wasm",setupFunc:ufe,kernelFunc:cfe},pfe=In(Zo),EC;function hfe(e){EC=e.wasm.cwrap(ei,null,["number","number","number","number"])}function ffe(e){let{backend:t,inputs:{logits:n},attrs:{dim:s}}=e,r=t.dataIdMap.get(n.dataId).id,a=t.makeOutput(n.shape,n.dtype),o=t.dataIdMap.get(a.dataId).id,i=n.shape[s],l=v.sizeFromShape(n.shape)/i;return v.sizeFromShape(a.shape)===0||EC(r,o,i,l),a}var mfe={kernelName:ei,backendName:"wasm",setupFunc:hfe,kernelFunc:ffe};function gfe(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,paddings:o}=s,i=v.sizeFromShape(a),l=[[0,0]];l.push(...o);for(let k=1+a.length;k<r.shape.length;++k)l.push([0,0]);let u=xC.kernelFunc({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),c=C.getReshaped(u.shape,a,i,!1),p=C.getPermuted(c.length,a.length,!1),d=C.getReshapedPermuted(u.shape,a,i,!1),m=hs({inputs:{x:u},backend:n,attrs:{shape:c}}),x=io({inputs:{x:m},backend:n,attrs:{perm:p}}),w=hs({inputs:{x},backend:n,attrs:{shape:d}});return n.disposeData(u.dataId),n.disposeData(m.dataId),n.disposeData(x.dataId),w}var yfe={kernelName:Ml,backendName:"wasm",kernelFunc:gfe},RC;function Afe(e){RC=e.wasm.cwrap("SparseFillEmptyRows","number",["number","number","number","number","number","number","number","number","number","number","number","number"])}function xfe(e){let{backend:t,inputs:n}=e,{indices:s,values:r,denseShape:a,defaultValue:o}=n,i=s.shape[0],l=s.shape[1],u=t.readSync(a.dataId)[0],c=[i+u,l],p=t.dataIdMap.get(s.dataId).id,d=t.dataIdMap.get(r.dataId).id,h=t.dataIdMap.get(o.dataId).id,f=t.makeOutput(c,s.dtype),m=t.dataIdMap.get(f.dataId).id,g=t.makeOutput(c.slice(0,1),r.dtype),y=t.dataIdMap.get(g.dataId).id,x=t.makeOutput([u],"bool"),A=t.dataIdMap.get(x.dataId).id,b=t.makeOutput([i],s.dtype),w=t.dataIdMap.get(b.dataId).id,k=t.makeOutput([4],"int32"),S=t.dataIdMap.get(k.dataId).id,E=RC(p,d,Ht[r.dtype],i,u,l,h,m,y,A,w,S),R=t.readSync(k.dataId),P;switch(R[0]){case 1:{P=C.getSparseFillEmptyRowsIndicesDenseShapeMismatch(R[1]);break}case 2:{P=C.getSparseFillEmptyRowsNegativeIndexErrorMessage(R[1],R[2]);break}case 3:P=C.getSparseFillEmptyRowsOutOfRangeIndexErrorMessage(R[1],R[2],R[3]);break;default:P=""}if(t.disposeData(k.dataId),P)throw t.disposeData(f.dataId),t.disposeData(g.dataId),t.disposeData(x.dataId),t.disposeData(b.dataId),new Error(P);let _=f,$=g;return E!==c[0]&&(_=rl({inputs:{x:f},attrs:{begin:0,size:[E,l]},backend:t}),$=rl({inputs:{x:g},attrs:{begin:0,size:E},backend:t}),t.disposeData(f.dataId),t.disposeData(g.dataId)),[_,$,x,b]}var bfe={kernelName:qp,backendName:"wasm",setupFunc:Afe,kernelFunc:xfe},_C;function vfe(e){_C=e.wasm.cwrap(Fc,null,["number","number","number","number","number","number","number"])}function wfe(e){let{backend:t,inputs:n}=e,{inputIndices:s,inputShape:r,newShape:a}=n;if(s.shape.length!==2)throw new Error(`Input indices should be a matrix but received shape
         ${s.shape}`);if(r.shape.length!==1)throw new Error(`Input shape should be a vector but received shape
-        ${r.shape}`);if(a.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${a.shape}`);let o=t.dataIdMap.get(s.dataId).id,i=t.dataIdMap.get(r.dataId).id,l=t.dataIdMap.get(a.dataId).id,u=s.shape[0],c=v.sizeFromShape(a.shape),p=t.makeOutput([u,c],s.dtype),d=t.dataIdMap.get(p.dataId).id,h=t.makeOutput([c],a.dtype),f=t.dataIdMap.get(h.dataId).id,m=t.makeOutput([3],"int32"),g=t.dataIdMap.get(m.dataId).id;_C(o,i,l,u,d,f,g);let y=t.readSync(m.dataId),x;switch(y[0]){case 0:{x=C.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(y[1],y[2]);break}case 1:{x=C.getSparseReshapeNegativeOutputDimErrorMessage(y[1],y[2]);break}case 2:x=C.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage();break;case 3:{let A=Array.from(t.readSync(r.dataId)),b=Array.from(t.readSync(h.dataId));x=C.getSparseReshapeInputOutputMultipleErrorMessage(A,b);break}case 4:{let A=Array.from(t.readSync(r.dataId)),b=Array.from(t.readSync(h.dataId));x=C.getSparseReshapeInputOutputMismatchErrorMessage(A,b);break}default:x=""}if(t.disposeData(m.dataId),x)throw t.disposeData(p.dataId),t.disposeData(h.dataId),new Error(x);return[p,h]}var kfe={kernelName:Oc,backendName:"wasm",setupFunc:vfe,kernelFunc:wfe},DC;function $C(e){DC=e.wasm.cwrap("SparseSegmentReduction",null,["number","number","number","number","number","number","number","number","number"])}function PC(e,t){let{backend:n,inputs:s}=e,{data:r,indices:a,segmentIds:o}=s,i=a.shape[0],l=n.readSync(o.dataId,i-1,i)[0],c=i>0?l+1:0;if(c<0)throw new Error(C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let p=r.shape.slice();p[0]=c;let d=n.dataIdMap.get(r.dataId).id,h=n.dataIdMap.get(a.dataId).id,f=n.dataIdMap.get(o.dataId).id,m=n.makeOutput(p,r.dtype),g=n.dataIdMap.get(m.dataId).id,y=n.makeOutput([4],"int32"),x=n.dataIdMap.get(y.dataId).id;DC(d,Ht[r.dtype],r.shape[0],h,f,g,x,t,0);let A=n.readSync(y.dataId),b;switch(A[0]){case 0:{b=C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage();break}case 1:{b=C.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage();break}case 2:b=C.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(A[1],A[2]);break;case 3:b=C.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(A[1],A[2],A[3]);break;default:b=""}if(n.disposeData(y.dataId),b)throw n.disposeData(m.dataId),new Error(b);return m}function Ife(e){return PC(e,!0)}var Sfe={kernelName:Kp,backendName:"wasm",setupFunc:$C,kernelFunc:Ife};function Cfe(e){return PC(e,!1)}var Tfe={kernelName:Zp,backendName:"wasm",setupFunc:$C,kernelFunc:Cfe};function Nfe(e){let{inputs:t,attrs:n,backend:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=n,i=v.parseAxisParam(o,r.shape)[0],l=C.prepareSplitSize(r,a,i),u=new Array(r.shape.length).fill(0),c=r.shape.slice();return l.map(p=>{let d=[...c];d[i]=p;let h=al({inputs:{x:r},attrs:{begin:u,size:d},backend:s});return u[i]+=p,h})}var Efe={kernelName:Ll,backendName:"wasm",kernelFunc:Nfe},Rfe=In(Qo),_fe=In(Mc),Dfe=!0,$fe=_n(ni,Dfe),FC;function Pfe(e){FC=e.wasm.cwrap(ai,null,["number","number","number","number"])}function Ffe(e){let{backend:t,inputs:n,attrs:s}=e,{alpha:r}=s,{x:a}=n,o=t.dataIdMap.get(a.dataId).id,i=t.makeOutput(a.shape,a.dtype),l=t.dataIdMap.get(i.dataId).id;return FC(o,r,Ht[a.dtype],l),i}var Ofe={kernelName:ai,backendName:"wasm",setupFunc:Pfe,kernelFunc:Ffe},OC;function Mfe(e){OC=e.wasm.cwrap(Bl,null,["number","array","number","array","array","array","array","array","number","number"])}function zfe(e){let{backend:t,inputs:n,attrs:s}=e,{x:r}=n,{begin:a,end:o,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:d}=s,{finalShapeSparse:h,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Ut.sliceInfo(r.shape,a,o,i,l,u,c,p,d),w;if(m)w=hs({inputs:{x:r},backend:t,attrs:{shape:f}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let k=Ut.computeOutShape(x,A,b),S=al({inputs:{x:r},backend:t,attrs:{begin:x,size:k}});w=hs({inputs:{x:S},backend:t,attrs:{shape:f}}),t.disposeData(S.dataId)}else{let k=t.makeOutput(h,"float32"),S=t.dataIdMap.get(r.dataId).id,E=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),R=new Uint8Array(new Int32Array(x).buffer),P=new Uint8Array(new Int32Array(A).buffer),_=new Uint8Array(new Int32Array(b).buffer),$=new Uint8Array(new Int32Array(h).buffer),T=new Uint8Array(new Int32Array(v.computeStrides(h)).buffer),F=t.dataIdMap.get(k.dataId).id;OC(S,E,r.shape.length,R,P,_,$,T,h.length,F),w=hs({inputs:{x:k},backend:t,attrs:{shape:f}}),t.disposeData(k.dataId)}return w}var Lfe={kernelName:Bl,backendName:"wasm",setupFunc:Mfe,kernelFunc:zfe};function Bfe(e){let{backend:t,inputs:n,attrs:s}=e,{data:r,dataSplits:a}=n,{separator:o,nGramWidths:i,leftPad:l,rightPad:u,padWidth:c,preserveShortSequences:p}=s,d=t.readSync(r.dataId),h=t.readSync(a.dataId),[f,m]=$x(d,h,o,i,l,u,c,p),g=t.makeOutput([f.length],"string"),y=t.dataIdMap.get(g.dataId);y.stringBytes=f;let x=t.makeOutput(a.shape,"int32");return t.typedArrayFromHeap(x).set(m),[g,x]}var Wfe={kernelName:zc,backendName:"wasm",kernelFunc:Bfe};function Vfe(e){let{backend:t,inputs:n,attrs:s}=e,{input:r,delimiter:a}=n,{skipEmpty:o}=s,i=t.readSync(r.dataId),l=t.readSync(a.dataId),[u,c,p]=Px(i,l[0],o),d=c.length,h=t.makeOutput([d,2],"int32");t.typedArrayFromHeap(h).set(u);let m=t.makeOutput([d],"string"),g=t.dataIdMap.get(m.dataId);g.stringBytes=c;let y=t.makeOutput([2],"int32");return t.typedArrayFromHeap(y).set(p),[h,m,y]}var Ufe={kernelName:Jp,backendName:"wasm",kernelFunc:Vfe};function Gfe(e){let{backend:t,inputs:n,attrs:s}=e,{input:r}=n,{numBuckets:a}=s,o=t.readSync(r.dataId),i=Fx(o,a),l=t.makeOutput(r.shape,"int32");return t.typedArrayFromHeap(l).set(i),l}var Hfe={kernelName:Qp,backendName:"wasm",kernelFunc:Gfe},jfe=!0,qfe=_n(si,jfe),MC;function Xfe(e){MC=e.wasm.cwrap(ei,null,["number","number","number","number"])}function Kfe(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,i=t.dataIdMap.get(o.dataId).id,l=i,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=hi(o,r,t),f=p;if(h){let A=t.dataIdMap.get(c.dataId).id;A!==i&&(u=c,l=A,f=C.getInnerMostAxes(f.length,u.shape.length))}C.assertAxesAreInnerMostDims("sum",f,u.shape.length);let[m,g]=C.computeOutAndReduceShapes(u.shape,f),y=v.sizeFromShape(g),x=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;MC(l,y,Ht[x.dtype],A)}if(h&&t.disposeData(c.dataId),a){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var Zfe={kernelName:ei,backendName:"wasm",setupFunc:Xfe,kernelFunc:Kfe},Yfe=In(Wl),Jfe=In(ri),zC;function Qfe(e){zC=e.wasm.cwrap(va,null,["number","array","number","array","number","number"])}function eme(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,a=n.dataIdMap.get(r.dataId).id,{reps:o}=s,i=new Array(r.shape.length);for(let d=0;d<i.length;d++)i[d]=r.shape[d]*o[d];let l=new Uint8Array(new Int32Array(r.shape).buffer),u=new Uint8Array(new Int32Array(i).buffer),c=n.makeOutput(i,r.dtype),p=n.dataIdMap.get(c.dataId).id;return zC(a,l,r.shape.length,u,i.length,Ht[c.dtype],p),c}var tme={kernelName:va,backendName:"wasm",setupFunc:Qfe,kernelFunc:eme},LC;function nme(e){LC=e.wasm.cwrap(Vl,null,["number","array","number","number","number","bool","number","number"])}var sme=({inputs:e,backend:t,attrs:n})=>{let{x:s}=e,{k:r,sorted:a}=n,o=t.dataIdMap.get(s.dataId).id,i=new Uint8Array(new Int32Array(s.shape).buffer),l=s.shape.slice();l[l.length-1]=r;let u=t.makeOutput(l,s.dtype),c=t.dataIdMap.get(u.dataId).id,p=t.makeOutput(l,"int32"),d=t.dataIdMap.get(p.dataId).id;return LC(o,i,s.shape.length,Ht[s.dtype],r,a,c,d),[u,p]},rme={kernelName:Vl,backendName:"wasm",setupFunc:nme,kernelFunc:sme},BC;function ame(e){BC=e.wasm.cwrap(Ul,null,["number","number","bool","number","number","number","number","number","number","array","number","number","number","number","number"])}function ome(e){let{backend:t,inputs:n,attrs:s}=e,{image:r,transforms:a}=n,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=s,[c,p,d,h]=r.shape,[f,m]=u!=null?u:[p,d],g=[c,f,m,h],y=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),x=t.makeOutput(g,r.dtype),A=t.dataIdMap.get(x.dataId).id,w=t.dataIdMap.get(r.dataId).id,S=t.dataIdMap.get(a.dataId).id,E=o==="nearest"?1:2,R;switch(i){case"constant":R=1;break;case"reflect":R=2;break;case"wrap":R=3;break;case"nearest":R=4;break;default:R=1;break}return BC(w,S,a.shape[0]>1,c,f,m,h,d,p,y,r.shape.length-1,E,R,l,A),x}var ime={kernelName:Ul,backendName:"wasm",setupFunc:ame,kernelFunc:ome};function lme(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r.shape[a],i=r.shape.length,l=new Array(i-1),u=0;for(let h=0;h<i;h++)h!==a&&(l[u++]=r.shape[h]);let c=new Array(o),p=new Array(i).fill(0),d=r.shape.slice();d[a]=1;for(let h=0;h<c.length;h++)p[a]=h,c[h]=al({inputs:{x:r},attrs:{begin:p,size:d},backend:n});return c.map(({dataId:h,dtype:f})=>({dataId:h,dtype:f,shape:l}))}var ume={kernelName:Gl,backendName:"wasm",kernelFunc:lme};function cme(e){let{inputs:{x:t},backend:n}=e,s=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(s).fill(0),s}var dme={kernelName:Hl,backendName:"wasm",kernelFunc:cme},pme=[Bce,Wce,Uce,jce,ede,sde,ode,ude,hde,xde,bde,vde,Ide,Sde,Nde,_de,Dde,$de,Ode,Lde,Vde,Hde,Xde,Kde,Yde,Jde,Qde,epe,spe,rpe,ope,upe,ppe,mpe,Ape,vpe,kpe,Spe,qce,Npe,Rpe,Dpe,$pe,Fpe,Ope,zpe,Bpe,Upe,Hpe,Xpe,Ype,ehe,nhe,ahe,ihe,lhe,dhe,fhe,yhe,xhe,whe,Ihe,Che,xC,Rhe,$he,Ohe,zhe,Bhe,Whe,Vhe,cde,Hhe,Xhe,Yhe,efe,tfe,nfe,afe,lfe,dfe,pfe,yde,mfe,yfe,bfe,kfe,Sfe,Tfe,Efe,Rfe,_fe,$fe,Ofe,Lfe,Wfe,Ufe,Hfe,qfe,Zfe,Yfe,Jfe,tme,rme,ime,Yce,ume,dme];for(let e of pme)cr(e);var py=Z();py.registerFlag("WASM_HAS_SIMD_SUPPORT",async()=>WebAssembly.validate(new Uint8Array([0,97,115,109,1,0,0,0,1,4,1,96,0,0,3,2,1,0,10,9,1,7,0,65,0,253,15,26,11])));py.registerFlag("WASM_HAS_MULTITHREAD_SUPPORT",async()=>{if(py.get("IS_NODE"))return!1;try{return new MessageChannel().port1.postMessage(new SharedArrayBuffer(1)),WebAssembly.validate(new Uint8Array([0,97,115,109,1,0,0,0,1,4,1,96,0,0,3,2,1,0,5,4,1,3,1,1,10,11,1,9,0,65,0,254,16,2,0,26,11]))}catch(e){return!1}});var P7=uo(m_()),hme=uo(g_()),F7=uo(y_()),O7=P7.default||P7,fme=F7.default||F7,WC=class extends cc{constructor(e){super(),this.wasm=e,this.dataIdNextNumber=1,this.wasm.tfjs.initWithThreadsCount(VC),hy=this.wasm.tfjs.getThreadsCount(),this.dataIdMap=new Mp(this,sn())}write(e,t,n){let s={id:this.dataIdNextNumber++};return this.move(s,e,t,n,1),s}numDataIds(){return this.dataIdMap.numDataIds()}async time(e){let t=v.now();return e(),{kernelMs:v.now()-t}}move(e,t,n,s,r){let a=this.dataIdNextNumber++;if(s==="string"){let u=t;this.dataIdMap.set(e,{id:a,stringBytes:u,shape:n,dtype:s,memoryOffset:null,refCount:r});return}let o=v.sizeFromShape(n),i=o*v.bytesPerElement(s),l=this.wasm._malloc(i);this.dataIdMap.set(e,{id:a,memoryOffset:l,shape:n,dtype:s,refCount:r}),this.wasm.tfjs.registerTensor(a,o,l),t!=null&&this.wasm.HEAPU8.set(new Uint8Array(t.buffer,t.byteOffset,i),l)}async read(e){return this.readSync(e)}readSync(e,t,n){let{memoryOffset:s,dtype:r,shape:a,stringBytes:o}=this.dataIdMap.get(e);if(r==="string")return(t==null||t===0)&&(n==null||n>=o.length)?o:o.slice(t,n);t=t||0,n=n||v.sizeFromShape(a);let i=v.bytesPerElement(r),l=this.wasm.HEAPU8.slice(s+t*i,s+n*i);return yme(l.buffer,r)}disposeData(e,t=!1){if(this.dataIdMap.has(e)){let n=this.dataIdMap.get(e);if(n.refCount--,!t&&n.refCount>0)return!1;this.wasm._free(n.memoryOffset),this.wasm.tfjs.disposeData(n.id),this.dataIdMap.delete(e)}return!0}refCount(e){return this.dataIdMap.has(e)?this.dataIdMap.get(e).refCount:0}incRef(e){let t=this.dataIdMap.get(e);t!=null&&t.refCount++}floatPrecision(){return 32}getMemoryOffset(e){return this.dataIdMap.get(e).memoryOffset}dispose(){this.wasm.tfjs.dispose(),"PThread"in this.wasm&&this.wasm.PThread.terminateAllThreads(),this.wasm=null}memory(){return{unreliable:!1}}makeOutput(e,t,n){let s;if(n==null)s=this.write(null,e,t);else{let r=this.dataIdNextNumber++;s={id:r},this.dataIdMap.set(s,{id:r,memoryOffset:n,shape:e,dtype:t,refCount:1});let a=v.sizeFromShape(e);this.wasm.tfjs.registerTensor(r,a,n)}return{dataId:s,shape:e,dtype:t}}typedArrayFromHeap({shape:e,dtype:t,dataId:n}){let s=this.wasm.HEAPU8.buffer,{memoryOffset:r}=this.dataIdMap.get(n),a=v.sizeFromShape(e);switch(t){case"float32":return new Float32Array(s,r,a);case"int32":return new Int32Array(s,r,a);case"bool":return new Uint8Array(s,r,a);default:throw new Error(`Unknown dtype ${t}`)}}};function mme(e){return(t,n)=>(v.fetch(e,{credentials:"same-origin"}).then(s=>{s.ok||t.env.a(`failed to load wasm binary file at '${e}'`),s.arrayBuffer().then(r=>{WebAssembly.instantiate(r,t).then(a=>{n(a.instance,a.module)})})}),{})}function M7(e,t,n){if(zm!=null)return zm;let s="tfjs-backend-wasm.wasm";return e&&t?s="tfjs-backend-wasm-threaded-simd.wasm":e&&(s="tfjs-backend-wasm-simd.wasm"),gp!=null&&gp[s]!=null?gp[s]:n+s}async function gme(){let[e,t]=await Promise.all([Z().getAsync("WASM_HAS_SIMD_SUPPORT"),Z().getAsync("WASM_HAS_MULTITHREAD_SUPPORT")]);return new Promise((n,s)=>{let r={};r.locateFile=(i,l)=>{if(i.endsWith(".worker.js")){let u=hme.wasmWorkerContents.replace(/\n/g,"\\n"),c=new Blob([u],{type:"application/javascript"});return URL.createObjectURL(c)}return i.endsWith(".wasm")?M7(e,t,pp!=null?pp:l):l+i},eb&&(r.instantiateWasm=mme(M7(e,t,pp!=null?pp:"")));let a=!1;r.onAbort=()=>{if(a||yp)return;yp=!0,s({message:"Make sure the server can serve the `.wasm` file relative to the bundled js file. For more details see https://github.com/tensorflow/tfjs/blob/master/tfjs-backend-wasm/README.md#using-bundlers"})};let o;t&&e&&zm==null?(r.mainScriptUrlOrBlob=new Blob(["var WasmBackendModuleThreadedSimd = "+O7.toString()],{type:"text/javascript"}),o=O7(r)):o=fme(r),o.then(i=>{a=!0,yp=!1;let l=null;i.tfjs={init:i.cwrap("init",null,[]),initWithThreadsCount:i.cwrap("init_with_threads_count",null,["number"]),getThreadsCount:i.cwrap("get_threads_count","number",[]),registerTensor:i.cwrap("register_tensor",null,["number","number","number"]),disposeData:i.cwrap("dispose_data",l,["number"]),dispose:i.cwrap("dispose",l,[])},n({wasm:i})}).catch(s)})}function yme(e,t){switch(t){case"float32":return new Float32Array(e);case"int32":return new Int32Array(e);case"bool":return new Uint8Array(e);default:throw new Error(`Unknown dtype ${t}`)}}var Ame=["tfjs-backend-wasm.wasm","tfjs-backend-wasm-simd.wasm","tfjs-backend-wasm-threaded-simd.wasm"],zm=null,pp=null,gp={},yp=!1,eb=!1;function xme(e,t=!1){if(Py("setWasmPath has been deprecated in favor of setWasmPaths and will be removed in a future release."),yp)throw new Error("The WASM backend was already initialized. Make sure you call `setWasmPath()` before you call `tf.setBackend()` or `tf.ready()`");zm=e,eb=t}function tb(e,t=!1){if(yp)throw new Error("The WASM backend was already initialized. Make sure you call `setWasmPaths()` before you call `tf.setBackend()` or `tf.ready()`");if(typeof e=="string")pp=e;else{gp=e;let n=Ame.filter(s=>gp[s]==null);if(n.length>0)throw new Error(`There were no entries found for the following binaries: ${n.join(",")}. Please either call setWasmPaths with a map providing a path for each binary, or with a string indicating the directory where all the binaries can be found.`)}eb=t}var VC=-1,hy=-1;function bme(e){VC=e}function vme(){if(hy===-1)throw new Error("WASM backend not initialized.");return hy}var wme="3.19.0",kme=2;ql("wasm",async()=>{let{wasm:e}=await gme();return new WC(e)},kme);var Sa=Z();Sa.registerFlag("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE",()=>15);Sa.registerFlag("WEBGPU_CPU_FORWARD",()=>!0);Sa.registerFlag("WEBGPU_MATMUL_WORK_PER_THREAD",()=>4);Sa.registerFlag("WEBGPU_MATMUL_PROGRAM_TYPE",()=>-1);Sa.registerFlag("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE",()=>!1);Sa.registerFlag("WEBGPU_USE_LOW_POWER_GPU",()=>!1);Sa.registerFlag("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e3);Sa.registerFlag("WEBGPU_USE_PROFILE_TOOL",()=>!1);Sa.registerFlag("WEBGPU_IMPORT_EXTERNAL_TEXTURE",()=>!1);var Ye;(function(e){e[e.MUL=0]="MUL",e[e.ADD=1]="ADD",e[e.SUB=2]="SUB",e[e.DIV=3]="DIV",e[e.EQUAL=4]="EQUAL",e[e.GREATER=5]="GREATER",e[e.GREATER_EQUAL=6]="GREATER_EQUAL",e[e.LESS=7]="LESS",e[e.LESS_EQUAL=8]="LESS_EQUAL",e[e.LOGICAL_AND=9]="LOGICAL_AND",e[e.NOT_EQUAL=10]="NOT_EQUAL",e[e.SQUARED_DIFFERENCE=11]="SQUARED_DIFFERENCE",e[e.INT_DIV=12]="INT_DIV",e[e.POW=13]="POW",e[e.PRELU=14]="PRELU",e[e.MAX=15]="MAX",e[e.MIN=16]="MIN",e[e.COMPLEX_MULTIPLY_REAL=17]="COMPLEX_MULTIPLY_REAL",e[e.COMPLEX_MULTIPLY_IMAG=18]="COMPLEX_MULTIPLY_IMAG"})(Ye||(Ye={}));var Ime="return a + b;",Sme="return areal * breal - aimag * bimag;",Cme="return areal * bimag + aimag * breal;",Tme="return a / b;",Nme="return a * b;",Eme="return (a - b) * (a - b);",Rme="return a - b;",_me="return f32(a == b);",Dme="return vec4<f32>(a == b);",$me="return f32(a > b);",Pme="return vec4<f32>(a > b);",Fme="return f32(a >= b);",Ome="return vec4<f32>(a >= b);",Mme="return f32(a < b);",zme="return vec4<f32>(a < b);",Lme="return f32(a <= b);",Bme="return vec4<f32>(a <= b);",Wme="return f32(f32(a) >= 1.0 && f32(b) >= 1.0);",Vme=`return (vec4<f32>(a >= vec4<f32>(1.0)) *
+        ${r.shape}`);if(a.shape.length!==1)throw new Error(`Target shape should be a vector but received shape ${a.shape}`);let o=t.dataIdMap.get(s.dataId).id,i=t.dataIdMap.get(r.dataId).id,l=t.dataIdMap.get(a.dataId).id,u=s.shape[0],c=v.sizeFromShape(a.shape),p=t.makeOutput([u,c],s.dtype),d=t.dataIdMap.get(p.dataId).id,h=t.makeOutput([c],a.dtype),f=t.dataIdMap.get(h.dataId).id,m=t.makeOutput([3],"int32"),g=t.dataIdMap.get(m.dataId).id;_C(o,i,l,u,d,f,g);let y=t.readSync(m.dataId),x;switch(y[0]){case 0:{x=C.getSparseReshapeMultipleNegativeOneOutputDimErrorMessage(y[1],y[2]);break}case 1:{x=C.getSparseReshapeNegativeOutputDimErrorMessage(y[1],y[2]);break}case 2:x=C.getSparseReshapeEmptyTensorZeroOutputDimErrorMessage();break;case 3:{let A=Array.from(t.readSync(r.dataId)),b=Array.from(t.readSync(h.dataId));x=C.getSparseReshapeInputOutputMultipleErrorMessage(A,b);break}case 4:{let A=Array.from(t.readSync(r.dataId)),b=Array.from(t.readSync(h.dataId));x=C.getSparseReshapeInputOutputMismatchErrorMessage(A,b);break}default:x=""}if(t.disposeData(m.dataId),x)throw t.disposeData(p.dataId),t.disposeData(h.dataId),new Error(x);return[p,h]}var kfe={kernelName:Fc,backendName:"wasm",setupFunc:vfe,kernelFunc:wfe},DC;function $C(e){DC=e.wasm.cwrap("SparseSegmentReduction",null,["number","number","number","number","number","number","number","number","number"])}function PC(e,t){let{backend:n,inputs:s}=e,{data:r,indices:a,segmentIds:o}=s,i=a.shape[0],l=n.readSync(o.dataId,i-1,i)[0],c=i>0?l+1:0;if(c<0)throw new Error(C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage());let p=r.shape.slice();p[0]=c;let d=n.dataIdMap.get(r.dataId).id,h=n.dataIdMap.get(a.dataId).id,f=n.dataIdMap.get(o.dataId).id,m=n.makeOutput(p,r.dtype),g=n.dataIdMap.get(m.dataId).id,y=n.makeOutput([4],"int32"),x=n.dataIdMap.get(y.dataId).id;DC(d,Ht[r.dtype],r.shape[0],h,f,g,x,t,0);let A=n.readSync(y.dataId),b;switch(A[0]){case 0:{b=C.getSparseSegmentReductionNegativeSegmentIdsErrorMessage();break}case 1:{b=C.getSparseSegmentReductionNonIncreasingSegmentIdsErrorMessage();break}case 2:b=C.getSparseSegmentReductionSegmentIdOutOfRangeErrorMessage(A[1],A[2]);break;case 3:b=C.getSparseSegmentReductionIndicesOutOfRangeErrorMessage(A[1],A[2],A[3]);break;default:b=""}if(n.disposeData(y.dataId),b)throw n.disposeData(m.dataId),new Error(b);return m}function Ife(e){return PC(e,!0)}var Sfe={kernelName:Xp,backendName:"wasm",setupFunc:$C,kernelFunc:Ife};function Cfe(e){return PC(e,!1)}var Tfe={kernelName:Kp,backendName:"wasm",setupFunc:$C,kernelFunc:Cfe};function Nfe(e){let{inputs:t,attrs:n,backend:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=n,i=v.parseAxisParam(o,r.shape)[0],l=C.prepareSplitSize(r,a,i),u=new Array(r.shape.length).fill(0),c=r.shape.slice();return l.map(p=>{let d=[...c];d[i]=p;let h=rl({inputs:{x:r},attrs:{begin:u,size:d},backend:s});return u[i]+=p,h})}var Efe={kernelName:zl,backendName:"wasm",kernelFunc:Nfe},Rfe=In(Jo),_fe=In(Oc),Dfe=!0,$fe=_n(ti,Dfe),FC;function Pfe(e){FC=e.wasm.cwrap(ri,null,["number","number","number","number"])}function Ffe(e){let{backend:t,inputs:n,attrs:s}=e,{alpha:r}=s,{x:a}=n,o=t.dataIdMap.get(a.dataId).id,i=t.makeOutput(a.shape,a.dtype),l=t.dataIdMap.get(i.dataId).id;return FC(o,r,Ht[a.dtype],l),i}var Ofe={kernelName:ri,backendName:"wasm",setupFunc:Pfe,kernelFunc:Ffe},OC;function Mfe(e){OC=e.wasm.cwrap(Ll,null,["number","array","number","array","array","array","array","array","number","number"])}function zfe(e){let{backend:t,inputs:n,attrs:s}=e,{x:r}=n,{begin:a,end:o,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:d}=s,{finalShapeSparse:h,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Ut.sliceInfo(r.shape,a,o,i,l,u,c,p,d),w;if(m)w=hs({inputs:{x:r},backend:t,attrs:{shape:f}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let k=Ut.computeOutShape(x,A,b),S=rl({inputs:{x:r},backend:t,attrs:{begin:x,size:k}});w=hs({inputs:{x:S},backend:t,attrs:{shape:f}}),t.disposeData(S.dataId)}else{let k=t.makeOutput(h,"float32"),S=t.dataIdMap.get(r.dataId).id,E=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),R=new Uint8Array(new Int32Array(x).buffer),P=new Uint8Array(new Int32Array(A).buffer),_=new Uint8Array(new Int32Array(b).buffer),$=new Uint8Array(new Int32Array(h).buffer),T=new Uint8Array(new Int32Array(v.computeStrides(h)).buffer),F=t.dataIdMap.get(k.dataId).id;OC(S,E,r.shape.length,R,P,_,$,T,h.length,F),w=hs({inputs:{x:k},backend:t,attrs:{shape:f}}),t.disposeData(k.dataId)}return w}var Lfe={kernelName:Ll,backendName:"wasm",setupFunc:Mfe,kernelFunc:zfe};function Bfe(e){let{backend:t,inputs:n,attrs:s}=e,{data:r,dataSplits:a}=n,{separator:o,nGramWidths:i,leftPad:l,rightPad:u,padWidth:c,preserveShortSequences:p}=s,d=t.readSync(r.dataId),h=t.readSync(a.dataId),[f,m]=$x(d,h,o,i,l,u,c,p),g=t.makeOutput([f.length],"string"),y=t.dataIdMap.get(g.dataId);y.stringBytes=f;let x=t.makeOutput(a.shape,"int32");return t.typedArrayFromHeap(x).set(m),[g,x]}var Wfe={kernelName:Mc,backendName:"wasm",kernelFunc:Bfe};function Vfe(e){let{backend:t,inputs:n,attrs:s}=e,{input:r,delimiter:a}=n,{skipEmpty:o}=s,i=t.readSync(r.dataId),l=t.readSync(a.dataId),[u,c,p]=Px(i,l[0],o),d=c.length,h=t.makeOutput([d,2],"int32");t.typedArrayFromHeap(h).set(u);let m=t.makeOutput([d],"string"),g=t.dataIdMap.get(m.dataId);g.stringBytes=c;let y=t.makeOutput([2],"int32");return t.typedArrayFromHeap(y).set(p),[h,m,y]}var Ufe={kernelName:Yp,backendName:"wasm",kernelFunc:Vfe};function Gfe(e){let{backend:t,inputs:n,attrs:s}=e,{input:r}=n,{numBuckets:a}=s,o=t.readSync(r.dataId),i=Fx(o,a),l=t.makeOutput(r.shape,"int32");return t.typedArrayFromHeap(l).set(i),l}var Hfe={kernelName:Jp,backendName:"wasm",kernelFunc:Gfe},jfe=!0,qfe=_n(ni,jfe),MC;function Xfe(e){MC=e.wasm.cwrap(Qo,null,["number","number","number","number"])}function Kfe(e){let{backend:t,inputs:n,attrs:s}=e,{axis:r,keepDims:a}=s,{x:o}=n,i=t.dataIdMap.get(o.dataId).id,l=i,u=o,{transposed:c,axes:p,originalAxes:d,inputWasTransposed:h}=pi(o,r,t),f=p;if(h){let A=t.dataIdMap.get(c.dataId).id;A!==i&&(u=c,l=A,f=C.getInnerMostAxes(f.length,u.shape.length))}C.assertAxesAreInnerMostDims("sum",f,u.shape.length);let[m,g]=C.computeOutAndReduceShapes(u.shape,f),y=v.sizeFromShape(g),x=t.makeOutput(m,u.dtype);if(v.sizeFromShape(u.shape)!==0){let A=t.dataIdMap.get(x.dataId).id;MC(l,y,Ht[x.dtype],A)}if(h&&t.disposeData(c.dataId),a){let A=C.expandShapeToKeepDim(x.shape,d);x.shape=A}return x}var Zfe={kernelName:Qo,backendName:"wasm",setupFunc:Xfe,kernelFunc:Kfe},Yfe=In(Bl),Jfe=In(si),zC;function Qfe(e){zC=e.wasm.cwrap(ba,null,["number","array","number","array","number","number"])}function eme(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,a=n.dataIdMap.get(r.dataId).id,{reps:o}=s,i=new Array(r.shape.length);for(let d=0;d<i.length;d++)i[d]=r.shape[d]*o[d];let l=new Uint8Array(new Int32Array(r.shape).buffer),u=new Uint8Array(new Int32Array(i).buffer),c=n.makeOutput(i,r.dtype),p=n.dataIdMap.get(c.dataId).id;return zC(a,l,r.shape.length,u,i.length,Ht[c.dtype],p),c}var tme={kernelName:ba,backendName:"wasm",setupFunc:Qfe,kernelFunc:eme},LC;function nme(e){LC=e.wasm.cwrap(Wl,null,["number","array","number","number","number","bool","number","number"])}var sme=({inputs:e,backend:t,attrs:n})=>{let{x:s}=e,{k:r,sorted:a}=n,o=t.dataIdMap.get(s.dataId).id,i=new Uint8Array(new Int32Array(s.shape).buffer),l=s.shape.slice();l[l.length-1]=r;let u=t.makeOutput(l,s.dtype),c=t.dataIdMap.get(u.dataId).id,p=t.makeOutput(l,"int32"),d=t.dataIdMap.get(p.dataId).id;return LC(o,i,s.shape.length,Ht[s.dtype],r,a,c,d),[u,p]},rme={kernelName:Wl,backendName:"wasm",setupFunc:nme,kernelFunc:sme},BC;function ame(e){BC=e.wasm.cwrap(Vl,null,["number","number","bool","number","number","number","number","number","number","array","number","number","number","number","number"])}function ome(e){let{backend:t,inputs:n,attrs:s}=e,{image:r,transforms:a}=n,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=s,[c,p,d,h]=r.shape,[f,m]=u!=null?u:[p,d],g=[c,f,m,h],y=new Uint8Array(new Int32Array(v.computeStrides(r.shape)).buffer),x=t.makeOutput(g,r.dtype),A=t.dataIdMap.get(x.dataId).id,w=t.dataIdMap.get(r.dataId).id,S=t.dataIdMap.get(a.dataId).id,E=o==="nearest"?1:2,R;switch(i){case"constant":R=1;break;case"reflect":R=2;break;case"wrap":R=3;break;case"nearest":R=4;break;default:R=1;break}return BC(w,S,a.shape[0]>1,c,f,m,h,d,p,y,r.shape.length-1,E,R,l,A),x}var ime={kernelName:Vl,backendName:"wasm",setupFunc:ame,kernelFunc:ome};function lme(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r.shape[a],i=r.shape.length,l=new Array(i-1),u=0;for(let h=0;h<i;h++)h!==a&&(l[u++]=r.shape[h]);let c=new Array(o),p=new Array(i).fill(0),d=r.shape.slice();d[a]=1;for(let h=0;h<c.length;h++)p[a]=h,c[h]=rl({inputs:{x:r},attrs:{begin:p,size:d},backend:n});return c.map(({dataId:h,dtype:f})=>({dataId:h,dtype:f,shape:l}))}var ume={kernelName:Ul,backendName:"wasm",kernelFunc:lme};function cme(e){let{inputs:{x:t},backend:n}=e,s=n.makeOutput(t.shape,t.dtype);return n.typedArrayFromHeap(s).fill(0),s}var dme={kernelName:Gl,backendName:"wasm",kernelFunc:cme},pme=[Bce,Wce,Uce,jce,ede,sde,ode,ude,hde,xde,bde,vde,Ide,Sde,Nde,_de,Dde,$de,Ode,Lde,Vde,Hde,Xde,Kde,Yde,Jde,Qde,epe,spe,rpe,ope,upe,ppe,mpe,Ape,vpe,kpe,Spe,qce,Npe,Rpe,Dpe,$pe,Fpe,Ope,zpe,Bpe,Upe,Hpe,Xpe,Ype,ehe,nhe,ahe,ihe,lhe,dhe,fhe,yhe,xhe,whe,Ihe,Che,xC,Rhe,$he,Ohe,zhe,Bhe,Whe,Vhe,cde,Hhe,Xhe,Yhe,efe,tfe,nfe,afe,lfe,dfe,pfe,yde,mfe,yfe,bfe,kfe,Sfe,Tfe,Efe,Rfe,_fe,$fe,Ofe,Lfe,Wfe,Ufe,Hfe,qfe,Zfe,Yfe,Jfe,tme,rme,ime,Yce,ume,dme];for(let e of pme)cr(e);var dy=X();dy.registerFlag("WASM_HAS_SIMD_SUPPORT",async()=>WebAssembly.validate(new Uint8Array([0,97,115,109,1,0,0,0,1,4,1,96,0,0,3,2,1,0,10,9,1,7,0,65,0,253,15,26,11])));dy.registerFlag("WASM_HAS_MULTITHREAD_SUPPORT",async()=>{if(dy.get("IS_NODE"))return!1;try{return new MessageChannel().port1.postMessage(new SharedArrayBuffer(1)),WebAssembly.validate(new Uint8Array([0,97,115,109,1,0,0,0,1,4,1,96,0,0,3,2,1,0,5,4,1,3,1,1,10,11,1,9,0,65,0,254,16,2,0,26,11]))}catch(e){return!1}});var P7=lo(m_()),hme=lo(g_()),F7=lo(y_()),O7=P7.default||P7,fme=F7.default||F7,WC=class extends uc{constructor(e){super(),this.wasm=e,this.dataIdNextNumber=1,this.wasm.tfjs.initWithThreadsCount(VC),py=this.wasm.tfjs.getThreadsCount(),this.dataIdMap=new Op(this,sn())}write(e,t,n){let s={id:this.dataIdNextNumber++};return this.move(s,e,t,n,1),s}numDataIds(){return this.dataIdMap.numDataIds()}async time(e){let t=v.now();return e(),{kernelMs:v.now()-t}}move(e,t,n,s,r){let a=this.dataIdNextNumber++;if(s==="string"){let u=t;this.dataIdMap.set(e,{id:a,stringBytes:u,shape:n,dtype:s,memoryOffset:null,refCount:r});return}let o=v.sizeFromShape(n),i=o*v.bytesPerElement(s),l=this.wasm._malloc(i);this.dataIdMap.set(e,{id:a,memoryOffset:l,shape:n,dtype:s,refCount:r}),this.wasm.tfjs.registerTensor(a,o,l),t!=null&&this.wasm.HEAPU8.set(new Uint8Array(t.buffer,t.byteOffset,i),l)}async read(e){return this.readSync(e)}readSync(e,t,n){let{memoryOffset:s,dtype:r,shape:a,stringBytes:o}=this.dataIdMap.get(e);if(r==="string")return(t==null||t===0)&&(n==null||n>=o.length)?o:o.slice(t,n);t=t||0,n=n||v.sizeFromShape(a);let i=v.bytesPerElement(r),l=this.wasm.HEAPU8.slice(s+t*i,s+n*i);return yme(l.buffer,r)}disposeData(e,t=!1){if(this.dataIdMap.has(e)){let n=this.dataIdMap.get(e);if(n.refCount--,!t&&n.refCount>0)return!1;this.wasm._free(n.memoryOffset),this.wasm.tfjs.disposeData(n.id),this.dataIdMap.delete(e)}return!0}refCount(e){return this.dataIdMap.has(e)?this.dataIdMap.get(e).refCount:0}incRef(e){let t=this.dataIdMap.get(e);t!=null&&t.refCount++}floatPrecision(){return 32}getMemoryOffset(e){return this.dataIdMap.get(e).memoryOffset}dispose(){this.wasm.tfjs.dispose(),"PThread"in this.wasm&&this.wasm.PThread.terminateAllThreads(),this.wasm=null}memory(){return{unreliable:!1}}makeOutput(e,t,n){let s;if(n==null)s=this.write(null,e,t);else{let r=this.dataIdNextNumber++;s={id:r},this.dataIdMap.set(s,{id:r,memoryOffset:n,shape:e,dtype:t,refCount:1});let a=v.sizeFromShape(e);this.wasm.tfjs.registerTensor(r,a,n)}return{dataId:s,shape:e,dtype:t}}typedArrayFromHeap({shape:e,dtype:t,dataId:n}){let s=this.wasm.HEAPU8.buffer,{memoryOffset:r}=this.dataIdMap.get(n),a=v.sizeFromShape(e);switch(t){case"float32":return new Float32Array(s,r,a);case"int32":return new Int32Array(s,r,a);case"bool":return new Uint8Array(s,r,a);default:throw new Error(`Unknown dtype ${t}`)}}};function mme(e){return(t,n)=>(v.fetch(e,{credentials:"same-origin"}).then(s=>{s.ok||t.env.a(`failed to load wasm binary file at '${e}'`),s.arrayBuffer().then(r=>{WebAssembly.instantiate(r,t).then(a=>{n(a.instance,a.module)})})}),{})}function M7(e,t,n){if(Mm!=null)return Mm;let s="tfjs-backend-wasm.wasm";return e&&t?s="tfjs-backend-wasm-threaded-simd.wasm":e&&(s="tfjs-backend-wasm-simd.wasm"),mp!=null&&mp[s]!=null?mp[s]:n+s}async function gme(){let[e,t]=await Promise.all([X().getAsync("WASM_HAS_SIMD_SUPPORT"),X().getAsync("WASM_HAS_MULTITHREAD_SUPPORT")]);return new Promise((n,s)=>{let r={};r.locateFile=(i,l)=>{if(i.endsWith(".worker.js")){let u=hme.wasmWorkerContents.replace(/\n/g,"\\n"),c=new Blob([u],{type:"application/javascript"});return URL.createObjectURL(c)}return i.endsWith(".wasm")?M7(e,t,dp!=null?dp:l):l+i},eb&&(r.instantiateWasm=mme(M7(e,t,dp!=null?dp:"")));let a=!1;r.onAbort=()=>{if(a||gp)return;gp=!0,s({message:"Make sure the server can serve the `.wasm` file relative to the bundled js file. For more details see https://github.com/tensorflow/tfjs/blob/master/tfjs-backend-wasm/README.md#using-bundlers"})};let o;t&&e&&Mm==null?(r.mainScriptUrlOrBlob=new Blob(["var WasmBackendModuleThreadedSimd = "+O7.toString()],{type:"text/javascript"}),o=O7(r)):o=fme(r),o.then(i=>{a=!0,gp=!1;let l=null;i.tfjs={init:i.cwrap("init",null,[]),initWithThreadsCount:i.cwrap("init_with_threads_count",null,["number"]),getThreadsCount:i.cwrap("get_threads_count","number",[]),registerTensor:i.cwrap("register_tensor",null,["number","number","number"]),disposeData:i.cwrap("dispose_data",l,["number"]),dispose:i.cwrap("dispose",l,[])},n({wasm:i})}).catch(s)})}function yme(e,t){switch(t){case"float32":return new Float32Array(e);case"int32":return new Int32Array(e);case"bool":return new Uint8Array(e);default:throw new Error(`Unknown dtype ${t}`)}}var Ame=["tfjs-backend-wasm.wasm","tfjs-backend-wasm-simd.wasm","tfjs-backend-wasm-threaded-simd.wasm"],Mm=null,dp=null,mp={},gp=!1,eb=!1;function xme(e,t=!1){if(Py("setWasmPath has been deprecated in favor of setWasmPaths and will be removed in a future release."),gp)throw new Error("The WASM backend was already initialized. Make sure you call `setWasmPath()` before you call `tf.setBackend()` or `tf.ready()`");Mm=e,eb=t}function tb(e,t=!1){if(gp)throw new Error("The WASM backend was already initialized. Make sure you call `setWasmPaths()` before you call `tf.setBackend()` or `tf.ready()`");if(typeof e=="string")dp=e;else{mp=e;let n=Ame.filter(s=>mp[s]==null);if(n.length>0)throw new Error(`There were no entries found for the following binaries: ${n.join(",")}. Please either call setWasmPaths with a map providing a path for each binary, or with a string indicating the directory where all the binaries can be found.`)}eb=t}var VC=-1,py=-1;function bme(e){VC=e}function vme(){if(py===-1)throw new Error("WASM backend not initialized.");return py}var wme="3.19.0",kme=2;jl("wasm",async()=>{let{wasm:e}=await gme();return new WC(e)},kme);var Ia=X();Ia.registerFlag("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE",()=>15);Ia.registerFlag("WEBGPU_CPU_FORWARD",()=>!0);Ia.registerFlag("WEBGPU_MATMUL_WORK_PER_THREAD",()=>4);Ia.registerFlag("WEBGPU_MATMUL_PROGRAM_TYPE",()=>-1);Ia.registerFlag("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE",()=>!1);Ia.registerFlag("WEBGPU_USE_LOW_POWER_GPU",()=>!1);Ia.registerFlag("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD",()=>1e3);Ia.registerFlag("WEBGPU_USE_PROFILE_TOOL",()=>!1);Ia.registerFlag("WEBGPU_IMPORT_EXTERNAL_TEXTURE",()=>!1);var Ye;(function(e){e[e.MUL=0]="MUL",e[e.ADD=1]="ADD",e[e.SUB=2]="SUB",e[e.DIV=3]="DIV",e[e.EQUAL=4]="EQUAL",e[e.GREATER=5]="GREATER",e[e.GREATER_EQUAL=6]="GREATER_EQUAL",e[e.LESS=7]="LESS",e[e.LESS_EQUAL=8]="LESS_EQUAL",e[e.LOGICAL_AND=9]="LOGICAL_AND",e[e.NOT_EQUAL=10]="NOT_EQUAL",e[e.SQUARED_DIFFERENCE=11]="SQUARED_DIFFERENCE",e[e.INT_DIV=12]="INT_DIV",e[e.POW=13]="POW",e[e.PRELU=14]="PRELU",e[e.MAX=15]="MAX",e[e.MIN=16]="MIN",e[e.COMPLEX_MULTIPLY_REAL=17]="COMPLEX_MULTIPLY_REAL",e[e.COMPLEX_MULTIPLY_IMAG=18]="COMPLEX_MULTIPLY_IMAG"})(Ye||(Ye={}));var Ime="return a + b;",Sme="return areal * breal - aimag * bimag;",Cme="return areal * bimag + aimag * breal;",Tme="return a / b;",Nme="return a * b;",Eme="return (a - b) * (a - b);",Rme="return a - b;",_me="return f32(a == b);",Dme="return vec4<f32>(a == b);",$me="return f32(a > b);",Pme="return vec4<f32>(a > b);",Fme="return f32(a >= b);",Ome="return vec4<f32>(a >= b);",Mme="return f32(a < b);",zme="return vec4<f32>(a < b);",Lme="return f32(a <= b);",Bme="return vec4<f32>(a <= b);",Wme="return f32(f32(a) >= 1.0 && f32(b) >= 1.0);",Vme=`return (vec4<f32>(a >= vec4<f32>(1.0)) *
   vec4<f32>(b >= vec4<f32>(1.0)));`,Ume=`
   if (isnan(a)) { return a; }
   if (isnan(b)) { return b; }
@@ -4773,7 +4773,7 @@ return a / b;`,Gie=`
     return resultTemp;
   `:n+`
     return ${e}(a, b);
-  `}function Lm(e,t){switch(e){case Ye.MUL:return Nme;case Ye.ADD:return Ime;case Ye.SUB:return Rme;case Ye.DIV:return Tme;case Ye.EQUAL:return t?Dme:_me;case Ye.GREATER:return t?Pme:$me;case Ye.GREATER_EQUAL:return t?Ome:Fme;case Ye.LESS:return t?zme:Mme;case Ye.LESS_EQUAL:return t?Bme:Lme;case Ye.LOGICAL_AND:return t?Vme:Wme;case Ye.NOT_EQUAL:return t?qme:jme;case Ye.SQUARED_DIFFERENCE:return Eme;case Ye.INT_DIV:return t?Hme:Gme;case Ye.PRELU:return t?Yme:Zme;case Ye.MAX:return z7("max",t);case Ye.MIN:return z7("min",t);case Ye.POW:return t?Kme:Xme;case Ye.COMPLEX_MULTIPLY_REAL:return Sme;case Ye.COMPLEX_MULTIPLY_IMAG:return Cme;default:throw new Error(`BinaryType ${e} is not implemented!`)}}var Fe;(function(e){e[e.ABS=0]="ABS",e[e.CEIL=1]="CEIL",e[e.COS=2]="COS",e[e.COSH=3]="COSH",e[e.ELU=4]="ELU",e[e.EXP=5]="EXP",e[e.EXPM1=6]="EXPM1",e[e.FLOOR=7]="FLOOR",e[e.LINEAR=8]="LINEAR",e[e.LOG=9]="LOG",e[e.LOGICAL_NOT=10]="LOGICAL_NOT",e[e.NEG=11]="NEG",e[e.RELU=12]="RELU",e[e.RELU6=13]="RELU6",e[e.LEAKYRELU=14]="LEAKYRELU",e[e.RSQRT=15]="RSQRT",e[e.SIN=16]="SIN",e[e.SINH=17]="SINH",e[e.SIGMOID=18]="SIGMOID",e[e.SQRT=19]="SQRT",e[e.SQUARE=20]="SQUARE",e[e.TANH=21]="TANH",e[e.TO_INT=22]="TO_INT"})(Fe||(Fe={}));var Jme="return abs(a);",Qme="return ceil(a);",e0e="return cos(a);",t0e=`
+  `}function zm(e,t){switch(e){case Ye.MUL:return Nme;case Ye.ADD:return Ime;case Ye.SUB:return Rme;case Ye.DIV:return Tme;case Ye.EQUAL:return t?Dme:_me;case Ye.GREATER:return t?Pme:$me;case Ye.GREATER_EQUAL:return t?Ome:Fme;case Ye.LESS:return t?zme:Mme;case Ye.LESS_EQUAL:return t?Bme:Lme;case Ye.LOGICAL_AND:return t?Vme:Wme;case Ye.NOT_EQUAL:return t?qme:jme;case Ye.SQUARED_DIFFERENCE:return Eme;case Ye.INT_DIV:return t?Hme:Gme;case Ye.PRELU:return t?Yme:Zme;case Ye.MAX:return z7("max",t);case Ye.MIN:return z7("min",t);case Ye.POW:return t?Kme:Xme;case Ye.COMPLEX_MULTIPLY_REAL:return Sme;case Ye.COMPLEX_MULTIPLY_IMAG:return Cme;default:throw new Error(`BinaryType ${e} is not implemented!`)}}var Fe;(function(e){e[e.ABS=0]="ABS",e[e.CEIL=1]="CEIL",e[e.COS=2]="COS",e[e.COSH=3]="COSH",e[e.ELU=4]="ELU",e[e.EXP=5]="EXP",e[e.EXPM1=6]="EXPM1",e[e.FLOOR=7]="FLOOR",e[e.LINEAR=8]="LINEAR",e[e.LOG=9]="LOG",e[e.LOGICAL_NOT=10]="LOGICAL_NOT",e[e.NEG=11]="NEG",e[e.RELU=12]="RELU",e[e.RELU6=13]="RELU6",e[e.LEAKYRELU=14]="LEAKYRELU",e[e.RSQRT=15]="RSQRT",e[e.SIN=16]="SIN",e[e.SINH=17]="SINH",e[e.SIGMOID=18]="SIGMOID",e[e.SQRT=19]="SQRT",e[e.SQUARE=20]="SQUARE",e[e.TANH=21]="TANH",e[e.TO_INT=22]="TO_INT"})(Fe||(Fe={}));var Jme="return abs(a);",Qme="return ceil(a);",e0e="return cos(a);",t0e=`
   let e2x = exp(-a);
   return (e2x + 1.0 / e2x) / 2.0;
 `,n0e="return exp(a) - 1.0;",s0e="if (a >= 0.0) { return a; }  return (exp(a) - 1.0);",r0e=`
@@ -4803,28 +4803,28 @@ return a / b;`,Gie=`
 `,v0e="return sqrt(a);",w0e="return a * a;",k0e=`
   let e2x = exp(-2.0 * abs(a));
   return sign(a) * (1.0 - e2x) / (1.0 + e2x);
-`,I0e="return f32(i32((a)));";function Oi(e,t){switch(e){case Fe.ABS:return Jme;case Fe.COS:return e0e;case Fe.COSH:return t0e;case Fe.CEIL:return Qme;case Fe.ELU:return t?r0e:s0e;case Fe.EXP:return a0e;case Fe.EXPM1:return n0e;case Fe.FLOOR:return o0e;case Fe.LINEAR:return i0e;case Fe.LOG:return l0e;case Fe.LOGICAL_NOT:return u0e;case Fe.NEG:return c0e;case Fe.LEAKYRELU:return t?p0e:d0e;case Fe.RELU:return t?g0e:h0e;case Fe.RELU6:return t?m0e:f0e;case Fe.RSQRT:return y0e;case Fe.SIGMOID:return A0e;case Fe.SIN:return x0e;case Fe.SINH:return b0e;case Fe.SQRT:return v0e;case Fe.SQUARE:return w0e;case Fe.TANH:return k0e;case Fe.TO_INT:return I0e;default:throw new Error(`BinaryType ${e} is not implemented!`)}}var nn=e=>{switch(e){case 1:return"f32";case 2:return"vec2<f32>";case 3:return"vec3<f32>";case 4:return"vec4<f32>";default:throw new Error(`${e}-component is not supported.`)}};function Ca(e,t=!1,n=!1,s=3){if(e===null)return"";let r="";if(e==="linear")r=Oi(Fe.LINEAR);else if(e==="relu")r=Oi(Fe.RELU,n);else if(e==="elu")r=Oi(Fe.ELU,n);else if(e==="relu6")r=Oi(Fe.RELU6,n);else if(e==="prelu")r=Lm(Ye.PRELU,n);else if(e==="sigmoid")r=Oi(Fe.SIGMOID,n);else if(e==="leakyrelu")r=Oi(Fe.LEAKYRELU,n);else throw new Error(`Activation ${e} has not been implemented for the WebGPU backend.`);let o=nn(n?4:1),i="";return t?i=`
+`,I0e="return f32(i32((a)));";function Fi(e,t){switch(e){case Fe.ABS:return Jme;case Fe.COS:return e0e;case Fe.COSH:return t0e;case Fe.CEIL:return Qme;case Fe.ELU:return t?r0e:s0e;case Fe.EXP:return a0e;case Fe.EXPM1:return n0e;case Fe.FLOOR:return o0e;case Fe.LINEAR:return i0e;case Fe.LOG:return l0e;case Fe.LOGICAL_NOT:return u0e;case Fe.NEG:return c0e;case Fe.LEAKYRELU:return t?p0e:d0e;case Fe.RELU:return t?g0e:h0e;case Fe.RELU6:return t?m0e:f0e;case Fe.RSQRT:return y0e;case Fe.SIGMOID:return A0e;case Fe.SIN:return x0e;case Fe.SINH:return b0e;case Fe.SQRT:return v0e;case Fe.SQUARE:return w0e;case Fe.TANH:return k0e;case Fe.TO_INT:return I0e;default:throw new Error(`BinaryType ${e} is not implemented!`)}}var nn=e=>{switch(e){case 1:return"f32";case 2:return"vec2<f32>";case 3:return"vec3<f32>";case 4:return"vec4<f32>";default:throw new Error(`${e}-component is not supported.`)}};function Sa(e,t=!1,n=!1,s=3){if(e===null)return"";let r="";if(e==="linear")r=Fi(Fe.LINEAR);else if(e==="relu")r=Fi(Fe.RELU,n);else if(e==="elu")r=Fi(Fe.ELU,n);else if(e==="relu6")r=Fi(Fe.RELU6,n);else if(e==="prelu")r=zm(Ye.PRELU,n);else if(e==="sigmoid")r=Fi(Fe.SIGMOID,n);else if(e==="leakyrelu")r=Fi(Fe.LEAKYRELU,n);else throw new Error(`Activation ${e} has not been implemented for the WebGPU backend.`);let o=nn(n?4:1),i="";return t?i=`
       fn activation(a : ${o}, coords : vec${s}<i32>) -> ${o} {
         let b = getPreluActivationWeightsByOutputCoords(coords);
         ${r}
       }`:i=`
       fn activation(a : ${o}, coords : vec${s}<i32>) -> ${o} {
         ${r}
-      }`,i}function dd(e,t){return`
+      }`,i}function cd(e,t){return`
       ${e?"value = value + getBiasByOutputCoords(coords);":""}
       ${t?"value = activation(value, coords);":""}
-      `}function S0e(e,t){if(Math.max(...e)>3)throw new Error("Cannot symbolically compute strides for rank > 4 tensor.");let n=e.length,s=e.map(a=>`${t}[${a}]`),r=new Array(n-1);r[n-2]=s[n-1];for(let a=n-3;a>=0;--a)r[a]=`(${r[a+1]} * ${s[a+1]})`;return r}var C0e=(e,t,n,s)=>{let r={dtype:s.dtype,shape:s.shape},a=T0e(n,r,t),o=e.createShaderModule({code:a,label:t.constructor.name});return e.createComputePipeline({compute:{module:o,entryPoint:"main"},label:t.constructor.name,layout:"auto"})};function Tn(e){if(e<=1)return"i32";if(e===2)return"vec2<i32>";if(e===3)return"vec3<i32>";if(e===4)return"vec4<i32>";if(e===5)return"vec5";if(e===6)return"vec6";throw Error(`GPU for rank ${e} is not yet supported`)}function Za(e){if(e===0)return"x";if(e===1)return"y";if(e===2)return"z";if(e===3)return"w";if(e===4)return"u";if(e===5)return"v";throw Error(`Index ${e} is not yet supported`)}function lt(){return`
-    ${pd()}
+      `}function S0e(e,t){if(Math.max(...e)>3)throw new Error("Cannot symbolically compute strides for rank > 4 tensor.");let n=e.length,s=e.map(a=>`${t}[${a}]`),r=new Array(n-1);r[n-2]=s[n-1];for(let a=n-3;a>=0;--a)r[a]=`(${r[a+1]} * ${s[a+1]})`;return r}var C0e=(e,t,n,s)=>{let r={dtype:s.dtype,shape:s.shape},a=T0e(n,r,t),o=e.createShaderModule({code:a,label:t.constructor.name});return e.createComputePipeline({compute:{module:o,entryPoint:"main"},label:t.constructor.name,layout:"auto"})};function Tn(e){if(e<=1)return"i32";if(e===2)return"vec2<i32>";if(e===3)return"vec3<i32>";if(e===4)return"vec4<i32>";if(e===5)return"vec5";if(e===6)return"vec6";throw Error(`GPU for rank ${e} is not yet supported`)}function Ka(e){if(e===0)return"x";if(e===1)return"y";if(e===2)return"z";if(e===3)return"w";if(e===4)return"u";if(e===5)return"v";throw Error(`Index ${e} is not yet supported`)}function lt(){return`
+    ${dd()}
       let index = getGlobalIndex();
-`}function pd(){return`
-  ${T2()}
+`}function dd(){return`
+  ${C2()}
   fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,
           @builtin(global_invocation_id) GlobalId : vec3<u32>,
           @builtin(num_workgroups) NumWorkgroups: vec3<u32>) {
     localId = LocalId;
     globalId = GlobalId;
     numWorkgroups = NumWorkgroups;
-`}function T2(){return`
+`}function C2(){return`
   @compute @workgroup_size(workGroupSizeX, workGroupSizeY, workGroupSizeZ)
 `}function T0e(e,t,n){let s=[];if(s.push(`
       const workGroupSizeX = ${n.workGroupSize[0]}u;
@@ -4855,7 +4855,7 @@ return a / b;`,Gie=`
           outShapeStrides : vec2<i32>,
         };
 
-        @group(0) @binding(0) var<storage, read_write> result: array<${Ap(t.dtype,n.isVec4)}>;
+        @group(0) @binding(0) var<storage, read_write> result: array<${yp(t.dtype,n.isVec4)}>;
         @group(0) @binding(2) var<uniform> uniforms: Uniform;
       `),[L7,s.join(`
 `),B7(t.shape),n.getUserCode()].join(`
@@ -4863,9 +4863,9 @@ return a / b;`,Gie=`
          outShapeStrides: ${u}, `,n.size&&(r&&(o+="@align(16) "),r=!1,o+="size : i32, "),n.uniforms&&(r&&(o+="@align(16) "),o+=n.uniforms),o+="};",s.push(o),n.atomic?s.push(`
       @group(0) @binding(0) var<storage, read_write> result: array<atomic<i32>>;
     `):s.push(`
-      @group(0) @binding(0) var<storage, read_write> result: array<${Ap(t.dtype,n.isVec4)}>;
+      @group(0) @binding(0) var<storage, read_write> result: array<${yp(t.dtype,n.isVec4)}>;
     `),n.variableNames.forEach((f,m)=>{s.push(`
-      @group(0) @binding(${1+m}) var<storage, read> ${f}: array<${n.variableTypes?n.variableTypes[m]:Ap(e[m].dtype,n.isVec4)}>;
+      @group(0) @binding(${1+m}) var<storage, read> ${f}: array<${n.variableTypes?n.variableTypes[m]:yp(e[m].dtype,n.isVec4)}>;
         `)}),o!==""&&s.push(`
       @group(0) @binding(${1+n.variableNames.length}) var<uniform> uniforms: Uniforms;
       `);let c=D0e(t.shape,n.dispatchLayout),p=[L7,s.join(`
@@ -4932,7 +4932,7 @@ return a / b;`,Gie=`
 `;function B7(e){let t=e.length;if(t<=1)return"fn getCoordsFromIndex(index : i32) -> i32 { return index; }";let n=v.computeStrides(e),s=Tn(t),r=[];for(let o=0;o<t;o++)r.push(`d${o}`);if(n.length===1)return`    fn getCoordsFromIndex(index : i32) -> vec2<i32> {
       let d0 = index / uniforms.outShapeStrides; let d1 = index - d0 * uniforms.outShapeStrides;
       return vec2<i32>(d0, d1);
-    }`;let a;return a="var index2 = index;"+n.map((o,i)=>{let l=`let ${r[i]} = index2 / uniforms.outShapeStrides.${Za(i)}`,u=i===n.length-1?`let ${r[i+1]} = index2 - ${r[i]} * uniforms.outShapeStrides.${Za(i)}`:`index2 = index2 - ${r[i]} * uniforms.outShapeStrides.${Za(i)}`;return`${l}; ${u};`}).join(""),`
+    }`;let a;return a="var index2 = index;"+n.map((o,i)=>{let l=`let ${r[i]} = index2 / uniforms.outShapeStrides.${Ka(i)}`,u=i===n.length-1?`let ${r[i+1]} = index2 - ${r[i]} * uniforms.outShapeStrides.${Ka(i)}`:`index2 = index2 - ${r[i]} * uniforms.outShapeStrides.${Ka(i)}`;return`${l}; ${u};`}).join(""),`
     fn getCoordsFromIndex(index : i32) -> ${s} {
       ${a}
       return ${s}(${r.join(",")});
@@ -4987,8 +4987,8 @@ return a / b;`,Gie=`
     fn ${o}Coords(coords : ${u}) -> f32{
       return get${a}();
     }
-  `;l<2&&c.length>=1?d="coords = 0;":d=c.map(g=>`coords.${Za(g+p)} = 0;`).join(`
-`);let h="";if(l<2&&i>0)h="coords";else if(l>1){let g=Tn(i),y=e.shape.map((x,A)=>`coords.${Za(A+p)}`).join(", ");h=`${g}(${y})`}else h="coords";let f=`uniforms.${r.charAt(0).toLowerCase()+r.slice(1)}Shape`,m=`${i}D`;return n?`
+  `;l<2&&c.length>=1?d="coords = 0;":d=c.map(g=>`coords.${Ka(g+p)} = 0;`).join(`
+`);let h="";if(l<2&&i>0)h="coords";else if(l>1){let g=Tn(i),y=e.shape.map((x,A)=>`coords.${Ka(A+p)}`).join(", ");h=`${g}(${y})`}else h="coords";let f=`uniforms.${r.charAt(0).toLowerCase()+r.slice(1)}Shape`,m=`${i}D`;return n?`
     fn ${o}Index(globalIndex : i32) -> vec4<f32> {
       var coords = getCoordsFromIndex(globalIndex);
       ${d}
@@ -5052,7 +5052,7 @@ return a / b;`,Gie=`
               coords.u * uniforms.outShapeStrides.u +
               coords.v;
         }
-        `;break;default:v.assert(!1,()=>`Unsupported ${e}D shape`);break}return t}function GC(e){return e.dispatch[1]===1&&e.dispatch[2]===1}function Ap(e,t){return e==="float32"?t?"vec4<f32>":"f32":e==="int32"||e==="bool"?t?"vec4<i32>":"i32":e}function P0e(e,t,n){let s=e.length,r=Ap(t,n),a;if(n?a=`fn setOutputAtIndex(flatIndex : i32, value : vec4<f32>) {
+        `;break;default:v.assert(!1,()=>`Unsupported ${e}D shape`);break}return t}function GC(e){return e.dispatch[1]===1&&e.dispatch[2]===1}function yp(e,t){return e==="float32"?t?"vec4<f32>":"f32":e==="int32"||e==="bool"?t?"vec4<i32>":"i32":e}function P0e(e,t,n){let s=e.length,r=yp(t,n),a;if(n?a=`fn setOutputAtIndex(flatIndex : i32, value : vec4<f32>) {
       result[flatIndex] = ${r}(value);
     }
     fn setOutputAtIndexI32(flatIndex : i32, value : vec4<i32>) {
@@ -5080,7 +5080,7 @@ return a / b;`,Gie=`
         let flatIndex = getOutputIndexFromCoords(${i}(${o.join(", ")}));
         setOutputAtIndexI32(flatIndex, value);
       }
-    `}return a}var HC={};Ve(HC,{ArrayBufferToTypedArray:()=>XC,GPUBytesPerElement:()=>qC,MatMulProgramType:()=>Hs,computeDispatch:()=>We,computeWorkGroupSizeForConv2d:()=>nb,computeWorkGroupSizeForMatMul:()=>jC,computeWorkPerThreadForConv2d:()=>sb,flatDispatchLayout:()=>at,isWebGPUSupported:()=>rb,tilesFitEvenlyIntoShape:()=>F0e});var qi=e=>{let t=1;for(let n=0;n<e.length;n++)t*=e[n];return t};function F0e(e,t){if(e.length!==t.length)throw new Error(`Cannot compute whether rank ${e.length} tiles fit evenly into rank ${t.length} shape - ranks must match.`);return t.every((n,s)=>n%e[s]===0)}function We(e,t,n=[1,1,1],s=[1,1,1]){let[r,a,o]=[Math.ceil(qi(e.x.map(i=>t[i]))/(n[0]*s[0])),e.y?Math.ceil(qi(e.y.map(i=>t[i]))/(n[1]*s[1])):1,e.z?Math.ceil(qi(e.z.map(i=>t[i]))/(n[2]*s[2])):1];return[r,a,o]}function nb(e,t,n=!1){if(n)return[8,8,1];let s=qi(e.x.map(a=>t[a])),r=qi(e.y.map(a=>t[a]));return s<=4?[4,16,1]:r<=4?[16,4,1]:[16,16,1]}function jC(e,t,n){return e===1?[32,1,1]:n===1?[1,32,1]:[8,8,1]}function sb(e,t,n=!1){if(n)return[4,4,1];let s=qi(e.x.map(a=>t[a])),r=qi(e.y.map(a=>t[a]));return s<=4?[1,2,1]:r<=4?[2,1,1]:[2,2,1]}function at(e){return{x:e.map((t,n)=>n)}}function qC(e){if(e==="float32"||e==="int32"||e==="bool"||e==="string")return 4;if(e==="complex64")return 8;throw new Error(`Unknown dtype ${e}`)}function XC(e,t){if(t==="float32")return new Float32Array(e);if(t==="int32")return new Int32Array(e);if(t==="bool"||t==="string")return Uint8Array.from(new Int32Array(e));throw new Error(`Unknown dtype ${t}`)}function rb(){return(typeof window!="undefined"||typeof WorkerGlobalScope!="undefined")&&!!navigator.gpu}var Hs;(function(e){e[e.MatMulPackedVec4Program=0]="MatMulPackedVec4Program",e[e.MatMulReduceProgram=1]="MatMulReduceProgram",e[e.MatMulSplitKProgram=2]="MatMulSplitKProgram",e[e.MatMulSmallOutputSizeProgram=3]="MatMulSmallOutputSizeProgram",e[e.MatMulPackedProgram=4]="MatMulPackedProgram",e[e.MatMulMax=5]="MatMulMax"})(Hs||(Hs={}));function KC(e,t,n,s,r=!1,a=!1,o=!1,i=1){v.assert(n&&i===1||!n,()=>`transposeA ${n} is not compatible with component size ${i}`);let l=`
+    `}return a}var HC={};Ve(HC,{ArrayBufferToTypedArray:()=>XC,GPUBytesPerElement:()=>qC,MatMulProgramType:()=>Hs,computeDispatch:()=>We,computeWorkGroupSizeForConv2d:()=>nb,computeWorkGroupSizeForMatMul:()=>jC,computeWorkPerThreadForConv2d:()=>sb,flatDispatchLayout:()=>at,isWebGPUSupported:()=>rb,tilesFitEvenlyIntoShape:()=>F0e});var ji=e=>{let t=1;for(let n=0;n<e.length;n++)t*=e[n];return t};function F0e(e,t){if(e.length!==t.length)throw new Error(`Cannot compute whether rank ${e.length} tiles fit evenly into rank ${t.length} shape - ranks must match.`);return t.every((n,s)=>n%e[s]===0)}function We(e,t,n=[1,1,1],s=[1,1,1]){let[r,a,o]=[Math.ceil(ji(e.x.map(i=>t[i]))/(n[0]*s[0])),e.y?Math.ceil(ji(e.y.map(i=>t[i]))/(n[1]*s[1])):1,e.z?Math.ceil(ji(e.z.map(i=>t[i]))/(n[2]*s[2])):1];return[r,a,o]}function nb(e,t,n=!1){if(n)return[8,8,1];let s=ji(e.x.map(a=>t[a])),r=ji(e.y.map(a=>t[a]));return s<=4?[4,16,1]:r<=4?[16,4,1]:[16,16,1]}function jC(e,t,n){return e===1?[32,1,1]:n===1?[1,32,1]:[8,8,1]}function sb(e,t,n=!1){if(n)return[4,4,1];let s=ji(e.x.map(a=>t[a])),r=ji(e.y.map(a=>t[a]));return s<=4?[1,2,1]:r<=4?[2,1,1]:[2,2,1]}function at(e){return{x:e.map((t,n)=>n)}}function qC(e){if(e==="float32"||e==="int32"||e==="bool"||e==="string")return 4;if(e==="complex64")return 8;throw new Error(`Unknown dtype ${e}`)}function XC(e,t){if(t==="float32")return new Float32Array(e);if(t==="int32")return new Int32Array(e);if(t==="bool"||t==="string")return Uint8Array.from(new Int32Array(e));throw new Error(`Unknown dtype ${t}`)}function rb(){return(typeof window!="undefined"||typeof WorkerGlobalScope!="undefined")&&!!navigator.gpu}var Hs;(function(e){e[e.MatMulPackedVec4Program=0]="MatMulPackedVec4Program",e[e.MatMulReduceProgram=1]="MatMulReduceProgram",e[e.MatMulSplitKProgram=2]="MatMulSplitKProgram",e[e.MatMulSmallOutputSizeProgram=3]="MatMulSmallOutputSizeProgram",e[e.MatMulPackedProgram=4]="MatMulPackedProgram",e[e.MatMulMax=5]="MatMulMax"})(Hs||(Hs={}));function KC(e,t,n,s,r=!1,a=!1,o=!1,i=1){v.assert(n&&i===1||!n,()=>`transposeA ${n} is not compatible with component size ${i}`);let l=`
       let batch = ${e?"0":"batchIn"};
       let batchASize = uniforms.aShape[1] * uniforms.aShape[2];
       ${n?`value = A[(batch * batchASize + col * uniforms.aShape[2] + row) / ${i}];`:`value = A[(batch * batchASize + row * uniforms.aShape[2] + col) / ${i}];`}
@@ -5106,7 +5106,7 @@ return a / b;`,Gie=`
     ${u}
     return value;
   }
-  `}function N2(e,t,n,s,r,a,o=!1,i=!1,l=!1,u=1){return`
+  `}function T2(e,t,n,s,r,a,o=!1,i=!1,l=!1,u=1){return`
   ${KC(n,s,r,a,o,i,l,u)}
   fn mm_write(batch: i32, row: i32, colIn: i32, valueIn: ${nn(u)}) {
     let col = colIn * ${u};
@@ -5114,7 +5114,7 @@ return a / b;`,Gie=`
     {
       var value = valueIn;
       let coords = vec3<i32>(batch, row, col);
-      ${dd(e,t)}
+      ${cd(e,t)}
       setOutputAtCoords(coords[0], coords[1], coords[2], value);
     }
   }
@@ -5227,7 +5227,7 @@ return a / b;`,Gie=`
     const TileSize = ${e[0]*4};
     var<workgroup> mm_Asub : array<vec4<f32>, ${e[0]}>;
 
-    ${pd()}
+    ${dd()}
       let tileCol = i32(localId.x);
       let globalCol = i32(globalId.x);
       let globalRow = i32(globalId.y);
@@ -5262,8 +5262,8 @@ return a / b;`,Gie=`
       mm_write(batch, globalRow, globalCol, acc);
     }
   `}var B0e=class{constructor(e,t,n,s,r,a=!1,o=!1,i=null,l=null,u=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[16,16,1],this.outputShape=t,this.dispatchLayout={x:[2],y:[1],z:[0]};let c=a?e[1]:e[2];this.workGroupSize=jC(t[1],c,t[2]),(t[1]===1||t[2]===1)&&(n=1),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[n,n,1]),v.arraysEqual(this.dispatch,[1,1,1])&&(n=1,this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[n,n,1]));let p=i!=null,d=u!=null;p&&this.variableNames.push("bias"),d&&this.variableNames.push("preluActivationWeights"),this.workPerThread=n,this.transposeA=a,this.transposeB=o,this.addBias=p,this.activation=l,this.hasPreluActivationWeights=d,this.batchAEqualOne=s,this.batchBEqualOne=r,[this.fitAOuter,this.fitBOuter,this.fitInner]=this.getShapeFit(t[1],t[2],c),this.shaderKey=`matMulPacked_${this.workPerThread}_${a}_${o}_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.outputShape[1]>1}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getShapeFit(e,t,n){let s=this.workGroupSize[1]*this.workPerThread,r=this.workGroupSize[0]*this.workPerThread;this.tileInner=32,this.outputShape[1]===1&&(this.tileInner=this.workGroupSize[0]*4);let a=e%s===0,o=t%r===0,i=n%this.tileInner===0;return[a,o,i]}getUserCode(){return`
-      ${Ca(this.activation,this.hasPreluActivationWeights)}
-      ${N2(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,!1,this.transposeB,this.fitAOuter,this.fitBOuter,this.fitInner)}
+      ${Sa(this.activation,this.hasPreluActivationWeights)}
+      ${T2(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,!1,this.transposeB,this.fitAOuter,this.fitBOuter,this.fitInner)}
       ${this.outputShape[1]>1?ab([this.workPerThread,this.workPerThread,1],this.workGroupSize,this.transposeA,this.tileInner):L0e(this.workGroupSize,this.transposeA)}
     `}},W0e=(e,t)=>e?`
         mm_Asub[inputRow][inputCol] = mm_readA(batch,
@@ -5360,12 +5360,12 @@ return a / b;`,Gie=`
         mm_write(batch, globalRow + innerRow, globalCol, acc[innerRow]);
     }
   }`}var U0e=class{constructor(e,t,n,s,r=!1,a=null,o=null,i=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[8,8,1],this.isVec4=!0,this.outputShape=t,this.dispatchLayout={x:[2],y:[1],z:[0]},t[1]===1&&!r?this.elementsPerThread=[4,1,1]:this.elementsPerThread=[4,4,1],this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,this.elementsPerThread);let l=a!=null,u=i!=null;l&&this.variableNames.push("bias"),u&&this.variableNames.push("preluActivationWeights"),this.tileAOuter=t[1]===1&&!r?1:this.workGroupSize[1]*this.elementsPerThread[1],this.tileBOuter=this.workGroupSize[0]*this.elementsPerThread[0],this.tileInner=this.tileBOuter,this.aShape=e,this.addBias=l,this.activation=o,this.hasPreluActivationWeights=u,this.batchAEqualOne=n,this.batchBEqualOne=s,this.transposeA=r;let c=r?e[1]:e[2];this.fitAOuter=t[1]%this.tileAOuter===0,this.fitBOuter=t[2]%this.tileBOuter===0,this.fitInner=c%this.tileInner===0,this.shaderKey=`matMulPackedVec4_${this.activation}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.elementsPerThread}_${this.batchAEqualOne}_${this.batchBEqualOne}_${this.transposeA}`}getUserCode(){return`
-      ${Ca(this.activation,this.hasPreluActivationWeights,!0)}
-      ${N2(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,!1,!1,this.fitAOuter,this.fitBOuter,this.fitInner,4)}
+      ${Sa(this.activation,this.hasPreluActivationWeights,!0)}
+      ${T2(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,!1,!1,this.fitAOuter,this.fitBOuter,this.fitInner,4)}
       ${ob(this.elementsPerThread,this.tileAOuter,this.tileBOuter,this.tileInner,4,this.transposeA)}
     `}};function G0e(){return`
     var<workgroup> sumValues : array<f32, workGroupSizeX>;
-    ${pd()}
+    ${dd()}
       let coords = getOutputCoords();
       let batch = coords[0];
       let row = coords[1];
@@ -5395,8 +5395,8 @@ return a / b;`,Gie=`
       }
     }
   `}var H0e=class{constructor(e,t,n,s=!1,r=!1,a=null,o=null,i=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout={x:[],y:[1,2],z:[0]},this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize);let l=a!=null,u=i!=null;l&&this.variableNames.push("bias"),u&&this.variableNames.push("preluActivationWeights"),this.transposeA=s,this.transposeB=r,this.addBias=l,this.activation=o,this.hasPreluActivationWeights=u,this.batchAEqualOne=t,this.batchBEqualOne=n,this.shaderKey=`matMulReduce_${this.activation}_${s}_${r}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getUserCode(){return`
-      ${Ca(this.activation,this.hasPreluActivationWeights)}
-      ${N2(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,this.transposeA,this.transposeB)}
+      ${Sa(this.activation,this.hasPreluActivationWeights)}
+      ${T2(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,this.transposeA,this.transposeB)}
       ${G0e()}
     `}};function j0e(e){let t=e[1],n=e[0],s=t>n?t:n;return`
   var<workgroup> mm_Asub : array<array<f32, ${s}>, ${t}>;
@@ -5408,7 +5408,7 @@ return a / b;`,Gie=`
   // shared memory, so it is instruction-Level parallelism for arithmetic
   // operations and others handle IO operations between barrier api, makes ALU
   // and load/store units work simultaneously, could improves the performance.
-  ${pd()}
+  ${dd()}
     let tileRow = i32(localId.y);
     let tileCol = i32(localId.x);
     let globalRow = i32(globalId.y);
@@ -5449,8 +5449,8 @@ return a / b;`,Gie=`
     mm_write(batch, globalRow, globalCol, acc);
   }
   `}var q0e=class{constructor(e,t,n,s=!1,r=!1,a=null,o=null,i=null){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[16,8,1],this.outputShape=n,this.dispatchLayout={x:[2],y:[1],z:[0]},this.dispatch=[Math.ceil(n[2]/this.workGroupSize[0]),Math.ceil(n[1]/this.workGroupSize[1]),n[0]];let l=a!=null;l&&this.variableNames.push("bias");let u=i!=null;u&&this.variableNames.push("preluActivationWeights"),this.transposeA=s,this.transposeB=r,this.addBias=l,this.activation=o,this.hasPreluActivationWeights=u,this.batchAEqualOne=e[0]===1,this.batchBEqualOne=t[0]===1,this.shaderKey=`matMulSmallOutputSize_${this.activation}_${s}_${r}_${this.batchAEqualOne}_${this.batchBEqualOne}`}getUserCode(){return`
-      ${Ca(this.activation,this.hasPreluActivationWeights)}
-      ${N2(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,this.transposeA,this.transposeB)}
+      ${Sa(this.activation,this.hasPreluActivationWeights)}
+      ${T2(this.addBias,this.activation,this.batchAEqualOne,this.batchBEqualOne,this.transposeA,this.transposeB)}
       ${j0e(this.workGroupSize)}
     `}},X0e=class{constructor(e,t,n,s,r=!1,a=!1){this.variableNames=["A","B"],this.uniforms="dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.workGroupSize=[8,8,1],this.atomic=!0,this.tileInner=32,v.assert(e[0]===1,()=>"MatMulSplitKProgram only supports batch = 1."),this.outputShape=e,this.dispatchLayout={x:[2],y:[1],z:[0,3]},this.elementsPerThread=[4,4,this.tileInner],this.outputShape[1]<16&&(this.elementsPerThread[1]=1),this.outputShape[2]<16&&(this.elementsPerThread[0]=1),this.dispatch=We(this.dispatchLayout,[this.outputShape[0],this.outputShape[1],this.outputShape[2],t],this.workGroupSize,this.elementsPerThread),this.transposeA=r,this.transposeB=a,this.batchAEqualOne=n,this.batchBEqualOne=s,this.shaderKey=`matMulSplitK_${r}_${a}_${n}_${s}_${this.elementsPerThread}`}getUserCode(){let e=`
      var oldValue = atomicLoad(&(result[flatIndex]));
@@ -5479,7 +5479,7 @@ return a / b;`,Gie=`
     `}makeMatMulSplitKSource(){let e=this.workGroupSize[1]*this.elementsPerThread[1],t=this.workGroupSize[0]*this.elementsPerThread[0],n=this.elementsPerThread[1],s=this.elementsPerThread[0],r=this.tileInner/this.workGroupSize[0],a=this.tileInner/this.workGroupSize[1];return v.assert(this.tileInner%this.workGroupSize[0]===0&&this.tileInner%this.workGroupSize[1]===0,()=>`tileInner ${this.tileInner} must be divisible by workGroupSize[0]${this.workGroupSize[0]} and workGroupSize[1]${this.workGroupSize[1]}`),`
       var<workgroup> mm_Asub : array<array<f32, ${this.tileInner}>, ${e}>;
       var<workgroup> mm_Bsub : array<array<f32, ${t}>, ${this.tileInner}>;
-      ${pd()}
+      ${dd()}
         let tileRow = i32(localId.y) * ${n};
         let tileCol = i32(localId.x) * ${s};
 
@@ -5536,12 +5536,12 @@ return a / b;`,Gie=`
         }
       }
     `}},K0e=class{constructor(e,t=null,n=null,s=null){this.uniforms="",this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.addBias=t!=null,this.hasPreluActivationWeights=s!=null,this.activation=n,this.addBias&&this.variableNames.push("bias"),this.hasPreluActivationWeights&&this.variableNames.push("preluActivationWeights"),this.shaderKey=`biasActivation_${n}`}getUserCode(){return`
-    ${Ca(this.activation,this.hasPreluActivationWeights)}
+    ${Sa(this.activation,this.hasPreluActivationWeights)}
     ${lt()}
       if (index < uniforms.size) {
         let coords = getCoordsFromIndex(index);
         var value = getXByOutputIndex(index);
-        ${dd(this.addBias,this.activation)}
+        ${cd(this.addBias,this.activation)}
         setOutputAtIndex(index, value);
       }
     }
@@ -5551,10 +5551,10 @@ return a / b;`,Gie=`
         setOutputAtIndex(index, uniforms.value);
       }
     }
-  `}};function ou(e){let{backend:t,attrs:n}=e,{shape:s,value:r}=n,{dtype:a}=n;if(a=a||v.inferDtype(r),a==="string"){let o=v.getArrayFromDType(a,v.sizeFromShape(s));return o.fill(r),t.makeTensorInfo(s,a,o)}else{let o=new Z0e(s),i=[{type:"float32",data:[r]}];return t.runWebGPUProgram(o,[],a,i)}}var Y0e={kernelName:kc,backendName:"webgpu",kernelFunc:ou};function Ue(e){let{inputs:t,attrs:n}=e,{x:s}=t,{shape:r}=n,a=v.sizeFromShape(s.shape),o=v.inferFromImplicitShape(r,a),i=v.sizeFromShape(o);return v.assert(a===i,()=>`The new shape (${o}) has ${i} elements and the old shape (${s.shape}) has ${a} elements. The new shape and old shape must have the same number of elements.`),e.backend.incRef(s.dataId),{dataId:s.dataId,shape:o,dtype:s.dtype}}var J0e={kernelName:_l,backendName:"webgpu",kernelFunc:Ue};function ib({a:e,b:t,transposeA:n,transposeB:s,backend:r,bias:a=null,preluActivationWeights:o=null,leakyreluAlpha:i=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,p=n?e.shape[u-2]:e.shape[u-1],d=s?t.shape[c-1]:t.shape[c-2],h=n?e.shape[u-1]:e.shape[u-2],f=s?t.shape[c-2]:t.shape[c-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(m),x=v.sizeFromShape(g),b=Xl.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,f]);v.assert(p===d,()=>`Error in matMul: inner shapes (${p}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${s} must match.`);let w=n?[y,p,h]:[y,h,p],k=s?[x,f,d]:[x,d,f],S=Ue({inputs:{x:e},backend:r,attrs:{shape:w}}),E=Ue({inputs:{x:t},backend:r,attrs:{shape:k}}),R=[S,E],P=Math.max(y,x),_=y===1,$=x===1,T=(p%4===0&&!n||h%4===0&&n)&&f%4===0&&!s,F=[S,E],G=[{type:"int32",data:[h]},{type:"int32",data:[f]},{type:"int32",data:[p]}],q,z,K=[P,h,f],B=Z().get("WEBGPU_MATMUL_PROGRAM_TYPE");switch(B<0&&(h*f<=128?B=Hs.MatMulReduceProgram:P===1&&h<=128&&f<=48&&d>=2e3?B=Hs.MatMulSplitKProgram:h<=16&&(f<=512||d>=2*f)||f<=16&&(h<=512||p>=2*h)?B=Hs.MatMulSmallOutputSizeProgram:T?B=Hs.MatMulPackedVec4Program:B=Hs.MatMulPackedProgram),B){case Hs.MatMulPackedVec4Program:q=new U0e(w,K,_,$,n,a,l,o);break;case Hs.MatMulReduceProgram:q=new H0e(K,_,$,n,s,a,l,o);break;case Hs.MatMulSplitKProgram:{if(z=ou({backend:r,attrs:{shape:K,value:0,dtype:e.dtype}}),q=new X0e(K,d,_,$,n,s),a||l){z=r.runWebGPUProgram(q,F,e.dtype,G,z);let Q=new K0e(z.shape,a,l,o),oe=null,Y=[z];a&&Y.push(a),o&&Y.push(o),l==="leakyrelu"&&(oe=[{type:"float32",data:[i]}],Q.uniforms+=" alpha : f32,");let ae=r.runWebGPUProgram(Q,Y,z.dtype,oe);R.push(z);let le=Ue({inputs:{x:ae},backend:r,attrs:{shape:b}});R.push(ae);for(let ye of R)r.disposeData(ye.dataId);return le}break}case Hs.MatMulSmallOutputSizeProgram:q=new q0e(w,k,K,n,s,a,l,o);break;case Hs.MatMulPackedProgram:q=new B0e(w,K,Z().get("WEBGPU_MATMUL_WORK_PER_THREAD"),_,$,n,s,a,l,o);break;default:throw new Error(`Unsupported MatMulProgramType ${B}.`)}a&&F.push(a),o&&F.push(o),l==="leakyrelu"&&(G.push({type:"float32",data:[i]}),q.uniforms+=" alpha : f32,"),z=r.runWebGPUProgram(q,F,e.dtype,G,z);let ee=Ue({inputs:{x:z},backend:r,attrs:{shape:b}});R.push(z);for(let Q of R)r.disposeData(Q.dataId);return ee}function Q0e(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=s;return ib({a:r,b:a,transposeA:l,transposeB:u,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:p,activation:c})}var e2e={kernelName:Ja,backendName:"webgpu",kernelFunc:Q0e},W7=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.workGroupSize=[128,1,1],this.size=!0,this.outputShape=C.assertAndGetBroadcastShape(t,n),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`binaryOpComplex_${e}`,this.op=e}getUserCode(){return`
+  `}};function au(e){let{backend:t,attrs:n}=e,{shape:s,value:r}=n,{dtype:a}=n;if(a=a||v.inferDtype(r),a==="string"){let o=v.getArrayFromDType(a,v.sizeFromShape(s));return o.fill(r),t.makeTensorInfo(s,a,o)}else{let o=new Z0e(s),i=[{type:"float32",data:[r]}];return t.runWebGPUProgram(o,[],a,i)}}var Y0e={kernelName:wc,backendName:"webgpu",kernelFunc:au};function Ue(e){let{inputs:t,attrs:n}=e,{x:s}=t,{shape:r}=n,a=v.sizeFromShape(s.shape),o=v.inferFromImplicitShape(r,a),i=v.sizeFromShape(o);return v.assert(a===i,()=>`The new shape (${o}) has ${i} elements and the old shape (${s.shape}) has ${a} elements. The new shape and old shape must have the same number of elements.`),e.backend.incRef(s.dataId),{dataId:s.dataId,shape:o,dtype:s.dtype}}var J0e={kernelName:Rl,backendName:"webgpu",kernelFunc:Ue};function ib({a:e,b:t,transposeA:n,transposeB:s,backend:r,bias:a=null,preluActivationWeights:o=null,leakyreluAlpha:i=0,activation:l=null}){let u=e.shape.length,c=t.shape.length,p=n?e.shape[u-2]:e.shape[u-1],d=s?t.shape[c-1]:t.shape[c-2],h=n?e.shape[u-1]:e.shape[u-2],f=s?t.shape[c-2]:t.shape[c-1],m=e.shape.slice(0,-2),g=t.shape.slice(0,-2),y=v.sizeFromShape(m),x=v.sizeFromShape(g),b=ql.assertAndGetBroadcastShape(e.shape.slice(0,-2),t.shape.slice(0,-2)).concat([h,f]);v.assert(p===d,()=>`Error in matMul: inner shapes (${p}) and (${d}) of Tensors with shapes ${e.shape} and ${t.shape} and transposeA=${n} and transposeB=${s} must match.`);let w=n?[y,p,h]:[y,h,p],k=s?[x,f,d]:[x,d,f],S=Ue({inputs:{x:e},backend:r,attrs:{shape:w}}),E=Ue({inputs:{x:t},backend:r,attrs:{shape:k}}),R=[S,E],P=Math.max(y,x),_=y===1,$=x===1,T=(p%4===0&&!n||h%4===0&&n)&&f%4===0&&!s,F=[S,E],G=[{type:"int32",data:[h]},{type:"int32",data:[f]},{type:"int32",data:[p]}],q,z,Z=[P,h,f],B=X().get("WEBGPU_MATMUL_PROGRAM_TYPE");switch(B<0&&(h*f<=128?B=Hs.MatMulReduceProgram:P===1&&h<=128&&f<=48&&d>=2e3?B=Hs.MatMulSplitKProgram:h<=16&&(f<=512||d>=2*f)||f<=16&&(h<=512||p>=2*h)?B=Hs.MatMulSmallOutputSizeProgram:T?B=Hs.MatMulPackedVec4Program:B=Hs.MatMulPackedProgram),B){case Hs.MatMulPackedVec4Program:q=new U0e(w,Z,_,$,n,a,l,o);break;case Hs.MatMulReduceProgram:q=new H0e(Z,_,$,n,s,a,l,o);break;case Hs.MatMulSplitKProgram:{if(z=au({backend:r,attrs:{shape:Z,value:0,dtype:e.dtype}}),q=new X0e(Z,d,_,$,n,s),a||l){z=r.runWebGPUProgram(q,F,e.dtype,G,z);let Q=new K0e(z.shape,a,l,o),oe=null,Y=[z];a&&Y.push(a),o&&Y.push(o),l==="leakyrelu"&&(oe=[{type:"float32",data:[i]}],Q.uniforms+=" alpha : f32,");let ae=r.runWebGPUProgram(Q,Y,z.dtype,oe);R.push(z);let le=Ue({inputs:{x:ae},backend:r,attrs:{shape:b}});R.push(ae);for(let ye of R)r.disposeData(ye.dataId);return le}break}case Hs.MatMulSmallOutputSizeProgram:q=new q0e(w,k,Z,n,s,a,l,o);break;case Hs.MatMulPackedProgram:q=new B0e(w,Z,X().get("WEBGPU_MATMUL_WORK_PER_THREAD"),_,$,n,s,a,l,o);break;default:throw new Error(`Unsupported MatMulProgramType ${B}.`)}a&&F.push(a),o&&F.push(o),l==="leakyrelu"&&(G.push({type:"float32",data:[i]}),q.uniforms+=" alpha : f32,"),z=r.runWebGPUProgram(q,F,e.dtype,G,z);let ee=Ue({inputs:{x:z},backend:r,attrs:{shape:b}});R.push(z);for(let Q of R)r.disposeData(Q.dataId);return ee}function Q0e(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a,bias:o,preluActivationWeights:i}=t,{transposeA:l,transposeB:u,activation:c,leakyreluAlpha:p}=s;return ib({a:r,b:a,transposeA:l,transposeB:u,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:p,activation:c})}var e2e={kernelName:Ya,backendName:"webgpu",kernelFunc:Q0e},W7=class{constructor(e,t,n){this.variableNames=["AReal","AImag","BReal","BImag"],this.workGroupSize=[128,1,1],this.size=!0,this.outputShape=C.assertAndGetBroadcastShape(t,n),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`binaryOpComplex_${e}`,this.op=e}getUserCode(){return`
       fn binaryOpComplex(
           areal : f32, aimag : f32, breal : f32, bimag : f32) -> f32 {
-        ${Lm(this.op,!1)}
+        ${zm(this.op,!1)}
       }
 
       ${lt()}
@@ -5566,11 +5566,11 @@ return a / b;`,Gie=`
           setOutputAtIndex(index, binaryOpComplex(areal, aimag, breal, bimag));
         }
       }
-    `}},fy=class{constructor(e,t,n){this.size=!0,this.variableNames=["A","B"],this.outputShape=C.assertAndGetBroadcastShape(t,n),this.dispatchLayout=at(this.outputShape),this.op=e,this.useSharedMemoryWithA=t.length===1&&n.length>1&&t[0]<1024,this.useSharedMemoryWithB=n.length===1&&t.length>1&&n[0]<1024,this.useSharedMemoryWithA||this.useSharedMemoryWithB?(this.isVec4=!1,this.lastDimensionSize=this.useSharedMemoryWithB?n[0]:t[0],this.shaderKey=`binary_${this.type}_${e}_${this.lastDimensionSize}_${this.useSharedMemoryWithB}`,this.type="shared",this.workGroupSize=[256,1,1],this.lastDimensionSize<256?this.workPerThread=1:this.lastDimensionSize<512?this.workPerThread=2:this.workPerThread=4):(v.arraysEqual(t,n)&&v.sizeFromShape(t)%4===0?(this.isVec4=!0,this.type="vec4",this.workPerThread=4):(this.isVec4=!1,this.type="plain",this.workPerThread=1),this.shaderKey=`binary_${this.type}_${e}`,this.workGroupSize=[128,1,1]),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1])}getUserCode(){let e;if(this.type==="shared"){let t=this.lastDimensionSize>1?`coords[${this.outputShape.length-1}]`:"0",n=this.useSharedMemoryWithB?`let a = getAByOutputCoords(coords);
+    `}},hy=class{constructor(e,t,n){this.size=!0,this.variableNames=["A","B"],this.outputShape=C.assertAndGetBroadcastShape(t,n),this.dispatchLayout=at(this.outputShape),this.op=e,this.useSharedMemoryWithA=t.length===1&&n.length>1&&t[0]<1024,this.useSharedMemoryWithB=n.length===1&&t.length>1&&n[0]<1024,this.useSharedMemoryWithA||this.useSharedMemoryWithB?(this.isVec4=!1,this.lastDimensionSize=this.useSharedMemoryWithB?n[0]:t[0],this.shaderKey=`binary_${this.type}_${e}_${this.lastDimensionSize}_${this.useSharedMemoryWithB}`,this.type="shared",this.workGroupSize=[256,1,1],this.lastDimensionSize<256?this.workPerThread=1:this.lastDimensionSize<512?this.workPerThread=2:this.workPerThread=4):(v.arraysEqual(t,n)&&v.sizeFromShape(t)%4===0?(this.isVec4=!0,this.type="vec4",this.workPerThread=4):(this.isVec4=!1,this.type="plain",this.workPerThread=1),this.shaderKey=`binary_${this.type}_${e}`,this.workGroupSize=[128,1,1]),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1])}getUserCode(){let e;if(this.type==="shared"){let t=this.lastDimensionSize>1?`coords[${this.outputShape.length-1}]`:"0",n=this.useSharedMemoryWithB?`let a = getAByOutputCoords(coords);
           let b = sharedBuf[${t}];`:`let a = sharedBuf[${t}];
           let b = getBByOutputCoords(coords);`;e=`
         fn binaryOperation(a : f32, b : f32) -> f32 {
-          ${Lm(this.op,this.isVec4)}
+          ${zm(this.op,this.isVec4)}
         }
         var<workgroup> sharedBuf : array<f32, ${this.lastDimensionSize}>;
         ${lt()}
@@ -5593,7 +5593,7 @@ return a / b;`,Gie=`
             }
           }
         }
-        `}else{let t=this.type==="vec4"?"vec4<f32>":"f32",n=Lm(this.op,this.isVec4);e=`
+        `}else{let t=this.type==="vec4"?"vec4<f32>":"f32",n=zm(this.op,this.isVec4);e=`
        fn binaryOperation(a : ${t}, b : ${t}) -> ${t} {
          ${n}
        }
@@ -5604,9 +5604,9 @@ return a / b;`,Gie=`
            setOutputAtIndex(index, binaryOperation(a, b));
          }
        }
-       `}return e}};function Fs(e){let{inputs:t}=e,{x:n}=t;return e.backend.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var t2e={kernelName:_o,backendName:"webgpu",kernelFunc:Fs};function hd(e){let{inputs:t,backend:n}=e,{real:s,imag:r}=t,a=n.makeTensorInfo(s.shape,"complex64"),o=n.tensorMap.get(a.dataId),i=Fs({inputs:{x:s},backend:n}),l=Fs({inputs:{x:r},backend:n});return o.complexTensorInfos={real:i,imag:l},a}var n2e={kernelName:Lp,backendName:"webgpu",kernelFunc:hd},Bh=class{constructor(e,t){this.variableNames=["A"],this.size=!0;let n=128;this.workGroupSize=[n,1,1],this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.op=t,this.shaderKey=`unary_${t}`}getUserCode(){return`
+       `}return e}};function Fs(e){let{inputs:t}=e,{x:n}=t;return e.backend.incRef(n.dataId),{dataId:n.dataId,shape:n.shape,dtype:n.dtype}}var t2e={kernelName:Ro,backendName:"webgpu",kernelFunc:Fs};function pd(e){let{inputs:t,backend:n}=e,{real:s,imag:r}=t,a=n.makeTensorInfo(s.shape,"complex64"),o=n.tensorMap.get(a.dataId),i=Fs({inputs:{x:s},backend:n}),l=Fs({inputs:{x:r},backend:n});return o.complexTensorInfos={real:i,imag:l},a}var n2e={kernelName:zp,backendName:"webgpu",kernelFunc:pd},Lh=class{constructor(e,t){this.variableNames=["A"],this.size=!0;let n=128;this.workGroupSize=[n,1,1],this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.op=t,this.shaderKey=`unary_${t}`}getUserCode(){return`
       fn unaryOperation(a : f32) -> f32 {
-        ${Oi(this.op,!1)}
+        ${Fi(this.op,!1)}
       }
       ${lt()}
         if (index < uniforms.size) {
@@ -5614,7 +5614,7 @@ return a / b;`,Gie=`
           setOutputAtIndex(index, unaryOperation(a));
         }
       }
-      `}};function Dn({opType:e,cpuKernelImpl:t,dtype:n}){return({inputs:s,backend:r})=>{let{x:a}=s,o=r,i=n||a.dtype;if(o.shouldExecuteOnCPU([a])&&t!=null){let u=o.tensorMap.get(a.dataId),c=t(u.values,i);return o.makeTensorInfo(a.shape,i,c)}let l=new Bh(a.shape,e);return o.runWebGPUProgram(l,[a],i)}}function os({opType:e,cpuKernelImpl:t,supportsComplex:n=!1,dtype:s}){return({inputs:r,backend:a})=>{let{a:o,b:i}=r,l=a;if(n&&o.dtype==="complex64"){let p=l.tensorMap.get(o.dataId),d=l.tensorMap.get(i.dataId),h,f;if(e!==Ye.MUL)[h,f]=[[p.complexTensorInfos.real,d.complexTensorInfos.real],[p.complexTensorInfos.imag,d.complexTensorInfos.imag]].map(g=>{let[y,x]=g,A={dataId:y.dataId,dtype:y.dtype,shape:o.shape},b={dataId:x.dataId,dtype:x.dtype,shape:i.shape},w=new fy(e,o.shape,i.shape);return l.runWebGPUProgram(w,[A,b],On(y.dtype,x.dtype))});else{let g=new W7(Ye.COMPLEX_MULTIPLY_REAL,o.shape,i.shape),y=new W7(Ye.COMPLEX_MULTIPLY_IMAG,o.shape,i.shape),x=[{dataId:p.complexTensorInfos.real.dataId,dtype:p.complexTensorInfos.real.dtype,shape:o.shape},{dataId:p.complexTensorInfos.imag.dataId,dtype:p.complexTensorInfos.imag.dtype,shape:o.shape},{dataId:d.complexTensorInfos.real.dataId,dtype:d.complexTensorInfos.real.dtype,shape:i.shape},{dataId:d.complexTensorInfos.imag.dataId,dtype:d.complexTensorInfos.imag.dtype,shape:i.shape}];h=l.runWebGPUProgram(g,x,"float32"),f=l.runWebGPUProgram(y,x,"float32")}let m=hd({inputs:{real:h,imag:f},backend:l});return l.disposeData(h.dataId),l.disposeData(f.dataId),m}let u=s||On(o.dtype,i.dtype);if((o.dtype==="string"||i.dtype==="string"||l.shouldExecuteOnCPU([o,i]))&&t!=null){let p=l.tensorMap.get(o.dataId).values,d=l.tensorMap.get(i.dataId).values,h=o.dtype==="string"?C.fromUint8ToStringArray(p):p,f=o.dtype==="string"?C.fromUint8ToStringArray(d):d,[m,g]=t(o.shape,i.shape,h,f,u);return l.makeTensorInfo(g,u,m)}let c=new fy(e,o.shape,i.shape);return l.runWebGPUProgram(c,[o,i],u)}}var{addImpl:s2e,ceilImpl:r2e,concatImpl:a2e,equalImpl:o2e,expImpl:i2e,expm1Impl:l2e,floorImpl:u2e,gatherNdImpl:c2e,gatherV2Impl:d2e,greaterEqualImpl:p2e,greaterImpl:h2e,lessEqualImpl:f2e,lessImpl:m2e,logImpl:g2e,maxImpl:y2e,maximumImpl:A2e,minimumImpl:x2e,multiplyImpl:b2e,negImpl:v2e,notEqualImpl:w2e,prodImpl:k2e,rangeImpl:I2e,rsqrtImpl:S2e,scatterImpl:C2e,simpleAbsImpl:T2e,sliceImpl:N2e,stridedSliceImpl:E2e,stringNGramsImpl:R2e,subImpl:_2e,tileImpl:D2e,topKImpl:$2e,transposeImpl:P2e,uniqueImpl:Fxe}=Sx,F2e=Dn({opType:Fe.ABS,cpuKernelImpl:T2e}),O2e={kernelName:il,backendName:"webgpu",kernelFunc:F2e},M2e=os({opType:Ye.ADD,cpuKernelImpl:s2e,supportsComplex:!0}),z2e={kernelName:xa,backendName:"webgpu",kernelFunc:M2e},L2e=class{constructor(e){this.workPerThread=4,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e[0],this.variableNames=e.map((t,n)=>`T${n}`),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.shaderKey="addN"}getUserCode(){let e=[];this.variableNames.forEach(s=>{e.push(`let v${s} = get${s}ByOutputCoords(coords);`)});let t=this.variableNames.map(s=>`v${s}`).join(" + ");return`
+      `}};function Dn({opType:e,cpuKernelImpl:t,dtype:n}){return({inputs:s,backend:r})=>{let{x:a}=s,o=r,i=n||a.dtype;if(o.shouldExecuteOnCPU([a])&&t!=null){let u=o.tensorMap.get(a.dataId),c=t(u.values,i);return o.makeTensorInfo(a.shape,i,c)}let l=new Lh(a.shape,e);return o.runWebGPUProgram(l,[a],i)}}function os({opType:e,cpuKernelImpl:t,supportsComplex:n=!1,dtype:s}){return({inputs:r,backend:a})=>{let{a:o,b:i}=r,l=a;if(n&&o.dtype==="complex64"){let p=l.tensorMap.get(o.dataId),d=l.tensorMap.get(i.dataId),h,f;if(e!==Ye.MUL)[h,f]=[[p.complexTensorInfos.real,d.complexTensorInfos.real],[p.complexTensorInfos.imag,d.complexTensorInfos.imag]].map(g=>{let[y,x]=g,A={dataId:y.dataId,dtype:y.dtype,shape:o.shape},b={dataId:x.dataId,dtype:x.dtype,shape:i.shape},w=new hy(e,o.shape,i.shape);return l.runWebGPUProgram(w,[A,b],On(y.dtype,x.dtype))});else{let g=new W7(Ye.COMPLEX_MULTIPLY_REAL,o.shape,i.shape),y=new W7(Ye.COMPLEX_MULTIPLY_IMAG,o.shape,i.shape),x=[{dataId:p.complexTensorInfos.real.dataId,dtype:p.complexTensorInfos.real.dtype,shape:o.shape},{dataId:p.complexTensorInfos.imag.dataId,dtype:p.complexTensorInfos.imag.dtype,shape:o.shape},{dataId:d.complexTensorInfos.real.dataId,dtype:d.complexTensorInfos.real.dtype,shape:i.shape},{dataId:d.complexTensorInfos.imag.dataId,dtype:d.complexTensorInfos.imag.dtype,shape:i.shape}];h=l.runWebGPUProgram(g,x,"float32"),f=l.runWebGPUProgram(y,x,"float32")}let m=pd({inputs:{real:h,imag:f},backend:l});return l.disposeData(h.dataId),l.disposeData(f.dataId),m}let u=s||On(o.dtype,i.dtype);if((o.dtype==="string"||i.dtype==="string"||l.shouldExecuteOnCPU([o,i]))&&t!=null){let p=l.tensorMap.get(o.dataId).values,d=l.tensorMap.get(i.dataId).values,h=o.dtype==="string"?C.fromUint8ToStringArray(p):p,f=o.dtype==="string"?C.fromUint8ToStringArray(d):d,[m,g]=t(o.shape,i.shape,h,f,u);return l.makeTensorInfo(g,u,m)}let c=new hy(e,o.shape,i.shape);return l.runWebGPUProgram(c,[o,i],u)}}var{addImpl:s2e,ceilImpl:r2e,concatImpl:a2e,equalImpl:o2e,expImpl:i2e,expm1Impl:l2e,floorImpl:u2e,gatherNdImpl:c2e,gatherV2Impl:d2e,greaterEqualImpl:p2e,greaterImpl:h2e,lessEqualImpl:f2e,lessImpl:m2e,logImpl:g2e,maxImpl:y2e,maximumImpl:A2e,minimumImpl:x2e,multiplyImpl:b2e,negImpl:v2e,notEqualImpl:w2e,prodImpl:k2e,rangeImpl:I2e,rsqrtImpl:S2e,scatterImpl:C2e,simpleAbsImpl:T2e,sliceImpl:N2e,stridedSliceImpl:E2e,stringNGramsImpl:R2e,subImpl:_2e,tileImpl:D2e,topKImpl:$2e,transposeImpl:P2e,uniqueImpl:Fxe}=Sx,F2e=Dn({opType:Fe.ABS,cpuKernelImpl:T2e}),O2e={kernelName:ol,backendName:"webgpu",kernelFunc:F2e},M2e=os({opType:Ye.ADD,cpuKernelImpl:s2e,supportsComplex:!0}),z2e={kernelName:Aa,backendName:"webgpu",kernelFunc:M2e},L2e=class{constructor(e){this.workPerThread=4,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e[0],this.variableNames=e.map((t,n)=>`T${n}`),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.shaderKey="addN"}getUserCode(){let e=[];this.variableNames.forEach(s=>{e.push(`let v${s} = get${s}ByOutputCoords(coords);`)});let t=this.variableNames.map(s=>`v${s}`).join(" + ");return`
       ${lt()}
         for (var i = 0; i < ${this.workPerThread}; i = i + 1) {
           let flatIndex = index * ${this.workPerThread} + i;
@@ -5626,10 +5626,10 @@ return a / b;`,Gie=`
           }
         }
       }
-    `}};function B2e(e){let{inputs:t,backend:n}=e,s=t;if(s.length===1)return Fs({inputs:{x:s[0]},backend:n});let r=s.map(i=>i.dtype).reduce((i,l)=>On(i,l)),a=s.map(i=>i.shape),o=new L2e(a);return n.runWebGPUProgram(o,s,r)}var W2e={kernelName:po,backendName:"webgpu",kernelFunc:B2e},ZC=class{constructor(e,t,n){this.workGroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="infinityValue : f32,",this.size=!0;let s=[t];C.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),s,e.length),this.op=n==="min"?"<":">";let[r]=C.computeOutAndReduceShapes(e,s);this.outputShape=r.length===0?[1]:r,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,[1,1,1]),this.inputShape=e,this.shaderKey=`argMinMax${this.op}`}getUserCode(){let e=`
+    `}};function B2e(e){let{inputs:t,backend:n}=e,s=t;if(s.length===1)return Fs({inputs:{x:s[0]},backend:n});let r=s.map(i=>i.dtype).reduce((i,l)=>On(i,l)),a=s.map(i=>i.shape),o=new L2e(a);return n.runWebGPUProgram(o,s,r)}var W2e={kernelName:co,backendName:"webgpu",kernelFunc:B2e},ZC=class{constructor(e,t,n){this.workGroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="infinityValue : f32,",this.size=!0;let s=[t];C.assertAxesAreInnerMostDims("arg"+n.charAt(0).toUpperCase()+n.slice(1),s,e.length),this.op=n==="min"?"<":">";let[r]=C.computeOutAndReduceShapes(e,s);this.outputShape=r.length===0?[1]:r,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,[1,1,1]),this.inputShape=e,this.shaderKey=`argMinMax${this.op}`}getUserCode(){let e=`
       var<workgroup> xBestIndices : array<i32, ${this.workGroupSize[0]}>;
       var<workgroup> xBestValues : array<f32, ${this.workGroupSize[0]}>;
-    `,t=()=>this.inputShape.length===1?"uniforms.xShape":`uniforms.xShape.${Za(this.inputShape.length-1)}`,n=()=>{let r="";if(this.outputShape.length===1)this.inputShape.length!==1&&(r+="outputCoords,");else for(let a=0;a<this.outputShape.length;a++)r+=`outputCoords.${Za(a)},`;return r};return`
+    `,t=()=>this.inputShape.length===1?"uniforms.xShape":`uniforms.xShape.${Ka(this.inputShape.length-1)}`,n=()=>{let r="";if(this.outputShape.length===1)this.inputShape.length!==1&&(r+="outputCoords,");else for(let a=0;a<this.outputShape.length;a++)r+=`outputCoords.${Ka(a)},`;return r};return`
       fn DIV_CEIL(a : u32, b : u32) -> u32 {
         return ((a - 1u) / b + 1u);
       }
@@ -5678,7 +5678,7 @@ return a / b;`,Gie=`
     `}},V2e=class{constructor(e,t){this.variableNames=["A"],this.workGroupSize=[16,16,1];let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[t[s]];this.outputShape=n,this.dispatchLayout={x:[0],y:[1]},this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[1,1,1]),this.shaderKey="transposeShared"}getUserCode(){return`
       const TILE_DIM = ${this.workGroupSize[0]};
       var<workgroup> tile : array<array<f32, ${this.workGroupSize[0]+1}>, ${this.workGroupSize[0]}>;
-      ${T2()}
+      ${C2()}
       fn main(@builtin(local_invocation_id) localId : vec3<u32>,
               @builtin(workgroup_id) workgroupId : vec3<u32>) {
         var x = i32(workgroupId.x) * TILE_DIM + i32(localId.x);
@@ -5709,7 +5709,7 @@ return a / b;`,Gie=`
           }
         }
       }
-    `}};function G2e(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=new Array(t);for(let s=0;s<e.length;s++)n[e[s]]=`resRC.${Za(s)}`;return n.join()}function Aa(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{perm:a}=s,o=n,i=r.shape.length,l=new Array(i);for(let c=0;c<l.length;c++)l[c]=r.shape[a[c]];if(n.shouldExecuteOnCPU([r])){let p=o.tensorMap.get(r.dataId).values,d=P2e(p,r.shape,r.dtype,a,l);return n.makeTensorInfo(l,r.dtype,d)}if(r.shape.length===2&&v.arraysEqual(a,[1,0])){let c=new V2e(r.shape,a);return o.runWebGPUProgram(c,[r],r.dtype)}let u=new U2e(r.shape,a);return o.runWebGPUProgram(u,[r],r.dtype)}var H2e={kernelName:Hr,backendName:"webgpu",kernelFunc:Aa};function j2e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=Aa({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMax",[o[0]],l.shape.length);let c=new ZC(l.shape,o[0],"max"),p=[{type:"float32",data:[Number.NEGATIVE_INFINITY]}],d=n.runWebGPUProgram(c,[l],"int32",p);return u.forEach(h=>n.disposeData(h.dataId)),d}var q2e={kernelName:ho,backendName:"webgpu",kernelFunc:j2e};function X2e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=Aa({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMin",[o[0]],l.shape.length);let c=new ZC(l.shape,o[0],"min"),p=[{type:"float32",data:[Number.POSITIVE_INFINITY]}],d=n.runWebGPUProgram(c,[l],"int32",p);return u.forEach(h=>n.disposeData(h.dataId)),d}var K2e={kernelName:gc,backendName:"webgpu",kernelFunc:X2e},YC=class{constructor(e,t){this.variableNames=["x"],this.uniforms="stride : vec2<i32>, pad : vec2<i32>, dilation : vec2<i32>, convDims : vec2<i32>, filterDims : vec2<i32>,",this.workGroupSize=[128,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`pool2D_${t}`,this.poolType=t}getUserCode(){let e="resultValue = max(value, resultValue);";this.poolType==="avg"&&(e="resultValue = resultValue + value; count = count + 1.0;");let t="resultValue";return this.poolType==="avg"&&(t="resultValue / count"),`
+    `}};function G2e(e){let t=e.length;if(t>6)throw Error(`Transpose for rank ${t} is not yet supported`);let n=new Array(t);for(let s=0;s<e.length;s++)n[e[s]]=`resRC.${Ka(s)}`;return n.join()}function ya(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{perm:a}=s,o=n,i=r.shape.length,l=new Array(i);for(let c=0;c<l.length;c++)l[c]=r.shape[a[c]];if(n.shouldExecuteOnCPU([r])){let p=o.tensorMap.get(r.dataId).values,d=P2e(p,r.shape,r.dtype,a,l);return n.makeTensorInfo(l,r.dtype,d)}if(r.shape.length===2&&v.arraysEqual(a,[1,0])){let c=new V2e(r.shape,a);return o.runWebGPUProgram(c,[r],r.dtype)}let u=new U2e(r.shape,a);return o.runWebGPUProgram(u,[r],r.dtype)}var H2e={kernelName:Gr,backendName:"webgpu",kernelFunc:ya};function j2e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=ya({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMax",[o[0]],l.shape.length);let c=new ZC(l.shape,o[0],"max"),p=[{type:"float32",data:[Number.NEGATIVE_INFINITY]}],d=n.runWebGPUProgram(c,[l],"int32",p);return u.forEach(h=>n.disposeData(h.dataId)),d}var q2e={kernelName:po,backendName:"webgpu",kernelFunc:j2e};function X2e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a}=s,o=v.parseAxisParam(a,r.shape),i=C.getAxesPermutation(o,r.shape.length),l=r,u=[];i!=null&&(l=ya({inputs:{x:r},backend:n,attrs:{perm:i}}),u.push(l),o=C.getInnerMostAxes(o.length,l.shape.length)),C.assertAxesAreInnerMostDims("argMin",[o[0]],l.shape.length);let c=new ZC(l.shape,o[0],"min"),p=[{type:"float32",data:[Number.POSITIVE_INFINITY]}],d=n.runWebGPUProgram(c,[l],"int32",p);return u.forEach(h=>n.disposeData(h.dataId)),d}var K2e={kernelName:mc,backendName:"webgpu",kernelFunc:X2e},YC=class{constructor(e,t){this.variableNames=["x"],this.uniforms="stride : vec2<i32>, pad : vec2<i32>, dilation : vec2<i32>, convDims : vec2<i32>, filterDims : vec2<i32>,",this.workGroupSize=[128,1,1],this.size=!0,this.outputShape=e.outShape,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`pool2D_${t}`,this.poolType=t}getUserCode(){let e="resultValue = max(value, resultValue);";this.poolType==="avg"&&(e="resultValue = resultValue + value; count = count + 1.0;");let t="resultValue";return this.poolType==="avg"&&(t="resultValue / count"),`
       ${lt()}
       if (index < uniforms.size) {
         let coords = getCoordsFromIndex(index);
@@ -5757,7 +5757,7 @@ return a / b;`,Gie=`
           setOutputAtIndex(index, value);
         }
       }
-    `}};function Z2e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1,c=C.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Fs({inputs:{x:r},backend:n});let p,d=[{type:"int32",data:[c.strideHeight,c.strideWidth]}];return c.filterHeight===1&&c.filterWidth===1?p=new JC(c):(p=new YC(c,"avg"),d.push({type:"int32",data:[c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.dilationHeight,c.dilationWidth]},{type:"int32",data:[c.inHeight,c.inWidth]},{type:"int32",data:[c.effectiveFilterHeight,c.effectiveFilterWidth]})),n.runWebGPUProgram(p,[r],r.dtype,d)}var Y2e={kernelName:fo,backendName:"webgpu",kernelFunc:Z2e};function J2e(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;return ib({a:r,b:a,transposeA:o,transposeB:i,backend:n})}var Q2e={kernelName:mo,backendName:"webgpu",kernelFunc:J2e},e1e=class{constructor(e,t){this.variableNames=["source"],this.workPerThread=1,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.rank=t.length,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.start=e,this.uniforms=`start : ${Tn(e.length)}, `,this.shaderKey="slice"}getUserCode(){let e=Tn(this.rank),t=t1e(this.rank),n;return this.start.length===1?n=this.outputShape.map((r,a)=>"sourceLoc = uniforms.start + coords;"):n=this.outputShape.map((r,a)=>`sourceLoc.${my[a]} = uniforms.start[${a}] + coords.${my[a]};`),`
+    `}};function Z2e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1,c=C.computePool2DInfo(r.shape,a,o,u,i,l);if(c.filterWidth===1&&c.filterHeight===1&&v.arraysEqual(c.inShape,c.outShape))return Fs({inputs:{x:r},backend:n});let p,d=[{type:"int32",data:[c.strideHeight,c.strideWidth]}];return c.filterHeight===1&&c.filterWidth===1?p=new JC(c):(p=new YC(c,"avg"),d.push({type:"int32",data:[c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.dilationHeight,c.dilationWidth]},{type:"int32",data:[c.inHeight,c.inWidth]},{type:"int32",data:[c.effectiveFilterHeight,c.effectiveFilterWidth]})),n.runWebGPUProgram(p,[r],r.dtype,d)}var Y2e={kernelName:ho,backendName:"webgpu",kernelFunc:Z2e};function J2e(e){let{inputs:t,backend:n,attrs:s}=e,{a:r,b:a}=t,{transposeA:o,transposeB:i}=s;return ib({a:r,b:a,transposeA:o,transposeB:i,backend:n})}var Q2e={kernelName:fo,backendName:"webgpu",kernelFunc:J2e},e1e=class{constructor(e,t){this.variableNames=["source"],this.workPerThread=1,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.rank=t.length,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.start=e,this.uniforms=`start : ${Tn(e.length)}, `,this.shaderKey="slice"}getUserCode(){let e=Tn(this.rank),t=t1e(this.rank),n;return this.start.length===1?n=this.outputShape.map((r,a)=>"sourceLoc = uniforms.start + coords;"):n=this.outputShape.map((r,a)=>`sourceLoc.${fy[a]} = uniforms.start[${a}] + coords.${fy[a]};`),`
       ${lt()}
         if (index < uniforms.size) {
           var sourceLoc : ${e};
@@ -5767,7 +5767,7 @@ return a / b;`,Gie=`
           setOutputAtIndex(index, getSource(${t}));
         }
       }
-    `}},my=["x","y","z","w","u","v"];function t1e(e){if(e===1)return"sourceLoc";if(e<=6)return my.slice(0,e).map(t=>`sourceLoc.${t}`).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}function fd(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,size:o}=s,[i,l]=Ut.parseSliceParams(r,a,o);if(Ut.assertParamsValid(r,i,l),n.shouldExecuteOnCPU([r])||r.dtype==="string"){let p=n.tensorMap.get(r.dataId),d=N2e(p.values,i,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,d)}if(v.sizeFromShape(l)===0)return n.makeTensorInfo(l,r.dtype,[]);let u=new e1e(i,l),c=[{type:"int32",data:i}];return n.runWebGPUProgram(u,[r],r.dtype,c)}var n1e={kernelName:Ol,backendName:"webgpu",kernelFunc:fd},s1e=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s;v.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGPU backend not implemented yet");let i=a.reduce((x,A)=>x*A),l=C.getReshaped(r.shape,a,i),u=C.getPermuted(l.length,a.length),c=C.getReshapedPermuted(r.shape,a,i),p=C.getSliceBeginCoords(o,a.length),d=C.getSliceSize(c,o,a.length),h=[],f=Ue({inputs:{x:r},backend:n,attrs:{shape:l}}),m=Aa({inputs:{x:f},backend:n,attrs:{perm:u}}),g=Ue({inputs:{x:m},backend:n,attrs:{shape:c}}),y=fd({inputs:{x:g},backend:n,attrs:{begin:p,size:d}});return h.push(f),h.push(m),h.push(g),h.forEach(x=>n.disposeData(x.dataId)),y},r1e={kernelName:ll,backendName:"webgpu",kernelFunc:s1e},QC=os({opType:Ye.NOT_EQUAL,dtype:"bool",cpuKernelImpl:w2e}),a1e={kernelName:Sl,backendName:"webgpu",kernelFunc:QC};function Wh(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.tensorMap.get(s.dataId);return Fs({inputs:{x:r.complexTensorInfos.real},backend:n})}var o1e={kernelName:qp,backendName:"webgpu",kernelFunc:Wh};function i1e(e,t){let n=new Bh(e.shape,Fe.TO_INT),s=t.runWebGPUProgram(n,[e],"int32");return{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}function gy(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dtype:a}=s;if(a==="complex64"){if(r.dtype==="complex64")return Fs({inputs:{x:r},backend:n});let o=Wt(r.shape),i=gy({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=hd({inputs:{real:i,imag:o},backend:n});return o.dispose(),n.disposeData(i.dataId),l}if(r.dtype==="complex64"){let o=Wh({inputs:{input:r},backend:n}),i=gy({inputs:{x:o},backend:n,attrs:{dtype:a}});return n.disposeData(o.dataId),i}if(!v.hasEncodingLoss(r.dtype,a)){let o=Fs({inputs:{x:r},backend:n});return{dataId:o.dataId,shape:o.shape,dtype:a}}if(a==="int32")return i1e(r,n);if(a==="bool"){let o=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),l=QC({inputs:{a:r,b:o},backend:n});return n.disposeData(o.dataId),l}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${a}`)}var l1e={kernelName:go,backendName:"webgpu",kernelFunc:gy},u1e=Dn({opType:Fe.CEIL,cpuKernelImpl:r2e}),c1e={kernelName:yo,backendName:"webgpu",kernelFunc:u1e},d1e=class{constructor(e){this.variableNames=["A"],this.uniforms="minVal : f32, maxVal : f32,",this.workPerThread=4,this.workGroupSize=[64,1,1],this.isVec4=!0,this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.shaderKey="clipVec4"}getUserCode(){return`
+    `}},fy=["x","y","z","w","u","v"];function t1e(e){if(e===1)return"sourceLoc";if(e<=6)return fy.slice(0,e).map(t=>`sourceLoc.${t}`).join(",");throw Error(`Slicing for rank ${e} is not yet supported`)}function hd(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,size:o}=s,[i,l]=Ut.parseSliceParams(r,a,o);if(Ut.assertParamsValid(r,i,l),n.shouldExecuteOnCPU([r])||r.dtype==="string"){let p=n.tensorMap.get(r.dataId),d=N2e(p.values,i,l,r.shape,r.dtype);return n.makeTensorInfo(l,r.dtype,d)}if(v.sizeFromShape(l)===0)return n.makeTensorInfo(l,r.dtype,[]);let u=new e1e(i,l),c=[{type:"int32",data:i}];return n.runWebGPUProgram(u,[r],r.dtype,c)}var n1e={kernelName:Fl,backendName:"webgpu",kernelFunc:hd},s1e=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,crops:o}=s;v.assert(r.shape.length<=4,()=>"batchToSpaceND for rank > 4 with a WebGPU backend not implemented yet");let i=a.reduce((x,A)=>x*A),l=C.getReshaped(r.shape,a,i),u=C.getPermuted(l.length,a.length),c=C.getReshapedPermuted(r.shape,a,i),p=C.getSliceBeginCoords(o,a.length),d=C.getSliceSize(c,o,a.length),h=[],f=Ue({inputs:{x:r},backend:n,attrs:{shape:l}}),m=ya({inputs:{x:f},backend:n,attrs:{perm:u}}),g=Ue({inputs:{x:m},backend:n,attrs:{shape:c}}),y=hd({inputs:{x:g},backend:n,attrs:{begin:p,size:d}});return h.push(f),h.push(m),h.push(g),h.forEach(x=>n.disposeData(x.dataId)),y},r1e={kernelName:il,backendName:"webgpu",kernelFunc:s1e},QC=os({opType:Ye.NOT_EQUAL,dtype:"bool",cpuKernelImpl:w2e}),a1e={kernelName:Il,backendName:"webgpu",kernelFunc:QC};function Bh(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.tensorMap.get(s.dataId);return Fs({inputs:{x:r.complexTensorInfos.real},backend:n})}var o1e={kernelName:jp,backendName:"webgpu",kernelFunc:Bh};function i1e(e,t){let n=new Lh(e.shape,Fe.TO_INT),s=t.runWebGPUProgram(n,[e],"int32");return{dataId:s.dataId,shape:s.shape,dtype:s.dtype}}function my(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{dtype:a}=s;if(a==="complex64"){if(r.dtype==="complex64")return Fs({inputs:{x:r},backend:n});let o=Wt(r.shape),i=my({inputs:{x:r},backend:n,attrs:{dtype:"float32"}}),l=pd({inputs:{real:i,imag:o},backend:n});return o.dispose(),n.disposeData(i.dataId),l}if(r.dtype==="complex64"){let o=Bh({inputs:{input:r},backend:n}),i=my({inputs:{x:o},backend:n,attrs:{dtype:a}});return n.disposeData(o.dataId),i}if(!v.hasEncodingLoss(r.dtype,a)){let o=Fs({inputs:{x:r},backend:n});return{dataId:o.dataId,shape:o.shape,dtype:a}}if(a==="int32")return i1e(r,n);if(a==="bool"){let o=n.makeTensorInfo([],"bool",v.getTypedArrayFromDType("bool",1)),l=QC({inputs:{a:r,b:o},backend:n});return n.disposeData(o.dataId),l}throw new Error(`Error in Cast: failed to cast ${r.dtype} to ${a}`)}var l1e={kernelName:mo,backendName:"webgpu",kernelFunc:my},u1e=Dn({opType:Fe.CEIL,cpuKernelImpl:r2e}),c1e={kernelName:go,backendName:"webgpu",kernelFunc:u1e},d1e=class{constructor(e){this.variableNames=["A"],this.uniforms="minVal : f32, maxVal : f32,",this.workPerThread=4,this.workGroupSize=[64,1,1],this.isVec4=!0,this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.shaderKey="clipVec4"}getUserCode(){return`
       ${lt()}
         if(index < uniforms.size) {
           let value = getAByOutputIndex(index);
@@ -5794,7 +5794,7 @@ return a / b;`,Gie=`
           setOutputAtIndex(index, clamp(value, uniforms.minVal, uniforms.maxVal));
         }
       }
-    `}};function h1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i,l=[{type:"float32",data:[a]},{type:"float32",data:[o]}];return v.sizeFromShape(r.shape)%4===0?i=new d1e(r.shape):i=new p1e(r.shape),n.runWebGPUProgram(i,[r],r.dtype,l)}var f1e={kernelName:ba,backendName:"webgpu",kernelFunc:h1e},m1e=class{constructor(e){this.uniforms="",this.workPerThread=4,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=C.computeOutShape(e,1),this.variableNames=e.map((t,n)=>`T${n}`),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.offsetLength=e.length-1;for(let t=0;t<this.offsetLength;t++)this.uniforms+=`offset${t} : i32,`;this.shaderKey="concat"}getUserCode(){let e=[];if(this.offsetLength>0){e.push("if (yC < uniforms.offset0){ setOutputAtCoords(coords.x, coords.y, getT0(yR, yC)); }");for(let r=1;r<this.offsetLength;r++)e.push(`else if (yC < uniforms.offset${[r]}){ setOutputAtCoords(coords.x, coords.y, getT${r}(yR, yC - uniforms.offset${r-1})); }`);let n=this.offsetLength,s=this.offsetLength-1;e.push(`else { setOutputAtCoords(coords.x, coords.y, getT${n}(yR, yC - uniforms.offset${s})); }`)}else e.push("setOutputAtCoords(coords.x, coords.y, getT0(yR, yC));");return`
+    `}};function h1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{clipValueMin:a,clipValueMax:o}=s,i,l=[{type:"float32",data:[a]},{type:"float32",data:[o]}];return v.sizeFromShape(r.shape)%4===0?i=new d1e(r.shape):i=new p1e(r.shape),n.runWebGPUProgram(i,[r],r.dtype,l)}var f1e={kernelName:xa,backendName:"webgpu",kernelFunc:h1e},m1e=class{constructor(e){this.uniforms="",this.workPerThread=4,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=C.computeOutShape(e,1),this.variableNames=e.map((t,n)=>`T${n}`),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]),this.offsetLength=e.length-1;for(let t=0;t<this.offsetLength;t++)this.uniforms+=`offset${t} : i32,`;this.shaderKey="concat"}getUserCode(){let e=[];if(this.offsetLength>0){e.push("if (yC < uniforms.offset0){ setOutputAtCoords(coords.x, coords.y, getT0(yR, yC)); }");for(let r=1;r<this.offsetLength;r++)e.push(`else if (yC < uniforms.offset${[r]}){ setOutputAtCoords(coords.x, coords.y, getT${r}(yR, yC - uniforms.offset${r-1})); }`);let n=this.offsetLength,s=this.offsetLength-1;e.push(`else { setOutputAtCoords(coords.x, coords.y, getT${n}(yR, yC - uniforms.offset${s})); }`)}else e.push("setOutputAtCoords(coords.x, coords.y, getT0(yR, yC));");return`
       ${lt()}
         for(var i = 0; i < ${this.workPerThread}; i = i + 1) {
           let flatIndex = index * ${this.workPerThread} + i;
@@ -5808,7 +5808,7 @@ return a / b;`,Gie=`
           }
         }
       }
-    `}};function E2(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.tensorMap.get(s.dataId);return Fs({inputs:{x:r.complexTensorInfos.imag},backend:n})}var g1e={kernelName:Gp,backendName:"webgpu",kernelFunc:E2};function hp(e,t,n){let s=e[0].dtype;if(s==="complex64"){let f=e.map(A=>Wh({inputs:{input:A},backend:n})),m=e.map(A=>E2({inputs:{input:A},backend:n})),g=hp(f,t,n),y=hp(m,t,n),x=hd({inputs:{real:g,imag:y},backend:n});return f.forEach(A=>n.disposeData(A.dataId)),m.forEach(A=>n.disposeData(A.dataId)),n.disposeData(g.dataId),n.disposeData(y.dataId),x}let r=n.shouldExecuteOnCPU(e);if(s==="string"&&(r=!0),r){let f=e.map(w=>{let k=v.sizeFromShape(w.shape.slice(t));return Ue({inputs:{x:w},backend:n,attrs:{shape:[-1,k]}})}),m=f.map(w=>({vals:n.readSync(w.dataId),shape:w.shape})),g=C.computeOutShape(f.map(w=>w.shape),1),y=f[0].shape[0]===1,x=a2e(m,g,s,y),A=C.computeOutShape(e.map(w=>w.shape),t),b=n.makeTensorInfo(A,s,x);return f.forEach(w=>n.disposeData(w.dataId)),b}let a=n.device.limits.maxStorageBuffersPerShaderStage-1;if(e.length>a){let f=[];for(let g=0;g<e.length;g+=a){let y=e.slice(g,g+a);f.push(hp(y,t,n))}let m=hp(f,t,n);for(let g of f)n.disposeData(g.dataId);return m}let{tensors2D:o,outShape:i}=y1e(e,t,n),l=o.map(f=>f.shape),u=new m1e(l),c=[],p=new Array(l.length-1);if(p.length>0){p[0]=l[0][1],c.push({type:"int32",data:[p[0]]});for(let f=1;f<p.length;f++)p[f]=p[f-1]+l[f][1],c.push({type:"int32",data:[p[f]]})}let d=n.runWebGPUProgram(u,o,o[0].dtype,c);o.forEach(f=>n.disposeData(f.dataId));let h=Ue({inputs:{x:d},backend:n,attrs:{shape:i}});return n.disposeData(d.dataId),h}function y1e(e,t,n){let s=C.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>Ue({inputs:{x:a},backend:n,attrs:{shape:[v.sizeFromShape(a.shape.slice(0,t)),v.sizeFromShape(a.shape.slice(t))]}})),outShape:s}}function eT(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s,a=v.parseAxisParam(r,t[0].shape)[0],o=C.computeOutShape(t.map(u=>u.shape),a);if(v.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let i=t.filter(u=>v.sizeFromShape(u.shape)>0);if(i.length===1)return Fs({inputs:{x:i[0]},backend:n});let l=i.map(u=>u.shape);return C.assertParamsConsistent(l,a),hp(i,a,n)}var A1e={kernelName:ul,backendName:"webgpu",kernelFunc:eT};function x1e(e,t,n,s,r=!1,a=null,o=!1,i=4,l=4,u=4){let c=R=>{switch(R){case 1:return"resData = x[xIndex];";case 3:return"resData = vec3<f32>(x[xIndex], x[xIndex + 1], x[xIndex + 2]);";case 4:return"resData = x[xIndex / 4];";default:throw new Error(`innerElementSize ${R} is not supported.`)}},p=R=>{switch(R){case 1:return"return W[row * uniforms.wShape[3] + colIn];";case 4:return"return W[row * uniforms.wShape[3] / 4 + colIn];";default:throw new Error(`innerElementSize ${R} is not supported.`)}},d=e?`
+    `}};function N2(e){let{inputs:t,backend:n}=e,{input:s}=t,r=n.tensorMap.get(s.dataId);return Fs({inputs:{x:r.complexTensorInfos.imag},backend:n})}var g1e={kernelName:Up,backendName:"webgpu",kernelFunc:N2};function pp(e,t,n){let s=e[0].dtype;if(s==="complex64"){let f=e.map(A=>Bh({inputs:{input:A},backend:n})),m=e.map(A=>N2({inputs:{input:A},backend:n})),g=pp(f,t,n),y=pp(m,t,n),x=pd({inputs:{real:g,imag:y},backend:n});return f.forEach(A=>n.disposeData(A.dataId)),m.forEach(A=>n.disposeData(A.dataId)),n.disposeData(g.dataId),n.disposeData(y.dataId),x}let r=n.shouldExecuteOnCPU(e);if(s==="string"&&(r=!0),r){let f=e.map(w=>{let k=v.sizeFromShape(w.shape.slice(t));return Ue({inputs:{x:w},backend:n,attrs:{shape:[-1,k]}})}),m=f.map(w=>({vals:n.readSync(w.dataId),shape:w.shape})),g=C.computeOutShape(f.map(w=>w.shape),1),y=f[0].shape[0]===1,x=a2e(m,g,s,y),A=C.computeOutShape(e.map(w=>w.shape),t),b=n.makeTensorInfo(A,s,x);return f.forEach(w=>n.disposeData(w.dataId)),b}let a=n.device.limits.maxStorageBuffersPerShaderStage-1;if(e.length>a){let f=[];for(let g=0;g<e.length;g+=a){let y=e.slice(g,g+a);f.push(pp(y,t,n))}let m=pp(f,t,n);for(let g of f)n.disposeData(g.dataId);return m}let{tensors2D:o,outShape:i}=y1e(e,t,n),l=o.map(f=>f.shape),u=new m1e(l),c=[],p=new Array(l.length-1);if(p.length>0){p[0]=l[0][1],c.push({type:"int32",data:[p[0]]});for(let f=1;f<p.length;f++)p[f]=p[f-1]+l[f][1],c.push({type:"int32",data:[p[f]]})}let d=n.runWebGPUProgram(u,o,o[0].dtype,c);o.forEach(f=>n.disposeData(f.dataId));let h=Ue({inputs:{x:d},backend:n,attrs:{shape:i}});return n.disposeData(d.dataId),h}function y1e(e,t,n){let s=C.computeOutShape(e.map(a=>a.shape),t);return{tensors2D:e.map(a=>Ue({inputs:{x:a},backend:n,attrs:{shape:[v.sizeFromShape(a.shape.slice(0,t)),v.sizeFromShape(a.shape.slice(t))]}})),outShape:s}}function eT(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s,a=v.parseAxisParam(r,t[0].shape)[0],o=C.computeOutShape(t.map(u=>u.shape),a);if(v.sizeFromShape(o)===0)return n.makeTensorInfo(o,t[0].dtype,[]);let i=t.filter(u=>v.sizeFromShape(u.shape)>0);if(i.length===1)return Fs({inputs:{x:i[0]},backend:n});let l=i.map(u=>u.shape);return C.assertParamsConsistent(l,a),pp(i,a,n)}var A1e={kernelName:ll,backendName:"webgpu",kernelFunc:eT};function x1e(e,t,n,s,r=!1,a=null,o=!1,i=4,l=4,u=4){let c=R=>{switch(R){case 1:return"resData = x[xIndex];";case 3:return"resData = vec3<f32>(x[xIndex], x[xIndex + 1], x[xIndex + 2]);";case 4:return"resData = x[xIndex / 4];";default:throw new Error(`innerElementSize ${R} is not supported.`)}},p=R=>{switch(R){case 1:return"return W[row * uniforms.wShape[3] + colIn];";case 4:return"return W[row * uniforms.wShape[3] / 4 + colIn];";default:throw new Error(`innerElementSize ${R} is not supported.`)}},d=e?`
       let coord = vec4<i32>(batch, xRow, xCol, xCh);
       `:`
       let coord = vec4<i32>(batch, xCh, xRow, xCol);
@@ -5858,7 +5858,7 @@ return a / b;`,Gie=`
         ${x}
       }
       return ${nn(i)}(0.0);`,b=`${p(l)}`,w=nn(u),k=nn(e?i:l),S=nn(e?l:i);return`
-      ${Ca(a,o,u===4,4)}
+      ${Sa(a,o,u===4,4)}
       fn mm_readA(batch: i32, row : i32, colIn : i32) -> ${k} {
         ${e?A:b}
       }
@@ -5874,13 +5874,13 @@ return a / b;`,Gie=`
         var value = valueIn;
         let outWidth = ${e?"uniforms.outShape[2]":"uniforms.outShape[3]"};
         ${h}
-        ${dd(r,a)}
+        ${cd(r,a)}
         setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
         }
       }`}var b1e=class{constructor(e,t,n,s,r=!1,a=null,o=!1){this.variableNames=["x","W"],this.uniforms="filterDims : vec2<i32>, pad : vec2<i32>, stride : vec2<i32>, dilation : vec2<i32>, dimAOuter : i32, dimBOuter : i32, dimInner : i32,",this.outputShape=e.outShape,this.isChannelsLast=e.dataFormat==="channelsLast",this.isVec4=((e.inChannels%4===0||e.inChannels%3===0)&&this.isChannelsLast||e.outWidth%4===0&&!this.isChannelsLast)&&e.outChannels%4===0,this.dispatchLayout=this.isChannelsLast?{x:[3],y:[1,2],z:[0]}:{x:[2,3],y:[1],z:[0]},this.workGroupSize=nb(this.dispatchLayout,this.outputShape,this.isVec4),this.elementsPerThread=sb(this.dispatchLayout,this.outputShape,this.isVec4),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,this.elementsPerThread),this.isVec4?(this.isChannelsLast&&e.inChannels%4!==0?(this.innerElementSize=3,this.variableTypes=["f32","vec4<f32>"]):(this.innerElementSize=4,this.variableTypes=["vec4<f32>","vec4<f32>"]),r&&(this.variableNames.push("bias"),this.variableTypes.push("vec4<f32>")),o&&(this.variableNames.push("preluActivationWeights"),this.variableTypes.push("vec4<f32>"))):(this.innerElementSize=this.elementsPerThread[0],r&&this.variableNames.push("bias"),o&&this.variableNames.push("preluActivationWeights")),this.addBias=r,this.activation=a,this.hasPreluActivationWeights=o,this.tileAOuter=this.workGroupSize[1]*this.elementsPerThread[1],this.tileBOuter=this.workGroupSize[0]*this.elementsPerThread[0],this.tileInner=Math.max(this.workGroupSize[0]*this.innerElementSize,this.workGroupSize[1]),this.fitAOuter=t%this.tileAOuter===0,this.fitBOuter=n%this.tileBOuter===0,this.fitInner=s%this.tileInner===0,this.shaderKey=`conv2DMM_${this.elementsPerThread}_${this.activation}}_${this.fitAOuter}_${this.fitBOuter}_${this.fitInner}_${this.isVec4}_${this.innerElementSize}_${this.isChannelsLast}`}getUserCode(){let e=this.isVec4?ob(this.elementsPerThread,this.tileAOuter,this.tileBOuter,this.tileInner,this.innerElementSize,!this.isChannelsLast):ab(this.elementsPerThread,this.workGroupSize,!this.isChannelsLast,this.tileInner),t=this.isVec4?[this.isChannelsLast?this.innerElementSize:4,4,4]:[1,1,1];return`
     ${x1e(this.isChannelsLast,this.fitAOuter,this.fitBOuter,this.fitInner,this.addBias,this.activation,this.hasPreluActivationWeights,t[0],t[1],t[2])}
     ${e}
-  `}};function V7(e,t){let n=e.length;return n>=3?t?[...e.slice(0,-3),e[n-3]*e[n-2],e[n-1]]:[...e.slice(0,-3),e[n-3],e[n-2]*e[n-1]]:!t&&n===1&&e[0]>1?[e[0],1]:null}function v1e({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let l=n.dataFormat==="channelsLast",u=!l,c=!1,p=l&&n.filterHeight===n.inHeight&&n.filterWidth===n.inWidth&&n.padInfo.type==="VALID",d=[],h,f;if(p){let y=n.inHeight*n.inWidth*n.inChannels;h=Ue({inputs:{x:e},backend:s,attrs:{shape:[1,n.batchSize,y]}}),f=Ue({inputs:{x:t},backend:s,attrs:{shape:[1,y,n.outChannels]}})}else h=Ue({inputs:{x:e},backend:s,attrs:{shape:l?[n.batchSize,n.inHeight*n.inWidth,n.inChannels]:[n.batchSize,n.inChannels,n.inHeight*n.inWidth]}}),f=Ue({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}});if(d.push(h),d.push(f),a!=null){let y=V7(a.shape,l);y!=null&&(a=Ue({inputs:{x:a},backend:s,attrs:{shape:y}}),d.push(a))}if(r!=null){let y=V7(r.shape,l);y!=null&&(r=Ue({inputs:{x:r},backend:s,attrs:{shape:y}}),d.push(r))}let m=ib({a:l?h:f,b:l?f:h,transposeA:u,transposeB:c,backend:s,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o}),g=Ue({inputs:{x:m},backend:s,attrs:{shape:n.outShape}});d.push(m);for(let y of d)s.disposeData(y.dataId);return g}function tT({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let l=r!=null,u=a!=null,c=n.dataFormat==="channelsLast";if(c&&n.filterHeight===n.inHeight&&n.filterWidth===n.inWidth&&n.padInfo.type==="VALID"||n.filterHeight===1&&n.filterWidth===1&&n.dilationHeight===1&&n.dilationWidth===1&&n.strideHeight===1&&n.strideWidth===1&&(n.padInfo.type==="SAME"||n.padInfo.type==="VALID"))return v1e({x:e,filter:t,convInfo:n,backend:s,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o});let d=c?n.outHeight*n.outWidth:n.outChannels,h=c?n.outChannels:n.outHeight*n.outWidth,f=n.filterHeight*n.filterWidth*n.inChannels,m=[n.padInfo.top,n.padInfo.left],g=[{type:"int32",data:[n.filterHeight,n.filterWidth]},{type:"int32",data:[...m]},{type:"int32",data:[n.strideHeight,n.strideWidth]},{type:"int32",data:[n.dilationHeight,n.dilationWidth]},{type:"int32",data:[d]},{type:"int32",data:[h]},{type:"int32",data:[f]}],y=new b1e(n,d,h,f,l,i,u),x=[],A=[e,t];l&&(!c&&r.shape.length===1&&(r=Ue({inputs:{x:r},backend:s,attrs:{shape:[r.shape[0],1,1]}}),x.push(r)),A.push(r)),u&&(!c&&a.shape.length===1&&(a=Ue({inputs:{x:a},backend:s,attrs:{shape:[a.shape[0],1,1]}}),x.push(a)),A.push(a)),i==="leakyrelu"&&(g.push({type:"float32",data:[o]}),y.uniforms+=" alpha : f32,");let b=s.runWebGPUProgram(y,A,e.dtype,g);for(let w of x)s.disposeData(w.dataId);return b}function w1e(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=n,p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,a.shape,o,u,i,c,!1,p);return tT({x:r,filter:a,convInfo:d,backend:s})}var k1e={kernelName:Ao,backendName:"webgpu",kernelFunc:w1e};function I1e(e=4){let t=a=>{switch(a){case 1:return"return W[getIndexFromCoords4D(coord, uniforms.wShape)];";case 4:return`
+  `}};function V7(e,t){let n=e.length;return n>=3?t?[...e.slice(0,-3),e[n-3]*e[n-2],e[n-1]]:[...e.slice(0,-3),e[n-3],e[n-2]*e[n-1]]:!t&&n===1&&e[0]>1?[e[0],1]:null}function v1e({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let l=n.dataFormat==="channelsLast",u=!l,c=!1,p=l&&n.filterHeight===n.inHeight&&n.filterWidth===n.inWidth&&n.padInfo.type==="VALID",d=[],h,f;if(p){let y=n.inHeight*n.inWidth*n.inChannels;h=Ue({inputs:{x:e},backend:s,attrs:{shape:[1,n.batchSize,y]}}),f=Ue({inputs:{x:t},backend:s,attrs:{shape:[1,y,n.outChannels]}})}else h=Ue({inputs:{x:e},backend:s,attrs:{shape:l?[n.batchSize,n.inHeight*n.inWidth,n.inChannels]:[n.batchSize,n.inChannels,n.inHeight*n.inWidth]}}),f=Ue({inputs:{x:t},backend:s,attrs:{shape:[1,n.inChannels,n.outChannels]}});if(d.push(h),d.push(f),a!=null){let y=V7(a.shape,l);y!=null&&(a=Ue({inputs:{x:a},backend:s,attrs:{shape:y}}),d.push(a))}if(r!=null){let y=V7(r.shape,l);y!=null&&(r=Ue({inputs:{x:r},backend:s,attrs:{shape:y}}),d.push(r))}let m=ib({a:l?h:f,b:l?f:h,transposeA:u,transposeB:c,backend:s,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o}),g=Ue({inputs:{x:m},backend:s,attrs:{shape:n.outShape}});d.push(m);for(let y of d)s.disposeData(y.dataId);return g}function tT({x:e,filter:t,convInfo:n,backend:s,bias:r=null,preluActivationWeights:a=null,leakyreluAlpha:o=0,activation:i=null}){let l=r!=null,u=a!=null,c=n.dataFormat==="channelsLast";if(c&&n.filterHeight===n.inHeight&&n.filterWidth===n.inWidth&&n.padInfo.type==="VALID"||n.filterHeight===1&&n.filterWidth===1&&n.dilationHeight===1&&n.dilationWidth===1&&n.strideHeight===1&&n.strideWidth===1&&(n.padInfo.type==="SAME"||n.padInfo.type==="VALID"))return v1e({x:e,filter:t,convInfo:n,backend:s,bias:r,activation:i,preluActivationWeights:a,leakyreluAlpha:o});let d=c?n.outHeight*n.outWidth:n.outChannels,h=c?n.outChannels:n.outHeight*n.outWidth,f=n.filterHeight*n.filterWidth*n.inChannels,m=[n.padInfo.top,n.padInfo.left],g=[{type:"int32",data:[n.filterHeight,n.filterWidth]},{type:"int32",data:[...m]},{type:"int32",data:[n.strideHeight,n.strideWidth]},{type:"int32",data:[n.dilationHeight,n.dilationWidth]},{type:"int32",data:[d]},{type:"int32",data:[h]},{type:"int32",data:[f]}],y=new b1e(n,d,h,f,l,i,u),x=[],A=[e,t];l&&(!c&&r.shape.length===1&&(r=Ue({inputs:{x:r},backend:s,attrs:{shape:[r.shape[0],1,1]}}),x.push(r)),A.push(r)),u&&(!c&&a.shape.length===1&&(a=Ue({inputs:{x:a},backend:s,attrs:{shape:[a.shape[0],1,1]}}),x.push(a)),A.push(a)),i==="leakyrelu"&&(g.push({type:"float32",data:[o]}),y.uniforms+=" alpha : f32,");let b=s.runWebGPUProgram(y,A,e.dtype,g);for(let w of x)s.disposeData(w.dataId);return b}function w1e(e){let{inputs:t,attrs:n,backend:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=n,p=C.convertConv2DDataFormat(l),d=C.computeConv2DInfo(r.shape,a.shape,o,u,i,c,!1,p);return tT({x:r,filter:a,convInfo:d,backend:s})}var k1e={kernelName:yo,backendName:"webgpu",kernelFunc:w1e};function I1e(e=4){let t=a=>{switch(a){case 1:return"return W[getIndexFromCoords4D(coord, uniforms.wShape)];";case 4:return`
             let coord1 = vec4<i32>(coordX, coordY, col + 1, rowInner);
             let coord2 = vec4<i32>(coordX, coordY, col + 2, rowInner);
             let coord3 = vec4<i32>(coordX, coordY, col + 3, rowInner);
@@ -5995,7 +5995,7 @@ return a / b;`,Gie=`
         setOutputAtIndex(index, dotProd);
       }
     }
-  `}};function T1e(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=s,p=C.convertConv2DDataFormat(u),d=C.computeConv2DInfo(o,a.shape,i,1,l,c,!1,p),h=[{type:"int32",data:[d.filterHeight,d.filterWidth]},{type:"int32",data:[d.filterHeight-1-d.padInfo.top,d.filterWidth-1-d.padInfo.left]},{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.batchSize,d.outHeight,d.outWidth,d.outChannels]}],f;if(Z().getBool("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE"))f=new C1e(d);else{f=new S1e(d);let m=d.inShape[1]*d.inShape[2],g=d.inShape[3],y=d.filterHeight*d.filterWidth*d.outChannels;h.push({type:"uint32",data:[m]},{type:"uint32",data:[g]},{type:"uint32",data:[y]})}return n.runWebGPUProgram(f,[r,a],"float32",h)}var N1e={kernelName:xo,backendName:"webgpu",kernelFunc:T1e},E1e=Dn({opType:Fe.COS}),R1e={kernelName:bo,backendName:"webgpu",kernelFunc:E1e},_1e=Dn({opType:Fe.COSH}),D1e={kernelName:vo,backendName:"webgpu",kernelFunc:_1e},$1e=class{constructor(e,t,n,s){this.variableNames=["Image","Boxes","BoxInd"],this.uniforms="extrapolationValue : f32,",this.workGroupSize=[64,1,1],this.size=!0;let[r]=t;this.outputShape=[r,n[0],n[1],e],this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.methodId=s==="bilinear"?1:0,this.cropHeightBiggerThan1=this.outputShape[1]>1,this.cropWidthBiggerThan1=this.outputShape[2]>1,this.shaderKey=`cropAndResize_${this.methodId}_${this.cropHeightBiggerThan1}_${this.cropWidthBiggerThan1}`}getUserCode(){let[e,t]=["f32(uniforms.imageShape[1] - 1)","f32(uniforms.imageShape[2] - 1)"],[n,s,r]=this.cropHeightBiggerThan1?[`(${e} / f32(uniforms.outShape[1] - 1))`,"(y2-y1) * height_ratio",`y1*${e} + f32(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${e}`],[a,o,i]=this.cropWidthBiggerThan1?[`(${t} / f32(uniforms.outShape[2] - 1))`,"(x2-x1) * width_ratio",`x1*${t} + f32(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${t}`];return`
+  `}};function T1e(e){let{inputs:t,backend:n,attrs:s}=e,{dy:r,filter:a}=t,{inputShape:o,strides:i,pad:l,dataFormat:u,dimRoundingMode:c}=s,p=C.convertConv2DDataFormat(u),d=C.computeConv2DInfo(o,a.shape,i,1,l,c,!1,p),h=[{type:"int32",data:[d.filterHeight,d.filterWidth]},{type:"int32",data:[d.filterHeight-1-d.padInfo.top,d.filterWidth-1-d.padInfo.left]},{type:"int32",data:[d.strideHeight,d.strideWidth]},{type:"int32",data:[d.batchSize,d.outHeight,d.outWidth,d.outChannels]}],f;if(X().getBool("WEBGPU_USE_NAIVE_CONV2D_TRANSPOSE"))f=new C1e(d);else{f=new S1e(d);let m=d.inShape[1]*d.inShape[2],g=d.inShape[3],y=d.filterHeight*d.filterWidth*d.outChannels;h.push({type:"uint32",data:[m]},{type:"uint32",data:[g]},{type:"uint32",data:[y]})}return n.runWebGPUProgram(f,[r,a],"float32",h)}var N1e={kernelName:Ao,backendName:"webgpu",kernelFunc:T1e},E1e=Dn({opType:Fe.COS}),R1e={kernelName:xo,backendName:"webgpu",kernelFunc:E1e},_1e=Dn({opType:Fe.COSH}),D1e={kernelName:bo,backendName:"webgpu",kernelFunc:_1e},$1e=class{constructor(e,t,n,s){this.variableNames=["Image","Boxes","BoxInd"],this.uniforms="extrapolationValue : f32,",this.workGroupSize=[64,1,1],this.size=!0;let[r]=t;this.outputShape=[r,n[0],n[1],e],this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.methodId=s==="bilinear"?1:0,this.cropHeightBiggerThan1=this.outputShape[1]>1,this.cropWidthBiggerThan1=this.outputShape[2]>1,this.shaderKey=`cropAndResize_${this.methodId}_${this.cropHeightBiggerThan1}_${this.cropWidthBiggerThan1}`}getUserCode(){let[e,t]=["f32(uniforms.imageShape[1] - 1)","f32(uniforms.imageShape[2] - 1)"],[n,s,r]=this.cropHeightBiggerThan1?[`(${e} / f32(uniforms.outShape[1] - 1))`,"(y2-y1) * height_ratio",`y1*${e} + f32(y)*(height_scale)`]:["0.0","0.0",`0.5 * (y1+y2) * ${e}`],[a,o,i]=this.cropWidthBiggerThan1?[`(${t} / f32(uniforms.outShape[2] - 1))`,"(x2-x1) * width_ratio",`x1*${t} + f32(x)*(width_scale)`]:["0.0","0.0",`0.5 * (x1+x2) * ${t}`];return`
       ${lt()}
       if (index < uniforms.size) {
         let coords = getCoordsFromIndex(index);
@@ -6051,7 +6051,7 @@ return a / b;`,Gie=`
         }
       }
     }
-    `}},P1e=e=>{let{inputs:t,backend:n,attrs:s}=e,{image:r,boxes:a,boxInd:o}=t,{cropSize:i,method:l,extrapolationValue:u}=s,c=new $1e(r.shape[3],a.shape,i,l),p=[{type:"float32",data:[u]}];return n.runWebGPUProgram(c,[r,a,o],"float32",p)},F1e={kernelName:dl,backendName:"webgpu",kernelFunc:P1e},Op;(function(e){e.Prod="*",e.Sum="+"})(Op||(Op={}));var U7=class{constructor(e,t,n,s){this.variableNames=["x"],this.uniforms="index : f32,",this.size=!0;let r=128;this.workGroupSize=[r,1,1],this.outputShape=t,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.exclusive=n,this.reverse=s,this.op=e,this.shaderKey=`cum_${this.op}_${this.exclusive}_${this.reverse}`}getUserCode(){let e=this.outputShape.length,t=this.op===Op.Prod?"1.0":"0.0",n=this.exclusive?t:`getX(${G7(e,"coords",this.op)})`,s=this.outputShape[this.outputShape.length-1],r="",a="";return this.exclusive?(r=this.reverse?`end != ${s-1}`:"end != 0",a=this.reverse?"end + 1":"end - 1"):(r=this.reverse?`end + pow2 < ${s}`:"end >= pow2",a=this.reverse?"end + pow2":"end - pow2"),`
+    `}},P1e=e=>{let{inputs:t,backend:n,attrs:s}=e,{image:r,boxes:a,boxInd:o}=t,{cropSize:i,method:l,extrapolationValue:u}=s,c=new $1e(r.shape[3],a.shape,i,l),p=[{type:"float32",data:[u]}];return n.runWebGPUProgram(c,[r,a,o],"float32",p)},F1e={kernelName:cl,backendName:"webgpu",kernelFunc:P1e},Fp;(function(e){e.Prod="*",e.Sum="+"})(Fp||(Fp={}));var U7=class{constructor(e,t,n,s){this.variableNames=["x"],this.uniforms="index : f32,",this.size=!0;let r=128;this.workGroupSize=[r,1,1],this.outputShape=t,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.exclusive=n,this.reverse=s,this.op=e,this.shaderKey=`cum_${this.op}_${this.exclusive}_${this.reverse}`}getUserCode(){let e=this.outputShape.length,t=this.op===Fp.Prod?"1.0":"0.0",n=this.exclusive?t:`getX(${G7(e,"coords",this.op)})`,s=this.outputShape[this.outputShape.length-1],r="",a="";return this.exclusive?(r=this.reverse?`end != ${s-1}`:"end != 0",a=this.reverse?"end + 1":"end - 1"):(r=this.reverse?`end + pow2 < ${s}`:"end >= pow2",a=this.reverse?"end + pow2":"end - pow2"),`
       ${lt()}
        if (index < uniforms.size) {
          var coords = getCoordsFromIndex(index);
@@ -6067,7 +6067,7 @@ return a / b;`,Gie=`
          setOutputAtIndex(index, val);
        }
       }
-    `}};function G7(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function H7(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function nT(e,t,n,s,r,a){let o=t.shape.length,i=C.getAxesPermutation([s],o),l=t;i!=null&&(l=Aa({inputs:{x:t},backend:n,attrs:{perm:i}}));let u=C.getInnerMostAxes(1,o)[0];if(u!==o-1)throw new Error(`WebGPU cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${s}`);let c=l.shape[u],p=Fs({inputs:{x:l},backend:n});for(let d=0;d<=Math.ceil(Math.log2(c))-1;d++){let h=new U7(e,l.shape,!1,a),f=p,m=[{type:"float32",data:[d]}];p=n.runWebGPUProgram(h,[p],p.dtype,m),n.disposeData(f.dataId)}if(r){let d=new U7(e,l.shape,r,a),h=p,f=[{type:"float32",data:[0]}];p=n.runWebGPUProgram(d,[p],p.dtype,f),n.disposeData(h.dataId)}if(i!=null){let d=C.getUndoAxesPermutation(i),h=Aa({inputs:{x:p},backend:n,attrs:{perm:d}});return n.disposeData(p.dataId),n.disposeData(l.dataId),h}return p}function O1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return nT(Op.Prod,r,n,a,o,i)}var M1e={kernelName:cl,backendName:"webgpu",kernelFunc:O1e};function z1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return nT(Op.Sum,r,n,a,o,i)}var L1e={kernelName:wo,backendName:"webgpu",kernelFunc:z1e},B1e=class{constructor(e,t){this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.uniforms="blockSize : i32,",this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`depthToSpace_${t}`,this.dataFormat=t}getUserCode(){return`
+    `}};function G7(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.x, ${t}.y`;if(e===3)return`${t}.x, ${t}.y, ${t}.z`;if(e===4)return`${t}.x, ${t}.y, ${t}.z, ${t}.w`;throw Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function H7(e,t,n){if(e===1)return`${t}`;if(e===2)return`${t}.y`;if(e===3)return`${t}.z`;if(e===4)return`${t}.w`;throw Error(`Cumulative ${n} for rank ${e} is not yet supported`)}function nT(e,t,n,s,r,a){let o=t.shape.length,i=C.getAxesPermutation([s],o),l=t;i!=null&&(l=ya({inputs:{x:t},backend:n,attrs:{perm:i}}));let u=C.getInnerMostAxes(1,o)[0];if(u!==o-1)throw new Error(`WebGPU cumprod shader expects an inner-most axis=${t.shape.length-1} but got axis=${s}`);let c=l.shape[u],p=Fs({inputs:{x:l},backend:n});for(let d=0;d<=Math.ceil(Math.log2(c))-1;d++){let h=new U7(e,l.shape,!1,a),f=p,m=[{type:"float32",data:[d]}];p=n.runWebGPUProgram(h,[p],p.dtype,m),n.disposeData(f.dataId)}if(r){let d=new U7(e,l.shape,r,a),h=p,f=[{type:"float32",data:[0]}];p=n.runWebGPUProgram(d,[p],p.dtype,f),n.disposeData(h.dataId)}if(i!=null){let d=C.getUndoAxesPermutation(i),h=ya({inputs:{x:p},backend:n,attrs:{perm:d}});return n.disposeData(p.dataId),n.disposeData(l.dataId),h}return p}function O1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return nT(Fp.Prod,r,n,a,o,i)}var M1e={kernelName:ul,backendName:"webgpu",kernelFunc:O1e};function z1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,exclusive:o,reverse:i}=s;return nT(Fp.Sum,r,n,a,o,i)}var L1e={kernelName:vo,backendName:"webgpu",kernelFunc:z1e},B1e=class{constructor(e,t){this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.uniforms="blockSize : i32,",this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`depthToSpace_${t}`,this.dataFormat=t}getUserCode(){return`
       ${lt()}
         if (index < uniforms.size) {
           let coords = getCoordsFromIndex(index);
@@ -6087,8 +6087,8 @@ return a / b;`,Gie=`
           let rlt = ${this.getInputSamplingString()};
           setOutputAtIndex(index, rlt);
         }
-      }`}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?"uniforms.outShape[3]":"uniforms.outShape[1]"}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function W1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockSize:a,dataFormat:o}=s,i=r.shape[0],l=o==="NHWC"?r.shape[1]:r.shape[2],u=o==="NHWC"?r.shape[2]:r.shape[3],c=o==="NHWC"?r.shape[3]:r.shape[1],p=l*a,d=u*a,h=c/(a*a),f=o==="NHWC"?[i,p,d,h]:[i,h,p,d],m=[{type:"int32",data:[a]}],g=new B1e(f,o);return n.runWebGPUProgram(g,[r],r.dtype,m)}var V1e={kernelName:pl,backendName:"webgpu",kernelFunc:W1e},U1e=class{constructor(e,t,n,s=!1,r=null,a=!1){this.variableNames=["x","W"],this.uniforms="pad : vec2<i32>, inDims : vec2<i32>,",this.workGroupSize=[16,16,1],this.outputShape=e,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),s&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),this.addBias=s,this.activation=r,this.hasPreluActivation=a,this.filterHeight=t,this.filterWidth=n,this.shaderKey=`depthwiseNCHW_${this.activation}_${this.filterHeight}_${this.filterWidth}`}getUserCode(){let e=this.filterWidth*this.filterHeight,t=this.workGroupSize[0]*this.workGroupSize[1]*this.workGroupSize[2],n=this.workGroupSize[1]+this.filterHeight-1,s=this.workGroupSize[0]+this.filterWidth-1;return`
-      ${Ca(this.activation,this.hasPreluActivation,!1,4)}
+      }`}getHeightCoordString(){return this.dataFormat==="NHWC"?"coords[1]":"coords[2]"}getWidthCoordString(){return this.dataFormat==="NHWC"?"coords[2]":"coords[3]"}getDepthCoordString(){return this.dataFormat==="NHWC"?"coords[3]":"coords[1]"}getOutputDepthSize(){return this.dataFormat==="NHWC"?"uniforms.outShape[3]":"uniforms.outShape[1]"}getInputSamplingString(){return this.dataFormat==="NHWC"?"getX(b, in_h, in_w, in_d)":"getX(b, in_d, in_h, in_w)"}};function W1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockSize:a,dataFormat:o}=s,i=r.shape[0],l=o==="NHWC"?r.shape[1]:r.shape[2],u=o==="NHWC"?r.shape[2]:r.shape[3],c=o==="NHWC"?r.shape[3]:r.shape[1],p=l*a,d=u*a,h=c/(a*a),f=o==="NHWC"?[i,p,d,h]:[i,h,p,d],m=[{type:"int32",data:[a]}],g=new B1e(f,o);return n.runWebGPUProgram(g,[r],r.dtype,m)}var V1e={kernelName:dl,backendName:"webgpu",kernelFunc:W1e},U1e=class{constructor(e,t,n,s=!1,r=null,a=!1){this.variableNames=["x","W"],this.uniforms="pad : vec2<i32>, inDims : vec2<i32>,",this.workGroupSize=[16,16,1],this.outputShape=e,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),s&&this.variableNames.push("bias"),a&&this.variableNames.push("preluActivationWeights"),this.addBias=s,this.activation=r,this.hasPreluActivation=a,this.filterHeight=t,this.filterWidth=n,this.shaderKey=`depthwiseNCHW_${this.activation}_${this.filterHeight}_${this.filterWidth}`}getUserCode(){let e=this.filterWidth*this.filterHeight,t=this.workGroupSize[0]*this.workGroupSize[1]*this.workGroupSize[2],n=this.workGroupSize[1]+this.filterHeight-1,s=this.workGroupSize[0]+this.filterWidth-1;return`
+      ${Sa(this.activation,this.hasPreluActivation,!1,4)}
 
       var<workgroup> mm_Asub : array<array<f32, ${s}>, ${n}>;
       var<workgroup> mm_Bsub : array<array<f32, ${this.filterWidth}>, ${this.filterHeight}>;
@@ -6101,7 +6101,7 @@ return a / b;`,Gie=`
         return value;
       }
 
-      ${T2()}
+      ${C2()}
       fn main(@builtin(local_invocation_id) LocalId : vec3<u32>,
               @builtin(global_invocation_id) GlobalId : vec3<u32>,
               @builtin(local_invocation_index) LocalIndex: u32,
@@ -6152,13 +6152,13 @@ return a / b;`,Gie=`
             value = fma(xVal, wVal, value);
           }
         }
-        ${dd(this.addBias,this.activation)}
+        ${cd(this.addBias,this.activation)}
         if (coordsInBounds4D(coords, uniforms.outShape)) {
           setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
         }
       }
     `}},sT=class{constructor(e,t=!1,n=null,s=!1){this.variableNames=["x","W"],this.uniforms="pad : vec2<i32>, inDims : vec2<i32>,",this.workGroupSize=[4,4,4],this.isVec4=!0,this.outputShape=e.outShape,this.dispatchLayout={x:[3],y:[2],z:[0,1]},this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[4,4,1]),v.assert(e.dataFormat==="channelsLast",()=>"TODO: NCHW is unimplemented"),t&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=n,this.hasPreluActivation=s,this.shaderKey=`depthwiseVec4_${n}_${this.convInfo.filterHeight}_${this.convInfo.filterWidth}`}getUserCode(){let e=4+this.convInfo.filterWidth-1;return`
-      ${Ca(this.activation,this.hasPreluActivation,!0,4)}
+      ${Sa(this.activation,this.hasPreluActivation,!0,4)}
       fn readX(batch : i32, row : i32, col : i32, channel : i32) -> vec4<f32> {
         var value = vec4<f32>(0.0);
         if (row >=0 && row < uniforms.inDims[0] && col >=0 && col < uniforms.inDims[1])
@@ -6167,7 +6167,7 @@ return a / b;`,Gie=`
         }
         return value;
       }
-      ${T2()}
+      ${C2()}
       fn main(@builtin(global_invocation_id) globalId: vec3<u32>) {
         let batch = i32(globalId.z) / uniforms.outShape[1];
         let r = i32(globalId.z) % uniforms.outShape[1];
@@ -6204,16 +6204,16 @@ return a / b;`,Gie=`
           let coords = vec4<i32>(batch, r, c + i, d1);
           if (coordsInBounds4D(coords, uniforms.outShape)) {
             var value = dotProd[i];
-            ${dd(this.addBias,this.activation)}
+            ${cd(this.addBias,this.activation)}
             setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
           }
         }
       }
     `}},rT=class{constructor(e,t=!1,n=null,s=!1){this.variableNames=["x","W"],this.uniforms=`pad : vec2<i32>, inDims : vec2<i32>, filterHeight : i32,
       filterWidth : i32, stride : vec2<i32>, dilation : vec2<i32>,`,this.workGroupSize=[256,1,1],this.outputShape=e.outShape,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.isChannelsLast=e.dataFormat==="channelsLast",t&&this.variableNames.push("bias"),s&&this.variableNames.push("preluActivationWeights"),this.convInfo=e,this.addBias=t,this.activation=n,this.hasPreluActivation=s,this.shaderKey=`depthwise_${this.activation}_${this.isChannelsLast}`}getUserCode(){let e=this.isChannelsLast?"getX(batch, xR, xC, d1);":"getX(batch, d1, xR, xC);";return`
-      ${Ca(this.activation,this.hasPreluActivation,!1,4)}
+      ${Sa(this.activation,this.hasPreluActivation,!1,4)}
 
-      ${pd()}
+      ${dd()}
         let coords = getOutputCoords();
         let batch = coords[0];
         let xRCCorner = vec2<i32>(coords.${this.isChannelsLast?"yz":"zw"}) * uniforms.stride - uniforms.pad;
@@ -6271,12 +6271,12 @@ return a / b;`,Gie=`
               }
             }
           }
-          ${dd(this.addBias,this.activation)}
+          ${cd(this.addBias,this.activation)}
         if (coordsInBounds4D(coords, uniforms.outShape)) {
           setOutputAtCoords(coords[0], coords[1], coords[2], coords[3], value);
         }
       }
-    `}};function G1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=s,p=C.convertConv2DDataFormat(l),d=u;d==null&&(d=[1,1]);let h=C.computeConv2DInfo(r.shape,a.shape,o,d,i,c,!0,p),f=[{type:"int32",data:[h.padInfo.top,h.padInfo.left]},{type:"int32",data:[h.inHeight,h.inWidth]}],m=h.dataFormat==="channelsLast",g;return!m&&h.inHeight>16&&h.inWidth>16&&h.strideHeight===1&&h.strideWidth===1&&h.dilationWidth===1&&h.dilationHeight===1&&h.inChannels===h.outChannels?g=new U1e(h.outShape,h.filterHeight,h.filterWidth):m&&h.inHeight>4&&h.inWidth>4&&h.strideHeight===1&&h.strideWidth===1&&h.inChannels===h.outChannels&&h.dilationHeight===1&&h.dilationWidth===1&&h.inChannels%4===0?g=new sT(h):(g=new rT(h),f.push({type:"int32",data:[h.filterHeight]},{type:"int32",data:[h.filterWidth]},{type:"int32",data:[h.strideHeight,h.strideWidth]},{type:"int32",data:[h.dilationHeight,h.dilationWidth]})),n.runWebGPUProgram(g,[r,a],r.dtype,f)}var H1e={kernelName:ko,backendName:"webgpu",kernelFunc:G1e},aT=os({opType:Ye.MUL,cpuKernelImpl:b2e,supportsComplex:!0}),j1e={kernelName:Wo,backendName:"webgpu",kernelFunc:aT},q1e=class{constructor(e,t){this.workGroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="reduceSize : i32,",this.size=!0,this.inputShape=[e.batchSize,e.inSize];let[n]=C.computeOutAndReduceShapes(this.inputShape,[1]);this.outputShape=n.length===0?[1]:n,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,[1,1,1]),this.reduceType=t,this.shaderKey=`reduce_${t}`}getUserCode(){let e="",t="0.0";this.reduceType==="min"||this.reduceType==="max"?(e=`
+    `}};function G1e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a}=t,{strides:o,pad:i,dataFormat:l,dilations:u,dimRoundingMode:c}=s,p=C.convertConv2DDataFormat(l),d=u;d==null&&(d=[1,1]);let h=C.computeConv2DInfo(r.shape,a.shape,o,d,i,c,!0,p),f=[{type:"int32",data:[h.padInfo.top,h.padInfo.left]},{type:"int32",data:[h.inHeight,h.inWidth]}],m=h.dataFormat==="channelsLast",g;return!m&&h.inHeight>16&&h.inWidth>16&&h.strideHeight===1&&h.strideWidth===1&&h.dilationWidth===1&&h.dilationHeight===1&&h.inChannels===h.outChannels?g=new U1e(h.outShape,h.filterHeight,h.filterWidth):m&&h.inHeight>4&&h.inWidth>4&&h.strideHeight===1&&h.strideWidth===1&&h.inChannels===h.outChannels&&h.dilationHeight===1&&h.dilationWidth===1&&h.inChannels%4===0?g=new sT(h):(g=new rT(h),f.push({type:"int32",data:[h.filterHeight]},{type:"int32",data:[h.filterWidth]},{type:"int32",data:[h.strideHeight,h.strideWidth]},{type:"int32",data:[h.dilationHeight,h.dilationWidth]})),n.runWebGPUProgram(g,[r,a],r.dtype,f)}var H1e={kernelName:wo,backendName:"webgpu",kernelFunc:G1e},aT=os({opType:Ye.MUL,cpuKernelImpl:b2e,supportsComplex:!0}),j1e={kernelName:Bo,backendName:"webgpu",kernelFunc:aT},q1e=class{constructor(e,t){this.workGroupSize=[64,1,1],this.variableNames=["x"],this.uniforms="reduceSize : i32,",this.size=!0,this.inputShape=[e.batchSize,e.inSize];let[n]=C.computeOutAndReduceShapes(this.inputShape,[1]);this.outputShape=n.length===0?[1]:n,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,[1,1,1]),this.reduceType=t,this.shaderKey=`reduce_${t}`}getUserCode(){let e="",t="0.0";this.reduceType==="min"||this.reduceType==="max"?(e=`
          if (isnan(candidate)) {
           bestValue = uniforms.NAN;
          } else if (!isnan(bestValue) && candidate ${this.reduceType==="min"?"<":">"} bestValue)
@@ -6324,7 +6324,7 @@ return a / b;`,Gie=`
           ${n}
         }
        }
-     `}};function Vh(e,t,n,s,r){let a=e.shape.length,o=[],i=v.parseAxisParam(t,e.shape),l=i,u=C.getAxesPermutation(l,a),c=e;u!=null&&(c=Aa({inputs:{x:e},attrs:{perm:u},backend:r}),l=C.getInnerMostAxes(l.length,a),o.push(c)),C.assertAxesAreInnerMostDims(s,l,a);let[p,d]=C.computeOutAndReduceShapes(c.shape,l),h=p;n&&(h=C.expandShapeToKeepDim(p,i));let f;if((s==="max"||s==="prod")&&r.shouldExecuteOnCPU([c])){let m=r.tensorMap.get(c.dataId).values;switch(s){case"max":let g=y2e(m,v.sizeFromShape(d),h,e.dtype);f=r.makeTensorInfo(h,e.dtype,g);break;case"prod":let{outVals:y,outShape:x,outDtype:A}=k2e(c.shape,c.dtype,m,l);f=r.makeTensorInfo(x,A,y);break;default:throw new Error(`${s} CPU implementation is not yet supported.`)}}else{let m=v.sizeFromShape(d),y=v.sizeFromShape(c.shape)/m,x={windowSize:m,inSize:m,batchSize:y,outSize:1},A=s==="mean"?"float32":sh(e.dtype),b=[{type:"int32",data:[m]}],w=new q1e(x,s),k=r.runWebGPUProgram(w,[c],A,b);o.push(k),f=Ue({inputs:{x:k},attrs:{shape:h},backend:r})}return o.forEach(m=>r.disposeData(m.dataId)),f}function lb(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Vh(r,a,o,"sum",n)}var X1e={kernelName:ei,backendName:"webgpu",kernelFunc:lb};function K1e(e){let{inputs:t,backend:n,attrs:s}=e,{equation:r}=s,a=t,{allDims:o,summedDims:i,idDims:l}=C.decodeEinsumEquation(r,a.length);C.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=C.getEinsumComputePath(i,l),p=c.length,d=null,h=o.length,f=[];for(let m=0;m<p;++m){for(let g of c[m]){let{permutationIndices:y,expandDims:x}=C.getEinsumPermutation(h,l[g]),A;C.isIdentityPermutation(y)?A=a[g]:(A=Aa({inputs:{x:a[g]},backend:n,attrs:{perm:y}}),f.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=Ue({inputs:{x:A},backend:n,attrs:{shape:b}}),f.push(A)),d===null?d=A:(d=aT({inputs:{a:A,b:d},backend:n}),f.push(d))}m<p-1&&(u[m]>=0&&(d=lb({inputs:{x:d},backend:n,attrs:{axis:u[m]-(o.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&n.disposeData(m.dataId);return d}var Z1e={kernelName:Up,backendName:"webgpu",kernelFunc:K1e},Y1e=Dn({opType:Fe.ELU}),J1e={kernelName:So,backendName:"webgpu",kernelFunc:Y1e},Q1e=os({opType:Ye.EQUAL,dtype:"bool",cpuKernelImpl:o2e}),ege={kernelName:hl,backendName:"webgpu",kernelFunc:Q1e},oT=Dn({opType:Fe.EXP,cpuKernelImpl:i2e,dtype:"float32"}),tge={kernelName:Co,backendName:"webgpu",kernelFunc:oT};function yy(e){let{inputs:t,attrs:n,backend:s}=e,{dim:r}=n,{input:a}=t,o=a.shape.length,i=a.shape.slice(),l=r;return r<0&&(v.assert(-(o+1)<=r,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+r+1),i.splice(l,0,1),Ue({inputs:{x:a},backend:s,attrs:{shape:i}})}var nge={kernelName:fl,backendName:"webgpu",kernelFunc:yy},sge=Dn({opType:Fe.EXPM1,cpuKernelImpl:l2e}),rge={kernelName:ml,backendName:"webgpu",kernelFunc:sge},age=class{constructor(e){this.outputShape=[],this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="flipLeftRight"}getUserCode(){return`
+     `}};function Wh(e,t,n,s,r){let a=e.shape.length,o=[],i=v.parseAxisParam(t,e.shape),l=i,u=C.getAxesPermutation(l,a),c=e;u!=null&&(c=ya({inputs:{x:e},attrs:{perm:u},backend:r}),l=C.getInnerMostAxes(l.length,a),o.push(c)),C.assertAxesAreInnerMostDims(s,l,a);let[p,d]=C.computeOutAndReduceShapes(c.shape,l),h=p;n&&(h=C.expandShapeToKeepDim(p,i));let f;if((s==="max"||s==="prod")&&r.shouldExecuteOnCPU([c])){let m=r.tensorMap.get(c.dataId).values;switch(s){case"max":let g=y2e(m,v.sizeFromShape(d),h,e.dtype);f=r.makeTensorInfo(h,e.dtype,g);break;case"prod":let{outVals:y,outShape:x,outDtype:A}=k2e(c.shape,c.dtype,m,l);f=r.makeTensorInfo(x,A,y);break;default:throw new Error(`${s} CPU implementation is not yet supported.`)}}else{let m=v.sizeFromShape(d),y=v.sizeFromShape(c.shape)/m,x={windowSize:m,inSize:m,batchSize:y,outSize:1},A=s==="mean"?"float32":nh(e.dtype),b=[{type:"int32",data:[m]}],w=new q1e(x,s),k=r.runWebGPUProgram(w,[c],A,b);o.push(k),f=Ue({inputs:{x:k},attrs:{shape:h},backend:r})}return o.forEach(m=>r.disposeData(m.dataId)),f}function lb(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Wh(r,a,o,"sum",n)}var X1e={kernelName:Qo,backendName:"webgpu",kernelFunc:lb};function K1e(e){let{inputs:t,backend:n,attrs:s}=e,{equation:r}=s,a=t,{allDims:o,summedDims:i,idDims:l}=C.decodeEinsumEquation(r,a.length);C.checkEinsumDimSizes(o.length,l,a);let{path:u,steps:c}=C.getEinsumComputePath(i,l),p=c.length,d=null,h=o.length,f=[];for(let m=0;m<p;++m){for(let g of c[m]){let{permutationIndices:y,expandDims:x}=C.getEinsumPermutation(h,l[g]),A;C.isIdentityPermutation(y)?A=a[g]:(A=ya({inputs:{x:a[g]},backend:n,attrs:{perm:y}}),f.push(A));let b=A.shape.slice();for(let w=0;w<x.length;++w)b.splice(x[w],0,1);v.arraysEqual(A.shape,b)||(A=Ue({inputs:{x:A},backend:n,attrs:{shape:b}}),f.push(A)),d===null?d=A:(d=aT({inputs:{a:A,b:d},backend:n}),f.push(d))}m<p-1&&(u[m]>=0&&(d=lb({inputs:{x:d},backend:n,attrs:{axis:u[m]-(o.length-h),keepDims:!1}}),f.push(d)),h--)}for(let m of f)m!==d&&n.disposeData(m.dataId);return d}var Z1e={kernelName:Vp,backendName:"webgpu",kernelFunc:K1e},Y1e=Dn({opType:Fe.ELU}),J1e={kernelName:Io,backendName:"webgpu",kernelFunc:Y1e},Q1e=os({opType:Ye.EQUAL,dtype:"bool",cpuKernelImpl:o2e}),ege={kernelName:pl,backendName:"webgpu",kernelFunc:Q1e},oT=Dn({opType:Fe.EXP,cpuKernelImpl:i2e,dtype:"float32"}),tge={kernelName:So,backendName:"webgpu",kernelFunc:oT};function gy(e){let{inputs:t,attrs:n,backend:s}=e,{dim:r}=n,{input:a}=t,o=a.shape.length,i=a.shape.slice(),l=r;return r<0&&(v.assert(-(o+1)<=r,()=>`Axis must be in the interval [${-(o+1)}, ${o}]`),l=o+r+1),i.splice(l,0,1),Ue({inputs:{x:a},backend:s,attrs:{shape:i}})}var nge={kernelName:hl,backendName:"webgpu",kernelFunc:gy},sge=Dn({opType:Fe.EXPM1,cpuKernelImpl:l2e}),rge={kernelName:fl,backendName:"webgpu",kernelFunc:sge},age=class{constructor(e){this.outputShape=[],this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="flipLeftRight"}getUserCode(){return`
       ${lt()}
         if (index < uniforms.size) {
           let coords = getCoordsFromIndex(index);
@@ -6333,7 +6333,7 @@ return a / b;`,Gie=`
           setOutputAtIndex(index, outputValue);
         }
       }
-    `}},oge={kernelName:gl,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,s=t,r=new age(n.shape);return s.runWebGPUProgram(r,[n],n.dtype)}},ige=Dn({opType:Fe.FLOOR,cpuKernelImpl:u2e}),lge={kernelName:To,backendName:"webgpu",kernelFunc:ige},uge=os({opType:Ye.INT_DIV,dtype:"int32"}),cge={kernelName:No,backendName:"webgpu",kernelFunc:uge},dge=class{constructor(e,t,n=!1){this.isFromPixels=!0,this.outputShape=[0],this.variableNames=[],this.workGroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[t,1,1]),this.importVideo=n,this.shaderKey=`fromPixels_${this.importVideo}`}getUserCode(){let e=this.importVideo?"textureLoad(src, vec2<i32>(coords.yx));":"textureLoad(src, vec2<i32>(coords.yx), 0)";return`
+    `}},oge={kernelName:ml,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{image:n}=e,s=t,r=new age(n.shape);return s.runWebGPUProgram(r,[n],n.dtype)}},ige=Dn({opType:Fe.FLOOR,cpuKernelImpl:u2e}),lge={kernelName:Co,backendName:"webgpu",kernelFunc:ige},uge=os({opType:Ye.INT_DIV,dtype:"int32"}),cge={kernelName:To,backendName:"webgpu",kernelFunc:uge},dge=class{constructor(e,t,n=!1){this.isFromPixels=!0,this.outputShape=[0],this.variableNames=[],this.workGroupSize=[256,1,1],this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[t,1,1]),this.importVideo=n,this.shaderKey=`fromPixels_${this.importVideo}`}getUserCode(){let e=this.importVideo?"textureLoad(src, vec2<i32>(coords.yx));":"textureLoad(src, vec2<i32>(coords.yx), 0)";return`
       @binding(1) @group(0) var src: ${this.importVideo?"texture_external":"texture_2d<f32>"};
       ${lt()}
         let flatIndex = index * uniforms.numChannels;
@@ -6345,7 +6345,7 @@ return a / b;`,Gie=`
           }
         }
       }
-  `}},pge={kernelName:bp,backendName:"webgpu",kernelFunc:hge},Ou,Jf=new Map;function hge(e){let{inputs:t,backend:n,attrs:s}=e,{pixels:r}=t,{numChannels:a}=s;if(r==null)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");let o=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,l=typeof HTMLCanvasElement!="undefined"&&r instanceof HTMLCanvasElement||typeof OffscreenCanvas!="undefined"&&r instanceof OffscreenCanvas,u=typeof ImageBitmap!="undefined"&&r instanceof ImageBitmap,[c,p]=o?[r.videoWidth,r.videoHeight]:[r.width,r.height],d=[p,c,a],h=Z().getBool("WEBGPU_IMPORT_EXTERNAL_TEXTURE")&&o,f=o||i;if(u||l||f){let x;if(h){let P=r;if(!Jf.has(P)||Jf.get(P).expired){let _={source:P};Jf.set(P,n.device.importExternalTexture(_))}x={width:c,height:p,format:null,usage:null,texture:Jf.get(P)}}else{f&&(Ou==null&&(Ou=document.createElement("canvas").getContext("2d")),Ou.canvas.width=c,Ou.canvas.height=p,Ou.drawImage(r,0,0,c,p),r=Ou.canvas);let P=GPUTextureUsage.COPY_DST|GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING,_="rgba8unorm",$=n.textureManager.acquireTexture(d[1],d[0],_,P);n.queue.copyExternalImageToTexture({source:r},{texture:$},[d[1],d[0]]),x={width:c,height:p,format:_,usage:P,texture:$}}let A=v.sizeFromShape(d),b=v.computeStrides(d),w=new dge(d,a,h),k=[{type:"uint32",data:[A]},{type:"uint32",data:[a]},{type:"uint32",data:[...b]}],S=n.makeTensorInfo([p,c],"int32"),E=n.tensorMap.get(S.dataId);E.resourceInfo=x;let R=n.runWebGPUProgram(w,[S],"int32",k);return n.disposeData(S.dataId),R}let m=r.data,g=m;if(a!=null&&a!==4){g=new Uint8Array(r.width*r.height*a);let x=m.length,A=0;for(let b=0;b<x;b++)b%4<a&&(g[A++]=m[b])}let y=n.makeTensorInfo(d,"int32",new Int32Array(g));return n.uploadToGPU(y.dataId),y}var fge=class{constructor(e,t,n,s,r){this.uniforms="varianceEpsilon : f32,",this.workGroupSize=[128,1,1],this.size=!0,this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,n),this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),s!=null&&(C.assertAndGetBroadcastShape(e,s),this.variableNames.push("offset")),r!=null&&(C.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale")),this.offsetShape=s,this.scaleShape=r,this.shaderKey="batchNorm"}getUserCode(){let e="0.0";this.offsetShape!=null&&(e="getOffsetByOutputIndex(index)");let t="1.0";return this.scaleShape!=null&&(t="getScaleByOutputIndex(index)"),`
+  `}},pge={kernelName:xp,backendName:"webgpu",kernelFunc:hge},Fu,Yf=new Map;function hge(e){let{inputs:t,backend:n,attrs:s}=e,{pixels:r}=t,{numChannels:a}=s;if(r==null)throw new Error("pixels passed to tf.browser.fromPixels() can not be null");let o=typeof HTMLVideoElement!="undefined"&&r instanceof HTMLVideoElement,i=typeof HTMLImageElement!="undefined"&&r instanceof HTMLImageElement,l=typeof HTMLCanvasElement!="undefined"&&r instanceof HTMLCanvasElement||typeof OffscreenCanvas!="undefined"&&r instanceof OffscreenCanvas,u=typeof ImageBitmap!="undefined"&&r instanceof ImageBitmap,[c,p]=o?[r.videoWidth,r.videoHeight]:[r.width,r.height],d=[p,c,a],h=X().getBool("WEBGPU_IMPORT_EXTERNAL_TEXTURE")&&o,f=o||i;if(u||l||f){let x;if(h){let P=r;if(!Yf.has(P)||Yf.get(P).expired){let _={source:P};Yf.set(P,n.device.importExternalTexture(_))}x={width:c,height:p,format:null,usage:null,texture:Yf.get(P)}}else{f&&(Fu==null&&(Fu=document.createElement("canvas").getContext("2d")),Fu.canvas.width=c,Fu.canvas.height=p,Fu.drawImage(r,0,0,c,p),r=Fu.canvas);let P=GPUTextureUsage.COPY_DST|GPUTextureUsage.RENDER_ATTACHMENT|GPUTextureUsage.TEXTURE_BINDING,_="rgba8unorm",$=n.textureManager.acquireTexture(d[1],d[0],_,P);n.queue.copyExternalImageToTexture({source:r},{texture:$},[d[1],d[0]]),x={width:c,height:p,format:_,usage:P,texture:$}}let A=v.sizeFromShape(d),b=v.computeStrides(d),w=new dge(d,a,h),k=[{type:"uint32",data:[A]},{type:"uint32",data:[a]},{type:"uint32",data:[...b]}],S=n.makeTensorInfo([p,c],"int32"),E=n.tensorMap.get(S.dataId);E.resourceInfo=x;let R=n.runWebGPUProgram(w,[S],"int32",k);return n.disposeData(S.dataId),R}let m=r.data,g=m;if(a!=null&&a!==4){g=new Uint8Array(r.width*r.height*a);let x=m.length,A=0;for(let b=0;b<x;b++)b%4<a&&(g[A++]=m[b])}let y=n.makeTensorInfo(d,"int32",new Int32Array(g));return n.uploadToGPU(y.dataId),y}var fge=class{constructor(e,t,n,s,r){this.uniforms="varianceEpsilon : f32,",this.workGroupSize=[128,1,1],this.size=!0,this.variableNames=["x","mean","variance"],C.assertAndGetBroadcastShape(e,t),C.assertAndGetBroadcastShape(e,n),this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),s!=null&&(C.assertAndGetBroadcastShape(e,s),this.variableNames.push("offset")),r!=null&&(C.assertAndGetBroadcastShape(e,r),this.variableNames.push("scale")),this.offsetShape=s,this.scaleShape=r,this.shaderKey="batchNorm"}getUserCode(){let e="0.0";this.offsetShape!=null&&(e="getOffsetByOutputIndex(index)");let t="1.0";return this.scaleShape!=null&&(t="getScaleByOutputIndex(index)"),`
       ${lt()}
         if (index < uniforms.size)
         {
@@ -6358,7 +6358,7 @@ return a / b;`,Gie=`
           setOutputAtIndex(index,dot(vec3<f32>(xValue, -meanValue, offsetValue), vec3<f32>(inv, inv, 1.0)));
         }
       }
-  `}},mge={kernelName:Eo,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s,scale:r,offset:a,mean:o,variance:i}=e,{varianceEpsilon:l}=t,u=n,c=[s,o,i],p=null;a!=null&&(p=a.shape,c.push(a));let d=null;r!=null&&(d=r.shape,c.push(r));let h=new fge(s.shape,o.shape,i.shape,p,d),f=[{type:"float32",data:[l]}];return u.runWebGPUProgram(h,c,s.dtype,f)}};function gge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=s,m=C.convertConv2DDataFormat(c),g=C.computeConv2DInfo(r.shape,a.shape,l,p,u,d,!1,m);return tT({x:r,filter:a,convInfo:g,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:f,activation:h})}var yge={kernelName:Qa,backendName:"webgpu",kernelFunc:gge};function Age(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dimRoundingMode:p,activation:d,leakyreluAlpha:h}=s,f=c;f==null&&(f=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(l,f),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${f}'`);let m=C.computeConv2DInfo(r.shape,a.shape,l,f,u,p,!0),g=[r,a],y=o!=null,x=i!=null;y&&g.push(o),x&&g.push(i);let A=[{type:"int32",data:[m.padInfo.top,m.padInfo.left]},{type:"int32",data:[m.inHeight,m.inWidth]}],b;return m.inHeight>4&&m.inWidth>4&&m.strideHeight===1&&m.strideWidth===1&&m.inChannels===m.outChannels&&m.dilationHeight===1&&m.dilationWidth===1&&m.inChannels%4===0?b=new sT(m,y,d,x):(b=new rT(m,y,d,x),A.push({type:"int32",data:[m.filterHeight]},{type:"int32",data:[m.filterWidth]},{type:"int32",data:[m.strideHeight,m.strideWidth]},{type:"int32",data:[m.dilationHeight,m.dilationWidth]})),d==="leakyrelu"&&(A.push({type:"float32",data:[h]}),b.uniforms+=" alpha : f32,"),n.runWebGPUProgram(b,g,"float32",A)}var xge={kernelName:eo,backendName:"webgpu",kernelFunc:Age},bge=class{constructor(e,t){this.variableNames=["A","indices"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`gathernd_${e}`,this.sliceDim=e,this.uniforms=`sliceDim : i32, strides : ${Tn(e)},`}getUserCode(){let e;return this.sliceDim>1?e="uniforms.strides[j]":e="uniforms.strides",`
+  `}},mge={kernelName:No,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s,scale:r,offset:a,mean:o,variance:i}=e,{varianceEpsilon:l}=t,u=n,c=[s,o,i],p=null;a!=null&&(p=a.shape,c.push(a));let d=null;r!=null&&(d=r.shape,c.push(r));let h=new fge(s.shape,o.shape,i.shape,p,d),f=[{type:"float32",data:[l]}];return u.runWebGPUProgram(h,c,s.dtype,f)}};function gge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dataFormat:c,dilations:p,dimRoundingMode:d,activation:h,leakyreluAlpha:f}=s,m=C.convertConv2DDataFormat(c),g=C.computeConv2DInfo(r.shape,a.shape,l,p,u,d,!1,m);return tT({x:r,filter:a,convInfo:g,backend:n,bias:o,preluActivationWeights:i,leakyreluAlpha:f,activation:h})}var yge={kernelName:Ja,backendName:"webgpu",kernelFunc:gge};function Age(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,filter:a,bias:o,preluActivationWeights:i}=t,{strides:l,pad:u,dilations:c,dimRoundingMode:p,activation:d,leakyreluAlpha:h}=s,f=c;f==null&&(f=[1,1]),v.assert(C.eitherStridesOrDilationsAreOne(l,f),()=>`Error in depthwiseConv2d: Either strides or dilations must be 1. Got strides ${l} and dilations '${f}'`);let m=C.computeConv2DInfo(r.shape,a.shape,l,f,u,p,!0),g=[r,a],y=o!=null,x=i!=null;y&&g.push(o),x&&g.push(i);let A=[{type:"int32",data:[m.padInfo.top,m.padInfo.left]},{type:"int32",data:[m.inHeight,m.inWidth]}],b;return m.inHeight>4&&m.inWidth>4&&m.strideHeight===1&&m.strideWidth===1&&m.inChannels===m.outChannels&&m.dilationHeight===1&&m.dilationWidth===1&&m.inChannels%4===0?b=new sT(m,y,d,x):(b=new rT(m,y,d,x),A.push({type:"int32",data:[m.filterHeight]},{type:"int32",data:[m.filterWidth]},{type:"int32",data:[m.strideHeight,m.strideWidth]},{type:"int32",data:[m.dilationHeight,m.dilationWidth]})),d==="leakyrelu"&&(A.push({type:"float32",data:[h]}),b.uniforms+=" alpha : f32,"),n.runWebGPUProgram(b,g,"float32",A)}var xge={kernelName:Qa,backendName:"webgpu",kernelFunc:Age},bge=class{constructor(e,t){this.variableNames=["A","indices"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey=`gathernd_${e}`,this.sliceDim=e,this.uniforms=`sliceDim : i32, strides : ${Tn(e)},`}getUserCode(){let e;return this.sliceDim>1?e="uniforms.strides[j]":e="uniforms.strides",`
         ${lt()}
         if (index < uniforms.size) {
           let coords = getCoordsFromIndex(index);
@@ -6372,7 +6372,7 @@ return a / b;`,Gie=`
           setOutputAtIndex(index, getA(flattenIndex, coords[1]));
         }
       }
-      `}};function vge(e){let{inputs:t,backend:n}=e,{params:s,indices:r}=t,a=r.shape,o=a[a.length-1],i=v.sizeFromShape(s.shape),[l,u,c,p]=C.prepareAndValidate(s,r),d=Ue({inputs:{x:r},backend:n,attrs:{shape:[u,o]}}),h=Ue({inputs:{x:s},backend:n,attrs:{shape:[v.sizeFromShape(s.shape)/c,c]}});if(n.shouldExecuteOnCPU([s,r])||s.dtype==="string"){let x=n.readSync(r.dataId),A=n.bufferSync(s),b=c2e(x,A,s.dtype,u,o,c,p,s.shape,i);return n.makeTensorInfo(l,s.dtype,b.values)}let f=new bge(o,[u,c]),m=[{type:"int32",data:[o]},{type:"int32",data:p}],g=n.runWebGPUProgram(f,[h,d],h.dtype,m),y=Ue({inputs:{x:g},backend:n,attrs:{shape:l}});return n.disposeData(d.dataId),n.disposeData(h.dataId),n.disposeData(g.dataId),y}var wge={kernelName:Al,backendName:"webgpu",kernelFunc:vge},kge=class{constructor(e,t){this.variableNames=["A","indices"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e.slice(),this.aShape=e,this.outputShape=t,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="gather"}getUserCode(){let e=Ige(this.aShape);return`
+      `}};function vge(e){let{inputs:t,backend:n}=e,{params:s,indices:r}=t,a=r.shape,o=a[a.length-1],i=v.sizeFromShape(s.shape),[l,u,c,p]=C.prepareAndValidate(s,r),d=Ue({inputs:{x:r},backend:n,attrs:{shape:[u,o]}}),h=Ue({inputs:{x:s},backend:n,attrs:{shape:[v.sizeFromShape(s.shape)/c,c]}});if(n.shouldExecuteOnCPU([s,r])||s.dtype==="string"){let x=n.readSync(r.dataId),A=n.bufferSync(s),b=c2e(x,A,s.dtype,u,o,c,p,s.shape,i);return n.makeTensorInfo(l,s.dtype,b.values)}let f=new bge(o,[u,c]),m=[{type:"int32",data:[o]},{type:"int32",data:p}],g=n.runWebGPUProgram(f,[h,d],h.dtype,m),y=Ue({inputs:{x:g},backend:n,attrs:{shape:l}});return n.disposeData(d.dataId),n.disposeData(h.dataId),n.disposeData(g.dataId),y}var wge={kernelName:yl,backendName:"webgpu",kernelFunc:vge},kge=class{constructor(e,t){this.variableNames=["A","indices"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e.slice(),this.aShape=e,this.outputShape=t,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="gather"}getUserCode(){let e=Ige(this.aShape);return`
       ${lt()}
         if (index < uniforms.size) {
           let resRC = getCoordsFromIndex(index);
@@ -6381,7 +6381,7 @@ return a / b;`,Gie=`
           setOutputAtIndex(index, inBounds * getA(${e}));
         }
       }
-    `}};function Ige(e){let t=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let s=0;s<e.length;s++)s===2?n.push("indexZ"):n.push(`${t[s]}`);return n.join()}function iT(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,indices:a}=t,{axis:o,batchDims:i}=s,l=v.parseAxisParam(o,r.shape)[0],u=C.segment_util.collectGatherOpShapeInfo(r,a,l,i),c=v.sizeFromShape(a.shape),p=[],d=Ue({inputs:{x:r},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=Ue({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});p.push(d),p.push(h);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([r,a])){let A=n.tensorMap.get(h.dataId).values,b=Le(h.shape,h.dtype,A),k=n.tensorMap.get(d.dataId).values,S=Le(d.shape,d.dtype,k),E=d2e(S,b,f);return p.forEach(R=>n.disposeData(R.dataId)),n.makeTensorInfo(u.outputShape,E.dtype,E.values)}let m=new kge(d.shape,f),g=n.runWebGPUProgram(m,[d,h],d.dtype);p.push(g);let y=Ue({inputs:{x:g},backend:n,attrs:{shape:u.outputShape}});return p.forEach(x=>n.disposeData(x.dataId)),y}var Sge={kernelName:yl,backendName:"webgpu",kernelFunc:iT},Cge=os({opType:Ye.GREATER,cpuKernelImpl:h2e,dtype:"bool"}),Tge={kernelName:xl,backendName:"webgpu",kernelFunc:Cge},Nge=os({opType:Ye.GREATER_EQUAL,dtype:"bool",cpuKernelImpl:p2e}),Ege={kernelName:Ro,backendName:"webgpu",kernelFunc:Nge};function Rge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s,o=[{type:"float32",data:[a]}],i=new Bh(r.shape,Fe.LEAKYRELU);return i.uniforms="alpha : f32,",n.runWebGPUProgram(i,[r],"float32",o)}var _ge={kernelName:Do,backendName:"webgpu",kernelFunc:Rge},Dge=os({opType:Ye.LESS,dtype:"bool",cpuKernelImpl:m2e}),$ge={kernelName:bl,backendName:"webgpu",kernelFunc:Dge},Pge=os({opType:Ye.LESS_EQUAL,dtype:"bool",cpuKernelImpl:f2e}),Fge={kernelName:vl,backendName:"webgpu",kernelFunc:Pge},Oge=Dn({opType:Fe.LOG,cpuKernelImpl:g2e}),Mge={kernelName:$o,backendName:"webgpu",kernelFunc:Oge},zge=os({opType:Ye.LOGICAL_AND,dtype:"bool"}),Lge={kernelName:wl,backendName:"webgpu",kernelFunc:zge},Bge=Dn({opType:Fe.LOGICAL_NOT}),Wge={kernelName:kl,backendName:"webgpu",kernelFunc:Bge};function lT(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reductionIndices:a,keepDims:o}=s;return Vh(r,a,o,"max",n)}var Vge={kernelName:Po,backendName:"webgpu",kernelFunc:lT},Uge=os({opType:Ye.MAX,cpuKernelImpl:A2e}),Gge={kernelName:Fo,backendName:"webgpu",kernelFunc:Uge};function Hge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1,c=C.computePool2DInfo(r.shape,a,o,u,i,l),p,d=[];if(c.filterHeight===1&&c.filterWidth===1){if(v.arraysEqual(c.inShape,c.outShape))return Fs({inputs:{x:r},backend:n});p=new JC(c),d.push({type:"int32",data:[c.strideHeight,c.strideWidth]})}else p=new YC(c,"max"),d.push({type:"int32",data:[c.strideHeight,c.strideWidth]},{type:"int32",data:[c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.dilationHeight,c.dilationWidth]},{type:"int32",data:[c.inHeight,c.inWidth]},{type:"int32",data:[c.effectiveFilterHeight,c.effectiveFilterWidth]});return n.runWebGPUProgram(p,[r],r.dtype,d)}var jge={kernelName:Oo,backendName:"webgpu",kernelFunc:Hge};function qge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{keepDims:a,axis:o}=s;return Vh(r,o,a,"mean",n)}var Xge={kernelName:Mo,backendName:"webgpu",kernelFunc:qge};function Kge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Vh(r,a,o,"min",n)}var Zge={kernelName:zo,backendName:"webgpu",kernelFunc:Kge},Yge=os({opType:Ye.MIN,cpuKernelImpl:x2e}),Jge={kernelName:Lo,backendName:"webgpu",kernelFunc:Yge},Qge=class{constructor(e,t,n){this.uniforms="",this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((s,r)=>s[0]+e[r]+s[1]),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.xShape=e,t.map((s,r)=>{this.uniforms+=` pad${r} : vec2<i32>,`}),this.offset=n==="reflect"?0:1,this.shaderKey=`mirrorPad_${n}`}getUserCode(){let e=this.xShape.length,t=this.xShape.map((l,u)=>`uniforms.pad${u}[0]`).join(","),n=this.xShape.map((l,u)=>`uniforms.pad${u}[0] + uniforms.xShape${e>1?`[${u}]`:""}`).join(","),s=e===1?"start":"start[i]",r=e===1?"end":"end[i]",a=e===1?"outC":"outC[i]",o=Tn(e),i=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
+    `}};function Ige(e){let t=["resRC.x","resRC.y","resRC.z","resRC.w"],n=[];for(let s=0;s<e.length;s++)s===2?n.push("indexZ"):n.push(`${t[s]}`);return n.join()}function iT(e){let{inputs:t,backend:n,attrs:s}=e,{x:r,indices:a}=t,{axis:o,batchDims:i}=s,l=v.parseAxisParam(o,r.shape)[0],u=C.segment_util.collectGatherOpShapeInfo(r,a,l,i),c=v.sizeFromShape(a.shape),p=[],d=Ue({inputs:{x:r},backend:n,attrs:{shape:[u.batchSize,u.outerSize,u.dimSize,u.sliceSize]}}),h=Ue({inputs:{x:a},backend:n,attrs:{shape:[u.batchSize,c/u.batchSize]}});p.push(d),p.push(h);let f=[u.batchSize,u.outerSize,c/u.batchSize,u.sliceSize];if(n.shouldExecuteOnCPU([r,a])){let A=n.tensorMap.get(h.dataId).values,b=Le(h.shape,h.dtype,A),k=n.tensorMap.get(d.dataId).values,S=Le(d.shape,d.dtype,k),E=d2e(S,b,f);return p.forEach(R=>n.disposeData(R.dataId)),n.makeTensorInfo(u.outputShape,E.dtype,E.values)}let m=new kge(d.shape,f),g=n.runWebGPUProgram(m,[d,h],d.dtype);p.push(g);let y=Ue({inputs:{x:g},backend:n,attrs:{shape:u.outputShape}});return p.forEach(x=>n.disposeData(x.dataId)),y}var Sge={kernelName:gl,backendName:"webgpu",kernelFunc:iT},Cge=os({opType:Ye.GREATER,cpuKernelImpl:h2e,dtype:"bool"}),Tge={kernelName:Al,backendName:"webgpu",kernelFunc:Cge},Nge=os({opType:Ye.GREATER_EQUAL,dtype:"bool",cpuKernelImpl:p2e}),Ege={kernelName:Eo,backendName:"webgpu",kernelFunc:Nge};function Rge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{alpha:a}=s,o=[{type:"float32",data:[a]}],i=new Lh(r.shape,Fe.LEAKYRELU);return i.uniforms="alpha : f32,",n.runWebGPUProgram(i,[r],"float32",o)}var _ge={kernelName:_o,backendName:"webgpu",kernelFunc:Rge},Dge=os({opType:Ye.LESS,dtype:"bool",cpuKernelImpl:m2e}),$ge={kernelName:xl,backendName:"webgpu",kernelFunc:Dge},Pge=os({opType:Ye.LESS_EQUAL,dtype:"bool",cpuKernelImpl:f2e}),Fge={kernelName:bl,backendName:"webgpu",kernelFunc:Pge},Oge=Dn({opType:Fe.LOG,cpuKernelImpl:g2e}),Mge={kernelName:Do,backendName:"webgpu",kernelFunc:Oge},zge=os({opType:Ye.LOGICAL_AND,dtype:"bool"}),Lge={kernelName:vl,backendName:"webgpu",kernelFunc:zge},Bge=Dn({opType:Fe.LOGICAL_NOT}),Wge={kernelName:wl,backendName:"webgpu",kernelFunc:Bge};function lT(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reductionIndices:a,keepDims:o}=s;return Wh(r,a,o,"max",n)}var Vge={kernelName:$o,backendName:"webgpu",kernelFunc:lT},Uge=os({opType:Ye.MAX,cpuKernelImpl:A2e}),Gge={kernelName:Po,backendName:"webgpu",kernelFunc:Uge};function Hge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{filterSize:a,strides:o,pad:i,dimRoundingMode:l}=s,u=1,c=C.computePool2DInfo(r.shape,a,o,u,i,l),p,d=[];if(c.filterHeight===1&&c.filterWidth===1){if(v.arraysEqual(c.inShape,c.outShape))return Fs({inputs:{x:r},backend:n});p=new JC(c),d.push({type:"int32",data:[c.strideHeight,c.strideWidth]})}else p=new YC(c,"max"),d.push({type:"int32",data:[c.strideHeight,c.strideWidth]},{type:"int32",data:[c.padInfo.top,c.padInfo.left]},{type:"int32",data:[c.dilationHeight,c.dilationWidth]},{type:"int32",data:[c.inHeight,c.inWidth]},{type:"int32",data:[c.effectiveFilterHeight,c.effectiveFilterWidth]});return n.runWebGPUProgram(p,[r],r.dtype,d)}var jge={kernelName:Fo,backendName:"webgpu",kernelFunc:Hge};function qge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{keepDims:a,axis:o}=s;return Wh(r,o,a,"mean",n)}var Xge={kernelName:Oo,backendName:"webgpu",kernelFunc:qge};function Kge(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Wh(r,a,o,"min",n)}var Zge={kernelName:Mo,backendName:"webgpu",kernelFunc:Kge},Yge=os({opType:Ye.MIN,cpuKernelImpl:x2e}),Jge={kernelName:zo,backendName:"webgpu",kernelFunc:Yge},Qge=class{constructor(e,t,n){this.uniforms="",this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((s,r)=>s[0]+e[r]+s[1]),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.xShape=e,t.map((s,r)=>{this.uniforms+=` pad${r} : vec2<i32>,`}),this.offset=n==="reflect"?0:1,this.shaderKey=`mirrorPad_${n}`}getUserCode(){let e=this.xShape.length,t=this.xShape.map((l,u)=>`uniforms.pad${u}[0]`).join(","),n=this.xShape.map((l,u)=>`uniforms.pad${u}[0] + uniforms.xShape${e>1?`[${u}]`:""}`).join(","),s=e===1?"start":"start[i]",r=e===1?"end":"end[i]",a=e===1?"outC":"outC[i]",o=Tn(e),i=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
       ${lt()}
         if (index < uniforms.size) {
           let start = ${o}(${t});
@@ -6398,7 +6398,7 @@ return a / b;`,Gie=`
           setOutputAtIndex(index, getX(${i}));
         }
       }
-    `}},e3e={kernelName:Bo,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{paddings:r,mode:a}=t,o=n,i=r.map(c=>({type:"int32",data:[c[0],c[1]]})),l=new Qge(s.shape,r,a);return o.runWebGPUProgram(l,[s],s.dtype,i)}};function t3e(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])){let a=n.tensorMap.get(s.dataId),[o,i]=v2e(a.values,s.shape,s.dtype);return n.makeTensorInfo(i,s.dtype,o)}let r=new Bh(s.shape,Fe.NEG);return n.runWebGPUProgram(r,[s],s.dtype)}var n3e={kernelName:Il,backendName:"webgpu",kernelFunc:t3e};function s3e(e){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l}=s,u=n.readSync(r.dataId),c=n.readSync(a.dataId),{selectedIndices:p}=dr.nonMaxSuppressionV3Impl(u,c,o,i,l);return n.makeTensorInfo([p.length],"int32",new Int32Array(p))}var r3e={kernelName:Cl,backendName:"webgpu",kernelFunc:s3e};function a3e(e){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=s,c=n.readSync(r.dataId),p=n.readSync(a.dataId),d=o,h=i,f=l,m=u,{selectedIndices:g,selectedScores:y}=dr.nonMaxSuppressionV5Impl(c,p,d,h,f,m);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var o3e={kernelName:Tl,backendName:"webgpu",kernelFunc:a3e};function Bm(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="complex64"){let r=Wh({inputs:{input:s},backend:n}),a=Bm({inputs:{x:r},backend:n}),o=E2({inputs:{input:s},backend:n}),i=Bm({inputs:{x:o},backend:n}),l=hd({inputs:{real:a,imag:i},backend:n});return n.disposeData(r.dataId),n.disposeData(a.dataId),n.disposeData(o.dataId),n.disposeData(i.dataId),l}else return ou({attrs:{shape:s.shape,dtype:s.dtype,value:s.dtype==="string"?"":0},backend:n})}var i3e={kernelName:Hl,backendName:"webgpu",kernelFunc:Bm};function uT(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(s.dtype==="complex64"){let r=Wh({inputs:{input:s},backend:n}),a=uT({inputs:{x:r},backend:n}),o=E2({inputs:{input:s},backend:n}),i=Bm({inputs:{x:o},backend:n}),l=hd({inputs:{real:a,imag:i},backend:n});return n.disposeData(r.dataId),n.disposeData(a.dataId),n.disposeData(o.dataId),n.disposeData(i.dataId),l}else return ou({attrs:{shape:s.shape,dtype:s.dtype,value:1},backend:n})}var l3e={kernelName:Nl,backendName:"webgpu",kernelFunc:uT};function u3e(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return yy({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let p=yy({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(p),p}),u=eT({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeData(c.dataId)),u}var c3e={kernelName:Rl,backendName:"webgpu",kernelFunc:u3e},d3e=class{constructor(e,t){this.variableNames=["x"],this.uniforms="constantValue : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((n,s)=>n[0]+e[s]+n[1]),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),t.map((n,s)=>{this.uniforms+=` pad${s} : vec2<i32>,`}),this.xShape=e,this.shaderKey="pad"}getUserCode(){let e=this.xShape.length,t=Tn(e),n=this.xShape.map((c,p)=>`uniforms.pad${p}[0]`).join(","),s=this.xShape.map((c,p)=>`uniforms.pad${p}[0] + uniforms.xShape${e>1?`[${p}]`:""}`).join(","),r=e>1?`${t}(${n})`:`${n}`,a=e>1?`${t}(${s})`:`${s}`,o=e>1?"any(outC < start)":"outC < start",i=e>1?"any(outC >= end)":"outC >= end",l=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
+    `}},e3e={kernelName:Lo,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{x:s}=e,{paddings:r,mode:a}=t,o=n,i=r.map(c=>({type:"int32",data:[c[0],c[1]]})),l=new Qge(s.shape,r,a);return o.runWebGPUProgram(l,[s],s.dtype,i)}};function t3e(e){let{inputs:t,backend:n}=e,{x:s}=t;if(n.shouldExecuteOnCPU([s])){let a=n.tensorMap.get(s.dataId),[o,i]=v2e(a.values,s.shape,s.dtype);return n.makeTensorInfo(i,s.dtype,o)}let r=new Lh(s.shape,Fe.NEG);return n.runWebGPUProgram(r,[s],s.dtype)}var n3e={kernelName:kl,backendName:"webgpu",kernelFunc:t3e};function s3e(e){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l}=s,u=n.readSync(r.dataId),c=n.readSync(a.dataId),{selectedIndices:p}=dr.nonMaxSuppressionV3Impl(u,c,o,i,l);return n.makeTensorInfo([p.length],"int32",new Int32Array(p))}var r3e={kernelName:Sl,backendName:"webgpu",kernelFunc:s3e};function a3e(e){console.warn("tf.nonMaxSuppression() in webgpu locks the UI thread. Call tf.nonMaxSuppressionAsync() instead");let{inputs:t,backend:n,attrs:s}=e,{boxes:r,scores:a}=t,{maxOutputSize:o,iouThreshold:i,scoreThreshold:l,softNmsSigma:u}=s,c=n.readSync(r.dataId),p=n.readSync(a.dataId),d=o,h=i,f=l,m=u,{selectedIndices:g,selectedScores:y}=dr.nonMaxSuppressionV5Impl(c,p,d,h,f,m);return[n.makeTensorInfo([g.length],"int32",new Int32Array(g)),n.makeTensorInfo([y.length],"float32",new Float32Array(y))]}var o3e={kernelName:Cl,backendName:"webgpu",kernelFunc:a3e};function Lm(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="complex64"){let r=Bh({inputs:{input:s},backend:n}),a=Lm({inputs:{x:r},backend:n}),o=N2({inputs:{input:s},backend:n}),i=Lm({inputs:{x:o},backend:n}),l=pd({inputs:{real:a,imag:i},backend:n});return n.disposeData(r.dataId),n.disposeData(a.dataId),n.disposeData(o.dataId),n.disposeData(i.dataId),l}else return au({attrs:{shape:s.shape,dtype:s.dtype,value:s.dtype==="string"?"":0},backend:n})}var i3e={kernelName:Gl,backendName:"webgpu",kernelFunc:Lm};function uT(e){let{inputs:t,backend:n}=e,{x:s}=t;if(s.dtype==="string")throw new Error("onesLike is not supported under string dtype");if(s.dtype==="complex64"){let r=Bh({inputs:{input:s},backend:n}),a=uT({inputs:{x:r},backend:n}),o=N2({inputs:{input:s},backend:n}),i=Lm({inputs:{x:o},backend:n}),l=pd({inputs:{real:a,imag:i},backend:n});return n.disposeData(r.dataId),n.disposeData(a.dataId),n.disposeData(o.dataId),n.disposeData(i.dataId),l}else return au({attrs:{shape:s.shape,dtype:s.dtype,value:1},backend:n})}var l3e={kernelName:Tl,backendName:"webgpu",kernelFunc:uT};function u3e(e){let{inputs:t,backend:n,attrs:s}=e,{axis:r}=s;if(t.length===1)return gy({inputs:{input:t[0]},backend:n,attrs:{dim:r}});let a=t[0].shape,o=t[0].dtype;t.forEach(c=>{v.assertShapesMatch(a,c.shape,"All tensors passed to stack must have matching shapes"),v.assert(o===c.dtype,()=>"All tensors passed to stack must have matching dtypes")});let i=[],l=t.map(c=>{let p=gy({inputs:{input:c},backend:n,attrs:{dim:r}});return i.push(p),p}),u=eT({inputs:l,backend:n,attrs:{axis:r}});return i.forEach(c=>n.disposeData(c.dataId)),u}var c3e={kernelName:El,backendName:"webgpu",kernelFunc:u3e},d3e=class{constructor(e,t){this.variableNames=["x"],this.uniforms="constantValue : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t.map((n,s)=>n[0]+e[s]+n[1]),this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),t.map((n,s)=>{this.uniforms+=` pad${s} : vec2<i32>,`}),this.xShape=e,this.shaderKey="pad"}getUserCode(){let e=this.xShape.length,t=Tn(e),n=this.xShape.map((c,p)=>`uniforms.pad${p}[0]`).join(","),s=this.xShape.map((c,p)=>`uniforms.pad${p}[0] + uniforms.xShape${e>1?`[${p}]`:""}`).join(","),r=e>1?`${t}(${n})`:`${n}`,a=e>1?`${t}(${s})`:`${s}`,o=e>1?"any(outC < start)":"outC < start",i=e>1?"any(outC >= end)":"outC >= end",l=e>1?["coords[0]","coords[1]","coords[2]","coords[3]"].slice(0,e):"coords";return`
       ${lt()}
         if (index < uniforms.size) {
           let start = ${r};
@@ -6413,7 +6413,7 @@ return a / b;`,Gie=`
           }
         }
       }
-    `}},cT=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{paddings:a,constantValue:o}=s;if(a.every(u=>v.arraysEqual(u,[0,0])))return Fs({inputs:{x:r},backend:n});if(v.sizeFromShape(r.shape)===0){let u=a.map((c,p)=>c[0]+r.shape[p]+c[1]);return ou({backend:n,attrs:{shape:u,value:o,dtype:r.dtype}})}let i=[{type:"float32",data:[o]}];a.map(u=>i.push({type:"int32",data:[u[0],u[1]]}));let l=new d3e(r.shape,a);return n.runWebGPUProgram(l,[r],r.dtype,i)},p3e={kernelName:Vo,backendName:"webgpu",kernelFunc:cT},h3e=os({opType:Ye.POW}),f3e={kernelName:Uo,backendName:"webgpu",kernelFunc:h3e};function m3e(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t,a=new fy(Ye.PRELU,s.shape,r.shape);return n.runWebGPUProgram(a,[s,r],"float32")}var g3e={kernelName:Go,backendName:"webgpu",kernelFunc:m3e};function y3e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Vh(r,a,o,"prod",n)}var A3e={kernelName:Ho,backendName:"webgpu",kernelFunc:y3e},x3e=e=>{let{backend:t,attrs:n}=e,{start:s,stop:r,step:a,dtype:o}=n,i=I2e(s,r,a,o);return t.makeTensorInfo([i.length],o,i)},b3e={kernelName:_c,backendName:"webgpu",kernelFunc:x3e},dT=os({opType:Ye.DIV}),v3e={kernelName:Io,backendName:"webgpu",kernelFunc:dT},w3e=Dn({opType:Fe.RELU}),k3e={kernelName:jo,backendName:"webgpu",kernelFunc:w3e},I3e=Dn({opType:Fe.RELU6}),S3e={kernelName:Ko,backendName:"webgpu",kernelFunc:I3e},C3e=class{constructor(e,t,n){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2<f32>, halfPixelCenters : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,n,e[3]],this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="resizeBilinear"}getUserCode(){return`
+    `}},cT=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{paddings:a,constantValue:o}=s;if(a.every(u=>v.arraysEqual(u,[0,0])))return Fs({inputs:{x:r},backend:n});if(v.sizeFromShape(r.shape)===0){let u=a.map((c,p)=>c[0]+r.shape[p]+c[1]);return au({backend:n,attrs:{shape:u,value:o,dtype:r.dtype}})}let i=[{type:"float32",data:[o]}];a.map(u=>i.push({type:"int32",data:[u[0],u[1]]}));let l=new d3e(r.shape,a);return n.runWebGPUProgram(l,[r],r.dtype,i)},p3e={kernelName:Wo,backendName:"webgpu",kernelFunc:cT},h3e=os({opType:Ye.POW}),f3e={kernelName:Vo,backendName:"webgpu",kernelFunc:h3e};function m3e(e){let{inputs:t,backend:n}=e,{x:s,alpha:r}=t,a=new hy(Ye.PRELU,s.shape,r.shape);return n.runWebGPUProgram(a,[s,r],"float32")}var g3e={kernelName:Uo,backendName:"webgpu",kernelFunc:m3e};function y3e(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{axis:a,keepDims:o}=s;return Wh(r,a,o,"prod",n)}var A3e={kernelName:Go,backendName:"webgpu",kernelFunc:y3e},x3e=e=>{let{backend:t,attrs:n}=e,{start:s,stop:r,step:a,dtype:o}=n,i=I2e(s,r,a,o);return t.makeTensorInfo([i.length],o,i)},b3e={kernelName:Rc,backendName:"webgpu",kernelFunc:x3e},dT=os({opType:Ye.DIV}),v3e={kernelName:ko,backendName:"webgpu",kernelFunc:dT},w3e=Dn({opType:Fe.RELU}),k3e={kernelName:Ho,backendName:"webgpu",kernelFunc:w3e},I3e=Dn({opType:Fe.RELU6}),S3e={kernelName:Xo,backendName:"webgpu",kernelFunc:I3e},C3e=class{constructor(e,t,n){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2<f32>, halfPixelCenters : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,n,e[3]],this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="resizeBilinear"}getUserCode(){return`
       ${lt()}
         if (index < uniforms.size) {
         let coords = getCoordsFromIndex(index);
@@ -6456,7 +6456,7 @@ return a / b;`,Gie=`
           setOutputAtIndex(index, newValue);
         }
       }
-    `}};function T3e(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,size:o,halfPixelCenters:i}=s,[l,u]=o,c=a&&l>1?1:0,p=a&&u>1?1:0,h=[{type:"float32",data:[c,p]},{type:"float32",data:[i?.5:0]}],f=new C3e(r.shape,l,u);return n.runWebGPUProgram(f,[r],"float32",h)}var N3e={kernelName:Xo,backendName:"webgpu",kernelFunc:T3e},E3e=class{constructor(e,t,n,s){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2<f32>, roundBase : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,n,e[3]],this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.halfPixelCenters=s,this.shaderKey=`resizeNearest_${s}`}getUserCode(){let e;return this.halfPixelCenters?e="max((vec2<f32>(rc) + vec2<f32>(0.5)) * effectiveInputOverOutputRatioRC, vec2<f32>(0.0))":e="vec2<f32>(rc) * effectiveInputOverOutputRatioRC",`
+    `}};function T3e(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,size:o,halfPixelCenters:i}=s,[l,u]=o,c=a&&l>1?1:0,p=a&&u>1?1:0,h=[{type:"float32",data:[c,p]},{type:"float32",data:[i?.5:0]}],f=new C3e(r.shape,l,u);return n.runWebGPUProgram(f,[r],"float32",h)}var N3e={kernelName:qo,backendName:"webgpu",kernelFunc:T3e},E3e=class{constructor(e,t,n,s){this.variableNames=["x"],this.uniforms="adjustHeightWidth : vec2<f32>, roundBase : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=[e[0],t,n,e[3]],this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.halfPixelCenters=s,this.shaderKey=`resizeNearest_${s}`}getUserCode(){let e;return this.halfPixelCenters?e="max((vec2<f32>(rc) + vec2<f32>(0.5)) * effectiveInputOverOutputRatioRC, vec2<f32>(0.0))":e="vec2<f32>(rc) * effectiveInputOverOutputRatioRC",`
       ${lt()}
         if (index < uniforms.size) {
           let coords = getCoordsFromIndex(index);
@@ -6487,7 +6487,7 @@ return a / b;`,Gie=`
           setOutputAtIndex(index, newValue);
         }
       }
-    `}};function R3e(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=a&&l>1?1:0,p=a&&u>1?1:0,h=[{type:"float32",data:[c,p]},{type:"float32",data:[a?.5:0]}],f=new E3e(r.shape,l,u,o);return n.runWebGPUProgram(f,[r],r.dtype,h)}var _3e={kernelName:qo,backendName:"webgpu",kernelFunc:R3e},D3e=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.uniforms=`centerX : f32, centerY : f32, sinRadians : f32,
+    `}};function R3e(e){let{inputs:t,backend:n,attrs:s}=e,{images:r}=t,{alignCorners:a,halfPixelCenters:o,size:i}=s,[l,u]=i,c=a&&l>1?1:0,p=a&&u>1?1:0,h=[{type:"float32",data:[c,p]},{type:"float32",data:[a?.5:0]}],f=new E3e(r.shape,l,u,o);return n.runWebGPUProgram(f,[r],r.dtype,h)}var _3e={kernelName:jo,backendName:"webgpu",kernelFunc:R3e},D3e=class{constructor(e,t){this.outputShape=[],this.variableNames=["x"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.uniforms=`centerX : f32, centerY : f32, sinRadians : f32,
           cosRadians : f32,`,this.shaderKey="rotate",this.outputShape=e,typeof t=="number"?(this.uniforms+=" fillValue : f32,",this.fillSnippet="var outputValue = uniforms.fillValue;",this.shaderKey+="_float"):(this.uniforms+=" fillValue : vec3<f32>,",this.fillSnippet="var outputValue = uniforms.fillValue[coords[3]];",this.shaderKey+="_vec3")}getUserCode(){return`
         ${lt()}
 
@@ -6509,7 +6509,7 @@ return a / b;`,Gie=`
             setOutputAtIndex(index, outputValue);
           }
         }
-      `}},$3e={kernelName:jl,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,{radians:r,fillValue:a,center:o}=t,i=n,l=new D3e(s.shape,a),[u,c]=C.getImageCenter(o,s.shape[1],s.shape[2]),p=[{type:"float32",data:[u]},{type:"float32",data:[c]},{type:"float32",data:[Math.sin(r)]},{type:"float32",data:[Math.cos(r)]}];return typeof a=="number"?p.push({type:"float32",data:[Number.parseFloat(a.toFixed(2))]}):p.push({type:"float32",data:a}),i.runWebGPUProgram(l,[s],s.dtype,p)}},P3e=Dn({opType:Fe.RSQRT,cpuKernelImpl:S2e}),F3e={kernelName:Zo,backendName:"webgpu",kernelFunc:P3e},lm=class{constructor(e,t,n,s,r,a,o,i=!0){this.variableNames=["updates","indices"],this.workGroupSize=[64,1,1],this.atomic=!0,this.outputShape=a,this.type=o,this.sumDupeIndices=i,this.dispatchLayout=at(e),this.dispatch=We(this.dispatchLayout,e,this.workGroupSize),this.sliceDimGreaterThanOne=t>1,this.shaderKey=`scatter_${n}_${s}_${this.sliceDimGreaterThanOne}_${o}_${i}`;let l=Tn(r.length);this.uniforms=`sliceDim : i32, strides: ${l}, size: i32,`,this.updatesRank=s,this.indicesRank=n}getUserCode(){let e="";this.indicesRank===1?e="coords[0]":this.indicesRank===2&&(e="coords[0], j");let t=`getIndices(${e})`,n=this.sliceDimGreaterThanOne?"uniforms.strides[j]":"uniforms.strides",s="",r="";this.dispatchLayout.x.length===1?(s="flattenedIndex",r=`
+      `}},$3e={kernelName:Hl,backendName:"webgpu",kernelFunc:({inputs:e,attrs:t,backend:n})=>{let{image:s}=e,{radians:r,fillValue:a,center:o}=t,i=n,l=new D3e(s.shape,a),[u,c]=C.getImageCenter(o,s.shape[1],s.shape[2]),p=[{type:"float32",data:[u]},{type:"float32",data:[c]},{type:"float32",data:[Math.sin(r)]},{type:"float32",data:[Math.cos(r)]}];return typeof a=="number"?p.push({type:"float32",data:[Number.parseFloat(a.toFixed(2))]}):p.push({type:"float32",data:a}),i.runWebGPUProgram(l,[s],s.dtype,p)}},P3e=Dn({opType:Fe.RSQRT,cpuKernelImpl:S2e}),F3e={kernelName:Ko,backendName:"webgpu",kernelFunc:P3e},im=class{constructor(e,t,n,s,r,a,o,i=!0){this.variableNames=["updates","indices"],this.workGroupSize=[64,1,1],this.atomic=!0,this.outputShape=a,this.type=o,this.sumDupeIndices=i,this.dispatchLayout=at(e),this.dispatch=We(this.dispatchLayout,e,this.workGroupSize),this.sliceDimGreaterThanOne=t>1,this.shaderKey=`scatter_${n}_${s}_${this.sliceDimGreaterThanOne}_${o}_${i}`;let l=Tn(r.length);this.uniforms=`sliceDim : i32, strides: ${l}, size: i32,`,this.updatesRank=s,this.indicesRank=n}getUserCode(){let e="";this.indicesRank===1?e="coords[0]":this.indicesRank===2&&(e="coords[0], j");let t=`getIndices(${e})`,n=this.sliceDimGreaterThanOne?"uniforms.strides[j]":"uniforms.strides",s="",r="";this.dispatchLayout.x.length===1?(s="flattenedIndex",r=`
       fn getUpdatesCoordsFromFlatIndex(index : i32) -> i32 {
         return index;
       }
@@ -6552,12 +6552,12 @@ return a / b;`,Gie=`
             flattenedIndex = flattenedIndex + indexInside * ${n};
           }
           let updateValue =
-              ${Ap(this.type,!1)}(${o});
+              ${yp(this.type,!1)}(${o});
           let flatIndex = getOutputIndexFromCoords(${s});
 
           ${i("&result[flatIndex]","updateValue")};
         }
-      }`}};function O3e(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r,updates:a}=t,{shape:o}=s,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:p}=C.calculateShapes(a,r,o),d=[p/u,u];if(p===0)return n.makeTensorInfo(o,r.dtype);let h=Ue({inputs:{x:r},backend:n,attrs:{shape:[l,i]}}),f=Ue({inputs:{x:a},backend:n,attrs:{shape:[l,u]}}),m=f.dtype,g=ou({backend:n,attrs:{shape:d,value:0,dtype:m}}),y=v.sizeFromShape(f.shape),x=[{type:"int32",data:[i]},{type:"int32",data:c},{type:"int32",data:[y]}],A=new lm(f.shape,i,h.shape.length,f.shape.length,c,d,m),b=n.runWebGPUProgram(A,[f,h],m,x,g),w=Ue({inputs:{x:b},backend:n,attrs:{shape:o}});return n.disposeData(h.dataId),n.disposeData(f.dataId),n.disposeData(b.dataId),w}var M3e={kernelName:Pl,backendName:"webgpu",kernelFunc:O3e},z3e=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.cRank=e,this.rank=n,this.shaderKey="select"}getUserCode(){let e,t;if(this.rank>4)throw Error(`Where for rank ${this.rank} is not yet supported`);if(this.rank===1)t="resRC",e="resRC";else{let s=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[],a=[];for(let o=0;o<this.outputShape.length;o++)a.push(`${s[o]}`),o<this.cRank&&r.push(`${s[o]}`);e=r.join(),t=a.join()}return`
+      }`}};function O3e(e){let{inputs:t,backend:n,attrs:s}=e,{indices:r,updates:a}=t,{shape:o}=s,{sliceRank:i,numUpdates:l,sliceSize:u,strides:c,outputSize:p}=C.calculateShapes(a,r,o),d=[p/u,u];if(p===0)return n.makeTensorInfo(o,r.dtype);let h=Ue({inputs:{x:r},backend:n,attrs:{shape:[l,i]}}),f=Ue({inputs:{x:a},backend:n,attrs:{shape:[l,u]}}),m=f.dtype,g=au({backend:n,attrs:{shape:d,value:0,dtype:m}}),y=v.sizeFromShape(f.shape),x=[{type:"int32",data:[i]},{type:"int32",data:c},{type:"int32",data:[y]}],A=new im(f.shape,i,h.shape.length,f.shape.length,c,d,m),b=n.runWebGPUProgram(A,[f,h],m,x,g),w=Ue({inputs:{x:b},backend:n,attrs:{shape:o}});return n.disposeData(h.dataId),n.disposeData(f.dataId),n.disposeData(b.dataId),w}var M3e={kernelName:$l,backendName:"webgpu",kernelFunc:O3e},z3e=class{constructor(e,t,n){this.variableNames=["c","a","b"],this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=t,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.cRank=e,this.rank=n,this.shaderKey="select"}getUserCode(){let e,t;if(this.rank>4)throw Error(`Where for rank ${this.rank} is not yet supported`);if(this.rank===1)t="resRC",e="resRC";else{let s=["resRC.x","resRC.y","resRC.z","resRC.w"],r=[],a=[];for(let o=0;o<this.outputShape.length;o++)a.push(`${s[o]}`),o<this.cRank&&r.push(`${s[o]}`);e=r.join(),t=a.join()}return`
       ${lt()}
         if (index < uniforms.size) {
           let resRC = getCoordsFromIndex(index);
@@ -6569,21 +6569,21 @@ return a / b;`,Gie=`
           }
         }
       }
-    `}};function L3e(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t,o=new z3e(s.shape.length,r.shape,r.shape.length);return n.runWebGPUProgram(o,[s,r,a],On(r.dtype,a.dtype))}var B3e={kernelName:Fl,backendName:"webgpu",kernelFunc:L3e},W3e=Dn({opType:Fe.SIGMOID}),V3e={kernelName:Jo,backendName:"webgpu",kernelFunc:W3e},U3e=Dn({opType:Fe.SIN}),G3e={kernelName:Yo,backendName:"webgpu",kernelFunc:U3e},H3e=Dn({opType:Fe.SINH}),j3e={kernelName:Ml,backendName:"webgpu",kernelFunc:H3e},pT=os({opType:Ye.SUB,cpuKernelImpl:_2e,supportsComplex:!0}),q3e={kernelName:si,backendName:"webgpu",kernelFunc:pT};function X3e(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{dim:a}=s,o=v.parseAxisParam([a],r.shape),i=lT({inputs:{x:r},backend:n,attrs:{reductionIndices:o,keepDims:!1}}),l=C.expandShapeToKeepDim(i.shape,o),u=Ue({inputs:{x:i},backend:n,attrs:{shape:l}}),c=pT({inputs:{a:r,b:u},backend:n}),p=oT({inputs:{x:c},backend:n}),d=lb({inputs:{x:p},backend:n,attrs:{axis:o,keepDims:!1}}),h=Ue({inputs:{x:d},backend:n,attrs:{shape:l}}),f=dT({inputs:{a:p,b:h},backend:n});return n.disposeData(i.dataId),n.disposeData(u.dataId),n.disposeData(c.dataId),n.disposeData(p.dataId),n.disposeData(d.dataId),n.disposeData(h.dataId),f}var K3e={kernelName:ti,backendName:"webgpu",kernelFunc:X3e},Z3e=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,paddings:o}=s;v.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGPU backend not implemented yet");let i=a.reduce((y,x)=>y*x),l=[[0,0]];l.push(...o);for(let y=1+a.length;y<r.shape.length;++y)l.push([0,0]);let u=[],c=cT({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),p=C.getReshaped(c.shape,a,i,!1),d=C.getPermuted(p.length,a.length,!1),h=C.getReshapedPermuted(c.shape,a,i,!1),f=Ue({inputs:{x:c},backend:n,attrs:{shape:p}}),m=Aa({inputs:{x:f},backend:n,attrs:{perm:d}}),g=Ue({inputs:{x:m},backend:n,attrs:{shape:h}});return u.push(c),u.push(f),u.push(m),u.forEach(y=>n.disposeData(y.dataId)),g},Y3e={kernelName:zl,backendName:"webgpu",kernelFunc:Z3e},J3e=class{constructor(e,t){this.variableNames=["A"],this.workGroupSize=[64,1,1],this.size=!0;let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.rank=this.outputShape.length,this.shaderKey="tile"}getUserCode(){let e=Q3e(this.rank,"uniforms.");return`
+    `}};function L3e(e){let{inputs:t,backend:n}=e,{condition:s,t:r,e:a}=t,o=new z3e(s.shape.length,r.shape,r.shape.length);return n.runWebGPUProgram(o,[s,r,a],On(r.dtype,a.dtype))}var B3e={kernelName:Pl,backendName:"webgpu",kernelFunc:L3e},W3e=Dn({opType:Fe.SIGMOID}),V3e={kernelName:Yo,backendName:"webgpu",kernelFunc:W3e},U3e=Dn({opType:Fe.SIN}),G3e={kernelName:Zo,backendName:"webgpu",kernelFunc:U3e},H3e=Dn({opType:Fe.SINH}),j3e={kernelName:Ol,backendName:"webgpu",kernelFunc:H3e},pT=os({opType:Ye.SUB,cpuKernelImpl:_2e,supportsComplex:!0}),q3e={kernelName:ni,backendName:"webgpu",kernelFunc:pT};function X3e(e){let{inputs:t,backend:n,attrs:s}=e,{logits:r}=t,{dim:a}=s,o=v.parseAxisParam([a],r.shape),i=lT({inputs:{x:r},backend:n,attrs:{reductionIndices:o,keepDims:!1}}),l=C.expandShapeToKeepDim(i.shape,o),u=Ue({inputs:{x:i},backend:n,attrs:{shape:l}}),c=pT({inputs:{a:r,b:u},backend:n}),p=oT({inputs:{x:c},backend:n}),d=lb({inputs:{x:p},backend:n,attrs:{axis:o,keepDims:!1}}),h=Ue({inputs:{x:d},backend:n,attrs:{shape:l}}),f=dT({inputs:{a:p,b:h},backend:n});return n.disposeData(i.dataId),n.disposeData(u.dataId),n.disposeData(c.dataId),n.disposeData(p.dataId),n.disposeData(d.dataId),n.disposeData(h.dataId),f}var K3e={kernelName:ei,backendName:"webgpu",kernelFunc:X3e},Z3e=e=>{let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{blockShape:a,paddings:o}=s;v.assert(r.shape.length<=4,()=>"spaceToBatchND for rank > 4 with a WebGPU backend not implemented yet");let i=a.reduce((y,x)=>y*x),l=[[0,0]];l.push(...o);for(let y=1+a.length;y<r.shape.length;++y)l.push([0,0]);let u=[],c=cT({inputs:{x:r},backend:n,attrs:{paddings:l,constantValue:0}}),p=C.getReshaped(c.shape,a,i,!1),d=C.getPermuted(p.length,a.length,!1),h=C.getReshapedPermuted(c.shape,a,i,!1),f=Ue({inputs:{x:c},backend:n,attrs:{shape:p}}),m=ya({inputs:{x:f},backend:n,attrs:{perm:d}}),g=Ue({inputs:{x:m},backend:n,attrs:{shape:h}});return u.push(c),u.push(f),u.push(m),u.forEach(y=>n.disposeData(y.dataId)),g},Y3e={kernelName:Ml,backendName:"webgpu",kernelFunc:Z3e},J3e=class{constructor(e,t){this.variableNames=["A"],this.workGroupSize=[64,1,1],this.size=!0;let n=new Array(e.length);for(let s=0;s<n.length;s++)n[s]=e[s]*t[s];this.outputShape=n,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.rank=this.outputShape.length,this.shaderKey="tile"}getUserCode(){let e=Q3e(this.rank,"uniforms.");return`
       ${lt()}
         if (index < uniforms.size) {
           let resRC = getCoordsFromIndex(index);
           setOutputAtIndex(index, getA(${e}));
         }
       }
-    `}};function Q3e(e,t=""){if(e>=5)throw Error(`Tile for rank ${e} is not yet supported`);if(e===1)return`(resRC % ${t}aShape)`;let n=["resRC.x","resRC.y","resRC.z","resRC.w"],s=[];for(let r=0;r<e;r++)s.push(`(${n[r]} % ${t}aShape[${r}])`);return s.join()}function hT(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reps:a}=s;if(n.shouldExecuteOnCPU([r])||r.dtype==="string"||r.shape.length>=5){let l=n.readSync(r.dataId),u=r.dtype==="string"?l.map(d=>v.decodeString(d)):l,c=Le(r.shape,r.dtype,u),p=D2e(c,a);return n.makeTensorInfo(p.shape,p.dtype,p.values)}let o=new J3e(r.shape,a);return n.runWebGPUProgram(o,[r],r.dtype)}var eye={kernelName:va,backendName:"webgpu",kernelFunc:hT};function tye(e){let{inputs:t,backend:n,attrs:s}=e,{sparseIndices:r,sparseValues:a,defaultValue:o}=t,{outputShape:i}=s,{sliceRank:l,numUpdates:u,sliceSize:c,strides:p,outputSize:d}=C.calculateShapes(a,r,i),h=!1;if(a.dtype==="string"){let E=n.bufferSync(r),R=n.bufferSync(a),P=v.decodeString(n.readSync(o.dataId)[0]),_=C2e(E,R,i,d,c,u,l,p,P,h);return n.makeTensorInfo(i,_.dtype,_.values)}let f=[d/c,c],m=Ue({inputs:{x:r},backend:n,attrs:{shape:[u,l]}}),g=a.shape.length?Ue({inputs:{x:a},backend:n,attrs:{shape:[u,c]}}):Fs({inputs:{x:a},backend:n}),y=g.dtype,x=n.makeTensorInfo([],y,v.makeZerosTypedArray(1,y)),A=Ue({inputs:{x:o},backend:n,attrs:{shape:Array(f.length).fill(1)}}),b=hT({inputs:{x:A},backend:n,attrs:{reps:f}}),w=v.sizeFromShape([u,c]),k=[{type:"int32",data:[l]},{type:"int32",data:p},{type:"int32",data:[w]}];switch(u){case 0:break;case 1:{let E=new lm([u,c],l,m.shape.length,g.shape.length,p,f,y,h);n.runWebGPUProgram(E,[g,m],y,k,b)}break;default:{let E=new lm([u,c],l,m.shape.length,x.shape.length,p,f,y,h);n.runWebGPUProgram(E,[x,m],y,k,b)}{let E=new lm([u,c],l,m.shape.length,g.shape.length,p,f,y);n.runWebGPUProgram(E,[g,m],y,k,b)}}let S=Ue({inputs:{x:b},backend:n,attrs:{shape:i}});return n.disposeData(m.dataId),n.disposeData(g.dataId),n.disposeData(A.dataId),n.disposeData(x.dataId),n.disposeData(b.dataId),S}var nye={kernelName:Yp,backendName:"webgpu",kernelFunc:tye};function sye(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=s,i=v.parseAxisParam(o,r.shape)[0],l=C.prepareSplitSize(r,a,i),u=r.shape.length,c=new Array(u).fill(0),p=r.shape.slice();return l.map(d=>{let h=[...p];h[i]=d;let f=fd({inputs:{x:r},backend:n,attrs:{begin:c,size:h}});return c[i]+=d,f})}var rye={kernelName:Ll,backendName:"webgpu",kernelFunc:sye},aye=Dn({opType:Fe.SQRT}),oye={kernelName:Qo,backendName:"webgpu",kernelFunc:aye},iye={kernelName:Mc,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{x:n}=e,s=t,r=new Bh(n.shape,Fe.SQUARE);return s.runWebGPUProgram(r,[n],n.dtype)}},lye=os({opType:Ye.SQUARED_DIFFERENCE}),uye={kernelName:ni,backendName:"webgpu",kernelFunc:lye},cye=class{constructor(e){this.variableNames=["x"],this.workPerThread=1,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]);let t=Tn(this.outputShape.length);this.uniforms=`begin : ${t},  strides : ${t}, `,this.shaderKey="stridedSlice"}getUserCode(){let e=this.outputShape.length,t="";if(e===1)t="coords * uniforms.strides + uniforms.begin";else{let s=0;t=this.outputShape.map((r,a)=>(s++,this.outputShape.length===1?`coords * uniforms.strides[${a}] + uniforms.begin[${a}]`:`coords[${s-1}] * uniforms.strides[${a}] + uniforms.begin[${a}]`)).join(",")}return`
+    `}};function Q3e(e,t=""){if(e>=5)throw Error(`Tile for rank ${e} is not yet supported`);if(e===1)return`(resRC % ${t}aShape)`;let n=["resRC.x","resRC.y","resRC.z","resRC.w"],s=[];for(let r=0;r<e;r++)s.push(`(${n[r]} % ${t}aShape[${r}])`);return s.join()}function hT(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{reps:a}=s;if(n.shouldExecuteOnCPU([r])||r.dtype==="string"||r.shape.length>=5){let l=n.readSync(r.dataId),u=r.dtype==="string"?l.map(d=>v.decodeString(d)):l,c=Le(r.shape,r.dtype,u),p=D2e(c,a);return n.makeTensorInfo(p.shape,p.dtype,p.values)}let o=new J3e(r.shape,a);return n.runWebGPUProgram(o,[r],r.dtype)}var eye={kernelName:ba,backendName:"webgpu",kernelFunc:hT};function tye(e){let{inputs:t,backend:n,attrs:s}=e,{sparseIndices:r,sparseValues:a,defaultValue:o}=t,{outputShape:i}=s,{sliceRank:l,numUpdates:u,sliceSize:c,strides:p,outputSize:d}=C.calculateShapes(a,r,i),h=!1;if(a.dtype==="string"){let E=n.bufferSync(r),R=n.bufferSync(a),P=v.decodeString(n.readSync(o.dataId)[0]),_=C2e(E,R,i,d,c,u,l,p,P,h);return n.makeTensorInfo(i,_.dtype,_.values)}let f=[d/c,c],m=Ue({inputs:{x:r},backend:n,attrs:{shape:[u,l]}}),g=a.shape.length?Ue({inputs:{x:a},backend:n,attrs:{shape:[u,c]}}):Fs({inputs:{x:a},backend:n}),y=g.dtype,x=n.makeTensorInfo([],y,v.makeZerosTypedArray(1,y)),A=Ue({inputs:{x:o},backend:n,attrs:{shape:Array(f.length).fill(1)}}),b=hT({inputs:{x:A},backend:n,attrs:{reps:f}}),w=v.sizeFromShape([u,c]),k=[{type:"int32",data:[l]},{type:"int32",data:p},{type:"int32",data:[w]}];switch(u){case 0:break;case 1:{let E=new im([u,c],l,m.shape.length,g.shape.length,p,f,y,h);n.runWebGPUProgram(E,[g,m],y,k,b)}break;default:{let E=new im([u,c],l,m.shape.length,x.shape.length,p,f,y,h);n.runWebGPUProgram(E,[x,m],y,k,b)}{let E=new im([u,c],l,m.shape.length,g.shape.length,p,f,y);n.runWebGPUProgram(E,[g,m],y,k,b)}}let S=Ue({inputs:{x:b},backend:n,attrs:{shape:i}});return n.disposeData(m.dataId),n.disposeData(g.dataId),n.disposeData(A.dataId),n.disposeData(x.dataId),n.disposeData(b.dataId),S}var nye={kernelName:Zp,backendName:"webgpu",kernelFunc:tye};function sye(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{numOrSizeSplits:a,axis:o}=s,i=v.parseAxisParam(o,r.shape)[0],l=C.prepareSplitSize(r,a,i),u=r.shape.length,c=new Array(u).fill(0),p=r.shape.slice();return l.map(d=>{let h=[...p];h[i]=d;let f=hd({inputs:{x:r},backend:n,attrs:{begin:c,size:h}});return c[i]+=d,f})}var rye={kernelName:zl,backendName:"webgpu",kernelFunc:sye},aye=Dn({opType:Fe.SQRT}),oye={kernelName:Jo,backendName:"webgpu",kernelFunc:aye},iye={kernelName:Oc,backendName:"webgpu",kernelFunc:({inputs:e,backend:t})=>{let{x:n}=e,s=t,r=new Lh(n.shape,Fe.SQUARE);return s.runWebGPUProgram(r,[n],n.dtype)}},lye=os({opType:Ye.SQUARED_DIFFERENCE}),uye={kernelName:ti,backendName:"webgpu",kernelFunc:lye},cye=class{constructor(e){this.variableNames=["x"],this.workPerThread=1,this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize,[this.workPerThread,1,1]);let t=Tn(this.outputShape.length);this.uniforms=`begin : ${t},  strides : ${t}, `,this.shaderKey="stridedSlice"}getUserCode(){let e=this.outputShape.length,t="";if(e===1)t="coords * uniforms.strides + uniforms.begin";else{let s=0;t=this.outputShape.map((r,a)=>(s++,this.outputShape.length===1?`coords * uniforms.strides[${a}] + uniforms.begin[${a}]`:`coords[${s-1}] * uniforms.strides[${a}] + uniforms.begin[${a}]`)).join(",")}return`
        ${lt()}
          if (index < uniforms.size) {
            let coords = getCoordsFromIndex(index);
            setOutputAtIndex(index, getX(${t}));
          }
        }
-     `}};function dye(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,end:o,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:d}=s,{finalShapeSparse:h,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Ut.sliceInfo(r.shape,a,o,i,l,u,c,p,d),w;if(m)w=Ue({inputs:{x:r},backend:n,attrs:{shape:f}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let k=Ut.computeOutShape(x,A,b),S=fd({inputs:{x:r},backend:n,attrs:{begin:x,size:k}});w=Ue({inputs:{x:S},backend:n,attrs:{shape:f}}),n.disposeData(S.dataId)}else if(n.shouldExecuteOnCPU([r])){let S=n.readSync(r.dataId),E=Le(r.shape,r.dtype,S),R=E2e(h,E,b,x);w=n.makeTensorInfo(f,r.dtype,R.values)}else{let S=new cye(h),E=[{type:"int32",data:x},{type:"int32",data:b}],R=n.runWebGPUProgram(S,[r],r.dtype,E);w=Ue({inputs:{x:R},backend:n,attrs:{shape:f}}),n.disposeData(R.dataId)}return w}var pye={kernelName:Bl,backendName:"webgpu",kernelFunc:dye};function hye(e){let{inputs:t,backend:n,attrs:s}=e,{separator:r,nGramWidths:a,leftPad:o,rightPad:i,padWidth:l,preserveShortSequences:u}=s,{data:c,dataSplits:p}=t,d=n.readSync(c.dataId),h=n.readSync(p.dataId),[f,m]=R2e(d,h,r,a,o,i,l,u);return[n.makeTensorInfo([f.length],"string",f),n.makeTensorInfo(p.shape,"int32",m)]}var fye={kernelName:zc,backendName:"webgpu",kernelFunc:hye},mye=Dn({opType:Fe.TANH}),gye={kernelName:ri,backendName:"webgpu",kernelFunc:mye},yye=class{constructor(e){this.variableNames=["x","indices"],this.workGroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.uniforms=`inputSize : i32, firstPass : i32, negativeInf : f32,
+     `}};function dye(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{begin:a,end:o,strides:i,beginMask:l,endMask:u,ellipsisMask:c,newAxisMask:p,shrinkAxisMask:d}=s,{finalShapeSparse:h,finalShape:f,isIdentity:m,sliceDim0:g,isSimpleSlice:y,begin:x,end:A,strides:b}=Ut.sliceInfo(r.shape,a,o,i,l,u,c,p,d),w;if(m)w=Ue({inputs:{x:r},backend:n,attrs:{shape:f}});else if(g||y){v.assert(r.shape.length>=1,()=>`Input must have rank at least 1, got: ${r.shape.length}`);let k=Ut.computeOutShape(x,A,b),S=hd({inputs:{x:r},backend:n,attrs:{begin:x,size:k}});w=Ue({inputs:{x:S},backend:n,attrs:{shape:f}}),n.disposeData(S.dataId)}else if(n.shouldExecuteOnCPU([r])){let S=n.readSync(r.dataId),E=Le(r.shape,r.dtype,S),R=E2e(h,E,b,x);w=n.makeTensorInfo(f,r.dtype,R.values)}else{let S=new cye(h),E=[{type:"int32",data:x},{type:"int32",data:b}],R=n.runWebGPUProgram(S,[r],r.dtype,E);w=Ue({inputs:{x:R},backend:n,attrs:{shape:f}}),n.disposeData(R.dataId)}return w}var pye={kernelName:Ll,backendName:"webgpu",kernelFunc:dye};function hye(e){let{inputs:t,backend:n,attrs:s}=e,{separator:r,nGramWidths:a,leftPad:o,rightPad:i,padWidth:l,preserveShortSequences:u}=s,{data:c,dataSplits:p}=t,d=n.readSync(c.dataId),h=n.readSync(p.dataId),[f,m]=R2e(d,h,r,a,o,i,l,u);return[n.makeTensorInfo([f.length],"string",f),n.makeTensorInfo(p.shape,"int32",m)]}var fye={kernelName:Mc,backendName:"webgpu",kernelFunc:hye},mye=Dn({opType:Fe.TANH}),gye={kernelName:si,backendName:"webgpu",kernelFunc:mye},yye=class{constructor(e){this.variableNames=["x","indices"],this.workGroupSize=[256,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.uniforms=`inputSize : i32, firstPass : i32, negativeInf : f32,
         dir : i32, inc : i32,`,this.shaderKey="swap"}getUserCode(){return`
         ${lt()}
           if (index < uniforms.size) {
@@ -6710,7 +6710,7 @@ return a / b;`,Gie=`
             }
           }
         }
-      `}};function Mu(e,t){t!==null&&e.disposeData(t.dataId)}function j7(e){let t=1;for(;t<e;)t*=2;return t}function xye(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{k:a,sorted:o}=s,i=r.shape,l=i[i.length-1];if(n.shouldExecuteOnCPU([r])){let w=n.readSync(r.dataId),[k,S]=$2e(w,i,r.dtype,a,o);return[n.makeTensorInfo(k.shape,k.dtype,k.values),n.makeTensorInfo(S.shape,S.dtype,S.values)]}if(a===0)return i[i.length-1]=0,[n.makeTensorInfo(i,r.dtype,[]),n.makeTensorInfo(i,"int32",[])];if(l===1)return[r,ou({attrs:{shape:i,dtype:"int32",value:0},backend:n})];let c=v.sizeFromShape(i)/l,p=Ue({inputs:{x:r},attrs:{shape:[c,l]},backend:n}),d=j7(a),h=j7(l),f=null,m=()=>f===null?[p,p]:[p,f],g=(w,k,S)=>{let E=m(),R=new yye(S),_=[{type:"int32",data:[l]},{type:"int32",data:[f===null?1:0]},{type:"float32",data:[Number.NEGATIVE_INFINITY]},{type:"int32",data:[w]},{type:"int32",data:[k]}],$=f;f=n.runWebGPUProgram(R,E,"int32",_),Mu(n,$)};for(let w=1;w<d;w*=2){let k=w*2;for(let S=w;S>=1;S/=2)g(k,S,[c,h])}for(let w=h;w>d;w/=2){let k=m(),S=new Aye([c,w/2]),R=[{type:"int32",data:[l]},{type:"int32",data:[f===null?1:0]},{type:"int32",data:[d]}],P=f;f=n.runWebGPUProgram(S,k,"int32",R),Mu(n,P);let _=d/2,$=_*2;for(let T=_;T>=1;T/=2)g($,T,f.shape)}let y=f;f=fd({inputs:{x:f},backend:n,attrs:{begin:0,size:[c,a]}}),Mu(n,y);let x=iT({inputs:{x:p,indices:f},backend:n,attrs:{axis:1,batchDims:1}});Mu(n,p);let A=i.slice(0,-1);A.push(a),y=f,f=Ue({inputs:{x:f},attrs:{shape:A},backend:n}),Mu(n,y);let b=x;return x=Ue({inputs:{x},attrs:{shape:A},backend:n}),Mu(n,b),[x,f]}var bye={kernelName:Vl,backendName:"webgpu",kernelFunc:xye},vye=class{constructor(e){this.variableNames=["Image","Transforms"],this.uniforms="interpolationModeId : i32, fillModeId : i32, fillValue : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="transform"}getUserCode(){return`
+      `}};function Ou(e,t){t!==null&&e.disposeData(t.dataId)}function j7(e){let t=1;for(;t<e;)t*=2;return t}function xye(e){let{inputs:t,backend:n,attrs:s}=e,{x:r}=t,{k:a,sorted:o}=s,i=r.shape,l=i[i.length-1];if(n.shouldExecuteOnCPU([r])){let w=n.readSync(r.dataId),[k,S]=$2e(w,i,r.dtype,a,o);return[n.makeTensorInfo(k.shape,k.dtype,k.values),n.makeTensorInfo(S.shape,S.dtype,S.values)]}if(a===0)return i[i.length-1]=0,[n.makeTensorInfo(i,r.dtype,[]),n.makeTensorInfo(i,"int32",[])];if(l===1)return[r,au({attrs:{shape:i,dtype:"int32",value:0},backend:n})];let c=v.sizeFromShape(i)/l,p=Ue({inputs:{x:r},attrs:{shape:[c,l]},backend:n}),d=j7(a),h=j7(l),f=null,m=()=>f===null?[p,p]:[p,f],g=(w,k,S)=>{let E=m(),R=new yye(S),_=[{type:"int32",data:[l]},{type:"int32",data:[f===null?1:0]},{type:"float32",data:[Number.NEGATIVE_INFINITY]},{type:"int32",data:[w]},{type:"int32",data:[k]}],$=f;f=n.runWebGPUProgram(R,E,"int32",_),Ou(n,$)};for(let w=1;w<d;w*=2){let k=w*2;for(let S=w;S>=1;S/=2)g(k,S,[c,h])}for(let w=h;w>d;w/=2){let k=m(),S=new Aye([c,w/2]),R=[{type:"int32",data:[l]},{type:"int32",data:[f===null?1:0]},{type:"int32",data:[d]}],P=f;f=n.runWebGPUProgram(S,k,"int32",R),Ou(n,P);let _=d/2,$=_*2;for(let T=_;T>=1;T/=2)g($,T,f.shape)}let y=f;f=hd({inputs:{x:f},backend:n,attrs:{begin:0,size:[c,a]}}),Ou(n,y);let x=iT({inputs:{x:p,indices:f},backend:n,attrs:{axis:1,batchDims:1}});Ou(n,p);let A=i.slice(0,-1);A.push(a),y=f,f=Ue({inputs:{x:f},attrs:{shape:A},backend:n}),Ou(n,y);let b=x;return x=Ue({inputs:{x},attrs:{shape:A},backend:n}),Ou(n,b),[x,f]}var bye={kernelName:Wl,backendName:"webgpu",kernelFunc:xye},vye=class{constructor(e){this.variableNames=["Image","Transforms"],this.uniforms="interpolationModeId : i32, fillModeId : i32, fillValue : f32,",this.workGroupSize=[64,1,1],this.size=!0,this.outputShape=e,this.dispatchLayout=at(this.outputShape),this.dispatch=We(this.dispatchLayout,this.outputShape,this.workGroupSize),this.shaderKey="transform"}getUserCode(){return`
           fn mapCoord(outCoord : f32, len : f32) -> f32{
             var inCoord = outCoord;
             if(uniforms.fillModeId == 2) {
@@ -6826,7 +6826,7 @@ return a / b;`,Gie=`
               setOutputAtIndex(index, outputValue);
             }
           }
-        `}};function wye(e){let{inputs:t,backend:n,attrs:s}=e,{image:r,transforms:a}=t,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=s,[c,p,d,h]=r.shape,[f,m]=u!=null?u:[p,d],g=[c,f,m,h],y=new vye(g),x=o==="nearest"?1:2,A;switch(i){case"constant":A=1;break;case"reflect":A=2;break;case"wrap":A=3;break;case"nearest":A=4;break;default:A=1;break}let b=[{type:"int32",data:[x]},{type:"int32",data:[A]},{type:"float32",data:[l]}];return n.runWebGPUProgram(y,[r,a],"float32",b)}var kye={kernelName:Ul,backendName:"webgpu",kernelFunc:wye};function Iye(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r,i=o.shape.length,l=r.shape[a],u=new Array(i-1),c=0;for(let m=0;m<i;m++)m!==a&&(u[c++]=o.shape[m]);let p=[],d=new Array(i).fill(0),h=o.shape.slice();h[a]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[a]=m;let g=fd({inputs:{x:o},backend:n,attrs:{begin:d,size:h}}),y=Ue({inputs:{x:g},backend:n,attrs:{shape:u}});f[m]=y,p.push(g)}return p.forEach(m=>n.disposeData(m.dataId)),f}var Sye={kernelName:Gl,backendName:"webgpu",kernelFunc:Iye},Cye=[e2e,O2e,z2e,W2e,q2e,K2e,Y2e,Q2e,r1e,l1e,c1e,f1e,n2e,A1e,k1e,N1e,R1e,D1e,F1e,M1e,L1e,V1e,H1e,Z1e,J1e,ege,tge,nge,rge,Y0e,oge,pge,lge,cge,mge,yge,xge,wge,Sge,Tge,Ege,t2e,g1e,_ge,$ge,Fge,Mge,Lge,Wge,Vge,Gge,jge,Xge,Zge,Jge,e3e,j1e,n3e,r3e,o3e,a1e,l3e,c3e,p3e,f3e,g3e,A3e,b3e,o1e,v3e,k3e,S3e,J0e,N3e,_3e,$3e,F3e,M3e,B3e,V3e,G3e,j3e,n1e,pye,fye,K3e,Y3e,nye,rye,oye,iye,uye,q3e,X1e,gye,eye,bye,kye,H2e,Sye,i3e];for(let e of Cye)cr(e);var Tye=class{constructor(e){this.device=e,this.numUsedBuffers=0,this.numFreeBuffers=0,this.freeBuffers=new Map,this.usedBuffers=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireUploadBuffer(e,t){return this.acquireBuffer(e,t,!0)}acquireBuffer(e,t,n=!1){let s=q7(e,t);if(this.freeBuffers.has(s)||this.freeBuffers.set(s,[]),this.usedBuffers.has(s)||this.usedBuffers.set(s,[]),this.numBytesUsed+=e,this.numUsedBuffers++,this.freeBuffers.get(s).length>0){this.numFreeBuffers--;let a=this.freeBuffers.get(s).shift();return this.usedBuffers.get(s).push(a),a}this.numBytesAllocated+=e;let r=this.device.createBuffer({size:e,usage:t,mappedAtCreation:n});return this.usedBuffers.get(s).push(r),r}releaseBuffer(e,t,n){if(this.freeBuffers.size===0)return;let s=q7(t,n);this.freeBuffers.has(s)||this.freeBuffers.set(s,[]),this.freeBuffers.get(s).push(e),this.numFreeBuffers++,this.numUsedBuffers--;let r=this.usedBuffers.get(s),a=r.indexOf(e);if(a<0)throw new Error("Cannot release a buffer that was never provided by this buffer manager");r.splice(a,1),this.numBytesUsed-=t}releaseUploadBuffer(e,t,n){e.mapAsync(GPUMapMode.WRITE).then(()=>{this.releaseBuffer(e,t,n)},s=>{})}getNumUsedBuffers(){return this.numUsedBuffers}getNumFreeBuffers(){return this.numFreeBuffers}dispose(){this.freeBuffers.forEach((e,t)=>{e.forEach(n=>{n.destroy()})}),this.usedBuffers.forEach((e,t)=>{e.forEach(n=>{n.destroy()})}),this.freeBuffers=new Map,this.usedBuffers=new Map,this.numUsedBuffers=0,this.numFreeBuffers=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function q7(e,t){return`${e}_${t}`}var Nye=class{constructor(e){this.device=e,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures=new Map,this.usedTextures=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireTexture(e,t,n,s){let r=K7(n),a=e*t*r,o=X7(e,t,n,s);if(this.freeTextures.has(o)||this.freeTextures.set(o,[]),this.usedTextures.has(o)||this.usedTextures.set(o,[]),this.numBytesUsed+=a,this.numUsedTextures++,this.freeTextures.get(o).length>0){this.numFreeTextures--;let l=this.freeTextures.get(o).shift();return this.usedTextures.get(o).push(l),l}this.numBytesAllocated+=a;let i=this.device.createTexture({size:[e,t],format:n,usage:s});return this.usedTextures.get(o).push(i),i}releaseTexture(e,t,n,s,r){if(this.freeTextures.size===0)return;let a=X7(t,n,s,r);this.freeTextures.has(a)||this.freeTextures.set(a,[]),this.freeTextures.get(a).push(e),this.numFreeTextures++,this.numUsedTextures--;let o=this.usedTextures.get(a),i=o.indexOf(e);if(i<0)throw new Error("Cannot release a texture that was never provided by this texture manager");o.splice(i,1);let l=K7(s),u=t*n*l;this.numBytesUsed-=u}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){this.freeTextures.forEach((e,t)=>{e.forEach(n=>{n.destroy()})}),this.usedTextures.forEach((e,t)=>{e.forEach(n=>{n.destroy()})}),this.freeTextures=new Map,this.usedTextures=new Map,this.numUsedTextures=0,this.numFreeTextures=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function X7(e,t,n,s){return`${e}_${t}_${n}_${s}`}function K7(e){if(e==="rgba8unorm")return 16;throw new Error(`${e} is not supported!`)}var Eye=Z().getNumber("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD"),Rye=(e,t)=>{let n=e.limits.maxComputeWorkgroupsPerDimension,s=t.dispatchLayout,r=t.dispatch;if(r.every(o=>o<=n))return r;v.assert(r[0]>n&&s.y===void 0&&s.z===void 0,()=>"Dispatch size exceeds WebGPU limits in Y or Z dimension.");let a=Math.ceil(Math.sqrt(r[0]));return a>n?(a=Math.ceil(Math.cbrt(r[0])),v.assert(a<=n,()=>"Total dispatch size exceeds WebGPU maximum."),[a,a,a]):[a,a,1]},R2=class extends cc{constructor(e,t=!1){if(super(),this.commandQueueOwnedIds=new WeakSet,this.dispatchNumberInEncoder=0,this.disposed=!1,this.downloadWaitMs=0,this.tensorDataPendingDisposal=[],this.stagingPendingDisposal=[],this.uniformPendingDisposal=[],this.uploadWaitMs=0,!rb())throw new Error("WebGPU is not supported on this device");this.pipelineCache={},this.device=e,this.queue=e.queue,this.currentCommandEncoder=null,this.currentComputePass=null,this.supportTimeQuery=t,this.bufferManager=new Tye(this.device),this.textureManager=new Nye(this.device),this.tensorMap=new Mp(this,sn()),this.supportTimeQuery&&(this.querySet=this.device.createQuerySet({type:"timestamp",count:2})),Z().getBool("WEBGPU_USE_PROFILE_TOOL")&&(this.dummyCanvas=document.createElement("canvas"),this.dummyCanvas.width=1,this.dummyCanvas.height=1,this.dummyContext=this.dummyCanvas.getContext("webgpu"),this.dummyContext.configure({device:e,format:"bgra8unorm"}),document.body.appendChild(this.dummyCanvas))}nextDataId(){return R2.nextDataId++}floatPrecision(){return 32}defaultGpuBufferUsage(){return GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST}disposeData(e,t=!1){if(this.tensorDataPendingDisposal.indexOf(e)>=0)return!1;if(!this.tensorMap.has(e))return!0;let n=this.tensorMap.get(e);if(this.decRef(e),!t&&n.refCount>0)return!1;if(this.commandQueueOwnedIds.has(e))return this.tensorDataPendingDisposal.push(e),!1;let{complexTensorInfos:s}=this.tensorMap.get(e);return s!=null&&(this.disposeData(s.real.dataId,t),this.disposeData(s.imag.dataId,t)),this.releaseResource(e),this.tensorMap.delete(e),!0}memory(){return{numBytesInGPU:this.bufferManager.numBytesUsed,numBytesAllocatedInGPU:this.bufferManager.numBytesAllocated,unreliable:!1}}releaseResource(e){let t=this.tensorMap.get(e);if(!(!t||!t.resourceInfo)){if("texture"in t.resourceInfo){let n=t.resourceInfo;n.texture instanceof GPUTexture&&this.textureManager.releaseTexture(n.texture,n.width,n.height,n.format,n.usage),n.texture=null}else{let n=t.resourceInfo;this.bufferManager.releaseBuffer(n.buffer,n.size,n.usage),n.buffer=null}t.resourceInfo=null}}refCount(e){return this.tensorMap.has(e)?this.tensorMap.get(e).refCount:0}incRef(e){let t=this.tensorMap.get(e);t.refCount++}decRef(e){if(this.tensorMap.has(e)){let t=this.tensorMap.get(e);t.refCount--}}write(e,t,n){if(n==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let s={id:this.nextDataId()};return this.tensorMap.set(s,{dtype:n,shape:t,values:e,refCount:1}),s}move(e,t,n,s,r){if(s==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.tensorMap.set(e,{dtype:s,shape:n,values:t,refCount:r})}submitQueue(){this.ensureComputePassEnded(),this.queue.submit([this.currentCommandEncoder.finish()]),this.currentCommandEncoder=null,this.dispatchNumberInEncoder=0,this.commandQueueOwnedIds=new WeakSet,this.tensorDataPendingDisposal.forEach(e=>{this.releaseResource(e),this.tensorMap.delete(e)}),this.uniformPendingDisposal.forEach(e=>this.bufferManager.releaseBuffer(e.buffer,e.size,e.usage)),this.stagingPendingDisposal.forEach(e=>this.bufferManager.releaseUploadBuffer(e.buffer,e.size,e.usage)),this.tensorDataPendingDisposal=[],this.uniformPendingDisposal=[],this.stagingPendingDisposal=[]}ensureCommandEncoderReady(){this.currentCommandEncoder||(this.currentCommandEncoder=this.device.createCommandEncoder())}ensureComputePassEnded(){this.currentComputePass&&(this.currentComputePass.end(),this.currentComputePass=null)}getComputePass(){return this.currentComputePass||(this.currentComputePass=this.currentCommandEncoder.beginComputePass()),this.currentComputePass}async getBufferData(e,t){let n=this.bufferManager.acquireBuffer(t,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(e,0,n,0,t),this.submitQueue(),await n.mapAsync(GPUMapMode.READ);let s=n.getMappedRange().slice(0);return n.unmap(),n!=null&&this.bufferManager.releaseBuffer(n,t,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ),Z().getBool("WEBGPU_USE_PROFILE_TOOL")&&(v.assert(this.dummyContext!==void 0,()=>"Fail to get context for profiling tool"),this.dummyContext.getCurrentTexture()),s}convertAndCacheOnCPU(e,t){let n=this.tensorMap.get(e);return this.releaseResource(e),n.values=t,n.values}readSync(e){let t=this.tensorMap.get(e),{values:n}=t;if(n==null)throw new Error("WebGPU readSync is only available for CPU-resident tensors.");return n}async read(e){if(!this.tensorMap.has(e))throw new Error(`Tensor ${e} was not registered!`);let t=this.tensorMap.get(e),{values:n}=t;if(n!=null)return this.convertAndCacheOnCPU(e,n);let s;if(t.dtype==="complex64"){let r=await Promise.all([this.read(t.complexTensorInfos.real.dataId),this.read(t.complexTensorInfos.imag.dataId)]),a=r[0],o=r[1];s=C.mergeRealAndImagArrays(a,o)}else{let r=t.resourceInfo,a=await this.getBufferData(r.buffer,r.size);s=XC(a,t.dtype)}return this.convertAndCacheOnCPU(e,s),s}readToGPU(e){let t=this.tensorMap.get(e),{values:n,dtype:s,shape:r,resourceInfo:a}=t;if(s==="complex64")throw new Error("Does not support reading buffer for complex64 dtype.");if(a==null)throw n!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let o=a.size,i=this.bufferManager.acquireBuffer(o,a.usage);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(a.buffer,0,i,0,o),this.submitQueue();let l=this.makeTensorInfo(r,s),u=sn().makeTensorFromTensorInfo(l),c=this.tensorMap.get(l.dataId);return c.resourceInfo={size:o,usage:this.defaultGpuBufferUsage(),buffer:i},{tensorRef:u,buffer:i,bufSize:o}}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let n=t.map(s=>v.decodeString(s));return Le(e.shape,e.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Le(e.shape,e.dtype,t)}async time(e){let t=this.activeTimers,n=[],s=!1;this.programTimersStack==null?(this.programTimersStack=n,s=!0):this.activeTimers.push(n),this.activeTimers=n,e();let r=v.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),a=v.flatten(this.activeTimers.map(l=>l.name)).filter(l=>l!=null);this.activeTimers=t,s&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null},i=await Promise.all(r);return o.kernelMs=v.sum(i),o.getExtraProfileInfo=()=>i.map((l,u)=>({name:a[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", "),this.uploadWaitMs=0,this.downloadWaitMs=0,o}makeTensorInfo(e,t,n){return t==="string"&&n!=null&&n.length>0&&v.isString(n[0])&&(n=n.map(r=>v.encodeString(r))),{dataId:this.write(n,e,t),shape:e,dtype:t}}tensorToBinding(e){if(!e)return null;let t=this.tensorMap.get(e.dataId);if("texture"in t.resourceInfo){let s=t.resourceInfo;return s.texture instanceof GPUExternalTexture?s.texture:s.texture.createView()}let n=t.resourceInfo;return{offset:0,size:n.size,buffer:n.buffer}}async getQueryTime(e){return this.supportTimeQuery?this.getTimeFromQuerySet(e):0}uploadToGPU(e){let t=this.tensorMap.get(e);if(t.resourceInfo)return;let n=qC(t.dtype)*v.sizeFromShape(t.shape),s=this.bufferManager.acquireBuffer(n,this.defaultGpuBufferUsage());if(t.resourceInfo={size:n,usage:this.defaultGpuBufferUsage(),buffer:s},t.values){let r=this.bufferManager.acquireUploadBuffer(n,GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC),a=r.getMappedRange();t.dtype==="int32"||t.dtype==="bool"?new Int32Array(a).set(t.values):new Float32Array(a).set(t.values),r.unmap(),this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(r,0,s,0,n);let o={size:n,usage:GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC,buffer:r};this.stagingPendingDisposal.push(o)}}makeUniforms(e){let t=0,n=0,s=[];e.forEach(i=>{i.data.length===0&&(i.data=[1]);let l;switch(i.data.length){case 1:l=4;break;case 2:l=8;break;case 3:l=16;break;case 4:l=16;break;case 5:l=16;break;case 6:l=16;break;default:v.assert(!1,()=>`Unsupported ${i.data.length}D shape`)}(n===5||n===6)&&(l=16),t=Math.ceil(t/l)*l,n=i.data.length,s.push(t),t+=i.data.length*4});let r=new ArrayBuffer(t);e.forEach((i,l)=>{let u=s[l];i.type==="int32"?new Int32Array(r,u,i.data.length).set(i.data):i.type==="uint32"?new Uint32Array(r,u,i.data.length).set(i.data):new Float32Array(r,u,i.data.length).set(i.data)});let a=this.bufferManager.acquireBuffer(t,GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM);this.queue.writeBuffer(a,0,r,0,t);let o={size:t,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM,buffer:a};return this.uniformPendingDisposal.push(o),{offset:0,size:t,buffer:a}}runWebGPUProgram(e,t,n,s,r){if(r||(r=this.makeTensorInfo(e.outputShape,n)),v.sizeFromShape(r.shape)===0)return this.tensorMap.get(r.dataId).values=v.getTypedArrayFromDType(r.dtype,0),r;this.uploadToGPU(r.dataId),e.dispatch=Rye(this.device,e);let a=[],o=[];if(!e.isFromPixels){a.push({type:"float32",data:[NaN]}),o=t.concat(r).map(g=>g.shape);let f="int32";o.map(g=>{a.push({type:f,data:g})});let m=v.computeStrides(r.shape);if(a.push({type:f,data:m}),e.size){let g=v.sizeFromShape(e.outputShape);a.push({type:f,data:[e.isVec4?g/4:g]})}}let i=t.map((f,m)=>{if(f.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");return this.uploadToGPU(f.dataId),{dtype:this.tensorMap.get(f.dataId).dtype,shape:f.shape,name:e.variableNames[m]}}),l=N0e(e,o,i,r),u;l in this.pipelineCache?u=this.pipelineCache[l]:(u=C0e(this.device,e,i,r),this.pipelineCache[l]=u),s&&(a=[...a,...s]);let c=[this.tensorToBinding(r),...t.map(f=>this.tensorToBinding(f)),this.makeUniforms(a)],p=this.device.createBindGroup({layout:u.getBindGroupLayout(0),entries:c.map((f,m)=>({binding:m,resource:f}))});this.ensureCommandEncoderReady();let d=this.getComputePass(),h=this.activeTimers!=null;return h&&this.supportTimeQuery&&d.writeTimestamp(this.querySet,0),d.setPipeline(u),d.setBindGroup(0,p),d.dispatchWorkgroups(e.dispatch[0],e.dispatch[1],e.dispatch[2]),h&&this.supportTimeQuery&&d.writeTimestamp(this.querySet,1),this.dispatchNumberInEncoder++,t.forEach(f=>{this.commandQueueOwnedIds.add(f.dataId)}),this.commandQueueOwnedIds.add(r.dataId),Z().get("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE")<=this.dispatchNumberInEncoder&&this.submitQueue(),h&&this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(this.querySet)}),r}async getTimeFromQuerySet(e){let t=this.bufferManager.acquireBuffer(16,GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE),n=this.bufferManager.acquireBuffer(16,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.resolveQuerySet(e,0,2,t,0),this.currentCommandEncoder.copyBufferToBuffer(t,0,n,0,16),this.submitQueue(),await n.mapAsync(GPUMapMode.READ);let s=new BigUint64Array(n.getMappedRange()),r=Number(s[1]-s[0]);return n.unmap(),this.bufferManager.releaseBuffer(n,16,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST),this.bufferManager.releaseBuffer(t,16,GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE),r/1e6}shouldExecuteOnCPU(e,t=Eye){return Z().getBool("WEBGPU_CPU_FORWARD")&&e.every(n=>this.tensorMap.get(n.dataId).resourceInfo==null&&v.sizeFromShape(n.shape)<t)}numDataIds(){return this.tensorMap.numDataIds()-this.tensorDataPendingDisposal.length}dispose(){this.disposed||(this.bufferManager.dispose(),this.textureManager.dispose(),this.disposed=!0)}};R2.nextDataId=0;var fT={};Ve(fT,{WebGPUBackend:()=>R2,webgpu_util:()=>HC});rb()&&ql("webgpu",async()=>{Z().set("CHECK_COMPUTATION_FOR_ERRORS",!1);let e={powerPreference:Z().get("WEBGPU_USE_LOW_POWER_GPU")?"low-power":"high-performance"},t=await navigator.gpu.requestAdapter(e),n=t.limits,s={},r=t.features.has("timestamp-query");s.requiredLimits={maxComputeWorkgroupStorageSize:n.maxComputeWorkgroupStorageSize,maxComputeWorkgroupsPerDimension:n.maxComputeWorkgroupsPerDimension,maxStorageBufferBindingSize:n.maxStorageBufferBindingSize},r?s.requiredFeatures=["timestamp-query"]:console.warn("This device doesn't support timestamp-query extension. Start Chrome browser with flag --disable-dawn-features=disallow_unsafe_apis then try again. Or zero will shown for the kernel time when profiling mode isenabled. Using performance.now is not workable for webgpu sinceit doesn't support synchronously to read data from GPU.");let a=await t.requestDevice(s);return new R2(a,r)},3);var _ye="3.19.0",Dye="3.19.0",$ye="3.19.0",Pye="3.19.0",Fye="3.19.0",Oye="3.19.0",Mye="3.19.0",Uh={tfjs:_ye,"tfjs-core":Dye,"tfjs-data":$ye,"tfjs-layers":Pye,"tfjs-converter":Fye,"tfjs-backend-webgl":Oye,"tfjs-backend-wasm":Mye};var mT=`
+        `}};function wye(e){let{inputs:t,backend:n,attrs:s}=e,{image:r,transforms:a}=t,{interpolation:o,fillMode:i,fillValue:l,outputShape:u}=s,[c,p,d,h]=r.shape,[f,m]=u!=null?u:[p,d],g=[c,f,m,h],y=new vye(g),x=o==="nearest"?1:2,A;switch(i){case"constant":A=1;break;case"reflect":A=2;break;case"wrap":A=3;break;case"nearest":A=4;break;default:A=1;break}let b=[{type:"int32",data:[x]},{type:"int32",data:[A]},{type:"float32",data:[l]}];return n.runWebGPUProgram(y,[r,a],"float32",b)}var kye={kernelName:Vl,backendName:"webgpu",kernelFunc:wye};function Iye(e){let{inputs:t,backend:n,attrs:s}=e,{value:r}=t,{axis:a}=s;a<0&&(a+=r.shape.length);let o=r,i=o.shape.length,l=r.shape[a],u=new Array(i-1),c=0;for(let m=0;m<i;m++)m!==a&&(u[c++]=o.shape[m]);let p=[],d=new Array(i).fill(0),h=o.shape.slice();h[a]=1;let f=new Array(l);for(let m=0;m<f.length;m++){d[a]=m;let g=hd({inputs:{x:o},backend:n,attrs:{begin:d,size:h}}),y=Ue({inputs:{x:g},backend:n,attrs:{shape:u}});f[m]=y,p.push(g)}return p.forEach(m=>n.disposeData(m.dataId)),f}var Sye={kernelName:Ul,backendName:"webgpu",kernelFunc:Iye},Cye=[e2e,O2e,z2e,W2e,q2e,K2e,Y2e,Q2e,r1e,l1e,c1e,f1e,n2e,A1e,k1e,N1e,R1e,D1e,F1e,M1e,L1e,V1e,H1e,Z1e,J1e,ege,tge,nge,rge,Y0e,oge,pge,lge,cge,mge,yge,xge,wge,Sge,Tge,Ege,t2e,g1e,_ge,$ge,Fge,Mge,Lge,Wge,Vge,Gge,jge,Xge,Zge,Jge,e3e,j1e,n3e,r3e,o3e,a1e,l3e,c3e,p3e,f3e,g3e,A3e,b3e,o1e,v3e,k3e,S3e,J0e,N3e,_3e,$3e,F3e,M3e,B3e,V3e,G3e,j3e,n1e,pye,fye,K3e,Y3e,nye,rye,oye,iye,uye,q3e,X1e,gye,eye,bye,kye,H2e,Sye,i3e];for(let e of Cye)cr(e);var Tye=class{constructor(e){this.device=e,this.numUsedBuffers=0,this.numFreeBuffers=0,this.freeBuffers=new Map,this.usedBuffers=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireUploadBuffer(e,t){return this.acquireBuffer(e,t,!0)}acquireBuffer(e,t,n=!1){let s=q7(e,t);if(this.freeBuffers.has(s)||this.freeBuffers.set(s,[]),this.usedBuffers.has(s)||this.usedBuffers.set(s,[]),this.numBytesUsed+=e,this.numUsedBuffers++,this.freeBuffers.get(s).length>0){this.numFreeBuffers--;let a=this.freeBuffers.get(s).shift();return this.usedBuffers.get(s).push(a),a}this.numBytesAllocated+=e;let r=this.device.createBuffer({size:e,usage:t,mappedAtCreation:n});return this.usedBuffers.get(s).push(r),r}releaseBuffer(e,t,n){if(this.freeBuffers.size===0)return;let s=q7(t,n);this.freeBuffers.has(s)||this.freeBuffers.set(s,[]),this.freeBuffers.get(s).push(e),this.numFreeBuffers++,this.numUsedBuffers--;let r=this.usedBuffers.get(s),a=r.indexOf(e);if(a<0)throw new Error("Cannot release a buffer that was never provided by this buffer manager");r.splice(a,1),this.numBytesUsed-=t}releaseUploadBuffer(e,t,n){e.mapAsync(GPUMapMode.WRITE).then(()=>{this.releaseBuffer(e,t,n)},s=>{})}getNumUsedBuffers(){return this.numUsedBuffers}getNumFreeBuffers(){return this.numFreeBuffers}dispose(){this.freeBuffers.forEach((e,t)=>{e.forEach(n=>{n.destroy()})}),this.usedBuffers.forEach((e,t)=>{e.forEach(n=>{n.destroy()})}),this.freeBuffers=new Map,this.usedBuffers=new Map,this.numUsedBuffers=0,this.numFreeBuffers=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function q7(e,t){return`${e}_${t}`}var Nye=class{constructor(e){this.device=e,this.numUsedTextures=0,this.numFreeTextures=0,this.freeTextures=new Map,this.usedTextures=new Map,this.numBytesUsed=0,this.numBytesAllocated=0}acquireTexture(e,t,n,s){let r=K7(n),a=e*t*r,o=X7(e,t,n,s);if(this.freeTextures.has(o)||this.freeTextures.set(o,[]),this.usedTextures.has(o)||this.usedTextures.set(o,[]),this.numBytesUsed+=a,this.numUsedTextures++,this.freeTextures.get(o).length>0){this.numFreeTextures--;let l=this.freeTextures.get(o).shift();return this.usedTextures.get(o).push(l),l}this.numBytesAllocated+=a;let i=this.device.createTexture({size:[e,t],format:n,usage:s});return this.usedTextures.get(o).push(i),i}releaseTexture(e,t,n,s,r){if(this.freeTextures.size===0)return;let a=X7(t,n,s,r);this.freeTextures.has(a)||this.freeTextures.set(a,[]),this.freeTextures.get(a).push(e),this.numFreeTextures++,this.numUsedTextures--;let o=this.usedTextures.get(a),i=o.indexOf(e);if(i<0)throw new Error("Cannot release a texture that was never provided by this texture manager");o.splice(i,1);let l=K7(s),u=t*n*l;this.numBytesUsed-=u}getNumUsedTextures(){return this.numUsedTextures}getNumFreeTextures(){return this.numFreeTextures}dispose(){this.freeTextures.forEach((e,t)=>{e.forEach(n=>{n.destroy()})}),this.usedTextures.forEach((e,t)=>{e.forEach(n=>{n.destroy()})}),this.freeTextures=new Map,this.usedTextures=new Map,this.numUsedTextures=0,this.numFreeTextures=0,this.numBytesUsed=0,this.numBytesAllocated=0}};function X7(e,t,n,s){return`${e}_${t}_${n}_${s}`}function K7(e){if(e==="rgba8unorm")return 16;throw new Error(`${e} is not supported!`)}var Eye=X().getNumber("WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD"),Rye=(e,t)=>{let n=e.limits.maxComputeWorkgroupsPerDimension,s=t.dispatchLayout,r=t.dispatch;if(r.every(o=>o<=n))return r;v.assert(r[0]>n&&s.y===void 0&&s.z===void 0,()=>"Dispatch size exceeds WebGPU limits in Y or Z dimension.");let a=Math.ceil(Math.sqrt(r[0]));return a>n?(a=Math.ceil(Math.cbrt(r[0])),v.assert(a<=n,()=>"Total dispatch size exceeds WebGPU maximum."),[a,a,a]):[a,a,1]},E2=class extends uc{constructor(e,t=!1){if(super(),this.commandQueueOwnedIds=new WeakSet,this.dispatchNumberInEncoder=0,this.disposed=!1,this.downloadWaitMs=0,this.tensorDataPendingDisposal=[],this.stagingPendingDisposal=[],this.uniformPendingDisposal=[],this.uploadWaitMs=0,!rb())throw new Error("WebGPU is not supported on this device");this.pipelineCache={},this.device=e,this.queue=e.queue,this.currentCommandEncoder=null,this.currentComputePass=null,this.supportTimeQuery=t,this.bufferManager=new Tye(this.device),this.textureManager=new Nye(this.device),this.tensorMap=new Op(this,sn()),this.supportTimeQuery&&(this.querySet=this.device.createQuerySet({type:"timestamp",count:2})),X().getBool("WEBGPU_USE_PROFILE_TOOL")&&(this.dummyCanvas=document.createElement("canvas"),this.dummyCanvas.width=1,this.dummyCanvas.height=1,this.dummyContext=this.dummyCanvas.getContext("webgpu"),this.dummyContext.configure({device:e,format:"bgra8unorm"}),document.body.appendChild(this.dummyCanvas))}nextDataId(){return E2.nextDataId++}floatPrecision(){return 32}defaultGpuBufferUsage(){return GPUBufferUsage.STORAGE|GPUBufferUsage.COPY_SRC|GPUBufferUsage.COPY_DST}disposeData(e,t=!1){if(this.tensorDataPendingDisposal.indexOf(e)>=0)return!1;if(!this.tensorMap.has(e))return!0;let n=this.tensorMap.get(e);if(this.decRef(e),!t&&n.refCount>0)return!1;if(this.commandQueueOwnedIds.has(e))return this.tensorDataPendingDisposal.push(e),!1;let{complexTensorInfos:s}=this.tensorMap.get(e);return s!=null&&(this.disposeData(s.real.dataId,t),this.disposeData(s.imag.dataId,t)),this.releaseResource(e),this.tensorMap.delete(e),!0}memory(){return{numBytesInGPU:this.bufferManager.numBytesUsed,numBytesAllocatedInGPU:this.bufferManager.numBytesAllocated,unreliable:!1}}releaseResource(e){let t=this.tensorMap.get(e);if(!(!t||!t.resourceInfo)){if("texture"in t.resourceInfo){let n=t.resourceInfo;n.texture instanceof GPUTexture&&this.textureManager.releaseTexture(n.texture,n.width,n.height,n.format,n.usage),n.texture=null}else{let n=t.resourceInfo;this.bufferManager.releaseBuffer(n.buffer,n.size,n.usage),n.buffer=null}t.resourceInfo=null}}refCount(e){return this.tensorMap.has(e)?this.tensorMap.get(e).refCount:0}incRef(e){let t=this.tensorMap.get(e);t.refCount++}decRef(e){if(this.tensorMap.has(e)){let t=this.tensorMap.get(e);t.refCount--}}write(e,t,n){if(n==="complex64"&&e!=null)throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");let s={id:this.nextDataId()};return this.tensorMap.set(s,{dtype:n,shape:t,values:e,refCount:1}),s}move(e,t,n,s,r){if(s==="complex64")throw new Error("Cannot write to a complex64 dtype. Please use tf.complex(real, imag).");this.tensorMap.set(e,{dtype:s,shape:n,values:t,refCount:r})}submitQueue(){this.ensureComputePassEnded(),this.queue.submit([this.currentCommandEncoder.finish()]),this.currentCommandEncoder=null,this.dispatchNumberInEncoder=0,this.commandQueueOwnedIds=new WeakSet,this.tensorDataPendingDisposal.forEach(e=>{this.releaseResource(e),this.tensorMap.delete(e)}),this.uniformPendingDisposal.forEach(e=>this.bufferManager.releaseBuffer(e.buffer,e.size,e.usage)),this.stagingPendingDisposal.forEach(e=>this.bufferManager.releaseUploadBuffer(e.buffer,e.size,e.usage)),this.tensorDataPendingDisposal=[],this.uniformPendingDisposal=[],this.stagingPendingDisposal=[]}ensureCommandEncoderReady(){this.currentCommandEncoder||(this.currentCommandEncoder=this.device.createCommandEncoder())}ensureComputePassEnded(){this.currentComputePass&&(this.currentComputePass.end(),this.currentComputePass=null)}getComputePass(){return this.currentComputePass||(this.currentComputePass=this.currentCommandEncoder.beginComputePass()),this.currentComputePass}async getBufferData(e,t){let n=this.bufferManager.acquireBuffer(t,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(e,0,n,0,t),this.submitQueue(),await n.mapAsync(GPUMapMode.READ);let s=n.getMappedRange().slice(0);return n.unmap(),n!=null&&this.bufferManager.releaseBuffer(n,t,GPUBufferUsage.COPY_DST|GPUBufferUsage.MAP_READ),X().getBool("WEBGPU_USE_PROFILE_TOOL")&&(v.assert(this.dummyContext!==void 0,()=>"Fail to get context for profiling tool"),this.dummyContext.getCurrentTexture()),s}convertAndCacheOnCPU(e,t){let n=this.tensorMap.get(e);return this.releaseResource(e),n.values=t,n.values}readSync(e){let t=this.tensorMap.get(e),{values:n}=t;if(n==null)throw new Error("WebGPU readSync is only available for CPU-resident tensors.");return n}async read(e){if(!this.tensorMap.has(e))throw new Error(`Tensor ${e} was not registered!`);let t=this.tensorMap.get(e),{values:n}=t;if(n!=null)return this.convertAndCacheOnCPU(e,n);let s;if(t.dtype==="complex64"){let r=await Promise.all([this.read(t.complexTensorInfos.real.dataId),this.read(t.complexTensorInfos.imag.dataId)]),a=r[0],o=r[1];s=C.mergeRealAndImagArrays(a,o)}else{let r=t.resourceInfo,a=await this.getBufferData(r.buffer,r.size);s=XC(a,t.dtype)}return this.convertAndCacheOnCPU(e,s),s}readToGPU(e){let t=this.tensorMap.get(e),{values:n,dtype:s,shape:r,resourceInfo:a}=t;if(s==="complex64")throw new Error("Does not support reading buffer for complex64 dtype.");if(a==null)throw n!=null?new Error("Data is not on GPU but on CPU."):new Error("There is no data on GPU or CPU.");let o=a.size,i=this.bufferManager.acquireBuffer(o,a.usage);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(a.buffer,0,i,0,o),this.submitQueue();let l=this.makeTensorInfo(r,s),u=sn().makeTensorFromTensorInfo(l),c=this.tensorMap.get(l.dataId);return c.resourceInfo={size:o,usage:this.defaultGpuBufferUsage(),buffer:i},{tensorRef:u,buffer:i,bufSize:o}}bufferSync(e){let t=this.readSync(e.dataId);if(e.dtype==="string")try{let n=t.map(s=>v.decodeString(s));return Le(e.shape,e.dtype,n)}catch(n){throw new Error("Failed to decode encoded string bytes into utf-8")}return Le(e.shape,e.dtype,t)}async time(e){let t=this.activeTimers,n=[],s=!1;this.programTimersStack==null?(this.programTimersStack=n,s=!0):this.activeTimers.push(n),this.activeTimers=n,e();let r=v.flatten(this.activeTimers.map(l=>l.query)).filter(l=>l!=null),a=v.flatten(this.activeTimers.map(l=>l.name)).filter(l=>l!=null);this.activeTimers=t,s&&(this.programTimersStack=null);let o={uploadWaitMs:this.uploadWaitMs,downloadWaitMs:this.downloadWaitMs,kernelMs:null,wallMs:null},i=await Promise.all(r);return o.kernelMs=v.sum(i),o.getExtraProfileInfo=()=>i.map((l,u)=>({name:a[u],ms:l})).map(l=>`${l.name}: ${l.ms}`).join(", "),this.uploadWaitMs=0,this.downloadWaitMs=0,o}makeTensorInfo(e,t,n){return t==="string"&&n!=null&&n.length>0&&v.isString(n[0])&&(n=n.map(r=>v.encodeString(r))),{dataId:this.write(n,e,t),shape:e,dtype:t}}tensorToBinding(e){if(!e)return null;let t=this.tensorMap.get(e.dataId);if("texture"in t.resourceInfo){let s=t.resourceInfo;return s.texture instanceof GPUExternalTexture?s.texture:s.texture.createView()}let n=t.resourceInfo;return{offset:0,size:n.size,buffer:n.buffer}}async getQueryTime(e){return this.supportTimeQuery?this.getTimeFromQuerySet(e):0}uploadToGPU(e){let t=this.tensorMap.get(e);if(t.resourceInfo)return;let n=qC(t.dtype)*v.sizeFromShape(t.shape),s=this.bufferManager.acquireBuffer(n,this.defaultGpuBufferUsage());if(t.resourceInfo={size:n,usage:this.defaultGpuBufferUsage(),buffer:s},t.values){let r=this.bufferManager.acquireUploadBuffer(n,GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC),a=r.getMappedRange();t.dtype==="int32"||t.dtype==="bool"?new Int32Array(a).set(t.values):new Float32Array(a).set(t.values),r.unmap(),this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.copyBufferToBuffer(r,0,s,0,n);let o={size:n,usage:GPUBufferUsage.MAP_WRITE|GPUBufferUsage.COPY_SRC,buffer:r};this.stagingPendingDisposal.push(o)}}makeUniforms(e){let t=0,n=0,s=[];e.forEach(i=>{i.data.length===0&&(i.data=[1]);let l;switch(i.data.length){case 1:l=4;break;case 2:l=8;break;case 3:l=16;break;case 4:l=16;break;case 5:l=16;break;case 6:l=16;break;default:v.assert(!1,()=>`Unsupported ${i.data.length}D shape`)}(n===5||n===6)&&(l=16),t=Math.ceil(t/l)*l,n=i.data.length,s.push(t),t+=i.data.length*4});let r=new ArrayBuffer(t);e.forEach((i,l)=>{let u=s[l];i.type==="int32"?new Int32Array(r,u,i.data.length).set(i.data):i.type==="uint32"?new Uint32Array(r,u,i.data.length).set(i.data):new Float32Array(r,u,i.data.length).set(i.data)});let a=this.bufferManager.acquireBuffer(t,GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM);this.queue.writeBuffer(a,0,r,0,t);let o={size:t,usage:GPUBufferUsage.COPY_DST|GPUBufferUsage.UNIFORM,buffer:a};return this.uniformPendingDisposal.push(o),{offset:0,size:t,buffer:a}}runWebGPUProgram(e,t,n,s,r){if(r||(r=this.makeTensorInfo(e.outputShape,n)),v.sizeFromShape(r.shape)===0)return this.tensorMap.get(r.dataId).values=v.getTypedArrayFromDType(r.dtype,0),r;this.uploadToGPU(r.dataId),e.dispatch=Rye(this.device,e);let a=[],o=[];if(!e.isFromPixels){a.push({type:"float32",data:[NaN]}),o=t.concat(r).map(g=>g.shape);let f="int32";o.map(g=>{a.push({type:f,data:g})});let m=v.computeStrides(r.shape);if(a.push({type:f,data:m}),e.size){let g=v.sizeFromShape(e.outputShape);a.push({type:f,data:[e.isVec4?g/4:g]})}}let i=t.map((f,m)=>{if(f.dtype==="complex64")throw new Error("GPGPUProgram does not support complex64 input. For complex64 dtypes, please separate the program into real and imaginary parts.");return this.uploadToGPU(f.dataId),{dtype:this.tensorMap.get(f.dataId).dtype,shape:f.shape,name:e.variableNames[m]}}),l=N0e(e,o,i,r),u;l in this.pipelineCache?u=this.pipelineCache[l]:(u=C0e(this.device,e,i,r),this.pipelineCache[l]=u),s&&(a=[...a,...s]);let c=[this.tensorToBinding(r),...t.map(f=>this.tensorToBinding(f)),this.makeUniforms(a)],p=this.device.createBindGroup({layout:u.getBindGroupLayout(0),entries:c.map((f,m)=>({binding:m,resource:f}))});this.ensureCommandEncoderReady();let d=this.getComputePass(),h=this.activeTimers!=null;return h&&this.supportTimeQuery&&d.writeTimestamp(this.querySet,0),d.setPipeline(u),d.setBindGroup(0,p),d.dispatchWorkgroups(e.dispatch[0],e.dispatch[1],e.dispatch[2]),h&&this.supportTimeQuery&&d.writeTimestamp(this.querySet,1),this.dispatchNumberInEncoder++,t.forEach(f=>{this.commandQueueOwnedIds.add(f.dataId)}),this.commandQueueOwnedIds.add(r.dataId),X().get("WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE")<=this.dispatchNumberInEncoder&&this.submitQueue(),h&&this.activeTimers.push({name:e.constructor.name,query:this.getQueryTime(this.querySet)}),r}async getTimeFromQuerySet(e){let t=this.bufferManager.acquireBuffer(16,GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE),n=this.bufferManager.acquireBuffer(16,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST);this.ensureCommandEncoderReady(),this.ensureComputePassEnded(),this.currentCommandEncoder.resolveQuerySet(e,0,2,t,0),this.currentCommandEncoder.copyBufferToBuffer(t,0,n,0,16),this.submitQueue(),await n.mapAsync(GPUMapMode.READ);let s=new BigUint64Array(n.getMappedRange()),r=Number(s[1]-s[0]);return n.unmap(),this.bufferManager.releaseBuffer(n,16,GPUBufferUsage.MAP_READ|GPUBufferUsage.COPY_DST),this.bufferManager.releaseBuffer(t,16,GPUBufferUsage.COPY_SRC|GPUBufferUsage.QUERY_RESOLVE),r/1e6}shouldExecuteOnCPU(e,t=Eye){return X().getBool("WEBGPU_CPU_FORWARD")&&e.every(n=>this.tensorMap.get(n.dataId).resourceInfo==null&&v.sizeFromShape(n.shape)<t)}numDataIds(){return this.tensorMap.numDataIds()-this.tensorDataPendingDisposal.length}dispose(){this.disposed||(this.bufferManager.dispose(),this.textureManager.dispose(),this.disposed=!0)}};E2.nextDataId=0;var fT={};Ve(fT,{WebGPUBackend:()=>E2,webgpu_util:()=>HC});rb()&&jl("webgpu",async()=>{X().set("CHECK_COMPUTATION_FOR_ERRORS",!1);let e={powerPreference:X().get("WEBGPU_USE_LOW_POWER_GPU")?"low-power":"high-performance"},t=await navigator.gpu.requestAdapter(e),n=t.limits,s={},r=t.features.has("timestamp-query");s.requiredLimits={maxComputeWorkgroupStorageSize:n.maxComputeWorkgroupStorageSize,maxComputeWorkgroupsPerDimension:n.maxComputeWorkgroupsPerDimension,maxStorageBufferBindingSize:n.maxStorageBufferBindingSize},r?s.requiredFeatures=["timestamp-query"]:console.warn("This device doesn't support timestamp-query extension. Start Chrome browser with flag --disable-dawn-features=disallow_unsafe_apis then try again. Or zero will shown for the kernel time when profiling mode isenabled. Using performance.now is not workable for webgpu sinceit doesn't support synchronously to read data from GPU.");let a=await t.requestDevice(s);return new E2(a,r)},3);var _ye="3.19.0",Dye="3.19.0",$ye="3.19.0",Pye="3.19.0",Fye="3.19.0",Oye="3.19.0",Mye="3.19.0",Vh={tfjs:_ye,"tfjs-core":Dye,"tfjs-data":$ye,"tfjs-layers":Pye,"tfjs-converter":Fye,"tfjs-backend-webgl":Oye,"tfjs-backend-wasm":Mye};var mT=`
   precision highp float;
   attribute vec2 pos;
   attribute vec2 uv;
@@ -6918,7 +6918,7 @@ return a / b;`,Gie=`
     c31 * m[6] + c32 * m[7] + c33 * m[8];
     gl_FragColor.a = c22.a;
   }
-`;var ub=(e,t,n)=>{let s=new RegExp("\\b"+t+" \\w+ (\\w+)","ig");e.replace(s,(r,a)=>(n[a]=0,r))},cb=class{constructor(t,n,s){me(this,"uniform",{});me(this,"attribute",{});me(this,"gl");me(this,"id");me(this,"compile",(t,n)=>{let s=this.gl.createShader(n);return s?(this.gl.shaderSource(s,t),this.gl.compileShader(s),this.gl.getShaderParameter(s,this.gl.COMPILE_STATUS)?s:(ie(`filter: gl compile failed: ${this.gl.getShaderInfoLog(s)}`),null)):(ie("filter: could not create shader"),null)});this.gl=t;let r=this.compile(n,this.gl.VERTEX_SHADER),a=this.compile(s,this.gl.FRAGMENT_SHADER);if(this.id=this.gl.createProgram(),!(!r||!a)){if(!this.id){ie("filter: could not create webgl program");return}if(this.gl.attachShader(this.id,r),this.gl.attachShader(this.id,a),this.gl.linkProgram(this.id),!this.gl.getProgramParameter(this.id,this.gl.LINK_STATUS)){ie(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);return}this.gl.useProgram(this.id),ub(n,"attribute",this.attribute);for(let o in this.attribute)this.attribute[o]=this.gl.getAttribLocation(this.id,o);ub(n,"uniform",this.uniform),ub(s,"uniform",this.uniform);for(let o in this.uniform)this.uniform[o]=this.gl.getUniformLocation(this.id,o)}}};function vT(){let e=0,t=null,n=!1,s=-1,r=[null,null],a=[],o=null,i=null,l=is(100,100),u={},c={INTERMEDIATE:1},p=l.getContext("webgl");if(!p){ie("filter: cannot get webgl context");return}this.gl=p;function d(x,A){if(!(x===l.width&&A===l.height)){if(l.width=x,l.height=A,!o){let b=new Float32Array([-1,-1,0,1,1,-1,1,1,-1,1,0,0,-1,1,0,0,1,-1,1,1,1,1,1,0]);o=p.createBuffer(),p.bindBuffer(p.ARRAY_BUFFER,o),p.bufferData(p.ARRAY_BUFFER,b,p.STATIC_DRAW),p.pixelStorei(p.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}p.viewport(0,0,l.width,l.height),r=[null,null]}}function h(x,A){let b=p.createFramebuffer();p.bindFramebuffer(p.FRAMEBUFFER,b);let w=p.createRenderbuffer();p.bindRenderbuffer(p.RENDERBUFFER,w);let k=p.createTexture();return p.bindTexture(p.TEXTURE_2D,k),p.texImage2D(p.TEXTURE_2D,0,p.RGBA,x,A,0,p.RGBA,p.UNSIGNED_BYTE,null),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_MAG_FILTER,p.LINEAR),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_MIN_FILTER,p.LINEAR),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_WRAP_S,p.CLAMP_TO_EDGE),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_WRAP_T,p.CLAMP_TO_EDGE),p.framebufferTexture2D(p.FRAMEBUFFER,p.COLOR_ATTACHMENT0,p.TEXTURE_2D,k,0),p.bindTexture(p.TEXTURE_2D,null),p.bindFramebuffer(p.FRAMEBUFFER,null),{fbo:b,texture:k}}function f(x){return r[x]=r[x]||h(l.width,l.height),r[x]}function m(x=0){if(!i)return;let A=null,b=null,w=!1;e===0?A=t:A=f(s).texture||null,e++,n&&!(x&c.INTERMEDIATE)?(b=null,w=e%2===0):(s=(s+1)%2,b=f(s).fbo||null),p.bindTexture(p.TEXTURE_2D,A),p.bindFramebuffer(p.FRAMEBUFFER,b),p.uniform1f(i.uniform.flipY,w?-1:1),p.drawArrays(p.TRIANGLES,0,6)}function g(x){if(u[x])return i=u[x],p.useProgram((i?i.id:null)||null),i;if(i=new cb(p,mT,x),!i)return ie("filter: could not get webgl program"),null;let A=Float32Array.BYTES_PER_ELEMENT,b=4*A;return p.enableVertexAttribArray(i.attribute.pos),p.vertexAttribPointer(i.attribute.pos,2,p.FLOAT,!1,b,0*A),p.enableVertexAttribArray(i.attribute.uv),p.vertexAttribPointer(i.attribute.uv,2,p.FLOAT,!1,b,2*A),u[x]=i,i}let y={colorMatrix:x=>{let A=new Float32Array(x);A[4]/=255,A[9]/=255,A[14]/=255,A[19]/=255;let b=A[18]===1&&A[3]===0&&A[8]===0&&A[13]===0&&A[15]===0&&A[16]===0&&A[17]===0&&A[19]===0?yT:gT,w=g(b);!w||(p.uniform1fv(w.uniform.m,A),m())},brightness:x=>{let A=(x||0)+1;y.colorMatrix([A,0,0,0,0,0,A,0,0,0,0,0,A,0,0,0,0,0,1,0])},saturation:x=>{let A=(x||0)*2/3+1,b=(A-1)*-.5;y.colorMatrix([A,b,b,0,0,b,A,b,0,0,b,b,A,0,0,0,0,0,1,0])},desaturate:()=>{y.saturation(-1)},contrast:x=>{let A=(x||0)+1,b=-128*(A-1);y.colorMatrix([A,0,0,0,b,0,A,0,0,b,0,0,A,0,b,0,0,0,1,0])},negative:()=>{y.contrast(-2)},hue:x=>{x=(x||0)/180*Math.PI;let A=Math.cos(x),b=Math.sin(x),w=.213,k=.715,S=.072;y.colorMatrix([w+A*(1-w)+b*-w,k+A*-k+b*-k,S+A*-S+b*(1-S),0,0,w+A*-w+b*.143,k+A*(1-k)+b*.14,S+A*-S+b*-.283,0,0,w+A*-w+b*-(1-w),k+A*-k+b*k,S+A*(1-S)+b*S,0,0,0,0,0,1,0])},desaturateLuminance:()=>{y.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},sepia:()=>{y.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},brownie:()=>{y.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},vintagePinhole:()=>{y.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},kodachrome:()=>{y.colorMatrix([1.1285582396593525,-.3967382283601348,-.03992559172921793,0,63.72958762196502,-.16404339962244616,1.0835251566291304,-.05498805115633132,0,24.732407896706203,-.16786010706155763,-.5603416277695248,1.6014850761964943,0,35.62982807460946,0,0,0,1,0])},technicolor:()=>{y.colorMatrix([1.9125277891456083,-.8545344976951645,-.09155508482755585,0,11.793603434377337,-.3087833385928097,1.7658908555458428,-.10601743074722245,0,-70.35205161461398,-.231103377548616,-.7501899197440212,1.847597816108189,0,30.950940869491138,0,0,0,1,0])},polaroid:()=>{y.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},shiftToBGR:()=>{y.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},convolution:x=>{let A=new Float32Array(x),b=1/l.width,w=1/l.height,k=g(bT);!k||(p.uniform1fv(k.uniform.m,A),p.uniform2f(k.uniform.px,b,w),m())},detectEdges:()=>{y.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},sobelX:()=>{y.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},sobelY:()=>{y.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},sharpen:x=>{let A=x||1;y.convolution.call(this,[0,-1*A,0,-1*A,1+4*A,-1*A,0,-1*A,0])},emboss:x=>{let A=x||1;y.convolution.call(this,[-2*A,-1*A,0,-1*A,1,1*A,0,1*A,2*A])},blur:x=>{let A=x/7/l.width,b=x/7/l.height,w=g(xT);!w||(p.uniform2f(w.uniform.px,0,b),m(c.INTERMEDIATE),p.uniform2f(w.uniform.px,A,0),m())},pixelate:x=>{let A=x/l.width,b=x/l.height,w=g(AT);!w||(p.uniform2f(w.uniform.size,A,b),m())}};this.add=function(x){let A=Array.prototype.slice.call(arguments,1),b=y[x];a.push({func:b,args:A})},this.reset=function(){a=[]},this.get=function(){return a},this.apply=function(x){d(x.width,x.height),e=0,t||(t=p.createTexture()),p.bindTexture(p.TEXTURE_2D,t),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_WRAP_S,p.CLAMP_TO_EDGE),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_WRAP_T,p.CLAMP_TO_EDGE),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_MIN_FILTER,p.NEAREST),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_MAG_FILTER,p.NEAREST),p.texImage2D(p.TEXTURE_2D,0,p.RGBA,p.RGBA,p.UNSIGNED_BYTE,x);for(let A=0;A<a.length;A++){n=A===a.length-1;let b=a[A];b.func.apply(this,b.args||[])}return l},this.draw=function(x){return this.add("brightness",0),this.apply(x)}}async function _2(e){let t=e.shape.length===4?rt(e):e,n=Zt(t,3,2),s=[ga(n[0]),ga(n[1]),ga(n[2])],r=[mn(n[0]),mn(n[1]),mn(n[2])],a=await Promise.all(r.map(h=>h.data())),o=.99*Math.max(a[0][0],a[1][0],a[2][0]),i=[he(n[0],s[0]),he(n[1],s[1]),he(n[2],s[2])],l=[he(r[0],s[0]),he(r[1],s[1]),he(r[2],s[2])],u=[pe(o,l[0]),pe(o,l[1]),pe(o,l[2])],c=[L(i[0],u[0]),L(i[1],u[1]),L(i[2],u[2])],p=on([c[0],c[1],c[2]],2),d=U(p,[1,t.shape[0],t.shape[1],3]);return ne([...n,...s,...r,...i,...l,...u,...c,p,t]),d}var D2=3840,mt=null,cn=null,md=null,$t,Ta={inputSum:0,cacheDiff:1,sumMethod:0,inputTensor:void 0};function is(e,t){let n;if(fe.browser)if(fe.worker){if(typeof OffscreenCanvas=="undefined")throw new Error("canvas error: attempted to run in web worker but OffscreenCanvas is not supported");n=new OffscreenCanvas(e,t)}else{if(typeof document=="undefined")throw new Error("canvas error: attempted to run in browser but DOM is not defined");n=document.createElement("canvas"),n.width=e,n.height=t}else typeof fe.Canvas!="undefined"?n=new fe.Canvas(e,t):typeof globalThis.Canvas!="undefined"&&(n=new globalThis.Canvas(e,t));return n}function $2(e,t){let n=t||is(e.width,e.height);return n.getContext("2d").drawImage(e,0,0),n}async function gd(e,t,n=!0){if(!e)return t.debug&&ie("input error: input is missing"),{tensor:null,canvas:null};if(!(e instanceof tt)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(typeof fe.Canvas!="undefined"&&e instanceof fe.Canvas)&&!(typeof globalThis.Canvas!="undefined"&&e instanceof globalThis.Canvas)&&!(typeof ImageData!="undefined"&&e instanceof ImageData)&&!(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)&&!(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)&&!(typeof HTMLMediaElement!="undefined"&&e instanceof HTMLMediaElement)&&!(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)&&!(typeof HTMLCanvasElement!="undefined"&&e instanceof HTMLCanvasElement)&&!(typeof OffscreenCanvas!="undefined"&&e instanceof OffscreenCanvas))throw new Error("input error: type is not recognized");if(e instanceof tt){let s=null;if(e.isDisposedInternal)throw new Error("input error: attempted to use tensor but it is disposed");if(!e.shape)throw new Error("input error: attempted to use tensor without a shape");if(e.shape.length===3){if(e.shape[2]===3)s=Kt(e,0);else if(e.shape[2]===4){let r=ci(e,[0,0,0],[-1,-1,3]);s=Kt(r,0),ne(r)}}else e.shape.length===4&&(e.shape[3]===3?s=Fn(e):e.shape[3]===4&&(s=no(e,[0,0,0,0],[-1,-1,-1,3])));if(s==null||s.shape.length!==4||s.shape[0]!==1||s.shape[3]!==3)throw new Error(`input error: attempted to use tensor with unrecognized shape: ${e.shape}`);if(s.dtype==="int32"){let r=ge(s,"float32");ne(s),s=r}return{tensor:s,canvas:t.filter.return?cn:null}}else{if(typeof e.readyState!="undefined"&&e.readyState<=2)return t.debug&&ie("input stream is not ready"),{tensor:null,canvas:mt};let s=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,r=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0;if(!s||!r)return t.debug&&ie("cannot determine input dimensions"),{tensor:null,canvas:mt};let a=s,o=r;if(a>D2&&(a=D2,o=Math.trunc(a*r/s)),o>D2&&(o=D2,a=Math.trunc(o*s/r)),(t.filter.width||0)>0?a=t.filter.width:(t.filter.height||0)>0&&(a=s*((t.filter.height||0)/r)),(t.filter.height||0)>0?o=t.filter.height:(t.filter.width||0)>0&&(o=r*((t.filter.width||0)/s)),!a||!o)throw new Error("input error: cannot determine dimension");(!mt||(mt==null?void 0:mt.width)!==a||(mt==null?void 0:mt.height)!==o)&&(mt=is(a,o));let i=mt.getContext("2d");if(typeof ImageData!="undefined"&&e instanceof ImageData?i.putImageData(e,0,0):t.filter.flip&&typeof i.translate!="undefined"?(i.translate(s,0),i.scale(-1,1),i.drawImage(e,0,0,s,r,0,0,mt==null?void 0:mt.width,mt==null?void 0:mt.height),i.setTransform(1,0,0,1,0,0)):i.drawImage(e,0,0,s,r,0,0,mt==null?void 0:mt.width,mt==null?void 0:mt.height),(!cn||mt.width!==cn.width||(mt==null?void 0:mt.height)!==(cn==null?void 0:cn.height))&&(cn=is(mt.width,mt.height)),t.filter.enabled&&fe.webgl.supported?($t||($t=fe.browser?new vT:null),fe.filter=!!$t,!$t||!$t.add?(t.debug&&ie("input process error: cannot initialize filters"),fe.webgl.supported=!1,t.filter.enabled=!1,$2(mt,cn)):($t.reset(),t.filter.brightness!==0&&$t.add("brightness",t.filter.brightness),t.filter.contrast!==0&&$t.add("contrast",t.filter.contrast),t.filter.sharpness!==0&&$t.add("sharpen",t.filter.sharpness),t.filter.blur!==0&&$t.add("blur",t.filter.blur),t.filter.saturation!==0&&$t.add("saturation",t.filter.saturation),t.filter.hue!==0&&$t.add("hue",t.filter.hue),t.filter.negative&&$t.add("negative"),t.filter.sepia&&$t.add("sepia"),t.filter.vintage&&$t.add("brownie"),t.filter.sepia&&$t.add("sepia"),t.filter.kodachrome&&$t.add("kodachrome"),t.filter.technicolor&&$t.add("technicolor"),t.filter.polaroid&&$t.add("polaroid"),t.filter.pixelate!==0&&$t.add("pixelate",t.filter.pixelate),$t.get()>0?cn=$t.apply(mt):cn=$t.draw(mt))):($2(mt,cn),$t&&($t=null),fe.filter=!!$t),!n)return{tensor:null,canvas:cn};if(!cn)throw new Error("canvas error: cannot create output");let l,u=3;if(typeof ImageData!="undefined"&&e instanceof ImageData||e.data&&e.width&&e.height)if(fe.browser&&Ys)l=Ys?Ys.fromPixels(e):null;else{u=e.data.length/e.height/e.width;let d=new Uint8Array(e.data.buffer);l=ft(d,[e.height,e.width,u],"int32")}else if((!md||cn.width!==md.width||cn.height!==md.height)&&(md=is(cn.width,cn.height)),Ys&&fe.browser)t.backend==="webgl"||t.backend==="humangl"||t.backend==="webgpu"?l=Ys.fromPixels(cn):(md=$2(cn),l=Ys.fromPixels(md));else{let f=$2(cn).getContext("2d").getImageData(0,0,a,o);u=f.data.length/a/o;let m=new Uint8Array(f.data.buffer);l=ft(m,[a,o,u])}if(u===4){let d=ci(l,[0,0,0],[-1,-1,3]);ne(l),l=d}if(!l)throw new Error("input error: cannot create tensor");let c=ge(l,"float32"),p=t.filter.equalization?await _2(c):Kt(c,0);return ne([l,c]),{tensor:p,canvas:t.filter.return?cn:null}}}async function wT(e,t){let n=!1;if(e.cacheSensitivity===0||!t.shape||t.shape.length!==4||t.shape[1]>2048||t.shape[2]>2048)return n;if(!Ta.inputTensor)Ta.inputTensor=Fn(t);else if(Ta.inputTensor.shape[1]!==t.shape[1]||Ta.inputTensor.shape[2]!==t.shape[2])ne(Ta.inputTensor),Ta.inputTensor=Fn(t);else{let s={};s.diff=he(t,Ta.inputTensor),s.squared=L(s.diff,s.diff),s.sum=ke(s.squared);let a=(await s.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;ne([Ta.inputTensor,s.diff,s.squared,s.sum]),Ta.inputTensor=Fn(t),n=a<=(e.cacheSensitivity||0)}return n}async function kT(e,t,n){let s={};if(!t||!n||t.shape.length!==4||t.shape.length!==n.shape.length)return e.debug||ie("invalid input tensor or tensor shapes do not match:",t.shape,n.shape),0;if(t.shape[0]!==1||n.shape[0]!==1||t.shape[3]!==3||n.shape[3]!==3)return e.debug||ie("input tensors must be of shape [1, height, width, 3]:",t.shape,n.shape),0;s.input1=Fn(t),s.input2=t.shape[1]!==n.shape[1]||t.shape[2]!==n.shape[2]?Ne.resizeBilinear(n,[t.shape[1],t.shape[2]]):Fn(n),s.diff=he(s.input1,s.input2),s.squared=L(s.diff,s.diff),s.sum=ke(s.squared);let a=(await s.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;return ne([s.input1,s.input2,s.diff,s.squared,s.sum]),a}var db=class{constructor(){me(this,"browser");me(this,"node");me(this,"worker");me(this,"platform","");me(this,"agent","");me(this,"backends",[]);me(this,"initial");me(this,"filter");me(this,"tfjs");me(this,"offscreen");me(this,"perfadd",!1);me(this,"wasm",{supported:void 0,backend:void 0,simd:void 0,multithread:void 0});me(this,"webgl",{supported:void 0,backend:void 0,version:void 0,renderer:void 0});me(this,"webgpu",{supported:void 0,backend:void 0,adapter:void 0});me(this,"cpu",{model:void 0,flags:[]});me(this,"kernels",[]);me(this,"Canvas");me(this,"Image");me(this,"ImageData");if(this.browser=typeof navigator!="undefined",this.node=typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined",this.tfjs={version:Uh["tfjs-core"]},this.offscreen=typeof OffscreenCanvas!="undefined",this.initial=!0,this.worker=this.browser&&this.offscreen?typeof WorkerGlobalScope!="undefined":void 0,typeof navigator!="undefined"){let t=navigator.userAgent.match(/\(([^()]+)\)/g);if(t&&t[0]){let n=t[0].match(/\(([^()]+)\)/g);this.platform=n&&n[0]?n[0].replace(/\(|\)/g,""):"",this.agent=navigator.userAgent.replace(t[0],""),this.platform[1]&&(this.agent=this.agent.replace(t[1],"")),this.agent=this.agent.replace(/  /g," ")}}else typeof process!="undefined"&&(this.platform=`${process.platform} ${process.arch}`,this.agent=`NodeJS ${process.version}`)}async updateBackend(){this.backends=Object.keys(sn().registryFactory),this.wasm.supported=typeof WebAssembly!="undefined",this.wasm.backend=this.backends.includes("wasm"),this.wasm.supported&&this.wasm.backend&&ss()==="wasm"&&(this.wasm.simd=await Z().getAsync("WASM_HAS_SIMD_SUPPORT"),this.wasm.multithread=await Z().getAsync("WASM_HAS_MULTITHREAD_SUPPORT"));let t=is(100,100),n=t?t.getContext("webgl2"):void 0;if(this.webgl.supported=typeof n!="undefined",this.webgl.backend=this.backends.includes("webgl"),this.webgl.supported&&this.webgl.backend&&(ss()==="webgl"||ss()==="humangl")){let s=Zs().gpgpu!=="undefined"?await Zs().getGPGPUContext().gl:null;s&&(this.webgl.version=s.getParameter(s.VERSION),this.webgl.renderer=s.getParameter(s.RENDERER))}this.webgpu.supported=this.browser&&typeof navigator.gpu!="undefined",this.webgpu.backend=this.backends.includes("webgpu");try{this.webgpu.supported&&(this.webgpu.adapter=(await navigator.gpu.requestAdapter()).name)}catch(s){this.webgpu.supported=!1}try{this.kernels=qr(ss()).map(s=>s.kernelName.toLowerCase())}catch(s){}}async updateCPU(){let t={model:"",flags:[]};this.node&&this.platform.startsWith("linux"),this.cpu?this.cpu=t:Object.defineProperty(this,"cpu",{value:t})}},fe=new db;var pb={};ia(pb,{age:()=>Wye,antispoof:()=>Vye,blazeface:()=>Hye,"blazeface-back":()=>Uye,"blazeface-front":()=>Gye,"blazepose-detector2d":()=>jye,"blazepose-detector3d":()=>qye,"blazepose-full":()=>Xye,"blazepose-heavy":()=>Kye,"blazepose-lite":()=>Zye,default:()=>EAe,efficientpose:()=>Yye,emotion:()=>Jye,faceboxes:()=>Qye,facemesh:()=>aAe,"facemesh-attention":()=>tAe,"facemesh-attention-alt":()=>eAe,"facemesh-detection-full":()=>nAe,"facemesh-detection-short":()=>sAe,"facemesh-orig":()=>rAe,faceres:()=>iAe,"faceres-deep":()=>oAe,gear:()=>lAe,gender:()=>cAe,"gender-ssrnet-imdb":()=>uAe,handdetect:()=>dAe,"handlandmark-full":()=>pAe,"handlandmark-lite":()=>hAe,"handlandmark-sparse":()=>fAe,handskeleton:()=>mAe,handtrack:()=>gAe,iris:()=>yAe,liveness:()=>AAe,"mb3-centernet":()=>xAe,meet:()=>bAe,mobileface:()=>vAe,mobilefacenet:()=>wAe,"movenet-lightning":()=>kAe,"movenet-multipose":()=>IAe,"movenet-thunder":()=>SAe,nanodet:()=>CAe,posenet:()=>TAe,selfie:()=>NAe});var Wye=161240,Vye=853098,Uye=538928,Gye=402048,Hye=538928,jye=7499400,qye=5928856,Xye=6338290,Kye=27501554,Zye=2725490,Yye=5651240,Jye=820516,Qye=2013002,eAe=2387598,tAe=2382414,nAe=1026192,sAe=201268,rAe=2955780,aAe=1477958,oAe=13957620,iAe=6978814,lAe=1498916,uAe=161236,cAe=201808,dAe=3515612,pAe=5431368,hAe=2023432,fAe=5286322,mAe=5502280,gAe=2964837,yAe=2599092,AAe=592976,xAe=4030290,bAe=372228,vAe=2183192,wAe=5171976,kAe=4650216,IAe=9448838,SAe=12477112,CAe=7574558,TAe=5032780,NAe=212886,EAe={age:Wye,antispoof:Vye,"blazeface-back":Uye,"blazeface-front":Gye,blazeface:Hye,"blazepose-detector2d":jye,"blazepose-detector3d":qye,"blazepose-full":Xye,"blazepose-heavy":Kye,"blazepose-lite":Zye,efficientpose:Yye,emotion:Jye,faceboxes:Qye,"facemesh-attention-alt":eAe,"facemesh-attention":tAe,"facemesh-detection-full":nAe,"facemesh-detection-short":sAe,"facemesh-orig":rAe,facemesh:aAe,"faceres-deep":oAe,faceres:iAe,gear:lAe,"gender-ssrnet-imdb":uAe,gender:cAe,handdetect:dAe,"handlandmark-full":pAe,"handlandmark-lite":hAe,"handlandmark-sparse":fAe,handskeleton:mAe,handtrack:gAe,iris:yAe,liveness:AAe,"mb3-centernet":xAe,meet:bAe,mobileface:vAe,mobilefacenet:wAe,"movenet-lightning":kAe,"movenet-multipose":IAe,"movenet-thunder":SAe,nanodet:CAe,posenet:TAe,selfie:NAe};var ls={cacheModels:!0,cacheSupported:!0,verbose:!0,debug:!1,modelBasePath:""},Or={};async function RAe(e,t){return ls.debug&&ie("load model fetch:",e,t),fetch(e,t)}function IT(e){ls.cacheModels=e.cacheModels,ls.verbose=e.debug,ls.modelBasePath=e.modelBasePath}async function qe(e){var u,c,p;let t=uv(ls.modelBasePath,e||"");t.toLowerCase().endsWith(".json")||(t+=".json");let n=t.includes("/")?t.split("/"):t.split("\\"),s=n[n.length-1].replace(".json",""),r="indexeddb://"+s;Or[s]={name:s,sizeFromManifest:0,sizeLoadedWeights:0,sizeDesired:pb[s],inCache:!1},ls.cacheSupported=typeof window!="undefined"&&typeof window.localStorage!="undefined"&&typeof window.indexedDB!="undefined";let a={};try{a=ls.cacheSupported&&ls.cacheModels?await Ts.listModels():{}}catch(d){ls.cacheSupported=!1}Or[s].inCache=ls.cacheSupported&&ls.cacheModels&&Object.keys(a).includes(r);let o=typeof fetch=="undefined"?{}:{fetchFunc:(d,h)=>RAe(d,h)},i=new $h(Or[s].inCache?r:t,o),l=!1;try{i.findIOHandler(),ls.debug&&ie("model load handler:",i.handler);let d=await i.handler.load();Or[s].sizeFromManifest=((u=d==null?void 0:d.weightData)==null?void 0:u.byteLength)||0,i.loadSync(d),Or[s].sizeLoadedWeights=((p=(c=i==null?void 0:i.artifacts)==null?void 0:c.weightData)==null?void 0:p.byteLength)||0,ls.verbose&&ie("load model:",i.modelUrl,{bytes:Or[s].sizeLoadedWeights},ls),l=!0}catch(d){ie("error loading model:",t,d)}if(l&&ls.cacheModels&&ls.cacheSupported&&!Or[s].inCache)try{let d=await i.save(r);ie("model saved:",r,d)}catch(d){ie("error saving model:",t,d)}return i}var hb="2.9.1";var m1={};ia(m1,{Models:()=>Qh,getModelStats:()=>I4,load:()=>S4,reset:()=>f1,validate:()=>C4});var fr,fb=[],$Ae=["white","black","asian","indian","other"],PAe=[15,23,28,35.5,45.5,55.5,65],ST=0,CT=0,mb=Number.MAX_SAFE_INTEGER;async function TT(e){var t;return fe.initial&&(fr=null),fr?e.debug&&ie("cached model:",fr.modelUrl):fr=await qe((t=e.face.gear)==null?void 0:t.modelPath),fr}async function gb(e,t,n,s){var o,i;if(!fr)return{age:0,gender:"unknown",genderScore:0,race:[]};let r=mb<(((o=t.face.gear)==null?void 0:o.skipFrames)||0),a=(((i=t.face.gear)==null?void 0:i.skipTime)||0)>ue()-CT;return t.skipAllowed&&a&&r&&ST===s&&fb[n]?(mb++,fb[n]):(mb=0,new Promise(async l=>{var y,x;if(!(fr!=null&&fr.inputs[0].shape))return;let u={},c=[[0,.1,.9,.9]];u.resize=Ne.cropAndResize(e,c,[0],[fr.inputs[0].shape[2],fr.inputs[0].shape[1]]);let p={age:0,gender:"unknown",genderScore:0,race:[]};(y=t.face.gear)!=null&&y.enabled&&([u.age,u.gender,u.race]=fr.execute(u.resize,["age_output","gender_output","race_output"]));let d=await u.gender.data();p.gender=d[0]>d[1]?"male":"female",p.genderScore=Math.round(100*(d[0]>d[1]?d[0]:d[1]))/100;let h=await u.race.data();for(let A=0;A<h.length;A++)h[A]>(((x=t.face.gear)==null?void 0:x.minConfidence)||.2)&&p.race.push({score:Math.round(100*h[A])/100,race:$Ae[A]});p.race.sort((A,b)=>b.score-A.score);let m=Array.from(await u.age.data()).map((A,b)=>[PAe[b],A]).sort((A,b)=>b[1]-A[1]),g=m[0][0];for(let A=1;A<m.length;A++)g+=m[A][1]*(m[A][0]-g);p.age=Math.round(10*g)/10,Object.keys(u).forEach(A=>ne(u[A])),fb[n]=p,ST=s,CT=ue(),l(p)}))}var nt={tf255:255,tf1:1,tf2:2,tf05:.5,tf127:127.5,rgb:[.2989,.587,.114]};function ET(){nt.tf255=Se(255,"float32"),nt.tf1=Se(1,"float32"),nt.tf2=Se(2,"float32"),nt.tf05=Se(.5,"float32"),nt.tf127=Se(127.5,"float32"),nt.rgb=Ft([.2989,.587,.114],"float32")}var Os,P2=[],RT=0,_T=0,yb=Number.MAX_SAFE_INTEGER;async function DT(e){return fe.initial&&(Os=null),Os?e.debug&&ie("cached model:",Os.modelUrl):Os=await qe(e.face.ssrnet.modelPathAge),Os}async function Ab(e,t,n,s){var o,i,l,u;if(!Os)return{age:0};let r=yb<(((o=t.face.ssrnet)==null?void 0:o.skipFrames)||0),a=(((i=t.face.ssrnet)==null?void 0:i.skipTime)||0)>ue()-_T;return t.skipAllowed&&r&&a&&RT===s&&((l=P2[n])==null?void 0:l.age)&&((u=P2[n])==null?void 0:u.age)>0?(yb++,P2[n]):(yb=0,new Promise(async c=>{if(!(Os!=null&&Os.inputs)||!Os.inputs[0]||!Os.inputs[0].shape)return;let p={};p.resize=Ne.resizeBilinear(e,[Os.inputs[0].shape[2],Os.inputs[0].shape[1]],!1),p.enhance=L(p.resize,nt.tf255);let d={age:0};if(t.face.ssrnet.enabled&&(p.age=Os.execute(p.enhance)),p.age){let h=await p.age.data();d.age=Math.trunc(10*h[0])/10}Object.keys(p).forEach(h=>ne(p[h])),P2[n]=d,RT=s,_T=ue(),c(d)}))}var mr,F2=[],PT=0,FT=0,xb=Number.MAX_SAFE_INTEGER,bb=[.2989,.587,.114];async function OT(e){return fe.initial&&(mr=null),mr?e.debug&&ie("cached model:",mr.modelUrl):mr=await qe(e.face.ssrnet.modelPathGender),mr}async function vb(e,t,n,s){var o,i,l,u;if(!mr)return{gender:"unknown",genderScore:0};let r=xb<(((o=t.face.ssrnet)==null?void 0:o.skipFrames)||0),a=(((i=t.face.ssrnet)==null?void 0:i.skipTime)||0)>ue()-FT;return t.skipAllowed&&r&&a&&PT===s&&((l=F2[n])==null?void 0:l.gender)&&((u=F2[n])==null?void 0:u.genderScore)>0?(xb++,F2[n]):(xb=0,new Promise(async c=>{if(!(mr!=null&&mr.inputs[0].shape))return;let p={};p.resize=Ne.resizeBilinear(e,[mr.inputs[0].shape[2],mr.inputs[0].shape[1]],!1),p.enhance=J(()=>{let[f,m,g]=Zt(p.resize,3,3),y=L(f,bb[0]),x=L(m,bb[1]),A=L(g,bb[2]),b=m0([y,x,A]);return L(he(b,nt.tf05),2)});let d={gender:"unknown",genderScore:0};t.face.ssrnet.enabled&&(p.gender=mr.execute(p.enhance));let h=await p.gender.data();d.gender=h[0]>h[1]?"female":"male",d.genderScore=h[0]>h[1]?Math.trunc(100*h[0])/100:Math.trunc(100*h[1])/100,Object.keys(p).forEach(f=>ne(p[f])),F2[n]=d,PT=s,FT=ue(),c(d)}))}var zn,O2=[],wb=Number.MAX_SAFE_INTEGER,zT=0,LT=0;async function BT(e){var t;return fe.initial&&(zn=null),zn?e.debug&&ie("cached model:",zn.modelUrl):zn=await qe((t=e.face.antispoof)==null?void 0:t.modelPath),zn}async function kb(e,t,n,s){var o,i;if(!zn)return 0;let r=(((o=t.face.antispoof)==null?void 0:o.skipTime)||0)>ue()-LT,a=wb<(((i=t.face.antispoof)==null?void 0:i.skipFrames)||0);return t.skipAllowed&&r&&a&&zT===s&&O2[n]?(wb++,O2[n]):(wb=0,new Promise(async l=>{let u=Ne.resizeBilinear(e,[zn!=null&&zn.inputs[0].shape?zn.inputs[0].shape[2]:0,zn!=null&&zn.inputs[0].shape?zn.inputs[0].shape[1]:0],!1),c=zn==null?void 0:zn.execute(u),p=(await c.data())[0];O2[n]=Math.round(100*p)/100,zT=s,LT=ue(),ne([u,c]),l(O2[n])}))}var gr={silhouette:[10,338,297,332,284,251,389,356,454,323,361,288,397,365,379,378,400,377,152,148,176,149,150,136,172,58,132,93,234,127,162,21,54,103,67,109],lipsUpperOuter:[185,40,39,37,0,267,269,270,409],lipsLowerOuter:[61,146,91,181,84,17,314,405,321,375,291],lipsUpperInner:[191,80,81,82,13,312,311,310,415],lipsLowerInner:[78,95,88,178,87,14,317,402,318,324,308],lipsLowerSemiOuter:[76,77,90,180,85,16,315,404,320,307,306],lipsUpperSemiOuter:[184,74,73,72,11,302,303,304,408],lipsLowerSemiInner:[62,96,89,179,86,15,316,403,319,325,292],lipsUpperSemiInner:[183,42,41,38,12,268,271,272,407],rightEyeUpper0:[246,161,160,159,158,157,173],rightEyeLower0:[33,7,163,144,145,153,154,155,133],rightEyeUpper1:[247,30,29,27,28,56,190],rightEyeLower1:[130,25,110,24,23,22,26,112,243],rightEyeUpper2:[113,225,224,223,222,221,189],rightEyeLower2:[226,31,228,229,230,231,232,233,244],rightEyeLower3:[143,111,117,118,119,120,121,128,245],rightEyebrowUpper:[156,70,63,105,66,107,55,193],rightEyebrowLower:[35,124,46,53,52,65],rightEyeIris:[473,474,475,476,477],leftEyeUpper0:[466,388,387,386,385,384,398],leftEyeLower0:[263,249,390,373,374,380,381,382,362],leftEyeUpper1:[467,260,259,257,258,286,414],leftEyeLower1:[359,255,339,254,253,252,256,341,463],leftEyeUpper2:[342,445,444,443,442,441,413],leftEyeLower2:[446,261,448,449,450,451,452,453,464],leftEyeLower3:[372,340,346,347,348,349,350,357,465],leftEyebrowUpper:[383,300,293,334,296,336,285,417],leftEyebrowLower:[265,353,276,283,282,295],leftEyeIris:[468,469,470,471,472],midwayBetweenEyes:[168],noseTip:[1],noseBottom:[2],noseRightCorner:[98],noseLeftCorner:[327],rightCheek:[205],leftCheek:[425]},Ib={count:468,mouth:13,symmetryLine:[13,gr.midwayBetweenEyes[0]]},iu={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Sb=[{key:"EyeUpper0",indices:[9,10,11,12,13,14,15]},{key:"EyeUpper1",indices:[25,26,27,28,29,30,31]},{key:"EyeUpper2",indices:[41,42,43,44,45,46,47]},{key:"EyeLower0",indices:[0,1,2,3,4,5,6,7,8]},{key:"EyeLower1",indices:[16,17,18,19,20,21,22,23,24]},{key:"EyeLower2",indices:[32,33,34,35,36,37,38,39,40]},{key:"EyeLower3",indices:[54,55,56,57,58,59,60,61,62]},{key:"EyebrowUpper",indices:[63,64,65,66,67,68,69,70]},{key:"EyebrowLower",indices:[48,49,50,51,52,53]}],Hh=[[.499976992607117,.652534008026123],[.500025987625122,.547487020492554],[.499974012374878,.602371990680695],[.482113003730774,.471979022026062],[.500150978565216,.527155995368958],[.499909996986389,.498252987861633],[.499523013830185,.40106201171875],[.289712011814117,.380764007568359],[.499954998493195,.312398016452789],[.499987006187439,.269918978214264],[.500023007392883,.107050001621246],[.500023007392883,.666234016418457],[.5000159740448,.679224014282227],[.500023007392883,.692348003387451],[.499976992607117,.695277988910675],[.499976992607117,.70593398809433],[.499976992607117,.719385027885437],[.499976992607117,.737019002437592],[.499967992305756,.781370997428894],[.499816000461578,.562981009483337],[.473773002624512,.573909997940063],[.104906998574734,.254140973091125],[.365929991006851,.409575998783112],[.338757991790771,.41302502155304],[.311120003461838,.409460008144379],[.274657994508743,.389131009578705],[.393361985683441,.403706014156342],[.345234006643295,.344011008739471],[.370094001293182,.346076011657715],[.319321990013123,.347265005111694],[.297903001308441,.353591024875641],[.24779200553894,.410809993743896],[.396889001131058,.842755019664764],[.280097991228104,.375599980354309],[.106310002505779,.399955987930298],[.2099249958992,.391353011131287],[.355807989835739,.534406006336212],[.471751004457474,.65040397644043],[.474155008792877,.680191993713379],[.439785003662109,.657229006290436],[.414617002010345,.66654098033905],[.450374007225037,.680860996246338],[.428770989179611,.682690978050232],[.374971002340317,.727805018424988],[.486716985702515,.547628998756409],[.485300987958908,.527395009994507],[.257764995098114,.314490020275116],[.401223003864288,.455172002315521],[.429818987846375,.548614978790283],[.421351999044418,.533740997314453],[.276895999908447,.532056987285614],[.483370006084442,.499586999416351],[.33721199631691,.282882988452911],[.296391993761063,.293242990970612],[.169294998049736,.193813979625702],[.447580009698868,.302609980106354],[.392390012741089,.353887975215912],[.354490011930466,.696784019470215],[.067304998636246,.730105042457581],[.442739009857178,.572826027870178],[.457098007202148,.584792017936707],[.381974011659622,.694710969924927],[.392388999462128,.694203019142151],[.277076005935669,.271932005882263],[.422551989555359,.563233017921448],[.385919004678726,.281364023685455],[.383103013038635,.255840003490448],[.331431001424789,.119714021682739],[.229923993349075,.232002973556519],[.364500999450684,.189113974571228],[.229622006416321,.299540996551514],[.173287004232407,.278747975826263],[.472878992557526,.666198015213013],[.446828007698059,.668527007102966],[.422762006521225,.673889994621277],[.445307999849319,.580065965652466],[.388103008270264,.693961024284363],[.403039008378983,.706539988517761],[.403629004955292,.693953037261963],[.460041999816895,.557139039039612],[.431158006191254,.692366003990173],[.452181994915009,.692366003990173],[.475387006998062,.692366003990173],[.465828001499176,.779190003871918],[.472328990697861,.736225962638855],[.473087012767792,.717857003211975],[.473122000694275,.704625964164734],[.473033010959625,.695277988910675],[.427942007780075,.695277988910675],[.426479011774063,.703539967536926],[.423162013292313,.711845993995667],[.4183090031147,.720062971115112],[.390094995498657,.639572978019714],[.013953999616206,.560034036636353],[.499913990497589,.58014702796936],[.413199990987778,.69539999961853],[.409626007080078,.701822996139526],[.468080013990402,.601534962654114],[.422728985548019,.585985004901886],[.463079988956451,.593783974647522],[.37211999297142,.47341400384903],[.334562003612518,.496073007583618],[.411671012639999,.546965003013611],[.242175996303558,.14767599105835],[.290776997804642,.201445996761322],[.327338010072708,.256527006626129],[.399509996175766,.748921036720276],[.441727995872498,.261676013469696],[.429764986038208,.187834024429321],[.412198007106781,.108901023864746],[.288955003023148,.398952007293701],[.218936994671822,.435410976409912],[.41278201341629,.398970007896423],[.257135003805161,.355440020561218],[.427684992551804,.437960982322693],[.448339998722076,.536936044692993],[.178560003638268,.45755398273468],[.247308000922203,.457193970680237],[.286267012357712,.467674970626831],[.332827985286713,.460712015628815],[.368755996227264,.447206974029541],[.398963987827301,.432654976844788],[.476410001516342,.405806005001068],[.189241006970406,.523923993110657],[.228962004184723,.348950982093811],[.490725994110107,.562400996685028],[.404670000076294,.485132992267609],[.019469000399113,.401564002037048],[.426243007183075,.420431017875671],[.396993011236191,.548797011375427],[.266469985246658,.376977026462555],[.439121007919312,.51895797252655],[.032313998788595,.644356966018677],[.419054001569748,.387154996395111],[.462783008813858,.505746960639954],[.238978996872902,.779744982719421],[.198220998048782,.831938028335571],[.107550002634525,.540755033493042],[.183610007166862,.740257024765015],[.134409993886948,.333683013916016],[.385764002799988,.883153975009918],[.490967005491257,.579378008842468],[.382384985685349,.508572995662689],[.174399003386497,.397670984268188],[.318785011768341,.39623498916626],[.343364000320435,.400596976280212],[.396100014448166,.710216999053955],[.187885001301765,.588537991046906],[.430987000465393,.944064974784851],[.318993002176285,.898285031318665],[.266247987747192,.869701027870178],[.500023007392883,.190576016902924],[.499976992607117,.954452991485596],[.366169989109039,.398822009563446],[.393207013607025,.39553701877594],[.410373002290726,.391080021858215],[.194993004202843,.342101991176605],[.388664990663528,.362284004688263],[.365961998701096,.355970978736877],[.343364000320435,.355356991291046],[.318785011768341,.35834002494812],[.301414996385574,.363156020641327],[.058132998645306,.319076001644135],[.301414996385574,.387449026107788],[.499987989664078,.618434011936188],[.415838003158569,.624195992946625],[.445681989192963,.566076993942261],[.465844005346298,.620640993118286],[.49992299079895,.351523995399475],[.288718998432159,.819945991039276],[.335278987884521,.852819979190826],[.440512001514435,.902418971061707],[.128294005990028,.791940987110138],[.408771991729736,.373893976211548],[.455606997013092,.451801002025604],[.499877005815506,.908990025520325],[.375436991453171,.924192011356354],[.11421000212431,.615022003650665],[.448662012815475,.695277988910675],[.4480200111866,.704632043838501],[.447111994028091,.715808033943176],[.444831997156143,.730794012546539],[.430011987686157,.766808986663818],[.406787008047104,.685672998428345],[.400738000869751,.681069016456604],[.392399996519089,.677703022956848],[.367855995893478,.663918972015381],[.247923001646996,.601333022117615],[.452769994735718,.420849978923798],[.43639200925827,.359887003898621],[.416164010763168,.368713974952698],[.413385987281799,.692366003990173],[.228018000721931,.683571994304657],[.468268007040024,.352671027183533],[.411361992359161,.804327011108398],[.499989002943039,.469825029373169],[.479153990745544,.442654013633728],[.499974012374878,.439637005329132],[.432112008333206,.493588984012604],[.499886006116867,.866917014122009],[.49991300702095,.821729004383087],[.456548988819122,.819200992584229],[.344549000263214,.745438992977142],[.37890899181366,.574010014533997],[.374292999505997,.780184984207153],[.319687992334366,.570737957954407],[.357154995203018,.604269981384277],[.295284003019333,.621580958366394],[.447750002145767,.862477004528046],[.410986006259918,.508723020553589],[.31395098567009,.775308012962341],[.354128003120422,.812552988529205],[.324548006057739,.703992962837219],[.189096003770828,.646299958229065],[.279776990413666,.71465802192688],[.1338230073452,.682700991630554],[.336768001317978,.644733011722565],[.429883986711502,.466521978378296],[.455527991056442,.548622965812683],[.437114000320435,.558896005153656],[.467287987470627,.529924988746643],[.414712011814117,.335219979286194],[.37704598903656,.322777986526489],[.344107985496521,.320150971412659],[.312875986099243,.32233202457428],[.283526003360748,.333190023899078],[.241245999932289,.382785975933075],[.102986000478268,.468762993812561],[.267612010240555,.424560010433197],[.297879010438919,.433175981044769],[.333433985710144,.433878004550934],[.366427004337311,.426115989685059],[.396012008190155,.416696012020111],[.420121014118195,.41022801399231],[.007561000064015,.480777025222778],[.432949006557465,.569517970085144],[.458638995885849,.479089021682739],[.473466008901596,.545744001865387],[.476087987422943,.563830018043518],[.468472003936768,.555056989192963],[.433990985155106,.582361996173859],[.483518004417419,.562983989715576],[.482482999563217,.57784903049469],[.42645001411438,.389798998832703],[.438998997211456,.39649498462677],[.450067013502121,.400434017181396],[.289712011814117,.368252992630005],[.276670008897781,.363372981548309],[.517862021923065,.471948027610779],[.710287988185883,.380764007568359],[.526226997375488,.573909997940063],[.895093023777008,.254140973091125],[.634069979190826,.409575998783112],[.661242008209229,.41302502155304],[.688880026340485,.409460008144379],[.725341975688934,.389131009578705],[.606630027294159,.40370500087738],[.654766023159027,.344011008739471],[.629905998706818,.346076011657715],[.680678009986877,.347265005111694],[.702096998691559,.353591024875641],[.75221198797226,.410804986953735],[.602918028831482,.842862963676453],[.719901978969574,.375599980354309],[.893692970275879,.399959981441498],[.790081977844238,.391354024410248],[.643998026847839,.534487962722778],[.528249025344849,.65040397644043],[.525849997997284,.680191040039062],[.560214996337891,.657229006290436],[.585384011268616,.66654098033905],[.549625992774963,.680860996246338],[.57122802734375,.682691991329193],[.624852001667023,.72809898853302],[.513050019741058,.547281980514526],[.51509702205658,.527251958847046],[.742246985435486,.314507007598877],[.598631024360657,.454979002475739],[.570338010787964,.548575043678284],[.578631997108459,.533622980117798],[.723087012767792,.532054007053375],[.516445994377136,.499638974666595],[.662801027297974,.282917976379395],[.70362401008606,.293271005153656],[.830704987049103,.193813979625702],[.552385985851288,.302568018436432],[.607609987258911,.353887975215912],[.645429015159607,.696707010269165],[.932694971561432,.730105042457581],[.557260990142822,.572826027870178],[.542901992797852,.584792017936707],[.6180260181427,.694710969924927],[.607590973377228,.694203019142151],[.722943007946014,.271963000297546],[.577413976192474,.563166975975037],[.614082992076874,.281386971473694],[.616907000541687,.255886018276215],[.668509006500244,.119913995265961],[.770092010498047,.232020974159241],[.635536015033722,.189248979091644],[.77039098739624,.299556016921997],[.826722025871277,.278755009174347],[.527121007442474,.666198015213013],[.553171992301941,.668527007102966],[.577238023281097,.673889994621277],[.554691970348358,.580065965652466],[.611896991729736,.693961024284363],[.59696102142334,.706539988517761],[.596370995044708,.693953037261963],[.539958000183105,.557139039039612],[.568841993808746,.692366003990173],[.547818005084991,.692366003990173],[.52461302280426,.692366003990173],[.534089982509613,.779141008853912],[.527670979499817,.736225962638855],[.526912987232208,.717857003211975],[.526877999305725,.704625964164734],[.526966989040375,.695277988910675],[.572058022022247,.695277988910675],[.573521018028259,.703539967536926],[.57683801651001,.711845993995667],[.581691026687622,.720062971115112],[.609944999217987,.639909982681274],[.986046016216278,.560034036636353],[.5867999792099,.69539999961853],[.590372025966644,.701822996139526],[.531915009021759,.601536989212036],[.577268004417419,.585934996604919],[.536915004253387,.593786001205444],[.627542972564697,.473352015018463],[.665585994720459,.495950996875763],[.588353991508484,.546862006187439],[.757824003696442,.14767599105835],[.709249973297119,.201507985591888],[.672684013843536,.256581008434296],[.600408971309662,.74900496006012],[.55826598405838,.261672019958496],[.570303976535797,.187870979309082],[.588165998458862,.109044015407562],[.711045026779175,.398952007293701],[.781069993972778,.435405015945435],[.587247014045715,.398931980133057],[.742869973182678,.355445981025696],[.572156012058258,.437651991844177],[.55186802148819,.536570012569427],[.821442008018494,.457556009292603],[.752701997756958,.457181990146637],[.71375697851181,.467626988887787],[.66711300611496,.460672974586487],[.631101012229919,.447153985500336],[.6008620262146,.432473003864288],[.523481011390686,.405627012252808],[.810747981071472,.523926019668579],[.771045982837677,.348959028720856],[.509127020835876,.562718033790588],[.595292985439301,.485023975372314],[.980530977249146,.401564002037048],[.573499977588654,.420000016689301],[.602994978427887,.548687994480133],[.733529984951019,.376977026462555],[.560611009597778,.519016981124878],[.967685997486115,.644356966018677],[.580985009670258,.387160003185272],[.537728011608124,.505385041236877],[.760966002941132,.779752969741821],[.801778972148895,.831938028335571],[.892440974712372,.54076099395752],[.816350996494293,.740260004997253],[.865594983100891,.333687007427216],[.614073991775513,.883246004581451],[.508952975273132,.579437971115112],[.617941975593567,.508316040039062],[.825608015060425,.397674977779388],[.681214988231659,.39623498916626],[.656635999679565,.400596976280212],[.603900015354156,.710216999053955],[.81208598613739,.588539004325867],[.56801301240921,.944564998149872],[.681007981300354,.898285031318665],[.733752012252808,.869701027870178],[.633830010890961,.398822009563446],[.606792986392975,.39553701877594],[.589659988880157,.391062021255493],[.805015981197357,.342108011245728],[.611334979534149,.362284004688263],[.634037971496582,.355970978736877],[.656635999679565,.355356991291046],[.681214988231659,.35834002494812],[.698584973812103,.363156020641327],[.941866993904114,.319076001644135],[.698584973812103,.387449026107788],[.584177017211914,.624107003211975],[.554318010807037,.566076993942261],[.534153997898102,.62064003944397],[.711217999458313,.819975018501282],[.664629995822906,.852871000766754],[.559099972248077,.902631998062134],[.871706008911133,.791940987110138],[.591234028339386,.373893976211548],[.544341027736664,.451583981513977],[.624562978744507,.924192011356354],[.88577002286911,.615028977394104],[.551338016986847,.695277988910675],[.551980018615723,.704632043838501],[.552887976169586,.715808033943176],[.555167973041534,.730794012546539],[.569944024085999,.767035007476807],[.593203008174896,.685675978660583],[.599261999130249,.681069016456604],[.607599973678589,.677703022956848],[.631937980651855,.663500010967255],[.752032995223999,.601315021514893],[.547226011753082,.420395016670227],[.563543975353241,.359827995300293],[.583841025829315,.368713974952698],[.586614012718201,.692366003990173],[.771915018558502,.683578014373779],[.531597018241882,.352482974529266],[.588370978832245,.804440975189209],[.52079701423645,.442565023899078],[.567984998226166,.493479013442993],[.543282985687256,.819254994392395],[.655317008495331,.745514988899231],[.621008992195129,.574018001556396],[.625559985637665,.78031200170517],[.680198013782501,.570719003677368],[.64276397228241,.604337990283966],[.704662978649139,.621529996395111],[.552012026309967,.862591981887817],[.589071989059448,.508637011051178],[.685944974422455,.775357007980347],[.645735025405884,.812640011310577],[.675342977046967,.703978002071381],[.810858011245728,.646304965019226],[.72012197971344,.714666962623596],[.866151988506317,.682704985141754],[.663187026977539,.644596993923187],[.570082008838654,.466325998306274],[.544561982154846,.548375964164734],[.562758982181549,.558784961700439],[.531987011432648,.530140042304993],[.585271000862122,.335177004337311],[.622952997684479,.32277899980545],[.655896008014679,.320163011550903],[.687132000923157,.322345972061157],[.716481983661652,.333200991153717],[.758756995201111,.382786989212036],[.897013008594513,.468769013881683],[.732392013072968,.424547016620636],[.70211398601532,.433162987232208],[.66652500629425,.433866024017334],[.633504986763,.426087975502014],[.603875994682312,.416586995124817],[.579657971858978,.409945011138916],[.992439985275269,.480777025222778],[.567192018032074,.569419980049133],[.54136598110199,.478899002075195],[.526564002037048,.546118021011353],[.523913025856018,.563830018043518],[.531529009342194,.555056989192963],[.566035985946655,.582329034805298],[.51631098985672,.563053965568542],[.5174720287323,.577877044677734],[.573594987392426,.389806985855103],[.560697972774506,.395331978797913],[.549755990505219,.399751007556915],[.710287988185883,.368252992630005],[.723330020904541,.363372981548309]],lu=[127,34,139,11,0,37,232,231,120,72,37,39,128,121,47,232,121,128,104,69,67,175,171,148,157,154,155,118,50,101,73,39,40,9,151,108,48,115,131,194,204,211,74,40,185,80,42,183,40,92,186,230,229,118,202,212,214,83,18,17,76,61,146,160,29,30,56,157,173,106,204,194,135,214,192,203,165,98,21,71,68,51,45,4,144,24,23,77,146,91,205,50,187,201,200,18,91,106,182,90,91,181,85,84,17,206,203,36,148,171,140,92,40,39,193,189,244,159,158,28,247,246,161,236,3,196,54,68,104,193,168,8,117,228,31,189,193,55,98,97,99,126,47,100,166,79,218,155,154,26,209,49,131,135,136,150,47,126,217,223,52,53,45,51,134,211,170,140,67,69,108,43,106,91,230,119,120,226,130,247,63,53,52,238,20,242,46,70,156,78,62,96,46,53,63,143,34,227,173,155,133,123,117,111,44,125,19,236,134,51,216,206,205,154,153,22,39,37,167,200,201,208,36,142,100,57,212,202,20,60,99,28,158,157,35,226,113,160,159,27,204,202,210,113,225,46,43,202,204,62,76,77,137,123,116,41,38,72,203,129,142,64,98,240,49,102,64,41,73,74,212,216,207,42,74,184,169,170,211,170,149,176,105,66,69,122,6,168,123,147,187,96,77,90,65,55,107,89,90,180,101,100,120,63,105,104,93,137,227,15,86,85,129,102,49,14,87,86,55,8,9,100,47,121,145,23,22,88,89,179,6,122,196,88,95,96,138,172,136,215,58,172,115,48,219,42,80,81,195,3,51,43,146,61,171,175,199,81,82,38,53,46,225,144,163,110,246,33,7,52,65,66,229,228,117,34,127,234,107,108,69,109,108,151,48,64,235,62,78,191,129,209,126,111,35,143,163,161,246,117,123,50,222,65,52,19,125,141,221,55,65,3,195,197,25,7,33,220,237,44,70,71,139,122,193,245,247,130,33,71,21,162,153,158,159,170,169,150,188,174,196,216,186,92,144,160,161,2,97,167,141,125,241,164,167,37,72,38,12,145,159,160,38,82,13,63,68,71,226,35,111,158,153,154,101,50,205,206,92,165,209,198,217,165,167,97,220,115,218,133,112,243,239,238,241,214,135,169,190,173,133,171,208,32,125,44,237,86,87,178,85,86,179,84,85,180,83,84,181,201,83,182,137,93,132,76,62,183,61,76,184,57,61,185,212,57,186,214,207,187,34,143,156,79,239,237,123,137,177,44,1,4,201,194,32,64,102,129,213,215,138,59,166,219,242,99,97,2,94,141,75,59,235,24,110,228,25,130,226,23,24,229,22,23,230,26,22,231,112,26,232,189,190,243,221,56,190,28,56,221,27,28,222,29,27,223,30,29,224,247,30,225,238,79,20,166,59,75,60,75,240,147,177,215,20,79,166,187,147,213,112,233,244,233,128,245,128,114,188,114,217,174,131,115,220,217,198,236,198,131,134,177,132,58,143,35,124,110,163,7,228,110,25,356,389,368,11,302,267,452,350,349,302,303,269,357,343,277,452,453,357,333,332,297,175,152,377,384,398,382,347,348,330,303,304,270,9,336,337,278,279,360,418,262,431,304,408,409,310,415,407,270,409,410,450,348,347,422,430,434,313,314,17,306,307,375,387,388,260,286,414,398,335,406,418,364,367,416,423,358,327,251,284,298,281,5,4,373,374,253,307,320,321,425,427,411,421,313,18,321,405,406,320,404,405,315,16,17,426,425,266,377,400,369,322,391,269,417,465,464,386,257,258,466,260,388,456,399,419,284,332,333,417,285,8,346,340,261,413,441,285,327,460,328,355,371,329,392,439,438,382,341,256,429,420,360,364,394,379,277,343,437,443,444,283,275,440,363,431,262,369,297,338,337,273,375,321,450,451,349,446,342,467,293,334,282,458,461,462,276,353,383,308,324,325,276,300,293,372,345,447,382,398,362,352,345,340,274,1,19,456,248,281,436,427,425,381,256,252,269,391,393,200,199,428,266,330,329,287,273,422,250,462,328,258,286,384,265,353,342,387,259,257,424,431,430,342,353,276,273,335,424,292,325,307,366,447,345,271,303,302,423,266,371,294,455,460,279,278,294,271,272,304,432,434,427,272,407,408,394,430,431,395,369,400,334,333,299,351,417,168,352,280,411,325,319,320,295,296,336,319,403,404,330,348,349,293,298,333,323,454,447,15,16,315,358,429,279,14,15,316,285,336,9,329,349,350,374,380,252,318,402,403,6,197,419,318,319,325,367,364,365,435,367,397,344,438,439,272,271,311,195,5,281,273,287,291,396,428,199,311,271,268,283,444,445,373,254,339,263,466,249,282,334,296,449,347,346,264,447,454,336,296,299,338,10,151,278,439,455,292,407,415,358,371,355,340,345,372,390,249,466,346,347,280,442,443,282,19,94,370,441,442,295,248,419,197,263,255,359,440,275,274,300,383,368,351,412,465,263,467,466,301,368,389,380,374,386,395,378,379,412,351,419,436,426,322,373,390,388,2,164,393,370,462,461,164,0,267,302,11,12,374,373,387,268,12,13,293,300,301,446,261,340,385,384,381,330,266,425,426,423,391,429,355,437,391,327,326,440,457,438,341,382,362,459,457,461,434,430,394,414,463,362,396,369,262,354,461,457,316,403,402,315,404,403,314,405,404,313,406,405,421,418,406,366,401,361,306,408,407,291,409,408,287,410,409,432,436,410,434,416,411,264,368,383,309,438,457,352,376,401,274,275,4,421,428,262,294,327,358,433,416,367,289,455,439,462,370,326,2,326,370,305,460,455,254,449,448,255,261,446,253,450,449,252,451,450,256,452,451,341,453,452,413,464,463,441,413,414,258,442,441,257,443,442,259,444,443,260,445,444,467,342,445,459,458,250,289,392,290,290,328,460,376,433,435,250,290,392,411,416,433,341,463,464,453,464,465,357,465,412,343,412,399,360,363,440,437,399,456,420,456,363,401,435,288,372,383,353,339,255,249,448,261,255,133,243,190,133,155,112,33,246,247,33,130,25,398,384,286,362,398,414,362,463,341,263,359,467,263,249,255,466,467,260,75,60,166,238,239,79,162,127,139,72,11,37,121,232,120,73,72,39,114,128,47,233,232,128,103,104,67,152,175,148,173,157,155,119,118,101,74,73,40,107,9,108,49,48,131,32,194,211,184,74,185,191,80,183,185,40,186,119,230,118,210,202,214,84,83,17,77,76,146,161,160,30,190,56,173,182,106,194,138,135,192,129,203,98,54,21,68,5,51,4,145,144,23,90,77,91,207,205,187,83,201,18,181,91,182,180,90,181,16,85,17,205,206,36,176,148,140,165,92,39,245,193,244,27,159,28,30,247,161,174,236,196,103,54,104,55,193,8,111,117,31,221,189,55,240,98,99,142,126,100,219,166,218,112,155,26,198,209,131,169,135,150,114,47,217,224,223,53,220,45,134,32,211,140,109,67,108,146,43,91,231,230,120,113,226,247,105,63,52,241,238,242,124,46,156,95,78,96,70,46,63,116,143,227,116,123,111,1,44,19,3,236,51,207,216,205,26,154,22,165,39,167,199,200,208,101,36,100,43,57,202,242,20,99,56,28,157,124,35,113,29,160,27,211,204,210,124,113,46,106,43,204,96,62,77,227,137,116,73,41,72,36,203,142,235,64,240,48,49,64,42,41,74,214,212,207,183,42,184,210,169,211,140,170,176,104,105,69,193,122,168,50,123,187,89,96,90,66,65,107,179,89,180,119,101,120,68,63,104,234,93,227,16,15,85,209,129,49,15,14,86,107,55,9,120,100,121,153,145,22,178,88,179,197,6,196,89,88,96,135,138,136,138,215,172,218,115,219,41,42,81,5,195,51,57,43,61,208,171,199,41,81,38,224,53,225,24,144,110,105,52,66,118,229,117,227,34,234,66,107,69,10,109,151,219,48,235,183,62,191,142,129,126,116,111,143,7,163,246,118,117,50,223,222,52,94,19,141,222,221,65,196,3,197,45,220,44,156,70,139,188,122,245,139,71,162,145,153,159,149,170,150,122,188,196,206,216,92,163,144,161,164,2,167,242,141,241,0,164,37,11,72,12,144,145,160,12,38,13,70,63,71,31,226,111,157,158,154,36,101,205,203,206,165,126,209,217,98,165,97,237,220,218,237,239,241,210,214,169,140,171,32,241,125,237,179,86,178,180,85,179,181,84,180,182,83,181,194,201,182,177,137,132,184,76,183,185,61,184,186,57,185,216,212,186,192,214,187,139,34,156,218,79,237,147,123,177,45,44,4,208,201,32,98,64,129,192,213,138,235,59,219,141,242,97,97,2,141,240,75,235,229,24,228,31,25,226,230,23,229,231,22,230,232,26,231,233,112,232,244,189,243,189,221,190,222,28,221,223,27,222,224,29,223,225,30,224,113,247,225,99,60,240,213,147,215,60,20,166,192,187,213,243,112,244,244,233,245,245,128,188,188,114,174,134,131,220,174,217,236,236,198,134,215,177,58,156,143,124,25,110,7,31,228,25,264,356,368,0,11,267,451,452,349,267,302,269,350,357,277,350,452,357,299,333,297,396,175,377,381,384,382,280,347,330,269,303,270,151,9,337,344,278,360,424,418,431,270,304,409,272,310,407,322,270,410,449,450,347,432,422,434,18,313,17,291,306,375,259,387,260,424,335,418,434,364,416,391,423,327,301,251,298,275,281,4,254,373,253,375,307,321,280,425,411,200,421,18,335,321,406,321,320,405,314,315,17,423,426,266,396,377,369,270,322,269,413,417,464,385,386,258,248,456,419,298,284,333,168,417,8,448,346,261,417,413,285,326,327,328,277,355,329,309,392,438,381,382,256,279,429,360,365,364,379,355,277,437,282,443,283,281,275,363,395,431,369,299,297,337,335,273,321,348,450,349,359,446,467,283,293,282,250,458,462,300,276,383,292,308,325,283,276,293,264,372,447,346,352,340,354,274,19,363,456,281,426,436,425,380,381,252,267,269,393,421,200,428,371,266,329,432,287,422,290,250,328,385,258,384,446,265,342,386,387,257,422,424,430,445,342,276,422,273,424,306,292,307,352,366,345,268,271,302,358,423,371,327,294,460,331,279,294,303,271,304,436,432,427,304,272,408,395,394,431,378,395,400,296,334,299,6,351,168,376,352,411,307,325,320,285,295,336,320,319,404,329,330,349,334,293,333,366,323,447,316,15,315,331,358,279,317,14,316,8,285,9,277,329,350,253,374,252,319,318,403,351,6,419,324,318,325,397,367,365,288,435,397,278,344,439,310,272,311,248,195,281,375,273,291,175,396,199,312,311,268,276,283,445,390,373,339,295,282,296,448,449,346,356,264,454,337,336,299,337,338,151,294,278,455,308,292,415,429,358,355,265,340,372,388,390,466,352,346,280,295,442,282,354,19,370,285,441,295,195,248,197,457,440,274,301,300,368,417,351,465,251,301,389,385,380,386,394,395,379,399,412,419,410,436,322,387,373,388,326,2,393,354,370,461,393,164,267,268,302,12,386,374,387,312,268,13,298,293,301,265,446,340,380,385,381,280,330,425,322,426,391,420,429,437,393,391,326,344,440,438,458,459,461,364,434,394,428,396,262,274,354,457,317,316,402,316,315,403,315,314,404,314,313,405,313,421,406,323,366,361,292,306,407,306,291,408,291,287,409,287,432,410,427,434,411,372,264,383,459,309,457,366,352,401,1,274,4,418,421,262,331,294,358,435,433,367,392,289,439,328,462,326,94,2,370,289,305,455,339,254,448,359,255,446,254,253,449,253,252,450,252,256,451,256,341,452,414,413,463,286,441,414,286,258,441,258,257,442,257,259,443,259,260,444,260,467,445,309,459,250,305,289,290,305,290,460,401,376,435,309,250,392,376,411,433,453,341,464,357,453,465,343,357,412,437,343,399,344,360,440,420,437,456,360,420,363,361,401,288,265,372,353,390,339,249,339,448,255];var OAe=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],MAe=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],zAe=[33,133,362,263,1,78,308],B8e=OAe.map(e=>Hh[e]),W8e=MAe.map(e=>Hh[e]),V8e=zAe.map(e=>Hh[e]);function fi(e){let t=e.map(n=>n[0]);return t.push(e[e.length-1][1]),t}var LAe=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],BAe=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],WAe=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],VAe=[[474,475],[475,476],[476,477],[477,474]],UAe=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],GAe=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],HAe=[[469,470],[470,471],[471,472],[472,469]],jAe=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]],U8e={lips:fi(LAe),leftEye:fi(BAe),leftEyebrow:fi(WAe),leftIris:fi(VAe),rightEye:fi(UAe),rightEyebrow:fi(GAe),rightIris:fi(HAe),faceOval:fi(jAe)};var yd=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],M2=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],z2=(e,t)=>e?[Math.trunc(Math.max(0,e.startPoint[0])),Math.trunc(Math.max(0,e.startPoint[1])),Math.trunc(Math.min(t.shape[2]||0,e.endPoint[0])-Math.max(0,e.startPoint[0])),Math.trunc(Math.min(t.shape[1]||0,e.endPoint[1])-Math.max(0,e.startPoint[1]))]:[0,0,0,0],L2=(e,t)=>e?[e.startPoint[0]/(t.shape[2]||0),e.startPoint[1]/(t.shape[1]||0),(e.endPoint[0]-e.startPoint[0])/(t.shape[2]||0),(e.endPoint[1]-e.startPoint[1])/(t.shape[1]||0)]:[0,0,0,0],GT=(e,t)=>{let n=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],s=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]];return{startPoint:n,endPoint:s,landmarks:e.landmarks,confidence:e.confidence}},Tb=(e,t,n)=>{let s=t.shape[1],r=t.shape[2],a=[e.startPoint[1]/s,e.startPoint[0]/r,e.endPoint[1]/s,e.endPoint[0]/r],o=Ne.cropAndResize(t,[a],[0],n),i=pe(o,nt.tf255);return ne(o),i},B2=(e,t)=>{let n=M2(e),s=yd(e),r=[t*s[0]/2,t*s[1]/2];return{startPoint:[n[0]-r[0],n[1]-r[1]],endPoint:[n[0]+r[0],n[1]+r[1]],landmarks:e.landmarks,confidence:e.confidence}},W2=e=>{let t=M2(e),n=yd(e),s=Math.max(...n)/2;return{startPoint:[Math.round(t[0]-s),Math.round(t[1]-s)],endPoint:[Math.round(t[0]+s),Math.round(t[1]+s)],landmarks:e.landmarks,confidence:e.confidence}},HT=e=>{let t=e.map(s=>s[0]),n=e.map(s=>s[1]);return{startPoint:[Math.min(...t),Math.min(...n)],endPoint:[Math.max(...t),Math.max(...n)],landmarks:e}},Nb=[[1,0,0],[0,1,0],[0,0,1]],qAe=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),XAe=(e,t)=>qAe(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var VT=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],uu=(e,t)=>{let n=0;for(let s=0;s<e.length;s++)n+=e[s]*t[s];return n},KAe=(e,t)=>{let n=[];for(let s=0;s<e.length;s++)n.push(e[s][t]);return n},UT=(e,t)=>{let n=[],s=e.length;for(let r=0;r<s;r++){n.push([]);for(let a=0;a<s;a++)n[r].push(uu(e[r],KAe(t,a)))}return n},jT=(e,t)=>{let n=Math.cos(e),s=Math.sin(e),r=[[n,-s,0],[s,n,0],[0,0,1]],a=VT(t[0],t[1]),o=UT(a,r),i=VT(-t[0],-t[1]);return UT(o,i)},ZAe=e=>{let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],n=[e[0][2],e[1][2]],s=[-uu(t[0],n),-uu(t[1],n)];return[t[0].concat(s[0]),t[1].concat(s[1]),[0,0,1]]},YAe=(e,t)=>[uu(e,t[0]),uu(e,t[1])];function qT(e){let t=e===192?{strides:[4],anchors:[1]}:{strides:[e/16,e/8],anchors:[2,6]},n=[];for(let s=0;s<t.strides.length;s++){let r=t.strides[s],a=Math.floor((e+r-1)/r),o=Math.floor((e+r-1)/r),i=t.anchors[s];for(let l=0;l<a;l++){let u=r*(l+.5);for(let c=0;c<o;c++){let p=r*(c+.5);for(let d=0;d<i;d++)n.push([p,u])}}}return n}function XT(e,t,n,s,r){let a=yd(t),o=e.map(h=>[a[0]/r*(h[0]-r/2),a[1]/r*(h[1]-r/2),h[2]||0]),i=n&&n!==0&&Math.abs(n)>.2,l=i?jT(n,[0,0]):Nb,u=i?o.map(h=>[...YAe(h,l),h[2]]):o,c=i?ZAe(s):Nb,p=M2(t),d=[uu(p,c[0]),uu(p,c[1])];return u.map(h=>[Math.trunc(h[0]+d[0]),Math.trunc(h[1]+d[1]),Math.trunc(h[2]||0)])}function KT(e,t,n,s){let r=t.landmarks.length>=Ib.count?Ib.symmetryLine:iu.symmetryLine,a=0,o=Nb,i;if(e&&fe.kernels.includes("rotatewithoffset"))if(a=XAe(t.landmarks[r[0]],t.landmarks[r[1]]),a&&a!==0&&Math.abs(a)>.2){let u=M2(t),c=[u[0]/n.shape[2],u[1]/n.shape[1]],p=Ne.rotateWithOffset(n,a,0,c);o=jT(-a,u),i=Tb(t,p,[s,s]),ne(p)}else i=Tb(t,n,[s,s]);else i=Tb(t,n,[s,s]);return[a,o,i]}var JAe=e=>{let t=e.map(s=>s[0]),n=e.map(s=>s[1]);return[Math.min(...t)+(Math.max(...t)-Math.min(...t))/2,Math.min(...n)+(Math.max(...n)-Math.min(...n))/2]},ZT=(e,t)=>{let n=JAe(e),s=yd(t);return{startPoint:[n[0]-s[0]/2,n[1]-s[1]/2],endPoint:[n[0]+s[0]/2,n[1]+s[1]/2]}};var YT=6,QAe=1.4,ea,JT=null,mi=0,jh=null,Ad=()=>mi;async function QT(e){var t;return fe.initial&&(ea=null),ea?e.debug&&ie("cached model:",ea.modelUrl):ea=await qe((t=e.face.detector)==null?void 0:t.modelPath),mi=ea.inputs[0].shape?ea.inputs[0].shape[2]:0,jh=Se(mi,"int32"),JT=or(qT(mi)),ea}function e5e(e){let t={};t.boxStarts=Oe(e,[0,1],[-1,2]),t.centers=ce(t.boxStarts,JT),t.boxSizes=Oe(e,[0,3],[-1,2]),t.boxSizesNormalized=pe(t.boxSizes,jh),t.centersNormalized=pe(t.centers,jh),t.halfBoxSize=pe(t.boxSizesNormalized,nt.tf2),t.starts=he(t.centersNormalized,t.halfBoxSize),t.ends=ce(t.centersNormalized,t.halfBoxSize),t.startNormalized=L(t.starts,jh),t.endNormalized=L(t.ends,jh);let n=Kl([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(s=>ne(t[s])),n}async function eN(e,t){var i,l,u,c;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let n={};n.resized=Ne.resizeBilinear(e,[mi,mi]),n.div=pe(n.resized,nt.tf127),n.normalized=he(n.div,nt.tf05);let s=ea==null?void 0:ea.execute(n.normalized);if(Array.isArray(s)&&s.length>2){let p=s.sort((d,h)=>d.size-h.size);n.concat384=Ct([p[0],p[2]],2),n.concat512=Ct([p[1],p[3]],2),n.concat=Ct([n.concat512,n.concat384],1),n.batch=rt(n.concat,0)}else Array.isArray(s)?n.batch=rt(s[0]):n.batch=rt(s);ne(s),n.boxes=e5e(n.batch),n.logits=Oe(n.batch,[0,0],[-1,1]),n.sigmoid=Cn(n.logits),n.scores=rt(n.sigmoid),n.nms=await Ne.nonMaxSuppressionAsync(n.boxes,n.scores,((i=t.face.detector)==null?void 0:i.maxDetected)||0,((l=t.face.detector)==null?void 0:l.iouThreshold)||0,((u=t.face.detector)==null?void 0:u.minConfidence)||0);let r=await n.nms.array(),a=[],o=await n.scores.data();for(let p=0;p<r.length;p++){let d=o[r[p]];if(d>(((c=t.face.detector)==null?void 0:c.minConfidence)||0)){let h={};h.bbox=Oe(n.boxes,[r[p],0],[1,-1]),h.slice=Oe(n.batch,[r[p],YT-1],[1,-1]),h.squeeze=rt(h.slice),h.landmarks=U(h.squeeze,[YT,-1]);let f=await h.bbox.data(),m={startPoint:[f[0],f[1]],endPoint:[f[2],f[3]],landmarks:await h.landmarks.array(),confidence:d},g=GT(m,[(e.shape[2]||0)/mi,(e.shape[1]||0)/mi]),y=B2(g,t.face.scale||QAe),x=W2(y);a.push(x),Object.keys(h).forEach(A=>ne(h[A]))}}return Object.keys(n).forEach(p=>ne(n[p])),a}var V2={};ia(V2,{connected:()=>_b,kpt:()=>Rb});var Rb=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPinky","rightPinky","leftIndex","rightIndex","leftThumb","rightThumb","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","bodyCenter","bodyTop","leftPalm","leftHand","rightPalm","rightHand"],_b={shoulders:["leftShoulder","rightShoulder"],hips:["rightHip","leftHip"],mouth:["leftMouth","rightMouth"],leftLegUpper:["leftHip","leftKnee"],leftLegLower:["leftKnee","leftAnkle"],leftFoot:["leftAnkle","leftHeel","leftFoot"],leftTorso:["leftShoulder","leftHip"],leftArmUpper:["leftShoulder","leftElbow"],leftArmLower:["leftElbow","leftWrist"],leftHand:["leftWrist","leftPalm"],leftHandPinky:["leftPalm","leftPinky"],leftHandIndex:["leftPalm","leftIndex"],leftHandThumb:["leftPalm","leftThumb"],leftEyeOutline:["leftEyeInside","leftEyeOutside"],rightLegUpper:["rightHip","rightKnee"],rightLegLower:["rightKnee","rightAnkle"],rightFoot:["rightAnkle","rightHeel","rightFoot"],rightTorso:["rightShoulder","rightHip"],rightArmUpper:["rightShoulder","rightElbow"],rightArmLower:["rightElbow","rightWrist"],rightHand:["rightWrist","rightPalm"],rightHandPinky:["rightPalm","rightPinky"],rightHandIndex:["rightPalm","rightIndex"],rightHandThumb:["rightPalm","rightThumb"],rightEyeOutline:["rightEyeInside","rightEyeOutside"]};var nN=224,t5e,n5e=5,U2=[8,16,32,32,32];async function sN(){let e=[],t=0;for(;t<n5e;){let n=0,s=t;for(;s<U2.length&&U2[s]===U2[t];)n+=2,s++;let r=U2[t],a=Math.ceil(nN/r),o=Math.ceil(nN/r);for(let i=0;i<a;++i)for(let l=0;l<o;++l)for(let u=0;u<n;++u)e.push({x:(l+.5)/o,y:(i+.5)/a});t=s}t5e={x:Ft(e.map(n=>n.x)),y:Ft(e.map(n=>n.y))}}function Na(e,t=[1,1]){let n=[e.map(i=>i[0]),e.map(i=>i[1])],s=[Math.min(...n[0]),Math.min(...n[1])],r=[Math.max(...n[0]),Math.max(...n[1])],a=[s[0],s[1],r[0]-s[0],r[1]-s[1]],o=[a[0]/t[0],a[1]/t[1],a[2]/t[0],a[3]/t[1]];return{box:a,boxRaw:o}}function rN(e,t=[1,1]){let n=[e.map(u=>u[0]),e.map(u=>u[1])],s=[Math.min(...n[0]),Math.min(...n[1])],r=[Math.max(...n[0]),Math.max(...n[1])],a=[(s[0]+r[0])/2,(s[1]+r[1])/2],o=Math.max(a[0]-s[0],a[1]-s[1],-a[0]+r[0],-a[1]+r[1]),i=[Math.trunc(a[0]-o),Math.trunc(a[1]-o),Math.trunc(2*o),Math.trunc(2*o)],l=[i[0]/t[0],i[1]/t[1],i[2]/t[0],i[3]/t[1]];return{box:i,boxRaw:l}}function G2(e,t){let n=[e[2]*t,e[3]*t];return[e[0]-(n[0]-e[2])/2,e[1]-(n[1]-e[3])/2,n[0],n[1]]}var iN={initial:!0},Ms={detector:null,landmarks:null},xd={detector:[224,224],landmarks:[256,256]},Db=Number.MAX_SAFE_INTEGER,r5e={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},j2=null,qh,gi=[[0,0],[0,0],[0,0],[0,0]],aN=0,oN=e=>1-1/(1+Math.exp(e));async function lN(e){if(iN.initial&&(Ms.detector=null),!Ms.detector&&e.body.detector&&e.body.detector.modelPath){Ms.detector=await qe(e.body.detector.modelPath);let t=Object.values(Ms.detector.modelSignature.inputs);xd.detector[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,xd.detector[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&Ms.detector&&ie("cached model:",Ms.detector.modelUrl);return await sN(),Ms.detector}async function uN(e){if(iN.initial&&(Ms.landmarks=null),Ms.landmarks)e.debug&&ie("cached model:",Ms.landmarks.modelUrl);else{Ms.landmarks=await qe(e.body.modelPath);let t=Object.values(Ms.landmarks.modelSignature.inputs);xd.landmarks[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,xd.landmarks[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return Ms.landmarks}async function a5e(e,t){let n={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;let s;if(qh&&(n.cropped=Ne.cropAndResize(e,[qh],[0],[e.shape[1],e.shape[2]])),e.shape[1]!==e.shape[2]){let r=[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],a=[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0];gi=[[0,0],r,a,[0,0]],n.pad=Js(n.cropped||e,gi),n.resize=Ne.resizeBilinear(n.pad,[t,t]),s=pe(n.resize,nt.tf255)}else e.shape[1]!==t?(n.resize=Ne.resizeBilinear(n.cropped||e,[t,t]),s=pe(n.resize,nt.tf255)):s=pe(n.cropped||e,nt.tf255);return Object.keys(n).forEach(r=>ne(n[r])),s}function o5e(e,t){for(let n of e)n.position=[Math.trunc(n.position[0]*(t[0]+gi[2][0]+gi[2][1])/t[0]-gi[2][0]),Math.trunc(n.position[1]*(t[1]+gi[1][0]+gi[1][1])/t[1]-gi[1][0]),n.position[2]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1],2*n.position[2]/(t[0]+t[1])];if(qh)for(let n of e)n.positionRaw=[n.positionRaw[0]+qh[1],n.positionRaw[1]+qh[0],n.positionRaw[2]],n.position=[Math.trunc(n.positionRaw[0]*t[0]),Math.trunc(n.positionRaw[1]*t[1]),n.positionRaw[2]];return e}async function i5e(e){let t=e.find(i=>i.part==="leftPalm"),n=e.find(i=>i.part==="leftWrist"),s=e.find(i=>i.part==="leftIndex");t.position[2]=((n.position[2]||0)+(s.position[2]||0))/2;let r=e.find(i=>i.part==="rightPalm"),a=e.find(i=>i.part==="rightWrist"),o=e.find(i=>i.part==="rightIndex");r.position[2]=((a.position[2]||0)+(o.position[2]||0))/2}async function l5e(e,t,n){var f;let s={};[s.ld,s.segmentation,s.heatmap,s.world,s.poseflag]=(f=Ms.landmarks)==null?void 0:f.execute(e,r5e.landmarks);let r=(await s.poseflag.data())[0],a=await s.ld.data(),o=await s.world.data();Object.keys(s).forEach(m=>ne(s[m]));let i=[],l=5;for(let m=0;m<a.length/l;m++){let g=oN(a[l*m+3]),y=oN(a[l*m+4]),x=Math.trunc(100*g*y*r)/100,A=[a[l*m+0]/xd.landmarks[0],a[l*m+1]/xd.landmarks[1],a[l*m+2]+0],b=[Math.trunc(n[0]*A[0]),Math.trunc(n[1]*A[1]),A[2]],w=[o[l*m+0],o[l*m+1],o[l*m+2]+0];i.push({part:Rb[m],positionRaw:A,position:b,distance:w,score:x})}if(r<(t.body.minConfidence||0))return null;i5e(i);let u=o5e(i,n),c=u.map(m=>m.position),p=Na(c,[n[0],n[1]]),d={};for(let[m,g]of Object.entries(_b)){let y=[];for(let x=0;x<g.length-1;x++){let A=u.find(w=>w.part===g[x]),b=u.find(w=>w.part===g[x+1]);A&&b&&y.push([A.position,b.position])}d[m]=y}return{id:0,score:Math.trunc(100*r)/100,box:p.box,boxRaw:p.boxRaw,keypoints:u,annotations:d}}async function $b(e,t){let n=[e.shape[2]||0,e.shape[1]||0],s=(t.body.skipTime||0)>ue()-aN,r=Db<(t.body.skipFrames||0);if(t.skipAllowed&&s&&r&&j2!==null)Db++;else{let a={};a.landmarks=await a5e(e,256),j2=await l5e(a.landmarks,t,n),Object.keys(a).forEach(o=>ne(a[o])),aN=ue(),Db=0}return j2?[j2]:[]}var bd=[{class:1,label:"person"},{class:2,label:"bicycle"},{class:3,label:"car"},{class:4,label:"motorcycle"},{class:5,label:"airplane"},{class:6,label:"bus"},{class:7,label:"train"},{class:8,label:"truck"},{class:9,label:"boat"},{class:10,label:"traffic light"},{class:11,label:"fire hydrant"},{class:12,label:"stop sign"},{class:13,label:"parking meter"},{class:14,label:"bench"},{class:15,label:"bird"},{class:16,label:"cat"},{class:17,label:"dog"},{class:18,label:"horse"},{class:19,label:"sheep"},{class:20,label:"cow"},{class:21,label:"elephant"},{class:22,label:"bear"},{class:23,label:"zebra"},{class:24,label:"giraffe"},{class:25,label:"backpack"},{class:26,label:"umbrella"},{class:27,label:"handbag"},{class:28,label:"tie"},{class:29,label:"suitcase"},{class:30,label:"frisbee"},{class:31,label:"skis"},{class:32,label:"snowboard"},{class:33,label:"sports ball"},{class:34,label:"kite"},{class:35,label:"baseball bat"},{class:36,label:"baseball glove"},{class:37,label:"skateboard"},{class:38,label:"surfboard"},{class:39,label:"tennis racket"},{class:40,label:"bottle"},{class:41,label:"wine glass"},{class:42,label:"cup"},{class:43,label:"fork"},{class:44,label:"knife"},{class:45,label:"spoon"},{class:46,label:"bowl"},{class:47,label:"banana"},{class:48,label:"apple"},{class:49,label:"sandwich"},{class:50,label:"orange"},{class:51,label:"broccoli"},{class:52,label:"carrot"},{class:53,label:"hot dog"},{class:54,label:"pizza"},{class:55,label:"donut"},{class:56,label:"cake"},{class:57,label:"chair"},{class:58,label:"couch"},{class:59,label:"potted plant"},{class:60,label:"bed"},{class:61,label:"dining table"},{class:62,label:"toilet"},{class:63,label:"tv"},{class:64,label:"laptop"},{class:65,label:"mouse"},{class:66,label:"remote"},{class:67,label:"keyboard"},{class:68,label:"cell phone"},{class:69,label:"microwave"},{class:70,label:"oven"},{class:71,label:"toaster"},{class:72,label:"sink"},{class:73,label:"refrigerator"},{class:74,label:"book"},{class:75,label:"clock"},{class:76,label:"vase"},{class:77,label:"scissors"},{class:78,label:"teddy bear"},{class:79,label:"hair drier"},{class:80,label:"toothbrush"}];var Ea,cu=0,Pb=[],dN=0,Fb=Number.MAX_SAFE_INTEGER;async function pN(e){if(fe.initial&&(Ea=null),Ea)e.debug&&ie("cached model:",Ea.modelUrl);else{Ea=await qe(e.object.modelPath);let t=Object.values(Ea.modelSignature.inputs);cu=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return Ea}async function u5e(e,t,n){if(!e)return[];let s={},r=[],a=await e.array();s.squeeze=rt(e);let o=Zt(s.squeeze,6,1);s.stack=on([o[1],o[0],o[3],o[2]],1),s.boxes=rt(s.stack),s.scores=rt(o[4]),s.classes=rt(o[5]),ne([e,...o]),s.nms=await Ne.nonMaxSuppressionAsync(s.boxes,s.scores,n.object.maxDetected,n.object.iouThreshold,n.object.minConfidence||0);let i=await s.nms.data(),l=0;for(let u of Array.from(i)){let c=Math.trunc(100*a[0][u][4])/100,p=a[0][u][5],d=bd[p].label,[h,f]=[a[0][u][0]/cu,a[0][u][1]/cu],m=[h,f,a[0][u][2]/cu-h,a[0][u][3]/cu-f],g=[Math.trunc(m[0]*t[0]),Math.trunc(m[1]*t[1]),Math.trunc(m[2]*t[0]),Math.trunc(m[3]*t[1])];r.push({id:l++,score:c,class:p,label:d,box:g,boxRaw:m})}return Object.keys(s).forEach(u=>ne(s[u])),r}async function Ob(e,t){let n=(t.object.skipTime||0)>ue()-dN,s=Fb<(t.object.skipFrames||0);return t.skipAllowed&&n&&s&&Pb.length>0?(Fb++,Pb):(Fb=0,new Promise(async r=>{let a=[e.shape[2]||0,e.shape[1]||0],o=Ne.resizeBilinear(e,[cu,cu]),i=t.object.enabled?Ea==null?void 0:Ea.execute(o,["tower_0/detections"]):null;dN=ue(),ne(o);let l=await u5e(i,a,t);Pb=l,r(l)}))}var q2={};ia(q2,{connected:()=>zb,kpt:()=>Mb});var Mb=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],zb={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var Ln,fN=0,us={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},Lb=Number.MAX_SAFE_INTEGER;async function mN(e){return fe.initial&&(Ln=null),Ln?e.debug&&ie("cached model:",Ln.modelUrl):Ln=await qe(e.body.modelPath),Ln}async function c5e(e,t){let[n,s]=e.shape,r=U(e,[s*n]),a=mn(r,0),o=(await a.data())[0];if(ne([r,a]),o>t){let i=Es(r,0),l=Yl(i,n),u=(await l.data())[0],c=pe(i,Se(n,"int32")),p=(await c.data())[0];return ne([l,c]),[u,p,o]}return[0,0,o]}async function Bb(e,t){let n=(t.body.skipTime||0)>ue()-fN,s=Lb<(t.body.skipFrames||0);return t.skipAllowed&&n&&s&&Object.keys(us.keypoints).length>0?(Lb++,[us]):(Lb=0,new Promise(async r=>{var p;let a=J(()=>{if(!(Ln!=null&&Ln.inputs[0].shape))return null;let d=Ne.resizeBilinear(e,[Ln.inputs[0].shape[2],Ln.inputs[0].shape[1]],!1),h=L(d,nt.tf2);return he(h,nt.tf1)}),o;if(t.body.enabled&&(o=Ln==null?void 0:Ln.execute(a)),fN=ue(),ne(a),o){us.keypoints.length=0;let d=o.squeeze();ne(o);let h=d.unstack(2);ne(d);for(let f=0;f<h.length;f++){let[m,g,y]=await c5e(h[f],t.body.minConfidence);y>(((p=t.body)==null?void 0:p.minConfidence)||0)&&us.keypoints.push({score:Math.round(100*y)/100,part:Mb[f],positionRaw:[m/Ln.inputs[0].shape[2],g/Ln.inputs[0].shape[1]],position:[Math.round(e.shape[2]*m/Ln.inputs[0].shape[2]),Math.round(e.shape[1]*g/Ln.inputs[0].shape[1])]})}h.forEach(f=>ne(f))}us.score=us.keypoints.reduce((d,h)=>h.score>d?h.score:d,0);let i=us.keypoints.map(d=>d.position[0]),l=us.keypoints.map(d=>d.position[1]);us.box=[Math.min(...i),Math.min(...l),Math.max(...i)-Math.min(...i),Math.max(...l)-Math.min(...l)];let u=us.keypoints.map(d=>d.positionRaw[0]),c=us.keypoints.map(d=>d.positionRaw[1]);us.boxRaw=[Math.min(...u),Math.min(...c),Math.max(...u)-Math.min(...u),Math.max(...c)-Math.min(...c)];for(let[d,h]of Object.entries(zb)){let f=[];for(let m=0;m<h.length-1;m++){let g=us.keypoints.find(x=>x.part===h[m]),y=us.keypoints.find(x=>x.part===h[m+1]);g&&y&&g.score>(t.body.minConfidence||0)&&y.score>(t.body.minConfidence||0)&&f.push([g.position,y.position])}us.annotations[d]=f}r([us])}))}var d5e=["angry","disgust","fear","happy","sad","surprise","neutral"],er,X2=[],yN=0,AN=0,Wb=Number.MAX_SAFE_INTEGER;async function xN(e){var t;return fe.initial&&(er=null),er?e.debug&&ie("cached model:",er.modelUrl):er=await qe((t=e.face.emotion)==null?void 0:t.modelPath),er}async function Vb(e,t,n,s){var o,i;if(!er)return[];let r=Wb<(((o=t.face.emotion)==null?void 0:o.skipFrames)||0),a=(((i=t.face.emotion)==null?void 0:i.skipTime)||0)>ue()-AN;return t.skipAllowed&&a&&r&&yN===s&&X2[n]&&X2[n].length>0?(Wb++,X2[n]):(Wb=0,new Promise(async l=>{var c,p;let u=[];if((c=t.face.emotion)!=null&&c.enabled){let d={},h=er!=null&&er.inputs[0].shape?er.inputs[0].shape[2]:0;d.resize=Ne.resizeBilinear(e,[h,h],!1),d.channels=L(d.resize,nt.rgb),d.grayscale=ke(d.channels,3,!0),d.grayscaleSub=he(d.grayscale,nt.tf05),d.grayscaleMul=L(d.grayscaleSub,nt.tf2),d.emotion=er==null?void 0:er.execute(d.grayscaleMul),AN=ue();let f=await d.emotion.data();for(let m=0;m<f.length;m++)f[m]>(((p=t.face.emotion)==null?void 0:p.minConfidence)||0)&&u.push({score:Math.min(.99,Math.trunc(100*f[m])/100),emotion:d5e[m]});u.sort((m,g)=>g.score-m.score),Object.keys(d).forEach(m=>ne(d[m]))}X2[n]=u,yN=s,l(u)}))}var zs,Ub=[],vN=0,wN=0,kN=Number.MAX_SAFE_INTEGER;async function IN(e){return fe.initial&&(zs=null),zs?e.debug&&ie("cached model:",zs.modelUrl):zs=await qe(e.face.mobilefacenet.modelPath),zs}async function Gb(e,t,n,s){var o,i;if(!zs)return[];let r=kN<(((o=t.face.embedding)==null?void 0:o.skipFrames)||0),a=(((i=t.face.embedding)==null?void 0:i.skipTime)||0)>ue()-wN;return t.skipAllowed&&a&&r&&vN===s&&Ub[n]?(kN++,Ub[n]):new Promise(async l=>{var c;let u=[];if(((c=t.face.embedding)==null?void 0:c.enabled)&&(zs==null?void 0:zs.inputs[0].shape)){let p={};p.crop=Ne.resizeBilinear(e,[zs.inputs[0].shape[2],zs.inputs[0].shape[1]],!1),p.data=zs==null?void 0:zs.execute(p.crop);let d=await p.data.data();u=Array.from(d)}Ub[n]=u,vN=s,wN=ue(),l(u)})}var Ra,yi=0,p5e=2.3,Hb=gr.leftEyeLower0,jb=gr.rightEyeLower0,vd={leftBounds:[Hb[0],Hb[Hb.length-1]],rightBounds:[jb[0],jb[jb.length-1]]},wd={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function EN(e){var t;return fe.initial&&(Ra=null),Ra?e.debug&&ie("cached model:",Ra.modelUrl):Ra=await qe((t=e.face.iris)==null?void 0:t.modelPath),yi=Ra.inputs[0].shape?Ra.inputs[0].shape[2]:0,yi===-1&&(yi=64),Ra}function K2(e,t,n,s){for(let r=0;r<Sb.length;r++){let{key:a,indices:o}=Sb[r],i=gr[`${n}${a}`];if(!s||s.includes(a))for(let l=0;l<o.length;l++){let u=o[l];e[i[l]]=[t[u][0],t[u][1],(t[u][2]+e[i[l]][2])/2]}}}var h5e=e=>{let t=e[vd.leftBounds[0]][2],n=e[vd.rightBounds[0]][2];return t-n},CN=(e,t,n,s,r,a=!1)=>{let o=W2(B2(HT([e[n],e[s]]),p5e)),i=yd(o),l=Ne.cropAndResize(t,[[o.startPoint[1]/r,o.startPoint[0]/r,o.endPoint[1]/r,o.endPoint[0]/r]],[0],[yi,yi]);if(a&&fe.kernels.includes("flipleftright")){let u=Ne.flipLeftRight(l);ne(l),l=u}return{box:o,boxSize:i,crop:l}},TN=(e,t,n,s=!1)=>{let r=[];for(let a=0;a<wd.numCoordinates;a++){let o=e[a*3],i=e[a*3+1],l=e[a*3+2];r.push([(s?1-o/yi:o/yi)*n[0]+t.startPoint[0],i/yi*n[1]+t.startPoint[1],l])}return{rawCoords:r,iris:r.slice(wd.index)}},NN=(e,t,n)=>{let s=e[gr[`${n}EyeUpper0`][wd.upperCenter]][2],r=e[gr[`${n}EyeLower0`][wd.lowerCenter]][2],a=(s+r)/2;return t.map((o,i)=>{let l=a;return i===2?l=s:i===4&&(l=r),[o[0],o[1],l]})};async function RN(e,t,n,s){if(!Ra)return n.debug&&ie("face mesh iris detection requested, but model is not loaded"),e;let{box:r,boxSize:a,crop:o}=CN(e,t,vd.leftBounds[0],vd.leftBounds[1],s,!0),{box:i,boxSize:l,crop:u}=CN(e,t,vd.rightBounds[0],vd.rightBounds[1],s,!0),c=Ct([o,u]);ne(o),ne(u);let p=Ra.execute(c);ne(c);let d=await p.data();ne(p);let h=d.slice(0,wd.numCoordinates*3),{rawCoords:f,iris:m}=TN(h,r,a,!0),g=d.slice(wd.numCoordinates*3),{rawCoords:y,iris:x}=TN(g,i,l,!1),A=h5e(e);Math.abs(A)<30?(K2(e,f,"left",null),K2(e,y,"right",null)):A<1?K2(e,f,"left",["EyeUpper0","EyeLower0"]):K2(e,y,"right",["EyeUpper0","EyeLower0"]);let b=NN(e,m,"left"),w=NN(e,x,"right");return e.concat(b).concat(w)}var f5e=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],m5e=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],g5e=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],y5e=[[474,475],[475,476],[476,477],[477,474]],A5e=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],x5e=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],b5e=[[469,470],[470,471],[471,472],[472,469]],v5e=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]];function Ai(e){let t=e.map(n=>n[0]);return t.push(e[e.length-1][1]),t}var w5e={lips:Ai(f5e),leftEye:Ai(m5e),leftEyebrow:Ai(g5e),leftIris:Ai(y5e),rightEye:Ai(A5e),rightEyebrow:Ai(x5e),rightIris:Ai(b5e),faceOval:Ai(v5e)},k5e=Object.entries(w5e).map(([e,t])=>t.map(n=>[n,e])).flat(),Ake=new Map(k5e),Xh=[61,146,91,181,84,17,314,405,321,375,291,185,40,39,37,0,267,269,270,409,78,95,88,178,87,14,317,402,318,324,308,191,80,81,82,13,312,311,310,415,76,77,90,180,85,16,315,404,320,307,306,184,74,73,72,11,302,303,304,408,62,96,89,179,86,15,316,403,319,325,292,183,42,41,38,12,268,271,272,407],du=[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173,130,25,110,24,23,22,26,112,243,247,30,29,27,28,56,190,226,31,228,229,230,231,232,233,244,113,225,224,223,222,221,189,35,124,46,53,52,65,143,111,117,118,119,120,121,128,245,156,70,63,105,66,107,55,193],pu=[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398,359,255,339,254,253,252,256,341,463,467,260,259,257,258,286,414,446,261,448,449,450,451,452,453,464,342,445,444,443,442,441,413,265,353,276,283,282,295,372,340,346,347,348,349,350,357,465,383,300,293,334,296,336,285,417];async function $N(e,t){let n={lips:await t.filter(a=>a.size===160)[0].data(),irisL:await t.filter(a=>a.size===10)[0].data(),eyeL:await t.filter(a=>a.size===142)[0].data(),irisR:await t.filter(a=>a.size===10)[1].data(),eyeR:await t.filter(a=>a.size===142)[1].data()},s=du.reduce((a,o)=>a+=e[o][2],0)/du.length;for(let a=0;a<n.irisL.length/2;a++)e.push([n.irisL[2*a+0],n.irisL[2*a+1],s]);let r=pu.reduce((a,o)=>a+=e[o][2],0)/pu.length;for(let a=0;a<n.irisR.length/2;a++)e.push([n.irisR[2*a+0],n.irisR[2*a+1],r]);for(let a=0;a<n.eyeL.length/2;a++)e[du[a]]=[n.eyeL[2*a+0],n.eyeL[2*a+1],e[du[a]][2]];for(let a=0;a<n.eyeR.length/2;a++)e[pu[a]]=[n.eyeR[2*a+0],n.eyeR[2*a+1],e[pu[a]][2]];for(let a=0;a<n.lips.length/2;a++)e[Xh[a]]=[n.lips[2*a+0],n.lips[2*a+1],e[Xh[a]][2]];return e}var ta={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},Bn=null,hu=0;async function PN(e,t){var i,l,u,c,p,d,h,f,m,g,y;let n=(((i=t.face.detector)==null?void 0:i.skipTime)||0)>ue()-ta.timestamp,s=ta.skipped<(((l=t.face.detector)==null?void 0:l.skipFrames)||0);!t.skipAllowed||!n||!s||ta.boxes.length===0?(ta.boxes=await eN(e,t),ta.timestamp=ue(),ta.skipped=0):ta.skipped++;let r=[],a=[],o=0;for(let x=0;x<ta.boxes.length;x++){let A=ta.boxes[x],b=0,w,k={id:o++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,annotations:{}};if([b,w,k.tensor]=KT((u=t.face.detector)==null?void 0:u.rotation,A,e,(c=t.face.mesh)!=null&&c.enabled?hu:Ad()),(p=t==null?void 0:t.filter)!=null&&p.equalization){let S=await _2(k.tensor);ne(k.tensor),k.tensor=S}if(k.boxScore=Math.round(100*A.confidence)/100,(d=t.face.mesh)!=null&&d.enabled)if(!Bn)t.debug&&ie("face mesh detection requested, but model is not loaded");else{let S=Bn.execute(k.tensor),R=await S.find(P=>P.shape[P.shape.length-1]===1).data();if(k.faceScore=Math.round(100*R[0])/100,k.faceScore<(((h=t.face.detector)==null?void 0:h.minConfidence)||1)){if(A.confidence=k.faceScore,(f=t.face.mesh)!=null&&f.keepInvalid){k.box=z2(A,e),k.boxRaw=L2(A,e),k.score=k.boxScore,k.mesh=A.landmarks.map(P=>[(A.startPoint[0]+A.endPoint[0])/2+(A.endPoint[0]+A.startPoint[0])*P[0]/Ad(),(A.startPoint[1]+A.endPoint[1])/2+(A.endPoint[1]+A.startPoint[1])*P[1]/Ad()]),k.meshRaw=k.mesh.map(P=>[P[0]/(e.shape[2]||1),P[1]/(e.shape[1]||1),(P[2]||0)/hu]);for(let P of Object.keys(iu))k.annotations[P]=[k.mesh[iu[P]]]}}else{let P=S.find(F=>F.shape[F.shape.length-1]===1404),_=U(P,[-1,3]),$=await _.array();ne(_),(m=t.face.attention)!=null&&m.enabled?$=await $N($,S):(g=t.face.iris)!=null&&g.enabled&&($=await RN($,k.tensor,t,hu)),k.mesh=XT($,A,b,w,hu),k.meshRaw=k.mesh.map(F=>[F[0]/(e.shape[2]||0),F[1]/(e.shape[1]||0),(F[2]||0)/hu]);for(let F of Object.keys(gr))k.annotations[F]=gr[F].map(G=>k.mesh[G]);k.score=k.faceScore;let T={...ZT(k.mesh,A),confidence:A.confidence,landmarks:A.landmarks};k.box=z2(T,e),k.boxRaw=L2(T,e),a.push(T)}ne(S)}else{k.box=z2(A,e),k.boxRaw=L2(A,e),k.score=k.boxScore,k.mesh=A.landmarks.map(S=>[(A.startPoint[0]+A.endPoint[0])/2+(A.endPoint[0]+A.startPoint[0])*S[0]/Ad(),(A.startPoint[1]+A.endPoint[1])/2+(A.endPoint[1]+A.startPoint[1])*S[1]/Ad()]),k.meshRaw=k.mesh.map(S=>[S[0]/(e.shape[2]||0),S[1]/(e.shape[1]||0),(S[2]||0)/hu]);for(let S of Object.keys(iu))k.annotations[S]=[k.mesh[iu[S]]]}k.score>(((y=t.face.detector)==null?void 0:y.minConfidence)||1)?r.push(k):ne(k.tensor)}return ta.boxes=a,r}async function FN(e){var t,n,s,r,a,o;return fe.initial&&(Bn=null),((n=(t=e==null?void 0:e.face)==null?void 0:t.attention)==null?void 0:n.enabled)&&(Bn==null?void 0:Bn.signature)&&Object.keys(((s=Bn==null?void 0:Bn.signature)==null?void 0:s.outputs)||{}).length<6&&(Bn=null),Bn?e.debug&&ie("cached model:",Bn.modelUrl):(r=e.face.attention)!=null&&r.enabled?Bn=await qe((a=e.face.attention)==null?void 0:a.modelPath):Bn=await qe((o=e.face.mesh)==null?void 0:o.modelPath),hu=Bn.inputs[0].shape?Bn.inputs[0].shape[2]:0,Bn}var ON=lu,MN=Hh;var Ls,Z2=[],zN=0,LN=0,Xb=Number.MAX_SAFE_INTEGER;async function BN(e){var t;return fe.initial&&(Ls=null),Ls?e.debug&&ie("cached model:",Ls.modelUrl):Ls=await qe((t=e.face.description)==null?void 0:t.modelPath),Ls}function Kb(e){let t=e.image||e.tensor||e;if(!(Ls!=null&&Ls.inputs[0].shape))return t;let n=Ne.resizeBilinear(t,[Ls.inputs[0].shape[2],Ls.inputs[0].shape[1]],!1),s=L(n,nt.tf255);return ne(n),s}async function Zb(e,t,n,s){var o,i,l,u;if(!Ls)return{age:0,gender:"unknown",genderScore:0,descriptor:[]};let r=Xb<(((o=t.face.description)==null?void 0:o.skipFrames)||0),a=(((i=t.face.description)==null?void 0:i.skipTime)||0)>ue()-zN;return t.skipAllowed&&r&&a&&LN===s&&((l=Z2[n])==null?void 0:l.age)&&((u=Z2[n])==null?void 0:u.age)>0?(Xb++,Z2[n]):(Xb=0,new Promise(async c=>{var d,h;let p={age:0,gender:"unknown",genderScore:0,descriptor:[]};if((d=t.face.description)!=null&&d.enabled){let f=Kb(e),m=Ls==null?void 0:Ls.execute(f);zN=ue(),ne(f);let y=await(await m.find(R=>R.shape[1]===1)).data(),x=Math.trunc(200*Math.abs(y[0]-.5))/100;x>(((h=t.face.description)==null?void 0:h.minConfidence)||0)&&(p.gender=y[0]<=.5?"female":"male",p.genderScore=Math.min(.99,x));let A=Es(m.find(R=>R.shape[1]===100),1),b=(await A.data())[0];ne(A);let k=await m.find(R=>R.shape[1]===100).data();p.age=Math.round(k[b-1]>k[b+1]?10*b-100*k[b-1]:10*b+100*k[b+1])/10;let S=m.find(R=>R.shape[1]===1024),E=S?await S.data():[];p.descriptor=Array.from(E),m.forEach(R=>ne(R))}Z2[n]=p,LN=s,c(p)}))}function Y2(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function Kh(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function UN(e,t,n){let s=t.shape[1],r=t.shape[2],a=[[e.startPoint[1]/s,e.startPoint[0]/r,e.endPoint[1]/s,e.endPoint[0]/r]];return Ne.cropAndResize(t,a,[0],n)}function GN(e,t){let n=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],s=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],r=e.palmLandmarks.map(a=>[a[0]*t[0],a[1]*t[1]]);return{startPoint:n,endPoint:s,palmLandmarks:r,confidence:e.confidence}}function J2(e,t=1.5){let n=Kh(e),s=Y2(e),r=[t*s[0]/2,t*s[1]/2],a=[n[0]-r[0],n[1]-r[1]],o=[n[0]+r[0],n[1]+r[1]];return{startPoint:a,endPoint:o,palmLandmarks:e.palmLandmarks}}function Q2(e){let t=Kh(e),n=Y2(e),r=Math.max(...n)/2,a=[t[0]-r,t[1]-r],o=[t[0]+r,t[1]+r];return{startPoint:a,endPoint:o,palmLandmarks:e.palmLandmarks}}function S5e(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function HN(e,t){let n=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return S5e(n)}var WN=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function xi(e,t){let n=0;for(let s=0;s<e.length;s++)n+=e[s]*t[s];return n}function C5e(e,t){let n=[];for(let s=0;s<e.length;s++)n.push(e[s][t]);return n}function VN(e,t){let n=[],s=e.length;for(let r=0;r<s;r++){n.push([]);for(let a=0;a<s;a++)n[r].push(xi(e[r],C5e(t,a)))}return n}function Jb(e,t){let n=Math.cos(e),s=Math.sin(e),r=[[n,-s,0],[s,n,0],[0,0,1]],a=WN(t[0],t[1]),o=VN(a,r),i=WN(-t[0],-t[1]);return VN(o,i)}function jN(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],n=[e[0][2],e[1][2]],s=[-xi(t[0],n),-xi(t[1],n)];return[t[0].concat(s[0]),t[1].concat(s[1]),[0,0,1]]}function Qb(e,t){return[xi(e,t[0]),xi(e,t[1])]}var XN=[{x:.015625,y:.015625},{x:.015625,y:.015625},{x:.046875,y:.015625},{x:.046875,y:.015625},{x:.078125,y:.015625},{x:.078125,y:.015625},{x:.109375,y:.015625},{x:.109375,y:.015625},{x:.140625,y:.015625},{x:.140625,y:.015625},{x:.171875,y:.015625},{x:.171875,y:.015625},{x:.203125,y:.015625},{x:.203125,y:.015625},{x:.234375,y:.015625},{x:.234375,y:.015625},{x:.265625,y:.015625},{x:.265625,y:.015625},{x:.296875,y:.015625},{x:.296875,y:.015625},{x:.328125,y:.015625},{x:.328125,y:.015625},{x:.359375,y:.015625},{x:.359375,y:.015625},{x:.390625,y:.015625},{x:.390625,y:.015625},{x:.421875,y:.015625},{x:.421875,y:.015625},{x:.453125,y:.015625},{x:.453125,y:.015625},{x:.484375,y:.015625},{x:.484375,y:.015625},{x:.515625,y:.015625},{x:.515625,y:.015625},{x:.546875,y:.015625},{x:.546875,y:.015625},{x:.578125,y:.015625},{x:.578125,y:.015625},{x:.609375,y:.015625},{x:.609375,y:.015625},{x:.640625,y:.015625},{x:.640625,y:.015625},{x:.671875,y:.015625},{x:.671875,y:.015625},{x:.703125,y:.015625},{x:.703125,y:.015625},{x:.734375,y:.015625},{x:.734375,y:.015625},{x:.765625,y:.015625},{x:.765625,y:.015625},{x:.796875,y:.015625},{x:.796875,y:.015625},{x:.828125,y:.015625},{x:.828125,y:.015625},{x:.859375,y:.015625},{x:.859375,y:.015625},{x:.890625,y:.015625},{x:.890625,y:.015625},{x:.921875,y:.015625},{x:.921875,y:.015625},{x:.953125,y:.015625},{x:.953125,y:.015625},{x:.984375,y:.015625},{x:.984375,y:.015625},{x:.015625,y:.046875},{x:.015625,y:.046875},{x:.046875,y:.046875},{x:.046875,y:.046875},{x:.078125,y:.046875},{x:.078125,y:.046875},{x:.109375,y:.046875},{x:.109375,y:.046875},{x:.140625,y:.046875},{x:.140625,y:.046875},{x:.171875,y:.046875},{x:.171875,y:.046875},{x:.203125,y:.046875},{x:.203125,y:.046875},{x:.234375,y:.046875},{x:.234375,y:.046875},{x:.265625,y:.046875},{x:.265625,y:.046875},{x:.296875,y:.046875},{x:.296875,y:.046875},{x:.328125,y:.046875},{x:.328125,y:.046875},{x:.359375,y:.046875},{x:.359375,y:.046875},{x:.390625,y:.046875},{x:.390625,y:.046875},{x:.421875,y:.046875},{x:.421875,y:.046875},{x:.453125,y:.046875},{x:.453125,y:.046875},{x:.484375,y:.046875},{x:.484375,y:.046875},{x:.515625,y:.046875},{x:.515625,y:.046875},{x:.546875,y:.046875},{x:.546875,y:.046875},{x:.578125,y:.046875},{x:.578125,y:.046875},{x:.609375,y:.046875},{x:.609375,y:.046875},{x:.640625,y:.046875},{x:.640625,y:.046875},{x:.671875,y:.046875},{x:.671875,y:.046875},{x:.703125,y:.046875},{x:.703125,y:.046875},{x:.734375,y:.046875},{x:.734375,y:.046875},{x:.765625,y:.046875},{x:.765625,y:.046875},{x:.796875,y:.046875},{x:.796875,y:.046875},{x:.828125,y:.046875},{x:.828125,y:.046875},{x:.859375,y:.046875},{x:.859375,y:.046875},{x:.890625,y:.046875},{x:.890625,y:.046875},{x:.921875,y:.046875},{x:.921875,y:.046875},{x:.953125,y:.046875},{x:.953125,y:.046875},{x:.984375,y:.046875},{x:.984375,y:.046875},{x:.015625,y:.078125},{x:.015625,y:.078125},{x:.046875,y:.078125},{x:.046875,y:.078125},{x:.078125,y:.078125},{x:.078125,y:.078125},{x:.109375,y:.078125},{x:.109375,y:.078125},{x:.140625,y:.078125},{x:.140625,y:.078125},{x:.171875,y:.078125},{x:.171875,y:.078125},{x:.203125,y:.078125},{x:.203125,y:.078125},{x:.234375,y:.078125},{x:.234375,y:.078125},{x:.265625,y:.078125},{x:.265625,y:.078125},{x:.296875,y:.078125},{x:.296875,y:.078125},{x:.328125,y:.078125},{x:.328125,y:.078125},{x:.359375,y:.078125},{x:.359375,y:.078125},{x:.390625,y:.078125},{x:.390625,y:.078125},{x:.421875,y:.078125},{x:.421875,y:.078125},{x:.453125,y:.078125},{x:.453125,y:.078125},{x:.484375,y:.078125},{x:.484375,y:.078125},{x:.515625,y:.078125},{x:.515625,y:.078125},{x:.546875,y:.078125},{x:.546875,y:.078125},{x:.578125,y:.078125},{x:.578125,y:.078125},{x:.609375,y:.078125},{x:.609375,y:.078125},{x:.640625,y:.078125},{x:.640625,y:.078125},{x:.671875,y:.078125},{x:.671875,y:.078125},{x:.703125,y:.078125},{x:.703125,y:.078125},{x:.734375,y:.078125},{x:.734375,y:.078125},{x:.765625,y:.078125},{x:.765625,y:.078125},{x:.796875,y:.078125},{x:.796875,y:.078125},{x:.828125,y:.078125},{x:.828125,y:.078125},{x:.859375,y:.078125},{x:.859375,y:.078125},{x:.890625,y:.078125},{x:.890625,y:.078125},{x:.921875,y:.078125},{x:.921875,y:.078125},{x:.953125,y:.078125},{x:.953125,y:.078125},{x:.984375,y:.078125},{x:.984375,y:.078125},{x:.015625,y:.109375},{x:.015625,y:.109375},{x:.046875,y:.109375},{x:.046875,y:.109375},{x:.078125,y:.109375},{x:.078125,y:.109375},{x:.109375,y:.109375},{x:.109375,y:.109375},{x:.140625,y:.109375},{x:.140625,y:.109375},{x:.171875,y:.109375},{x:.171875,y:.109375},{x:.203125,y:.109375},{x:.203125,y:.109375},{x:.234375,y:.109375},{x:.234375,y:.109375},{x:.265625,y:.109375},{x:.265625,y:.109375},{x:.296875,y:.109375},{x:.296875,y:.109375},{x:.328125,y:.109375},{x:.328125,y:.109375},{x:.359375,y:.109375},{x:.359375,y:.109375},{x:.390625,y:.109375},{x:.390625,y:.109375},{x:.421875,y:.109375},{x:.421875,y:.109375},{x:.453125,y:.109375},{x:.453125,y:.109375},{x:.484375,y:.109375},{x:.484375,y:.109375},{x:.515625,y:.109375},{x:.515625,y:.109375},{x:.546875,y:.109375},{x:.546875,y:.109375},{x:.578125,y:.109375},{x:.578125,y:.109375},{x:.609375,y:.109375},{x:.609375,y:.109375},{x:.640625,y:.109375},{x:.640625,y:.109375},{x:.671875,y:.109375},{x:.671875,y:.109375},{x:.703125,y:.109375},{x:.703125,y:.109375},{x:.734375,y:.109375},{x:.734375,y:.109375},{x:.765625,y:.109375},{x:.765625,y:.109375},{x:.796875,y:.109375},{x:.796875,y:.109375},{x:.828125,y:.109375},{x:.828125,y:.109375},{x:.859375,y:.109375},{x:.859375,y:.109375},{x:.890625,y:.109375},{x:.890625,y:.109375},{x:.921875,y:.109375},{x:.921875,y:.109375},{x:.953125,y:.109375},{x:.953125,y:.109375},{x:.984375,y:.109375},{x:.984375,y:.109375},{x:.015625,y:.140625},{x:.015625,y:.140625},{x:.046875,y:.140625},{x:.046875,y:.140625},{x:.078125,y:.140625},{x:.078125,y:.140625},{x:.109375,y:.140625},{x:.109375,y:.140625},{x:.140625,y:.140625},{x:.140625,y:.140625},{x:.171875,y:.140625},{x:.171875,y:.140625},{x:.203125,y:.140625},{x:.203125,y:.140625},{x:.234375,y:.140625},{x:.234375,y:.140625},{x:.265625,y:.140625},{x:.265625,y:.140625},{x:.296875,y:.140625},{x:.296875,y:.140625},{x:.328125,y:.140625},{x:.328125,y:.140625},{x:.359375,y:.140625},{x:.359375,y:.140625},{x:.390625,y:.140625},{x:.390625,y:.140625},{x:.421875,y:.140625},{x:.421875,y:.140625},{x:.453125,y:.140625},{x:.453125,y:.140625},{x:.484375,y:.140625},{x:.484375,y:.140625},{x:.515625,y:.140625},{x:.515625,y:.140625},{x:.546875,y:.140625},{x:.546875,y:.140625},{x:.578125,y:.140625},{x:.578125,y:.140625},{x:.609375,y:.140625},{x:.609375,y:.140625},{x:.640625,y:.140625},{x:.640625,y:.140625},{x:.671875,y:.140625},{x:.671875,y:.140625},{x:.703125,y:.140625},{x:.703125,y:.140625},{x:.734375,y:.140625},{x:.734375,y:.140625},{x:.765625,y:.140625},{x:.765625,y:.140625},{x:.796875,y:.140625},{x:.796875,y:.140625},{x:.828125,y:.140625},{x:.828125,y:.140625},{x:.859375,y:.140625},{x:.859375,y:.140625},{x:.890625,y:.140625},{x:.890625,y:.140625},{x:.921875,y:.140625},{x:.921875,y:.140625},{x:.953125,y:.140625},{x:.953125,y:.140625},{x:.984375,y:.140625},{x:.984375,y:.140625},{x:.015625,y:.171875},{x:.015625,y:.171875},{x:.046875,y:.171875},{x:.046875,y:.171875},{x:.078125,y:.171875},{x:.078125,y:.171875},{x:.109375,y:.171875},{x:.109375,y:.171875},{x:.140625,y:.171875},{x:.140625,y:.171875},{x:.171875,y:.171875},{x:.171875,y:.171875},{x:.203125,y:.171875},{x:.203125,y:.171875},{x:.234375,y:.171875},{x:.234375,y:.171875},{x:.265625,y:.171875},{x:.265625,y:.171875},{x:.296875,y:.171875},{x:.296875,y:.171875},{x:.328125,y:.171875},{x:.328125,y:.171875},{x:.359375,y:.171875},{x:.359375,y:.171875},{x:.390625,y:.171875},{x:.390625,y:.171875},{x:.421875,y:.171875},{x:.421875,y:.171875},{x:.453125,y:.171875},{x:.453125,y:.171875},{x:.484375,y:.171875},{x:.484375,y:.171875},{x:.515625,y:.171875},{x:.515625,y:.171875},{x:.546875,y:.171875},{x:.546875,y:.171875},{x:.578125,y:.171875},{x:.578125,y:.171875},{x:.609375,y:.171875},{x:.609375,y:.171875},{x:.640625,y:.171875},{x:.640625,y:.171875},{x:.671875,y:.171875},{x:.671875,y:.171875},{x:.703125,y:.171875},{x:.703125,y:.171875},{x:.734375,y:.171875},{x:.734375,y:.171875},{x:.765625,y:.171875},{x:.765625,y:.171875},{x:.796875,y:.171875},{x:.796875,y:.171875},{x:.828125,y:.171875},{x:.828125,y:.171875},{x:.859375,y:.171875},{x:.859375,y:.171875},{x:.890625,y:.171875},{x:.890625,y:.171875},{x:.921875,y:.171875},{x:.921875,y:.171875},{x:.953125,y:.171875},{x:.953125,y:.171875},{x:.984375,y:.171875},{x:.984375,y:.171875},{x:.015625,y:.203125},{x:.015625,y:.203125},{x:.046875,y:.203125},{x:.046875,y:.203125},{x:.078125,y:.203125},{x:.078125,y:.203125},{x:.109375,y:.203125},{x:.109375,y:.203125},{x:.140625,y:.203125},{x:.140625,y:.203125},{x:.171875,y:.203125},{x:.171875,y:.203125},{x:.203125,y:.203125},{x:.203125,y:.203125},{x:.234375,y:.203125},{x:.234375,y:.203125},{x:.265625,y:.203125},{x:.265625,y:.203125},{x:.296875,y:.203125},{x:.296875,y:.203125},{x:.328125,y:.203125},{x:.328125,y:.203125},{x:.359375,y:.203125},{x:.359375,y:.203125},{x:.390625,y:.203125},{x:.390625,y:.203125},{x:.421875,y:.203125},{x:.421875,y:.203125},{x:.453125,y:.203125},{x:.453125,y:.203125},{x:.484375,y:.203125},{x:.484375,y:.203125},{x:.515625,y:.203125},{x:.515625,y:.203125},{x:.546875,y:.203125},{x:.546875,y:.203125},{x:.578125,y:.203125},{x:.578125,y:.203125},{x:.609375,y:.203125},{x:.609375,y:.203125},{x:.640625,y:.203125},{x:.640625,y:.203125},{x:.671875,y:.203125},{x:.671875,y:.203125},{x:.703125,y:.203125},{x:.703125,y:.203125},{x:.734375,y:.203125},{x:.734375,y:.203125},{x:.765625,y:.203125},{x:.765625,y:.203125},{x:.796875,y:.203125},{x:.796875,y:.203125},{x:.828125,y:.203125},{x:.828125,y:.203125},{x:.859375,y:.203125},{x:.859375,y:.203125},{x:.890625,y:.203125},{x:.890625,y:.203125},{x:.921875,y:.203125},{x:.921875,y:.203125},{x:.953125,y:.203125},{x:.953125,y:.203125},{x:.984375,y:.203125},{x:.984375,y:.203125},{x:.015625,y:.234375},{x:.015625,y:.234375},{x:.046875,y:.234375},{x:.046875,y:.234375},{x:.078125,y:.234375},{x:.078125,y:.234375},{x:.109375,y:.234375},{x:.109375,y:.234375},{x:.140625,y:.234375},{x:.140625,y:.234375},{x:.171875,y:.234375},{x:.171875,y:.234375},{x:.203125,y:.234375},{x:.203125,y:.234375},{x:.234375,y:.234375},{x:.234375,y:.234375},{x:.265625,y:.234375},{x:.265625,y:.234375},{x:.296875,y:.234375},{x:.296875,y:.234375},{x:.328125,y:.234375},{x:.328125,y:.234375},{x:.359375,y:.234375},{x:.359375,y:.234375},{x:.390625,y:.234375},{x:.390625,y:.234375},{x:.421875,y:.234375},{x:.421875,y:.234375},{x:.453125,y:.234375},{x:.453125,y:.234375},{x:.484375,y:.234375},{x:.484375,y:.234375},{x:.515625,y:.234375},{x:.515625,y:.234375},{x:.546875,y:.234375},{x:.546875,y:.234375},{x:.578125,y:.234375},{x:.578125,y:.234375},{x:.609375,y:.234375},{x:.609375,y:.234375},{x:.640625,y:.234375},{x:.640625,y:.234375},{x:.671875,y:.234375},{x:.671875,y:.234375},{x:.703125,y:.234375},{x:.703125,y:.234375},{x:.734375,y:.234375},{x:.734375,y:.234375},{x:.765625,y:.234375},{x:.765625,y:.234375},{x:.796875,y:.234375},{x:.796875,y:.234375},{x:.828125,y:.234375},{x:.828125,y:.234375},{x:.859375,y:.234375},{x:.859375,y:.234375},{x:.890625,y:.234375},{x:.890625,y:.234375},{x:.921875,y:.234375},{x:.921875,y:.234375},{x:.953125,y:.234375},{x:.953125,y:.234375},{x:.984375,y:.234375},{x:.984375,y:.234375},{x:.015625,y:.265625},{x:.015625,y:.265625},{x:.046875,y:.265625},{x:.046875,y:.265625},{x:.078125,y:.265625},{x:.078125,y:.265625},{x:.109375,y:.265625},{x:.109375,y:.265625},{x:.140625,y:.265625},{x:.140625,y:.265625},{x:.171875,y:.265625},{x:.171875,y:.265625},{x:.203125,y:.265625},{x:.203125,y:.265625},{x:.234375,y:.265625},{x:.234375,y:.265625},{x:.265625,y:.265625},{x:.265625,y:.265625},{x:.296875,y:.265625},{x:.296875,y:.265625},{x:.328125,y:.265625},{x:.328125,y:.265625},{x:.359375,y:.265625},{x:.359375,y:.265625},{x:.390625,y:.265625},{x:.390625,y:.265625},{x:.421875,y:.265625},{x:.421875,y:.265625},{x:.453125,y:.265625},{x:.453125,y:.265625},{x:.484375,y:.265625},{x:.484375,y:.265625},{x:.515625,y:.265625},{x:.515625,y:.265625},{x:.546875,y:.265625},{x:.546875,y:.265625},{x:.578125,y:.265625},{x:.578125,y:.265625},{x:.609375,y:.265625},{x:.609375,y:.265625},{x:.640625,y:.265625},{x:.640625,y:.265625},{x:.671875,y:.265625},{x:.671875,y:.265625},{x:.703125,y:.265625},{x:.703125,y:.265625},{x:.734375,y:.265625},{x:.734375,y:.265625},{x:.765625,y:.265625},{x:.765625,y:.265625},{x:.796875,y:.265625},{x:.796875,y:.265625},{x:.828125,y:.265625},{x:.828125,y:.265625},{x:.859375,y:.265625},{x:.859375,y:.265625},{x:.890625,y:.265625},{x:.890625,y:.265625},{x:.921875,y:.265625},{x:.921875,y:.265625},{x:.953125,y:.265625},{x:.953125,y:.265625},{x:.984375,y:.265625},{x:.984375,y:.265625},{x:.015625,y:.296875},{x:.015625,y:.296875},{x:.046875,y:.296875},{x:.046875,y:.296875},{x:.078125,y:.296875},{x:.078125,y:.296875},{x:.109375,y:.296875},{x:.109375,y:.296875},{x:.140625,y:.296875},{x:.140625,y:.296875},{x:.171875,y:.296875},{x:.171875,y:.296875},{x:.203125,y:.296875},{x:.203125,y:.296875},{x:.234375,y:.296875},{x:.234375,y:.296875},{x:.265625,y:.296875},{x:.265625,y:.296875},{x:.296875,y:.296875},{x:.296875,y:.296875},{x:.328125,y:.296875},{x:.328125,y:.296875},{x:.359375,y:.296875},{x:.359375,y:.296875},{x:.390625,y:.296875},{x:.390625,y:.296875},{x:.421875,y:.296875},{x:.421875,y:.296875},{x:.453125,y:.296875},{x:.453125,y:.296875},{x:.484375,y:.296875},{x:.484375,y:.296875},{x:.515625,y:.296875},{x:.515625,y:.296875},{x:.546875,y:.296875},{x:.546875,y:.296875},{x:.578125,y:.296875},{x:.578125,y:.296875},{x:.609375,y:.296875},{x:.609375,y:.296875},{x:.640625,y:.296875},{x:.640625,y:.296875},{x:.671875,y:.296875},{x:.671875,y:.296875},{x:.703125,y:.296875},{x:.703125,y:.296875},{x:.734375,y:.296875},{x:.734375,y:.296875},{x:.765625,y:.296875},{x:.765625,y:.296875},{x:.796875,y:.296875},{x:.796875,y:.296875},{x:.828125,y:.296875},{x:.828125,y:.296875},{x:.859375,y:.296875},{x:.859375,y:.296875},{x:.890625,y:.296875},{x:.890625,y:.296875},{x:.921875,y:.296875},{x:.921875,y:.296875},{x:.953125,y:.296875},{x:.953125,y:.296875},{x:.984375,y:.296875},{x:.984375,y:.296875},{x:.015625,y:.328125},{x:.015625,y:.328125},{x:.046875,y:.328125},{x:.046875,y:.328125},{x:.078125,y:.328125},{x:.078125,y:.328125},{x:.109375,y:.328125},{x:.109375,y:.328125},{x:.140625,y:.328125},{x:.140625,y:.328125},{x:.171875,y:.328125},{x:.171875,y:.328125},{x:.203125,y:.328125},{x:.203125,y:.328125},{x:.234375,y:.328125},{x:.234375,y:.328125},{x:.265625,y:.328125},{x:.265625,y:.328125},{x:.296875,y:.328125},{x:.296875,y:.328125},{x:.328125,y:.328125},{x:.328125,y:.328125},{x:.359375,y:.328125},{x:.359375,y:.328125},{x:.390625,y:.328125},{x:.390625,y:.328125},{x:.421875,y:.328125},{x:.421875,y:.328125},{x:.453125,y:.328125},{x:.453125,y:.328125},{x:.484375,y:.328125},{x:.484375,y:.328125},{x:.515625,y:.328125},{x:.515625,y:.328125},{x:.546875,y:.328125},{x:.546875,y:.328125},{x:.578125,y:.328125},{x:.578125,y:.328125},{x:.609375,y:.328125},{x:.609375,y:.328125},{x:.640625,y:.328125},{x:.640625,y:.328125},{x:.671875,y:.328125},{x:.671875,y:.328125},{x:.703125,y:.328125},{x:.703125,y:.328125},{x:.734375,y:.328125},{x:.734375,y:.328125},{x:.765625,y:.328125},{x:.765625,y:.328125},{x:.796875,y:.328125},{x:.796875,y:.328125},{x:.828125,y:.328125},{x:.828125,y:.328125},{x:.859375,y:.328125},{x:.859375,y:.328125},{x:.890625,y:.328125},{x:.890625,y:.328125},{x:.921875,y:.328125},{x:.921875,y:.328125},{x:.953125,y:.328125},{x:.953125,y:.328125},{x:.984375,y:.328125},{x:.984375,y:.328125},{x:.015625,y:.359375},{x:.015625,y:.359375},{x:.046875,y:.359375},{x:.046875,y:.359375},{x:.078125,y:.359375},{x:.078125,y:.359375},{x:.109375,y:.359375},{x:.109375,y:.359375},{x:.140625,y:.359375},{x:.140625,y:.359375},{x:.171875,y:.359375},{x:.171875,y:.359375},{x:.203125,y:.359375},{x:.203125,y:.359375},{x:.234375,y:.359375},{x:.234375,y:.359375},{x:.265625,y:.359375},{x:.265625,y:.359375},{x:.296875,y:.359375},{x:.296875,y:.359375},{x:.328125,y:.359375},{x:.328125,y:.359375},{x:.359375,y:.359375},{x:.359375,y:.359375},{x:.390625,y:.359375},{x:.390625,y:.359375},{x:.421875,y:.359375},{x:.421875,y:.359375},{x:.453125,y:.359375},{x:.453125,y:.359375},{x:.484375,y:.359375},{x:.484375,y:.359375},{x:.515625,y:.359375},{x:.515625,y:.359375},{x:.546875,y:.359375},{x:.546875,y:.359375},{x:.578125,y:.359375},{x:.578125,y:.359375},{x:.609375,y:.359375},{x:.609375,y:.359375},{x:.640625,y:.359375},{x:.640625,y:.359375},{x:.671875,y:.359375},{x:.671875,y:.359375},{x:.703125,y:.359375},{x:.703125,y:.359375},{x:.734375,y:.359375},{x:.734375,y:.359375},{x:.765625,y:.359375},{x:.765625,y:.359375},{x:.796875,y:.359375},{x:.796875,y:.359375},{x:.828125,y:.359375},{x:.828125,y:.359375},{x:.859375,y:.359375},{x:.859375,y:.359375},{x:.890625,y:.359375},{x:.890625,y:.359375},{x:.921875,y:.359375},{x:.921875,y:.359375},{x:.953125,y:.359375},{x:.953125,y:.359375},{x:.984375,y:.359375},{x:.984375,y:.359375},{x:.015625,y:.390625},{x:.015625,y:.390625},{x:.046875,y:.390625},{x:.046875,y:.390625},{x:.078125,y:.390625},{x:.078125,y:.390625},{x:.109375,y:.390625},{x:.109375,y:.390625},{x:.140625,y:.390625},{x:.140625,y:.390625},{x:.171875,y:.390625},{x:.171875,y:.390625},{x:.203125,y:.390625},{x:.203125,y:.390625},{x:.234375,y:.390625},{x:.234375,y:.390625},{x:.265625,y:.390625},{x:.265625,y:.390625},{x:.296875,y:.390625},{x:.296875,y:.390625},{x:.328125,y:.390625},{x:.328125,y:.390625},{x:.359375,y:.390625},{x:.359375,y:.390625},{x:.390625,y:.390625},{x:.390625,y:.390625},{x:.421875,y:.390625},{x:.421875,y:.390625},{x:.453125,y:.390625},{x:.453125,y:.390625},{x:.484375,y:.390625},{x:.484375,y:.390625},{x:.515625,y:.390625},{x:.515625,y:.390625},{x:.546875,y:.390625},{x:.546875,y:.390625},{x:.578125,y:.390625},{x:.578125,y:.390625},{x:.609375,y:.390625},{x:.609375,y:.390625},{x:.640625,y:.390625},{x:.640625,y:.390625},{x:.671875,y:.390625},{x:.671875,y:.390625},{x:.703125,y:.390625},{x:.703125,y:.390625},{x:.734375,y:.390625},{x:.734375,y:.390625},{x:.765625,y:.390625},{x:.765625,y:.390625},{x:.796875,y:.390625},{x:.796875,y:.390625},{x:.828125,y:.390625},{x:.828125,y:.390625},{x:.859375,y:.390625},{x:.859375,y:.390625},{x:.890625,y:.390625},{x:.890625,y:.390625},{x:.921875,y:.390625},{x:.921875,y:.390625},{x:.953125,y:.390625},{x:.953125,y:.390625},{x:.984375,y:.390625},{x:.984375,y:.390625},{x:.015625,y:.421875},{x:.015625,y:.421875},{x:.046875,y:.421875},{x:.046875,y:.421875},{x:.078125,y:.421875},{x:.078125,y:.421875},{x:.109375,y:.421875},{x:.109375,y:.421875},{x:.140625,y:.421875},{x:.140625,y:.421875},{x:.171875,y:.421875},{x:.171875,y:.421875},{x:.203125,y:.421875},{x:.203125,y:.421875},{x:.234375,y:.421875},{x:.234375,y:.421875},{x:.265625,y:.421875},{x:.265625,y:.421875},{x:.296875,y:.421875},{x:.296875,y:.421875},{x:.328125,y:.421875},{x:.328125,y:.421875},{x:.359375,y:.421875},{x:.359375,y:.421875},{x:.390625,y:.421875},{x:.390625,y:.421875},{x:.421875,y:.421875},{x:.421875,y:.421875},{x:.453125,y:.421875},{x:.453125,y:.421875},{x:.484375,y:.421875},{x:.484375,y:.421875},{x:.515625,y:.421875},{x:.515625,y:.421875},{x:.546875,y:.421875},{x:.546875,y:.421875},{x:.578125,y:.421875},{x:.578125,y:.421875},{x:.609375,y:.421875},{x:.609375,y:.421875},{x:.640625,y:.421875},{x:.640625,y:.421875},{x:.671875,y:.421875},{x:.671875,y:.421875},{x:.703125,y:.421875},{x:.703125,y:.421875},{x:.734375,y:.421875},{x:.734375,y:.421875},{x:.765625,y:.421875},{x:.765625,y:.421875},{x:.796875,y:.421875},{x:.796875,y:.421875},{x:.828125,y:.421875},{x:.828125,y:.421875},{x:.859375,y:.421875},{x:.859375,y:.421875},{x:.890625,y:.421875},{x:.890625,y:.421875},{x:.921875,y:.421875},{x:.921875,y:.421875},{x:.953125,y:.421875},{x:.953125,y:.421875},{x:.984375,y:.421875},{x:.984375,y:.421875},{x:.015625,y:.453125},{x:.015625,y:.453125},{x:.046875,y:.453125},{x:.046875,y:.453125},{x:.078125,y:.453125},{x:.078125,y:.453125},{x:.109375,y:.453125},{x:.109375,y:.453125},{x:.140625,y:.453125},{x:.140625,y:.453125},{x:.171875,y:.453125},{x:.171875,y:.453125},{x:.203125,y:.453125},{x:.203125,y:.453125},{x:.234375,y:.453125},{x:.234375,y:.453125},{x:.265625,y:.453125},{x:.265625,y:.453125},{x:.296875,y:.453125},{x:.296875,y:.453125},{x:.328125,y:.453125},{x:.328125,y:.453125},{x:.359375,y:.453125},{x:.359375,y:.453125},{x:.390625,y:.453125},{x:.390625,y:.453125},{x:.421875,y:.453125},{x:.421875,y:.453125},{x:.453125,y:.453125},{x:.453125,y:.453125},{x:.484375,y:.453125},{x:.484375,y:.453125},{x:.515625,y:.453125},{x:.515625,y:.453125},{x:.546875,y:.453125},{x:.546875,y:.453125},{x:.578125,y:.453125},{x:.578125,y:.453125},{x:.609375,y:.453125},{x:.609375,y:.453125},{x:.640625,y:.453125},{x:.640625,y:.453125},{x:.671875,y:.453125},{x:.671875,y:.453125},{x:.703125,y:.453125},{x:.703125,y:.453125},{x:.734375,y:.453125},{x:.734375,y:.453125},{x:.765625,y:.453125},{x:.765625,y:.453125},{x:.796875,y:.453125},{x:.796875,y:.453125},{x:.828125,y:.453125},{x:.828125,y:.453125},{x:.859375,y:.453125},{x:.859375,y:.453125},{x:.890625,y:.453125},{x:.890625,y:.453125},{x:.921875,y:.453125},{x:.921875,y:.453125},{x:.953125,y:.453125},{x:.953125,y:.453125},{x:.984375,y:.453125},{x:.984375,y:.453125},{x:.015625,y:.484375},{x:.015625,y:.484375},{x:.046875,y:.484375},{x:.046875,y:.484375},{x:.078125,y:.484375},{x:.078125,y:.484375},{x:.109375,y:.484375},{x:.109375,y:.484375},{x:.140625,y:.484375},{x:.140625,y:.484375},{x:.171875,y:.484375},{x:.171875,y:.484375},{x:.203125,y:.484375},{x:.203125,y:.484375},{x:.234375,y:.484375},{x:.234375,y:.484375},{x:.265625,y:.484375},{x:.265625,y:.484375},{x:.296875,y:.484375},{x:.296875,y:.484375},{x:.328125,y:.484375},{x:.328125,y:.484375},{x:.359375,y:.484375},{x:.359375,y:.484375},{x:.390625,y:.484375},{x:.390625,y:.484375},{x:.421875,y:.484375},{x:.421875,y:.484375},{x:.453125,y:.484375},{x:.453125,y:.484375},{x:.484375,y:.484375},{x:.484375,y:.484375},{x:.515625,y:.484375},{x:.515625,y:.484375},{x:.546875,y:.484375},{x:.546875,y:.484375},{x:.578125,y:.484375},{x:.578125,y:.484375},{x:.609375,y:.484375},{x:.609375,y:.484375},{x:.640625,y:.484375},{x:.640625,y:.484375},{x:.671875,y:.484375},{x:.671875,y:.484375},{x:.703125,y:.484375},{x:.703125,y:.484375},{x:.734375,y:.484375},{x:.734375,y:.484375},{x:.765625,y:.484375},{x:.765625,y:.484375},{x:.796875,y:.484375},{x:.796875,y:.484375},{x:.828125,y:.484375},{x:.828125,y:.484375},{x:.859375,y:.484375},{x:.859375,y:.484375},{x:.890625,y:.484375},{x:.890625,y:.484375},{x:.921875,y:.484375},{x:.921875,y:.484375},{x:.953125,y:.484375},{x:.953125,y:.484375},{x:.984375,y:.484375},{x:.984375,y:.484375},{x:.015625,y:.515625},{x:.015625,y:.515625},{x:.046875,y:.515625},{x:.046875,y:.515625},{x:.078125,y:.515625},{x:.078125,y:.515625},{x:.109375,y:.515625},{x:.109375,y:.515625},{x:.140625,y:.515625},{x:.140625,y:.515625},{x:.171875,y:.515625},{x:.171875,y:.515625},{x:.203125,y:.515625},{x:.203125,y:.515625},{x:.234375,y:.515625},{x:.234375,y:.515625},{x:.265625,y:.515625},{x:.265625,y:.515625},{x:.296875,y:.515625},{x:.296875,y:.515625},{x:.328125,y:.515625},{x:.328125,y:.515625},{x:.359375,y:.515625},{x:.359375,y:.515625},{x:.390625,y:.515625},{x:.390625,y:.515625},{x:.421875,y:.515625},{x:.421875,y:.515625},{x:.453125,y:.515625},{x:.453125,y:.515625},{x:.484375,y:.515625},{x:.484375,y:.515625},{x:.515625,y:.515625},{x:.515625,y:.515625},{x:.546875,y:.515625},{x:.546875,y:.515625},{x:.578125,y:.515625},{x:.578125,y:.515625},{x:.609375,y:.515625},{x:.609375,y:.515625},{x:.640625,y:.515625},{x:.640625,y:.515625},{x:.671875,y:.515625},{x:.671875,y:.515625},{x:.703125,y:.515625},{x:.703125,y:.515625},{x:.734375,y:.515625},{x:.734375,y:.515625},{x:.765625,y:.515625},{x:.765625,y:.515625},{x:.796875,y:.515625},{x:.796875,y:.515625},{x:.828125,y:.515625},{x:.828125,y:.515625},{x:.859375,y:.515625},{x:.859375,y:.515625},{x:.890625,y:.515625},{x:.890625,y:.515625},{x:.921875,y:.515625},{x:.921875,y:.515625},{x:.953125,y:.515625},{x:.953125,y:.515625},{x:.984375,y:.515625},{x:.984375,y:.515625},{x:.015625,y:.546875},{x:.015625,y:.546875},{x:.046875,y:.546875},{x:.046875,y:.546875},{x:.078125,y:.546875},{x:.078125,y:.546875},{x:.109375,y:.546875},{x:.109375,y:.546875},{x:.140625,y:.546875},{x:.140625,y:.546875},{x:.171875,y:.546875},{x:.171875,y:.546875},{x:.203125,y:.546875},{x:.203125,y:.546875},{x:.234375,y:.546875},{x:.234375,y:.546875},{x:.265625,y:.546875},{x:.265625,y:.546875},{x:.296875,y:.546875},{x:.296875,y:.546875},{x:.328125,y:.546875},{x:.328125,y:.546875},{x:.359375,y:.546875},{x:.359375,y:.546875},{x:.390625,y:.546875},{x:.390625,y:.546875},{x:.421875,y:.546875},{x:.421875,y:.546875},{x:.453125,y:.546875},{x:.453125,y:.546875},{x:.484375,y:.546875},{x:.484375,y:.546875},{x:.515625,y:.546875},{x:.515625,y:.546875},{x:.546875,y:.546875},{x:.546875,y:.546875},{x:.578125,y:.546875},{x:.578125,y:.546875},{x:.609375,y:.546875},{x:.609375,y:.546875},{x:.640625,y:.546875},{x:.640625,y:.546875},{x:.671875,y:.546875},{x:.671875,y:.546875},{x:.703125,y:.546875},{x:.703125,y:.546875},{x:.734375,y:.546875},{x:.734375,y:.546875},{x:.765625,y:.546875},{x:.765625,y:.546875},{x:.796875,y:.546875},{x:.796875,y:.546875},{x:.828125,y:.546875},{x:.828125,y:.546875},{x:.859375,y:.546875},{x:.859375,y:.546875},{x:.890625,y:.546875},{x:.890625,y:.546875},{x:.921875,y:.546875},{x:.921875,y:.546875},{x:.953125,y:.546875},{x:.953125,y:.546875},{x:.984375,y:.546875},{x:.984375,y:.546875},{x:.015625,y:.578125},{x:.015625,y:.578125},{x:.046875,y:.578125},{x:.046875,y:.578125},{x:.078125,y:.578125},{x:.078125,y:.578125},{x:.109375,y:.578125},{x:.109375,y:.578125},{x:.140625,y:.578125},{x:.140625,y:.578125},{x:.171875,y:.578125},{x:.171875,y:.578125},{x:.203125,y:.578125},{x:.203125,y:.578125},{x:.234375,y:.578125},{x:.234375,y:.578125},{x:.265625,y:.578125},{x:.265625,y:.578125},{x:.296875,y:.578125},{x:.296875,y:.578125},{x:.328125,y:.578125},{x:.328125,y:.578125},{x:.359375,y:.578125},{x:.359375,y:.578125},{x:.390625,y:.578125},{x:.390625,y:.578125},{x:.421875,y:.578125},{x:.421875,y:.578125},{x:.453125,y:.578125},{x:.453125,y:.578125},{x:.484375,y:.578125},{x:.484375,y:.578125},{x:.515625,y:.578125},{x:.515625,y:.578125},{x:.546875,y:.578125},{x:.546875,y:.578125},{x:.578125,y:.578125},{x:.578125,y:.578125},{x:.609375,y:.578125},{x:.609375,y:.578125},{x:.640625,y:.578125},{x:.640625,y:.578125},{x:.671875,y:.578125},{x:.671875,y:.578125},{x:.703125,y:.578125},{x:.703125,y:.578125},{x:.734375,y:.578125},{x:.734375,y:.578125},{x:.765625,y:.578125},{x:.765625,y:.578125},{x:.796875,y:.578125},{x:.796875,y:.578125},{x:.828125,y:.578125},{x:.828125,y:.578125},{x:.859375,y:.578125},{x:.859375,y:.578125},{x:.890625,y:.578125},{x:.890625,y:.578125},{x:.921875,y:.578125},{x:.921875,y:.578125},{x:.953125,y:.578125},{x:.953125,y:.578125},{x:.984375,y:.578125},{x:.984375,y:.578125},{x:.015625,y:.609375},{x:.015625,y:.609375},{x:.046875,y:.609375},{x:.046875,y:.609375},{x:.078125,y:.609375},{x:.078125,y:.609375},{x:.109375,y:.609375},{x:.109375,y:.609375},{x:.140625,y:.609375},{x:.140625,y:.609375},{x:.171875,y:.609375},{x:.171875,y:.609375},{x:.203125,y:.609375},{x:.203125,y:.609375},{x:.234375,y:.609375},{x:.234375,y:.609375},{x:.265625,y:.609375},{x:.265625,y:.609375},{x:.296875,y:.609375},{x:.296875,y:.609375},{x:.328125,y:.609375},{x:.328125,y:.609375},{x:.359375,y:.609375},{x:.359375,y:.609375},{x:.390625,y:.609375},{x:.390625,y:.609375},{x:.421875,y:.609375},{x:.421875,y:.609375},{x:.453125,y:.609375},{x:.453125,y:.609375},{x:.484375,y:.609375},{x:.484375,y:.609375},{x:.515625,y:.609375},{x:.515625,y:.609375},{x:.546875,y:.609375},{x:.546875,y:.609375},{x:.578125,y:.609375},{x:.578125,y:.609375},{x:.609375,y:.609375},{x:.609375,y:.609375},{x:.640625,y:.609375},{x:.640625,y:.609375},{x:.671875,y:.609375},{x:.671875,y:.609375},{x:.703125,y:.609375},{x:.703125,y:.609375},{x:.734375,y:.609375},{x:.734375,y:.609375},{x:.765625,y:.609375},{x:.765625,y:.609375},{x:.796875,y:.609375},{x:.796875,y:.609375},{x:.828125,y:.609375},{x:.828125,y:.609375},{x:.859375,y:.609375},{x:.859375,y:.609375},{x:.890625,y:.609375},{x:.890625,y:.609375},{x:.921875,y:.609375},{x:.921875,y:.609375},{x:.953125,y:.609375},{x:.953125,y:.609375},{x:.984375,y:.609375},{x:.984375,y:.609375},{x:.015625,y:.640625},{x:.015625,y:.640625},{x:.046875,y:.640625},{x:.046875,y:.640625},{x:.078125,y:.640625},{x:.078125,y:.640625},{x:.109375,y:.640625},{x:.109375,y:.640625},{x:.140625,y:.640625},{x:.140625,y:.640625},{x:.171875,y:.640625},{x:.171875,y:.640625},{x:.203125,y:.640625},{x:.203125,y:.640625},{x:.234375,y:.640625},{x:.234375,y:.640625},{x:.265625,y:.640625},{x:.265625,y:.640625},{x:.296875,y:.640625},{x:.296875,y:.640625},{x:.328125,y:.640625},{x:.328125,y:.640625},{x:.359375,y:.640625},{x:.359375,y:.640625},{x:.390625,y:.640625},{x:.390625,y:.640625},{x:.421875,y:.640625},{x:.421875,y:.640625},{x:.453125,y:.640625},{x:.453125,y:.640625},{x:.484375,y:.640625},{x:.484375,y:.640625},{x:.515625,y:.640625},{x:.515625,y:.640625},{x:.546875,y:.640625},{x:.546875,y:.640625},{x:.578125,y:.640625},{x:.578125,y:.640625},{x:.609375,y:.640625},{x:.609375,y:.640625},{x:.640625,y:.640625},{x:.640625,y:.640625},{x:.671875,y:.640625},{x:.671875,y:.640625},{x:.703125,y:.640625},{x:.703125,y:.640625},{x:.734375,y:.640625},{x:.734375,y:.640625},{x:.765625,y:.640625},{x:.765625,y:.640625},{x:.796875,y:.640625},{x:.796875,y:.640625},{x:.828125,y:.640625},{x:.828125,y:.640625},{x:.859375,y:.640625},{x:.859375,y:.640625},{x:.890625,y:.640625},{x:.890625,y:.640625},{x:.921875,y:.640625},{x:.921875,y:.640625},{x:.953125,y:.640625},{x:.953125,y:.640625},{x:.984375,y:.640625},{x:.984375,y:.640625},{x:.015625,y:.671875},{x:.015625,y:.671875},{x:.046875,y:.671875},{x:.046875,y:.671875},{x:.078125,y:.671875},{x:.078125,y:.671875},{x:.109375,y:.671875},{x:.109375,y:.671875},{x:.140625,y:.671875},{x:.140625,y:.671875},{x:.171875,y:.671875},{x:.171875,y:.671875},{x:.203125,y:.671875},{x:.203125,y:.671875},{x:.234375,y:.671875},{x:.234375,y:.671875},{x:.265625,y:.671875},{x:.265625,y:.671875},{x:.296875,y:.671875},{x:.296875,y:.671875},{x:.328125,y:.671875},{x:.328125,y:.671875},{x:.359375,y:.671875},{x:.359375,y:.671875},{x:.390625,y:.671875},{x:.390625,y:.671875},{x:.421875,y:.671875},{x:.421875,y:.671875},{x:.453125,y:.671875},{x:.453125,y:.671875},{x:.484375,y:.671875},{x:.484375,y:.671875},{x:.515625,y:.671875},{x:.515625,y:.671875},{x:.546875,y:.671875},{x:.546875,y:.671875},{x:.578125,y:.671875},{x:.578125,y:.671875},{x:.609375,y:.671875},{x:.609375,y:.671875},{x:.640625,y:.671875},{x:.640625,y:.671875},{x:.671875,y:.671875},{x:.671875,y:.671875},{x:.703125,y:.671875},{x:.703125,y:.671875},{x:.734375,y:.671875},{x:.734375,y:.671875},{x:.765625,y:.671875},{x:.765625,y:.671875},{x:.796875,y:.671875},{x:.796875,y:.671875},{x:.828125,y:.671875},{x:.828125,y:.671875},{x:.859375,y:.671875},{x:.859375,y:.671875},{x:.890625,y:.671875},{x:.890625,y:.671875},{x:.921875,y:.671875},{x:.921875,y:.671875},{x:.953125,y:.671875},{x:.953125,y:.671875},{x:.984375,y:.671875},{x:.984375,y:.671875},{x:.015625,y:.703125},{x:.015625,y:.703125},{x:.046875,y:.703125},{x:.046875,y:.703125},{x:.078125,y:.703125},{x:.078125,y:.703125},{x:.109375,y:.703125},{x:.109375,y:.703125},{x:.140625,y:.703125},{x:.140625,y:.703125},{x:.171875,y:.703125},{x:.171875,y:.703125},{x:.203125,y:.703125},{x:.203125,y:.703125},{x:.234375,y:.703125},{x:.234375,y:.703125},{x:.265625,y:.703125},{x:.265625,y:.703125},{x:.296875,y:.703125},{x:.296875,y:.703125},{x:.328125,y:.703125},{x:.328125,y:.703125},{x:.359375,y:.703125},{x:.359375,y:.703125},{x:.390625,y:.703125},{x:.390625,y:.703125},{x:.421875,y:.703125},{x:.421875,y:.703125},{x:.453125,y:.703125},{x:.453125,y:.703125},{x:.484375,y:.703125},{x:.484375,y:.703125},{x:.515625,y:.703125},{x:.515625,y:.703125},{x:.546875,y:.703125},{x:.546875,y:.703125},{x:.578125,y:.703125},{x:.578125,y:.703125},{x:.609375,y:.703125},{x:.609375,y:.703125},{x:.640625,y:.703125},{x:.640625,y:.703125},{x:.671875,y:.703125},{x:.671875,y:.703125},{x:.703125,y:.703125},{x:.703125,y:.703125},{x:.734375,y:.703125},{x:.734375,y:.703125},{x:.765625,y:.703125},{x:.765625,y:.703125},{x:.796875,y:.703125},{x:.796875,y:.703125},{x:.828125,y:.703125},{x:.828125,y:.703125},{x:.859375,y:.703125},{x:.859375,y:.703125},{x:.890625,y:.703125},{x:.890625,y:.703125},{x:.921875,y:.703125},{x:.921875,y:.703125},{x:.953125,y:.703125},{x:.953125,y:.703125},{x:.984375,y:.703125},{x:.984375,y:.703125},{x:.015625,y:.734375},{x:.015625,y:.734375},{x:.046875,y:.734375},{x:.046875,y:.734375},{x:.078125,y:.734375},{x:.078125,y:.734375},{x:.109375,y:.734375},{x:.109375,y:.734375},{x:.140625,y:.734375},{x:.140625,y:.734375},{x:.171875,y:.734375},{x:.171875,y:.734375},{x:.203125,y:.734375},{x:.203125,y:.734375},{x:.234375,y:.734375},{x:.234375,y:.734375},{x:.265625,y:.734375},{x:.265625,y:.734375},{x:.296875,y:.734375},{x:.296875,y:.734375},{x:.328125,y:.734375},{x:.328125,y:.734375},{x:.359375,y:.734375},{x:.359375,y:.734375},{x:.390625,y:.734375},{x:.390625,y:.734375},{x:.421875,y:.734375},{x:.421875,y:.734375},{x:.453125,y:.734375},{x:.453125,y:.734375},{x:.484375,y:.734375},{x:.484375,y:.734375},{x:.515625,y:.734375},{x:.515625,y:.734375},{x:.546875,y:.734375},{x:.546875,y:.734375},{x:.578125,y:.734375},{x:.578125,y:.734375},{x:.609375,y:.734375},{x:.609375,y:.734375},{x:.640625,y:.734375},{x:.640625,y:.734375},{x:.671875,y:.734375},{x:.671875,y:.734375},{x:.703125,y:.734375},{x:.703125,y:.734375},{x:.734375,y:.734375},{x:.734375,y:.734375},{x:.765625,y:.734375},{x:.765625,y:.734375},{x:.796875,y:.734375},{x:.796875,y:.734375},{x:.828125,y:.734375},{x:.828125,y:.734375},{x:.859375,y:.734375},{x:.859375,y:.734375},{x:.890625,y:.734375},{x:.890625,y:.734375},{x:.921875,y:.734375},{x:.921875,y:.734375},{x:.953125,y:.734375},{x:.953125,y:.734375},{x:.984375,y:.734375},{x:.984375,y:.734375},{x:.015625,y:.765625},{x:.015625,y:.765625},{x:.046875,y:.765625},{x:.046875,y:.765625},{x:.078125,y:.765625},{x:.078125,y:.765625},{x:.109375,y:.765625},{x:.109375,y:.765625},{x:.140625,y:.765625},{x:.140625,y:.765625},{x:.171875,y:.765625},{x:.171875,y:.765625},{x:.203125,y:.765625},{x:.203125,y:.765625},{x:.234375,y:.765625},{x:.234375,y:.765625},{x:.265625,y:.765625},{x:.265625,y:.765625},{x:.296875,y:.765625},{x:.296875,y:.765625},{x:.328125,y:.765625},{x:.328125,y:.765625},{x:.359375,y:.765625},{x:.359375,y:.765625},{x:.390625,y:.765625},{x:.390625,y:.765625},{x:.421875,y:.765625},{x:.421875,y:.765625},{x:.453125,y:.765625},{x:.453125,y:.765625},{x:.484375,y:.765625},{x:.484375,y:.765625},{x:.515625,y:.765625},{x:.515625,y:.765625},{x:.546875,y:.765625},{x:.546875,y:.765625},{x:.578125,y:.765625},{x:.578125,y:.765625},{x:.609375,y:.765625},{x:.609375,y:.765625},{x:.640625,y:.765625},{x:.640625,y:.765625},{x:.671875,y:.765625},{x:.671875,y:.765625},{x:.703125,y:.765625},{x:.703125,y:.765625},{x:.734375,y:.765625},{x:.734375,y:.765625},{x:.765625,y:.765625},{x:.765625,y:.765625},{x:.796875,y:.765625},{x:.796875,y:.765625},{x:.828125,y:.765625},{x:.828125,y:.765625},{x:.859375,y:.765625},{x:.859375,y:.765625},{x:.890625,y:.765625},{x:.890625,y:.765625},{x:.921875,y:.765625},{x:.921875,y:.765625},{x:.953125,y:.765625},{x:.953125,y:.765625},{x:.984375,y:.765625},{x:.984375,y:.765625},{x:.015625,y:.796875},{x:.015625,y:.796875},{x:.046875,y:.796875},{x:.046875,y:.796875},{x:.078125,y:.796875},{x:.078125,y:.796875},{x:.109375,y:.796875},{x:.109375,y:.796875},{x:.140625,y:.796875},{x:.140625,y:.796875},{x:.171875,y:.796875},{x:.171875,y:.796875},{x:.203125,y:.796875},{x:.203125,y:.796875},{x:.234375,y:.796875},{x:.234375,y:.796875},{x:.265625,y:.796875},{x:.265625,y:.796875},{x:.296875,y:.796875},{x:.296875,y:.796875},{x:.328125,y:.796875},{x:.328125,y:.796875},{x:.359375,y:.796875},{x:.359375,y:.796875},{x:.390625,y:.796875},{x:.390625,y:.796875},{x:.421875,y:.796875},{x:.421875,y:.796875},{x:.453125,y:.796875},{x:.453125,y:.796875},{x:.484375,y:.796875},{x:.484375,y:.796875},{x:.515625,y:.796875},{x:.515625,y:.796875},{x:.546875,y:.796875},{x:.546875,y:.796875},{x:.578125,y:.796875},{x:.578125,y:.796875},{x:.609375,y:.796875},{x:.609375,y:.796875},{x:.640625,y:.796875},{x:.640625,y:.796875},{x:.671875,y:.796875},{x:.671875,y:.796875},{x:.703125,y:.796875},{x:.703125,y:.796875},{x:.734375,y:.796875},{x:.734375,y:.796875},{x:.765625,y:.796875},{x:.765625,y:.796875},{x:.796875,y:.796875},{x:.796875,y:.796875},{x:.828125,y:.796875},{x:.828125,y:.796875},{x:.859375,y:.796875},{x:.859375,y:.796875},{x:.890625,y:.796875},{x:.890625,y:.796875},{x:.921875,y:.796875},{x:.921875,y:.796875},{x:.953125,y:.796875},{x:.953125,y:.796875},{x:.984375,y:.796875},{x:.984375,y:.796875},{x:.015625,y:.828125},{x:.015625,y:.828125},{x:.046875,y:.828125},{x:.046875,y:.828125},{x:.078125,y:.828125},{x:.078125,y:.828125},{x:.109375,y:.828125},{x:.109375,y:.828125},{x:.140625,y:.828125},{x:.140625,y:.828125},{x:.171875,y:.828125},{x:.171875,y:.828125},{x:.203125,y:.828125},{x:.203125,y:.828125},{x:.234375,y:.828125},{x:.234375,y:.828125},{x:.265625,y:.828125},{x:.265625,y:.828125},{x:.296875,y:.828125},{x:.296875,y:.828125},{x:.328125,y:.828125},{x:.328125,y:.828125},{x:.359375,y:.828125},{x:.359375,y:.828125},{x:.390625,y:.828125},{x:.390625,y:.828125},{x:.421875,y:.828125},{x:.421875,y:.828125},{x:.453125,y:.828125},{x:.453125,y:.828125},{x:.484375,y:.828125},{x:.484375,y:.828125},{x:.515625,y:.828125},{x:.515625,y:.828125},{x:.546875,y:.828125},{x:.546875,y:.828125},{x:.578125,y:.828125},{x:.578125,y:.828125},{x:.609375,y:.828125},{x:.609375,y:.828125},{x:.640625,y:.828125},{x:.640625,y:.828125},{x:.671875,y:.828125},{x:.671875,y:.828125},{x:.703125,y:.828125},{x:.703125,y:.828125},{x:.734375,y:.828125},{x:.734375,y:.828125},{x:.765625,y:.828125},{x:.765625,y:.828125},{x:.796875,y:.828125},{x:.796875,y:.828125},{x:.828125,y:.828125},{x:.828125,y:.828125},{x:.859375,y:.828125},{x:.859375,y:.828125},{x:.890625,y:.828125},{x:.890625,y:.828125},{x:.921875,y:.828125},{x:.921875,y:.828125},{x:.953125,y:.828125},{x:.953125,y:.828125},{x:.984375,y:.828125},{x:.984375,y:.828125},{x:.015625,y:.859375},{x:.015625,y:.859375},{x:.046875,y:.859375},{x:.046875,y:.859375},{x:.078125,y:.859375},{x:.078125,y:.859375},{x:.109375,y:.859375},{x:.109375,y:.859375},{x:.140625,y:.859375},{x:.140625,y:.859375},{x:.171875,y:.859375},{x:.171875,y:.859375},{x:.203125,y:.859375},{x:.203125,y:.859375},{x:.234375,y:.859375},{x:.234375,y:.859375},{x:.265625,y:.859375},{x:.265625,y:.859375},{x:.296875,y:.859375},{x:.296875,y:.859375},{x:.328125,y:.859375},{x:.328125,y:.859375},{x:.359375,y:.859375},{x:.359375,y:.859375},{x:.390625,y:.859375},{x:.390625,y:.859375},{x:.421875,y:.859375},{x:.421875,y:.859375},{x:.453125,y:.859375},{x:.453125,y:.859375},{x:.484375,y:.859375},{x:.484375,y:.859375},{x:.515625,y:.859375},{x:.515625,y:.859375},{x:.546875,y:.859375},{x:.546875,y:.859375},{x:.578125,y:.859375},{x:.578125,y:.859375},{x:.609375,y:.859375},{x:.609375,y:.859375},{x:.640625,y:.859375},{x:.640625,y:.859375},{x:.671875,y:.859375},{x:.671875,y:.859375},{x:.703125,y:.859375},{x:.703125,y:.859375},{x:.734375,y:.859375},{x:.734375,y:.859375},{x:.765625,y:.859375},{x:.765625,y:.859375},{x:.796875,y:.859375},{x:.796875,y:.859375},{x:.828125,y:.859375},{x:.828125,y:.859375},{x:.859375,y:.859375},{x:.859375,y:.859375},{x:.890625,y:.859375},{x:.890625,y:.859375},{x:.921875,y:.859375},{x:.921875,y:.859375},{x:.953125,y:.859375},{x:.953125,y:.859375},{x:.984375,y:.859375},{x:.984375,y:.859375},{x:.015625,y:.890625},{x:.015625,y:.890625},{x:.046875,y:.890625},{x:.046875,y:.890625},{x:.078125,y:.890625},{x:.078125,y:.890625},{x:.109375,y:.890625},{x:.109375,y:.890625},{x:.140625,y:.890625},{x:.140625,y:.890625},{x:.171875,y:.890625},{x:.171875,y:.890625},{x:.203125,y:.890625},{x:.203125,y:.890625},{x:.234375,y:.890625},{x:.234375,y:.890625},{x:.265625,y:.890625},{x:.265625,y:.890625},{x:.296875,y:.890625},{x:.296875,y:.890625},{x:.328125,y:.890625},{x:.328125,y:.890625},{x:.359375,y:.890625},{x:.359375,y:.890625},{x:.390625,y:.890625},{x:.390625,y:.890625},{x:.421875,y:.890625},{x:.421875,y:.890625},{x:.453125,y:.890625},{x:.453125,y:.890625},{x:.484375,y:.890625},{x:.484375,y:.890625},{x:.515625,y:.890625},{x:.515625,y:.890625},{x:.546875,y:.890625},{x:.546875,y:.890625},{x:.578125,y:.890625},{x:.578125,y:.890625},{x:.609375,y:.890625},{x:.609375,y:.890625},{x:.640625,y:.890625},{x:.640625,y:.890625},{x:.671875,y:.890625},{x:.671875,y:.890625},{x:.703125,y:.890625},{x:.703125,y:.890625},{x:.734375,y:.890625},{x:.734375,y:.890625},{x:.765625,y:.890625},{x:.765625,y:.890625},{x:.796875,y:.890625},{x:.796875,y:.890625},{x:.828125,y:.890625},{x:.828125,y:.890625},{x:.859375,y:.890625},{x:.859375,y:.890625},{x:.890625,y:.890625},{x:.890625,y:.890625},{x:.921875,y:.890625},{x:.921875,y:.890625},{x:.953125,y:.890625},{x:.953125,y:.890625},{x:.984375,y:.890625},{x:.984375,y:.890625},{x:.015625,y:.921875},{x:.015625,y:.921875},{x:.046875,y:.921875},{x:.046875,y:.921875},{x:.078125,y:.921875},{x:.078125,y:.921875},{x:.109375,y:.921875},{x:.109375,y:.921875},{x:.140625,y:.921875},{x:.140625,y:.921875},{x:.171875,y:.921875},{x:.171875,y:.921875},{x:.203125,y:.921875},{x:.203125,y:.921875},{x:.234375,y:.921875},{x:.234375,y:.921875},{x:.265625,y:.921875},{x:.265625,y:.921875},{x:.296875,y:.921875},{x:.296875,y:.921875},{x:.328125,y:.921875},{x:.328125,y:.921875},{x:.359375,y:.921875},{x:.359375,y:.921875},{x:.390625,y:.921875},{x:.390625,y:.921875},{x:.421875,y:.921875},{x:.421875,y:.921875},{x:.453125,y:.921875},{x:.453125,y:.921875},{x:.484375,y:.921875},{x:.484375,y:.921875},{x:.515625,y:.921875},{x:.515625,y:.921875},{x:.546875,y:.921875},{x:.546875,y:.921875},{x:.578125,y:.921875},{x:.578125,y:.921875},{x:.609375,y:.921875},{x:.609375,y:.921875},{x:.640625,y:.921875},{x:.640625,y:.921875},{x:.671875,y:.921875},{x:.671875,y:.921875},{x:.703125,y:.921875},{x:.703125,y:.921875},{x:.734375,y:.921875},{x:.734375,y:.921875},{x:.765625,y:.921875},{x:.765625,y:.921875},{x:.796875,y:.921875},{x:.796875,y:.921875},{x:.828125,y:.921875},{x:.828125,y:.921875},{x:.859375,y:.921875},{x:.859375,y:.921875},{x:.890625,y:.921875},{x:.890625,y:.921875},{x:.921875,y:.921875},{x:.921875,y:.921875},{x:.953125,y:.921875},{x:.953125,y:.921875},{x:.984375,y:.921875},{x:.984375,y:.921875},{x:.015625,y:.953125},{x:.015625,y:.953125},{x:.046875,y:.953125},{x:.046875,y:.953125},{x:.078125,y:.953125},{x:.078125,y:.953125},{x:.109375,y:.953125},{x:.109375,y:.953125},{x:.140625,y:.953125},{x:.140625,y:.953125},{x:.171875,y:.953125},{x:.171875,y:.953125},{x:.203125,y:.953125},{x:.203125,y:.953125},{x:.234375,y:.953125},{x:.234375,y:.953125},{x:.265625,y:.953125},{x:.265625,y:.953125},{x:.296875,y:.953125},{x:.296875,y:.953125},{x:.328125,y:.953125},{x:.328125,y:.953125},{x:.359375,y:.953125},{x:.359375,y:.953125},{x:.390625,y:.953125},{x:.390625,y:.953125},{x:.421875,y:.953125},{x:.421875,y:.953125},{x:.453125,y:.953125},{x:.453125,y:.953125},{x:.484375,y:.953125},{x:.484375,y:.953125},{x:.515625,y:.953125},{x:.515625,y:.953125},{x:.546875,y:.953125},{x:.546875,y:.953125},{x:.578125,y:.953125},{x:.578125,y:.953125},{x:.609375,y:.953125},{x:.609375,y:.953125},{x:.640625,y:.953125},{x:.640625,y:.953125},{x:.671875,y:.953125},{x:.671875,y:.953125},{x:.703125,y:.953125},{x:.703125,y:.953125},{x:.734375,y:.953125},{x:.734375,y:.953125},{x:.765625,y:.953125},{x:.765625,y:.953125},{x:.796875,y:.953125},{x:.796875,y:.953125},{x:.828125,y:.953125},{x:.828125,y:.953125},{x:.859375,y:.953125},{x:.859375,y:.953125},{x:.890625,y:.953125},{x:.890625,y:.953125},{x:.921875,y:.953125},{x:.921875,y:.953125},{x:.953125,y:.953125},{x:.953125,y:.953125},{x:.984375,y:.953125},{x:.984375,y:.953125},{x:.015625,y:.984375},{x:.015625,y:.984375},{x:.046875,y:.984375},{x:.046875,y:.984375},{x:.078125,y:.984375},{x:.078125,y:.984375},{x:.109375,y:.984375},{x:.109375,y:.984375},{x:.140625,y:.984375},{x:.140625,y:.984375},{x:.171875,y:.984375},{x:.171875,y:.984375},{x:.203125,y:.984375},{x:.203125,y:.984375},{x:.234375,y:.984375},{x:.234375,y:.984375},{x:.265625,y:.984375},{x:.265625,y:.984375},{x:.296875,y:.984375},{x:.296875,y:.984375},{x:.328125,y:.984375},{x:.328125,y:.984375},{x:.359375,y:.984375},{x:.359375,y:.984375},{x:.390625,y:.984375},{x:.390625,y:.984375},{x:.421875,y:.984375},{x:.421875,y:.984375},{x:.453125,y:.984375},{x:.453125,y:.984375},{x:.484375,y:.984375},{x:.484375,y:.984375},{x:.515625,y:.984375},{x:.515625,y:.984375},{x:.546875,y:.984375},{x:.546875,y:.984375},{x:.578125,y:.984375},{x:.578125,y:.984375},{x:.609375,y:.984375},{x:.609375,y:.984375},{x:.640625,y:.984375},{x:.640625,y:.984375},{x:.671875,y:.984375},{x:.671875,y:.984375},{x:.703125,y:.984375},{x:.703125,y:.984375},{x:.734375,y:.984375},{x:.734375,y:.984375},{x:.765625,y:.984375},{x:.765625,y:.984375},{x:.796875,y:.984375},{x:.796875,y:.984375},{x:.828125,y:.984375},{x:.828125,y:.984375},{x:.859375,y:.984375},{x:.859375,y:.984375},{x:.890625,y:.984375},{x:.890625,y:.984375},{x:.921875,y:.984375},{x:.921875,y:.984375},{x:.953125,y:.984375},{x:.953125,y:.984375},{x:.984375,y:.984375},{x:.984375,y:.984375},{x:.03125,y:.03125},{x:.03125,y:.03125},{x:.09375,y:.03125},{x:.09375,y:.03125},{x:.15625,y:.03125},{x:.15625,y:.03125},{x:.21875,y:.03125},{x:.21875,y:.03125},{x:.28125,y:.03125},{x:.28125,y:.03125},{x:.34375,y:.03125},{x:.34375,y:.03125},{x:.40625,y:.03125},{x:.40625,y:.03125},{x:.46875,y:.03125},{x:.46875,y:.03125},{x:.53125,y:.03125},{x:.53125,y:.03125},{x:.59375,y:.03125},{x:.59375,y:.03125},{x:.65625,y:.03125},{x:.65625,y:.03125},{x:.71875,y:.03125},{x:.71875,y:.03125},{x:.78125,y:.03125},{x:.78125,y:.03125},{x:.84375,y:.03125},{x:.84375,y:.03125},{x:.90625,y:.03125},{x:.90625,y:.03125},{x:.96875,y:.03125},{x:.96875,y:.03125},{x:.03125,y:.09375},{x:.03125,y:.09375},{x:.09375,y:.09375},{x:.09375,y:.09375},{x:.15625,y:.09375},{x:.15625,y:.09375},{x:.21875,y:.09375},{x:.21875,y:.09375},{x:.28125,y:.09375},{x:.28125,y:.09375},{x:.34375,y:.09375},{x:.34375,y:.09375},{x:.40625,y:.09375},{x:.40625,y:.09375},{x:.46875,y:.09375},{x:.46875,y:.09375},{x:.53125,y:.09375},{x:.53125,y:.09375},{x:.59375,y:.09375},{x:.59375,y:.09375},{x:.65625,y:.09375},{x:.65625,y:.09375},{x:.71875,y:.09375},{x:.71875,y:.09375},{x:.78125,y:.09375},{x:.78125,y:.09375},{x:.84375,y:.09375},{x:.84375,y:.09375},{x:.90625,y:.09375},{x:.90625,y:.09375},{x:.96875,y:.09375},{x:.96875,y:.09375},{x:.03125,y:.15625},{x:.03125,y:.15625},{x:.09375,y:.15625},{x:.09375,y:.15625},{x:.15625,y:.15625},{x:.15625,y:.15625},{x:.21875,y:.15625},{x:.21875,y:.15625},{x:.28125,y:.15625},{x:.28125,y:.15625},{x:.34375,y:.15625},{x:.34375,y:.15625},{x:.40625,y:.15625},{x:.40625,y:.15625},{x:.46875,y:.15625},{x:.46875,y:.15625},{x:.53125,y:.15625},{x:.53125,y:.15625},{x:.59375,y:.15625},{x:.59375,y:.15625},{x:.65625,y:.15625},{x:.65625,y:.15625},{x:.71875,y:.15625},{x:.71875,y:.15625},{x:.78125,y:.15625},{x:.78125,y:.15625},{x:.84375,y:.15625},{x:.84375,y:.15625},{x:.90625,y:.15625},{x:.90625,y:.15625},{x:.96875,y:.15625},{x:.96875,y:.15625},{x:.03125,y:.21875},{x:.03125,y:.21875},{x:.09375,y:.21875},{x:.09375,y:.21875},{x:.15625,y:.21875},{x:.15625,y:.21875},{x:.21875,y:.21875},{x:.21875,y:.21875},{x:.28125,y:.21875},{x:.28125,y:.21875},{x:.34375,y:.21875},{x:.34375,y:.21875},{x:.40625,y:.21875},{x:.40625,y:.21875},{x:.46875,y:.21875},{x:.46875,y:.21875},{x:.53125,y:.21875},{x:.53125,y:.21875},{x:.59375,y:.21875},{x:.59375,y:.21875},{x:.65625,y:.21875},{x:.65625,y:.21875},{x:.71875,y:.21875},{x:.71875,y:.21875},{x:.78125,y:.21875},{x:.78125,y:.21875},{x:.84375,y:.21875},{x:.84375,y:.21875},{x:.90625,y:.21875},{x:.90625,y:.21875},{x:.96875,y:.21875},{x:.96875,y:.21875},{x:.03125,y:.28125},{x:.03125,y:.28125},{x:.09375,y:.28125},{x:.09375,y:.28125},{x:.15625,y:.28125},{x:.15625,y:.28125},{x:.21875,y:.28125},{x:.21875,y:.28125},{x:.28125,y:.28125},{x:.28125,y:.28125},{x:.34375,y:.28125},{x:.34375,y:.28125},{x:.40625,y:.28125},{x:.40625,y:.28125},{x:.46875,y:.28125},{x:.46875,y:.28125},{x:.53125,y:.28125},{x:.53125,y:.28125},{x:.59375,y:.28125},{x:.59375,y:.28125},{x:.65625,y:.28125},{x:.65625,y:.28125},{x:.71875,y:.28125},{x:.71875,y:.28125},{x:.78125,y:.28125},{x:.78125,y:.28125},{x:.84375,y:.28125},{x:.84375,y:.28125},{x:.90625,y:.28125},{x:.90625,y:.28125},{x:.96875,y:.28125},{x:.96875,y:.28125},{x:.03125,y:.34375},{x:.03125,y:.34375},{x:.09375,y:.34375},{x:.09375,y:.34375},{x:.15625,y:.34375},{x:.15625,y:.34375},{x:.21875,y:.34375},{x:.21875,y:.34375},{x:.28125,y:.34375},{x:.28125,y:.34375},{x:.34375,y:.34375},{x:.34375,y:.34375},{x:.40625,y:.34375},{x:.40625,y:.34375},{x:.46875,y:.34375},{x:.46875,y:.34375},{x:.53125,y:.34375},{x:.53125,y:.34375},{x:.59375,y:.34375},{x:.59375,y:.34375},{x:.65625,y:.34375},{x:.65625,y:.34375},{x:.71875,y:.34375},{x:.71875,y:.34375},{x:.78125,y:.34375},{x:.78125,y:.34375},{x:.84375,y:.34375},{x:.84375,y:.34375},{x:.90625,y:.34375},{x:.90625,y:.34375},{x:.96875,y:.34375},{x:.96875,y:.34375},{x:.03125,y:.40625},{x:.03125,y:.40625},{x:.09375,y:.40625},{x:.09375,y:.40625},{x:.15625,y:.40625},{x:.15625,y:.40625},{x:.21875,y:.40625},{x:.21875,y:.40625},{x:.28125,y:.40625},{x:.28125,y:.40625},{x:.34375,y:.40625},{x:.34375,y:.40625},{x:.40625,y:.40625},{x:.40625,y:.40625},{x:.46875,y:.40625},{x:.46875,y:.40625},{x:.53125,y:.40625},{x:.53125,y:.40625},{x:.59375,y:.40625},{x:.59375,y:.40625},{x:.65625,y:.40625},{x:.65625,y:.40625},{x:.71875,y:.40625},{x:.71875,y:.40625},{x:.78125,y:.40625},{x:.78125,y:.40625},{x:.84375,y:.40625},{x:.84375,y:.40625},{x:.90625,y:.40625},{x:.90625,y:.40625},{x:.96875,y:.40625},{x:.96875,y:.40625},{x:.03125,y:.46875},{x:.03125,y:.46875},{x:.09375,y:.46875},{x:.09375,y:.46875},{x:.15625,y:.46875},{x:.15625,y:.46875},{x:.21875,y:.46875},{x:.21875,y:.46875},{x:.28125,y:.46875},{x:.28125,y:.46875},{x:.34375,y:.46875},{x:.34375,y:.46875},{x:.40625,y:.46875},{x:.40625,y:.46875},{x:.46875,y:.46875},{x:.46875,y:.46875},{x:.53125,y:.46875},{x:.53125,y:.46875},{x:.59375,y:.46875},{x:.59375,y:.46875},{x:.65625,y:.46875},{x:.65625,y:.46875},{x:.71875,y:.46875},{x:.71875,y:.46875},{x:.78125,y:.46875},{x:.78125,y:.46875},{x:.84375,y:.46875},{x:.84375,y:.46875},{x:.90625,y:.46875},{x:.90625,y:.46875},{x:.96875,y:.46875},{x:.96875,y:.46875},{x:.03125,y:.53125},{x:.03125,y:.53125},{x:.09375,y:.53125},{x:.09375,y:.53125},{x:.15625,y:.53125},{x:.15625,y:.53125},{x:.21875,y:.53125},{x:.21875,y:.53125},{x:.28125,y:.53125},{x:.28125,y:.53125},{x:.34375,y:.53125},{x:.34375,y:.53125},{x:.40625,y:.53125},{x:.40625,y:.53125},{x:.46875,y:.53125},{x:.46875,y:.53125},{x:.53125,y:.53125},{x:.53125,y:.53125},{x:.59375,y:.53125},{x:.59375,y:.53125},{x:.65625,y:.53125},{x:.65625,y:.53125},{x:.71875,y:.53125},{x:.71875,y:.53125},{x:.78125,y:.53125},{x:.78125,y:.53125},{x:.84375,y:.53125},{x:.84375,y:.53125},{x:.90625,y:.53125},{x:.90625,y:.53125},{x:.96875,y:.53125},{x:.96875,y:.53125},{x:.03125,y:.59375},{x:.03125,y:.59375},{x:.09375,y:.59375},{x:.09375,y:.59375},{x:.15625,y:.59375},{x:.15625,y:.59375},{x:.21875,y:.59375},{x:.21875,y:.59375},{x:.28125,y:.59375},{x:.28125,y:.59375},{x:.34375,y:.59375},{x:.34375,y:.59375},{x:.40625,y:.59375},{x:.40625,y:.59375},{x:.46875,y:.59375},{x:.46875,y:.59375},{x:.53125,y:.59375},{x:.53125,y:.59375},{x:.59375,y:.59375},{x:.59375,y:.59375},{x:.65625,y:.59375},{x:.65625,y:.59375},{x:.71875,y:.59375},{x:.71875,y:.59375},{x:.78125,y:.59375},{x:.78125,y:.59375},{x:.84375,y:.59375},{x:.84375,y:.59375},{x:.90625,y:.59375},{x:.90625,y:.59375},{x:.96875,y:.59375},{x:.96875,y:.59375},{x:.03125,y:.65625},{x:.03125,y:.65625},{x:.09375,y:.65625},{x:.09375,y:.65625},{x:.15625,y:.65625},{x:.15625,y:.65625},{x:.21875,y:.65625},{x:.21875,y:.65625},{x:.28125,y:.65625},{x:.28125,y:.65625},{x:.34375,y:.65625},{x:.34375,y:.65625},{x:.40625,y:.65625},{x:.40625,y:.65625},{x:.46875,y:.65625},{x:.46875,y:.65625},{x:.53125,y:.65625},{x:.53125,y:.65625},{x:.59375,y:.65625},{x:.59375,y:.65625},{x:.65625,y:.65625},{x:.65625,y:.65625},{x:.71875,y:.65625},{x:.71875,y:.65625},{x:.78125,y:.65625},{x:.78125,y:.65625},{x:.84375,y:.65625},{x:.84375,y:.65625},{x:.90625,y:.65625},{x:.90625,y:.65625},{x:.96875,y:.65625},{x:.96875,y:.65625},{x:.03125,y:.71875},{x:.03125,y:.71875},{x:.09375,y:.71875},{x:.09375,y:.71875},{x:.15625,y:.71875},{x:.15625,y:.71875},{x:.21875,y:.71875},{x:.21875,y:.71875},{x:.28125,y:.71875},{x:.28125,y:.71875},{x:.34375,y:.71875},{x:.34375,y:.71875},{x:.40625,y:.71875},{x:.40625,y:.71875},{x:.46875,y:.71875},{x:.46875,y:.71875},{x:.53125,y:.71875},{x:.53125,y:.71875},{x:.59375,y:.71875},{x:.59375,y:.71875},{x:.65625,y:.71875},{x:.65625,y:.71875},{x:.71875,y:.71875},{x:.71875,y:.71875},{x:.78125,y:.71875},{x:.78125,y:.71875},{x:.84375,y:.71875},{x:.84375,y:.71875},{x:.90625,y:.71875},{x:.90625,y:.71875},{x:.96875,y:.71875},{x:.96875,y:.71875},{x:.03125,y:.78125},{x:.03125,y:.78125},{x:.09375,y:.78125},{x:.09375,y:.78125},{x:.15625,y:.78125},{x:.15625,y:.78125},{x:.21875,y:.78125},{x:.21875,y:.78125},{x:.28125,y:.78125},{x:.28125,y:.78125},{x:.34375,y:.78125},{x:.34375,y:.78125},{x:.40625,y:.78125},{x:.40625,y:.78125},{x:.46875,y:.78125},{x:.46875,y:.78125},{x:.53125,y:.78125},{x:.53125,y:.78125},{x:.59375,y:.78125},{x:.59375,y:.78125},{x:.65625,y:.78125},{x:.65625,y:.78125},{x:.71875,y:.78125},{x:.71875,y:.78125},{x:.78125,y:.78125},{x:.78125,y:.78125},{x:.84375,y:.78125},{x:.84375,y:.78125},{x:.90625,y:.78125},{x:.90625,y:.78125},{x:.96875,y:.78125},{x:.96875,y:.78125},{x:.03125,y:.84375},{x:.03125,y:.84375},{x:.09375,y:.84375},{x:.09375,y:.84375},{x:.15625,y:.84375},{x:.15625,y:.84375},{x:.21875,y:.84375},{x:.21875,y:.84375},{x:.28125,y:.84375},{x:.28125,y:.84375},{x:.34375,y:.84375},{x:.34375,y:.84375},{x:.40625,y:.84375},{x:.40625,y:.84375},{x:.46875,y:.84375},{x:.46875,y:.84375},{x:.53125,y:.84375},{x:.53125,y:.84375},{x:.59375,y:.84375},{x:.59375,y:.84375},{x:.65625,y:.84375},{x:.65625,y:.84375},{x:.71875,y:.84375},{x:.71875,y:.84375},{x:.78125,y:.84375},{x:.78125,y:.84375},{x:.84375,y:.84375},{x:.84375,y:.84375},{x:.90625,y:.84375},{x:.90625,y:.84375},{x:.96875,y:.84375},{x:.96875,y:.84375},{x:.03125,y:.90625},{x:.03125,y:.90625},{x:.09375,y:.90625},{x:.09375,y:.90625},{x:.15625,y:.90625},{x:.15625,y:.90625},{x:.21875,y:.90625},{x:.21875,y:.90625},{x:.28125,y:.90625},{x:.28125,y:.90625},{x:.34375,y:.90625},{x:.34375,y:.90625},{x:.40625,y:.90625},{x:.40625,y:.90625},{x:.46875,y:.90625},{x:.46875,y:.90625},{x:.53125,y:.90625},{x:.53125,y:.90625},{x:.59375,y:.90625},{x:.59375,y:.90625},{x:.65625,y:.90625},{x:.65625,y:.90625},{x:.71875,y:.90625},{x:.71875,y:.90625},{x:.78125,y:.90625},{x:.78125,y:.90625},{x:.84375,y:.90625},{x:.84375,y:.90625},{x:.90625,y:.90625},{x:.90625,y:.90625},{x:.96875,y:.90625},{x:.96875,y:.90625},{x:.03125,y:.96875},{x:.03125,y:.96875},{x:.09375,y:.96875},{x:.09375,y:.96875},{x:.15625,y:.96875},{x:.15625,y:.96875},{x:.21875,y:.96875},{x:.21875,y:.96875},{x:.28125,y:.96875},{x:.28125,y:.96875},{x:.34375,y:.96875},{x:.34375,y:.96875},{x:.40625,y:.96875},{x:.40625,y:.96875},{x:.46875,y:.96875},{x:.46875,y:.96875},{x:.53125,y:.96875},{x:.53125,y:.96875},{x:.59375,y:.96875},{x:.59375,y:.96875},{x:.65625,y:.96875},{x:.65625,y:.96875},{x:.71875,y:.96875},{x:.71875,y:.96875},{x:.78125,y:.96875},{x:.78125,y:.96875},{x:.84375,y:.96875},{x:.84375,y:.96875},{x:.90625,y:.96875},{x:.90625,y:.96875},{x:.96875,y:.96875},{x:.96875,y:.96875},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375}];var e1=class{constructor(t){me(this,"model");me(this,"anchors");me(this,"anchorsTensor");me(this,"inputSize");me(this,"inputSizeTensor");me(this,"doubleInputSizeTensor");this.model=t,this.anchors=XN.map(n=>[n.x,n.y]),this.anchorsTensor=or(this.anchors),this.inputSize=this.model&&this.model.inputs&&this.model.inputs[0].shape?this.model.inputs[0].shape[2]:0,this.inputSizeTensor=Ft([this.inputSize,this.inputSize]),this.doubleInputSizeTensor=Ft([this.inputSize*2,this.inputSize*2])}normalizeBoxes(t){let n={};n.boxOffsets=Oe(t,[0,0],[-1,2]),n.boxSizes=Oe(t,[0,2],[-1,2]),n.div=pe(n.boxOffsets,this.inputSizeTensor),n.boxCenterPoints=ce(n.div,this.anchorsTensor),n.halfBoxSizes=pe(n.boxSizes,this.doubleInputSizeTensor),n.sub=he(n.boxCenterPoints,n.halfBoxSizes),n.startPoints=L(n.sub,this.inputSizeTensor),n.add=ce(n.boxCenterPoints,n.halfBoxSizes),n.endPoints=L(n.add,this.inputSizeTensor);let s=Kl([n.startPoints,n.endPoints],1);return Object.keys(n).forEach(r=>ne(n[r])),s}normalizeLandmarks(t,n){let s={};s.reshape=U(t,[-1,7,2]),s.div=pe(s.reshape,this.inputSizeTensor),s.landmarks=ce(s.div,this.anchors[n]);let r=L(s.landmarks,this.inputSizeTensor);return Object.keys(s).forEach(a=>ne(s[a])),r}async predict(t,n){let s={};s.resize=Ne.resizeBilinear(t,[this.inputSize,this.inputSize]),s.div=pe(s.resize,nt.tf127),s.image=he(s.div,nt.tf1),s.batched=this.model.execute(s.image),s.predictions=rt(s.batched),s.slice=Oe(s.predictions,[0,0],[-1,1]),s.sigmoid=Cn(s.slice),s.scores=rt(s.sigmoid);let r=await s.scores.data();s.boxes=Oe(s.predictions,[0,1],[-1,4]),s.norm=this.normalizeBoxes(s.boxes),s.nms=await Ne.nonMaxSuppressionAsync(s.norm,s.scores,3*n.hand.maxDetected,n.hand.iouThreshold,n.hand.minConfidence);let a=await s.nms.array(),o=[];for(let i of a){let l={};l.box=Oe(s.norm,[i,0],[1,-1]),l.slice=Oe(s.predictions,[i,5],[1,14]),l.norm=this.normalizeLandmarks(l.slice,i),l.palmLandmarks=U(l.norm,[-1,2]);let u=await l.box.data(),c=u.slice(0,2),p=u.slice(2,4),d=await l.palmLandmarks.array(),h={startPoint:c,endPoint:p,palmLandmarks:d,confidence:r[i]},f=GN(h,[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]);o.push(f),Object.keys(l).forEach(m=>ne(l[m]))}return Object.keys(s).forEach(i=>ne(s[i])),o}};var E5e=5,KN=1.65,ZN=[0,5,9,13,17,1,2],R5e=0,_5e=2,YN=0,t1=class{constructor(t,n){me(this,"handDetector");me(this,"handPoseModel");me(this,"inputSize");me(this,"storedBoxes");me(this,"skipped");me(this,"detectedHands");this.handDetector=t,this.handPoseModel=n,this.inputSize=this.handPoseModel&&this.handPoseModel.inputs[0].shape?this.handPoseModel.inputs[0].shape[2]:0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let n=t.map(o=>o[0]),s=t.map(o=>o[1]),r=[Math.min(...n),Math.min(...s)],a=[Math.max(...n),Math.max(...s)];return{startPoint:r,endPoint:a}}getBoxForPalmLandmarks(t,n){let s=t.map(a=>Qb([...a,1],n)),r=this.calculateLandmarksBoundingBox(s);return J2(Q2(r),E5e)}getBoxForHandLandmarks(t){let n=this.calculateLandmarksBoundingBox(t),s=J2(Q2(n),KN);s.palmLandmarks=[];for(let r=0;r<ZN.length;r++)s.palmLandmarks.push(t[ZN[r]].slice(0,2));return s}transformRawCoords(t,n,s,r){let a=Y2(n),o=[a[0]/this.inputSize,a[1]/this.inputSize,(a[0]+a[1])/this.inputSize/2],i=t.map(h=>[o[0]*(h[0]-this.inputSize/2),o[1]*(h[1]-this.inputSize/2),o[2]*h[2]]),l=Jb(s,[0,0]),u=i.map(h=>[...Qb(h,l),h[2]]),c=jN(r),p=[...Kh(n),1],d=[xi(p,c[0]),xi(p,c[1])];return u.map(h=>[Math.trunc(h[0]+d[0]),Math.trunc(h[1]+d[1]),Math.trunc(h[2])])}async estimateHands(t,n){let s=!1,r,a=(n.hand.skipTime||0)>ue()-YN,o=this.skipped<(n.hand.skipFrames||0);n.skipAllowed&&a&&o&&(r=await this.handDetector.predict(t,n),this.skipped=0),n.skipAllowed&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==n.hand.maxDetected||!n.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(s=!0));let i=[];for(let l=0;l<this.storedBoxes.length;l++){let u=this.storedBoxes[l];if(!!u)if(n.hand.landmarks){let c=n.hand.rotation?HN(u.palmLandmarks[R5e],u.palmLandmarks[_5e]):0,p=Kh(u),d=[p[0]/t.shape[2],p[1]/t.shape[1]],h=n.hand.rotation&&fe.kernels.includes("rotatewithoffset")?Ne.rotateWithOffset(t,c,0,d):t.clone(),f=Jb(-c,p),m=s?this.getBoxForPalmLandmarks(u.palmLandmarks,f):u,g=UN(m,h,[this.inputSize,this.inputSize]),y=pe(g,nt.tf255);ne(g),ne(h);let[x,A]=this.handPoseModel.execute(y);YN=ue(),ne(y);let b=(await x.data())[0];if(ne(x),b>=n.hand.minConfidence/4){let w=U(A,[-1,3]),k=await w.array();ne(A),ne(w);let S=this.transformRawCoords(k,m,c,f),E=this.getBoxForHandLandmarks(S);this.storedBoxes[l]={...E,confidence:b};let R={landmarks:S,confidence:b,boxConfidence:u.confidence,fingerConfidence:b,box:{topLeft:E.startPoint,bottomRight:E.endPoint}};i.push(R)}else this.storedBoxes[l]=null;ne(A)}else{let c=J2(Q2(u),KN),p={confidence:u.confidence,boxConfidence:u.confidence,fingerConfidence:0,box:{topLeft:c.startPoint,bottomRight:c.endPoint},landmarks:[]};i.push(p)}}return this.storedBoxes=this.storedBoxes.filter(l=>l!==null),this.detectedHands=i.length,i.length>n.hand.maxDetected&&(i.length=n.hand.maxDetected),i}};var cs={thumb:0,index:1,middle:2,ring:3,pinky:4,all:[0,1,2,3,4],nameMapping:{0:"thumb",1:"index",2:"middle",3:"ring",4:"pinky"},pointsMapping:{0:[[0,1],[1,2],[2,3],[3,4]],1:[[0,5],[5,6],[6,7],[7,8]],2:[[0,9],[9,10],[10,11],[11,12]],3:[[0,13],[13,14],[14,15],[15,16]],4:[[0,17],[17,18],[18,19],[19,20]]},getName:e=>cs.nameMapping[e],getPoints:e=>cs.pointsMapping[e]},vi={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>vi.nameMapping[e]},jt={verticalUp:0,verticalDown:1,horizontalLeft:2,horizontalRight:3,diagonalUpRight:4,diagonalUpLeft:5,diagonalDownRight:6,diagonalDownLeft:7,nameMapping:{0:"verticalUp",1:"verticalDown",2:"horizontalLeft",3:"horizontalRight",4:"diagonalUpRight",5:"diagonalUpLeft",6:"diagonalDownRight",7:"diagonalDownLeft"},getName:e=>jt.nameMapping[e]},bi=class{constructor(t){me(this,"name");me(this,"curls");me(this,"directions");me(this,"weights");me(this,"weightsRelative");this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}curl(t,n,s){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([n,s])}direction(t,n,s){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([n,s])}weight(t,n){this.weights[t]=n;let s=this.weights.reduce((r,a)=>r+a,0);this.weightsRelative=this.weights.map(r=>r*5/s)}matchAgainst(t,n){let s=0;for(let r in t){let a=t[r],o=this.curls[r];if(typeof o=="undefined"){s+=this.weightsRelative[r];continue}for(let[i,l]of o)if(a===i){s+=l*this.weightsRelative[r];break}}for(let r in n){let a=n[r],o=this.directions[r];if(typeof o=="undefined"){s+=this.weightsRelative[r];continue}for(let[i,l]of o)if(a===i){s+=l*this.weightsRelative[r];break}}return s/10}};var{thumb:Mr,index:_a,middle:Da,ring:fu,pinky:mu}=cs,{none:zr,half:$5e,full:Lr}=vi,{verticalUp:kd,verticalDown:$ke,horizontalLeft:e4,horizontalRight:P5e,diagonalUpRight:F5e,diagonalUpLeft:Id,diagonalDownRight:Pke,diagonalDownLeft:Fke}=jt,wi=new bi("thumbs up");wi.curl(Mr,zr,1);wi.direction(Mr,kd,1);wi.direction(Mr,Id,.25);wi.direction(Mr,F5e,.25);for(let e of[cs.index,cs.middle,cs.ring,cs.pinky])wi.curl(e,Lr,1),wi.direction(e,e4,1),wi.direction(e,P5e,1);var dn=new bi("victory");dn.curl(Mr,$5e,.5);dn.curl(Mr,zr,.5);dn.direction(Mr,kd,1);dn.direction(Mr,Id,1);dn.curl(_a,zr,1);dn.direction(_a,kd,.75);dn.direction(_a,Id,1);dn.curl(Da,zr,1);dn.direction(Da,kd,1);dn.direction(Da,Id,.75);dn.curl(fu,Lr,1);dn.direction(fu,kd,.2);dn.direction(fu,Id,1);dn.direction(fu,e4,.2);dn.curl(mu,Lr,1);dn.direction(mu,kd,.2);dn.direction(mu,Id,1);dn.direction(mu,e4,.2);dn.weight(_a,2);dn.weight(Da,2);var ki=new bi("point");ki.curl(Mr,Lr,1);ki.curl(_a,zr,.5);ki.curl(Da,Lr,.5);ki.curl(fu,Lr,.5);ki.curl(mu,Lr,.5);ki.weight(_a,2);ki.weight(Da,2);var Ii=new bi("middle finger");Ii.curl(Mr,zr,1);Ii.curl(_a,Lr,.5);Ii.curl(Da,Lr,.5);Ii.curl(fu,Lr,.5);Ii.curl(mu,Lr,.5);Ii.weight(_a,2);Ii.weight(Da,2);var Sd=new bi("open palm");Sd.curl(Mr,zr,.75);Sd.curl(_a,zr,.75);Sd.curl(Da,zr,.75);Sd.curl(fu,zr,.75);Sd.curl(mu,zr,.75);var JN=[wi,dn,ki,Ii,Sd];var O5e=.7,gu={HALF_CURL_START_LIMIT:60,NO_CURL_START_LIMIT:130,DISTANCE_VOTE_POWER:1.1,SINGLE_ANGLE_VOTE_POWER:.9,TOTAL_ANGLE_VOTE_POWER:1.6};function QN(e,t,n,s){let r=(t-s)/(e-n),a=Math.atan(r)*180/Math.PI;return a<=0?a=-a:a>0&&(a=180-a),a}function tE(e,t){if(!e||!t)return[0,0];let n=QN(e[0],e[1],t[0],t[1]);if(e.length===2)return n;let s=QN(e[1],e[2],t[1],t[2]);return[n,s]}function eE(e,t=1){let n=0,s=0,r=0;return e>=75&&e<=105?n=1*t:e>=25&&e<=155?s=1*t:r=1*t,[n,s,r]}function M5e(e,t,n){let s=e[0]-t[0],r=e[0]-n[0],a=t[0]-n[0],o=e[1]-t[1],i=e[1]-n[1],l=t[1]-n[1],u=e[2]-t[2],c=e[2]-n[2],p=t[2]-n[2],d=Math.sqrt(s*s+o*o+u*u),h=Math.sqrt(r*r+i*i+c*c),f=Math.sqrt(a*a+l*l+p*p),m=(f*f+d*d-h*h)/(2*f*d);m>1?m=1:m<-1&&(m=-1);let g=Math.acos(m);g=57.2958*g%180;let y;return g>gu.NO_CURL_START_LIMIT?y=vi.none:g>gu.HALF_CURL_START_LIMIT?y=vi.half:y=vi.full,y}function nE(e,t,n,s){let r;return s===Math.abs(e)?e>0?r=jt.horizontalLeft:r=jt.horizontalRight:s===Math.abs(t)?t>0?r=jt.horizontalLeft:r=jt.horizontalRight:n>0?r=jt.horizontalLeft:r=jt.horizontalRight,r}function sE(e,t,n,s){let r;return s===Math.abs(e)?e<0?r=jt.verticalDown:r=jt.verticalUp:s===Math.abs(t)?t<0?r=jt.verticalDown:r=jt.verticalUp:n<0?r=jt.verticalDown:r=jt.verticalUp,r}function z5e(e,t,n,s,r,a,o,i){let l,u=sE(e,t,n,s),c=nE(r,a,o,i);return u===jt.verticalUp?c===jt.horizontalLeft?l=jt.diagonalUpLeft:l=jt.diagonalUpRight:c===jt.horizontalLeft?l=jt.diagonalDownLeft:l=jt.diagonalDownRight,l}function L5e(e,t,n,s){let r=e[0]-t[0],a=e[0]-n[0],o=t[0]-n[0],i=e[1]-t[1],l=e[1]-n[1],u=t[1]-n[1],c=Math.max(Math.abs(r),Math.abs(a),Math.abs(o)),p=Math.max(Math.abs(i),Math.abs(l),Math.abs(u)),d=0,h=0,f=0,m=p/(c+1e-5);m>1.5?d+=gu.DISTANCE_VOTE_POWER:m>.66?h+=gu.DISTANCE_VOTE_POWER:f+=gu.DISTANCE_VOTE_POWER;let g=Math.sqrt(r*r+i*i),y=Math.sqrt(a*a+l*l),x=Math.sqrt(o*o+u*u),A=Math.max(g,y,x),b=e[0],w=e[1],k=n[0],S=n[1];A===g?(k=n[0],S=n[1]):A===x&&(b=t[0],w=t[1]);let P=tE([b,w],[k,S]),_=eE(P,gu.TOTAL_ANGLE_VOTE_POWER);d+=_[0],h+=_[1],f+=_[2];for(let T of s){let F=eE(T,gu.SINGLE_ANGLE_VOTE_POWER);d+=F[0],h+=F[1],f+=F[2]}let $;return d===Math.max(d,h,f)?$=sE(l,i,u,p):f===Math.max(h,f)?$=nE(a,r,o,c):$=z5e(l,i,u,p,a,r,o,c),$}function rE(e){let t=[],n=[],s=[],r=[];if(!e)return{curls:s,directions:r};for(let a of cs.all){let o=cs.getPoints(a),i=[],l=[];for(let u of o){let c=e[u[0]],p=e[u[1]],d=tE(c,p),h=d[0],f=d[1];i.push(h),l.push(f)}t.push(i),n.push(l)}for(let a of cs.all){let o=a===cs.thumb?1:0,i=cs.getPoints(a),l=e[i[o][0]],u=e[i[o+1][1]],c=e[i[3][1]],p=M5e(l,u,c),d=L5e(l,u,c,t[a].slice(o));s[a]=p,r[a]=d}return{curls:s,directions:r}}function n1(e){if(!e||e.length===0)return null;let t=rE(e),n={};for(let s of cs.all)n[cs.getName(s)]={curl:vi.getName(t.curls[s]),direction:jt.getName(t.directions[s])};return n}function aE(e){let t=[];if(!e||e.length===0)return t;let n=rE(e);for(let s of JN){let r=s.matchAgainst(n.curls,n.directions);r>=O5e&&t.push({name:s.name,confidence:r})}return t}var oE={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],palm:[0]},Cd,Td,iE;async function n4(e,t){let n=await iE.estimateHands(e,t);if(!n)return[];let s=[];for(let r=0;r<n.length;r++){let a={};if(n[r].landmarks)for(let c of Object.keys(oE))a[c]=oE[c].map(p=>n[r].landmarks[p]);let o=n[r].landmarks,i=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],l=[0,0,0,0];if(o&&o.length>0){for(let c of o)c[0]<i[0]&&(i[0]=c[0]),c[1]<i[1]&&(i[1]=c[1]),c[0]>i[2]&&(i[2]=c[0]),c[1]>i[3]&&(i[3]=c[1]);i[2]-=i[0],i[3]-=i[1],l=[i[0]/(e.shape[2]||0),i[1]/(e.shape[1]||0),i[2]/(e.shape[2]||0),i[3]/(e.shape[1]||0)]}else i=n[r].box?[Math.trunc(Math.max(0,n[r].box.topLeft[0])),Math.trunc(Math.max(0,n[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,n[r].box.bottomRight[0])-Math.max(0,n[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,n[r].box.bottomRight[1])-Math.max(0,n[r].box.topLeft[1]))]:[0,0,0,0],l=[n[r].box.topLeft[0]/(e.shape[2]||0),n[r].box.topLeft[1]/(e.shape[1]||0),(n[r].box.bottomRight[0]-n[r].box.topLeft[0])/(e.shape[2]||0),(n[r].box.bottomRight[1]-n[r].box.topLeft[1])/(e.shape[1]||0)];let u=n1(o);s.push({id:r,score:Math.round(100*n[r].confidence)/100,boxScore:Math.round(100*n[r].boxConfidence)/100,fingerScore:Math.round(100*n[r].fingerConfidence)/100,label:"hand",box:i,boxRaw:l,keypoints:o,annotations:a,landmarks:u})}return s}async function s4(e){var n,s;fe.initial&&(Cd=null,Td=null),!Cd||!Td?[Cd,Td]=await Promise.all([e.hand.enabled?qe((n=e.hand.detector)==null?void 0:n.modelPath):null,e.hand.landmarks?qe((s=e.hand.skeleton)==null?void 0:s.modelPath):null]):(e.debug&&ie("cached model:",Cd.modelUrl),e.debug&&ie("cached model:",Td.modelUrl));let t=new e1(Cd);return iE=new t1(t,Td),[Cd,Td]}var An=[null,null],B5e=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],Si=[[0,0],[0,0]],W5e=["hand","fist","pinch","point","face","tip","pinchtip"],uE=4,cE=1.6,V5e=512,U5e=1.4,s1=Number.MAX_SAFE_INTEGER,r4=0,$a=[0,0],Jt={boxes:[],hands:[]},dE={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],base:[0],palm:[0,17,13,9,5,1,0]};async function pE(e){var t;if(fe.initial&&(An[0]=null),An[0])e.debug&&ie("cached model:",An[0].modelUrl);else{r1(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),An[0]=await qe((t=e.hand.detector)==null?void 0:t.modelPath);let n=Object.values(An[0].modelSignature.inputs);Si[0][0]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[1].size):0,Si[0][1]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[2].size):0}return An[0]}async function hE(e){var t;if(fe.initial&&(An[1]=null),An[1])e.debug&&ie("cached model:",An[1].modelUrl);else{An[1]=await qe((t=e.hand.skeleton)==null?void 0:t.modelPath);let n=Object.values(An[1].modelSignature.inputs);Si[1][0]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[1].size):0,Si[1][1]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[2].size):0}return An[1]}async function G5e(e,t){let n=[];if(!e||!An[0])return n;let s={},r=(e.shape[2]||1)/(e.shape[1]||1),a=Math.min(Math.round((e.shape[1]||0)/8)*8,V5e),o=Math.round(a*r/8)*8;s.resize=Ne.resizeBilinear(e,[a,o]),s.cast=ge(s.resize,"int32"),[s.rawScores,s.rawBoxes]=await An[0].executeAsync(s.cast,B5e),s.boxes=rt(s.rawBoxes,[0,2]),s.scores=rt(s.rawScores,[0]);let i=es(s.scores,1);ne(i[uE]),i.splice(uE,1),s.filtered=on(i,1),ne(i),s.max=mn(s.filtered,1),s.argmax=Es(s.filtered,1);let l=0;s.nms=await Ne.nonMaxSuppressionAsync(s.boxes,s.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let u=await s.nms.data(),c=await s.max.data(),p=await s.argmax.data();for(let d of Array.from(u)){let h=Oe(s.boxes,d,1),f=await h.data();ne(h);let m=[f[1],f[0],f[3]-f[1],f[2]-f[0]],g=G2(m,U5e),y=[Math.trunc(m[0]*$a[0]),Math.trunc(m[1]*$a[1]),Math.trunc(m[2]*$a[0]),Math.trunc(m[3]*$a[1])],x=c[d],A=W5e[p[d]],b={id:l++,score:x,box:y,boxRaw:g,label:A};n.push(b)}return Object.keys(s).forEach(d=>ne(s[d])),n.sort((d,h)=>h.score-d.score),n.length>(t.hand.maxDetected||1)&&(n.length=t.hand.maxDetected||1),n}async function a4(e,t,n){let s={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&An[1]&&n.hand.landmarks&&t.score>(n.hand.minConfidence||0)){let r={},a=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=Ne.cropAndResize(e,[a],[0],[Si[1][0],Si[1][1]],"bilinear"),r.div=pe(r.crop,nt.tf255),[r.score,r.keypoints]=An[1].execute(r.div,["Identity_1","Identity"]);let o=(await r.score.data())[0],i=(100-Math.trunc(100/(1+Math.exp(o))))/100;if(i>=(n.hand.minConfidence||0)){s.fingerScore=i,r.reshaped=U(r.keypoints,[-1,3]);let c=(await r.reshaped.array()).map(p=>[p[0]/Si[1][1],p[1]/Si[1][0],p[2]||0]).map(p=>[p[0]*t.boxRaw[2],p[1]*t.boxRaw[3],p[2]||0]);s.keypoints=c.map(p=>[$a[0]*(p[0]+t.boxRaw[0]),$a[1]*(p[1]+t.boxRaw[1]),p[2]||0]),s.landmarks=n1(s.keypoints);for(let p of Object.keys(dE))s.annotations[p]=dE[p].map(d=>s.landmarks&&s.keypoints[d]?s.keypoints[d]:null)}Object.keys(r).forEach(l=>ne(r[l]))}return s}async function o4(e,t){var r,a;if(!An[0]||!An[1]||!((r=An[0])!=null&&r.inputs[0].shape)||!((a=An[1])!=null&&a.inputs[0].shape))return[];$a=[e.shape[2]||0,e.shape[1]||0],s1++;let n=(t.hand.skipTime||0)>ue()-r4,s=s1<(t.hand.skipFrames||0);return t.skipAllowed&&n&&s?Jt.hands:new Promise(async o=>{let i=3*(t.hand.skipTime||0)>ue()-r4,l=s1<3*(t.hand.skipFrames||0);t.skipAllowed&&Jt.hands.length===t.hand.maxDetected?Jt.hands=await Promise.all(Jt.boxes.map(c=>a4(e,c,t))):t.skipAllowed&&i&&l&&Jt.hands.length>0?Jt.hands=await Promise.all(Jt.boxes.map(c=>a4(e,c,t))):(Jt.boxes=await G5e(e,t),r4=ue(),Jt.hands=await Promise.all(Jt.boxes.map(c=>a4(e,c,t))),s1=0);let u=[...Jt.boxes];if(Jt.boxes.length=0,t.cacheSensitivity>0)for(let c=0;c<Jt.hands.length;c++){let p=rN(Jt.hands[c].keypoints,$a);if(p.box[2]/(e.shape[2]||1)>.05&&p.box[3]/(e.shape[1]||1)>.05&&Jt.hands[c].fingerScore&&Jt.hands[c].fingerScore>(t.hand.minConfidence||0)){let d=G2(p.box,cE),h=G2(p.boxRaw,cE);Jt.boxes.push({...u[c],box:d,boxRaw:h})}}for(let c=0;c<Jt.hands.length;c++){let p=Na(Jt.hands[c].keypoints,$a);Jt.hands[c].box=p.box,Jt.hands[c].boxRaw=p.boxRaw}o(Jt.hands)})}var Wn,a1=[],i4=Number.MAX_SAFE_INTEGER,mE=0,gE=0;async function yE(e){var t;return fe.initial&&(Wn=null),Wn?e.debug&&ie("cached model:",Wn.modelUrl):Wn=await qe((t=e.face.liveness)==null?void 0:t.modelPath),Wn}async function l4(e,t,n,s){var o,i;if(!Wn)return 0;let r=(((o=t.face.liveness)==null?void 0:o.skipTime)||0)>ue()-gE,a=i4<(((i=t.face.liveness)==null?void 0:i.skipFrames)||0);return t.skipAllowed&&r&&a&&mE===s&&a1[n]?(i4++,a1[n]):(i4=0,new Promise(async l=>{let u=Ne.resizeBilinear(e,[Wn!=null&&Wn.inputs[0].shape?Wn.inputs[0].shape[2]:0,Wn!=null&&Wn.inputs[0].shape?Wn.inputs[0].shape[1]:0],!1),c=Wn==null?void 0:Wn.execute(u),p=(await c.data())[0];a1[n]=Math.round(100*p)/100,mE=s,gE=ue(),ne([u,c]),l(a1[n])}))}var Zh={};ia(Zh,{connected:()=>i1,horizontal:()=>u4,kpt:()=>o1,relative:()=>d4,vertical:()=>c4});var o1=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],u4=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],c4=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],d4=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],i1={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var xE=.005,Bs={keypoints:[],padding:[[0,0],[0,0],[0,0],[0,0]]};function p4(e){for(let t of u4){let n=e.keypoints.findIndex(r=>r.part===t[0]),s=e.keypoints.findIndex(r=>r.part===t[1]);if(e.keypoints[n]&&e.keypoints[s]&&e.keypoints[n].position[0]<e.keypoints[s].position[0]){let r=e.keypoints[n];e.keypoints[n]=e.keypoints[s],e.keypoints[s]=r}}for(let t of c4){let n=e.keypoints.findIndex(r=>r&&r.part===t[0]),s=e.keypoints.findIndex(r=>r&&r.part===t[1]);e.keypoints[n]&&e.keypoints[s]&&e.keypoints[n].position[1]<e.keypoints[s].position[1]&&e.keypoints.splice(n,1)}for(let[t,n]of d4){let s=e.keypoints.findIndex(u=>u&&u.part===t[0]),r=e.keypoints.findIndex(u=>u&&u.part===t[1]),a=e.keypoints.findIndex(u=>u&&u.part===n[0]),o=e.keypoints.findIndex(u=>u&&u.part===n[1]);if(!e.keypoints[a]||!e.keypoints[o])continue;let i=e.keypoints[s]?[Math.abs(e.keypoints[a].position[0]-e.keypoints[s].position[0]),Math.abs(e.keypoints[o].position[0]-e.keypoints[s].position[0])]:[0,0],l=e.keypoints[r]?[Math.abs(e.keypoints[o].position[0]-e.keypoints[r].position[0]),Math.abs(e.keypoints[a].position[0]-e.keypoints[r].position[0])]:[0,0];if(i[0]>i[1]||l[0]>l[1]){let u=e.keypoints[s];e.keypoints[s]=e.keypoints[r],e.keypoints[r]=u}}}function bE(e){for(let t=0;t<e.length;t++)if(e[t]&&Bs.keypoints[t]){let n=[Math.abs(e[t].positionRaw[0]-Bs.keypoints[t].positionRaw[0]),Math.abs(e[t].positionRaw[1]-Bs.keypoints[t].positionRaw[1])];n[0]<xE&&n[1]<xE?e[t]=Bs.keypoints[t]:Bs.keypoints[t]=e[t]}else Bs.keypoints[t]=e[t];return e}function vE(e,t){let n={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;Bs.padding=[[0,0],[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0],[0,0]],n.pad=Js(e,Bs.padding),n.resize=Ne.resizeBilinear(n.pad,[t,t]);let s=ge(n.resize,"int32");return Object.keys(n).forEach(r=>ne(n[r])),s}function wE(e,t){e.keypoints=e.keypoints.filter(s=>s&&s.position);for(let s of e.keypoints)s.position=[s.position[0]*(t[0]+Bs.padding[2][0]+Bs.padding[2][1])/t[0]-Bs.padding[2][0],s.position[1]*(t[1]+Bs.padding[1][0]+Bs.padding[1][1])/t[1]-Bs.padding[1][0]],s.positionRaw=[s.position[0]/t[0],s.position[1]/t[1]];let n=Na(e.keypoints.map(s=>s.position),t);return e.box=n.box,e.boxRaw=n.boxRaw,e}var Ws,l1=0,h4=Number.MAX_SAFE_INTEGER,yu={boxes:[],bodies:[],last:0};async function kE(e){return fe.initial&&(Ws=null),Ws?e.debug&&ie("cached model:",Ws.modelUrl):(r1(["size"],e),Ws=await qe(e.body.modelPath)),l1=Ws.inputs[0].shape?Ws.inputs[0].shape[2]:0,l1<64&&(l1=256),Ws}async function j5e(e,t,n){let s=e[0][0],r=[],a=0;for(let c=0;c<s.length;c++)if(a=s[c][2],a>t.body.minConfidence){let p=[s[c][1],s[c][0]];r.push({score:Math.round(100*a)/100,part:o1[c],positionRaw:p,position:[Math.round((n.shape[2]||0)*p[0]),Math.round((n.shape[1]||0)*p[1])]})}a=r.reduce((c,p)=>p.score>c?p.score:c,0);let o=[],i=Na(r.map(c=>c.position),[n.shape[2],n.shape[1]]),l={};for(let[c,p]of Object.entries(i1)){let d=[];for(let h=0;h<p.length-1;h++){let f=r.find(g=>g.part===p[h]),m=r.find(g=>g.part===p[h+1]);f&&m&&f.score>(t.body.minConfidence||0)&&m.score>(t.body.minConfidence||0)&&d.push([f.position,m.position])}l[c]=d}let u={id:0,score:a,box:i.box,boxRaw:i.boxRaw,keypoints:r,annotations:l};return p4(u),o.push(u),o}async function q5e(e,t,n){let s=[];for(let r=0;r<e[0].length;r++){let a=e[0][r],o=Math.round(100*a[51+4])/100;if(o>t.body.minConfidence){let i=[];for(let p=0;p<17;p++){let d=a[3*p+2];if(d>t.body.minConfidence){let h=[a[3*p+1],a[3*p+0]];i.push({part:o1[p],score:Math.round(100*d)/100,positionRaw:h,position:[Math.round((n.shape[2]||0)*h[0]),Math.round((n.shape[1]||0)*h[1])]})}}let l=Na(i.map(p=>p.position),[n.shape[2],n.shape[1]]),u={};for(let[p,d]of Object.entries(i1)){let h=[];for(let f=0;f<d.length-1;f++){let m=i.find(y=>y.part===d[f]),g=i.find(y=>y.part===d[f+1]);m&&g&&m.score>(t.body.minConfidence||0)&&g.score>(t.body.minConfidence||0)&&h.push([m.position,g.position])}u[p]=h}let c={id:r,score:o,box:l.box,boxRaw:l.boxRaw,keypoints:[...i],annotations:u};p4(c),s.push(c)}}return s.sort((r,a)=>a.score-r.score),s.length>t.body.maxDetected&&(s.length=t.body.maxDetected),s}async function f4(e,t){if(!Ws||!(Ws!=null&&Ws.inputs[0].shape))return[];t.skipAllowed||(yu.boxes.length=0),h4++;let n=(t.body.skipTime||0)>ue()-yu.last,s=h4<(t.body.skipFrames||0);return t.skipAllowed&&n&&s?yu.bodies:new Promise(async r=>{let a={};h4=0,a.input=vE(e,l1),a.res=Ws==null?void 0:Ws.execute(a.input),yu.last=ue();let o=await a.res.array();yu.bodies=a.res.shape[2]===17?await j5e(o,t,e):await q5e(o,t,e);for(let i of yu.bodies)wE(i,[e.shape[2]||1,e.shape[1]||1]),bE(i.keypoints);Object.keys(a).forEach(i=>ne(a[i])),r(yu.bodies)})}var Nd,u1=[],SE=0,m4=Number.MAX_SAFE_INTEGER,d1=0,c1=2.5;async function CE(e){if(!Nd||fe.initial){Nd=await qe(e.object.modelPath);let t=Object.values(Nd.modelSignature.inputs);d1=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&ie("cached model:",Nd.modelUrl);return Nd}async function X5e(e,t,n){let s=0,r=[];for(let l of[1,2,4])J(async()=>{let u=l*13,c=rt(e.find(m=>m.shape[1]===u**2&&(m.shape[2]||0)===bd.length)),p=rt(e.find(m=>m.shape[1]===u**2&&(m.shape[2]||0)<bd.length)),h=await p.reshape([-1,4,p.shape[1]/4]).argMax(2).array(),f=await c.array();for(let m=0;m<c.shape[0];m++)for(let g=0;g<c.shape[1];g++){let y=f[m][g];if(y>(n.object.minConfidence||0)&&g!==61){let x=(.5+Math.trunc(m%u))/u,A=(.5+Math.trunc(m/u))/u,b=h[m].map($=>$*(u/l/d1)),[w,k]=[x-c1/l*b[0],A-c1/l*b[1]],[S,E]=[x+c1/l*b[2]-w,A+c1/l*b[3]-k],R=[w,k,S,E];R=R.map($=>Math.max(0,Math.min($,1)));let P=[R[0]*t[0],R[1]*t[1],R[2]*t[0],R[3]*t[1]],_={id:s++,score:Math.round(100*y)/100,class:g+1,label:bd[g].label,box:P.map($=>Math.trunc($)),boxRaw:R};r.push(_)}}});e.forEach(l=>ne(l));let a=r.map(l=>[l.boxRaw[1],l.boxRaw[0],l.boxRaw[3],l.boxRaw[2]]),o=r.map(l=>l.score),i=[];if(a&&a.length>0){let l=await Ne.nonMaxSuppressionAsync(a,o,n.object.maxDetected,n.object.iouThreshold,n.object.minConfidence);i=await l.data(),ne(l)}return r=r.filter((l,u)=>i.includes(u)).sort((l,u)=>u.score-l.score),r}async function g4(e,t){let n=(t.object.skipTime||0)>ue()-SE,s=m4<(t.object.skipFrames||0);return t.skipAllowed&&n&&s&&u1.length>0?(m4++,u1):(m4=0,!fe.kernels.includes("mod")||!fe.kernels.includes("sparsetodense")?u1:new Promise(async r=>{let a=[e.shape[2]||0,e.shape[1]||0],o=Ne.resizeBilinear(e,[d1,d1],!1),i=pe(o,nt.tf255),l=i.transpose([0,3,1,2]);ne(i),ne(o);let u;t.object.enabled&&(u=Nd.execute(l)),SE=ue(),ne(l);let c=await X5e(u,a,t);u1=c,r(c)}))}var Jh=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],K5e=Jh.length,Yh=Jh.reduce((e,t,n)=>(e[t]=n,e),{}),Z5e=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],aIe=Z5e.map(([e,t])=>[Yh[e],Yh[t]]),NE=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function EE(e){let t=e.reduce(({maxX:n,maxY:s,minX:r,minY:a},{position:{x:o,y:i}})=>({maxX:Math.max(n,o),maxY:Math.max(s,i),minX:Math.min(r,o),minY:Math.min(a,i)}),{maxX:Number.NEGATIVE_INFINITY,maxY:Number.NEGATIVE_INFINITY,minX:Number.POSITIVE_INFINITY,minY:Number.POSITIVE_INFINITY});return[t.minX,t.minY,t.maxX-t.minX,t.maxY-t.minY]}function RE(e,[t,n],[s,r]){let a=t/s,o=n/r,i=(u,c)=>({id:c,score:u.score,boxRaw:[u.box[0]/r,u.box[1]/s,u.box[2]/r,u.box[3]/s],box:[Math.trunc(u.box[0]*o),Math.trunc(u.box[1]*a),Math.trunc(u.box[2]*o),Math.trunc(u.box[3]*a)],keypoints:u.keypoints.map(({score:p,part:d,position:h})=>({score:p,part:d,position:[Math.trunc(h.x*o),Math.trunc(h.y*a)],positionRaw:[h.x/s,h.y/s]})),annotations:{}});return e.map((u,c)=>i(u,c))}var p1=class{constructor(t,n){me(this,"priorityQueue");me(this,"numberOfElements");me(this,"getElementValue");this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=n}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(Math.floor(t/2),t);)this.exchange(t,Math.floor(t/2)),t=Math.floor(t/2)}sink(t){for(;2*t<=this.numberOfElements;){let n=2*t;if(n<this.numberOfElements&&this.less(n,n+1)&&n++,!this.less(t,n))break;this.exchange(t,n),t=n}}getValueAt(t){return this.getElementValue(this.priorityQueue[t])}less(t,n){return this.getValueAt(t)<this.getValueAt(n)}exchange(t,n){let s=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[n],this.priorityQueue[n]=s}};function y4(e,t,n,s){return{y:s.get(e,t,n),x:s.get(e,t,n+K5e)}}function A4(e,t,n){let{heatmapY:s,heatmapX:r,id:a}=e,{y:o,x:i}=y4(s,r,a,n);return{x:e.heatmapX*t+i,y:e.heatmapY*t+o}}function x4(e,t,n){return e<t?t:e>n?n:e}function _E(e,t,n,s){let r=n-e,a=s-t;return r*r+a*a}function b4(e,t){return{x:e.x+t.x,y:e.y+t.y}}var Br,J5e=["MobilenetV1/offset_2/BiasAdd","MobilenetV1/heatmap_2/BiasAdd","MobilenetV1/displacement_fwd_2/BiasAdd","MobilenetV1/displacement_bwd_2/BiasAdd"],h1=1,Ed=16,Q5e=50**2;function DE(e,t,n,s,r,a,o=2){let i=y=>({y:a.get(y.y,y.x,e),x:a.get(y.y,y.x,a.shape[2]/2+e)}),l=(y,x,A)=>({y:x4(Math.round(y.y/Ed),0,x-1),x:x4(Math.round(y.x/Ed),0,A-1)}),[u,c]=s.shape,p=l(t.position,u,c),d=i(p),f=b4(t.position,d);for(let y=0;y<o;y++){let x=l(f,u,c),A=y4(x.y,x.x,n,r);f=b4({x:x.x*Ed,y:x.y*Ed},{x:A.x,y:A.y})}let m=l(f,u,c),g=s.get(m.y,m.x,n);return{position:f,part:Jh[n],score:g}}function exe(e,t,n,s,r){let a=NE.map(([d,h])=>[Yh[d],Yh[h]]),o=a.map(([,d])=>d),i=a.map(([d])=>d),l=t.shape[2],u=o.length,c=new Array(l),p=A4(e.part,Ed,n);c[e.part.id]={score:e.score,part:Jh[e.part.id],position:p};for(let d=u-1;d>=0;--d){let h=o[d],f=i[d];c[h]&&!c[f]&&(c[f]=DE(d,c[h],f,t,n,r))}for(let d=0;d<u;++d){let h=i[d],f=o[d];c[h]&&!c[f]&&(c[f]=DE(d,c[h],f,t,n,s))}return c}function txe(e,t,n,s,r){let[a,o]=r.shape,i=!0,l=Math.max(n-h1,0),u=Math.min(n+h1+1,a);for(let c=l;c<u;++c){let p=Math.max(s-h1,0),d=Math.min(s+h1+1,o);for(let h=p;h<d;++h)if(r.get(c,h,e)>t){i=!1;break}if(!i)break}return i}function nxe(e,t){let[n,s,r]=t.shape,a=new p1(n*s*r,({score:o})=>o);for(let o=0;o<n;++o)for(let i=0;i<s;++i)for(let l=0;l<r;++l){let u=t.get(o,i,l);u<e||txe(l,u,o,i,t)&&a.enqueue({score:u,part:{heatmapY:o,heatmapX:i,id:l}})}return a}function $E(e,{x:t,y:n},s){return e.some(({keypoints:r})=>{var o;let a=(o=r[s])==null?void 0:o.position;return a?_E(n,t,a.y,a.x)<=Q5e:!1})}function sxe(e,t){return t.reduce((s,{position:r,score:a},o)=>($E(e,r,o)||(s+=a),s),0)/t.length}function rxe(e,t,n,s,r,a){let o=[],i=nxe(a,t);for(;o.length<r&&!i.empty();){let l=i.dequeue(),u=A4(l.part,Ed,e);if($E(o,u,l.part.id))continue;let c=exe(l,t,e,n,s);c=c.filter(h=>h.score>a);let p=sxe(o,c),d=EE(c);p>a&&o.push({keypoints:c,box:d,score:Math.round(100*p)/100})}return o}async function v4(e,t){let n=J(()=>{if(!Br.inputs[0].shape)return[];let o=Ne.resizeBilinear(e,[Br.inputs[0].shape[2],Br.inputs[0].shape[1]]),i=he(pe(ge(o,"float32"),127.5),1),u=Br.execute(i,J5e).map(c=>rt(c,[0]));return u[1]=Cn(u[1]),u}),s=await Promise.all(n.map(o=>o.buffer()));for(let o of n)ne(o);let r=await rxe(s[0],s[1],s[2],s[3],t.body.maxDetected,t.body.minConfidence);return Br.inputs[0].shape?RE(r,[e.shape[1],e.shape[2]],[Br.inputs[0].shape[2],Br.inputs[0].shape[1]]):[]}async function PE(e){return!Br||fe.initial?Br=await qe(e.body.modelPath):e.debug&&ie("cached model:",Br.modelUrl),Br}var na,w4=!1;async function k4(e){return!na||fe.initial?na=await qe(e.segmentation.modelPath):e.debug&&ie("cached model:",na.modelUrl),na}async function OE(e,t,n){var m,g;if(w4)return{data:[],canvas:null,alpha:null};w4=!0,na||await k4(n);let s=await gd(e,n),r=((m=s.tensor)==null?void 0:m.shape[2])||0,a=((g=s.tensor)==null?void 0:g.shape[1])||0;if(!s.tensor)return{data:[],canvas:null,alpha:null};let o={};o.resize=Ne.resizeBilinear(s.tensor,[na.inputs[0].shape?na.inputs[0].shape[1]:0,na.inputs[0].shape?na.inputs[0].shape[2]:0],!1),ne(s.tensor),o.norm=pe(o.resize,nt.tf255),o.res=na.execute(o.norm),o.squeeze=rt(o.res,0),o.squeeze.shape[2]===2?(o.softmax=Jl(o.squeeze),[o.bg,o.fg]=es(o.softmax,2),o.expand=Kt(o.fg,2),o.pad=Kt(o.expand,0),o.crop=Ne.cropAndResize(o.pad,[[0,0,.5,.5]],[0],[r,a]),o.data=rt(o.crop,0)):o.data=Ne.resizeBilinear(o.squeeze,[a,r]);let i=Array.from(await o.data.data());if(fe.node&&!fe.Canvas&&typeof ImageData=="undefined")return n.debug&&ie("canvas support missing"),Object.keys(o).forEach(y=>ne(o[y])),{data:i,canvas:null,alpha:null};let l=is(r,a);Ys&&await Ys.toPixels(o.data,l);let u=l.getContext("2d");n.segmentation.blur&&n.segmentation.blur>0&&(u.filter=`blur(${n.segmentation.blur}px)`);let c=u.getImageData(0,0,r,a),p=is(r,a),d=p.getContext("2d");s.canvas&&d.drawImage(s.canvas,0,0),d.globalCompositeOperation="darken",n.segmentation.blur&&n.segmentation.blur>0&&(d.filter=`blur(${n.segmentation.blur}px)`),d.drawImage(l,0,0),d.globalCompositeOperation="source-over",d.filter="none";let h=d.getImageData(0,0,r,a);for(let y=0;y<r*a;y++)h.data[4*y+3]=c.data[4*y+0];d.putImageData(h,0,0);let f=null;if(t&&p){f=is(r,a);let y=await gd(t,n);ne(y.tensor);let x=f.getContext("2d");x.drawImage(y.canvas,0,0,f.width,f.height),x.drawImage(p,0,0)}return Object.keys(o).forEach(y=>ne(o[y])),w4=!1,{data:i,canvas:p,alpha:l}}var Qh=class{constructor(){me(this,"ssrnetage",null);me(this,"gear",null);me(this,"blazeposedetect",null);me(this,"blazepose",null);me(this,"centernet",null);me(this,"efficientpose",null);me(this,"mobilefacenet",null);me(this,"emotion",null);me(this,"facedetect",null);me(this,"faceiris",null);me(this,"facemesh",null);me(this,"faceres",null);me(this,"ssrnetgender",null);me(this,"handpose",null);me(this,"handskeleton",null);me(this,"handtrack",null);me(this,"liveness",null);me(this,"movenet",null);me(this,"nanodet",null);me(this,"posenet",null);me(this,"segmentation",null);me(this,"antispoof",null)}},I4=e=>{let t=0,n=0,s=0;for(let a of Object.values(Or))t+=a.sizeFromManifest,n+=a.sizeLoadedWeights,s+=a.sizeDesired;let r=s>0?n/s:0;return{numLoadedModels:Object.values(Or).length,numEnabledModels:void 0,numDefinedModels:Object.keys(e.models).length,percentageLoaded:r,totalSizeFromManifest:t,totalSizeWeights:n,totalSizeLoading:s,totalSizeEnabled:void 0,modelStats:Object.values(Or)}};function f1(e){for(let t of Object.keys(e.models))e.models[t]=null}async function S4(e){var t,n,s,r,a,o,i,l,u,c,p,d,h,f,m,g,y,x,A,b,w,k,S,E,R,P,_,$,T,F,G;fe.initial&&f1(e),e.config.hand.enabled&&(!e.models.handpose&&((n=(t=e.config.hand.detector)==null?void 0:t.modelPath)==null?void 0:n.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await s4(e.config)),!e.models.handskeleton&&e.config.hand.landmarks&&((r=(s=e.config.hand.detector)==null?void 0:s.modelPath)==null?void 0:r.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await s4(e.config))),e.config.body.enabled&&!e.models.blazepose&&((o=(a=e.config.body)==null?void 0:a.modelPath)==null?void 0:o.includes("blazepose"))&&(e.models.blazepose=uN(e.config)),e.config.body.enabled&&!e.models.blazeposedetect&&e.config.body.detector&&e.config.body.detector.modelPath&&(e.models.blazeposedetect=lN(e.config)),e.config.body.enabled&&!e.models.efficientpose&&((l=(i=e.config.body)==null?void 0:i.modelPath)==null?void 0:l.includes("efficientpose"))&&(e.models.efficientpose=mN(e.config)),e.config.body.enabled&&!e.models.movenet&&((c=(u=e.config.body)==null?void 0:u.modelPath)==null?void 0:c.includes("movenet"))&&(e.models.movenet=kE(e.config)),e.config.body.enabled&&!e.models.posenet&&((d=(p=e.config.body)==null?void 0:p.modelPath)==null?void 0:d.includes("posenet"))&&(e.models.posenet=PE(e.config)),e.config.face.enabled&&!e.models.facedetect&&(e.models.facedetect=QT(e.config)),e.config.face.enabled&&((h=e.config.face.antispoof)==null?void 0:h.enabled)&&!e.models.antispoof&&(e.models.antispoof=BT(e.config)),e.config.face.enabled&&((f=e.config.face.liveness)==null?void 0:f.enabled)&&!e.models.liveness&&(e.models.liveness=yE(e.config)),e.config.face.enabled&&((m=e.config.face.description)==null?void 0:m.enabled)&&!e.models.faceres&&(e.models.faceres=BN(e.config)),e.config.face.enabled&&((g=e.config.face.emotion)==null?void 0:g.enabled)&&!e.models.emotion&&(e.models.emotion=xN(e.config)),e.config.face.enabled&&((y=e.config.face.iris)==null?void 0:y.enabled)&&!((x=e.config.face.attention)!=null&&x.enabled)&&!e.models.faceiris&&(e.models.faceiris=EN(e.config)),e.config.face.enabled&&((A=e.config.face.mesh)==null?void 0:A.enabled)&&!e.models.facemesh&&(e.models.facemesh=FN(e.config)),e.config.face.enabled&&((b=e.config.face.gear)==null?void 0:b.enabled)&&!e.models.gear&&(e.models.gear=TT(e.config)),e.config.face.enabled&&((w=e.config.face.ssrnet)==null?void 0:w.enabled)&&!e.models.ssrnetage&&(e.models.ssrnetage=DT(e.config)),e.config.face.enabled&&((k=e.config.face.ssrnet)==null?void 0:k.enabled)&&!e.models.ssrnetgender&&(e.models.ssrnetgender=OT(e.config)),e.config.face.enabled&&((S=e.config.face.mobilefacenet)==null?void 0:S.enabled)&&!e.models.mobilefacenet&&(e.models.mobilefacenet=IN(e.config)),e.config.hand.enabled&&!e.models.handtrack&&((R=(E=e.config.hand.detector)==null?void 0:E.modelPath)==null?void 0:R.includes("handtrack"))&&(e.models.handtrack=pE(e.config)),e.config.hand.enabled&&e.config.hand.landmarks&&!e.models.handskeleton&&((_=(P=e.config.hand.detector)==null?void 0:P.modelPath)==null?void 0:_.includes("handtrack"))&&(e.models.handskeleton=hE(e.config)),e.config.object.enabled&&!e.models.centernet&&((T=($=e.config.object)==null?void 0:$.modelPath)==null?void 0:T.includes("centernet"))&&(e.models.centernet=pN(e.config)),e.config.object.enabled&&!e.models.nanodet&&((G=(F=e.config.object)==null?void 0:F.modelPath)==null?void 0:G.includes("nanodet"))&&(e.models.nanodet=CE(e.config)),e.config.segmentation.enabled&&!e.models.segmentation&&(e.models.segmentation=k4(e.config));for await(let q of Object.keys(e.models))e.models[q]&&typeof e.models[q]!="undefined"&&(e.models[q]=await e.models[q])}async function C4(e){let t=["const","placeholder","noop","pad","squeeze","add","sub","mul","div"];for(let n of Object.keys(e.models)){let s=e.models[n];if(!s)continue;let r=[],a=s==null?void 0:s.executor;if(a&&a.graph.nodes)for(let i of Object.values(a.graph.nodes)){let l=i.op.toLowerCase();r.includes(l)||r.push(l)}else!a&&e.config.debug&&ie("model signature not determined:",n);let o=[];for(let i of r)!t.includes(i)&&!e.env.kernels.includes(i)&&!e.env.kernels.includes(i.replace("_",""))&&!e.env.kernels.includes(i.replace("native",""))&&!e.env.kernels.includes(i.replace("v2",""))&&o.push(i);e.config.debug&&o.length>0&&ie("model validation failed:",n,o)}}var Pt={name:"humangl",priority:999,canvas:null,gl:null,extensions:[],webGLattr:{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!1,desynchronized:!0}};function axe(){let e=Pt.gl;!e||(Pt.extensions=e.getSupportedExtensions())}async function zE(e){var t;if(e.config.backend==="humangl"&&(Pt.name in sn().registry&&(!Pt.gl||!Pt.gl.getParameter(Pt.gl.VERSION))&&(ie("error: humangl backend invalid context"),f1(e)),!Oy(Pt.name))){try{Pt.canvas=await is(100,100)}catch(s){ie("error: cannot create canvas:",s);return}try{if(Pt.gl=(t=Pt.canvas)==null?void 0:t.getContext("webgl2",Pt.webGLattr),!Pt.gl.getParameter(Pt.gl.VERSION).includes("2.0")){ie("override: using fallback webgl backend as webgl 2.0 is not detected"),e.config.backend="webgl";return}Pt.canvas&&(Pt.canvas.addEventListener("webglcontextlost",async r=>{throw ie("error: humangl:",r.type),ie("possible browser memory leak using webgl or conflict with multiple backend registrations"),e.emit("error"),new Error("backend error: webgl context lost")}),Pt.canvas.addEventListener("webglcontextrestored",r=>{ie("error: humangl context restored:",r)}),Pt.canvas.addEventListener("webglcontextcreationerror",r=>{ie("error: humangl context create:",r)}))}catch(s){ie("error: cannot get WebGL context:",s);return}try{x2(2,Pt.gl)}catch(s){ie("error: cannot set WebGL context:",s);return}try{let s=new ju(Pt.gl);ql(Pt.name,()=>new id(s),Pt.priority)}catch(s){ie("error: cannot register WebGL backend:",s);return}try{qr("webgl").forEach(r=>{let a={...r,backendName:Pt.name};cr(a)})}catch(s){ie("error: cannot update WebGL backend registration:",s);return}let n=Zs().getGPGPUContext?Zs().getGPGPUContext().gl:null;if(n)ie(`humangl webgl version:${n.getParameter(n.VERSION)} renderer:${n.getParameter(n.RENDERER)}`);else{ie("error: no current gl context:",n,Pt.gl);return}try{$r.set("WEBGL_VERSION",2)}catch(s){ie("error: cannot set WebGL backend flags:",s);return}axe(),ie("backend registered:",Pt.name)}}function oxe(){if(!fe.kernels.includes("mod")){let e={kernelName:"Mod",backendName:ss(),kernelFunc:t=>J(()=>he(t.inputs.a,L(pe(t.inputs.a,t.inputs.b),t.inputs.b)))};cr(e),fe.kernels.push("mod")}if(!fe.kernels.includes("floormod")){let e={kernelName:"FloorMod",backendName:ss(),kernelFunc:t=>J(()=>Bc(t.inputs.a/t.inputs.b)*t.inputs.b+Yl(t.inputs.a,t.inputs.b))};cr(e),fe.kernels.push("floormod")}}async function g1(e,t=!1){if(e.state="backend",t||fe.initial||e.config.backend&&e.config.backend.length>0&&ss()!==e.config.backend){let n=ue();if(e.config.backend&&e.config.backend.length>0){if(typeof window=="undefined"&&typeof WorkerGlobalScope!="undefined"&&e.config.debug&&e.config.debug&&ie("running inside web worker"),fe.browser&&e.config.backend==="tensorflow"&&(e.config.debug&&ie("override: backend set to tensorflow while running in browser"),e.config.backend="humangl"),fe.node&&(e.config.backend==="webgl"||e.config.backend==="humangl")&&(e.config.debug&&ie(`override: backend set to ${e.config.backend} while running in nodejs`),e.config.backend="tensorflow"),fe.browser&&e.config.backend==="webgpu")if(typeof navigator=="undefined"||typeof navigator.gpu=="undefined")ie("override: backend set to webgpu but browser does not support webgpu"),e.config.backend="humangl";else{let r=await navigator.gpu.requestAdapter();if(e.config.debug&&ie("enumerated webgpu adapter:",r),!r)ie("override: backend set to webgpu but browser reports no available gpu"),e.config.backend="humangl";else{let a="requestAdapterInfo"in r?await r.requestAdapterInfo():void 0;ie("webgpu adapter info:",a)}}e.config.backend==="humangl"&&await zE(e);let s=Object.keys(sn().registryFactory);if(e.config.debug&&ie("available backends:",s),s.includes(e.config.backend)||(ie(`error: backend ${e.config.backend} not found in registry`),e.config.backend=fe.node?"tensorflow":"webgl",e.config.debug&&ie(`override: setting backend ${e.config.backend}`)),e.config.debug&&ie("setting backend:",e.config.backend),e.config.backend==="wasm"){try{Z().set("CANVAS2D_WILL_READ_FREQUENTLY",!0)}catch(o){}if(e.config.debug&&ie("wasm path:",e.config.wasmPath),typeof(je==null?void 0:je.setWasmPaths)!="undefined")await tb(e.config.wasmPath,e.config.wasmPlatformFetch);else throw new Error("backend error: attempting to use wasm backend but wasm path is not set");let r=await Z().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await Z().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");e.config.debug&&ie(`wasm execution: ${r?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),e.config.debug&&!r&&ie("warning: wasm simd support is not enabled")}try{await Fy(e.config.backend),await Lc(),ET()}catch(r){return ie("error: cannot set backend:",e.config.backend,r),!1}}if(ss()==="humangl"&&($r.set("CHECK_COMPUTATION_FOR_ERRORS",!1),$r.set("WEBGL_CPU_FORWARD",!0),$r.set("WEBGL_USE_SHAPES_UNIFORMS",!0),$r.set("CPU_HANDOFF_SIZE_THRESHOLD",256),typeof e.config.deallocate!="undefined"&&e.config.deallocate&&(ie("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),$r.set("WEBGL_DELETE_TEXTURE_THRESHOLD",0)),Zs().getGPGPUContext)){let s=await Zs().getGPGPUContext().gl;e.config.debug&&ie(`gl version:${s.getParameter(s.VERSION)} renderer:${s.getParameter(s.RENDERER)}`)}ss(),$y(),await Lc(),e.performance.initBackend=Math.trunc(ue()-n),e.config.backend=ss(),await fe.updateBackend(),oxe()}return!0}function r1(e,t){for(let n of e){let s={kernelName:n,backendName:t.backend,kernelFunc:()=>{t.debug&&ie("kernelFunc",n,t.backend)}};cr(s)}fe.kernels=qr(ss()).map(n=>n.kernelName.toLowerCase())}var $4={};ia($4,{all:()=>D4,body:()=>_d,canvas:()=>_4,face:()=>Rd,gesture:()=>Pd,hand:()=>Dd,object:()=>$d,options:()=>Vn,person:()=>R4});var tr=e=>{if(!e)ie("draw error: invalid canvas");else if(!e.getContext)ie("draw error: canvas context not defined");else{let t=e.getContext("2d");if(!t)ie("draw error: cannot get canvas context");else return t}return null},Au=e=>Math.round(e*180/Math.PI),Pa=(e,t)=>{if(!t.useDepth||typeof e=="undefined")return t.color;let n=Uint8ClampedArray.from([127+2*e,127-2*e,255]);return`rgba(${n[0]}, ${n[1]}, ${n[2]}, ${t.alpha})`};function Fa(e,t,n,s,r){e.fillStyle=Pa(s,r),e.beginPath(),e.arc(t,n,r.pointSize,0,2*Math.PI),e.fill()}function sa(e,t,n,s,r,a){if(e.beginPath(),e.lineWidth=a.lineWidth,a.useCurves){let o=(t+t+s)/2,i=(n+n+r)/2;e.ellipse(o,i,s/2,r/2,0,0,2*Math.PI)}else e.moveTo(t+a.roundRect,n),e.lineTo(t+s-a.roundRect,n),e.quadraticCurveTo(t+s,n,t+s,n+a.roundRect),e.lineTo(t+s,n+r-a.roundRect),e.quadraticCurveTo(t+s,n+r,t+s-a.roundRect,n+r),e.lineTo(t+a.roundRect,n+r),e.quadraticCurveTo(t,n+r,t,n+r-a.roundRect),e.lineTo(t,n+a.roundRect),e.quadraticCurveTo(t,n,t+a.roundRect,n),e.closePath();e.stroke()}function T4(e,t,n){if(!(t.length<2)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let s of t)e.strokeStyle=Pa(s[2]||0,n),e.lineTo(Math.trunc(s[0]),Math.trunc(s[1]));e.stroke(),n.fillPolygons&&(e.closePath(),e.fill())}}function BE(e,t,n){if(!(t.length<2)){if(e.lineWidth=n.lineWidth,!n.useCurves||t.length<=2){T4(e,t,n);return}e.moveTo(t[0][0],t[0][1]);for(let s=0;s<t.length-2;s++){let r=(t[s][0]+t[s+1][0])/2,a=(t[s][1]+t[s+1][1])/2;e.quadraticCurveTo(t[s][0],t[s][1],r,a)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),n.fillPolygons&&(e.closePath(),e.fill())}}function N4(e,t,n,s=5){let r,a,o;e.beginPath(),e.moveTo(t[0],t[1]),e.lineTo(n[0],n[1]),r=Math.atan2(n[1]-t[1],n[0]-t[0]),a=s*Math.cos(r)+n[0],o=s*Math.sin(r)+n[1],e.moveTo(a,o),r+=1/3*(2*Math.PI),a=s*Math.cos(r)+n[0],o=s*Math.sin(r)+n[1],e.lineTo(a,o),r+=1/3*(2*Math.PI),a=s*Math.cos(r)+n[0],o=s*Math.sin(r)+n[1],e.lineTo(a,o),e.closePath(),e.stroke(),e.fill()}var Vn={color:"rgba(173, 216, 230, 0.6)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",alpha:.5,font:'small-caps 16px "Segoe UI"',lineHeight:18,lineWidth:4,pointSize:2,roundRect:8,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawAttention:!0,drawGestures:!0,drawPolygons:!0,drawGaze:!0,fillPolygons:!1,useDepth:!0,useCurves:!1};var gt;function lxe(e,t){if(gt.drawLabels){let n=[];if(n.push(`face: ${Math.trunc(100*e.score)}%`),e.genderScore&&n.push(`${e.gender||""} ${Math.trunc(100*e.genderScore)}%`),e.age&&n.push(`age: ${e.age||""}`),e.iris&&n.push(`distance: ${e.iris}`),e.real&&n.push(`real: ${Math.trunc(100*e.real)}%`),e.live&&n.push(`live: ${Math.trunc(100*e.live)}%`),e.emotion&&e.emotion.length>0){let s=e.emotion.map(r=>`${Math.trunc(100*r.score)}% ${r.emotion}`);s.length>3&&(s.length=3),n.push(s.join(" "))}e.rotation&&e.rotation.angle&&e.rotation.gaze&&(e.rotation.angle.roll&&n.push(`roll: ${Au(e.rotation.angle.roll)}\xB0 yaw:${Au(e.rotation.angle.yaw)}\xB0 pitch:${Au(e.rotation.angle.pitch)}\xB0`),e.rotation.gaze.bearing&&n.push(`gaze: ${Au(e.rotation.gaze.bearing)}\xB0`)),n.length===0&&n.push("face"),t.fillStyle=gt.color;for(let s=n.length-1;s>=0;s--){let r=Math.max(e.box[0],0),a=s*gt.lineHeight+e.box[1];gt.shadowColor&&gt.shadowColor!==""&&(t.fillStyle=gt.shadowColor,t.fillText(n[s],r+5,a+16)),t.fillStyle=gt.labelColor,t.fillText(n[s],r+4,a+15)}}}function uxe(e,t){if(e.annotations&&e.annotations.leftEyeIris&&e.annotations.leftEyeIris[0]){t.strokeStyle=gt.useDepth?"rgba(255, 200, 255, 0.3)":gt.color,t.beginPath();let n=Math.abs(e.annotations.leftEyeIris[3][0]-e.annotations.leftEyeIris[1][0])/2,s=Math.abs(e.annotations.leftEyeIris[4][1]-e.annotations.leftEyeIris[2][1])/2;t.ellipse(e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1],n,s,0,0,2*Math.PI),t.stroke(),gt.fillPolygons&&(t.fillStyle=gt.useDepth?"rgba(255, 255, 200, 0.3)":gt.color,t.fill())}if(e.annotations&&e.annotations.rightEyeIris&&e.annotations.rightEyeIris[0]){t.strokeStyle=gt.useDepth?"rgba(255, 200, 255, 0.3)":gt.color,t.beginPath();let n=Math.abs(e.annotations.rightEyeIris[3][0]-e.annotations.rightEyeIris[1][0])/2,s=Math.abs(e.annotations.rightEyeIris[4][1]-e.annotations.rightEyeIris[2][1])/2;t.ellipse(e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1],n,s,0,0,2*Math.PI),t.stroke(),gt.fillPolygons&&(t.fillStyle=gt.useDepth?"rgba(255, 255, 200, 0.3)":gt.color,t.fill())}}function cxe(e,t){var n;if(gt.drawGaze&&((n=e.rotation)==null?void 0:n.angle)&&typeof Path2D!="undefined"){t.strokeStyle="pink";let s=e.box[0]+e.box[2]/2-e.box[3]*Au(e.rotation.angle.yaw)/90,r=e.box[1]+e.box[3]/2+e.box[2]*Au(e.rotation.angle.pitch)/90,a=new Path2D(`
+`;var ub=(e,t,n)=>{let s=new RegExp("\\b"+t+" \\w+ (\\w+)","ig");e.replace(s,(r,a)=>(n[a]=0,r))},cb=class{constructor(t,n,s){me(this,"uniform",{});me(this,"attribute",{});me(this,"gl");me(this,"id");me(this,"compile",(t,n)=>{let s=this.gl.createShader(n);return s?(this.gl.shaderSource(s,t),this.gl.compileShader(s),this.gl.getShaderParameter(s,this.gl.COMPILE_STATUS)?s:(ie(`filter: gl compile failed: ${this.gl.getShaderInfoLog(s)}`),null)):(ie("filter: could not create shader"),null)});this.gl=t;let r=this.compile(n,this.gl.VERTEX_SHADER),a=this.compile(s,this.gl.FRAGMENT_SHADER);if(this.id=this.gl.createProgram(),!(!r||!a)){if(!this.id){ie("filter: could not create webgl program");return}if(this.gl.attachShader(this.id,r),this.gl.attachShader(this.id,a),this.gl.linkProgram(this.id),!this.gl.getProgramParameter(this.id,this.gl.LINK_STATUS)){ie(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);return}this.gl.useProgram(this.id),ub(n,"attribute",this.attribute);for(let o in this.attribute)this.attribute[o]=this.gl.getAttribLocation(this.id,o);ub(n,"uniform",this.uniform),ub(s,"uniform",this.uniform);for(let o in this.uniform)this.uniform[o]=this.gl.getUniformLocation(this.id,o)}}};function vT(){let e=0,t=null,n=!1,s=-1,r=[null,null],a=[],o=null,i=null,l=is(100,100),u={},c={INTERMEDIATE:1},p=l.getContext("webgl");if(!p){ie("filter: cannot get webgl context");return}this.gl=p;function d(x,A){if(!(x===l.width&&A===l.height)){if(l.width=x,l.height=A,!o){let b=new Float32Array([-1,-1,0,1,1,-1,1,1,-1,1,0,0,-1,1,0,0,1,-1,1,1,1,1,1,0]);o=p.createBuffer(),p.bindBuffer(p.ARRAY_BUFFER,o),p.bufferData(p.ARRAY_BUFFER,b,p.STATIC_DRAW),p.pixelStorei(p.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}p.viewport(0,0,l.width,l.height),r=[null,null]}}function h(x,A){let b=p.createFramebuffer();p.bindFramebuffer(p.FRAMEBUFFER,b);let w=p.createRenderbuffer();p.bindRenderbuffer(p.RENDERBUFFER,w);let k=p.createTexture();return p.bindTexture(p.TEXTURE_2D,k),p.texImage2D(p.TEXTURE_2D,0,p.RGBA,x,A,0,p.RGBA,p.UNSIGNED_BYTE,null),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_MAG_FILTER,p.LINEAR),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_MIN_FILTER,p.LINEAR),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_WRAP_S,p.CLAMP_TO_EDGE),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_WRAP_T,p.CLAMP_TO_EDGE),p.framebufferTexture2D(p.FRAMEBUFFER,p.COLOR_ATTACHMENT0,p.TEXTURE_2D,k,0),p.bindTexture(p.TEXTURE_2D,null),p.bindFramebuffer(p.FRAMEBUFFER,null),{fbo:b,texture:k}}function f(x){return r[x]=r[x]||h(l.width,l.height),r[x]}function m(x=0){if(!i)return;let A=null,b=null,w=!1;e===0?A=t:A=f(s).texture||null,e++,n&&!(x&c.INTERMEDIATE)?(b=null,w=e%2===0):(s=(s+1)%2,b=f(s).fbo||null),p.bindTexture(p.TEXTURE_2D,A),p.bindFramebuffer(p.FRAMEBUFFER,b),p.uniform1f(i.uniform.flipY,w?-1:1),p.drawArrays(p.TRIANGLES,0,6)}function g(x){if(u[x])return i=u[x],p.useProgram((i?i.id:null)||null),i;if(i=new cb(p,mT,x),!i)return ie("filter: could not get webgl program"),null;let A=Float32Array.BYTES_PER_ELEMENT,b=4*A;return p.enableVertexAttribArray(i.attribute.pos),p.vertexAttribPointer(i.attribute.pos,2,p.FLOAT,!1,b,0*A),p.enableVertexAttribArray(i.attribute.uv),p.vertexAttribPointer(i.attribute.uv,2,p.FLOAT,!1,b,2*A),u[x]=i,i}let y={colorMatrix:x=>{let A=new Float32Array(x);A[4]/=255,A[9]/=255,A[14]/=255,A[19]/=255;let b=A[18]===1&&A[3]===0&&A[8]===0&&A[13]===0&&A[15]===0&&A[16]===0&&A[17]===0&&A[19]===0?yT:gT,w=g(b);!w||(p.uniform1fv(w.uniform.m,A),m())},brightness:x=>{let A=(x||0)+1;y.colorMatrix([A,0,0,0,0,0,A,0,0,0,0,0,A,0,0,0,0,0,1,0])},saturation:x=>{let A=(x||0)*2/3+1,b=(A-1)*-.5;y.colorMatrix([A,b,b,0,0,b,A,b,0,0,b,b,A,0,0,0,0,0,1,0])},desaturate:()=>{y.saturation(-1)},contrast:x=>{let A=(x||0)+1,b=-128*(A-1);y.colorMatrix([A,0,0,0,b,0,A,0,0,b,0,0,A,0,b,0,0,0,1,0])},negative:()=>{y.contrast(-2)},hue:x=>{x=(x||0)/180*Math.PI;let A=Math.cos(x),b=Math.sin(x),w=.213,k=.715,S=.072;y.colorMatrix([w+A*(1-w)+b*-w,k+A*-k+b*-k,S+A*-S+b*(1-S),0,0,w+A*-w+b*.143,k+A*(1-k)+b*.14,S+A*-S+b*-.283,0,0,w+A*-w+b*-(1-w),k+A*-k+b*k,S+A*(1-S)+b*S,0,0,0,0,0,1,0])},desaturateLuminance:()=>{y.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},sepia:()=>{y.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},brownie:()=>{y.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},vintagePinhole:()=>{y.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},kodachrome:()=>{y.colorMatrix([1.1285582396593525,-.3967382283601348,-.03992559172921793,0,63.72958762196502,-.16404339962244616,1.0835251566291304,-.05498805115633132,0,24.732407896706203,-.16786010706155763,-.5603416277695248,1.6014850761964943,0,35.62982807460946,0,0,0,1,0])},technicolor:()=>{y.colorMatrix([1.9125277891456083,-.8545344976951645,-.09155508482755585,0,11.793603434377337,-.3087833385928097,1.7658908555458428,-.10601743074722245,0,-70.35205161461398,-.231103377548616,-.7501899197440212,1.847597816108189,0,30.950940869491138,0,0,0,1,0])},polaroid:()=>{y.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},shiftToBGR:()=>{y.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},convolution:x=>{let A=new Float32Array(x),b=1/l.width,w=1/l.height,k=g(bT);!k||(p.uniform1fv(k.uniform.m,A),p.uniform2f(k.uniform.px,b,w),m())},detectEdges:()=>{y.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},sobelX:()=>{y.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},sobelY:()=>{y.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},sharpen:x=>{let A=x||1;y.convolution.call(this,[0,-1*A,0,-1*A,1+4*A,-1*A,0,-1*A,0])},emboss:x=>{let A=x||1;y.convolution.call(this,[-2*A,-1*A,0,-1*A,1,1*A,0,1*A,2*A])},blur:x=>{let A=x/7/l.width,b=x/7/l.height,w=g(xT);!w||(p.uniform2f(w.uniform.px,0,b),m(c.INTERMEDIATE),p.uniform2f(w.uniform.px,A,0),m())},pixelate:x=>{let A=x/l.width,b=x/l.height,w=g(AT);!w||(p.uniform2f(w.uniform.size,A,b),m())}};this.add=function(x){let A=Array.prototype.slice.call(arguments,1),b=y[x];a.push({func:b,args:A})},this.reset=function(){a=[]},this.get=function(){return a},this.apply=function(x){d(x.width,x.height),e=0,t||(t=p.createTexture()),p.bindTexture(p.TEXTURE_2D,t),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_WRAP_S,p.CLAMP_TO_EDGE),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_WRAP_T,p.CLAMP_TO_EDGE),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_MIN_FILTER,p.NEAREST),p.texParameteri(p.TEXTURE_2D,p.TEXTURE_MAG_FILTER,p.NEAREST),p.texImage2D(p.TEXTURE_2D,0,p.RGBA,p.RGBA,p.UNSIGNED_BYTE,x);for(let A=0;A<a.length;A++){n=A===a.length-1;let b=a[A];b.func.apply(this,b.args||[])}return l},this.draw=function(x){return this.add("brightness",0),this.apply(x)}}async function R2(e){let t=e.shape.length===4?rt(e):e,n=Zt(t,3,2),s=[ma(n[0]),ma(n[1]),ma(n[2])],r=[mn(n[0]),mn(n[1]),mn(n[2])],a=await Promise.all(r.map(h=>h.data())),o=.99*Math.max(a[0][0],a[1][0],a[2][0]),i=[he(n[0],s[0]),he(n[1],s[1]),he(n[2],s[2])],l=[he(r[0],s[0]),he(r[1],s[1]),he(r[2],s[2])],u=[pe(o,l[0]),pe(o,l[1]),pe(o,l[2])],c=[L(i[0],u[0]),L(i[1],u[1]),L(i[2],u[2])],p=on([c[0],c[1],c[2]],2),d=U(p,[1,t.shape[0],t.shape[1],3]);return ne([...n,...s,...r,...i,...l,...u,...c,p,t]),d}var _2=3840,mt=null,cn=null,fd=null,$t,Ca={inputSum:0,cacheDiff:1,sumMethod:0,inputTensor:void 0};function is(e,t){let n;if(fe.browser)if(fe.worker){if(typeof OffscreenCanvas=="undefined")throw new Error("canvas error: attempted to run in web worker but OffscreenCanvas is not supported");n=new OffscreenCanvas(e,t)}else{if(typeof document=="undefined")throw new Error("canvas error: attempted to run in browser but DOM is not defined");n=document.createElement("canvas"),n.width=e,n.height=t}else typeof fe.Canvas!="undefined"?n=new fe.Canvas(e,t):typeof globalThis.Canvas!="undefined"&&(n=new globalThis.Canvas(e,t));return n}function D2(e,t){let n=t||is(e.width,e.height);return n.getContext("2d").drawImage(e,0,0),n}async function md(e,t,n=!0){if(!e)return t.debug&&ie("input error: input is missing"),{tensor:null,canvas:null};if(!(e instanceof tt)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(typeof fe.Canvas!="undefined"&&e instanceof fe.Canvas)&&!(typeof globalThis.Canvas!="undefined"&&e instanceof globalThis.Canvas)&&!(typeof ImageData!="undefined"&&e instanceof ImageData)&&!(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)&&!(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)&&!(typeof HTMLMediaElement!="undefined"&&e instanceof HTMLMediaElement)&&!(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)&&!(typeof HTMLCanvasElement!="undefined"&&e instanceof HTMLCanvasElement)&&!(typeof OffscreenCanvas!="undefined"&&e instanceof OffscreenCanvas))throw new Error("input error: type is not recognized");if(e instanceof tt){let s=null;if(e.isDisposedInternal)throw new Error("input error: attempted to use tensor but it is disposed");if(!e.shape)throw new Error("input error: attempted to use tensor without a shape");if(e.shape.length===3){if(e.shape[2]===3)s=Kt(e,0);else if(e.shape[2]===4){let r=ui(e,[0,0,0],[-1,-1,3]);s=Kt(r,0),ne(r)}}else e.shape.length===4&&(e.shape[3]===3?s=Fn(e):e.shape[3]===4&&(s=to(e,[0,0,0,0],[-1,-1,-1,3])));if(s==null||s.shape.length!==4||s.shape[0]!==1||s.shape[3]!==3)throw new Error(`input error: attempted to use tensor with unrecognized shape: ${e.shape}`);if(s.dtype==="int32"){let r=ge(s,"float32");ne(s),s=r}return{tensor:s,canvas:t.filter.return?cn:null}}else{if(typeof e.readyState!="undefined"&&e.readyState<=2)return t.debug&&ie("input stream is not ready"),{tensor:null,canvas:mt};let s=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,r=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0;if(!s||!r)return t.debug&&ie("cannot determine input dimensions"),{tensor:null,canvas:mt};let a=s,o=r;if(a>_2&&(a=_2,o=Math.trunc(a*r/s)),o>_2&&(o=_2,a=Math.trunc(o*s/r)),(t.filter.width||0)>0?a=t.filter.width:(t.filter.height||0)>0&&(a=s*((t.filter.height||0)/r)),(t.filter.height||0)>0?o=t.filter.height:(t.filter.width||0)>0&&(o=r*((t.filter.width||0)/s)),!a||!o)throw new Error("input error: cannot determine dimension");(!mt||(mt==null?void 0:mt.width)!==a||(mt==null?void 0:mt.height)!==o)&&(mt=is(a,o));let i=mt.getContext("2d");if(typeof ImageData!="undefined"&&e instanceof ImageData?i.putImageData(e,0,0):t.filter.flip&&typeof i.translate!="undefined"?(i.translate(s,0),i.scale(-1,1),i.drawImage(e,0,0,s,r,0,0,mt==null?void 0:mt.width,mt==null?void 0:mt.height),i.setTransform(1,0,0,1,0,0)):i.drawImage(e,0,0,s,r,0,0,mt==null?void 0:mt.width,mt==null?void 0:mt.height),(!cn||mt.width!==cn.width||(mt==null?void 0:mt.height)!==(cn==null?void 0:cn.height))&&(cn=is(mt.width,mt.height)),t.filter.enabled&&fe.webgl.supported?($t||($t=fe.browser?new vT:null),fe.filter=!!$t,!$t||!$t.add?(t.debug&&ie("input process error: cannot initialize filters"),fe.webgl.supported=!1,t.filter.enabled=!1,D2(mt,cn)):($t.reset(),t.filter.brightness!==0&&$t.add("brightness",t.filter.brightness),t.filter.contrast!==0&&$t.add("contrast",t.filter.contrast),t.filter.sharpness!==0&&$t.add("sharpen",t.filter.sharpness),t.filter.blur!==0&&$t.add("blur",t.filter.blur),t.filter.saturation!==0&&$t.add("saturation",t.filter.saturation),t.filter.hue!==0&&$t.add("hue",t.filter.hue),t.filter.negative&&$t.add("negative"),t.filter.sepia&&$t.add("sepia"),t.filter.vintage&&$t.add("brownie"),t.filter.sepia&&$t.add("sepia"),t.filter.kodachrome&&$t.add("kodachrome"),t.filter.technicolor&&$t.add("technicolor"),t.filter.polaroid&&$t.add("polaroid"),t.filter.pixelate!==0&&$t.add("pixelate",t.filter.pixelate),$t.get()>0?cn=$t.apply(mt):cn=$t.draw(mt))):(D2(mt,cn),$t&&($t=null),fe.filter=!!$t),!n)return{tensor:null,canvas:cn};if(!cn)throw new Error("canvas error: cannot create output");let l,u=3;if(typeof ImageData!="undefined"&&e instanceof ImageData||e.data&&e.width&&e.height)if(fe.browser&&Ys)l=Ys?Ys.fromPixels(e):null;else{u=e.data.length/e.height/e.width;let d=new Uint8Array(e.data.buffer);l=ft(d,[e.height,e.width,u],"int32")}else if((!fd||cn.width!==fd.width||cn.height!==fd.height)&&(fd=is(cn.width,cn.height)),Ys&&fe.browser)t.backend==="webgl"||t.backend==="humangl"||t.backend==="webgpu"?l=Ys.fromPixels(cn):(fd=D2(cn),l=Ys.fromPixels(fd));else{let f=D2(cn).getContext("2d").getImageData(0,0,a,o);u=f.data.length/a/o;let m=new Uint8Array(f.data.buffer);l=ft(m,[a,o,u])}if(u===4){let d=ui(l,[0,0,0],[-1,-1,3]);ne(l),l=d}if(!l)throw new Error("input error: cannot create tensor");let c=ge(l,"float32"),p=t.filter.equalization?await R2(c):Kt(c,0);return ne([l,c]),{tensor:p,canvas:t.filter.return?cn:null}}}async function wT(e,t){let n=!1;if(e.cacheSensitivity===0||!t.shape||t.shape.length!==4||t.shape[1]>2048||t.shape[2]>2048)return n;if(!Ca.inputTensor)Ca.inputTensor=Fn(t);else if(Ca.inputTensor.shape[1]!==t.shape[1]||Ca.inputTensor.shape[2]!==t.shape[2])ne(Ca.inputTensor),Ca.inputTensor=Fn(t);else{let s={};s.diff=he(t,Ca.inputTensor),s.squared=L(s.diff,s.diff),s.sum=ke(s.squared);let a=(await s.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;ne([Ca.inputTensor,s.diff,s.squared,s.sum]),Ca.inputTensor=Fn(t),n=a<=(e.cacheSensitivity||0)}return n}async function kT(e,t,n){let s={};if(!t||!n||t.shape.length!==4||t.shape.length!==n.shape.length)return e.debug||ie("invalid input tensor or tensor shapes do not match:",t.shape,n.shape),0;if(t.shape[0]!==1||n.shape[0]!==1||t.shape[3]!==3||n.shape[3]!==3)return e.debug||ie("input tensors must be of shape [1, height, width, 3]:",t.shape,n.shape),0;s.input1=Fn(t),s.input2=t.shape[1]!==n.shape[1]||t.shape[2]!==n.shape[2]?Ne.resizeBilinear(n,[t.shape[1],t.shape[2]]):Fn(n),s.diff=he(s.input1,s.input2),s.squared=L(s.diff,s.diff),s.sum=ke(s.squared);let a=(await s.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;return ne([s.input1,s.input2,s.diff,s.squared,s.sum]),a}var db=class{constructor(){me(this,"browser");me(this,"node");me(this,"worker");me(this,"platform","");me(this,"agent","");me(this,"backends",[]);me(this,"initial");me(this,"filter");me(this,"tfjs");me(this,"offscreen");me(this,"perfadd",!1);me(this,"wasm",{supported:void 0,backend:void 0,simd:void 0,multithread:void 0});me(this,"webgl",{supported:void 0,backend:void 0,version:void 0,renderer:void 0});me(this,"webgpu",{supported:void 0,backend:void 0,adapter:void 0});me(this,"cpu",{model:void 0,flags:[]});me(this,"kernels",[]);me(this,"Canvas");me(this,"Image");me(this,"ImageData");if(this.browser=typeof navigator!="undefined",this.node=typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined",this.tfjs={version:Vh["tfjs-core"]},this.offscreen=typeof OffscreenCanvas!="undefined",this.initial=!0,this.worker=this.browser&&this.offscreen?typeof WorkerGlobalScope!="undefined":void 0,typeof navigator!="undefined"){let t=navigator.userAgent.match(/\(([^()]+)\)/g);if(t&&t[0]){let n=t[0].match(/\(([^()]+)\)/g);this.platform=n&&n[0]?n[0].replace(/\(|\)/g,""):"",this.agent=navigator.userAgent.replace(t[0],""),this.platform[1]&&(this.agent=this.agent.replace(t[1],"")),this.agent=this.agent.replace(/  /g," ")}}else typeof process!="undefined"&&(this.platform=`${process.platform} ${process.arch}`,this.agent=`NodeJS ${process.version}`)}async updateBackend(){this.backends=Object.keys(sn().registryFactory),this.wasm.supported=typeof WebAssembly!="undefined",this.wasm.backend=this.backends.includes("wasm"),this.wasm.supported&&this.wasm.backend&&ss()==="wasm"&&(this.wasm.simd=await X().getAsync("WASM_HAS_SIMD_SUPPORT"),this.wasm.multithread=await X().getAsync("WASM_HAS_MULTITHREAD_SUPPORT"));let t=is(100,100),n=t?t.getContext("webgl2"):void 0;if(this.webgl.supported=typeof n!="undefined",this.webgl.backend=this.backends.includes("webgl"),this.webgl.supported&&this.webgl.backend&&(ss()==="webgl"||ss()==="humangl")){let s=Zs().gpgpu!=="undefined"?await Zs().getGPGPUContext().gl:null;s&&(this.webgl.version=s.getParameter(s.VERSION),this.webgl.renderer=s.getParameter(s.RENDERER))}this.webgpu.supported=this.browser&&typeof navigator.gpu!="undefined",this.webgpu.backend=this.backends.includes("webgpu");try{this.webgpu.supported&&(this.webgpu.adapter=(await navigator.gpu.requestAdapter()).name)}catch(s){this.webgpu.supported=!1}try{this.kernels=jr(ss()).map(s=>s.kernelName.toLowerCase())}catch(s){}}async updateCPU(){let t={model:"",flags:[]};this.node&&this.platform.startsWith("linux"),this.cpu?this.cpu=t:Object.defineProperty(this,"cpu",{value:t})}},fe=new db;var pb={};oa(pb,{age:()=>Wye,antispoof:()=>Vye,blazeface:()=>Hye,"blazeface-back":()=>Uye,"blazeface-front":()=>Gye,"blazepose-detector2d":()=>jye,"blazepose-detector3d":()=>qye,"blazepose-full":()=>Xye,"blazepose-heavy":()=>Kye,"blazepose-lite":()=>Zye,default:()=>EAe,efficientpose:()=>Yye,emotion:()=>Jye,faceboxes:()=>Qye,facemesh:()=>aAe,"facemesh-attention":()=>tAe,"facemesh-attention-alt":()=>eAe,"facemesh-detection-full":()=>nAe,"facemesh-detection-short":()=>sAe,"facemesh-orig":()=>rAe,faceres:()=>iAe,"faceres-deep":()=>oAe,gear:()=>lAe,gender:()=>cAe,"gender-ssrnet-imdb":()=>uAe,handdetect:()=>dAe,"handlandmark-full":()=>pAe,"handlandmark-lite":()=>hAe,"handlandmark-sparse":()=>fAe,handskeleton:()=>mAe,handtrack:()=>gAe,iris:()=>yAe,liveness:()=>AAe,"mb3-centernet":()=>xAe,meet:()=>bAe,mobileface:()=>vAe,mobilefacenet:()=>wAe,"movenet-lightning":()=>kAe,"movenet-multipose":()=>IAe,"movenet-thunder":()=>SAe,nanodet:()=>CAe,posenet:()=>TAe,selfie:()=>NAe});var Wye=161240,Vye=853098,Uye=538928,Gye=402048,Hye=538928,jye=7499400,qye=5928856,Xye=6338290,Kye=27501554,Zye=2725490,Yye=5651240,Jye=820516,Qye=2013002,eAe=2387598,tAe=2382414,nAe=1026192,sAe=201268,rAe=2955780,aAe=1477958,oAe=13957620,iAe=6978814,lAe=1498916,uAe=161236,cAe=201808,dAe=3515612,pAe=5431368,hAe=2023432,fAe=5286322,mAe=5502280,gAe=2964837,yAe=2599092,AAe=592976,xAe=4030290,bAe=372228,vAe=2183192,wAe=5171976,kAe=4650216,IAe=9448838,SAe=12477112,CAe=7574558,TAe=5032780,NAe=212886,EAe={age:Wye,antispoof:Vye,"blazeface-back":Uye,"blazeface-front":Gye,blazeface:Hye,"blazepose-detector2d":jye,"blazepose-detector3d":qye,"blazepose-full":Xye,"blazepose-heavy":Kye,"blazepose-lite":Zye,efficientpose:Yye,emotion:Jye,faceboxes:Qye,"facemesh-attention-alt":eAe,"facemesh-attention":tAe,"facemesh-detection-full":nAe,"facemesh-detection-short":sAe,"facemesh-orig":rAe,facemesh:aAe,"faceres-deep":oAe,faceres:iAe,gear:lAe,"gender-ssrnet-imdb":uAe,gender:cAe,handdetect:dAe,"handlandmark-full":pAe,"handlandmark-lite":hAe,"handlandmark-sparse":fAe,handskeleton:mAe,handtrack:gAe,iris:yAe,liveness:AAe,"mb3-centernet":xAe,meet:bAe,mobileface:vAe,mobilefacenet:wAe,"movenet-lightning":kAe,"movenet-multipose":IAe,"movenet-thunder":SAe,nanodet:CAe,posenet:TAe,selfie:NAe};var ls={cacheModels:!0,cacheSupported:!0,verbose:!0,debug:!1,modelBasePath:""},Fr={};async function RAe(e,t){return ls.debug&&ie("load model fetch:",e,t),fetch(e,t)}function IT(e){ls.cacheModels=e.cacheModels,ls.verbose=e.debug,ls.modelBasePath=e.modelBasePath}async function qe(e){var u,c,p;let t=uv(ls.modelBasePath,e||"");t.toLowerCase().endsWith(".json")||(t+=".json");let n=t.includes("/")?t.split("/"):t.split("\\"),s=n[n.length-1].replace(".json",""),r="indexeddb://"+s;Fr[s]={name:s,sizeFromManifest:0,sizeLoadedWeights:0,sizeDesired:pb[s],inCache:!1},ls.cacheSupported=typeof window!="undefined"&&typeof window.localStorage!="undefined"&&typeof window.indexedDB!="undefined";let a={};try{a=ls.cacheSupported&&ls.cacheModels?await Ts.listModels():{}}catch(d){ls.cacheSupported=!1}Fr[s].inCache=ls.cacheSupported&&ls.cacheModels&&Object.keys(a).includes(r);let o=typeof fetch=="undefined"?{}:{fetchFunc:(d,h)=>RAe(d,h)},i=new Dh(Fr[s].inCache?r:t,o),l=!1;try{i.findIOHandler(),ls.debug&&ie("model load handler:",i.handler);let d=await i.handler.load();Fr[s].sizeFromManifest=((u=d==null?void 0:d.weightData)==null?void 0:u.byteLength)||0,i.loadSync(d),Fr[s].sizeLoadedWeights=((p=(c=i==null?void 0:i.artifacts)==null?void 0:c.weightData)==null?void 0:p.byteLength)||0,ls.verbose&&ie("load model:",i.modelUrl,{bytes:Fr[s].sizeLoadedWeights},ls),l=!0}catch(d){ie("error loading model:",t,d)}if(l&&ls.cacheModels&&ls.cacheSupported&&!Fr[s].inCache)try{let d=await i.save(r);ie("model saved:",r,d)}catch(d){ie("error saving model:",t,d)}return i}var hb="2.9.1";var f1={};oa(f1,{Models:()=>Jh,getModelStats:()=>I4,load:()=>S4,reset:()=>h1,validate:()=>C4});var fr,fb=[],$Ae=["white","black","asian","indian","other"],PAe=[15,23,28,35.5,45.5,55.5,65],ST=0,CT=0,mb=Number.MAX_SAFE_INTEGER;async function TT(e){var t;return fe.initial&&(fr=null),fr?e.debug&&ie("cached model:",fr.modelUrl):fr=await qe((t=e.face.gear)==null?void 0:t.modelPath),fr}async function gb(e,t,n,s){var o,i;if(!fr)return{age:0,gender:"unknown",genderScore:0,race:[]};let r=mb<(((o=t.face.gear)==null?void 0:o.skipFrames)||0),a=(((i=t.face.gear)==null?void 0:i.skipTime)||0)>ue()-CT;return t.skipAllowed&&a&&r&&ST===s&&fb[n]?(mb++,fb[n]):(mb=0,new Promise(async l=>{var y,x;if(!(fr!=null&&fr.inputs[0].shape))return;let u={},c=[[0,.1,.9,.9]];u.resize=Ne.cropAndResize(e,c,[0],[fr.inputs[0].shape[2],fr.inputs[0].shape[1]]);let p={age:0,gender:"unknown",genderScore:0,race:[]};(y=t.face.gear)!=null&&y.enabled&&([u.age,u.gender,u.race]=fr.execute(u.resize,["age_output","gender_output","race_output"]));let d=await u.gender.data();p.gender=d[0]>d[1]?"male":"female",p.genderScore=Math.round(100*(d[0]>d[1]?d[0]:d[1]))/100;let h=await u.race.data();for(let A=0;A<h.length;A++)h[A]>(((x=t.face.gear)==null?void 0:x.minConfidence)||.2)&&p.race.push({score:Math.round(100*h[A])/100,race:$Ae[A]});p.race.sort((A,b)=>b.score-A.score);let m=Array.from(await u.age.data()).map((A,b)=>[PAe[b],A]).sort((A,b)=>b[1]-A[1]),g=m[0][0];for(let A=1;A<m.length;A++)g+=m[A][1]*(m[A][0]-g);p.age=Math.round(10*g)/10,Object.keys(u).forEach(A=>ne(u[A])),fb[n]=p,ST=s,CT=ue(),l(p)}))}var nt={tf255:255,tf1:1,tf2:2,tf05:.5,tf127:127.5,rgb:[.2989,.587,.114]};function ET(){nt.tf255=Se(255,"float32"),nt.tf1=Se(1,"float32"),nt.tf2=Se(2,"float32"),nt.tf05=Se(.5,"float32"),nt.tf127=Se(127.5,"float32"),nt.rgb=Ft([.2989,.587,.114],"float32")}var Os,$2=[],RT=0,_T=0,yb=Number.MAX_SAFE_INTEGER;async function DT(e){return fe.initial&&(Os=null),Os?e.debug&&ie("cached model:",Os.modelUrl):Os=await qe(e.face.ssrnet.modelPathAge),Os}async function Ab(e,t,n,s){var o,i,l,u;if(!Os)return{age:0};let r=yb<(((o=t.face.ssrnet)==null?void 0:o.skipFrames)||0),a=(((i=t.face.ssrnet)==null?void 0:i.skipTime)||0)>ue()-_T;return t.skipAllowed&&r&&a&&RT===s&&((l=$2[n])==null?void 0:l.age)&&((u=$2[n])==null?void 0:u.age)>0?(yb++,$2[n]):(yb=0,new Promise(async c=>{if(!(Os!=null&&Os.inputs)||!Os.inputs[0]||!Os.inputs[0].shape)return;let p={};p.resize=Ne.resizeBilinear(e,[Os.inputs[0].shape[2],Os.inputs[0].shape[1]],!1),p.enhance=L(p.resize,nt.tf255);let d={age:0};if(t.face.ssrnet.enabled&&(p.age=Os.execute(p.enhance)),p.age){let h=await p.age.data();d.age=Math.trunc(10*h[0])/10}Object.keys(p).forEach(h=>ne(p[h])),$2[n]=d,RT=s,_T=ue(),c(d)}))}var mr,P2=[],PT=0,FT=0,xb=Number.MAX_SAFE_INTEGER,bb=[.2989,.587,.114];async function OT(e){return fe.initial&&(mr=null),mr?e.debug&&ie("cached model:",mr.modelUrl):mr=await qe(e.face.ssrnet.modelPathGender),mr}async function vb(e,t,n,s){var o,i,l,u;if(!mr)return{gender:"unknown",genderScore:0};let r=xb<(((o=t.face.ssrnet)==null?void 0:o.skipFrames)||0),a=(((i=t.face.ssrnet)==null?void 0:i.skipTime)||0)>ue()-FT;return t.skipAllowed&&r&&a&&PT===s&&((l=P2[n])==null?void 0:l.gender)&&((u=P2[n])==null?void 0:u.genderScore)>0?(xb++,P2[n]):(xb=0,new Promise(async c=>{if(!(mr!=null&&mr.inputs[0].shape))return;let p={};p.resize=Ne.resizeBilinear(e,[mr.inputs[0].shape[2],mr.inputs[0].shape[1]],!1),p.enhance=J(()=>{let[f,m,g]=Zt(p.resize,3,3),y=L(f,bb[0]),x=L(m,bb[1]),A=L(g,bb[2]),b=f0([y,x,A]);return L(he(b,nt.tf05),2)});let d={gender:"unknown",genderScore:0};t.face.ssrnet.enabled&&(p.gender=mr.execute(p.enhance));let h=await p.gender.data();d.gender=h[0]>h[1]?"female":"male",d.genderScore=h[0]>h[1]?Math.trunc(100*h[0])/100:Math.trunc(100*h[1])/100,Object.keys(p).forEach(f=>ne(p[f])),P2[n]=d,PT=s,FT=ue(),c(d)}))}var zn,F2=[],wb=Number.MAX_SAFE_INTEGER,zT=0,LT=0;async function BT(e){var t;return fe.initial&&(zn=null),zn?e.debug&&ie("cached model:",zn.modelUrl):zn=await qe((t=e.face.antispoof)==null?void 0:t.modelPath),zn}async function kb(e,t,n,s){var o,i;if(!zn)return 0;let r=(((o=t.face.antispoof)==null?void 0:o.skipTime)||0)>ue()-LT,a=wb<(((i=t.face.antispoof)==null?void 0:i.skipFrames)||0);return t.skipAllowed&&r&&a&&zT===s&&F2[n]?(wb++,F2[n]):(wb=0,new Promise(async l=>{let u=Ne.resizeBilinear(e,[zn!=null&&zn.inputs[0].shape?zn.inputs[0].shape[2]:0,zn!=null&&zn.inputs[0].shape?zn.inputs[0].shape[1]:0],!1),c=zn==null?void 0:zn.execute(u),p=(await c.data())[0];F2[n]=Math.round(100*p)/100,zT=s,LT=ue(),ne([u,c]),l(F2[n])}))}var gr={silhouette:[10,338,297,332,284,251,389,356,454,323,361,288,397,365,379,378,400,377,152,148,176,149,150,136,172,58,132,93,234,127,162,21,54,103,67,109],lipsUpperOuter:[185,40,39,37,0,267,269,270,409],lipsLowerOuter:[61,146,91,181,84,17,314,405,321,375,291],lipsUpperInner:[191,80,81,82,13,312,311,310,415],lipsLowerInner:[78,95,88,178,87,14,317,402,318,324,308],lipsLowerSemiOuter:[76,77,90,180,85,16,315,404,320,307,306],lipsUpperSemiOuter:[184,74,73,72,11,302,303,304,408],lipsLowerSemiInner:[62,96,89,179,86,15,316,403,319,325,292],lipsUpperSemiInner:[183,42,41,38,12,268,271,272,407],rightEyeUpper0:[246,161,160,159,158,157,173],rightEyeLower0:[33,7,163,144,145,153,154,155,133],rightEyeUpper1:[247,30,29,27,28,56,190],rightEyeLower1:[130,25,110,24,23,22,26,112,243],rightEyeUpper2:[113,225,224,223,222,221,189],rightEyeLower2:[226,31,228,229,230,231,232,233,244],rightEyeLower3:[143,111,117,118,119,120,121,128,245],rightEyebrowUpper:[156,70,63,105,66,107,55,193],rightEyebrowLower:[35,124,46,53,52,65],rightEyeIris:[473,474,475,476,477],leftEyeUpper0:[466,388,387,386,385,384,398],leftEyeLower0:[263,249,390,373,374,380,381,382,362],leftEyeUpper1:[467,260,259,257,258,286,414],leftEyeLower1:[359,255,339,254,253,252,256,341,463],leftEyeUpper2:[342,445,444,443,442,441,413],leftEyeLower2:[446,261,448,449,450,451,452,453,464],leftEyeLower3:[372,340,346,347,348,349,350,357,465],leftEyebrowUpper:[383,300,293,334,296,336,285,417],leftEyebrowLower:[265,353,276,283,282,295],leftEyeIris:[468,469,470,471,472],midwayBetweenEyes:[168],noseTip:[1],noseBottom:[2],noseRightCorner:[98],noseLeftCorner:[327],rightCheek:[205],leftCheek:[425]},Ib={count:468,mouth:13,symmetryLine:[13,gr.midwayBetweenEyes[0]]},ou={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Sb=[{key:"EyeUpper0",indices:[9,10,11,12,13,14,15]},{key:"EyeUpper1",indices:[25,26,27,28,29,30,31]},{key:"EyeUpper2",indices:[41,42,43,44,45,46,47]},{key:"EyeLower0",indices:[0,1,2,3,4,5,6,7,8]},{key:"EyeLower1",indices:[16,17,18,19,20,21,22,23,24]},{key:"EyeLower2",indices:[32,33,34,35,36,37,38,39,40]},{key:"EyeLower3",indices:[54,55,56,57,58,59,60,61,62]},{key:"EyebrowUpper",indices:[63,64,65,66,67,68,69,70]},{key:"EyebrowLower",indices:[48,49,50,51,52,53]}],Gh=[[.499976992607117,.652534008026123],[.500025987625122,.547487020492554],[.499974012374878,.602371990680695],[.482113003730774,.471979022026062],[.500150978565216,.527155995368958],[.499909996986389,.498252987861633],[.499523013830185,.40106201171875],[.289712011814117,.380764007568359],[.499954998493195,.312398016452789],[.499987006187439,.269918978214264],[.500023007392883,.107050001621246],[.500023007392883,.666234016418457],[.5000159740448,.679224014282227],[.500023007392883,.692348003387451],[.499976992607117,.695277988910675],[.499976992607117,.70593398809433],[.499976992607117,.719385027885437],[.499976992607117,.737019002437592],[.499967992305756,.781370997428894],[.499816000461578,.562981009483337],[.473773002624512,.573909997940063],[.104906998574734,.254140973091125],[.365929991006851,.409575998783112],[.338757991790771,.41302502155304],[.311120003461838,.409460008144379],[.274657994508743,.389131009578705],[.393361985683441,.403706014156342],[.345234006643295,.344011008739471],[.370094001293182,.346076011657715],[.319321990013123,.347265005111694],[.297903001308441,.353591024875641],[.24779200553894,.410809993743896],[.396889001131058,.842755019664764],[.280097991228104,.375599980354309],[.106310002505779,.399955987930298],[.2099249958992,.391353011131287],[.355807989835739,.534406006336212],[.471751004457474,.65040397644043],[.474155008792877,.680191993713379],[.439785003662109,.657229006290436],[.414617002010345,.66654098033905],[.450374007225037,.680860996246338],[.428770989179611,.682690978050232],[.374971002340317,.727805018424988],[.486716985702515,.547628998756409],[.485300987958908,.527395009994507],[.257764995098114,.314490020275116],[.401223003864288,.455172002315521],[.429818987846375,.548614978790283],[.421351999044418,.533740997314453],[.276895999908447,.532056987285614],[.483370006084442,.499586999416351],[.33721199631691,.282882988452911],[.296391993761063,.293242990970612],[.169294998049736,.193813979625702],[.447580009698868,.302609980106354],[.392390012741089,.353887975215912],[.354490011930466,.696784019470215],[.067304998636246,.730105042457581],[.442739009857178,.572826027870178],[.457098007202148,.584792017936707],[.381974011659622,.694710969924927],[.392388999462128,.694203019142151],[.277076005935669,.271932005882263],[.422551989555359,.563233017921448],[.385919004678726,.281364023685455],[.383103013038635,.255840003490448],[.331431001424789,.119714021682739],[.229923993349075,.232002973556519],[.364500999450684,.189113974571228],[.229622006416321,.299540996551514],[.173287004232407,.278747975826263],[.472878992557526,.666198015213013],[.446828007698059,.668527007102966],[.422762006521225,.673889994621277],[.445307999849319,.580065965652466],[.388103008270264,.693961024284363],[.403039008378983,.706539988517761],[.403629004955292,.693953037261963],[.460041999816895,.557139039039612],[.431158006191254,.692366003990173],[.452181994915009,.692366003990173],[.475387006998062,.692366003990173],[.465828001499176,.779190003871918],[.472328990697861,.736225962638855],[.473087012767792,.717857003211975],[.473122000694275,.704625964164734],[.473033010959625,.695277988910675],[.427942007780075,.695277988910675],[.426479011774063,.703539967536926],[.423162013292313,.711845993995667],[.4183090031147,.720062971115112],[.390094995498657,.639572978019714],[.013953999616206,.560034036636353],[.499913990497589,.58014702796936],[.413199990987778,.69539999961853],[.409626007080078,.701822996139526],[.468080013990402,.601534962654114],[.422728985548019,.585985004901886],[.463079988956451,.593783974647522],[.37211999297142,.47341400384903],[.334562003612518,.496073007583618],[.411671012639999,.546965003013611],[.242175996303558,.14767599105835],[.290776997804642,.201445996761322],[.327338010072708,.256527006626129],[.399509996175766,.748921036720276],[.441727995872498,.261676013469696],[.429764986038208,.187834024429321],[.412198007106781,.108901023864746],[.288955003023148,.398952007293701],[.218936994671822,.435410976409912],[.41278201341629,.398970007896423],[.257135003805161,.355440020561218],[.427684992551804,.437960982322693],[.448339998722076,.536936044692993],[.178560003638268,.45755398273468],[.247308000922203,.457193970680237],[.286267012357712,.467674970626831],[.332827985286713,.460712015628815],[.368755996227264,.447206974029541],[.398963987827301,.432654976844788],[.476410001516342,.405806005001068],[.189241006970406,.523923993110657],[.228962004184723,.348950982093811],[.490725994110107,.562400996685028],[.404670000076294,.485132992267609],[.019469000399113,.401564002037048],[.426243007183075,.420431017875671],[.396993011236191,.548797011375427],[.266469985246658,.376977026462555],[.439121007919312,.51895797252655],[.032313998788595,.644356966018677],[.419054001569748,.387154996395111],[.462783008813858,.505746960639954],[.238978996872902,.779744982719421],[.198220998048782,.831938028335571],[.107550002634525,.540755033493042],[.183610007166862,.740257024765015],[.134409993886948,.333683013916016],[.385764002799988,.883153975009918],[.490967005491257,.579378008842468],[.382384985685349,.508572995662689],[.174399003386497,.397670984268188],[.318785011768341,.39623498916626],[.343364000320435,.400596976280212],[.396100014448166,.710216999053955],[.187885001301765,.588537991046906],[.430987000465393,.944064974784851],[.318993002176285,.898285031318665],[.266247987747192,.869701027870178],[.500023007392883,.190576016902924],[.499976992607117,.954452991485596],[.366169989109039,.398822009563446],[.393207013607025,.39553701877594],[.410373002290726,.391080021858215],[.194993004202843,.342101991176605],[.388664990663528,.362284004688263],[.365961998701096,.355970978736877],[.343364000320435,.355356991291046],[.318785011768341,.35834002494812],[.301414996385574,.363156020641327],[.058132998645306,.319076001644135],[.301414996385574,.387449026107788],[.499987989664078,.618434011936188],[.415838003158569,.624195992946625],[.445681989192963,.566076993942261],[.465844005346298,.620640993118286],[.49992299079895,.351523995399475],[.288718998432159,.819945991039276],[.335278987884521,.852819979190826],[.440512001514435,.902418971061707],[.128294005990028,.791940987110138],[.408771991729736,.373893976211548],[.455606997013092,.451801002025604],[.499877005815506,.908990025520325],[.375436991453171,.924192011356354],[.11421000212431,.615022003650665],[.448662012815475,.695277988910675],[.4480200111866,.704632043838501],[.447111994028091,.715808033943176],[.444831997156143,.730794012546539],[.430011987686157,.766808986663818],[.406787008047104,.685672998428345],[.400738000869751,.681069016456604],[.392399996519089,.677703022956848],[.367855995893478,.663918972015381],[.247923001646996,.601333022117615],[.452769994735718,.420849978923798],[.43639200925827,.359887003898621],[.416164010763168,.368713974952698],[.413385987281799,.692366003990173],[.228018000721931,.683571994304657],[.468268007040024,.352671027183533],[.411361992359161,.804327011108398],[.499989002943039,.469825029373169],[.479153990745544,.442654013633728],[.499974012374878,.439637005329132],[.432112008333206,.493588984012604],[.499886006116867,.866917014122009],[.49991300702095,.821729004383087],[.456548988819122,.819200992584229],[.344549000263214,.745438992977142],[.37890899181366,.574010014533997],[.374292999505997,.780184984207153],[.319687992334366,.570737957954407],[.357154995203018,.604269981384277],[.295284003019333,.621580958366394],[.447750002145767,.862477004528046],[.410986006259918,.508723020553589],[.31395098567009,.775308012962341],[.354128003120422,.812552988529205],[.324548006057739,.703992962837219],[.189096003770828,.646299958229065],[.279776990413666,.71465802192688],[.1338230073452,.682700991630554],[.336768001317978,.644733011722565],[.429883986711502,.466521978378296],[.455527991056442,.548622965812683],[.437114000320435,.558896005153656],[.467287987470627,.529924988746643],[.414712011814117,.335219979286194],[.37704598903656,.322777986526489],[.344107985496521,.320150971412659],[.312875986099243,.32233202457428],[.283526003360748,.333190023899078],[.241245999932289,.382785975933075],[.102986000478268,.468762993812561],[.267612010240555,.424560010433197],[.297879010438919,.433175981044769],[.333433985710144,.433878004550934],[.366427004337311,.426115989685059],[.396012008190155,.416696012020111],[.420121014118195,.41022801399231],[.007561000064015,.480777025222778],[.432949006557465,.569517970085144],[.458638995885849,.479089021682739],[.473466008901596,.545744001865387],[.476087987422943,.563830018043518],[.468472003936768,.555056989192963],[.433990985155106,.582361996173859],[.483518004417419,.562983989715576],[.482482999563217,.57784903049469],[.42645001411438,.389798998832703],[.438998997211456,.39649498462677],[.450067013502121,.400434017181396],[.289712011814117,.368252992630005],[.276670008897781,.363372981548309],[.517862021923065,.471948027610779],[.710287988185883,.380764007568359],[.526226997375488,.573909997940063],[.895093023777008,.254140973091125],[.634069979190826,.409575998783112],[.661242008209229,.41302502155304],[.688880026340485,.409460008144379],[.725341975688934,.389131009578705],[.606630027294159,.40370500087738],[.654766023159027,.344011008739471],[.629905998706818,.346076011657715],[.680678009986877,.347265005111694],[.702096998691559,.353591024875641],[.75221198797226,.410804986953735],[.602918028831482,.842862963676453],[.719901978969574,.375599980354309],[.893692970275879,.399959981441498],[.790081977844238,.391354024410248],[.643998026847839,.534487962722778],[.528249025344849,.65040397644043],[.525849997997284,.680191040039062],[.560214996337891,.657229006290436],[.585384011268616,.66654098033905],[.549625992774963,.680860996246338],[.57122802734375,.682691991329193],[.624852001667023,.72809898853302],[.513050019741058,.547281980514526],[.51509702205658,.527251958847046],[.742246985435486,.314507007598877],[.598631024360657,.454979002475739],[.570338010787964,.548575043678284],[.578631997108459,.533622980117798],[.723087012767792,.532054007053375],[.516445994377136,.499638974666595],[.662801027297974,.282917976379395],[.70362401008606,.293271005153656],[.830704987049103,.193813979625702],[.552385985851288,.302568018436432],[.607609987258911,.353887975215912],[.645429015159607,.696707010269165],[.932694971561432,.730105042457581],[.557260990142822,.572826027870178],[.542901992797852,.584792017936707],[.6180260181427,.694710969924927],[.607590973377228,.694203019142151],[.722943007946014,.271963000297546],[.577413976192474,.563166975975037],[.614082992076874,.281386971473694],[.616907000541687,.255886018276215],[.668509006500244,.119913995265961],[.770092010498047,.232020974159241],[.635536015033722,.189248979091644],[.77039098739624,.299556016921997],[.826722025871277,.278755009174347],[.527121007442474,.666198015213013],[.553171992301941,.668527007102966],[.577238023281097,.673889994621277],[.554691970348358,.580065965652466],[.611896991729736,.693961024284363],[.59696102142334,.706539988517761],[.596370995044708,.693953037261963],[.539958000183105,.557139039039612],[.568841993808746,.692366003990173],[.547818005084991,.692366003990173],[.52461302280426,.692366003990173],[.534089982509613,.779141008853912],[.527670979499817,.736225962638855],[.526912987232208,.717857003211975],[.526877999305725,.704625964164734],[.526966989040375,.695277988910675],[.572058022022247,.695277988910675],[.573521018028259,.703539967536926],[.57683801651001,.711845993995667],[.581691026687622,.720062971115112],[.609944999217987,.639909982681274],[.986046016216278,.560034036636353],[.5867999792099,.69539999961853],[.590372025966644,.701822996139526],[.531915009021759,.601536989212036],[.577268004417419,.585934996604919],[.536915004253387,.593786001205444],[.627542972564697,.473352015018463],[.665585994720459,.495950996875763],[.588353991508484,.546862006187439],[.757824003696442,.14767599105835],[.709249973297119,.201507985591888],[.672684013843536,.256581008434296],[.600408971309662,.74900496006012],[.55826598405838,.261672019958496],[.570303976535797,.187870979309082],[.588165998458862,.109044015407562],[.711045026779175,.398952007293701],[.781069993972778,.435405015945435],[.587247014045715,.398931980133057],[.742869973182678,.355445981025696],[.572156012058258,.437651991844177],[.55186802148819,.536570012569427],[.821442008018494,.457556009292603],[.752701997756958,.457181990146637],[.71375697851181,.467626988887787],[.66711300611496,.460672974586487],[.631101012229919,.447153985500336],[.6008620262146,.432473003864288],[.523481011390686,.405627012252808],[.810747981071472,.523926019668579],[.771045982837677,.348959028720856],[.509127020835876,.562718033790588],[.595292985439301,.485023975372314],[.980530977249146,.401564002037048],[.573499977588654,.420000016689301],[.602994978427887,.548687994480133],[.733529984951019,.376977026462555],[.560611009597778,.519016981124878],[.967685997486115,.644356966018677],[.580985009670258,.387160003185272],[.537728011608124,.505385041236877],[.760966002941132,.779752969741821],[.801778972148895,.831938028335571],[.892440974712372,.54076099395752],[.816350996494293,.740260004997253],[.865594983100891,.333687007427216],[.614073991775513,.883246004581451],[.508952975273132,.579437971115112],[.617941975593567,.508316040039062],[.825608015060425,.397674977779388],[.681214988231659,.39623498916626],[.656635999679565,.400596976280212],[.603900015354156,.710216999053955],[.81208598613739,.588539004325867],[.56801301240921,.944564998149872],[.681007981300354,.898285031318665],[.733752012252808,.869701027870178],[.633830010890961,.398822009563446],[.606792986392975,.39553701877594],[.589659988880157,.391062021255493],[.805015981197357,.342108011245728],[.611334979534149,.362284004688263],[.634037971496582,.355970978736877],[.656635999679565,.355356991291046],[.681214988231659,.35834002494812],[.698584973812103,.363156020641327],[.941866993904114,.319076001644135],[.698584973812103,.387449026107788],[.584177017211914,.624107003211975],[.554318010807037,.566076993942261],[.534153997898102,.62064003944397],[.711217999458313,.819975018501282],[.664629995822906,.852871000766754],[.559099972248077,.902631998062134],[.871706008911133,.791940987110138],[.591234028339386,.373893976211548],[.544341027736664,.451583981513977],[.624562978744507,.924192011356354],[.88577002286911,.615028977394104],[.551338016986847,.695277988910675],[.551980018615723,.704632043838501],[.552887976169586,.715808033943176],[.555167973041534,.730794012546539],[.569944024085999,.767035007476807],[.593203008174896,.685675978660583],[.599261999130249,.681069016456604],[.607599973678589,.677703022956848],[.631937980651855,.663500010967255],[.752032995223999,.601315021514893],[.547226011753082,.420395016670227],[.563543975353241,.359827995300293],[.583841025829315,.368713974952698],[.586614012718201,.692366003990173],[.771915018558502,.683578014373779],[.531597018241882,.352482974529266],[.588370978832245,.804440975189209],[.52079701423645,.442565023899078],[.567984998226166,.493479013442993],[.543282985687256,.819254994392395],[.655317008495331,.745514988899231],[.621008992195129,.574018001556396],[.625559985637665,.78031200170517],[.680198013782501,.570719003677368],[.64276397228241,.604337990283966],[.704662978649139,.621529996395111],[.552012026309967,.862591981887817],[.589071989059448,.508637011051178],[.685944974422455,.775357007980347],[.645735025405884,.812640011310577],[.675342977046967,.703978002071381],[.810858011245728,.646304965019226],[.72012197971344,.714666962623596],[.866151988506317,.682704985141754],[.663187026977539,.644596993923187],[.570082008838654,.466325998306274],[.544561982154846,.548375964164734],[.562758982181549,.558784961700439],[.531987011432648,.530140042304993],[.585271000862122,.335177004337311],[.622952997684479,.32277899980545],[.655896008014679,.320163011550903],[.687132000923157,.322345972061157],[.716481983661652,.333200991153717],[.758756995201111,.382786989212036],[.897013008594513,.468769013881683],[.732392013072968,.424547016620636],[.70211398601532,.433162987232208],[.66652500629425,.433866024017334],[.633504986763,.426087975502014],[.603875994682312,.416586995124817],[.579657971858978,.409945011138916],[.992439985275269,.480777025222778],[.567192018032074,.569419980049133],[.54136598110199,.478899002075195],[.526564002037048,.546118021011353],[.523913025856018,.563830018043518],[.531529009342194,.555056989192963],[.566035985946655,.582329034805298],[.51631098985672,.563053965568542],[.5174720287323,.577877044677734],[.573594987392426,.389806985855103],[.560697972774506,.395331978797913],[.549755990505219,.399751007556915],[.710287988185883,.368252992630005],[.723330020904541,.363372981548309]],iu=[127,34,139,11,0,37,232,231,120,72,37,39,128,121,47,232,121,128,104,69,67,175,171,148,157,154,155,118,50,101,73,39,40,9,151,108,48,115,131,194,204,211,74,40,185,80,42,183,40,92,186,230,229,118,202,212,214,83,18,17,76,61,146,160,29,30,56,157,173,106,204,194,135,214,192,203,165,98,21,71,68,51,45,4,144,24,23,77,146,91,205,50,187,201,200,18,91,106,182,90,91,181,85,84,17,206,203,36,148,171,140,92,40,39,193,189,244,159,158,28,247,246,161,236,3,196,54,68,104,193,168,8,117,228,31,189,193,55,98,97,99,126,47,100,166,79,218,155,154,26,209,49,131,135,136,150,47,126,217,223,52,53,45,51,134,211,170,140,67,69,108,43,106,91,230,119,120,226,130,247,63,53,52,238,20,242,46,70,156,78,62,96,46,53,63,143,34,227,173,155,133,123,117,111,44,125,19,236,134,51,216,206,205,154,153,22,39,37,167,200,201,208,36,142,100,57,212,202,20,60,99,28,158,157,35,226,113,160,159,27,204,202,210,113,225,46,43,202,204,62,76,77,137,123,116,41,38,72,203,129,142,64,98,240,49,102,64,41,73,74,212,216,207,42,74,184,169,170,211,170,149,176,105,66,69,122,6,168,123,147,187,96,77,90,65,55,107,89,90,180,101,100,120,63,105,104,93,137,227,15,86,85,129,102,49,14,87,86,55,8,9,100,47,121,145,23,22,88,89,179,6,122,196,88,95,96,138,172,136,215,58,172,115,48,219,42,80,81,195,3,51,43,146,61,171,175,199,81,82,38,53,46,225,144,163,110,246,33,7,52,65,66,229,228,117,34,127,234,107,108,69,109,108,151,48,64,235,62,78,191,129,209,126,111,35,143,163,161,246,117,123,50,222,65,52,19,125,141,221,55,65,3,195,197,25,7,33,220,237,44,70,71,139,122,193,245,247,130,33,71,21,162,153,158,159,170,169,150,188,174,196,216,186,92,144,160,161,2,97,167,141,125,241,164,167,37,72,38,12,145,159,160,38,82,13,63,68,71,226,35,111,158,153,154,101,50,205,206,92,165,209,198,217,165,167,97,220,115,218,133,112,243,239,238,241,214,135,169,190,173,133,171,208,32,125,44,237,86,87,178,85,86,179,84,85,180,83,84,181,201,83,182,137,93,132,76,62,183,61,76,184,57,61,185,212,57,186,214,207,187,34,143,156,79,239,237,123,137,177,44,1,4,201,194,32,64,102,129,213,215,138,59,166,219,242,99,97,2,94,141,75,59,235,24,110,228,25,130,226,23,24,229,22,23,230,26,22,231,112,26,232,189,190,243,221,56,190,28,56,221,27,28,222,29,27,223,30,29,224,247,30,225,238,79,20,166,59,75,60,75,240,147,177,215,20,79,166,187,147,213,112,233,244,233,128,245,128,114,188,114,217,174,131,115,220,217,198,236,198,131,134,177,132,58,143,35,124,110,163,7,228,110,25,356,389,368,11,302,267,452,350,349,302,303,269,357,343,277,452,453,357,333,332,297,175,152,377,384,398,382,347,348,330,303,304,270,9,336,337,278,279,360,418,262,431,304,408,409,310,415,407,270,409,410,450,348,347,422,430,434,313,314,17,306,307,375,387,388,260,286,414,398,335,406,418,364,367,416,423,358,327,251,284,298,281,5,4,373,374,253,307,320,321,425,427,411,421,313,18,321,405,406,320,404,405,315,16,17,426,425,266,377,400,369,322,391,269,417,465,464,386,257,258,466,260,388,456,399,419,284,332,333,417,285,8,346,340,261,413,441,285,327,460,328,355,371,329,392,439,438,382,341,256,429,420,360,364,394,379,277,343,437,443,444,283,275,440,363,431,262,369,297,338,337,273,375,321,450,451,349,446,342,467,293,334,282,458,461,462,276,353,383,308,324,325,276,300,293,372,345,447,382,398,362,352,345,340,274,1,19,456,248,281,436,427,425,381,256,252,269,391,393,200,199,428,266,330,329,287,273,422,250,462,328,258,286,384,265,353,342,387,259,257,424,431,430,342,353,276,273,335,424,292,325,307,366,447,345,271,303,302,423,266,371,294,455,460,279,278,294,271,272,304,432,434,427,272,407,408,394,430,431,395,369,400,334,333,299,351,417,168,352,280,411,325,319,320,295,296,336,319,403,404,330,348,349,293,298,333,323,454,447,15,16,315,358,429,279,14,15,316,285,336,9,329,349,350,374,380,252,318,402,403,6,197,419,318,319,325,367,364,365,435,367,397,344,438,439,272,271,311,195,5,281,273,287,291,396,428,199,311,271,268,283,444,445,373,254,339,263,466,249,282,334,296,449,347,346,264,447,454,336,296,299,338,10,151,278,439,455,292,407,415,358,371,355,340,345,372,390,249,466,346,347,280,442,443,282,19,94,370,441,442,295,248,419,197,263,255,359,440,275,274,300,383,368,351,412,465,263,467,466,301,368,389,380,374,386,395,378,379,412,351,419,436,426,322,373,390,388,2,164,393,370,462,461,164,0,267,302,11,12,374,373,387,268,12,13,293,300,301,446,261,340,385,384,381,330,266,425,426,423,391,429,355,437,391,327,326,440,457,438,341,382,362,459,457,461,434,430,394,414,463,362,396,369,262,354,461,457,316,403,402,315,404,403,314,405,404,313,406,405,421,418,406,366,401,361,306,408,407,291,409,408,287,410,409,432,436,410,434,416,411,264,368,383,309,438,457,352,376,401,274,275,4,421,428,262,294,327,358,433,416,367,289,455,439,462,370,326,2,326,370,305,460,455,254,449,448,255,261,446,253,450,449,252,451,450,256,452,451,341,453,452,413,464,463,441,413,414,258,442,441,257,443,442,259,444,443,260,445,444,467,342,445,459,458,250,289,392,290,290,328,460,376,433,435,250,290,392,411,416,433,341,463,464,453,464,465,357,465,412,343,412,399,360,363,440,437,399,456,420,456,363,401,435,288,372,383,353,339,255,249,448,261,255,133,243,190,133,155,112,33,246,247,33,130,25,398,384,286,362,398,414,362,463,341,263,359,467,263,249,255,466,467,260,75,60,166,238,239,79,162,127,139,72,11,37,121,232,120,73,72,39,114,128,47,233,232,128,103,104,67,152,175,148,173,157,155,119,118,101,74,73,40,107,9,108,49,48,131,32,194,211,184,74,185,191,80,183,185,40,186,119,230,118,210,202,214,84,83,17,77,76,146,161,160,30,190,56,173,182,106,194,138,135,192,129,203,98,54,21,68,5,51,4,145,144,23,90,77,91,207,205,187,83,201,18,181,91,182,180,90,181,16,85,17,205,206,36,176,148,140,165,92,39,245,193,244,27,159,28,30,247,161,174,236,196,103,54,104,55,193,8,111,117,31,221,189,55,240,98,99,142,126,100,219,166,218,112,155,26,198,209,131,169,135,150,114,47,217,224,223,53,220,45,134,32,211,140,109,67,108,146,43,91,231,230,120,113,226,247,105,63,52,241,238,242,124,46,156,95,78,96,70,46,63,116,143,227,116,123,111,1,44,19,3,236,51,207,216,205,26,154,22,165,39,167,199,200,208,101,36,100,43,57,202,242,20,99,56,28,157,124,35,113,29,160,27,211,204,210,124,113,46,106,43,204,96,62,77,227,137,116,73,41,72,36,203,142,235,64,240,48,49,64,42,41,74,214,212,207,183,42,184,210,169,211,140,170,176,104,105,69,193,122,168,50,123,187,89,96,90,66,65,107,179,89,180,119,101,120,68,63,104,234,93,227,16,15,85,209,129,49,15,14,86,107,55,9,120,100,121,153,145,22,178,88,179,197,6,196,89,88,96,135,138,136,138,215,172,218,115,219,41,42,81,5,195,51,57,43,61,208,171,199,41,81,38,224,53,225,24,144,110,105,52,66,118,229,117,227,34,234,66,107,69,10,109,151,219,48,235,183,62,191,142,129,126,116,111,143,7,163,246,118,117,50,223,222,52,94,19,141,222,221,65,196,3,197,45,220,44,156,70,139,188,122,245,139,71,162,145,153,159,149,170,150,122,188,196,206,216,92,163,144,161,164,2,167,242,141,241,0,164,37,11,72,12,144,145,160,12,38,13,70,63,71,31,226,111,157,158,154,36,101,205,203,206,165,126,209,217,98,165,97,237,220,218,237,239,241,210,214,169,140,171,32,241,125,237,179,86,178,180,85,179,181,84,180,182,83,181,194,201,182,177,137,132,184,76,183,185,61,184,186,57,185,216,212,186,192,214,187,139,34,156,218,79,237,147,123,177,45,44,4,208,201,32,98,64,129,192,213,138,235,59,219,141,242,97,97,2,141,240,75,235,229,24,228,31,25,226,230,23,229,231,22,230,232,26,231,233,112,232,244,189,243,189,221,190,222,28,221,223,27,222,224,29,223,225,30,224,113,247,225,99,60,240,213,147,215,60,20,166,192,187,213,243,112,244,244,233,245,245,128,188,188,114,174,134,131,220,174,217,236,236,198,134,215,177,58,156,143,124,25,110,7,31,228,25,264,356,368,0,11,267,451,452,349,267,302,269,350,357,277,350,452,357,299,333,297,396,175,377,381,384,382,280,347,330,269,303,270,151,9,337,344,278,360,424,418,431,270,304,409,272,310,407,322,270,410,449,450,347,432,422,434,18,313,17,291,306,375,259,387,260,424,335,418,434,364,416,391,423,327,301,251,298,275,281,4,254,373,253,375,307,321,280,425,411,200,421,18,335,321,406,321,320,405,314,315,17,423,426,266,396,377,369,270,322,269,413,417,464,385,386,258,248,456,419,298,284,333,168,417,8,448,346,261,417,413,285,326,327,328,277,355,329,309,392,438,381,382,256,279,429,360,365,364,379,355,277,437,282,443,283,281,275,363,395,431,369,299,297,337,335,273,321,348,450,349,359,446,467,283,293,282,250,458,462,300,276,383,292,308,325,283,276,293,264,372,447,346,352,340,354,274,19,363,456,281,426,436,425,380,381,252,267,269,393,421,200,428,371,266,329,432,287,422,290,250,328,385,258,384,446,265,342,386,387,257,422,424,430,445,342,276,422,273,424,306,292,307,352,366,345,268,271,302,358,423,371,327,294,460,331,279,294,303,271,304,436,432,427,304,272,408,395,394,431,378,395,400,296,334,299,6,351,168,376,352,411,307,325,320,285,295,336,320,319,404,329,330,349,334,293,333,366,323,447,316,15,315,331,358,279,317,14,316,8,285,9,277,329,350,253,374,252,319,318,403,351,6,419,324,318,325,397,367,365,288,435,397,278,344,439,310,272,311,248,195,281,375,273,291,175,396,199,312,311,268,276,283,445,390,373,339,295,282,296,448,449,346,356,264,454,337,336,299,337,338,151,294,278,455,308,292,415,429,358,355,265,340,372,388,390,466,352,346,280,295,442,282,354,19,370,285,441,295,195,248,197,457,440,274,301,300,368,417,351,465,251,301,389,385,380,386,394,395,379,399,412,419,410,436,322,387,373,388,326,2,393,354,370,461,393,164,267,268,302,12,386,374,387,312,268,13,298,293,301,265,446,340,380,385,381,280,330,425,322,426,391,420,429,437,393,391,326,344,440,438,458,459,461,364,434,394,428,396,262,274,354,457,317,316,402,316,315,403,315,314,404,314,313,405,313,421,406,323,366,361,292,306,407,306,291,408,291,287,409,287,432,410,427,434,411,372,264,383,459,309,457,366,352,401,1,274,4,418,421,262,331,294,358,435,433,367,392,289,439,328,462,326,94,2,370,289,305,455,339,254,448,359,255,446,254,253,449,253,252,450,252,256,451,256,341,452,414,413,463,286,441,414,286,258,441,258,257,442,257,259,443,259,260,444,260,467,445,309,459,250,305,289,290,305,290,460,401,376,435,309,250,392,376,411,433,453,341,464,357,453,465,343,357,412,437,343,399,344,360,440,420,437,456,360,420,363,361,401,288,265,372,353,390,339,249,339,448,255];var OAe=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],MAe=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],zAe=[33,133,362,263,1,78,308],B8e=OAe.map(e=>Gh[e]),W8e=MAe.map(e=>Gh[e]),V8e=zAe.map(e=>Gh[e]);function hi(e){let t=e.map(n=>n[0]);return t.push(e[e.length-1][1]),t}var LAe=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],BAe=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],WAe=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],VAe=[[474,475],[475,476],[476,477],[477,474]],UAe=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],GAe=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],HAe=[[469,470],[470,471],[471,472],[472,469]],jAe=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]],U8e={lips:hi(LAe),leftEye:hi(BAe),leftEyebrow:hi(WAe),leftIris:hi(VAe),rightEye:hi(UAe),rightEyebrow:hi(GAe),rightIris:hi(HAe),faceOval:hi(jAe)};var gd=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],O2=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],M2=(e,t)=>e?[Math.trunc(Math.max(0,e.startPoint[0])),Math.trunc(Math.max(0,e.startPoint[1])),Math.trunc(Math.min(t.shape[2]||0,e.endPoint[0])-Math.max(0,e.startPoint[0])),Math.trunc(Math.min(t.shape[1]||0,e.endPoint[1])-Math.max(0,e.startPoint[1]))]:[0,0,0,0],z2=(e,t)=>e?[e.startPoint[0]/(t.shape[2]||0),e.startPoint[1]/(t.shape[1]||0),(e.endPoint[0]-e.startPoint[0])/(t.shape[2]||0),(e.endPoint[1]-e.startPoint[1])/(t.shape[1]||0)]:[0,0,0,0],GT=(e,t)=>{let n=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],s=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]];return{startPoint:n,endPoint:s,landmarks:e.landmarks,confidence:e.confidence}},Tb=(e,t,n)=>{let s=t.shape[1],r=t.shape[2],a=[e.startPoint[1]/s,e.startPoint[0]/r,e.endPoint[1]/s,e.endPoint[0]/r],o=Ne.cropAndResize(t,[a],[0],n),i=pe(o,nt.tf255);return ne(o),i},L2=(e,t)=>{let n=O2(e),s=gd(e),r=[t*s[0]/2,t*s[1]/2];return{startPoint:[n[0]-r[0],n[1]-r[1]],endPoint:[n[0]+r[0],n[1]+r[1]],landmarks:e.landmarks,confidence:e.confidence}},B2=e=>{let t=O2(e),n=gd(e),s=Math.max(...n)/2;return{startPoint:[Math.round(t[0]-s),Math.round(t[1]-s)],endPoint:[Math.round(t[0]+s),Math.round(t[1]+s)],landmarks:e.landmarks,confidence:e.confidence}},HT=e=>{let t=e.map(s=>s[0]),n=e.map(s=>s[1]);return{startPoint:[Math.min(...t),Math.min(...n)],endPoint:[Math.max(...t),Math.max(...n)],landmarks:e}},Nb=[[1,0,0],[0,1,0],[0,0,1]],qAe=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),XAe=(e,t)=>qAe(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var VT=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],lu=(e,t)=>{let n=0;for(let s=0;s<e.length;s++)n+=e[s]*t[s];return n},KAe=(e,t)=>{let n=[];for(let s=0;s<e.length;s++)n.push(e[s][t]);return n},UT=(e,t)=>{let n=[],s=e.length;for(let r=0;r<s;r++){n.push([]);for(let a=0;a<s;a++)n[r].push(lu(e[r],KAe(t,a)))}return n},jT=(e,t)=>{let n=Math.cos(e),s=Math.sin(e),r=[[n,-s,0],[s,n,0],[0,0,1]],a=VT(t[0],t[1]),o=UT(a,r),i=VT(-t[0],-t[1]);return UT(o,i)},ZAe=e=>{let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],n=[e[0][2],e[1][2]],s=[-lu(t[0],n),-lu(t[1],n)];return[t[0].concat(s[0]),t[1].concat(s[1]),[0,0,1]]},YAe=(e,t)=>[lu(e,t[0]),lu(e,t[1])];function qT(e){let t=e===192?{strides:[4],anchors:[1]}:{strides:[e/16,e/8],anchors:[2,6]},n=[];for(let s=0;s<t.strides.length;s++){let r=t.strides[s],a=Math.floor((e+r-1)/r),o=Math.floor((e+r-1)/r),i=t.anchors[s];for(let l=0;l<a;l++){let u=r*(l+.5);for(let c=0;c<o;c++){let p=r*(c+.5);for(let d=0;d<i;d++)n.push([p,u])}}}return n}function XT(e,t,n,s,r){let a=gd(t),o=e.map(h=>[a[0]/r*(h[0]-r/2),a[1]/r*(h[1]-r/2),h[2]||0]),i=n&&n!==0&&Math.abs(n)>.2,l=i?jT(n,[0,0]):Nb,u=i?o.map(h=>[...YAe(h,l),h[2]]):o,c=i?ZAe(s):Nb,p=O2(t),d=[lu(p,c[0]),lu(p,c[1])];return u.map(h=>[Math.trunc(h[0]+d[0]),Math.trunc(h[1]+d[1]),Math.trunc(h[2]||0)])}function KT(e,t,n,s){let r=t.landmarks.length>=Ib.count?Ib.symmetryLine:ou.symmetryLine,a=0,o=Nb,i;if(e&&fe.kernels.includes("rotatewithoffset"))if(a=XAe(t.landmarks[r[0]],t.landmarks[r[1]]),a&&a!==0&&Math.abs(a)>.2){let u=O2(t),c=[u[0]/n.shape[2],u[1]/n.shape[1]],p=Ne.rotateWithOffset(n,a,0,c);o=jT(-a,u),i=Tb(t,p,[s,s]),ne(p)}else i=Tb(t,n,[s,s]);else i=Tb(t,n,[s,s]);return[a,o,i]}var JAe=e=>{let t=e.map(s=>s[0]),n=e.map(s=>s[1]);return[Math.min(...t)+(Math.max(...t)-Math.min(...t))/2,Math.min(...n)+(Math.max(...n)-Math.min(...n))/2]},ZT=(e,t)=>{let n=JAe(e),s=gd(t);return{startPoint:[n[0]-s[0]/2,n[1]-s[1]/2],endPoint:[n[0]+s[0]/2,n[1]+s[1]/2]}};var YT=6,QAe=1.4,Qr,JT=null,fi=0,Hh=null,yd=()=>fi;async function QT(e){var t;return fe.initial&&(Qr=null),Qr?e.debug&&ie("cached model:",Qr.modelUrl):Qr=await qe((t=e.face.detector)==null?void 0:t.modelPath),fi=Qr.inputs[0].shape?Qr.inputs[0].shape[2]:0,Hh=Se(fi,"int32"),JT=or(qT(fi)),Qr}function e5e(e){let t={};t.boxStarts=Oe(e,[0,1],[-1,2]),t.centers=ce(t.boxStarts,JT),t.boxSizes=Oe(e,[0,3],[-1,2]),t.boxSizesNormalized=pe(t.boxSizes,Hh),t.centersNormalized=pe(t.centers,Hh),t.halfBoxSize=pe(t.boxSizesNormalized,nt.tf2),t.starts=he(t.centersNormalized,t.halfBoxSize),t.ends=ce(t.centersNormalized,t.halfBoxSize),t.startNormalized=L(t.starts,Hh),t.endNormalized=L(t.ends,Hh);let n=Xl([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(s=>ne(t[s])),n}async function eN(e,t){var i,l,u,c;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let n={};n.resized=Ne.resizeBilinear(e,[fi,fi]),n.div=pe(n.resized,nt.tf127),n.normalized=he(n.div,nt.tf05);let s=Qr==null?void 0:Qr.execute(n.normalized);if(Array.isArray(s)&&s.length>2){let p=s.sort((d,h)=>d.size-h.size);n.concat384=Ct([p[0],p[2]],2),n.concat512=Ct([p[1],p[3]],2),n.concat=Ct([n.concat512,n.concat384],1),n.batch=rt(n.concat,0)}else Array.isArray(s)?n.batch=rt(s[0]):n.batch=rt(s);ne(s),n.boxes=e5e(n.batch),n.logits=Oe(n.batch,[0,0],[-1,1]),n.sigmoid=Cn(n.logits),n.scores=rt(n.sigmoid),n.nms=await Ne.nonMaxSuppressionAsync(n.boxes,n.scores,((i=t.face.detector)==null?void 0:i.maxDetected)||0,((l=t.face.detector)==null?void 0:l.iouThreshold)||0,((u=t.face.detector)==null?void 0:u.minConfidence)||0);let r=await n.nms.array(),a=[],o=await n.scores.data();for(let p=0;p<r.length;p++){let d=o[r[p]];if(d>(((c=t.face.detector)==null?void 0:c.minConfidence)||0)){let h={};h.bbox=Oe(n.boxes,[r[p],0],[1,-1]),h.slice=Oe(n.batch,[r[p],YT-1],[1,-1]),h.squeeze=rt(h.slice),h.landmarks=U(h.squeeze,[YT,-1]);let f=await h.bbox.data(),m={startPoint:[f[0],f[1]],endPoint:[f[2],f[3]],landmarks:await h.landmarks.array(),confidence:d},g=GT(m,[(e.shape[2]||0)/fi,(e.shape[1]||0)/fi]),y=L2(g,t.face.scale||QAe),x=B2(y);a.push(x),Object.keys(h).forEach(A=>ne(h[A]))}}return Object.keys(n).forEach(p=>ne(n[p])),a}var W2={};oa(W2,{connected:()=>_b,kpt:()=>Rb});var Rb=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPinky","rightPinky","leftIndex","rightIndex","leftThumb","rightThumb","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","bodyCenter","bodyTop","leftPalm","leftHand","rightPalm","rightHand"],_b={shoulders:["leftShoulder","rightShoulder"],hips:["rightHip","leftHip"],mouth:["leftMouth","rightMouth"],leftLegUpper:["leftHip","leftKnee"],leftLegLower:["leftKnee","leftAnkle"],leftFoot:["leftAnkle","leftHeel","leftFoot"],leftTorso:["leftShoulder","leftHip"],leftArmUpper:["leftShoulder","leftElbow"],leftArmLower:["leftElbow","leftWrist"],leftHand:["leftWrist","leftPalm"],leftHandPinky:["leftPalm","leftPinky"],leftHandIndex:["leftPalm","leftIndex"],leftHandThumb:["leftPalm","leftThumb"],leftEyeOutline:["leftEyeInside","leftEyeOutside"],rightLegUpper:["rightHip","rightKnee"],rightLegLower:["rightKnee","rightAnkle"],rightFoot:["rightAnkle","rightHeel","rightFoot"],rightTorso:["rightShoulder","rightHip"],rightArmUpper:["rightShoulder","rightElbow"],rightArmLower:["rightElbow","rightWrist"],rightHand:["rightWrist","rightPalm"],rightHandPinky:["rightPalm","rightPinky"],rightHandIndex:["rightPalm","rightIndex"],rightHandThumb:["rightPalm","rightThumb"],rightEyeOutline:["rightEyeInside","rightEyeOutside"]};var nN=224,t5e,n5e=5,V2=[8,16,32,32,32];async function sN(){let e=[],t=0;for(;t<n5e;){let n=0,s=t;for(;s<V2.length&&V2[s]===V2[t];)n+=2,s++;let r=V2[t],a=Math.ceil(nN/r),o=Math.ceil(nN/r);for(let i=0;i<a;++i)for(let l=0;l<o;++l)for(let u=0;u<n;++u)e.push({x:(l+.5)/o,y:(i+.5)/a});t=s}t5e={x:Ft(e.map(n=>n.x)),y:Ft(e.map(n=>n.y))}}function Ta(e,t=[1,1]){let n=[e.map(i=>i[0]),e.map(i=>i[1])],s=[Math.min(...n[0]),Math.min(...n[1])],r=[Math.max(...n[0]),Math.max(...n[1])],a=[s[0],s[1],r[0]-s[0],r[1]-s[1]],o=[a[0]/t[0],a[1]/t[1],a[2]/t[0],a[3]/t[1]];return{box:a,boxRaw:o}}function rN(e,t=[1,1]){let n=[e.map(u=>u[0]),e.map(u=>u[1])],s=[Math.min(...n[0]),Math.min(...n[1])],r=[Math.max(...n[0]),Math.max(...n[1])],a=[(s[0]+r[0])/2,(s[1]+r[1])/2],o=Math.max(a[0]-s[0],a[1]-s[1],-a[0]+r[0],-a[1]+r[1]),i=[Math.trunc(a[0]-o),Math.trunc(a[1]-o),Math.trunc(2*o),Math.trunc(2*o)],l=[i[0]/t[0],i[1]/t[1],i[2]/t[0],i[3]/t[1]];return{box:i,boxRaw:l}}function U2(e,t){let n=[e[2]*t,e[3]*t];return[e[0]-(n[0]-e[2])/2,e[1]-(n[1]-e[3])/2,n[0],n[1]]}var iN={initial:!0},Ms={detector:null,landmarks:null},Ad={detector:[224,224],landmarks:[256,256]},Db=Number.MAX_SAFE_INTEGER,r5e={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},H2=null,jh,mi=[[0,0],[0,0],[0,0],[0,0]],aN=0,oN=e=>1-1/(1+Math.exp(e));async function lN(e){if(iN.initial&&(Ms.detector=null),!Ms.detector&&e.body.detector&&e.body.detector.modelPath){Ms.detector=await qe(e.body.detector.modelPath);let t=Object.values(Ms.detector.modelSignature.inputs);Ad.detector[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,Ad.detector[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&Ms.detector&&ie("cached model:",Ms.detector.modelUrl);return await sN(),Ms.detector}async function uN(e){if(iN.initial&&(Ms.landmarks=null),Ms.landmarks)e.debug&&ie("cached model:",Ms.landmarks.modelUrl);else{Ms.landmarks=await qe(e.body.modelPath);let t=Object.values(Ms.landmarks.modelSignature.inputs);Ad.landmarks[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,Ad.landmarks[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return Ms.landmarks}async function a5e(e,t){let n={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;let s;if(jh&&(n.cropped=Ne.cropAndResize(e,[jh],[0],[e.shape[1],e.shape[2]])),e.shape[1]!==e.shape[2]){let r=[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],a=[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0];mi=[[0,0],r,a,[0,0]],n.pad=Js(n.cropped||e,mi),n.resize=Ne.resizeBilinear(n.pad,[t,t]),s=pe(n.resize,nt.tf255)}else e.shape[1]!==t?(n.resize=Ne.resizeBilinear(n.cropped||e,[t,t]),s=pe(n.resize,nt.tf255)):s=pe(n.cropped||e,nt.tf255);return Object.keys(n).forEach(r=>ne(n[r])),s}function o5e(e,t){for(let n of e)n.position=[Math.trunc(n.position[0]*(t[0]+mi[2][0]+mi[2][1])/t[0]-mi[2][0]),Math.trunc(n.position[1]*(t[1]+mi[1][0]+mi[1][1])/t[1]-mi[1][0]),n.position[2]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1],2*n.position[2]/(t[0]+t[1])];if(jh)for(let n of e)n.positionRaw=[n.positionRaw[0]+jh[1],n.positionRaw[1]+jh[0],n.positionRaw[2]],n.position=[Math.trunc(n.positionRaw[0]*t[0]),Math.trunc(n.positionRaw[1]*t[1]),n.positionRaw[2]];return e}async function i5e(e){let t=e.find(i=>i.part==="leftPalm"),n=e.find(i=>i.part==="leftWrist"),s=e.find(i=>i.part==="leftIndex");t.position[2]=((n.position[2]||0)+(s.position[2]||0))/2;let r=e.find(i=>i.part==="rightPalm"),a=e.find(i=>i.part==="rightWrist"),o=e.find(i=>i.part==="rightIndex");r.position[2]=((a.position[2]||0)+(o.position[2]||0))/2}async function l5e(e,t,n){var f;let s={};[s.ld,s.segmentation,s.heatmap,s.world,s.poseflag]=(f=Ms.landmarks)==null?void 0:f.execute(e,r5e.landmarks);let r=(await s.poseflag.data())[0],a=await s.ld.data(),o=await s.world.data();Object.keys(s).forEach(m=>ne(s[m]));let i=[],l=5;for(let m=0;m<a.length/l;m++){let g=oN(a[l*m+3]),y=oN(a[l*m+4]),x=Math.trunc(100*g*y*r)/100,A=[a[l*m+0]/Ad.landmarks[0],a[l*m+1]/Ad.landmarks[1],a[l*m+2]+0],b=[Math.trunc(n[0]*A[0]),Math.trunc(n[1]*A[1]),A[2]],w=[o[l*m+0],o[l*m+1],o[l*m+2]+0];i.push({part:Rb[m],positionRaw:A,position:b,distance:w,score:x})}if(r<(t.body.minConfidence||0))return null;i5e(i);let u=o5e(i,n),c=u.map(m=>m.position),p=Ta(c,[n[0],n[1]]),d={};for(let[m,g]of Object.entries(_b)){let y=[];for(let x=0;x<g.length-1;x++){let A=u.find(w=>w.part===g[x]),b=u.find(w=>w.part===g[x+1]);A&&b&&y.push([A.position,b.position])}d[m]=y}return{id:0,score:Math.trunc(100*r)/100,box:p.box,boxRaw:p.boxRaw,keypoints:u,annotations:d}}async function $b(e,t){let n=[e.shape[2]||0,e.shape[1]||0],s=(t.body.skipTime||0)>ue()-aN,r=Db<(t.body.skipFrames||0);if(t.skipAllowed&&s&&r&&H2!==null)Db++;else{let a={};a.landmarks=await a5e(e,256),H2=await l5e(a.landmarks,t,n),Object.keys(a).forEach(o=>ne(a[o])),aN=ue(),Db=0}return H2?[H2]:[]}var xd=[{class:1,label:"person"},{class:2,label:"bicycle"},{class:3,label:"car"},{class:4,label:"motorcycle"},{class:5,label:"airplane"},{class:6,label:"bus"},{class:7,label:"train"},{class:8,label:"truck"},{class:9,label:"boat"},{class:10,label:"traffic light"},{class:11,label:"fire hydrant"},{class:12,label:"stop sign"},{class:13,label:"parking meter"},{class:14,label:"bench"},{class:15,label:"bird"},{class:16,label:"cat"},{class:17,label:"dog"},{class:18,label:"horse"},{class:19,label:"sheep"},{class:20,label:"cow"},{class:21,label:"elephant"},{class:22,label:"bear"},{class:23,label:"zebra"},{class:24,label:"giraffe"},{class:25,label:"backpack"},{class:26,label:"umbrella"},{class:27,label:"handbag"},{class:28,label:"tie"},{class:29,label:"suitcase"},{class:30,label:"frisbee"},{class:31,label:"skis"},{class:32,label:"snowboard"},{class:33,label:"sports ball"},{class:34,label:"kite"},{class:35,label:"baseball bat"},{class:36,label:"baseball glove"},{class:37,label:"skateboard"},{class:38,label:"surfboard"},{class:39,label:"tennis racket"},{class:40,label:"bottle"},{class:41,label:"wine glass"},{class:42,label:"cup"},{class:43,label:"fork"},{class:44,label:"knife"},{class:45,label:"spoon"},{class:46,label:"bowl"},{class:47,label:"banana"},{class:48,label:"apple"},{class:49,label:"sandwich"},{class:50,label:"orange"},{class:51,label:"broccoli"},{class:52,label:"carrot"},{class:53,label:"hot dog"},{class:54,label:"pizza"},{class:55,label:"donut"},{class:56,label:"cake"},{class:57,label:"chair"},{class:58,label:"couch"},{class:59,label:"potted plant"},{class:60,label:"bed"},{class:61,label:"dining table"},{class:62,label:"toilet"},{class:63,label:"tv"},{class:64,label:"laptop"},{class:65,label:"mouse"},{class:66,label:"remote"},{class:67,label:"keyboard"},{class:68,label:"cell phone"},{class:69,label:"microwave"},{class:70,label:"oven"},{class:71,label:"toaster"},{class:72,label:"sink"},{class:73,label:"refrigerator"},{class:74,label:"book"},{class:75,label:"clock"},{class:76,label:"vase"},{class:77,label:"scissors"},{class:78,label:"teddy bear"},{class:79,label:"hair drier"},{class:80,label:"toothbrush"}];var Na,uu=0,Pb=[],dN=0,Fb=Number.MAX_SAFE_INTEGER;async function pN(e){if(fe.initial&&(Na=null),Na)e.debug&&ie("cached model:",Na.modelUrl);else{Na=await qe(e.object.modelPath);let t=Object.values(Na.modelSignature.inputs);uu=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return Na}async function u5e(e,t,n){if(!e)return[];let s={},r=[],a=await e.array();s.squeeze=rt(e);let o=Zt(s.squeeze,6,1);s.stack=on([o[1],o[0],o[3],o[2]],1),s.boxes=rt(s.stack),s.scores=rt(o[4]),s.classes=rt(o[5]),ne([e,...o]),s.nms=await Ne.nonMaxSuppressionAsync(s.boxes,s.scores,n.object.maxDetected,n.object.iouThreshold,n.object.minConfidence||0);let i=await s.nms.data(),l=0;for(let u of Array.from(i)){let c=Math.trunc(100*a[0][u][4])/100,p=a[0][u][5],d=xd[p].label,[h,f]=[a[0][u][0]/uu,a[0][u][1]/uu],m=[h,f,a[0][u][2]/uu-h,a[0][u][3]/uu-f],g=[Math.trunc(m[0]*t[0]),Math.trunc(m[1]*t[1]),Math.trunc(m[2]*t[0]),Math.trunc(m[3]*t[1])];r.push({id:l++,score:c,class:p,label:d,box:g,boxRaw:m})}return Object.keys(s).forEach(u=>ne(s[u])),r}async function Ob(e,t){let n=(t.object.skipTime||0)>ue()-dN,s=Fb<(t.object.skipFrames||0);return t.skipAllowed&&n&&s&&Pb.length>0?(Fb++,Pb):(Fb=0,new Promise(async r=>{let a=[e.shape[2]||0,e.shape[1]||0],o=Ne.resizeBilinear(e,[uu,uu]),i=t.object.enabled?Na==null?void 0:Na.execute(o,["tower_0/detections"]):null;dN=ue(),ne(o);let l=await u5e(i,a,t);Pb=l,r(l)}))}var j2={};oa(j2,{connected:()=>zb,kpt:()=>Mb});var Mb=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],zb={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var Ln,fN=0,us={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},Lb=Number.MAX_SAFE_INTEGER;async function mN(e){return fe.initial&&(Ln=null),Ln?e.debug&&ie("cached model:",Ln.modelUrl):Ln=await qe(e.body.modelPath),Ln}async function c5e(e,t){let[n,s]=e.shape,r=U(e,[s*n]),a=mn(r,0),o=(await a.data())[0];if(ne([r,a]),o>t){let i=Es(r,0),l=Zl(i,n),u=(await l.data())[0],c=pe(i,Se(n,"int32")),p=(await c.data())[0];return ne([l,c]),[u,p,o]}return[0,0,o]}async function Bb(e,t){let n=(t.body.skipTime||0)>ue()-fN,s=Lb<(t.body.skipFrames||0);return t.skipAllowed&&n&&s&&Object.keys(us.keypoints).length>0?(Lb++,[us]):(Lb=0,new Promise(async r=>{var p;let a=J(()=>{if(!(Ln!=null&&Ln.inputs[0].shape))return null;let d=Ne.resizeBilinear(e,[Ln.inputs[0].shape[2],Ln.inputs[0].shape[1]],!1),h=L(d,nt.tf2);return he(h,nt.tf1)}),o;if(t.body.enabled&&(o=Ln==null?void 0:Ln.execute(a)),fN=ue(),ne(a),o){us.keypoints.length=0;let d=o.squeeze();ne(o);let h=d.unstack(2);ne(d);for(let f=0;f<h.length;f++){let[m,g,y]=await c5e(h[f],t.body.minConfidence);y>(((p=t.body)==null?void 0:p.minConfidence)||0)&&us.keypoints.push({score:Math.round(100*y)/100,part:Mb[f],positionRaw:[m/Ln.inputs[0].shape[2],g/Ln.inputs[0].shape[1]],position:[Math.round(e.shape[2]*m/Ln.inputs[0].shape[2]),Math.round(e.shape[1]*g/Ln.inputs[0].shape[1])]})}h.forEach(f=>ne(f))}us.score=us.keypoints.reduce((d,h)=>h.score>d?h.score:d,0);let i=us.keypoints.map(d=>d.position[0]),l=us.keypoints.map(d=>d.position[1]);us.box=[Math.min(...i),Math.min(...l),Math.max(...i)-Math.min(...i),Math.max(...l)-Math.min(...l)];let u=us.keypoints.map(d=>d.positionRaw[0]),c=us.keypoints.map(d=>d.positionRaw[1]);us.boxRaw=[Math.min(...u),Math.min(...c),Math.max(...u)-Math.min(...u),Math.max(...c)-Math.min(...c)];for(let[d,h]of Object.entries(zb)){let f=[];for(let m=0;m<h.length-1;m++){let g=us.keypoints.find(x=>x.part===h[m]),y=us.keypoints.find(x=>x.part===h[m+1]);g&&y&&g.score>(t.body.minConfidence||0)&&y.score>(t.body.minConfidence||0)&&f.push([g.position,y.position])}us.annotations[d]=f}r([us])}))}var d5e=["angry","disgust","fear","happy","sad","surprise","neutral"],er,q2=[],yN=0,AN=0,Wb=Number.MAX_SAFE_INTEGER;async function xN(e){var t;return fe.initial&&(er=null),er?e.debug&&ie("cached model:",er.modelUrl):er=await qe((t=e.face.emotion)==null?void 0:t.modelPath),er}async function Vb(e,t,n,s){var o,i;if(!er)return[];let r=Wb<(((o=t.face.emotion)==null?void 0:o.skipFrames)||0),a=(((i=t.face.emotion)==null?void 0:i.skipTime)||0)>ue()-AN;return t.skipAllowed&&a&&r&&yN===s&&q2[n]&&q2[n].length>0?(Wb++,q2[n]):(Wb=0,new Promise(async l=>{var c,p;let u=[];if((c=t.face.emotion)!=null&&c.enabled){let d={},h=er!=null&&er.inputs[0].shape?er.inputs[0].shape[2]:0;d.resize=Ne.resizeBilinear(e,[h,h],!1),d.channels=L(d.resize,nt.rgb),d.grayscale=ke(d.channels,3,!0),d.grayscaleSub=he(d.grayscale,nt.tf05),d.grayscaleMul=L(d.grayscaleSub,nt.tf2),d.emotion=er==null?void 0:er.execute(d.grayscaleMul),AN=ue();let f=await d.emotion.data();for(let m=0;m<f.length;m++)f[m]>(((p=t.face.emotion)==null?void 0:p.minConfidence)||0)&&u.push({score:Math.min(.99,Math.trunc(100*f[m])/100),emotion:d5e[m]});u.sort((m,g)=>g.score-m.score),Object.keys(d).forEach(m=>ne(d[m]))}q2[n]=u,yN=s,l(u)}))}var zs,Ub=[],vN=0,wN=0,kN=Number.MAX_SAFE_INTEGER;async function IN(e){return fe.initial&&(zs=null),zs?e.debug&&ie("cached model:",zs.modelUrl):zs=await qe(e.face.mobilefacenet.modelPath),zs}async function Gb(e,t,n,s){var o,i;if(!zs)return[];let r=kN<(((o=t.face.embedding)==null?void 0:o.skipFrames)||0),a=(((i=t.face.embedding)==null?void 0:i.skipTime)||0)>ue()-wN;return t.skipAllowed&&a&&r&&vN===s&&Ub[n]?(kN++,Ub[n]):new Promise(async l=>{var c;let u=[];if(((c=t.face.embedding)==null?void 0:c.enabled)&&(zs==null?void 0:zs.inputs[0].shape)){let p={};p.crop=Ne.resizeBilinear(e,[zs.inputs[0].shape[2],zs.inputs[0].shape[1]],!1),p.data=zs==null?void 0:zs.execute(p.crop);let d=await p.data.data();u=Array.from(d)}Ub[n]=u,vN=s,wN=ue(),l(u)})}var Ea,gi=0,p5e=2.3,Hb=gr.leftEyeLower0,jb=gr.rightEyeLower0,bd={leftBounds:[Hb[0],Hb[Hb.length-1]],rightBounds:[jb[0],jb[jb.length-1]]},vd={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function EN(e){var t;return fe.initial&&(Ea=null),Ea?e.debug&&ie("cached model:",Ea.modelUrl):Ea=await qe((t=e.face.iris)==null?void 0:t.modelPath),gi=Ea.inputs[0].shape?Ea.inputs[0].shape[2]:0,gi===-1&&(gi=64),Ea}function X2(e,t,n,s){for(let r=0;r<Sb.length;r++){let{key:a,indices:o}=Sb[r],i=gr[`${n}${a}`];if(!s||s.includes(a))for(let l=0;l<o.length;l++){let u=o[l];e[i[l]]=[t[u][0],t[u][1],(t[u][2]+e[i[l]][2])/2]}}}var h5e=e=>{let t=e[bd.leftBounds[0]][2],n=e[bd.rightBounds[0]][2];return t-n},CN=(e,t,n,s,r,a=!1)=>{let o=B2(L2(HT([e[n],e[s]]),p5e)),i=gd(o),l=Ne.cropAndResize(t,[[o.startPoint[1]/r,o.startPoint[0]/r,o.endPoint[1]/r,o.endPoint[0]/r]],[0],[gi,gi]);if(a&&fe.kernels.includes("flipleftright")){let u=Ne.flipLeftRight(l);ne(l),l=u}return{box:o,boxSize:i,crop:l}},TN=(e,t,n,s=!1)=>{let r=[];for(let a=0;a<vd.numCoordinates;a++){let o=e[a*3],i=e[a*3+1],l=e[a*3+2];r.push([(s?1-o/gi:o/gi)*n[0]+t.startPoint[0],i/gi*n[1]+t.startPoint[1],l])}return{rawCoords:r,iris:r.slice(vd.index)}},NN=(e,t,n)=>{let s=e[gr[`${n}EyeUpper0`][vd.upperCenter]][2],r=e[gr[`${n}EyeLower0`][vd.lowerCenter]][2],a=(s+r)/2;return t.map((o,i)=>{let l=a;return i===2?l=s:i===4&&(l=r),[o[0],o[1],l]})};async function RN(e,t,n,s){if(!Ea)return n.debug&&ie("face mesh iris detection requested, but model is not loaded"),e;let{box:r,boxSize:a,crop:o}=CN(e,t,bd.leftBounds[0],bd.leftBounds[1],s,!0),{box:i,boxSize:l,crop:u}=CN(e,t,bd.rightBounds[0],bd.rightBounds[1],s,!0),c=Ct([o,u]);ne(o),ne(u);let p=Ea.execute(c);ne(c);let d=await p.data();ne(p);let h=d.slice(0,vd.numCoordinates*3),{rawCoords:f,iris:m}=TN(h,r,a,!0),g=d.slice(vd.numCoordinates*3),{rawCoords:y,iris:x}=TN(g,i,l,!1),A=h5e(e);Math.abs(A)<30?(X2(e,f,"left",null),X2(e,y,"right",null)):A<1?X2(e,f,"left",["EyeUpper0","EyeLower0"]):X2(e,y,"right",["EyeUpper0","EyeLower0"]);let b=NN(e,m,"left"),w=NN(e,x,"right");return e.concat(b).concat(w)}var f5e=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],m5e=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],g5e=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],y5e=[[474,475],[475,476],[476,477],[477,474]],A5e=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],x5e=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],b5e=[[469,470],[470,471],[471,472],[472,469]],v5e=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]];function yi(e){let t=e.map(n=>n[0]);return t.push(e[e.length-1][1]),t}var w5e={lips:yi(f5e),leftEye:yi(m5e),leftEyebrow:yi(g5e),leftIris:yi(y5e),rightEye:yi(A5e),rightEyebrow:yi(x5e),rightIris:yi(b5e),faceOval:yi(v5e)},k5e=Object.entries(w5e).map(([e,t])=>t.map(n=>[n,e])).flat(),Ake=new Map(k5e),qh=[61,146,91,181,84,17,314,405,321,375,291,185,40,39,37,0,267,269,270,409,78,95,88,178,87,14,317,402,318,324,308,191,80,81,82,13,312,311,310,415,76,77,90,180,85,16,315,404,320,307,306,184,74,73,72,11,302,303,304,408,62,96,89,179,86,15,316,403,319,325,292,183,42,41,38,12,268,271,272,407],cu=[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173,130,25,110,24,23,22,26,112,243,247,30,29,27,28,56,190,226,31,228,229,230,231,232,233,244,113,225,224,223,222,221,189,35,124,46,53,52,65,143,111,117,118,119,120,121,128,245,156,70,63,105,66,107,55,193],du=[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398,359,255,339,254,253,252,256,341,463,467,260,259,257,258,286,414,446,261,448,449,450,451,452,453,464,342,445,444,443,442,441,413,265,353,276,283,282,295,372,340,346,347,348,349,350,357,465,383,300,293,334,296,336,285,417];async function $N(e,t){let n={lips:await t.filter(a=>a.size===160)[0].data(),irisL:await t.filter(a=>a.size===10)[0].data(),eyeL:await t.filter(a=>a.size===142)[0].data(),irisR:await t.filter(a=>a.size===10)[1].data(),eyeR:await t.filter(a=>a.size===142)[1].data()},s=cu.reduce((a,o)=>a+=e[o][2],0)/cu.length;for(let a=0;a<n.irisL.length/2;a++)e.push([n.irisL[2*a+0],n.irisL[2*a+1],s]);let r=du.reduce((a,o)=>a+=e[o][2],0)/du.length;for(let a=0;a<n.irisR.length/2;a++)e.push([n.irisR[2*a+0],n.irisR[2*a+1],r]);for(let a=0;a<n.eyeL.length/2;a++)e[cu[a]]=[n.eyeL[2*a+0],n.eyeL[2*a+1],e[cu[a]][2]];for(let a=0;a<n.eyeR.length/2;a++)e[du[a]]=[n.eyeR[2*a+0],n.eyeR[2*a+1],e[du[a]][2]];for(let a=0;a<n.lips.length/2;a++)e[qh[a]]=[n.lips[2*a+0],n.lips[2*a+1],e[qh[a]][2]];return e}var ea={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},Bn=null,pu=0;async function PN(e,t){var i,l,u,c,p,d,h,f,m,g,y;let n=(((i=t.face.detector)==null?void 0:i.skipTime)||0)>ue()-ea.timestamp,s=ea.skipped<(((l=t.face.detector)==null?void 0:l.skipFrames)||0);!t.skipAllowed||!n||!s||ea.boxes.length===0?(ea.boxes=await eN(e,t),ea.timestamp=ue(),ea.skipped=0):ea.skipped++;let r=[],a=[],o=0;for(let x=0;x<ea.boxes.length;x++){let A=ea.boxes[x],b=0,w,k={id:o++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,annotations:{}};if([b,w,k.tensor]=KT((u=t.face.detector)==null?void 0:u.rotation,A,e,(c=t.face.mesh)!=null&&c.enabled?pu:yd()),(p=t==null?void 0:t.filter)!=null&&p.equalization){let S=await R2(k.tensor);ne(k.tensor),k.tensor=S}if(k.boxScore=Math.round(100*A.confidence)/100,(d=t.face.mesh)!=null&&d.enabled)if(!Bn)t.debug&&ie("face mesh detection requested, but model is not loaded");else{let S=Bn.execute(k.tensor),R=await S.find(P=>P.shape[P.shape.length-1]===1).data();if(k.faceScore=Math.round(100*R[0])/100,k.faceScore<(((h=t.face.detector)==null?void 0:h.minConfidence)||1)){if(A.confidence=k.faceScore,(f=t.face.mesh)!=null&&f.keepInvalid){k.box=M2(A,e),k.boxRaw=z2(A,e),k.score=k.boxScore,k.mesh=A.landmarks.map(P=>[(A.startPoint[0]+A.endPoint[0])/2+(A.endPoint[0]+A.startPoint[0])*P[0]/yd(),(A.startPoint[1]+A.endPoint[1])/2+(A.endPoint[1]+A.startPoint[1])*P[1]/yd()]),k.meshRaw=k.mesh.map(P=>[P[0]/(e.shape[2]||1),P[1]/(e.shape[1]||1),(P[2]||0)/pu]);for(let P of Object.keys(ou))k.annotations[P]=[k.mesh[ou[P]]]}}else{let P=S.find(F=>F.shape[F.shape.length-1]===1404),_=U(P,[-1,3]),$=await _.array();ne(_),(m=t.face.attention)!=null&&m.enabled?$=await $N($,S):(g=t.face.iris)!=null&&g.enabled&&($=await RN($,k.tensor,t,pu)),k.mesh=XT($,A,b,w,pu),k.meshRaw=k.mesh.map(F=>[F[0]/(e.shape[2]||0),F[1]/(e.shape[1]||0),(F[2]||0)/pu]);for(let F of Object.keys(gr))k.annotations[F]=gr[F].map(G=>k.mesh[G]);k.score=k.faceScore;let T={...ZT(k.mesh,A),confidence:A.confidence,landmarks:A.landmarks};k.box=M2(T,e),k.boxRaw=z2(T,e),a.push(T)}ne(S)}else{k.box=M2(A,e),k.boxRaw=z2(A,e),k.score=k.boxScore,k.mesh=A.landmarks.map(S=>[(A.startPoint[0]+A.endPoint[0])/2+(A.endPoint[0]+A.startPoint[0])*S[0]/yd(),(A.startPoint[1]+A.endPoint[1])/2+(A.endPoint[1]+A.startPoint[1])*S[1]/yd()]),k.meshRaw=k.mesh.map(S=>[S[0]/(e.shape[2]||0),S[1]/(e.shape[1]||0),(S[2]||0)/pu]);for(let S of Object.keys(ou))k.annotations[S]=[k.mesh[ou[S]]]}k.score>(((y=t.face.detector)==null?void 0:y.minConfidence)||1)?r.push(k):ne(k.tensor)}return ea.boxes=a,r}async function FN(e){var t,n,s,r,a,o;return fe.initial&&(Bn=null),((n=(t=e==null?void 0:e.face)==null?void 0:t.attention)==null?void 0:n.enabled)&&(Bn==null?void 0:Bn.signature)&&Object.keys(((s=Bn==null?void 0:Bn.signature)==null?void 0:s.outputs)||{}).length<6&&(Bn=null),Bn?e.debug&&ie("cached model:",Bn.modelUrl):(r=e.face.attention)!=null&&r.enabled?Bn=await qe((a=e.face.attention)==null?void 0:a.modelPath):Bn=await qe((o=e.face.mesh)==null?void 0:o.modelPath),pu=Bn.inputs[0].shape?Bn.inputs[0].shape[2]:0,Bn}var ON=iu,MN=Gh;var Ls,K2=[],zN=0,LN=0,Xb=Number.MAX_SAFE_INTEGER;async function BN(e){var t;return fe.initial&&(Ls=null),Ls?e.debug&&ie("cached model:",Ls.modelUrl):Ls=await qe((t=e.face.description)==null?void 0:t.modelPath),Ls}function Kb(e){let t=e.image||e.tensor||e;if(!(Ls!=null&&Ls.inputs[0].shape))return t;let n=Ne.resizeBilinear(t,[Ls.inputs[0].shape[2],Ls.inputs[0].shape[1]],!1),s=L(n,nt.tf255);return ne(n),s}async function Zb(e,t,n,s){var o,i,l,u;if(!Ls)return{age:0,gender:"unknown",genderScore:0,descriptor:[]};let r=Xb<(((o=t.face.description)==null?void 0:o.skipFrames)||0),a=(((i=t.face.description)==null?void 0:i.skipTime)||0)>ue()-zN;return t.skipAllowed&&r&&a&&LN===s&&((l=K2[n])==null?void 0:l.age)&&((u=K2[n])==null?void 0:u.age)>0?(Xb++,K2[n]):(Xb=0,new Promise(async c=>{var d,h;let p={age:0,gender:"unknown",genderScore:0,descriptor:[]};if((d=t.face.description)!=null&&d.enabled){let f=Kb(e),m=Ls==null?void 0:Ls.execute(f);zN=ue(),ne(f);let y=await(await m.find(R=>R.shape[1]===1)).data(),x=Math.trunc(200*Math.abs(y[0]-.5))/100;x>(((h=t.face.description)==null?void 0:h.minConfidence)||0)&&(p.gender=y[0]<=.5?"female":"male",p.genderScore=Math.min(.99,x));let A=Es(m.find(R=>R.shape[1]===100),1),b=(await A.data())[0];ne(A);let k=await m.find(R=>R.shape[1]===100).data();p.age=Math.round(k[b-1]>k[b+1]?10*b-100*k[b-1]:10*b+100*k[b+1])/10;let S=m.find(R=>R.shape[1]===1024),E=S?await S.data():[];p.descriptor=Array.from(E),m.forEach(R=>ne(R))}K2[n]=p,LN=s,c(p)}))}function Z2(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function Xh(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function UN(e,t,n){let s=t.shape[1],r=t.shape[2],a=[[e.startPoint[1]/s,e.startPoint[0]/r,e.endPoint[1]/s,e.endPoint[0]/r]];return Ne.cropAndResize(t,a,[0],n)}function GN(e,t){let n=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],s=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],r=e.palmLandmarks.map(a=>[a[0]*t[0],a[1]*t[1]]);return{startPoint:n,endPoint:s,palmLandmarks:r,confidence:e.confidence}}function Y2(e,t=1.5){let n=Xh(e),s=Z2(e),r=[t*s[0]/2,t*s[1]/2],a=[n[0]-r[0],n[1]-r[1]],o=[n[0]+r[0],n[1]+r[1]];return{startPoint:a,endPoint:o,palmLandmarks:e.palmLandmarks}}function J2(e){let t=Xh(e),n=Z2(e),r=Math.max(...n)/2,a=[t[0]-r,t[1]-r],o=[t[0]+r,t[1]+r];return{startPoint:a,endPoint:o,palmLandmarks:e.palmLandmarks}}function S5e(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function HN(e,t){let n=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return S5e(n)}var WN=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function Ai(e,t){let n=0;for(let s=0;s<e.length;s++)n+=e[s]*t[s];return n}function C5e(e,t){let n=[];for(let s=0;s<e.length;s++)n.push(e[s][t]);return n}function VN(e,t){let n=[],s=e.length;for(let r=0;r<s;r++){n.push([]);for(let a=0;a<s;a++)n[r].push(Ai(e[r],C5e(t,a)))}return n}function Jb(e,t){let n=Math.cos(e),s=Math.sin(e),r=[[n,-s,0],[s,n,0],[0,0,1]],a=WN(t[0],t[1]),o=VN(a,r),i=WN(-t[0],-t[1]);return VN(o,i)}function jN(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],n=[e[0][2],e[1][2]],s=[-Ai(t[0],n),-Ai(t[1],n)];return[t[0].concat(s[0]),t[1].concat(s[1]),[0,0,1]]}function Qb(e,t){return[Ai(e,t[0]),Ai(e,t[1])]}var XN=[{x:.015625,y:.015625},{x:.015625,y:.015625},{x:.046875,y:.015625},{x:.046875,y:.015625},{x:.078125,y:.015625},{x:.078125,y:.015625},{x:.109375,y:.015625},{x:.109375,y:.015625},{x:.140625,y:.015625},{x:.140625,y:.015625},{x:.171875,y:.015625},{x:.171875,y:.015625},{x:.203125,y:.015625},{x:.203125,y:.015625},{x:.234375,y:.015625},{x:.234375,y:.015625},{x:.265625,y:.015625},{x:.265625,y:.015625},{x:.296875,y:.015625},{x:.296875,y:.015625},{x:.328125,y:.015625},{x:.328125,y:.015625},{x:.359375,y:.015625},{x:.359375,y:.015625},{x:.390625,y:.015625},{x:.390625,y:.015625},{x:.421875,y:.015625},{x:.421875,y:.015625},{x:.453125,y:.015625},{x:.453125,y:.015625},{x:.484375,y:.015625},{x:.484375,y:.015625},{x:.515625,y:.015625},{x:.515625,y:.015625},{x:.546875,y:.015625},{x:.546875,y:.015625},{x:.578125,y:.015625},{x:.578125,y:.015625},{x:.609375,y:.015625},{x:.609375,y:.015625},{x:.640625,y:.015625},{x:.640625,y:.015625},{x:.671875,y:.015625},{x:.671875,y:.015625},{x:.703125,y:.015625},{x:.703125,y:.015625},{x:.734375,y:.015625},{x:.734375,y:.015625},{x:.765625,y:.015625},{x:.765625,y:.015625},{x:.796875,y:.015625},{x:.796875,y:.015625},{x:.828125,y:.015625},{x:.828125,y:.015625},{x:.859375,y:.015625},{x:.859375,y:.015625},{x:.890625,y:.015625},{x:.890625,y:.015625},{x:.921875,y:.015625},{x:.921875,y:.015625},{x:.953125,y:.015625},{x:.953125,y:.015625},{x:.984375,y:.015625},{x:.984375,y:.015625},{x:.015625,y:.046875},{x:.015625,y:.046875},{x:.046875,y:.046875},{x:.046875,y:.046875},{x:.078125,y:.046875},{x:.078125,y:.046875},{x:.109375,y:.046875},{x:.109375,y:.046875},{x:.140625,y:.046875},{x:.140625,y:.046875},{x:.171875,y:.046875},{x:.171875,y:.046875},{x:.203125,y:.046875},{x:.203125,y:.046875},{x:.234375,y:.046875},{x:.234375,y:.046875},{x:.265625,y:.046875},{x:.265625,y:.046875},{x:.296875,y:.046875},{x:.296875,y:.046875},{x:.328125,y:.046875},{x:.328125,y:.046875},{x:.359375,y:.046875},{x:.359375,y:.046875},{x:.390625,y:.046875},{x:.390625,y:.046875},{x:.421875,y:.046875},{x:.421875,y:.046875},{x:.453125,y:.046875},{x:.453125,y:.046875},{x:.484375,y:.046875},{x:.484375,y:.046875},{x:.515625,y:.046875},{x:.515625,y:.046875},{x:.546875,y:.046875},{x:.546875,y:.046875},{x:.578125,y:.046875},{x:.578125,y:.046875},{x:.609375,y:.046875},{x:.609375,y:.046875},{x:.640625,y:.046875},{x:.640625,y:.046875},{x:.671875,y:.046875},{x:.671875,y:.046875},{x:.703125,y:.046875},{x:.703125,y:.046875},{x:.734375,y:.046875},{x:.734375,y:.046875},{x:.765625,y:.046875},{x:.765625,y:.046875},{x:.796875,y:.046875},{x:.796875,y:.046875},{x:.828125,y:.046875},{x:.828125,y:.046875},{x:.859375,y:.046875},{x:.859375,y:.046875},{x:.890625,y:.046875},{x:.890625,y:.046875},{x:.921875,y:.046875},{x:.921875,y:.046875},{x:.953125,y:.046875},{x:.953125,y:.046875},{x:.984375,y:.046875},{x:.984375,y:.046875},{x:.015625,y:.078125},{x:.015625,y:.078125},{x:.046875,y:.078125},{x:.046875,y:.078125},{x:.078125,y:.078125},{x:.078125,y:.078125},{x:.109375,y:.078125},{x:.109375,y:.078125},{x:.140625,y:.078125},{x:.140625,y:.078125},{x:.171875,y:.078125},{x:.171875,y:.078125},{x:.203125,y:.078125},{x:.203125,y:.078125},{x:.234375,y:.078125},{x:.234375,y:.078125},{x:.265625,y:.078125},{x:.265625,y:.078125},{x:.296875,y:.078125},{x:.296875,y:.078125},{x:.328125,y:.078125},{x:.328125,y:.078125},{x:.359375,y:.078125},{x:.359375,y:.078125},{x:.390625,y:.078125},{x:.390625,y:.078125},{x:.421875,y:.078125},{x:.421875,y:.078125},{x:.453125,y:.078125},{x:.453125,y:.078125},{x:.484375,y:.078125},{x:.484375,y:.078125},{x:.515625,y:.078125},{x:.515625,y:.078125},{x:.546875,y:.078125},{x:.546875,y:.078125},{x:.578125,y:.078125},{x:.578125,y:.078125},{x:.609375,y:.078125},{x:.609375,y:.078125},{x:.640625,y:.078125},{x:.640625,y:.078125},{x:.671875,y:.078125},{x:.671875,y:.078125},{x:.703125,y:.078125},{x:.703125,y:.078125},{x:.734375,y:.078125},{x:.734375,y:.078125},{x:.765625,y:.078125},{x:.765625,y:.078125},{x:.796875,y:.078125},{x:.796875,y:.078125},{x:.828125,y:.078125},{x:.828125,y:.078125},{x:.859375,y:.078125},{x:.859375,y:.078125},{x:.890625,y:.078125},{x:.890625,y:.078125},{x:.921875,y:.078125},{x:.921875,y:.078125},{x:.953125,y:.078125},{x:.953125,y:.078125},{x:.984375,y:.078125},{x:.984375,y:.078125},{x:.015625,y:.109375},{x:.015625,y:.109375},{x:.046875,y:.109375},{x:.046875,y:.109375},{x:.078125,y:.109375},{x:.078125,y:.109375},{x:.109375,y:.109375},{x:.109375,y:.109375},{x:.140625,y:.109375},{x:.140625,y:.109375},{x:.171875,y:.109375},{x:.171875,y:.109375},{x:.203125,y:.109375},{x:.203125,y:.109375},{x:.234375,y:.109375},{x:.234375,y:.109375},{x:.265625,y:.109375},{x:.265625,y:.109375},{x:.296875,y:.109375},{x:.296875,y:.109375},{x:.328125,y:.109375},{x:.328125,y:.109375},{x:.359375,y:.109375},{x:.359375,y:.109375},{x:.390625,y:.109375},{x:.390625,y:.109375},{x:.421875,y:.109375},{x:.421875,y:.109375},{x:.453125,y:.109375},{x:.453125,y:.109375},{x:.484375,y:.109375},{x:.484375,y:.109375},{x:.515625,y:.109375},{x:.515625,y:.109375},{x:.546875,y:.109375},{x:.546875,y:.109375},{x:.578125,y:.109375},{x:.578125,y:.109375},{x:.609375,y:.109375},{x:.609375,y:.109375},{x:.640625,y:.109375},{x:.640625,y:.109375},{x:.671875,y:.109375},{x:.671875,y:.109375},{x:.703125,y:.109375},{x:.703125,y:.109375},{x:.734375,y:.109375},{x:.734375,y:.109375},{x:.765625,y:.109375},{x:.765625,y:.109375},{x:.796875,y:.109375},{x:.796875,y:.109375},{x:.828125,y:.109375},{x:.828125,y:.109375},{x:.859375,y:.109375},{x:.859375,y:.109375},{x:.890625,y:.109375},{x:.890625,y:.109375},{x:.921875,y:.109375},{x:.921875,y:.109375},{x:.953125,y:.109375},{x:.953125,y:.109375},{x:.984375,y:.109375},{x:.984375,y:.109375},{x:.015625,y:.140625},{x:.015625,y:.140625},{x:.046875,y:.140625},{x:.046875,y:.140625},{x:.078125,y:.140625},{x:.078125,y:.140625},{x:.109375,y:.140625},{x:.109375,y:.140625},{x:.140625,y:.140625},{x:.140625,y:.140625},{x:.171875,y:.140625},{x:.171875,y:.140625},{x:.203125,y:.140625},{x:.203125,y:.140625},{x:.234375,y:.140625},{x:.234375,y:.140625},{x:.265625,y:.140625},{x:.265625,y:.140625},{x:.296875,y:.140625},{x:.296875,y:.140625},{x:.328125,y:.140625},{x:.328125,y:.140625},{x:.359375,y:.140625},{x:.359375,y:.140625},{x:.390625,y:.140625},{x:.390625,y:.140625},{x:.421875,y:.140625},{x:.421875,y:.140625},{x:.453125,y:.140625},{x:.453125,y:.140625},{x:.484375,y:.140625},{x:.484375,y:.140625},{x:.515625,y:.140625},{x:.515625,y:.140625},{x:.546875,y:.140625},{x:.546875,y:.140625},{x:.578125,y:.140625},{x:.578125,y:.140625},{x:.609375,y:.140625},{x:.609375,y:.140625},{x:.640625,y:.140625},{x:.640625,y:.140625},{x:.671875,y:.140625},{x:.671875,y:.140625},{x:.703125,y:.140625},{x:.703125,y:.140625},{x:.734375,y:.140625},{x:.734375,y:.140625},{x:.765625,y:.140625},{x:.765625,y:.140625},{x:.796875,y:.140625},{x:.796875,y:.140625},{x:.828125,y:.140625},{x:.828125,y:.140625},{x:.859375,y:.140625},{x:.859375,y:.140625},{x:.890625,y:.140625},{x:.890625,y:.140625},{x:.921875,y:.140625},{x:.921875,y:.140625},{x:.953125,y:.140625},{x:.953125,y:.140625},{x:.984375,y:.140625},{x:.984375,y:.140625},{x:.015625,y:.171875},{x:.015625,y:.171875},{x:.046875,y:.171875},{x:.046875,y:.171875},{x:.078125,y:.171875},{x:.078125,y:.171875},{x:.109375,y:.171875},{x:.109375,y:.171875},{x:.140625,y:.171875},{x:.140625,y:.171875},{x:.171875,y:.171875},{x:.171875,y:.171875},{x:.203125,y:.171875},{x:.203125,y:.171875},{x:.234375,y:.171875},{x:.234375,y:.171875},{x:.265625,y:.171875},{x:.265625,y:.171875},{x:.296875,y:.171875},{x:.296875,y:.171875},{x:.328125,y:.171875},{x:.328125,y:.171875},{x:.359375,y:.171875},{x:.359375,y:.171875},{x:.390625,y:.171875},{x:.390625,y:.171875},{x:.421875,y:.171875},{x:.421875,y:.171875},{x:.453125,y:.171875},{x:.453125,y:.171875},{x:.484375,y:.171875},{x:.484375,y:.171875},{x:.515625,y:.171875},{x:.515625,y:.171875},{x:.546875,y:.171875},{x:.546875,y:.171875},{x:.578125,y:.171875},{x:.578125,y:.171875},{x:.609375,y:.171875},{x:.609375,y:.171875},{x:.640625,y:.171875},{x:.640625,y:.171875},{x:.671875,y:.171875},{x:.671875,y:.171875},{x:.703125,y:.171875},{x:.703125,y:.171875},{x:.734375,y:.171875},{x:.734375,y:.171875},{x:.765625,y:.171875},{x:.765625,y:.171875},{x:.796875,y:.171875},{x:.796875,y:.171875},{x:.828125,y:.171875},{x:.828125,y:.171875},{x:.859375,y:.171875},{x:.859375,y:.171875},{x:.890625,y:.171875},{x:.890625,y:.171875},{x:.921875,y:.171875},{x:.921875,y:.171875},{x:.953125,y:.171875},{x:.953125,y:.171875},{x:.984375,y:.171875},{x:.984375,y:.171875},{x:.015625,y:.203125},{x:.015625,y:.203125},{x:.046875,y:.203125},{x:.046875,y:.203125},{x:.078125,y:.203125},{x:.078125,y:.203125},{x:.109375,y:.203125},{x:.109375,y:.203125},{x:.140625,y:.203125},{x:.140625,y:.203125},{x:.171875,y:.203125},{x:.171875,y:.203125},{x:.203125,y:.203125},{x:.203125,y:.203125},{x:.234375,y:.203125},{x:.234375,y:.203125},{x:.265625,y:.203125},{x:.265625,y:.203125},{x:.296875,y:.203125},{x:.296875,y:.203125},{x:.328125,y:.203125},{x:.328125,y:.203125},{x:.359375,y:.203125},{x:.359375,y:.203125},{x:.390625,y:.203125},{x:.390625,y:.203125},{x:.421875,y:.203125},{x:.421875,y:.203125},{x:.453125,y:.203125},{x:.453125,y:.203125},{x:.484375,y:.203125},{x:.484375,y:.203125},{x:.515625,y:.203125},{x:.515625,y:.203125},{x:.546875,y:.203125},{x:.546875,y:.203125},{x:.578125,y:.203125},{x:.578125,y:.203125},{x:.609375,y:.203125},{x:.609375,y:.203125},{x:.640625,y:.203125},{x:.640625,y:.203125},{x:.671875,y:.203125},{x:.671875,y:.203125},{x:.703125,y:.203125},{x:.703125,y:.203125},{x:.734375,y:.203125},{x:.734375,y:.203125},{x:.765625,y:.203125},{x:.765625,y:.203125},{x:.796875,y:.203125},{x:.796875,y:.203125},{x:.828125,y:.203125},{x:.828125,y:.203125},{x:.859375,y:.203125},{x:.859375,y:.203125},{x:.890625,y:.203125},{x:.890625,y:.203125},{x:.921875,y:.203125},{x:.921875,y:.203125},{x:.953125,y:.203125},{x:.953125,y:.203125},{x:.984375,y:.203125},{x:.984375,y:.203125},{x:.015625,y:.234375},{x:.015625,y:.234375},{x:.046875,y:.234375},{x:.046875,y:.234375},{x:.078125,y:.234375},{x:.078125,y:.234375},{x:.109375,y:.234375},{x:.109375,y:.234375},{x:.140625,y:.234375},{x:.140625,y:.234375},{x:.171875,y:.234375},{x:.171875,y:.234375},{x:.203125,y:.234375},{x:.203125,y:.234375},{x:.234375,y:.234375},{x:.234375,y:.234375},{x:.265625,y:.234375},{x:.265625,y:.234375},{x:.296875,y:.234375},{x:.296875,y:.234375},{x:.328125,y:.234375},{x:.328125,y:.234375},{x:.359375,y:.234375},{x:.359375,y:.234375},{x:.390625,y:.234375},{x:.390625,y:.234375},{x:.421875,y:.234375},{x:.421875,y:.234375},{x:.453125,y:.234375},{x:.453125,y:.234375},{x:.484375,y:.234375},{x:.484375,y:.234375},{x:.515625,y:.234375},{x:.515625,y:.234375},{x:.546875,y:.234375},{x:.546875,y:.234375},{x:.578125,y:.234375},{x:.578125,y:.234375},{x:.609375,y:.234375},{x:.609375,y:.234375},{x:.640625,y:.234375},{x:.640625,y:.234375},{x:.671875,y:.234375},{x:.671875,y:.234375},{x:.703125,y:.234375},{x:.703125,y:.234375},{x:.734375,y:.234375},{x:.734375,y:.234375},{x:.765625,y:.234375},{x:.765625,y:.234375},{x:.796875,y:.234375},{x:.796875,y:.234375},{x:.828125,y:.234375},{x:.828125,y:.234375},{x:.859375,y:.234375},{x:.859375,y:.234375},{x:.890625,y:.234375},{x:.890625,y:.234375},{x:.921875,y:.234375},{x:.921875,y:.234375},{x:.953125,y:.234375},{x:.953125,y:.234375},{x:.984375,y:.234375},{x:.984375,y:.234375},{x:.015625,y:.265625},{x:.015625,y:.265625},{x:.046875,y:.265625},{x:.046875,y:.265625},{x:.078125,y:.265625},{x:.078125,y:.265625},{x:.109375,y:.265625},{x:.109375,y:.265625},{x:.140625,y:.265625},{x:.140625,y:.265625},{x:.171875,y:.265625},{x:.171875,y:.265625},{x:.203125,y:.265625},{x:.203125,y:.265625},{x:.234375,y:.265625},{x:.234375,y:.265625},{x:.265625,y:.265625},{x:.265625,y:.265625},{x:.296875,y:.265625},{x:.296875,y:.265625},{x:.328125,y:.265625},{x:.328125,y:.265625},{x:.359375,y:.265625},{x:.359375,y:.265625},{x:.390625,y:.265625},{x:.390625,y:.265625},{x:.421875,y:.265625},{x:.421875,y:.265625},{x:.453125,y:.265625},{x:.453125,y:.265625},{x:.484375,y:.265625},{x:.484375,y:.265625},{x:.515625,y:.265625},{x:.515625,y:.265625},{x:.546875,y:.265625},{x:.546875,y:.265625},{x:.578125,y:.265625},{x:.578125,y:.265625},{x:.609375,y:.265625},{x:.609375,y:.265625},{x:.640625,y:.265625},{x:.640625,y:.265625},{x:.671875,y:.265625},{x:.671875,y:.265625},{x:.703125,y:.265625},{x:.703125,y:.265625},{x:.734375,y:.265625},{x:.734375,y:.265625},{x:.765625,y:.265625},{x:.765625,y:.265625},{x:.796875,y:.265625},{x:.796875,y:.265625},{x:.828125,y:.265625},{x:.828125,y:.265625},{x:.859375,y:.265625},{x:.859375,y:.265625},{x:.890625,y:.265625},{x:.890625,y:.265625},{x:.921875,y:.265625},{x:.921875,y:.265625},{x:.953125,y:.265625},{x:.953125,y:.265625},{x:.984375,y:.265625},{x:.984375,y:.265625},{x:.015625,y:.296875},{x:.015625,y:.296875},{x:.046875,y:.296875},{x:.046875,y:.296875},{x:.078125,y:.296875},{x:.078125,y:.296875},{x:.109375,y:.296875},{x:.109375,y:.296875},{x:.140625,y:.296875},{x:.140625,y:.296875},{x:.171875,y:.296875},{x:.171875,y:.296875},{x:.203125,y:.296875},{x:.203125,y:.296875},{x:.234375,y:.296875},{x:.234375,y:.296875},{x:.265625,y:.296875},{x:.265625,y:.296875},{x:.296875,y:.296875},{x:.296875,y:.296875},{x:.328125,y:.296875},{x:.328125,y:.296875},{x:.359375,y:.296875},{x:.359375,y:.296875},{x:.390625,y:.296875},{x:.390625,y:.296875},{x:.421875,y:.296875},{x:.421875,y:.296875},{x:.453125,y:.296875},{x:.453125,y:.296875},{x:.484375,y:.296875},{x:.484375,y:.296875},{x:.515625,y:.296875},{x:.515625,y:.296875},{x:.546875,y:.296875},{x:.546875,y:.296875},{x:.578125,y:.296875},{x:.578125,y:.296875},{x:.609375,y:.296875},{x:.609375,y:.296875},{x:.640625,y:.296875},{x:.640625,y:.296875},{x:.671875,y:.296875},{x:.671875,y:.296875},{x:.703125,y:.296875},{x:.703125,y:.296875},{x:.734375,y:.296875},{x:.734375,y:.296875},{x:.765625,y:.296875},{x:.765625,y:.296875},{x:.796875,y:.296875},{x:.796875,y:.296875},{x:.828125,y:.296875},{x:.828125,y:.296875},{x:.859375,y:.296875},{x:.859375,y:.296875},{x:.890625,y:.296875},{x:.890625,y:.296875},{x:.921875,y:.296875},{x:.921875,y:.296875},{x:.953125,y:.296875},{x:.953125,y:.296875},{x:.984375,y:.296875},{x:.984375,y:.296875},{x:.015625,y:.328125},{x:.015625,y:.328125},{x:.046875,y:.328125},{x:.046875,y:.328125},{x:.078125,y:.328125},{x:.078125,y:.328125},{x:.109375,y:.328125},{x:.109375,y:.328125},{x:.140625,y:.328125},{x:.140625,y:.328125},{x:.171875,y:.328125},{x:.171875,y:.328125},{x:.203125,y:.328125},{x:.203125,y:.328125},{x:.234375,y:.328125},{x:.234375,y:.328125},{x:.265625,y:.328125},{x:.265625,y:.328125},{x:.296875,y:.328125},{x:.296875,y:.328125},{x:.328125,y:.328125},{x:.328125,y:.328125},{x:.359375,y:.328125},{x:.359375,y:.328125},{x:.390625,y:.328125},{x:.390625,y:.328125},{x:.421875,y:.328125},{x:.421875,y:.328125},{x:.453125,y:.328125},{x:.453125,y:.328125},{x:.484375,y:.328125},{x:.484375,y:.328125},{x:.515625,y:.328125},{x:.515625,y:.328125},{x:.546875,y:.328125},{x:.546875,y:.328125},{x:.578125,y:.328125},{x:.578125,y:.328125},{x:.609375,y:.328125},{x:.609375,y:.328125},{x:.640625,y:.328125},{x:.640625,y:.328125},{x:.671875,y:.328125},{x:.671875,y:.328125},{x:.703125,y:.328125},{x:.703125,y:.328125},{x:.734375,y:.328125},{x:.734375,y:.328125},{x:.765625,y:.328125},{x:.765625,y:.328125},{x:.796875,y:.328125},{x:.796875,y:.328125},{x:.828125,y:.328125},{x:.828125,y:.328125},{x:.859375,y:.328125},{x:.859375,y:.328125},{x:.890625,y:.328125},{x:.890625,y:.328125},{x:.921875,y:.328125},{x:.921875,y:.328125},{x:.953125,y:.328125},{x:.953125,y:.328125},{x:.984375,y:.328125},{x:.984375,y:.328125},{x:.015625,y:.359375},{x:.015625,y:.359375},{x:.046875,y:.359375},{x:.046875,y:.359375},{x:.078125,y:.359375},{x:.078125,y:.359375},{x:.109375,y:.359375},{x:.109375,y:.359375},{x:.140625,y:.359375},{x:.140625,y:.359375},{x:.171875,y:.359375},{x:.171875,y:.359375},{x:.203125,y:.359375},{x:.203125,y:.359375},{x:.234375,y:.359375},{x:.234375,y:.359375},{x:.265625,y:.359375},{x:.265625,y:.359375},{x:.296875,y:.359375},{x:.296875,y:.359375},{x:.328125,y:.359375},{x:.328125,y:.359375},{x:.359375,y:.359375},{x:.359375,y:.359375},{x:.390625,y:.359375},{x:.390625,y:.359375},{x:.421875,y:.359375},{x:.421875,y:.359375},{x:.453125,y:.359375},{x:.453125,y:.359375},{x:.484375,y:.359375},{x:.484375,y:.359375},{x:.515625,y:.359375},{x:.515625,y:.359375},{x:.546875,y:.359375},{x:.546875,y:.359375},{x:.578125,y:.359375},{x:.578125,y:.359375},{x:.609375,y:.359375},{x:.609375,y:.359375},{x:.640625,y:.359375},{x:.640625,y:.359375},{x:.671875,y:.359375},{x:.671875,y:.359375},{x:.703125,y:.359375},{x:.703125,y:.359375},{x:.734375,y:.359375},{x:.734375,y:.359375},{x:.765625,y:.359375},{x:.765625,y:.359375},{x:.796875,y:.359375},{x:.796875,y:.359375},{x:.828125,y:.359375},{x:.828125,y:.359375},{x:.859375,y:.359375},{x:.859375,y:.359375},{x:.890625,y:.359375},{x:.890625,y:.359375},{x:.921875,y:.359375},{x:.921875,y:.359375},{x:.953125,y:.359375},{x:.953125,y:.359375},{x:.984375,y:.359375},{x:.984375,y:.359375},{x:.015625,y:.390625},{x:.015625,y:.390625},{x:.046875,y:.390625},{x:.046875,y:.390625},{x:.078125,y:.390625},{x:.078125,y:.390625},{x:.109375,y:.390625},{x:.109375,y:.390625},{x:.140625,y:.390625},{x:.140625,y:.390625},{x:.171875,y:.390625},{x:.171875,y:.390625},{x:.203125,y:.390625},{x:.203125,y:.390625},{x:.234375,y:.390625},{x:.234375,y:.390625},{x:.265625,y:.390625},{x:.265625,y:.390625},{x:.296875,y:.390625},{x:.296875,y:.390625},{x:.328125,y:.390625},{x:.328125,y:.390625},{x:.359375,y:.390625},{x:.359375,y:.390625},{x:.390625,y:.390625},{x:.390625,y:.390625},{x:.421875,y:.390625},{x:.421875,y:.390625},{x:.453125,y:.390625},{x:.453125,y:.390625},{x:.484375,y:.390625},{x:.484375,y:.390625},{x:.515625,y:.390625},{x:.515625,y:.390625},{x:.546875,y:.390625},{x:.546875,y:.390625},{x:.578125,y:.390625},{x:.578125,y:.390625},{x:.609375,y:.390625},{x:.609375,y:.390625},{x:.640625,y:.390625},{x:.640625,y:.390625},{x:.671875,y:.390625},{x:.671875,y:.390625},{x:.703125,y:.390625},{x:.703125,y:.390625},{x:.734375,y:.390625},{x:.734375,y:.390625},{x:.765625,y:.390625},{x:.765625,y:.390625},{x:.796875,y:.390625},{x:.796875,y:.390625},{x:.828125,y:.390625},{x:.828125,y:.390625},{x:.859375,y:.390625},{x:.859375,y:.390625},{x:.890625,y:.390625},{x:.890625,y:.390625},{x:.921875,y:.390625},{x:.921875,y:.390625},{x:.953125,y:.390625},{x:.953125,y:.390625},{x:.984375,y:.390625},{x:.984375,y:.390625},{x:.015625,y:.421875},{x:.015625,y:.421875},{x:.046875,y:.421875},{x:.046875,y:.421875},{x:.078125,y:.421875},{x:.078125,y:.421875},{x:.109375,y:.421875},{x:.109375,y:.421875},{x:.140625,y:.421875},{x:.140625,y:.421875},{x:.171875,y:.421875},{x:.171875,y:.421875},{x:.203125,y:.421875},{x:.203125,y:.421875},{x:.234375,y:.421875},{x:.234375,y:.421875},{x:.265625,y:.421875},{x:.265625,y:.421875},{x:.296875,y:.421875},{x:.296875,y:.421875},{x:.328125,y:.421875},{x:.328125,y:.421875},{x:.359375,y:.421875},{x:.359375,y:.421875},{x:.390625,y:.421875},{x:.390625,y:.421875},{x:.421875,y:.421875},{x:.421875,y:.421875},{x:.453125,y:.421875},{x:.453125,y:.421875},{x:.484375,y:.421875},{x:.484375,y:.421875},{x:.515625,y:.421875},{x:.515625,y:.421875},{x:.546875,y:.421875},{x:.546875,y:.421875},{x:.578125,y:.421875},{x:.578125,y:.421875},{x:.609375,y:.421875},{x:.609375,y:.421875},{x:.640625,y:.421875},{x:.640625,y:.421875},{x:.671875,y:.421875},{x:.671875,y:.421875},{x:.703125,y:.421875},{x:.703125,y:.421875},{x:.734375,y:.421875},{x:.734375,y:.421875},{x:.765625,y:.421875},{x:.765625,y:.421875},{x:.796875,y:.421875},{x:.796875,y:.421875},{x:.828125,y:.421875},{x:.828125,y:.421875},{x:.859375,y:.421875},{x:.859375,y:.421875},{x:.890625,y:.421875},{x:.890625,y:.421875},{x:.921875,y:.421875},{x:.921875,y:.421875},{x:.953125,y:.421875},{x:.953125,y:.421875},{x:.984375,y:.421875},{x:.984375,y:.421875},{x:.015625,y:.453125},{x:.015625,y:.453125},{x:.046875,y:.453125},{x:.046875,y:.453125},{x:.078125,y:.453125},{x:.078125,y:.453125},{x:.109375,y:.453125},{x:.109375,y:.453125},{x:.140625,y:.453125},{x:.140625,y:.453125},{x:.171875,y:.453125},{x:.171875,y:.453125},{x:.203125,y:.453125},{x:.203125,y:.453125},{x:.234375,y:.453125},{x:.234375,y:.453125},{x:.265625,y:.453125},{x:.265625,y:.453125},{x:.296875,y:.453125},{x:.296875,y:.453125},{x:.328125,y:.453125},{x:.328125,y:.453125},{x:.359375,y:.453125},{x:.359375,y:.453125},{x:.390625,y:.453125},{x:.390625,y:.453125},{x:.421875,y:.453125},{x:.421875,y:.453125},{x:.453125,y:.453125},{x:.453125,y:.453125},{x:.484375,y:.453125},{x:.484375,y:.453125},{x:.515625,y:.453125},{x:.515625,y:.453125},{x:.546875,y:.453125},{x:.546875,y:.453125},{x:.578125,y:.453125},{x:.578125,y:.453125},{x:.609375,y:.453125},{x:.609375,y:.453125},{x:.640625,y:.453125},{x:.640625,y:.453125},{x:.671875,y:.453125},{x:.671875,y:.453125},{x:.703125,y:.453125},{x:.703125,y:.453125},{x:.734375,y:.453125},{x:.734375,y:.453125},{x:.765625,y:.453125},{x:.765625,y:.453125},{x:.796875,y:.453125},{x:.796875,y:.453125},{x:.828125,y:.453125},{x:.828125,y:.453125},{x:.859375,y:.453125},{x:.859375,y:.453125},{x:.890625,y:.453125},{x:.890625,y:.453125},{x:.921875,y:.453125},{x:.921875,y:.453125},{x:.953125,y:.453125},{x:.953125,y:.453125},{x:.984375,y:.453125},{x:.984375,y:.453125},{x:.015625,y:.484375},{x:.015625,y:.484375},{x:.046875,y:.484375},{x:.046875,y:.484375},{x:.078125,y:.484375},{x:.078125,y:.484375},{x:.109375,y:.484375},{x:.109375,y:.484375},{x:.140625,y:.484375},{x:.140625,y:.484375},{x:.171875,y:.484375},{x:.171875,y:.484375},{x:.203125,y:.484375},{x:.203125,y:.484375},{x:.234375,y:.484375},{x:.234375,y:.484375},{x:.265625,y:.484375},{x:.265625,y:.484375},{x:.296875,y:.484375},{x:.296875,y:.484375},{x:.328125,y:.484375},{x:.328125,y:.484375},{x:.359375,y:.484375},{x:.359375,y:.484375},{x:.390625,y:.484375},{x:.390625,y:.484375},{x:.421875,y:.484375},{x:.421875,y:.484375},{x:.453125,y:.484375},{x:.453125,y:.484375},{x:.484375,y:.484375},{x:.484375,y:.484375},{x:.515625,y:.484375},{x:.515625,y:.484375},{x:.546875,y:.484375},{x:.546875,y:.484375},{x:.578125,y:.484375},{x:.578125,y:.484375},{x:.609375,y:.484375},{x:.609375,y:.484375},{x:.640625,y:.484375},{x:.640625,y:.484375},{x:.671875,y:.484375},{x:.671875,y:.484375},{x:.703125,y:.484375},{x:.703125,y:.484375},{x:.734375,y:.484375},{x:.734375,y:.484375},{x:.765625,y:.484375},{x:.765625,y:.484375},{x:.796875,y:.484375},{x:.796875,y:.484375},{x:.828125,y:.484375},{x:.828125,y:.484375},{x:.859375,y:.484375},{x:.859375,y:.484375},{x:.890625,y:.484375},{x:.890625,y:.484375},{x:.921875,y:.484375},{x:.921875,y:.484375},{x:.953125,y:.484375},{x:.953125,y:.484375},{x:.984375,y:.484375},{x:.984375,y:.484375},{x:.015625,y:.515625},{x:.015625,y:.515625},{x:.046875,y:.515625},{x:.046875,y:.515625},{x:.078125,y:.515625},{x:.078125,y:.515625},{x:.109375,y:.515625},{x:.109375,y:.515625},{x:.140625,y:.515625},{x:.140625,y:.515625},{x:.171875,y:.515625},{x:.171875,y:.515625},{x:.203125,y:.515625},{x:.203125,y:.515625},{x:.234375,y:.515625},{x:.234375,y:.515625},{x:.265625,y:.515625},{x:.265625,y:.515625},{x:.296875,y:.515625},{x:.296875,y:.515625},{x:.328125,y:.515625},{x:.328125,y:.515625},{x:.359375,y:.515625},{x:.359375,y:.515625},{x:.390625,y:.515625},{x:.390625,y:.515625},{x:.421875,y:.515625},{x:.421875,y:.515625},{x:.453125,y:.515625},{x:.453125,y:.515625},{x:.484375,y:.515625},{x:.484375,y:.515625},{x:.515625,y:.515625},{x:.515625,y:.515625},{x:.546875,y:.515625},{x:.546875,y:.515625},{x:.578125,y:.515625},{x:.578125,y:.515625},{x:.609375,y:.515625},{x:.609375,y:.515625},{x:.640625,y:.515625},{x:.640625,y:.515625},{x:.671875,y:.515625},{x:.671875,y:.515625},{x:.703125,y:.515625},{x:.703125,y:.515625},{x:.734375,y:.515625},{x:.734375,y:.515625},{x:.765625,y:.515625},{x:.765625,y:.515625},{x:.796875,y:.515625},{x:.796875,y:.515625},{x:.828125,y:.515625},{x:.828125,y:.515625},{x:.859375,y:.515625},{x:.859375,y:.515625},{x:.890625,y:.515625},{x:.890625,y:.515625},{x:.921875,y:.515625},{x:.921875,y:.515625},{x:.953125,y:.515625},{x:.953125,y:.515625},{x:.984375,y:.515625},{x:.984375,y:.515625},{x:.015625,y:.546875},{x:.015625,y:.546875},{x:.046875,y:.546875},{x:.046875,y:.546875},{x:.078125,y:.546875},{x:.078125,y:.546875},{x:.109375,y:.546875},{x:.109375,y:.546875},{x:.140625,y:.546875},{x:.140625,y:.546875},{x:.171875,y:.546875},{x:.171875,y:.546875},{x:.203125,y:.546875},{x:.203125,y:.546875},{x:.234375,y:.546875},{x:.234375,y:.546875},{x:.265625,y:.546875},{x:.265625,y:.546875},{x:.296875,y:.546875},{x:.296875,y:.546875},{x:.328125,y:.546875},{x:.328125,y:.546875},{x:.359375,y:.546875},{x:.359375,y:.546875},{x:.390625,y:.546875},{x:.390625,y:.546875},{x:.421875,y:.546875},{x:.421875,y:.546875},{x:.453125,y:.546875},{x:.453125,y:.546875},{x:.484375,y:.546875},{x:.484375,y:.546875},{x:.515625,y:.546875},{x:.515625,y:.546875},{x:.546875,y:.546875},{x:.546875,y:.546875},{x:.578125,y:.546875},{x:.578125,y:.546875},{x:.609375,y:.546875},{x:.609375,y:.546875},{x:.640625,y:.546875},{x:.640625,y:.546875},{x:.671875,y:.546875},{x:.671875,y:.546875},{x:.703125,y:.546875},{x:.703125,y:.546875},{x:.734375,y:.546875},{x:.734375,y:.546875},{x:.765625,y:.546875},{x:.765625,y:.546875},{x:.796875,y:.546875},{x:.796875,y:.546875},{x:.828125,y:.546875},{x:.828125,y:.546875},{x:.859375,y:.546875},{x:.859375,y:.546875},{x:.890625,y:.546875},{x:.890625,y:.546875},{x:.921875,y:.546875},{x:.921875,y:.546875},{x:.953125,y:.546875},{x:.953125,y:.546875},{x:.984375,y:.546875},{x:.984375,y:.546875},{x:.015625,y:.578125},{x:.015625,y:.578125},{x:.046875,y:.578125},{x:.046875,y:.578125},{x:.078125,y:.578125},{x:.078125,y:.578125},{x:.109375,y:.578125},{x:.109375,y:.578125},{x:.140625,y:.578125},{x:.140625,y:.578125},{x:.171875,y:.578125},{x:.171875,y:.578125},{x:.203125,y:.578125},{x:.203125,y:.578125},{x:.234375,y:.578125},{x:.234375,y:.578125},{x:.265625,y:.578125},{x:.265625,y:.578125},{x:.296875,y:.578125},{x:.296875,y:.578125},{x:.328125,y:.578125},{x:.328125,y:.578125},{x:.359375,y:.578125},{x:.359375,y:.578125},{x:.390625,y:.578125},{x:.390625,y:.578125},{x:.421875,y:.578125},{x:.421875,y:.578125},{x:.453125,y:.578125},{x:.453125,y:.578125},{x:.484375,y:.578125},{x:.484375,y:.578125},{x:.515625,y:.578125},{x:.515625,y:.578125},{x:.546875,y:.578125},{x:.546875,y:.578125},{x:.578125,y:.578125},{x:.578125,y:.578125},{x:.609375,y:.578125},{x:.609375,y:.578125},{x:.640625,y:.578125},{x:.640625,y:.578125},{x:.671875,y:.578125},{x:.671875,y:.578125},{x:.703125,y:.578125},{x:.703125,y:.578125},{x:.734375,y:.578125},{x:.734375,y:.578125},{x:.765625,y:.578125},{x:.765625,y:.578125},{x:.796875,y:.578125},{x:.796875,y:.578125},{x:.828125,y:.578125},{x:.828125,y:.578125},{x:.859375,y:.578125},{x:.859375,y:.578125},{x:.890625,y:.578125},{x:.890625,y:.578125},{x:.921875,y:.578125},{x:.921875,y:.578125},{x:.953125,y:.578125},{x:.953125,y:.578125},{x:.984375,y:.578125},{x:.984375,y:.578125},{x:.015625,y:.609375},{x:.015625,y:.609375},{x:.046875,y:.609375},{x:.046875,y:.609375},{x:.078125,y:.609375},{x:.078125,y:.609375},{x:.109375,y:.609375},{x:.109375,y:.609375},{x:.140625,y:.609375},{x:.140625,y:.609375},{x:.171875,y:.609375},{x:.171875,y:.609375},{x:.203125,y:.609375},{x:.203125,y:.609375},{x:.234375,y:.609375},{x:.234375,y:.609375},{x:.265625,y:.609375},{x:.265625,y:.609375},{x:.296875,y:.609375},{x:.296875,y:.609375},{x:.328125,y:.609375},{x:.328125,y:.609375},{x:.359375,y:.609375},{x:.359375,y:.609375},{x:.390625,y:.609375},{x:.390625,y:.609375},{x:.421875,y:.609375},{x:.421875,y:.609375},{x:.453125,y:.609375},{x:.453125,y:.609375},{x:.484375,y:.609375},{x:.484375,y:.609375},{x:.515625,y:.609375},{x:.515625,y:.609375},{x:.546875,y:.609375},{x:.546875,y:.609375},{x:.578125,y:.609375},{x:.578125,y:.609375},{x:.609375,y:.609375},{x:.609375,y:.609375},{x:.640625,y:.609375},{x:.640625,y:.609375},{x:.671875,y:.609375},{x:.671875,y:.609375},{x:.703125,y:.609375},{x:.703125,y:.609375},{x:.734375,y:.609375},{x:.734375,y:.609375},{x:.765625,y:.609375},{x:.765625,y:.609375},{x:.796875,y:.609375},{x:.796875,y:.609375},{x:.828125,y:.609375},{x:.828125,y:.609375},{x:.859375,y:.609375},{x:.859375,y:.609375},{x:.890625,y:.609375},{x:.890625,y:.609375},{x:.921875,y:.609375},{x:.921875,y:.609375},{x:.953125,y:.609375},{x:.953125,y:.609375},{x:.984375,y:.609375},{x:.984375,y:.609375},{x:.015625,y:.640625},{x:.015625,y:.640625},{x:.046875,y:.640625},{x:.046875,y:.640625},{x:.078125,y:.640625},{x:.078125,y:.640625},{x:.109375,y:.640625},{x:.109375,y:.640625},{x:.140625,y:.640625},{x:.140625,y:.640625},{x:.171875,y:.640625},{x:.171875,y:.640625},{x:.203125,y:.640625},{x:.203125,y:.640625},{x:.234375,y:.640625},{x:.234375,y:.640625},{x:.265625,y:.640625},{x:.265625,y:.640625},{x:.296875,y:.640625},{x:.296875,y:.640625},{x:.328125,y:.640625},{x:.328125,y:.640625},{x:.359375,y:.640625},{x:.359375,y:.640625},{x:.390625,y:.640625},{x:.390625,y:.640625},{x:.421875,y:.640625},{x:.421875,y:.640625},{x:.453125,y:.640625},{x:.453125,y:.640625},{x:.484375,y:.640625},{x:.484375,y:.640625},{x:.515625,y:.640625},{x:.515625,y:.640625},{x:.546875,y:.640625},{x:.546875,y:.640625},{x:.578125,y:.640625},{x:.578125,y:.640625},{x:.609375,y:.640625},{x:.609375,y:.640625},{x:.640625,y:.640625},{x:.640625,y:.640625},{x:.671875,y:.640625},{x:.671875,y:.640625},{x:.703125,y:.640625},{x:.703125,y:.640625},{x:.734375,y:.640625},{x:.734375,y:.640625},{x:.765625,y:.640625},{x:.765625,y:.640625},{x:.796875,y:.640625},{x:.796875,y:.640625},{x:.828125,y:.640625},{x:.828125,y:.640625},{x:.859375,y:.640625},{x:.859375,y:.640625},{x:.890625,y:.640625},{x:.890625,y:.640625},{x:.921875,y:.640625},{x:.921875,y:.640625},{x:.953125,y:.640625},{x:.953125,y:.640625},{x:.984375,y:.640625},{x:.984375,y:.640625},{x:.015625,y:.671875},{x:.015625,y:.671875},{x:.046875,y:.671875},{x:.046875,y:.671875},{x:.078125,y:.671875},{x:.078125,y:.671875},{x:.109375,y:.671875},{x:.109375,y:.671875},{x:.140625,y:.671875},{x:.140625,y:.671875},{x:.171875,y:.671875},{x:.171875,y:.671875},{x:.203125,y:.671875},{x:.203125,y:.671875},{x:.234375,y:.671875},{x:.234375,y:.671875},{x:.265625,y:.671875},{x:.265625,y:.671875},{x:.296875,y:.671875},{x:.296875,y:.671875},{x:.328125,y:.671875},{x:.328125,y:.671875},{x:.359375,y:.671875},{x:.359375,y:.671875},{x:.390625,y:.671875},{x:.390625,y:.671875},{x:.421875,y:.671875},{x:.421875,y:.671875},{x:.453125,y:.671875},{x:.453125,y:.671875},{x:.484375,y:.671875},{x:.484375,y:.671875},{x:.515625,y:.671875},{x:.515625,y:.671875},{x:.546875,y:.671875},{x:.546875,y:.671875},{x:.578125,y:.671875},{x:.578125,y:.671875},{x:.609375,y:.671875},{x:.609375,y:.671875},{x:.640625,y:.671875},{x:.640625,y:.671875},{x:.671875,y:.671875},{x:.671875,y:.671875},{x:.703125,y:.671875},{x:.703125,y:.671875},{x:.734375,y:.671875},{x:.734375,y:.671875},{x:.765625,y:.671875},{x:.765625,y:.671875},{x:.796875,y:.671875},{x:.796875,y:.671875},{x:.828125,y:.671875},{x:.828125,y:.671875},{x:.859375,y:.671875},{x:.859375,y:.671875},{x:.890625,y:.671875},{x:.890625,y:.671875},{x:.921875,y:.671875},{x:.921875,y:.671875},{x:.953125,y:.671875},{x:.953125,y:.671875},{x:.984375,y:.671875},{x:.984375,y:.671875},{x:.015625,y:.703125},{x:.015625,y:.703125},{x:.046875,y:.703125},{x:.046875,y:.703125},{x:.078125,y:.703125},{x:.078125,y:.703125},{x:.109375,y:.703125},{x:.109375,y:.703125},{x:.140625,y:.703125},{x:.140625,y:.703125},{x:.171875,y:.703125},{x:.171875,y:.703125},{x:.203125,y:.703125},{x:.203125,y:.703125},{x:.234375,y:.703125},{x:.234375,y:.703125},{x:.265625,y:.703125},{x:.265625,y:.703125},{x:.296875,y:.703125},{x:.296875,y:.703125},{x:.328125,y:.703125},{x:.328125,y:.703125},{x:.359375,y:.703125},{x:.359375,y:.703125},{x:.390625,y:.703125},{x:.390625,y:.703125},{x:.421875,y:.703125},{x:.421875,y:.703125},{x:.453125,y:.703125},{x:.453125,y:.703125},{x:.484375,y:.703125},{x:.484375,y:.703125},{x:.515625,y:.703125},{x:.515625,y:.703125},{x:.546875,y:.703125},{x:.546875,y:.703125},{x:.578125,y:.703125},{x:.578125,y:.703125},{x:.609375,y:.703125},{x:.609375,y:.703125},{x:.640625,y:.703125},{x:.640625,y:.703125},{x:.671875,y:.703125},{x:.671875,y:.703125},{x:.703125,y:.703125},{x:.703125,y:.703125},{x:.734375,y:.703125},{x:.734375,y:.703125},{x:.765625,y:.703125},{x:.765625,y:.703125},{x:.796875,y:.703125},{x:.796875,y:.703125},{x:.828125,y:.703125},{x:.828125,y:.703125},{x:.859375,y:.703125},{x:.859375,y:.703125},{x:.890625,y:.703125},{x:.890625,y:.703125},{x:.921875,y:.703125},{x:.921875,y:.703125},{x:.953125,y:.703125},{x:.953125,y:.703125},{x:.984375,y:.703125},{x:.984375,y:.703125},{x:.015625,y:.734375},{x:.015625,y:.734375},{x:.046875,y:.734375},{x:.046875,y:.734375},{x:.078125,y:.734375},{x:.078125,y:.734375},{x:.109375,y:.734375},{x:.109375,y:.734375},{x:.140625,y:.734375},{x:.140625,y:.734375},{x:.171875,y:.734375},{x:.171875,y:.734375},{x:.203125,y:.734375},{x:.203125,y:.734375},{x:.234375,y:.734375},{x:.234375,y:.734375},{x:.265625,y:.734375},{x:.265625,y:.734375},{x:.296875,y:.734375},{x:.296875,y:.734375},{x:.328125,y:.734375},{x:.328125,y:.734375},{x:.359375,y:.734375},{x:.359375,y:.734375},{x:.390625,y:.734375},{x:.390625,y:.734375},{x:.421875,y:.734375},{x:.421875,y:.734375},{x:.453125,y:.734375},{x:.453125,y:.734375},{x:.484375,y:.734375},{x:.484375,y:.734375},{x:.515625,y:.734375},{x:.515625,y:.734375},{x:.546875,y:.734375},{x:.546875,y:.734375},{x:.578125,y:.734375},{x:.578125,y:.734375},{x:.609375,y:.734375},{x:.609375,y:.734375},{x:.640625,y:.734375},{x:.640625,y:.734375},{x:.671875,y:.734375},{x:.671875,y:.734375},{x:.703125,y:.734375},{x:.703125,y:.734375},{x:.734375,y:.734375},{x:.734375,y:.734375},{x:.765625,y:.734375},{x:.765625,y:.734375},{x:.796875,y:.734375},{x:.796875,y:.734375},{x:.828125,y:.734375},{x:.828125,y:.734375},{x:.859375,y:.734375},{x:.859375,y:.734375},{x:.890625,y:.734375},{x:.890625,y:.734375},{x:.921875,y:.734375},{x:.921875,y:.734375},{x:.953125,y:.734375},{x:.953125,y:.734375},{x:.984375,y:.734375},{x:.984375,y:.734375},{x:.015625,y:.765625},{x:.015625,y:.765625},{x:.046875,y:.765625},{x:.046875,y:.765625},{x:.078125,y:.765625},{x:.078125,y:.765625},{x:.109375,y:.765625},{x:.109375,y:.765625},{x:.140625,y:.765625},{x:.140625,y:.765625},{x:.171875,y:.765625},{x:.171875,y:.765625},{x:.203125,y:.765625},{x:.203125,y:.765625},{x:.234375,y:.765625},{x:.234375,y:.765625},{x:.265625,y:.765625},{x:.265625,y:.765625},{x:.296875,y:.765625},{x:.296875,y:.765625},{x:.328125,y:.765625},{x:.328125,y:.765625},{x:.359375,y:.765625},{x:.359375,y:.765625},{x:.390625,y:.765625},{x:.390625,y:.765625},{x:.421875,y:.765625},{x:.421875,y:.765625},{x:.453125,y:.765625},{x:.453125,y:.765625},{x:.484375,y:.765625},{x:.484375,y:.765625},{x:.515625,y:.765625},{x:.515625,y:.765625},{x:.546875,y:.765625},{x:.546875,y:.765625},{x:.578125,y:.765625},{x:.578125,y:.765625},{x:.609375,y:.765625},{x:.609375,y:.765625},{x:.640625,y:.765625},{x:.640625,y:.765625},{x:.671875,y:.765625},{x:.671875,y:.765625},{x:.703125,y:.765625},{x:.703125,y:.765625},{x:.734375,y:.765625},{x:.734375,y:.765625},{x:.765625,y:.765625},{x:.765625,y:.765625},{x:.796875,y:.765625},{x:.796875,y:.765625},{x:.828125,y:.765625},{x:.828125,y:.765625},{x:.859375,y:.765625},{x:.859375,y:.765625},{x:.890625,y:.765625},{x:.890625,y:.765625},{x:.921875,y:.765625},{x:.921875,y:.765625},{x:.953125,y:.765625},{x:.953125,y:.765625},{x:.984375,y:.765625},{x:.984375,y:.765625},{x:.015625,y:.796875},{x:.015625,y:.796875},{x:.046875,y:.796875},{x:.046875,y:.796875},{x:.078125,y:.796875},{x:.078125,y:.796875},{x:.109375,y:.796875},{x:.109375,y:.796875},{x:.140625,y:.796875},{x:.140625,y:.796875},{x:.171875,y:.796875},{x:.171875,y:.796875},{x:.203125,y:.796875},{x:.203125,y:.796875},{x:.234375,y:.796875},{x:.234375,y:.796875},{x:.265625,y:.796875},{x:.265625,y:.796875},{x:.296875,y:.796875},{x:.296875,y:.796875},{x:.328125,y:.796875},{x:.328125,y:.796875},{x:.359375,y:.796875},{x:.359375,y:.796875},{x:.390625,y:.796875},{x:.390625,y:.796875},{x:.421875,y:.796875},{x:.421875,y:.796875},{x:.453125,y:.796875},{x:.453125,y:.796875},{x:.484375,y:.796875},{x:.484375,y:.796875},{x:.515625,y:.796875},{x:.515625,y:.796875},{x:.546875,y:.796875},{x:.546875,y:.796875},{x:.578125,y:.796875},{x:.578125,y:.796875},{x:.609375,y:.796875},{x:.609375,y:.796875},{x:.640625,y:.796875},{x:.640625,y:.796875},{x:.671875,y:.796875},{x:.671875,y:.796875},{x:.703125,y:.796875},{x:.703125,y:.796875},{x:.734375,y:.796875},{x:.734375,y:.796875},{x:.765625,y:.796875},{x:.765625,y:.796875},{x:.796875,y:.796875},{x:.796875,y:.796875},{x:.828125,y:.796875},{x:.828125,y:.796875},{x:.859375,y:.796875},{x:.859375,y:.796875},{x:.890625,y:.796875},{x:.890625,y:.796875},{x:.921875,y:.796875},{x:.921875,y:.796875},{x:.953125,y:.796875},{x:.953125,y:.796875},{x:.984375,y:.796875},{x:.984375,y:.796875},{x:.015625,y:.828125},{x:.015625,y:.828125},{x:.046875,y:.828125},{x:.046875,y:.828125},{x:.078125,y:.828125},{x:.078125,y:.828125},{x:.109375,y:.828125},{x:.109375,y:.828125},{x:.140625,y:.828125},{x:.140625,y:.828125},{x:.171875,y:.828125},{x:.171875,y:.828125},{x:.203125,y:.828125},{x:.203125,y:.828125},{x:.234375,y:.828125},{x:.234375,y:.828125},{x:.265625,y:.828125},{x:.265625,y:.828125},{x:.296875,y:.828125},{x:.296875,y:.828125},{x:.328125,y:.828125},{x:.328125,y:.828125},{x:.359375,y:.828125},{x:.359375,y:.828125},{x:.390625,y:.828125},{x:.390625,y:.828125},{x:.421875,y:.828125},{x:.421875,y:.828125},{x:.453125,y:.828125},{x:.453125,y:.828125},{x:.484375,y:.828125},{x:.484375,y:.828125},{x:.515625,y:.828125},{x:.515625,y:.828125},{x:.546875,y:.828125},{x:.546875,y:.828125},{x:.578125,y:.828125},{x:.578125,y:.828125},{x:.609375,y:.828125},{x:.609375,y:.828125},{x:.640625,y:.828125},{x:.640625,y:.828125},{x:.671875,y:.828125},{x:.671875,y:.828125},{x:.703125,y:.828125},{x:.703125,y:.828125},{x:.734375,y:.828125},{x:.734375,y:.828125},{x:.765625,y:.828125},{x:.765625,y:.828125},{x:.796875,y:.828125},{x:.796875,y:.828125},{x:.828125,y:.828125},{x:.828125,y:.828125},{x:.859375,y:.828125},{x:.859375,y:.828125},{x:.890625,y:.828125},{x:.890625,y:.828125},{x:.921875,y:.828125},{x:.921875,y:.828125},{x:.953125,y:.828125},{x:.953125,y:.828125},{x:.984375,y:.828125},{x:.984375,y:.828125},{x:.015625,y:.859375},{x:.015625,y:.859375},{x:.046875,y:.859375},{x:.046875,y:.859375},{x:.078125,y:.859375},{x:.078125,y:.859375},{x:.109375,y:.859375},{x:.109375,y:.859375},{x:.140625,y:.859375},{x:.140625,y:.859375},{x:.171875,y:.859375},{x:.171875,y:.859375},{x:.203125,y:.859375},{x:.203125,y:.859375},{x:.234375,y:.859375},{x:.234375,y:.859375},{x:.265625,y:.859375},{x:.265625,y:.859375},{x:.296875,y:.859375},{x:.296875,y:.859375},{x:.328125,y:.859375},{x:.328125,y:.859375},{x:.359375,y:.859375},{x:.359375,y:.859375},{x:.390625,y:.859375},{x:.390625,y:.859375},{x:.421875,y:.859375},{x:.421875,y:.859375},{x:.453125,y:.859375},{x:.453125,y:.859375},{x:.484375,y:.859375},{x:.484375,y:.859375},{x:.515625,y:.859375},{x:.515625,y:.859375},{x:.546875,y:.859375},{x:.546875,y:.859375},{x:.578125,y:.859375},{x:.578125,y:.859375},{x:.609375,y:.859375},{x:.609375,y:.859375},{x:.640625,y:.859375},{x:.640625,y:.859375},{x:.671875,y:.859375},{x:.671875,y:.859375},{x:.703125,y:.859375},{x:.703125,y:.859375},{x:.734375,y:.859375},{x:.734375,y:.859375},{x:.765625,y:.859375},{x:.765625,y:.859375},{x:.796875,y:.859375},{x:.796875,y:.859375},{x:.828125,y:.859375},{x:.828125,y:.859375},{x:.859375,y:.859375},{x:.859375,y:.859375},{x:.890625,y:.859375},{x:.890625,y:.859375},{x:.921875,y:.859375},{x:.921875,y:.859375},{x:.953125,y:.859375},{x:.953125,y:.859375},{x:.984375,y:.859375},{x:.984375,y:.859375},{x:.015625,y:.890625},{x:.015625,y:.890625},{x:.046875,y:.890625},{x:.046875,y:.890625},{x:.078125,y:.890625},{x:.078125,y:.890625},{x:.109375,y:.890625},{x:.109375,y:.890625},{x:.140625,y:.890625},{x:.140625,y:.890625},{x:.171875,y:.890625},{x:.171875,y:.890625},{x:.203125,y:.890625},{x:.203125,y:.890625},{x:.234375,y:.890625},{x:.234375,y:.890625},{x:.265625,y:.890625},{x:.265625,y:.890625},{x:.296875,y:.890625},{x:.296875,y:.890625},{x:.328125,y:.890625},{x:.328125,y:.890625},{x:.359375,y:.890625},{x:.359375,y:.890625},{x:.390625,y:.890625},{x:.390625,y:.890625},{x:.421875,y:.890625},{x:.421875,y:.890625},{x:.453125,y:.890625},{x:.453125,y:.890625},{x:.484375,y:.890625},{x:.484375,y:.890625},{x:.515625,y:.890625},{x:.515625,y:.890625},{x:.546875,y:.890625},{x:.546875,y:.890625},{x:.578125,y:.890625},{x:.578125,y:.890625},{x:.609375,y:.890625},{x:.609375,y:.890625},{x:.640625,y:.890625},{x:.640625,y:.890625},{x:.671875,y:.890625},{x:.671875,y:.890625},{x:.703125,y:.890625},{x:.703125,y:.890625},{x:.734375,y:.890625},{x:.734375,y:.890625},{x:.765625,y:.890625},{x:.765625,y:.890625},{x:.796875,y:.890625},{x:.796875,y:.890625},{x:.828125,y:.890625},{x:.828125,y:.890625},{x:.859375,y:.890625},{x:.859375,y:.890625},{x:.890625,y:.890625},{x:.890625,y:.890625},{x:.921875,y:.890625},{x:.921875,y:.890625},{x:.953125,y:.890625},{x:.953125,y:.890625},{x:.984375,y:.890625},{x:.984375,y:.890625},{x:.015625,y:.921875},{x:.015625,y:.921875},{x:.046875,y:.921875},{x:.046875,y:.921875},{x:.078125,y:.921875},{x:.078125,y:.921875},{x:.109375,y:.921875},{x:.109375,y:.921875},{x:.140625,y:.921875},{x:.140625,y:.921875},{x:.171875,y:.921875},{x:.171875,y:.921875},{x:.203125,y:.921875},{x:.203125,y:.921875},{x:.234375,y:.921875},{x:.234375,y:.921875},{x:.265625,y:.921875},{x:.265625,y:.921875},{x:.296875,y:.921875},{x:.296875,y:.921875},{x:.328125,y:.921875},{x:.328125,y:.921875},{x:.359375,y:.921875},{x:.359375,y:.921875},{x:.390625,y:.921875},{x:.390625,y:.921875},{x:.421875,y:.921875},{x:.421875,y:.921875},{x:.453125,y:.921875},{x:.453125,y:.921875},{x:.484375,y:.921875},{x:.484375,y:.921875},{x:.515625,y:.921875},{x:.515625,y:.921875},{x:.546875,y:.921875},{x:.546875,y:.921875},{x:.578125,y:.921875},{x:.578125,y:.921875},{x:.609375,y:.921875},{x:.609375,y:.921875},{x:.640625,y:.921875},{x:.640625,y:.921875},{x:.671875,y:.921875},{x:.671875,y:.921875},{x:.703125,y:.921875},{x:.703125,y:.921875},{x:.734375,y:.921875},{x:.734375,y:.921875},{x:.765625,y:.921875},{x:.765625,y:.921875},{x:.796875,y:.921875},{x:.796875,y:.921875},{x:.828125,y:.921875},{x:.828125,y:.921875},{x:.859375,y:.921875},{x:.859375,y:.921875},{x:.890625,y:.921875},{x:.890625,y:.921875},{x:.921875,y:.921875},{x:.921875,y:.921875},{x:.953125,y:.921875},{x:.953125,y:.921875},{x:.984375,y:.921875},{x:.984375,y:.921875},{x:.015625,y:.953125},{x:.015625,y:.953125},{x:.046875,y:.953125},{x:.046875,y:.953125},{x:.078125,y:.953125},{x:.078125,y:.953125},{x:.109375,y:.953125},{x:.109375,y:.953125},{x:.140625,y:.953125},{x:.140625,y:.953125},{x:.171875,y:.953125},{x:.171875,y:.953125},{x:.203125,y:.953125},{x:.203125,y:.953125},{x:.234375,y:.953125},{x:.234375,y:.953125},{x:.265625,y:.953125},{x:.265625,y:.953125},{x:.296875,y:.953125},{x:.296875,y:.953125},{x:.328125,y:.953125},{x:.328125,y:.953125},{x:.359375,y:.953125},{x:.359375,y:.953125},{x:.390625,y:.953125},{x:.390625,y:.953125},{x:.421875,y:.953125},{x:.421875,y:.953125},{x:.453125,y:.953125},{x:.453125,y:.953125},{x:.484375,y:.953125},{x:.484375,y:.953125},{x:.515625,y:.953125},{x:.515625,y:.953125},{x:.546875,y:.953125},{x:.546875,y:.953125},{x:.578125,y:.953125},{x:.578125,y:.953125},{x:.609375,y:.953125},{x:.609375,y:.953125},{x:.640625,y:.953125},{x:.640625,y:.953125},{x:.671875,y:.953125},{x:.671875,y:.953125},{x:.703125,y:.953125},{x:.703125,y:.953125},{x:.734375,y:.953125},{x:.734375,y:.953125},{x:.765625,y:.953125},{x:.765625,y:.953125},{x:.796875,y:.953125},{x:.796875,y:.953125},{x:.828125,y:.953125},{x:.828125,y:.953125},{x:.859375,y:.953125},{x:.859375,y:.953125},{x:.890625,y:.953125},{x:.890625,y:.953125},{x:.921875,y:.953125},{x:.921875,y:.953125},{x:.953125,y:.953125},{x:.953125,y:.953125},{x:.984375,y:.953125},{x:.984375,y:.953125},{x:.015625,y:.984375},{x:.015625,y:.984375},{x:.046875,y:.984375},{x:.046875,y:.984375},{x:.078125,y:.984375},{x:.078125,y:.984375},{x:.109375,y:.984375},{x:.109375,y:.984375},{x:.140625,y:.984375},{x:.140625,y:.984375},{x:.171875,y:.984375},{x:.171875,y:.984375},{x:.203125,y:.984375},{x:.203125,y:.984375},{x:.234375,y:.984375},{x:.234375,y:.984375},{x:.265625,y:.984375},{x:.265625,y:.984375},{x:.296875,y:.984375},{x:.296875,y:.984375},{x:.328125,y:.984375},{x:.328125,y:.984375},{x:.359375,y:.984375},{x:.359375,y:.984375},{x:.390625,y:.984375},{x:.390625,y:.984375},{x:.421875,y:.984375},{x:.421875,y:.984375},{x:.453125,y:.984375},{x:.453125,y:.984375},{x:.484375,y:.984375},{x:.484375,y:.984375},{x:.515625,y:.984375},{x:.515625,y:.984375},{x:.546875,y:.984375},{x:.546875,y:.984375},{x:.578125,y:.984375},{x:.578125,y:.984375},{x:.609375,y:.984375},{x:.609375,y:.984375},{x:.640625,y:.984375},{x:.640625,y:.984375},{x:.671875,y:.984375},{x:.671875,y:.984375},{x:.703125,y:.984375},{x:.703125,y:.984375},{x:.734375,y:.984375},{x:.734375,y:.984375},{x:.765625,y:.984375},{x:.765625,y:.984375},{x:.796875,y:.984375},{x:.796875,y:.984375},{x:.828125,y:.984375},{x:.828125,y:.984375},{x:.859375,y:.984375},{x:.859375,y:.984375},{x:.890625,y:.984375},{x:.890625,y:.984375},{x:.921875,y:.984375},{x:.921875,y:.984375},{x:.953125,y:.984375},{x:.953125,y:.984375},{x:.984375,y:.984375},{x:.984375,y:.984375},{x:.03125,y:.03125},{x:.03125,y:.03125},{x:.09375,y:.03125},{x:.09375,y:.03125},{x:.15625,y:.03125},{x:.15625,y:.03125},{x:.21875,y:.03125},{x:.21875,y:.03125},{x:.28125,y:.03125},{x:.28125,y:.03125},{x:.34375,y:.03125},{x:.34375,y:.03125},{x:.40625,y:.03125},{x:.40625,y:.03125},{x:.46875,y:.03125},{x:.46875,y:.03125},{x:.53125,y:.03125},{x:.53125,y:.03125},{x:.59375,y:.03125},{x:.59375,y:.03125},{x:.65625,y:.03125},{x:.65625,y:.03125},{x:.71875,y:.03125},{x:.71875,y:.03125},{x:.78125,y:.03125},{x:.78125,y:.03125},{x:.84375,y:.03125},{x:.84375,y:.03125},{x:.90625,y:.03125},{x:.90625,y:.03125},{x:.96875,y:.03125},{x:.96875,y:.03125},{x:.03125,y:.09375},{x:.03125,y:.09375},{x:.09375,y:.09375},{x:.09375,y:.09375},{x:.15625,y:.09375},{x:.15625,y:.09375},{x:.21875,y:.09375},{x:.21875,y:.09375},{x:.28125,y:.09375},{x:.28125,y:.09375},{x:.34375,y:.09375},{x:.34375,y:.09375},{x:.40625,y:.09375},{x:.40625,y:.09375},{x:.46875,y:.09375},{x:.46875,y:.09375},{x:.53125,y:.09375},{x:.53125,y:.09375},{x:.59375,y:.09375},{x:.59375,y:.09375},{x:.65625,y:.09375},{x:.65625,y:.09375},{x:.71875,y:.09375},{x:.71875,y:.09375},{x:.78125,y:.09375},{x:.78125,y:.09375},{x:.84375,y:.09375},{x:.84375,y:.09375},{x:.90625,y:.09375},{x:.90625,y:.09375},{x:.96875,y:.09375},{x:.96875,y:.09375},{x:.03125,y:.15625},{x:.03125,y:.15625},{x:.09375,y:.15625},{x:.09375,y:.15625},{x:.15625,y:.15625},{x:.15625,y:.15625},{x:.21875,y:.15625},{x:.21875,y:.15625},{x:.28125,y:.15625},{x:.28125,y:.15625},{x:.34375,y:.15625},{x:.34375,y:.15625},{x:.40625,y:.15625},{x:.40625,y:.15625},{x:.46875,y:.15625},{x:.46875,y:.15625},{x:.53125,y:.15625},{x:.53125,y:.15625},{x:.59375,y:.15625},{x:.59375,y:.15625},{x:.65625,y:.15625},{x:.65625,y:.15625},{x:.71875,y:.15625},{x:.71875,y:.15625},{x:.78125,y:.15625},{x:.78125,y:.15625},{x:.84375,y:.15625},{x:.84375,y:.15625},{x:.90625,y:.15625},{x:.90625,y:.15625},{x:.96875,y:.15625},{x:.96875,y:.15625},{x:.03125,y:.21875},{x:.03125,y:.21875},{x:.09375,y:.21875},{x:.09375,y:.21875},{x:.15625,y:.21875},{x:.15625,y:.21875},{x:.21875,y:.21875},{x:.21875,y:.21875},{x:.28125,y:.21875},{x:.28125,y:.21875},{x:.34375,y:.21875},{x:.34375,y:.21875},{x:.40625,y:.21875},{x:.40625,y:.21875},{x:.46875,y:.21875},{x:.46875,y:.21875},{x:.53125,y:.21875},{x:.53125,y:.21875},{x:.59375,y:.21875},{x:.59375,y:.21875},{x:.65625,y:.21875},{x:.65625,y:.21875},{x:.71875,y:.21875},{x:.71875,y:.21875},{x:.78125,y:.21875},{x:.78125,y:.21875},{x:.84375,y:.21875},{x:.84375,y:.21875},{x:.90625,y:.21875},{x:.90625,y:.21875},{x:.96875,y:.21875},{x:.96875,y:.21875},{x:.03125,y:.28125},{x:.03125,y:.28125},{x:.09375,y:.28125},{x:.09375,y:.28125},{x:.15625,y:.28125},{x:.15625,y:.28125},{x:.21875,y:.28125},{x:.21875,y:.28125},{x:.28125,y:.28125},{x:.28125,y:.28125},{x:.34375,y:.28125},{x:.34375,y:.28125},{x:.40625,y:.28125},{x:.40625,y:.28125},{x:.46875,y:.28125},{x:.46875,y:.28125},{x:.53125,y:.28125},{x:.53125,y:.28125},{x:.59375,y:.28125},{x:.59375,y:.28125},{x:.65625,y:.28125},{x:.65625,y:.28125},{x:.71875,y:.28125},{x:.71875,y:.28125},{x:.78125,y:.28125},{x:.78125,y:.28125},{x:.84375,y:.28125},{x:.84375,y:.28125},{x:.90625,y:.28125},{x:.90625,y:.28125},{x:.96875,y:.28125},{x:.96875,y:.28125},{x:.03125,y:.34375},{x:.03125,y:.34375},{x:.09375,y:.34375},{x:.09375,y:.34375},{x:.15625,y:.34375},{x:.15625,y:.34375},{x:.21875,y:.34375},{x:.21875,y:.34375},{x:.28125,y:.34375},{x:.28125,y:.34375},{x:.34375,y:.34375},{x:.34375,y:.34375},{x:.40625,y:.34375},{x:.40625,y:.34375},{x:.46875,y:.34375},{x:.46875,y:.34375},{x:.53125,y:.34375},{x:.53125,y:.34375},{x:.59375,y:.34375},{x:.59375,y:.34375},{x:.65625,y:.34375},{x:.65625,y:.34375},{x:.71875,y:.34375},{x:.71875,y:.34375},{x:.78125,y:.34375},{x:.78125,y:.34375},{x:.84375,y:.34375},{x:.84375,y:.34375},{x:.90625,y:.34375},{x:.90625,y:.34375},{x:.96875,y:.34375},{x:.96875,y:.34375},{x:.03125,y:.40625},{x:.03125,y:.40625},{x:.09375,y:.40625},{x:.09375,y:.40625},{x:.15625,y:.40625},{x:.15625,y:.40625},{x:.21875,y:.40625},{x:.21875,y:.40625},{x:.28125,y:.40625},{x:.28125,y:.40625},{x:.34375,y:.40625},{x:.34375,y:.40625},{x:.40625,y:.40625},{x:.40625,y:.40625},{x:.46875,y:.40625},{x:.46875,y:.40625},{x:.53125,y:.40625},{x:.53125,y:.40625},{x:.59375,y:.40625},{x:.59375,y:.40625},{x:.65625,y:.40625},{x:.65625,y:.40625},{x:.71875,y:.40625},{x:.71875,y:.40625},{x:.78125,y:.40625},{x:.78125,y:.40625},{x:.84375,y:.40625},{x:.84375,y:.40625},{x:.90625,y:.40625},{x:.90625,y:.40625},{x:.96875,y:.40625},{x:.96875,y:.40625},{x:.03125,y:.46875},{x:.03125,y:.46875},{x:.09375,y:.46875},{x:.09375,y:.46875},{x:.15625,y:.46875},{x:.15625,y:.46875},{x:.21875,y:.46875},{x:.21875,y:.46875},{x:.28125,y:.46875},{x:.28125,y:.46875},{x:.34375,y:.46875},{x:.34375,y:.46875},{x:.40625,y:.46875},{x:.40625,y:.46875},{x:.46875,y:.46875},{x:.46875,y:.46875},{x:.53125,y:.46875},{x:.53125,y:.46875},{x:.59375,y:.46875},{x:.59375,y:.46875},{x:.65625,y:.46875},{x:.65625,y:.46875},{x:.71875,y:.46875},{x:.71875,y:.46875},{x:.78125,y:.46875},{x:.78125,y:.46875},{x:.84375,y:.46875},{x:.84375,y:.46875},{x:.90625,y:.46875},{x:.90625,y:.46875},{x:.96875,y:.46875},{x:.96875,y:.46875},{x:.03125,y:.53125},{x:.03125,y:.53125},{x:.09375,y:.53125},{x:.09375,y:.53125},{x:.15625,y:.53125},{x:.15625,y:.53125},{x:.21875,y:.53125},{x:.21875,y:.53125},{x:.28125,y:.53125},{x:.28125,y:.53125},{x:.34375,y:.53125},{x:.34375,y:.53125},{x:.40625,y:.53125},{x:.40625,y:.53125},{x:.46875,y:.53125},{x:.46875,y:.53125},{x:.53125,y:.53125},{x:.53125,y:.53125},{x:.59375,y:.53125},{x:.59375,y:.53125},{x:.65625,y:.53125},{x:.65625,y:.53125},{x:.71875,y:.53125},{x:.71875,y:.53125},{x:.78125,y:.53125},{x:.78125,y:.53125},{x:.84375,y:.53125},{x:.84375,y:.53125},{x:.90625,y:.53125},{x:.90625,y:.53125},{x:.96875,y:.53125},{x:.96875,y:.53125},{x:.03125,y:.59375},{x:.03125,y:.59375},{x:.09375,y:.59375},{x:.09375,y:.59375},{x:.15625,y:.59375},{x:.15625,y:.59375},{x:.21875,y:.59375},{x:.21875,y:.59375},{x:.28125,y:.59375},{x:.28125,y:.59375},{x:.34375,y:.59375},{x:.34375,y:.59375},{x:.40625,y:.59375},{x:.40625,y:.59375},{x:.46875,y:.59375},{x:.46875,y:.59375},{x:.53125,y:.59375},{x:.53125,y:.59375},{x:.59375,y:.59375},{x:.59375,y:.59375},{x:.65625,y:.59375},{x:.65625,y:.59375},{x:.71875,y:.59375},{x:.71875,y:.59375},{x:.78125,y:.59375},{x:.78125,y:.59375},{x:.84375,y:.59375},{x:.84375,y:.59375},{x:.90625,y:.59375},{x:.90625,y:.59375},{x:.96875,y:.59375},{x:.96875,y:.59375},{x:.03125,y:.65625},{x:.03125,y:.65625},{x:.09375,y:.65625},{x:.09375,y:.65625},{x:.15625,y:.65625},{x:.15625,y:.65625},{x:.21875,y:.65625},{x:.21875,y:.65625},{x:.28125,y:.65625},{x:.28125,y:.65625},{x:.34375,y:.65625},{x:.34375,y:.65625},{x:.40625,y:.65625},{x:.40625,y:.65625},{x:.46875,y:.65625},{x:.46875,y:.65625},{x:.53125,y:.65625},{x:.53125,y:.65625},{x:.59375,y:.65625},{x:.59375,y:.65625},{x:.65625,y:.65625},{x:.65625,y:.65625},{x:.71875,y:.65625},{x:.71875,y:.65625},{x:.78125,y:.65625},{x:.78125,y:.65625},{x:.84375,y:.65625},{x:.84375,y:.65625},{x:.90625,y:.65625},{x:.90625,y:.65625},{x:.96875,y:.65625},{x:.96875,y:.65625},{x:.03125,y:.71875},{x:.03125,y:.71875},{x:.09375,y:.71875},{x:.09375,y:.71875},{x:.15625,y:.71875},{x:.15625,y:.71875},{x:.21875,y:.71875},{x:.21875,y:.71875},{x:.28125,y:.71875},{x:.28125,y:.71875},{x:.34375,y:.71875},{x:.34375,y:.71875},{x:.40625,y:.71875},{x:.40625,y:.71875},{x:.46875,y:.71875},{x:.46875,y:.71875},{x:.53125,y:.71875},{x:.53125,y:.71875},{x:.59375,y:.71875},{x:.59375,y:.71875},{x:.65625,y:.71875},{x:.65625,y:.71875},{x:.71875,y:.71875},{x:.71875,y:.71875},{x:.78125,y:.71875},{x:.78125,y:.71875},{x:.84375,y:.71875},{x:.84375,y:.71875},{x:.90625,y:.71875},{x:.90625,y:.71875},{x:.96875,y:.71875},{x:.96875,y:.71875},{x:.03125,y:.78125},{x:.03125,y:.78125},{x:.09375,y:.78125},{x:.09375,y:.78125},{x:.15625,y:.78125},{x:.15625,y:.78125},{x:.21875,y:.78125},{x:.21875,y:.78125},{x:.28125,y:.78125},{x:.28125,y:.78125},{x:.34375,y:.78125},{x:.34375,y:.78125},{x:.40625,y:.78125},{x:.40625,y:.78125},{x:.46875,y:.78125},{x:.46875,y:.78125},{x:.53125,y:.78125},{x:.53125,y:.78125},{x:.59375,y:.78125},{x:.59375,y:.78125},{x:.65625,y:.78125},{x:.65625,y:.78125},{x:.71875,y:.78125},{x:.71875,y:.78125},{x:.78125,y:.78125},{x:.78125,y:.78125},{x:.84375,y:.78125},{x:.84375,y:.78125},{x:.90625,y:.78125},{x:.90625,y:.78125},{x:.96875,y:.78125},{x:.96875,y:.78125},{x:.03125,y:.84375},{x:.03125,y:.84375},{x:.09375,y:.84375},{x:.09375,y:.84375},{x:.15625,y:.84375},{x:.15625,y:.84375},{x:.21875,y:.84375},{x:.21875,y:.84375},{x:.28125,y:.84375},{x:.28125,y:.84375},{x:.34375,y:.84375},{x:.34375,y:.84375},{x:.40625,y:.84375},{x:.40625,y:.84375},{x:.46875,y:.84375},{x:.46875,y:.84375},{x:.53125,y:.84375},{x:.53125,y:.84375},{x:.59375,y:.84375},{x:.59375,y:.84375},{x:.65625,y:.84375},{x:.65625,y:.84375},{x:.71875,y:.84375},{x:.71875,y:.84375},{x:.78125,y:.84375},{x:.78125,y:.84375},{x:.84375,y:.84375},{x:.84375,y:.84375},{x:.90625,y:.84375},{x:.90625,y:.84375},{x:.96875,y:.84375},{x:.96875,y:.84375},{x:.03125,y:.90625},{x:.03125,y:.90625},{x:.09375,y:.90625},{x:.09375,y:.90625},{x:.15625,y:.90625},{x:.15625,y:.90625},{x:.21875,y:.90625},{x:.21875,y:.90625},{x:.28125,y:.90625},{x:.28125,y:.90625},{x:.34375,y:.90625},{x:.34375,y:.90625},{x:.40625,y:.90625},{x:.40625,y:.90625},{x:.46875,y:.90625},{x:.46875,y:.90625},{x:.53125,y:.90625},{x:.53125,y:.90625},{x:.59375,y:.90625},{x:.59375,y:.90625},{x:.65625,y:.90625},{x:.65625,y:.90625},{x:.71875,y:.90625},{x:.71875,y:.90625},{x:.78125,y:.90625},{x:.78125,y:.90625},{x:.84375,y:.90625},{x:.84375,y:.90625},{x:.90625,y:.90625},{x:.90625,y:.90625},{x:.96875,y:.90625},{x:.96875,y:.90625},{x:.03125,y:.96875},{x:.03125,y:.96875},{x:.09375,y:.96875},{x:.09375,y:.96875},{x:.15625,y:.96875},{x:.15625,y:.96875},{x:.21875,y:.96875},{x:.21875,y:.96875},{x:.28125,y:.96875},{x:.28125,y:.96875},{x:.34375,y:.96875},{x:.34375,y:.96875},{x:.40625,y:.96875},{x:.40625,y:.96875},{x:.46875,y:.96875},{x:.46875,y:.96875},{x:.53125,y:.96875},{x:.53125,y:.96875},{x:.59375,y:.96875},{x:.59375,y:.96875},{x:.65625,y:.96875},{x:.65625,y:.96875},{x:.71875,y:.96875},{x:.71875,y:.96875},{x:.78125,y:.96875},{x:.78125,y:.96875},{x:.84375,y:.96875},{x:.84375,y:.96875},{x:.90625,y:.96875},{x:.90625,y:.96875},{x:.96875,y:.96875},{x:.96875,y:.96875},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375}];var Q2=class{constructor(t){me(this,"model");me(this,"anchors");me(this,"anchorsTensor");me(this,"inputSize");me(this,"inputSizeTensor");me(this,"doubleInputSizeTensor");this.model=t,this.anchors=XN.map(n=>[n.x,n.y]),this.anchorsTensor=or(this.anchors),this.inputSize=this.model&&this.model.inputs&&this.model.inputs[0].shape?this.model.inputs[0].shape[2]:0,this.inputSizeTensor=Ft([this.inputSize,this.inputSize]),this.doubleInputSizeTensor=Ft([this.inputSize*2,this.inputSize*2])}normalizeBoxes(t){let n={};n.boxOffsets=Oe(t,[0,0],[-1,2]),n.boxSizes=Oe(t,[0,2],[-1,2]),n.div=pe(n.boxOffsets,this.inputSizeTensor),n.boxCenterPoints=ce(n.div,this.anchorsTensor),n.halfBoxSizes=pe(n.boxSizes,this.doubleInputSizeTensor),n.sub=he(n.boxCenterPoints,n.halfBoxSizes),n.startPoints=L(n.sub,this.inputSizeTensor),n.add=ce(n.boxCenterPoints,n.halfBoxSizes),n.endPoints=L(n.add,this.inputSizeTensor);let s=Xl([n.startPoints,n.endPoints],1);return Object.keys(n).forEach(r=>ne(n[r])),s}normalizeLandmarks(t,n){let s={};s.reshape=U(t,[-1,7,2]),s.div=pe(s.reshape,this.inputSizeTensor),s.landmarks=ce(s.div,this.anchors[n]);let r=L(s.landmarks,this.inputSizeTensor);return Object.keys(s).forEach(a=>ne(s[a])),r}async predict(t,n){let s={};s.resize=Ne.resizeBilinear(t,[this.inputSize,this.inputSize]),s.div=pe(s.resize,nt.tf127),s.image=he(s.div,nt.tf1),s.batched=this.model.execute(s.image),s.predictions=rt(s.batched),s.slice=Oe(s.predictions,[0,0],[-1,1]),s.sigmoid=Cn(s.slice),s.scores=rt(s.sigmoid);let r=await s.scores.data();s.boxes=Oe(s.predictions,[0,1],[-1,4]),s.norm=this.normalizeBoxes(s.boxes),s.nms=await Ne.nonMaxSuppressionAsync(s.norm,s.scores,3*n.hand.maxDetected,n.hand.iouThreshold,n.hand.minConfidence);let a=await s.nms.array(),o=[];for(let i of a){let l={};l.box=Oe(s.norm,[i,0],[1,-1]),l.slice=Oe(s.predictions,[i,5],[1,14]),l.norm=this.normalizeLandmarks(l.slice,i),l.palmLandmarks=U(l.norm,[-1,2]);let u=await l.box.data(),c=u.slice(0,2),p=u.slice(2,4),d=await l.palmLandmarks.array(),h={startPoint:c,endPoint:p,palmLandmarks:d,confidence:r[i]},f=GN(h,[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]);o.push(f),Object.keys(l).forEach(m=>ne(l[m]))}return Object.keys(s).forEach(i=>ne(s[i])),o}};var E5e=5,KN=1.65,ZN=[0,5,9,13,17,1,2],R5e=0,_5e=2,YN=0,e1=class{constructor(t,n){me(this,"handDetector");me(this,"handPoseModel");me(this,"inputSize");me(this,"storedBoxes");me(this,"skipped");me(this,"detectedHands");this.handDetector=t,this.handPoseModel=n,this.inputSize=this.handPoseModel&&this.handPoseModel.inputs[0].shape?this.handPoseModel.inputs[0].shape[2]:0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let n=t.map(o=>o[0]),s=t.map(o=>o[1]),r=[Math.min(...n),Math.min(...s)],a=[Math.max(...n),Math.max(...s)];return{startPoint:r,endPoint:a}}getBoxForPalmLandmarks(t,n){let s=t.map(a=>Qb([...a,1],n)),r=this.calculateLandmarksBoundingBox(s);return Y2(J2(r),E5e)}getBoxForHandLandmarks(t){let n=this.calculateLandmarksBoundingBox(t),s=Y2(J2(n),KN);s.palmLandmarks=[];for(let r=0;r<ZN.length;r++)s.palmLandmarks.push(t[ZN[r]].slice(0,2));return s}transformRawCoords(t,n,s,r){let a=Z2(n),o=[a[0]/this.inputSize,a[1]/this.inputSize,(a[0]+a[1])/this.inputSize/2],i=t.map(h=>[o[0]*(h[0]-this.inputSize/2),o[1]*(h[1]-this.inputSize/2),o[2]*h[2]]),l=Jb(s,[0,0]),u=i.map(h=>[...Qb(h,l),h[2]]),c=jN(r),p=[...Xh(n),1],d=[Ai(p,c[0]),Ai(p,c[1])];return u.map(h=>[Math.trunc(h[0]+d[0]),Math.trunc(h[1]+d[1]),Math.trunc(h[2])])}async estimateHands(t,n){let s=!1,r,a=(n.hand.skipTime||0)>ue()-YN,o=this.skipped<(n.hand.skipFrames||0);n.skipAllowed&&a&&o&&(r=await this.handDetector.predict(t,n),this.skipped=0),n.skipAllowed&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==n.hand.maxDetected||!n.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(s=!0));let i=[];for(let l=0;l<this.storedBoxes.length;l++){let u=this.storedBoxes[l];if(!!u)if(n.hand.landmarks){let c=n.hand.rotation?HN(u.palmLandmarks[R5e],u.palmLandmarks[_5e]):0,p=Xh(u),d=[p[0]/t.shape[2],p[1]/t.shape[1]],h=n.hand.rotation&&fe.kernels.includes("rotatewithoffset")?Ne.rotateWithOffset(t,c,0,d):t.clone(),f=Jb(-c,p),m=s?this.getBoxForPalmLandmarks(u.palmLandmarks,f):u,g=UN(m,h,[this.inputSize,this.inputSize]),y=pe(g,nt.tf255);ne(g),ne(h);let[x,A]=this.handPoseModel.execute(y);YN=ue(),ne(y);let b=(await x.data())[0];if(ne(x),b>=n.hand.minConfidence/4){let w=U(A,[-1,3]),k=await w.array();ne(A),ne(w);let S=this.transformRawCoords(k,m,c,f),E=this.getBoxForHandLandmarks(S);this.storedBoxes[l]={...E,confidence:b};let R={landmarks:S,confidence:b,boxConfidence:u.confidence,fingerConfidence:b,box:{topLeft:E.startPoint,bottomRight:E.endPoint}};i.push(R)}else this.storedBoxes[l]=null;ne(A)}else{let c=Y2(J2(u),KN),p={confidence:u.confidence,boxConfidence:u.confidence,fingerConfidence:0,box:{topLeft:c.startPoint,bottomRight:c.endPoint},landmarks:[]};i.push(p)}}return this.storedBoxes=this.storedBoxes.filter(l=>l!==null),this.detectedHands=i.length,i.length>n.hand.maxDetected&&(i.length=n.hand.maxDetected),i}};var cs={thumb:0,index:1,middle:2,ring:3,pinky:4,all:[0,1,2,3,4],nameMapping:{0:"thumb",1:"index",2:"middle",3:"ring",4:"pinky"},pointsMapping:{0:[[0,1],[1,2],[2,3],[3,4]],1:[[0,5],[5,6],[6,7],[7,8]],2:[[0,9],[9,10],[10,11],[11,12]],3:[[0,13],[13,14],[14,15],[15,16]],4:[[0,17],[17,18],[18,19],[19,20]]},getName:e=>cs.nameMapping[e],getPoints:e=>cs.pointsMapping[e]},bi={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>bi.nameMapping[e]},jt={verticalUp:0,verticalDown:1,horizontalLeft:2,horizontalRight:3,diagonalUpRight:4,diagonalUpLeft:5,diagonalDownRight:6,diagonalDownLeft:7,nameMapping:{0:"verticalUp",1:"verticalDown",2:"horizontalLeft",3:"horizontalRight",4:"diagonalUpRight",5:"diagonalUpLeft",6:"diagonalDownRight",7:"diagonalDownLeft"},getName:e=>jt.nameMapping[e]},xi=class{constructor(t){me(this,"name");me(this,"curls");me(this,"directions");me(this,"weights");me(this,"weightsRelative");this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}curl(t,n,s){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([n,s])}direction(t,n,s){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([n,s])}weight(t,n){this.weights[t]=n;let s=this.weights.reduce((r,a)=>r+a,0);this.weightsRelative=this.weights.map(r=>r*5/s)}matchAgainst(t,n){let s=0;for(let r in t){let a=t[r],o=this.curls[r];if(typeof o=="undefined"){s+=this.weightsRelative[r];continue}for(let[i,l]of o)if(a===i){s+=l*this.weightsRelative[r];break}}for(let r in n){let a=n[r],o=this.directions[r];if(typeof o=="undefined"){s+=this.weightsRelative[r];continue}for(let[i,l]of o)if(a===i){s+=l*this.weightsRelative[r];break}}return s/10}};var{thumb:Or,index:Ra,middle:_a,ring:hu,pinky:fu}=cs,{none:Mr,half:$5e,full:zr}=bi,{verticalUp:wd,verticalDown:$ke,horizontalLeft:e4,horizontalRight:P5e,diagonalUpRight:F5e,diagonalUpLeft:kd,diagonalDownRight:Pke,diagonalDownLeft:Fke}=jt,vi=new xi("thumbs up");vi.curl(Or,Mr,1);vi.direction(Or,wd,1);vi.direction(Or,kd,.25);vi.direction(Or,F5e,.25);for(let e of[cs.index,cs.middle,cs.ring,cs.pinky])vi.curl(e,zr,1),vi.direction(e,e4,1),vi.direction(e,P5e,1);var dn=new xi("victory");dn.curl(Or,$5e,.5);dn.curl(Or,Mr,.5);dn.direction(Or,wd,1);dn.direction(Or,kd,1);dn.curl(Ra,Mr,1);dn.direction(Ra,wd,.75);dn.direction(Ra,kd,1);dn.curl(_a,Mr,1);dn.direction(_a,wd,1);dn.direction(_a,kd,.75);dn.curl(hu,zr,1);dn.direction(hu,wd,.2);dn.direction(hu,kd,1);dn.direction(hu,e4,.2);dn.curl(fu,zr,1);dn.direction(fu,wd,.2);dn.direction(fu,kd,1);dn.direction(fu,e4,.2);dn.weight(Ra,2);dn.weight(_a,2);var wi=new xi("point");wi.curl(Or,zr,1);wi.curl(Ra,Mr,.5);wi.curl(_a,zr,.5);wi.curl(hu,zr,.5);wi.curl(fu,zr,.5);wi.weight(Ra,2);wi.weight(_a,2);var ki=new xi("middle finger");ki.curl(Or,Mr,1);ki.curl(Ra,zr,.5);ki.curl(_a,zr,.5);ki.curl(hu,zr,.5);ki.curl(fu,zr,.5);ki.weight(Ra,2);ki.weight(_a,2);var Id=new xi("open palm");Id.curl(Or,Mr,.75);Id.curl(Ra,Mr,.75);Id.curl(_a,Mr,.75);Id.curl(hu,Mr,.75);Id.curl(fu,Mr,.75);var JN=[vi,dn,wi,ki,Id];var O5e=.7,mu={HALF_CURL_START_LIMIT:60,NO_CURL_START_LIMIT:130,DISTANCE_VOTE_POWER:1.1,SINGLE_ANGLE_VOTE_POWER:.9,TOTAL_ANGLE_VOTE_POWER:1.6};function QN(e,t,n,s){let r=(t-s)/(e-n),a=Math.atan(r)*180/Math.PI;return a<=0?a=-a:a>0&&(a=180-a),a}function tE(e,t){if(!e||!t)return[0,0];let n=QN(e[0],e[1],t[0],t[1]);if(e.length===2)return n;let s=QN(e[1],e[2],t[1],t[2]);return[n,s]}function eE(e,t=1){let n=0,s=0,r=0;return e>=75&&e<=105?n=1*t:e>=25&&e<=155?s=1*t:r=1*t,[n,s,r]}function M5e(e,t,n){let s=e[0]-t[0],r=e[0]-n[0],a=t[0]-n[0],o=e[1]-t[1],i=e[1]-n[1],l=t[1]-n[1],u=e[2]-t[2],c=e[2]-n[2],p=t[2]-n[2],d=Math.sqrt(s*s+o*o+u*u),h=Math.sqrt(r*r+i*i+c*c),f=Math.sqrt(a*a+l*l+p*p),m=(f*f+d*d-h*h)/(2*f*d);m>1?m=1:m<-1&&(m=-1);let g=Math.acos(m);g=57.2958*g%180;let y;return g>mu.NO_CURL_START_LIMIT?y=bi.none:g>mu.HALF_CURL_START_LIMIT?y=bi.half:y=bi.full,y}function nE(e,t,n,s){let r;return s===Math.abs(e)?e>0?r=jt.horizontalLeft:r=jt.horizontalRight:s===Math.abs(t)?t>0?r=jt.horizontalLeft:r=jt.horizontalRight:n>0?r=jt.horizontalLeft:r=jt.horizontalRight,r}function sE(e,t,n,s){let r;return s===Math.abs(e)?e<0?r=jt.verticalDown:r=jt.verticalUp:s===Math.abs(t)?t<0?r=jt.verticalDown:r=jt.verticalUp:n<0?r=jt.verticalDown:r=jt.verticalUp,r}function z5e(e,t,n,s,r,a,o,i){let l,u=sE(e,t,n,s),c=nE(r,a,o,i);return u===jt.verticalUp?c===jt.horizontalLeft?l=jt.diagonalUpLeft:l=jt.diagonalUpRight:c===jt.horizontalLeft?l=jt.diagonalDownLeft:l=jt.diagonalDownRight,l}function L5e(e,t,n,s){let r=e[0]-t[0],a=e[0]-n[0],o=t[0]-n[0],i=e[1]-t[1],l=e[1]-n[1],u=t[1]-n[1],c=Math.max(Math.abs(r),Math.abs(a),Math.abs(o)),p=Math.max(Math.abs(i),Math.abs(l),Math.abs(u)),d=0,h=0,f=0,m=p/(c+1e-5);m>1.5?d+=mu.DISTANCE_VOTE_POWER:m>.66?h+=mu.DISTANCE_VOTE_POWER:f+=mu.DISTANCE_VOTE_POWER;let g=Math.sqrt(r*r+i*i),y=Math.sqrt(a*a+l*l),x=Math.sqrt(o*o+u*u),A=Math.max(g,y,x),b=e[0],w=e[1],k=n[0],S=n[1];A===g?(k=n[0],S=n[1]):A===x&&(b=t[0],w=t[1]);let P=tE([b,w],[k,S]),_=eE(P,mu.TOTAL_ANGLE_VOTE_POWER);d+=_[0],h+=_[1],f+=_[2];for(let T of s){let F=eE(T,mu.SINGLE_ANGLE_VOTE_POWER);d+=F[0],h+=F[1],f+=F[2]}let $;return d===Math.max(d,h,f)?$=sE(l,i,u,p):f===Math.max(h,f)?$=nE(a,r,o,c):$=z5e(l,i,u,p,a,r,o,c),$}function rE(e){let t=[],n=[],s=[],r=[];if(!e)return{curls:s,directions:r};for(let a of cs.all){let o=cs.getPoints(a),i=[],l=[];for(let u of o){let c=e[u[0]],p=e[u[1]],d=tE(c,p),h=d[0],f=d[1];i.push(h),l.push(f)}t.push(i),n.push(l)}for(let a of cs.all){let o=a===cs.thumb?1:0,i=cs.getPoints(a),l=e[i[o][0]],u=e[i[o+1][1]],c=e[i[3][1]],p=M5e(l,u,c),d=L5e(l,u,c,t[a].slice(o));s[a]=p,r[a]=d}return{curls:s,directions:r}}function t1(e){if(!e||e.length===0)return null;let t=rE(e),n={};for(let s of cs.all)n[cs.getName(s)]={curl:bi.getName(t.curls[s]),direction:jt.getName(t.directions[s])};return n}function aE(e){let t=[];if(!e||e.length===0)return t;let n=rE(e);for(let s of JN){let r=s.matchAgainst(n.curls,n.directions);r>=O5e&&t.push({name:s.name,confidence:r})}return t}var oE={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],palm:[0]},Sd,Cd,iE;async function n4(e,t){let n=await iE.estimateHands(e,t);if(!n)return[];let s=[];for(let r=0;r<n.length;r++){let a={};if(n[r].landmarks)for(let c of Object.keys(oE))a[c]=oE[c].map(p=>n[r].landmarks[p]);let o=n[r].landmarks,i=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],l=[0,0,0,0];if(o&&o.length>0){for(let c of o)c[0]<i[0]&&(i[0]=c[0]),c[1]<i[1]&&(i[1]=c[1]),c[0]>i[2]&&(i[2]=c[0]),c[1]>i[3]&&(i[3]=c[1]);i[2]-=i[0],i[3]-=i[1],l=[i[0]/(e.shape[2]||0),i[1]/(e.shape[1]||0),i[2]/(e.shape[2]||0),i[3]/(e.shape[1]||0)]}else i=n[r].box?[Math.trunc(Math.max(0,n[r].box.topLeft[0])),Math.trunc(Math.max(0,n[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,n[r].box.bottomRight[0])-Math.max(0,n[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,n[r].box.bottomRight[1])-Math.max(0,n[r].box.topLeft[1]))]:[0,0,0,0],l=[n[r].box.topLeft[0]/(e.shape[2]||0),n[r].box.topLeft[1]/(e.shape[1]||0),(n[r].box.bottomRight[0]-n[r].box.topLeft[0])/(e.shape[2]||0),(n[r].box.bottomRight[1]-n[r].box.topLeft[1])/(e.shape[1]||0)];let u=t1(o);s.push({id:r,score:Math.round(100*n[r].confidence)/100,boxScore:Math.round(100*n[r].boxConfidence)/100,fingerScore:Math.round(100*n[r].fingerConfidence)/100,label:"hand",box:i,boxRaw:l,keypoints:o,annotations:a,landmarks:u})}return s}async function s4(e){var n,s;fe.initial&&(Sd=null,Cd=null),!Sd||!Cd?[Sd,Cd]=await Promise.all([e.hand.enabled?qe((n=e.hand.detector)==null?void 0:n.modelPath):null,e.hand.landmarks?qe((s=e.hand.skeleton)==null?void 0:s.modelPath):null]):(e.debug&&ie("cached model:",Sd.modelUrl),e.debug&&ie("cached model:",Cd.modelUrl));let t=new Q2(Sd);return iE=new e1(t,Cd),[Sd,Cd]}var An=[null,null],B5e=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],Ii=[[0,0],[0,0]],W5e=["hand","fist","pinch","point","face","tip","pinchtip"],uE=4,cE=1.6,V5e=512,U5e=1.4,n1=Number.MAX_SAFE_INTEGER,r4=0,Da=[0,0],Jt={boxes:[],hands:[]},dE={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],base:[0],palm:[0,17,13,9,5,1,0]};async function pE(e){var t;if(fe.initial&&(An[0]=null),An[0])e.debug&&ie("cached model:",An[0].modelUrl);else{s1(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),An[0]=await qe((t=e.hand.detector)==null?void 0:t.modelPath);let n=Object.values(An[0].modelSignature.inputs);Ii[0][0]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[1].size):0,Ii[0][1]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[2].size):0}return An[0]}async function hE(e){var t;if(fe.initial&&(An[1]=null),An[1])e.debug&&ie("cached model:",An[1].modelUrl);else{An[1]=await qe((t=e.hand.skeleton)==null?void 0:t.modelPath);let n=Object.values(An[1].modelSignature.inputs);Ii[1][0]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[1].size):0,Ii[1][1]=Array.isArray(n)?parseInt(n[0].tensorShape.dim[2].size):0}return An[1]}async function G5e(e,t){let n=[];if(!e||!An[0])return n;let s={},r=(e.shape[2]||1)/(e.shape[1]||1),a=Math.min(Math.round((e.shape[1]||0)/8)*8,V5e),o=Math.round(a*r/8)*8;s.resize=Ne.resizeBilinear(e,[a,o]),s.cast=ge(s.resize,"int32"),[s.rawScores,s.rawBoxes]=await An[0].executeAsync(s.cast,B5e),s.boxes=rt(s.rawBoxes,[0,2]),s.scores=rt(s.rawScores,[0]);let i=es(s.scores,1);ne(i[uE]),i.splice(uE,1),s.filtered=on(i,1),ne(i),s.max=mn(s.filtered,1),s.argmax=Es(s.filtered,1);let l=0;s.nms=await Ne.nonMaxSuppressionAsync(s.boxes,s.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let u=await s.nms.data(),c=await s.max.data(),p=await s.argmax.data();for(let d of Array.from(u)){let h=Oe(s.boxes,d,1),f=await h.data();ne(h);let m=[f[1],f[0],f[3]-f[1],f[2]-f[0]],g=U2(m,U5e),y=[Math.trunc(m[0]*Da[0]),Math.trunc(m[1]*Da[1]),Math.trunc(m[2]*Da[0]),Math.trunc(m[3]*Da[1])],x=c[d],A=W5e[p[d]],b={id:l++,score:x,box:y,boxRaw:g,label:A};n.push(b)}return Object.keys(s).forEach(d=>ne(s[d])),n.sort((d,h)=>h.score-d.score),n.length>(t.hand.maxDetected||1)&&(n.length=t.hand.maxDetected||1),n}async function a4(e,t,n){let s={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&An[1]&&n.hand.landmarks&&t.score>(n.hand.minConfidence||0)){let r={},a=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=Ne.cropAndResize(e,[a],[0],[Ii[1][0],Ii[1][1]],"bilinear"),r.div=pe(r.crop,nt.tf255),[r.score,r.keypoints]=An[1].execute(r.div,["Identity_1","Identity"]);let o=(await r.score.data())[0],i=(100-Math.trunc(100/(1+Math.exp(o))))/100;if(i>=(n.hand.minConfidence||0)){s.fingerScore=i,r.reshaped=U(r.keypoints,[-1,3]);let c=(await r.reshaped.array()).map(p=>[p[0]/Ii[1][1],p[1]/Ii[1][0],p[2]||0]).map(p=>[p[0]*t.boxRaw[2],p[1]*t.boxRaw[3],p[2]||0]);s.keypoints=c.map(p=>[Da[0]*(p[0]+t.boxRaw[0]),Da[1]*(p[1]+t.boxRaw[1]),p[2]||0]),s.landmarks=t1(s.keypoints);for(let p of Object.keys(dE))s.annotations[p]=dE[p].map(d=>s.landmarks&&s.keypoints[d]?s.keypoints[d]:null)}Object.keys(r).forEach(l=>ne(r[l]))}return s}async function o4(e,t){var r,a;if(!An[0]||!An[1]||!((r=An[0])!=null&&r.inputs[0].shape)||!((a=An[1])!=null&&a.inputs[0].shape))return[];Da=[e.shape[2]||0,e.shape[1]||0],n1++;let n=(t.hand.skipTime||0)>ue()-r4,s=n1<(t.hand.skipFrames||0);return t.skipAllowed&&n&&s?Jt.hands:new Promise(async o=>{let i=3*(t.hand.skipTime||0)>ue()-r4,l=n1<3*(t.hand.skipFrames||0);t.skipAllowed&&Jt.hands.length===t.hand.maxDetected?Jt.hands=await Promise.all(Jt.boxes.map(c=>a4(e,c,t))):t.skipAllowed&&i&&l&&Jt.hands.length>0?Jt.hands=await Promise.all(Jt.boxes.map(c=>a4(e,c,t))):(Jt.boxes=await G5e(e,t),r4=ue(),Jt.hands=await Promise.all(Jt.boxes.map(c=>a4(e,c,t))),n1=0);let u=[...Jt.boxes];if(Jt.boxes.length=0,t.cacheSensitivity>0)for(let c=0;c<Jt.hands.length;c++){let p=rN(Jt.hands[c].keypoints,Da);if(p.box[2]/(e.shape[2]||1)>.05&&p.box[3]/(e.shape[1]||1)>.05&&Jt.hands[c].fingerScore&&Jt.hands[c].fingerScore>(t.hand.minConfidence||0)){let d=U2(p.box,cE),h=U2(p.boxRaw,cE);Jt.boxes.push({...u[c],box:d,boxRaw:h})}}for(let c=0;c<Jt.hands.length;c++){let p=Ta(Jt.hands[c].keypoints,Da);Jt.hands[c].box=p.box,Jt.hands[c].boxRaw=p.boxRaw}o(Jt.hands)})}var Wn,r1=[],i4=Number.MAX_SAFE_INTEGER,mE=0,gE=0;async function yE(e){var t;return fe.initial&&(Wn=null),Wn?e.debug&&ie("cached model:",Wn.modelUrl):Wn=await qe((t=e.face.liveness)==null?void 0:t.modelPath),Wn}async function l4(e,t,n,s){var o,i;if(!Wn)return 0;let r=(((o=t.face.liveness)==null?void 0:o.skipTime)||0)>ue()-gE,a=i4<(((i=t.face.liveness)==null?void 0:i.skipFrames)||0);return t.skipAllowed&&r&&a&&mE===s&&r1[n]?(i4++,r1[n]):(i4=0,new Promise(async l=>{let u=Ne.resizeBilinear(e,[Wn!=null&&Wn.inputs[0].shape?Wn.inputs[0].shape[2]:0,Wn!=null&&Wn.inputs[0].shape?Wn.inputs[0].shape[1]:0],!1),c=Wn==null?void 0:Wn.execute(u),p=(await c.data())[0];r1[n]=Math.round(100*p)/100,mE=s,gE=ue(),ne([u,c]),l(r1[n])}))}var Kh={};oa(Kh,{connected:()=>o1,horizontal:()=>u4,kpt:()=>a1,relative:()=>d4,vertical:()=>c4});var a1=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],u4=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],c4=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],d4=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],o1={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var xE=.005,Bs={keypoints:[],padding:[[0,0],[0,0],[0,0],[0,0]]};function p4(e){for(let t of u4){let n=e.keypoints.findIndex(r=>r.part===t[0]),s=e.keypoints.findIndex(r=>r.part===t[1]);if(e.keypoints[n]&&e.keypoints[s]&&e.keypoints[n].position[0]<e.keypoints[s].position[0]){let r=e.keypoints[n];e.keypoints[n]=e.keypoints[s],e.keypoints[s]=r}}for(let t of c4){let n=e.keypoints.findIndex(r=>r&&r.part===t[0]),s=e.keypoints.findIndex(r=>r&&r.part===t[1]);e.keypoints[n]&&e.keypoints[s]&&e.keypoints[n].position[1]<e.keypoints[s].position[1]&&e.keypoints.splice(n,1)}for(let[t,n]of d4){let s=e.keypoints.findIndex(u=>u&&u.part===t[0]),r=e.keypoints.findIndex(u=>u&&u.part===t[1]),a=e.keypoints.findIndex(u=>u&&u.part===n[0]),o=e.keypoints.findIndex(u=>u&&u.part===n[1]);if(!e.keypoints[a]||!e.keypoints[o])continue;let i=e.keypoints[s]?[Math.abs(e.keypoints[a].position[0]-e.keypoints[s].position[0]),Math.abs(e.keypoints[o].position[0]-e.keypoints[s].position[0])]:[0,0],l=e.keypoints[r]?[Math.abs(e.keypoints[o].position[0]-e.keypoints[r].position[0]),Math.abs(e.keypoints[a].position[0]-e.keypoints[r].position[0])]:[0,0];if(i[0]>i[1]||l[0]>l[1]){let u=e.keypoints[s];e.keypoints[s]=e.keypoints[r],e.keypoints[r]=u}}}function bE(e){for(let t=0;t<e.length;t++)if(e[t]&&Bs.keypoints[t]){let n=[Math.abs(e[t].positionRaw[0]-Bs.keypoints[t].positionRaw[0]),Math.abs(e[t].positionRaw[1]-Bs.keypoints[t].positionRaw[1])];n[0]<xE&&n[1]<xE?e[t]=Bs.keypoints[t]:Bs.keypoints[t]=e[t]}else Bs.keypoints[t]=e[t];return e}function vE(e,t){let n={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;Bs.padding=[[0,0],[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0],[0,0]],n.pad=Js(e,Bs.padding),n.resize=Ne.resizeBilinear(n.pad,[t,t]);let s=ge(n.resize,"int32");return Object.keys(n).forEach(r=>ne(n[r])),s}function wE(e,t){e.keypoints=e.keypoints.filter(s=>s&&s.position);for(let s of e.keypoints)s.position=[s.position[0]*(t[0]+Bs.padding[2][0]+Bs.padding[2][1])/t[0]-Bs.padding[2][0],s.position[1]*(t[1]+Bs.padding[1][0]+Bs.padding[1][1])/t[1]-Bs.padding[1][0]],s.positionRaw=[s.position[0]/t[0],s.position[1]/t[1]];let n=Ta(e.keypoints.map(s=>s.position),t);return e.box=n.box,e.boxRaw=n.boxRaw,e}var Ws,i1=0,h4=Number.MAX_SAFE_INTEGER,gu={boxes:[],bodies:[],last:0};async function kE(e){return fe.initial&&(Ws=null),Ws?e.debug&&ie("cached model:",Ws.modelUrl):(s1(["size"],e),Ws=await qe(e.body.modelPath)),i1=Ws.inputs[0].shape?Ws.inputs[0].shape[2]:0,i1<64&&(i1=256),Ws}async function j5e(e,t,n){let s=e[0][0],r=[],a=0;for(let c=0;c<s.length;c++)if(a=s[c][2],a>t.body.minConfidence){let p=[s[c][1],s[c][0]];r.push({score:Math.round(100*a)/100,part:a1[c],positionRaw:p,position:[Math.round((n.shape[2]||0)*p[0]),Math.round((n.shape[1]||0)*p[1])]})}a=r.reduce((c,p)=>p.score>c?p.score:c,0);let o=[],i=Ta(r.map(c=>c.position),[n.shape[2],n.shape[1]]),l={};for(let[c,p]of Object.entries(o1)){let d=[];for(let h=0;h<p.length-1;h++){let f=r.find(g=>g.part===p[h]),m=r.find(g=>g.part===p[h+1]);f&&m&&f.score>(t.body.minConfidence||0)&&m.score>(t.body.minConfidence||0)&&d.push([f.position,m.position])}l[c]=d}let u={id:0,score:a,box:i.box,boxRaw:i.boxRaw,keypoints:r,annotations:l};return p4(u),o.push(u),o}async function q5e(e,t,n){let s=[];for(let r=0;r<e[0].length;r++){let a=e[0][r],o=Math.round(100*a[51+4])/100;if(o>t.body.minConfidence){let i=[];for(let p=0;p<17;p++){let d=a[3*p+2];if(d>t.body.minConfidence){let h=[a[3*p+1],a[3*p+0]];i.push({part:a1[p],score:Math.round(100*d)/100,positionRaw:h,position:[Math.round((n.shape[2]||0)*h[0]),Math.round((n.shape[1]||0)*h[1])]})}}let l=Ta(i.map(p=>p.position),[n.shape[2],n.shape[1]]),u={};for(let[p,d]of Object.entries(o1)){let h=[];for(let f=0;f<d.length-1;f++){let m=i.find(y=>y.part===d[f]),g=i.find(y=>y.part===d[f+1]);m&&g&&m.score>(t.body.minConfidence||0)&&g.score>(t.body.minConfidence||0)&&h.push([m.position,g.position])}u[p]=h}let c={id:r,score:o,box:l.box,boxRaw:l.boxRaw,keypoints:[...i],annotations:u};p4(c),s.push(c)}}return s.sort((r,a)=>a.score-r.score),s.length>t.body.maxDetected&&(s.length=t.body.maxDetected),s}async function f4(e,t){if(!Ws||!(Ws!=null&&Ws.inputs[0].shape))return[];t.skipAllowed||(gu.boxes.length=0),h4++;let n=(t.body.skipTime||0)>ue()-gu.last,s=h4<(t.body.skipFrames||0);return t.skipAllowed&&n&&s?gu.bodies:new Promise(async r=>{let a={};h4=0,a.input=vE(e,i1),a.res=Ws==null?void 0:Ws.execute(a.input),gu.last=ue();let o=await a.res.array();gu.bodies=a.res.shape[2]===17?await j5e(o,t,e):await q5e(o,t,e);for(let i of gu.bodies)wE(i,[e.shape[2]||1,e.shape[1]||1]),bE(i.keypoints);Object.keys(a).forEach(i=>ne(a[i])),r(gu.bodies)})}var Td,l1=[],SE=0,m4=Number.MAX_SAFE_INTEGER,c1=0,u1=2.5;async function CE(e){if(!Td||fe.initial){Td=await qe(e.object.modelPath);let t=Object.values(Td.modelSignature.inputs);c1=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&ie("cached model:",Td.modelUrl);return Td}async function X5e(e,t,n){let s=0,r=[];for(let l of[1,2,4])J(async()=>{let u=l*13,c=rt(e.find(m=>m.shape[1]===u**2&&(m.shape[2]||0)===xd.length)),p=rt(e.find(m=>m.shape[1]===u**2&&(m.shape[2]||0)<xd.length)),h=await p.reshape([-1,4,p.shape[1]/4]).argMax(2).array(),f=await c.array();for(let m=0;m<c.shape[0];m++)for(let g=0;g<c.shape[1];g++){let y=f[m][g];if(y>(n.object.minConfidence||0)&&g!==61){let x=(.5+Math.trunc(m%u))/u,A=(.5+Math.trunc(m/u))/u,b=h[m].map($=>$*(u/l/c1)),[w,k]=[x-u1/l*b[0],A-u1/l*b[1]],[S,E]=[x+u1/l*b[2]-w,A+u1/l*b[3]-k],R=[w,k,S,E];R=R.map($=>Math.max(0,Math.min($,1)));let P=[R[0]*t[0],R[1]*t[1],R[2]*t[0],R[3]*t[1]],_={id:s++,score:Math.round(100*y)/100,class:g+1,label:xd[g].label,box:P.map($=>Math.trunc($)),boxRaw:R};r.push(_)}}});e.forEach(l=>ne(l));let a=r.map(l=>[l.boxRaw[1],l.boxRaw[0],l.boxRaw[3],l.boxRaw[2]]),o=r.map(l=>l.score),i=[];if(a&&a.length>0){let l=await Ne.nonMaxSuppressionAsync(a,o,n.object.maxDetected,n.object.iouThreshold,n.object.minConfidence);i=await l.data(),ne(l)}return r=r.filter((l,u)=>i.includes(u)).sort((l,u)=>u.score-l.score),r}async function g4(e,t){let n=(t.object.skipTime||0)>ue()-SE,s=m4<(t.object.skipFrames||0);return t.skipAllowed&&n&&s&&l1.length>0?(m4++,l1):(m4=0,!fe.kernels.includes("mod")||!fe.kernels.includes("sparsetodense")?l1:new Promise(async r=>{let a=[e.shape[2]||0,e.shape[1]||0],o=Ne.resizeBilinear(e,[c1,c1],!1),i=pe(o,nt.tf255),l=i.transpose([0,3,1,2]);ne(i),ne(o);let u;t.object.enabled&&(u=Td.execute(l)),SE=ue(),ne(l);let c=await X5e(u,a,t);l1=c,r(c)}))}var Yh=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],K5e=Yh.length,Zh=Yh.reduce((e,t,n)=>(e[t]=n,e),{}),Z5e=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],aIe=Z5e.map(([e,t])=>[Zh[e],Zh[t]]),NE=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function EE(e){let t=e.reduce(({maxX:n,maxY:s,minX:r,minY:a},{position:{x:o,y:i}})=>({maxX:Math.max(n,o),maxY:Math.max(s,i),minX:Math.min(r,o),minY:Math.min(a,i)}),{maxX:Number.NEGATIVE_INFINITY,maxY:Number.NEGATIVE_INFINITY,minX:Number.POSITIVE_INFINITY,minY:Number.POSITIVE_INFINITY});return[t.minX,t.minY,t.maxX-t.minX,t.maxY-t.minY]}function RE(e,[t,n],[s,r]){let a=t/s,o=n/r,i=(u,c)=>({id:c,score:u.score,boxRaw:[u.box[0]/r,u.box[1]/s,u.box[2]/r,u.box[3]/s],box:[Math.trunc(u.box[0]*o),Math.trunc(u.box[1]*a),Math.trunc(u.box[2]*o),Math.trunc(u.box[3]*a)],keypoints:u.keypoints.map(({score:p,part:d,position:h})=>({score:p,part:d,position:[Math.trunc(h.x*o),Math.trunc(h.y*a)],positionRaw:[h.x/s,h.y/s]})),annotations:{}});return e.map((u,c)=>i(u,c))}var d1=class{constructor(t,n){me(this,"priorityQueue");me(this,"numberOfElements");me(this,"getElementValue");this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=n}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(Math.floor(t/2),t);)this.exchange(t,Math.floor(t/2)),t=Math.floor(t/2)}sink(t){for(;2*t<=this.numberOfElements;){let n=2*t;if(n<this.numberOfElements&&this.less(n,n+1)&&n++,!this.less(t,n))break;this.exchange(t,n),t=n}}getValueAt(t){return this.getElementValue(this.priorityQueue[t])}less(t,n){return this.getValueAt(t)<this.getValueAt(n)}exchange(t,n){let s=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[n],this.priorityQueue[n]=s}};function y4(e,t,n,s){return{y:s.get(e,t,n),x:s.get(e,t,n+K5e)}}function A4(e,t,n){let{heatmapY:s,heatmapX:r,id:a}=e,{y:o,x:i}=y4(s,r,a,n);return{x:e.heatmapX*t+i,y:e.heatmapY*t+o}}function x4(e,t,n){return e<t?t:e>n?n:e}function _E(e,t,n,s){let r=n-e,a=s-t;return r*r+a*a}function b4(e,t){return{x:e.x+t.x,y:e.y+t.y}}var Lr,J5e=["MobilenetV1/offset_2/BiasAdd","MobilenetV1/heatmap_2/BiasAdd","MobilenetV1/displacement_fwd_2/BiasAdd","MobilenetV1/displacement_bwd_2/BiasAdd"],p1=1,Nd=16,Q5e=50**2;function DE(e,t,n,s,r,a,o=2){let i=y=>({y:a.get(y.y,y.x,e),x:a.get(y.y,y.x,a.shape[2]/2+e)}),l=(y,x,A)=>({y:x4(Math.round(y.y/Nd),0,x-1),x:x4(Math.round(y.x/Nd),0,A-1)}),[u,c]=s.shape,p=l(t.position,u,c),d=i(p),f=b4(t.position,d);for(let y=0;y<o;y++){let x=l(f,u,c),A=y4(x.y,x.x,n,r);f=b4({x:x.x*Nd,y:x.y*Nd},{x:A.x,y:A.y})}let m=l(f,u,c),g=s.get(m.y,m.x,n);return{position:f,part:Yh[n],score:g}}function exe(e,t,n,s,r){let a=NE.map(([d,h])=>[Zh[d],Zh[h]]),o=a.map(([,d])=>d),i=a.map(([d])=>d),l=t.shape[2],u=o.length,c=new Array(l),p=A4(e.part,Nd,n);c[e.part.id]={score:e.score,part:Yh[e.part.id],position:p};for(let d=u-1;d>=0;--d){let h=o[d],f=i[d];c[h]&&!c[f]&&(c[f]=DE(d,c[h],f,t,n,r))}for(let d=0;d<u;++d){let h=i[d],f=o[d];c[h]&&!c[f]&&(c[f]=DE(d,c[h],f,t,n,s))}return c}function txe(e,t,n,s,r){let[a,o]=r.shape,i=!0,l=Math.max(n-p1,0),u=Math.min(n+p1+1,a);for(let c=l;c<u;++c){let p=Math.max(s-p1,0),d=Math.min(s+p1+1,o);for(let h=p;h<d;++h)if(r.get(c,h,e)>t){i=!1;break}if(!i)break}return i}function nxe(e,t){let[n,s,r]=t.shape,a=new d1(n*s*r,({score:o})=>o);for(let o=0;o<n;++o)for(let i=0;i<s;++i)for(let l=0;l<r;++l){let u=t.get(o,i,l);u<e||txe(l,u,o,i,t)&&a.enqueue({score:u,part:{heatmapY:o,heatmapX:i,id:l}})}return a}function $E(e,{x:t,y:n},s){return e.some(({keypoints:r})=>{var o;let a=(o=r[s])==null?void 0:o.position;return a?_E(n,t,a.y,a.x)<=Q5e:!1})}function sxe(e,t){return t.reduce((s,{position:r,score:a},o)=>($E(e,r,o)||(s+=a),s),0)/t.length}function rxe(e,t,n,s,r,a){let o=[],i=nxe(a,t);for(;o.length<r&&!i.empty();){let l=i.dequeue(),u=A4(l.part,Nd,e);if($E(o,u,l.part.id))continue;let c=exe(l,t,e,n,s);c=c.filter(h=>h.score>a);let p=sxe(o,c),d=EE(c);p>a&&o.push({keypoints:c,box:d,score:Math.round(100*p)/100})}return o}async function v4(e,t){let n=J(()=>{if(!Lr.inputs[0].shape)return[];let o=Ne.resizeBilinear(e,[Lr.inputs[0].shape[2],Lr.inputs[0].shape[1]]),i=he(pe(ge(o,"float32"),127.5),1),u=Lr.execute(i,J5e).map(c=>rt(c,[0]));return u[1]=Cn(u[1]),u}),s=await Promise.all(n.map(o=>o.buffer()));for(let o of n)ne(o);let r=await rxe(s[0],s[1],s[2],s[3],t.body.maxDetected,t.body.minConfidence);return Lr.inputs[0].shape?RE(r,[e.shape[1],e.shape[2]],[Lr.inputs[0].shape[2],Lr.inputs[0].shape[1]]):[]}async function PE(e){return!Lr||fe.initial?Lr=await qe(e.body.modelPath):e.debug&&ie("cached model:",Lr.modelUrl),Lr}var ta,w4=!1;async function k4(e){return!ta||fe.initial?ta=await qe(e.segmentation.modelPath):e.debug&&ie("cached model:",ta.modelUrl),ta}async function OE(e,t,n){var m,g;if(w4)return{data:[],canvas:null,alpha:null};w4=!0,ta||await k4(n);let s=await md(e,n),r=((m=s.tensor)==null?void 0:m.shape[2])||0,a=((g=s.tensor)==null?void 0:g.shape[1])||0;if(!s.tensor)return{data:[],canvas:null,alpha:null};let o={};o.resize=Ne.resizeBilinear(s.tensor,[ta.inputs[0].shape?ta.inputs[0].shape[1]:0,ta.inputs[0].shape?ta.inputs[0].shape[2]:0],!1),ne(s.tensor),o.norm=pe(o.resize,nt.tf255),o.res=ta.execute(o.norm),o.squeeze=rt(o.res,0),o.squeeze.shape[2]===2?(o.softmax=Yl(o.squeeze),[o.bg,o.fg]=es(o.softmax,2),o.expand=Kt(o.fg,2),o.pad=Kt(o.expand,0),o.crop=Ne.cropAndResize(o.pad,[[0,0,.5,.5]],[0],[r,a]),o.data=rt(o.crop,0)):o.data=Ne.resizeBilinear(o.squeeze,[a,r]);let i=Array.from(await o.data.data());if(fe.node&&!fe.Canvas&&typeof ImageData=="undefined")return n.debug&&ie("canvas support missing"),Object.keys(o).forEach(y=>ne(o[y])),{data:i,canvas:null,alpha:null};let l=is(r,a);Ys&&await Ys.toPixels(o.data,l);let u=l.getContext("2d");n.segmentation.blur&&n.segmentation.blur>0&&(u.filter=`blur(${n.segmentation.blur}px)`);let c=u.getImageData(0,0,r,a),p=is(r,a),d=p.getContext("2d");s.canvas&&d.drawImage(s.canvas,0,0),d.globalCompositeOperation="darken",n.segmentation.blur&&n.segmentation.blur>0&&(d.filter=`blur(${n.segmentation.blur}px)`),d.drawImage(l,0,0),d.globalCompositeOperation="source-over",d.filter="none";let h=d.getImageData(0,0,r,a);for(let y=0;y<r*a;y++)h.data[4*y+3]=c.data[4*y+0];d.putImageData(h,0,0);let f=null;if(t&&p){f=is(r,a);let y=await md(t,n);ne(y.tensor);let x=f.getContext("2d");x.drawImage(y.canvas,0,0,f.width,f.height),x.drawImage(p,0,0)}return Object.keys(o).forEach(y=>ne(o[y])),w4=!1,{data:i,canvas:p,alpha:l}}var Jh=class{constructor(){me(this,"ssrnetage",null);me(this,"gear",null);me(this,"blazeposedetect",null);me(this,"blazepose",null);me(this,"centernet",null);me(this,"efficientpose",null);me(this,"mobilefacenet",null);me(this,"emotion",null);me(this,"facedetect",null);me(this,"faceiris",null);me(this,"facemesh",null);me(this,"faceres",null);me(this,"ssrnetgender",null);me(this,"handpose",null);me(this,"handskeleton",null);me(this,"handtrack",null);me(this,"liveness",null);me(this,"movenet",null);me(this,"nanodet",null);me(this,"posenet",null);me(this,"segmentation",null);me(this,"antispoof",null)}},I4=e=>{let t=0,n=0,s=0;for(let a of Object.values(Fr))t+=a.sizeFromManifest,n+=a.sizeLoadedWeights,s+=a.sizeDesired;let r=s>0?n/s:0;return{numLoadedModels:Object.values(Fr).length,numEnabledModels:void 0,numDefinedModels:Object.keys(e.models).length,percentageLoaded:r,totalSizeFromManifest:t,totalSizeWeights:n,totalSizeLoading:s,totalSizeEnabled:void 0,modelStats:Object.values(Fr)}};function h1(e){for(let t of Object.keys(e.models))e.models[t]=null}async function S4(e){var t,n,s,r,a,o,i,l,u,c,p,d,h,f,m,g,y,x,A,b,w,k,S,E,R,P,_,$,T,F,G;fe.initial&&h1(e),e.config.hand.enabled&&(!e.models.handpose&&((n=(t=e.config.hand.detector)==null?void 0:t.modelPath)==null?void 0:n.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await s4(e.config)),!e.models.handskeleton&&e.config.hand.landmarks&&((r=(s=e.config.hand.detector)==null?void 0:s.modelPath)==null?void 0:r.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await s4(e.config))),e.config.body.enabled&&!e.models.blazepose&&((o=(a=e.config.body)==null?void 0:a.modelPath)==null?void 0:o.includes("blazepose"))&&(e.models.blazepose=uN(e.config)),e.config.body.enabled&&!e.models.blazeposedetect&&e.config.body.detector&&e.config.body.detector.modelPath&&(e.models.blazeposedetect=lN(e.config)),e.config.body.enabled&&!e.models.efficientpose&&((l=(i=e.config.body)==null?void 0:i.modelPath)==null?void 0:l.includes("efficientpose"))&&(e.models.efficientpose=mN(e.config)),e.config.body.enabled&&!e.models.movenet&&((c=(u=e.config.body)==null?void 0:u.modelPath)==null?void 0:c.includes("movenet"))&&(e.models.movenet=kE(e.config)),e.config.body.enabled&&!e.models.posenet&&((d=(p=e.config.body)==null?void 0:p.modelPath)==null?void 0:d.includes("posenet"))&&(e.models.posenet=PE(e.config)),e.config.face.enabled&&!e.models.facedetect&&(e.models.facedetect=QT(e.config)),e.config.face.enabled&&((h=e.config.face.antispoof)==null?void 0:h.enabled)&&!e.models.antispoof&&(e.models.antispoof=BT(e.config)),e.config.face.enabled&&((f=e.config.face.liveness)==null?void 0:f.enabled)&&!e.models.liveness&&(e.models.liveness=yE(e.config)),e.config.face.enabled&&((m=e.config.face.description)==null?void 0:m.enabled)&&!e.models.faceres&&(e.models.faceres=BN(e.config)),e.config.face.enabled&&((g=e.config.face.emotion)==null?void 0:g.enabled)&&!e.models.emotion&&(e.models.emotion=xN(e.config)),e.config.face.enabled&&((y=e.config.face.iris)==null?void 0:y.enabled)&&!((x=e.config.face.attention)!=null&&x.enabled)&&!e.models.faceiris&&(e.models.faceiris=EN(e.config)),e.config.face.enabled&&((A=e.config.face.mesh)==null?void 0:A.enabled)&&!e.models.facemesh&&(e.models.facemesh=FN(e.config)),e.config.face.enabled&&((b=e.config.face.gear)==null?void 0:b.enabled)&&!e.models.gear&&(e.models.gear=TT(e.config)),e.config.face.enabled&&((w=e.config.face.ssrnet)==null?void 0:w.enabled)&&!e.models.ssrnetage&&(e.models.ssrnetage=DT(e.config)),e.config.face.enabled&&((k=e.config.face.ssrnet)==null?void 0:k.enabled)&&!e.models.ssrnetgender&&(e.models.ssrnetgender=OT(e.config)),e.config.face.enabled&&((S=e.config.face.mobilefacenet)==null?void 0:S.enabled)&&!e.models.mobilefacenet&&(e.models.mobilefacenet=IN(e.config)),e.config.hand.enabled&&!e.models.handtrack&&((R=(E=e.config.hand.detector)==null?void 0:E.modelPath)==null?void 0:R.includes("handtrack"))&&(e.models.handtrack=pE(e.config)),e.config.hand.enabled&&e.config.hand.landmarks&&!e.models.handskeleton&&((_=(P=e.config.hand.detector)==null?void 0:P.modelPath)==null?void 0:_.includes("handtrack"))&&(e.models.handskeleton=hE(e.config)),e.config.object.enabled&&!e.models.centernet&&((T=($=e.config.object)==null?void 0:$.modelPath)==null?void 0:T.includes("centernet"))&&(e.models.centernet=pN(e.config)),e.config.object.enabled&&!e.models.nanodet&&((G=(F=e.config.object)==null?void 0:F.modelPath)==null?void 0:G.includes("nanodet"))&&(e.models.nanodet=CE(e.config)),e.config.segmentation.enabled&&!e.models.segmentation&&(e.models.segmentation=k4(e.config));for await(let q of Object.keys(e.models))e.models[q]&&typeof e.models[q]!="undefined"&&(e.models[q]=await e.models[q])}async function C4(e){let t=["const","placeholder","noop","pad","squeeze","add","sub","mul","div"];for(let n of Object.keys(e.models)){let s=e.models[n];if(!s)continue;let r=[],a=s==null?void 0:s.executor;if(a&&a.graph.nodes)for(let i of Object.values(a.graph.nodes)){let l=i.op.toLowerCase();r.includes(l)||r.push(l)}else!a&&e.config.debug&&ie("model signature not determined:",n);let o=[];for(let i of r)!t.includes(i)&&!e.env.kernels.includes(i)&&!e.env.kernels.includes(i.replace("_",""))&&!e.env.kernels.includes(i.replace("native",""))&&!e.env.kernels.includes(i.replace("v2",""))&&o.push(i);e.config.debug&&o.length>0&&ie("model validation failed:",n,o)}}var Pt={name:"humangl",priority:999,canvas:null,gl:null,extensions:[],webGLattr:{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!1,desynchronized:!0}};function axe(){let e=Pt.gl;!e||(Pt.extensions=e.getSupportedExtensions())}async function zE(e){var t;if(e.config.backend==="humangl"&&(Pt.name in sn().registry&&(!Pt.gl||!Pt.gl.getParameter(Pt.gl.VERSION))&&(ie("error: humangl backend invalid context"),h1(e)),!Oy(Pt.name))){try{Pt.canvas=await is(100,100)}catch(s){ie("error: cannot create canvas:",s);return}try{if(Pt.gl=(t=Pt.canvas)==null?void 0:t.getContext("webgl2",Pt.webGLattr),!Pt.gl.getParameter(Pt.gl.VERSION).includes("2.0")){ie("override: using fallback webgl backend as webgl 2.0 is not detected"),e.config.backend="webgl";return}Pt.canvas&&(Pt.canvas.addEventListener("webglcontextlost",async r=>{throw ie("error: humangl:",r.type),ie("possible browser memory leak using webgl or conflict with multiple backend registrations"),e.emit("error"),new Error("backend error: webgl context lost")}),Pt.canvas.addEventListener("webglcontextrestored",r=>{ie("error: humangl context restored:",r)}),Pt.canvas.addEventListener("webglcontextcreationerror",r=>{ie("error: humangl context create:",r)}))}catch(s){ie("error: cannot get WebGL context:",s);return}try{A2(2,Pt.gl)}catch(s){ie("error: cannot set WebGL context:",s);return}try{let s=new Hu(Pt.gl);jl(Pt.name,()=>new od(s),Pt.priority)}catch(s){ie("error: cannot register WebGL backend:",s);return}try{jr("webgl").forEach(r=>{let a={...r,backendName:Pt.name};cr(a)})}catch(s){ie("error: cannot update WebGL backend registration:",s);return}let n=Zs().getGPGPUContext?Zs().getGPGPUContext().gl:null;if(n)ie(`humangl webgl version:${n.getParameter(n.VERSION)} renderer:${n.getParameter(n.RENDERER)}`);else{ie("error: no current gl context:",n,Pt.gl);return}try{X().flagRegistry.WEBGL_VERSION&&X().set("WEBGL_VERSION",2)}catch(s){ie("error: cannot set WebGL backend flags:",s);return}axe(),ie("backend registered:",Pt.name)}}function oxe(){if(!fe.kernels.includes("mod")){let e={kernelName:"Mod",backendName:ss(),kernelFunc:t=>J(()=>he(t.inputs.a,L(pe(t.inputs.a,t.inputs.b),t.inputs.b)))};cr(e),fe.kernels.push("mod")}if(!fe.kernels.includes("floormod")){let e={kernelName:"FloorMod",backendName:ss(),kernelFunc:t=>J(()=>Lc(t.inputs.a/t.inputs.b)*t.inputs.b+Zl(t.inputs.a,t.inputs.b))};cr(e),fe.kernels.push("floormod")}}async function m1(e,t=!1){if(e.state="backend",t||fe.initial||e.config.backend&&e.config.backend.length>0&&ss()!==e.config.backend){let n=ue();if(e.config.backend&&e.config.backend.length>0){if(typeof window=="undefined"&&typeof WorkerGlobalScope!="undefined"&&e.config.debug&&e.config.debug&&ie("running inside web worker"),fe.browser&&e.config.backend==="tensorflow"&&(e.config.debug&&ie("override: backend set to tensorflow while running in browser"),e.config.backend="humangl"),fe.node&&(e.config.backend==="webgl"||e.config.backend==="humangl")&&(e.config.debug&&ie(`override: backend set to ${e.config.backend} while running in nodejs`),e.config.backend="tensorflow"),fe.browser&&e.config.backend==="webgpu")if(typeof navigator=="undefined"||typeof navigator.gpu=="undefined")ie("override: backend set to webgpu but browser does not support webgpu"),e.config.backend="humangl";else{let r=await navigator.gpu.requestAdapter();if(e.config.debug&&ie("enumerated webgpu adapter:",r),!r)ie("override: backend set to webgpu but browser reports no available gpu"),e.config.backend="humangl";else{let a="requestAdapterInfo"in r?await r.requestAdapterInfo():void 0;ie("webgpu adapter info:",a)}}e.config.backend==="humangl"&&await zE(e);let s=Object.keys(sn().registryFactory);if(e.config.debug&&ie("available backends:",s),s.includes(e.config.backend)||(ie(`error: backend ${e.config.backend} not found in registry`),e.config.backend=fe.node?"tensorflow":"webgl",e.config.debug&&ie(`override: setting backend ${e.config.backend}`)),e.config.debug&&ie("setting backend:",e.config.backend),e.config.backend==="wasm"){if(X().flagRegistry.CANVAS2D_WILL_READ_FREQUENTLY&&X().set("CANVAS2D_WILL_READ_FREQUENTLY",!0),e.config.debug&&ie("wasm path:",e.config.wasmPath),typeof(je==null?void 0:je.setWasmPaths)!="undefined")await tb(e.config.wasmPath,e.config.wasmPlatformFetch);else throw new Error("backend error: attempting to use wasm backend but wasm path is not set");let r=await X().getAsync("WASM_HAS_SIMD_SUPPORT"),a=await X().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");e.config.debug&&ie(`wasm execution: ${r?"SIMD":"no SIMD"} ${a?"multithreaded":"singlethreaded"}`),e.config.debug&&!r&&ie("warning: wasm simd support is not enabled")}try{await Fy(e.config.backend),await zc(),ET()}catch(r){return ie("error: cannot set backend:",e.config.backend,r),!1}}if(ss()==="humangl"&&(X().flagRegistry.CHECK_COMPUTATION_FOR_ERRORS&&X().set("CHECK_COMPUTATION_FOR_ERRORS",!1),X().flagRegistry.WEBGL_CPU_FORWARD&&X().set("WEBGL_CPU_FORWARD",!0),X().flagRegistry.WEBGL_USE_SHAPES_UNIFORMS&&X().set("WEBGL_USE_SHAPES_UNIFORMS",!0),X().flagRegistry.CPU_HANDOFF_SIZE_THRESHOLD&&X().set("CPU_HANDOFF_SIZE_THRESHOLD",256),X().flagRegistry.WEBGL_EXP_CONV&&X().set("WEBGL_EXP_CONV",!0),X().flagRegistry.USE_SETTIMEOUTWPM&&X().set("USE_SETTIMEOUTWPM",!0),typeof e.config.deallocate!="undefined"&&e.config.deallocate&&(ie("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),X().set("WEBGL_DELETE_TEXTURE_THRESHOLD",0)),Zs().getGPGPUContext)){let s=await Zs().getGPGPUContext().gl;e.config.debug&&ie(`gl version:${s.getParameter(s.VERSION)} renderer:${s.getParameter(s.RENDERER)}`)}ss(),$y(),await zc(),e.performance.initBackend=Math.trunc(ue()-n),e.config.backend=ss(),await fe.updateBackend(),oxe()}return!0}function s1(e,t){for(let n of e){let s={kernelName:n,backendName:t.backend,kernelFunc:()=>{t.debug&&ie("kernelFunc",n,t.backend)}};cr(s)}fe.kernels=jr(ss()).map(n=>n.kernelName.toLowerCase())}var $4={};oa($4,{all:()=>D4,body:()=>Rd,canvas:()=>_4,face:()=>Ed,gesture:()=>$d,hand:()=>_d,object:()=>Dd,options:()=>Vn,person:()=>R4});var tr=e=>{if(!e)ie("draw error: invalid canvas");else if(!e.getContext)ie("draw error: canvas context not defined");else{let t=e.getContext("2d");if(!t)ie("draw error: cannot get canvas context");else return t}return null},yu=e=>Math.round(e*180/Math.PI),$a=(e,t)=>{if(!t.useDepth||typeof e=="undefined")return t.color;let n=Uint8ClampedArray.from([127+2*e,127-2*e,255]);return`rgba(${n[0]}, ${n[1]}, ${n[2]}, ${t.alpha})`};function Pa(e,t,n,s,r){e.fillStyle=$a(s,r),e.beginPath(),e.arc(t,n,r.pointSize,0,2*Math.PI),e.fill()}function na(e,t,n,s,r,a){if(e.beginPath(),e.lineWidth=a.lineWidth,a.useCurves){let o=(t+t+s)/2,i=(n+n+r)/2;e.ellipse(o,i,s/2,r/2,0,0,2*Math.PI)}else e.moveTo(t+a.roundRect,n),e.lineTo(t+s-a.roundRect,n),e.quadraticCurveTo(t+s,n,t+s,n+a.roundRect),e.lineTo(t+s,n+r-a.roundRect),e.quadraticCurveTo(t+s,n+r,t+s-a.roundRect,n+r),e.lineTo(t+a.roundRect,n+r),e.quadraticCurveTo(t,n+r,t,n+r-a.roundRect),e.lineTo(t,n+a.roundRect),e.quadraticCurveTo(t,n,t+a.roundRect,n),e.closePath();e.stroke()}function T4(e,t,n){if(!(t.length<2)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let s of t)e.strokeStyle=$a(s[2]||0,n),e.lineTo(Math.trunc(s[0]),Math.trunc(s[1]));e.stroke(),n.fillPolygons&&(e.closePath(),e.fill())}}function BE(e,t,n){if(!(t.length<2)){if(e.lineWidth=n.lineWidth,!n.useCurves||t.length<=2){T4(e,t,n);return}e.moveTo(t[0][0],t[0][1]);for(let s=0;s<t.length-2;s++){let r=(t[s][0]+t[s+1][0])/2,a=(t[s][1]+t[s+1][1])/2;e.quadraticCurveTo(t[s][0],t[s][1],r,a)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),n.fillPolygons&&(e.closePath(),e.fill())}}function N4(e,t,n,s=5){let r,a,o;e.beginPath(),e.moveTo(t[0],t[1]),e.lineTo(n[0],n[1]),r=Math.atan2(n[1]-t[1],n[0]-t[0]),a=s*Math.cos(r)+n[0],o=s*Math.sin(r)+n[1],e.moveTo(a,o),r+=1/3*(2*Math.PI),a=s*Math.cos(r)+n[0],o=s*Math.sin(r)+n[1],e.lineTo(a,o),r+=1/3*(2*Math.PI),a=s*Math.cos(r)+n[0],o=s*Math.sin(r)+n[1],e.lineTo(a,o),e.closePath(),e.stroke(),e.fill()}var Vn={color:"rgba(173, 216, 230, 0.6)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",alpha:.5,font:'small-caps 16px "Segoe UI"',lineHeight:18,lineWidth:4,pointSize:2,roundRect:8,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawAttention:!0,drawGestures:!0,drawPolygons:!0,drawGaze:!0,fillPolygons:!1,useDepth:!0,useCurves:!1};var gt;function lxe(e,t){if(gt.drawLabels){let n=[];if(n.push(`face: ${Math.trunc(100*e.score)}%`),e.genderScore&&n.push(`${e.gender||""} ${Math.trunc(100*e.genderScore)}%`),e.age&&n.push(`age: ${e.age||""}`),e.iris&&n.push(`distance: ${e.iris}`),e.real&&n.push(`real: ${Math.trunc(100*e.real)}%`),e.live&&n.push(`live: ${Math.trunc(100*e.live)}%`),e.emotion&&e.emotion.length>0){let s=e.emotion.map(r=>`${Math.trunc(100*r.score)}% ${r.emotion}`);s.length>3&&(s.length=3),n.push(s.join(" "))}e.rotation&&e.rotation.angle&&e.rotation.gaze&&(e.rotation.angle.roll&&n.push(`roll: ${yu(e.rotation.angle.roll)}\xB0 yaw:${yu(e.rotation.angle.yaw)}\xB0 pitch:${yu(e.rotation.angle.pitch)}\xB0`),e.rotation.gaze.bearing&&n.push(`gaze: ${yu(e.rotation.gaze.bearing)}\xB0`)),n.length===0&&n.push("face"),t.fillStyle=gt.color;for(let s=n.length-1;s>=0;s--){let r=Math.max(e.box[0],0),a=s*gt.lineHeight+e.box[1];gt.shadowColor&&gt.shadowColor!==""&&(t.fillStyle=gt.shadowColor,t.fillText(n[s],r+5,a+16)),t.fillStyle=gt.labelColor,t.fillText(n[s],r+4,a+15)}}}function uxe(e,t){if(e.annotations&&e.annotations.leftEyeIris&&e.annotations.leftEyeIris[0]){t.strokeStyle=gt.useDepth?"rgba(255, 200, 255, 0.3)":gt.color,t.beginPath();let n=Math.abs(e.annotations.leftEyeIris[3][0]-e.annotations.leftEyeIris[1][0])/2,s=Math.abs(e.annotations.leftEyeIris[4][1]-e.annotations.leftEyeIris[2][1])/2;t.ellipse(e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1],n,s,0,0,2*Math.PI),t.stroke(),gt.fillPolygons&&(t.fillStyle=gt.useDepth?"rgba(255, 255, 200, 0.3)":gt.color,t.fill())}if(e.annotations&&e.annotations.rightEyeIris&&e.annotations.rightEyeIris[0]){t.strokeStyle=gt.useDepth?"rgba(255, 200, 255, 0.3)":gt.color,t.beginPath();let n=Math.abs(e.annotations.rightEyeIris[3][0]-e.annotations.rightEyeIris[1][0])/2,s=Math.abs(e.annotations.rightEyeIris[4][1]-e.annotations.rightEyeIris[2][1])/2;t.ellipse(e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1],n,s,0,0,2*Math.PI),t.stroke(),gt.fillPolygons&&(t.fillStyle=gt.useDepth?"rgba(255, 255, 200, 0.3)":gt.color,t.fill())}}function cxe(e,t){var n;if(gt.drawGaze&&((n=e.rotation)==null?void 0:n.angle)&&typeof Path2D!="undefined"){t.strokeStyle="pink";let s=e.box[0]+e.box[2]/2-e.box[3]*yu(e.rotation.angle.yaw)/90,r=e.box[1]+e.box[3]/2+e.box[2]*yu(e.rotation.angle.pitch)/90,a=new Path2D(`
       M ${e.box[0]+e.box[2]/2} ${e.box[1]}
       C
         ${s} ${e.box[1]},
@@ -6930,7 +6930,7 @@ return a / b;`,Gie=`
         ${e.box[0]} ${r},
         ${e.box[0]+e.box[2]} ${r},
         ${e.box[0]+e.box[2]} ${e.box[1]+e.box[3]/2}
-    `);t.stroke(o),t.stroke(a)}}function dxe(e,t){var n,s,r,a;if(gt.drawGaze&&((s=(n=e.rotation)==null?void 0:n.gaze)==null?void 0:s.strength)&&((a=(r=e.rotation)==null?void 0:r.gaze)==null?void 0:a.bearing)&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let o=[e.annotations.leftEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.leftEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];N4(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[o[0],o[1]],4);let i=[e.annotations.rightEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.rightEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];N4(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[i[0],i[1]],4)}}function pxe(e,t){if(gt.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let n=0;n<lu.length/3;n++){let s=[lu[n*3+0],lu[n*3+1],lu[n*3+2]].map(r=>e.mesh[r]);T4(t,s,gt)}uxe(e,t)}}function hxe(e,t){if(gt.drawPoints&&e.mesh.length>=468)for(let n=0;n<e.mesh.length;n++)Fa(t,e.mesh[n][0],e.mesh[n][1],e.mesh[n][2],gt),gt.drawAttention&&(Xh.includes(n)&&Fa(t,e.mesh[n][0],e.mesh[n][1],e.mesh[n][2]+127,gt),du.includes(n)&&Fa(t,e.mesh[n][0],e.mesh[n][1],e.mesh[n][2]-127,gt),pu.includes(n)&&Fa(t,e.mesh[n][0],e.mesh[n][1],e.mesh[n][2]-127,gt))}function fxe(e,t){gt.drawBoxes&&sa(t,e.box[0],e.box[1],e.box[2],e.box[3],gt)}async function Rd(e,t,n){if(gt=Xt(Vn,n),!t||!e)return;let s=tr(e);if(!!s){s.font=gt.font,s.strokeStyle=gt.color,s.fillStyle=gt.color;for(let r of t)fxe(r,s),lxe(r,s),r.mesh&&r.mesh.length>0&&(hxe(r,s),pxe(r,s),cxe(r,s),dxe(r,s))}}async function _d(e,t,n){var a;let s=Xt(Vn,n);if(!t||!e)return;let r=tr(e);if(!!r){r.lineJoin="round";for(let o=0;o<t.length;o++){if(r.strokeStyle=s.color,r.fillStyle=s.color,r.lineWidth=s.lineWidth,r.font=s.font,s.drawBoxes&&t[o].box&&((a=t[o].box)==null?void 0:a.length)===4&&(sa(r,t[o].box[0],t[o].box[1],t[o].box[2],t[o].box[3],s),s.drawLabels&&(s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(`body ${100*t[o].score}%`,t[o].box[0]+3,1+t[o].box[1]+s.lineHeight,t[o].box[2])),r.fillStyle=s.labelColor,r.fillText(`body ${100*t[o].score}%`,t[o].box[0]+2,0+t[o].box[1]+s.lineHeight,t[o].box[2]))),s.drawPoints&&t[o].keypoints)for(let i=0;i<t[o].keypoints.length;i++)!t[o].keypoints[i].score||t[o].keypoints[i].score===0||(r.fillStyle=Pa(t[o].keypoints[i].position[2],s),Fa(r,t[o].keypoints[i].position[0],t[o].keypoints[i].position[1],0,s));if(s.drawLabels&&t[o].keypoints){r.font=s.font;for(let i of t[o].keypoints)!i.score||i.score===0||(r.fillStyle=Pa(i.position[2],s),r.fillText(`${i.part} ${Math.trunc(100*i.score)}%`,i.position[0]+4,i.position[1]+4))}if(s.drawPolygons&&t[o].keypoints&&t[o].annotations)for(let i of Object.values(t[o].annotations))for(let l of i)BE(r,l,s)}}}async function Dd(e,t,n){let s=Xt(Vn,n);if(!t||!e)return;let r=tr(e);if(!!r){r.lineJoin="round",r.font=s.font;for(let a of t){if(s.drawBoxes&&(r.strokeStyle=s.color,r.fillStyle=s.color,sa(r,a.box[0],a.box[1],a.box[2],a.box[3],s),s.drawLabels&&(s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(`hand:${Math.trunc(100*a.score)}%`,a.box[0]+3,1+a.box[1]+s.lineHeight,a.box[2])),r.fillStyle=s.labelColor,r.fillText(`hand:${Math.trunc(100*a.score)}%`,a.box[0]+2,0+a.box[1]+s.lineHeight,a.box[2])),r.stroke()),s.drawPoints&&a.keypoints&&a.keypoints.length>0)for(let o of a.keypoints)r.fillStyle=Pa(o[2],s),Fa(r,o[0],o[1],0,s);if(s.drawLabels&&a.annotations){let o=(i,l)=>{if(!i||i.length===0||!i[0])return;let u=i[i.length-1][2]||-256;r.fillStyle=Pa(u,s),r.fillText(l,i[i.length-1][0]+4,i[i.length-1][1]+4)};r.font=s.font,o(a.annotations.index,"index"),o(a.annotations.middle,"middle"),o(a.annotations.ring,"ring"),o(a.annotations.pinky,"pinky"),o(a.annotations.thumb,"thumb"),o(a.annotations.palm,"palm")}if(s.drawPolygons&&a.annotations){let o=i=>{if(!(!i||i.length===0||!i[0]))for(let l=0;l<i.length;l++){r.beginPath();let u=i[l][2]||0;r.strokeStyle=Pa(l*u,s),r.moveTo(i[l>0?l-1:0][0],i[l>0?l-1:0][1]),r.lineTo(i[l][0],i[l][1]),r.stroke()}};r.lineWidth=s.lineWidth,o(a.annotations.index),o(a.annotations.middle),o(a.annotations.ring),o(a.annotations.pinky),o(a.annotations.thumb)}}}}async function $d(e,t,n){let s=Xt(Vn,n);if(!t||!e)return;let r=tr(e);if(!!r){r.lineJoin="round",r.font=s.font;for(let a of t)if(s.drawBoxes){if(r.strokeStyle=s.color,r.fillStyle=s.color,sa(r,a.box[0],a.box[1],a.box[2],a.box[3],s),s.drawLabels){let o=`${a.label} ${Math.round(100*a.score)}%`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(o,a.box[0]+3,1+a.box[1]+s.lineHeight,a.box[2])),r.fillStyle=s.labelColor,r.fillText(o,a.box[0]+2,0+a.box[1]+s.lineHeight,a.box[2])}r.stroke()}}}async function Pd(e,t,n){let s=Xt(Vn,n);if(!(!t||!e)&&s.drawGestures){let r=tr(e);if(!r)return;r.font=s.font,r.fillStyle=s.color;let a=1;for(let o=0;o<t.length;o++){let i=[],l=[];if([i,l]=Object.entries(t[o]),l.length>1&&l[1].length>0){let u=i[1]>0?`#${i[1]}`:"",c=`${i[0]} ${u}: ${l[1]}`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(c,8,2+a*s.lineHeight)),r.fillStyle=s.labelColor,r.fillText(c,6,0+a*s.lineHeight),a+=1}}}}var E4=0;async function R4(e,t,n){let s=Xt(Vn,n);if(!t||!e)return;let r=tr(e);if(!!r){r.lineJoin="round",r.font=s.font;for(let a=0;a<t.length;a++)if(s.drawBoxes){if(r.strokeStyle=s.color,r.fillStyle=s.color,sa(r,t[a].box[0],t[a].box[1],t[a].box[2],t[a].box[3],s),s.drawLabels){let o=`person #${a}`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(o,t[a].box[0]+3,1+t[a].box[1]+s.lineHeight,t[a].box[2])),r.fillStyle=s.labelColor,r.fillText(o,t[a].box[0]+2,0+t[a].box[1]+s.lineHeight,t[a].box[2])}r.stroke()}}}async function _4(e,t){if(!e||!t)return;let n=tr(t);!n||n.drawImage(e,0,0)}async function D4(e,t,n){if(!t||!t.performance||!t||!e)return null;let s=ue(),r=Xt(Vn,n),a=Promise.all([Rd(e,t.face,r),_d(e,t.body,r),Dd(e,t.hand,r),$d(e,t.object,r),Pd(e,t.gesture,r)]);return E4=fe.perfadd?E4+Math.round(ue()-s):Math.round(ue()-s),t.performance.draw=E4,a}var Fd=.1,P4=.5;function mxe(e,t,n){let s=!1,r=n.length-1;for(let a=0;a<n.length;r=a++)n[a].y>t!=n[r].y>t&&e<(n[r].x-n[a].x)*(t-n[a].y)/(n[r].y-n[a].y)+n[a].x&&(s=!s);return s}async function WE(e){if(!e.tensor||!e.mesh||e.mesh.length<100)return e.tensor;let t=e.tensor.shape[2]||0,n=e.tensor.shape[1]||0,s=await e.tensor.buffer(),r=[];for(let o of gr.silhouette)r.push({x:(e.mesh[o][0]-e.box[0])/e.box[2],y:(e.mesh[o][1]-e.box[1])/e.box[3]});Fd&&Fd>0&&(r=r.map(o=>({x:o.x>.5?o.x+Fd:o.x-Fd,y:o.y>.5?o.y+Fd:o.y-Fd})));for(let o=0;o<t;o++)for(let i=0;i<n;i++)mxe(o/t,i/t,r)||(s.set(P4*s.get(0,i,o,0),0,i,o,0),s.set(P4*s.get(0,i,o,1),0,i,o,1),s.set(P4*s.get(0,i,o,2),0,i,o,2));let a=s.toTensor();return ne(s),a}var yxe=e=>{let t=(p,d)=>Math.atan2(p[1]-d[1],p[0]-d[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let n=[0,-.1],s=1,r=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),a=r?e.mesh[473]:e.mesh[468],o=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],i=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],l=[(o[0]-a[0])/i[0]-n[0],s*(a[1]-o[1])/i[1]-n[1]],u=Math.sqrt(l[0]*l[0]+l[1]*l[1]);return u=Math.min(u,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],l)+Math.PI/2)%Math.PI,strength:u}},VE=(e,t)=>{let n=m=>{let g=Math.sqrt(m[0]*m[0]+m[1]*m[1]+m[2]*m[2]);return m[0]/=g,m[1]/=g,m[2]/=g,m},s=(m,g)=>{let y=m[0]-g[0],x=m[1]-g[1],A=m[2]-g[2];return[y,x,A]},r=(m,g)=>{let y=m[1]*g[2]-m[2]*g[1],x=m[2]*g[0]-m[0]*g[2],A=m[0]*g[1]-m[1]*g[0];return[y,x,A]},a=m=>{let[g,y,x,A,b,w,k,S,E]=m,R,P,_;return A<1?A>-1?(_=Math.asin(A),P=Math.atan2(-k,g),R=Math.atan2(-w,b)):(_=-Math.PI/2,P=-Math.atan2(S,E),R=0):(_=Math.PI/2,P=Math.atan2(S,E),R=0),isNaN(R)&&(R=0),isNaN(P)&&(P=0),isNaN(_)&&(_=0),{pitch:2*-R,yaw:2*-P,roll:2*-_}},o=e.meshRaw;if(!o||o.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let i=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,l=[o[10],o[152],o[234],o[454]].map(m=>[m[0]*t[0]/i,m[1]*t[1]/i,m[2]]),u=n(s(l[1],l[0])),c=n(s(l[3],l[2])),p=n(r(c,u));c=r(u,p);let d=[c[0],c[1],c[2],u[0],u[1],u[2],p[0],p[1],p[2]],h=a(d),f=o.length===478?yxe(e):{bearing:0,strength:0};return{angle:h,matrix:d,gaze:f}};var F4=async(e,t)=>{var h,f,m,g,y,x,A,b,w,k,S,E,R,P,_,$,T,F,G,q,z,K;let n=ue(),s,r,a,o,i,l,u,c,p=[];e.state="run:face";let d=await PN(t,e.config);if(e.performance.face=fe.perfadd?(e.performance.face||0)+Math.trunc(ue()-n):Math.trunc(ue()-n),!t.shape||t.shape.length!==4)return[];if(!d)return[];for(let B=0;B<d.length;B++){if(e.analyze("Get Face"),!d[B].tensor||d[B].tensor.isDisposedInternal){ie("Face object is disposed:",d[B].tensor);continue}if((h=e.config.face.detector)!=null&&h.mask){let ae=await WE(d[B]);ne(d[B].tensor),d[B].tensor=ae}let ee=d[B].mesh&&d[B].mesh.length>200?VE(d[B],[t.shape[2],t.shape[1]]):null;e.analyze("Start Emotion:"),e.config.async?o=(f=e.config.face.emotion)!=null&&f.enabled?Vb(d[B].tensor||ft([]),e.config,B,d.length):[]:(e.state="run:emotion",n=ue(),o=(m=e.config.face.emotion)!=null&&m.enabled?await Vb(d[B].tensor||ft([]),e.config,B,d.length):[],e.performance.emotion=fe.perfadd?(e.performance.emotion||0)+Math.trunc(ue()-n):Math.trunc(ue()-n)),e.analyze("End Emotion:"),e.analyze("Start AntiSpoof:"),e.config.async?l=(g=e.config.face.antispoof)!=null&&g.enabled?kb(d[B].tensor||ft([]),e.config,B,d.length):0:(e.state="run:antispoof",n=ue(),l=(y=e.config.face.antispoof)!=null&&y.enabled?await kb(d[B].tensor||ft([]),e.config,B,d.length):0,e.performance.antispoof=fe.perfadd?(e.performance.antispoof||0)+Math.trunc(ue()-n):Math.trunc(ue()-n)),e.analyze("End AntiSpoof:"),e.analyze("Start Liveness:"),e.config.async?u=(x=e.config.face.liveness)!=null&&x.enabled?l4(d[B].tensor||ft([]),e.config,B,d.length):0:(e.state="run:liveness",n=ue(),u=(A=e.config.face.liveness)!=null&&A.enabled?await l4(d[B].tensor||ft([]),e.config,B,d.length):0,e.performance.liveness=fe.perfadd?(e.performance.antispoof||0)+Math.trunc(ue()-n):Math.trunc(ue()-n)),e.analyze("End Liveness:"),e.analyze("Start GEAR:"),e.config.async?r=(b=e.config.face.gear)!=null&&b.enabled?gb(d[B].tensor||ft([]),e.config,B,d.length):null:(e.state="run:gear",n=ue(),r=(w=e.config.face.gear)!=null&&w.enabled?await gb(d[B].tensor||ft([]),e.config,B,d.length):null,e.performance.gear=Math.trunc(ue()-n)),e.analyze("End GEAR:"),e.analyze("Start SSRNet:"),e.config.async?(s=(k=e.config.face.ssrnet)!=null&&k.enabled?Ab(d[B].tensor||ft([]),e.config,B,d.length):null,a=(S=e.config.face.ssrnet)!=null&&S.enabled?vb(d[B].tensor||ft([]),e.config,B,d.length):null):(e.state="run:ssrnet",n=ue(),s=(E=e.config.face.ssrnet)!=null&&E.enabled?await Ab(d[B].tensor||ft([]),e.config,B,d.length):null,a=(R=e.config.face.ssrnet)!=null&&R.enabled?await vb(d[B].tensor||ft([]),e.config,B,d.length):null,e.performance.ssrnet=Math.trunc(ue()-n)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?i=(P=e.config.face.mobilefacenet)!=null&&P.enabled?Gb(d[B].tensor||ft([]),e.config,B,d.length):null:(e.state="run:mobilefacenet",n=ue(),i=(_=e.config.face.mobilefacenet)!=null&&_.enabled?await Gb(d[B].tensor||ft([]),e.config,B,d.length):null,e.performance.mobilefacenet=Math.trunc(ue()-n)),e.analyze("End MobileFaceNet:"),e.analyze("Start Description:"),e.config.async?c=($=e.config.face.description)!=null&&$.enabled?Zb(d[B].tensor||ft([]),e.config,B,d.length):null:(e.state="run:description",n=ue(),c=(T=e.config.face.description)!=null&&T.enabled?await Zb(d[B].tensor||ft([]),e.config,B,d.length):null,e.performance.description=fe.perfadd?(e.performance.description||0)+Math.trunc(ue()-n):Math.trunc(ue()-n)),e.analyze("End Description:"),e.config.async&&([s,a,o,i,c,r,l,u]=await Promise.all([s,a,o,i,c,r,l,u])),e.analyze("Finish Face:"),((F=e.config.face.ssrnet)==null?void 0:F.enabled)&&s&&a&&(c={...c,age:s.age,gender:a.gender,genderScore:a.genderScore}),((G=e.config.face.gear)==null?void 0:G.enabled)&&r&&(c={...c,age:r.age,gender:r.gender,genderScore:r.genderScore,race:r.race}),((q=e.config.face.mobilefacenet)==null?void 0:q.enabled)&&i&&(c.descriptor=i),(z=e.config.face.iris)!=null&&z.enabled;let Q=d[B].annotations&&d[B].annotations.leftEyeIris&&d[B].annotations.leftEyeIris[0]&&d[B].annotations.rightEyeIris&&d[B].annotations.rightEyeIris[0]&&d[B].annotations.leftEyeIris.length>0&&d[B].annotations.rightEyeIris.length>0&&d[B].annotations.leftEyeIris[0]!==null&&d[B].annotations.rightEyeIris[0]!==null?Math.max(Math.abs(d[B].annotations.leftEyeIris[3][0]-d[B].annotations.leftEyeIris[1][0]),Math.abs(d[B].annotations.rightEyeIris[4][1]-d[B].annotations.rightEyeIris[2][1]))/t.shape[2]:0,oe=(K=e.config.face.detector)!=null&&K.return?rt(d[B].tensor):null;ne(d[B].tensor),d[B].tensor&&delete d[B].tensor;let Y={...d[B],id:B};c!=null&&c.age&&(Y.age=c.age),c!=null&&c.gender&&(Y.gender=c.gender),c!=null&&c.genderScore&&(Y.genderScore=c==null?void 0:c.genderScore),c!=null&&c.descriptor&&(Y.embedding=c==null?void 0:c.descriptor),c!=null&&c.race&&(Y.race=c==null?void 0:c.race),o&&(Y.emotion=o),l&&(Y.real=l),u&&(Y.live=u),Q&&Q!==0&&(Y.iris=Math.trunc(500/Q/11.7)/100),ee&&(Y.rotation=ee),oe&&(Y.tensor=oe),p.push(Y),e.analyze("End Face")}return e.analyze("End FaceMesh:"),e.config.async&&(e.performance.face&&delete e.performance.face,e.performance.age&&delete e.performance.age,e.performance.gender&&delete e.performance.gender,e.performance.emotion&&delete e.performance.emotion),p};var UE=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){let s=e[n].keypoints.find(l=>l.part==="leftWrist"),r=e[n].keypoints.find(l=>l.part==="rightWrist"),a=e[n].keypoints.find(l=>l.part==="nose");a&&s&&r&&s.position[1]<a.position[1]&&r.position[1]<a.position[1]?t.push({body:n,gesture:"i give up"}):a&&s&&s.position[1]<a.position[1]?t.push({body:n,gesture:"raise left hand"}):a&&r&&r.position[1]<a.position[1]&&t.push({body:n,gesture:"raise right hand"});let o=e[n].keypoints.find(l=>l.part==="leftShoulder"),i=e[n].keypoints.find(l=>l.part==="rightShoulder");o&&i&&Math.abs(o.positionRaw[1]-i.positionRaw[1])>.1&&t.push({body:n,gesture:`leaning ${o.position[1]>i.position[1]?"left":"right"}`})}return t},GE=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++)if(e[n].mesh&&e[n].mesh.length>450){let s=(e[n].mesh[33][2]||0)-(e[n].mesh[263][2]||0),r=e[n].mesh[33][0]-e[n].mesh[263][0];Math.abs(s/r)<=.15?t.push({face:n,gesture:"facing center"}):t.push({face:n,gesture:`facing ${s<0?"left":"right"}`}),Math.abs(e[n].mesh[374][1]-e[n].mesh[386][1])/Math.abs(e[n].mesh[443][1]-e[n].mesh[450][1])<.2&&t.push({face:n,gesture:"blink left eye"}),Math.abs(e[n].mesh[145][1]-e[n].mesh[159][1])/Math.abs(e[n].mesh[223][1]-e[n].mesh[230][1])<.2&&t.push({face:n,gesture:"blink right eye"});let i=Math.min(100,500*Math.abs(e[n].mesh[13][1]-e[n].mesh[14][1])/Math.abs(e[n].mesh[10][1]-e[n].mesh[152][1]));i>10&&t.push({face:n,gesture:`mouth ${Math.trunc(i)}% open`});let l=e[n].mesh[152][2]||0;Math.abs(l)>10&&t.push({face:n,gesture:`head ${l<0?"up":"down"}`})}return t},HE=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){if(!e[n].annotations||!e[n].annotations.leftEyeIris||!e[n].annotations.leftEyeIris[0]||!e[n].annotations.rightEyeIris||!e[n].annotations.rightEyeIris[0])continue;let s=e[n].annotations.leftEyeIris[3][0]-e[n].annotations.leftEyeIris[1][0],r=e[n].annotations.leftEyeIris[4][1]-e[n].annotations.leftEyeIris[2][1],a=Math.abs(s*r),o=e[n].annotations.rightEyeIris[3][0]-e[n].annotations.rightEyeIris[1][0],i=e[n].annotations.rightEyeIris[4][1]-e[n].annotations.rightEyeIris[2][1],l=Math.abs(o*i),u=!1;Math.abs(a-l)/Math.max(a,l)<.25&&(u=!0,t.push({iris:n,gesture:"facing center"}));let p=Math.abs(e[n].mesh[263][0]-e[n].annotations.leftEyeIris[0][0])/e[n].box[2],d=Math.abs(e[n].mesh[33][0]-e[n].annotations.rightEyeIris[0][0])/e[n].box[2];(p>.06||d>.06)&&(u=!1),p>d?p>.05&&t.push({iris:n,gesture:"looking right"}):d>.05&&t.push({iris:n,gesture:"looking left"});let h=Math.abs(e[n].mesh[145][1]-e[n].annotations.rightEyeIris[0][1])/e[n].box[3],f=Math.abs(e[n].mesh[374][1]-e[n].annotations.leftEyeIris[0][1])/e[n].box[3];(f<.01||h<.01||f>.022||h>.022)&&(u=!1),(f<.01||h<.01)&&t.push({iris:n,gesture:"looking down"}),(f>.022||h>.022)&&t.push({iris:n,gesture:"looking up"}),u&&t.push({iris:n,gesture:"looking center"})}return t},jE=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){let s=[];if(e[n].annotations)for(let[r,a]of Object.entries(e[n].annotations))r!=="palmBase"&&Array.isArray(a)&&a[0]&&s.push({name:r.toLowerCase(),position:a[0]});if(s&&s.length>0){let r=s.reduce((o,i)=>(o.position[2]||0)<(i.position[2]||0)?o:i);t.push({hand:n,gesture:`${r.name} forward`});let a=s.reduce((o,i)=>o.position[1]<i.position[1]?o:i);t.push({hand:n,gesture:`${a.name} up`})}if(e[n].keypoints){let r=aE(e[n].keypoints);for(let a of r)t.push({hand:n,gesture:a.name})}}return t};var Ee={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null},O4=0;function qE(e,t){var o,i,l,u,c,p,d,h,f,m,g,y,x,A,b,w,k,S,E,R,P,_,$,T,F,G,q;let n=ue();if(!e)return{face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null};let s=Date.now()-e.timestamp,r=s<1e3?8-Math.log(s+1):1;if(e.canvas&&(Ee.canvas=e.canvas),e.error&&(Ee.error=e.error),!Ee.body||e.body.length!==Ee.body.length)Ee.body=JSON.parse(JSON.stringify(e.body));else for(let z=0;z<e.body.length;z++){let K=e.body[z].box.map((Y,ae)=>((r-1)*Ee.body[z].box[ae]+Y)/r),B=e.body[z].boxRaw.map((Y,ae)=>((r-1)*Ee.body[z].boxRaw[ae]+Y)/r),ee=e.body[z].keypoints.map((Y,ae)=>{var le,ye,we,Re,_e,Be,Ge,ot,dt;return{score:Y.score,part:Y.part,position:[Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].position[0]||0)+(Y.position[0]||0))/r:Y.position[0],Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].position[1]||0)+(Y.position[1]||0))/r:Y.position[1],Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].position[2]||0)+(Y.position[2]||0))/r:Y.position[2]],positionRaw:[Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].positionRaw[0]||0)+(Y.positionRaw[0]||0))/r:Y.positionRaw[0],Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].positionRaw[1]||0)+(Y.positionRaw[1]||0))/r:Y.positionRaw[1],Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].positionRaw[2]||0)+(Y.positionRaw[2]||0))/r:Y.positionRaw[2]],distance:[Ee.body[z].keypoints[ae]?((r-1)*(((le=Ee.body[z].keypoints[ae].distance)==null?void 0:le[0])||0)+(((ye=Y.distance)==null?void 0:ye[0])||0))/r:(we=Y.distance)==null?void 0:we[0],Ee.body[z].keypoints[ae]?((r-1)*(((Re=Ee.body[z].keypoints[ae].distance)==null?void 0:Re[1])||0)+(((_e=Y.distance)==null?void 0:_e[1])||0))/r:(Be=Y.distance)==null?void 0:Be[1],Ee.body[z].keypoints[ae]?((r-1)*(((Ge=Ee.body[z].keypoints[ae].distance)==null?void 0:Ge[2])||0)+(((ot=Y.distance)==null?void 0:ot[2])||0))/r:(dt=Y.distance)==null?void 0:dt[2]]}}),Q={},oe={connected:{}};(i=(o=t.body)==null?void 0:o.modelPath)!=null&&i.includes("efficientpose")?oe=q2:(u=(l=t.body)==null?void 0:l.modelPath)!=null&&u.includes("blazepose")?oe=V2:(p=(c=t.body)==null?void 0:c.modelPath)!=null&&p.includes("movenet")&&(oe=Zh);for(let[Y,ae]of Object.entries(oe.connected)){let le=[];for(let ye=0;ye<ae.length-1;ye++){let we=ee.find(_e=>_e.part===ae[ye]),Re=ee.find(_e=>_e.part===ae[ye+1]);we&&Re&&le.push([we.position,Re.position])}Q[Y]=le}Ee.body[z]={...e.body[z],box:K,boxRaw:B,keypoints:ee,annotations:Q}}if(!Ee.hand||e.hand.length!==Ee.hand.length)Ee.hand=JSON.parse(JSON.stringify(e.hand));else for(let z=0;z<e.hand.length;z++){let K=e.hand[z].box.map((oe,Y)=>((r-1)*Ee.hand[z].box[Y]+oe)/r),B=e.hand[z].boxRaw.map((oe,Y)=>((r-1)*Ee.hand[z].boxRaw[Y]+oe)/r);Ee.hand[z].keypoints.length!==e.hand[z].keypoints.length&&(Ee.hand[z].keypoints=e.hand[z].keypoints);let ee=e.hand[z].keypoints&&e.hand[z].keypoints.length>0?e.hand[z].keypoints.map((oe,Y)=>oe.map((ae,le)=>((r-1)*(Ee.hand[z].keypoints[Y][le]||1)+(ae||0))/r)):[],Q={};if(Object.keys(Ee.hand[z].annotations).length!==Object.keys(e.hand[z].annotations).length)Ee.hand[z].annotations=e.hand[z].annotations,Q=Ee.hand[z].annotations;else if(e.hand[z].annotations)for(let oe of Object.keys(e.hand[z].annotations))Q[oe]=e.hand[z].annotations[oe]&&e.hand[z].annotations[oe][0]?e.hand[z].annotations[oe].map((Y,ae)=>Y.map((le,ye)=>((r-1)*Ee.hand[z].annotations[oe][ae][ye]+le)/r)):null;Ee.hand[z]={...e.hand[z],box:K,boxRaw:B,keypoints:ee,annotations:Q}}if(!Ee.face||e.face.length!==Ee.face.length)Ee.face=JSON.parse(JSON.stringify(e.face));else for(let z=0;z<e.face.length;z++){let K=e.face[z].box.map((ee,Q)=>((r-1)*Ee.face[z].box[Q]+ee)/r),B=e.face[z].boxRaw.map((ee,Q)=>((r-1)*Ee.face[z].boxRaw[Q]+ee)/r);if(e.face[z].rotation){let ee={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};ee.matrix=(d=e.face[z].rotation)==null?void 0:d.matrix,ee.angle={roll:((r-1)*(((f=(h=Ee.face[z].rotation)==null?void 0:h.angle)==null?void 0:f.roll)||0)+(((g=(m=e.face[z].rotation)==null?void 0:m.angle)==null?void 0:g.roll)||0))/r,yaw:((r-1)*(((x=(y=Ee.face[z].rotation)==null?void 0:y.angle)==null?void 0:x.yaw)||0)+(((b=(A=e.face[z].rotation)==null?void 0:A.angle)==null?void 0:b.yaw)||0))/r,pitch:((r-1)*(((k=(w=Ee.face[z].rotation)==null?void 0:w.angle)==null?void 0:k.pitch)||0)+(((E=(S=e.face[z].rotation)==null?void 0:S.angle)==null?void 0:E.pitch)||0))/r},ee.gaze={bearing:((r-1)*(((P=(R=Ee.face[z].rotation)==null?void 0:R.gaze)==null?void 0:P.bearing)||0)+((($=(_=e.face[z].rotation)==null?void 0:_.gaze)==null?void 0:$.bearing)||0))/r,strength:((r-1)*(((F=(T=Ee.face[z].rotation)==null?void 0:T.gaze)==null?void 0:F.strength)||0)+(((q=(G=e.face[z].rotation)==null?void 0:G.gaze)==null?void 0:q.strength)||0))/r},Ee.face[z]={...e.face[z],rotation:ee,box:K,boxRaw:B}}Ee.face[z]={...e.face[z],box:K,boxRaw:B}}if(!Ee.object||e.object.length!==Ee.object.length)Ee.object=JSON.parse(JSON.stringify(e.object));else for(let z=0;z<e.object.length;z++){let K=e.object[z].box.map((ee,Q)=>((r-1)*Ee.object[z].box[Q]+ee)/r),B=e.object[z].boxRaw.map((ee,Q)=>((r-1)*Ee.object[z].boxRaw[Q]+ee)/r);Ee.object[z]={...e.object[z],box:K,boxRaw:B}}if(e.persons){let z=e.persons;if(!Ee.persons||z.length!==Ee.persons.length)Ee.persons=JSON.parse(JSON.stringify(z));else for(let K=0;K<z.length;K++)Ee.persons[K].box=z[K].box.map((B,ee)=>((r-1)*Ee.persons[K].box[ee]+B)/r)}e.gesture&&(Ee.gesture=e.gesture);let a=ue();return O4=fe.perfadd?O4+Math.round(a-n):Math.round(a-n),e.performance&&(Ee.performance={...e.performance,interpolate:O4}),Ee}var L4={};ia(L4,{distance:()=>ef,match:()=>z4,similarity:()=>M4});function ef(e,t,n={order:2,multiplier:25}){let s=0;for(let r=0;r<e.length;r++){let a=!n.order||n.order===2?e[r]-t[r]:Math.abs(e[r]-t[r]);s+=!n.order||n.order===2?a*a:a**n.order}return(n.multiplier||20)*s}var XE=(e,t,n,s)=>{if(e===0)return 1;let r=t===2?Math.sqrt(e):e**(1/t),a=(1-r/100-n)/(s-n);return Math.max(Math.min(a,1),0)};function M4(e,t,n={order:2,multiplier:25,min:.2,max:.8}){let s=ef(e,t,n);return XE(s,n.order||2,n.min||0,n.max||1)}function z4(e,t,n={order:2,multiplier:25,threshold:0,min:.2,max:.8}){if(!Array.isArray(e)||!Array.isArray(t)||e.length<64||t.length===0||e.length!==t[0].length)return{index:-1,distance:Number.POSITIVE_INFINITY,similarity:0};let s=Number.MAX_SAFE_INTEGER,r=-1;for(let o=0;o<t.length;o++){let i=ef(e,t[o],n);if(i<s&&(s=i,r=o),s<(n.threshold||0))break}let a=XE(s,n.order||2,n.min||0,n.max||1);return{index:r,distance:s,similarity:a}}function KE(e,t,n,s,r){var i,l,u,c,p,d,h,f,m,g,y,x,A,b,w,k;let a=0,o=[];for(let S of e){let E={id:a++,face:S,body:null,hands:{left:null,right:null},gestures:[],box:[0,0,0,0]};for(let F of t)S.box[0]>F.box[0]&&S.box[0]<F.box[0]+F.box[2]&&S.box[1]+S.box[3]>F.box[1]&&S.box[1]+S.box[3]<F.box[1]+F.box[3]&&(E.body=F);if(E.body)for(let F of n)F.box[0]+F.box[2]>E.body.box[0]&&F.box[0]+F.box[2]<E.body.box[0]+E.body.box[2]&&F.box[1]+F.box[3]>E.body.box[1]&&F.box[1]+F.box[3]<E.body.box[1]+E.body.box[3]&&E.hands&&(E.hands.left=F),F.box[0]<E.body.box[0]+E.body.box[2]&&F.box[0]>E.body.box[0]&&F.box[1]+F.box[3]>E.body.box[1]&&F.box[1]+F.box[3]<E.body.box[1]+E.body.box[3]&&E.hands&&(E.hands.right=F);for(let F of s)F.face!==void 0&&F.face===S.id?(i=E.gestures)==null||i.push(F):F.iris!==void 0&&F.iris===S.id?(l=E.gestures)==null||l.push(F):F.body!==void 0&&F.body===((u=E.body)==null?void 0:u.id)?(c=E.gestures)==null||c.push(F):F.hand!==void 0&&F.hand===((d=(p=E.hands)==null?void 0:p.left)==null?void 0:d.id)?(h=E.gestures)==null||h.push(F):F.hand!==void 0&&F.hand===((m=(f=E.hands)==null?void 0:f.right)==null?void 0:m.id)&&((g=E.gestures)==null||g.push(F));let R=[],P=[],_=F=>{F&&F.length===4&&(R.push(F[0],F[0]+F[2]),P.push(F[1],F[1]+F[3]))};_((y=E.face)==null?void 0:y.box),_((x=E.body)==null?void 0:x.box),_((b=(A=E.hands)==null?void 0:A.left)==null?void 0:b.box),_((k=(w=E.hands)==null?void 0:w.right)==null?void 0:k.box);let $=Math.min(...R),T=Math.min(...P);E.box=[$,T,Math.max(...R)-$,Math.max(...P)-T],r&&r[1]&&r[2]&&(E.boxRaw=[E.box[0]/r[2],E.box[1]/r[1],E.box[2]/r[2],E.box[3]/r[1]]),o.push(E)}return o}var y1=`
+    `);t.stroke(o),t.stroke(a)}}function dxe(e,t){var n,s,r,a;if(gt.drawGaze&&((s=(n=e.rotation)==null?void 0:n.gaze)==null?void 0:s.strength)&&((a=(r=e.rotation)==null?void 0:r.gaze)==null?void 0:a.bearing)&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let o=[e.annotations.leftEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.leftEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];N4(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[o[0],o[1]],4);let i=[e.annotations.rightEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.rightEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];N4(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[i[0],i[1]],4)}}function pxe(e,t){if(gt.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let n=0;n<iu.length/3;n++){let s=[iu[n*3+0],iu[n*3+1],iu[n*3+2]].map(r=>e.mesh[r]);T4(t,s,gt)}uxe(e,t)}}function hxe(e,t){if(gt.drawPoints&&e.mesh.length>=468)for(let n=0;n<e.mesh.length;n++)Pa(t,e.mesh[n][0],e.mesh[n][1],e.mesh[n][2],gt),gt.drawAttention&&(qh.includes(n)&&Pa(t,e.mesh[n][0],e.mesh[n][1],e.mesh[n][2]+127,gt),cu.includes(n)&&Pa(t,e.mesh[n][0],e.mesh[n][1],e.mesh[n][2]-127,gt),du.includes(n)&&Pa(t,e.mesh[n][0],e.mesh[n][1],e.mesh[n][2]-127,gt))}function fxe(e,t){gt.drawBoxes&&na(t,e.box[0],e.box[1],e.box[2],e.box[3],gt)}async function Ed(e,t,n){if(gt=Xt(Vn,n),!t||!e)return;let s=tr(e);if(!!s){s.font=gt.font,s.strokeStyle=gt.color,s.fillStyle=gt.color;for(let r of t)fxe(r,s),lxe(r,s),r.mesh&&r.mesh.length>0&&(hxe(r,s),pxe(r,s),cxe(r,s),dxe(r,s))}}async function Rd(e,t,n){var a;let s=Xt(Vn,n);if(!t||!e)return;let r=tr(e);if(!!r){r.lineJoin="round";for(let o=0;o<t.length;o++){if(r.strokeStyle=s.color,r.fillStyle=s.color,r.lineWidth=s.lineWidth,r.font=s.font,s.drawBoxes&&t[o].box&&((a=t[o].box)==null?void 0:a.length)===4&&(na(r,t[o].box[0],t[o].box[1],t[o].box[2],t[o].box[3],s),s.drawLabels&&(s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(`body ${100*t[o].score}%`,t[o].box[0]+3,1+t[o].box[1]+s.lineHeight,t[o].box[2])),r.fillStyle=s.labelColor,r.fillText(`body ${100*t[o].score}%`,t[o].box[0]+2,0+t[o].box[1]+s.lineHeight,t[o].box[2]))),s.drawPoints&&t[o].keypoints)for(let i=0;i<t[o].keypoints.length;i++)!t[o].keypoints[i].score||t[o].keypoints[i].score===0||(r.fillStyle=$a(t[o].keypoints[i].position[2],s),Pa(r,t[o].keypoints[i].position[0],t[o].keypoints[i].position[1],0,s));if(s.drawLabels&&t[o].keypoints){r.font=s.font;for(let i of t[o].keypoints)!i.score||i.score===0||(r.fillStyle=$a(i.position[2],s),r.fillText(`${i.part} ${Math.trunc(100*i.score)}%`,i.position[0]+4,i.position[1]+4))}if(s.drawPolygons&&t[o].keypoints&&t[o].annotations)for(let i of Object.values(t[o].annotations))for(let l of i)BE(r,l,s)}}}async function _d(e,t,n){let s=Xt(Vn,n);if(!t||!e)return;let r=tr(e);if(!!r){r.lineJoin="round",r.font=s.font;for(let a of t){if(s.drawBoxes&&(r.strokeStyle=s.color,r.fillStyle=s.color,na(r,a.box[0],a.box[1],a.box[2],a.box[3],s),s.drawLabels&&(s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(`hand:${Math.trunc(100*a.score)}%`,a.box[0]+3,1+a.box[1]+s.lineHeight,a.box[2])),r.fillStyle=s.labelColor,r.fillText(`hand:${Math.trunc(100*a.score)}%`,a.box[0]+2,0+a.box[1]+s.lineHeight,a.box[2])),r.stroke()),s.drawPoints&&a.keypoints&&a.keypoints.length>0)for(let o of a.keypoints)r.fillStyle=$a(o[2],s),Pa(r,o[0],o[1],0,s);if(s.drawLabels&&a.annotations){let o=(i,l)=>{if(!i||i.length===0||!i[0])return;let u=i[i.length-1][2]||-256;r.fillStyle=$a(u,s),r.fillText(l,i[i.length-1][0]+4,i[i.length-1][1]+4)};r.font=s.font,o(a.annotations.index,"index"),o(a.annotations.middle,"middle"),o(a.annotations.ring,"ring"),o(a.annotations.pinky,"pinky"),o(a.annotations.thumb,"thumb"),o(a.annotations.palm,"palm")}if(s.drawPolygons&&a.annotations){let o=i=>{if(!(!i||i.length===0||!i[0]))for(let l=0;l<i.length;l++){r.beginPath();let u=i[l][2]||0;r.strokeStyle=$a(l*u,s),r.moveTo(i[l>0?l-1:0][0],i[l>0?l-1:0][1]),r.lineTo(i[l][0],i[l][1]),r.stroke()}};r.lineWidth=s.lineWidth,o(a.annotations.index),o(a.annotations.middle),o(a.annotations.ring),o(a.annotations.pinky),o(a.annotations.thumb)}}}}async function Dd(e,t,n){let s=Xt(Vn,n);if(!t||!e)return;let r=tr(e);if(!!r){r.lineJoin="round",r.font=s.font;for(let a of t)if(s.drawBoxes){if(r.strokeStyle=s.color,r.fillStyle=s.color,na(r,a.box[0],a.box[1],a.box[2],a.box[3],s),s.drawLabels){let o=`${a.label} ${Math.round(100*a.score)}%`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(o,a.box[0]+3,1+a.box[1]+s.lineHeight,a.box[2])),r.fillStyle=s.labelColor,r.fillText(o,a.box[0]+2,0+a.box[1]+s.lineHeight,a.box[2])}r.stroke()}}}async function $d(e,t,n){let s=Xt(Vn,n);if(!(!t||!e)&&s.drawGestures){let r=tr(e);if(!r)return;r.font=s.font,r.fillStyle=s.color;let a=1;for(let o=0;o<t.length;o++){let i=[],l=[];if([i,l]=Object.entries(t[o]),l.length>1&&l[1].length>0){let u=i[1]>0?`#${i[1]}`:"",c=`${i[0]} ${u}: ${l[1]}`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(c,8,2+a*s.lineHeight)),r.fillStyle=s.labelColor,r.fillText(c,6,0+a*s.lineHeight),a+=1}}}}var E4=0;async function R4(e,t,n){let s=Xt(Vn,n);if(!t||!e)return;let r=tr(e);if(!!r){r.lineJoin="round",r.font=s.font;for(let a=0;a<t.length;a++)if(s.drawBoxes){if(r.strokeStyle=s.color,r.fillStyle=s.color,na(r,t[a].box[0],t[a].box[1],t[a].box[2],t[a].box[3],s),s.drawLabels){let o=`person #${a}`;s.shadowColor&&s.shadowColor!==""&&(r.fillStyle=s.shadowColor,r.fillText(o,t[a].box[0]+3,1+t[a].box[1]+s.lineHeight,t[a].box[2])),r.fillStyle=s.labelColor,r.fillText(o,t[a].box[0]+2,0+t[a].box[1]+s.lineHeight,t[a].box[2])}r.stroke()}}}async function _4(e,t){if(!e||!t)return;let n=tr(t);!n||n.drawImage(e,0,0)}async function D4(e,t,n){if(!t||!t.performance||!t||!e)return null;let s=ue(),r=Xt(Vn,n),a=Promise.all([Ed(e,t.face,r),Rd(e,t.body,r),_d(e,t.hand,r),Dd(e,t.object,r),$d(e,t.gesture,r)]);return E4=fe.perfadd?E4+Math.round(ue()-s):Math.round(ue()-s),t.performance.draw=E4,a}var Pd=.1,P4=.5;function mxe(e,t,n){let s=!1,r=n.length-1;for(let a=0;a<n.length;r=a++)n[a].y>t!=n[r].y>t&&e<(n[r].x-n[a].x)*(t-n[a].y)/(n[r].y-n[a].y)+n[a].x&&(s=!s);return s}async function WE(e){if(!e.tensor||!e.mesh||e.mesh.length<100)return e.tensor;let t=e.tensor.shape[2]||0,n=e.tensor.shape[1]||0,s=await e.tensor.buffer(),r=[];for(let o of gr.silhouette)r.push({x:(e.mesh[o][0]-e.box[0])/e.box[2],y:(e.mesh[o][1]-e.box[1])/e.box[3]});Pd&&Pd>0&&(r=r.map(o=>({x:o.x>.5?o.x+Pd:o.x-Pd,y:o.y>.5?o.y+Pd:o.y-Pd})));for(let o=0;o<t;o++)for(let i=0;i<n;i++)mxe(o/t,i/t,r)||(s.set(P4*s.get(0,i,o,0),0,i,o,0),s.set(P4*s.get(0,i,o,1),0,i,o,1),s.set(P4*s.get(0,i,o,2),0,i,o,2));let a=s.toTensor();return ne(s),a}var yxe=e=>{let t=(p,d)=>Math.atan2(p[1]-d[1],p[0]-d[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let n=[0,-.1],s=1,r=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),a=r?e.mesh[473]:e.mesh[468],o=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],i=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],l=[(o[0]-a[0])/i[0]-n[0],s*(a[1]-o[1])/i[1]-n[1]],u=Math.sqrt(l[0]*l[0]+l[1]*l[1]);return u=Math.min(u,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],l)+Math.PI/2)%Math.PI,strength:u}},VE=(e,t)=>{let n=m=>{let g=Math.sqrt(m[0]*m[0]+m[1]*m[1]+m[2]*m[2]);return m[0]/=g,m[1]/=g,m[2]/=g,m},s=(m,g)=>{let y=m[0]-g[0],x=m[1]-g[1],A=m[2]-g[2];return[y,x,A]},r=(m,g)=>{let y=m[1]*g[2]-m[2]*g[1],x=m[2]*g[0]-m[0]*g[2],A=m[0]*g[1]-m[1]*g[0];return[y,x,A]},a=m=>{let[g,y,x,A,b,w,k,S,E]=m,R,P,_;return A<1?A>-1?(_=Math.asin(A),P=Math.atan2(-k,g),R=Math.atan2(-w,b)):(_=-Math.PI/2,P=-Math.atan2(S,E),R=0):(_=Math.PI/2,P=Math.atan2(S,E),R=0),isNaN(R)&&(R=0),isNaN(P)&&(P=0),isNaN(_)&&(_=0),{pitch:2*-R,yaw:2*-P,roll:2*-_}},o=e.meshRaw;if(!o||o.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let i=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,l=[o[10],o[152],o[234],o[454]].map(m=>[m[0]*t[0]/i,m[1]*t[1]/i,m[2]]),u=n(s(l[1],l[0])),c=n(s(l[3],l[2])),p=n(r(c,u));c=r(u,p);let d=[c[0],c[1],c[2],u[0],u[1],u[2],p[0],p[1],p[2]],h=a(d),f=o.length===478?yxe(e):{bearing:0,strength:0};return{angle:h,matrix:d,gaze:f}};var F4=async(e,t)=>{var h,f,m,g,y,x,A,b,w,k,S,E,R,P,_,$,T,F,G,q,z,Z;let n=ue(),s,r,a,o,i,l,u,c,p=[];e.state="run:face";let d=await PN(t,e.config);if(e.performance.face=fe.perfadd?(e.performance.face||0)+Math.trunc(ue()-n):Math.trunc(ue()-n),!t.shape||t.shape.length!==4)return[];if(!d)return[];for(let B=0;B<d.length;B++){if(e.analyze("Get Face"),!d[B].tensor||d[B].tensor.isDisposedInternal){ie("Face object is disposed:",d[B].tensor);continue}if((h=e.config.face.detector)!=null&&h.mask){let ae=await WE(d[B]);ne(d[B].tensor),d[B].tensor=ae}let ee=d[B].mesh&&d[B].mesh.length>200?VE(d[B],[t.shape[2],t.shape[1]]):null;e.analyze("Start Emotion:"),e.config.async?o=(f=e.config.face.emotion)!=null&&f.enabled?Vb(d[B].tensor||ft([]),e.config,B,d.length):[]:(e.state="run:emotion",n=ue(),o=(m=e.config.face.emotion)!=null&&m.enabled?await Vb(d[B].tensor||ft([]),e.config,B,d.length):[],e.performance.emotion=fe.perfadd?(e.performance.emotion||0)+Math.trunc(ue()-n):Math.trunc(ue()-n)),e.analyze("End Emotion:"),e.analyze("Start AntiSpoof:"),e.config.async?l=(g=e.config.face.antispoof)!=null&&g.enabled?kb(d[B].tensor||ft([]),e.config,B,d.length):0:(e.state="run:antispoof",n=ue(),l=(y=e.config.face.antispoof)!=null&&y.enabled?await kb(d[B].tensor||ft([]),e.config,B,d.length):0,e.performance.antispoof=fe.perfadd?(e.performance.antispoof||0)+Math.trunc(ue()-n):Math.trunc(ue()-n)),e.analyze("End AntiSpoof:"),e.analyze("Start Liveness:"),e.config.async?u=(x=e.config.face.liveness)!=null&&x.enabled?l4(d[B].tensor||ft([]),e.config,B,d.length):0:(e.state="run:liveness",n=ue(),u=(A=e.config.face.liveness)!=null&&A.enabled?await l4(d[B].tensor||ft([]),e.config,B,d.length):0,e.performance.liveness=fe.perfadd?(e.performance.antispoof||0)+Math.trunc(ue()-n):Math.trunc(ue()-n)),e.analyze("End Liveness:"),e.analyze("Start GEAR:"),e.config.async?r=(b=e.config.face.gear)!=null&&b.enabled?gb(d[B].tensor||ft([]),e.config,B,d.length):null:(e.state="run:gear",n=ue(),r=(w=e.config.face.gear)!=null&&w.enabled?await gb(d[B].tensor||ft([]),e.config,B,d.length):null,e.performance.gear=Math.trunc(ue()-n)),e.analyze("End GEAR:"),e.analyze("Start SSRNet:"),e.config.async?(s=(k=e.config.face.ssrnet)!=null&&k.enabled?Ab(d[B].tensor||ft([]),e.config,B,d.length):null,a=(S=e.config.face.ssrnet)!=null&&S.enabled?vb(d[B].tensor||ft([]),e.config,B,d.length):null):(e.state="run:ssrnet",n=ue(),s=(E=e.config.face.ssrnet)!=null&&E.enabled?await Ab(d[B].tensor||ft([]),e.config,B,d.length):null,a=(R=e.config.face.ssrnet)!=null&&R.enabled?await vb(d[B].tensor||ft([]),e.config,B,d.length):null,e.performance.ssrnet=Math.trunc(ue()-n)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?i=(P=e.config.face.mobilefacenet)!=null&&P.enabled?Gb(d[B].tensor||ft([]),e.config,B,d.length):null:(e.state="run:mobilefacenet",n=ue(),i=(_=e.config.face.mobilefacenet)!=null&&_.enabled?await Gb(d[B].tensor||ft([]),e.config,B,d.length):null,e.performance.mobilefacenet=Math.trunc(ue()-n)),e.analyze("End MobileFaceNet:"),e.analyze("Start Description:"),e.config.async?c=($=e.config.face.description)!=null&&$.enabled?Zb(d[B].tensor||ft([]),e.config,B,d.length):null:(e.state="run:description",n=ue(),c=(T=e.config.face.description)!=null&&T.enabled?await Zb(d[B].tensor||ft([]),e.config,B,d.length):null,e.performance.description=fe.perfadd?(e.performance.description||0)+Math.trunc(ue()-n):Math.trunc(ue()-n)),e.analyze("End Description:"),e.config.async&&([s,a,o,i,c,r,l,u]=await Promise.all([s,a,o,i,c,r,l,u])),e.analyze("Finish Face:"),((F=e.config.face.ssrnet)==null?void 0:F.enabled)&&s&&a&&(c={...c,age:s.age,gender:a.gender,genderScore:a.genderScore}),((G=e.config.face.gear)==null?void 0:G.enabled)&&r&&(c={...c,age:r.age,gender:r.gender,genderScore:r.genderScore,race:r.race}),((q=e.config.face.mobilefacenet)==null?void 0:q.enabled)&&i&&(c.descriptor=i),(z=e.config.face.iris)!=null&&z.enabled;let Q=d[B].annotations&&d[B].annotations.leftEyeIris&&d[B].annotations.leftEyeIris[0]&&d[B].annotations.rightEyeIris&&d[B].annotations.rightEyeIris[0]&&d[B].annotations.leftEyeIris.length>0&&d[B].annotations.rightEyeIris.length>0&&d[B].annotations.leftEyeIris[0]!==null&&d[B].annotations.rightEyeIris[0]!==null?Math.max(Math.abs(d[B].annotations.leftEyeIris[3][0]-d[B].annotations.leftEyeIris[1][0]),Math.abs(d[B].annotations.rightEyeIris[4][1]-d[B].annotations.rightEyeIris[2][1]))/t.shape[2]:0,oe=(Z=e.config.face.detector)!=null&&Z.return?rt(d[B].tensor):null;ne(d[B].tensor),d[B].tensor&&delete d[B].tensor;let Y={...d[B],id:B};c!=null&&c.age&&(Y.age=c.age),c!=null&&c.gender&&(Y.gender=c.gender),c!=null&&c.genderScore&&(Y.genderScore=c==null?void 0:c.genderScore),c!=null&&c.descriptor&&(Y.embedding=c==null?void 0:c.descriptor),c!=null&&c.race&&(Y.race=c==null?void 0:c.race),o&&(Y.emotion=o),l&&(Y.real=l),u&&(Y.live=u),Q&&Q!==0&&(Y.iris=Math.trunc(500/Q/11.7)/100),ee&&(Y.rotation=ee),oe&&(Y.tensor=oe),p.push(Y),e.analyze("End Face")}return e.analyze("End FaceMesh:"),e.config.async&&(e.performance.face&&delete e.performance.face,e.performance.age&&delete e.performance.age,e.performance.gender&&delete e.performance.gender,e.performance.emotion&&delete e.performance.emotion),p};var UE=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){let s=e[n].keypoints.find(l=>l.part==="leftWrist"),r=e[n].keypoints.find(l=>l.part==="rightWrist"),a=e[n].keypoints.find(l=>l.part==="nose");a&&s&&r&&s.position[1]<a.position[1]&&r.position[1]<a.position[1]?t.push({body:n,gesture:"i give up"}):a&&s&&s.position[1]<a.position[1]?t.push({body:n,gesture:"raise left hand"}):a&&r&&r.position[1]<a.position[1]&&t.push({body:n,gesture:"raise right hand"});let o=e[n].keypoints.find(l=>l.part==="leftShoulder"),i=e[n].keypoints.find(l=>l.part==="rightShoulder");o&&i&&Math.abs(o.positionRaw[1]-i.positionRaw[1])>.1&&t.push({body:n,gesture:`leaning ${o.position[1]>i.position[1]?"left":"right"}`})}return t},GE=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++)if(e[n].mesh&&e[n].mesh.length>450){let s=(e[n].mesh[33][2]||0)-(e[n].mesh[263][2]||0),r=e[n].mesh[33][0]-e[n].mesh[263][0];Math.abs(s/r)<=.15?t.push({face:n,gesture:"facing center"}):t.push({face:n,gesture:`facing ${s<0?"left":"right"}`}),Math.abs(e[n].mesh[374][1]-e[n].mesh[386][1])/Math.abs(e[n].mesh[443][1]-e[n].mesh[450][1])<.2&&t.push({face:n,gesture:"blink left eye"}),Math.abs(e[n].mesh[145][1]-e[n].mesh[159][1])/Math.abs(e[n].mesh[223][1]-e[n].mesh[230][1])<.2&&t.push({face:n,gesture:"blink right eye"});let i=Math.min(100,500*Math.abs(e[n].mesh[13][1]-e[n].mesh[14][1])/Math.abs(e[n].mesh[10][1]-e[n].mesh[152][1]));i>10&&t.push({face:n,gesture:`mouth ${Math.trunc(i)}% open`});let l=e[n].mesh[152][2]||0;Math.abs(l)>10&&t.push({face:n,gesture:`head ${l<0?"up":"down"}`})}return t},HE=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){if(!e[n].annotations||!e[n].annotations.leftEyeIris||!e[n].annotations.leftEyeIris[0]||!e[n].annotations.rightEyeIris||!e[n].annotations.rightEyeIris[0])continue;let s=e[n].annotations.leftEyeIris[3][0]-e[n].annotations.leftEyeIris[1][0],r=e[n].annotations.leftEyeIris[4][1]-e[n].annotations.leftEyeIris[2][1],a=Math.abs(s*r),o=e[n].annotations.rightEyeIris[3][0]-e[n].annotations.rightEyeIris[1][0],i=e[n].annotations.rightEyeIris[4][1]-e[n].annotations.rightEyeIris[2][1],l=Math.abs(o*i),u=!1;Math.abs(a-l)/Math.max(a,l)<.25&&(u=!0,t.push({iris:n,gesture:"facing center"}));let p=Math.abs(e[n].mesh[263][0]-e[n].annotations.leftEyeIris[0][0])/e[n].box[2],d=Math.abs(e[n].mesh[33][0]-e[n].annotations.rightEyeIris[0][0])/e[n].box[2];(p>.06||d>.06)&&(u=!1),p>d?p>.05&&t.push({iris:n,gesture:"looking right"}):d>.05&&t.push({iris:n,gesture:"looking left"});let h=Math.abs(e[n].mesh[145][1]-e[n].annotations.rightEyeIris[0][1])/e[n].box[3],f=Math.abs(e[n].mesh[374][1]-e[n].annotations.leftEyeIris[0][1])/e[n].box[3];(f<.01||h<.01||f>.022||h>.022)&&(u=!1),(f<.01||h<.01)&&t.push({iris:n,gesture:"looking down"}),(f>.022||h>.022)&&t.push({iris:n,gesture:"looking up"}),u&&t.push({iris:n,gesture:"looking center"})}return t},jE=e=>{if(!e)return[];let t=[];for(let n=0;n<e.length;n++){let s=[];if(e[n].annotations)for(let[r,a]of Object.entries(e[n].annotations))r!=="palmBase"&&Array.isArray(a)&&a[0]&&s.push({name:r.toLowerCase(),position:a[0]});if(s&&s.length>0){let r=s.reduce((o,i)=>(o.position[2]||0)<(i.position[2]||0)?o:i);t.push({hand:n,gesture:`${r.name} forward`});let a=s.reduce((o,i)=>o.position[1]<i.position[1]?o:i);t.push({hand:n,gesture:`${a.name} up`})}if(e[n].keypoints){let r=aE(e[n].keypoints);for(let a of r)t.push({hand:n,gesture:a.name})}}return t};var Ee={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null},O4=0;function qE(e,t){var o,i,l,u,c,p,d,h,f,m,g,y,x,A,b,w,k,S,E,R,P,_,$,T,F,G,q;let n=ue();if(!e)return{face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null};let s=Date.now()-e.timestamp,r=s<1e3?8-Math.log(s+1):1;if(e.canvas&&(Ee.canvas=e.canvas),e.error&&(Ee.error=e.error),!Ee.body||e.body.length!==Ee.body.length)Ee.body=JSON.parse(JSON.stringify(e.body));else for(let z=0;z<e.body.length;z++){let Z=e.body[z].box.map((Y,ae)=>((r-1)*Ee.body[z].box[ae]+Y)/r),B=e.body[z].boxRaw.map((Y,ae)=>((r-1)*Ee.body[z].boxRaw[ae]+Y)/r),ee=e.body[z].keypoints.map((Y,ae)=>{var le,ye,we,Re,_e,Be,Ge,ot,dt;return{score:Y.score,part:Y.part,position:[Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].position[0]||0)+(Y.position[0]||0))/r:Y.position[0],Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].position[1]||0)+(Y.position[1]||0))/r:Y.position[1],Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].position[2]||0)+(Y.position[2]||0))/r:Y.position[2]],positionRaw:[Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].positionRaw[0]||0)+(Y.positionRaw[0]||0))/r:Y.positionRaw[0],Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].positionRaw[1]||0)+(Y.positionRaw[1]||0))/r:Y.positionRaw[1],Ee.body[z].keypoints[ae]?((r-1)*(Ee.body[z].keypoints[ae].positionRaw[2]||0)+(Y.positionRaw[2]||0))/r:Y.positionRaw[2]],distance:[Ee.body[z].keypoints[ae]?((r-1)*(((le=Ee.body[z].keypoints[ae].distance)==null?void 0:le[0])||0)+(((ye=Y.distance)==null?void 0:ye[0])||0))/r:(we=Y.distance)==null?void 0:we[0],Ee.body[z].keypoints[ae]?((r-1)*(((Re=Ee.body[z].keypoints[ae].distance)==null?void 0:Re[1])||0)+(((_e=Y.distance)==null?void 0:_e[1])||0))/r:(Be=Y.distance)==null?void 0:Be[1],Ee.body[z].keypoints[ae]?((r-1)*(((Ge=Ee.body[z].keypoints[ae].distance)==null?void 0:Ge[2])||0)+(((ot=Y.distance)==null?void 0:ot[2])||0))/r:(dt=Y.distance)==null?void 0:dt[2]]}}),Q={},oe={connected:{}};(i=(o=t.body)==null?void 0:o.modelPath)!=null&&i.includes("efficientpose")?oe=j2:(u=(l=t.body)==null?void 0:l.modelPath)!=null&&u.includes("blazepose")?oe=W2:(p=(c=t.body)==null?void 0:c.modelPath)!=null&&p.includes("movenet")&&(oe=Kh);for(let[Y,ae]of Object.entries(oe.connected)){let le=[];for(let ye=0;ye<ae.length-1;ye++){let we=ee.find(_e=>_e.part===ae[ye]),Re=ee.find(_e=>_e.part===ae[ye+1]);we&&Re&&le.push([we.position,Re.position])}Q[Y]=le}Ee.body[z]={...e.body[z],box:Z,boxRaw:B,keypoints:ee,annotations:Q}}if(!Ee.hand||e.hand.length!==Ee.hand.length)Ee.hand=JSON.parse(JSON.stringify(e.hand));else for(let z=0;z<e.hand.length;z++){let Z=e.hand[z].box.map((oe,Y)=>((r-1)*Ee.hand[z].box[Y]+oe)/r),B=e.hand[z].boxRaw.map((oe,Y)=>((r-1)*Ee.hand[z].boxRaw[Y]+oe)/r);Ee.hand[z].keypoints.length!==e.hand[z].keypoints.length&&(Ee.hand[z].keypoints=e.hand[z].keypoints);let ee=e.hand[z].keypoints&&e.hand[z].keypoints.length>0?e.hand[z].keypoints.map((oe,Y)=>oe.map((ae,le)=>((r-1)*(Ee.hand[z].keypoints[Y][le]||1)+(ae||0))/r)):[],Q={};if(Object.keys(Ee.hand[z].annotations).length!==Object.keys(e.hand[z].annotations).length)Ee.hand[z].annotations=e.hand[z].annotations,Q=Ee.hand[z].annotations;else if(e.hand[z].annotations)for(let oe of Object.keys(e.hand[z].annotations))Q[oe]=e.hand[z].annotations[oe]&&e.hand[z].annotations[oe][0]?e.hand[z].annotations[oe].map((Y,ae)=>Y.map((le,ye)=>((r-1)*Ee.hand[z].annotations[oe][ae][ye]+le)/r)):null;Ee.hand[z]={...e.hand[z],box:Z,boxRaw:B,keypoints:ee,annotations:Q}}if(!Ee.face||e.face.length!==Ee.face.length)Ee.face=JSON.parse(JSON.stringify(e.face));else for(let z=0;z<e.face.length;z++){let Z=e.face[z].box.map((ee,Q)=>((r-1)*Ee.face[z].box[Q]+ee)/r),B=e.face[z].boxRaw.map((ee,Q)=>((r-1)*Ee.face[z].boxRaw[Q]+ee)/r);if(e.face[z].rotation){let ee={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};ee.matrix=(d=e.face[z].rotation)==null?void 0:d.matrix,ee.angle={roll:((r-1)*(((f=(h=Ee.face[z].rotation)==null?void 0:h.angle)==null?void 0:f.roll)||0)+(((g=(m=e.face[z].rotation)==null?void 0:m.angle)==null?void 0:g.roll)||0))/r,yaw:((r-1)*(((x=(y=Ee.face[z].rotation)==null?void 0:y.angle)==null?void 0:x.yaw)||0)+(((b=(A=e.face[z].rotation)==null?void 0:A.angle)==null?void 0:b.yaw)||0))/r,pitch:((r-1)*(((k=(w=Ee.face[z].rotation)==null?void 0:w.angle)==null?void 0:k.pitch)||0)+(((E=(S=e.face[z].rotation)==null?void 0:S.angle)==null?void 0:E.pitch)||0))/r},ee.gaze={bearing:((r-1)*(((P=(R=Ee.face[z].rotation)==null?void 0:R.gaze)==null?void 0:P.bearing)||0)+((($=(_=e.face[z].rotation)==null?void 0:_.gaze)==null?void 0:$.bearing)||0))/r,strength:((r-1)*(((F=(T=Ee.face[z].rotation)==null?void 0:T.gaze)==null?void 0:F.strength)||0)+(((q=(G=e.face[z].rotation)==null?void 0:G.gaze)==null?void 0:q.strength)||0))/r},Ee.face[z]={...e.face[z],rotation:ee,box:Z,boxRaw:B}}Ee.face[z]={...e.face[z],box:Z,boxRaw:B}}if(!Ee.object||e.object.length!==Ee.object.length)Ee.object=JSON.parse(JSON.stringify(e.object));else for(let z=0;z<e.object.length;z++){let Z=e.object[z].box.map((ee,Q)=>((r-1)*Ee.object[z].box[Q]+ee)/r),B=e.object[z].boxRaw.map((ee,Q)=>((r-1)*Ee.object[z].boxRaw[Q]+ee)/r);Ee.object[z]={...e.object[z],box:Z,boxRaw:B}}if(e.persons){let z=e.persons;if(!Ee.persons||z.length!==Ee.persons.length)Ee.persons=JSON.parse(JSON.stringify(z));else for(let Z=0;Z<z.length;Z++)Ee.persons[Z].box=z[Z].box.map((B,ee)=>((r-1)*Ee.persons[Z].box[ee]+B)/r)}e.gesture&&(Ee.gesture=e.gesture);let a=ue();return O4=fe.perfadd?O4+Math.round(a-n):Math.round(a-n),e.performance&&(Ee.performance={...e.performance,interpolate:O4}),Ee}var L4={};oa(L4,{distance:()=>Qh,match:()=>z4,similarity:()=>M4});function Qh(e,t,n={order:2,multiplier:25}){let s=0;for(let r=0;r<e.length;r++){let a=!n.order||n.order===2?e[r]-t[r]:Math.abs(e[r]-t[r]);s+=!n.order||n.order===2?a*a:a**n.order}return(n.multiplier||20)*s}var XE=(e,t,n,s)=>{if(e===0)return 1;let r=t===2?Math.sqrt(e):e**(1/t),a=(1-r/100-n)/(s-n);return Math.max(Math.min(a,1),0)};function M4(e,t,n={order:2,multiplier:25,min:.2,max:.8}){let s=Qh(e,t,n);return XE(s,n.order||2,n.min||0,n.max||1)}function z4(e,t,n={order:2,multiplier:25,threshold:0,min:.2,max:.8}){if(!Array.isArray(e)||!Array.isArray(t)||e.length<64||t.length===0||e.length!==t[0].length)return{index:-1,distance:Number.POSITIVE_INFINITY,similarity:0};let s=Number.MAX_SAFE_INTEGER,r=-1;for(let o=0;o<t.length;o++){let i=Qh(e,t[o],n);if(i<s&&(s=i,r=o),s<(n.threshold||0))break}let a=XE(s,n.order||2,n.min||0,n.max||1);return{index:r,distance:s,similarity:a}}function KE(e,t,n,s,r){var i,l,u,c,p,d,h,f,m,g,y,x,A,b,w,k;let a=0,o=[];for(let S of e){let E={id:a++,face:S,body:null,hands:{left:null,right:null},gestures:[],box:[0,0,0,0]};for(let F of t)S.box[0]>F.box[0]&&S.box[0]<F.box[0]+F.box[2]&&S.box[1]+S.box[3]>F.box[1]&&S.box[1]+S.box[3]<F.box[1]+F.box[3]&&(E.body=F);if(E.body)for(let F of n)F.box[0]+F.box[2]>E.body.box[0]&&F.box[0]+F.box[2]<E.body.box[0]+E.body.box[2]&&F.box[1]+F.box[3]>E.body.box[1]&&F.box[1]+F.box[3]<E.body.box[1]+E.body.box[3]&&E.hands&&(E.hands.left=F),F.box[0]<E.body.box[0]+E.body.box[2]&&F.box[0]>E.body.box[0]&&F.box[1]+F.box[3]>E.body.box[1]&&F.box[1]+F.box[3]<E.body.box[1]+E.body.box[3]&&E.hands&&(E.hands.right=F);for(let F of s)F.face!==void 0&&F.face===S.id?(i=E.gestures)==null||i.push(F):F.iris!==void 0&&F.iris===S.id?(l=E.gestures)==null||l.push(F):F.body!==void 0&&F.body===((u=E.body)==null?void 0:u.id)?(c=E.gestures)==null||c.push(F):F.hand!==void 0&&F.hand===((d=(p=E.hands)==null?void 0:p.left)==null?void 0:d.id)?(h=E.gestures)==null||h.push(F):F.hand!==void 0&&F.hand===((m=(f=E.hands)==null?void 0:f.right)==null?void 0:m.id)&&((g=E.gestures)==null||g.push(F));let R=[],P=[],_=F=>{F&&F.length===4&&(R.push(F[0],F[0]+F[2]),P.push(F[1],F[1]+F[3]))};_((y=E.face)==null?void 0:y.box),_((x=E.body)==null?void 0:x.box),_((b=(A=E.hands)==null?void 0:A.left)==null?void 0:b.box),_((k=(w=E.hands)==null?void 0:w.right)==null?void 0:k.box);let $=Math.min(...R),T=Math.min(...P);E.box=[$,T,Math.max(...R)-$,Math.max(...P)-T],r&&r[1]&&r[2]&&(E.boxRaw=[E.box[0]/r[2],E.box[1]/r[1],E.box[2]/r[2],E.box[3]/r[1]]),o.push(E)}return o}var g1=`
 /9j/4AAQSkZJRgABAQEAYABgAAD/4QBoRXhpZgAATU0AKgAAAAgABAEaAAUAAAABAAAAPgEbAAUA
 AAABAAAARgEoAAMAAAABAAIAAAExAAIAAAARAAAATgAAAAAAAABgAAAAAQAAAGAAAAABcGFpbnQu
 bmV0IDQuMi4xMwAA/9sAQwAGBAUGBQQGBgUGBwcGCAoQCgoJCQoUDg8MEBcUGBgXFBYWGh0lHxob
@@ -7081,7 +7081,7 @@ PQ4GJ+ashuK0MhWaoWcA0AaOmASMK7jRNPWYBmHyiuepO2x10qfcv6vYxCzYqoGK4HVYVTJrmb5l
 c6oaM5TUJ8EgGsG4kLNUHT0M64OaqMMikSRsuKbnFMRLG3zVehOaGNE445NNlnVFpDMu6uie9Vo1
 8z5mOAOST2pDK91cNN+5tsrH3PrW54a06KxT7fdrlh/q1Pc+tJ6IUdZGvHPLezMcnBOWbsPap5r3
 ylFtbdT1xUWNWzU0/Zbwlgfmx8zGsHWtRHmMqE59aAMyNifvHPc1f0gtPdqkY5JosJHeNci2tktY
-euPnNY+oXWZEVJNrZ9aun8SIq/CzodHuriIokhDIR1ronbKZr0o6o8ipoz//2Q==`,A1=`
+euPnNY+oXWZEVJNrZ9aun8SIq/CzodHuriIokhDIR1ronbKZr0o6o8ipoz//2Q==`,y1=`
 /9j/4AAQSkZJRgABAQAAAQABAAD/2wBDAAsICAoIBwsKCQoNDAsNERwSEQ8PESIZGhQcKSQrKigk
 JyctMkA3LTA9MCcnOEw5PUNFSElIKzZPVU5GVEBHSEX/2wBDAQwNDREPESESEiFFLicuRUVFRUVF
 RUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUVFRUX/wAARCASwBLADASIA
@@ -7649,4 +7649,4 @@ AAAAAAJAAAAAAAAAAAAAABAJEAAAAAAAAAAAAAAAIEoBKAAAAAAAAAAAAAAABAlAAAAAAAIAAAAA
 BAkBAkBAkBAlACEgMZjdjbFW8bWrEx8YWANb6Fp+bfwab+vLDKMFK9qxH5L0bAr8OPRPKz2AY7J2
 SbAjYZAI2E7AIEgIEgIEgMdkSy2NgY7MdlmyNoBXsxmFuyNgVTVjNV3KjlBRNTlXTVHKCrlIqt5T
 lBhEMohlFerLlBjEMohMVTEARDKCITsAk2AEgAAAkAAAAAAAAAAAAAAAAAAAAAAAASAAAAAAAAD/
-2Q==`;async function kxe(e){let t=(r,a="application/octet-stream")=>fetch(`data:${a};base64,${r}`).then(o=>o.blob()),n,s;switch(e.config.warmup){case"face":n=await t(y1);break;case"body":case"full":n=await t(A1);break;default:n=null}if(n){let r=await createImageBitmap(n);s=await e.detect(r,e.config),r.close()}return s}async function Ixe(e){return new Promise(t=>{let n;switch(e.config.warmup){case"face":n="data:image/jpeg;base64,"+y1;break;case"full":case"body":n="data:image/jpeg;base64,"+A1;break;default:n=null}let s;if(typeof Image!="undefined")s=new Image;else if(fe.Image)s=new fe.Image;else return;s.onload=async()=>{let r=is(s.naturalWidth,s.naturalHeight);if(!r)ie("Warmup: Canvas not found"),t(void 0);else{let a=r.getContext("2d");a&&a.drawImage(s,0,0);let o=await e.image(r),i=await e.detect(o.tensor,e.config);t(i)}},n?s.src=n:t(void 0)})}async function Sxe(e){let t=r=>Buffer.from(r,"base64"),n;e.config.warmup==="face"?n=t(y1):n=t(A1);let s;if("node"in je){let r=(void 0).decodeJpeg(n),a=r.expandDims(0);e.tf.dispose(r),s=await e.detect(a,e.config),e.tf.dispose(a)}else e.config.debug&&ie("Warmup tfjs-node not loaded");return s}async function Cxe(e){let t;return typeof createImageBitmap=="function"?t=await kxe(e):typeof Image!="undefined"||fe.Canvas!==void 0?t=await Ixe(e):t=await Sxe(e),t}async function Txe(e){let t=ss(),n=Zs();if(t!=="webgl"&&t!=="humangl"||!n||!n.checkCompileCompletion)return;Z().set("ENGINE_COMPILE_ONLY",!0);let s=sn().state.numTensors,r=[];for(let[i,l]of Object.entries(e).filter(([u,c])=>u!==null&&c!==null)){let u=l.inputs&&l.inputs[0]&&l.inputs[0].shape?[...l.inputs[0].shape]:[1,64,64,3],c=l.inputs&&l.inputs[0]&&l.inputs[0].dtype?l.inputs[0].dtype:"float32";for(let d=0;d<u.length;d++)u[d]===-1&&(u[d]=d===0?1:64);let p=Wt(u,c);try{let d=l.execute(p);r.push(i),Array.isArray(d)?d.forEach(h=>ne(h)):ne(d)}catch(d){ie("compile fail model:",i)}ne(p)}let a=await n.checkCompileCompletionAsync();n.getUniformLocations(),ie("compile pass models:",r),ie("compile pass kernels:",a.length),Z().set("ENGINE_COMPILE_ONLY",!1);let o=sn().state.numTensors;o-s>0&&ie("tensor leak:",o-s)}async function ZE(e,t){let n=ue();return e.state="warmup",t&&(e.config=Xt(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?{face:[],body:[],hand:[],gesture:[],object:[],performance:e.performance,timestamp:ue(),persons:[],error:null}:new Promise(async s=>{await Txe(e.models);let r=await Cxe(e),a=ue();e.config.debug&&ie("warmup",e.config.warmup,Math.round(a-n),"ms"),e.emit("warmup"),s(r)})}var Od,tf,nf,x1,B4=class{constructor(t){me(this,"version");me(this,"config");me(this,"result");me(this,"state");me(this,"process");me(this,"tf");me(this,"env");me(this,"draw");me(this,"models");me(this,"events");me(this,"faceTriangulation");me(this,"faceUVMap");me(this,"performance");Yd(this,Od,void 0);Yd(this,tf,void 0);Yd(this,nf,void 0);me(this,"gl");me(this,"analyze",(...t)=>{if(!Zd(this,tf))return;let n=this.tf.engine().state.numTensors,s=Zd(this,Od);Jd(this,Od,n);let r=n-s;r!==0&&ie(...t,r)});Yd(this,x1,t=>{if(!Zd(this,nf))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof tt))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});me(this,"similarity",M4);me(this,"distance",ef);me(this,"match",z4);me(this,"emit",t=>{var n;this.events&&this.events.dispatchEvent&&((n=this.events)==null||n.dispatchEvent(new Event(t)))});var s;this.env=fe;let n=(((s=Uh)==null?void 0:s.tfjs)||Gy).replace(/-(.*)/,"");Ba.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${n}/dist/`,Ba.modelBasePath=fe.browser?"../models/":"file://models/",Ba.backend=fe.browser?"humangl":"tensorflow",this.version=hb,Object.defineProperty(this,"version",{value:hb}),this.config=JSON.parse(JSON.stringify(Ba)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=Xt(this.config,t)),IT(this.config),this.tf=je,this.state="idle",Jd(this,Od,0),Jd(this,tf,!1),Jd(this,nf,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new Qh,this.draw={options:Vn,canvas:(r,a)=>_4(r,a),face:(r,a,o)=>Rd(r,a,o),body:(r,a,o)=>_d(r,a,o),hand:(r,a,o)=>Dd(r,a,o),gesture:(r,a,o)=>Pd(r,a,o),object:(r,a,o)=>$d(r,a,o),person:(r,a,o)=>R4(r,a,o),all:(r,a,o)=>D4(r,a,o)},this.result={face:[],body:[],hand:[],gesture:[],object:[],performance:{},timestamp:0,persons:[],error:null},this.process={tensor:null,canvas:null},this.faceTriangulation=ON,this.faceUVMap=MN,this.gl=Pt,this.emit("create")}reset(){let t=this.config.backend;this.config=JSON.parse(JSON.stringify(Ba)),this.config.backend=t}validate(t){return t3(Ba,t||this.config)}now(){return ue()}image(t,n=!0){return gd(t,this.config,n)}async segmentation(t,n){return OE(t,n,this.config)}enhance(t){return Kb(t)}compare(t,n){return kT(this.config,t,n)}async init(){await g1(this,!0),await this.tf.ready()}async load(t){this.state="load";let n=ue(),s=Object.values(this.models).filter(o=>o).length;t&&(this.config=Xt(this.config,t)),this.env.initial&&(this.config.debug&&ie(`version: ${this.version}`),this.config.debug&&ie(`tfjs version: ${this.tf.version["tfjs-core"]}`),await g1(this)||ie("error: backend check failed"),await Lc(),this.env.browser&&(this.config.debug&&ie("configuration:",this.config),this.config.debug&&ie("environment:",this.env),this.config.debug&&ie("tf flags:",this.tf.ENV.flags))),await S4(this),this.env.initial&&this.config.debug&&ie("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.env.initial=!1,Object.values(this.models).filter(o=>o).length!==s&&(await C4(this),this.emit("load"));let a=Math.trunc(ue()-n);a>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+a:a)}next(t=this.result){return qE(t,this.config)}getModelStats(){return I4(this)}async warmup(t){let n=ue(),s=await ZE(this,t),r=ue();return this.performance.warmup=Math.trunc(r-n),s}async profile(t,n){let s=await this.tf.profile(()=>this.detect(t,n)),r={};for(let i of s.kernels)r[i.name]?r[i.name]+=i.kernelTimeMs:r[i.name]=i.kernelTimeMs;let a=[];Object.entries(r).forEach(i=>a.push({name:i[0],ms:i[1]})),a.sort((i,l)=>l.ms-i.ms),a.length=20;let o={};for(let i of a)o[i.name]=i.ms;return o}async detect(t,n){return this.state="detect",new Promise(async s=>{var g,y,x,A,b,w,k,S,E,R,P,_,$,T,F,G,q,z,K,B,ee,Q;this.state="config";let r;this.config=Xt(this.config,n),this.state="check";let a=Zd(this,x1).call(this,t);a&&(ie(a,t),this.emit("error"),s({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:ue(),persons:[],error:a}));let o=ue();await g1(this),await this.load(),r=ue(),this.state="image";let i=await gd(t,this.config);if(this.process=i,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(ue()-r):Math.trunc(ue()-r),this.analyze("Get Image:"),!i.tensor){this.config.debug&&ie("could not convert input to tensor"),this.emit("error"),s({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:ue(),persons:[],error:"could not convert input to tensor"});return}this.emit("image"),r=ue(),this.config.skipAllowed=await wT(this.config,i.tensor),this.performance.totalFrames||(this.performance.totalFrames=0),this.performance.cachedFrames||(this.performance.cachedFrames=0),this.performance.totalFrames++,this.config.skipAllowed&&this.performance.cachedFrames++,this.performance.cacheCheck=this.env.perfadd?(this.performance.cacheCheck||0)+Math.trunc(ue()-r):Math.trunc(ue()-r),this.analyze("Check Changed:");let l=[],u=[],c=[],p=[];this.state="detect:face",this.config.async?(l=this.config.face.enabled?F4(this,i.tensor):[],this.performance.face&&delete this.performance.face):(r=ue(),l=this.config.face.enabled?await F4(this,i.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.config.async&&(this.config.body.maxDetected===-1||this.config.hand.maxDetected===-1)&&(l=await l),this.analyze("Start Body:"),this.state="detect:body";let d=this.config.body.maxDetected===-1?Xt(this.config,{body:{maxDetected:this.config.face.enabled?1*l.length:1}}):this.config;this.config.async?((g=this.config.body.modelPath)!=null&&g.includes("posenet")?u=this.config.body.enabled?v4(i.tensor,d):[]:(y=this.config.body.modelPath)!=null&&y.includes("blazepose")?u=this.config.body.enabled?$b(i.tensor,d):[]:(x=this.config.body.modelPath)!=null&&x.includes("efficientpose")?u=this.config.body.enabled?Bb(i.tensor,d):[]:(A=this.config.body.modelPath)!=null&&A.includes("movenet")&&(u=this.config.body.enabled?f4(i.tensor,d):[]),this.performance.body&&delete this.performance.body):(r=ue(),(b=this.config.body.modelPath)!=null&&b.includes("posenet")?u=this.config.body.enabled?await v4(i.tensor,d):[]:(w=this.config.body.modelPath)!=null&&w.includes("blazepose")?u=this.config.body.enabled?await $b(i.tensor,d):[]:(k=this.config.body.modelPath)!=null&&k.includes("efficientpose")?u=this.config.body.enabled?await Bb(i.tensor,d):[]:(S=this.config.body.modelPath)!=null&&S.includes("movenet")&&(u=this.config.body.enabled?await f4(i.tensor,d):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let h=this.config.hand.maxDetected===-1?Xt(this.config,{hand:{maxDetected:this.config.face.enabled?2*l.length:1}}):this.config;this.config.async?((R=(E=this.config.hand.detector)==null?void 0:E.modelPath)!=null&&R.includes("handdetect")?c=this.config.hand.enabled?n4(i.tensor,h):[]:(_=(P=this.config.hand.detector)==null?void 0:P.modelPath)!=null&&_.includes("handtrack")&&(c=this.config.hand.enabled?o4(i.tensor,h):[]),this.performance.hand&&delete this.performance.hand):(r=ue(),(T=($=this.config.hand.detector)==null?void 0:$.modelPath)!=null&&T.includes("handdetect")?c=this.config.hand.enabled?await n4(i.tensor,h):[]:(G=(F=this.config.hand.detector)==null?void 0:F.modelPath)!=null&&G.includes("handtrack")&&(c=this.config.hand.enabled?await o4(i.tensor,h):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?((q=this.config.object.modelPath)!=null&&q.includes("nanodet")?p=this.config.object.enabled?g4(i.tensor,this.config):[]:(z=this.config.object.modelPath)!=null&&z.includes("centernet")&&(p=this.config.object.enabled?Ob(i.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=ue(),(K=this.config.object.modelPath)!=null&&K.includes("nanodet")?p=this.config.object.enabled?await g4(i.tensor,this.config):[]:(B=this.config.object.modelPath)!=null&&B.includes("centernet")&&(p=this.config.object.enabled?await Ob(i.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([l,u,c,p]=await Promise.all([l,u,c,p])),this.state="detect:gesture";let f=[];this.config.gesture.enabled&&(r=ue(),f=[...GE(l),...UE(u),...jE(c),...HE(l)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(ue()-o):Math.trunc(ue()-o);let m=((Q=(ee=this.process)==null?void 0:ee.tensor)==null?void 0:Q.shape)||[];this.result={face:l,body:u,hand:c,gesture:f,object:p,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,get persons(){return KE(l,u,c,f,m)}},ne(i.tensor),this.emit("detect"),this.state="idle",s(this.result)})}};Od=new WeakMap,tf=new WeakMap,nf=new WeakMap,x1=new WeakMap;return KR(Exe);})();
+2Q==`;async function kxe(e){let t=(r,a="application/octet-stream")=>fetch(`data:${a};base64,${r}`).then(o=>o.blob()),n,s;switch(e.config.warmup){case"face":n=await t(g1);break;case"body":case"full":n=await t(y1);break;default:n=null}if(n){let r=await createImageBitmap(n);s=await e.detect(r,e.config),r.close()}return s}async function Ixe(e){return new Promise(t=>{let n;switch(e.config.warmup){case"face":n="data:image/jpeg;base64,"+g1;break;case"full":case"body":n="data:image/jpeg;base64,"+y1;break;default:n=null}let s;if(typeof Image!="undefined")s=new Image;else if(fe.Image)s=new fe.Image;else return;s.onload=async()=>{let r=is(s.naturalWidth,s.naturalHeight);if(!r)ie("Warmup: Canvas not found"),t(void 0);else{let a=r.getContext("2d");a&&a.drawImage(s,0,0);let o=await e.image(r),i=await e.detect(o.tensor,e.config);t(i)}},n?s.src=n:t(void 0)})}async function Sxe(e){let t=r=>Buffer.from(r,"base64"),n;e.config.warmup==="face"?n=t(g1):n=t(y1);let s;if("node"in je){let r=(void 0).decodeJpeg(n),a=r.expandDims(0);e.tf.dispose(r),s=await e.detect(a,e.config),e.tf.dispose(a)}else e.config.debug&&ie("Warmup tfjs-node not loaded");return s}async function Cxe(e){let t;return typeof createImageBitmap=="function"?t=await kxe(e):typeof Image!="undefined"||fe.Canvas!==void 0?t=await Ixe(e):t=await Sxe(e),t}async function Txe(e){if(!X().flagRegistry.ENGINE_COMPILE_ONLY)return;let t=ss(),n=Zs();if(t!=="webgl"&&t!=="humangl"||!n||!n.checkCompileCompletion)return;X().set("ENGINE_COMPILE_ONLY",!0);let s=sn().state.numTensors,r=[];for(let[i,l]of Object.entries(e).filter(([u,c])=>u!==null&&c!==null)){let u=l.inputs&&l.inputs[0]&&l.inputs[0].shape?[...l.inputs[0].shape]:[1,64,64,3],c=l.inputs&&l.inputs[0]&&l.inputs[0].dtype?l.inputs[0].dtype:"float32";for(let d=0;d<u.length;d++)u[d]===-1&&(u[d]=d===0?1:64);let p=Wt(u,c);try{let d=l.execute(p);r.push(i),Array.isArray(d)?d.forEach(h=>ne(h)):ne(d)}catch(d){ie("compile fail model:",i)}ne(p)}let a=await n.checkCompileCompletionAsync();n.getUniformLocations(),ie("compile pass models:",r),ie("compile pass kernels:",a.length),X().set("ENGINE_COMPILE_ONLY",!1);let o=sn().state.numTensors;o-s>0&&ie("tensor leak:",o-s)}async function ZE(e,t){let n=ue();return e.state="warmup",t&&(e.config=Xt(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?{face:[],body:[],hand:[],gesture:[],object:[],performance:e.performance,timestamp:ue(),persons:[],error:null}:new Promise(async s=>{await Txe(e.models);let r=await Cxe(e),a=ue();e.config.debug&&ie("warmup",e.config.warmup,Math.round(a-n),"ms"),e.emit("warmup"),s(r)})}var Fd,ef,tf,A1,B4=class{constructor(t){me(this,"version");me(this,"config");me(this,"result");me(this,"state");me(this,"process");me(this,"tf");me(this,"env");me(this,"draw");me(this,"models");me(this,"events");me(this,"faceTriangulation");me(this,"faceUVMap");me(this,"performance");Zd(this,Fd,void 0);Zd(this,ef,void 0);Zd(this,tf,void 0);me(this,"gl");me(this,"analyze",(...t)=>{if(!Kd(this,ef))return;let n=this.tf.engine().state.numTensors,s=Kd(this,Fd);Yd(this,Fd,n);let r=n-s;r!==0&&ie(...t,r)});Zd(this,A1,t=>{if(!Kd(this,tf))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof tt))return"input must be a tensor";try{this.tf.getBackend()}catch(n){return"backend not loaded"}return null});me(this,"similarity",M4);me(this,"distance",Qh);me(this,"match",z4);me(this,"emit",t=>{var n;this.events&&this.events.dispatchEvent&&((n=this.events)==null||n.dispatchEvent(new Event(t)))});var s;this.env=fe;let n=(((s=Vh)==null?void 0:s.tfjs)||Gy).replace(/-(.*)/,"");La.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${n}/dist/`,La.modelBasePath=fe.browser?"../models/":"file://models/",La.backend=fe.browser?"humangl":"tensorflow",this.version=hb,Object.defineProperty(this,"version",{value:hb}),this.config=JSON.parse(JSON.stringify(La)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=Xt(this.config,t)),IT(this.config),this.tf=je,this.state="idle",Yd(this,Fd,0),Yd(this,ef,!1),Yd(this,tf,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new Jh,this.draw={options:Vn,canvas:(r,a)=>_4(r,a),face:(r,a,o)=>Ed(r,a,o),body:(r,a,o)=>Rd(r,a,o),hand:(r,a,o)=>_d(r,a,o),gesture:(r,a,o)=>$d(r,a,o),object:(r,a,o)=>Dd(r,a,o),person:(r,a,o)=>R4(r,a,o),all:(r,a,o)=>D4(r,a,o)},this.result={face:[],body:[],hand:[],gesture:[],object:[],performance:{},timestamp:0,persons:[],error:null},this.process={tensor:null,canvas:null},this.faceTriangulation=ON,this.faceUVMap=MN,this.gl=Pt,this.emit("create")}reset(){let t=this.config.backend;this.config=JSON.parse(JSON.stringify(La)),this.config.backend=t}validate(t){return e3(La,t||this.config)}now(){return ue()}image(t,n=!0){return md(t,this.config,n)}async segmentation(t,n){return OE(t,n,this.config)}enhance(t){return Kb(t)}compare(t,n){return kT(this.config,t,n)}async init(){await m1(this,!0),await this.tf.ready()}async load(t){this.state="load";let n=ue(),s=Object.values(this.models).filter(o=>o).length;t&&(this.config=Xt(this.config,t)),this.env.initial&&(this.config.debug&&ie(`version: ${this.version}`),this.config.debug&&ie(`tfjs version: ${this.tf.version["tfjs-core"]}`),await m1(this)||ie("error: backend check failed"),await zc(),this.env.browser&&(this.config.debug&&ie("configuration:",this.config),this.config.debug&&ie("environment:",this.env),this.config.debug&&ie("tf flags:",this.tf.ENV.flags))),await S4(this),this.env.initial&&this.config.debug&&ie("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.env.initial=!1,Object.values(this.models).filter(o=>o).length!==s&&(await C4(this),this.emit("load"));let a=Math.trunc(ue()-n);a>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+a:a)}next(t=this.result){return qE(t,this.config)}getModelStats(){return I4(this)}async warmup(t){let n=ue(),s=await ZE(this,t),r=ue();return this.performance.warmup=Math.trunc(r-n),s}async profile(t,n){let s=await this.tf.profile(()=>this.detect(t,n)),r={},a=0;for(let i of s.kernels)r[i.name]?r[i.name]+=i.kernelTimeMs:r[i.name]=i.kernelTimeMs,a+=i.kernelTimeMs;let o=[];Object.entries(r).forEach(i=>o.push({kernel:i[0],time:i[1],perc:0}));for(let i of o)i.perc=Math.round(1e3*i.time/a)/1e3,i.time=Math.round(1e3*i.time)/1e3;return o.sort((i,l)=>l.time-i.time),o.length=20,o}async detect(t,n){return this.state="detect",new Promise(async s=>{var g,y,x,A,b,w,k,S,E,R,P,_,$,T,F,G,q,z,Z,B,ee,Q;this.state="config";let r;this.config=Xt(this.config,n),this.state="check";let a=Kd(this,A1).call(this,t);a&&(ie(a,t),this.emit("error"),s({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:ue(),persons:[],error:a}));let o=ue();await m1(this),await this.load(),r=ue(),this.state="image";let i=await md(t,this.config);if(this.process=i,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(ue()-r):Math.trunc(ue()-r),this.analyze("Get Image:"),!i.tensor){this.config.debug&&ie("could not convert input to tensor"),this.emit("error"),s({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:ue(),persons:[],error:"could not convert input to tensor"});return}this.emit("image"),r=ue(),this.config.skipAllowed=await wT(this.config,i.tensor),this.performance.totalFrames||(this.performance.totalFrames=0),this.performance.cachedFrames||(this.performance.cachedFrames=0),this.performance.totalFrames++,this.config.skipAllowed&&this.performance.cachedFrames++,this.performance.cacheCheck=this.env.perfadd?(this.performance.cacheCheck||0)+Math.trunc(ue()-r):Math.trunc(ue()-r),this.analyze("Check Changed:");let l=[],u=[],c=[],p=[];this.state="detect:face",this.config.async?(l=this.config.face.enabled?F4(this,i.tensor):[],this.performance.face&&delete this.performance.face):(r=ue(),l=this.config.face.enabled?await F4(this,i.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.config.async&&(this.config.body.maxDetected===-1||this.config.hand.maxDetected===-1)&&(l=await l),this.analyze("Start Body:"),this.state="detect:body";let d=this.config.body.maxDetected===-1?Xt(this.config,{body:{maxDetected:this.config.face.enabled?1*l.length:1}}):this.config;this.config.async?((g=this.config.body.modelPath)!=null&&g.includes("posenet")?u=this.config.body.enabled?v4(i.tensor,d):[]:(y=this.config.body.modelPath)!=null&&y.includes("blazepose")?u=this.config.body.enabled?$b(i.tensor,d):[]:(x=this.config.body.modelPath)!=null&&x.includes("efficientpose")?u=this.config.body.enabled?Bb(i.tensor,d):[]:(A=this.config.body.modelPath)!=null&&A.includes("movenet")&&(u=this.config.body.enabled?f4(i.tensor,d):[]),this.performance.body&&delete this.performance.body):(r=ue(),(b=this.config.body.modelPath)!=null&&b.includes("posenet")?u=this.config.body.enabled?await v4(i.tensor,d):[]:(w=this.config.body.modelPath)!=null&&w.includes("blazepose")?u=this.config.body.enabled?await $b(i.tensor,d):[]:(k=this.config.body.modelPath)!=null&&k.includes("efficientpose")?u=this.config.body.enabled?await Bb(i.tensor,d):[]:(S=this.config.body.modelPath)!=null&&S.includes("movenet")&&(u=this.config.body.enabled?await f4(i.tensor,d):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let h=this.config.hand.maxDetected===-1?Xt(this.config,{hand:{maxDetected:this.config.face.enabled?2*l.length:1}}):this.config;this.config.async?((R=(E=this.config.hand.detector)==null?void 0:E.modelPath)!=null&&R.includes("handdetect")?c=this.config.hand.enabled?n4(i.tensor,h):[]:(_=(P=this.config.hand.detector)==null?void 0:P.modelPath)!=null&&_.includes("handtrack")&&(c=this.config.hand.enabled?o4(i.tensor,h):[]),this.performance.hand&&delete this.performance.hand):(r=ue(),(T=($=this.config.hand.detector)==null?void 0:$.modelPath)!=null&&T.includes("handdetect")?c=this.config.hand.enabled?await n4(i.tensor,h):[]:(G=(F=this.config.hand.detector)==null?void 0:F.modelPath)!=null&&G.includes("handtrack")&&(c=this.config.hand.enabled?await o4(i.tensor,h):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?((q=this.config.object.modelPath)!=null&&q.includes("nanodet")?p=this.config.object.enabled?g4(i.tensor,this.config):[]:(z=this.config.object.modelPath)!=null&&z.includes("centernet")&&(p=this.config.object.enabled?Ob(i.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=ue(),(Z=this.config.object.modelPath)!=null&&Z.includes("nanodet")?p=this.config.object.enabled?await g4(i.tensor,this.config):[]:(B=this.config.object.modelPath)!=null&&B.includes("centernet")&&(p=this.config.object.enabled?await Ob(i.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([l,u,c,p]=await Promise.all([l,u,c,p])),this.state="detect:gesture";let f=[];this.config.gesture.enabled&&(r=ue(),f=[...GE(l),...UE(u),...jE(c),...HE(l)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(ue()-r):Math.trunc(ue()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(ue()-o):Math.trunc(ue()-o);let m=((Q=(ee=this.process)==null?void 0:ee.tensor)==null?void 0:Q.shape)||[];this.result={face:l,body:u,hand:c,gesture:f,object:p,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,get persons(){return KE(l,u,c,f,m)}},ne(i.tensor),this.emit("detect"),this.state="idle",s(this.result)})}};Fd=new WeakMap,ef=new WeakMap,tf=new WeakMap,A1=new WeakMap;return KR(Exe);})();
diff --git a/dist/human.node-gpu.d.ts b/dist/human.node-gpu.d.ts
index 4f1e9723..925302ef 100644
--- a/dist/human.node-gpu.d.ts
+++ b/dist/human.node-gpu.d.ts
@@ -1330,7 +1330,11 @@ declare class Human {
      * - result object will contain total exeuction time information for top-20 kernels
      * - actual detection object can be accessed via `human.result`
      */
-    profile(input: Input, userConfig?: Partial<Config>): Promise<Record<string, number>>;
+    profile(input: Input, userConfig?: Partial<Config>): Promise<Array<{
+        kernel: string;
+        time: number;
+        perc: number;
+    }>>;
     /** Main detection method
      * - Analyze configuration: {@link Config}
      * - Pre-process input: {@link Input}
diff --git a/dist/human.node-gpu.js b/dist/human.node-gpu.js
index 884a7669..19fd89d6 100644
--- a/dist/human.node-gpu.js
+++ b/dist/human.node-gpu.js
@@ -4,7 +4,7 @@
   author: <https://github.com/vladmandic>'
 */
 
-var An=Object.create;var h2=Object.defineProperty;var sn=Object.getOwnPropertyDescriptor;var an=Object.getOwnPropertyNames;var ln=Object.getPrototypeOf,yn=Object.prototype.hasOwnProperty;var xn=(e,t,o)=>t in e?h2(e,t,{enumerable:!0,configurable:!0,writable:!0,value:o}):e[t]=o;var cn=(e,t)=>()=>(t||e((t={exports:{}}).exports,t),t.exports),ue=(e,t)=>{for(var o in t)h2(e,o,{get:t[o],enumerable:!0})},dt=(e,t,o,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of an(t))!yn.call(e,r)&&r!==o&&h2(e,r,{get:()=>t[r],enumerable:!(n=sn(t,r))||n.enumerable});return e};var Z=(e,t,o)=>(o=e!=null?An(ln(e)):{},dt(t||!e||!e.__esModule?h2(o,"default",{value:e,enumerable:!0}):o,e)),dn=e=>dt(h2({},"__esModule",{value:!0}),e);var T=(e,t,o)=>(xn(e,typeof t!="symbol"?t+"":t,o),o),ft=(e,t,o)=>{if(!t.has(e))throw TypeError("Cannot "+o)};var b2=(e,t,o)=>(ft(e,t,"read from private field"),o?o.call(e):t.get(e)),g2=(e,t,o)=>{if(t.has(e))throw TypeError("Cannot add the same private member more than once");t instanceof WeakSet?t.add(e):t.set(e,o)},M2=(e,t,o,n)=>(ft(e,t,"write to private field"),n?n.call(e,o):t.set(e,o),o);var D=cn((f7,S5)=>{"use strict";var pt=Object.defineProperty,fn=Object.getOwnPropertyDescriptor,mn=Object.getOwnPropertyNames,pn=Object.prototype.hasOwnProperty,z5=(e,t,o,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of mn(t))!pn.call(e,r)&&r!==o&&pt(e,r,{get:()=>t[r],enumerable:!(n=fn(t,r))||n.enumerable});return e},un=(e,t,o)=>(z5(e,t,"default"),o&&z5(o,t,"default")),hn=e=>z5(pt({},"__esModule",{value:!0}),e),ut={};S5.exports=hn(ut);un(ut,require("@tensorflow/tfjs-node-gpu"),S5.exports)});var y7={};ue(y7,{Human:()=>it,default:()=>it,defaults:()=>he,draw:()=>tt,env:()=>v,match:()=>at,models:()=>R5});module.exports=dn(y7);function p(...e){let t=new Date,o=`${t.getHours().toString().padStart(2,"0")}:${t.getMinutes().toString().padStart(2,"0")}:${t.getSeconds().toString().padStart(2,"0")}.${t.getMilliseconds().toString().padStart(3,"0")}`;e&&console.log(o,"Human:",...e)}function mt(e,t){let o=e.endsWith("/")?"":"/",r=t.startsWith(".")||t.startsWith("/")||t.startsWith("http:")||t.startsWith("https:")||t.startsWith("file:")?`${t}`:`${e}${o}${t}`;if(!r.toLocaleLowerCase().includes(".json"))throw new Error(`modelpath error: expecting json file: ${r}`);return r}var h=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function E5(e,t,o="config",n=[]){for(let r of Object.keys(t))if(typeof t[r]=="object")E5(e[r],t[r],r,n);else{let A=e&&typeof e[r]!="undefined";A||n.push({reason:"unknown property",where:`${o}.${r} = ${t[r]}`});let s=e&&typeof e[r]==typeof t[r];A&&!s&&n.push({reason:"property type mismatch",where:`${o}.${r} = ${t[r]}`,expected:typeof e[r]})}return t.debug&&o==="config"&&n.length>0&&p("invalid configuration",n),n}function r0(...e){let t=o=>o&&typeof o=="object";return e.reduce((o,n)=>(Object.keys(n||{}).forEach(r=>{let A=o[r],s=n[r];Array.isArray(A)&&Array.isArray(s)?o[r]=A.concat(...s):t(A)&&t(s)?o[r]=r0(A,s):o[r]=s}),o),{})}var he={backend:"",modelBasePath:"",cacheModels:!0,wasmPath:"",wasmPlatformFetch:!1,debug:!1,async:!0,warmup:"full",cacheSensitivity:.7,skipAllowed:!1,deallocate:!1,filter:{enabled:!0,equalization:!1,width:0,height:0,flip:!1,return:!0,brightness:0,contrast:0,sharpness:0,blur:0,saturation:0,hue:0,negative:!1,sepia:!1,vintage:!1,kodachrome:!1,technicolor:!1,polaroid:!1,pixelate:0},gesture:{enabled:!0},face:{enabled:!0,detector:{modelPath:"blazeface.json",rotation:!0,maxDetected:1,skipFrames:99,skipTime:2500,minConfidence:.2,iouThreshold:.1,mask:!1,return:!1},mesh:{enabled:!0,modelPath:"facemesh.json",keepInvalid:!1},attention:{enabled:!1,modelPath:"facemesh-attention.json"},iris:{enabled:!0,modelPath:"iris.json"},emotion:{enabled:!0,minConfidence:.1,skipFrames:99,skipTime:1500,modelPath:"emotion.json"},description:{enabled:!0,modelPath:"faceres.json",skipFrames:99,skipTime:3e3,minConfidence:.1},antispoof:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"antispoof.json"},liveness:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"liveness.json"}},body:{enabled:!0,modelPath:"movenet-lightning.json",maxDetected:-1,minConfidence:.3,skipFrames:1,skipTime:200},hand:{enabled:!0,rotation:!0,skipFrames:99,skipTime:1e3,minConfidence:.5,iouThreshold:.2,maxDetected:-1,landmarks:!0,detector:{modelPath:"handtrack.json"},skeleton:{modelPath:"handlandmark-full.json"}},object:{enabled:!1,modelPath:"mb3-centernet.json",minConfidence:.2,iouThreshold:.4,maxDetected:10,skipFrames:99,skipTime:2e3},segmentation:{enabled:!1,modelPath:"selfie.json",blur:8}};var p0=Z(D());var N=Z(D());var ht=`
+var An=Object.create;var h2=Object.defineProperty;var sn=Object.getOwnPropertyDescriptor;var an=Object.getOwnPropertyNames;var ln=Object.getPrototypeOf,yn=Object.prototype.hasOwnProperty;var xn=(e,t,o)=>t in e?h2(e,t,{enumerable:!0,configurable:!0,writable:!0,value:o}):e[t]=o;var cn=(e,t)=>()=>(t||e((t={exports:{}}).exports,t),t.exports),ue=(e,t)=>{for(var o in t)h2(e,o,{get:t[o],enumerable:!0})},dt=(e,t,o,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of an(t))!yn.call(e,r)&&r!==o&&h2(e,r,{get:()=>t[r],enumerable:!(n=sn(t,r))||n.enumerable});return e};var Z=(e,t,o)=>(o=e!=null?An(ln(e)):{},dt(t||!e||!e.__esModule?h2(o,"default",{value:e,enumerable:!0}):o,e)),dn=e=>dt(h2({},"__esModule",{value:!0}),e);var T=(e,t,o)=>(xn(e,typeof t!="symbol"?t+"":t,o),o),ft=(e,t,o)=>{if(!t.has(e))throw TypeError("Cannot "+o)};var b2=(e,t,o)=>(ft(e,t,"read from private field"),o?o.call(e):t.get(e)),g2=(e,t,o)=>{if(t.has(e))throw TypeError("Cannot add the same private member more than once");t instanceof WeakSet?t.add(e):t.set(e,o)},M2=(e,t,o,n)=>(ft(e,t,"write to private field"),n?n.call(e,o):t.set(e,o),o);var D=cn((f7,S5)=>{"use strict";var pt=Object.defineProperty,fn=Object.getOwnPropertyDescriptor,mn=Object.getOwnPropertyNames,pn=Object.prototype.hasOwnProperty,z5=(e,t,o,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of mn(t))!pn.call(e,r)&&r!==o&&pt(e,r,{get:()=>t[r],enumerable:!(n=fn(t,r))||n.enumerable});return e},un=(e,t,o)=>(z5(e,t,"default"),o&&z5(o,t,"default")),hn=e=>z5(pt({},"__esModule",{value:!0}),e),ut={};S5.exports=hn(ut);un(ut,require("@tensorflow/tfjs-node-gpu"),S5.exports)});var y7={};ue(y7,{Human:()=>it,default:()=>it,defaults:()=>he,draw:()=>tt,env:()=>v,match:()=>at,models:()=>R5});module.exports=dn(y7);function p(...e){let t=new Date,o=`${t.getHours().toString().padStart(2,"0")}:${t.getMinutes().toString().padStart(2,"0")}:${t.getSeconds().toString().padStart(2,"0")}.${t.getMilliseconds().toString().padStart(3,"0")}`;e&&console.log(o,"Human:",...e)}function mt(e,t){let o=e.endsWith("/")?"":"/",r=t.startsWith(".")||t.startsWith("/")||t.startsWith("http:")||t.startsWith("https:")||t.startsWith("file:")?`${t}`:`${e}${o}${t}`;if(!r.toLocaleLowerCase().includes(".json"))throw new Error(`modelpath error: expecting json file: ${r}`);return r}var h=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function E5(e,t,o="config",n=[]){for(let r of Object.keys(t))if(typeof t[r]=="object")E5(e[r],t[r],r,n);else{let A=e&&typeof e[r]!="undefined";A||n.push({reason:"unknown property",where:`${o}.${r} = ${t[r]}`});let s=e&&typeof e[r]==typeof t[r];A&&!s&&n.push({reason:"property type mismatch",where:`${o}.${r} = ${t[r]}`,expected:typeof e[r]})}return t.debug&&o==="config"&&n.length>0&&p("invalid configuration",n),n}function r0(...e){let t=o=>o&&typeof o=="object";return e.reduce((o,n)=>(Object.keys(n||{}).forEach(r=>{let A=o[r],s=n[r];Array.isArray(A)&&Array.isArray(s)?o[r]=A.concat(...s):t(A)&&t(s)?o[r]=r0(A,s):o[r]=s}),o),{})}var he={backend:"",modelBasePath:"",cacheModels:!0,wasmPath:"",wasmPlatformFetch:!1,debug:!1,async:!0,warmup:"full",cacheSensitivity:.7,skipAllowed:!1,deallocate:!1,filter:{enabled:!0,equalization:!1,width:0,height:0,flip:!1,return:!0,brightness:0,contrast:0,sharpness:0,blur:0,saturation:0,hue:0,negative:!1,sepia:!1,vintage:!1,kodachrome:!1,technicolor:!1,polaroid:!1,pixelate:0},gesture:{enabled:!0},face:{enabled:!0,detector:{modelPath:"blazeface.json",rotation:!0,maxDetected:1,skipFrames:99,skipTime:2500,minConfidence:.2,iouThreshold:.1,mask:!1,return:!1},mesh:{enabled:!0,modelPath:"facemesh.json",keepInvalid:!1},attention:{enabled:!1,modelPath:"facemesh-attention.json"},iris:{enabled:!0,modelPath:"iris.json"},emotion:{enabled:!0,minConfidence:.1,skipFrames:99,skipTime:1500,modelPath:"emotion.json"},description:{enabled:!0,modelPath:"faceres.json",skipFrames:99,skipTime:3e3,minConfidence:.1},antispoof:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"antispoof.json"},liveness:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"liveness.json"}},body:{enabled:!0,modelPath:"movenet-lightning.json",maxDetected:-1,minConfidence:.3,skipFrames:1,skipTime:200},hand:{enabled:!0,rotation:!0,skipFrames:99,skipTime:1e3,minConfidence:.5,iouThreshold:.2,maxDetected:-1,landmarks:!0,detector:{modelPath:"handtrack.json"},skeleton:{modelPath:"handlandmark-full.json"}},object:{enabled:!1,modelPath:"mb3-centernet.json",minConfidence:.2,iouThreshold:.4,maxDetected:10,skipFrames:99,skipTime:2e3},segmentation:{enabled:!1,modelPath:"selfie.json",blur:8}};var p0=Z(D());var O=Z(D());var ht=`
   precision highp float;
   attribute vec2 pos;
   attribute vec2 uv;
@@ -96,7 +96,7 @@ var An=Object.create;var h2=Object.defineProperty;var sn=Object.getOwnPropertyDe
     c31 * m[6] + c32 * m[7] + c33 * m[8];
     gl_FragColor.a = c22.a;
   }
-`;var C5=(e,t,o)=>{let n=new RegExp("\\b"+t+" \\w+ (\\w+)","ig");e.replace(n,(r,A)=>(o[A]=0,r))},j5=class{constructor(t,o,n){T(this,"uniform",{});T(this,"attribute",{});T(this,"gl");T(this,"id");T(this,"compile",(t,o)=>{let n=this.gl.createShader(o);return n?(this.gl.shaderSource(n,t),this.gl.compileShader(n),this.gl.getShaderParameter(n,this.gl.COMPILE_STATUS)?n:(p(`filter: gl compile failed: ${this.gl.getShaderInfoLog(n)}`),null)):(p("filter: could not create shader"),null)});this.gl=t;let r=this.compile(o,this.gl.VERTEX_SHADER),A=this.compile(n,this.gl.FRAGMENT_SHADER);if(this.id=this.gl.createProgram(),!(!r||!A)){if(!this.id){p("filter: could not create webgl program");return}if(this.gl.attachShader(this.id,r),this.gl.attachShader(this.id,A),this.gl.linkProgram(this.id),!this.gl.getProgramParameter(this.id,this.gl.LINK_STATUS)){p(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);return}this.gl.useProgram(this.id),C5(o,"attribute",this.attribute);for(let s in this.attribute)this.attribute[s]=this.gl.getAttribLocation(this.id,s);C5(o,"uniform",this.uniform),C5(n,"uniform",this.uniform);for(let s in this.uniform)this.uniform[s]=this.gl.getUniformLocation(this.id,s)}}};function vt(){let e=0,t=null,o=!1,n=-1,r=[null,null],A=[],s=null,a=null,i=R0(100,100),x={},c={INTERMEDIATE:1},l=i.getContext("webgl");if(!l){p("filter: cannot get webgl context");return}this.gl=l;function y(b,d){if(!(b===i.width&&d===i.height)){if(i.width=b,i.height=d,!s){let M=new Float32Array([-1,-1,0,1,1,-1,1,1,-1,1,0,0,-1,1,0,0,1,-1,1,1,1,1,1,0]);s=l.createBuffer(),l.bindBuffer(l.ARRAY_BUFFER,s),l.bufferData(l.ARRAY_BUFFER,M,l.STATIC_DRAW),l.pixelStorei(l.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}l.viewport(0,0,i.width,i.height),r=[null,null]}}function f(b,d){let M=l.createFramebuffer();l.bindFramebuffer(l.FRAMEBUFFER,M);let S=l.createRenderbuffer();l.bindRenderbuffer(l.RENDERBUFFER,S);let w=l.createTexture();return l.bindTexture(l.TEXTURE_2D,w),l.texImage2D(l.TEXTURE_2D,0,l.RGBA,b,d,0,l.RGBA,l.UNSIGNED_BYTE,null),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MAG_FILTER,l.LINEAR),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MIN_FILTER,l.LINEAR),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_S,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_T,l.CLAMP_TO_EDGE),l.framebufferTexture2D(l.FRAMEBUFFER,l.COLOR_ATTACHMENT0,l.TEXTURE_2D,w,0),l.bindTexture(l.TEXTURE_2D,null),l.bindFramebuffer(l.FRAMEBUFFER,null),{fbo:M,texture:w}}function u(b){return r[b]=r[b]||f(i.width,i.height),r[b]}function m(b=0){if(!a)return;let d=null,M=null,S=!1;e===0?d=t:d=u(n).texture||null,e++,o&&!(b&c.INTERMEDIATE)?(M=null,S=e%2===0):(n=(n+1)%2,M=u(n).fbo||null),l.bindTexture(l.TEXTURE_2D,d),l.bindFramebuffer(l.FRAMEBUFFER,M),l.uniform1f(a.uniform.flipY,S?-1:1),l.drawArrays(l.TRIANGLES,0,6)}function P(b){if(x[b])return a=x[b],l.useProgram((a?a.id:null)||null),a;if(a=new j5(l,ht,b),!a)return p("filter: could not get webgl program"),null;let d=Float32Array.BYTES_PER_ELEMENT,M=4*d;return l.enableVertexAttribArray(a.attribute.pos),l.vertexAttribPointer(a.attribute.pos,2,l.FLOAT,!1,M,0*d),l.enableVertexAttribArray(a.attribute.uv),l.vertexAttribPointer(a.attribute.uv,2,l.FLOAT,!1,M,2*d),x[b]=a,a}let g={colorMatrix:b=>{let d=new Float32Array(b);d[4]/=255,d[9]/=255,d[14]/=255,d[19]/=255;let M=d[18]===1&&d[3]===0&&d[8]===0&&d[13]===0&&d[15]===0&&d[16]===0&&d[17]===0&&d[19]===0?gt:bt,S=P(M);!S||(l.uniform1fv(S.uniform.m,d),m())},brightness:b=>{let d=(b||0)+1;g.colorMatrix([d,0,0,0,0,0,d,0,0,0,0,0,d,0,0,0,0,0,1,0])},saturation:b=>{let d=(b||0)*2/3+1,M=(d-1)*-.5;g.colorMatrix([d,M,M,0,0,M,d,M,0,0,M,M,d,0,0,0,0,0,1,0])},desaturate:()=>{g.saturation(-1)},contrast:b=>{let d=(b||0)+1,M=-128*(d-1);g.colorMatrix([d,0,0,0,M,0,d,0,0,M,0,0,d,0,M,0,0,0,1,0])},negative:()=>{g.contrast(-2)},hue:b=>{b=(b||0)/180*Math.PI;let d=Math.cos(b),M=Math.sin(b),S=.213,w=.715,j=.072;g.colorMatrix([S+d*(1-S)+M*-S,w+d*-w+M*-w,j+d*-j+M*(1-j),0,0,S+d*-S+M*.143,w+d*(1-w)+M*.14,j+d*-j+M*-.283,0,0,S+d*-S+M*-(1-S),w+d*-w+M*w,j+d*(1-j)+M*j,0,0,0,0,0,1,0])},desaturateLuminance:()=>{g.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},sepia:()=>{g.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},brownie:()=>{g.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},vintagePinhole:()=>{g.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},kodachrome:()=>{g.colorMatrix([1.1285582396593525,-.3967382283601348,-.03992559172921793,0,63.72958762196502,-.16404339962244616,1.0835251566291304,-.05498805115633132,0,24.732407896706203,-.16786010706155763,-.5603416277695248,1.6014850761964943,0,35.62982807460946,0,0,0,1,0])},technicolor:()=>{g.colorMatrix([1.9125277891456083,-.8545344976951645,-.09155508482755585,0,11.793603434377337,-.3087833385928097,1.7658908555458428,-.10601743074722245,0,-70.35205161461398,-.231103377548616,-.7501899197440212,1.847597816108189,0,30.950940869491138,0,0,0,1,0])},polaroid:()=>{g.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},shiftToBGR:()=>{g.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},convolution:b=>{let d=new Float32Array(b),M=1/i.width,S=1/i.height,w=P(Rt);!w||(l.uniform1fv(w.uniform.m,d),l.uniform2f(w.uniform.px,M,S),m())},detectEdges:()=>{g.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},sobelX:()=>{g.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},sobelY:()=>{g.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},sharpen:b=>{let d=b||1;g.convolution.call(this,[0,-1*d,0,-1*d,1+4*d,-1*d,0,-1*d,0])},emboss:b=>{let d=b||1;g.convolution.call(this,[-2*d,-1*d,0,-1*d,1,1*d,0,1*d,2*d])},blur:b=>{let d=b/7/i.width,M=b/7/i.height,S=P(Pt);!S||(l.uniform2f(S.uniform.px,0,M),m(c.INTERMEDIATE),l.uniform2f(S.uniform.px,d,0),m())},pixelate:b=>{let d=b/i.width,M=b/i.height,S=P(Mt);!S||(l.uniform2f(S.uniform.size,d,M),m())}};this.add=function(b){let d=Array.prototype.slice.call(arguments,1),M=g[b];A.push({func:M,args:d})},this.reset=function(){A=[]},this.get=function(){return A},this.apply=function(b){y(b.width,b.height),e=0,t||(t=l.createTexture()),l.bindTexture(l.TEXTURE_2D,t),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_S,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_T,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MIN_FILTER,l.NEAREST),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MAG_FILTER,l.NEAREST),l.texImage2D(l.TEXTURE_2D,0,l.RGBA,l.RGBA,l.UNSIGNED_BYTE,b);for(let d=0;d<A.length;d++){o=d===A.length-1;let M=A[d];M.func.apply(this,M.args||[])}return i},this.draw=function(b){return this.add("brightness",0),this.apply(b)}}var X=Z(D());async function O2(e){let t=e.shape.length===4?X.squeeze(e):e,o=X.split(t,3,2),n=[X.min(o[0]),X.min(o[1]),X.min(o[2])],r=[X.max(o[0]),X.max(o[1]),X.max(o[2])],A=await Promise.all(r.map(f=>f.data())),s=.99*Math.max(A[0][0],A[1][0],A[2][0]),a=[X.sub(o[0],n[0]),X.sub(o[1],n[1]),X.sub(o[2],n[2])],i=[X.sub(r[0],n[0]),X.sub(r[1],n[1]),X.sub(r[2],n[2])],x=[X.div(s,i[0]),X.div(s,i[1]),X.div(s,i[2])],c=[X.mul(a[0],x[0]),X.mul(a[1],x[1]),X.mul(a[2],x[2])],l=X.stack([c[0],c[1],c[2]],2),y=X.reshape(l,[1,t.shape[0],t.shape[1],3]);return X.dispose([...o,...n,...r,...a,...i,...x,...c,l,t]),y}var L2=3840,q=null,i0=null,Ue=null,e0,ae={inputSum:0,cacheDiff:1,sumMethod:0,inputTensor:void 0};function R0(e,t){let o;if(v.browser)if(v.worker){if(typeof OffscreenCanvas=="undefined")throw new Error("canvas error: attempted to run in web worker but OffscreenCanvas is not supported");o=new OffscreenCanvas(e,t)}else{if(typeof document=="undefined")throw new Error("canvas error: attempted to run in browser but DOM is not defined");o=document.createElement("canvas"),o.width=e,o.height=t}else typeof v.Canvas!="undefined"?o=new v.Canvas(e,t):typeof globalThis.Canvas!="undefined"&&(o=new globalThis.Canvas(e,t));return o}function W2(e,t){let o=t||R0(e.width,e.height);return o.getContext("2d").drawImage(e,0,0),o}async function Ye(e,t,o=!0){if(!e)return t.debug&&p("input error: input is missing"),{tensor:null,canvas:null};if(!(e instanceof N.Tensor)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(typeof v.Canvas!="undefined"&&e instanceof v.Canvas)&&!(typeof globalThis.Canvas!="undefined"&&e instanceof globalThis.Canvas)&&!(typeof ImageData!="undefined"&&e instanceof ImageData)&&!(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)&&!(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)&&!(typeof HTMLMediaElement!="undefined"&&e instanceof HTMLMediaElement)&&!(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)&&!(typeof HTMLCanvasElement!="undefined"&&e instanceof HTMLCanvasElement)&&!(typeof OffscreenCanvas!="undefined"&&e instanceof OffscreenCanvas))throw new Error("input error: type is not recognized");if(e instanceof N.Tensor){let n=null;if(e.isDisposedInternal)throw new Error("input error: attempted to use tensor but it is disposed");if(!e.shape)throw new Error("input error: attempted to use tensor without a shape");if(e.shape.length===3){if(e.shape[2]===3)n=N.expandDims(e,0);else if(e.shape[2]===4){let r=N.slice3d(e,[0,0,0],[-1,-1,3]);n=N.expandDims(r,0),N.dispose(r)}}else e.shape.length===4&&(e.shape[3]===3?n=N.clone(e):e.shape[3]===4&&(n=N.slice4d(e,[0,0,0,0],[-1,-1,-1,3])));if(n==null||n.shape.length!==4||n.shape[0]!==1||n.shape[3]!==3)throw new Error(`input error: attempted to use tensor with unrecognized shape: ${e.shape}`);if(n.dtype==="int32"){let r=N.cast(n,"float32");N.dispose(n),n=r}return{tensor:n,canvas:t.filter.return?i0:null}}else{if(typeof e.readyState!="undefined"&&e.readyState<=2)return t.debug&&p("input stream is not ready"),{tensor:null,canvas:q};let n=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,r=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0;if(!n||!r)return t.debug&&p("cannot determine input dimensions"),{tensor:null,canvas:q};let A=n,s=r;if(A>L2&&(A=L2,s=Math.trunc(A*r/n)),s>L2&&(s=L2,A=Math.trunc(s*n/r)),(t.filter.width||0)>0?A=t.filter.width:(t.filter.height||0)>0&&(A=n*((t.filter.height||0)/r)),(t.filter.height||0)>0?s=t.filter.height:(t.filter.width||0)>0&&(s=r*((t.filter.width||0)/n)),!A||!s)throw new Error("input error: cannot determine dimension");(!q||(q==null?void 0:q.width)!==A||(q==null?void 0:q.height)!==s)&&(q=R0(A,s));let a=q.getContext("2d");if(typeof ImageData!="undefined"&&e instanceof ImageData?a.putImageData(e,0,0):t.filter.flip&&typeof a.translate!="undefined"?(a.translate(n,0),a.scale(-1,1),a.drawImage(e,0,0,n,r,0,0,q==null?void 0:q.width,q==null?void 0:q.height),a.setTransform(1,0,0,1,0,0)):a.drawImage(e,0,0,n,r,0,0,q==null?void 0:q.width,q==null?void 0:q.height),(!i0||q.width!==i0.width||(q==null?void 0:q.height)!==(i0==null?void 0:i0.height))&&(i0=R0(q.width,q.height)),t.filter.enabled&&v.webgl.supported?(e0||(e0=v.browser?new vt:null),v.filter=!!e0,!e0||!e0.add?(t.debug&&p("input process error: cannot initialize filters"),v.webgl.supported=!1,t.filter.enabled=!1,W2(q,i0)):(e0.reset(),t.filter.brightness!==0&&e0.add("brightness",t.filter.brightness),t.filter.contrast!==0&&e0.add("contrast",t.filter.contrast),t.filter.sharpness!==0&&e0.add("sharpen",t.filter.sharpness),t.filter.blur!==0&&e0.add("blur",t.filter.blur),t.filter.saturation!==0&&e0.add("saturation",t.filter.saturation),t.filter.hue!==0&&e0.add("hue",t.filter.hue),t.filter.negative&&e0.add("negative"),t.filter.sepia&&e0.add("sepia"),t.filter.vintage&&e0.add("brownie"),t.filter.sepia&&e0.add("sepia"),t.filter.kodachrome&&e0.add("kodachrome"),t.filter.technicolor&&e0.add("technicolor"),t.filter.polaroid&&e0.add("polaroid"),t.filter.pixelate!==0&&e0.add("pixelate",t.filter.pixelate),e0.get()>0?i0=e0.apply(q):i0=e0.draw(q))):(W2(q,i0),e0&&(e0=null),v.filter=!!e0),!o)return{tensor:null,canvas:i0};if(!i0)throw new Error("canvas error: cannot create output");let i,x=3;if(typeof ImageData!="undefined"&&e instanceof ImageData||e.data&&e.width&&e.height)if(v.browser&&N.browser)i=N.browser?N.browser.fromPixels(e):null;else{x=e.data.length/e.height/e.width;let y=new Uint8Array(e.data.buffer);i=N.tensor(y,[e.height,e.width,x],"int32")}else if((!Ue||i0.width!==Ue.width||i0.height!==Ue.height)&&(Ue=R0(i0.width,i0.height)),N.browser&&v.browser)t.backend==="webgl"||t.backend==="humangl"||t.backend==="webgpu"?i=N.browser.fromPixels(i0):(Ue=W2(i0),i=N.browser.fromPixels(Ue));else{let u=W2(i0).getContext("2d").getImageData(0,0,A,s);x=u.data.length/A/s;let m=new Uint8Array(u.data.buffer);i=N.tensor(m,[A,s,x])}if(x===4){let y=N.slice3d(i,[0,0,0],[-1,-1,3]);N.dispose(i),i=y}if(!i)throw new Error("input error: cannot create tensor");let c=N.cast(i,"float32"),l=t.filter.equalization?await O2(c):N.expandDims(c,0);return N.dispose([i,c]),{tensor:l,canvas:t.filter.return?i0:null}}}async function Tt(e,t){let o=!1;if(e.cacheSensitivity===0||!t.shape||t.shape.length!==4||t.shape[1]>2048||t.shape[2]>2048)return o;if(!ae.inputTensor)ae.inputTensor=N.clone(t);else if(ae.inputTensor.shape[1]!==t.shape[1]||ae.inputTensor.shape[2]!==t.shape[2])N.dispose(ae.inputTensor),ae.inputTensor=N.clone(t);else{let n={};n.diff=N.sub(t,ae.inputTensor),n.squared=N.mul(n.diff,n.diff),n.sum=N.sum(n.squared);let A=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;N.dispose([ae.inputTensor,n.diff,n.squared,n.sum]),ae.inputTensor=N.clone(t),o=A<=(e.cacheSensitivity||0)}return o}async function wt(e,t,o){let n={};if(!t||!o||t.shape.length!==4||t.shape.length!==o.shape.length)return e.debug||p("invalid input tensor or tensor shapes do not match:",t.shape,o.shape),0;if(t.shape[0]!==1||o.shape[0]!==1||t.shape[3]!==3||o.shape[3]!==3)return e.debug||p("input tensors must be of shape [1, height, width, 3]:",t.shape,o.shape),0;n.input1=N.clone(t),n.input2=t.shape[1]!==o.shape[1]||t.shape[2]!==o.shape[2]?N.image.resizeBilinear(o,[t.shape[1],t.shape[2]]):N.clone(o),n.diff=N.sub(n.input1,n.input2),n.squared=N.mul(n.diff,n.diff),n.sum=N.sum(n.squared);let A=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;return N.dispose([n.input1,n.input2,n.diff,n.squared,n.sum]),A}var I5=class{constructor(){T(this,"browser");T(this,"node");T(this,"worker");T(this,"platform","");T(this,"agent","");T(this,"backends",[]);T(this,"initial");T(this,"filter");T(this,"tfjs");T(this,"offscreen");T(this,"perfadd",!1);T(this,"wasm",{supported:void 0,backend:void 0,simd:void 0,multithread:void 0});T(this,"webgl",{supported:void 0,backend:void 0,version:void 0,renderer:void 0});T(this,"webgpu",{supported:void 0,backend:void 0,adapter:void 0});T(this,"cpu",{model:void 0,flags:[]});T(this,"kernels",[]);T(this,"Canvas");T(this,"Image");T(this,"ImageData");if(this.browser=typeof navigator!="undefined",this.node=typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined",this.tfjs={version:p0.version["tfjs-core"]},this.offscreen=typeof OffscreenCanvas!="undefined",this.initial=!0,this.worker=this.browser&&this.offscreen?typeof WorkerGlobalScope!="undefined":void 0,typeof navigator!="undefined"){let t=navigator.userAgent.match(/\(([^()]+)\)/g);if(t&&t[0]){let o=t[0].match(/\(([^()]+)\)/g);this.platform=o&&o[0]?o[0].replace(/\(|\)/g,""):"",this.agent=navigator.userAgent.replace(t[0],""),this.platform[1]&&(this.agent=this.agent.replace(t[1],"")),this.agent=this.agent.replace(/  /g," ")}}else typeof process!="undefined"&&(this.platform=`${process.platform} ${process.arch}`,this.agent=`NodeJS ${process.version}`)}async updateBackend(){this.backends=Object.keys(p0.engine().registryFactory),this.wasm.supported=typeof WebAssembly!="undefined",this.wasm.backend=this.backends.includes("wasm"),this.wasm.supported&&this.wasm.backend&&p0.getBackend()==="wasm"&&(this.wasm.simd=await p0.env().getAsync("WASM_HAS_SIMD_SUPPORT"),this.wasm.multithread=await p0.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT"));let t=R0(100,100),o=t?t.getContext("webgl2"):void 0;if(this.webgl.supported=typeof o!="undefined",this.webgl.backend=this.backends.includes("webgl"),this.webgl.supported&&this.webgl.backend&&(p0.getBackend()==="webgl"||p0.getBackend()==="humangl")){let n=p0.backend().gpgpu!=="undefined"?await p0.backend().getGPGPUContext().gl:null;n&&(this.webgl.version=n.getParameter(n.VERSION),this.webgl.renderer=n.getParameter(n.RENDERER))}this.webgpu.supported=this.browser&&typeof navigator.gpu!="undefined",this.webgpu.backend=this.backends.includes("webgpu");try{this.webgpu.supported&&(this.webgpu.adapter=(await navigator.gpu.requestAdapter()).name)}catch(n){this.webgpu.supported=!1}try{this.kernels=p0.getKernelsForBackend(p0.getBackend()).map(n=>n.kernelName.toLowerCase())}catch(n){}}async updateCPU(){let t={model:"",flags:[]};this.node&&this.platform.startsWith("linux"),this.cpu?this.cpu=t:Object.defineProperty(this,"cpu",{value:t})}},v=new I5;var F2=Z(D());var N5={};ue(N5,{age:()=>Pn,antispoof:()=>Rn,blazeface:()=>wn,"blazeface-back":()=>vn,"blazeface-front":()=>Tn,"blazepose-detector2d":()=>kn,"blazepose-detector3d":()=>En,"blazepose-full":()=>zn,"blazepose-heavy":()=>Sn,"blazepose-lite":()=>Cn,default:()=>yr,efficientpose:()=>jn,emotion:()=>In,faceboxes:()=>Nn,facemesh:()=>Bn,"facemesh-attention":()=>Ln,"facemesh-attention-alt":()=>On,"facemesh-detection-full":()=>Wn,"facemesh-detection-short":()=>Fn,"facemesh-orig":()=>Gn,faceres:()=>Vn,"faceres-deep":()=>Hn,gear:()=>Dn,gender:()=>Xn,"gender-ssrnet-imdb":()=>Zn,handdetect:()=>qn,"handlandmark-full":()=>Un,"handlandmark-lite":()=>Yn,"handlandmark-sparse":()=>Kn,handskeleton:()=>Jn,handtrack:()=>Qn,iris:()=>_n,liveness:()=>$n,"mb3-centernet":()=>er,meet:()=>tr,mobileface:()=>or,mobilefacenet:()=>nr,"movenet-lightning":()=>rr,"movenet-multipose":()=>Ar,"movenet-thunder":()=>sr,nanodet:()=>ar,posenet:()=>ir,selfie:()=>lr});var Pn=161240,Rn=853098,vn=538928,Tn=402048,wn=538928,kn=7499400,En=5928856,zn=6338290,Sn=27501554,Cn=2725490,jn=5651240,In=820516,Nn=2013002,On=2387598,Ln=2382414,Wn=1026192,Fn=201268,Gn=2955780,Bn=1477958,Hn=13957620,Vn=6978814,Dn=1498916,Zn=161236,Xn=201808,qn=3515612,Un=5431368,Yn=2023432,Kn=5286322,Jn=5502280,Qn=2964837,_n=2599092,$n=592976,er=4030290,tr=372228,or=2183192,nr=5171976,rr=4650216,Ar=9448838,sr=12477112,ar=7574558,ir=5032780,lr=212886,yr={age:Pn,antispoof:Rn,"blazeface-back":vn,"blazeface-front":Tn,blazeface:wn,"blazepose-detector2d":kn,"blazepose-detector3d":En,"blazepose-full":zn,"blazepose-heavy":Sn,"blazepose-lite":Cn,efficientpose:jn,emotion:In,faceboxes:Nn,"facemesh-attention-alt":On,"facemesh-attention":Ln,"facemesh-detection-full":Wn,"facemesh-detection-short":Fn,"facemesh-orig":Gn,facemesh:Bn,"faceres-deep":Hn,faceres:Vn,gear:Dn,"gender-ssrnet-imdb":Zn,gender:Xn,handdetect:qn,"handlandmark-full":Un,"handlandmark-lite":Yn,"handlandmark-sparse":Kn,handskeleton:Jn,handtrack:Qn,iris:_n,liveness:$n,"mb3-centernet":er,meet:tr,mobileface:or,mobilefacenet:nr,"movenet-lightning":rr,"movenet-multipose":Ar,"movenet-thunder":sr,nanodet:ar,posenet:ir,selfie:lr};var v0={cacheModels:!0,cacheSupported:!0,verbose:!0,debug:!1,modelBasePath:""},q0={};async function xr(e,t){return v0.debug&&p("load model fetch:",e,t),fetch(e,t)}function kt(e){v0.cacheModels=e.cacheModels,v0.verbose=e.debug,v0.modelBasePath=e.modelBasePath}async function G(e){var x,c,l;let t=mt(v0.modelBasePath,e||"");t.toLowerCase().endsWith(".json")||(t+=".json");let o=t.includes("/")?t.split("/"):t.split("\\"),n=o[o.length-1].replace(".json",""),r="indexeddb://"+n;q0[n]={name:n,sizeFromManifest:0,sizeLoadedWeights:0,sizeDesired:N5[n],inCache:!1},v0.cacheSupported=typeof window!="undefined"&&typeof window.localStorage!="undefined"&&typeof window.indexedDB!="undefined";let A={};try{A=v0.cacheSupported&&v0.cacheModels?await F2.io.listModels():{}}catch(y){v0.cacheSupported=!1}q0[n].inCache=v0.cacheSupported&&v0.cacheModels&&Object.keys(A).includes(r);let s=typeof fetch=="undefined"?{}:{fetchFunc:(y,f)=>xr(y,f)},a=new F2.GraphModel(q0[n].inCache?r:t,s),i=!1;try{a.findIOHandler(),v0.debug&&p("model load handler:",a.handler);let y=await a.handler.load();q0[n].sizeFromManifest=((x=y==null?void 0:y.weightData)==null?void 0:x.byteLength)||0,a.loadSync(y),q0[n].sizeLoadedWeights=((l=(c=a==null?void 0:a.artifacts)==null?void 0:c.weightData)==null?void 0:l.byteLength)||0,v0.verbose&&p("load model:",a.modelUrl,{bytes:q0[n].sizeLoadedWeights},v0),i=!0}catch(y){p("error loading model:",t,y)}if(i&&v0.cacheModels&&v0.cacheSupported&&!q0[n].inCache)try{let y=await a.save(r);p("model saved:",r,y)}catch(y){p("error saving model:",t,y)}return a}var ee=Z(D());var O5="2.9.1";var y0=Z(D());var R5={};ue(R5,{Models:()=>C2,getModelStats:()=>q1,load:()=>U1,reset:()=>P5,validate:()=>Y1});var G2=Z(D());var D0,L5=[],fr=["white","black","asian","indian","other"],mr=[15,23,28,35.5,45.5,55.5,65],Et=0,zt=0,W5=Number.MAX_SAFE_INTEGER;async function St(e){var t;return v.initial&&(D0=null),D0?e.debug&&p("cached model:",D0.modelUrl):D0=await G((t=e.face.gear)==null?void 0:t.modelPath),D0}async function F5(e,t,o,n){var s,a;if(!D0)return{age:0,gender:"unknown",genderScore:0,race:[]};let r=W5<(((s=t.face.gear)==null?void 0:s.skipFrames)||0),A=(((a=t.face.gear)==null?void 0:a.skipTime)||0)>h()-zt;return t.skipAllowed&&A&&r&&Et===n&&L5[o]?(W5++,L5[o]):(W5=0,new Promise(async i=>{var g,b;if(!(D0!=null&&D0.inputs[0].shape))return;let x={},c=[[0,.1,.9,.9]];x.resize=G2.image.cropAndResize(e,c,[0],[D0.inputs[0].shape[2],D0.inputs[0].shape[1]]);let l={age:0,gender:"unknown",genderScore:0,race:[]};(g=t.face.gear)!=null&&g.enabled&&([x.age,x.gender,x.race]=D0.execute(x.resize,["age_output","gender_output","race_output"]));let y=await x.gender.data();l.gender=y[0]>y[1]?"male":"female",l.genderScore=Math.round(100*(y[0]>y[1]?y[0]:y[1]))/100;let f=await x.race.data();for(let d=0;d<f.length;d++)f[d]>(((b=t.face.gear)==null?void 0:b.minConfidence)||.2)&&l.race.push({score:Math.round(100*f[d])/100,race:fr[d]});l.race.sort((d,M)=>M.score-d.score);let m=Array.from(await x.age.data()).map((d,M)=>[mr[M],d]).sort((d,M)=>M[1]-d[1]),P=m[0][0];for(let d=1;d<m.length;d++)P+=m[d][1]*(m[d][0]-P);l.age=Math.round(10*P)/10,Object.keys(x).forEach(d=>G2.dispose(x[d])),L5[o]=l,Et=n,zt=h(),i(l)}))}var Ke=Z(D());var be=Z(D()),V={tf255:255,tf1:1,tf2:2,tf05:.5,tf127:127.5,rgb:[.2989,.587,.114]};function jt(){V.tf255=be.scalar(255,"float32"),V.tf1=be.scalar(1,"float32"),V.tf2=be.scalar(2,"float32"),V.tf05=be.scalar(.5,"float32"),V.tf127=be.scalar(127.5,"float32"),V.rgb=be.tensor1d([.2989,.587,.114],"float32")}var S0,B2=[],It=0,Nt=0,G5=Number.MAX_SAFE_INTEGER;async function Ot(e){return v.initial&&(S0=null),S0?e.debug&&p("cached model:",S0.modelUrl):S0=await G(e.face.ssrnet.modelPathAge),S0}async function B5(e,t,o,n){var s,a,i,x;if(!S0)return{age:0};let r=G5<(((s=t.face.ssrnet)==null?void 0:s.skipFrames)||0),A=(((a=t.face.ssrnet)==null?void 0:a.skipTime)||0)>h()-Nt;return t.skipAllowed&&r&&A&&It===n&&((i=B2[o])==null?void 0:i.age)&&((x=B2[o])==null?void 0:x.age)>0?(G5++,B2[o]):(G5=0,new Promise(async c=>{if(!(S0!=null&&S0.inputs)||!S0.inputs[0]||!S0.inputs[0].shape)return;let l={};l.resize=Ke.image.resizeBilinear(e,[S0.inputs[0].shape[2],S0.inputs[0].shape[1]],!1),l.enhance=Ke.mul(l.resize,V.tf255);let y={age:0};if(t.face.ssrnet.enabled&&(l.age=S0.execute(l.enhance)),l.age){let f=await l.age.data();y.age=Math.trunc(10*f[0])/10}Object.keys(l).forEach(f=>Ke.dispose(l[f])),B2[o]=y,It=n,Nt=h(),c(y)}))}var u0=Z(D());var Z0,H2=[],Wt=0,Ft=0,H5=Number.MAX_SAFE_INTEGER,V5=[.2989,.587,.114];async function Gt(e){return v.initial&&(Z0=null),Z0?e.debug&&p("cached model:",Z0.modelUrl):Z0=await G(e.face.ssrnet.modelPathGender),Z0}async function D5(e,t,o,n){var s,a,i,x;if(!Z0)return{gender:"unknown",genderScore:0};let r=H5<(((s=t.face.ssrnet)==null?void 0:s.skipFrames)||0),A=(((a=t.face.ssrnet)==null?void 0:a.skipTime)||0)>h()-Ft;return t.skipAllowed&&r&&A&&Wt===n&&((i=H2[o])==null?void 0:i.gender)&&((x=H2[o])==null?void 0:x.genderScore)>0?(H5++,H2[o]):(H5=0,new Promise(async c=>{if(!(Z0!=null&&Z0.inputs[0].shape))return;let l={};l.resize=u0.image.resizeBilinear(e,[Z0.inputs[0].shape[2],Z0.inputs[0].shape[1]],!1),l.enhance=u0.tidy(()=>{let[u,m,P]=u0.split(l.resize,3,3),g=u0.mul(u,V5[0]),b=u0.mul(m,V5[1]),d=u0.mul(P,V5[2]),M=u0.addN([g,b,d]);return u0.mul(u0.sub(M,V.tf05),2)});let y={gender:"unknown",genderScore:0};t.face.ssrnet.enabled&&(l.gender=Z0.execute(l.enhance));let f=await l.gender.data();y.gender=f[0]>f[1]?"female":"male",y.genderScore=f[0]>f[1]?Math.trunc(100*f[0])/100:Math.trunc(100*f[1])/100,Object.keys(l).forEach(u=>u0.dispose(l[u])),H2[o]=y,Wt=n,Ft=h(),c(y)}))}var D2=Z(D());var h0,V2=[],Z5=Number.MAX_SAFE_INTEGER,Ht=0,Vt=0;async function Dt(e){var t;return v.initial&&(h0=null),h0?e.debug&&p("cached model:",h0.modelUrl):h0=await G((t=e.face.antispoof)==null?void 0:t.modelPath),h0}async function X5(e,t,o,n){var s,a;if(!h0)return 0;let r=(((s=t.face.antispoof)==null?void 0:s.skipTime)||0)>h()-Vt,A=Z5<(((a=t.face.antispoof)==null?void 0:a.skipFrames)||0);return t.skipAllowed&&r&&A&&Ht===n&&V2[o]?(Z5++,V2[o]):(Z5=0,new Promise(async i=>{let x=D2.image.resizeBilinear(e,[h0!=null&&h0.inputs[0].shape?h0.inputs[0].shape[2]:0,h0!=null&&h0.inputs[0].shape?h0.inputs[0].shape[1]:0],!1),c=h0==null?void 0:h0.execute(x),l=(await c.data())[0];V2[o]=Math.round(100*l)/100,Ht=n,Vt=h(),D2.dispose([x,c]),i(V2[o])}))}var O=Z(D());var ie=Z(D());var X0={silhouette:[10,338,297,332,284,251,389,356,454,323,361,288,397,365,379,378,400,377,152,148,176,149,150,136,172,58,132,93,234,127,162,21,54,103,67,109],lipsUpperOuter:[185,40,39,37,0,267,269,270,409],lipsLowerOuter:[61,146,91,181,84,17,314,405,321,375,291],lipsUpperInner:[191,80,81,82,13,312,311,310,415],lipsLowerInner:[78,95,88,178,87,14,317,402,318,324,308],lipsLowerSemiOuter:[76,77,90,180,85,16,315,404,320,307,306],lipsUpperSemiOuter:[184,74,73,72,11,302,303,304,408],lipsLowerSemiInner:[62,96,89,179,86,15,316,403,319,325,292],lipsUpperSemiInner:[183,42,41,38,12,268,271,272,407],rightEyeUpper0:[246,161,160,159,158,157,173],rightEyeLower0:[33,7,163,144,145,153,154,155,133],rightEyeUpper1:[247,30,29,27,28,56,190],rightEyeLower1:[130,25,110,24,23,22,26,112,243],rightEyeUpper2:[113,225,224,223,222,221,189],rightEyeLower2:[226,31,228,229,230,231,232,233,244],rightEyeLower3:[143,111,117,118,119,120,121,128,245],rightEyebrowUpper:[156,70,63,105,66,107,55,193],rightEyebrowLower:[35,124,46,53,52,65],rightEyeIris:[473,474,475,476,477],leftEyeUpper0:[466,388,387,386,385,384,398],leftEyeLower0:[263,249,390,373,374,380,381,382,362],leftEyeUpper1:[467,260,259,257,258,286,414],leftEyeLower1:[359,255,339,254,253,252,256,341,463],leftEyeUpper2:[342,445,444,443,442,441,413],leftEyeLower2:[446,261,448,449,450,451,452,453,464],leftEyeLower3:[372,340,346,347,348,349,350,357,465],leftEyebrowUpper:[383,300,293,334,296,336,285,417],leftEyebrowLower:[265,353,276,283,282,295],leftEyeIris:[468,469,470,471,472],midwayBetweenEyes:[168],noseTip:[1],noseBottom:[2],noseRightCorner:[98],noseLeftCorner:[327],rightCheek:[205],leftCheek:[425]},q5={count:468,mouth:13,symmetryLine:[13,X0.midwayBetweenEyes[0]]},Ie={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},U5=[{key:"EyeUpper0",indices:[9,10,11,12,13,14,15]},{key:"EyeUpper1",indices:[25,26,27,28,29,30,31]},{key:"EyeUpper2",indices:[41,42,43,44,45,46,47]},{key:"EyeLower0",indices:[0,1,2,3,4,5,6,7,8]},{key:"EyeLower1",indices:[16,17,18,19,20,21,22,23,24]},{key:"EyeLower2",indices:[32,33,34,35,36,37,38,39,40]},{key:"EyeLower3",indices:[54,55,56,57,58,59,60,61,62]},{key:"EyebrowUpper",indices:[63,64,65,66,67,68,69,70]},{key:"EyebrowLower",indices:[48,49,50,51,52,53]}],R2=[[.499976992607117,.652534008026123],[.500025987625122,.547487020492554],[.499974012374878,.602371990680695],[.482113003730774,.471979022026062],[.500150978565216,.527155995368958],[.499909996986389,.498252987861633],[.499523013830185,.40106201171875],[.289712011814117,.380764007568359],[.499954998493195,.312398016452789],[.499987006187439,.269918978214264],[.500023007392883,.107050001621246],[.500023007392883,.666234016418457],[.5000159740448,.679224014282227],[.500023007392883,.692348003387451],[.499976992607117,.695277988910675],[.499976992607117,.70593398809433],[.499976992607117,.719385027885437],[.499976992607117,.737019002437592],[.499967992305756,.781370997428894],[.499816000461578,.562981009483337],[.473773002624512,.573909997940063],[.104906998574734,.254140973091125],[.365929991006851,.409575998783112],[.338757991790771,.41302502155304],[.311120003461838,.409460008144379],[.274657994508743,.389131009578705],[.393361985683441,.403706014156342],[.345234006643295,.344011008739471],[.370094001293182,.346076011657715],[.319321990013123,.347265005111694],[.297903001308441,.353591024875641],[.24779200553894,.410809993743896],[.396889001131058,.842755019664764],[.280097991228104,.375599980354309],[.106310002505779,.399955987930298],[.2099249958992,.391353011131287],[.355807989835739,.534406006336212],[.471751004457474,.65040397644043],[.474155008792877,.680191993713379],[.439785003662109,.657229006290436],[.414617002010345,.66654098033905],[.450374007225037,.680860996246338],[.428770989179611,.682690978050232],[.374971002340317,.727805018424988],[.486716985702515,.547628998756409],[.485300987958908,.527395009994507],[.257764995098114,.314490020275116],[.401223003864288,.455172002315521],[.429818987846375,.548614978790283],[.421351999044418,.533740997314453],[.276895999908447,.532056987285614],[.483370006084442,.499586999416351],[.33721199631691,.282882988452911],[.296391993761063,.293242990970612],[.169294998049736,.193813979625702],[.447580009698868,.302609980106354],[.392390012741089,.353887975215912],[.354490011930466,.696784019470215],[.067304998636246,.730105042457581],[.442739009857178,.572826027870178],[.457098007202148,.584792017936707],[.381974011659622,.694710969924927],[.392388999462128,.694203019142151],[.277076005935669,.271932005882263],[.422551989555359,.563233017921448],[.385919004678726,.281364023685455],[.383103013038635,.255840003490448],[.331431001424789,.119714021682739],[.229923993349075,.232002973556519],[.364500999450684,.189113974571228],[.229622006416321,.299540996551514],[.173287004232407,.278747975826263],[.472878992557526,.666198015213013],[.446828007698059,.668527007102966],[.422762006521225,.673889994621277],[.445307999849319,.580065965652466],[.388103008270264,.693961024284363],[.403039008378983,.706539988517761],[.403629004955292,.693953037261963],[.460041999816895,.557139039039612],[.431158006191254,.692366003990173],[.452181994915009,.692366003990173],[.475387006998062,.692366003990173],[.465828001499176,.779190003871918],[.472328990697861,.736225962638855],[.473087012767792,.717857003211975],[.473122000694275,.704625964164734],[.473033010959625,.695277988910675],[.427942007780075,.695277988910675],[.426479011774063,.703539967536926],[.423162013292313,.711845993995667],[.4183090031147,.720062971115112],[.390094995498657,.639572978019714],[.013953999616206,.560034036636353],[.499913990497589,.58014702796936],[.413199990987778,.69539999961853],[.409626007080078,.701822996139526],[.468080013990402,.601534962654114],[.422728985548019,.585985004901886],[.463079988956451,.593783974647522],[.37211999297142,.47341400384903],[.334562003612518,.496073007583618],[.411671012639999,.546965003013611],[.242175996303558,.14767599105835],[.290776997804642,.201445996761322],[.327338010072708,.256527006626129],[.399509996175766,.748921036720276],[.441727995872498,.261676013469696],[.429764986038208,.187834024429321],[.412198007106781,.108901023864746],[.288955003023148,.398952007293701],[.218936994671822,.435410976409912],[.41278201341629,.398970007896423],[.257135003805161,.355440020561218],[.427684992551804,.437960982322693],[.448339998722076,.536936044692993],[.178560003638268,.45755398273468],[.247308000922203,.457193970680237],[.286267012357712,.467674970626831],[.332827985286713,.460712015628815],[.368755996227264,.447206974029541],[.398963987827301,.432654976844788],[.476410001516342,.405806005001068],[.189241006970406,.523923993110657],[.228962004184723,.348950982093811],[.490725994110107,.562400996685028],[.404670000076294,.485132992267609],[.019469000399113,.401564002037048],[.426243007183075,.420431017875671],[.396993011236191,.548797011375427],[.266469985246658,.376977026462555],[.439121007919312,.51895797252655],[.032313998788595,.644356966018677],[.419054001569748,.387154996395111],[.462783008813858,.505746960639954],[.238978996872902,.779744982719421],[.198220998048782,.831938028335571],[.107550002634525,.540755033493042],[.183610007166862,.740257024765015],[.134409993886948,.333683013916016],[.385764002799988,.883153975009918],[.490967005491257,.579378008842468],[.382384985685349,.508572995662689],[.174399003386497,.397670984268188],[.318785011768341,.39623498916626],[.343364000320435,.400596976280212],[.396100014448166,.710216999053955],[.187885001301765,.588537991046906],[.430987000465393,.944064974784851],[.318993002176285,.898285031318665],[.266247987747192,.869701027870178],[.500023007392883,.190576016902924],[.499976992607117,.954452991485596],[.366169989109039,.398822009563446],[.393207013607025,.39553701877594],[.410373002290726,.391080021858215],[.194993004202843,.342101991176605],[.388664990663528,.362284004688263],[.365961998701096,.355970978736877],[.343364000320435,.355356991291046],[.318785011768341,.35834002494812],[.301414996385574,.363156020641327],[.058132998645306,.319076001644135],[.301414996385574,.387449026107788],[.499987989664078,.618434011936188],[.415838003158569,.624195992946625],[.445681989192963,.566076993942261],[.465844005346298,.620640993118286],[.49992299079895,.351523995399475],[.288718998432159,.819945991039276],[.335278987884521,.852819979190826],[.440512001514435,.902418971061707],[.128294005990028,.791940987110138],[.408771991729736,.373893976211548],[.455606997013092,.451801002025604],[.499877005815506,.908990025520325],[.375436991453171,.924192011356354],[.11421000212431,.615022003650665],[.448662012815475,.695277988910675],[.4480200111866,.704632043838501],[.447111994028091,.715808033943176],[.444831997156143,.730794012546539],[.430011987686157,.766808986663818],[.406787008047104,.685672998428345],[.400738000869751,.681069016456604],[.392399996519089,.677703022956848],[.367855995893478,.663918972015381],[.247923001646996,.601333022117615],[.452769994735718,.420849978923798],[.43639200925827,.359887003898621],[.416164010763168,.368713974952698],[.413385987281799,.692366003990173],[.228018000721931,.683571994304657],[.468268007040024,.352671027183533],[.411361992359161,.804327011108398],[.499989002943039,.469825029373169],[.479153990745544,.442654013633728],[.499974012374878,.439637005329132],[.432112008333206,.493588984012604],[.499886006116867,.866917014122009],[.49991300702095,.821729004383087],[.456548988819122,.819200992584229],[.344549000263214,.745438992977142],[.37890899181366,.574010014533997],[.374292999505997,.780184984207153],[.319687992334366,.570737957954407],[.357154995203018,.604269981384277],[.295284003019333,.621580958366394],[.447750002145767,.862477004528046],[.410986006259918,.508723020553589],[.31395098567009,.775308012962341],[.354128003120422,.812552988529205],[.324548006057739,.703992962837219],[.189096003770828,.646299958229065],[.279776990413666,.71465802192688],[.1338230073452,.682700991630554],[.336768001317978,.644733011722565],[.429883986711502,.466521978378296],[.455527991056442,.548622965812683],[.437114000320435,.558896005153656],[.467287987470627,.529924988746643],[.414712011814117,.335219979286194],[.37704598903656,.322777986526489],[.344107985496521,.320150971412659],[.312875986099243,.32233202457428],[.283526003360748,.333190023899078],[.241245999932289,.382785975933075],[.102986000478268,.468762993812561],[.267612010240555,.424560010433197],[.297879010438919,.433175981044769],[.333433985710144,.433878004550934],[.366427004337311,.426115989685059],[.396012008190155,.416696012020111],[.420121014118195,.41022801399231],[.007561000064015,.480777025222778],[.432949006557465,.569517970085144],[.458638995885849,.479089021682739],[.473466008901596,.545744001865387],[.476087987422943,.563830018043518],[.468472003936768,.555056989192963],[.433990985155106,.582361996173859],[.483518004417419,.562983989715576],[.482482999563217,.57784903049469],[.42645001411438,.389798998832703],[.438998997211456,.39649498462677],[.450067013502121,.400434017181396],[.289712011814117,.368252992630005],[.276670008897781,.363372981548309],[.517862021923065,.471948027610779],[.710287988185883,.380764007568359],[.526226997375488,.573909997940063],[.895093023777008,.254140973091125],[.634069979190826,.409575998783112],[.661242008209229,.41302502155304],[.688880026340485,.409460008144379],[.725341975688934,.389131009578705],[.606630027294159,.40370500087738],[.654766023159027,.344011008739471],[.629905998706818,.346076011657715],[.680678009986877,.347265005111694],[.702096998691559,.353591024875641],[.75221198797226,.410804986953735],[.602918028831482,.842862963676453],[.719901978969574,.375599980354309],[.893692970275879,.399959981441498],[.790081977844238,.391354024410248],[.643998026847839,.534487962722778],[.528249025344849,.65040397644043],[.525849997997284,.680191040039062],[.560214996337891,.657229006290436],[.585384011268616,.66654098033905],[.549625992774963,.680860996246338],[.57122802734375,.682691991329193],[.624852001667023,.72809898853302],[.513050019741058,.547281980514526],[.51509702205658,.527251958847046],[.742246985435486,.314507007598877],[.598631024360657,.454979002475739],[.570338010787964,.548575043678284],[.578631997108459,.533622980117798],[.723087012767792,.532054007053375],[.516445994377136,.499638974666595],[.662801027297974,.282917976379395],[.70362401008606,.293271005153656],[.830704987049103,.193813979625702],[.552385985851288,.302568018436432],[.607609987258911,.353887975215912],[.645429015159607,.696707010269165],[.932694971561432,.730105042457581],[.557260990142822,.572826027870178],[.542901992797852,.584792017936707],[.6180260181427,.694710969924927],[.607590973377228,.694203019142151],[.722943007946014,.271963000297546],[.577413976192474,.563166975975037],[.614082992076874,.281386971473694],[.616907000541687,.255886018276215],[.668509006500244,.119913995265961],[.770092010498047,.232020974159241],[.635536015033722,.189248979091644],[.77039098739624,.299556016921997],[.826722025871277,.278755009174347],[.527121007442474,.666198015213013],[.553171992301941,.668527007102966],[.577238023281097,.673889994621277],[.554691970348358,.580065965652466],[.611896991729736,.693961024284363],[.59696102142334,.706539988517761],[.596370995044708,.693953037261963],[.539958000183105,.557139039039612],[.568841993808746,.692366003990173],[.547818005084991,.692366003990173],[.52461302280426,.692366003990173],[.534089982509613,.779141008853912],[.527670979499817,.736225962638855],[.526912987232208,.717857003211975],[.526877999305725,.704625964164734],[.526966989040375,.695277988910675],[.572058022022247,.695277988910675],[.573521018028259,.703539967536926],[.57683801651001,.711845993995667],[.581691026687622,.720062971115112],[.609944999217987,.639909982681274],[.986046016216278,.560034036636353],[.5867999792099,.69539999961853],[.590372025966644,.701822996139526],[.531915009021759,.601536989212036],[.577268004417419,.585934996604919],[.536915004253387,.593786001205444],[.627542972564697,.473352015018463],[.665585994720459,.495950996875763],[.588353991508484,.546862006187439],[.757824003696442,.14767599105835],[.709249973297119,.201507985591888],[.672684013843536,.256581008434296],[.600408971309662,.74900496006012],[.55826598405838,.261672019958496],[.570303976535797,.187870979309082],[.588165998458862,.109044015407562],[.711045026779175,.398952007293701],[.781069993972778,.435405015945435],[.587247014045715,.398931980133057],[.742869973182678,.355445981025696],[.572156012058258,.437651991844177],[.55186802148819,.536570012569427],[.821442008018494,.457556009292603],[.752701997756958,.457181990146637],[.71375697851181,.467626988887787],[.66711300611496,.460672974586487],[.631101012229919,.447153985500336],[.6008620262146,.432473003864288],[.523481011390686,.405627012252808],[.810747981071472,.523926019668579],[.771045982837677,.348959028720856],[.509127020835876,.562718033790588],[.595292985439301,.485023975372314],[.980530977249146,.401564002037048],[.573499977588654,.420000016689301],[.602994978427887,.548687994480133],[.733529984951019,.376977026462555],[.560611009597778,.519016981124878],[.967685997486115,.644356966018677],[.580985009670258,.387160003185272],[.537728011608124,.505385041236877],[.760966002941132,.779752969741821],[.801778972148895,.831938028335571],[.892440974712372,.54076099395752],[.816350996494293,.740260004997253],[.865594983100891,.333687007427216],[.614073991775513,.883246004581451],[.508952975273132,.579437971115112],[.617941975593567,.508316040039062],[.825608015060425,.397674977779388],[.681214988231659,.39623498916626],[.656635999679565,.400596976280212],[.603900015354156,.710216999053955],[.81208598613739,.588539004325867],[.56801301240921,.944564998149872],[.681007981300354,.898285031318665],[.733752012252808,.869701027870178],[.633830010890961,.398822009563446],[.606792986392975,.39553701877594],[.589659988880157,.391062021255493],[.805015981197357,.342108011245728],[.611334979534149,.362284004688263],[.634037971496582,.355970978736877],[.656635999679565,.355356991291046],[.681214988231659,.35834002494812],[.698584973812103,.363156020641327],[.941866993904114,.319076001644135],[.698584973812103,.387449026107788],[.584177017211914,.624107003211975],[.554318010807037,.566076993942261],[.534153997898102,.62064003944397],[.711217999458313,.819975018501282],[.664629995822906,.852871000766754],[.559099972248077,.902631998062134],[.871706008911133,.791940987110138],[.591234028339386,.373893976211548],[.544341027736664,.451583981513977],[.624562978744507,.924192011356354],[.88577002286911,.615028977394104],[.551338016986847,.695277988910675],[.551980018615723,.704632043838501],[.552887976169586,.715808033943176],[.555167973041534,.730794012546539],[.569944024085999,.767035007476807],[.593203008174896,.685675978660583],[.599261999130249,.681069016456604],[.607599973678589,.677703022956848],[.631937980651855,.663500010967255],[.752032995223999,.601315021514893],[.547226011753082,.420395016670227],[.563543975353241,.359827995300293],[.583841025829315,.368713974952698],[.586614012718201,.692366003990173],[.771915018558502,.683578014373779],[.531597018241882,.352482974529266],[.588370978832245,.804440975189209],[.52079701423645,.442565023899078],[.567984998226166,.493479013442993],[.543282985687256,.819254994392395],[.655317008495331,.745514988899231],[.621008992195129,.574018001556396],[.625559985637665,.78031200170517],[.680198013782501,.570719003677368],[.64276397228241,.604337990283966],[.704662978649139,.621529996395111],[.552012026309967,.862591981887817],[.589071989059448,.508637011051178],[.685944974422455,.775357007980347],[.645735025405884,.812640011310577],[.675342977046967,.703978002071381],[.810858011245728,.646304965019226],[.72012197971344,.714666962623596],[.866151988506317,.682704985141754],[.663187026977539,.644596993923187],[.570082008838654,.466325998306274],[.544561982154846,.548375964164734],[.562758982181549,.558784961700439],[.531987011432648,.530140042304993],[.585271000862122,.335177004337311],[.622952997684479,.32277899980545],[.655896008014679,.320163011550903],[.687132000923157,.322345972061157],[.716481983661652,.333200991153717],[.758756995201111,.382786989212036],[.897013008594513,.468769013881683],[.732392013072968,.424547016620636],[.70211398601532,.433162987232208],[.66652500629425,.433866024017334],[.633504986763,.426087975502014],[.603875994682312,.416586995124817],[.579657971858978,.409945011138916],[.992439985275269,.480777025222778],[.567192018032074,.569419980049133],[.54136598110199,.478899002075195],[.526564002037048,.546118021011353],[.523913025856018,.563830018043518],[.531529009342194,.555056989192963],[.566035985946655,.582329034805298],[.51631098985672,.563053965568542],[.5174720287323,.577877044677734],[.573594987392426,.389806985855103],[.560697972774506,.395331978797913],[.549755990505219,.399751007556915],[.710287988185883,.368252992630005],[.723330020904541,.363372981548309]],Ne=[127,34,139,11,0,37,232,231,120,72,37,39,128,121,47,232,121,128,104,69,67,175,171,148,157,154,155,118,50,101,73,39,40,9,151,108,48,115,131,194,204,211,74,40,185,80,42,183,40,92,186,230,229,118,202,212,214,83,18,17,76,61,146,160,29,30,56,157,173,106,204,194,135,214,192,203,165,98,21,71,68,51,45,4,144,24,23,77,146,91,205,50,187,201,200,18,91,106,182,90,91,181,85,84,17,206,203,36,148,171,140,92,40,39,193,189,244,159,158,28,247,246,161,236,3,196,54,68,104,193,168,8,117,228,31,189,193,55,98,97,99,126,47,100,166,79,218,155,154,26,209,49,131,135,136,150,47,126,217,223,52,53,45,51,134,211,170,140,67,69,108,43,106,91,230,119,120,226,130,247,63,53,52,238,20,242,46,70,156,78,62,96,46,53,63,143,34,227,173,155,133,123,117,111,44,125,19,236,134,51,216,206,205,154,153,22,39,37,167,200,201,208,36,142,100,57,212,202,20,60,99,28,158,157,35,226,113,160,159,27,204,202,210,113,225,46,43,202,204,62,76,77,137,123,116,41,38,72,203,129,142,64,98,240,49,102,64,41,73,74,212,216,207,42,74,184,169,170,211,170,149,176,105,66,69,122,6,168,123,147,187,96,77,90,65,55,107,89,90,180,101,100,120,63,105,104,93,137,227,15,86,85,129,102,49,14,87,86,55,8,9,100,47,121,145,23,22,88,89,179,6,122,196,88,95,96,138,172,136,215,58,172,115,48,219,42,80,81,195,3,51,43,146,61,171,175,199,81,82,38,53,46,225,144,163,110,246,33,7,52,65,66,229,228,117,34,127,234,107,108,69,109,108,151,48,64,235,62,78,191,129,209,126,111,35,143,163,161,246,117,123,50,222,65,52,19,125,141,221,55,65,3,195,197,25,7,33,220,237,44,70,71,139,122,193,245,247,130,33,71,21,162,153,158,159,170,169,150,188,174,196,216,186,92,144,160,161,2,97,167,141,125,241,164,167,37,72,38,12,145,159,160,38,82,13,63,68,71,226,35,111,158,153,154,101,50,205,206,92,165,209,198,217,165,167,97,220,115,218,133,112,243,239,238,241,214,135,169,190,173,133,171,208,32,125,44,237,86,87,178,85,86,179,84,85,180,83,84,181,201,83,182,137,93,132,76,62,183,61,76,184,57,61,185,212,57,186,214,207,187,34,143,156,79,239,237,123,137,177,44,1,4,201,194,32,64,102,129,213,215,138,59,166,219,242,99,97,2,94,141,75,59,235,24,110,228,25,130,226,23,24,229,22,23,230,26,22,231,112,26,232,189,190,243,221,56,190,28,56,221,27,28,222,29,27,223,30,29,224,247,30,225,238,79,20,166,59,75,60,75,240,147,177,215,20,79,166,187,147,213,112,233,244,233,128,245,128,114,188,114,217,174,131,115,220,217,198,236,198,131,134,177,132,58,143,35,124,110,163,7,228,110,25,356,389,368,11,302,267,452,350,349,302,303,269,357,343,277,452,453,357,333,332,297,175,152,377,384,398,382,347,348,330,303,304,270,9,336,337,278,279,360,418,262,431,304,408,409,310,415,407,270,409,410,450,348,347,422,430,434,313,314,17,306,307,375,387,388,260,286,414,398,335,406,418,364,367,416,423,358,327,251,284,298,281,5,4,373,374,253,307,320,321,425,427,411,421,313,18,321,405,406,320,404,405,315,16,17,426,425,266,377,400,369,322,391,269,417,465,464,386,257,258,466,260,388,456,399,419,284,332,333,417,285,8,346,340,261,413,441,285,327,460,328,355,371,329,392,439,438,382,341,256,429,420,360,364,394,379,277,343,437,443,444,283,275,440,363,431,262,369,297,338,337,273,375,321,450,451,349,446,342,467,293,334,282,458,461,462,276,353,383,308,324,325,276,300,293,372,345,447,382,398,362,352,345,340,274,1,19,456,248,281,436,427,425,381,256,252,269,391,393,200,199,428,266,330,329,287,273,422,250,462,328,258,286,384,265,353,342,387,259,257,424,431,430,342,353,276,273,335,424,292,325,307,366,447,345,271,303,302,423,266,371,294,455,460,279,278,294,271,272,304,432,434,427,272,407,408,394,430,431,395,369,400,334,333,299,351,417,168,352,280,411,325,319,320,295,296,336,319,403,404,330,348,349,293,298,333,323,454,447,15,16,315,358,429,279,14,15,316,285,336,9,329,349,350,374,380,252,318,402,403,6,197,419,318,319,325,367,364,365,435,367,397,344,438,439,272,271,311,195,5,281,273,287,291,396,428,199,311,271,268,283,444,445,373,254,339,263,466,249,282,334,296,449,347,346,264,447,454,336,296,299,338,10,151,278,439,455,292,407,415,358,371,355,340,345,372,390,249,466,346,347,280,442,443,282,19,94,370,441,442,295,248,419,197,263,255,359,440,275,274,300,383,368,351,412,465,263,467,466,301,368,389,380,374,386,395,378,379,412,351,419,436,426,322,373,390,388,2,164,393,370,462,461,164,0,267,302,11,12,374,373,387,268,12,13,293,300,301,446,261,340,385,384,381,330,266,425,426,423,391,429,355,437,391,327,326,440,457,438,341,382,362,459,457,461,434,430,394,414,463,362,396,369,262,354,461,457,316,403,402,315,404,403,314,405,404,313,406,405,421,418,406,366,401,361,306,408,407,291,409,408,287,410,409,432,436,410,434,416,411,264,368,383,309,438,457,352,376,401,274,275,4,421,428,262,294,327,358,433,416,367,289,455,439,462,370,326,2,326,370,305,460,455,254,449,448,255,261,446,253,450,449,252,451,450,256,452,451,341,453,452,413,464,463,441,413,414,258,442,441,257,443,442,259,444,443,260,445,444,467,342,445,459,458,250,289,392,290,290,328,460,376,433,435,250,290,392,411,416,433,341,463,464,453,464,465,357,465,412,343,412,399,360,363,440,437,399,456,420,456,363,401,435,288,372,383,353,339,255,249,448,261,255,133,243,190,133,155,112,33,246,247,33,130,25,398,384,286,362,398,414,362,463,341,263,359,467,263,249,255,466,467,260,75,60,166,238,239,79,162,127,139,72,11,37,121,232,120,73,72,39,114,128,47,233,232,128,103,104,67,152,175,148,173,157,155,119,118,101,74,73,40,107,9,108,49,48,131,32,194,211,184,74,185,191,80,183,185,40,186,119,230,118,210,202,214,84,83,17,77,76,146,161,160,30,190,56,173,182,106,194,138,135,192,129,203,98,54,21,68,5,51,4,145,144,23,90,77,91,207,205,187,83,201,18,181,91,182,180,90,181,16,85,17,205,206,36,176,148,140,165,92,39,245,193,244,27,159,28,30,247,161,174,236,196,103,54,104,55,193,8,111,117,31,221,189,55,240,98,99,142,126,100,219,166,218,112,155,26,198,209,131,169,135,150,114,47,217,224,223,53,220,45,134,32,211,140,109,67,108,146,43,91,231,230,120,113,226,247,105,63,52,241,238,242,124,46,156,95,78,96,70,46,63,116,143,227,116,123,111,1,44,19,3,236,51,207,216,205,26,154,22,165,39,167,199,200,208,101,36,100,43,57,202,242,20,99,56,28,157,124,35,113,29,160,27,211,204,210,124,113,46,106,43,204,96,62,77,227,137,116,73,41,72,36,203,142,235,64,240,48,49,64,42,41,74,214,212,207,183,42,184,210,169,211,140,170,176,104,105,69,193,122,168,50,123,187,89,96,90,66,65,107,179,89,180,119,101,120,68,63,104,234,93,227,16,15,85,209,129,49,15,14,86,107,55,9,120,100,121,153,145,22,178,88,179,197,6,196,89,88,96,135,138,136,138,215,172,218,115,219,41,42,81,5,195,51,57,43,61,208,171,199,41,81,38,224,53,225,24,144,110,105,52,66,118,229,117,227,34,234,66,107,69,10,109,151,219,48,235,183,62,191,142,129,126,116,111,143,7,163,246,118,117,50,223,222,52,94,19,141,222,221,65,196,3,197,45,220,44,156,70,139,188,122,245,139,71,162,145,153,159,149,170,150,122,188,196,206,216,92,163,144,161,164,2,167,242,141,241,0,164,37,11,72,12,144,145,160,12,38,13,70,63,71,31,226,111,157,158,154,36,101,205,203,206,165,126,209,217,98,165,97,237,220,218,237,239,241,210,214,169,140,171,32,241,125,237,179,86,178,180,85,179,181,84,180,182,83,181,194,201,182,177,137,132,184,76,183,185,61,184,186,57,185,216,212,186,192,214,187,139,34,156,218,79,237,147,123,177,45,44,4,208,201,32,98,64,129,192,213,138,235,59,219,141,242,97,97,2,141,240,75,235,229,24,228,31,25,226,230,23,229,231,22,230,232,26,231,233,112,232,244,189,243,189,221,190,222,28,221,223,27,222,224,29,223,225,30,224,113,247,225,99,60,240,213,147,215,60,20,166,192,187,213,243,112,244,244,233,245,245,128,188,188,114,174,134,131,220,174,217,236,236,198,134,215,177,58,156,143,124,25,110,7,31,228,25,264,356,368,0,11,267,451,452,349,267,302,269,350,357,277,350,452,357,299,333,297,396,175,377,381,384,382,280,347,330,269,303,270,151,9,337,344,278,360,424,418,431,270,304,409,272,310,407,322,270,410,449,450,347,432,422,434,18,313,17,291,306,375,259,387,260,424,335,418,434,364,416,391,423,327,301,251,298,275,281,4,254,373,253,375,307,321,280,425,411,200,421,18,335,321,406,321,320,405,314,315,17,423,426,266,396,377,369,270,322,269,413,417,464,385,386,258,248,456,419,298,284,333,168,417,8,448,346,261,417,413,285,326,327,328,277,355,329,309,392,438,381,382,256,279,429,360,365,364,379,355,277,437,282,443,283,281,275,363,395,431,369,299,297,337,335,273,321,348,450,349,359,446,467,283,293,282,250,458,462,300,276,383,292,308,325,283,276,293,264,372,447,346,352,340,354,274,19,363,456,281,426,436,425,380,381,252,267,269,393,421,200,428,371,266,329,432,287,422,290,250,328,385,258,384,446,265,342,386,387,257,422,424,430,445,342,276,422,273,424,306,292,307,352,366,345,268,271,302,358,423,371,327,294,460,331,279,294,303,271,304,436,432,427,304,272,408,395,394,431,378,395,400,296,334,299,6,351,168,376,352,411,307,325,320,285,295,336,320,319,404,329,330,349,334,293,333,366,323,447,316,15,315,331,358,279,317,14,316,8,285,9,277,329,350,253,374,252,319,318,403,351,6,419,324,318,325,397,367,365,288,435,397,278,344,439,310,272,311,248,195,281,375,273,291,175,396,199,312,311,268,276,283,445,390,373,339,295,282,296,448,449,346,356,264,454,337,336,299,337,338,151,294,278,455,308,292,415,429,358,355,265,340,372,388,390,466,352,346,280,295,442,282,354,19,370,285,441,295,195,248,197,457,440,274,301,300,368,417,351,465,251,301,389,385,380,386,394,395,379,399,412,419,410,436,322,387,373,388,326,2,393,354,370,461,393,164,267,268,302,12,386,374,387,312,268,13,298,293,301,265,446,340,380,385,381,280,330,425,322,426,391,420,429,437,393,391,326,344,440,438,458,459,461,364,434,394,428,396,262,274,354,457,317,316,402,316,315,403,315,314,404,314,313,405,313,421,406,323,366,361,292,306,407,306,291,408,291,287,409,287,432,410,427,434,411,372,264,383,459,309,457,366,352,401,1,274,4,418,421,262,331,294,358,435,433,367,392,289,439,328,462,326,94,2,370,289,305,455,339,254,448,359,255,446,254,253,449,253,252,450,252,256,451,256,341,452,414,413,463,286,441,414,286,258,441,258,257,442,257,259,443,259,260,444,260,467,445,309,459,250,305,289,290,305,290,460,401,376,435,309,250,392,376,411,433,453,341,464,357,453,465,343,357,412,437,343,399,344,360,440,420,437,456,360,420,363,361,401,288,265,372,353,390,339,249,339,448,255];var ur=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],hr=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],br=[33,133,362,263,1,78,308],L7=ur.map(e=>R2[e]),W7=hr.map(e=>R2[e]),F7=br.map(e=>R2[e]);function ge(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var gr=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Mr=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Pr=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],Rr=[[474,475],[475,476],[476,477],[477,474]],vr=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],Tr=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],wr=[[469,470],[470,471],[471,472],[472,469]],kr=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]],G7={lips:ge(gr),leftEye:ge(Mr),leftEyebrow:ge(Pr),leftIris:ge(Rr),rightEye:ge(vr),rightEyebrow:ge(Tr),rightIris:ge(wr),faceOval:ge(kr)};var Je=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],Z2=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],X2=(e,t)=>e?[Math.trunc(Math.max(0,e.startPoint[0])),Math.trunc(Math.max(0,e.startPoint[1])),Math.trunc(Math.min(t.shape[2]||0,e.endPoint[0])-Math.max(0,e.startPoint[0])),Math.trunc(Math.min(t.shape[1]||0,e.endPoint[1])-Math.max(0,e.startPoint[1]))]:[0,0,0,0],q2=(e,t)=>e?[e.startPoint[0]/(t.shape[2]||0),e.startPoint[1]/(t.shape[1]||0),(e.endPoint[0]-e.startPoint[0])/(t.shape[2]||0),(e.endPoint[1]-e.startPoint[1])/(t.shape[1]||0)]:[0,0,0,0],Ut=(e,t)=>{let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]];return{startPoint:o,endPoint:n,landmarks:e.landmarks,confidence:e.confidence}},K5=(e,t,o)=>{let n=t.shape[1],r=t.shape[2],A=[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r],s=ie.image.cropAndResize(t,[A],[0],o),a=ie.div(s,V.tf255);return ie.dispose(s),a},U2=(e,t)=>{let o=Z2(e),n=Je(e),r=[t*n[0]/2,t*n[1]/2];return{startPoint:[o[0]-r[0],o[1]-r[1]],endPoint:[o[0]+r[0],o[1]+r[1]],landmarks:e.landmarks,confidence:e.confidence}},Y2=e=>{let t=Z2(e),o=Je(e),n=Math.max(...o)/2;return{startPoint:[Math.round(t[0]-n),Math.round(t[1]-n)],endPoint:[Math.round(t[0]+n),Math.round(t[1]+n)],landmarks:e.landmarks,confidence:e.confidence}},Yt=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return{startPoint:[Math.min(...t),Math.min(...o)],endPoint:[Math.max(...t),Math.max(...o)],landmarks:e}},J5=[[1,0,0],[0,1,0],[0,0,1]],Er=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),zr=(e,t)=>Er(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var Xt=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],Oe=(e,t)=>{let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o},Sr=(e,t)=>{let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o},qt=(e,t)=>{let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let A=0;A<n;A++)o[r].push(Oe(e[r],Sr(t,A)))}return o},Kt=(e,t)=>{let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],A=Xt(t[0],t[1]),s=qt(A,r),a=Xt(-t[0],-t[1]);return qt(s,a)},Cr=e=>{let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-Oe(t[0],o),-Oe(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]},jr=(e,t)=>[Oe(e,t[0]),Oe(e,t[1])];function Jt(e){let t=e===192?{strides:[4],anchors:[1]}:{strides:[e/16,e/8],anchors:[2,6]},o=[];for(let n=0;n<t.strides.length;n++){let r=t.strides[n],A=Math.floor((e+r-1)/r),s=Math.floor((e+r-1)/r),a=t.anchors[n];for(let i=0;i<A;i++){let x=r*(i+.5);for(let c=0;c<s;c++){let l=r*(c+.5);for(let y=0;y<a;y++)o.push([l,x])}}}return o}function Qt(e,t,o,n,r){let A=Je(t),s=e.map(f=>[A[0]/r*(f[0]-r/2),A[1]/r*(f[1]-r/2),f[2]||0]),a=o&&o!==0&&Math.abs(o)>.2,i=a?Kt(o,[0,0]):J5,x=a?s.map(f=>[...jr(f,i),f[2]]):s,c=a?Cr(n):J5,l=Z2(t),y=[Oe(l,c[0]),Oe(l,c[1])];return x.map(f=>[Math.trunc(f[0]+y[0]),Math.trunc(f[1]+y[1]),Math.trunc(f[2]||0)])}function _t(e,t,o,n){let r=t.landmarks.length>=q5.count?q5.symmetryLine:Ie.symmetryLine,A=0,s=J5,a;if(e&&v.kernels.includes("rotatewithoffset"))if(A=zr(t.landmarks[r[0]],t.landmarks[r[1]]),A&&A!==0&&Math.abs(A)>.2){let x=Z2(t),c=[x[0]/o.shape[2],x[1]/o.shape[1]],l=ie.image.rotateWithOffset(o,A,0,c);s=Kt(-A,x),a=K5(t,l,[n,n]),ie.dispose(l)}else a=K5(t,o,[n,n]);else a=K5(t,o,[n,n]);return[A,s,a]}var Ir=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return[Math.min(...t)+(Math.max(...t)-Math.min(...t))/2,Math.min(...o)+(Math.max(...o)-Math.min(...o))/2]},$t=(e,t)=>{let o=Ir(e),n=Je(t);return{startPoint:[o[0]-n[0]/2,o[1]-n[1]/2],endPoint:[o[0]+n[0]/2,o[1]+n[1]/2]}};var e3=6,Nr=1.4,te,t3=null,Me=0,v2=null,Qe=()=>Me;async function o3(e){var t;return v.initial&&(te=null),te?e.debug&&p("cached model:",te.modelUrl):te=await G((t=e.face.detector)==null?void 0:t.modelPath),Me=te.inputs[0].shape?te.inputs[0].shape[2]:0,v2=O.scalar(Me,"int32"),t3=O.tensor2d(Jt(Me)),te}function Or(e){let t={};t.boxStarts=O.slice(e,[0,1],[-1,2]),t.centers=O.add(t.boxStarts,t3),t.boxSizes=O.slice(e,[0,3],[-1,2]),t.boxSizesNormalized=O.div(t.boxSizes,v2),t.centersNormalized=O.div(t.centers,v2),t.halfBoxSize=O.div(t.boxSizesNormalized,V.tf2),t.starts=O.sub(t.centersNormalized,t.halfBoxSize),t.ends=O.add(t.centersNormalized,t.halfBoxSize),t.startNormalized=O.mul(t.starts,v2),t.endNormalized=O.mul(t.ends,v2);let o=O.concat2d([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(n=>O.dispose(t[n])),o}async function n3(e,t){var a,i,x,c;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let o={};o.resized=O.image.resizeBilinear(e,[Me,Me]),o.div=O.div(o.resized,V.tf127),o.normalized=O.sub(o.div,V.tf05);let n=te==null?void 0:te.execute(o.normalized);if(Array.isArray(n)&&n.length>2){let l=n.sort((y,f)=>y.size-f.size);o.concat384=O.concat([l[0],l[2]],2),o.concat512=O.concat([l[1],l[3]],2),o.concat=O.concat([o.concat512,o.concat384],1),o.batch=O.squeeze(o.concat,0)}else Array.isArray(n)?o.batch=O.squeeze(n[0]):o.batch=O.squeeze(n);O.dispose(n),o.boxes=Or(o.batch),o.logits=O.slice(o.batch,[0,0],[-1,1]),o.sigmoid=O.sigmoid(o.logits),o.scores=O.squeeze(o.sigmoid),o.nms=await O.image.nonMaxSuppressionAsync(o.boxes,o.scores,((a=t.face.detector)==null?void 0:a.maxDetected)||0,((i=t.face.detector)==null?void 0:i.iouThreshold)||0,((x=t.face.detector)==null?void 0:x.minConfidence)||0);let r=await o.nms.array(),A=[],s=await o.scores.data();for(let l=0;l<r.length;l++){let y=s[r[l]];if(y>(((c=t.face.detector)==null?void 0:c.minConfidence)||0)){let f={};f.bbox=O.slice(o.boxes,[r[l],0],[1,-1]),f.slice=O.slice(o.batch,[r[l],e3-1],[1,-1]),f.squeeze=O.squeeze(f.slice),f.landmarks=O.reshape(f.squeeze,[e3,-1]);let u=await f.bbox.data(),m={startPoint:[u[0],u[1]],endPoint:[u[2],u[3]],landmarks:await f.landmarks.array(),confidence:y},P=Ut(m,[(e.shape[2]||0)/Me,(e.shape[1]||0)/Me]),g=U2(P,t.face.scale||Nr),b=Y2(g);A.push(b),Object.keys(f).forEach(d=>O.dispose(f[d]))}}return Object.keys(o).forEach(l=>O.dispose(o[l])),A}var I0=Z(D());var K2={};ue(K2,{connected:()=>$5,kpt:()=>_5});var _5=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPinky","rightPinky","leftIndex","rightIndex","leftThumb","rightThumb","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","bodyCenter","bodyTop","leftPalm","leftHand","rightPalm","rightHand"],$5={shoulders:["leftShoulder","rightShoulder"],hips:["rightHip","leftHip"],mouth:["leftMouth","rightMouth"],leftLegUpper:["leftHip","leftKnee"],leftLegLower:["leftKnee","leftAnkle"],leftFoot:["leftAnkle","leftHeel","leftFoot"],leftTorso:["leftShoulder","leftHip"],leftArmUpper:["leftShoulder","leftElbow"],leftArmLower:["leftElbow","leftWrist"],leftHand:["leftWrist","leftPalm"],leftHandPinky:["leftPalm","leftPinky"],leftHandIndex:["leftPalm","leftIndex"],leftHandThumb:["leftPalm","leftThumb"],leftEyeOutline:["leftEyeInside","leftEyeOutside"],rightLegUpper:["rightHip","rightKnee"],rightLegLower:["rightKnee","rightAnkle"],rightFoot:["rightAnkle","rightHeel","rightFoot"],rightTorso:["rightShoulder","rightHip"],rightArmUpper:["rightShoulder","rightElbow"],rightArmLower:["rightElbow","rightWrist"],rightHand:["rightWrist","rightPalm"],rightHandPinky:["rightPalm","rightPinky"],rightHandIndex:["rightPalm","rightIndex"],rightHandThumb:["rightPalm","rightThumb"],rightEyeOutline:["rightEyeInside","rightEyeOutside"]};var C0=Z(D()),A3=224,Lr,Wr=5,J2=[8,16,32,32,32];async function s3(){let e=[],t=0;for(;t<Wr;){let o=0,n=t;for(;n<J2.length&&J2[n]===J2[t];)o+=2,n++;let r=J2[t],A=Math.ceil(A3/r),s=Math.ceil(A3/r);for(let a=0;a<A;++a)for(let i=0;i<s;++i)for(let x=0;x<o;++x)e.push({x:(i+.5)/s,y:(a+.5)/A});t=n}Lr={x:C0.tensor1d(e.map(o=>o.x)),y:C0.tensor1d(e.map(o=>o.y))}}function le(e,t=[1,1]){let o=[e.map(a=>a[0]),e.map(a=>a[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],A=[n[0],n[1],r[0]-n[0],r[1]-n[1]],s=[A[0]/t[0],A[1]/t[1],A[2]/t[0],A[3]/t[1]];return{box:A,boxRaw:s}}function a3(e,t=[1,1]){let o=[e.map(x=>x[0]),e.map(x=>x[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],A=[(n[0]+r[0])/2,(n[1]+r[1])/2],s=Math.max(A[0]-n[0],A[1]-n[1],-A[0]+r[0],-A[1]+r[1]),a=[Math.trunc(A[0]-s),Math.trunc(A[1]-s),Math.trunc(2*s),Math.trunc(2*s)],i=[a[0]/t[0],a[1]/t[1],a[2]/t[0],a[3]/t[1]];return{box:a,boxRaw:i}}function Q2(e,t){let o=[e[2]*t,e[3]*t];return[e[0]-(o[0]-e[2])/2,e[1]-(o[1]-e[3])/2,o[0],o[1]]}var y3={initial:!0},j0={detector:null,landmarks:null},_e={detector:[224,224],landmarks:[256,256]},e1=Number.MAX_SAFE_INTEGER,Gr={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},$2=null,T2,Pe=[[0,0],[0,0],[0,0],[0,0]],i3=0,l3=e=>1-1/(1+Math.exp(e));async function x3(e){if(y3.initial&&(j0.detector=null),!j0.detector&&e.body.detector&&e.body.detector.modelPath){j0.detector=await G(e.body.detector.modelPath);let t=Object.values(j0.detector.modelSignature.inputs);_e.detector[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,_e.detector[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&j0.detector&&p("cached model:",j0.detector.modelUrl);return await s3(),j0.detector}async function c3(e){if(y3.initial&&(j0.landmarks=null),j0.landmarks)e.debug&&p("cached model:",j0.landmarks.modelUrl);else{j0.landmarks=await G(e.body.modelPath);let t=Object.values(j0.landmarks.modelSignature.inputs);_e.landmarks[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,_e.landmarks[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return j0.landmarks}async function Br(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;let n;if(T2&&(o.cropped=I0.image.cropAndResize(e,[T2],[0],[e.shape[1],e.shape[2]])),e.shape[1]!==e.shape[2]){let r=[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],A=[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0];Pe=[[0,0],r,A,[0,0]],o.pad=I0.pad(o.cropped||e,Pe),o.resize=I0.image.resizeBilinear(o.pad,[t,t]),n=I0.div(o.resize,V.tf255)}else e.shape[1]!==t?(o.resize=I0.image.resizeBilinear(o.cropped||e,[t,t]),n=I0.div(o.resize,V.tf255)):n=I0.div(o.cropped||e,V.tf255);return Object.keys(o).forEach(r=>I0.dispose(o[r])),n}function Hr(e,t){for(let o of e)o.position=[Math.trunc(o.position[0]*(t[0]+Pe[2][0]+Pe[2][1])/t[0]-Pe[2][0]),Math.trunc(o.position[1]*(t[1]+Pe[1][0]+Pe[1][1])/t[1]-Pe[1][0]),o.position[2]],o.positionRaw=[o.position[0]/t[0],o.position[1]/t[1],2*o.position[2]/(t[0]+t[1])];if(T2)for(let o of e)o.positionRaw=[o.positionRaw[0]+T2[1],o.positionRaw[1]+T2[0],o.positionRaw[2]],o.position=[Math.trunc(o.positionRaw[0]*t[0]),Math.trunc(o.positionRaw[1]*t[1]),o.positionRaw[2]];return e}async function Vr(e){let t=e.find(a=>a.part==="leftPalm"),o=e.find(a=>a.part==="leftWrist"),n=e.find(a=>a.part==="leftIndex");t.position[2]=((o.position[2]||0)+(n.position[2]||0))/2;let r=e.find(a=>a.part==="rightPalm"),A=e.find(a=>a.part==="rightWrist"),s=e.find(a=>a.part==="rightIndex");r.position[2]=((A.position[2]||0)+(s.position[2]||0))/2}async function Dr(e,t,o){var u;let n={};[n.ld,n.segmentation,n.heatmap,n.world,n.poseflag]=(u=j0.landmarks)==null?void 0:u.execute(e,Gr.landmarks);let r=(await n.poseflag.data())[0],A=await n.ld.data(),s=await n.world.data();Object.keys(n).forEach(m=>I0.dispose(n[m]));let a=[],i=5;for(let m=0;m<A.length/i;m++){let P=l3(A[i*m+3]),g=l3(A[i*m+4]),b=Math.trunc(100*P*g*r)/100,d=[A[i*m+0]/_e.landmarks[0],A[i*m+1]/_e.landmarks[1],A[i*m+2]+0],M=[Math.trunc(o[0]*d[0]),Math.trunc(o[1]*d[1]),d[2]],S=[s[i*m+0],s[i*m+1],s[i*m+2]+0];a.push({part:_5[m],positionRaw:d,position:M,distance:S,score:b})}if(r<(t.body.minConfidence||0))return null;Vr(a);let x=Hr(a,o),c=x.map(m=>m.position),l=le(c,[o[0],o[1]]),y={};for(let[m,P]of Object.entries($5)){let g=[];for(let b=0;b<P.length-1;b++){let d=x.find(S=>S.part===P[b]),M=x.find(S=>S.part===P[b+1]);d&&M&&g.push([d.position,M.position])}y[m]=g}return{id:0,score:Math.trunc(100*r)/100,box:l.box,boxRaw:l.boxRaw,keypoints:x,annotations:y}}async function t1(e,t){let o=[e.shape[2]||0,e.shape[1]||0],n=(t.body.skipTime||0)>h()-i3,r=e1<(t.body.skipFrames||0);if(t.skipAllowed&&n&&r&&$2!==null)e1++;else{let A={};A.landmarks=await Br(e,256),$2=await Dr(A.landmarks,t,o),Object.keys(A).forEach(s=>I0.dispose(A[s])),i3=h(),e1=0}return $2?[$2]:[]}var T0=Z(D());var $e=[{class:1,label:"person"},{class:2,label:"bicycle"},{class:3,label:"car"},{class:4,label:"motorcycle"},{class:5,label:"airplane"},{class:6,label:"bus"},{class:7,label:"train"},{class:8,label:"truck"},{class:9,label:"boat"},{class:10,label:"traffic light"},{class:11,label:"fire hydrant"},{class:12,label:"stop sign"},{class:13,label:"parking meter"},{class:14,label:"bench"},{class:15,label:"bird"},{class:16,label:"cat"},{class:17,label:"dog"},{class:18,label:"horse"},{class:19,label:"sheep"},{class:20,label:"cow"},{class:21,label:"elephant"},{class:22,label:"bear"},{class:23,label:"zebra"},{class:24,label:"giraffe"},{class:25,label:"backpack"},{class:26,label:"umbrella"},{class:27,label:"handbag"},{class:28,label:"tie"},{class:29,label:"suitcase"},{class:30,label:"frisbee"},{class:31,label:"skis"},{class:32,label:"snowboard"},{class:33,label:"sports ball"},{class:34,label:"kite"},{class:35,label:"baseball bat"},{class:36,label:"baseball glove"},{class:37,label:"skateboard"},{class:38,label:"surfboard"},{class:39,label:"tennis racket"},{class:40,label:"bottle"},{class:41,label:"wine glass"},{class:42,label:"cup"},{class:43,label:"fork"},{class:44,label:"knife"},{class:45,label:"spoon"},{class:46,label:"bowl"},{class:47,label:"banana"},{class:48,label:"apple"},{class:49,label:"sandwich"},{class:50,label:"orange"},{class:51,label:"broccoli"},{class:52,label:"carrot"},{class:53,label:"hot dog"},{class:54,label:"pizza"},{class:55,label:"donut"},{class:56,label:"cake"},{class:57,label:"chair"},{class:58,label:"couch"},{class:59,label:"potted plant"},{class:60,label:"bed"},{class:61,label:"dining table"},{class:62,label:"toilet"},{class:63,label:"tv"},{class:64,label:"laptop"},{class:65,label:"mouse"},{class:66,label:"remote"},{class:67,label:"keyboard"},{class:68,label:"cell phone"},{class:69,label:"microwave"},{class:70,label:"oven"},{class:71,label:"toaster"},{class:72,label:"sink"},{class:73,label:"refrigerator"},{class:74,label:"book"},{class:75,label:"clock"},{class:76,label:"vase"},{class:77,label:"scissors"},{class:78,label:"teddy bear"},{class:79,label:"hair drier"},{class:80,label:"toothbrush"}];var ye,Le=0,o1=[],f3=0,n1=Number.MAX_SAFE_INTEGER;async function m3(e){if(v.initial&&(ye=null),ye)e.debug&&p("cached model:",ye.modelUrl);else{ye=await G(e.object.modelPath);let t=Object.values(ye.modelSignature.inputs);Le=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return ye}async function Zr(e,t,o){if(!e)return[];let n={},r=[],A=await e.array();n.squeeze=T0.squeeze(e);let s=T0.split(n.squeeze,6,1);n.stack=T0.stack([s[1],s[0],s[3],s[2]],1),n.boxes=T0.squeeze(n.stack),n.scores=T0.squeeze(s[4]),n.classes=T0.squeeze(s[5]),T0.dispose([e,...s]),n.nms=await T0.image.nonMaxSuppressionAsync(n.boxes,n.scores,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence||0);let a=await n.nms.data(),i=0;for(let x of Array.from(a)){let c=Math.trunc(100*A[0][x][4])/100,l=A[0][x][5],y=$e[l].label,[f,u]=[A[0][x][0]/Le,A[0][x][1]/Le],m=[f,u,A[0][x][2]/Le-f,A[0][x][3]/Le-u],P=[Math.trunc(m[0]*t[0]),Math.trunc(m[1]*t[1]),Math.trunc(m[2]*t[0]),Math.trunc(m[3]*t[1])];r.push({id:i++,score:c,class:l,label:y,box:P,boxRaw:m})}return Object.keys(n).forEach(x=>T0.dispose(n[x])),r}async function r1(e,t){let o=(t.object.skipTime||0)>h()-f3,n=n1<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&o1.length>0?(n1++,o1):(n1=0,new Promise(async r=>{let A=[e.shape[2]||0,e.shape[1]||0],s=T0.image.resizeBilinear(e,[Le,Le]),a=t.object.enabled?ye==null?void 0:ye.execute(s,["tower_0/detections"]):null;f3=h(),T0.dispose(s);let i=await Zr(a,A,t);o1=i,r(i)}))}var _=Z(D());var e5={};ue(e5,{connected:()=>s1,kpt:()=>A1});var A1=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],s1={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var b0,u3=0,w0={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},a1=Number.MAX_SAFE_INTEGER;async function h3(e){return v.initial&&(b0=null),b0?e.debug&&p("cached model:",b0.modelUrl):b0=await G(e.body.modelPath),b0}async function Xr(e,t){let[o,n]=e.shape,r=_.reshape(e,[n*o]),A=_.max(r,0),s=(await A.data())[0];if(_.dispose([r,A]),s>t){let a=_.argMax(r,0),i=_.mod(a,o),x=(await i.data())[0],c=_.div(a,_.scalar(o,"int32")),l=(await c.data())[0];return _.dispose([i,c]),[x,l,s]}return[0,0,s]}async function i1(e,t){let o=(t.body.skipTime||0)>h()-u3,n=a1<(t.body.skipFrames||0);return t.skipAllowed&&o&&n&&Object.keys(w0.keypoints).length>0?(a1++,[w0]):(a1=0,new Promise(async r=>{var l;let A=_.tidy(()=>{if(!(b0!=null&&b0.inputs[0].shape))return null;let y=_.image.resizeBilinear(e,[b0.inputs[0].shape[2],b0.inputs[0].shape[1]],!1),f=_.mul(y,V.tf2);return _.sub(f,V.tf1)}),s;if(t.body.enabled&&(s=b0==null?void 0:b0.execute(A)),u3=h(),_.dispose(A),s){w0.keypoints.length=0;let y=s.squeeze();_.dispose(s);let f=y.unstack(2);_.dispose(y);for(let u=0;u<f.length;u++){let[m,P,g]=await Xr(f[u],t.body.minConfidence);g>(((l=t.body)==null?void 0:l.minConfidence)||0)&&w0.keypoints.push({score:Math.round(100*g)/100,part:A1[u],positionRaw:[m/b0.inputs[0].shape[2],P/b0.inputs[0].shape[1]],position:[Math.round(e.shape[2]*m/b0.inputs[0].shape[2]),Math.round(e.shape[1]*P/b0.inputs[0].shape[1])]})}f.forEach(u=>_.dispose(u))}w0.score=w0.keypoints.reduce((y,f)=>f.score>y?f.score:y,0);let a=w0.keypoints.map(y=>y.position[0]),i=w0.keypoints.map(y=>y.position[1]);w0.box=[Math.min(...a),Math.min(...i),Math.max(...a)-Math.min(...a),Math.max(...i)-Math.min(...i)];let x=w0.keypoints.map(y=>y.positionRaw[0]),c=w0.keypoints.map(y=>y.positionRaw[1]);w0.boxRaw=[Math.min(...x),Math.min(...c),Math.max(...x)-Math.min(...x),Math.max(...c)-Math.min(...c)];for(let[y,f]of Object.entries(s1)){let u=[];for(let m=0;m<f.length-1;m++){let P=w0.keypoints.find(b=>b.part===f[m]),g=w0.keypoints.find(b=>b.part===f[m+1]);P&&g&&P.score>(t.body.minConfidence||0)&&g.score>(t.body.minConfidence||0)&&u.push([P.position,g.position])}w0.annotations[y]=u}r([w0])}))}var U0=Z(D());var qr=["angry","disgust","fear","happy","sad","surprise","neutral"],H0,t5=[],g3=0,M3=0,l1=Number.MAX_SAFE_INTEGER;async function P3(e){var t;return v.initial&&(H0=null),H0?e.debug&&p("cached model:",H0.modelUrl):H0=await G((t=e.face.emotion)==null?void 0:t.modelPath),H0}async function y1(e,t,o,n){var s,a;if(!H0)return[];let r=l1<(((s=t.face.emotion)==null?void 0:s.skipFrames)||0),A=(((a=t.face.emotion)==null?void 0:a.skipTime)||0)>h()-M3;return t.skipAllowed&&A&&r&&g3===n&&t5[o]&&t5[o].length>0?(l1++,t5[o]):(l1=0,new Promise(async i=>{var c,l;let x=[];if((c=t.face.emotion)!=null&&c.enabled){let y={},f=H0!=null&&H0.inputs[0].shape?H0.inputs[0].shape[2]:0;y.resize=U0.image.resizeBilinear(e,[f,f],!1),y.channels=U0.mul(y.resize,V.rgb),y.grayscale=U0.sum(y.channels,3,!0),y.grayscaleSub=U0.sub(y.grayscale,V.tf05),y.grayscaleMul=U0.mul(y.grayscaleSub,V.tf2),y.emotion=H0==null?void 0:H0.execute(y.grayscaleMul),M3=h();let u=await y.emotion.data();for(let m=0;m<u.length;m++)u[m]>(((l=t.face.emotion)==null?void 0:l.minConfidence)||0)&&x.push({score:Math.min(.99,Math.trunc(100*u[m])/100),emotion:qr[m]});x.sort((m,P)=>P.score-m.score),Object.keys(y).forEach(m=>U0.dispose(y[m]))}t5[o]=x,g3=n,i(x)}))}var k3=Z(D());var N0,x1=[],v3=0,T3=0,w3=Number.MAX_SAFE_INTEGER;async function E3(e){return v.initial&&(N0=null),N0?e.debug&&p("cached model:",N0.modelUrl):N0=await G(e.face.mobilefacenet.modelPath),N0}async function c1(e,t,o,n){var s,a;if(!N0)return[];let r=w3<(((s=t.face.embedding)==null?void 0:s.skipFrames)||0),A=(((a=t.face.embedding)==null?void 0:a.skipTime)||0)>h()-T3;return t.skipAllowed&&A&&r&&v3===n&&x1[o]?(w3++,x1[o]):new Promise(async i=>{var c;let x=[];if(((c=t.face.embedding)==null?void 0:c.enabled)&&(N0==null?void 0:N0.inputs[0].shape)){let l={};l.crop=k3.image.resizeBilinear(e,[N0.inputs[0].shape[2],N0.inputs[0].shape[1]],!1),l.data=N0==null?void 0:N0.execute(l.crop);let y=await l.data.data();x=Array.from(y)}x1[o]=x,v3=n,T3=h(),i(x)})}var Be=Z(D());var Y0=Z(D());var xe,Re=0,Ur=2.3,d1=X0.leftEyeLower0,f1=X0.rightEyeLower0,e2={leftBounds:[d1[0],d1[d1.length-1]],rightBounds:[f1[0],f1[f1.length-1]]},t2={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function I3(e){var t;return v.initial&&(xe=null),xe?e.debug&&p("cached model:",xe.modelUrl):xe=await G((t=e.face.iris)==null?void 0:t.modelPath),Re=xe.inputs[0].shape?xe.inputs[0].shape[2]:0,Re===-1&&(Re=64),xe}function o5(e,t,o,n){for(let r=0;r<U5.length;r++){let{key:A,indices:s}=U5[r],a=X0[`${o}${A}`];if(!n||n.includes(A))for(let i=0;i<s.length;i++){let x=s[i];e[a[i]]=[t[x][0],t[x][1],(t[x][2]+e[a[i]][2])/2]}}}var Yr=e=>{let t=e[e2.leftBounds[0]][2],o=e[e2.rightBounds[0]][2];return t-o},S3=(e,t,o,n,r,A=!1)=>{let s=Y2(U2(Yt([e[o],e[n]]),Ur)),a=Je(s),i=Y0.image.cropAndResize(t,[[s.startPoint[1]/r,s.startPoint[0]/r,s.endPoint[1]/r,s.endPoint[0]/r]],[0],[Re,Re]);if(A&&v.kernels.includes("flipleftright")){let x=Y0.image.flipLeftRight(i);Y0.dispose(i),i=x}return{box:s,boxSize:a,crop:i}},C3=(e,t,o,n=!1)=>{let r=[];for(let A=0;A<t2.numCoordinates;A++){let s=e[A*3],a=e[A*3+1],i=e[A*3+2];r.push([(n?1-s/Re:s/Re)*o[0]+t.startPoint[0],a/Re*o[1]+t.startPoint[1],i])}return{rawCoords:r,iris:r.slice(t2.index)}},j3=(e,t,o)=>{let n=e[X0[`${o}EyeUpper0`][t2.upperCenter]][2],r=e[X0[`${o}EyeLower0`][t2.lowerCenter]][2],A=(n+r)/2;return t.map((s,a)=>{let i=A;return a===2?i=n:a===4&&(i=r),[s[0],s[1],i]})};async function N3(e,t,o,n){if(!xe)return o.debug&&p("face mesh iris detection requested, but model is not loaded"),e;let{box:r,boxSize:A,crop:s}=S3(e,t,e2.leftBounds[0],e2.leftBounds[1],n,!0),{box:a,boxSize:i,crop:x}=S3(e,t,e2.rightBounds[0],e2.rightBounds[1],n,!0),c=Y0.concat([s,x]);Y0.dispose(s),Y0.dispose(x);let l=xe.execute(c);Y0.dispose(c);let y=await l.data();Y0.dispose(l);let f=y.slice(0,t2.numCoordinates*3),{rawCoords:u,iris:m}=C3(f,r,A,!0),P=y.slice(t2.numCoordinates*3),{rawCoords:g,iris:b}=C3(P,a,i,!1),d=Yr(e);Math.abs(d)<30?(o5(e,u,"left",null),o5(e,g,"right",null)):d<1?o5(e,u,"left",["EyeUpper0","EyeLower0"]):o5(e,g,"right",["EyeUpper0","EyeLower0"]);let M=j3(e,m,"left"),S=j3(e,b,"right");return e.concat(M).concat(S)}var Kr=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Jr=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Qr=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],_r=[[474,475],[475,476],[476,477],[477,474]],$r=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],eA=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],tA=[[469,470],[470,471],[471,472],[472,469]],oA=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]];function ve(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var nA={lips:ve(Kr),leftEye:ve(Jr),leftEyebrow:ve(Qr),leftIris:ve(_r),rightEye:ve($r),rightEyebrow:ve(eA),rightIris:ve(tA),faceOval:ve(oA)},rA=Object.entries(nA).map(([e,t])=>t.map(o=>[o,e])).flat(),f4=new Map(rA),w2=[61,146,91,181,84,17,314,405,321,375,291,185,40,39,37,0,267,269,270,409,78,95,88,178,87,14,317,402,318,324,308,191,80,81,82,13,312,311,310,415,76,77,90,180,85,16,315,404,320,307,306,184,74,73,72,11,302,303,304,408,62,96,89,179,86,15,316,403,319,325,292,183,42,41,38,12,268,271,272,407],We=[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173,130,25,110,24,23,22,26,112,243,247,30,29,27,28,56,190,226,31,228,229,230,231,232,233,244,113,225,224,223,222,221,189,35,124,46,53,52,65,143,111,117,118,119,120,121,128,245,156,70,63,105,66,107,55,193],Fe=[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398,359,255,339,254,253,252,256,341,463,467,260,259,257,258,286,414,446,261,448,449,450,451,452,453,464,342,445,444,443,442,441,413,265,353,276,283,282,295,372,340,346,347,348,349,350,357,465,383,300,293,334,296,336,285,417];async function W3(e,t){let o={lips:await t.filter(A=>A.size===160)[0].data(),irisL:await t.filter(A=>A.size===10)[0].data(),eyeL:await t.filter(A=>A.size===142)[0].data(),irisR:await t.filter(A=>A.size===10)[1].data(),eyeR:await t.filter(A=>A.size===142)[1].data()},n=We.reduce((A,s)=>A+=e[s][2],0)/We.length;for(let A=0;A<o.irisL.length/2;A++)e.push([o.irisL[2*A+0],o.irisL[2*A+1],n]);let r=Fe.reduce((A,s)=>A+=e[s][2],0)/Fe.length;for(let A=0;A<o.irisR.length/2;A++)e.push([o.irisR[2*A+0],o.irisR[2*A+1],r]);for(let A=0;A<o.eyeL.length/2;A++)e[We[A]]=[o.eyeL[2*A+0],o.eyeL[2*A+1],e[We[A]][2]];for(let A=0;A<o.eyeR.length/2;A++)e[Fe[A]]=[o.eyeR[2*A+0],o.eyeR[2*A+1],e[Fe[A]][2]];for(let A=0;A<o.lips.length/2;A++)e[w2[A]]=[o.lips[2*A+0],o.lips[2*A+1],e[w2[A]][2]];return e}var oe={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},g0=null,Ge=0;async function F3(e,t){var a,i,x,c,l,y,f,u,m,P,g;let o=(((a=t.face.detector)==null?void 0:a.skipTime)||0)>h()-oe.timestamp,n=oe.skipped<(((i=t.face.detector)==null?void 0:i.skipFrames)||0);!t.skipAllowed||!o||!n||oe.boxes.length===0?(oe.boxes=await n3(e,t),oe.timestamp=h(),oe.skipped=0):oe.skipped++;let r=[],A=[],s=0;for(let b=0;b<oe.boxes.length;b++){let d=oe.boxes[b],M=0,S,w={id:s++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,annotations:{}};if([M,S,w.tensor]=_t((x=t.face.detector)==null?void 0:x.rotation,d,e,(c=t.face.mesh)!=null&&c.enabled?Ge:Qe()),(l=t==null?void 0:t.filter)!=null&&l.equalization){let j=await O2(w.tensor);Be.dispose(w.tensor),w.tensor=j}if(w.boxScore=Math.round(100*d.confidence)/100,(y=t.face.mesh)!=null&&y.enabled)if(!g0)t.debug&&p("face mesh detection requested, but model is not loaded");else{let j=g0.execute(w.tensor),F=await j.find(H=>H.shape[H.shape.length-1]===1).data();if(w.faceScore=Math.round(100*F[0])/100,w.faceScore<(((f=t.face.detector)==null?void 0:f.minConfidence)||1)){if(d.confidence=w.faceScore,(u=t.face.mesh)!=null&&u.keepInvalid){w.box=X2(d,e),w.boxRaw=q2(d,e),w.score=w.boxScore,w.mesh=d.landmarks.map(H=>[(d.startPoint[0]+d.endPoint[0])/2+(d.endPoint[0]+d.startPoint[0])*H[0]/Qe(),(d.startPoint[1]+d.endPoint[1])/2+(d.endPoint[1]+d.startPoint[1])*H[1]/Qe()]),w.meshRaw=w.mesh.map(H=>[H[0]/(e.shape[2]||1),H[1]/(e.shape[1]||1),(H[2]||0)/Ge]);for(let H of Object.keys(Ie))w.annotations[H]=[w.mesh[Ie[H]]]}}else{let H=j.find(E=>E.shape[E.shape.length-1]===1404),Y=Be.reshape(H,[-1,3]),J=await Y.array();Be.dispose(Y),(m=t.face.attention)!=null&&m.enabled?J=await W3(J,j):(P=t.face.iris)!=null&&P.enabled&&(J=await N3(J,w.tensor,t,Ge)),w.mesh=Qt(J,d,M,S,Ge),w.meshRaw=w.mesh.map(E=>[E[0]/(e.shape[2]||0),E[1]/(e.shape[1]||0),(E[2]||0)/Ge]);for(let E of Object.keys(X0))w.annotations[E]=X0[E].map(G0=>w.mesh[G0]);w.score=w.faceScore;let x0={...$t(w.mesh,d),confidence:d.confidence,landmarks:d.landmarks};w.box=X2(x0,e),w.boxRaw=q2(x0,e),A.push(x0)}Be.dispose(j)}else{w.box=X2(d,e),w.boxRaw=q2(d,e),w.score=w.boxScore,w.mesh=d.landmarks.map(j=>[(d.startPoint[0]+d.endPoint[0])/2+(d.endPoint[0]+d.startPoint[0])*j[0]/Qe(),(d.startPoint[1]+d.endPoint[1])/2+(d.endPoint[1]+d.startPoint[1])*j[1]/Qe()]),w.meshRaw=w.mesh.map(j=>[j[0]/(e.shape[2]||0),j[1]/(e.shape[1]||0),(j[2]||0)/Ge]);for(let j of Object.keys(Ie))w.annotations[j]=[w.mesh[Ie[j]]]}w.score>(((g=t.face.detector)==null?void 0:g.minConfidence)||1)?r.push(w):Be.dispose(w.tensor)}return oe.boxes=A,r}async function G3(e){var t,o,n,r,A,s;return v.initial&&(g0=null),((o=(t=e==null?void 0:e.face)==null?void 0:t.attention)==null?void 0:o.enabled)&&(g0==null?void 0:g0.signature)&&Object.keys(((n=g0==null?void 0:g0.signature)==null?void 0:n.outputs)||{}).length<6&&(g0=null),g0?e.debug&&p("cached model:",g0.modelUrl):(r=e.face.attention)!=null&&r.enabled?g0=await G((A=e.face.attention)==null?void 0:A.modelPath):g0=await G((s=e.face.mesh)==null?void 0:s.modelPath),Ge=g0.inputs[0].shape?g0.inputs[0].shape[2]:0,g0}var B3=Ne,H3=R2;var K0=Z(D());var O0,n5=[],V3=0,D3=0,p1=Number.MAX_SAFE_INTEGER;async function Z3(e){var t;return v.initial&&(O0=null),O0?e.debug&&p("cached model:",O0.modelUrl):O0=await G((t=e.face.description)==null?void 0:t.modelPath),O0}function u1(e){let t=e.image||e.tensor||e;if(!(O0!=null&&O0.inputs[0].shape))return t;let o=K0.image.resizeBilinear(t,[O0.inputs[0].shape[2],O0.inputs[0].shape[1]],!1),n=K0.mul(o,V.tf255);return K0.dispose(o),n}async function h1(e,t,o,n){var s,a,i,x;if(!O0)return{age:0,gender:"unknown",genderScore:0,descriptor:[]};let r=p1<(((s=t.face.description)==null?void 0:s.skipFrames)||0),A=(((a=t.face.description)==null?void 0:a.skipTime)||0)>h()-V3;return t.skipAllowed&&r&&A&&D3===n&&((i=n5[o])==null?void 0:i.age)&&((x=n5[o])==null?void 0:x.age)>0?(p1++,n5[o]):(p1=0,new Promise(async c=>{var y,f;let l={age:0,gender:"unknown",genderScore:0,descriptor:[]};if((y=t.face.description)!=null&&y.enabled){let u=u1(e),m=O0==null?void 0:O0.execute(u);V3=h(),K0.dispose(u);let g=await(await m.find(F=>F.shape[1]===1)).data(),b=Math.trunc(200*Math.abs(g[0]-.5))/100;b>(((f=t.face.description)==null?void 0:f.minConfidence)||0)&&(l.gender=g[0]<=.5?"female":"male",l.genderScore=Math.min(.99,b));let d=K0.argMax(m.find(F=>F.shape[1]===100),1),M=(await d.data())[0];K0.dispose(d);let w=await m.find(F=>F.shape[1]===100).data();l.age=Math.round(w[M-1]>w[M+1]?10*M-100*w[M-1]:10*M+100*w[M+1])/10;let j=m.find(F=>F.shape[1]===1024),C=j?await j.data():[];l.descriptor=Array.from(C),m.forEach(F=>K0.dispose(F))}n5[o]=l,D3=n,c(l)}))}var W=Z(D());var U3=Z(D());function r5(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function k2(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function Y3(e,t,o){let n=t.shape[1],r=t.shape[2],A=[[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r]];return U3.image.cropAndResize(t,A,[0],o)}function K3(e,t){let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],r=e.palmLandmarks.map(A=>[A[0]*t[0],A[1]*t[1]]);return{startPoint:o,endPoint:n,palmLandmarks:r,confidence:e.confidence}}function A5(e,t=1.5){let o=k2(e),n=r5(e),r=[t*n[0]/2,t*n[1]/2],A=[o[0]-r[0],o[1]-r[1]],s=[o[0]+r[0],o[1]+r[1]];return{startPoint:A,endPoint:s,palmLandmarks:e.palmLandmarks}}function s5(e){let t=k2(e),o=r5(e),r=Math.max(...o)/2,A=[t[0]-r,t[1]-r],s=[t[0]+r,t[1]+r];return{startPoint:A,endPoint:s,palmLandmarks:e.palmLandmarks}}function sA(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function J3(e,t){let o=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return sA(o)}var X3=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function Te(e,t){let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o}function aA(e,t){let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o}function q3(e,t){let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let A=0;A<n;A++)o[r].push(Te(e[r],aA(t,A)))}return o}function g1(e,t){let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],A=X3(t[0],t[1]),s=q3(A,r),a=X3(-t[0],-t[1]);return q3(s,a)}function Q3(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-Te(t[0],o),-Te(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]}function M1(e,t){return[Te(e,t[0]),Te(e,t[1])]}var $3=[{x:.015625,y:.015625},{x:.015625,y:.015625},{x:.046875,y:.015625},{x:.046875,y:.015625},{x:.078125,y:.015625},{x:.078125,y:.015625},{x:.109375,y:.015625},{x:.109375,y:.015625},{x:.140625,y:.015625},{x:.140625,y:.015625},{x:.171875,y:.015625},{x:.171875,y:.015625},{x:.203125,y:.015625},{x:.203125,y:.015625},{x:.234375,y:.015625},{x:.234375,y:.015625},{x:.265625,y:.015625},{x:.265625,y:.015625},{x:.296875,y:.015625},{x:.296875,y:.015625},{x:.328125,y:.015625},{x:.328125,y:.015625},{x:.359375,y:.015625},{x:.359375,y:.015625},{x:.390625,y:.015625},{x:.390625,y:.015625},{x:.421875,y:.015625},{x:.421875,y:.015625},{x:.453125,y:.015625},{x:.453125,y:.015625},{x:.484375,y:.015625},{x:.484375,y:.015625},{x:.515625,y:.015625},{x:.515625,y:.015625},{x:.546875,y:.015625},{x:.546875,y:.015625},{x:.578125,y:.015625},{x:.578125,y:.015625},{x:.609375,y:.015625},{x:.609375,y:.015625},{x:.640625,y:.015625},{x:.640625,y:.015625},{x:.671875,y:.015625},{x:.671875,y:.015625},{x:.703125,y:.015625},{x:.703125,y:.015625},{x:.734375,y:.015625},{x:.734375,y:.015625},{x:.765625,y:.015625},{x:.765625,y:.015625},{x:.796875,y:.015625},{x:.796875,y:.015625},{x:.828125,y:.015625},{x:.828125,y:.015625},{x:.859375,y:.015625},{x:.859375,y:.015625},{x:.890625,y:.015625},{x:.890625,y:.015625},{x:.921875,y:.015625},{x:.921875,y:.015625},{x:.953125,y:.015625},{x:.953125,y:.015625},{x:.984375,y:.015625},{x:.984375,y:.015625},{x:.015625,y:.046875},{x:.015625,y:.046875},{x:.046875,y:.046875},{x:.046875,y:.046875},{x:.078125,y:.046875},{x:.078125,y:.046875},{x:.109375,y:.046875},{x:.109375,y:.046875},{x:.140625,y:.046875},{x:.140625,y:.046875},{x:.171875,y:.046875},{x:.171875,y:.046875},{x:.203125,y:.046875},{x:.203125,y:.046875},{x:.234375,y:.046875},{x:.234375,y:.046875},{x:.265625,y:.046875},{x:.265625,y:.046875},{x:.296875,y:.046875},{x:.296875,y:.046875},{x:.328125,y:.046875},{x:.328125,y:.046875},{x:.359375,y:.046875},{x:.359375,y:.046875},{x:.390625,y:.046875},{x:.390625,y:.046875},{x:.421875,y:.046875},{x:.421875,y:.046875},{x:.453125,y:.046875},{x:.453125,y:.046875},{x:.484375,y:.046875},{x:.484375,y:.046875},{x:.515625,y:.046875},{x:.515625,y:.046875},{x:.546875,y:.046875},{x:.546875,y:.046875},{x:.578125,y:.046875},{x:.578125,y:.046875},{x:.609375,y:.046875},{x:.609375,y:.046875},{x:.640625,y:.046875},{x:.640625,y:.046875},{x:.671875,y:.046875},{x:.671875,y:.046875},{x:.703125,y:.046875},{x:.703125,y:.046875},{x:.734375,y:.046875},{x:.734375,y:.046875},{x:.765625,y:.046875},{x:.765625,y:.046875},{x:.796875,y:.046875},{x:.796875,y:.046875},{x:.828125,y:.046875},{x:.828125,y:.046875},{x:.859375,y:.046875},{x:.859375,y:.046875},{x:.890625,y:.046875},{x:.890625,y:.046875},{x:.921875,y:.046875},{x:.921875,y:.046875},{x:.953125,y:.046875},{x:.953125,y:.046875},{x:.984375,y:.046875},{x:.984375,y:.046875},{x:.015625,y:.078125},{x:.015625,y:.078125},{x:.046875,y:.078125},{x:.046875,y:.078125},{x:.078125,y:.078125},{x:.078125,y:.078125},{x:.109375,y:.078125},{x:.109375,y:.078125},{x:.140625,y:.078125},{x:.140625,y:.078125},{x:.171875,y:.078125},{x:.171875,y:.078125},{x:.203125,y:.078125},{x:.203125,y:.078125},{x:.234375,y:.078125},{x:.234375,y:.078125},{x:.265625,y:.078125},{x:.265625,y:.078125},{x:.296875,y:.078125},{x:.296875,y:.078125},{x:.328125,y:.078125},{x:.328125,y:.078125},{x:.359375,y:.078125},{x:.359375,y:.078125},{x:.390625,y:.078125},{x:.390625,y:.078125},{x:.421875,y:.078125},{x:.421875,y:.078125},{x:.453125,y:.078125},{x:.453125,y:.078125},{x:.484375,y:.078125},{x:.484375,y:.078125},{x:.515625,y:.078125},{x:.515625,y:.078125},{x:.546875,y:.078125},{x:.546875,y:.078125},{x:.578125,y:.078125},{x:.578125,y:.078125},{x:.609375,y:.078125},{x:.609375,y:.078125},{x:.640625,y:.078125},{x:.640625,y:.078125},{x:.671875,y:.078125},{x:.671875,y:.078125},{x:.703125,y:.078125},{x:.703125,y:.078125},{x:.734375,y:.078125},{x:.734375,y:.078125},{x:.765625,y:.078125},{x:.765625,y:.078125},{x:.796875,y:.078125},{x:.796875,y:.078125},{x:.828125,y:.078125},{x:.828125,y:.078125},{x:.859375,y:.078125},{x:.859375,y:.078125},{x:.890625,y:.078125},{x:.890625,y:.078125},{x:.921875,y:.078125},{x:.921875,y:.078125},{x:.953125,y:.078125},{x:.953125,y:.078125},{x:.984375,y:.078125},{x:.984375,y:.078125},{x:.015625,y:.109375},{x:.015625,y:.109375},{x:.046875,y:.109375},{x:.046875,y:.109375},{x:.078125,y:.109375},{x:.078125,y:.109375},{x:.109375,y:.109375},{x:.109375,y:.109375},{x:.140625,y:.109375},{x:.140625,y:.109375},{x:.171875,y:.109375},{x:.171875,y:.109375},{x:.203125,y:.109375},{x:.203125,y:.109375},{x:.234375,y:.109375},{x:.234375,y:.109375},{x:.265625,y:.109375},{x:.265625,y:.109375},{x:.296875,y:.109375},{x:.296875,y:.109375},{x:.328125,y:.109375},{x:.328125,y:.109375},{x:.359375,y:.109375},{x:.359375,y:.109375},{x:.390625,y:.109375},{x:.390625,y:.109375},{x:.421875,y:.109375},{x:.421875,y:.109375},{x:.453125,y:.109375},{x:.453125,y:.109375},{x:.484375,y:.109375},{x:.484375,y:.109375},{x:.515625,y:.109375},{x:.515625,y:.109375},{x:.546875,y:.109375},{x:.546875,y:.109375},{x:.578125,y:.109375},{x:.578125,y:.109375},{x:.609375,y:.109375},{x:.609375,y:.109375},{x:.640625,y:.109375},{x:.640625,y:.109375},{x:.671875,y:.109375},{x:.671875,y:.109375},{x:.703125,y:.109375},{x:.703125,y:.109375},{x:.734375,y:.109375},{x:.734375,y:.109375},{x:.765625,y:.109375},{x:.765625,y:.109375},{x:.796875,y:.109375},{x:.796875,y:.109375},{x:.828125,y:.109375},{x:.828125,y:.109375},{x:.859375,y:.109375},{x:.859375,y:.109375},{x:.890625,y:.109375},{x:.890625,y:.109375},{x:.921875,y:.109375},{x:.921875,y:.109375},{x:.953125,y:.109375},{x:.953125,y:.109375},{x:.984375,y:.109375},{x:.984375,y:.109375},{x:.015625,y:.140625},{x:.015625,y:.140625},{x:.046875,y:.140625},{x:.046875,y:.140625},{x:.078125,y:.140625},{x:.078125,y:.140625},{x:.109375,y:.140625},{x:.109375,y:.140625},{x:.140625,y:.140625},{x:.140625,y:.140625},{x:.171875,y:.140625},{x:.171875,y:.140625},{x:.203125,y:.140625},{x:.203125,y:.140625},{x:.234375,y:.140625},{x:.234375,y:.140625},{x:.265625,y:.140625},{x:.265625,y:.140625},{x:.296875,y:.140625},{x:.296875,y:.140625},{x:.328125,y:.140625},{x:.328125,y:.140625},{x:.359375,y:.140625},{x:.359375,y:.140625},{x:.390625,y:.140625},{x:.390625,y:.140625},{x:.421875,y:.140625},{x:.421875,y:.140625},{x:.453125,y:.140625},{x:.453125,y:.140625},{x:.484375,y:.140625},{x:.484375,y:.140625},{x:.515625,y:.140625},{x:.515625,y:.140625},{x:.546875,y:.140625},{x:.546875,y:.140625},{x:.578125,y:.140625},{x:.578125,y:.140625},{x:.609375,y:.140625},{x:.609375,y:.140625},{x:.640625,y:.140625},{x:.640625,y:.140625},{x:.671875,y:.140625},{x:.671875,y:.140625},{x:.703125,y:.140625},{x:.703125,y:.140625},{x:.734375,y:.140625},{x:.734375,y:.140625},{x:.765625,y:.140625},{x:.765625,y:.140625},{x:.796875,y:.140625},{x:.796875,y:.140625},{x:.828125,y:.140625},{x:.828125,y:.140625},{x:.859375,y:.140625},{x:.859375,y:.140625},{x:.890625,y:.140625},{x:.890625,y:.140625},{x:.921875,y:.140625},{x:.921875,y:.140625},{x:.953125,y:.140625},{x:.953125,y:.140625},{x:.984375,y:.140625},{x:.984375,y:.140625},{x:.015625,y:.171875},{x:.015625,y:.171875},{x:.046875,y:.171875},{x:.046875,y:.171875},{x:.078125,y:.171875},{x:.078125,y:.171875},{x:.109375,y:.171875},{x:.109375,y:.171875},{x:.140625,y:.171875},{x:.140625,y:.171875},{x:.171875,y:.171875},{x:.171875,y:.171875},{x:.203125,y:.171875},{x:.203125,y:.171875},{x:.234375,y:.171875},{x:.234375,y:.171875},{x:.265625,y:.171875},{x:.265625,y:.171875},{x:.296875,y:.171875},{x:.296875,y:.171875},{x:.328125,y:.171875},{x:.328125,y:.171875},{x:.359375,y:.171875},{x:.359375,y:.171875},{x:.390625,y:.171875},{x:.390625,y:.171875},{x:.421875,y:.171875},{x:.421875,y:.171875},{x:.453125,y:.171875},{x:.453125,y:.171875},{x:.484375,y:.171875},{x:.484375,y:.171875},{x:.515625,y:.171875},{x:.515625,y:.171875},{x:.546875,y:.171875},{x:.546875,y:.171875},{x:.578125,y:.171875},{x:.578125,y:.171875},{x:.609375,y:.171875},{x:.609375,y:.171875},{x:.640625,y:.171875},{x:.640625,y:.171875},{x:.671875,y:.171875},{x:.671875,y:.171875},{x:.703125,y:.171875},{x:.703125,y:.171875},{x:.734375,y:.171875},{x:.734375,y:.171875},{x:.765625,y:.171875},{x:.765625,y:.171875},{x:.796875,y:.171875},{x:.796875,y:.171875},{x:.828125,y:.171875},{x:.828125,y:.171875},{x:.859375,y:.171875},{x:.859375,y:.171875},{x:.890625,y:.171875},{x:.890625,y:.171875},{x:.921875,y:.171875},{x:.921875,y:.171875},{x:.953125,y:.171875},{x:.953125,y:.171875},{x:.984375,y:.171875},{x:.984375,y:.171875},{x:.015625,y:.203125},{x:.015625,y:.203125},{x:.046875,y:.203125},{x:.046875,y:.203125},{x:.078125,y:.203125},{x:.078125,y:.203125},{x:.109375,y:.203125},{x:.109375,y:.203125},{x:.140625,y:.203125},{x:.140625,y:.203125},{x:.171875,y:.203125},{x:.171875,y:.203125},{x:.203125,y:.203125},{x:.203125,y:.203125},{x:.234375,y:.203125},{x:.234375,y:.203125},{x:.265625,y:.203125},{x:.265625,y:.203125},{x:.296875,y:.203125},{x:.296875,y:.203125},{x:.328125,y:.203125},{x:.328125,y:.203125},{x:.359375,y:.203125},{x:.359375,y:.203125},{x:.390625,y:.203125},{x:.390625,y:.203125},{x:.421875,y:.203125},{x:.421875,y:.203125},{x:.453125,y:.203125},{x:.453125,y:.203125},{x:.484375,y:.203125},{x:.484375,y:.203125},{x:.515625,y:.203125},{x:.515625,y:.203125},{x:.546875,y:.203125},{x:.546875,y:.203125},{x:.578125,y:.203125},{x:.578125,y:.203125},{x:.609375,y:.203125},{x:.609375,y:.203125},{x:.640625,y:.203125},{x:.640625,y:.203125},{x:.671875,y:.203125},{x:.671875,y:.203125},{x:.703125,y:.203125},{x:.703125,y:.203125},{x:.734375,y:.203125},{x:.734375,y:.203125},{x:.765625,y:.203125},{x:.765625,y:.203125},{x:.796875,y:.203125},{x:.796875,y:.203125},{x:.828125,y:.203125},{x:.828125,y:.203125},{x:.859375,y:.203125},{x:.859375,y:.203125},{x:.890625,y:.203125},{x:.890625,y:.203125},{x:.921875,y:.203125},{x:.921875,y:.203125},{x:.953125,y:.203125},{x:.953125,y:.203125},{x:.984375,y:.203125},{x:.984375,y:.203125},{x:.015625,y:.234375},{x:.015625,y:.234375},{x:.046875,y:.234375},{x:.046875,y:.234375},{x:.078125,y:.234375},{x:.078125,y:.234375},{x:.109375,y:.234375},{x:.109375,y:.234375},{x:.140625,y:.234375},{x:.140625,y:.234375},{x:.171875,y:.234375},{x:.171875,y:.234375},{x:.203125,y:.234375},{x:.203125,y:.234375},{x:.234375,y:.234375},{x:.234375,y:.234375},{x:.265625,y:.234375},{x:.265625,y:.234375},{x:.296875,y:.234375},{x:.296875,y:.234375},{x:.328125,y:.234375},{x:.328125,y:.234375},{x:.359375,y:.234375},{x:.359375,y:.234375},{x:.390625,y:.234375},{x:.390625,y:.234375},{x:.421875,y:.234375},{x:.421875,y:.234375},{x:.453125,y:.234375},{x:.453125,y:.234375},{x:.484375,y:.234375},{x:.484375,y:.234375},{x:.515625,y:.234375},{x:.515625,y:.234375},{x:.546875,y:.234375},{x:.546875,y:.234375},{x:.578125,y:.234375},{x:.578125,y:.234375},{x:.609375,y:.234375},{x:.609375,y:.234375},{x:.640625,y:.234375},{x:.640625,y:.234375},{x:.671875,y:.234375},{x:.671875,y:.234375},{x:.703125,y:.234375},{x:.703125,y:.234375},{x:.734375,y:.234375},{x:.734375,y:.234375},{x:.765625,y:.234375},{x:.765625,y:.234375},{x:.796875,y:.234375},{x:.796875,y:.234375},{x:.828125,y:.234375},{x:.828125,y:.234375},{x:.859375,y:.234375},{x:.859375,y:.234375},{x:.890625,y:.234375},{x:.890625,y:.234375},{x:.921875,y:.234375},{x:.921875,y:.234375},{x:.953125,y:.234375},{x:.953125,y:.234375},{x:.984375,y:.234375},{x:.984375,y:.234375},{x:.015625,y:.265625},{x:.015625,y:.265625},{x:.046875,y:.265625},{x:.046875,y:.265625},{x:.078125,y:.265625},{x:.078125,y:.265625},{x:.109375,y:.265625},{x:.109375,y:.265625},{x:.140625,y:.265625},{x:.140625,y:.265625},{x:.171875,y:.265625},{x:.171875,y:.265625},{x:.203125,y:.265625},{x:.203125,y:.265625},{x:.234375,y:.265625},{x:.234375,y:.265625},{x:.265625,y:.265625},{x:.265625,y:.265625},{x:.296875,y:.265625},{x:.296875,y:.265625},{x:.328125,y:.265625},{x:.328125,y:.265625},{x:.359375,y:.265625},{x:.359375,y:.265625},{x:.390625,y:.265625},{x:.390625,y:.265625},{x:.421875,y:.265625},{x:.421875,y:.265625},{x:.453125,y:.265625},{x:.453125,y:.265625},{x:.484375,y:.265625},{x:.484375,y:.265625},{x:.515625,y:.265625},{x:.515625,y:.265625},{x:.546875,y:.265625},{x:.546875,y:.265625},{x:.578125,y:.265625},{x:.578125,y:.265625},{x:.609375,y:.265625},{x:.609375,y:.265625},{x:.640625,y:.265625},{x:.640625,y:.265625},{x:.671875,y:.265625},{x:.671875,y:.265625},{x:.703125,y:.265625},{x:.703125,y:.265625},{x:.734375,y:.265625},{x:.734375,y:.265625},{x:.765625,y:.265625},{x:.765625,y:.265625},{x:.796875,y:.265625},{x:.796875,y:.265625},{x:.828125,y:.265625},{x:.828125,y:.265625},{x:.859375,y:.265625},{x:.859375,y:.265625},{x:.890625,y:.265625},{x:.890625,y:.265625},{x:.921875,y:.265625},{x:.921875,y:.265625},{x:.953125,y:.265625},{x:.953125,y:.265625},{x:.984375,y:.265625},{x:.984375,y:.265625},{x:.015625,y:.296875},{x:.015625,y:.296875},{x:.046875,y:.296875},{x:.046875,y:.296875},{x:.078125,y:.296875},{x:.078125,y:.296875},{x:.109375,y:.296875},{x:.109375,y:.296875},{x:.140625,y:.296875},{x:.140625,y:.296875},{x:.171875,y:.296875},{x:.171875,y:.296875},{x:.203125,y:.296875},{x:.203125,y:.296875},{x:.234375,y:.296875},{x:.234375,y:.296875},{x:.265625,y:.296875},{x:.265625,y:.296875},{x:.296875,y:.296875},{x:.296875,y:.296875},{x:.328125,y:.296875},{x:.328125,y:.296875},{x:.359375,y:.296875},{x:.359375,y:.296875},{x:.390625,y:.296875},{x:.390625,y:.296875},{x:.421875,y:.296875},{x:.421875,y:.296875},{x:.453125,y:.296875},{x:.453125,y:.296875},{x:.484375,y:.296875},{x:.484375,y:.296875},{x:.515625,y:.296875},{x:.515625,y:.296875},{x:.546875,y:.296875},{x:.546875,y:.296875},{x:.578125,y:.296875},{x:.578125,y:.296875},{x:.609375,y:.296875},{x:.609375,y:.296875},{x:.640625,y:.296875},{x:.640625,y:.296875},{x:.671875,y:.296875},{x:.671875,y:.296875},{x:.703125,y:.296875},{x:.703125,y:.296875},{x:.734375,y:.296875},{x:.734375,y:.296875},{x:.765625,y:.296875},{x:.765625,y:.296875},{x:.796875,y:.296875},{x:.796875,y:.296875},{x:.828125,y:.296875},{x:.828125,y:.296875},{x:.859375,y:.296875},{x:.859375,y:.296875},{x:.890625,y:.296875},{x:.890625,y:.296875},{x:.921875,y:.296875},{x:.921875,y:.296875},{x:.953125,y:.296875},{x:.953125,y:.296875},{x:.984375,y:.296875},{x:.984375,y:.296875},{x:.015625,y:.328125},{x:.015625,y:.328125},{x:.046875,y:.328125},{x:.046875,y:.328125},{x:.078125,y:.328125},{x:.078125,y:.328125},{x:.109375,y:.328125},{x:.109375,y:.328125},{x:.140625,y:.328125},{x:.140625,y:.328125},{x:.171875,y:.328125},{x:.171875,y:.328125},{x:.203125,y:.328125},{x:.203125,y:.328125},{x:.234375,y:.328125},{x:.234375,y:.328125},{x:.265625,y:.328125},{x:.265625,y:.328125},{x:.296875,y:.328125},{x:.296875,y:.328125},{x:.328125,y:.328125},{x:.328125,y:.328125},{x:.359375,y:.328125},{x:.359375,y:.328125},{x:.390625,y:.328125},{x:.390625,y:.328125},{x:.421875,y:.328125},{x:.421875,y:.328125},{x:.453125,y:.328125},{x:.453125,y:.328125},{x:.484375,y:.328125},{x:.484375,y:.328125},{x:.515625,y:.328125},{x:.515625,y:.328125},{x:.546875,y:.328125},{x:.546875,y:.328125},{x:.578125,y:.328125},{x:.578125,y:.328125},{x:.609375,y:.328125},{x:.609375,y:.328125},{x:.640625,y:.328125},{x:.640625,y:.328125},{x:.671875,y:.328125},{x:.671875,y:.328125},{x:.703125,y:.328125},{x:.703125,y:.328125},{x:.734375,y:.328125},{x:.734375,y:.328125},{x:.765625,y:.328125},{x:.765625,y:.328125},{x:.796875,y:.328125},{x:.796875,y:.328125},{x:.828125,y:.328125},{x:.828125,y:.328125},{x:.859375,y:.328125},{x:.859375,y:.328125},{x:.890625,y:.328125},{x:.890625,y:.328125},{x:.921875,y:.328125},{x:.921875,y:.328125},{x:.953125,y:.328125},{x:.953125,y:.328125},{x:.984375,y:.328125},{x:.984375,y:.328125},{x:.015625,y:.359375},{x:.015625,y:.359375},{x:.046875,y:.359375},{x:.046875,y:.359375},{x:.078125,y:.359375},{x:.078125,y:.359375},{x:.109375,y:.359375},{x:.109375,y:.359375},{x:.140625,y:.359375},{x:.140625,y:.359375},{x:.171875,y:.359375},{x:.171875,y:.359375},{x:.203125,y:.359375},{x:.203125,y:.359375},{x:.234375,y:.359375},{x:.234375,y:.359375},{x:.265625,y:.359375},{x:.265625,y:.359375},{x:.296875,y:.359375},{x:.296875,y:.359375},{x:.328125,y:.359375},{x:.328125,y:.359375},{x:.359375,y:.359375},{x:.359375,y:.359375},{x:.390625,y:.359375},{x:.390625,y:.359375},{x:.421875,y:.359375},{x:.421875,y:.359375},{x:.453125,y:.359375},{x:.453125,y:.359375},{x:.484375,y:.359375},{x:.484375,y:.359375},{x:.515625,y:.359375},{x:.515625,y:.359375},{x:.546875,y:.359375},{x:.546875,y:.359375},{x:.578125,y:.359375},{x:.578125,y:.359375},{x:.609375,y:.359375},{x:.609375,y:.359375},{x:.640625,y:.359375},{x:.640625,y:.359375},{x:.671875,y:.359375},{x:.671875,y:.359375},{x:.703125,y:.359375},{x:.703125,y:.359375},{x:.734375,y:.359375},{x:.734375,y:.359375},{x:.765625,y:.359375},{x:.765625,y:.359375},{x:.796875,y:.359375},{x:.796875,y:.359375},{x:.828125,y:.359375},{x:.828125,y:.359375},{x:.859375,y:.359375},{x:.859375,y:.359375},{x:.890625,y:.359375},{x:.890625,y:.359375},{x:.921875,y:.359375},{x:.921875,y:.359375},{x:.953125,y:.359375},{x:.953125,y:.359375},{x:.984375,y:.359375},{x:.984375,y:.359375},{x:.015625,y:.390625},{x:.015625,y:.390625},{x:.046875,y:.390625},{x:.046875,y:.390625},{x:.078125,y:.390625},{x:.078125,y:.390625},{x:.109375,y:.390625},{x:.109375,y:.390625},{x:.140625,y:.390625},{x:.140625,y:.390625},{x:.171875,y:.390625},{x:.171875,y:.390625},{x:.203125,y:.390625},{x:.203125,y:.390625},{x:.234375,y:.390625},{x:.234375,y:.390625},{x:.265625,y:.390625},{x:.265625,y:.390625},{x:.296875,y:.390625},{x:.296875,y:.390625},{x:.328125,y:.390625},{x:.328125,y:.390625},{x:.359375,y:.390625},{x:.359375,y:.390625},{x:.390625,y:.390625},{x:.390625,y:.390625},{x:.421875,y:.390625},{x:.421875,y:.390625},{x:.453125,y:.390625},{x:.453125,y:.390625},{x:.484375,y:.390625},{x:.484375,y:.390625},{x:.515625,y:.390625},{x:.515625,y:.390625},{x:.546875,y:.390625},{x:.546875,y:.390625},{x:.578125,y:.390625},{x:.578125,y:.390625},{x:.609375,y:.390625},{x:.609375,y:.390625},{x:.640625,y:.390625},{x:.640625,y:.390625},{x:.671875,y:.390625},{x:.671875,y:.390625},{x:.703125,y:.390625},{x:.703125,y:.390625},{x:.734375,y:.390625},{x:.734375,y:.390625},{x:.765625,y:.390625},{x:.765625,y:.390625},{x:.796875,y:.390625},{x:.796875,y:.390625},{x:.828125,y:.390625},{x:.828125,y:.390625},{x:.859375,y:.390625},{x:.859375,y:.390625},{x:.890625,y:.390625},{x:.890625,y:.390625},{x:.921875,y:.390625},{x:.921875,y:.390625},{x:.953125,y:.390625},{x:.953125,y:.390625},{x:.984375,y:.390625},{x:.984375,y:.390625},{x:.015625,y:.421875},{x:.015625,y:.421875},{x:.046875,y:.421875},{x:.046875,y:.421875},{x:.078125,y:.421875},{x:.078125,y:.421875},{x:.109375,y:.421875},{x:.109375,y:.421875},{x:.140625,y:.421875},{x:.140625,y:.421875},{x:.171875,y:.421875},{x:.171875,y:.421875},{x:.203125,y:.421875},{x:.203125,y:.421875},{x:.234375,y:.421875},{x:.234375,y:.421875},{x:.265625,y:.421875},{x:.265625,y:.421875},{x:.296875,y:.421875},{x:.296875,y:.421875},{x:.328125,y:.421875},{x:.328125,y:.421875},{x:.359375,y:.421875},{x:.359375,y:.421875},{x:.390625,y:.421875},{x:.390625,y:.421875},{x:.421875,y:.421875},{x:.421875,y:.421875},{x:.453125,y:.421875},{x:.453125,y:.421875},{x:.484375,y:.421875},{x:.484375,y:.421875},{x:.515625,y:.421875},{x:.515625,y:.421875},{x:.546875,y:.421875},{x:.546875,y:.421875},{x:.578125,y:.421875},{x:.578125,y:.421875},{x:.609375,y:.421875},{x:.609375,y:.421875},{x:.640625,y:.421875},{x:.640625,y:.421875},{x:.671875,y:.421875},{x:.671875,y:.421875},{x:.703125,y:.421875},{x:.703125,y:.421875},{x:.734375,y:.421875},{x:.734375,y:.421875},{x:.765625,y:.421875},{x:.765625,y:.421875},{x:.796875,y:.421875},{x:.796875,y:.421875},{x:.828125,y:.421875},{x:.828125,y:.421875},{x:.859375,y:.421875},{x:.859375,y:.421875},{x:.890625,y:.421875},{x:.890625,y:.421875},{x:.921875,y:.421875},{x:.921875,y:.421875},{x:.953125,y:.421875},{x:.953125,y:.421875},{x:.984375,y:.421875},{x:.984375,y:.421875},{x:.015625,y:.453125},{x:.015625,y:.453125},{x:.046875,y:.453125},{x:.046875,y:.453125},{x:.078125,y:.453125},{x:.078125,y:.453125},{x:.109375,y:.453125},{x:.109375,y:.453125},{x:.140625,y:.453125},{x:.140625,y:.453125},{x:.171875,y:.453125},{x:.171875,y:.453125},{x:.203125,y:.453125},{x:.203125,y:.453125},{x:.234375,y:.453125},{x:.234375,y:.453125},{x:.265625,y:.453125},{x:.265625,y:.453125},{x:.296875,y:.453125},{x:.296875,y:.453125},{x:.328125,y:.453125},{x:.328125,y:.453125},{x:.359375,y:.453125},{x:.359375,y:.453125},{x:.390625,y:.453125},{x:.390625,y:.453125},{x:.421875,y:.453125},{x:.421875,y:.453125},{x:.453125,y:.453125},{x:.453125,y:.453125},{x:.484375,y:.453125},{x:.484375,y:.453125},{x:.515625,y:.453125},{x:.515625,y:.453125},{x:.546875,y:.453125},{x:.546875,y:.453125},{x:.578125,y:.453125},{x:.578125,y:.453125},{x:.609375,y:.453125},{x:.609375,y:.453125},{x:.640625,y:.453125},{x:.640625,y:.453125},{x:.671875,y:.453125},{x:.671875,y:.453125},{x:.703125,y:.453125},{x:.703125,y:.453125},{x:.734375,y:.453125},{x:.734375,y:.453125},{x:.765625,y:.453125},{x:.765625,y:.453125},{x:.796875,y:.453125},{x:.796875,y:.453125},{x:.828125,y:.453125},{x:.828125,y:.453125},{x:.859375,y:.453125},{x:.859375,y:.453125},{x:.890625,y:.453125},{x:.890625,y:.453125},{x:.921875,y:.453125},{x:.921875,y:.453125},{x:.953125,y:.453125},{x:.953125,y:.453125},{x:.984375,y:.453125},{x:.984375,y:.453125},{x:.015625,y:.484375},{x:.015625,y:.484375},{x:.046875,y:.484375},{x:.046875,y:.484375},{x:.078125,y:.484375},{x:.078125,y:.484375},{x:.109375,y:.484375},{x:.109375,y:.484375},{x:.140625,y:.484375},{x:.140625,y:.484375},{x:.171875,y:.484375},{x:.171875,y:.484375},{x:.203125,y:.484375},{x:.203125,y:.484375},{x:.234375,y:.484375},{x:.234375,y:.484375},{x:.265625,y:.484375},{x:.265625,y:.484375},{x:.296875,y:.484375},{x:.296875,y:.484375},{x:.328125,y:.484375},{x:.328125,y:.484375},{x:.359375,y:.484375},{x:.359375,y:.484375},{x:.390625,y:.484375},{x:.390625,y:.484375},{x:.421875,y:.484375},{x:.421875,y:.484375},{x:.453125,y:.484375},{x:.453125,y:.484375},{x:.484375,y:.484375},{x:.484375,y:.484375},{x:.515625,y:.484375},{x:.515625,y:.484375},{x:.546875,y:.484375},{x:.546875,y:.484375},{x:.578125,y:.484375},{x:.578125,y:.484375},{x:.609375,y:.484375},{x:.609375,y:.484375},{x:.640625,y:.484375},{x:.640625,y:.484375},{x:.671875,y:.484375},{x:.671875,y:.484375},{x:.703125,y:.484375},{x:.703125,y:.484375},{x:.734375,y:.484375},{x:.734375,y:.484375},{x:.765625,y:.484375},{x:.765625,y:.484375},{x:.796875,y:.484375},{x:.796875,y:.484375},{x:.828125,y:.484375},{x:.828125,y:.484375},{x:.859375,y:.484375},{x:.859375,y:.484375},{x:.890625,y:.484375},{x:.890625,y:.484375},{x:.921875,y:.484375},{x:.921875,y:.484375},{x:.953125,y:.484375},{x:.953125,y:.484375},{x:.984375,y:.484375},{x:.984375,y:.484375},{x:.015625,y:.515625},{x:.015625,y:.515625},{x:.046875,y:.515625},{x:.046875,y:.515625},{x:.078125,y:.515625},{x:.078125,y:.515625},{x:.109375,y:.515625},{x:.109375,y:.515625},{x:.140625,y:.515625},{x:.140625,y:.515625},{x:.171875,y:.515625},{x:.171875,y:.515625},{x:.203125,y:.515625},{x:.203125,y:.515625},{x:.234375,y:.515625},{x:.234375,y:.515625},{x:.265625,y:.515625},{x:.265625,y:.515625},{x:.296875,y:.515625},{x:.296875,y:.515625},{x:.328125,y:.515625},{x:.328125,y:.515625},{x:.359375,y:.515625},{x:.359375,y:.515625},{x:.390625,y:.515625},{x:.390625,y:.515625},{x:.421875,y:.515625},{x:.421875,y:.515625},{x:.453125,y:.515625},{x:.453125,y:.515625},{x:.484375,y:.515625},{x:.484375,y:.515625},{x:.515625,y:.515625},{x:.515625,y:.515625},{x:.546875,y:.515625},{x:.546875,y:.515625},{x:.578125,y:.515625},{x:.578125,y:.515625},{x:.609375,y:.515625},{x:.609375,y:.515625},{x:.640625,y:.515625},{x:.640625,y:.515625},{x:.671875,y:.515625},{x:.671875,y:.515625},{x:.703125,y:.515625},{x:.703125,y:.515625},{x:.734375,y:.515625},{x:.734375,y:.515625},{x:.765625,y:.515625},{x:.765625,y:.515625},{x:.796875,y:.515625},{x:.796875,y:.515625},{x:.828125,y:.515625},{x:.828125,y:.515625},{x:.859375,y:.515625},{x:.859375,y:.515625},{x:.890625,y:.515625},{x:.890625,y:.515625},{x:.921875,y:.515625},{x:.921875,y:.515625},{x:.953125,y:.515625},{x:.953125,y:.515625},{x:.984375,y:.515625},{x:.984375,y:.515625},{x:.015625,y:.546875},{x:.015625,y:.546875},{x:.046875,y:.546875},{x:.046875,y:.546875},{x:.078125,y:.546875},{x:.078125,y:.546875},{x:.109375,y:.546875},{x:.109375,y:.546875},{x:.140625,y:.546875},{x:.140625,y:.546875},{x:.171875,y:.546875},{x:.171875,y:.546875},{x:.203125,y:.546875},{x:.203125,y:.546875},{x:.234375,y:.546875},{x:.234375,y:.546875},{x:.265625,y:.546875},{x:.265625,y:.546875},{x:.296875,y:.546875},{x:.296875,y:.546875},{x:.328125,y:.546875},{x:.328125,y:.546875},{x:.359375,y:.546875},{x:.359375,y:.546875},{x:.390625,y:.546875},{x:.390625,y:.546875},{x:.421875,y:.546875},{x:.421875,y:.546875},{x:.453125,y:.546875},{x:.453125,y:.546875},{x:.484375,y:.546875},{x:.484375,y:.546875},{x:.515625,y:.546875},{x:.515625,y:.546875},{x:.546875,y:.546875},{x:.546875,y:.546875},{x:.578125,y:.546875},{x:.578125,y:.546875},{x:.609375,y:.546875},{x:.609375,y:.546875},{x:.640625,y:.546875},{x:.640625,y:.546875},{x:.671875,y:.546875},{x:.671875,y:.546875},{x:.703125,y:.546875},{x:.703125,y:.546875},{x:.734375,y:.546875},{x:.734375,y:.546875},{x:.765625,y:.546875},{x:.765625,y:.546875},{x:.796875,y:.546875},{x:.796875,y:.546875},{x:.828125,y:.546875},{x:.828125,y:.546875},{x:.859375,y:.546875},{x:.859375,y:.546875},{x:.890625,y:.546875},{x:.890625,y:.546875},{x:.921875,y:.546875},{x:.921875,y:.546875},{x:.953125,y:.546875},{x:.953125,y:.546875},{x:.984375,y:.546875},{x:.984375,y:.546875},{x:.015625,y:.578125},{x:.015625,y:.578125},{x:.046875,y:.578125},{x:.046875,y:.578125},{x:.078125,y:.578125},{x:.078125,y:.578125},{x:.109375,y:.578125},{x:.109375,y:.578125},{x:.140625,y:.578125},{x:.140625,y:.578125},{x:.171875,y:.578125},{x:.171875,y:.578125},{x:.203125,y:.578125},{x:.203125,y:.578125},{x:.234375,y:.578125},{x:.234375,y:.578125},{x:.265625,y:.578125},{x:.265625,y:.578125},{x:.296875,y:.578125},{x:.296875,y:.578125},{x:.328125,y:.578125},{x:.328125,y:.578125},{x:.359375,y:.578125},{x:.359375,y:.578125},{x:.390625,y:.578125},{x:.390625,y:.578125},{x:.421875,y:.578125},{x:.421875,y:.578125},{x:.453125,y:.578125},{x:.453125,y:.578125},{x:.484375,y:.578125},{x:.484375,y:.578125},{x:.515625,y:.578125},{x:.515625,y:.578125},{x:.546875,y:.578125},{x:.546875,y:.578125},{x:.578125,y:.578125},{x:.578125,y:.578125},{x:.609375,y:.578125},{x:.609375,y:.578125},{x:.640625,y:.578125},{x:.640625,y:.578125},{x:.671875,y:.578125},{x:.671875,y:.578125},{x:.703125,y:.578125},{x:.703125,y:.578125},{x:.734375,y:.578125},{x:.734375,y:.578125},{x:.765625,y:.578125},{x:.765625,y:.578125},{x:.796875,y:.578125},{x:.796875,y:.578125},{x:.828125,y:.578125},{x:.828125,y:.578125},{x:.859375,y:.578125},{x:.859375,y:.578125},{x:.890625,y:.578125},{x:.890625,y:.578125},{x:.921875,y:.578125},{x:.921875,y:.578125},{x:.953125,y:.578125},{x:.953125,y:.578125},{x:.984375,y:.578125},{x:.984375,y:.578125},{x:.015625,y:.609375},{x:.015625,y:.609375},{x:.046875,y:.609375},{x:.046875,y:.609375},{x:.078125,y:.609375},{x:.078125,y:.609375},{x:.109375,y:.609375},{x:.109375,y:.609375},{x:.140625,y:.609375},{x:.140625,y:.609375},{x:.171875,y:.609375},{x:.171875,y:.609375},{x:.203125,y:.609375},{x:.203125,y:.609375},{x:.234375,y:.609375},{x:.234375,y:.609375},{x:.265625,y:.609375},{x:.265625,y:.609375},{x:.296875,y:.609375},{x:.296875,y:.609375},{x:.328125,y:.609375},{x:.328125,y:.609375},{x:.359375,y:.609375},{x:.359375,y:.609375},{x:.390625,y:.609375},{x:.390625,y:.609375},{x:.421875,y:.609375},{x:.421875,y:.609375},{x:.453125,y:.609375},{x:.453125,y:.609375},{x:.484375,y:.609375},{x:.484375,y:.609375},{x:.515625,y:.609375},{x:.515625,y:.609375},{x:.546875,y:.609375},{x:.546875,y:.609375},{x:.578125,y:.609375},{x:.578125,y:.609375},{x:.609375,y:.609375},{x:.609375,y:.609375},{x:.640625,y:.609375},{x:.640625,y:.609375},{x:.671875,y:.609375},{x:.671875,y:.609375},{x:.703125,y:.609375},{x:.703125,y:.609375},{x:.734375,y:.609375},{x:.734375,y:.609375},{x:.765625,y:.609375},{x:.765625,y:.609375},{x:.796875,y:.609375},{x:.796875,y:.609375},{x:.828125,y:.609375},{x:.828125,y:.609375},{x:.859375,y:.609375},{x:.859375,y:.609375},{x:.890625,y:.609375},{x:.890625,y:.609375},{x:.921875,y:.609375},{x:.921875,y:.609375},{x:.953125,y:.609375},{x:.953125,y:.609375},{x:.984375,y:.609375},{x:.984375,y:.609375},{x:.015625,y:.640625},{x:.015625,y:.640625},{x:.046875,y:.640625},{x:.046875,y:.640625},{x:.078125,y:.640625},{x:.078125,y:.640625},{x:.109375,y:.640625},{x:.109375,y:.640625},{x:.140625,y:.640625},{x:.140625,y:.640625},{x:.171875,y:.640625},{x:.171875,y:.640625},{x:.203125,y:.640625},{x:.203125,y:.640625},{x:.234375,y:.640625},{x:.234375,y:.640625},{x:.265625,y:.640625},{x:.265625,y:.640625},{x:.296875,y:.640625},{x:.296875,y:.640625},{x:.328125,y:.640625},{x:.328125,y:.640625},{x:.359375,y:.640625},{x:.359375,y:.640625},{x:.390625,y:.640625},{x:.390625,y:.640625},{x:.421875,y:.640625},{x:.421875,y:.640625},{x:.453125,y:.640625},{x:.453125,y:.640625},{x:.484375,y:.640625},{x:.484375,y:.640625},{x:.515625,y:.640625},{x:.515625,y:.640625},{x:.546875,y:.640625},{x:.546875,y:.640625},{x:.578125,y:.640625},{x:.578125,y:.640625},{x:.609375,y:.640625},{x:.609375,y:.640625},{x:.640625,y:.640625},{x:.640625,y:.640625},{x:.671875,y:.640625},{x:.671875,y:.640625},{x:.703125,y:.640625},{x:.703125,y:.640625},{x:.734375,y:.640625},{x:.734375,y:.640625},{x:.765625,y:.640625},{x:.765625,y:.640625},{x:.796875,y:.640625},{x:.796875,y:.640625},{x:.828125,y:.640625},{x:.828125,y:.640625},{x:.859375,y:.640625},{x:.859375,y:.640625},{x:.890625,y:.640625},{x:.890625,y:.640625},{x:.921875,y:.640625},{x:.921875,y:.640625},{x:.953125,y:.640625},{x:.953125,y:.640625},{x:.984375,y:.640625},{x:.984375,y:.640625},{x:.015625,y:.671875},{x:.015625,y:.671875},{x:.046875,y:.671875},{x:.046875,y:.671875},{x:.078125,y:.671875},{x:.078125,y:.671875},{x:.109375,y:.671875},{x:.109375,y:.671875},{x:.140625,y:.671875},{x:.140625,y:.671875},{x:.171875,y:.671875},{x:.171875,y:.671875},{x:.203125,y:.671875},{x:.203125,y:.671875},{x:.234375,y:.671875},{x:.234375,y:.671875},{x:.265625,y:.671875},{x:.265625,y:.671875},{x:.296875,y:.671875},{x:.296875,y:.671875},{x:.328125,y:.671875},{x:.328125,y:.671875},{x:.359375,y:.671875},{x:.359375,y:.671875},{x:.390625,y:.671875},{x:.390625,y:.671875},{x:.421875,y:.671875},{x:.421875,y:.671875},{x:.453125,y:.671875},{x:.453125,y:.671875},{x:.484375,y:.671875},{x:.484375,y:.671875},{x:.515625,y:.671875},{x:.515625,y:.671875},{x:.546875,y:.671875},{x:.546875,y:.671875},{x:.578125,y:.671875},{x:.578125,y:.671875},{x:.609375,y:.671875},{x:.609375,y:.671875},{x:.640625,y:.671875},{x:.640625,y:.671875},{x:.671875,y:.671875},{x:.671875,y:.671875},{x:.703125,y:.671875},{x:.703125,y:.671875},{x:.734375,y:.671875},{x:.734375,y:.671875},{x:.765625,y:.671875},{x:.765625,y:.671875},{x:.796875,y:.671875},{x:.796875,y:.671875},{x:.828125,y:.671875},{x:.828125,y:.671875},{x:.859375,y:.671875},{x:.859375,y:.671875},{x:.890625,y:.671875},{x:.890625,y:.671875},{x:.921875,y:.671875},{x:.921875,y:.671875},{x:.953125,y:.671875},{x:.953125,y:.671875},{x:.984375,y:.671875},{x:.984375,y:.671875},{x:.015625,y:.703125},{x:.015625,y:.703125},{x:.046875,y:.703125},{x:.046875,y:.703125},{x:.078125,y:.703125},{x:.078125,y:.703125},{x:.109375,y:.703125},{x:.109375,y:.703125},{x:.140625,y:.703125},{x:.140625,y:.703125},{x:.171875,y:.703125},{x:.171875,y:.703125},{x:.203125,y:.703125},{x:.203125,y:.703125},{x:.234375,y:.703125},{x:.234375,y:.703125},{x:.265625,y:.703125},{x:.265625,y:.703125},{x:.296875,y:.703125},{x:.296875,y:.703125},{x:.328125,y:.703125},{x:.328125,y:.703125},{x:.359375,y:.703125},{x:.359375,y:.703125},{x:.390625,y:.703125},{x:.390625,y:.703125},{x:.421875,y:.703125},{x:.421875,y:.703125},{x:.453125,y:.703125},{x:.453125,y:.703125},{x:.484375,y:.703125},{x:.484375,y:.703125},{x:.515625,y:.703125},{x:.515625,y:.703125},{x:.546875,y:.703125},{x:.546875,y:.703125},{x:.578125,y:.703125},{x:.578125,y:.703125},{x:.609375,y:.703125},{x:.609375,y:.703125},{x:.640625,y:.703125},{x:.640625,y:.703125},{x:.671875,y:.703125},{x:.671875,y:.703125},{x:.703125,y:.703125},{x:.703125,y:.703125},{x:.734375,y:.703125},{x:.734375,y:.703125},{x:.765625,y:.703125},{x:.765625,y:.703125},{x:.796875,y:.703125},{x:.796875,y:.703125},{x:.828125,y:.703125},{x:.828125,y:.703125},{x:.859375,y:.703125},{x:.859375,y:.703125},{x:.890625,y:.703125},{x:.890625,y:.703125},{x:.921875,y:.703125},{x:.921875,y:.703125},{x:.953125,y:.703125},{x:.953125,y:.703125},{x:.984375,y:.703125},{x:.984375,y:.703125},{x:.015625,y:.734375},{x:.015625,y:.734375},{x:.046875,y:.734375},{x:.046875,y:.734375},{x:.078125,y:.734375},{x:.078125,y:.734375},{x:.109375,y:.734375},{x:.109375,y:.734375},{x:.140625,y:.734375},{x:.140625,y:.734375},{x:.171875,y:.734375},{x:.171875,y:.734375},{x:.203125,y:.734375},{x:.203125,y:.734375},{x:.234375,y:.734375},{x:.234375,y:.734375},{x:.265625,y:.734375},{x:.265625,y:.734375},{x:.296875,y:.734375},{x:.296875,y:.734375},{x:.328125,y:.734375},{x:.328125,y:.734375},{x:.359375,y:.734375},{x:.359375,y:.734375},{x:.390625,y:.734375},{x:.390625,y:.734375},{x:.421875,y:.734375},{x:.421875,y:.734375},{x:.453125,y:.734375},{x:.453125,y:.734375},{x:.484375,y:.734375},{x:.484375,y:.734375},{x:.515625,y:.734375},{x:.515625,y:.734375},{x:.546875,y:.734375},{x:.546875,y:.734375},{x:.578125,y:.734375},{x:.578125,y:.734375},{x:.609375,y:.734375},{x:.609375,y:.734375},{x:.640625,y:.734375},{x:.640625,y:.734375},{x:.671875,y:.734375},{x:.671875,y:.734375},{x:.703125,y:.734375},{x:.703125,y:.734375},{x:.734375,y:.734375},{x:.734375,y:.734375},{x:.765625,y:.734375},{x:.765625,y:.734375},{x:.796875,y:.734375},{x:.796875,y:.734375},{x:.828125,y:.734375},{x:.828125,y:.734375},{x:.859375,y:.734375},{x:.859375,y:.734375},{x:.890625,y:.734375},{x:.890625,y:.734375},{x:.921875,y:.734375},{x:.921875,y:.734375},{x:.953125,y:.734375},{x:.953125,y:.734375},{x:.984375,y:.734375},{x:.984375,y:.734375},{x:.015625,y:.765625},{x:.015625,y:.765625},{x:.046875,y:.765625},{x:.046875,y:.765625},{x:.078125,y:.765625},{x:.078125,y:.765625},{x:.109375,y:.765625},{x:.109375,y:.765625},{x:.140625,y:.765625},{x:.140625,y:.765625},{x:.171875,y:.765625},{x:.171875,y:.765625},{x:.203125,y:.765625},{x:.203125,y:.765625},{x:.234375,y:.765625},{x:.234375,y:.765625},{x:.265625,y:.765625},{x:.265625,y:.765625},{x:.296875,y:.765625},{x:.296875,y:.765625},{x:.328125,y:.765625},{x:.328125,y:.765625},{x:.359375,y:.765625},{x:.359375,y:.765625},{x:.390625,y:.765625},{x:.390625,y:.765625},{x:.421875,y:.765625},{x:.421875,y:.765625},{x:.453125,y:.765625},{x:.453125,y:.765625},{x:.484375,y:.765625},{x:.484375,y:.765625},{x:.515625,y:.765625},{x:.515625,y:.765625},{x:.546875,y:.765625},{x:.546875,y:.765625},{x:.578125,y:.765625},{x:.578125,y:.765625},{x:.609375,y:.765625},{x:.609375,y:.765625},{x:.640625,y:.765625},{x:.640625,y:.765625},{x:.671875,y:.765625},{x:.671875,y:.765625},{x:.703125,y:.765625},{x:.703125,y:.765625},{x:.734375,y:.765625},{x:.734375,y:.765625},{x:.765625,y:.765625},{x:.765625,y:.765625},{x:.796875,y:.765625},{x:.796875,y:.765625},{x:.828125,y:.765625},{x:.828125,y:.765625},{x:.859375,y:.765625},{x:.859375,y:.765625},{x:.890625,y:.765625},{x:.890625,y:.765625},{x:.921875,y:.765625},{x:.921875,y:.765625},{x:.953125,y:.765625},{x:.953125,y:.765625},{x:.984375,y:.765625},{x:.984375,y:.765625},{x:.015625,y:.796875},{x:.015625,y:.796875},{x:.046875,y:.796875},{x:.046875,y:.796875},{x:.078125,y:.796875},{x:.078125,y:.796875},{x:.109375,y:.796875},{x:.109375,y:.796875},{x:.140625,y:.796875},{x:.140625,y:.796875},{x:.171875,y:.796875},{x:.171875,y:.796875},{x:.203125,y:.796875},{x:.203125,y:.796875},{x:.234375,y:.796875},{x:.234375,y:.796875},{x:.265625,y:.796875},{x:.265625,y:.796875},{x:.296875,y:.796875},{x:.296875,y:.796875},{x:.328125,y:.796875},{x:.328125,y:.796875},{x:.359375,y:.796875},{x:.359375,y:.796875},{x:.390625,y:.796875},{x:.390625,y:.796875},{x:.421875,y:.796875},{x:.421875,y:.796875},{x:.453125,y:.796875},{x:.453125,y:.796875},{x:.484375,y:.796875},{x:.484375,y:.796875},{x:.515625,y:.796875},{x:.515625,y:.796875},{x:.546875,y:.796875},{x:.546875,y:.796875},{x:.578125,y:.796875},{x:.578125,y:.796875},{x:.609375,y:.796875},{x:.609375,y:.796875},{x:.640625,y:.796875},{x:.640625,y:.796875},{x:.671875,y:.796875},{x:.671875,y:.796875},{x:.703125,y:.796875},{x:.703125,y:.796875},{x:.734375,y:.796875},{x:.734375,y:.796875},{x:.765625,y:.796875},{x:.765625,y:.796875},{x:.796875,y:.796875},{x:.796875,y:.796875},{x:.828125,y:.796875},{x:.828125,y:.796875},{x:.859375,y:.796875},{x:.859375,y:.796875},{x:.890625,y:.796875},{x:.890625,y:.796875},{x:.921875,y:.796875},{x:.921875,y:.796875},{x:.953125,y:.796875},{x:.953125,y:.796875},{x:.984375,y:.796875},{x:.984375,y:.796875},{x:.015625,y:.828125},{x:.015625,y:.828125},{x:.046875,y:.828125},{x:.046875,y:.828125},{x:.078125,y:.828125},{x:.078125,y:.828125},{x:.109375,y:.828125},{x:.109375,y:.828125},{x:.140625,y:.828125},{x:.140625,y:.828125},{x:.171875,y:.828125},{x:.171875,y:.828125},{x:.203125,y:.828125},{x:.203125,y:.828125},{x:.234375,y:.828125},{x:.234375,y:.828125},{x:.265625,y:.828125},{x:.265625,y:.828125},{x:.296875,y:.828125},{x:.296875,y:.828125},{x:.328125,y:.828125},{x:.328125,y:.828125},{x:.359375,y:.828125},{x:.359375,y:.828125},{x:.390625,y:.828125},{x:.390625,y:.828125},{x:.421875,y:.828125},{x:.421875,y:.828125},{x:.453125,y:.828125},{x:.453125,y:.828125},{x:.484375,y:.828125},{x:.484375,y:.828125},{x:.515625,y:.828125},{x:.515625,y:.828125},{x:.546875,y:.828125},{x:.546875,y:.828125},{x:.578125,y:.828125},{x:.578125,y:.828125},{x:.609375,y:.828125},{x:.609375,y:.828125},{x:.640625,y:.828125},{x:.640625,y:.828125},{x:.671875,y:.828125},{x:.671875,y:.828125},{x:.703125,y:.828125},{x:.703125,y:.828125},{x:.734375,y:.828125},{x:.734375,y:.828125},{x:.765625,y:.828125},{x:.765625,y:.828125},{x:.796875,y:.828125},{x:.796875,y:.828125},{x:.828125,y:.828125},{x:.828125,y:.828125},{x:.859375,y:.828125},{x:.859375,y:.828125},{x:.890625,y:.828125},{x:.890625,y:.828125},{x:.921875,y:.828125},{x:.921875,y:.828125},{x:.953125,y:.828125},{x:.953125,y:.828125},{x:.984375,y:.828125},{x:.984375,y:.828125},{x:.015625,y:.859375},{x:.015625,y:.859375},{x:.046875,y:.859375},{x:.046875,y:.859375},{x:.078125,y:.859375},{x:.078125,y:.859375},{x:.109375,y:.859375},{x:.109375,y:.859375},{x:.140625,y:.859375},{x:.140625,y:.859375},{x:.171875,y:.859375},{x:.171875,y:.859375},{x:.203125,y:.859375},{x:.203125,y:.859375},{x:.234375,y:.859375},{x:.234375,y:.859375},{x:.265625,y:.859375},{x:.265625,y:.859375},{x:.296875,y:.859375},{x:.296875,y:.859375},{x:.328125,y:.859375},{x:.328125,y:.859375},{x:.359375,y:.859375},{x:.359375,y:.859375},{x:.390625,y:.859375},{x:.390625,y:.859375},{x:.421875,y:.859375},{x:.421875,y:.859375},{x:.453125,y:.859375},{x:.453125,y:.859375},{x:.484375,y:.859375},{x:.484375,y:.859375},{x:.515625,y:.859375},{x:.515625,y:.859375},{x:.546875,y:.859375},{x:.546875,y:.859375},{x:.578125,y:.859375},{x:.578125,y:.859375},{x:.609375,y:.859375},{x:.609375,y:.859375},{x:.640625,y:.859375},{x:.640625,y:.859375},{x:.671875,y:.859375},{x:.671875,y:.859375},{x:.703125,y:.859375},{x:.703125,y:.859375},{x:.734375,y:.859375},{x:.734375,y:.859375},{x:.765625,y:.859375},{x:.765625,y:.859375},{x:.796875,y:.859375},{x:.796875,y:.859375},{x:.828125,y:.859375},{x:.828125,y:.859375},{x:.859375,y:.859375},{x:.859375,y:.859375},{x:.890625,y:.859375},{x:.890625,y:.859375},{x:.921875,y:.859375},{x:.921875,y:.859375},{x:.953125,y:.859375},{x:.953125,y:.859375},{x:.984375,y:.859375},{x:.984375,y:.859375},{x:.015625,y:.890625},{x:.015625,y:.890625},{x:.046875,y:.890625},{x:.046875,y:.890625},{x:.078125,y:.890625},{x:.078125,y:.890625},{x:.109375,y:.890625},{x:.109375,y:.890625},{x:.140625,y:.890625},{x:.140625,y:.890625},{x:.171875,y:.890625},{x:.171875,y:.890625},{x:.203125,y:.890625},{x:.203125,y:.890625},{x:.234375,y:.890625},{x:.234375,y:.890625},{x:.265625,y:.890625},{x:.265625,y:.890625},{x:.296875,y:.890625},{x:.296875,y:.890625},{x:.328125,y:.890625},{x:.328125,y:.890625},{x:.359375,y:.890625},{x:.359375,y:.890625},{x:.390625,y:.890625},{x:.390625,y:.890625},{x:.421875,y:.890625},{x:.421875,y:.890625},{x:.453125,y:.890625},{x:.453125,y:.890625},{x:.484375,y:.890625},{x:.484375,y:.890625},{x:.515625,y:.890625},{x:.515625,y:.890625},{x:.546875,y:.890625},{x:.546875,y:.890625},{x:.578125,y:.890625},{x:.578125,y:.890625},{x:.609375,y:.890625},{x:.609375,y:.890625},{x:.640625,y:.890625},{x:.640625,y:.890625},{x:.671875,y:.890625},{x:.671875,y:.890625},{x:.703125,y:.890625},{x:.703125,y:.890625},{x:.734375,y:.890625},{x:.734375,y:.890625},{x:.765625,y:.890625},{x:.765625,y:.890625},{x:.796875,y:.890625},{x:.796875,y:.890625},{x:.828125,y:.890625},{x:.828125,y:.890625},{x:.859375,y:.890625},{x:.859375,y:.890625},{x:.890625,y:.890625},{x:.890625,y:.890625},{x:.921875,y:.890625},{x:.921875,y:.890625},{x:.953125,y:.890625},{x:.953125,y:.890625},{x:.984375,y:.890625},{x:.984375,y:.890625},{x:.015625,y:.921875},{x:.015625,y:.921875},{x:.046875,y:.921875},{x:.046875,y:.921875},{x:.078125,y:.921875},{x:.078125,y:.921875},{x:.109375,y:.921875},{x:.109375,y:.921875},{x:.140625,y:.921875},{x:.140625,y:.921875},{x:.171875,y:.921875},{x:.171875,y:.921875},{x:.203125,y:.921875},{x:.203125,y:.921875},{x:.234375,y:.921875},{x:.234375,y:.921875},{x:.265625,y:.921875},{x:.265625,y:.921875},{x:.296875,y:.921875},{x:.296875,y:.921875},{x:.328125,y:.921875},{x:.328125,y:.921875},{x:.359375,y:.921875},{x:.359375,y:.921875},{x:.390625,y:.921875},{x:.390625,y:.921875},{x:.421875,y:.921875},{x:.421875,y:.921875},{x:.453125,y:.921875},{x:.453125,y:.921875},{x:.484375,y:.921875},{x:.484375,y:.921875},{x:.515625,y:.921875},{x:.515625,y:.921875},{x:.546875,y:.921875},{x:.546875,y:.921875},{x:.578125,y:.921875},{x:.578125,y:.921875},{x:.609375,y:.921875},{x:.609375,y:.921875},{x:.640625,y:.921875},{x:.640625,y:.921875},{x:.671875,y:.921875},{x:.671875,y:.921875},{x:.703125,y:.921875},{x:.703125,y:.921875},{x:.734375,y:.921875},{x:.734375,y:.921875},{x:.765625,y:.921875},{x:.765625,y:.921875},{x:.796875,y:.921875},{x:.796875,y:.921875},{x:.828125,y:.921875},{x:.828125,y:.921875},{x:.859375,y:.921875},{x:.859375,y:.921875},{x:.890625,y:.921875},{x:.890625,y:.921875},{x:.921875,y:.921875},{x:.921875,y:.921875},{x:.953125,y:.921875},{x:.953125,y:.921875},{x:.984375,y:.921875},{x:.984375,y:.921875},{x:.015625,y:.953125},{x:.015625,y:.953125},{x:.046875,y:.953125},{x:.046875,y:.953125},{x:.078125,y:.953125},{x:.078125,y:.953125},{x:.109375,y:.953125},{x:.109375,y:.953125},{x:.140625,y:.953125},{x:.140625,y:.953125},{x:.171875,y:.953125},{x:.171875,y:.953125},{x:.203125,y:.953125},{x:.203125,y:.953125},{x:.234375,y:.953125},{x:.234375,y:.953125},{x:.265625,y:.953125},{x:.265625,y:.953125},{x:.296875,y:.953125},{x:.296875,y:.953125},{x:.328125,y:.953125},{x:.328125,y:.953125},{x:.359375,y:.953125},{x:.359375,y:.953125},{x:.390625,y:.953125},{x:.390625,y:.953125},{x:.421875,y:.953125},{x:.421875,y:.953125},{x:.453125,y:.953125},{x:.453125,y:.953125},{x:.484375,y:.953125},{x:.484375,y:.953125},{x:.515625,y:.953125},{x:.515625,y:.953125},{x:.546875,y:.953125},{x:.546875,y:.953125},{x:.578125,y:.953125},{x:.578125,y:.953125},{x:.609375,y:.953125},{x:.609375,y:.953125},{x:.640625,y:.953125},{x:.640625,y:.953125},{x:.671875,y:.953125},{x:.671875,y:.953125},{x:.703125,y:.953125},{x:.703125,y:.953125},{x:.734375,y:.953125},{x:.734375,y:.953125},{x:.765625,y:.953125},{x:.765625,y:.953125},{x:.796875,y:.953125},{x:.796875,y:.953125},{x:.828125,y:.953125},{x:.828125,y:.953125},{x:.859375,y:.953125},{x:.859375,y:.953125},{x:.890625,y:.953125},{x:.890625,y:.953125},{x:.921875,y:.953125},{x:.921875,y:.953125},{x:.953125,y:.953125},{x:.953125,y:.953125},{x:.984375,y:.953125},{x:.984375,y:.953125},{x:.015625,y:.984375},{x:.015625,y:.984375},{x:.046875,y:.984375},{x:.046875,y:.984375},{x:.078125,y:.984375},{x:.078125,y:.984375},{x:.109375,y:.984375},{x:.109375,y:.984375},{x:.140625,y:.984375},{x:.140625,y:.984375},{x:.171875,y:.984375},{x:.171875,y:.984375},{x:.203125,y:.984375},{x:.203125,y:.984375},{x:.234375,y:.984375},{x:.234375,y:.984375},{x:.265625,y:.984375},{x:.265625,y:.984375},{x:.296875,y:.984375},{x:.296875,y:.984375},{x:.328125,y:.984375},{x:.328125,y:.984375},{x:.359375,y:.984375},{x:.359375,y:.984375},{x:.390625,y:.984375},{x:.390625,y:.984375},{x:.421875,y:.984375},{x:.421875,y:.984375},{x:.453125,y:.984375},{x:.453125,y:.984375},{x:.484375,y:.984375},{x:.484375,y:.984375},{x:.515625,y:.984375},{x:.515625,y:.984375},{x:.546875,y:.984375},{x:.546875,y:.984375},{x:.578125,y:.984375},{x:.578125,y:.984375},{x:.609375,y:.984375},{x:.609375,y:.984375},{x:.640625,y:.984375},{x:.640625,y:.984375},{x:.671875,y:.984375},{x:.671875,y:.984375},{x:.703125,y:.984375},{x:.703125,y:.984375},{x:.734375,y:.984375},{x:.734375,y:.984375},{x:.765625,y:.984375},{x:.765625,y:.984375},{x:.796875,y:.984375},{x:.796875,y:.984375},{x:.828125,y:.984375},{x:.828125,y:.984375},{x:.859375,y:.984375},{x:.859375,y:.984375},{x:.890625,y:.984375},{x:.890625,y:.984375},{x:.921875,y:.984375},{x:.921875,y:.984375},{x:.953125,y:.984375},{x:.953125,y:.984375},{x:.984375,y:.984375},{x:.984375,y:.984375},{x:.03125,y:.03125},{x:.03125,y:.03125},{x:.09375,y:.03125},{x:.09375,y:.03125},{x:.15625,y:.03125},{x:.15625,y:.03125},{x:.21875,y:.03125},{x:.21875,y:.03125},{x:.28125,y:.03125},{x:.28125,y:.03125},{x:.34375,y:.03125},{x:.34375,y:.03125},{x:.40625,y:.03125},{x:.40625,y:.03125},{x:.46875,y:.03125},{x:.46875,y:.03125},{x:.53125,y:.03125},{x:.53125,y:.03125},{x:.59375,y:.03125},{x:.59375,y:.03125},{x:.65625,y:.03125},{x:.65625,y:.03125},{x:.71875,y:.03125},{x:.71875,y:.03125},{x:.78125,y:.03125},{x:.78125,y:.03125},{x:.84375,y:.03125},{x:.84375,y:.03125},{x:.90625,y:.03125},{x:.90625,y:.03125},{x:.96875,y:.03125},{x:.96875,y:.03125},{x:.03125,y:.09375},{x:.03125,y:.09375},{x:.09375,y:.09375},{x:.09375,y:.09375},{x:.15625,y:.09375},{x:.15625,y:.09375},{x:.21875,y:.09375},{x:.21875,y:.09375},{x:.28125,y:.09375},{x:.28125,y:.09375},{x:.34375,y:.09375},{x:.34375,y:.09375},{x:.40625,y:.09375},{x:.40625,y:.09375},{x:.46875,y:.09375},{x:.46875,y:.09375},{x:.53125,y:.09375},{x:.53125,y:.09375},{x:.59375,y:.09375},{x:.59375,y:.09375},{x:.65625,y:.09375},{x:.65625,y:.09375},{x:.71875,y:.09375},{x:.71875,y:.09375},{x:.78125,y:.09375},{x:.78125,y:.09375},{x:.84375,y:.09375},{x:.84375,y:.09375},{x:.90625,y:.09375},{x:.90625,y:.09375},{x:.96875,y:.09375},{x:.96875,y:.09375},{x:.03125,y:.15625},{x:.03125,y:.15625},{x:.09375,y:.15625},{x:.09375,y:.15625},{x:.15625,y:.15625},{x:.15625,y:.15625},{x:.21875,y:.15625},{x:.21875,y:.15625},{x:.28125,y:.15625},{x:.28125,y:.15625},{x:.34375,y:.15625},{x:.34375,y:.15625},{x:.40625,y:.15625},{x:.40625,y:.15625},{x:.46875,y:.15625},{x:.46875,y:.15625},{x:.53125,y:.15625},{x:.53125,y:.15625},{x:.59375,y:.15625},{x:.59375,y:.15625},{x:.65625,y:.15625},{x:.65625,y:.15625},{x:.71875,y:.15625},{x:.71875,y:.15625},{x:.78125,y:.15625},{x:.78125,y:.15625},{x:.84375,y:.15625},{x:.84375,y:.15625},{x:.90625,y:.15625},{x:.90625,y:.15625},{x:.96875,y:.15625},{x:.96875,y:.15625},{x:.03125,y:.21875},{x:.03125,y:.21875},{x:.09375,y:.21875},{x:.09375,y:.21875},{x:.15625,y:.21875},{x:.15625,y:.21875},{x:.21875,y:.21875},{x:.21875,y:.21875},{x:.28125,y:.21875},{x:.28125,y:.21875},{x:.34375,y:.21875},{x:.34375,y:.21875},{x:.40625,y:.21875},{x:.40625,y:.21875},{x:.46875,y:.21875},{x:.46875,y:.21875},{x:.53125,y:.21875},{x:.53125,y:.21875},{x:.59375,y:.21875},{x:.59375,y:.21875},{x:.65625,y:.21875},{x:.65625,y:.21875},{x:.71875,y:.21875},{x:.71875,y:.21875},{x:.78125,y:.21875},{x:.78125,y:.21875},{x:.84375,y:.21875},{x:.84375,y:.21875},{x:.90625,y:.21875},{x:.90625,y:.21875},{x:.96875,y:.21875},{x:.96875,y:.21875},{x:.03125,y:.28125},{x:.03125,y:.28125},{x:.09375,y:.28125},{x:.09375,y:.28125},{x:.15625,y:.28125},{x:.15625,y:.28125},{x:.21875,y:.28125},{x:.21875,y:.28125},{x:.28125,y:.28125},{x:.28125,y:.28125},{x:.34375,y:.28125},{x:.34375,y:.28125},{x:.40625,y:.28125},{x:.40625,y:.28125},{x:.46875,y:.28125},{x:.46875,y:.28125},{x:.53125,y:.28125},{x:.53125,y:.28125},{x:.59375,y:.28125},{x:.59375,y:.28125},{x:.65625,y:.28125},{x:.65625,y:.28125},{x:.71875,y:.28125},{x:.71875,y:.28125},{x:.78125,y:.28125},{x:.78125,y:.28125},{x:.84375,y:.28125},{x:.84375,y:.28125},{x:.90625,y:.28125},{x:.90625,y:.28125},{x:.96875,y:.28125},{x:.96875,y:.28125},{x:.03125,y:.34375},{x:.03125,y:.34375},{x:.09375,y:.34375},{x:.09375,y:.34375},{x:.15625,y:.34375},{x:.15625,y:.34375},{x:.21875,y:.34375},{x:.21875,y:.34375},{x:.28125,y:.34375},{x:.28125,y:.34375},{x:.34375,y:.34375},{x:.34375,y:.34375},{x:.40625,y:.34375},{x:.40625,y:.34375},{x:.46875,y:.34375},{x:.46875,y:.34375},{x:.53125,y:.34375},{x:.53125,y:.34375},{x:.59375,y:.34375},{x:.59375,y:.34375},{x:.65625,y:.34375},{x:.65625,y:.34375},{x:.71875,y:.34375},{x:.71875,y:.34375},{x:.78125,y:.34375},{x:.78125,y:.34375},{x:.84375,y:.34375},{x:.84375,y:.34375},{x:.90625,y:.34375},{x:.90625,y:.34375},{x:.96875,y:.34375},{x:.96875,y:.34375},{x:.03125,y:.40625},{x:.03125,y:.40625},{x:.09375,y:.40625},{x:.09375,y:.40625},{x:.15625,y:.40625},{x:.15625,y:.40625},{x:.21875,y:.40625},{x:.21875,y:.40625},{x:.28125,y:.40625},{x:.28125,y:.40625},{x:.34375,y:.40625},{x:.34375,y:.40625},{x:.40625,y:.40625},{x:.40625,y:.40625},{x:.46875,y:.40625},{x:.46875,y:.40625},{x:.53125,y:.40625},{x:.53125,y:.40625},{x:.59375,y:.40625},{x:.59375,y:.40625},{x:.65625,y:.40625},{x:.65625,y:.40625},{x:.71875,y:.40625},{x:.71875,y:.40625},{x:.78125,y:.40625},{x:.78125,y:.40625},{x:.84375,y:.40625},{x:.84375,y:.40625},{x:.90625,y:.40625},{x:.90625,y:.40625},{x:.96875,y:.40625},{x:.96875,y:.40625},{x:.03125,y:.46875},{x:.03125,y:.46875},{x:.09375,y:.46875},{x:.09375,y:.46875},{x:.15625,y:.46875},{x:.15625,y:.46875},{x:.21875,y:.46875},{x:.21875,y:.46875},{x:.28125,y:.46875},{x:.28125,y:.46875},{x:.34375,y:.46875},{x:.34375,y:.46875},{x:.40625,y:.46875},{x:.40625,y:.46875},{x:.46875,y:.46875},{x:.46875,y:.46875},{x:.53125,y:.46875},{x:.53125,y:.46875},{x:.59375,y:.46875},{x:.59375,y:.46875},{x:.65625,y:.46875},{x:.65625,y:.46875},{x:.71875,y:.46875},{x:.71875,y:.46875},{x:.78125,y:.46875},{x:.78125,y:.46875},{x:.84375,y:.46875},{x:.84375,y:.46875},{x:.90625,y:.46875},{x:.90625,y:.46875},{x:.96875,y:.46875},{x:.96875,y:.46875},{x:.03125,y:.53125},{x:.03125,y:.53125},{x:.09375,y:.53125},{x:.09375,y:.53125},{x:.15625,y:.53125},{x:.15625,y:.53125},{x:.21875,y:.53125},{x:.21875,y:.53125},{x:.28125,y:.53125},{x:.28125,y:.53125},{x:.34375,y:.53125},{x:.34375,y:.53125},{x:.40625,y:.53125},{x:.40625,y:.53125},{x:.46875,y:.53125},{x:.46875,y:.53125},{x:.53125,y:.53125},{x:.53125,y:.53125},{x:.59375,y:.53125},{x:.59375,y:.53125},{x:.65625,y:.53125},{x:.65625,y:.53125},{x:.71875,y:.53125},{x:.71875,y:.53125},{x:.78125,y:.53125},{x:.78125,y:.53125},{x:.84375,y:.53125},{x:.84375,y:.53125},{x:.90625,y:.53125},{x:.90625,y:.53125},{x:.96875,y:.53125},{x:.96875,y:.53125},{x:.03125,y:.59375},{x:.03125,y:.59375},{x:.09375,y:.59375},{x:.09375,y:.59375},{x:.15625,y:.59375},{x:.15625,y:.59375},{x:.21875,y:.59375},{x:.21875,y:.59375},{x:.28125,y:.59375},{x:.28125,y:.59375},{x:.34375,y:.59375},{x:.34375,y:.59375},{x:.40625,y:.59375},{x:.40625,y:.59375},{x:.46875,y:.59375},{x:.46875,y:.59375},{x:.53125,y:.59375},{x:.53125,y:.59375},{x:.59375,y:.59375},{x:.59375,y:.59375},{x:.65625,y:.59375},{x:.65625,y:.59375},{x:.71875,y:.59375},{x:.71875,y:.59375},{x:.78125,y:.59375},{x:.78125,y:.59375},{x:.84375,y:.59375},{x:.84375,y:.59375},{x:.90625,y:.59375},{x:.90625,y:.59375},{x:.96875,y:.59375},{x:.96875,y:.59375},{x:.03125,y:.65625},{x:.03125,y:.65625},{x:.09375,y:.65625},{x:.09375,y:.65625},{x:.15625,y:.65625},{x:.15625,y:.65625},{x:.21875,y:.65625},{x:.21875,y:.65625},{x:.28125,y:.65625},{x:.28125,y:.65625},{x:.34375,y:.65625},{x:.34375,y:.65625},{x:.40625,y:.65625},{x:.40625,y:.65625},{x:.46875,y:.65625},{x:.46875,y:.65625},{x:.53125,y:.65625},{x:.53125,y:.65625},{x:.59375,y:.65625},{x:.59375,y:.65625},{x:.65625,y:.65625},{x:.65625,y:.65625},{x:.71875,y:.65625},{x:.71875,y:.65625},{x:.78125,y:.65625},{x:.78125,y:.65625},{x:.84375,y:.65625},{x:.84375,y:.65625},{x:.90625,y:.65625},{x:.90625,y:.65625},{x:.96875,y:.65625},{x:.96875,y:.65625},{x:.03125,y:.71875},{x:.03125,y:.71875},{x:.09375,y:.71875},{x:.09375,y:.71875},{x:.15625,y:.71875},{x:.15625,y:.71875},{x:.21875,y:.71875},{x:.21875,y:.71875},{x:.28125,y:.71875},{x:.28125,y:.71875},{x:.34375,y:.71875},{x:.34375,y:.71875},{x:.40625,y:.71875},{x:.40625,y:.71875},{x:.46875,y:.71875},{x:.46875,y:.71875},{x:.53125,y:.71875},{x:.53125,y:.71875},{x:.59375,y:.71875},{x:.59375,y:.71875},{x:.65625,y:.71875},{x:.65625,y:.71875},{x:.71875,y:.71875},{x:.71875,y:.71875},{x:.78125,y:.71875},{x:.78125,y:.71875},{x:.84375,y:.71875},{x:.84375,y:.71875},{x:.90625,y:.71875},{x:.90625,y:.71875},{x:.96875,y:.71875},{x:.96875,y:.71875},{x:.03125,y:.78125},{x:.03125,y:.78125},{x:.09375,y:.78125},{x:.09375,y:.78125},{x:.15625,y:.78125},{x:.15625,y:.78125},{x:.21875,y:.78125},{x:.21875,y:.78125},{x:.28125,y:.78125},{x:.28125,y:.78125},{x:.34375,y:.78125},{x:.34375,y:.78125},{x:.40625,y:.78125},{x:.40625,y:.78125},{x:.46875,y:.78125},{x:.46875,y:.78125},{x:.53125,y:.78125},{x:.53125,y:.78125},{x:.59375,y:.78125},{x:.59375,y:.78125},{x:.65625,y:.78125},{x:.65625,y:.78125},{x:.71875,y:.78125},{x:.71875,y:.78125},{x:.78125,y:.78125},{x:.78125,y:.78125},{x:.84375,y:.78125},{x:.84375,y:.78125},{x:.90625,y:.78125},{x:.90625,y:.78125},{x:.96875,y:.78125},{x:.96875,y:.78125},{x:.03125,y:.84375},{x:.03125,y:.84375},{x:.09375,y:.84375},{x:.09375,y:.84375},{x:.15625,y:.84375},{x:.15625,y:.84375},{x:.21875,y:.84375},{x:.21875,y:.84375},{x:.28125,y:.84375},{x:.28125,y:.84375},{x:.34375,y:.84375},{x:.34375,y:.84375},{x:.40625,y:.84375},{x:.40625,y:.84375},{x:.46875,y:.84375},{x:.46875,y:.84375},{x:.53125,y:.84375},{x:.53125,y:.84375},{x:.59375,y:.84375},{x:.59375,y:.84375},{x:.65625,y:.84375},{x:.65625,y:.84375},{x:.71875,y:.84375},{x:.71875,y:.84375},{x:.78125,y:.84375},{x:.78125,y:.84375},{x:.84375,y:.84375},{x:.84375,y:.84375},{x:.90625,y:.84375},{x:.90625,y:.84375},{x:.96875,y:.84375},{x:.96875,y:.84375},{x:.03125,y:.90625},{x:.03125,y:.90625},{x:.09375,y:.90625},{x:.09375,y:.90625},{x:.15625,y:.90625},{x:.15625,y:.90625},{x:.21875,y:.90625},{x:.21875,y:.90625},{x:.28125,y:.90625},{x:.28125,y:.90625},{x:.34375,y:.90625},{x:.34375,y:.90625},{x:.40625,y:.90625},{x:.40625,y:.90625},{x:.46875,y:.90625},{x:.46875,y:.90625},{x:.53125,y:.90625},{x:.53125,y:.90625},{x:.59375,y:.90625},{x:.59375,y:.90625},{x:.65625,y:.90625},{x:.65625,y:.90625},{x:.71875,y:.90625},{x:.71875,y:.90625},{x:.78125,y:.90625},{x:.78125,y:.90625},{x:.84375,y:.90625},{x:.84375,y:.90625},{x:.90625,y:.90625},{x:.90625,y:.90625},{x:.96875,y:.90625},{x:.96875,y:.90625},{x:.03125,y:.96875},{x:.03125,y:.96875},{x:.09375,y:.96875},{x:.09375,y:.96875},{x:.15625,y:.96875},{x:.15625,y:.96875},{x:.21875,y:.96875},{x:.21875,y:.96875},{x:.28125,y:.96875},{x:.28125,y:.96875},{x:.34375,y:.96875},{x:.34375,y:.96875},{x:.40625,y:.96875},{x:.40625,y:.96875},{x:.46875,y:.96875},{x:.46875,y:.96875},{x:.53125,y:.96875},{x:.53125,y:.96875},{x:.59375,y:.96875},{x:.59375,y:.96875},{x:.65625,y:.96875},{x:.65625,y:.96875},{x:.71875,y:.96875},{x:.71875,y:.96875},{x:.78125,y:.96875},{x:.78125,y:.96875},{x:.84375,y:.96875},{x:.84375,y:.96875},{x:.90625,y:.96875},{x:.90625,y:.96875},{x:.96875,y:.96875},{x:.96875,y:.96875},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375}];var a5=class{constructor(t){T(this,"model");T(this,"anchors");T(this,"anchorsTensor");T(this,"inputSize");T(this,"inputSizeTensor");T(this,"doubleInputSizeTensor");this.model=t,this.anchors=$3.map(o=>[o.x,o.y]),this.anchorsTensor=W.tensor2d(this.anchors),this.inputSize=this.model&&this.model.inputs&&this.model.inputs[0].shape?this.model.inputs[0].shape[2]:0,this.inputSizeTensor=W.tensor1d([this.inputSize,this.inputSize]),this.doubleInputSizeTensor=W.tensor1d([this.inputSize*2,this.inputSize*2])}normalizeBoxes(t){let o={};o.boxOffsets=W.slice(t,[0,0],[-1,2]),o.boxSizes=W.slice(t,[0,2],[-1,2]),o.div=W.div(o.boxOffsets,this.inputSizeTensor),o.boxCenterPoints=W.add(o.div,this.anchorsTensor),o.halfBoxSizes=W.div(o.boxSizes,this.doubleInputSizeTensor),o.sub=W.sub(o.boxCenterPoints,o.halfBoxSizes),o.startPoints=W.mul(o.sub,this.inputSizeTensor),o.add=W.add(o.boxCenterPoints,o.halfBoxSizes),o.endPoints=W.mul(o.add,this.inputSizeTensor);let n=W.concat2d([o.startPoints,o.endPoints],1);return Object.keys(o).forEach(r=>W.dispose(o[r])),n}normalizeLandmarks(t,o){let n={};n.reshape=W.reshape(t,[-1,7,2]),n.div=W.div(n.reshape,this.inputSizeTensor),n.landmarks=W.add(n.div,this.anchors[o]);let r=W.mul(n.landmarks,this.inputSizeTensor);return Object.keys(n).forEach(A=>W.dispose(n[A])),r}async predict(t,o){let n={};n.resize=W.image.resizeBilinear(t,[this.inputSize,this.inputSize]),n.div=W.div(n.resize,V.tf127),n.image=W.sub(n.div,V.tf1),n.batched=this.model.execute(n.image),n.predictions=W.squeeze(n.batched),n.slice=W.slice(n.predictions,[0,0],[-1,1]),n.sigmoid=W.sigmoid(n.slice),n.scores=W.squeeze(n.sigmoid);let r=await n.scores.data();n.boxes=W.slice(n.predictions,[0,1],[-1,4]),n.norm=this.normalizeBoxes(n.boxes),n.nms=await W.image.nonMaxSuppressionAsync(n.norm,n.scores,3*o.hand.maxDetected,o.hand.iouThreshold,o.hand.minConfidence);let A=await n.nms.array(),s=[];for(let a of A){let i={};i.box=W.slice(n.norm,[a,0],[1,-1]),i.slice=W.slice(n.predictions,[a,5],[1,14]),i.norm=this.normalizeLandmarks(i.slice,a),i.palmLandmarks=W.reshape(i.norm,[-1,2]);let x=await i.box.data(),c=x.slice(0,2),l=x.slice(2,4),y=await i.palmLandmarks.array(),f={startPoint:c,endPoint:l,palmLandmarks:y,confidence:r[a]},u=K3(f,[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]);s.push(u),Object.keys(i).forEach(m=>W.dispose(i[m]))}return Object.keys(n).forEach(a=>W.dispose(n[a])),s}};var L0=Z(D());var yA=5,eo=1.65,to=[0,5,9,13,17,1,2],xA=0,cA=2,oo=0,i5=class{constructor(t,o){T(this,"handDetector");T(this,"handPoseModel");T(this,"inputSize");T(this,"storedBoxes");T(this,"skipped");T(this,"detectedHands");this.handDetector=t,this.handPoseModel=o,this.inputSize=this.handPoseModel&&this.handPoseModel.inputs[0].shape?this.handPoseModel.inputs[0].shape[2]:0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let o=t.map(s=>s[0]),n=t.map(s=>s[1]),r=[Math.min(...o),Math.min(...n)],A=[Math.max(...o),Math.max(...n)];return{startPoint:r,endPoint:A}}getBoxForPalmLandmarks(t,o){let n=t.map(A=>M1([...A,1],o)),r=this.calculateLandmarksBoundingBox(n);return A5(s5(r),yA)}getBoxForHandLandmarks(t){let o=this.calculateLandmarksBoundingBox(t),n=A5(s5(o),eo);n.palmLandmarks=[];for(let r=0;r<to.length;r++)n.palmLandmarks.push(t[to[r]].slice(0,2));return n}transformRawCoords(t,o,n,r){let A=r5(o),s=[A[0]/this.inputSize,A[1]/this.inputSize,(A[0]+A[1])/this.inputSize/2],a=t.map(f=>[s[0]*(f[0]-this.inputSize/2),s[1]*(f[1]-this.inputSize/2),s[2]*f[2]]),i=g1(n,[0,0]),x=a.map(f=>[...M1(f,i),f[2]]),c=Q3(r),l=[...k2(o),1],y=[Te(l,c[0]),Te(l,c[1])];return x.map(f=>[Math.trunc(f[0]+y[0]),Math.trunc(f[1]+y[1]),Math.trunc(f[2])])}async estimateHands(t,o){let n=!1,r,A=(o.hand.skipTime||0)>h()-oo,s=this.skipped<(o.hand.skipFrames||0);o.skipAllowed&&A&&s&&(r=await this.handDetector.predict(t,o),this.skipped=0),o.skipAllowed&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==o.hand.maxDetected||!o.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(n=!0));let a=[];for(let i=0;i<this.storedBoxes.length;i++){let x=this.storedBoxes[i];if(!!x)if(o.hand.landmarks){let c=o.hand.rotation?J3(x.palmLandmarks[xA],x.palmLandmarks[cA]):0,l=k2(x),y=[l[0]/t.shape[2],l[1]/t.shape[1]],f=o.hand.rotation&&v.kernels.includes("rotatewithoffset")?L0.image.rotateWithOffset(t,c,0,y):t.clone(),u=g1(-c,l),m=n?this.getBoxForPalmLandmarks(x.palmLandmarks,u):x,P=Y3(m,f,[this.inputSize,this.inputSize]),g=L0.div(P,V.tf255);L0.dispose(P),L0.dispose(f);let[b,d]=this.handPoseModel.execute(g);oo=h(),L0.dispose(g);let M=(await b.data())[0];if(L0.dispose(b),M>=o.hand.minConfidence/4){let S=L0.reshape(d,[-1,3]),w=await S.array();L0.dispose(d),L0.dispose(S);let j=this.transformRawCoords(w,m,c,u),C=this.getBoxForHandLandmarks(j);this.storedBoxes[i]={...C,confidence:M};let F={landmarks:j,confidence:M,boxConfidence:x.confidence,fingerConfidence:M,box:{topLeft:C.startPoint,bottomRight:C.endPoint}};a.push(F)}else this.storedBoxes[i]=null;L0.dispose(d)}else{let c=A5(s5(x),eo),l={confidence:x.confidence,boxConfidence:x.confidence,fingerConfidence:0,box:{topLeft:c.startPoint,bottomRight:c.endPoint},landmarks:[]};a.push(l)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=a.length,a.length>o.hand.maxDetected&&(a.length=o.hand.maxDetected),a}};var k0={thumb:0,index:1,middle:2,ring:3,pinky:4,all:[0,1,2,3,4],nameMapping:{0:"thumb",1:"index",2:"middle",3:"ring",4:"pinky"},pointsMapping:{0:[[0,1],[1,2],[2,3],[3,4]],1:[[0,5],[5,6],[6,7],[7,8]],2:[[0,9],[9,10],[10,11],[11,12]],3:[[0,13],[13,14],[14,15],[15,16]],4:[[0,17],[17,18],[18,19],[19,20]]},getName:e=>k0.nameMapping[e],getPoints:e=>k0.pointsMapping[e]},ke={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>ke.nameMapping[e]},o0={verticalUp:0,verticalDown:1,horizontalLeft:2,horizontalRight:3,diagonalUpRight:4,diagonalUpLeft:5,diagonalDownRight:6,diagonalDownLeft:7,nameMapping:{0:"verticalUp",1:"verticalDown",2:"horizontalLeft",3:"horizontalRight",4:"diagonalUpRight",5:"diagonalUpLeft",6:"diagonalDownRight",7:"diagonalDownLeft"},getName:e=>o0.nameMapping[e]},we=class{constructor(t){T(this,"name");T(this,"curls");T(this,"directions");T(this,"weights");T(this,"weightsRelative");this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}curl(t,o,n){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([o,n])}direction(t,o,n){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([o,n])}weight(t,o){this.weights[t]=o;let n=this.weights.reduce((r,A)=>r+A,0);this.weightsRelative=this.weights.map(r=>r*5/n)}matchAgainst(t,o){let n=0;for(let r in t){let A=t[r],s=this.curls[r];if(typeof s=="undefined"){n+=this.weightsRelative[r];continue}for(let[a,i]of s)if(A===a){n+=i*this.weightsRelative[r];break}}for(let r in o){let A=o[r],s=this.directions[r];if(typeof s=="undefined"){n+=this.weightsRelative[r];continue}for(let[a,i]of s)if(A===a){n+=i*this.weightsRelative[r];break}}return n/10}};var{thumb:J0,index:ce,middle:de,ring:He,pinky:Ve}=k0,{none:Q0,half:fA,full:_0}=ke,{verticalUp:o2,verticalDown:z4,horizontalLeft:P1,horizontalRight:mA,diagonalUpRight:pA,diagonalUpLeft:n2,diagonalDownRight:S4,diagonalDownLeft:C4}=o0,Ee=new we("thumbs up");Ee.curl(J0,Q0,1);Ee.direction(J0,o2,1);Ee.direction(J0,n2,.25);Ee.direction(J0,pA,.25);for(let e of[k0.index,k0.middle,k0.ring,k0.pinky])Ee.curl(e,_0,1),Ee.direction(e,P1,1),Ee.direction(e,mA,1);var l0=new we("victory");l0.curl(J0,fA,.5);l0.curl(J0,Q0,.5);l0.direction(J0,o2,1);l0.direction(J0,n2,1);l0.curl(ce,Q0,1);l0.direction(ce,o2,.75);l0.direction(ce,n2,1);l0.curl(de,Q0,1);l0.direction(de,o2,1);l0.direction(de,n2,.75);l0.curl(He,_0,1);l0.direction(He,o2,.2);l0.direction(He,n2,1);l0.direction(He,P1,.2);l0.curl(Ve,_0,1);l0.direction(Ve,o2,.2);l0.direction(Ve,n2,1);l0.direction(Ve,P1,.2);l0.weight(ce,2);l0.weight(de,2);var ze=new we("point");ze.curl(J0,_0,1);ze.curl(ce,Q0,.5);ze.curl(de,_0,.5);ze.curl(He,_0,.5);ze.curl(Ve,_0,.5);ze.weight(ce,2);ze.weight(de,2);var Se=new we("middle finger");Se.curl(J0,Q0,1);Se.curl(ce,_0,.5);Se.curl(de,_0,.5);Se.curl(He,_0,.5);Se.curl(Ve,_0,.5);Se.weight(ce,2);Se.weight(de,2);var r2=new we("open palm");r2.curl(J0,Q0,.75);r2.curl(ce,Q0,.75);r2.curl(de,Q0,.75);r2.curl(He,Q0,.75);r2.curl(Ve,Q0,.75);var no=[Ee,l0,ze,Se,r2];var uA=.7,De={HALF_CURL_START_LIMIT:60,NO_CURL_START_LIMIT:130,DISTANCE_VOTE_POWER:1.1,SINGLE_ANGLE_VOTE_POWER:.9,TOTAL_ANGLE_VOTE_POWER:1.6};function ro(e,t,o,n){let r=(t-n)/(e-o),A=Math.atan(r)*180/Math.PI;return A<=0?A=-A:A>0&&(A=180-A),A}function so(e,t){if(!e||!t)return[0,0];let o=ro(e[0],e[1],t[0],t[1]);if(e.length===2)return o;let n=ro(e[1],e[2],t[1],t[2]);return[o,n]}function Ao(e,t=1){let o=0,n=0,r=0;return e>=75&&e<=105?o=1*t:e>=25&&e<=155?n=1*t:r=1*t,[o,n,r]}function hA(e,t,o){let n=e[0]-t[0],r=e[0]-o[0],A=t[0]-o[0],s=e[1]-t[1],a=e[1]-o[1],i=t[1]-o[1],x=e[2]-t[2],c=e[2]-o[2],l=t[2]-o[2],y=Math.sqrt(n*n+s*s+x*x),f=Math.sqrt(r*r+a*a+c*c),u=Math.sqrt(A*A+i*i+l*l),m=(u*u+y*y-f*f)/(2*u*y);m>1?m=1:m<-1&&(m=-1);let P=Math.acos(m);P=57.2958*P%180;let g;return P>De.NO_CURL_START_LIMIT?g=ke.none:P>De.HALF_CURL_START_LIMIT?g=ke.half:g=ke.full,g}function ao(e,t,o,n){let r;return n===Math.abs(e)?e>0?r=o0.horizontalLeft:r=o0.horizontalRight:n===Math.abs(t)?t>0?r=o0.horizontalLeft:r=o0.horizontalRight:o>0?r=o0.horizontalLeft:r=o0.horizontalRight,r}function io(e,t,o,n){let r;return n===Math.abs(e)?e<0?r=o0.verticalDown:r=o0.verticalUp:n===Math.abs(t)?t<0?r=o0.verticalDown:r=o0.verticalUp:o<0?r=o0.verticalDown:r=o0.verticalUp,r}function bA(e,t,o,n,r,A,s,a){let i,x=io(e,t,o,n),c=ao(r,A,s,a);return x===o0.verticalUp?c===o0.horizontalLeft?i=o0.diagonalUpLeft:i=o0.diagonalUpRight:c===o0.horizontalLeft?i=o0.diagonalDownLeft:i=o0.diagonalDownRight,i}function gA(e,t,o,n){let r=e[0]-t[0],A=e[0]-o[0],s=t[0]-o[0],a=e[1]-t[1],i=e[1]-o[1],x=t[1]-o[1],c=Math.max(Math.abs(r),Math.abs(A),Math.abs(s)),l=Math.max(Math.abs(a),Math.abs(i),Math.abs(x)),y=0,f=0,u=0,m=l/(c+1e-5);m>1.5?y+=De.DISTANCE_VOTE_POWER:m>.66?f+=De.DISTANCE_VOTE_POWER:u+=De.DISTANCE_VOTE_POWER;let P=Math.sqrt(r*r+a*a),g=Math.sqrt(A*A+i*i),b=Math.sqrt(s*s+x*x),d=Math.max(P,g,b),M=e[0],S=e[1],w=o[0],j=o[1];d===P?(w=o[0],j=o[1]):d===b&&(M=t[0],S=t[1]);let H=so([M,S],[w,j]),Y=Ao(H,De.TOTAL_ANGLE_VOTE_POWER);y+=Y[0],f+=Y[1],u+=Y[2];for(let x0 of n){let E=Ao(x0,De.SINGLE_ANGLE_VOTE_POWER);y+=E[0],f+=E[1],u+=E[2]}let J;return y===Math.max(y,f,u)?J=io(i,a,x,l):u===Math.max(f,u)?J=ao(A,r,s,c):J=bA(i,a,x,l,A,r,s,c),J}function lo(e){let t=[],o=[],n=[],r=[];if(!e)return{curls:n,directions:r};for(let A of k0.all){let s=k0.getPoints(A),a=[],i=[];for(let x of s){let c=e[x[0]],l=e[x[1]],y=so(c,l),f=y[0],u=y[1];a.push(f),i.push(u)}t.push(a),o.push(i)}for(let A of k0.all){let s=A===k0.thumb?1:0,a=k0.getPoints(A),i=e[a[s][0]],x=e[a[s+1][1]],c=e[a[3][1]],l=hA(i,x,c),y=gA(i,x,c,t[A].slice(s));n[A]=l,r[A]=y}return{curls:n,directions:r}}function l5(e){if(!e||e.length===0)return null;let t=lo(e),o={};for(let n of k0.all)o[k0.getName(n)]={curl:ke.getName(t.curls[n]),direction:o0.getName(t.directions[n])};return o}function yo(e){let t=[];if(!e||e.length===0)return t;let o=lo(e);for(let n of no){let r=n.matchAgainst(o.curls,o.directions);r>=uA&&t.push({name:n.name,confidence:r})}return t}var xo={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],palm:[0]},A2,s2,co;async function v1(e,t){let o=await co.estimateHands(e,t);if(!o)return[];let n=[];for(let r=0;r<o.length;r++){let A={};if(o[r].landmarks)for(let c of Object.keys(xo))A[c]=xo[c].map(l=>o[r].landmarks[l]);let s=o[r].landmarks,a=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],i=[0,0,0,0];if(s&&s.length>0){for(let c of s)c[0]<a[0]&&(a[0]=c[0]),c[1]<a[1]&&(a[1]=c[1]),c[0]>a[2]&&(a[2]=c[0]),c[1]>a[3]&&(a[3]=c[1]);a[2]-=a[0],a[3]-=a[1],i=[a[0]/(e.shape[2]||0),a[1]/(e.shape[1]||0),a[2]/(e.shape[2]||0),a[3]/(e.shape[1]||0)]}else a=o[r].box?[Math.trunc(Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.max(0,o[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,o[r].box.bottomRight[0])-Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,o[r].box.bottomRight[1])-Math.max(0,o[r].box.topLeft[1]))]:[0,0,0,0],i=[o[r].box.topLeft[0]/(e.shape[2]||0),o[r].box.topLeft[1]/(e.shape[1]||0),(o[r].box.bottomRight[0]-o[r].box.topLeft[0])/(e.shape[2]||0),(o[r].box.bottomRight[1]-o[r].box.topLeft[1])/(e.shape[1]||0)];let x=l5(s);n.push({id:r,score:Math.round(100*o[r].confidence)/100,boxScore:Math.round(100*o[r].boxConfidence)/100,fingerScore:Math.round(100*o[r].fingerConfidence)/100,label:"hand",box:a,boxRaw:i,keypoints:s,annotations:A,landmarks:x})}return n}async function T1(e){var o,n;v.initial&&(A2=null,s2=null),!A2||!s2?[A2,s2]=await Promise.all([e.hand.enabled?G((o=e.hand.detector)==null?void 0:o.modelPath):null,e.hand.landmarks?G((n=e.hand.skeleton)==null?void 0:n.modelPath):null]):(e.debug&&p("cached model:",A2.modelUrl),e.debug&&p("cached model:",s2.modelUrl));let t=new a5(A2);return co=new i5(t,s2),[A2,s2]}var Q=Z(D());var d0=[null,null],MA=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],Ce=[[0,0],[0,0]],PA=["hand","fist","pinch","point","face","tip","pinchtip"],mo=4,po=1.6,RA=512,vA=1.4,y5=Number.MAX_SAFE_INTEGER,w1=0,fe=[0,0],A0={boxes:[],hands:[]},uo={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],base:[0],palm:[0,17,13,9,5,1,0]};async function ho(e){var t;if(v.initial&&(d0[0]=null),d0[0])e.debug&&p("cached model:",d0[0].modelUrl);else{x5(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),d0[0]=await G((t=e.hand.detector)==null?void 0:t.modelPath);let o=Object.values(d0[0].modelSignature.inputs);Ce[0][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ce[0][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return d0[0]}async function bo(e){var t;if(v.initial&&(d0[1]=null),d0[1])e.debug&&p("cached model:",d0[1].modelUrl);else{d0[1]=await G((t=e.hand.skeleton)==null?void 0:t.modelPath);let o=Object.values(d0[1].modelSignature.inputs);Ce[1][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ce[1][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return d0[1]}async function TA(e,t){let o=[];if(!e||!d0[0])return o;let n={},r=(e.shape[2]||1)/(e.shape[1]||1),A=Math.min(Math.round((e.shape[1]||0)/8)*8,RA),s=Math.round(A*r/8)*8;n.resize=Q.image.resizeBilinear(e,[A,s]),n.cast=Q.cast(n.resize,"int32"),[n.rawScores,n.rawBoxes]=await d0[0].executeAsync(n.cast,MA),n.boxes=Q.squeeze(n.rawBoxes,[0,2]),n.scores=Q.squeeze(n.rawScores,[0]);let a=Q.unstack(n.scores,1);Q.dispose(a[mo]),a.splice(mo,1),n.filtered=Q.stack(a,1),Q.dispose(a),n.max=Q.max(n.filtered,1),n.argmax=Q.argMax(n.filtered,1);let i=0;n.nms=await Q.image.nonMaxSuppressionAsync(n.boxes,n.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let x=await n.nms.data(),c=await n.max.data(),l=await n.argmax.data();for(let y of Array.from(x)){let f=Q.slice(n.boxes,y,1),u=await f.data();Q.dispose(f);let m=[u[1],u[0],u[3]-u[1],u[2]-u[0]],P=Q2(m,vA),g=[Math.trunc(m[0]*fe[0]),Math.trunc(m[1]*fe[1]),Math.trunc(m[2]*fe[0]),Math.trunc(m[3]*fe[1])],b=c[y],d=PA[l[y]],M={id:i++,score:b,box:g,boxRaw:P,label:d};o.push(M)}return Object.keys(n).forEach(y=>Q.dispose(n[y])),o.sort((y,f)=>f.score-y.score),o.length>(t.hand.maxDetected||1)&&(o.length=t.hand.maxDetected||1),o}async function k1(e,t,o){let n={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&d0[1]&&o.hand.landmarks&&t.score>(o.hand.minConfidence||0)){let r={},A=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=Q.image.cropAndResize(e,[A],[0],[Ce[1][0],Ce[1][1]],"bilinear"),r.div=Q.div(r.crop,V.tf255),[r.score,r.keypoints]=d0[1].execute(r.div,["Identity_1","Identity"]);let s=(await r.score.data())[0],a=(100-Math.trunc(100/(1+Math.exp(s))))/100;if(a>=(o.hand.minConfidence||0)){n.fingerScore=a,r.reshaped=Q.reshape(r.keypoints,[-1,3]);let c=(await r.reshaped.array()).map(l=>[l[0]/Ce[1][1],l[1]/Ce[1][0],l[2]||0]).map(l=>[l[0]*t.boxRaw[2],l[1]*t.boxRaw[3],l[2]||0]);n.keypoints=c.map(l=>[fe[0]*(l[0]+t.boxRaw[0]),fe[1]*(l[1]+t.boxRaw[1]),l[2]||0]),n.landmarks=l5(n.keypoints);for(let l of Object.keys(uo))n.annotations[l]=uo[l].map(y=>n.landmarks&&n.keypoints[y]?n.keypoints[y]:null)}Object.keys(r).forEach(i=>Q.dispose(r[i]))}return n}async function E1(e,t){var r,A;if(!d0[0]||!d0[1]||!((r=d0[0])!=null&&r.inputs[0].shape)||!((A=d0[1])!=null&&A.inputs[0].shape))return[];fe=[e.shape[2]||0,e.shape[1]||0],y5++;let o=(t.hand.skipTime||0)>h()-w1,n=y5<(t.hand.skipFrames||0);return t.skipAllowed&&o&&n?A0.hands:new Promise(async s=>{let a=3*(t.hand.skipTime||0)>h()-w1,i=y5<3*(t.hand.skipFrames||0);t.skipAllowed&&A0.hands.length===t.hand.maxDetected?A0.hands=await Promise.all(A0.boxes.map(c=>k1(e,c,t))):t.skipAllowed&&a&&i&&A0.hands.length>0?A0.hands=await Promise.all(A0.boxes.map(c=>k1(e,c,t))):(A0.boxes=await TA(e,t),w1=h(),A0.hands=await Promise.all(A0.boxes.map(c=>k1(e,c,t))),y5=0);let x=[...A0.boxes];if(A0.boxes.length=0,t.cacheSensitivity>0)for(let c=0;c<A0.hands.length;c++){let l=a3(A0.hands[c].keypoints,fe);if(l.box[2]/(e.shape[2]||1)>.05&&l.box[3]/(e.shape[1]||1)>.05&&A0.hands[c].fingerScore&&A0.hands[c].fingerScore>(t.hand.minConfidence||0)){let y=Q2(l.box,po),f=Q2(l.boxRaw,po);A0.boxes.push({...x[c],box:y,boxRaw:f})}}for(let c=0;c<A0.hands.length;c++){let l=le(A0.hands[c].keypoints,fe);A0.hands[c].box=l.box,A0.hands[c].boxRaw=l.boxRaw}s(A0.hands)})}var d5=Z(D());var M0,c5=[],z1=Number.MAX_SAFE_INTEGER,Mo=0,Po=0;async function Ro(e){var t;return v.initial&&(M0=null),M0?e.debug&&p("cached model:",M0.modelUrl):M0=await G((t=e.face.liveness)==null?void 0:t.modelPath),M0}async function S1(e,t,o,n){var s,a;if(!M0)return 0;let r=(((s=t.face.liveness)==null?void 0:s.skipTime)||0)>h()-Po,A=z1<(((a=t.face.liveness)==null?void 0:a.skipFrames)||0);return t.skipAllowed&&r&&A&&Mo===n&&c5[o]?(z1++,c5[o]):(z1=0,new Promise(async i=>{let x=d5.image.resizeBilinear(e,[M0!=null&&M0.inputs[0].shape?M0.inputs[0].shape[2]:0,M0!=null&&M0.inputs[0].shape?M0.inputs[0].shape[1]:0],!1),c=M0==null?void 0:M0.execute(x),l=(await c.data())[0];c5[o]=Math.round(100*l)/100,Mo=n,Po=h(),d5.dispose([x,c]),i(c5[o])}))}var zo=Z(D());var E2={};ue(E2,{connected:()=>m5,horizontal:()=>C1,kpt:()=>f5,relative:()=>I1,vertical:()=>j1});var f5=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],C1=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],j1=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],I1=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],m5={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var je=Z(D()),To=.005,W0={keypoints:[],padding:[[0,0],[0,0],[0,0],[0,0]]};function N1(e){for(let t of C1){let o=e.keypoints.findIndex(r=>r.part===t[0]),n=e.keypoints.findIndex(r=>r.part===t[1]);if(e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[0]<e.keypoints[n].position[0]){let r=e.keypoints[o];e.keypoints[o]=e.keypoints[n],e.keypoints[n]=r}}for(let t of j1){let o=e.keypoints.findIndex(r=>r&&r.part===t[0]),n=e.keypoints.findIndex(r=>r&&r.part===t[1]);e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[1]<e.keypoints[n].position[1]&&e.keypoints.splice(o,1)}for(let[t,o]of I1){let n=e.keypoints.findIndex(x=>x&&x.part===t[0]),r=e.keypoints.findIndex(x=>x&&x.part===t[1]),A=e.keypoints.findIndex(x=>x&&x.part===o[0]),s=e.keypoints.findIndex(x=>x&&x.part===o[1]);if(!e.keypoints[A]||!e.keypoints[s])continue;let a=e.keypoints[n]?[Math.abs(e.keypoints[A].position[0]-e.keypoints[n].position[0]),Math.abs(e.keypoints[s].position[0]-e.keypoints[n].position[0])]:[0,0],i=e.keypoints[r]?[Math.abs(e.keypoints[s].position[0]-e.keypoints[r].position[0]),Math.abs(e.keypoints[A].position[0]-e.keypoints[r].position[0])]:[0,0];if(a[0]>a[1]||i[0]>i[1]){let x=e.keypoints[n];e.keypoints[n]=e.keypoints[r],e.keypoints[r]=x}}}function wo(e){for(let t=0;t<e.length;t++)if(e[t]&&W0.keypoints[t]){let o=[Math.abs(e[t].positionRaw[0]-W0.keypoints[t].positionRaw[0]),Math.abs(e[t].positionRaw[1]-W0.keypoints[t].positionRaw[1])];o[0]<To&&o[1]<To?e[t]=W0.keypoints[t]:W0.keypoints[t]=e[t]}else W0.keypoints[t]=e[t];return e}function ko(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;W0.padding=[[0,0],[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0],[0,0]],o.pad=je.pad(e,W0.padding),o.resize=je.image.resizeBilinear(o.pad,[t,t]);let n=je.cast(o.resize,"int32");return Object.keys(o).forEach(r=>je.dispose(o[r])),n}function Eo(e,t){e.keypoints=e.keypoints.filter(n=>n&&n.position);for(let n of e.keypoints)n.position=[n.position[0]*(t[0]+W0.padding[2][0]+W0.padding[2][1])/t[0]-W0.padding[2][0],n.position[1]*(t[1]+W0.padding[1][0]+W0.padding[1][1])/t[1]-W0.padding[1][0]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1]];let o=le(e.keypoints.map(n=>n.position),t);return e.box=o.box,e.boxRaw=o.boxRaw,e}var F0,p5=0,O1=Number.MAX_SAFE_INTEGER,Ze={boxes:[],bodies:[],last:0};async function So(e){return v.initial&&(F0=null),F0?e.debug&&p("cached model:",F0.modelUrl):(x5(["size"],e),F0=await G(e.body.modelPath)),p5=F0.inputs[0].shape?F0.inputs[0].shape[2]:0,p5<64&&(p5=256),F0}async function kA(e,t,o){let n=e[0][0],r=[],A=0;for(let c=0;c<n.length;c++)if(A=n[c][2],A>t.body.minConfidence){let l=[n[c][1],n[c][0]];r.push({score:Math.round(100*A)/100,part:f5[c],positionRaw:l,position:[Math.round((o.shape[2]||0)*l[0]),Math.round((o.shape[1]||0)*l[1])]})}A=r.reduce((c,l)=>l.score>c?l.score:c,0);let s=[],a=le(r.map(c=>c.position),[o.shape[2],o.shape[1]]),i={};for(let[c,l]of Object.entries(m5)){let y=[];for(let f=0;f<l.length-1;f++){let u=r.find(P=>P.part===l[f]),m=r.find(P=>P.part===l[f+1]);u&&m&&u.score>(t.body.minConfidence||0)&&m.score>(t.body.minConfidence||0)&&y.push([u.position,m.position])}i[c]=y}let x={id:0,score:A,box:a.box,boxRaw:a.boxRaw,keypoints:r,annotations:i};return N1(x),s.push(x),s}async function EA(e,t,o){let n=[];for(let r=0;r<e[0].length;r++){let A=e[0][r],s=Math.round(100*A[51+4])/100;if(s>t.body.minConfidence){let a=[];for(let l=0;l<17;l++){let y=A[3*l+2];if(y>t.body.minConfidence){let f=[A[3*l+1],A[3*l+0]];a.push({part:f5[l],score:Math.round(100*y)/100,positionRaw:f,position:[Math.round((o.shape[2]||0)*f[0]),Math.round((o.shape[1]||0)*f[1])]})}}let i=le(a.map(l=>l.position),[o.shape[2],o.shape[1]]),x={};for(let[l,y]of Object.entries(m5)){let f=[];for(let u=0;u<y.length-1;u++){let m=a.find(g=>g.part===y[u]),P=a.find(g=>g.part===y[u+1]);m&&P&&m.score>(t.body.minConfidence||0)&&P.score>(t.body.minConfidence||0)&&f.push([m.position,P.position])}x[l]=f}let c={id:r,score:s,box:i.box,boxRaw:i.boxRaw,keypoints:[...a],annotations:x};N1(c),n.push(c)}}return n.sort((r,A)=>A.score-r.score),n.length>t.body.maxDetected&&(n.length=t.body.maxDetected),n}async function L1(e,t){if(!F0||!(F0!=null&&F0.inputs[0].shape))return[];t.skipAllowed||(Ze.boxes.length=0),O1++;let o=(t.body.skipTime||0)>h()-Ze.last,n=O1<(t.body.skipFrames||0);return t.skipAllowed&&o&&n?Ze.bodies:new Promise(async r=>{let A={};O1=0,A.input=ko(e,p5),A.res=F0==null?void 0:F0.execute(A.input),Ze.last=h();let s=await A.res.array();Ze.bodies=A.res.shape[2]===17?await kA(s,t,e):await EA(s,t,e);for(let a of Ze.bodies)Eo(a,[e.shape[2]||1,e.shape[1]||1]),wo(a.keypoints);Object.keys(A).forEach(a=>zo.dispose(A[a])),r(Ze.bodies)})}var E0=Z(D());var a2,u5=[],jo=0,W1=Number.MAX_SAFE_INTEGER,b5=0,h5=2.5;async function Io(e){if(!a2||v.initial){a2=await G(e.object.modelPath);let t=Object.values(a2.modelSignature.inputs);b5=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&p("cached model:",a2.modelUrl);return a2}async function zA(e,t,o){let n=0,r=[];for(let i of[1,2,4])E0.tidy(async()=>{let x=i*13,c=E0.squeeze(e.find(m=>m.shape[1]===x**2&&(m.shape[2]||0)===$e.length)),l=E0.squeeze(e.find(m=>m.shape[1]===x**2&&(m.shape[2]||0)<$e.length)),f=await l.reshape([-1,4,l.shape[1]/4]).argMax(2).array(),u=await c.array();for(let m=0;m<c.shape[0];m++)for(let P=0;P<c.shape[1];P++){let g=u[m][P];if(g>(o.object.minConfidence||0)&&P!==61){let b=(.5+Math.trunc(m%x))/x,d=(.5+Math.trunc(m/x))/x,M=f[m].map(J=>J*(x/i/b5)),[S,w]=[b-h5/i*M[0],d-h5/i*M[1]],[j,C]=[b+h5/i*M[2]-S,d+h5/i*M[3]-w],F=[S,w,j,C];F=F.map(J=>Math.max(0,Math.min(J,1)));let H=[F[0]*t[0],F[1]*t[1],F[2]*t[0],F[3]*t[1]],Y={id:n++,score:Math.round(100*g)/100,class:P+1,label:$e[P].label,box:H.map(J=>Math.trunc(J)),boxRaw:F};r.push(Y)}}});e.forEach(i=>E0.dispose(i));let A=r.map(i=>[i.boxRaw[1],i.boxRaw[0],i.boxRaw[3],i.boxRaw[2]]),s=r.map(i=>i.score),a=[];if(A&&A.length>0){let i=await E0.image.nonMaxSuppressionAsync(A,s,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence);a=await i.data(),E0.dispose(i)}return r=r.filter((i,x)=>a.includes(x)).sort((i,x)=>x.score-i.score),r}async function F1(e,t){let o=(t.object.skipTime||0)>h()-jo,n=W1<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&u5.length>0?(W1++,u5):(W1=0,!v.kernels.includes("mod")||!v.kernels.includes("sparsetodense")?u5:new Promise(async r=>{let A=[e.shape[2]||0,e.shape[1]||0],s=E0.image.resizeBilinear(e,[b5,b5],!1),a=E0.div(s,V.tf255),i=a.transpose([0,3,1,2]);E0.dispose(a),E0.dispose(s);let x;t.object.enabled&&(x=a2.execute(i)),jo=h(),E0.dispose(i);let c=await zA(x,A,t);u5=c,r(c)}))}var z0=Z(D());var S2=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],SA=S2.length,z2=S2.reduce((e,t,o)=>(e[t]=o,e),{}),CA=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],ts=CA.map(([e,t])=>[z2[e],z2[t]]),Oo=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function Lo(e){let t=e.reduce(({maxX:o,maxY:n,minX:r,minY:A},{position:{x:s,y:a}})=>({maxX:Math.max(o,s),maxY:Math.max(n,a),minX:Math.min(r,s),minY:Math.min(A,a)}),{maxX:Number.NEGATIVE_INFINITY,maxY:Number.NEGATIVE_INFINITY,minX:Number.POSITIVE_INFINITY,minY:Number.POSITIVE_INFINITY});return[t.minX,t.minY,t.maxX-t.minX,t.maxY-t.minY]}function Wo(e,[t,o],[n,r]){let A=t/n,s=o/r,a=(x,c)=>({id:c,score:x.score,boxRaw:[x.box[0]/r,x.box[1]/n,x.box[2]/r,x.box[3]/n],box:[Math.trunc(x.box[0]*s),Math.trunc(x.box[1]*A),Math.trunc(x.box[2]*s),Math.trunc(x.box[3]*A)],keypoints:x.keypoints.map(({score:l,part:y,position:f})=>({score:l,part:y,position:[Math.trunc(f.x*s),Math.trunc(f.y*A)],positionRaw:[f.x/n,f.y/n]})),annotations:{}});return e.map((x,c)=>a(x,c))}var g5=class{constructor(t,o){T(this,"priorityQueue");T(this,"numberOfElements");T(this,"getElementValue");this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=o}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(Math.floor(t/2),t);)this.exchange(t,Math.floor(t/2)),t=Math.floor(t/2)}sink(t){for(;2*t<=this.numberOfElements;){let o=2*t;if(o<this.numberOfElements&&this.less(o,o+1)&&o++,!this.less(t,o))break;this.exchange(t,o),t=o}}getValueAt(t){return this.getElementValue(this.priorityQueue[t])}less(t,o){return this.getValueAt(t)<this.getValueAt(o)}exchange(t,o){let n=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[o],this.priorityQueue[o]=n}};function G1(e,t,o,n){return{y:n.get(e,t,o),x:n.get(e,t,o+SA)}}function B1(e,t,o){let{heatmapY:n,heatmapX:r,id:A}=e,{y:s,x:a}=G1(n,r,A,o);return{x:e.heatmapX*t+a,y:e.heatmapY*t+s}}function H1(e,t,o){return e<t?t:e>o?o:e}function Fo(e,t,o,n){let r=o-e,A=n-t;return r*r+A*A}function V1(e,t){return{x:e.x+t.x,y:e.y+t.y}}var $0,IA=["MobilenetV1/offset_2/BiasAdd","MobilenetV1/heatmap_2/BiasAdd","MobilenetV1/displacement_fwd_2/BiasAdd","MobilenetV1/displacement_bwd_2/BiasAdd"],M5=1,i2=16,NA=50**2;function Go(e,t,o,n,r,A,s=2){let a=g=>({y:A.get(g.y,g.x,e),x:A.get(g.y,g.x,A.shape[2]/2+e)}),i=(g,b,d)=>({y:H1(Math.round(g.y/i2),0,b-1),x:H1(Math.round(g.x/i2),0,d-1)}),[x,c]=n.shape,l=i(t.position,x,c),y=a(l),u=V1(t.position,y);for(let g=0;g<s;g++){let b=i(u,x,c),d=G1(b.y,b.x,o,r);u=V1({x:b.x*i2,y:b.y*i2},{x:d.x,y:d.y})}let m=i(u,x,c),P=n.get(m.y,m.x,o);return{position:u,part:S2[o],score:P}}function OA(e,t,o,n,r){let A=Oo.map(([y,f])=>[z2[y],z2[f]]),s=A.map(([,y])=>y),a=A.map(([y])=>y),i=t.shape[2],x=s.length,c=new Array(i),l=B1(e.part,i2,o);c[e.part.id]={score:e.score,part:S2[e.part.id],position:l};for(let y=x-1;y>=0;--y){let f=s[y],u=a[y];c[f]&&!c[u]&&(c[u]=Go(y,c[f],u,t,o,r))}for(let y=0;y<x;++y){let f=a[y],u=s[y];c[f]&&!c[u]&&(c[u]=Go(y,c[f],u,t,o,n))}return c}function LA(e,t,o,n,r){let[A,s]=r.shape,a=!0,i=Math.max(o-M5,0),x=Math.min(o+M5+1,A);for(let c=i;c<x;++c){let l=Math.max(n-M5,0),y=Math.min(n+M5+1,s);for(let f=l;f<y;++f)if(r.get(c,f,e)>t){a=!1;break}if(!a)break}return a}function WA(e,t){let[o,n,r]=t.shape,A=new g5(o*n*r,({score:s})=>s);for(let s=0;s<o;++s)for(let a=0;a<n;++a)for(let i=0;i<r;++i){let x=t.get(s,a,i);x<e||LA(i,x,s,a,t)&&A.enqueue({score:x,part:{heatmapY:s,heatmapX:a,id:i}})}return A}function Bo(e,{x:t,y:o},n){return e.some(({keypoints:r})=>{var s;let A=(s=r[n])==null?void 0:s.position;return A?Fo(o,t,A.y,A.x)<=NA:!1})}function FA(e,t){return t.reduce((n,{position:r,score:A},s)=>(Bo(e,r,s)||(n+=A),n),0)/t.length}function GA(e,t,o,n,r,A){let s=[],a=WA(A,t);for(;s.length<r&&!a.empty();){let i=a.dequeue(),x=B1(i.part,i2,e);if(Bo(s,x,i.part.id))continue;let c=OA(i,t,e,o,n);c=c.filter(f=>f.score>A);let l=FA(s,c),y=Lo(c);l>A&&s.push({keypoints:c,box:y,score:Math.round(100*l)/100})}return s}async function D1(e,t){let o=z0.tidy(()=>{if(!$0.inputs[0].shape)return[];let s=z0.image.resizeBilinear(e,[$0.inputs[0].shape[2],$0.inputs[0].shape[1]]),a=z0.sub(z0.div(z0.cast(s,"float32"),127.5),1),x=$0.execute(a,IA).map(c=>z0.squeeze(c,[0]));return x[1]=z0.sigmoid(x[1]),x}),n=await Promise.all(o.map(s=>s.buffer()));for(let s of o)z0.dispose(s);let r=await GA(n[0],n[1],n[2],n[3],t.body.maxDetected,t.body.minConfidence);return $0.inputs[0].shape?Wo(r,[e.shape[1],e.shape[2]],[$0.inputs[0].shape[2],$0.inputs[0].shape[1]]):[]}async function Ho(e){return!$0||v.initial?$0=await G(e.body.modelPath):e.debug&&p("cached model:",$0.modelUrl),$0}var n0=Z(D());var ne,Z1=!1;async function X1(e){return!ne||v.initial?ne=await G(e.segmentation.modelPath):e.debug&&p("cached model:",ne.modelUrl),ne}async function Do(e,t,o){var m,P;if(Z1)return{data:[],canvas:null,alpha:null};Z1=!0,ne||await X1(o);let n=await Ye(e,o),r=((m=n.tensor)==null?void 0:m.shape[2])||0,A=((P=n.tensor)==null?void 0:P.shape[1])||0;if(!n.tensor)return{data:[],canvas:null,alpha:null};let s={};s.resize=n0.image.resizeBilinear(n.tensor,[ne.inputs[0].shape?ne.inputs[0].shape[1]:0,ne.inputs[0].shape?ne.inputs[0].shape[2]:0],!1),n0.dispose(n.tensor),s.norm=n0.div(s.resize,V.tf255),s.res=ne.execute(s.norm),s.squeeze=n0.squeeze(s.res,0),s.squeeze.shape[2]===2?(s.softmax=n0.softmax(s.squeeze),[s.bg,s.fg]=n0.unstack(s.softmax,2),s.expand=n0.expandDims(s.fg,2),s.pad=n0.expandDims(s.expand,0),s.crop=n0.image.cropAndResize(s.pad,[[0,0,.5,.5]],[0],[r,A]),s.data=n0.squeeze(s.crop,0)):s.data=n0.image.resizeBilinear(s.squeeze,[A,r]);let a=Array.from(await s.data.data());if(v.node&&!v.Canvas&&typeof ImageData=="undefined")return o.debug&&p("canvas support missing"),Object.keys(s).forEach(g=>n0.dispose(s[g])),{data:a,canvas:null,alpha:null};let i=R0(r,A);n0.browser&&await n0.browser.toPixels(s.data,i);let x=i.getContext("2d");o.segmentation.blur&&o.segmentation.blur>0&&(x.filter=`blur(${o.segmentation.blur}px)`);let c=x.getImageData(0,0,r,A),l=R0(r,A),y=l.getContext("2d");n.canvas&&y.drawImage(n.canvas,0,0),y.globalCompositeOperation="darken",o.segmentation.blur&&o.segmentation.blur>0&&(y.filter=`blur(${o.segmentation.blur}px)`),y.drawImage(i,0,0),y.globalCompositeOperation="source-over",y.filter="none";let f=y.getImageData(0,0,r,A);for(let g=0;g<r*A;g++)f.data[4*g+3]=c.data[4*g+0];y.putImageData(f,0,0);let u=null;if(t&&l){u=R0(r,A);let g=await Ye(t,o);n0.dispose(g.tensor);let b=u.getContext("2d");b.drawImage(g.canvas,0,0,u.width,u.height),b.drawImage(l,0,0)}return Object.keys(s).forEach(g=>n0.dispose(s[g])),Z1=!1,{data:a,canvas:l,alpha:i}}var C2=class{constructor(){T(this,"ssrnetage",null);T(this,"gear",null);T(this,"blazeposedetect",null);T(this,"blazepose",null);T(this,"centernet",null);T(this,"efficientpose",null);T(this,"mobilefacenet",null);T(this,"emotion",null);T(this,"facedetect",null);T(this,"faceiris",null);T(this,"facemesh",null);T(this,"faceres",null);T(this,"ssrnetgender",null);T(this,"handpose",null);T(this,"handskeleton",null);T(this,"handtrack",null);T(this,"liveness",null);T(this,"movenet",null);T(this,"nanodet",null);T(this,"posenet",null);T(this,"segmentation",null);T(this,"antispoof",null)}},q1=e=>{let t=0,o=0,n=0;for(let A of Object.values(q0))t+=A.sizeFromManifest,o+=A.sizeLoadedWeights,n+=A.sizeDesired;let r=n>0?o/n:0;return{numLoadedModels:Object.values(q0).length,numEnabledModels:void 0,numDefinedModels:Object.keys(e.models).length,percentageLoaded:r,totalSizeFromManifest:t,totalSizeWeights:o,totalSizeLoading:n,totalSizeEnabled:void 0,modelStats:Object.values(q0)}};function P5(e){for(let t of Object.keys(e.models))e.models[t]=null}async function U1(e){var t,o,n,r,A,s,a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0;v.initial&&P5(e),e.config.hand.enabled&&(!e.models.handpose&&((o=(t=e.config.hand.detector)==null?void 0:t.modelPath)==null?void 0:o.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await T1(e.config)),!e.models.handskeleton&&e.config.hand.landmarks&&((r=(n=e.config.hand.detector)==null?void 0:n.modelPath)==null?void 0:r.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await T1(e.config))),e.config.body.enabled&&!e.models.blazepose&&((s=(A=e.config.body)==null?void 0:A.modelPath)==null?void 0:s.includes("blazepose"))&&(e.models.blazepose=c3(e.config)),e.config.body.enabled&&!e.models.blazeposedetect&&e.config.body.detector&&e.config.body.detector.modelPath&&(e.models.blazeposedetect=x3(e.config)),e.config.body.enabled&&!e.models.efficientpose&&((i=(a=e.config.body)==null?void 0:a.modelPath)==null?void 0:i.includes("efficientpose"))&&(e.models.efficientpose=h3(e.config)),e.config.body.enabled&&!e.models.movenet&&((c=(x=e.config.body)==null?void 0:x.modelPath)==null?void 0:c.includes("movenet"))&&(e.models.movenet=So(e.config)),e.config.body.enabled&&!e.models.posenet&&((y=(l=e.config.body)==null?void 0:l.modelPath)==null?void 0:y.includes("posenet"))&&(e.models.posenet=Ho(e.config)),e.config.face.enabled&&!e.models.facedetect&&(e.models.facedetect=o3(e.config)),e.config.face.enabled&&((f=e.config.face.antispoof)==null?void 0:f.enabled)&&!e.models.antispoof&&(e.models.antispoof=Dt(e.config)),e.config.face.enabled&&((u=e.config.face.liveness)==null?void 0:u.enabled)&&!e.models.liveness&&(e.models.liveness=Ro(e.config)),e.config.face.enabled&&((m=e.config.face.description)==null?void 0:m.enabled)&&!e.models.faceres&&(e.models.faceres=Z3(e.config)),e.config.face.enabled&&((P=e.config.face.emotion)==null?void 0:P.enabled)&&!e.models.emotion&&(e.models.emotion=P3(e.config)),e.config.face.enabled&&((g=e.config.face.iris)==null?void 0:g.enabled)&&!((b=e.config.face.attention)!=null&&b.enabled)&&!e.models.faceiris&&(e.models.faceiris=I3(e.config)),e.config.face.enabled&&((d=e.config.face.mesh)==null?void 0:d.enabled)&&!e.models.facemesh&&(e.models.facemesh=G3(e.config)),e.config.face.enabled&&((M=e.config.face.gear)==null?void 0:M.enabled)&&!e.models.gear&&(e.models.gear=St(e.config)),e.config.face.enabled&&((S=e.config.face.ssrnet)==null?void 0:S.enabled)&&!e.models.ssrnetage&&(e.models.ssrnetage=Ot(e.config)),e.config.face.enabled&&((w=e.config.face.ssrnet)==null?void 0:w.enabled)&&!e.models.ssrnetgender&&(e.models.ssrnetgender=Gt(e.config)),e.config.face.enabled&&((j=e.config.face.mobilefacenet)==null?void 0:j.enabled)&&!e.models.mobilefacenet&&(e.models.mobilefacenet=E3(e.config)),e.config.hand.enabled&&!e.models.handtrack&&((F=(C=e.config.hand.detector)==null?void 0:C.modelPath)==null?void 0:F.includes("handtrack"))&&(e.models.handtrack=ho(e.config)),e.config.hand.enabled&&e.config.hand.landmarks&&!e.models.handskeleton&&((Y=(H=e.config.hand.detector)==null?void 0:H.modelPath)==null?void 0:Y.includes("handtrack"))&&(e.models.handskeleton=bo(e.config)),e.config.object.enabled&&!e.models.centernet&&((x0=(J=e.config.object)==null?void 0:J.modelPath)==null?void 0:x0.includes("centernet"))&&(e.models.centernet=m3(e.config)),e.config.object.enabled&&!e.models.nanodet&&((G0=(E=e.config.object)==null?void 0:E.modelPath)==null?void 0:G0.includes("nanodet"))&&(e.models.nanodet=Io(e.config)),e.config.segmentation.enabled&&!e.models.segmentation&&(e.models.segmentation=X1(e.config));for await(let B0 of Object.keys(e.models))e.models[B0]&&typeof e.models[B0]!="undefined"&&(e.models[B0]=await e.models[B0])}async function Y1(e){let t=["const","placeholder","noop","pad","squeeze","add","sub","mul","div"];for(let o of Object.keys(e.models)){let n=e.models[o];if(!n)continue;let r=[],A=n==null?void 0:n.executor;if(A&&A.graph.nodes)for(let a of Object.values(A.graph.nodes)){let i=a.op.toLowerCase();r.includes(i)||r.push(i)}else!A&&e.config.debug&&p("model signature not determined:",o);let s=[];for(let a of r)!t.includes(a)&&!e.env.kernels.includes(a)&&!e.env.kernels.includes(a.replace("_",""))&&!e.env.kernels.includes(a.replace("native",""))&&!e.env.kernels.includes(a.replace("v2",""))&&s.push(a);e.config.debug&&s.length>0&&p("model validation failed:",o,s)}}var t0={name:"humangl",priority:999,canvas:null,gl:null,extensions:[],webGLattr:{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!1,desynchronized:!0}};function BA(){let e=t0.gl;!e||(t0.extensions=e.getSupportedExtensions())}async function Xo(e){var t;if(e.config.backend==="humangl"&&(t0.name in y0.engine().registry&&(!t0.gl||!t0.gl.getParameter(t0.gl.VERSION))&&(p("error: humangl backend invalid context"),P5(e)),!y0.findBackend(t0.name))){try{t0.canvas=await R0(100,100)}catch(n){p("error: cannot create canvas:",n);return}try{if(t0.gl=(t=t0.canvas)==null?void 0:t.getContext("webgl2",t0.webGLattr),!t0.gl.getParameter(t0.gl.VERSION).includes("2.0")){p("override: using fallback webgl backend as webgl 2.0 is not detected"),e.config.backend="webgl";return}t0.canvas&&(t0.canvas.addEventListener("webglcontextlost",async r=>{throw p("error: humangl:",r.type),p("possible browser memory leak using webgl or conflict with multiple backend registrations"),e.emit("error"),new Error("backend error: webgl context lost")}),t0.canvas.addEventListener("webglcontextrestored",r=>{p("error: humangl context restored:",r)}),t0.canvas.addEventListener("webglcontextcreationerror",r=>{p("error: humangl context create:",r)}))}catch(n){p("error: cannot get WebGL context:",n);return}try{y0.setWebGLContext(2,t0.gl)}catch(n){p("error: cannot set WebGL context:",n);return}try{let n=new y0.GPGPUContext(t0.gl);y0.registerBackend(t0.name,()=>new y0.MathBackendWebGL(n),t0.priority)}catch(n){p("error: cannot register WebGL backend:",n);return}try{y0.getKernelsForBackend("webgl").forEach(r=>{let A={...r,backendName:t0.name};y0.registerKernel(A)})}catch(n){p("error: cannot update WebGL backend registration:",n);return}let o=y0.backend().getGPGPUContext?y0.backend().getGPGPUContext().gl:null;if(o)p(`humangl webgl version:${o.getParameter(o.VERSION)} renderer:${o.getParameter(o.RENDERER)}`);else{p("error: no current gl context:",o,t0.gl);return}try{y0.ENV.set("WEBGL_VERSION",2)}catch(n){p("error: cannot set WebGL backend flags:",n);return}BA(),p("backend registered:",t0.name)}}var I=Z(D());function HA(){if(!v.kernels.includes("mod")){let e={kernelName:"Mod",backendName:I.getBackend(),kernelFunc:t=>I.tidy(()=>I.sub(t.inputs.a,I.mul(I.div(t.inputs.a,t.inputs.b),t.inputs.b)))};I.registerKernel(e),v.kernels.push("mod")}if(!v.kernels.includes("floormod")){let e={kernelName:"FloorMod",backendName:I.getBackend(),kernelFunc:t=>I.tidy(()=>I.floorDiv(t.inputs.a/t.inputs.b)*t.inputs.b+I.mod(t.inputs.a,t.inputs.b))};I.registerKernel(e),v.kernels.push("floormod")}}async function v5(e,t=!1){if(e.state="backend",t||v.initial||e.config.backend&&e.config.backend.length>0&&I.getBackend()!==e.config.backend){let o=h();if(e.config.backend&&e.config.backend.length>0){if(typeof window=="undefined"&&typeof WorkerGlobalScope!="undefined"&&e.config.debug&&e.config.debug&&p("running inside web worker"),v.browser&&e.config.backend==="tensorflow"&&(e.config.debug&&p("override: backend set to tensorflow while running in browser"),e.config.backend="humangl"),v.node&&(e.config.backend==="webgl"||e.config.backend==="humangl")&&(e.config.debug&&p(`override: backend set to ${e.config.backend} while running in nodejs`),e.config.backend="tensorflow"),v.browser&&e.config.backend==="webgpu")if(typeof navigator=="undefined"||typeof navigator.gpu=="undefined")p("override: backend set to webgpu but browser does not support webgpu"),e.config.backend="humangl";else{let r=await navigator.gpu.requestAdapter();if(e.config.debug&&p("enumerated webgpu adapter:",r),!r)p("override: backend set to webgpu but browser reports no available gpu"),e.config.backend="humangl";else{let A="requestAdapterInfo"in r?await r.requestAdapterInfo():void 0;p("webgpu adapter info:",A)}}e.config.backend==="humangl"&&await Xo(e);let n=Object.keys(I.engine().registryFactory);if(e.config.debug&&p("available backends:",n),n.includes(e.config.backend)||(p(`error: backend ${e.config.backend} not found in registry`),e.config.backend=v.node?"tensorflow":"webgl",e.config.debug&&p(`override: setting backend ${e.config.backend}`)),e.config.debug&&p("setting backend:",e.config.backend),e.config.backend==="wasm"){try{I.env().set("CANVAS2D_WILL_READ_FREQUENTLY",!0)}catch(s){}if(e.config.debug&&p("wasm path:",e.config.wasmPath),typeof(I==null?void 0:I.setWasmPaths)!="undefined")await I.setWasmPaths(e.config.wasmPath,e.config.wasmPlatformFetch);else throw new Error("backend error: attempting to use wasm backend but wasm path is not set");let r=await I.env().getAsync("WASM_HAS_SIMD_SUPPORT"),A=await I.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");e.config.debug&&p(`wasm execution: ${r?"SIMD":"no SIMD"} ${A?"multithreaded":"singlethreaded"}`),e.config.debug&&!r&&p("warning: wasm simd support is not enabled")}try{await I.setBackend(e.config.backend),await I.ready(),jt()}catch(r){return p("error: cannot set backend:",e.config.backend,r),!1}}if(I.getBackend()==="humangl"&&(I.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),I.ENV.set("WEBGL_CPU_FORWARD",!0),I.ENV.set("WEBGL_USE_SHAPES_UNIFORMS",!0),I.ENV.set("CPU_HANDOFF_SIZE_THRESHOLD",256),typeof e.config.deallocate!="undefined"&&e.config.deallocate&&(p("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),I.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",0)),I.backend().getGPGPUContext)){let n=await I.backend().getGPGPUContext().gl;e.config.debug&&p(`gl version:${n.getParameter(n.VERSION)} renderer:${n.getParameter(n.RENDERER)}`)}I.getBackend(),I.enableProdMode(),await I.ready(),e.performance.initBackend=Math.trunc(h()-o),e.config.backend=I.getBackend(),await v.updateBackend(),HA()}return!0}function x5(e,t){for(let o of e){let n={kernelName:o,backendName:t.backend,kernelFunc:()=>{t.debug&&p("kernelFunc",o,t.backend)}};I.registerKernel(n)}v.kernels=I.getKernelsForBackend(I.getBackend()).map(o=>o.kernelName.toLowerCase())}var tt={};ue(tt,{all:()=>et,body:()=>y2,canvas:()=>$1,face:()=>l2,gesture:()=>d2,hand:()=>x2,object:()=>c2,options:()=>P0,person:()=>_1});var V0=e=>{if(!e)p("draw error: invalid canvas");else if(!e.getContext)p("draw error: canvas context not defined");else{let t=e.getContext("2d");if(!t)p("draw error: cannot get canvas context");else return t}return null},Xe=e=>Math.round(e*180/Math.PI),me=(e,t)=>{if(!t.useDepth||typeof e=="undefined")return t.color;let o=Uint8ClampedArray.from([127+2*e,127-2*e,255]);return`rgba(${o[0]}, ${o[1]}, ${o[2]}, ${t.alpha})`};function pe(e,t,o,n,r){e.fillStyle=me(n,r),e.beginPath(),e.arc(t,o,r.pointSize,0,2*Math.PI),e.fill()}function re(e,t,o,n,r,A){if(e.beginPath(),e.lineWidth=A.lineWidth,A.useCurves){let s=(t+t+n)/2,a=(o+o+r)/2;e.ellipse(s,a,n/2,r/2,0,0,2*Math.PI)}else e.moveTo(t+A.roundRect,o),e.lineTo(t+n-A.roundRect,o),e.quadraticCurveTo(t+n,o,t+n,o+A.roundRect),e.lineTo(t+n,o+r-A.roundRect),e.quadraticCurveTo(t+n,o+r,t+n-A.roundRect,o+r),e.lineTo(t+A.roundRect,o+r),e.quadraticCurveTo(t,o+r,t,o+r-A.roundRect),e.lineTo(t,o+A.roundRect),e.quadraticCurveTo(t,o,t+A.roundRect,o),e.closePath();e.stroke()}function K1(e,t,o){if(!(t.length<2)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let n of t)e.strokeStyle=me(n[2]||0,o),e.lineTo(Math.trunc(n[0]),Math.trunc(n[1]));e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function Uo(e,t,o){if(!(t.length<2)){if(e.lineWidth=o.lineWidth,!o.useCurves||t.length<=2){K1(e,t,o);return}e.moveTo(t[0][0],t[0][1]);for(let n=0;n<t.length-2;n++){let r=(t[n][0]+t[n+1][0])/2,A=(t[n][1]+t[n+1][1])/2;e.quadraticCurveTo(t[n][0],t[n][1],r,A)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function J1(e,t,o,n=5){let r,A,s;e.beginPath(),e.moveTo(t[0],t[1]),e.lineTo(o[0],o[1]),r=Math.atan2(o[1]-t[1],o[0]-t[0]),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.moveTo(A,s),r+=1/3*(2*Math.PI),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.lineTo(A,s),r+=1/3*(2*Math.PI),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.lineTo(A,s),e.closePath(),e.stroke(),e.fill()}var P0={color:"rgba(173, 216, 230, 0.6)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",alpha:.5,font:'small-caps 16px "Segoe UI"',lineHeight:18,lineWidth:4,pointSize:2,roundRect:8,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawAttention:!0,drawGestures:!0,drawPolygons:!0,drawGaze:!0,fillPolygons:!1,useDepth:!0,useCurves:!1};var U;function DA(e,t){if(U.drawLabels){let o=[];if(o.push(`face: ${Math.trunc(100*e.score)}%`),e.genderScore&&o.push(`${e.gender||""} ${Math.trunc(100*e.genderScore)}%`),e.age&&o.push(`age: ${e.age||""}`),e.iris&&o.push(`distance: ${e.iris}`),e.real&&o.push(`real: ${Math.trunc(100*e.real)}%`),e.live&&o.push(`live: ${Math.trunc(100*e.live)}%`),e.emotion&&e.emotion.length>0){let n=e.emotion.map(r=>`${Math.trunc(100*r.score)}% ${r.emotion}`);n.length>3&&(n.length=3),o.push(n.join(" "))}e.rotation&&e.rotation.angle&&e.rotation.gaze&&(e.rotation.angle.roll&&o.push(`roll: ${Xe(e.rotation.angle.roll)}\xB0 yaw:${Xe(e.rotation.angle.yaw)}\xB0 pitch:${Xe(e.rotation.angle.pitch)}\xB0`),e.rotation.gaze.bearing&&o.push(`gaze: ${Xe(e.rotation.gaze.bearing)}\xB0`)),o.length===0&&o.push("face"),t.fillStyle=U.color;for(let n=o.length-1;n>=0;n--){let r=Math.max(e.box[0],0),A=n*U.lineHeight+e.box[1];U.shadowColor&&U.shadowColor!==""&&(t.fillStyle=U.shadowColor,t.fillText(o[n],r+5,A+16)),t.fillStyle=U.labelColor,t.fillText(o[n],r+4,A+15)}}}function ZA(e,t){if(e.annotations&&e.annotations.leftEyeIris&&e.annotations.leftEyeIris[0]){t.strokeStyle=U.useDepth?"rgba(255, 200, 255, 0.3)":U.color,t.beginPath();let o=Math.abs(e.annotations.leftEyeIris[3][0]-e.annotations.leftEyeIris[1][0])/2,n=Math.abs(e.annotations.leftEyeIris[4][1]-e.annotations.leftEyeIris[2][1])/2;t.ellipse(e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),U.fillPolygons&&(t.fillStyle=U.useDepth?"rgba(255, 255, 200, 0.3)":U.color,t.fill())}if(e.annotations&&e.annotations.rightEyeIris&&e.annotations.rightEyeIris[0]){t.strokeStyle=U.useDepth?"rgba(255, 200, 255, 0.3)":U.color,t.beginPath();let o=Math.abs(e.annotations.rightEyeIris[3][0]-e.annotations.rightEyeIris[1][0])/2,n=Math.abs(e.annotations.rightEyeIris[4][1]-e.annotations.rightEyeIris[2][1])/2;t.ellipse(e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),U.fillPolygons&&(t.fillStyle=U.useDepth?"rgba(255, 255, 200, 0.3)":U.color,t.fill())}}function XA(e,t){var o;if(U.drawGaze&&((o=e.rotation)==null?void 0:o.angle)&&typeof Path2D!="undefined"){t.strokeStyle="pink";let n=e.box[0]+e.box[2]/2-e.box[3]*Xe(e.rotation.angle.yaw)/90,r=e.box[1]+e.box[3]/2+e.box[2]*Xe(e.rotation.angle.pitch)/90,A=new Path2D(`
+`;var C5=(e,t,o)=>{let n=new RegExp("\\b"+t+" \\w+ (\\w+)","ig");e.replace(n,(r,A)=>(o[A]=0,r))},I5=class{constructor(t,o,n){T(this,"uniform",{});T(this,"attribute",{});T(this,"gl");T(this,"id");T(this,"compile",(t,o)=>{let n=this.gl.createShader(o);return n?(this.gl.shaderSource(n,t),this.gl.compileShader(n),this.gl.getShaderParameter(n,this.gl.COMPILE_STATUS)?n:(p(`filter: gl compile failed: ${this.gl.getShaderInfoLog(n)}`),null)):(p("filter: could not create shader"),null)});this.gl=t;let r=this.compile(o,this.gl.VERTEX_SHADER),A=this.compile(n,this.gl.FRAGMENT_SHADER);if(this.id=this.gl.createProgram(),!(!r||!A)){if(!this.id){p("filter: could not create webgl program");return}if(this.gl.attachShader(this.id,r),this.gl.attachShader(this.id,A),this.gl.linkProgram(this.id),!this.gl.getProgramParameter(this.id,this.gl.LINK_STATUS)){p(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);return}this.gl.useProgram(this.id),C5(o,"attribute",this.attribute);for(let s in this.attribute)this.attribute[s]=this.gl.getAttribLocation(this.id,s);C5(o,"uniform",this.uniform),C5(n,"uniform",this.uniform);for(let s in this.uniform)this.uniform[s]=this.gl.getUniformLocation(this.id,s)}}};function vt(){let e=0,t=null,o=!1,n=-1,r=[null,null],A=[],s=null,a=null,i=R0(100,100),x={},c={INTERMEDIATE:1},l=i.getContext("webgl");if(!l){p("filter: cannot get webgl context");return}this.gl=l;function y(b,d){if(!(b===i.width&&d===i.height)){if(i.width=b,i.height=d,!s){let M=new Float32Array([-1,-1,0,1,1,-1,1,1,-1,1,0,0,-1,1,0,0,1,-1,1,1,1,1,1,0]);s=l.createBuffer(),l.bindBuffer(l.ARRAY_BUFFER,s),l.bufferData(l.ARRAY_BUFFER,M,l.STATIC_DRAW),l.pixelStorei(l.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}l.viewport(0,0,i.width,i.height),r=[null,null]}}function f(b,d){let M=l.createFramebuffer();l.bindFramebuffer(l.FRAMEBUFFER,M);let S=l.createRenderbuffer();l.bindRenderbuffer(l.RENDERBUFFER,S);let w=l.createTexture();return l.bindTexture(l.TEXTURE_2D,w),l.texImage2D(l.TEXTURE_2D,0,l.RGBA,b,d,0,l.RGBA,l.UNSIGNED_BYTE,null),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MAG_FILTER,l.LINEAR),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MIN_FILTER,l.LINEAR),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_S,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_T,l.CLAMP_TO_EDGE),l.framebufferTexture2D(l.FRAMEBUFFER,l.COLOR_ATTACHMENT0,l.TEXTURE_2D,w,0),l.bindTexture(l.TEXTURE_2D,null),l.bindFramebuffer(l.FRAMEBUFFER,null),{fbo:M,texture:w}}function u(b){return r[b]=r[b]||f(i.width,i.height),r[b]}function m(b=0){if(!a)return;let d=null,M=null,S=!1;e===0?d=t:d=u(n).texture||null,e++,o&&!(b&c.INTERMEDIATE)?(M=null,S=e%2===0):(n=(n+1)%2,M=u(n).fbo||null),l.bindTexture(l.TEXTURE_2D,d),l.bindFramebuffer(l.FRAMEBUFFER,M),l.uniform1f(a.uniform.flipY,S?-1:1),l.drawArrays(l.TRIANGLES,0,6)}function P(b){if(x[b])return a=x[b],l.useProgram((a?a.id:null)||null),a;if(a=new I5(l,ht,b),!a)return p("filter: could not get webgl program"),null;let d=Float32Array.BYTES_PER_ELEMENT,M=4*d;return l.enableVertexAttribArray(a.attribute.pos),l.vertexAttribPointer(a.attribute.pos,2,l.FLOAT,!1,M,0*d),l.enableVertexAttribArray(a.attribute.uv),l.vertexAttribPointer(a.attribute.uv,2,l.FLOAT,!1,M,2*d),x[b]=a,a}let g={colorMatrix:b=>{let d=new Float32Array(b);d[4]/=255,d[9]/=255,d[14]/=255,d[19]/=255;let M=d[18]===1&&d[3]===0&&d[8]===0&&d[13]===0&&d[15]===0&&d[16]===0&&d[17]===0&&d[19]===0?gt:bt,S=P(M);!S||(l.uniform1fv(S.uniform.m,d),m())},brightness:b=>{let d=(b||0)+1;g.colorMatrix([d,0,0,0,0,0,d,0,0,0,0,0,d,0,0,0,0,0,1,0])},saturation:b=>{let d=(b||0)*2/3+1,M=(d-1)*-.5;g.colorMatrix([d,M,M,0,0,M,d,M,0,0,M,M,d,0,0,0,0,0,1,0])},desaturate:()=>{g.saturation(-1)},contrast:b=>{let d=(b||0)+1,M=-128*(d-1);g.colorMatrix([d,0,0,0,M,0,d,0,0,M,0,0,d,0,M,0,0,0,1,0])},negative:()=>{g.contrast(-2)},hue:b=>{b=(b||0)/180*Math.PI;let d=Math.cos(b),M=Math.sin(b),S=.213,w=.715,j=.072;g.colorMatrix([S+d*(1-S)+M*-S,w+d*-w+M*-w,j+d*-j+M*(1-j),0,0,S+d*-S+M*.143,w+d*(1-w)+M*.14,j+d*-j+M*-.283,0,0,S+d*-S+M*-(1-S),w+d*-w+M*w,j+d*(1-j)+M*j,0,0,0,0,0,1,0])},desaturateLuminance:()=>{g.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},sepia:()=>{g.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},brownie:()=>{g.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},vintagePinhole:()=>{g.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},kodachrome:()=>{g.colorMatrix([1.1285582396593525,-.3967382283601348,-.03992559172921793,0,63.72958762196502,-.16404339962244616,1.0835251566291304,-.05498805115633132,0,24.732407896706203,-.16786010706155763,-.5603416277695248,1.6014850761964943,0,35.62982807460946,0,0,0,1,0])},technicolor:()=>{g.colorMatrix([1.9125277891456083,-.8545344976951645,-.09155508482755585,0,11.793603434377337,-.3087833385928097,1.7658908555458428,-.10601743074722245,0,-70.35205161461398,-.231103377548616,-.7501899197440212,1.847597816108189,0,30.950940869491138,0,0,0,1,0])},polaroid:()=>{g.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},shiftToBGR:()=>{g.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},convolution:b=>{let d=new Float32Array(b),M=1/i.width,S=1/i.height,w=P(Rt);!w||(l.uniform1fv(w.uniform.m,d),l.uniform2f(w.uniform.px,M,S),m())},detectEdges:()=>{g.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},sobelX:()=>{g.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},sobelY:()=>{g.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},sharpen:b=>{let d=b||1;g.convolution.call(this,[0,-1*d,0,-1*d,1+4*d,-1*d,0,-1*d,0])},emboss:b=>{let d=b||1;g.convolution.call(this,[-2*d,-1*d,0,-1*d,1,1*d,0,1*d,2*d])},blur:b=>{let d=b/7/i.width,M=b/7/i.height,S=P(Pt);!S||(l.uniform2f(S.uniform.px,0,M),m(c.INTERMEDIATE),l.uniform2f(S.uniform.px,d,0),m())},pixelate:b=>{let d=b/i.width,M=b/i.height,S=P(Mt);!S||(l.uniform2f(S.uniform.size,d,M),m())}};this.add=function(b){let d=Array.prototype.slice.call(arguments,1),M=g[b];A.push({func:M,args:d})},this.reset=function(){A=[]},this.get=function(){return A},this.apply=function(b){y(b.width,b.height),e=0,t||(t=l.createTexture()),l.bindTexture(l.TEXTURE_2D,t),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_S,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_T,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MIN_FILTER,l.NEAREST),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MAG_FILTER,l.NEAREST),l.texImage2D(l.TEXTURE_2D,0,l.RGBA,l.RGBA,l.UNSIGNED_BYTE,b);for(let d=0;d<A.length;d++){o=d===A.length-1;let M=A[d];M.func.apply(this,M.args||[])}return i},this.draw=function(b){return this.add("brightness",0),this.apply(b)}}var X=Z(D());async function N2(e){let t=e.shape.length===4?X.squeeze(e):e,o=X.split(t,3,2),n=[X.min(o[0]),X.min(o[1]),X.min(o[2])],r=[X.max(o[0]),X.max(o[1]),X.max(o[2])],A=await Promise.all(r.map(f=>f.data())),s=.99*Math.max(A[0][0],A[1][0],A[2][0]),a=[X.sub(o[0],n[0]),X.sub(o[1],n[1]),X.sub(o[2],n[2])],i=[X.sub(r[0],n[0]),X.sub(r[1],n[1]),X.sub(r[2],n[2])],x=[X.div(s,i[0]),X.div(s,i[1]),X.div(s,i[2])],c=[X.mul(a[0],x[0]),X.mul(a[1],x[1]),X.mul(a[2],x[2])],l=X.stack([c[0],c[1],c[2]],2),y=X.reshape(l,[1,t.shape[0],t.shape[1],3]);return X.dispose([...o,...n,...r,...a,...i,...x,...c,l,t]),y}var L2=3840,q=null,l0=null,Ue=null,e0,ae={inputSum:0,cacheDiff:1,sumMethod:0,inputTensor:void 0};function R0(e,t){let o;if(v.browser)if(v.worker){if(typeof OffscreenCanvas=="undefined")throw new Error("canvas error: attempted to run in web worker but OffscreenCanvas is not supported");o=new OffscreenCanvas(e,t)}else{if(typeof document=="undefined")throw new Error("canvas error: attempted to run in browser but DOM is not defined");o=document.createElement("canvas"),o.width=e,o.height=t}else typeof v.Canvas!="undefined"?o=new v.Canvas(e,t):typeof globalThis.Canvas!="undefined"&&(o=new globalThis.Canvas(e,t));return o}function W2(e,t){let o=t||R0(e.width,e.height);return o.getContext("2d").drawImage(e,0,0),o}async function Ye(e,t,o=!0){if(!e)return t.debug&&p("input error: input is missing"),{tensor:null,canvas:null};if(!(e instanceof O.Tensor)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(typeof v.Canvas!="undefined"&&e instanceof v.Canvas)&&!(typeof globalThis.Canvas!="undefined"&&e instanceof globalThis.Canvas)&&!(typeof ImageData!="undefined"&&e instanceof ImageData)&&!(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)&&!(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)&&!(typeof HTMLMediaElement!="undefined"&&e instanceof HTMLMediaElement)&&!(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)&&!(typeof HTMLCanvasElement!="undefined"&&e instanceof HTMLCanvasElement)&&!(typeof OffscreenCanvas!="undefined"&&e instanceof OffscreenCanvas))throw new Error("input error: type is not recognized");if(e instanceof O.Tensor){let n=null;if(e.isDisposedInternal)throw new Error("input error: attempted to use tensor but it is disposed");if(!e.shape)throw new Error("input error: attempted to use tensor without a shape");if(e.shape.length===3){if(e.shape[2]===3)n=O.expandDims(e,0);else if(e.shape[2]===4){let r=O.slice3d(e,[0,0,0],[-1,-1,3]);n=O.expandDims(r,0),O.dispose(r)}}else e.shape.length===4&&(e.shape[3]===3?n=O.clone(e):e.shape[3]===4&&(n=O.slice4d(e,[0,0,0,0],[-1,-1,-1,3])));if(n==null||n.shape.length!==4||n.shape[0]!==1||n.shape[3]!==3)throw new Error(`input error: attempted to use tensor with unrecognized shape: ${e.shape}`);if(n.dtype==="int32"){let r=O.cast(n,"float32");O.dispose(n),n=r}return{tensor:n,canvas:t.filter.return?l0:null}}else{if(typeof e.readyState!="undefined"&&e.readyState<=2)return t.debug&&p("input stream is not ready"),{tensor:null,canvas:q};let n=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,r=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0;if(!n||!r)return t.debug&&p("cannot determine input dimensions"),{tensor:null,canvas:q};let A=n,s=r;if(A>L2&&(A=L2,s=Math.trunc(A*r/n)),s>L2&&(s=L2,A=Math.trunc(s*n/r)),(t.filter.width||0)>0?A=t.filter.width:(t.filter.height||0)>0&&(A=n*((t.filter.height||0)/r)),(t.filter.height||0)>0?s=t.filter.height:(t.filter.width||0)>0&&(s=r*((t.filter.width||0)/n)),!A||!s)throw new Error("input error: cannot determine dimension");(!q||(q==null?void 0:q.width)!==A||(q==null?void 0:q.height)!==s)&&(q=R0(A,s));let a=q.getContext("2d");if(typeof ImageData!="undefined"&&e instanceof ImageData?a.putImageData(e,0,0):t.filter.flip&&typeof a.translate!="undefined"?(a.translate(n,0),a.scale(-1,1),a.drawImage(e,0,0,n,r,0,0,q==null?void 0:q.width,q==null?void 0:q.height),a.setTransform(1,0,0,1,0,0)):a.drawImage(e,0,0,n,r,0,0,q==null?void 0:q.width,q==null?void 0:q.height),(!l0||q.width!==l0.width||(q==null?void 0:q.height)!==(l0==null?void 0:l0.height))&&(l0=R0(q.width,q.height)),t.filter.enabled&&v.webgl.supported?(e0||(e0=v.browser?new vt:null),v.filter=!!e0,!e0||!e0.add?(t.debug&&p("input process error: cannot initialize filters"),v.webgl.supported=!1,t.filter.enabled=!1,W2(q,l0)):(e0.reset(),t.filter.brightness!==0&&e0.add("brightness",t.filter.brightness),t.filter.contrast!==0&&e0.add("contrast",t.filter.contrast),t.filter.sharpness!==0&&e0.add("sharpen",t.filter.sharpness),t.filter.blur!==0&&e0.add("blur",t.filter.blur),t.filter.saturation!==0&&e0.add("saturation",t.filter.saturation),t.filter.hue!==0&&e0.add("hue",t.filter.hue),t.filter.negative&&e0.add("negative"),t.filter.sepia&&e0.add("sepia"),t.filter.vintage&&e0.add("brownie"),t.filter.sepia&&e0.add("sepia"),t.filter.kodachrome&&e0.add("kodachrome"),t.filter.technicolor&&e0.add("technicolor"),t.filter.polaroid&&e0.add("polaroid"),t.filter.pixelate!==0&&e0.add("pixelate",t.filter.pixelate),e0.get()>0?l0=e0.apply(q):l0=e0.draw(q))):(W2(q,l0),e0&&(e0=null),v.filter=!!e0),!o)return{tensor:null,canvas:l0};if(!l0)throw new Error("canvas error: cannot create output");let i,x=3;if(typeof ImageData!="undefined"&&e instanceof ImageData||e.data&&e.width&&e.height)if(v.browser&&O.browser)i=O.browser?O.browser.fromPixels(e):null;else{x=e.data.length/e.height/e.width;let y=new Uint8Array(e.data.buffer);i=O.tensor(y,[e.height,e.width,x],"int32")}else if((!Ue||l0.width!==Ue.width||l0.height!==Ue.height)&&(Ue=R0(l0.width,l0.height)),O.browser&&v.browser)t.backend==="webgl"||t.backend==="humangl"||t.backend==="webgpu"?i=O.browser.fromPixels(l0):(Ue=W2(l0),i=O.browser.fromPixels(Ue));else{let u=W2(l0).getContext("2d").getImageData(0,0,A,s);x=u.data.length/A/s;let m=new Uint8Array(u.data.buffer);i=O.tensor(m,[A,s,x])}if(x===4){let y=O.slice3d(i,[0,0,0],[-1,-1,3]);O.dispose(i),i=y}if(!i)throw new Error("input error: cannot create tensor");let c=O.cast(i,"float32"),l=t.filter.equalization?await N2(c):O.expandDims(c,0);return O.dispose([i,c]),{tensor:l,canvas:t.filter.return?l0:null}}}async function Tt(e,t){let o=!1;if(e.cacheSensitivity===0||!t.shape||t.shape.length!==4||t.shape[1]>2048||t.shape[2]>2048)return o;if(!ae.inputTensor)ae.inputTensor=O.clone(t);else if(ae.inputTensor.shape[1]!==t.shape[1]||ae.inputTensor.shape[2]!==t.shape[2])O.dispose(ae.inputTensor),ae.inputTensor=O.clone(t);else{let n={};n.diff=O.sub(t,ae.inputTensor),n.squared=O.mul(n.diff,n.diff),n.sum=O.sum(n.squared);let A=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;O.dispose([ae.inputTensor,n.diff,n.squared,n.sum]),ae.inputTensor=O.clone(t),o=A<=(e.cacheSensitivity||0)}return o}async function wt(e,t,o){let n={};if(!t||!o||t.shape.length!==4||t.shape.length!==o.shape.length)return e.debug||p("invalid input tensor or tensor shapes do not match:",t.shape,o.shape),0;if(t.shape[0]!==1||o.shape[0]!==1||t.shape[3]!==3||o.shape[3]!==3)return e.debug||p("input tensors must be of shape [1, height, width, 3]:",t.shape,o.shape),0;n.input1=O.clone(t),n.input2=t.shape[1]!==o.shape[1]||t.shape[2]!==o.shape[2]?O.image.resizeBilinear(o,[t.shape[1],t.shape[2]]):O.clone(o),n.diff=O.sub(n.input1,n.input2),n.squared=O.mul(n.diff,n.diff),n.sum=O.sum(n.squared);let A=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;return O.dispose([n.input1,n.input2,n.diff,n.squared,n.sum]),A}var j5=class{constructor(){T(this,"browser");T(this,"node");T(this,"worker");T(this,"platform","");T(this,"agent","");T(this,"backends",[]);T(this,"initial");T(this,"filter");T(this,"tfjs");T(this,"offscreen");T(this,"perfadd",!1);T(this,"wasm",{supported:void 0,backend:void 0,simd:void 0,multithread:void 0});T(this,"webgl",{supported:void 0,backend:void 0,version:void 0,renderer:void 0});T(this,"webgpu",{supported:void 0,backend:void 0,adapter:void 0});T(this,"cpu",{model:void 0,flags:[]});T(this,"kernels",[]);T(this,"Canvas");T(this,"Image");T(this,"ImageData");if(this.browser=typeof navigator!="undefined",this.node=typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined",this.tfjs={version:p0.version["tfjs-core"]},this.offscreen=typeof OffscreenCanvas!="undefined",this.initial=!0,this.worker=this.browser&&this.offscreen?typeof WorkerGlobalScope!="undefined":void 0,typeof navigator!="undefined"){let t=navigator.userAgent.match(/\(([^()]+)\)/g);if(t&&t[0]){let o=t[0].match(/\(([^()]+)\)/g);this.platform=o&&o[0]?o[0].replace(/\(|\)/g,""):"",this.agent=navigator.userAgent.replace(t[0],""),this.platform[1]&&(this.agent=this.agent.replace(t[1],"")),this.agent=this.agent.replace(/  /g," ")}}else typeof process!="undefined"&&(this.platform=`${process.platform} ${process.arch}`,this.agent=`NodeJS ${process.version}`)}async updateBackend(){this.backends=Object.keys(p0.engine().registryFactory),this.wasm.supported=typeof WebAssembly!="undefined",this.wasm.backend=this.backends.includes("wasm"),this.wasm.supported&&this.wasm.backend&&p0.getBackend()==="wasm"&&(this.wasm.simd=await p0.env().getAsync("WASM_HAS_SIMD_SUPPORT"),this.wasm.multithread=await p0.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT"));let t=R0(100,100),o=t?t.getContext("webgl2"):void 0;if(this.webgl.supported=typeof o!="undefined",this.webgl.backend=this.backends.includes("webgl"),this.webgl.supported&&this.webgl.backend&&(p0.getBackend()==="webgl"||p0.getBackend()==="humangl")){let n=p0.backend().gpgpu!=="undefined"?await p0.backend().getGPGPUContext().gl:null;n&&(this.webgl.version=n.getParameter(n.VERSION),this.webgl.renderer=n.getParameter(n.RENDERER))}this.webgpu.supported=this.browser&&typeof navigator.gpu!="undefined",this.webgpu.backend=this.backends.includes("webgpu");try{this.webgpu.supported&&(this.webgpu.adapter=(await navigator.gpu.requestAdapter()).name)}catch(n){this.webgpu.supported=!1}try{this.kernels=p0.getKernelsForBackend(p0.getBackend()).map(n=>n.kernelName.toLowerCase())}catch(n){}}async updateCPU(){let t={model:"",flags:[]};this.node&&this.platform.startsWith("linux"),this.cpu?this.cpu=t:Object.defineProperty(this,"cpu",{value:t})}},v=new j5;var F2=Z(D());var O5={};ue(O5,{age:()=>Pn,antispoof:()=>Rn,blazeface:()=>wn,"blazeface-back":()=>vn,"blazeface-front":()=>Tn,"blazepose-detector2d":()=>kn,"blazepose-detector3d":()=>En,"blazepose-full":()=>zn,"blazepose-heavy":()=>Sn,"blazepose-lite":()=>Cn,default:()=>yr,efficientpose:()=>In,emotion:()=>jn,faceboxes:()=>On,facemesh:()=>Bn,"facemesh-attention":()=>Ln,"facemesh-attention-alt":()=>Nn,"facemesh-detection-full":()=>Wn,"facemesh-detection-short":()=>Fn,"facemesh-orig":()=>Gn,faceres:()=>Vn,"faceres-deep":()=>Hn,gear:()=>Dn,gender:()=>Xn,"gender-ssrnet-imdb":()=>Zn,handdetect:()=>qn,"handlandmark-full":()=>Un,"handlandmark-lite":()=>Yn,"handlandmark-sparse":()=>Kn,handskeleton:()=>Jn,handtrack:()=>Qn,iris:()=>_n,liveness:()=>$n,"mb3-centernet":()=>er,meet:()=>tr,mobileface:()=>or,mobilefacenet:()=>nr,"movenet-lightning":()=>rr,"movenet-multipose":()=>Ar,"movenet-thunder":()=>sr,nanodet:()=>ar,posenet:()=>ir,selfie:()=>lr});var Pn=161240,Rn=853098,vn=538928,Tn=402048,wn=538928,kn=7499400,En=5928856,zn=6338290,Sn=27501554,Cn=2725490,In=5651240,jn=820516,On=2013002,Nn=2387598,Ln=2382414,Wn=1026192,Fn=201268,Gn=2955780,Bn=1477958,Hn=13957620,Vn=6978814,Dn=1498916,Zn=161236,Xn=201808,qn=3515612,Un=5431368,Yn=2023432,Kn=5286322,Jn=5502280,Qn=2964837,_n=2599092,$n=592976,er=4030290,tr=372228,or=2183192,nr=5171976,rr=4650216,Ar=9448838,sr=12477112,ar=7574558,ir=5032780,lr=212886,yr={age:Pn,antispoof:Rn,"blazeface-back":vn,"blazeface-front":Tn,blazeface:wn,"blazepose-detector2d":kn,"blazepose-detector3d":En,"blazepose-full":zn,"blazepose-heavy":Sn,"blazepose-lite":Cn,efficientpose:In,emotion:jn,faceboxes:On,"facemesh-attention-alt":Nn,"facemesh-attention":Ln,"facemesh-detection-full":Wn,"facemesh-detection-short":Fn,"facemesh-orig":Gn,facemesh:Bn,"faceres-deep":Hn,faceres:Vn,gear:Dn,"gender-ssrnet-imdb":Zn,gender:Xn,handdetect:qn,"handlandmark-full":Un,"handlandmark-lite":Yn,"handlandmark-sparse":Kn,handskeleton:Jn,handtrack:Qn,iris:_n,liveness:$n,"mb3-centernet":er,meet:tr,mobileface:or,mobilefacenet:nr,"movenet-lightning":rr,"movenet-multipose":Ar,"movenet-thunder":sr,nanodet:ar,posenet:ir,selfie:lr};var v0={cacheModels:!0,cacheSupported:!0,verbose:!0,debug:!1,modelBasePath:""},q0={};async function xr(e,t){return v0.debug&&p("load model fetch:",e,t),fetch(e,t)}function kt(e){v0.cacheModels=e.cacheModels,v0.verbose=e.debug,v0.modelBasePath=e.modelBasePath}async function G(e){var x,c,l;let t=mt(v0.modelBasePath,e||"");t.toLowerCase().endsWith(".json")||(t+=".json");let o=t.includes("/")?t.split("/"):t.split("\\"),n=o[o.length-1].replace(".json",""),r="indexeddb://"+n;q0[n]={name:n,sizeFromManifest:0,sizeLoadedWeights:0,sizeDesired:O5[n],inCache:!1},v0.cacheSupported=typeof window!="undefined"&&typeof window.localStorage!="undefined"&&typeof window.indexedDB!="undefined";let A={};try{A=v0.cacheSupported&&v0.cacheModels?await F2.io.listModels():{}}catch(y){v0.cacheSupported=!1}q0[n].inCache=v0.cacheSupported&&v0.cacheModels&&Object.keys(A).includes(r);let s=typeof fetch=="undefined"?{}:{fetchFunc:(y,f)=>xr(y,f)},a=new F2.GraphModel(q0[n].inCache?r:t,s),i=!1;try{a.findIOHandler(),v0.debug&&p("model load handler:",a.handler);let y=await a.handler.load();q0[n].sizeFromManifest=((x=y==null?void 0:y.weightData)==null?void 0:x.byteLength)||0,a.loadSync(y),q0[n].sizeLoadedWeights=((l=(c=a==null?void 0:a.artifacts)==null?void 0:c.weightData)==null?void 0:l.byteLength)||0,v0.verbose&&p("load model:",a.modelUrl,{bytes:q0[n].sizeLoadedWeights},v0),i=!0}catch(y){p("error loading model:",t,y)}if(i&&v0.cacheModels&&v0.cacheSupported&&!q0[n].inCache)try{let y=await a.save(r);p("model saved:",r,y)}catch(y){p("error saving model:",t,y)}return a}var ee=Z(D());var N5="2.9.1";var s0=Z(D());var R5={};ue(R5,{Models:()=>C2,getModelStats:()=>q1,load:()=>U1,reset:()=>P5,validate:()=>Y1});var G2=Z(D());var D0,L5=[],fr=["white","black","asian","indian","other"],mr=[15,23,28,35.5,45.5,55.5,65],Et=0,zt=0,W5=Number.MAX_SAFE_INTEGER;async function St(e){var t;return v.initial&&(D0=null),D0?e.debug&&p("cached model:",D0.modelUrl):D0=await G((t=e.face.gear)==null?void 0:t.modelPath),D0}async function F5(e,t,o,n){var s,a;if(!D0)return{age:0,gender:"unknown",genderScore:0,race:[]};let r=W5<(((s=t.face.gear)==null?void 0:s.skipFrames)||0),A=(((a=t.face.gear)==null?void 0:a.skipTime)||0)>h()-zt;return t.skipAllowed&&A&&r&&Et===n&&L5[o]?(W5++,L5[o]):(W5=0,new Promise(async i=>{var g,b;if(!(D0!=null&&D0.inputs[0].shape))return;let x={},c=[[0,.1,.9,.9]];x.resize=G2.image.cropAndResize(e,c,[0],[D0.inputs[0].shape[2],D0.inputs[0].shape[1]]);let l={age:0,gender:"unknown",genderScore:0,race:[]};(g=t.face.gear)!=null&&g.enabled&&([x.age,x.gender,x.race]=D0.execute(x.resize,["age_output","gender_output","race_output"]));let y=await x.gender.data();l.gender=y[0]>y[1]?"male":"female",l.genderScore=Math.round(100*(y[0]>y[1]?y[0]:y[1]))/100;let f=await x.race.data();for(let d=0;d<f.length;d++)f[d]>(((b=t.face.gear)==null?void 0:b.minConfidence)||.2)&&l.race.push({score:Math.round(100*f[d])/100,race:fr[d]});l.race.sort((d,M)=>M.score-d.score);let m=Array.from(await x.age.data()).map((d,M)=>[mr[M],d]).sort((d,M)=>M[1]-d[1]),P=m[0][0];for(let d=1;d<m.length;d++)P+=m[d][1]*(m[d][0]-P);l.age=Math.round(10*P)/10,Object.keys(x).forEach(d=>G2.dispose(x[d])),L5[o]=l,Et=n,zt=h(),i(l)}))}var Ke=Z(D());var be=Z(D()),V={tf255:255,tf1:1,tf2:2,tf05:.5,tf127:127.5,rgb:[.2989,.587,.114]};function It(){V.tf255=be.scalar(255,"float32"),V.tf1=be.scalar(1,"float32"),V.tf2=be.scalar(2,"float32"),V.tf05=be.scalar(.5,"float32"),V.tf127=be.scalar(127.5,"float32"),V.rgb=be.tensor1d([.2989,.587,.114],"float32")}var S0,B2=[],jt=0,Ot=0,G5=Number.MAX_SAFE_INTEGER;async function Nt(e){return v.initial&&(S0=null),S0?e.debug&&p("cached model:",S0.modelUrl):S0=await G(e.face.ssrnet.modelPathAge),S0}async function B5(e,t,o,n){var s,a,i,x;if(!S0)return{age:0};let r=G5<(((s=t.face.ssrnet)==null?void 0:s.skipFrames)||0),A=(((a=t.face.ssrnet)==null?void 0:a.skipTime)||0)>h()-Ot;return t.skipAllowed&&r&&A&&jt===n&&((i=B2[o])==null?void 0:i.age)&&((x=B2[o])==null?void 0:x.age)>0?(G5++,B2[o]):(G5=0,new Promise(async c=>{if(!(S0!=null&&S0.inputs)||!S0.inputs[0]||!S0.inputs[0].shape)return;let l={};l.resize=Ke.image.resizeBilinear(e,[S0.inputs[0].shape[2],S0.inputs[0].shape[1]],!1),l.enhance=Ke.mul(l.resize,V.tf255);let y={age:0};if(t.face.ssrnet.enabled&&(l.age=S0.execute(l.enhance)),l.age){let f=await l.age.data();y.age=Math.trunc(10*f[0])/10}Object.keys(l).forEach(f=>Ke.dispose(l[f])),B2[o]=y,jt=n,Ot=h(),c(y)}))}var u0=Z(D());var Z0,H2=[],Wt=0,Ft=0,H5=Number.MAX_SAFE_INTEGER,V5=[.2989,.587,.114];async function Gt(e){return v.initial&&(Z0=null),Z0?e.debug&&p("cached model:",Z0.modelUrl):Z0=await G(e.face.ssrnet.modelPathGender),Z0}async function D5(e,t,o,n){var s,a,i,x;if(!Z0)return{gender:"unknown",genderScore:0};let r=H5<(((s=t.face.ssrnet)==null?void 0:s.skipFrames)||0),A=(((a=t.face.ssrnet)==null?void 0:a.skipTime)||0)>h()-Ft;return t.skipAllowed&&r&&A&&Wt===n&&((i=H2[o])==null?void 0:i.gender)&&((x=H2[o])==null?void 0:x.genderScore)>0?(H5++,H2[o]):(H5=0,new Promise(async c=>{if(!(Z0!=null&&Z0.inputs[0].shape))return;let l={};l.resize=u0.image.resizeBilinear(e,[Z0.inputs[0].shape[2],Z0.inputs[0].shape[1]],!1),l.enhance=u0.tidy(()=>{let[u,m,P]=u0.split(l.resize,3,3),g=u0.mul(u,V5[0]),b=u0.mul(m,V5[1]),d=u0.mul(P,V5[2]),M=u0.addN([g,b,d]);return u0.mul(u0.sub(M,V.tf05),2)});let y={gender:"unknown",genderScore:0};t.face.ssrnet.enabled&&(l.gender=Z0.execute(l.enhance));let f=await l.gender.data();y.gender=f[0]>f[1]?"female":"male",y.genderScore=f[0]>f[1]?Math.trunc(100*f[0])/100:Math.trunc(100*f[1])/100,Object.keys(l).forEach(u=>u0.dispose(l[u])),H2[o]=y,Wt=n,Ft=h(),c(y)}))}var D2=Z(D());var h0,V2=[],Z5=Number.MAX_SAFE_INTEGER,Ht=0,Vt=0;async function Dt(e){var t;return v.initial&&(h0=null),h0?e.debug&&p("cached model:",h0.modelUrl):h0=await G((t=e.face.antispoof)==null?void 0:t.modelPath),h0}async function X5(e,t,o,n){var s,a;if(!h0)return 0;let r=(((s=t.face.antispoof)==null?void 0:s.skipTime)||0)>h()-Vt,A=Z5<(((a=t.face.antispoof)==null?void 0:a.skipFrames)||0);return t.skipAllowed&&r&&A&&Ht===n&&V2[o]?(Z5++,V2[o]):(Z5=0,new Promise(async i=>{let x=D2.image.resizeBilinear(e,[h0!=null&&h0.inputs[0].shape?h0.inputs[0].shape[2]:0,h0!=null&&h0.inputs[0].shape?h0.inputs[0].shape[1]:0],!1),c=h0==null?void 0:h0.execute(x),l=(await c.data())[0];V2[o]=Math.round(100*l)/100,Ht=n,Vt=h(),D2.dispose([x,c]),i(V2[o])}))}var N=Z(D());var ie=Z(D());var X0={silhouette:[10,338,297,332,284,251,389,356,454,323,361,288,397,365,379,378,400,377,152,148,176,149,150,136,172,58,132,93,234,127,162,21,54,103,67,109],lipsUpperOuter:[185,40,39,37,0,267,269,270,409],lipsLowerOuter:[61,146,91,181,84,17,314,405,321,375,291],lipsUpperInner:[191,80,81,82,13,312,311,310,415],lipsLowerInner:[78,95,88,178,87,14,317,402,318,324,308],lipsLowerSemiOuter:[76,77,90,180,85,16,315,404,320,307,306],lipsUpperSemiOuter:[184,74,73,72,11,302,303,304,408],lipsLowerSemiInner:[62,96,89,179,86,15,316,403,319,325,292],lipsUpperSemiInner:[183,42,41,38,12,268,271,272,407],rightEyeUpper0:[246,161,160,159,158,157,173],rightEyeLower0:[33,7,163,144,145,153,154,155,133],rightEyeUpper1:[247,30,29,27,28,56,190],rightEyeLower1:[130,25,110,24,23,22,26,112,243],rightEyeUpper2:[113,225,224,223,222,221,189],rightEyeLower2:[226,31,228,229,230,231,232,233,244],rightEyeLower3:[143,111,117,118,119,120,121,128,245],rightEyebrowUpper:[156,70,63,105,66,107,55,193],rightEyebrowLower:[35,124,46,53,52,65],rightEyeIris:[473,474,475,476,477],leftEyeUpper0:[466,388,387,386,385,384,398],leftEyeLower0:[263,249,390,373,374,380,381,382,362],leftEyeUpper1:[467,260,259,257,258,286,414],leftEyeLower1:[359,255,339,254,253,252,256,341,463],leftEyeUpper2:[342,445,444,443,442,441,413],leftEyeLower2:[446,261,448,449,450,451,452,453,464],leftEyeLower3:[372,340,346,347,348,349,350,357,465],leftEyebrowUpper:[383,300,293,334,296,336,285,417],leftEyebrowLower:[265,353,276,283,282,295],leftEyeIris:[468,469,470,471,472],midwayBetweenEyes:[168],noseTip:[1],noseBottom:[2],noseRightCorner:[98],noseLeftCorner:[327],rightCheek:[205],leftCheek:[425]},q5={count:468,mouth:13,symmetryLine:[13,X0.midwayBetweenEyes[0]]},je={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},U5=[{key:"EyeUpper0",indices:[9,10,11,12,13,14,15]},{key:"EyeUpper1",indices:[25,26,27,28,29,30,31]},{key:"EyeUpper2",indices:[41,42,43,44,45,46,47]},{key:"EyeLower0",indices:[0,1,2,3,4,5,6,7,8]},{key:"EyeLower1",indices:[16,17,18,19,20,21,22,23,24]},{key:"EyeLower2",indices:[32,33,34,35,36,37,38,39,40]},{key:"EyeLower3",indices:[54,55,56,57,58,59,60,61,62]},{key:"EyebrowUpper",indices:[63,64,65,66,67,68,69,70]},{key:"EyebrowLower",indices:[48,49,50,51,52,53]}],R2=[[.499976992607117,.652534008026123],[.500025987625122,.547487020492554],[.499974012374878,.602371990680695],[.482113003730774,.471979022026062],[.500150978565216,.527155995368958],[.499909996986389,.498252987861633],[.499523013830185,.40106201171875],[.289712011814117,.380764007568359],[.499954998493195,.312398016452789],[.499987006187439,.269918978214264],[.500023007392883,.107050001621246],[.500023007392883,.666234016418457],[.5000159740448,.679224014282227],[.500023007392883,.692348003387451],[.499976992607117,.695277988910675],[.499976992607117,.70593398809433],[.499976992607117,.719385027885437],[.499976992607117,.737019002437592],[.499967992305756,.781370997428894],[.499816000461578,.562981009483337],[.473773002624512,.573909997940063],[.104906998574734,.254140973091125],[.365929991006851,.409575998783112],[.338757991790771,.41302502155304],[.311120003461838,.409460008144379],[.274657994508743,.389131009578705],[.393361985683441,.403706014156342],[.345234006643295,.344011008739471],[.370094001293182,.346076011657715],[.319321990013123,.347265005111694],[.297903001308441,.353591024875641],[.24779200553894,.410809993743896],[.396889001131058,.842755019664764],[.280097991228104,.375599980354309],[.106310002505779,.399955987930298],[.2099249958992,.391353011131287],[.355807989835739,.534406006336212],[.471751004457474,.65040397644043],[.474155008792877,.680191993713379],[.439785003662109,.657229006290436],[.414617002010345,.66654098033905],[.450374007225037,.680860996246338],[.428770989179611,.682690978050232],[.374971002340317,.727805018424988],[.486716985702515,.547628998756409],[.485300987958908,.527395009994507],[.257764995098114,.314490020275116],[.401223003864288,.455172002315521],[.429818987846375,.548614978790283],[.421351999044418,.533740997314453],[.276895999908447,.532056987285614],[.483370006084442,.499586999416351],[.33721199631691,.282882988452911],[.296391993761063,.293242990970612],[.169294998049736,.193813979625702],[.447580009698868,.302609980106354],[.392390012741089,.353887975215912],[.354490011930466,.696784019470215],[.067304998636246,.730105042457581],[.442739009857178,.572826027870178],[.457098007202148,.584792017936707],[.381974011659622,.694710969924927],[.392388999462128,.694203019142151],[.277076005935669,.271932005882263],[.422551989555359,.563233017921448],[.385919004678726,.281364023685455],[.383103013038635,.255840003490448],[.331431001424789,.119714021682739],[.229923993349075,.232002973556519],[.364500999450684,.189113974571228],[.229622006416321,.299540996551514],[.173287004232407,.278747975826263],[.472878992557526,.666198015213013],[.446828007698059,.668527007102966],[.422762006521225,.673889994621277],[.445307999849319,.580065965652466],[.388103008270264,.693961024284363],[.403039008378983,.706539988517761],[.403629004955292,.693953037261963],[.460041999816895,.557139039039612],[.431158006191254,.692366003990173],[.452181994915009,.692366003990173],[.475387006998062,.692366003990173],[.465828001499176,.779190003871918],[.472328990697861,.736225962638855],[.473087012767792,.717857003211975],[.473122000694275,.704625964164734],[.473033010959625,.695277988910675],[.427942007780075,.695277988910675],[.426479011774063,.703539967536926],[.423162013292313,.711845993995667],[.4183090031147,.720062971115112],[.390094995498657,.639572978019714],[.013953999616206,.560034036636353],[.499913990497589,.58014702796936],[.413199990987778,.69539999961853],[.409626007080078,.701822996139526],[.468080013990402,.601534962654114],[.422728985548019,.585985004901886],[.463079988956451,.593783974647522],[.37211999297142,.47341400384903],[.334562003612518,.496073007583618],[.411671012639999,.546965003013611],[.242175996303558,.14767599105835],[.290776997804642,.201445996761322],[.327338010072708,.256527006626129],[.399509996175766,.748921036720276],[.441727995872498,.261676013469696],[.429764986038208,.187834024429321],[.412198007106781,.108901023864746],[.288955003023148,.398952007293701],[.218936994671822,.435410976409912],[.41278201341629,.398970007896423],[.257135003805161,.355440020561218],[.427684992551804,.437960982322693],[.448339998722076,.536936044692993],[.178560003638268,.45755398273468],[.247308000922203,.457193970680237],[.286267012357712,.467674970626831],[.332827985286713,.460712015628815],[.368755996227264,.447206974029541],[.398963987827301,.432654976844788],[.476410001516342,.405806005001068],[.189241006970406,.523923993110657],[.228962004184723,.348950982093811],[.490725994110107,.562400996685028],[.404670000076294,.485132992267609],[.019469000399113,.401564002037048],[.426243007183075,.420431017875671],[.396993011236191,.548797011375427],[.266469985246658,.376977026462555],[.439121007919312,.51895797252655],[.032313998788595,.644356966018677],[.419054001569748,.387154996395111],[.462783008813858,.505746960639954],[.238978996872902,.779744982719421],[.198220998048782,.831938028335571],[.107550002634525,.540755033493042],[.183610007166862,.740257024765015],[.134409993886948,.333683013916016],[.385764002799988,.883153975009918],[.490967005491257,.579378008842468],[.382384985685349,.508572995662689],[.174399003386497,.397670984268188],[.318785011768341,.39623498916626],[.343364000320435,.400596976280212],[.396100014448166,.710216999053955],[.187885001301765,.588537991046906],[.430987000465393,.944064974784851],[.318993002176285,.898285031318665],[.266247987747192,.869701027870178],[.500023007392883,.190576016902924],[.499976992607117,.954452991485596],[.366169989109039,.398822009563446],[.393207013607025,.39553701877594],[.410373002290726,.391080021858215],[.194993004202843,.342101991176605],[.388664990663528,.362284004688263],[.365961998701096,.355970978736877],[.343364000320435,.355356991291046],[.318785011768341,.35834002494812],[.301414996385574,.363156020641327],[.058132998645306,.319076001644135],[.301414996385574,.387449026107788],[.499987989664078,.618434011936188],[.415838003158569,.624195992946625],[.445681989192963,.566076993942261],[.465844005346298,.620640993118286],[.49992299079895,.351523995399475],[.288718998432159,.819945991039276],[.335278987884521,.852819979190826],[.440512001514435,.902418971061707],[.128294005990028,.791940987110138],[.408771991729736,.373893976211548],[.455606997013092,.451801002025604],[.499877005815506,.908990025520325],[.375436991453171,.924192011356354],[.11421000212431,.615022003650665],[.448662012815475,.695277988910675],[.4480200111866,.704632043838501],[.447111994028091,.715808033943176],[.444831997156143,.730794012546539],[.430011987686157,.766808986663818],[.406787008047104,.685672998428345],[.400738000869751,.681069016456604],[.392399996519089,.677703022956848],[.367855995893478,.663918972015381],[.247923001646996,.601333022117615],[.452769994735718,.420849978923798],[.43639200925827,.359887003898621],[.416164010763168,.368713974952698],[.413385987281799,.692366003990173],[.228018000721931,.683571994304657],[.468268007040024,.352671027183533],[.411361992359161,.804327011108398],[.499989002943039,.469825029373169],[.479153990745544,.442654013633728],[.499974012374878,.439637005329132],[.432112008333206,.493588984012604],[.499886006116867,.866917014122009],[.49991300702095,.821729004383087],[.456548988819122,.819200992584229],[.344549000263214,.745438992977142],[.37890899181366,.574010014533997],[.374292999505997,.780184984207153],[.319687992334366,.570737957954407],[.357154995203018,.604269981384277],[.295284003019333,.621580958366394],[.447750002145767,.862477004528046],[.410986006259918,.508723020553589],[.31395098567009,.775308012962341],[.354128003120422,.812552988529205],[.324548006057739,.703992962837219],[.189096003770828,.646299958229065],[.279776990413666,.71465802192688],[.1338230073452,.682700991630554],[.336768001317978,.644733011722565],[.429883986711502,.466521978378296],[.455527991056442,.548622965812683],[.437114000320435,.558896005153656],[.467287987470627,.529924988746643],[.414712011814117,.335219979286194],[.37704598903656,.322777986526489],[.344107985496521,.320150971412659],[.312875986099243,.32233202457428],[.283526003360748,.333190023899078],[.241245999932289,.382785975933075],[.102986000478268,.468762993812561],[.267612010240555,.424560010433197],[.297879010438919,.433175981044769],[.333433985710144,.433878004550934],[.366427004337311,.426115989685059],[.396012008190155,.416696012020111],[.420121014118195,.41022801399231],[.007561000064015,.480777025222778],[.432949006557465,.569517970085144],[.458638995885849,.479089021682739],[.473466008901596,.545744001865387],[.476087987422943,.563830018043518],[.468472003936768,.555056989192963],[.433990985155106,.582361996173859],[.483518004417419,.562983989715576],[.482482999563217,.57784903049469],[.42645001411438,.389798998832703],[.438998997211456,.39649498462677],[.450067013502121,.400434017181396],[.289712011814117,.368252992630005],[.276670008897781,.363372981548309],[.517862021923065,.471948027610779],[.710287988185883,.380764007568359],[.526226997375488,.573909997940063],[.895093023777008,.254140973091125],[.634069979190826,.409575998783112],[.661242008209229,.41302502155304],[.688880026340485,.409460008144379],[.725341975688934,.389131009578705],[.606630027294159,.40370500087738],[.654766023159027,.344011008739471],[.629905998706818,.346076011657715],[.680678009986877,.347265005111694],[.702096998691559,.353591024875641],[.75221198797226,.410804986953735],[.602918028831482,.842862963676453],[.719901978969574,.375599980354309],[.893692970275879,.399959981441498],[.790081977844238,.391354024410248],[.643998026847839,.534487962722778],[.528249025344849,.65040397644043],[.525849997997284,.680191040039062],[.560214996337891,.657229006290436],[.585384011268616,.66654098033905],[.549625992774963,.680860996246338],[.57122802734375,.682691991329193],[.624852001667023,.72809898853302],[.513050019741058,.547281980514526],[.51509702205658,.527251958847046],[.742246985435486,.314507007598877],[.598631024360657,.454979002475739],[.570338010787964,.548575043678284],[.578631997108459,.533622980117798],[.723087012767792,.532054007053375],[.516445994377136,.499638974666595],[.662801027297974,.282917976379395],[.70362401008606,.293271005153656],[.830704987049103,.193813979625702],[.552385985851288,.302568018436432],[.607609987258911,.353887975215912],[.645429015159607,.696707010269165],[.932694971561432,.730105042457581],[.557260990142822,.572826027870178],[.542901992797852,.584792017936707],[.6180260181427,.694710969924927],[.607590973377228,.694203019142151],[.722943007946014,.271963000297546],[.577413976192474,.563166975975037],[.614082992076874,.281386971473694],[.616907000541687,.255886018276215],[.668509006500244,.119913995265961],[.770092010498047,.232020974159241],[.635536015033722,.189248979091644],[.77039098739624,.299556016921997],[.826722025871277,.278755009174347],[.527121007442474,.666198015213013],[.553171992301941,.668527007102966],[.577238023281097,.673889994621277],[.554691970348358,.580065965652466],[.611896991729736,.693961024284363],[.59696102142334,.706539988517761],[.596370995044708,.693953037261963],[.539958000183105,.557139039039612],[.568841993808746,.692366003990173],[.547818005084991,.692366003990173],[.52461302280426,.692366003990173],[.534089982509613,.779141008853912],[.527670979499817,.736225962638855],[.526912987232208,.717857003211975],[.526877999305725,.704625964164734],[.526966989040375,.695277988910675],[.572058022022247,.695277988910675],[.573521018028259,.703539967536926],[.57683801651001,.711845993995667],[.581691026687622,.720062971115112],[.609944999217987,.639909982681274],[.986046016216278,.560034036636353],[.5867999792099,.69539999961853],[.590372025966644,.701822996139526],[.531915009021759,.601536989212036],[.577268004417419,.585934996604919],[.536915004253387,.593786001205444],[.627542972564697,.473352015018463],[.665585994720459,.495950996875763],[.588353991508484,.546862006187439],[.757824003696442,.14767599105835],[.709249973297119,.201507985591888],[.672684013843536,.256581008434296],[.600408971309662,.74900496006012],[.55826598405838,.261672019958496],[.570303976535797,.187870979309082],[.588165998458862,.109044015407562],[.711045026779175,.398952007293701],[.781069993972778,.435405015945435],[.587247014045715,.398931980133057],[.742869973182678,.355445981025696],[.572156012058258,.437651991844177],[.55186802148819,.536570012569427],[.821442008018494,.457556009292603],[.752701997756958,.457181990146637],[.71375697851181,.467626988887787],[.66711300611496,.460672974586487],[.631101012229919,.447153985500336],[.6008620262146,.432473003864288],[.523481011390686,.405627012252808],[.810747981071472,.523926019668579],[.771045982837677,.348959028720856],[.509127020835876,.562718033790588],[.595292985439301,.485023975372314],[.980530977249146,.401564002037048],[.573499977588654,.420000016689301],[.602994978427887,.548687994480133],[.733529984951019,.376977026462555],[.560611009597778,.519016981124878],[.967685997486115,.644356966018677],[.580985009670258,.387160003185272],[.537728011608124,.505385041236877],[.760966002941132,.779752969741821],[.801778972148895,.831938028335571],[.892440974712372,.54076099395752],[.816350996494293,.740260004997253],[.865594983100891,.333687007427216],[.614073991775513,.883246004581451],[.508952975273132,.579437971115112],[.617941975593567,.508316040039062],[.825608015060425,.397674977779388],[.681214988231659,.39623498916626],[.656635999679565,.400596976280212],[.603900015354156,.710216999053955],[.81208598613739,.588539004325867],[.56801301240921,.944564998149872],[.681007981300354,.898285031318665],[.733752012252808,.869701027870178],[.633830010890961,.398822009563446],[.606792986392975,.39553701877594],[.589659988880157,.391062021255493],[.805015981197357,.342108011245728],[.611334979534149,.362284004688263],[.634037971496582,.355970978736877],[.656635999679565,.355356991291046],[.681214988231659,.35834002494812],[.698584973812103,.363156020641327],[.941866993904114,.319076001644135],[.698584973812103,.387449026107788],[.584177017211914,.624107003211975],[.554318010807037,.566076993942261],[.534153997898102,.62064003944397],[.711217999458313,.819975018501282],[.664629995822906,.852871000766754],[.559099972248077,.902631998062134],[.871706008911133,.791940987110138],[.591234028339386,.373893976211548],[.544341027736664,.451583981513977],[.624562978744507,.924192011356354],[.88577002286911,.615028977394104],[.551338016986847,.695277988910675],[.551980018615723,.704632043838501],[.552887976169586,.715808033943176],[.555167973041534,.730794012546539],[.569944024085999,.767035007476807],[.593203008174896,.685675978660583],[.599261999130249,.681069016456604],[.607599973678589,.677703022956848],[.631937980651855,.663500010967255],[.752032995223999,.601315021514893],[.547226011753082,.420395016670227],[.563543975353241,.359827995300293],[.583841025829315,.368713974952698],[.586614012718201,.692366003990173],[.771915018558502,.683578014373779],[.531597018241882,.352482974529266],[.588370978832245,.804440975189209],[.52079701423645,.442565023899078],[.567984998226166,.493479013442993],[.543282985687256,.819254994392395],[.655317008495331,.745514988899231],[.621008992195129,.574018001556396],[.625559985637665,.78031200170517],[.680198013782501,.570719003677368],[.64276397228241,.604337990283966],[.704662978649139,.621529996395111],[.552012026309967,.862591981887817],[.589071989059448,.508637011051178],[.685944974422455,.775357007980347],[.645735025405884,.812640011310577],[.675342977046967,.703978002071381],[.810858011245728,.646304965019226],[.72012197971344,.714666962623596],[.866151988506317,.682704985141754],[.663187026977539,.644596993923187],[.570082008838654,.466325998306274],[.544561982154846,.548375964164734],[.562758982181549,.558784961700439],[.531987011432648,.530140042304993],[.585271000862122,.335177004337311],[.622952997684479,.32277899980545],[.655896008014679,.320163011550903],[.687132000923157,.322345972061157],[.716481983661652,.333200991153717],[.758756995201111,.382786989212036],[.897013008594513,.468769013881683],[.732392013072968,.424547016620636],[.70211398601532,.433162987232208],[.66652500629425,.433866024017334],[.633504986763,.426087975502014],[.603875994682312,.416586995124817],[.579657971858978,.409945011138916],[.992439985275269,.480777025222778],[.567192018032074,.569419980049133],[.54136598110199,.478899002075195],[.526564002037048,.546118021011353],[.523913025856018,.563830018043518],[.531529009342194,.555056989192963],[.566035985946655,.582329034805298],[.51631098985672,.563053965568542],[.5174720287323,.577877044677734],[.573594987392426,.389806985855103],[.560697972774506,.395331978797913],[.549755990505219,.399751007556915],[.710287988185883,.368252992630005],[.723330020904541,.363372981548309]],Oe=[127,34,139,11,0,37,232,231,120,72,37,39,128,121,47,232,121,128,104,69,67,175,171,148,157,154,155,118,50,101,73,39,40,9,151,108,48,115,131,194,204,211,74,40,185,80,42,183,40,92,186,230,229,118,202,212,214,83,18,17,76,61,146,160,29,30,56,157,173,106,204,194,135,214,192,203,165,98,21,71,68,51,45,4,144,24,23,77,146,91,205,50,187,201,200,18,91,106,182,90,91,181,85,84,17,206,203,36,148,171,140,92,40,39,193,189,244,159,158,28,247,246,161,236,3,196,54,68,104,193,168,8,117,228,31,189,193,55,98,97,99,126,47,100,166,79,218,155,154,26,209,49,131,135,136,150,47,126,217,223,52,53,45,51,134,211,170,140,67,69,108,43,106,91,230,119,120,226,130,247,63,53,52,238,20,242,46,70,156,78,62,96,46,53,63,143,34,227,173,155,133,123,117,111,44,125,19,236,134,51,216,206,205,154,153,22,39,37,167,200,201,208,36,142,100,57,212,202,20,60,99,28,158,157,35,226,113,160,159,27,204,202,210,113,225,46,43,202,204,62,76,77,137,123,116,41,38,72,203,129,142,64,98,240,49,102,64,41,73,74,212,216,207,42,74,184,169,170,211,170,149,176,105,66,69,122,6,168,123,147,187,96,77,90,65,55,107,89,90,180,101,100,120,63,105,104,93,137,227,15,86,85,129,102,49,14,87,86,55,8,9,100,47,121,145,23,22,88,89,179,6,122,196,88,95,96,138,172,136,215,58,172,115,48,219,42,80,81,195,3,51,43,146,61,171,175,199,81,82,38,53,46,225,144,163,110,246,33,7,52,65,66,229,228,117,34,127,234,107,108,69,109,108,151,48,64,235,62,78,191,129,209,126,111,35,143,163,161,246,117,123,50,222,65,52,19,125,141,221,55,65,3,195,197,25,7,33,220,237,44,70,71,139,122,193,245,247,130,33,71,21,162,153,158,159,170,169,150,188,174,196,216,186,92,144,160,161,2,97,167,141,125,241,164,167,37,72,38,12,145,159,160,38,82,13,63,68,71,226,35,111,158,153,154,101,50,205,206,92,165,209,198,217,165,167,97,220,115,218,133,112,243,239,238,241,214,135,169,190,173,133,171,208,32,125,44,237,86,87,178,85,86,179,84,85,180,83,84,181,201,83,182,137,93,132,76,62,183,61,76,184,57,61,185,212,57,186,214,207,187,34,143,156,79,239,237,123,137,177,44,1,4,201,194,32,64,102,129,213,215,138,59,166,219,242,99,97,2,94,141,75,59,235,24,110,228,25,130,226,23,24,229,22,23,230,26,22,231,112,26,232,189,190,243,221,56,190,28,56,221,27,28,222,29,27,223,30,29,224,247,30,225,238,79,20,166,59,75,60,75,240,147,177,215,20,79,166,187,147,213,112,233,244,233,128,245,128,114,188,114,217,174,131,115,220,217,198,236,198,131,134,177,132,58,143,35,124,110,163,7,228,110,25,356,389,368,11,302,267,452,350,349,302,303,269,357,343,277,452,453,357,333,332,297,175,152,377,384,398,382,347,348,330,303,304,270,9,336,337,278,279,360,418,262,431,304,408,409,310,415,407,270,409,410,450,348,347,422,430,434,313,314,17,306,307,375,387,388,260,286,414,398,335,406,418,364,367,416,423,358,327,251,284,298,281,5,4,373,374,253,307,320,321,425,427,411,421,313,18,321,405,406,320,404,405,315,16,17,426,425,266,377,400,369,322,391,269,417,465,464,386,257,258,466,260,388,456,399,419,284,332,333,417,285,8,346,340,261,413,441,285,327,460,328,355,371,329,392,439,438,382,341,256,429,420,360,364,394,379,277,343,437,443,444,283,275,440,363,431,262,369,297,338,337,273,375,321,450,451,349,446,342,467,293,334,282,458,461,462,276,353,383,308,324,325,276,300,293,372,345,447,382,398,362,352,345,340,274,1,19,456,248,281,436,427,425,381,256,252,269,391,393,200,199,428,266,330,329,287,273,422,250,462,328,258,286,384,265,353,342,387,259,257,424,431,430,342,353,276,273,335,424,292,325,307,366,447,345,271,303,302,423,266,371,294,455,460,279,278,294,271,272,304,432,434,427,272,407,408,394,430,431,395,369,400,334,333,299,351,417,168,352,280,411,325,319,320,295,296,336,319,403,404,330,348,349,293,298,333,323,454,447,15,16,315,358,429,279,14,15,316,285,336,9,329,349,350,374,380,252,318,402,403,6,197,419,318,319,325,367,364,365,435,367,397,344,438,439,272,271,311,195,5,281,273,287,291,396,428,199,311,271,268,283,444,445,373,254,339,263,466,249,282,334,296,449,347,346,264,447,454,336,296,299,338,10,151,278,439,455,292,407,415,358,371,355,340,345,372,390,249,466,346,347,280,442,443,282,19,94,370,441,442,295,248,419,197,263,255,359,440,275,274,300,383,368,351,412,465,263,467,466,301,368,389,380,374,386,395,378,379,412,351,419,436,426,322,373,390,388,2,164,393,370,462,461,164,0,267,302,11,12,374,373,387,268,12,13,293,300,301,446,261,340,385,384,381,330,266,425,426,423,391,429,355,437,391,327,326,440,457,438,341,382,362,459,457,461,434,430,394,414,463,362,396,369,262,354,461,457,316,403,402,315,404,403,314,405,404,313,406,405,421,418,406,366,401,361,306,408,407,291,409,408,287,410,409,432,436,410,434,416,411,264,368,383,309,438,457,352,376,401,274,275,4,421,428,262,294,327,358,433,416,367,289,455,439,462,370,326,2,326,370,305,460,455,254,449,448,255,261,446,253,450,449,252,451,450,256,452,451,341,453,452,413,464,463,441,413,414,258,442,441,257,443,442,259,444,443,260,445,444,467,342,445,459,458,250,289,392,290,290,328,460,376,433,435,250,290,392,411,416,433,341,463,464,453,464,465,357,465,412,343,412,399,360,363,440,437,399,456,420,456,363,401,435,288,372,383,353,339,255,249,448,261,255,133,243,190,133,155,112,33,246,247,33,130,25,398,384,286,362,398,414,362,463,341,263,359,467,263,249,255,466,467,260,75,60,166,238,239,79,162,127,139,72,11,37,121,232,120,73,72,39,114,128,47,233,232,128,103,104,67,152,175,148,173,157,155,119,118,101,74,73,40,107,9,108,49,48,131,32,194,211,184,74,185,191,80,183,185,40,186,119,230,118,210,202,214,84,83,17,77,76,146,161,160,30,190,56,173,182,106,194,138,135,192,129,203,98,54,21,68,5,51,4,145,144,23,90,77,91,207,205,187,83,201,18,181,91,182,180,90,181,16,85,17,205,206,36,176,148,140,165,92,39,245,193,244,27,159,28,30,247,161,174,236,196,103,54,104,55,193,8,111,117,31,221,189,55,240,98,99,142,126,100,219,166,218,112,155,26,198,209,131,169,135,150,114,47,217,224,223,53,220,45,134,32,211,140,109,67,108,146,43,91,231,230,120,113,226,247,105,63,52,241,238,242,124,46,156,95,78,96,70,46,63,116,143,227,116,123,111,1,44,19,3,236,51,207,216,205,26,154,22,165,39,167,199,200,208,101,36,100,43,57,202,242,20,99,56,28,157,124,35,113,29,160,27,211,204,210,124,113,46,106,43,204,96,62,77,227,137,116,73,41,72,36,203,142,235,64,240,48,49,64,42,41,74,214,212,207,183,42,184,210,169,211,140,170,176,104,105,69,193,122,168,50,123,187,89,96,90,66,65,107,179,89,180,119,101,120,68,63,104,234,93,227,16,15,85,209,129,49,15,14,86,107,55,9,120,100,121,153,145,22,178,88,179,197,6,196,89,88,96,135,138,136,138,215,172,218,115,219,41,42,81,5,195,51,57,43,61,208,171,199,41,81,38,224,53,225,24,144,110,105,52,66,118,229,117,227,34,234,66,107,69,10,109,151,219,48,235,183,62,191,142,129,126,116,111,143,7,163,246,118,117,50,223,222,52,94,19,141,222,221,65,196,3,197,45,220,44,156,70,139,188,122,245,139,71,162,145,153,159,149,170,150,122,188,196,206,216,92,163,144,161,164,2,167,242,141,241,0,164,37,11,72,12,144,145,160,12,38,13,70,63,71,31,226,111,157,158,154,36,101,205,203,206,165,126,209,217,98,165,97,237,220,218,237,239,241,210,214,169,140,171,32,241,125,237,179,86,178,180,85,179,181,84,180,182,83,181,194,201,182,177,137,132,184,76,183,185,61,184,186,57,185,216,212,186,192,214,187,139,34,156,218,79,237,147,123,177,45,44,4,208,201,32,98,64,129,192,213,138,235,59,219,141,242,97,97,2,141,240,75,235,229,24,228,31,25,226,230,23,229,231,22,230,232,26,231,233,112,232,244,189,243,189,221,190,222,28,221,223,27,222,224,29,223,225,30,224,113,247,225,99,60,240,213,147,215,60,20,166,192,187,213,243,112,244,244,233,245,245,128,188,188,114,174,134,131,220,174,217,236,236,198,134,215,177,58,156,143,124,25,110,7,31,228,25,264,356,368,0,11,267,451,452,349,267,302,269,350,357,277,350,452,357,299,333,297,396,175,377,381,384,382,280,347,330,269,303,270,151,9,337,344,278,360,424,418,431,270,304,409,272,310,407,322,270,410,449,450,347,432,422,434,18,313,17,291,306,375,259,387,260,424,335,418,434,364,416,391,423,327,301,251,298,275,281,4,254,373,253,375,307,321,280,425,411,200,421,18,335,321,406,321,320,405,314,315,17,423,426,266,396,377,369,270,322,269,413,417,464,385,386,258,248,456,419,298,284,333,168,417,8,448,346,261,417,413,285,326,327,328,277,355,329,309,392,438,381,382,256,279,429,360,365,364,379,355,277,437,282,443,283,281,275,363,395,431,369,299,297,337,335,273,321,348,450,349,359,446,467,283,293,282,250,458,462,300,276,383,292,308,325,283,276,293,264,372,447,346,352,340,354,274,19,363,456,281,426,436,425,380,381,252,267,269,393,421,200,428,371,266,329,432,287,422,290,250,328,385,258,384,446,265,342,386,387,257,422,424,430,445,342,276,422,273,424,306,292,307,352,366,345,268,271,302,358,423,371,327,294,460,331,279,294,303,271,304,436,432,427,304,272,408,395,394,431,378,395,400,296,334,299,6,351,168,376,352,411,307,325,320,285,295,336,320,319,404,329,330,349,334,293,333,366,323,447,316,15,315,331,358,279,317,14,316,8,285,9,277,329,350,253,374,252,319,318,403,351,6,419,324,318,325,397,367,365,288,435,397,278,344,439,310,272,311,248,195,281,375,273,291,175,396,199,312,311,268,276,283,445,390,373,339,295,282,296,448,449,346,356,264,454,337,336,299,337,338,151,294,278,455,308,292,415,429,358,355,265,340,372,388,390,466,352,346,280,295,442,282,354,19,370,285,441,295,195,248,197,457,440,274,301,300,368,417,351,465,251,301,389,385,380,386,394,395,379,399,412,419,410,436,322,387,373,388,326,2,393,354,370,461,393,164,267,268,302,12,386,374,387,312,268,13,298,293,301,265,446,340,380,385,381,280,330,425,322,426,391,420,429,437,393,391,326,344,440,438,458,459,461,364,434,394,428,396,262,274,354,457,317,316,402,316,315,403,315,314,404,314,313,405,313,421,406,323,366,361,292,306,407,306,291,408,291,287,409,287,432,410,427,434,411,372,264,383,459,309,457,366,352,401,1,274,4,418,421,262,331,294,358,435,433,367,392,289,439,328,462,326,94,2,370,289,305,455,339,254,448,359,255,446,254,253,449,253,252,450,252,256,451,256,341,452,414,413,463,286,441,414,286,258,441,258,257,442,257,259,443,259,260,444,260,467,445,309,459,250,305,289,290,305,290,460,401,376,435,309,250,392,376,411,433,453,341,464,357,453,465,343,357,412,437,343,399,344,360,440,420,437,456,360,420,363,361,401,288,265,372,353,390,339,249,339,448,255];var ur=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],hr=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],br=[33,133,362,263,1,78,308],L7=ur.map(e=>R2[e]),W7=hr.map(e=>R2[e]),F7=br.map(e=>R2[e]);function ge(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var gr=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Mr=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Pr=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],Rr=[[474,475],[475,476],[476,477],[477,474]],vr=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],Tr=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],wr=[[469,470],[470,471],[471,472],[472,469]],kr=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]],G7={lips:ge(gr),leftEye:ge(Mr),leftEyebrow:ge(Pr),leftIris:ge(Rr),rightEye:ge(vr),rightEyebrow:ge(Tr),rightIris:ge(wr),faceOval:ge(kr)};var Je=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],Z2=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],X2=(e,t)=>e?[Math.trunc(Math.max(0,e.startPoint[0])),Math.trunc(Math.max(0,e.startPoint[1])),Math.trunc(Math.min(t.shape[2]||0,e.endPoint[0])-Math.max(0,e.startPoint[0])),Math.trunc(Math.min(t.shape[1]||0,e.endPoint[1])-Math.max(0,e.startPoint[1]))]:[0,0,0,0],q2=(e,t)=>e?[e.startPoint[0]/(t.shape[2]||0),e.startPoint[1]/(t.shape[1]||0),(e.endPoint[0]-e.startPoint[0])/(t.shape[2]||0),(e.endPoint[1]-e.startPoint[1])/(t.shape[1]||0)]:[0,0,0,0],Ut=(e,t)=>{let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]];return{startPoint:o,endPoint:n,landmarks:e.landmarks,confidence:e.confidence}},K5=(e,t,o)=>{let n=t.shape[1],r=t.shape[2],A=[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r],s=ie.image.cropAndResize(t,[A],[0],o),a=ie.div(s,V.tf255);return ie.dispose(s),a},U2=(e,t)=>{let o=Z2(e),n=Je(e),r=[t*n[0]/2,t*n[1]/2];return{startPoint:[o[0]-r[0],o[1]-r[1]],endPoint:[o[0]+r[0],o[1]+r[1]],landmarks:e.landmarks,confidence:e.confidence}},Y2=e=>{let t=Z2(e),o=Je(e),n=Math.max(...o)/2;return{startPoint:[Math.round(t[0]-n),Math.round(t[1]-n)],endPoint:[Math.round(t[0]+n),Math.round(t[1]+n)],landmarks:e.landmarks,confidence:e.confidence}},Yt=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return{startPoint:[Math.min(...t),Math.min(...o)],endPoint:[Math.max(...t),Math.max(...o)],landmarks:e}},J5=[[1,0,0],[0,1,0],[0,0,1]],Er=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),zr=(e,t)=>Er(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var Xt=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],Ne=(e,t)=>{let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o},Sr=(e,t)=>{let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o},qt=(e,t)=>{let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let A=0;A<n;A++)o[r].push(Ne(e[r],Sr(t,A)))}return o},Kt=(e,t)=>{let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],A=Xt(t[0],t[1]),s=qt(A,r),a=Xt(-t[0],-t[1]);return qt(s,a)},Cr=e=>{let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-Ne(t[0],o),-Ne(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]},Ir=(e,t)=>[Ne(e,t[0]),Ne(e,t[1])];function Jt(e){let t=e===192?{strides:[4],anchors:[1]}:{strides:[e/16,e/8],anchors:[2,6]},o=[];for(let n=0;n<t.strides.length;n++){let r=t.strides[n],A=Math.floor((e+r-1)/r),s=Math.floor((e+r-1)/r),a=t.anchors[n];for(let i=0;i<A;i++){let x=r*(i+.5);for(let c=0;c<s;c++){let l=r*(c+.5);for(let y=0;y<a;y++)o.push([l,x])}}}return o}function Qt(e,t,o,n,r){let A=Je(t),s=e.map(f=>[A[0]/r*(f[0]-r/2),A[1]/r*(f[1]-r/2),f[2]||0]),a=o&&o!==0&&Math.abs(o)>.2,i=a?Kt(o,[0,0]):J5,x=a?s.map(f=>[...Ir(f,i),f[2]]):s,c=a?Cr(n):J5,l=Z2(t),y=[Ne(l,c[0]),Ne(l,c[1])];return x.map(f=>[Math.trunc(f[0]+y[0]),Math.trunc(f[1]+y[1]),Math.trunc(f[2]||0)])}function _t(e,t,o,n){let r=t.landmarks.length>=q5.count?q5.symmetryLine:je.symmetryLine,A=0,s=J5,a;if(e&&v.kernels.includes("rotatewithoffset"))if(A=zr(t.landmarks[r[0]],t.landmarks[r[1]]),A&&A!==0&&Math.abs(A)>.2){let x=Z2(t),c=[x[0]/o.shape[2],x[1]/o.shape[1]],l=ie.image.rotateWithOffset(o,A,0,c);s=Kt(-A,x),a=K5(t,l,[n,n]),ie.dispose(l)}else a=K5(t,o,[n,n]);else a=K5(t,o,[n,n]);return[A,s,a]}var jr=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return[Math.min(...t)+(Math.max(...t)-Math.min(...t))/2,Math.min(...o)+(Math.max(...o)-Math.min(...o))/2]},$t=(e,t)=>{let o=jr(e),n=Je(t);return{startPoint:[o[0]-n[0]/2,o[1]-n[1]/2],endPoint:[o[0]+n[0]/2,o[1]+n[1]/2]}};var e3=6,Or=1.4,te,t3=null,Me=0,v2=null,Qe=()=>Me;async function o3(e){var t;return v.initial&&(te=null),te?e.debug&&p("cached model:",te.modelUrl):te=await G((t=e.face.detector)==null?void 0:t.modelPath),Me=te.inputs[0].shape?te.inputs[0].shape[2]:0,v2=N.scalar(Me,"int32"),t3=N.tensor2d(Jt(Me)),te}function Nr(e){let t={};t.boxStarts=N.slice(e,[0,1],[-1,2]),t.centers=N.add(t.boxStarts,t3),t.boxSizes=N.slice(e,[0,3],[-1,2]),t.boxSizesNormalized=N.div(t.boxSizes,v2),t.centersNormalized=N.div(t.centers,v2),t.halfBoxSize=N.div(t.boxSizesNormalized,V.tf2),t.starts=N.sub(t.centersNormalized,t.halfBoxSize),t.ends=N.add(t.centersNormalized,t.halfBoxSize),t.startNormalized=N.mul(t.starts,v2),t.endNormalized=N.mul(t.ends,v2);let o=N.concat2d([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(n=>N.dispose(t[n])),o}async function n3(e,t){var a,i,x,c;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let o={};o.resized=N.image.resizeBilinear(e,[Me,Me]),o.div=N.div(o.resized,V.tf127),o.normalized=N.sub(o.div,V.tf05);let n=te==null?void 0:te.execute(o.normalized);if(Array.isArray(n)&&n.length>2){let l=n.sort((y,f)=>y.size-f.size);o.concat384=N.concat([l[0],l[2]],2),o.concat512=N.concat([l[1],l[3]],2),o.concat=N.concat([o.concat512,o.concat384],1),o.batch=N.squeeze(o.concat,0)}else Array.isArray(n)?o.batch=N.squeeze(n[0]):o.batch=N.squeeze(n);N.dispose(n),o.boxes=Nr(o.batch),o.logits=N.slice(o.batch,[0,0],[-1,1]),o.sigmoid=N.sigmoid(o.logits),o.scores=N.squeeze(o.sigmoid),o.nms=await N.image.nonMaxSuppressionAsync(o.boxes,o.scores,((a=t.face.detector)==null?void 0:a.maxDetected)||0,((i=t.face.detector)==null?void 0:i.iouThreshold)||0,((x=t.face.detector)==null?void 0:x.minConfidence)||0);let r=await o.nms.array(),A=[],s=await o.scores.data();for(let l=0;l<r.length;l++){let y=s[r[l]];if(y>(((c=t.face.detector)==null?void 0:c.minConfidence)||0)){let f={};f.bbox=N.slice(o.boxes,[r[l],0],[1,-1]),f.slice=N.slice(o.batch,[r[l],e3-1],[1,-1]),f.squeeze=N.squeeze(f.slice),f.landmarks=N.reshape(f.squeeze,[e3,-1]);let u=await f.bbox.data(),m={startPoint:[u[0],u[1]],endPoint:[u[2],u[3]],landmarks:await f.landmarks.array(),confidence:y},P=Ut(m,[(e.shape[2]||0)/Me,(e.shape[1]||0)/Me]),g=U2(P,t.face.scale||Or),b=Y2(g);A.push(b),Object.keys(f).forEach(d=>N.dispose(f[d]))}}return Object.keys(o).forEach(l=>N.dispose(o[l])),A}var j0=Z(D());var K2={};ue(K2,{connected:()=>$5,kpt:()=>_5});var _5=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPinky","rightPinky","leftIndex","rightIndex","leftThumb","rightThumb","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","bodyCenter","bodyTop","leftPalm","leftHand","rightPalm","rightHand"],$5={shoulders:["leftShoulder","rightShoulder"],hips:["rightHip","leftHip"],mouth:["leftMouth","rightMouth"],leftLegUpper:["leftHip","leftKnee"],leftLegLower:["leftKnee","leftAnkle"],leftFoot:["leftAnkle","leftHeel","leftFoot"],leftTorso:["leftShoulder","leftHip"],leftArmUpper:["leftShoulder","leftElbow"],leftArmLower:["leftElbow","leftWrist"],leftHand:["leftWrist","leftPalm"],leftHandPinky:["leftPalm","leftPinky"],leftHandIndex:["leftPalm","leftIndex"],leftHandThumb:["leftPalm","leftThumb"],leftEyeOutline:["leftEyeInside","leftEyeOutside"],rightLegUpper:["rightHip","rightKnee"],rightLegLower:["rightKnee","rightAnkle"],rightFoot:["rightAnkle","rightHeel","rightFoot"],rightTorso:["rightShoulder","rightHip"],rightArmUpper:["rightShoulder","rightElbow"],rightArmLower:["rightElbow","rightWrist"],rightHand:["rightWrist","rightPalm"],rightHandPinky:["rightPalm","rightPinky"],rightHandIndex:["rightPalm","rightIndex"],rightHandThumb:["rightPalm","rightThumb"],rightEyeOutline:["rightEyeInside","rightEyeOutside"]};var C0=Z(D()),A3=224,Lr,Wr=5,J2=[8,16,32,32,32];async function s3(){let e=[],t=0;for(;t<Wr;){let o=0,n=t;for(;n<J2.length&&J2[n]===J2[t];)o+=2,n++;let r=J2[t],A=Math.ceil(A3/r),s=Math.ceil(A3/r);for(let a=0;a<A;++a)for(let i=0;i<s;++i)for(let x=0;x<o;++x)e.push({x:(i+.5)/s,y:(a+.5)/A});t=n}Lr={x:C0.tensor1d(e.map(o=>o.x)),y:C0.tensor1d(e.map(o=>o.y))}}function le(e,t=[1,1]){let o=[e.map(a=>a[0]),e.map(a=>a[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],A=[n[0],n[1],r[0]-n[0],r[1]-n[1]],s=[A[0]/t[0],A[1]/t[1],A[2]/t[0],A[3]/t[1]];return{box:A,boxRaw:s}}function a3(e,t=[1,1]){let o=[e.map(x=>x[0]),e.map(x=>x[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],A=[(n[0]+r[0])/2,(n[1]+r[1])/2],s=Math.max(A[0]-n[0],A[1]-n[1],-A[0]+r[0],-A[1]+r[1]),a=[Math.trunc(A[0]-s),Math.trunc(A[1]-s),Math.trunc(2*s),Math.trunc(2*s)],i=[a[0]/t[0],a[1]/t[1],a[2]/t[0],a[3]/t[1]];return{box:a,boxRaw:i}}function Q2(e,t){let o=[e[2]*t,e[3]*t];return[e[0]-(o[0]-e[2])/2,e[1]-(o[1]-e[3])/2,o[0],o[1]]}var y3={initial:!0},I0={detector:null,landmarks:null},_e={detector:[224,224],landmarks:[256,256]},e1=Number.MAX_SAFE_INTEGER,Gr={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},$2=null,T2,Pe=[[0,0],[0,0],[0,0],[0,0]],i3=0,l3=e=>1-1/(1+Math.exp(e));async function x3(e){if(y3.initial&&(I0.detector=null),!I0.detector&&e.body.detector&&e.body.detector.modelPath){I0.detector=await G(e.body.detector.modelPath);let t=Object.values(I0.detector.modelSignature.inputs);_e.detector[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,_e.detector[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&I0.detector&&p("cached model:",I0.detector.modelUrl);return await s3(),I0.detector}async function c3(e){if(y3.initial&&(I0.landmarks=null),I0.landmarks)e.debug&&p("cached model:",I0.landmarks.modelUrl);else{I0.landmarks=await G(e.body.modelPath);let t=Object.values(I0.landmarks.modelSignature.inputs);_e.landmarks[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,_e.landmarks[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return I0.landmarks}async function Br(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;let n;if(T2&&(o.cropped=j0.image.cropAndResize(e,[T2],[0],[e.shape[1],e.shape[2]])),e.shape[1]!==e.shape[2]){let r=[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],A=[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0];Pe=[[0,0],r,A,[0,0]],o.pad=j0.pad(o.cropped||e,Pe),o.resize=j0.image.resizeBilinear(o.pad,[t,t]),n=j0.div(o.resize,V.tf255)}else e.shape[1]!==t?(o.resize=j0.image.resizeBilinear(o.cropped||e,[t,t]),n=j0.div(o.resize,V.tf255)):n=j0.div(o.cropped||e,V.tf255);return Object.keys(o).forEach(r=>j0.dispose(o[r])),n}function Hr(e,t){for(let o of e)o.position=[Math.trunc(o.position[0]*(t[0]+Pe[2][0]+Pe[2][1])/t[0]-Pe[2][0]),Math.trunc(o.position[1]*(t[1]+Pe[1][0]+Pe[1][1])/t[1]-Pe[1][0]),o.position[2]],o.positionRaw=[o.position[0]/t[0],o.position[1]/t[1],2*o.position[2]/(t[0]+t[1])];if(T2)for(let o of e)o.positionRaw=[o.positionRaw[0]+T2[1],o.positionRaw[1]+T2[0],o.positionRaw[2]],o.position=[Math.trunc(o.positionRaw[0]*t[0]),Math.trunc(o.positionRaw[1]*t[1]),o.positionRaw[2]];return e}async function Vr(e){let t=e.find(a=>a.part==="leftPalm"),o=e.find(a=>a.part==="leftWrist"),n=e.find(a=>a.part==="leftIndex");t.position[2]=((o.position[2]||0)+(n.position[2]||0))/2;let r=e.find(a=>a.part==="rightPalm"),A=e.find(a=>a.part==="rightWrist"),s=e.find(a=>a.part==="rightIndex");r.position[2]=((A.position[2]||0)+(s.position[2]||0))/2}async function Dr(e,t,o){var u;let n={};[n.ld,n.segmentation,n.heatmap,n.world,n.poseflag]=(u=I0.landmarks)==null?void 0:u.execute(e,Gr.landmarks);let r=(await n.poseflag.data())[0],A=await n.ld.data(),s=await n.world.data();Object.keys(n).forEach(m=>j0.dispose(n[m]));let a=[],i=5;for(let m=0;m<A.length/i;m++){let P=l3(A[i*m+3]),g=l3(A[i*m+4]),b=Math.trunc(100*P*g*r)/100,d=[A[i*m+0]/_e.landmarks[0],A[i*m+1]/_e.landmarks[1],A[i*m+2]+0],M=[Math.trunc(o[0]*d[0]),Math.trunc(o[1]*d[1]),d[2]],S=[s[i*m+0],s[i*m+1],s[i*m+2]+0];a.push({part:_5[m],positionRaw:d,position:M,distance:S,score:b})}if(r<(t.body.minConfidence||0))return null;Vr(a);let x=Hr(a,o),c=x.map(m=>m.position),l=le(c,[o[0],o[1]]),y={};for(let[m,P]of Object.entries($5)){let g=[];for(let b=0;b<P.length-1;b++){let d=x.find(S=>S.part===P[b]),M=x.find(S=>S.part===P[b+1]);d&&M&&g.push([d.position,M.position])}y[m]=g}return{id:0,score:Math.trunc(100*r)/100,box:l.box,boxRaw:l.boxRaw,keypoints:x,annotations:y}}async function t1(e,t){let o=[e.shape[2]||0,e.shape[1]||0],n=(t.body.skipTime||0)>h()-i3,r=e1<(t.body.skipFrames||0);if(t.skipAllowed&&n&&r&&$2!==null)e1++;else{let A={};A.landmarks=await Br(e,256),$2=await Dr(A.landmarks,t,o),Object.keys(A).forEach(s=>j0.dispose(A[s])),i3=h(),e1=0}return $2?[$2]:[]}var T0=Z(D());var $e=[{class:1,label:"person"},{class:2,label:"bicycle"},{class:3,label:"car"},{class:4,label:"motorcycle"},{class:5,label:"airplane"},{class:6,label:"bus"},{class:7,label:"train"},{class:8,label:"truck"},{class:9,label:"boat"},{class:10,label:"traffic light"},{class:11,label:"fire hydrant"},{class:12,label:"stop sign"},{class:13,label:"parking meter"},{class:14,label:"bench"},{class:15,label:"bird"},{class:16,label:"cat"},{class:17,label:"dog"},{class:18,label:"horse"},{class:19,label:"sheep"},{class:20,label:"cow"},{class:21,label:"elephant"},{class:22,label:"bear"},{class:23,label:"zebra"},{class:24,label:"giraffe"},{class:25,label:"backpack"},{class:26,label:"umbrella"},{class:27,label:"handbag"},{class:28,label:"tie"},{class:29,label:"suitcase"},{class:30,label:"frisbee"},{class:31,label:"skis"},{class:32,label:"snowboard"},{class:33,label:"sports ball"},{class:34,label:"kite"},{class:35,label:"baseball bat"},{class:36,label:"baseball glove"},{class:37,label:"skateboard"},{class:38,label:"surfboard"},{class:39,label:"tennis racket"},{class:40,label:"bottle"},{class:41,label:"wine glass"},{class:42,label:"cup"},{class:43,label:"fork"},{class:44,label:"knife"},{class:45,label:"spoon"},{class:46,label:"bowl"},{class:47,label:"banana"},{class:48,label:"apple"},{class:49,label:"sandwich"},{class:50,label:"orange"},{class:51,label:"broccoli"},{class:52,label:"carrot"},{class:53,label:"hot dog"},{class:54,label:"pizza"},{class:55,label:"donut"},{class:56,label:"cake"},{class:57,label:"chair"},{class:58,label:"couch"},{class:59,label:"potted plant"},{class:60,label:"bed"},{class:61,label:"dining table"},{class:62,label:"toilet"},{class:63,label:"tv"},{class:64,label:"laptop"},{class:65,label:"mouse"},{class:66,label:"remote"},{class:67,label:"keyboard"},{class:68,label:"cell phone"},{class:69,label:"microwave"},{class:70,label:"oven"},{class:71,label:"toaster"},{class:72,label:"sink"},{class:73,label:"refrigerator"},{class:74,label:"book"},{class:75,label:"clock"},{class:76,label:"vase"},{class:77,label:"scissors"},{class:78,label:"teddy bear"},{class:79,label:"hair drier"},{class:80,label:"toothbrush"}];var ye,Le=0,o1=[],f3=0,n1=Number.MAX_SAFE_INTEGER;async function m3(e){if(v.initial&&(ye=null),ye)e.debug&&p("cached model:",ye.modelUrl);else{ye=await G(e.object.modelPath);let t=Object.values(ye.modelSignature.inputs);Le=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return ye}async function Zr(e,t,o){if(!e)return[];let n={},r=[],A=await e.array();n.squeeze=T0.squeeze(e);let s=T0.split(n.squeeze,6,1);n.stack=T0.stack([s[1],s[0],s[3],s[2]],1),n.boxes=T0.squeeze(n.stack),n.scores=T0.squeeze(s[4]),n.classes=T0.squeeze(s[5]),T0.dispose([e,...s]),n.nms=await T0.image.nonMaxSuppressionAsync(n.boxes,n.scores,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence||0);let a=await n.nms.data(),i=0;for(let x of Array.from(a)){let c=Math.trunc(100*A[0][x][4])/100,l=A[0][x][5],y=$e[l].label,[f,u]=[A[0][x][0]/Le,A[0][x][1]/Le],m=[f,u,A[0][x][2]/Le-f,A[0][x][3]/Le-u],P=[Math.trunc(m[0]*t[0]),Math.trunc(m[1]*t[1]),Math.trunc(m[2]*t[0]),Math.trunc(m[3]*t[1])];r.push({id:i++,score:c,class:l,label:y,box:P,boxRaw:m})}return Object.keys(n).forEach(x=>T0.dispose(n[x])),r}async function r1(e,t){let o=(t.object.skipTime||0)>h()-f3,n=n1<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&o1.length>0?(n1++,o1):(n1=0,new Promise(async r=>{let A=[e.shape[2]||0,e.shape[1]||0],s=T0.image.resizeBilinear(e,[Le,Le]),a=t.object.enabled?ye==null?void 0:ye.execute(s,["tower_0/detections"]):null;f3=h(),T0.dispose(s);let i=await Zr(a,A,t);o1=i,r(i)}))}var _=Z(D());var e5={};ue(e5,{connected:()=>s1,kpt:()=>A1});var A1=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],s1={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var b0,u3=0,w0={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},a1=Number.MAX_SAFE_INTEGER;async function h3(e){return v.initial&&(b0=null),b0?e.debug&&p("cached model:",b0.modelUrl):b0=await G(e.body.modelPath),b0}async function Xr(e,t){let[o,n]=e.shape,r=_.reshape(e,[n*o]),A=_.max(r,0),s=(await A.data())[0];if(_.dispose([r,A]),s>t){let a=_.argMax(r,0),i=_.mod(a,o),x=(await i.data())[0],c=_.div(a,_.scalar(o,"int32")),l=(await c.data())[0];return _.dispose([i,c]),[x,l,s]}return[0,0,s]}async function i1(e,t){let o=(t.body.skipTime||0)>h()-u3,n=a1<(t.body.skipFrames||0);return t.skipAllowed&&o&&n&&Object.keys(w0.keypoints).length>0?(a1++,[w0]):(a1=0,new Promise(async r=>{var l;let A=_.tidy(()=>{if(!(b0!=null&&b0.inputs[0].shape))return null;let y=_.image.resizeBilinear(e,[b0.inputs[0].shape[2],b0.inputs[0].shape[1]],!1),f=_.mul(y,V.tf2);return _.sub(f,V.tf1)}),s;if(t.body.enabled&&(s=b0==null?void 0:b0.execute(A)),u3=h(),_.dispose(A),s){w0.keypoints.length=0;let y=s.squeeze();_.dispose(s);let f=y.unstack(2);_.dispose(y);for(let u=0;u<f.length;u++){let[m,P,g]=await Xr(f[u],t.body.minConfidence);g>(((l=t.body)==null?void 0:l.minConfidence)||0)&&w0.keypoints.push({score:Math.round(100*g)/100,part:A1[u],positionRaw:[m/b0.inputs[0].shape[2],P/b0.inputs[0].shape[1]],position:[Math.round(e.shape[2]*m/b0.inputs[0].shape[2]),Math.round(e.shape[1]*P/b0.inputs[0].shape[1])]})}f.forEach(u=>_.dispose(u))}w0.score=w0.keypoints.reduce((y,f)=>f.score>y?f.score:y,0);let a=w0.keypoints.map(y=>y.position[0]),i=w0.keypoints.map(y=>y.position[1]);w0.box=[Math.min(...a),Math.min(...i),Math.max(...a)-Math.min(...a),Math.max(...i)-Math.min(...i)];let x=w0.keypoints.map(y=>y.positionRaw[0]),c=w0.keypoints.map(y=>y.positionRaw[1]);w0.boxRaw=[Math.min(...x),Math.min(...c),Math.max(...x)-Math.min(...x),Math.max(...c)-Math.min(...c)];for(let[y,f]of Object.entries(s1)){let u=[];for(let m=0;m<f.length-1;m++){let P=w0.keypoints.find(b=>b.part===f[m]),g=w0.keypoints.find(b=>b.part===f[m+1]);P&&g&&P.score>(t.body.minConfidence||0)&&g.score>(t.body.minConfidence||0)&&u.push([P.position,g.position])}w0.annotations[y]=u}r([w0])}))}var U0=Z(D());var qr=["angry","disgust","fear","happy","sad","surprise","neutral"],H0,t5=[],g3=0,M3=0,l1=Number.MAX_SAFE_INTEGER;async function P3(e){var t;return v.initial&&(H0=null),H0?e.debug&&p("cached model:",H0.modelUrl):H0=await G((t=e.face.emotion)==null?void 0:t.modelPath),H0}async function y1(e,t,o,n){var s,a;if(!H0)return[];let r=l1<(((s=t.face.emotion)==null?void 0:s.skipFrames)||0),A=(((a=t.face.emotion)==null?void 0:a.skipTime)||0)>h()-M3;return t.skipAllowed&&A&&r&&g3===n&&t5[o]&&t5[o].length>0?(l1++,t5[o]):(l1=0,new Promise(async i=>{var c,l;let x=[];if((c=t.face.emotion)!=null&&c.enabled){let y={},f=H0!=null&&H0.inputs[0].shape?H0.inputs[0].shape[2]:0;y.resize=U0.image.resizeBilinear(e,[f,f],!1),y.channels=U0.mul(y.resize,V.rgb),y.grayscale=U0.sum(y.channels,3,!0),y.grayscaleSub=U0.sub(y.grayscale,V.tf05),y.grayscaleMul=U0.mul(y.grayscaleSub,V.tf2),y.emotion=H0==null?void 0:H0.execute(y.grayscaleMul),M3=h();let u=await y.emotion.data();for(let m=0;m<u.length;m++)u[m]>(((l=t.face.emotion)==null?void 0:l.minConfidence)||0)&&x.push({score:Math.min(.99,Math.trunc(100*u[m])/100),emotion:qr[m]});x.sort((m,P)=>P.score-m.score),Object.keys(y).forEach(m=>U0.dispose(y[m]))}t5[o]=x,g3=n,i(x)}))}var k3=Z(D());var O0,x1=[],v3=0,T3=0,w3=Number.MAX_SAFE_INTEGER;async function E3(e){return v.initial&&(O0=null),O0?e.debug&&p("cached model:",O0.modelUrl):O0=await G(e.face.mobilefacenet.modelPath),O0}async function c1(e,t,o,n){var s,a;if(!O0)return[];let r=w3<(((s=t.face.embedding)==null?void 0:s.skipFrames)||0),A=(((a=t.face.embedding)==null?void 0:a.skipTime)||0)>h()-T3;return t.skipAllowed&&A&&r&&v3===n&&x1[o]?(w3++,x1[o]):new Promise(async i=>{var c;let x=[];if(((c=t.face.embedding)==null?void 0:c.enabled)&&(O0==null?void 0:O0.inputs[0].shape)){let l={};l.crop=k3.image.resizeBilinear(e,[O0.inputs[0].shape[2],O0.inputs[0].shape[1]],!1),l.data=O0==null?void 0:O0.execute(l.crop);let y=await l.data.data();x=Array.from(y)}x1[o]=x,v3=n,T3=h(),i(x)})}var Be=Z(D());var Y0=Z(D());var xe,Re=0,Ur=2.3,d1=X0.leftEyeLower0,f1=X0.rightEyeLower0,e2={leftBounds:[d1[0],d1[d1.length-1]],rightBounds:[f1[0],f1[f1.length-1]]},t2={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function j3(e){var t;return v.initial&&(xe=null),xe?e.debug&&p("cached model:",xe.modelUrl):xe=await G((t=e.face.iris)==null?void 0:t.modelPath),Re=xe.inputs[0].shape?xe.inputs[0].shape[2]:0,Re===-1&&(Re=64),xe}function o5(e,t,o,n){for(let r=0;r<U5.length;r++){let{key:A,indices:s}=U5[r],a=X0[`${o}${A}`];if(!n||n.includes(A))for(let i=0;i<s.length;i++){let x=s[i];e[a[i]]=[t[x][0],t[x][1],(t[x][2]+e[a[i]][2])/2]}}}var Yr=e=>{let t=e[e2.leftBounds[0]][2],o=e[e2.rightBounds[0]][2];return t-o},S3=(e,t,o,n,r,A=!1)=>{let s=Y2(U2(Yt([e[o],e[n]]),Ur)),a=Je(s),i=Y0.image.cropAndResize(t,[[s.startPoint[1]/r,s.startPoint[0]/r,s.endPoint[1]/r,s.endPoint[0]/r]],[0],[Re,Re]);if(A&&v.kernels.includes("flipleftright")){let x=Y0.image.flipLeftRight(i);Y0.dispose(i),i=x}return{box:s,boxSize:a,crop:i}},C3=(e,t,o,n=!1)=>{let r=[];for(let A=0;A<t2.numCoordinates;A++){let s=e[A*3],a=e[A*3+1],i=e[A*3+2];r.push([(n?1-s/Re:s/Re)*o[0]+t.startPoint[0],a/Re*o[1]+t.startPoint[1],i])}return{rawCoords:r,iris:r.slice(t2.index)}},I3=(e,t,o)=>{let n=e[X0[`${o}EyeUpper0`][t2.upperCenter]][2],r=e[X0[`${o}EyeLower0`][t2.lowerCenter]][2],A=(n+r)/2;return t.map((s,a)=>{let i=A;return a===2?i=n:a===4&&(i=r),[s[0],s[1],i]})};async function O3(e,t,o,n){if(!xe)return o.debug&&p("face mesh iris detection requested, but model is not loaded"),e;let{box:r,boxSize:A,crop:s}=S3(e,t,e2.leftBounds[0],e2.leftBounds[1],n,!0),{box:a,boxSize:i,crop:x}=S3(e,t,e2.rightBounds[0],e2.rightBounds[1],n,!0),c=Y0.concat([s,x]);Y0.dispose(s),Y0.dispose(x);let l=xe.execute(c);Y0.dispose(c);let y=await l.data();Y0.dispose(l);let f=y.slice(0,t2.numCoordinates*3),{rawCoords:u,iris:m}=C3(f,r,A,!0),P=y.slice(t2.numCoordinates*3),{rawCoords:g,iris:b}=C3(P,a,i,!1),d=Yr(e);Math.abs(d)<30?(o5(e,u,"left",null),o5(e,g,"right",null)):d<1?o5(e,u,"left",["EyeUpper0","EyeLower0"]):o5(e,g,"right",["EyeUpper0","EyeLower0"]);let M=I3(e,m,"left"),S=I3(e,b,"right");return e.concat(M).concat(S)}var Kr=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Jr=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Qr=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],_r=[[474,475],[475,476],[476,477],[477,474]],$r=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],eA=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],tA=[[469,470],[470,471],[471,472],[472,469]],oA=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]];function ve(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var nA={lips:ve(Kr),leftEye:ve(Jr),leftEyebrow:ve(Qr),leftIris:ve(_r),rightEye:ve($r),rightEyebrow:ve(eA),rightIris:ve(tA),faceOval:ve(oA)},rA=Object.entries(nA).map(([e,t])=>t.map(o=>[o,e])).flat(),f4=new Map(rA),w2=[61,146,91,181,84,17,314,405,321,375,291,185,40,39,37,0,267,269,270,409,78,95,88,178,87,14,317,402,318,324,308,191,80,81,82,13,312,311,310,415,76,77,90,180,85,16,315,404,320,307,306,184,74,73,72,11,302,303,304,408,62,96,89,179,86,15,316,403,319,325,292,183,42,41,38,12,268,271,272,407],We=[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173,130,25,110,24,23,22,26,112,243,247,30,29,27,28,56,190,226,31,228,229,230,231,232,233,244,113,225,224,223,222,221,189,35,124,46,53,52,65,143,111,117,118,119,120,121,128,245,156,70,63,105,66,107,55,193],Fe=[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398,359,255,339,254,253,252,256,341,463,467,260,259,257,258,286,414,446,261,448,449,450,451,452,453,464,342,445,444,443,442,441,413,265,353,276,283,282,295,372,340,346,347,348,349,350,357,465,383,300,293,334,296,336,285,417];async function W3(e,t){let o={lips:await t.filter(A=>A.size===160)[0].data(),irisL:await t.filter(A=>A.size===10)[0].data(),eyeL:await t.filter(A=>A.size===142)[0].data(),irisR:await t.filter(A=>A.size===10)[1].data(),eyeR:await t.filter(A=>A.size===142)[1].data()},n=We.reduce((A,s)=>A+=e[s][2],0)/We.length;for(let A=0;A<o.irisL.length/2;A++)e.push([o.irisL[2*A+0],o.irisL[2*A+1],n]);let r=Fe.reduce((A,s)=>A+=e[s][2],0)/Fe.length;for(let A=0;A<o.irisR.length/2;A++)e.push([o.irisR[2*A+0],o.irisR[2*A+1],r]);for(let A=0;A<o.eyeL.length/2;A++)e[We[A]]=[o.eyeL[2*A+0],o.eyeL[2*A+1],e[We[A]][2]];for(let A=0;A<o.eyeR.length/2;A++)e[Fe[A]]=[o.eyeR[2*A+0],o.eyeR[2*A+1],e[Fe[A]][2]];for(let A=0;A<o.lips.length/2;A++)e[w2[A]]=[o.lips[2*A+0],o.lips[2*A+1],e[w2[A]][2]];return e}var oe={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},g0=null,Ge=0;async function F3(e,t){var a,i,x,c,l,y,f,u,m,P,g;let o=(((a=t.face.detector)==null?void 0:a.skipTime)||0)>h()-oe.timestamp,n=oe.skipped<(((i=t.face.detector)==null?void 0:i.skipFrames)||0);!t.skipAllowed||!o||!n||oe.boxes.length===0?(oe.boxes=await n3(e,t),oe.timestamp=h(),oe.skipped=0):oe.skipped++;let r=[],A=[],s=0;for(let b=0;b<oe.boxes.length;b++){let d=oe.boxes[b],M=0,S,w={id:s++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,annotations:{}};if([M,S,w.tensor]=_t((x=t.face.detector)==null?void 0:x.rotation,d,e,(c=t.face.mesh)!=null&&c.enabled?Ge:Qe()),(l=t==null?void 0:t.filter)!=null&&l.equalization){let j=await N2(w.tensor);Be.dispose(w.tensor),w.tensor=j}if(w.boxScore=Math.round(100*d.confidence)/100,(y=t.face.mesh)!=null&&y.enabled)if(!g0)t.debug&&p("face mesh detection requested, but model is not loaded");else{let j=g0.execute(w.tensor),F=await j.find(H=>H.shape[H.shape.length-1]===1).data();if(w.faceScore=Math.round(100*F[0])/100,w.faceScore<(((f=t.face.detector)==null?void 0:f.minConfidence)||1)){if(d.confidence=w.faceScore,(u=t.face.mesh)!=null&&u.keepInvalid){w.box=X2(d,e),w.boxRaw=q2(d,e),w.score=w.boxScore,w.mesh=d.landmarks.map(H=>[(d.startPoint[0]+d.endPoint[0])/2+(d.endPoint[0]+d.startPoint[0])*H[0]/Qe(),(d.startPoint[1]+d.endPoint[1])/2+(d.endPoint[1]+d.startPoint[1])*H[1]/Qe()]),w.meshRaw=w.mesh.map(H=>[H[0]/(e.shape[2]||1),H[1]/(e.shape[1]||1),(H[2]||0)/Ge]);for(let H of Object.keys(je))w.annotations[H]=[w.mesh[je[H]]]}}else{let H=j.find(E=>E.shape[E.shape.length-1]===1404),Y=Be.reshape(H,[-1,3]),J=await Y.array();Be.dispose(Y),(m=t.face.attention)!=null&&m.enabled?J=await W3(J,j):(P=t.face.iris)!=null&&P.enabled&&(J=await O3(J,w.tensor,t,Ge)),w.mesh=Qt(J,d,M,S,Ge),w.meshRaw=w.mesh.map(E=>[E[0]/(e.shape[2]||0),E[1]/(e.shape[1]||0),(E[2]||0)/Ge]);for(let E of Object.keys(X0))w.annotations[E]=X0[E].map(G0=>w.mesh[G0]);w.score=w.faceScore;let x0={...$t(w.mesh,d),confidence:d.confidence,landmarks:d.landmarks};w.box=X2(x0,e),w.boxRaw=q2(x0,e),A.push(x0)}Be.dispose(j)}else{w.box=X2(d,e),w.boxRaw=q2(d,e),w.score=w.boxScore,w.mesh=d.landmarks.map(j=>[(d.startPoint[0]+d.endPoint[0])/2+(d.endPoint[0]+d.startPoint[0])*j[0]/Qe(),(d.startPoint[1]+d.endPoint[1])/2+(d.endPoint[1]+d.startPoint[1])*j[1]/Qe()]),w.meshRaw=w.mesh.map(j=>[j[0]/(e.shape[2]||0),j[1]/(e.shape[1]||0),(j[2]||0)/Ge]);for(let j of Object.keys(je))w.annotations[j]=[w.mesh[je[j]]]}w.score>(((g=t.face.detector)==null?void 0:g.minConfidence)||1)?r.push(w):Be.dispose(w.tensor)}return oe.boxes=A,r}async function G3(e){var t,o,n,r,A,s;return v.initial&&(g0=null),((o=(t=e==null?void 0:e.face)==null?void 0:t.attention)==null?void 0:o.enabled)&&(g0==null?void 0:g0.signature)&&Object.keys(((n=g0==null?void 0:g0.signature)==null?void 0:n.outputs)||{}).length<6&&(g0=null),g0?e.debug&&p("cached model:",g0.modelUrl):(r=e.face.attention)!=null&&r.enabled?g0=await G((A=e.face.attention)==null?void 0:A.modelPath):g0=await G((s=e.face.mesh)==null?void 0:s.modelPath),Ge=g0.inputs[0].shape?g0.inputs[0].shape[2]:0,g0}var B3=Oe,H3=R2;var K0=Z(D());var N0,n5=[],V3=0,D3=0,p1=Number.MAX_SAFE_INTEGER;async function Z3(e){var t;return v.initial&&(N0=null),N0?e.debug&&p("cached model:",N0.modelUrl):N0=await G((t=e.face.description)==null?void 0:t.modelPath),N0}function u1(e){let t=e.image||e.tensor||e;if(!(N0!=null&&N0.inputs[0].shape))return t;let o=K0.image.resizeBilinear(t,[N0.inputs[0].shape[2],N0.inputs[0].shape[1]],!1),n=K0.mul(o,V.tf255);return K0.dispose(o),n}async function h1(e,t,o,n){var s,a,i,x;if(!N0)return{age:0,gender:"unknown",genderScore:0,descriptor:[]};let r=p1<(((s=t.face.description)==null?void 0:s.skipFrames)||0),A=(((a=t.face.description)==null?void 0:a.skipTime)||0)>h()-V3;return t.skipAllowed&&r&&A&&D3===n&&((i=n5[o])==null?void 0:i.age)&&((x=n5[o])==null?void 0:x.age)>0?(p1++,n5[o]):(p1=0,new Promise(async c=>{var y,f;let l={age:0,gender:"unknown",genderScore:0,descriptor:[]};if((y=t.face.description)!=null&&y.enabled){let u=u1(e),m=N0==null?void 0:N0.execute(u);V3=h(),K0.dispose(u);let g=await(await m.find(F=>F.shape[1]===1)).data(),b=Math.trunc(200*Math.abs(g[0]-.5))/100;b>(((f=t.face.description)==null?void 0:f.minConfidence)||0)&&(l.gender=g[0]<=.5?"female":"male",l.genderScore=Math.min(.99,b));let d=K0.argMax(m.find(F=>F.shape[1]===100),1),M=(await d.data())[0];K0.dispose(d);let w=await m.find(F=>F.shape[1]===100).data();l.age=Math.round(w[M-1]>w[M+1]?10*M-100*w[M-1]:10*M+100*w[M+1])/10;let j=m.find(F=>F.shape[1]===1024),C=j?await j.data():[];l.descriptor=Array.from(C),m.forEach(F=>K0.dispose(F))}n5[o]=l,D3=n,c(l)}))}var W=Z(D());var U3=Z(D());function r5(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function k2(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function Y3(e,t,o){let n=t.shape[1],r=t.shape[2],A=[[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r]];return U3.image.cropAndResize(t,A,[0],o)}function K3(e,t){let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],r=e.palmLandmarks.map(A=>[A[0]*t[0],A[1]*t[1]]);return{startPoint:o,endPoint:n,palmLandmarks:r,confidence:e.confidence}}function A5(e,t=1.5){let o=k2(e),n=r5(e),r=[t*n[0]/2,t*n[1]/2],A=[o[0]-r[0],o[1]-r[1]],s=[o[0]+r[0],o[1]+r[1]];return{startPoint:A,endPoint:s,palmLandmarks:e.palmLandmarks}}function s5(e){let t=k2(e),o=r5(e),r=Math.max(...o)/2,A=[t[0]-r,t[1]-r],s=[t[0]+r,t[1]+r];return{startPoint:A,endPoint:s,palmLandmarks:e.palmLandmarks}}function sA(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function J3(e,t){let o=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return sA(o)}var X3=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function Te(e,t){let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o}function aA(e,t){let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o}function q3(e,t){let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let A=0;A<n;A++)o[r].push(Te(e[r],aA(t,A)))}return o}function g1(e,t){let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],A=X3(t[0],t[1]),s=q3(A,r),a=X3(-t[0],-t[1]);return q3(s,a)}function Q3(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-Te(t[0],o),-Te(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]}function M1(e,t){return[Te(e,t[0]),Te(e,t[1])]}var $3=[{x:.015625,y:.015625},{x:.015625,y:.015625},{x:.046875,y:.015625},{x:.046875,y:.015625},{x:.078125,y:.015625},{x:.078125,y:.015625},{x:.109375,y:.015625},{x:.109375,y:.015625},{x:.140625,y:.015625},{x:.140625,y:.015625},{x:.171875,y:.015625},{x:.171875,y:.015625},{x:.203125,y:.015625},{x:.203125,y:.015625},{x:.234375,y:.015625},{x:.234375,y:.015625},{x:.265625,y:.015625},{x:.265625,y:.015625},{x:.296875,y:.015625},{x:.296875,y:.015625},{x:.328125,y:.015625},{x:.328125,y:.015625},{x:.359375,y:.015625},{x:.359375,y:.015625},{x:.390625,y:.015625},{x:.390625,y:.015625},{x:.421875,y:.015625},{x:.421875,y:.015625},{x:.453125,y:.015625},{x:.453125,y:.015625},{x:.484375,y:.015625},{x:.484375,y:.015625},{x:.515625,y:.015625},{x:.515625,y:.015625},{x:.546875,y:.015625},{x:.546875,y:.015625},{x:.578125,y:.015625},{x:.578125,y:.015625},{x:.609375,y:.015625},{x:.609375,y:.015625},{x:.640625,y:.015625},{x:.640625,y:.015625},{x:.671875,y:.015625},{x:.671875,y:.015625},{x:.703125,y:.015625},{x:.703125,y:.015625},{x:.734375,y:.015625},{x:.734375,y:.015625},{x:.765625,y:.015625},{x:.765625,y:.015625},{x:.796875,y:.015625},{x:.796875,y:.015625},{x:.828125,y:.015625},{x:.828125,y:.015625},{x:.859375,y:.015625},{x:.859375,y:.015625},{x:.890625,y:.015625},{x:.890625,y:.015625},{x:.921875,y:.015625},{x:.921875,y:.015625},{x:.953125,y:.015625},{x:.953125,y:.015625},{x:.984375,y:.015625},{x:.984375,y:.015625},{x:.015625,y:.046875},{x:.015625,y:.046875},{x:.046875,y:.046875},{x:.046875,y:.046875},{x:.078125,y:.046875},{x:.078125,y:.046875},{x:.109375,y:.046875},{x:.109375,y:.046875},{x:.140625,y:.046875},{x:.140625,y:.046875},{x:.171875,y:.046875},{x:.171875,y:.046875},{x:.203125,y:.046875},{x:.203125,y:.046875},{x:.234375,y:.046875},{x:.234375,y:.046875},{x:.265625,y:.046875},{x:.265625,y:.046875},{x:.296875,y:.046875},{x:.296875,y:.046875},{x:.328125,y:.046875},{x:.328125,y:.046875},{x:.359375,y:.046875},{x:.359375,y:.046875},{x:.390625,y:.046875},{x:.390625,y:.046875},{x:.421875,y:.046875},{x:.421875,y:.046875},{x:.453125,y:.046875},{x:.453125,y:.046875},{x:.484375,y:.046875},{x:.484375,y:.046875},{x:.515625,y:.046875},{x:.515625,y:.046875},{x:.546875,y:.046875},{x:.546875,y:.046875},{x:.578125,y:.046875},{x:.578125,y:.046875},{x:.609375,y:.046875},{x:.609375,y:.046875},{x:.640625,y:.046875},{x:.640625,y:.046875},{x:.671875,y:.046875},{x:.671875,y:.046875},{x:.703125,y:.046875},{x:.703125,y:.046875},{x:.734375,y:.046875},{x:.734375,y:.046875},{x:.765625,y:.046875},{x:.765625,y:.046875},{x:.796875,y:.046875},{x:.796875,y:.046875},{x:.828125,y:.046875},{x:.828125,y:.046875},{x:.859375,y:.046875},{x:.859375,y:.046875},{x:.890625,y:.046875},{x:.890625,y:.046875},{x:.921875,y:.046875},{x:.921875,y:.046875},{x:.953125,y:.046875},{x:.953125,y:.046875},{x:.984375,y:.046875},{x:.984375,y:.046875},{x:.015625,y:.078125},{x:.015625,y:.078125},{x:.046875,y:.078125},{x:.046875,y:.078125},{x:.078125,y:.078125},{x:.078125,y:.078125},{x:.109375,y:.078125},{x:.109375,y:.078125},{x:.140625,y:.078125},{x:.140625,y:.078125},{x:.171875,y:.078125},{x:.171875,y:.078125},{x:.203125,y:.078125},{x:.203125,y:.078125},{x:.234375,y:.078125},{x:.234375,y:.078125},{x:.265625,y:.078125},{x:.265625,y:.078125},{x:.296875,y:.078125},{x:.296875,y:.078125},{x:.328125,y:.078125},{x:.328125,y:.078125},{x:.359375,y:.078125},{x:.359375,y:.078125},{x:.390625,y:.078125},{x:.390625,y:.078125},{x:.421875,y:.078125},{x:.421875,y:.078125},{x:.453125,y:.078125},{x:.453125,y:.078125},{x:.484375,y:.078125},{x:.484375,y:.078125},{x:.515625,y:.078125},{x:.515625,y:.078125},{x:.546875,y:.078125},{x:.546875,y:.078125},{x:.578125,y:.078125},{x:.578125,y:.078125},{x:.609375,y:.078125},{x:.609375,y:.078125},{x:.640625,y:.078125},{x:.640625,y:.078125},{x:.671875,y:.078125},{x:.671875,y:.078125},{x:.703125,y:.078125},{x:.703125,y:.078125},{x:.734375,y:.078125},{x:.734375,y:.078125},{x:.765625,y:.078125},{x:.765625,y:.078125},{x:.796875,y:.078125},{x:.796875,y:.078125},{x:.828125,y:.078125},{x:.828125,y:.078125},{x:.859375,y:.078125},{x:.859375,y:.078125},{x:.890625,y:.078125},{x:.890625,y:.078125},{x:.921875,y:.078125},{x:.921875,y:.078125},{x:.953125,y:.078125},{x:.953125,y:.078125},{x:.984375,y:.078125},{x:.984375,y:.078125},{x:.015625,y:.109375},{x:.015625,y:.109375},{x:.046875,y:.109375},{x:.046875,y:.109375},{x:.078125,y:.109375},{x:.078125,y:.109375},{x:.109375,y:.109375},{x:.109375,y:.109375},{x:.140625,y:.109375},{x:.140625,y:.109375},{x:.171875,y:.109375},{x:.171875,y:.109375},{x:.203125,y:.109375},{x:.203125,y:.109375},{x:.234375,y:.109375},{x:.234375,y:.109375},{x:.265625,y:.109375},{x:.265625,y:.109375},{x:.296875,y:.109375},{x:.296875,y:.109375},{x:.328125,y:.109375},{x:.328125,y:.109375},{x:.359375,y:.109375},{x:.359375,y:.109375},{x:.390625,y:.109375},{x:.390625,y:.109375},{x:.421875,y:.109375},{x:.421875,y:.109375},{x:.453125,y:.109375},{x:.453125,y:.109375},{x:.484375,y:.109375},{x:.484375,y:.109375},{x:.515625,y:.109375},{x:.515625,y:.109375},{x:.546875,y:.109375},{x:.546875,y:.109375},{x:.578125,y:.109375},{x:.578125,y:.109375},{x:.609375,y:.109375},{x:.609375,y:.109375},{x:.640625,y:.109375},{x:.640625,y:.109375},{x:.671875,y:.109375},{x:.671875,y:.109375},{x:.703125,y:.109375},{x:.703125,y:.109375},{x:.734375,y:.109375},{x:.734375,y:.109375},{x:.765625,y:.109375},{x:.765625,y:.109375},{x:.796875,y:.109375},{x:.796875,y:.109375},{x:.828125,y:.109375},{x:.828125,y:.109375},{x:.859375,y:.109375},{x:.859375,y:.109375},{x:.890625,y:.109375},{x:.890625,y:.109375},{x:.921875,y:.109375},{x:.921875,y:.109375},{x:.953125,y:.109375},{x:.953125,y:.109375},{x:.984375,y:.109375},{x:.984375,y:.109375},{x:.015625,y:.140625},{x:.015625,y:.140625},{x:.046875,y:.140625},{x:.046875,y:.140625},{x:.078125,y:.140625},{x:.078125,y:.140625},{x:.109375,y:.140625},{x:.109375,y:.140625},{x:.140625,y:.140625},{x:.140625,y:.140625},{x:.171875,y:.140625},{x:.171875,y:.140625},{x:.203125,y:.140625},{x:.203125,y:.140625},{x:.234375,y:.140625},{x:.234375,y:.140625},{x:.265625,y:.140625},{x:.265625,y:.140625},{x:.296875,y:.140625},{x:.296875,y:.140625},{x:.328125,y:.140625},{x:.328125,y:.140625},{x:.359375,y:.140625},{x:.359375,y:.140625},{x:.390625,y:.140625},{x:.390625,y:.140625},{x:.421875,y:.140625},{x:.421875,y:.140625},{x:.453125,y:.140625},{x:.453125,y:.140625},{x:.484375,y:.140625},{x:.484375,y:.140625},{x:.515625,y:.140625},{x:.515625,y:.140625},{x:.546875,y:.140625},{x:.546875,y:.140625},{x:.578125,y:.140625},{x:.578125,y:.140625},{x:.609375,y:.140625},{x:.609375,y:.140625},{x:.640625,y:.140625},{x:.640625,y:.140625},{x:.671875,y:.140625},{x:.671875,y:.140625},{x:.703125,y:.140625},{x:.703125,y:.140625},{x:.734375,y:.140625},{x:.734375,y:.140625},{x:.765625,y:.140625},{x:.765625,y:.140625},{x:.796875,y:.140625},{x:.796875,y:.140625},{x:.828125,y:.140625},{x:.828125,y:.140625},{x:.859375,y:.140625},{x:.859375,y:.140625},{x:.890625,y:.140625},{x:.890625,y:.140625},{x:.921875,y:.140625},{x:.921875,y:.140625},{x:.953125,y:.140625},{x:.953125,y:.140625},{x:.984375,y:.140625},{x:.984375,y:.140625},{x:.015625,y:.171875},{x:.015625,y:.171875},{x:.046875,y:.171875},{x:.046875,y:.171875},{x:.078125,y:.171875},{x:.078125,y:.171875},{x:.109375,y:.171875},{x:.109375,y:.171875},{x:.140625,y:.171875},{x:.140625,y:.171875},{x:.171875,y:.171875},{x:.171875,y:.171875},{x:.203125,y:.171875},{x:.203125,y:.171875},{x:.234375,y:.171875},{x:.234375,y:.171875},{x:.265625,y:.171875},{x:.265625,y:.171875},{x:.296875,y:.171875},{x:.296875,y:.171875},{x:.328125,y:.171875},{x:.328125,y:.171875},{x:.359375,y:.171875},{x:.359375,y:.171875},{x:.390625,y:.171875},{x:.390625,y:.171875},{x:.421875,y:.171875},{x:.421875,y:.171875},{x:.453125,y:.171875},{x:.453125,y:.171875},{x:.484375,y:.171875},{x:.484375,y:.171875},{x:.515625,y:.171875},{x:.515625,y:.171875},{x:.546875,y:.171875},{x:.546875,y:.171875},{x:.578125,y:.171875},{x:.578125,y:.171875},{x:.609375,y:.171875},{x:.609375,y:.171875},{x:.640625,y:.171875},{x:.640625,y:.171875},{x:.671875,y:.171875},{x:.671875,y:.171875},{x:.703125,y:.171875},{x:.703125,y:.171875},{x:.734375,y:.171875},{x:.734375,y:.171875},{x:.765625,y:.171875},{x:.765625,y:.171875},{x:.796875,y:.171875},{x:.796875,y:.171875},{x:.828125,y:.171875},{x:.828125,y:.171875},{x:.859375,y:.171875},{x:.859375,y:.171875},{x:.890625,y:.171875},{x:.890625,y:.171875},{x:.921875,y:.171875},{x:.921875,y:.171875},{x:.953125,y:.171875},{x:.953125,y:.171875},{x:.984375,y:.171875},{x:.984375,y:.171875},{x:.015625,y:.203125},{x:.015625,y:.203125},{x:.046875,y:.203125},{x:.046875,y:.203125},{x:.078125,y:.203125},{x:.078125,y:.203125},{x:.109375,y:.203125},{x:.109375,y:.203125},{x:.140625,y:.203125},{x:.140625,y:.203125},{x:.171875,y:.203125},{x:.171875,y:.203125},{x:.203125,y:.203125},{x:.203125,y:.203125},{x:.234375,y:.203125},{x:.234375,y:.203125},{x:.265625,y:.203125},{x:.265625,y:.203125},{x:.296875,y:.203125},{x:.296875,y:.203125},{x:.328125,y:.203125},{x:.328125,y:.203125},{x:.359375,y:.203125},{x:.359375,y:.203125},{x:.390625,y:.203125},{x:.390625,y:.203125},{x:.421875,y:.203125},{x:.421875,y:.203125},{x:.453125,y:.203125},{x:.453125,y:.203125},{x:.484375,y:.203125},{x:.484375,y:.203125},{x:.515625,y:.203125},{x:.515625,y:.203125},{x:.546875,y:.203125},{x:.546875,y:.203125},{x:.578125,y:.203125},{x:.578125,y:.203125},{x:.609375,y:.203125},{x:.609375,y:.203125},{x:.640625,y:.203125},{x:.640625,y:.203125},{x:.671875,y:.203125},{x:.671875,y:.203125},{x:.703125,y:.203125},{x:.703125,y:.203125},{x:.734375,y:.203125},{x:.734375,y:.203125},{x:.765625,y:.203125},{x:.765625,y:.203125},{x:.796875,y:.203125},{x:.796875,y:.203125},{x:.828125,y:.203125},{x:.828125,y:.203125},{x:.859375,y:.203125},{x:.859375,y:.203125},{x:.890625,y:.203125},{x:.890625,y:.203125},{x:.921875,y:.203125},{x:.921875,y:.203125},{x:.953125,y:.203125},{x:.953125,y:.203125},{x:.984375,y:.203125},{x:.984375,y:.203125},{x:.015625,y:.234375},{x:.015625,y:.234375},{x:.046875,y:.234375},{x:.046875,y:.234375},{x:.078125,y:.234375},{x:.078125,y:.234375},{x:.109375,y:.234375},{x:.109375,y:.234375},{x:.140625,y:.234375},{x:.140625,y:.234375},{x:.171875,y:.234375},{x:.171875,y:.234375},{x:.203125,y:.234375},{x:.203125,y:.234375},{x:.234375,y:.234375},{x:.234375,y:.234375},{x:.265625,y:.234375},{x:.265625,y:.234375},{x:.296875,y:.234375},{x:.296875,y:.234375},{x:.328125,y:.234375},{x:.328125,y:.234375},{x:.359375,y:.234375},{x:.359375,y:.234375},{x:.390625,y:.234375},{x:.390625,y:.234375},{x:.421875,y:.234375},{x:.421875,y:.234375},{x:.453125,y:.234375},{x:.453125,y:.234375},{x:.484375,y:.234375},{x:.484375,y:.234375},{x:.515625,y:.234375},{x:.515625,y:.234375},{x:.546875,y:.234375},{x:.546875,y:.234375},{x:.578125,y:.234375},{x:.578125,y:.234375},{x:.609375,y:.234375},{x:.609375,y:.234375},{x:.640625,y:.234375},{x:.640625,y:.234375},{x:.671875,y:.234375},{x:.671875,y:.234375},{x:.703125,y:.234375},{x:.703125,y:.234375},{x:.734375,y:.234375},{x:.734375,y:.234375},{x:.765625,y:.234375},{x:.765625,y:.234375},{x:.796875,y:.234375},{x:.796875,y:.234375},{x:.828125,y:.234375},{x:.828125,y:.234375},{x:.859375,y:.234375},{x:.859375,y:.234375},{x:.890625,y:.234375},{x:.890625,y:.234375},{x:.921875,y:.234375},{x:.921875,y:.234375},{x:.953125,y:.234375},{x:.953125,y:.234375},{x:.984375,y:.234375},{x:.984375,y:.234375},{x:.015625,y:.265625},{x:.015625,y:.265625},{x:.046875,y:.265625},{x:.046875,y:.265625},{x:.078125,y:.265625},{x:.078125,y:.265625},{x:.109375,y:.265625},{x:.109375,y:.265625},{x:.140625,y:.265625},{x:.140625,y:.265625},{x:.171875,y:.265625},{x:.171875,y:.265625},{x:.203125,y:.265625},{x:.203125,y:.265625},{x:.234375,y:.265625},{x:.234375,y:.265625},{x:.265625,y:.265625},{x:.265625,y:.265625},{x:.296875,y:.265625},{x:.296875,y:.265625},{x:.328125,y:.265625},{x:.328125,y:.265625},{x:.359375,y:.265625},{x:.359375,y:.265625},{x:.390625,y:.265625},{x:.390625,y:.265625},{x:.421875,y:.265625},{x:.421875,y:.265625},{x:.453125,y:.265625},{x:.453125,y:.265625},{x:.484375,y:.265625},{x:.484375,y:.265625},{x:.515625,y:.265625},{x:.515625,y:.265625},{x:.546875,y:.265625},{x:.546875,y:.265625},{x:.578125,y:.265625},{x:.578125,y:.265625},{x:.609375,y:.265625},{x:.609375,y:.265625},{x:.640625,y:.265625},{x:.640625,y:.265625},{x:.671875,y:.265625},{x:.671875,y:.265625},{x:.703125,y:.265625},{x:.703125,y:.265625},{x:.734375,y:.265625},{x:.734375,y:.265625},{x:.765625,y:.265625},{x:.765625,y:.265625},{x:.796875,y:.265625},{x:.796875,y:.265625},{x:.828125,y:.265625},{x:.828125,y:.265625},{x:.859375,y:.265625},{x:.859375,y:.265625},{x:.890625,y:.265625},{x:.890625,y:.265625},{x:.921875,y:.265625},{x:.921875,y:.265625},{x:.953125,y:.265625},{x:.953125,y:.265625},{x:.984375,y:.265625},{x:.984375,y:.265625},{x:.015625,y:.296875},{x:.015625,y:.296875},{x:.046875,y:.296875},{x:.046875,y:.296875},{x:.078125,y:.296875},{x:.078125,y:.296875},{x:.109375,y:.296875},{x:.109375,y:.296875},{x:.140625,y:.296875},{x:.140625,y:.296875},{x:.171875,y:.296875},{x:.171875,y:.296875},{x:.203125,y:.296875},{x:.203125,y:.296875},{x:.234375,y:.296875},{x:.234375,y:.296875},{x:.265625,y:.296875},{x:.265625,y:.296875},{x:.296875,y:.296875},{x:.296875,y:.296875},{x:.328125,y:.296875},{x:.328125,y:.296875},{x:.359375,y:.296875},{x:.359375,y:.296875},{x:.390625,y:.296875},{x:.390625,y:.296875},{x:.421875,y:.296875},{x:.421875,y:.296875},{x:.453125,y:.296875},{x:.453125,y:.296875},{x:.484375,y:.296875},{x:.484375,y:.296875},{x:.515625,y:.296875},{x:.515625,y:.296875},{x:.546875,y:.296875},{x:.546875,y:.296875},{x:.578125,y:.296875},{x:.578125,y:.296875},{x:.609375,y:.296875},{x:.609375,y:.296875},{x:.640625,y:.296875},{x:.640625,y:.296875},{x:.671875,y:.296875},{x:.671875,y:.296875},{x:.703125,y:.296875},{x:.703125,y:.296875},{x:.734375,y:.296875},{x:.734375,y:.296875},{x:.765625,y:.296875},{x:.765625,y:.296875},{x:.796875,y:.296875},{x:.796875,y:.296875},{x:.828125,y:.296875},{x:.828125,y:.296875},{x:.859375,y:.296875},{x:.859375,y:.296875},{x:.890625,y:.296875},{x:.890625,y:.296875},{x:.921875,y:.296875},{x:.921875,y:.296875},{x:.953125,y:.296875},{x:.953125,y:.296875},{x:.984375,y:.296875},{x:.984375,y:.296875},{x:.015625,y:.328125},{x:.015625,y:.328125},{x:.046875,y:.328125},{x:.046875,y:.328125},{x:.078125,y:.328125},{x:.078125,y:.328125},{x:.109375,y:.328125},{x:.109375,y:.328125},{x:.140625,y:.328125},{x:.140625,y:.328125},{x:.171875,y:.328125},{x:.171875,y:.328125},{x:.203125,y:.328125},{x:.203125,y:.328125},{x:.234375,y:.328125},{x:.234375,y:.328125},{x:.265625,y:.328125},{x:.265625,y:.328125},{x:.296875,y:.328125},{x:.296875,y:.328125},{x:.328125,y:.328125},{x:.328125,y:.328125},{x:.359375,y:.328125},{x:.359375,y:.328125},{x:.390625,y:.328125},{x:.390625,y:.328125},{x:.421875,y:.328125},{x:.421875,y:.328125},{x:.453125,y:.328125},{x:.453125,y:.328125},{x:.484375,y:.328125},{x:.484375,y:.328125},{x:.515625,y:.328125},{x:.515625,y:.328125},{x:.546875,y:.328125},{x:.546875,y:.328125},{x:.578125,y:.328125},{x:.578125,y:.328125},{x:.609375,y:.328125},{x:.609375,y:.328125},{x:.640625,y:.328125},{x:.640625,y:.328125},{x:.671875,y:.328125},{x:.671875,y:.328125},{x:.703125,y:.328125},{x:.703125,y:.328125},{x:.734375,y:.328125},{x:.734375,y:.328125},{x:.765625,y:.328125},{x:.765625,y:.328125},{x:.796875,y:.328125},{x:.796875,y:.328125},{x:.828125,y:.328125},{x:.828125,y:.328125},{x:.859375,y:.328125},{x:.859375,y:.328125},{x:.890625,y:.328125},{x:.890625,y:.328125},{x:.921875,y:.328125},{x:.921875,y:.328125},{x:.953125,y:.328125},{x:.953125,y:.328125},{x:.984375,y:.328125},{x:.984375,y:.328125},{x:.015625,y:.359375},{x:.015625,y:.359375},{x:.046875,y:.359375},{x:.046875,y:.359375},{x:.078125,y:.359375},{x:.078125,y:.359375},{x:.109375,y:.359375},{x:.109375,y:.359375},{x:.140625,y:.359375},{x:.140625,y:.359375},{x:.171875,y:.359375},{x:.171875,y:.359375},{x:.203125,y:.359375},{x:.203125,y:.359375},{x:.234375,y:.359375},{x:.234375,y:.359375},{x:.265625,y:.359375},{x:.265625,y:.359375},{x:.296875,y:.359375},{x:.296875,y:.359375},{x:.328125,y:.359375},{x:.328125,y:.359375},{x:.359375,y:.359375},{x:.359375,y:.359375},{x:.390625,y:.359375},{x:.390625,y:.359375},{x:.421875,y:.359375},{x:.421875,y:.359375},{x:.453125,y:.359375},{x:.453125,y:.359375},{x:.484375,y:.359375},{x:.484375,y:.359375},{x:.515625,y:.359375},{x:.515625,y:.359375},{x:.546875,y:.359375},{x:.546875,y:.359375},{x:.578125,y:.359375},{x:.578125,y:.359375},{x:.609375,y:.359375},{x:.609375,y:.359375},{x:.640625,y:.359375},{x:.640625,y:.359375},{x:.671875,y:.359375},{x:.671875,y:.359375},{x:.703125,y:.359375},{x:.703125,y:.359375},{x:.734375,y:.359375},{x:.734375,y:.359375},{x:.765625,y:.359375},{x:.765625,y:.359375},{x:.796875,y:.359375},{x:.796875,y:.359375},{x:.828125,y:.359375},{x:.828125,y:.359375},{x:.859375,y:.359375},{x:.859375,y:.359375},{x:.890625,y:.359375},{x:.890625,y:.359375},{x:.921875,y:.359375},{x:.921875,y:.359375},{x:.953125,y:.359375},{x:.953125,y:.359375},{x:.984375,y:.359375},{x:.984375,y:.359375},{x:.015625,y:.390625},{x:.015625,y:.390625},{x:.046875,y:.390625},{x:.046875,y:.390625},{x:.078125,y:.390625},{x:.078125,y:.390625},{x:.109375,y:.390625},{x:.109375,y:.390625},{x:.140625,y:.390625},{x:.140625,y:.390625},{x:.171875,y:.390625},{x:.171875,y:.390625},{x:.203125,y:.390625},{x:.203125,y:.390625},{x:.234375,y:.390625},{x:.234375,y:.390625},{x:.265625,y:.390625},{x:.265625,y:.390625},{x:.296875,y:.390625},{x:.296875,y:.390625},{x:.328125,y:.390625},{x:.328125,y:.390625},{x:.359375,y:.390625},{x:.359375,y:.390625},{x:.390625,y:.390625},{x:.390625,y:.390625},{x:.421875,y:.390625},{x:.421875,y:.390625},{x:.453125,y:.390625},{x:.453125,y:.390625},{x:.484375,y:.390625},{x:.484375,y:.390625},{x:.515625,y:.390625},{x:.515625,y:.390625},{x:.546875,y:.390625},{x:.546875,y:.390625},{x:.578125,y:.390625},{x:.578125,y:.390625},{x:.609375,y:.390625},{x:.609375,y:.390625},{x:.640625,y:.390625},{x:.640625,y:.390625},{x:.671875,y:.390625},{x:.671875,y:.390625},{x:.703125,y:.390625},{x:.703125,y:.390625},{x:.734375,y:.390625},{x:.734375,y:.390625},{x:.765625,y:.390625},{x:.765625,y:.390625},{x:.796875,y:.390625},{x:.796875,y:.390625},{x:.828125,y:.390625},{x:.828125,y:.390625},{x:.859375,y:.390625},{x:.859375,y:.390625},{x:.890625,y:.390625},{x:.890625,y:.390625},{x:.921875,y:.390625},{x:.921875,y:.390625},{x:.953125,y:.390625},{x:.953125,y:.390625},{x:.984375,y:.390625},{x:.984375,y:.390625},{x:.015625,y:.421875},{x:.015625,y:.421875},{x:.046875,y:.421875},{x:.046875,y:.421875},{x:.078125,y:.421875},{x:.078125,y:.421875},{x:.109375,y:.421875},{x:.109375,y:.421875},{x:.140625,y:.421875},{x:.140625,y:.421875},{x:.171875,y:.421875},{x:.171875,y:.421875},{x:.203125,y:.421875},{x:.203125,y:.421875},{x:.234375,y:.421875},{x:.234375,y:.421875},{x:.265625,y:.421875},{x:.265625,y:.421875},{x:.296875,y:.421875},{x:.296875,y:.421875},{x:.328125,y:.421875},{x:.328125,y:.421875},{x:.359375,y:.421875},{x:.359375,y:.421875},{x:.390625,y:.421875},{x:.390625,y:.421875},{x:.421875,y:.421875},{x:.421875,y:.421875},{x:.453125,y:.421875},{x:.453125,y:.421875},{x:.484375,y:.421875},{x:.484375,y:.421875},{x:.515625,y:.421875},{x:.515625,y:.421875},{x:.546875,y:.421875},{x:.546875,y:.421875},{x:.578125,y:.421875},{x:.578125,y:.421875},{x:.609375,y:.421875},{x:.609375,y:.421875},{x:.640625,y:.421875},{x:.640625,y:.421875},{x:.671875,y:.421875},{x:.671875,y:.421875},{x:.703125,y:.421875},{x:.703125,y:.421875},{x:.734375,y:.421875},{x:.734375,y:.421875},{x:.765625,y:.421875},{x:.765625,y:.421875},{x:.796875,y:.421875},{x:.796875,y:.421875},{x:.828125,y:.421875},{x:.828125,y:.421875},{x:.859375,y:.421875},{x:.859375,y:.421875},{x:.890625,y:.421875},{x:.890625,y:.421875},{x:.921875,y:.421875},{x:.921875,y:.421875},{x:.953125,y:.421875},{x:.953125,y:.421875},{x:.984375,y:.421875},{x:.984375,y:.421875},{x:.015625,y:.453125},{x:.015625,y:.453125},{x:.046875,y:.453125},{x:.046875,y:.453125},{x:.078125,y:.453125},{x:.078125,y:.453125},{x:.109375,y:.453125},{x:.109375,y:.453125},{x:.140625,y:.453125},{x:.140625,y:.453125},{x:.171875,y:.453125},{x:.171875,y:.453125},{x:.203125,y:.453125},{x:.203125,y:.453125},{x:.234375,y:.453125},{x:.234375,y:.453125},{x:.265625,y:.453125},{x:.265625,y:.453125},{x:.296875,y:.453125},{x:.296875,y:.453125},{x:.328125,y:.453125},{x:.328125,y:.453125},{x:.359375,y:.453125},{x:.359375,y:.453125},{x:.390625,y:.453125},{x:.390625,y:.453125},{x:.421875,y:.453125},{x:.421875,y:.453125},{x:.453125,y:.453125},{x:.453125,y:.453125},{x:.484375,y:.453125},{x:.484375,y:.453125},{x:.515625,y:.453125},{x:.515625,y:.453125},{x:.546875,y:.453125},{x:.546875,y:.453125},{x:.578125,y:.453125},{x:.578125,y:.453125},{x:.609375,y:.453125},{x:.609375,y:.453125},{x:.640625,y:.453125},{x:.640625,y:.453125},{x:.671875,y:.453125},{x:.671875,y:.453125},{x:.703125,y:.453125},{x:.703125,y:.453125},{x:.734375,y:.453125},{x:.734375,y:.453125},{x:.765625,y:.453125},{x:.765625,y:.453125},{x:.796875,y:.453125},{x:.796875,y:.453125},{x:.828125,y:.453125},{x:.828125,y:.453125},{x:.859375,y:.453125},{x:.859375,y:.453125},{x:.890625,y:.453125},{x:.890625,y:.453125},{x:.921875,y:.453125},{x:.921875,y:.453125},{x:.953125,y:.453125},{x:.953125,y:.453125},{x:.984375,y:.453125},{x:.984375,y:.453125},{x:.015625,y:.484375},{x:.015625,y:.484375},{x:.046875,y:.484375},{x:.046875,y:.484375},{x:.078125,y:.484375},{x:.078125,y:.484375},{x:.109375,y:.484375},{x:.109375,y:.484375},{x:.140625,y:.484375},{x:.140625,y:.484375},{x:.171875,y:.484375},{x:.171875,y:.484375},{x:.203125,y:.484375},{x:.203125,y:.484375},{x:.234375,y:.484375},{x:.234375,y:.484375},{x:.265625,y:.484375},{x:.265625,y:.484375},{x:.296875,y:.484375},{x:.296875,y:.484375},{x:.328125,y:.484375},{x:.328125,y:.484375},{x:.359375,y:.484375},{x:.359375,y:.484375},{x:.390625,y:.484375},{x:.390625,y:.484375},{x:.421875,y:.484375},{x:.421875,y:.484375},{x:.453125,y:.484375},{x:.453125,y:.484375},{x:.484375,y:.484375},{x:.484375,y:.484375},{x:.515625,y:.484375},{x:.515625,y:.484375},{x:.546875,y:.484375},{x:.546875,y:.484375},{x:.578125,y:.484375},{x:.578125,y:.484375},{x:.609375,y:.484375},{x:.609375,y:.484375},{x:.640625,y:.484375},{x:.640625,y:.484375},{x:.671875,y:.484375},{x:.671875,y:.484375},{x:.703125,y:.484375},{x:.703125,y:.484375},{x:.734375,y:.484375},{x:.734375,y:.484375},{x:.765625,y:.484375},{x:.765625,y:.484375},{x:.796875,y:.484375},{x:.796875,y:.484375},{x:.828125,y:.484375},{x:.828125,y:.484375},{x:.859375,y:.484375},{x:.859375,y:.484375},{x:.890625,y:.484375},{x:.890625,y:.484375},{x:.921875,y:.484375},{x:.921875,y:.484375},{x:.953125,y:.484375},{x:.953125,y:.484375},{x:.984375,y:.484375},{x:.984375,y:.484375},{x:.015625,y:.515625},{x:.015625,y:.515625},{x:.046875,y:.515625},{x:.046875,y:.515625},{x:.078125,y:.515625},{x:.078125,y:.515625},{x:.109375,y:.515625},{x:.109375,y:.515625},{x:.140625,y:.515625},{x:.140625,y:.515625},{x:.171875,y:.515625},{x:.171875,y:.515625},{x:.203125,y:.515625},{x:.203125,y:.515625},{x:.234375,y:.515625},{x:.234375,y:.515625},{x:.265625,y:.515625},{x:.265625,y:.515625},{x:.296875,y:.515625},{x:.296875,y:.515625},{x:.328125,y:.515625},{x:.328125,y:.515625},{x:.359375,y:.515625},{x:.359375,y:.515625},{x:.390625,y:.515625},{x:.390625,y:.515625},{x:.421875,y:.515625},{x:.421875,y:.515625},{x:.453125,y:.515625},{x:.453125,y:.515625},{x:.484375,y:.515625},{x:.484375,y:.515625},{x:.515625,y:.515625},{x:.515625,y:.515625},{x:.546875,y:.515625},{x:.546875,y:.515625},{x:.578125,y:.515625},{x:.578125,y:.515625},{x:.609375,y:.515625},{x:.609375,y:.515625},{x:.640625,y:.515625},{x:.640625,y:.515625},{x:.671875,y:.515625},{x:.671875,y:.515625},{x:.703125,y:.515625},{x:.703125,y:.515625},{x:.734375,y:.515625},{x:.734375,y:.515625},{x:.765625,y:.515625},{x:.765625,y:.515625},{x:.796875,y:.515625},{x:.796875,y:.515625},{x:.828125,y:.515625},{x:.828125,y:.515625},{x:.859375,y:.515625},{x:.859375,y:.515625},{x:.890625,y:.515625},{x:.890625,y:.515625},{x:.921875,y:.515625},{x:.921875,y:.515625},{x:.953125,y:.515625},{x:.953125,y:.515625},{x:.984375,y:.515625},{x:.984375,y:.515625},{x:.015625,y:.546875},{x:.015625,y:.546875},{x:.046875,y:.546875},{x:.046875,y:.546875},{x:.078125,y:.546875},{x:.078125,y:.546875},{x:.109375,y:.546875},{x:.109375,y:.546875},{x:.140625,y:.546875},{x:.140625,y:.546875},{x:.171875,y:.546875},{x:.171875,y:.546875},{x:.203125,y:.546875},{x:.203125,y:.546875},{x:.234375,y:.546875},{x:.234375,y:.546875},{x:.265625,y:.546875},{x:.265625,y:.546875},{x:.296875,y:.546875},{x:.296875,y:.546875},{x:.328125,y:.546875},{x:.328125,y:.546875},{x:.359375,y:.546875},{x:.359375,y:.546875},{x:.390625,y:.546875},{x:.390625,y:.546875},{x:.421875,y:.546875},{x:.421875,y:.546875},{x:.453125,y:.546875},{x:.453125,y:.546875},{x:.484375,y:.546875},{x:.484375,y:.546875},{x:.515625,y:.546875},{x:.515625,y:.546875},{x:.546875,y:.546875},{x:.546875,y:.546875},{x:.578125,y:.546875},{x:.578125,y:.546875},{x:.609375,y:.546875},{x:.609375,y:.546875},{x:.640625,y:.546875},{x:.640625,y:.546875},{x:.671875,y:.546875},{x:.671875,y:.546875},{x:.703125,y:.546875},{x:.703125,y:.546875},{x:.734375,y:.546875},{x:.734375,y:.546875},{x:.765625,y:.546875},{x:.765625,y:.546875},{x:.796875,y:.546875},{x:.796875,y:.546875},{x:.828125,y:.546875},{x:.828125,y:.546875},{x:.859375,y:.546875},{x:.859375,y:.546875},{x:.890625,y:.546875},{x:.890625,y:.546875},{x:.921875,y:.546875},{x:.921875,y:.546875},{x:.953125,y:.546875},{x:.953125,y:.546875},{x:.984375,y:.546875},{x:.984375,y:.546875},{x:.015625,y:.578125},{x:.015625,y:.578125},{x:.046875,y:.578125},{x:.046875,y:.578125},{x:.078125,y:.578125},{x:.078125,y:.578125},{x:.109375,y:.578125},{x:.109375,y:.578125},{x:.140625,y:.578125},{x:.140625,y:.578125},{x:.171875,y:.578125},{x:.171875,y:.578125},{x:.203125,y:.578125},{x:.203125,y:.578125},{x:.234375,y:.578125},{x:.234375,y:.578125},{x:.265625,y:.578125},{x:.265625,y:.578125},{x:.296875,y:.578125},{x:.296875,y:.578125},{x:.328125,y:.578125},{x:.328125,y:.578125},{x:.359375,y:.578125},{x:.359375,y:.578125},{x:.390625,y:.578125},{x:.390625,y:.578125},{x:.421875,y:.578125},{x:.421875,y:.578125},{x:.453125,y:.578125},{x:.453125,y:.578125},{x:.484375,y:.578125},{x:.484375,y:.578125},{x:.515625,y:.578125},{x:.515625,y:.578125},{x:.546875,y:.578125},{x:.546875,y:.578125},{x:.578125,y:.578125},{x:.578125,y:.578125},{x:.609375,y:.578125},{x:.609375,y:.578125},{x:.640625,y:.578125},{x:.640625,y:.578125},{x:.671875,y:.578125},{x:.671875,y:.578125},{x:.703125,y:.578125},{x:.703125,y:.578125},{x:.734375,y:.578125},{x:.734375,y:.578125},{x:.765625,y:.578125},{x:.765625,y:.578125},{x:.796875,y:.578125},{x:.796875,y:.578125},{x:.828125,y:.578125},{x:.828125,y:.578125},{x:.859375,y:.578125},{x:.859375,y:.578125},{x:.890625,y:.578125},{x:.890625,y:.578125},{x:.921875,y:.578125},{x:.921875,y:.578125},{x:.953125,y:.578125},{x:.953125,y:.578125},{x:.984375,y:.578125},{x:.984375,y:.578125},{x:.015625,y:.609375},{x:.015625,y:.609375},{x:.046875,y:.609375},{x:.046875,y:.609375},{x:.078125,y:.609375},{x:.078125,y:.609375},{x:.109375,y:.609375},{x:.109375,y:.609375},{x:.140625,y:.609375},{x:.140625,y:.609375},{x:.171875,y:.609375},{x:.171875,y:.609375},{x:.203125,y:.609375},{x:.203125,y:.609375},{x:.234375,y:.609375},{x:.234375,y:.609375},{x:.265625,y:.609375},{x:.265625,y:.609375},{x:.296875,y:.609375},{x:.296875,y:.609375},{x:.328125,y:.609375},{x:.328125,y:.609375},{x:.359375,y:.609375},{x:.359375,y:.609375},{x:.390625,y:.609375},{x:.390625,y:.609375},{x:.421875,y:.609375},{x:.421875,y:.609375},{x:.453125,y:.609375},{x:.453125,y:.609375},{x:.484375,y:.609375},{x:.484375,y:.609375},{x:.515625,y:.609375},{x:.515625,y:.609375},{x:.546875,y:.609375},{x:.546875,y:.609375},{x:.578125,y:.609375},{x:.578125,y:.609375},{x:.609375,y:.609375},{x:.609375,y:.609375},{x:.640625,y:.609375},{x:.640625,y:.609375},{x:.671875,y:.609375},{x:.671875,y:.609375},{x:.703125,y:.609375},{x:.703125,y:.609375},{x:.734375,y:.609375},{x:.734375,y:.609375},{x:.765625,y:.609375},{x:.765625,y:.609375},{x:.796875,y:.609375},{x:.796875,y:.609375},{x:.828125,y:.609375},{x:.828125,y:.609375},{x:.859375,y:.609375},{x:.859375,y:.609375},{x:.890625,y:.609375},{x:.890625,y:.609375},{x:.921875,y:.609375},{x:.921875,y:.609375},{x:.953125,y:.609375},{x:.953125,y:.609375},{x:.984375,y:.609375},{x:.984375,y:.609375},{x:.015625,y:.640625},{x:.015625,y:.640625},{x:.046875,y:.640625},{x:.046875,y:.640625},{x:.078125,y:.640625},{x:.078125,y:.640625},{x:.109375,y:.640625},{x:.109375,y:.640625},{x:.140625,y:.640625},{x:.140625,y:.640625},{x:.171875,y:.640625},{x:.171875,y:.640625},{x:.203125,y:.640625},{x:.203125,y:.640625},{x:.234375,y:.640625},{x:.234375,y:.640625},{x:.265625,y:.640625},{x:.265625,y:.640625},{x:.296875,y:.640625},{x:.296875,y:.640625},{x:.328125,y:.640625},{x:.328125,y:.640625},{x:.359375,y:.640625},{x:.359375,y:.640625},{x:.390625,y:.640625},{x:.390625,y:.640625},{x:.421875,y:.640625},{x:.421875,y:.640625},{x:.453125,y:.640625},{x:.453125,y:.640625},{x:.484375,y:.640625},{x:.484375,y:.640625},{x:.515625,y:.640625},{x:.515625,y:.640625},{x:.546875,y:.640625},{x:.546875,y:.640625},{x:.578125,y:.640625},{x:.578125,y:.640625},{x:.609375,y:.640625},{x:.609375,y:.640625},{x:.640625,y:.640625},{x:.640625,y:.640625},{x:.671875,y:.640625},{x:.671875,y:.640625},{x:.703125,y:.640625},{x:.703125,y:.640625},{x:.734375,y:.640625},{x:.734375,y:.640625},{x:.765625,y:.640625},{x:.765625,y:.640625},{x:.796875,y:.640625},{x:.796875,y:.640625},{x:.828125,y:.640625},{x:.828125,y:.640625},{x:.859375,y:.640625},{x:.859375,y:.640625},{x:.890625,y:.640625},{x:.890625,y:.640625},{x:.921875,y:.640625},{x:.921875,y:.640625},{x:.953125,y:.640625},{x:.953125,y:.640625},{x:.984375,y:.640625},{x:.984375,y:.640625},{x:.015625,y:.671875},{x:.015625,y:.671875},{x:.046875,y:.671875},{x:.046875,y:.671875},{x:.078125,y:.671875},{x:.078125,y:.671875},{x:.109375,y:.671875},{x:.109375,y:.671875},{x:.140625,y:.671875},{x:.140625,y:.671875},{x:.171875,y:.671875},{x:.171875,y:.671875},{x:.203125,y:.671875},{x:.203125,y:.671875},{x:.234375,y:.671875},{x:.234375,y:.671875},{x:.265625,y:.671875},{x:.265625,y:.671875},{x:.296875,y:.671875},{x:.296875,y:.671875},{x:.328125,y:.671875},{x:.328125,y:.671875},{x:.359375,y:.671875},{x:.359375,y:.671875},{x:.390625,y:.671875},{x:.390625,y:.671875},{x:.421875,y:.671875},{x:.421875,y:.671875},{x:.453125,y:.671875},{x:.453125,y:.671875},{x:.484375,y:.671875},{x:.484375,y:.671875},{x:.515625,y:.671875},{x:.515625,y:.671875},{x:.546875,y:.671875},{x:.546875,y:.671875},{x:.578125,y:.671875},{x:.578125,y:.671875},{x:.609375,y:.671875},{x:.609375,y:.671875},{x:.640625,y:.671875},{x:.640625,y:.671875},{x:.671875,y:.671875},{x:.671875,y:.671875},{x:.703125,y:.671875},{x:.703125,y:.671875},{x:.734375,y:.671875},{x:.734375,y:.671875},{x:.765625,y:.671875},{x:.765625,y:.671875},{x:.796875,y:.671875},{x:.796875,y:.671875},{x:.828125,y:.671875},{x:.828125,y:.671875},{x:.859375,y:.671875},{x:.859375,y:.671875},{x:.890625,y:.671875},{x:.890625,y:.671875},{x:.921875,y:.671875},{x:.921875,y:.671875},{x:.953125,y:.671875},{x:.953125,y:.671875},{x:.984375,y:.671875},{x:.984375,y:.671875},{x:.015625,y:.703125},{x:.015625,y:.703125},{x:.046875,y:.703125},{x:.046875,y:.703125},{x:.078125,y:.703125},{x:.078125,y:.703125},{x:.109375,y:.703125},{x:.109375,y:.703125},{x:.140625,y:.703125},{x:.140625,y:.703125},{x:.171875,y:.703125},{x:.171875,y:.703125},{x:.203125,y:.703125},{x:.203125,y:.703125},{x:.234375,y:.703125},{x:.234375,y:.703125},{x:.265625,y:.703125},{x:.265625,y:.703125},{x:.296875,y:.703125},{x:.296875,y:.703125},{x:.328125,y:.703125},{x:.328125,y:.703125},{x:.359375,y:.703125},{x:.359375,y:.703125},{x:.390625,y:.703125},{x:.390625,y:.703125},{x:.421875,y:.703125},{x:.421875,y:.703125},{x:.453125,y:.703125},{x:.453125,y:.703125},{x:.484375,y:.703125},{x:.484375,y:.703125},{x:.515625,y:.703125},{x:.515625,y:.703125},{x:.546875,y:.703125},{x:.546875,y:.703125},{x:.578125,y:.703125},{x:.578125,y:.703125},{x:.609375,y:.703125},{x:.609375,y:.703125},{x:.640625,y:.703125},{x:.640625,y:.703125},{x:.671875,y:.703125},{x:.671875,y:.703125},{x:.703125,y:.703125},{x:.703125,y:.703125},{x:.734375,y:.703125},{x:.734375,y:.703125},{x:.765625,y:.703125},{x:.765625,y:.703125},{x:.796875,y:.703125},{x:.796875,y:.703125},{x:.828125,y:.703125},{x:.828125,y:.703125},{x:.859375,y:.703125},{x:.859375,y:.703125},{x:.890625,y:.703125},{x:.890625,y:.703125},{x:.921875,y:.703125},{x:.921875,y:.703125},{x:.953125,y:.703125},{x:.953125,y:.703125},{x:.984375,y:.703125},{x:.984375,y:.703125},{x:.015625,y:.734375},{x:.015625,y:.734375},{x:.046875,y:.734375},{x:.046875,y:.734375},{x:.078125,y:.734375},{x:.078125,y:.734375},{x:.109375,y:.734375},{x:.109375,y:.734375},{x:.140625,y:.734375},{x:.140625,y:.734375},{x:.171875,y:.734375},{x:.171875,y:.734375},{x:.203125,y:.734375},{x:.203125,y:.734375},{x:.234375,y:.734375},{x:.234375,y:.734375},{x:.265625,y:.734375},{x:.265625,y:.734375},{x:.296875,y:.734375},{x:.296875,y:.734375},{x:.328125,y:.734375},{x:.328125,y:.734375},{x:.359375,y:.734375},{x:.359375,y:.734375},{x:.390625,y:.734375},{x:.390625,y:.734375},{x:.421875,y:.734375},{x:.421875,y:.734375},{x:.453125,y:.734375},{x:.453125,y:.734375},{x:.484375,y:.734375},{x:.484375,y:.734375},{x:.515625,y:.734375},{x:.515625,y:.734375},{x:.546875,y:.734375},{x:.546875,y:.734375},{x:.578125,y:.734375},{x:.578125,y:.734375},{x:.609375,y:.734375},{x:.609375,y:.734375},{x:.640625,y:.734375},{x:.640625,y:.734375},{x:.671875,y:.734375},{x:.671875,y:.734375},{x:.703125,y:.734375},{x:.703125,y:.734375},{x:.734375,y:.734375},{x:.734375,y:.734375},{x:.765625,y:.734375},{x:.765625,y:.734375},{x:.796875,y:.734375},{x:.796875,y:.734375},{x:.828125,y:.734375},{x:.828125,y:.734375},{x:.859375,y:.734375},{x:.859375,y:.734375},{x:.890625,y:.734375},{x:.890625,y:.734375},{x:.921875,y:.734375},{x:.921875,y:.734375},{x:.953125,y:.734375},{x:.953125,y:.734375},{x:.984375,y:.734375},{x:.984375,y:.734375},{x:.015625,y:.765625},{x:.015625,y:.765625},{x:.046875,y:.765625},{x:.046875,y:.765625},{x:.078125,y:.765625},{x:.078125,y:.765625},{x:.109375,y:.765625},{x:.109375,y:.765625},{x:.140625,y:.765625},{x:.140625,y:.765625},{x:.171875,y:.765625},{x:.171875,y:.765625},{x:.203125,y:.765625},{x:.203125,y:.765625},{x:.234375,y:.765625},{x:.234375,y:.765625},{x:.265625,y:.765625},{x:.265625,y:.765625},{x:.296875,y:.765625},{x:.296875,y:.765625},{x:.328125,y:.765625},{x:.328125,y:.765625},{x:.359375,y:.765625},{x:.359375,y:.765625},{x:.390625,y:.765625},{x:.390625,y:.765625},{x:.421875,y:.765625},{x:.421875,y:.765625},{x:.453125,y:.765625},{x:.453125,y:.765625},{x:.484375,y:.765625},{x:.484375,y:.765625},{x:.515625,y:.765625},{x:.515625,y:.765625},{x:.546875,y:.765625},{x:.546875,y:.765625},{x:.578125,y:.765625},{x:.578125,y:.765625},{x:.609375,y:.765625},{x:.609375,y:.765625},{x:.640625,y:.765625},{x:.640625,y:.765625},{x:.671875,y:.765625},{x:.671875,y:.765625},{x:.703125,y:.765625},{x:.703125,y:.765625},{x:.734375,y:.765625},{x:.734375,y:.765625},{x:.765625,y:.765625},{x:.765625,y:.765625},{x:.796875,y:.765625},{x:.796875,y:.765625},{x:.828125,y:.765625},{x:.828125,y:.765625},{x:.859375,y:.765625},{x:.859375,y:.765625},{x:.890625,y:.765625},{x:.890625,y:.765625},{x:.921875,y:.765625},{x:.921875,y:.765625},{x:.953125,y:.765625},{x:.953125,y:.765625},{x:.984375,y:.765625},{x:.984375,y:.765625},{x:.015625,y:.796875},{x:.015625,y:.796875},{x:.046875,y:.796875},{x:.046875,y:.796875},{x:.078125,y:.796875},{x:.078125,y:.796875},{x:.109375,y:.796875},{x:.109375,y:.796875},{x:.140625,y:.796875},{x:.140625,y:.796875},{x:.171875,y:.796875},{x:.171875,y:.796875},{x:.203125,y:.796875},{x:.203125,y:.796875},{x:.234375,y:.796875},{x:.234375,y:.796875},{x:.265625,y:.796875},{x:.265625,y:.796875},{x:.296875,y:.796875},{x:.296875,y:.796875},{x:.328125,y:.796875},{x:.328125,y:.796875},{x:.359375,y:.796875},{x:.359375,y:.796875},{x:.390625,y:.796875},{x:.390625,y:.796875},{x:.421875,y:.796875},{x:.421875,y:.796875},{x:.453125,y:.796875},{x:.453125,y:.796875},{x:.484375,y:.796875},{x:.484375,y:.796875},{x:.515625,y:.796875},{x:.515625,y:.796875},{x:.546875,y:.796875},{x:.546875,y:.796875},{x:.578125,y:.796875},{x:.578125,y:.796875},{x:.609375,y:.796875},{x:.609375,y:.796875},{x:.640625,y:.796875},{x:.640625,y:.796875},{x:.671875,y:.796875},{x:.671875,y:.796875},{x:.703125,y:.796875},{x:.703125,y:.796875},{x:.734375,y:.796875},{x:.734375,y:.796875},{x:.765625,y:.796875},{x:.765625,y:.796875},{x:.796875,y:.796875},{x:.796875,y:.796875},{x:.828125,y:.796875},{x:.828125,y:.796875},{x:.859375,y:.796875},{x:.859375,y:.796875},{x:.890625,y:.796875},{x:.890625,y:.796875},{x:.921875,y:.796875},{x:.921875,y:.796875},{x:.953125,y:.796875},{x:.953125,y:.796875},{x:.984375,y:.796875},{x:.984375,y:.796875},{x:.015625,y:.828125},{x:.015625,y:.828125},{x:.046875,y:.828125},{x:.046875,y:.828125},{x:.078125,y:.828125},{x:.078125,y:.828125},{x:.109375,y:.828125},{x:.109375,y:.828125},{x:.140625,y:.828125},{x:.140625,y:.828125},{x:.171875,y:.828125},{x:.171875,y:.828125},{x:.203125,y:.828125},{x:.203125,y:.828125},{x:.234375,y:.828125},{x:.234375,y:.828125},{x:.265625,y:.828125},{x:.265625,y:.828125},{x:.296875,y:.828125},{x:.296875,y:.828125},{x:.328125,y:.828125},{x:.328125,y:.828125},{x:.359375,y:.828125},{x:.359375,y:.828125},{x:.390625,y:.828125},{x:.390625,y:.828125},{x:.421875,y:.828125},{x:.421875,y:.828125},{x:.453125,y:.828125},{x:.453125,y:.828125},{x:.484375,y:.828125},{x:.484375,y:.828125},{x:.515625,y:.828125},{x:.515625,y:.828125},{x:.546875,y:.828125},{x:.546875,y:.828125},{x:.578125,y:.828125},{x:.578125,y:.828125},{x:.609375,y:.828125},{x:.609375,y:.828125},{x:.640625,y:.828125},{x:.640625,y:.828125},{x:.671875,y:.828125},{x:.671875,y:.828125},{x:.703125,y:.828125},{x:.703125,y:.828125},{x:.734375,y:.828125},{x:.734375,y:.828125},{x:.765625,y:.828125},{x:.765625,y:.828125},{x:.796875,y:.828125},{x:.796875,y:.828125},{x:.828125,y:.828125},{x:.828125,y:.828125},{x:.859375,y:.828125},{x:.859375,y:.828125},{x:.890625,y:.828125},{x:.890625,y:.828125},{x:.921875,y:.828125},{x:.921875,y:.828125},{x:.953125,y:.828125},{x:.953125,y:.828125},{x:.984375,y:.828125},{x:.984375,y:.828125},{x:.015625,y:.859375},{x:.015625,y:.859375},{x:.046875,y:.859375},{x:.046875,y:.859375},{x:.078125,y:.859375},{x:.078125,y:.859375},{x:.109375,y:.859375},{x:.109375,y:.859375},{x:.140625,y:.859375},{x:.140625,y:.859375},{x:.171875,y:.859375},{x:.171875,y:.859375},{x:.203125,y:.859375},{x:.203125,y:.859375},{x:.234375,y:.859375},{x:.234375,y:.859375},{x:.265625,y:.859375},{x:.265625,y:.859375},{x:.296875,y:.859375},{x:.296875,y:.859375},{x:.328125,y:.859375},{x:.328125,y:.859375},{x:.359375,y:.859375},{x:.359375,y:.859375},{x:.390625,y:.859375},{x:.390625,y:.859375},{x:.421875,y:.859375},{x:.421875,y:.859375},{x:.453125,y:.859375},{x:.453125,y:.859375},{x:.484375,y:.859375},{x:.484375,y:.859375},{x:.515625,y:.859375},{x:.515625,y:.859375},{x:.546875,y:.859375},{x:.546875,y:.859375},{x:.578125,y:.859375},{x:.578125,y:.859375},{x:.609375,y:.859375},{x:.609375,y:.859375},{x:.640625,y:.859375},{x:.640625,y:.859375},{x:.671875,y:.859375},{x:.671875,y:.859375},{x:.703125,y:.859375},{x:.703125,y:.859375},{x:.734375,y:.859375},{x:.734375,y:.859375},{x:.765625,y:.859375},{x:.765625,y:.859375},{x:.796875,y:.859375},{x:.796875,y:.859375},{x:.828125,y:.859375},{x:.828125,y:.859375},{x:.859375,y:.859375},{x:.859375,y:.859375},{x:.890625,y:.859375},{x:.890625,y:.859375},{x:.921875,y:.859375},{x:.921875,y:.859375},{x:.953125,y:.859375},{x:.953125,y:.859375},{x:.984375,y:.859375},{x:.984375,y:.859375},{x:.015625,y:.890625},{x:.015625,y:.890625},{x:.046875,y:.890625},{x:.046875,y:.890625},{x:.078125,y:.890625},{x:.078125,y:.890625},{x:.109375,y:.890625},{x:.109375,y:.890625},{x:.140625,y:.890625},{x:.140625,y:.890625},{x:.171875,y:.890625},{x:.171875,y:.890625},{x:.203125,y:.890625},{x:.203125,y:.890625},{x:.234375,y:.890625},{x:.234375,y:.890625},{x:.265625,y:.890625},{x:.265625,y:.890625},{x:.296875,y:.890625},{x:.296875,y:.890625},{x:.328125,y:.890625},{x:.328125,y:.890625},{x:.359375,y:.890625},{x:.359375,y:.890625},{x:.390625,y:.890625},{x:.390625,y:.890625},{x:.421875,y:.890625},{x:.421875,y:.890625},{x:.453125,y:.890625},{x:.453125,y:.890625},{x:.484375,y:.890625},{x:.484375,y:.890625},{x:.515625,y:.890625},{x:.515625,y:.890625},{x:.546875,y:.890625},{x:.546875,y:.890625},{x:.578125,y:.890625},{x:.578125,y:.890625},{x:.609375,y:.890625},{x:.609375,y:.890625},{x:.640625,y:.890625},{x:.640625,y:.890625},{x:.671875,y:.890625},{x:.671875,y:.890625},{x:.703125,y:.890625},{x:.703125,y:.890625},{x:.734375,y:.890625},{x:.734375,y:.890625},{x:.765625,y:.890625},{x:.765625,y:.890625},{x:.796875,y:.890625},{x:.796875,y:.890625},{x:.828125,y:.890625},{x:.828125,y:.890625},{x:.859375,y:.890625},{x:.859375,y:.890625},{x:.890625,y:.890625},{x:.890625,y:.890625},{x:.921875,y:.890625},{x:.921875,y:.890625},{x:.953125,y:.890625},{x:.953125,y:.890625},{x:.984375,y:.890625},{x:.984375,y:.890625},{x:.015625,y:.921875},{x:.015625,y:.921875},{x:.046875,y:.921875},{x:.046875,y:.921875},{x:.078125,y:.921875},{x:.078125,y:.921875},{x:.109375,y:.921875},{x:.109375,y:.921875},{x:.140625,y:.921875},{x:.140625,y:.921875},{x:.171875,y:.921875},{x:.171875,y:.921875},{x:.203125,y:.921875},{x:.203125,y:.921875},{x:.234375,y:.921875},{x:.234375,y:.921875},{x:.265625,y:.921875},{x:.265625,y:.921875},{x:.296875,y:.921875},{x:.296875,y:.921875},{x:.328125,y:.921875},{x:.328125,y:.921875},{x:.359375,y:.921875},{x:.359375,y:.921875},{x:.390625,y:.921875},{x:.390625,y:.921875},{x:.421875,y:.921875},{x:.421875,y:.921875},{x:.453125,y:.921875},{x:.453125,y:.921875},{x:.484375,y:.921875},{x:.484375,y:.921875},{x:.515625,y:.921875},{x:.515625,y:.921875},{x:.546875,y:.921875},{x:.546875,y:.921875},{x:.578125,y:.921875},{x:.578125,y:.921875},{x:.609375,y:.921875},{x:.609375,y:.921875},{x:.640625,y:.921875},{x:.640625,y:.921875},{x:.671875,y:.921875},{x:.671875,y:.921875},{x:.703125,y:.921875},{x:.703125,y:.921875},{x:.734375,y:.921875},{x:.734375,y:.921875},{x:.765625,y:.921875},{x:.765625,y:.921875},{x:.796875,y:.921875},{x:.796875,y:.921875},{x:.828125,y:.921875},{x:.828125,y:.921875},{x:.859375,y:.921875},{x:.859375,y:.921875},{x:.890625,y:.921875},{x:.890625,y:.921875},{x:.921875,y:.921875},{x:.921875,y:.921875},{x:.953125,y:.921875},{x:.953125,y:.921875},{x:.984375,y:.921875},{x:.984375,y:.921875},{x:.015625,y:.953125},{x:.015625,y:.953125},{x:.046875,y:.953125},{x:.046875,y:.953125},{x:.078125,y:.953125},{x:.078125,y:.953125},{x:.109375,y:.953125},{x:.109375,y:.953125},{x:.140625,y:.953125},{x:.140625,y:.953125},{x:.171875,y:.953125},{x:.171875,y:.953125},{x:.203125,y:.953125},{x:.203125,y:.953125},{x:.234375,y:.953125},{x:.234375,y:.953125},{x:.265625,y:.953125},{x:.265625,y:.953125},{x:.296875,y:.953125},{x:.296875,y:.953125},{x:.328125,y:.953125},{x:.328125,y:.953125},{x:.359375,y:.953125},{x:.359375,y:.953125},{x:.390625,y:.953125},{x:.390625,y:.953125},{x:.421875,y:.953125},{x:.421875,y:.953125},{x:.453125,y:.953125},{x:.453125,y:.953125},{x:.484375,y:.953125},{x:.484375,y:.953125},{x:.515625,y:.953125},{x:.515625,y:.953125},{x:.546875,y:.953125},{x:.546875,y:.953125},{x:.578125,y:.953125},{x:.578125,y:.953125},{x:.609375,y:.953125},{x:.609375,y:.953125},{x:.640625,y:.953125},{x:.640625,y:.953125},{x:.671875,y:.953125},{x:.671875,y:.953125},{x:.703125,y:.953125},{x:.703125,y:.953125},{x:.734375,y:.953125},{x:.734375,y:.953125},{x:.765625,y:.953125},{x:.765625,y:.953125},{x:.796875,y:.953125},{x:.796875,y:.953125},{x:.828125,y:.953125},{x:.828125,y:.953125},{x:.859375,y:.953125},{x:.859375,y:.953125},{x:.890625,y:.953125},{x:.890625,y:.953125},{x:.921875,y:.953125},{x:.921875,y:.953125},{x:.953125,y:.953125},{x:.953125,y:.953125},{x:.984375,y:.953125},{x:.984375,y:.953125},{x:.015625,y:.984375},{x:.015625,y:.984375},{x:.046875,y:.984375},{x:.046875,y:.984375},{x:.078125,y:.984375},{x:.078125,y:.984375},{x:.109375,y:.984375},{x:.109375,y:.984375},{x:.140625,y:.984375},{x:.140625,y:.984375},{x:.171875,y:.984375},{x:.171875,y:.984375},{x:.203125,y:.984375},{x:.203125,y:.984375},{x:.234375,y:.984375},{x:.234375,y:.984375},{x:.265625,y:.984375},{x:.265625,y:.984375},{x:.296875,y:.984375},{x:.296875,y:.984375},{x:.328125,y:.984375},{x:.328125,y:.984375},{x:.359375,y:.984375},{x:.359375,y:.984375},{x:.390625,y:.984375},{x:.390625,y:.984375},{x:.421875,y:.984375},{x:.421875,y:.984375},{x:.453125,y:.984375},{x:.453125,y:.984375},{x:.484375,y:.984375},{x:.484375,y:.984375},{x:.515625,y:.984375},{x:.515625,y:.984375},{x:.546875,y:.984375},{x:.546875,y:.984375},{x:.578125,y:.984375},{x:.578125,y:.984375},{x:.609375,y:.984375},{x:.609375,y:.984375},{x:.640625,y:.984375},{x:.640625,y:.984375},{x:.671875,y:.984375},{x:.671875,y:.984375},{x:.703125,y:.984375},{x:.703125,y:.984375},{x:.734375,y:.984375},{x:.734375,y:.984375},{x:.765625,y:.984375},{x:.765625,y:.984375},{x:.796875,y:.984375},{x:.796875,y:.984375},{x:.828125,y:.984375},{x:.828125,y:.984375},{x:.859375,y:.984375},{x:.859375,y:.984375},{x:.890625,y:.984375},{x:.890625,y:.984375},{x:.921875,y:.984375},{x:.921875,y:.984375},{x:.953125,y:.984375},{x:.953125,y:.984375},{x:.984375,y:.984375},{x:.984375,y:.984375},{x:.03125,y:.03125},{x:.03125,y:.03125},{x:.09375,y:.03125},{x:.09375,y:.03125},{x:.15625,y:.03125},{x:.15625,y:.03125},{x:.21875,y:.03125},{x:.21875,y:.03125},{x:.28125,y:.03125},{x:.28125,y:.03125},{x:.34375,y:.03125},{x:.34375,y:.03125},{x:.40625,y:.03125},{x:.40625,y:.03125},{x:.46875,y:.03125},{x:.46875,y:.03125},{x:.53125,y:.03125},{x:.53125,y:.03125},{x:.59375,y:.03125},{x:.59375,y:.03125},{x:.65625,y:.03125},{x:.65625,y:.03125},{x:.71875,y:.03125},{x:.71875,y:.03125},{x:.78125,y:.03125},{x:.78125,y:.03125},{x:.84375,y:.03125},{x:.84375,y:.03125},{x:.90625,y:.03125},{x:.90625,y:.03125},{x:.96875,y:.03125},{x:.96875,y:.03125},{x:.03125,y:.09375},{x:.03125,y:.09375},{x:.09375,y:.09375},{x:.09375,y:.09375},{x:.15625,y:.09375},{x:.15625,y:.09375},{x:.21875,y:.09375},{x:.21875,y:.09375},{x:.28125,y:.09375},{x:.28125,y:.09375},{x:.34375,y:.09375},{x:.34375,y:.09375},{x:.40625,y:.09375},{x:.40625,y:.09375},{x:.46875,y:.09375},{x:.46875,y:.09375},{x:.53125,y:.09375},{x:.53125,y:.09375},{x:.59375,y:.09375},{x:.59375,y:.09375},{x:.65625,y:.09375},{x:.65625,y:.09375},{x:.71875,y:.09375},{x:.71875,y:.09375},{x:.78125,y:.09375},{x:.78125,y:.09375},{x:.84375,y:.09375},{x:.84375,y:.09375},{x:.90625,y:.09375},{x:.90625,y:.09375},{x:.96875,y:.09375},{x:.96875,y:.09375},{x:.03125,y:.15625},{x:.03125,y:.15625},{x:.09375,y:.15625},{x:.09375,y:.15625},{x:.15625,y:.15625},{x:.15625,y:.15625},{x:.21875,y:.15625},{x:.21875,y:.15625},{x:.28125,y:.15625},{x:.28125,y:.15625},{x:.34375,y:.15625},{x:.34375,y:.15625},{x:.40625,y:.15625},{x:.40625,y:.15625},{x:.46875,y:.15625},{x:.46875,y:.15625},{x:.53125,y:.15625},{x:.53125,y:.15625},{x:.59375,y:.15625},{x:.59375,y:.15625},{x:.65625,y:.15625},{x:.65625,y:.15625},{x:.71875,y:.15625},{x:.71875,y:.15625},{x:.78125,y:.15625},{x:.78125,y:.15625},{x:.84375,y:.15625},{x:.84375,y:.15625},{x:.90625,y:.15625},{x:.90625,y:.15625},{x:.96875,y:.15625},{x:.96875,y:.15625},{x:.03125,y:.21875},{x:.03125,y:.21875},{x:.09375,y:.21875},{x:.09375,y:.21875},{x:.15625,y:.21875},{x:.15625,y:.21875},{x:.21875,y:.21875},{x:.21875,y:.21875},{x:.28125,y:.21875},{x:.28125,y:.21875},{x:.34375,y:.21875},{x:.34375,y:.21875},{x:.40625,y:.21875},{x:.40625,y:.21875},{x:.46875,y:.21875},{x:.46875,y:.21875},{x:.53125,y:.21875},{x:.53125,y:.21875},{x:.59375,y:.21875},{x:.59375,y:.21875},{x:.65625,y:.21875},{x:.65625,y:.21875},{x:.71875,y:.21875},{x:.71875,y:.21875},{x:.78125,y:.21875},{x:.78125,y:.21875},{x:.84375,y:.21875},{x:.84375,y:.21875},{x:.90625,y:.21875},{x:.90625,y:.21875},{x:.96875,y:.21875},{x:.96875,y:.21875},{x:.03125,y:.28125},{x:.03125,y:.28125},{x:.09375,y:.28125},{x:.09375,y:.28125},{x:.15625,y:.28125},{x:.15625,y:.28125},{x:.21875,y:.28125},{x:.21875,y:.28125},{x:.28125,y:.28125},{x:.28125,y:.28125},{x:.34375,y:.28125},{x:.34375,y:.28125},{x:.40625,y:.28125},{x:.40625,y:.28125},{x:.46875,y:.28125},{x:.46875,y:.28125},{x:.53125,y:.28125},{x:.53125,y:.28125},{x:.59375,y:.28125},{x:.59375,y:.28125},{x:.65625,y:.28125},{x:.65625,y:.28125},{x:.71875,y:.28125},{x:.71875,y:.28125},{x:.78125,y:.28125},{x:.78125,y:.28125},{x:.84375,y:.28125},{x:.84375,y:.28125},{x:.90625,y:.28125},{x:.90625,y:.28125},{x:.96875,y:.28125},{x:.96875,y:.28125},{x:.03125,y:.34375},{x:.03125,y:.34375},{x:.09375,y:.34375},{x:.09375,y:.34375},{x:.15625,y:.34375},{x:.15625,y:.34375},{x:.21875,y:.34375},{x:.21875,y:.34375},{x:.28125,y:.34375},{x:.28125,y:.34375},{x:.34375,y:.34375},{x:.34375,y:.34375},{x:.40625,y:.34375},{x:.40625,y:.34375},{x:.46875,y:.34375},{x:.46875,y:.34375},{x:.53125,y:.34375},{x:.53125,y:.34375},{x:.59375,y:.34375},{x:.59375,y:.34375},{x:.65625,y:.34375},{x:.65625,y:.34375},{x:.71875,y:.34375},{x:.71875,y:.34375},{x:.78125,y:.34375},{x:.78125,y:.34375},{x:.84375,y:.34375},{x:.84375,y:.34375},{x:.90625,y:.34375},{x:.90625,y:.34375},{x:.96875,y:.34375},{x:.96875,y:.34375},{x:.03125,y:.40625},{x:.03125,y:.40625},{x:.09375,y:.40625},{x:.09375,y:.40625},{x:.15625,y:.40625},{x:.15625,y:.40625},{x:.21875,y:.40625},{x:.21875,y:.40625},{x:.28125,y:.40625},{x:.28125,y:.40625},{x:.34375,y:.40625},{x:.34375,y:.40625},{x:.40625,y:.40625},{x:.40625,y:.40625},{x:.46875,y:.40625},{x:.46875,y:.40625},{x:.53125,y:.40625},{x:.53125,y:.40625},{x:.59375,y:.40625},{x:.59375,y:.40625},{x:.65625,y:.40625},{x:.65625,y:.40625},{x:.71875,y:.40625},{x:.71875,y:.40625},{x:.78125,y:.40625},{x:.78125,y:.40625},{x:.84375,y:.40625},{x:.84375,y:.40625},{x:.90625,y:.40625},{x:.90625,y:.40625},{x:.96875,y:.40625},{x:.96875,y:.40625},{x:.03125,y:.46875},{x:.03125,y:.46875},{x:.09375,y:.46875},{x:.09375,y:.46875},{x:.15625,y:.46875},{x:.15625,y:.46875},{x:.21875,y:.46875},{x:.21875,y:.46875},{x:.28125,y:.46875},{x:.28125,y:.46875},{x:.34375,y:.46875},{x:.34375,y:.46875},{x:.40625,y:.46875},{x:.40625,y:.46875},{x:.46875,y:.46875},{x:.46875,y:.46875},{x:.53125,y:.46875},{x:.53125,y:.46875},{x:.59375,y:.46875},{x:.59375,y:.46875},{x:.65625,y:.46875},{x:.65625,y:.46875},{x:.71875,y:.46875},{x:.71875,y:.46875},{x:.78125,y:.46875},{x:.78125,y:.46875},{x:.84375,y:.46875},{x:.84375,y:.46875},{x:.90625,y:.46875},{x:.90625,y:.46875},{x:.96875,y:.46875},{x:.96875,y:.46875},{x:.03125,y:.53125},{x:.03125,y:.53125},{x:.09375,y:.53125},{x:.09375,y:.53125},{x:.15625,y:.53125},{x:.15625,y:.53125},{x:.21875,y:.53125},{x:.21875,y:.53125},{x:.28125,y:.53125},{x:.28125,y:.53125},{x:.34375,y:.53125},{x:.34375,y:.53125},{x:.40625,y:.53125},{x:.40625,y:.53125},{x:.46875,y:.53125},{x:.46875,y:.53125},{x:.53125,y:.53125},{x:.53125,y:.53125},{x:.59375,y:.53125},{x:.59375,y:.53125},{x:.65625,y:.53125},{x:.65625,y:.53125},{x:.71875,y:.53125},{x:.71875,y:.53125},{x:.78125,y:.53125},{x:.78125,y:.53125},{x:.84375,y:.53125},{x:.84375,y:.53125},{x:.90625,y:.53125},{x:.90625,y:.53125},{x:.96875,y:.53125},{x:.96875,y:.53125},{x:.03125,y:.59375},{x:.03125,y:.59375},{x:.09375,y:.59375},{x:.09375,y:.59375},{x:.15625,y:.59375},{x:.15625,y:.59375},{x:.21875,y:.59375},{x:.21875,y:.59375},{x:.28125,y:.59375},{x:.28125,y:.59375},{x:.34375,y:.59375},{x:.34375,y:.59375},{x:.40625,y:.59375},{x:.40625,y:.59375},{x:.46875,y:.59375},{x:.46875,y:.59375},{x:.53125,y:.59375},{x:.53125,y:.59375},{x:.59375,y:.59375},{x:.59375,y:.59375},{x:.65625,y:.59375},{x:.65625,y:.59375},{x:.71875,y:.59375},{x:.71875,y:.59375},{x:.78125,y:.59375},{x:.78125,y:.59375},{x:.84375,y:.59375},{x:.84375,y:.59375},{x:.90625,y:.59375},{x:.90625,y:.59375},{x:.96875,y:.59375},{x:.96875,y:.59375},{x:.03125,y:.65625},{x:.03125,y:.65625},{x:.09375,y:.65625},{x:.09375,y:.65625},{x:.15625,y:.65625},{x:.15625,y:.65625},{x:.21875,y:.65625},{x:.21875,y:.65625},{x:.28125,y:.65625},{x:.28125,y:.65625},{x:.34375,y:.65625},{x:.34375,y:.65625},{x:.40625,y:.65625},{x:.40625,y:.65625},{x:.46875,y:.65625},{x:.46875,y:.65625},{x:.53125,y:.65625},{x:.53125,y:.65625},{x:.59375,y:.65625},{x:.59375,y:.65625},{x:.65625,y:.65625},{x:.65625,y:.65625},{x:.71875,y:.65625},{x:.71875,y:.65625},{x:.78125,y:.65625},{x:.78125,y:.65625},{x:.84375,y:.65625},{x:.84375,y:.65625},{x:.90625,y:.65625},{x:.90625,y:.65625},{x:.96875,y:.65625},{x:.96875,y:.65625},{x:.03125,y:.71875},{x:.03125,y:.71875},{x:.09375,y:.71875},{x:.09375,y:.71875},{x:.15625,y:.71875},{x:.15625,y:.71875},{x:.21875,y:.71875},{x:.21875,y:.71875},{x:.28125,y:.71875},{x:.28125,y:.71875},{x:.34375,y:.71875},{x:.34375,y:.71875},{x:.40625,y:.71875},{x:.40625,y:.71875},{x:.46875,y:.71875},{x:.46875,y:.71875},{x:.53125,y:.71875},{x:.53125,y:.71875},{x:.59375,y:.71875},{x:.59375,y:.71875},{x:.65625,y:.71875},{x:.65625,y:.71875},{x:.71875,y:.71875},{x:.71875,y:.71875},{x:.78125,y:.71875},{x:.78125,y:.71875},{x:.84375,y:.71875},{x:.84375,y:.71875},{x:.90625,y:.71875},{x:.90625,y:.71875},{x:.96875,y:.71875},{x:.96875,y:.71875},{x:.03125,y:.78125},{x:.03125,y:.78125},{x:.09375,y:.78125},{x:.09375,y:.78125},{x:.15625,y:.78125},{x:.15625,y:.78125},{x:.21875,y:.78125},{x:.21875,y:.78125},{x:.28125,y:.78125},{x:.28125,y:.78125},{x:.34375,y:.78125},{x:.34375,y:.78125},{x:.40625,y:.78125},{x:.40625,y:.78125},{x:.46875,y:.78125},{x:.46875,y:.78125},{x:.53125,y:.78125},{x:.53125,y:.78125},{x:.59375,y:.78125},{x:.59375,y:.78125},{x:.65625,y:.78125},{x:.65625,y:.78125},{x:.71875,y:.78125},{x:.71875,y:.78125},{x:.78125,y:.78125},{x:.78125,y:.78125},{x:.84375,y:.78125},{x:.84375,y:.78125},{x:.90625,y:.78125},{x:.90625,y:.78125},{x:.96875,y:.78125},{x:.96875,y:.78125},{x:.03125,y:.84375},{x:.03125,y:.84375},{x:.09375,y:.84375},{x:.09375,y:.84375},{x:.15625,y:.84375},{x:.15625,y:.84375},{x:.21875,y:.84375},{x:.21875,y:.84375},{x:.28125,y:.84375},{x:.28125,y:.84375},{x:.34375,y:.84375},{x:.34375,y:.84375},{x:.40625,y:.84375},{x:.40625,y:.84375},{x:.46875,y:.84375},{x:.46875,y:.84375},{x:.53125,y:.84375},{x:.53125,y:.84375},{x:.59375,y:.84375},{x:.59375,y:.84375},{x:.65625,y:.84375},{x:.65625,y:.84375},{x:.71875,y:.84375},{x:.71875,y:.84375},{x:.78125,y:.84375},{x:.78125,y:.84375},{x:.84375,y:.84375},{x:.84375,y:.84375},{x:.90625,y:.84375},{x:.90625,y:.84375},{x:.96875,y:.84375},{x:.96875,y:.84375},{x:.03125,y:.90625},{x:.03125,y:.90625},{x:.09375,y:.90625},{x:.09375,y:.90625},{x:.15625,y:.90625},{x:.15625,y:.90625},{x:.21875,y:.90625},{x:.21875,y:.90625},{x:.28125,y:.90625},{x:.28125,y:.90625},{x:.34375,y:.90625},{x:.34375,y:.90625},{x:.40625,y:.90625},{x:.40625,y:.90625},{x:.46875,y:.90625},{x:.46875,y:.90625},{x:.53125,y:.90625},{x:.53125,y:.90625},{x:.59375,y:.90625},{x:.59375,y:.90625},{x:.65625,y:.90625},{x:.65625,y:.90625},{x:.71875,y:.90625},{x:.71875,y:.90625},{x:.78125,y:.90625},{x:.78125,y:.90625},{x:.84375,y:.90625},{x:.84375,y:.90625},{x:.90625,y:.90625},{x:.90625,y:.90625},{x:.96875,y:.90625},{x:.96875,y:.90625},{x:.03125,y:.96875},{x:.03125,y:.96875},{x:.09375,y:.96875},{x:.09375,y:.96875},{x:.15625,y:.96875},{x:.15625,y:.96875},{x:.21875,y:.96875},{x:.21875,y:.96875},{x:.28125,y:.96875},{x:.28125,y:.96875},{x:.34375,y:.96875},{x:.34375,y:.96875},{x:.40625,y:.96875},{x:.40625,y:.96875},{x:.46875,y:.96875},{x:.46875,y:.96875},{x:.53125,y:.96875},{x:.53125,y:.96875},{x:.59375,y:.96875},{x:.59375,y:.96875},{x:.65625,y:.96875},{x:.65625,y:.96875},{x:.71875,y:.96875},{x:.71875,y:.96875},{x:.78125,y:.96875},{x:.78125,y:.96875},{x:.84375,y:.96875},{x:.84375,y:.96875},{x:.90625,y:.96875},{x:.90625,y:.96875},{x:.96875,y:.96875},{x:.96875,y:.96875},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375}];var a5=class{constructor(t){T(this,"model");T(this,"anchors");T(this,"anchorsTensor");T(this,"inputSize");T(this,"inputSizeTensor");T(this,"doubleInputSizeTensor");this.model=t,this.anchors=$3.map(o=>[o.x,o.y]),this.anchorsTensor=W.tensor2d(this.anchors),this.inputSize=this.model&&this.model.inputs&&this.model.inputs[0].shape?this.model.inputs[0].shape[2]:0,this.inputSizeTensor=W.tensor1d([this.inputSize,this.inputSize]),this.doubleInputSizeTensor=W.tensor1d([this.inputSize*2,this.inputSize*2])}normalizeBoxes(t){let o={};o.boxOffsets=W.slice(t,[0,0],[-1,2]),o.boxSizes=W.slice(t,[0,2],[-1,2]),o.div=W.div(o.boxOffsets,this.inputSizeTensor),o.boxCenterPoints=W.add(o.div,this.anchorsTensor),o.halfBoxSizes=W.div(o.boxSizes,this.doubleInputSizeTensor),o.sub=W.sub(o.boxCenterPoints,o.halfBoxSizes),o.startPoints=W.mul(o.sub,this.inputSizeTensor),o.add=W.add(o.boxCenterPoints,o.halfBoxSizes),o.endPoints=W.mul(o.add,this.inputSizeTensor);let n=W.concat2d([o.startPoints,o.endPoints],1);return Object.keys(o).forEach(r=>W.dispose(o[r])),n}normalizeLandmarks(t,o){let n={};n.reshape=W.reshape(t,[-1,7,2]),n.div=W.div(n.reshape,this.inputSizeTensor),n.landmarks=W.add(n.div,this.anchors[o]);let r=W.mul(n.landmarks,this.inputSizeTensor);return Object.keys(n).forEach(A=>W.dispose(n[A])),r}async predict(t,o){let n={};n.resize=W.image.resizeBilinear(t,[this.inputSize,this.inputSize]),n.div=W.div(n.resize,V.tf127),n.image=W.sub(n.div,V.tf1),n.batched=this.model.execute(n.image),n.predictions=W.squeeze(n.batched),n.slice=W.slice(n.predictions,[0,0],[-1,1]),n.sigmoid=W.sigmoid(n.slice),n.scores=W.squeeze(n.sigmoid);let r=await n.scores.data();n.boxes=W.slice(n.predictions,[0,1],[-1,4]),n.norm=this.normalizeBoxes(n.boxes),n.nms=await W.image.nonMaxSuppressionAsync(n.norm,n.scores,3*o.hand.maxDetected,o.hand.iouThreshold,o.hand.minConfidence);let A=await n.nms.array(),s=[];for(let a of A){let i={};i.box=W.slice(n.norm,[a,0],[1,-1]),i.slice=W.slice(n.predictions,[a,5],[1,14]),i.norm=this.normalizeLandmarks(i.slice,a),i.palmLandmarks=W.reshape(i.norm,[-1,2]);let x=await i.box.data(),c=x.slice(0,2),l=x.slice(2,4),y=await i.palmLandmarks.array(),f={startPoint:c,endPoint:l,palmLandmarks:y,confidence:r[a]},u=K3(f,[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]);s.push(u),Object.keys(i).forEach(m=>W.dispose(i[m]))}return Object.keys(n).forEach(a=>W.dispose(n[a])),s}};var L0=Z(D());var yA=5,eo=1.65,to=[0,5,9,13,17,1,2],xA=0,cA=2,oo=0,i5=class{constructor(t,o){T(this,"handDetector");T(this,"handPoseModel");T(this,"inputSize");T(this,"storedBoxes");T(this,"skipped");T(this,"detectedHands");this.handDetector=t,this.handPoseModel=o,this.inputSize=this.handPoseModel&&this.handPoseModel.inputs[0].shape?this.handPoseModel.inputs[0].shape[2]:0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let o=t.map(s=>s[0]),n=t.map(s=>s[1]),r=[Math.min(...o),Math.min(...n)],A=[Math.max(...o),Math.max(...n)];return{startPoint:r,endPoint:A}}getBoxForPalmLandmarks(t,o){let n=t.map(A=>M1([...A,1],o)),r=this.calculateLandmarksBoundingBox(n);return A5(s5(r),yA)}getBoxForHandLandmarks(t){let o=this.calculateLandmarksBoundingBox(t),n=A5(s5(o),eo);n.palmLandmarks=[];for(let r=0;r<to.length;r++)n.palmLandmarks.push(t[to[r]].slice(0,2));return n}transformRawCoords(t,o,n,r){let A=r5(o),s=[A[0]/this.inputSize,A[1]/this.inputSize,(A[0]+A[1])/this.inputSize/2],a=t.map(f=>[s[0]*(f[0]-this.inputSize/2),s[1]*(f[1]-this.inputSize/2),s[2]*f[2]]),i=g1(n,[0,0]),x=a.map(f=>[...M1(f,i),f[2]]),c=Q3(r),l=[...k2(o),1],y=[Te(l,c[0]),Te(l,c[1])];return x.map(f=>[Math.trunc(f[0]+y[0]),Math.trunc(f[1]+y[1]),Math.trunc(f[2])])}async estimateHands(t,o){let n=!1,r,A=(o.hand.skipTime||0)>h()-oo,s=this.skipped<(o.hand.skipFrames||0);o.skipAllowed&&A&&s&&(r=await this.handDetector.predict(t,o),this.skipped=0),o.skipAllowed&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==o.hand.maxDetected||!o.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(n=!0));let a=[];for(let i=0;i<this.storedBoxes.length;i++){let x=this.storedBoxes[i];if(!!x)if(o.hand.landmarks){let c=o.hand.rotation?J3(x.palmLandmarks[xA],x.palmLandmarks[cA]):0,l=k2(x),y=[l[0]/t.shape[2],l[1]/t.shape[1]],f=o.hand.rotation&&v.kernels.includes("rotatewithoffset")?L0.image.rotateWithOffset(t,c,0,y):t.clone(),u=g1(-c,l),m=n?this.getBoxForPalmLandmarks(x.palmLandmarks,u):x,P=Y3(m,f,[this.inputSize,this.inputSize]),g=L0.div(P,V.tf255);L0.dispose(P),L0.dispose(f);let[b,d]=this.handPoseModel.execute(g);oo=h(),L0.dispose(g);let M=(await b.data())[0];if(L0.dispose(b),M>=o.hand.minConfidence/4){let S=L0.reshape(d,[-1,3]),w=await S.array();L0.dispose(d),L0.dispose(S);let j=this.transformRawCoords(w,m,c,u),C=this.getBoxForHandLandmarks(j);this.storedBoxes[i]={...C,confidence:M};let F={landmarks:j,confidence:M,boxConfidence:x.confidence,fingerConfidence:M,box:{topLeft:C.startPoint,bottomRight:C.endPoint}};a.push(F)}else this.storedBoxes[i]=null;L0.dispose(d)}else{let c=A5(s5(x),eo),l={confidence:x.confidence,boxConfidence:x.confidence,fingerConfidence:0,box:{topLeft:c.startPoint,bottomRight:c.endPoint},landmarks:[]};a.push(l)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=a.length,a.length>o.hand.maxDetected&&(a.length=o.hand.maxDetected),a}};var k0={thumb:0,index:1,middle:2,ring:3,pinky:4,all:[0,1,2,3,4],nameMapping:{0:"thumb",1:"index",2:"middle",3:"ring",4:"pinky"},pointsMapping:{0:[[0,1],[1,2],[2,3],[3,4]],1:[[0,5],[5,6],[6,7],[7,8]],2:[[0,9],[9,10],[10,11],[11,12]],3:[[0,13],[13,14],[14,15],[15,16]],4:[[0,17],[17,18],[18,19],[19,20]]},getName:e=>k0.nameMapping[e],getPoints:e=>k0.pointsMapping[e]},ke={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>ke.nameMapping[e]},o0={verticalUp:0,verticalDown:1,horizontalLeft:2,horizontalRight:3,diagonalUpRight:4,diagonalUpLeft:5,diagonalDownRight:6,diagonalDownLeft:7,nameMapping:{0:"verticalUp",1:"verticalDown",2:"horizontalLeft",3:"horizontalRight",4:"diagonalUpRight",5:"diagonalUpLeft",6:"diagonalDownRight",7:"diagonalDownLeft"},getName:e=>o0.nameMapping[e]},we=class{constructor(t){T(this,"name");T(this,"curls");T(this,"directions");T(this,"weights");T(this,"weightsRelative");this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}curl(t,o,n){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([o,n])}direction(t,o,n){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([o,n])}weight(t,o){this.weights[t]=o;let n=this.weights.reduce((r,A)=>r+A,0);this.weightsRelative=this.weights.map(r=>r*5/n)}matchAgainst(t,o){let n=0;for(let r in t){let A=t[r],s=this.curls[r];if(typeof s=="undefined"){n+=this.weightsRelative[r];continue}for(let[a,i]of s)if(A===a){n+=i*this.weightsRelative[r];break}}for(let r in o){let A=o[r],s=this.directions[r];if(typeof s=="undefined"){n+=this.weightsRelative[r];continue}for(let[a,i]of s)if(A===a){n+=i*this.weightsRelative[r];break}}return n/10}};var{thumb:J0,index:ce,middle:de,ring:He,pinky:Ve}=k0,{none:Q0,half:fA,full:_0}=ke,{verticalUp:o2,verticalDown:z4,horizontalLeft:P1,horizontalRight:mA,diagonalUpRight:pA,diagonalUpLeft:n2,diagonalDownRight:S4,diagonalDownLeft:C4}=o0,Ee=new we("thumbs up");Ee.curl(J0,Q0,1);Ee.direction(J0,o2,1);Ee.direction(J0,n2,.25);Ee.direction(J0,pA,.25);for(let e of[k0.index,k0.middle,k0.ring,k0.pinky])Ee.curl(e,_0,1),Ee.direction(e,P1,1),Ee.direction(e,mA,1);var y0=new we("victory");y0.curl(J0,fA,.5);y0.curl(J0,Q0,.5);y0.direction(J0,o2,1);y0.direction(J0,n2,1);y0.curl(ce,Q0,1);y0.direction(ce,o2,.75);y0.direction(ce,n2,1);y0.curl(de,Q0,1);y0.direction(de,o2,1);y0.direction(de,n2,.75);y0.curl(He,_0,1);y0.direction(He,o2,.2);y0.direction(He,n2,1);y0.direction(He,P1,.2);y0.curl(Ve,_0,1);y0.direction(Ve,o2,.2);y0.direction(Ve,n2,1);y0.direction(Ve,P1,.2);y0.weight(ce,2);y0.weight(de,2);var ze=new we("point");ze.curl(J0,_0,1);ze.curl(ce,Q0,.5);ze.curl(de,_0,.5);ze.curl(He,_0,.5);ze.curl(Ve,_0,.5);ze.weight(ce,2);ze.weight(de,2);var Se=new we("middle finger");Se.curl(J0,Q0,1);Se.curl(ce,_0,.5);Se.curl(de,_0,.5);Se.curl(He,_0,.5);Se.curl(Ve,_0,.5);Se.weight(ce,2);Se.weight(de,2);var r2=new we("open palm");r2.curl(J0,Q0,.75);r2.curl(ce,Q0,.75);r2.curl(de,Q0,.75);r2.curl(He,Q0,.75);r2.curl(Ve,Q0,.75);var no=[Ee,y0,ze,Se,r2];var uA=.7,De={HALF_CURL_START_LIMIT:60,NO_CURL_START_LIMIT:130,DISTANCE_VOTE_POWER:1.1,SINGLE_ANGLE_VOTE_POWER:.9,TOTAL_ANGLE_VOTE_POWER:1.6};function ro(e,t,o,n){let r=(t-n)/(e-o),A=Math.atan(r)*180/Math.PI;return A<=0?A=-A:A>0&&(A=180-A),A}function so(e,t){if(!e||!t)return[0,0];let o=ro(e[0],e[1],t[0],t[1]);if(e.length===2)return o;let n=ro(e[1],e[2],t[1],t[2]);return[o,n]}function Ao(e,t=1){let o=0,n=0,r=0;return e>=75&&e<=105?o=1*t:e>=25&&e<=155?n=1*t:r=1*t,[o,n,r]}function hA(e,t,o){let n=e[0]-t[0],r=e[0]-o[0],A=t[0]-o[0],s=e[1]-t[1],a=e[1]-o[1],i=t[1]-o[1],x=e[2]-t[2],c=e[2]-o[2],l=t[2]-o[2],y=Math.sqrt(n*n+s*s+x*x),f=Math.sqrt(r*r+a*a+c*c),u=Math.sqrt(A*A+i*i+l*l),m=(u*u+y*y-f*f)/(2*u*y);m>1?m=1:m<-1&&(m=-1);let P=Math.acos(m);P=57.2958*P%180;let g;return P>De.NO_CURL_START_LIMIT?g=ke.none:P>De.HALF_CURL_START_LIMIT?g=ke.half:g=ke.full,g}function ao(e,t,o,n){let r;return n===Math.abs(e)?e>0?r=o0.horizontalLeft:r=o0.horizontalRight:n===Math.abs(t)?t>0?r=o0.horizontalLeft:r=o0.horizontalRight:o>0?r=o0.horizontalLeft:r=o0.horizontalRight,r}function io(e,t,o,n){let r;return n===Math.abs(e)?e<0?r=o0.verticalDown:r=o0.verticalUp:n===Math.abs(t)?t<0?r=o0.verticalDown:r=o0.verticalUp:o<0?r=o0.verticalDown:r=o0.verticalUp,r}function bA(e,t,o,n,r,A,s,a){let i,x=io(e,t,o,n),c=ao(r,A,s,a);return x===o0.verticalUp?c===o0.horizontalLeft?i=o0.diagonalUpLeft:i=o0.diagonalUpRight:c===o0.horizontalLeft?i=o0.diagonalDownLeft:i=o0.diagonalDownRight,i}function gA(e,t,o,n){let r=e[0]-t[0],A=e[0]-o[0],s=t[0]-o[0],a=e[1]-t[1],i=e[1]-o[1],x=t[1]-o[1],c=Math.max(Math.abs(r),Math.abs(A),Math.abs(s)),l=Math.max(Math.abs(a),Math.abs(i),Math.abs(x)),y=0,f=0,u=0,m=l/(c+1e-5);m>1.5?y+=De.DISTANCE_VOTE_POWER:m>.66?f+=De.DISTANCE_VOTE_POWER:u+=De.DISTANCE_VOTE_POWER;let P=Math.sqrt(r*r+a*a),g=Math.sqrt(A*A+i*i),b=Math.sqrt(s*s+x*x),d=Math.max(P,g,b),M=e[0],S=e[1],w=o[0],j=o[1];d===P?(w=o[0],j=o[1]):d===b&&(M=t[0],S=t[1]);let H=so([M,S],[w,j]),Y=Ao(H,De.TOTAL_ANGLE_VOTE_POWER);y+=Y[0],f+=Y[1],u+=Y[2];for(let x0 of n){let E=Ao(x0,De.SINGLE_ANGLE_VOTE_POWER);y+=E[0],f+=E[1],u+=E[2]}let J;return y===Math.max(y,f,u)?J=io(i,a,x,l):u===Math.max(f,u)?J=ao(A,r,s,c):J=bA(i,a,x,l,A,r,s,c),J}function lo(e){let t=[],o=[],n=[],r=[];if(!e)return{curls:n,directions:r};for(let A of k0.all){let s=k0.getPoints(A),a=[],i=[];for(let x of s){let c=e[x[0]],l=e[x[1]],y=so(c,l),f=y[0],u=y[1];a.push(f),i.push(u)}t.push(a),o.push(i)}for(let A of k0.all){let s=A===k0.thumb?1:0,a=k0.getPoints(A),i=e[a[s][0]],x=e[a[s+1][1]],c=e[a[3][1]],l=hA(i,x,c),y=gA(i,x,c,t[A].slice(s));n[A]=l,r[A]=y}return{curls:n,directions:r}}function l5(e){if(!e||e.length===0)return null;let t=lo(e),o={};for(let n of k0.all)o[k0.getName(n)]={curl:ke.getName(t.curls[n]),direction:o0.getName(t.directions[n])};return o}function yo(e){let t=[];if(!e||e.length===0)return t;let o=lo(e);for(let n of no){let r=n.matchAgainst(o.curls,o.directions);r>=uA&&t.push({name:n.name,confidence:r})}return t}var xo={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],palm:[0]},A2,s2,co;async function v1(e,t){let o=await co.estimateHands(e,t);if(!o)return[];let n=[];for(let r=0;r<o.length;r++){let A={};if(o[r].landmarks)for(let c of Object.keys(xo))A[c]=xo[c].map(l=>o[r].landmarks[l]);let s=o[r].landmarks,a=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],i=[0,0,0,0];if(s&&s.length>0){for(let c of s)c[0]<a[0]&&(a[0]=c[0]),c[1]<a[1]&&(a[1]=c[1]),c[0]>a[2]&&(a[2]=c[0]),c[1]>a[3]&&(a[3]=c[1]);a[2]-=a[0],a[3]-=a[1],i=[a[0]/(e.shape[2]||0),a[1]/(e.shape[1]||0),a[2]/(e.shape[2]||0),a[3]/(e.shape[1]||0)]}else a=o[r].box?[Math.trunc(Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.max(0,o[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,o[r].box.bottomRight[0])-Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,o[r].box.bottomRight[1])-Math.max(0,o[r].box.topLeft[1]))]:[0,0,0,0],i=[o[r].box.topLeft[0]/(e.shape[2]||0),o[r].box.topLeft[1]/(e.shape[1]||0),(o[r].box.bottomRight[0]-o[r].box.topLeft[0])/(e.shape[2]||0),(o[r].box.bottomRight[1]-o[r].box.topLeft[1])/(e.shape[1]||0)];let x=l5(s);n.push({id:r,score:Math.round(100*o[r].confidence)/100,boxScore:Math.round(100*o[r].boxConfidence)/100,fingerScore:Math.round(100*o[r].fingerConfidence)/100,label:"hand",box:a,boxRaw:i,keypoints:s,annotations:A,landmarks:x})}return n}async function T1(e){var o,n;v.initial&&(A2=null,s2=null),!A2||!s2?[A2,s2]=await Promise.all([e.hand.enabled?G((o=e.hand.detector)==null?void 0:o.modelPath):null,e.hand.landmarks?G((n=e.hand.skeleton)==null?void 0:n.modelPath):null]):(e.debug&&p("cached model:",A2.modelUrl),e.debug&&p("cached model:",s2.modelUrl));let t=new a5(A2);return co=new i5(t,s2),[A2,s2]}var Q=Z(D());var d0=[null,null],MA=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],Ce=[[0,0],[0,0]],PA=["hand","fist","pinch","point","face","tip","pinchtip"],mo=4,po=1.6,RA=512,vA=1.4,y5=Number.MAX_SAFE_INTEGER,w1=0,fe=[0,0],A0={boxes:[],hands:[]},uo={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],base:[0],palm:[0,17,13,9,5,1,0]};async function ho(e){var t;if(v.initial&&(d0[0]=null),d0[0])e.debug&&p("cached model:",d0[0].modelUrl);else{x5(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),d0[0]=await G((t=e.hand.detector)==null?void 0:t.modelPath);let o=Object.values(d0[0].modelSignature.inputs);Ce[0][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ce[0][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return d0[0]}async function bo(e){var t;if(v.initial&&(d0[1]=null),d0[1])e.debug&&p("cached model:",d0[1].modelUrl);else{d0[1]=await G((t=e.hand.skeleton)==null?void 0:t.modelPath);let o=Object.values(d0[1].modelSignature.inputs);Ce[1][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ce[1][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return d0[1]}async function TA(e,t){let o=[];if(!e||!d0[0])return o;let n={},r=(e.shape[2]||1)/(e.shape[1]||1),A=Math.min(Math.round((e.shape[1]||0)/8)*8,RA),s=Math.round(A*r/8)*8;n.resize=Q.image.resizeBilinear(e,[A,s]),n.cast=Q.cast(n.resize,"int32"),[n.rawScores,n.rawBoxes]=await d0[0].executeAsync(n.cast,MA),n.boxes=Q.squeeze(n.rawBoxes,[0,2]),n.scores=Q.squeeze(n.rawScores,[0]);let a=Q.unstack(n.scores,1);Q.dispose(a[mo]),a.splice(mo,1),n.filtered=Q.stack(a,1),Q.dispose(a),n.max=Q.max(n.filtered,1),n.argmax=Q.argMax(n.filtered,1);let i=0;n.nms=await Q.image.nonMaxSuppressionAsync(n.boxes,n.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let x=await n.nms.data(),c=await n.max.data(),l=await n.argmax.data();for(let y of Array.from(x)){let f=Q.slice(n.boxes,y,1),u=await f.data();Q.dispose(f);let m=[u[1],u[0],u[3]-u[1],u[2]-u[0]],P=Q2(m,vA),g=[Math.trunc(m[0]*fe[0]),Math.trunc(m[1]*fe[1]),Math.trunc(m[2]*fe[0]),Math.trunc(m[3]*fe[1])],b=c[y],d=PA[l[y]],M={id:i++,score:b,box:g,boxRaw:P,label:d};o.push(M)}return Object.keys(n).forEach(y=>Q.dispose(n[y])),o.sort((y,f)=>f.score-y.score),o.length>(t.hand.maxDetected||1)&&(o.length=t.hand.maxDetected||1),o}async function k1(e,t,o){let n={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&d0[1]&&o.hand.landmarks&&t.score>(o.hand.minConfidence||0)){let r={},A=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=Q.image.cropAndResize(e,[A],[0],[Ce[1][0],Ce[1][1]],"bilinear"),r.div=Q.div(r.crop,V.tf255),[r.score,r.keypoints]=d0[1].execute(r.div,["Identity_1","Identity"]);let s=(await r.score.data())[0],a=(100-Math.trunc(100/(1+Math.exp(s))))/100;if(a>=(o.hand.minConfidence||0)){n.fingerScore=a,r.reshaped=Q.reshape(r.keypoints,[-1,3]);let c=(await r.reshaped.array()).map(l=>[l[0]/Ce[1][1],l[1]/Ce[1][0],l[2]||0]).map(l=>[l[0]*t.boxRaw[2],l[1]*t.boxRaw[3],l[2]||0]);n.keypoints=c.map(l=>[fe[0]*(l[0]+t.boxRaw[0]),fe[1]*(l[1]+t.boxRaw[1]),l[2]||0]),n.landmarks=l5(n.keypoints);for(let l of Object.keys(uo))n.annotations[l]=uo[l].map(y=>n.landmarks&&n.keypoints[y]?n.keypoints[y]:null)}Object.keys(r).forEach(i=>Q.dispose(r[i]))}return n}async function E1(e,t){var r,A;if(!d0[0]||!d0[1]||!((r=d0[0])!=null&&r.inputs[0].shape)||!((A=d0[1])!=null&&A.inputs[0].shape))return[];fe=[e.shape[2]||0,e.shape[1]||0],y5++;let o=(t.hand.skipTime||0)>h()-w1,n=y5<(t.hand.skipFrames||0);return t.skipAllowed&&o&&n?A0.hands:new Promise(async s=>{let a=3*(t.hand.skipTime||0)>h()-w1,i=y5<3*(t.hand.skipFrames||0);t.skipAllowed&&A0.hands.length===t.hand.maxDetected?A0.hands=await Promise.all(A0.boxes.map(c=>k1(e,c,t))):t.skipAllowed&&a&&i&&A0.hands.length>0?A0.hands=await Promise.all(A0.boxes.map(c=>k1(e,c,t))):(A0.boxes=await TA(e,t),w1=h(),A0.hands=await Promise.all(A0.boxes.map(c=>k1(e,c,t))),y5=0);let x=[...A0.boxes];if(A0.boxes.length=0,t.cacheSensitivity>0)for(let c=0;c<A0.hands.length;c++){let l=a3(A0.hands[c].keypoints,fe);if(l.box[2]/(e.shape[2]||1)>.05&&l.box[3]/(e.shape[1]||1)>.05&&A0.hands[c].fingerScore&&A0.hands[c].fingerScore>(t.hand.minConfidence||0)){let y=Q2(l.box,po),f=Q2(l.boxRaw,po);A0.boxes.push({...x[c],box:y,boxRaw:f})}}for(let c=0;c<A0.hands.length;c++){let l=le(A0.hands[c].keypoints,fe);A0.hands[c].box=l.box,A0.hands[c].boxRaw=l.boxRaw}s(A0.hands)})}var d5=Z(D());var M0,c5=[],z1=Number.MAX_SAFE_INTEGER,Mo=0,Po=0;async function Ro(e){var t;return v.initial&&(M0=null),M0?e.debug&&p("cached model:",M0.modelUrl):M0=await G((t=e.face.liveness)==null?void 0:t.modelPath),M0}async function S1(e,t,o,n){var s,a;if(!M0)return 0;let r=(((s=t.face.liveness)==null?void 0:s.skipTime)||0)>h()-Po,A=z1<(((a=t.face.liveness)==null?void 0:a.skipFrames)||0);return t.skipAllowed&&r&&A&&Mo===n&&c5[o]?(z1++,c5[o]):(z1=0,new Promise(async i=>{let x=d5.image.resizeBilinear(e,[M0!=null&&M0.inputs[0].shape?M0.inputs[0].shape[2]:0,M0!=null&&M0.inputs[0].shape?M0.inputs[0].shape[1]:0],!1),c=M0==null?void 0:M0.execute(x),l=(await c.data())[0];c5[o]=Math.round(100*l)/100,Mo=n,Po=h(),d5.dispose([x,c]),i(c5[o])}))}var zo=Z(D());var E2={};ue(E2,{connected:()=>m5,horizontal:()=>C1,kpt:()=>f5,relative:()=>j1,vertical:()=>I1});var f5=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],C1=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],I1=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],j1=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],m5={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var Ie=Z(D()),To=.005,W0={keypoints:[],padding:[[0,0],[0,0],[0,0],[0,0]]};function O1(e){for(let t of C1){let o=e.keypoints.findIndex(r=>r.part===t[0]),n=e.keypoints.findIndex(r=>r.part===t[1]);if(e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[0]<e.keypoints[n].position[0]){let r=e.keypoints[o];e.keypoints[o]=e.keypoints[n],e.keypoints[n]=r}}for(let t of I1){let o=e.keypoints.findIndex(r=>r&&r.part===t[0]),n=e.keypoints.findIndex(r=>r&&r.part===t[1]);e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[1]<e.keypoints[n].position[1]&&e.keypoints.splice(o,1)}for(let[t,o]of j1){let n=e.keypoints.findIndex(x=>x&&x.part===t[0]),r=e.keypoints.findIndex(x=>x&&x.part===t[1]),A=e.keypoints.findIndex(x=>x&&x.part===o[0]),s=e.keypoints.findIndex(x=>x&&x.part===o[1]);if(!e.keypoints[A]||!e.keypoints[s])continue;let a=e.keypoints[n]?[Math.abs(e.keypoints[A].position[0]-e.keypoints[n].position[0]),Math.abs(e.keypoints[s].position[0]-e.keypoints[n].position[0])]:[0,0],i=e.keypoints[r]?[Math.abs(e.keypoints[s].position[0]-e.keypoints[r].position[0]),Math.abs(e.keypoints[A].position[0]-e.keypoints[r].position[0])]:[0,0];if(a[0]>a[1]||i[0]>i[1]){let x=e.keypoints[n];e.keypoints[n]=e.keypoints[r],e.keypoints[r]=x}}}function wo(e){for(let t=0;t<e.length;t++)if(e[t]&&W0.keypoints[t]){let o=[Math.abs(e[t].positionRaw[0]-W0.keypoints[t].positionRaw[0]),Math.abs(e[t].positionRaw[1]-W0.keypoints[t].positionRaw[1])];o[0]<To&&o[1]<To?e[t]=W0.keypoints[t]:W0.keypoints[t]=e[t]}else W0.keypoints[t]=e[t];return e}function ko(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;W0.padding=[[0,0],[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0],[0,0]],o.pad=Ie.pad(e,W0.padding),o.resize=Ie.image.resizeBilinear(o.pad,[t,t]);let n=Ie.cast(o.resize,"int32");return Object.keys(o).forEach(r=>Ie.dispose(o[r])),n}function Eo(e,t){e.keypoints=e.keypoints.filter(n=>n&&n.position);for(let n of e.keypoints)n.position=[n.position[0]*(t[0]+W0.padding[2][0]+W0.padding[2][1])/t[0]-W0.padding[2][0],n.position[1]*(t[1]+W0.padding[1][0]+W0.padding[1][1])/t[1]-W0.padding[1][0]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1]];let o=le(e.keypoints.map(n=>n.position),t);return e.box=o.box,e.boxRaw=o.boxRaw,e}var F0,p5=0,N1=Number.MAX_SAFE_INTEGER,Ze={boxes:[],bodies:[],last:0};async function So(e){return v.initial&&(F0=null),F0?e.debug&&p("cached model:",F0.modelUrl):(x5(["size"],e),F0=await G(e.body.modelPath)),p5=F0.inputs[0].shape?F0.inputs[0].shape[2]:0,p5<64&&(p5=256),F0}async function kA(e,t,o){let n=e[0][0],r=[],A=0;for(let c=0;c<n.length;c++)if(A=n[c][2],A>t.body.minConfidence){let l=[n[c][1],n[c][0]];r.push({score:Math.round(100*A)/100,part:f5[c],positionRaw:l,position:[Math.round((o.shape[2]||0)*l[0]),Math.round((o.shape[1]||0)*l[1])]})}A=r.reduce((c,l)=>l.score>c?l.score:c,0);let s=[],a=le(r.map(c=>c.position),[o.shape[2],o.shape[1]]),i={};for(let[c,l]of Object.entries(m5)){let y=[];for(let f=0;f<l.length-1;f++){let u=r.find(P=>P.part===l[f]),m=r.find(P=>P.part===l[f+1]);u&&m&&u.score>(t.body.minConfidence||0)&&m.score>(t.body.minConfidence||0)&&y.push([u.position,m.position])}i[c]=y}let x={id:0,score:A,box:a.box,boxRaw:a.boxRaw,keypoints:r,annotations:i};return O1(x),s.push(x),s}async function EA(e,t,o){let n=[];for(let r=0;r<e[0].length;r++){let A=e[0][r],s=Math.round(100*A[51+4])/100;if(s>t.body.minConfidence){let a=[];for(let l=0;l<17;l++){let y=A[3*l+2];if(y>t.body.minConfidence){let f=[A[3*l+1],A[3*l+0]];a.push({part:f5[l],score:Math.round(100*y)/100,positionRaw:f,position:[Math.round((o.shape[2]||0)*f[0]),Math.round((o.shape[1]||0)*f[1])]})}}let i=le(a.map(l=>l.position),[o.shape[2],o.shape[1]]),x={};for(let[l,y]of Object.entries(m5)){let f=[];for(let u=0;u<y.length-1;u++){let m=a.find(g=>g.part===y[u]),P=a.find(g=>g.part===y[u+1]);m&&P&&m.score>(t.body.minConfidence||0)&&P.score>(t.body.minConfidence||0)&&f.push([m.position,P.position])}x[l]=f}let c={id:r,score:s,box:i.box,boxRaw:i.boxRaw,keypoints:[...a],annotations:x};O1(c),n.push(c)}}return n.sort((r,A)=>A.score-r.score),n.length>t.body.maxDetected&&(n.length=t.body.maxDetected),n}async function L1(e,t){if(!F0||!(F0!=null&&F0.inputs[0].shape))return[];t.skipAllowed||(Ze.boxes.length=0),N1++;let o=(t.body.skipTime||0)>h()-Ze.last,n=N1<(t.body.skipFrames||0);return t.skipAllowed&&o&&n?Ze.bodies:new Promise(async r=>{let A={};N1=0,A.input=ko(e,p5),A.res=F0==null?void 0:F0.execute(A.input),Ze.last=h();let s=await A.res.array();Ze.bodies=A.res.shape[2]===17?await kA(s,t,e):await EA(s,t,e);for(let a of Ze.bodies)Eo(a,[e.shape[2]||1,e.shape[1]||1]),wo(a.keypoints);Object.keys(A).forEach(a=>zo.dispose(A[a])),r(Ze.bodies)})}var E0=Z(D());var a2,u5=[],Io=0,W1=Number.MAX_SAFE_INTEGER,b5=0,h5=2.5;async function jo(e){if(!a2||v.initial){a2=await G(e.object.modelPath);let t=Object.values(a2.modelSignature.inputs);b5=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&p("cached model:",a2.modelUrl);return a2}async function zA(e,t,o){let n=0,r=[];for(let i of[1,2,4])E0.tidy(async()=>{let x=i*13,c=E0.squeeze(e.find(m=>m.shape[1]===x**2&&(m.shape[2]||0)===$e.length)),l=E0.squeeze(e.find(m=>m.shape[1]===x**2&&(m.shape[2]||0)<$e.length)),f=await l.reshape([-1,4,l.shape[1]/4]).argMax(2).array(),u=await c.array();for(let m=0;m<c.shape[0];m++)for(let P=0;P<c.shape[1];P++){let g=u[m][P];if(g>(o.object.minConfidence||0)&&P!==61){let b=(.5+Math.trunc(m%x))/x,d=(.5+Math.trunc(m/x))/x,M=f[m].map(J=>J*(x/i/b5)),[S,w]=[b-h5/i*M[0],d-h5/i*M[1]],[j,C]=[b+h5/i*M[2]-S,d+h5/i*M[3]-w],F=[S,w,j,C];F=F.map(J=>Math.max(0,Math.min(J,1)));let H=[F[0]*t[0],F[1]*t[1],F[2]*t[0],F[3]*t[1]],Y={id:n++,score:Math.round(100*g)/100,class:P+1,label:$e[P].label,box:H.map(J=>Math.trunc(J)),boxRaw:F};r.push(Y)}}});e.forEach(i=>E0.dispose(i));let A=r.map(i=>[i.boxRaw[1],i.boxRaw[0],i.boxRaw[3],i.boxRaw[2]]),s=r.map(i=>i.score),a=[];if(A&&A.length>0){let i=await E0.image.nonMaxSuppressionAsync(A,s,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence);a=await i.data(),E0.dispose(i)}return r=r.filter((i,x)=>a.includes(x)).sort((i,x)=>x.score-i.score),r}async function F1(e,t){let o=(t.object.skipTime||0)>h()-Io,n=W1<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&u5.length>0?(W1++,u5):(W1=0,!v.kernels.includes("mod")||!v.kernels.includes("sparsetodense")?u5:new Promise(async r=>{let A=[e.shape[2]||0,e.shape[1]||0],s=E0.image.resizeBilinear(e,[b5,b5],!1),a=E0.div(s,V.tf255),i=a.transpose([0,3,1,2]);E0.dispose(a),E0.dispose(s);let x;t.object.enabled&&(x=a2.execute(i)),Io=h(),E0.dispose(i);let c=await zA(x,A,t);u5=c,r(c)}))}var z0=Z(D());var S2=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],SA=S2.length,z2=S2.reduce((e,t,o)=>(e[t]=o,e),{}),CA=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],ts=CA.map(([e,t])=>[z2[e],z2[t]]),No=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function Lo(e){let t=e.reduce(({maxX:o,maxY:n,minX:r,minY:A},{position:{x:s,y:a}})=>({maxX:Math.max(o,s),maxY:Math.max(n,a),minX:Math.min(r,s),minY:Math.min(A,a)}),{maxX:Number.NEGATIVE_INFINITY,maxY:Number.NEGATIVE_INFINITY,minX:Number.POSITIVE_INFINITY,minY:Number.POSITIVE_INFINITY});return[t.minX,t.minY,t.maxX-t.minX,t.maxY-t.minY]}function Wo(e,[t,o],[n,r]){let A=t/n,s=o/r,a=(x,c)=>({id:c,score:x.score,boxRaw:[x.box[0]/r,x.box[1]/n,x.box[2]/r,x.box[3]/n],box:[Math.trunc(x.box[0]*s),Math.trunc(x.box[1]*A),Math.trunc(x.box[2]*s),Math.trunc(x.box[3]*A)],keypoints:x.keypoints.map(({score:l,part:y,position:f})=>({score:l,part:y,position:[Math.trunc(f.x*s),Math.trunc(f.y*A)],positionRaw:[f.x/n,f.y/n]})),annotations:{}});return e.map((x,c)=>a(x,c))}var g5=class{constructor(t,o){T(this,"priorityQueue");T(this,"numberOfElements");T(this,"getElementValue");this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=o}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(Math.floor(t/2),t);)this.exchange(t,Math.floor(t/2)),t=Math.floor(t/2)}sink(t){for(;2*t<=this.numberOfElements;){let o=2*t;if(o<this.numberOfElements&&this.less(o,o+1)&&o++,!this.less(t,o))break;this.exchange(t,o),t=o}}getValueAt(t){return this.getElementValue(this.priorityQueue[t])}less(t,o){return this.getValueAt(t)<this.getValueAt(o)}exchange(t,o){let n=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[o],this.priorityQueue[o]=n}};function G1(e,t,o,n){return{y:n.get(e,t,o),x:n.get(e,t,o+SA)}}function B1(e,t,o){let{heatmapY:n,heatmapX:r,id:A}=e,{y:s,x:a}=G1(n,r,A,o);return{x:e.heatmapX*t+a,y:e.heatmapY*t+s}}function H1(e,t,o){return e<t?t:e>o?o:e}function Fo(e,t,o,n){let r=o-e,A=n-t;return r*r+A*A}function V1(e,t){return{x:e.x+t.x,y:e.y+t.y}}var $0,jA=["MobilenetV1/offset_2/BiasAdd","MobilenetV1/heatmap_2/BiasAdd","MobilenetV1/displacement_fwd_2/BiasAdd","MobilenetV1/displacement_bwd_2/BiasAdd"],M5=1,i2=16,OA=50**2;function Go(e,t,o,n,r,A,s=2){let a=g=>({y:A.get(g.y,g.x,e),x:A.get(g.y,g.x,A.shape[2]/2+e)}),i=(g,b,d)=>({y:H1(Math.round(g.y/i2),0,b-1),x:H1(Math.round(g.x/i2),0,d-1)}),[x,c]=n.shape,l=i(t.position,x,c),y=a(l),u=V1(t.position,y);for(let g=0;g<s;g++){let b=i(u,x,c),d=G1(b.y,b.x,o,r);u=V1({x:b.x*i2,y:b.y*i2},{x:d.x,y:d.y})}let m=i(u,x,c),P=n.get(m.y,m.x,o);return{position:u,part:S2[o],score:P}}function NA(e,t,o,n,r){let A=No.map(([y,f])=>[z2[y],z2[f]]),s=A.map(([,y])=>y),a=A.map(([y])=>y),i=t.shape[2],x=s.length,c=new Array(i),l=B1(e.part,i2,o);c[e.part.id]={score:e.score,part:S2[e.part.id],position:l};for(let y=x-1;y>=0;--y){let f=s[y],u=a[y];c[f]&&!c[u]&&(c[u]=Go(y,c[f],u,t,o,r))}for(let y=0;y<x;++y){let f=a[y],u=s[y];c[f]&&!c[u]&&(c[u]=Go(y,c[f],u,t,o,n))}return c}function LA(e,t,o,n,r){let[A,s]=r.shape,a=!0,i=Math.max(o-M5,0),x=Math.min(o+M5+1,A);for(let c=i;c<x;++c){let l=Math.max(n-M5,0),y=Math.min(n+M5+1,s);for(let f=l;f<y;++f)if(r.get(c,f,e)>t){a=!1;break}if(!a)break}return a}function WA(e,t){let[o,n,r]=t.shape,A=new g5(o*n*r,({score:s})=>s);for(let s=0;s<o;++s)for(let a=0;a<n;++a)for(let i=0;i<r;++i){let x=t.get(s,a,i);x<e||LA(i,x,s,a,t)&&A.enqueue({score:x,part:{heatmapY:s,heatmapX:a,id:i}})}return A}function Bo(e,{x:t,y:o},n){return e.some(({keypoints:r})=>{var s;let A=(s=r[n])==null?void 0:s.position;return A?Fo(o,t,A.y,A.x)<=OA:!1})}function FA(e,t){return t.reduce((n,{position:r,score:A},s)=>(Bo(e,r,s)||(n+=A),n),0)/t.length}function GA(e,t,o,n,r,A){let s=[],a=WA(A,t);for(;s.length<r&&!a.empty();){let i=a.dequeue(),x=B1(i.part,i2,e);if(Bo(s,x,i.part.id))continue;let c=NA(i,t,e,o,n);c=c.filter(f=>f.score>A);let l=FA(s,c),y=Lo(c);l>A&&s.push({keypoints:c,box:y,score:Math.round(100*l)/100})}return s}async function D1(e,t){let o=z0.tidy(()=>{if(!$0.inputs[0].shape)return[];let s=z0.image.resizeBilinear(e,[$0.inputs[0].shape[2],$0.inputs[0].shape[1]]),a=z0.sub(z0.div(z0.cast(s,"float32"),127.5),1),x=$0.execute(a,jA).map(c=>z0.squeeze(c,[0]));return x[1]=z0.sigmoid(x[1]),x}),n=await Promise.all(o.map(s=>s.buffer()));for(let s of o)z0.dispose(s);let r=await GA(n[0],n[1],n[2],n[3],t.body.maxDetected,t.body.minConfidence);return $0.inputs[0].shape?Wo(r,[e.shape[1],e.shape[2]],[$0.inputs[0].shape[2],$0.inputs[0].shape[1]]):[]}async function Ho(e){return!$0||v.initial?$0=await G(e.body.modelPath):e.debug&&p("cached model:",$0.modelUrl),$0}var n0=Z(D());var ne,Z1=!1;async function X1(e){return!ne||v.initial?ne=await G(e.segmentation.modelPath):e.debug&&p("cached model:",ne.modelUrl),ne}async function Do(e,t,o){var m,P;if(Z1)return{data:[],canvas:null,alpha:null};Z1=!0,ne||await X1(o);let n=await Ye(e,o),r=((m=n.tensor)==null?void 0:m.shape[2])||0,A=((P=n.tensor)==null?void 0:P.shape[1])||0;if(!n.tensor)return{data:[],canvas:null,alpha:null};let s={};s.resize=n0.image.resizeBilinear(n.tensor,[ne.inputs[0].shape?ne.inputs[0].shape[1]:0,ne.inputs[0].shape?ne.inputs[0].shape[2]:0],!1),n0.dispose(n.tensor),s.norm=n0.div(s.resize,V.tf255),s.res=ne.execute(s.norm),s.squeeze=n0.squeeze(s.res,0),s.squeeze.shape[2]===2?(s.softmax=n0.softmax(s.squeeze),[s.bg,s.fg]=n0.unstack(s.softmax,2),s.expand=n0.expandDims(s.fg,2),s.pad=n0.expandDims(s.expand,0),s.crop=n0.image.cropAndResize(s.pad,[[0,0,.5,.5]],[0],[r,A]),s.data=n0.squeeze(s.crop,0)):s.data=n0.image.resizeBilinear(s.squeeze,[A,r]);let a=Array.from(await s.data.data());if(v.node&&!v.Canvas&&typeof ImageData=="undefined")return o.debug&&p("canvas support missing"),Object.keys(s).forEach(g=>n0.dispose(s[g])),{data:a,canvas:null,alpha:null};let i=R0(r,A);n0.browser&&await n0.browser.toPixels(s.data,i);let x=i.getContext("2d");o.segmentation.blur&&o.segmentation.blur>0&&(x.filter=`blur(${o.segmentation.blur}px)`);let c=x.getImageData(0,0,r,A),l=R0(r,A),y=l.getContext("2d");n.canvas&&y.drawImage(n.canvas,0,0),y.globalCompositeOperation="darken",o.segmentation.blur&&o.segmentation.blur>0&&(y.filter=`blur(${o.segmentation.blur}px)`),y.drawImage(i,0,0),y.globalCompositeOperation="source-over",y.filter="none";let f=y.getImageData(0,0,r,A);for(let g=0;g<r*A;g++)f.data[4*g+3]=c.data[4*g+0];y.putImageData(f,0,0);let u=null;if(t&&l){u=R0(r,A);let g=await Ye(t,o);n0.dispose(g.tensor);let b=u.getContext("2d");b.drawImage(g.canvas,0,0,u.width,u.height),b.drawImage(l,0,0)}return Object.keys(s).forEach(g=>n0.dispose(s[g])),Z1=!1,{data:a,canvas:l,alpha:i}}var C2=class{constructor(){T(this,"ssrnetage",null);T(this,"gear",null);T(this,"blazeposedetect",null);T(this,"blazepose",null);T(this,"centernet",null);T(this,"efficientpose",null);T(this,"mobilefacenet",null);T(this,"emotion",null);T(this,"facedetect",null);T(this,"faceiris",null);T(this,"facemesh",null);T(this,"faceres",null);T(this,"ssrnetgender",null);T(this,"handpose",null);T(this,"handskeleton",null);T(this,"handtrack",null);T(this,"liveness",null);T(this,"movenet",null);T(this,"nanodet",null);T(this,"posenet",null);T(this,"segmentation",null);T(this,"antispoof",null)}},q1=e=>{let t=0,o=0,n=0;for(let A of Object.values(q0))t+=A.sizeFromManifest,o+=A.sizeLoadedWeights,n+=A.sizeDesired;let r=n>0?o/n:0;return{numLoadedModels:Object.values(q0).length,numEnabledModels:void 0,numDefinedModels:Object.keys(e.models).length,percentageLoaded:r,totalSizeFromManifest:t,totalSizeWeights:o,totalSizeLoading:n,totalSizeEnabled:void 0,modelStats:Object.values(q0)}};function P5(e){for(let t of Object.keys(e.models))e.models[t]=null}async function U1(e){var t,o,n,r,A,s,a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0;v.initial&&P5(e),e.config.hand.enabled&&(!e.models.handpose&&((o=(t=e.config.hand.detector)==null?void 0:t.modelPath)==null?void 0:o.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await T1(e.config)),!e.models.handskeleton&&e.config.hand.landmarks&&((r=(n=e.config.hand.detector)==null?void 0:n.modelPath)==null?void 0:r.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await T1(e.config))),e.config.body.enabled&&!e.models.blazepose&&((s=(A=e.config.body)==null?void 0:A.modelPath)==null?void 0:s.includes("blazepose"))&&(e.models.blazepose=c3(e.config)),e.config.body.enabled&&!e.models.blazeposedetect&&e.config.body.detector&&e.config.body.detector.modelPath&&(e.models.blazeposedetect=x3(e.config)),e.config.body.enabled&&!e.models.efficientpose&&((i=(a=e.config.body)==null?void 0:a.modelPath)==null?void 0:i.includes("efficientpose"))&&(e.models.efficientpose=h3(e.config)),e.config.body.enabled&&!e.models.movenet&&((c=(x=e.config.body)==null?void 0:x.modelPath)==null?void 0:c.includes("movenet"))&&(e.models.movenet=So(e.config)),e.config.body.enabled&&!e.models.posenet&&((y=(l=e.config.body)==null?void 0:l.modelPath)==null?void 0:y.includes("posenet"))&&(e.models.posenet=Ho(e.config)),e.config.face.enabled&&!e.models.facedetect&&(e.models.facedetect=o3(e.config)),e.config.face.enabled&&((f=e.config.face.antispoof)==null?void 0:f.enabled)&&!e.models.antispoof&&(e.models.antispoof=Dt(e.config)),e.config.face.enabled&&((u=e.config.face.liveness)==null?void 0:u.enabled)&&!e.models.liveness&&(e.models.liveness=Ro(e.config)),e.config.face.enabled&&((m=e.config.face.description)==null?void 0:m.enabled)&&!e.models.faceres&&(e.models.faceres=Z3(e.config)),e.config.face.enabled&&((P=e.config.face.emotion)==null?void 0:P.enabled)&&!e.models.emotion&&(e.models.emotion=P3(e.config)),e.config.face.enabled&&((g=e.config.face.iris)==null?void 0:g.enabled)&&!((b=e.config.face.attention)!=null&&b.enabled)&&!e.models.faceiris&&(e.models.faceiris=j3(e.config)),e.config.face.enabled&&((d=e.config.face.mesh)==null?void 0:d.enabled)&&!e.models.facemesh&&(e.models.facemesh=G3(e.config)),e.config.face.enabled&&((M=e.config.face.gear)==null?void 0:M.enabled)&&!e.models.gear&&(e.models.gear=St(e.config)),e.config.face.enabled&&((S=e.config.face.ssrnet)==null?void 0:S.enabled)&&!e.models.ssrnetage&&(e.models.ssrnetage=Nt(e.config)),e.config.face.enabled&&((w=e.config.face.ssrnet)==null?void 0:w.enabled)&&!e.models.ssrnetgender&&(e.models.ssrnetgender=Gt(e.config)),e.config.face.enabled&&((j=e.config.face.mobilefacenet)==null?void 0:j.enabled)&&!e.models.mobilefacenet&&(e.models.mobilefacenet=E3(e.config)),e.config.hand.enabled&&!e.models.handtrack&&((F=(C=e.config.hand.detector)==null?void 0:C.modelPath)==null?void 0:F.includes("handtrack"))&&(e.models.handtrack=ho(e.config)),e.config.hand.enabled&&e.config.hand.landmarks&&!e.models.handskeleton&&((Y=(H=e.config.hand.detector)==null?void 0:H.modelPath)==null?void 0:Y.includes("handtrack"))&&(e.models.handskeleton=bo(e.config)),e.config.object.enabled&&!e.models.centernet&&((x0=(J=e.config.object)==null?void 0:J.modelPath)==null?void 0:x0.includes("centernet"))&&(e.models.centernet=m3(e.config)),e.config.object.enabled&&!e.models.nanodet&&((G0=(E=e.config.object)==null?void 0:E.modelPath)==null?void 0:G0.includes("nanodet"))&&(e.models.nanodet=jo(e.config)),e.config.segmentation.enabled&&!e.models.segmentation&&(e.models.segmentation=X1(e.config));for await(let B0 of Object.keys(e.models))e.models[B0]&&typeof e.models[B0]!="undefined"&&(e.models[B0]=await e.models[B0])}async function Y1(e){let t=["const","placeholder","noop","pad","squeeze","add","sub","mul","div"];for(let o of Object.keys(e.models)){let n=e.models[o];if(!n)continue;let r=[],A=n==null?void 0:n.executor;if(A&&A.graph.nodes)for(let a of Object.values(A.graph.nodes)){let i=a.op.toLowerCase();r.includes(i)||r.push(i)}else!A&&e.config.debug&&p("model signature not determined:",o);let s=[];for(let a of r)!t.includes(a)&&!e.env.kernels.includes(a)&&!e.env.kernels.includes(a.replace("_",""))&&!e.env.kernels.includes(a.replace("native",""))&&!e.env.kernels.includes(a.replace("v2",""))&&s.push(a);e.config.debug&&s.length>0&&p("model validation failed:",o,s)}}var t0={name:"humangl",priority:999,canvas:null,gl:null,extensions:[],webGLattr:{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!1,desynchronized:!0}};function BA(){let e=t0.gl;!e||(t0.extensions=e.getSupportedExtensions())}async function Xo(e){var t;if(e.config.backend==="humangl"&&(t0.name in s0.engine().registry&&(!t0.gl||!t0.gl.getParameter(t0.gl.VERSION))&&(p("error: humangl backend invalid context"),P5(e)),!s0.findBackend(t0.name))){try{t0.canvas=await R0(100,100)}catch(n){p("error: cannot create canvas:",n);return}try{if(t0.gl=(t=t0.canvas)==null?void 0:t.getContext("webgl2",t0.webGLattr),!t0.gl.getParameter(t0.gl.VERSION).includes("2.0")){p("override: using fallback webgl backend as webgl 2.0 is not detected"),e.config.backend="webgl";return}t0.canvas&&(t0.canvas.addEventListener("webglcontextlost",async r=>{throw p("error: humangl:",r.type),p("possible browser memory leak using webgl or conflict with multiple backend registrations"),e.emit("error"),new Error("backend error: webgl context lost")}),t0.canvas.addEventListener("webglcontextrestored",r=>{p("error: humangl context restored:",r)}),t0.canvas.addEventListener("webglcontextcreationerror",r=>{p("error: humangl context create:",r)}))}catch(n){p("error: cannot get WebGL context:",n);return}try{s0.setWebGLContext(2,t0.gl)}catch(n){p("error: cannot set WebGL context:",n);return}try{let n=new s0.GPGPUContext(t0.gl);s0.registerBackend(t0.name,()=>new s0.MathBackendWebGL(n),t0.priority)}catch(n){p("error: cannot register WebGL backend:",n);return}try{s0.getKernelsForBackend("webgl").forEach(r=>{let A={...r,backendName:t0.name};s0.registerKernel(A)})}catch(n){p("error: cannot update WebGL backend registration:",n);return}let o=s0.backend().getGPGPUContext?s0.backend().getGPGPUContext().gl:null;if(o)p(`humangl webgl version:${o.getParameter(o.VERSION)} renderer:${o.getParameter(o.RENDERER)}`);else{p("error: no current gl context:",o,t0.gl);return}try{s0.env().flagRegistry.WEBGL_VERSION&&s0.env().set("WEBGL_VERSION",2)}catch(n){p("error: cannot set WebGL backend flags:",n);return}BA(),p("backend registered:",t0.name)}}var I=Z(D());function HA(){if(!v.kernels.includes("mod")){let e={kernelName:"Mod",backendName:I.getBackend(),kernelFunc:t=>I.tidy(()=>I.sub(t.inputs.a,I.mul(I.div(t.inputs.a,t.inputs.b),t.inputs.b)))};I.registerKernel(e),v.kernels.push("mod")}if(!v.kernels.includes("floormod")){let e={kernelName:"FloorMod",backendName:I.getBackend(),kernelFunc:t=>I.tidy(()=>I.floorDiv(t.inputs.a/t.inputs.b)*t.inputs.b+I.mod(t.inputs.a,t.inputs.b))};I.registerKernel(e),v.kernels.push("floormod")}}async function v5(e,t=!1){if(e.state="backend",t||v.initial||e.config.backend&&e.config.backend.length>0&&I.getBackend()!==e.config.backend){let o=h();if(e.config.backend&&e.config.backend.length>0){if(typeof window=="undefined"&&typeof WorkerGlobalScope!="undefined"&&e.config.debug&&e.config.debug&&p("running inside web worker"),v.browser&&e.config.backend==="tensorflow"&&(e.config.debug&&p("override: backend set to tensorflow while running in browser"),e.config.backend="humangl"),v.node&&(e.config.backend==="webgl"||e.config.backend==="humangl")&&(e.config.debug&&p(`override: backend set to ${e.config.backend} while running in nodejs`),e.config.backend="tensorflow"),v.browser&&e.config.backend==="webgpu")if(typeof navigator=="undefined"||typeof navigator.gpu=="undefined")p("override: backend set to webgpu but browser does not support webgpu"),e.config.backend="humangl";else{let r=await navigator.gpu.requestAdapter();if(e.config.debug&&p("enumerated webgpu adapter:",r),!r)p("override: backend set to webgpu but browser reports no available gpu"),e.config.backend="humangl";else{let A="requestAdapterInfo"in r?await r.requestAdapterInfo():void 0;p("webgpu adapter info:",A)}}e.config.backend==="humangl"&&await Xo(e);let n=Object.keys(I.engine().registryFactory);if(e.config.debug&&p("available backends:",n),n.includes(e.config.backend)||(p(`error: backend ${e.config.backend} not found in registry`),e.config.backend=v.node?"tensorflow":"webgl",e.config.debug&&p(`override: setting backend ${e.config.backend}`)),e.config.debug&&p("setting backend:",e.config.backend),e.config.backend==="wasm"){if(I.env().flagRegistry.CANVAS2D_WILL_READ_FREQUENTLY&&I.env().set("CANVAS2D_WILL_READ_FREQUENTLY",!0),e.config.debug&&p("wasm path:",e.config.wasmPath),typeof(I==null?void 0:I.setWasmPaths)!="undefined")await I.setWasmPaths(e.config.wasmPath,e.config.wasmPlatformFetch);else throw new Error("backend error: attempting to use wasm backend but wasm path is not set");let r=await I.env().getAsync("WASM_HAS_SIMD_SUPPORT"),A=await I.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");e.config.debug&&p(`wasm execution: ${r?"SIMD":"no SIMD"} ${A?"multithreaded":"singlethreaded"}`),e.config.debug&&!r&&p("warning: wasm simd support is not enabled")}try{await I.setBackend(e.config.backend),await I.ready(),It()}catch(r){return p("error: cannot set backend:",e.config.backend,r),!1}}if(I.getBackend()==="humangl"&&(I.env().flagRegistry.CHECK_COMPUTATION_FOR_ERRORS&&I.env().set("CHECK_COMPUTATION_FOR_ERRORS",!1),I.env().flagRegistry.WEBGL_CPU_FORWARD&&I.env().set("WEBGL_CPU_FORWARD",!0),I.env().flagRegistry.WEBGL_USE_SHAPES_UNIFORMS&&I.env().set("WEBGL_USE_SHAPES_UNIFORMS",!0),I.env().flagRegistry.CPU_HANDOFF_SIZE_THRESHOLD&&I.env().set("CPU_HANDOFF_SIZE_THRESHOLD",256),I.env().flagRegistry.WEBGL_EXP_CONV&&I.env().set("WEBGL_EXP_CONV",!0),I.env().flagRegistry.USE_SETTIMEOUTWPM&&I.env().set("USE_SETTIMEOUTWPM",!0),typeof e.config.deallocate!="undefined"&&e.config.deallocate&&(p("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),I.env().set("WEBGL_DELETE_TEXTURE_THRESHOLD",0)),I.backend().getGPGPUContext)){let n=await I.backend().getGPGPUContext().gl;e.config.debug&&p(`gl version:${n.getParameter(n.VERSION)} renderer:${n.getParameter(n.RENDERER)}`)}I.getBackend(),I.enableProdMode(),await I.ready(),e.performance.initBackend=Math.trunc(h()-o),e.config.backend=I.getBackend(),await v.updateBackend(),HA()}return!0}function x5(e,t){for(let o of e){let n={kernelName:o,backendName:t.backend,kernelFunc:()=>{t.debug&&p("kernelFunc",o,t.backend)}};I.registerKernel(n)}v.kernels=I.getKernelsForBackend(I.getBackend()).map(o=>o.kernelName.toLowerCase())}var tt={};ue(tt,{all:()=>et,body:()=>y2,canvas:()=>$1,face:()=>l2,gesture:()=>d2,hand:()=>x2,object:()=>c2,options:()=>P0,person:()=>_1});var V0=e=>{if(!e)p("draw error: invalid canvas");else if(!e.getContext)p("draw error: canvas context not defined");else{let t=e.getContext("2d");if(!t)p("draw error: cannot get canvas context");else return t}return null},Xe=e=>Math.round(e*180/Math.PI),me=(e,t)=>{if(!t.useDepth||typeof e=="undefined")return t.color;let o=Uint8ClampedArray.from([127+2*e,127-2*e,255]);return`rgba(${o[0]}, ${o[1]}, ${o[2]}, ${t.alpha})`};function pe(e,t,o,n,r){e.fillStyle=me(n,r),e.beginPath(),e.arc(t,o,r.pointSize,0,2*Math.PI),e.fill()}function re(e,t,o,n,r,A){if(e.beginPath(),e.lineWidth=A.lineWidth,A.useCurves){let s=(t+t+n)/2,a=(o+o+r)/2;e.ellipse(s,a,n/2,r/2,0,0,2*Math.PI)}else e.moveTo(t+A.roundRect,o),e.lineTo(t+n-A.roundRect,o),e.quadraticCurveTo(t+n,o,t+n,o+A.roundRect),e.lineTo(t+n,o+r-A.roundRect),e.quadraticCurveTo(t+n,o+r,t+n-A.roundRect,o+r),e.lineTo(t+A.roundRect,o+r),e.quadraticCurveTo(t,o+r,t,o+r-A.roundRect),e.lineTo(t,o+A.roundRect),e.quadraticCurveTo(t,o,t+A.roundRect,o),e.closePath();e.stroke()}function K1(e,t,o){if(!(t.length<2)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let n of t)e.strokeStyle=me(n[2]||0,o),e.lineTo(Math.trunc(n[0]),Math.trunc(n[1]));e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function Uo(e,t,o){if(!(t.length<2)){if(e.lineWidth=o.lineWidth,!o.useCurves||t.length<=2){K1(e,t,o);return}e.moveTo(t[0][0],t[0][1]);for(let n=0;n<t.length-2;n++){let r=(t[n][0]+t[n+1][0])/2,A=(t[n][1]+t[n+1][1])/2;e.quadraticCurveTo(t[n][0],t[n][1],r,A)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function J1(e,t,o,n=5){let r,A,s;e.beginPath(),e.moveTo(t[0],t[1]),e.lineTo(o[0],o[1]),r=Math.atan2(o[1]-t[1],o[0]-t[0]),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.moveTo(A,s),r+=1/3*(2*Math.PI),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.lineTo(A,s),r+=1/3*(2*Math.PI),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.lineTo(A,s),e.closePath(),e.stroke(),e.fill()}var P0={color:"rgba(173, 216, 230, 0.6)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",alpha:.5,font:'small-caps 16px "Segoe UI"',lineHeight:18,lineWidth:4,pointSize:2,roundRect:8,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawAttention:!0,drawGestures:!0,drawPolygons:!0,drawGaze:!0,fillPolygons:!1,useDepth:!0,useCurves:!1};var U;function DA(e,t){if(U.drawLabels){let o=[];if(o.push(`face: ${Math.trunc(100*e.score)}%`),e.genderScore&&o.push(`${e.gender||""} ${Math.trunc(100*e.genderScore)}%`),e.age&&o.push(`age: ${e.age||""}`),e.iris&&o.push(`distance: ${e.iris}`),e.real&&o.push(`real: ${Math.trunc(100*e.real)}%`),e.live&&o.push(`live: ${Math.trunc(100*e.live)}%`),e.emotion&&e.emotion.length>0){let n=e.emotion.map(r=>`${Math.trunc(100*r.score)}% ${r.emotion}`);n.length>3&&(n.length=3),o.push(n.join(" "))}e.rotation&&e.rotation.angle&&e.rotation.gaze&&(e.rotation.angle.roll&&o.push(`roll: ${Xe(e.rotation.angle.roll)}\xB0 yaw:${Xe(e.rotation.angle.yaw)}\xB0 pitch:${Xe(e.rotation.angle.pitch)}\xB0`),e.rotation.gaze.bearing&&o.push(`gaze: ${Xe(e.rotation.gaze.bearing)}\xB0`)),o.length===0&&o.push("face"),t.fillStyle=U.color;for(let n=o.length-1;n>=0;n--){let r=Math.max(e.box[0],0),A=n*U.lineHeight+e.box[1];U.shadowColor&&U.shadowColor!==""&&(t.fillStyle=U.shadowColor,t.fillText(o[n],r+5,A+16)),t.fillStyle=U.labelColor,t.fillText(o[n],r+4,A+15)}}}function ZA(e,t){if(e.annotations&&e.annotations.leftEyeIris&&e.annotations.leftEyeIris[0]){t.strokeStyle=U.useDepth?"rgba(255, 200, 255, 0.3)":U.color,t.beginPath();let o=Math.abs(e.annotations.leftEyeIris[3][0]-e.annotations.leftEyeIris[1][0])/2,n=Math.abs(e.annotations.leftEyeIris[4][1]-e.annotations.leftEyeIris[2][1])/2;t.ellipse(e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),U.fillPolygons&&(t.fillStyle=U.useDepth?"rgba(255, 255, 200, 0.3)":U.color,t.fill())}if(e.annotations&&e.annotations.rightEyeIris&&e.annotations.rightEyeIris[0]){t.strokeStyle=U.useDepth?"rgba(255, 200, 255, 0.3)":U.color,t.beginPath();let o=Math.abs(e.annotations.rightEyeIris[3][0]-e.annotations.rightEyeIris[1][0])/2,n=Math.abs(e.annotations.rightEyeIris[4][1]-e.annotations.rightEyeIris[2][1])/2;t.ellipse(e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),U.fillPolygons&&(t.fillStyle=U.useDepth?"rgba(255, 255, 200, 0.3)":U.color,t.fill())}}function XA(e,t){var o;if(U.drawGaze&&((o=e.rotation)==null?void 0:o.angle)&&typeof Path2D!="undefined"){t.strokeStyle="pink";let n=e.box[0]+e.box[2]/2-e.box[3]*Xe(e.rotation.angle.yaw)/90,r=e.box[1]+e.box[3]/2+e.box[2]*Xe(e.rotation.angle.pitch)/90,A=new Path2D(`
       M ${e.box[0]+e.box[2]/2} ${e.box[1]}
       C
         ${n} ${e.box[1]},
@@ -108,7 +108,7 @@ var An=Object.create;var h2=Object.defineProperty;var sn=Object.getOwnPropertyDe
         ${e.box[0]} ${r},
         ${e.box[0]+e.box[2]} ${r},
         ${e.box[0]+e.box[2]} ${e.box[1]+e.box[3]/2}
-    `);t.stroke(s),t.stroke(A)}}function qA(e,t){var o,n,r,A;if(U.drawGaze&&((n=(o=e.rotation)==null?void 0:o.gaze)==null?void 0:n.strength)&&((A=(r=e.rotation)==null?void 0:r.gaze)==null?void 0:A.bearing)&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let s=[e.annotations.leftEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.leftEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];J1(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[s[0],s[1]],4);let a=[e.annotations.rightEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.rightEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];J1(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[a[0],a[1]],4)}}function UA(e,t){if(U.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let o=0;o<Ne.length/3;o++){let n=[Ne[o*3+0],Ne[o*3+1],Ne[o*3+2]].map(r=>e.mesh[r]);K1(t,n,U)}ZA(e,t)}}function YA(e,t){if(U.drawPoints&&e.mesh.length>=468)for(let o=0;o<e.mesh.length;o++)pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2],U),U.drawAttention&&(w2.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]+127,U),We.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,U),Fe.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,U))}function KA(e,t){U.drawBoxes&&re(t,e.box[0],e.box[1],e.box[2],e.box[3],U)}async function l2(e,t,o){if(U=r0(P0,o),!t||!e)return;let n=V0(e);if(!!n){n.font=U.font,n.strokeStyle=U.color,n.fillStyle=U.color;for(let r of t)KA(r,n),DA(r,n),r.mesh&&r.mesh.length>0&&(YA(r,n),UA(r,n),XA(r,n),qA(r,n))}}async function y2(e,t,o){var A;let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round";for(let s=0;s<t.length;s++){if(r.strokeStyle=n.color,r.fillStyle=n.color,r.lineWidth=n.lineWidth,r.font=n.font,n.drawBoxes&&t[s].box&&((A=t[s].box)==null?void 0:A.length)===4&&(re(r,t[s].box[0],t[s].box[1],t[s].box[2],t[s].box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`body ${100*t[s].score}%`,t[s].box[0]+3,1+t[s].box[1]+n.lineHeight,t[s].box[2])),r.fillStyle=n.labelColor,r.fillText(`body ${100*t[s].score}%`,t[s].box[0]+2,0+t[s].box[1]+n.lineHeight,t[s].box[2]))),n.drawPoints&&t[s].keypoints)for(let a=0;a<t[s].keypoints.length;a++)!t[s].keypoints[a].score||t[s].keypoints[a].score===0||(r.fillStyle=me(t[s].keypoints[a].position[2],n),pe(r,t[s].keypoints[a].position[0],t[s].keypoints[a].position[1],0,n));if(n.drawLabels&&t[s].keypoints){r.font=n.font;for(let a of t[s].keypoints)!a.score||a.score===0||(r.fillStyle=me(a.position[2],n),r.fillText(`${a.part} ${Math.trunc(100*a.score)}%`,a.position[0]+4,a.position[1]+4))}if(n.drawPolygons&&t[s].keypoints&&t[s].annotations)for(let a of Object.values(t[s].annotations))for(let i of a)Uo(r,i,n)}}}async function x2(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A of t){if(n.drawBoxes&&(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,A.box[0],A.box[1],A.box[2],A.box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`hand:${Math.trunc(100*A.score)}%`,A.box[0]+3,1+A.box[1]+n.lineHeight,A.box[2])),r.fillStyle=n.labelColor,r.fillText(`hand:${Math.trunc(100*A.score)}%`,A.box[0]+2,0+A.box[1]+n.lineHeight,A.box[2])),r.stroke()),n.drawPoints&&A.keypoints&&A.keypoints.length>0)for(let s of A.keypoints)r.fillStyle=me(s[2],n),pe(r,s[0],s[1],0,n);if(n.drawLabels&&A.annotations){let s=(a,i)=>{if(!a||a.length===0||!a[0])return;let x=a[a.length-1][2]||-256;r.fillStyle=me(x,n),r.fillText(i,a[a.length-1][0]+4,a[a.length-1][1]+4)};r.font=n.font,s(A.annotations.index,"index"),s(A.annotations.middle,"middle"),s(A.annotations.ring,"ring"),s(A.annotations.pinky,"pinky"),s(A.annotations.thumb,"thumb"),s(A.annotations.palm,"palm")}if(n.drawPolygons&&A.annotations){let s=a=>{if(!(!a||a.length===0||!a[0]))for(let i=0;i<a.length;i++){r.beginPath();let x=a[i][2]||0;r.strokeStyle=me(i*x,n),r.moveTo(a[i>0?i-1:0][0],a[i>0?i-1:0][1]),r.lineTo(a[i][0],a[i][1]),r.stroke()}};r.lineWidth=n.lineWidth,s(A.annotations.index),s(A.annotations.middle),s(A.annotations.ring),s(A.annotations.pinky),s(A.annotations.thumb)}}}}async function c2(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A of t)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,A.box[0],A.box[1],A.box[2],A.box[3],n),n.drawLabels){let s=`${A.label} ${Math.round(100*A.score)}%`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(s,A.box[0]+3,1+A.box[1]+n.lineHeight,A.box[2])),r.fillStyle=n.labelColor,r.fillText(s,A.box[0]+2,0+A.box[1]+n.lineHeight,A.box[2])}r.stroke()}}}async function d2(e,t,o){let n=r0(P0,o);if(!(!t||!e)&&n.drawGestures){let r=V0(e);if(!r)return;r.font=n.font,r.fillStyle=n.color;let A=1;for(let s=0;s<t.length;s++){let a=[],i=[];if([a,i]=Object.entries(t[s]),i.length>1&&i[1].length>0){let x=a[1]>0?`#${a[1]}`:"",c=`${a[0]} ${x}: ${i[1]}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(c,8,2+A*n.lineHeight)),r.fillStyle=n.labelColor,r.fillText(c,6,0+A*n.lineHeight),A+=1}}}}var Q1=0;async function _1(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A=0;A<t.length;A++)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,t[A].box[0],t[A].box[1],t[A].box[2],t[A].box[3],n),n.drawLabels){let s=`person #${A}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(s,t[A].box[0]+3,1+t[A].box[1]+n.lineHeight,t[A].box[2])),r.fillStyle=n.labelColor,r.fillText(s,t[A].box[0]+2,0+t[A].box[1]+n.lineHeight,t[A].box[2])}r.stroke()}}}async function $1(e,t){if(!e||!t)return;let o=V0(t);!o||o.drawImage(e,0,0)}async function et(e,t,o){if(!t||!t.performance||!t||!e)return null;let n=h(),r=r0(P0,o),A=Promise.all([l2(e,t.face,r),y2(e,t.body,r),x2(e,t.hand,r),c2(e,t.object,r),d2(e,t.gesture,r)]);return Q1=v.perfadd?Q1+Math.round(h()-n):Math.round(h()-n),t.performance.draw=Q1,A}var s0=Z(D());var Yo=Z(D());var f2=.1,ot=.5;function JA(e,t,o){let n=!1,r=o.length-1;for(let A=0;A<o.length;r=A++)o[A].y>t!=o[r].y>t&&e<(o[r].x-o[A].x)*(t-o[A].y)/(o[r].y-o[A].y)+o[A].x&&(n=!n);return n}async function Ko(e){if(!e.tensor||!e.mesh||e.mesh.length<100)return e.tensor;let t=e.tensor.shape[2]||0,o=e.tensor.shape[1]||0,n=await e.tensor.buffer(),r=[];for(let s of X0.silhouette)r.push({x:(e.mesh[s][0]-e.box[0])/e.box[2],y:(e.mesh[s][1]-e.box[1])/e.box[3]});f2&&f2>0&&(r=r.map(s=>({x:s.x>.5?s.x+f2:s.x-f2,y:s.y>.5?s.y+f2:s.y-f2})));for(let s=0;s<t;s++)for(let a=0;a<o;a++)JA(s/t,a/t,r)||(n.set(ot*n.get(0,a,s,0),0,a,s,0),n.set(ot*n.get(0,a,s,1),0,a,s,1),n.set(ot*n.get(0,a,s,2),0,a,s,2));let A=n.toTensor();return Yo.dispose(n),A}var _A=e=>{let t=(l,y)=>Math.atan2(l[1]-y[1],l[0]-y[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let o=[0,-.1],n=1,r=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),A=r?e.mesh[473]:e.mesh[468],s=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],a=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],i=[(s[0]-A[0])/a[0]-o[0],n*(A[1]-s[1])/a[1]-o[1]],x=Math.sqrt(i[0]*i[0]+i[1]*i[1]);return x=Math.min(x,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],i)+Math.PI/2)%Math.PI,strength:x}},Jo=(e,t)=>{let o=m=>{let P=Math.sqrt(m[0]*m[0]+m[1]*m[1]+m[2]*m[2]);return m[0]/=P,m[1]/=P,m[2]/=P,m},n=(m,P)=>{let g=m[0]-P[0],b=m[1]-P[1],d=m[2]-P[2];return[g,b,d]},r=(m,P)=>{let g=m[1]*P[2]-m[2]*P[1],b=m[2]*P[0]-m[0]*P[2],d=m[0]*P[1]-m[1]*P[0];return[g,b,d]},A=m=>{let[P,g,b,d,M,S,w,j,C]=m,F,H,Y;return d<1?d>-1?(Y=Math.asin(d),H=Math.atan2(-w,P),F=Math.atan2(-S,M)):(Y=-Math.PI/2,H=-Math.atan2(j,C),F=0):(Y=Math.PI/2,H=Math.atan2(j,C),F=0),isNaN(F)&&(F=0),isNaN(H)&&(H=0),isNaN(Y)&&(Y=0),{pitch:2*-F,yaw:2*-H,roll:2*-Y}},s=e.meshRaw;if(!s||s.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let a=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,i=[s[10],s[152],s[234],s[454]].map(m=>[m[0]*t[0]/a,m[1]*t[1]/a,m[2]]),x=o(n(i[1],i[0])),c=o(n(i[3],i[2])),l=o(r(c,x));c=r(x,l);let y=[c[0],c[1],c[2],x[0],x[1],x[2],l[0],l[1],l[2]],f=A(y),u=s.length===478?_A(e):{bearing:0,strength:0};return{angle:f,matrix:y,gaze:u}};var nt=async(e,t)=>{var f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0,R,c0;let o=h(),n,r,A,s,a,i,x,c,l=[];e.state="run:face";let y=await F3(t,e.config);if(e.performance.face=v.perfadd?(e.performance.face||0)+Math.trunc(h()-o):Math.trunc(h()-o),!t.shape||t.shape.length!==4)return[];if(!y)return[];for(let k=0;k<y.length;k++){if(e.analyze("Get Face"),!y[k].tensor||y[k].tensor.isDisposedInternal){p("Face object is disposed:",y[k].tensor);continue}if((f=e.config.face.detector)!=null&&f.mask){let K=await Ko(y[k]);s0.dispose(y[k].tensor),y[k].tensor=K}let $=y[k].mesh&&y[k].mesh.length>200?Jo(y[k],[t.shape[2],t.shape[1]]):null;e.analyze("Start Emotion:"),e.config.async?s=(u=e.config.face.emotion)!=null&&u.enabled?y1(y[k].tensor||s0.tensor([]),e.config,k,y.length):[]:(e.state="run:emotion",o=h(),s=(m=e.config.face.emotion)!=null&&m.enabled?await y1(y[k].tensor||s0.tensor([]),e.config,k,y.length):[],e.performance.emotion=v.perfadd?(e.performance.emotion||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Emotion:"),e.analyze("Start AntiSpoof:"),e.config.async?i=(P=e.config.face.antispoof)!=null&&P.enabled?X5(y[k].tensor||s0.tensor([]),e.config,k,y.length):0:(e.state="run:antispoof",o=h(),i=(g=e.config.face.antispoof)!=null&&g.enabled?await X5(y[k].tensor||s0.tensor([]),e.config,k,y.length):0,e.performance.antispoof=v.perfadd?(e.performance.antispoof||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End AntiSpoof:"),e.analyze("Start Liveness:"),e.config.async?x=(b=e.config.face.liveness)!=null&&b.enabled?S1(y[k].tensor||s0.tensor([]),e.config,k,y.length):0:(e.state="run:liveness",o=h(),x=(d=e.config.face.liveness)!=null&&d.enabled?await S1(y[k].tensor||s0.tensor([]),e.config,k,y.length):0,e.performance.liveness=v.perfadd?(e.performance.antispoof||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Liveness:"),e.analyze("Start GEAR:"),e.config.async?r=(M=e.config.face.gear)!=null&&M.enabled?F5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null:(e.state="run:gear",o=h(),r=(S=e.config.face.gear)!=null&&S.enabled?await F5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,e.performance.gear=Math.trunc(h()-o)),e.analyze("End GEAR:"),e.analyze("Start SSRNet:"),e.config.async?(n=(w=e.config.face.ssrnet)!=null&&w.enabled?B5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,A=(j=e.config.face.ssrnet)!=null&&j.enabled?D5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null):(e.state="run:ssrnet",o=h(),n=(C=e.config.face.ssrnet)!=null&&C.enabled?await B5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,A=(F=e.config.face.ssrnet)!=null&&F.enabled?await D5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,e.performance.ssrnet=Math.trunc(h()-o)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?a=(H=e.config.face.mobilefacenet)!=null&&H.enabled?c1(y[k].tensor||s0.tensor([]),e.config,k,y.length):null:(e.state="run:mobilefacenet",o=h(),a=(Y=e.config.face.mobilefacenet)!=null&&Y.enabled?await c1(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,e.performance.mobilefacenet=Math.trunc(h()-o)),e.analyze("End MobileFaceNet:"),e.analyze("Start Description:"),e.config.async?c=(J=e.config.face.description)!=null&&J.enabled?h1(y[k].tensor||s0.tensor([]),e.config,k,y.length):null:(e.state="run:description",o=h(),c=(x0=e.config.face.description)!=null&&x0.enabled?await h1(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,e.performance.description=v.perfadd?(e.performance.description||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Description:"),e.config.async&&([n,A,s,a,c,r,i,x]=await Promise.all([n,A,s,a,c,r,i,x])),e.analyze("Finish Face:"),((E=e.config.face.ssrnet)==null?void 0:E.enabled)&&n&&A&&(c={...c,age:n.age,gender:A.gender,genderScore:A.genderScore}),((G0=e.config.face.gear)==null?void 0:G0.enabled)&&r&&(c={...c,age:r.age,gender:r.gender,genderScore:r.genderScore,race:r.race}),((B0=e.config.face.mobilefacenet)==null?void 0:B0.enabled)&&a&&(c.descriptor=a),(R=e.config.face.iris)!=null&&R.enabled;let a0=y[k].annotations&&y[k].annotations.leftEyeIris&&y[k].annotations.leftEyeIris[0]&&y[k].annotations.rightEyeIris&&y[k].annotations.rightEyeIris[0]&&y[k].annotations.leftEyeIris.length>0&&y[k].annotations.rightEyeIris.length>0&&y[k].annotations.leftEyeIris[0]!==null&&y[k].annotations.rightEyeIris[0]!==null?Math.max(Math.abs(y[k].annotations.leftEyeIris[3][0]-y[k].annotations.leftEyeIris[1][0]),Math.abs(y[k].annotations.rightEyeIris[4][1]-y[k].annotations.rightEyeIris[2][1]))/t.shape[2]:0,f0=(c0=e.config.face.detector)!=null&&c0.return?s0.squeeze(y[k].tensor):null;s0.dispose(y[k].tensor),y[k].tensor&&delete y[k].tensor;let L={...y[k],id:k};c!=null&&c.age&&(L.age=c.age),c!=null&&c.gender&&(L.gender=c.gender),c!=null&&c.genderScore&&(L.genderScore=c==null?void 0:c.genderScore),c!=null&&c.descriptor&&(L.embedding=c==null?void 0:c.descriptor),c!=null&&c.race&&(L.race=c==null?void 0:c.race),s&&(L.emotion=s),i&&(L.real=i),x&&(L.live=x),a0&&a0!==0&&(L.iris=Math.trunc(500/a0/11.7)/100),$&&(L.rotation=$),f0&&(L.tensor=f0),l.push(L),e.analyze("End Face")}return e.analyze("End FaceMesh:"),e.config.async&&(e.performance.face&&delete e.performance.face,e.performance.age&&delete e.performance.age,e.performance.gender&&delete e.performance.gender,e.performance.emotion&&delete e.performance.emotion),l};var Qo=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=e[o].keypoints.find(i=>i.part==="leftWrist"),r=e[o].keypoints.find(i=>i.part==="rightWrist"),A=e[o].keypoints.find(i=>i.part==="nose");A&&n&&r&&n.position[1]<A.position[1]&&r.position[1]<A.position[1]?t.push({body:o,gesture:"i give up"}):A&&n&&n.position[1]<A.position[1]?t.push({body:o,gesture:"raise left hand"}):A&&r&&r.position[1]<A.position[1]&&t.push({body:o,gesture:"raise right hand"});let s=e[o].keypoints.find(i=>i.part==="leftShoulder"),a=e[o].keypoints.find(i=>i.part==="rightShoulder");s&&a&&Math.abs(s.positionRaw[1]-a.positionRaw[1])>.1&&t.push({body:o,gesture:`leaning ${s.position[1]>a.position[1]?"left":"right"}`})}return t},_o=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++)if(e[o].mesh&&e[o].mesh.length>450){let n=(e[o].mesh[33][2]||0)-(e[o].mesh[263][2]||0),r=e[o].mesh[33][0]-e[o].mesh[263][0];Math.abs(n/r)<=.15?t.push({face:o,gesture:"facing center"}):t.push({face:o,gesture:`facing ${n<0?"left":"right"}`}),Math.abs(e[o].mesh[374][1]-e[o].mesh[386][1])/Math.abs(e[o].mesh[443][1]-e[o].mesh[450][1])<.2&&t.push({face:o,gesture:"blink left eye"}),Math.abs(e[o].mesh[145][1]-e[o].mesh[159][1])/Math.abs(e[o].mesh[223][1]-e[o].mesh[230][1])<.2&&t.push({face:o,gesture:"blink right eye"});let a=Math.min(100,500*Math.abs(e[o].mesh[13][1]-e[o].mesh[14][1])/Math.abs(e[o].mesh[10][1]-e[o].mesh[152][1]));a>10&&t.push({face:o,gesture:`mouth ${Math.trunc(a)}% open`});let i=e[o].mesh[152][2]||0;Math.abs(i)>10&&t.push({face:o,gesture:`head ${i<0?"up":"down"}`})}return t},$o=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){if(!e[o].annotations||!e[o].annotations.leftEyeIris||!e[o].annotations.leftEyeIris[0]||!e[o].annotations.rightEyeIris||!e[o].annotations.rightEyeIris[0])continue;let n=e[o].annotations.leftEyeIris[3][0]-e[o].annotations.leftEyeIris[1][0],r=e[o].annotations.leftEyeIris[4][1]-e[o].annotations.leftEyeIris[2][1],A=Math.abs(n*r),s=e[o].annotations.rightEyeIris[3][0]-e[o].annotations.rightEyeIris[1][0],a=e[o].annotations.rightEyeIris[4][1]-e[o].annotations.rightEyeIris[2][1],i=Math.abs(s*a),x=!1;Math.abs(A-i)/Math.max(A,i)<.25&&(x=!0,t.push({iris:o,gesture:"facing center"}));let l=Math.abs(e[o].mesh[263][0]-e[o].annotations.leftEyeIris[0][0])/e[o].box[2],y=Math.abs(e[o].mesh[33][0]-e[o].annotations.rightEyeIris[0][0])/e[o].box[2];(l>.06||y>.06)&&(x=!1),l>y?l>.05&&t.push({iris:o,gesture:"looking right"}):y>.05&&t.push({iris:o,gesture:"looking left"});let f=Math.abs(e[o].mesh[145][1]-e[o].annotations.rightEyeIris[0][1])/e[o].box[3],u=Math.abs(e[o].mesh[374][1]-e[o].annotations.leftEyeIris[0][1])/e[o].box[3];(u<.01||f<.01||u>.022||f>.022)&&(x=!1),(u<.01||f<.01)&&t.push({iris:o,gesture:"looking down"}),(u>.022||f>.022)&&t.push({iris:o,gesture:"looking up"}),x&&t.push({iris:o,gesture:"looking center"})}return t},en=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=[];if(e[o].annotations)for(let[r,A]of Object.entries(e[o].annotations))r!=="palmBase"&&Array.isArray(A)&&A[0]&&n.push({name:r.toLowerCase(),position:A[0]});if(n&&n.length>0){let r=n.reduce((s,a)=>(s.position[2]||0)<(a.position[2]||0)?s:a);t.push({hand:o,gesture:`${r.name} forward`});let A=n.reduce((s,a)=>s.position[1]<a.position[1]?s:a);t.push({hand:o,gesture:`${A.name} up`})}if(e[o].keypoints){let r=yo(e[o].keypoints);for(let A of r)t.push({hand:o,gesture:A.name})}}return t};var z={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null},rt=0;function tn(e,t){var s,a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0;let o=h();if(!e)return{face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null};let n=Date.now()-e.timestamp,r=n<1e3?8-Math.log(n+1):1;if(e.canvas&&(z.canvas=e.canvas),e.error&&(z.error=e.error),!z.body||e.body.length!==z.body.length)z.body=JSON.parse(JSON.stringify(e.body));else for(let R=0;R<e.body.length;R++){let c0=e.body[R].box.map((L,K)=>((r-1)*z.body[R].box[K]+L)/r),k=e.body[R].boxRaw.map((L,K)=>((r-1)*z.body[R].boxRaw[K]+L)/r),$=e.body[R].keypoints.map((L,K)=>{var Ae,se,p2,u2,qe,lt,yt,xt,ct;return{score:L.score,part:L.part,position:[z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[0]||0)+(L.position[0]||0))/r:L.position[0],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[1]||0)+(L.position[1]||0))/r:L.position[1],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[2]||0)+(L.position[2]||0))/r:L.position[2]],positionRaw:[z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[0]||0)+(L.positionRaw[0]||0))/r:L.positionRaw[0],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[1]||0)+(L.positionRaw[1]||0))/r:L.positionRaw[1],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[2]||0)+(L.positionRaw[2]||0))/r:L.positionRaw[2]],distance:[z.body[R].keypoints[K]?((r-1)*(((Ae=z.body[R].keypoints[K].distance)==null?void 0:Ae[0])||0)+(((se=L.distance)==null?void 0:se[0])||0))/r:(p2=L.distance)==null?void 0:p2[0],z.body[R].keypoints[K]?((r-1)*(((u2=z.body[R].keypoints[K].distance)==null?void 0:u2[1])||0)+(((qe=L.distance)==null?void 0:qe[1])||0))/r:(lt=L.distance)==null?void 0:lt[1],z.body[R].keypoints[K]?((r-1)*(((yt=z.body[R].keypoints[K].distance)==null?void 0:yt[2])||0)+(((xt=L.distance)==null?void 0:xt[2])||0))/r:(ct=L.distance)==null?void 0:ct[2]]}}),a0={},f0={connected:{}};(a=(s=t.body)==null?void 0:s.modelPath)!=null&&a.includes("efficientpose")?f0=e5:(x=(i=t.body)==null?void 0:i.modelPath)!=null&&x.includes("blazepose")?f0=K2:(l=(c=t.body)==null?void 0:c.modelPath)!=null&&l.includes("movenet")&&(f0=E2);for(let[L,K]of Object.entries(f0.connected)){let Ae=[];for(let se=0;se<K.length-1;se++){let p2=$.find(qe=>qe.part===K[se]),u2=$.find(qe=>qe.part===K[se+1]);p2&&u2&&Ae.push([p2.position,u2.position])}a0[L]=Ae}z.body[R]={...e.body[R],box:c0,boxRaw:k,keypoints:$,annotations:a0}}if(!z.hand||e.hand.length!==z.hand.length)z.hand=JSON.parse(JSON.stringify(e.hand));else for(let R=0;R<e.hand.length;R++){let c0=e.hand[R].box.map((f0,L)=>((r-1)*z.hand[R].box[L]+f0)/r),k=e.hand[R].boxRaw.map((f0,L)=>((r-1)*z.hand[R].boxRaw[L]+f0)/r);z.hand[R].keypoints.length!==e.hand[R].keypoints.length&&(z.hand[R].keypoints=e.hand[R].keypoints);let $=e.hand[R].keypoints&&e.hand[R].keypoints.length>0?e.hand[R].keypoints.map((f0,L)=>f0.map((K,Ae)=>((r-1)*(z.hand[R].keypoints[L][Ae]||1)+(K||0))/r)):[],a0={};if(Object.keys(z.hand[R].annotations).length!==Object.keys(e.hand[R].annotations).length)z.hand[R].annotations=e.hand[R].annotations,a0=z.hand[R].annotations;else if(e.hand[R].annotations)for(let f0 of Object.keys(e.hand[R].annotations))a0[f0]=e.hand[R].annotations[f0]&&e.hand[R].annotations[f0][0]?e.hand[R].annotations[f0].map((L,K)=>L.map((Ae,se)=>((r-1)*z.hand[R].annotations[f0][K][se]+Ae)/r)):null;z.hand[R]={...e.hand[R],box:c0,boxRaw:k,keypoints:$,annotations:a0}}if(!z.face||e.face.length!==z.face.length)z.face=JSON.parse(JSON.stringify(e.face));else for(let R=0;R<e.face.length;R++){let c0=e.face[R].box.map(($,a0)=>((r-1)*z.face[R].box[a0]+$)/r),k=e.face[R].boxRaw.map(($,a0)=>((r-1)*z.face[R].boxRaw[a0]+$)/r);if(e.face[R].rotation){let $={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};$.matrix=(y=e.face[R].rotation)==null?void 0:y.matrix,$.angle={roll:((r-1)*(((u=(f=z.face[R].rotation)==null?void 0:f.angle)==null?void 0:u.roll)||0)+(((P=(m=e.face[R].rotation)==null?void 0:m.angle)==null?void 0:P.roll)||0))/r,yaw:((r-1)*(((b=(g=z.face[R].rotation)==null?void 0:g.angle)==null?void 0:b.yaw)||0)+(((M=(d=e.face[R].rotation)==null?void 0:d.angle)==null?void 0:M.yaw)||0))/r,pitch:((r-1)*(((w=(S=z.face[R].rotation)==null?void 0:S.angle)==null?void 0:w.pitch)||0)+(((C=(j=e.face[R].rotation)==null?void 0:j.angle)==null?void 0:C.pitch)||0))/r},$.gaze={bearing:((r-1)*(((H=(F=z.face[R].rotation)==null?void 0:F.gaze)==null?void 0:H.bearing)||0)+(((J=(Y=e.face[R].rotation)==null?void 0:Y.gaze)==null?void 0:J.bearing)||0))/r,strength:((r-1)*(((E=(x0=z.face[R].rotation)==null?void 0:x0.gaze)==null?void 0:E.strength)||0)+(((B0=(G0=e.face[R].rotation)==null?void 0:G0.gaze)==null?void 0:B0.strength)||0))/r},z.face[R]={...e.face[R],rotation:$,box:c0,boxRaw:k}}z.face[R]={...e.face[R],box:c0,boxRaw:k}}if(!z.object||e.object.length!==z.object.length)z.object=JSON.parse(JSON.stringify(e.object));else for(let R=0;R<e.object.length;R++){let c0=e.object[R].box.map(($,a0)=>((r-1)*z.object[R].box[a0]+$)/r),k=e.object[R].boxRaw.map(($,a0)=>((r-1)*z.object[R].boxRaw[a0]+$)/r);z.object[R]={...e.object[R],box:c0,boxRaw:k}}if(e.persons){let R=e.persons;if(!z.persons||R.length!==z.persons.length)z.persons=JSON.parse(JSON.stringify(R));else for(let c0=0;c0<R.length;c0++)z.persons[c0].box=R[c0].box.map((k,$)=>((r-1)*z.persons[c0].box[$]+k)/r)}e.gesture&&(z.gesture=e.gesture);let A=h();return rt=v.perfadd?rt+Math.round(A-o):Math.round(A-o),e.performance&&(z.performance={...e.performance,interpolate:rt}),z}var at={};ue(at,{distance:()=>j2,match:()=>st,similarity:()=>At});function j2(e,t,o={order:2,multiplier:25}){let n=0;for(let r=0;r<e.length;r++){let A=!o.order||o.order===2?e[r]-t[r]:Math.abs(e[r]-t[r]);n+=!o.order||o.order===2?A*A:A**o.order}return(o.multiplier||20)*n}var on=(e,t,o,n)=>{if(e===0)return 1;let r=t===2?Math.sqrt(e):e**(1/t),A=(1-r/100-o)/(n-o);return Math.max(Math.min(A,1),0)};function At(e,t,o={order:2,multiplier:25,min:.2,max:.8}){let n=j2(e,t,o);return on(n,o.order||2,o.min||0,o.max||1)}function st(e,t,o={order:2,multiplier:25,threshold:0,min:.2,max:.8}){if(!Array.isArray(e)||!Array.isArray(t)||e.length<64||t.length===0||e.length!==t[0].length)return{index:-1,distance:Number.POSITIVE_INFINITY,similarity:0};let n=Number.MAX_SAFE_INTEGER,r=-1;for(let s=0;s<t.length;s++){let a=j2(e,t[s],o);if(a<n&&(n=a,r=s),n<(o.threshold||0))break}let A=on(n,o.order||2,o.min||0,o.max||1);return{index:r,distance:n,similarity:A}}function nn(e,t,o,n,r){var a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w;let A=0,s=[];for(let j of e){let C={id:A++,face:j,body:null,hands:{left:null,right:null},gestures:[],box:[0,0,0,0]};for(let E of t)j.box[0]>E.box[0]&&j.box[0]<E.box[0]+E.box[2]&&j.box[1]+j.box[3]>E.box[1]&&j.box[1]+j.box[3]<E.box[1]+E.box[3]&&(C.body=E);if(C.body)for(let E of o)E.box[0]+E.box[2]>C.body.box[0]&&E.box[0]+E.box[2]<C.body.box[0]+C.body.box[2]&&E.box[1]+E.box[3]>C.body.box[1]&&E.box[1]+E.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.left=E),E.box[0]<C.body.box[0]+C.body.box[2]&&E.box[0]>C.body.box[0]&&E.box[1]+E.box[3]>C.body.box[1]&&E.box[1]+E.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.right=E);for(let E of n)E.face!==void 0&&E.face===j.id?(a=C.gestures)==null||a.push(E):E.iris!==void 0&&E.iris===j.id?(i=C.gestures)==null||i.push(E):E.body!==void 0&&E.body===((x=C.body)==null?void 0:x.id)?(c=C.gestures)==null||c.push(E):E.hand!==void 0&&E.hand===((y=(l=C.hands)==null?void 0:l.left)==null?void 0:y.id)?(f=C.gestures)==null||f.push(E):E.hand!==void 0&&E.hand===((m=(u=C.hands)==null?void 0:u.right)==null?void 0:m.id)&&((P=C.gestures)==null||P.push(E));let F=[],H=[],Y=E=>{E&&E.length===4&&(F.push(E[0],E[0]+E[2]),H.push(E[1],E[1]+E[3]))};Y((g=C.face)==null?void 0:g.box),Y((b=C.body)==null?void 0:b.box),Y((M=(d=C.hands)==null?void 0:d.left)==null?void 0:M.box),Y((w=(S=C.hands)==null?void 0:S.right)==null?void 0:w.box);let J=Math.min(...F),x0=Math.min(...H);C.box=[J,x0,Math.max(...F)-J,Math.max(...H)-x0],r&&r[1]&&r[2]&&(C.boxRaw=[C.box[0]/r[2],C.box[1]/r[1],C.box[2]/r[2],C.box[3]/r[1]]),s.push(C)}return s}var T5=`
+    `);t.stroke(s),t.stroke(A)}}function qA(e,t){var o,n,r,A;if(U.drawGaze&&((n=(o=e.rotation)==null?void 0:o.gaze)==null?void 0:n.strength)&&((A=(r=e.rotation)==null?void 0:r.gaze)==null?void 0:A.bearing)&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let s=[e.annotations.leftEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.leftEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];J1(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[s[0],s[1]],4);let a=[e.annotations.rightEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.rightEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];J1(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[a[0],a[1]],4)}}function UA(e,t){if(U.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let o=0;o<Oe.length/3;o++){let n=[Oe[o*3+0],Oe[o*3+1],Oe[o*3+2]].map(r=>e.mesh[r]);K1(t,n,U)}ZA(e,t)}}function YA(e,t){if(U.drawPoints&&e.mesh.length>=468)for(let o=0;o<e.mesh.length;o++)pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2],U),U.drawAttention&&(w2.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]+127,U),We.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,U),Fe.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,U))}function KA(e,t){U.drawBoxes&&re(t,e.box[0],e.box[1],e.box[2],e.box[3],U)}async function l2(e,t,o){if(U=r0(P0,o),!t||!e)return;let n=V0(e);if(!!n){n.font=U.font,n.strokeStyle=U.color,n.fillStyle=U.color;for(let r of t)KA(r,n),DA(r,n),r.mesh&&r.mesh.length>0&&(YA(r,n),UA(r,n),XA(r,n),qA(r,n))}}async function y2(e,t,o){var A;let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round";for(let s=0;s<t.length;s++){if(r.strokeStyle=n.color,r.fillStyle=n.color,r.lineWidth=n.lineWidth,r.font=n.font,n.drawBoxes&&t[s].box&&((A=t[s].box)==null?void 0:A.length)===4&&(re(r,t[s].box[0],t[s].box[1],t[s].box[2],t[s].box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`body ${100*t[s].score}%`,t[s].box[0]+3,1+t[s].box[1]+n.lineHeight,t[s].box[2])),r.fillStyle=n.labelColor,r.fillText(`body ${100*t[s].score}%`,t[s].box[0]+2,0+t[s].box[1]+n.lineHeight,t[s].box[2]))),n.drawPoints&&t[s].keypoints)for(let a=0;a<t[s].keypoints.length;a++)!t[s].keypoints[a].score||t[s].keypoints[a].score===0||(r.fillStyle=me(t[s].keypoints[a].position[2],n),pe(r,t[s].keypoints[a].position[0],t[s].keypoints[a].position[1],0,n));if(n.drawLabels&&t[s].keypoints){r.font=n.font;for(let a of t[s].keypoints)!a.score||a.score===0||(r.fillStyle=me(a.position[2],n),r.fillText(`${a.part} ${Math.trunc(100*a.score)}%`,a.position[0]+4,a.position[1]+4))}if(n.drawPolygons&&t[s].keypoints&&t[s].annotations)for(let a of Object.values(t[s].annotations))for(let i of a)Uo(r,i,n)}}}async function x2(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A of t){if(n.drawBoxes&&(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,A.box[0],A.box[1],A.box[2],A.box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`hand:${Math.trunc(100*A.score)}%`,A.box[0]+3,1+A.box[1]+n.lineHeight,A.box[2])),r.fillStyle=n.labelColor,r.fillText(`hand:${Math.trunc(100*A.score)}%`,A.box[0]+2,0+A.box[1]+n.lineHeight,A.box[2])),r.stroke()),n.drawPoints&&A.keypoints&&A.keypoints.length>0)for(let s of A.keypoints)r.fillStyle=me(s[2],n),pe(r,s[0],s[1],0,n);if(n.drawLabels&&A.annotations){let s=(a,i)=>{if(!a||a.length===0||!a[0])return;let x=a[a.length-1][2]||-256;r.fillStyle=me(x,n),r.fillText(i,a[a.length-1][0]+4,a[a.length-1][1]+4)};r.font=n.font,s(A.annotations.index,"index"),s(A.annotations.middle,"middle"),s(A.annotations.ring,"ring"),s(A.annotations.pinky,"pinky"),s(A.annotations.thumb,"thumb"),s(A.annotations.palm,"palm")}if(n.drawPolygons&&A.annotations){let s=a=>{if(!(!a||a.length===0||!a[0]))for(let i=0;i<a.length;i++){r.beginPath();let x=a[i][2]||0;r.strokeStyle=me(i*x,n),r.moveTo(a[i>0?i-1:0][0],a[i>0?i-1:0][1]),r.lineTo(a[i][0],a[i][1]),r.stroke()}};r.lineWidth=n.lineWidth,s(A.annotations.index),s(A.annotations.middle),s(A.annotations.ring),s(A.annotations.pinky),s(A.annotations.thumb)}}}}async function c2(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A of t)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,A.box[0],A.box[1],A.box[2],A.box[3],n),n.drawLabels){let s=`${A.label} ${Math.round(100*A.score)}%`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(s,A.box[0]+3,1+A.box[1]+n.lineHeight,A.box[2])),r.fillStyle=n.labelColor,r.fillText(s,A.box[0]+2,0+A.box[1]+n.lineHeight,A.box[2])}r.stroke()}}}async function d2(e,t,o){let n=r0(P0,o);if(!(!t||!e)&&n.drawGestures){let r=V0(e);if(!r)return;r.font=n.font,r.fillStyle=n.color;let A=1;for(let s=0;s<t.length;s++){let a=[],i=[];if([a,i]=Object.entries(t[s]),i.length>1&&i[1].length>0){let x=a[1]>0?`#${a[1]}`:"",c=`${a[0]} ${x}: ${i[1]}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(c,8,2+A*n.lineHeight)),r.fillStyle=n.labelColor,r.fillText(c,6,0+A*n.lineHeight),A+=1}}}}var Q1=0;async function _1(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A=0;A<t.length;A++)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,t[A].box[0],t[A].box[1],t[A].box[2],t[A].box[3],n),n.drawLabels){let s=`person #${A}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(s,t[A].box[0]+3,1+t[A].box[1]+n.lineHeight,t[A].box[2])),r.fillStyle=n.labelColor,r.fillText(s,t[A].box[0]+2,0+t[A].box[1]+n.lineHeight,t[A].box[2])}r.stroke()}}}async function $1(e,t){if(!e||!t)return;let o=V0(t);!o||o.drawImage(e,0,0)}async function et(e,t,o){if(!t||!t.performance||!t||!e)return null;let n=h(),r=r0(P0,o),A=Promise.all([l2(e,t.face,r),y2(e,t.body,r),x2(e,t.hand,r),c2(e,t.object,r),d2(e,t.gesture,r)]);return Q1=v.perfadd?Q1+Math.round(h()-n):Math.round(h()-n),t.performance.draw=Q1,A}var a0=Z(D());var Yo=Z(D());var f2=.1,ot=.5;function JA(e,t,o){let n=!1,r=o.length-1;for(let A=0;A<o.length;r=A++)o[A].y>t!=o[r].y>t&&e<(o[r].x-o[A].x)*(t-o[A].y)/(o[r].y-o[A].y)+o[A].x&&(n=!n);return n}async function Ko(e){if(!e.tensor||!e.mesh||e.mesh.length<100)return e.tensor;let t=e.tensor.shape[2]||0,o=e.tensor.shape[1]||0,n=await e.tensor.buffer(),r=[];for(let s of X0.silhouette)r.push({x:(e.mesh[s][0]-e.box[0])/e.box[2],y:(e.mesh[s][1]-e.box[1])/e.box[3]});f2&&f2>0&&(r=r.map(s=>({x:s.x>.5?s.x+f2:s.x-f2,y:s.y>.5?s.y+f2:s.y-f2})));for(let s=0;s<t;s++)for(let a=0;a<o;a++)JA(s/t,a/t,r)||(n.set(ot*n.get(0,a,s,0),0,a,s,0),n.set(ot*n.get(0,a,s,1),0,a,s,1),n.set(ot*n.get(0,a,s,2),0,a,s,2));let A=n.toTensor();return Yo.dispose(n),A}var _A=e=>{let t=(l,y)=>Math.atan2(l[1]-y[1],l[0]-y[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let o=[0,-.1],n=1,r=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),A=r?e.mesh[473]:e.mesh[468],s=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],a=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],i=[(s[0]-A[0])/a[0]-o[0],n*(A[1]-s[1])/a[1]-o[1]],x=Math.sqrt(i[0]*i[0]+i[1]*i[1]);return x=Math.min(x,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],i)+Math.PI/2)%Math.PI,strength:x}},Jo=(e,t)=>{let o=m=>{let P=Math.sqrt(m[0]*m[0]+m[1]*m[1]+m[2]*m[2]);return m[0]/=P,m[1]/=P,m[2]/=P,m},n=(m,P)=>{let g=m[0]-P[0],b=m[1]-P[1],d=m[2]-P[2];return[g,b,d]},r=(m,P)=>{let g=m[1]*P[2]-m[2]*P[1],b=m[2]*P[0]-m[0]*P[2],d=m[0]*P[1]-m[1]*P[0];return[g,b,d]},A=m=>{let[P,g,b,d,M,S,w,j,C]=m,F,H,Y;return d<1?d>-1?(Y=Math.asin(d),H=Math.atan2(-w,P),F=Math.atan2(-S,M)):(Y=-Math.PI/2,H=-Math.atan2(j,C),F=0):(Y=Math.PI/2,H=Math.atan2(j,C),F=0),isNaN(F)&&(F=0),isNaN(H)&&(H=0),isNaN(Y)&&(Y=0),{pitch:2*-F,yaw:2*-H,roll:2*-Y}},s=e.meshRaw;if(!s||s.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let a=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,i=[s[10],s[152],s[234],s[454]].map(m=>[m[0]*t[0]/a,m[1]*t[1]/a,m[2]]),x=o(n(i[1],i[0])),c=o(n(i[3],i[2])),l=o(r(c,x));c=r(x,l);let y=[c[0],c[1],c[2],x[0],x[1],x[2],l[0],l[1],l[2]],f=A(y),u=s.length===478?_A(e):{bearing:0,strength:0};return{angle:f,matrix:y,gaze:u}};var nt=async(e,t)=>{var f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0,R,c0;let o=h(),n,r,A,s,a,i,x,c,l=[];e.state="run:face";let y=await F3(t,e.config);if(e.performance.face=v.perfadd?(e.performance.face||0)+Math.trunc(h()-o):Math.trunc(h()-o),!t.shape||t.shape.length!==4)return[];if(!y)return[];for(let k=0;k<y.length;k++){if(e.analyze("Get Face"),!y[k].tensor||y[k].tensor.isDisposedInternal){p("Face object is disposed:",y[k].tensor);continue}if((f=e.config.face.detector)!=null&&f.mask){let K=await Ko(y[k]);a0.dispose(y[k].tensor),y[k].tensor=K}let $=y[k].mesh&&y[k].mesh.length>200?Jo(y[k],[t.shape[2],t.shape[1]]):null;e.analyze("Start Emotion:"),e.config.async?s=(u=e.config.face.emotion)!=null&&u.enabled?y1(y[k].tensor||a0.tensor([]),e.config,k,y.length):[]:(e.state="run:emotion",o=h(),s=(m=e.config.face.emotion)!=null&&m.enabled?await y1(y[k].tensor||a0.tensor([]),e.config,k,y.length):[],e.performance.emotion=v.perfadd?(e.performance.emotion||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Emotion:"),e.analyze("Start AntiSpoof:"),e.config.async?i=(P=e.config.face.antispoof)!=null&&P.enabled?X5(y[k].tensor||a0.tensor([]),e.config,k,y.length):0:(e.state="run:antispoof",o=h(),i=(g=e.config.face.antispoof)!=null&&g.enabled?await X5(y[k].tensor||a0.tensor([]),e.config,k,y.length):0,e.performance.antispoof=v.perfadd?(e.performance.antispoof||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End AntiSpoof:"),e.analyze("Start Liveness:"),e.config.async?x=(b=e.config.face.liveness)!=null&&b.enabled?S1(y[k].tensor||a0.tensor([]),e.config,k,y.length):0:(e.state="run:liveness",o=h(),x=(d=e.config.face.liveness)!=null&&d.enabled?await S1(y[k].tensor||a0.tensor([]),e.config,k,y.length):0,e.performance.liveness=v.perfadd?(e.performance.antispoof||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Liveness:"),e.analyze("Start GEAR:"),e.config.async?r=(M=e.config.face.gear)!=null&&M.enabled?F5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null:(e.state="run:gear",o=h(),r=(S=e.config.face.gear)!=null&&S.enabled?await F5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,e.performance.gear=Math.trunc(h()-o)),e.analyze("End GEAR:"),e.analyze("Start SSRNet:"),e.config.async?(n=(w=e.config.face.ssrnet)!=null&&w.enabled?B5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,A=(j=e.config.face.ssrnet)!=null&&j.enabled?D5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null):(e.state="run:ssrnet",o=h(),n=(C=e.config.face.ssrnet)!=null&&C.enabled?await B5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,A=(F=e.config.face.ssrnet)!=null&&F.enabled?await D5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,e.performance.ssrnet=Math.trunc(h()-o)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?a=(H=e.config.face.mobilefacenet)!=null&&H.enabled?c1(y[k].tensor||a0.tensor([]),e.config,k,y.length):null:(e.state="run:mobilefacenet",o=h(),a=(Y=e.config.face.mobilefacenet)!=null&&Y.enabled?await c1(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,e.performance.mobilefacenet=Math.trunc(h()-o)),e.analyze("End MobileFaceNet:"),e.analyze("Start Description:"),e.config.async?c=(J=e.config.face.description)!=null&&J.enabled?h1(y[k].tensor||a0.tensor([]),e.config,k,y.length):null:(e.state="run:description",o=h(),c=(x0=e.config.face.description)!=null&&x0.enabled?await h1(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,e.performance.description=v.perfadd?(e.performance.description||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Description:"),e.config.async&&([n,A,s,a,c,r,i,x]=await Promise.all([n,A,s,a,c,r,i,x])),e.analyze("Finish Face:"),((E=e.config.face.ssrnet)==null?void 0:E.enabled)&&n&&A&&(c={...c,age:n.age,gender:A.gender,genderScore:A.genderScore}),((G0=e.config.face.gear)==null?void 0:G0.enabled)&&r&&(c={...c,age:r.age,gender:r.gender,genderScore:r.genderScore,race:r.race}),((B0=e.config.face.mobilefacenet)==null?void 0:B0.enabled)&&a&&(c.descriptor=a),(R=e.config.face.iris)!=null&&R.enabled;let i0=y[k].annotations&&y[k].annotations.leftEyeIris&&y[k].annotations.leftEyeIris[0]&&y[k].annotations.rightEyeIris&&y[k].annotations.rightEyeIris[0]&&y[k].annotations.leftEyeIris.length>0&&y[k].annotations.rightEyeIris.length>0&&y[k].annotations.leftEyeIris[0]!==null&&y[k].annotations.rightEyeIris[0]!==null?Math.max(Math.abs(y[k].annotations.leftEyeIris[3][0]-y[k].annotations.leftEyeIris[1][0]),Math.abs(y[k].annotations.rightEyeIris[4][1]-y[k].annotations.rightEyeIris[2][1]))/t.shape[2]:0,m0=(c0=e.config.face.detector)!=null&&c0.return?a0.squeeze(y[k].tensor):null;a0.dispose(y[k].tensor),y[k].tensor&&delete y[k].tensor;let L={...y[k],id:k};c!=null&&c.age&&(L.age=c.age),c!=null&&c.gender&&(L.gender=c.gender),c!=null&&c.genderScore&&(L.genderScore=c==null?void 0:c.genderScore),c!=null&&c.descriptor&&(L.embedding=c==null?void 0:c.descriptor),c!=null&&c.race&&(L.race=c==null?void 0:c.race),s&&(L.emotion=s),i&&(L.real=i),x&&(L.live=x),i0&&i0!==0&&(L.iris=Math.trunc(500/i0/11.7)/100),$&&(L.rotation=$),m0&&(L.tensor=m0),l.push(L),e.analyze("End Face")}return e.analyze("End FaceMesh:"),e.config.async&&(e.performance.face&&delete e.performance.face,e.performance.age&&delete e.performance.age,e.performance.gender&&delete e.performance.gender,e.performance.emotion&&delete e.performance.emotion),l};var Qo=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=e[o].keypoints.find(i=>i.part==="leftWrist"),r=e[o].keypoints.find(i=>i.part==="rightWrist"),A=e[o].keypoints.find(i=>i.part==="nose");A&&n&&r&&n.position[1]<A.position[1]&&r.position[1]<A.position[1]?t.push({body:o,gesture:"i give up"}):A&&n&&n.position[1]<A.position[1]?t.push({body:o,gesture:"raise left hand"}):A&&r&&r.position[1]<A.position[1]&&t.push({body:o,gesture:"raise right hand"});let s=e[o].keypoints.find(i=>i.part==="leftShoulder"),a=e[o].keypoints.find(i=>i.part==="rightShoulder");s&&a&&Math.abs(s.positionRaw[1]-a.positionRaw[1])>.1&&t.push({body:o,gesture:`leaning ${s.position[1]>a.position[1]?"left":"right"}`})}return t},_o=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++)if(e[o].mesh&&e[o].mesh.length>450){let n=(e[o].mesh[33][2]||0)-(e[o].mesh[263][2]||0),r=e[o].mesh[33][0]-e[o].mesh[263][0];Math.abs(n/r)<=.15?t.push({face:o,gesture:"facing center"}):t.push({face:o,gesture:`facing ${n<0?"left":"right"}`}),Math.abs(e[o].mesh[374][1]-e[o].mesh[386][1])/Math.abs(e[o].mesh[443][1]-e[o].mesh[450][1])<.2&&t.push({face:o,gesture:"blink left eye"}),Math.abs(e[o].mesh[145][1]-e[o].mesh[159][1])/Math.abs(e[o].mesh[223][1]-e[o].mesh[230][1])<.2&&t.push({face:o,gesture:"blink right eye"});let a=Math.min(100,500*Math.abs(e[o].mesh[13][1]-e[o].mesh[14][1])/Math.abs(e[o].mesh[10][1]-e[o].mesh[152][1]));a>10&&t.push({face:o,gesture:`mouth ${Math.trunc(a)}% open`});let i=e[o].mesh[152][2]||0;Math.abs(i)>10&&t.push({face:o,gesture:`head ${i<0?"up":"down"}`})}return t},$o=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){if(!e[o].annotations||!e[o].annotations.leftEyeIris||!e[o].annotations.leftEyeIris[0]||!e[o].annotations.rightEyeIris||!e[o].annotations.rightEyeIris[0])continue;let n=e[o].annotations.leftEyeIris[3][0]-e[o].annotations.leftEyeIris[1][0],r=e[o].annotations.leftEyeIris[4][1]-e[o].annotations.leftEyeIris[2][1],A=Math.abs(n*r),s=e[o].annotations.rightEyeIris[3][0]-e[o].annotations.rightEyeIris[1][0],a=e[o].annotations.rightEyeIris[4][1]-e[o].annotations.rightEyeIris[2][1],i=Math.abs(s*a),x=!1;Math.abs(A-i)/Math.max(A,i)<.25&&(x=!0,t.push({iris:o,gesture:"facing center"}));let l=Math.abs(e[o].mesh[263][0]-e[o].annotations.leftEyeIris[0][0])/e[o].box[2],y=Math.abs(e[o].mesh[33][0]-e[o].annotations.rightEyeIris[0][0])/e[o].box[2];(l>.06||y>.06)&&(x=!1),l>y?l>.05&&t.push({iris:o,gesture:"looking right"}):y>.05&&t.push({iris:o,gesture:"looking left"});let f=Math.abs(e[o].mesh[145][1]-e[o].annotations.rightEyeIris[0][1])/e[o].box[3],u=Math.abs(e[o].mesh[374][1]-e[o].annotations.leftEyeIris[0][1])/e[o].box[3];(u<.01||f<.01||u>.022||f>.022)&&(x=!1),(u<.01||f<.01)&&t.push({iris:o,gesture:"looking down"}),(u>.022||f>.022)&&t.push({iris:o,gesture:"looking up"}),x&&t.push({iris:o,gesture:"looking center"})}return t},en=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=[];if(e[o].annotations)for(let[r,A]of Object.entries(e[o].annotations))r!=="palmBase"&&Array.isArray(A)&&A[0]&&n.push({name:r.toLowerCase(),position:A[0]});if(n&&n.length>0){let r=n.reduce((s,a)=>(s.position[2]||0)<(a.position[2]||0)?s:a);t.push({hand:o,gesture:`${r.name} forward`});let A=n.reduce((s,a)=>s.position[1]<a.position[1]?s:a);t.push({hand:o,gesture:`${A.name} up`})}if(e[o].keypoints){let r=yo(e[o].keypoints);for(let A of r)t.push({hand:o,gesture:A.name})}}return t};var z={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null},rt=0;function tn(e,t){var s,a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0;let o=h();if(!e)return{face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null};let n=Date.now()-e.timestamp,r=n<1e3?8-Math.log(n+1):1;if(e.canvas&&(z.canvas=e.canvas),e.error&&(z.error=e.error),!z.body||e.body.length!==z.body.length)z.body=JSON.parse(JSON.stringify(e.body));else for(let R=0;R<e.body.length;R++){let c0=e.body[R].box.map((L,K)=>((r-1)*z.body[R].box[K]+L)/r),k=e.body[R].boxRaw.map((L,K)=>((r-1)*z.body[R].boxRaw[K]+L)/r),$=e.body[R].keypoints.map((L,K)=>{var Ae,se,p2,u2,qe,lt,yt,xt,ct;return{score:L.score,part:L.part,position:[z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[0]||0)+(L.position[0]||0))/r:L.position[0],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[1]||0)+(L.position[1]||0))/r:L.position[1],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[2]||0)+(L.position[2]||0))/r:L.position[2]],positionRaw:[z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[0]||0)+(L.positionRaw[0]||0))/r:L.positionRaw[0],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[1]||0)+(L.positionRaw[1]||0))/r:L.positionRaw[1],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[2]||0)+(L.positionRaw[2]||0))/r:L.positionRaw[2]],distance:[z.body[R].keypoints[K]?((r-1)*(((Ae=z.body[R].keypoints[K].distance)==null?void 0:Ae[0])||0)+(((se=L.distance)==null?void 0:se[0])||0))/r:(p2=L.distance)==null?void 0:p2[0],z.body[R].keypoints[K]?((r-1)*(((u2=z.body[R].keypoints[K].distance)==null?void 0:u2[1])||0)+(((qe=L.distance)==null?void 0:qe[1])||0))/r:(lt=L.distance)==null?void 0:lt[1],z.body[R].keypoints[K]?((r-1)*(((yt=z.body[R].keypoints[K].distance)==null?void 0:yt[2])||0)+(((xt=L.distance)==null?void 0:xt[2])||0))/r:(ct=L.distance)==null?void 0:ct[2]]}}),i0={},m0={connected:{}};(a=(s=t.body)==null?void 0:s.modelPath)!=null&&a.includes("efficientpose")?m0=e5:(x=(i=t.body)==null?void 0:i.modelPath)!=null&&x.includes("blazepose")?m0=K2:(l=(c=t.body)==null?void 0:c.modelPath)!=null&&l.includes("movenet")&&(m0=E2);for(let[L,K]of Object.entries(m0.connected)){let Ae=[];for(let se=0;se<K.length-1;se++){let p2=$.find(qe=>qe.part===K[se]),u2=$.find(qe=>qe.part===K[se+1]);p2&&u2&&Ae.push([p2.position,u2.position])}i0[L]=Ae}z.body[R]={...e.body[R],box:c0,boxRaw:k,keypoints:$,annotations:i0}}if(!z.hand||e.hand.length!==z.hand.length)z.hand=JSON.parse(JSON.stringify(e.hand));else for(let R=0;R<e.hand.length;R++){let c0=e.hand[R].box.map((m0,L)=>((r-1)*z.hand[R].box[L]+m0)/r),k=e.hand[R].boxRaw.map((m0,L)=>((r-1)*z.hand[R].boxRaw[L]+m0)/r);z.hand[R].keypoints.length!==e.hand[R].keypoints.length&&(z.hand[R].keypoints=e.hand[R].keypoints);let $=e.hand[R].keypoints&&e.hand[R].keypoints.length>0?e.hand[R].keypoints.map((m0,L)=>m0.map((K,Ae)=>((r-1)*(z.hand[R].keypoints[L][Ae]||1)+(K||0))/r)):[],i0={};if(Object.keys(z.hand[R].annotations).length!==Object.keys(e.hand[R].annotations).length)z.hand[R].annotations=e.hand[R].annotations,i0=z.hand[R].annotations;else if(e.hand[R].annotations)for(let m0 of Object.keys(e.hand[R].annotations))i0[m0]=e.hand[R].annotations[m0]&&e.hand[R].annotations[m0][0]?e.hand[R].annotations[m0].map((L,K)=>L.map((Ae,se)=>((r-1)*z.hand[R].annotations[m0][K][se]+Ae)/r)):null;z.hand[R]={...e.hand[R],box:c0,boxRaw:k,keypoints:$,annotations:i0}}if(!z.face||e.face.length!==z.face.length)z.face=JSON.parse(JSON.stringify(e.face));else for(let R=0;R<e.face.length;R++){let c0=e.face[R].box.map(($,i0)=>((r-1)*z.face[R].box[i0]+$)/r),k=e.face[R].boxRaw.map(($,i0)=>((r-1)*z.face[R].boxRaw[i0]+$)/r);if(e.face[R].rotation){let $={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};$.matrix=(y=e.face[R].rotation)==null?void 0:y.matrix,$.angle={roll:((r-1)*(((u=(f=z.face[R].rotation)==null?void 0:f.angle)==null?void 0:u.roll)||0)+(((P=(m=e.face[R].rotation)==null?void 0:m.angle)==null?void 0:P.roll)||0))/r,yaw:((r-1)*(((b=(g=z.face[R].rotation)==null?void 0:g.angle)==null?void 0:b.yaw)||0)+(((M=(d=e.face[R].rotation)==null?void 0:d.angle)==null?void 0:M.yaw)||0))/r,pitch:((r-1)*(((w=(S=z.face[R].rotation)==null?void 0:S.angle)==null?void 0:w.pitch)||0)+(((C=(j=e.face[R].rotation)==null?void 0:j.angle)==null?void 0:C.pitch)||0))/r},$.gaze={bearing:((r-1)*(((H=(F=z.face[R].rotation)==null?void 0:F.gaze)==null?void 0:H.bearing)||0)+(((J=(Y=e.face[R].rotation)==null?void 0:Y.gaze)==null?void 0:J.bearing)||0))/r,strength:((r-1)*(((E=(x0=z.face[R].rotation)==null?void 0:x0.gaze)==null?void 0:E.strength)||0)+(((B0=(G0=e.face[R].rotation)==null?void 0:G0.gaze)==null?void 0:B0.strength)||0))/r},z.face[R]={...e.face[R],rotation:$,box:c0,boxRaw:k}}z.face[R]={...e.face[R],box:c0,boxRaw:k}}if(!z.object||e.object.length!==z.object.length)z.object=JSON.parse(JSON.stringify(e.object));else for(let R=0;R<e.object.length;R++){let c0=e.object[R].box.map(($,i0)=>((r-1)*z.object[R].box[i0]+$)/r),k=e.object[R].boxRaw.map(($,i0)=>((r-1)*z.object[R].boxRaw[i0]+$)/r);z.object[R]={...e.object[R],box:c0,boxRaw:k}}if(e.persons){let R=e.persons;if(!z.persons||R.length!==z.persons.length)z.persons=JSON.parse(JSON.stringify(R));else for(let c0=0;c0<R.length;c0++)z.persons[c0].box=R[c0].box.map((k,$)=>((r-1)*z.persons[c0].box[$]+k)/r)}e.gesture&&(z.gesture=e.gesture);let A=h();return rt=v.perfadd?rt+Math.round(A-o):Math.round(A-o),e.performance&&(z.performance={...e.performance,interpolate:rt}),z}var at={};ue(at,{distance:()=>I2,match:()=>st,similarity:()=>At});function I2(e,t,o={order:2,multiplier:25}){let n=0;for(let r=0;r<e.length;r++){let A=!o.order||o.order===2?e[r]-t[r]:Math.abs(e[r]-t[r]);n+=!o.order||o.order===2?A*A:A**o.order}return(o.multiplier||20)*n}var on=(e,t,o,n)=>{if(e===0)return 1;let r=t===2?Math.sqrt(e):e**(1/t),A=(1-r/100-o)/(n-o);return Math.max(Math.min(A,1),0)};function At(e,t,o={order:2,multiplier:25,min:.2,max:.8}){let n=I2(e,t,o);return on(n,o.order||2,o.min||0,o.max||1)}function st(e,t,o={order:2,multiplier:25,threshold:0,min:.2,max:.8}){if(!Array.isArray(e)||!Array.isArray(t)||e.length<64||t.length===0||e.length!==t[0].length)return{index:-1,distance:Number.POSITIVE_INFINITY,similarity:0};let n=Number.MAX_SAFE_INTEGER,r=-1;for(let s=0;s<t.length;s++){let a=I2(e,t[s],o);if(a<n&&(n=a,r=s),n<(o.threshold||0))break}let A=on(n,o.order||2,o.min||0,o.max||1);return{index:r,distance:n,similarity:A}}function nn(e,t,o,n,r){var a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w;let A=0,s=[];for(let j of e){let C={id:A++,face:j,body:null,hands:{left:null,right:null},gestures:[],box:[0,0,0,0]};for(let E of t)j.box[0]>E.box[0]&&j.box[0]<E.box[0]+E.box[2]&&j.box[1]+j.box[3]>E.box[1]&&j.box[1]+j.box[3]<E.box[1]+E.box[3]&&(C.body=E);if(C.body)for(let E of o)E.box[0]+E.box[2]>C.body.box[0]&&E.box[0]+E.box[2]<C.body.box[0]+C.body.box[2]&&E.box[1]+E.box[3]>C.body.box[1]&&E.box[1]+E.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.left=E),E.box[0]<C.body.box[0]+C.body.box[2]&&E.box[0]>C.body.box[0]&&E.box[1]+E.box[3]>C.body.box[1]&&E.box[1]+E.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.right=E);for(let E of n)E.face!==void 0&&E.face===j.id?(a=C.gestures)==null||a.push(E):E.iris!==void 0&&E.iris===j.id?(i=C.gestures)==null||i.push(E):E.body!==void 0&&E.body===((x=C.body)==null?void 0:x.id)?(c=C.gestures)==null||c.push(E):E.hand!==void 0&&E.hand===((y=(l=C.hands)==null?void 0:l.left)==null?void 0:y.id)?(f=C.gestures)==null||f.push(E):E.hand!==void 0&&E.hand===((m=(u=C.hands)==null?void 0:u.right)==null?void 0:m.id)&&((P=C.gestures)==null||P.push(E));let F=[],H=[],Y=E=>{E&&E.length===4&&(F.push(E[0],E[0]+E[2]),H.push(E[1],E[1]+E[3]))};Y((g=C.face)==null?void 0:g.box),Y((b=C.body)==null?void 0:b.box),Y((M=(d=C.hands)==null?void 0:d.left)==null?void 0:M.box),Y((w=(S=C.hands)==null?void 0:S.right)==null?void 0:w.box);let J=Math.min(...F),x0=Math.min(...H);C.box=[J,x0,Math.max(...F)-J,Math.max(...H)-x0],r&&r[1]&&r[2]&&(C.boxRaw=[C.box[0]/r[2],C.box[1]/r[1],C.box[2]/r[2],C.box[3]/r[1]]),s.push(C)}return s}var T5=`
 /9j/4AAQSkZJRgABAQEAYABgAAD/4QBoRXhpZgAATU0AKgAAAAgABAEaAAUAAAABAAAAPgEbAAUA
 AAABAAAARgEoAAMAAAABAAIAAAExAAIAAAARAAAATgAAAAAAAABgAAAAAQAAAGAAAAABcGFpbnQu
 bmV0IDQuMi4xMwAA/9sAQwAGBAUGBQQGBgUGBwcGCAoQCgoJCQoUDg8MEBcUGBgXFBYWGh0lHxob
@@ -827,4 +827,4 @@ AAAAAAJAAAAAAAAAAAAAABAJEAAAAAAAAAAAAAAAIEoBKAAAAAAAAAAAAAAABAlAAAAAAAIAAAAA
 BAkBAkBAkBAlACEgMZjdjbFW8bWrEx8YWANb6Fp+bfwab+vLDKMFK9qxH5L0bAr8OPRPKz2AY7J2
 SbAjYZAI2E7AIEgIEgIEgMdkSy2NgY7MdlmyNoBXsxmFuyNgVTVjNV3KjlBRNTlXTVHKCrlIqt5T
 lBhEMohlFerLlBjEMohMVTEARDKCITsAk2AEgAAAkAAAAAAAAAAAAAAAAAAAAAAAASAAAAAAAAD/
-2Q==`;var m0=Z(D());async function r7(e){let t=(r,A="application/octet-stream")=>fetch(`data:${A};base64,${r}`).then(s=>s.blob()),o,n;switch(e.config.warmup){case"face":o=await t(T5);break;case"body":case"full":o=await t(w5);break;default:o=null}if(o){let r=await createImageBitmap(o);n=await e.detect(r,e.config),r.close()}return n}async function A7(e){return new Promise(t=>{let o;switch(e.config.warmup){case"face":o="data:image/jpeg;base64,"+T5;break;case"full":case"body":o="data:image/jpeg;base64,"+w5;break;default:o=null}let n;if(typeof Image!="undefined")n=new Image;else if(v.Image)n=new v.Image;else return;n.onload=async()=>{let r=R0(n.naturalWidth,n.naturalHeight);if(!r)p("Warmup: Canvas not found"),t(void 0);else{let A=r.getContext("2d");A&&A.drawImage(n,0,0);let s=await e.image(r),a=await e.detect(s.tensor,e.config);t(a)}},o?n.src=o:t(void 0)})}async function s7(e){let t=r=>Buffer.from(r,"base64"),o;e.config.warmup==="face"?o=t(T5):o=t(w5);let n;if("node"in m0){let r=m0.node.decodeJpeg(o),A=r.expandDims(0);e.tf.dispose(r),n=await e.detect(A,e.config),e.tf.dispose(A)}else e.config.debug&&p("Warmup tfjs-node not loaded");return n}async function a7(e){let t;return typeof createImageBitmap=="function"?t=await r7(e):typeof Image!="undefined"||v.Canvas!==void 0?t=await A7(e):t=await s7(e),t}async function i7(e){let t=m0.getBackend(),o=m0.backend();if(t!=="webgl"&&t!=="humangl"||!o||!o.checkCompileCompletion)return;m0.env().set("ENGINE_COMPILE_ONLY",!0);let n=m0.engine().state.numTensors,r=[];for(let[a,i]of Object.entries(e).filter(([x,c])=>x!==null&&c!==null)){let x=i.inputs&&i.inputs[0]&&i.inputs[0].shape?[...i.inputs[0].shape]:[1,64,64,3],c=i.inputs&&i.inputs[0]&&i.inputs[0].dtype?i.inputs[0].dtype:"float32";for(let y=0;y<x.length;y++)x[y]===-1&&(x[y]=y===0?1:64);let l=m0.zeros(x,c);try{let y=i.execute(l);r.push(a),Array.isArray(y)?y.forEach(f=>m0.dispose(f)):m0.dispose(y)}catch(y){p("compile fail model:",a)}m0.dispose(l)}let A=await o.checkCompileCompletionAsync();o.getUniformLocations(),p("compile pass models:",r),p("compile pass kernels:",A.length),m0.env().set("ENGINE_COMPILE_ONLY",!1);let s=m0.engine().state.numTensors;s-n>0&&p("tensor leak:",s-n)}async function rn(e,t){let o=h();return e.state="warmup",t&&(e.config=r0(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?{face:[],body:[],hand:[],gesture:[],object:[],performance:e.performance,timestamp:h(),persons:[],error:null}:new Promise(async n=>{await i7(e.models);let r=await a7(e),A=h();e.config.debug&&p("warmup",e.config.warmup,Math.round(A-o),"ms"),e.emit("warmup"),n(r)})}var m2,I2,N2,k5,it=class{constructor(t){T(this,"version");T(this,"config");T(this,"result");T(this,"state");T(this,"process");T(this,"tf");T(this,"env");T(this,"draw");T(this,"models");T(this,"events");T(this,"faceTriangulation");T(this,"faceUVMap");T(this,"performance");g2(this,m2,void 0);g2(this,I2,void 0);g2(this,N2,void 0);T(this,"gl");T(this,"analyze",(...t)=>{if(!b2(this,I2))return;let o=this.tf.engine().state.numTensors,n=b2(this,m2);M2(this,m2,o);let r=o-n;r!==0&&p(...t,r)});g2(this,k5,t=>{if(!b2(this,N2))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof ee.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(o){return"backend not loaded"}return null});T(this,"similarity",At);T(this,"distance",j2);T(this,"match",st);T(this,"emit",t=>{var o;this.events&&this.events.dispatchEvent&&((o=this.events)==null||o.dispatchEvent(new Event(t)))});var n;this.env=v;let o=(((n=ee.version)==null?void 0:n.tfjs)||ee.version_core).replace(/-(.*)/,"");he.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${o}/dist/`,he.modelBasePath=v.browser?"../models/":"file://models/",he.backend=v.browser?"humangl":"tensorflow",this.version=O5,Object.defineProperty(this,"version",{value:O5}),this.config=JSON.parse(JSON.stringify(he)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=r0(this.config,t)),kt(this.config),this.tf=ee,this.state="idle",M2(this,m2,0),M2(this,I2,!1),M2(this,N2,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new C2,this.draw={options:P0,canvas:(r,A)=>$1(r,A),face:(r,A,s)=>l2(r,A,s),body:(r,A,s)=>y2(r,A,s),hand:(r,A,s)=>x2(r,A,s),gesture:(r,A,s)=>d2(r,A,s),object:(r,A,s)=>c2(r,A,s),person:(r,A,s)=>_1(r,A,s),all:(r,A,s)=>et(r,A,s)},this.result={face:[],body:[],hand:[],gesture:[],object:[],performance:{},timestamp:0,persons:[],error:null},this.process={tensor:null,canvas:null},this.faceTriangulation=B3,this.faceUVMap=H3,this.gl=t0,this.emit("create")}reset(){let t=this.config.backend;this.config=JSON.parse(JSON.stringify(he)),this.config.backend=t}validate(t){return E5(he,t||this.config)}now(){return h()}image(t,o=!0){return Ye(t,this.config,o)}async segmentation(t,o){return Do(t,o,this.config)}enhance(t){return u1(t)}compare(t,o){return wt(this.config,t,o)}async init(){await v5(this,!0),await this.tf.ready()}async load(t){this.state="load";let o=h(),n=Object.values(this.models).filter(s=>s).length;t&&(this.config=r0(this.config,t)),this.env.initial&&(this.config.debug&&p(`version: ${this.version}`),this.config.debug&&p(`tfjs version: ${this.tf.version["tfjs-core"]}`),await v5(this)||p("error: backend check failed"),await ee.ready(),this.env.browser&&(this.config.debug&&p("configuration:",this.config),this.config.debug&&p("environment:",this.env),this.config.debug&&p("tf flags:",this.tf.ENV.flags))),await U1(this),this.env.initial&&this.config.debug&&p("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.env.initial=!1,Object.values(this.models).filter(s=>s).length!==n&&(await Y1(this),this.emit("load"));let A=Math.trunc(h()-o);A>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+A:A)}next(t=this.result){return tn(t,this.config)}getModelStats(){return q1(this)}async warmup(t){let o=h(),n=await rn(this,t),r=h();return this.performance.warmup=Math.trunc(r-o),n}async profile(t,o){let n=await this.tf.profile(()=>this.detect(t,o)),r={};for(let a of n.kernels)r[a.name]?r[a.name]+=a.kernelTimeMs:r[a.name]=a.kernelTimeMs;let A=[];Object.entries(r).forEach(a=>A.push({name:a[0],ms:a[1]})),A.sort((a,i)=>i.ms-a.ms),A.length=20;let s={};for(let a of A)s[a.name]=a.ms;return s}async detect(t,o){return this.state="detect",new Promise(async n=>{var P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0,R,c0,k,$,a0;this.state="config";let r;this.config=r0(this.config,o),this.state="check";let A=b2(this,k5).call(this,t);A&&(p(A,t),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:h(),persons:[],error:A}));let s=h();await v5(this),await this.load(),r=h(),this.state="image";let a=await Ye(t,this.config);if(this.process=a,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(h()-r):Math.trunc(h()-r),this.analyze("Get Image:"),!a.tensor){this.config.debug&&p("could not convert input to tensor"),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:h(),persons:[],error:"could not convert input to tensor"});return}this.emit("image"),r=h(),this.config.skipAllowed=await Tt(this.config,a.tensor),this.performance.totalFrames||(this.performance.totalFrames=0),this.performance.cachedFrames||(this.performance.cachedFrames=0),this.performance.totalFrames++,this.config.skipAllowed&&this.performance.cachedFrames++,this.performance.cacheCheck=this.env.perfadd?(this.performance.cacheCheck||0)+Math.trunc(h()-r):Math.trunc(h()-r),this.analyze("Check Changed:");let i=[],x=[],c=[],l=[];this.state="detect:face",this.config.async?(i=this.config.face.enabled?nt(this,a.tensor):[],this.performance.face&&delete this.performance.face):(r=h(),i=this.config.face.enabled?await nt(this,a.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.config.async&&(this.config.body.maxDetected===-1||this.config.hand.maxDetected===-1)&&(i=await i),this.analyze("Start Body:"),this.state="detect:body";let y=this.config.body.maxDetected===-1?r0(this.config,{body:{maxDetected:this.config.face.enabled?1*i.length:1}}):this.config;this.config.async?((P=this.config.body.modelPath)!=null&&P.includes("posenet")?x=this.config.body.enabled?D1(a.tensor,y):[]:(g=this.config.body.modelPath)!=null&&g.includes("blazepose")?x=this.config.body.enabled?t1(a.tensor,y):[]:(b=this.config.body.modelPath)!=null&&b.includes("efficientpose")?x=this.config.body.enabled?i1(a.tensor,y):[]:(d=this.config.body.modelPath)!=null&&d.includes("movenet")&&(x=this.config.body.enabled?L1(a.tensor,y):[]),this.performance.body&&delete this.performance.body):(r=h(),(M=this.config.body.modelPath)!=null&&M.includes("posenet")?x=this.config.body.enabled?await D1(a.tensor,y):[]:(S=this.config.body.modelPath)!=null&&S.includes("blazepose")?x=this.config.body.enabled?await t1(a.tensor,y):[]:(w=this.config.body.modelPath)!=null&&w.includes("efficientpose")?x=this.config.body.enabled?await i1(a.tensor,y):[]:(j=this.config.body.modelPath)!=null&&j.includes("movenet")&&(x=this.config.body.enabled?await L1(a.tensor,y):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let f=this.config.hand.maxDetected===-1?r0(this.config,{hand:{maxDetected:this.config.face.enabled?2*i.length:1}}):this.config;this.config.async?((F=(C=this.config.hand.detector)==null?void 0:C.modelPath)!=null&&F.includes("handdetect")?c=this.config.hand.enabled?v1(a.tensor,f):[]:(Y=(H=this.config.hand.detector)==null?void 0:H.modelPath)!=null&&Y.includes("handtrack")&&(c=this.config.hand.enabled?E1(a.tensor,f):[]),this.performance.hand&&delete this.performance.hand):(r=h(),(x0=(J=this.config.hand.detector)==null?void 0:J.modelPath)!=null&&x0.includes("handdetect")?c=this.config.hand.enabled?await v1(a.tensor,f):[]:(G0=(E=this.config.hand.detector)==null?void 0:E.modelPath)!=null&&G0.includes("handtrack")&&(c=this.config.hand.enabled?await E1(a.tensor,f):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?((B0=this.config.object.modelPath)!=null&&B0.includes("nanodet")?l=this.config.object.enabled?F1(a.tensor,this.config):[]:(R=this.config.object.modelPath)!=null&&R.includes("centernet")&&(l=this.config.object.enabled?r1(a.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=h(),(c0=this.config.object.modelPath)!=null&&c0.includes("nanodet")?l=this.config.object.enabled?await F1(a.tensor,this.config):[]:(k=this.config.object.modelPath)!=null&&k.includes("centernet")&&(l=this.config.object.enabled?await r1(a.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([i,x,c,l]=await Promise.all([i,x,c,l])),this.state="detect:gesture";let u=[];this.config.gesture.enabled&&(r=h(),u=[..._o(i),...Qo(x),...en(c),...$o(i)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(h()-s):Math.trunc(h()-s);let m=((a0=($=this.process)==null?void 0:$.tensor)==null?void 0:a0.shape)||[];this.result={face:i,body:x,hand:c,gesture:u,object:l,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,get persons(){return nn(i,x,c,u,m)}},ee.dispose(a.tensor),this.emit("detect"),this.state="idle",n(this.result)})}};m2=new WeakMap,I2=new WeakMap,N2=new WeakMap,k5=new WeakMap;0&&(module.exports={Human,defaults,draw,env,match,models});
+2Q==`;var f0=Z(D());async function r7(e){let t=(r,A="application/octet-stream")=>fetch(`data:${A};base64,${r}`).then(s=>s.blob()),o,n;switch(e.config.warmup){case"face":o=await t(T5);break;case"body":case"full":o=await t(w5);break;default:o=null}if(o){let r=await createImageBitmap(o);n=await e.detect(r,e.config),r.close()}return n}async function A7(e){return new Promise(t=>{let o;switch(e.config.warmup){case"face":o="data:image/jpeg;base64,"+T5;break;case"full":case"body":o="data:image/jpeg;base64,"+w5;break;default:o=null}let n;if(typeof Image!="undefined")n=new Image;else if(v.Image)n=new v.Image;else return;n.onload=async()=>{let r=R0(n.naturalWidth,n.naturalHeight);if(!r)p("Warmup: Canvas not found"),t(void 0);else{let A=r.getContext("2d");A&&A.drawImage(n,0,0);let s=await e.image(r),a=await e.detect(s.tensor,e.config);t(a)}},o?n.src=o:t(void 0)})}async function s7(e){let t=r=>Buffer.from(r,"base64"),o;e.config.warmup==="face"?o=t(T5):o=t(w5);let n;if("node"in f0){let r=f0.node.decodeJpeg(o),A=r.expandDims(0);e.tf.dispose(r),n=await e.detect(A,e.config),e.tf.dispose(A)}else e.config.debug&&p("Warmup tfjs-node not loaded");return n}async function a7(e){let t;return typeof createImageBitmap=="function"?t=await r7(e):typeof Image!="undefined"||v.Canvas!==void 0?t=await A7(e):t=await s7(e),t}async function i7(e){if(!f0.env().flagRegistry.ENGINE_COMPILE_ONLY)return;let t=f0.getBackend(),o=f0.backend();if(t!=="webgl"&&t!=="humangl"||!o||!o.checkCompileCompletion)return;f0.env().set("ENGINE_COMPILE_ONLY",!0);let n=f0.engine().state.numTensors,r=[];for(let[a,i]of Object.entries(e).filter(([x,c])=>x!==null&&c!==null)){let x=i.inputs&&i.inputs[0]&&i.inputs[0].shape?[...i.inputs[0].shape]:[1,64,64,3],c=i.inputs&&i.inputs[0]&&i.inputs[0].dtype?i.inputs[0].dtype:"float32";for(let y=0;y<x.length;y++)x[y]===-1&&(x[y]=y===0?1:64);let l=f0.zeros(x,c);try{let y=i.execute(l);r.push(a),Array.isArray(y)?y.forEach(f=>f0.dispose(f)):f0.dispose(y)}catch(y){p("compile fail model:",a)}f0.dispose(l)}let A=await o.checkCompileCompletionAsync();o.getUniformLocations(),p("compile pass models:",r),p("compile pass kernels:",A.length),f0.env().set("ENGINE_COMPILE_ONLY",!1);let s=f0.engine().state.numTensors;s-n>0&&p("tensor leak:",s-n)}async function rn(e,t){let o=h();return e.state="warmup",t&&(e.config=r0(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?{face:[],body:[],hand:[],gesture:[],object:[],performance:e.performance,timestamp:h(),persons:[],error:null}:new Promise(async n=>{await i7(e.models);let r=await a7(e),A=h();e.config.debug&&p("warmup",e.config.warmup,Math.round(A-o),"ms"),e.emit("warmup"),n(r)})}var m2,j2,O2,k5,it=class{constructor(t){T(this,"version");T(this,"config");T(this,"result");T(this,"state");T(this,"process");T(this,"tf");T(this,"env");T(this,"draw");T(this,"models");T(this,"events");T(this,"faceTriangulation");T(this,"faceUVMap");T(this,"performance");g2(this,m2,void 0);g2(this,j2,void 0);g2(this,O2,void 0);T(this,"gl");T(this,"analyze",(...t)=>{if(!b2(this,j2))return;let o=this.tf.engine().state.numTensors,n=b2(this,m2);M2(this,m2,o);let r=o-n;r!==0&&p(...t,r)});g2(this,k5,t=>{if(!b2(this,O2))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof ee.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(o){return"backend not loaded"}return null});T(this,"similarity",At);T(this,"distance",I2);T(this,"match",st);T(this,"emit",t=>{var o;this.events&&this.events.dispatchEvent&&((o=this.events)==null||o.dispatchEvent(new Event(t)))});var n;this.env=v;let o=(((n=ee.version)==null?void 0:n.tfjs)||ee.version_core).replace(/-(.*)/,"");he.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${o}/dist/`,he.modelBasePath=v.browser?"../models/":"file://models/",he.backend=v.browser?"humangl":"tensorflow",this.version=N5,Object.defineProperty(this,"version",{value:N5}),this.config=JSON.parse(JSON.stringify(he)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=r0(this.config,t)),kt(this.config),this.tf=ee,this.state="idle",M2(this,m2,0),M2(this,j2,!1),M2(this,O2,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new C2,this.draw={options:P0,canvas:(r,A)=>$1(r,A),face:(r,A,s)=>l2(r,A,s),body:(r,A,s)=>y2(r,A,s),hand:(r,A,s)=>x2(r,A,s),gesture:(r,A,s)=>d2(r,A,s),object:(r,A,s)=>c2(r,A,s),person:(r,A,s)=>_1(r,A,s),all:(r,A,s)=>et(r,A,s)},this.result={face:[],body:[],hand:[],gesture:[],object:[],performance:{},timestamp:0,persons:[],error:null},this.process={tensor:null,canvas:null},this.faceTriangulation=B3,this.faceUVMap=H3,this.gl=t0,this.emit("create")}reset(){let t=this.config.backend;this.config=JSON.parse(JSON.stringify(he)),this.config.backend=t}validate(t){return E5(he,t||this.config)}now(){return h()}image(t,o=!0){return Ye(t,this.config,o)}async segmentation(t,o){return Do(t,o,this.config)}enhance(t){return u1(t)}compare(t,o){return wt(this.config,t,o)}async init(){await v5(this,!0),await this.tf.ready()}async load(t){this.state="load";let o=h(),n=Object.values(this.models).filter(s=>s).length;t&&(this.config=r0(this.config,t)),this.env.initial&&(this.config.debug&&p(`version: ${this.version}`),this.config.debug&&p(`tfjs version: ${this.tf.version["tfjs-core"]}`),await v5(this)||p("error: backend check failed"),await ee.ready(),this.env.browser&&(this.config.debug&&p("configuration:",this.config),this.config.debug&&p("environment:",this.env),this.config.debug&&p("tf flags:",this.tf.ENV.flags))),await U1(this),this.env.initial&&this.config.debug&&p("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.env.initial=!1,Object.values(this.models).filter(s=>s).length!==n&&(await Y1(this),this.emit("load"));let A=Math.trunc(h()-o);A>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+A:A)}next(t=this.result){return tn(t,this.config)}getModelStats(){return q1(this)}async warmup(t){let o=h(),n=await rn(this,t),r=h();return this.performance.warmup=Math.trunc(r-o),n}async profile(t,o){let n=await this.tf.profile(()=>this.detect(t,o)),r={},A=0;for(let a of n.kernels)r[a.name]?r[a.name]+=a.kernelTimeMs:r[a.name]=a.kernelTimeMs,A+=a.kernelTimeMs;let s=[];Object.entries(r).forEach(a=>s.push({kernel:a[0],time:a[1],perc:0}));for(let a of s)a.perc=Math.round(1e3*a.time/A)/1e3,a.time=Math.round(1e3*a.time)/1e3;return s.sort((a,i)=>i.time-a.time),s.length=20,s}async detect(t,o){return this.state="detect",new Promise(async n=>{var P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0,R,c0,k,$,i0;this.state="config";let r;this.config=r0(this.config,o),this.state="check";let A=b2(this,k5).call(this,t);A&&(p(A,t),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:h(),persons:[],error:A}));let s=h();await v5(this),await this.load(),r=h(),this.state="image";let a=await Ye(t,this.config);if(this.process=a,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(h()-r):Math.trunc(h()-r),this.analyze("Get Image:"),!a.tensor){this.config.debug&&p("could not convert input to tensor"),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:h(),persons:[],error:"could not convert input to tensor"});return}this.emit("image"),r=h(),this.config.skipAllowed=await Tt(this.config,a.tensor),this.performance.totalFrames||(this.performance.totalFrames=0),this.performance.cachedFrames||(this.performance.cachedFrames=0),this.performance.totalFrames++,this.config.skipAllowed&&this.performance.cachedFrames++,this.performance.cacheCheck=this.env.perfadd?(this.performance.cacheCheck||0)+Math.trunc(h()-r):Math.trunc(h()-r),this.analyze("Check Changed:");let i=[],x=[],c=[],l=[];this.state="detect:face",this.config.async?(i=this.config.face.enabled?nt(this,a.tensor):[],this.performance.face&&delete this.performance.face):(r=h(),i=this.config.face.enabled?await nt(this,a.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.config.async&&(this.config.body.maxDetected===-1||this.config.hand.maxDetected===-1)&&(i=await i),this.analyze("Start Body:"),this.state="detect:body";let y=this.config.body.maxDetected===-1?r0(this.config,{body:{maxDetected:this.config.face.enabled?1*i.length:1}}):this.config;this.config.async?((P=this.config.body.modelPath)!=null&&P.includes("posenet")?x=this.config.body.enabled?D1(a.tensor,y):[]:(g=this.config.body.modelPath)!=null&&g.includes("blazepose")?x=this.config.body.enabled?t1(a.tensor,y):[]:(b=this.config.body.modelPath)!=null&&b.includes("efficientpose")?x=this.config.body.enabled?i1(a.tensor,y):[]:(d=this.config.body.modelPath)!=null&&d.includes("movenet")&&(x=this.config.body.enabled?L1(a.tensor,y):[]),this.performance.body&&delete this.performance.body):(r=h(),(M=this.config.body.modelPath)!=null&&M.includes("posenet")?x=this.config.body.enabled?await D1(a.tensor,y):[]:(S=this.config.body.modelPath)!=null&&S.includes("blazepose")?x=this.config.body.enabled?await t1(a.tensor,y):[]:(w=this.config.body.modelPath)!=null&&w.includes("efficientpose")?x=this.config.body.enabled?await i1(a.tensor,y):[]:(j=this.config.body.modelPath)!=null&&j.includes("movenet")&&(x=this.config.body.enabled?await L1(a.tensor,y):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let f=this.config.hand.maxDetected===-1?r0(this.config,{hand:{maxDetected:this.config.face.enabled?2*i.length:1}}):this.config;this.config.async?((F=(C=this.config.hand.detector)==null?void 0:C.modelPath)!=null&&F.includes("handdetect")?c=this.config.hand.enabled?v1(a.tensor,f):[]:(Y=(H=this.config.hand.detector)==null?void 0:H.modelPath)!=null&&Y.includes("handtrack")&&(c=this.config.hand.enabled?E1(a.tensor,f):[]),this.performance.hand&&delete this.performance.hand):(r=h(),(x0=(J=this.config.hand.detector)==null?void 0:J.modelPath)!=null&&x0.includes("handdetect")?c=this.config.hand.enabled?await v1(a.tensor,f):[]:(G0=(E=this.config.hand.detector)==null?void 0:E.modelPath)!=null&&G0.includes("handtrack")&&(c=this.config.hand.enabled?await E1(a.tensor,f):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?((B0=this.config.object.modelPath)!=null&&B0.includes("nanodet")?l=this.config.object.enabled?F1(a.tensor,this.config):[]:(R=this.config.object.modelPath)!=null&&R.includes("centernet")&&(l=this.config.object.enabled?r1(a.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=h(),(c0=this.config.object.modelPath)!=null&&c0.includes("nanodet")?l=this.config.object.enabled?await F1(a.tensor,this.config):[]:(k=this.config.object.modelPath)!=null&&k.includes("centernet")&&(l=this.config.object.enabled?await r1(a.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([i,x,c,l]=await Promise.all([i,x,c,l])),this.state="detect:gesture";let u=[];this.config.gesture.enabled&&(r=h(),u=[..._o(i),...Qo(x),...en(c),...$o(i)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(h()-s):Math.trunc(h()-s);let m=((i0=($=this.process)==null?void 0:$.tensor)==null?void 0:i0.shape)||[];this.result={face:i,body:x,hand:c,gesture:u,object:l,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,get persons(){return nn(i,x,c,u,m)}},ee.dispose(a.tensor),this.emit("detect"),this.state="idle",n(this.result)})}};m2=new WeakMap,j2=new WeakMap,O2=new WeakMap,k5=new WeakMap;0&&(module.exports={Human,defaults,draw,env,match,models});
diff --git a/dist/human.node-wasm.d.ts b/dist/human.node-wasm.d.ts
index 4f1e9723..925302ef 100644
--- a/dist/human.node-wasm.d.ts
+++ b/dist/human.node-wasm.d.ts
@@ -1330,7 +1330,11 @@ declare class Human {
      * - result object will contain total exeuction time information for top-20 kernels
      * - actual detection object can be accessed via `human.result`
      */
-    profile(input: Input, userConfig?: Partial<Config>): Promise<Record<string, number>>;
+    profile(input: Input, userConfig?: Partial<Config>): Promise<Array<{
+        kernel: string;
+        time: number;
+        perc: number;
+    }>>;
     /** Main detection method
      * - Analyze configuration: {@link Config}
      * - Pre-process input: {@link Input}
diff --git a/dist/human.node-wasm.js b/dist/human.node-wasm.js
index 3be0ea15..cf70c518 100644
--- a/dist/human.node-wasm.js
+++ b/dist/human.node-wasm.js
@@ -4,7 +4,7 @@
   author: <https://github.com/vladmandic>'
 */
 
-var sn=Object.create;var h2=Object.defineProperty;var an=Object.getOwnPropertyDescriptor;var ln=Object.getOwnPropertyNames;var yn=Object.getPrototypeOf,xn=Object.prototype.hasOwnProperty;var cn=(e,t,o)=>t in e?h2(e,t,{enumerable:!0,configurable:!0,writable:!0,value:o}):e[t]=o;var dn=(e,t)=>()=>(t||e((t={exports:{}}).exports,t),t.exports),ue=(e,t)=>{for(var o in t)h2(e,o,{get:t[o],enumerable:!0})},ft=(e,t,o,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of ln(t))!xn.call(e,r)&&r!==o&&h2(e,r,{get:()=>t[r],enumerable:!(n=an(t,r))||n.enumerable});return e};var Z=(e,t,o)=>(o=e!=null?sn(yn(e)):{},ft(t||!e||!e.__esModule?h2(o,"default",{value:e,enumerable:!0}):o,e)),fn=e=>ft(h2({},"__esModule",{value:!0}),e);var T=(e,t,o)=>(cn(e,typeof t!="symbol"?t+"":t,o),o),mt=(e,t,o)=>{if(!t.has(e))throw TypeError("Cannot "+o)};var b2=(e,t,o)=>(mt(e,t,"read from private field"),o?o.call(e):t.get(e)),g2=(e,t,o)=>{if(t.has(e))throw TypeError("Cannot add the same private member more than once");t instanceof WeakSet?t.add(e):t.set(e,o)},M2=(e,t,o,n)=>(mt(e,t,"write to private field"),n?n.call(e,o):t.set(e,o),o);var D=dn((f7,O2)=>{"use strict";var ut=Object.defineProperty,mn=Object.getOwnPropertyDescriptor,pn=Object.getOwnPropertyNames,un=Object.prototype.hasOwnProperty,S5=(e,t,o,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of pn(t))!un.call(e,r)&&r!==o&&ut(e,r,{get:()=>t[r],enumerable:!(n=mn(t,r))||n.enumerable});return e},ht=(e,t,o)=>(S5(e,t,"default"),o&&S5(o,t,"default")),hn=e=>S5(ut({},"__esModule",{value:!0}),e),C5={};O2.exports=hn(C5);ht(C5,require("@tensorflow/tfjs"),O2.exports);ht(C5,require("@tensorflow/tfjs-backend-wasm"),O2.exports)});var y7={};ue(y7,{Human:()=>lt,default:()=>lt,defaults:()=>he,draw:()=>ot,env:()=>v,match:()=>it,models:()=>v5});module.exports=fn(y7);function p(...e){let t=new Date,o=`${t.getHours().toString().padStart(2,"0")}:${t.getMinutes().toString().padStart(2,"0")}:${t.getSeconds().toString().padStart(2,"0")}.${t.getMilliseconds().toString().padStart(3,"0")}`;e&&console.log(o,"Human:",...e)}function pt(e,t){let o=e.endsWith("/")?"":"/",r=t.startsWith(".")||t.startsWith("/")||t.startsWith("http:")||t.startsWith("https:")||t.startsWith("file:")?`${t}`:`${e}${o}${t}`;if(!r.toLocaleLowerCase().includes(".json"))throw new Error(`modelpath error: expecting json file: ${r}`);return r}var h=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function z5(e,t,o="config",n=[]){for(let r of Object.keys(t))if(typeof t[r]=="object")z5(e[r],t[r],r,n);else{let A=e&&typeof e[r]!="undefined";A||n.push({reason:"unknown property",where:`${o}.${r} = ${t[r]}`});let s=e&&typeof e[r]==typeof t[r];A&&!s&&n.push({reason:"property type mismatch",where:`${o}.${r} = ${t[r]}`,expected:typeof e[r]})}return t.debug&&o==="config"&&n.length>0&&p("invalid configuration",n),n}function r0(...e){let t=o=>o&&typeof o=="object";return e.reduce((o,n)=>(Object.keys(n||{}).forEach(r=>{let A=o[r],s=n[r];Array.isArray(A)&&Array.isArray(s)?o[r]=A.concat(...s):t(A)&&t(s)?o[r]=r0(A,s):o[r]=s}),o),{})}var he={backend:"",modelBasePath:"",cacheModels:!0,wasmPath:"",wasmPlatformFetch:!1,debug:!1,async:!0,warmup:"full",cacheSensitivity:.7,skipAllowed:!1,deallocate:!1,filter:{enabled:!0,equalization:!1,width:0,height:0,flip:!1,return:!0,brightness:0,contrast:0,sharpness:0,blur:0,saturation:0,hue:0,negative:!1,sepia:!1,vintage:!1,kodachrome:!1,technicolor:!1,polaroid:!1,pixelate:0},gesture:{enabled:!0},face:{enabled:!0,detector:{modelPath:"blazeface.json",rotation:!0,maxDetected:1,skipFrames:99,skipTime:2500,minConfidence:.2,iouThreshold:.1,mask:!1,return:!1},mesh:{enabled:!0,modelPath:"facemesh.json",keepInvalid:!1},attention:{enabled:!1,modelPath:"facemesh-attention.json"},iris:{enabled:!0,modelPath:"iris.json"},emotion:{enabled:!0,minConfidence:.1,skipFrames:99,skipTime:1500,modelPath:"emotion.json"},description:{enabled:!0,modelPath:"faceres.json",skipFrames:99,skipTime:3e3,minConfidence:.1},antispoof:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"antispoof.json"},liveness:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"liveness.json"}},body:{enabled:!0,modelPath:"movenet-lightning.json",maxDetected:-1,minConfidence:.3,skipFrames:1,skipTime:200},hand:{enabled:!0,rotation:!0,skipFrames:99,skipTime:1e3,minConfidence:.5,iouThreshold:.2,maxDetected:-1,landmarks:!0,detector:{modelPath:"handtrack.json"},skeleton:{modelPath:"handlandmark-full.json"}},object:{enabled:!1,modelPath:"mb3-centernet.json",minConfidence:.2,iouThreshold:.4,maxDetected:10,skipFrames:99,skipTime:2e3},segmentation:{enabled:!1,modelPath:"selfie.json",blur:8}};var p0=Z(D());var N=Z(D());var bt=`
+var sn=Object.create;var h2=Object.defineProperty;var an=Object.getOwnPropertyDescriptor;var ln=Object.getOwnPropertyNames;var yn=Object.getPrototypeOf,xn=Object.prototype.hasOwnProperty;var cn=(e,t,o)=>t in e?h2(e,t,{enumerable:!0,configurable:!0,writable:!0,value:o}):e[t]=o;var dn=(e,t)=>()=>(t||e((t={exports:{}}).exports,t),t.exports),ue=(e,t)=>{for(var o in t)h2(e,o,{get:t[o],enumerable:!0})},ft=(e,t,o,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of ln(t))!xn.call(e,r)&&r!==o&&h2(e,r,{get:()=>t[r],enumerable:!(n=an(t,r))||n.enumerable});return e};var Z=(e,t,o)=>(o=e!=null?sn(yn(e)):{},ft(t||!e||!e.__esModule?h2(o,"default",{value:e,enumerable:!0}):o,e)),fn=e=>ft(h2({},"__esModule",{value:!0}),e);var T=(e,t,o)=>(cn(e,typeof t!="symbol"?t+"":t,o),o),mt=(e,t,o)=>{if(!t.has(e))throw TypeError("Cannot "+o)};var b2=(e,t,o)=>(mt(e,t,"read from private field"),o?o.call(e):t.get(e)),g2=(e,t,o)=>{if(t.has(e))throw TypeError("Cannot add the same private member more than once");t instanceof WeakSet?t.add(e):t.set(e,o)},M2=(e,t,o,n)=>(mt(e,t,"write to private field"),n?n.call(e,o):t.set(e,o),o);var D=dn((f7,N2)=>{"use strict";var ut=Object.defineProperty,mn=Object.getOwnPropertyDescriptor,pn=Object.getOwnPropertyNames,un=Object.prototype.hasOwnProperty,S5=(e,t,o,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of pn(t))!un.call(e,r)&&r!==o&&ut(e,r,{get:()=>t[r],enumerable:!(n=mn(t,r))||n.enumerable});return e},ht=(e,t,o)=>(S5(e,t,"default"),o&&S5(o,t,"default")),hn=e=>S5(ut({},"__esModule",{value:!0}),e),C5={};N2.exports=hn(C5);ht(C5,require("@tensorflow/tfjs"),N2.exports);ht(C5,require("@tensorflow/tfjs-backend-wasm"),N2.exports)});var y7={};ue(y7,{Human:()=>lt,default:()=>lt,defaults:()=>he,draw:()=>ot,env:()=>v,match:()=>it,models:()=>v5});module.exports=fn(y7);function p(...e){let t=new Date,o=`${t.getHours().toString().padStart(2,"0")}:${t.getMinutes().toString().padStart(2,"0")}:${t.getSeconds().toString().padStart(2,"0")}.${t.getMilliseconds().toString().padStart(3,"0")}`;e&&console.log(o,"Human:",...e)}function pt(e,t){let o=e.endsWith("/")?"":"/",r=t.startsWith(".")||t.startsWith("/")||t.startsWith("http:")||t.startsWith("https:")||t.startsWith("file:")?`${t}`:`${e}${o}${t}`;if(!r.toLocaleLowerCase().includes(".json"))throw new Error(`modelpath error: expecting json file: ${r}`);return r}var h=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function z5(e,t,o="config",n=[]){for(let r of Object.keys(t))if(typeof t[r]=="object")z5(e[r],t[r],r,n);else{let A=e&&typeof e[r]!="undefined";A||n.push({reason:"unknown property",where:`${o}.${r} = ${t[r]}`});let s=e&&typeof e[r]==typeof t[r];A&&!s&&n.push({reason:"property type mismatch",where:`${o}.${r} = ${t[r]}`,expected:typeof e[r]})}return t.debug&&o==="config"&&n.length>0&&p("invalid configuration",n),n}function r0(...e){let t=o=>o&&typeof o=="object";return e.reduce((o,n)=>(Object.keys(n||{}).forEach(r=>{let A=o[r],s=n[r];Array.isArray(A)&&Array.isArray(s)?o[r]=A.concat(...s):t(A)&&t(s)?o[r]=r0(A,s):o[r]=s}),o),{})}var he={backend:"",modelBasePath:"",cacheModels:!0,wasmPath:"",wasmPlatformFetch:!1,debug:!1,async:!0,warmup:"full",cacheSensitivity:.7,skipAllowed:!1,deallocate:!1,filter:{enabled:!0,equalization:!1,width:0,height:0,flip:!1,return:!0,brightness:0,contrast:0,sharpness:0,blur:0,saturation:0,hue:0,negative:!1,sepia:!1,vintage:!1,kodachrome:!1,technicolor:!1,polaroid:!1,pixelate:0},gesture:{enabled:!0},face:{enabled:!0,detector:{modelPath:"blazeface.json",rotation:!0,maxDetected:1,skipFrames:99,skipTime:2500,minConfidence:.2,iouThreshold:.1,mask:!1,return:!1},mesh:{enabled:!0,modelPath:"facemesh.json",keepInvalid:!1},attention:{enabled:!1,modelPath:"facemesh-attention.json"},iris:{enabled:!0,modelPath:"iris.json"},emotion:{enabled:!0,minConfidence:.1,skipFrames:99,skipTime:1500,modelPath:"emotion.json"},description:{enabled:!0,modelPath:"faceres.json",skipFrames:99,skipTime:3e3,minConfidence:.1},antispoof:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"antispoof.json"},liveness:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"liveness.json"}},body:{enabled:!0,modelPath:"movenet-lightning.json",maxDetected:-1,minConfidence:.3,skipFrames:1,skipTime:200},hand:{enabled:!0,rotation:!0,skipFrames:99,skipTime:1e3,minConfidence:.5,iouThreshold:.2,maxDetected:-1,landmarks:!0,detector:{modelPath:"handtrack.json"},skeleton:{modelPath:"handlandmark-full.json"}},object:{enabled:!1,modelPath:"mb3-centernet.json",minConfidence:.2,iouThreshold:.4,maxDetected:10,skipFrames:99,skipTime:2e3},segmentation:{enabled:!1,modelPath:"selfie.json",blur:8}};var p0=Z(D());var O=Z(D());var bt=`
   precision highp float;
   attribute vec2 pos;
   attribute vec2 uv;
@@ -96,7 +96,7 @@ var sn=Object.create;var h2=Object.defineProperty;var an=Object.getOwnPropertyDe
     c31 * m[6] + c32 * m[7] + c33 * m[8];
     gl_FragColor.a = c22.a;
   }
-`;var j5=(e,t,o)=>{let n=new RegExp("\\b"+t+" \\w+ (\\w+)","ig");e.replace(n,(r,A)=>(o[A]=0,r))},I5=class{constructor(t,o,n){T(this,"uniform",{});T(this,"attribute",{});T(this,"gl");T(this,"id");T(this,"compile",(t,o)=>{let n=this.gl.createShader(o);return n?(this.gl.shaderSource(n,t),this.gl.compileShader(n),this.gl.getShaderParameter(n,this.gl.COMPILE_STATUS)?n:(p(`filter: gl compile failed: ${this.gl.getShaderInfoLog(n)}`),null)):(p("filter: could not create shader"),null)});this.gl=t;let r=this.compile(o,this.gl.VERTEX_SHADER),A=this.compile(n,this.gl.FRAGMENT_SHADER);if(this.id=this.gl.createProgram(),!(!r||!A)){if(!this.id){p("filter: could not create webgl program");return}if(this.gl.attachShader(this.id,r),this.gl.attachShader(this.id,A),this.gl.linkProgram(this.id),!this.gl.getProgramParameter(this.id,this.gl.LINK_STATUS)){p(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);return}this.gl.useProgram(this.id),j5(o,"attribute",this.attribute);for(let s in this.attribute)this.attribute[s]=this.gl.getAttribLocation(this.id,s);j5(o,"uniform",this.uniform),j5(n,"uniform",this.uniform);for(let s in this.uniform)this.uniform[s]=this.gl.getUniformLocation(this.id,s)}}};function Tt(){let e=0,t=null,o=!1,n=-1,r=[null,null],A=[],s=null,a=null,i=R0(100,100),x={},c={INTERMEDIATE:1},l=i.getContext("webgl");if(!l){p("filter: cannot get webgl context");return}this.gl=l;function y(b,d){if(!(b===i.width&&d===i.height)){if(i.width=b,i.height=d,!s){let M=new Float32Array([-1,-1,0,1,1,-1,1,1,-1,1,0,0,-1,1,0,0,1,-1,1,1,1,1,1,0]);s=l.createBuffer(),l.bindBuffer(l.ARRAY_BUFFER,s),l.bufferData(l.ARRAY_BUFFER,M,l.STATIC_DRAW),l.pixelStorei(l.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}l.viewport(0,0,i.width,i.height),r=[null,null]}}function f(b,d){let M=l.createFramebuffer();l.bindFramebuffer(l.FRAMEBUFFER,M);let S=l.createRenderbuffer();l.bindRenderbuffer(l.RENDERBUFFER,S);let w=l.createTexture();return l.bindTexture(l.TEXTURE_2D,w),l.texImage2D(l.TEXTURE_2D,0,l.RGBA,b,d,0,l.RGBA,l.UNSIGNED_BYTE,null),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MAG_FILTER,l.LINEAR),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MIN_FILTER,l.LINEAR),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_S,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_T,l.CLAMP_TO_EDGE),l.framebufferTexture2D(l.FRAMEBUFFER,l.COLOR_ATTACHMENT0,l.TEXTURE_2D,w,0),l.bindTexture(l.TEXTURE_2D,null),l.bindFramebuffer(l.FRAMEBUFFER,null),{fbo:M,texture:w}}function u(b){return r[b]=r[b]||f(i.width,i.height),r[b]}function m(b=0){if(!a)return;let d=null,M=null,S=!1;e===0?d=t:d=u(n).texture||null,e++,o&&!(b&c.INTERMEDIATE)?(M=null,S=e%2===0):(n=(n+1)%2,M=u(n).fbo||null),l.bindTexture(l.TEXTURE_2D,d),l.bindFramebuffer(l.FRAMEBUFFER,M),l.uniform1f(a.uniform.flipY,S?-1:1),l.drawArrays(l.TRIANGLES,0,6)}function P(b){if(x[b])return a=x[b],l.useProgram((a?a.id:null)||null),a;if(a=new I5(l,bt,b),!a)return p("filter: could not get webgl program"),null;let d=Float32Array.BYTES_PER_ELEMENT,M=4*d;return l.enableVertexAttribArray(a.attribute.pos),l.vertexAttribPointer(a.attribute.pos,2,l.FLOAT,!1,M,0*d),l.enableVertexAttribArray(a.attribute.uv),l.vertexAttribPointer(a.attribute.uv,2,l.FLOAT,!1,M,2*d),x[b]=a,a}let g={colorMatrix:b=>{let d=new Float32Array(b);d[4]/=255,d[9]/=255,d[14]/=255,d[19]/=255;let M=d[18]===1&&d[3]===0&&d[8]===0&&d[13]===0&&d[15]===0&&d[16]===0&&d[17]===0&&d[19]===0?Mt:gt,S=P(M);!S||(l.uniform1fv(S.uniform.m,d),m())},brightness:b=>{let d=(b||0)+1;g.colorMatrix([d,0,0,0,0,0,d,0,0,0,0,0,d,0,0,0,0,0,1,0])},saturation:b=>{let d=(b||0)*2/3+1,M=(d-1)*-.5;g.colorMatrix([d,M,M,0,0,M,d,M,0,0,M,M,d,0,0,0,0,0,1,0])},desaturate:()=>{g.saturation(-1)},contrast:b=>{let d=(b||0)+1,M=-128*(d-1);g.colorMatrix([d,0,0,0,M,0,d,0,0,M,0,0,d,0,M,0,0,0,1,0])},negative:()=>{g.contrast(-2)},hue:b=>{b=(b||0)/180*Math.PI;let d=Math.cos(b),M=Math.sin(b),S=.213,w=.715,j=.072;g.colorMatrix([S+d*(1-S)+M*-S,w+d*-w+M*-w,j+d*-j+M*(1-j),0,0,S+d*-S+M*.143,w+d*(1-w)+M*.14,j+d*-j+M*-.283,0,0,S+d*-S+M*-(1-S),w+d*-w+M*w,j+d*(1-j)+M*j,0,0,0,0,0,1,0])},desaturateLuminance:()=>{g.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},sepia:()=>{g.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},brownie:()=>{g.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},vintagePinhole:()=>{g.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},kodachrome:()=>{g.colorMatrix([1.1285582396593525,-.3967382283601348,-.03992559172921793,0,63.72958762196502,-.16404339962244616,1.0835251566291304,-.05498805115633132,0,24.732407896706203,-.16786010706155763,-.5603416277695248,1.6014850761964943,0,35.62982807460946,0,0,0,1,0])},technicolor:()=>{g.colorMatrix([1.9125277891456083,-.8545344976951645,-.09155508482755585,0,11.793603434377337,-.3087833385928097,1.7658908555458428,-.10601743074722245,0,-70.35205161461398,-.231103377548616,-.7501899197440212,1.847597816108189,0,30.950940869491138,0,0,0,1,0])},polaroid:()=>{g.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},shiftToBGR:()=>{g.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},convolution:b=>{let d=new Float32Array(b),M=1/i.width,S=1/i.height,w=P(vt);!w||(l.uniform1fv(w.uniform.m,d),l.uniform2f(w.uniform.px,M,S),m())},detectEdges:()=>{g.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},sobelX:()=>{g.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},sobelY:()=>{g.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},sharpen:b=>{let d=b||1;g.convolution.call(this,[0,-1*d,0,-1*d,1+4*d,-1*d,0,-1*d,0])},emboss:b=>{let d=b||1;g.convolution.call(this,[-2*d,-1*d,0,-1*d,1,1*d,0,1*d,2*d])},blur:b=>{let d=b/7/i.width,M=b/7/i.height,S=P(Rt);!S||(l.uniform2f(S.uniform.px,0,M),m(c.INTERMEDIATE),l.uniform2f(S.uniform.px,d,0),m())},pixelate:b=>{let d=b/i.width,M=b/i.height,S=P(Pt);!S||(l.uniform2f(S.uniform.size,d,M),m())}};this.add=function(b){let d=Array.prototype.slice.call(arguments,1),M=g[b];A.push({func:M,args:d})},this.reset=function(){A=[]},this.get=function(){return A},this.apply=function(b){y(b.width,b.height),e=0,t||(t=l.createTexture()),l.bindTexture(l.TEXTURE_2D,t),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_S,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_T,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MIN_FILTER,l.NEAREST),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MAG_FILTER,l.NEAREST),l.texImage2D(l.TEXTURE_2D,0,l.RGBA,l.RGBA,l.UNSIGNED_BYTE,b);for(let d=0;d<A.length;d++){o=d===A.length-1;let M=A[d];M.func.apply(this,M.args||[])}return i},this.draw=function(b){return this.add("brightness",0),this.apply(b)}}var X=Z(D());async function L2(e){let t=e.shape.length===4?X.squeeze(e):e,o=X.split(t,3,2),n=[X.min(o[0]),X.min(o[1]),X.min(o[2])],r=[X.max(o[0]),X.max(o[1]),X.max(o[2])],A=await Promise.all(r.map(f=>f.data())),s=.99*Math.max(A[0][0],A[1][0],A[2][0]),a=[X.sub(o[0],n[0]),X.sub(o[1],n[1]),X.sub(o[2],n[2])],i=[X.sub(r[0],n[0]),X.sub(r[1],n[1]),X.sub(r[2],n[2])],x=[X.div(s,i[0]),X.div(s,i[1]),X.div(s,i[2])],c=[X.mul(a[0],x[0]),X.mul(a[1],x[1]),X.mul(a[2],x[2])],l=X.stack([c[0],c[1],c[2]],2),y=X.reshape(l,[1,t.shape[0],t.shape[1],3]);return X.dispose([...o,...n,...r,...a,...i,...x,...c,l,t]),y}var W2=3840,q=null,i0=null,Ue=null,e0,ae={inputSum:0,cacheDiff:1,sumMethod:0,inputTensor:void 0};function R0(e,t){let o;if(v.browser)if(v.worker){if(typeof OffscreenCanvas=="undefined")throw new Error("canvas error: attempted to run in web worker but OffscreenCanvas is not supported");o=new OffscreenCanvas(e,t)}else{if(typeof document=="undefined")throw new Error("canvas error: attempted to run in browser but DOM is not defined");o=document.createElement("canvas"),o.width=e,o.height=t}else typeof v.Canvas!="undefined"?o=new v.Canvas(e,t):typeof globalThis.Canvas!="undefined"&&(o=new globalThis.Canvas(e,t));return o}function F2(e,t){let o=t||R0(e.width,e.height);return o.getContext("2d").drawImage(e,0,0),o}async function Ye(e,t,o=!0){if(!e)return t.debug&&p("input error: input is missing"),{tensor:null,canvas:null};if(!(e instanceof N.Tensor)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(typeof v.Canvas!="undefined"&&e instanceof v.Canvas)&&!(typeof globalThis.Canvas!="undefined"&&e instanceof globalThis.Canvas)&&!(typeof ImageData!="undefined"&&e instanceof ImageData)&&!(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)&&!(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)&&!(typeof HTMLMediaElement!="undefined"&&e instanceof HTMLMediaElement)&&!(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)&&!(typeof HTMLCanvasElement!="undefined"&&e instanceof HTMLCanvasElement)&&!(typeof OffscreenCanvas!="undefined"&&e instanceof OffscreenCanvas))throw new Error("input error: type is not recognized");if(e instanceof N.Tensor){let n=null;if(e.isDisposedInternal)throw new Error("input error: attempted to use tensor but it is disposed");if(!e.shape)throw new Error("input error: attempted to use tensor without a shape");if(e.shape.length===3){if(e.shape[2]===3)n=N.expandDims(e,0);else if(e.shape[2]===4){let r=N.slice3d(e,[0,0,0],[-1,-1,3]);n=N.expandDims(r,0),N.dispose(r)}}else e.shape.length===4&&(e.shape[3]===3?n=N.clone(e):e.shape[3]===4&&(n=N.slice4d(e,[0,0,0,0],[-1,-1,-1,3])));if(n==null||n.shape.length!==4||n.shape[0]!==1||n.shape[3]!==3)throw new Error(`input error: attempted to use tensor with unrecognized shape: ${e.shape}`);if(n.dtype==="int32"){let r=N.cast(n,"float32");N.dispose(n),n=r}return{tensor:n,canvas:t.filter.return?i0:null}}else{if(typeof e.readyState!="undefined"&&e.readyState<=2)return t.debug&&p("input stream is not ready"),{tensor:null,canvas:q};let n=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,r=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0;if(!n||!r)return t.debug&&p("cannot determine input dimensions"),{tensor:null,canvas:q};let A=n,s=r;if(A>W2&&(A=W2,s=Math.trunc(A*r/n)),s>W2&&(s=W2,A=Math.trunc(s*n/r)),(t.filter.width||0)>0?A=t.filter.width:(t.filter.height||0)>0&&(A=n*((t.filter.height||0)/r)),(t.filter.height||0)>0?s=t.filter.height:(t.filter.width||0)>0&&(s=r*((t.filter.width||0)/n)),!A||!s)throw new Error("input error: cannot determine dimension");(!q||(q==null?void 0:q.width)!==A||(q==null?void 0:q.height)!==s)&&(q=R0(A,s));let a=q.getContext("2d");if(typeof ImageData!="undefined"&&e instanceof ImageData?a.putImageData(e,0,0):t.filter.flip&&typeof a.translate!="undefined"?(a.translate(n,0),a.scale(-1,1),a.drawImage(e,0,0,n,r,0,0,q==null?void 0:q.width,q==null?void 0:q.height),a.setTransform(1,0,0,1,0,0)):a.drawImage(e,0,0,n,r,0,0,q==null?void 0:q.width,q==null?void 0:q.height),(!i0||q.width!==i0.width||(q==null?void 0:q.height)!==(i0==null?void 0:i0.height))&&(i0=R0(q.width,q.height)),t.filter.enabled&&v.webgl.supported?(e0||(e0=v.browser?new Tt:null),v.filter=!!e0,!e0||!e0.add?(t.debug&&p("input process error: cannot initialize filters"),v.webgl.supported=!1,t.filter.enabled=!1,F2(q,i0)):(e0.reset(),t.filter.brightness!==0&&e0.add("brightness",t.filter.brightness),t.filter.contrast!==0&&e0.add("contrast",t.filter.contrast),t.filter.sharpness!==0&&e0.add("sharpen",t.filter.sharpness),t.filter.blur!==0&&e0.add("blur",t.filter.blur),t.filter.saturation!==0&&e0.add("saturation",t.filter.saturation),t.filter.hue!==0&&e0.add("hue",t.filter.hue),t.filter.negative&&e0.add("negative"),t.filter.sepia&&e0.add("sepia"),t.filter.vintage&&e0.add("brownie"),t.filter.sepia&&e0.add("sepia"),t.filter.kodachrome&&e0.add("kodachrome"),t.filter.technicolor&&e0.add("technicolor"),t.filter.polaroid&&e0.add("polaroid"),t.filter.pixelate!==0&&e0.add("pixelate",t.filter.pixelate),e0.get()>0?i0=e0.apply(q):i0=e0.draw(q))):(F2(q,i0),e0&&(e0=null),v.filter=!!e0),!o)return{tensor:null,canvas:i0};if(!i0)throw new Error("canvas error: cannot create output");let i,x=3;if(typeof ImageData!="undefined"&&e instanceof ImageData||e.data&&e.width&&e.height)if(v.browser&&N.browser)i=N.browser?N.browser.fromPixels(e):null;else{x=e.data.length/e.height/e.width;let y=new Uint8Array(e.data.buffer);i=N.tensor(y,[e.height,e.width,x],"int32")}else if((!Ue||i0.width!==Ue.width||i0.height!==Ue.height)&&(Ue=R0(i0.width,i0.height)),N.browser&&v.browser)t.backend==="webgl"||t.backend==="humangl"||t.backend==="webgpu"?i=N.browser.fromPixels(i0):(Ue=F2(i0),i=N.browser.fromPixels(Ue));else{let u=F2(i0).getContext("2d").getImageData(0,0,A,s);x=u.data.length/A/s;let m=new Uint8Array(u.data.buffer);i=N.tensor(m,[A,s,x])}if(x===4){let y=N.slice3d(i,[0,0,0],[-1,-1,3]);N.dispose(i),i=y}if(!i)throw new Error("input error: cannot create tensor");let c=N.cast(i,"float32"),l=t.filter.equalization?await L2(c):N.expandDims(c,0);return N.dispose([i,c]),{tensor:l,canvas:t.filter.return?i0:null}}}async function wt(e,t){let o=!1;if(e.cacheSensitivity===0||!t.shape||t.shape.length!==4||t.shape[1]>2048||t.shape[2]>2048)return o;if(!ae.inputTensor)ae.inputTensor=N.clone(t);else if(ae.inputTensor.shape[1]!==t.shape[1]||ae.inputTensor.shape[2]!==t.shape[2])N.dispose(ae.inputTensor),ae.inputTensor=N.clone(t);else{let n={};n.diff=N.sub(t,ae.inputTensor),n.squared=N.mul(n.diff,n.diff),n.sum=N.sum(n.squared);let A=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;N.dispose([ae.inputTensor,n.diff,n.squared,n.sum]),ae.inputTensor=N.clone(t),o=A<=(e.cacheSensitivity||0)}return o}async function kt(e,t,o){let n={};if(!t||!o||t.shape.length!==4||t.shape.length!==o.shape.length)return e.debug||p("invalid input tensor or tensor shapes do not match:",t.shape,o.shape),0;if(t.shape[0]!==1||o.shape[0]!==1||t.shape[3]!==3||o.shape[3]!==3)return e.debug||p("input tensors must be of shape [1, height, width, 3]:",t.shape,o.shape),0;n.input1=N.clone(t),n.input2=t.shape[1]!==o.shape[1]||t.shape[2]!==o.shape[2]?N.image.resizeBilinear(o,[t.shape[1],t.shape[2]]):N.clone(o),n.diff=N.sub(n.input1,n.input2),n.squared=N.mul(n.diff,n.diff),n.sum=N.sum(n.squared);let A=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;return N.dispose([n.input1,n.input2,n.diff,n.squared,n.sum]),A}var N5=class{constructor(){T(this,"browser");T(this,"node");T(this,"worker");T(this,"platform","");T(this,"agent","");T(this,"backends",[]);T(this,"initial");T(this,"filter");T(this,"tfjs");T(this,"offscreen");T(this,"perfadd",!1);T(this,"wasm",{supported:void 0,backend:void 0,simd:void 0,multithread:void 0});T(this,"webgl",{supported:void 0,backend:void 0,version:void 0,renderer:void 0});T(this,"webgpu",{supported:void 0,backend:void 0,adapter:void 0});T(this,"cpu",{model:void 0,flags:[]});T(this,"kernels",[]);T(this,"Canvas");T(this,"Image");T(this,"ImageData");if(this.browser=typeof navigator!="undefined",this.node=typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined",this.tfjs={version:p0.version["tfjs-core"]},this.offscreen=typeof OffscreenCanvas!="undefined",this.initial=!0,this.worker=this.browser&&this.offscreen?typeof WorkerGlobalScope!="undefined":void 0,typeof navigator!="undefined"){let t=navigator.userAgent.match(/\(([^()]+)\)/g);if(t&&t[0]){let o=t[0].match(/\(([^()]+)\)/g);this.platform=o&&o[0]?o[0].replace(/\(|\)/g,""):"",this.agent=navigator.userAgent.replace(t[0],""),this.platform[1]&&(this.agent=this.agent.replace(t[1],"")),this.agent=this.agent.replace(/  /g," ")}}else typeof process!="undefined"&&(this.platform=`${process.platform} ${process.arch}`,this.agent=`NodeJS ${process.version}`)}async updateBackend(){this.backends=Object.keys(p0.engine().registryFactory),this.wasm.supported=typeof WebAssembly!="undefined",this.wasm.backend=this.backends.includes("wasm"),this.wasm.supported&&this.wasm.backend&&p0.getBackend()==="wasm"&&(this.wasm.simd=await p0.env().getAsync("WASM_HAS_SIMD_SUPPORT"),this.wasm.multithread=await p0.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT"));let t=R0(100,100),o=t?t.getContext("webgl2"):void 0;if(this.webgl.supported=typeof o!="undefined",this.webgl.backend=this.backends.includes("webgl"),this.webgl.supported&&this.webgl.backend&&(p0.getBackend()==="webgl"||p0.getBackend()==="humangl")){let n=p0.backend().gpgpu!=="undefined"?await p0.backend().getGPGPUContext().gl:null;n&&(this.webgl.version=n.getParameter(n.VERSION),this.webgl.renderer=n.getParameter(n.RENDERER))}this.webgpu.supported=this.browser&&typeof navigator.gpu!="undefined",this.webgpu.backend=this.backends.includes("webgpu");try{this.webgpu.supported&&(this.webgpu.adapter=(await navigator.gpu.requestAdapter()).name)}catch(n){this.webgpu.supported=!1}try{this.kernels=p0.getKernelsForBackend(p0.getBackend()).map(n=>n.kernelName.toLowerCase())}catch(n){}}async updateCPU(){let t={model:"",flags:[]};this.node&&this.platform.startsWith("linux"),this.cpu?this.cpu=t:Object.defineProperty(this,"cpu",{value:t})}},v=new N5;var G2=Z(D());var O5={};ue(O5,{age:()=>Pn,antispoof:()=>Rn,blazeface:()=>wn,"blazeface-back":()=>vn,"blazeface-front":()=>Tn,"blazepose-detector2d":()=>kn,"blazepose-detector3d":()=>En,"blazepose-full":()=>zn,"blazepose-heavy":()=>Sn,"blazepose-lite":()=>Cn,default:()=>yr,efficientpose:()=>jn,emotion:()=>In,faceboxes:()=>Nn,facemesh:()=>Bn,"facemesh-attention":()=>Ln,"facemesh-attention-alt":()=>On,"facemesh-detection-full":()=>Wn,"facemesh-detection-short":()=>Fn,"facemesh-orig":()=>Gn,faceres:()=>Vn,"faceres-deep":()=>Hn,gear:()=>Dn,gender:()=>Xn,"gender-ssrnet-imdb":()=>Zn,handdetect:()=>qn,"handlandmark-full":()=>Un,"handlandmark-lite":()=>Yn,"handlandmark-sparse":()=>Kn,handskeleton:()=>Jn,handtrack:()=>Qn,iris:()=>_n,liveness:()=>$n,"mb3-centernet":()=>er,meet:()=>tr,mobileface:()=>or,mobilefacenet:()=>nr,"movenet-lightning":()=>rr,"movenet-multipose":()=>Ar,"movenet-thunder":()=>sr,nanodet:()=>ar,posenet:()=>ir,selfie:()=>lr});var Pn=161240,Rn=853098,vn=538928,Tn=402048,wn=538928,kn=7499400,En=5928856,zn=6338290,Sn=27501554,Cn=2725490,jn=5651240,In=820516,Nn=2013002,On=2387598,Ln=2382414,Wn=1026192,Fn=201268,Gn=2955780,Bn=1477958,Hn=13957620,Vn=6978814,Dn=1498916,Zn=161236,Xn=201808,qn=3515612,Un=5431368,Yn=2023432,Kn=5286322,Jn=5502280,Qn=2964837,_n=2599092,$n=592976,er=4030290,tr=372228,or=2183192,nr=5171976,rr=4650216,Ar=9448838,sr=12477112,ar=7574558,ir=5032780,lr=212886,yr={age:Pn,antispoof:Rn,"blazeface-back":vn,"blazeface-front":Tn,blazeface:wn,"blazepose-detector2d":kn,"blazepose-detector3d":En,"blazepose-full":zn,"blazepose-heavy":Sn,"blazepose-lite":Cn,efficientpose:jn,emotion:In,faceboxes:Nn,"facemesh-attention-alt":On,"facemesh-attention":Ln,"facemesh-detection-full":Wn,"facemesh-detection-short":Fn,"facemesh-orig":Gn,facemesh:Bn,"faceres-deep":Hn,faceres:Vn,gear:Dn,"gender-ssrnet-imdb":Zn,gender:Xn,handdetect:qn,"handlandmark-full":Un,"handlandmark-lite":Yn,"handlandmark-sparse":Kn,handskeleton:Jn,handtrack:Qn,iris:_n,liveness:$n,"mb3-centernet":er,meet:tr,mobileface:or,mobilefacenet:nr,"movenet-lightning":rr,"movenet-multipose":Ar,"movenet-thunder":sr,nanodet:ar,posenet:ir,selfie:lr};var v0={cacheModels:!0,cacheSupported:!0,verbose:!0,debug:!1,modelBasePath:""},q0={};async function xr(e,t){return v0.debug&&p("load model fetch:",e,t),fetch(e,t)}function Et(e){v0.cacheModels=e.cacheModels,v0.verbose=e.debug,v0.modelBasePath=e.modelBasePath}async function G(e){var x,c,l;let t=pt(v0.modelBasePath,e||"");t.toLowerCase().endsWith(".json")||(t+=".json");let o=t.includes("/")?t.split("/"):t.split("\\"),n=o[o.length-1].replace(".json",""),r="indexeddb://"+n;q0[n]={name:n,sizeFromManifest:0,sizeLoadedWeights:0,sizeDesired:O5[n],inCache:!1},v0.cacheSupported=typeof window!="undefined"&&typeof window.localStorage!="undefined"&&typeof window.indexedDB!="undefined";let A={};try{A=v0.cacheSupported&&v0.cacheModels?await G2.io.listModels():{}}catch(y){v0.cacheSupported=!1}q0[n].inCache=v0.cacheSupported&&v0.cacheModels&&Object.keys(A).includes(r);let s=typeof fetch=="undefined"?{}:{fetchFunc:(y,f)=>xr(y,f)},a=new G2.GraphModel(q0[n].inCache?r:t,s),i=!1;try{a.findIOHandler(),v0.debug&&p("model load handler:",a.handler);let y=await a.handler.load();q0[n].sizeFromManifest=((x=y==null?void 0:y.weightData)==null?void 0:x.byteLength)||0,a.loadSync(y),q0[n].sizeLoadedWeights=((l=(c=a==null?void 0:a.artifacts)==null?void 0:c.weightData)==null?void 0:l.byteLength)||0,v0.verbose&&p("load model:",a.modelUrl,{bytes:q0[n].sizeLoadedWeights},v0),i=!0}catch(y){p("error loading model:",t,y)}if(i&&v0.cacheModels&&v0.cacheSupported&&!q0[n].inCache)try{let y=await a.save(r);p("model saved:",r,y)}catch(y){p("error saving model:",t,y)}return a}var ee=Z(D());var L5="2.9.1";var y0=Z(D());var v5={};ue(v5,{Models:()=>C2,getModelStats:()=>U1,load:()=>Y1,reset:()=>R5,validate:()=>K1});var B2=Z(D());var D0,W5=[],fr=["white","black","asian","indian","other"],mr=[15,23,28,35.5,45.5,55.5,65],zt=0,St=0,F5=Number.MAX_SAFE_INTEGER;async function Ct(e){var t;return v.initial&&(D0=null),D0?e.debug&&p("cached model:",D0.modelUrl):D0=await G((t=e.face.gear)==null?void 0:t.modelPath),D0}async function G5(e,t,o,n){var s,a;if(!D0)return{age:0,gender:"unknown",genderScore:0,race:[]};let r=F5<(((s=t.face.gear)==null?void 0:s.skipFrames)||0),A=(((a=t.face.gear)==null?void 0:a.skipTime)||0)>h()-St;return t.skipAllowed&&A&&r&&zt===n&&W5[o]?(F5++,W5[o]):(F5=0,new Promise(async i=>{var g,b;if(!(D0!=null&&D0.inputs[0].shape))return;let x={},c=[[0,.1,.9,.9]];x.resize=B2.image.cropAndResize(e,c,[0],[D0.inputs[0].shape[2],D0.inputs[0].shape[1]]);let l={age:0,gender:"unknown",genderScore:0,race:[]};(g=t.face.gear)!=null&&g.enabled&&([x.age,x.gender,x.race]=D0.execute(x.resize,["age_output","gender_output","race_output"]));let y=await x.gender.data();l.gender=y[0]>y[1]?"male":"female",l.genderScore=Math.round(100*(y[0]>y[1]?y[0]:y[1]))/100;let f=await x.race.data();for(let d=0;d<f.length;d++)f[d]>(((b=t.face.gear)==null?void 0:b.minConfidence)||.2)&&l.race.push({score:Math.round(100*f[d])/100,race:fr[d]});l.race.sort((d,M)=>M.score-d.score);let m=Array.from(await x.age.data()).map((d,M)=>[mr[M],d]).sort((d,M)=>M[1]-d[1]),P=m[0][0];for(let d=1;d<m.length;d++)P+=m[d][1]*(m[d][0]-P);l.age=Math.round(10*P)/10,Object.keys(x).forEach(d=>B2.dispose(x[d])),W5[o]=l,zt=n,St=h(),i(l)}))}var Ke=Z(D());var be=Z(D()),V={tf255:255,tf1:1,tf2:2,tf05:.5,tf127:127.5,rgb:[.2989,.587,.114]};function It(){V.tf255=be.scalar(255,"float32"),V.tf1=be.scalar(1,"float32"),V.tf2=be.scalar(2,"float32"),V.tf05=be.scalar(.5,"float32"),V.tf127=be.scalar(127.5,"float32"),V.rgb=be.tensor1d([.2989,.587,.114],"float32")}var S0,H2=[],Nt=0,Ot=0,B5=Number.MAX_SAFE_INTEGER;async function Lt(e){return v.initial&&(S0=null),S0?e.debug&&p("cached model:",S0.modelUrl):S0=await G(e.face.ssrnet.modelPathAge),S0}async function H5(e,t,o,n){var s,a,i,x;if(!S0)return{age:0};let r=B5<(((s=t.face.ssrnet)==null?void 0:s.skipFrames)||0),A=(((a=t.face.ssrnet)==null?void 0:a.skipTime)||0)>h()-Ot;return t.skipAllowed&&r&&A&&Nt===n&&((i=H2[o])==null?void 0:i.age)&&((x=H2[o])==null?void 0:x.age)>0?(B5++,H2[o]):(B5=0,new Promise(async c=>{if(!(S0!=null&&S0.inputs)||!S0.inputs[0]||!S0.inputs[0].shape)return;let l={};l.resize=Ke.image.resizeBilinear(e,[S0.inputs[0].shape[2],S0.inputs[0].shape[1]],!1),l.enhance=Ke.mul(l.resize,V.tf255);let y={age:0};if(t.face.ssrnet.enabled&&(l.age=S0.execute(l.enhance)),l.age){let f=await l.age.data();y.age=Math.trunc(10*f[0])/10}Object.keys(l).forEach(f=>Ke.dispose(l[f])),H2[o]=y,Nt=n,Ot=h(),c(y)}))}var u0=Z(D());var Z0,V2=[],Ft=0,Gt=0,V5=Number.MAX_SAFE_INTEGER,D5=[.2989,.587,.114];async function Bt(e){return v.initial&&(Z0=null),Z0?e.debug&&p("cached model:",Z0.modelUrl):Z0=await G(e.face.ssrnet.modelPathGender),Z0}async function Z5(e,t,o,n){var s,a,i,x;if(!Z0)return{gender:"unknown",genderScore:0};let r=V5<(((s=t.face.ssrnet)==null?void 0:s.skipFrames)||0),A=(((a=t.face.ssrnet)==null?void 0:a.skipTime)||0)>h()-Gt;return t.skipAllowed&&r&&A&&Ft===n&&((i=V2[o])==null?void 0:i.gender)&&((x=V2[o])==null?void 0:x.genderScore)>0?(V5++,V2[o]):(V5=0,new Promise(async c=>{if(!(Z0!=null&&Z0.inputs[0].shape))return;let l={};l.resize=u0.image.resizeBilinear(e,[Z0.inputs[0].shape[2],Z0.inputs[0].shape[1]],!1),l.enhance=u0.tidy(()=>{let[u,m,P]=u0.split(l.resize,3,3),g=u0.mul(u,D5[0]),b=u0.mul(m,D5[1]),d=u0.mul(P,D5[2]),M=u0.addN([g,b,d]);return u0.mul(u0.sub(M,V.tf05),2)});let y={gender:"unknown",genderScore:0};t.face.ssrnet.enabled&&(l.gender=Z0.execute(l.enhance));let f=await l.gender.data();y.gender=f[0]>f[1]?"female":"male",y.genderScore=f[0]>f[1]?Math.trunc(100*f[0])/100:Math.trunc(100*f[1])/100,Object.keys(l).forEach(u=>u0.dispose(l[u])),V2[o]=y,Ft=n,Gt=h(),c(y)}))}var Z2=Z(D());var h0,D2=[],X5=Number.MAX_SAFE_INTEGER,Vt=0,Dt=0;async function Zt(e){var t;return v.initial&&(h0=null),h0?e.debug&&p("cached model:",h0.modelUrl):h0=await G((t=e.face.antispoof)==null?void 0:t.modelPath),h0}async function q5(e,t,o,n){var s,a;if(!h0)return 0;let r=(((s=t.face.antispoof)==null?void 0:s.skipTime)||0)>h()-Dt,A=X5<(((a=t.face.antispoof)==null?void 0:a.skipFrames)||0);return t.skipAllowed&&r&&A&&Vt===n&&D2[o]?(X5++,D2[o]):(X5=0,new Promise(async i=>{let x=Z2.image.resizeBilinear(e,[h0!=null&&h0.inputs[0].shape?h0.inputs[0].shape[2]:0,h0!=null&&h0.inputs[0].shape?h0.inputs[0].shape[1]:0],!1),c=h0==null?void 0:h0.execute(x),l=(await c.data())[0];D2[o]=Math.round(100*l)/100,Vt=n,Dt=h(),Z2.dispose([x,c]),i(D2[o])}))}var O=Z(D());var ie=Z(D());var X0={silhouette:[10,338,297,332,284,251,389,356,454,323,361,288,397,365,379,378,400,377,152,148,176,149,150,136,172,58,132,93,234,127,162,21,54,103,67,109],lipsUpperOuter:[185,40,39,37,0,267,269,270,409],lipsLowerOuter:[61,146,91,181,84,17,314,405,321,375,291],lipsUpperInner:[191,80,81,82,13,312,311,310,415],lipsLowerInner:[78,95,88,178,87,14,317,402,318,324,308],lipsLowerSemiOuter:[76,77,90,180,85,16,315,404,320,307,306],lipsUpperSemiOuter:[184,74,73,72,11,302,303,304,408],lipsLowerSemiInner:[62,96,89,179,86,15,316,403,319,325,292],lipsUpperSemiInner:[183,42,41,38,12,268,271,272,407],rightEyeUpper0:[246,161,160,159,158,157,173],rightEyeLower0:[33,7,163,144,145,153,154,155,133],rightEyeUpper1:[247,30,29,27,28,56,190],rightEyeLower1:[130,25,110,24,23,22,26,112,243],rightEyeUpper2:[113,225,224,223,222,221,189],rightEyeLower2:[226,31,228,229,230,231,232,233,244],rightEyeLower3:[143,111,117,118,119,120,121,128,245],rightEyebrowUpper:[156,70,63,105,66,107,55,193],rightEyebrowLower:[35,124,46,53,52,65],rightEyeIris:[473,474,475,476,477],leftEyeUpper0:[466,388,387,386,385,384,398],leftEyeLower0:[263,249,390,373,374,380,381,382,362],leftEyeUpper1:[467,260,259,257,258,286,414],leftEyeLower1:[359,255,339,254,253,252,256,341,463],leftEyeUpper2:[342,445,444,443,442,441,413],leftEyeLower2:[446,261,448,449,450,451,452,453,464],leftEyeLower3:[372,340,346,347,348,349,350,357,465],leftEyebrowUpper:[383,300,293,334,296,336,285,417],leftEyebrowLower:[265,353,276,283,282,295],leftEyeIris:[468,469,470,471,472],midwayBetweenEyes:[168],noseTip:[1],noseBottom:[2],noseRightCorner:[98],noseLeftCorner:[327],rightCheek:[205],leftCheek:[425]},U5={count:468,mouth:13,symmetryLine:[13,X0.midwayBetweenEyes[0]]},Ie={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Y5=[{key:"EyeUpper0",indices:[9,10,11,12,13,14,15]},{key:"EyeUpper1",indices:[25,26,27,28,29,30,31]},{key:"EyeUpper2",indices:[41,42,43,44,45,46,47]},{key:"EyeLower0",indices:[0,1,2,3,4,5,6,7,8]},{key:"EyeLower1",indices:[16,17,18,19,20,21,22,23,24]},{key:"EyeLower2",indices:[32,33,34,35,36,37,38,39,40]},{key:"EyeLower3",indices:[54,55,56,57,58,59,60,61,62]},{key:"EyebrowUpper",indices:[63,64,65,66,67,68,69,70]},{key:"EyebrowLower",indices:[48,49,50,51,52,53]}],R2=[[.499976992607117,.652534008026123],[.500025987625122,.547487020492554],[.499974012374878,.602371990680695],[.482113003730774,.471979022026062],[.500150978565216,.527155995368958],[.499909996986389,.498252987861633],[.499523013830185,.40106201171875],[.289712011814117,.380764007568359],[.499954998493195,.312398016452789],[.499987006187439,.269918978214264],[.500023007392883,.107050001621246],[.500023007392883,.666234016418457],[.5000159740448,.679224014282227],[.500023007392883,.692348003387451],[.499976992607117,.695277988910675],[.499976992607117,.70593398809433],[.499976992607117,.719385027885437],[.499976992607117,.737019002437592],[.499967992305756,.781370997428894],[.499816000461578,.562981009483337],[.473773002624512,.573909997940063],[.104906998574734,.254140973091125],[.365929991006851,.409575998783112],[.338757991790771,.41302502155304],[.311120003461838,.409460008144379],[.274657994508743,.389131009578705],[.393361985683441,.403706014156342],[.345234006643295,.344011008739471],[.370094001293182,.346076011657715],[.319321990013123,.347265005111694],[.297903001308441,.353591024875641],[.24779200553894,.410809993743896],[.396889001131058,.842755019664764],[.280097991228104,.375599980354309],[.106310002505779,.399955987930298],[.2099249958992,.391353011131287],[.355807989835739,.534406006336212],[.471751004457474,.65040397644043],[.474155008792877,.680191993713379],[.439785003662109,.657229006290436],[.414617002010345,.66654098033905],[.450374007225037,.680860996246338],[.428770989179611,.682690978050232],[.374971002340317,.727805018424988],[.486716985702515,.547628998756409],[.485300987958908,.527395009994507],[.257764995098114,.314490020275116],[.401223003864288,.455172002315521],[.429818987846375,.548614978790283],[.421351999044418,.533740997314453],[.276895999908447,.532056987285614],[.483370006084442,.499586999416351],[.33721199631691,.282882988452911],[.296391993761063,.293242990970612],[.169294998049736,.193813979625702],[.447580009698868,.302609980106354],[.392390012741089,.353887975215912],[.354490011930466,.696784019470215],[.067304998636246,.730105042457581],[.442739009857178,.572826027870178],[.457098007202148,.584792017936707],[.381974011659622,.694710969924927],[.392388999462128,.694203019142151],[.277076005935669,.271932005882263],[.422551989555359,.563233017921448],[.385919004678726,.281364023685455],[.383103013038635,.255840003490448],[.331431001424789,.119714021682739],[.229923993349075,.232002973556519],[.364500999450684,.189113974571228],[.229622006416321,.299540996551514],[.173287004232407,.278747975826263],[.472878992557526,.666198015213013],[.446828007698059,.668527007102966],[.422762006521225,.673889994621277],[.445307999849319,.580065965652466],[.388103008270264,.693961024284363],[.403039008378983,.706539988517761],[.403629004955292,.693953037261963],[.460041999816895,.557139039039612],[.431158006191254,.692366003990173],[.452181994915009,.692366003990173],[.475387006998062,.692366003990173],[.465828001499176,.779190003871918],[.472328990697861,.736225962638855],[.473087012767792,.717857003211975],[.473122000694275,.704625964164734],[.473033010959625,.695277988910675],[.427942007780075,.695277988910675],[.426479011774063,.703539967536926],[.423162013292313,.711845993995667],[.4183090031147,.720062971115112],[.390094995498657,.639572978019714],[.013953999616206,.560034036636353],[.499913990497589,.58014702796936],[.413199990987778,.69539999961853],[.409626007080078,.701822996139526],[.468080013990402,.601534962654114],[.422728985548019,.585985004901886],[.463079988956451,.593783974647522],[.37211999297142,.47341400384903],[.334562003612518,.496073007583618],[.411671012639999,.546965003013611],[.242175996303558,.14767599105835],[.290776997804642,.201445996761322],[.327338010072708,.256527006626129],[.399509996175766,.748921036720276],[.441727995872498,.261676013469696],[.429764986038208,.187834024429321],[.412198007106781,.108901023864746],[.288955003023148,.398952007293701],[.218936994671822,.435410976409912],[.41278201341629,.398970007896423],[.257135003805161,.355440020561218],[.427684992551804,.437960982322693],[.448339998722076,.536936044692993],[.178560003638268,.45755398273468],[.247308000922203,.457193970680237],[.286267012357712,.467674970626831],[.332827985286713,.460712015628815],[.368755996227264,.447206974029541],[.398963987827301,.432654976844788],[.476410001516342,.405806005001068],[.189241006970406,.523923993110657],[.228962004184723,.348950982093811],[.490725994110107,.562400996685028],[.404670000076294,.485132992267609],[.019469000399113,.401564002037048],[.426243007183075,.420431017875671],[.396993011236191,.548797011375427],[.266469985246658,.376977026462555],[.439121007919312,.51895797252655],[.032313998788595,.644356966018677],[.419054001569748,.387154996395111],[.462783008813858,.505746960639954],[.238978996872902,.779744982719421],[.198220998048782,.831938028335571],[.107550002634525,.540755033493042],[.183610007166862,.740257024765015],[.134409993886948,.333683013916016],[.385764002799988,.883153975009918],[.490967005491257,.579378008842468],[.382384985685349,.508572995662689],[.174399003386497,.397670984268188],[.318785011768341,.39623498916626],[.343364000320435,.400596976280212],[.396100014448166,.710216999053955],[.187885001301765,.588537991046906],[.430987000465393,.944064974784851],[.318993002176285,.898285031318665],[.266247987747192,.869701027870178],[.500023007392883,.190576016902924],[.499976992607117,.954452991485596],[.366169989109039,.398822009563446],[.393207013607025,.39553701877594],[.410373002290726,.391080021858215],[.194993004202843,.342101991176605],[.388664990663528,.362284004688263],[.365961998701096,.355970978736877],[.343364000320435,.355356991291046],[.318785011768341,.35834002494812],[.301414996385574,.363156020641327],[.058132998645306,.319076001644135],[.301414996385574,.387449026107788],[.499987989664078,.618434011936188],[.415838003158569,.624195992946625],[.445681989192963,.566076993942261],[.465844005346298,.620640993118286],[.49992299079895,.351523995399475],[.288718998432159,.819945991039276],[.335278987884521,.852819979190826],[.440512001514435,.902418971061707],[.128294005990028,.791940987110138],[.408771991729736,.373893976211548],[.455606997013092,.451801002025604],[.499877005815506,.908990025520325],[.375436991453171,.924192011356354],[.11421000212431,.615022003650665],[.448662012815475,.695277988910675],[.4480200111866,.704632043838501],[.447111994028091,.715808033943176],[.444831997156143,.730794012546539],[.430011987686157,.766808986663818],[.406787008047104,.685672998428345],[.400738000869751,.681069016456604],[.392399996519089,.677703022956848],[.367855995893478,.663918972015381],[.247923001646996,.601333022117615],[.452769994735718,.420849978923798],[.43639200925827,.359887003898621],[.416164010763168,.368713974952698],[.413385987281799,.692366003990173],[.228018000721931,.683571994304657],[.468268007040024,.352671027183533],[.411361992359161,.804327011108398],[.499989002943039,.469825029373169],[.479153990745544,.442654013633728],[.499974012374878,.439637005329132],[.432112008333206,.493588984012604],[.499886006116867,.866917014122009],[.49991300702095,.821729004383087],[.456548988819122,.819200992584229],[.344549000263214,.745438992977142],[.37890899181366,.574010014533997],[.374292999505997,.780184984207153],[.319687992334366,.570737957954407],[.357154995203018,.604269981384277],[.295284003019333,.621580958366394],[.447750002145767,.862477004528046],[.410986006259918,.508723020553589],[.31395098567009,.775308012962341],[.354128003120422,.812552988529205],[.324548006057739,.703992962837219],[.189096003770828,.646299958229065],[.279776990413666,.71465802192688],[.1338230073452,.682700991630554],[.336768001317978,.644733011722565],[.429883986711502,.466521978378296],[.455527991056442,.548622965812683],[.437114000320435,.558896005153656],[.467287987470627,.529924988746643],[.414712011814117,.335219979286194],[.37704598903656,.322777986526489],[.344107985496521,.320150971412659],[.312875986099243,.32233202457428],[.283526003360748,.333190023899078],[.241245999932289,.382785975933075],[.102986000478268,.468762993812561],[.267612010240555,.424560010433197],[.297879010438919,.433175981044769],[.333433985710144,.433878004550934],[.366427004337311,.426115989685059],[.396012008190155,.416696012020111],[.420121014118195,.41022801399231],[.007561000064015,.480777025222778],[.432949006557465,.569517970085144],[.458638995885849,.479089021682739],[.473466008901596,.545744001865387],[.476087987422943,.563830018043518],[.468472003936768,.555056989192963],[.433990985155106,.582361996173859],[.483518004417419,.562983989715576],[.482482999563217,.57784903049469],[.42645001411438,.389798998832703],[.438998997211456,.39649498462677],[.450067013502121,.400434017181396],[.289712011814117,.368252992630005],[.276670008897781,.363372981548309],[.517862021923065,.471948027610779],[.710287988185883,.380764007568359],[.526226997375488,.573909997940063],[.895093023777008,.254140973091125],[.634069979190826,.409575998783112],[.661242008209229,.41302502155304],[.688880026340485,.409460008144379],[.725341975688934,.389131009578705],[.606630027294159,.40370500087738],[.654766023159027,.344011008739471],[.629905998706818,.346076011657715],[.680678009986877,.347265005111694],[.702096998691559,.353591024875641],[.75221198797226,.410804986953735],[.602918028831482,.842862963676453],[.719901978969574,.375599980354309],[.893692970275879,.399959981441498],[.790081977844238,.391354024410248],[.643998026847839,.534487962722778],[.528249025344849,.65040397644043],[.525849997997284,.680191040039062],[.560214996337891,.657229006290436],[.585384011268616,.66654098033905],[.549625992774963,.680860996246338],[.57122802734375,.682691991329193],[.624852001667023,.72809898853302],[.513050019741058,.547281980514526],[.51509702205658,.527251958847046],[.742246985435486,.314507007598877],[.598631024360657,.454979002475739],[.570338010787964,.548575043678284],[.578631997108459,.533622980117798],[.723087012767792,.532054007053375],[.516445994377136,.499638974666595],[.662801027297974,.282917976379395],[.70362401008606,.293271005153656],[.830704987049103,.193813979625702],[.552385985851288,.302568018436432],[.607609987258911,.353887975215912],[.645429015159607,.696707010269165],[.932694971561432,.730105042457581],[.557260990142822,.572826027870178],[.542901992797852,.584792017936707],[.6180260181427,.694710969924927],[.607590973377228,.694203019142151],[.722943007946014,.271963000297546],[.577413976192474,.563166975975037],[.614082992076874,.281386971473694],[.616907000541687,.255886018276215],[.668509006500244,.119913995265961],[.770092010498047,.232020974159241],[.635536015033722,.189248979091644],[.77039098739624,.299556016921997],[.826722025871277,.278755009174347],[.527121007442474,.666198015213013],[.553171992301941,.668527007102966],[.577238023281097,.673889994621277],[.554691970348358,.580065965652466],[.611896991729736,.693961024284363],[.59696102142334,.706539988517761],[.596370995044708,.693953037261963],[.539958000183105,.557139039039612],[.568841993808746,.692366003990173],[.547818005084991,.692366003990173],[.52461302280426,.692366003990173],[.534089982509613,.779141008853912],[.527670979499817,.736225962638855],[.526912987232208,.717857003211975],[.526877999305725,.704625964164734],[.526966989040375,.695277988910675],[.572058022022247,.695277988910675],[.573521018028259,.703539967536926],[.57683801651001,.711845993995667],[.581691026687622,.720062971115112],[.609944999217987,.639909982681274],[.986046016216278,.560034036636353],[.5867999792099,.69539999961853],[.590372025966644,.701822996139526],[.531915009021759,.601536989212036],[.577268004417419,.585934996604919],[.536915004253387,.593786001205444],[.627542972564697,.473352015018463],[.665585994720459,.495950996875763],[.588353991508484,.546862006187439],[.757824003696442,.14767599105835],[.709249973297119,.201507985591888],[.672684013843536,.256581008434296],[.600408971309662,.74900496006012],[.55826598405838,.261672019958496],[.570303976535797,.187870979309082],[.588165998458862,.109044015407562],[.711045026779175,.398952007293701],[.781069993972778,.435405015945435],[.587247014045715,.398931980133057],[.742869973182678,.355445981025696],[.572156012058258,.437651991844177],[.55186802148819,.536570012569427],[.821442008018494,.457556009292603],[.752701997756958,.457181990146637],[.71375697851181,.467626988887787],[.66711300611496,.460672974586487],[.631101012229919,.447153985500336],[.6008620262146,.432473003864288],[.523481011390686,.405627012252808],[.810747981071472,.523926019668579],[.771045982837677,.348959028720856],[.509127020835876,.562718033790588],[.595292985439301,.485023975372314],[.980530977249146,.401564002037048],[.573499977588654,.420000016689301],[.602994978427887,.548687994480133],[.733529984951019,.376977026462555],[.560611009597778,.519016981124878],[.967685997486115,.644356966018677],[.580985009670258,.387160003185272],[.537728011608124,.505385041236877],[.760966002941132,.779752969741821],[.801778972148895,.831938028335571],[.892440974712372,.54076099395752],[.816350996494293,.740260004997253],[.865594983100891,.333687007427216],[.614073991775513,.883246004581451],[.508952975273132,.579437971115112],[.617941975593567,.508316040039062],[.825608015060425,.397674977779388],[.681214988231659,.39623498916626],[.656635999679565,.400596976280212],[.603900015354156,.710216999053955],[.81208598613739,.588539004325867],[.56801301240921,.944564998149872],[.681007981300354,.898285031318665],[.733752012252808,.869701027870178],[.633830010890961,.398822009563446],[.606792986392975,.39553701877594],[.589659988880157,.391062021255493],[.805015981197357,.342108011245728],[.611334979534149,.362284004688263],[.634037971496582,.355970978736877],[.656635999679565,.355356991291046],[.681214988231659,.35834002494812],[.698584973812103,.363156020641327],[.941866993904114,.319076001644135],[.698584973812103,.387449026107788],[.584177017211914,.624107003211975],[.554318010807037,.566076993942261],[.534153997898102,.62064003944397],[.711217999458313,.819975018501282],[.664629995822906,.852871000766754],[.559099972248077,.902631998062134],[.871706008911133,.791940987110138],[.591234028339386,.373893976211548],[.544341027736664,.451583981513977],[.624562978744507,.924192011356354],[.88577002286911,.615028977394104],[.551338016986847,.695277988910675],[.551980018615723,.704632043838501],[.552887976169586,.715808033943176],[.555167973041534,.730794012546539],[.569944024085999,.767035007476807],[.593203008174896,.685675978660583],[.599261999130249,.681069016456604],[.607599973678589,.677703022956848],[.631937980651855,.663500010967255],[.752032995223999,.601315021514893],[.547226011753082,.420395016670227],[.563543975353241,.359827995300293],[.583841025829315,.368713974952698],[.586614012718201,.692366003990173],[.771915018558502,.683578014373779],[.531597018241882,.352482974529266],[.588370978832245,.804440975189209],[.52079701423645,.442565023899078],[.567984998226166,.493479013442993],[.543282985687256,.819254994392395],[.655317008495331,.745514988899231],[.621008992195129,.574018001556396],[.625559985637665,.78031200170517],[.680198013782501,.570719003677368],[.64276397228241,.604337990283966],[.704662978649139,.621529996395111],[.552012026309967,.862591981887817],[.589071989059448,.508637011051178],[.685944974422455,.775357007980347],[.645735025405884,.812640011310577],[.675342977046967,.703978002071381],[.810858011245728,.646304965019226],[.72012197971344,.714666962623596],[.866151988506317,.682704985141754],[.663187026977539,.644596993923187],[.570082008838654,.466325998306274],[.544561982154846,.548375964164734],[.562758982181549,.558784961700439],[.531987011432648,.530140042304993],[.585271000862122,.335177004337311],[.622952997684479,.32277899980545],[.655896008014679,.320163011550903],[.687132000923157,.322345972061157],[.716481983661652,.333200991153717],[.758756995201111,.382786989212036],[.897013008594513,.468769013881683],[.732392013072968,.424547016620636],[.70211398601532,.433162987232208],[.66652500629425,.433866024017334],[.633504986763,.426087975502014],[.603875994682312,.416586995124817],[.579657971858978,.409945011138916],[.992439985275269,.480777025222778],[.567192018032074,.569419980049133],[.54136598110199,.478899002075195],[.526564002037048,.546118021011353],[.523913025856018,.563830018043518],[.531529009342194,.555056989192963],[.566035985946655,.582329034805298],[.51631098985672,.563053965568542],[.5174720287323,.577877044677734],[.573594987392426,.389806985855103],[.560697972774506,.395331978797913],[.549755990505219,.399751007556915],[.710287988185883,.368252992630005],[.723330020904541,.363372981548309]],Ne=[127,34,139,11,0,37,232,231,120,72,37,39,128,121,47,232,121,128,104,69,67,175,171,148,157,154,155,118,50,101,73,39,40,9,151,108,48,115,131,194,204,211,74,40,185,80,42,183,40,92,186,230,229,118,202,212,214,83,18,17,76,61,146,160,29,30,56,157,173,106,204,194,135,214,192,203,165,98,21,71,68,51,45,4,144,24,23,77,146,91,205,50,187,201,200,18,91,106,182,90,91,181,85,84,17,206,203,36,148,171,140,92,40,39,193,189,244,159,158,28,247,246,161,236,3,196,54,68,104,193,168,8,117,228,31,189,193,55,98,97,99,126,47,100,166,79,218,155,154,26,209,49,131,135,136,150,47,126,217,223,52,53,45,51,134,211,170,140,67,69,108,43,106,91,230,119,120,226,130,247,63,53,52,238,20,242,46,70,156,78,62,96,46,53,63,143,34,227,173,155,133,123,117,111,44,125,19,236,134,51,216,206,205,154,153,22,39,37,167,200,201,208,36,142,100,57,212,202,20,60,99,28,158,157,35,226,113,160,159,27,204,202,210,113,225,46,43,202,204,62,76,77,137,123,116,41,38,72,203,129,142,64,98,240,49,102,64,41,73,74,212,216,207,42,74,184,169,170,211,170,149,176,105,66,69,122,6,168,123,147,187,96,77,90,65,55,107,89,90,180,101,100,120,63,105,104,93,137,227,15,86,85,129,102,49,14,87,86,55,8,9,100,47,121,145,23,22,88,89,179,6,122,196,88,95,96,138,172,136,215,58,172,115,48,219,42,80,81,195,3,51,43,146,61,171,175,199,81,82,38,53,46,225,144,163,110,246,33,7,52,65,66,229,228,117,34,127,234,107,108,69,109,108,151,48,64,235,62,78,191,129,209,126,111,35,143,163,161,246,117,123,50,222,65,52,19,125,141,221,55,65,3,195,197,25,7,33,220,237,44,70,71,139,122,193,245,247,130,33,71,21,162,153,158,159,170,169,150,188,174,196,216,186,92,144,160,161,2,97,167,141,125,241,164,167,37,72,38,12,145,159,160,38,82,13,63,68,71,226,35,111,158,153,154,101,50,205,206,92,165,209,198,217,165,167,97,220,115,218,133,112,243,239,238,241,214,135,169,190,173,133,171,208,32,125,44,237,86,87,178,85,86,179,84,85,180,83,84,181,201,83,182,137,93,132,76,62,183,61,76,184,57,61,185,212,57,186,214,207,187,34,143,156,79,239,237,123,137,177,44,1,4,201,194,32,64,102,129,213,215,138,59,166,219,242,99,97,2,94,141,75,59,235,24,110,228,25,130,226,23,24,229,22,23,230,26,22,231,112,26,232,189,190,243,221,56,190,28,56,221,27,28,222,29,27,223,30,29,224,247,30,225,238,79,20,166,59,75,60,75,240,147,177,215,20,79,166,187,147,213,112,233,244,233,128,245,128,114,188,114,217,174,131,115,220,217,198,236,198,131,134,177,132,58,143,35,124,110,163,7,228,110,25,356,389,368,11,302,267,452,350,349,302,303,269,357,343,277,452,453,357,333,332,297,175,152,377,384,398,382,347,348,330,303,304,270,9,336,337,278,279,360,418,262,431,304,408,409,310,415,407,270,409,410,450,348,347,422,430,434,313,314,17,306,307,375,387,388,260,286,414,398,335,406,418,364,367,416,423,358,327,251,284,298,281,5,4,373,374,253,307,320,321,425,427,411,421,313,18,321,405,406,320,404,405,315,16,17,426,425,266,377,400,369,322,391,269,417,465,464,386,257,258,466,260,388,456,399,419,284,332,333,417,285,8,346,340,261,413,441,285,327,460,328,355,371,329,392,439,438,382,341,256,429,420,360,364,394,379,277,343,437,443,444,283,275,440,363,431,262,369,297,338,337,273,375,321,450,451,349,446,342,467,293,334,282,458,461,462,276,353,383,308,324,325,276,300,293,372,345,447,382,398,362,352,345,340,274,1,19,456,248,281,436,427,425,381,256,252,269,391,393,200,199,428,266,330,329,287,273,422,250,462,328,258,286,384,265,353,342,387,259,257,424,431,430,342,353,276,273,335,424,292,325,307,366,447,345,271,303,302,423,266,371,294,455,460,279,278,294,271,272,304,432,434,427,272,407,408,394,430,431,395,369,400,334,333,299,351,417,168,352,280,411,325,319,320,295,296,336,319,403,404,330,348,349,293,298,333,323,454,447,15,16,315,358,429,279,14,15,316,285,336,9,329,349,350,374,380,252,318,402,403,6,197,419,318,319,325,367,364,365,435,367,397,344,438,439,272,271,311,195,5,281,273,287,291,396,428,199,311,271,268,283,444,445,373,254,339,263,466,249,282,334,296,449,347,346,264,447,454,336,296,299,338,10,151,278,439,455,292,407,415,358,371,355,340,345,372,390,249,466,346,347,280,442,443,282,19,94,370,441,442,295,248,419,197,263,255,359,440,275,274,300,383,368,351,412,465,263,467,466,301,368,389,380,374,386,395,378,379,412,351,419,436,426,322,373,390,388,2,164,393,370,462,461,164,0,267,302,11,12,374,373,387,268,12,13,293,300,301,446,261,340,385,384,381,330,266,425,426,423,391,429,355,437,391,327,326,440,457,438,341,382,362,459,457,461,434,430,394,414,463,362,396,369,262,354,461,457,316,403,402,315,404,403,314,405,404,313,406,405,421,418,406,366,401,361,306,408,407,291,409,408,287,410,409,432,436,410,434,416,411,264,368,383,309,438,457,352,376,401,274,275,4,421,428,262,294,327,358,433,416,367,289,455,439,462,370,326,2,326,370,305,460,455,254,449,448,255,261,446,253,450,449,252,451,450,256,452,451,341,453,452,413,464,463,441,413,414,258,442,441,257,443,442,259,444,443,260,445,444,467,342,445,459,458,250,289,392,290,290,328,460,376,433,435,250,290,392,411,416,433,341,463,464,453,464,465,357,465,412,343,412,399,360,363,440,437,399,456,420,456,363,401,435,288,372,383,353,339,255,249,448,261,255,133,243,190,133,155,112,33,246,247,33,130,25,398,384,286,362,398,414,362,463,341,263,359,467,263,249,255,466,467,260,75,60,166,238,239,79,162,127,139,72,11,37,121,232,120,73,72,39,114,128,47,233,232,128,103,104,67,152,175,148,173,157,155,119,118,101,74,73,40,107,9,108,49,48,131,32,194,211,184,74,185,191,80,183,185,40,186,119,230,118,210,202,214,84,83,17,77,76,146,161,160,30,190,56,173,182,106,194,138,135,192,129,203,98,54,21,68,5,51,4,145,144,23,90,77,91,207,205,187,83,201,18,181,91,182,180,90,181,16,85,17,205,206,36,176,148,140,165,92,39,245,193,244,27,159,28,30,247,161,174,236,196,103,54,104,55,193,8,111,117,31,221,189,55,240,98,99,142,126,100,219,166,218,112,155,26,198,209,131,169,135,150,114,47,217,224,223,53,220,45,134,32,211,140,109,67,108,146,43,91,231,230,120,113,226,247,105,63,52,241,238,242,124,46,156,95,78,96,70,46,63,116,143,227,116,123,111,1,44,19,3,236,51,207,216,205,26,154,22,165,39,167,199,200,208,101,36,100,43,57,202,242,20,99,56,28,157,124,35,113,29,160,27,211,204,210,124,113,46,106,43,204,96,62,77,227,137,116,73,41,72,36,203,142,235,64,240,48,49,64,42,41,74,214,212,207,183,42,184,210,169,211,140,170,176,104,105,69,193,122,168,50,123,187,89,96,90,66,65,107,179,89,180,119,101,120,68,63,104,234,93,227,16,15,85,209,129,49,15,14,86,107,55,9,120,100,121,153,145,22,178,88,179,197,6,196,89,88,96,135,138,136,138,215,172,218,115,219,41,42,81,5,195,51,57,43,61,208,171,199,41,81,38,224,53,225,24,144,110,105,52,66,118,229,117,227,34,234,66,107,69,10,109,151,219,48,235,183,62,191,142,129,126,116,111,143,7,163,246,118,117,50,223,222,52,94,19,141,222,221,65,196,3,197,45,220,44,156,70,139,188,122,245,139,71,162,145,153,159,149,170,150,122,188,196,206,216,92,163,144,161,164,2,167,242,141,241,0,164,37,11,72,12,144,145,160,12,38,13,70,63,71,31,226,111,157,158,154,36,101,205,203,206,165,126,209,217,98,165,97,237,220,218,237,239,241,210,214,169,140,171,32,241,125,237,179,86,178,180,85,179,181,84,180,182,83,181,194,201,182,177,137,132,184,76,183,185,61,184,186,57,185,216,212,186,192,214,187,139,34,156,218,79,237,147,123,177,45,44,4,208,201,32,98,64,129,192,213,138,235,59,219,141,242,97,97,2,141,240,75,235,229,24,228,31,25,226,230,23,229,231,22,230,232,26,231,233,112,232,244,189,243,189,221,190,222,28,221,223,27,222,224,29,223,225,30,224,113,247,225,99,60,240,213,147,215,60,20,166,192,187,213,243,112,244,244,233,245,245,128,188,188,114,174,134,131,220,174,217,236,236,198,134,215,177,58,156,143,124,25,110,7,31,228,25,264,356,368,0,11,267,451,452,349,267,302,269,350,357,277,350,452,357,299,333,297,396,175,377,381,384,382,280,347,330,269,303,270,151,9,337,344,278,360,424,418,431,270,304,409,272,310,407,322,270,410,449,450,347,432,422,434,18,313,17,291,306,375,259,387,260,424,335,418,434,364,416,391,423,327,301,251,298,275,281,4,254,373,253,375,307,321,280,425,411,200,421,18,335,321,406,321,320,405,314,315,17,423,426,266,396,377,369,270,322,269,413,417,464,385,386,258,248,456,419,298,284,333,168,417,8,448,346,261,417,413,285,326,327,328,277,355,329,309,392,438,381,382,256,279,429,360,365,364,379,355,277,437,282,443,283,281,275,363,395,431,369,299,297,337,335,273,321,348,450,349,359,446,467,283,293,282,250,458,462,300,276,383,292,308,325,283,276,293,264,372,447,346,352,340,354,274,19,363,456,281,426,436,425,380,381,252,267,269,393,421,200,428,371,266,329,432,287,422,290,250,328,385,258,384,446,265,342,386,387,257,422,424,430,445,342,276,422,273,424,306,292,307,352,366,345,268,271,302,358,423,371,327,294,460,331,279,294,303,271,304,436,432,427,304,272,408,395,394,431,378,395,400,296,334,299,6,351,168,376,352,411,307,325,320,285,295,336,320,319,404,329,330,349,334,293,333,366,323,447,316,15,315,331,358,279,317,14,316,8,285,9,277,329,350,253,374,252,319,318,403,351,6,419,324,318,325,397,367,365,288,435,397,278,344,439,310,272,311,248,195,281,375,273,291,175,396,199,312,311,268,276,283,445,390,373,339,295,282,296,448,449,346,356,264,454,337,336,299,337,338,151,294,278,455,308,292,415,429,358,355,265,340,372,388,390,466,352,346,280,295,442,282,354,19,370,285,441,295,195,248,197,457,440,274,301,300,368,417,351,465,251,301,389,385,380,386,394,395,379,399,412,419,410,436,322,387,373,388,326,2,393,354,370,461,393,164,267,268,302,12,386,374,387,312,268,13,298,293,301,265,446,340,380,385,381,280,330,425,322,426,391,420,429,437,393,391,326,344,440,438,458,459,461,364,434,394,428,396,262,274,354,457,317,316,402,316,315,403,315,314,404,314,313,405,313,421,406,323,366,361,292,306,407,306,291,408,291,287,409,287,432,410,427,434,411,372,264,383,459,309,457,366,352,401,1,274,4,418,421,262,331,294,358,435,433,367,392,289,439,328,462,326,94,2,370,289,305,455,339,254,448,359,255,446,254,253,449,253,252,450,252,256,451,256,341,452,414,413,463,286,441,414,286,258,441,258,257,442,257,259,443,259,260,444,260,467,445,309,459,250,305,289,290,305,290,460,401,376,435,309,250,392,376,411,433,453,341,464,357,453,465,343,357,412,437,343,399,344,360,440,420,437,456,360,420,363,361,401,288,265,372,353,390,339,249,339,448,255];var ur=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],hr=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],br=[33,133,362,263,1,78,308],L7=ur.map(e=>R2[e]),W7=hr.map(e=>R2[e]),F7=br.map(e=>R2[e]);function ge(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var gr=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Mr=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Pr=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],Rr=[[474,475],[475,476],[476,477],[477,474]],vr=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],Tr=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],wr=[[469,470],[470,471],[471,472],[472,469]],kr=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]],G7={lips:ge(gr),leftEye:ge(Mr),leftEyebrow:ge(Pr),leftIris:ge(Rr),rightEye:ge(vr),rightEyebrow:ge(Tr),rightIris:ge(wr),faceOval:ge(kr)};var Je=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],X2=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],q2=(e,t)=>e?[Math.trunc(Math.max(0,e.startPoint[0])),Math.trunc(Math.max(0,e.startPoint[1])),Math.trunc(Math.min(t.shape[2]||0,e.endPoint[0])-Math.max(0,e.startPoint[0])),Math.trunc(Math.min(t.shape[1]||0,e.endPoint[1])-Math.max(0,e.startPoint[1]))]:[0,0,0,0],U2=(e,t)=>e?[e.startPoint[0]/(t.shape[2]||0),e.startPoint[1]/(t.shape[1]||0),(e.endPoint[0]-e.startPoint[0])/(t.shape[2]||0),(e.endPoint[1]-e.startPoint[1])/(t.shape[1]||0)]:[0,0,0,0],Yt=(e,t)=>{let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]];return{startPoint:o,endPoint:n,landmarks:e.landmarks,confidence:e.confidence}},J5=(e,t,o)=>{let n=t.shape[1],r=t.shape[2],A=[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r],s=ie.image.cropAndResize(t,[A],[0],o),a=ie.div(s,V.tf255);return ie.dispose(s),a},Y2=(e,t)=>{let o=X2(e),n=Je(e),r=[t*n[0]/2,t*n[1]/2];return{startPoint:[o[0]-r[0],o[1]-r[1]],endPoint:[o[0]+r[0],o[1]+r[1]],landmarks:e.landmarks,confidence:e.confidence}},K2=e=>{let t=X2(e),o=Je(e),n=Math.max(...o)/2;return{startPoint:[Math.round(t[0]-n),Math.round(t[1]-n)],endPoint:[Math.round(t[0]+n),Math.round(t[1]+n)],landmarks:e.landmarks,confidence:e.confidence}},Kt=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return{startPoint:[Math.min(...t),Math.min(...o)],endPoint:[Math.max(...t),Math.max(...o)],landmarks:e}},Q5=[[1,0,0],[0,1,0],[0,0,1]],Er=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),zr=(e,t)=>Er(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var qt=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],Oe=(e,t)=>{let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o},Sr=(e,t)=>{let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o},Ut=(e,t)=>{let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let A=0;A<n;A++)o[r].push(Oe(e[r],Sr(t,A)))}return o},Jt=(e,t)=>{let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],A=qt(t[0],t[1]),s=Ut(A,r),a=qt(-t[0],-t[1]);return Ut(s,a)},Cr=e=>{let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-Oe(t[0],o),-Oe(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]},jr=(e,t)=>[Oe(e,t[0]),Oe(e,t[1])];function Qt(e){let t=e===192?{strides:[4],anchors:[1]}:{strides:[e/16,e/8],anchors:[2,6]},o=[];for(let n=0;n<t.strides.length;n++){let r=t.strides[n],A=Math.floor((e+r-1)/r),s=Math.floor((e+r-1)/r),a=t.anchors[n];for(let i=0;i<A;i++){let x=r*(i+.5);for(let c=0;c<s;c++){let l=r*(c+.5);for(let y=0;y<a;y++)o.push([l,x])}}}return o}function _t(e,t,o,n,r){let A=Je(t),s=e.map(f=>[A[0]/r*(f[0]-r/2),A[1]/r*(f[1]-r/2),f[2]||0]),a=o&&o!==0&&Math.abs(o)>.2,i=a?Jt(o,[0,0]):Q5,x=a?s.map(f=>[...jr(f,i),f[2]]):s,c=a?Cr(n):Q5,l=X2(t),y=[Oe(l,c[0]),Oe(l,c[1])];return x.map(f=>[Math.trunc(f[0]+y[0]),Math.trunc(f[1]+y[1]),Math.trunc(f[2]||0)])}function $t(e,t,o,n){let r=t.landmarks.length>=U5.count?U5.symmetryLine:Ie.symmetryLine,A=0,s=Q5,a;if(e&&v.kernels.includes("rotatewithoffset"))if(A=zr(t.landmarks[r[0]],t.landmarks[r[1]]),A&&A!==0&&Math.abs(A)>.2){let x=X2(t),c=[x[0]/o.shape[2],x[1]/o.shape[1]],l=ie.image.rotateWithOffset(o,A,0,c);s=Jt(-A,x),a=J5(t,l,[n,n]),ie.dispose(l)}else a=J5(t,o,[n,n]);else a=J5(t,o,[n,n]);return[A,s,a]}var Ir=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return[Math.min(...t)+(Math.max(...t)-Math.min(...t))/2,Math.min(...o)+(Math.max(...o)-Math.min(...o))/2]},e3=(e,t)=>{let o=Ir(e),n=Je(t);return{startPoint:[o[0]-n[0]/2,o[1]-n[1]/2],endPoint:[o[0]+n[0]/2,o[1]+n[1]/2]}};var t3=6,Nr=1.4,te,o3=null,Me=0,v2=null,Qe=()=>Me;async function n3(e){var t;return v.initial&&(te=null),te?e.debug&&p("cached model:",te.modelUrl):te=await G((t=e.face.detector)==null?void 0:t.modelPath),Me=te.inputs[0].shape?te.inputs[0].shape[2]:0,v2=O.scalar(Me,"int32"),o3=O.tensor2d(Qt(Me)),te}function Or(e){let t={};t.boxStarts=O.slice(e,[0,1],[-1,2]),t.centers=O.add(t.boxStarts,o3),t.boxSizes=O.slice(e,[0,3],[-1,2]),t.boxSizesNormalized=O.div(t.boxSizes,v2),t.centersNormalized=O.div(t.centers,v2),t.halfBoxSize=O.div(t.boxSizesNormalized,V.tf2),t.starts=O.sub(t.centersNormalized,t.halfBoxSize),t.ends=O.add(t.centersNormalized,t.halfBoxSize),t.startNormalized=O.mul(t.starts,v2),t.endNormalized=O.mul(t.ends,v2);let o=O.concat2d([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(n=>O.dispose(t[n])),o}async function r3(e,t){var a,i,x,c;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let o={};o.resized=O.image.resizeBilinear(e,[Me,Me]),o.div=O.div(o.resized,V.tf127),o.normalized=O.sub(o.div,V.tf05);let n=te==null?void 0:te.execute(o.normalized);if(Array.isArray(n)&&n.length>2){let l=n.sort((y,f)=>y.size-f.size);o.concat384=O.concat([l[0],l[2]],2),o.concat512=O.concat([l[1],l[3]],2),o.concat=O.concat([o.concat512,o.concat384],1),o.batch=O.squeeze(o.concat,0)}else Array.isArray(n)?o.batch=O.squeeze(n[0]):o.batch=O.squeeze(n);O.dispose(n),o.boxes=Or(o.batch),o.logits=O.slice(o.batch,[0,0],[-1,1]),o.sigmoid=O.sigmoid(o.logits),o.scores=O.squeeze(o.sigmoid),o.nms=await O.image.nonMaxSuppressionAsync(o.boxes,o.scores,((a=t.face.detector)==null?void 0:a.maxDetected)||0,((i=t.face.detector)==null?void 0:i.iouThreshold)||0,((x=t.face.detector)==null?void 0:x.minConfidence)||0);let r=await o.nms.array(),A=[],s=await o.scores.data();for(let l=0;l<r.length;l++){let y=s[r[l]];if(y>(((c=t.face.detector)==null?void 0:c.minConfidence)||0)){let f={};f.bbox=O.slice(o.boxes,[r[l],0],[1,-1]),f.slice=O.slice(o.batch,[r[l],t3-1],[1,-1]),f.squeeze=O.squeeze(f.slice),f.landmarks=O.reshape(f.squeeze,[t3,-1]);let u=await f.bbox.data(),m={startPoint:[u[0],u[1]],endPoint:[u[2],u[3]],landmarks:await f.landmarks.array(),confidence:y},P=Yt(m,[(e.shape[2]||0)/Me,(e.shape[1]||0)/Me]),g=Y2(P,t.face.scale||Nr),b=K2(g);A.push(b),Object.keys(f).forEach(d=>O.dispose(f[d]))}}return Object.keys(o).forEach(l=>O.dispose(o[l])),A}var I0=Z(D());var J2={};ue(J2,{connected:()=>e1,kpt:()=>$5});var $5=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPinky","rightPinky","leftIndex","rightIndex","leftThumb","rightThumb","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","bodyCenter","bodyTop","leftPalm","leftHand","rightPalm","rightHand"],e1={shoulders:["leftShoulder","rightShoulder"],hips:["rightHip","leftHip"],mouth:["leftMouth","rightMouth"],leftLegUpper:["leftHip","leftKnee"],leftLegLower:["leftKnee","leftAnkle"],leftFoot:["leftAnkle","leftHeel","leftFoot"],leftTorso:["leftShoulder","leftHip"],leftArmUpper:["leftShoulder","leftElbow"],leftArmLower:["leftElbow","leftWrist"],leftHand:["leftWrist","leftPalm"],leftHandPinky:["leftPalm","leftPinky"],leftHandIndex:["leftPalm","leftIndex"],leftHandThumb:["leftPalm","leftThumb"],leftEyeOutline:["leftEyeInside","leftEyeOutside"],rightLegUpper:["rightHip","rightKnee"],rightLegLower:["rightKnee","rightAnkle"],rightFoot:["rightAnkle","rightHeel","rightFoot"],rightTorso:["rightShoulder","rightHip"],rightArmUpper:["rightShoulder","rightElbow"],rightArmLower:["rightElbow","rightWrist"],rightHand:["rightWrist","rightPalm"],rightHandPinky:["rightPalm","rightPinky"],rightHandIndex:["rightPalm","rightIndex"],rightHandThumb:["rightPalm","rightThumb"],rightEyeOutline:["rightEyeInside","rightEyeOutside"]};var C0=Z(D()),s3=224,Lr,Wr=5,Q2=[8,16,32,32,32];async function a3(){let e=[],t=0;for(;t<Wr;){let o=0,n=t;for(;n<Q2.length&&Q2[n]===Q2[t];)o+=2,n++;let r=Q2[t],A=Math.ceil(s3/r),s=Math.ceil(s3/r);for(let a=0;a<A;++a)for(let i=0;i<s;++i)for(let x=0;x<o;++x)e.push({x:(i+.5)/s,y:(a+.5)/A});t=n}Lr={x:C0.tensor1d(e.map(o=>o.x)),y:C0.tensor1d(e.map(o=>o.y))}}function le(e,t=[1,1]){let o=[e.map(a=>a[0]),e.map(a=>a[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],A=[n[0],n[1],r[0]-n[0],r[1]-n[1]],s=[A[0]/t[0],A[1]/t[1],A[2]/t[0],A[3]/t[1]];return{box:A,boxRaw:s}}function i3(e,t=[1,1]){let o=[e.map(x=>x[0]),e.map(x=>x[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],A=[(n[0]+r[0])/2,(n[1]+r[1])/2],s=Math.max(A[0]-n[0],A[1]-n[1],-A[0]+r[0],-A[1]+r[1]),a=[Math.trunc(A[0]-s),Math.trunc(A[1]-s),Math.trunc(2*s),Math.trunc(2*s)],i=[a[0]/t[0],a[1]/t[1],a[2]/t[0],a[3]/t[1]];return{box:a,boxRaw:i}}function _2(e,t){let o=[e[2]*t,e[3]*t];return[e[0]-(o[0]-e[2])/2,e[1]-(o[1]-e[3])/2,o[0],o[1]]}var x3={initial:!0},j0={detector:null,landmarks:null},_e={detector:[224,224],landmarks:[256,256]},t1=Number.MAX_SAFE_INTEGER,Gr={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},e5=null,T2,Pe=[[0,0],[0,0],[0,0],[0,0]],l3=0,y3=e=>1-1/(1+Math.exp(e));async function c3(e){if(x3.initial&&(j0.detector=null),!j0.detector&&e.body.detector&&e.body.detector.modelPath){j0.detector=await G(e.body.detector.modelPath);let t=Object.values(j0.detector.modelSignature.inputs);_e.detector[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,_e.detector[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&j0.detector&&p("cached model:",j0.detector.modelUrl);return await a3(),j0.detector}async function d3(e){if(x3.initial&&(j0.landmarks=null),j0.landmarks)e.debug&&p("cached model:",j0.landmarks.modelUrl);else{j0.landmarks=await G(e.body.modelPath);let t=Object.values(j0.landmarks.modelSignature.inputs);_e.landmarks[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,_e.landmarks[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return j0.landmarks}async function Br(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;let n;if(T2&&(o.cropped=I0.image.cropAndResize(e,[T2],[0],[e.shape[1],e.shape[2]])),e.shape[1]!==e.shape[2]){let r=[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],A=[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0];Pe=[[0,0],r,A,[0,0]],o.pad=I0.pad(o.cropped||e,Pe),o.resize=I0.image.resizeBilinear(o.pad,[t,t]),n=I0.div(o.resize,V.tf255)}else e.shape[1]!==t?(o.resize=I0.image.resizeBilinear(o.cropped||e,[t,t]),n=I0.div(o.resize,V.tf255)):n=I0.div(o.cropped||e,V.tf255);return Object.keys(o).forEach(r=>I0.dispose(o[r])),n}function Hr(e,t){for(let o of e)o.position=[Math.trunc(o.position[0]*(t[0]+Pe[2][0]+Pe[2][1])/t[0]-Pe[2][0]),Math.trunc(o.position[1]*(t[1]+Pe[1][0]+Pe[1][1])/t[1]-Pe[1][0]),o.position[2]],o.positionRaw=[o.position[0]/t[0],o.position[1]/t[1],2*o.position[2]/(t[0]+t[1])];if(T2)for(let o of e)o.positionRaw=[o.positionRaw[0]+T2[1],o.positionRaw[1]+T2[0],o.positionRaw[2]],o.position=[Math.trunc(o.positionRaw[0]*t[0]),Math.trunc(o.positionRaw[1]*t[1]),o.positionRaw[2]];return e}async function Vr(e){let t=e.find(a=>a.part==="leftPalm"),o=e.find(a=>a.part==="leftWrist"),n=e.find(a=>a.part==="leftIndex");t.position[2]=((o.position[2]||0)+(n.position[2]||0))/2;let r=e.find(a=>a.part==="rightPalm"),A=e.find(a=>a.part==="rightWrist"),s=e.find(a=>a.part==="rightIndex");r.position[2]=((A.position[2]||0)+(s.position[2]||0))/2}async function Dr(e,t,o){var u;let n={};[n.ld,n.segmentation,n.heatmap,n.world,n.poseflag]=(u=j0.landmarks)==null?void 0:u.execute(e,Gr.landmarks);let r=(await n.poseflag.data())[0],A=await n.ld.data(),s=await n.world.data();Object.keys(n).forEach(m=>I0.dispose(n[m]));let a=[],i=5;for(let m=0;m<A.length/i;m++){let P=y3(A[i*m+3]),g=y3(A[i*m+4]),b=Math.trunc(100*P*g*r)/100,d=[A[i*m+0]/_e.landmarks[0],A[i*m+1]/_e.landmarks[1],A[i*m+2]+0],M=[Math.trunc(o[0]*d[0]),Math.trunc(o[1]*d[1]),d[2]],S=[s[i*m+0],s[i*m+1],s[i*m+2]+0];a.push({part:$5[m],positionRaw:d,position:M,distance:S,score:b})}if(r<(t.body.minConfidence||0))return null;Vr(a);let x=Hr(a,o),c=x.map(m=>m.position),l=le(c,[o[0],o[1]]),y={};for(let[m,P]of Object.entries(e1)){let g=[];for(let b=0;b<P.length-1;b++){let d=x.find(S=>S.part===P[b]),M=x.find(S=>S.part===P[b+1]);d&&M&&g.push([d.position,M.position])}y[m]=g}return{id:0,score:Math.trunc(100*r)/100,box:l.box,boxRaw:l.boxRaw,keypoints:x,annotations:y}}async function o1(e,t){let o=[e.shape[2]||0,e.shape[1]||0],n=(t.body.skipTime||0)>h()-l3,r=t1<(t.body.skipFrames||0);if(t.skipAllowed&&n&&r&&e5!==null)t1++;else{let A={};A.landmarks=await Br(e,256),e5=await Dr(A.landmarks,t,o),Object.keys(A).forEach(s=>I0.dispose(A[s])),l3=h(),t1=0}return e5?[e5]:[]}var T0=Z(D());var $e=[{class:1,label:"person"},{class:2,label:"bicycle"},{class:3,label:"car"},{class:4,label:"motorcycle"},{class:5,label:"airplane"},{class:6,label:"bus"},{class:7,label:"train"},{class:8,label:"truck"},{class:9,label:"boat"},{class:10,label:"traffic light"},{class:11,label:"fire hydrant"},{class:12,label:"stop sign"},{class:13,label:"parking meter"},{class:14,label:"bench"},{class:15,label:"bird"},{class:16,label:"cat"},{class:17,label:"dog"},{class:18,label:"horse"},{class:19,label:"sheep"},{class:20,label:"cow"},{class:21,label:"elephant"},{class:22,label:"bear"},{class:23,label:"zebra"},{class:24,label:"giraffe"},{class:25,label:"backpack"},{class:26,label:"umbrella"},{class:27,label:"handbag"},{class:28,label:"tie"},{class:29,label:"suitcase"},{class:30,label:"frisbee"},{class:31,label:"skis"},{class:32,label:"snowboard"},{class:33,label:"sports ball"},{class:34,label:"kite"},{class:35,label:"baseball bat"},{class:36,label:"baseball glove"},{class:37,label:"skateboard"},{class:38,label:"surfboard"},{class:39,label:"tennis racket"},{class:40,label:"bottle"},{class:41,label:"wine glass"},{class:42,label:"cup"},{class:43,label:"fork"},{class:44,label:"knife"},{class:45,label:"spoon"},{class:46,label:"bowl"},{class:47,label:"banana"},{class:48,label:"apple"},{class:49,label:"sandwich"},{class:50,label:"orange"},{class:51,label:"broccoli"},{class:52,label:"carrot"},{class:53,label:"hot dog"},{class:54,label:"pizza"},{class:55,label:"donut"},{class:56,label:"cake"},{class:57,label:"chair"},{class:58,label:"couch"},{class:59,label:"potted plant"},{class:60,label:"bed"},{class:61,label:"dining table"},{class:62,label:"toilet"},{class:63,label:"tv"},{class:64,label:"laptop"},{class:65,label:"mouse"},{class:66,label:"remote"},{class:67,label:"keyboard"},{class:68,label:"cell phone"},{class:69,label:"microwave"},{class:70,label:"oven"},{class:71,label:"toaster"},{class:72,label:"sink"},{class:73,label:"refrigerator"},{class:74,label:"book"},{class:75,label:"clock"},{class:76,label:"vase"},{class:77,label:"scissors"},{class:78,label:"teddy bear"},{class:79,label:"hair drier"},{class:80,label:"toothbrush"}];var ye,Le=0,n1=[],m3=0,r1=Number.MAX_SAFE_INTEGER;async function p3(e){if(v.initial&&(ye=null),ye)e.debug&&p("cached model:",ye.modelUrl);else{ye=await G(e.object.modelPath);let t=Object.values(ye.modelSignature.inputs);Le=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return ye}async function Zr(e,t,o){if(!e)return[];let n={},r=[],A=await e.array();n.squeeze=T0.squeeze(e);let s=T0.split(n.squeeze,6,1);n.stack=T0.stack([s[1],s[0],s[3],s[2]],1),n.boxes=T0.squeeze(n.stack),n.scores=T0.squeeze(s[4]),n.classes=T0.squeeze(s[5]),T0.dispose([e,...s]),n.nms=await T0.image.nonMaxSuppressionAsync(n.boxes,n.scores,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence||0);let a=await n.nms.data(),i=0;for(let x of Array.from(a)){let c=Math.trunc(100*A[0][x][4])/100,l=A[0][x][5],y=$e[l].label,[f,u]=[A[0][x][0]/Le,A[0][x][1]/Le],m=[f,u,A[0][x][2]/Le-f,A[0][x][3]/Le-u],P=[Math.trunc(m[0]*t[0]),Math.trunc(m[1]*t[1]),Math.trunc(m[2]*t[0]),Math.trunc(m[3]*t[1])];r.push({id:i++,score:c,class:l,label:y,box:P,boxRaw:m})}return Object.keys(n).forEach(x=>T0.dispose(n[x])),r}async function A1(e,t){let o=(t.object.skipTime||0)>h()-m3,n=r1<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&n1.length>0?(r1++,n1):(r1=0,new Promise(async r=>{let A=[e.shape[2]||0,e.shape[1]||0],s=T0.image.resizeBilinear(e,[Le,Le]),a=t.object.enabled?ye==null?void 0:ye.execute(s,["tower_0/detections"]):null;m3=h(),T0.dispose(s);let i=await Zr(a,A,t);n1=i,r(i)}))}var _=Z(D());var t5={};ue(t5,{connected:()=>a1,kpt:()=>s1});var s1=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],a1={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var b0,h3=0,w0={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},i1=Number.MAX_SAFE_INTEGER;async function b3(e){return v.initial&&(b0=null),b0?e.debug&&p("cached model:",b0.modelUrl):b0=await G(e.body.modelPath),b0}async function Xr(e,t){let[o,n]=e.shape,r=_.reshape(e,[n*o]),A=_.max(r,0),s=(await A.data())[0];if(_.dispose([r,A]),s>t){let a=_.argMax(r,0),i=_.mod(a,o),x=(await i.data())[0],c=_.div(a,_.scalar(o,"int32")),l=(await c.data())[0];return _.dispose([i,c]),[x,l,s]}return[0,0,s]}async function l1(e,t){let o=(t.body.skipTime||0)>h()-h3,n=i1<(t.body.skipFrames||0);return t.skipAllowed&&o&&n&&Object.keys(w0.keypoints).length>0?(i1++,[w0]):(i1=0,new Promise(async r=>{var l;let A=_.tidy(()=>{if(!(b0!=null&&b0.inputs[0].shape))return null;let y=_.image.resizeBilinear(e,[b0.inputs[0].shape[2],b0.inputs[0].shape[1]],!1),f=_.mul(y,V.tf2);return _.sub(f,V.tf1)}),s;if(t.body.enabled&&(s=b0==null?void 0:b0.execute(A)),h3=h(),_.dispose(A),s){w0.keypoints.length=0;let y=s.squeeze();_.dispose(s);let f=y.unstack(2);_.dispose(y);for(let u=0;u<f.length;u++){let[m,P,g]=await Xr(f[u],t.body.minConfidence);g>(((l=t.body)==null?void 0:l.minConfidence)||0)&&w0.keypoints.push({score:Math.round(100*g)/100,part:s1[u],positionRaw:[m/b0.inputs[0].shape[2],P/b0.inputs[0].shape[1]],position:[Math.round(e.shape[2]*m/b0.inputs[0].shape[2]),Math.round(e.shape[1]*P/b0.inputs[0].shape[1])]})}f.forEach(u=>_.dispose(u))}w0.score=w0.keypoints.reduce((y,f)=>f.score>y?f.score:y,0);let a=w0.keypoints.map(y=>y.position[0]),i=w0.keypoints.map(y=>y.position[1]);w0.box=[Math.min(...a),Math.min(...i),Math.max(...a)-Math.min(...a),Math.max(...i)-Math.min(...i)];let x=w0.keypoints.map(y=>y.positionRaw[0]),c=w0.keypoints.map(y=>y.positionRaw[1]);w0.boxRaw=[Math.min(...x),Math.min(...c),Math.max(...x)-Math.min(...x),Math.max(...c)-Math.min(...c)];for(let[y,f]of Object.entries(a1)){let u=[];for(let m=0;m<f.length-1;m++){let P=w0.keypoints.find(b=>b.part===f[m]),g=w0.keypoints.find(b=>b.part===f[m+1]);P&&g&&P.score>(t.body.minConfidence||0)&&g.score>(t.body.minConfidence||0)&&u.push([P.position,g.position])}w0.annotations[y]=u}r([w0])}))}var U0=Z(D());var qr=["angry","disgust","fear","happy","sad","surprise","neutral"],H0,o5=[],M3=0,P3=0,y1=Number.MAX_SAFE_INTEGER;async function R3(e){var t;return v.initial&&(H0=null),H0?e.debug&&p("cached model:",H0.modelUrl):H0=await G((t=e.face.emotion)==null?void 0:t.modelPath),H0}async function x1(e,t,o,n){var s,a;if(!H0)return[];let r=y1<(((s=t.face.emotion)==null?void 0:s.skipFrames)||0),A=(((a=t.face.emotion)==null?void 0:a.skipTime)||0)>h()-P3;return t.skipAllowed&&A&&r&&M3===n&&o5[o]&&o5[o].length>0?(y1++,o5[o]):(y1=0,new Promise(async i=>{var c,l;let x=[];if((c=t.face.emotion)!=null&&c.enabled){let y={},f=H0!=null&&H0.inputs[0].shape?H0.inputs[0].shape[2]:0;y.resize=U0.image.resizeBilinear(e,[f,f],!1),y.channels=U0.mul(y.resize,V.rgb),y.grayscale=U0.sum(y.channels,3,!0),y.grayscaleSub=U0.sub(y.grayscale,V.tf05),y.grayscaleMul=U0.mul(y.grayscaleSub,V.tf2),y.emotion=H0==null?void 0:H0.execute(y.grayscaleMul),P3=h();let u=await y.emotion.data();for(let m=0;m<u.length;m++)u[m]>(((l=t.face.emotion)==null?void 0:l.minConfidence)||0)&&x.push({score:Math.min(.99,Math.trunc(100*u[m])/100),emotion:qr[m]});x.sort((m,P)=>P.score-m.score),Object.keys(y).forEach(m=>U0.dispose(y[m]))}o5[o]=x,M3=n,i(x)}))}var E3=Z(D());var N0,c1=[],T3=0,w3=0,k3=Number.MAX_SAFE_INTEGER;async function z3(e){return v.initial&&(N0=null),N0?e.debug&&p("cached model:",N0.modelUrl):N0=await G(e.face.mobilefacenet.modelPath),N0}async function d1(e,t,o,n){var s,a;if(!N0)return[];let r=k3<(((s=t.face.embedding)==null?void 0:s.skipFrames)||0),A=(((a=t.face.embedding)==null?void 0:a.skipTime)||0)>h()-w3;return t.skipAllowed&&A&&r&&T3===n&&c1[o]?(k3++,c1[o]):new Promise(async i=>{var c;let x=[];if(((c=t.face.embedding)==null?void 0:c.enabled)&&(N0==null?void 0:N0.inputs[0].shape)){let l={};l.crop=E3.image.resizeBilinear(e,[N0.inputs[0].shape[2],N0.inputs[0].shape[1]],!1),l.data=N0==null?void 0:N0.execute(l.crop);let y=await l.data.data();x=Array.from(y)}c1[o]=x,T3=n,w3=h(),i(x)})}var Be=Z(D());var Y0=Z(D());var xe,Re=0,Ur=2.3,f1=X0.leftEyeLower0,m1=X0.rightEyeLower0,e2={leftBounds:[f1[0],f1[f1.length-1]],rightBounds:[m1[0],m1[m1.length-1]]},t2={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function N3(e){var t;return v.initial&&(xe=null),xe?e.debug&&p("cached model:",xe.modelUrl):xe=await G((t=e.face.iris)==null?void 0:t.modelPath),Re=xe.inputs[0].shape?xe.inputs[0].shape[2]:0,Re===-1&&(Re=64),xe}function n5(e,t,o,n){for(let r=0;r<Y5.length;r++){let{key:A,indices:s}=Y5[r],a=X0[`${o}${A}`];if(!n||n.includes(A))for(let i=0;i<s.length;i++){let x=s[i];e[a[i]]=[t[x][0],t[x][1],(t[x][2]+e[a[i]][2])/2]}}}var Yr=e=>{let t=e[e2.leftBounds[0]][2],o=e[e2.rightBounds[0]][2];return t-o},C3=(e,t,o,n,r,A=!1)=>{let s=K2(Y2(Kt([e[o],e[n]]),Ur)),a=Je(s),i=Y0.image.cropAndResize(t,[[s.startPoint[1]/r,s.startPoint[0]/r,s.endPoint[1]/r,s.endPoint[0]/r]],[0],[Re,Re]);if(A&&v.kernels.includes("flipleftright")){let x=Y0.image.flipLeftRight(i);Y0.dispose(i),i=x}return{box:s,boxSize:a,crop:i}},j3=(e,t,o,n=!1)=>{let r=[];for(let A=0;A<t2.numCoordinates;A++){let s=e[A*3],a=e[A*3+1],i=e[A*3+2];r.push([(n?1-s/Re:s/Re)*o[0]+t.startPoint[0],a/Re*o[1]+t.startPoint[1],i])}return{rawCoords:r,iris:r.slice(t2.index)}},I3=(e,t,o)=>{let n=e[X0[`${o}EyeUpper0`][t2.upperCenter]][2],r=e[X0[`${o}EyeLower0`][t2.lowerCenter]][2],A=(n+r)/2;return t.map((s,a)=>{let i=A;return a===2?i=n:a===4&&(i=r),[s[0],s[1],i]})};async function O3(e,t,o,n){if(!xe)return o.debug&&p("face mesh iris detection requested, but model is not loaded"),e;let{box:r,boxSize:A,crop:s}=C3(e,t,e2.leftBounds[0],e2.leftBounds[1],n,!0),{box:a,boxSize:i,crop:x}=C3(e,t,e2.rightBounds[0],e2.rightBounds[1],n,!0),c=Y0.concat([s,x]);Y0.dispose(s),Y0.dispose(x);let l=xe.execute(c);Y0.dispose(c);let y=await l.data();Y0.dispose(l);let f=y.slice(0,t2.numCoordinates*3),{rawCoords:u,iris:m}=j3(f,r,A,!0),P=y.slice(t2.numCoordinates*3),{rawCoords:g,iris:b}=j3(P,a,i,!1),d=Yr(e);Math.abs(d)<30?(n5(e,u,"left",null),n5(e,g,"right",null)):d<1?n5(e,u,"left",["EyeUpper0","EyeLower0"]):n5(e,g,"right",["EyeUpper0","EyeLower0"]);let M=I3(e,m,"left"),S=I3(e,b,"right");return e.concat(M).concat(S)}var Kr=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Jr=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Qr=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],_r=[[474,475],[475,476],[476,477],[477,474]],$r=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],eA=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],tA=[[469,470],[470,471],[471,472],[472,469]],oA=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]];function ve(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var nA={lips:ve(Kr),leftEye:ve(Jr),leftEyebrow:ve(Qr),leftIris:ve(_r),rightEye:ve($r),rightEyebrow:ve(eA),rightIris:ve(tA),faceOval:ve(oA)},rA=Object.entries(nA).map(([e,t])=>t.map(o=>[o,e])).flat(),f4=new Map(rA),w2=[61,146,91,181,84,17,314,405,321,375,291,185,40,39,37,0,267,269,270,409,78,95,88,178,87,14,317,402,318,324,308,191,80,81,82,13,312,311,310,415,76,77,90,180,85,16,315,404,320,307,306,184,74,73,72,11,302,303,304,408,62,96,89,179,86,15,316,403,319,325,292,183,42,41,38,12,268,271,272,407],We=[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173,130,25,110,24,23,22,26,112,243,247,30,29,27,28,56,190,226,31,228,229,230,231,232,233,244,113,225,224,223,222,221,189,35,124,46,53,52,65,143,111,117,118,119,120,121,128,245,156,70,63,105,66,107,55,193],Fe=[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398,359,255,339,254,253,252,256,341,463,467,260,259,257,258,286,414,446,261,448,449,450,451,452,453,464,342,445,444,443,442,441,413,265,353,276,283,282,295,372,340,346,347,348,349,350,357,465,383,300,293,334,296,336,285,417];async function F3(e,t){let o={lips:await t.filter(A=>A.size===160)[0].data(),irisL:await t.filter(A=>A.size===10)[0].data(),eyeL:await t.filter(A=>A.size===142)[0].data(),irisR:await t.filter(A=>A.size===10)[1].data(),eyeR:await t.filter(A=>A.size===142)[1].data()},n=We.reduce((A,s)=>A+=e[s][2],0)/We.length;for(let A=0;A<o.irisL.length/2;A++)e.push([o.irisL[2*A+0],o.irisL[2*A+1],n]);let r=Fe.reduce((A,s)=>A+=e[s][2],0)/Fe.length;for(let A=0;A<o.irisR.length/2;A++)e.push([o.irisR[2*A+0],o.irisR[2*A+1],r]);for(let A=0;A<o.eyeL.length/2;A++)e[We[A]]=[o.eyeL[2*A+0],o.eyeL[2*A+1],e[We[A]][2]];for(let A=0;A<o.eyeR.length/2;A++)e[Fe[A]]=[o.eyeR[2*A+0],o.eyeR[2*A+1],e[Fe[A]][2]];for(let A=0;A<o.lips.length/2;A++)e[w2[A]]=[o.lips[2*A+0],o.lips[2*A+1],e[w2[A]][2]];return e}var oe={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},g0=null,Ge=0;async function G3(e,t){var a,i,x,c,l,y,f,u,m,P,g;let o=(((a=t.face.detector)==null?void 0:a.skipTime)||0)>h()-oe.timestamp,n=oe.skipped<(((i=t.face.detector)==null?void 0:i.skipFrames)||0);!t.skipAllowed||!o||!n||oe.boxes.length===0?(oe.boxes=await r3(e,t),oe.timestamp=h(),oe.skipped=0):oe.skipped++;let r=[],A=[],s=0;for(let b=0;b<oe.boxes.length;b++){let d=oe.boxes[b],M=0,S,w={id:s++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,annotations:{}};if([M,S,w.tensor]=$t((x=t.face.detector)==null?void 0:x.rotation,d,e,(c=t.face.mesh)!=null&&c.enabled?Ge:Qe()),(l=t==null?void 0:t.filter)!=null&&l.equalization){let j=await L2(w.tensor);Be.dispose(w.tensor),w.tensor=j}if(w.boxScore=Math.round(100*d.confidence)/100,(y=t.face.mesh)!=null&&y.enabled)if(!g0)t.debug&&p("face mesh detection requested, but model is not loaded");else{let j=g0.execute(w.tensor),F=await j.find(H=>H.shape[H.shape.length-1]===1).data();if(w.faceScore=Math.round(100*F[0])/100,w.faceScore<(((f=t.face.detector)==null?void 0:f.minConfidence)||1)){if(d.confidence=w.faceScore,(u=t.face.mesh)!=null&&u.keepInvalid){w.box=q2(d,e),w.boxRaw=U2(d,e),w.score=w.boxScore,w.mesh=d.landmarks.map(H=>[(d.startPoint[0]+d.endPoint[0])/2+(d.endPoint[0]+d.startPoint[0])*H[0]/Qe(),(d.startPoint[1]+d.endPoint[1])/2+(d.endPoint[1]+d.startPoint[1])*H[1]/Qe()]),w.meshRaw=w.mesh.map(H=>[H[0]/(e.shape[2]||1),H[1]/(e.shape[1]||1),(H[2]||0)/Ge]);for(let H of Object.keys(Ie))w.annotations[H]=[w.mesh[Ie[H]]]}}else{let H=j.find(E=>E.shape[E.shape.length-1]===1404),Y=Be.reshape(H,[-1,3]),J=await Y.array();Be.dispose(Y),(m=t.face.attention)!=null&&m.enabled?J=await F3(J,j):(P=t.face.iris)!=null&&P.enabled&&(J=await O3(J,w.tensor,t,Ge)),w.mesh=_t(J,d,M,S,Ge),w.meshRaw=w.mesh.map(E=>[E[0]/(e.shape[2]||0),E[1]/(e.shape[1]||0),(E[2]||0)/Ge]);for(let E of Object.keys(X0))w.annotations[E]=X0[E].map(G0=>w.mesh[G0]);w.score=w.faceScore;let x0={...e3(w.mesh,d),confidence:d.confidence,landmarks:d.landmarks};w.box=q2(x0,e),w.boxRaw=U2(x0,e),A.push(x0)}Be.dispose(j)}else{w.box=q2(d,e),w.boxRaw=U2(d,e),w.score=w.boxScore,w.mesh=d.landmarks.map(j=>[(d.startPoint[0]+d.endPoint[0])/2+(d.endPoint[0]+d.startPoint[0])*j[0]/Qe(),(d.startPoint[1]+d.endPoint[1])/2+(d.endPoint[1]+d.startPoint[1])*j[1]/Qe()]),w.meshRaw=w.mesh.map(j=>[j[0]/(e.shape[2]||0),j[1]/(e.shape[1]||0),(j[2]||0)/Ge]);for(let j of Object.keys(Ie))w.annotations[j]=[w.mesh[Ie[j]]]}w.score>(((g=t.face.detector)==null?void 0:g.minConfidence)||1)?r.push(w):Be.dispose(w.tensor)}return oe.boxes=A,r}async function B3(e){var t,o,n,r,A,s;return v.initial&&(g0=null),((o=(t=e==null?void 0:e.face)==null?void 0:t.attention)==null?void 0:o.enabled)&&(g0==null?void 0:g0.signature)&&Object.keys(((n=g0==null?void 0:g0.signature)==null?void 0:n.outputs)||{}).length<6&&(g0=null),g0?e.debug&&p("cached model:",g0.modelUrl):(r=e.face.attention)!=null&&r.enabled?g0=await G((A=e.face.attention)==null?void 0:A.modelPath):g0=await G((s=e.face.mesh)==null?void 0:s.modelPath),Ge=g0.inputs[0].shape?g0.inputs[0].shape[2]:0,g0}var H3=Ne,V3=R2;var K0=Z(D());var O0,r5=[],D3=0,Z3=0,u1=Number.MAX_SAFE_INTEGER;async function X3(e){var t;return v.initial&&(O0=null),O0?e.debug&&p("cached model:",O0.modelUrl):O0=await G((t=e.face.description)==null?void 0:t.modelPath),O0}function h1(e){let t=e.image||e.tensor||e;if(!(O0!=null&&O0.inputs[0].shape))return t;let o=K0.image.resizeBilinear(t,[O0.inputs[0].shape[2],O0.inputs[0].shape[1]],!1),n=K0.mul(o,V.tf255);return K0.dispose(o),n}async function b1(e,t,o,n){var s,a,i,x;if(!O0)return{age:0,gender:"unknown",genderScore:0,descriptor:[]};let r=u1<(((s=t.face.description)==null?void 0:s.skipFrames)||0),A=(((a=t.face.description)==null?void 0:a.skipTime)||0)>h()-D3;return t.skipAllowed&&r&&A&&Z3===n&&((i=r5[o])==null?void 0:i.age)&&((x=r5[o])==null?void 0:x.age)>0?(u1++,r5[o]):(u1=0,new Promise(async c=>{var y,f;let l={age:0,gender:"unknown",genderScore:0,descriptor:[]};if((y=t.face.description)!=null&&y.enabled){let u=h1(e),m=O0==null?void 0:O0.execute(u);D3=h(),K0.dispose(u);let g=await(await m.find(F=>F.shape[1]===1)).data(),b=Math.trunc(200*Math.abs(g[0]-.5))/100;b>(((f=t.face.description)==null?void 0:f.minConfidence)||0)&&(l.gender=g[0]<=.5?"female":"male",l.genderScore=Math.min(.99,b));let d=K0.argMax(m.find(F=>F.shape[1]===100),1),M=(await d.data())[0];K0.dispose(d);let w=await m.find(F=>F.shape[1]===100).data();l.age=Math.round(w[M-1]>w[M+1]?10*M-100*w[M-1]:10*M+100*w[M+1])/10;let j=m.find(F=>F.shape[1]===1024),C=j?await j.data():[];l.descriptor=Array.from(C),m.forEach(F=>K0.dispose(F))}r5[o]=l,Z3=n,c(l)}))}var W=Z(D());var Y3=Z(D());function A5(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function k2(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function K3(e,t,o){let n=t.shape[1],r=t.shape[2],A=[[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r]];return Y3.image.cropAndResize(t,A,[0],o)}function J3(e,t){let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],r=e.palmLandmarks.map(A=>[A[0]*t[0],A[1]*t[1]]);return{startPoint:o,endPoint:n,palmLandmarks:r,confidence:e.confidence}}function s5(e,t=1.5){let o=k2(e),n=A5(e),r=[t*n[0]/2,t*n[1]/2],A=[o[0]-r[0],o[1]-r[1]],s=[o[0]+r[0],o[1]+r[1]];return{startPoint:A,endPoint:s,palmLandmarks:e.palmLandmarks}}function a5(e){let t=k2(e),o=A5(e),r=Math.max(...o)/2,A=[t[0]-r,t[1]-r],s=[t[0]+r,t[1]+r];return{startPoint:A,endPoint:s,palmLandmarks:e.palmLandmarks}}function sA(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function Q3(e,t){let o=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return sA(o)}var q3=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function Te(e,t){let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o}function aA(e,t){let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o}function U3(e,t){let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let A=0;A<n;A++)o[r].push(Te(e[r],aA(t,A)))}return o}function M1(e,t){let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],A=q3(t[0],t[1]),s=U3(A,r),a=q3(-t[0],-t[1]);return U3(s,a)}function _3(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-Te(t[0],o),-Te(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]}function P1(e,t){return[Te(e,t[0]),Te(e,t[1])]}var eo=[{x:.015625,y:.015625},{x:.015625,y:.015625},{x:.046875,y:.015625},{x:.046875,y:.015625},{x:.078125,y:.015625},{x:.078125,y:.015625},{x:.109375,y:.015625},{x:.109375,y:.015625},{x:.140625,y:.015625},{x:.140625,y:.015625},{x:.171875,y:.015625},{x:.171875,y:.015625},{x:.203125,y:.015625},{x:.203125,y:.015625},{x:.234375,y:.015625},{x:.234375,y:.015625},{x:.265625,y:.015625},{x:.265625,y:.015625},{x:.296875,y:.015625},{x:.296875,y:.015625},{x:.328125,y:.015625},{x:.328125,y:.015625},{x:.359375,y:.015625},{x:.359375,y:.015625},{x:.390625,y:.015625},{x:.390625,y:.015625},{x:.421875,y:.015625},{x:.421875,y:.015625},{x:.453125,y:.015625},{x:.453125,y:.015625},{x:.484375,y:.015625},{x:.484375,y:.015625},{x:.515625,y:.015625},{x:.515625,y:.015625},{x:.546875,y:.015625},{x:.546875,y:.015625},{x:.578125,y:.015625},{x:.578125,y:.015625},{x:.609375,y:.015625},{x:.609375,y:.015625},{x:.640625,y:.015625},{x:.640625,y:.015625},{x:.671875,y:.015625},{x:.671875,y:.015625},{x:.703125,y:.015625},{x:.703125,y:.015625},{x:.734375,y:.015625},{x:.734375,y:.015625},{x:.765625,y:.015625},{x:.765625,y:.015625},{x:.796875,y:.015625},{x:.796875,y:.015625},{x:.828125,y:.015625},{x:.828125,y:.015625},{x:.859375,y:.015625},{x:.859375,y:.015625},{x:.890625,y:.015625},{x:.890625,y:.015625},{x:.921875,y:.015625},{x:.921875,y:.015625},{x:.953125,y:.015625},{x:.953125,y:.015625},{x:.984375,y:.015625},{x:.984375,y:.015625},{x:.015625,y:.046875},{x:.015625,y:.046875},{x:.046875,y:.046875},{x:.046875,y:.046875},{x:.078125,y:.046875},{x:.078125,y:.046875},{x:.109375,y:.046875},{x:.109375,y:.046875},{x:.140625,y:.046875},{x:.140625,y:.046875},{x:.171875,y:.046875},{x:.171875,y:.046875},{x:.203125,y:.046875},{x:.203125,y:.046875},{x:.234375,y:.046875},{x:.234375,y:.046875},{x:.265625,y:.046875},{x:.265625,y:.046875},{x:.296875,y:.046875},{x:.296875,y:.046875},{x:.328125,y:.046875},{x:.328125,y:.046875},{x:.359375,y:.046875},{x:.359375,y:.046875},{x:.390625,y:.046875},{x:.390625,y:.046875},{x:.421875,y:.046875},{x:.421875,y:.046875},{x:.453125,y:.046875},{x:.453125,y:.046875},{x:.484375,y:.046875},{x:.484375,y:.046875},{x:.515625,y:.046875},{x:.515625,y:.046875},{x:.546875,y:.046875},{x:.546875,y:.046875},{x:.578125,y:.046875},{x:.578125,y:.046875},{x:.609375,y:.046875},{x:.609375,y:.046875},{x:.640625,y:.046875},{x:.640625,y:.046875},{x:.671875,y:.046875},{x:.671875,y:.046875},{x:.703125,y:.046875},{x:.703125,y:.046875},{x:.734375,y:.046875},{x:.734375,y:.046875},{x:.765625,y:.046875},{x:.765625,y:.046875},{x:.796875,y:.046875},{x:.796875,y:.046875},{x:.828125,y:.046875},{x:.828125,y:.046875},{x:.859375,y:.046875},{x:.859375,y:.046875},{x:.890625,y:.046875},{x:.890625,y:.046875},{x:.921875,y:.046875},{x:.921875,y:.046875},{x:.953125,y:.046875},{x:.953125,y:.046875},{x:.984375,y:.046875},{x:.984375,y:.046875},{x:.015625,y:.078125},{x:.015625,y:.078125},{x:.046875,y:.078125},{x:.046875,y:.078125},{x:.078125,y:.078125},{x:.078125,y:.078125},{x:.109375,y:.078125},{x:.109375,y:.078125},{x:.140625,y:.078125},{x:.140625,y:.078125},{x:.171875,y:.078125},{x:.171875,y:.078125},{x:.203125,y:.078125},{x:.203125,y:.078125},{x:.234375,y:.078125},{x:.234375,y:.078125},{x:.265625,y:.078125},{x:.265625,y:.078125},{x:.296875,y:.078125},{x:.296875,y:.078125},{x:.328125,y:.078125},{x:.328125,y:.078125},{x:.359375,y:.078125},{x:.359375,y:.078125},{x:.390625,y:.078125},{x:.390625,y:.078125},{x:.421875,y:.078125},{x:.421875,y:.078125},{x:.453125,y:.078125},{x:.453125,y:.078125},{x:.484375,y:.078125},{x:.484375,y:.078125},{x:.515625,y:.078125},{x:.515625,y:.078125},{x:.546875,y:.078125},{x:.546875,y:.078125},{x:.578125,y:.078125},{x:.578125,y:.078125},{x:.609375,y:.078125},{x:.609375,y:.078125},{x:.640625,y:.078125},{x:.640625,y:.078125},{x:.671875,y:.078125},{x:.671875,y:.078125},{x:.703125,y:.078125},{x:.703125,y:.078125},{x:.734375,y:.078125},{x:.734375,y:.078125},{x:.765625,y:.078125},{x:.765625,y:.078125},{x:.796875,y:.078125},{x:.796875,y:.078125},{x:.828125,y:.078125},{x:.828125,y:.078125},{x:.859375,y:.078125},{x:.859375,y:.078125},{x:.890625,y:.078125},{x:.890625,y:.078125},{x:.921875,y:.078125},{x:.921875,y:.078125},{x:.953125,y:.078125},{x:.953125,y:.078125},{x:.984375,y:.078125},{x:.984375,y:.078125},{x:.015625,y:.109375},{x:.015625,y:.109375},{x:.046875,y:.109375},{x:.046875,y:.109375},{x:.078125,y:.109375},{x:.078125,y:.109375},{x:.109375,y:.109375},{x:.109375,y:.109375},{x:.140625,y:.109375},{x:.140625,y:.109375},{x:.171875,y:.109375},{x:.171875,y:.109375},{x:.203125,y:.109375},{x:.203125,y:.109375},{x:.234375,y:.109375},{x:.234375,y:.109375},{x:.265625,y:.109375},{x:.265625,y:.109375},{x:.296875,y:.109375},{x:.296875,y:.109375},{x:.328125,y:.109375},{x:.328125,y:.109375},{x:.359375,y:.109375},{x:.359375,y:.109375},{x:.390625,y:.109375},{x:.390625,y:.109375},{x:.421875,y:.109375},{x:.421875,y:.109375},{x:.453125,y:.109375},{x:.453125,y:.109375},{x:.484375,y:.109375},{x:.484375,y:.109375},{x:.515625,y:.109375},{x:.515625,y:.109375},{x:.546875,y:.109375},{x:.546875,y:.109375},{x:.578125,y:.109375},{x:.578125,y:.109375},{x:.609375,y:.109375},{x:.609375,y:.109375},{x:.640625,y:.109375},{x:.640625,y:.109375},{x:.671875,y:.109375},{x:.671875,y:.109375},{x:.703125,y:.109375},{x:.703125,y:.109375},{x:.734375,y:.109375},{x:.734375,y:.109375},{x:.765625,y:.109375},{x:.765625,y:.109375},{x:.796875,y:.109375},{x:.796875,y:.109375},{x:.828125,y:.109375},{x:.828125,y:.109375},{x:.859375,y:.109375},{x:.859375,y:.109375},{x:.890625,y:.109375},{x:.890625,y:.109375},{x:.921875,y:.109375},{x:.921875,y:.109375},{x:.953125,y:.109375},{x:.953125,y:.109375},{x:.984375,y:.109375},{x:.984375,y:.109375},{x:.015625,y:.140625},{x:.015625,y:.140625},{x:.046875,y:.140625},{x:.046875,y:.140625},{x:.078125,y:.140625},{x:.078125,y:.140625},{x:.109375,y:.140625},{x:.109375,y:.140625},{x:.140625,y:.140625},{x:.140625,y:.140625},{x:.171875,y:.140625},{x:.171875,y:.140625},{x:.203125,y:.140625},{x:.203125,y:.140625},{x:.234375,y:.140625},{x:.234375,y:.140625},{x:.265625,y:.140625},{x:.265625,y:.140625},{x:.296875,y:.140625},{x:.296875,y:.140625},{x:.328125,y:.140625},{x:.328125,y:.140625},{x:.359375,y:.140625},{x:.359375,y:.140625},{x:.390625,y:.140625},{x:.390625,y:.140625},{x:.421875,y:.140625},{x:.421875,y:.140625},{x:.453125,y:.140625},{x:.453125,y:.140625},{x:.484375,y:.140625},{x:.484375,y:.140625},{x:.515625,y:.140625},{x:.515625,y:.140625},{x:.546875,y:.140625},{x:.546875,y:.140625},{x:.578125,y:.140625},{x:.578125,y:.140625},{x:.609375,y:.140625},{x:.609375,y:.140625},{x:.640625,y:.140625},{x:.640625,y:.140625},{x:.671875,y:.140625},{x:.671875,y:.140625},{x:.703125,y:.140625},{x:.703125,y:.140625},{x:.734375,y:.140625},{x:.734375,y:.140625},{x:.765625,y:.140625},{x:.765625,y:.140625},{x:.796875,y:.140625},{x:.796875,y:.140625},{x:.828125,y:.140625},{x:.828125,y:.140625},{x:.859375,y:.140625},{x:.859375,y:.140625},{x:.890625,y:.140625},{x:.890625,y:.140625},{x:.921875,y:.140625},{x:.921875,y:.140625},{x:.953125,y:.140625},{x:.953125,y:.140625},{x:.984375,y:.140625},{x:.984375,y:.140625},{x:.015625,y:.171875},{x:.015625,y:.171875},{x:.046875,y:.171875},{x:.046875,y:.171875},{x:.078125,y:.171875},{x:.078125,y:.171875},{x:.109375,y:.171875},{x:.109375,y:.171875},{x:.140625,y:.171875},{x:.140625,y:.171875},{x:.171875,y:.171875},{x:.171875,y:.171875},{x:.203125,y:.171875},{x:.203125,y:.171875},{x:.234375,y:.171875},{x:.234375,y:.171875},{x:.265625,y:.171875},{x:.265625,y:.171875},{x:.296875,y:.171875},{x:.296875,y:.171875},{x:.328125,y:.171875},{x:.328125,y:.171875},{x:.359375,y:.171875},{x:.359375,y:.171875},{x:.390625,y:.171875},{x:.390625,y:.171875},{x:.421875,y:.171875},{x:.421875,y:.171875},{x:.453125,y:.171875},{x:.453125,y:.171875},{x:.484375,y:.171875},{x:.484375,y:.171875},{x:.515625,y:.171875},{x:.515625,y:.171875},{x:.546875,y:.171875},{x:.546875,y:.171875},{x:.578125,y:.171875},{x:.578125,y:.171875},{x:.609375,y:.171875},{x:.609375,y:.171875},{x:.640625,y:.171875},{x:.640625,y:.171875},{x:.671875,y:.171875},{x:.671875,y:.171875},{x:.703125,y:.171875},{x:.703125,y:.171875},{x:.734375,y:.171875},{x:.734375,y:.171875},{x:.765625,y:.171875},{x:.765625,y:.171875},{x:.796875,y:.171875},{x:.796875,y:.171875},{x:.828125,y:.171875},{x:.828125,y:.171875},{x:.859375,y:.171875},{x:.859375,y:.171875},{x:.890625,y:.171875},{x:.890625,y:.171875},{x:.921875,y:.171875},{x:.921875,y:.171875},{x:.953125,y:.171875},{x:.953125,y:.171875},{x:.984375,y:.171875},{x:.984375,y:.171875},{x:.015625,y:.203125},{x:.015625,y:.203125},{x:.046875,y:.203125},{x:.046875,y:.203125},{x:.078125,y:.203125},{x:.078125,y:.203125},{x:.109375,y:.203125},{x:.109375,y:.203125},{x:.140625,y:.203125},{x:.140625,y:.203125},{x:.171875,y:.203125},{x:.171875,y:.203125},{x:.203125,y:.203125},{x:.203125,y:.203125},{x:.234375,y:.203125},{x:.234375,y:.203125},{x:.265625,y:.203125},{x:.265625,y:.203125},{x:.296875,y:.203125},{x:.296875,y:.203125},{x:.328125,y:.203125},{x:.328125,y:.203125},{x:.359375,y:.203125},{x:.359375,y:.203125},{x:.390625,y:.203125},{x:.390625,y:.203125},{x:.421875,y:.203125},{x:.421875,y:.203125},{x:.453125,y:.203125},{x:.453125,y:.203125},{x:.484375,y:.203125},{x:.484375,y:.203125},{x:.515625,y:.203125},{x:.515625,y:.203125},{x:.546875,y:.203125},{x:.546875,y:.203125},{x:.578125,y:.203125},{x:.578125,y:.203125},{x:.609375,y:.203125},{x:.609375,y:.203125},{x:.640625,y:.203125},{x:.640625,y:.203125},{x:.671875,y:.203125},{x:.671875,y:.203125},{x:.703125,y:.203125},{x:.703125,y:.203125},{x:.734375,y:.203125},{x:.734375,y:.203125},{x:.765625,y:.203125},{x:.765625,y:.203125},{x:.796875,y:.203125},{x:.796875,y:.203125},{x:.828125,y:.203125},{x:.828125,y:.203125},{x:.859375,y:.203125},{x:.859375,y:.203125},{x:.890625,y:.203125},{x:.890625,y:.203125},{x:.921875,y:.203125},{x:.921875,y:.203125},{x:.953125,y:.203125},{x:.953125,y:.203125},{x:.984375,y:.203125},{x:.984375,y:.203125},{x:.015625,y:.234375},{x:.015625,y:.234375},{x:.046875,y:.234375},{x:.046875,y:.234375},{x:.078125,y:.234375},{x:.078125,y:.234375},{x:.109375,y:.234375},{x:.109375,y:.234375},{x:.140625,y:.234375},{x:.140625,y:.234375},{x:.171875,y:.234375},{x:.171875,y:.234375},{x:.203125,y:.234375},{x:.203125,y:.234375},{x:.234375,y:.234375},{x:.234375,y:.234375},{x:.265625,y:.234375},{x:.265625,y:.234375},{x:.296875,y:.234375},{x:.296875,y:.234375},{x:.328125,y:.234375},{x:.328125,y:.234375},{x:.359375,y:.234375},{x:.359375,y:.234375},{x:.390625,y:.234375},{x:.390625,y:.234375},{x:.421875,y:.234375},{x:.421875,y:.234375},{x:.453125,y:.234375},{x:.453125,y:.234375},{x:.484375,y:.234375},{x:.484375,y:.234375},{x:.515625,y:.234375},{x:.515625,y:.234375},{x:.546875,y:.234375},{x:.546875,y:.234375},{x:.578125,y:.234375},{x:.578125,y:.234375},{x:.609375,y:.234375},{x:.609375,y:.234375},{x:.640625,y:.234375},{x:.640625,y:.234375},{x:.671875,y:.234375},{x:.671875,y:.234375},{x:.703125,y:.234375},{x:.703125,y:.234375},{x:.734375,y:.234375},{x:.734375,y:.234375},{x:.765625,y:.234375},{x:.765625,y:.234375},{x:.796875,y:.234375},{x:.796875,y:.234375},{x:.828125,y:.234375},{x:.828125,y:.234375},{x:.859375,y:.234375},{x:.859375,y:.234375},{x:.890625,y:.234375},{x:.890625,y:.234375},{x:.921875,y:.234375},{x:.921875,y:.234375},{x:.953125,y:.234375},{x:.953125,y:.234375},{x:.984375,y:.234375},{x:.984375,y:.234375},{x:.015625,y:.265625},{x:.015625,y:.265625},{x:.046875,y:.265625},{x:.046875,y:.265625},{x:.078125,y:.265625},{x:.078125,y:.265625},{x:.109375,y:.265625},{x:.109375,y:.265625},{x:.140625,y:.265625},{x:.140625,y:.265625},{x:.171875,y:.265625},{x:.171875,y:.265625},{x:.203125,y:.265625},{x:.203125,y:.265625},{x:.234375,y:.265625},{x:.234375,y:.265625},{x:.265625,y:.265625},{x:.265625,y:.265625},{x:.296875,y:.265625},{x:.296875,y:.265625},{x:.328125,y:.265625},{x:.328125,y:.265625},{x:.359375,y:.265625},{x:.359375,y:.265625},{x:.390625,y:.265625},{x:.390625,y:.265625},{x:.421875,y:.265625},{x:.421875,y:.265625},{x:.453125,y:.265625},{x:.453125,y:.265625},{x:.484375,y:.265625},{x:.484375,y:.265625},{x:.515625,y:.265625},{x:.515625,y:.265625},{x:.546875,y:.265625},{x:.546875,y:.265625},{x:.578125,y:.265625},{x:.578125,y:.265625},{x:.609375,y:.265625},{x:.609375,y:.265625},{x:.640625,y:.265625},{x:.640625,y:.265625},{x:.671875,y:.265625},{x:.671875,y:.265625},{x:.703125,y:.265625},{x:.703125,y:.265625},{x:.734375,y:.265625},{x:.734375,y:.265625},{x:.765625,y:.265625},{x:.765625,y:.265625},{x:.796875,y:.265625},{x:.796875,y:.265625},{x:.828125,y:.265625},{x:.828125,y:.265625},{x:.859375,y:.265625},{x:.859375,y:.265625},{x:.890625,y:.265625},{x:.890625,y:.265625},{x:.921875,y:.265625},{x:.921875,y:.265625},{x:.953125,y:.265625},{x:.953125,y:.265625},{x:.984375,y:.265625},{x:.984375,y:.265625},{x:.015625,y:.296875},{x:.015625,y:.296875},{x:.046875,y:.296875},{x:.046875,y:.296875},{x:.078125,y:.296875},{x:.078125,y:.296875},{x:.109375,y:.296875},{x:.109375,y:.296875},{x:.140625,y:.296875},{x:.140625,y:.296875},{x:.171875,y:.296875},{x:.171875,y:.296875},{x:.203125,y:.296875},{x:.203125,y:.296875},{x:.234375,y:.296875},{x:.234375,y:.296875},{x:.265625,y:.296875},{x:.265625,y:.296875},{x:.296875,y:.296875},{x:.296875,y:.296875},{x:.328125,y:.296875},{x:.328125,y:.296875},{x:.359375,y:.296875},{x:.359375,y:.296875},{x:.390625,y:.296875},{x:.390625,y:.296875},{x:.421875,y:.296875},{x:.421875,y:.296875},{x:.453125,y:.296875},{x:.453125,y:.296875},{x:.484375,y:.296875},{x:.484375,y:.296875},{x:.515625,y:.296875},{x:.515625,y:.296875},{x:.546875,y:.296875},{x:.546875,y:.296875},{x:.578125,y:.296875},{x:.578125,y:.296875},{x:.609375,y:.296875},{x:.609375,y:.296875},{x:.640625,y:.296875},{x:.640625,y:.296875},{x:.671875,y:.296875},{x:.671875,y:.296875},{x:.703125,y:.296875},{x:.703125,y:.296875},{x:.734375,y:.296875},{x:.734375,y:.296875},{x:.765625,y:.296875},{x:.765625,y:.296875},{x:.796875,y:.296875},{x:.796875,y:.296875},{x:.828125,y:.296875},{x:.828125,y:.296875},{x:.859375,y:.296875},{x:.859375,y:.296875},{x:.890625,y:.296875},{x:.890625,y:.296875},{x:.921875,y:.296875},{x:.921875,y:.296875},{x:.953125,y:.296875},{x:.953125,y:.296875},{x:.984375,y:.296875},{x:.984375,y:.296875},{x:.015625,y:.328125},{x:.015625,y:.328125},{x:.046875,y:.328125},{x:.046875,y:.328125},{x:.078125,y:.328125},{x:.078125,y:.328125},{x:.109375,y:.328125},{x:.109375,y:.328125},{x:.140625,y:.328125},{x:.140625,y:.328125},{x:.171875,y:.328125},{x:.171875,y:.328125},{x:.203125,y:.328125},{x:.203125,y:.328125},{x:.234375,y:.328125},{x:.234375,y:.328125},{x:.265625,y:.328125},{x:.265625,y:.328125},{x:.296875,y:.328125},{x:.296875,y:.328125},{x:.328125,y:.328125},{x:.328125,y:.328125},{x:.359375,y:.328125},{x:.359375,y:.328125},{x:.390625,y:.328125},{x:.390625,y:.328125},{x:.421875,y:.328125},{x:.421875,y:.328125},{x:.453125,y:.328125},{x:.453125,y:.328125},{x:.484375,y:.328125},{x:.484375,y:.328125},{x:.515625,y:.328125},{x:.515625,y:.328125},{x:.546875,y:.328125},{x:.546875,y:.328125},{x:.578125,y:.328125},{x:.578125,y:.328125},{x:.609375,y:.328125},{x:.609375,y:.328125},{x:.640625,y:.328125},{x:.640625,y:.328125},{x:.671875,y:.328125},{x:.671875,y:.328125},{x:.703125,y:.328125},{x:.703125,y:.328125},{x:.734375,y:.328125},{x:.734375,y:.328125},{x:.765625,y:.328125},{x:.765625,y:.328125},{x:.796875,y:.328125},{x:.796875,y:.328125},{x:.828125,y:.328125},{x:.828125,y:.328125},{x:.859375,y:.328125},{x:.859375,y:.328125},{x:.890625,y:.328125},{x:.890625,y:.328125},{x:.921875,y:.328125},{x:.921875,y:.328125},{x:.953125,y:.328125},{x:.953125,y:.328125},{x:.984375,y:.328125},{x:.984375,y:.328125},{x:.015625,y:.359375},{x:.015625,y:.359375},{x:.046875,y:.359375},{x:.046875,y:.359375},{x:.078125,y:.359375},{x:.078125,y:.359375},{x:.109375,y:.359375},{x:.109375,y:.359375},{x:.140625,y:.359375},{x:.140625,y:.359375},{x:.171875,y:.359375},{x:.171875,y:.359375},{x:.203125,y:.359375},{x:.203125,y:.359375},{x:.234375,y:.359375},{x:.234375,y:.359375},{x:.265625,y:.359375},{x:.265625,y:.359375},{x:.296875,y:.359375},{x:.296875,y:.359375},{x:.328125,y:.359375},{x:.328125,y:.359375},{x:.359375,y:.359375},{x:.359375,y:.359375},{x:.390625,y:.359375},{x:.390625,y:.359375},{x:.421875,y:.359375},{x:.421875,y:.359375},{x:.453125,y:.359375},{x:.453125,y:.359375},{x:.484375,y:.359375},{x:.484375,y:.359375},{x:.515625,y:.359375},{x:.515625,y:.359375},{x:.546875,y:.359375},{x:.546875,y:.359375},{x:.578125,y:.359375},{x:.578125,y:.359375},{x:.609375,y:.359375},{x:.609375,y:.359375},{x:.640625,y:.359375},{x:.640625,y:.359375},{x:.671875,y:.359375},{x:.671875,y:.359375},{x:.703125,y:.359375},{x:.703125,y:.359375},{x:.734375,y:.359375},{x:.734375,y:.359375},{x:.765625,y:.359375},{x:.765625,y:.359375},{x:.796875,y:.359375},{x:.796875,y:.359375},{x:.828125,y:.359375},{x:.828125,y:.359375},{x:.859375,y:.359375},{x:.859375,y:.359375},{x:.890625,y:.359375},{x:.890625,y:.359375},{x:.921875,y:.359375},{x:.921875,y:.359375},{x:.953125,y:.359375},{x:.953125,y:.359375},{x:.984375,y:.359375},{x:.984375,y:.359375},{x:.015625,y:.390625},{x:.015625,y:.390625},{x:.046875,y:.390625},{x:.046875,y:.390625},{x:.078125,y:.390625},{x:.078125,y:.390625},{x:.109375,y:.390625},{x:.109375,y:.390625},{x:.140625,y:.390625},{x:.140625,y:.390625},{x:.171875,y:.390625},{x:.171875,y:.390625},{x:.203125,y:.390625},{x:.203125,y:.390625},{x:.234375,y:.390625},{x:.234375,y:.390625},{x:.265625,y:.390625},{x:.265625,y:.390625},{x:.296875,y:.390625},{x:.296875,y:.390625},{x:.328125,y:.390625},{x:.328125,y:.390625},{x:.359375,y:.390625},{x:.359375,y:.390625},{x:.390625,y:.390625},{x:.390625,y:.390625},{x:.421875,y:.390625},{x:.421875,y:.390625},{x:.453125,y:.390625},{x:.453125,y:.390625},{x:.484375,y:.390625},{x:.484375,y:.390625},{x:.515625,y:.390625},{x:.515625,y:.390625},{x:.546875,y:.390625},{x:.546875,y:.390625},{x:.578125,y:.390625},{x:.578125,y:.390625},{x:.609375,y:.390625},{x:.609375,y:.390625},{x:.640625,y:.390625},{x:.640625,y:.390625},{x:.671875,y:.390625},{x:.671875,y:.390625},{x:.703125,y:.390625},{x:.703125,y:.390625},{x:.734375,y:.390625},{x:.734375,y:.390625},{x:.765625,y:.390625},{x:.765625,y:.390625},{x:.796875,y:.390625},{x:.796875,y:.390625},{x:.828125,y:.390625},{x:.828125,y:.390625},{x:.859375,y:.390625},{x:.859375,y:.390625},{x:.890625,y:.390625},{x:.890625,y:.390625},{x:.921875,y:.390625},{x:.921875,y:.390625},{x:.953125,y:.390625},{x:.953125,y:.390625},{x:.984375,y:.390625},{x:.984375,y:.390625},{x:.015625,y:.421875},{x:.015625,y:.421875},{x:.046875,y:.421875},{x:.046875,y:.421875},{x:.078125,y:.421875},{x:.078125,y:.421875},{x:.109375,y:.421875},{x:.109375,y:.421875},{x:.140625,y:.421875},{x:.140625,y:.421875},{x:.171875,y:.421875},{x:.171875,y:.421875},{x:.203125,y:.421875},{x:.203125,y:.421875},{x:.234375,y:.421875},{x:.234375,y:.421875},{x:.265625,y:.421875},{x:.265625,y:.421875},{x:.296875,y:.421875},{x:.296875,y:.421875},{x:.328125,y:.421875},{x:.328125,y:.421875},{x:.359375,y:.421875},{x:.359375,y:.421875},{x:.390625,y:.421875},{x:.390625,y:.421875},{x:.421875,y:.421875},{x:.421875,y:.421875},{x:.453125,y:.421875},{x:.453125,y:.421875},{x:.484375,y:.421875},{x:.484375,y:.421875},{x:.515625,y:.421875},{x:.515625,y:.421875},{x:.546875,y:.421875},{x:.546875,y:.421875},{x:.578125,y:.421875},{x:.578125,y:.421875},{x:.609375,y:.421875},{x:.609375,y:.421875},{x:.640625,y:.421875},{x:.640625,y:.421875},{x:.671875,y:.421875},{x:.671875,y:.421875},{x:.703125,y:.421875},{x:.703125,y:.421875},{x:.734375,y:.421875},{x:.734375,y:.421875},{x:.765625,y:.421875},{x:.765625,y:.421875},{x:.796875,y:.421875},{x:.796875,y:.421875},{x:.828125,y:.421875},{x:.828125,y:.421875},{x:.859375,y:.421875},{x:.859375,y:.421875},{x:.890625,y:.421875},{x:.890625,y:.421875},{x:.921875,y:.421875},{x:.921875,y:.421875},{x:.953125,y:.421875},{x:.953125,y:.421875},{x:.984375,y:.421875},{x:.984375,y:.421875},{x:.015625,y:.453125},{x:.015625,y:.453125},{x:.046875,y:.453125},{x:.046875,y:.453125},{x:.078125,y:.453125},{x:.078125,y:.453125},{x:.109375,y:.453125},{x:.109375,y:.453125},{x:.140625,y:.453125},{x:.140625,y:.453125},{x:.171875,y:.453125},{x:.171875,y:.453125},{x:.203125,y:.453125},{x:.203125,y:.453125},{x:.234375,y:.453125},{x:.234375,y:.453125},{x:.265625,y:.453125},{x:.265625,y:.453125},{x:.296875,y:.453125},{x:.296875,y:.453125},{x:.328125,y:.453125},{x:.328125,y:.453125},{x:.359375,y:.453125},{x:.359375,y:.453125},{x:.390625,y:.453125},{x:.390625,y:.453125},{x:.421875,y:.453125},{x:.421875,y:.453125},{x:.453125,y:.453125},{x:.453125,y:.453125},{x:.484375,y:.453125},{x:.484375,y:.453125},{x:.515625,y:.453125},{x:.515625,y:.453125},{x:.546875,y:.453125},{x:.546875,y:.453125},{x:.578125,y:.453125},{x:.578125,y:.453125},{x:.609375,y:.453125},{x:.609375,y:.453125},{x:.640625,y:.453125},{x:.640625,y:.453125},{x:.671875,y:.453125},{x:.671875,y:.453125},{x:.703125,y:.453125},{x:.703125,y:.453125},{x:.734375,y:.453125},{x:.734375,y:.453125},{x:.765625,y:.453125},{x:.765625,y:.453125},{x:.796875,y:.453125},{x:.796875,y:.453125},{x:.828125,y:.453125},{x:.828125,y:.453125},{x:.859375,y:.453125},{x:.859375,y:.453125},{x:.890625,y:.453125},{x:.890625,y:.453125},{x:.921875,y:.453125},{x:.921875,y:.453125},{x:.953125,y:.453125},{x:.953125,y:.453125},{x:.984375,y:.453125},{x:.984375,y:.453125},{x:.015625,y:.484375},{x:.015625,y:.484375},{x:.046875,y:.484375},{x:.046875,y:.484375},{x:.078125,y:.484375},{x:.078125,y:.484375},{x:.109375,y:.484375},{x:.109375,y:.484375},{x:.140625,y:.484375},{x:.140625,y:.484375},{x:.171875,y:.484375},{x:.171875,y:.484375},{x:.203125,y:.484375},{x:.203125,y:.484375},{x:.234375,y:.484375},{x:.234375,y:.484375},{x:.265625,y:.484375},{x:.265625,y:.484375},{x:.296875,y:.484375},{x:.296875,y:.484375},{x:.328125,y:.484375},{x:.328125,y:.484375},{x:.359375,y:.484375},{x:.359375,y:.484375},{x:.390625,y:.484375},{x:.390625,y:.484375},{x:.421875,y:.484375},{x:.421875,y:.484375},{x:.453125,y:.484375},{x:.453125,y:.484375},{x:.484375,y:.484375},{x:.484375,y:.484375},{x:.515625,y:.484375},{x:.515625,y:.484375},{x:.546875,y:.484375},{x:.546875,y:.484375},{x:.578125,y:.484375},{x:.578125,y:.484375},{x:.609375,y:.484375},{x:.609375,y:.484375},{x:.640625,y:.484375},{x:.640625,y:.484375},{x:.671875,y:.484375},{x:.671875,y:.484375},{x:.703125,y:.484375},{x:.703125,y:.484375},{x:.734375,y:.484375},{x:.734375,y:.484375},{x:.765625,y:.484375},{x:.765625,y:.484375},{x:.796875,y:.484375},{x:.796875,y:.484375},{x:.828125,y:.484375},{x:.828125,y:.484375},{x:.859375,y:.484375},{x:.859375,y:.484375},{x:.890625,y:.484375},{x:.890625,y:.484375},{x:.921875,y:.484375},{x:.921875,y:.484375},{x:.953125,y:.484375},{x:.953125,y:.484375},{x:.984375,y:.484375},{x:.984375,y:.484375},{x:.015625,y:.515625},{x:.015625,y:.515625},{x:.046875,y:.515625},{x:.046875,y:.515625},{x:.078125,y:.515625},{x:.078125,y:.515625},{x:.109375,y:.515625},{x:.109375,y:.515625},{x:.140625,y:.515625},{x:.140625,y:.515625},{x:.171875,y:.515625},{x:.171875,y:.515625},{x:.203125,y:.515625},{x:.203125,y:.515625},{x:.234375,y:.515625},{x:.234375,y:.515625},{x:.265625,y:.515625},{x:.265625,y:.515625},{x:.296875,y:.515625},{x:.296875,y:.515625},{x:.328125,y:.515625},{x:.328125,y:.515625},{x:.359375,y:.515625},{x:.359375,y:.515625},{x:.390625,y:.515625},{x:.390625,y:.515625},{x:.421875,y:.515625},{x:.421875,y:.515625},{x:.453125,y:.515625},{x:.453125,y:.515625},{x:.484375,y:.515625},{x:.484375,y:.515625},{x:.515625,y:.515625},{x:.515625,y:.515625},{x:.546875,y:.515625},{x:.546875,y:.515625},{x:.578125,y:.515625},{x:.578125,y:.515625},{x:.609375,y:.515625},{x:.609375,y:.515625},{x:.640625,y:.515625},{x:.640625,y:.515625},{x:.671875,y:.515625},{x:.671875,y:.515625},{x:.703125,y:.515625},{x:.703125,y:.515625},{x:.734375,y:.515625},{x:.734375,y:.515625},{x:.765625,y:.515625},{x:.765625,y:.515625},{x:.796875,y:.515625},{x:.796875,y:.515625},{x:.828125,y:.515625},{x:.828125,y:.515625},{x:.859375,y:.515625},{x:.859375,y:.515625},{x:.890625,y:.515625},{x:.890625,y:.515625},{x:.921875,y:.515625},{x:.921875,y:.515625},{x:.953125,y:.515625},{x:.953125,y:.515625},{x:.984375,y:.515625},{x:.984375,y:.515625},{x:.015625,y:.546875},{x:.015625,y:.546875},{x:.046875,y:.546875},{x:.046875,y:.546875},{x:.078125,y:.546875},{x:.078125,y:.546875},{x:.109375,y:.546875},{x:.109375,y:.546875},{x:.140625,y:.546875},{x:.140625,y:.546875},{x:.171875,y:.546875},{x:.171875,y:.546875},{x:.203125,y:.546875},{x:.203125,y:.546875},{x:.234375,y:.546875},{x:.234375,y:.546875},{x:.265625,y:.546875},{x:.265625,y:.546875},{x:.296875,y:.546875},{x:.296875,y:.546875},{x:.328125,y:.546875},{x:.328125,y:.546875},{x:.359375,y:.546875},{x:.359375,y:.546875},{x:.390625,y:.546875},{x:.390625,y:.546875},{x:.421875,y:.546875},{x:.421875,y:.546875},{x:.453125,y:.546875},{x:.453125,y:.546875},{x:.484375,y:.546875},{x:.484375,y:.546875},{x:.515625,y:.546875},{x:.515625,y:.546875},{x:.546875,y:.546875},{x:.546875,y:.546875},{x:.578125,y:.546875},{x:.578125,y:.546875},{x:.609375,y:.546875},{x:.609375,y:.546875},{x:.640625,y:.546875},{x:.640625,y:.546875},{x:.671875,y:.546875},{x:.671875,y:.546875},{x:.703125,y:.546875},{x:.703125,y:.546875},{x:.734375,y:.546875},{x:.734375,y:.546875},{x:.765625,y:.546875},{x:.765625,y:.546875},{x:.796875,y:.546875},{x:.796875,y:.546875},{x:.828125,y:.546875},{x:.828125,y:.546875},{x:.859375,y:.546875},{x:.859375,y:.546875},{x:.890625,y:.546875},{x:.890625,y:.546875},{x:.921875,y:.546875},{x:.921875,y:.546875},{x:.953125,y:.546875},{x:.953125,y:.546875},{x:.984375,y:.546875},{x:.984375,y:.546875},{x:.015625,y:.578125},{x:.015625,y:.578125},{x:.046875,y:.578125},{x:.046875,y:.578125},{x:.078125,y:.578125},{x:.078125,y:.578125},{x:.109375,y:.578125},{x:.109375,y:.578125},{x:.140625,y:.578125},{x:.140625,y:.578125},{x:.171875,y:.578125},{x:.171875,y:.578125},{x:.203125,y:.578125},{x:.203125,y:.578125},{x:.234375,y:.578125},{x:.234375,y:.578125},{x:.265625,y:.578125},{x:.265625,y:.578125},{x:.296875,y:.578125},{x:.296875,y:.578125},{x:.328125,y:.578125},{x:.328125,y:.578125},{x:.359375,y:.578125},{x:.359375,y:.578125},{x:.390625,y:.578125},{x:.390625,y:.578125},{x:.421875,y:.578125},{x:.421875,y:.578125},{x:.453125,y:.578125},{x:.453125,y:.578125},{x:.484375,y:.578125},{x:.484375,y:.578125},{x:.515625,y:.578125},{x:.515625,y:.578125},{x:.546875,y:.578125},{x:.546875,y:.578125},{x:.578125,y:.578125},{x:.578125,y:.578125},{x:.609375,y:.578125},{x:.609375,y:.578125},{x:.640625,y:.578125},{x:.640625,y:.578125},{x:.671875,y:.578125},{x:.671875,y:.578125},{x:.703125,y:.578125},{x:.703125,y:.578125},{x:.734375,y:.578125},{x:.734375,y:.578125},{x:.765625,y:.578125},{x:.765625,y:.578125},{x:.796875,y:.578125},{x:.796875,y:.578125},{x:.828125,y:.578125},{x:.828125,y:.578125},{x:.859375,y:.578125},{x:.859375,y:.578125},{x:.890625,y:.578125},{x:.890625,y:.578125},{x:.921875,y:.578125},{x:.921875,y:.578125},{x:.953125,y:.578125},{x:.953125,y:.578125},{x:.984375,y:.578125},{x:.984375,y:.578125},{x:.015625,y:.609375},{x:.015625,y:.609375},{x:.046875,y:.609375},{x:.046875,y:.609375},{x:.078125,y:.609375},{x:.078125,y:.609375},{x:.109375,y:.609375},{x:.109375,y:.609375},{x:.140625,y:.609375},{x:.140625,y:.609375},{x:.171875,y:.609375},{x:.171875,y:.609375},{x:.203125,y:.609375},{x:.203125,y:.609375},{x:.234375,y:.609375},{x:.234375,y:.609375},{x:.265625,y:.609375},{x:.265625,y:.609375},{x:.296875,y:.609375},{x:.296875,y:.609375},{x:.328125,y:.609375},{x:.328125,y:.609375},{x:.359375,y:.609375},{x:.359375,y:.609375},{x:.390625,y:.609375},{x:.390625,y:.609375},{x:.421875,y:.609375},{x:.421875,y:.609375},{x:.453125,y:.609375},{x:.453125,y:.609375},{x:.484375,y:.609375},{x:.484375,y:.609375},{x:.515625,y:.609375},{x:.515625,y:.609375},{x:.546875,y:.609375},{x:.546875,y:.609375},{x:.578125,y:.609375},{x:.578125,y:.609375},{x:.609375,y:.609375},{x:.609375,y:.609375},{x:.640625,y:.609375},{x:.640625,y:.609375},{x:.671875,y:.609375},{x:.671875,y:.609375},{x:.703125,y:.609375},{x:.703125,y:.609375},{x:.734375,y:.609375},{x:.734375,y:.609375},{x:.765625,y:.609375},{x:.765625,y:.609375},{x:.796875,y:.609375},{x:.796875,y:.609375},{x:.828125,y:.609375},{x:.828125,y:.609375},{x:.859375,y:.609375},{x:.859375,y:.609375},{x:.890625,y:.609375},{x:.890625,y:.609375},{x:.921875,y:.609375},{x:.921875,y:.609375},{x:.953125,y:.609375},{x:.953125,y:.609375},{x:.984375,y:.609375},{x:.984375,y:.609375},{x:.015625,y:.640625},{x:.015625,y:.640625},{x:.046875,y:.640625},{x:.046875,y:.640625},{x:.078125,y:.640625},{x:.078125,y:.640625},{x:.109375,y:.640625},{x:.109375,y:.640625},{x:.140625,y:.640625},{x:.140625,y:.640625},{x:.171875,y:.640625},{x:.171875,y:.640625},{x:.203125,y:.640625},{x:.203125,y:.640625},{x:.234375,y:.640625},{x:.234375,y:.640625},{x:.265625,y:.640625},{x:.265625,y:.640625},{x:.296875,y:.640625},{x:.296875,y:.640625},{x:.328125,y:.640625},{x:.328125,y:.640625},{x:.359375,y:.640625},{x:.359375,y:.640625},{x:.390625,y:.640625},{x:.390625,y:.640625},{x:.421875,y:.640625},{x:.421875,y:.640625},{x:.453125,y:.640625},{x:.453125,y:.640625},{x:.484375,y:.640625},{x:.484375,y:.640625},{x:.515625,y:.640625},{x:.515625,y:.640625},{x:.546875,y:.640625},{x:.546875,y:.640625},{x:.578125,y:.640625},{x:.578125,y:.640625},{x:.609375,y:.640625},{x:.609375,y:.640625},{x:.640625,y:.640625},{x:.640625,y:.640625},{x:.671875,y:.640625},{x:.671875,y:.640625},{x:.703125,y:.640625},{x:.703125,y:.640625},{x:.734375,y:.640625},{x:.734375,y:.640625},{x:.765625,y:.640625},{x:.765625,y:.640625},{x:.796875,y:.640625},{x:.796875,y:.640625},{x:.828125,y:.640625},{x:.828125,y:.640625},{x:.859375,y:.640625},{x:.859375,y:.640625},{x:.890625,y:.640625},{x:.890625,y:.640625},{x:.921875,y:.640625},{x:.921875,y:.640625},{x:.953125,y:.640625},{x:.953125,y:.640625},{x:.984375,y:.640625},{x:.984375,y:.640625},{x:.015625,y:.671875},{x:.015625,y:.671875},{x:.046875,y:.671875},{x:.046875,y:.671875},{x:.078125,y:.671875},{x:.078125,y:.671875},{x:.109375,y:.671875},{x:.109375,y:.671875},{x:.140625,y:.671875},{x:.140625,y:.671875},{x:.171875,y:.671875},{x:.171875,y:.671875},{x:.203125,y:.671875},{x:.203125,y:.671875},{x:.234375,y:.671875},{x:.234375,y:.671875},{x:.265625,y:.671875},{x:.265625,y:.671875},{x:.296875,y:.671875},{x:.296875,y:.671875},{x:.328125,y:.671875},{x:.328125,y:.671875},{x:.359375,y:.671875},{x:.359375,y:.671875},{x:.390625,y:.671875},{x:.390625,y:.671875},{x:.421875,y:.671875},{x:.421875,y:.671875},{x:.453125,y:.671875},{x:.453125,y:.671875},{x:.484375,y:.671875},{x:.484375,y:.671875},{x:.515625,y:.671875},{x:.515625,y:.671875},{x:.546875,y:.671875},{x:.546875,y:.671875},{x:.578125,y:.671875},{x:.578125,y:.671875},{x:.609375,y:.671875},{x:.609375,y:.671875},{x:.640625,y:.671875},{x:.640625,y:.671875},{x:.671875,y:.671875},{x:.671875,y:.671875},{x:.703125,y:.671875},{x:.703125,y:.671875},{x:.734375,y:.671875},{x:.734375,y:.671875},{x:.765625,y:.671875},{x:.765625,y:.671875},{x:.796875,y:.671875},{x:.796875,y:.671875},{x:.828125,y:.671875},{x:.828125,y:.671875},{x:.859375,y:.671875},{x:.859375,y:.671875},{x:.890625,y:.671875},{x:.890625,y:.671875},{x:.921875,y:.671875},{x:.921875,y:.671875},{x:.953125,y:.671875},{x:.953125,y:.671875},{x:.984375,y:.671875},{x:.984375,y:.671875},{x:.015625,y:.703125},{x:.015625,y:.703125},{x:.046875,y:.703125},{x:.046875,y:.703125},{x:.078125,y:.703125},{x:.078125,y:.703125},{x:.109375,y:.703125},{x:.109375,y:.703125},{x:.140625,y:.703125},{x:.140625,y:.703125},{x:.171875,y:.703125},{x:.171875,y:.703125},{x:.203125,y:.703125},{x:.203125,y:.703125},{x:.234375,y:.703125},{x:.234375,y:.703125},{x:.265625,y:.703125},{x:.265625,y:.703125},{x:.296875,y:.703125},{x:.296875,y:.703125},{x:.328125,y:.703125},{x:.328125,y:.703125},{x:.359375,y:.703125},{x:.359375,y:.703125},{x:.390625,y:.703125},{x:.390625,y:.703125},{x:.421875,y:.703125},{x:.421875,y:.703125},{x:.453125,y:.703125},{x:.453125,y:.703125},{x:.484375,y:.703125},{x:.484375,y:.703125},{x:.515625,y:.703125},{x:.515625,y:.703125},{x:.546875,y:.703125},{x:.546875,y:.703125},{x:.578125,y:.703125},{x:.578125,y:.703125},{x:.609375,y:.703125},{x:.609375,y:.703125},{x:.640625,y:.703125},{x:.640625,y:.703125},{x:.671875,y:.703125},{x:.671875,y:.703125},{x:.703125,y:.703125},{x:.703125,y:.703125},{x:.734375,y:.703125},{x:.734375,y:.703125},{x:.765625,y:.703125},{x:.765625,y:.703125},{x:.796875,y:.703125},{x:.796875,y:.703125},{x:.828125,y:.703125},{x:.828125,y:.703125},{x:.859375,y:.703125},{x:.859375,y:.703125},{x:.890625,y:.703125},{x:.890625,y:.703125},{x:.921875,y:.703125},{x:.921875,y:.703125},{x:.953125,y:.703125},{x:.953125,y:.703125},{x:.984375,y:.703125},{x:.984375,y:.703125},{x:.015625,y:.734375},{x:.015625,y:.734375},{x:.046875,y:.734375},{x:.046875,y:.734375},{x:.078125,y:.734375},{x:.078125,y:.734375},{x:.109375,y:.734375},{x:.109375,y:.734375},{x:.140625,y:.734375},{x:.140625,y:.734375},{x:.171875,y:.734375},{x:.171875,y:.734375},{x:.203125,y:.734375},{x:.203125,y:.734375},{x:.234375,y:.734375},{x:.234375,y:.734375},{x:.265625,y:.734375},{x:.265625,y:.734375},{x:.296875,y:.734375},{x:.296875,y:.734375},{x:.328125,y:.734375},{x:.328125,y:.734375},{x:.359375,y:.734375},{x:.359375,y:.734375},{x:.390625,y:.734375},{x:.390625,y:.734375},{x:.421875,y:.734375},{x:.421875,y:.734375},{x:.453125,y:.734375},{x:.453125,y:.734375},{x:.484375,y:.734375},{x:.484375,y:.734375},{x:.515625,y:.734375},{x:.515625,y:.734375},{x:.546875,y:.734375},{x:.546875,y:.734375},{x:.578125,y:.734375},{x:.578125,y:.734375},{x:.609375,y:.734375},{x:.609375,y:.734375},{x:.640625,y:.734375},{x:.640625,y:.734375},{x:.671875,y:.734375},{x:.671875,y:.734375},{x:.703125,y:.734375},{x:.703125,y:.734375},{x:.734375,y:.734375},{x:.734375,y:.734375},{x:.765625,y:.734375},{x:.765625,y:.734375},{x:.796875,y:.734375},{x:.796875,y:.734375},{x:.828125,y:.734375},{x:.828125,y:.734375},{x:.859375,y:.734375},{x:.859375,y:.734375},{x:.890625,y:.734375},{x:.890625,y:.734375},{x:.921875,y:.734375},{x:.921875,y:.734375},{x:.953125,y:.734375},{x:.953125,y:.734375},{x:.984375,y:.734375},{x:.984375,y:.734375},{x:.015625,y:.765625},{x:.015625,y:.765625},{x:.046875,y:.765625},{x:.046875,y:.765625},{x:.078125,y:.765625},{x:.078125,y:.765625},{x:.109375,y:.765625},{x:.109375,y:.765625},{x:.140625,y:.765625},{x:.140625,y:.765625},{x:.171875,y:.765625},{x:.171875,y:.765625},{x:.203125,y:.765625},{x:.203125,y:.765625},{x:.234375,y:.765625},{x:.234375,y:.765625},{x:.265625,y:.765625},{x:.265625,y:.765625},{x:.296875,y:.765625},{x:.296875,y:.765625},{x:.328125,y:.765625},{x:.328125,y:.765625},{x:.359375,y:.765625},{x:.359375,y:.765625},{x:.390625,y:.765625},{x:.390625,y:.765625},{x:.421875,y:.765625},{x:.421875,y:.765625},{x:.453125,y:.765625},{x:.453125,y:.765625},{x:.484375,y:.765625},{x:.484375,y:.765625},{x:.515625,y:.765625},{x:.515625,y:.765625},{x:.546875,y:.765625},{x:.546875,y:.765625},{x:.578125,y:.765625},{x:.578125,y:.765625},{x:.609375,y:.765625},{x:.609375,y:.765625},{x:.640625,y:.765625},{x:.640625,y:.765625},{x:.671875,y:.765625},{x:.671875,y:.765625},{x:.703125,y:.765625},{x:.703125,y:.765625},{x:.734375,y:.765625},{x:.734375,y:.765625},{x:.765625,y:.765625},{x:.765625,y:.765625},{x:.796875,y:.765625},{x:.796875,y:.765625},{x:.828125,y:.765625},{x:.828125,y:.765625},{x:.859375,y:.765625},{x:.859375,y:.765625},{x:.890625,y:.765625},{x:.890625,y:.765625},{x:.921875,y:.765625},{x:.921875,y:.765625},{x:.953125,y:.765625},{x:.953125,y:.765625},{x:.984375,y:.765625},{x:.984375,y:.765625},{x:.015625,y:.796875},{x:.015625,y:.796875},{x:.046875,y:.796875},{x:.046875,y:.796875},{x:.078125,y:.796875},{x:.078125,y:.796875},{x:.109375,y:.796875},{x:.109375,y:.796875},{x:.140625,y:.796875},{x:.140625,y:.796875},{x:.171875,y:.796875},{x:.171875,y:.796875},{x:.203125,y:.796875},{x:.203125,y:.796875},{x:.234375,y:.796875},{x:.234375,y:.796875},{x:.265625,y:.796875},{x:.265625,y:.796875},{x:.296875,y:.796875},{x:.296875,y:.796875},{x:.328125,y:.796875},{x:.328125,y:.796875},{x:.359375,y:.796875},{x:.359375,y:.796875},{x:.390625,y:.796875},{x:.390625,y:.796875},{x:.421875,y:.796875},{x:.421875,y:.796875},{x:.453125,y:.796875},{x:.453125,y:.796875},{x:.484375,y:.796875},{x:.484375,y:.796875},{x:.515625,y:.796875},{x:.515625,y:.796875},{x:.546875,y:.796875},{x:.546875,y:.796875},{x:.578125,y:.796875},{x:.578125,y:.796875},{x:.609375,y:.796875},{x:.609375,y:.796875},{x:.640625,y:.796875},{x:.640625,y:.796875},{x:.671875,y:.796875},{x:.671875,y:.796875},{x:.703125,y:.796875},{x:.703125,y:.796875},{x:.734375,y:.796875},{x:.734375,y:.796875},{x:.765625,y:.796875},{x:.765625,y:.796875},{x:.796875,y:.796875},{x:.796875,y:.796875},{x:.828125,y:.796875},{x:.828125,y:.796875},{x:.859375,y:.796875},{x:.859375,y:.796875},{x:.890625,y:.796875},{x:.890625,y:.796875},{x:.921875,y:.796875},{x:.921875,y:.796875},{x:.953125,y:.796875},{x:.953125,y:.796875},{x:.984375,y:.796875},{x:.984375,y:.796875},{x:.015625,y:.828125},{x:.015625,y:.828125},{x:.046875,y:.828125},{x:.046875,y:.828125},{x:.078125,y:.828125},{x:.078125,y:.828125},{x:.109375,y:.828125},{x:.109375,y:.828125},{x:.140625,y:.828125},{x:.140625,y:.828125},{x:.171875,y:.828125},{x:.171875,y:.828125},{x:.203125,y:.828125},{x:.203125,y:.828125},{x:.234375,y:.828125},{x:.234375,y:.828125},{x:.265625,y:.828125},{x:.265625,y:.828125},{x:.296875,y:.828125},{x:.296875,y:.828125},{x:.328125,y:.828125},{x:.328125,y:.828125},{x:.359375,y:.828125},{x:.359375,y:.828125},{x:.390625,y:.828125},{x:.390625,y:.828125},{x:.421875,y:.828125},{x:.421875,y:.828125},{x:.453125,y:.828125},{x:.453125,y:.828125},{x:.484375,y:.828125},{x:.484375,y:.828125},{x:.515625,y:.828125},{x:.515625,y:.828125},{x:.546875,y:.828125},{x:.546875,y:.828125},{x:.578125,y:.828125},{x:.578125,y:.828125},{x:.609375,y:.828125},{x:.609375,y:.828125},{x:.640625,y:.828125},{x:.640625,y:.828125},{x:.671875,y:.828125},{x:.671875,y:.828125},{x:.703125,y:.828125},{x:.703125,y:.828125},{x:.734375,y:.828125},{x:.734375,y:.828125},{x:.765625,y:.828125},{x:.765625,y:.828125},{x:.796875,y:.828125},{x:.796875,y:.828125},{x:.828125,y:.828125},{x:.828125,y:.828125},{x:.859375,y:.828125},{x:.859375,y:.828125},{x:.890625,y:.828125},{x:.890625,y:.828125},{x:.921875,y:.828125},{x:.921875,y:.828125},{x:.953125,y:.828125},{x:.953125,y:.828125},{x:.984375,y:.828125},{x:.984375,y:.828125},{x:.015625,y:.859375},{x:.015625,y:.859375},{x:.046875,y:.859375},{x:.046875,y:.859375},{x:.078125,y:.859375},{x:.078125,y:.859375},{x:.109375,y:.859375},{x:.109375,y:.859375},{x:.140625,y:.859375},{x:.140625,y:.859375},{x:.171875,y:.859375},{x:.171875,y:.859375},{x:.203125,y:.859375},{x:.203125,y:.859375},{x:.234375,y:.859375},{x:.234375,y:.859375},{x:.265625,y:.859375},{x:.265625,y:.859375},{x:.296875,y:.859375},{x:.296875,y:.859375},{x:.328125,y:.859375},{x:.328125,y:.859375},{x:.359375,y:.859375},{x:.359375,y:.859375},{x:.390625,y:.859375},{x:.390625,y:.859375},{x:.421875,y:.859375},{x:.421875,y:.859375},{x:.453125,y:.859375},{x:.453125,y:.859375},{x:.484375,y:.859375},{x:.484375,y:.859375},{x:.515625,y:.859375},{x:.515625,y:.859375},{x:.546875,y:.859375},{x:.546875,y:.859375},{x:.578125,y:.859375},{x:.578125,y:.859375},{x:.609375,y:.859375},{x:.609375,y:.859375},{x:.640625,y:.859375},{x:.640625,y:.859375},{x:.671875,y:.859375},{x:.671875,y:.859375},{x:.703125,y:.859375},{x:.703125,y:.859375},{x:.734375,y:.859375},{x:.734375,y:.859375},{x:.765625,y:.859375},{x:.765625,y:.859375},{x:.796875,y:.859375},{x:.796875,y:.859375},{x:.828125,y:.859375},{x:.828125,y:.859375},{x:.859375,y:.859375},{x:.859375,y:.859375},{x:.890625,y:.859375},{x:.890625,y:.859375},{x:.921875,y:.859375},{x:.921875,y:.859375},{x:.953125,y:.859375},{x:.953125,y:.859375},{x:.984375,y:.859375},{x:.984375,y:.859375},{x:.015625,y:.890625},{x:.015625,y:.890625},{x:.046875,y:.890625},{x:.046875,y:.890625},{x:.078125,y:.890625},{x:.078125,y:.890625},{x:.109375,y:.890625},{x:.109375,y:.890625},{x:.140625,y:.890625},{x:.140625,y:.890625},{x:.171875,y:.890625},{x:.171875,y:.890625},{x:.203125,y:.890625},{x:.203125,y:.890625},{x:.234375,y:.890625},{x:.234375,y:.890625},{x:.265625,y:.890625},{x:.265625,y:.890625},{x:.296875,y:.890625},{x:.296875,y:.890625},{x:.328125,y:.890625},{x:.328125,y:.890625},{x:.359375,y:.890625},{x:.359375,y:.890625},{x:.390625,y:.890625},{x:.390625,y:.890625},{x:.421875,y:.890625},{x:.421875,y:.890625},{x:.453125,y:.890625},{x:.453125,y:.890625},{x:.484375,y:.890625},{x:.484375,y:.890625},{x:.515625,y:.890625},{x:.515625,y:.890625},{x:.546875,y:.890625},{x:.546875,y:.890625},{x:.578125,y:.890625},{x:.578125,y:.890625},{x:.609375,y:.890625},{x:.609375,y:.890625},{x:.640625,y:.890625},{x:.640625,y:.890625},{x:.671875,y:.890625},{x:.671875,y:.890625},{x:.703125,y:.890625},{x:.703125,y:.890625},{x:.734375,y:.890625},{x:.734375,y:.890625},{x:.765625,y:.890625},{x:.765625,y:.890625},{x:.796875,y:.890625},{x:.796875,y:.890625},{x:.828125,y:.890625},{x:.828125,y:.890625},{x:.859375,y:.890625},{x:.859375,y:.890625},{x:.890625,y:.890625},{x:.890625,y:.890625},{x:.921875,y:.890625},{x:.921875,y:.890625},{x:.953125,y:.890625},{x:.953125,y:.890625},{x:.984375,y:.890625},{x:.984375,y:.890625},{x:.015625,y:.921875},{x:.015625,y:.921875},{x:.046875,y:.921875},{x:.046875,y:.921875},{x:.078125,y:.921875},{x:.078125,y:.921875},{x:.109375,y:.921875},{x:.109375,y:.921875},{x:.140625,y:.921875},{x:.140625,y:.921875},{x:.171875,y:.921875},{x:.171875,y:.921875},{x:.203125,y:.921875},{x:.203125,y:.921875},{x:.234375,y:.921875},{x:.234375,y:.921875},{x:.265625,y:.921875},{x:.265625,y:.921875},{x:.296875,y:.921875},{x:.296875,y:.921875},{x:.328125,y:.921875},{x:.328125,y:.921875},{x:.359375,y:.921875},{x:.359375,y:.921875},{x:.390625,y:.921875},{x:.390625,y:.921875},{x:.421875,y:.921875},{x:.421875,y:.921875},{x:.453125,y:.921875},{x:.453125,y:.921875},{x:.484375,y:.921875},{x:.484375,y:.921875},{x:.515625,y:.921875},{x:.515625,y:.921875},{x:.546875,y:.921875},{x:.546875,y:.921875},{x:.578125,y:.921875},{x:.578125,y:.921875},{x:.609375,y:.921875},{x:.609375,y:.921875},{x:.640625,y:.921875},{x:.640625,y:.921875},{x:.671875,y:.921875},{x:.671875,y:.921875},{x:.703125,y:.921875},{x:.703125,y:.921875},{x:.734375,y:.921875},{x:.734375,y:.921875},{x:.765625,y:.921875},{x:.765625,y:.921875},{x:.796875,y:.921875},{x:.796875,y:.921875},{x:.828125,y:.921875},{x:.828125,y:.921875},{x:.859375,y:.921875},{x:.859375,y:.921875},{x:.890625,y:.921875},{x:.890625,y:.921875},{x:.921875,y:.921875},{x:.921875,y:.921875},{x:.953125,y:.921875},{x:.953125,y:.921875},{x:.984375,y:.921875},{x:.984375,y:.921875},{x:.015625,y:.953125},{x:.015625,y:.953125},{x:.046875,y:.953125},{x:.046875,y:.953125},{x:.078125,y:.953125},{x:.078125,y:.953125},{x:.109375,y:.953125},{x:.109375,y:.953125},{x:.140625,y:.953125},{x:.140625,y:.953125},{x:.171875,y:.953125},{x:.171875,y:.953125},{x:.203125,y:.953125},{x:.203125,y:.953125},{x:.234375,y:.953125},{x:.234375,y:.953125},{x:.265625,y:.953125},{x:.265625,y:.953125},{x:.296875,y:.953125},{x:.296875,y:.953125},{x:.328125,y:.953125},{x:.328125,y:.953125},{x:.359375,y:.953125},{x:.359375,y:.953125},{x:.390625,y:.953125},{x:.390625,y:.953125},{x:.421875,y:.953125},{x:.421875,y:.953125},{x:.453125,y:.953125},{x:.453125,y:.953125},{x:.484375,y:.953125},{x:.484375,y:.953125},{x:.515625,y:.953125},{x:.515625,y:.953125},{x:.546875,y:.953125},{x:.546875,y:.953125},{x:.578125,y:.953125},{x:.578125,y:.953125},{x:.609375,y:.953125},{x:.609375,y:.953125},{x:.640625,y:.953125},{x:.640625,y:.953125},{x:.671875,y:.953125},{x:.671875,y:.953125},{x:.703125,y:.953125},{x:.703125,y:.953125},{x:.734375,y:.953125},{x:.734375,y:.953125},{x:.765625,y:.953125},{x:.765625,y:.953125},{x:.796875,y:.953125},{x:.796875,y:.953125},{x:.828125,y:.953125},{x:.828125,y:.953125},{x:.859375,y:.953125},{x:.859375,y:.953125},{x:.890625,y:.953125},{x:.890625,y:.953125},{x:.921875,y:.953125},{x:.921875,y:.953125},{x:.953125,y:.953125},{x:.953125,y:.953125},{x:.984375,y:.953125},{x:.984375,y:.953125},{x:.015625,y:.984375},{x:.015625,y:.984375},{x:.046875,y:.984375},{x:.046875,y:.984375},{x:.078125,y:.984375},{x:.078125,y:.984375},{x:.109375,y:.984375},{x:.109375,y:.984375},{x:.140625,y:.984375},{x:.140625,y:.984375},{x:.171875,y:.984375},{x:.171875,y:.984375},{x:.203125,y:.984375},{x:.203125,y:.984375},{x:.234375,y:.984375},{x:.234375,y:.984375},{x:.265625,y:.984375},{x:.265625,y:.984375},{x:.296875,y:.984375},{x:.296875,y:.984375},{x:.328125,y:.984375},{x:.328125,y:.984375},{x:.359375,y:.984375},{x:.359375,y:.984375},{x:.390625,y:.984375},{x:.390625,y:.984375},{x:.421875,y:.984375},{x:.421875,y:.984375},{x:.453125,y:.984375},{x:.453125,y:.984375},{x:.484375,y:.984375},{x:.484375,y:.984375},{x:.515625,y:.984375},{x:.515625,y:.984375},{x:.546875,y:.984375},{x:.546875,y:.984375},{x:.578125,y:.984375},{x:.578125,y:.984375},{x:.609375,y:.984375},{x:.609375,y:.984375},{x:.640625,y:.984375},{x:.640625,y:.984375},{x:.671875,y:.984375},{x:.671875,y:.984375},{x:.703125,y:.984375},{x:.703125,y:.984375},{x:.734375,y:.984375},{x:.734375,y:.984375},{x:.765625,y:.984375},{x:.765625,y:.984375},{x:.796875,y:.984375},{x:.796875,y:.984375},{x:.828125,y:.984375},{x:.828125,y:.984375},{x:.859375,y:.984375},{x:.859375,y:.984375},{x:.890625,y:.984375},{x:.890625,y:.984375},{x:.921875,y:.984375},{x:.921875,y:.984375},{x:.953125,y:.984375},{x:.953125,y:.984375},{x:.984375,y:.984375},{x:.984375,y:.984375},{x:.03125,y:.03125},{x:.03125,y:.03125},{x:.09375,y:.03125},{x:.09375,y:.03125},{x:.15625,y:.03125},{x:.15625,y:.03125},{x:.21875,y:.03125},{x:.21875,y:.03125},{x:.28125,y:.03125},{x:.28125,y:.03125},{x:.34375,y:.03125},{x:.34375,y:.03125},{x:.40625,y:.03125},{x:.40625,y:.03125},{x:.46875,y:.03125},{x:.46875,y:.03125},{x:.53125,y:.03125},{x:.53125,y:.03125},{x:.59375,y:.03125},{x:.59375,y:.03125},{x:.65625,y:.03125},{x:.65625,y:.03125},{x:.71875,y:.03125},{x:.71875,y:.03125},{x:.78125,y:.03125},{x:.78125,y:.03125},{x:.84375,y:.03125},{x:.84375,y:.03125},{x:.90625,y:.03125},{x:.90625,y:.03125},{x:.96875,y:.03125},{x:.96875,y:.03125},{x:.03125,y:.09375},{x:.03125,y:.09375},{x:.09375,y:.09375},{x:.09375,y:.09375},{x:.15625,y:.09375},{x:.15625,y:.09375},{x:.21875,y:.09375},{x:.21875,y:.09375},{x:.28125,y:.09375},{x:.28125,y:.09375},{x:.34375,y:.09375},{x:.34375,y:.09375},{x:.40625,y:.09375},{x:.40625,y:.09375},{x:.46875,y:.09375},{x:.46875,y:.09375},{x:.53125,y:.09375},{x:.53125,y:.09375},{x:.59375,y:.09375},{x:.59375,y:.09375},{x:.65625,y:.09375},{x:.65625,y:.09375},{x:.71875,y:.09375},{x:.71875,y:.09375},{x:.78125,y:.09375},{x:.78125,y:.09375},{x:.84375,y:.09375},{x:.84375,y:.09375},{x:.90625,y:.09375},{x:.90625,y:.09375},{x:.96875,y:.09375},{x:.96875,y:.09375},{x:.03125,y:.15625},{x:.03125,y:.15625},{x:.09375,y:.15625},{x:.09375,y:.15625},{x:.15625,y:.15625},{x:.15625,y:.15625},{x:.21875,y:.15625},{x:.21875,y:.15625},{x:.28125,y:.15625},{x:.28125,y:.15625},{x:.34375,y:.15625},{x:.34375,y:.15625},{x:.40625,y:.15625},{x:.40625,y:.15625},{x:.46875,y:.15625},{x:.46875,y:.15625},{x:.53125,y:.15625},{x:.53125,y:.15625},{x:.59375,y:.15625},{x:.59375,y:.15625},{x:.65625,y:.15625},{x:.65625,y:.15625},{x:.71875,y:.15625},{x:.71875,y:.15625},{x:.78125,y:.15625},{x:.78125,y:.15625},{x:.84375,y:.15625},{x:.84375,y:.15625},{x:.90625,y:.15625},{x:.90625,y:.15625},{x:.96875,y:.15625},{x:.96875,y:.15625},{x:.03125,y:.21875},{x:.03125,y:.21875},{x:.09375,y:.21875},{x:.09375,y:.21875},{x:.15625,y:.21875},{x:.15625,y:.21875},{x:.21875,y:.21875},{x:.21875,y:.21875},{x:.28125,y:.21875},{x:.28125,y:.21875},{x:.34375,y:.21875},{x:.34375,y:.21875},{x:.40625,y:.21875},{x:.40625,y:.21875},{x:.46875,y:.21875},{x:.46875,y:.21875},{x:.53125,y:.21875},{x:.53125,y:.21875},{x:.59375,y:.21875},{x:.59375,y:.21875},{x:.65625,y:.21875},{x:.65625,y:.21875},{x:.71875,y:.21875},{x:.71875,y:.21875},{x:.78125,y:.21875},{x:.78125,y:.21875},{x:.84375,y:.21875},{x:.84375,y:.21875},{x:.90625,y:.21875},{x:.90625,y:.21875},{x:.96875,y:.21875},{x:.96875,y:.21875},{x:.03125,y:.28125},{x:.03125,y:.28125},{x:.09375,y:.28125},{x:.09375,y:.28125},{x:.15625,y:.28125},{x:.15625,y:.28125},{x:.21875,y:.28125},{x:.21875,y:.28125},{x:.28125,y:.28125},{x:.28125,y:.28125},{x:.34375,y:.28125},{x:.34375,y:.28125},{x:.40625,y:.28125},{x:.40625,y:.28125},{x:.46875,y:.28125},{x:.46875,y:.28125},{x:.53125,y:.28125},{x:.53125,y:.28125},{x:.59375,y:.28125},{x:.59375,y:.28125},{x:.65625,y:.28125},{x:.65625,y:.28125},{x:.71875,y:.28125},{x:.71875,y:.28125},{x:.78125,y:.28125},{x:.78125,y:.28125},{x:.84375,y:.28125},{x:.84375,y:.28125},{x:.90625,y:.28125},{x:.90625,y:.28125},{x:.96875,y:.28125},{x:.96875,y:.28125},{x:.03125,y:.34375},{x:.03125,y:.34375},{x:.09375,y:.34375},{x:.09375,y:.34375},{x:.15625,y:.34375},{x:.15625,y:.34375},{x:.21875,y:.34375},{x:.21875,y:.34375},{x:.28125,y:.34375},{x:.28125,y:.34375},{x:.34375,y:.34375},{x:.34375,y:.34375},{x:.40625,y:.34375},{x:.40625,y:.34375},{x:.46875,y:.34375},{x:.46875,y:.34375},{x:.53125,y:.34375},{x:.53125,y:.34375},{x:.59375,y:.34375},{x:.59375,y:.34375},{x:.65625,y:.34375},{x:.65625,y:.34375},{x:.71875,y:.34375},{x:.71875,y:.34375},{x:.78125,y:.34375},{x:.78125,y:.34375},{x:.84375,y:.34375},{x:.84375,y:.34375},{x:.90625,y:.34375},{x:.90625,y:.34375},{x:.96875,y:.34375},{x:.96875,y:.34375},{x:.03125,y:.40625},{x:.03125,y:.40625},{x:.09375,y:.40625},{x:.09375,y:.40625},{x:.15625,y:.40625},{x:.15625,y:.40625},{x:.21875,y:.40625},{x:.21875,y:.40625},{x:.28125,y:.40625},{x:.28125,y:.40625},{x:.34375,y:.40625},{x:.34375,y:.40625},{x:.40625,y:.40625},{x:.40625,y:.40625},{x:.46875,y:.40625},{x:.46875,y:.40625},{x:.53125,y:.40625},{x:.53125,y:.40625},{x:.59375,y:.40625},{x:.59375,y:.40625},{x:.65625,y:.40625},{x:.65625,y:.40625},{x:.71875,y:.40625},{x:.71875,y:.40625},{x:.78125,y:.40625},{x:.78125,y:.40625},{x:.84375,y:.40625},{x:.84375,y:.40625},{x:.90625,y:.40625},{x:.90625,y:.40625},{x:.96875,y:.40625},{x:.96875,y:.40625},{x:.03125,y:.46875},{x:.03125,y:.46875},{x:.09375,y:.46875},{x:.09375,y:.46875},{x:.15625,y:.46875},{x:.15625,y:.46875},{x:.21875,y:.46875},{x:.21875,y:.46875},{x:.28125,y:.46875},{x:.28125,y:.46875},{x:.34375,y:.46875},{x:.34375,y:.46875},{x:.40625,y:.46875},{x:.40625,y:.46875},{x:.46875,y:.46875},{x:.46875,y:.46875},{x:.53125,y:.46875},{x:.53125,y:.46875},{x:.59375,y:.46875},{x:.59375,y:.46875},{x:.65625,y:.46875},{x:.65625,y:.46875},{x:.71875,y:.46875},{x:.71875,y:.46875},{x:.78125,y:.46875},{x:.78125,y:.46875},{x:.84375,y:.46875},{x:.84375,y:.46875},{x:.90625,y:.46875},{x:.90625,y:.46875},{x:.96875,y:.46875},{x:.96875,y:.46875},{x:.03125,y:.53125},{x:.03125,y:.53125},{x:.09375,y:.53125},{x:.09375,y:.53125},{x:.15625,y:.53125},{x:.15625,y:.53125},{x:.21875,y:.53125},{x:.21875,y:.53125},{x:.28125,y:.53125},{x:.28125,y:.53125},{x:.34375,y:.53125},{x:.34375,y:.53125},{x:.40625,y:.53125},{x:.40625,y:.53125},{x:.46875,y:.53125},{x:.46875,y:.53125},{x:.53125,y:.53125},{x:.53125,y:.53125},{x:.59375,y:.53125},{x:.59375,y:.53125},{x:.65625,y:.53125},{x:.65625,y:.53125},{x:.71875,y:.53125},{x:.71875,y:.53125},{x:.78125,y:.53125},{x:.78125,y:.53125},{x:.84375,y:.53125},{x:.84375,y:.53125},{x:.90625,y:.53125},{x:.90625,y:.53125},{x:.96875,y:.53125},{x:.96875,y:.53125},{x:.03125,y:.59375},{x:.03125,y:.59375},{x:.09375,y:.59375},{x:.09375,y:.59375},{x:.15625,y:.59375},{x:.15625,y:.59375},{x:.21875,y:.59375},{x:.21875,y:.59375},{x:.28125,y:.59375},{x:.28125,y:.59375},{x:.34375,y:.59375},{x:.34375,y:.59375},{x:.40625,y:.59375},{x:.40625,y:.59375},{x:.46875,y:.59375},{x:.46875,y:.59375},{x:.53125,y:.59375},{x:.53125,y:.59375},{x:.59375,y:.59375},{x:.59375,y:.59375},{x:.65625,y:.59375},{x:.65625,y:.59375},{x:.71875,y:.59375},{x:.71875,y:.59375},{x:.78125,y:.59375},{x:.78125,y:.59375},{x:.84375,y:.59375},{x:.84375,y:.59375},{x:.90625,y:.59375},{x:.90625,y:.59375},{x:.96875,y:.59375},{x:.96875,y:.59375},{x:.03125,y:.65625},{x:.03125,y:.65625},{x:.09375,y:.65625},{x:.09375,y:.65625},{x:.15625,y:.65625},{x:.15625,y:.65625},{x:.21875,y:.65625},{x:.21875,y:.65625},{x:.28125,y:.65625},{x:.28125,y:.65625},{x:.34375,y:.65625},{x:.34375,y:.65625},{x:.40625,y:.65625},{x:.40625,y:.65625},{x:.46875,y:.65625},{x:.46875,y:.65625},{x:.53125,y:.65625},{x:.53125,y:.65625},{x:.59375,y:.65625},{x:.59375,y:.65625},{x:.65625,y:.65625},{x:.65625,y:.65625},{x:.71875,y:.65625},{x:.71875,y:.65625},{x:.78125,y:.65625},{x:.78125,y:.65625},{x:.84375,y:.65625},{x:.84375,y:.65625},{x:.90625,y:.65625},{x:.90625,y:.65625},{x:.96875,y:.65625},{x:.96875,y:.65625},{x:.03125,y:.71875},{x:.03125,y:.71875},{x:.09375,y:.71875},{x:.09375,y:.71875},{x:.15625,y:.71875},{x:.15625,y:.71875},{x:.21875,y:.71875},{x:.21875,y:.71875},{x:.28125,y:.71875},{x:.28125,y:.71875},{x:.34375,y:.71875},{x:.34375,y:.71875},{x:.40625,y:.71875},{x:.40625,y:.71875},{x:.46875,y:.71875},{x:.46875,y:.71875},{x:.53125,y:.71875},{x:.53125,y:.71875},{x:.59375,y:.71875},{x:.59375,y:.71875},{x:.65625,y:.71875},{x:.65625,y:.71875},{x:.71875,y:.71875},{x:.71875,y:.71875},{x:.78125,y:.71875},{x:.78125,y:.71875},{x:.84375,y:.71875},{x:.84375,y:.71875},{x:.90625,y:.71875},{x:.90625,y:.71875},{x:.96875,y:.71875},{x:.96875,y:.71875},{x:.03125,y:.78125},{x:.03125,y:.78125},{x:.09375,y:.78125},{x:.09375,y:.78125},{x:.15625,y:.78125},{x:.15625,y:.78125},{x:.21875,y:.78125},{x:.21875,y:.78125},{x:.28125,y:.78125},{x:.28125,y:.78125},{x:.34375,y:.78125},{x:.34375,y:.78125},{x:.40625,y:.78125},{x:.40625,y:.78125},{x:.46875,y:.78125},{x:.46875,y:.78125},{x:.53125,y:.78125},{x:.53125,y:.78125},{x:.59375,y:.78125},{x:.59375,y:.78125},{x:.65625,y:.78125},{x:.65625,y:.78125},{x:.71875,y:.78125},{x:.71875,y:.78125},{x:.78125,y:.78125},{x:.78125,y:.78125},{x:.84375,y:.78125},{x:.84375,y:.78125},{x:.90625,y:.78125},{x:.90625,y:.78125},{x:.96875,y:.78125},{x:.96875,y:.78125},{x:.03125,y:.84375},{x:.03125,y:.84375},{x:.09375,y:.84375},{x:.09375,y:.84375},{x:.15625,y:.84375},{x:.15625,y:.84375},{x:.21875,y:.84375},{x:.21875,y:.84375},{x:.28125,y:.84375},{x:.28125,y:.84375},{x:.34375,y:.84375},{x:.34375,y:.84375},{x:.40625,y:.84375},{x:.40625,y:.84375},{x:.46875,y:.84375},{x:.46875,y:.84375},{x:.53125,y:.84375},{x:.53125,y:.84375},{x:.59375,y:.84375},{x:.59375,y:.84375},{x:.65625,y:.84375},{x:.65625,y:.84375},{x:.71875,y:.84375},{x:.71875,y:.84375},{x:.78125,y:.84375},{x:.78125,y:.84375},{x:.84375,y:.84375},{x:.84375,y:.84375},{x:.90625,y:.84375},{x:.90625,y:.84375},{x:.96875,y:.84375},{x:.96875,y:.84375},{x:.03125,y:.90625},{x:.03125,y:.90625},{x:.09375,y:.90625},{x:.09375,y:.90625},{x:.15625,y:.90625},{x:.15625,y:.90625},{x:.21875,y:.90625},{x:.21875,y:.90625},{x:.28125,y:.90625},{x:.28125,y:.90625},{x:.34375,y:.90625},{x:.34375,y:.90625},{x:.40625,y:.90625},{x:.40625,y:.90625},{x:.46875,y:.90625},{x:.46875,y:.90625},{x:.53125,y:.90625},{x:.53125,y:.90625},{x:.59375,y:.90625},{x:.59375,y:.90625},{x:.65625,y:.90625},{x:.65625,y:.90625},{x:.71875,y:.90625},{x:.71875,y:.90625},{x:.78125,y:.90625},{x:.78125,y:.90625},{x:.84375,y:.90625},{x:.84375,y:.90625},{x:.90625,y:.90625},{x:.90625,y:.90625},{x:.96875,y:.90625},{x:.96875,y:.90625},{x:.03125,y:.96875},{x:.03125,y:.96875},{x:.09375,y:.96875},{x:.09375,y:.96875},{x:.15625,y:.96875},{x:.15625,y:.96875},{x:.21875,y:.96875},{x:.21875,y:.96875},{x:.28125,y:.96875},{x:.28125,y:.96875},{x:.34375,y:.96875},{x:.34375,y:.96875},{x:.40625,y:.96875},{x:.40625,y:.96875},{x:.46875,y:.96875},{x:.46875,y:.96875},{x:.53125,y:.96875},{x:.53125,y:.96875},{x:.59375,y:.96875},{x:.59375,y:.96875},{x:.65625,y:.96875},{x:.65625,y:.96875},{x:.71875,y:.96875},{x:.71875,y:.96875},{x:.78125,y:.96875},{x:.78125,y:.96875},{x:.84375,y:.96875},{x:.84375,y:.96875},{x:.90625,y:.96875},{x:.90625,y:.96875},{x:.96875,y:.96875},{x:.96875,y:.96875},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375}];var i5=class{constructor(t){T(this,"model");T(this,"anchors");T(this,"anchorsTensor");T(this,"inputSize");T(this,"inputSizeTensor");T(this,"doubleInputSizeTensor");this.model=t,this.anchors=eo.map(o=>[o.x,o.y]),this.anchorsTensor=W.tensor2d(this.anchors),this.inputSize=this.model&&this.model.inputs&&this.model.inputs[0].shape?this.model.inputs[0].shape[2]:0,this.inputSizeTensor=W.tensor1d([this.inputSize,this.inputSize]),this.doubleInputSizeTensor=W.tensor1d([this.inputSize*2,this.inputSize*2])}normalizeBoxes(t){let o={};o.boxOffsets=W.slice(t,[0,0],[-1,2]),o.boxSizes=W.slice(t,[0,2],[-1,2]),o.div=W.div(o.boxOffsets,this.inputSizeTensor),o.boxCenterPoints=W.add(o.div,this.anchorsTensor),o.halfBoxSizes=W.div(o.boxSizes,this.doubleInputSizeTensor),o.sub=W.sub(o.boxCenterPoints,o.halfBoxSizes),o.startPoints=W.mul(o.sub,this.inputSizeTensor),o.add=W.add(o.boxCenterPoints,o.halfBoxSizes),o.endPoints=W.mul(o.add,this.inputSizeTensor);let n=W.concat2d([o.startPoints,o.endPoints],1);return Object.keys(o).forEach(r=>W.dispose(o[r])),n}normalizeLandmarks(t,o){let n={};n.reshape=W.reshape(t,[-1,7,2]),n.div=W.div(n.reshape,this.inputSizeTensor),n.landmarks=W.add(n.div,this.anchors[o]);let r=W.mul(n.landmarks,this.inputSizeTensor);return Object.keys(n).forEach(A=>W.dispose(n[A])),r}async predict(t,o){let n={};n.resize=W.image.resizeBilinear(t,[this.inputSize,this.inputSize]),n.div=W.div(n.resize,V.tf127),n.image=W.sub(n.div,V.tf1),n.batched=this.model.execute(n.image),n.predictions=W.squeeze(n.batched),n.slice=W.slice(n.predictions,[0,0],[-1,1]),n.sigmoid=W.sigmoid(n.slice),n.scores=W.squeeze(n.sigmoid);let r=await n.scores.data();n.boxes=W.slice(n.predictions,[0,1],[-1,4]),n.norm=this.normalizeBoxes(n.boxes),n.nms=await W.image.nonMaxSuppressionAsync(n.norm,n.scores,3*o.hand.maxDetected,o.hand.iouThreshold,o.hand.minConfidence);let A=await n.nms.array(),s=[];for(let a of A){let i={};i.box=W.slice(n.norm,[a,0],[1,-1]),i.slice=W.slice(n.predictions,[a,5],[1,14]),i.norm=this.normalizeLandmarks(i.slice,a),i.palmLandmarks=W.reshape(i.norm,[-1,2]);let x=await i.box.data(),c=x.slice(0,2),l=x.slice(2,4),y=await i.palmLandmarks.array(),f={startPoint:c,endPoint:l,palmLandmarks:y,confidence:r[a]},u=J3(f,[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]);s.push(u),Object.keys(i).forEach(m=>W.dispose(i[m]))}return Object.keys(n).forEach(a=>W.dispose(n[a])),s}};var L0=Z(D());var yA=5,to=1.65,oo=[0,5,9,13,17,1,2],xA=0,cA=2,no=0,l5=class{constructor(t,o){T(this,"handDetector");T(this,"handPoseModel");T(this,"inputSize");T(this,"storedBoxes");T(this,"skipped");T(this,"detectedHands");this.handDetector=t,this.handPoseModel=o,this.inputSize=this.handPoseModel&&this.handPoseModel.inputs[0].shape?this.handPoseModel.inputs[0].shape[2]:0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let o=t.map(s=>s[0]),n=t.map(s=>s[1]),r=[Math.min(...o),Math.min(...n)],A=[Math.max(...o),Math.max(...n)];return{startPoint:r,endPoint:A}}getBoxForPalmLandmarks(t,o){let n=t.map(A=>P1([...A,1],o)),r=this.calculateLandmarksBoundingBox(n);return s5(a5(r),yA)}getBoxForHandLandmarks(t){let o=this.calculateLandmarksBoundingBox(t),n=s5(a5(o),to);n.palmLandmarks=[];for(let r=0;r<oo.length;r++)n.palmLandmarks.push(t[oo[r]].slice(0,2));return n}transformRawCoords(t,o,n,r){let A=A5(o),s=[A[0]/this.inputSize,A[1]/this.inputSize,(A[0]+A[1])/this.inputSize/2],a=t.map(f=>[s[0]*(f[0]-this.inputSize/2),s[1]*(f[1]-this.inputSize/2),s[2]*f[2]]),i=M1(n,[0,0]),x=a.map(f=>[...P1(f,i),f[2]]),c=_3(r),l=[...k2(o),1],y=[Te(l,c[0]),Te(l,c[1])];return x.map(f=>[Math.trunc(f[0]+y[0]),Math.trunc(f[1]+y[1]),Math.trunc(f[2])])}async estimateHands(t,o){let n=!1,r,A=(o.hand.skipTime||0)>h()-no,s=this.skipped<(o.hand.skipFrames||0);o.skipAllowed&&A&&s&&(r=await this.handDetector.predict(t,o),this.skipped=0),o.skipAllowed&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==o.hand.maxDetected||!o.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(n=!0));let a=[];for(let i=0;i<this.storedBoxes.length;i++){let x=this.storedBoxes[i];if(!!x)if(o.hand.landmarks){let c=o.hand.rotation?Q3(x.palmLandmarks[xA],x.palmLandmarks[cA]):0,l=k2(x),y=[l[0]/t.shape[2],l[1]/t.shape[1]],f=o.hand.rotation&&v.kernels.includes("rotatewithoffset")?L0.image.rotateWithOffset(t,c,0,y):t.clone(),u=M1(-c,l),m=n?this.getBoxForPalmLandmarks(x.palmLandmarks,u):x,P=K3(m,f,[this.inputSize,this.inputSize]),g=L0.div(P,V.tf255);L0.dispose(P),L0.dispose(f);let[b,d]=this.handPoseModel.execute(g);no=h(),L0.dispose(g);let M=(await b.data())[0];if(L0.dispose(b),M>=o.hand.minConfidence/4){let S=L0.reshape(d,[-1,3]),w=await S.array();L0.dispose(d),L0.dispose(S);let j=this.transformRawCoords(w,m,c,u),C=this.getBoxForHandLandmarks(j);this.storedBoxes[i]={...C,confidence:M};let F={landmarks:j,confidence:M,boxConfidence:x.confidence,fingerConfidence:M,box:{topLeft:C.startPoint,bottomRight:C.endPoint}};a.push(F)}else this.storedBoxes[i]=null;L0.dispose(d)}else{let c=s5(a5(x),to),l={confidence:x.confidence,boxConfidence:x.confidence,fingerConfidence:0,box:{topLeft:c.startPoint,bottomRight:c.endPoint},landmarks:[]};a.push(l)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=a.length,a.length>o.hand.maxDetected&&(a.length=o.hand.maxDetected),a}};var k0={thumb:0,index:1,middle:2,ring:3,pinky:4,all:[0,1,2,3,4],nameMapping:{0:"thumb",1:"index",2:"middle",3:"ring",4:"pinky"},pointsMapping:{0:[[0,1],[1,2],[2,3],[3,4]],1:[[0,5],[5,6],[6,7],[7,8]],2:[[0,9],[9,10],[10,11],[11,12]],3:[[0,13],[13,14],[14,15],[15,16]],4:[[0,17],[17,18],[18,19],[19,20]]},getName:e=>k0.nameMapping[e],getPoints:e=>k0.pointsMapping[e]},ke={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>ke.nameMapping[e]},o0={verticalUp:0,verticalDown:1,horizontalLeft:2,horizontalRight:3,diagonalUpRight:4,diagonalUpLeft:5,diagonalDownRight:6,diagonalDownLeft:7,nameMapping:{0:"verticalUp",1:"verticalDown",2:"horizontalLeft",3:"horizontalRight",4:"diagonalUpRight",5:"diagonalUpLeft",6:"diagonalDownRight",7:"diagonalDownLeft"},getName:e=>o0.nameMapping[e]},we=class{constructor(t){T(this,"name");T(this,"curls");T(this,"directions");T(this,"weights");T(this,"weightsRelative");this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}curl(t,o,n){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([o,n])}direction(t,o,n){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([o,n])}weight(t,o){this.weights[t]=o;let n=this.weights.reduce((r,A)=>r+A,0);this.weightsRelative=this.weights.map(r=>r*5/n)}matchAgainst(t,o){let n=0;for(let r in t){let A=t[r],s=this.curls[r];if(typeof s=="undefined"){n+=this.weightsRelative[r];continue}for(let[a,i]of s)if(A===a){n+=i*this.weightsRelative[r];break}}for(let r in o){let A=o[r],s=this.directions[r];if(typeof s=="undefined"){n+=this.weightsRelative[r];continue}for(let[a,i]of s)if(A===a){n+=i*this.weightsRelative[r];break}}return n/10}};var{thumb:J0,index:ce,middle:de,ring:He,pinky:Ve}=k0,{none:Q0,half:fA,full:_0}=ke,{verticalUp:o2,verticalDown:z4,horizontalLeft:R1,horizontalRight:mA,diagonalUpRight:pA,diagonalUpLeft:n2,diagonalDownRight:S4,diagonalDownLeft:C4}=o0,Ee=new we("thumbs up");Ee.curl(J0,Q0,1);Ee.direction(J0,o2,1);Ee.direction(J0,n2,.25);Ee.direction(J0,pA,.25);for(let e of[k0.index,k0.middle,k0.ring,k0.pinky])Ee.curl(e,_0,1),Ee.direction(e,R1,1),Ee.direction(e,mA,1);var l0=new we("victory");l0.curl(J0,fA,.5);l0.curl(J0,Q0,.5);l0.direction(J0,o2,1);l0.direction(J0,n2,1);l0.curl(ce,Q0,1);l0.direction(ce,o2,.75);l0.direction(ce,n2,1);l0.curl(de,Q0,1);l0.direction(de,o2,1);l0.direction(de,n2,.75);l0.curl(He,_0,1);l0.direction(He,o2,.2);l0.direction(He,n2,1);l0.direction(He,R1,.2);l0.curl(Ve,_0,1);l0.direction(Ve,o2,.2);l0.direction(Ve,n2,1);l0.direction(Ve,R1,.2);l0.weight(ce,2);l0.weight(de,2);var ze=new we("point");ze.curl(J0,_0,1);ze.curl(ce,Q0,.5);ze.curl(de,_0,.5);ze.curl(He,_0,.5);ze.curl(Ve,_0,.5);ze.weight(ce,2);ze.weight(de,2);var Se=new we("middle finger");Se.curl(J0,Q0,1);Se.curl(ce,_0,.5);Se.curl(de,_0,.5);Se.curl(He,_0,.5);Se.curl(Ve,_0,.5);Se.weight(ce,2);Se.weight(de,2);var r2=new we("open palm");r2.curl(J0,Q0,.75);r2.curl(ce,Q0,.75);r2.curl(de,Q0,.75);r2.curl(He,Q0,.75);r2.curl(Ve,Q0,.75);var ro=[Ee,l0,ze,Se,r2];var uA=.7,De={HALF_CURL_START_LIMIT:60,NO_CURL_START_LIMIT:130,DISTANCE_VOTE_POWER:1.1,SINGLE_ANGLE_VOTE_POWER:.9,TOTAL_ANGLE_VOTE_POWER:1.6};function Ao(e,t,o,n){let r=(t-n)/(e-o),A=Math.atan(r)*180/Math.PI;return A<=0?A=-A:A>0&&(A=180-A),A}function ao(e,t){if(!e||!t)return[0,0];let o=Ao(e[0],e[1],t[0],t[1]);if(e.length===2)return o;let n=Ao(e[1],e[2],t[1],t[2]);return[o,n]}function so(e,t=1){let o=0,n=0,r=0;return e>=75&&e<=105?o=1*t:e>=25&&e<=155?n=1*t:r=1*t,[o,n,r]}function hA(e,t,o){let n=e[0]-t[0],r=e[0]-o[0],A=t[0]-o[0],s=e[1]-t[1],a=e[1]-o[1],i=t[1]-o[1],x=e[2]-t[2],c=e[2]-o[2],l=t[2]-o[2],y=Math.sqrt(n*n+s*s+x*x),f=Math.sqrt(r*r+a*a+c*c),u=Math.sqrt(A*A+i*i+l*l),m=(u*u+y*y-f*f)/(2*u*y);m>1?m=1:m<-1&&(m=-1);let P=Math.acos(m);P=57.2958*P%180;let g;return P>De.NO_CURL_START_LIMIT?g=ke.none:P>De.HALF_CURL_START_LIMIT?g=ke.half:g=ke.full,g}function io(e,t,o,n){let r;return n===Math.abs(e)?e>0?r=o0.horizontalLeft:r=o0.horizontalRight:n===Math.abs(t)?t>0?r=o0.horizontalLeft:r=o0.horizontalRight:o>0?r=o0.horizontalLeft:r=o0.horizontalRight,r}function lo(e,t,o,n){let r;return n===Math.abs(e)?e<0?r=o0.verticalDown:r=o0.verticalUp:n===Math.abs(t)?t<0?r=o0.verticalDown:r=o0.verticalUp:o<0?r=o0.verticalDown:r=o0.verticalUp,r}function bA(e,t,o,n,r,A,s,a){let i,x=lo(e,t,o,n),c=io(r,A,s,a);return x===o0.verticalUp?c===o0.horizontalLeft?i=o0.diagonalUpLeft:i=o0.diagonalUpRight:c===o0.horizontalLeft?i=o0.diagonalDownLeft:i=o0.diagonalDownRight,i}function gA(e,t,o,n){let r=e[0]-t[0],A=e[0]-o[0],s=t[0]-o[0],a=e[1]-t[1],i=e[1]-o[1],x=t[1]-o[1],c=Math.max(Math.abs(r),Math.abs(A),Math.abs(s)),l=Math.max(Math.abs(a),Math.abs(i),Math.abs(x)),y=0,f=0,u=0,m=l/(c+1e-5);m>1.5?y+=De.DISTANCE_VOTE_POWER:m>.66?f+=De.DISTANCE_VOTE_POWER:u+=De.DISTANCE_VOTE_POWER;let P=Math.sqrt(r*r+a*a),g=Math.sqrt(A*A+i*i),b=Math.sqrt(s*s+x*x),d=Math.max(P,g,b),M=e[0],S=e[1],w=o[0],j=o[1];d===P?(w=o[0],j=o[1]):d===b&&(M=t[0],S=t[1]);let H=ao([M,S],[w,j]),Y=so(H,De.TOTAL_ANGLE_VOTE_POWER);y+=Y[0],f+=Y[1],u+=Y[2];for(let x0 of n){let E=so(x0,De.SINGLE_ANGLE_VOTE_POWER);y+=E[0],f+=E[1],u+=E[2]}let J;return y===Math.max(y,f,u)?J=lo(i,a,x,l):u===Math.max(f,u)?J=io(A,r,s,c):J=bA(i,a,x,l,A,r,s,c),J}function yo(e){let t=[],o=[],n=[],r=[];if(!e)return{curls:n,directions:r};for(let A of k0.all){let s=k0.getPoints(A),a=[],i=[];for(let x of s){let c=e[x[0]],l=e[x[1]],y=ao(c,l),f=y[0],u=y[1];a.push(f),i.push(u)}t.push(a),o.push(i)}for(let A of k0.all){let s=A===k0.thumb?1:0,a=k0.getPoints(A),i=e[a[s][0]],x=e[a[s+1][1]],c=e[a[3][1]],l=hA(i,x,c),y=gA(i,x,c,t[A].slice(s));n[A]=l,r[A]=y}return{curls:n,directions:r}}function y5(e){if(!e||e.length===0)return null;let t=yo(e),o={};for(let n of k0.all)o[k0.getName(n)]={curl:ke.getName(t.curls[n]),direction:o0.getName(t.directions[n])};return o}function xo(e){let t=[];if(!e||e.length===0)return t;let o=yo(e);for(let n of ro){let r=n.matchAgainst(o.curls,o.directions);r>=uA&&t.push({name:n.name,confidence:r})}return t}var co={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],palm:[0]},A2,s2,fo;async function T1(e,t){let o=await fo.estimateHands(e,t);if(!o)return[];let n=[];for(let r=0;r<o.length;r++){let A={};if(o[r].landmarks)for(let c of Object.keys(co))A[c]=co[c].map(l=>o[r].landmarks[l]);let s=o[r].landmarks,a=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],i=[0,0,0,0];if(s&&s.length>0){for(let c of s)c[0]<a[0]&&(a[0]=c[0]),c[1]<a[1]&&(a[1]=c[1]),c[0]>a[2]&&(a[2]=c[0]),c[1]>a[3]&&(a[3]=c[1]);a[2]-=a[0],a[3]-=a[1],i=[a[0]/(e.shape[2]||0),a[1]/(e.shape[1]||0),a[2]/(e.shape[2]||0),a[3]/(e.shape[1]||0)]}else a=o[r].box?[Math.trunc(Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.max(0,o[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,o[r].box.bottomRight[0])-Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,o[r].box.bottomRight[1])-Math.max(0,o[r].box.topLeft[1]))]:[0,0,0,0],i=[o[r].box.topLeft[0]/(e.shape[2]||0),o[r].box.topLeft[1]/(e.shape[1]||0),(o[r].box.bottomRight[0]-o[r].box.topLeft[0])/(e.shape[2]||0),(o[r].box.bottomRight[1]-o[r].box.topLeft[1])/(e.shape[1]||0)];let x=y5(s);n.push({id:r,score:Math.round(100*o[r].confidence)/100,boxScore:Math.round(100*o[r].boxConfidence)/100,fingerScore:Math.round(100*o[r].fingerConfidence)/100,label:"hand",box:a,boxRaw:i,keypoints:s,annotations:A,landmarks:x})}return n}async function w1(e){var o,n;v.initial&&(A2=null,s2=null),!A2||!s2?[A2,s2]=await Promise.all([e.hand.enabled?G((o=e.hand.detector)==null?void 0:o.modelPath):null,e.hand.landmarks?G((n=e.hand.skeleton)==null?void 0:n.modelPath):null]):(e.debug&&p("cached model:",A2.modelUrl),e.debug&&p("cached model:",s2.modelUrl));let t=new i5(A2);return fo=new l5(t,s2),[A2,s2]}var Q=Z(D());var d0=[null,null],MA=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],Ce=[[0,0],[0,0]],PA=["hand","fist","pinch","point","face","tip","pinchtip"],po=4,uo=1.6,RA=512,vA=1.4,x5=Number.MAX_SAFE_INTEGER,k1=0,fe=[0,0],A0={boxes:[],hands:[]},ho={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],base:[0],palm:[0,17,13,9,5,1,0]};async function bo(e){var t;if(v.initial&&(d0[0]=null),d0[0])e.debug&&p("cached model:",d0[0].modelUrl);else{c5(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),d0[0]=await G((t=e.hand.detector)==null?void 0:t.modelPath);let o=Object.values(d0[0].modelSignature.inputs);Ce[0][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ce[0][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return d0[0]}async function go(e){var t;if(v.initial&&(d0[1]=null),d0[1])e.debug&&p("cached model:",d0[1].modelUrl);else{d0[1]=await G((t=e.hand.skeleton)==null?void 0:t.modelPath);let o=Object.values(d0[1].modelSignature.inputs);Ce[1][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ce[1][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return d0[1]}async function TA(e,t){let o=[];if(!e||!d0[0])return o;let n={},r=(e.shape[2]||1)/(e.shape[1]||1),A=Math.min(Math.round((e.shape[1]||0)/8)*8,RA),s=Math.round(A*r/8)*8;n.resize=Q.image.resizeBilinear(e,[A,s]),n.cast=Q.cast(n.resize,"int32"),[n.rawScores,n.rawBoxes]=await d0[0].executeAsync(n.cast,MA),n.boxes=Q.squeeze(n.rawBoxes,[0,2]),n.scores=Q.squeeze(n.rawScores,[0]);let a=Q.unstack(n.scores,1);Q.dispose(a[po]),a.splice(po,1),n.filtered=Q.stack(a,1),Q.dispose(a),n.max=Q.max(n.filtered,1),n.argmax=Q.argMax(n.filtered,1);let i=0;n.nms=await Q.image.nonMaxSuppressionAsync(n.boxes,n.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let x=await n.nms.data(),c=await n.max.data(),l=await n.argmax.data();for(let y of Array.from(x)){let f=Q.slice(n.boxes,y,1),u=await f.data();Q.dispose(f);let m=[u[1],u[0],u[3]-u[1],u[2]-u[0]],P=_2(m,vA),g=[Math.trunc(m[0]*fe[0]),Math.trunc(m[1]*fe[1]),Math.trunc(m[2]*fe[0]),Math.trunc(m[3]*fe[1])],b=c[y],d=PA[l[y]],M={id:i++,score:b,box:g,boxRaw:P,label:d};o.push(M)}return Object.keys(n).forEach(y=>Q.dispose(n[y])),o.sort((y,f)=>f.score-y.score),o.length>(t.hand.maxDetected||1)&&(o.length=t.hand.maxDetected||1),o}async function E1(e,t,o){let n={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&d0[1]&&o.hand.landmarks&&t.score>(o.hand.minConfidence||0)){let r={},A=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=Q.image.cropAndResize(e,[A],[0],[Ce[1][0],Ce[1][1]],"bilinear"),r.div=Q.div(r.crop,V.tf255),[r.score,r.keypoints]=d0[1].execute(r.div,["Identity_1","Identity"]);let s=(await r.score.data())[0],a=(100-Math.trunc(100/(1+Math.exp(s))))/100;if(a>=(o.hand.minConfidence||0)){n.fingerScore=a,r.reshaped=Q.reshape(r.keypoints,[-1,3]);let c=(await r.reshaped.array()).map(l=>[l[0]/Ce[1][1],l[1]/Ce[1][0],l[2]||0]).map(l=>[l[0]*t.boxRaw[2],l[1]*t.boxRaw[3],l[2]||0]);n.keypoints=c.map(l=>[fe[0]*(l[0]+t.boxRaw[0]),fe[1]*(l[1]+t.boxRaw[1]),l[2]||0]),n.landmarks=y5(n.keypoints);for(let l of Object.keys(ho))n.annotations[l]=ho[l].map(y=>n.landmarks&&n.keypoints[y]?n.keypoints[y]:null)}Object.keys(r).forEach(i=>Q.dispose(r[i]))}return n}async function z1(e,t){var r,A;if(!d0[0]||!d0[1]||!((r=d0[0])!=null&&r.inputs[0].shape)||!((A=d0[1])!=null&&A.inputs[0].shape))return[];fe=[e.shape[2]||0,e.shape[1]||0],x5++;let o=(t.hand.skipTime||0)>h()-k1,n=x5<(t.hand.skipFrames||0);return t.skipAllowed&&o&&n?A0.hands:new Promise(async s=>{let a=3*(t.hand.skipTime||0)>h()-k1,i=x5<3*(t.hand.skipFrames||0);t.skipAllowed&&A0.hands.length===t.hand.maxDetected?A0.hands=await Promise.all(A0.boxes.map(c=>E1(e,c,t))):t.skipAllowed&&a&&i&&A0.hands.length>0?A0.hands=await Promise.all(A0.boxes.map(c=>E1(e,c,t))):(A0.boxes=await TA(e,t),k1=h(),A0.hands=await Promise.all(A0.boxes.map(c=>E1(e,c,t))),x5=0);let x=[...A0.boxes];if(A0.boxes.length=0,t.cacheSensitivity>0)for(let c=0;c<A0.hands.length;c++){let l=i3(A0.hands[c].keypoints,fe);if(l.box[2]/(e.shape[2]||1)>.05&&l.box[3]/(e.shape[1]||1)>.05&&A0.hands[c].fingerScore&&A0.hands[c].fingerScore>(t.hand.minConfidence||0)){let y=_2(l.box,uo),f=_2(l.boxRaw,uo);A0.boxes.push({...x[c],box:y,boxRaw:f})}}for(let c=0;c<A0.hands.length;c++){let l=le(A0.hands[c].keypoints,fe);A0.hands[c].box=l.box,A0.hands[c].boxRaw=l.boxRaw}s(A0.hands)})}var f5=Z(D());var M0,d5=[],S1=Number.MAX_SAFE_INTEGER,Po=0,Ro=0;async function vo(e){var t;return v.initial&&(M0=null),M0?e.debug&&p("cached model:",M0.modelUrl):M0=await G((t=e.face.liveness)==null?void 0:t.modelPath),M0}async function C1(e,t,o,n){var s,a;if(!M0)return 0;let r=(((s=t.face.liveness)==null?void 0:s.skipTime)||0)>h()-Ro,A=S1<(((a=t.face.liveness)==null?void 0:a.skipFrames)||0);return t.skipAllowed&&r&&A&&Po===n&&d5[o]?(S1++,d5[o]):(S1=0,new Promise(async i=>{let x=f5.image.resizeBilinear(e,[M0!=null&&M0.inputs[0].shape?M0.inputs[0].shape[2]:0,M0!=null&&M0.inputs[0].shape?M0.inputs[0].shape[1]:0],!1),c=M0==null?void 0:M0.execute(x),l=(await c.data())[0];d5[o]=Math.round(100*l)/100,Po=n,Ro=h(),f5.dispose([x,c]),i(d5[o])}))}var So=Z(D());var E2={};ue(E2,{connected:()=>p5,horizontal:()=>j1,kpt:()=>m5,relative:()=>N1,vertical:()=>I1});var m5=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],j1=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],I1=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],N1=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],p5={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var je=Z(D()),wo=.005,W0={keypoints:[],padding:[[0,0],[0,0],[0,0],[0,0]]};function O1(e){for(let t of j1){let o=e.keypoints.findIndex(r=>r.part===t[0]),n=e.keypoints.findIndex(r=>r.part===t[1]);if(e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[0]<e.keypoints[n].position[0]){let r=e.keypoints[o];e.keypoints[o]=e.keypoints[n],e.keypoints[n]=r}}for(let t of I1){let o=e.keypoints.findIndex(r=>r&&r.part===t[0]),n=e.keypoints.findIndex(r=>r&&r.part===t[1]);e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[1]<e.keypoints[n].position[1]&&e.keypoints.splice(o,1)}for(let[t,o]of N1){let n=e.keypoints.findIndex(x=>x&&x.part===t[0]),r=e.keypoints.findIndex(x=>x&&x.part===t[1]),A=e.keypoints.findIndex(x=>x&&x.part===o[0]),s=e.keypoints.findIndex(x=>x&&x.part===o[1]);if(!e.keypoints[A]||!e.keypoints[s])continue;let a=e.keypoints[n]?[Math.abs(e.keypoints[A].position[0]-e.keypoints[n].position[0]),Math.abs(e.keypoints[s].position[0]-e.keypoints[n].position[0])]:[0,0],i=e.keypoints[r]?[Math.abs(e.keypoints[s].position[0]-e.keypoints[r].position[0]),Math.abs(e.keypoints[A].position[0]-e.keypoints[r].position[0])]:[0,0];if(a[0]>a[1]||i[0]>i[1]){let x=e.keypoints[n];e.keypoints[n]=e.keypoints[r],e.keypoints[r]=x}}}function ko(e){for(let t=0;t<e.length;t++)if(e[t]&&W0.keypoints[t]){let o=[Math.abs(e[t].positionRaw[0]-W0.keypoints[t].positionRaw[0]),Math.abs(e[t].positionRaw[1]-W0.keypoints[t].positionRaw[1])];o[0]<wo&&o[1]<wo?e[t]=W0.keypoints[t]:W0.keypoints[t]=e[t]}else W0.keypoints[t]=e[t];return e}function Eo(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;W0.padding=[[0,0],[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0],[0,0]],o.pad=je.pad(e,W0.padding),o.resize=je.image.resizeBilinear(o.pad,[t,t]);let n=je.cast(o.resize,"int32");return Object.keys(o).forEach(r=>je.dispose(o[r])),n}function zo(e,t){e.keypoints=e.keypoints.filter(n=>n&&n.position);for(let n of e.keypoints)n.position=[n.position[0]*(t[0]+W0.padding[2][0]+W0.padding[2][1])/t[0]-W0.padding[2][0],n.position[1]*(t[1]+W0.padding[1][0]+W0.padding[1][1])/t[1]-W0.padding[1][0]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1]];let o=le(e.keypoints.map(n=>n.position),t);return e.box=o.box,e.boxRaw=o.boxRaw,e}var F0,u5=0,L1=Number.MAX_SAFE_INTEGER,Ze={boxes:[],bodies:[],last:0};async function Co(e){return v.initial&&(F0=null),F0?e.debug&&p("cached model:",F0.modelUrl):(c5(["size"],e),F0=await G(e.body.modelPath)),u5=F0.inputs[0].shape?F0.inputs[0].shape[2]:0,u5<64&&(u5=256),F0}async function kA(e,t,o){let n=e[0][0],r=[],A=0;for(let c=0;c<n.length;c++)if(A=n[c][2],A>t.body.minConfidence){let l=[n[c][1],n[c][0]];r.push({score:Math.round(100*A)/100,part:m5[c],positionRaw:l,position:[Math.round((o.shape[2]||0)*l[0]),Math.round((o.shape[1]||0)*l[1])]})}A=r.reduce((c,l)=>l.score>c?l.score:c,0);let s=[],a=le(r.map(c=>c.position),[o.shape[2],o.shape[1]]),i={};for(let[c,l]of Object.entries(p5)){let y=[];for(let f=0;f<l.length-1;f++){let u=r.find(P=>P.part===l[f]),m=r.find(P=>P.part===l[f+1]);u&&m&&u.score>(t.body.minConfidence||0)&&m.score>(t.body.minConfidence||0)&&y.push([u.position,m.position])}i[c]=y}let x={id:0,score:A,box:a.box,boxRaw:a.boxRaw,keypoints:r,annotations:i};return O1(x),s.push(x),s}async function EA(e,t,o){let n=[];for(let r=0;r<e[0].length;r++){let A=e[0][r],s=Math.round(100*A[51+4])/100;if(s>t.body.minConfidence){let a=[];for(let l=0;l<17;l++){let y=A[3*l+2];if(y>t.body.minConfidence){let f=[A[3*l+1],A[3*l+0]];a.push({part:m5[l],score:Math.round(100*y)/100,positionRaw:f,position:[Math.round((o.shape[2]||0)*f[0]),Math.round((o.shape[1]||0)*f[1])]})}}let i=le(a.map(l=>l.position),[o.shape[2],o.shape[1]]),x={};for(let[l,y]of Object.entries(p5)){let f=[];for(let u=0;u<y.length-1;u++){let m=a.find(g=>g.part===y[u]),P=a.find(g=>g.part===y[u+1]);m&&P&&m.score>(t.body.minConfidence||0)&&P.score>(t.body.minConfidence||0)&&f.push([m.position,P.position])}x[l]=f}let c={id:r,score:s,box:i.box,boxRaw:i.boxRaw,keypoints:[...a],annotations:x};O1(c),n.push(c)}}return n.sort((r,A)=>A.score-r.score),n.length>t.body.maxDetected&&(n.length=t.body.maxDetected),n}async function W1(e,t){if(!F0||!(F0!=null&&F0.inputs[0].shape))return[];t.skipAllowed||(Ze.boxes.length=0),L1++;let o=(t.body.skipTime||0)>h()-Ze.last,n=L1<(t.body.skipFrames||0);return t.skipAllowed&&o&&n?Ze.bodies:new Promise(async r=>{let A={};L1=0,A.input=Eo(e,u5),A.res=F0==null?void 0:F0.execute(A.input),Ze.last=h();let s=await A.res.array();Ze.bodies=A.res.shape[2]===17?await kA(s,t,e):await EA(s,t,e);for(let a of Ze.bodies)zo(a,[e.shape[2]||1,e.shape[1]||1]),ko(a.keypoints);Object.keys(A).forEach(a=>So.dispose(A[a])),r(Ze.bodies)})}var E0=Z(D());var a2,h5=[],Io=0,F1=Number.MAX_SAFE_INTEGER,g5=0,b5=2.5;async function No(e){if(!a2||v.initial){a2=await G(e.object.modelPath);let t=Object.values(a2.modelSignature.inputs);g5=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&p("cached model:",a2.modelUrl);return a2}async function zA(e,t,o){let n=0,r=[];for(let i of[1,2,4])E0.tidy(async()=>{let x=i*13,c=E0.squeeze(e.find(m=>m.shape[1]===x**2&&(m.shape[2]||0)===$e.length)),l=E0.squeeze(e.find(m=>m.shape[1]===x**2&&(m.shape[2]||0)<$e.length)),f=await l.reshape([-1,4,l.shape[1]/4]).argMax(2).array(),u=await c.array();for(let m=0;m<c.shape[0];m++)for(let P=0;P<c.shape[1];P++){let g=u[m][P];if(g>(o.object.minConfidence||0)&&P!==61){let b=(.5+Math.trunc(m%x))/x,d=(.5+Math.trunc(m/x))/x,M=f[m].map(J=>J*(x/i/g5)),[S,w]=[b-b5/i*M[0],d-b5/i*M[1]],[j,C]=[b+b5/i*M[2]-S,d+b5/i*M[3]-w],F=[S,w,j,C];F=F.map(J=>Math.max(0,Math.min(J,1)));let H=[F[0]*t[0],F[1]*t[1],F[2]*t[0],F[3]*t[1]],Y={id:n++,score:Math.round(100*g)/100,class:P+1,label:$e[P].label,box:H.map(J=>Math.trunc(J)),boxRaw:F};r.push(Y)}}});e.forEach(i=>E0.dispose(i));let A=r.map(i=>[i.boxRaw[1],i.boxRaw[0],i.boxRaw[3],i.boxRaw[2]]),s=r.map(i=>i.score),a=[];if(A&&A.length>0){let i=await E0.image.nonMaxSuppressionAsync(A,s,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence);a=await i.data(),E0.dispose(i)}return r=r.filter((i,x)=>a.includes(x)).sort((i,x)=>x.score-i.score),r}async function G1(e,t){let o=(t.object.skipTime||0)>h()-Io,n=F1<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&h5.length>0?(F1++,h5):(F1=0,!v.kernels.includes("mod")||!v.kernels.includes("sparsetodense")?h5:new Promise(async r=>{let A=[e.shape[2]||0,e.shape[1]||0],s=E0.image.resizeBilinear(e,[g5,g5],!1),a=E0.div(s,V.tf255),i=a.transpose([0,3,1,2]);E0.dispose(a),E0.dispose(s);let x;t.object.enabled&&(x=a2.execute(i)),Io=h(),E0.dispose(i);let c=await zA(x,A,t);h5=c,r(c)}))}var z0=Z(D());var S2=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],SA=S2.length,z2=S2.reduce((e,t,o)=>(e[t]=o,e),{}),CA=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],ts=CA.map(([e,t])=>[z2[e],z2[t]]),Lo=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function Wo(e){let t=e.reduce(({maxX:o,maxY:n,minX:r,minY:A},{position:{x:s,y:a}})=>({maxX:Math.max(o,s),maxY:Math.max(n,a),minX:Math.min(r,s),minY:Math.min(A,a)}),{maxX:Number.NEGATIVE_INFINITY,maxY:Number.NEGATIVE_INFINITY,minX:Number.POSITIVE_INFINITY,minY:Number.POSITIVE_INFINITY});return[t.minX,t.minY,t.maxX-t.minX,t.maxY-t.minY]}function Fo(e,[t,o],[n,r]){let A=t/n,s=o/r,a=(x,c)=>({id:c,score:x.score,boxRaw:[x.box[0]/r,x.box[1]/n,x.box[2]/r,x.box[3]/n],box:[Math.trunc(x.box[0]*s),Math.trunc(x.box[1]*A),Math.trunc(x.box[2]*s),Math.trunc(x.box[3]*A)],keypoints:x.keypoints.map(({score:l,part:y,position:f})=>({score:l,part:y,position:[Math.trunc(f.x*s),Math.trunc(f.y*A)],positionRaw:[f.x/n,f.y/n]})),annotations:{}});return e.map((x,c)=>a(x,c))}var M5=class{constructor(t,o){T(this,"priorityQueue");T(this,"numberOfElements");T(this,"getElementValue");this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=o}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(Math.floor(t/2),t);)this.exchange(t,Math.floor(t/2)),t=Math.floor(t/2)}sink(t){for(;2*t<=this.numberOfElements;){let o=2*t;if(o<this.numberOfElements&&this.less(o,o+1)&&o++,!this.less(t,o))break;this.exchange(t,o),t=o}}getValueAt(t){return this.getElementValue(this.priorityQueue[t])}less(t,o){return this.getValueAt(t)<this.getValueAt(o)}exchange(t,o){let n=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[o],this.priorityQueue[o]=n}};function B1(e,t,o,n){return{y:n.get(e,t,o),x:n.get(e,t,o+SA)}}function H1(e,t,o){let{heatmapY:n,heatmapX:r,id:A}=e,{y:s,x:a}=B1(n,r,A,o);return{x:e.heatmapX*t+a,y:e.heatmapY*t+s}}function V1(e,t,o){return e<t?t:e>o?o:e}function Go(e,t,o,n){let r=o-e,A=n-t;return r*r+A*A}function D1(e,t){return{x:e.x+t.x,y:e.y+t.y}}var $0,IA=["MobilenetV1/offset_2/BiasAdd","MobilenetV1/heatmap_2/BiasAdd","MobilenetV1/displacement_fwd_2/BiasAdd","MobilenetV1/displacement_bwd_2/BiasAdd"],P5=1,i2=16,NA=50**2;function Bo(e,t,o,n,r,A,s=2){let a=g=>({y:A.get(g.y,g.x,e),x:A.get(g.y,g.x,A.shape[2]/2+e)}),i=(g,b,d)=>({y:V1(Math.round(g.y/i2),0,b-1),x:V1(Math.round(g.x/i2),0,d-1)}),[x,c]=n.shape,l=i(t.position,x,c),y=a(l),u=D1(t.position,y);for(let g=0;g<s;g++){let b=i(u,x,c),d=B1(b.y,b.x,o,r);u=D1({x:b.x*i2,y:b.y*i2},{x:d.x,y:d.y})}let m=i(u,x,c),P=n.get(m.y,m.x,o);return{position:u,part:S2[o],score:P}}function OA(e,t,o,n,r){let A=Lo.map(([y,f])=>[z2[y],z2[f]]),s=A.map(([,y])=>y),a=A.map(([y])=>y),i=t.shape[2],x=s.length,c=new Array(i),l=H1(e.part,i2,o);c[e.part.id]={score:e.score,part:S2[e.part.id],position:l};for(let y=x-1;y>=0;--y){let f=s[y],u=a[y];c[f]&&!c[u]&&(c[u]=Bo(y,c[f],u,t,o,r))}for(let y=0;y<x;++y){let f=a[y],u=s[y];c[f]&&!c[u]&&(c[u]=Bo(y,c[f],u,t,o,n))}return c}function LA(e,t,o,n,r){let[A,s]=r.shape,a=!0,i=Math.max(o-P5,0),x=Math.min(o+P5+1,A);for(let c=i;c<x;++c){let l=Math.max(n-P5,0),y=Math.min(n+P5+1,s);for(let f=l;f<y;++f)if(r.get(c,f,e)>t){a=!1;break}if(!a)break}return a}function WA(e,t){let[o,n,r]=t.shape,A=new M5(o*n*r,({score:s})=>s);for(let s=0;s<o;++s)for(let a=0;a<n;++a)for(let i=0;i<r;++i){let x=t.get(s,a,i);x<e||LA(i,x,s,a,t)&&A.enqueue({score:x,part:{heatmapY:s,heatmapX:a,id:i}})}return A}function Ho(e,{x:t,y:o},n){return e.some(({keypoints:r})=>{var s;let A=(s=r[n])==null?void 0:s.position;return A?Go(o,t,A.y,A.x)<=NA:!1})}function FA(e,t){return t.reduce((n,{position:r,score:A},s)=>(Ho(e,r,s)||(n+=A),n),0)/t.length}function GA(e,t,o,n,r,A){let s=[],a=WA(A,t);for(;s.length<r&&!a.empty();){let i=a.dequeue(),x=H1(i.part,i2,e);if(Ho(s,x,i.part.id))continue;let c=OA(i,t,e,o,n);c=c.filter(f=>f.score>A);let l=FA(s,c),y=Wo(c);l>A&&s.push({keypoints:c,box:y,score:Math.round(100*l)/100})}return s}async function Z1(e,t){let o=z0.tidy(()=>{if(!$0.inputs[0].shape)return[];let s=z0.image.resizeBilinear(e,[$0.inputs[0].shape[2],$0.inputs[0].shape[1]]),a=z0.sub(z0.div(z0.cast(s,"float32"),127.5),1),x=$0.execute(a,IA).map(c=>z0.squeeze(c,[0]));return x[1]=z0.sigmoid(x[1]),x}),n=await Promise.all(o.map(s=>s.buffer()));for(let s of o)z0.dispose(s);let r=await GA(n[0],n[1],n[2],n[3],t.body.maxDetected,t.body.minConfidence);return $0.inputs[0].shape?Fo(r,[e.shape[1],e.shape[2]],[$0.inputs[0].shape[2],$0.inputs[0].shape[1]]):[]}async function Vo(e){return!$0||v.initial?$0=await G(e.body.modelPath):e.debug&&p("cached model:",$0.modelUrl),$0}var n0=Z(D());var ne,X1=!1;async function q1(e){return!ne||v.initial?ne=await G(e.segmentation.modelPath):e.debug&&p("cached model:",ne.modelUrl),ne}async function Zo(e,t,o){var m,P;if(X1)return{data:[],canvas:null,alpha:null};X1=!0,ne||await q1(o);let n=await Ye(e,o),r=((m=n.tensor)==null?void 0:m.shape[2])||0,A=((P=n.tensor)==null?void 0:P.shape[1])||0;if(!n.tensor)return{data:[],canvas:null,alpha:null};let s={};s.resize=n0.image.resizeBilinear(n.tensor,[ne.inputs[0].shape?ne.inputs[0].shape[1]:0,ne.inputs[0].shape?ne.inputs[0].shape[2]:0],!1),n0.dispose(n.tensor),s.norm=n0.div(s.resize,V.tf255),s.res=ne.execute(s.norm),s.squeeze=n0.squeeze(s.res,0),s.squeeze.shape[2]===2?(s.softmax=n0.softmax(s.squeeze),[s.bg,s.fg]=n0.unstack(s.softmax,2),s.expand=n0.expandDims(s.fg,2),s.pad=n0.expandDims(s.expand,0),s.crop=n0.image.cropAndResize(s.pad,[[0,0,.5,.5]],[0],[r,A]),s.data=n0.squeeze(s.crop,0)):s.data=n0.image.resizeBilinear(s.squeeze,[A,r]);let a=Array.from(await s.data.data());if(v.node&&!v.Canvas&&typeof ImageData=="undefined")return o.debug&&p("canvas support missing"),Object.keys(s).forEach(g=>n0.dispose(s[g])),{data:a,canvas:null,alpha:null};let i=R0(r,A);n0.browser&&await n0.browser.toPixels(s.data,i);let x=i.getContext("2d");o.segmentation.blur&&o.segmentation.blur>0&&(x.filter=`blur(${o.segmentation.blur}px)`);let c=x.getImageData(0,0,r,A),l=R0(r,A),y=l.getContext("2d");n.canvas&&y.drawImage(n.canvas,0,0),y.globalCompositeOperation="darken",o.segmentation.blur&&o.segmentation.blur>0&&(y.filter=`blur(${o.segmentation.blur}px)`),y.drawImage(i,0,0),y.globalCompositeOperation="source-over",y.filter="none";let f=y.getImageData(0,0,r,A);for(let g=0;g<r*A;g++)f.data[4*g+3]=c.data[4*g+0];y.putImageData(f,0,0);let u=null;if(t&&l){u=R0(r,A);let g=await Ye(t,o);n0.dispose(g.tensor);let b=u.getContext("2d");b.drawImage(g.canvas,0,0,u.width,u.height),b.drawImage(l,0,0)}return Object.keys(s).forEach(g=>n0.dispose(s[g])),X1=!1,{data:a,canvas:l,alpha:i}}var C2=class{constructor(){T(this,"ssrnetage",null);T(this,"gear",null);T(this,"blazeposedetect",null);T(this,"blazepose",null);T(this,"centernet",null);T(this,"efficientpose",null);T(this,"mobilefacenet",null);T(this,"emotion",null);T(this,"facedetect",null);T(this,"faceiris",null);T(this,"facemesh",null);T(this,"faceres",null);T(this,"ssrnetgender",null);T(this,"handpose",null);T(this,"handskeleton",null);T(this,"handtrack",null);T(this,"liveness",null);T(this,"movenet",null);T(this,"nanodet",null);T(this,"posenet",null);T(this,"segmentation",null);T(this,"antispoof",null)}},U1=e=>{let t=0,o=0,n=0;for(let A of Object.values(q0))t+=A.sizeFromManifest,o+=A.sizeLoadedWeights,n+=A.sizeDesired;let r=n>0?o/n:0;return{numLoadedModels:Object.values(q0).length,numEnabledModels:void 0,numDefinedModels:Object.keys(e.models).length,percentageLoaded:r,totalSizeFromManifest:t,totalSizeWeights:o,totalSizeLoading:n,totalSizeEnabled:void 0,modelStats:Object.values(q0)}};function R5(e){for(let t of Object.keys(e.models))e.models[t]=null}async function Y1(e){var t,o,n,r,A,s,a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0;v.initial&&R5(e),e.config.hand.enabled&&(!e.models.handpose&&((o=(t=e.config.hand.detector)==null?void 0:t.modelPath)==null?void 0:o.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await w1(e.config)),!e.models.handskeleton&&e.config.hand.landmarks&&((r=(n=e.config.hand.detector)==null?void 0:n.modelPath)==null?void 0:r.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await w1(e.config))),e.config.body.enabled&&!e.models.blazepose&&((s=(A=e.config.body)==null?void 0:A.modelPath)==null?void 0:s.includes("blazepose"))&&(e.models.blazepose=d3(e.config)),e.config.body.enabled&&!e.models.blazeposedetect&&e.config.body.detector&&e.config.body.detector.modelPath&&(e.models.blazeposedetect=c3(e.config)),e.config.body.enabled&&!e.models.efficientpose&&((i=(a=e.config.body)==null?void 0:a.modelPath)==null?void 0:i.includes("efficientpose"))&&(e.models.efficientpose=b3(e.config)),e.config.body.enabled&&!e.models.movenet&&((c=(x=e.config.body)==null?void 0:x.modelPath)==null?void 0:c.includes("movenet"))&&(e.models.movenet=Co(e.config)),e.config.body.enabled&&!e.models.posenet&&((y=(l=e.config.body)==null?void 0:l.modelPath)==null?void 0:y.includes("posenet"))&&(e.models.posenet=Vo(e.config)),e.config.face.enabled&&!e.models.facedetect&&(e.models.facedetect=n3(e.config)),e.config.face.enabled&&((f=e.config.face.antispoof)==null?void 0:f.enabled)&&!e.models.antispoof&&(e.models.antispoof=Zt(e.config)),e.config.face.enabled&&((u=e.config.face.liveness)==null?void 0:u.enabled)&&!e.models.liveness&&(e.models.liveness=vo(e.config)),e.config.face.enabled&&((m=e.config.face.description)==null?void 0:m.enabled)&&!e.models.faceres&&(e.models.faceres=X3(e.config)),e.config.face.enabled&&((P=e.config.face.emotion)==null?void 0:P.enabled)&&!e.models.emotion&&(e.models.emotion=R3(e.config)),e.config.face.enabled&&((g=e.config.face.iris)==null?void 0:g.enabled)&&!((b=e.config.face.attention)!=null&&b.enabled)&&!e.models.faceiris&&(e.models.faceiris=N3(e.config)),e.config.face.enabled&&((d=e.config.face.mesh)==null?void 0:d.enabled)&&!e.models.facemesh&&(e.models.facemesh=B3(e.config)),e.config.face.enabled&&((M=e.config.face.gear)==null?void 0:M.enabled)&&!e.models.gear&&(e.models.gear=Ct(e.config)),e.config.face.enabled&&((S=e.config.face.ssrnet)==null?void 0:S.enabled)&&!e.models.ssrnetage&&(e.models.ssrnetage=Lt(e.config)),e.config.face.enabled&&((w=e.config.face.ssrnet)==null?void 0:w.enabled)&&!e.models.ssrnetgender&&(e.models.ssrnetgender=Bt(e.config)),e.config.face.enabled&&((j=e.config.face.mobilefacenet)==null?void 0:j.enabled)&&!e.models.mobilefacenet&&(e.models.mobilefacenet=z3(e.config)),e.config.hand.enabled&&!e.models.handtrack&&((F=(C=e.config.hand.detector)==null?void 0:C.modelPath)==null?void 0:F.includes("handtrack"))&&(e.models.handtrack=bo(e.config)),e.config.hand.enabled&&e.config.hand.landmarks&&!e.models.handskeleton&&((Y=(H=e.config.hand.detector)==null?void 0:H.modelPath)==null?void 0:Y.includes("handtrack"))&&(e.models.handskeleton=go(e.config)),e.config.object.enabled&&!e.models.centernet&&((x0=(J=e.config.object)==null?void 0:J.modelPath)==null?void 0:x0.includes("centernet"))&&(e.models.centernet=p3(e.config)),e.config.object.enabled&&!e.models.nanodet&&((G0=(E=e.config.object)==null?void 0:E.modelPath)==null?void 0:G0.includes("nanodet"))&&(e.models.nanodet=No(e.config)),e.config.segmentation.enabled&&!e.models.segmentation&&(e.models.segmentation=q1(e.config));for await(let B0 of Object.keys(e.models))e.models[B0]&&typeof e.models[B0]!="undefined"&&(e.models[B0]=await e.models[B0])}async function K1(e){let t=["const","placeholder","noop","pad","squeeze","add","sub","mul","div"];for(let o of Object.keys(e.models)){let n=e.models[o];if(!n)continue;let r=[],A=n==null?void 0:n.executor;if(A&&A.graph.nodes)for(let a of Object.values(A.graph.nodes)){let i=a.op.toLowerCase();r.includes(i)||r.push(i)}else!A&&e.config.debug&&p("model signature not determined:",o);let s=[];for(let a of r)!t.includes(a)&&!e.env.kernels.includes(a)&&!e.env.kernels.includes(a.replace("_",""))&&!e.env.kernels.includes(a.replace("native",""))&&!e.env.kernels.includes(a.replace("v2",""))&&s.push(a);e.config.debug&&s.length>0&&p("model validation failed:",o,s)}}var t0={name:"humangl",priority:999,canvas:null,gl:null,extensions:[],webGLattr:{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!1,desynchronized:!0}};function BA(){let e=t0.gl;!e||(t0.extensions=e.getSupportedExtensions())}async function qo(e){var t;if(e.config.backend==="humangl"&&(t0.name in y0.engine().registry&&(!t0.gl||!t0.gl.getParameter(t0.gl.VERSION))&&(p("error: humangl backend invalid context"),R5(e)),!y0.findBackend(t0.name))){try{t0.canvas=await R0(100,100)}catch(n){p("error: cannot create canvas:",n);return}try{if(t0.gl=(t=t0.canvas)==null?void 0:t.getContext("webgl2",t0.webGLattr),!t0.gl.getParameter(t0.gl.VERSION).includes("2.0")){p("override: using fallback webgl backend as webgl 2.0 is not detected"),e.config.backend="webgl";return}t0.canvas&&(t0.canvas.addEventListener("webglcontextlost",async r=>{throw p("error: humangl:",r.type),p("possible browser memory leak using webgl or conflict with multiple backend registrations"),e.emit("error"),new Error("backend error: webgl context lost")}),t0.canvas.addEventListener("webglcontextrestored",r=>{p("error: humangl context restored:",r)}),t0.canvas.addEventListener("webglcontextcreationerror",r=>{p("error: humangl context create:",r)}))}catch(n){p("error: cannot get WebGL context:",n);return}try{y0.setWebGLContext(2,t0.gl)}catch(n){p("error: cannot set WebGL context:",n);return}try{let n=new y0.GPGPUContext(t0.gl);y0.registerBackend(t0.name,()=>new y0.MathBackendWebGL(n),t0.priority)}catch(n){p("error: cannot register WebGL backend:",n);return}try{y0.getKernelsForBackend("webgl").forEach(r=>{let A={...r,backendName:t0.name};y0.registerKernel(A)})}catch(n){p("error: cannot update WebGL backend registration:",n);return}let o=y0.backend().getGPGPUContext?y0.backend().getGPGPUContext().gl:null;if(o)p(`humangl webgl version:${o.getParameter(o.VERSION)} renderer:${o.getParameter(o.RENDERER)}`);else{p("error: no current gl context:",o,t0.gl);return}try{y0.ENV.set("WEBGL_VERSION",2)}catch(n){p("error: cannot set WebGL backend flags:",n);return}BA(),p("backend registered:",t0.name)}}var I=Z(D());function HA(){if(!v.kernels.includes("mod")){let e={kernelName:"Mod",backendName:I.getBackend(),kernelFunc:t=>I.tidy(()=>I.sub(t.inputs.a,I.mul(I.div(t.inputs.a,t.inputs.b),t.inputs.b)))};I.registerKernel(e),v.kernels.push("mod")}if(!v.kernels.includes("floormod")){let e={kernelName:"FloorMod",backendName:I.getBackend(),kernelFunc:t=>I.tidy(()=>I.floorDiv(t.inputs.a/t.inputs.b)*t.inputs.b+I.mod(t.inputs.a,t.inputs.b))};I.registerKernel(e),v.kernels.push("floormod")}}async function T5(e,t=!1){if(e.state="backend",t||v.initial||e.config.backend&&e.config.backend.length>0&&I.getBackend()!==e.config.backend){let o=h();if(e.config.backend&&e.config.backend.length>0){if(typeof window=="undefined"&&typeof WorkerGlobalScope!="undefined"&&e.config.debug&&e.config.debug&&p("running inside web worker"),v.browser&&e.config.backend==="tensorflow"&&(e.config.debug&&p("override: backend set to tensorflow while running in browser"),e.config.backend="humangl"),v.node&&(e.config.backend==="webgl"||e.config.backend==="humangl")&&(e.config.debug&&p(`override: backend set to ${e.config.backend} while running in nodejs`),e.config.backend="tensorflow"),v.browser&&e.config.backend==="webgpu")if(typeof navigator=="undefined"||typeof navigator.gpu=="undefined")p("override: backend set to webgpu but browser does not support webgpu"),e.config.backend="humangl";else{let r=await navigator.gpu.requestAdapter();if(e.config.debug&&p("enumerated webgpu adapter:",r),!r)p("override: backend set to webgpu but browser reports no available gpu"),e.config.backend="humangl";else{let A="requestAdapterInfo"in r?await r.requestAdapterInfo():void 0;p("webgpu adapter info:",A)}}e.config.backend==="humangl"&&await qo(e);let n=Object.keys(I.engine().registryFactory);if(e.config.debug&&p("available backends:",n),n.includes(e.config.backend)||(p(`error: backend ${e.config.backend} not found in registry`),e.config.backend=v.node?"tensorflow":"webgl",e.config.debug&&p(`override: setting backend ${e.config.backend}`)),e.config.debug&&p("setting backend:",e.config.backend),e.config.backend==="wasm"){try{I.env().set("CANVAS2D_WILL_READ_FREQUENTLY",!0)}catch(s){}if(e.config.debug&&p("wasm path:",e.config.wasmPath),typeof(I==null?void 0:I.setWasmPaths)!="undefined")await I.setWasmPaths(e.config.wasmPath,e.config.wasmPlatformFetch);else throw new Error("backend error: attempting to use wasm backend but wasm path is not set");let r=await I.env().getAsync("WASM_HAS_SIMD_SUPPORT"),A=await I.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");e.config.debug&&p(`wasm execution: ${r?"SIMD":"no SIMD"} ${A?"multithreaded":"singlethreaded"}`),e.config.debug&&!r&&p("warning: wasm simd support is not enabled")}try{await I.setBackend(e.config.backend),await I.ready(),It()}catch(r){return p("error: cannot set backend:",e.config.backend,r),!1}}if(I.getBackend()==="humangl"&&(I.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),I.ENV.set("WEBGL_CPU_FORWARD",!0),I.ENV.set("WEBGL_USE_SHAPES_UNIFORMS",!0),I.ENV.set("CPU_HANDOFF_SIZE_THRESHOLD",256),typeof e.config.deallocate!="undefined"&&e.config.deallocate&&(p("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),I.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",0)),I.backend().getGPGPUContext)){let n=await I.backend().getGPGPUContext().gl;e.config.debug&&p(`gl version:${n.getParameter(n.VERSION)} renderer:${n.getParameter(n.RENDERER)}`)}I.getBackend(),I.enableProdMode(),await I.ready(),e.performance.initBackend=Math.trunc(h()-o),e.config.backend=I.getBackend(),await v.updateBackend(),HA()}return!0}function c5(e,t){for(let o of e){let n={kernelName:o,backendName:t.backend,kernelFunc:()=>{t.debug&&p("kernelFunc",o,t.backend)}};I.registerKernel(n)}v.kernels=I.getKernelsForBackend(I.getBackend()).map(o=>o.kernelName.toLowerCase())}var ot={};ue(ot,{all:()=>tt,body:()=>y2,canvas:()=>et,face:()=>l2,gesture:()=>d2,hand:()=>x2,object:()=>c2,options:()=>P0,person:()=>$1});var V0=e=>{if(!e)p("draw error: invalid canvas");else if(!e.getContext)p("draw error: canvas context not defined");else{let t=e.getContext("2d");if(!t)p("draw error: cannot get canvas context");else return t}return null},Xe=e=>Math.round(e*180/Math.PI),me=(e,t)=>{if(!t.useDepth||typeof e=="undefined")return t.color;let o=Uint8ClampedArray.from([127+2*e,127-2*e,255]);return`rgba(${o[0]}, ${o[1]}, ${o[2]}, ${t.alpha})`};function pe(e,t,o,n,r){e.fillStyle=me(n,r),e.beginPath(),e.arc(t,o,r.pointSize,0,2*Math.PI),e.fill()}function re(e,t,o,n,r,A){if(e.beginPath(),e.lineWidth=A.lineWidth,A.useCurves){let s=(t+t+n)/2,a=(o+o+r)/2;e.ellipse(s,a,n/2,r/2,0,0,2*Math.PI)}else e.moveTo(t+A.roundRect,o),e.lineTo(t+n-A.roundRect,o),e.quadraticCurveTo(t+n,o,t+n,o+A.roundRect),e.lineTo(t+n,o+r-A.roundRect),e.quadraticCurveTo(t+n,o+r,t+n-A.roundRect,o+r),e.lineTo(t+A.roundRect,o+r),e.quadraticCurveTo(t,o+r,t,o+r-A.roundRect),e.lineTo(t,o+A.roundRect),e.quadraticCurveTo(t,o,t+A.roundRect,o),e.closePath();e.stroke()}function J1(e,t,o){if(!(t.length<2)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let n of t)e.strokeStyle=me(n[2]||0,o),e.lineTo(Math.trunc(n[0]),Math.trunc(n[1]));e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function Yo(e,t,o){if(!(t.length<2)){if(e.lineWidth=o.lineWidth,!o.useCurves||t.length<=2){J1(e,t,o);return}e.moveTo(t[0][0],t[0][1]);for(let n=0;n<t.length-2;n++){let r=(t[n][0]+t[n+1][0])/2,A=(t[n][1]+t[n+1][1])/2;e.quadraticCurveTo(t[n][0],t[n][1],r,A)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function Q1(e,t,o,n=5){let r,A,s;e.beginPath(),e.moveTo(t[0],t[1]),e.lineTo(o[0],o[1]),r=Math.atan2(o[1]-t[1],o[0]-t[0]),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.moveTo(A,s),r+=1/3*(2*Math.PI),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.lineTo(A,s),r+=1/3*(2*Math.PI),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.lineTo(A,s),e.closePath(),e.stroke(),e.fill()}var P0={color:"rgba(173, 216, 230, 0.6)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",alpha:.5,font:'small-caps 16px "Segoe UI"',lineHeight:18,lineWidth:4,pointSize:2,roundRect:8,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawAttention:!0,drawGestures:!0,drawPolygons:!0,drawGaze:!0,fillPolygons:!1,useDepth:!0,useCurves:!1};var U;function DA(e,t){if(U.drawLabels){let o=[];if(o.push(`face: ${Math.trunc(100*e.score)}%`),e.genderScore&&o.push(`${e.gender||""} ${Math.trunc(100*e.genderScore)}%`),e.age&&o.push(`age: ${e.age||""}`),e.iris&&o.push(`distance: ${e.iris}`),e.real&&o.push(`real: ${Math.trunc(100*e.real)}%`),e.live&&o.push(`live: ${Math.trunc(100*e.live)}%`),e.emotion&&e.emotion.length>0){let n=e.emotion.map(r=>`${Math.trunc(100*r.score)}% ${r.emotion}`);n.length>3&&(n.length=3),o.push(n.join(" "))}e.rotation&&e.rotation.angle&&e.rotation.gaze&&(e.rotation.angle.roll&&o.push(`roll: ${Xe(e.rotation.angle.roll)}\xB0 yaw:${Xe(e.rotation.angle.yaw)}\xB0 pitch:${Xe(e.rotation.angle.pitch)}\xB0`),e.rotation.gaze.bearing&&o.push(`gaze: ${Xe(e.rotation.gaze.bearing)}\xB0`)),o.length===0&&o.push("face"),t.fillStyle=U.color;for(let n=o.length-1;n>=0;n--){let r=Math.max(e.box[0],0),A=n*U.lineHeight+e.box[1];U.shadowColor&&U.shadowColor!==""&&(t.fillStyle=U.shadowColor,t.fillText(o[n],r+5,A+16)),t.fillStyle=U.labelColor,t.fillText(o[n],r+4,A+15)}}}function ZA(e,t){if(e.annotations&&e.annotations.leftEyeIris&&e.annotations.leftEyeIris[0]){t.strokeStyle=U.useDepth?"rgba(255, 200, 255, 0.3)":U.color,t.beginPath();let o=Math.abs(e.annotations.leftEyeIris[3][0]-e.annotations.leftEyeIris[1][0])/2,n=Math.abs(e.annotations.leftEyeIris[4][1]-e.annotations.leftEyeIris[2][1])/2;t.ellipse(e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),U.fillPolygons&&(t.fillStyle=U.useDepth?"rgba(255, 255, 200, 0.3)":U.color,t.fill())}if(e.annotations&&e.annotations.rightEyeIris&&e.annotations.rightEyeIris[0]){t.strokeStyle=U.useDepth?"rgba(255, 200, 255, 0.3)":U.color,t.beginPath();let o=Math.abs(e.annotations.rightEyeIris[3][0]-e.annotations.rightEyeIris[1][0])/2,n=Math.abs(e.annotations.rightEyeIris[4][1]-e.annotations.rightEyeIris[2][1])/2;t.ellipse(e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),U.fillPolygons&&(t.fillStyle=U.useDepth?"rgba(255, 255, 200, 0.3)":U.color,t.fill())}}function XA(e,t){var o;if(U.drawGaze&&((o=e.rotation)==null?void 0:o.angle)&&typeof Path2D!="undefined"){t.strokeStyle="pink";let n=e.box[0]+e.box[2]/2-e.box[3]*Xe(e.rotation.angle.yaw)/90,r=e.box[1]+e.box[3]/2+e.box[2]*Xe(e.rotation.angle.pitch)/90,A=new Path2D(`
+`;var I5=(e,t,o)=>{let n=new RegExp("\\b"+t+" \\w+ (\\w+)","ig");e.replace(n,(r,A)=>(o[A]=0,r))},j5=class{constructor(t,o,n){T(this,"uniform",{});T(this,"attribute",{});T(this,"gl");T(this,"id");T(this,"compile",(t,o)=>{let n=this.gl.createShader(o);return n?(this.gl.shaderSource(n,t),this.gl.compileShader(n),this.gl.getShaderParameter(n,this.gl.COMPILE_STATUS)?n:(p(`filter: gl compile failed: ${this.gl.getShaderInfoLog(n)}`),null)):(p("filter: could not create shader"),null)});this.gl=t;let r=this.compile(o,this.gl.VERTEX_SHADER),A=this.compile(n,this.gl.FRAGMENT_SHADER);if(this.id=this.gl.createProgram(),!(!r||!A)){if(!this.id){p("filter: could not create webgl program");return}if(this.gl.attachShader(this.id,r),this.gl.attachShader(this.id,A),this.gl.linkProgram(this.id),!this.gl.getProgramParameter(this.id,this.gl.LINK_STATUS)){p(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);return}this.gl.useProgram(this.id),I5(o,"attribute",this.attribute);for(let s in this.attribute)this.attribute[s]=this.gl.getAttribLocation(this.id,s);I5(o,"uniform",this.uniform),I5(n,"uniform",this.uniform);for(let s in this.uniform)this.uniform[s]=this.gl.getUniformLocation(this.id,s)}}};function Tt(){let e=0,t=null,o=!1,n=-1,r=[null,null],A=[],s=null,a=null,i=R0(100,100),x={},c={INTERMEDIATE:1},l=i.getContext("webgl");if(!l){p("filter: cannot get webgl context");return}this.gl=l;function y(b,d){if(!(b===i.width&&d===i.height)){if(i.width=b,i.height=d,!s){let M=new Float32Array([-1,-1,0,1,1,-1,1,1,-1,1,0,0,-1,1,0,0,1,-1,1,1,1,1,1,0]);s=l.createBuffer(),l.bindBuffer(l.ARRAY_BUFFER,s),l.bufferData(l.ARRAY_BUFFER,M,l.STATIC_DRAW),l.pixelStorei(l.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}l.viewport(0,0,i.width,i.height),r=[null,null]}}function f(b,d){let M=l.createFramebuffer();l.bindFramebuffer(l.FRAMEBUFFER,M);let S=l.createRenderbuffer();l.bindRenderbuffer(l.RENDERBUFFER,S);let w=l.createTexture();return l.bindTexture(l.TEXTURE_2D,w),l.texImage2D(l.TEXTURE_2D,0,l.RGBA,b,d,0,l.RGBA,l.UNSIGNED_BYTE,null),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MAG_FILTER,l.LINEAR),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MIN_FILTER,l.LINEAR),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_S,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_T,l.CLAMP_TO_EDGE),l.framebufferTexture2D(l.FRAMEBUFFER,l.COLOR_ATTACHMENT0,l.TEXTURE_2D,w,0),l.bindTexture(l.TEXTURE_2D,null),l.bindFramebuffer(l.FRAMEBUFFER,null),{fbo:M,texture:w}}function u(b){return r[b]=r[b]||f(i.width,i.height),r[b]}function m(b=0){if(!a)return;let d=null,M=null,S=!1;e===0?d=t:d=u(n).texture||null,e++,o&&!(b&c.INTERMEDIATE)?(M=null,S=e%2===0):(n=(n+1)%2,M=u(n).fbo||null),l.bindTexture(l.TEXTURE_2D,d),l.bindFramebuffer(l.FRAMEBUFFER,M),l.uniform1f(a.uniform.flipY,S?-1:1),l.drawArrays(l.TRIANGLES,0,6)}function P(b){if(x[b])return a=x[b],l.useProgram((a?a.id:null)||null),a;if(a=new j5(l,bt,b),!a)return p("filter: could not get webgl program"),null;let d=Float32Array.BYTES_PER_ELEMENT,M=4*d;return l.enableVertexAttribArray(a.attribute.pos),l.vertexAttribPointer(a.attribute.pos,2,l.FLOAT,!1,M,0*d),l.enableVertexAttribArray(a.attribute.uv),l.vertexAttribPointer(a.attribute.uv,2,l.FLOAT,!1,M,2*d),x[b]=a,a}let g={colorMatrix:b=>{let d=new Float32Array(b);d[4]/=255,d[9]/=255,d[14]/=255,d[19]/=255;let M=d[18]===1&&d[3]===0&&d[8]===0&&d[13]===0&&d[15]===0&&d[16]===0&&d[17]===0&&d[19]===0?Mt:gt,S=P(M);!S||(l.uniform1fv(S.uniform.m,d),m())},brightness:b=>{let d=(b||0)+1;g.colorMatrix([d,0,0,0,0,0,d,0,0,0,0,0,d,0,0,0,0,0,1,0])},saturation:b=>{let d=(b||0)*2/3+1,M=(d-1)*-.5;g.colorMatrix([d,M,M,0,0,M,d,M,0,0,M,M,d,0,0,0,0,0,1,0])},desaturate:()=>{g.saturation(-1)},contrast:b=>{let d=(b||0)+1,M=-128*(d-1);g.colorMatrix([d,0,0,0,M,0,d,0,0,M,0,0,d,0,M,0,0,0,1,0])},negative:()=>{g.contrast(-2)},hue:b=>{b=(b||0)/180*Math.PI;let d=Math.cos(b),M=Math.sin(b),S=.213,w=.715,j=.072;g.colorMatrix([S+d*(1-S)+M*-S,w+d*-w+M*-w,j+d*-j+M*(1-j),0,0,S+d*-S+M*.143,w+d*(1-w)+M*.14,j+d*-j+M*-.283,0,0,S+d*-S+M*-(1-S),w+d*-w+M*w,j+d*(1-j)+M*j,0,0,0,0,0,1,0])},desaturateLuminance:()=>{g.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},sepia:()=>{g.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},brownie:()=>{g.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},vintagePinhole:()=>{g.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},kodachrome:()=>{g.colorMatrix([1.1285582396593525,-.3967382283601348,-.03992559172921793,0,63.72958762196502,-.16404339962244616,1.0835251566291304,-.05498805115633132,0,24.732407896706203,-.16786010706155763,-.5603416277695248,1.6014850761964943,0,35.62982807460946,0,0,0,1,0])},technicolor:()=>{g.colorMatrix([1.9125277891456083,-.8545344976951645,-.09155508482755585,0,11.793603434377337,-.3087833385928097,1.7658908555458428,-.10601743074722245,0,-70.35205161461398,-.231103377548616,-.7501899197440212,1.847597816108189,0,30.950940869491138,0,0,0,1,0])},polaroid:()=>{g.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},shiftToBGR:()=>{g.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},convolution:b=>{let d=new Float32Array(b),M=1/i.width,S=1/i.height,w=P(vt);!w||(l.uniform1fv(w.uniform.m,d),l.uniform2f(w.uniform.px,M,S),m())},detectEdges:()=>{g.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},sobelX:()=>{g.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},sobelY:()=>{g.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},sharpen:b=>{let d=b||1;g.convolution.call(this,[0,-1*d,0,-1*d,1+4*d,-1*d,0,-1*d,0])},emboss:b=>{let d=b||1;g.convolution.call(this,[-2*d,-1*d,0,-1*d,1,1*d,0,1*d,2*d])},blur:b=>{let d=b/7/i.width,M=b/7/i.height,S=P(Rt);!S||(l.uniform2f(S.uniform.px,0,M),m(c.INTERMEDIATE),l.uniform2f(S.uniform.px,d,0),m())},pixelate:b=>{let d=b/i.width,M=b/i.height,S=P(Pt);!S||(l.uniform2f(S.uniform.size,d,M),m())}};this.add=function(b){let d=Array.prototype.slice.call(arguments,1),M=g[b];A.push({func:M,args:d})},this.reset=function(){A=[]},this.get=function(){return A},this.apply=function(b){y(b.width,b.height),e=0,t||(t=l.createTexture()),l.bindTexture(l.TEXTURE_2D,t),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_S,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_T,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MIN_FILTER,l.NEAREST),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MAG_FILTER,l.NEAREST),l.texImage2D(l.TEXTURE_2D,0,l.RGBA,l.RGBA,l.UNSIGNED_BYTE,b);for(let d=0;d<A.length;d++){o=d===A.length-1;let M=A[d];M.func.apply(this,M.args||[])}return i},this.draw=function(b){return this.add("brightness",0),this.apply(b)}}var X=Z(D());async function L2(e){let t=e.shape.length===4?X.squeeze(e):e,o=X.split(t,3,2),n=[X.min(o[0]),X.min(o[1]),X.min(o[2])],r=[X.max(o[0]),X.max(o[1]),X.max(o[2])],A=await Promise.all(r.map(f=>f.data())),s=.99*Math.max(A[0][0],A[1][0],A[2][0]),a=[X.sub(o[0],n[0]),X.sub(o[1],n[1]),X.sub(o[2],n[2])],i=[X.sub(r[0],n[0]),X.sub(r[1],n[1]),X.sub(r[2],n[2])],x=[X.div(s,i[0]),X.div(s,i[1]),X.div(s,i[2])],c=[X.mul(a[0],x[0]),X.mul(a[1],x[1]),X.mul(a[2],x[2])],l=X.stack([c[0],c[1],c[2]],2),y=X.reshape(l,[1,t.shape[0],t.shape[1],3]);return X.dispose([...o,...n,...r,...a,...i,...x,...c,l,t]),y}var W2=3840,q=null,l0=null,Ue=null,e0,ae={inputSum:0,cacheDiff:1,sumMethod:0,inputTensor:void 0};function R0(e,t){let o;if(v.browser)if(v.worker){if(typeof OffscreenCanvas=="undefined")throw new Error("canvas error: attempted to run in web worker but OffscreenCanvas is not supported");o=new OffscreenCanvas(e,t)}else{if(typeof document=="undefined")throw new Error("canvas error: attempted to run in browser but DOM is not defined");o=document.createElement("canvas"),o.width=e,o.height=t}else typeof v.Canvas!="undefined"?o=new v.Canvas(e,t):typeof globalThis.Canvas!="undefined"&&(o=new globalThis.Canvas(e,t));return o}function F2(e,t){let o=t||R0(e.width,e.height);return o.getContext("2d").drawImage(e,0,0),o}async function Ye(e,t,o=!0){if(!e)return t.debug&&p("input error: input is missing"),{tensor:null,canvas:null};if(!(e instanceof O.Tensor)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(typeof v.Canvas!="undefined"&&e instanceof v.Canvas)&&!(typeof globalThis.Canvas!="undefined"&&e instanceof globalThis.Canvas)&&!(typeof ImageData!="undefined"&&e instanceof ImageData)&&!(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)&&!(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)&&!(typeof HTMLMediaElement!="undefined"&&e instanceof HTMLMediaElement)&&!(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)&&!(typeof HTMLCanvasElement!="undefined"&&e instanceof HTMLCanvasElement)&&!(typeof OffscreenCanvas!="undefined"&&e instanceof OffscreenCanvas))throw new Error("input error: type is not recognized");if(e instanceof O.Tensor){let n=null;if(e.isDisposedInternal)throw new Error("input error: attempted to use tensor but it is disposed");if(!e.shape)throw new Error("input error: attempted to use tensor without a shape");if(e.shape.length===3){if(e.shape[2]===3)n=O.expandDims(e,0);else if(e.shape[2]===4){let r=O.slice3d(e,[0,0,0],[-1,-1,3]);n=O.expandDims(r,0),O.dispose(r)}}else e.shape.length===4&&(e.shape[3]===3?n=O.clone(e):e.shape[3]===4&&(n=O.slice4d(e,[0,0,0,0],[-1,-1,-1,3])));if(n==null||n.shape.length!==4||n.shape[0]!==1||n.shape[3]!==3)throw new Error(`input error: attempted to use tensor with unrecognized shape: ${e.shape}`);if(n.dtype==="int32"){let r=O.cast(n,"float32");O.dispose(n),n=r}return{tensor:n,canvas:t.filter.return?l0:null}}else{if(typeof e.readyState!="undefined"&&e.readyState<=2)return t.debug&&p("input stream is not ready"),{tensor:null,canvas:q};let n=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,r=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0;if(!n||!r)return t.debug&&p("cannot determine input dimensions"),{tensor:null,canvas:q};let A=n,s=r;if(A>W2&&(A=W2,s=Math.trunc(A*r/n)),s>W2&&(s=W2,A=Math.trunc(s*n/r)),(t.filter.width||0)>0?A=t.filter.width:(t.filter.height||0)>0&&(A=n*((t.filter.height||0)/r)),(t.filter.height||0)>0?s=t.filter.height:(t.filter.width||0)>0&&(s=r*((t.filter.width||0)/n)),!A||!s)throw new Error("input error: cannot determine dimension");(!q||(q==null?void 0:q.width)!==A||(q==null?void 0:q.height)!==s)&&(q=R0(A,s));let a=q.getContext("2d");if(typeof ImageData!="undefined"&&e instanceof ImageData?a.putImageData(e,0,0):t.filter.flip&&typeof a.translate!="undefined"?(a.translate(n,0),a.scale(-1,1),a.drawImage(e,0,0,n,r,0,0,q==null?void 0:q.width,q==null?void 0:q.height),a.setTransform(1,0,0,1,0,0)):a.drawImage(e,0,0,n,r,0,0,q==null?void 0:q.width,q==null?void 0:q.height),(!l0||q.width!==l0.width||(q==null?void 0:q.height)!==(l0==null?void 0:l0.height))&&(l0=R0(q.width,q.height)),t.filter.enabled&&v.webgl.supported?(e0||(e0=v.browser?new Tt:null),v.filter=!!e0,!e0||!e0.add?(t.debug&&p("input process error: cannot initialize filters"),v.webgl.supported=!1,t.filter.enabled=!1,F2(q,l0)):(e0.reset(),t.filter.brightness!==0&&e0.add("brightness",t.filter.brightness),t.filter.contrast!==0&&e0.add("contrast",t.filter.contrast),t.filter.sharpness!==0&&e0.add("sharpen",t.filter.sharpness),t.filter.blur!==0&&e0.add("blur",t.filter.blur),t.filter.saturation!==0&&e0.add("saturation",t.filter.saturation),t.filter.hue!==0&&e0.add("hue",t.filter.hue),t.filter.negative&&e0.add("negative"),t.filter.sepia&&e0.add("sepia"),t.filter.vintage&&e0.add("brownie"),t.filter.sepia&&e0.add("sepia"),t.filter.kodachrome&&e0.add("kodachrome"),t.filter.technicolor&&e0.add("technicolor"),t.filter.polaroid&&e0.add("polaroid"),t.filter.pixelate!==0&&e0.add("pixelate",t.filter.pixelate),e0.get()>0?l0=e0.apply(q):l0=e0.draw(q))):(F2(q,l0),e0&&(e0=null),v.filter=!!e0),!o)return{tensor:null,canvas:l0};if(!l0)throw new Error("canvas error: cannot create output");let i,x=3;if(typeof ImageData!="undefined"&&e instanceof ImageData||e.data&&e.width&&e.height)if(v.browser&&O.browser)i=O.browser?O.browser.fromPixels(e):null;else{x=e.data.length/e.height/e.width;let y=new Uint8Array(e.data.buffer);i=O.tensor(y,[e.height,e.width,x],"int32")}else if((!Ue||l0.width!==Ue.width||l0.height!==Ue.height)&&(Ue=R0(l0.width,l0.height)),O.browser&&v.browser)t.backend==="webgl"||t.backend==="humangl"||t.backend==="webgpu"?i=O.browser.fromPixels(l0):(Ue=F2(l0),i=O.browser.fromPixels(Ue));else{let u=F2(l0).getContext("2d").getImageData(0,0,A,s);x=u.data.length/A/s;let m=new Uint8Array(u.data.buffer);i=O.tensor(m,[A,s,x])}if(x===4){let y=O.slice3d(i,[0,0,0],[-1,-1,3]);O.dispose(i),i=y}if(!i)throw new Error("input error: cannot create tensor");let c=O.cast(i,"float32"),l=t.filter.equalization?await L2(c):O.expandDims(c,0);return O.dispose([i,c]),{tensor:l,canvas:t.filter.return?l0:null}}}async function wt(e,t){let o=!1;if(e.cacheSensitivity===0||!t.shape||t.shape.length!==4||t.shape[1]>2048||t.shape[2]>2048)return o;if(!ae.inputTensor)ae.inputTensor=O.clone(t);else if(ae.inputTensor.shape[1]!==t.shape[1]||ae.inputTensor.shape[2]!==t.shape[2])O.dispose(ae.inputTensor),ae.inputTensor=O.clone(t);else{let n={};n.diff=O.sub(t,ae.inputTensor),n.squared=O.mul(n.diff,n.diff),n.sum=O.sum(n.squared);let A=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;O.dispose([ae.inputTensor,n.diff,n.squared,n.sum]),ae.inputTensor=O.clone(t),o=A<=(e.cacheSensitivity||0)}return o}async function kt(e,t,o){let n={};if(!t||!o||t.shape.length!==4||t.shape.length!==o.shape.length)return e.debug||p("invalid input tensor or tensor shapes do not match:",t.shape,o.shape),0;if(t.shape[0]!==1||o.shape[0]!==1||t.shape[3]!==3||o.shape[3]!==3)return e.debug||p("input tensors must be of shape [1, height, width, 3]:",t.shape,o.shape),0;n.input1=O.clone(t),n.input2=t.shape[1]!==o.shape[1]||t.shape[2]!==o.shape[2]?O.image.resizeBilinear(o,[t.shape[1],t.shape[2]]):O.clone(o),n.diff=O.sub(n.input1,n.input2),n.squared=O.mul(n.diff,n.diff),n.sum=O.sum(n.squared);let A=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;return O.dispose([n.input1,n.input2,n.diff,n.squared,n.sum]),A}var O5=class{constructor(){T(this,"browser");T(this,"node");T(this,"worker");T(this,"platform","");T(this,"agent","");T(this,"backends",[]);T(this,"initial");T(this,"filter");T(this,"tfjs");T(this,"offscreen");T(this,"perfadd",!1);T(this,"wasm",{supported:void 0,backend:void 0,simd:void 0,multithread:void 0});T(this,"webgl",{supported:void 0,backend:void 0,version:void 0,renderer:void 0});T(this,"webgpu",{supported:void 0,backend:void 0,adapter:void 0});T(this,"cpu",{model:void 0,flags:[]});T(this,"kernels",[]);T(this,"Canvas");T(this,"Image");T(this,"ImageData");if(this.browser=typeof navigator!="undefined",this.node=typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined",this.tfjs={version:p0.version["tfjs-core"]},this.offscreen=typeof OffscreenCanvas!="undefined",this.initial=!0,this.worker=this.browser&&this.offscreen?typeof WorkerGlobalScope!="undefined":void 0,typeof navigator!="undefined"){let t=navigator.userAgent.match(/\(([^()]+)\)/g);if(t&&t[0]){let o=t[0].match(/\(([^()]+)\)/g);this.platform=o&&o[0]?o[0].replace(/\(|\)/g,""):"",this.agent=navigator.userAgent.replace(t[0],""),this.platform[1]&&(this.agent=this.agent.replace(t[1],"")),this.agent=this.agent.replace(/  /g," ")}}else typeof process!="undefined"&&(this.platform=`${process.platform} ${process.arch}`,this.agent=`NodeJS ${process.version}`)}async updateBackend(){this.backends=Object.keys(p0.engine().registryFactory),this.wasm.supported=typeof WebAssembly!="undefined",this.wasm.backend=this.backends.includes("wasm"),this.wasm.supported&&this.wasm.backend&&p0.getBackend()==="wasm"&&(this.wasm.simd=await p0.env().getAsync("WASM_HAS_SIMD_SUPPORT"),this.wasm.multithread=await p0.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT"));let t=R0(100,100),o=t?t.getContext("webgl2"):void 0;if(this.webgl.supported=typeof o!="undefined",this.webgl.backend=this.backends.includes("webgl"),this.webgl.supported&&this.webgl.backend&&(p0.getBackend()==="webgl"||p0.getBackend()==="humangl")){let n=p0.backend().gpgpu!=="undefined"?await p0.backend().getGPGPUContext().gl:null;n&&(this.webgl.version=n.getParameter(n.VERSION),this.webgl.renderer=n.getParameter(n.RENDERER))}this.webgpu.supported=this.browser&&typeof navigator.gpu!="undefined",this.webgpu.backend=this.backends.includes("webgpu");try{this.webgpu.supported&&(this.webgpu.adapter=(await navigator.gpu.requestAdapter()).name)}catch(n){this.webgpu.supported=!1}try{this.kernels=p0.getKernelsForBackend(p0.getBackend()).map(n=>n.kernelName.toLowerCase())}catch(n){}}async updateCPU(){let t={model:"",flags:[]};this.node&&this.platform.startsWith("linux"),this.cpu?this.cpu=t:Object.defineProperty(this,"cpu",{value:t})}},v=new O5;var G2=Z(D());var N5={};ue(N5,{age:()=>Pn,antispoof:()=>Rn,blazeface:()=>wn,"blazeface-back":()=>vn,"blazeface-front":()=>Tn,"blazepose-detector2d":()=>kn,"blazepose-detector3d":()=>En,"blazepose-full":()=>zn,"blazepose-heavy":()=>Sn,"blazepose-lite":()=>Cn,default:()=>yr,efficientpose:()=>In,emotion:()=>jn,faceboxes:()=>On,facemesh:()=>Bn,"facemesh-attention":()=>Ln,"facemesh-attention-alt":()=>Nn,"facemesh-detection-full":()=>Wn,"facemesh-detection-short":()=>Fn,"facemesh-orig":()=>Gn,faceres:()=>Vn,"faceres-deep":()=>Hn,gear:()=>Dn,gender:()=>Xn,"gender-ssrnet-imdb":()=>Zn,handdetect:()=>qn,"handlandmark-full":()=>Un,"handlandmark-lite":()=>Yn,"handlandmark-sparse":()=>Kn,handskeleton:()=>Jn,handtrack:()=>Qn,iris:()=>_n,liveness:()=>$n,"mb3-centernet":()=>er,meet:()=>tr,mobileface:()=>or,mobilefacenet:()=>nr,"movenet-lightning":()=>rr,"movenet-multipose":()=>Ar,"movenet-thunder":()=>sr,nanodet:()=>ar,posenet:()=>ir,selfie:()=>lr});var Pn=161240,Rn=853098,vn=538928,Tn=402048,wn=538928,kn=7499400,En=5928856,zn=6338290,Sn=27501554,Cn=2725490,In=5651240,jn=820516,On=2013002,Nn=2387598,Ln=2382414,Wn=1026192,Fn=201268,Gn=2955780,Bn=1477958,Hn=13957620,Vn=6978814,Dn=1498916,Zn=161236,Xn=201808,qn=3515612,Un=5431368,Yn=2023432,Kn=5286322,Jn=5502280,Qn=2964837,_n=2599092,$n=592976,er=4030290,tr=372228,or=2183192,nr=5171976,rr=4650216,Ar=9448838,sr=12477112,ar=7574558,ir=5032780,lr=212886,yr={age:Pn,antispoof:Rn,"blazeface-back":vn,"blazeface-front":Tn,blazeface:wn,"blazepose-detector2d":kn,"blazepose-detector3d":En,"blazepose-full":zn,"blazepose-heavy":Sn,"blazepose-lite":Cn,efficientpose:In,emotion:jn,faceboxes:On,"facemesh-attention-alt":Nn,"facemesh-attention":Ln,"facemesh-detection-full":Wn,"facemesh-detection-short":Fn,"facemesh-orig":Gn,facemesh:Bn,"faceres-deep":Hn,faceres:Vn,gear:Dn,"gender-ssrnet-imdb":Zn,gender:Xn,handdetect:qn,"handlandmark-full":Un,"handlandmark-lite":Yn,"handlandmark-sparse":Kn,handskeleton:Jn,handtrack:Qn,iris:_n,liveness:$n,"mb3-centernet":er,meet:tr,mobileface:or,mobilefacenet:nr,"movenet-lightning":rr,"movenet-multipose":Ar,"movenet-thunder":sr,nanodet:ar,posenet:ir,selfie:lr};var v0={cacheModels:!0,cacheSupported:!0,verbose:!0,debug:!1,modelBasePath:""},q0={};async function xr(e,t){return v0.debug&&p("load model fetch:",e,t),fetch(e,t)}function Et(e){v0.cacheModels=e.cacheModels,v0.verbose=e.debug,v0.modelBasePath=e.modelBasePath}async function G(e){var x,c,l;let t=pt(v0.modelBasePath,e||"");t.toLowerCase().endsWith(".json")||(t+=".json");let o=t.includes("/")?t.split("/"):t.split("\\"),n=o[o.length-1].replace(".json",""),r="indexeddb://"+n;q0[n]={name:n,sizeFromManifest:0,sizeLoadedWeights:0,sizeDesired:N5[n],inCache:!1},v0.cacheSupported=typeof window!="undefined"&&typeof window.localStorage!="undefined"&&typeof window.indexedDB!="undefined";let A={};try{A=v0.cacheSupported&&v0.cacheModels?await G2.io.listModels():{}}catch(y){v0.cacheSupported=!1}q0[n].inCache=v0.cacheSupported&&v0.cacheModels&&Object.keys(A).includes(r);let s=typeof fetch=="undefined"?{}:{fetchFunc:(y,f)=>xr(y,f)},a=new G2.GraphModel(q0[n].inCache?r:t,s),i=!1;try{a.findIOHandler(),v0.debug&&p("model load handler:",a.handler);let y=await a.handler.load();q0[n].sizeFromManifest=((x=y==null?void 0:y.weightData)==null?void 0:x.byteLength)||0,a.loadSync(y),q0[n].sizeLoadedWeights=((l=(c=a==null?void 0:a.artifacts)==null?void 0:c.weightData)==null?void 0:l.byteLength)||0,v0.verbose&&p("load model:",a.modelUrl,{bytes:q0[n].sizeLoadedWeights},v0),i=!0}catch(y){p("error loading model:",t,y)}if(i&&v0.cacheModels&&v0.cacheSupported&&!q0[n].inCache)try{let y=await a.save(r);p("model saved:",r,y)}catch(y){p("error saving model:",t,y)}return a}var ee=Z(D());var L5="2.9.1";var s0=Z(D());var v5={};ue(v5,{Models:()=>C2,getModelStats:()=>U1,load:()=>Y1,reset:()=>R5,validate:()=>K1});var B2=Z(D());var D0,W5=[],fr=["white","black","asian","indian","other"],mr=[15,23,28,35.5,45.5,55.5,65],zt=0,St=0,F5=Number.MAX_SAFE_INTEGER;async function Ct(e){var t;return v.initial&&(D0=null),D0?e.debug&&p("cached model:",D0.modelUrl):D0=await G((t=e.face.gear)==null?void 0:t.modelPath),D0}async function G5(e,t,o,n){var s,a;if(!D0)return{age:0,gender:"unknown",genderScore:0,race:[]};let r=F5<(((s=t.face.gear)==null?void 0:s.skipFrames)||0),A=(((a=t.face.gear)==null?void 0:a.skipTime)||0)>h()-St;return t.skipAllowed&&A&&r&&zt===n&&W5[o]?(F5++,W5[o]):(F5=0,new Promise(async i=>{var g,b;if(!(D0!=null&&D0.inputs[0].shape))return;let x={},c=[[0,.1,.9,.9]];x.resize=B2.image.cropAndResize(e,c,[0],[D0.inputs[0].shape[2],D0.inputs[0].shape[1]]);let l={age:0,gender:"unknown",genderScore:0,race:[]};(g=t.face.gear)!=null&&g.enabled&&([x.age,x.gender,x.race]=D0.execute(x.resize,["age_output","gender_output","race_output"]));let y=await x.gender.data();l.gender=y[0]>y[1]?"male":"female",l.genderScore=Math.round(100*(y[0]>y[1]?y[0]:y[1]))/100;let f=await x.race.data();for(let d=0;d<f.length;d++)f[d]>(((b=t.face.gear)==null?void 0:b.minConfidence)||.2)&&l.race.push({score:Math.round(100*f[d])/100,race:fr[d]});l.race.sort((d,M)=>M.score-d.score);let m=Array.from(await x.age.data()).map((d,M)=>[mr[M],d]).sort((d,M)=>M[1]-d[1]),P=m[0][0];for(let d=1;d<m.length;d++)P+=m[d][1]*(m[d][0]-P);l.age=Math.round(10*P)/10,Object.keys(x).forEach(d=>B2.dispose(x[d])),W5[o]=l,zt=n,St=h(),i(l)}))}var Ke=Z(D());var be=Z(D()),V={tf255:255,tf1:1,tf2:2,tf05:.5,tf127:127.5,rgb:[.2989,.587,.114]};function jt(){V.tf255=be.scalar(255,"float32"),V.tf1=be.scalar(1,"float32"),V.tf2=be.scalar(2,"float32"),V.tf05=be.scalar(.5,"float32"),V.tf127=be.scalar(127.5,"float32"),V.rgb=be.tensor1d([.2989,.587,.114],"float32")}var S0,H2=[],Ot=0,Nt=0,B5=Number.MAX_SAFE_INTEGER;async function Lt(e){return v.initial&&(S0=null),S0?e.debug&&p("cached model:",S0.modelUrl):S0=await G(e.face.ssrnet.modelPathAge),S0}async function H5(e,t,o,n){var s,a,i,x;if(!S0)return{age:0};let r=B5<(((s=t.face.ssrnet)==null?void 0:s.skipFrames)||0),A=(((a=t.face.ssrnet)==null?void 0:a.skipTime)||0)>h()-Nt;return t.skipAllowed&&r&&A&&Ot===n&&((i=H2[o])==null?void 0:i.age)&&((x=H2[o])==null?void 0:x.age)>0?(B5++,H2[o]):(B5=0,new Promise(async c=>{if(!(S0!=null&&S0.inputs)||!S0.inputs[0]||!S0.inputs[0].shape)return;let l={};l.resize=Ke.image.resizeBilinear(e,[S0.inputs[0].shape[2],S0.inputs[0].shape[1]],!1),l.enhance=Ke.mul(l.resize,V.tf255);let y={age:0};if(t.face.ssrnet.enabled&&(l.age=S0.execute(l.enhance)),l.age){let f=await l.age.data();y.age=Math.trunc(10*f[0])/10}Object.keys(l).forEach(f=>Ke.dispose(l[f])),H2[o]=y,Ot=n,Nt=h(),c(y)}))}var u0=Z(D());var Z0,V2=[],Ft=0,Gt=0,V5=Number.MAX_SAFE_INTEGER,D5=[.2989,.587,.114];async function Bt(e){return v.initial&&(Z0=null),Z0?e.debug&&p("cached model:",Z0.modelUrl):Z0=await G(e.face.ssrnet.modelPathGender),Z0}async function Z5(e,t,o,n){var s,a,i,x;if(!Z0)return{gender:"unknown",genderScore:0};let r=V5<(((s=t.face.ssrnet)==null?void 0:s.skipFrames)||0),A=(((a=t.face.ssrnet)==null?void 0:a.skipTime)||0)>h()-Gt;return t.skipAllowed&&r&&A&&Ft===n&&((i=V2[o])==null?void 0:i.gender)&&((x=V2[o])==null?void 0:x.genderScore)>0?(V5++,V2[o]):(V5=0,new Promise(async c=>{if(!(Z0!=null&&Z0.inputs[0].shape))return;let l={};l.resize=u0.image.resizeBilinear(e,[Z0.inputs[0].shape[2],Z0.inputs[0].shape[1]],!1),l.enhance=u0.tidy(()=>{let[u,m,P]=u0.split(l.resize,3,3),g=u0.mul(u,D5[0]),b=u0.mul(m,D5[1]),d=u0.mul(P,D5[2]),M=u0.addN([g,b,d]);return u0.mul(u0.sub(M,V.tf05),2)});let y={gender:"unknown",genderScore:0};t.face.ssrnet.enabled&&(l.gender=Z0.execute(l.enhance));let f=await l.gender.data();y.gender=f[0]>f[1]?"female":"male",y.genderScore=f[0]>f[1]?Math.trunc(100*f[0])/100:Math.trunc(100*f[1])/100,Object.keys(l).forEach(u=>u0.dispose(l[u])),V2[o]=y,Ft=n,Gt=h(),c(y)}))}var Z2=Z(D());var h0,D2=[],X5=Number.MAX_SAFE_INTEGER,Vt=0,Dt=0;async function Zt(e){var t;return v.initial&&(h0=null),h0?e.debug&&p("cached model:",h0.modelUrl):h0=await G((t=e.face.antispoof)==null?void 0:t.modelPath),h0}async function q5(e,t,o,n){var s,a;if(!h0)return 0;let r=(((s=t.face.antispoof)==null?void 0:s.skipTime)||0)>h()-Dt,A=X5<(((a=t.face.antispoof)==null?void 0:a.skipFrames)||0);return t.skipAllowed&&r&&A&&Vt===n&&D2[o]?(X5++,D2[o]):(X5=0,new Promise(async i=>{let x=Z2.image.resizeBilinear(e,[h0!=null&&h0.inputs[0].shape?h0.inputs[0].shape[2]:0,h0!=null&&h0.inputs[0].shape?h0.inputs[0].shape[1]:0],!1),c=h0==null?void 0:h0.execute(x),l=(await c.data())[0];D2[o]=Math.round(100*l)/100,Vt=n,Dt=h(),Z2.dispose([x,c]),i(D2[o])}))}var N=Z(D());var ie=Z(D());var X0={silhouette:[10,338,297,332,284,251,389,356,454,323,361,288,397,365,379,378,400,377,152,148,176,149,150,136,172,58,132,93,234,127,162,21,54,103,67,109],lipsUpperOuter:[185,40,39,37,0,267,269,270,409],lipsLowerOuter:[61,146,91,181,84,17,314,405,321,375,291],lipsUpperInner:[191,80,81,82,13,312,311,310,415],lipsLowerInner:[78,95,88,178,87,14,317,402,318,324,308],lipsLowerSemiOuter:[76,77,90,180,85,16,315,404,320,307,306],lipsUpperSemiOuter:[184,74,73,72,11,302,303,304,408],lipsLowerSemiInner:[62,96,89,179,86,15,316,403,319,325,292],lipsUpperSemiInner:[183,42,41,38,12,268,271,272,407],rightEyeUpper0:[246,161,160,159,158,157,173],rightEyeLower0:[33,7,163,144,145,153,154,155,133],rightEyeUpper1:[247,30,29,27,28,56,190],rightEyeLower1:[130,25,110,24,23,22,26,112,243],rightEyeUpper2:[113,225,224,223,222,221,189],rightEyeLower2:[226,31,228,229,230,231,232,233,244],rightEyeLower3:[143,111,117,118,119,120,121,128,245],rightEyebrowUpper:[156,70,63,105,66,107,55,193],rightEyebrowLower:[35,124,46,53,52,65],rightEyeIris:[473,474,475,476,477],leftEyeUpper0:[466,388,387,386,385,384,398],leftEyeLower0:[263,249,390,373,374,380,381,382,362],leftEyeUpper1:[467,260,259,257,258,286,414],leftEyeLower1:[359,255,339,254,253,252,256,341,463],leftEyeUpper2:[342,445,444,443,442,441,413],leftEyeLower2:[446,261,448,449,450,451,452,453,464],leftEyeLower3:[372,340,346,347,348,349,350,357,465],leftEyebrowUpper:[383,300,293,334,296,336,285,417],leftEyebrowLower:[265,353,276,283,282,295],leftEyeIris:[468,469,470,471,472],midwayBetweenEyes:[168],noseTip:[1],noseBottom:[2],noseRightCorner:[98],noseLeftCorner:[327],rightCheek:[205],leftCheek:[425]},U5={count:468,mouth:13,symmetryLine:[13,X0.midwayBetweenEyes[0]]},je={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},Y5=[{key:"EyeUpper0",indices:[9,10,11,12,13,14,15]},{key:"EyeUpper1",indices:[25,26,27,28,29,30,31]},{key:"EyeUpper2",indices:[41,42,43,44,45,46,47]},{key:"EyeLower0",indices:[0,1,2,3,4,5,6,7,8]},{key:"EyeLower1",indices:[16,17,18,19,20,21,22,23,24]},{key:"EyeLower2",indices:[32,33,34,35,36,37,38,39,40]},{key:"EyeLower3",indices:[54,55,56,57,58,59,60,61,62]},{key:"EyebrowUpper",indices:[63,64,65,66,67,68,69,70]},{key:"EyebrowLower",indices:[48,49,50,51,52,53]}],R2=[[.499976992607117,.652534008026123],[.500025987625122,.547487020492554],[.499974012374878,.602371990680695],[.482113003730774,.471979022026062],[.500150978565216,.527155995368958],[.499909996986389,.498252987861633],[.499523013830185,.40106201171875],[.289712011814117,.380764007568359],[.499954998493195,.312398016452789],[.499987006187439,.269918978214264],[.500023007392883,.107050001621246],[.500023007392883,.666234016418457],[.5000159740448,.679224014282227],[.500023007392883,.692348003387451],[.499976992607117,.695277988910675],[.499976992607117,.70593398809433],[.499976992607117,.719385027885437],[.499976992607117,.737019002437592],[.499967992305756,.781370997428894],[.499816000461578,.562981009483337],[.473773002624512,.573909997940063],[.104906998574734,.254140973091125],[.365929991006851,.409575998783112],[.338757991790771,.41302502155304],[.311120003461838,.409460008144379],[.274657994508743,.389131009578705],[.393361985683441,.403706014156342],[.345234006643295,.344011008739471],[.370094001293182,.346076011657715],[.319321990013123,.347265005111694],[.297903001308441,.353591024875641],[.24779200553894,.410809993743896],[.396889001131058,.842755019664764],[.280097991228104,.375599980354309],[.106310002505779,.399955987930298],[.2099249958992,.391353011131287],[.355807989835739,.534406006336212],[.471751004457474,.65040397644043],[.474155008792877,.680191993713379],[.439785003662109,.657229006290436],[.414617002010345,.66654098033905],[.450374007225037,.680860996246338],[.428770989179611,.682690978050232],[.374971002340317,.727805018424988],[.486716985702515,.547628998756409],[.485300987958908,.527395009994507],[.257764995098114,.314490020275116],[.401223003864288,.455172002315521],[.429818987846375,.548614978790283],[.421351999044418,.533740997314453],[.276895999908447,.532056987285614],[.483370006084442,.499586999416351],[.33721199631691,.282882988452911],[.296391993761063,.293242990970612],[.169294998049736,.193813979625702],[.447580009698868,.302609980106354],[.392390012741089,.353887975215912],[.354490011930466,.696784019470215],[.067304998636246,.730105042457581],[.442739009857178,.572826027870178],[.457098007202148,.584792017936707],[.381974011659622,.694710969924927],[.392388999462128,.694203019142151],[.277076005935669,.271932005882263],[.422551989555359,.563233017921448],[.385919004678726,.281364023685455],[.383103013038635,.255840003490448],[.331431001424789,.119714021682739],[.229923993349075,.232002973556519],[.364500999450684,.189113974571228],[.229622006416321,.299540996551514],[.173287004232407,.278747975826263],[.472878992557526,.666198015213013],[.446828007698059,.668527007102966],[.422762006521225,.673889994621277],[.445307999849319,.580065965652466],[.388103008270264,.693961024284363],[.403039008378983,.706539988517761],[.403629004955292,.693953037261963],[.460041999816895,.557139039039612],[.431158006191254,.692366003990173],[.452181994915009,.692366003990173],[.475387006998062,.692366003990173],[.465828001499176,.779190003871918],[.472328990697861,.736225962638855],[.473087012767792,.717857003211975],[.473122000694275,.704625964164734],[.473033010959625,.695277988910675],[.427942007780075,.695277988910675],[.426479011774063,.703539967536926],[.423162013292313,.711845993995667],[.4183090031147,.720062971115112],[.390094995498657,.639572978019714],[.013953999616206,.560034036636353],[.499913990497589,.58014702796936],[.413199990987778,.69539999961853],[.409626007080078,.701822996139526],[.468080013990402,.601534962654114],[.422728985548019,.585985004901886],[.463079988956451,.593783974647522],[.37211999297142,.47341400384903],[.334562003612518,.496073007583618],[.411671012639999,.546965003013611],[.242175996303558,.14767599105835],[.290776997804642,.201445996761322],[.327338010072708,.256527006626129],[.399509996175766,.748921036720276],[.441727995872498,.261676013469696],[.429764986038208,.187834024429321],[.412198007106781,.108901023864746],[.288955003023148,.398952007293701],[.218936994671822,.435410976409912],[.41278201341629,.398970007896423],[.257135003805161,.355440020561218],[.427684992551804,.437960982322693],[.448339998722076,.536936044692993],[.178560003638268,.45755398273468],[.247308000922203,.457193970680237],[.286267012357712,.467674970626831],[.332827985286713,.460712015628815],[.368755996227264,.447206974029541],[.398963987827301,.432654976844788],[.476410001516342,.405806005001068],[.189241006970406,.523923993110657],[.228962004184723,.348950982093811],[.490725994110107,.562400996685028],[.404670000076294,.485132992267609],[.019469000399113,.401564002037048],[.426243007183075,.420431017875671],[.396993011236191,.548797011375427],[.266469985246658,.376977026462555],[.439121007919312,.51895797252655],[.032313998788595,.644356966018677],[.419054001569748,.387154996395111],[.462783008813858,.505746960639954],[.238978996872902,.779744982719421],[.198220998048782,.831938028335571],[.107550002634525,.540755033493042],[.183610007166862,.740257024765015],[.134409993886948,.333683013916016],[.385764002799988,.883153975009918],[.490967005491257,.579378008842468],[.382384985685349,.508572995662689],[.174399003386497,.397670984268188],[.318785011768341,.39623498916626],[.343364000320435,.400596976280212],[.396100014448166,.710216999053955],[.187885001301765,.588537991046906],[.430987000465393,.944064974784851],[.318993002176285,.898285031318665],[.266247987747192,.869701027870178],[.500023007392883,.190576016902924],[.499976992607117,.954452991485596],[.366169989109039,.398822009563446],[.393207013607025,.39553701877594],[.410373002290726,.391080021858215],[.194993004202843,.342101991176605],[.388664990663528,.362284004688263],[.365961998701096,.355970978736877],[.343364000320435,.355356991291046],[.318785011768341,.35834002494812],[.301414996385574,.363156020641327],[.058132998645306,.319076001644135],[.301414996385574,.387449026107788],[.499987989664078,.618434011936188],[.415838003158569,.624195992946625],[.445681989192963,.566076993942261],[.465844005346298,.620640993118286],[.49992299079895,.351523995399475],[.288718998432159,.819945991039276],[.335278987884521,.852819979190826],[.440512001514435,.902418971061707],[.128294005990028,.791940987110138],[.408771991729736,.373893976211548],[.455606997013092,.451801002025604],[.499877005815506,.908990025520325],[.375436991453171,.924192011356354],[.11421000212431,.615022003650665],[.448662012815475,.695277988910675],[.4480200111866,.704632043838501],[.447111994028091,.715808033943176],[.444831997156143,.730794012546539],[.430011987686157,.766808986663818],[.406787008047104,.685672998428345],[.400738000869751,.681069016456604],[.392399996519089,.677703022956848],[.367855995893478,.663918972015381],[.247923001646996,.601333022117615],[.452769994735718,.420849978923798],[.43639200925827,.359887003898621],[.416164010763168,.368713974952698],[.413385987281799,.692366003990173],[.228018000721931,.683571994304657],[.468268007040024,.352671027183533],[.411361992359161,.804327011108398],[.499989002943039,.469825029373169],[.479153990745544,.442654013633728],[.499974012374878,.439637005329132],[.432112008333206,.493588984012604],[.499886006116867,.866917014122009],[.49991300702095,.821729004383087],[.456548988819122,.819200992584229],[.344549000263214,.745438992977142],[.37890899181366,.574010014533997],[.374292999505997,.780184984207153],[.319687992334366,.570737957954407],[.357154995203018,.604269981384277],[.295284003019333,.621580958366394],[.447750002145767,.862477004528046],[.410986006259918,.508723020553589],[.31395098567009,.775308012962341],[.354128003120422,.812552988529205],[.324548006057739,.703992962837219],[.189096003770828,.646299958229065],[.279776990413666,.71465802192688],[.1338230073452,.682700991630554],[.336768001317978,.644733011722565],[.429883986711502,.466521978378296],[.455527991056442,.548622965812683],[.437114000320435,.558896005153656],[.467287987470627,.529924988746643],[.414712011814117,.335219979286194],[.37704598903656,.322777986526489],[.344107985496521,.320150971412659],[.312875986099243,.32233202457428],[.283526003360748,.333190023899078],[.241245999932289,.382785975933075],[.102986000478268,.468762993812561],[.267612010240555,.424560010433197],[.297879010438919,.433175981044769],[.333433985710144,.433878004550934],[.366427004337311,.426115989685059],[.396012008190155,.416696012020111],[.420121014118195,.41022801399231],[.007561000064015,.480777025222778],[.432949006557465,.569517970085144],[.458638995885849,.479089021682739],[.473466008901596,.545744001865387],[.476087987422943,.563830018043518],[.468472003936768,.555056989192963],[.433990985155106,.582361996173859],[.483518004417419,.562983989715576],[.482482999563217,.57784903049469],[.42645001411438,.389798998832703],[.438998997211456,.39649498462677],[.450067013502121,.400434017181396],[.289712011814117,.368252992630005],[.276670008897781,.363372981548309],[.517862021923065,.471948027610779],[.710287988185883,.380764007568359],[.526226997375488,.573909997940063],[.895093023777008,.254140973091125],[.634069979190826,.409575998783112],[.661242008209229,.41302502155304],[.688880026340485,.409460008144379],[.725341975688934,.389131009578705],[.606630027294159,.40370500087738],[.654766023159027,.344011008739471],[.629905998706818,.346076011657715],[.680678009986877,.347265005111694],[.702096998691559,.353591024875641],[.75221198797226,.410804986953735],[.602918028831482,.842862963676453],[.719901978969574,.375599980354309],[.893692970275879,.399959981441498],[.790081977844238,.391354024410248],[.643998026847839,.534487962722778],[.528249025344849,.65040397644043],[.525849997997284,.680191040039062],[.560214996337891,.657229006290436],[.585384011268616,.66654098033905],[.549625992774963,.680860996246338],[.57122802734375,.682691991329193],[.624852001667023,.72809898853302],[.513050019741058,.547281980514526],[.51509702205658,.527251958847046],[.742246985435486,.314507007598877],[.598631024360657,.454979002475739],[.570338010787964,.548575043678284],[.578631997108459,.533622980117798],[.723087012767792,.532054007053375],[.516445994377136,.499638974666595],[.662801027297974,.282917976379395],[.70362401008606,.293271005153656],[.830704987049103,.193813979625702],[.552385985851288,.302568018436432],[.607609987258911,.353887975215912],[.645429015159607,.696707010269165],[.932694971561432,.730105042457581],[.557260990142822,.572826027870178],[.542901992797852,.584792017936707],[.6180260181427,.694710969924927],[.607590973377228,.694203019142151],[.722943007946014,.271963000297546],[.577413976192474,.563166975975037],[.614082992076874,.281386971473694],[.616907000541687,.255886018276215],[.668509006500244,.119913995265961],[.770092010498047,.232020974159241],[.635536015033722,.189248979091644],[.77039098739624,.299556016921997],[.826722025871277,.278755009174347],[.527121007442474,.666198015213013],[.553171992301941,.668527007102966],[.577238023281097,.673889994621277],[.554691970348358,.580065965652466],[.611896991729736,.693961024284363],[.59696102142334,.706539988517761],[.596370995044708,.693953037261963],[.539958000183105,.557139039039612],[.568841993808746,.692366003990173],[.547818005084991,.692366003990173],[.52461302280426,.692366003990173],[.534089982509613,.779141008853912],[.527670979499817,.736225962638855],[.526912987232208,.717857003211975],[.526877999305725,.704625964164734],[.526966989040375,.695277988910675],[.572058022022247,.695277988910675],[.573521018028259,.703539967536926],[.57683801651001,.711845993995667],[.581691026687622,.720062971115112],[.609944999217987,.639909982681274],[.986046016216278,.560034036636353],[.5867999792099,.69539999961853],[.590372025966644,.701822996139526],[.531915009021759,.601536989212036],[.577268004417419,.585934996604919],[.536915004253387,.593786001205444],[.627542972564697,.473352015018463],[.665585994720459,.495950996875763],[.588353991508484,.546862006187439],[.757824003696442,.14767599105835],[.709249973297119,.201507985591888],[.672684013843536,.256581008434296],[.600408971309662,.74900496006012],[.55826598405838,.261672019958496],[.570303976535797,.187870979309082],[.588165998458862,.109044015407562],[.711045026779175,.398952007293701],[.781069993972778,.435405015945435],[.587247014045715,.398931980133057],[.742869973182678,.355445981025696],[.572156012058258,.437651991844177],[.55186802148819,.536570012569427],[.821442008018494,.457556009292603],[.752701997756958,.457181990146637],[.71375697851181,.467626988887787],[.66711300611496,.460672974586487],[.631101012229919,.447153985500336],[.6008620262146,.432473003864288],[.523481011390686,.405627012252808],[.810747981071472,.523926019668579],[.771045982837677,.348959028720856],[.509127020835876,.562718033790588],[.595292985439301,.485023975372314],[.980530977249146,.401564002037048],[.573499977588654,.420000016689301],[.602994978427887,.548687994480133],[.733529984951019,.376977026462555],[.560611009597778,.519016981124878],[.967685997486115,.644356966018677],[.580985009670258,.387160003185272],[.537728011608124,.505385041236877],[.760966002941132,.779752969741821],[.801778972148895,.831938028335571],[.892440974712372,.54076099395752],[.816350996494293,.740260004997253],[.865594983100891,.333687007427216],[.614073991775513,.883246004581451],[.508952975273132,.579437971115112],[.617941975593567,.508316040039062],[.825608015060425,.397674977779388],[.681214988231659,.39623498916626],[.656635999679565,.400596976280212],[.603900015354156,.710216999053955],[.81208598613739,.588539004325867],[.56801301240921,.944564998149872],[.681007981300354,.898285031318665],[.733752012252808,.869701027870178],[.633830010890961,.398822009563446],[.606792986392975,.39553701877594],[.589659988880157,.391062021255493],[.805015981197357,.342108011245728],[.611334979534149,.362284004688263],[.634037971496582,.355970978736877],[.656635999679565,.355356991291046],[.681214988231659,.35834002494812],[.698584973812103,.363156020641327],[.941866993904114,.319076001644135],[.698584973812103,.387449026107788],[.584177017211914,.624107003211975],[.554318010807037,.566076993942261],[.534153997898102,.62064003944397],[.711217999458313,.819975018501282],[.664629995822906,.852871000766754],[.559099972248077,.902631998062134],[.871706008911133,.791940987110138],[.591234028339386,.373893976211548],[.544341027736664,.451583981513977],[.624562978744507,.924192011356354],[.88577002286911,.615028977394104],[.551338016986847,.695277988910675],[.551980018615723,.704632043838501],[.552887976169586,.715808033943176],[.555167973041534,.730794012546539],[.569944024085999,.767035007476807],[.593203008174896,.685675978660583],[.599261999130249,.681069016456604],[.607599973678589,.677703022956848],[.631937980651855,.663500010967255],[.752032995223999,.601315021514893],[.547226011753082,.420395016670227],[.563543975353241,.359827995300293],[.583841025829315,.368713974952698],[.586614012718201,.692366003990173],[.771915018558502,.683578014373779],[.531597018241882,.352482974529266],[.588370978832245,.804440975189209],[.52079701423645,.442565023899078],[.567984998226166,.493479013442993],[.543282985687256,.819254994392395],[.655317008495331,.745514988899231],[.621008992195129,.574018001556396],[.625559985637665,.78031200170517],[.680198013782501,.570719003677368],[.64276397228241,.604337990283966],[.704662978649139,.621529996395111],[.552012026309967,.862591981887817],[.589071989059448,.508637011051178],[.685944974422455,.775357007980347],[.645735025405884,.812640011310577],[.675342977046967,.703978002071381],[.810858011245728,.646304965019226],[.72012197971344,.714666962623596],[.866151988506317,.682704985141754],[.663187026977539,.644596993923187],[.570082008838654,.466325998306274],[.544561982154846,.548375964164734],[.562758982181549,.558784961700439],[.531987011432648,.530140042304993],[.585271000862122,.335177004337311],[.622952997684479,.32277899980545],[.655896008014679,.320163011550903],[.687132000923157,.322345972061157],[.716481983661652,.333200991153717],[.758756995201111,.382786989212036],[.897013008594513,.468769013881683],[.732392013072968,.424547016620636],[.70211398601532,.433162987232208],[.66652500629425,.433866024017334],[.633504986763,.426087975502014],[.603875994682312,.416586995124817],[.579657971858978,.409945011138916],[.992439985275269,.480777025222778],[.567192018032074,.569419980049133],[.54136598110199,.478899002075195],[.526564002037048,.546118021011353],[.523913025856018,.563830018043518],[.531529009342194,.555056989192963],[.566035985946655,.582329034805298],[.51631098985672,.563053965568542],[.5174720287323,.577877044677734],[.573594987392426,.389806985855103],[.560697972774506,.395331978797913],[.549755990505219,.399751007556915],[.710287988185883,.368252992630005],[.723330020904541,.363372981548309]],Oe=[127,34,139,11,0,37,232,231,120,72,37,39,128,121,47,232,121,128,104,69,67,175,171,148,157,154,155,118,50,101,73,39,40,9,151,108,48,115,131,194,204,211,74,40,185,80,42,183,40,92,186,230,229,118,202,212,214,83,18,17,76,61,146,160,29,30,56,157,173,106,204,194,135,214,192,203,165,98,21,71,68,51,45,4,144,24,23,77,146,91,205,50,187,201,200,18,91,106,182,90,91,181,85,84,17,206,203,36,148,171,140,92,40,39,193,189,244,159,158,28,247,246,161,236,3,196,54,68,104,193,168,8,117,228,31,189,193,55,98,97,99,126,47,100,166,79,218,155,154,26,209,49,131,135,136,150,47,126,217,223,52,53,45,51,134,211,170,140,67,69,108,43,106,91,230,119,120,226,130,247,63,53,52,238,20,242,46,70,156,78,62,96,46,53,63,143,34,227,173,155,133,123,117,111,44,125,19,236,134,51,216,206,205,154,153,22,39,37,167,200,201,208,36,142,100,57,212,202,20,60,99,28,158,157,35,226,113,160,159,27,204,202,210,113,225,46,43,202,204,62,76,77,137,123,116,41,38,72,203,129,142,64,98,240,49,102,64,41,73,74,212,216,207,42,74,184,169,170,211,170,149,176,105,66,69,122,6,168,123,147,187,96,77,90,65,55,107,89,90,180,101,100,120,63,105,104,93,137,227,15,86,85,129,102,49,14,87,86,55,8,9,100,47,121,145,23,22,88,89,179,6,122,196,88,95,96,138,172,136,215,58,172,115,48,219,42,80,81,195,3,51,43,146,61,171,175,199,81,82,38,53,46,225,144,163,110,246,33,7,52,65,66,229,228,117,34,127,234,107,108,69,109,108,151,48,64,235,62,78,191,129,209,126,111,35,143,163,161,246,117,123,50,222,65,52,19,125,141,221,55,65,3,195,197,25,7,33,220,237,44,70,71,139,122,193,245,247,130,33,71,21,162,153,158,159,170,169,150,188,174,196,216,186,92,144,160,161,2,97,167,141,125,241,164,167,37,72,38,12,145,159,160,38,82,13,63,68,71,226,35,111,158,153,154,101,50,205,206,92,165,209,198,217,165,167,97,220,115,218,133,112,243,239,238,241,214,135,169,190,173,133,171,208,32,125,44,237,86,87,178,85,86,179,84,85,180,83,84,181,201,83,182,137,93,132,76,62,183,61,76,184,57,61,185,212,57,186,214,207,187,34,143,156,79,239,237,123,137,177,44,1,4,201,194,32,64,102,129,213,215,138,59,166,219,242,99,97,2,94,141,75,59,235,24,110,228,25,130,226,23,24,229,22,23,230,26,22,231,112,26,232,189,190,243,221,56,190,28,56,221,27,28,222,29,27,223,30,29,224,247,30,225,238,79,20,166,59,75,60,75,240,147,177,215,20,79,166,187,147,213,112,233,244,233,128,245,128,114,188,114,217,174,131,115,220,217,198,236,198,131,134,177,132,58,143,35,124,110,163,7,228,110,25,356,389,368,11,302,267,452,350,349,302,303,269,357,343,277,452,453,357,333,332,297,175,152,377,384,398,382,347,348,330,303,304,270,9,336,337,278,279,360,418,262,431,304,408,409,310,415,407,270,409,410,450,348,347,422,430,434,313,314,17,306,307,375,387,388,260,286,414,398,335,406,418,364,367,416,423,358,327,251,284,298,281,5,4,373,374,253,307,320,321,425,427,411,421,313,18,321,405,406,320,404,405,315,16,17,426,425,266,377,400,369,322,391,269,417,465,464,386,257,258,466,260,388,456,399,419,284,332,333,417,285,8,346,340,261,413,441,285,327,460,328,355,371,329,392,439,438,382,341,256,429,420,360,364,394,379,277,343,437,443,444,283,275,440,363,431,262,369,297,338,337,273,375,321,450,451,349,446,342,467,293,334,282,458,461,462,276,353,383,308,324,325,276,300,293,372,345,447,382,398,362,352,345,340,274,1,19,456,248,281,436,427,425,381,256,252,269,391,393,200,199,428,266,330,329,287,273,422,250,462,328,258,286,384,265,353,342,387,259,257,424,431,430,342,353,276,273,335,424,292,325,307,366,447,345,271,303,302,423,266,371,294,455,460,279,278,294,271,272,304,432,434,427,272,407,408,394,430,431,395,369,400,334,333,299,351,417,168,352,280,411,325,319,320,295,296,336,319,403,404,330,348,349,293,298,333,323,454,447,15,16,315,358,429,279,14,15,316,285,336,9,329,349,350,374,380,252,318,402,403,6,197,419,318,319,325,367,364,365,435,367,397,344,438,439,272,271,311,195,5,281,273,287,291,396,428,199,311,271,268,283,444,445,373,254,339,263,466,249,282,334,296,449,347,346,264,447,454,336,296,299,338,10,151,278,439,455,292,407,415,358,371,355,340,345,372,390,249,466,346,347,280,442,443,282,19,94,370,441,442,295,248,419,197,263,255,359,440,275,274,300,383,368,351,412,465,263,467,466,301,368,389,380,374,386,395,378,379,412,351,419,436,426,322,373,390,388,2,164,393,370,462,461,164,0,267,302,11,12,374,373,387,268,12,13,293,300,301,446,261,340,385,384,381,330,266,425,426,423,391,429,355,437,391,327,326,440,457,438,341,382,362,459,457,461,434,430,394,414,463,362,396,369,262,354,461,457,316,403,402,315,404,403,314,405,404,313,406,405,421,418,406,366,401,361,306,408,407,291,409,408,287,410,409,432,436,410,434,416,411,264,368,383,309,438,457,352,376,401,274,275,4,421,428,262,294,327,358,433,416,367,289,455,439,462,370,326,2,326,370,305,460,455,254,449,448,255,261,446,253,450,449,252,451,450,256,452,451,341,453,452,413,464,463,441,413,414,258,442,441,257,443,442,259,444,443,260,445,444,467,342,445,459,458,250,289,392,290,290,328,460,376,433,435,250,290,392,411,416,433,341,463,464,453,464,465,357,465,412,343,412,399,360,363,440,437,399,456,420,456,363,401,435,288,372,383,353,339,255,249,448,261,255,133,243,190,133,155,112,33,246,247,33,130,25,398,384,286,362,398,414,362,463,341,263,359,467,263,249,255,466,467,260,75,60,166,238,239,79,162,127,139,72,11,37,121,232,120,73,72,39,114,128,47,233,232,128,103,104,67,152,175,148,173,157,155,119,118,101,74,73,40,107,9,108,49,48,131,32,194,211,184,74,185,191,80,183,185,40,186,119,230,118,210,202,214,84,83,17,77,76,146,161,160,30,190,56,173,182,106,194,138,135,192,129,203,98,54,21,68,5,51,4,145,144,23,90,77,91,207,205,187,83,201,18,181,91,182,180,90,181,16,85,17,205,206,36,176,148,140,165,92,39,245,193,244,27,159,28,30,247,161,174,236,196,103,54,104,55,193,8,111,117,31,221,189,55,240,98,99,142,126,100,219,166,218,112,155,26,198,209,131,169,135,150,114,47,217,224,223,53,220,45,134,32,211,140,109,67,108,146,43,91,231,230,120,113,226,247,105,63,52,241,238,242,124,46,156,95,78,96,70,46,63,116,143,227,116,123,111,1,44,19,3,236,51,207,216,205,26,154,22,165,39,167,199,200,208,101,36,100,43,57,202,242,20,99,56,28,157,124,35,113,29,160,27,211,204,210,124,113,46,106,43,204,96,62,77,227,137,116,73,41,72,36,203,142,235,64,240,48,49,64,42,41,74,214,212,207,183,42,184,210,169,211,140,170,176,104,105,69,193,122,168,50,123,187,89,96,90,66,65,107,179,89,180,119,101,120,68,63,104,234,93,227,16,15,85,209,129,49,15,14,86,107,55,9,120,100,121,153,145,22,178,88,179,197,6,196,89,88,96,135,138,136,138,215,172,218,115,219,41,42,81,5,195,51,57,43,61,208,171,199,41,81,38,224,53,225,24,144,110,105,52,66,118,229,117,227,34,234,66,107,69,10,109,151,219,48,235,183,62,191,142,129,126,116,111,143,7,163,246,118,117,50,223,222,52,94,19,141,222,221,65,196,3,197,45,220,44,156,70,139,188,122,245,139,71,162,145,153,159,149,170,150,122,188,196,206,216,92,163,144,161,164,2,167,242,141,241,0,164,37,11,72,12,144,145,160,12,38,13,70,63,71,31,226,111,157,158,154,36,101,205,203,206,165,126,209,217,98,165,97,237,220,218,237,239,241,210,214,169,140,171,32,241,125,237,179,86,178,180,85,179,181,84,180,182,83,181,194,201,182,177,137,132,184,76,183,185,61,184,186,57,185,216,212,186,192,214,187,139,34,156,218,79,237,147,123,177,45,44,4,208,201,32,98,64,129,192,213,138,235,59,219,141,242,97,97,2,141,240,75,235,229,24,228,31,25,226,230,23,229,231,22,230,232,26,231,233,112,232,244,189,243,189,221,190,222,28,221,223,27,222,224,29,223,225,30,224,113,247,225,99,60,240,213,147,215,60,20,166,192,187,213,243,112,244,244,233,245,245,128,188,188,114,174,134,131,220,174,217,236,236,198,134,215,177,58,156,143,124,25,110,7,31,228,25,264,356,368,0,11,267,451,452,349,267,302,269,350,357,277,350,452,357,299,333,297,396,175,377,381,384,382,280,347,330,269,303,270,151,9,337,344,278,360,424,418,431,270,304,409,272,310,407,322,270,410,449,450,347,432,422,434,18,313,17,291,306,375,259,387,260,424,335,418,434,364,416,391,423,327,301,251,298,275,281,4,254,373,253,375,307,321,280,425,411,200,421,18,335,321,406,321,320,405,314,315,17,423,426,266,396,377,369,270,322,269,413,417,464,385,386,258,248,456,419,298,284,333,168,417,8,448,346,261,417,413,285,326,327,328,277,355,329,309,392,438,381,382,256,279,429,360,365,364,379,355,277,437,282,443,283,281,275,363,395,431,369,299,297,337,335,273,321,348,450,349,359,446,467,283,293,282,250,458,462,300,276,383,292,308,325,283,276,293,264,372,447,346,352,340,354,274,19,363,456,281,426,436,425,380,381,252,267,269,393,421,200,428,371,266,329,432,287,422,290,250,328,385,258,384,446,265,342,386,387,257,422,424,430,445,342,276,422,273,424,306,292,307,352,366,345,268,271,302,358,423,371,327,294,460,331,279,294,303,271,304,436,432,427,304,272,408,395,394,431,378,395,400,296,334,299,6,351,168,376,352,411,307,325,320,285,295,336,320,319,404,329,330,349,334,293,333,366,323,447,316,15,315,331,358,279,317,14,316,8,285,9,277,329,350,253,374,252,319,318,403,351,6,419,324,318,325,397,367,365,288,435,397,278,344,439,310,272,311,248,195,281,375,273,291,175,396,199,312,311,268,276,283,445,390,373,339,295,282,296,448,449,346,356,264,454,337,336,299,337,338,151,294,278,455,308,292,415,429,358,355,265,340,372,388,390,466,352,346,280,295,442,282,354,19,370,285,441,295,195,248,197,457,440,274,301,300,368,417,351,465,251,301,389,385,380,386,394,395,379,399,412,419,410,436,322,387,373,388,326,2,393,354,370,461,393,164,267,268,302,12,386,374,387,312,268,13,298,293,301,265,446,340,380,385,381,280,330,425,322,426,391,420,429,437,393,391,326,344,440,438,458,459,461,364,434,394,428,396,262,274,354,457,317,316,402,316,315,403,315,314,404,314,313,405,313,421,406,323,366,361,292,306,407,306,291,408,291,287,409,287,432,410,427,434,411,372,264,383,459,309,457,366,352,401,1,274,4,418,421,262,331,294,358,435,433,367,392,289,439,328,462,326,94,2,370,289,305,455,339,254,448,359,255,446,254,253,449,253,252,450,252,256,451,256,341,452,414,413,463,286,441,414,286,258,441,258,257,442,257,259,443,259,260,444,260,467,445,309,459,250,305,289,290,305,290,460,401,376,435,309,250,392,376,411,433,453,341,464,357,453,465,343,357,412,437,343,399,344,360,440,420,437,456,360,420,363,361,401,288,265,372,353,390,339,249,339,448,255];var ur=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],hr=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],br=[33,133,362,263,1,78,308],L7=ur.map(e=>R2[e]),W7=hr.map(e=>R2[e]),F7=br.map(e=>R2[e]);function ge(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var gr=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Mr=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Pr=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],Rr=[[474,475],[475,476],[476,477],[477,474]],vr=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],Tr=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],wr=[[469,470],[470,471],[471,472],[472,469]],kr=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]],G7={lips:ge(gr),leftEye:ge(Mr),leftEyebrow:ge(Pr),leftIris:ge(Rr),rightEye:ge(vr),rightEyebrow:ge(Tr),rightIris:ge(wr),faceOval:ge(kr)};var Je=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],X2=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],q2=(e,t)=>e?[Math.trunc(Math.max(0,e.startPoint[0])),Math.trunc(Math.max(0,e.startPoint[1])),Math.trunc(Math.min(t.shape[2]||0,e.endPoint[0])-Math.max(0,e.startPoint[0])),Math.trunc(Math.min(t.shape[1]||0,e.endPoint[1])-Math.max(0,e.startPoint[1]))]:[0,0,0,0],U2=(e,t)=>e?[e.startPoint[0]/(t.shape[2]||0),e.startPoint[1]/(t.shape[1]||0),(e.endPoint[0]-e.startPoint[0])/(t.shape[2]||0),(e.endPoint[1]-e.startPoint[1])/(t.shape[1]||0)]:[0,0,0,0],Yt=(e,t)=>{let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]];return{startPoint:o,endPoint:n,landmarks:e.landmarks,confidence:e.confidence}},J5=(e,t,o)=>{let n=t.shape[1],r=t.shape[2],A=[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r],s=ie.image.cropAndResize(t,[A],[0],o),a=ie.div(s,V.tf255);return ie.dispose(s),a},Y2=(e,t)=>{let o=X2(e),n=Je(e),r=[t*n[0]/2,t*n[1]/2];return{startPoint:[o[0]-r[0],o[1]-r[1]],endPoint:[o[0]+r[0],o[1]+r[1]],landmarks:e.landmarks,confidence:e.confidence}},K2=e=>{let t=X2(e),o=Je(e),n=Math.max(...o)/2;return{startPoint:[Math.round(t[0]-n),Math.round(t[1]-n)],endPoint:[Math.round(t[0]+n),Math.round(t[1]+n)],landmarks:e.landmarks,confidence:e.confidence}},Kt=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return{startPoint:[Math.min(...t),Math.min(...o)],endPoint:[Math.max(...t),Math.max(...o)],landmarks:e}},Q5=[[1,0,0],[0,1,0],[0,0,1]],Er=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),zr=(e,t)=>Er(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var qt=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],Ne=(e,t)=>{let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o},Sr=(e,t)=>{let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o},Ut=(e,t)=>{let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let A=0;A<n;A++)o[r].push(Ne(e[r],Sr(t,A)))}return o},Jt=(e,t)=>{let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],A=qt(t[0],t[1]),s=Ut(A,r),a=qt(-t[0],-t[1]);return Ut(s,a)},Cr=e=>{let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-Ne(t[0],o),-Ne(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]},Ir=(e,t)=>[Ne(e,t[0]),Ne(e,t[1])];function Qt(e){let t=e===192?{strides:[4],anchors:[1]}:{strides:[e/16,e/8],anchors:[2,6]},o=[];for(let n=0;n<t.strides.length;n++){let r=t.strides[n],A=Math.floor((e+r-1)/r),s=Math.floor((e+r-1)/r),a=t.anchors[n];for(let i=0;i<A;i++){let x=r*(i+.5);for(let c=0;c<s;c++){let l=r*(c+.5);for(let y=0;y<a;y++)o.push([l,x])}}}return o}function _t(e,t,o,n,r){let A=Je(t),s=e.map(f=>[A[0]/r*(f[0]-r/2),A[1]/r*(f[1]-r/2),f[2]||0]),a=o&&o!==0&&Math.abs(o)>.2,i=a?Jt(o,[0,0]):Q5,x=a?s.map(f=>[...Ir(f,i),f[2]]):s,c=a?Cr(n):Q5,l=X2(t),y=[Ne(l,c[0]),Ne(l,c[1])];return x.map(f=>[Math.trunc(f[0]+y[0]),Math.trunc(f[1]+y[1]),Math.trunc(f[2]||0)])}function $t(e,t,o,n){let r=t.landmarks.length>=U5.count?U5.symmetryLine:je.symmetryLine,A=0,s=Q5,a;if(e&&v.kernels.includes("rotatewithoffset"))if(A=zr(t.landmarks[r[0]],t.landmarks[r[1]]),A&&A!==0&&Math.abs(A)>.2){let x=X2(t),c=[x[0]/o.shape[2],x[1]/o.shape[1]],l=ie.image.rotateWithOffset(o,A,0,c);s=Jt(-A,x),a=J5(t,l,[n,n]),ie.dispose(l)}else a=J5(t,o,[n,n]);else a=J5(t,o,[n,n]);return[A,s,a]}var jr=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return[Math.min(...t)+(Math.max(...t)-Math.min(...t))/2,Math.min(...o)+(Math.max(...o)-Math.min(...o))/2]},e3=(e,t)=>{let o=jr(e),n=Je(t);return{startPoint:[o[0]-n[0]/2,o[1]-n[1]/2],endPoint:[o[0]+n[0]/2,o[1]+n[1]/2]}};var t3=6,Or=1.4,te,o3=null,Me=0,v2=null,Qe=()=>Me;async function n3(e){var t;return v.initial&&(te=null),te?e.debug&&p("cached model:",te.modelUrl):te=await G((t=e.face.detector)==null?void 0:t.modelPath),Me=te.inputs[0].shape?te.inputs[0].shape[2]:0,v2=N.scalar(Me,"int32"),o3=N.tensor2d(Qt(Me)),te}function Nr(e){let t={};t.boxStarts=N.slice(e,[0,1],[-1,2]),t.centers=N.add(t.boxStarts,o3),t.boxSizes=N.slice(e,[0,3],[-1,2]),t.boxSizesNormalized=N.div(t.boxSizes,v2),t.centersNormalized=N.div(t.centers,v2),t.halfBoxSize=N.div(t.boxSizesNormalized,V.tf2),t.starts=N.sub(t.centersNormalized,t.halfBoxSize),t.ends=N.add(t.centersNormalized,t.halfBoxSize),t.startNormalized=N.mul(t.starts,v2),t.endNormalized=N.mul(t.ends,v2);let o=N.concat2d([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(n=>N.dispose(t[n])),o}async function r3(e,t){var a,i,x,c;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let o={};o.resized=N.image.resizeBilinear(e,[Me,Me]),o.div=N.div(o.resized,V.tf127),o.normalized=N.sub(o.div,V.tf05);let n=te==null?void 0:te.execute(o.normalized);if(Array.isArray(n)&&n.length>2){let l=n.sort((y,f)=>y.size-f.size);o.concat384=N.concat([l[0],l[2]],2),o.concat512=N.concat([l[1],l[3]],2),o.concat=N.concat([o.concat512,o.concat384],1),o.batch=N.squeeze(o.concat,0)}else Array.isArray(n)?o.batch=N.squeeze(n[0]):o.batch=N.squeeze(n);N.dispose(n),o.boxes=Nr(o.batch),o.logits=N.slice(o.batch,[0,0],[-1,1]),o.sigmoid=N.sigmoid(o.logits),o.scores=N.squeeze(o.sigmoid),o.nms=await N.image.nonMaxSuppressionAsync(o.boxes,o.scores,((a=t.face.detector)==null?void 0:a.maxDetected)||0,((i=t.face.detector)==null?void 0:i.iouThreshold)||0,((x=t.face.detector)==null?void 0:x.minConfidence)||0);let r=await o.nms.array(),A=[],s=await o.scores.data();for(let l=0;l<r.length;l++){let y=s[r[l]];if(y>(((c=t.face.detector)==null?void 0:c.minConfidence)||0)){let f={};f.bbox=N.slice(o.boxes,[r[l],0],[1,-1]),f.slice=N.slice(o.batch,[r[l],t3-1],[1,-1]),f.squeeze=N.squeeze(f.slice),f.landmarks=N.reshape(f.squeeze,[t3,-1]);let u=await f.bbox.data(),m={startPoint:[u[0],u[1]],endPoint:[u[2],u[3]],landmarks:await f.landmarks.array(),confidence:y},P=Yt(m,[(e.shape[2]||0)/Me,(e.shape[1]||0)/Me]),g=Y2(P,t.face.scale||Or),b=K2(g);A.push(b),Object.keys(f).forEach(d=>N.dispose(f[d]))}}return Object.keys(o).forEach(l=>N.dispose(o[l])),A}var j0=Z(D());var J2={};ue(J2,{connected:()=>e1,kpt:()=>$5});var $5=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPinky","rightPinky","leftIndex","rightIndex","leftThumb","rightThumb","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","bodyCenter","bodyTop","leftPalm","leftHand","rightPalm","rightHand"],e1={shoulders:["leftShoulder","rightShoulder"],hips:["rightHip","leftHip"],mouth:["leftMouth","rightMouth"],leftLegUpper:["leftHip","leftKnee"],leftLegLower:["leftKnee","leftAnkle"],leftFoot:["leftAnkle","leftHeel","leftFoot"],leftTorso:["leftShoulder","leftHip"],leftArmUpper:["leftShoulder","leftElbow"],leftArmLower:["leftElbow","leftWrist"],leftHand:["leftWrist","leftPalm"],leftHandPinky:["leftPalm","leftPinky"],leftHandIndex:["leftPalm","leftIndex"],leftHandThumb:["leftPalm","leftThumb"],leftEyeOutline:["leftEyeInside","leftEyeOutside"],rightLegUpper:["rightHip","rightKnee"],rightLegLower:["rightKnee","rightAnkle"],rightFoot:["rightAnkle","rightHeel","rightFoot"],rightTorso:["rightShoulder","rightHip"],rightArmUpper:["rightShoulder","rightElbow"],rightArmLower:["rightElbow","rightWrist"],rightHand:["rightWrist","rightPalm"],rightHandPinky:["rightPalm","rightPinky"],rightHandIndex:["rightPalm","rightIndex"],rightHandThumb:["rightPalm","rightThumb"],rightEyeOutline:["rightEyeInside","rightEyeOutside"]};var C0=Z(D()),s3=224,Lr,Wr=5,Q2=[8,16,32,32,32];async function a3(){let e=[],t=0;for(;t<Wr;){let o=0,n=t;for(;n<Q2.length&&Q2[n]===Q2[t];)o+=2,n++;let r=Q2[t],A=Math.ceil(s3/r),s=Math.ceil(s3/r);for(let a=0;a<A;++a)for(let i=0;i<s;++i)for(let x=0;x<o;++x)e.push({x:(i+.5)/s,y:(a+.5)/A});t=n}Lr={x:C0.tensor1d(e.map(o=>o.x)),y:C0.tensor1d(e.map(o=>o.y))}}function le(e,t=[1,1]){let o=[e.map(a=>a[0]),e.map(a=>a[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],A=[n[0],n[1],r[0]-n[0],r[1]-n[1]],s=[A[0]/t[0],A[1]/t[1],A[2]/t[0],A[3]/t[1]];return{box:A,boxRaw:s}}function i3(e,t=[1,1]){let o=[e.map(x=>x[0]),e.map(x=>x[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],A=[(n[0]+r[0])/2,(n[1]+r[1])/2],s=Math.max(A[0]-n[0],A[1]-n[1],-A[0]+r[0],-A[1]+r[1]),a=[Math.trunc(A[0]-s),Math.trunc(A[1]-s),Math.trunc(2*s),Math.trunc(2*s)],i=[a[0]/t[0],a[1]/t[1],a[2]/t[0],a[3]/t[1]];return{box:a,boxRaw:i}}function _2(e,t){let o=[e[2]*t,e[3]*t];return[e[0]-(o[0]-e[2])/2,e[1]-(o[1]-e[3])/2,o[0],o[1]]}var x3={initial:!0},I0={detector:null,landmarks:null},_e={detector:[224,224],landmarks:[256,256]},t1=Number.MAX_SAFE_INTEGER,Gr={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},e5=null,T2,Pe=[[0,0],[0,0],[0,0],[0,0]],l3=0,y3=e=>1-1/(1+Math.exp(e));async function c3(e){if(x3.initial&&(I0.detector=null),!I0.detector&&e.body.detector&&e.body.detector.modelPath){I0.detector=await G(e.body.detector.modelPath);let t=Object.values(I0.detector.modelSignature.inputs);_e.detector[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,_e.detector[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&I0.detector&&p("cached model:",I0.detector.modelUrl);return await a3(),I0.detector}async function d3(e){if(x3.initial&&(I0.landmarks=null),I0.landmarks)e.debug&&p("cached model:",I0.landmarks.modelUrl);else{I0.landmarks=await G(e.body.modelPath);let t=Object.values(I0.landmarks.modelSignature.inputs);_e.landmarks[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,_e.landmarks[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return I0.landmarks}async function Br(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;let n;if(T2&&(o.cropped=j0.image.cropAndResize(e,[T2],[0],[e.shape[1],e.shape[2]])),e.shape[1]!==e.shape[2]){let r=[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],A=[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0];Pe=[[0,0],r,A,[0,0]],o.pad=j0.pad(o.cropped||e,Pe),o.resize=j0.image.resizeBilinear(o.pad,[t,t]),n=j0.div(o.resize,V.tf255)}else e.shape[1]!==t?(o.resize=j0.image.resizeBilinear(o.cropped||e,[t,t]),n=j0.div(o.resize,V.tf255)):n=j0.div(o.cropped||e,V.tf255);return Object.keys(o).forEach(r=>j0.dispose(o[r])),n}function Hr(e,t){for(let o of e)o.position=[Math.trunc(o.position[0]*(t[0]+Pe[2][0]+Pe[2][1])/t[0]-Pe[2][0]),Math.trunc(o.position[1]*(t[1]+Pe[1][0]+Pe[1][1])/t[1]-Pe[1][0]),o.position[2]],o.positionRaw=[o.position[0]/t[0],o.position[1]/t[1],2*o.position[2]/(t[0]+t[1])];if(T2)for(let o of e)o.positionRaw=[o.positionRaw[0]+T2[1],o.positionRaw[1]+T2[0],o.positionRaw[2]],o.position=[Math.trunc(o.positionRaw[0]*t[0]),Math.trunc(o.positionRaw[1]*t[1]),o.positionRaw[2]];return e}async function Vr(e){let t=e.find(a=>a.part==="leftPalm"),o=e.find(a=>a.part==="leftWrist"),n=e.find(a=>a.part==="leftIndex");t.position[2]=((o.position[2]||0)+(n.position[2]||0))/2;let r=e.find(a=>a.part==="rightPalm"),A=e.find(a=>a.part==="rightWrist"),s=e.find(a=>a.part==="rightIndex");r.position[2]=((A.position[2]||0)+(s.position[2]||0))/2}async function Dr(e,t,o){var u;let n={};[n.ld,n.segmentation,n.heatmap,n.world,n.poseflag]=(u=I0.landmarks)==null?void 0:u.execute(e,Gr.landmarks);let r=(await n.poseflag.data())[0],A=await n.ld.data(),s=await n.world.data();Object.keys(n).forEach(m=>j0.dispose(n[m]));let a=[],i=5;for(let m=0;m<A.length/i;m++){let P=y3(A[i*m+3]),g=y3(A[i*m+4]),b=Math.trunc(100*P*g*r)/100,d=[A[i*m+0]/_e.landmarks[0],A[i*m+1]/_e.landmarks[1],A[i*m+2]+0],M=[Math.trunc(o[0]*d[0]),Math.trunc(o[1]*d[1]),d[2]],S=[s[i*m+0],s[i*m+1],s[i*m+2]+0];a.push({part:$5[m],positionRaw:d,position:M,distance:S,score:b})}if(r<(t.body.minConfidence||0))return null;Vr(a);let x=Hr(a,o),c=x.map(m=>m.position),l=le(c,[o[0],o[1]]),y={};for(let[m,P]of Object.entries(e1)){let g=[];for(let b=0;b<P.length-1;b++){let d=x.find(S=>S.part===P[b]),M=x.find(S=>S.part===P[b+1]);d&&M&&g.push([d.position,M.position])}y[m]=g}return{id:0,score:Math.trunc(100*r)/100,box:l.box,boxRaw:l.boxRaw,keypoints:x,annotations:y}}async function o1(e,t){let o=[e.shape[2]||0,e.shape[1]||0],n=(t.body.skipTime||0)>h()-l3,r=t1<(t.body.skipFrames||0);if(t.skipAllowed&&n&&r&&e5!==null)t1++;else{let A={};A.landmarks=await Br(e,256),e5=await Dr(A.landmarks,t,o),Object.keys(A).forEach(s=>j0.dispose(A[s])),l3=h(),t1=0}return e5?[e5]:[]}var T0=Z(D());var $e=[{class:1,label:"person"},{class:2,label:"bicycle"},{class:3,label:"car"},{class:4,label:"motorcycle"},{class:5,label:"airplane"},{class:6,label:"bus"},{class:7,label:"train"},{class:8,label:"truck"},{class:9,label:"boat"},{class:10,label:"traffic light"},{class:11,label:"fire hydrant"},{class:12,label:"stop sign"},{class:13,label:"parking meter"},{class:14,label:"bench"},{class:15,label:"bird"},{class:16,label:"cat"},{class:17,label:"dog"},{class:18,label:"horse"},{class:19,label:"sheep"},{class:20,label:"cow"},{class:21,label:"elephant"},{class:22,label:"bear"},{class:23,label:"zebra"},{class:24,label:"giraffe"},{class:25,label:"backpack"},{class:26,label:"umbrella"},{class:27,label:"handbag"},{class:28,label:"tie"},{class:29,label:"suitcase"},{class:30,label:"frisbee"},{class:31,label:"skis"},{class:32,label:"snowboard"},{class:33,label:"sports ball"},{class:34,label:"kite"},{class:35,label:"baseball bat"},{class:36,label:"baseball glove"},{class:37,label:"skateboard"},{class:38,label:"surfboard"},{class:39,label:"tennis racket"},{class:40,label:"bottle"},{class:41,label:"wine glass"},{class:42,label:"cup"},{class:43,label:"fork"},{class:44,label:"knife"},{class:45,label:"spoon"},{class:46,label:"bowl"},{class:47,label:"banana"},{class:48,label:"apple"},{class:49,label:"sandwich"},{class:50,label:"orange"},{class:51,label:"broccoli"},{class:52,label:"carrot"},{class:53,label:"hot dog"},{class:54,label:"pizza"},{class:55,label:"donut"},{class:56,label:"cake"},{class:57,label:"chair"},{class:58,label:"couch"},{class:59,label:"potted plant"},{class:60,label:"bed"},{class:61,label:"dining table"},{class:62,label:"toilet"},{class:63,label:"tv"},{class:64,label:"laptop"},{class:65,label:"mouse"},{class:66,label:"remote"},{class:67,label:"keyboard"},{class:68,label:"cell phone"},{class:69,label:"microwave"},{class:70,label:"oven"},{class:71,label:"toaster"},{class:72,label:"sink"},{class:73,label:"refrigerator"},{class:74,label:"book"},{class:75,label:"clock"},{class:76,label:"vase"},{class:77,label:"scissors"},{class:78,label:"teddy bear"},{class:79,label:"hair drier"},{class:80,label:"toothbrush"}];var ye,Le=0,n1=[],m3=0,r1=Number.MAX_SAFE_INTEGER;async function p3(e){if(v.initial&&(ye=null),ye)e.debug&&p("cached model:",ye.modelUrl);else{ye=await G(e.object.modelPath);let t=Object.values(ye.modelSignature.inputs);Le=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return ye}async function Zr(e,t,o){if(!e)return[];let n={},r=[],A=await e.array();n.squeeze=T0.squeeze(e);let s=T0.split(n.squeeze,6,1);n.stack=T0.stack([s[1],s[0],s[3],s[2]],1),n.boxes=T0.squeeze(n.stack),n.scores=T0.squeeze(s[4]),n.classes=T0.squeeze(s[5]),T0.dispose([e,...s]),n.nms=await T0.image.nonMaxSuppressionAsync(n.boxes,n.scores,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence||0);let a=await n.nms.data(),i=0;for(let x of Array.from(a)){let c=Math.trunc(100*A[0][x][4])/100,l=A[0][x][5],y=$e[l].label,[f,u]=[A[0][x][0]/Le,A[0][x][1]/Le],m=[f,u,A[0][x][2]/Le-f,A[0][x][3]/Le-u],P=[Math.trunc(m[0]*t[0]),Math.trunc(m[1]*t[1]),Math.trunc(m[2]*t[0]),Math.trunc(m[3]*t[1])];r.push({id:i++,score:c,class:l,label:y,box:P,boxRaw:m})}return Object.keys(n).forEach(x=>T0.dispose(n[x])),r}async function A1(e,t){let o=(t.object.skipTime||0)>h()-m3,n=r1<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&n1.length>0?(r1++,n1):(r1=0,new Promise(async r=>{let A=[e.shape[2]||0,e.shape[1]||0],s=T0.image.resizeBilinear(e,[Le,Le]),a=t.object.enabled?ye==null?void 0:ye.execute(s,["tower_0/detections"]):null;m3=h(),T0.dispose(s);let i=await Zr(a,A,t);n1=i,r(i)}))}var _=Z(D());var t5={};ue(t5,{connected:()=>a1,kpt:()=>s1});var s1=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],a1={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var b0,h3=0,w0={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},i1=Number.MAX_SAFE_INTEGER;async function b3(e){return v.initial&&(b0=null),b0?e.debug&&p("cached model:",b0.modelUrl):b0=await G(e.body.modelPath),b0}async function Xr(e,t){let[o,n]=e.shape,r=_.reshape(e,[n*o]),A=_.max(r,0),s=(await A.data())[0];if(_.dispose([r,A]),s>t){let a=_.argMax(r,0),i=_.mod(a,o),x=(await i.data())[0],c=_.div(a,_.scalar(o,"int32")),l=(await c.data())[0];return _.dispose([i,c]),[x,l,s]}return[0,0,s]}async function l1(e,t){let o=(t.body.skipTime||0)>h()-h3,n=i1<(t.body.skipFrames||0);return t.skipAllowed&&o&&n&&Object.keys(w0.keypoints).length>0?(i1++,[w0]):(i1=0,new Promise(async r=>{var l;let A=_.tidy(()=>{if(!(b0!=null&&b0.inputs[0].shape))return null;let y=_.image.resizeBilinear(e,[b0.inputs[0].shape[2],b0.inputs[0].shape[1]],!1),f=_.mul(y,V.tf2);return _.sub(f,V.tf1)}),s;if(t.body.enabled&&(s=b0==null?void 0:b0.execute(A)),h3=h(),_.dispose(A),s){w0.keypoints.length=0;let y=s.squeeze();_.dispose(s);let f=y.unstack(2);_.dispose(y);for(let u=0;u<f.length;u++){let[m,P,g]=await Xr(f[u],t.body.minConfidence);g>(((l=t.body)==null?void 0:l.minConfidence)||0)&&w0.keypoints.push({score:Math.round(100*g)/100,part:s1[u],positionRaw:[m/b0.inputs[0].shape[2],P/b0.inputs[0].shape[1]],position:[Math.round(e.shape[2]*m/b0.inputs[0].shape[2]),Math.round(e.shape[1]*P/b0.inputs[0].shape[1])]})}f.forEach(u=>_.dispose(u))}w0.score=w0.keypoints.reduce((y,f)=>f.score>y?f.score:y,0);let a=w0.keypoints.map(y=>y.position[0]),i=w0.keypoints.map(y=>y.position[1]);w0.box=[Math.min(...a),Math.min(...i),Math.max(...a)-Math.min(...a),Math.max(...i)-Math.min(...i)];let x=w0.keypoints.map(y=>y.positionRaw[0]),c=w0.keypoints.map(y=>y.positionRaw[1]);w0.boxRaw=[Math.min(...x),Math.min(...c),Math.max(...x)-Math.min(...x),Math.max(...c)-Math.min(...c)];for(let[y,f]of Object.entries(a1)){let u=[];for(let m=0;m<f.length-1;m++){let P=w0.keypoints.find(b=>b.part===f[m]),g=w0.keypoints.find(b=>b.part===f[m+1]);P&&g&&P.score>(t.body.minConfidence||0)&&g.score>(t.body.minConfidence||0)&&u.push([P.position,g.position])}w0.annotations[y]=u}r([w0])}))}var U0=Z(D());var qr=["angry","disgust","fear","happy","sad","surprise","neutral"],H0,o5=[],M3=0,P3=0,y1=Number.MAX_SAFE_INTEGER;async function R3(e){var t;return v.initial&&(H0=null),H0?e.debug&&p("cached model:",H0.modelUrl):H0=await G((t=e.face.emotion)==null?void 0:t.modelPath),H0}async function x1(e,t,o,n){var s,a;if(!H0)return[];let r=y1<(((s=t.face.emotion)==null?void 0:s.skipFrames)||0),A=(((a=t.face.emotion)==null?void 0:a.skipTime)||0)>h()-P3;return t.skipAllowed&&A&&r&&M3===n&&o5[o]&&o5[o].length>0?(y1++,o5[o]):(y1=0,new Promise(async i=>{var c,l;let x=[];if((c=t.face.emotion)!=null&&c.enabled){let y={},f=H0!=null&&H0.inputs[0].shape?H0.inputs[0].shape[2]:0;y.resize=U0.image.resizeBilinear(e,[f,f],!1),y.channels=U0.mul(y.resize,V.rgb),y.grayscale=U0.sum(y.channels,3,!0),y.grayscaleSub=U0.sub(y.grayscale,V.tf05),y.grayscaleMul=U0.mul(y.grayscaleSub,V.tf2),y.emotion=H0==null?void 0:H0.execute(y.grayscaleMul),P3=h();let u=await y.emotion.data();for(let m=0;m<u.length;m++)u[m]>(((l=t.face.emotion)==null?void 0:l.minConfidence)||0)&&x.push({score:Math.min(.99,Math.trunc(100*u[m])/100),emotion:qr[m]});x.sort((m,P)=>P.score-m.score),Object.keys(y).forEach(m=>U0.dispose(y[m]))}o5[o]=x,M3=n,i(x)}))}var E3=Z(D());var O0,c1=[],T3=0,w3=0,k3=Number.MAX_SAFE_INTEGER;async function z3(e){return v.initial&&(O0=null),O0?e.debug&&p("cached model:",O0.modelUrl):O0=await G(e.face.mobilefacenet.modelPath),O0}async function d1(e,t,o,n){var s,a;if(!O0)return[];let r=k3<(((s=t.face.embedding)==null?void 0:s.skipFrames)||0),A=(((a=t.face.embedding)==null?void 0:a.skipTime)||0)>h()-w3;return t.skipAllowed&&A&&r&&T3===n&&c1[o]?(k3++,c1[o]):new Promise(async i=>{var c;let x=[];if(((c=t.face.embedding)==null?void 0:c.enabled)&&(O0==null?void 0:O0.inputs[0].shape)){let l={};l.crop=E3.image.resizeBilinear(e,[O0.inputs[0].shape[2],O0.inputs[0].shape[1]],!1),l.data=O0==null?void 0:O0.execute(l.crop);let y=await l.data.data();x=Array.from(y)}c1[o]=x,T3=n,w3=h(),i(x)})}var Be=Z(D());var Y0=Z(D());var xe,Re=0,Ur=2.3,f1=X0.leftEyeLower0,m1=X0.rightEyeLower0,e2={leftBounds:[f1[0],f1[f1.length-1]],rightBounds:[m1[0],m1[m1.length-1]]},t2={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function O3(e){var t;return v.initial&&(xe=null),xe?e.debug&&p("cached model:",xe.modelUrl):xe=await G((t=e.face.iris)==null?void 0:t.modelPath),Re=xe.inputs[0].shape?xe.inputs[0].shape[2]:0,Re===-1&&(Re=64),xe}function n5(e,t,o,n){for(let r=0;r<Y5.length;r++){let{key:A,indices:s}=Y5[r],a=X0[`${o}${A}`];if(!n||n.includes(A))for(let i=0;i<s.length;i++){let x=s[i];e[a[i]]=[t[x][0],t[x][1],(t[x][2]+e[a[i]][2])/2]}}}var Yr=e=>{let t=e[e2.leftBounds[0]][2],o=e[e2.rightBounds[0]][2];return t-o},C3=(e,t,o,n,r,A=!1)=>{let s=K2(Y2(Kt([e[o],e[n]]),Ur)),a=Je(s),i=Y0.image.cropAndResize(t,[[s.startPoint[1]/r,s.startPoint[0]/r,s.endPoint[1]/r,s.endPoint[0]/r]],[0],[Re,Re]);if(A&&v.kernels.includes("flipleftright")){let x=Y0.image.flipLeftRight(i);Y0.dispose(i),i=x}return{box:s,boxSize:a,crop:i}},I3=(e,t,o,n=!1)=>{let r=[];for(let A=0;A<t2.numCoordinates;A++){let s=e[A*3],a=e[A*3+1],i=e[A*3+2];r.push([(n?1-s/Re:s/Re)*o[0]+t.startPoint[0],a/Re*o[1]+t.startPoint[1],i])}return{rawCoords:r,iris:r.slice(t2.index)}},j3=(e,t,o)=>{let n=e[X0[`${o}EyeUpper0`][t2.upperCenter]][2],r=e[X0[`${o}EyeLower0`][t2.lowerCenter]][2],A=(n+r)/2;return t.map((s,a)=>{let i=A;return a===2?i=n:a===4&&(i=r),[s[0],s[1],i]})};async function N3(e,t,o,n){if(!xe)return o.debug&&p("face mesh iris detection requested, but model is not loaded"),e;let{box:r,boxSize:A,crop:s}=C3(e,t,e2.leftBounds[0],e2.leftBounds[1],n,!0),{box:a,boxSize:i,crop:x}=C3(e,t,e2.rightBounds[0],e2.rightBounds[1],n,!0),c=Y0.concat([s,x]);Y0.dispose(s),Y0.dispose(x);let l=xe.execute(c);Y0.dispose(c);let y=await l.data();Y0.dispose(l);let f=y.slice(0,t2.numCoordinates*3),{rawCoords:u,iris:m}=I3(f,r,A,!0),P=y.slice(t2.numCoordinates*3),{rawCoords:g,iris:b}=I3(P,a,i,!1),d=Yr(e);Math.abs(d)<30?(n5(e,u,"left",null),n5(e,g,"right",null)):d<1?n5(e,u,"left",["EyeUpper0","EyeLower0"]):n5(e,g,"right",["EyeUpper0","EyeLower0"]);let M=j3(e,m,"left"),S=j3(e,b,"right");return e.concat(M).concat(S)}var Kr=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Jr=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Qr=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],_r=[[474,475],[475,476],[476,477],[477,474]],$r=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],eA=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],tA=[[469,470],[470,471],[471,472],[472,469]],oA=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]];function ve(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var nA={lips:ve(Kr),leftEye:ve(Jr),leftEyebrow:ve(Qr),leftIris:ve(_r),rightEye:ve($r),rightEyebrow:ve(eA),rightIris:ve(tA),faceOval:ve(oA)},rA=Object.entries(nA).map(([e,t])=>t.map(o=>[o,e])).flat(),f4=new Map(rA),w2=[61,146,91,181,84,17,314,405,321,375,291,185,40,39,37,0,267,269,270,409,78,95,88,178,87,14,317,402,318,324,308,191,80,81,82,13,312,311,310,415,76,77,90,180,85,16,315,404,320,307,306,184,74,73,72,11,302,303,304,408,62,96,89,179,86,15,316,403,319,325,292,183,42,41,38,12,268,271,272,407],We=[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173,130,25,110,24,23,22,26,112,243,247,30,29,27,28,56,190,226,31,228,229,230,231,232,233,244,113,225,224,223,222,221,189,35,124,46,53,52,65,143,111,117,118,119,120,121,128,245,156,70,63,105,66,107,55,193],Fe=[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398,359,255,339,254,253,252,256,341,463,467,260,259,257,258,286,414,446,261,448,449,450,451,452,453,464,342,445,444,443,442,441,413,265,353,276,283,282,295,372,340,346,347,348,349,350,357,465,383,300,293,334,296,336,285,417];async function F3(e,t){let o={lips:await t.filter(A=>A.size===160)[0].data(),irisL:await t.filter(A=>A.size===10)[0].data(),eyeL:await t.filter(A=>A.size===142)[0].data(),irisR:await t.filter(A=>A.size===10)[1].data(),eyeR:await t.filter(A=>A.size===142)[1].data()},n=We.reduce((A,s)=>A+=e[s][2],0)/We.length;for(let A=0;A<o.irisL.length/2;A++)e.push([o.irisL[2*A+0],o.irisL[2*A+1],n]);let r=Fe.reduce((A,s)=>A+=e[s][2],0)/Fe.length;for(let A=0;A<o.irisR.length/2;A++)e.push([o.irisR[2*A+0],o.irisR[2*A+1],r]);for(let A=0;A<o.eyeL.length/2;A++)e[We[A]]=[o.eyeL[2*A+0],o.eyeL[2*A+1],e[We[A]][2]];for(let A=0;A<o.eyeR.length/2;A++)e[Fe[A]]=[o.eyeR[2*A+0],o.eyeR[2*A+1],e[Fe[A]][2]];for(let A=0;A<o.lips.length/2;A++)e[w2[A]]=[o.lips[2*A+0],o.lips[2*A+1],e[w2[A]][2]];return e}var oe={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},g0=null,Ge=0;async function G3(e,t){var a,i,x,c,l,y,f,u,m,P,g;let o=(((a=t.face.detector)==null?void 0:a.skipTime)||0)>h()-oe.timestamp,n=oe.skipped<(((i=t.face.detector)==null?void 0:i.skipFrames)||0);!t.skipAllowed||!o||!n||oe.boxes.length===0?(oe.boxes=await r3(e,t),oe.timestamp=h(),oe.skipped=0):oe.skipped++;let r=[],A=[],s=0;for(let b=0;b<oe.boxes.length;b++){let d=oe.boxes[b],M=0,S,w={id:s++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,annotations:{}};if([M,S,w.tensor]=$t((x=t.face.detector)==null?void 0:x.rotation,d,e,(c=t.face.mesh)!=null&&c.enabled?Ge:Qe()),(l=t==null?void 0:t.filter)!=null&&l.equalization){let j=await L2(w.tensor);Be.dispose(w.tensor),w.tensor=j}if(w.boxScore=Math.round(100*d.confidence)/100,(y=t.face.mesh)!=null&&y.enabled)if(!g0)t.debug&&p("face mesh detection requested, but model is not loaded");else{let j=g0.execute(w.tensor),F=await j.find(H=>H.shape[H.shape.length-1]===1).data();if(w.faceScore=Math.round(100*F[0])/100,w.faceScore<(((f=t.face.detector)==null?void 0:f.minConfidence)||1)){if(d.confidence=w.faceScore,(u=t.face.mesh)!=null&&u.keepInvalid){w.box=q2(d,e),w.boxRaw=U2(d,e),w.score=w.boxScore,w.mesh=d.landmarks.map(H=>[(d.startPoint[0]+d.endPoint[0])/2+(d.endPoint[0]+d.startPoint[0])*H[0]/Qe(),(d.startPoint[1]+d.endPoint[1])/2+(d.endPoint[1]+d.startPoint[1])*H[1]/Qe()]),w.meshRaw=w.mesh.map(H=>[H[0]/(e.shape[2]||1),H[1]/(e.shape[1]||1),(H[2]||0)/Ge]);for(let H of Object.keys(je))w.annotations[H]=[w.mesh[je[H]]]}}else{let H=j.find(E=>E.shape[E.shape.length-1]===1404),Y=Be.reshape(H,[-1,3]),J=await Y.array();Be.dispose(Y),(m=t.face.attention)!=null&&m.enabled?J=await F3(J,j):(P=t.face.iris)!=null&&P.enabled&&(J=await N3(J,w.tensor,t,Ge)),w.mesh=_t(J,d,M,S,Ge),w.meshRaw=w.mesh.map(E=>[E[0]/(e.shape[2]||0),E[1]/(e.shape[1]||0),(E[2]||0)/Ge]);for(let E of Object.keys(X0))w.annotations[E]=X0[E].map(G0=>w.mesh[G0]);w.score=w.faceScore;let x0={...e3(w.mesh,d),confidence:d.confidence,landmarks:d.landmarks};w.box=q2(x0,e),w.boxRaw=U2(x0,e),A.push(x0)}Be.dispose(j)}else{w.box=q2(d,e),w.boxRaw=U2(d,e),w.score=w.boxScore,w.mesh=d.landmarks.map(j=>[(d.startPoint[0]+d.endPoint[0])/2+(d.endPoint[0]+d.startPoint[0])*j[0]/Qe(),(d.startPoint[1]+d.endPoint[1])/2+(d.endPoint[1]+d.startPoint[1])*j[1]/Qe()]),w.meshRaw=w.mesh.map(j=>[j[0]/(e.shape[2]||0),j[1]/(e.shape[1]||0),(j[2]||0)/Ge]);for(let j of Object.keys(je))w.annotations[j]=[w.mesh[je[j]]]}w.score>(((g=t.face.detector)==null?void 0:g.minConfidence)||1)?r.push(w):Be.dispose(w.tensor)}return oe.boxes=A,r}async function B3(e){var t,o,n,r,A,s;return v.initial&&(g0=null),((o=(t=e==null?void 0:e.face)==null?void 0:t.attention)==null?void 0:o.enabled)&&(g0==null?void 0:g0.signature)&&Object.keys(((n=g0==null?void 0:g0.signature)==null?void 0:n.outputs)||{}).length<6&&(g0=null),g0?e.debug&&p("cached model:",g0.modelUrl):(r=e.face.attention)!=null&&r.enabled?g0=await G((A=e.face.attention)==null?void 0:A.modelPath):g0=await G((s=e.face.mesh)==null?void 0:s.modelPath),Ge=g0.inputs[0].shape?g0.inputs[0].shape[2]:0,g0}var H3=Oe,V3=R2;var K0=Z(D());var N0,r5=[],D3=0,Z3=0,u1=Number.MAX_SAFE_INTEGER;async function X3(e){var t;return v.initial&&(N0=null),N0?e.debug&&p("cached model:",N0.modelUrl):N0=await G((t=e.face.description)==null?void 0:t.modelPath),N0}function h1(e){let t=e.image||e.tensor||e;if(!(N0!=null&&N0.inputs[0].shape))return t;let o=K0.image.resizeBilinear(t,[N0.inputs[0].shape[2],N0.inputs[0].shape[1]],!1),n=K0.mul(o,V.tf255);return K0.dispose(o),n}async function b1(e,t,o,n){var s,a,i,x;if(!N0)return{age:0,gender:"unknown",genderScore:0,descriptor:[]};let r=u1<(((s=t.face.description)==null?void 0:s.skipFrames)||0),A=(((a=t.face.description)==null?void 0:a.skipTime)||0)>h()-D3;return t.skipAllowed&&r&&A&&Z3===n&&((i=r5[o])==null?void 0:i.age)&&((x=r5[o])==null?void 0:x.age)>0?(u1++,r5[o]):(u1=0,new Promise(async c=>{var y,f;let l={age:0,gender:"unknown",genderScore:0,descriptor:[]};if((y=t.face.description)!=null&&y.enabled){let u=h1(e),m=N0==null?void 0:N0.execute(u);D3=h(),K0.dispose(u);let g=await(await m.find(F=>F.shape[1]===1)).data(),b=Math.trunc(200*Math.abs(g[0]-.5))/100;b>(((f=t.face.description)==null?void 0:f.minConfidence)||0)&&(l.gender=g[0]<=.5?"female":"male",l.genderScore=Math.min(.99,b));let d=K0.argMax(m.find(F=>F.shape[1]===100),1),M=(await d.data())[0];K0.dispose(d);let w=await m.find(F=>F.shape[1]===100).data();l.age=Math.round(w[M-1]>w[M+1]?10*M-100*w[M-1]:10*M+100*w[M+1])/10;let j=m.find(F=>F.shape[1]===1024),C=j?await j.data():[];l.descriptor=Array.from(C),m.forEach(F=>K0.dispose(F))}r5[o]=l,Z3=n,c(l)}))}var W=Z(D());var Y3=Z(D());function A5(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function k2(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function K3(e,t,o){let n=t.shape[1],r=t.shape[2],A=[[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r]];return Y3.image.cropAndResize(t,A,[0],o)}function J3(e,t){let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],r=e.palmLandmarks.map(A=>[A[0]*t[0],A[1]*t[1]]);return{startPoint:o,endPoint:n,palmLandmarks:r,confidence:e.confidence}}function s5(e,t=1.5){let o=k2(e),n=A5(e),r=[t*n[0]/2,t*n[1]/2],A=[o[0]-r[0],o[1]-r[1]],s=[o[0]+r[0],o[1]+r[1]];return{startPoint:A,endPoint:s,palmLandmarks:e.palmLandmarks}}function a5(e){let t=k2(e),o=A5(e),r=Math.max(...o)/2,A=[t[0]-r,t[1]-r],s=[t[0]+r,t[1]+r];return{startPoint:A,endPoint:s,palmLandmarks:e.palmLandmarks}}function sA(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function Q3(e,t){let o=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return sA(o)}var q3=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function Te(e,t){let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o}function aA(e,t){let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o}function U3(e,t){let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let A=0;A<n;A++)o[r].push(Te(e[r],aA(t,A)))}return o}function M1(e,t){let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],A=q3(t[0],t[1]),s=U3(A,r),a=q3(-t[0],-t[1]);return U3(s,a)}function _3(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-Te(t[0],o),-Te(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]}function P1(e,t){return[Te(e,t[0]),Te(e,t[1])]}var eo=[{x:.015625,y:.015625},{x:.015625,y:.015625},{x:.046875,y:.015625},{x:.046875,y:.015625},{x:.078125,y:.015625},{x:.078125,y:.015625},{x:.109375,y:.015625},{x:.109375,y:.015625},{x:.140625,y:.015625},{x:.140625,y:.015625},{x:.171875,y:.015625},{x:.171875,y:.015625},{x:.203125,y:.015625},{x:.203125,y:.015625},{x:.234375,y:.015625},{x:.234375,y:.015625},{x:.265625,y:.015625},{x:.265625,y:.015625},{x:.296875,y:.015625},{x:.296875,y:.015625},{x:.328125,y:.015625},{x:.328125,y:.015625},{x:.359375,y:.015625},{x:.359375,y:.015625},{x:.390625,y:.015625},{x:.390625,y:.015625},{x:.421875,y:.015625},{x:.421875,y:.015625},{x:.453125,y:.015625},{x:.453125,y:.015625},{x:.484375,y:.015625},{x:.484375,y:.015625},{x:.515625,y:.015625},{x:.515625,y:.015625},{x:.546875,y:.015625},{x:.546875,y:.015625},{x:.578125,y:.015625},{x:.578125,y:.015625},{x:.609375,y:.015625},{x:.609375,y:.015625},{x:.640625,y:.015625},{x:.640625,y:.015625},{x:.671875,y:.015625},{x:.671875,y:.015625},{x:.703125,y:.015625},{x:.703125,y:.015625},{x:.734375,y:.015625},{x:.734375,y:.015625},{x:.765625,y:.015625},{x:.765625,y:.015625},{x:.796875,y:.015625},{x:.796875,y:.015625},{x:.828125,y:.015625},{x:.828125,y:.015625},{x:.859375,y:.015625},{x:.859375,y:.015625},{x:.890625,y:.015625},{x:.890625,y:.015625},{x:.921875,y:.015625},{x:.921875,y:.015625},{x:.953125,y:.015625},{x:.953125,y:.015625},{x:.984375,y:.015625},{x:.984375,y:.015625},{x:.015625,y:.046875},{x:.015625,y:.046875},{x:.046875,y:.046875},{x:.046875,y:.046875},{x:.078125,y:.046875},{x:.078125,y:.046875},{x:.109375,y:.046875},{x:.109375,y:.046875},{x:.140625,y:.046875},{x:.140625,y:.046875},{x:.171875,y:.046875},{x:.171875,y:.046875},{x:.203125,y:.046875},{x:.203125,y:.046875},{x:.234375,y:.046875},{x:.234375,y:.046875},{x:.265625,y:.046875},{x:.265625,y:.046875},{x:.296875,y:.046875},{x:.296875,y:.046875},{x:.328125,y:.046875},{x:.328125,y:.046875},{x:.359375,y:.046875},{x:.359375,y:.046875},{x:.390625,y:.046875},{x:.390625,y:.046875},{x:.421875,y:.046875},{x:.421875,y:.046875},{x:.453125,y:.046875},{x:.453125,y:.046875},{x:.484375,y:.046875},{x:.484375,y:.046875},{x:.515625,y:.046875},{x:.515625,y:.046875},{x:.546875,y:.046875},{x:.546875,y:.046875},{x:.578125,y:.046875},{x:.578125,y:.046875},{x:.609375,y:.046875},{x:.609375,y:.046875},{x:.640625,y:.046875},{x:.640625,y:.046875},{x:.671875,y:.046875},{x:.671875,y:.046875},{x:.703125,y:.046875},{x:.703125,y:.046875},{x:.734375,y:.046875},{x:.734375,y:.046875},{x:.765625,y:.046875},{x:.765625,y:.046875},{x:.796875,y:.046875},{x:.796875,y:.046875},{x:.828125,y:.046875},{x:.828125,y:.046875},{x:.859375,y:.046875},{x:.859375,y:.046875},{x:.890625,y:.046875},{x:.890625,y:.046875},{x:.921875,y:.046875},{x:.921875,y:.046875},{x:.953125,y:.046875},{x:.953125,y:.046875},{x:.984375,y:.046875},{x:.984375,y:.046875},{x:.015625,y:.078125},{x:.015625,y:.078125},{x:.046875,y:.078125},{x:.046875,y:.078125},{x:.078125,y:.078125},{x:.078125,y:.078125},{x:.109375,y:.078125},{x:.109375,y:.078125},{x:.140625,y:.078125},{x:.140625,y:.078125},{x:.171875,y:.078125},{x:.171875,y:.078125},{x:.203125,y:.078125},{x:.203125,y:.078125},{x:.234375,y:.078125},{x:.234375,y:.078125},{x:.265625,y:.078125},{x:.265625,y:.078125},{x:.296875,y:.078125},{x:.296875,y:.078125},{x:.328125,y:.078125},{x:.328125,y:.078125},{x:.359375,y:.078125},{x:.359375,y:.078125},{x:.390625,y:.078125},{x:.390625,y:.078125},{x:.421875,y:.078125},{x:.421875,y:.078125},{x:.453125,y:.078125},{x:.453125,y:.078125},{x:.484375,y:.078125},{x:.484375,y:.078125},{x:.515625,y:.078125},{x:.515625,y:.078125},{x:.546875,y:.078125},{x:.546875,y:.078125},{x:.578125,y:.078125},{x:.578125,y:.078125},{x:.609375,y:.078125},{x:.609375,y:.078125},{x:.640625,y:.078125},{x:.640625,y:.078125},{x:.671875,y:.078125},{x:.671875,y:.078125},{x:.703125,y:.078125},{x:.703125,y:.078125},{x:.734375,y:.078125},{x:.734375,y:.078125},{x:.765625,y:.078125},{x:.765625,y:.078125},{x:.796875,y:.078125},{x:.796875,y:.078125},{x:.828125,y:.078125},{x:.828125,y:.078125},{x:.859375,y:.078125},{x:.859375,y:.078125},{x:.890625,y:.078125},{x:.890625,y:.078125},{x:.921875,y:.078125},{x:.921875,y:.078125},{x:.953125,y:.078125},{x:.953125,y:.078125},{x:.984375,y:.078125},{x:.984375,y:.078125},{x:.015625,y:.109375},{x:.015625,y:.109375},{x:.046875,y:.109375},{x:.046875,y:.109375},{x:.078125,y:.109375},{x:.078125,y:.109375},{x:.109375,y:.109375},{x:.109375,y:.109375},{x:.140625,y:.109375},{x:.140625,y:.109375},{x:.171875,y:.109375},{x:.171875,y:.109375},{x:.203125,y:.109375},{x:.203125,y:.109375},{x:.234375,y:.109375},{x:.234375,y:.109375},{x:.265625,y:.109375},{x:.265625,y:.109375},{x:.296875,y:.109375},{x:.296875,y:.109375},{x:.328125,y:.109375},{x:.328125,y:.109375},{x:.359375,y:.109375},{x:.359375,y:.109375},{x:.390625,y:.109375},{x:.390625,y:.109375},{x:.421875,y:.109375},{x:.421875,y:.109375},{x:.453125,y:.109375},{x:.453125,y:.109375},{x:.484375,y:.109375},{x:.484375,y:.109375},{x:.515625,y:.109375},{x:.515625,y:.109375},{x:.546875,y:.109375},{x:.546875,y:.109375},{x:.578125,y:.109375},{x:.578125,y:.109375},{x:.609375,y:.109375},{x:.609375,y:.109375},{x:.640625,y:.109375},{x:.640625,y:.109375},{x:.671875,y:.109375},{x:.671875,y:.109375},{x:.703125,y:.109375},{x:.703125,y:.109375},{x:.734375,y:.109375},{x:.734375,y:.109375},{x:.765625,y:.109375},{x:.765625,y:.109375},{x:.796875,y:.109375},{x:.796875,y:.109375},{x:.828125,y:.109375},{x:.828125,y:.109375},{x:.859375,y:.109375},{x:.859375,y:.109375},{x:.890625,y:.109375},{x:.890625,y:.109375},{x:.921875,y:.109375},{x:.921875,y:.109375},{x:.953125,y:.109375},{x:.953125,y:.109375},{x:.984375,y:.109375},{x:.984375,y:.109375},{x:.015625,y:.140625},{x:.015625,y:.140625},{x:.046875,y:.140625},{x:.046875,y:.140625},{x:.078125,y:.140625},{x:.078125,y:.140625},{x:.109375,y:.140625},{x:.109375,y:.140625},{x:.140625,y:.140625},{x:.140625,y:.140625},{x:.171875,y:.140625},{x:.171875,y:.140625},{x:.203125,y:.140625},{x:.203125,y:.140625},{x:.234375,y:.140625},{x:.234375,y:.140625},{x:.265625,y:.140625},{x:.265625,y:.140625},{x:.296875,y:.140625},{x:.296875,y:.140625},{x:.328125,y:.140625},{x:.328125,y:.140625},{x:.359375,y:.140625},{x:.359375,y:.140625},{x:.390625,y:.140625},{x:.390625,y:.140625},{x:.421875,y:.140625},{x:.421875,y:.140625},{x:.453125,y:.140625},{x:.453125,y:.140625},{x:.484375,y:.140625},{x:.484375,y:.140625},{x:.515625,y:.140625},{x:.515625,y:.140625},{x:.546875,y:.140625},{x:.546875,y:.140625},{x:.578125,y:.140625},{x:.578125,y:.140625},{x:.609375,y:.140625},{x:.609375,y:.140625},{x:.640625,y:.140625},{x:.640625,y:.140625},{x:.671875,y:.140625},{x:.671875,y:.140625},{x:.703125,y:.140625},{x:.703125,y:.140625},{x:.734375,y:.140625},{x:.734375,y:.140625},{x:.765625,y:.140625},{x:.765625,y:.140625},{x:.796875,y:.140625},{x:.796875,y:.140625},{x:.828125,y:.140625},{x:.828125,y:.140625},{x:.859375,y:.140625},{x:.859375,y:.140625},{x:.890625,y:.140625},{x:.890625,y:.140625},{x:.921875,y:.140625},{x:.921875,y:.140625},{x:.953125,y:.140625},{x:.953125,y:.140625},{x:.984375,y:.140625},{x:.984375,y:.140625},{x:.015625,y:.171875},{x:.015625,y:.171875},{x:.046875,y:.171875},{x:.046875,y:.171875},{x:.078125,y:.171875},{x:.078125,y:.171875},{x:.109375,y:.171875},{x:.109375,y:.171875},{x:.140625,y:.171875},{x:.140625,y:.171875},{x:.171875,y:.171875},{x:.171875,y:.171875},{x:.203125,y:.171875},{x:.203125,y:.171875},{x:.234375,y:.171875},{x:.234375,y:.171875},{x:.265625,y:.171875},{x:.265625,y:.171875},{x:.296875,y:.171875},{x:.296875,y:.171875},{x:.328125,y:.171875},{x:.328125,y:.171875},{x:.359375,y:.171875},{x:.359375,y:.171875},{x:.390625,y:.171875},{x:.390625,y:.171875},{x:.421875,y:.171875},{x:.421875,y:.171875},{x:.453125,y:.171875},{x:.453125,y:.171875},{x:.484375,y:.171875},{x:.484375,y:.171875},{x:.515625,y:.171875},{x:.515625,y:.171875},{x:.546875,y:.171875},{x:.546875,y:.171875},{x:.578125,y:.171875},{x:.578125,y:.171875},{x:.609375,y:.171875},{x:.609375,y:.171875},{x:.640625,y:.171875},{x:.640625,y:.171875},{x:.671875,y:.171875},{x:.671875,y:.171875},{x:.703125,y:.171875},{x:.703125,y:.171875},{x:.734375,y:.171875},{x:.734375,y:.171875},{x:.765625,y:.171875},{x:.765625,y:.171875},{x:.796875,y:.171875},{x:.796875,y:.171875},{x:.828125,y:.171875},{x:.828125,y:.171875},{x:.859375,y:.171875},{x:.859375,y:.171875},{x:.890625,y:.171875},{x:.890625,y:.171875},{x:.921875,y:.171875},{x:.921875,y:.171875},{x:.953125,y:.171875},{x:.953125,y:.171875},{x:.984375,y:.171875},{x:.984375,y:.171875},{x:.015625,y:.203125},{x:.015625,y:.203125},{x:.046875,y:.203125},{x:.046875,y:.203125},{x:.078125,y:.203125},{x:.078125,y:.203125},{x:.109375,y:.203125},{x:.109375,y:.203125},{x:.140625,y:.203125},{x:.140625,y:.203125},{x:.171875,y:.203125},{x:.171875,y:.203125},{x:.203125,y:.203125},{x:.203125,y:.203125},{x:.234375,y:.203125},{x:.234375,y:.203125},{x:.265625,y:.203125},{x:.265625,y:.203125},{x:.296875,y:.203125},{x:.296875,y:.203125},{x:.328125,y:.203125},{x:.328125,y:.203125},{x:.359375,y:.203125},{x:.359375,y:.203125},{x:.390625,y:.203125},{x:.390625,y:.203125},{x:.421875,y:.203125},{x:.421875,y:.203125},{x:.453125,y:.203125},{x:.453125,y:.203125},{x:.484375,y:.203125},{x:.484375,y:.203125},{x:.515625,y:.203125},{x:.515625,y:.203125},{x:.546875,y:.203125},{x:.546875,y:.203125},{x:.578125,y:.203125},{x:.578125,y:.203125},{x:.609375,y:.203125},{x:.609375,y:.203125},{x:.640625,y:.203125},{x:.640625,y:.203125},{x:.671875,y:.203125},{x:.671875,y:.203125},{x:.703125,y:.203125},{x:.703125,y:.203125},{x:.734375,y:.203125},{x:.734375,y:.203125},{x:.765625,y:.203125},{x:.765625,y:.203125},{x:.796875,y:.203125},{x:.796875,y:.203125},{x:.828125,y:.203125},{x:.828125,y:.203125},{x:.859375,y:.203125},{x:.859375,y:.203125},{x:.890625,y:.203125},{x:.890625,y:.203125},{x:.921875,y:.203125},{x:.921875,y:.203125},{x:.953125,y:.203125},{x:.953125,y:.203125},{x:.984375,y:.203125},{x:.984375,y:.203125},{x:.015625,y:.234375},{x:.015625,y:.234375},{x:.046875,y:.234375},{x:.046875,y:.234375},{x:.078125,y:.234375},{x:.078125,y:.234375},{x:.109375,y:.234375},{x:.109375,y:.234375},{x:.140625,y:.234375},{x:.140625,y:.234375},{x:.171875,y:.234375},{x:.171875,y:.234375},{x:.203125,y:.234375},{x:.203125,y:.234375},{x:.234375,y:.234375},{x:.234375,y:.234375},{x:.265625,y:.234375},{x:.265625,y:.234375},{x:.296875,y:.234375},{x:.296875,y:.234375},{x:.328125,y:.234375},{x:.328125,y:.234375},{x:.359375,y:.234375},{x:.359375,y:.234375},{x:.390625,y:.234375},{x:.390625,y:.234375},{x:.421875,y:.234375},{x:.421875,y:.234375},{x:.453125,y:.234375},{x:.453125,y:.234375},{x:.484375,y:.234375},{x:.484375,y:.234375},{x:.515625,y:.234375},{x:.515625,y:.234375},{x:.546875,y:.234375},{x:.546875,y:.234375},{x:.578125,y:.234375},{x:.578125,y:.234375},{x:.609375,y:.234375},{x:.609375,y:.234375},{x:.640625,y:.234375},{x:.640625,y:.234375},{x:.671875,y:.234375},{x:.671875,y:.234375},{x:.703125,y:.234375},{x:.703125,y:.234375},{x:.734375,y:.234375},{x:.734375,y:.234375},{x:.765625,y:.234375},{x:.765625,y:.234375},{x:.796875,y:.234375},{x:.796875,y:.234375},{x:.828125,y:.234375},{x:.828125,y:.234375},{x:.859375,y:.234375},{x:.859375,y:.234375},{x:.890625,y:.234375},{x:.890625,y:.234375},{x:.921875,y:.234375},{x:.921875,y:.234375},{x:.953125,y:.234375},{x:.953125,y:.234375},{x:.984375,y:.234375},{x:.984375,y:.234375},{x:.015625,y:.265625},{x:.015625,y:.265625},{x:.046875,y:.265625},{x:.046875,y:.265625},{x:.078125,y:.265625},{x:.078125,y:.265625},{x:.109375,y:.265625},{x:.109375,y:.265625},{x:.140625,y:.265625},{x:.140625,y:.265625},{x:.171875,y:.265625},{x:.171875,y:.265625},{x:.203125,y:.265625},{x:.203125,y:.265625},{x:.234375,y:.265625},{x:.234375,y:.265625},{x:.265625,y:.265625},{x:.265625,y:.265625},{x:.296875,y:.265625},{x:.296875,y:.265625},{x:.328125,y:.265625},{x:.328125,y:.265625},{x:.359375,y:.265625},{x:.359375,y:.265625},{x:.390625,y:.265625},{x:.390625,y:.265625},{x:.421875,y:.265625},{x:.421875,y:.265625},{x:.453125,y:.265625},{x:.453125,y:.265625},{x:.484375,y:.265625},{x:.484375,y:.265625},{x:.515625,y:.265625},{x:.515625,y:.265625},{x:.546875,y:.265625},{x:.546875,y:.265625},{x:.578125,y:.265625},{x:.578125,y:.265625},{x:.609375,y:.265625},{x:.609375,y:.265625},{x:.640625,y:.265625},{x:.640625,y:.265625},{x:.671875,y:.265625},{x:.671875,y:.265625},{x:.703125,y:.265625},{x:.703125,y:.265625},{x:.734375,y:.265625},{x:.734375,y:.265625},{x:.765625,y:.265625},{x:.765625,y:.265625},{x:.796875,y:.265625},{x:.796875,y:.265625},{x:.828125,y:.265625},{x:.828125,y:.265625},{x:.859375,y:.265625},{x:.859375,y:.265625},{x:.890625,y:.265625},{x:.890625,y:.265625},{x:.921875,y:.265625},{x:.921875,y:.265625},{x:.953125,y:.265625},{x:.953125,y:.265625},{x:.984375,y:.265625},{x:.984375,y:.265625},{x:.015625,y:.296875},{x:.015625,y:.296875},{x:.046875,y:.296875},{x:.046875,y:.296875},{x:.078125,y:.296875},{x:.078125,y:.296875},{x:.109375,y:.296875},{x:.109375,y:.296875},{x:.140625,y:.296875},{x:.140625,y:.296875},{x:.171875,y:.296875},{x:.171875,y:.296875},{x:.203125,y:.296875},{x:.203125,y:.296875},{x:.234375,y:.296875},{x:.234375,y:.296875},{x:.265625,y:.296875},{x:.265625,y:.296875},{x:.296875,y:.296875},{x:.296875,y:.296875},{x:.328125,y:.296875},{x:.328125,y:.296875},{x:.359375,y:.296875},{x:.359375,y:.296875},{x:.390625,y:.296875},{x:.390625,y:.296875},{x:.421875,y:.296875},{x:.421875,y:.296875},{x:.453125,y:.296875},{x:.453125,y:.296875},{x:.484375,y:.296875},{x:.484375,y:.296875},{x:.515625,y:.296875},{x:.515625,y:.296875},{x:.546875,y:.296875},{x:.546875,y:.296875},{x:.578125,y:.296875},{x:.578125,y:.296875},{x:.609375,y:.296875},{x:.609375,y:.296875},{x:.640625,y:.296875},{x:.640625,y:.296875},{x:.671875,y:.296875},{x:.671875,y:.296875},{x:.703125,y:.296875},{x:.703125,y:.296875},{x:.734375,y:.296875},{x:.734375,y:.296875},{x:.765625,y:.296875},{x:.765625,y:.296875},{x:.796875,y:.296875},{x:.796875,y:.296875},{x:.828125,y:.296875},{x:.828125,y:.296875},{x:.859375,y:.296875},{x:.859375,y:.296875},{x:.890625,y:.296875},{x:.890625,y:.296875},{x:.921875,y:.296875},{x:.921875,y:.296875},{x:.953125,y:.296875},{x:.953125,y:.296875},{x:.984375,y:.296875},{x:.984375,y:.296875},{x:.015625,y:.328125},{x:.015625,y:.328125},{x:.046875,y:.328125},{x:.046875,y:.328125},{x:.078125,y:.328125},{x:.078125,y:.328125},{x:.109375,y:.328125},{x:.109375,y:.328125},{x:.140625,y:.328125},{x:.140625,y:.328125},{x:.171875,y:.328125},{x:.171875,y:.328125},{x:.203125,y:.328125},{x:.203125,y:.328125},{x:.234375,y:.328125},{x:.234375,y:.328125},{x:.265625,y:.328125},{x:.265625,y:.328125},{x:.296875,y:.328125},{x:.296875,y:.328125},{x:.328125,y:.328125},{x:.328125,y:.328125},{x:.359375,y:.328125},{x:.359375,y:.328125},{x:.390625,y:.328125},{x:.390625,y:.328125},{x:.421875,y:.328125},{x:.421875,y:.328125},{x:.453125,y:.328125},{x:.453125,y:.328125},{x:.484375,y:.328125},{x:.484375,y:.328125},{x:.515625,y:.328125},{x:.515625,y:.328125},{x:.546875,y:.328125},{x:.546875,y:.328125},{x:.578125,y:.328125},{x:.578125,y:.328125},{x:.609375,y:.328125},{x:.609375,y:.328125},{x:.640625,y:.328125},{x:.640625,y:.328125},{x:.671875,y:.328125},{x:.671875,y:.328125},{x:.703125,y:.328125},{x:.703125,y:.328125},{x:.734375,y:.328125},{x:.734375,y:.328125},{x:.765625,y:.328125},{x:.765625,y:.328125},{x:.796875,y:.328125},{x:.796875,y:.328125},{x:.828125,y:.328125},{x:.828125,y:.328125},{x:.859375,y:.328125},{x:.859375,y:.328125},{x:.890625,y:.328125},{x:.890625,y:.328125},{x:.921875,y:.328125},{x:.921875,y:.328125},{x:.953125,y:.328125},{x:.953125,y:.328125},{x:.984375,y:.328125},{x:.984375,y:.328125},{x:.015625,y:.359375},{x:.015625,y:.359375},{x:.046875,y:.359375},{x:.046875,y:.359375},{x:.078125,y:.359375},{x:.078125,y:.359375},{x:.109375,y:.359375},{x:.109375,y:.359375},{x:.140625,y:.359375},{x:.140625,y:.359375},{x:.171875,y:.359375},{x:.171875,y:.359375},{x:.203125,y:.359375},{x:.203125,y:.359375},{x:.234375,y:.359375},{x:.234375,y:.359375},{x:.265625,y:.359375},{x:.265625,y:.359375},{x:.296875,y:.359375},{x:.296875,y:.359375},{x:.328125,y:.359375},{x:.328125,y:.359375},{x:.359375,y:.359375},{x:.359375,y:.359375},{x:.390625,y:.359375},{x:.390625,y:.359375},{x:.421875,y:.359375},{x:.421875,y:.359375},{x:.453125,y:.359375},{x:.453125,y:.359375},{x:.484375,y:.359375},{x:.484375,y:.359375},{x:.515625,y:.359375},{x:.515625,y:.359375},{x:.546875,y:.359375},{x:.546875,y:.359375},{x:.578125,y:.359375},{x:.578125,y:.359375},{x:.609375,y:.359375},{x:.609375,y:.359375},{x:.640625,y:.359375},{x:.640625,y:.359375},{x:.671875,y:.359375},{x:.671875,y:.359375},{x:.703125,y:.359375},{x:.703125,y:.359375},{x:.734375,y:.359375},{x:.734375,y:.359375},{x:.765625,y:.359375},{x:.765625,y:.359375},{x:.796875,y:.359375},{x:.796875,y:.359375},{x:.828125,y:.359375},{x:.828125,y:.359375},{x:.859375,y:.359375},{x:.859375,y:.359375},{x:.890625,y:.359375},{x:.890625,y:.359375},{x:.921875,y:.359375},{x:.921875,y:.359375},{x:.953125,y:.359375},{x:.953125,y:.359375},{x:.984375,y:.359375},{x:.984375,y:.359375},{x:.015625,y:.390625},{x:.015625,y:.390625},{x:.046875,y:.390625},{x:.046875,y:.390625},{x:.078125,y:.390625},{x:.078125,y:.390625},{x:.109375,y:.390625},{x:.109375,y:.390625},{x:.140625,y:.390625},{x:.140625,y:.390625},{x:.171875,y:.390625},{x:.171875,y:.390625},{x:.203125,y:.390625},{x:.203125,y:.390625},{x:.234375,y:.390625},{x:.234375,y:.390625},{x:.265625,y:.390625},{x:.265625,y:.390625},{x:.296875,y:.390625},{x:.296875,y:.390625},{x:.328125,y:.390625},{x:.328125,y:.390625},{x:.359375,y:.390625},{x:.359375,y:.390625},{x:.390625,y:.390625},{x:.390625,y:.390625},{x:.421875,y:.390625},{x:.421875,y:.390625},{x:.453125,y:.390625},{x:.453125,y:.390625},{x:.484375,y:.390625},{x:.484375,y:.390625},{x:.515625,y:.390625},{x:.515625,y:.390625},{x:.546875,y:.390625},{x:.546875,y:.390625},{x:.578125,y:.390625},{x:.578125,y:.390625},{x:.609375,y:.390625},{x:.609375,y:.390625},{x:.640625,y:.390625},{x:.640625,y:.390625},{x:.671875,y:.390625},{x:.671875,y:.390625},{x:.703125,y:.390625},{x:.703125,y:.390625},{x:.734375,y:.390625},{x:.734375,y:.390625},{x:.765625,y:.390625},{x:.765625,y:.390625},{x:.796875,y:.390625},{x:.796875,y:.390625},{x:.828125,y:.390625},{x:.828125,y:.390625},{x:.859375,y:.390625},{x:.859375,y:.390625},{x:.890625,y:.390625},{x:.890625,y:.390625},{x:.921875,y:.390625},{x:.921875,y:.390625},{x:.953125,y:.390625},{x:.953125,y:.390625},{x:.984375,y:.390625},{x:.984375,y:.390625},{x:.015625,y:.421875},{x:.015625,y:.421875},{x:.046875,y:.421875},{x:.046875,y:.421875},{x:.078125,y:.421875},{x:.078125,y:.421875},{x:.109375,y:.421875},{x:.109375,y:.421875},{x:.140625,y:.421875},{x:.140625,y:.421875},{x:.171875,y:.421875},{x:.171875,y:.421875},{x:.203125,y:.421875},{x:.203125,y:.421875},{x:.234375,y:.421875},{x:.234375,y:.421875},{x:.265625,y:.421875},{x:.265625,y:.421875},{x:.296875,y:.421875},{x:.296875,y:.421875},{x:.328125,y:.421875},{x:.328125,y:.421875},{x:.359375,y:.421875},{x:.359375,y:.421875},{x:.390625,y:.421875},{x:.390625,y:.421875},{x:.421875,y:.421875},{x:.421875,y:.421875},{x:.453125,y:.421875},{x:.453125,y:.421875},{x:.484375,y:.421875},{x:.484375,y:.421875},{x:.515625,y:.421875},{x:.515625,y:.421875},{x:.546875,y:.421875},{x:.546875,y:.421875},{x:.578125,y:.421875},{x:.578125,y:.421875},{x:.609375,y:.421875},{x:.609375,y:.421875},{x:.640625,y:.421875},{x:.640625,y:.421875},{x:.671875,y:.421875},{x:.671875,y:.421875},{x:.703125,y:.421875},{x:.703125,y:.421875},{x:.734375,y:.421875},{x:.734375,y:.421875},{x:.765625,y:.421875},{x:.765625,y:.421875},{x:.796875,y:.421875},{x:.796875,y:.421875},{x:.828125,y:.421875},{x:.828125,y:.421875},{x:.859375,y:.421875},{x:.859375,y:.421875},{x:.890625,y:.421875},{x:.890625,y:.421875},{x:.921875,y:.421875},{x:.921875,y:.421875},{x:.953125,y:.421875},{x:.953125,y:.421875},{x:.984375,y:.421875},{x:.984375,y:.421875},{x:.015625,y:.453125},{x:.015625,y:.453125},{x:.046875,y:.453125},{x:.046875,y:.453125},{x:.078125,y:.453125},{x:.078125,y:.453125},{x:.109375,y:.453125},{x:.109375,y:.453125},{x:.140625,y:.453125},{x:.140625,y:.453125},{x:.171875,y:.453125},{x:.171875,y:.453125},{x:.203125,y:.453125},{x:.203125,y:.453125},{x:.234375,y:.453125},{x:.234375,y:.453125},{x:.265625,y:.453125},{x:.265625,y:.453125},{x:.296875,y:.453125},{x:.296875,y:.453125},{x:.328125,y:.453125},{x:.328125,y:.453125},{x:.359375,y:.453125},{x:.359375,y:.453125},{x:.390625,y:.453125},{x:.390625,y:.453125},{x:.421875,y:.453125},{x:.421875,y:.453125},{x:.453125,y:.453125},{x:.453125,y:.453125},{x:.484375,y:.453125},{x:.484375,y:.453125},{x:.515625,y:.453125},{x:.515625,y:.453125},{x:.546875,y:.453125},{x:.546875,y:.453125},{x:.578125,y:.453125},{x:.578125,y:.453125},{x:.609375,y:.453125},{x:.609375,y:.453125},{x:.640625,y:.453125},{x:.640625,y:.453125},{x:.671875,y:.453125},{x:.671875,y:.453125},{x:.703125,y:.453125},{x:.703125,y:.453125},{x:.734375,y:.453125},{x:.734375,y:.453125},{x:.765625,y:.453125},{x:.765625,y:.453125},{x:.796875,y:.453125},{x:.796875,y:.453125},{x:.828125,y:.453125},{x:.828125,y:.453125},{x:.859375,y:.453125},{x:.859375,y:.453125},{x:.890625,y:.453125},{x:.890625,y:.453125},{x:.921875,y:.453125},{x:.921875,y:.453125},{x:.953125,y:.453125},{x:.953125,y:.453125},{x:.984375,y:.453125},{x:.984375,y:.453125},{x:.015625,y:.484375},{x:.015625,y:.484375},{x:.046875,y:.484375},{x:.046875,y:.484375},{x:.078125,y:.484375},{x:.078125,y:.484375},{x:.109375,y:.484375},{x:.109375,y:.484375},{x:.140625,y:.484375},{x:.140625,y:.484375},{x:.171875,y:.484375},{x:.171875,y:.484375},{x:.203125,y:.484375},{x:.203125,y:.484375},{x:.234375,y:.484375},{x:.234375,y:.484375},{x:.265625,y:.484375},{x:.265625,y:.484375},{x:.296875,y:.484375},{x:.296875,y:.484375},{x:.328125,y:.484375},{x:.328125,y:.484375},{x:.359375,y:.484375},{x:.359375,y:.484375},{x:.390625,y:.484375},{x:.390625,y:.484375},{x:.421875,y:.484375},{x:.421875,y:.484375},{x:.453125,y:.484375},{x:.453125,y:.484375},{x:.484375,y:.484375},{x:.484375,y:.484375},{x:.515625,y:.484375},{x:.515625,y:.484375},{x:.546875,y:.484375},{x:.546875,y:.484375},{x:.578125,y:.484375},{x:.578125,y:.484375},{x:.609375,y:.484375},{x:.609375,y:.484375},{x:.640625,y:.484375},{x:.640625,y:.484375},{x:.671875,y:.484375},{x:.671875,y:.484375},{x:.703125,y:.484375},{x:.703125,y:.484375},{x:.734375,y:.484375},{x:.734375,y:.484375},{x:.765625,y:.484375},{x:.765625,y:.484375},{x:.796875,y:.484375},{x:.796875,y:.484375},{x:.828125,y:.484375},{x:.828125,y:.484375},{x:.859375,y:.484375},{x:.859375,y:.484375},{x:.890625,y:.484375},{x:.890625,y:.484375},{x:.921875,y:.484375},{x:.921875,y:.484375},{x:.953125,y:.484375},{x:.953125,y:.484375},{x:.984375,y:.484375},{x:.984375,y:.484375},{x:.015625,y:.515625},{x:.015625,y:.515625},{x:.046875,y:.515625},{x:.046875,y:.515625},{x:.078125,y:.515625},{x:.078125,y:.515625},{x:.109375,y:.515625},{x:.109375,y:.515625},{x:.140625,y:.515625},{x:.140625,y:.515625},{x:.171875,y:.515625},{x:.171875,y:.515625},{x:.203125,y:.515625},{x:.203125,y:.515625},{x:.234375,y:.515625},{x:.234375,y:.515625},{x:.265625,y:.515625},{x:.265625,y:.515625},{x:.296875,y:.515625},{x:.296875,y:.515625},{x:.328125,y:.515625},{x:.328125,y:.515625},{x:.359375,y:.515625},{x:.359375,y:.515625},{x:.390625,y:.515625},{x:.390625,y:.515625},{x:.421875,y:.515625},{x:.421875,y:.515625},{x:.453125,y:.515625},{x:.453125,y:.515625},{x:.484375,y:.515625},{x:.484375,y:.515625},{x:.515625,y:.515625},{x:.515625,y:.515625},{x:.546875,y:.515625},{x:.546875,y:.515625},{x:.578125,y:.515625},{x:.578125,y:.515625},{x:.609375,y:.515625},{x:.609375,y:.515625},{x:.640625,y:.515625},{x:.640625,y:.515625},{x:.671875,y:.515625},{x:.671875,y:.515625},{x:.703125,y:.515625},{x:.703125,y:.515625},{x:.734375,y:.515625},{x:.734375,y:.515625},{x:.765625,y:.515625},{x:.765625,y:.515625},{x:.796875,y:.515625},{x:.796875,y:.515625},{x:.828125,y:.515625},{x:.828125,y:.515625},{x:.859375,y:.515625},{x:.859375,y:.515625},{x:.890625,y:.515625},{x:.890625,y:.515625},{x:.921875,y:.515625},{x:.921875,y:.515625},{x:.953125,y:.515625},{x:.953125,y:.515625},{x:.984375,y:.515625},{x:.984375,y:.515625},{x:.015625,y:.546875},{x:.015625,y:.546875},{x:.046875,y:.546875},{x:.046875,y:.546875},{x:.078125,y:.546875},{x:.078125,y:.546875},{x:.109375,y:.546875},{x:.109375,y:.546875},{x:.140625,y:.546875},{x:.140625,y:.546875},{x:.171875,y:.546875},{x:.171875,y:.546875},{x:.203125,y:.546875},{x:.203125,y:.546875},{x:.234375,y:.546875},{x:.234375,y:.546875},{x:.265625,y:.546875},{x:.265625,y:.546875},{x:.296875,y:.546875},{x:.296875,y:.546875},{x:.328125,y:.546875},{x:.328125,y:.546875},{x:.359375,y:.546875},{x:.359375,y:.546875},{x:.390625,y:.546875},{x:.390625,y:.546875},{x:.421875,y:.546875},{x:.421875,y:.546875},{x:.453125,y:.546875},{x:.453125,y:.546875},{x:.484375,y:.546875},{x:.484375,y:.546875},{x:.515625,y:.546875},{x:.515625,y:.546875},{x:.546875,y:.546875},{x:.546875,y:.546875},{x:.578125,y:.546875},{x:.578125,y:.546875},{x:.609375,y:.546875},{x:.609375,y:.546875},{x:.640625,y:.546875},{x:.640625,y:.546875},{x:.671875,y:.546875},{x:.671875,y:.546875},{x:.703125,y:.546875},{x:.703125,y:.546875},{x:.734375,y:.546875},{x:.734375,y:.546875},{x:.765625,y:.546875},{x:.765625,y:.546875},{x:.796875,y:.546875},{x:.796875,y:.546875},{x:.828125,y:.546875},{x:.828125,y:.546875},{x:.859375,y:.546875},{x:.859375,y:.546875},{x:.890625,y:.546875},{x:.890625,y:.546875},{x:.921875,y:.546875},{x:.921875,y:.546875},{x:.953125,y:.546875},{x:.953125,y:.546875},{x:.984375,y:.546875},{x:.984375,y:.546875},{x:.015625,y:.578125},{x:.015625,y:.578125},{x:.046875,y:.578125},{x:.046875,y:.578125},{x:.078125,y:.578125},{x:.078125,y:.578125},{x:.109375,y:.578125},{x:.109375,y:.578125},{x:.140625,y:.578125},{x:.140625,y:.578125},{x:.171875,y:.578125},{x:.171875,y:.578125},{x:.203125,y:.578125},{x:.203125,y:.578125},{x:.234375,y:.578125},{x:.234375,y:.578125},{x:.265625,y:.578125},{x:.265625,y:.578125},{x:.296875,y:.578125},{x:.296875,y:.578125},{x:.328125,y:.578125},{x:.328125,y:.578125},{x:.359375,y:.578125},{x:.359375,y:.578125},{x:.390625,y:.578125},{x:.390625,y:.578125},{x:.421875,y:.578125},{x:.421875,y:.578125},{x:.453125,y:.578125},{x:.453125,y:.578125},{x:.484375,y:.578125},{x:.484375,y:.578125},{x:.515625,y:.578125},{x:.515625,y:.578125},{x:.546875,y:.578125},{x:.546875,y:.578125},{x:.578125,y:.578125},{x:.578125,y:.578125},{x:.609375,y:.578125},{x:.609375,y:.578125},{x:.640625,y:.578125},{x:.640625,y:.578125},{x:.671875,y:.578125},{x:.671875,y:.578125},{x:.703125,y:.578125},{x:.703125,y:.578125},{x:.734375,y:.578125},{x:.734375,y:.578125},{x:.765625,y:.578125},{x:.765625,y:.578125},{x:.796875,y:.578125},{x:.796875,y:.578125},{x:.828125,y:.578125},{x:.828125,y:.578125},{x:.859375,y:.578125},{x:.859375,y:.578125},{x:.890625,y:.578125},{x:.890625,y:.578125},{x:.921875,y:.578125},{x:.921875,y:.578125},{x:.953125,y:.578125},{x:.953125,y:.578125},{x:.984375,y:.578125},{x:.984375,y:.578125},{x:.015625,y:.609375},{x:.015625,y:.609375},{x:.046875,y:.609375},{x:.046875,y:.609375},{x:.078125,y:.609375},{x:.078125,y:.609375},{x:.109375,y:.609375},{x:.109375,y:.609375},{x:.140625,y:.609375},{x:.140625,y:.609375},{x:.171875,y:.609375},{x:.171875,y:.609375},{x:.203125,y:.609375},{x:.203125,y:.609375},{x:.234375,y:.609375},{x:.234375,y:.609375},{x:.265625,y:.609375},{x:.265625,y:.609375},{x:.296875,y:.609375},{x:.296875,y:.609375},{x:.328125,y:.609375},{x:.328125,y:.609375},{x:.359375,y:.609375},{x:.359375,y:.609375},{x:.390625,y:.609375},{x:.390625,y:.609375},{x:.421875,y:.609375},{x:.421875,y:.609375},{x:.453125,y:.609375},{x:.453125,y:.609375},{x:.484375,y:.609375},{x:.484375,y:.609375},{x:.515625,y:.609375},{x:.515625,y:.609375},{x:.546875,y:.609375},{x:.546875,y:.609375},{x:.578125,y:.609375},{x:.578125,y:.609375},{x:.609375,y:.609375},{x:.609375,y:.609375},{x:.640625,y:.609375},{x:.640625,y:.609375},{x:.671875,y:.609375},{x:.671875,y:.609375},{x:.703125,y:.609375},{x:.703125,y:.609375},{x:.734375,y:.609375},{x:.734375,y:.609375},{x:.765625,y:.609375},{x:.765625,y:.609375},{x:.796875,y:.609375},{x:.796875,y:.609375},{x:.828125,y:.609375},{x:.828125,y:.609375},{x:.859375,y:.609375},{x:.859375,y:.609375},{x:.890625,y:.609375},{x:.890625,y:.609375},{x:.921875,y:.609375},{x:.921875,y:.609375},{x:.953125,y:.609375},{x:.953125,y:.609375},{x:.984375,y:.609375},{x:.984375,y:.609375},{x:.015625,y:.640625},{x:.015625,y:.640625},{x:.046875,y:.640625},{x:.046875,y:.640625},{x:.078125,y:.640625},{x:.078125,y:.640625},{x:.109375,y:.640625},{x:.109375,y:.640625},{x:.140625,y:.640625},{x:.140625,y:.640625},{x:.171875,y:.640625},{x:.171875,y:.640625},{x:.203125,y:.640625},{x:.203125,y:.640625},{x:.234375,y:.640625},{x:.234375,y:.640625},{x:.265625,y:.640625},{x:.265625,y:.640625},{x:.296875,y:.640625},{x:.296875,y:.640625},{x:.328125,y:.640625},{x:.328125,y:.640625},{x:.359375,y:.640625},{x:.359375,y:.640625},{x:.390625,y:.640625},{x:.390625,y:.640625},{x:.421875,y:.640625},{x:.421875,y:.640625},{x:.453125,y:.640625},{x:.453125,y:.640625},{x:.484375,y:.640625},{x:.484375,y:.640625},{x:.515625,y:.640625},{x:.515625,y:.640625},{x:.546875,y:.640625},{x:.546875,y:.640625},{x:.578125,y:.640625},{x:.578125,y:.640625},{x:.609375,y:.640625},{x:.609375,y:.640625},{x:.640625,y:.640625},{x:.640625,y:.640625},{x:.671875,y:.640625},{x:.671875,y:.640625},{x:.703125,y:.640625},{x:.703125,y:.640625},{x:.734375,y:.640625},{x:.734375,y:.640625},{x:.765625,y:.640625},{x:.765625,y:.640625},{x:.796875,y:.640625},{x:.796875,y:.640625},{x:.828125,y:.640625},{x:.828125,y:.640625},{x:.859375,y:.640625},{x:.859375,y:.640625},{x:.890625,y:.640625},{x:.890625,y:.640625},{x:.921875,y:.640625},{x:.921875,y:.640625},{x:.953125,y:.640625},{x:.953125,y:.640625},{x:.984375,y:.640625},{x:.984375,y:.640625},{x:.015625,y:.671875},{x:.015625,y:.671875},{x:.046875,y:.671875},{x:.046875,y:.671875},{x:.078125,y:.671875},{x:.078125,y:.671875},{x:.109375,y:.671875},{x:.109375,y:.671875},{x:.140625,y:.671875},{x:.140625,y:.671875},{x:.171875,y:.671875},{x:.171875,y:.671875},{x:.203125,y:.671875},{x:.203125,y:.671875},{x:.234375,y:.671875},{x:.234375,y:.671875},{x:.265625,y:.671875},{x:.265625,y:.671875},{x:.296875,y:.671875},{x:.296875,y:.671875},{x:.328125,y:.671875},{x:.328125,y:.671875},{x:.359375,y:.671875},{x:.359375,y:.671875},{x:.390625,y:.671875},{x:.390625,y:.671875},{x:.421875,y:.671875},{x:.421875,y:.671875},{x:.453125,y:.671875},{x:.453125,y:.671875},{x:.484375,y:.671875},{x:.484375,y:.671875},{x:.515625,y:.671875},{x:.515625,y:.671875},{x:.546875,y:.671875},{x:.546875,y:.671875},{x:.578125,y:.671875},{x:.578125,y:.671875},{x:.609375,y:.671875},{x:.609375,y:.671875},{x:.640625,y:.671875},{x:.640625,y:.671875},{x:.671875,y:.671875},{x:.671875,y:.671875},{x:.703125,y:.671875},{x:.703125,y:.671875},{x:.734375,y:.671875},{x:.734375,y:.671875},{x:.765625,y:.671875},{x:.765625,y:.671875},{x:.796875,y:.671875},{x:.796875,y:.671875},{x:.828125,y:.671875},{x:.828125,y:.671875},{x:.859375,y:.671875},{x:.859375,y:.671875},{x:.890625,y:.671875},{x:.890625,y:.671875},{x:.921875,y:.671875},{x:.921875,y:.671875},{x:.953125,y:.671875},{x:.953125,y:.671875},{x:.984375,y:.671875},{x:.984375,y:.671875},{x:.015625,y:.703125},{x:.015625,y:.703125},{x:.046875,y:.703125},{x:.046875,y:.703125},{x:.078125,y:.703125},{x:.078125,y:.703125},{x:.109375,y:.703125},{x:.109375,y:.703125},{x:.140625,y:.703125},{x:.140625,y:.703125},{x:.171875,y:.703125},{x:.171875,y:.703125},{x:.203125,y:.703125},{x:.203125,y:.703125},{x:.234375,y:.703125},{x:.234375,y:.703125},{x:.265625,y:.703125},{x:.265625,y:.703125},{x:.296875,y:.703125},{x:.296875,y:.703125},{x:.328125,y:.703125},{x:.328125,y:.703125},{x:.359375,y:.703125},{x:.359375,y:.703125},{x:.390625,y:.703125},{x:.390625,y:.703125},{x:.421875,y:.703125},{x:.421875,y:.703125},{x:.453125,y:.703125},{x:.453125,y:.703125},{x:.484375,y:.703125},{x:.484375,y:.703125},{x:.515625,y:.703125},{x:.515625,y:.703125},{x:.546875,y:.703125},{x:.546875,y:.703125},{x:.578125,y:.703125},{x:.578125,y:.703125},{x:.609375,y:.703125},{x:.609375,y:.703125},{x:.640625,y:.703125},{x:.640625,y:.703125},{x:.671875,y:.703125},{x:.671875,y:.703125},{x:.703125,y:.703125},{x:.703125,y:.703125},{x:.734375,y:.703125},{x:.734375,y:.703125},{x:.765625,y:.703125},{x:.765625,y:.703125},{x:.796875,y:.703125},{x:.796875,y:.703125},{x:.828125,y:.703125},{x:.828125,y:.703125},{x:.859375,y:.703125},{x:.859375,y:.703125},{x:.890625,y:.703125},{x:.890625,y:.703125},{x:.921875,y:.703125},{x:.921875,y:.703125},{x:.953125,y:.703125},{x:.953125,y:.703125},{x:.984375,y:.703125},{x:.984375,y:.703125},{x:.015625,y:.734375},{x:.015625,y:.734375},{x:.046875,y:.734375},{x:.046875,y:.734375},{x:.078125,y:.734375},{x:.078125,y:.734375},{x:.109375,y:.734375},{x:.109375,y:.734375},{x:.140625,y:.734375},{x:.140625,y:.734375},{x:.171875,y:.734375},{x:.171875,y:.734375},{x:.203125,y:.734375},{x:.203125,y:.734375},{x:.234375,y:.734375},{x:.234375,y:.734375},{x:.265625,y:.734375},{x:.265625,y:.734375},{x:.296875,y:.734375},{x:.296875,y:.734375},{x:.328125,y:.734375},{x:.328125,y:.734375},{x:.359375,y:.734375},{x:.359375,y:.734375},{x:.390625,y:.734375},{x:.390625,y:.734375},{x:.421875,y:.734375},{x:.421875,y:.734375},{x:.453125,y:.734375},{x:.453125,y:.734375},{x:.484375,y:.734375},{x:.484375,y:.734375},{x:.515625,y:.734375},{x:.515625,y:.734375},{x:.546875,y:.734375},{x:.546875,y:.734375},{x:.578125,y:.734375},{x:.578125,y:.734375},{x:.609375,y:.734375},{x:.609375,y:.734375},{x:.640625,y:.734375},{x:.640625,y:.734375},{x:.671875,y:.734375},{x:.671875,y:.734375},{x:.703125,y:.734375},{x:.703125,y:.734375},{x:.734375,y:.734375},{x:.734375,y:.734375},{x:.765625,y:.734375},{x:.765625,y:.734375},{x:.796875,y:.734375},{x:.796875,y:.734375},{x:.828125,y:.734375},{x:.828125,y:.734375},{x:.859375,y:.734375},{x:.859375,y:.734375},{x:.890625,y:.734375},{x:.890625,y:.734375},{x:.921875,y:.734375},{x:.921875,y:.734375},{x:.953125,y:.734375},{x:.953125,y:.734375},{x:.984375,y:.734375},{x:.984375,y:.734375},{x:.015625,y:.765625},{x:.015625,y:.765625},{x:.046875,y:.765625},{x:.046875,y:.765625},{x:.078125,y:.765625},{x:.078125,y:.765625},{x:.109375,y:.765625},{x:.109375,y:.765625},{x:.140625,y:.765625},{x:.140625,y:.765625},{x:.171875,y:.765625},{x:.171875,y:.765625},{x:.203125,y:.765625},{x:.203125,y:.765625},{x:.234375,y:.765625},{x:.234375,y:.765625},{x:.265625,y:.765625},{x:.265625,y:.765625},{x:.296875,y:.765625},{x:.296875,y:.765625},{x:.328125,y:.765625},{x:.328125,y:.765625},{x:.359375,y:.765625},{x:.359375,y:.765625},{x:.390625,y:.765625},{x:.390625,y:.765625},{x:.421875,y:.765625},{x:.421875,y:.765625},{x:.453125,y:.765625},{x:.453125,y:.765625},{x:.484375,y:.765625},{x:.484375,y:.765625},{x:.515625,y:.765625},{x:.515625,y:.765625},{x:.546875,y:.765625},{x:.546875,y:.765625},{x:.578125,y:.765625},{x:.578125,y:.765625},{x:.609375,y:.765625},{x:.609375,y:.765625},{x:.640625,y:.765625},{x:.640625,y:.765625},{x:.671875,y:.765625},{x:.671875,y:.765625},{x:.703125,y:.765625},{x:.703125,y:.765625},{x:.734375,y:.765625},{x:.734375,y:.765625},{x:.765625,y:.765625},{x:.765625,y:.765625},{x:.796875,y:.765625},{x:.796875,y:.765625},{x:.828125,y:.765625},{x:.828125,y:.765625},{x:.859375,y:.765625},{x:.859375,y:.765625},{x:.890625,y:.765625},{x:.890625,y:.765625},{x:.921875,y:.765625},{x:.921875,y:.765625},{x:.953125,y:.765625},{x:.953125,y:.765625},{x:.984375,y:.765625},{x:.984375,y:.765625},{x:.015625,y:.796875},{x:.015625,y:.796875},{x:.046875,y:.796875},{x:.046875,y:.796875},{x:.078125,y:.796875},{x:.078125,y:.796875},{x:.109375,y:.796875},{x:.109375,y:.796875},{x:.140625,y:.796875},{x:.140625,y:.796875},{x:.171875,y:.796875},{x:.171875,y:.796875},{x:.203125,y:.796875},{x:.203125,y:.796875},{x:.234375,y:.796875},{x:.234375,y:.796875},{x:.265625,y:.796875},{x:.265625,y:.796875},{x:.296875,y:.796875},{x:.296875,y:.796875},{x:.328125,y:.796875},{x:.328125,y:.796875},{x:.359375,y:.796875},{x:.359375,y:.796875},{x:.390625,y:.796875},{x:.390625,y:.796875},{x:.421875,y:.796875},{x:.421875,y:.796875},{x:.453125,y:.796875},{x:.453125,y:.796875},{x:.484375,y:.796875},{x:.484375,y:.796875},{x:.515625,y:.796875},{x:.515625,y:.796875},{x:.546875,y:.796875},{x:.546875,y:.796875},{x:.578125,y:.796875},{x:.578125,y:.796875},{x:.609375,y:.796875},{x:.609375,y:.796875},{x:.640625,y:.796875},{x:.640625,y:.796875},{x:.671875,y:.796875},{x:.671875,y:.796875},{x:.703125,y:.796875},{x:.703125,y:.796875},{x:.734375,y:.796875},{x:.734375,y:.796875},{x:.765625,y:.796875},{x:.765625,y:.796875},{x:.796875,y:.796875},{x:.796875,y:.796875},{x:.828125,y:.796875},{x:.828125,y:.796875},{x:.859375,y:.796875},{x:.859375,y:.796875},{x:.890625,y:.796875},{x:.890625,y:.796875},{x:.921875,y:.796875},{x:.921875,y:.796875},{x:.953125,y:.796875},{x:.953125,y:.796875},{x:.984375,y:.796875},{x:.984375,y:.796875},{x:.015625,y:.828125},{x:.015625,y:.828125},{x:.046875,y:.828125},{x:.046875,y:.828125},{x:.078125,y:.828125},{x:.078125,y:.828125},{x:.109375,y:.828125},{x:.109375,y:.828125},{x:.140625,y:.828125},{x:.140625,y:.828125},{x:.171875,y:.828125},{x:.171875,y:.828125},{x:.203125,y:.828125},{x:.203125,y:.828125},{x:.234375,y:.828125},{x:.234375,y:.828125},{x:.265625,y:.828125},{x:.265625,y:.828125},{x:.296875,y:.828125},{x:.296875,y:.828125},{x:.328125,y:.828125},{x:.328125,y:.828125},{x:.359375,y:.828125},{x:.359375,y:.828125},{x:.390625,y:.828125},{x:.390625,y:.828125},{x:.421875,y:.828125},{x:.421875,y:.828125},{x:.453125,y:.828125},{x:.453125,y:.828125},{x:.484375,y:.828125},{x:.484375,y:.828125},{x:.515625,y:.828125},{x:.515625,y:.828125},{x:.546875,y:.828125},{x:.546875,y:.828125},{x:.578125,y:.828125},{x:.578125,y:.828125},{x:.609375,y:.828125},{x:.609375,y:.828125},{x:.640625,y:.828125},{x:.640625,y:.828125},{x:.671875,y:.828125},{x:.671875,y:.828125},{x:.703125,y:.828125},{x:.703125,y:.828125},{x:.734375,y:.828125},{x:.734375,y:.828125},{x:.765625,y:.828125},{x:.765625,y:.828125},{x:.796875,y:.828125},{x:.796875,y:.828125},{x:.828125,y:.828125},{x:.828125,y:.828125},{x:.859375,y:.828125},{x:.859375,y:.828125},{x:.890625,y:.828125},{x:.890625,y:.828125},{x:.921875,y:.828125},{x:.921875,y:.828125},{x:.953125,y:.828125},{x:.953125,y:.828125},{x:.984375,y:.828125},{x:.984375,y:.828125},{x:.015625,y:.859375},{x:.015625,y:.859375},{x:.046875,y:.859375},{x:.046875,y:.859375},{x:.078125,y:.859375},{x:.078125,y:.859375},{x:.109375,y:.859375},{x:.109375,y:.859375},{x:.140625,y:.859375},{x:.140625,y:.859375},{x:.171875,y:.859375},{x:.171875,y:.859375},{x:.203125,y:.859375},{x:.203125,y:.859375},{x:.234375,y:.859375},{x:.234375,y:.859375},{x:.265625,y:.859375},{x:.265625,y:.859375},{x:.296875,y:.859375},{x:.296875,y:.859375},{x:.328125,y:.859375},{x:.328125,y:.859375},{x:.359375,y:.859375},{x:.359375,y:.859375},{x:.390625,y:.859375},{x:.390625,y:.859375},{x:.421875,y:.859375},{x:.421875,y:.859375},{x:.453125,y:.859375},{x:.453125,y:.859375},{x:.484375,y:.859375},{x:.484375,y:.859375},{x:.515625,y:.859375},{x:.515625,y:.859375},{x:.546875,y:.859375},{x:.546875,y:.859375},{x:.578125,y:.859375},{x:.578125,y:.859375},{x:.609375,y:.859375},{x:.609375,y:.859375},{x:.640625,y:.859375},{x:.640625,y:.859375},{x:.671875,y:.859375},{x:.671875,y:.859375},{x:.703125,y:.859375},{x:.703125,y:.859375},{x:.734375,y:.859375},{x:.734375,y:.859375},{x:.765625,y:.859375},{x:.765625,y:.859375},{x:.796875,y:.859375},{x:.796875,y:.859375},{x:.828125,y:.859375},{x:.828125,y:.859375},{x:.859375,y:.859375},{x:.859375,y:.859375},{x:.890625,y:.859375},{x:.890625,y:.859375},{x:.921875,y:.859375},{x:.921875,y:.859375},{x:.953125,y:.859375},{x:.953125,y:.859375},{x:.984375,y:.859375},{x:.984375,y:.859375},{x:.015625,y:.890625},{x:.015625,y:.890625},{x:.046875,y:.890625},{x:.046875,y:.890625},{x:.078125,y:.890625},{x:.078125,y:.890625},{x:.109375,y:.890625},{x:.109375,y:.890625},{x:.140625,y:.890625},{x:.140625,y:.890625},{x:.171875,y:.890625},{x:.171875,y:.890625},{x:.203125,y:.890625},{x:.203125,y:.890625},{x:.234375,y:.890625},{x:.234375,y:.890625},{x:.265625,y:.890625},{x:.265625,y:.890625},{x:.296875,y:.890625},{x:.296875,y:.890625},{x:.328125,y:.890625},{x:.328125,y:.890625},{x:.359375,y:.890625},{x:.359375,y:.890625},{x:.390625,y:.890625},{x:.390625,y:.890625},{x:.421875,y:.890625},{x:.421875,y:.890625},{x:.453125,y:.890625},{x:.453125,y:.890625},{x:.484375,y:.890625},{x:.484375,y:.890625},{x:.515625,y:.890625},{x:.515625,y:.890625},{x:.546875,y:.890625},{x:.546875,y:.890625},{x:.578125,y:.890625},{x:.578125,y:.890625},{x:.609375,y:.890625},{x:.609375,y:.890625},{x:.640625,y:.890625},{x:.640625,y:.890625},{x:.671875,y:.890625},{x:.671875,y:.890625},{x:.703125,y:.890625},{x:.703125,y:.890625},{x:.734375,y:.890625},{x:.734375,y:.890625},{x:.765625,y:.890625},{x:.765625,y:.890625},{x:.796875,y:.890625},{x:.796875,y:.890625},{x:.828125,y:.890625},{x:.828125,y:.890625},{x:.859375,y:.890625},{x:.859375,y:.890625},{x:.890625,y:.890625},{x:.890625,y:.890625},{x:.921875,y:.890625},{x:.921875,y:.890625},{x:.953125,y:.890625},{x:.953125,y:.890625},{x:.984375,y:.890625},{x:.984375,y:.890625},{x:.015625,y:.921875},{x:.015625,y:.921875},{x:.046875,y:.921875},{x:.046875,y:.921875},{x:.078125,y:.921875},{x:.078125,y:.921875},{x:.109375,y:.921875},{x:.109375,y:.921875},{x:.140625,y:.921875},{x:.140625,y:.921875},{x:.171875,y:.921875},{x:.171875,y:.921875},{x:.203125,y:.921875},{x:.203125,y:.921875},{x:.234375,y:.921875},{x:.234375,y:.921875},{x:.265625,y:.921875},{x:.265625,y:.921875},{x:.296875,y:.921875},{x:.296875,y:.921875},{x:.328125,y:.921875},{x:.328125,y:.921875},{x:.359375,y:.921875},{x:.359375,y:.921875},{x:.390625,y:.921875},{x:.390625,y:.921875},{x:.421875,y:.921875},{x:.421875,y:.921875},{x:.453125,y:.921875},{x:.453125,y:.921875},{x:.484375,y:.921875},{x:.484375,y:.921875},{x:.515625,y:.921875},{x:.515625,y:.921875},{x:.546875,y:.921875},{x:.546875,y:.921875},{x:.578125,y:.921875},{x:.578125,y:.921875},{x:.609375,y:.921875},{x:.609375,y:.921875},{x:.640625,y:.921875},{x:.640625,y:.921875},{x:.671875,y:.921875},{x:.671875,y:.921875},{x:.703125,y:.921875},{x:.703125,y:.921875},{x:.734375,y:.921875},{x:.734375,y:.921875},{x:.765625,y:.921875},{x:.765625,y:.921875},{x:.796875,y:.921875},{x:.796875,y:.921875},{x:.828125,y:.921875},{x:.828125,y:.921875},{x:.859375,y:.921875},{x:.859375,y:.921875},{x:.890625,y:.921875},{x:.890625,y:.921875},{x:.921875,y:.921875},{x:.921875,y:.921875},{x:.953125,y:.921875},{x:.953125,y:.921875},{x:.984375,y:.921875},{x:.984375,y:.921875},{x:.015625,y:.953125},{x:.015625,y:.953125},{x:.046875,y:.953125},{x:.046875,y:.953125},{x:.078125,y:.953125},{x:.078125,y:.953125},{x:.109375,y:.953125},{x:.109375,y:.953125},{x:.140625,y:.953125},{x:.140625,y:.953125},{x:.171875,y:.953125},{x:.171875,y:.953125},{x:.203125,y:.953125},{x:.203125,y:.953125},{x:.234375,y:.953125},{x:.234375,y:.953125},{x:.265625,y:.953125},{x:.265625,y:.953125},{x:.296875,y:.953125},{x:.296875,y:.953125},{x:.328125,y:.953125},{x:.328125,y:.953125},{x:.359375,y:.953125},{x:.359375,y:.953125},{x:.390625,y:.953125},{x:.390625,y:.953125},{x:.421875,y:.953125},{x:.421875,y:.953125},{x:.453125,y:.953125},{x:.453125,y:.953125},{x:.484375,y:.953125},{x:.484375,y:.953125},{x:.515625,y:.953125},{x:.515625,y:.953125},{x:.546875,y:.953125},{x:.546875,y:.953125},{x:.578125,y:.953125},{x:.578125,y:.953125},{x:.609375,y:.953125},{x:.609375,y:.953125},{x:.640625,y:.953125},{x:.640625,y:.953125},{x:.671875,y:.953125},{x:.671875,y:.953125},{x:.703125,y:.953125},{x:.703125,y:.953125},{x:.734375,y:.953125},{x:.734375,y:.953125},{x:.765625,y:.953125},{x:.765625,y:.953125},{x:.796875,y:.953125},{x:.796875,y:.953125},{x:.828125,y:.953125},{x:.828125,y:.953125},{x:.859375,y:.953125},{x:.859375,y:.953125},{x:.890625,y:.953125},{x:.890625,y:.953125},{x:.921875,y:.953125},{x:.921875,y:.953125},{x:.953125,y:.953125},{x:.953125,y:.953125},{x:.984375,y:.953125},{x:.984375,y:.953125},{x:.015625,y:.984375},{x:.015625,y:.984375},{x:.046875,y:.984375},{x:.046875,y:.984375},{x:.078125,y:.984375},{x:.078125,y:.984375},{x:.109375,y:.984375},{x:.109375,y:.984375},{x:.140625,y:.984375},{x:.140625,y:.984375},{x:.171875,y:.984375},{x:.171875,y:.984375},{x:.203125,y:.984375},{x:.203125,y:.984375},{x:.234375,y:.984375},{x:.234375,y:.984375},{x:.265625,y:.984375},{x:.265625,y:.984375},{x:.296875,y:.984375},{x:.296875,y:.984375},{x:.328125,y:.984375},{x:.328125,y:.984375},{x:.359375,y:.984375},{x:.359375,y:.984375},{x:.390625,y:.984375},{x:.390625,y:.984375},{x:.421875,y:.984375},{x:.421875,y:.984375},{x:.453125,y:.984375},{x:.453125,y:.984375},{x:.484375,y:.984375},{x:.484375,y:.984375},{x:.515625,y:.984375},{x:.515625,y:.984375},{x:.546875,y:.984375},{x:.546875,y:.984375},{x:.578125,y:.984375},{x:.578125,y:.984375},{x:.609375,y:.984375},{x:.609375,y:.984375},{x:.640625,y:.984375},{x:.640625,y:.984375},{x:.671875,y:.984375},{x:.671875,y:.984375},{x:.703125,y:.984375},{x:.703125,y:.984375},{x:.734375,y:.984375},{x:.734375,y:.984375},{x:.765625,y:.984375},{x:.765625,y:.984375},{x:.796875,y:.984375},{x:.796875,y:.984375},{x:.828125,y:.984375},{x:.828125,y:.984375},{x:.859375,y:.984375},{x:.859375,y:.984375},{x:.890625,y:.984375},{x:.890625,y:.984375},{x:.921875,y:.984375},{x:.921875,y:.984375},{x:.953125,y:.984375},{x:.953125,y:.984375},{x:.984375,y:.984375},{x:.984375,y:.984375},{x:.03125,y:.03125},{x:.03125,y:.03125},{x:.09375,y:.03125},{x:.09375,y:.03125},{x:.15625,y:.03125},{x:.15625,y:.03125},{x:.21875,y:.03125},{x:.21875,y:.03125},{x:.28125,y:.03125},{x:.28125,y:.03125},{x:.34375,y:.03125},{x:.34375,y:.03125},{x:.40625,y:.03125},{x:.40625,y:.03125},{x:.46875,y:.03125},{x:.46875,y:.03125},{x:.53125,y:.03125},{x:.53125,y:.03125},{x:.59375,y:.03125},{x:.59375,y:.03125},{x:.65625,y:.03125},{x:.65625,y:.03125},{x:.71875,y:.03125},{x:.71875,y:.03125},{x:.78125,y:.03125},{x:.78125,y:.03125},{x:.84375,y:.03125},{x:.84375,y:.03125},{x:.90625,y:.03125},{x:.90625,y:.03125},{x:.96875,y:.03125},{x:.96875,y:.03125},{x:.03125,y:.09375},{x:.03125,y:.09375},{x:.09375,y:.09375},{x:.09375,y:.09375},{x:.15625,y:.09375},{x:.15625,y:.09375},{x:.21875,y:.09375},{x:.21875,y:.09375},{x:.28125,y:.09375},{x:.28125,y:.09375},{x:.34375,y:.09375},{x:.34375,y:.09375},{x:.40625,y:.09375},{x:.40625,y:.09375},{x:.46875,y:.09375},{x:.46875,y:.09375},{x:.53125,y:.09375},{x:.53125,y:.09375},{x:.59375,y:.09375},{x:.59375,y:.09375},{x:.65625,y:.09375},{x:.65625,y:.09375},{x:.71875,y:.09375},{x:.71875,y:.09375},{x:.78125,y:.09375},{x:.78125,y:.09375},{x:.84375,y:.09375},{x:.84375,y:.09375},{x:.90625,y:.09375},{x:.90625,y:.09375},{x:.96875,y:.09375},{x:.96875,y:.09375},{x:.03125,y:.15625},{x:.03125,y:.15625},{x:.09375,y:.15625},{x:.09375,y:.15625},{x:.15625,y:.15625},{x:.15625,y:.15625},{x:.21875,y:.15625},{x:.21875,y:.15625},{x:.28125,y:.15625},{x:.28125,y:.15625},{x:.34375,y:.15625},{x:.34375,y:.15625},{x:.40625,y:.15625},{x:.40625,y:.15625},{x:.46875,y:.15625},{x:.46875,y:.15625},{x:.53125,y:.15625},{x:.53125,y:.15625},{x:.59375,y:.15625},{x:.59375,y:.15625},{x:.65625,y:.15625},{x:.65625,y:.15625},{x:.71875,y:.15625},{x:.71875,y:.15625},{x:.78125,y:.15625},{x:.78125,y:.15625},{x:.84375,y:.15625},{x:.84375,y:.15625},{x:.90625,y:.15625},{x:.90625,y:.15625},{x:.96875,y:.15625},{x:.96875,y:.15625},{x:.03125,y:.21875},{x:.03125,y:.21875},{x:.09375,y:.21875},{x:.09375,y:.21875},{x:.15625,y:.21875},{x:.15625,y:.21875},{x:.21875,y:.21875},{x:.21875,y:.21875},{x:.28125,y:.21875},{x:.28125,y:.21875},{x:.34375,y:.21875},{x:.34375,y:.21875},{x:.40625,y:.21875},{x:.40625,y:.21875},{x:.46875,y:.21875},{x:.46875,y:.21875},{x:.53125,y:.21875},{x:.53125,y:.21875},{x:.59375,y:.21875},{x:.59375,y:.21875},{x:.65625,y:.21875},{x:.65625,y:.21875},{x:.71875,y:.21875},{x:.71875,y:.21875},{x:.78125,y:.21875},{x:.78125,y:.21875},{x:.84375,y:.21875},{x:.84375,y:.21875},{x:.90625,y:.21875},{x:.90625,y:.21875},{x:.96875,y:.21875},{x:.96875,y:.21875},{x:.03125,y:.28125},{x:.03125,y:.28125},{x:.09375,y:.28125},{x:.09375,y:.28125},{x:.15625,y:.28125},{x:.15625,y:.28125},{x:.21875,y:.28125},{x:.21875,y:.28125},{x:.28125,y:.28125},{x:.28125,y:.28125},{x:.34375,y:.28125},{x:.34375,y:.28125},{x:.40625,y:.28125},{x:.40625,y:.28125},{x:.46875,y:.28125},{x:.46875,y:.28125},{x:.53125,y:.28125},{x:.53125,y:.28125},{x:.59375,y:.28125},{x:.59375,y:.28125},{x:.65625,y:.28125},{x:.65625,y:.28125},{x:.71875,y:.28125},{x:.71875,y:.28125},{x:.78125,y:.28125},{x:.78125,y:.28125},{x:.84375,y:.28125},{x:.84375,y:.28125},{x:.90625,y:.28125},{x:.90625,y:.28125},{x:.96875,y:.28125},{x:.96875,y:.28125},{x:.03125,y:.34375},{x:.03125,y:.34375},{x:.09375,y:.34375},{x:.09375,y:.34375},{x:.15625,y:.34375},{x:.15625,y:.34375},{x:.21875,y:.34375},{x:.21875,y:.34375},{x:.28125,y:.34375},{x:.28125,y:.34375},{x:.34375,y:.34375},{x:.34375,y:.34375},{x:.40625,y:.34375},{x:.40625,y:.34375},{x:.46875,y:.34375},{x:.46875,y:.34375},{x:.53125,y:.34375},{x:.53125,y:.34375},{x:.59375,y:.34375},{x:.59375,y:.34375},{x:.65625,y:.34375},{x:.65625,y:.34375},{x:.71875,y:.34375},{x:.71875,y:.34375},{x:.78125,y:.34375},{x:.78125,y:.34375},{x:.84375,y:.34375},{x:.84375,y:.34375},{x:.90625,y:.34375},{x:.90625,y:.34375},{x:.96875,y:.34375},{x:.96875,y:.34375},{x:.03125,y:.40625},{x:.03125,y:.40625},{x:.09375,y:.40625},{x:.09375,y:.40625},{x:.15625,y:.40625},{x:.15625,y:.40625},{x:.21875,y:.40625},{x:.21875,y:.40625},{x:.28125,y:.40625},{x:.28125,y:.40625},{x:.34375,y:.40625},{x:.34375,y:.40625},{x:.40625,y:.40625},{x:.40625,y:.40625},{x:.46875,y:.40625},{x:.46875,y:.40625},{x:.53125,y:.40625},{x:.53125,y:.40625},{x:.59375,y:.40625},{x:.59375,y:.40625},{x:.65625,y:.40625},{x:.65625,y:.40625},{x:.71875,y:.40625},{x:.71875,y:.40625},{x:.78125,y:.40625},{x:.78125,y:.40625},{x:.84375,y:.40625},{x:.84375,y:.40625},{x:.90625,y:.40625},{x:.90625,y:.40625},{x:.96875,y:.40625},{x:.96875,y:.40625},{x:.03125,y:.46875},{x:.03125,y:.46875},{x:.09375,y:.46875},{x:.09375,y:.46875},{x:.15625,y:.46875},{x:.15625,y:.46875},{x:.21875,y:.46875},{x:.21875,y:.46875},{x:.28125,y:.46875},{x:.28125,y:.46875},{x:.34375,y:.46875},{x:.34375,y:.46875},{x:.40625,y:.46875},{x:.40625,y:.46875},{x:.46875,y:.46875},{x:.46875,y:.46875},{x:.53125,y:.46875},{x:.53125,y:.46875},{x:.59375,y:.46875},{x:.59375,y:.46875},{x:.65625,y:.46875},{x:.65625,y:.46875},{x:.71875,y:.46875},{x:.71875,y:.46875},{x:.78125,y:.46875},{x:.78125,y:.46875},{x:.84375,y:.46875},{x:.84375,y:.46875},{x:.90625,y:.46875},{x:.90625,y:.46875},{x:.96875,y:.46875},{x:.96875,y:.46875},{x:.03125,y:.53125},{x:.03125,y:.53125},{x:.09375,y:.53125},{x:.09375,y:.53125},{x:.15625,y:.53125},{x:.15625,y:.53125},{x:.21875,y:.53125},{x:.21875,y:.53125},{x:.28125,y:.53125},{x:.28125,y:.53125},{x:.34375,y:.53125},{x:.34375,y:.53125},{x:.40625,y:.53125},{x:.40625,y:.53125},{x:.46875,y:.53125},{x:.46875,y:.53125},{x:.53125,y:.53125},{x:.53125,y:.53125},{x:.59375,y:.53125},{x:.59375,y:.53125},{x:.65625,y:.53125},{x:.65625,y:.53125},{x:.71875,y:.53125},{x:.71875,y:.53125},{x:.78125,y:.53125},{x:.78125,y:.53125},{x:.84375,y:.53125},{x:.84375,y:.53125},{x:.90625,y:.53125},{x:.90625,y:.53125},{x:.96875,y:.53125},{x:.96875,y:.53125},{x:.03125,y:.59375},{x:.03125,y:.59375},{x:.09375,y:.59375},{x:.09375,y:.59375},{x:.15625,y:.59375},{x:.15625,y:.59375},{x:.21875,y:.59375},{x:.21875,y:.59375},{x:.28125,y:.59375},{x:.28125,y:.59375},{x:.34375,y:.59375},{x:.34375,y:.59375},{x:.40625,y:.59375},{x:.40625,y:.59375},{x:.46875,y:.59375},{x:.46875,y:.59375},{x:.53125,y:.59375},{x:.53125,y:.59375},{x:.59375,y:.59375},{x:.59375,y:.59375},{x:.65625,y:.59375},{x:.65625,y:.59375},{x:.71875,y:.59375},{x:.71875,y:.59375},{x:.78125,y:.59375},{x:.78125,y:.59375},{x:.84375,y:.59375},{x:.84375,y:.59375},{x:.90625,y:.59375},{x:.90625,y:.59375},{x:.96875,y:.59375},{x:.96875,y:.59375},{x:.03125,y:.65625},{x:.03125,y:.65625},{x:.09375,y:.65625},{x:.09375,y:.65625},{x:.15625,y:.65625},{x:.15625,y:.65625},{x:.21875,y:.65625},{x:.21875,y:.65625},{x:.28125,y:.65625},{x:.28125,y:.65625},{x:.34375,y:.65625},{x:.34375,y:.65625},{x:.40625,y:.65625},{x:.40625,y:.65625},{x:.46875,y:.65625},{x:.46875,y:.65625},{x:.53125,y:.65625},{x:.53125,y:.65625},{x:.59375,y:.65625},{x:.59375,y:.65625},{x:.65625,y:.65625},{x:.65625,y:.65625},{x:.71875,y:.65625},{x:.71875,y:.65625},{x:.78125,y:.65625},{x:.78125,y:.65625},{x:.84375,y:.65625},{x:.84375,y:.65625},{x:.90625,y:.65625},{x:.90625,y:.65625},{x:.96875,y:.65625},{x:.96875,y:.65625},{x:.03125,y:.71875},{x:.03125,y:.71875},{x:.09375,y:.71875},{x:.09375,y:.71875},{x:.15625,y:.71875},{x:.15625,y:.71875},{x:.21875,y:.71875},{x:.21875,y:.71875},{x:.28125,y:.71875},{x:.28125,y:.71875},{x:.34375,y:.71875},{x:.34375,y:.71875},{x:.40625,y:.71875},{x:.40625,y:.71875},{x:.46875,y:.71875},{x:.46875,y:.71875},{x:.53125,y:.71875},{x:.53125,y:.71875},{x:.59375,y:.71875},{x:.59375,y:.71875},{x:.65625,y:.71875},{x:.65625,y:.71875},{x:.71875,y:.71875},{x:.71875,y:.71875},{x:.78125,y:.71875},{x:.78125,y:.71875},{x:.84375,y:.71875},{x:.84375,y:.71875},{x:.90625,y:.71875},{x:.90625,y:.71875},{x:.96875,y:.71875},{x:.96875,y:.71875},{x:.03125,y:.78125},{x:.03125,y:.78125},{x:.09375,y:.78125},{x:.09375,y:.78125},{x:.15625,y:.78125},{x:.15625,y:.78125},{x:.21875,y:.78125},{x:.21875,y:.78125},{x:.28125,y:.78125},{x:.28125,y:.78125},{x:.34375,y:.78125},{x:.34375,y:.78125},{x:.40625,y:.78125},{x:.40625,y:.78125},{x:.46875,y:.78125},{x:.46875,y:.78125},{x:.53125,y:.78125},{x:.53125,y:.78125},{x:.59375,y:.78125},{x:.59375,y:.78125},{x:.65625,y:.78125},{x:.65625,y:.78125},{x:.71875,y:.78125},{x:.71875,y:.78125},{x:.78125,y:.78125},{x:.78125,y:.78125},{x:.84375,y:.78125},{x:.84375,y:.78125},{x:.90625,y:.78125},{x:.90625,y:.78125},{x:.96875,y:.78125},{x:.96875,y:.78125},{x:.03125,y:.84375},{x:.03125,y:.84375},{x:.09375,y:.84375},{x:.09375,y:.84375},{x:.15625,y:.84375},{x:.15625,y:.84375},{x:.21875,y:.84375},{x:.21875,y:.84375},{x:.28125,y:.84375},{x:.28125,y:.84375},{x:.34375,y:.84375},{x:.34375,y:.84375},{x:.40625,y:.84375},{x:.40625,y:.84375},{x:.46875,y:.84375},{x:.46875,y:.84375},{x:.53125,y:.84375},{x:.53125,y:.84375},{x:.59375,y:.84375},{x:.59375,y:.84375},{x:.65625,y:.84375},{x:.65625,y:.84375},{x:.71875,y:.84375},{x:.71875,y:.84375},{x:.78125,y:.84375},{x:.78125,y:.84375},{x:.84375,y:.84375},{x:.84375,y:.84375},{x:.90625,y:.84375},{x:.90625,y:.84375},{x:.96875,y:.84375},{x:.96875,y:.84375},{x:.03125,y:.90625},{x:.03125,y:.90625},{x:.09375,y:.90625},{x:.09375,y:.90625},{x:.15625,y:.90625},{x:.15625,y:.90625},{x:.21875,y:.90625},{x:.21875,y:.90625},{x:.28125,y:.90625},{x:.28125,y:.90625},{x:.34375,y:.90625},{x:.34375,y:.90625},{x:.40625,y:.90625},{x:.40625,y:.90625},{x:.46875,y:.90625},{x:.46875,y:.90625},{x:.53125,y:.90625},{x:.53125,y:.90625},{x:.59375,y:.90625},{x:.59375,y:.90625},{x:.65625,y:.90625},{x:.65625,y:.90625},{x:.71875,y:.90625},{x:.71875,y:.90625},{x:.78125,y:.90625},{x:.78125,y:.90625},{x:.84375,y:.90625},{x:.84375,y:.90625},{x:.90625,y:.90625},{x:.90625,y:.90625},{x:.96875,y:.90625},{x:.96875,y:.90625},{x:.03125,y:.96875},{x:.03125,y:.96875},{x:.09375,y:.96875},{x:.09375,y:.96875},{x:.15625,y:.96875},{x:.15625,y:.96875},{x:.21875,y:.96875},{x:.21875,y:.96875},{x:.28125,y:.96875},{x:.28125,y:.96875},{x:.34375,y:.96875},{x:.34375,y:.96875},{x:.40625,y:.96875},{x:.40625,y:.96875},{x:.46875,y:.96875},{x:.46875,y:.96875},{x:.53125,y:.96875},{x:.53125,y:.96875},{x:.59375,y:.96875},{x:.59375,y:.96875},{x:.65625,y:.96875},{x:.65625,y:.96875},{x:.71875,y:.96875},{x:.71875,y:.96875},{x:.78125,y:.96875},{x:.78125,y:.96875},{x:.84375,y:.96875},{x:.84375,y:.96875},{x:.90625,y:.96875},{x:.90625,y:.96875},{x:.96875,y:.96875},{x:.96875,y:.96875},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375}];var i5=class{constructor(t){T(this,"model");T(this,"anchors");T(this,"anchorsTensor");T(this,"inputSize");T(this,"inputSizeTensor");T(this,"doubleInputSizeTensor");this.model=t,this.anchors=eo.map(o=>[o.x,o.y]),this.anchorsTensor=W.tensor2d(this.anchors),this.inputSize=this.model&&this.model.inputs&&this.model.inputs[0].shape?this.model.inputs[0].shape[2]:0,this.inputSizeTensor=W.tensor1d([this.inputSize,this.inputSize]),this.doubleInputSizeTensor=W.tensor1d([this.inputSize*2,this.inputSize*2])}normalizeBoxes(t){let o={};o.boxOffsets=W.slice(t,[0,0],[-1,2]),o.boxSizes=W.slice(t,[0,2],[-1,2]),o.div=W.div(o.boxOffsets,this.inputSizeTensor),o.boxCenterPoints=W.add(o.div,this.anchorsTensor),o.halfBoxSizes=W.div(o.boxSizes,this.doubleInputSizeTensor),o.sub=W.sub(o.boxCenterPoints,o.halfBoxSizes),o.startPoints=W.mul(o.sub,this.inputSizeTensor),o.add=W.add(o.boxCenterPoints,o.halfBoxSizes),o.endPoints=W.mul(o.add,this.inputSizeTensor);let n=W.concat2d([o.startPoints,o.endPoints],1);return Object.keys(o).forEach(r=>W.dispose(o[r])),n}normalizeLandmarks(t,o){let n={};n.reshape=W.reshape(t,[-1,7,2]),n.div=W.div(n.reshape,this.inputSizeTensor),n.landmarks=W.add(n.div,this.anchors[o]);let r=W.mul(n.landmarks,this.inputSizeTensor);return Object.keys(n).forEach(A=>W.dispose(n[A])),r}async predict(t,o){let n={};n.resize=W.image.resizeBilinear(t,[this.inputSize,this.inputSize]),n.div=W.div(n.resize,V.tf127),n.image=W.sub(n.div,V.tf1),n.batched=this.model.execute(n.image),n.predictions=W.squeeze(n.batched),n.slice=W.slice(n.predictions,[0,0],[-1,1]),n.sigmoid=W.sigmoid(n.slice),n.scores=W.squeeze(n.sigmoid);let r=await n.scores.data();n.boxes=W.slice(n.predictions,[0,1],[-1,4]),n.norm=this.normalizeBoxes(n.boxes),n.nms=await W.image.nonMaxSuppressionAsync(n.norm,n.scores,3*o.hand.maxDetected,o.hand.iouThreshold,o.hand.minConfidence);let A=await n.nms.array(),s=[];for(let a of A){let i={};i.box=W.slice(n.norm,[a,0],[1,-1]),i.slice=W.slice(n.predictions,[a,5],[1,14]),i.norm=this.normalizeLandmarks(i.slice,a),i.palmLandmarks=W.reshape(i.norm,[-1,2]);let x=await i.box.data(),c=x.slice(0,2),l=x.slice(2,4),y=await i.palmLandmarks.array(),f={startPoint:c,endPoint:l,palmLandmarks:y,confidence:r[a]},u=J3(f,[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]);s.push(u),Object.keys(i).forEach(m=>W.dispose(i[m]))}return Object.keys(n).forEach(a=>W.dispose(n[a])),s}};var L0=Z(D());var yA=5,to=1.65,oo=[0,5,9,13,17,1,2],xA=0,cA=2,no=0,l5=class{constructor(t,o){T(this,"handDetector");T(this,"handPoseModel");T(this,"inputSize");T(this,"storedBoxes");T(this,"skipped");T(this,"detectedHands");this.handDetector=t,this.handPoseModel=o,this.inputSize=this.handPoseModel&&this.handPoseModel.inputs[0].shape?this.handPoseModel.inputs[0].shape[2]:0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let o=t.map(s=>s[0]),n=t.map(s=>s[1]),r=[Math.min(...o),Math.min(...n)],A=[Math.max(...o),Math.max(...n)];return{startPoint:r,endPoint:A}}getBoxForPalmLandmarks(t,o){let n=t.map(A=>P1([...A,1],o)),r=this.calculateLandmarksBoundingBox(n);return s5(a5(r),yA)}getBoxForHandLandmarks(t){let o=this.calculateLandmarksBoundingBox(t),n=s5(a5(o),to);n.palmLandmarks=[];for(let r=0;r<oo.length;r++)n.palmLandmarks.push(t[oo[r]].slice(0,2));return n}transformRawCoords(t,o,n,r){let A=A5(o),s=[A[0]/this.inputSize,A[1]/this.inputSize,(A[0]+A[1])/this.inputSize/2],a=t.map(f=>[s[0]*(f[0]-this.inputSize/2),s[1]*(f[1]-this.inputSize/2),s[2]*f[2]]),i=M1(n,[0,0]),x=a.map(f=>[...P1(f,i),f[2]]),c=_3(r),l=[...k2(o),1],y=[Te(l,c[0]),Te(l,c[1])];return x.map(f=>[Math.trunc(f[0]+y[0]),Math.trunc(f[1]+y[1]),Math.trunc(f[2])])}async estimateHands(t,o){let n=!1,r,A=(o.hand.skipTime||0)>h()-no,s=this.skipped<(o.hand.skipFrames||0);o.skipAllowed&&A&&s&&(r=await this.handDetector.predict(t,o),this.skipped=0),o.skipAllowed&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==o.hand.maxDetected||!o.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(n=!0));let a=[];for(let i=0;i<this.storedBoxes.length;i++){let x=this.storedBoxes[i];if(!!x)if(o.hand.landmarks){let c=o.hand.rotation?Q3(x.palmLandmarks[xA],x.palmLandmarks[cA]):0,l=k2(x),y=[l[0]/t.shape[2],l[1]/t.shape[1]],f=o.hand.rotation&&v.kernels.includes("rotatewithoffset")?L0.image.rotateWithOffset(t,c,0,y):t.clone(),u=M1(-c,l),m=n?this.getBoxForPalmLandmarks(x.palmLandmarks,u):x,P=K3(m,f,[this.inputSize,this.inputSize]),g=L0.div(P,V.tf255);L0.dispose(P),L0.dispose(f);let[b,d]=this.handPoseModel.execute(g);no=h(),L0.dispose(g);let M=(await b.data())[0];if(L0.dispose(b),M>=o.hand.minConfidence/4){let S=L0.reshape(d,[-1,3]),w=await S.array();L0.dispose(d),L0.dispose(S);let j=this.transformRawCoords(w,m,c,u),C=this.getBoxForHandLandmarks(j);this.storedBoxes[i]={...C,confidence:M};let F={landmarks:j,confidence:M,boxConfidence:x.confidence,fingerConfidence:M,box:{topLeft:C.startPoint,bottomRight:C.endPoint}};a.push(F)}else this.storedBoxes[i]=null;L0.dispose(d)}else{let c=s5(a5(x),to),l={confidence:x.confidence,boxConfidence:x.confidence,fingerConfidence:0,box:{topLeft:c.startPoint,bottomRight:c.endPoint},landmarks:[]};a.push(l)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=a.length,a.length>o.hand.maxDetected&&(a.length=o.hand.maxDetected),a}};var k0={thumb:0,index:1,middle:2,ring:3,pinky:4,all:[0,1,2,3,4],nameMapping:{0:"thumb",1:"index",2:"middle",3:"ring",4:"pinky"},pointsMapping:{0:[[0,1],[1,2],[2,3],[3,4]],1:[[0,5],[5,6],[6,7],[7,8]],2:[[0,9],[9,10],[10,11],[11,12]],3:[[0,13],[13,14],[14,15],[15,16]],4:[[0,17],[17,18],[18,19],[19,20]]},getName:e=>k0.nameMapping[e],getPoints:e=>k0.pointsMapping[e]},ke={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>ke.nameMapping[e]},o0={verticalUp:0,verticalDown:1,horizontalLeft:2,horizontalRight:3,diagonalUpRight:4,diagonalUpLeft:5,diagonalDownRight:6,diagonalDownLeft:7,nameMapping:{0:"verticalUp",1:"verticalDown",2:"horizontalLeft",3:"horizontalRight",4:"diagonalUpRight",5:"diagonalUpLeft",6:"diagonalDownRight",7:"diagonalDownLeft"},getName:e=>o0.nameMapping[e]},we=class{constructor(t){T(this,"name");T(this,"curls");T(this,"directions");T(this,"weights");T(this,"weightsRelative");this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}curl(t,o,n){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([o,n])}direction(t,o,n){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([o,n])}weight(t,o){this.weights[t]=o;let n=this.weights.reduce((r,A)=>r+A,0);this.weightsRelative=this.weights.map(r=>r*5/n)}matchAgainst(t,o){let n=0;for(let r in t){let A=t[r],s=this.curls[r];if(typeof s=="undefined"){n+=this.weightsRelative[r];continue}for(let[a,i]of s)if(A===a){n+=i*this.weightsRelative[r];break}}for(let r in o){let A=o[r],s=this.directions[r];if(typeof s=="undefined"){n+=this.weightsRelative[r];continue}for(let[a,i]of s)if(A===a){n+=i*this.weightsRelative[r];break}}return n/10}};var{thumb:J0,index:ce,middle:de,ring:He,pinky:Ve}=k0,{none:Q0,half:fA,full:_0}=ke,{verticalUp:o2,verticalDown:z4,horizontalLeft:R1,horizontalRight:mA,diagonalUpRight:pA,diagonalUpLeft:n2,diagonalDownRight:S4,diagonalDownLeft:C4}=o0,Ee=new we("thumbs up");Ee.curl(J0,Q0,1);Ee.direction(J0,o2,1);Ee.direction(J0,n2,.25);Ee.direction(J0,pA,.25);for(let e of[k0.index,k0.middle,k0.ring,k0.pinky])Ee.curl(e,_0,1),Ee.direction(e,R1,1),Ee.direction(e,mA,1);var y0=new we("victory");y0.curl(J0,fA,.5);y0.curl(J0,Q0,.5);y0.direction(J0,o2,1);y0.direction(J0,n2,1);y0.curl(ce,Q0,1);y0.direction(ce,o2,.75);y0.direction(ce,n2,1);y0.curl(de,Q0,1);y0.direction(de,o2,1);y0.direction(de,n2,.75);y0.curl(He,_0,1);y0.direction(He,o2,.2);y0.direction(He,n2,1);y0.direction(He,R1,.2);y0.curl(Ve,_0,1);y0.direction(Ve,o2,.2);y0.direction(Ve,n2,1);y0.direction(Ve,R1,.2);y0.weight(ce,2);y0.weight(de,2);var ze=new we("point");ze.curl(J0,_0,1);ze.curl(ce,Q0,.5);ze.curl(de,_0,.5);ze.curl(He,_0,.5);ze.curl(Ve,_0,.5);ze.weight(ce,2);ze.weight(de,2);var Se=new we("middle finger");Se.curl(J0,Q0,1);Se.curl(ce,_0,.5);Se.curl(de,_0,.5);Se.curl(He,_0,.5);Se.curl(Ve,_0,.5);Se.weight(ce,2);Se.weight(de,2);var r2=new we("open palm");r2.curl(J0,Q0,.75);r2.curl(ce,Q0,.75);r2.curl(de,Q0,.75);r2.curl(He,Q0,.75);r2.curl(Ve,Q0,.75);var ro=[Ee,y0,ze,Se,r2];var uA=.7,De={HALF_CURL_START_LIMIT:60,NO_CURL_START_LIMIT:130,DISTANCE_VOTE_POWER:1.1,SINGLE_ANGLE_VOTE_POWER:.9,TOTAL_ANGLE_VOTE_POWER:1.6};function Ao(e,t,o,n){let r=(t-n)/(e-o),A=Math.atan(r)*180/Math.PI;return A<=0?A=-A:A>0&&(A=180-A),A}function ao(e,t){if(!e||!t)return[0,0];let o=Ao(e[0],e[1],t[0],t[1]);if(e.length===2)return o;let n=Ao(e[1],e[2],t[1],t[2]);return[o,n]}function so(e,t=1){let o=0,n=0,r=0;return e>=75&&e<=105?o=1*t:e>=25&&e<=155?n=1*t:r=1*t,[o,n,r]}function hA(e,t,o){let n=e[0]-t[0],r=e[0]-o[0],A=t[0]-o[0],s=e[1]-t[1],a=e[1]-o[1],i=t[1]-o[1],x=e[2]-t[2],c=e[2]-o[2],l=t[2]-o[2],y=Math.sqrt(n*n+s*s+x*x),f=Math.sqrt(r*r+a*a+c*c),u=Math.sqrt(A*A+i*i+l*l),m=(u*u+y*y-f*f)/(2*u*y);m>1?m=1:m<-1&&(m=-1);let P=Math.acos(m);P=57.2958*P%180;let g;return P>De.NO_CURL_START_LIMIT?g=ke.none:P>De.HALF_CURL_START_LIMIT?g=ke.half:g=ke.full,g}function io(e,t,o,n){let r;return n===Math.abs(e)?e>0?r=o0.horizontalLeft:r=o0.horizontalRight:n===Math.abs(t)?t>0?r=o0.horizontalLeft:r=o0.horizontalRight:o>0?r=o0.horizontalLeft:r=o0.horizontalRight,r}function lo(e,t,o,n){let r;return n===Math.abs(e)?e<0?r=o0.verticalDown:r=o0.verticalUp:n===Math.abs(t)?t<0?r=o0.verticalDown:r=o0.verticalUp:o<0?r=o0.verticalDown:r=o0.verticalUp,r}function bA(e,t,o,n,r,A,s,a){let i,x=lo(e,t,o,n),c=io(r,A,s,a);return x===o0.verticalUp?c===o0.horizontalLeft?i=o0.diagonalUpLeft:i=o0.diagonalUpRight:c===o0.horizontalLeft?i=o0.diagonalDownLeft:i=o0.diagonalDownRight,i}function gA(e,t,o,n){let r=e[0]-t[0],A=e[0]-o[0],s=t[0]-o[0],a=e[1]-t[1],i=e[1]-o[1],x=t[1]-o[1],c=Math.max(Math.abs(r),Math.abs(A),Math.abs(s)),l=Math.max(Math.abs(a),Math.abs(i),Math.abs(x)),y=0,f=0,u=0,m=l/(c+1e-5);m>1.5?y+=De.DISTANCE_VOTE_POWER:m>.66?f+=De.DISTANCE_VOTE_POWER:u+=De.DISTANCE_VOTE_POWER;let P=Math.sqrt(r*r+a*a),g=Math.sqrt(A*A+i*i),b=Math.sqrt(s*s+x*x),d=Math.max(P,g,b),M=e[0],S=e[1],w=o[0],j=o[1];d===P?(w=o[0],j=o[1]):d===b&&(M=t[0],S=t[1]);let H=ao([M,S],[w,j]),Y=so(H,De.TOTAL_ANGLE_VOTE_POWER);y+=Y[0],f+=Y[1],u+=Y[2];for(let x0 of n){let E=so(x0,De.SINGLE_ANGLE_VOTE_POWER);y+=E[0],f+=E[1],u+=E[2]}let J;return y===Math.max(y,f,u)?J=lo(i,a,x,l):u===Math.max(f,u)?J=io(A,r,s,c):J=bA(i,a,x,l,A,r,s,c),J}function yo(e){let t=[],o=[],n=[],r=[];if(!e)return{curls:n,directions:r};for(let A of k0.all){let s=k0.getPoints(A),a=[],i=[];for(let x of s){let c=e[x[0]],l=e[x[1]],y=ao(c,l),f=y[0],u=y[1];a.push(f),i.push(u)}t.push(a),o.push(i)}for(let A of k0.all){let s=A===k0.thumb?1:0,a=k0.getPoints(A),i=e[a[s][0]],x=e[a[s+1][1]],c=e[a[3][1]],l=hA(i,x,c),y=gA(i,x,c,t[A].slice(s));n[A]=l,r[A]=y}return{curls:n,directions:r}}function y5(e){if(!e||e.length===0)return null;let t=yo(e),o={};for(let n of k0.all)o[k0.getName(n)]={curl:ke.getName(t.curls[n]),direction:o0.getName(t.directions[n])};return o}function xo(e){let t=[];if(!e||e.length===0)return t;let o=yo(e);for(let n of ro){let r=n.matchAgainst(o.curls,o.directions);r>=uA&&t.push({name:n.name,confidence:r})}return t}var co={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],palm:[0]},A2,s2,fo;async function T1(e,t){let o=await fo.estimateHands(e,t);if(!o)return[];let n=[];for(let r=0;r<o.length;r++){let A={};if(o[r].landmarks)for(let c of Object.keys(co))A[c]=co[c].map(l=>o[r].landmarks[l]);let s=o[r].landmarks,a=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],i=[0,0,0,0];if(s&&s.length>0){for(let c of s)c[0]<a[0]&&(a[0]=c[0]),c[1]<a[1]&&(a[1]=c[1]),c[0]>a[2]&&(a[2]=c[0]),c[1]>a[3]&&(a[3]=c[1]);a[2]-=a[0],a[3]-=a[1],i=[a[0]/(e.shape[2]||0),a[1]/(e.shape[1]||0),a[2]/(e.shape[2]||0),a[3]/(e.shape[1]||0)]}else a=o[r].box?[Math.trunc(Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.max(0,o[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,o[r].box.bottomRight[0])-Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,o[r].box.bottomRight[1])-Math.max(0,o[r].box.topLeft[1]))]:[0,0,0,0],i=[o[r].box.topLeft[0]/(e.shape[2]||0),o[r].box.topLeft[1]/(e.shape[1]||0),(o[r].box.bottomRight[0]-o[r].box.topLeft[0])/(e.shape[2]||0),(o[r].box.bottomRight[1]-o[r].box.topLeft[1])/(e.shape[1]||0)];let x=y5(s);n.push({id:r,score:Math.round(100*o[r].confidence)/100,boxScore:Math.round(100*o[r].boxConfidence)/100,fingerScore:Math.round(100*o[r].fingerConfidence)/100,label:"hand",box:a,boxRaw:i,keypoints:s,annotations:A,landmarks:x})}return n}async function w1(e){var o,n;v.initial&&(A2=null,s2=null),!A2||!s2?[A2,s2]=await Promise.all([e.hand.enabled?G((o=e.hand.detector)==null?void 0:o.modelPath):null,e.hand.landmarks?G((n=e.hand.skeleton)==null?void 0:n.modelPath):null]):(e.debug&&p("cached model:",A2.modelUrl),e.debug&&p("cached model:",s2.modelUrl));let t=new i5(A2);return fo=new l5(t,s2),[A2,s2]}var Q=Z(D());var d0=[null,null],MA=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],Ce=[[0,0],[0,0]],PA=["hand","fist","pinch","point","face","tip","pinchtip"],po=4,uo=1.6,RA=512,vA=1.4,x5=Number.MAX_SAFE_INTEGER,k1=0,fe=[0,0],A0={boxes:[],hands:[]},ho={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],base:[0],palm:[0,17,13,9,5,1,0]};async function bo(e){var t;if(v.initial&&(d0[0]=null),d0[0])e.debug&&p("cached model:",d0[0].modelUrl);else{c5(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),d0[0]=await G((t=e.hand.detector)==null?void 0:t.modelPath);let o=Object.values(d0[0].modelSignature.inputs);Ce[0][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ce[0][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return d0[0]}async function go(e){var t;if(v.initial&&(d0[1]=null),d0[1])e.debug&&p("cached model:",d0[1].modelUrl);else{d0[1]=await G((t=e.hand.skeleton)==null?void 0:t.modelPath);let o=Object.values(d0[1].modelSignature.inputs);Ce[1][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ce[1][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return d0[1]}async function TA(e,t){let o=[];if(!e||!d0[0])return o;let n={},r=(e.shape[2]||1)/(e.shape[1]||1),A=Math.min(Math.round((e.shape[1]||0)/8)*8,RA),s=Math.round(A*r/8)*8;n.resize=Q.image.resizeBilinear(e,[A,s]),n.cast=Q.cast(n.resize,"int32"),[n.rawScores,n.rawBoxes]=await d0[0].executeAsync(n.cast,MA),n.boxes=Q.squeeze(n.rawBoxes,[0,2]),n.scores=Q.squeeze(n.rawScores,[0]);let a=Q.unstack(n.scores,1);Q.dispose(a[po]),a.splice(po,1),n.filtered=Q.stack(a,1),Q.dispose(a),n.max=Q.max(n.filtered,1),n.argmax=Q.argMax(n.filtered,1);let i=0;n.nms=await Q.image.nonMaxSuppressionAsync(n.boxes,n.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let x=await n.nms.data(),c=await n.max.data(),l=await n.argmax.data();for(let y of Array.from(x)){let f=Q.slice(n.boxes,y,1),u=await f.data();Q.dispose(f);let m=[u[1],u[0],u[3]-u[1],u[2]-u[0]],P=_2(m,vA),g=[Math.trunc(m[0]*fe[0]),Math.trunc(m[1]*fe[1]),Math.trunc(m[2]*fe[0]),Math.trunc(m[3]*fe[1])],b=c[y],d=PA[l[y]],M={id:i++,score:b,box:g,boxRaw:P,label:d};o.push(M)}return Object.keys(n).forEach(y=>Q.dispose(n[y])),o.sort((y,f)=>f.score-y.score),o.length>(t.hand.maxDetected||1)&&(o.length=t.hand.maxDetected||1),o}async function E1(e,t,o){let n={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&d0[1]&&o.hand.landmarks&&t.score>(o.hand.minConfidence||0)){let r={},A=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=Q.image.cropAndResize(e,[A],[0],[Ce[1][0],Ce[1][1]],"bilinear"),r.div=Q.div(r.crop,V.tf255),[r.score,r.keypoints]=d0[1].execute(r.div,["Identity_1","Identity"]);let s=(await r.score.data())[0],a=(100-Math.trunc(100/(1+Math.exp(s))))/100;if(a>=(o.hand.minConfidence||0)){n.fingerScore=a,r.reshaped=Q.reshape(r.keypoints,[-1,3]);let c=(await r.reshaped.array()).map(l=>[l[0]/Ce[1][1],l[1]/Ce[1][0],l[2]||0]).map(l=>[l[0]*t.boxRaw[2],l[1]*t.boxRaw[3],l[2]||0]);n.keypoints=c.map(l=>[fe[0]*(l[0]+t.boxRaw[0]),fe[1]*(l[1]+t.boxRaw[1]),l[2]||0]),n.landmarks=y5(n.keypoints);for(let l of Object.keys(ho))n.annotations[l]=ho[l].map(y=>n.landmarks&&n.keypoints[y]?n.keypoints[y]:null)}Object.keys(r).forEach(i=>Q.dispose(r[i]))}return n}async function z1(e,t){var r,A;if(!d0[0]||!d0[1]||!((r=d0[0])!=null&&r.inputs[0].shape)||!((A=d0[1])!=null&&A.inputs[0].shape))return[];fe=[e.shape[2]||0,e.shape[1]||0],x5++;let o=(t.hand.skipTime||0)>h()-k1,n=x5<(t.hand.skipFrames||0);return t.skipAllowed&&o&&n?A0.hands:new Promise(async s=>{let a=3*(t.hand.skipTime||0)>h()-k1,i=x5<3*(t.hand.skipFrames||0);t.skipAllowed&&A0.hands.length===t.hand.maxDetected?A0.hands=await Promise.all(A0.boxes.map(c=>E1(e,c,t))):t.skipAllowed&&a&&i&&A0.hands.length>0?A0.hands=await Promise.all(A0.boxes.map(c=>E1(e,c,t))):(A0.boxes=await TA(e,t),k1=h(),A0.hands=await Promise.all(A0.boxes.map(c=>E1(e,c,t))),x5=0);let x=[...A0.boxes];if(A0.boxes.length=0,t.cacheSensitivity>0)for(let c=0;c<A0.hands.length;c++){let l=i3(A0.hands[c].keypoints,fe);if(l.box[2]/(e.shape[2]||1)>.05&&l.box[3]/(e.shape[1]||1)>.05&&A0.hands[c].fingerScore&&A0.hands[c].fingerScore>(t.hand.minConfidence||0)){let y=_2(l.box,uo),f=_2(l.boxRaw,uo);A0.boxes.push({...x[c],box:y,boxRaw:f})}}for(let c=0;c<A0.hands.length;c++){let l=le(A0.hands[c].keypoints,fe);A0.hands[c].box=l.box,A0.hands[c].boxRaw=l.boxRaw}s(A0.hands)})}var f5=Z(D());var M0,d5=[],S1=Number.MAX_SAFE_INTEGER,Po=0,Ro=0;async function vo(e){var t;return v.initial&&(M0=null),M0?e.debug&&p("cached model:",M0.modelUrl):M0=await G((t=e.face.liveness)==null?void 0:t.modelPath),M0}async function C1(e,t,o,n){var s,a;if(!M0)return 0;let r=(((s=t.face.liveness)==null?void 0:s.skipTime)||0)>h()-Ro,A=S1<(((a=t.face.liveness)==null?void 0:a.skipFrames)||0);return t.skipAllowed&&r&&A&&Po===n&&d5[o]?(S1++,d5[o]):(S1=0,new Promise(async i=>{let x=f5.image.resizeBilinear(e,[M0!=null&&M0.inputs[0].shape?M0.inputs[0].shape[2]:0,M0!=null&&M0.inputs[0].shape?M0.inputs[0].shape[1]:0],!1),c=M0==null?void 0:M0.execute(x),l=(await c.data())[0];d5[o]=Math.round(100*l)/100,Po=n,Ro=h(),f5.dispose([x,c]),i(d5[o])}))}var So=Z(D());var E2={};ue(E2,{connected:()=>p5,horizontal:()=>I1,kpt:()=>m5,relative:()=>O1,vertical:()=>j1});var m5=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],I1=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],j1=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],O1=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],p5={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var Ie=Z(D()),wo=.005,W0={keypoints:[],padding:[[0,0],[0,0],[0,0],[0,0]]};function N1(e){for(let t of I1){let o=e.keypoints.findIndex(r=>r.part===t[0]),n=e.keypoints.findIndex(r=>r.part===t[1]);if(e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[0]<e.keypoints[n].position[0]){let r=e.keypoints[o];e.keypoints[o]=e.keypoints[n],e.keypoints[n]=r}}for(let t of j1){let o=e.keypoints.findIndex(r=>r&&r.part===t[0]),n=e.keypoints.findIndex(r=>r&&r.part===t[1]);e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[1]<e.keypoints[n].position[1]&&e.keypoints.splice(o,1)}for(let[t,o]of O1){let n=e.keypoints.findIndex(x=>x&&x.part===t[0]),r=e.keypoints.findIndex(x=>x&&x.part===t[1]),A=e.keypoints.findIndex(x=>x&&x.part===o[0]),s=e.keypoints.findIndex(x=>x&&x.part===o[1]);if(!e.keypoints[A]||!e.keypoints[s])continue;let a=e.keypoints[n]?[Math.abs(e.keypoints[A].position[0]-e.keypoints[n].position[0]),Math.abs(e.keypoints[s].position[0]-e.keypoints[n].position[0])]:[0,0],i=e.keypoints[r]?[Math.abs(e.keypoints[s].position[0]-e.keypoints[r].position[0]),Math.abs(e.keypoints[A].position[0]-e.keypoints[r].position[0])]:[0,0];if(a[0]>a[1]||i[0]>i[1]){let x=e.keypoints[n];e.keypoints[n]=e.keypoints[r],e.keypoints[r]=x}}}function ko(e){for(let t=0;t<e.length;t++)if(e[t]&&W0.keypoints[t]){let o=[Math.abs(e[t].positionRaw[0]-W0.keypoints[t].positionRaw[0]),Math.abs(e[t].positionRaw[1]-W0.keypoints[t].positionRaw[1])];o[0]<wo&&o[1]<wo?e[t]=W0.keypoints[t]:W0.keypoints[t]=e[t]}else W0.keypoints[t]=e[t];return e}function Eo(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;W0.padding=[[0,0],[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0],[0,0]],o.pad=Ie.pad(e,W0.padding),o.resize=Ie.image.resizeBilinear(o.pad,[t,t]);let n=Ie.cast(o.resize,"int32");return Object.keys(o).forEach(r=>Ie.dispose(o[r])),n}function zo(e,t){e.keypoints=e.keypoints.filter(n=>n&&n.position);for(let n of e.keypoints)n.position=[n.position[0]*(t[0]+W0.padding[2][0]+W0.padding[2][1])/t[0]-W0.padding[2][0],n.position[1]*(t[1]+W0.padding[1][0]+W0.padding[1][1])/t[1]-W0.padding[1][0]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1]];let o=le(e.keypoints.map(n=>n.position),t);return e.box=o.box,e.boxRaw=o.boxRaw,e}var F0,u5=0,L1=Number.MAX_SAFE_INTEGER,Ze={boxes:[],bodies:[],last:0};async function Co(e){return v.initial&&(F0=null),F0?e.debug&&p("cached model:",F0.modelUrl):(c5(["size"],e),F0=await G(e.body.modelPath)),u5=F0.inputs[0].shape?F0.inputs[0].shape[2]:0,u5<64&&(u5=256),F0}async function kA(e,t,o){let n=e[0][0],r=[],A=0;for(let c=0;c<n.length;c++)if(A=n[c][2],A>t.body.minConfidence){let l=[n[c][1],n[c][0]];r.push({score:Math.round(100*A)/100,part:m5[c],positionRaw:l,position:[Math.round((o.shape[2]||0)*l[0]),Math.round((o.shape[1]||0)*l[1])]})}A=r.reduce((c,l)=>l.score>c?l.score:c,0);let s=[],a=le(r.map(c=>c.position),[o.shape[2],o.shape[1]]),i={};for(let[c,l]of Object.entries(p5)){let y=[];for(let f=0;f<l.length-1;f++){let u=r.find(P=>P.part===l[f]),m=r.find(P=>P.part===l[f+1]);u&&m&&u.score>(t.body.minConfidence||0)&&m.score>(t.body.minConfidence||0)&&y.push([u.position,m.position])}i[c]=y}let x={id:0,score:A,box:a.box,boxRaw:a.boxRaw,keypoints:r,annotations:i};return N1(x),s.push(x),s}async function EA(e,t,o){let n=[];for(let r=0;r<e[0].length;r++){let A=e[0][r],s=Math.round(100*A[51+4])/100;if(s>t.body.minConfidence){let a=[];for(let l=0;l<17;l++){let y=A[3*l+2];if(y>t.body.minConfidence){let f=[A[3*l+1],A[3*l+0]];a.push({part:m5[l],score:Math.round(100*y)/100,positionRaw:f,position:[Math.round((o.shape[2]||0)*f[0]),Math.round((o.shape[1]||0)*f[1])]})}}let i=le(a.map(l=>l.position),[o.shape[2],o.shape[1]]),x={};for(let[l,y]of Object.entries(p5)){let f=[];for(let u=0;u<y.length-1;u++){let m=a.find(g=>g.part===y[u]),P=a.find(g=>g.part===y[u+1]);m&&P&&m.score>(t.body.minConfidence||0)&&P.score>(t.body.minConfidence||0)&&f.push([m.position,P.position])}x[l]=f}let c={id:r,score:s,box:i.box,boxRaw:i.boxRaw,keypoints:[...a],annotations:x};N1(c),n.push(c)}}return n.sort((r,A)=>A.score-r.score),n.length>t.body.maxDetected&&(n.length=t.body.maxDetected),n}async function W1(e,t){if(!F0||!(F0!=null&&F0.inputs[0].shape))return[];t.skipAllowed||(Ze.boxes.length=0),L1++;let o=(t.body.skipTime||0)>h()-Ze.last,n=L1<(t.body.skipFrames||0);return t.skipAllowed&&o&&n?Ze.bodies:new Promise(async r=>{let A={};L1=0,A.input=Eo(e,u5),A.res=F0==null?void 0:F0.execute(A.input),Ze.last=h();let s=await A.res.array();Ze.bodies=A.res.shape[2]===17?await kA(s,t,e):await EA(s,t,e);for(let a of Ze.bodies)zo(a,[e.shape[2]||1,e.shape[1]||1]),ko(a.keypoints);Object.keys(A).forEach(a=>So.dispose(A[a])),r(Ze.bodies)})}var E0=Z(D());var a2,h5=[],jo=0,F1=Number.MAX_SAFE_INTEGER,g5=0,b5=2.5;async function Oo(e){if(!a2||v.initial){a2=await G(e.object.modelPath);let t=Object.values(a2.modelSignature.inputs);g5=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&p("cached model:",a2.modelUrl);return a2}async function zA(e,t,o){let n=0,r=[];for(let i of[1,2,4])E0.tidy(async()=>{let x=i*13,c=E0.squeeze(e.find(m=>m.shape[1]===x**2&&(m.shape[2]||0)===$e.length)),l=E0.squeeze(e.find(m=>m.shape[1]===x**2&&(m.shape[2]||0)<$e.length)),f=await l.reshape([-1,4,l.shape[1]/4]).argMax(2).array(),u=await c.array();for(let m=0;m<c.shape[0];m++)for(let P=0;P<c.shape[1];P++){let g=u[m][P];if(g>(o.object.minConfidence||0)&&P!==61){let b=(.5+Math.trunc(m%x))/x,d=(.5+Math.trunc(m/x))/x,M=f[m].map(J=>J*(x/i/g5)),[S,w]=[b-b5/i*M[0],d-b5/i*M[1]],[j,C]=[b+b5/i*M[2]-S,d+b5/i*M[3]-w],F=[S,w,j,C];F=F.map(J=>Math.max(0,Math.min(J,1)));let H=[F[0]*t[0],F[1]*t[1],F[2]*t[0],F[3]*t[1]],Y={id:n++,score:Math.round(100*g)/100,class:P+1,label:$e[P].label,box:H.map(J=>Math.trunc(J)),boxRaw:F};r.push(Y)}}});e.forEach(i=>E0.dispose(i));let A=r.map(i=>[i.boxRaw[1],i.boxRaw[0],i.boxRaw[3],i.boxRaw[2]]),s=r.map(i=>i.score),a=[];if(A&&A.length>0){let i=await E0.image.nonMaxSuppressionAsync(A,s,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence);a=await i.data(),E0.dispose(i)}return r=r.filter((i,x)=>a.includes(x)).sort((i,x)=>x.score-i.score),r}async function G1(e,t){let o=(t.object.skipTime||0)>h()-jo,n=F1<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&h5.length>0?(F1++,h5):(F1=0,!v.kernels.includes("mod")||!v.kernels.includes("sparsetodense")?h5:new Promise(async r=>{let A=[e.shape[2]||0,e.shape[1]||0],s=E0.image.resizeBilinear(e,[g5,g5],!1),a=E0.div(s,V.tf255),i=a.transpose([0,3,1,2]);E0.dispose(a),E0.dispose(s);let x;t.object.enabled&&(x=a2.execute(i)),jo=h(),E0.dispose(i);let c=await zA(x,A,t);h5=c,r(c)}))}var z0=Z(D());var S2=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],SA=S2.length,z2=S2.reduce((e,t,o)=>(e[t]=o,e),{}),CA=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],ts=CA.map(([e,t])=>[z2[e],z2[t]]),Lo=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function Wo(e){let t=e.reduce(({maxX:o,maxY:n,minX:r,minY:A},{position:{x:s,y:a}})=>({maxX:Math.max(o,s),maxY:Math.max(n,a),minX:Math.min(r,s),minY:Math.min(A,a)}),{maxX:Number.NEGATIVE_INFINITY,maxY:Number.NEGATIVE_INFINITY,minX:Number.POSITIVE_INFINITY,minY:Number.POSITIVE_INFINITY});return[t.minX,t.minY,t.maxX-t.minX,t.maxY-t.minY]}function Fo(e,[t,o],[n,r]){let A=t/n,s=o/r,a=(x,c)=>({id:c,score:x.score,boxRaw:[x.box[0]/r,x.box[1]/n,x.box[2]/r,x.box[3]/n],box:[Math.trunc(x.box[0]*s),Math.trunc(x.box[1]*A),Math.trunc(x.box[2]*s),Math.trunc(x.box[3]*A)],keypoints:x.keypoints.map(({score:l,part:y,position:f})=>({score:l,part:y,position:[Math.trunc(f.x*s),Math.trunc(f.y*A)],positionRaw:[f.x/n,f.y/n]})),annotations:{}});return e.map((x,c)=>a(x,c))}var M5=class{constructor(t,o){T(this,"priorityQueue");T(this,"numberOfElements");T(this,"getElementValue");this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=o}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(Math.floor(t/2),t);)this.exchange(t,Math.floor(t/2)),t=Math.floor(t/2)}sink(t){for(;2*t<=this.numberOfElements;){let o=2*t;if(o<this.numberOfElements&&this.less(o,o+1)&&o++,!this.less(t,o))break;this.exchange(t,o),t=o}}getValueAt(t){return this.getElementValue(this.priorityQueue[t])}less(t,o){return this.getValueAt(t)<this.getValueAt(o)}exchange(t,o){let n=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[o],this.priorityQueue[o]=n}};function B1(e,t,o,n){return{y:n.get(e,t,o),x:n.get(e,t,o+SA)}}function H1(e,t,o){let{heatmapY:n,heatmapX:r,id:A}=e,{y:s,x:a}=B1(n,r,A,o);return{x:e.heatmapX*t+a,y:e.heatmapY*t+s}}function V1(e,t,o){return e<t?t:e>o?o:e}function Go(e,t,o,n){let r=o-e,A=n-t;return r*r+A*A}function D1(e,t){return{x:e.x+t.x,y:e.y+t.y}}var $0,jA=["MobilenetV1/offset_2/BiasAdd","MobilenetV1/heatmap_2/BiasAdd","MobilenetV1/displacement_fwd_2/BiasAdd","MobilenetV1/displacement_bwd_2/BiasAdd"],P5=1,i2=16,OA=50**2;function Bo(e,t,o,n,r,A,s=2){let a=g=>({y:A.get(g.y,g.x,e),x:A.get(g.y,g.x,A.shape[2]/2+e)}),i=(g,b,d)=>({y:V1(Math.round(g.y/i2),0,b-1),x:V1(Math.round(g.x/i2),0,d-1)}),[x,c]=n.shape,l=i(t.position,x,c),y=a(l),u=D1(t.position,y);for(let g=0;g<s;g++){let b=i(u,x,c),d=B1(b.y,b.x,o,r);u=D1({x:b.x*i2,y:b.y*i2},{x:d.x,y:d.y})}let m=i(u,x,c),P=n.get(m.y,m.x,o);return{position:u,part:S2[o],score:P}}function NA(e,t,o,n,r){let A=Lo.map(([y,f])=>[z2[y],z2[f]]),s=A.map(([,y])=>y),a=A.map(([y])=>y),i=t.shape[2],x=s.length,c=new Array(i),l=H1(e.part,i2,o);c[e.part.id]={score:e.score,part:S2[e.part.id],position:l};for(let y=x-1;y>=0;--y){let f=s[y],u=a[y];c[f]&&!c[u]&&(c[u]=Bo(y,c[f],u,t,o,r))}for(let y=0;y<x;++y){let f=a[y],u=s[y];c[f]&&!c[u]&&(c[u]=Bo(y,c[f],u,t,o,n))}return c}function LA(e,t,o,n,r){let[A,s]=r.shape,a=!0,i=Math.max(o-P5,0),x=Math.min(o+P5+1,A);for(let c=i;c<x;++c){let l=Math.max(n-P5,0),y=Math.min(n+P5+1,s);for(let f=l;f<y;++f)if(r.get(c,f,e)>t){a=!1;break}if(!a)break}return a}function WA(e,t){let[o,n,r]=t.shape,A=new M5(o*n*r,({score:s})=>s);for(let s=0;s<o;++s)for(let a=0;a<n;++a)for(let i=0;i<r;++i){let x=t.get(s,a,i);x<e||LA(i,x,s,a,t)&&A.enqueue({score:x,part:{heatmapY:s,heatmapX:a,id:i}})}return A}function Ho(e,{x:t,y:o},n){return e.some(({keypoints:r})=>{var s;let A=(s=r[n])==null?void 0:s.position;return A?Go(o,t,A.y,A.x)<=OA:!1})}function FA(e,t){return t.reduce((n,{position:r,score:A},s)=>(Ho(e,r,s)||(n+=A),n),0)/t.length}function GA(e,t,o,n,r,A){let s=[],a=WA(A,t);for(;s.length<r&&!a.empty();){let i=a.dequeue(),x=H1(i.part,i2,e);if(Ho(s,x,i.part.id))continue;let c=NA(i,t,e,o,n);c=c.filter(f=>f.score>A);let l=FA(s,c),y=Wo(c);l>A&&s.push({keypoints:c,box:y,score:Math.round(100*l)/100})}return s}async function Z1(e,t){let o=z0.tidy(()=>{if(!$0.inputs[0].shape)return[];let s=z0.image.resizeBilinear(e,[$0.inputs[0].shape[2],$0.inputs[0].shape[1]]),a=z0.sub(z0.div(z0.cast(s,"float32"),127.5),1),x=$0.execute(a,jA).map(c=>z0.squeeze(c,[0]));return x[1]=z0.sigmoid(x[1]),x}),n=await Promise.all(o.map(s=>s.buffer()));for(let s of o)z0.dispose(s);let r=await GA(n[0],n[1],n[2],n[3],t.body.maxDetected,t.body.minConfidence);return $0.inputs[0].shape?Fo(r,[e.shape[1],e.shape[2]],[$0.inputs[0].shape[2],$0.inputs[0].shape[1]]):[]}async function Vo(e){return!$0||v.initial?$0=await G(e.body.modelPath):e.debug&&p("cached model:",$0.modelUrl),$0}var n0=Z(D());var ne,X1=!1;async function q1(e){return!ne||v.initial?ne=await G(e.segmentation.modelPath):e.debug&&p("cached model:",ne.modelUrl),ne}async function Zo(e,t,o){var m,P;if(X1)return{data:[],canvas:null,alpha:null};X1=!0,ne||await q1(o);let n=await Ye(e,o),r=((m=n.tensor)==null?void 0:m.shape[2])||0,A=((P=n.tensor)==null?void 0:P.shape[1])||0;if(!n.tensor)return{data:[],canvas:null,alpha:null};let s={};s.resize=n0.image.resizeBilinear(n.tensor,[ne.inputs[0].shape?ne.inputs[0].shape[1]:0,ne.inputs[0].shape?ne.inputs[0].shape[2]:0],!1),n0.dispose(n.tensor),s.norm=n0.div(s.resize,V.tf255),s.res=ne.execute(s.norm),s.squeeze=n0.squeeze(s.res,0),s.squeeze.shape[2]===2?(s.softmax=n0.softmax(s.squeeze),[s.bg,s.fg]=n0.unstack(s.softmax,2),s.expand=n0.expandDims(s.fg,2),s.pad=n0.expandDims(s.expand,0),s.crop=n0.image.cropAndResize(s.pad,[[0,0,.5,.5]],[0],[r,A]),s.data=n0.squeeze(s.crop,0)):s.data=n0.image.resizeBilinear(s.squeeze,[A,r]);let a=Array.from(await s.data.data());if(v.node&&!v.Canvas&&typeof ImageData=="undefined")return o.debug&&p("canvas support missing"),Object.keys(s).forEach(g=>n0.dispose(s[g])),{data:a,canvas:null,alpha:null};let i=R0(r,A);n0.browser&&await n0.browser.toPixels(s.data,i);let x=i.getContext("2d");o.segmentation.blur&&o.segmentation.blur>0&&(x.filter=`blur(${o.segmentation.blur}px)`);let c=x.getImageData(0,0,r,A),l=R0(r,A),y=l.getContext("2d");n.canvas&&y.drawImage(n.canvas,0,0),y.globalCompositeOperation="darken",o.segmentation.blur&&o.segmentation.blur>0&&(y.filter=`blur(${o.segmentation.blur}px)`),y.drawImage(i,0,0),y.globalCompositeOperation="source-over",y.filter="none";let f=y.getImageData(0,0,r,A);for(let g=0;g<r*A;g++)f.data[4*g+3]=c.data[4*g+0];y.putImageData(f,0,0);let u=null;if(t&&l){u=R0(r,A);let g=await Ye(t,o);n0.dispose(g.tensor);let b=u.getContext("2d");b.drawImage(g.canvas,0,0,u.width,u.height),b.drawImage(l,0,0)}return Object.keys(s).forEach(g=>n0.dispose(s[g])),X1=!1,{data:a,canvas:l,alpha:i}}var C2=class{constructor(){T(this,"ssrnetage",null);T(this,"gear",null);T(this,"blazeposedetect",null);T(this,"blazepose",null);T(this,"centernet",null);T(this,"efficientpose",null);T(this,"mobilefacenet",null);T(this,"emotion",null);T(this,"facedetect",null);T(this,"faceiris",null);T(this,"facemesh",null);T(this,"faceres",null);T(this,"ssrnetgender",null);T(this,"handpose",null);T(this,"handskeleton",null);T(this,"handtrack",null);T(this,"liveness",null);T(this,"movenet",null);T(this,"nanodet",null);T(this,"posenet",null);T(this,"segmentation",null);T(this,"antispoof",null)}},U1=e=>{let t=0,o=0,n=0;for(let A of Object.values(q0))t+=A.sizeFromManifest,o+=A.sizeLoadedWeights,n+=A.sizeDesired;let r=n>0?o/n:0;return{numLoadedModels:Object.values(q0).length,numEnabledModels:void 0,numDefinedModels:Object.keys(e.models).length,percentageLoaded:r,totalSizeFromManifest:t,totalSizeWeights:o,totalSizeLoading:n,totalSizeEnabled:void 0,modelStats:Object.values(q0)}};function R5(e){for(let t of Object.keys(e.models))e.models[t]=null}async function Y1(e){var t,o,n,r,A,s,a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0;v.initial&&R5(e),e.config.hand.enabled&&(!e.models.handpose&&((o=(t=e.config.hand.detector)==null?void 0:t.modelPath)==null?void 0:o.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await w1(e.config)),!e.models.handskeleton&&e.config.hand.landmarks&&((r=(n=e.config.hand.detector)==null?void 0:n.modelPath)==null?void 0:r.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await w1(e.config))),e.config.body.enabled&&!e.models.blazepose&&((s=(A=e.config.body)==null?void 0:A.modelPath)==null?void 0:s.includes("blazepose"))&&(e.models.blazepose=d3(e.config)),e.config.body.enabled&&!e.models.blazeposedetect&&e.config.body.detector&&e.config.body.detector.modelPath&&(e.models.blazeposedetect=c3(e.config)),e.config.body.enabled&&!e.models.efficientpose&&((i=(a=e.config.body)==null?void 0:a.modelPath)==null?void 0:i.includes("efficientpose"))&&(e.models.efficientpose=b3(e.config)),e.config.body.enabled&&!e.models.movenet&&((c=(x=e.config.body)==null?void 0:x.modelPath)==null?void 0:c.includes("movenet"))&&(e.models.movenet=Co(e.config)),e.config.body.enabled&&!e.models.posenet&&((y=(l=e.config.body)==null?void 0:l.modelPath)==null?void 0:y.includes("posenet"))&&(e.models.posenet=Vo(e.config)),e.config.face.enabled&&!e.models.facedetect&&(e.models.facedetect=n3(e.config)),e.config.face.enabled&&((f=e.config.face.antispoof)==null?void 0:f.enabled)&&!e.models.antispoof&&(e.models.antispoof=Zt(e.config)),e.config.face.enabled&&((u=e.config.face.liveness)==null?void 0:u.enabled)&&!e.models.liveness&&(e.models.liveness=vo(e.config)),e.config.face.enabled&&((m=e.config.face.description)==null?void 0:m.enabled)&&!e.models.faceres&&(e.models.faceres=X3(e.config)),e.config.face.enabled&&((P=e.config.face.emotion)==null?void 0:P.enabled)&&!e.models.emotion&&(e.models.emotion=R3(e.config)),e.config.face.enabled&&((g=e.config.face.iris)==null?void 0:g.enabled)&&!((b=e.config.face.attention)!=null&&b.enabled)&&!e.models.faceiris&&(e.models.faceiris=O3(e.config)),e.config.face.enabled&&((d=e.config.face.mesh)==null?void 0:d.enabled)&&!e.models.facemesh&&(e.models.facemesh=B3(e.config)),e.config.face.enabled&&((M=e.config.face.gear)==null?void 0:M.enabled)&&!e.models.gear&&(e.models.gear=Ct(e.config)),e.config.face.enabled&&((S=e.config.face.ssrnet)==null?void 0:S.enabled)&&!e.models.ssrnetage&&(e.models.ssrnetage=Lt(e.config)),e.config.face.enabled&&((w=e.config.face.ssrnet)==null?void 0:w.enabled)&&!e.models.ssrnetgender&&(e.models.ssrnetgender=Bt(e.config)),e.config.face.enabled&&((j=e.config.face.mobilefacenet)==null?void 0:j.enabled)&&!e.models.mobilefacenet&&(e.models.mobilefacenet=z3(e.config)),e.config.hand.enabled&&!e.models.handtrack&&((F=(C=e.config.hand.detector)==null?void 0:C.modelPath)==null?void 0:F.includes("handtrack"))&&(e.models.handtrack=bo(e.config)),e.config.hand.enabled&&e.config.hand.landmarks&&!e.models.handskeleton&&((Y=(H=e.config.hand.detector)==null?void 0:H.modelPath)==null?void 0:Y.includes("handtrack"))&&(e.models.handskeleton=go(e.config)),e.config.object.enabled&&!e.models.centernet&&((x0=(J=e.config.object)==null?void 0:J.modelPath)==null?void 0:x0.includes("centernet"))&&(e.models.centernet=p3(e.config)),e.config.object.enabled&&!e.models.nanodet&&((G0=(E=e.config.object)==null?void 0:E.modelPath)==null?void 0:G0.includes("nanodet"))&&(e.models.nanodet=Oo(e.config)),e.config.segmentation.enabled&&!e.models.segmentation&&(e.models.segmentation=q1(e.config));for await(let B0 of Object.keys(e.models))e.models[B0]&&typeof e.models[B0]!="undefined"&&(e.models[B0]=await e.models[B0])}async function K1(e){let t=["const","placeholder","noop","pad","squeeze","add","sub","mul","div"];for(let o of Object.keys(e.models)){let n=e.models[o];if(!n)continue;let r=[],A=n==null?void 0:n.executor;if(A&&A.graph.nodes)for(let a of Object.values(A.graph.nodes)){let i=a.op.toLowerCase();r.includes(i)||r.push(i)}else!A&&e.config.debug&&p("model signature not determined:",o);let s=[];for(let a of r)!t.includes(a)&&!e.env.kernels.includes(a)&&!e.env.kernels.includes(a.replace("_",""))&&!e.env.kernels.includes(a.replace("native",""))&&!e.env.kernels.includes(a.replace("v2",""))&&s.push(a);e.config.debug&&s.length>0&&p("model validation failed:",o,s)}}var t0={name:"humangl",priority:999,canvas:null,gl:null,extensions:[],webGLattr:{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!1,desynchronized:!0}};function BA(){let e=t0.gl;!e||(t0.extensions=e.getSupportedExtensions())}async function qo(e){var t;if(e.config.backend==="humangl"&&(t0.name in s0.engine().registry&&(!t0.gl||!t0.gl.getParameter(t0.gl.VERSION))&&(p("error: humangl backend invalid context"),R5(e)),!s0.findBackend(t0.name))){try{t0.canvas=await R0(100,100)}catch(n){p("error: cannot create canvas:",n);return}try{if(t0.gl=(t=t0.canvas)==null?void 0:t.getContext("webgl2",t0.webGLattr),!t0.gl.getParameter(t0.gl.VERSION).includes("2.0")){p("override: using fallback webgl backend as webgl 2.0 is not detected"),e.config.backend="webgl";return}t0.canvas&&(t0.canvas.addEventListener("webglcontextlost",async r=>{throw p("error: humangl:",r.type),p("possible browser memory leak using webgl or conflict with multiple backend registrations"),e.emit("error"),new Error("backend error: webgl context lost")}),t0.canvas.addEventListener("webglcontextrestored",r=>{p("error: humangl context restored:",r)}),t0.canvas.addEventListener("webglcontextcreationerror",r=>{p("error: humangl context create:",r)}))}catch(n){p("error: cannot get WebGL context:",n);return}try{s0.setWebGLContext(2,t0.gl)}catch(n){p("error: cannot set WebGL context:",n);return}try{let n=new s0.GPGPUContext(t0.gl);s0.registerBackend(t0.name,()=>new s0.MathBackendWebGL(n),t0.priority)}catch(n){p("error: cannot register WebGL backend:",n);return}try{s0.getKernelsForBackend("webgl").forEach(r=>{let A={...r,backendName:t0.name};s0.registerKernel(A)})}catch(n){p("error: cannot update WebGL backend registration:",n);return}let o=s0.backend().getGPGPUContext?s0.backend().getGPGPUContext().gl:null;if(o)p(`humangl webgl version:${o.getParameter(o.VERSION)} renderer:${o.getParameter(o.RENDERER)}`);else{p("error: no current gl context:",o,t0.gl);return}try{s0.env().flagRegistry.WEBGL_VERSION&&s0.env().set("WEBGL_VERSION",2)}catch(n){p("error: cannot set WebGL backend flags:",n);return}BA(),p("backend registered:",t0.name)}}var I=Z(D());function HA(){if(!v.kernels.includes("mod")){let e={kernelName:"Mod",backendName:I.getBackend(),kernelFunc:t=>I.tidy(()=>I.sub(t.inputs.a,I.mul(I.div(t.inputs.a,t.inputs.b),t.inputs.b)))};I.registerKernel(e),v.kernels.push("mod")}if(!v.kernels.includes("floormod")){let e={kernelName:"FloorMod",backendName:I.getBackend(),kernelFunc:t=>I.tidy(()=>I.floorDiv(t.inputs.a/t.inputs.b)*t.inputs.b+I.mod(t.inputs.a,t.inputs.b))};I.registerKernel(e),v.kernels.push("floormod")}}async function T5(e,t=!1){if(e.state="backend",t||v.initial||e.config.backend&&e.config.backend.length>0&&I.getBackend()!==e.config.backend){let o=h();if(e.config.backend&&e.config.backend.length>0){if(typeof window=="undefined"&&typeof WorkerGlobalScope!="undefined"&&e.config.debug&&e.config.debug&&p("running inside web worker"),v.browser&&e.config.backend==="tensorflow"&&(e.config.debug&&p("override: backend set to tensorflow while running in browser"),e.config.backend="humangl"),v.node&&(e.config.backend==="webgl"||e.config.backend==="humangl")&&(e.config.debug&&p(`override: backend set to ${e.config.backend} while running in nodejs`),e.config.backend="tensorflow"),v.browser&&e.config.backend==="webgpu")if(typeof navigator=="undefined"||typeof navigator.gpu=="undefined")p("override: backend set to webgpu but browser does not support webgpu"),e.config.backend="humangl";else{let r=await navigator.gpu.requestAdapter();if(e.config.debug&&p("enumerated webgpu adapter:",r),!r)p("override: backend set to webgpu but browser reports no available gpu"),e.config.backend="humangl";else{let A="requestAdapterInfo"in r?await r.requestAdapterInfo():void 0;p("webgpu adapter info:",A)}}e.config.backend==="humangl"&&await qo(e);let n=Object.keys(I.engine().registryFactory);if(e.config.debug&&p("available backends:",n),n.includes(e.config.backend)||(p(`error: backend ${e.config.backend} not found in registry`),e.config.backend=v.node?"tensorflow":"webgl",e.config.debug&&p(`override: setting backend ${e.config.backend}`)),e.config.debug&&p("setting backend:",e.config.backend),e.config.backend==="wasm"){if(I.env().flagRegistry.CANVAS2D_WILL_READ_FREQUENTLY&&I.env().set("CANVAS2D_WILL_READ_FREQUENTLY",!0),e.config.debug&&p("wasm path:",e.config.wasmPath),typeof(I==null?void 0:I.setWasmPaths)!="undefined")await I.setWasmPaths(e.config.wasmPath,e.config.wasmPlatformFetch);else throw new Error("backend error: attempting to use wasm backend but wasm path is not set");let r=await I.env().getAsync("WASM_HAS_SIMD_SUPPORT"),A=await I.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");e.config.debug&&p(`wasm execution: ${r?"SIMD":"no SIMD"} ${A?"multithreaded":"singlethreaded"}`),e.config.debug&&!r&&p("warning: wasm simd support is not enabled")}try{await I.setBackend(e.config.backend),await I.ready(),jt()}catch(r){return p("error: cannot set backend:",e.config.backend,r),!1}}if(I.getBackend()==="humangl"&&(I.env().flagRegistry.CHECK_COMPUTATION_FOR_ERRORS&&I.env().set("CHECK_COMPUTATION_FOR_ERRORS",!1),I.env().flagRegistry.WEBGL_CPU_FORWARD&&I.env().set("WEBGL_CPU_FORWARD",!0),I.env().flagRegistry.WEBGL_USE_SHAPES_UNIFORMS&&I.env().set("WEBGL_USE_SHAPES_UNIFORMS",!0),I.env().flagRegistry.CPU_HANDOFF_SIZE_THRESHOLD&&I.env().set("CPU_HANDOFF_SIZE_THRESHOLD",256),I.env().flagRegistry.WEBGL_EXP_CONV&&I.env().set("WEBGL_EXP_CONV",!0),I.env().flagRegistry.USE_SETTIMEOUTWPM&&I.env().set("USE_SETTIMEOUTWPM",!0),typeof e.config.deallocate!="undefined"&&e.config.deallocate&&(p("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),I.env().set("WEBGL_DELETE_TEXTURE_THRESHOLD",0)),I.backend().getGPGPUContext)){let n=await I.backend().getGPGPUContext().gl;e.config.debug&&p(`gl version:${n.getParameter(n.VERSION)} renderer:${n.getParameter(n.RENDERER)}`)}I.getBackend(),I.enableProdMode(),await I.ready(),e.performance.initBackend=Math.trunc(h()-o),e.config.backend=I.getBackend(),await v.updateBackend(),HA()}return!0}function c5(e,t){for(let o of e){let n={kernelName:o,backendName:t.backend,kernelFunc:()=>{t.debug&&p("kernelFunc",o,t.backend)}};I.registerKernel(n)}v.kernels=I.getKernelsForBackend(I.getBackend()).map(o=>o.kernelName.toLowerCase())}var ot={};ue(ot,{all:()=>tt,body:()=>y2,canvas:()=>et,face:()=>l2,gesture:()=>d2,hand:()=>x2,object:()=>c2,options:()=>P0,person:()=>$1});var V0=e=>{if(!e)p("draw error: invalid canvas");else if(!e.getContext)p("draw error: canvas context not defined");else{let t=e.getContext("2d");if(!t)p("draw error: cannot get canvas context");else return t}return null},Xe=e=>Math.round(e*180/Math.PI),me=(e,t)=>{if(!t.useDepth||typeof e=="undefined")return t.color;let o=Uint8ClampedArray.from([127+2*e,127-2*e,255]);return`rgba(${o[0]}, ${o[1]}, ${o[2]}, ${t.alpha})`};function pe(e,t,o,n,r){e.fillStyle=me(n,r),e.beginPath(),e.arc(t,o,r.pointSize,0,2*Math.PI),e.fill()}function re(e,t,o,n,r,A){if(e.beginPath(),e.lineWidth=A.lineWidth,A.useCurves){let s=(t+t+n)/2,a=(o+o+r)/2;e.ellipse(s,a,n/2,r/2,0,0,2*Math.PI)}else e.moveTo(t+A.roundRect,o),e.lineTo(t+n-A.roundRect,o),e.quadraticCurveTo(t+n,o,t+n,o+A.roundRect),e.lineTo(t+n,o+r-A.roundRect),e.quadraticCurveTo(t+n,o+r,t+n-A.roundRect,o+r),e.lineTo(t+A.roundRect,o+r),e.quadraticCurveTo(t,o+r,t,o+r-A.roundRect),e.lineTo(t,o+A.roundRect),e.quadraticCurveTo(t,o,t+A.roundRect,o),e.closePath();e.stroke()}function J1(e,t,o){if(!(t.length<2)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let n of t)e.strokeStyle=me(n[2]||0,o),e.lineTo(Math.trunc(n[0]),Math.trunc(n[1]));e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function Yo(e,t,o){if(!(t.length<2)){if(e.lineWidth=o.lineWidth,!o.useCurves||t.length<=2){J1(e,t,o);return}e.moveTo(t[0][0],t[0][1]);for(let n=0;n<t.length-2;n++){let r=(t[n][0]+t[n+1][0])/2,A=(t[n][1]+t[n+1][1])/2;e.quadraticCurveTo(t[n][0],t[n][1],r,A)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function Q1(e,t,o,n=5){let r,A,s;e.beginPath(),e.moveTo(t[0],t[1]),e.lineTo(o[0],o[1]),r=Math.atan2(o[1]-t[1],o[0]-t[0]),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.moveTo(A,s),r+=1/3*(2*Math.PI),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.lineTo(A,s),r+=1/3*(2*Math.PI),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.lineTo(A,s),e.closePath(),e.stroke(),e.fill()}var P0={color:"rgba(173, 216, 230, 0.6)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",alpha:.5,font:'small-caps 16px "Segoe UI"',lineHeight:18,lineWidth:4,pointSize:2,roundRect:8,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawAttention:!0,drawGestures:!0,drawPolygons:!0,drawGaze:!0,fillPolygons:!1,useDepth:!0,useCurves:!1};var U;function DA(e,t){if(U.drawLabels){let o=[];if(o.push(`face: ${Math.trunc(100*e.score)}%`),e.genderScore&&o.push(`${e.gender||""} ${Math.trunc(100*e.genderScore)}%`),e.age&&o.push(`age: ${e.age||""}`),e.iris&&o.push(`distance: ${e.iris}`),e.real&&o.push(`real: ${Math.trunc(100*e.real)}%`),e.live&&o.push(`live: ${Math.trunc(100*e.live)}%`),e.emotion&&e.emotion.length>0){let n=e.emotion.map(r=>`${Math.trunc(100*r.score)}% ${r.emotion}`);n.length>3&&(n.length=3),o.push(n.join(" "))}e.rotation&&e.rotation.angle&&e.rotation.gaze&&(e.rotation.angle.roll&&o.push(`roll: ${Xe(e.rotation.angle.roll)}\xB0 yaw:${Xe(e.rotation.angle.yaw)}\xB0 pitch:${Xe(e.rotation.angle.pitch)}\xB0`),e.rotation.gaze.bearing&&o.push(`gaze: ${Xe(e.rotation.gaze.bearing)}\xB0`)),o.length===0&&o.push("face"),t.fillStyle=U.color;for(let n=o.length-1;n>=0;n--){let r=Math.max(e.box[0],0),A=n*U.lineHeight+e.box[1];U.shadowColor&&U.shadowColor!==""&&(t.fillStyle=U.shadowColor,t.fillText(o[n],r+5,A+16)),t.fillStyle=U.labelColor,t.fillText(o[n],r+4,A+15)}}}function ZA(e,t){if(e.annotations&&e.annotations.leftEyeIris&&e.annotations.leftEyeIris[0]){t.strokeStyle=U.useDepth?"rgba(255, 200, 255, 0.3)":U.color,t.beginPath();let o=Math.abs(e.annotations.leftEyeIris[3][0]-e.annotations.leftEyeIris[1][0])/2,n=Math.abs(e.annotations.leftEyeIris[4][1]-e.annotations.leftEyeIris[2][1])/2;t.ellipse(e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),U.fillPolygons&&(t.fillStyle=U.useDepth?"rgba(255, 255, 200, 0.3)":U.color,t.fill())}if(e.annotations&&e.annotations.rightEyeIris&&e.annotations.rightEyeIris[0]){t.strokeStyle=U.useDepth?"rgba(255, 200, 255, 0.3)":U.color,t.beginPath();let o=Math.abs(e.annotations.rightEyeIris[3][0]-e.annotations.rightEyeIris[1][0])/2,n=Math.abs(e.annotations.rightEyeIris[4][1]-e.annotations.rightEyeIris[2][1])/2;t.ellipse(e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),U.fillPolygons&&(t.fillStyle=U.useDepth?"rgba(255, 255, 200, 0.3)":U.color,t.fill())}}function XA(e,t){var o;if(U.drawGaze&&((o=e.rotation)==null?void 0:o.angle)&&typeof Path2D!="undefined"){t.strokeStyle="pink";let n=e.box[0]+e.box[2]/2-e.box[3]*Xe(e.rotation.angle.yaw)/90,r=e.box[1]+e.box[3]/2+e.box[2]*Xe(e.rotation.angle.pitch)/90,A=new Path2D(`
       M ${e.box[0]+e.box[2]/2} ${e.box[1]}
       C
         ${n} ${e.box[1]},
@@ -108,7 +108,7 @@ var sn=Object.create;var h2=Object.defineProperty;var an=Object.getOwnPropertyDe
         ${e.box[0]} ${r},
         ${e.box[0]+e.box[2]} ${r},
         ${e.box[0]+e.box[2]} ${e.box[1]+e.box[3]/2}
-    `);t.stroke(s),t.stroke(A)}}function qA(e,t){var o,n,r,A;if(U.drawGaze&&((n=(o=e.rotation)==null?void 0:o.gaze)==null?void 0:n.strength)&&((A=(r=e.rotation)==null?void 0:r.gaze)==null?void 0:A.bearing)&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let s=[e.annotations.leftEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.leftEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];Q1(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[s[0],s[1]],4);let a=[e.annotations.rightEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.rightEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];Q1(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[a[0],a[1]],4)}}function UA(e,t){if(U.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let o=0;o<Ne.length/3;o++){let n=[Ne[o*3+0],Ne[o*3+1],Ne[o*3+2]].map(r=>e.mesh[r]);J1(t,n,U)}ZA(e,t)}}function YA(e,t){if(U.drawPoints&&e.mesh.length>=468)for(let o=0;o<e.mesh.length;o++)pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2],U),U.drawAttention&&(w2.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]+127,U),We.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,U),Fe.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,U))}function KA(e,t){U.drawBoxes&&re(t,e.box[0],e.box[1],e.box[2],e.box[3],U)}async function l2(e,t,o){if(U=r0(P0,o),!t||!e)return;let n=V0(e);if(!!n){n.font=U.font,n.strokeStyle=U.color,n.fillStyle=U.color;for(let r of t)KA(r,n),DA(r,n),r.mesh&&r.mesh.length>0&&(YA(r,n),UA(r,n),XA(r,n),qA(r,n))}}async function y2(e,t,o){var A;let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round";for(let s=0;s<t.length;s++){if(r.strokeStyle=n.color,r.fillStyle=n.color,r.lineWidth=n.lineWidth,r.font=n.font,n.drawBoxes&&t[s].box&&((A=t[s].box)==null?void 0:A.length)===4&&(re(r,t[s].box[0],t[s].box[1],t[s].box[2],t[s].box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`body ${100*t[s].score}%`,t[s].box[0]+3,1+t[s].box[1]+n.lineHeight,t[s].box[2])),r.fillStyle=n.labelColor,r.fillText(`body ${100*t[s].score}%`,t[s].box[0]+2,0+t[s].box[1]+n.lineHeight,t[s].box[2]))),n.drawPoints&&t[s].keypoints)for(let a=0;a<t[s].keypoints.length;a++)!t[s].keypoints[a].score||t[s].keypoints[a].score===0||(r.fillStyle=me(t[s].keypoints[a].position[2],n),pe(r,t[s].keypoints[a].position[0],t[s].keypoints[a].position[1],0,n));if(n.drawLabels&&t[s].keypoints){r.font=n.font;for(let a of t[s].keypoints)!a.score||a.score===0||(r.fillStyle=me(a.position[2],n),r.fillText(`${a.part} ${Math.trunc(100*a.score)}%`,a.position[0]+4,a.position[1]+4))}if(n.drawPolygons&&t[s].keypoints&&t[s].annotations)for(let a of Object.values(t[s].annotations))for(let i of a)Yo(r,i,n)}}}async function x2(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A of t){if(n.drawBoxes&&(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,A.box[0],A.box[1],A.box[2],A.box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`hand:${Math.trunc(100*A.score)}%`,A.box[0]+3,1+A.box[1]+n.lineHeight,A.box[2])),r.fillStyle=n.labelColor,r.fillText(`hand:${Math.trunc(100*A.score)}%`,A.box[0]+2,0+A.box[1]+n.lineHeight,A.box[2])),r.stroke()),n.drawPoints&&A.keypoints&&A.keypoints.length>0)for(let s of A.keypoints)r.fillStyle=me(s[2],n),pe(r,s[0],s[1],0,n);if(n.drawLabels&&A.annotations){let s=(a,i)=>{if(!a||a.length===0||!a[0])return;let x=a[a.length-1][2]||-256;r.fillStyle=me(x,n),r.fillText(i,a[a.length-1][0]+4,a[a.length-1][1]+4)};r.font=n.font,s(A.annotations.index,"index"),s(A.annotations.middle,"middle"),s(A.annotations.ring,"ring"),s(A.annotations.pinky,"pinky"),s(A.annotations.thumb,"thumb"),s(A.annotations.palm,"palm")}if(n.drawPolygons&&A.annotations){let s=a=>{if(!(!a||a.length===0||!a[0]))for(let i=0;i<a.length;i++){r.beginPath();let x=a[i][2]||0;r.strokeStyle=me(i*x,n),r.moveTo(a[i>0?i-1:0][0],a[i>0?i-1:0][1]),r.lineTo(a[i][0],a[i][1]),r.stroke()}};r.lineWidth=n.lineWidth,s(A.annotations.index),s(A.annotations.middle),s(A.annotations.ring),s(A.annotations.pinky),s(A.annotations.thumb)}}}}async function c2(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A of t)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,A.box[0],A.box[1],A.box[2],A.box[3],n),n.drawLabels){let s=`${A.label} ${Math.round(100*A.score)}%`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(s,A.box[0]+3,1+A.box[1]+n.lineHeight,A.box[2])),r.fillStyle=n.labelColor,r.fillText(s,A.box[0]+2,0+A.box[1]+n.lineHeight,A.box[2])}r.stroke()}}}async function d2(e,t,o){let n=r0(P0,o);if(!(!t||!e)&&n.drawGestures){let r=V0(e);if(!r)return;r.font=n.font,r.fillStyle=n.color;let A=1;for(let s=0;s<t.length;s++){let a=[],i=[];if([a,i]=Object.entries(t[s]),i.length>1&&i[1].length>0){let x=a[1]>0?`#${a[1]}`:"",c=`${a[0]} ${x}: ${i[1]}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(c,8,2+A*n.lineHeight)),r.fillStyle=n.labelColor,r.fillText(c,6,0+A*n.lineHeight),A+=1}}}}var _1=0;async function $1(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A=0;A<t.length;A++)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,t[A].box[0],t[A].box[1],t[A].box[2],t[A].box[3],n),n.drawLabels){let s=`person #${A}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(s,t[A].box[0]+3,1+t[A].box[1]+n.lineHeight,t[A].box[2])),r.fillStyle=n.labelColor,r.fillText(s,t[A].box[0]+2,0+t[A].box[1]+n.lineHeight,t[A].box[2])}r.stroke()}}}async function et(e,t){if(!e||!t)return;let o=V0(t);!o||o.drawImage(e,0,0)}async function tt(e,t,o){if(!t||!t.performance||!t||!e)return null;let n=h(),r=r0(P0,o),A=Promise.all([l2(e,t.face,r),y2(e,t.body,r),x2(e,t.hand,r),c2(e,t.object,r),d2(e,t.gesture,r)]);return _1=v.perfadd?_1+Math.round(h()-n):Math.round(h()-n),t.performance.draw=_1,A}var s0=Z(D());var Ko=Z(D());var f2=.1,nt=.5;function JA(e,t,o){let n=!1,r=o.length-1;for(let A=0;A<o.length;r=A++)o[A].y>t!=o[r].y>t&&e<(o[r].x-o[A].x)*(t-o[A].y)/(o[r].y-o[A].y)+o[A].x&&(n=!n);return n}async function Jo(e){if(!e.tensor||!e.mesh||e.mesh.length<100)return e.tensor;let t=e.tensor.shape[2]||0,o=e.tensor.shape[1]||0,n=await e.tensor.buffer(),r=[];for(let s of X0.silhouette)r.push({x:(e.mesh[s][0]-e.box[0])/e.box[2],y:(e.mesh[s][1]-e.box[1])/e.box[3]});f2&&f2>0&&(r=r.map(s=>({x:s.x>.5?s.x+f2:s.x-f2,y:s.y>.5?s.y+f2:s.y-f2})));for(let s=0;s<t;s++)for(let a=0;a<o;a++)JA(s/t,a/t,r)||(n.set(nt*n.get(0,a,s,0),0,a,s,0),n.set(nt*n.get(0,a,s,1),0,a,s,1),n.set(nt*n.get(0,a,s,2),0,a,s,2));let A=n.toTensor();return Ko.dispose(n),A}var _A=e=>{let t=(l,y)=>Math.atan2(l[1]-y[1],l[0]-y[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let o=[0,-.1],n=1,r=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),A=r?e.mesh[473]:e.mesh[468],s=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],a=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],i=[(s[0]-A[0])/a[0]-o[0],n*(A[1]-s[1])/a[1]-o[1]],x=Math.sqrt(i[0]*i[0]+i[1]*i[1]);return x=Math.min(x,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],i)+Math.PI/2)%Math.PI,strength:x}},Qo=(e,t)=>{let o=m=>{let P=Math.sqrt(m[0]*m[0]+m[1]*m[1]+m[2]*m[2]);return m[0]/=P,m[1]/=P,m[2]/=P,m},n=(m,P)=>{let g=m[0]-P[0],b=m[1]-P[1],d=m[2]-P[2];return[g,b,d]},r=(m,P)=>{let g=m[1]*P[2]-m[2]*P[1],b=m[2]*P[0]-m[0]*P[2],d=m[0]*P[1]-m[1]*P[0];return[g,b,d]},A=m=>{let[P,g,b,d,M,S,w,j,C]=m,F,H,Y;return d<1?d>-1?(Y=Math.asin(d),H=Math.atan2(-w,P),F=Math.atan2(-S,M)):(Y=-Math.PI/2,H=-Math.atan2(j,C),F=0):(Y=Math.PI/2,H=Math.atan2(j,C),F=0),isNaN(F)&&(F=0),isNaN(H)&&(H=0),isNaN(Y)&&(Y=0),{pitch:2*-F,yaw:2*-H,roll:2*-Y}},s=e.meshRaw;if(!s||s.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let a=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,i=[s[10],s[152],s[234],s[454]].map(m=>[m[0]*t[0]/a,m[1]*t[1]/a,m[2]]),x=o(n(i[1],i[0])),c=o(n(i[3],i[2])),l=o(r(c,x));c=r(x,l);let y=[c[0],c[1],c[2],x[0],x[1],x[2],l[0],l[1],l[2]],f=A(y),u=s.length===478?_A(e):{bearing:0,strength:0};return{angle:f,matrix:y,gaze:u}};var rt=async(e,t)=>{var f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0,R,c0;let o=h(),n,r,A,s,a,i,x,c,l=[];e.state="run:face";let y=await G3(t,e.config);if(e.performance.face=v.perfadd?(e.performance.face||0)+Math.trunc(h()-o):Math.trunc(h()-o),!t.shape||t.shape.length!==4)return[];if(!y)return[];for(let k=0;k<y.length;k++){if(e.analyze("Get Face"),!y[k].tensor||y[k].tensor.isDisposedInternal){p("Face object is disposed:",y[k].tensor);continue}if((f=e.config.face.detector)!=null&&f.mask){let K=await Jo(y[k]);s0.dispose(y[k].tensor),y[k].tensor=K}let $=y[k].mesh&&y[k].mesh.length>200?Qo(y[k],[t.shape[2],t.shape[1]]):null;e.analyze("Start Emotion:"),e.config.async?s=(u=e.config.face.emotion)!=null&&u.enabled?x1(y[k].tensor||s0.tensor([]),e.config,k,y.length):[]:(e.state="run:emotion",o=h(),s=(m=e.config.face.emotion)!=null&&m.enabled?await x1(y[k].tensor||s0.tensor([]),e.config,k,y.length):[],e.performance.emotion=v.perfadd?(e.performance.emotion||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Emotion:"),e.analyze("Start AntiSpoof:"),e.config.async?i=(P=e.config.face.antispoof)!=null&&P.enabled?q5(y[k].tensor||s0.tensor([]),e.config,k,y.length):0:(e.state="run:antispoof",o=h(),i=(g=e.config.face.antispoof)!=null&&g.enabled?await q5(y[k].tensor||s0.tensor([]),e.config,k,y.length):0,e.performance.antispoof=v.perfadd?(e.performance.antispoof||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End AntiSpoof:"),e.analyze("Start Liveness:"),e.config.async?x=(b=e.config.face.liveness)!=null&&b.enabled?C1(y[k].tensor||s0.tensor([]),e.config,k,y.length):0:(e.state="run:liveness",o=h(),x=(d=e.config.face.liveness)!=null&&d.enabled?await C1(y[k].tensor||s0.tensor([]),e.config,k,y.length):0,e.performance.liveness=v.perfadd?(e.performance.antispoof||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Liveness:"),e.analyze("Start GEAR:"),e.config.async?r=(M=e.config.face.gear)!=null&&M.enabled?G5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null:(e.state="run:gear",o=h(),r=(S=e.config.face.gear)!=null&&S.enabled?await G5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,e.performance.gear=Math.trunc(h()-o)),e.analyze("End GEAR:"),e.analyze("Start SSRNet:"),e.config.async?(n=(w=e.config.face.ssrnet)!=null&&w.enabled?H5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,A=(j=e.config.face.ssrnet)!=null&&j.enabled?Z5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null):(e.state="run:ssrnet",o=h(),n=(C=e.config.face.ssrnet)!=null&&C.enabled?await H5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,A=(F=e.config.face.ssrnet)!=null&&F.enabled?await Z5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,e.performance.ssrnet=Math.trunc(h()-o)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?a=(H=e.config.face.mobilefacenet)!=null&&H.enabled?d1(y[k].tensor||s0.tensor([]),e.config,k,y.length):null:(e.state="run:mobilefacenet",o=h(),a=(Y=e.config.face.mobilefacenet)!=null&&Y.enabled?await d1(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,e.performance.mobilefacenet=Math.trunc(h()-o)),e.analyze("End MobileFaceNet:"),e.analyze("Start Description:"),e.config.async?c=(J=e.config.face.description)!=null&&J.enabled?b1(y[k].tensor||s0.tensor([]),e.config,k,y.length):null:(e.state="run:description",o=h(),c=(x0=e.config.face.description)!=null&&x0.enabled?await b1(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,e.performance.description=v.perfadd?(e.performance.description||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Description:"),e.config.async&&([n,A,s,a,c,r,i,x]=await Promise.all([n,A,s,a,c,r,i,x])),e.analyze("Finish Face:"),((E=e.config.face.ssrnet)==null?void 0:E.enabled)&&n&&A&&(c={...c,age:n.age,gender:A.gender,genderScore:A.genderScore}),((G0=e.config.face.gear)==null?void 0:G0.enabled)&&r&&(c={...c,age:r.age,gender:r.gender,genderScore:r.genderScore,race:r.race}),((B0=e.config.face.mobilefacenet)==null?void 0:B0.enabled)&&a&&(c.descriptor=a),(R=e.config.face.iris)!=null&&R.enabled;let a0=y[k].annotations&&y[k].annotations.leftEyeIris&&y[k].annotations.leftEyeIris[0]&&y[k].annotations.rightEyeIris&&y[k].annotations.rightEyeIris[0]&&y[k].annotations.leftEyeIris.length>0&&y[k].annotations.rightEyeIris.length>0&&y[k].annotations.leftEyeIris[0]!==null&&y[k].annotations.rightEyeIris[0]!==null?Math.max(Math.abs(y[k].annotations.leftEyeIris[3][0]-y[k].annotations.leftEyeIris[1][0]),Math.abs(y[k].annotations.rightEyeIris[4][1]-y[k].annotations.rightEyeIris[2][1]))/t.shape[2]:0,f0=(c0=e.config.face.detector)!=null&&c0.return?s0.squeeze(y[k].tensor):null;s0.dispose(y[k].tensor),y[k].tensor&&delete y[k].tensor;let L={...y[k],id:k};c!=null&&c.age&&(L.age=c.age),c!=null&&c.gender&&(L.gender=c.gender),c!=null&&c.genderScore&&(L.genderScore=c==null?void 0:c.genderScore),c!=null&&c.descriptor&&(L.embedding=c==null?void 0:c.descriptor),c!=null&&c.race&&(L.race=c==null?void 0:c.race),s&&(L.emotion=s),i&&(L.real=i),x&&(L.live=x),a0&&a0!==0&&(L.iris=Math.trunc(500/a0/11.7)/100),$&&(L.rotation=$),f0&&(L.tensor=f0),l.push(L),e.analyze("End Face")}return e.analyze("End FaceMesh:"),e.config.async&&(e.performance.face&&delete e.performance.face,e.performance.age&&delete e.performance.age,e.performance.gender&&delete e.performance.gender,e.performance.emotion&&delete e.performance.emotion),l};var _o=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=e[o].keypoints.find(i=>i.part==="leftWrist"),r=e[o].keypoints.find(i=>i.part==="rightWrist"),A=e[o].keypoints.find(i=>i.part==="nose");A&&n&&r&&n.position[1]<A.position[1]&&r.position[1]<A.position[1]?t.push({body:o,gesture:"i give up"}):A&&n&&n.position[1]<A.position[1]?t.push({body:o,gesture:"raise left hand"}):A&&r&&r.position[1]<A.position[1]&&t.push({body:o,gesture:"raise right hand"});let s=e[o].keypoints.find(i=>i.part==="leftShoulder"),a=e[o].keypoints.find(i=>i.part==="rightShoulder");s&&a&&Math.abs(s.positionRaw[1]-a.positionRaw[1])>.1&&t.push({body:o,gesture:`leaning ${s.position[1]>a.position[1]?"left":"right"}`})}return t},$o=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++)if(e[o].mesh&&e[o].mesh.length>450){let n=(e[o].mesh[33][2]||0)-(e[o].mesh[263][2]||0),r=e[o].mesh[33][0]-e[o].mesh[263][0];Math.abs(n/r)<=.15?t.push({face:o,gesture:"facing center"}):t.push({face:o,gesture:`facing ${n<0?"left":"right"}`}),Math.abs(e[o].mesh[374][1]-e[o].mesh[386][1])/Math.abs(e[o].mesh[443][1]-e[o].mesh[450][1])<.2&&t.push({face:o,gesture:"blink left eye"}),Math.abs(e[o].mesh[145][1]-e[o].mesh[159][1])/Math.abs(e[o].mesh[223][1]-e[o].mesh[230][1])<.2&&t.push({face:o,gesture:"blink right eye"});let a=Math.min(100,500*Math.abs(e[o].mesh[13][1]-e[o].mesh[14][1])/Math.abs(e[o].mesh[10][1]-e[o].mesh[152][1]));a>10&&t.push({face:o,gesture:`mouth ${Math.trunc(a)}% open`});let i=e[o].mesh[152][2]||0;Math.abs(i)>10&&t.push({face:o,gesture:`head ${i<0?"up":"down"}`})}return t},en=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){if(!e[o].annotations||!e[o].annotations.leftEyeIris||!e[o].annotations.leftEyeIris[0]||!e[o].annotations.rightEyeIris||!e[o].annotations.rightEyeIris[0])continue;let n=e[o].annotations.leftEyeIris[3][0]-e[o].annotations.leftEyeIris[1][0],r=e[o].annotations.leftEyeIris[4][1]-e[o].annotations.leftEyeIris[2][1],A=Math.abs(n*r),s=e[o].annotations.rightEyeIris[3][0]-e[o].annotations.rightEyeIris[1][0],a=e[o].annotations.rightEyeIris[4][1]-e[o].annotations.rightEyeIris[2][1],i=Math.abs(s*a),x=!1;Math.abs(A-i)/Math.max(A,i)<.25&&(x=!0,t.push({iris:o,gesture:"facing center"}));let l=Math.abs(e[o].mesh[263][0]-e[o].annotations.leftEyeIris[0][0])/e[o].box[2],y=Math.abs(e[o].mesh[33][0]-e[o].annotations.rightEyeIris[0][0])/e[o].box[2];(l>.06||y>.06)&&(x=!1),l>y?l>.05&&t.push({iris:o,gesture:"looking right"}):y>.05&&t.push({iris:o,gesture:"looking left"});let f=Math.abs(e[o].mesh[145][1]-e[o].annotations.rightEyeIris[0][1])/e[o].box[3],u=Math.abs(e[o].mesh[374][1]-e[o].annotations.leftEyeIris[0][1])/e[o].box[3];(u<.01||f<.01||u>.022||f>.022)&&(x=!1),(u<.01||f<.01)&&t.push({iris:o,gesture:"looking down"}),(u>.022||f>.022)&&t.push({iris:o,gesture:"looking up"}),x&&t.push({iris:o,gesture:"looking center"})}return t},tn=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=[];if(e[o].annotations)for(let[r,A]of Object.entries(e[o].annotations))r!=="palmBase"&&Array.isArray(A)&&A[0]&&n.push({name:r.toLowerCase(),position:A[0]});if(n&&n.length>0){let r=n.reduce((s,a)=>(s.position[2]||0)<(a.position[2]||0)?s:a);t.push({hand:o,gesture:`${r.name} forward`});let A=n.reduce((s,a)=>s.position[1]<a.position[1]?s:a);t.push({hand:o,gesture:`${A.name} up`})}if(e[o].keypoints){let r=xo(e[o].keypoints);for(let A of r)t.push({hand:o,gesture:A.name})}}return t};var z={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null},At=0;function on(e,t){var s,a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0;let o=h();if(!e)return{face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null};let n=Date.now()-e.timestamp,r=n<1e3?8-Math.log(n+1):1;if(e.canvas&&(z.canvas=e.canvas),e.error&&(z.error=e.error),!z.body||e.body.length!==z.body.length)z.body=JSON.parse(JSON.stringify(e.body));else for(let R=0;R<e.body.length;R++){let c0=e.body[R].box.map((L,K)=>((r-1)*z.body[R].box[K]+L)/r),k=e.body[R].boxRaw.map((L,K)=>((r-1)*z.body[R].boxRaw[K]+L)/r),$=e.body[R].keypoints.map((L,K)=>{var Ae,se,p2,u2,qe,yt,xt,ct,dt;return{score:L.score,part:L.part,position:[z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[0]||0)+(L.position[0]||0))/r:L.position[0],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[1]||0)+(L.position[1]||0))/r:L.position[1],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[2]||0)+(L.position[2]||0))/r:L.position[2]],positionRaw:[z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[0]||0)+(L.positionRaw[0]||0))/r:L.positionRaw[0],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[1]||0)+(L.positionRaw[1]||0))/r:L.positionRaw[1],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[2]||0)+(L.positionRaw[2]||0))/r:L.positionRaw[2]],distance:[z.body[R].keypoints[K]?((r-1)*(((Ae=z.body[R].keypoints[K].distance)==null?void 0:Ae[0])||0)+(((se=L.distance)==null?void 0:se[0])||0))/r:(p2=L.distance)==null?void 0:p2[0],z.body[R].keypoints[K]?((r-1)*(((u2=z.body[R].keypoints[K].distance)==null?void 0:u2[1])||0)+(((qe=L.distance)==null?void 0:qe[1])||0))/r:(yt=L.distance)==null?void 0:yt[1],z.body[R].keypoints[K]?((r-1)*(((xt=z.body[R].keypoints[K].distance)==null?void 0:xt[2])||0)+(((ct=L.distance)==null?void 0:ct[2])||0))/r:(dt=L.distance)==null?void 0:dt[2]]}}),a0={},f0={connected:{}};(a=(s=t.body)==null?void 0:s.modelPath)!=null&&a.includes("efficientpose")?f0=t5:(x=(i=t.body)==null?void 0:i.modelPath)!=null&&x.includes("blazepose")?f0=J2:(l=(c=t.body)==null?void 0:c.modelPath)!=null&&l.includes("movenet")&&(f0=E2);for(let[L,K]of Object.entries(f0.connected)){let Ae=[];for(let se=0;se<K.length-1;se++){let p2=$.find(qe=>qe.part===K[se]),u2=$.find(qe=>qe.part===K[se+1]);p2&&u2&&Ae.push([p2.position,u2.position])}a0[L]=Ae}z.body[R]={...e.body[R],box:c0,boxRaw:k,keypoints:$,annotations:a0}}if(!z.hand||e.hand.length!==z.hand.length)z.hand=JSON.parse(JSON.stringify(e.hand));else for(let R=0;R<e.hand.length;R++){let c0=e.hand[R].box.map((f0,L)=>((r-1)*z.hand[R].box[L]+f0)/r),k=e.hand[R].boxRaw.map((f0,L)=>((r-1)*z.hand[R].boxRaw[L]+f0)/r);z.hand[R].keypoints.length!==e.hand[R].keypoints.length&&(z.hand[R].keypoints=e.hand[R].keypoints);let $=e.hand[R].keypoints&&e.hand[R].keypoints.length>0?e.hand[R].keypoints.map((f0,L)=>f0.map((K,Ae)=>((r-1)*(z.hand[R].keypoints[L][Ae]||1)+(K||0))/r)):[],a0={};if(Object.keys(z.hand[R].annotations).length!==Object.keys(e.hand[R].annotations).length)z.hand[R].annotations=e.hand[R].annotations,a0=z.hand[R].annotations;else if(e.hand[R].annotations)for(let f0 of Object.keys(e.hand[R].annotations))a0[f0]=e.hand[R].annotations[f0]&&e.hand[R].annotations[f0][0]?e.hand[R].annotations[f0].map((L,K)=>L.map((Ae,se)=>((r-1)*z.hand[R].annotations[f0][K][se]+Ae)/r)):null;z.hand[R]={...e.hand[R],box:c0,boxRaw:k,keypoints:$,annotations:a0}}if(!z.face||e.face.length!==z.face.length)z.face=JSON.parse(JSON.stringify(e.face));else for(let R=0;R<e.face.length;R++){let c0=e.face[R].box.map(($,a0)=>((r-1)*z.face[R].box[a0]+$)/r),k=e.face[R].boxRaw.map(($,a0)=>((r-1)*z.face[R].boxRaw[a0]+$)/r);if(e.face[R].rotation){let $={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};$.matrix=(y=e.face[R].rotation)==null?void 0:y.matrix,$.angle={roll:((r-1)*(((u=(f=z.face[R].rotation)==null?void 0:f.angle)==null?void 0:u.roll)||0)+(((P=(m=e.face[R].rotation)==null?void 0:m.angle)==null?void 0:P.roll)||0))/r,yaw:((r-1)*(((b=(g=z.face[R].rotation)==null?void 0:g.angle)==null?void 0:b.yaw)||0)+(((M=(d=e.face[R].rotation)==null?void 0:d.angle)==null?void 0:M.yaw)||0))/r,pitch:((r-1)*(((w=(S=z.face[R].rotation)==null?void 0:S.angle)==null?void 0:w.pitch)||0)+(((C=(j=e.face[R].rotation)==null?void 0:j.angle)==null?void 0:C.pitch)||0))/r},$.gaze={bearing:((r-1)*(((H=(F=z.face[R].rotation)==null?void 0:F.gaze)==null?void 0:H.bearing)||0)+(((J=(Y=e.face[R].rotation)==null?void 0:Y.gaze)==null?void 0:J.bearing)||0))/r,strength:((r-1)*(((E=(x0=z.face[R].rotation)==null?void 0:x0.gaze)==null?void 0:E.strength)||0)+(((B0=(G0=e.face[R].rotation)==null?void 0:G0.gaze)==null?void 0:B0.strength)||0))/r},z.face[R]={...e.face[R],rotation:$,box:c0,boxRaw:k}}z.face[R]={...e.face[R],box:c0,boxRaw:k}}if(!z.object||e.object.length!==z.object.length)z.object=JSON.parse(JSON.stringify(e.object));else for(let R=0;R<e.object.length;R++){let c0=e.object[R].box.map(($,a0)=>((r-1)*z.object[R].box[a0]+$)/r),k=e.object[R].boxRaw.map(($,a0)=>((r-1)*z.object[R].boxRaw[a0]+$)/r);z.object[R]={...e.object[R],box:c0,boxRaw:k}}if(e.persons){let R=e.persons;if(!z.persons||R.length!==z.persons.length)z.persons=JSON.parse(JSON.stringify(R));else for(let c0=0;c0<R.length;c0++)z.persons[c0].box=R[c0].box.map((k,$)=>((r-1)*z.persons[c0].box[$]+k)/r)}e.gesture&&(z.gesture=e.gesture);let A=h();return At=v.perfadd?At+Math.round(A-o):Math.round(A-o),e.performance&&(z.performance={...e.performance,interpolate:At}),z}var it={};ue(it,{distance:()=>j2,match:()=>at,similarity:()=>st});function j2(e,t,o={order:2,multiplier:25}){let n=0;for(let r=0;r<e.length;r++){let A=!o.order||o.order===2?e[r]-t[r]:Math.abs(e[r]-t[r]);n+=!o.order||o.order===2?A*A:A**o.order}return(o.multiplier||20)*n}var nn=(e,t,o,n)=>{if(e===0)return 1;let r=t===2?Math.sqrt(e):e**(1/t),A=(1-r/100-o)/(n-o);return Math.max(Math.min(A,1),0)};function st(e,t,o={order:2,multiplier:25,min:.2,max:.8}){let n=j2(e,t,o);return nn(n,o.order||2,o.min||0,o.max||1)}function at(e,t,o={order:2,multiplier:25,threshold:0,min:.2,max:.8}){if(!Array.isArray(e)||!Array.isArray(t)||e.length<64||t.length===0||e.length!==t[0].length)return{index:-1,distance:Number.POSITIVE_INFINITY,similarity:0};let n=Number.MAX_SAFE_INTEGER,r=-1;for(let s=0;s<t.length;s++){let a=j2(e,t[s],o);if(a<n&&(n=a,r=s),n<(o.threshold||0))break}let A=nn(n,o.order||2,o.min||0,o.max||1);return{index:r,distance:n,similarity:A}}function rn(e,t,o,n,r){var a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w;let A=0,s=[];for(let j of e){let C={id:A++,face:j,body:null,hands:{left:null,right:null},gestures:[],box:[0,0,0,0]};for(let E of t)j.box[0]>E.box[0]&&j.box[0]<E.box[0]+E.box[2]&&j.box[1]+j.box[3]>E.box[1]&&j.box[1]+j.box[3]<E.box[1]+E.box[3]&&(C.body=E);if(C.body)for(let E of o)E.box[0]+E.box[2]>C.body.box[0]&&E.box[0]+E.box[2]<C.body.box[0]+C.body.box[2]&&E.box[1]+E.box[3]>C.body.box[1]&&E.box[1]+E.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.left=E),E.box[0]<C.body.box[0]+C.body.box[2]&&E.box[0]>C.body.box[0]&&E.box[1]+E.box[3]>C.body.box[1]&&E.box[1]+E.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.right=E);for(let E of n)E.face!==void 0&&E.face===j.id?(a=C.gestures)==null||a.push(E):E.iris!==void 0&&E.iris===j.id?(i=C.gestures)==null||i.push(E):E.body!==void 0&&E.body===((x=C.body)==null?void 0:x.id)?(c=C.gestures)==null||c.push(E):E.hand!==void 0&&E.hand===((y=(l=C.hands)==null?void 0:l.left)==null?void 0:y.id)?(f=C.gestures)==null||f.push(E):E.hand!==void 0&&E.hand===((m=(u=C.hands)==null?void 0:u.right)==null?void 0:m.id)&&((P=C.gestures)==null||P.push(E));let F=[],H=[],Y=E=>{E&&E.length===4&&(F.push(E[0],E[0]+E[2]),H.push(E[1],E[1]+E[3]))};Y((g=C.face)==null?void 0:g.box),Y((b=C.body)==null?void 0:b.box),Y((M=(d=C.hands)==null?void 0:d.left)==null?void 0:M.box),Y((w=(S=C.hands)==null?void 0:S.right)==null?void 0:w.box);let J=Math.min(...F),x0=Math.min(...H);C.box=[J,x0,Math.max(...F)-J,Math.max(...H)-x0],r&&r[1]&&r[2]&&(C.boxRaw=[C.box[0]/r[2],C.box[1]/r[1],C.box[2]/r[2],C.box[3]/r[1]]),s.push(C)}return s}var w5=`
+    `);t.stroke(s),t.stroke(A)}}function qA(e,t){var o,n,r,A;if(U.drawGaze&&((n=(o=e.rotation)==null?void 0:o.gaze)==null?void 0:n.strength)&&((A=(r=e.rotation)==null?void 0:r.gaze)==null?void 0:A.bearing)&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let s=[e.annotations.leftEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.leftEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];Q1(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[s[0],s[1]],4);let a=[e.annotations.rightEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.rightEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];Q1(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[a[0],a[1]],4)}}function UA(e,t){if(U.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let o=0;o<Oe.length/3;o++){let n=[Oe[o*3+0],Oe[o*3+1],Oe[o*3+2]].map(r=>e.mesh[r]);J1(t,n,U)}ZA(e,t)}}function YA(e,t){if(U.drawPoints&&e.mesh.length>=468)for(let o=0;o<e.mesh.length;o++)pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2],U),U.drawAttention&&(w2.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]+127,U),We.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,U),Fe.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,U))}function KA(e,t){U.drawBoxes&&re(t,e.box[0],e.box[1],e.box[2],e.box[3],U)}async function l2(e,t,o){if(U=r0(P0,o),!t||!e)return;let n=V0(e);if(!!n){n.font=U.font,n.strokeStyle=U.color,n.fillStyle=U.color;for(let r of t)KA(r,n),DA(r,n),r.mesh&&r.mesh.length>0&&(YA(r,n),UA(r,n),XA(r,n),qA(r,n))}}async function y2(e,t,o){var A;let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round";for(let s=0;s<t.length;s++){if(r.strokeStyle=n.color,r.fillStyle=n.color,r.lineWidth=n.lineWidth,r.font=n.font,n.drawBoxes&&t[s].box&&((A=t[s].box)==null?void 0:A.length)===4&&(re(r,t[s].box[0],t[s].box[1],t[s].box[2],t[s].box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`body ${100*t[s].score}%`,t[s].box[0]+3,1+t[s].box[1]+n.lineHeight,t[s].box[2])),r.fillStyle=n.labelColor,r.fillText(`body ${100*t[s].score}%`,t[s].box[0]+2,0+t[s].box[1]+n.lineHeight,t[s].box[2]))),n.drawPoints&&t[s].keypoints)for(let a=0;a<t[s].keypoints.length;a++)!t[s].keypoints[a].score||t[s].keypoints[a].score===0||(r.fillStyle=me(t[s].keypoints[a].position[2],n),pe(r,t[s].keypoints[a].position[0],t[s].keypoints[a].position[1],0,n));if(n.drawLabels&&t[s].keypoints){r.font=n.font;for(let a of t[s].keypoints)!a.score||a.score===0||(r.fillStyle=me(a.position[2],n),r.fillText(`${a.part} ${Math.trunc(100*a.score)}%`,a.position[0]+4,a.position[1]+4))}if(n.drawPolygons&&t[s].keypoints&&t[s].annotations)for(let a of Object.values(t[s].annotations))for(let i of a)Yo(r,i,n)}}}async function x2(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A of t){if(n.drawBoxes&&(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,A.box[0],A.box[1],A.box[2],A.box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`hand:${Math.trunc(100*A.score)}%`,A.box[0]+3,1+A.box[1]+n.lineHeight,A.box[2])),r.fillStyle=n.labelColor,r.fillText(`hand:${Math.trunc(100*A.score)}%`,A.box[0]+2,0+A.box[1]+n.lineHeight,A.box[2])),r.stroke()),n.drawPoints&&A.keypoints&&A.keypoints.length>0)for(let s of A.keypoints)r.fillStyle=me(s[2],n),pe(r,s[0],s[1],0,n);if(n.drawLabels&&A.annotations){let s=(a,i)=>{if(!a||a.length===0||!a[0])return;let x=a[a.length-1][2]||-256;r.fillStyle=me(x,n),r.fillText(i,a[a.length-1][0]+4,a[a.length-1][1]+4)};r.font=n.font,s(A.annotations.index,"index"),s(A.annotations.middle,"middle"),s(A.annotations.ring,"ring"),s(A.annotations.pinky,"pinky"),s(A.annotations.thumb,"thumb"),s(A.annotations.palm,"palm")}if(n.drawPolygons&&A.annotations){let s=a=>{if(!(!a||a.length===0||!a[0]))for(let i=0;i<a.length;i++){r.beginPath();let x=a[i][2]||0;r.strokeStyle=me(i*x,n),r.moveTo(a[i>0?i-1:0][0],a[i>0?i-1:0][1]),r.lineTo(a[i][0],a[i][1]),r.stroke()}};r.lineWidth=n.lineWidth,s(A.annotations.index),s(A.annotations.middle),s(A.annotations.ring),s(A.annotations.pinky),s(A.annotations.thumb)}}}}async function c2(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A of t)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,A.box[0],A.box[1],A.box[2],A.box[3],n),n.drawLabels){let s=`${A.label} ${Math.round(100*A.score)}%`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(s,A.box[0]+3,1+A.box[1]+n.lineHeight,A.box[2])),r.fillStyle=n.labelColor,r.fillText(s,A.box[0]+2,0+A.box[1]+n.lineHeight,A.box[2])}r.stroke()}}}async function d2(e,t,o){let n=r0(P0,o);if(!(!t||!e)&&n.drawGestures){let r=V0(e);if(!r)return;r.font=n.font,r.fillStyle=n.color;let A=1;for(let s=0;s<t.length;s++){let a=[],i=[];if([a,i]=Object.entries(t[s]),i.length>1&&i[1].length>0){let x=a[1]>0?`#${a[1]}`:"",c=`${a[0]} ${x}: ${i[1]}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(c,8,2+A*n.lineHeight)),r.fillStyle=n.labelColor,r.fillText(c,6,0+A*n.lineHeight),A+=1}}}}var _1=0;async function $1(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A=0;A<t.length;A++)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,t[A].box[0],t[A].box[1],t[A].box[2],t[A].box[3],n),n.drawLabels){let s=`person #${A}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(s,t[A].box[0]+3,1+t[A].box[1]+n.lineHeight,t[A].box[2])),r.fillStyle=n.labelColor,r.fillText(s,t[A].box[0]+2,0+t[A].box[1]+n.lineHeight,t[A].box[2])}r.stroke()}}}async function et(e,t){if(!e||!t)return;let o=V0(t);!o||o.drawImage(e,0,0)}async function tt(e,t,o){if(!t||!t.performance||!t||!e)return null;let n=h(),r=r0(P0,o),A=Promise.all([l2(e,t.face,r),y2(e,t.body,r),x2(e,t.hand,r),c2(e,t.object,r),d2(e,t.gesture,r)]);return _1=v.perfadd?_1+Math.round(h()-n):Math.round(h()-n),t.performance.draw=_1,A}var a0=Z(D());var Ko=Z(D());var f2=.1,nt=.5;function JA(e,t,o){let n=!1,r=o.length-1;for(let A=0;A<o.length;r=A++)o[A].y>t!=o[r].y>t&&e<(o[r].x-o[A].x)*(t-o[A].y)/(o[r].y-o[A].y)+o[A].x&&(n=!n);return n}async function Jo(e){if(!e.tensor||!e.mesh||e.mesh.length<100)return e.tensor;let t=e.tensor.shape[2]||0,o=e.tensor.shape[1]||0,n=await e.tensor.buffer(),r=[];for(let s of X0.silhouette)r.push({x:(e.mesh[s][0]-e.box[0])/e.box[2],y:(e.mesh[s][1]-e.box[1])/e.box[3]});f2&&f2>0&&(r=r.map(s=>({x:s.x>.5?s.x+f2:s.x-f2,y:s.y>.5?s.y+f2:s.y-f2})));for(let s=0;s<t;s++)for(let a=0;a<o;a++)JA(s/t,a/t,r)||(n.set(nt*n.get(0,a,s,0),0,a,s,0),n.set(nt*n.get(0,a,s,1),0,a,s,1),n.set(nt*n.get(0,a,s,2),0,a,s,2));let A=n.toTensor();return Ko.dispose(n),A}var _A=e=>{let t=(l,y)=>Math.atan2(l[1]-y[1],l[0]-y[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let o=[0,-.1],n=1,r=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),A=r?e.mesh[473]:e.mesh[468],s=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],a=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],i=[(s[0]-A[0])/a[0]-o[0],n*(A[1]-s[1])/a[1]-o[1]],x=Math.sqrt(i[0]*i[0]+i[1]*i[1]);return x=Math.min(x,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],i)+Math.PI/2)%Math.PI,strength:x}},Qo=(e,t)=>{let o=m=>{let P=Math.sqrt(m[0]*m[0]+m[1]*m[1]+m[2]*m[2]);return m[0]/=P,m[1]/=P,m[2]/=P,m},n=(m,P)=>{let g=m[0]-P[0],b=m[1]-P[1],d=m[2]-P[2];return[g,b,d]},r=(m,P)=>{let g=m[1]*P[2]-m[2]*P[1],b=m[2]*P[0]-m[0]*P[2],d=m[0]*P[1]-m[1]*P[0];return[g,b,d]},A=m=>{let[P,g,b,d,M,S,w,j,C]=m,F,H,Y;return d<1?d>-1?(Y=Math.asin(d),H=Math.atan2(-w,P),F=Math.atan2(-S,M)):(Y=-Math.PI/2,H=-Math.atan2(j,C),F=0):(Y=Math.PI/2,H=Math.atan2(j,C),F=0),isNaN(F)&&(F=0),isNaN(H)&&(H=0),isNaN(Y)&&(Y=0),{pitch:2*-F,yaw:2*-H,roll:2*-Y}},s=e.meshRaw;if(!s||s.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let a=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,i=[s[10],s[152],s[234],s[454]].map(m=>[m[0]*t[0]/a,m[1]*t[1]/a,m[2]]),x=o(n(i[1],i[0])),c=o(n(i[3],i[2])),l=o(r(c,x));c=r(x,l);let y=[c[0],c[1],c[2],x[0],x[1],x[2],l[0],l[1],l[2]],f=A(y),u=s.length===478?_A(e):{bearing:0,strength:0};return{angle:f,matrix:y,gaze:u}};var rt=async(e,t)=>{var f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0,R,c0;let o=h(),n,r,A,s,a,i,x,c,l=[];e.state="run:face";let y=await G3(t,e.config);if(e.performance.face=v.perfadd?(e.performance.face||0)+Math.trunc(h()-o):Math.trunc(h()-o),!t.shape||t.shape.length!==4)return[];if(!y)return[];for(let k=0;k<y.length;k++){if(e.analyze("Get Face"),!y[k].tensor||y[k].tensor.isDisposedInternal){p("Face object is disposed:",y[k].tensor);continue}if((f=e.config.face.detector)!=null&&f.mask){let K=await Jo(y[k]);a0.dispose(y[k].tensor),y[k].tensor=K}let $=y[k].mesh&&y[k].mesh.length>200?Qo(y[k],[t.shape[2],t.shape[1]]):null;e.analyze("Start Emotion:"),e.config.async?s=(u=e.config.face.emotion)!=null&&u.enabled?x1(y[k].tensor||a0.tensor([]),e.config,k,y.length):[]:(e.state="run:emotion",o=h(),s=(m=e.config.face.emotion)!=null&&m.enabled?await x1(y[k].tensor||a0.tensor([]),e.config,k,y.length):[],e.performance.emotion=v.perfadd?(e.performance.emotion||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Emotion:"),e.analyze("Start AntiSpoof:"),e.config.async?i=(P=e.config.face.antispoof)!=null&&P.enabled?q5(y[k].tensor||a0.tensor([]),e.config,k,y.length):0:(e.state="run:antispoof",o=h(),i=(g=e.config.face.antispoof)!=null&&g.enabled?await q5(y[k].tensor||a0.tensor([]),e.config,k,y.length):0,e.performance.antispoof=v.perfadd?(e.performance.antispoof||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End AntiSpoof:"),e.analyze("Start Liveness:"),e.config.async?x=(b=e.config.face.liveness)!=null&&b.enabled?C1(y[k].tensor||a0.tensor([]),e.config,k,y.length):0:(e.state="run:liveness",o=h(),x=(d=e.config.face.liveness)!=null&&d.enabled?await C1(y[k].tensor||a0.tensor([]),e.config,k,y.length):0,e.performance.liveness=v.perfadd?(e.performance.antispoof||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Liveness:"),e.analyze("Start GEAR:"),e.config.async?r=(M=e.config.face.gear)!=null&&M.enabled?G5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null:(e.state="run:gear",o=h(),r=(S=e.config.face.gear)!=null&&S.enabled?await G5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,e.performance.gear=Math.trunc(h()-o)),e.analyze("End GEAR:"),e.analyze("Start SSRNet:"),e.config.async?(n=(w=e.config.face.ssrnet)!=null&&w.enabled?H5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,A=(j=e.config.face.ssrnet)!=null&&j.enabled?Z5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null):(e.state="run:ssrnet",o=h(),n=(C=e.config.face.ssrnet)!=null&&C.enabled?await H5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,A=(F=e.config.face.ssrnet)!=null&&F.enabled?await Z5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,e.performance.ssrnet=Math.trunc(h()-o)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?a=(H=e.config.face.mobilefacenet)!=null&&H.enabled?d1(y[k].tensor||a0.tensor([]),e.config,k,y.length):null:(e.state="run:mobilefacenet",o=h(),a=(Y=e.config.face.mobilefacenet)!=null&&Y.enabled?await d1(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,e.performance.mobilefacenet=Math.trunc(h()-o)),e.analyze("End MobileFaceNet:"),e.analyze("Start Description:"),e.config.async?c=(J=e.config.face.description)!=null&&J.enabled?b1(y[k].tensor||a0.tensor([]),e.config,k,y.length):null:(e.state="run:description",o=h(),c=(x0=e.config.face.description)!=null&&x0.enabled?await b1(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,e.performance.description=v.perfadd?(e.performance.description||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Description:"),e.config.async&&([n,A,s,a,c,r,i,x]=await Promise.all([n,A,s,a,c,r,i,x])),e.analyze("Finish Face:"),((E=e.config.face.ssrnet)==null?void 0:E.enabled)&&n&&A&&(c={...c,age:n.age,gender:A.gender,genderScore:A.genderScore}),((G0=e.config.face.gear)==null?void 0:G0.enabled)&&r&&(c={...c,age:r.age,gender:r.gender,genderScore:r.genderScore,race:r.race}),((B0=e.config.face.mobilefacenet)==null?void 0:B0.enabled)&&a&&(c.descriptor=a),(R=e.config.face.iris)!=null&&R.enabled;let i0=y[k].annotations&&y[k].annotations.leftEyeIris&&y[k].annotations.leftEyeIris[0]&&y[k].annotations.rightEyeIris&&y[k].annotations.rightEyeIris[0]&&y[k].annotations.leftEyeIris.length>0&&y[k].annotations.rightEyeIris.length>0&&y[k].annotations.leftEyeIris[0]!==null&&y[k].annotations.rightEyeIris[0]!==null?Math.max(Math.abs(y[k].annotations.leftEyeIris[3][0]-y[k].annotations.leftEyeIris[1][0]),Math.abs(y[k].annotations.rightEyeIris[4][1]-y[k].annotations.rightEyeIris[2][1]))/t.shape[2]:0,m0=(c0=e.config.face.detector)!=null&&c0.return?a0.squeeze(y[k].tensor):null;a0.dispose(y[k].tensor),y[k].tensor&&delete y[k].tensor;let L={...y[k],id:k};c!=null&&c.age&&(L.age=c.age),c!=null&&c.gender&&(L.gender=c.gender),c!=null&&c.genderScore&&(L.genderScore=c==null?void 0:c.genderScore),c!=null&&c.descriptor&&(L.embedding=c==null?void 0:c.descriptor),c!=null&&c.race&&(L.race=c==null?void 0:c.race),s&&(L.emotion=s),i&&(L.real=i),x&&(L.live=x),i0&&i0!==0&&(L.iris=Math.trunc(500/i0/11.7)/100),$&&(L.rotation=$),m0&&(L.tensor=m0),l.push(L),e.analyze("End Face")}return e.analyze("End FaceMesh:"),e.config.async&&(e.performance.face&&delete e.performance.face,e.performance.age&&delete e.performance.age,e.performance.gender&&delete e.performance.gender,e.performance.emotion&&delete e.performance.emotion),l};var _o=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=e[o].keypoints.find(i=>i.part==="leftWrist"),r=e[o].keypoints.find(i=>i.part==="rightWrist"),A=e[o].keypoints.find(i=>i.part==="nose");A&&n&&r&&n.position[1]<A.position[1]&&r.position[1]<A.position[1]?t.push({body:o,gesture:"i give up"}):A&&n&&n.position[1]<A.position[1]?t.push({body:o,gesture:"raise left hand"}):A&&r&&r.position[1]<A.position[1]&&t.push({body:o,gesture:"raise right hand"});let s=e[o].keypoints.find(i=>i.part==="leftShoulder"),a=e[o].keypoints.find(i=>i.part==="rightShoulder");s&&a&&Math.abs(s.positionRaw[1]-a.positionRaw[1])>.1&&t.push({body:o,gesture:`leaning ${s.position[1]>a.position[1]?"left":"right"}`})}return t},$o=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++)if(e[o].mesh&&e[o].mesh.length>450){let n=(e[o].mesh[33][2]||0)-(e[o].mesh[263][2]||0),r=e[o].mesh[33][0]-e[o].mesh[263][0];Math.abs(n/r)<=.15?t.push({face:o,gesture:"facing center"}):t.push({face:o,gesture:`facing ${n<0?"left":"right"}`}),Math.abs(e[o].mesh[374][1]-e[o].mesh[386][1])/Math.abs(e[o].mesh[443][1]-e[o].mesh[450][1])<.2&&t.push({face:o,gesture:"blink left eye"}),Math.abs(e[o].mesh[145][1]-e[o].mesh[159][1])/Math.abs(e[o].mesh[223][1]-e[o].mesh[230][1])<.2&&t.push({face:o,gesture:"blink right eye"});let a=Math.min(100,500*Math.abs(e[o].mesh[13][1]-e[o].mesh[14][1])/Math.abs(e[o].mesh[10][1]-e[o].mesh[152][1]));a>10&&t.push({face:o,gesture:`mouth ${Math.trunc(a)}% open`});let i=e[o].mesh[152][2]||0;Math.abs(i)>10&&t.push({face:o,gesture:`head ${i<0?"up":"down"}`})}return t},en=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){if(!e[o].annotations||!e[o].annotations.leftEyeIris||!e[o].annotations.leftEyeIris[0]||!e[o].annotations.rightEyeIris||!e[o].annotations.rightEyeIris[0])continue;let n=e[o].annotations.leftEyeIris[3][0]-e[o].annotations.leftEyeIris[1][0],r=e[o].annotations.leftEyeIris[4][1]-e[o].annotations.leftEyeIris[2][1],A=Math.abs(n*r),s=e[o].annotations.rightEyeIris[3][0]-e[o].annotations.rightEyeIris[1][0],a=e[o].annotations.rightEyeIris[4][1]-e[o].annotations.rightEyeIris[2][1],i=Math.abs(s*a),x=!1;Math.abs(A-i)/Math.max(A,i)<.25&&(x=!0,t.push({iris:o,gesture:"facing center"}));let l=Math.abs(e[o].mesh[263][0]-e[o].annotations.leftEyeIris[0][0])/e[o].box[2],y=Math.abs(e[o].mesh[33][0]-e[o].annotations.rightEyeIris[0][0])/e[o].box[2];(l>.06||y>.06)&&(x=!1),l>y?l>.05&&t.push({iris:o,gesture:"looking right"}):y>.05&&t.push({iris:o,gesture:"looking left"});let f=Math.abs(e[o].mesh[145][1]-e[o].annotations.rightEyeIris[0][1])/e[o].box[3],u=Math.abs(e[o].mesh[374][1]-e[o].annotations.leftEyeIris[0][1])/e[o].box[3];(u<.01||f<.01||u>.022||f>.022)&&(x=!1),(u<.01||f<.01)&&t.push({iris:o,gesture:"looking down"}),(u>.022||f>.022)&&t.push({iris:o,gesture:"looking up"}),x&&t.push({iris:o,gesture:"looking center"})}return t},tn=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=[];if(e[o].annotations)for(let[r,A]of Object.entries(e[o].annotations))r!=="palmBase"&&Array.isArray(A)&&A[0]&&n.push({name:r.toLowerCase(),position:A[0]});if(n&&n.length>0){let r=n.reduce((s,a)=>(s.position[2]||0)<(a.position[2]||0)?s:a);t.push({hand:o,gesture:`${r.name} forward`});let A=n.reduce((s,a)=>s.position[1]<a.position[1]?s:a);t.push({hand:o,gesture:`${A.name} up`})}if(e[o].keypoints){let r=xo(e[o].keypoints);for(let A of r)t.push({hand:o,gesture:A.name})}}return t};var z={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null},At=0;function on(e,t){var s,a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0;let o=h();if(!e)return{face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null};let n=Date.now()-e.timestamp,r=n<1e3?8-Math.log(n+1):1;if(e.canvas&&(z.canvas=e.canvas),e.error&&(z.error=e.error),!z.body||e.body.length!==z.body.length)z.body=JSON.parse(JSON.stringify(e.body));else for(let R=0;R<e.body.length;R++){let c0=e.body[R].box.map((L,K)=>((r-1)*z.body[R].box[K]+L)/r),k=e.body[R].boxRaw.map((L,K)=>((r-1)*z.body[R].boxRaw[K]+L)/r),$=e.body[R].keypoints.map((L,K)=>{var Ae,se,p2,u2,qe,yt,xt,ct,dt;return{score:L.score,part:L.part,position:[z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[0]||0)+(L.position[0]||0))/r:L.position[0],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[1]||0)+(L.position[1]||0))/r:L.position[1],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[2]||0)+(L.position[2]||0))/r:L.position[2]],positionRaw:[z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[0]||0)+(L.positionRaw[0]||0))/r:L.positionRaw[0],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[1]||0)+(L.positionRaw[1]||0))/r:L.positionRaw[1],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[2]||0)+(L.positionRaw[2]||0))/r:L.positionRaw[2]],distance:[z.body[R].keypoints[K]?((r-1)*(((Ae=z.body[R].keypoints[K].distance)==null?void 0:Ae[0])||0)+(((se=L.distance)==null?void 0:se[0])||0))/r:(p2=L.distance)==null?void 0:p2[0],z.body[R].keypoints[K]?((r-1)*(((u2=z.body[R].keypoints[K].distance)==null?void 0:u2[1])||0)+(((qe=L.distance)==null?void 0:qe[1])||0))/r:(yt=L.distance)==null?void 0:yt[1],z.body[R].keypoints[K]?((r-1)*(((xt=z.body[R].keypoints[K].distance)==null?void 0:xt[2])||0)+(((ct=L.distance)==null?void 0:ct[2])||0))/r:(dt=L.distance)==null?void 0:dt[2]]}}),i0={},m0={connected:{}};(a=(s=t.body)==null?void 0:s.modelPath)!=null&&a.includes("efficientpose")?m0=t5:(x=(i=t.body)==null?void 0:i.modelPath)!=null&&x.includes("blazepose")?m0=J2:(l=(c=t.body)==null?void 0:c.modelPath)!=null&&l.includes("movenet")&&(m0=E2);for(let[L,K]of Object.entries(m0.connected)){let Ae=[];for(let se=0;se<K.length-1;se++){let p2=$.find(qe=>qe.part===K[se]),u2=$.find(qe=>qe.part===K[se+1]);p2&&u2&&Ae.push([p2.position,u2.position])}i0[L]=Ae}z.body[R]={...e.body[R],box:c0,boxRaw:k,keypoints:$,annotations:i0}}if(!z.hand||e.hand.length!==z.hand.length)z.hand=JSON.parse(JSON.stringify(e.hand));else for(let R=0;R<e.hand.length;R++){let c0=e.hand[R].box.map((m0,L)=>((r-1)*z.hand[R].box[L]+m0)/r),k=e.hand[R].boxRaw.map((m0,L)=>((r-1)*z.hand[R].boxRaw[L]+m0)/r);z.hand[R].keypoints.length!==e.hand[R].keypoints.length&&(z.hand[R].keypoints=e.hand[R].keypoints);let $=e.hand[R].keypoints&&e.hand[R].keypoints.length>0?e.hand[R].keypoints.map((m0,L)=>m0.map((K,Ae)=>((r-1)*(z.hand[R].keypoints[L][Ae]||1)+(K||0))/r)):[],i0={};if(Object.keys(z.hand[R].annotations).length!==Object.keys(e.hand[R].annotations).length)z.hand[R].annotations=e.hand[R].annotations,i0=z.hand[R].annotations;else if(e.hand[R].annotations)for(let m0 of Object.keys(e.hand[R].annotations))i0[m0]=e.hand[R].annotations[m0]&&e.hand[R].annotations[m0][0]?e.hand[R].annotations[m0].map((L,K)=>L.map((Ae,se)=>((r-1)*z.hand[R].annotations[m0][K][se]+Ae)/r)):null;z.hand[R]={...e.hand[R],box:c0,boxRaw:k,keypoints:$,annotations:i0}}if(!z.face||e.face.length!==z.face.length)z.face=JSON.parse(JSON.stringify(e.face));else for(let R=0;R<e.face.length;R++){let c0=e.face[R].box.map(($,i0)=>((r-1)*z.face[R].box[i0]+$)/r),k=e.face[R].boxRaw.map(($,i0)=>((r-1)*z.face[R].boxRaw[i0]+$)/r);if(e.face[R].rotation){let $={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};$.matrix=(y=e.face[R].rotation)==null?void 0:y.matrix,$.angle={roll:((r-1)*(((u=(f=z.face[R].rotation)==null?void 0:f.angle)==null?void 0:u.roll)||0)+(((P=(m=e.face[R].rotation)==null?void 0:m.angle)==null?void 0:P.roll)||0))/r,yaw:((r-1)*(((b=(g=z.face[R].rotation)==null?void 0:g.angle)==null?void 0:b.yaw)||0)+(((M=(d=e.face[R].rotation)==null?void 0:d.angle)==null?void 0:M.yaw)||0))/r,pitch:((r-1)*(((w=(S=z.face[R].rotation)==null?void 0:S.angle)==null?void 0:w.pitch)||0)+(((C=(j=e.face[R].rotation)==null?void 0:j.angle)==null?void 0:C.pitch)||0))/r},$.gaze={bearing:((r-1)*(((H=(F=z.face[R].rotation)==null?void 0:F.gaze)==null?void 0:H.bearing)||0)+(((J=(Y=e.face[R].rotation)==null?void 0:Y.gaze)==null?void 0:J.bearing)||0))/r,strength:((r-1)*(((E=(x0=z.face[R].rotation)==null?void 0:x0.gaze)==null?void 0:E.strength)||0)+(((B0=(G0=e.face[R].rotation)==null?void 0:G0.gaze)==null?void 0:B0.strength)||0))/r},z.face[R]={...e.face[R],rotation:$,box:c0,boxRaw:k}}z.face[R]={...e.face[R],box:c0,boxRaw:k}}if(!z.object||e.object.length!==z.object.length)z.object=JSON.parse(JSON.stringify(e.object));else for(let R=0;R<e.object.length;R++){let c0=e.object[R].box.map(($,i0)=>((r-1)*z.object[R].box[i0]+$)/r),k=e.object[R].boxRaw.map(($,i0)=>((r-1)*z.object[R].boxRaw[i0]+$)/r);z.object[R]={...e.object[R],box:c0,boxRaw:k}}if(e.persons){let R=e.persons;if(!z.persons||R.length!==z.persons.length)z.persons=JSON.parse(JSON.stringify(R));else for(let c0=0;c0<R.length;c0++)z.persons[c0].box=R[c0].box.map((k,$)=>((r-1)*z.persons[c0].box[$]+k)/r)}e.gesture&&(z.gesture=e.gesture);let A=h();return At=v.perfadd?At+Math.round(A-o):Math.round(A-o),e.performance&&(z.performance={...e.performance,interpolate:At}),z}var it={};ue(it,{distance:()=>I2,match:()=>at,similarity:()=>st});function I2(e,t,o={order:2,multiplier:25}){let n=0;for(let r=0;r<e.length;r++){let A=!o.order||o.order===2?e[r]-t[r]:Math.abs(e[r]-t[r]);n+=!o.order||o.order===2?A*A:A**o.order}return(o.multiplier||20)*n}var nn=(e,t,o,n)=>{if(e===0)return 1;let r=t===2?Math.sqrt(e):e**(1/t),A=(1-r/100-o)/(n-o);return Math.max(Math.min(A,1),0)};function st(e,t,o={order:2,multiplier:25,min:.2,max:.8}){let n=I2(e,t,o);return nn(n,o.order||2,o.min||0,o.max||1)}function at(e,t,o={order:2,multiplier:25,threshold:0,min:.2,max:.8}){if(!Array.isArray(e)||!Array.isArray(t)||e.length<64||t.length===0||e.length!==t[0].length)return{index:-1,distance:Number.POSITIVE_INFINITY,similarity:0};let n=Number.MAX_SAFE_INTEGER,r=-1;for(let s=0;s<t.length;s++){let a=I2(e,t[s],o);if(a<n&&(n=a,r=s),n<(o.threshold||0))break}let A=nn(n,o.order||2,o.min||0,o.max||1);return{index:r,distance:n,similarity:A}}function rn(e,t,o,n,r){var a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w;let A=0,s=[];for(let j of e){let C={id:A++,face:j,body:null,hands:{left:null,right:null},gestures:[],box:[0,0,0,0]};for(let E of t)j.box[0]>E.box[0]&&j.box[0]<E.box[0]+E.box[2]&&j.box[1]+j.box[3]>E.box[1]&&j.box[1]+j.box[3]<E.box[1]+E.box[3]&&(C.body=E);if(C.body)for(let E of o)E.box[0]+E.box[2]>C.body.box[0]&&E.box[0]+E.box[2]<C.body.box[0]+C.body.box[2]&&E.box[1]+E.box[3]>C.body.box[1]&&E.box[1]+E.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.left=E),E.box[0]<C.body.box[0]+C.body.box[2]&&E.box[0]>C.body.box[0]&&E.box[1]+E.box[3]>C.body.box[1]&&E.box[1]+E.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.right=E);for(let E of n)E.face!==void 0&&E.face===j.id?(a=C.gestures)==null||a.push(E):E.iris!==void 0&&E.iris===j.id?(i=C.gestures)==null||i.push(E):E.body!==void 0&&E.body===((x=C.body)==null?void 0:x.id)?(c=C.gestures)==null||c.push(E):E.hand!==void 0&&E.hand===((y=(l=C.hands)==null?void 0:l.left)==null?void 0:y.id)?(f=C.gestures)==null||f.push(E):E.hand!==void 0&&E.hand===((m=(u=C.hands)==null?void 0:u.right)==null?void 0:m.id)&&((P=C.gestures)==null||P.push(E));let F=[],H=[],Y=E=>{E&&E.length===4&&(F.push(E[0],E[0]+E[2]),H.push(E[1],E[1]+E[3]))};Y((g=C.face)==null?void 0:g.box),Y((b=C.body)==null?void 0:b.box),Y((M=(d=C.hands)==null?void 0:d.left)==null?void 0:M.box),Y((w=(S=C.hands)==null?void 0:S.right)==null?void 0:w.box);let J=Math.min(...F),x0=Math.min(...H);C.box=[J,x0,Math.max(...F)-J,Math.max(...H)-x0],r&&r[1]&&r[2]&&(C.boxRaw=[C.box[0]/r[2],C.box[1]/r[1],C.box[2]/r[2],C.box[3]/r[1]]),s.push(C)}return s}var w5=`
 /9j/4AAQSkZJRgABAQEAYABgAAD/4QBoRXhpZgAATU0AKgAAAAgABAEaAAUAAAABAAAAPgEbAAUA
 AAABAAAARgEoAAMAAAABAAIAAAExAAIAAAARAAAATgAAAAAAAABgAAAAAQAAAGAAAAABcGFpbnQu
 bmV0IDQuMi4xMwAA/9sAQwAGBAUGBQQGBgUGBwcGCAoQCgoJCQoUDg8MEBcUGBgXFBYWGh0lHxob
@@ -827,4 +827,4 @@ AAAAAAJAAAAAAAAAAAAAABAJEAAAAAAAAAAAAAAAIEoBKAAAAAAAAAAAAAAABAlAAAAAAAIAAAAA
 BAkBAkBAkBAlACEgMZjdjbFW8bWrEx8YWANb6Fp+bfwab+vLDKMFK9qxH5L0bAr8OPRPKz2AY7J2
 SbAjYZAI2E7AIEgIEgIEgMdkSy2NgY7MdlmyNoBXsxmFuyNgVTVjNV3KjlBRNTlXTVHKCrlIqt5T
 lBhEMohlFerLlBjEMohMVTEARDKCITsAk2AEgAAAkAAAAAAAAAAAAAAAAAAAAAAAASAAAAAAAAD/
-2Q==`;var m0=Z(D());async function r7(e){let t=(r,A="application/octet-stream")=>fetch(`data:${A};base64,${r}`).then(s=>s.blob()),o,n;switch(e.config.warmup){case"face":o=await t(w5);break;case"body":case"full":o=await t(k5);break;default:o=null}if(o){let r=await createImageBitmap(o);n=await e.detect(r,e.config),r.close()}return n}async function A7(e){return new Promise(t=>{let o;switch(e.config.warmup){case"face":o="data:image/jpeg;base64,"+w5;break;case"full":case"body":o="data:image/jpeg;base64,"+k5;break;default:o=null}let n;if(typeof Image!="undefined")n=new Image;else if(v.Image)n=new v.Image;else return;n.onload=async()=>{let r=R0(n.naturalWidth,n.naturalHeight);if(!r)p("Warmup: Canvas not found"),t(void 0);else{let A=r.getContext("2d");A&&A.drawImage(n,0,0);let s=await e.image(r),a=await e.detect(s.tensor,e.config);t(a)}},o?n.src=o:t(void 0)})}async function s7(e){let t=r=>Buffer.from(r,"base64"),o;e.config.warmup==="face"?o=t(w5):o=t(k5);let n;if("node"in m0){let r=m0.node.decodeJpeg(o),A=r.expandDims(0);e.tf.dispose(r),n=await e.detect(A,e.config),e.tf.dispose(A)}else e.config.debug&&p("Warmup tfjs-node not loaded");return n}async function a7(e){let t;return typeof createImageBitmap=="function"?t=await r7(e):typeof Image!="undefined"||v.Canvas!==void 0?t=await A7(e):t=await s7(e),t}async function i7(e){let t=m0.getBackend(),o=m0.backend();if(t!=="webgl"&&t!=="humangl"||!o||!o.checkCompileCompletion)return;m0.env().set("ENGINE_COMPILE_ONLY",!0);let n=m0.engine().state.numTensors,r=[];for(let[a,i]of Object.entries(e).filter(([x,c])=>x!==null&&c!==null)){let x=i.inputs&&i.inputs[0]&&i.inputs[0].shape?[...i.inputs[0].shape]:[1,64,64,3],c=i.inputs&&i.inputs[0]&&i.inputs[0].dtype?i.inputs[0].dtype:"float32";for(let y=0;y<x.length;y++)x[y]===-1&&(x[y]=y===0?1:64);let l=m0.zeros(x,c);try{let y=i.execute(l);r.push(a),Array.isArray(y)?y.forEach(f=>m0.dispose(f)):m0.dispose(y)}catch(y){p("compile fail model:",a)}m0.dispose(l)}let A=await o.checkCompileCompletionAsync();o.getUniformLocations(),p("compile pass models:",r),p("compile pass kernels:",A.length),m0.env().set("ENGINE_COMPILE_ONLY",!1);let s=m0.engine().state.numTensors;s-n>0&&p("tensor leak:",s-n)}async function An(e,t){let o=h();return e.state="warmup",t&&(e.config=r0(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?{face:[],body:[],hand:[],gesture:[],object:[],performance:e.performance,timestamp:h(),persons:[],error:null}:new Promise(async n=>{await i7(e.models);let r=await a7(e),A=h();e.config.debug&&p("warmup",e.config.warmup,Math.round(A-o),"ms"),e.emit("warmup"),n(r)})}var m2,I2,N2,E5,lt=class{constructor(t){T(this,"version");T(this,"config");T(this,"result");T(this,"state");T(this,"process");T(this,"tf");T(this,"env");T(this,"draw");T(this,"models");T(this,"events");T(this,"faceTriangulation");T(this,"faceUVMap");T(this,"performance");g2(this,m2,void 0);g2(this,I2,void 0);g2(this,N2,void 0);T(this,"gl");T(this,"analyze",(...t)=>{if(!b2(this,I2))return;let o=this.tf.engine().state.numTensors,n=b2(this,m2);M2(this,m2,o);let r=o-n;r!==0&&p(...t,r)});g2(this,E5,t=>{if(!b2(this,N2))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof ee.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(o){return"backend not loaded"}return null});T(this,"similarity",st);T(this,"distance",j2);T(this,"match",at);T(this,"emit",t=>{var o;this.events&&this.events.dispatchEvent&&((o=this.events)==null||o.dispatchEvent(new Event(t)))});var n;this.env=v;let o=(((n=ee.version)==null?void 0:n.tfjs)||ee.version_core).replace(/-(.*)/,"");he.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${o}/dist/`,he.modelBasePath=v.browser?"../models/":"file://models/",he.backend=v.browser?"humangl":"tensorflow",this.version=L5,Object.defineProperty(this,"version",{value:L5}),this.config=JSON.parse(JSON.stringify(he)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=r0(this.config,t)),Et(this.config),this.tf=ee,this.state="idle",M2(this,m2,0),M2(this,I2,!1),M2(this,N2,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new C2,this.draw={options:P0,canvas:(r,A)=>et(r,A),face:(r,A,s)=>l2(r,A,s),body:(r,A,s)=>y2(r,A,s),hand:(r,A,s)=>x2(r,A,s),gesture:(r,A,s)=>d2(r,A,s),object:(r,A,s)=>c2(r,A,s),person:(r,A,s)=>$1(r,A,s),all:(r,A,s)=>tt(r,A,s)},this.result={face:[],body:[],hand:[],gesture:[],object:[],performance:{},timestamp:0,persons:[],error:null},this.process={tensor:null,canvas:null},this.faceTriangulation=H3,this.faceUVMap=V3,this.gl=t0,this.emit("create")}reset(){let t=this.config.backend;this.config=JSON.parse(JSON.stringify(he)),this.config.backend=t}validate(t){return z5(he,t||this.config)}now(){return h()}image(t,o=!0){return Ye(t,this.config,o)}async segmentation(t,o){return Zo(t,o,this.config)}enhance(t){return h1(t)}compare(t,o){return kt(this.config,t,o)}async init(){await T5(this,!0),await this.tf.ready()}async load(t){this.state="load";let o=h(),n=Object.values(this.models).filter(s=>s).length;t&&(this.config=r0(this.config,t)),this.env.initial&&(this.config.debug&&p(`version: ${this.version}`),this.config.debug&&p(`tfjs version: ${this.tf.version["tfjs-core"]}`),await T5(this)||p("error: backend check failed"),await ee.ready(),this.env.browser&&(this.config.debug&&p("configuration:",this.config),this.config.debug&&p("environment:",this.env),this.config.debug&&p("tf flags:",this.tf.ENV.flags))),await Y1(this),this.env.initial&&this.config.debug&&p("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.env.initial=!1,Object.values(this.models).filter(s=>s).length!==n&&(await K1(this),this.emit("load"));let A=Math.trunc(h()-o);A>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+A:A)}next(t=this.result){return on(t,this.config)}getModelStats(){return U1(this)}async warmup(t){let o=h(),n=await An(this,t),r=h();return this.performance.warmup=Math.trunc(r-o),n}async profile(t,o){let n=await this.tf.profile(()=>this.detect(t,o)),r={};for(let a of n.kernels)r[a.name]?r[a.name]+=a.kernelTimeMs:r[a.name]=a.kernelTimeMs;let A=[];Object.entries(r).forEach(a=>A.push({name:a[0],ms:a[1]})),A.sort((a,i)=>i.ms-a.ms),A.length=20;let s={};for(let a of A)s[a.name]=a.ms;return s}async detect(t,o){return this.state="detect",new Promise(async n=>{var P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0,R,c0,k,$,a0;this.state="config";let r;this.config=r0(this.config,o),this.state="check";let A=b2(this,E5).call(this,t);A&&(p(A,t),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:h(),persons:[],error:A}));let s=h();await T5(this),await this.load(),r=h(),this.state="image";let a=await Ye(t,this.config);if(this.process=a,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(h()-r):Math.trunc(h()-r),this.analyze("Get Image:"),!a.tensor){this.config.debug&&p("could not convert input to tensor"),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:h(),persons:[],error:"could not convert input to tensor"});return}this.emit("image"),r=h(),this.config.skipAllowed=await wt(this.config,a.tensor),this.performance.totalFrames||(this.performance.totalFrames=0),this.performance.cachedFrames||(this.performance.cachedFrames=0),this.performance.totalFrames++,this.config.skipAllowed&&this.performance.cachedFrames++,this.performance.cacheCheck=this.env.perfadd?(this.performance.cacheCheck||0)+Math.trunc(h()-r):Math.trunc(h()-r),this.analyze("Check Changed:");let i=[],x=[],c=[],l=[];this.state="detect:face",this.config.async?(i=this.config.face.enabled?rt(this,a.tensor):[],this.performance.face&&delete this.performance.face):(r=h(),i=this.config.face.enabled?await rt(this,a.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.config.async&&(this.config.body.maxDetected===-1||this.config.hand.maxDetected===-1)&&(i=await i),this.analyze("Start Body:"),this.state="detect:body";let y=this.config.body.maxDetected===-1?r0(this.config,{body:{maxDetected:this.config.face.enabled?1*i.length:1}}):this.config;this.config.async?((P=this.config.body.modelPath)!=null&&P.includes("posenet")?x=this.config.body.enabled?Z1(a.tensor,y):[]:(g=this.config.body.modelPath)!=null&&g.includes("blazepose")?x=this.config.body.enabled?o1(a.tensor,y):[]:(b=this.config.body.modelPath)!=null&&b.includes("efficientpose")?x=this.config.body.enabled?l1(a.tensor,y):[]:(d=this.config.body.modelPath)!=null&&d.includes("movenet")&&(x=this.config.body.enabled?W1(a.tensor,y):[]),this.performance.body&&delete this.performance.body):(r=h(),(M=this.config.body.modelPath)!=null&&M.includes("posenet")?x=this.config.body.enabled?await Z1(a.tensor,y):[]:(S=this.config.body.modelPath)!=null&&S.includes("blazepose")?x=this.config.body.enabled?await o1(a.tensor,y):[]:(w=this.config.body.modelPath)!=null&&w.includes("efficientpose")?x=this.config.body.enabled?await l1(a.tensor,y):[]:(j=this.config.body.modelPath)!=null&&j.includes("movenet")&&(x=this.config.body.enabled?await W1(a.tensor,y):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let f=this.config.hand.maxDetected===-1?r0(this.config,{hand:{maxDetected:this.config.face.enabled?2*i.length:1}}):this.config;this.config.async?((F=(C=this.config.hand.detector)==null?void 0:C.modelPath)!=null&&F.includes("handdetect")?c=this.config.hand.enabled?T1(a.tensor,f):[]:(Y=(H=this.config.hand.detector)==null?void 0:H.modelPath)!=null&&Y.includes("handtrack")&&(c=this.config.hand.enabled?z1(a.tensor,f):[]),this.performance.hand&&delete this.performance.hand):(r=h(),(x0=(J=this.config.hand.detector)==null?void 0:J.modelPath)!=null&&x0.includes("handdetect")?c=this.config.hand.enabled?await T1(a.tensor,f):[]:(G0=(E=this.config.hand.detector)==null?void 0:E.modelPath)!=null&&G0.includes("handtrack")&&(c=this.config.hand.enabled?await z1(a.tensor,f):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?((B0=this.config.object.modelPath)!=null&&B0.includes("nanodet")?l=this.config.object.enabled?G1(a.tensor,this.config):[]:(R=this.config.object.modelPath)!=null&&R.includes("centernet")&&(l=this.config.object.enabled?A1(a.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=h(),(c0=this.config.object.modelPath)!=null&&c0.includes("nanodet")?l=this.config.object.enabled?await G1(a.tensor,this.config):[]:(k=this.config.object.modelPath)!=null&&k.includes("centernet")&&(l=this.config.object.enabled?await A1(a.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([i,x,c,l]=await Promise.all([i,x,c,l])),this.state="detect:gesture";let u=[];this.config.gesture.enabled&&(r=h(),u=[...$o(i),..._o(x),...tn(c),...en(i)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(h()-s):Math.trunc(h()-s);let m=((a0=($=this.process)==null?void 0:$.tensor)==null?void 0:a0.shape)||[];this.result={face:i,body:x,hand:c,gesture:u,object:l,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,get persons(){return rn(i,x,c,u,m)}},ee.dispose(a.tensor),this.emit("detect"),this.state="idle",n(this.result)})}};m2=new WeakMap,I2=new WeakMap,N2=new WeakMap,E5=new WeakMap;0&&(module.exports={Human,defaults,draw,env,match,models});
+2Q==`;var f0=Z(D());async function r7(e){let t=(r,A="application/octet-stream")=>fetch(`data:${A};base64,${r}`).then(s=>s.blob()),o,n;switch(e.config.warmup){case"face":o=await t(w5);break;case"body":case"full":o=await t(k5);break;default:o=null}if(o){let r=await createImageBitmap(o);n=await e.detect(r,e.config),r.close()}return n}async function A7(e){return new Promise(t=>{let o;switch(e.config.warmup){case"face":o="data:image/jpeg;base64,"+w5;break;case"full":case"body":o="data:image/jpeg;base64,"+k5;break;default:o=null}let n;if(typeof Image!="undefined")n=new Image;else if(v.Image)n=new v.Image;else return;n.onload=async()=>{let r=R0(n.naturalWidth,n.naturalHeight);if(!r)p("Warmup: Canvas not found"),t(void 0);else{let A=r.getContext("2d");A&&A.drawImage(n,0,0);let s=await e.image(r),a=await e.detect(s.tensor,e.config);t(a)}},o?n.src=o:t(void 0)})}async function s7(e){let t=r=>Buffer.from(r,"base64"),o;e.config.warmup==="face"?o=t(w5):o=t(k5);let n;if("node"in f0){let r=f0.node.decodeJpeg(o),A=r.expandDims(0);e.tf.dispose(r),n=await e.detect(A,e.config),e.tf.dispose(A)}else e.config.debug&&p("Warmup tfjs-node not loaded");return n}async function a7(e){let t;return typeof createImageBitmap=="function"?t=await r7(e):typeof Image!="undefined"||v.Canvas!==void 0?t=await A7(e):t=await s7(e),t}async function i7(e){if(!f0.env().flagRegistry.ENGINE_COMPILE_ONLY)return;let t=f0.getBackend(),o=f0.backend();if(t!=="webgl"&&t!=="humangl"||!o||!o.checkCompileCompletion)return;f0.env().set("ENGINE_COMPILE_ONLY",!0);let n=f0.engine().state.numTensors,r=[];for(let[a,i]of Object.entries(e).filter(([x,c])=>x!==null&&c!==null)){let x=i.inputs&&i.inputs[0]&&i.inputs[0].shape?[...i.inputs[0].shape]:[1,64,64,3],c=i.inputs&&i.inputs[0]&&i.inputs[0].dtype?i.inputs[0].dtype:"float32";for(let y=0;y<x.length;y++)x[y]===-1&&(x[y]=y===0?1:64);let l=f0.zeros(x,c);try{let y=i.execute(l);r.push(a),Array.isArray(y)?y.forEach(f=>f0.dispose(f)):f0.dispose(y)}catch(y){p("compile fail model:",a)}f0.dispose(l)}let A=await o.checkCompileCompletionAsync();o.getUniformLocations(),p("compile pass models:",r),p("compile pass kernels:",A.length),f0.env().set("ENGINE_COMPILE_ONLY",!1);let s=f0.engine().state.numTensors;s-n>0&&p("tensor leak:",s-n)}async function An(e,t){let o=h();return e.state="warmup",t&&(e.config=r0(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?{face:[],body:[],hand:[],gesture:[],object:[],performance:e.performance,timestamp:h(),persons:[],error:null}:new Promise(async n=>{await i7(e.models);let r=await a7(e),A=h();e.config.debug&&p("warmup",e.config.warmup,Math.round(A-o),"ms"),e.emit("warmup"),n(r)})}var m2,j2,O2,E5,lt=class{constructor(t){T(this,"version");T(this,"config");T(this,"result");T(this,"state");T(this,"process");T(this,"tf");T(this,"env");T(this,"draw");T(this,"models");T(this,"events");T(this,"faceTriangulation");T(this,"faceUVMap");T(this,"performance");g2(this,m2,void 0);g2(this,j2,void 0);g2(this,O2,void 0);T(this,"gl");T(this,"analyze",(...t)=>{if(!b2(this,j2))return;let o=this.tf.engine().state.numTensors,n=b2(this,m2);M2(this,m2,o);let r=o-n;r!==0&&p(...t,r)});g2(this,E5,t=>{if(!b2(this,O2))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof ee.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(o){return"backend not loaded"}return null});T(this,"similarity",st);T(this,"distance",I2);T(this,"match",at);T(this,"emit",t=>{var o;this.events&&this.events.dispatchEvent&&((o=this.events)==null||o.dispatchEvent(new Event(t)))});var n;this.env=v;let o=(((n=ee.version)==null?void 0:n.tfjs)||ee.version_core).replace(/-(.*)/,"");he.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${o}/dist/`,he.modelBasePath=v.browser?"../models/":"file://models/",he.backend=v.browser?"humangl":"tensorflow",this.version=L5,Object.defineProperty(this,"version",{value:L5}),this.config=JSON.parse(JSON.stringify(he)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=r0(this.config,t)),Et(this.config),this.tf=ee,this.state="idle",M2(this,m2,0),M2(this,j2,!1),M2(this,O2,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new C2,this.draw={options:P0,canvas:(r,A)=>et(r,A),face:(r,A,s)=>l2(r,A,s),body:(r,A,s)=>y2(r,A,s),hand:(r,A,s)=>x2(r,A,s),gesture:(r,A,s)=>d2(r,A,s),object:(r,A,s)=>c2(r,A,s),person:(r,A,s)=>$1(r,A,s),all:(r,A,s)=>tt(r,A,s)},this.result={face:[],body:[],hand:[],gesture:[],object:[],performance:{},timestamp:0,persons:[],error:null},this.process={tensor:null,canvas:null},this.faceTriangulation=H3,this.faceUVMap=V3,this.gl=t0,this.emit("create")}reset(){let t=this.config.backend;this.config=JSON.parse(JSON.stringify(he)),this.config.backend=t}validate(t){return z5(he,t||this.config)}now(){return h()}image(t,o=!0){return Ye(t,this.config,o)}async segmentation(t,o){return Zo(t,o,this.config)}enhance(t){return h1(t)}compare(t,o){return kt(this.config,t,o)}async init(){await T5(this,!0),await this.tf.ready()}async load(t){this.state="load";let o=h(),n=Object.values(this.models).filter(s=>s).length;t&&(this.config=r0(this.config,t)),this.env.initial&&(this.config.debug&&p(`version: ${this.version}`),this.config.debug&&p(`tfjs version: ${this.tf.version["tfjs-core"]}`),await T5(this)||p("error: backend check failed"),await ee.ready(),this.env.browser&&(this.config.debug&&p("configuration:",this.config),this.config.debug&&p("environment:",this.env),this.config.debug&&p("tf flags:",this.tf.ENV.flags))),await Y1(this),this.env.initial&&this.config.debug&&p("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.env.initial=!1,Object.values(this.models).filter(s=>s).length!==n&&(await K1(this),this.emit("load"));let A=Math.trunc(h()-o);A>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+A:A)}next(t=this.result){return on(t,this.config)}getModelStats(){return U1(this)}async warmup(t){let o=h(),n=await An(this,t),r=h();return this.performance.warmup=Math.trunc(r-o),n}async profile(t,o){let n=await this.tf.profile(()=>this.detect(t,o)),r={},A=0;for(let a of n.kernels)r[a.name]?r[a.name]+=a.kernelTimeMs:r[a.name]=a.kernelTimeMs,A+=a.kernelTimeMs;let s=[];Object.entries(r).forEach(a=>s.push({kernel:a[0],time:a[1],perc:0}));for(let a of s)a.perc=Math.round(1e3*a.time/A)/1e3,a.time=Math.round(1e3*a.time)/1e3;return s.sort((a,i)=>i.time-a.time),s.length=20,s}async detect(t,o){return this.state="detect",new Promise(async n=>{var P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0,R,c0,k,$,i0;this.state="config";let r;this.config=r0(this.config,o),this.state="check";let A=b2(this,E5).call(this,t);A&&(p(A,t),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:h(),persons:[],error:A}));let s=h();await T5(this),await this.load(),r=h(),this.state="image";let a=await Ye(t,this.config);if(this.process=a,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(h()-r):Math.trunc(h()-r),this.analyze("Get Image:"),!a.tensor){this.config.debug&&p("could not convert input to tensor"),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:h(),persons:[],error:"could not convert input to tensor"});return}this.emit("image"),r=h(),this.config.skipAllowed=await wt(this.config,a.tensor),this.performance.totalFrames||(this.performance.totalFrames=0),this.performance.cachedFrames||(this.performance.cachedFrames=0),this.performance.totalFrames++,this.config.skipAllowed&&this.performance.cachedFrames++,this.performance.cacheCheck=this.env.perfadd?(this.performance.cacheCheck||0)+Math.trunc(h()-r):Math.trunc(h()-r),this.analyze("Check Changed:");let i=[],x=[],c=[],l=[];this.state="detect:face",this.config.async?(i=this.config.face.enabled?rt(this,a.tensor):[],this.performance.face&&delete this.performance.face):(r=h(),i=this.config.face.enabled?await rt(this,a.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.config.async&&(this.config.body.maxDetected===-1||this.config.hand.maxDetected===-1)&&(i=await i),this.analyze("Start Body:"),this.state="detect:body";let y=this.config.body.maxDetected===-1?r0(this.config,{body:{maxDetected:this.config.face.enabled?1*i.length:1}}):this.config;this.config.async?((P=this.config.body.modelPath)!=null&&P.includes("posenet")?x=this.config.body.enabled?Z1(a.tensor,y):[]:(g=this.config.body.modelPath)!=null&&g.includes("blazepose")?x=this.config.body.enabled?o1(a.tensor,y):[]:(b=this.config.body.modelPath)!=null&&b.includes("efficientpose")?x=this.config.body.enabled?l1(a.tensor,y):[]:(d=this.config.body.modelPath)!=null&&d.includes("movenet")&&(x=this.config.body.enabled?W1(a.tensor,y):[]),this.performance.body&&delete this.performance.body):(r=h(),(M=this.config.body.modelPath)!=null&&M.includes("posenet")?x=this.config.body.enabled?await Z1(a.tensor,y):[]:(S=this.config.body.modelPath)!=null&&S.includes("blazepose")?x=this.config.body.enabled?await o1(a.tensor,y):[]:(w=this.config.body.modelPath)!=null&&w.includes("efficientpose")?x=this.config.body.enabled?await l1(a.tensor,y):[]:(j=this.config.body.modelPath)!=null&&j.includes("movenet")&&(x=this.config.body.enabled?await W1(a.tensor,y):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let f=this.config.hand.maxDetected===-1?r0(this.config,{hand:{maxDetected:this.config.face.enabled?2*i.length:1}}):this.config;this.config.async?((F=(C=this.config.hand.detector)==null?void 0:C.modelPath)!=null&&F.includes("handdetect")?c=this.config.hand.enabled?T1(a.tensor,f):[]:(Y=(H=this.config.hand.detector)==null?void 0:H.modelPath)!=null&&Y.includes("handtrack")&&(c=this.config.hand.enabled?z1(a.tensor,f):[]),this.performance.hand&&delete this.performance.hand):(r=h(),(x0=(J=this.config.hand.detector)==null?void 0:J.modelPath)!=null&&x0.includes("handdetect")?c=this.config.hand.enabled?await T1(a.tensor,f):[]:(G0=(E=this.config.hand.detector)==null?void 0:E.modelPath)!=null&&G0.includes("handtrack")&&(c=this.config.hand.enabled?await z1(a.tensor,f):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?((B0=this.config.object.modelPath)!=null&&B0.includes("nanodet")?l=this.config.object.enabled?G1(a.tensor,this.config):[]:(R=this.config.object.modelPath)!=null&&R.includes("centernet")&&(l=this.config.object.enabled?A1(a.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=h(),(c0=this.config.object.modelPath)!=null&&c0.includes("nanodet")?l=this.config.object.enabled?await G1(a.tensor,this.config):[]:(k=this.config.object.modelPath)!=null&&k.includes("centernet")&&(l=this.config.object.enabled?await A1(a.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([i,x,c,l]=await Promise.all([i,x,c,l])),this.state="detect:gesture";let u=[];this.config.gesture.enabled&&(r=h(),u=[...$o(i),..._o(x),...tn(c),...en(i)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(h()-s):Math.trunc(h()-s);let m=((i0=($=this.process)==null?void 0:$.tensor)==null?void 0:i0.shape)||[];this.result={face:i,body:x,hand:c,gesture:u,object:l,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,get persons(){return rn(i,x,c,u,m)}},ee.dispose(a.tensor),this.emit("detect"),this.state="idle",n(this.result)})}};m2=new WeakMap,j2=new WeakMap,O2=new WeakMap,E5=new WeakMap;0&&(module.exports={Human,defaults,draw,env,match,models});
diff --git a/dist/human.node.d.ts b/dist/human.node.d.ts
index 4f1e9723..925302ef 100644
--- a/dist/human.node.d.ts
+++ b/dist/human.node.d.ts
@@ -1330,7 +1330,11 @@ declare class Human {
      * - result object will contain total exeuction time information for top-20 kernels
      * - actual detection object can be accessed via `human.result`
      */
-    profile(input: Input, userConfig?: Partial<Config>): Promise<Record<string, number>>;
+    profile(input: Input, userConfig?: Partial<Config>): Promise<Array<{
+        kernel: string;
+        time: number;
+        perc: number;
+    }>>;
     /** Main detection method
      * - Analyze configuration: {@link Config}
      * - Pre-process input: {@link Input}
diff --git a/dist/human.node.js b/dist/human.node.js
index 8dd48a56..a821adbd 100644
--- a/dist/human.node.js
+++ b/dist/human.node.js
@@ -4,7 +4,7 @@
   author: <https://github.com/vladmandic>'
 */
 
-var An=Object.create;var h2=Object.defineProperty;var sn=Object.getOwnPropertyDescriptor;var an=Object.getOwnPropertyNames;var ln=Object.getPrototypeOf,yn=Object.prototype.hasOwnProperty;var xn=(e,t,o)=>t in e?h2(e,t,{enumerable:!0,configurable:!0,writable:!0,value:o}):e[t]=o;var cn=(e,t)=>()=>(t||e((t={exports:{}}).exports,t),t.exports),ue=(e,t)=>{for(var o in t)h2(e,o,{get:t[o],enumerable:!0})},dt=(e,t,o,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of an(t))!yn.call(e,r)&&r!==o&&h2(e,r,{get:()=>t[r],enumerable:!(n=sn(t,r))||n.enumerable});return e};var Z=(e,t,o)=>(o=e!=null?An(ln(e)):{},dt(t||!e||!e.__esModule?h2(o,"default",{value:e,enumerable:!0}):o,e)),dn=e=>dt(h2({},"__esModule",{value:!0}),e);var T=(e,t,o)=>(xn(e,typeof t!="symbol"?t+"":t,o),o),ft=(e,t,o)=>{if(!t.has(e))throw TypeError("Cannot "+o)};var b2=(e,t,o)=>(ft(e,t,"read from private field"),o?o.call(e):t.get(e)),g2=(e,t,o)=>{if(t.has(e))throw TypeError("Cannot add the same private member more than once");t instanceof WeakSet?t.add(e):t.set(e,o)},M2=(e,t,o,n)=>(ft(e,t,"write to private field"),n?n.call(e,o):t.set(e,o),o);var D=cn((f7,S5)=>{"use strict";var pt=Object.defineProperty,fn=Object.getOwnPropertyDescriptor,mn=Object.getOwnPropertyNames,pn=Object.prototype.hasOwnProperty,z5=(e,t,o,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of mn(t))!pn.call(e,r)&&r!==o&&pt(e,r,{get:()=>t[r],enumerable:!(n=fn(t,r))||n.enumerable});return e},un=(e,t,o)=>(z5(e,t,"default"),o&&z5(o,t,"default")),hn=e=>z5(pt({},"__esModule",{value:!0}),e),ut={};S5.exports=hn(ut);un(ut,require("@tensorflow/tfjs-node"),S5.exports)});var y7={};ue(y7,{Human:()=>it,default:()=>it,defaults:()=>he,draw:()=>tt,env:()=>v,match:()=>at,models:()=>R5});module.exports=dn(y7);function p(...e){let t=new Date,o=`${t.getHours().toString().padStart(2,"0")}:${t.getMinutes().toString().padStart(2,"0")}:${t.getSeconds().toString().padStart(2,"0")}.${t.getMilliseconds().toString().padStart(3,"0")}`;e&&console.log(o,"Human:",...e)}function mt(e,t){let o=e.endsWith("/")?"":"/",r=t.startsWith(".")||t.startsWith("/")||t.startsWith("http:")||t.startsWith("https:")||t.startsWith("file:")?`${t}`:`${e}${o}${t}`;if(!r.toLocaleLowerCase().includes(".json"))throw new Error(`modelpath error: expecting json file: ${r}`);return r}var h=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function E5(e,t,o="config",n=[]){for(let r of Object.keys(t))if(typeof t[r]=="object")E5(e[r],t[r],r,n);else{let A=e&&typeof e[r]!="undefined";A||n.push({reason:"unknown property",where:`${o}.${r} = ${t[r]}`});let s=e&&typeof e[r]==typeof t[r];A&&!s&&n.push({reason:"property type mismatch",where:`${o}.${r} = ${t[r]}`,expected:typeof e[r]})}return t.debug&&o==="config"&&n.length>0&&p("invalid configuration",n),n}function r0(...e){let t=o=>o&&typeof o=="object";return e.reduce((o,n)=>(Object.keys(n||{}).forEach(r=>{let A=o[r],s=n[r];Array.isArray(A)&&Array.isArray(s)?o[r]=A.concat(...s):t(A)&&t(s)?o[r]=r0(A,s):o[r]=s}),o),{})}var he={backend:"",modelBasePath:"",cacheModels:!0,wasmPath:"",wasmPlatformFetch:!1,debug:!1,async:!0,warmup:"full",cacheSensitivity:.7,skipAllowed:!1,deallocate:!1,filter:{enabled:!0,equalization:!1,width:0,height:0,flip:!1,return:!0,brightness:0,contrast:0,sharpness:0,blur:0,saturation:0,hue:0,negative:!1,sepia:!1,vintage:!1,kodachrome:!1,technicolor:!1,polaroid:!1,pixelate:0},gesture:{enabled:!0},face:{enabled:!0,detector:{modelPath:"blazeface.json",rotation:!0,maxDetected:1,skipFrames:99,skipTime:2500,minConfidence:.2,iouThreshold:.1,mask:!1,return:!1},mesh:{enabled:!0,modelPath:"facemesh.json",keepInvalid:!1},attention:{enabled:!1,modelPath:"facemesh-attention.json"},iris:{enabled:!0,modelPath:"iris.json"},emotion:{enabled:!0,minConfidence:.1,skipFrames:99,skipTime:1500,modelPath:"emotion.json"},description:{enabled:!0,modelPath:"faceres.json",skipFrames:99,skipTime:3e3,minConfidence:.1},antispoof:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"antispoof.json"},liveness:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"liveness.json"}},body:{enabled:!0,modelPath:"movenet-lightning.json",maxDetected:-1,minConfidence:.3,skipFrames:1,skipTime:200},hand:{enabled:!0,rotation:!0,skipFrames:99,skipTime:1e3,minConfidence:.5,iouThreshold:.2,maxDetected:-1,landmarks:!0,detector:{modelPath:"handtrack.json"},skeleton:{modelPath:"handlandmark-full.json"}},object:{enabled:!1,modelPath:"mb3-centernet.json",minConfidence:.2,iouThreshold:.4,maxDetected:10,skipFrames:99,skipTime:2e3},segmentation:{enabled:!1,modelPath:"selfie.json",blur:8}};var p0=Z(D());var N=Z(D());var ht=`
+var An=Object.create;var h2=Object.defineProperty;var sn=Object.getOwnPropertyDescriptor;var an=Object.getOwnPropertyNames;var ln=Object.getPrototypeOf,yn=Object.prototype.hasOwnProperty;var xn=(e,t,o)=>t in e?h2(e,t,{enumerable:!0,configurable:!0,writable:!0,value:o}):e[t]=o;var cn=(e,t)=>()=>(t||e((t={exports:{}}).exports,t),t.exports),ue=(e,t)=>{for(var o in t)h2(e,o,{get:t[o],enumerable:!0})},dt=(e,t,o,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of an(t))!yn.call(e,r)&&r!==o&&h2(e,r,{get:()=>t[r],enumerable:!(n=sn(t,r))||n.enumerable});return e};var Z=(e,t,o)=>(o=e!=null?An(ln(e)):{},dt(t||!e||!e.__esModule?h2(o,"default",{value:e,enumerable:!0}):o,e)),dn=e=>dt(h2({},"__esModule",{value:!0}),e);var T=(e,t,o)=>(xn(e,typeof t!="symbol"?t+"":t,o),o),ft=(e,t,o)=>{if(!t.has(e))throw TypeError("Cannot "+o)};var b2=(e,t,o)=>(ft(e,t,"read from private field"),o?o.call(e):t.get(e)),g2=(e,t,o)=>{if(t.has(e))throw TypeError("Cannot add the same private member more than once");t instanceof WeakSet?t.add(e):t.set(e,o)},M2=(e,t,o,n)=>(ft(e,t,"write to private field"),n?n.call(e,o):t.set(e,o),o);var D=cn((f7,S5)=>{"use strict";var pt=Object.defineProperty,fn=Object.getOwnPropertyDescriptor,mn=Object.getOwnPropertyNames,pn=Object.prototype.hasOwnProperty,z5=(e,t,o,n)=>{if(t&&typeof t=="object"||typeof t=="function")for(let r of mn(t))!pn.call(e,r)&&r!==o&&pt(e,r,{get:()=>t[r],enumerable:!(n=fn(t,r))||n.enumerable});return e},un=(e,t,o)=>(z5(e,t,"default"),o&&z5(o,t,"default")),hn=e=>z5(pt({},"__esModule",{value:!0}),e),ut={};S5.exports=hn(ut);un(ut,require("@tensorflow/tfjs-node"),S5.exports)});var y7={};ue(y7,{Human:()=>it,default:()=>it,defaults:()=>he,draw:()=>tt,env:()=>v,match:()=>at,models:()=>R5});module.exports=dn(y7);function p(...e){let t=new Date,o=`${t.getHours().toString().padStart(2,"0")}:${t.getMinutes().toString().padStart(2,"0")}:${t.getSeconds().toString().padStart(2,"0")}.${t.getMilliseconds().toString().padStart(3,"0")}`;e&&console.log(o,"Human:",...e)}function mt(e,t){let o=e.endsWith("/")?"":"/",r=t.startsWith(".")||t.startsWith("/")||t.startsWith("http:")||t.startsWith("https:")||t.startsWith("file:")?`${t}`:`${e}${o}${t}`;if(!r.toLocaleLowerCase().includes(".json"))throw new Error(`modelpath error: expecting json file: ${r}`);return r}var h=()=>typeof performance!="undefined"?performance.now():parseInt((Number(process.hrtime.bigint())/1e3/1e3).toString());function E5(e,t,o="config",n=[]){for(let r of Object.keys(t))if(typeof t[r]=="object")E5(e[r],t[r],r,n);else{let A=e&&typeof e[r]!="undefined";A||n.push({reason:"unknown property",where:`${o}.${r} = ${t[r]}`});let s=e&&typeof e[r]==typeof t[r];A&&!s&&n.push({reason:"property type mismatch",where:`${o}.${r} = ${t[r]}`,expected:typeof e[r]})}return t.debug&&o==="config"&&n.length>0&&p("invalid configuration",n),n}function r0(...e){let t=o=>o&&typeof o=="object";return e.reduce((o,n)=>(Object.keys(n||{}).forEach(r=>{let A=o[r],s=n[r];Array.isArray(A)&&Array.isArray(s)?o[r]=A.concat(...s):t(A)&&t(s)?o[r]=r0(A,s):o[r]=s}),o),{})}var he={backend:"",modelBasePath:"",cacheModels:!0,wasmPath:"",wasmPlatformFetch:!1,debug:!1,async:!0,warmup:"full",cacheSensitivity:.7,skipAllowed:!1,deallocate:!1,filter:{enabled:!0,equalization:!1,width:0,height:0,flip:!1,return:!0,brightness:0,contrast:0,sharpness:0,blur:0,saturation:0,hue:0,negative:!1,sepia:!1,vintage:!1,kodachrome:!1,technicolor:!1,polaroid:!1,pixelate:0},gesture:{enabled:!0},face:{enabled:!0,detector:{modelPath:"blazeface.json",rotation:!0,maxDetected:1,skipFrames:99,skipTime:2500,minConfidence:.2,iouThreshold:.1,mask:!1,return:!1},mesh:{enabled:!0,modelPath:"facemesh.json",keepInvalid:!1},attention:{enabled:!1,modelPath:"facemesh-attention.json"},iris:{enabled:!0,modelPath:"iris.json"},emotion:{enabled:!0,minConfidence:.1,skipFrames:99,skipTime:1500,modelPath:"emotion.json"},description:{enabled:!0,modelPath:"faceres.json",skipFrames:99,skipTime:3e3,minConfidence:.1},antispoof:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"antispoof.json"},liveness:{enabled:!1,skipFrames:99,skipTime:4e3,modelPath:"liveness.json"}},body:{enabled:!0,modelPath:"movenet-lightning.json",maxDetected:-1,minConfidence:.3,skipFrames:1,skipTime:200},hand:{enabled:!0,rotation:!0,skipFrames:99,skipTime:1e3,minConfidence:.5,iouThreshold:.2,maxDetected:-1,landmarks:!0,detector:{modelPath:"handtrack.json"},skeleton:{modelPath:"handlandmark-full.json"}},object:{enabled:!1,modelPath:"mb3-centernet.json",minConfidence:.2,iouThreshold:.4,maxDetected:10,skipFrames:99,skipTime:2e3},segmentation:{enabled:!1,modelPath:"selfie.json",blur:8}};var p0=Z(D());var O=Z(D());var ht=`
   precision highp float;
   attribute vec2 pos;
   attribute vec2 uv;
@@ -96,7 +96,7 @@ var An=Object.create;var h2=Object.defineProperty;var sn=Object.getOwnPropertyDe
     c31 * m[6] + c32 * m[7] + c33 * m[8];
     gl_FragColor.a = c22.a;
   }
-`;var C5=(e,t,o)=>{let n=new RegExp("\\b"+t+" \\w+ (\\w+)","ig");e.replace(n,(r,A)=>(o[A]=0,r))},j5=class{constructor(t,o,n){T(this,"uniform",{});T(this,"attribute",{});T(this,"gl");T(this,"id");T(this,"compile",(t,o)=>{let n=this.gl.createShader(o);return n?(this.gl.shaderSource(n,t),this.gl.compileShader(n),this.gl.getShaderParameter(n,this.gl.COMPILE_STATUS)?n:(p(`filter: gl compile failed: ${this.gl.getShaderInfoLog(n)}`),null)):(p("filter: could not create shader"),null)});this.gl=t;let r=this.compile(o,this.gl.VERTEX_SHADER),A=this.compile(n,this.gl.FRAGMENT_SHADER);if(this.id=this.gl.createProgram(),!(!r||!A)){if(!this.id){p("filter: could not create webgl program");return}if(this.gl.attachShader(this.id,r),this.gl.attachShader(this.id,A),this.gl.linkProgram(this.id),!this.gl.getProgramParameter(this.id,this.gl.LINK_STATUS)){p(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);return}this.gl.useProgram(this.id),C5(o,"attribute",this.attribute);for(let s in this.attribute)this.attribute[s]=this.gl.getAttribLocation(this.id,s);C5(o,"uniform",this.uniform),C5(n,"uniform",this.uniform);for(let s in this.uniform)this.uniform[s]=this.gl.getUniformLocation(this.id,s)}}};function vt(){let e=0,t=null,o=!1,n=-1,r=[null,null],A=[],s=null,a=null,i=R0(100,100),x={},c={INTERMEDIATE:1},l=i.getContext("webgl");if(!l){p("filter: cannot get webgl context");return}this.gl=l;function y(b,d){if(!(b===i.width&&d===i.height)){if(i.width=b,i.height=d,!s){let M=new Float32Array([-1,-1,0,1,1,-1,1,1,-1,1,0,0,-1,1,0,0,1,-1,1,1,1,1,1,0]);s=l.createBuffer(),l.bindBuffer(l.ARRAY_BUFFER,s),l.bufferData(l.ARRAY_BUFFER,M,l.STATIC_DRAW),l.pixelStorei(l.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}l.viewport(0,0,i.width,i.height),r=[null,null]}}function f(b,d){let M=l.createFramebuffer();l.bindFramebuffer(l.FRAMEBUFFER,M);let S=l.createRenderbuffer();l.bindRenderbuffer(l.RENDERBUFFER,S);let w=l.createTexture();return l.bindTexture(l.TEXTURE_2D,w),l.texImage2D(l.TEXTURE_2D,0,l.RGBA,b,d,0,l.RGBA,l.UNSIGNED_BYTE,null),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MAG_FILTER,l.LINEAR),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MIN_FILTER,l.LINEAR),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_S,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_T,l.CLAMP_TO_EDGE),l.framebufferTexture2D(l.FRAMEBUFFER,l.COLOR_ATTACHMENT0,l.TEXTURE_2D,w,0),l.bindTexture(l.TEXTURE_2D,null),l.bindFramebuffer(l.FRAMEBUFFER,null),{fbo:M,texture:w}}function u(b){return r[b]=r[b]||f(i.width,i.height),r[b]}function m(b=0){if(!a)return;let d=null,M=null,S=!1;e===0?d=t:d=u(n).texture||null,e++,o&&!(b&c.INTERMEDIATE)?(M=null,S=e%2===0):(n=(n+1)%2,M=u(n).fbo||null),l.bindTexture(l.TEXTURE_2D,d),l.bindFramebuffer(l.FRAMEBUFFER,M),l.uniform1f(a.uniform.flipY,S?-1:1),l.drawArrays(l.TRIANGLES,0,6)}function P(b){if(x[b])return a=x[b],l.useProgram((a?a.id:null)||null),a;if(a=new j5(l,ht,b),!a)return p("filter: could not get webgl program"),null;let d=Float32Array.BYTES_PER_ELEMENT,M=4*d;return l.enableVertexAttribArray(a.attribute.pos),l.vertexAttribPointer(a.attribute.pos,2,l.FLOAT,!1,M,0*d),l.enableVertexAttribArray(a.attribute.uv),l.vertexAttribPointer(a.attribute.uv,2,l.FLOAT,!1,M,2*d),x[b]=a,a}let g={colorMatrix:b=>{let d=new Float32Array(b);d[4]/=255,d[9]/=255,d[14]/=255,d[19]/=255;let M=d[18]===1&&d[3]===0&&d[8]===0&&d[13]===0&&d[15]===0&&d[16]===0&&d[17]===0&&d[19]===0?gt:bt,S=P(M);!S||(l.uniform1fv(S.uniform.m,d),m())},brightness:b=>{let d=(b||0)+1;g.colorMatrix([d,0,0,0,0,0,d,0,0,0,0,0,d,0,0,0,0,0,1,0])},saturation:b=>{let d=(b||0)*2/3+1,M=(d-1)*-.5;g.colorMatrix([d,M,M,0,0,M,d,M,0,0,M,M,d,0,0,0,0,0,1,0])},desaturate:()=>{g.saturation(-1)},contrast:b=>{let d=(b||0)+1,M=-128*(d-1);g.colorMatrix([d,0,0,0,M,0,d,0,0,M,0,0,d,0,M,0,0,0,1,0])},negative:()=>{g.contrast(-2)},hue:b=>{b=(b||0)/180*Math.PI;let d=Math.cos(b),M=Math.sin(b),S=.213,w=.715,j=.072;g.colorMatrix([S+d*(1-S)+M*-S,w+d*-w+M*-w,j+d*-j+M*(1-j),0,0,S+d*-S+M*.143,w+d*(1-w)+M*.14,j+d*-j+M*-.283,0,0,S+d*-S+M*-(1-S),w+d*-w+M*w,j+d*(1-j)+M*j,0,0,0,0,0,1,0])},desaturateLuminance:()=>{g.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},sepia:()=>{g.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},brownie:()=>{g.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},vintagePinhole:()=>{g.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},kodachrome:()=>{g.colorMatrix([1.1285582396593525,-.3967382283601348,-.03992559172921793,0,63.72958762196502,-.16404339962244616,1.0835251566291304,-.05498805115633132,0,24.732407896706203,-.16786010706155763,-.5603416277695248,1.6014850761964943,0,35.62982807460946,0,0,0,1,0])},technicolor:()=>{g.colorMatrix([1.9125277891456083,-.8545344976951645,-.09155508482755585,0,11.793603434377337,-.3087833385928097,1.7658908555458428,-.10601743074722245,0,-70.35205161461398,-.231103377548616,-.7501899197440212,1.847597816108189,0,30.950940869491138,0,0,0,1,0])},polaroid:()=>{g.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},shiftToBGR:()=>{g.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},convolution:b=>{let d=new Float32Array(b),M=1/i.width,S=1/i.height,w=P(Rt);!w||(l.uniform1fv(w.uniform.m,d),l.uniform2f(w.uniform.px,M,S),m())},detectEdges:()=>{g.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},sobelX:()=>{g.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},sobelY:()=>{g.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},sharpen:b=>{let d=b||1;g.convolution.call(this,[0,-1*d,0,-1*d,1+4*d,-1*d,0,-1*d,0])},emboss:b=>{let d=b||1;g.convolution.call(this,[-2*d,-1*d,0,-1*d,1,1*d,0,1*d,2*d])},blur:b=>{let d=b/7/i.width,M=b/7/i.height,S=P(Pt);!S||(l.uniform2f(S.uniform.px,0,M),m(c.INTERMEDIATE),l.uniform2f(S.uniform.px,d,0),m())},pixelate:b=>{let d=b/i.width,M=b/i.height,S=P(Mt);!S||(l.uniform2f(S.uniform.size,d,M),m())}};this.add=function(b){let d=Array.prototype.slice.call(arguments,1),M=g[b];A.push({func:M,args:d})},this.reset=function(){A=[]},this.get=function(){return A},this.apply=function(b){y(b.width,b.height),e=0,t||(t=l.createTexture()),l.bindTexture(l.TEXTURE_2D,t),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_S,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_T,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MIN_FILTER,l.NEAREST),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MAG_FILTER,l.NEAREST),l.texImage2D(l.TEXTURE_2D,0,l.RGBA,l.RGBA,l.UNSIGNED_BYTE,b);for(let d=0;d<A.length;d++){o=d===A.length-1;let M=A[d];M.func.apply(this,M.args||[])}return i},this.draw=function(b){return this.add("brightness",0),this.apply(b)}}var X=Z(D());async function O2(e){let t=e.shape.length===4?X.squeeze(e):e,o=X.split(t,3,2),n=[X.min(o[0]),X.min(o[1]),X.min(o[2])],r=[X.max(o[0]),X.max(o[1]),X.max(o[2])],A=await Promise.all(r.map(f=>f.data())),s=.99*Math.max(A[0][0],A[1][0],A[2][0]),a=[X.sub(o[0],n[0]),X.sub(o[1],n[1]),X.sub(o[2],n[2])],i=[X.sub(r[0],n[0]),X.sub(r[1],n[1]),X.sub(r[2],n[2])],x=[X.div(s,i[0]),X.div(s,i[1]),X.div(s,i[2])],c=[X.mul(a[0],x[0]),X.mul(a[1],x[1]),X.mul(a[2],x[2])],l=X.stack([c[0],c[1],c[2]],2),y=X.reshape(l,[1,t.shape[0],t.shape[1],3]);return X.dispose([...o,...n,...r,...a,...i,...x,...c,l,t]),y}var L2=3840,q=null,i0=null,Ue=null,e0,ae={inputSum:0,cacheDiff:1,sumMethod:0,inputTensor:void 0};function R0(e,t){let o;if(v.browser)if(v.worker){if(typeof OffscreenCanvas=="undefined")throw new Error("canvas error: attempted to run in web worker but OffscreenCanvas is not supported");o=new OffscreenCanvas(e,t)}else{if(typeof document=="undefined")throw new Error("canvas error: attempted to run in browser but DOM is not defined");o=document.createElement("canvas"),o.width=e,o.height=t}else typeof v.Canvas!="undefined"?o=new v.Canvas(e,t):typeof globalThis.Canvas!="undefined"&&(o=new globalThis.Canvas(e,t));return o}function W2(e,t){let o=t||R0(e.width,e.height);return o.getContext("2d").drawImage(e,0,0),o}async function Ye(e,t,o=!0){if(!e)return t.debug&&p("input error: input is missing"),{tensor:null,canvas:null};if(!(e instanceof N.Tensor)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(typeof v.Canvas!="undefined"&&e instanceof v.Canvas)&&!(typeof globalThis.Canvas!="undefined"&&e instanceof globalThis.Canvas)&&!(typeof ImageData!="undefined"&&e instanceof ImageData)&&!(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)&&!(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)&&!(typeof HTMLMediaElement!="undefined"&&e instanceof HTMLMediaElement)&&!(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)&&!(typeof HTMLCanvasElement!="undefined"&&e instanceof HTMLCanvasElement)&&!(typeof OffscreenCanvas!="undefined"&&e instanceof OffscreenCanvas))throw new Error("input error: type is not recognized");if(e instanceof N.Tensor){let n=null;if(e.isDisposedInternal)throw new Error("input error: attempted to use tensor but it is disposed");if(!e.shape)throw new Error("input error: attempted to use tensor without a shape");if(e.shape.length===3){if(e.shape[2]===3)n=N.expandDims(e,0);else if(e.shape[2]===4){let r=N.slice3d(e,[0,0,0],[-1,-1,3]);n=N.expandDims(r,0),N.dispose(r)}}else e.shape.length===4&&(e.shape[3]===3?n=N.clone(e):e.shape[3]===4&&(n=N.slice4d(e,[0,0,0,0],[-1,-1,-1,3])));if(n==null||n.shape.length!==4||n.shape[0]!==1||n.shape[3]!==3)throw new Error(`input error: attempted to use tensor with unrecognized shape: ${e.shape}`);if(n.dtype==="int32"){let r=N.cast(n,"float32");N.dispose(n),n=r}return{tensor:n,canvas:t.filter.return?i0:null}}else{if(typeof e.readyState!="undefined"&&e.readyState<=2)return t.debug&&p("input stream is not ready"),{tensor:null,canvas:q};let n=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,r=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0;if(!n||!r)return t.debug&&p("cannot determine input dimensions"),{tensor:null,canvas:q};let A=n,s=r;if(A>L2&&(A=L2,s=Math.trunc(A*r/n)),s>L2&&(s=L2,A=Math.trunc(s*n/r)),(t.filter.width||0)>0?A=t.filter.width:(t.filter.height||0)>0&&(A=n*((t.filter.height||0)/r)),(t.filter.height||0)>0?s=t.filter.height:(t.filter.width||0)>0&&(s=r*((t.filter.width||0)/n)),!A||!s)throw new Error("input error: cannot determine dimension");(!q||(q==null?void 0:q.width)!==A||(q==null?void 0:q.height)!==s)&&(q=R0(A,s));let a=q.getContext("2d");if(typeof ImageData!="undefined"&&e instanceof ImageData?a.putImageData(e,0,0):t.filter.flip&&typeof a.translate!="undefined"?(a.translate(n,0),a.scale(-1,1),a.drawImage(e,0,0,n,r,0,0,q==null?void 0:q.width,q==null?void 0:q.height),a.setTransform(1,0,0,1,0,0)):a.drawImage(e,0,0,n,r,0,0,q==null?void 0:q.width,q==null?void 0:q.height),(!i0||q.width!==i0.width||(q==null?void 0:q.height)!==(i0==null?void 0:i0.height))&&(i0=R0(q.width,q.height)),t.filter.enabled&&v.webgl.supported?(e0||(e0=v.browser?new vt:null),v.filter=!!e0,!e0||!e0.add?(t.debug&&p("input process error: cannot initialize filters"),v.webgl.supported=!1,t.filter.enabled=!1,W2(q,i0)):(e0.reset(),t.filter.brightness!==0&&e0.add("brightness",t.filter.brightness),t.filter.contrast!==0&&e0.add("contrast",t.filter.contrast),t.filter.sharpness!==0&&e0.add("sharpen",t.filter.sharpness),t.filter.blur!==0&&e0.add("blur",t.filter.blur),t.filter.saturation!==0&&e0.add("saturation",t.filter.saturation),t.filter.hue!==0&&e0.add("hue",t.filter.hue),t.filter.negative&&e0.add("negative"),t.filter.sepia&&e0.add("sepia"),t.filter.vintage&&e0.add("brownie"),t.filter.sepia&&e0.add("sepia"),t.filter.kodachrome&&e0.add("kodachrome"),t.filter.technicolor&&e0.add("technicolor"),t.filter.polaroid&&e0.add("polaroid"),t.filter.pixelate!==0&&e0.add("pixelate",t.filter.pixelate),e0.get()>0?i0=e0.apply(q):i0=e0.draw(q))):(W2(q,i0),e0&&(e0=null),v.filter=!!e0),!o)return{tensor:null,canvas:i0};if(!i0)throw new Error("canvas error: cannot create output");let i,x=3;if(typeof ImageData!="undefined"&&e instanceof ImageData||e.data&&e.width&&e.height)if(v.browser&&N.browser)i=N.browser?N.browser.fromPixels(e):null;else{x=e.data.length/e.height/e.width;let y=new Uint8Array(e.data.buffer);i=N.tensor(y,[e.height,e.width,x],"int32")}else if((!Ue||i0.width!==Ue.width||i0.height!==Ue.height)&&(Ue=R0(i0.width,i0.height)),N.browser&&v.browser)t.backend==="webgl"||t.backend==="humangl"||t.backend==="webgpu"?i=N.browser.fromPixels(i0):(Ue=W2(i0),i=N.browser.fromPixels(Ue));else{let u=W2(i0).getContext("2d").getImageData(0,0,A,s);x=u.data.length/A/s;let m=new Uint8Array(u.data.buffer);i=N.tensor(m,[A,s,x])}if(x===4){let y=N.slice3d(i,[0,0,0],[-1,-1,3]);N.dispose(i),i=y}if(!i)throw new Error("input error: cannot create tensor");let c=N.cast(i,"float32"),l=t.filter.equalization?await O2(c):N.expandDims(c,0);return N.dispose([i,c]),{tensor:l,canvas:t.filter.return?i0:null}}}async function Tt(e,t){let o=!1;if(e.cacheSensitivity===0||!t.shape||t.shape.length!==4||t.shape[1]>2048||t.shape[2]>2048)return o;if(!ae.inputTensor)ae.inputTensor=N.clone(t);else if(ae.inputTensor.shape[1]!==t.shape[1]||ae.inputTensor.shape[2]!==t.shape[2])N.dispose(ae.inputTensor),ae.inputTensor=N.clone(t);else{let n={};n.diff=N.sub(t,ae.inputTensor),n.squared=N.mul(n.diff,n.diff),n.sum=N.sum(n.squared);let A=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;N.dispose([ae.inputTensor,n.diff,n.squared,n.sum]),ae.inputTensor=N.clone(t),o=A<=(e.cacheSensitivity||0)}return o}async function wt(e,t,o){let n={};if(!t||!o||t.shape.length!==4||t.shape.length!==o.shape.length)return e.debug||p("invalid input tensor or tensor shapes do not match:",t.shape,o.shape),0;if(t.shape[0]!==1||o.shape[0]!==1||t.shape[3]!==3||o.shape[3]!==3)return e.debug||p("input tensors must be of shape [1, height, width, 3]:",t.shape,o.shape),0;n.input1=N.clone(t),n.input2=t.shape[1]!==o.shape[1]||t.shape[2]!==o.shape[2]?N.image.resizeBilinear(o,[t.shape[1],t.shape[2]]):N.clone(o),n.diff=N.sub(n.input1,n.input2),n.squared=N.mul(n.diff,n.diff),n.sum=N.sum(n.squared);let A=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;return N.dispose([n.input1,n.input2,n.diff,n.squared,n.sum]),A}var I5=class{constructor(){T(this,"browser");T(this,"node");T(this,"worker");T(this,"platform","");T(this,"agent","");T(this,"backends",[]);T(this,"initial");T(this,"filter");T(this,"tfjs");T(this,"offscreen");T(this,"perfadd",!1);T(this,"wasm",{supported:void 0,backend:void 0,simd:void 0,multithread:void 0});T(this,"webgl",{supported:void 0,backend:void 0,version:void 0,renderer:void 0});T(this,"webgpu",{supported:void 0,backend:void 0,adapter:void 0});T(this,"cpu",{model:void 0,flags:[]});T(this,"kernels",[]);T(this,"Canvas");T(this,"Image");T(this,"ImageData");if(this.browser=typeof navigator!="undefined",this.node=typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined",this.tfjs={version:p0.version["tfjs-core"]},this.offscreen=typeof OffscreenCanvas!="undefined",this.initial=!0,this.worker=this.browser&&this.offscreen?typeof WorkerGlobalScope!="undefined":void 0,typeof navigator!="undefined"){let t=navigator.userAgent.match(/\(([^()]+)\)/g);if(t&&t[0]){let o=t[0].match(/\(([^()]+)\)/g);this.platform=o&&o[0]?o[0].replace(/\(|\)/g,""):"",this.agent=navigator.userAgent.replace(t[0],""),this.platform[1]&&(this.agent=this.agent.replace(t[1],"")),this.agent=this.agent.replace(/  /g," ")}}else typeof process!="undefined"&&(this.platform=`${process.platform} ${process.arch}`,this.agent=`NodeJS ${process.version}`)}async updateBackend(){this.backends=Object.keys(p0.engine().registryFactory),this.wasm.supported=typeof WebAssembly!="undefined",this.wasm.backend=this.backends.includes("wasm"),this.wasm.supported&&this.wasm.backend&&p0.getBackend()==="wasm"&&(this.wasm.simd=await p0.env().getAsync("WASM_HAS_SIMD_SUPPORT"),this.wasm.multithread=await p0.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT"));let t=R0(100,100),o=t?t.getContext("webgl2"):void 0;if(this.webgl.supported=typeof o!="undefined",this.webgl.backend=this.backends.includes("webgl"),this.webgl.supported&&this.webgl.backend&&(p0.getBackend()==="webgl"||p0.getBackend()==="humangl")){let n=p0.backend().gpgpu!=="undefined"?await p0.backend().getGPGPUContext().gl:null;n&&(this.webgl.version=n.getParameter(n.VERSION),this.webgl.renderer=n.getParameter(n.RENDERER))}this.webgpu.supported=this.browser&&typeof navigator.gpu!="undefined",this.webgpu.backend=this.backends.includes("webgpu");try{this.webgpu.supported&&(this.webgpu.adapter=(await navigator.gpu.requestAdapter()).name)}catch(n){this.webgpu.supported=!1}try{this.kernels=p0.getKernelsForBackend(p0.getBackend()).map(n=>n.kernelName.toLowerCase())}catch(n){}}async updateCPU(){let t={model:"",flags:[]};this.node&&this.platform.startsWith("linux"),this.cpu?this.cpu=t:Object.defineProperty(this,"cpu",{value:t})}},v=new I5;var F2=Z(D());var N5={};ue(N5,{age:()=>Pn,antispoof:()=>Rn,blazeface:()=>wn,"blazeface-back":()=>vn,"blazeface-front":()=>Tn,"blazepose-detector2d":()=>kn,"blazepose-detector3d":()=>En,"blazepose-full":()=>zn,"blazepose-heavy":()=>Sn,"blazepose-lite":()=>Cn,default:()=>yr,efficientpose:()=>jn,emotion:()=>In,faceboxes:()=>Nn,facemesh:()=>Bn,"facemesh-attention":()=>Ln,"facemesh-attention-alt":()=>On,"facemesh-detection-full":()=>Wn,"facemesh-detection-short":()=>Fn,"facemesh-orig":()=>Gn,faceres:()=>Vn,"faceres-deep":()=>Hn,gear:()=>Dn,gender:()=>Xn,"gender-ssrnet-imdb":()=>Zn,handdetect:()=>qn,"handlandmark-full":()=>Un,"handlandmark-lite":()=>Yn,"handlandmark-sparse":()=>Kn,handskeleton:()=>Jn,handtrack:()=>Qn,iris:()=>_n,liveness:()=>$n,"mb3-centernet":()=>er,meet:()=>tr,mobileface:()=>or,mobilefacenet:()=>nr,"movenet-lightning":()=>rr,"movenet-multipose":()=>Ar,"movenet-thunder":()=>sr,nanodet:()=>ar,posenet:()=>ir,selfie:()=>lr});var Pn=161240,Rn=853098,vn=538928,Tn=402048,wn=538928,kn=7499400,En=5928856,zn=6338290,Sn=27501554,Cn=2725490,jn=5651240,In=820516,Nn=2013002,On=2387598,Ln=2382414,Wn=1026192,Fn=201268,Gn=2955780,Bn=1477958,Hn=13957620,Vn=6978814,Dn=1498916,Zn=161236,Xn=201808,qn=3515612,Un=5431368,Yn=2023432,Kn=5286322,Jn=5502280,Qn=2964837,_n=2599092,$n=592976,er=4030290,tr=372228,or=2183192,nr=5171976,rr=4650216,Ar=9448838,sr=12477112,ar=7574558,ir=5032780,lr=212886,yr={age:Pn,antispoof:Rn,"blazeface-back":vn,"blazeface-front":Tn,blazeface:wn,"blazepose-detector2d":kn,"blazepose-detector3d":En,"blazepose-full":zn,"blazepose-heavy":Sn,"blazepose-lite":Cn,efficientpose:jn,emotion:In,faceboxes:Nn,"facemesh-attention-alt":On,"facemesh-attention":Ln,"facemesh-detection-full":Wn,"facemesh-detection-short":Fn,"facemesh-orig":Gn,facemesh:Bn,"faceres-deep":Hn,faceres:Vn,gear:Dn,"gender-ssrnet-imdb":Zn,gender:Xn,handdetect:qn,"handlandmark-full":Un,"handlandmark-lite":Yn,"handlandmark-sparse":Kn,handskeleton:Jn,handtrack:Qn,iris:_n,liveness:$n,"mb3-centernet":er,meet:tr,mobileface:or,mobilefacenet:nr,"movenet-lightning":rr,"movenet-multipose":Ar,"movenet-thunder":sr,nanodet:ar,posenet:ir,selfie:lr};var v0={cacheModels:!0,cacheSupported:!0,verbose:!0,debug:!1,modelBasePath:""},q0={};async function xr(e,t){return v0.debug&&p("load model fetch:",e,t),fetch(e,t)}function kt(e){v0.cacheModels=e.cacheModels,v0.verbose=e.debug,v0.modelBasePath=e.modelBasePath}async function G(e){var x,c,l;let t=mt(v0.modelBasePath,e||"");t.toLowerCase().endsWith(".json")||(t+=".json");let o=t.includes("/")?t.split("/"):t.split("\\"),n=o[o.length-1].replace(".json",""),r="indexeddb://"+n;q0[n]={name:n,sizeFromManifest:0,sizeLoadedWeights:0,sizeDesired:N5[n],inCache:!1},v0.cacheSupported=typeof window!="undefined"&&typeof window.localStorage!="undefined"&&typeof window.indexedDB!="undefined";let A={};try{A=v0.cacheSupported&&v0.cacheModels?await F2.io.listModels():{}}catch(y){v0.cacheSupported=!1}q0[n].inCache=v0.cacheSupported&&v0.cacheModels&&Object.keys(A).includes(r);let s=typeof fetch=="undefined"?{}:{fetchFunc:(y,f)=>xr(y,f)},a=new F2.GraphModel(q0[n].inCache?r:t,s),i=!1;try{a.findIOHandler(),v0.debug&&p("model load handler:",a.handler);let y=await a.handler.load();q0[n].sizeFromManifest=((x=y==null?void 0:y.weightData)==null?void 0:x.byteLength)||0,a.loadSync(y),q0[n].sizeLoadedWeights=((l=(c=a==null?void 0:a.artifacts)==null?void 0:c.weightData)==null?void 0:l.byteLength)||0,v0.verbose&&p("load model:",a.modelUrl,{bytes:q0[n].sizeLoadedWeights},v0),i=!0}catch(y){p("error loading model:",t,y)}if(i&&v0.cacheModels&&v0.cacheSupported&&!q0[n].inCache)try{let y=await a.save(r);p("model saved:",r,y)}catch(y){p("error saving model:",t,y)}return a}var ee=Z(D());var O5="2.9.1";var y0=Z(D());var R5={};ue(R5,{Models:()=>C2,getModelStats:()=>q1,load:()=>U1,reset:()=>P5,validate:()=>Y1});var G2=Z(D());var D0,L5=[],fr=["white","black","asian","indian","other"],mr=[15,23,28,35.5,45.5,55.5,65],Et=0,zt=0,W5=Number.MAX_SAFE_INTEGER;async function St(e){var t;return v.initial&&(D0=null),D0?e.debug&&p("cached model:",D0.modelUrl):D0=await G((t=e.face.gear)==null?void 0:t.modelPath),D0}async function F5(e,t,o,n){var s,a;if(!D0)return{age:0,gender:"unknown",genderScore:0,race:[]};let r=W5<(((s=t.face.gear)==null?void 0:s.skipFrames)||0),A=(((a=t.face.gear)==null?void 0:a.skipTime)||0)>h()-zt;return t.skipAllowed&&A&&r&&Et===n&&L5[o]?(W5++,L5[o]):(W5=0,new Promise(async i=>{var g,b;if(!(D0!=null&&D0.inputs[0].shape))return;let x={},c=[[0,.1,.9,.9]];x.resize=G2.image.cropAndResize(e,c,[0],[D0.inputs[0].shape[2],D0.inputs[0].shape[1]]);let l={age:0,gender:"unknown",genderScore:0,race:[]};(g=t.face.gear)!=null&&g.enabled&&([x.age,x.gender,x.race]=D0.execute(x.resize,["age_output","gender_output","race_output"]));let y=await x.gender.data();l.gender=y[0]>y[1]?"male":"female",l.genderScore=Math.round(100*(y[0]>y[1]?y[0]:y[1]))/100;let f=await x.race.data();for(let d=0;d<f.length;d++)f[d]>(((b=t.face.gear)==null?void 0:b.minConfidence)||.2)&&l.race.push({score:Math.round(100*f[d])/100,race:fr[d]});l.race.sort((d,M)=>M.score-d.score);let m=Array.from(await x.age.data()).map((d,M)=>[mr[M],d]).sort((d,M)=>M[1]-d[1]),P=m[0][0];for(let d=1;d<m.length;d++)P+=m[d][1]*(m[d][0]-P);l.age=Math.round(10*P)/10,Object.keys(x).forEach(d=>G2.dispose(x[d])),L5[o]=l,Et=n,zt=h(),i(l)}))}var Ke=Z(D());var be=Z(D()),V={tf255:255,tf1:1,tf2:2,tf05:.5,tf127:127.5,rgb:[.2989,.587,.114]};function jt(){V.tf255=be.scalar(255,"float32"),V.tf1=be.scalar(1,"float32"),V.tf2=be.scalar(2,"float32"),V.tf05=be.scalar(.5,"float32"),V.tf127=be.scalar(127.5,"float32"),V.rgb=be.tensor1d([.2989,.587,.114],"float32")}var S0,B2=[],It=0,Nt=0,G5=Number.MAX_SAFE_INTEGER;async function Ot(e){return v.initial&&(S0=null),S0?e.debug&&p("cached model:",S0.modelUrl):S0=await G(e.face.ssrnet.modelPathAge),S0}async function B5(e,t,o,n){var s,a,i,x;if(!S0)return{age:0};let r=G5<(((s=t.face.ssrnet)==null?void 0:s.skipFrames)||0),A=(((a=t.face.ssrnet)==null?void 0:a.skipTime)||0)>h()-Nt;return t.skipAllowed&&r&&A&&It===n&&((i=B2[o])==null?void 0:i.age)&&((x=B2[o])==null?void 0:x.age)>0?(G5++,B2[o]):(G5=0,new Promise(async c=>{if(!(S0!=null&&S0.inputs)||!S0.inputs[0]||!S0.inputs[0].shape)return;let l={};l.resize=Ke.image.resizeBilinear(e,[S0.inputs[0].shape[2],S0.inputs[0].shape[1]],!1),l.enhance=Ke.mul(l.resize,V.tf255);let y={age:0};if(t.face.ssrnet.enabled&&(l.age=S0.execute(l.enhance)),l.age){let f=await l.age.data();y.age=Math.trunc(10*f[0])/10}Object.keys(l).forEach(f=>Ke.dispose(l[f])),B2[o]=y,It=n,Nt=h(),c(y)}))}var u0=Z(D());var Z0,H2=[],Wt=0,Ft=0,H5=Number.MAX_SAFE_INTEGER,V5=[.2989,.587,.114];async function Gt(e){return v.initial&&(Z0=null),Z0?e.debug&&p("cached model:",Z0.modelUrl):Z0=await G(e.face.ssrnet.modelPathGender),Z0}async function D5(e,t,o,n){var s,a,i,x;if(!Z0)return{gender:"unknown",genderScore:0};let r=H5<(((s=t.face.ssrnet)==null?void 0:s.skipFrames)||0),A=(((a=t.face.ssrnet)==null?void 0:a.skipTime)||0)>h()-Ft;return t.skipAllowed&&r&&A&&Wt===n&&((i=H2[o])==null?void 0:i.gender)&&((x=H2[o])==null?void 0:x.genderScore)>0?(H5++,H2[o]):(H5=0,new Promise(async c=>{if(!(Z0!=null&&Z0.inputs[0].shape))return;let l={};l.resize=u0.image.resizeBilinear(e,[Z0.inputs[0].shape[2],Z0.inputs[0].shape[1]],!1),l.enhance=u0.tidy(()=>{let[u,m,P]=u0.split(l.resize,3,3),g=u0.mul(u,V5[0]),b=u0.mul(m,V5[1]),d=u0.mul(P,V5[2]),M=u0.addN([g,b,d]);return u0.mul(u0.sub(M,V.tf05),2)});let y={gender:"unknown",genderScore:0};t.face.ssrnet.enabled&&(l.gender=Z0.execute(l.enhance));let f=await l.gender.data();y.gender=f[0]>f[1]?"female":"male",y.genderScore=f[0]>f[1]?Math.trunc(100*f[0])/100:Math.trunc(100*f[1])/100,Object.keys(l).forEach(u=>u0.dispose(l[u])),H2[o]=y,Wt=n,Ft=h(),c(y)}))}var D2=Z(D());var h0,V2=[],Z5=Number.MAX_SAFE_INTEGER,Ht=0,Vt=0;async function Dt(e){var t;return v.initial&&(h0=null),h0?e.debug&&p("cached model:",h0.modelUrl):h0=await G((t=e.face.antispoof)==null?void 0:t.modelPath),h0}async function X5(e,t,o,n){var s,a;if(!h0)return 0;let r=(((s=t.face.antispoof)==null?void 0:s.skipTime)||0)>h()-Vt,A=Z5<(((a=t.face.antispoof)==null?void 0:a.skipFrames)||0);return t.skipAllowed&&r&&A&&Ht===n&&V2[o]?(Z5++,V2[o]):(Z5=0,new Promise(async i=>{let x=D2.image.resizeBilinear(e,[h0!=null&&h0.inputs[0].shape?h0.inputs[0].shape[2]:0,h0!=null&&h0.inputs[0].shape?h0.inputs[0].shape[1]:0],!1),c=h0==null?void 0:h0.execute(x),l=(await c.data())[0];V2[o]=Math.round(100*l)/100,Ht=n,Vt=h(),D2.dispose([x,c]),i(V2[o])}))}var O=Z(D());var ie=Z(D());var X0={silhouette:[10,338,297,332,284,251,389,356,454,323,361,288,397,365,379,378,400,377,152,148,176,149,150,136,172,58,132,93,234,127,162,21,54,103,67,109],lipsUpperOuter:[185,40,39,37,0,267,269,270,409],lipsLowerOuter:[61,146,91,181,84,17,314,405,321,375,291],lipsUpperInner:[191,80,81,82,13,312,311,310,415],lipsLowerInner:[78,95,88,178,87,14,317,402,318,324,308],lipsLowerSemiOuter:[76,77,90,180,85,16,315,404,320,307,306],lipsUpperSemiOuter:[184,74,73,72,11,302,303,304,408],lipsLowerSemiInner:[62,96,89,179,86,15,316,403,319,325,292],lipsUpperSemiInner:[183,42,41,38,12,268,271,272,407],rightEyeUpper0:[246,161,160,159,158,157,173],rightEyeLower0:[33,7,163,144,145,153,154,155,133],rightEyeUpper1:[247,30,29,27,28,56,190],rightEyeLower1:[130,25,110,24,23,22,26,112,243],rightEyeUpper2:[113,225,224,223,222,221,189],rightEyeLower2:[226,31,228,229,230,231,232,233,244],rightEyeLower3:[143,111,117,118,119,120,121,128,245],rightEyebrowUpper:[156,70,63,105,66,107,55,193],rightEyebrowLower:[35,124,46,53,52,65],rightEyeIris:[473,474,475,476,477],leftEyeUpper0:[466,388,387,386,385,384,398],leftEyeLower0:[263,249,390,373,374,380,381,382,362],leftEyeUpper1:[467,260,259,257,258,286,414],leftEyeLower1:[359,255,339,254,253,252,256,341,463],leftEyeUpper2:[342,445,444,443,442,441,413],leftEyeLower2:[446,261,448,449,450,451,452,453,464],leftEyeLower3:[372,340,346,347,348,349,350,357,465],leftEyebrowUpper:[383,300,293,334,296,336,285,417],leftEyebrowLower:[265,353,276,283,282,295],leftEyeIris:[468,469,470,471,472],midwayBetweenEyes:[168],noseTip:[1],noseBottom:[2],noseRightCorner:[98],noseLeftCorner:[327],rightCheek:[205],leftCheek:[425]},q5={count:468,mouth:13,symmetryLine:[13,X0.midwayBetweenEyes[0]]},Ie={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},U5=[{key:"EyeUpper0",indices:[9,10,11,12,13,14,15]},{key:"EyeUpper1",indices:[25,26,27,28,29,30,31]},{key:"EyeUpper2",indices:[41,42,43,44,45,46,47]},{key:"EyeLower0",indices:[0,1,2,3,4,5,6,7,8]},{key:"EyeLower1",indices:[16,17,18,19,20,21,22,23,24]},{key:"EyeLower2",indices:[32,33,34,35,36,37,38,39,40]},{key:"EyeLower3",indices:[54,55,56,57,58,59,60,61,62]},{key:"EyebrowUpper",indices:[63,64,65,66,67,68,69,70]},{key:"EyebrowLower",indices:[48,49,50,51,52,53]}],R2=[[.499976992607117,.652534008026123],[.500025987625122,.547487020492554],[.499974012374878,.602371990680695],[.482113003730774,.471979022026062],[.500150978565216,.527155995368958],[.499909996986389,.498252987861633],[.499523013830185,.40106201171875],[.289712011814117,.380764007568359],[.499954998493195,.312398016452789],[.499987006187439,.269918978214264],[.500023007392883,.107050001621246],[.500023007392883,.666234016418457],[.5000159740448,.679224014282227],[.500023007392883,.692348003387451],[.499976992607117,.695277988910675],[.499976992607117,.70593398809433],[.499976992607117,.719385027885437],[.499976992607117,.737019002437592],[.499967992305756,.781370997428894],[.499816000461578,.562981009483337],[.473773002624512,.573909997940063],[.104906998574734,.254140973091125],[.365929991006851,.409575998783112],[.338757991790771,.41302502155304],[.311120003461838,.409460008144379],[.274657994508743,.389131009578705],[.393361985683441,.403706014156342],[.345234006643295,.344011008739471],[.370094001293182,.346076011657715],[.319321990013123,.347265005111694],[.297903001308441,.353591024875641],[.24779200553894,.410809993743896],[.396889001131058,.842755019664764],[.280097991228104,.375599980354309],[.106310002505779,.399955987930298],[.2099249958992,.391353011131287],[.355807989835739,.534406006336212],[.471751004457474,.65040397644043],[.474155008792877,.680191993713379],[.439785003662109,.657229006290436],[.414617002010345,.66654098033905],[.450374007225037,.680860996246338],[.428770989179611,.682690978050232],[.374971002340317,.727805018424988],[.486716985702515,.547628998756409],[.485300987958908,.527395009994507],[.257764995098114,.314490020275116],[.401223003864288,.455172002315521],[.429818987846375,.548614978790283],[.421351999044418,.533740997314453],[.276895999908447,.532056987285614],[.483370006084442,.499586999416351],[.33721199631691,.282882988452911],[.296391993761063,.293242990970612],[.169294998049736,.193813979625702],[.447580009698868,.302609980106354],[.392390012741089,.353887975215912],[.354490011930466,.696784019470215],[.067304998636246,.730105042457581],[.442739009857178,.572826027870178],[.457098007202148,.584792017936707],[.381974011659622,.694710969924927],[.392388999462128,.694203019142151],[.277076005935669,.271932005882263],[.422551989555359,.563233017921448],[.385919004678726,.281364023685455],[.383103013038635,.255840003490448],[.331431001424789,.119714021682739],[.229923993349075,.232002973556519],[.364500999450684,.189113974571228],[.229622006416321,.299540996551514],[.173287004232407,.278747975826263],[.472878992557526,.666198015213013],[.446828007698059,.668527007102966],[.422762006521225,.673889994621277],[.445307999849319,.580065965652466],[.388103008270264,.693961024284363],[.403039008378983,.706539988517761],[.403629004955292,.693953037261963],[.460041999816895,.557139039039612],[.431158006191254,.692366003990173],[.452181994915009,.692366003990173],[.475387006998062,.692366003990173],[.465828001499176,.779190003871918],[.472328990697861,.736225962638855],[.473087012767792,.717857003211975],[.473122000694275,.704625964164734],[.473033010959625,.695277988910675],[.427942007780075,.695277988910675],[.426479011774063,.703539967536926],[.423162013292313,.711845993995667],[.4183090031147,.720062971115112],[.390094995498657,.639572978019714],[.013953999616206,.560034036636353],[.499913990497589,.58014702796936],[.413199990987778,.69539999961853],[.409626007080078,.701822996139526],[.468080013990402,.601534962654114],[.422728985548019,.585985004901886],[.463079988956451,.593783974647522],[.37211999297142,.47341400384903],[.334562003612518,.496073007583618],[.411671012639999,.546965003013611],[.242175996303558,.14767599105835],[.290776997804642,.201445996761322],[.327338010072708,.256527006626129],[.399509996175766,.748921036720276],[.441727995872498,.261676013469696],[.429764986038208,.187834024429321],[.412198007106781,.108901023864746],[.288955003023148,.398952007293701],[.218936994671822,.435410976409912],[.41278201341629,.398970007896423],[.257135003805161,.355440020561218],[.427684992551804,.437960982322693],[.448339998722076,.536936044692993],[.178560003638268,.45755398273468],[.247308000922203,.457193970680237],[.286267012357712,.467674970626831],[.332827985286713,.460712015628815],[.368755996227264,.447206974029541],[.398963987827301,.432654976844788],[.476410001516342,.405806005001068],[.189241006970406,.523923993110657],[.228962004184723,.348950982093811],[.490725994110107,.562400996685028],[.404670000076294,.485132992267609],[.019469000399113,.401564002037048],[.426243007183075,.420431017875671],[.396993011236191,.548797011375427],[.266469985246658,.376977026462555],[.439121007919312,.51895797252655],[.032313998788595,.644356966018677],[.419054001569748,.387154996395111],[.462783008813858,.505746960639954],[.238978996872902,.779744982719421],[.198220998048782,.831938028335571],[.107550002634525,.540755033493042],[.183610007166862,.740257024765015],[.134409993886948,.333683013916016],[.385764002799988,.883153975009918],[.490967005491257,.579378008842468],[.382384985685349,.508572995662689],[.174399003386497,.397670984268188],[.318785011768341,.39623498916626],[.343364000320435,.400596976280212],[.396100014448166,.710216999053955],[.187885001301765,.588537991046906],[.430987000465393,.944064974784851],[.318993002176285,.898285031318665],[.266247987747192,.869701027870178],[.500023007392883,.190576016902924],[.499976992607117,.954452991485596],[.366169989109039,.398822009563446],[.393207013607025,.39553701877594],[.410373002290726,.391080021858215],[.194993004202843,.342101991176605],[.388664990663528,.362284004688263],[.365961998701096,.355970978736877],[.343364000320435,.355356991291046],[.318785011768341,.35834002494812],[.301414996385574,.363156020641327],[.058132998645306,.319076001644135],[.301414996385574,.387449026107788],[.499987989664078,.618434011936188],[.415838003158569,.624195992946625],[.445681989192963,.566076993942261],[.465844005346298,.620640993118286],[.49992299079895,.351523995399475],[.288718998432159,.819945991039276],[.335278987884521,.852819979190826],[.440512001514435,.902418971061707],[.128294005990028,.791940987110138],[.408771991729736,.373893976211548],[.455606997013092,.451801002025604],[.499877005815506,.908990025520325],[.375436991453171,.924192011356354],[.11421000212431,.615022003650665],[.448662012815475,.695277988910675],[.4480200111866,.704632043838501],[.447111994028091,.715808033943176],[.444831997156143,.730794012546539],[.430011987686157,.766808986663818],[.406787008047104,.685672998428345],[.400738000869751,.681069016456604],[.392399996519089,.677703022956848],[.367855995893478,.663918972015381],[.247923001646996,.601333022117615],[.452769994735718,.420849978923798],[.43639200925827,.359887003898621],[.416164010763168,.368713974952698],[.413385987281799,.692366003990173],[.228018000721931,.683571994304657],[.468268007040024,.352671027183533],[.411361992359161,.804327011108398],[.499989002943039,.469825029373169],[.479153990745544,.442654013633728],[.499974012374878,.439637005329132],[.432112008333206,.493588984012604],[.499886006116867,.866917014122009],[.49991300702095,.821729004383087],[.456548988819122,.819200992584229],[.344549000263214,.745438992977142],[.37890899181366,.574010014533997],[.374292999505997,.780184984207153],[.319687992334366,.570737957954407],[.357154995203018,.604269981384277],[.295284003019333,.621580958366394],[.447750002145767,.862477004528046],[.410986006259918,.508723020553589],[.31395098567009,.775308012962341],[.354128003120422,.812552988529205],[.324548006057739,.703992962837219],[.189096003770828,.646299958229065],[.279776990413666,.71465802192688],[.1338230073452,.682700991630554],[.336768001317978,.644733011722565],[.429883986711502,.466521978378296],[.455527991056442,.548622965812683],[.437114000320435,.558896005153656],[.467287987470627,.529924988746643],[.414712011814117,.335219979286194],[.37704598903656,.322777986526489],[.344107985496521,.320150971412659],[.312875986099243,.32233202457428],[.283526003360748,.333190023899078],[.241245999932289,.382785975933075],[.102986000478268,.468762993812561],[.267612010240555,.424560010433197],[.297879010438919,.433175981044769],[.333433985710144,.433878004550934],[.366427004337311,.426115989685059],[.396012008190155,.416696012020111],[.420121014118195,.41022801399231],[.007561000064015,.480777025222778],[.432949006557465,.569517970085144],[.458638995885849,.479089021682739],[.473466008901596,.545744001865387],[.476087987422943,.563830018043518],[.468472003936768,.555056989192963],[.433990985155106,.582361996173859],[.483518004417419,.562983989715576],[.482482999563217,.57784903049469],[.42645001411438,.389798998832703],[.438998997211456,.39649498462677],[.450067013502121,.400434017181396],[.289712011814117,.368252992630005],[.276670008897781,.363372981548309],[.517862021923065,.471948027610779],[.710287988185883,.380764007568359],[.526226997375488,.573909997940063],[.895093023777008,.254140973091125],[.634069979190826,.409575998783112],[.661242008209229,.41302502155304],[.688880026340485,.409460008144379],[.725341975688934,.389131009578705],[.606630027294159,.40370500087738],[.654766023159027,.344011008739471],[.629905998706818,.346076011657715],[.680678009986877,.347265005111694],[.702096998691559,.353591024875641],[.75221198797226,.410804986953735],[.602918028831482,.842862963676453],[.719901978969574,.375599980354309],[.893692970275879,.399959981441498],[.790081977844238,.391354024410248],[.643998026847839,.534487962722778],[.528249025344849,.65040397644043],[.525849997997284,.680191040039062],[.560214996337891,.657229006290436],[.585384011268616,.66654098033905],[.549625992774963,.680860996246338],[.57122802734375,.682691991329193],[.624852001667023,.72809898853302],[.513050019741058,.547281980514526],[.51509702205658,.527251958847046],[.742246985435486,.314507007598877],[.598631024360657,.454979002475739],[.570338010787964,.548575043678284],[.578631997108459,.533622980117798],[.723087012767792,.532054007053375],[.516445994377136,.499638974666595],[.662801027297974,.282917976379395],[.70362401008606,.293271005153656],[.830704987049103,.193813979625702],[.552385985851288,.302568018436432],[.607609987258911,.353887975215912],[.645429015159607,.696707010269165],[.932694971561432,.730105042457581],[.557260990142822,.572826027870178],[.542901992797852,.584792017936707],[.6180260181427,.694710969924927],[.607590973377228,.694203019142151],[.722943007946014,.271963000297546],[.577413976192474,.563166975975037],[.614082992076874,.281386971473694],[.616907000541687,.255886018276215],[.668509006500244,.119913995265961],[.770092010498047,.232020974159241],[.635536015033722,.189248979091644],[.77039098739624,.299556016921997],[.826722025871277,.278755009174347],[.527121007442474,.666198015213013],[.553171992301941,.668527007102966],[.577238023281097,.673889994621277],[.554691970348358,.580065965652466],[.611896991729736,.693961024284363],[.59696102142334,.706539988517761],[.596370995044708,.693953037261963],[.539958000183105,.557139039039612],[.568841993808746,.692366003990173],[.547818005084991,.692366003990173],[.52461302280426,.692366003990173],[.534089982509613,.779141008853912],[.527670979499817,.736225962638855],[.526912987232208,.717857003211975],[.526877999305725,.704625964164734],[.526966989040375,.695277988910675],[.572058022022247,.695277988910675],[.573521018028259,.703539967536926],[.57683801651001,.711845993995667],[.581691026687622,.720062971115112],[.609944999217987,.639909982681274],[.986046016216278,.560034036636353],[.5867999792099,.69539999961853],[.590372025966644,.701822996139526],[.531915009021759,.601536989212036],[.577268004417419,.585934996604919],[.536915004253387,.593786001205444],[.627542972564697,.473352015018463],[.665585994720459,.495950996875763],[.588353991508484,.546862006187439],[.757824003696442,.14767599105835],[.709249973297119,.201507985591888],[.672684013843536,.256581008434296],[.600408971309662,.74900496006012],[.55826598405838,.261672019958496],[.570303976535797,.187870979309082],[.588165998458862,.109044015407562],[.711045026779175,.398952007293701],[.781069993972778,.435405015945435],[.587247014045715,.398931980133057],[.742869973182678,.355445981025696],[.572156012058258,.437651991844177],[.55186802148819,.536570012569427],[.821442008018494,.457556009292603],[.752701997756958,.457181990146637],[.71375697851181,.467626988887787],[.66711300611496,.460672974586487],[.631101012229919,.447153985500336],[.6008620262146,.432473003864288],[.523481011390686,.405627012252808],[.810747981071472,.523926019668579],[.771045982837677,.348959028720856],[.509127020835876,.562718033790588],[.595292985439301,.485023975372314],[.980530977249146,.401564002037048],[.573499977588654,.420000016689301],[.602994978427887,.548687994480133],[.733529984951019,.376977026462555],[.560611009597778,.519016981124878],[.967685997486115,.644356966018677],[.580985009670258,.387160003185272],[.537728011608124,.505385041236877],[.760966002941132,.779752969741821],[.801778972148895,.831938028335571],[.892440974712372,.54076099395752],[.816350996494293,.740260004997253],[.865594983100891,.333687007427216],[.614073991775513,.883246004581451],[.508952975273132,.579437971115112],[.617941975593567,.508316040039062],[.825608015060425,.397674977779388],[.681214988231659,.39623498916626],[.656635999679565,.400596976280212],[.603900015354156,.710216999053955],[.81208598613739,.588539004325867],[.56801301240921,.944564998149872],[.681007981300354,.898285031318665],[.733752012252808,.869701027870178],[.633830010890961,.398822009563446],[.606792986392975,.39553701877594],[.589659988880157,.391062021255493],[.805015981197357,.342108011245728],[.611334979534149,.362284004688263],[.634037971496582,.355970978736877],[.656635999679565,.355356991291046],[.681214988231659,.35834002494812],[.698584973812103,.363156020641327],[.941866993904114,.319076001644135],[.698584973812103,.387449026107788],[.584177017211914,.624107003211975],[.554318010807037,.566076993942261],[.534153997898102,.62064003944397],[.711217999458313,.819975018501282],[.664629995822906,.852871000766754],[.559099972248077,.902631998062134],[.871706008911133,.791940987110138],[.591234028339386,.373893976211548],[.544341027736664,.451583981513977],[.624562978744507,.924192011356354],[.88577002286911,.615028977394104],[.551338016986847,.695277988910675],[.551980018615723,.704632043838501],[.552887976169586,.715808033943176],[.555167973041534,.730794012546539],[.569944024085999,.767035007476807],[.593203008174896,.685675978660583],[.599261999130249,.681069016456604],[.607599973678589,.677703022956848],[.631937980651855,.663500010967255],[.752032995223999,.601315021514893],[.547226011753082,.420395016670227],[.563543975353241,.359827995300293],[.583841025829315,.368713974952698],[.586614012718201,.692366003990173],[.771915018558502,.683578014373779],[.531597018241882,.352482974529266],[.588370978832245,.804440975189209],[.52079701423645,.442565023899078],[.567984998226166,.493479013442993],[.543282985687256,.819254994392395],[.655317008495331,.745514988899231],[.621008992195129,.574018001556396],[.625559985637665,.78031200170517],[.680198013782501,.570719003677368],[.64276397228241,.604337990283966],[.704662978649139,.621529996395111],[.552012026309967,.862591981887817],[.589071989059448,.508637011051178],[.685944974422455,.775357007980347],[.645735025405884,.812640011310577],[.675342977046967,.703978002071381],[.810858011245728,.646304965019226],[.72012197971344,.714666962623596],[.866151988506317,.682704985141754],[.663187026977539,.644596993923187],[.570082008838654,.466325998306274],[.544561982154846,.548375964164734],[.562758982181549,.558784961700439],[.531987011432648,.530140042304993],[.585271000862122,.335177004337311],[.622952997684479,.32277899980545],[.655896008014679,.320163011550903],[.687132000923157,.322345972061157],[.716481983661652,.333200991153717],[.758756995201111,.382786989212036],[.897013008594513,.468769013881683],[.732392013072968,.424547016620636],[.70211398601532,.433162987232208],[.66652500629425,.433866024017334],[.633504986763,.426087975502014],[.603875994682312,.416586995124817],[.579657971858978,.409945011138916],[.992439985275269,.480777025222778],[.567192018032074,.569419980049133],[.54136598110199,.478899002075195],[.526564002037048,.546118021011353],[.523913025856018,.563830018043518],[.531529009342194,.555056989192963],[.566035985946655,.582329034805298],[.51631098985672,.563053965568542],[.5174720287323,.577877044677734],[.573594987392426,.389806985855103],[.560697972774506,.395331978797913],[.549755990505219,.399751007556915],[.710287988185883,.368252992630005],[.723330020904541,.363372981548309]],Ne=[127,34,139,11,0,37,232,231,120,72,37,39,128,121,47,232,121,128,104,69,67,175,171,148,157,154,155,118,50,101,73,39,40,9,151,108,48,115,131,194,204,211,74,40,185,80,42,183,40,92,186,230,229,118,202,212,214,83,18,17,76,61,146,160,29,30,56,157,173,106,204,194,135,214,192,203,165,98,21,71,68,51,45,4,144,24,23,77,146,91,205,50,187,201,200,18,91,106,182,90,91,181,85,84,17,206,203,36,148,171,140,92,40,39,193,189,244,159,158,28,247,246,161,236,3,196,54,68,104,193,168,8,117,228,31,189,193,55,98,97,99,126,47,100,166,79,218,155,154,26,209,49,131,135,136,150,47,126,217,223,52,53,45,51,134,211,170,140,67,69,108,43,106,91,230,119,120,226,130,247,63,53,52,238,20,242,46,70,156,78,62,96,46,53,63,143,34,227,173,155,133,123,117,111,44,125,19,236,134,51,216,206,205,154,153,22,39,37,167,200,201,208,36,142,100,57,212,202,20,60,99,28,158,157,35,226,113,160,159,27,204,202,210,113,225,46,43,202,204,62,76,77,137,123,116,41,38,72,203,129,142,64,98,240,49,102,64,41,73,74,212,216,207,42,74,184,169,170,211,170,149,176,105,66,69,122,6,168,123,147,187,96,77,90,65,55,107,89,90,180,101,100,120,63,105,104,93,137,227,15,86,85,129,102,49,14,87,86,55,8,9,100,47,121,145,23,22,88,89,179,6,122,196,88,95,96,138,172,136,215,58,172,115,48,219,42,80,81,195,3,51,43,146,61,171,175,199,81,82,38,53,46,225,144,163,110,246,33,7,52,65,66,229,228,117,34,127,234,107,108,69,109,108,151,48,64,235,62,78,191,129,209,126,111,35,143,163,161,246,117,123,50,222,65,52,19,125,141,221,55,65,3,195,197,25,7,33,220,237,44,70,71,139,122,193,245,247,130,33,71,21,162,153,158,159,170,169,150,188,174,196,216,186,92,144,160,161,2,97,167,141,125,241,164,167,37,72,38,12,145,159,160,38,82,13,63,68,71,226,35,111,158,153,154,101,50,205,206,92,165,209,198,217,165,167,97,220,115,218,133,112,243,239,238,241,214,135,169,190,173,133,171,208,32,125,44,237,86,87,178,85,86,179,84,85,180,83,84,181,201,83,182,137,93,132,76,62,183,61,76,184,57,61,185,212,57,186,214,207,187,34,143,156,79,239,237,123,137,177,44,1,4,201,194,32,64,102,129,213,215,138,59,166,219,242,99,97,2,94,141,75,59,235,24,110,228,25,130,226,23,24,229,22,23,230,26,22,231,112,26,232,189,190,243,221,56,190,28,56,221,27,28,222,29,27,223,30,29,224,247,30,225,238,79,20,166,59,75,60,75,240,147,177,215,20,79,166,187,147,213,112,233,244,233,128,245,128,114,188,114,217,174,131,115,220,217,198,236,198,131,134,177,132,58,143,35,124,110,163,7,228,110,25,356,389,368,11,302,267,452,350,349,302,303,269,357,343,277,452,453,357,333,332,297,175,152,377,384,398,382,347,348,330,303,304,270,9,336,337,278,279,360,418,262,431,304,408,409,310,415,407,270,409,410,450,348,347,422,430,434,313,314,17,306,307,375,387,388,260,286,414,398,335,406,418,364,367,416,423,358,327,251,284,298,281,5,4,373,374,253,307,320,321,425,427,411,421,313,18,321,405,406,320,404,405,315,16,17,426,425,266,377,400,369,322,391,269,417,465,464,386,257,258,466,260,388,456,399,419,284,332,333,417,285,8,346,340,261,413,441,285,327,460,328,355,371,329,392,439,438,382,341,256,429,420,360,364,394,379,277,343,437,443,444,283,275,440,363,431,262,369,297,338,337,273,375,321,450,451,349,446,342,467,293,334,282,458,461,462,276,353,383,308,324,325,276,300,293,372,345,447,382,398,362,352,345,340,274,1,19,456,248,281,436,427,425,381,256,252,269,391,393,200,199,428,266,330,329,287,273,422,250,462,328,258,286,384,265,353,342,387,259,257,424,431,430,342,353,276,273,335,424,292,325,307,366,447,345,271,303,302,423,266,371,294,455,460,279,278,294,271,272,304,432,434,427,272,407,408,394,430,431,395,369,400,334,333,299,351,417,168,352,280,411,325,319,320,295,296,336,319,403,404,330,348,349,293,298,333,323,454,447,15,16,315,358,429,279,14,15,316,285,336,9,329,349,350,374,380,252,318,402,403,6,197,419,318,319,325,367,364,365,435,367,397,344,438,439,272,271,311,195,5,281,273,287,291,396,428,199,311,271,268,283,444,445,373,254,339,263,466,249,282,334,296,449,347,346,264,447,454,336,296,299,338,10,151,278,439,455,292,407,415,358,371,355,340,345,372,390,249,466,346,347,280,442,443,282,19,94,370,441,442,295,248,419,197,263,255,359,440,275,274,300,383,368,351,412,465,263,467,466,301,368,389,380,374,386,395,378,379,412,351,419,436,426,322,373,390,388,2,164,393,370,462,461,164,0,267,302,11,12,374,373,387,268,12,13,293,300,301,446,261,340,385,384,381,330,266,425,426,423,391,429,355,437,391,327,326,440,457,438,341,382,362,459,457,461,434,430,394,414,463,362,396,369,262,354,461,457,316,403,402,315,404,403,314,405,404,313,406,405,421,418,406,366,401,361,306,408,407,291,409,408,287,410,409,432,436,410,434,416,411,264,368,383,309,438,457,352,376,401,274,275,4,421,428,262,294,327,358,433,416,367,289,455,439,462,370,326,2,326,370,305,460,455,254,449,448,255,261,446,253,450,449,252,451,450,256,452,451,341,453,452,413,464,463,441,413,414,258,442,441,257,443,442,259,444,443,260,445,444,467,342,445,459,458,250,289,392,290,290,328,460,376,433,435,250,290,392,411,416,433,341,463,464,453,464,465,357,465,412,343,412,399,360,363,440,437,399,456,420,456,363,401,435,288,372,383,353,339,255,249,448,261,255,133,243,190,133,155,112,33,246,247,33,130,25,398,384,286,362,398,414,362,463,341,263,359,467,263,249,255,466,467,260,75,60,166,238,239,79,162,127,139,72,11,37,121,232,120,73,72,39,114,128,47,233,232,128,103,104,67,152,175,148,173,157,155,119,118,101,74,73,40,107,9,108,49,48,131,32,194,211,184,74,185,191,80,183,185,40,186,119,230,118,210,202,214,84,83,17,77,76,146,161,160,30,190,56,173,182,106,194,138,135,192,129,203,98,54,21,68,5,51,4,145,144,23,90,77,91,207,205,187,83,201,18,181,91,182,180,90,181,16,85,17,205,206,36,176,148,140,165,92,39,245,193,244,27,159,28,30,247,161,174,236,196,103,54,104,55,193,8,111,117,31,221,189,55,240,98,99,142,126,100,219,166,218,112,155,26,198,209,131,169,135,150,114,47,217,224,223,53,220,45,134,32,211,140,109,67,108,146,43,91,231,230,120,113,226,247,105,63,52,241,238,242,124,46,156,95,78,96,70,46,63,116,143,227,116,123,111,1,44,19,3,236,51,207,216,205,26,154,22,165,39,167,199,200,208,101,36,100,43,57,202,242,20,99,56,28,157,124,35,113,29,160,27,211,204,210,124,113,46,106,43,204,96,62,77,227,137,116,73,41,72,36,203,142,235,64,240,48,49,64,42,41,74,214,212,207,183,42,184,210,169,211,140,170,176,104,105,69,193,122,168,50,123,187,89,96,90,66,65,107,179,89,180,119,101,120,68,63,104,234,93,227,16,15,85,209,129,49,15,14,86,107,55,9,120,100,121,153,145,22,178,88,179,197,6,196,89,88,96,135,138,136,138,215,172,218,115,219,41,42,81,5,195,51,57,43,61,208,171,199,41,81,38,224,53,225,24,144,110,105,52,66,118,229,117,227,34,234,66,107,69,10,109,151,219,48,235,183,62,191,142,129,126,116,111,143,7,163,246,118,117,50,223,222,52,94,19,141,222,221,65,196,3,197,45,220,44,156,70,139,188,122,245,139,71,162,145,153,159,149,170,150,122,188,196,206,216,92,163,144,161,164,2,167,242,141,241,0,164,37,11,72,12,144,145,160,12,38,13,70,63,71,31,226,111,157,158,154,36,101,205,203,206,165,126,209,217,98,165,97,237,220,218,237,239,241,210,214,169,140,171,32,241,125,237,179,86,178,180,85,179,181,84,180,182,83,181,194,201,182,177,137,132,184,76,183,185,61,184,186,57,185,216,212,186,192,214,187,139,34,156,218,79,237,147,123,177,45,44,4,208,201,32,98,64,129,192,213,138,235,59,219,141,242,97,97,2,141,240,75,235,229,24,228,31,25,226,230,23,229,231,22,230,232,26,231,233,112,232,244,189,243,189,221,190,222,28,221,223,27,222,224,29,223,225,30,224,113,247,225,99,60,240,213,147,215,60,20,166,192,187,213,243,112,244,244,233,245,245,128,188,188,114,174,134,131,220,174,217,236,236,198,134,215,177,58,156,143,124,25,110,7,31,228,25,264,356,368,0,11,267,451,452,349,267,302,269,350,357,277,350,452,357,299,333,297,396,175,377,381,384,382,280,347,330,269,303,270,151,9,337,344,278,360,424,418,431,270,304,409,272,310,407,322,270,410,449,450,347,432,422,434,18,313,17,291,306,375,259,387,260,424,335,418,434,364,416,391,423,327,301,251,298,275,281,4,254,373,253,375,307,321,280,425,411,200,421,18,335,321,406,321,320,405,314,315,17,423,426,266,396,377,369,270,322,269,413,417,464,385,386,258,248,456,419,298,284,333,168,417,8,448,346,261,417,413,285,326,327,328,277,355,329,309,392,438,381,382,256,279,429,360,365,364,379,355,277,437,282,443,283,281,275,363,395,431,369,299,297,337,335,273,321,348,450,349,359,446,467,283,293,282,250,458,462,300,276,383,292,308,325,283,276,293,264,372,447,346,352,340,354,274,19,363,456,281,426,436,425,380,381,252,267,269,393,421,200,428,371,266,329,432,287,422,290,250,328,385,258,384,446,265,342,386,387,257,422,424,430,445,342,276,422,273,424,306,292,307,352,366,345,268,271,302,358,423,371,327,294,460,331,279,294,303,271,304,436,432,427,304,272,408,395,394,431,378,395,400,296,334,299,6,351,168,376,352,411,307,325,320,285,295,336,320,319,404,329,330,349,334,293,333,366,323,447,316,15,315,331,358,279,317,14,316,8,285,9,277,329,350,253,374,252,319,318,403,351,6,419,324,318,325,397,367,365,288,435,397,278,344,439,310,272,311,248,195,281,375,273,291,175,396,199,312,311,268,276,283,445,390,373,339,295,282,296,448,449,346,356,264,454,337,336,299,337,338,151,294,278,455,308,292,415,429,358,355,265,340,372,388,390,466,352,346,280,295,442,282,354,19,370,285,441,295,195,248,197,457,440,274,301,300,368,417,351,465,251,301,389,385,380,386,394,395,379,399,412,419,410,436,322,387,373,388,326,2,393,354,370,461,393,164,267,268,302,12,386,374,387,312,268,13,298,293,301,265,446,340,380,385,381,280,330,425,322,426,391,420,429,437,393,391,326,344,440,438,458,459,461,364,434,394,428,396,262,274,354,457,317,316,402,316,315,403,315,314,404,314,313,405,313,421,406,323,366,361,292,306,407,306,291,408,291,287,409,287,432,410,427,434,411,372,264,383,459,309,457,366,352,401,1,274,4,418,421,262,331,294,358,435,433,367,392,289,439,328,462,326,94,2,370,289,305,455,339,254,448,359,255,446,254,253,449,253,252,450,252,256,451,256,341,452,414,413,463,286,441,414,286,258,441,258,257,442,257,259,443,259,260,444,260,467,445,309,459,250,305,289,290,305,290,460,401,376,435,309,250,392,376,411,433,453,341,464,357,453,465,343,357,412,437,343,399,344,360,440,420,437,456,360,420,363,361,401,288,265,372,353,390,339,249,339,448,255];var ur=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],hr=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],br=[33,133,362,263,1,78,308],L7=ur.map(e=>R2[e]),W7=hr.map(e=>R2[e]),F7=br.map(e=>R2[e]);function ge(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var gr=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Mr=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Pr=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],Rr=[[474,475],[475,476],[476,477],[477,474]],vr=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],Tr=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],wr=[[469,470],[470,471],[471,472],[472,469]],kr=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]],G7={lips:ge(gr),leftEye:ge(Mr),leftEyebrow:ge(Pr),leftIris:ge(Rr),rightEye:ge(vr),rightEyebrow:ge(Tr),rightIris:ge(wr),faceOval:ge(kr)};var Je=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],Z2=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],X2=(e,t)=>e?[Math.trunc(Math.max(0,e.startPoint[0])),Math.trunc(Math.max(0,e.startPoint[1])),Math.trunc(Math.min(t.shape[2]||0,e.endPoint[0])-Math.max(0,e.startPoint[0])),Math.trunc(Math.min(t.shape[1]||0,e.endPoint[1])-Math.max(0,e.startPoint[1]))]:[0,0,0,0],q2=(e,t)=>e?[e.startPoint[0]/(t.shape[2]||0),e.startPoint[1]/(t.shape[1]||0),(e.endPoint[0]-e.startPoint[0])/(t.shape[2]||0),(e.endPoint[1]-e.startPoint[1])/(t.shape[1]||0)]:[0,0,0,0],Ut=(e,t)=>{let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]];return{startPoint:o,endPoint:n,landmarks:e.landmarks,confidence:e.confidence}},K5=(e,t,o)=>{let n=t.shape[1],r=t.shape[2],A=[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r],s=ie.image.cropAndResize(t,[A],[0],o),a=ie.div(s,V.tf255);return ie.dispose(s),a},U2=(e,t)=>{let o=Z2(e),n=Je(e),r=[t*n[0]/2,t*n[1]/2];return{startPoint:[o[0]-r[0],o[1]-r[1]],endPoint:[o[0]+r[0],o[1]+r[1]],landmarks:e.landmarks,confidence:e.confidence}},Y2=e=>{let t=Z2(e),o=Je(e),n=Math.max(...o)/2;return{startPoint:[Math.round(t[0]-n),Math.round(t[1]-n)],endPoint:[Math.round(t[0]+n),Math.round(t[1]+n)],landmarks:e.landmarks,confidence:e.confidence}},Yt=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return{startPoint:[Math.min(...t),Math.min(...o)],endPoint:[Math.max(...t),Math.max(...o)],landmarks:e}},J5=[[1,0,0],[0,1,0],[0,0,1]],Er=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),zr=(e,t)=>Er(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var Xt=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],Oe=(e,t)=>{let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o},Sr=(e,t)=>{let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o},qt=(e,t)=>{let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let A=0;A<n;A++)o[r].push(Oe(e[r],Sr(t,A)))}return o},Kt=(e,t)=>{let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],A=Xt(t[0],t[1]),s=qt(A,r),a=Xt(-t[0],-t[1]);return qt(s,a)},Cr=e=>{let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-Oe(t[0],o),-Oe(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]},jr=(e,t)=>[Oe(e,t[0]),Oe(e,t[1])];function Jt(e){let t=e===192?{strides:[4],anchors:[1]}:{strides:[e/16,e/8],anchors:[2,6]},o=[];for(let n=0;n<t.strides.length;n++){let r=t.strides[n],A=Math.floor((e+r-1)/r),s=Math.floor((e+r-1)/r),a=t.anchors[n];for(let i=0;i<A;i++){let x=r*(i+.5);for(let c=0;c<s;c++){let l=r*(c+.5);for(let y=0;y<a;y++)o.push([l,x])}}}return o}function Qt(e,t,o,n,r){let A=Je(t),s=e.map(f=>[A[0]/r*(f[0]-r/2),A[1]/r*(f[1]-r/2),f[2]||0]),a=o&&o!==0&&Math.abs(o)>.2,i=a?Kt(o,[0,0]):J5,x=a?s.map(f=>[...jr(f,i),f[2]]):s,c=a?Cr(n):J5,l=Z2(t),y=[Oe(l,c[0]),Oe(l,c[1])];return x.map(f=>[Math.trunc(f[0]+y[0]),Math.trunc(f[1]+y[1]),Math.trunc(f[2]||0)])}function _t(e,t,o,n){let r=t.landmarks.length>=q5.count?q5.symmetryLine:Ie.symmetryLine,A=0,s=J5,a;if(e&&v.kernels.includes("rotatewithoffset"))if(A=zr(t.landmarks[r[0]],t.landmarks[r[1]]),A&&A!==0&&Math.abs(A)>.2){let x=Z2(t),c=[x[0]/o.shape[2],x[1]/o.shape[1]],l=ie.image.rotateWithOffset(o,A,0,c);s=Kt(-A,x),a=K5(t,l,[n,n]),ie.dispose(l)}else a=K5(t,o,[n,n]);else a=K5(t,o,[n,n]);return[A,s,a]}var Ir=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return[Math.min(...t)+(Math.max(...t)-Math.min(...t))/2,Math.min(...o)+(Math.max(...o)-Math.min(...o))/2]},$t=(e,t)=>{let o=Ir(e),n=Je(t);return{startPoint:[o[0]-n[0]/2,o[1]-n[1]/2],endPoint:[o[0]+n[0]/2,o[1]+n[1]/2]}};var e3=6,Nr=1.4,te,t3=null,Me=0,v2=null,Qe=()=>Me;async function o3(e){var t;return v.initial&&(te=null),te?e.debug&&p("cached model:",te.modelUrl):te=await G((t=e.face.detector)==null?void 0:t.modelPath),Me=te.inputs[0].shape?te.inputs[0].shape[2]:0,v2=O.scalar(Me,"int32"),t3=O.tensor2d(Jt(Me)),te}function Or(e){let t={};t.boxStarts=O.slice(e,[0,1],[-1,2]),t.centers=O.add(t.boxStarts,t3),t.boxSizes=O.slice(e,[0,3],[-1,2]),t.boxSizesNormalized=O.div(t.boxSizes,v2),t.centersNormalized=O.div(t.centers,v2),t.halfBoxSize=O.div(t.boxSizesNormalized,V.tf2),t.starts=O.sub(t.centersNormalized,t.halfBoxSize),t.ends=O.add(t.centersNormalized,t.halfBoxSize),t.startNormalized=O.mul(t.starts,v2),t.endNormalized=O.mul(t.ends,v2);let o=O.concat2d([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(n=>O.dispose(t[n])),o}async function n3(e,t){var a,i,x,c;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let o={};o.resized=O.image.resizeBilinear(e,[Me,Me]),o.div=O.div(o.resized,V.tf127),o.normalized=O.sub(o.div,V.tf05);let n=te==null?void 0:te.execute(o.normalized);if(Array.isArray(n)&&n.length>2){let l=n.sort((y,f)=>y.size-f.size);o.concat384=O.concat([l[0],l[2]],2),o.concat512=O.concat([l[1],l[3]],2),o.concat=O.concat([o.concat512,o.concat384],1),o.batch=O.squeeze(o.concat,0)}else Array.isArray(n)?o.batch=O.squeeze(n[0]):o.batch=O.squeeze(n);O.dispose(n),o.boxes=Or(o.batch),o.logits=O.slice(o.batch,[0,0],[-1,1]),o.sigmoid=O.sigmoid(o.logits),o.scores=O.squeeze(o.sigmoid),o.nms=await O.image.nonMaxSuppressionAsync(o.boxes,o.scores,((a=t.face.detector)==null?void 0:a.maxDetected)||0,((i=t.face.detector)==null?void 0:i.iouThreshold)||0,((x=t.face.detector)==null?void 0:x.minConfidence)||0);let r=await o.nms.array(),A=[],s=await o.scores.data();for(let l=0;l<r.length;l++){let y=s[r[l]];if(y>(((c=t.face.detector)==null?void 0:c.minConfidence)||0)){let f={};f.bbox=O.slice(o.boxes,[r[l],0],[1,-1]),f.slice=O.slice(o.batch,[r[l],e3-1],[1,-1]),f.squeeze=O.squeeze(f.slice),f.landmarks=O.reshape(f.squeeze,[e3,-1]);let u=await f.bbox.data(),m={startPoint:[u[0],u[1]],endPoint:[u[2],u[3]],landmarks:await f.landmarks.array(),confidence:y},P=Ut(m,[(e.shape[2]||0)/Me,(e.shape[1]||0)/Me]),g=U2(P,t.face.scale||Nr),b=Y2(g);A.push(b),Object.keys(f).forEach(d=>O.dispose(f[d]))}}return Object.keys(o).forEach(l=>O.dispose(o[l])),A}var I0=Z(D());var K2={};ue(K2,{connected:()=>$5,kpt:()=>_5});var _5=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPinky","rightPinky","leftIndex","rightIndex","leftThumb","rightThumb","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","bodyCenter","bodyTop","leftPalm","leftHand","rightPalm","rightHand"],$5={shoulders:["leftShoulder","rightShoulder"],hips:["rightHip","leftHip"],mouth:["leftMouth","rightMouth"],leftLegUpper:["leftHip","leftKnee"],leftLegLower:["leftKnee","leftAnkle"],leftFoot:["leftAnkle","leftHeel","leftFoot"],leftTorso:["leftShoulder","leftHip"],leftArmUpper:["leftShoulder","leftElbow"],leftArmLower:["leftElbow","leftWrist"],leftHand:["leftWrist","leftPalm"],leftHandPinky:["leftPalm","leftPinky"],leftHandIndex:["leftPalm","leftIndex"],leftHandThumb:["leftPalm","leftThumb"],leftEyeOutline:["leftEyeInside","leftEyeOutside"],rightLegUpper:["rightHip","rightKnee"],rightLegLower:["rightKnee","rightAnkle"],rightFoot:["rightAnkle","rightHeel","rightFoot"],rightTorso:["rightShoulder","rightHip"],rightArmUpper:["rightShoulder","rightElbow"],rightArmLower:["rightElbow","rightWrist"],rightHand:["rightWrist","rightPalm"],rightHandPinky:["rightPalm","rightPinky"],rightHandIndex:["rightPalm","rightIndex"],rightHandThumb:["rightPalm","rightThumb"],rightEyeOutline:["rightEyeInside","rightEyeOutside"]};var C0=Z(D()),A3=224,Lr,Wr=5,J2=[8,16,32,32,32];async function s3(){let e=[],t=0;for(;t<Wr;){let o=0,n=t;for(;n<J2.length&&J2[n]===J2[t];)o+=2,n++;let r=J2[t],A=Math.ceil(A3/r),s=Math.ceil(A3/r);for(let a=0;a<A;++a)for(let i=0;i<s;++i)for(let x=0;x<o;++x)e.push({x:(i+.5)/s,y:(a+.5)/A});t=n}Lr={x:C0.tensor1d(e.map(o=>o.x)),y:C0.tensor1d(e.map(o=>o.y))}}function le(e,t=[1,1]){let o=[e.map(a=>a[0]),e.map(a=>a[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],A=[n[0],n[1],r[0]-n[0],r[1]-n[1]],s=[A[0]/t[0],A[1]/t[1],A[2]/t[0],A[3]/t[1]];return{box:A,boxRaw:s}}function a3(e,t=[1,1]){let o=[e.map(x=>x[0]),e.map(x=>x[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],A=[(n[0]+r[0])/2,(n[1]+r[1])/2],s=Math.max(A[0]-n[0],A[1]-n[1],-A[0]+r[0],-A[1]+r[1]),a=[Math.trunc(A[0]-s),Math.trunc(A[1]-s),Math.trunc(2*s),Math.trunc(2*s)],i=[a[0]/t[0],a[1]/t[1],a[2]/t[0],a[3]/t[1]];return{box:a,boxRaw:i}}function Q2(e,t){let o=[e[2]*t,e[3]*t];return[e[0]-(o[0]-e[2])/2,e[1]-(o[1]-e[3])/2,o[0],o[1]]}var y3={initial:!0},j0={detector:null,landmarks:null},_e={detector:[224,224],landmarks:[256,256]},e1=Number.MAX_SAFE_INTEGER,Gr={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},$2=null,T2,Pe=[[0,0],[0,0],[0,0],[0,0]],i3=0,l3=e=>1-1/(1+Math.exp(e));async function x3(e){if(y3.initial&&(j0.detector=null),!j0.detector&&e.body.detector&&e.body.detector.modelPath){j0.detector=await G(e.body.detector.modelPath);let t=Object.values(j0.detector.modelSignature.inputs);_e.detector[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,_e.detector[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&j0.detector&&p("cached model:",j0.detector.modelUrl);return await s3(),j0.detector}async function c3(e){if(y3.initial&&(j0.landmarks=null),j0.landmarks)e.debug&&p("cached model:",j0.landmarks.modelUrl);else{j0.landmarks=await G(e.body.modelPath);let t=Object.values(j0.landmarks.modelSignature.inputs);_e.landmarks[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,_e.landmarks[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return j0.landmarks}async function Br(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;let n;if(T2&&(o.cropped=I0.image.cropAndResize(e,[T2],[0],[e.shape[1],e.shape[2]])),e.shape[1]!==e.shape[2]){let r=[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],A=[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0];Pe=[[0,0],r,A,[0,0]],o.pad=I0.pad(o.cropped||e,Pe),o.resize=I0.image.resizeBilinear(o.pad,[t,t]),n=I0.div(o.resize,V.tf255)}else e.shape[1]!==t?(o.resize=I0.image.resizeBilinear(o.cropped||e,[t,t]),n=I0.div(o.resize,V.tf255)):n=I0.div(o.cropped||e,V.tf255);return Object.keys(o).forEach(r=>I0.dispose(o[r])),n}function Hr(e,t){for(let o of e)o.position=[Math.trunc(o.position[0]*(t[0]+Pe[2][0]+Pe[2][1])/t[0]-Pe[2][0]),Math.trunc(o.position[1]*(t[1]+Pe[1][0]+Pe[1][1])/t[1]-Pe[1][0]),o.position[2]],o.positionRaw=[o.position[0]/t[0],o.position[1]/t[1],2*o.position[2]/(t[0]+t[1])];if(T2)for(let o of e)o.positionRaw=[o.positionRaw[0]+T2[1],o.positionRaw[1]+T2[0],o.positionRaw[2]],o.position=[Math.trunc(o.positionRaw[0]*t[0]),Math.trunc(o.positionRaw[1]*t[1]),o.positionRaw[2]];return e}async function Vr(e){let t=e.find(a=>a.part==="leftPalm"),o=e.find(a=>a.part==="leftWrist"),n=e.find(a=>a.part==="leftIndex");t.position[2]=((o.position[2]||0)+(n.position[2]||0))/2;let r=e.find(a=>a.part==="rightPalm"),A=e.find(a=>a.part==="rightWrist"),s=e.find(a=>a.part==="rightIndex");r.position[2]=((A.position[2]||0)+(s.position[2]||0))/2}async function Dr(e,t,o){var u;let n={};[n.ld,n.segmentation,n.heatmap,n.world,n.poseflag]=(u=j0.landmarks)==null?void 0:u.execute(e,Gr.landmarks);let r=(await n.poseflag.data())[0],A=await n.ld.data(),s=await n.world.data();Object.keys(n).forEach(m=>I0.dispose(n[m]));let a=[],i=5;for(let m=0;m<A.length/i;m++){let P=l3(A[i*m+3]),g=l3(A[i*m+4]),b=Math.trunc(100*P*g*r)/100,d=[A[i*m+0]/_e.landmarks[0],A[i*m+1]/_e.landmarks[1],A[i*m+2]+0],M=[Math.trunc(o[0]*d[0]),Math.trunc(o[1]*d[1]),d[2]],S=[s[i*m+0],s[i*m+1],s[i*m+2]+0];a.push({part:_5[m],positionRaw:d,position:M,distance:S,score:b})}if(r<(t.body.minConfidence||0))return null;Vr(a);let x=Hr(a,o),c=x.map(m=>m.position),l=le(c,[o[0],o[1]]),y={};for(let[m,P]of Object.entries($5)){let g=[];for(let b=0;b<P.length-1;b++){let d=x.find(S=>S.part===P[b]),M=x.find(S=>S.part===P[b+1]);d&&M&&g.push([d.position,M.position])}y[m]=g}return{id:0,score:Math.trunc(100*r)/100,box:l.box,boxRaw:l.boxRaw,keypoints:x,annotations:y}}async function t1(e,t){let o=[e.shape[2]||0,e.shape[1]||0],n=(t.body.skipTime||0)>h()-i3,r=e1<(t.body.skipFrames||0);if(t.skipAllowed&&n&&r&&$2!==null)e1++;else{let A={};A.landmarks=await Br(e,256),$2=await Dr(A.landmarks,t,o),Object.keys(A).forEach(s=>I0.dispose(A[s])),i3=h(),e1=0}return $2?[$2]:[]}var T0=Z(D());var $e=[{class:1,label:"person"},{class:2,label:"bicycle"},{class:3,label:"car"},{class:4,label:"motorcycle"},{class:5,label:"airplane"},{class:6,label:"bus"},{class:7,label:"train"},{class:8,label:"truck"},{class:9,label:"boat"},{class:10,label:"traffic light"},{class:11,label:"fire hydrant"},{class:12,label:"stop sign"},{class:13,label:"parking meter"},{class:14,label:"bench"},{class:15,label:"bird"},{class:16,label:"cat"},{class:17,label:"dog"},{class:18,label:"horse"},{class:19,label:"sheep"},{class:20,label:"cow"},{class:21,label:"elephant"},{class:22,label:"bear"},{class:23,label:"zebra"},{class:24,label:"giraffe"},{class:25,label:"backpack"},{class:26,label:"umbrella"},{class:27,label:"handbag"},{class:28,label:"tie"},{class:29,label:"suitcase"},{class:30,label:"frisbee"},{class:31,label:"skis"},{class:32,label:"snowboard"},{class:33,label:"sports ball"},{class:34,label:"kite"},{class:35,label:"baseball bat"},{class:36,label:"baseball glove"},{class:37,label:"skateboard"},{class:38,label:"surfboard"},{class:39,label:"tennis racket"},{class:40,label:"bottle"},{class:41,label:"wine glass"},{class:42,label:"cup"},{class:43,label:"fork"},{class:44,label:"knife"},{class:45,label:"spoon"},{class:46,label:"bowl"},{class:47,label:"banana"},{class:48,label:"apple"},{class:49,label:"sandwich"},{class:50,label:"orange"},{class:51,label:"broccoli"},{class:52,label:"carrot"},{class:53,label:"hot dog"},{class:54,label:"pizza"},{class:55,label:"donut"},{class:56,label:"cake"},{class:57,label:"chair"},{class:58,label:"couch"},{class:59,label:"potted plant"},{class:60,label:"bed"},{class:61,label:"dining table"},{class:62,label:"toilet"},{class:63,label:"tv"},{class:64,label:"laptop"},{class:65,label:"mouse"},{class:66,label:"remote"},{class:67,label:"keyboard"},{class:68,label:"cell phone"},{class:69,label:"microwave"},{class:70,label:"oven"},{class:71,label:"toaster"},{class:72,label:"sink"},{class:73,label:"refrigerator"},{class:74,label:"book"},{class:75,label:"clock"},{class:76,label:"vase"},{class:77,label:"scissors"},{class:78,label:"teddy bear"},{class:79,label:"hair drier"},{class:80,label:"toothbrush"}];var ye,Le=0,o1=[],f3=0,n1=Number.MAX_SAFE_INTEGER;async function m3(e){if(v.initial&&(ye=null),ye)e.debug&&p("cached model:",ye.modelUrl);else{ye=await G(e.object.modelPath);let t=Object.values(ye.modelSignature.inputs);Le=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return ye}async function Zr(e,t,o){if(!e)return[];let n={},r=[],A=await e.array();n.squeeze=T0.squeeze(e);let s=T0.split(n.squeeze,6,1);n.stack=T0.stack([s[1],s[0],s[3],s[2]],1),n.boxes=T0.squeeze(n.stack),n.scores=T0.squeeze(s[4]),n.classes=T0.squeeze(s[5]),T0.dispose([e,...s]),n.nms=await T0.image.nonMaxSuppressionAsync(n.boxes,n.scores,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence||0);let a=await n.nms.data(),i=0;for(let x of Array.from(a)){let c=Math.trunc(100*A[0][x][4])/100,l=A[0][x][5],y=$e[l].label,[f,u]=[A[0][x][0]/Le,A[0][x][1]/Le],m=[f,u,A[0][x][2]/Le-f,A[0][x][3]/Le-u],P=[Math.trunc(m[0]*t[0]),Math.trunc(m[1]*t[1]),Math.trunc(m[2]*t[0]),Math.trunc(m[3]*t[1])];r.push({id:i++,score:c,class:l,label:y,box:P,boxRaw:m})}return Object.keys(n).forEach(x=>T0.dispose(n[x])),r}async function r1(e,t){let o=(t.object.skipTime||0)>h()-f3,n=n1<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&o1.length>0?(n1++,o1):(n1=0,new Promise(async r=>{let A=[e.shape[2]||0,e.shape[1]||0],s=T0.image.resizeBilinear(e,[Le,Le]),a=t.object.enabled?ye==null?void 0:ye.execute(s,["tower_0/detections"]):null;f3=h(),T0.dispose(s);let i=await Zr(a,A,t);o1=i,r(i)}))}var _=Z(D());var e5={};ue(e5,{connected:()=>s1,kpt:()=>A1});var A1=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],s1={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var b0,u3=0,w0={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},a1=Number.MAX_SAFE_INTEGER;async function h3(e){return v.initial&&(b0=null),b0?e.debug&&p("cached model:",b0.modelUrl):b0=await G(e.body.modelPath),b0}async function Xr(e,t){let[o,n]=e.shape,r=_.reshape(e,[n*o]),A=_.max(r,0),s=(await A.data())[0];if(_.dispose([r,A]),s>t){let a=_.argMax(r,0),i=_.mod(a,o),x=(await i.data())[0],c=_.div(a,_.scalar(o,"int32")),l=(await c.data())[0];return _.dispose([i,c]),[x,l,s]}return[0,0,s]}async function i1(e,t){let o=(t.body.skipTime||0)>h()-u3,n=a1<(t.body.skipFrames||0);return t.skipAllowed&&o&&n&&Object.keys(w0.keypoints).length>0?(a1++,[w0]):(a1=0,new Promise(async r=>{var l;let A=_.tidy(()=>{if(!(b0!=null&&b0.inputs[0].shape))return null;let y=_.image.resizeBilinear(e,[b0.inputs[0].shape[2],b0.inputs[0].shape[1]],!1),f=_.mul(y,V.tf2);return _.sub(f,V.tf1)}),s;if(t.body.enabled&&(s=b0==null?void 0:b0.execute(A)),u3=h(),_.dispose(A),s){w0.keypoints.length=0;let y=s.squeeze();_.dispose(s);let f=y.unstack(2);_.dispose(y);for(let u=0;u<f.length;u++){let[m,P,g]=await Xr(f[u],t.body.minConfidence);g>(((l=t.body)==null?void 0:l.minConfidence)||0)&&w0.keypoints.push({score:Math.round(100*g)/100,part:A1[u],positionRaw:[m/b0.inputs[0].shape[2],P/b0.inputs[0].shape[1]],position:[Math.round(e.shape[2]*m/b0.inputs[0].shape[2]),Math.round(e.shape[1]*P/b0.inputs[0].shape[1])]})}f.forEach(u=>_.dispose(u))}w0.score=w0.keypoints.reduce((y,f)=>f.score>y?f.score:y,0);let a=w0.keypoints.map(y=>y.position[0]),i=w0.keypoints.map(y=>y.position[1]);w0.box=[Math.min(...a),Math.min(...i),Math.max(...a)-Math.min(...a),Math.max(...i)-Math.min(...i)];let x=w0.keypoints.map(y=>y.positionRaw[0]),c=w0.keypoints.map(y=>y.positionRaw[1]);w0.boxRaw=[Math.min(...x),Math.min(...c),Math.max(...x)-Math.min(...x),Math.max(...c)-Math.min(...c)];for(let[y,f]of Object.entries(s1)){let u=[];for(let m=0;m<f.length-1;m++){let P=w0.keypoints.find(b=>b.part===f[m]),g=w0.keypoints.find(b=>b.part===f[m+1]);P&&g&&P.score>(t.body.minConfidence||0)&&g.score>(t.body.minConfidence||0)&&u.push([P.position,g.position])}w0.annotations[y]=u}r([w0])}))}var U0=Z(D());var qr=["angry","disgust","fear","happy","sad","surprise","neutral"],H0,t5=[],g3=0,M3=0,l1=Number.MAX_SAFE_INTEGER;async function P3(e){var t;return v.initial&&(H0=null),H0?e.debug&&p("cached model:",H0.modelUrl):H0=await G((t=e.face.emotion)==null?void 0:t.modelPath),H0}async function y1(e,t,o,n){var s,a;if(!H0)return[];let r=l1<(((s=t.face.emotion)==null?void 0:s.skipFrames)||0),A=(((a=t.face.emotion)==null?void 0:a.skipTime)||0)>h()-M3;return t.skipAllowed&&A&&r&&g3===n&&t5[o]&&t5[o].length>0?(l1++,t5[o]):(l1=0,new Promise(async i=>{var c,l;let x=[];if((c=t.face.emotion)!=null&&c.enabled){let y={},f=H0!=null&&H0.inputs[0].shape?H0.inputs[0].shape[2]:0;y.resize=U0.image.resizeBilinear(e,[f,f],!1),y.channels=U0.mul(y.resize,V.rgb),y.grayscale=U0.sum(y.channels,3,!0),y.grayscaleSub=U0.sub(y.grayscale,V.tf05),y.grayscaleMul=U0.mul(y.grayscaleSub,V.tf2),y.emotion=H0==null?void 0:H0.execute(y.grayscaleMul),M3=h();let u=await y.emotion.data();for(let m=0;m<u.length;m++)u[m]>(((l=t.face.emotion)==null?void 0:l.minConfidence)||0)&&x.push({score:Math.min(.99,Math.trunc(100*u[m])/100),emotion:qr[m]});x.sort((m,P)=>P.score-m.score),Object.keys(y).forEach(m=>U0.dispose(y[m]))}t5[o]=x,g3=n,i(x)}))}var k3=Z(D());var N0,x1=[],v3=0,T3=0,w3=Number.MAX_SAFE_INTEGER;async function E3(e){return v.initial&&(N0=null),N0?e.debug&&p("cached model:",N0.modelUrl):N0=await G(e.face.mobilefacenet.modelPath),N0}async function c1(e,t,o,n){var s,a;if(!N0)return[];let r=w3<(((s=t.face.embedding)==null?void 0:s.skipFrames)||0),A=(((a=t.face.embedding)==null?void 0:a.skipTime)||0)>h()-T3;return t.skipAllowed&&A&&r&&v3===n&&x1[o]?(w3++,x1[o]):new Promise(async i=>{var c;let x=[];if(((c=t.face.embedding)==null?void 0:c.enabled)&&(N0==null?void 0:N0.inputs[0].shape)){let l={};l.crop=k3.image.resizeBilinear(e,[N0.inputs[0].shape[2],N0.inputs[0].shape[1]],!1),l.data=N0==null?void 0:N0.execute(l.crop);let y=await l.data.data();x=Array.from(y)}x1[o]=x,v3=n,T3=h(),i(x)})}var Be=Z(D());var Y0=Z(D());var xe,Re=0,Ur=2.3,d1=X0.leftEyeLower0,f1=X0.rightEyeLower0,e2={leftBounds:[d1[0],d1[d1.length-1]],rightBounds:[f1[0],f1[f1.length-1]]},t2={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function I3(e){var t;return v.initial&&(xe=null),xe?e.debug&&p("cached model:",xe.modelUrl):xe=await G((t=e.face.iris)==null?void 0:t.modelPath),Re=xe.inputs[0].shape?xe.inputs[0].shape[2]:0,Re===-1&&(Re=64),xe}function o5(e,t,o,n){for(let r=0;r<U5.length;r++){let{key:A,indices:s}=U5[r],a=X0[`${o}${A}`];if(!n||n.includes(A))for(let i=0;i<s.length;i++){let x=s[i];e[a[i]]=[t[x][0],t[x][1],(t[x][2]+e[a[i]][2])/2]}}}var Yr=e=>{let t=e[e2.leftBounds[0]][2],o=e[e2.rightBounds[0]][2];return t-o},S3=(e,t,o,n,r,A=!1)=>{let s=Y2(U2(Yt([e[o],e[n]]),Ur)),a=Je(s),i=Y0.image.cropAndResize(t,[[s.startPoint[1]/r,s.startPoint[0]/r,s.endPoint[1]/r,s.endPoint[0]/r]],[0],[Re,Re]);if(A&&v.kernels.includes("flipleftright")){let x=Y0.image.flipLeftRight(i);Y0.dispose(i),i=x}return{box:s,boxSize:a,crop:i}},C3=(e,t,o,n=!1)=>{let r=[];for(let A=0;A<t2.numCoordinates;A++){let s=e[A*3],a=e[A*3+1],i=e[A*3+2];r.push([(n?1-s/Re:s/Re)*o[0]+t.startPoint[0],a/Re*o[1]+t.startPoint[1],i])}return{rawCoords:r,iris:r.slice(t2.index)}},j3=(e,t,o)=>{let n=e[X0[`${o}EyeUpper0`][t2.upperCenter]][2],r=e[X0[`${o}EyeLower0`][t2.lowerCenter]][2],A=(n+r)/2;return t.map((s,a)=>{let i=A;return a===2?i=n:a===4&&(i=r),[s[0],s[1],i]})};async function N3(e,t,o,n){if(!xe)return o.debug&&p("face mesh iris detection requested, but model is not loaded"),e;let{box:r,boxSize:A,crop:s}=S3(e,t,e2.leftBounds[0],e2.leftBounds[1],n,!0),{box:a,boxSize:i,crop:x}=S3(e,t,e2.rightBounds[0],e2.rightBounds[1],n,!0),c=Y0.concat([s,x]);Y0.dispose(s),Y0.dispose(x);let l=xe.execute(c);Y0.dispose(c);let y=await l.data();Y0.dispose(l);let f=y.slice(0,t2.numCoordinates*3),{rawCoords:u,iris:m}=C3(f,r,A,!0),P=y.slice(t2.numCoordinates*3),{rawCoords:g,iris:b}=C3(P,a,i,!1),d=Yr(e);Math.abs(d)<30?(o5(e,u,"left",null),o5(e,g,"right",null)):d<1?o5(e,u,"left",["EyeUpper0","EyeLower0"]):o5(e,g,"right",["EyeUpper0","EyeLower0"]);let M=j3(e,m,"left"),S=j3(e,b,"right");return e.concat(M).concat(S)}var Kr=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Jr=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Qr=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],_r=[[474,475],[475,476],[476,477],[477,474]],$r=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],eA=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],tA=[[469,470],[470,471],[471,472],[472,469]],oA=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]];function ve(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var nA={lips:ve(Kr),leftEye:ve(Jr),leftEyebrow:ve(Qr),leftIris:ve(_r),rightEye:ve($r),rightEyebrow:ve(eA),rightIris:ve(tA),faceOval:ve(oA)},rA=Object.entries(nA).map(([e,t])=>t.map(o=>[o,e])).flat(),f4=new Map(rA),w2=[61,146,91,181,84,17,314,405,321,375,291,185,40,39,37,0,267,269,270,409,78,95,88,178,87,14,317,402,318,324,308,191,80,81,82,13,312,311,310,415,76,77,90,180,85,16,315,404,320,307,306,184,74,73,72,11,302,303,304,408,62,96,89,179,86,15,316,403,319,325,292,183,42,41,38,12,268,271,272,407],We=[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173,130,25,110,24,23,22,26,112,243,247,30,29,27,28,56,190,226,31,228,229,230,231,232,233,244,113,225,224,223,222,221,189,35,124,46,53,52,65,143,111,117,118,119,120,121,128,245,156,70,63,105,66,107,55,193],Fe=[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398,359,255,339,254,253,252,256,341,463,467,260,259,257,258,286,414,446,261,448,449,450,451,452,453,464,342,445,444,443,442,441,413,265,353,276,283,282,295,372,340,346,347,348,349,350,357,465,383,300,293,334,296,336,285,417];async function W3(e,t){let o={lips:await t.filter(A=>A.size===160)[0].data(),irisL:await t.filter(A=>A.size===10)[0].data(),eyeL:await t.filter(A=>A.size===142)[0].data(),irisR:await t.filter(A=>A.size===10)[1].data(),eyeR:await t.filter(A=>A.size===142)[1].data()},n=We.reduce((A,s)=>A+=e[s][2],0)/We.length;for(let A=0;A<o.irisL.length/2;A++)e.push([o.irisL[2*A+0],o.irisL[2*A+1],n]);let r=Fe.reduce((A,s)=>A+=e[s][2],0)/Fe.length;for(let A=0;A<o.irisR.length/2;A++)e.push([o.irisR[2*A+0],o.irisR[2*A+1],r]);for(let A=0;A<o.eyeL.length/2;A++)e[We[A]]=[o.eyeL[2*A+0],o.eyeL[2*A+1],e[We[A]][2]];for(let A=0;A<o.eyeR.length/2;A++)e[Fe[A]]=[o.eyeR[2*A+0],o.eyeR[2*A+1],e[Fe[A]][2]];for(let A=0;A<o.lips.length/2;A++)e[w2[A]]=[o.lips[2*A+0],o.lips[2*A+1],e[w2[A]][2]];return e}var oe={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},g0=null,Ge=0;async function F3(e,t){var a,i,x,c,l,y,f,u,m,P,g;let o=(((a=t.face.detector)==null?void 0:a.skipTime)||0)>h()-oe.timestamp,n=oe.skipped<(((i=t.face.detector)==null?void 0:i.skipFrames)||0);!t.skipAllowed||!o||!n||oe.boxes.length===0?(oe.boxes=await n3(e,t),oe.timestamp=h(),oe.skipped=0):oe.skipped++;let r=[],A=[],s=0;for(let b=0;b<oe.boxes.length;b++){let d=oe.boxes[b],M=0,S,w={id:s++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,annotations:{}};if([M,S,w.tensor]=_t((x=t.face.detector)==null?void 0:x.rotation,d,e,(c=t.face.mesh)!=null&&c.enabled?Ge:Qe()),(l=t==null?void 0:t.filter)!=null&&l.equalization){let j=await O2(w.tensor);Be.dispose(w.tensor),w.tensor=j}if(w.boxScore=Math.round(100*d.confidence)/100,(y=t.face.mesh)!=null&&y.enabled)if(!g0)t.debug&&p("face mesh detection requested, but model is not loaded");else{let j=g0.execute(w.tensor),F=await j.find(H=>H.shape[H.shape.length-1]===1).data();if(w.faceScore=Math.round(100*F[0])/100,w.faceScore<(((f=t.face.detector)==null?void 0:f.minConfidence)||1)){if(d.confidence=w.faceScore,(u=t.face.mesh)!=null&&u.keepInvalid){w.box=X2(d,e),w.boxRaw=q2(d,e),w.score=w.boxScore,w.mesh=d.landmarks.map(H=>[(d.startPoint[0]+d.endPoint[0])/2+(d.endPoint[0]+d.startPoint[0])*H[0]/Qe(),(d.startPoint[1]+d.endPoint[1])/2+(d.endPoint[1]+d.startPoint[1])*H[1]/Qe()]),w.meshRaw=w.mesh.map(H=>[H[0]/(e.shape[2]||1),H[1]/(e.shape[1]||1),(H[2]||0)/Ge]);for(let H of Object.keys(Ie))w.annotations[H]=[w.mesh[Ie[H]]]}}else{let H=j.find(E=>E.shape[E.shape.length-1]===1404),Y=Be.reshape(H,[-1,3]),J=await Y.array();Be.dispose(Y),(m=t.face.attention)!=null&&m.enabled?J=await W3(J,j):(P=t.face.iris)!=null&&P.enabled&&(J=await N3(J,w.tensor,t,Ge)),w.mesh=Qt(J,d,M,S,Ge),w.meshRaw=w.mesh.map(E=>[E[0]/(e.shape[2]||0),E[1]/(e.shape[1]||0),(E[2]||0)/Ge]);for(let E of Object.keys(X0))w.annotations[E]=X0[E].map(G0=>w.mesh[G0]);w.score=w.faceScore;let x0={...$t(w.mesh,d),confidence:d.confidence,landmarks:d.landmarks};w.box=X2(x0,e),w.boxRaw=q2(x0,e),A.push(x0)}Be.dispose(j)}else{w.box=X2(d,e),w.boxRaw=q2(d,e),w.score=w.boxScore,w.mesh=d.landmarks.map(j=>[(d.startPoint[0]+d.endPoint[0])/2+(d.endPoint[0]+d.startPoint[0])*j[0]/Qe(),(d.startPoint[1]+d.endPoint[1])/2+(d.endPoint[1]+d.startPoint[1])*j[1]/Qe()]),w.meshRaw=w.mesh.map(j=>[j[0]/(e.shape[2]||0),j[1]/(e.shape[1]||0),(j[2]||0)/Ge]);for(let j of Object.keys(Ie))w.annotations[j]=[w.mesh[Ie[j]]]}w.score>(((g=t.face.detector)==null?void 0:g.minConfidence)||1)?r.push(w):Be.dispose(w.tensor)}return oe.boxes=A,r}async function G3(e){var t,o,n,r,A,s;return v.initial&&(g0=null),((o=(t=e==null?void 0:e.face)==null?void 0:t.attention)==null?void 0:o.enabled)&&(g0==null?void 0:g0.signature)&&Object.keys(((n=g0==null?void 0:g0.signature)==null?void 0:n.outputs)||{}).length<6&&(g0=null),g0?e.debug&&p("cached model:",g0.modelUrl):(r=e.face.attention)!=null&&r.enabled?g0=await G((A=e.face.attention)==null?void 0:A.modelPath):g0=await G((s=e.face.mesh)==null?void 0:s.modelPath),Ge=g0.inputs[0].shape?g0.inputs[0].shape[2]:0,g0}var B3=Ne,H3=R2;var K0=Z(D());var O0,n5=[],V3=0,D3=0,p1=Number.MAX_SAFE_INTEGER;async function Z3(e){var t;return v.initial&&(O0=null),O0?e.debug&&p("cached model:",O0.modelUrl):O0=await G((t=e.face.description)==null?void 0:t.modelPath),O0}function u1(e){let t=e.image||e.tensor||e;if(!(O0!=null&&O0.inputs[0].shape))return t;let o=K0.image.resizeBilinear(t,[O0.inputs[0].shape[2],O0.inputs[0].shape[1]],!1),n=K0.mul(o,V.tf255);return K0.dispose(o),n}async function h1(e,t,o,n){var s,a,i,x;if(!O0)return{age:0,gender:"unknown",genderScore:0,descriptor:[]};let r=p1<(((s=t.face.description)==null?void 0:s.skipFrames)||0),A=(((a=t.face.description)==null?void 0:a.skipTime)||0)>h()-V3;return t.skipAllowed&&r&&A&&D3===n&&((i=n5[o])==null?void 0:i.age)&&((x=n5[o])==null?void 0:x.age)>0?(p1++,n5[o]):(p1=0,new Promise(async c=>{var y,f;let l={age:0,gender:"unknown",genderScore:0,descriptor:[]};if((y=t.face.description)!=null&&y.enabled){let u=u1(e),m=O0==null?void 0:O0.execute(u);V3=h(),K0.dispose(u);let g=await(await m.find(F=>F.shape[1]===1)).data(),b=Math.trunc(200*Math.abs(g[0]-.5))/100;b>(((f=t.face.description)==null?void 0:f.minConfidence)||0)&&(l.gender=g[0]<=.5?"female":"male",l.genderScore=Math.min(.99,b));let d=K0.argMax(m.find(F=>F.shape[1]===100),1),M=(await d.data())[0];K0.dispose(d);let w=await m.find(F=>F.shape[1]===100).data();l.age=Math.round(w[M-1]>w[M+1]?10*M-100*w[M-1]:10*M+100*w[M+1])/10;let j=m.find(F=>F.shape[1]===1024),C=j?await j.data():[];l.descriptor=Array.from(C),m.forEach(F=>K0.dispose(F))}n5[o]=l,D3=n,c(l)}))}var W=Z(D());var U3=Z(D());function r5(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function k2(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function Y3(e,t,o){let n=t.shape[1],r=t.shape[2],A=[[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r]];return U3.image.cropAndResize(t,A,[0],o)}function K3(e,t){let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],r=e.palmLandmarks.map(A=>[A[0]*t[0],A[1]*t[1]]);return{startPoint:o,endPoint:n,palmLandmarks:r,confidence:e.confidence}}function A5(e,t=1.5){let o=k2(e),n=r5(e),r=[t*n[0]/2,t*n[1]/2],A=[o[0]-r[0],o[1]-r[1]],s=[o[0]+r[0],o[1]+r[1]];return{startPoint:A,endPoint:s,palmLandmarks:e.palmLandmarks}}function s5(e){let t=k2(e),o=r5(e),r=Math.max(...o)/2,A=[t[0]-r,t[1]-r],s=[t[0]+r,t[1]+r];return{startPoint:A,endPoint:s,palmLandmarks:e.palmLandmarks}}function sA(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function J3(e,t){let o=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return sA(o)}var X3=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function Te(e,t){let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o}function aA(e,t){let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o}function q3(e,t){let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let A=0;A<n;A++)o[r].push(Te(e[r],aA(t,A)))}return o}function g1(e,t){let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],A=X3(t[0],t[1]),s=q3(A,r),a=X3(-t[0],-t[1]);return q3(s,a)}function Q3(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-Te(t[0],o),-Te(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]}function M1(e,t){return[Te(e,t[0]),Te(e,t[1])]}var $3=[{x:.015625,y:.015625},{x:.015625,y:.015625},{x:.046875,y:.015625},{x:.046875,y:.015625},{x:.078125,y:.015625},{x:.078125,y:.015625},{x:.109375,y:.015625},{x:.109375,y:.015625},{x:.140625,y:.015625},{x:.140625,y:.015625},{x:.171875,y:.015625},{x:.171875,y:.015625},{x:.203125,y:.015625},{x:.203125,y:.015625},{x:.234375,y:.015625},{x:.234375,y:.015625},{x:.265625,y:.015625},{x:.265625,y:.015625},{x:.296875,y:.015625},{x:.296875,y:.015625},{x:.328125,y:.015625},{x:.328125,y:.015625},{x:.359375,y:.015625},{x:.359375,y:.015625},{x:.390625,y:.015625},{x:.390625,y:.015625},{x:.421875,y:.015625},{x:.421875,y:.015625},{x:.453125,y:.015625},{x:.453125,y:.015625},{x:.484375,y:.015625},{x:.484375,y:.015625},{x:.515625,y:.015625},{x:.515625,y:.015625},{x:.546875,y:.015625},{x:.546875,y:.015625},{x:.578125,y:.015625},{x:.578125,y:.015625},{x:.609375,y:.015625},{x:.609375,y:.015625},{x:.640625,y:.015625},{x:.640625,y:.015625},{x:.671875,y:.015625},{x:.671875,y:.015625},{x:.703125,y:.015625},{x:.703125,y:.015625},{x:.734375,y:.015625},{x:.734375,y:.015625},{x:.765625,y:.015625},{x:.765625,y:.015625},{x:.796875,y:.015625},{x:.796875,y:.015625},{x:.828125,y:.015625},{x:.828125,y:.015625},{x:.859375,y:.015625},{x:.859375,y:.015625},{x:.890625,y:.015625},{x:.890625,y:.015625},{x:.921875,y:.015625},{x:.921875,y:.015625},{x:.953125,y:.015625},{x:.953125,y:.015625},{x:.984375,y:.015625},{x:.984375,y:.015625},{x:.015625,y:.046875},{x:.015625,y:.046875},{x:.046875,y:.046875},{x:.046875,y:.046875},{x:.078125,y:.046875},{x:.078125,y:.046875},{x:.109375,y:.046875},{x:.109375,y:.046875},{x:.140625,y:.046875},{x:.140625,y:.046875},{x:.171875,y:.046875},{x:.171875,y:.046875},{x:.203125,y:.046875},{x:.203125,y:.046875},{x:.234375,y:.046875},{x:.234375,y:.046875},{x:.265625,y:.046875},{x:.265625,y:.046875},{x:.296875,y:.046875},{x:.296875,y:.046875},{x:.328125,y:.046875},{x:.328125,y:.046875},{x:.359375,y:.046875},{x:.359375,y:.046875},{x:.390625,y:.046875},{x:.390625,y:.046875},{x:.421875,y:.046875},{x:.421875,y:.046875},{x:.453125,y:.046875},{x:.453125,y:.046875},{x:.484375,y:.046875},{x:.484375,y:.046875},{x:.515625,y:.046875},{x:.515625,y:.046875},{x:.546875,y:.046875},{x:.546875,y:.046875},{x:.578125,y:.046875},{x:.578125,y:.046875},{x:.609375,y:.046875},{x:.609375,y:.046875},{x:.640625,y:.046875},{x:.640625,y:.046875},{x:.671875,y:.046875},{x:.671875,y:.046875},{x:.703125,y:.046875},{x:.703125,y:.046875},{x:.734375,y:.046875},{x:.734375,y:.046875},{x:.765625,y:.046875},{x:.765625,y:.046875},{x:.796875,y:.046875},{x:.796875,y:.046875},{x:.828125,y:.046875},{x:.828125,y:.046875},{x:.859375,y:.046875},{x:.859375,y:.046875},{x:.890625,y:.046875},{x:.890625,y:.046875},{x:.921875,y:.046875},{x:.921875,y:.046875},{x:.953125,y:.046875},{x:.953125,y:.046875},{x:.984375,y:.046875},{x:.984375,y:.046875},{x:.015625,y:.078125},{x:.015625,y:.078125},{x:.046875,y:.078125},{x:.046875,y:.078125},{x:.078125,y:.078125},{x:.078125,y:.078125},{x:.109375,y:.078125},{x:.109375,y:.078125},{x:.140625,y:.078125},{x:.140625,y:.078125},{x:.171875,y:.078125},{x:.171875,y:.078125},{x:.203125,y:.078125},{x:.203125,y:.078125},{x:.234375,y:.078125},{x:.234375,y:.078125},{x:.265625,y:.078125},{x:.265625,y:.078125},{x:.296875,y:.078125},{x:.296875,y:.078125},{x:.328125,y:.078125},{x:.328125,y:.078125},{x:.359375,y:.078125},{x:.359375,y:.078125},{x:.390625,y:.078125},{x:.390625,y:.078125},{x:.421875,y:.078125},{x:.421875,y:.078125},{x:.453125,y:.078125},{x:.453125,y:.078125},{x:.484375,y:.078125},{x:.484375,y:.078125},{x:.515625,y:.078125},{x:.515625,y:.078125},{x:.546875,y:.078125},{x:.546875,y:.078125},{x:.578125,y:.078125},{x:.578125,y:.078125},{x:.609375,y:.078125},{x:.609375,y:.078125},{x:.640625,y:.078125},{x:.640625,y:.078125},{x:.671875,y:.078125},{x:.671875,y:.078125},{x:.703125,y:.078125},{x:.703125,y:.078125},{x:.734375,y:.078125},{x:.734375,y:.078125},{x:.765625,y:.078125},{x:.765625,y:.078125},{x:.796875,y:.078125},{x:.796875,y:.078125},{x:.828125,y:.078125},{x:.828125,y:.078125},{x:.859375,y:.078125},{x:.859375,y:.078125},{x:.890625,y:.078125},{x:.890625,y:.078125},{x:.921875,y:.078125},{x:.921875,y:.078125},{x:.953125,y:.078125},{x:.953125,y:.078125},{x:.984375,y:.078125},{x:.984375,y:.078125},{x:.015625,y:.109375},{x:.015625,y:.109375},{x:.046875,y:.109375},{x:.046875,y:.109375},{x:.078125,y:.109375},{x:.078125,y:.109375},{x:.109375,y:.109375},{x:.109375,y:.109375},{x:.140625,y:.109375},{x:.140625,y:.109375},{x:.171875,y:.109375},{x:.171875,y:.109375},{x:.203125,y:.109375},{x:.203125,y:.109375},{x:.234375,y:.109375},{x:.234375,y:.109375},{x:.265625,y:.109375},{x:.265625,y:.109375},{x:.296875,y:.109375},{x:.296875,y:.109375},{x:.328125,y:.109375},{x:.328125,y:.109375},{x:.359375,y:.109375},{x:.359375,y:.109375},{x:.390625,y:.109375},{x:.390625,y:.109375},{x:.421875,y:.109375},{x:.421875,y:.109375},{x:.453125,y:.109375},{x:.453125,y:.109375},{x:.484375,y:.109375},{x:.484375,y:.109375},{x:.515625,y:.109375},{x:.515625,y:.109375},{x:.546875,y:.109375},{x:.546875,y:.109375},{x:.578125,y:.109375},{x:.578125,y:.109375},{x:.609375,y:.109375},{x:.609375,y:.109375},{x:.640625,y:.109375},{x:.640625,y:.109375},{x:.671875,y:.109375},{x:.671875,y:.109375},{x:.703125,y:.109375},{x:.703125,y:.109375},{x:.734375,y:.109375},{x:.734375,y:.109375},{x:.765625,y:.109375},{x:.765625,y:.109375},{x:.796875,y:.109375},{x:.796875,y:.109375},{x:.828125,y:.109375},{x:.828125,y:.109375},{x:.859375,y:.109375},{x:.859375,y:.109375},{x:.890625,y:.109375},{x:.890625,y:.109375},{x:.921875,y:.109375},{x:.921875,y:.109375},{x:.953125,y:.109375},{x:.953125,y:.109375},{x:.984375,y:.109375},{x:.984375,y:.109375},{x:.015625,y:.140625},{x:.015625,y:.140625},{x:.046875,y:.140625},{x:.046875,y:.140625},{x:.078125,y:.140625},{x:.078125,y:.140625},{x:.109375,y:.140625},{x:.109375,y:.140625},{x:.140625,y:.140625},{x:.140625,y:.140625},{x:.171875,y:.140625},{x:.171875,y:.140625},{x:.203125,y:.140625},{x:.203125,y:.140625},{x:.234375,y:.140625},{x:.234375,y:.140625},{x:.265625,y:.140625},{x:.265625,y:.140625},{x:.296875,y:.140625},{x:.296875,y:.140625},{x:.328125,y:.140625},{x:.328125,y:.140625},{x:.359375,y:.140625},{x:.359375,y:.140625},{x:.390625,y:.140625},{x:.390625,y:.140625},{x:.421875,y:.140625},{x:.421875,y:.140625},{x:.453125,y:.140625},{x:.453125,y:.140625},{x:.484375,y:.140625},{x:.484375,y:.140625},{x:.515625,y:.140625},{x:.515625,y:.140625},{x:.546875,y:.140625},{x:.546875,y:.140625},{x:.578125,y:.140625},{x:.578125,y:.140625},{x:.609375,y:.140625},{x:.609375,y:.140625},{x:.640625,y:.140625},{x:.640625,y:.140625},{x:.671875,y:.140625},{x:.671875,y:.140625},{x:.703125,y:.140625},{x:.703125,y:.140625},{x:.734375,y:.140625},{x:.734375,y:.140625},{x:.765625,y:.140625},{x:.765625,y:.140625},{x:.796875,y:.140625},{x:.796875,y:.140625},{x:.828125,y:.140625},{x:.828125,y:.140625},{x:.859375,y:.140625},{x:.859375,y:.140625},{x:.890625,y:.140625},{x:.890625,y:.140625},{x:.921875,y:.140625},{x:.921875,y:.140625},{x:.953125,y:.140625},{x:.953125,y:.140625},{x:.984375,y:.140625},{x:.984375,y:.140625},{x:.015625,y:.171875},{x:.015625,y:.171875},{x:.046875,y:.171875},{x:.046875,y:.171875},{x:.078125,y:.171875},{x:.078125,y:.171875},{x:.109375,y:.171875},{x:.109375,y:.171875},{x:.140625,y:.171875},{x:.140625,y:.171875},{x:.171875,y:.171875},{x:.171875,y:.171875},{x:.203125,y:.171875},{x:.203125,y:.171875},{x:.234375,y:.171875},{x:.234375,y:.171875},{x:.265625,y:.171875},{x:.265625,y:.171875},{x:.296875,y:.171875},{x:.296875,y:.171875},{x:.328125,y:.171875},{x:.328125,y:.171875},{x:.359375,y:.171875},{x:.359375,y:.171875},{x:.390625,y:.171875},{x:.390625,y:.171875},{x:.421875,y:.171875},{x:.421875,y:.171875},{x:.453125,y:.171875},{x:.453125,y:.171875},{x:.484375,y:.171875},{x:.484375,y:.171875},{x:.515625,y:.171875},{x:.515625,y:.171875},{x:.546875,y:.171875},{x:.546875,y:.171875},{x:.578125,y:.171875},{x:.578125,y:.171875},{x:.609375,y:.171875},{x:.609375,y:.171875},{x:.640625,y:.171875},{x:.640625,y:.171875},{x:.671875,y:.171875},{x:.671875,y:.171875},{x:.703125,y:.171875},{x:.703125,y:.171875},{x:.734375,y:.171875},{x:.734375,y:.171875},{x:.765625,y:.171875},{x:.765625,y:.171875},{x:.796875,y:.171875},{x:.796875,y:.171875},{x:.828125,y:.171875},{x:.828125,y:.171875},{x:.859375,y:.171875},{x:.859375,y:.171875},{x:.890625,y:.171875},{x:.890625,y:.171875},{x:.921875,y:.171875},{x:.921875,y:.171875},{x:.953125,y:.171875},{x:.953125,y:.171875},{x:.984375,y:.171875},{x:.984375,y:.171875},{x:.015625,y:.203125},{x:.015625,y:.203125},{x:.046875,y:.203125},{x:.046875,y:.203125},{x:.078125,y:.203125},{x:.078125,y:.203125},{x:.109375,y:.203125},{x:.109375,y:.203125},{x:.140625,y:.203125},{x:.140625,y:.203125},{x:.171875,y:.203125},{x:.171875,y:.203125},{x:.203125,y:.203125},{x:.203125,y:.203125},{x:.234375,y:.203125},{x:.234375,y:.203125},{x:.265625,y:.203125},{x:.265625,y:.203125},{x:.296875,y:.203125},{x:.296875,y:.203125},{x:.328125,y:.203125},{x:.328125,y:.203125},{x:.359375,y:.203125},{x:.359375,y:.203125},{x:.390625,y:.203125},{x:.390625,y:.203125},{x:.421875,y:.203125},{x:.421875,y:.203125},{x:.453125,y:.203125},{x:.453125,y:.203125},{x:.484375,y:.203125},{x:.484375,y:.203125},{x:.515625,y:.203125},{x:.515625,y:.203125},{x:.546875,y:.203125},{x:.546875,y:.203125},{x:.578125,y:.203125},{x:.578125,y:.203125},{x:.609375,y:.203125},{x:.609375,y:.203125},{x:.640625,y:.203125},{x:.640625,y:.203125},{x:.671875,y:.203125},{x:.671875,y:.203125},{x:.703125,y:.203125},{x:.703125,y:.203125},{x:.734375,y:.203125},{x:.734375,y:.203125},{x:.765625,y:.203125},{x:.765625,y:.203125},{x:.796875,y:.203125},{x:.796875,y:.203125},{x:.828125,y:.203125},{x:.828125,y:.203125},{x:.859375,y:.203125},{x:.859375,y:.203125},{x:.890625,y:.203125},{x:.890625,y:.203125},{x:.921875,y:.203125},{x:.921875,y:.203125},{x:.953125,y:.203125},{x:.953125,y:.203125},{x:.984375,y:.203125},{x:.984375,y:.203125},{x:.015625,y:.234375},{x:.015625,y:.234375},{x:.046875,y:.234375},{x:.046875,y:.234375},{x:.078125,y:.234375},{x:.078125,y:.234375},{x:.109375,y:.234375},{x:.109375,y:.234375},{x:.140625,y:.234375},{x:.140625,y:.234375},{x:.171875,y:.234375},{x:.171875,y:.234375},{x:.203125,y:.234375},{x:.203125,y:.234375},{x:.234375,y:.234375},{x:.234375,y:.234375},{x:.265625,y:.234375},{x:.265625,y:.234375},{x:.296875,y:.234375},{x:.296875,y:.234375},{x:.328125,y:.234375},{x:.328125,y:.234375},{x:.359375,y:.234375},{x:.359375,y:.234375},{x:.390625,y:.234375},{x:.390625,y:.234375},{x:.421875,y:.234375},{x:.421875,y:.234375},{x:.453125,y:.234375},{x:.453125,y:.234375},{x:.484375,y:.234375},{x:.484375,y:.234375},{x:.515625,y:.234375},{x:.515625,y:.234375},{x:.546875,y:.234375},{x:.546875,y:.234375},{x:.578125,y:.234375},{x:.578125,y:.234375},{x:.609375,y:.234375},{x:.609375,y:.234375},{x:.640625,y:.234375},{x:.640625,y:.234375},{x:.671875,y:.234375},{x:.671875,y:.234375},{x:.703125,y:.234375},{x:.703125,y:.234375},{x:.734375,y:.234375},{x:.734375,y:.234375},{x:.765625,y:.234375},{x:.765625,y:.234375},{x:.796875,y:.234375},{x:.796875,y:.234375},{x:.828125,y:.234375},{x:.828125,y:.234375},{x:.859375,y:.234375},{x:.859375,y:.234375},{x:.890625,y:.234375},{x:.890625,y:.234375},{x:.921875,y:.234375},{x:.921875,y:.234375},{x:.953125,y:.234375},{x:.953125,y:.234375},{x:.984375,y:.234375},{x:.984375,y:.234375},{x:.015625,y:.265625},{x:.015625,y:.265625},{x:.046875,y:.265625},{x:.046875,y:.265625},{x:.078125,y:.265625},{x:.078125,y:.265625},{x:.109375,y:.265625},{x:.109375,y:.265625},{x:.140625,y:.265625},{x:.140625,y:.265625},{x:.171875,y:.265625},{x:.171875,y:.265625},{x:.203125,y:.265625},{x:.203125,y:.265625},{x:.234375,y:.265625},{x:.234375,y:.265625},{x:.265625,y:.265625},{x:.265625,y:.265625},{x:.296875,y:.265625},{x:.296875,y:.265625},{x:.328125,y:.265625},{x:.328125,y:.265625},{x:.359375,y:.265625},{x:.359375,y:.265625},{x:.390625,y:.265625},{x:.390625,y:.265625},{x:.421875,y:.265625},{x:.421875,y:.265625},{x:.453125,y:.265625},{x:.453125,y:.265625},{x:.484375,y:.265625},{x:.484375,y:.265625},{x:.515625,y:.265625},{x:.515625,y:.265625},{x:.546875,y:.265625},{x:.546875,y:.265625},{x:.578125,y:.265625},{x:.578125,y:.265625},{x:.609375,y:.265625},{x:.609375,y:.265625},{x:.640625,y:.265625},{x:.640625,y:.265625},{x:.671875,y:.265625},{x:.671875,y:.265625},{x:.703125,y:.265625},{x:.703125,y:.265625},{x:.734375,y:.265625},{x:.734375,y:.265625},{x:.765625,y:.265625},{x:.765625,y:.265625},{x:.796875,y:.265625},{x:.796875,y:.265625},{x:.828125,y:.265625},{x:.828125,y:.265625},{x:.859375,y:.265625},{x:.859375,y:.265625},{x:.890625,y:.265625},{x:.890625,y:.265625},{x:.921875,y:.265625},{x:.921875,y:.265625},{x:.953125,y:.265625},{x:.953125,y:.265625},{x:.984375,y:.265625},{x:.984375,y:.265625},{x:.015625,y:.296875},{x:.015625,y:.296875},{x:.046875,y:.296875},{x:.046875,y:.296875},{x:.078125,y:.296875},{x:.078125,y:.296875},{x:.109375,y:.296875},{x:.109375,y:.296875},{x:.140625,y:.296875},{x:.140625,y:.296875},{x:.171875,y:.296875},{x:.171875,y:.296875},{x:.203125,y:.296875},{x:.203125,y:.296875},{x:.234375,y:.296875},{x:.234375,y:.296875},{x:.265625,y:.296875},{x:.265625,y:.296875},{x:.296875,y:.296875},{x:.296875,y:.296875},{x:.328125,y:.296875},{x:.328125,y:.296875},{x:.359375,y:.296875},{x:.359375,y:.296875},{x:.390625,y:.296875},{x:.390625,y:.296875},{x:.421875,y:.296875},{x:.421875,y:.296875},{x:.453125,y:.296875},{x:.453125,y:.296875},{x:.484375,y:.296875},{x:.484375,y:.296875},{x:.515625,y:.296875},{x:.515625,y:.296875},{x:.546875,y:.296875},{x:.546875,y:.296875},{x:.578125,y:.296875},{x:.578125,y:.296875},{x:.609375,y:.296875},{x:.609375,y:.296875},{x:.640625,y:.296875},{x:.640625,y:.296875},{x:.671875,y:.296875},{x:.671875,y:.296875},{x:.703125,y:.296875},{x:.703125,y:.296875},{x:.734375,y:.296875},{x:.734375,y:.296875},{x:.765625,y:.296875},{x:.765625,y:.296875},{x:.796875,y:.296875},{x:.796875,y:.296875},{x:.828125,y:.296875},{x:.828125,y:.296875},{x:.859375,y:.296875},{x:.859375,y:.296875},{x:.890625,y:.296875},{x:.890625,y:.296875},{x:.921875,y:.296875},{x:.921875,y:.296875},{x:.953125,y:.296875},{x:.953125,y:.296875},{x:.984375,y:.296875},{x:.984375,y:.296875},{x:.015625,y:.328125},{x:.015625,y:.328125},{x:.046875,y:.328125},{x:.046875,y:.328125},{x:.078125,y:.328125},{x:.078125,y:.328125},{x:.109375,y:.328125},{x:.109375,y:.328125},{x:.140625,y:.328125},{x:.140625,y:.328125},{x:.171875,y:.328125},{x:.171875,y:.328125},{x:.203125,y:.328125},{x:.203125,y:.328125},{x:.234375,y:.328125},{x:.234375,y:.328125},{x:.265625,y:.328125},{x:.265625,y:.328125},{x:.296875,y:.328125},{x:.296875,y:.328125},{x:.328125,y:.328125},{x:.328125,y:.328125},{x:.359375,y:.328125},{x:.359375,y:.328125},{x:.390625,y:.328125},{x:.390625,y:.328125},{x:.421875,y:.328125},{x:.421875,y:.328125},{x:.453125,y:.328125},{x:.453125,y:.328125},{x:.484375,y:.328125},{x:.484375,y:.328125},{x:.515625,y:.328125},{x:.515625,y:.328125},{x:.546875,y:.328125},{x:.546875,y:.328125},{x:.578125,y:.328125},{x:.578125,y:.328125},{x:.609375,y:.328125},{x:.609375,y:.328125},{x:.640625,y:.328125},{x:.640625,y:.328125},{x:.671875,y:.328125},{x:.671875,y:.328125},{x:.703125,y:.328125},{x:.703125,y:.328125},{x:.734375,y:.328125},{x:.734375,y:.328125},{x:.765625,y:.328125},{x:.765625,y:.328125},{x:.796875,y:.328125},{x:.796875,y:.328125},{x:.828125,y:.328125},{x:.828125,y:.328125},{x:.859375,y:.328125},{x:.859375,y:.328125},{x:.890625,y:.328125},{x:.890625,y:.328125},{x:.921875,y:.328125},{x:.921875,y:.328125},{x:.953125,y:.328125},{x:.953125,y:.328125},{x:.984375,y:.328125},{x:.984375,y:.328125},{x:.015625,y:.359375},{x:.015625,y:.359375},{x:.046875,y:.359375},{x:.046875,y:.359375},{x:.078125,y:.359375},{x:.078125,y:.359375},{x:.109375,y:.359375},{x:.109375,y:.359375},{x:.140625,y:.359375},{x:.140625,y:.359375},{x:.171875,y:.359375},{x:.171875,y:.359375},{x:.203125,y:.359375},{x:.203125,y:.359375},{x:.234375,y:.359375},{x:.234375,y:.359375},{x:.265625,y:.359375},{x:.265625,y:.359375},{x:.296875,y:.359375},{x:.296875,y:.359375},{x:.328125,y:.359375},{x:.328125,y:.359375},{x:.359375,y:.359375},{x:.359375,y:.359375},{x:.390625,y:.359375},{x:.390625,y:.359375},{x:.421875,y:.359375},{x:.421875,y:.359375},{x:.453125,y:.359375},{x:.453125,y:.359375},{x:.484375,y:.359375},{x:.484375,y:.359375},{x:.515625,y:.359375},{x:.515625,y:.359375},{x:.546875,y:.359375},{x:.546875,y:.359375},{x:.578125,y:.359375},{x:.578125,y:.359375},{x:.609375,y:.359375},{x:.609375,y:.359375},{x:.640625,y:.359375},{x:.640625,y:.359375},{x:.671875,y:.359375},{x:.671875,y:.359375},{x:.703125,y:.359375},{x:.703125,y:.359375},{x:.734375,y:.359375},{x:.734375,y:.359375},{x:.765625,y:.359375},{x:.765625,y:.359375},{x:.796875,y:.359375},{x:.796875,y:.359375},{x:.828125,y:.359375},{x:.828125,y:.359375},{x:.859375,y:.359375},{x:.859375,y:.359375},{x:.890625,y:.359375},{x:.890625,y:.359375},{x:.921875,y:.359375},{x:.921875,y:.359375},{x:.953125,y:.359375},{x:.953125,y:.359375},{x:.984375,y:.359375},{x:.984375,y:.359375},{x:.015625,y:.390625},{x:.015625,y:.390625},{x:.046875,y:.390625},{x:.046875,y:.390625},{x:.078125,y:.390625},{x:.078125,y:.390625},{x:.109375,y:.390625},{x:.109375,y:.390625},{x:.140625,y:.390625},{x:.140625,y:.390625},{x:.171875,y:.390625},{x:.171875,y:.390625},{x:.203125,y:.390625},{x:.203125,y:.390625},{x:.234375,y:.390625},{x:.234375,y:.390625},{x:.265625,y:.390625},{x:.265625,y:.390625},{x:.296875,y:.390625},{x:.296875,y:.390625},{x:.328125,y:.390625},{x:.328125,y:.390625},{x:.359375,y:.390625},{x:.359375,y:.390625},{x:.390625,y:.390625},{x:.390625,y:.390625},{x:.421875,y:.390625},{x:.421875,y:.390625},{x:.453125,y:.390625},{x:.453125,y:.390625},{x:.484375,y:.390625},{x:.484375,y:.390625},{x:.515625,y:.390625},{x:.515625,y:.390625},{x:.546875,y:.390625},{x:.546875,y:.390625},{x:.578125,y:.390625},{x:.578125,y:.390625},{x:.609375,y:.390625},{x:.609375,y:.390625},{x:.640625,y:.390625},{x:.640625,y:.390625},{x:.671875,y:.390625},{x:.671875,y:.390625},{x:.703125,y:.390625},{x:.703125,y:.390625},{x:.734375,y:.390625},{x:.734375,y:.390625},{x:.765625,y:.390625},{x:.765625,y:.390625},{x:.796875,y:.390625},{x:.796875,y:.390625},{x:.828125,y:.390625},{x:.828125,y:.390625},{x:.859375,y:.390625},{x:.859375,y:.390625},{x:.890625,y:.390625},{x:.890625,y:.390625},{x:.921875,y:.390625},{x:.921875,y:.390625},{x:.953125,y:.390625},{x:.953125,y:.390625},{x:.984375,y:.390625},{x:.984375,y:.390625},{x:.015625,y:.421875},{x:.015625,y:.421875},{x:.046875,y:.421875},{x:.046875,y:.421875},{x:.078125,y:.421875},{x:.078125,y:.421875},{x:.109375,y:.421875},{x:.109375,y:.421875},{x:.140625,y:.421875},{x:.140625,y:.421875},{x:.171875,y:.421875},{x:.171875,y:.421875},{x:.203125,y:.421875},{x:.203125,y:.421875},{x:.234375,y:.421875},{x:.234375,y:.421875},{x:.265625,y:.421875},{x:.265625,y:.421875},{x:.296875,y:.421875},{x:.296875,y:.421875},{x:.328125,y:.421875},{x:.328125,y:.421875},{x:.359375,y:.421875},{x:.359375,y:.421875},{x:.390625,y:.421875},{x:.390625,y:.421875},{x:.421875,y:.421875},{x:.421875,y:.421875},{x:.453125,y:.421875},{x:.453125,y:.421875},{x:.484375,y:.421875},{x:.484375,y:.421875},{x:.515625,y:.421875},{x:.515625,y:.421875},{x:.546875,y:.421875},{x:.546875,y:.421875},{x:.578125,y:.421875},{x:.578125,y:.421875},{x:.609375,y:.421875},{x:.609375,y:.421875},{x:.640625,y:.421875},{x:.640625,y:.421875},{x:.671875,y:.421875},{x:.671875,y:.421875},{x:.703125,y:.421875},{x:.703125,y:.421875},{x:.734375,y:.421875},{x:.734375,y:.421875},{x:.765625,y:.421875},{x:.765625,y:.421875},{x:.796875,y:.421875},{x:.796875,y:.421875},{x:.828125,y:.421875},{x:.828125,y:.421875},{x:.859375,y:.421875},{x:.859375,y:.421875},{x:.890625,y:.421875},{x:.890625,y:.421875},{x:.921875,y:.421875},{x:.921875,y:.421875},{x:.953125,y:.421875},{x:.953125,y:.421875},{x:.984375,y:.421875},{x:.984375,y:.421875},{x:.015625,y:.453125},{x:.015625,y:.453125},{x:.046875,y:.453125},{x:.046875,y:.453125},{x:.078125,y:.453125},{x:.078125,y:.453125},{x:.109375,y:.453125},{x:.109375,y:.453125},{x:.140625,y:.453125},{x:.140625,y:.453125},{x:.171875,y:.453125},{x:.171875,y:.453125},{x:.203125,y:.453125},{x:.203125,y:.453125},{x:.234375,y:.453125},{x:.234375,y:.453125},{x:.265625,y:.453125},{x:.265625,y:.453125},{x:.296875,y:.453125},{x:.296875,y:.453125},{x:.328125,y:.453125},{x:.328125,y:.453125},{x:.359375,y:.453125},{x:.359375,y:.453125},{x:.390625,y:.453125},{x:.390625,y:.453125},{x:.421875,y:.453125},{x:.421875,y:.453125},{x:.453125,y:.453125},{x:.453125,y:.453125},{x:.484375,y:.453125},{x:.484375,y:.453125},{x:.515625,y:.453125},{x:.515625,y:.453125},{x:.546875,y:.453125},{x:.546875,y:.453125},{x:.578125,y:.453125},{x:.578125,y:.453125},{x:.609375,y:.453125},{x:.609375,y:.453125},{x:.640625,y:.453125},{x:.640625,y:.453125},{x:.671875,y:.453125},{x:.671875,y:.453125},{x:.703125,y:.453125},{x:.703125,y:.453125},{x:.734375,y:.453125},{x:.734375,y:.453125},{x:.765625,y:.453125},{x:.765625,y:.453125},{x:.796875,y:.453125},{x:.796875,y:.453125},{x:.828125,y:.453125},{x:.828125,y:.453125},{x:.859375,y:.453125},{x:.859375,y:.453125},{x:.890625,y:.453125},{x:.890625,y:.453125},{x:.921875,y:.453125},{x:.921875,y:.453125},{x:.953125,y:.453125},{x:.953125,y:.453125},{x:.984375,y:.453125},{x:.984375,y:.453125},{x:.015625,y:.484375},{x:.015625,y:.484375},{x:.046875,y:.484375},{x:.046875,y:.484375},{x:.078125,y:.484375},{x:.078125,y:.484375},{x:.109375,y:.484375},{x:.109375,y:.484375},{x:.140625,y:.484375},{x:.140625,y:.484375},{x:.171875,y:.484375},{x:.171875,y:.484375},{x:.203125,y:.484375},{x:.203125,y:.484375},{x:.234375,y:.484375},{x:.234375,y:.484375},{x:.265625,y:.484375},{x:.265625,y:.484375},{x:.296875,y:.484375},{x:.296875,y:.484375},{x:.328125,y:.484375},{x:.328125,y:.484375},{x:.359375,y:.484375},{x:.359375,y:.484375},{x:.390625,y:.484375},{x:.390625,y:.484375},{x:.421875,y:.484375},{x:.421875,y:.484375},{x:.453125,y:.484375},{x:.453125,y:.484375},{x:.484375,y:.484375},{x:.484375,y:.484375},{x:.515625,y:.484375},{x:.515625,y:.484375},{x:.546875,y:.484375},{x:.546875,y:.484375},{x:.578125,y:.484375},{x:.578125,y:.484375},{x:.609375,y:.484375},{x:.609375,y:.484375},{x:.640625,y:.484375},{x:.640625,y:.484375},{x:.671875,y:.484375},{x:.671875,y:.484375},{x:.703125,y:.484375},{x:.703125,y:.484375},{x:.734375,y:.484375},{x:.734375,y:.484375},{x:.765625,y:.484375},{x:.765625,y:.484375},{x:.796875,y:.484375},{x:.796875,y:.484375},{x:.828125,y:.484375},{x:.828125,y:.484375},{x:.859375,y:.484375},{x:.859375,y:.484375},{x:.890625,y:.484375},{x:.890625,y:.484375},{x:.921875,y:.484375},{x:.921875,y:.484375},{x:.953125,y:.484375},{x:.953125,y:.484375},{x:.984375,y:.484375},{x:.984375,y:.484375},{x:.015625,y:.515625},{x:.015625,y:.515625},{x:.046875,y:.515625},{x:.046875,y:.515625},{x:.078125,y:.515625},{x:.078125,y:.515625},{x:.109375,y:.515625},{x:.109375,y:.515625},{x:.140625,y:.515625},{x:.140625,y:.515625},{x:.171875,y:.515625},{x:.171875,y:.515625},{x:.203125,y:.515625},{x:.203125,y:.515625},{x:.234375,y:.515625},{x:.234375,y:.515625},{x:.265625,y:.515625},{x:.265625,y:.515625},{x:.296875,y:.515625},{x:.296875,y:.515625},{x:.328125,y:.515625},{x:.328125,y:.515625},{x:.359375,y:.515625},{x:.359375,y:.515625},{x:.390625,y:.515625},{x:.390625,y:.515625},{x:.421875,y:.515625},{x:.421875,y:.515625},{x:.453125,y:.515625},{x:.453125,y:.515625},{x:.484375,y:.515625},{x:.484375,y:.515625},{x:.515625,y:.515625},{x:.515625,y:.515625},{x:.546875,y:.515625},{x:.546875,y:.515625},{x:.578125,y:.515625},{x:.578125,y:.515625},{x:.609375,y:.515625},{x:.609375,y:.515625},{x:.640625,y:.515625},{x:.640625,y:.515625},{x:.671875,y:.515625},{x:.671875,y:.515625},{x:.703125,y:.515625},{x:.703125,y:.515625},{x:.734375,y:.515625},{x:.734375,y:.515625},{x:.765625,y:.515625},{x:.765625,y:.515625},{x:.796875,y:.515625},{x:.796875,y:.515625},{x:.828125,y:.515625},{x:.828125,y:.515625},{x:.859375,y:.515625},{x:.859375,y:.515625},{x:.890625,y:.515625},{x:.890625,y:.515625},{x:.921875,y:.515625},{x:.921875,y:.515625},{x:.953125,y:.515625},{x:.953125,y:.515625},{x:.984375,y:.515625},{x:.984375,y:.515625},{x:.015625,y:.546875},{x:.015625,y:.546875},{x:.046875,y:.546875},{x:.046875,y:.546875},{x:.078125,y:.546875},{x:.078125,y:.546875},{x:.109375,y:.546875},{x:.109375,y:.546875},{x:.140625,y:.546875},{x:.140625,y:.546875},{x:.171875,y:.546875},{x:.171875,y:.546875},{x:.203125,y:.546875},{x:.203125,y:.546875},{x:.234375,y:.546875},{x:.234375,y:.546875},{x:.265625,y:.546875},{x:.265625,y:.546875},{x:.296875,y:.546875},{x:.296875,y:.546875},{x:.328125,y:.546875},{x:.328125,y:.546875},{x:.359375,y:.546875},{x:.359375,y:.546875},{x:.390625,y:.546875},{x:.390625,y:.546875},{x:.421875,y:.546875},{x:.421875,y:.546875},{x:.453125,y:.546875},{x:.453125,y:.546875},{x:.484375,y:.546875},{x:.484375,y:.546875},{x:.515625,y:.546875},{x:.515625,y:.546875},{x:.546875,y:.546875},{x:.546875,y:.546875},{x:.578125,y:.546875},{x:.578125,y:.546875},{x:.609375,y:.546875},{x:.609375,y:.546875},{x:.640625,y:.546875},{x:.640625,y:.546875},{x:.671875,y:.546875},{x:.671875,y:.546875},{x:.703125,y:.546875},{x:.703125,y:.546875},{x:.734375,y:.546875},{x:.734375,y:.546875},{x:.765625,y:.546875},{x:.765625,y:.546875},{x:.796875,y:.546875},{x:.796875,y:.546875},{x:.828125,y:.546875},{x:.828125,y:.546875},{x:.859375,y:.546875},{x:.859375,y:.546875},{x:.890625,y:.546875},{x:.890625,y:.546875},{x:.921875,y:.546875},{x:.921875,y:.546875},{x:.953125,y:.546875},{x:.953125,y:.546875},{x:.984375,y:.546875},{x:.984375,y:.546875},{x:.015625,y:.578125},{x:.015625,y:.578125},{x:.046875,y:.578125},{x:.046875,y:.578125},{x:.078125,y:.578125},{x:.078125,y:.578125},{x:.109375,y:.578125},{x:.109375,y:.578125},{x:.140625,y:.578125},{x:.140625,y:.578125},{x:.171875,y:.578125},{x:.171875,y:.578125},{x:.203125,y:.578125},{x:.203125,y:.578125},{x:.234375,y:.578125},{x:.234375,y:.578125},{x:.265625,y:.578125},{x:.265625,y:.578125},{x:.296875,y:.578125},{x:.296875,y:.578125},{x:.328125,y:.578125},{x:.328125,y:.578125},{x:.359375,y:.578125},{x:.359375,y:.578125},{x:.390625,y:.578125},{x:.390625,y:.578125},{x:.421875,y:.578125},{x:.421875,y:.578125},{x:.453125,y:.578125},{x:.453125,y:.578125},{x:.484375,y:.578125},{x:.484375,y:.578125},{x:.515625,y:.578125},{x:.515625,y:.578125},{x:.546875,y:.578125},{x:.546875,y:.578125},{x:.578125,y:.578125},{x:.578125,y:.578125},{x:.609375,y:.578125},{x:.609375,y:.578125},{x:.640625,y:.578125},{x:.640625,y:.578125},{x:.671875,y:.578125},{x:.671875,y:.578125},{x:.703125,y:.578125},{x:.703125,y:.578125},{x:.734375,y:.578125},{x:.734375,y:.578125},{x:.765625,y:.578125},{x:.765625,y:.578125},{x:.796875,y:.578125},{x:.796875,y:.578125},{x:.828125,y:.578125},{x:.828125,y:.578125},{x:.859375,y:.578125},{x:.859375,y:.578125},{x:.890625,y:.578125},{x:.890625,y:.578125},{x:.921875,y:.578125},{x:.921875,y:.578125},{x:.953125,y:.578125},{x:.953125,y:.578125},{x:.984375,y:.578125},{x:.984375,y:.578125},{x:.015625,y:.609375},{x:.015625,y:.609375},{x:.046875,y:.609375},{x:.046875,y:.609375},{x:.078125,y:.609375},{x:.078125,y:.609375},{x:.109375,y:.609375},{x:.109375,y:.609375},{x:.140625,y:.609375},{x:.140625,y:.609375},{x:.171875,y:.609375},{x:.171875,y:.609375},{x:.203125,y:.609375},{x:.203125,y:.609375},{x:.234375,y:.609375},{x:.234375,y:.609375},{x:.265625,y:.609375},{x:.265625,y:.609375},{x:.296875,y:.609375},{x:.296875,y:.609375},{x:.328125,y:.609375},{x:.328125,y:.609375},{x:.359375,y:.609375},{x:.359375,y:.609375},{x:.390625,y:.609375},{x:.390625,y:.609375},{x:.421875,y:.609375},{x:.421875,y:.609375},{x:.453125,y:.609375},{x:.453125,y:.609375},{x:.484375,y:.609375},{x:.484375,y:.609375},{x:.515625,y:.609375},{x:.515625,y:.609375},{x:.546875,y:.609375},{x:.546875,y:.609375},{x:.578125,y:.609375},{x:.578125,y:.609375},{x:.609375,y:.609375},{x:.609375,y:.609375},{x:.640625,y:.609375},{x:.640625,y:.609375},{x:.671875,y:.609375},{x:.671875,y:.609375},{x:.703125,y:.609375},{x:.703125,y:.609375},{x:.734375,y:.609375},{x:.734375,y:.609375},{x:.765625,y:.609375},{x:.765625,y:.609375},{x:.796875,y:.609375},{x:.796875,y:.609375},{x:.828125,y:.609375},{x:.828125,y:.609375},{x:.859375,y:.609375},{x:.859375,y:.609375},{x:.890625,y:.609375},{x:.890625,y:.609375},{x:.921875,y:.609375},{x:.921875,y:.609375},{x:.953125,y:.609375},{x:.953125,y:.609375},{x:.984375,y:.609375},{x:.984375,y:.609375},{x:.015625,y:.640625},{x:.015625,y:.640625},{x:.046875,y:.640625},{x:.046875,y:.640625},{x:.078125,y:.640625},{x:.078125,y:.640625},{x:.109375,y:.640625},{x:.109375,y:.640625},{x:.140625,y:.640625},{x:.140625,y:.640625},{x:.171875,y:.640625},{x:.171875,y:.640625},{x:.203125,y:.640625},{x:.203125,y:.640625},{x:.234375,y:.640625},{x:.234375,y:.640625},{x:.265625,y:.640625},{x:.265625,y:.640625},{x:.296875,y:.640625},{x:.296875,y:.640625},{x:.328125,y:.640625},{x:.328125,y:.640625},{x:.359375,y:.640625},{x:.359375,y:.640625},{x:.390625,y:.640625},{x:.390625,y:.640625},{x:.421875,y:.640625},{x:.421875,y:.640625},{x:.453125,y:.640625},{x:.453125,y:.640625},{x:.484375,y:.640625},{x:.484375,y:.640625},{x:.515625,y:.640625},{x:.515625,y:.640625},{x:.546875,y:.640625},{x:.546875,y:.640625},{x:.578125,y:.640625},{x:.578125,y:.640625},{x:.609375,y:.640625},{x:.609375,y:.640625},{x:.640625,y:.640625},{x:.640625,y:.640625},{x:.671875,y:.640625},{x:.671875,y:.640625},{x:.703125,y:.640625},{x:.703125,y:.640625},{x:.734375,y:.640625},{x:.734375,y:.640625},{x:.765625,y:.640625},{x:.765625,y:.640625},{x:.796875,y:.640625},{x:.796875,y:.640625},{x:.828125,y:.640625},{x:.828125,y:.640625},{x:.859375,y:.640625},{x:.859375,y:.640625},{x:.890625,y:.640625},{x:.890625,y:.640625},{x:.921875,y:.640625},{x:.921875,y:.640625},{x:.953125,y:.640625},{x:.953125,y:.640625},{x:.984375,y:.640625},{x:.984375,y:.640625},{x:.015625,y:.671875},{x:.015625,y:.671875},{x:.046875,y:.671875},{x:.046875,y:.671875},{x:.078125,y:.671875},{x:.078125,y:.671875},{x:.109375,y:.671875},{x:.109375,y:.671875},{x:.140625,y:.671875},{x:.140625,y:.671875},{x:.171875,y:.671875},{x:.171875,y:.671875},{x:.203125,y:.671875},{x:.203125,y:.671875},{x:.234375,y:.671875},{x:.234375,y:.671875},{x:.265625,y:.671875},{x:.265625,y:.671875},{x:.296875,y:.671875},{x:.296875,y:.671875},{x:.328125,y:.671875},{x:.328125,y:.671875},{x:.359375,y:.671875},{x:.359375,y:.671875},{x:.390625,y:.671875},{x:.390625,y:.671875},{x:.421875,y:.671875},{x:.421875,y:.671875},{x:.453125,y:.671875},{x:.453125,y:.671875},{x:.484375,y:.671875},{x:.484375,y:.671875},{x:.515625,y:.671875},{x:.515625,y:.671875},{x:.546875,y:.671875},{x:.546875,y:.671875},{x:.578125,y:.671875},{x:.578125,y:.671875},{x:.609375,y:.671875},{x:.609375,y:.671875},{x:.640625,y:.671875},{x:.640625,y:.671875},{x:.671875,y:.671875},{x:.671875,y:.671875},{x:.703125,y:.671875},{x:.703125,y:.671875},{x:.734375,y:.671875},{x:.734375,y:.671875},{x:.765625,y:.671875},{x:.765625,y:.671875},{x:.796875,y:.671875},{x:.796875,y:.671875},{x:.828125,y:.671875},{x:.828125,y:.671875},{x:.859375,y:.671875},{x:.859375,y:.671875},{x:.890625,y:.671875},{x:.890625,y:.671875},{x:.921875,y:.671875},{x:.921875,y:.671875},{x:.953125,y:.671875},{x:.953125,y:.671875},{x:.984375,y:.671875},{x:.984375,y:.671875},{x:.015625,y:.703125},{x:.015625,y:.703125},{x:.046875,y:.703125},{x:.046875,y:.703125},{x:.078125,y:.703125},{x:.078125,y:.703125},{x:.109375,y:.703125},{x:.109375,y:.703125},{x:.140625,y:.703125},{x:.140625,y:.703125},{x:.171875,y:.703125},{x:.171875,y:.703125},{x:.203125,y:.703125},{x:.203125,y:.703125},{x:.234375,y:.703125},{x:.234375,y:.703125},{x:.265625,y:.703125},{x:.265625,y:.703125},{x:.296875,y:.703125},{x:.296875,y:.703125},{x:.328125,y:.703125},{x:.328125,y:.703125},{x:.359375,y:.703125},{x:.359375,y:.703125},{x:.390625,y:.703125},{x:.390625,y:.703125},{x:.421875,y:.703125},{x:.421875,y:.703125},{x:.453125,y:.703125},{x:.453125,y:.703125},{x:.484375,y:.703125},{x:.484375,y:.703125},{x:.515625,y:.703125},{x:.515625,y:.703125},{x:.546875,y:.703125},{x:.546875,y:.703125},{x:.578125,y:.703125},{x:.578125,y:.703125},{x:.609375,y:.703125},{x:.609375,y:.703125},{x:.640625,y:.703125},{x:.640625,y:.703125},{x:.671875,y:.703125},{x:.671875,y:.703125},{x:.703125,y:.703125},{x:.703125,y:.703125},{x:.734375,y:.703125},{x:.734375,y:.703125},{x:.765625,y:.703125},{x:.765625,y:.703125},{x:.796875,y:.703125},{x:.796875,y:.703125},{x:.828125,y:.703125},{x:.828125,y:.703125},{x:.859375,y:.703125},{x:.859375,y:.703125},{x:.890625,y:.703125},{x:.890625,y:.703125},{x:.921875,y:.703125},{x:.921875,y:.703125},{x:.953125,y:.703125},{x:.953125,y:.703125},{x:.984375,y:.703125},{x:.984375,y:.703125},{x:.015625,y:.734375},{x:.015625,y:.734375},{x:.046875,y:.734375},{x:.046875,y:.734375},{x:.078125,y:.734375},{x:.078125,y:.734375},{x:.109375,y:.734375},{x:.109375,y:.734375},{x:.140625,y:.734375},{x:.140625,y:.734375},{x:.171875,y:.734375},{x:.171875,y:.734375},{x:.203125,y:.734375},{x:.203125,y:.734375},{x:.234375,y:.734375},{x:.234375,y:.734375},{x:.265625,y:.734375},{x:.265625,y:.734375},{x:.296875,y:.734375},{x:.296875,y:.734375},{x:.328125,y:.734375},{x:.328125,y:.734375},{x:.359375,y:.734375},{x:.359375,y:.734375},{x:.390625,y:.734375},{x:.390625,y:.734375},{x:.421875,y:.734375},{x:.421875,y:.734375},{x:.453125,y:.734375},{x:.453125,y:.734375},{x:.484375,y:.734375},{x:.484375,y:.734375},{x:.515625,y:.734375},{x:.515625,y:.734375},{x:.546875,y:.734375},{x:.546875,y:.734375},{x:.578125,y:.734375},{x:.578125,y:.734375},{x:.609375,y:.734375},{x:.609375,y:.734375},{x:.640625,y:.734375},{x:.640625,y:.734375},{x:.671875,y:.734375},{x:.671875,y:.734375},{x:.703125,y:.734375},{x:.703125,y:.734375},{x:.734375,y:.734375},{x:.734375,y:.734375},{x:.765625,y:.734375},{x:.765625,y:.734375},{x:.796875,y:.734375},{x:.796875,y:.734375},{x:.828125,y:.734375},{x:.828125,y:.734375},{x:.859375,y:.734375},{x:.859375,y:.734375},{x:.890625,y:.734375},{x:.890625,y:.734375},{x:.921875,y:.734375},{x:.921875,y:.734375},{x:.953125,y:.734375},{x:.953125,y:.734375},{x:.984375,y:.734375},{x:.984375,y:.734375},{x:.015625,y:.765625},{x:.015625,y:.765625},{x:.046875,y:.765625},{x:.046875,y:.765625},{x:.078125,y:.765625},{x:.078125,y:.765625},{x:.109375,y:.765625},{x:.109375,y:.765625},{x:.140625,y:.765625},{x:.140625,y:.765625},{x:.171875,y:.765625},{x:.171875,y:.765625},{x:.203125,y:.765625},{x:.203125,y:.765625},{x:.234375,y:.765625},{x:.234375,y:.765625},{x:.265625,y:.765625},{x:.265625,y:.765625},{x:.296875,y:.765625},{x:.296875,y:.765625},{x:.328125,y:.765625},{x:.328125,y:.765625},{x:.359375,y:.765625},{x:.359375,y:.765625},{x:.390625,y:.765625},{x:.390625,y:.765625},{x:.421875,y:.765625},{x:.421875,y:.765625},{x:.453125,y:.765625},{x:.453125,y:.765625},{x:.484375,y:.765625},{x:.484375,y:.765625},{x:.515625,y:.765625},{x:.515625,y:.765625},{x:.546875,y:.765625},{x:.546875,y:.765625},{x:.578125,y:.765625},{x:.578125,y:.765625},{x:.609375,y:.765625},{x:.609375,y:.765625},{x:.640625,y:.765625},{x:.640625,y:.765625},{x:.671875,y:.765625},{x:.671875,y:.765625},{x:.703125,y:.765625},{x:.703125,y:.765625},{x:.734375,y:.765625},{x:.734375,y:.765625},{x:.765625,y:.765625},{x:.765625,y:.765625},{x:.796875,y:.765625},{x:.796875,y:.765625},{x:.828125,y:.765625},{x:.828125,y:.765625},{x:.859375,y:.765625},{x:.859375,y:.765625},{x:.890625,y:.765625},{x:.890625,y:.765625},{x:.921875,y:.765625},{x:.921875,y:.765625},{x:.953125,y:.765625},{x:.953125,y:.765625},{x:.984375,y:.765625},{x:.984375,y:.765625},{x:.015625,y:.796875},{x:.015625,y:.796875},{x:.046875,y:.796875},{x:.046875,y:.796875},{x:.078125,y:.796875},{x:.078125,y:.796875},{x:.109375,y:.796875},{x:.109375,y:.796875},{x:.140625,y:.796875},{x:.140625,y:.796875},{x:.171875,y:.796875},{x:.171875,y:.796875},{x:.203125,y:.796875},{x:.203125,y:.796875},{x:.234375,y:.796875},{x:.234375,y:.796875},{x:.265625,y:.796875},{x:.265625,y:.796875},{x:.296875,y:.796875},{x:.296875,y:.796875},{x:.328125,y:.796875},{x:.328125,y:.796875},{x:.359375,y:.796875},{x:.359375,y:.796875},{x:.390625,y:.796875},{x:.390625,y:.796875},{x:.421875,y:.796875},{x:.421875,y:.796875},{x:.453125,y:.796875},{x:.453125,y:.796875},{x:.484375,y:.796875},{x:.484375,y:.796875},{x:.515625,y:.796875},{x:.515625,y:.796875},{x:.546875,y:.796875},{x:.546875,y:.796875},{x:.578125,y:.796875},{x:.578125,y:.796875},{x:.609375,y:.796875},{x:.609375,y:.796875},{x:.640625,y:.796875},{x:.640625,y:.796875},{x:.671875,y:.796875},{x:.671875,y:.796875},{x:.703125,y:.796875},{x:.703125,y:.796875},{x:.734375,y:.796875},{x:.734375,y:.796875},{x:.765625,y:.796875},{x:.765625,y:.796875},{x:.796875,y:.796875},{x:.796875,y:.796875},{x:.828125,y:.796875},{x:.828125,y:.796875},{x:.859375,y:.796875},{x:.859375,y:.796875},{x:.890625,y:.796875},{x:.890625,y:.796875},{x:.921875,y:.796875},{x:.921875,y:.796875},{x:.953125,y:.796875},{x:.953125,y:.796875},{x:.984375,y:.796875},{x:.984375,y:.796875},{x:.015625,y:.828125},{x:.015625,y:.828125},{x:.046875,y:.828125},{x:.046875,y:.828125},{x:.078125,y:.828125},{x:.078125,y:.828125},{x:.109375,y:.828125},{x:.109375,y:.828125},{x:.140625,y:.828125},{x:.140625,y:.828125},{x:.171875,y:.828125},{x:.171875,y:.828125},{x:.203125,y:.828125},{x:.203125,y:.828125},{x:.234375,y:.828125},{x:.234375,y:.828125},{x:.265625,y:.828125},{x:.265625,y:.828125},{x:.296875,y:.828125},{x:.296875,y:.828125},{x:.328125,y:.828125},{x:.328125,y:.828125},{x:.359375,y:.828125},{x:.359375,y:.828125},{x:.390625,y:.828125},{x:.390625,y:.828125},{x:.421875,y:.828125},{x:.421875,y:.828125},{x:.453125,y:.828125},{x:.453125,y:.828125},{x:.484375,y:.828125},{x:.484375,y:.828125},{x:.515625,y:.828125},{x:.515625,y:.828125},{x:.546875,y:.828125},{x:.546875,y:.828125},{x:.578125,y:.828125},{x:.578125,y:.828125},{x:.609375,y:.828125},{x:.609375,y:.828125},{x:.640625,y:.828125},{x:.640625,y:.828125},{x:.671875,y:.828125},{x:.671875,y:.828125},{x:.703125,y:.828125},{x:.703125,y:.828125},{x:.734375,y:.828125},{x:.734375,y:.828125},{x:.765625,y:.828125},{x:.765625,y:.828125},{x:.796875,y:.828125},{x:.796875,y:.828125},{x:.828125,y:.828125},{x:.828125,y:.828125},{x:.859375,y:.828125},{x:.859375,y:.828125},{x:.890625,y:.828125},{x:.890625,y:.828125},{x:.921875,y:.828125},{x:.921875,y:.828125},{x:.953125,y:.828125},{x:.953125,y:.828125},{x:.984375,y:.828125},{x:.984375,y:.828125},{x:.015625,y:.859375},{x:.015625,y:.859375},{x:.046875,y:.859375},{x:.046875,y:.859375},{x:.078125,y:.859375},{x:.078125,y:.859375},{x:.109375,y:.859375},{x:.109375,y:.859375},{x:.140625,y:.859375},{x:.140625,y:.859375},{x:.171875,y:.859375},{x:.171875,y:.859375},{x:.203125,y:.859375},{x:.203125,y:.859375},{x:.234375,y:.859375},{x:.234375,y:.859375},{x:.265625,y:.859375},{x:.265625,y:.859375},{x:.296875,y:.859375},{x:.296875,y:.859375},{x:.328125,y:.859375},{x:.328125,y:.859375},{x:.359375,y:.859375},{x:.359375,y:.859375},{x:.390625,y:.859375},{x:.390625,y:.859375},{x:.421875,y:.859375},{x:.421875,y:.859375},{x:.453125,y:.859375},{x:.453125,y:.859375},{x:.484375,y:.859375},{x:.484375,y:.859375},{x:.515625,y:.859375},{x:.515625,y:.859375},{x:.546875,y:.859375},{x:.546875,y:.859375},{x:.578125,y:.859375},{x:.578125,y:.859375},{x:.609375,y:.859375},{x:.609375,y:.859375},{x:.640625,y:.859375},{x:.640625,y:.859375},{x:.671875,y:.859375},{x:.671875,y:.859375},{x:.703125,y:.859375},{x:.703125,y:.859375},{x:.734375,y:.859375},{x:.734375,y:.859375},{x:.765625,y:.859375},{x:.765625,y:.859375},{x:.796875,y:.859375},{x:.796875,y:.859375},{x:.828125,y:.859375},{x:.828125,y:.859375},{x:.859375,y:.859375},{x:.859375,y:.859375},{x:.890625,y:.859375},{x:.890625,y:.859375},{x:.921875,y:.859375},{x:.921875,y:.859375},{x:.953125,y:.859375},{x:.953125,y:.859375},{x:.984375,y:.859375},{x:.984375,y:.859375},{x:.015625,y:.890625},{x:.015625,y:.890625},{x:.046875,y:.890625},{x:.046875,y:.890625},{x:.078125,y:.890625},{x:.078125,y:.890625},{x:.109375,y:.890625},{x:.109375,y:.890625},{x:.140625,y:.890625},{x:.140625,y:.890625},{x:.171875,y:.890625},{x:.171875,y:.890625},{x:.203125,y:.890625},{x:.203125,y:.890625},{x:.234375,y:.890625},{x:.234375,y:.890625},{x:.265625,y:.890625},{x:.265625,y:.890625},{x:.296875,y:.890625},{x:.296875,y:.890625},{x:.328125,y:.890625},{x:.328125,y:.890625},{x:.359375,y:.890625},{x:.359375,y:.890625},{x:.390625,y:.890625},{x:.390625,y:.890625},{x:.421875,y:.890625},{x:.421875,y:.890625},{x:.453125,y:.890625},{x:.453125,y:.890625},{x:.484375,y:.890625},{x:.484375,y:.890625},{x:.515625,y:.890625},{x:.515625,y:.890625},{x:.546875,y:.890625},{x:.546875,y:.890625},{x:.578125,y:.890625},{x:.578125,y:.890625},{x:.609375,y:.890625},{x:.609375,y:.890625},{x:.640625,y:.890625},{x:.640625,y:.890625},{x:.671875,y:.890625},{x:.671875,y:.890625},{x:.703125,y:.890625},{x:.703125,y:.890625},{x:.734375,y:.890625},{x:.734375,y:.890625},{x:.765625,y:.890625},{x:.765625,y:.890625},{x:.796875,y:.890625},{x:.796875,y:.890625},{x:.828125,y:.890625},{x:.828125,y:.890625},{x:.859375,y:.890625},{x:.859375,y:.890625},{x:.890625,y:.890625},{x:.890625,y:.890625},{x:.921875,y:.890625},{x:.921875,y:.890625},{x:.953125,y:.890625},{x:.953125,y:.890625},{x:.984375,y:.890625},{x:.984375,y:.890625},{x:.015625,y:.921875},{x:.015625,y:.921875},{x:.046875,y:.921875},{x:.046875,y:.921875},{x:.078125,y:.921875},{x:.078125,y:.921875},{x:.109375,y:.921875},{x:.109375,y:.921875},{x:.140625,y:.921875},{x:.140625,y:.921875},{x:.171875,y:.921875},{x:.171875,y:.921875},{x:.203125,y:.921875},{x:.203125,y:.921875},{x:.234375,y:.921875},{x:.234375,y:.921875},{x:.265625,y:.921875},{x:.265625,y:.921875},{x:.296875,y:.921875},{x:.296875,y:.921875},{x:.328125,y:.921875},{x:.328125,y:.921875},{x:.359375,y:.921875},{x:.359375,y:.921875},{x:.390625,y:.921875},{x:.390625,y:.921875},{x:.421875,y:.921875},{x:.421875,y:.921875},{x:.453125,y:.921875},{x:.453125,y:.921875},{x:.484375,y:.921875},{x:.484375,y:.921875},{x:.515625,y:.921875},{x:.515625,y:.921875},{x:.546875,y:.921875},{x:.546875,y:.921875},{x:.578125,y:.921875},{x:.578125,y:.921875},{x:.609375,y:.921875},{x:.609375,y:.921875},{x:.640625,y:.921875},{x:.640625,y:.921875},{x:.671875,y:.921875},{x:.671875,y:.921875},{x:.703125,y:.921875},{x:.703125,y:.921875},{x:.734375,y:.921875},{x:.734375,y:.921875},{x:.765625,y:.921875},{x:.765625,y:.921875},{x:.796875,y:.921875},{x:.796875,y:.921875},{x:.828125,y:.921875},{x:.828125,y:.921875},{x:.859375,y:.921875},{x:.859375,y:.921875},{x:.890625,y:.921875},{x:.890625,y:.921875},{x:.921875,y:.921875},{x:.921875,y:.921875},{x:.953125,y:.921875},{x:.953125,y:.921875},{x:.984375,y:.921875},{x:.984375,y:.921875},{x:.015625,y:.953125},{x:.015625,y:.953125},{x:.046875,y:.953125},{x:.046875,y:.953125},{x:.078125,y:.953125},{x:.078125,y:.953125},{x:.109375,y:.953125},{x:.109375,y:.953125},{x:.140625,y:.953125},{x:.140625,y:.953125},{x:.171875,y:.953125},{x:.171875,y:.953125},{x:.203125,y:.953125},{x:.203125,y:.953125},{x:.234375,y:.953125},{x:.234375,y:.953125},{x:.265625,y:.953125},{x:.265625,y:.953125},{x:.296875,y:.953125},{x:.296875,y:.953125},{x:.328125,y:.953125},{x:.328125,y:.953125},{x:.359375,y:.953125},{x:.359375,y:.953125},{x:.390625,y:.953125},{x:.390625,y:.953125},{x:.421875,y:.953125},{x:.421875,y:.953125},{x:.453125,y:.953125},{x:.453125,y:.953125},{x:.484375,y:.953125},{x:.484375,y:.953125},{x:.515625,y:.953125},{x:.515625,y:.953125},{x:.546875,y:.953125},{x:.546875,y:.953125},{x:.578125,y:.953125},{x:.578125,y:.953125},{x:.609375,y:.953125},{x:.609375,y:.953125},{x:.640625,y:.953125},{x:.640625,y:.953125},{x:.671875,y:.953125},{x:.671875,y:.953125},{x:.703125,y:.953125},{x:.703125,y:.953125},{x:.734375,y:.953125},{x:.734375,y:.953125},{x:.765625,y:.953125},{x:.765625,y:.953125},{x:.796875,y:.953125},{x:.796875,y:.953125},{x:.828125,y:.953125},{x:.828125,y:.953125},{x:.859375,y:.953125},{x:.859375,y:.953125},{x:.890625,y:.953125},{x:.890625,y:.953125},{x:.921875,y:.953125},{x:.921875,y:.953125},{x:.953125,y:.953125},{x:.953125,y:.953125},{x:.984375,y:.953125},{x:.984375,y:.953125},{x:.015625,y:.984375},{x:.015625,y:.984375},{x:.046875,y:.984375},{x:.046875,y:.984375},{x:.078125,y:.984375},{x:.078125,y:.984375},{x:.109375,y:.984375},{x:.109375,y:.984375},{x:.140625,y:.984375},{x:.140625,y:.984375},{x:.171875,y:.984375},{x:.171875,y:.984375},{x:.203125,y:.984375},{x:.203125,y:.984375},{x:.234375,y:.984375},{x:.234375,y:.984375},{x:.265625,y:.984375},{x:.265625,y:.984375},{x:.296875,y:.984375},{x:.296875,y:.984375},{x:.328125,y:.984375},{x:.328125,y:.984375},{x:.359375,y:.984375},{x:.359375,y:.984375},{x:.390625,y:.984375},{x:.390625,y:.984375},{x:.421875,y:.984375},{x:.421875,y:.984375},{x:.453125,y:.984375},{x:.453125,y:.984375},{x:.484375,y:.984375},{x:.484375,y:.984375},{x:.515625,y:.984375},{x:.515625,y:.984375},{x:.546875,y:.984375},{x:.546875,y:.984375},{x:.578125,y:.984375},{x:.578125,y:.984375},{x:.609375,y:.984375},{x:.609375,y:.984375},{x:.640625,y:.984375},{x:.640625,y:.984375},{x:.671875,y:.984375},{x:.671875,y:.984375},{x:.703125,y:.984375},{x:.703125,y:.984375},{x:.734375,y:.984375},{x:.734375,y:.984375},{x:.765625,y:.984375},{x:.765625,y:.984375},{x:.796875,y:.984375},{x:.796875,y:.984375},{x:.828125,y:.984375},{x:.828125,y:.984375},{x:.859375,y:.984375},{x:.859375,y:.984375},{x:.890625,y:.984375},{x:.890625,y:.984375},{x:.921875,y:.984375},{x:.921875,y:.984375},{x:.953125,y:.984375},{x:.953125,y:.984375},{x:.984375,y:.984375},{x:.984375,y:.984375},{x:.03125,y:.03125},{x:.03125,y:.03125},{x:.09375,y:.03125},{x:.09375,y:.03125},{x:.15625,y:.03125},{x:.15625,y:.03125},{x:.21875,y:.03125},{x:.21875,y:.03125},{x:.28125,y:.03125},{x:.28125,y:.03125},{x:.34375,y:.03125},{x:.34375,y:.03125},{x:.40625,y:.03125},{x:.40625,y:.03125},{x:.46875,y:.03125},{x:.46875,y:.03125},{x:.53125,y:.03125},{x:.53125,y:.03125},{x:.59375,y:.03125},{x:.59375,y:.03125},{x:.65625,y:.03125},{x:.65625,y:.03125},{x:.71875,y:.03125},{x:.71875,y:.03125},{x:.78125,y:.03125},{x:.78125,y:.03125},{x:.84375,y:.03125},{x:.84375,y:.03125},{x:.90625,y:.03125},{x:.90625,y:.03125},{x:.96875,y:.03125},{x:.96875,y:.03125},{x:.03125,y:.09375},{x:.03125,y:.09375},{x:.09375,y:.09375},{x:.09375,y:.09375},{x:.15625,y:.09375},{x:.15625,y:.09375},{x:.21875,y:.09375},{x:.21875,y:.09375},{x:.28125,y:.09375},{x:.28125,y:.09375},{x:.34375,y:.09375},{x:.34375,y:.09375},{x:.40625,y:.09375},{x:.40625,y:.09375},{x:.46875,y:.09375},{x:.46875,y:.09375},{x:.53125,y:.09375},{x:.53125,y:.09375},{x:.59375,y:.09375},{x:.59375,y:.09375},{x:.65625,y:.09375},{x:.65625,y:.09375},{x:.71875,y:.09375},{x:.71875,y:.09375},{x:.78125,y:.09375},{x:.78125,y:.09375},{x:.84375,y:.09375},{x:.84375,y:.09375},{x:.90625,y:.09375},{x:.90625,y:.09375},{x:.96875,y:.09375},{x:.96875,y:.09375},{x:.03125,y:.15625},{x:.03125,y:.15625},{x:.09375,y:.15625},{x:.09375,y:.15625},{x:.15625,y:.15625},{x:.15625,y:.15625},{x:.21875,y:.15625},{x:.21875,y:.15625},{x:.28125,y:.15625},{x:.28125,y:.15625},{x:.34375,y:.15625},{x:.34375,y:.15625},{x:.40625,y:.15625},{x:.40625,y:.15625},{x:.46875,y:.15625},{x:.46875,y:.15625},{x:.53125,y:.15625},{x:.53125,y:.15625},{x:.59375,y:.15625},{x:.59375,y:.15625},{x:.65625,y:.15625},{x:.65625,y:.15625},{x:.71875,y:.15625},{x:.71875,y:.15625},{x:.78125,y:.15625},{x:.78125,y:.15625},{x:.84375,y:.15625},{x:.84375,y:.15625},{x:.90625,y:.15625},{x:.90625,y:.15625},{x:.96875,y:.15625},{x:.96875,y:.15625},{x:.03125,y:.21875},{x:.03125,y:.21875},{x:.09375,y:.21875},{x:.09375,y:.21875},{x:.15625,y:.21875},{x:.15625,y:.21875},{x:.21875,y:.21875},{x:.21875,y:.21875},{x:.28125,y:.21875},{x:.28125,y:.21875},{x:.34375,y:.21875},{x:.34375,y:.21875},{x:.40625,y:.21875},{x:.40625,y:.21875},{x:.46875,y:.21875},{x:.46875,y:.21875},{x:.53125,y:.21875},{x:.53125,y:.21875},{x:.59375,y:.21875},{x:.59375,y:.21875},{x:.65625,y:.21875},{x:.65625,y:.21875},{x:.71875,y:.21875},{x:.71875,y:.21875},{x:.78125,y:.21875},{x:.78125,y:.21875},{x:.84375,y:.21875},{x:.84375,y:.21875},{x:.90625,y:.21875},{x:.90625,y:.21875},{x:.96875,y:.21875},{x:.96875,y:.21875},{x:.03125,y:.28125},{x:.03125,y:.28125},{x:.09375,y:.28125},{x:.09375,y:.28125},{x:.15625,y:.28125},{x:.15625,y:.28125},{x:.21875,y:.28125},{x:.21875,y:.28125},{x:.28125,y:.28125},{x:.28125,y:.28125},{x:.34375,y:.28125},{x:.34375,y:.28125},{x:.40625,y:.28125},{x:.40625,y:.28125},{x:.46875,y:.28125},{x:.46875,y:.28125},{x:.53125,y:.28125},{x:.53125,y:.28125},{x:.59375,y:.28125},{x:.59375,y:.28125},{x:.65625,y:.28125},{x:.65625,y:.28125},{x:.71875,y:.28125},{x:.71875,y:.28125},{x:.78125,y:.28125},{x:.78125,y:.28125},{x:.84375,y:.28125},{x:.84375,y:.28125},{x:.90625,y:.28125},{x:.90625,y:.28125},{x:.96875,y:.28125},{x:.96875,y:.28125},{x:.03125,y:.34375},{x:.03125,y:.34375},{x:.09375,y:.34375},{x:.09375,y:.34375},{x:.15625,y:.34375},{x:.15625,y:.34375},{x:.21875,y:.34375},{x:.21875,y:.34375},{x:.28125,y:.34375},{x:.28125,y:.34375},{x:.34375,y:.34375},{x:.34375,y:.34375},{x:.40625,y:.34375},{x:.40625,y:.34375},{x:.46875,y:.34375},{x:.46875,y:.34375},{x:.53125,y:.34375},{x:.53125,y:.34375},{x:.59375,y:.34375},{x:.59375,y:.34375},{x:.65625,y:.34375},{x:.65625,y:.34375},{x:.71875,y:.34375},{x:.71875,y:.34375},{x:.78125,y:.34375},{x:.78125,y:.34375},{x:.84375,y:.34375},{x:.84375,y:.34375},{x:.90625,y:.34375},{x:.90625,y:.34375},{x:.96875,y:.34375},{x:.96875,y:.34375},{x:.03125,y:.40625},{x:.03125,y:.40625},{x:.09375,y:.40625},{x:.09375,y:.40625},{x:.15625,y:.40625},{x:.15625,y:.40625},{x:.21875,y:.40625},{x:.21875,y:.40625},{x:.28125,y:.40625},{x:.28125,y:.40625},{x:.34375,y:.40625},{x:.34375,y:.40625},{x:.40625,y:.40625},{x:.40625,y:.40625},{x:.46875,y:.40625},{x:.46875,y:.40625},{x:.53125,y:.40625},{x:.53125,y:.40625},{x:.59375,y:.40625},{x:.59375,y:.40625},{x:.65625,y:.40625},{x:.65625,y:.40625},{x:.71875,y:.40625},{x:.71875,y:.40625},{x:.78125,y:.40625},{x:.78125,y:.40625},{x:.84375,y:.40625},{x:.84375,y:.40625},{x:.90625,y:.40625},{x:.90625,y:.40625},{x:.96875,y:.40625},{x:.96875,y:.40625},{x:.03125,y:.46875},{x:.03125,y:.46875},{x:.09375,y:.46875},{x:.09375,y:.46875},{x:.15625,y:.46875},{x:.15625,y:.46875},{x:.21875,y:.46875},{x:.21875,y:.46875},{x:.28125,y:.46875},{x:.28125,y:.46875},{x:.34375,y:.46875},{x:.34375,y:.46875},{x:.40625,y:.46875},{x:.40625,y:.46875},{x:.46875,y:.46875},{x:.46875,y:.46875},{x:.53125,y:.46875},{x:.53125,y:.46875},{x:.59375,y:.46875},{x:.59375,y:.46875},{x:.65625,y:.46875},{x:.65625,y:.46875},{x:.71875,y:.46875},{x:.71875,y:.46875},{x:.78125,y:.46875},{x:.78125,y:.46875},{x:.84375,y:.46875},{x:.84375,y:.46875},{x:.90625,y:.46875},{x:.90625,y:.46875},{x:.96875,y:.46875},{x:.96875,y:.46875},{x:.03125,y:.53125},{x:.03125,y:.53125},{x:.09375,y:.53125},{x:.09375,y:.53125},{x:.15625,y:.53125},{x:.15625,y:.53125},{x:.21875,y:.53125},{x:.21875,y:.53125},{x:.28125,y:.53125},{x:.28125,y:.53125},{x:.34375,y:.53125},{x:.34375,y:.53125},{x:.40625,y:.53125},{x:.40625,y:.53125},{x:.46875,y:.53125},{x:.46875,y:.53125},{x:.53125,y:.53125},{x:.53125,y:.53125},{x:.59375,y:.53125},{x:.59375,y:.53125},{x:.65625,y:.53125},{x:.65625,y:.53125},{x:.71875,y:.53125},{x:.71875,y:.53125},{x:.78125,y:.53125},{x:.78125,y:.53125},{x:.84375,y:.53125},{x:.84375,y:.53125},{x:.90625,y:.53125},{x:.90625,y:.53125},{x:.96875,y:.53125},{x:.96875,y:.53125},{x:.03125,y:.59375},{x:.03125,y:.59375},{x:.09375,y:.59375},{x:.09375,y:.59375},{x:.15625,y:.59375},{x:.15625,y:.59375},{x:.21875,y:.59375},{x:.21875,y:.59375},{x:.28125,y:.59375},{x:.28125,y:.59375},{x:.34375,y:.59375},{x:.34375,y:.59375},{x:.40625,y:.59375},{x:.40625,y:.59375},{x:.46875,y:.59375},{x:.46875,y:.59375},{x:.53125,y:.59375},{x:.53125,y:.59375},{x:.59375,y:.59375},{x:.59375,y:.59375},{x:.65625,y:.59375},{x:.65625,y:.59375},{x:.71875,y:.59375},{x:.71875,y:.59375},{x:.78125,y:.59375},{x:.78125,y:.59375},{x:.84375,y:.59375},{x:.84375,y:.59375},{x:.90625,y:.59375},{x:.90625,y:.59375},{x:.96875,y:.59375},{x:.96875,y:.59375},{x:.03125,y:.65625},{x:.03125,y:.65625},{x:.09375,y:.65625},{x:.09375,y:.65625},{x:.15625,y:.65625},{x:.15625,y:.65625},{x:.21875,y:.65625},{x:.21875,y:.65625},{x:.28125,y:.65625},{x:.28125,y:.65625},{x:.34375,y:.65625},{x:.34375,y:.65625},{x:.40625,y:.65625},{x:.40625,y:.65625},{x:.46875,y:.65625},{x:.46875,y:.65625},{x:.53125,y:.65625},{x:.53125,y:.65625},{x:.59375,y:.65625},{x:.59375,y:.65625},{x:.65625,y:.65625},{x:.65625,y:.65625},{x:.71875,y:.65625},{x:.71875,y:.65625},{x:.78125,y:.65625},{x:.78125,y:.65625},{x:.84375,y:.65625},{x:.84375,y:.65625},{x:.90625,y:.65625},{x:.90625,y:.65625},{x:.96875,y:.65625},{x:.96875,y:.65625},{x:.03125,y:.71875},{x:.03125,y:.71875},{x:.09375,y:.71875},{x:.09375,y:.71875},{x:.15625,y:.71875},{x:.15625,y:.71875},{x:.21875,y:.71875},{x:.21875,y:.71875},{x:.28125,y:.71875},{x:.28125,y:.71875},{x:.34375,y:.71875},{x:.34375,y:.71875},{x:.40625,y:.71875},{x:.40625,y:.71875},{x:.46875,y:.71875},{x:.46875,y:.71875},{x:.53125,y:.71875},{x:.53125,y:.71875},{x:.59375,y:.71875},{x:.59375,y:.71875},{x:.65625,y:.71875},{x:.65625,y:.71875},{x:.71875,y:.71875},{x:.71875,y:.71875},{x:.78125,y:.71875},{x:.78125,y:.71875},{x:.84375,y:.71875},{x:.84375,y:.71875},{x:.90625,y:.71875},{x:.90625,y:.71875},{x:.96875,y:.71875},{x:.96875,y:.71875},{x:.03125,y:.78125},{x:.03125,y:.78125},{x:.09375,y:.78125},{x:.09375,y:.78125},{x:.15625,y:.78125},{x:.15625,y:.78125},{x:.21875,y:.78125},{x:.21875,y:.78125},{x:.28125,y:.78125},{x:.28125,y:.78125},{x:.34375,y:.78125},{x:.34375,y:.78125},{x:.40625,y:.78125},{x:.40625,y:.78125},{x:.46875,y:.78125},{x:.46875,y:.78125},{x:.53125,y:.78125},{x:.53125,y:.78125},{x:.59375,y:.78125},{x:.59375,y:.78125},{x:.65625,y:.78125},{x:.65625,y:.78125},{x:.71875,y:.78125},{x:.71875,y:.78125},{x:.78125,y:.78125},{x:.78125,y:.78125},{x:.84375,y:.78125},{x:.84375,y:.78125},{x:.90625,y:.78125},{x:.90625,y:.78125},{x:.96875,y:.78125},{x:.96875,y:.78125},{x:.03125,y:.84375},{x:.03125,y:.84375},{x:.09375,y:.84375},{x:.09375,y:.84375},{x:.15625,y:.84375},{x:.15625,y:.84375},{x:.21875,y:.84375},{x:.21875,y:.84375},{x:.28125,y:.84375},{x:.28125,y:.84375},{x:.34375,y:.84375},{x:.34375,y:.84375},{x:.40625,y:.84375},{x:.40625,y:.84375},{x:.46875,y:.84375},{x:.46875,y:.84375},{x:.53125,y:.84375},{x:.53125,y:.84375},{x:.59375,y:.84375},{x:.59375,y:.84375},{x:.65625,y:.84375},{x:.65625,y:.84375},{x:.71875,y:.84375},{x:.71875,y:.84375},{x:.78125,y:.84375},{x:.78125,y:.84375},{x:.84375,y:.84375},{x:.84375,y:.84375},{x:.90625,y:.84375},{x:.90625,y:.84375},{x:.96875,y:.84375},{x:.96875,y:.84375},{x:.03125,y:.90625},{x:.03125,y:.90625},{x:.09375,y:.90625},{x:.09375,y:.90625},{x:.15625,y:.90625},{x:.15625,y:.90625},{x:.21875,y:.90625},{x:.21875,y:.90625},{x:.28125,y:.90625},{x:.28125,y:.90625},{x:.34375,y:.90625},{x:.34375,y:.90625},{x:.40625,y:.90625},{x:.40625,y:.90625},{x:.46875,y:.90625},{x:.46875,y:.90625},{x:.53125,y:.90625},{x:.53125,y:.90625},{x:.59375,y:.90625},{x:.59375,y:.90625},{x:.65625,y:.90625},{x:.65625,y:.90625},{x:.71875,y:.90625},{x:.71875,y:.90625},{x:.78125,y:.90625},{x:.78125,y:.90625},{x:.84375,y:.90625},{x:.84375,y:.90625},{x:.90625,y:.90625},{x:.90625,y:.90625},{x:.96875,y:.90625},{x:.96875,y:.90625},{x:.03125,y:.96875},{x:.03125,y:.96875},{x:.09375,y:.96875},{x:.09375,y:.96875},{x:.15625,y:.96875},{x:.15625,y:.96875},{x:.21875,y:.96875},{x:.21875,y:.96875},{x:.28125,y:.96875},{x:.28125,y:.96875},{x:.34375,y:.96875},{x:.34375,y:.96875},{x:.40625,y:.96875},{x:.40625,y:.96875},{x:.46875,y:.96875},{x:.46875,y:.96875},{x:.53125,y:.96875},{x:.53125,y:.96875},{x:.59375,y:.96875},{x:.59375,y:.96875},{x:.65625,y:.96875},{x:.65625,y:.96875},{x:.71875,y:.96875},{x:.71875,y:.96875},{x:.78125,y:.96875},{x:.78125,y:.96875},{x:.84375,y:.96875},{x:.84375,y:.96875},{x:.90625,y:.96875},{x:.90625,y:.96875},{x:.96875,y:.96875},{x:.96875,y:.96875},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375}];var a5=class{constructor(t){T(this,"model");T(this,"anchors");T(this,"anchorsTensor");T(this,"inputSize");T(this,"inputSizeTensor");T(this,"doubleInputSizeTensor");this.model=t,this.anchors=$3.map(o=>[o.x,o.y]),this.anchorsTensor=W.tensor2d(this.anchors),this.inputSize=this.model&&this.model.inputs&&this.model.inputs[0].shape?this.model.inputs[0].shape[2]:0,this.inputSizeTensor=W.tensor1d([this.inputSize,this.inputSize]),this.doubleInputSizeTensor=W.tensor1d([this.inputSize*2,this.inputSize*2])}normalizeBoxes(t){let o={};o.boxOffsets=W.slice(t,[0,0],[-1,2]),o.boxSizes=W.slice(t,[0,2],[-1,2]),o.div=W.div(o.boxOffsets,this.inputSizeTensor),o.boxCenterPoints=W.add(o.div,this.anchorsTensor),o.halfBoxSizes=W.div(o.boxSizes,this.doubleInputSizeTensor),o.sub=W.sub(o.boxCenterPoints,o.halfBoxSizes),o.startPoints=W.mul(o.sub,this.inputSizeTensor),o.add=W.add(o.boxCenterPoints,o.halfBoxSizes),o.endPoints=W.mul(o.add,this.inputSizeTensor);let n=W.concat2d([o.startPoints,o.endPoints],1);return Object.keys(o).forEach(r=>W.dispose(o[r])),n}normalizeLandmarks(t,o){let n={};n.reshape=W.reshape(t,[-1,7,2]),n.div=W.div(n.reshape,this.inputSizeTensor),n.landmarks=W.add(n.div,this.anchors[o]);let r=W.mul(n.landmarks,this.inputSizeTensor);return Object.keys(n).forEach(A=>W.dispose(n[A])),r}async predict(t,o){let n={};n.resize=W.image.resizeBilinear(t,[this.inputSize,this.inputSize]),n.div=W.div(n.resize,V.tf127),n.image=W.sub(n.div,V.tf1),n.batched=this.model.execute(n.image),n.predictions=W.squeeze(n.batched),n.slice=W.slice(n.predictions,[0,0],[-1,1]),n.sigmoid=W.sigmoid(n.slice),n.scores=W.squeeze(n.sigmoid);let r=await n.scores.data();n.boxes=W.slice(n.predictions,[0,1],[-1,4]),n.norm=this.normalizeBoxes(n.boxes),n.nms=await W.image.nonMaxSuppressionAsync(n.norm,n.scores,3*o.hand.maxDetected,o.hand.iouThreshold,o.hand.minConfidence);let A=await n.nms.array(),s=[];for(let a of A){let i={};i.box=W.slice(n.norm,[a,0],[1,-1]),i.slice=W.slice(n.predictions,[a,5],[1,14]),i.norm=this.normalizeLandmarks(i.slice,a),i.palmLandmarks=W.reshape(i.norm,[-1,2]);let x=await i.box.data(),c=x.slice(0,2),l=x.slice(2,4),y=await i.palmLandmarks.array(),f={startPoint:c,endPoint:l,palmLandmarks:y,confidence:r[a]},u=K3(f,[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]);s.push(u),Object.keys(i).forEach(m=>W.dispose(i[m]))}return Object.keys(n).forEach(a=>W.dispose(n[a])),s}};var L0=Z(D());var yA=5,eo=1.65,to=[0,5,9,13,17,1,2],xA=0,cA=2,oo=0,i5=class{constructor(t,o){T(this,"handDetector");T(this,"handPoseModel");T(this,"inputSize");T(this,"storedBoxes");T(this,"skipped");T(this,"detectedHands");this.handDetector=t,this.handPoseModel=o,this.inputSize=this.handPoseModel&&this.handPoseModel.inputs[0].shape?this.handPoseModel.inputs[0].shape[2]:0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let o=t.map(s=>s[0]),n=t.map(s=>s[1]),r=[Math.min(...o),Math.min(...n)],A=[Math.max(...o),Math.max(...n)];return{startPoint:r,endPoint:A}}getBoxForPalmLandmarks(t,o){let n=t.map(A=>M1([...A,1],o)),r=this.calculateLandmarksBoundingBox(n);return A5(s5(r),yA)}getBoxForHandLandmarks(t){let o=this.calculateLandmarksBoundingBox(t),n=A5(s5(o),eo);n.palmLandmarks=[];for(let r=0;r<to.length;r++)n.palmLandmarks.push(t[to[r]].slice(0,2));return n}transformRawCoords(t,o,n,r){let A=r5(o),s=[A[0]/this.inputSize,A[1]/this.inputSize,(A[0]+A[1])/this.inputSize/2],a=t.map(f=>[s[0]*(f[0]-this.inputSize/2),s[1]*(f[1]-this.inputSize/2),s[2]*f[2]]),i=g1(n,[0,0]),x=a.map(f=>[...M1(f,i),f[2]]),c=Q3(r),l=[...k2(o),1],y=[Te(l,c[0]),Te(l,c[1])];return x.map(f=>[Math.trunc(f[0]+y[0]),Math.trunc(f[1]+y[1]),Math.trunc(f[2])])}async estimateHands(t,o){let n=!1,r,A=(o.hand.skipTime||0)>h()-oo,s=this.skipped<(o.hand.skipFrames||0);o.skipAllowed&&A&&s&&(r=await this.handDetector.predict(t,o),this.skipped=0),o.skipAllowed&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==o.hand.maxDetected||!o.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(n=!0));let a=[];for(let i=0;i<this.storedBoxes.length;i++){let x=this.storedBoxes[i];if(!!x)if(o.hand.landmarks){let c=o.hand.rotation?J3(x.palmLandmarks[xA],x.palmLandmarks[cA]):0,l=k2(x),y=[l[0]/t.shape[2],l[1]/t.shape[1]],f=o.hand.rotation&&v.kernels.includes("rotatewithoffset")?L0.image.rotateWithOffset(t,c,0,y):t.clone(),u=g1(-c,l),m=n?this.getBoxForPalmLandmarks(x.palmLandmarks,u):x,P=Y3(m,f,[this.inputSize,this.inputSize]),g=L0.div(P,V.tf255);L0.dispose(P),L0.dispose(f);let[b,d]=this.handPoseModel.execute(g);oo=h(),L0.dispose(g);let M=(await b.data())[0];if(L0.dispose(b),M>=o.hand.minConfidence/4){let S=L0.reshape(d,[-1,3]),w=await S.array();L0.dispose(d),L0.dispose(S);let j=this.transformRawCoords(w,m,c,u),C=this.getBoxForHandLandmarks(j);this.storedBoxes[i]={...C,confidence:M};let F={landmarks:j,confidence:M,boxConfidence:x.confidence,fingerConfidence:M,box:{topLeft:C.startPoint,bottomRight:C.endPoint}};a.push(F)}else this.storedBoxes[i]=null;L0.dispose(d)}else{let c=A5(s5(x),eo),l={confidence:x.confidence,boxConfidence:x.confidence,fingerConfidence:0,box:{topLeft:c.startPoint,bottomRight:c.endPoint},landmarks:[]};a.push(l)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=a.length,a.length>o.hand.maxDetected&&(a.length=o.hand.maxDetected),a}};var k0={thumb:0,index:1,middle:2,ring:3,pinky:4,all:[0,1,2,3,4],nameMapping:{0:"thumb",1:"index",2:"middle",3:"ring",4:"pinky"},pointsMapping:{0:[[0,1],[1,2],[2,3],[3,4]],1:[[0,5],[5,6],[6,7],[7,8]],2:[[0,9],[9,10],[10,11],[11,12]],3:[[0,13],[13,14],[14,15],[15,16]],4:[[0,17],[17,18],[18,19],[19,20]]},getName:e=>k0.nameMapping[e],getPoints:e=>k0.pointsMapping[e]},ke={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>ke.nameMapping[e]},o0={verticalUp:0,verticalDown:1,horizontalLeft:2,horizontalRight:3,diagonalUpRight:4,diagonalUpLeft:5,diagonalDownRight:6,diagonalDownLeft:7,nameMapping:{0:"verticalUp",1:"verticalDown",2:"horizontalLeft",3:"horizontalRight",4:"diagonalUpRight",5:"diagonalUpLeft",6:"diagonalDownRight",7:"diagonalDownLeft"},getName:e=>o0.nameMapping[e]},we=class{constructor(t){T(this,"name");T(this,"curls");T(this,"directions");T(this,"weights");T(this,"weightsRelative");this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}curl(t,o,n){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([o,n])}direction(t,o,n){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([o,n])}weight(t,o){this.weights[t]=o;let n=this.weights.reduce((r,A)=>r+A,0);this.weightsRelative=this.weights.map(r=>r*5/n)}matchAgainst(t,o){let n=0;for(let r in t){let A=t[r],s=this.curls[r];if(typeof s=="undefined"){n+=this.weightsRelative[r];continue}for(let[a,i]of s)if(A===a){n+=i*this.weightsRelative[r];break}}for(let r in o){let A=o[r],s=this.directions[r];if(typeof s=="undefined"){n+=this.weightsRelative[r];continue}for(let[a,i]of s)if(A===a){n+=i*this.weightsRelative[r];break}}return n/10}};var{thumb:J0,index:ce,middle:de,ring:He,pinky:Ve}=k0,{none:Q0,half:fA,full:_0}=ke,{verticalUp:o2,verticalDown:z4,horizontalLeft:P1,horizontalRight:mA,diagonalUpRight:pA,diagonalUpLeft:n2,diagonalDownRight:S4,diagonalDownLeft:C4}=o0,Ee=new we("thumbs up");Ee.curl(J0,Q0,1);Ee.direction(J0,o2,1);Ee.direction(J0,n2,.25);Ee.direction(J0,pA,.25);for(let e of[k0.index,k0.middle,k0.ring,k0.pinky])Ee.curl(e,_0,1),Ee.direction(e,P1,1),Ee.direction(e,mA,1);var l0=new we("victory");l0.curl(J0,fA,.5);l0.curl(J0,Q0,.5);l0.direction(J0,o2,1);l0.direction(J0,n2,1);l0.curl(ce,Q0,1);l0.direction(ce,o2,.75);l0.direction(ce,n2,1);l0.curl(de,Q0,1);l0.direction(de,o2,1);l0.direction(de,n2,.75);l0.curl(He,_0,1);l0.direction(He,o2,.2);l0.direction(He,n2,1);l0.direction(He,P1,.2);l0.curl(Ve,_0,1);l0.direction(Ve,o2,.2);l0.direction(Ve,n2,1);l0.direction(Ve,P1,.2);l0.weight(ce,2);l0.weight(de,2);var ze=new we("point");ze.curl(J0,_0,1);ze.curl(ce,Q0,.5);ze.curl(de,_0,.5);ze.curl(He,_0,.5);ze.curl(Ve,_0,.5);ze.weight(ce,2);ze.weight(de,2);var Se=new we("middle finger");Se.curl(J0,Q0,1);Se.curl(ce,_0,.5);Se.curl(de,_0,.5);Se.curl(He,_0,.5);Se.curl(Ve,_0,.5);Se.weight(ce,2);Se.weight(de,2);var r2=new we("open palm");r2.curl(J0,Q0,.75);r2.curl(ce,Q0,.75);r2.curl(de,Q0,.75);r2.curl(He,Q0,.75);r2.curl(Ve,Q0,.75);var no=[Ee,l0,ze,Se,r2];var uA=.7,De={HALF_CURL_START_LIMIT:60,NO_CURL_START_LIMIT:130,DISTANCE_VOTE_POWER:1.1,SINGLE_ANGLE_VOTE_POWER:.9,TOTAL_ANGLE_VOTE_POWER:1.6};function ro(e,t,o,n){let r=(t-n)/(e-o),A=Math.atan(r)*180/Math.PI;return A<=0?A=-A:A>0&&(A=180-A),A}function so(e,t){if(!e||!t)return[0,0];let o=ro(e[0],e[1],t[0],t[1]);if(e.length===2)return o;let n=ro(e[1],e[2],t[1],t[2]);return[o,n]}function Ao(e,t=1){let o=0,n=0,r=0;return e>=75&&e<=105?o=1*t:e>=25&&e<=155?n=1*t:r=1*t,[o,n,r]}function hA(e,t,o){let n=e[0]-t[0],r=e[0]-o[0],A=t[0]-o[0],s=e[1]-t[1],a=e[1]-o[1],i=t[1]-o[1],x=e[2]-t[2],c=e[2]-o[2],l=t[2]-o[2],y=Math.sqrt(n*n+s*s+x*x),f=Math.sqrt(r*r+a*a+c*c),u=Math.sqrt(A*A+i*i+l*l),m=(u*u+y*y-f*f)/(2*u*y);m>1?m=1:m<-1&&(m=-1);let P=Math.acos(m);P=57.2958*P%180;let g;return P>De.NO_CURL_START_LIMIT?g=ke.none:P>De.HALF_CURL_START_LIMIT?g=ke.half:g=ke.full,g}function ao(e,t,o,n){let r;return n===Math.abs(e)?e>0?r=o0.horizontalLeft:r=o0.horizontalRight:n===Math.abs(t)?t>0?r=o0.horizontalLeft:r=o0.horizontalRight:o>0?r=o0.horizontalLeft:r=o0.horizontalRight,r}function io(e,t,o,n){let r;return n===Math.abs(e)?e<0?r=o0.verticalDown:r=o0.verticalUp:n===Math.abs(t)?t<0?r=o0.verticalDown:r=o0.verticalUp:o<0?r=o0.verticalDown:r=o0.verticalUp,r}function bA(e,t,o,n,r,A,s,a){let i,x=io(e,t,o,n),c=ao(r,A,s,a);return x===o0.verticalUp?c===o0.horizontalLeft?i=o0.diagonalUpLeft:i=o0.diagonalUpRight:c===o0.horizontalLeft?i=o0.diagonalDownLeft:i=o0.diagonalDownRight,i}function gA(e,t,o,n){let r=e[0]-t[0],A=e[0]-o[0],s=t[0]-o[0],a=e[1]-t[1],i=e[1]-o[1],x=t[1]-o[1],c=Math.max(Math.abs(r),Math.abs(A),Math.abs(s)),l=Math.max(Math.abs(a),Math.abs(i),Math.abs(x)),y=0,f=0,u=0,m=l/(c+1e-5);m>1.5?y+=De.DISTANCE_VOTE_POWER:m>.66?f+=De.DISTANCE_VOTE_POWER:u+=De.DISTANCE_VOTE_POWER;let P=Math.sqrt(r*r+a*a),g=Math.sqrt(A*A+i*i),b=Math.sqrt(s*s+x*x),d=Math.max(P,g,b),M=e[0],S=e[1],w=o[0],j=o[1];d===P?(w=o[0],j=o[1]):d===b&&(M=t[0],S=t[1]);let H=so([M,S],[w,j]),Y=Ao(H,De.TOTAL_ANGLE_VOTE_POWER);y+=Y[0],f+=Y[1],u+=Y[2];for(let x0 of n){let E=Ao(x0,De.SINGLE_ANGLE_VOTE_POWER);y+=E[0],f+=E[1],u+=E[2]}let J;return y===Math.max(y,f,u)?J=io(i,a,x,l):u===Math.max(f,u)?J=ao(A,r,s,c):J=bA(i,a,x,l,A,r,s,c),J}function lo(e){let t=[],o=[],n=[],r=[];if(!e)return{curls:n,directions:r};for(let A of k0.all){let s=k0.getPoints(A),a=[],i=[];for(let x of s){let c=e[x[0]],l=e[x[1]],y=so(c,l),f=y[0],u=y[1];a.push(f),i.push(u)}t.push(a),o.push(i)}for(let A of k0.all){let s=A===k0.thumb?1:0,a=k0.getPoints(A),i=e[a[s][0]],x=e[a[s+1][1]],c=e[a[3][1]],l=hA(i,x,c),y=gA(i,x,c,t[A].slice(s));n[A]=l,r[A]=y}return{curls:n,directions:r}}function l5(e){if(!e||e.length===0)return null;let t=lo(e),o={};for(let n of k0.all)o[k0.getName(n)]={curl:ke.getName(t.curls[n]),direction:o0.getName(t.directions[n])};return o}function yo(e){let t=[];if(!e||e.length===0)return t;let o=lo(e);for(let n of no){let r=n.matchAgainst(o.curls,o.directions);r>=uA&&t.push({name:n.name,confidence:r})}return t}var xo={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],palm:[0]},A2,s2,co;async function v1(e,t){let o=await co.estimateHands(e,t);if(!o)return[];let n=[];for(let r=0;r<o.length;r++){let A={};if(o[r].landmarks)for(let c of Object.keys(xo))A[c]=xo[c].map(l=>o[r].landmarks[l]);let s=o[r].landmarks,a=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],i=[0,0,0,0];if(s&&s.length>0){for(let c of s)c[0]<a[0]&&(a[0]=c[0]),c[1]<a[1]&&(a[1]=c[1]),c[0]>a[2]&&(a[2]=c[0]),c[1]>a[3]&&(a[3]=c[1]);a[2]-=a[0],a[3]-=a[1],i=[a[0]/(e.shape[2]||0),a[1]/(e.shape[1]||0),a[2]/(e.shape[2]||0),a[3]/(e.shape[1]||0)]}else a=o[r].box?[Math.trunc(Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.max(0,o[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,o[r].box.bottomRight[0])-Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,o[r].box.bottomRight[1])-Math.max(0,o[r].box.topLeft[1]))]:[0,0,0,0],i=[o[r].box.topLeft[0]/(e.shape[2]||0),o[r].box.topLeft[1]/(e.shape[1]||0),(o[r].box.bottomRight[0]-o[r].box.topLeft[0])/(e.shape[2]||0),(o[r].box.bottomRight[1]-o[r].box.topLeft[1])/(e.shape[1]||0)];let x=l5(s);n.push({id:r,score:Math.round(100*o[r].confidence)/100,boxScore:Math.round(100*o[r].boxConfidence)/100,fingerScore:Math.round(100*o[r].fingerConfidence)/100,label:"hand",box:a,boxRaw:i,keypoints:s,annotations:A,landmarks:x})}return n}async function T1(e){var o,n;v.initial&&(A2=null,s2=null),!A2||!s2?[A2,s2]=await Promise.all([e.hand.enabled?G((o=e.hand.detector)==null?void 0:o.modelPath):null,e.hand.landmarks?G((n=e.hand.skeleton)==null?void 0:n.modelPath):null]):(e.debug&&p("cached model:",A2.modelUrl),e.debug&&p("cached model:",s2.modelUrl));let t=new a5(A2);return co=new i5(t,s2),[A2,s2]}var Q=Z(D());var d0=[null,null],MA=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],Ce=[[0,0],[0,0]],PA=["hand","fist","pinch","point","face","tip","pinchtip"],mo=4,po=1.6,RA=512,vA=1.4,y5=Number.MAX_SAFE_INTEGER,w1=0,fe=[0,0],A0={boxes:[],hands:[]},uo={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],base:[0],palm:[0,17,13,9,5,1,0]};async function ho(e){var t;if(v.initial&&(d0[0]=null),d0[0])e.debug&&p("cached model:",d0[0].modelUrl);else{x5(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),d0[0]=await G((t=e.hand.detector)==null?void 0:t.modelPath);let o=Object.values(d0[0].modelSignature.inputs);Ce[0][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ce[0][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return d0[0]}async function bo(e){var t;if(v.initial&&(d0[1]=null),d0[1])e.debug&&p("cached model:",d0[1].modelUrl);else{d0[1]=await G((t=e.hand.skeleton)==null?void 0:t.modelPath);let o=Object.values(d0[1].modelSignature.inputs);Ce[1][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ce[1][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return d0[1]}async function TA(e,t){let o=[];if(!e||!d0[0])return o;let n={},r=(e.shape[2]||1)/(e.shape[1]||1),A=Math.min(Math.round((e.shape[1]||0)/8)*8,RA),s=Math.round(A*r/8)*8;n.resize=Q.image.resizeBilinear(e,[A,s]),n.cast=Q.cast(n.resize,"int32"),[n.rawScores,n.rawBoxes]=await d0[0].executeAsync(n.cast,MA),n.boxes=Q.squeeze(n.rawBoxes,[0,2]),n.scores=Q.squeeze(n.rawScores,[0]);let a=Q.unstack(n.scores,1);Q.dispose(a[mo]),a.splice(mo,1),n.filtered=Q.stack(a,1),Q.dispose(a),n.max=Q.max(n.filtered,1),n.argmax=Q.argMax(n.filtered,1);let i=0;n.nms=await Q.image.nonMaxSuppressionAsync(n.boxes,n.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let x=await n.nms.data(),c=await n.max.data(),l=await n.argmax.data();for(let y of Array.from(x)){let f=Q.slice(n.boxes,y,1),u=await f.data();Q.dispose(f);let m=[u[1],u[0],u[3]-u[1],u[2]-u[0]],P=Q2(m,vA),g=[Math.trunc(m[0]*fe[0]),Math.trunc(m[1]*fe[1]),Math.trunc(m[2]*fe[0]),Math.trunc(m[3]*fe[1])],b=c[y],d=PA[l[y]],M={id:i++,score:b,box:g,boxRaw:P,label:d};o.push(M)}return Object.keys(n).forEach(y=>Q.dispose(n[y])),o.sort((y,f)=>f.score-y.score),o.length>(t.hand.maxDetected||1)&&(o.length=t.hand.maxDetected||1),o}async function k1(e,t,o){let n={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&d0[1]&&o.hand.landmarks&&t.score>(o.hand.minConfidence||0)){let r={},A=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=Q.image.cropAndResize(e,[A],[0],[Ce[1][0],Ce[1][1]],"bilinear"),r.div=Q.div(r.crop,V.tf255),[r.score,r.keypoints]=d0[1].execute(r.div,["Identity_1","Identity"]);let s=(await r.score.data())[0],a=(100-Math.trunc(100/(1+Math.exp(s))))/100;if(a>=(o.hand.minConfidence||0)){n.fingerScore=a,r.reshaped=Q.reshape(r.keypoints,[-1,3]);let c=(await r.reshaped.array()).map(l=>[l[0]/Ce[1][1],l[1]/Ce[1][0],l[2]||0]).map(l=>[l[0]*t.boxRaw[2],l[1]*t.boxRaw[3],l[2]||0]);n.keypoints=c.map(l=>[fe[0]*(l[0]+t.boxRaw[0]),fe[1]*(l[1]+t.boxRaw[1]),l[2]||0]),n.landmarks=l5(n.keypoints);for(let l of Object.keys(uo))n.annotations[l]=uo[l].map(y=>n.landmarks&&n.keypoints[y]?n.keypoints[y]:null)}Object.keys(r).forEach(i=>Q.dispose(r[i]))}return n}async function E1(e,t){var r,A;if(!d0[0]||!d0[1]||!((r=d0[0])!=null&&r.inputs[0].shape)||!((A=d0[1])!=null&&A.inputs[0].shape))return[];fe=[e.shape[2]||0,e.shape[1]||0],y5++;let o=(t.hand.skipTime||0)>h()-w1,n=y5<(t.hand.skipFrames||0);return t.skipAllowed&&o&&n?A0.hands:new Promise(async s=>{let a=3*(t.hand.skipTime||0)>h()-w1,i=y5<3*(t.hand.skipFrames||0);t.skipAllowed&&A0.hands.length===t.hand.maxDetected?A0.hands=await Promise.all(A0.boxes.map(c=>k1(e,c,t))):t.skipAllowed&&a&&i&&A0.hands.length>0?A0.hands=await Promise.all(A0.boxes.map(c=>k1(e,c,t))):(A0.boxes=await TA(e,t),w1=h(),A0.hands=await Promise.all(A0.boxes.map(c=>k1(e,c,t))),y5=0);let x=[...A0.boxes];if(A0.boxes.length=0,t.cacheSensitivity>0)for(let c=0;c<A0.hands.length;c++){let l=a3(A0.hands[c].keypoints,fe);if(l.box[2]/(e.shape[2]||1)>.05&&l.box[3]/(e.shape[1]||1)>.05&&A0.hands[c].fingerScore&&A0.hands[c].fingerScore>(t.hand.minConfidence||0)){let y=Q2(l.box,po),f=Q2(l.boxRaw,po);A0.boxes.push({...x[c],box:y,boxRaw:f})}}for(let c=0;c<A0.hands.length;c++){let l=le(A0.hands[c].keypoints,fe);A0.hands[c].box=l.box,A0.hands[c].boxRaw=l.boxRaw}s(A0.hands)})}var d5=Z(D());var M0,c5=[],z1=Number.MAX_SAFE_INTEGER,Mo=0,Po=0;async function Ro(e){var t;return v.initial&&(M0=null),M0?e.debug&&p("cached model:",M0.modelUrl):M0=await G((t=e.face.liveness)==null?void 0:t.modelPath),M0}async function S1(e,t,o,n){var s,a;if(!M0)return 0;let r=(((s=t.face.liveness)==null?void 0:s.skipTime)||0)>h()-Po,A=z1<(((a=t.face.liveness)==null?void 0:a.skipFrames)||0);return t.skipAllowed&&r&&A&&Mo===n&&c5[o]?(z1++,c5[o]):(z1=0,new Promise(async i=>{let x=d5.image.resizeBilinear(e,[M0!=null&&M0.inputs[0].shape?M0.inputs[0].shape[2]:0,M0!=null&&M0.inputs[0].shape?M0.inputs[0].shape[1]:0],!1),c=M0==null?void 0:M0.execute(x),l=(await c.data())[0];c5[o]=Math.round(100*l)/100,Mo=n,Po=h(),d5.dispose([x,c]),i(c5[o])}))}var zo=Z(D());var E2={};ue(E2,{connected:()=>m5,horizontal:()=>C1,kpt:()=>f5,relative:()=>I1,vertical:()=>j1});var f5=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],C1=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],j1=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],I1=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],m5={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var je=Z(D()),To=.005,W0={keypoints:[],padding:[[0,0],[0,0],[0,0],[0,0]]};function N1(e){for(let t of C1){let o=e.keypoints.findIndex(r=>r.part===t[0]),n=e.keypoints.findIndex(r=>r.part===t[1]);if(e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[0]<e.keypoints[n].position[0]){let r=e.keypoints[o];e.keypoints[o]=e.keypoints[n],e.keypoints[n]=r}}for(let t of j1){let o=e.keypoints.findIndex(r=>r&&r.part===t[0]),n=e.keypoints.findIndex(r=>r&&r.part===t[1]);e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[1]<e.keypoints[n].position[1]&&e.keypoints.splice(o,1)}for(let[t,o]of I1){let n=e.keypoints.findIndex(x=>x&&x.part===t[0]),r=e.keypoints.findIndex(x=>x&&x.part===t[1]),A=e.keypoints.findIndex(x=>x&&x.part===o[0]),s=e.keypoints.findIndex(x=>x&&x.part===o[1]);if(!e.keypoints[A]||!e.keypoints[s])continue;let a=e.keypoints[n]?[Math.abs(e.keypoints[A].position[0]-e.keypoints[n].position[0]),Math.abs(e.keypoints[s].position[0]-e.keypoints[n].position[0])]:[0,0],i=e.keypoints[r]?[Math.abs(e.keypoints[s].position[0]-e.keypoints[r].position[0]),Math.abs(e.keypoints[A].position[0]-e.keypoints[r].position[0])]:[0,0];if(a[0]>a[1]||i[0]>i[1]){let x=e.keypoints[n];e.keypoints[n]=e.keypoints[r],e.keypoints[r]=x}}}function wo(e){for(let t=0;t<e.length;t++)if(e[t]&&W0.keypoints[t]){let o=[Math.abs(e[t].positionRaw[0]-W0.keypoints[t].positionRaw[0]),Math.abs(e[t].positionRaw[1]-W0.keypoints[t].positionRaw[1])];o[0]<To&&o[1]<To?e[t]=W0.keypoints[t]:W0.keypoints[t]=e[t]}else W0.keypoints[t]=e[t];return e}function ko(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;W0.padding=[[0,0],[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0],[0,0]],o.pad=je.pad(e,W0.padding),o.resize=je.image.resizeBilinear(o.pad,[t,t]);let n=je.cast(o.resize,"int32");return Object.keys(o).forEach(r=>je.dispose(o[r])),n}function Eo(e,t){e.keypoints=e.keypoints.filter(n=>n&&n.position);for(let n of e.keypoints)n.position=[n.position[0]*(t[0]+W0.padding[2][0]+W0.padding[2][1])/t[0]-W0.padding[2][0],n.position[1]*(t[1]+W0.padding[1][0]+W0.padding[1][1])/t[1]-W0.padding[1][0]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1]];let o=le(e.keypoints.map(n=>n.position),t);return e.box=o.box,e.boxRaw=o.boxRaw,e}var F0,p5=0,O1=Number.MAX_SAFE_INTEGER,Ze={boxes:[],bodies:[],last:0};async function So(e){return v.initial&&(F0=null),F0?e.debug&&p("cached model:",F0.modelUrl):(x5(["size"],e),F0=await G(e.body.modelPath)),p5=F0.inputs[0].shape?F0.inputs[0].shape[2]:0,p5<64&&(p5=256),F0}async function kA(e,t,o){let n=e[0][0],r=[],A=0;for(let c=0;c<n.length;c++)if(A=n[c][2],A>t.body.minConfidence){let l=[n[c][1],n[c][0]];r.push({score:Math.round(100*A)/100,part:f5[c],positionRaw:l,position:[Math.round((o.shape[2]||0)*l[0]),Math.round((o.shape[1]||0)*l[1])]})}A=r.reduce((c,l)=>l.score>c?l.score:c,0);let s=[],a=le(r.map(c=>c.position),[o.shape[2],o.shape[1]]),i={};for(let[c,l]of Object.entries(m5)){let y=[];for(let f=0;f<l.length-1;f++){let u=r.find(P=>P.part===l[f]),m=r.find(P=>P.part===l[f+1]);u&&m&&u.score>(t.body.minConfidence||0)&&m.score>(t.body.minConfidence||0)&&y.push([u.position,m.position])}i[c]=y}let x={id:0,score:A,box:a.box,boxRaw:a.boxRaw,keypoints:r,annotations:i};return N1(x),s.push(x),s}async function EA(e,t,o){let n=[];for(let r=0;r<e[0].length;r++){let A=e[0][r],s=Math.round(100*A[51+4])/100;if(s>t.body.minConfidence){let a=[];for(let l=0;l<17;l++){let y=A[3*l+2];if(y>t.body.minConfidence){let f=[A[3*l+1],A[3*l+0]];a.push({part:f5[l],score:Math.round(100*y)/100,positionRaw:f,position:[Math.round((o.shape[2]||0)*f[0]),Math.round((o.shape[1]||0)*f[1])]})}}let i=le(a.map(l=>l.position),[o.shape[2],o.shape[1]]),x={};for(let[l,y]of Object.entries(m5)){let f=[];for(let u=0;u<y.length-1;u++){let m=a.find(g=>g.part===y[u]),P=a.find(g=>g.part===y[u+1]);m&&P&&m.score>(t.body.minConfidence||0)&&P.score>(t.body.minConfidence||0)&&f.push([m.position,P.position])}x[l]=f}let c={id:r,score:s,box:i.box,boxRaw:i.boxRaw,keypoints:[...a],annotations:x};N1(c),n.push(c)}}return n.sort((r,A)=>A.score-r.score),n.length>t.body.maxDetected&&(n.length=t.body.maxDetected),n}async function L1(e,t){if(!F0||!(F0!=null&&F0.inputs[0].shape))return[];t.skipAllowed||(Ze.boxes.length=0),O1++;let o=(t.body.skipTime||0)>h()-Ze.last,n=O1<(t.body.skipFrames||0);return t.skipAllowed&&o&&n?Ze.bodies:new Promise(async r=>{let A={};O1=0,A.input=ko(e,p5),A.res=F0==null?void 0:F0.execute(A.input),Ze.last=h();let s=await A.res.array();Ze.bodies=A.res.shape[2]===17?await kA(s,t,e):await EA(s,t,e);for(let a of Ze.bodies)Eo(a,[e.shape[2]||1,e.shape[1]||1]),wo(a.keypoints);Object.keys(A).forEach(a=>zo.dispose(A[a])),r(Ze.bodies)})}var E0=Z(D());var a2,u5=[],jo=0,W1=Number.MAX_SAFE_INTEGER,b5=0,h5=2.5;async function Io(e){if(!a2||v.initial){a2=await G(e.object.modelPath);let t=Object.values(a2.modelSignature.inputs);b5=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&p("cached model:",a2.modelUrl);return a2}async function zA(e,t,o){let n=0,r=[];for(let i of[1,2,4])E0.tidy(async()=>{let x=i*13,c=E0.squeeze(e.find(m=>m.shape[1]===x**2&&(m.shape[2]||0)===$e.length)),l=E0.squeeze(e.find(m=>m.shape[1]===x**2&&(m.shape[2]||0)<$e.length)),f=await l.reshape([-1,4,l.shape[1]/4]).argMax(2).array(),u=await c.array();for(let m=0;m<c.shape[0];m++)for(let P=0;P<c.shape[1];P++){let g=u[m][P];if(g>(o.object.minConfidence||0)&&P!==61){let b=(.5+Math.trunc(m%x))/x,d=(.5+Math.trunc(m/x))/x,M=f[m].map(J=>J*(x/i/b5)),[S,w]=[b-h5/i*M[0],d-h5/i*M[1]],[j,C]=[b+h5/i*M[2]-S,d+h5/i*M[3]-w],F=[S,w,j,C];F=F.map(J=>Math.max(0,Math.min(J,1)));let H=[F[0]*t[0],F[1]*t[1],F[2]*t[0],F[3]*t[1]],Y={id:n++,score:Math.round(100*g)/100,class:P+1,label:$e[P].label,box:H.map(J=>Math.trunc(J)),boxRaw:F};r.push(Y)}}});e.forEach(i=>E0.dispose(i));let A=r.map(i=>[i.boxRaw[1],i.boxRaw[0],i.boxRaw[3],i.boxRaw[2]]),s=r.map(i=>i.score),a=[];if(A&&A.length>0){let i=await E0.image.nonMaxSuppressionAsync(A,s,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence);a=await i.data(),E0.dispose(i)}return r=r.filter((i,x)=>a.includes(x)).sort((i,x)=>x.score-i.score),r}async function F1(e,t){let o=(t.object.skipTime||0)>h()-jo,n=W1<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&u5.length>0?(W1++,u5):(W1=0,!v.kernels.includes("mod")||!v.kernels.includes("sparsetodense")?u5:new Promise(async r=>{let A=[e.shape[2]||0,e.shape[1]||0],s=E0.image.resizeBilinear(e,[b5,b5],!1),a=E0.div(s,V.tf255),i=a.transpose([0,3,1,2]);E0.dispose(a),E0.dispose(s);let x;t.object.enabled&&(x=a2.execute(i)),jo=h(),E0.dispose(i);let c=await zA(x,A,t);u5=c,r(c)}))}var z0=Z(D());var S2=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],SA=S2.length,z2=S2.reduce((e,t,o)=>(e[t]=o,e),{}),CA=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],ts=CA.map(([e,t])=>[z2[e],z2[t]]),Oo=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function Lo(e){let t=e.reduce(({maxX:o,maxY:n,minX:r,minY:A},{position:{x:s,y:a}})=>({maxX:Math.max(o,s),maxY:Math.max(n,a),minX:Math.min(r,s),minY:Math.min(A,a)}),{maxX:Number.NEGATIVE_INFINITY,maxY:Number.NEGATIVE_INFINITY,minX:Number.POSITIVE_INFINITY,minY:Number.POSITIVE_INFINITY});return[t.minX,t.minY,t.maxX-t.minX,t.maxY-t.minY]}function Wo(e,[t,o],[n,r]){let A=t/n,s=o/r,a=(x,c)=>({id:c,score:x.score,boxRaw:[x.box[0]/r,x.box[1]/n,x.box[2]/r,x.box[3]/n],box:[Math.trunc(x.box[0]*s),Math.trunc(x.box[1]*A),Math.trunc(x.box[2]*s),Math.trunc(x.box[3]*A)],keypoints:x.keypoints.map(({score:l,part:y,position:f})=>({score:l,part:y,position:[Math.trunc(f.x*s),Math.trunc(f.y*A)],positionRaw:[f.x/n,f.y/n]})),annotations:{}});return e.map((x,c)=>a(x,c))}var g5=class{constructor(t,o){T(this,"priorityQueue");T(this,"numberOfElements");T(this,"getElementValue");this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=o}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(Math.floor(t/2),t);)this.exchange(t,Math.floor(t/2)),t=Math.floor(t/2)}sink(t){for(;2*t<=this.numberOfElements;){let o=2*t;if(o<this.numberOfElements&&this.less(o,o+1)&&o++,!this.less(t,o))break;this.exchange(t,o),t=o}}getValueAt(t){return this.getElementValue(this.priorityQueue[t])}less(t,o){return this.getValueAt(t)<this.getValueAt(o)}exchange(t,o){let n=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[o],this.priorityQueue[o]=n}};function G1(e,t,o,n){return{y:n.get(e,t,o),x:n.get(e,t,o+SA)}}function B1(e,t,o){let{heatmapY:n,heatmapX:r,id:A}=e,{y:s,x:a}=G1(n,r,A,o);return{x:e.heatmapX*t+a,y:e.heatmapY*t+s}}function H1(e,t,o){return e<t?t:e>o?o:e}function Fo(e,t,o,n){let r=o-e,A=n-t;return r*r+A*A}function V1(e,t){return{x:e.x+t.x,y:e.y+t.y}}var $0,IA=["MobilenetV1/offset_2/BiasAdd","MobilenetV1/heatmap_2/BiasAdd","MobilenetV1/displacement_fwd_2/BiasAdd","MobilenetV1/displacement_bwd_2/BiasAdd"],M5=1,i2=16,NA=50**2;function Go(e,t,o,n,r,A,s=2){let a=g=>({y:A.get(g.y,g.x,e),x:A.get(g.y,g.x,A.shape[2]/2+e)}),i=(g,b,d)=>({y:H1(Math.round(g.y/i2),0,b-1),x:H1(Math.round(g.x/i2),0,d-1)}),[x,c]=n.shape,l=i(t.position,x,c),y=a(l),u=V1(t.position,y);for(let g=0;g<s;g++){let b=i(u,x,c),d=G1(b.y,b.x,o,r);u=V1({x:b.x*i2,y:b.y*i2},{x:d.x,y:d.y})}let m=i(u,x,c),P=n.get(m.y,m.x,o);return{position:u,part:S2[o],score:P}}function OA(e,t,o,n,r){let A=Oo.map(([y,f])=>[z2[y],z2[f]]),s=A.map(([,y])=>y),a=A.map(([y])=>y),i=t.shape[2],x=s.length,c=new Array(i),l=B1(e.part,i2,o);c[e.part.id]={score:e.score,part:S2[e.part.id],position:l};for(let y=x-1;y>=0;--y){let f=s[y],u=a[y];c[f]&&!c[u]&&(c[u]=Go(y,c[f],u,t,o,r))}for(let y=0;y<x;++y){let f=a[y],u=s[y];c[f]&&!c[u]&&(c[u]=Go(y,c[f],u,t,o,n))}return c}function LA(e,t,o,n,r){let[A,s]=r.shape,a=!0,i=Math.max(o-M5,0),x=Math.min(o+M5+1,A);for(let c=i;c<x;++c){let l=Math.max(n-M5,0),y=Math.min(n+M5+1,s);for(let f=l;f<y;++f)if(r.get(c,f,e)>t){a=!1;break}if(!a)break}return a}function WA(e,t){let[o,n,r]=t.shape,A=new g5(o*n*r,({score:s})=>s);for(let s=0;s<o;++s)for(let a=0;a<n;++a)for(let i=0;i<r;++i){let x=t.get(s,a,i);x<e||LA(i,x,s,a,t)&&A.enqueue({score:x,part:{heatmapY:s,heatmapX:a,id:i}})}return A}function Bo(e,{x:t,y:o},n){return e.some(({keypoints:r})=>{var s;let A=(s=r[n])==null?void 0:s.position;return A?Fo(o,t,A.y,A.x)<=NA:!1})}function FA(e,t){return t.reduce((n,{position:r,score:A},s)=>(Bo(e,r,s)||(n+=A),n),0)/t.length}function GA(e,t,o,n,r,A){let s=[],a=WA(A,t);for(;s.length<r&&!a.empty();){let i=a.dequeue(),x=B1(i.part,i2,e);if(Bo(s,x,i.part.id))continue;let c=OA(i,t,e,o,n);c=c.filter(f=>f.score>A);let l=FA(s,c),y=Lo(c);l>A&&s.push({keypoints:c,box:y,score:Math.round(100*l)/100})}return s}async function D1(e,t){let o=z0.tidy(()=>{if(!$0.inputs[0].shape)return[];let s=z0.image.resizeBilinear(e,[$0.inputs[0].shape[2],$0.inputs[0].shape[1]]),a=z0.sub(z0.div(z0.cast(s,"float32"),127.5),1),x=$0.execute(a,IA).map(c=>z0.squeeze(c,[0]));return x[1]=z0.sigmoid(x[1]),x}),n=await Promise.all(o.map(s=>s.buffer()));for(let s of o)z0.dispose(s);let r=await GA(n[0],n[1],n[2],n[3],t.body.maxDetected,t.body.minConfidence);return $0.inputs[0].shape?Wo(r,[e.shape[1],e.shape[2]],[$0.inputs[0].shape[2],$0.inputs[0].shape[1]]):[]}async function Ho(e){return!$0||v.initial?$0=await G(e.body.modelPath):e.debug&&p("cached model:",$0.modelUrl),$0}var n0=Z(D());var ne,Z1=!1;async function X1(e){return!ne||v.initial?ne=await G(e.segmentation.modelPath):e.debug&&p("cached model:",ne.modelUrl),ne}async function Do(e,t,o){var m,P;if(Z1)return{data:[],canvas:null,alpha:null};Z1=!0,ne||await X1(o);let n=await Ye(e,o),r=((m=n.tensor)==null?void 0:m.shape[2])||0,A=((P=n.tensor)==null?void 0:P.shape[1])||0;if(!n.tensor)return{data:[],canvas:null,alpha:null};let s={};s.resize=n0.image.resizeBilinear(n.tensor,[ne.inputs[0].shape?ne.inputs[0].shape[1]:0,ne.inputs[0].shape?ne.inputs[0].shape[2]:0],!1),n0.dispose(n.tensor),s.norm=n0.div(s.resize,V.tf255),s.res=ne.execute(s.norm),s.squeeze=n0.squeeze(s.res,0),s.squeeze.shape[2]===2?(s.softmax=n0.softmax(s.squeeze),[s.bg,s.fg]=n0.unstack(s.softmax,2),s.expand=n0.expandDims(s.fg,2),s.pad=n0.expandDims(s.expand,0),s.crop=n0.image.cropAndResize(s.pad,[[0,0,.5,.5]],[0],[r,A]),s.data=n0.squeeze(s.crop,0)):s.data=n0.image.resizeBilinear(s.squeeze,[A,r]);let a=Array.from(await s.data.data());if(v.node&&!v.Canvas&&typeof ImageData=="undefined")return o.debug&&p("canvas support missing"),Object.keys(s).forEach(g=>n0.dispose(s[g])),{data:a,canvas:null,alpha:null};let i=R0(r,A);n0.browser&&await n0.browser.toPixels(s.data,i);let x=i.getContext("2d");o.segmentation.blur&&o.segmentation.blur>0&&(x.filter=`blur(${o.segmentation.blur}px)`);let c=x.getImageData(0,0,r,A),l=R0(r,A),y=l.getContext("2d");n.canvas&&y.drawImage(n.canvas,0,0),y.globalCompositeOperation="darken",o.segmentation.blur&&o.segmentation.blur>0&&(y.filter=`blur(${o.segmentation.blur}px)`),y.drawImage(i,0,0),y.globalCompositeOperation="source-over",y.filter="none";let f=y.getImageData(0,0,r,A);for(let g=0;g<r*A;g++)f.data[4*g+3]=c.data[4*g+0];y.putImageData(f,0,0);let u=null;if(t&&l){u=R0(r,A);let g=await Ye(t,o);n0.dispose(g.tensor);let b=u.getContext("2d");b.drawImage(g.canvas,0,0,u.width,u.height),b.drawImage(l,0,0)}return Object.keys(s).forEach(g=>n0.dispose(s[g])),Z1=!1,{data:a,canvas:l,alpha:i}}var C2=class{constructor(){T(this,"ssrnetage",null);T(this,"gear",null);T(this,"blazeposedetect",null);T(this,"blazepose",null);T(this,"centernet",null);T(this,"efficientpose",null);T(this,"mobilefacenet",null);T(this,"emotion",null);T(this,"facedetect",null);T(this,"faceiris",null);T(this,"facemesh",null);T(this,"faceres",null);T(this,"ssrnetgender",null);T(this,"handpose",null);T(this,"handskeleton",null);T(this,"handtrack",null);T(this,"liveness",null);T(this,"movenet",null);T(this,"nanodet",null);T(this,"posenet",null);T(this,"segmentation",null);T(this,"antispoof",null)}},q1=e=>{let t=0,o=0,n=0;for(let A of Object.values(q0))t+=A.sizeFromManifest,o+=A.sizeLoadedWeights,n+=A.sizeDesired;let r=n>0?o/n:0;return{numLoadedModels:Object.values(q0).length,numEnabledModels:void 0,numDefinedModels:Object.keys(e.models).length,percentageLoaded:r,totalSizeFromManifest:t,totalSizeWeights:o,totalSizeLoading:n,totalSizeEnabled:void 0,modelStats:Object.values(q0)}};function P5(e){for(let t of Object.keys(e.models))e.models[t]=null}async function U1(e){var t,o,n,r,A,s,a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0;v.initial&&P5(e),e.config.hand.enabled&&(!e.models.handpose&&((o=(t=e.config.hand.detector)==null?void 0:t.modelPath)==null?void 0:o.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await T1(e.config)),!e.models.handskeleton&&e.config.hand.landmarks&&((r=(n=e.config.hand.detector)==null?void 0:n.modelPath)==null?void 0:r.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await T1(e.config))),e.config.body.enabled&&!e.models.blazepose&&((s=(A=e.config.body)==null?void 0:A.modelPath)==null?void 0:s.includes("blazepose"))&&(e.models.blazepose=c3(e.config)),e.config.body.enabled&&!e.models.blazeposedetect&&e.config.body.detector&&e.config.body.detector.modelPath&&(e.models.blazeposedetect=x3(e.config)),e.config.body.enabled&&!e.models.efficientpose&&((i=(a=e.config.body)==null?void 0:a.modelPath)==null?void 0:i.includes("efficientpose"))&&(e.models.efficientpose=h3(e.config)),e.config.body.enabled&&!e.models.movenet&&((c=(x=e.config.body)==null?void 0:x.modelPath)==null?void 0:c.includes("movenet"))&&(e.models.movenet=So(e.config)),e.config.body.enabled&&!e.models.posenet&&((y=(l=e.config.body)==null?void 0:l.modelPath)==null?void 0:y.includes("posenet"))&&(e.models.posenet=Ho(e.config)),e.config.face.enabled&&!e.models.facedetect&&(e.models.facedetect=o3(e.config)),e.config.face.enabled&&((f=e.config.face.antispoof)==null?void 0:f.enabled)&&!e.models.antispoof&&(e.models.antispoof=Dt(e.config)),e.config.face.enabled&&((u=e.config.face.liveness)==null?void 0:u.enabled)&&!e.models.liveness&&(e.models.liveness=Ro(e.config)),e.config.face.enabled&&((m=e.config.face.description)==null?void 0:m.enabled)&&!e.models.faceres&&(e.models.faceres=Z3(e.config)),e.config.face.enabled&&((P=e.config.face.emotion)==null?void 0:P.enabled)&&!e.models.emotion&&(e.models.emotion=P3(e.config)),e.config.face.enabled&&((g=e.config.face.iris)==null?void 0:g.enabled)&&!((b=e.config.face.attention)!=null&&b.enabled)&&!e.models.faceiris&&(e.models.faceiris=I3(e.config)),e.config.face.enabled&&((d=e.config.face.mesh)==null?void 0:d.enabled)&&!e.models.facemesh&&(e.models.facemesh=G3(e.config)),e.config.face.enabled&&((M=e.config.face.gear)==null?void 0:M.enabled)&&!e.models.gear&&(e.models.gear=St(e.config)),e.config.face.enabled&&((S=e.config.face.ssrnet)==null?void 0:S.enabled)&&!e.models.ssrnetage&&(e.models.ssrnetage=Ot(e.config)),e.config.face.enabled&&((w=e.config.face.ssrnet)==null?void 0:w.enabled)&&!e.models.ssrnetgender&&(e.models.ssrnetgender=Gt(e.config)),e.config.face.enabled&&((j=e.config.face.mobilefacenet)==null?void 0:j.enabled)&&!e.models.mobilefacenet&&(e.models.mobilefacenet=E3(e.config)),e.config.hand.enabled&&!e.models.handtrack&&((F=(C=e.config.hand.detector)==null?void 0:C.modelPath)==null?void 0:F.includes("handtrack"))&&(e.models.handtrack=ho(e.config)),e.config.hand.enabled&&e.config.hand.landmarks&&!e.models.handskeleton&&((Y=(H=e.config.hand.detector)==null?void 0:H.modelPath)==null?void 0:Y.includes("handtrack"))&&(e.models.handskeleton=bo(e.config)),e.config.object.enabled&&!e.models.centernet&&((x0=(J=e.config.object)==null?void 0:J.modelPath)==null?void 0:x0.includes("centernet"))&&(e.models.centernet=m3(e.config)),e.config.object.enabled&&!e.models.nanodet&&((G0=(E=e.config.object)==null?void 0:E.modelPath)==null?void 0:G0.includes("nanodet"))&&(e.models.nanodet=Io(e.config)),e.config.segmentation.enabled&&!e.models.segmentation&&(e.models.segmentation=X1(e.config));for await(let B0 of Object.keys(e.models))e.models[B0]&&typeof e.models[B0]!="undefined"&&(e.models[B0]=await e.models[B0])}async function Y1(e){let t=["const","placeholder","noop","pad","squeeze","add","sub","mul","div"];for(let o of Object.keys(e.models)){let n=e.models[o];if(!n)continue;let r=[],A=n==null?void 0:n.executor;if(A&&A.graph.nodes)for(let a of Object.values(A.graph.nodes)){let i=a.op.toLowerCase();r.includes(i)||r.push(i)}else!A&&e.config.debug&&p("model signature not determined:",o);let s=[];for(let a of r)!t.includes(a)&&!e.env.kernels.includes(a)&&!e.env.kernels.includes(a.replace("_",""))&&!e.env.kernels.includes(a.replace("native",""))&&!e.env.kernels.includes(a.replace("v2",""))&&s.push(a);e.config.debug&&s.length>0&&p("model validation failed:",o,s)}}var t0={name:"humangl",priority:999,canvas:null,gl:null,extensions:[],webGLattr:{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!1,desynchronized:!0}};function BA(){let e=t0.gl;!e||(t0.extensions=e.getSupportedExtensions())}async function Xo(e){var t;if(e.config.backend==="humangl"&&(t0.name in y0.engine().registry&&(!t0.gl||!t0.gl.getParameter(t0.gl.VERSION))&&(p("error: humangl backend invalid context"),P5(e)),!y0.findBackend(t0.name))){try{t0.canvas=await R0(100,100)}catch(n){p("error: cannot create canvas:",n);return}try{if(t0.gl=(t=t0.canvas)==null?void 0:t.getContext("webgl2",t0.webGLattr),!t0.gl.getParameter(t0.gl.VERSION).includes("2.0")){p("override: using fallback webgl backend as webgl 2.0 is not detected"),e.config.backend="webgl";return}t0.canvas&&(t0.canvas.addEventListener("webglcontextlost",async r=>{throw p("error: humangl:",r.type),p("possible browser memory leak using webgl or conflict with multiple backend registrations"),e.emit("error"),new Error("backend error: webgl context lost")}),t0.canvas.addEventListener("webglcontextrestored",r=>{p("error: humangl context restored:",r)}),t0.canvas.addEventListener("webglcontextcreationerror",r=>{p("error: humangl context create:",r)}))}catch(n){p("error: cannot get WebGL context:",n);return}try{y0.setWebGLContext(2,t0.gl)}catch(n){p("error: cannot set WebGL context:",n);return}try{let n=new y0.GPGPUContext(t0.gl);y0.registerBackend(t0.name,()=>new y0.MathBackendWebGL(n),t0.priority)}catch(n){p("error: cannot register WebGL backend:",n);return}try{y0.getKernelsForBackend("webgl").forEach(r=>{let A={...r,backendName:t0.name};y0.registerKernel(A)})}catch(n){p("error: cannot update WebGL backend registration:",n);return}let o=y0.backend().getGPGPUContext?y0.backend().getGPGPUContext().gl:null;if(o)p(`humangl webgl version:${o.getParameter(o.VERSION)} renderer:${o.getParameter(o.RENDERER)}`);else{p("error: no current gl context:",o,t0.gl);return}try{y0.ENV.set("WEBGL_VERSION",2)}catch(n){p("error: cannot set WebGL backend flags:",n);return}BA(),p("backend registered:",t0.name)}}var I=Z(D());function HA(){if(!v.kernels.includes("mod")){let e={kernelName:"Mod",backendName:I.getBackend(),kernelFunc:t=>I.tidy(()=>I.sub(t.inputs.a,I.mul(I.div(t.inputs.a,t.inputs.b),t.inputs.b)))};I.registerKernel(e),v.kernels.push("mod")}if(!v.kernels.includes("floormod")){let e={kernelName:"FloorMod",backendName:I.getBackend(),kernelFunc:t=>I.tidy(()=>I.floorDiv(t.inputs.a/t.inputs.b)*t.inputs.b+I.mod(t.inputs.a,t.inputs.b))};I.registerKernel(e),v.kernels.push("floormod")}}async function v5(e,t=!1){if(e.state="backend",t||v.initial||e.config.backend&&e.config.backend.length>0&&I.getBackend()!==e.config.backend){let o=h();if(e.config.backend&&e.config.backend.length>0){if(typeof window=="undefined"&&typeof WorkerGlobalScope!="undefined"&&e.config.debug&&e.config.debug&&p("running inside web worker"),v.browser&&e.config.backend==="tensorflow"&&(e.config.debug&&p("override: backend set to tensorflow while running in browser"),e.config.backend="humangl"),v.node&&(e.config.backend==="webgl"||e.config.backend==="humangl")&&(e.config.debug&&p(`override: backend set to ${e.config.backend} while running in nodejs`),e.config.backend="tensorflow"),v.browser&&e.config.backend==="webgpu")if(typeof navigator=="undefined"||typeof navigator.gpu=="undefined")p("override: backend set to webgpu but browser does not support webgpu"),e.config.backend="humangl";else{let r=await navigator.gpu.requestAdapter();if(e.config.debug&&p("enumerated webgpu adapter:",r),!r)p("override: backend set to webgpu but browser reports no available gpu"),e.config.backend="humangl";else{let A="requestAdapterInfo"in r?await r.requestAdapterInfo():void 0;p("webgpu adapter info:",A)}}e.config.backend==="humangl"&&await Xo(e);let n=Object.keys(I.engine().registryFactory);if(e.config.debug&&p("available backends:",n),n.includes(e.config.backend)||(p(`error: backend ${e.config.backend} not found in registry`),e.config.backend=v.node?"tensorflow":"webgl",e.config.debug&&p(`override: setting backend ${e.config.backend}`)),e.config.debug&&p("setting backend:",e.config.backend),e.config.backend==="wasm"){try{I.env().set("CANVAS2D_WILL_READ_FREQUENTLY",!0)}catch(s){}if(e.config.debug&&p("wasm path:",e.config.wasmPath),typeof(I==null?void 0:I.setWasmPaths)!="undefined")await I.setWasmPaths(e.config.wasmPath,e.config.wasmPlatformFetch);else throw new Error("backend error: attempting to use wasm backend but wasm path is not set");let r=await I.env().getAsync("WASM_HAS_SIMD_SUPPORT"),A=await I.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");e.config.debug&&p(`wasm execution: ${r?"SIMD":"no SIMD"} ${A?"multithreaded":"singlethreaded"}`),e.config.debug&&!r&&p("warning: wasm simd support is not enabled")}try{await I.setBackend(e.config.backend),await I.ready(),jt()}catch(r){return p("error: cannot set backend:",e.config.backend,r),!1}}if(I.getBackend()==="humangl"&&(I.ENV.set("CHECK_COMPUTATION_FOR_ERRORS",!1),I.ENV.set("WEBGL_CPU_FORWARD",!0),I.ENV.set("WEBGL_USE_SHAPES_UNIFORMS",!0),I.ENV.set("CPU_HANDOFF_SIZE_THRESHOLD",256),typeof e.config.deallocate!="undefined"&&e.config.deallocate&&(p("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),I.ENV.set("WEBGL_DELETE_TEXTURE_THRESHOLD",0)),I.backend().getGPGPUContext)){let n=await I.backend().getGPGPUContext().gl;e.config.debug&&p(`gl version:${n.getParameter(n.VERSION)} renderer:${n.getParameter(n.RENDERER)}`)}I.getBackend(),I.enableProdMode(),await I.ready(),e.performance.initBackend=Math.trunc(h()-o),e.config.backend=I.getBackend(),await v.updateBackend(),HA()}return!0}function x5(e,t){for(let o of e){let n={kernelName:o,backendName:t.backend,kernelFunc:()=>{t.debug&&p("kernelFunc",o,t.backend)}};I.registerKernel(n)}v.kernels=I.getKernelsForBackend(I.getBackend()).map(o=>o.kernelName.toLowerCase())}var tt={};ue(tt,{all:()=>et,body:()=>y2,canvas:()=>$1,face:()=>l2,gesture:()=>d2,hand:()=>x2,object:()=>c2,options:()=>P0,person:()=>_1});var V0=e=>{if(!e)p("draw error: invalid canvas");else if(!e.getContext)p("draw error: canvas context not defined");else{let t=e.getContext("2d");if(!t)p("draw error: cannot get canvas context");else return t}return null},Xe=e=>Math.round(e*180/Math.PI),me=(e,t)=>{if(!t.useDepth||typeof e=="undefined")return t.color;let o=Uint8ClampedArray.from([127+2*e,127-2*e,255]);return`rgba(${o[0]}, ${o[1]}, ${o[2]}, ${t.alpha})`};function pe(e,t,o,n,r){e.fillStyle=me(n,r),e.beginPath(),e.arc(t,o,r.pointSize,0,2*Math.PI),e.fill()}function re(e,t,o,n,r,A){if(e.beginPath(),e.lineWidth=A.lineWidth,A.useCurves){let s=(t+t+n)/2,a=(o+o+r)/2;e.ellipse(s,a,n/2,r/2,0,0,2*Math.PI)}else e.moveTo(t+A.roundRect,o),e.lineTo(t+n-A.roundRect,o),e.quadraticCurveTo(t+n,o,t+n,o+A.roundRect),e.lineTo(t+n,o+r-A.roundRect),e.quadraticCurveTo(t+n,o+r,t+n-A.roundRect,o+r),e.lineTo(t+A.roundRect,o+r),e.quadraticCurveTo(t,o+r,t,o+r-A.roundRect),e.lineTo(t,o+A.roundRect),e.quadraticCurveTo(t,o,t+A.roundRect,o),e.closePath();e.stroke()}function K1(e,t,o){if(!(t.length<2)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let n of t)e.strokeStyle=me(n[2]||0,o),e.lineTo(Math.trunc(n[0]),Math.trunc(n[1]));e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function Uo(e,t,o){if(!(t.length<2)){if(e.lineWidth=o.lineWidth,!o.useCurves||t.length<=2){K1(e,t,o);return}e.moveTo(t[0][0],t[0][1]);for(let n=0;n<t.length-2;n++){let r=(t[n][0]+t[n+1][0])/2,A=(t[n][1]+t[n+1][1])/2;e.quadraticCurveTo(t[n][0],t[n][1],r,A)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function J1(e,t,o,n=5){let r,A,s;e.beginPath(),e.moveTo(t[0],t[1]),e.lineTo(o[0],o[1]),r=Math.atan2(o[1]-t[1],o[0]-t[0]),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.moveTo(A,s),r+=1/3*(2*Math.PI),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.lineTo(A,s),r+=1/3*(2*Math.PI),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.lineTo(A,s),e.closePath(),e.stroke(),e.fill()}var P0={color:"rgba(173, 216, 230, 0.6)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",alpha:.5,font:'small-caps 16px "Segoe UI"',lineHeight:18,lineWidth:4,pointSize:2,roundRect:8,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawAttention:!0,drawGestures:!0,drawPolygons:!0,drawGaze:!0,fillPolygons:!1,useDepth:!0,useCurves:!1};var U;function DA(e,t){if(U.drawLabels){let o=[];if(o.push(`face: ${Math.trunc(100*e.score)}%`),e.genderScore&&o.push(`${e.gender||""} ${Math.trunc(100*e.genderScore)}%`),e.age&&o.push(`age: ${e.age||""}`),e.iris&&o.push(`distance: ${e.iris}`),e.real&&o.push(`real: ${Math.trunc(100*e.real)}%`),e.live&&o.push(`live: ${Math.trunc(100*e.live)}%`),e.emotion&&e.emotion.length>0){let n=e.emotion.map(r=>`${Math.trunc(100*r.score)}% ${r.emotion}`);n.length>3&&(n.length=3),o.push(n.join(" "))}e.rotation&&e.rotation.angle&&e.rotation.gaze&&(e.rotation.angle.roll&&o.push(`roll: ${Xe(e.rotation.angle.roll)}\xB0 yaw:${Xe(e.rotation.angle.yaw)}\xB0 pitch:${Xe(e.rotation.angle.pitch)}\xB0`),e.rotation.gaze.bearing&&o.push(`gaze: ${Xe(e.rotation.gaze.bearing)}\xB0`)),o.length===0&&o.push("face"),t.fillStyle=U.color;for(let n=o.length-1;n>=0;n--){let r=Math.max(e.box[0],0),A=n*U.lineHeight+e.box[1];U.shadowColor&&U.shadowColor!==""&&(t.fillStyle=U.shadowColor,t.fillText(o[n],r+5,A+16)),t.fillStyle=U.labelColor,t.fillText(o[n],r+4,A+15)}}}function ZA(e,t){if(e.annotations&&e.annotations.leftEyeIris&&e.annotations.leftEyeIris[0]){t.strokeStyle=U.useDepth?"rgba(255, 200, 255, 0.3)":U.color,t.beginPath();let o=Math.abs(e.annotations.leftEyeIris[3][0]-e.annotations.leftEyeIris[1][0])/2,n=Math.abs(e.annotations.leftEyeIris[4][1]-e.annotations.leftEyeIris[2][1])/2;t.ellipse(e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),U.fillPolygons&&(t.fillStyle=U.useDepth?"rgba(255, 255, 200, 0.3)":U.color,t.fill())}if(e.annotations&&e.annotations.rightEyeIris&&e.annotations.rightEyeIris[0]){t.strokeStyle=U.useDepth?"rgba(255, 200, 255, 0.3)":U.color,t.beginPath();let o=Math.abs(e.annotations.rightEyeIris[3][0]-e.annotations.rightEyeIris[1][0])/2,n=Math.abs(e.annotations.rightEyeIris[4][1]-e.annotations.rightEyeIris[2][1])/2;t.ellipse(e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),U.fillPolygons&&(t.fillStyle=U.useDepth?"rgba(255, 255, 200, 0.3)":U.color,t.fill())}}function XA(e,t){var o;if(U.drawGaze&&((o=e.rotation)==null?void 0:o.angle)&&typeof Path2D!="undefined"){t.strokeStyle="pink";let n=e.box[0]+e.box[2]/2-e.box[3]*Xe(e.rotation.angle.yaw)/90,r=e.box[1]+e.box[3]/2+e.box[2]*Xe(e.rotation.angle.pitch)/90,A=new Path2D(`
+`;var C5=(e,t,o)=>{let n=new RegExp("\\b"+t+" \\w+ (\\w+)","ig");e.replace(n,(r,A)=>(o[A]=0,r))},I5=class{constructor(t,o,n){T(this,"uniform",{});T(this,"attribute",{});T(this,"gl");T(this,"id");T(this,"compile",(t,o)=>{let n=this.gl.createShader(o);return n?(this.gl.shaderSource(n,t),this.gl.compileShader(n),this.gl.getShaderParameter(n,this.gl.COMPILE_STATUS)?n:(p(`filter: gl compile failed: ${this.gl.getShaderInfoLog(n)}`),null)):(p("filter: could not create shader"),null)});this.gl=t;let r=this.compile(o,this.gl.VERTEX_SHADER),A=this.compile(n,this.gl.FRAGMENT_SHADER);if(this.id=this.gl.createProgram(),!(!r||!A)){if(!this.id){p("filter: could not create webgl program");return}if(this.gl.attachShader(this.id,r),this.gl.attachShader(this.id,A),this.gl.linkProgram(this.id),!this.gl.getProgramParameter(this.id,this.gl.LINK_STATUS)){p(`filter: gl link failed: ${this.gl.getProgramInfoLog(this.id)}`);return}this.gl.useProgram(this.id),C5(o,"attribute",this.attribute);for(let s in this.attribute)this.attribute[s]=this.gl.getAttribLocation(this.id,s);C5(o,"uniform",this.uniform),C5(n,"uniform",this.uniform);for(let s in this.uniform)this.uniform[s]=this.gl.getUniformLocation(this.id,s)}}};function vt(){let e=0,t=null,o=!1,n=-1,r=[null,null],A=[],s=null,a=null,i=R0(100,100),x={},c={INTERMEDIATE:1},l=i.getContext("webgl");if(!l){p("filter: cannot get webgl context");return}this.gl=l;function y(b,d){if(!(b===i.width&&d===i.height)){if(i.width=b,i.height=d,!s){let M=new Float32Array([-1,-1,0,1,1,-1,1,1,-1,1,0,0,-1,1,0,0,1,-1,1,1,1,1,1,0]);s=l.createBuffer(),l.bindBuffer(l.ARRAY_BUFFER,s),l.bufferData(l.ARRAY_BUFFER,M,l.STATIC_DRAW),l.pixelStorei(l.UNPACK_PREMULTIPLY_ALPHA_WEBGL,!0)}l.viewport(0,0,i.width,i.height),r=[null,null]}}function f(b,d){let M=l.createFramebuffer();l.bindFramebuffer(l.FRAMEBUFFER,M);let S=l.createRenderbuffer();l.bindRenderbuffer(l.RENDERBUFFER,S);let w=l.createTexture();return l.bindTexture(l.TEXTURE_2D,w),l.texImage2D(l.TEXTURE_2D,0,l.RGBA,b,d,0,l.RGBA,l.UNSIGNED_BYTE,null),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MAG_FILTER,l.LINEAR),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MIN_FILTER,l.LINEAR),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_S,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_T,l.CLAMP_TO_EDGE),l.framebufferTexture2D(l.FRAMEBUFFER,l.COLOR_ATTACHMENT0,l.TEXTURE_2D,w,0),l.bindTexture(l.TEXTURE_2D,null),l.bindFramebuffer(l.FRAMEBUFFER,null),{fbo:M,texture:w}}function u(b){return r[b]=r[b]||f(i.width,i.height),r[b]}function m(b=0){if(!a)return;let d=null,M=null,S=!1;e===0?d=t:d=u(n).texture||null,e++,o&&!(b&c.INTERMEDIATE)?(M=null,S=e%2===0):(n=(n+1)%2,M=u(n).fbo||null),l.bindTexture(l.TEXTURE_2D,d),l.bindFramebuffer(l.FRAMEBUFFER,M),l.uniform1f(a.uniform.flipY,S?-1:1),l.drawArrays(l.TRIANGLES,0,6)}function P(b){if(x[b])return a=x[b],l.useProgram((a?a.id:null)||null),a;if(a=new I5(l,ht,b),!a)return p("filter: could not get webgl program"),null;let d=Float32Array.BYTES_PER_ELEMENT,M=4*d;return l.enableVertexAttribArray(a.attribute.pos),l.vertexAttribPointer(a.attribute.pos,2,l.FLOAT,!1,M,0*d),l.enableVertexAttribArray(a.attribute.uv),l.vertexAttribPointer(a.attribute.uv,2,l.FLOAT,!1,M,2*d),x[b]=a,a}let g={colorMatrix:b=>{let d=new Float32Array(b);d[4]/=255,d[9]/=255,d[14]/=255,d[19]/=255;let M=d[18]===1&&d[3]===0&&d[8]===0&&d[13]===0&&d[15]===0&&d[16]===0&&d[17]===0&&d[19]===0?gt:bt,S=P(M);!S||(l.uniform1fv(S.uniform.m,d),m())},brightness:b=>{let d=(b||0)+1;g.colorMatrix([d,0,0,0,0,0,d,0,0,0,0,0,d,0,0,0,0,0,1,0])},saturation:b=>{let d=(b||0)*2/3+1,M=(d-1)*-.5;g.colorMatrix([d,M,M,0,0,M,d,M,0,0,M,M,d,0,0,0,0,0,1,0])},desaturate:()=>{g.saturation(-1)},contrast:b=>{let d=(b||0)+1,M=-128*(d-1);g.colorMatrix([d,0,0,0,M,0,d,0,0,M,0,0,d,0,M,0,0,0,1,0])},negative:()=>{g.contrast(-2)},hue:b=>{b=(b||0)/180*Math.PI;let d=Math.cos(b),M=Math.sin(b),S=.213,w=.715,j=.072;g.colorMatrix([S+d*(1-S)+M*-S,w+d*-w+M*-w,j+d*-j+M*(1-j),0,0,S+d*-S+M*.143,w+d*(1-w)+M*.14,j+d*-j+M*-.283,0,0,S+d*-S+M*-(1-S),w+d*-w+M*w,j+d*(1-j)+M*j,0,0,0,0,0,1,0])},desaturateLuminance:()=>{g.colorMatrix([.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,.2764723,.929708,.0938197,0,-37.1,0,0,0,1,0])},sepia:()=>{g.colorMatrix([.393,.7689999,.18899999,0,0,.349,.6859999,.16799999,0,0,.272,.5339999,.13099999,0,0,0,0,0,1,0])},brownie:()=>{g.colorMatrix([.5997023498159715,.34553243048391263,-.2708298674538042,0,47.43192855600873,-.037703249837783157,.8609577587992641,.15059552388459913,0,-36.96841498319127,.24113635128153335,-.07441037908422492,.44972182064877153,0,-7.562075277591283,0,0,0,1,0])},vintagePinhole:()=>{g.colorMatrix([.6279345635605994,.3202183420819367,-.03965408211312453,0,9.651285835294123,.02578397704808868,.6441188644374771,.03259127616149294,0,7.462829176470591,.0466055556782719,-.0851232987247891,.5241648018700465,0,5.159190588235296,0,0,0,1,0])},kodachrome:()=>{g.colorMatrix([1.1285582396593525,-.3967382283601348,-.03992559172921793,0,63.72958762196502,-.16404339962244616,1.0835251566291304,-.05498805115633132,0,24.732407896706203,-.16786010706155763,-.5603416277695248,1.6014850761964943,0,35.62982807460946,0,0,0,1,0])},technicolor:()=>{g.colorMatrix([1.9125277891456083,-.8545344976951645,-.09155508482755585,0,11.793603434377337,-.3087833385928097,1.7658908555458428,-.10601743074722245,0,-70.35205161461398,-.231103377548616,-.7501899197440212,1.847597816108189,0,30.950940869491138,0,0,0,1,0])},polaroid:()=>{g.colorMatrix([1.438,-.062,-.062,0,0,-.122,1.378,-.122,0,0,-.016,-.016,1.483,0,0,0,0,0,1,0])},shiftToBGR:()=>{g.colorMatrix([0,0,1,0,0,0,1,0,0,0,1,0,0,0,0,0,0,0,1,0])},convolution:b=>{let d=new Float32Array(b),M=1/i.width,S=1/i.height,w=P(Rt);!w||(l.uniform1fv(w.uniform.m,d),l.uniform2f(w.uniform.px,M,S),m())},detectEdges:()=>{g.convolution.call(this,[0,1,0,1,-4,1,0,1,0])},sobelX:()=>{g.convolution.call(this,[-1,0,1,-2,0,2,-1,0,1])},sobelY:()=>{g.convolution.call(this,[-1,-2,-1,0,0,0,1,2,1])},sharpen:b=>{let d=b||1;g.convolution.call(this,[0,-1*d,0,-1*d,1+4*d,-1*d,0,-1*d,0])},emboss:b=>{let d=b||1;g.convolution.call(this,[-2*d,-1*d,0,-1*d,1,1*d,0,1*d,2*d])},blur:b=>{let d=b/7/i.width,M=b/7/i.height,S=P(Pt);!S||(l.uniform2f(S.uniform.px,0,M),m(c.INTERMEDIATE),l.uniform2f(S.uniform.px,d,0),m())},pixelate:b=>{let d=b/i.width,M=b/i.height,S=P(Mt);!S||(l.uniform2f(S.uniform.size,d,M),m())}};this.add=function(b){let d=Array.prototype.slice.call(arguments,1),M=g[b];A.push({func:M,args:d})},this.reset=function(){A=[]},this.get=function(){return A},this.apply=function(b){y(b.width,b.height),e=0,t||(t=l.createTexture()),l.bindTexture(l.TEXTURE_2D,t),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_S,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_WRAP_T,l.CLAMP_TO_EDGE),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MIN_FILTER,l.NEAREST),l.texParameteri(l.TEXTURE_2D,l.TEXTURE_MAG_FILTER,l.NEAREST),l.texImage2D(l.TEXTURE_2D,0,l.RGBA,l.RGBA,l.UNSIGNED_BYTE,b);for(let d=0;d<A.length;d++){o=d===A.length-1;let M=A[d];M.func.apply(this,M.args||[])}return i},this.draw=function(b){return this.add("brightness",0),this.apply(b)}}var X=Z(D());async function N2(e){let t=e.shape.length===4?X.squeeze(e):e,o=X.split(t,3,2),n=[X.min(o[0]),X.min(o[1]),X.min(o[2])],r=[X.max(o[0]),X.max(o[1]),X.max(o[2])],A=await Promise.all(r.map(f=>f.data())),s=.99*Math.max(A[0][0],A[1][0],A[2][0]),a=[X.sub(o[0],n[0]),X.sub(o[1],n[1]),X.sub(o[2],n[2])],i=[X.sub(r[0],n[0]),X.sub(r[1],n[1]),X.sub(r[2],n[2])],x=[X.div(s,i[0]),X.div(s,i[1]),X.div(s,i[2])],c=[X.mul(a[0],x[0]),X.mul(a[1],x[1]),X.mul(a[2],x[2])],l=X.stack([c[0],c[1],c[2]],2),y=X.reshape(l,[1,t.shape[0],t.shape[1],3]);return X.dispose([...o,...n,...r,...a,...i,...x,...c,l,t]),y}var L2=3840,q=null,l0=null,Ue=null,e0,ae={inputSum:0,cacheDiff:1,sumMethod:0,inputTensor:void 0};function R0(e,t){let o;if(v.browser)if(v.worker){if(typeof OffscreenCanvas=="undefined")throw new Error("canvas error: attempted to run in web worker but OffscreenCanvas is not supported");o=new OffscreenCanvas(e,t)}else{if(typeof document=="undefined")throw new Error("canvas error: attempted to run in browser but DOM is not defined");o=document.createElement("canvas"),o.width=e,o.height=t}else typeof v.Canvas!="undefined"?o=new v.Canvas(e,t):typeof globalThis.Canvas!="undefined"&&(o=new globalThis.Canvas(e,t));return o}function W2(e,t){let o=t||R0(e.width,e.height);return o.getContext("2d").drawImage(e,0,0),o}async function Ye(e,t,o=!0){if(!e)return t.debug&&p("input error: input is missing"),{tensor:null,canvas:null};if(!(e instanceof O.Tensor)&&!(typeof Image!="undefined"&&e instanceof Image)&&!(typeof v.Canvas!="undefined"&&e instanceof v.Canvas)&&!(typeof globalThis.Canvas!="undefined"&&e instanceof globalThis.Canvas)&&!(typeof ImageData!="undefined"&&e instanceof ImageData)&&!(typeof ImageBitmap!="undefined"&&e instanceof ImageBitmap)&&!(typeof HTMLImageElement!="undefined"&&e instanceof HTMLImageElement)&&!(typeof HTMLMediaElement!="undefined"&&e instanceof HTMLMediaElement)&&!(typeof HTMLVideoElement!="undefined"&&e instanceof HTMLVideoElement)&&!(typeof HTMLCanvasElement!="undefined"&&e instanceof HTMLCanvasElement)&&!(typeof OffscreenCanvas!="undefined"&&e instanceof OffscreenCanvas))throw new Error("input error: type is not recognized");if(e instanceof O.Tensor){let n=null;if(e.isDisposedInternal)throw new Error("input error: attempted to use tensor but it is disposed");if(!e.shape)throw new Error("input error: attempted to use tensor without a shape");if(e.shape.length===3){if(e.shape[2]===3)n=O.expandDims(e,0);else if(e.shape[2]===4){let r=O.slice3d(e,[0,0,0],[-1,-1,3]);n=O.expandDims(r,0),O.dispose(r)}}else e.shape.length===4&&(e.shape[3]===3?n=O.clone(e):e.shape[3]===4&&(n=O.slice4d(e,[0,0,0,0],[-1,-1,-1,3])));if(n==null||n.shape.length!==4||n.shape[0]!==1||n.shape[3]!==3)throw new Error(`input error: attempted to use tensor with unrecognized shape: ${e.shape}`);if(n.dtype==="int32"){let r=O.cast(n,"float32");O.dispose(n),n=r}return{tensor:n,canvas:t.filter.return?l0:null}}else{if(typeof e.readyState!="undefined"&&e.readyState<=2)return t.debug&&p("input stream is not ready"),{tensor:null,canvas:q};let n=e.naturalWidth||e.videoWidth||e.width||e.shape&&e.shape[1]>0,r=e.naturalHeight||e.videoHeight||e.height||e.shape&&e.shape[2]>0;if(!n||!r)return t.debug&&p("cannot determine input dimensions"),{tensor:null,canvas:q};let A=n,s=r;if(A>L2&&(A=L2,s=Math.trunc(A*r/n)),s>L2&&(s=L2,A=Math.trunc(s*n/r)),(t.filter.width||0)>0?A=t.filter.width:(t.filter.height||0)>0&&(A=n*((t.filter.height||0)/r)),(t.filter.height||0)>0?s=t.filter.height:(t.filter.width||0)>0&&(s=r*((t.filter.width||0)/n)),!A||!s)throw new Error("input error: cannot determine dimension");(!q||(q==null?void 0:q.width)!==A||(q==null?void 0:q.height)!==s)&&(q=R0(A,s));let a=q.getContext("2d");if(typeof ImageData!="undefined"&&e instanceof ImageData?a.putImageData(e,0,0):t.filter.flip&&typeof a.translate!="undefined"?(a.translate(n,0),a.scale(-1,1),a.drawImage(e,0,0,n,r,0,0,q==null?void 0:q.width,q==null?void 0:q.height),a.setTransform(1,0,0,1,0,0)):a.drawImage(e,0,0,n,r,0,0,q==null?void 0:q.width,q==null?void 0:q.height),(!l0||q.width!==l0.width||(q==null?void 0:q.height)!==(l0==null?void 0:l0.height))&&(l0=R0(q.width,q.height)),t.filter.enabled&&v.webgl.supported?(e0||(e0=v.browser?new vt:null),v.filter=!!e0,!e0||!e0.add?(t.debug&&p("input process error: cannot initialize filters"),v.webgl.supported=!1,t.filter.enabled=!1,W2(q,l0)):(e0.reset(),t.filter.brightness!==0&&e0.add("brightness",t.filter.brightness),t.filter.contrast!==0&&e0.add("contrast",t.filter.contrast),t.filter.sharpness!==0&&e0.add("sharpen",t.filter.sharpness),t.filter.blur!==0&&e0.add("blur",t.filter.blur),t.filter.saturation!==0&&e0.add("saturation",t.filter.saturation),t.filter.hue!==0&&e0.add("hue",t.filter.hue),t.filter.negative&&e0.add("negative"),t.filter.sepia&&e0.add("sepia"),t.filter.vintage&&e0.add("brownie"),t.filter.sepia&&e0.add("sepia"),t.filter.kodachrome&&e0.add("kodachrome"),t.filter.technicolor&&e0.add("technicolor"),t.filter.polaroid&&e0.add("polaroid"),t.filter.pixelate!==0&&e0.add("pixelate",t.filter.pixelate),e0.get()>0?l0=e0.apply(q):l0=e0.draw(q))):(W2(q,l0),e0&&(e0=null),v.filter=!!e0),!o)return{tensor:null,canvas:l0};if(!l0)throw new Error("canvas error: cannot create output");let i,x=3;if(typeof ImageData!="undefined"&&e instanceof ImageData||e.data&&e.width&&e.height)if(v.browser&&O.browser)i=O.browser?O.browser.fromPixels(e):null;else{x=e.data.length/e.height/e.width;let y=new Uint8Array(e.data.buffer);i=O.tensor(y,[e.height,e.width,x],"int32")}else if((!Ue||l0.width!==Ue.width||l0.height!==Ue.height)&&(Ue=R0(l0.width,l0.height)),O.browser&&v.browser)t.backend==="webgl"||t.backend==="humangl"||t.backend==="webgpu"?i=O.browser.fromPixels(l0):(Ue=W2(l0),i=O.browser.fromPixels(Ue));else{let u=W2(l0).getContext("2d").getImageData(0,0,A,s);x=u.data.length/A/s;let m=new Uint8Array(u.data.buffer);i=O.tensor(m,[A,s,x])}if(x===4){let y=O.slice3d(i,[0,0,0],[-1,-1,3]);O.dispose(i),i=y}if(!i)throw new Error("input error: cannot create tensor");let c=O.cast(i,"float32"),l=t.filter.equalization?await N2(c):O.expandDims(c,0);return O.dispose([i,c]),{tensor:l,canvas:t.filter.return?l0:null}}}async function Tt(e,t){let o=!1;if(e.cacheSensitivity===0||!t.shape||t.shape.length!==4||t.shape[1]>2048||t.shape[2]>2048)return o;if(!ae.inputTensor)ae.inputTensor=O.clone(t);else if(ae.inputTensor.shape[1]!==t.shape[1]||ae.inputTensor.shape[2]!==t.shape[2])O.dispose(ae.inputTensor),ae.inputTensor=O.clone(t);else{let n={};n.diff=O.sub(t,ae.inputTensor),n.squared=O.mul(n.diff,n.diff),n.sum=O.sum(n.squared);let A=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;O.dispose([ae.inputTensor,n.diff,n.squared,n.sum]),ae.inputTensor=O.clone(t),o=A<=(e.cacheSensitivity||0)}return o}async function wt(e,t,o){let n={};if(!t||!o||t.shape.length!==4||t.shape.length!==o.shape.length)return e.debug||p("invalid input tensor or tensor shapes do not match:",t.shape,o.shape),0;if(t.shape[0]!==1||o.shape[0]!==1||t.shape[3]!==3||o.shape[3]!==3)return e.debug||p("input tensors must be of shape [1, height, width, 3]:",t.shape,o.shape),0;n.input1=O.clone(t),n.input2=t.shape[1]!==o.shape[1]||t.shape[2]!==o.shape[2]?O.image.resizeBilinear(o,[t.shape[1],t.shape[2]]):O.clone(o),n.diff=O.sub(n.input1,n.input2),n.squared=O.mul(n.diff,n.diff),n.sum=O.sum(n.squared);let A=(await n.sum.data())[0]/(t.shape[1]||1)/(t.shape[2]||1)/255/3;return O.dispose([n.input1,n.input2,n.diff,n.squared,n.sum]),A}var j5=class{constructor(){T(this,"browser");T(this,"node");T(this,"worker");T(this,"platform","");T(this,"agent","");T(this,"backends",[]);T(this,"initial");T(this,"filter");T(this,"tfjs");T(this,"offscreen");T(this,"perfadd",!1);T(this,"wasm",{supported:void 0,backend:void 0,simd:void 0,multithread:void 0});T(this,"webgl",{supported:void 0,backend:void 0,version:void 0,renderer:void 0});T(this,"webgpu",{supported:void 0,backend:void 0,adapter:void 0});T(this,"cpu",{model:void 0,flags:[]});T(this,"kernels",[]);T(this,"Canvas");T(this,"Image");T(this,"ImageData");if(this.browser=typeof navigator!="undefined",this.node=typeof process!="undefined"&&typeof process.versions!="undefined"&&typeof process.versions.node!="undefined",this.tfjs={version:p0.version["tfjs-core"]},this.offscreen=typeof OffscreenCanvas!="undefined",this.initial=!0,this.worker=this.browser&&this.offscreen?typeof WorkerGlobalScope!="undefined":void 0,typeof navigator!="undefined"){let t=navigator.userAgent.match(/\(([^()]+)\)/g);if(t&&t[0]){let o=t[0].match(/\(([^()]+)\)/g);this.platform=o&&o[0]?o[0].replace(/\(|\)/g,""):"",this.agent=navigator.userAgent.replace(t[0],""),this.platform[1]&&(this.agent=this.agent.replace(t[1],"")),this.agent=this.agent.replace(/  /g," ")}}else typeof process!="undefined"&&(this.platform=`${process.platform} ${process.arch}`,this.agent=`NodeJS ${process.version}`)}async updateBackend(){this.backends=Object.keys(p0.engine().registryFactory),this.wasm.supported=typeof WebAssembly!="undefined",this.wasm.backend=this.backends.includes("wasm"),this.wasm.supported&&this.wasm.backend&&p0.getBackend()==="wasm"&&(this.wasm.simd=await p0.env().getAsync("WASM_HAS_SIMD_SUPPORT"),this.wasm.multithread=await p0.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT"));let t=R0(100,100),o=t?t.getContext("webgl2"):void 0;if(this.webgl.supported=typeof o!="undefined",this.webgl.backend=this.backends.includes("webgl"),this.webgl.supported&&this.webgl.backend&&(p0.getBackend()==="webgl"||p0.getBackend()==="humangl")){let n=p0.backend().gpgpu!=="undefined"?await p0.backend().getGPGPUContext().gl:null;n&&(this.webgl.version=n.getParameter(n.VERSION),this.webgl.renderer=n.getParameter(n.RENDERER))}this.webgpu.supported=this.browser&&typeof navigator.gpu!="undefined",this.webgpu.backend=this.backends.includes("webgpu");try{this.webgpu.supported&&(this.webgpu.adapter=(await navigator.gpu.requestAdapter()).name)}catch(n){this.webgpu.supported=!1}try{this.kernels=p0.getKernelsForBackend(p0.getBackend()).map(n=>n.kernelName.toLowerCase())}catch(n){}}async updateCPU(){let t={model:"",flags:[]};this.node&&this.platform.startsWith("linux"),this.cpu?this.cpu=t:Object.defineProperty(this,"cpu",{value:t})}},v=new j5;var F2=Z(D());var O5={};ue(O5,{age:()=>Pn,antispoof:()=>Rn,blazeface:()=>wn,"blazeface-back":()=>vn,"blazeface-front":()=>Tn,"blazepose-detector2d":()=>kn,"blazepose-detector3d":()=>En,"blazepose-full":()=>zn,"blazepose-heavy":()=>Sn,"blazepose-lite":()=>Cn,default:()=>yr,efficientpose:()=>In,emotion:()=>jn,faceboxes:()=>On,facemesh:()=>Bn,"facemesh-attention":()=>Ln,"facemesh-attention-alt":()=>Nn,"facemesh-detection-full":()=>Wn,"facemesh-detection-short":()=>Fn,"facemesh-orig":()=>Gn,faceres:()=>Vn,"faceres-deep":()=>Hn,gear:()=>Dn,gender:()=>Xn,"gender-ssrnet-imdb":()=>Zn,handdetect:()=>qn,"handlandmark-full":()=>Un,"handlandmark-lite":()=>Yn,"handlandmark-sparse":()=>Kn,handskeleton:()=>Jn,handtrack:()=>Qn,iris:()=>_n,liveness:()=>$n,"mb3-centernet":()=>er,meet:()=>tr,mobileface:()=>or,mobilefacenet:()=>nr,"movenet-lightning":()=>rr,"movenet-multipose":()=>Ar,"movenet-thunder":()=>sr,nanodet:()=>ar,posenet:()=>ir,selfie:()=>lr});var Pn=161240,Rn=853098,vn=538928,Tn=402048,wn=538928,kn=7499400,En=5928856,zn=6338290,Sn=27501554,Cn=2725490,In=5651240,jn=820516,On=2013002,Nn=2387598,Ln=2382414,Wn=1026192,Fn=201268,Gn=2955780,Bn=1477958,Hn=13957620,Vn=6978814,Dn=1498916,Zn=161236,Xn=201808,qn=3515612,Un=5431368,Yn=2023432,Kn=5286322,Jn=5502280,Qn=2964837,_n=2599092,$n=592976,er=4030290,tr=372228,or=2183192,nr=5171976,rr=4650216,Ar=9448838,sr=12477112,ar=7574558,ir=5032780,lr=212886,yr={age:Pn,antispoof:Rn,"blazeface-back":vn,"blazeface-front":Tn,blazeface:wn,"blazepose-detector2d":kn,"blazepose-detector3d":En,"blazepose-full":zn,"blazepose-heavy":Sn,"blazepose-lite":Cn,efficientpose:In,emotion:jn,faceboxes:On,"facemesh-attention-alt":Nn,"facemesh-attention":Ln,"facemesh-detection-full":Wn,"facemesh-detection-short":Fn,"facemesh-orig":Gn,facemesh:Bn,"faceres-deep":Hn,faceres:Vn,gear:Dn,"gender-ssrnet-imdb":Zn,gender:Xn,handdetect:qn,"handlandmark-full":Un,"handlandmark-lite":Yn,"handlandmark-sparse":Kn,handskeleton:Jn,handtrack:Qn,iris:_n,liveness:$n,"mb3-centernet":er,meet:tr,mobileface:or,mobilefacenet:nr,"movenet-lightning":rr,"movenet-multipose":Ar,"movenet-thunder":sr,nanodet:ar,posenet:ir,selfie:lr};var v0={cacheModels:!0,cacheSupported:!0,verbose:!0,debug:!1,modelBasePath:""},q0={};async function xr(e,t){return v0.debug&&p("load model fetch:",e,t),fetch(e,t)}function kt(e){v0.cacheModels=e.cacheModels,v0.verbose=e.debug,v0.modelBasePath=e.modelBasePath}async function G(e){var x,c,l;let t=mt(v0.modelBasePath,e||"");t.toLowerCase().endsWith(".json")||(t+=".json");let o=t.includes("/")?t.split("/"):t.split("\\"),n=o[o.length-1].replace(".json",""),r="indexeddb://"+n;q0[n]={name:n,sizeFromManifest:0,sizeLoadedWeights:0,sizeDesired:O5[n],inCache:!1},v0.cacheSupported=typeof window!="undefined"&&typeof window.localStorage!="undefined"&&typeof window.indexedDB!="undefined";let A={};try{A=v0.cacheSupported&&v0.cacheModels?await F2.io.listModels():{}}catch(y){v0.cacheSupported=!1}q0[n].inCache=v0.cacheSupported&&v0.cacheModels&&Object.keys(A).includes(r);let s=typeof fetch=="undefined"?{}:{fetchFunc:(y,f)=>xr(y,f)},a=new F2.GraphModel(q0[n].inCache?r:t,s),i=!1;try{a.findIOHandler(),v0.debug&&p("model load handler:",a.handler);let y=await a.handler.load();q0[n].sizeFromManifest=((x=y==null?void 0:y.weightData)==null?void 0:x.byteLength)||0,a.loadSync(y),q0[n].sizeLoadedWeights=((l=(c=a==null?void 0:a.artifacts)==null?void 0:c.weightData)==null?void 0:l.byteLength)||0,v0.verbose&&p("load model:",a.modelUrl,{bytes:q0[n].sizeLoadedWeights},v0),i=!0}catch(y){p("error loading model:",t,y)}if(i&&v0.cacheModels&&v0.cacheSupported&&!q0[n].inCache)try{let y=await a.save(r);p("model saved:",r,y)}catch(y){p("error saving model:",t,y)}return a}var ee=Z(D());var N5="2.9.1";var s0=Z(D());var R5={};ue(R5,{Models:()=>C2,getModelStats:()=>q1,load:()=>U1,reset:()=>P5,validate:()=>Y1});var G2=Z(D());var D0,L5=[],fr=["white","black","asian","indian","other"],mr=[15,23,28,35.5,45.5,55.5,65],Et=0,zt=0,W5=Number.MAX_SAFE_INTEGER;async function St(e){var t;return v.initial&&(D0=null),D0?e.debug&&p("cached model:",D0.modelUrl):D0=await G((t=e.face.gear)==null?void 0:t.modelPath),D0}async function F5(e,t,o,n){var s,a;if(!D0)return{age:0,gender:"unknown",genderScore:0,race:[]};let r=W5<(((s=t.face.gear)==null?void 0:s.skipFrames)||0),A=(((a=t.face.gear)==null?void 0:a.skipTime)||0)>h()-zt;return t.skipAllowed&&A&&r&&Et===n&&L5[o]?(W5++,L5[o]):(W5=0,new Promise(async i=>{var g,b;if(!(D0!=null&&D0.inputs[0].shape))return;let x={},c=[[0,.1,.9,.9]];x.resize=G2.image.cropAndResize(e,c,[0],[D0.inputs[0].shape[2],D0.inputs[0].shape[1]]);let l={age:0,gender:"unknown",genderScore:0,race:[]};(g=t.face.gear)!=null&&g.enabled&&([x.age,x.gender,x.race]=D0.execute(x.resize,["age_output","gender_output","race_output"]));let y=await x.gender.data();l.gender=y[0]>y[1]?"male":"female",l.genderScore=Math.round(100*(y[0]>y[1]?y[0]:y[1]))/100;let f=await x.race.data();for(let d=0;d<f.length;d++)f[d]>(((b=t.face.gear)==null?void 0:b.minConfidence)||.2)&&l.race.push({score:Math.round(100*f[d])/100,race:fr[d]});l.race.sort((d,M)=>M.score-d.score);let m=Array.from(await x.age.data()).map((d,M)=>[mr[M],d]).sort((d,M)=>M[1]-d[1]),P=m[0][0];for(let d=1;d<m.length;d++)P+=m[d][1]*(m[d][0]-P);l.age=Math.round(10*P)/10,Object.keys(x).forEach(d=>G2.dispose(x[d])),L5[o]=l,Et=n,zt=h(),i(l)}))}var Ke=Z(D());var be=Z(D()),V={tf255:255,tf1:1,tf2:2,tf05:.5,tf127:127.5,rgb:[.2989,.587,.114]};function It(){V.tf255=be.scalar(255,"float32"),V.tf1=be.scalar(1,"float32"),V.tf2=be.scalar(2,"float32"),V.tf05=be.scalar(.5,"float32"),V.tf127=be.scalar(127.5,"float32"),V.rgb=be.tensor1d([.2989,.587,.114],"float32")}var S0,B2=[],jt=0,Ot=0,G5=Number.MAX_SAFE_INTEGER;async function Nt(e){return v.initial&&(S0=null),S0?e.debug&&p("cached model:",S0.modelUrl):S0=await G(e.face.ssrnet.modelPathAge),S0}async function B5(e,t,o,n){var s,a,i,x;if(!S0)return{age:0};let r=G5<(((s=t.face.ssrnet)==null?void 0:s.skipFrames)||0),A=(((a=t.face.ssrnet)==null?void 0:a.skipTime)||0)>h()-Ot;return t.skipAllowed&&r&&A&&jt===n&&((i=B2[o])==null?void 0:i.age)&&((x=B2[o])==null?void 0:x.age)>0?(G5++,B2[o]):(G5=0,new Promise(async c=>{if(!(S0!=null&&S0.inputs)||!S0.inputs[0]||!S0.inputs[0].shape)return;let l={};l.resize=Ke.image.resizeBilinear(e,[S0.inputs[0].shape[2],S0.inputs[0].shape[1]],!1),l.enhance=Ke.mul(l.resize,V.tf255);let y={age:0};if(t.face.ssrnet.enabled&&(l.age=S0.execute(l.enhance)),l.age){let f=await l.age.data();y.age=Math.trunc(10*f[0])/10}Object.keys(l).forEach(f=>Ke.dispose(l[f])),B2[o]=y,jt=n,Ot=h(),c(y)}))}var u0=Z(D());var Z0,H2=[],Wt=0,Ft=0,H5=Number.MAX_SAFE_INTEGER,V5=[.2989,.587,.114];async function Gt(e){return v.initial&&(Z0=null),Z0?e.debug&&p("cached model:",Z0.modelUrl):Z0=await G(e.face.ssrnet.modelPathGender),Z0}async function D5(e,t,o,n){var s,a,i,x;if(!Z0)return{gender:"unknown",genderScore:0};let r=H5<(((s=t.face.ssrnet)==null?void 0:s.skipFrames)||0),A=(((a=t.face.ssrnet)==null?void 0:a.skipTime)||0)>h()-Ft;return t.skipAllowed&&r&&A&&Wt===n&&((i=H2[o])==null?void 0:i.gender)&&((x=H2[o])==null?void 0:x.genderScore)>0?(H5++,H2[o]):(H5=0,new Promise(async c=>{if(!(Z0!=null&&Z0.inputs[0].shape))return;let l={};l.resize=u0.image.resizeBilinear(e,[Z0.inputs[0].shape[2],Z0.inputs[0].shape[1]],!1),l.enhance=u0.tidy(()=>{let[u,m,P]=u0.split(l.resize,3,3),g=u0.mul(u,V5[0]),b=u0.mul(m,V5[1]),d=u0.mul(P,V5[2]),M=u0.addN([g,b,d]);return u0.mul(u0.sub(M,V.tf05),2)});let y={gender:"unknown",genderScore:0};t.face.ssrnet.enabled&&(l.gender=Z0.execute(l.enhance));let f=await l.gender.data();y.gender=f[0]>f[1]?"female":"male",y.genderScore=f[0]>f[1]?Math.trunc(100*f[0])/100:Math.trunc(100*f[1])/100,Object.keys(l).forEach(u=>u0.dispose(l[u])),H2[o]=y,Wt=n,Ft=h(),c(y)}))}var D2=Z(D());var h0,V2=[],Z5=Number.MAX_SAFE_INTEGER,Ht=0,Vt=0;async function Dt(e){var t;return v.initial&&(h0=null),h0?e.debug&&p("cached model:",h0.modelUrl):h0=await G((t=e.face.antispoof)==null?void 0:t.modelPath),h0}async function X5(e,t,o,n){var s,a;if(!h0)return 0;let r=(((s=t.face.antispoof)==null?void 0:s.skipTime)||0)>h()-Vt,A=Z5<(((a=t.face.antispoof)==null?void 0:a.skipFrames)||0);return t.skipAllowed&&r&&A&&Ht===n&&V2[o]?(Z5++,V2[o]):(Z5=0,new Promise(async i=>{let x=D2.image.resizeBilinear(e,[h0!=null&&h0.inputs[0].shape?h0.inputs[0].shape[2]:0,h0!=null&&h0.inputs[0].shape?h0.inputs[0].shape[1]:0],!1),c=h0==null?void 0:h0.execute(x),l=(await c.data())[0];V2[o]=Math.round(100*l)/100,Ht=n,Vt=h(),D2.dispose([x,c]),i(V2[o])}))}var N=Z(D());var ie=Z(D());var X0={silhouette:[10,338,297,332,284,251,389,356,454,323,361,288,397,365,379,378,400,377,152,148,176,149,150,136,172,58,132,93,234,127,162,21,54,103,67,109],lipsUpperOuter:[185,40,39,37,0,267,269,270,409],lipsLowerOuter:[61,146,91,181,84,17,314,405,321,375,291],lipsUpperInner:[191,80,81,82,13,312,311,310,415],lipsLowerInner:[78,95,88,178,87,14,317,402,318,324,308],lipsLowerSemiOuter:[76,77,90,180,85,16,315,404,320,307,306],lipsUpperSemiOuter:[184,74,73,72,11,302,303,304,408],lipsLowerSemiInner:[62,96,89,179,86,15,316,403,319,325,292],lipsUpperSemiInner:[183,42,41,38,12,268,271,272,407],rightEyeUpper0:[246,161,160,159,158,157,173],rightEyeLower0:[33,7,163,144,145,153,154,155,133],rightEyeUpper1:[247,30,29,27,28,56,190],rightEyeLower1:[130,25,110,24,23,22,26,112,243],rightEyeUpper2:[113,225,224,223,222,221,189],rightEyeLower2:[226,31,228,229,230,231,232,233,244],rightEyeLower3:[143,111,117,118,119,120,121,128,245],rightEyebrowUpper:[156,70,63,105,66,107,55,193],rightEyebrowLower:[35,124,46,53,52,65],rightEyeIris:[473,474,475,476,477],leftEyeUpper0:[466,388,387,386,385,384,398],leftEyeLower0:[263,249,390,373,374,380,381,382,362],leftEyeUpper1:[467,260,259,257,258,286,414],leftEyeLower1:[359,255,339,254,253,252,256,341,463],leftEyeUpper2:[342,445,444,443,442,441,413],leftEyeLower2:[446,261,448,449,450,451,452,453,464],leftEyeLower3:[372,340,346,347,348,349,350,357,465],leftEyebrowUpper:[383,300,293,334,296,336,285,417],leftEyebrowLower:[265,353,276,283,282,295],leftEyeIris:[468,469,470,471,472],midwayBetweenEyes:[168],noseTip:[1],noseBottom:[2],noseRightCorner:[98],noseLeftCorner:[327],rightCheek:[205],leftCheek:[425]},q5={count:468,mouth:13,symmetryLine:[13,X0.midwayBetweenEyes[0]]},je={leftEye:0,rightEye:1,nose:2,mouth:3,leftEar:4,rightEar:5,symmetryLine:[3,2]},U5=[{key:"EyeUpper0",indices:[9,10,11,12,13,14,15]},{key:"EyeUpper1",indices:[25,26,27,28,29,30,31]},{key:"EyeUpper2",indices:[41,42,43,44,45,46,47]},{key:"EyeLower0",indices:[0,1,2,3,4,5,6,7,8]},{key:"EyeLower1",indices:[16,17,18,19,20,21,22,23,24]},{key:"EyeLower2",indices:[32,33,34,35,36,37,38,39,40]},{key:"EyeLower3",indices:[54,55,56,57,58,59,60,61,62]},{key:"EyebrowUpper",indices:[63,64,65,66,67,68,69,70]},{key:"EyebrowLower",indices:[48,49,50,51,52,53]}],R2=[[.499976992607117,.652534008026123],[.500025987625122,.547487020492554],[.499974012374878,.602371990680695],[.482113003730774,.471979022026062],[.500150978565216,.527155995368958],[.499909996986389,.498252987861633],[.499523013830185,.40106201171875],[.289712011814117,.380764007568359],[.499954998493195,.312398016452789],[.499987006187439,.269918978214264],[.500023007392883,.107050001621246],[.500023007392883,.666234016418457],[.5000159740448,.679224014282227],[.500023007392883,.692348003387451],[.499976992607117,.695277988910675],[.499976992607117,.70593398809433],[.499976992607117,.719385027885437],[.499976992607117,.737019002437592],[.499967992305756,.781370997428894],[.499816000461578,.562981009483337],[.473773002624512,.573909997940063],[.104906998574734,.254140973091125],[.365929991006851,.409575998783112],[.338757991790771,.41302502155304],[.311120003461838,.409460008144379],[.274657994508743,.389131009578705],[.393361985683441,.403706014156342],[.345234006643295,.344011008739471],[.370094001293182,.346076011657715],[.319321990013123,.347265005111694],[.297903001308441,.353591024875641],[.24779200553894,.410809993743896],[.396889001131058,.842755019664764],[.280097991228104,.375599980354309],[.106310002505779,.399955987930298],[.2099249958992,.391353011131287],[.355807989835739,.534406006336212],[.471751004457474,.65040397644043],[.474155008792877,.680191993713379],[.439785003662109,.657229006290436],[.414617002010345,.66654098033905],[.450374007225037,.680860996246338],[.428770989179611,.682690978050232],[.374971002340317,.727805018424988],[.486716985702515,.547628998756409],[.485300987958908,.527395009994507],[.257764995098114,.314490020275116],[.401223003864288,.455172002315521],[.429818987846375,.548614978790283],[.421351999044418,.533740997314453],[.276895999908447,.532056987285614],[.483370006084442,.499586999416351],[.33721199631691,.282882988452911],[.296391993761063,.293242990970612],[.169294998049736,.193813979625702],[.447580009698868,.302609980106354],[.392390012741089,.353887975215912],[.354490011930466,.696784019470215],[.067304998636246,.730105042457581],[.442739009857178,.572826027870178],[.457098007202148,.584792017936707],[.381974011659622,.694710969924927],[.392388999462128,.694203019142151],[.277076005935669,.271932005882263],[.422551989555359,.563233017921448],[.385919004678726,.281364023685455],[.383103013038635,.255840003490448],[.331431001424789,.119714021682739],[.229923993349075,.232002973556519],[.364500999450684,.189113974571228],[.229622006416321,.299540996551514],[.173287004232407,.278747975826263],[.472878992557526,.666198015213013],[.446828007698059,.668527007102966],[.422762006521225,.673889994621277],[.445307999849319,.580065965652466],[.388103008270264,.693961024284363],[.403039008378983,.706539988517761],[.403629004955292,.693953037261963],[.460041999816895,.557139039039612],[.431158006191254,.692366003990173],[.452181994915009,.692366003990173],[.475387006998062,.692366003990173],[.465828001499176,.779190003871918],[.472328990697861,.736225962638855],[.473087012767792,.717857003211975],[.473122000694275,.704625964164734],[.473033010959625,.695277988910675],[.427942007780075,.695277988910675],[.426479011774063,.703539967536926],[.423162013292313,.711845993995667],[.4183090031147,.720062971115112],[.390094995498657,.639572978019714],[.013953999616206,.560034036636353],[.499913990497589,.58014702796936],[.413199990987778,.69539999961853],[.409626007080078,.701822996139526],[.468080013990402,.601534962654114],[.422728985548019,.585985004901886],[.463079988956451,.593783974647522],[.37211999297142,.47341400384903],[.334562003612518,.496073007583618],[.411671012639999,.546965003013611],[.242175996303558,.14767599105835],[.290776997804642,.201445996761322],[.327338010072708,.256527006626129],[.399509996175766,.748921036720276],[.441727995872498,.261676013469696],[.429764986038208,.187834024429321],[.412198007106781,.108901023864746],[.288955003023148,.398952007293701],[.218936994671822,.435410976409912],[.41278201341629,.398970007896423],[.257135003805161,.355440020561218],[.427684992551804,.437960982322693],[.448339998722076,.536936044692993],[.178560003638268,.45755398273468],[.247308000922203,.457193970680237],[.286267012357712,.467674970626831],[.332827985286713,.460712015628815],[.368755996227264,.447206974029541],[.398963987827301,.432654976844788],[.476410001516342,.405806005001068],[.189241006970406,.523923993110657],[.228962004184723,.348950982093811],[.490725994110107,.562400996685028],[.404670000076294,.485132992267609],[.019469000399113,.401564002037048],[.426243007183075,.420431017875671],[.396993011236191,.548797011375427],[.266469985246658,.376977026462555],[.439121007919312,.51895797252655],[.032313998788595,.644356966018677],[.419054001569748,.387154996395111],[.462783008813858,.505746960639954],[.238978996872902,.779744982719421],[.198220998048782,.831938028335571],[.107550002634525,.540755033493042],[.183610007166862,.740257024765015],[.134409993886948,.333683013916016],[.385764002799988,.883153975009918],[.490967005491257,.579378008842468],[.382384985685349,.508572995662689],[.174399003386497,.397670984268188],[.318785011768341,.39623498916626],[.343364000320435,.400596976280212],[.396100014448166,.710216999053955],[.187885001301765,.588537991046906],[.430987000465393,.944064974784851],[.318993002176285,.898285031318665],[.266247987747192,.869701027870178],[.500023007392883,.190576016902924],[.499976992607117,.954452991485596],[.366169989109039,.398822009563446],[.393207013607025,.39553701877594],[.410373002290726,.391080021858215],[.194993004202843,.342101991176605],[.388664990663528,.362284004688263],[.365961998701096,.355970978736877],[.343364000320435,.355356991291046],[.318785011768341,.35834002494812],[.301414996385574,.363156020641327],[.058132998645306,.319076001644135],[.301414996385574,.387449026107788],[.499987989664078,.618434011936188],[.415838003158569,.624195992946625],[.445681989192963,.566076993942261],[.465844005346298,.620640993118286],[.49992299079895,.351523995399475],[.288718998432159,.819945991039276],[.335278987884521,.852819979190826],[.440512001514435,.902418971061707],[.128294005990028,.791940987110138],[.408771991729736,.373893976211548],[.455606997013092,.451801002025604],[.499877005815506,.908990025520325],[.375436991453171,.924192011356354],[.11421000212431,.615022003650665],[.448662012815475,.695277988910675],[.4480200111866,.704632043838501],[.447111994028091,.715808033943176],[.444831997156143,.730794012546539],[.430011987686157,.766808986663818],[.406787008047104,.685672998428345],[.400738000869751,.681069016456604],[.392399996519089,.677703022956848],[.367855995893478,.663918972015381],[.247923001646996,.601333022117615],[.452769994735718,.420849978923798],[.43639200925827,.359887003898621],[.416164010763168,.368713974952698],[.413385987281799,.692366003990173],[.228018000721931,.683571994304657],[.468268007040024,.352671027183533],[.411361992359161,.804327011108398],[.499989002943039,.469825029373169],[.479153990745544,.442654013633728],[.499974012374878,.439637005329132],[.432112008333206,.493588984012604],[.499886006116867,.866917014122009],[.49991300702095,.821729004383087],[.456548988819122,.819200992584229],[.344549000263214,.745438992977142],[.37890899181366,.574010014533997],[.374292999505997,.780184984207153],[.319687992334366,.570737957954407],[.357154995203018,.604269981384277],[.295284003019333,.621580958366394],[.447750002145767,.862477004528046],[.410986006259918,.508723020553589],[.31395098567009,.775308012962341],[.354128003120422,.812552988529205],[.324548006057739,.703992962837219],[.189096003770828,.646299958229065],[.279776990413666,.71465802192688],[.1338230073452,.682700991630554],[.336768001317978,.644733011722565],[.429883986711502,.466521978378296],[.455527991056442,.548622965812683],[.437114000320435,.558896005153656],[.467287987470627,.529924988746643],[.414712011814117,.335219979286194],[.37704598903656,.322777986526489],[.344107985496521,.320150971412659],[.312875986099243,.32233202457428],[.283526003360748,.333190023899078],[.241245999932289,.382785975933075],[.102986000478268,.468762993812561],[.267612010240555,.424560010433197],[.297879010438919,.433175981044769],[.333433985710144,.433878004550934],[.366427004337311,.426115989685059],[.396012008190155,.416696012020111],[.420121014118195,.41022801399231],[.007561000064015,.480777025222778],[.432949006557465,.569517970085144],[.458638995885849,.479089021682739],[.473466008901596,.545744001865387],[.476087987422943,.563830018043518],[.468472003936768,.555056989192963],[.433990985155106,.582361996173859],[.483518004417419,.562983989715576],[.482482999563217,.57784903049469],[.42645001411438,.389798998832703],[.438998997211456,.39649498462677],[.450067013502121,.400434017181396],[.289712011814117,.368252992630005],[.276670008897781,.363372981548309],[.517862021923065,.471948027610779],[.710287988185883,.380764007568359],[.526226997375488,.573909997940063],[.895093023777008,.254140973091125],[.634069979190826,.409575998783112],[.661242008209229,.41302502155304],[.688880026340485,.409460008144379],[.725341975688934,.389131009578705],[.606630027294159,.40370500087738],[.654766023159027,.344011008739471],[.629905998706818,.346076011657715],[.680678009986877,.347265005111694],[.702096998691559,.353591024875641],[.75221198797226,.410804986953735],[.602918028831482,.842862963676453],[.719901978969574,.375599980354309],[.893692970275879,.399959981441498],[.790081977844238,.391354024410248],[.643998026847839,.534487962722778],[.528249025344849,.65040397644043],[.525849997997284,.680191040039062],[.560214996337891,.657229006290436],[.585384011268616,.66654098033905],[.549625992774963,.680860996246338],[.57122802734375,.682691991329193],[.624852001667023,.72809898853302],[.513050019741058,.547281980514526],[.51509702205658,.527251958847046],[.742246985435486,.314507007598877],[.598631024360657,.454979002475739],[.570338010787964,.548575043678284],[.578631997108459,.533622980117798],[.723087012767792,.532054007053375],[.516445994377136,.499638974666595],[.662801027297974,.282917976379395],[.70362401008606,.293271005153656],[.830704987049103,.193813979625702],[.552385985851288,.302568018436432],[.607609987258911,.353887975215912],[.645429015159607,.696707010269165],[.932694971561432,.730105042457581],[.557260990142822,.572826027870178],[.542901992797852,.584792017936707],[.6180260181427,.694710969924927],[.607590973377228,.694203019142151],[.722943007946014,.271963000297546],[.577413976192474,.563166975975037],[.614082992076874,.281386971473694],[.616907000541687,.255886018276215],[.668509006500244,.119913995265961],[.770092010498047,.232020974159241],[.635536015033722,.189248979091644],[.77039098739624,.299556016921997],[.826722025871277,.278755009174347],[.527121007442474,.666198015213013],[.553171992301941,.668527007102966],[.577238023281097,.673889994621277],[.554691970348358,.580065965652466],[.611896991729736,.693961024284363],[.59696102142334,.706539988517761],[.596370995044708,.693953037261963],[.539958000183105,.557139039039612],[.568841993808746,.692366003990173],[.547818005084991,.692366003990173],[.52461302280426,.692366003990173],[.534089982509613,.779141008853912],[.527670979499817,.736225962638855],[.526912987232208,.717857003211975],[.526877999305725,.704625964164734],[.526966989040375,.695277988910675],[.572058022022247,.695277988910675],[.573521018028259,.703539967536926],[.57683801651001,.711845993995667],[.581691026687622,.720062971115112],[.609944999217987,.639909982681274],[.986046016216278,.560034036636353],[.5867999792099,.69539999961853],[.590372025966644,.701822996139526],[.531915009021759,.601536989212036],[.577268004417419,.585934996604919],[.536915004253387,.593786001205444],[.627542972564697,.473352015018463],[.665585994720459,.495950996875763],[.588353991508484,.546862006187439],[.757824003696442,.14767599105835],[.709249973297119,.201507985591888],[.672684013843536,.256581008434296],[.600408971309662,.74900496006012],[.55826598405838,.261672019958496],[.570303976535797,.187870979309082],[.588165998458862,.109044015407562],[.711045026779175,.398952007293701],[.781069993972778,.435405015945435],[.587247014045715,.398931980133057],[.742869973182678,.355445981025696],[.572156012058258,.437651991844177],[.55186802148819,.536570012569427],[.821442008018494,.457556009292603],[.752701997756958,.457181990146637],[.71375697851181,.467626988887787],[.66711300611496,.460672974586487],[.631101012229919,.447153985500336],[.6008620262146,.432473003864288],[.523481011390686,.405627012252808],[.810747981071472,.523926019668579],[.771045982837677,.348959028720856],[.509127020835876,.562718033790588],[.595292985439301,.485023975372314],[.980530977249146,.401564002037048],[.573499977588654,.420000016689301],[.602994978427887,.548687994480133],[.733529984951019,.376977026462555],[.560611009597778,.519016981124878],[.967685997486115,.644356966018677],[.580985009670258,.387160003185272],[.537728011608124,.505385041236877],[.760966002941132,.779752969741821],[.801778972148895,.831938028335571],[.892440974712372,.54076099395752],[.816350996494293,.740260004997253],[.865594983100891,.333687007427216],[.614073991775513,.883246004581451],[.508952975273132,.579437971115112],[.617941975593567,.508316040039062],[.825608015060425,.397674977779388],[.681214988231659,.39623498916626],[.656635999679565,.400596976280212],[.603900015354156,.710216999053955],[.81208598613739,.588539004325867],[.56801301240921,.944564998149872],[.681007981300354,.898285031318665],[.733752012252808,.869701027870178],[.633830010890961,.398822009563446],[.606792986392975,.39553701877594],[.589659988880157,.391062021255493],[.805015981197357,.342108011245728],[.611334979534149,.362284004688263],[.634037971496582,.355970978736877],[.656635999679565,.355356991291046],[.681214988231659,.35834002494812],[.698584973812103,.363156020641327],[.941866993904114,.319076001644135],[.698584973812103,.387449026107788],[.584177017211914,.624107003211975],[.554318010807037,.566076993942261],[.534153997898102,.62064003944397],[.711217999458313,.819975018501282],[.664629995822906,.852871000766754],[.559099972248077,.902631998062134],[.871706008911133,.791940987110138],[.591234028339386,.373893976211548],[.544341027736664,.451583981513977],[.624562978744507,.924192011356354],[.88577002286911,.615028977394104],[.551338016986847,.695277988910675],[.551980018615723,.704632043838501],[.552887976169586,.715808033943176],[.555167973041534,.730794012546539],[.569944024085999,.767035007476807],[.593203008174896,.685675978660583],[.599261999130249,.681069016456604],[.607599973678589,.677703022956848],[.631937980651855,.663500010967255],[.752032995223999,.601315021514893],[.547226011753082,.420395016670227],[.563543975353241,.359827995300293],[.583841025829315,.368713974952698],[.586614012718201,.692366003990173],[.771915018558502,.683578014373779],[.531597018241882,.352482974529266],[.588370978832245,.804440975189209],[.52079701423645,.442565023899078],[.567984998226166,.493479013442993],[.543282985687256,.819254994392395],[.655317008495331,.745514988899231],[.621008992195129,.574018001556396],[.625559985637665,.78031200170517],[.680198013782501,.570719003677368],[.64276397228241,.604337990283966],[.704662978649139,.621529996395111],[.552012026309967,.862591981887817],[.589071989059448,.508637011051178],[.685944974422455,.775357007980347],[.645735025405884,.812640011310577],[.675342977046967,.703978002071381],[.810858011245728,.646304965019226],[.72012197971344,.714666962623596],[.866151988506317,.682704985141754],[.663187026977539,.644596993923187],[.570082008838654,.466325998306274],[.544561982154846,.548375964164734],[.562758982181549,.558784961700439],[.531987011432648,.530140042304993],[.585271000862122,.335177004337311],[.622952997684479,.32277899980545],[.655896008014679,.320163011550903],[.687132000923157,.322345972061157],[.716481983661652,.333200991153717],[.758756995201111,.382786989212036],[.897013008594513,.468769013881683],[.732392013072968,.424547016620636],[.70211398601532,.433162987232208],[.66652500629425,.433866024017334],[.633504986763,.426087975502014],[.603875994682312,.416586995124817],[.579657971858978,.409945011138916],[.992439985275269,.480777025222778],[.567192018032074,.569419980049133],[.54136598110199,.478899002075195],[.526564002037048,.546118021011353],[.523913025856018,.563830018043518],[.531529009342194,.555056989192963],[.566035985946655,.582329034805298],[.51631098985672,.563053965568542],[.5174720287323,.577877044677734],[.573594987392426,.389806985855103],[.560697972774506,.395331978797913],[.549755990505219,.399751007556915],[.710287988185883,.368252992630005],[.723330020904541,.363372981548309]],Oe=[127,34,139,11,0,37,232,231,120,72,37,39,128,121,47,232,121,128,104,69,67,175,171,148,157,154,155,118,50,101,73,39,40,9,151,108,48,115,131,194,204,211,74,40,185,80,42,183,40,92,186,230,229,118,202,212,214,83,18,17,76,61,146,160,29,30,56,157,173,106,204,194,135,214,192,203,165,98,21,71,68,51,45,4,144,24,23,77,146,91,205,50,187,201,200,18,91,106,182,90,91,181,85,84,17,206,203,36,148,171,140,92,40,39,193,189,244,159,158,28,247,246,161,236,3,196,54,68,104,193,168,8,117,228,31,189,193,55,98,97,99,126,47,100,166,79,218,155,154,26,209,49,131,135,136,150,47,126,217,223,52,53,45,51,134,211,170,140,67,69,108,43,106,91,230,119,120,226,130,247,63,53,52,238,20,242,46,70,156,78,62,96,46,53,63,143,34,227,173,155,133,123,117,111,44,125,19,236,134,51,216,206,205,154,153,22,39,37,167,200,201,208,36,142,100,57,212,202,20,60,99,28,158,157,35,226,113,160,159,27,204,202,210,113,225,46,43,202,204,62,76,77,137,123,116,41,38,72,203,129,142,64,98,240,49,102,64,41,73,74,212,216,207,42,74,184,169,170,211,170,149,176,105,66,69,122,6,168,123,147,187,96,77,90,65,55,107,89,90,180,101,100,120,63,105,104,93,137,227,15,86,85,129,102,49,14,87,86,55,8,9,100,47,121,145,23,22,88,89,179,6,122,196,88,95,96,138,172,136,215,58,172,115,48,219,42,80,81,195,3,51,43,146,61,171,175,199,81,82,38,53,46,225,144,163,110,246,33,7,52,65,66,229,228,117,34,127,234,107,108,69,109,108,151,48,64,235,62,78,191,129,209,126,111,35,143,163,161,246,117,123,50,222,65,52,19,125,141,221,55,65,3,195,197,25,7,33,220,237,44,70,71,139,122,193,245,247,130,33,71,21,162,153,158,159,170,169,150,188,174,196,216,186,92,144,160,161,2,97,167,141,125,241,164,167,37,72,38,12,145,159,160,38,82,13,63,68,71,226,35,111,158,153,154,101,50,205,206,92,165,209,198,217,165,167,97,220,115,218,133,112,243,239,238,241,214,135,169,190,173,133,171,208,32,125,44,237,86,87,178,85,86,179,84,85,180,83,84,181,201,83,182,137,93,132,76,62,183,61,76,184,57,61,185,212,57,186,214,207,187,34,143,156,79,239,237,123,137,177,44,1,4,201,194,32,64,102,129,213,215,138,59,166,219,242,99,97,2,94,141,75,59,235,24,110,228,25,130,226,23,24,229,22,23,230,26,22,231,112,26,232,189,190,243,221,56,190,28,56,221,27,28,222,29,27,223,30,29,224,247,30,225,238,79,20,166,59,75,60,75,240,147,177,215,20,79,166,187,147,213,112,233,244,233,128,245,128,114,188,114,217,174,131,115,220,217,198,236,198,131,134,177,132,58,143,35,124,110,163,7,228,110,25,356,389,368,11,302,267,452,350,349,302,303,269,357,343,277,452,453,357,333,332,297,175,152,377,384,398,382,347,348,330,303,304,270,9,336,337,278,279,360,418,262,431,304,408,409,310,415,407,270,409,410,450,348,347,422,430,434,313,314,17,306,307,375,387,388,260,286,414,398,335,406,418,364,367,416,423,358,327,251,284,298,281,5,4,373,374,253,307,320,321,425,427,411,421,313,18,321,405,406,320,404,405,315,16,17,426,425,266,377,400,369,322,391,269,417,465,464,386,257,258,466,260,388,456,399,419,284,332,333,417,285,8,346,340,261,413,441,285,327,460,328,355,371,329,392,439,438,382,341,256,429,420,360,364,394,379,277,343,437,443,444,283,275,440,363,431,262,369,297,338,337,273,375,321,450,451,349,446,342,467,293,334,282,458,461,462,276,353,383,308,324,325,276,300,293,372,345,447,382,398,362,352,345,340,274,1,19,456,248,281,436,427,425,381,256,252,269,391,393,200,199,428,266,330,329,287,273,422,250,462,328,258,286,384,265,353,342,387,259,257,424,431,430,342,353,276,273,335,424,292,325,307,366,447,345,271,303,302,423,266,371,294,455,460,279,278,294,271,272,304,432,434,427,272,407,408,394,430,431,395,369,400,334,333,299,351,417,168,352,280,411,325,319,320,295,296,336,319,403,404,330,348,349,293,298,333,323,454,447,15,16,315,358,429,279,14,15,316,285,336,9,329,349,350,374,380,252,318,402,403,6,197,419,318,319,325,367,364,365,435,367,397,344,438,439,272,271,311,195,5,281,273,287,291,396,428,199,311,271,268,283,444,445,373,254,339,263,466,249,282,334,296,449,347,346,264,447,454,336,296,299,338,10,151,278,439,455,292,407,415,358,371,355,340,345,372,390,249,466,346,347,280,442,443,282,19,94,370,441,442,295,248,419,197,263,255,359,440,275,274,300,383,368,351,412,465,263,467,466,301,368,389,380,374,386,395,378,379,412,351,419,436,426,322,373,390,388,2,164,393,370,462,461,164,0,267,302,11,12,374,373,387,268,12,13,293,300,301,446,261,340,385,384,381,330,266,425,426,423,391,429,355,437,391,327,326,440,457,438,341,382,362,459,457,461,434,430,394,414,463,362,396,369,262,354,461,457,316,403,402,315,404,403,314,405,404,313,406,405,421,418,406,366,401,361,306,408,407,291,409,408,287,410,409,432,436,410,434,416,411,264,368,383,309,438,457,352,376,401,274,275,4,421,428,262,294,327,358,433,416,367,289,455,439,462,370,326,2,326,370,305,460,455,254,449,448,255,261,446,253,450,449,252,451,450,256,452,451,341,453,452,413,464,463,441,413,414,258,442,441,257,443,442,259,444,443,260,445,444,467,342,445,459,458,250,289,392,290,290,328,460,376,433,435,250,290,392,411,416,433,341,463,464,453,464,465,357,465,412,343,412,399,360,363,440,437,399,456,420,456,363,401,435,288,372,383,353,339,255,249,448,261,255,133,243,190,133,155,112,33,246,247,33,130,25,398,384,286,362,398,414,362,463,341,263,359,467,263,249,255,466,467,260,75,60,166,238,239,79,162,127,139,72,11,37,121,232,120,73,72,39,114,128,47,233,232,128,103,104,67,152,175,148,173,157,155,119,118,101,74,73,40,107,9,108,49,48,131,32,194,211,184,74,185,191,80,183,185,40,186,119,230,118,210,202,214,84,83,17,77,76,146,161,160,30,190,56,173,182,106,194,138,135,192,129,203,98,54,21,68,5,51,4,145,144,23,90,77,91,207,205,187,83,201,18,181,91,182,180,90,181,16,85,17,205,206,36,176,148,140,165,92,39,245,193,244,27,159,28,30,247,161,174,236,196,103,54,104,55,193,8,111,117,31,221,189,55,240,98,99,142,126,100,219,166,218,112,155,26,198,209,131,169,135,150,114,47,217,224,223,53,220,45,134,32,211,140,109,67,108,146,43,91,231,230,120,113,226,247,105,63,52,241,238,242,124,46,156,95,78,96,70,46,63,116,143,227,116,123,111,1,44,19,3,236,51,207,216,205,26,154,22,165,39,167,199,200,208,101,36,100,43,57,202,242,20,99,56,28,157,124,35,113,29,160,27,211,204,210,124,113,46,106,43,204,96,62,77,227,137,116,73,41,72,36,203,142,235,64,240,48,49,64,42,41,74,214,212,207,183,42,184,210,169,211,140,170,176,104,105,69,193,122,168,50,123,187,89,96,90,66,65,107,179,89,180,119,101,120,68,63,104,234,93,227,16,15,85,209,129,49,15,14,86,107,55,9,120,100,121,153,145,22,178,88,179,197,6,196,89,88,96,135,138,136,138,215,172,218,115,219,41,42,81,5,195,51,57,43,61,208,171,199,41,81,38,224,53,225,24,144,110,105,52,66,118,229,117,227,34,234,66,107,69,10,109,151,219,48,235,183,62,191,142,129,126,116,111,143,7,163,246,118,117,50,223,222,52,94,19,141,222,221,65,196,3,197,45,220,44,156,70,139,188,122,245,139,71,162,145,153,159,149,170,150,122,188,196,206,216,92,163,144,161,164,2,167,242,141,241,0,164,37,11,72,12,144,145,160,12,38,13,70,63,71,31,226,111,157,158,154,36,101,205,203,206,165,126,209,217,98,165,97,237,220,218,237,239,241,210,214,169,140,171,32,241,125,237,179,86,178,180,85,179,181,84,180,182,83,181,194,201,182,177,137,132,184,76,183,185,61,184,186,57,185,216,212,186,192,214,187,139,34,156,218,79,237,147,123,177,45,44,4,208,201,32,98,64,129,192,213,138,235,59,219,141,242,97,97,2,141,240,75,235,229,24,228,31,25,226,230,23,229,231,22,230,232,26,231,233,112,232,244,189,243,189,221,190,222,28,221,223,27,222,224,29,223,225,30,224,113,247,225,99,60,240,213,147,215,60,20,166,192,187,213,243,112,244,244,233,245,245,128,188,188,114,174,134,131,220,174,217,236,236,198,134,215,177,58,156,143,124,25,110,7,31,228,25,264,356,368,0,11,267,451,452,349,267,302,269,350,357,277,350,452,357,299,333,297,396,175,377,381,384,382,280,347,330,269,303,270,151,9,337,344,278,360,424,418,431,270,304,409,272,310,407,322,270,410,449,450,347,432,422,434,18,313,17,291,306,375,259,387,260,424,335,418,434,364,416,391,423,327,301,251,298,275,281,4,254,373,253,375,307,321,280,425,411,200,421,18,335,321,406,321,320,405,314,315,17,423,426,266,396,377,369,270,322,269,413,417,464,385,386,258,248,456,419,298,284,333,168,417,8,448,346,261,417,413,285,326,327,328,277,355,329,309,392,438,381,382,256,279,429,360,365,364,379,355,277,437,282,443,283,281,275,363,395,431,369,299,297,337,335,273,321,348,450,349,359,446,467,283,293,282,250,458,462,300,276,383,292,308,325,283,276,293,264,372,447,346,352,340,354,274,19,363,456,281,426,436,425,380,381,252,267,269,393,421,200,428,371,266,329,432,287,422,290,250,328,385,258,384,446,265,342,386,387,257,422,424,430,445,342,276,422,273,424,306,292,307,352,366,345,268,271,302,358,423,371,327,294,460,331,279,294,303,271,304,436,432,427,304,272,408,395,394,431,378,395,400,296,334,299,6,351,168,376,352,411,307,325,320,285,295,336,320,319,404,329,330,349,334,293,333,366,323,447,316,15,315,331,358,279,317,14,316,8,285,9,277,329,350,253,374,252,319,318,403,351,6,419,324,318,325,397,367,365,288,435,397,278,344,439,310,272,311,248,195,281,375,273,291,175,396,199,312,311,268,276,283,445,390,373,339,295,282,296,448,449,346,356,264,454,337,336,299,337,338,151,294,278,455,308,292,415,429,358,355,265,340,372,388,390,466,352,346,280,295,442,282,354,19,370,285,441,295,195,248,197,457,440,274,301,300,368,417,351,465,251,301,389,385,380,386,394,395,379,399,412,419,410,436,322,387,373,388,326,2,393,354,370,461,393,164,267,268,302,12,386,374,387,312,268,13,298,293,301,265,446,340,380,385,381,280,330,425,322,426,391,420,429,437,393,391,326,344,440,438,458,459,461,364,434,394,428,396,262,274,354,457,317,316,402,316,315,403,315,314,404,314,313,405,313,421,406,323,366,361,292,306,407,306,291,408,291,287,409,287,432,410,427,434,411,372,264,383,459,309,457,366,352,401,1,274,4,418,421,262,331,294,358,435,433,367,392,289,439,328,462,326,94,2,370,289,305,455,339,254,448,359,255,446,254,253,449,253,252,450,252,256,451,256,341,452,414,413,463,286,441,414,286,258,441,258,257,442,257,259,443,259,260,444,260,467,445,309,459,250,305,289,290,305,290,460,401,376,435,309,250,392,376,411,433,453,341,464,357,453,465,343,357,412,437,343,399,344,360,440,420,437,456,360,420,363,361,401,288,265,372,353,390,339,249,339,448,255];var ur=[127,234,132,58,172,150,149,148,152,377,378,379,397,288,361,454,356,70,63,105,66,107,336,296,334,293,300,168,6,195,4,98,97,2,326,327,33,160,158,133,153,144,362,385,387,263,373,380,57,40,37,0,267,270,287,321,314,17,84,91,78,81,13,311,308,402,14,178],hr=[33,133,362,263,1,62,308,159,145,386,374,6,102,331,2,13,14,70,105,107,336,334,300,54,10,284,50,280,234,454,58,288,152],br=[33,133,362,263,1,78,308],L7=ur.map(e=>R2[e]),W7=hr.map(e=>R2[e]),F7=br.map(e=>R2[e]);function ge(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var gr=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Mr=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Pr=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],Rr=[[474,475],[475,476],[476,477],[477,474]],vr=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],Tr=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],wr=[[469,470],[470,471],[471,472],[472,469]],kr=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]],G7={lips:ge(gr),leftEye:ge(Mr),leftEyebrow:ge(Pr),leftIris:ge(Rr),rightEye:ge(vr),rightEyebrow:ge(Tr),rightIris:ge(wr),faceOval:ge(kr)};var Je=e=>[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])],Z2=e=>[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2,1],X2=(e,t)=>e?[Math.trunc(Math.max(0,e.startPoint[0])),Math.trunc(Math.max(0,e.startPoint[1])),Math.trunc(Math.min(t.shape[2]||0,e.endPoint[0])-Math.max(0,e.startPoint[0])),Math.trunc(Math.min(t.shape[1]||0,e.endPoint[1])-Math.max(0,e.startPoint[1]))]:[0,0,0,0],q2=(e,t)=>e?[e.startPoint[0]/(t.shape[2]||0),e.startPoint[1]/(t.shape[1]||0),(e.endPoint[0]-e.startPoint[0])/(t.shape[2]||0),(e.endPoint[1]-e.startPoint[1])/(t.shape[1]||0)]:[0,0,0,0],Ut=(e,t)=>{let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]];return{startPoint:o,endPoint:n,landmarks:e.landmarks,confidence:e.confidence}},K5=(e,t,o)=>{let n=t.shape[1],r=t.shape[2],A=[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r],s=ie.image.cropAndResize(t,[A],[0],o),a=ie.div(s,V.tf255);return ie.dispose(s),a},U2=(e,t)=>{let o=Z2(e),n=Je(e),r=[t*n[0]/2,t*n[1]/2];return{startPoint:[o[0]-r[0],o[1]-r[1]],endPoint:[o[0]+r[0],o[1]+r[1]],landmarks:e.landmarks,confidence:e.confidence}},Y2=e=>{let t=Z2(e),o=Je(e),n=Math.max(...o)/2;return{startPoint:[Math.round(t[0]-n),Math.round(t[1]-n)],endPoint:[Math.round(t[0]+n),Math.round(t[1]+n)],landmarks:e.landmarks,confidence:e.confidence}},Yt=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return{startPoint:[Math.min(...t),Math.min(...o)],endPoint:[Math.max(...t),Math.max(...o)],landmarks:e}},J5=[[1,0,0],[0,1,0],[0,0,1]],Er=e=>e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI)),zr=(e,t)=>Er(Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]));var Xt=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]],Ne=(e,t)=>{let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o},Sr=(e,t)=>{let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o},qt=(e,t)=>{let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let A=0;A<n;A++)o[r].push(Ne(e[r],Sr(t,A)))}return o},Kt=(e,t)=>{let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],A=Xt(t[0],t[1]),s=qt(A,r),a=Xt(-t[0],-t[1]);return qt(s,a)},Cr=e=>{let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-Ne(t[0],o),-Ne(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]},Ir=(e,t)=>[Ne(e,t[0]),Ne(e,t[1])];function Jt(e){let t=e===192?{strides:[4],anchors:[1]}:{strides:[e/16,e/8],anchors:[2,6]},o=[];for(let n=0;n<t.strides.length;n++){let r=t.strides[n],A=Math.floor((e+r-1)/r),s=Math.floor((e+r-1)/r),a=t.anchors[n];for(let i=0;i<A;i++){let x=r*(i+.5);for(let c=0;c<s;c++){let l=r*(c+.5);for(let y=0;y<a;y++)o.push([l,x])}}}return o}function Qt(e,t,o,n,r){let A=Je(t),s=e.map(f=>[A[0]/r*(f[0]-r/2),A[1]/r*(f[1]-r/2),f[2]||0]),a=o&&o!==0&&Math.abs(o)>.2,i=a?Kt(o,[0,0]):J5,x=a?s.map(f=>[...Ir(f,i),f[2]]):s,c=a?Cr(n):J5,l=Z2(t),y=[Ne(l,c[0]),Ne(l,c[1])];return x.map(f=>[Math.trunc(f[0]+y[0]),Math.trunc(f[1]+y[1]),Math.trunc(f[2]||0)])}function _t(e,t,o,n){let r=t.landmarks.length>=q5.count?q5.symmetryLine:je.symmetryLine,A=0,s=J5,a;if(e&&v.kernels.includes("rotatewithoffset"))if(A=zr(t.landmarks[r[0]],t.landmarks[r[1]]),A&&A!==0&&Math.abs(A)>.2){let x=Z2(t),c=[x[0]/o.shape[2],x[1]/o.shape[1]],l=ie.image.rotateWithOffset(o,A,0,c);s=Kt(-A,x),a=K5(t,l,[n,n]),ie.dispose(l)}else a=K5(t,o,[n,n]);else a=K5(t,o,[n,n]);return[A,s,a]}var jr=e=>{let t=e.map(n=>n[0]),o=e.map(n=>n[1]);return[Math.min(...t)+(Math.max(...t)-Math.min(...t))/2,Math.min(...o)+(Math.max(...o)-Math.min(...o))/2]},$t=(e,t)=>{let o=jr(e),n=Je(t);return{startPoint:[o[0]-n[0]/2,o[1]-n[1]/2],endPoint:[o[0]+n[0]/2,o[1]+n[1]/2]}};var e3=6,Or=1.4,te,t3=null,Me=0,v2=null,Qe=()=>Me;async function o3(e){var t;return v.initial&&(te=null),te?e.debug&&p("cached model:",te.modelUrl):te=await G((t=e.face.detector)==null?void 0:t.modelPath),Me=te.inputs[0].shape?te.inputs[0].shape[2]:0,v2=N.scalar(Me,"int32"),t3=N.tensor2d(Jt(Me)),te}function Nr(e){let t={};t.boxStarts=N.slice(e,[0,1],[-1,2]),t.centers=N.add(t.boxStarts,t3),t.boxSizes=N.slice(e,[0,3],[-1,2]),t.boxSizesNormalized=N.div(t.boxSizes,v2),t.centersNormalized=N.div(t.centers,v2),t.halfBoxSize=N.div(t.boxSizesNormalized,V.tf2),t.starts=N.sub(t.centersNormalized,t.halfBoxSize),t.ends=N.add(t.centersNormalized,t.halfBoxSize),t.startNormalized=N.mul(t.starts,v2),t.endNormalized=N.mul(t.ends,v2);let o=N.concat2d([t.startNormalized,t.endNormalized],1);return Object.keys(t).forEach(n=>N.dispose(t[n])),o}async function n3(e,t){var a,i,x,c;if(!e||e.isDisposedInternal||e.shape.length!==4||e.shape[1]<1||e.shape[2]<1)return[];let o={};o.resized=N.image.resizeBilinear(e,[Me,Me]),o.div=N.div(o.resized,V.tf127),o.normalized=N.sub(o.div,V.tf05);let n=te==null?void 0:te.execute(o.normalized);if(Array.isArray(n)&&n.length>2){let l=n.sort((y,f)=>y.size-f.size);o.concat384=N.concat([l[0],l[2]],2),o.concat512=N.concat([l[1],l[3]],2),o.concat=N.concat([o.concat512,o.concat384],1),o.batch=N.squeeze(o.concat,0)}else Array.isArray(n)?o.batch=N.squeeze(n[0]):o.batch=N.squeeze(n);N.dispose(n),o.boxes=Nr(o.batch),o.logits=N.slice(o.batch,[0,0],[-1,1]),o.sigmoid=N.sigmoid(o.logits),o.scores=N.squeeze(o.sigmoid),o.nms=await N.image.nonMaxSuppressionAsync(o.boxes,o.scores,((a=t.face.detector)==null?void 0:a.maxDetected)||0,((i=t.face.detector)==null?void 0:i.iouThreshold)||0,((x=t.face.detector)==null?void 0:x.minConfidence)||0);let r=await o.nms.array(),A=[],s=await o.scores.data();for(let l=0;l<r.length;l++){let y=s[r[l]];if(y>(((c=t.face.detector)==null?void 0:c.minConfidence)||0)){let f={};f.bbox=N.slice(o.boxes,[r[l],0],[1,-1]),f.slice=N.slice(o.batch,[r[l],e3-1],[1,-1]),f.squeeze=N.squeeze(f.slice),f.landmarks=N.reshape(f.squeeze,[e3,-1]);let u=await f.bbox.data(),m={startPoint:[u[0],u[1]],endPoint:[u[2],u[3]],landmarks:await f.landmarks.array(),confidence:y},P=Ut(m,[(e.shape[2]||0)/Me,(e.shape[1]||0)/Me]),g=U2(P,t.face.scale||Or),b=Y2(g);A.push(b),Object.keys(f).forEach(d=>N.dispose(f[d]))}}return Object.keys(o).forEach(l=>N.dispose(o[l])),A}var j0=Z(D());var K2={};ue(K2,{connected:()=>$5,kpt:()=>_5});var _5=["nose","leftEyeInside","leftEye","leftEyeOutside","rightEyeInside","rightEye","rightEyeOutside","leftEar","rightEar","leftMouth","rightMouth","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftPinky","rightPinky","leftIndex","rightIndex","leftThumb","rightThumb","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle","leftHeel","rightHeel","leftFoot","rightFoot","bodyCenter","bodyTop","leftPalm","leftHand","rightPalm","rightHand"],$5={shoulders:["leftShoulder","rightShoulder"],hips:["rightHip","leftHip"],mouth:["leftMouth","rightMouth"],leftLegUpper:["leftHip","leftKnee"],leftLegLower:["leftKnee","leftAnkle"],leftFoot:["leftAnkle","leftHeel","leftFoot"],leftTorso:["leftShoulder","leftHip"],leftArmUpper:["leftShoulder","leftElbow"],leftArmLower:["leftElbow","leftWrist"],leftHand:["leftWrist","leftPalm"],leftHandPinky:["leftPalm","leftPinky"],leftHandIndex:["leftPalm","leftIndex"],leftHandThumb:["leftPalm","leftThumb"],leftEyeOutline:["leftEyeInside","leftEyeOutside"],rightLegUpper:["rightHip","rightKnee"],rightLegLower:["rightKnee","rightAnkle"],rightFoot:["rightAnkle","rightHeel","rightFoot"],rightTorso:["rightShoulder","rightHip"],rightArmUpper:["rightShoulder","rightElbow"],rightArmLower:["rightElbow","rightWrist"],rightHand:["rightWrist","rightPalm"],rightHandPinky:["rightPalm","rightPinky"],rightHandIndex:["rightPalm","rightIndex"],rightHandThumb:["rightPalm","rightThumb"],rightEyeOutline:["rightEyeInside","rightEyeOutside"]};var C0=Z(D()),A3=224,Lr,Wr=5,J2=[8,16,32,32,32];async function s3(){let e=[],t=0;for(;t<Wr;){let o=0,n=t;for(;n<J2.length&&J2[n]===J2[t];)o+=2,n++;let r=J2[t],A=Math.ceil(A3/r),s=Math.ceil(A3/r);for(let a=0;a<A;++a)for(let i=0;i<s;++i)for(let x=0;x<o;++x)e.push({x:(i+.5)/s,y:(a+.5)/A});t=n}Lr={x:C0.tensor1d(e.map(o=>o.x)),y:C0.tensor1d(e.map(o=>o.y))}}function le(e,t=[1,1]){let o=[e.map(a=>a[0]),e.map(a=>a[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],A=[n[0],n[1],r[0]-n[0],r[1]-n[1]],s=[A[0]/t[0],A[1]/t[1],A[2]/t[0],A[3]/t[1]];return{box:A,boxRaw:s}}function a3(e,t=[1,1]){let o=[e.map(x=>x[0]),e.map(x=>x[1])],n=[Math.min(...o[0]),Math.min(...o[1])],r=[Math.max(...o[0]),Math.max(...o[1])],A=[(n[0]+r[0])/2,(n[1]+r[1])/2],s=Math.max(A[0]-n[0],A[1]-n[1],-A[0]+r[0],-A[1]+r[1]),a=[Math.trunc(A[0]-s),Math.trunc(A[1]-s),Math.trunc(2*s),Math.trunc(2*s)],i=[a[0]/t[0],a[1]/t[1],a[2]/t[0],a[3]/t[1]];return{box:a,boxRaw:i}}function Q2(e,t){let o=[e[2]*t,e[3]*t];return[e[0]-(o[0]-e[2])/2,e[1]-(o[1]-e[3])/2,o[0],o[1]]}var y3={initial:!0},I0={detector:null,landmarks:null},_e={detector:[224,224],landmarks:[256,256]},e1=Number.MAX_SAFE_INTEGER,Gr={landmarks:["ld_3d","activation_segmentation","activation_heatmap","world_3d","output_poseflag"],detector:[]},$2=null,T2,Pe=[[0,0],[0,0],[0,0],[0,0]],i3=0,l3=e=>1-1/(1+Math.exp(e));async function x3(e){if(y3.initial&&(I0.detector=null),!I0.detector&&e.body.detector&&e.body.detector.modelPath){I0.detector=await G(e.body.detector.modelPath);let t=Object.values(I0.detector.modelSignature.inputs);_e.detector[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,_e.detector[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&I0.detector&&p("cached model:",I0.detector.modelUrl);return await s3(),I0.detector}async function c3(e){if(y3.initial&&(I0.landmarks=null),I0.landmarks)e.debug&&p("cached model:",I0.landmarks.modelUrl);else{I0.landmarks=await G(e.body.modelPath);let t=Object.values(I0.landmarks.modelSignature.inputs);_e.landmarks[0]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[1].size):0,_e.landmarks[1]=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return I0.landmarks}async function Br(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;let n;if(T2&&(o.cropped=j0.image.cropAndResize(e,[T2],[0],[e.shape[1],e.shape[2]])),e.shape[1]!==e.shape[2]){let r=[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],A=[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0];Pe=[[0,0],r,A,[0,0]],o.pad=j0.pad(o.cropped||e,Pe),o.resize=j0.image.resizeBilinear(o.pad,[t,t]),n=j0.div(o.resize,V.tf255)}else e.shape[1]!==t?(o.resize=j0.image.resizeBilinear(o.cropped||e,[t,t]),n=j0.div(o.resize,V.tf255)):n=j0.div(o.cropped||e,V.tf255);return Object.keys(o).forEach(r=>j0.dispose(o[r])),n}function Hr(e,t){for(let o of e)o.position=[Math.trunc(o.position[0]*(t[0]+Pe[2][0]+Pe[2][1])/t[0]-Pe[2][0]),Math.trunc(o.position[1]*(t[1]+Pe[1][0]+Pe[1][1])/t[1]-Pe[1][0]),o.position[2]],o.positionRaw=[o.position[0]/t[0],o.position[1]/t[1],2*o.position[2]/(t[0]+t[1])];if(T2)for(let o of e)o.positionRaw=[o.positionRaw[0]+T2[1],o.positionRaw[1]+T2[0],o.positionRaw[2]],o.position=[Math.trunc(o.positionRaw[0]*t[0]),Math.trunc(o.positionRaw[1]*t[1]),o.positionRaw[2]];return e}async function Vr(e){let t=e.find(a=>a.part==="leftPalm"),o=e.find(a=>a.part==="leftWrist"),n=e.find(a=>a.part==="leftIndex");t.position[2]=((o.position[2]||0)+(n.position[2]||0))/2;let r=e.find(a=>a.part==="rightPalm"),A=e.find(a=>a.part==="rightWrist"),s=e.find(a=>a.part==="rightIndex");r.position[2]=((A.position[2]||0)+(s.position[2]||0))/2}async function Dr(e,t,o){var u;let n={};[n.ld,n.segmentation,n.heatmap,n.world,n.poseflag]=(u=I0.landmarks)==null?void 0:u.execute(e,Gr.landmarks);let r=(await n.poseflag.data())[0],A=await n.ld.data(),s=await n.world.data();Object.keys(n).forEach(m=>j0.dispose(n[m]));let a=[],i=5;for(let m=0;m<A.length/i;m++){let P=l3(A[i*m+3]),g=l3(A[i*m+4]),b=Math.trunc(100*P*g*r)/100,d=[A[i*m+0]/_e.landmarks[0],A[i*m+1]/_e.landmarks[1],A[i*m+2]+0],M=[Math.trunc(o[0]*d[0]),Math.trunc(o[1]*d[1]),d[2]],S=[s[i*m+0],s[i*m+1],s[i*m+2]+0];a.push({part:_5[m],positionRaw:d,position:M,distance:S,score:b})}if(r<(t.body.minConfidence||0))return null;Vr(a);let x=Hr(a,o),c=x.map(m=>m.position),l=le(c,[o[0],o[1]]),y={};for(let[m,P]of Object.entries($5)){let g=[];for(let b=0;b<P.length-1;b++){let d=x.find(S=>S.part===P[b]),M=x.find(S=>S.part===P[b+1]);d&&M&&g.push([d.position,M.position])}y[m]=g}return{id:0,score:Math.trunc(100*r)/100,box:l.box,boxRaw:l.boxRaw,keypoints:x,annotations:y}}async function t1(e,t){let o=[e.shape[2]||0,e.shape[1]||0],n=(t.body.skipTime||0)>h()-i3,r=e1<(t.body.skipFrames||0);if(t.skipAllowed&&n&&r&&$2!==null)e1++;else{let A={};A.landmarks=await Br(e,256),$2=await Dr(A.landmarks,t,o),Object.keys(A).forEach(s=>j0.dispose(A[s])),i3=h(),e1=0}return $2?[$2]:[]}var T0=Z(D());var $e=[{class:1,label:"person"},{class:2,label:"bicycle"},{class:3,label:"car"},{class:4,label:"motorcycle"},{class:5,label:"airplane"},{class:6,label:"bus"},{class:7,label:"train"},{class:8,label:"truck"},{class:9,label:"boat"},{class:10,label:"traffic light"},{class:11,label:"fire hydrant"},{class:12,label:"stop sign"},{class:13,label:"parking meter"},{class:14,label:"bench"},{class:15,label:"bird"},{class:16,label:"cat"},{class:17,label:"dog"},{class:18,label:"horse"},{class:19,label:"sheep"},{class:20,label:"cow"},{class:21,label:"elephant"},{class:22,label:"bear"},{class:23,label:"zebra"},{class:24,label:"giraffe"},{class:25,label:"backpack"},{class:26,label:"umbrella"},{class:27,label:"handbag"},{class:28,label:"tie"},{class:29,label:"suitcase"},{class:30,label:"frisbee"},{class:31,label:"skis"},{class:32,label:"snowboard"},{class:33,label:"sports ball"},{class:34,label:"kite"},{class:35,label:"baseball bat"},{class:36,label:"baseball glove"},{class:37,label:"skateboard"},{class:38,label:"surfboard"},{class:39,label:"tennis racket"},{class:40,label:"bottle"},{class:41,label:"wine glass"},{class:42,label:"cup"},{class:43,label:"fork"},{class:44,label:"knife"},{class:45,label:"spoon"},{class:46,label:"bowl"},{class:47,label:"banana"},{class:48,label:"apple"},{class:49,label:"sandwich"},{class:50,label:"orange"},{class:51,label:"broccoli"},{class:52,label:"carrot"},{class:53,label:"hot dog"},{class:54,label:"pizza"},{class:55,label:"donut"},{class:56,label:"cake"},{class:57,label:"chair"},{class:58,label:"couch"},{class:59,label:"potted plant"},{class:60,label:"bed"},{class:61,label:"dining table"},{class:62,label:"toilet"},{class:63,label:"tv"},{class:64,label:"laptop"},{class:65,label:"mouse"},{class:66,label:"remote"},{class:67,label:"keyboard"},{class:68,label:"cell phone"},{class:69,label:"microwave"},{class:70,label:"oven"},{class:71,label:"toaster"},{class:72,label:"sink"},{class:73,label:"refrigerator"},{class:74,label:"book"},{class:75,label:"clock"},{class:76,label:"vase"},{class:77,label:"scissors"},{class:78,label:"teddy bear"},{class:79,label:"hair drier"},{class:80,label:"toothbrush"}];var ye,Le=0,o1=[],f3=0,n1=Number.MAX_SAFE_INTEGER;async function m3(e){if(v.initial&&(ye=null),ye)e.debug&&p("cached model:",ye.modelUrl);else{ye=await G(e.object.modelPath);let t=Object.values(ye.modelSignature.inputs);Le=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}return ye}async function Zr(e,t,o){if(!e)return[];let n={},r=[],A=await e.array();n.squeeze=T0.squeeze(e);let s=T0.split(n.squeeze,6,1);n.stack=T0.stack([s[1],s[0],s[3],s[2]],1),n.boxes=T0.squeeze(n.stack),n.scores=T0.squeeze(s[4]),n.classes=T0.squeeze(s[5]),T0.dispose([e,...s]),n.nms=await T0.image.nonMaxSuppressionAsync(n.boxes,n.scores,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence||0);let a=await n.nms.data(),i=0;for(let x of Array.from(a)){let c=Math.trunc(100*A[0][x][4])/100,l=A[0][x][5],y=$e[l].label,[f,u]=[A[0][x][0]/Le,A[0][x][1]/Le],m=[f,u,A[0][x][2]/Le-f,A[0][x][3]/Le-u],P=[Math.trunc(m[0]*t[0]),Math.trunc(m[1]*t[1]),Math.trunc(m[2]*t[0]),Math.trunc(m[3]*t[1])];r.push({id:i++,score:c,class:l,label:y,box:P,boxRaw:m})}return Object.keys(n).forEach(x=>T0.dispose(n[x])),r}async function r1(e,t){let o=(t.object.skipTime||0)>h()-f3,n=n1<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&o1.length>0?(n1++,o1):(n1=0,new Promise(async r=>{let A=[e.shape[2]||0,e.shape[1]||0],s=T0.image.resizeBilinear(e,[Le,Le]),a=t.object.enabled?ye==null?void 0:ye.execute(s,["tower_0/detections"]):null;f3=h(),T0.dispose(s);let i=await Zr(a,A,t);o1=i,r(i)}))}var _=Z(D());var e5={};ue(e5,{connected:()=>s1,kpt:()=>A1});var A1=["head","neck","rightShoulder","rightElbow","rightWrist","chest","leftShoulder","leftElbow","leftWrist","bodyCenter","rightHip","rightKnee","rightAnkle","leftHip","leftKnee","leftAnkle"],s1={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var b0,u3=0,w0={id:0,keypoints:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,annotations:{}},a1=Number.MAX_SAFE_INTEGER;async function h3(e){return v.initial&&(b0=null),b0?e.debug&&p("cached model:",b0.modelUrl):b0=await G(e.body.modelPath),b0}async function Xr(e,t){let[o,n]=e.shape,r=_.reshape(e,[n*o]),A=_.max(r,0),s=(await A.data())[0];if(_.dispose([r,A]),s>t){let a=_.argMax(r,0),i=_.mod(a,o),x=(await i.data())[0],c=_.div(a,_.scalar(o,"int32")),l=(await c.data())[0];return _.dispose([i,c]),[x,l,s]}return[0,0,s]}async function i1(e,t){let o=(t.body.skipTime||0)>h()-u3,n=a1<(t.body.skipFrames||0);return t.skipAllowed&&o&&n&&Object.keys(w0.keypoints).length>0?(a1++,[w0]):(a1=0,new Promise(async r=>{var l;let A=_.tidy(()=>{if(!(b0!=null&&b0.inputs[0].shape))return null;let y=_.image.resizeBilinear(e,[b0.inputs[0].shape[2],b0.inputs[0].shape[1]],!1),f=_.mul(y,V.tf2);return _.sub(f,V.tf1)}),s;if(t.body.enabled&&(s=b0==null?void 0:b0.execute(A)),u3=h(),_.dispose(A),s){w0.keypoints.length=0;let y=s.squeeze();_.dispose(s);let f=y.unstack(2);_.dispose(y);for(let u=0;u<f.length;u++){let[m,P,g]=await Xr(f[u],t.body.minConfidence);g>(((l=t.body)==null?void 0:l.minConfidence)||0)&&w0.keypoints.push({score:Math.round(100*g)/100,part:A1[u],positionRaw:[m/b0.inputs[0].shape[2],P/b0.inputs[0].shape[1]],position:[Math.round(e.shape[2]*m/b0.inputs[0].shape[2]),Math.round(e.shape[1]*P/b0.inputs[0].shape[1])]})}f.forEach(u=>_.dispose(u))}w0.score=w0.keypoints.reduce((y,f)=>f.score>y?f.score:y,0);let a=w0.keypoints.map(y=>y.position[0]),i=w0.keypoints.map(y=>y.position[1]);w0.box=[Math.min(...a),Math.min(...i),Math.max(...a)-Math.min(...a),Math.max(...i)-Math.min(...i)];let x=w0.keypoints.map(y=>y.positionRaw[0]),c=w0.keypoints.map(y=>y.positionRaw[1]);w0.boxRaw=[Math.min(...x),Math.min(...c),Math.max(...x)-Math.min(...x),Math.max(...c)-Math.min(...c)];for(let[y,f]of Object.entries(s1)){let u=[];for(let m=0;m<f.length-1;m++){let P=w0.keypoints.find(b=>b.part===f[m]),g=w0.keypoints.find(b=>b.part===f[m+1]);P&&g&&P.score>(t.body.minConfidence||0)&&g.score>(t.body.minConfidence||0)&&u.push([P.position,g.position])}w0.annotations[y]=u}r([w0])}))}var U0=Z(D());var qr=["angry","disgust","fear","happy","sad","surprise","neutral"],H0,t5=[],g3=0,M3=0,l1=Number.MAX_SAFE_INTEGER;async function P3(e){var t;return v.initial&&(H0=null),H0?e.debug&&p("cached model:",H0.modelUrl):H0=await G((t=e.face.emotion)==null?void 0:t.modelPath),H0}async function y1(e,t,o,n){var s,a;if(!H0)return[];let r=l1<(((s=t.face.emotion)==null?void 0:s.skipFrames)||0),A=(((a=t.face.emotion)==null?void 0:a.skipTime)||0)>h()-M3;return t.skipAllowed&&A&&r&&g3===n&&t5[o]&&t5[o].length>0?(l1++,t5[o]):(l1=0,new Promise(async i=>{var c,l;let x=[];if((c=t.face.emotion)!=null&&c.enabled){let y={},f=H0!=null&&H0.inputs[0].shape?H0.inputs[0].shape[2]:0;y.resize=U0.image.resizeBilinear(e,[f,f],!1),y.channels=U0.mul(y.resize,V.rgb),y.grayscale=U0.sum(y.channels,3,!0),y.grayscaleSub=U0.sub(y.grayscale,V.tf05),y.grayscaleMul=U0.mul(y.grayscaleSub,V.tf2),y.emotion=H0==null?void 0:H0.execute(y.grayscaleMul),M3=h();let u=await y.emotion.data();for(let m=0;m<u.length;m++)u[m]>(((l=t.face.emotion)==null?void 0:l.minConfidence)||0)&&x.push({score:Math.min(.99,Math.trunc(100*u[m])/100),emotion:qr[m]});x.sort((m,P)=>P.score-m.score),Object.keys(y).forEach(m=>U0.dispose(y[m]))}t5[o]=x,g3=n,i(x)}))}var k3=Z(D());var O0,x1=[],v3=0,T3=0,w3=Number.MAX_SAFE_INTEGER;async function E3(e){return v.initial&&(O0=null),O0?e.debug&&p("cached model:",O0.modelUrl):O0=await G(e.face.mobilefacenet.modelPath),O0}async function c1(e,t,o,n){var s,a;if(!O0)return[];let r=w3<(((s=t.face.embedding)==null?void 0:s.skipFrames)||0),A=(((a=t.face.embedding)==null?void 0:a.skipTime)||0)>h()-T3;return t.skipAllowed&&A&&r&&v3===n&&x1[o]?(w3++,x1[o]):new Promise(async i=>{var c;let x=[];if(((c=t.face.embedding)==null?void 0:c.enabled)&&(O0==null?void 0:O0.inputs[0].shape)){let l={};l.crop=k3.image.resizeBilinear(e,[O0.inputs[0].shape[2],O0.inputs[0].shape[1]],!1),l.data=O0==null?void 0:O0.execute(l.crop);let y=await l.data.data();x=Array.from(y)}x1[o]=x,v3=n,T3=h(),i(x)})}var Be=Z(D());var Y0=Z(D());var xe,Re=0,Ur=2.3,d1=X0.leftEyeLower0,f1=X0.rightEyeLower0,e2={leftBounds:[d1[0],d1[d1.length-1]],rightBounds:[f1[0],f1[f1.length-1]]},t2={upperCenter:3,lowerCenter:4,index:71,numCoordinates:76};async function j3(e){var t;return v.initial&&(xe=null),xe?e.debug&&p("cached model:",xe.modelUrl):xe=await G((t=e.face.iris)==null?void 0:t.modelPath),Re=xe.inputs[0].shape?xe.inputs[0].shape[2]:0,Re===-1&&(Re=64),xe}function o5(e,t,o,n){for(let r=0;r<U5.length;r++){let{key:A,indices:s}=U5[r],a=X0[`${o}${A}`];if(!n||n.includes(A))for(let i=0;i<s.length;i++){let x=s[i];e[a[i]]=[t[x][0],t[x][1],(t[x][2]+e[a[i]][2])/2]}}}var Yr=e=>{let t=e[e2.leftBounds[0]][2],o=e[e2.rightBounds[0]][2];return t-o},S3=(e,t,o,n,r,A=!1)=>{let s=Y2(U2(Yt([e[o],e[n]]),Ur)),a=Je(s),i=Y0.image.cropAndResize(t,[[s.startPoint[1]/r,s.startPoint[0]/r,s.endPoint[1]/r,s.endPoint[0]/r]],[0],[Re,Re]);if(A&&v.kernels.includes("flipleftright")){let x=Y0.image.flipLeftRight(i);Y0.dispose(i),i=x}return{box:s,boxSize:a,crop:i}},C3=(e,t,o,n=!1)=>{let r=[];for(let A=0;A<t2.numCoordinates;A++){let s=e[A*3],a=e[A*3+1],i=e[A*3+2];r.push([(n?1-s/Re:s/Re)*o[0]+t.startPoint[0],a/Re*o[1]+t.startPoint[1],i])}return{rawCoords:r,iris:r.slice(t2.index)}},I3=(e,t,o)=>{let n=e[X0[`${o}EyeUpper0`][t2.upperCenter]][2],r=e[X0[`${o}EyeLower0`][t2.lowerCenter]][2],A=(n+r)/2;return t.map((s,a)=>{let i=A;return a===2?i=n:a===4&&(i=r),[s[0],s[1],i]})};async function O3(e,t,o,n){if(!xe)return o.debug&&p("face mesh iris detection requested, but model is not loaded"),e;let{box:r,boxSize:A,crop:s}=S3(e,t,e2.leftBounds[0],e2.leftBounds[1],n,!0),{box:a,boxSize:i,crop:x}=S3(e,t,e2.rightBounds[0],e2.rightBounds[1],n,!0),c=Y0.concat([s,x]);Y0.dispose(s),Y0.dispose(x);let l=xe.execute(c);Y0.dispose(c);let y=await l.data();Y0.dispose(l);let f=y.slice(0,t2.numCoordinates*3),{rawCoords:u,iris:m}=C3(f,r,A,!0),P=y.slice(t2.numCoordinates*3),{rawCoords:g,iris:b}=C3(P,a,i,!1),d=Yr(e);Math.abs(d)<30?(o5(e,u,"left",null),o5(e,g,"right",null)):d<1?o5(e,u,"left",["EyeUpper0","EyeLower0"]):o5(e,g,"right",["EyeUpper0","EyeLower0"]);let M=I3(e,m,"left"),S=I3(e,b,"right");return e.concat(M).concat(S)}var Kr=[[61,146],[146,91],[91,181],[181,84],[84,17],[17,314],[314,405],[405,321],[321,375],[375,291],[61,185],[185,40],[40,39],[39,37],[37,0],[0,267],[267,269],[269,270],[270,409],[409,291],[78,95],[95,88],[88,178],[178,87],[87,14],[14,317],[317,402],[402,318],[318,324],[324,308],[78,191],[191,80],[80,81],[81,82],[82,13],[13,312],[312,311],[311,310],[310,415],[415,308]],Jr=[[263,249],[249,390],[390,373],[373,374],[374,380],[380,381],[381,382],[382,362],[263,466],[466,388],[388,387],[387,386],[386,385],[385,384],[384,398],[398,362]],Qr=[[276,283],[283,282],[282,295],[295,285],[300,293],[293,334],[334,296],[296,336]],_r=[[474,475],[475,476],[476,477],[477,474]],$r=[[33,7],[7,163],[163,144],[144,145],[145,153],[153,154],[154,155],[155,133],[33,246],[246,161],[161,160],[160,159],[159,158],[158,157],[157,173],[173,133]],eA=[[46,53],[53,52],[52,65],[65,55],[70,63],[63,105],[105,66],[66,107]],tA=[[469,470],[470,471],[471,472],[472,469]],oA=[[10,338],[338,297],[297,332],[332,284],[284,251],[251,389],[389,356],[356,454],[454,323],[323,361],[361,288],[288,397],[397,365],[365,379],[379,378],[378,400],[400,377],[377,152],[152,148],[148,176],[176,149],[149,150],[150,136],[136,172],[172,58],[58,132],[132,93],[93,234],[234,127],[127,162],[162,21],[21,54],[54,103],[103,67],[67,109],[109,10]];function ve(e){let t=e.map(o=>o[0]);return t.push(e[e.length-1][1]),t}var nA={lips:ve(Kr),leftEye:ve(Jr),leftEyebrow:ve(Qr),leftIris:ve(_r),rightEye:ve($r),rightEyebrow:ve(eA),rightIris:ve(tA),faceOval:ve(oA)},rA=Object.entries(nA).map(([e,t])=>t.map(o=>[o,e])).flat(),f4=new Map(rA),w2=[61,146,91,181,84,17,314,405,321,375,291,185,40,39,37,0,267,269,270,409,78,95,88,178,87,14,317,402,318,324,308,191,80,81,82,13,312,311,310,415,76,77,90,180,85,16,315,404,320,307,306,184,74,73,72,11,302,303,304,408,62,96,89,179,86,15,316,403,319,325,292,183,42,41,38,12,268,271,272,407],We=[33,7,163,144,145,153,154,155,133,246,161,160,159,158,157,173,130,25,110,24,23,22,26,112,243,247,30,29,27,28,56,190,226,31,228,229,230,231,232,233,244,113,225,224,223,222,221,189,35,124,46,53,52,65,143,111,117,118,119,120,121,128,245,156,70,63,105,66,107,55,193],Fe=[263,249,390,373,374,380,381,382,362,466,388,387,386,385,384,398,359,255,339,254,253,252,256,341,463,467,260,259,257,258,286,414,446,261,448,449,450,451,452,453,464,342,445,444,443,442,441,413,265,353,276,283,282,295,372,340,346,347,348,349,350,357,465,383,300,293,334,296,336,285,417];async function W3(e,t){let o={lips:await t.filter(A=>A.size===160)[0].data(),irisL:await t.filter(A=>A.size===10)[0].data(),eyeL:await t.filter(A=>A.size===142)[0].data(),irisR:await t.filter(A=>A.size===10)[1].data(),eyeR:await t.filter(A=>A.size===142)[1].data()},n=We.reduce((A,s)=>A+=e[s][2],0)/We.length;for(let A=0;A<o.irisL.length/2;A++)e.push([o.irisL[2*A+0],o.irisL[2*A+1],n]);let r=Fe.reduce((A,s)=>A+=e[s][2],0)/Fe.length;for(let A=0;A<o.irisR.length/2;A++)e.push([o.irisR[2*A+0],o.irisR[2*A+1],r]);for(let A=0;A<o.eyeL.length/2;A++)e[We[A]]=[o.eyeL[2*A+0],o.eyeL[2*A+1],e[We[A]][2]];for(let A=0;A<o.eyeR.length/2;A++)e[Fe[A]]=[o.eyeR[2*A+0],o.eyeR[2*A+1],e[Fe[A]][2]];for(let A=0;A<o.lips.length/2;A++)e[w2[A]]=[o.lips[2*A+0],o.lips[2*A+1],e[w2[A]][2]];return e}var oe={boxes:[],skipped:Number.MAX_SAFE_INTEGER,timestamp:0},g0=null,Ge=0;async function F3(e,t){var a,i,x,c,l,y,f,u,m,P,g;let o=(((a=t.face.detector)==null?void 0:a.skipTime)||0)>h()-oe.timestamp,n=oe.skipped<(((i=t.face.detector)==null?void 0:i.skipFrames)||0);!t.skipAllowed||!o||!n||oe.boxes.length===0?(oe.boxes=await n3(e,t),oe.timestamp=h(),oe.skipped=0):oe.skipped++;let r=[],A=[],s=0;for(let b=0;b<oe.boxes.length;b++){let d=oe.boxes[b],M=0,S,w={id:s++,mesh:[],meshRaw:[],box:[0,0,0,0],boxRaw:[0,0,0,0],score:0,boxScore:0,faceScore:0,annotations:{}};if([M,S,w.tensor]=_t((x=t.face.detector)==null?void 0:x.rotation,d,e,(c=t.face.mesh)!=null&&c.enabled?Ge:Qe()),(l=t==null?void 0:t.filter)!=null&&l.equalization){let j=await N2(w.tensor);Be.dispose(w.tensor),w.tensor=j}if(w.boxScore=Math.round(100*d.confidence)/100,(y=t.face.mesh)!=null&&y.enabled)if(!g0)t.debug&&p("face mesh detection requested, but model is not loaded");else{let j=g0.execute(w.tensor),F=await j.find(H=>H.shape[H.shape.length-1]===1).data();if(w.faceScore=Math.round(100*F[0])/100,w.faceScore<(((f=t.face.detector)==null?void 0:f.minConfidence)||1)){if(d.confidence=w.faceScore,(u=t.face.mesh)!=null&&u.keepInvalid){w.box=X2(d,e),w.boxRaw=q2(d,e),w.score=w.boxScore,w.mesh=d.landmarks.map(H=>[(d.startPoint[0]+d.endPoint[0])/2+(d.endPoint[0]+d.startPoint[0])*H[0]/Qe(),(d.startPoint[1]+d.endPoint[1])/2+(d.endPoint[1]+d.startPoint[1])*H[1]/Qe()]),w.meshRaw=w.mesh.map(H=>[H[0]/(e.shape[2]||1),H[1]/(e.shape[1]||1),(H[2]||0)/Ge]);for(let H of Object.keys(je))w.annotations[H]=[w.mesh[je[H]]]}}else{let H=j.find(E=>E.shape[E.shape.length-1]===1404),Y=Be.reshape(H,[-1,3]),J=await Y.array();Be.dispose(Y),(m=t.face.attention)!=null&&m.enabled?J=await W3(J,j):(P=t.face.iris)!=null&&P.enabled&&(J=await O3(J,w.tensor,t,Ge)),w.mesh=Qt(J,d,M,S,Ge),w.meshRaw=w.mesh.map(E=>[E[0]/(e.shape[2]||0),E[1]/(e.shape[1]||0),(E[2]||0)/Ge]);for(let E of Object.keys(X0))w.annotations[E]=X0[E].map(G0=>w.mesh[G0]);w.score=w.faceScore;let x0={...$t(w.mesh,d),confidence:d.confidence,landmarks:d.landmarks};w.box=X2(x0,e),w.boxRaw=q2(x0,e),A.push(x0)}Be.dispose(j)}else{w.box=X2(d,e),w.boxRaw=q2(d,e),w.score=w.boxScore,w.mesh=d.landmarks.map(j=>[(d.startPoint[0]+d.endPoint[0])/2+(d.endPoint[0]+d.startPoint[0])*j[0]/Qe(),(d.startPoint[1]+d.endPoint[1])/2+(d.endPoint[1]+d.startPoint[1])*j[1]/Qe()]),w.meshRaw=w.mesh.map(j=>[j[0]/(e.shape[2]||0),j[1]/(e.shape[1]||0),(j[2]||0)/Ge]);for(let j of Object.keys(je))w.annotations[j]=[w.mesh[je[j]]]}w.score>(((g=t.face.detector)==null?void 0:g.minConfidence)||1)?r.push(w):Be.dispose(w.tensor)}return oe.boxes=A,r}async function G3(e){var t,o,n,r,A,s;return v.initial&&(g0=null),((o=(t=e==null?void 0:e.face)==null?void 0:t.attention)==null?void 0:o.enabled)&&(g0==null?void 0:g0.signature)&&Object.keys(((n=g0==null?void 0:g0.signature)==null?void 0:n.outputs)||{}).length<6&&(g0=null),g0?e.debug&&p("cached model:",g0.modelUrl):(r=e.face.attention)!=null&&r.enabled?g0=await G((A=e.face.attention)==null?void 0:A.modelPath):g0=await G((s=e.face.mesh)==null?void 0:s.modelPath),Ge=g0.inputs[0].shape?g0.inputs[0].shape[2]:0,g0}var B3=Oe,H3=R2;var K0=Z(D());var N0,n5=[],V3=0,D3=0,p1=Number.MAX_SAFE_INTEGER;async function Z3(e){var t;return v.initial&&(N0=null),N0?e.debug&&p("cached model:",N0.modelUrl):N0=await G((t=e.face.description)==null?void 0:t.modelPath),N0}function u1(e){let t=e.image||e.tensor||e;if(!(N0!=null&&N0.inputs[0].shape))return t;let o=K0.image.resizeBilinear(t,[N0.inputs[0].shape[2],N0.inputs[0].shape[1]],!1),n=K0.mul(o,V.tf255);return K0.dispose(o),n}async function h1(e,t,o,n){var s,a,i,x;if(!N0)return{age:0,gender:"unknown",genderScore:0,descriptor:[]};let r=p1<(((s=t.face.description)==null?void 0:s.skipFrames)||0),A=(((a=t.face.description)==null?void 0:a.skipTime)||0)>h()-V3;return t.skipAllowed&&r&&A&&D3===n&&((i=n5[o])==null?void 0:i.age)&&((x=n5[o])==null?void 0:x.age)>0?(p1++,n5[o]):(p1=0,new Promise(async c=>{var y,f;let l={age:0,gender:"unknown",genderScore:0,descriptor:[]};if((y=t.face.description)!=null&&y.enabled){let u=u1(e),m=N0==null?void 0:N0.execute(u);V3=h(),K0.dispose(u);let g=await(await m.find(F=>F.shape[1]===1)).data(),b=Math.trunc(200*Math.abs(g[0]-.5))/100;b>(((f=t.face.description)==null?void 0:f.minConfidence)||0)&&(l.gender=g[0]<=.5?"female":"male",l.genderScore=Math.min(.99,b));let d=K0.argMax(m.find(F=>F.shape[1]===100),1),M=(await d.data())[0];K0.dispose(d);let w=await m.find(F=>F.shape[1]===100).data();l.age=Math.round(w[M-1]>w[M+1]?10*M-100*w[M-1]:10*M+100*w[M+1])/10;let j=m.find(F=>F.shape[1]===1024),C=j?await j.data():[];l.descriptor=Array.from(C),m.forEach(F=>K0.dispose(F))}n5[o]=l,D3=n,c(l)}))}var W=Z(D());var U3=Z(D());function r5(e){return[Math.abs(e.endPoint[0]-e.startPoint[0]),Math.abs(e.endPoint[1]-e.startPoint[1])]}function k2(e){return[e.startPoint[0]+(e.endPoint[0]-e.startPoint[0])/2,e.startPoint[1]+(e.endPoint[1]-e.startPoint[1])/2]}function Y3(e,t,o){let n=t.shape[1],r=t.shape[2],A=[[e.startPoint[1]/n,e.startPoint[0]/r,e.endPoint[1]/n,e.endPoint[0]/r]];return U3.image.cropAndResize(t,A,[0],o)}function K3(e,t){let o=[e.startPoint[0]*t[0],e.startPoint[1]*t[1]],n=[e.endPoint[0]*t[0],e.endPoint[1]*t[1]],r=e.palmLandmarks.map(A=>[A[0]*t[0],A[1]*t[1]]);return{startPoint:o,endPoint:n,palmLandmarks:r,confidence:e.confidence}}function A5(e,t=1.5){let o=k2(e),n=r5(e),r=[t*n[0]/2,t*n[1]/2],A=[o[0]-r[0],o[1]-r[1]],s=[o[0]+r[0],o[1]+r[1]];return{startPoint:A,endPoint:s,palmLandmarks:e.palmLandmarks}}function s5(e){let t=k2(e),o=r5(e),r=Math.max(...o)/2,A=[t[0]-r,t[1]-r],s=[t[0]+r,t[1]+r];return{startPoint:A,endPoint:s,palmLandmarks:e.palmLandmarks}}function sA(e){return e-2*Math.PI*Math.floor((e+Math.PI)/(2*Math.PI))}function J3(e,t){let o=Math.PI/2-Math.atan2(-(t[1]-e[1]),t[0]-e[0]);return sA(o)}var X3=(e,t)=>[[1,0,e],[0,1,t],[0,0,1]];function Te(e,t){let o=0;for(let n=0;n<e.length;n++)o+=e[n]*t[n];return o}function aA(e,t){let o=[];for(let n=0;n<e.length;n++)o.push(e[n][t]);return o}function q3(e,t){let o=[],n=e.length;for(let r=0;r<n;r++){o.push([]);for(let A=0;A<n;A++)o[r].push(Te(e[r],aA(t,A)))}return o}function g1(e,t){let o=Math.cos(e),n=Math.sin(e),r=[[o,-n,0],[n,o,0],[0,0,1]],A=X3(t[0],t[1]),s=q3(A,r),a=X3(-t[0],-t[1]);return q3(s,a)}function Q3(e){let t=[[e[0][0],e[1][0]],[e[0][1],e[1][1]]],o=[e[0][2],e[1][2]],n=[-Te(t[0],o),-Te(t[1],o)];return[t[0].concat(n[0]),t[1].concat(n[1]),[0,0,1]]}function M1(e,t){return[Te(e,t[0]),Te(e,t[1])]}var $3=[{x:.015625,y:.015625},{x:.015625,y:.015625},{x:.046875,y:.015625},{x:.046875,y:.015625},{x:.078125,y:.015625},{x:.078125,y:.015625},{x:.109375,y:.015625},{x:.109375,y:.015625},{x:.140625,y:.015625},{x:.140625,y:.015625},{x:.171875,y:.015625},{x:.171875,y:.015625},{x:.203125,y:.015625},{x:.203125,y:.015625},{x:.234375,y:.015625},{x:.234375,y:.015625},{x:.265625,y:.015625},{x:.265625,y:.015625},{x:.296875,y:.015625},{x:.296875,y:.015625},{x:.328125,y:.015625},{x:.328125,y:.015625},{x:.359375,y:.015625},{x:.359375,y:.015625},{x:.390625,y:.015625},{x:.390625,y:.015625},{x:.421875,y:.015625},{x:.421875,y:.015625},{x:.453125,y:.015625},{x:.453125,y:.015625},{x:.484375,y:.015625},{x:.484375,y:.015625},{x:.515625,y:.015625},{x:.515625,y:.015625},{x:.546875,y:.015625},{x:.546875,y:.015625},{x:.578125,y:.015625},{x:.578125,y:.015625},{x:.609375,y:.015625},{x:.609375,y:.015625},{x:.640625,y:.015625},{x:.640625,y:.015625},{x:.671875,y:.015625},{x:.671875,y:.015625},{x:.703125,y:.015625},{x:.703125,y:.015625},{x:.734375,y:.015625},{x:.734375,y:.015625},{x:.765625,y:.015625},{x:.765625,y:.015625},{x:.796875,y:.015625},{x:.796875,y:.015625},{x:.828125,y:.015625},{x:.828125,y:.015625},{x:.859375,y:.015625},{x:.859375,y:.015625},{x:.890625,y:.015625},{x:.890625,y:.015625},{x:.921875,y:.015625},{x:.921875,y:.015625},{x:.953125,y:.015625},{x:.953125,y:.015625},{x:.984375,y:.015625},{x:.984375,y:.015625},{x:.015625,y:.046875},{x:.015625,y:.046875},{x:.046875,y:.046875},{x:.046875,y:.046875},{x:.078125,y:.046875},{x:.078125,y:.046875},{x:.109375,y:.046875},{x:.109375,y:.046875},{x:.140625,y:.046875},{x:.140625,y:.046875},{x:.171875,y:.046875},{x:.171875,y:.046875},{x:.203125,y:.046875},{x:.203125,y:.046875},{x:.234375,y:.046875},{x:.234375,y:.046875},{x:.265625,y:.046875},{x:.265625,y:.046875},{x:.296875,y:.046875},{x:.296875,y:.046875},{x:.328125,y:.046875},{x:.328125,y:.046875},{x:.359375,y:.046875},{x:.359375,y:.046875},{x:.390625,y:.046875},{x:.390625,y:.046875},{x:.421875,y:.046875},{x:.421875,y:.046875},{x:.453125,y:.046875},{x:.453125,y:.046875},{x:.484375,y:.046875},{x:.484375,y:.046875},{x:.515625,y:.046875},{x:.515625,y:.046875},{x:.546875,y:.046875},{x:.546875,y:.046875},{x:.578125,y:.046875},{x:.578125,y:.046875},{x:.609375,y:.046875},{x:.609375,y:.046875},{x:.640625,y:.046875},{x:.640625,y:.046875},{x:.671875,y:.046875},{x:.671875,y:.046875},{x:.703125,y:.046875},{x:.703125,y:.046875},{x:.734375,y:.046875},{x:.734375,y:.046875},{x:.765625,y:.046875},{x:.765625,y:.046875},{x:.796875,y:.046875},{x:.796875,y:.046875},{x:.828125,y:.046875},{x:.828125,y:.046875},{x:.859375,y:.046875},{x:.859375,y:.046875},{x:.890625,y:.046875},{x:.890625,y:.046875},{x:.921875,y:.046875},{x:.921875,y:.046875},{x:.953125,y:.046875},{x:.953125,y:.046875},{x:.984375,y:.046875},{x:.984375,y:.046875},{x:.015625,y:.078125},{x:.015625,y:.078125},{x:.046875,y:.078125},{x:.046875,y:.078125},{x:.078125,y:.078125},{x:.078125,y:.078125},{x:.109375,y:.078125},{x:.109375,y:.078125},{x:.140625,y:.078125},{x:.140625,y:.078125},{x:.171875,y:.078125},{x:.171875,y:.078125},{x:.203125,y:.078125},{x:.203125,y:.078125},{x:.234375,y:.078125},{x:.234375,y:.078125},{x:.265625,y:.078125},{x:.265625,y:.078125},{x:.296875,y:.078125},{x:.296875,y:.078125},{x:.328125,y:.078125},{x:.328125,y:.078125},{x:.359375,y:.078125},{x:.359375,y:.078125},{x:.390625,y:.078125},{x:.390625,y:.078125},{x:.421875,y:.078125},{x:.421875,y:.078125},{x:.453125,y:.078125},{x:.453125,y:.078125},{x:.484375,y:.078125},{x:.484375,y:.078125},{x:.515625,y:.078125},{x:.515625,y:.078125},{x:.546875,y:.078125},{x:.546875,y:.078125},{x:.578125,y:.078125},{x:.578125,y:.078125},{x:.609375,y:.078125},{x:.609375,y:.078125},{x:.640625,y:.078125},{x:.640625,y:.078125},{x:.671875,y:.078125},{x:.671875,y:.078125},{x:.703125,y:.078125},{x:.703125,y:.078125},{x:.734375,y:.078125},{x:.734375,y:.078125},{x:.765625,y:.078125},{x:.765625,y:.078125},{x:.796875,y:.078125},{x:.796875,y:.078125},{x:.828125,y:.078125},{x:.828125,y:.078125},{x:.859375,y:.078125},{x:.859375,y:.078125},{x:.890625,y:.078125},{x:.890625,y:.078125},{x:.921875,y:.078125},{x:.921875,y:.078125},{x:.953125,y:.078125},{x:.953125,y:.078125},{x:.984375,y:.078125},{x:.984375,y:.078125},{x:.015625,y:.109375},{x:.015625,y:.109375},{x:.046875,y:.109375},{x:.046875,y:.109375},{x:.078125,y:.109375},{x:.078125,y:.109375},{x:.109375,y:.109375},{x:.109375,y:.109375},{x:.140625,y:.109375},{x:.140625,y:.109375},{x:.171875,y:.109375},{x:.171875,y:.109375},{x:.203125,y:.109375},{x:.203125,y:.109375},{x:.234375,y:.109375},{x:.234375,y:.109375},{x:.265625,y:.109375},{x:.265625,y:.109375},{x:.296875,y:.109375},{x:.296875,y:.109375},{x:.328125,y:.109375},{x:.328125,y:.109375},{x:.359375,y:.109375},{x:.359375,y:.109375},{x:.390625,y:.109375},{x:.390625,y:.109375},{x:.421875,y:.109375},{x:.421875,y:.109375},{x:.453125,y:.109375},{x:.453125,y:.109375},{x:.484375,y:.109375},{x:.484375,y:.109375},{x:.515625,y:.109375},{x:.515625,y:.109375},{x:.546875,y:.109375},{x:.546875,y:.109375},{x:.578125,y:.109375},{x:.578125,y:.109375},{x:.609375,y:.109375},{x:.609375,y:.109375},{x:.640625,y:.109375},{x:.640625,y:.109375},{x:.671875,y:.109375},{x:.671875,y:.109375},{x:.703125,y:.109375},{x:.703125,y:.109375},{x:.734375,y:.109375},{x:.734375,y:.109375},{x:.765625,y:.109375},{x:.765625,y:.109375},{x:.796875,y:.109375},{x:.796875,y:.109375},{x:.828125,y:.109375},{x:.828125,y:.109375},{x:.859375,y:.109375},{x:.859375,y:.109375},{x:.890625,y:.109375},{x:.890625,y:.109375},{x:.921875,y:.109375},{x:.921875,y:.109375},{x:.953125,y:.109375},{x:.953125,y:.109375},{x:.984375,y:.109375},{x:.984375,y:.109375},{x:.015625,y:.140625},{x:.015625,y:.140625},{x:.046875,y:.140625},{x:.046875,y:.140625},{x:.078125,y:.140625},{x:.078125,y:.140625},{x:.109375,y:.140625},{x:.109375,y:.140625},{x:.140625,y:.140625},{x:.140625,y:.140625},{x:.171875,y:.140625},{x:.171875,y:.140625},{x:.203125,y:.140625},{x:.203125,y:.140625},{x:.234375,y:.140625},{x:.234375,y:.140625},{x:.265625,y:.140625},{x:.265625,y:.140625},{x:.296875,y:.140625},{x:.296875,y:.140625},{x:.328125,y:.140625},{x:.328125,y:.140625},{x:.359375,y:.140625},{x:.359375,y:.140625},{x:.390625,y:.140625},{x:.390625,y:.140625},{x:.421875,y:.140625},{x:.421875,y:.140625},{x:.453125,y:.140625},{x:.453125,y:.140625},{x:.484375,y:.140625},{x:.484375,y:.140625},{x:.515625,y:.140625},{x:.515625,y:.140625},{x:.546875,y:.140625},{x:.546875,y:.140625},{x:.578125,y:.140625},{x:.578125,y:.140625},{x:.609375,y:.140625},{x:.609375,y:.140625},{x:.640625,y:.140625},{x:.640625,y:.140625},{x:.671875,y:.140625},{x:.671875,y:.140625},{x:.703125,y:.140625},{x:.703125,y:.140625},{x:.734375,y:.140625},{x:.734375,y:.140625},{x:.765625,y:.140625},{x:.765625,y:.140625},{x:.796875,y:.140625},{x:.796875,y:.140625},{x:.828125,y:.140625},{x:.828125,y:.140625},{x:.859375,y:.140625},{x:.859375,y:.140625},{x:.890625,y:.140625},{x:.890625,y:.140625},{x:.921875,y:.140625},{x:.921875,y:.140625},{x:.953125,y:.140625},{x:.953125,y:.140625},{x:.984375,y:.140625},{x:.984375,y:.140625},{x:.015625,y:.171875},{x:.015625,y:.171875},{x:.046875,y:.171875},{x:.046875,y:.171875},{x:.078125,y:.171875},{x:.078125,y:.171875},{x:.109375,y:.171875},{x:.109375,y:.171875},{x:.140625,y:.171875},{x:.140625,y:.171875},{x:.171875,y:.171875},{x:.171875,y:.171875},{x:.203125,y:.171875},{x:.203125,y:.171875},{x:.234375,y:.171875},{x:.234375,y:.171875},{x:.265625,y:.171875},{x:.265625,y:.171875},{x:.296875,y:.171875},{x:.296875,y:.171875},{x:.328125,y:.171875},{x:.328125,y:.171875},{x:.359375,y:.171875},{x:.359375,y:.171875},{x:.390625,y:.171875},{x:.390625,y:.171875},{x:.421875,y:.171875},{x:.421875,y:.171875},{x:.453125,y:.171875},{x:.453125,y:.171875},{x:.484375,y:.171875},{x:.484375,y:.171875},{x:.515625,y:.171875},{x:.515625,y:.171875},{x:.546875,y:.171875},{x:.546875,y:.171875},{x:.578125,y:.171875},{x:.578125,y:.171875},{x:.609375,y:.171875},{x:.609375,y:.171875},{x:.640625,y:.171875},{x:.640625,y:.171875},{x:.671875,y:.171875},{x:.671875,y:.171875},{x:.703125,y:.171875},{x:.703125,y:.171875},{x:.734375,y:.171875},{x:.734375,y:.171875},{x:.765625,y:.171875},{x:.765625,y:.171875},{x:.796875,y:.171875},{x:.796875,y:.171875},{x:.828125,y:.171875},{x:.828125,y:.171875},{x:.859375,y:.171875},{x:.859375,y:.171875},{x:.890625,y:.171875},{x:.890625,y:.171875},{x:.921875,y:.171875},{x:.921875,y:.171875},{x:.953125,y:.171875},{x:.953125,y:.171875},{x:.984375,y:.171875},{x:.984375,y:.171875},{x:.015625,y:.203125},{x:.015625,y:.203125},{x:.046875,y:.203125},{x:.046875,y:.203125},{x:.078125,y:.203125},{x:.078125,y:.203125},{x:.109375,y:.203125},{x:.109375,y:.203125},{x:.140625,y:.203125},{x:.140625,y:.203125},{x:.171875,y:.203125},{x:.171875,y:.203125},{x:.203125,y:.203125},{x:.203125,y:.203125},{x:.234375,y:.203125},{x:.234375,y:.203125},{x:.265625,y:.203125},{x:.265625,y:.203125},{x:.296875,y:.203125},{x:.296875,y:.203125},{x:.328125,y:.203125},{x:.328125,y:.203125},{x:.359375,y:.203125},{x:.359375,y:.203125},{x:.390625,y:.203125},{x:.390625,y:.203125},{x:.421875,y:.203125},{x:.421875,y:.203125},{x:.453125,y:.203125},{x:.453125,y:.203125},{x:.484375,y:.203125},{x:.484375,y:.203125},{x:.515625,y:.203125},{x:.515625,y:.203125},{x:.546875,y:.203125},{x:.546875,y:.203125},{x:.578125,y:.203125},{x:.578125,y:.203125},{x:.609375,y:.203125},{x:.609375,y:.203125},{x:.640625,y:.203125},{x:.640625,y:.203125},{x:.671875,y:.203125},{x:.671875,y:.203125},{x:.703125,y:.203125},{x:.703125,y:.203125},{x:.734375,y:.203125},{x:.734375,y:.203125},{x:.765625,y:.203125},{x:.765625,y:.203125},{x:.796875,y:.203125},{x:.796875,y:.203125},{x:.828125,y:.203125},{x:.828125,y:.203125},{x:.859375,y:.203125},{x:.859375,y:.203125},{x:.890625,y:.203125},{x:.890625,y:.203125},{x:.921875,y:.203125},{x:.921875,y:.203125},{x:.953125,y:.203125},{x:.953125,y:.203125},{x:.984375,y:.203125},{x:.984375,y:.203125},{x:.015625,y:.234375},{x:.015625,y:.234375},{x:.046875,y:.234375},{x:.046875,y:.234375},{x:.078125,y:.234375},{x:.078125,y:.234375},{x:.109375,y:.234375},{x:.109375,y:.234375},{x:.140625,y:.234375},{x:.140625,y:.234375},{x:.171875,y:.234375},{x:.171875,y:.234375},{x:.203125,y:.234375},{x:.203125,y:.234375},{x:.234375,y:.234375},{x:.234375,y:.234375},{x:.265625,y:.234375},{x:.265625,y:.234375},{x:.296875,y:.234375},{x:.296875,y:.234375},{x:.328125,y:.234375},{x:.328125,y:.234375},{x:.359375,y:.234375},{x:.359375,y:.234375},{x:.390625,y:.234375},{x:.390625,y:.234375},{x:.421875,y:.234375},{x:.421875,y:.234375},{x:.453125,y:.234375},{x:.453125,y:.234375},{x:.484375,y:.234375},{x:.484375,y:.234375},{x:.515625,y:.234375},{x:.515625,y:.234375},{x:.546875,y:.234375},{x:.546875,y:.234375},{x:.578125,y:.234375},{x:.578125,y:.234375},{x:.609375,y:.234375},{x:.609375,y:.234375},{x:.640625,y:.234375},{x:.640625,y:.234375},{x:.671875,y:.234375},{x:.671875,y:.234375},{x:.703125,y:.234375},{x:.703125,y:.234375},{x:.734375,y:.234375},{x:.734375,y:.234375},{x:.765625,y:.234375},{x:.765625,y:.234375},{x:.796875,y:.234375},{x:.796875,y:.234375},{x:.828125,y:.234375},{x:.828125,y:.234375},{x:.859375,y:.234375},{x:.859375,y:.234375},{x:.890625,y:.234375},{x:.890625,y:.234375},{x:.921875,y:.234375},{x:.921875,y:.234375},{x:.953125,y:.234375},{x:.953125,y:.234375},{x:.984375,y:.234375},{x:.984375,y:.234375},{x:.015625,y:.265625},{x:.015625,y:.265625},{x:.046875,y:.265625},{x:.046875,y:.265625},{x:.078125,y:.265625},{x:.078125,y:.265625},{x:.109375,y:.265625},{x:.109375,y:.265625},{x:.140625,y:.265625},{x:.140625,y:.265625},{x:.171875,y:.265625},{x:.171875,y:.265625},{x:.203125,y:.265625},{x:.203125,y:.265625},{x:.234375,y:.265625},{x:.234375,y:.265625},{x:.265625,y:.265625},{x:.265625,y:.265625},{x:.296875,y:.265625},{x:.296875,y:.265625},{x:.328125,y:.265625},{x:.328125,y:.265625},{x:.359375,y:.265625},{x:.359375,y:.265625},{x:.390625,y:.265625},{x:.390625,y:.265625},{x:.421875,y:.265625},{x:.421875,y:.265625},{x:.453125,y:.265625},{x:.453125,y:.265625},{x:.484375,y:.265625},{x:.484375,y:.265625},{x:.515625,y:.265625},{x:.515625,y:.265625},{x:.546875,y:.265625},{x:.546875,y:.265625},{x:.578125,y:.265625},{x:.578125,y:.265625},{x:.609375,y:.265625},{x:.609375,y:.265625},{x:.640625,y:.265625},{x:.640625,y:.265625},{x:.671875,y:.265625},{x:.671875,y:.265625},{x:.703125,y:.265625},{x:.703125,y:.265625},{x:.734375,y:.265625},{x:.734375,y:.265625},{x:.765625,y:.265625},{x:.765625,y:.265625},{x:.796875,y:.265625},{x:.796875,y:.265625},{x:.828125,y:.265625},{x:.828125,y:.265625},{x:.859375,y:.265625},{x:.859375,y:.265625},{x:.890625,y:.265625},{x:.890625,y:.265625},{x:.921875,y:.265625},{x:.921875,y:.265625},{x:.953125,y:.265625},{x:.953125,y:.265625},{x:.984375,y:.265625},{x:.984375,y:.265625},{x:.015625,y:.296875},{x:.015625,y:.296875},{x:.046875,y:.296875},{x:.046875,y:.296875},{x:.078125,y:.296875},{x:.078125,y:.296875},{x:.109375,y:.296875},{x:.109375,y:.296875},{x:.140625,y:.296875},{x:.140625,y:.296875},{x:.171875,y:.296875},{x:.171875,y:.296875},{x:.203125,y:.296875},{x:.203125,y:.296875},{x:.234375,y:.296875},{x:.234375,y:.296875},{x:.265625,y:.296875},{x:.265625,y:.296875},{x:.296875,y:.296875},{x:.296875,y:.296875},{x:.328125,y:.296875},{x:.328125,y:.296875},{x:.359375,y:.296875},{x:.359375,y:.296875},{x:.390625,y:.296875},{x:.390625,y:.296875},{x:.421875,y:.296875},{x:.421875,y:.296875},{x:.453125,y:.296875},{x:.453125,y:.296875},{x:.484375,y:.296875},{x:.484375,y:.296875},{x:.515625,y:.296875},{x:.515625,y:.296875},{x:.546875,y:.296875},{x:.546875,y:.296875},{x:.578125,y:.296875},{x:.578125,y:.296875},{x:.609375,y:.296875},{x:.609375,y:.296875},{x:.640625,y:.296875},{x:.640625,y:.296875},{x:.671875,y:.296875},{x:.671875,y:.296875},{x:.703125,y:.296875},{x:.703125,y:.296875},{x:.734375,y:.296875},{x:.734375,y:.296875},{x:.765625,y:.296875},{x:.765625,y:.296875},{x:.796875,y:.296875},{x:.796875,y:.296875},{x:.828125,y:.296875},{x:.828125,y:.296875},{x:.859375,y:.296875},{x:.859375,y:.296875},{x:.890625,y:.296875},{x:.890625,y:.296875},{x:.921875,y:.296875},{x:.921875,y:.296875},{x:.953125,y:.296875},{x:.953125,y:.296875},{x:.984375,y:.296875},{x:.984375,y:.296875},{x:.015625,y:.328125},{x:.015625,y:.328125},{x:.046875,y:.328125},{x:.046875,y:.328125},{x:.078125,y:.328125},{x:.078125,y:.328125},{x:.109375,y:.328125},{x:.109375,y:.328125},{x:.140625,y:.328125},{x:.140625,y:.328125},{x:.171875,y:.328125},{x:.171875,y:.328125},{x:.203125,y:.328125},{x:.203125,y:.328125},{x:.234375,y:.328125},{x:.234375,y:.328125},{x:.265625,y:.328125},{x:.265625,y:.328125},{x:.296875,y:.328125},{x:.296875,y:.328125},{x:.328125,y:.328125},{x:.328125,y:.328125},{x:.359375,y:.328125},{x:.359375,y:.328125},{x:.390625,y:.328125},{x:.390625,y:.328125},{x:.421875,y:.328125},{x:.421875,y:.328125},{x:.453125,y:.328125},{x:.453125,y:.328125},{x:.484375,y:.328125},{x:.484375,y:.328125},{x:.515625,y:.328125},{x:.515625,y:.328125},{x:.546875,y:.328125},{x:.546875,y:.328125},{x:.578125,y:.328125},{x:.578125,y:.328125},{x:.609375,y:.328125},{x:.609375,y:.328125},{x:.640625,y:.328125},{x:.640625,y:.328125},{x:.671875,y:.328125},{x:.671875,y:.328125},{x:.703125,y:.328125},{x:.703125,y:.328125},{x:.734375,y:.328125},{x:.734375,y:.328125},{x:.765625,y:.328125},{x:.765625,y:.328125},{x:.796875,y:.328125},{x:.796875,y:.328125},{x:.828125,y:.328125},{x:.828125,y:.328125},{x:.859375,y:.328125},{x:.859375,y:.328125},{x:.890625,y:.328125},{x:.890625,y:.328125},{x:.921875,y:.328125},{x:.921875,y:.328125},{x:.953125,y:.328125},{x:.953125,y:.328125},{x:.984375,y:.328125},{x:.984375,y:.328125},{x:.015625,y:.359375},{x:.015625,y:.359375},{x:.046875,y:.359375},{x:.046875,y:.359375},{x:.078125,y:.359375},{x:.078125,y:.359375},{x:.109375,y:.359375},{x:.109375,y:.359375},{x:.140625,y:.359375},{x:.140625,y:.359375},{x:.171875,y:.359375},{x:.171875,y:.359375},{x:.203125,y:.359375},{x:.203125,y:.359375},{x:.234375,y:.359375},{x:.234375,y:.359375},{x:.265625,y:.359375},{x:.265625,y:.359375},{x:.296875,y:.359375},{x:.296875,y:.359375},{x:.328125,y:.359375},{x:.328125,y:.359375},{x:.359375,y:.359375},{x:.359375,y:.359375},{x:.390625,y:.359375},{x:.390625,y:.359375},{x:.421875,y:.359375},{x:.421875,y:.359375},{x:.453125,y:.359375},{x:.453125,y:.359375},{x:.484375,y:.359375},{x:.484375,y:.359375},{x:.515625,y:.359375},{x:.515625,y:.359375},{x:.546875,y:.359375},{x:.546875,y:.359375},{x:.578125,y:.359375},{x:.578125,y:.359375},{x:.609375,y:.359375},{x:.609375,y:.359375},{x:.640625,y:.359375},{x:.640625,y:.359375},{x:.671875,y:.359375},{x:.671875,y:.359375},{x:.703125,y:.359375},{x:.703125,y:.359375},{x:.734375,y:.359375},{x:.734375,y:.359375},{x:.765625,y:.359375},{x:.765625,y:.359375},{x:.796875,y:.359375},{x:.796875,y:.359375},{x:.828125,y:.359375},{x:.828125,y:.359375},{x:.859375,y:.359375},{x:.859375,y:.359375},{x:.890625,y:.359375},{x:.890625,y:.359375},{x:.921875,y:.359375},{x:.921875,y:.359375},{x:.953125,y:.359375},{x:.953125,y:.359375},{x:.984375,y:.359375},{x:.984375,y:.359375},{x:.015625,y:.390625},{x:.015625,y:.390625},{x:.046875,y:.390625},{x:.046875,y:.390625},{x:.078125,y:.390625},{x:.078125,y:.390625},{x:.109375,y:.390625},{x:.109375,y:.390625},{x:.140625,y:.390625},{x:.140625,y:.390625},{x:.171875,y:.390625},{x:.171875,y:.390625},{x:.203125,y:.390625},{x:.203125,y:.390625},{x:.234375,y:.390625},{x:.234375,y:.390625},{x:.265625,y:.390625},{x:.265625,y:.390625},{x:.296875,y:.390625},{x:.296875,y:.390625},{x:.328125,y:.390625},{x:.328125,y:.390625},{x:.359375,y:.390625},{x:.359375,y:.390625},{x:.390625,y:.390625},{x:.390625,y:.390625},{x:.421875,y:.390625},{x:.421875,y:.390625},{x:.453125,y:.390625},{x:.453125,y:.390625},{x:.484375,y:.390625},{x:.484375,y:.390625},{x:.515625,y:.390625},{x:.515625,y:.390625},{x:.546875,y:.390625},{x:.546875,y:.390625},{x:.578125,y:.390625},{x:.578125,y:.390625},{x:.609375,y:.390625},{x:.609375,y:.390625},{x:.640625,y:.390625},{x:.640625,y:.390625},{x:.671875,y:.390625},{x:.671875,y:.390625},{x:.703125,y:.390625},{x:.703125,y:.390625},{x:.734375,y:.390625},{x:.734375,y:.390625},{x:.765625,y:.390625},{x:.765625,y:.390625},{x:.796875,y:.390625},{x:.796875,y:.390625},{x:.828125,y:.390625},{x:.828125,y:.390625},{x:.859375,y:.390625},{x:.859375,y:.390625},{x:.890625,y:.390625},{x:.890625,y:.390625},{x:.921875,y:.390625},{x:.921875,y:.390625},{x:.953125,y:.390625},{x:.953125,y:.390625},{x:.984375,y:.390625},{x:.984375,y:.390625},{x:.015625,y:.421875},{x:.015625,y:.421875},{x:.046875,y:.421875},{x:.046875,y:.421875},{x:.078125,y:.421875},{x:.078125,y:.421875},{x:.109375,y:.421875},{x:.109375,y:.421875},{x:.140625,y:.421875},{x:.140625,y:.421875},{x:.171875,y:.421875},{x:.171875,y:.421875},{x:.203125,y:.421875},{x:.203125,y:.421875},{x:.234375,y:.421875},{x:.234375,y:.421875},{x:.265625,y:.421875},{x:.265625,y:.421875},{x:.296875,y:.421875},{x:.296875,y:.421875},{x:.328125,y:.421875},{x:.328125,y:.421875},{x:.359375,y:.421875},{x:.359375,y:.421875},{x:.390625,y:.421875},{x:.390625,y:.421875},{x:.421875,y:.421875},{x:.421875,y:.421875},{x:.453125,y:.421875},{x:.453125,y:.421875},{x:.484375,y:.421875},{x:.484375,y:.421875},{x:.515625,y:.421875},{x:.515625,y:.421875},{x:.546875,y:.421875},{x:.546875,y:.421875},{x:.578125,y:.421875},{x:.578125,y:.421875},{x:.609375,y:.421875},{x:.609375,y:.421875},{x:.640625,y:.421875},{x:.640625,y:.421875},{x:.671875,y:.421875},{x:.671875,y:.421875},{x:.703125,y:.421875},{x:.703125,y:.421875},{x:.734375,y:.421875},{x:.734375,y:.421875},{x:.765625,y:.421875},{x:.765625,y:.421875},{x:.796875,y:.421875},{x:.796875,y:.421875},{x:.828125,y:.421875},{x:.828125,y:.421875},{x:.859375,y:.421875},{x:.859375,y:.421875},{x:.890625,y:.421875},{x:.890625,y:.421875},{x:.921875,y:.421875},{x:.921875,y:.421875},{x:.953125,y:.421875},{x:.953125,y:.421875},{x:.984375,y:.421875},{x:.984375,y:.421875},{x:.015625,y:.453125},{x:.015625,y:.453125},{x:.046875,y:.453125},{x:.046875,y:.453125},{x:.078125,y:.453125},{x:.078125,y:.453125},{x:.109375,y:.453125},{x:.109375,y:.453125},{x:.140625,y:.453125},{x:.140625,y:.453125},{x:.171875,y:.453125},{x:.171875,y:.453125},{x:.203125,y:.453125},{x:.203125,y:.453125},{x:.234375,y:.453125},{x:.234375,y:.453125},{x:.265625,y:.453125},{x:.265625,y:.453125},{x:.296875,y:.453125},{x:.296875,y:.453125},{x:.328125,y:.453125},{x:.328125,y:.453125},{x:.359375,y:.453125},{x:.359375,y:.453125},{x:.390625,y:.453125},{x:.390625,y:.453125},{x:.421875,y:.453125},{x:.421875,y:.453125},{x:.453125,y:.453125},{x:.453125,y:.453125},{x:.484375,y:.453125},{x:.484375,y:.453125},{x:.515625,y:.453125},{x:.515625,y:.453125},{x:.546875,y:.453125},{x:.546875,y:.453125},{x:.578125,y:.453125},{x:.578125,y:.453125},{x:.609375,y:.453125},{x:.609375,y:.453125},{x:.640625,y:.453125},{x:.640625,y:.453125},{x:.671875,y:.453125},{x:.671875,y:.453125},{x:.703125,y:.453125},{x:.703125,y:.453125},{x:.734375,y:.453125},{x:.734375,y:.453125},{x:.765625,y:.453125},{x:.765625,y:.453125},{x:.796875,y:.453125},{x:.796875,y:.453125},{x:.828125,y:.453125},{x:.828125,y:.453125},{x:.859375,y:.453125},{x:.859375,y:.453125},{x:.890625,y:.453125},{x:.890625,y:.453125},{x:.921875,y:.453125},{x:.921875,y:.453125},{x:.953125,y:.453125},{x:.953125,y:.453125},{x:.984375,y:.453125},{x:.984375,y:.453125},{x:.015625,y:.484375},{x:.015625,y:.484375},{x:.046875,y:.484375},{x:.046875,y:.484375},{x:.078125,y:.484375},{x:.078125,y:.484375},{x:.109375,y:.484375},{x:.109375,y:.484375},{x:.140625,y:.484375},{x:.140625,y:.484375},{x:.171875,y:.484375},{x:.171875,y:.484375},{x:.203125,y:.484375},{x:.203125,y:.484375},{x:.234375,y:.484375},{x:.234375,y:.484375},{x:.265625,y:.484375},{x:.265625,y:.484375},{x:.296875,y:.484375},{x:.296875,y:.484375},{x:.328125,y:.484375},{x:.328125,y:.484375},{x:.359375,y:.484375},{x:.359375,y:.484375},{x:.390625,y:.484375},{x:.390625,y:.484375},{x:.421875,y:.484375},{x:.421875,y:.484375},{x:.453125,y:.484375},{x:.453125,y:.484375},{x:.484375,y:.484375},{x:.484375,y:.484375},{x:.515625,y:.484375},{x:.515625,y:.484375},{x:.546875,y:.484375},{x:.546875,y:.484375},{x:.578125,y:.484375},{x:.578125,y:.484375},{x:.609375,y:.484375},{x:.609375,y:.484375},{x:.640625,y:.484375},{x:.640625,y:.484375},{x:.671875,y:.484375},{x:.671875,y:.484375},{x:.703125,y:.484375},{x:.703125,y:.484375},{x:.734375,y:.484375},{x:.734375,y:.484375},{x:.765625,y:.484375},{x:.765625,y:.484375},{x:.796875,y:.484375},{x:.796875,y:.484375},{x:.828125,y:.484375},{x:.828125,y:.484375},{x:.859375,y:.484375},{x:.859375,y:.484375},{x:.890625,y:.484375},{x:.890625,y:.484375},{x:.921875,y:.484375},{x:.921875,y:.484375},{x:.953125,y:.484375},{x:.953125,y:.484375},{x:.984375,y:.484375},{x:.984375,y:.484375},{x:.015625,y:.515625},{x:.015625,y:.515625},{x:.046875,y:.515625},{x:.046875,y:.515625},{x:.078125,y:.515625},{x:.078125,y:.515625},{x:.109375,y:.515625},{x:.109375,y:.515625},{x:.140625,y:.515625},{x:.140625,y:.515625},{x:.171875,y:.515625},{x:.171875,y:.515625},{x:.203125,y:.515625},{x:.203125,y:.515625},{x:.234375,y:.515625},{x:.234375,y:.515625},{x:.265625,y:.515625},{x:.265625,y:.515625},{x:.296875,y:.515625},{x:.296875,y:.515625},{x:.328125,y:.515625},{x:.328125,y:.515625},{x:.359375,y:.515625},{x:.359375,y:.515625},{x:.390625,y:.515625},{x:.390625,y:.515625},{x:.421875,y:.515625},{x:.421875,y:.515625},{x:.453125,y:.515625},{x:.453125,y:.515625},{x:.484375,y:.515625},{x:.484375,y:.515625},{x:.515625,y:.515625},{x:.515625,y:.515625},{x:.546875,y:.515625},{x:.546875,y:.515625},{x:.578125,y:.515625},{x:.578125,y:.515625},{x:.609375,y:.515625},{x:.609375,y:.515625},{x:.640625,y:.515625},{x:.640625,y:.515625},{x:.671875,y:.515625},{x:.671875,y:.515625},{x:.703125,y:.515625},{x:.703125,y:.515625},{x:.734375,y:.515625},{x:.734375,y:.515625},{x:.765625,y:.515625},{x:.765625,y:.515625},{x:.796875,y:.515625},{x:.796875,y:.515625},{x:.828125,y:.515625},{x:.828125,y:.515625},{x:.859375,y:.515625},{x:.859375,y:.515625},{x:.890625,y:.515625},{x:.890625,y:.515625},{x:.921875,y:.515625},{x:.921875,y:.515625},{x:.953125,y:.515625},{x:.953125,y:.515625},{x:.984375,y:.515625},{x:.984375,y:.515625},{x:.015625,y:.546875},{x:.015625,y:.546875},{x:.046875,y:.546875},{x:.046875,y:.546875},{x:.078125,y:.546875},{x:.078125,y:.546875},{x:.109375,y:.546875},{x:.109375,y:.546875},{x:.140625,y:.546875},{x:.140625,y:.546875},{x:.171875,y:.546875},{x:.171875,y:.546875},{x:.203125,y:.546875},{x:.203125,y:.546875},{x:.234375,y:.546875},{x:.234375,y:.546875},{x:.265625,y:.546875},{x:.265625,y:.546875},{x:.296875,y:.546875},{x:.296875,y:.546875},{x:.328125,y:.546875},{x:.328125,y:.546875},{x:.359375,y:.546875},{x:.359375,y:.546875},{x:.390625,y:.546875},{x:.390625,y:.546875},{x:.421875,y:.546875},{x:.421875,y:.546875},{x:.453125,y:.546875},{x:.453125,y:.546875},{x:.484375,y:.546875},{x:.484375,y:.546875},{x:.515625,y:.546875},{x:.515625,y:.546875},{x:.546875,y:.546875},{x:.546875,y:.546875},{x:.578125,y:.546875},{x:.578125,y:.546875},{x:.609375,y:.546875},{x:.609375,y:.546875},{x:.640625,y:.546875},{x:.640625,y:.546875},{x:.671875,y:.546875},{x:.671875,y:.546875},{x:.703125,y:.546875},{x:.703125,y:.546875},{x:.734375,y:.546875},{x:.734375,y:.546875},{x:.765625,y:.546875},{x:.765625,y:.546875},{x:.796875,y:.546875},{x:.796875,y:.546875},{x:.828125,y:.546875},{x:.828125,y:.546875},{x:.859375,y:.546875},{x:.859375,y:.546875},{x:.890625,y:.546875},{x:.890625,y:.546875},{x:.921875,y:.546875},{x:.921875,y:.546875},{x:.953125,y:.546875},{x:.953125,y:.546875},{x:.984375,y:.546875},{x:.984375,y:.546875},{x:.015625,y:.578125},{x:.015625,y:.578125},{x:.046875,y:.578125},{x:.046875,y:.578125},{x:.078125,y:.578125},{x:.078125,y:.578125},{x:.109375,y:.578125},{x:.109375,y:.578125},{x:.140625,y:.578125},{x:.140625,y:.578125},{x:.171875,y:.578125},{x:.171875,y:.578125},{x:.203125,y:.578125},{x:.203125,y:.578125},{x:.234375,y:.578125},{x:.234375,y:.578125},{x:.265625,y:.578125},{x:.265625,y:.578125},{x:.296875,y:.578125},{x:.296875,y:.578125},{x:.328125,y:.578125},{x:.328125,y:.578125},{x:.359375,y:.578125},{x:.359375,y:.578125},{x:.390625,y:.578125},{x:.390625,y:.578125},{x:.421875,y:.578125},{x:.421875,y:.578125},{x:.453125,y:.578125},{x:.453125,y:.578125},{x:.484375,y:.578125},{x:.484375,y:.578125},{x:.515625,y:.578125},{x:.515625,y:.578125},{x:.546875,y:.578125},{x:.546875,y:.578125},{x:.578125,y:.578125},{x:.578125,y:.578125},{x:.609375,y:.578125},{x:.609375,y:.578125},{x:.640625,y:.578125},{x:.640625,y:.578125},{x:.671875,y:.578125},{x:.671875,y:.578125},{x:.703125,y:.578125},{x:.703125,y:.578125},{x:.734375,y:.578125},{x:.734375,y:.578125},{x:.765625,y:.578125},{x:.765625,y:.578125},{x:.796875,y:.578125},{x:.796875,y:.578125},{x:.828125,y:.578125},{x:.828125,y:.578125},{x:.859375,y:.578125},{x:.859375,y:.578125},{x:.890625,y:.578125},{x:.890625,y:.578125},{x:.921875,y:.578125},{x:.921875,y:.578125},{x:.953125,y:.578125},{x:.953125,y:.578125},{x:.984375,y:.578125},{x:.984375,y:.578125},{x:.015625,y:.609375},{x:.015625,y:.609375},{x:.046875,y:.609375},{x:.046875,y:.609375},{x:.078125,y:.609375},{x:.078125,y:.609375},{x:.109375,y:.609375},{x:.109375,y:.609375},{x:.140625,y:.609375},{x:.140625,y:.609375},{x:.171875,y:.609375},{x:.171875,y:.609375},{x:.203125,y:.609375},{x:.203125,y:.609375},{x:.234375,y:.609375},{x:.234375,y:.609375},{x:.265625,y:.609375},{x:.265625,y:.609375},{x:.296875,y:.609375},{x:.296875,y:.609375},{x:.328125,y:.609375},{x:.328125,y:.609375},{x:.359375,y:.609375},{x:.359375,y:.609375},{x:.390625,y:.609375},{x:.390625,y:.609375},{x:.421875,y:.609375},{x:.421875,y:.609375},{x:.453125,y:.609375},{x:.453125,y:.609375},{x:.484375,y:.609375},{x:.484375,y:.609375},{x:.515625,y:.609375},{x:.515625,y:.609375},{x:.546875,y:.609375},{x:.546875,y:.609375},{x:.578125,y:.609375},{x:.578125,y:.609375},{x:.609375,y:.609375},{x:.609375,y:.609375},{x:.640625,y:.609375},{x:.640625,y:.609375},{x:.671875,y:.609375},{x:.671875,y:.609375},{x:.703125,y:.609375},{x:.703125,y:.609375},{x:.734375,y:.609375},{x:.734375,y:.609375},{x:.765625,y:.609375},{x:.765625,y:.609375},{x:.796875,y:.609375},{x:.796875,y:.609375},{x:.828125,y:.609375},{x:.828125,y:.609375},{x:.859375,y:.609375},{x:.859375,y:.609375},{x:.890625,y:.609375},{x:.890625,y:.609375},{x:.921875,y:.609375},{x:.921875,y:.609375},{x:.953125,y:.609375},{x:.953125,y:.609375},{x:.984375,y:.609375},{x:.984375,y:.609375},{x:.015625,y:.640625},{x:.015625,y:.640625},{x:.046875,y:.640625},{x:.046875,y:.640625},{x:.078125,y:.640625},{x:.078125,y:.640625},{x:.109375,y:.640625},{x:.109375,y:.640625},{x:.140625,y:.640625},{x:.140625,y:.640625},{x:.171875,y:.640625},{x:.171875,y:.640625},{x:.203125,y:.640625},{x:.203125,y:.640625},{x:.234375,y:.640625},{x:.234375,y:.640625},{x:.265625,y:.640625},{x:.265625,y:.640625},{x:.296875,y:.640625},{x:.296875,y:.640625},{x:.328125,y:.640625},{x:.328125,y:.640625},{x:.359375,y:.640625},{x:.359375,y:.640625},{x:.390625,y:.640625},{x:.390625,y:.640625},{x:.421875,y:.640625},{x:.421875,y:.640625},{x:.453125,y:.640625},{x:.453125,y:.640625},{x:.484375,y:.640625},{x:.484375,y:.640625},{x:.515625,y:.640625},{x:.515625,y:.640625},{x:.546875,y:.640625},{x:.546875,y:.640625},{x:.578125,y:.640625},{x:.578125,y:.640625},{x:.609375,y:.640625},{x:.609375,y:.640625},{x:.640625,y:.640625},{x:.640625,y:.640625},{x:.671875,y:.640625},{x:.671875,y:.640625},{x:.703125,y:.640625},{x:.703125,y:.640625},{x:.734375,y:.640625},{x:.734375,y:.640625},{x:.765625,y:.640625},{x:.765625,y:.640625},{x:.796875,y:.640625},{x:.796875,y:.640625},{x:.828125,y:.640625},{x:.828125,y:.640625},{x:.859375,y:.640625},{x:.859375,y:.640625},{x:.890625,y:.640625},{x:.890625,y:.640625},{x:.921875,y:.640625},{x:.921875,y:.640625},{x:.953125,y:.640625},{x:.953125,y:.640625},{x:.984375,y:.640625},{x:.984375,y:.640625},{x:.015625,y:.671875},{x:.015625,y:.671875},{x:.046875,y:.671875},{x:.046875,y:.671875},{x:.078125,y:.671875},{x:.078125,y:.671875},{x:.109375,y:.671875},{x:.109375,y:.671875},{x:.140625,y:.671875},{x:.140625,y:.671875},{x:.171875,y:.671875},{x:.171875,y:.671875},{x:.203125,y:.671875},{x:.203125,y:.671875},{x:.234375,y:.671875},{x:.234375,y:.671875},{x:.265625,y:.671875},{x:.265625,y:.671875},{x:.296875,y:.671875},{x:.296875,y:.671875},{x:.328125,y:.671875},{x:.328125,y:.671875},{x:.359375,y:.671875},{x:.359375,y:.671875},{x:.390625,y:.671875},{x:.390625,y:.671875},{x:.421875,y:.671875},{x:.421875,y:.671875},{x:.453125,y:.671875},{x:.453125,y:.671875},{x:.484375,y:.671875},{x:.484375,y:.671875},{x:.515625,y:.671875},{x:.515625,y:.671875},{x:.546875,y:.671875},{x:.546875,y:.671875},{x:.578125,y:.671875},{x:.578125,y:.671875},{x:.609375,y:.671875},{x:.609375,y:.671875},{x:.640625,y:.671875},{x:.640625,y:.671875},{x:.671875,y:.671875},{x:.671875,y:.671875},{x:.703125,y:.671875},{x:.703125,y:.671875},{x:.734375,y:.671875},{x:.734375,y:.671875},{x:.765625,y:.671875},{x:.765625,y:.671875},{x:.796875,y:.671875},{x:.796875,y:.671875},{x:.828125,y:.671875},{x:.828125,y:.671875},{x:.859375,y:.671875},{x:.859375,y:.671875},{x:.890625,y:.671875},{x:.890625,y:.671875},{x:.921875,y:.671875},{x:.921875,y:.671875},{x:.953125,y:.671875},{x:.953125,y:.671875},{x:.984375,y:.671875},{x:.984375,y:.671875},{x:.015625,y:.703125},{x:.015625,y:.703125},{x:.046875,y:.703125},{x:.046875,y:.703125},{x:.078125,y:.703125},{x:.078125,y:.703125},{x:.109375,y:.703125},{x:.109375,y:.703125},{x:.140625,y:.703125},{x:.140625,y:.703125},{x:.171875,y:.703125},{x:.171875,y:.703125},{x:.203125,y:.703125},{x:.203125,y:.703125},{x:.234375,y:.703125},{x:.234375,y:.703125},{x:.265625,y:.703125},{x:.265625,y:.703125},{x:.296875,y:.703125},{x:.296875,y:.703125},{x:.328125,y:.703125},{x:.328125,y:.703125},{x:.359375,y:.703125},{x:.359375,y:.703125},{x:.390625,y:.703125},{x:.390625,y:.703125},{x:.421875,y:.703125},{x:.421875,y:.703125},{x:.453125,y:.703125},{x:.453125,y:.703125},{x:.484375,y:.703125},{x:.484375,y:.703125},{x:.515625,y:.703125},{x:.515625,y:.703125},{x:.546875,y:.703125},{x:.546875,y:.703125},{x:.578125,y:.703125},{x:.578125,y:.703125},{x:.609375,y:.703125},{x:.609375,y:.703125},{x:.640625,y:.703125},{x:.640625,y:.703125},{x:.671875,y:.703125},{x:.671875,y:.703125},{x:.703125,y:.703125},{x:.703125,y:.703125},{x:.734375,y:.703125},{x:.734375,y:.703125},{x:.765625,y:.703125},{x:.765625,y:.703125},{x:.796875,y:.703125},{x:.796875,y:.703125},{x:.828125,y:.703125},{x:.828125,y:.703125},{x:.859375,y:.703125},{x:.859375,y:.703125},{x:.890625,y:.703125},{x:.890625,y:.703125},{x:.921875,y:.703125},{x:.921875,y:.703125},{x:.953125,y:.703125},{x:.953125,y:.703125},{x:.984375,y:.703125},{x:.984375,y:.703125},{x:.015625,y:.734375},{x:.015625,y:.734375},{x:.046875,y:.734375},{x:.046875,y:.734375},{x:.078125,y:.734375},{x:.078125,y:.734375},{x:.109375,y:.734375},{x:.109375,y:.734375},{x:.140625,y:.734375},{x:.140625,y:.734375},{x:.171875,y:.734375},{x:.171875,y:.734375},{x:.203125,y:.734375},{x:.203125,y:.734375},{x:.234375,y:.734375},{x:.234375,y:.734375},{x:.265625,y:.734375},{x:.265625,y:.734375},{x:.296875,y:.734375},{x:.296875,y:.734375},{x:.328125,y:.734375},{x:.328125,y:.734375},{x:.359375,y:.734375},{x:.359375,y:.734375},{x:.390625,y:.734375},{x:.390625,y:.734375},{x:.421875,y:.734375},{x:.421875,y:.734375},{x:.453125,y:.734375},{x:.453125,y:.734375},{x:.484375,y:.734375},{x:.484375,y:.734375},{x:.515625,y:.734375},{x:.515625,y:.734375},{x:.546875,y:.734375},{x:.546875,y:.734375},{x:.578125,y:.734375},{x:.578125,y:.734375},{x:.609375,y:.734375},{x:.609375,y:.734375},{x:.640625,y:.734375},{x:.640625,y:.734375},{x:.671875,y:.734375},{x:.671875,y:.734375},{x:.703125,y:.734375},{x:.703125,y:.734375},{x:.734375,y:.734375},{x:.734375,y:.734375},{x:.765625,y:.734375},{x:.765625,y:.734375},{x:.796875,y:.734375},{x:.796875,y:.734375},{x:.828125,y:.734375},{x:.828125,y:.734375},{x:.859375,y:.734375},{x:.859375,y:.734375},{x:.890625,y:.734375},{x:.890625,y:.734375},{x:.921875,y:.734375},{x:.921875,y:.734375},{x:.953125,y:.734375},{x:.953125,y:.734375},{x:.984375,y:.734375},{x:.984375,y:.734375},{x:.015625,y:.765625},{x:.015625,y:.765625},{x:.046875,y:.765625},{x:.046875,y:.765625},{x:.078125,y:.765625},{x:.078125,y:.765625},{x:.109375,y:.765625},{x:.109375,y:.765625},{x:.140625,y:.765625},{x:.140625,y:.765625},{x:.171875,y:.765625},{x:.171875,y:.765625},{x:.203125,y:.765625},{x:.203125,y:.765625},{x:.234375,y:.765625},{x:.234375,y:.765625},{x:.265625,y:.765625},{x:.265625,y:.765625},{x:.296875,y:.765625},{x:.296875,y:.765625},{x:.328125,y:.765625},{x:.328125,y:.765625},{x:.359375,y:.765625},{x:.359375,y:.765625},{x:.390625,y:.765625},{x:.390625,y:.765625},{x:.421875,y:.765625},{x:.421875,y:.765625},{x:.453125,y:.765625},{x:.453125,y:.765625},{x:.484375,y:.765625},{x:.484375,y:.765625},{x:.515625,y:.765625},{x:.515625,y:.765625},{x:.546875,y:.765625},{x:.546875,y:.765625},{x:.578125,y:.765625},{x:.578125,y:.765625},{x:.609375,y:.765625},{x:.609375,y:.765625},{x:.640625,y:.765625},{x:.640625,y:.765625},{x:.671875,y:.765625},{x:.671875,y:.765625},{x:.703125,y:.765625},{x:.703125,y:.765625},{x:.734375,y:.765625},{x:.734375,y:.765625},{x:.765625,y:.765625},{x:.765625,y:.765625},{x:.796875,y:.765625},{x:.796875,y:.765625},{x:.828125,y:.765625},{x:.828125,y:.765625},{x:.859375,y:.765625},{x:.859375,y:.765625},{x:.890625,y:.765625},{x:.890625,y:.765625},{x:.921875,y:.765625},{x:.921875,y:.765625},{x:.953125,y:.765625},{x:.953125,y:.765625},{x:.984375,y:.765625},{x:.984375,y:.765625},{x:.015625,y:.796875},{x:.015625,y:.796875},{x:.046875,y:.796875},{x:.046875,y:.796875},{x:.078125,y:.796875},{x:.078125,y:.796875},{x:.109375,y:.796875},{x:.109375,y:.796875},{x:.140625,y:.796875},{x:.140625,y:.796875},{x:.171875,y:.796875},{x:.171875,y:.796875},{x:.203125,y:.796875},{x:.203125,y:.796875},{x:.234375,y:.796875},{x:.234375,y:.796875},{x:.265625,y:.796875},{x:.265625,y:.796875},{x:.296875,y:.796875},{x:.296875,y:.796875},{x:.328125,y:.796875},{x:.328125,y:.796875},{x:.359375,y:.796875},{x:.359375,y:.796875},{x:.390625,y:.796875},{x:.390625,y:.796875},{x:.421875,y:.796875},{x:.421875,y:.796875},{x:.453125,y:.796875},{x:.453125,y:.796875},{x:.484375,y:.796875},{x:.484375,y:.796875},{x:.515625,y:.796875},{x:.515625,y:.796875},{x:.546875,y:.796875},{x:.546875,y:.796875},{x:.578125,y:.796875},{x:.578125,y:.796875},{x:.609375,y:.796875},{x:.609375,y:.796875},{x:.640625,y:.796875},{x:.640625,y:.796875},{x:.671875,y:.796875},{x:.671875,y:.796875},{x:.703125,y:.796875},{x:.703125,y:.796875},{x:.734375,y:.796875},{x:.734375,y:.796875},{x:.765625,y:.796875},{x:.765625,y:.796875},{x:.796875,y:.796875},{x:.796875,y:.796875},{x:.828125,y:.796875},{x:.828125,y:.796875},{x:.859375,y:.796875},{x:.859375,y:.796875},{x:.890625,y:.796875},{x:.890625,y:.796875},{x:.921875,y:.796875},{x:.921875,y:.796875},{x:.953125,y:.796875},{x:.953125,y:.796875},{x:.984375,y:.796875},{x:.984375,y:.796875},{x:.015625,y:.828125},{x:.015625,y:.828125},{x:.046875,y:.828125},{x:.046875,y:.828125},{x:.078125,y:.828125},{x:.078125,y:.828125},{x:.109375,y:.828125},{x:.109375,y:.828125},{x:.140625,y:.828125},{x:.140625,y:.828125},{x:.171875,y:.828125},{x:.171875,y:.828125},{x:.203125,y:.828125},{x:.203125,y:.828125},{x:.234375,y:.828125},{x:.234375,y:.828125},{x:.265625,y:.828125},{x:.265625,y:.828125},{x:.296875,y:.828125},{x:.296875,y:.828125},{x:.328125,y:.828125},{x:.328125,y:.828125},{x:.359375,y:.828125},{x:.359375,y:.828125},{x:.390625,y:.828125},{x:.390625,y:.828125},{x:.421875,y:.828125},{x:.421875,y:.828125},{x:.453125,y:.828125},{x:.453125,y:.828125},{x:.484375,y:.828125},{x:.484375,y:.828125},{x:.515625,y:.828125},{x:.515625,y:.828125},{x:.546875,y:.828125},{x:.546875,y:.828125},{x:.578125,y:.828125},{x:.578125,y:.828125},{x:.609375,y:.828125},{x:.609375,y:.828125},{x:.640625,y:.828125},{x:.640625,y:.828125},{x:.671875,y:.828125},{x:.671875,y:.828125},{x:.703125,y:.828125},{x:.703125,y:.828125},{x:.734375,y:.828125},{x:.734375,y:.828125},{x:.765625,y:.828125},{x:.765625,y:.828125},{x:.796875,y:.828125},{x:.796875,y:.828125},{x:.828125,y:.828125},{x:.828125,y:.828125},{x:.859375,y:.828125},{x:.859375,y:.828125},{x:.890625,y:.828125},{x:.890625,y:.828125},{x:.921875,y:.828125},{x:.921875,y:.828125},{x:.953125,y:.828125},{x:.953125,y:.828125},{x:.984375,y:.828125},{x:.984375,y:.828125},{x:.015625,y:.859375},{x:.015625,y:.859375},{x:.046875,y:.859375},{x:.046875,y:.859375},{x:.078125,y:.859375},{x:.078125,y:.859375},{x:.109375,y:.859375},{x:.109375,y:.859375},{x:.140625,y:.859375},{x:.140625,y:.859375},{x:.171875,y:.859375},{x:.171875,y:.859375},{x:.203125,y:.859375},{x:.203125,y:.859375},{x:.234375,y:.859375},{x:.234375,y:.859375},{x:.265625,y:.859375},{x:.265625,y:.859375},{x:.296875,y:.859375},{x:.296875,y:.859375},{x:.328125,y:.859375},{x:.328125,y:.859375},{x:.359375,y:.859375},{x:.359375,y:.859375},{x:.390625,y:.859375},{x:.390625,y:.859375},{x:.421875,y:.859375},{x:.421875,y:.859375},{x:.453125,y:.859375},{x:.453125,y:.859375},{x:.484375,y:.859375},{x:.484375,y:.859375},{x:.515625,y:.859375},{x:.515625,y:.859375},{x:.546875,y:.859375},{x:.546875,y:.859375},{x:.578125,y:.859375},{x:.578125,y:.859375},{x:.609375,y:.859375},{x:.609375,y:.859375},{x:.640625,y:.859375},{x:.640625,y:.859375},{x:.671875,y:.859375},{x:.671875,y:.859375},{x:.703125,y:.859375},{x:.703125,y:.859375},{x:.734375,y:.859375},{x:.734375,y:.859375},{x:.765625,y:.859375},{x:.765625,y:.859375},{x:.796875,y:.859375},{x:.796875,y:.859375},{x:.828125,y:.859375},{x:.828125,y:.859375},{x:.859375,y:.859375},{x:.859375,y:.859375},{x:.890625,y:.859375},{x:.890625,y:.859375},{x:.921875,y:.859375},{x:.921875,y:.859375},{x:.953125,y:.859375},{x:.953125,y:.859375},{x:.984375,y:.859375},{x:.984375,y:.859375},{x:.015625,y:.890625},{x:.015625,y:.890625},{x:.046875,y:.890625},{x:.046875,y:.890625},{x:.078125,y:.890625},{x:.078125,y:.890625},{x:.109375,y:.890625},{x:.109375,y:.890625},{x:.140625,y:.890625},{x:.140625,y:.890625},{x:.171875,y:.890625},{x:.171875,y:.890625},{x:.203125,y:.890625},{x:.203125,y:.890625},{x:.234375,y:.890625},{x:.234375,y:.890625},{x:.265625,y:.890625},{x:.265625,y:.890625},{x:.296875,y:.890625},{x:.296875,y:.890625},{x:.328125,y:.890625},{x:.328125,y:.890625},{x:.359375,y:.890625},{x:.359375,y:.890625},{x:.390625,y:.890625},{x:.390625,y:.890625},{x:.421875,y:.890625},{x:.421875,y:.890625},{x:.453125,y:.890625},{x:.453125,y:.890625},{x:.484375,y:.890625},{x:.484375,y:.890625},{x:.515625,y:.890625},{x:.515625,y:.890625},{x:.546875,y:.890625},{x:.546875,y:.890625},{x:.578125,y:.890625},{x:.578125,y:.890625},{x:.609375,y:.890625},{x:.609375,y:.890625},{x:.640625,y:.890625},{x:.640625,y:.890625},{x:.671875,y:.890625},{x:.671875,y:.890625},{x:.703125,y:.890625},{x:.703125,y:.890625},{x:.734375,y:.890625},{x:.734375,y:.890625},{x:.765625,y:.890625},{x:.765625,y:.890625},{x:.796875,y:.890625},{x:.796875,y:.890625},{x:.828125,y:.890625},{x:.828125,y:.890625},{x:.859375,y:.890625},{x:.859375,y:.890625},{x:.890625,y:.890625},{x:.890625,y:.890625},{x:.921875,y:.890625},{x:.921875,y:.890625},{x:.953125,y:.890625},{x:.953125,y:.890625},{x:.984375,y:.890625},{x:.984375,y:.890625},{x:.015625,y:.921875},{x:.015625,y:.921875},{x:.046875,y:.921875},{x:.046875,y:.921875},{x:.078125,y:.921875},{x:.078125,y:.921875},{x:.109375,y:.921875},{x:.109375,y:.921875},{x:.140625,y:.921875},{x:.140625,y:.921875},{x:.171875,y:.921875},{x:.171875,y:.921875},{x:.203125,y:.921875},{x:.203125,y:.921875},{x:.234375,y:.921875},{x:.234375,y:.921875},{x:.265625,y:.921875},{x:.265625,y:.921875},{x:.296875,y:.921875},{x:.296875,y:.921875},{x:.328125,y:.921875},{x:.328125,y:.921875},{x:.359375,y:.921875},{x:.359375,y:.921875},{x:.390625,y:.921875},{x:.390625,y:.921875},{x:.421875,y:.921875},{x:.421875,y:.921875},{x:.453125,y:.921875},{x:.453125,y:.921875},{x:.484375,y:.921875},{x:.484375,y:.921875},{x:.515625,y:.921875},{x:.515625,y:.921875},{x:.546875,y:.921875},{x:.546875,y:.921875},{x:.578125,y:.921875},{x:.578125,y:.921875},{x:.609375,y:.921875},{x:.609375,y:.921875},{x:.640625,y:.921875},{x:.640625,y:.921875},{x:.671875,y:.921875},{x:.671875,y:.921875},{x:.703125,y:.921875},{x:.703125,y:.921875},{x:.734375,y:.921875},{x:.734375,y:.921875},{x:.765625,y:.921875},{x:.765625,y:.921875},{x:.796875,y:.921875},{x:.796875,y:.921875},{x:.828125,y:.921875},{x:.828125,y:.921875},{x:.859375,y:.921875},{x:.859375,y:.921875},{x:.890625,y:.921875},{x:.890625,y:.921875},{x:.921875,y:.921875},{x:.921875,y:.921875},{x:.953125,y:.921875},{x:.953125,y:.921875},{x:.984375,y:.921875},{x:.984375,y:.921875},{x:.015625,y:.953125},{x:.015625,y:.953125},{x:.046875,y:.953125},{x:.046875,y:.953125},{x:.078125,y:.953125},{x:.078125,y:.953125},{x:.109375,y:.953125},{x:.109375,y:.953125},{x:.140625,y:.953125},{x:.140625,y:.953125},{x:.171875,y:.953125},{x:.171875,y:.953125},{x:.203125,y:.953125},{x:.203125,y:.953125},{x:.234375,y:.953125},{x:.234375,y:.953125},{x:.265625,y:.953125},{x:.265625,y:.953125},{x:.296875,y:.953125},{x:.296875,y:.953125},{x:.328125,y:.953125},{x:.328125,y:.953125},{x:.359375,y:.953125},{x:.359375,y:.953125},{x:.390625,y:.953125},{x:.390625,y:.953125},{x:.421875,y:.953125},{x:.421875,y:.953125},{x:.453125,y:.953125},{x:.453125,y:.953125},{x:.484375,y:.953125},{x:.484375,y:.953125},{x:.515625,y:.953125},{x:.515625,y:.953125},{x:.546875,y:.953125},{x:.546875,y:.953125},{x:.578125,y:.953125},{x:.578125,y:.953125},{x:.609375,y:.953125},{x:.609375,y:.953125},{x:.640625,y:.953125},{x:.640625,y:.953125},{x:.671875,y:.953125},{x:.671875,y:.953125},{x:.703125,y:.953125},{x:.703125,y:.953125},{x:.734375,y:.953125},{x:.734375,y:.953125},{x:.765625,y:.953125},{x:.765625,y:.953125},{x:.796875,y:.953125},{x:.796875,y:.953125},{x:.828125,y:.953125},{x:.828125,y:.953125},{x:.859375,y:.953125},{x:.859375,y:.953125},{x:.890625,y:.953125},{x:.890625,y:.953125},{x:.921875,y:.953125},{x:.921875,y:.953125},{x:.953125,y:.953125},{x:.953125,y:.953125},{x:.984375,y:.953125},{x:.984375,y:.953125},{x:.015625,y:.984375},{x:.015625,y:.984375},{x:.046875,y:.984375},{x:.046875,y:.984375},{x:.078125,y:.984375},{x:.078125,y:.984375},{x:.109375,y:.984375},{x:.109375,y:.984375},{x:.140625,y:.984375},{x:.140625,y:.984375},{x:.171875,y:.984375},{x:.171875,y:.984375},{x:.203125,y:.984375},{x:.203125,y:.984375},{x:.234375,y:.984375},{x:.234375,y:.984375},{x:.265625,y:.984375},{x:.265625,y:.984375},{x:.296875,y:.984375},{x:.296875,y:.984375},{x:.328125,y:.984375},{x:.328125,y:.984375},{x:.359375,y:.984375},{x:.359375,y:.984375},{x:.390625,y:.984375},{x:.390625,y:.984375},{x:.421875,y:.984375},{x:.421875,y:.984375},{x:.453125,y:.984375},{x:.453125,y:.984375},{x:.484375,y:.984375},{x:.484375,y:.984375},{x:.515625,y:.984375},{x:.515625,y:.984375},{x:.546875,y:.984375},{x:.546875,y:.984375},{x:.578125,y:.984375},{x:.578125,y:.984375},{x:.609375,y:.984375},{x:.609375,y:.984375},{x:.640625,y:.984375},{x:.640625,y:.984375},{x:.671875,y:.984375},{x:.671875,y:.984375},{x:.703125,y:.984375},{x:.703125,y:.984375},{x:.734375,y:.984375},{x:.734375,y:.984375},{x:.765625,y:.984375},{x:.765625,y:.984375},{x:.796875,y:.984375},{x:.796875,y:.984375},{x:.828125,y:.984375},{x:.828125,y:.984375},{x:.859375,y:.984375},{x:.859375,y:.984375},{x:.890625,y:.984375},{x:.890625,y:.984375},{x:.921875,y:.984375},{x:.921875,y:.984375},{x:.953125,y:.984375},{x:.953125,y:.984375},{x:.984375,y:.984375},{x:.984375,y:.984375},{x:.03125,y:.03125},{x:.03125,y:.03125},{x:.09375,y:.03125},{x:.09375,y:.03125},{x:.15625,y:.03125},{x:.15625,y:.03125},{x:.21875,y:.03125},{x:.21875,y:.03125},{x:.28125,y:.03125},{x:.28125,y:.03125},{x:.34375,y:.03125},{x:.34375,y:.03125},{x:.40625,y:.03125},{x:.40625,y:.03125},{x:.46875,y:.03125},{x:.46875,y:.03125},{x:.53125,y:.03125},{x:.53125,y:.03125},{x:.59375,y:.03125},{x:.59375,y:.03125},{x:.65625,y:.03125},{x:.65625,y:.03125},{x:.71875,y:.03125},{x:.71875,y:.03125},{x:.78125,y:.03125},{x:.78125,y:.03125},{x:.84375,y:.03125},{x:.84375,y:.03125},{x:.90625,y:.03125},{x:.90625,y:.03125},{x:.96875,y:.03125},{x:.96875,y:.03125},{x:.03125,y:.09375},{x:.03125,y:.09375},{x:.09375,y:.09375},{x:.09375,y:.09375},{x:.15625,y:.09375},{x:.15625,y:.09375},{x:.21875,y:.09375},{x:.21875,y:.09375},{x:.28125,y:.09375},{x:.28125,y:.09375},{x:.34375,y:.09375},{x:.34375,y:.09375},{x:.40625,y:.09375},{x:.40625,y:.09375},{x:.46875,y:.09375},{x:.46875,y:.09375},{x:.53125,y:.09375},{x:.53125,y:.09375},{x:.59375,y:.09375},{x:.59375,y:.09375},{x:.65625,y:.09375},{x:.65625,y:.09375},{x:.71875,y:.09375},{x:.71875,y:.09375},{x:.78125,y:.09375},{x:.78125,y:.09375},{x:.84375,y:.09375},{x:.84375,y:.09375},{x:.90625,y:.09375},{x:.90625,y:.09375},{x:.96875,y:.09375},{x:.96875,y:.09375},{x:.03125,y:.15625},{x:.03125,y:.15625},{x:.09375,y:.15625},{x:.09375,y:.15625},{x:.15625,y:.15625},{x:.15625,y:.15625},{x:.21875,y:.15625},{x:.21875,y:.15625},{x:.28125,y:.15625},{x:.28125,y:.15625},{x:.34375,y:.15625},{x:.34375,y:.15625},{x:.40625,y:.15625},{x:.40625,y:.15625},{x:.46875,y:.15625},{x:.46875,y:.15625},{x:.53125,y:.15625},{x:.53125,y:.15625},{x:.59375,y:.15625},{x:.59375,y:.15625},{x:.65625,y:.15625},{x:.65625,y:.15625},{x:.71875,y:.15625},{x:.71875,y:.15625},{x:.78125,y:.15625},{x:.78125,y:.15625},{x:.84375,y:.15625},{x:.84375,y:.15625},{x:.90625,y:.15625},{x:.90625,y:.15625},{x:.96875,y:.15625},{x:.96875,y:.15625},{x:.03125,y:.21875},{x:.03125,y:.21875},{x:.09375,y:.21875},{x:.09375,y:.21875},{x:.15625,y:.21875},{x:.15625,y:.21875},{x:.21875,y:.21875},{x:.21875,y:.21875},{x:.28125,y:.21875},{x:.28125,y:.21875},{x:.34375,y:.21875},{x:.34375,y:.21875},{x:.40625,y:.21875},{x:.40625,y:.21875},{x:.46875,y:.21875},{x:.46875,y:.21875},{x:.53125,y:.21875},{x:.53125,y:.21875},{x:.59375,y:.21875},{x:.59375,y:.21875},{x:.65625,y:.21875},{x:.65625,y:.21875},{x:.71875,y:.21875},{x:.71875,y:.21875},{x:.78125,y:.21875},{x:.78125,y:.21875},{x:.84375,y:.21875},{x:.84375,y:.21875},{x:.90625,y:.21875},{x:.90625,y:.21875},{x:.96875,y:.21875},{x:.96875,y:.21875},{x:.03125,y:.28125},{x:.03125,y:.28125},{x:.09375,y:.28125},{x:.09375,y:.28125},{x:.15625,y:.28125},{x:.15625,y:.28125},{x:.21875,y:.28125},{x:.21875,y:.28125},{x:.28125,y:.28125},{x:.28125,y:.28125},{x:.34375,y:.28125},{x:.34375,y:.28125},{x:.40625,y:.28125},{x:.40625,y:.28125},{x:.46875,y:.28125},{x:.46875,y:.28125},{x:.53125,y:.28125},{x:.53125,y:.28125},{x:.59375,y:.28125},{x:.59375,y:.28125},{x:.65625,y:.28125},{x:.65625,y:.28125},{x:.71875,y:.28125},{x:.71875,y:.28125},{x:.78125,y:.28125},{x:.78125,y:.28125},{x:.84375,y:.28125},{x:.84375,y:.28125},{x:.90625,y:.28125},{x:.90625,y:.28125},{x:.96875,y:.28125},{x:.96875,y:.28125},{x:.03125,y:.34375},{x:.03125,y:.34375},{x:.09375,y:.34375},{x:.09375,y:.34375},{x:.15625,y:.34375},{x:.15625,y:.34375},{x:.21875,y:.34375},{x:.21875,y:.34375},{x:.28125,y:.34375},{x:.28125,y:.34375},{x:.34375,y:.34375},{x:.34375,y:.34375},{x:.40625,y:.34375},{x:.40625,y:.34375},{x:.46875,y:.34375},{x:.46875,y:.34375},{x:.53125,y:.34375},{x:.53125,y:.34375},{x:.59375,y:.34375},{x:.59375,y:.34375},{x:.65625,y:.34375},{x:.65625,y:.34375},{x:.71875,y:.34375},{x:.71875,y:.34375},{x:.78125,y:.34375},{x:.78125,y:.34375},{x:.84375,y:.34375},{x:.84375,y:.34375},{x:.90625,y:.34375},{x:.90625,y:.34375},{x:.96875,y:.34375},{x:.96875,y:.34375},{x:.03125,y:.40625},{x:.03125,y:.40625},{x:.09375,y:.40625},{x:.09375,y:.40625},{x:.15625,y:.40625},{x:.15625,y:.40625},{x:.21875,y:.40625},{x:.21875,y:.40625},{x:.28125,y:.40625},{x:.28125,y:.40625},{x:.34375,y:.40625},{x:.34375,y:.40625},{x:.40625,y:.40625},{x:.40625,y:.40625},{x:.46875,y:.40625},{x:.46875,y:.40625},{x:.53125,y:.40625},{x:.53125,y:.40625},{x:.59375,y:.40625},{x:.59375,y:.40625},{x:.65625,y:.40625},{x:.65625,y:.40625},{x:.71875,y:.40625},{x:.71875,y:.40625},{x:.78125,y:.40625},{x:.78125,y:.40625},{x:.84375,y:.40625},{x:.84375,y:.40625},{x:.90625,y:.40625},{x:.90625,y:.40625},{x:.96875,y:.40625},{x:.96875,y:.40625},{x:.03125,y:.46875},{x:.03125,y:.46875},{x:.09375,y:.46875},{x:.09375,y:.46875},{x:.15625,y:.46875},{x:.15625,y:.46875},{x:.21875,y:.46875},{x:.21875,y:.46875},{x:.28125,y:.46875},{x:.28125,y:.46875},{x:.34375,y:.46875},{x:.34375,y:.46875},{x:.40625,y:.46875},{x:.40625,y:.46875},{x:.46875,y:.46875},{x:.46875,y:.46875},{x:.53125,y:.46875},{x:.53125,y:.46875},{x:.59375,y:.46875},{x:.59375,y:.46875},{x:.65625,y:.46875},{x:.65625,y:.46875},{x:.71875,y:.46875},{x:.71875,y:.46875},{x:.78125,y:.46875},{x:.78125,y:.46875},{x:.84375,y:.46875},{x:.84375,y:.46875},{x:.90625,y:.46875},{x:.90625,y:.46875},{x:.96875,y:.46875},{x:.96875,y:.46875},{x:.03125,y:.53125},{x:.03125,y:.53125},{x:.09375,y:.53125},{x:.09375,y:.53125},{x:.15625,y:.53125},{x:.15625,y:.53125},{x:.21875,y:.53125},{x:.21875,y:.53125},{x:.28125,y:.53125},{x:.28125,y:.53125},{x:.34375,y:.53125},{x:.34375,y:.53125},{x:.40625,y:.53125},{x:.40625,y:.53125},{x:.46875,y:.53125},{x:.46875,y:.53125},{x:.53125,y:.53125},{x:.53125,y:.53125},{x:.59375,y:.53125},{x:.59375,y:.53125},{x:.65625,y:.53125},{x:.65625,y:.53125},{x:.71875,y:.53125},{x:.71875,y:.53125},{x:.78125,y:.53125},{x:.78125,y:.53125},{x:.84375,y:.53125},{x:.84375,y:.53125},{x:.90625,y:.53125},{x:.90625,y:.53125},{x:.96875,y:.53125},{x:.96875,y:.53125},{x:.03125,y:.59375},{x:.03125,y:.59375},{x:.09375,y:.59375},{x:.09375,y:.59375},{x:.15625,y:.59375},{x:.15625,y:.59375},{x:.21875,y:.59375},{x:.21875,y:.59375},{x:.28125,y:.59375},{x:.28125,y:.59375},{x:.34375,y:.59375},{x:.34375,y:.59375},{x:.40625,y:.59375},{x:.40625,y:.59375},{x:.46875,y:.59375},{x:.46875,y:.59375},{x:.53125,y:.59375},{x:.53125,y:.59375},{x:.59375,y:.59375},{x:.59375,y:.59375},{x:.65625,y:.59375},{x:.65625,y:.59375},{x:.71875,y:.59375},{x:.71875,y:.59375},{x:.78125,y:.59375},{x:.78125,y:.59375},{x:.84375,y:.59375},{x:.84375,y:.59375},{x:.90625,y:.59375},{x:.90625,y:.59375},{x:.96875,y:.59375},{x:.96875,y:.59375},{x:.03125,y:.65625},{x:.03125,y:.65625},{x:.09375,y:.65625},{x:.09375,y:.65625},{x:.15625,y:.65625},{x:.15625,y:.65625},{x:.21875,y:.65625},{x:.21875,y:.65625},{x:.28125,y:.65625},{x:.28125,y:.65625},{x:.34375,y:.65625},{x:.34375,y:.65625},{x:.40625,y:.65625},{x:.40625,y:.65625},{x:.46875,y:.65625},{x:.46875,y:.65625},{x:.53125,y:.65625},{x:.53125,y:.65625},{x:.59375,y:.65625},{x:.59375,y:.65625},{x:.65625,y:.65625},{x:.65625,y:.65625},{x:.71875,y:.65625},{x:.71875,y:.65625},{x:.78125,y:.65625},{x:.78125,y:.65625},{x:.84375,y:.65625},{x:.84375,y:.65625},{x:.90625,y:.65625},{x:.90625,y:.65625},{x:.96875,y:.65625},{x:.96875,y:.65625},{x:.03125,y:.71875},{x:.03125,y:.71875},{x:.09375,y:.71875},{x:.09375,y:.71875},{x:.15625,y:.71875},{x:.15625,y:.71875},{x:.21875,y:.71875},{x:.21875,y:.71875},{x:.28125,y:.71875},{x:.28125,y:.71875},{x:.34375,y:.71875},{x:.34375,y:.71875},{x:.40625,y:.71875},{x:.40625,y:.71875},{x:.46875,y:.71875},{x:.46875,y:.71875},{x:.53125,y:.71875},{x:.53125,y:.71875},{x:.59375,y:.71875},{x:.59375,y:.71875},{x:.65625,y:.71875},{x:.65625,y:.71875},{x:.71875,y:.71875},{x:.71875,y:.71875},{x:.78125,y:.71875},{x:.78125,y:.71875},{x:.84375,y:.71875},{x:.84375,y:.71875},{x:.90625,y:.71875},{x:.90625,y:.71875},{x:.96875,y:.71875},{x:.96875,y:.71875},{x:.03125,y:.78125},{x:.03125,y:.78125},{x:.09375,y:.78125},{x:.09375,y:.78125},{x:.15625,y:.78125},{x:.15625,y:.78125},{x:.21875,y:.78125},{x:.21875,y:.78125},{x:.28125,y:.78125},{x:.28125,y:.78125},{x:.34375,y:.78125},{x:.34375,y:.78125},{x:.40625,y:.78125},{x:.40625,y:.78125},{x:.46875,y:.78125},{x:.46875,y:.78125},{x:.53125,y:.78125},{x:.53125,y:.78125},{x:.59375,y:.78125},{x:.59375,y:.78125},{x:.65625,y:.78125},{x:.65625,y:.78125},{x:.71875,y:.78125},{x:.71875,y:.78125},{x:.78125,y:.78125},{x:.78125,y:.78125},{x:.84375,y:.78125},{x:.84375,y:.78125},{x:.90625,y:.78125},{x:.90625,y:.78125},{x:.96875,y:.78125},{x:.96875,y:.78125},{x:.03125,y:.84375},{x:.03125,y:.84375},{x:.09375,y:.84375},{x:.09375,y:.84375},{x:.15625,y:.84375},{x:.15625,y:.84375},{x:.21875,y:.84375},{x:.21875,y:.84375},{x:.28125,y:.84375},{x:.28125,y:.84375},{x:.34375,y:.84375},{x:.34375,y:.84375},{x:.40625,y:.84375},{x:.40625,y:.84375},{x:.46875,y:.84375},{x:.46875,y:.84375},{x:.53125,y:.84375},{x:.53125,y:.84375},{x:.59375,y:.84375},{x:.59375,y:.84375},{x:.65625,y:.84375},{x:.65625,y:.84375},{x:.71875,y:.84375},{x:.71875,y:.84375},{x:.78125,y:.84375},{x:.78125,y:.84375},{x:.84375,y:.84375},{x:.84375,y:.84375},{x:.90625,y:.84375},{x:.90625,y:.84375},{x:.96875,y:.84375},{x:.96875,y:.84375},{x:.03125,y:.90625},{x:.03125,y:.90625},{x:.09375,y:.90625},{x:.09375,y:.90625},{x:.15625,y:.90625},{x:.15625,y:.90625},{x:.21875,y:.90625},{x:.21875,y:.90625},{x:.28125,y:.90625},{x:.28125,y:.90625},{x:.34375,y:.90625},{x:.34375,y:.90625},{x:.40625,y:.90625},{x:.40625,y:.90625},{x:.46875,y:.90625},{x:.46875,y:.90625},{x:.53125,y:.90625},{x:.53125,y:.90625},{x:.59375,y:.90625},{x:.59375,y:.90625},{x:.65625,y:.90625},{x:.65625,y:.90625},{x:.71875,y:.90625},{x:.71875,y:.90625},{x:.78125,y:.90625},{x:.78125,y:.90625},{x:.84375,y:.90625},{x:.84375,y:.90625},{x:.90625,y:.90625},{x:.90625,y:.90625},{x:.96875,y:.90625},{x:.96875,y:.90625},{x:.03125,y:.96875},{x:.03125,y:.96875},{x:.09375,y:.96875},{x:.09375,y:.96875},{x:.15625,y:.96875},{x:.15625,y:.96875},{x:.21875,y:.96875},{x:.21875,y:.96875},{x:.28125,y:.96875},{x:.28125,y:.96875},{x:.34375,y:.96875},{x:.34375,y:.96875},{x:.40625,y:.96875},{x:.40625,y:.96875},{x:.46875,y:.96875},{x:.46875,y:.96875},{x:.53125,y:.96875},{x:.53125,y:.96875},{x:.59375,y:.96875},{x:.59375,y:.96875},{x:.65625,y:.96875},{x:.65625,y:.96875},{x:.71875,y:.96875},{x:.71875,y:.96875},{x:.78125,y:.96875},{x:.78125,y:.96875},{x:.84375,y:.96875},{x:.84375,y:.96875},{x:.90625,y:.96875},{x:.90625,y:.96875},{x:.96875,y:.96875},{x:.96875,y:.96875},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.0625,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.1875,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.3125,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.4375,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.5625,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.6875,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.8125,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.9375,y:.0625},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.0625,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.1875,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.3125,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.4375,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.5625,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.6875,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.8125,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.9375,y:.1875},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.0625,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.1875,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.3125,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.4375,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.5625,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.6875,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.8125,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.9375,y:.3125},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.0625,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.1875,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.3125,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.4375,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.5625,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.6875,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.8125,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.9375,y:.4375},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.0625,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.1875,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.3125,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.4375,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.5625,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.6875,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.8125,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.9375,y:.5625},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.0625,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.1875,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.3125,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.4375,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.5625,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.6875,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.8125,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.9375,y:.6875},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.0625,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.1875,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.3125,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.4375,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.5625,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.6875,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.8125,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.9375,y:.8125},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.0625,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.1875,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.3125,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.4375,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.5625,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.6875,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.8125,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375},{x:.9375,y:.9375}];var a5=class{constructor(t){T(this,"model");T(this,"anchors");T(this,"anchorsTensor");T(this,"inputSize");T(this,"inputSizeTensor");T(this,"doubleInputSizeTensor");this.model=t,this.anchors=$3.map(o=>[o.x,o.y]),this.anchorsTensor=W.tensor2d(this.anchors),this.inputSize=this.model&&this.model.inputs&&this.model.inputs[0].shape?this.model.inputs[0].shape[2]:0,this.inputSizeTensor=W.tensor1d([this.inputSize,this.inputSize]),this.doubleInputSizeTensor=W.tensor1d([this.inputSize*2,this.inputSize*2])}normalizeBoxes(t){let o={};o.boxOffsets=W.slice(t,[0,0],[-1,2]),o.boxSizes=W.slice(t,[0,2],[-1,2]),o.div=W.div(o.boxOffsets,this.inputSizeTensor),o.boxCenterPoints=W.add(o.div,this.anchorsTensor),o.halfBoxSizes=W.div(o.boxSizes,this.doubleInputSizeTensor),o.sub=W.sub(o.boxCenterPoints,o.halfBoxSizes),o.startPoints=W.mul(o.sub,this.inputSizeTensor),o.add=W.add(o.boxCenterPoints,o.halfBoxSizes),o.endPoints=W.mul(o.add,this.inputSizeTensor);let n=W.concat2d([o.startPoints,o.endPoints],1);return Object.keys(o).forEach(r=>W.dispose(o[r])),n}normalizeLandmarks(t,o){let n={};n.reshape=W.reshape(t,[-1,7,2]),n.div=W.div(n.reshape,this.inputSizeTensor),n.landmarks=W.add(n.div,this.anchors[o]);let r=W.mul(n.landmarks,this.inputSizeTensor);return Object.keys(n).forEach(A=>W.dispose(n[A])),r}async predict(t,o){let n={};n.resize=W.image.resizeBilinear(t,[this.inputSize,this.inputSize]),n.div=W.div(n.resize,V.tf127),n.image=W.sub(n.div,V.tf1),n.batched=this.model.execute(n.image),n.predictions=W.squeeze(n.batched),n.slice=W.slice(n.predictions,[0,0],[-1,1]),n.sigmoid=W.sigmoid(n.slice),n.scores=W.squeeze(n.sigmoid);let r=await n.scores.data();n.boxes=W.slice(n.predictions,[0,1],[-1,4]),n.norm=this.normalizeBoxes(n.boxes),n.nms=await W.image.nonMaxSuppressionAsync(n.norm,n.scores,3*o.hand.maxDetected,o.hand.iouThreshold,o.hand.minConfidence);let A=await n.nms.array(),s=[];for(let a of A){let i={};i.box=W.slice(n.norm,[a,0],[1,-1]),i.slice=W.slice(n.predictions,[a,5],[1,14]),i.norm=this.normalizeLandmarks(i.slice,a),i.palmLandmarks=W.reshape(i.norm,[-1,2]);let x=await i.box.data(),c=x.slice(0,2),l=x.slice(2,4),y=await i.palmLandmarks.array(),f={startPoint:c,endPoint:l,palmLandmarks:y,confidence:r[a]},u=K3(f,[t.shape[2]/this.inputSize,t.shape[1]/this.inputSize]);s.push(u),Object.keys(i).forEach(m=>W.dispose(i[m]))}return Object.keys(n).forEach(a=>W.dispose(n[a])),s}};var L0=Z(D());var yA=5,eo=1.65,to=[0,5,9,13,17,1,2],xA=0,cA=2,oo=0,i5=class{constructor(t,o){T(this,"handDetector");T(this,"handPoseModel");T(this,"inputSize");T(this,"storedBoxes");T(this,"skipped");T(this,"detectedHands");this.handDetector=t,this.handPoseModel=o,this.inputSize=this.handPoseModel&&this.handPoseModel.inputs[0].shape?this.handPoseModel.inputs[0].shape[2]:0,this.storedBoxes=[],this.skipped=Number.MAX_SAFE_INTEGER,this.detectedHands=0}calculateLandmarksBoundingBox(t){let o=t.map(s=>s[0]),n=t.map(s=>s[1]),r=[Math.min(...o),Math.min(...n)],A=[Math.max(...o),Math.max(...n)];return{startPoint:r,endPoint:A}}getBoxForPalmLandmarks(t,o){let n=t.map(A=>M1([...A,1],o)),r=this.calculateLandmarksBoundingBox(n);return A5(s5(r),yA)}getBoxForHandLandmarks(t){let o=this.calculateLandmarksBoundingBox(t),n=A5(s5(o),eo);n.palmLandmarks=[];for(let r=0;r<to.length;r++)n.palmLandmarks.push(t[to[r]].slice(0,2));return n}transformRawCoords(t,o,n,r){let A=r5(o),s=[A[0]/this.inputSize,A[1]/this.inputSize,(A[0]+A[1])/this.inputSize/2],a=t.map(f=>[s[0]*(f[0]-this.inputSize/2),s[1]*(f[1]-this.inputSize/2),s[2]*f[2]]),i=g1(n,[0,0]),x=a.map(f=>[...M1(f,i),f[2]]),c=Q3(r),l=[...k2(o),1],y=[Te(l,c[0]),Te(l,c[1])];return x.map(f=>[Math.trunc(f[0]+y[0]),Math.trunc(f[1]+y[1]),Math.trunc(f[2])])}async estimateHands(t,o){let n=!1,r,A=(o.hand.skipTime||0)>h()-oo,s=this.skipped<(o.hand.skipFrames||0);o.skipAllowed&&A&&s&&(r=await this.handDetector.predict(t,o),this.skipped=0),o.skipAllowed&&this.skipped++,r&&r.length>0&&(r.length!==this.detectedHands&&this.detectedHands!==o.hand.maxDetected||!o.hand.landmarks)&&(this.detectedHands=0,this.storedBoxes=[...r],this.storedBoxes.length>0&&(n=!0));let a=[];for(let i=0;i<this.storedBoxes.length;i++){let x=this.storedBoxes[i];if(!!x)if(o.hand.landmarks){let c=o.hand.rotation?J3(x.palmLandmarks[xA],x.palmLandmarks[cA]):0,l=k2(x),y=[l[0]/t.shape[2],l[1]/t.shape[1]],f=o.hand.rotation&&v.kernels.includes("rotatewithoffset")?L0.image.rotateWithOffset(t,c,0,y):t.clone(),u=g1(-c,l),m=n?this.getBoxForPalmLandmarks(x.palmLandmarks,u):x,P=Y3(m,f,[this.inputSize,this.inputSize]),g=L0.div(P,V.tf255);L0.dispose(P),L0.dispose(f);let[b,d]=this.handPoseModel.execute(g);oo=h(),L0.dispose(g);let M=(await b.data())[0];if(L0.dispose(b),M>=o.hand.minConfidence/4){let S=L0.reshape(d,[-1,3]),w=await S.array();L0.dispose(d),L0.dispose(S);let j=this.transformRawCoords(w,m,c,u),C=this.getBoxForHandLandmarks(j);this.storedBoxes[i]={...C,confidence:M};let F={landmarks:j,confidence:M,boxConfidence:x.confidence,fingerConfidence:M,box:{topLeft:C.startPoint,bottomRight:C.endPoint}};a.push(F)}else this.storedBoxes[i]=null;L0.dispose(d)}else{let c=A5(s5(x),eo),l={confidence:x.confidence,boxConfidence:x.confidence,fingerConfidence:0,box:{topLeft:c.startPoint,bottomRight:c.endPoint},landmarks:[]};a.push(l)}}return this.storedBoxes=this.storedBoxes.filter(i=>i!==null),this.detectedHands=a.length,a.length>o.hand.maxDetected&&(a.length=o.hand.maxDetected),a}};var k0={thumb:0,index:1,middle:2,ring:3,pinky:4,all:[0,1,2,3,4],nameMapping:{0:"thumb",1:"index",2:"middle",3:"ring",4:"pinky"},pointsMapping:{0:[[0,1],[1,2],[2,3],[3,4]],1:[[0,5],[5,6],[6,7],[7,8]],2:[[0,9],[9,10],[10,11],[11,12]],3:[[0,13],[13,14],[14,15],[15,16]],4:[[0,17],[17,18],[18,19],[19,20]]},getName:e=>k0.nameMapping[e],getPoints:e=>k0.pointsMapping[e]},ke={none:0,half:1,full:2,nameMapping:{0:"none",1:"half",2:"full"},getName:e=>ke.nameMapping[e]},o0={verticalUp:0,verticalDown:1,horizontalLeft:2,horizontalRight:3,diagonalUpRight:4,diagonalUpLeft:5,diagonalDownRight:6,diagonalDownLeft:7,nameMapping:{0:"verticalUp",1:"verticalDown",2:"horizontalLeft",3:"horizontalRight",4:"diagonalUpRight",5:"diagonalUpLeft",6:"diagonalDownRight",7:"diagonalDownLeft"},getName:e=>o0.nameMapping[e]},we=class{constructor(t){T(this,"name");T(this,"curls");T(this,"directions");T(this,"weights");T(this,"weightsRelative");this.name=t,this.curls={},this.directions={},this.weights=[1,1,1,1,1],this.weightsRelative=[1,1,1,1,1]}curl(t,o,n){typeof this.curls[t]=="undefined"&&(this.curls[t]=[]),this.curls[t].push([o,n])}direction(t,o,n){this.directions[t]||(this.directions[t]=[]),this.directions[t].push([o,n])}weight(t,o){this.weights[t]=o;let n=this.weights.reduce((r,A)=>r+A,0);this.weightsRelative=this.weights.map(r=>r*5/n)}matchAgainst(t,o){let n=0;for(let r in t){let A=t[r],s=this.curls[r];if(typeof s=="undefined"){n+=this.weightsRelative[r];continue}for(let[a,i]of s)if(A===a){n+=i*this.weightsRelative[r];break}}for(let r in o){let A=o[r],s=this.directions[r];if(typeof s=="undefined"){n+=this.weightsRelative[r];continue}for(let[a,i]of s)if(A===a){n+=i*this.weightsRelative[r];break}}return n/10}};var{thumb:J0,index:ce,middle:de,ring:He,pinky:Ve}=k0,{none:Q0,half:fA,full:_0}=ke,{verticalUp:o2,verticalDown:z4,horizontalLeft:P1,horizontalRight:mA,diagonalUpRight:pA,diagonalUpLeft:n2,diagonalDownRight:S4,diagonalDownLeft:C4}=o0,Ee=new we("thumbs up");Ee.curl(J0,Q0,1);Ee.direction(J0,o2,1);Ee.direction(J0,n2,.25);Ee.direction(J0,pA,.25);for(let e of[k0.index,k0.middle,k0.ring,k0.pinky])Ee.curl(e,_0,1),Ee.direction(e,P1,1),Ee.direction(e,mA,1);var y0=new we("victory");y0.curl(J0,fA,.5);y0.curl(J0,Q0,.5);y0.direction(J0,o2,1);y0.direction(J0,n2,1);y0.curl(ce,Q0,1);y0.direction(ce,o2,.75);y0.direction(ce,n2,1);y0.curl(de,Q0,1);y0.direction(de,o2,1);y0.direction(de,n2,.75);y0.curl(He,_0,1);y0.direction(He,o2,.2);y0.direction(He,n2,1);y0.direction(He,P1,.2);y0.curl(Ve,_0,1);y0.direction(Ve,o2,.2);y0.direction(Ve,n2,1);y0.direction(Ve,P1,.2);y0.weight(ce,2);y0.weight(de,2);var ze=new we("point");ze.curl(J0,_0,1);ze.curl(ce,Q0,.5);ze.curl(de,_0,.5);ze.curl(He,_0,.5);ze.curl(Ve,_0,.5);ze.weight(ce,2);ze.weight(de,2);var Se=new we("middle finger");Se.curl(J0,Q0,1);Se.curl(ce,_0,.5);Se.curl(de,_0,.5);Se.curl(He,_0,.5);Se.curl(Ve,_0,.5);Se.weight(ce,2);Se.weight(de,2);var r2=new we("open palm");r2.curl(J0,Q0,.75);r2.curl(ce,Q0,.75);r2.curl(de,Q0,.75);r2.curl(He,Q0,.75);r2.curl(Ve,Q0,.75);var no=[Ee,y0,ze,Se,r2];var uA=.7,De={HALF_CURL_START_LIMIT:60,NO_CURL_START_LIMIT:130,DISTANCE_VOTE_POWER:1.1,SINGLE_ANGLE_VOTE_POWER:.9,TOTAL_ANGLE_VOTE_POWER:1.6};function ro(e,t,o,n){let r=(t-n)/(e-o),A=Math.atan(r)*180/Math.PI;return A<=0?A=-A:A>0&&(A=180-A),A}function so(e,t){if(!e||!t)return[0,0];let o=ro(e[0],e[1],t[0],t[1]);if(e.length===2)return o;let n=ro(e[1],e[2],t[1],t[2]);return[o,n]}function Ao(e,t=1){let o=0,n=0,r=0;return e>=75&&e<=105?o=1*t:e>=25&&e<=155?n=1*t:r=1*t,[o,n,r]}function hA(e,t,o){let n=e[0]-t[0],r=e[0]-o[0],A=t[0]-o[0],s=e[1]-t[1],a=e[1]-o[1],i=t[1]-o[1],x=e[2]-t[2],c=e[2]-o[2],l=t[2]-o[2],y=Math.sqrt(n*n+s*s+x*x),f=Math.sqrt(r*r+a*a+c*c),u=Math.sqrt(A*A+i*i+l*l),m=(u*u+y*y-f*f)/(2*u*y);m>1?m=1:m<-1&&(m=-1);let P=Math.acos(m);P=57.2958*P%180;let g;return P>De.NO_CURL_START_LIMIT?g=ke.none:P>De.HALF_CURL_START_LIMIT?g=ke.half:g=ke.full,g}function ao(e,t,o,n){let r;return n===Math.abs(e)?e>0?r=o0.horizontalLeft:r=o0.horizontalRight:n===Math.abs(t)?t>0?r=o0.horizontalLeft:r=o0.horizontalRight:o>0?r=o0.horizontalLeft:r=o0.horizontalRight,r}function io(e,t,o,n){let r;return n===Math.abs(e)?e<0?r=o0.verticalDown:r=o0.verticalUp:n===Math.abs(t)?t<0?r=o0.verticalDown:r=o0.verticalUp:o<0?r=o0.verticalDown:r=o0.verticalUp,r}function bA(e,t,o,n,r,A,s,a){let i,x=io(e,t,o,n),c=ao(r,A,s,a);return x===o0.verticalUp?c===o0.horizontalLeft?i=o0.diagonalUpLeft:i=o0.diagonalUpRight:c===o0.horizontalLeft?i=o0.diagonalDownLeft:i=o0.diagonalDownRight,i}function gA(e,t,o,n){let r=e[0]-t[0],A=e[0]-o[0],s=t[0]-o[0],a=e[1]-t[1],i=e[1]-o[1],x=t[1]-o[1],c=Math.max(Math.abs(r),Math.abs(A),Math.abs(s)),l=Math.max(Math.abs(a),Math.abs(i),Math.abs(x)),y=0,f=0,u=0,m=l/(c+1e-5);m>1.5?y+=De.DISTANCE_VOTE_POWER:m>.66?f+=De.DISTANCE_VOTE_POWER:u+=De.DISTANCE_VOTE_POWER;let P=Math.sqrt(r*r+a*a),g=Math.sqrt(A*A+i*i),b=Math.sqrt(s*s+x*x),d=Math.max(P,g,b),M=e[0],S=e[1],w=o[0],j=o[1];d===P?(w=o[0],j=o[1]):d===b&&(M=t[0],S=t[1]);let H=so([M,S],[w,j]),Y=Ao(H,De.TOTAL_ANGLE_VOTE_POWER);y+=Y[0],f+=Y[1],u+=Y[2];for(let x0 of n){let E=Ao(x0,De.SINGLE_ANGLE_VOTE_POWER);y+=E[0],f+=E[1],u+=E[2]}let J;return y===Math.max(y,f,u)?J=io(i,a,x,l):u===Math.max(f,u)?J=ao(A,r,s,c):J=bA(i,a,x,l,A,r,s,c),J}function lo(e){let t=[],o=[],n=[],r=[];if(!e)return{curls:n,directions:r};for(let A of k0.all){let s=k0.getPoints(A),a=[],i=[];for(let x of s){let c=e[x[0]],l=e[x[1]],y=so(c,l),f=y[0],u=y[1];a.push(f),i.push(u)}t.push(a),o.push(i)}for(let A of k0.all){let s=A===k0.thumb?1:0,a=k0.getPoints(A),i=e[a[s][0]],x=e[a[s+1][1]],c=e[a[3][1]],l=hA(i,x,c),y=gA(i,x,c,t[A].slice(s));n[A]=l,r[A]=y}return{curls:n,directions:r}}function l5(e){if(!e||e.length===0)return null;let t=lo(e),o={};for(let n of k0.all)o[k0.getName(n)]={curl:ke.getName(t.curls[n]),direction:o0.getName(t.directions[n])};return o}function yo(e){let t=[];if(!e||e.length===0)return t;let o=lo(e);for(let n of no){let r=n.matchAgainst(o.curls,o.directions);r>=uA&&t.push({name:n.name,confidence:r})}return t}var xo={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],palm:[0]},A2,s2,co;async function v1(e,t){let o=await co.estimateHands(e,t);if(!o)return[];let n=[];for(let r=0;r<o.length;r++){let A={};if(o[r].landmarks)for(let c of Object.keys(xo))A[c]=xo[c].map(l=>o[r].landmarks[l]);let s=o[r].landmarks,a=[Number.MAX_SAFE_INTEGER,Number.MAX_SAFE_INTEGER,0,0],i=[0,0,0,0];if(s&&s.length>0){for(let c of s)c[0]<a[0]&&(a[0]=c[0]),c[1]<a[1]&&(a[1]=c[1]),c[0]>a[2]&&(a[2]=c[0]),c[1]>a[3]&&(a[3]=c[1]);a[2]-=a[0],a[3]-=a[1],i=[a[0]/(e.shape[2]||0),a[1]/(e.shape[1]||0),a[2]/(e.shape[2]||0),a[3]/(e.shape[1]||0)]}else a=o[r].box?[Math.trunc(Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.max(0,o[r].box.topLeft[1])),Math.trunc(Math.min(e.shape[2]||0,o[r].box.bottomRight[0])-Math.max(0,o[r].box.topLeft[0])),Math.trunc(Math.min(e.shape[1]||0,o[r].box.bottomRight[1])-Math.max(0,o[r].box.topLeft[1]))]:[0,0,0,0],i=[o[r].box.topLeft[0]/(e.shape[2]||0),o[r].box.topLeft[1]/(e.shape[1]||0),(o[r].box.bottomRight[0]-o[r].box.topLeft[0])/(e.shape[2]||0),(o[r].box.bottomRight[1]-o[r].box.topLeft[1])/(e.shape[1]||0)];let x=l5(s);n.push({id:r,score:Math.round(100*o[r].confidence)/100,boxScore:Math.round(100*o[r].boxConfidence)/100,fingerScore:Math.round(100*o[r].fingerConfidence)/100,label:"hand",box:a,boxRaw:i,keypoints:s,annotations:A,landmarks:x})}return n}async function T1(e){var o,n;v.initial&&(A2=null,s2=null),!A2||!s2?[A2,s2]=await Promise.all([e.hand.enabled?G((o=e.hand.detector)==null?void 0:o.modelPath):null,e.hand.landmarks?G((n=e.hand.skeleton)==null?void 0:n.modelPath):null]):(e.debug&&p("cached model:",A2.modelUrl),e.debug&&p("cached model:",s2.modelUrl));let t=new a5(A2);return co=new i5(t,s2),[A2,s2]}var Q=Z(D());var d0=[null,null],MA=["StatefulPartitionedCall/Postprocessor/Slice","StatefulPartitionedCall/Postprocessor/ExpandDims_1"],Ce=[[0,0],[0,0]],PA=["hand","fist","pinch","point","face","tip","pinchtip"],mo=4,po=1.6,RA=512,vA=1.4,y5=Number.MAX_SAFE_INTEGER,w1=0,fe=[0,0],A0={boxes:[],hands:[]},uo={thumb:[1,2,3,4],index:[5,6,7,8],middle:[9,10,11,12],ring:[13,14,15,16],pinky:[17,18,19,20],base:[0],palm:[0,17,13,9,5,1,0]};async function ho(e){var t;if(v.initial&&(d0[0]=null),d0[0])e.debug&&p("cached model:",d0[0].modelUrl);else{x5(["tensorlistreserve","enter","tensorlistfromtensor","merge","loopcond","switch","exit","tensorliststack","nextiteration","tensorlistsetitem","tensorlistgetitem","reciprocal","shape","split","where"],e),d0[0]=await G((t=e.hand.detector)==null?void 0:t.modelPath);let o=Object.values(d0[0].modelSignature.inputs);Ce[0][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ce[0][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return d0[0]}async function bo(e){var t;if(v.initial&&(d0[1]=null),d0[1])e.debug&&p("cached model:",d0[1].modelUrl);else{d0[1]=await G((t=e.hand.skeleton)==null?void 0:t.modelPath);let o=Object.values(d0[1].modelSignature.inputs);Ce[1][0]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[1].size):0,Ce[1][1]=Array.isArray(o)?parseInt(o[0].tensorShape.dim[2].size):0}return d0[1]}async function TA(e,t){let o=[];if(!e||!d0[0])return o;let n={},r=(e.shape[2]||1)/(e.shape[1]||1),A=Math.min(Math.round((e.shape[1]||0)/8)*8,RA),s=Math.round(A*r/8)*8;n.resize=Q.image.resizeBilinear(e,[A,s]),n.cast=Q.cast(n.resize,"int32"),[n.rawScores,n.rawBoxes]=await d0[0].executeAsync(n.cast,MA),n.boxes=Q.squeeze(n.rawBoxes,[0,2]),n.scores=Q.squeeze(n.rawScores,[0]);let a=Q.unstack(n.scores,1);Q.dispose(a[mo]),a.splice(mo,1),n.filtered=Q.stack(a,1),Q.dispose(a),n.max=Q.max(n.filtered,1),n.argmax=Q.argMax(n.filtered,1);let i=0;n.nms=await Q.image.nonMaxSuppressionAsync(n.boxes,n.max,(t.hand.maxDetected||0)+1,t.hand.iouThreshold||0,t.hand.minConfidence||1);let x=await n.nms.data(),c=await n.max.data(),l=await n.argmax.data();for(let y of Array.from(x)){let f=Q.slice(n.boxes,y,1),u=await f.data();Q.dispose(f);let m=[u[1],u[0],u[3]-u[1],u[2]-u[0]],P=Q2(m,vA),g=[Math.trunc(m[0]*fe[0]),Math.trunc(m[1]*fe[1]),Math.trunc(m[2]*fe[0]),Math.trunc(m[3]*fe[1])],b=c[y],d=PA[l[y]],M={id:i++,score:b,box:g,boxRaw:P,label:d};o.push(M)}return Object.keys(n).forEach(y=>Q.dispose(n[y])),o.sort((y,f)=>f.score-y.score),o.length>(t.hand.maxDetected||1)&&(o.length=t.hand.maxDetected||1),o}async function k1(e,t,o){let n={id:t.id,score:Math.round(100*t.score)/100,boxScore:Math.round(100*t.score)/100,fingerScore:0,box:t.box,boxRaw:t.boxRaw,label:t.label,keypoints:[],landmarks:{},annotations:{}};if(e&&d0[1]&&o.hand.landmarks&&t.score>(o.hand.minConfidence||0)){let r={},A=[t.boxRaw[1],t.boxRaw[0],t.boxRaw[3]+t.boxRaw[1],t.boxRaw[2]+t.boxRaw[0]];r.crop=Q.image.cropAndResize(e,[A],[0],[Ce[1][0],Ce[1][1]],"bilinear"),r.div=Q.div(r.crop,V.tf255),[r.score,r.keypoints]=d0[1].execute(r.div,["Identity_1","Identity"]);let s=(await r.score.data())[0],a=(100-Math.trunc(100/(1+Math.exp(s))))/100;if(a>=(o.hand.minConfidence||0)){n.fingerScore=a,r.reshaped=Q.reshape(r.keypoints,[-1,3]);let c=(await r.reshaped.array()).map(l=>[l[0]/Ce[1][1],l[1]/Ce[1][0],l[2]||0]).map(l=>[l[0]*t.boxRaw[2],l[1]*t.boxRaw[3],l[2]||0]);n.keypoints=c.map(l=>[fe[0]*(l[0]+t.boxRaw[0]),fe[1]*(l[1]+t.boxRaw[1]),l[2]||0]),n.landmarks=l5(n.keypoints);for(let l of Object.keys(uo))n.annotations[l]=uo[l].map(y=>n.landmarks&&n.keypoints[y]?n.keypoints[y]:null)}Object.keys(r).forEach(i=>Q.dispose(r[i]))}return n}async function E1(e,t){var r,A;if(!d0[0]||!d0[1]||!((r=d0[0])!=null&&r.inputs[0].shape)||!((A=d0[1])!=null&&A.inputs[0].shape))return[];fe=[e.shape[2]||0,e.shape[1]||0],y5++;let o=(t.hand.skipTime||0)>h()-w1,n=y5<(t.hand.skipFrames||0);return t.skipAllowed&&o&&n?A0.hands:new Promise(async s=>{let a=3*(t.hand.skipTime||0)>h()-w1,i=y5<3*(t.hand.skipFrames||0);t.skipAllowed&&A0.hands.length===t.hand.maxDetected?A0.hands=await Promise.all(A0.boxes.map(c=>k1(e,c,t))):t.skipAllowed&&a&&i&&A0.hands.length>0?A0.hands=await Promise.all(A0.boxes.map(c=>k1(e,c,t))):(A0.boxes=await TA(e,t),w1=h(),A0.hands=await Promise.all(A0.boxes.map(c=>k1(e,c,t))),y5=0);let x=[...A0.boxes];if(A0.boxes.length=0,t.cacheSensitivity>0)for(let c=0;c<A0.hands.length;c++){let l=a3(A0.hands[c].keypoints,fe);if(l.box[2]/(e.shape[2]||1)>.05&&l.box[3]/(e.shape[1]||1)>.05&&A0.hands[c].fingerScore&&A0.hands[c].fingerScore>(t.hand.minConfidence||0)){let y=Q2(l.box,po),f=Q2(l.boxRaw,po);A0.boxes.push({...x[c],box:y,boxRaw:f})}}for(let c=0;c<A0.hands.length;c++){let l=le(A0.hands[c].keypoints,fe);A0.hands[c].box=l.box,A0.hands[c].boxRaw=l.boxRaw}s(A0.hands)})}var d5=Z(D());var M0,c5=[],z1=Number.MAX_SAFE_INTEGER,Mo=0,Po=0;async function Ro(e){var t;return v.initial&&(M0=null),M0?e.debug&&p("cached model:",M0.modelUrl):M0=await G((t=e.face.liveness)==null?void 0:t.modelPath),M0}async function S1(e,t,o,n){var s,a;if(!M0)return 0;let r=(((s=t.face.liveness)==null?void 0:s.skipTime)||0)>h()-Po,A=z1<(((a=t.face.liveness)==null?void 0:a.skipFrames)||0);return t.skipAllowed&&r&&A&&Mo===n&&c5[o]?(z1++,c5[o]):(z1=0,new Promise(async i=>{let x=d5.image.resizeBilinear(e,[M0!=null&&M0.inputs[0].shape?M0.inputs[0].shape[2]:0,M0!=null&&M0.inputs[0].shape?M0.inputs[0].shape[1]:0],!1),c=M0==null?void 0:M0.execute(x),l=(await c.data())[0];c5[o]=Math.round(100*l)/100,Mo=n,Po=h(),d5.dispose([x,c]),i(c5[o])}))}var zo=Z(D());var E2={};ue(E2,{connected:()=>m5,horizontal:()=>C1,kpt:()=>f5,relative:()=>j1,vertical:()=>I1});var f5=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],C1=[["leftEye","rightEye"],["leftEar","rightEar"],["leftShoulder","rightShoulder"],["leftElbow","rightElbow"],["leftWrist","rightWrist"],["leftHip","rightHip"],["leftKnee","rightKnee"],["leftAnkle","rightAnkle"]],I1=[["leftKnee","leftShoulder"],["rightKnee","rightShoulder"],["leftAnkle","leftKnee"],["rightAnkle","rightKnee"]],j1=[[["leftHip","rightHip"],["leftShoulder","rightShoulder"]],[["leftElbow","rightElbow"],["leftShoulder","rightShoulder"]]],m5={leftLeg:["leftHip","leftKnee","leftAnkle"],rightLeg:["rightHip","rightKnee","rightAnkle"],torso:["leftShoulder","rightShoulder","rightHip","leftHip","leftShoulder"],leftArm:["leftShoulder","leftElbow","leftWrist"],rightArm:["rightShoulder","rightElbow","rightWrist"],head:[]};var Ie=Z(D()),To=.005,W0={keypoints:[],padding:[[0,0],[0,0],[0,0],[0,0]]};function O1(e){for(let t of C1){let o=e.keypoints.findIndex(r=>r.part===t[0]),n=e.keypoints.findIndex(r=>r.part===t[1]);if(e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[0]<e.keypoints[n].position[0]){let r=e.keypoints[o];e.keypoints[o]=e.keypoints[n],e.keypoints[n]=r}}for(let t of I1){let o=e.keypoints.findIndex(r=>r&&r.part===t[0]),n=e.keypoints.findIndex(r=>r&&r.part===t[1]);e.keypoints[o]&&e.keypoints[n]&&e.keypoints[o].position[1]<e.keypoints[n].position[1]&&e.keypoints.splice(o,1)}for(let[t,o]of j1){let n=e.keypoints.findIndex(x=>x&&x.part===t[0]),r=e.keypoints.findIndex(x=>x&&x.part===t[1]),A=e.keypoints.findIndex(x=>x&&x.part===o[0]),s=e.keypoints.findIndex(x=>x&&x.part===o[1]);if(!e.keypoints[A]||!e.keypoints[s])continue;let a=e.keypoints[n]?[Math.abs(e.keypoints[A].position[0]-e.keypoints[n].position[0]),Math.abs(e.keypoints[s].position[0]-e.keypoints[n].position[0])]:[0,0],i=e.keypoints[r]?[Math.abs(e.keypoints[s].position[0]-e.keypoints[r].position[0]),Math.abs(e.keypoints[A].position[0]-e.keypoints[r].position[0])]:[0,0];if(a[0]>a[1]||i[0]>i[1]){let x=e.keypoints[n];e.keypoints[n]=e.keypoints[r],e.keypoints[r]=x}}}function wo(e){for(let t=0;t<e.length;t++)if(e[t]&&W0.keypoints[t]){let o=[Math.abs(e[t].positionRaw[0]-W0.keypoints[t].positionRaw[0]),Math.abs(e[t].positionRaw[1]-W0.keypoints[t].positionRaw[1])];o[0]<To&&o[1]<To?e[t]=W0.keypoints[t]:W0.keypoints[t]=e[t]}else W0.keypoints[t]=e[t];return e}function ko(e,t){let o={};if(!e.shape||!e.shape[1]||!e.shape[2])return e;W0.padding=[[0,0],[e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0,e.shape[2]>e.shape[1]?Math.trunc((e.shape[2]-e.shape[1])/2):0],[e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0,e.shape[1]>e.shape[2]?Math.trunc((e.shape[1]-e.shape[2])/2):0],[0,0]],o.pad=Ie.pad(e,W0.padding),o.resize=Ie.image.resizeBilinear(o.pad,[t,t]);let n=Ie.cast(o.resize,"int32");return Object.keys(o).forEach(r=>Ie.dispose(o[r])),n}function Eo(e,t){e.keypoints=e.keypoints.filter(n=>n&&n.position);for(let n of e.keypoints)n.position=[n.position[0]*(t[0]+W0.padding[2][0]+W0.padding[2][1])/t[0]-W0.padding[2][0],n.position[1]*(t[1]+W0.padding[1][0]+W0.padding[1][1])/t[1]-W0.padding[1][0]],n.positionRaw=[n.position[0]/t[0],n.position[1]/t[1]];let o=le(e.keypoints.map(n=>n.position),t);return e.box=o.box,e.boxRaw=o.boxRaw,e}var F0,p5=0,N1=Number.MAX_SAFE_INTEGER,Ze={boxes:[],bodies:[],last:0};async function So(e){return v.initial&&(F0=null),F0?e.debug&&p("cached model:",F0.modelUrl):(x5(["size"],e),F0=await G(e.body.modelPath)),p5=F0.inputs[0].shape?F0.inputs[0].shape[2]:0,p5<64&&(p5=256),F0}async function kA(e,t,o){let n=e[0][0],r=[],A=0;for(let c=0;c<n.length;c++)if(A=n[c][2],A>t.body.minConfidence){let l=[n[c][1],n[c][0]];r.push({score:Math.round(100*A)/100,part:f5[c],positionRaw:l,position:[Math.round((o.shape[2]||0)*l[0]),Math.round((o.shape[1]||0)*l[1])]})}A=r.reduce((c,l)=>l.score>c?l.score:c,0);let s=[],a=le(r.map(c=>c.position),[o.shape[2],o.shape[1]]),i={};for(let[c,l]of Object.entries(m5)){let y=[];for(let f=0;f<l.length-1;f++){let u=r.find(P=>P.part===l[f]),m=r.find(P=>P.part===l[f+1]);u&&m&&u.score>(t.body.minConfidence||0)&&m.score>(t.body.minConfidence||0)&&y.push([u.position,m.position])}i[c]=y}let x={id:0,score:A,box:a.box,boxRaw:a.boxRaw,keypoints:r,annotations:i};return O1(x),s.push(x),s}async function EA(e,t,o){let n=[];for(let r=0;r<e[0].length;r++){let A=e[0][r],s=Math.round(100*A[51+4])/100;if(s>t.body.minConfidence){let a=[];for(let l=0;l<17;l++){let y=A[3*l+2];if(y>t.body.minConfidence){let f=[A[3*l+1],A[3*l+0]];a.push({part:f5[l],score:Math.round(100*y)/100,positionRaw:f,position:[Math.round((o.shape[2]||0)*f[0]),Math.round((o.shape[1]||0)*f[1])]})}}let i=le(a.map(l=>l.position),[o.shape[2],o.shape[1]]),x={};for(let[l,y]of Object.entries(m5)){let f=[];for(let u=0;u<y.length-1;u++){let m=a.find(g=>g.part===y[u]),P=a.find(g=>g.part===y[u+1]);m&&P&&m.score>(t.body.minConfidence||0)&&P.score>(t.body.minConfidence||0)&&f.push([m.position,P.position])}x[l]=f}let c={id:r,score:s,box:i.box,boxRaw:i.boxRaw,keypoints:[...a],annotations:x};O1(c),n.push(c)}}return n.sort((r,A)=>A.score-r.score),n.length>t.body.maxDetected&&(n.length=t.body.maxDetected),n}async function L1(e,t){if(!F0||!(F0!=null&&F0.inputs[0].shape))return[];t.skipAllowed||(Ze.boxes.length=0),N1++;let o=(t.body.skipTime||0)>h()-Ze.last,n=N1<(t.body.skipFrames||0);return t.skipAllowed&&o&&n?Ze.bodies:new Promise(async r=>{let A={};N1=0,A.input=ko(e,p5),A.res=F0==null?void 0:F0.execute(A.input),Ze.last=h();let s=await A.res.array();Ze.bodies=A.res.shape[2]===17?await kA(s,t,e):await EA(s,t,e);for(let a of Ze.bodies)Eo(a,[e.shape[2]||1,e.shape[1]||1]),wo(a.keypoints);Object.keys(A).forEach(a=>zo.dispose(A[a])),r(Ze.bodies)})}var E0=Z(D());var a2,u5=[],Io=0,W1=Number.MAX_SAFE_INTEGER,b5=0,h5=2.5;async function jo(e){if(!a2||v.initial){a2=await G(e.object.modelPath);let t=Object.values(a2.modelSignature.inputs);b5=Array.isArray(t)?parseInt(t[0].tensorShape.dim[2].size):0}else e.debug&&p("cached model:",a2.modelUrl);return a2}async function zA(e,t,o){let n=0,r=[];for(let i of[1,2,4])E0.tidy(async()=>{let x=i*13,c=E0.squeeze(e.find(m=>m.shape[1]===x**2&&(m.shape[2]||0)===$e.length)),l=E0.squeeze(e.find(m=>m.shape[1]===x**2&&(m.shape[2]||0)<$e.length)),f=await l.reshape([-1,4,l.shape[1]/4]).argMax(2).array(),u=await c.array();for(let m=0;m<c.shape[0];m++)for(let P=0;P<c.shape[1];P++){let g=u[m][P];if(g>(o.object.minConfidence||0)&&P!==61){let b=(.5+Math.trunc(m%x))/x,d=(.5+Math.trunc(m/x))/x,M=f[m].map(J=>J*(x/i/b5)),[S,w]=[b-h5/i*M[0],d-h5/i*M[1]],[j,C]=[b+h5/i*M[2]-S,d+h5/i*M[3]-w],F=[S,w,j,C];F=F.map(J=>Math.max(0,Math.min(J,1)));let H=[F[0]*t[0],F[1]*t[1],F[2]*t[0],F[3]*t[1]],Y={id:n++,score:Math.round(100*g)/100,class:P+1,label:$e[P].label,box:H.map(J=>Math.trunc(J)),boxRaw:F};r.push(Y)}}});e.forEach(i=>E0.dispose(i));let A=r.map(i=>[i.boxRaw[1],i.boxRaw[0],i.boxRaw[3],i.boxRaw[2]]),s=r.map(i=>i.score),a=[];if(A&&A.length>0){let i=await E0.image.nonMaxSuppressionAsync(A,s,o.object.maxDetected,o.object.iouThreshold,o.object.minConfidence);a=await i.data(),E0.dispose(i)}return r=r.filter((i,x)=>a.includes(x)).sort((i,x)=>x.score-i.score),r}async function F1(e,t){let o=(t.object.skipTime||0)>h()-Io,n=W1<(t.object.skipFrames||0);return t.skipAllowed&&o&&n&&u5.length>0?(W1++,u5):(W1=0,!v.kernels.includes("mod")||!v.kernels.includes("sparsetodense")?u5:new Promise(async r=>{let A=[e.shape[2]||0,e.shape[1]||0],s=E0.image.resizeBilinear(e,[b5,b5],!1),a=E0.div(s,V.tf255),i=a.transpose([0,3,1,2]);E0.dispose(a),E0.dispose(s);let x;t.object.enabled&&(x=a2.execute(i)),Io=h(),E0.dispose(i);let c=await zA(x,A,t);u5=c,r(c)}))}var z0=Z(D());var S2=["nose","leftEye","rightEye","leftEar","rightEar","leftShoulder","rightShoulder","leftElbow","rightElbow","leftWrist","rightWrist","leftHip","rightHip","leftKnee","rightKnee","leftAnkle","rightAnkle"],SA=S2.length,z2=S2.reduce((e,t,o)=>(e[t]=o,e),{}),CA=[["leftHip","leftShoulder"],["leftElbow","leftShoulder"],["leftElbow","leftWrist"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["rightHip","rightShoulder"],["rightElbow","rightShoulder"],["rightElbow","rightWrist"],["rightHip","rightKnee"],["rightKnee","rightAnkle"],["leftShoulder","rightShoulder"],["leftHip","rightHip"]],ts=CA.map(([e,t])=>[z2[e],z2[t]]),No=[["nose","leftEye"],["leftEye","leftEar"],["nose","rightEye"],["rightEye","rightEar"],["nose","leftShoulder"],["leftShoulder","leftElbow"],["leftElbow","leftWrist"],["leftShoulder","leftHip"],["leftHip","leftKnee"],["leftKnee","leftAnkle"],["nose","rightShoulder"],["rightShoulder","rightElbow"],["rightElbow","rightWrist"],["rightShoulder","rightHip"],["rightHip","rightKnee"],["rightKnee","rightAnkle"]];function Lo(e){let t=e.reduce(({maxX:o,maxY:n,minX:r,minY:A},{position:{x:s,y:a}})=>({maxX:Math.max(o,s),maxY:Math.max(n,a),minX:Math.min(r,s),minY:Math.min(A,a)}),{maxX:Number.NEGATIVE_INFINITY,maxY:Number.NEGATIVE_INFINITY,minX:Number.POSITIVE_INFINITY,minY:Number.POSITIVE_INFINITY});return[t.minX,t.minY,t.maxX-t.minX,t.maxY-t.minY]}function Wo(e,[t,o],[n,r]){let A=t/n,s=o/r,a=(x,c)=>({id:c,score:x.score,boxRaw:[x.box[0]/r,x.box[1]/n,x.box[2]/r,x.box[3]/n],box:[Math.trunc(x.box[0]*s),Math.trunc(x.box[1]*A),Math.trunc(x.box[2]*s),Math.trunc(x.box[3]*A)],keypoints:x.keypoints.map(({score:l,part:y,position:f})=>({score:l,part:y,position:[Math.trunc(f.x*s),Math.trunc(f.y*A)],positionRaw:[f.x/n,f.y/n]})),annotations:{}});return e.map((x,c)=>a(x,c))}var g5=class{constructor(t,o){T(this,"priorityQueue");T(this,"numberOfElements");T(this,"getElementValue");this.priorityQueue=new Array(t),this.numberOfElements=-1,this.getElementValue=o}enqueue(t){this.priorityQueue[++this.numberOfElements]=t,this.swim(this.numberOfElements)}dequeue(){let t=this.priorityQueue[0];return this.exchange(0,this.numberOfElements--),this.sink(0),this.priorityQueue[this.numberOfElements+1]=null,t}empty(){return this.numberOfElements===-1}size(){return this.numberOfElements+1}all(){return this.priorityQueue.slice(0,this.numberOfElements+1)}max(){return this.priorityQueue[0]}swim(t){for(;t>0&&this.less(Math.floor(t/2),t);)this.exchange(t,Math.floor(t/2)),t=Math.floor(t/2)}sink(t){for(;2*t<=this.numberOfElements;){let o=2*t;if(o<this.numberOfElements&&this.less(o,o+1)&&o++,!this.less(t,o))break;this.exchange(t,o),t=o}}getValueAt(t){return this.getElementValue(this.priorityQueue[t])}less(t,o){return this.getValueAt(t)<this.getValueAt(o)}exchange(t,o){let n=this.priorityQueue[t];this.priorityQueue[t]=this.priorityQueue[o],this.priorityQueue[o]=n}};function G1(e,t,o,n){return{y:n.get(e,t,o),x:n.get(e,t,o+SA)}}function B1(e,t,o){let{heatmapY:n,heatmapX:r,id:A}=e,{y:s,x:a}=G1(n,r,A,o);return{x:e.heatmapX*t+a,y:e.heatmapY*t+s}}function H1(e,t,o){return e<t?t:e>o?o:e}function Fo(e,t,o,n){let r=o-e,A=n-t;return r*r+A*A}function V1(e,t){return{x:e.x+t.x,y:e.y+t.y}}var $0,jA=["MobilenetV1/offset_2/BiasAdd","MobilenetV1/heatmap_2/BiasAdd","MobilenetV1/displacement_fwd_2/BiasAdd","MobilenetV1/displacement_bwd_2/BiasAdd"],M5=1,i2=16,OA=50**2;function Go(e,t,o,n,r,A,s=2){let a=g=>({y:A.get(g.y,g.x,e),x:A.get(g.y,g.x,A.shape[2]/2+e)}),i=(g,b,d)=>({y:H1(Math.round(g.y/i2),0,b-1),x:H1(Math.round(g.x/i2),0,d-1)}),[x,c]=n.shape,l=i(t.position,x,c),y=a(l),u=V1(t.position,y);for(let g=0;g<s;g++){let b=i(u,x,c),d=G1(b.y,b.x,o,r);u=V1({x:b.x*i2,y:b.y*i2},{x:d.x,y:d.y})}let m=i(u,x,c),P=n.get(m.y,m.x,o);return{position:u,part:S2[o],score:P}}function NA(e,t,o,n,r){let A=No.map(([y,f])=>[z2[y],z2[f]]),s=A.map(([,y])=>y),a=A.map(([y])=>y),i=t.shape[2],x=s.length,c=new Array(i),l=B1(e.part,i2,o);c[e.part.id]={score:e.score,part:S2[e.part.id],position:l};for(let y=x-1;y>=0;--y){let f=s[y],u=a[y];c[f]&&!c[u]&&(c[u]=Go(y,c[f],u,t,o,r))}for(let y=0;y<x;++y){let f=a[y],u=s[y];c[f]&&!c[u]&&(c[u]=Go(y,c[f],u,t,o,n))}return c}function LA(e,t,o,n,r){let[A,s]=r.shape,a=!0,i=Math.max(o-M5,0),x=Math.min(o+M5+1,A);for(let c=i;c<x;++c){let l=Math.max(n-M5,0),y=Math.min(n+M5+1,s);for(let f=l;f<y;++f)if(r.get(c,f,e)>t){a=!1;break}if(!a)break}return a}function WA(e,t){let[o,n,r]=t.shape,A=new g5(o*n*r,({score:s})=>s);for(let s=0;s<o;++s)for(let a=0;a<n;++a)for(let i=0;i<r;++i){let x=t.get(s,a,i);x<e||LA(i,x,s,a,t)&&A.enqueue({score:x,part:{heatmapY:s,heatmapX:a,id:i}})}return A}function Bo(e,{x:t,y:o},n){return e.some(({keypoints:r})=>{var s;let A=(s=r[n])==null?void 0:s.position;return A?Fo(o,t,A.y,A.x)<=OA:!1})}function FA(e,t){return t.reduce((n,{position:r,score:A},s)=>(Bo(e,r,s)||(n+=A),n),0)/t.length}function GA(e,t,o,n,r,A){let s=[],a=WA(A,t);for(;s.length<r&&!a.empty();){let i=a.dequeue(),x=B1(i.part,i2,e);if(Bo(s,x,i.part.id))continue;let c=NA(i,t,e,o,n);c=c.filter(f=>f.score>A);let l=FA(s,c),y=Lo(c);l>A&&s.push({keypoints:c,box:y,score:Math.round(100*l)/100})}return s}async function D1(e,t){let o=z0.tidy(()=>{if(!$0.inputs[0].shape)return[];let s=z0.image.resizeBilinear(e,[$0.inputs[0].shape[2],$0.inputs[0].shape[1]]),a=z0.sub(z0.div(z0.cast(s,"float32"),127.5),1),x=$0.execute(a,jA).map(c=>z0.squeeze(c,[0]));return x[1]=z0.sigmoid(x[1]),x}),n=await Promise.all(o.map(s=>s.buffer()));for(let s of o)z0.dispose(s);let r=await GA(n[0],n[1],n[2],n[3],t.body.maxDetected,t.body.minConfidence);return $0.inputs[0].shape?Wo(r,[e.shape[1],e.shape[2]],[$0.inputs[0].shape[2],$0.inputs[0].shape[1]]):[]}async function Ho(e){return!$0||v.initial?$0=await G(e.body.modelPath):e.debug&&p("cached model:",$0.modelUrl),$0}var n0=Z(D());var ne,Z1=!1;async function X1(e){return!ne||v.initial?ne=await G(e.segmentation.modelPath):e.debug&&p("cached model:",ne.modelUrl),ne}async function Do(e,t,o){var m,P;if(Z1)return{data:[],canvas:null,alpha:null};Z1=!0,ne||await X1(o);let n=await Ye(e,o),r=((m=n.tensor)==null?void 0:m.shape[2])||0,A=((P=n.tensor)==null?void 0:P.shape[1])||0;if(!n.tensor)return{data:[],canvas:null,alpha:null};let s={};s.resize=n0.image.resizeBilinear(n.tensor,[ne.inputs[0].shape?ne.inputs[0].shape[1]:0,ne.inputs[0].shape?ne.inputs[0].shape[2]:0],!1),n0.dispose(n.tensor),s.norm=n0.div(s.resize,V.tf255),s.res=ne.execute(s.norm),s.squeeze=n0.squeeze(s.res,0),s.squeeze.shape[2]===2?(s.softmax=n0.softmax(s.squeeze),[s.bg,s.fg]=n0.unstack(s.softmax,2),s.expand=n0.expandDims(s.fg,2),s.pad=n0.expandDims(s.expand,0),s.crop=n0.image.cropAndResize(s.pad,[[0,0,.5,.5]],[0],[r,A]),s.data=n0.squeeze(s.crop,0)):s.data=n0.image.resizeBilinear(s.squeeze,[A,r]);let a=Array.from(await s.data.data());if(v.node&&!v.Canvas&&typeof ImageData=="undefined")return o.debug&&p("canvas support missing"),Object.keys(s).forEach(g=>n0.dispose(s[g])),{data:a,canvas:null,alpha:null};let i=R0(r,A);n0.browser&&await n0.browser.toPixels(s.data,i);let x=i.getContext("2d");o.segmentation.blur&&o.segmentation.blur>0&&(x.filter=`blur(${o.segmentation.blur}px)`);let c=x.getImageData(0,0,r,A),l=R0(r,A),y=l.getContext("2d");n.canvas&&y.drawImage(n.canvas,0,0),y.globalCompositeOperation="darken",o.segmentation.blur&&o.segmentation.blur>0&&(y.filter=`blur(${o.segmentation.blur}px)`),y.drawImage(i,0,0),y.globalCompositeOperation="source-over",y.filter="none";let f=y.getImageData(0,0,r,A);for(let g=0;g<r*A;g++)f.data[4*g+3]=c.data[4*g+0];y.putImageData(f,0,0);let u=null;if(t&&l){u=R0(r,A);let g=await Ye(t,o);n0.dispose(g.tensor);let b=u.getContext("2d");b.drawImage(g.canvas,0,0,u.width,u.height),b.drawImage(l,0,0)}return Object.keys(s).forEach(g=>n0.dispose(s[g])),Z1=!1,{data:a,canvas:l,alpha:i}}var C2=class{constructor(){T(this,"ssrnetage",null);T(this,"gear",null);T(this,"blazeposedetect",null);T(this,"blazepose",null);T(this,"centernet",null);T(this,"efficientpose",null);T(this,"mobilefacenet",null);T(this,"emotion",null);T(this,"facedetect",null);T(this,"faceiris",null);T(this,"facemesh",null);T(this,"faceres",null);T(this,"ssrnetgender",null);T(this,"handpose",null);T(this,"handskeleton",null);T(this,"handtrack",null);T(this,"liveness",null);T(this,"movenet",null);T(this,"nanodet",null);T(this,"posenet",null);T(this,"segmentation",null);T(this,"antispoof",null)}},q1=e=>{let t=0,o=0,n=0;for(let A of Object.values(q0))t+=A.sizeFromManifest,o+=A.sizeLoadedWeights,n+=A.sizeDesired;let r=n>0?o/n:0;return{numLoadedModels:Object.values(q0).length,numEnabledModels:void 0,numDefinedModels:Object.keys(e.models).length,percentageLoaded:r,totalSizeFromManifest:t,totalSizeWeights:o,totalSizeLoading:n,totalSizeEnabled:void 0,modelStats:Object.values(q0)}};function P5(e){for(let t of Object.keys(e.models))e.models[t]=null}async function U1(e){var t,o,n,r,A,s,a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0;v.initial&&P5(e),e.config.hand.enabled&&(!e.models.handpose&&((o=(t=e.config.hand.detector)==null?void 0:t.modelPath)==null?void 0:o.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await T1(e.config)),!e.models.handskeleton&&e.config.hand.landmarks&&((r=(n=e.config.hand.detector)==null?void 0:n.modelPath)==null?void 0:r.includes("handdetect"))&&([e.models.handpose,e.models.handskeleton]=await T1(e.config))),e.config.body.enabled&&!e.models.blazepose&&((s=(A=e.config.body)==null?void 0:A.modelPath)==null?void 0:s.includes("blazepose"))&&(e.models.blazepose=c3(e.config)),e.config.body.enabled&&!e.models.blazeposedetect&&e.config.body.detector&&e.config.body.detector.modelPath&&(e.models.blazeposedetect=x3(e.config)),e.config.body.enabled&&!e.models.efficientpose&&((i=(a=e.config.body)==null?void 0:a.modelPath)==null?void 0:i.includes("efficientpose"))&&(e.models.efficientpose=h3(e.config)),e.config.body.enabled&&!e.models.movenet&&((c=(x=e.config.body)==null?void 0:x.modelPath)==null?void 0:c.includes("movenet"))&&(e.models.movenet=So(e.config)),e.config.body.enabled&&!e.models.posenet&&((y=(l=e.config.body)==null?void 0:l.modelPath)==null?void 0:y.includes("posenet"))&&(e.models.posenet=Ho(e.config)),e.config.face.enabled&&!e.models.facedetect&&(e.models.facedetect=o3(e.config)),e.config.face.enabled&&((f=e.config.face.antispoof)==null?void 0:f.enabled)&&!e.models.antispoof&&(e.models.antispoof=Dt(e.config)),e.config.face.enabled&&((u=e.config.face.liveness)==null?void 0:u.enabled)&&!e.models.liveness&&(e.models.liveness=Ro(e.config)),e.config.face.enabled&&((m=e.config.face.description)==null?void 0:m.enabled)&&!e.models.faceres&&(e.models.faceres=Z3(e.config)),e.config.face.enabled&&((P=e.config.face.emotion)==null?void 0:P.enabled)&&!e.models.emotion&&(e.models.emotion=P3(e.config)),e.config.face.enabled&&((g=e.config.face.iris)==null?void 0:g.enabled)&&!((b=e.config.face.attention)!=null&&b.enabled)&&!e.models.faceiris&&(e.models.faceiris=j3(e.config)),e.config.face.enabled&&((d=e.config.face.mesh)==null?void 0:d.enabled)&&!e.models.facemesh&&(e.models.facemesh=G3(e.config)),e.config.face.enabled&&((M=e.config.face.gear)==null?void 0:M.enabled)&&!e.models.gear&&(e.models.gear=St(e.config)),e.config.face.enabled&&((S=e.config.face.ssrnet)==null?void 0:S.enabled)&&!e.models.ssrnetage&&(e.models.ssrnetage=Nt(e.config)),e.config.face.enabled&&((w=e.config.face.ssrnet)==null?void 0:w.enabled)&&!e.models.ssrnetgender&&(e.models.ssrnetgender=Gt(e.config)),e.config.face.enabled&&((j=e.config.face.mobilefacenet)==null?void 0:j.enabled)&&!e.models.mobilefacenet&&(e.models.mobilefacenet=E3(e.config)),e.config.hand.enabled&&!e.models.handtrack&&((F=(C=e.config.hand.detector)==null?void 0:C.modelPath)==null?void 0:F.includes("handtrack"))&&(e.models.handtrack=ho(e.config)),e.config.hand.enabled&&e.config.hand.landmarks&&!e.models.handskeleton&&((Y=(H=e.config.hand.detector)==null?void 0:H.modelPath)==null?void 0:Y.includes("handtrack"))&&(e.models.handskeleton=bo(e.config)),e.config.object.enabled&&!e.models.centernet&&((x0=(J=e.config.object)==null?void 0:J.modelPath)==null?void 0:x0.includes("centernet"))&&(e.models.centernet=m3(e.config)),e.config.object.enabled&&!e.models.nanodet&&((G0=(E=e.config.object)==null?void 0:E.modelPath)==null?void 0:G0.includes("nanodet"))&&(e.models.nanodet=jo(e.config)),e.config.segmentation.enabled&&!e.models.segmentation&&(e.models.segmentation=X1(e.config));for await(let B0 of Object.keys(e.models))e.models[B0]&&typeof e.models[B0]!="undefined"&&(e.models[B0]=await e.models[B0])}async function Y1(e){let t=["const","placeholder","noop","pad","squeeze","add","sub","mul","div"];for(let o of Object.keys(e.models)){let n=e.models[o];if(!n)continue;let r=[],A=n==null?void 0:n.executor;if(A&&A.graph.nodes)for(let a of Object.values(A.graph.nodes)){let i=a.op.toLowerCase();r.includes(i)||r.push(i)}else!A&&e.config.debug&&p("model signature not determined:",o);let s=[];for(let a of r)!t.includes(a)&&!e.env.kernels.includes(a)&&!e.env.kernels.includes(a.replace("_",""))&&!e.env.kernels.includes(a.replace("native",""))&&!e.env.kernels.includes(a.replace("v2",""))&&s.push(a);e.config.debug&&s.length>0&&p("model validation failed:",o,s)}}var t0={name:"humangl",priority:999,canvas:null,gl:null,extensions:[],webGLattr:{alpha:!1,antialias:!1,premultipliedAlpha:!1,preserveDrawingBuffer:!1,depth:!1,stencil:!1,failIfMajorPerformanceCaveat:!1,desynchronized:!0}};function BA(){let e=t0.gl;!e||(t0.extensions=e.getSupportedExtensions())}async function Xo(e){var t;if(e.config.backend==="humangl"&&(t0.name in s0.engine().registry&&(!t0.gl||!t0.gl.getParameter(t0.gl.VERSION))&&(p("error: humangl backend invalid context"),P5(e)),!s0.findBackend(t0.name))){try{t0.canvas=await R0(100,100)}catch(n){p("error: cannot create canvas:",n);return}try{if(t0.gl=(t=t0.canvas)==null?void 0:t.getContext("webgl2",t0.webGLattr),!t0.gl.getParameter(t0.gl.VERSION).includes("2.0")){p("override: using fallback webgl backend as webgl 2.0 is not detected"),e.config.backend="webgl";return}t0.canvas&&(t0.canvas.addEventListener("webglcontextlost",async r=>{throw p("error: humangl:",r.type),p("possible browser memory leak using webgl or conflict with multiple backend registrations"),e.emit("error"),new Error("backend error: webgl context lost")}),t0.canvas.addEventListener("webglcontextrestored",r=>{p("error: humangl context restored:",r)}),t0.canvas.addEventListener("webglcontextcreationerror",r=>{p("error: humangl context create:",r)}))}catch(n){p("error: cannot get WebGL context:",n);return}try{s0.setWebGLContext(2,t0.gl)}catch(n){p("error: cannot set WebGL context:",n);return}try{let n=new s0.GPGPUContext(t0.gl);s0.registerBackend(t0.name,()=>new s0.MathBackendWebGL(n),t0.priority)}catch(n){p("error: cannot register WebGL backend:",n);return}try{s0.getKernelsForBackend("webgl").forEach(r=>{let A={...r,backendName:t0.name};s0.registerKernel(A)})}catch(n){p("error: cannot update WebGL backend registration:",n);return}let o=s0.backend().getGPGPUContext?s0.backend().getGPGPUContext().gl:null;if(o)p(`humangl webgl version:${o.getParameter(o.VERSION)} renderer:${o.getParameter(o.RENDERER)}`);else{p("error: no current gl context:",o,t0.gl);return}try{s0.env().flagRegistry.WEBGL_VERSION&&s0.env().set("WEBGL_VERSION",2)}catch(n){p("error: cannot set WebGL backend flags:",n);return}BA(),p("backend registered:",t0.name)}}var I=Z(D());function HA(){if(!v.kernels.includes("mod")){let e={kernelName:"Mod",backendName:I.getBackend(),kernelFunc:t=>I.tidy(()=>I.sub(t.inputs.a,I.mul(I.div(t.inputs.a,t.inputs.b),t.inputs.b)))};I.registerKernel(e),v.kernels.push("mod")}if(!v.kernels.includes("floormod")){let e={kernelName:"FloorMod",backendName:I.getBackend(),kernelFunc:t=>I.tidy(()=>I.floorDiv(t.inputs.a/t.inputs.b)*t.inputs.b+I.mod(t.inputs.a,t.inputs.b))};I.registerKernel(e),v.kernels.push("floormod")}}async function v5(e,t=!1){if(e.state="backend",t||v.initial||e.config.backend&&e.config.backend.length>0&&I.getBackend()!==e.config.backend){let o=h();if(e.config.backend&&e.config.backend.length>0){if(typeof window=="undefined"&&typeof WorkerGlobalScope!="undefined"&&e.config.debug&&e.config.debug&&p("running inside web worker"),v.browser&&e.config.backend==="tensorflow"&&(e.config.debug&&p("override: backend set to tensorflow while running in browser"),e.config.backend="humangl"),v.node&&(e.config.backend==="webgl"||e.config.backend==="humangl")&&(e.config.debug&&p(`override: backend set to ${e.config.backend} while running in nodejs`),e.config.backend="tensorflow"),v.browser&&e.config.backend==="webgpu")if(typeof navigator=="undefined"||typeof navigator.gpu=="undefined")p("override: backend set to webgpu but browser does not support webgpu"),e.config.backend="humangl";else{let r=await navigator.gpu.requestAdapter();if(e.config.debug&&p("enumerated webgpu adapter:",r),!r)p("override: backend set to webgpu but browser reports no available gpu"),e.config.backend="humangl";else{let A="requestAdapterInfo"in r?await r.requestAdapterInfo():void 0;p("webgpu adapter info:",A)}}e.config.backend==="humangl"&&await Xo(e);let n=Object.keys(I.engine().registryFactory);if(e.config.debug&&p("available backends:",n),n.includes(e.config.backend)||(p(`error: backend ${e.config.backend} not found in registry`),e.config.backend=v.node?"tensorflow":"webgl",e.config.debug&&p(`override: setting backend ${e.config.backend}`)),e.config.debug&&p("setting backend:",e.config.backend),e.config.backend==="wasm"){if(I.env().flagRegistry.CANVAS2D_WILL_READ_FREQUENTLY&&I.env().set("CANVAS2D_WILL_READ_FREQUENTLY",!0),e.config.debug&&p("wasm path:",e.config.wasmPath),typeof(I==null?void 0:I.setWasmPaths)!="undefined")await I.setWasmPaths(e.config.wasmPath,e.config.wasmPlatformFetch);else throw new Error("backend error: attempting to use wasm backend but wasm path is not set");let r=await I.env().getAsync("WASM_HAS_SIMD_SUPPORT"),A=await I.env().getAsync("WASM_HAS_MULTITHREAD_SUPPORT");e.config.debug&&p(`wasm execution: ${r?"SIMD":"no SIMD"} ${A?"multithreaded":"singlethreaded"}`),e.config.debug&&!r&&p("warning: wasm simd support is not enabled")}try{await I.setBackend(e.config.backend),await I.ready(),It()}catch(r){return p("error: cannot set backend:",e.config.backend,r),!1}}if(I.getBackend()==="humangl"&&(I.env().flagRegistry.CHECK_COMPUTATION_FOR_ERRORS&&I.env().set("CHECK_COMPUTATION_FOR_ERRORS",!1),I.env().flagRegistry.WEBGL_CPU_FORWARD&&I.env().set("WEBGL_CPU_FORWARD",!0),I.env().flagRegistry.WEBGL_USE_SHAPES_UNIFORMS&&I.env().set("WEBGL_USE_SHAPES_UNIFORMS",!0),I.env().flagRegistry.CPU_HANDOFF_SIZE_THRESHOLD&&I.env().set("CPU_HANDOFF_SIZE_THRESHOLD",256),I.env().flagRegistry.WEBGL_EXP_CONV&&I.env().set("WEBGL_EXP_CONV",!0),I.env().flagRegistry.USE_SETTIMEOUTWPM&&I.env().set("USE_SETTIMEOUTWPM",!0),typeof e.config.deallocate!="undefined"&&e.config.deallocate&&(p("changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:",!0),I.env().set("WEBGL_DELETE_TEXTURE_THRESHOLD",0)),I.backend().getGPGPUContext)){let n=await I.backend().getGPGPUContext().gl;e.config.debug&&p(`gl version:${n.getParameter(n.VERSION)} renderer:${n.getParameter(n.RENDERER)}`)}I.getBackend(),I.enableProdMode(),await I.ready(),e.performance.initBackend=Math.trunc(h()-o),e.config.backend=I.getBackend(),await v.updateBackend(),HA()}return!0}function x5(e,t){for(let o of e){let n={kernelName:o,backendName:t.backend,kernelFunc:()=>{t.debug&&p("kernelFunc",o,t.backend)}};I.registerKernel(n)}v.kernels=I.getKernelsForBackend(I.getBackend()).map(o=>o.kernelName.toLowerCase())}var tt={};ue(tt,{all:()=>et,body:()=>y2,canvas:()=>$1,face:()=>l2,gesture:()=>d2,hand:()=>x2,object:()=>c2,options:()=>P0,person:()=>_1});var V0=e=>{if(!e)p("draw error: invalid canvas");else if(!e.getContext)p("draw error: canvas context not defined");else{let t=e.getContext("2d");if(!t)p("draw error: cannot get canvas context");else return t}return null},Xe=e=>Math.round(e*180/Math.PI),me=(e,t)=>{if(!t.useDepth||typeof e=="undefined")return t.color;let o=Uint8ClampedArray.from([127+2*e,127-2*e,255]);return`rgba(${o[0]}, ${o[1]}, ${o[2]}, ${t.alpha})`};function pe(e,t,o,n,r){e.fillStyle=me(n,r),e.beginPath(),e.arc(t,o,r.pointSize,0,2*Math.PI),e.fill()}function re(e,t,o,n,r,A){if(e.beginPath(),e.lineWidth=A.lineWidth,A.useCurves){let s=(t+t+n)/2,a=(o+o+r)/2;e.ellipse(s,a,n/2,r/2,0,0,2*Math.PI)}else e.moveTo(t+A.roundRect,o),e.lineTo(t+n-A.roundRect,o),e.quadraticCurveTo(t+n,o,t+n,o+A.roundRect),e.lineTo(t+n,o+r-A.roundRect),e.quadraticCurveTo(t+n,o+r,t+n-A.roundRect,o+r),e.lineTo(t+A.roundRect,o+r),e.quadraticCurveTo(t,o+r,t,o+r-A.roundRect),e.lineTo(t,o+A.roundRect),e.quadraticCurveTo(t,o,t+A.roundRect,o),e.closePath();e.stroke()}function K1(e,t,o){if(!(t.length<2)){e.beginPath(),e.moveTo(t[0][0],t[0][1]);for(let n of t)e.strokeStyle=me(n[2]||0,o),e.lineTo(Math.trunc(n[0]),Math.trunc(n[1]));e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function Uo(e,t,o){if(!(t.length<2)){if(e.lineWidth=o.lineWidth,!o.useCurves||t.length<=2){K1(e,t,o);return}e.moveTo(t[0][0],t[0][1]);for(let n=0;n<t.length-2;n++){let r=(t[n][0]+t[n+1][0])/2,A=(t[n][1]+t[n+1][1])/2;e.quadraticCurveTo(t[n][0],t[n][1],r,A)}e.quadraticCurveTo(t[t.length-2][0],t[t.length-2][1],t[t.length-1][0],t[t.length-1][1]),e.stroke(),o.fillPolygons&&(e.closePath(),e.fill())}}function J1(e,t,o,n=5){let r,A,s;e.beginPath(),e.moveTo(t[0],t[1]),e.lineTo(o[0],o[1]),r=Math.atan2(o[1]-t[1],o[0]-t[0]),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.moveTo(A,s),r+=1/3*(2*Math.PI),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.lineTo(A,s),r+=1/3*(2*Math.PI),A=n*Math.cos(r)+o[0],s=n*Math.sin(r)+o[1],e.lineTo(A,s),e.closePath(),e.stroke(),e.fill()}var P0={color:"rgba(173, 216, 230, 0.6)",labelColor:"rgba(173, 216, 230, 1)",shadowColor:"black",alpha:.5,font:'small-caps 16px "Segoe UI"',lineHeight:18,lineWidth:4,pointSize:2,roundRect:8,drawPoints:!1,drawLabels:!0,drawBoxes:!0,drawAttention:!0,drawGestures:!0,drawPolygons:!0,drawGaze:!0,fillPolygons:!1,useDepth:!0,useCurves:!1};var U;function DA(e,t){if(U.drawLabels){let o=[];if(o.push(`face: ${Math.trunc(100*e.score)}%`),e.genderScore&&o.push(`${e.gender||""} ${Math.trunc(100*e.genderScore)}%`),e.age&&o.push(`age: ${e.age||""}`),e.iris&&o.push(`distance: ${e.iris}`),e.real&&o.push(`real: ${Math.trunc(100*e.real)}%`),e.live&&o.push(`live: ${Math.trunc(100*e.live)}%`),e.emotion&&e.emotion.length>0){let n=e.emotion.map(r=>`${Math.trunc(100*r.score)}% ${r.emotion}`);n.length>3&&(n.length=3),o.push(n.join(" "))}e.rotation&&e.rotation.angle&&e.rotation.gaze&&(e.rotation.angle.roll&&o.push(`roll: ${Xe(e.rotation.angle.roll)}\xB0 yaw:${Xe(e.rotation.angle.yaw)}\xB0 pitch:${Xe(e.rotation.angle.pitch)}\xB0`),e.rotation.gaze.bearing&&o.push(`gaze: ${Xe(e.rotation.gaze.bearing)}\xB0`)),o.length===0&&o.push("face"),t.fillStyle=U.color;for(let n=o.length-1;n>=0;n--){let r=Math.max(e.box[0],0),A=n*U.lineHeight+e.box[1];U.shadowColor&&U.shadowColor!==""&&(t.fillStyle=U.shadowColor,t.fillText(o[n],r+5,A+16)),t.fillStyle=U.labelColor,t.fillText(o[n],r+4,A+15)}}}function ZA(e,t){if(e.annotations&&e.annotations.leftEyeIris&&e.annotations.leftEyeIris[0]){t.strokeStyle=U.useDepth?"rgba(255, 200, 255, 0.3)":U.color,t.beginPath();let o=Math.abs(e.annotations.leftEyeIris[3][0]-e.annotations.leftEyeIris[1][0])/2,n=Math.abs(e.annotations.leftEyeIris[4][1]-e.annotations.leftEyeIris[2][1])/2;t.ellipse(e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),U.fillPolygons&&(t.fillStyle=U.useDepth?"rgba(255, 255, 200, 0.3)":U.color,t.fill())}if(e.annotations&&e.annotations.rightEyeIris&&e.annotations.rightEyeIris[0]){t.strokeStyle=U.useDepth?"rgba(255, 200, 255, 0.3)":U.color,t.beginPath();let o=Math.abs(e.annotations.rightEyeIris[3][0]-e.annotations.rightEyeIris[1][0])/2,n=Math.abs(e.annotations.rightEyeIris[4][1]-e.annotations.rightEyeIris[2][1])/2;t.ellipse(e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1],o,n,0,0,2*Math.PI),t.stroke(),U.fillPolygons&&(t.fillStyle=U.useDepth?"rgba(255, 255, 200, 0.3)":U.color,t.fill())}}function XA(e,t){var o;if(U.drawGaze&&((o=e.rotation)==null?void 0:o.angle)&&typeof Path2D!="undefined"){t.strokeStyle="pink";let n=e.box[0]+e.box[2]/2-e.box[3]*Xe(e.rotation.angle.yaw)/90,r=e.box[1]+e.box[3]/2+e.box[2]*Xe(e.rotation.angle.pitch)/90,A=new Path2D(`
       M ${e.box[0]+e.box[2]/2} ${e.box[1]}
       C
         ${n} ${e.box[1]},
@@ -108,7 +108,7 @@ var An=Object.create;var h2=Object.defineProperty;var sn=Object.getOwnPropertyDe
         ${e.box[0]} ${r},
         ${e.box[0]+e.box[2]} ${r},
         ${e.box[0]+e.box[2]} ${e.box[1]+e.box[3]/2}
-    `);t.stroke(s),t.stroke(A)}}function qA(e,t){var o,n,r,A;if(U.drawGaze&&((n=(o=e.rotation)==null?void 0:o.gaze)==null?void 0:n.strength)&&((A=(r=e.rotation)==null?void 0:r.gaze)==null?void 0:A.bearing)&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let s=[e.annotations.leftEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.leftEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];J1(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[s[0],s[1]],4);let a=[e.annotations.rightEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.rightEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];J1(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[a[0],a[1]],4)}}function UA(e,t){if(U.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let o=0;o<Ne.length/3;o++){let n=[Ne[o*3+0],Ne[o*3+1],Ne[o*3+2]].map(r=>e.mesh[r]);K1(t,n,U)}ZA(e,t)}}function YA(e,t){if(U.drawPoints&&e.mesh.length>=468)for(let o=0;o<e.mesh.length;o++)pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2],U),U.drawAttention&&(w2.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]+127,U),We.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,U),Fe.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,U))}function KA(e,t){U.drawBoxes&&re(t,e.box[0],e.box[1],e.box[2],e.box[3],U)}async function l2(e,t,o){if(U=r0(P0,o),!t||!e)return;let n=V0(e);if(!!n){n.font=U.font,n.strokeStyle=U.color,n.fillStyle=U.color;for(let r of t)KA(r,n),DA(r,n),r.mesh&&r.mesh.length>0&&(YA(r,n),UA(r,n),XA(r,n),qA(r,n))}}async function y2(e,t,o){var A;let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round";for(let s=0;s<t.length;s++){if(r.strokeStyle=n.color,r.fillStyle=n.color,r.lineWidth=n.lineWidth,r.font=n.font,n.drawBoxes&&t[s].box&&((A=t[s].box)==null?void 0:A.length)===4&&(re(r,t[s].box[0],t[s].box[1],t[s].box[2],t[s].box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`body ${100*t[s].score}%`,t[s].box[0]+3,1+t[s].box[1]+n.lineHeight,t[s].box[2])),r.fillStyle=n.labelColor,r.fillText(`body ${100*t[s].score}%`,t[s].box[0]+2,0+t[s].box[1]+n.lineHeight,t[s].box[2]))),n.drawPoints&&t[s].keypoints)for(let a=0;a<t[s].keypoints.length;a++)!t[s].keypoints[a].score||t[s].keypoints[a].score===0||(r.fillStyle=me(t[s].keypoints[a].position[2],n),pe(r,t[s].keypoints[a].position[0],t[s].keypoints[a].position[1],0,n));if(n.drawLabels&&t[s].keypoints){r.font=n.font;for(let a of t[s].keypoints)!a.score||a.score===0||(r.fillStyle=me(a.position[2],n),r.fillText(`${a.part} ${Math.trunc(100*a.score)}%`,a.position[0]+4,a.position[1]+4))}if(n.drawPolygons&&t[s].keypoints&&t[s].annotations)for(let a of Object.values(t[s].annotations))for(let i of a)Uo(r,i,n)}}}async function x2(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A of t){if(n.drawBoxes&&(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,A.box[0],A.box[1],A.box[2],A.box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`hand:${Math.trunc(100*A.score)}%`,A.box[0]+3,1+A.box[1]+n.lineHeight,A.box[2])),r.fillStyle=n.labelColor,r.fillText(`hand:${Math.trunc(100*A.score)}%`,A.box[0]+2,0+A.box[1]+n.lineHeight,A.box[2])),r.stroke()),n.drawPoints&&A.keypoints&&A.keypoints.length>0)for(let s of A.keypoints)r.fillStyle=me(s[2],n),pe(r,s[0],s[1],0,n);if(n.drawLabels&&A.annotations){let s=(a,i)=>{if(!a||a.length===0||!a[0])return;let x=a[a.length-1][2]||-256;r.fillStyle=me(x,n),r.fillText(i,a[a.length-1][0]+4,a[a.length-1][1]+4)};r.font=n.font,s(A.annotations.index,"index"),s(A.annotations.middle,"middle"),s(A.annotations.ring,"ring"),s(A.annotations.pinky,"pinky"),s(A.annotations.thumb,"thumb"),s(A.annotations.palm,"palm")}if(n.drawPolygons&&A.annotations){let s=a=>{if(!(!a||a.length===0||!a[0]))for(let i=0;i<a.length;i++){r.beginPath();let x=a[i][2]||0;r.strokeStyle=me(i*x,n),r.moveTo(a[i>0?i-1:0][0],a[i>0?i-1:0][1]),r.lineTo(a[i][0],a[i][1]),r.stroke()}};r.lineWidth=n.lineWidth,s(A.annotations.index),s(A.annotations.middle),s(A.annotations.ring),s(A.annotations.pinky),s(A.annotations.thumb)}}}}async function c2(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A of t)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,A.box[0],A.box[1],A.box[2],A.box[3],n),n.drawLabels){let s=`${A.label} ${Math.round(100*A.score)}%`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(s,A.box[0]+3,1+A.box[1]+n.lineHeight,A.box[2])),r.fillStyle=n.labelColor,r.fillText(s,A.box[0]+2,0+A.box[1]+n.lineHeight,A.box[2])}r.stroke()}}}async function d2(e,t,o){let n=r0(P0,o);if(!(!t||!e)&&n.drawGestures){let r=V0(e);if(!r)return;r.font=n.font,r.fillStyle=n.color;let A=1;for(let s=0;s<t.length;s++){let a=[],i=[];if([a,i]=Object.entries(t[s]),i.length>1&&i[1].length>0){let x=a[1]>0?`#${a[1]}`:"",c=`${a[0]} ${x}: ${i[1]}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(c,8,2+A*n.lineHeight)),r.fillStyle=n.labelColor,r.fillText(c,6,0+A*n.lineHeight),A+=1}}}}var Q1=0;async function _1(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A=0;A<t.length;A++)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,t[A].box[0],t[A].box[1],t[A].box[2],t[A].box[3],n),n.drawLabels){let s=`person #${A}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(s,t[A].box[0]+3,1+t[A].box[1]+n.lineHeight,t[A].box[2])),r.fillStyle=n.labelColor,r.fillText(s,t[A].box[0]+2,0+t[A].box[1]+n.lineHeight,t[A].box[2])}r.stroke()}}}async function $1(e,t){if(!e||!t)return;let o=V0(t);!o||o.drawImage(e,0,0)}async function et(e,t,o){if(!t||!t.performance||!t||!e)return null;let n=h(),r=r0(P0,o),A=Promise.all([l2(e,t.face,r),y2(e,t.body,r),x2(e,t.hand,r),c2(e,t.object,r),d2(e,t.gesture,r)]);return Q1=v.perfadd?Q1+Math.round(h()-n):Math.round(h()-n),t.performance.draw=Q1,A}var s0=Z(D());var Yo=Z(D());var f2=.1,ot=.5;function JA(e,t,o){let n=!1,r=o.length-1;for(let A=0;A<o.length;r=A++)o[A].y>t!=o[r].y>t&&e<(o[r].x-o[A].x)*(t-o[A].y)/(o[r].y-o[A].y)+o[A].x&&(n=!n);return n}async function Ko(e){if(!e.tensor||!e.mesh||e.mesh.length<100)return e.tensor;let t=e.tensor.shape[2]||0,o=e.tensor.shape[1]||0,n=await e.tensor.buffer(),r=[];for(let s of X0.silhouette)r.push({x:(e.mesh[s][0]-e.box[0])/e.box[2],y:(e.mesh[s][1]-e.box[1])/e.box[3]});f2&&f2>0&&(r=r.map(s=>({x:s.x>.5?s.x+f2:s.x-f2,y:s.y>.5?s.y+f2:s.y-f2})));for(let s=0;s<t;s++)for(let a=0;a<o;a++)JA(s/t,a/t,r)||(n.set(ot*n.get(0,a,s,0),0,a,s,0),n.set(ot*n.get(0,a,s,1),0,a,s,1),n.set(ot*n.get(0,a,s,2),0,a,s,2));let A=n.toTensor();return Yo.dispose(n),A}var _A=e=>{let t=(l,y)=>Math.atan2(l[1]-y[1],l[0]-y[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let o=[0,-.1],n=1,r=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),A=r?e.mesh[473]:e.mesh[468],s=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],a=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],i=[(s[0]-A[0])/a[0]-o[0],n*(A[1]-s[1])/a[1]-o[1]],x=Math.sqrt(i[0]*i[0]+i[1]*i[1]);return x=Math.min(x,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],i)+Math.PI/2)%Math.PI,strength:x}},Jo=(e,t)=>{let o=m=>{let P=Math.sqrt(m[0]*m[0]+m[1]*m[1]+m[2]*m[2]);return m[0]/=P,m[1]/=P,m[2]/=P,m},n=(m,P)=>{let g=m[0]-P[0],b=m[1]-P[1],d=m[2]-P[2];return[g,b,d]},r=(m,P)=>{let g=m[1]*P[2]-m[2]*P[1],b=m[2]*P[0]-m[0]*P[2],d=m[0]*P[1]-m[1]*P[0];return[g,b,d]},A=m=>{let[P,g,b,d,M,S,w,j,C]=m,F,H,Y;return d<1?d>-1?(Y=Math.asin(d),H=Math.atan2(-w,P),F=Math.atan2(-S,M)):(Y=-Math.PI/2,H=-Math.atan2(j,C),F=0):(Y=Math.PI/2,H=Math.atan2(j,C),F=0),isNaN(F)&&(F=0),isNaN(H)&&(H=0),isNaN(Y)&&(Y=0),{pitch:2*-F,yaw:2*-H,roll:2*-Y}},s=e.meshRaw;if(!s||s.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let a=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,i=[s[10],s[152],s[234],s[454]].map(m=>[m[0]*t[0]/a,m[1]*t[1]/a,m[2]]),x=o(n(i[1],i[0])),c=o(n(i[3],i[2])),l=o(r(c,x));c=r(x,l);let y=[c[0],c[1],c[2],x[0],x[1],x[2],l[0],l[1],l[2]],f=A(y),u=s.length===478?_A(e):{bearing:0,strength:0};return{angle:f,matrix:y,gaze:u}};var nt=async(e,t)=>{var f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0,R,c0;let o=h(),n,r,A,s,a,i,x,c,l=[];e.state="run:face";let y=await F3(t,e.config);if(e.performance.face=v.perfadd?(e.performance.face||0)+Math.trunc(h()-o):Math.trunc(h()-o),!t.shape||t.shape.length!==4)return[];if(!y)return[];for(let k=0;k<y.length;k++){if(e.analyze("Get Face"),!y[k].tensor||y[k].tensor.isDisposedInternal){p("Face object is disposed:",y[k].tensor);continue}if((f=e.config.face.detector)!=null&&f.mask){let K=await Ko(y[k]);s0.dispose(y[k].tensor),y[k].tensor=K}let $=y[k].mesh&&y[k].mesh.length>200?Jo(y[k],[t.shape[2],t.shape[1]]):null;e.analyze("Start Emotion:"),e.config.async?s=(u=e.config.face.emotion)!=null&&u.enabled?y1(y[k].tensor||s0.tensor([]),e.config,k,y.length):[]:(e.state="run:emotion",o=h(),s=(m=e.config.face.emotion)!=null&&m.enabled?await y1(y[k].tensor||s0.tensor([]),e.config,k,y.length):[],e.performance.emotion=v.perfadd?(e.performance.emotion||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Emotion:"),e.analyze("Start AntiSpoof:"),e.config.async?i=(P=e.config.face.antispoof)!=null&&P.enabled?X5(y[k].tensor||s0.tensor([]),e.config,k,y.length):0:(e.state="run:antispoof",o=h(),i=(g=e.config.face.antispoof)!=null&&g.enabled?await X5(y[k].tensor||s0.tensor([]),e.config,k,y.length):0,e.performance.antispoof=v.perfadd?(e.performance.antispoof||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End AntiSpoof:"),e.analyze("Start Liveness:"),e.config.async?x=(b=e.config.face.liveness)!=null&&b.enabled?S1(y[k].tensor||s0.tensor([]),e.config,k,y.length):0:(e.state="run:liveness",o=h(),x=(d=e.config.face.liveness)!=null&&d.enabled?await S1(y[k].tensor||s0.tensor([]),e.config,k,y.length):0,e.performance.liveness=v.perfadd?(e.performance.antispoof||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Liveness:"),e.analyze("Start GEAR:"),e.config.async?r=(M=e.config.face.gear)!=null&&M.enabled?F5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null:(e.state="run:gear",o=h(),r=(S=e.config.face.gear)!=null&&S.enabled?await F5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,e.performance.gear=Math.trunc(h()-o)),e.analyze("End GEAR:"),e.analyze("Start SSRNet:"),e.config.async?(n=(w=e.config.face.ssrnet)!=null&&w.enabled?B5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,A=(j=e.config.face.ssrnet)!=null&&j.enabled?D5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null):(e.state="run:ssrnet",o=h(),n=(C=e.config.face.ssrnet)!=null&&C.enabled?await B5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,A=(F=e.config.face.ssrnet)!=null&&F.enabled?await D5(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,e.performance.ssrnet=Math.trunc(h()-o)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?a=(H=e.config.face.mobilefacenet)!=null&&H.enabled?c1(y[k].tensor||s0.tensor([]),e.config,k,y.length):null:(e.state="run:mobilefacenet",o=h(),a=(Y=e.config.face.mobilefacenet)!=null&&Y.enabled?await c1(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,e.performance.mobilefacenet=Math.trunc(h()-o)),e.analyze("End MobileFaceNet:"),e.analyze("Start Description:"),e.config.async?c=(J=e.config.face.description)!=null&&J.enabled?h1(y[k].tensor||s0.tensor([]),e.config,k,y.length):null:(e.state="run:description",o=h(),c=(x0=e.config.face.description)!=null&&x0.enabled?await h1(y[k].tensor||s0.tensor([]),e.config,k,y.length):null,e.performance.description=v.perfadd?(e.performance.description||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Description:"),e.config.async&&([n,A,s,a,c,r,i,x]=await Promise.all([n,A,s,a,c,r,i,x])),e.analyze("Finish Face:"),((E=e.config.face.ssrnet)==null?void 0:E.enabled)&&n&&A&&(c={...c,age:n.age,gender:A.gender,genderScore:A.genderScore}),((G0=e.config.face.gear)==null?void 0:G0.enabled)&&r&&(c={...c,age:r.age,gender:r.gender,genderScore:r.genderScore,race:r.race}),((B0=e.config.face.mobilefacenet)==null?void 0:B0.enabled)&&a&&(c.descriptor=a),(R=e.config.face.iris)!=null&&R.enabled;let a0=y[k].annotations&&y[k].annotations.leftEyeIris&&y[k].annotations.leftEyeIris[0]&&y[k].annotations.rightEyeIris&&y[k].annotations.rightEyeIris[0]&&y[k].annotations.leftEyeIris.length>0&&y[k].annotations.rightEyeIris.length>0&&y[k].annotations.leftEyeIris[0]!==null&&y[k].annotations.rightEyeIris[0]!==null?Math.max(Math.abs(y[k].annotations.leftEyeIris[3][0]-y[k].annotations.leftEyeIris[1][0]),Math.abs(y[k].annotations.rightEyeIris[4][1]-y[k].annotations.rightEyeIris[2][1]))/t.shape[2]:0,f0=(c0=e.config.face.detector)!=null&&c0.return?s0.squeeze(y[k].tensor):null;s0.dispose(y[k].tensor),y[k].tensor&&delete y[k].tensor;let L={...y[k],id:k};c!=null&&c.age&&(L.age=c.age),c!=null&&c.gender&&(L.gender=c.gender),c!=null&&c.genderScore&&(L.genderScore=c==null?void 0:c.genderScore),c!=null&&c.descriptor&&(L.embedding=c==null?void 0:c.descriptor),c!=null&&c.race&&(L.race=c==null?void 0:c.race),s&&(L.emotion=s),i&&(L.real=i),x&&(L.live=x),a0&&a0!==0&&(L.iris=Math.trunc(500/a0/11.7)/100),$&&(L.rotation=$),f0&&(L.tensor=f0),l.push(L),e.analyze("End Face")}return e.analyze("End FaceMesh:"),e.config.async&&(e.performance.face&&delete e.performance.face,e.performance.age&&delete e.performance.age,e.performance.gender&&delete e.performance.gender,e.performance.emotion&&delete e.performance.emotion),l};var Qo=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=e[o].keypoints.find(i=>i.part==="leftWrist"),r=e[o].keypoints.find(i=>i.part==="rightWrist"),A=e[o].keypoints.find(i=>i.part==="nose");A&&n&&r&&n.position[1]<A.position[1]&&r.position[1]<A.position[1]?t.push({body:o,gesture:"i give up"}):A&&n&&n.position[1]<A.position[1]?t.push({body:o,gesture:"raise left hand"}):A&&r&&r.position[1]<A.position[1]&&t.push({body:o,gesture:"raise right hand"});let s=e[o].keypoints.find(i=>i.part==="leftShoulder"),a=e[o].keypoints.find(i=>i.part==="rightShoulder");s&&a&&Math.abs(s.positionRaw[1]-a.positionRaw[1])>.1&&t.push({body:o,gesture:`leaning ${s.position[1]>a.position[1]?"left":"right"}`})}return t},_o=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++)if(e[o].mesh&&e[o].mesh.length>450){let n=(e[o].mesh[33][2]||0)-(e[o].mesh[263][2]||0),r=e[o].mesh[33][0]-e[o].mesh[263][0];Math.abs(n/r)<=.15?t.push({face:o,gesture:"facing center"}):t.push({face:o,gesture:`facing ${n<0?"left":"right"}`}),Math.abs(e[o].mesh[374][1]-e[o].mesh[386][1])/Math.abs(e[o].mesh[443][1]-e[o].mesh[450][1])<.2&&t.push({face:o,gesture:"blink left eye"}),Math.abs(e[o].mesh[145][1]-e[o].mesh[159][1])/Math.abs(e[o].mesh[223][1]-e[o].mesh[230][1])<.2&&t.push({face:o,gesture:"blink right eye"});let a=Math.min(100,500*Math.abs(e[o].mesh[13][1]-e[o].mesh[14][1])/Math.abs(e[o].mesh[10][1]-e[o].mesh[152][1]));a>10&&t.push({face:o,gesture:`mouth ${Math.trunc(a)}% open`});let i=e[o].mesh[152][2]||0;Math.abs(i)>10&&t.push({face:o,gesture:`head ${i<0?"up":"down"}`})}return t},$o=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){if(!e[o].annotations||!e[o].annotations.leftEyeIris||!e[o].annotations.leftEyeIris[0]||!e[o].annotations.rightEyeIris||!e[o].annotations.rightEyeIris[0])continue;let n=e[o].annotations.leftEyeIris[3][0]-e[o].annotations.leftEyeIris[1][0],r=e[o].annotations.leftEyeIris[4][1]-e[o].annotations.leftEyeIris[2][1],A=Math.abs(n*r),s=e[o].annotations.rightEyeIris[3][0]-e[o].annotations.rightEyeIris[1][0],a=e[o].annotations.rightEyeIris[4][1]-e[o].annotations.rightEyeIris[2][1],i=Math.abs(s*a),x=!1;Math.abs(A-i)/Math.max(A,i)<.25&&(x=!0,t.push({iris:o,gesture:"facing center"}));let l=Math.abs(e[o].mesh[263][0]-e[o].annotations.leftEyeIris[0][0])/e[o].box[2],y=Math.abs(e[o].mesh[33][0]-e[o].annotations.rightEyeIris[0][0])/e[o].box[2];(l>.06||y>.06)&&(x=!1),l>y?l>.05&&t.push({iris:o,gesture:"looking right"}):y>.05&&t.push({iris:o,gesture:"looking left"});let f=Math.abs(e[o].mesh[145][1]-e[o].annotations.rightEyeIris[0][1])/e[o].box[3],u=Math.abs(e[o].mesh[374][1]-e[o].annotations.leftEyeIris[0][1])/e[o].box[3];(u<.01||f<.01||u>.022||f>.022)&&(x=!1),(u<.01||f<.01)&&t.push({iris:o,gesture:"looking down"}),(u>.022||f>.022)&&t.push({iris:o,gesture:"looking up"}),x&&t.push({iris:o,gesture:"looking center"})}return t},en=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=[];if(e[o].annotations)for(let[r,A]of Object.entries(e[o].annotations))r!=="palmBase"&&Array.isArray(A)&&A[0]&&n.push({name:r.toLowerCase(),position:A[0]});if(n&&n.length>0){let r=n.reduce((s,a)=>(s.position[2]||0)<(a.position[2]||0)?s:a);t.push({hand:o,gesture:`${r.name} forward`});let A=n.reduce((s,a)=>s.position[1]<a.position[1]?s:a);t.push({hand:o,gesture:`${A.name} up`})}if(e[o].keypoints){let r=yo(e[o].keypoints);for(let A of r)t.push({hand:o,gesture:A.name})}}return t};var z={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null},rt=0;function tn(e,t){var s,a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0;let o=h();if(!e)return{face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null};let n=Date.now()-e.timestamp,r=n<1e3?8-Math.log(n+1):1;if(e.canvas&&(z.canvas=e.canvas),e.error&&(z.error=e.error),!z.body||e.body.length!==z.body.length)z.body=JSON.parse(JSON.stringify(e.body));else for(let R=0;R<e.body.length;R++){let c0=e.body[R].box.map((L,K)=>((r-1)*z.body[R].box[K]+L)/r),k=e.body[R].boxRaw.map((L,K)=>((r-1)*z.body[R].boxRaw[K]+L)/r),$=e.body[R].keypoints.map((L,K)=>{var Ae,se,p2,u2,qe,lt,yt,xt,ct;return{score:L.score,part:L.part,position:[z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[0]||0)+(L.position[0]||0))/r:L.position[0],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[1]||0)+(L.position[1]||0))/r:L.position[1],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[2]||0)+(L.position[2]||0))/r:L.position[2]],positionRaw:[z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[0]||0)+(L.positionRaw[0]||0))/r:L.positionRaw[0],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[1]||0)+(L.positionRaw[1]||0))/r:L.positionRaw[1],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[2]||0)+(L.positionRaw[2]||0))/r:L.positionRaw[2]],distance:[z.body[R].keypoints[K]?((r-1)*(((Ae=z.body[R].keypoints[K].distance)==null?void 0:Ae[0])||0)+(((se=L.distance)==null?void 0:se[0])||0))/r:(p2=L.distance)==null?void 0:p2[0],z.body[R].keypoints[K]?((r-1)*(((u2=z.body[R].keypoints[K].distance)==null?void 0:u2[1])||0)+(((qe=L.distance)==null?void 0:qe[1])||0))/r:(lt=L.distance)==null?void 0:lt[1],z.body[R].keypoints[K]?((r-1)*(((yt=z.body[R].keypoints[K].distance)==null?void 0:yt[2])||0)+(((xt=L.distance)==null?void 0:xt[2])||0))/r:(ct=L.distance)==null?void 0:ct[2]]}}),a0={},f0={connected:{}};(a=(s=t.body)==null?void 0:s.modelPath)!=null&&a.includes("efficientpose")?f0=e5:(x=(i=t.body)==null?void 0:i.modelPath)!=null&&x.includes("blazepose")?f0=K2:(l=(c=t.body)==null?void 0:c.modelPath)!=null&&l.includes("movenet")&&(f0=E2);for(let[L,K]of Object.entries(f0.connected)){let Ae=[];for(let se=0;se<K.length-1;se++){let p2=$.find(qe=>qe.part===K[se]),u2=$.find(qe=>qe.part===K[se+1]);p2&&u2&&Ae.push([p2.position,u2.position])}a0[L]=Ae}z.body[R]={...e.body[R],box:c0,boxRaw:k,keypoints:$,annotations:a0}}if(!z.hand||e.hand.length!==z.hand.length)z.hand=JSON.parse(JSON.stringify(e.hand));else for(let R=0;R<e.hand.length;R++){let c0=e.hand[R].box.map((f0,L)=>((r-1)*z.hand[R].box[L]+f0)/r),k=e.hand[R].boxRaw.map((f0,L)=>((r-1)*z.hand[R].boxRaw[L]+f0)/r);z.hand[R].keypoints.length!==e.hand[R].keypoints.length&&(z.hand[R].keypoints=e.hand[R].keypoints);let $=e.hand[R].keypoints&&e.hand[R].keypoints.length>0?e.hand[R].keypoints.map((f0,L)=>f0.map((K,Ae)=>((r-1)*(z.hand[R].keypoints[L][Ae]||1)+(K||0))/r)):[],a0={};if(Object.keys(z.hand[R].annotations).length!==Object.keys(e.hand[R].annotations).length)z.hand[R].annotations=e.hand[R].annotations,a0=z.hand[R].annotations;else if(e.hand[R].annotations)for(let f0 of Object.keys(e.hand[R].annotations))a0[f0]=e.hand[R].annotations[f0]&&e.hand[R].annotations[f0][0]?e.hand[R].annotations[f0].map((L,K)=>L.map((Ae,se)=>((r-1)*z.hand[R].annotations[f0][K][se]+Ae)/r)):null;z.hand[R]={...e.hand[R],box:c0,boxRaw:k,keypoints:$,annotations:a0}}if(!z.face||e.face.length!==z.face.length)z.face=JSON.parse(JSON.stringify(e.face));else for(let R=0;R<e.face.length;R++){let c0=e.face[R].box.map(($,a0)=>((r-1)*z.face[R].box[a0]+$)/r),k=e.face[R].boxRaw.map(($,a0)=>((r-1)*z.face[R].boxRaw[a0]+$)/r);if(e.face[R].rotation){let $={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};$.matrix=(y=e.face[R].rotation)==null?void 0:y.matrix,$.angle={roll:((r-1)*(((u=(f=z.face[R].rotation)==null?void 0:f.angle)==null?void 0:u.roll)||0)+(((P=(m=e.face[R].rotation)==null?void 0:m.angle)==null?void 0:P.roll)||0))/r,yaw:((r-1)*(((b=(g=z.face[R].rotation)==null?void 0:g.angle)==null?void 0:b.yaw)||0)+(((M=(d=e.face[R].rotation)==null?void 0:d.angle)==null?void 0:M.yaw)||0))/r,pitch:((r-1)*(((w=(S=z.face[R].rotation)==null?void 0:S.angle)==null?void 0:w.pitch)||0)+(((C=(j=e.face[R].rotation)==null?void 0:j.angle)==null?void 0:C.pitch)||0))/r},$.gaze={bearing:((r-1)*(((H=(F=z.face[R].rotation)==null?void 0:F.gaze)==null?void 0:H.bearing)||0)+(((J=(Y=e.face[R].rotation)==null?void 0:Y.gaze)==null?void 0:J.bearing)||0))/r,strength:((r-1)*(((E=(x0=z.face[R].rotation)==null?void 0:x0.gaze)==null?void 0:E.strength)||0)+(((B0=(G0=e.face[R].rotation)==null?void 0:G0.gaze)==null?void 0:B0.strength)||0))/r},z.face[R]={...e.face[R],rotation:$,box:c0,boxRaw:k}}z.face[R]={...e.face[R],box:c0,boxRaw:k}}if(!z.object||e.object.length!==z.object.length)z.object=JSON.parse(JSON.stringify(e.object));else for(let R=0;R<e.object.length;R++){let c0=e.object[R].box.map(($,a0)=>((r-1)*z.object[R].box[a0]+$)/r),k=e.object[R].boxRaw.map(($,a0)=>((r-1)*z.object[R].boxRaw[a0]+$)/r);z.object[R]={...e.object[R],box:c0,boxRaw:k}}if(e.persons){let R=e.persons;if(!z.persons||R.length!==z.persons.length)z.persons=JSON.parse(JSON.stringify(R));else for(let c0=0;c0<R.length;c0++)z.persons[c0].box=R[c0].box.map((k,$)=>((r-1)*z.persons[c0].box[$]+k)/r)}e.gesture&&(z.gesture=e.gesture);let A=h();return rt=v.perfadd?rt+Math.round(A-o):Math.round(A-o),e.performance&&(z.performance={...e.performance,interpolate:rt}),z}var at={};ue(at,{distance:()=>j2,match:()=>st,similarity:()=>At});function j2(e,t,o={order:2,multiplier:25}){let n=0;for(let r=0;r<e.length;r++){let A=!o.order||o.order===2?e[r]-t[r]:Math.abs(e[r]-t[r]);n+=!o.order||o.order===2?A*A:A**o.order}return(o.multiplier||20)*n}var on=(e,t,o,n)=>{if(e===0)return 1;let r=t===2?Math.sqrt(e):e**(1/t),A=(1-r/100-o)/(n-o);return Math.max(Math.min(A,1),0)};function At(e,t,o={order:2,multiplier:25,min:.2,max:.8}){let n=j2(e,t,o);return on(n,o.order||2,o.min||0,o.max||1)}function st(e,t,o={order:2,multiplier:25,threshold:0,min:.2,max:.8}){if(!Array.isArray(e)||!Array.isArray(t)||e.length<64||t.length===0||e.length!==t[0].length)return{index:-1,distance:Number.POSITIVE_INFINITY,similarity:0};let n=Number.MAX_SAFE_INTEGER,r=-1;for(let s=0;s<t.length;s++){let a=j2(e,t[s],o);if(a<n&&(n=a,r=s),n<(o.threshold||0))break}let A=on(n,o.order||2,o.min||0,o.max||1);return{index:r,distance:n,similarity:A}}function nn(e,t,o,n,r){var a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w;let A=0,s=[];for(let j of e){let C={id:A++,face:j,body:null,hands:{left:null,right:null},gestures:[],box:[0,0,0,0]};for(let E of t)j.box[0]>E.box[0]&&j.box[0]<E.box[0]+E.box[2]&&j.box[1]+j.box[3]>E.box[1]&&j.box[1]+j.box[3]<E.box[1]+E.box[3]&&(C.body=E);if(C.body)for(let E of o)E.box[0]+E.box[2]>C.body.box[0]&&E.box[0]+E.box[2]<C.body.box[0]+C.body.box[2]&&E.box[1]+E.box[3]>C.body.box[1]&&E.box[1]+E.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.left=E),E.box[0]<C.body.box[0]+C.body.box[2]&&E.box[0]>C.body.box[0]&&E.box[1]+E.box[3]>C.body.box[1]&&E.box[1]+E.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.right=E);for(let E of n)E.face!==void 0&&E.face===j.id?(a=C.gestures)==null||a.push(E):E.iris!==void 0&&E.iris===j.id?(i=C.gestures)==null||i.push(E):E.body!==void 0&&E.body===((x=C.body)==null?void 0:x.id)?(c=C.gestures)==null||c.push(E):E.hand!==void 0&&E.hand===((y=(l=C.hands)==null?void 0:l.left)==null?void 0:y.id)?(f=C.gestures)==null||f.push(E):E.hand!==void 0&&E.hand===((m=(u=C.hands)==null?void 0:u.right)==null?void 0:m.id)&&((P=C.gestures)==null||P.push(E));let F=[],H=[],Y=E=>{E&&E.length===4&&(F.push(E[0],E[0]+E[2]),H.push(E[1],E[1]+E[3]))};Y((g=C.face)==null?void 0:g.box),Y((b=C.body)==null?void 0:b.box),Y((M=(d=C.hands)==null?void 0:d.left)==null?void 0:M.box),Y((w=(S=C.hands)==null?void 0:S.right)==null?void 0:w.box);let J=Math.min(...F),x0=Math.min(...H);C.box=[J,x0,Math.max(...F)-J,Math.max(...H)-x0],r&&r[1]&&r[2]&&(C.boxRaw=[C.box[0]/r[2],C.box[1]/r[1],C.box[2]/r[2],C.box[3]/r[1]]),s.push(C)}return s}var T5=`
+    `);t.stroke(s),t.stroke(A)}}function qA(e,t){var o,n,r,A;if(U.drawGaze&&((n=(o=e.rotation)==null?void 0:o.gaze)==null?void 0:n.strength)&&((A=(r=e.rotation)==null?void 0:r.gaze)==null?void 0:A.bearing)&&e.annotations.leftEyeIris&&e.annotations.rightEyeIris&&e.annotations.leftEyeIris[0]&&e.annotations.rightEyeIris[0]){t.strokeStyle="pink",t.fillStyle="pink";let s=[e.annotations.leftEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.leftEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];J1(t,[e.annotations.leftEyeIris[0][0],e.annotations.leftEyeIris[0][1]],[s[0],s[1]],4);let a=[e.annotations.rightEyeIris[0][0]+Math.sin(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[3],e.annotations.rightEyeIris[0][1]+Math.cos(e.rotation.gaze.bearing)*e.rotation.gaze.strength*e.box[2]];J1(t,[e.annotations.rightEyeIris[0][0],e.annotations.rightEyeIris[0][1]],[a[0],a[1]],4)}}function UA(e,t){if(U.drawPolygons&&e.mesh.length>=468){t.lineWidth=1;for(let o=0;o<Oe.length/3;o++){let n=[Oe[o*3+0],Oe[o*3+1],Oe[o*3+2]].map(r=>e.mesh[r]);K1(t,n,U)}ZA(e,t)}}function YA(e,t){if(U.drawPoints&&e.mesh.length>=468)for(let o=0;o<e.mesh.length;o++)pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2],U),U.drawAttention&&(w2.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]+127,U),We.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,U),Fe.includes(o)&&pe(t,e.mesh[o][0],e.mesh[o][1],e.mesh[o][2]-127,U))}function KA(e,t){U.drawBoxes&&re(t,e.box[0],e.box[1],e.box[2],e.box[3],U)}async function l2(e,t,o){if(U=r0(P0,o),!t||!e)return;let n=V0(e);if(!!n){n.font=U.font,n.strokeStyle=U.color,n.fillStyle=U.color;for(let r of t)KA(r,n),DA(r,n),r.mesh&&r.mesh.length>0&&(YA(r,n),UA(r,n),XA(r,n),qA(r,n))}}async function y2(e,t,o){var A;let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round";for(let s=0;s<t.length;s++){if(r.strokeStyle=n.color,r.fillStyle=n.color,r.lineWidth=n.lineWidth,r.font=n.font,n.drawBoxes&&t[s].box&&((A=t[s].box)==null?void 0:A.length)===4&&(re(r,t[s].box[0],t[s].box[1],t[s].box[2],t[s].box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`body ${100*t[s].score}%`,t[s].box[0]+3,1+t[s].box[1]+n.lineHeight,t[s].box[2])),r.fillStyle=n.labelColor,r.fillText(`body ${100*t[s].score}%`,t[s].box[0]+2,0+t[s].box[1]+n.lineHeight,t[s].box[2]))),n.drawPoints&&t[s].keypoints)for(let a=0;a<t[s].keypoints.length;a++)!t[s].keypoints[a].score||t[s].keypoints[a].score===0||(r.fillStyle=me(t[s].keypoints[a].position[2],n),pe(r,t[s].keypoints[a].position[0],t[s].keypoints[a].position[1],0,n));if(n.drawLabels&&t[s].keypoints){r.font=n.font;for(let a of t[s].keypoints)!a.score||a.score===0||(r.fillStyle=me(a.position[2],n),r.fillText(`${a.part} ${Math.trunc(100*a.score)}%`,a.position[0]+4,a.position[1]+4))}if(n.drawPolygons&&t[s].keypoints&&t[s].annotations)for(let a of Object.values(t[s].annotations))for(let i of a)Uo(r,i,n)}}}async function x2(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A of t){if(n.drawBoxes&&(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,A.box[0],A.box[1],A.box[2],A.box[3],n),n.drawLabels&&(n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(`hand:${Math.trunc(100*A.score)}%`,A.box[0]+3,1+A.box[1]+n.lineHeight,A.box[2])),r.fillStyle=n.labelColor,r.fillText(`hand:${Math.trunc(100*A.score)}%`,A.box[0]+2,0+A.box[1]+n.lineHeight,A.box[2])),r.stroke()),n.drawPoints&&A.keypoints&&A.keypoints.length>0)for(let s of A.keypoints)r.fillStyle=me(s[2],n),pe(r,s[0],s[1],0,n);if(n.drawLabels&&A.annotations){let s=(a,i)=>{if(!a||a.length===0||!a[0])return;let x=a[a.length-1][2]||-256;r.fillStyle=me(x,n),r.fillText(i,a[a.length-1][0]+4,a[a.length-1][1]+4)};r.font=n.font,s(A.annotations.index,"index"),s(A.annotations.middle,"middle"),s(A.annotations.ring,"ring"),s(A.annotations.pinky,"pinky"),s(A.annotations.thumb,"thumb"),s(A.annotations.palm,"palm")}if(n.drawPolygons&&A.annotations){let s=a=>{if(!(!a||a.length===0||!a[0]))for(let i=0;i<a.length;i++){r.beginPath();let x=a[i][2]||0;r.strokeStyle=me(i*x,n),r.moveTo(a[i>0?i-1:0][0],a[i>0?i-1:0][1]),r.lineTo(a[i][0],a[i][1]),r.stroke()}};r.lineWidth=n.lineWidth,s(A.annotations.index),s(A.annotations.middle),s(A.annotations.ring),s(A.annotations.pinky),s(A.annotations.thumb)}}}}async function c2(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A of t)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,A.box[0],A.box[1],A.box[2],A.box[3],n),n.drawLabels){let s=`${A.label} ${Math.round(100*A.score)}%`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(s,A.box[0]+3,1+A.box[1]+n.lineHeight,A.box[2])),r.fillStyle=n.labelColor,r.fillText(s,A.box[0]+2,0+A.box[1]+n.lineHeight,A.box[2])}r.stroke()}}}async function d2(e,t,o){let n=r0(P0,o);if(!(!t||!e)&&n.drawGestures){let r=V0(e);if(!r)return;r.font=n.font,r.fillStyle=n.color;let A=1;for(let s=0;s<t.length;s++){let a=[],i=[];if([a,i]=Object.entries(t[s]),i.length>1&&i[1].length>0){let x=a[1]>0?`#${a[1]}`:"",c=`${a[0]} ${x}: ${i[1]}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(c,8,2+A*n.lineHeight)),r.fillStyle=n.labelColor,r.fillText(c,6,0+A*n.lineHeight),A+=1}}}}var Q1=0;async function _1(e,t,o){let n=r0(P0,o);if(!t||!e)return;let r=V0(e);if(!!r){r.lineJoin="round",r.font=n.font;for(let A=0;A<t.length;A++)if(n.drawBoxes){if(r.strokeStyle=n.color,r.fillStyle=n.color,re(r,t[A].box[0],t[A].box[1],t[A].box[2],t[A].box[3],n),n.drawLabels){let s=`person #${A}`;n.shadowColor&&n.shadowColor!==""&&(r.fillStyle=n.shadowColor,r.fillText(s,t[A].box[0]+3,1+t[A].box[1]+n.lineHeight,t[A].box[2])),r.fillStyle=n.labelColor,r.fillText(s,t[A].box[0]+2,0+t[A].box[1]+n.lineHeight,t[A].box[2])}r.stroke()}}}async function $1(e,t){if(!e||!t)return;let o=V0(t);!o||o.drawImage(e,0,0)}async function et(e,t,o){if(!t||!t.performance||!t||!e)return null;let n=h(),r=r0(P0,o),A=Promise.all([l2(e,t.face,r),y2(e,t.body,r),x2(e,t.hand,r),c2(e,t.object,r),d2(e,t.gesture,r)]);return Q1=v.perfadd?Q1+Math.round(h()-n):Math.round(h()-n),t.performance.draw=Q1,A}var a0=Z(D());var Yo=Z(D());var f2=.1,ot=.5;function JA(e,t,o){let n=!1,r=o.length-1;for(let A=0;A<o.length;r=A++)o[A].y>t!=o[r].y>t&&e<(o[r].x-o[A].x)*(t-o[A].y)/(o[r].y-o[A].y)+o[A].x&&(n=!n);return n}async function Ko(e){if(!e.tensor||!e.mesh||e.mesh.length<100)return e.tensor;let t=e.tensor.shape[2]||0,o=e.tensor.shape[1]||0,n=await e.tensor.buffer(),r=[];for(let s of X0.silhouette)r.push({x:(e.mesh[s][0]-e.box[0])/e.box[2],y:(e.mesh[s][1]-e.box[1])/e.box[3]});f2&&f2>0&&(r=r.map(s=>({x:s.x>.5?s.x+f2:s.x-f2,y:s.y>.5?s.y+f2:s.y-f2})));for(let s=0;s<t;s++)for(let a=0;a<o;a++)JA(s/t,a/t,r)||(n.set(ot*n.get(0,a,s,0),0,a,s,0),n.set(ot*n.get(0,a,s,1),0,a,s,1),n.set(ot*n.get(0,a,s,2),0,a,s,2));let A=n.toTensor();return Yo.dispose(n),A}var _A=e=>{let t=(l,y)=>Math.atan2(l[1]-y[1],l[0]-y[0]);if(!e.annotations.rightEyeIris||!e.annotations.leftEyeIris)return{bearing:0,strength:0};let o=[0,-.1],n=1,r=(e.mesh[33][2]||0)>(e.mesh[263][2]||0),A=r?e.mesh[473]:e.mesh[468],s=r?[(e.mesh[133][0]+e.mesh[33][0])/2,(e.mesh[133][1]+e.mesh[33][1])/2]:[(e.mesh[263][0]+e.mesh[362][0])/2,(e.mesh[263][1]+e.mesh[362][1])/2],a=r?[e.mesh[133][0]-e.mesh[33][0],e.mesh[23][1]-e.mesh[27][1]]:[e.mesh[263][0]-e.mesh[362][0],e.mesh[253][1]-e.mesh[257][1]],i=[(s[0]-A[0])/a[0]-o[0],n*(A[1]-s[1])/a[1]-o[1]],x=Math.sqrt(i[0]*i[0]+i[1]*i[1]);return x=Math.min(x,e.boxRaw[2]/2,e.boxRaw[3]/2),{bearing:(t([0,0],i)+Math.PI/2)%Math.PI,strength:x}},Jo=(e,t)=>{let o=m=>{let P=Math.sqrt(m[0]*m[0]+m[1]*m[1]+m[2]*m[2]);return m[0]/=P,m[1]/=P,m[2]/=P,m},n=(m,P)=>{let g=m[0]-P[0],b=m[1]-P[1],d=m[2]-P[2];return[g,b,d]},r=(m,P)=>{let g=m[1]*P[2]-m[2]*P[1],b=m[2]*P[0]-m[0]*P[2],d=m[0]*P[1]-m[1]*P[0];return[g,b,d]},A=m=>{let[P,g,b,d,M,S,w,j,C]=m,F,H,Y;return d<1?d>-1?(Y=Math.asin(d),H=Math.atan2(-w,P),F=Math.atan2(-S,M)):(Y=-Math.PI/2,H=-Math.atan2(j,C),F=0):(Y=Math.PI/2,H=Math.atan2(j,C),F=0),isNaN(F)&&(F=0),isNaN(H)&&(H=0),isNaN(Y)&&(Y=0),{pitch:2*-F,yaw:2*-H,roll:2*-Y}},s=e.meshRaw;if(!s||s.length<300)return{angle:{pitch:0,yaw:0,roll:0},matrix:[1,0,0,0,1,0,0,0,1],gaze:{bearing:0,strength:0}};let a=Math.max(e.boxRaw[2]*t[0],e.boxRaw[3]*t[1])/1.5,i=[s[10],s[152],s[234],s[454]].map(m=>[m[0]*t[0]/a,m[1]*t[1]/a,m[2]]),x=o(n(i[1],i[0])),c=o(n(i[3],i[2])),l=o(r(c,x));c=r(x,l);let y=[c[0],c[1],c[2],x[0],x[1],x[2],l[0],l[1],l[2]],f=A(y),u=s.length===478?_A(e):{bearing:0,strength:0};return{angle:f,matrix:y,gaze:u}};var nt=async(e,t)=>{var f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0,R,c0;let o=h(),n,r,A,s,a,i,x,c,l=[];e.state="run:face";let y=await F3(t,e.config);if(e.performance.face=v.perfadd?(e.performance.face||0)+Math.trunc(h()-o):Math.trunc(h()-o),!t.shape||t.shape.length!==4)return[];if(!y)return[];for(let k=0;k<y.length;k++){if(e.analyze("Get Face"),!y[k].tensor||y[k].tensor.isDisposedInternal){p("Face object is disposed:",y[k].tensor);continue}if((f=e.config.face.detector)!=null&&f.mask){let K=await Ko(y[k]);a0.dispose(y[k].tensor),y[k].tensor=K}let $=y[k].mesh&&y[k].mesh.length>200?Jo(y[k],[t.shape[2],t.shape[1]]):null;e.analyze("Start Emotion:"),e.config.async?s=(u=e.config.face.emotion)!=null&&u.enabled?y1(y[k].tensor||a0.tensor([]),e.config,k,y.length):[]:(e.state="run:emotion",o=h(),s=(m=e.config.face.emotion)!=null&&m.enabled?await y1(y[k].tensor||a0.tensor([]),e.config,k,y.length):[],e.performance.emotion=v.perfadd?(e.performance.emotion||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Emotion:"),e.analyze("Start AntiSpoof:"),e.config.async?i=(P=e.config.face.antispoof)!=null&&P.enabled?X5(y[k].tensor||a0.tensor([]),e.config,k,y.length):0:(e.state="run:antispoof",o=h(),i=(g=e.config.face.antispoof)!=null&&g.enabled?await X5(y[k].tensor||a0.tensor([]),e.config,k,y.length):0,e.performance.antispoof=v.perfadd?(e.performance.antispoof||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End AntiSpoof:"),e.analyze("Start Liveness:"),e.config.async?x=(b=e.config.face.liveness)!=null&&b.enabled?S1(y[k].tensor||a0.tensor([]),e.config,k,y.length):0:(e.state="run:liveness",o=h(),x=(d=e.config.face.liveness)!=null&&d.enabled?await S1(y[k].tensor||a0.tensor([]),e.config,k,y.length):0,e.performance.liveness=v.perfadd?(e.performance.antispoof||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Liveness:"),e.analyze("Start GEAR:"),e.config.async?r=(M=e.config.face.gear)!=null&&M.enabled?F5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null:(e.state="run:gear",o=h(),r=(S=e.config.face.gear)!=null&&S.enabled?await F5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,e.performance.gear=Math.trunc(h()-o)),e.analyze("End GEAR:"),e.analyze("Start SSRNet:"),e.config.async?(n=(w=e.config.face.ssrnet)!=null&&w.enabled?B5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,A=(j=e.config.face.ssrnet)!=null&&j.enabled?D5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null):(e.state="run:ssrnet",o=h(),n=(C=e.config.face.ssrnet)!=null&&C.enabled?await B5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,A=(F=e.config.face.ssrnet)!=null&&F.enabled?await D5(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,e.performance.ssrnet=Math.trunc(h()-o)),e.analyze("End SSRNet:"),e.analyze("Start MobileFaceNet:"),e.config.async?a=(H=e.config.face.mobilefacenet)!=null&&H.enabled?c1(y[k].tensor||a0.tensor([]),e.config,k,y.length):null:(e.state="run:mobilefacenet",o=h(),a=(Y=e.config.face.mobilefacenet)!=null&&Y.enabled?await c1(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,e.performance.mobilefacenet=Math.trunc(h()-o)),e.analyze("End MobileFaceNet:"),e.analyze("Start Description:"),e.config.async?c=(J=e.config.face.description)!=null&&J.enabled?h1(y[k].tensor||a0.tensor([]),e.config,k,y.length):null:(e.state="run:description",o=h(),c=(x0=e.config.face.description)!=null&&x0.enabled?await h1(y[k].tensor||a0.tensor([]),e.config,k,y.length):null,e.performance.description=v.perfadd?(e.performance.description||0)+Math.trunc(h()-o):Math.trunc(h()-o)),e.analyze("End Description:"),e.config.async&&([n,A,s,a,c,r,i,x]=await Promise.all([n,A,s,a,c,r,i,x])),e.analyze("Finish Face:"),((E=e.config.face.ssrnet)==null?void 0:E.enabled)&&n&&A&&(c={...c,age:n.age,gender:A.gender,genderScore:A.genderScore}),((G0=e.config.face.gear)==null?void 0:G0.enabled)&&r&&(c={...c,age:r.age,gender:r.gender,genderScore:r.genderScore,race:r.race}),((B0=e.config.face.mobilefacenet)==null?void 0:B0.enabled)&&a&&(c.descriptor=a),(R=e.config.face.iris)!=null&&R.enabled;let i0=y[k].annotations&&y[k].annotations.leftEyeIris&&y[k].annotations.leftEyeIris[0]&&y[k].annotations.rightEyeIris&&y[k].annotations.rightEyeIris[0]&&y[k].annotations.leftEyeIris.length>0&&y[k].annotations.rightEyeIris.length>0&&y[k].annotations.leftEyeIris[0]!==null&&y[k].annotations.rightEyeIris[0]!==null?Math.max(Math.abs(y[k].annotations.leftEyeIris[3][0]-y[k].annotations.leftEyeIris[1][0]),Math.abs(y[k].annotations.rightEyeIris[4][1]-y[k].annotations.rightEyeIris[2][1]))/t.shape[2]:0,m0=(c0=e.config.face.detector)!=null&&c0.return?a0.squeeze(y[k].tensor):null;a0.dispose(y[k].tensor),y[k].tensor&&delete y[k].tensor;let L={...y[k],id:k};c!=null&&c.age&&(L.age=c.age),c!=null&&c.gender&&(L.gender=c.gender),c!=null&&c.genderScore&&(L.genderScore=c==null?void 0:c.genderScore),c!=null&&c.descriptor&&(L.embedding=c==null?void 0:c.descriptor),c!=null&&c.race&&(L.race=c==null?void 0:c.race),s&&(L.emotion=s),i&&(L.real=i),x&&(L.live=x),i0&&i0!==0&&(L.iris=Math.trunc(500/i0/11.7)/100),$&&(L.rotation=$),m0&&(L.tensor=m0),l.push(L),e.analyze("End Face")}return e.analyze("End FaceMesh:"),e.config.async&&(e.performance.face&&delete e.performance.face,e.performance.age&&delete e.performance.age,e.performance.gender&&delete e.performance.gender,e.performance.emotion&&delete e.performance.emotion),l};var Qo=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=e[o].keypoints.find(i=>i.part==="leftWrist"),r=e[o].keypoints.find(i=>i.part==="rightWrist"),A=e[o].keypoints.find(i=>i.part==="nose");A&&n&&r&&n.position[1]<A.position[1]&&r.position[1]<A.position[1]?t.push({body:o,gesture:"i give up"}):A&&n&&n.position[1]<A.position[1]?t.push({body:o,gesture:"raise left hand"}):A&&r&&r.position[1]<A.position[1]&&t.push({body:o,gesture:"raise right hand"});let s=e[o].keypoints.find(i=>i.part==="leftShoulder"),a=e[o].keypoints.find(i=>i.part==="rightShoulder");s&&a&&Math.abs(s.positionRaw[1]-a.positionRaw[1])>.1&&t.push({body:o,gesture:`leaning ${s.position[1]>a.position[1]?"left":"right"}`})}return t},_o=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++)if(e[o].mesh&&e[o].mesh.length>450){let n=(e[o].mesh[33][2]||0)-(e[o].mesh[263][2]||0),r=e[o].mesh[33][0]-e[o].mesh[263][0];Math.abs(n/r)<=.15?t.push({face:o,gesture:"facing center"}):t.push({face:o,gesture:`facing ${n<0?"left":"right"}`}),Math.abs(e[o].mesh[374][1]-e[o].mesh[386][1])/Math.abs(e[o].mesh[443][1]-e[o].mesh[450][1])<.2&&t.push({face:o,gesture:"blink left eye"}),Math.abs(e[o].mesh[145][1]-e[o].mesh[159][1])/Math.abs(e[o].mesh[223][1]-e[o].mesh[230][1])<.2&&t.push({face:o,gesture:"blink right eye"});let a=Math.min(100,500*Math.abs(e[o].mesh[13][1]-e[o].mesh[14][1])/Math.abs(e[o].mesh[10][1]-e[o].mesh[152][1]));a>10&&t.push({face:o,gesture:`mouth ${Math.trunc(a)}% open`});let i=e[o].mesh[152][2]||0;Math.abs(i)>10&&t.push({face:o,gesture:`head ${i<0?"up":"down"}`})}return t},$o=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){if(!e[o].annotations||!e[o].annotations.leftEyeIris||!e[o].annotations.leftEyeIris[0]||!e[o].annotations.rightEyeIris||!e[o].annotations.rightEyeIris[0])continue;let n=e[o].annotations.leftEyeIris[3][0]-e[o].annotations.leftEyeIris[1][0],r=e[o].annotations.leftEyeIris[4][1]-e[o].annotations.leftEyeIris[2][1],A=Math.abs(n*r),s=e[o].annotations.rightEyeIris[3][0]-e[o].annotations.rightEyeIris[1][0],a=e[o].annotations.rightEyeIris[4][1]-e[o].annotations.rightEyeIris[2][1],i=Math.abs(s*a),x=!1;Math.abs(A-i)/Math.max(A,i)<.25&&(x=!0,t.push({iris:o,gesture:"facing center"}));let l=Math.abs(e[o].mesh[263][0]-e[o].annotations.leftEyeIris[0][0])/e[o].box[2],y=Math.abs(e[o].mesh[33][0]-e[o].annotations.rightEyeIris[0][0])/e[o].box[2];(l>.06||y>.06)&&(x=!1),l>y?l>.05&&t.push({iris:o,gesture:"looking right"}):y>.05&&t.push({iris:o,gesture:"looking left"});let f=Math.abs(e[o].mesh[145][1]-e[o].annotations.rightEyeIris[0][1])/e[o].box[3],u=Math.abs(e[o].mesh[374][1]-e[o].annotations.leftEyeIris[0][1])/e[o].box[3];(u<.01||f<.01||u>.022||f>.022)&&(x=!1),(u<.01||f<.01)&&t.push({iris:o,gesture:"looking down"}),(u>.022||f>.022)&&t.push({iris:o,gesture:"looking up"}),x&&t.push({iris:o,gesture:"looking center"})}return t},en=e=>{if(!e)return[];let t=[];for(let o=0;o<e.length;o++){let n=[];if(e[o].annotations)for(let[r,A]of Object.entries(e[o].annotations))r!=="palmBase"&&Array.isArray(A)&&A[0]&&n.push({name:r.toLowerCase(),position:A[0]});if(n&&n.length>0){let r=n.reduce((s,a)=>(s.position[2]||0)<(a.position[2]||0)?s:a);t.push({hand:o,gesture:`${r.name} forward`});let A=n.reduce((s,a)=>s.position[1]<a.position[1]?s:a);t.push({hand:o,gesture:`${A.name} up`})}if(e[o].keypoints){let r=yo(e[o].keypoints);for(let A of r)t.push({hand:o,gesture:A.name})}}return t};var z={face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null},rt=0;function tn(e,t){var s,a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0;let o=h();if(!e)return{face:[],body:[],hand:[],gesture:[],object:[],persons:[],performance:{},timestamp:0,error:null};let n=Date.now()-e.timestamp,r=n<1e3?8-Math.log(n+1):1;if(e.canvas&&(z.canvas=e.canvas),e.error&&(z.error=e.error),!z.body||e.body.length!==z.body.length)z.body=JSON.parse(JSON.stringify(e.body));else for(let R=0;R<e.body.length;R++){let c0=e.body[R].box.map((L,K)=>((r-1)*z.body[R].box[K]+L)/r),k=e.body[R].boxRaw.map((L,K)=>((r-1)*z.body[R].boxRaw[K]+L)/r),$=e.body[R].keypoints.map((L,K)=>{var Ae,se,p2,u2,qe,lt,yt,xt,ct;return{score:L.score,part:L.part,position:[z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[0]||0)+(L.position[0]||0))/r:L.position[0],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[1]||0)+(L.position[1]||0))/r:L.position[1],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].position[2]||0)+(L.position[2]||0))/r:L.position[2]],positionRaw:[z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[0]||0)+(L.positionRaw[0]||0))/r:L.positionRaw[0],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[1]||0)+(L.positionRaw[1]||0))/r:L.positionRaw[1],z.body[R].keypoints[K]?((r-1)*(z.body[R].keypoints[K].positionRaw[2]||0)+(L.positionRaw[2]||0))/r:L.positionRaw[2]],distance:[z.body[R].keypoints[K]?((r-1)*(((Ae=z.body[R].keypoints[K].distance)==null?void 0:Ae[0])||0)+(((se=L.distance)==null?void 0:se[0])||0))/r:(p2=L.distance)==null?void 0:p2[0],z.body[R].keypoints[K]?((r-1)*(((u2=z.body[R].keypoints[K].distance)==null?void 0:u2[1])||0)+(((qe=L.distance)==null?void 0:qe[1])||0))/r:(lt=L.distance)==null?void 0:lt[1],z.body[R].keypoints[K]?((r-1)*(((yt=z.body[R].keypoints[K].distance)==null?void 0:yt[2])||0)+(((xt=L.distance)==null?void 0:xt[2])||0))/r:(ct=L.distance)==null?void 0:ct[2]]}}),i0={},m0={connected:{}};(a=(s=t.body)==null?void 0:s.modelPath)!=null&&a.includes("efficientpose")?m0=e5:(x=(i=t.body)==null?void 0:i.modelPath)!=null&&x.includes("blazepose")?m0=K2:(l=(c=t.body)==null?void 0:c.modelPath)!=null&&l.includes("movenet")&&(m0=E2);for(let[L,K]of Object.entries(m0.connected)){let Ae=[];for(let se=0;se<K.length-1;se++){let p2=$.find(qe=>qe.part===K[se]),u2=$.find(qe=>qe.part===K[se+1]);p2&&u2&&Ae.push([p2.position,u2.position])}i0[L]=Ae}z.body[R]={...e.body[R],box:c0,boxRaw:k,keypoints:$,annotations:i0}}if(!z.hand||e.hand.length!==z.hand.length)z.hand=JSON.parse(JSON.stringify(e.hand));else for(let R=0;R<e.hand.length;R++){let c0=e.hand[R].box.map((m0,L)=>((r-1)*z.hand[R].box[L]+m0)/r),k=e.hand[R].boxRaw.map((m0,L)=>((r-1)*z.hand[R].boxRaw[L]+m0)/r);z.hand[R].keypoints.length!==e.hand[R].keypoints.length&&(z.hand[R].keypoints=e.hand[R].keypoints);let $=e.hand[R].keypoints&&e.hand[R].keypoints.length>0?e.hand[R].keypoints.map((m0,L)=>m0.map((K,Ae)=>((r-1)*(z.hand[R].keypoints[L][Ae]||1)+(K||0))/r)):[],i0={};if(Object.keys(z.hand[R].annotations).length!==Object.keys(e.hand[R].annotations).length)z.hand[R].annotations=e.hand[R].annotations,i0=z.hand[R].annotations;else if(e.hand[R].annotations)for(let m0 of Object.keys(e.hand[R].annotations))i0[m0]=e.hand[R].annotations[m0]&&e.hand[R].annotations[m0][0]?e.hand[R].annotations[m0].map((L,K)=>L.map((Ae,se)=>((r-1)*z.hand[R].annotations[m0][K][se]+Ae)/r)):null;z.hand[R]={...e.hand[R],box:c0,boxRaw:k,keypoints:$,annotations:i0}}if(!z.face||e.face.length!==z.face.length)z.face=JSON.parse(JSON.stringify(e.face));else for(let R=0;R<e.face.length;R++){let c0=e.face[R].box.map(($,i0)=>((r-1)*z.face[R].box[i0]+$)/r),k=e.face[R].boxRaw.map(($,i0)=>((r-1)*z.face[R].boxRaw[i0]+$)/r);if(e.face[R].rotation){let $={matrix:[0,0,0,0,0,0,0,0,0],angle:{roll:0,yaw:0,pitch:0},gaze:{bearing:0,strength:0}};$.matrix=(y=e.face[R].rotation)==null?void 0:y.matrix,$.angle={roll:((r-1)*(((u=(f=z.face[R].rotation)==null?void 0:f.angle)==null?void 0:u.roll)||0)+(((P=(m=e.face[R].rotation)==null?void 0:m.angle)==null?void 0:P.roll)||0))/r,yaw:((r-1)*(((b=(g=z.face[R].rotation)==null?void 0:g.angle)==null?void 0:b.yaw)||0)+(((M=(d=e.face[R].rotation)==null?void 0:d.angle)==null?void 0:M.yaw)||0))/r,pitch:((r-1)*(((w=(S=z.face[R].rotation)==null?void 0:S.angle)==null?void 0:w.pitch)||0)+(((C=(j=e.face[R].rotation)==null?void 0:j.angle)==null?void 0:C.pitch)||0))/r},$.gaze={bearing:((r-1)*(((H=(F=z.face[R].rotation)==null?void 0:F.gaze)==null?void 0:H.bearing)||0)+(((J=(Y=e.face[R].rotation)==null?void 0:Y.gaze)==null?void 0:J.bearing)||0))/r,strength:((r-1)*(((E=(x0=z.face[R].rotation)==null?void 0:x0.gaze)==null?void 0:E.strength)||0)+(((B0=(G0=e.face[R].rotation)==null?void 0:G0.gaze)==null?void 0:B0.strength)||0))/r},z.face[R]={...e.face[R],rotation:$,box:c0,boxRaw:k}}z.face[R]={...e.face[R],box:c0,boxRaw:k}}if(!z.object||e.object.length!==z.object.length)z.object=JSON.parse(JSON.stringify(e.object));else for(let R=0;R<e.object.length;R++){let c0=e.object[R].box.map(($,i0)=>((r-1)*z.object[R].box[i0]+$)/r),k=e.object[R].boxRaw.map(($,i0)=>((r-1)*z.object[R].boxRaw[i0]+$)/r);z.object[R]={...e.object[R],box:c0,boxRaw:k}}if(e.persons){let R=e.persons;if(!z.persons||R.length!==z.persons.length)z.persons=JSON.parse(JSON.stringify(R));else for(let c0=0;c0<R.length;c0++)z.persons[c0].box=R[c0].box.map((k,$)=>((r-1)*z.persons[c0].box[$]+k)/r)}e.gesture&&(z.gesture=e.gesture);let A=h();return rt=v.perfadd?rt+Math.round(A-o):Math.round(A-o),e.performance&&(z.performance={...e.performance,interpolate:rt}),z}var at={};ue(at,{distance:()=>I2,match:()=>st,similarity:()=>At});function I2(e,t,o={order:2,multiplier:25}){let n=0;for(let r=0;r<e.length;r++){let A=!o.order||o.order===2?e[r]-t[r]:Math.abs(e[r]-t[r]);n+=!o.order||o.order===2?A*A:A**o.order}return(o.multiplier||20)*n}var on=(e,t,o,n)=>{if(e===0)return 1;let r=t===2?Math.sqrt(e):e**(1/t),A=(1-r/100-o)/(n-o);return Math.max(Math.min(A,1),0)};function At(e,t,o={order:2,multiplier:25,min:.2,max:.8}){let n=I2(e,t,o);return on(n,o.order||2,o.min||0,o.max||1)}function st(e,t,o={order:2,multiplier:25,threshold:0,min:.2,max:.8}){if(!Array.isArray(e)||!Array.isArray(t)||e.length<64||t.length===0||e.length!==t[0].length)return{index:-1,distance:Number.POSITIVE_INFINITY,similarity:0};let n=Number.MAX_SAFE_INTEGER,r=-1;for(let s=0;s<t.length;s++){let a=I2(e,t[s],o);if(a<n&&(n=a,r=s),n<(o.threshold||0))break}let A=on(n,o.order||2,o.min||0,o.max||1);return{index:r,distance:n,similarity:A}}function nn(e,t,o,n,r){var a,i,x,c,l,y,f,u,m,P,g,b,d,M,S,w;let A=0,s=[];for(let j of e){let C={id:A++,face:j,body:null,hands:{left:null,right:null},gestures:[],box:[0,0,0,0]};for(let E of t)j.box[0]>E.box[0]&&j.box[0]<E.box[0]+E.box[2]&&j.box[1]+j.box[3]>E.box[1]&&j.box[1]+j.box[3]<E.box[1]+E.box[3]&&(C.body=E);if(C.body)for(let E of o)E.box[0]+E.box[2]>C.body.box[0]&&E.box[0]+E.box[2]<C.body.box[0]+C.body.box[2]&&E.box[1]+E.box[3]>C.body.box[1]&&E.box[1]+E.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.left=E),E.box[0]<C.body.box[0]+C.body.box[2]&&E.box[0]>C.body.box[0]&&E.box[1]+E.box[3]>C.body.box[1]&&E.box[1]+E.box[3]<C.body.box[1]+C.body.box[3]&&C.hands&&(C.hands.right=E);for(let E of n)E.face!==void 0&&E.face===j.id?(a=C.gestures)==null||a.push(E):E.iris!==void 0&&E.iris===j.id?(i=C.gestures)==null||i.push(E):E.body!==void 0&&E.body===((x=C.body)==null?void 0:x.id)?(c=C.gestures)==null||c.push(E):E.hand!==void 0&&E.hand===((y=(l=C.hands)==null?void 0:l.left)==null?void 0:y.id)?(f=C.gestures)==null||f.push(E):E.hand!==void 0&&E.hand===((m=(u=C.hands)==null?void 0:u.right)==null?void 0:m.id)&&((P=C.gestures)==null||P.push(E));let F=[],H=[],Y=E=>{E&&E.length===4&&(F.push(E[0],E[0]+E[2]),H.push(E[1],E[1]+E[3]))};Y((g=C.face)==null?void 0:g.box),Y((b=C.body)==null?void 0:b.box),Y((M=(d=C.hands)==null?void 0:d.left)==null?void 0:M.box),Y((w=(S=C.hands)==null?void 0:S.right)==null?void 0:w.box);let J=Math.min(...F),x0=Math.min(...H);C.box=[J,x0,Math.max(...F)-J,Math.max(...H)-x0],r&&r[1]&&r[2]&&(C.boxRaw=[C.box[0]/r[2],C.box[1]/r[1],C.box[2]/r[2],C.box[3]/r[1]]),s.push(C)}return s}var T5=`
 /9j/4AAQSkZJRgABAQEAYABgAAD/4QBoRXhpZgAATU0AKgAAAAgABAEaAAUAAAABAAAAPgEbAAUA
 AAABAAAARgEoAAMAAAABAAIAAAExAAIAAAARAAAATgAAAAAAAABgAAAAAQAAAGAAAAABcGFpbnQu
 bmV0IDQuMi4xMwAA/9sAQwAGBAUGBQQGBgUGBwcGCAoQCgoJCQoUDg8MEBcUGBgXFBYWGh0lHxob
@@ -827,4 +827,4 @@ AAAAAAJAAAAAAAAAAAAAABAJEAAAAAAAAAAAAAAAIEoBKAAAAAAAAAAAAAAABAlAAAAAAAIAAAAA
 BAkBAkBAkBAlACEgMZjdjbFW8bWrEx8YWANb6Fp+bfwab+vLDKMFK9qxH5L0bAr8OPRPKz2AY7J2
 SbAjYZAI2E7AIEgIEgIEgMdkSy2NgY7MdlmyNoBXsxmFuyNgVTVjNV3KjlBRNTlXTVHKCrlIqt5T
 lBhEMohlFerLlBjEMohMVTEARDKCITsAk2AEgAAAkAAAAAAAAAAAAAAAAAAAAAAAASAAAAAAAAD/
-2Q==`;var m0=Z(D());async function r7(e){let t=(r,A="application/octet-stream")=>fetch(`data:${A};base64,${r}`).then(s=>s.blob()),o,n;switch(e.config.warmup){case"face":o=await t(T5);break;case"body":case"full":o=await t(w5);break;default:o=null}if(o){let r=await createImageBitmap(o);n=await e.detect(r,e.config),r.close()}return n}async function A7(e){return new Promise(t=>{let o;switch(e.config.warmup){case"face":o="data:image/jpeg;base64,"+T5;break;case"full":case"body":o="data:image/jpeg;base64,"+w5;break;default:o=null}let n;if(typeof Image!="undefined")n=new Image;else if(v.Image)n=new v.Image;else return;n.onload=async()=>{let r=R0(n.naturalWidth,n.naturalHeight);if(!r)p("Warmup: Canvas not found"),t(void 0);else{let A=r.getContext("2d");A&&A.drawImage(n,0,0);let s=await e.image(r),a=await e.detect(s.tensor,e.config);t(a)}},o?n.src=o:t(void 0)})}async function s7(e){let t=r=>Buffer.from(r,"base64"),o;e.config.warmup==="face"?o=t(T5):o=t(w5);let n;if("node"in m0){let r=m0.node.decodeJpeg(o),A=r.expandDims(0);e.tf.dispose(r),n=await e.detect(A,e.config),e.tf.dispose(A)}else e.config.debug&&p("Warmup tfjs-node not loaded");return n}async function a7(e){let t;return typeof createImageBitmap=="function"?t=await r7(e):typeof Image!="undefined"||v.Canvas!==void 0?t=await A7(e):t=await s7(e),t}async function i7(e){let t=m0.getBackend(),o=m0.backend();if(t!=="webgl"&&t!=="humangl"||!o||!o.checkCompileCompletion)return;m0.env().set("ENGINE_COMPILE_ONLY",!0);let n=m0.engine().state.numTensors,r=[];for(let[a,i]of Object.entries(e).filter(([x,c])=>x!==null&&c!==null)){let x=i.inputs&&i.inputs[0]&&i.inputs[0].shape?[...i.inputs[0].shape]:[1,64,64,3],c=i.inputs&&i.inputs[0]&&i.inputs[0].dtype?i.inputs[0].dtype:"float32";for(let y=0;y<x.length;y++)x[y]===-1&&(x[y]=y===0?1:64);let l=m0.zeros(x,c);try{let y=i.execute(l);r.push(a),Array.isArray(y)?y.forEach(f=>m0.dispose(f)):m0.dispose(y)}catch(y){p("compile fail model:",a)}m0.dispose(l)}let A=await o.checkCompileCompletionAsync();o.getUniformLocations(),p("compile pass models:",r),p("compile pass kernels:",A.length),m0.env().set("ENGINE_COMPILE_ONLY",!1);let s=m0.engine().state.numTensors;s-n>0&&p("tensor leak:",s-n)}async function rn(e,t){let o=h();return e.state="warmup",t&&(e.config=r0(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?{face:[],body:[],hand:[],gesture:[],object:[],performance:e.performance,timestamp:h(),persons:[],error:null}:new Promise(async n=>{await i7(e.models);let r=await a7(e),A=h();e.config.debug&&p("warmup",e.config.warmup,Math.round(A-o),"ms"),e.emit("warmup"),n(r)})}var m2,I2,N2,k5,it=class{constructor(t){T(this,"version");T(this,"config");T(this,"result");T(this,"state");T(this,"process");T(this,"tf");T(this,"env");T(this,"draw");T(this,"models");T(this,"events");T(this,"faceTriangulation");T(this,"faceUVMap");T(this,"performance");g2(this,m2,void 0);g2(this,I2,void 0);g2(this,N2,void 0);T(this,"gl");T(this,"analyze",(...t)=>{if(!b2(this,I2))return;let o=this.tf.engine().state.numTensors,n=b2(this,m2);M2(this,m2,o);let r=o-n;r!==0&&p(...t,r)});g2(this,k5,t=>{if(!b2(this,N2))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof ee.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(o){return"backend not loaded"}return null});T(this,"similarity",At);T(this,"distance",j2);T(this,"match",st);T(this,"emit",t=>{var o;this.events&&this.events.dispatchEvent&&((o=this.events)==null||o.dispatchEvent(new Event(t)))});var n;this.env=v;let o=(((n=ee.version)==null?void 0:n.tfjs)||ee.version_core).replace(/-(.*)/,"");he.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${o}/dist/`,he.modelBasePath=v.browser?"../models/":"file://models/",he.backend=v.browser?"humangl":"tensorflow",this.version=O5,Object.defineProperty(this,"version",{value:O5}),this.config=JSON.parse(JSON.stringify(he)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=r0(this.config,t)),kt(this.config),this.tf=ee,this.state="idle",M2(this,m2,0),M2(this,I2,!1),M2(this,N2,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new C2,this.draw={options:P0,canvas:(r,A)=>$1(r,A),face:(r,A,s)=>l2(r,A,s),body:(r,A,s)=>y2(r,A,s),hand:(r,A,s)=>x2(r,A,s),gesture:(r,A,s)=>d2(r,A,s),object:(r,A,s)=>c2(r,A,s),person:(r,A,s)=>_1(r,A,s),all:(r,A,s)=>et(r,A,s)},this.result={face:[],body:[],hand:[],gesture:[],object:[],performance:{},timestamp:0,persons:[],error:null},this.process={tensor:null,canvas:null},this.faceTriangulation=B3,this.faceUVMap=H3,this.gl=t0,this.emit("create")}reset(){let t=this.config.backend;this.config=JSON.parse(JSON.stringify(he)),this.config.backend=t}validate(t){return E5(he,t||this.config)}now(){return h()}image(t,o=!0){return Ye(t,this.config,o)}async segmentation(t,o){return Do(t,o,this.config)}enhance(t){return u1(t)}compare(t,o){return wt(this.config,t,o)}async init(){await v5(this,!0),await this.tf.ready()}async load(t){this.state="load";let o=h(),n=Object.values(this.models).filter(s=>s).length;t&&(this.config=r0(this.config,t)),this.env.initial&&(this.config.debug&&p(`version: ${this.version}`),this.config.debug&&p(`tfjs version: ${this.tf.version["tfjs-core"]}`),await v5(this)||p("error: backend check failed"),await ee.ready(),this.env.browser&&(this.config.debug&&p("configuration:",this.config),this.config.debug&&p("environment:",this.env),this.config.debug&&p("tf flags:",this.tf.ENV.flags))),await U1(this),this.env.initial&&this.config.debug&&p("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.env.initial=!1,Object.values(this.models).filter(s=>s).length!==n&&(await Y1(this),this.emit("load"));let A=Math.trunc(h()-o);A>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+A:A)}next(t=this.result){return tn(t,this.config)}getModelStats(){return q1(this)}async warmup(t){let o=h(),n=await rn(this,t),r=h();return this.performance.warmup=Math.trunc(r-o),n}async profile(t,o){let n=await this.tf.profile(()=>this.detect(t,o)),r={};for(let a of n.kernels)r[a.name]?r[a.name]+=a.kernelTimeMs:r[a.name]=a.kernelTimeMs;let A=[];Object.entries(r).forEach(a=>A.push({name:a[0],ms:a[1]})),A.sort((a,i)=>i.ms-a.ms),A.length=20;let s={};for(let a of A)s[a.name]=a.ms;return s}async detect(t,o){return this.state="detect",new Promise(async n=>{var P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0,R,c0,k,$,a0;this.state="config";let r;this.config=r0(this.config,o),this.state="check";let A=b2(this,k5).call(this,t);A&&(p(A,t),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:h(),persons:[],error:A}));let s=h();await v5(this),await this.load(),r=h(),this.state="image";let a=await Ye(t,this.config);if(this.process=a,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(h()-r):Math.trunc(h()-r),this.analyze("Get Image:"),!a.tensor){this.config.debug&&p("could not convert input to tensor"),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:h(),persons:[],error:"could not convert input to tensor"});return}this.emit("image"),r=h(),this.config.skipAllowed=await Tt(this.config,a.tensor),this.performance.totalFrames||(this.performance.totalFrames=0),this.performance.cachedFrames||(this.performance.cachedFrames=0),this.performance.totalFrames++,this.config.skipAllowed&&this.performance.cachedFrames++,this.performance.cacheCheck=this.env.perfadd?(this.performance.cacheCheck||0)+Math.trunc(h()-r):Math.trunc(h()-r),this.analyze("Check Changed:");let i=[],x=[],c=[],l=[];this.state="detect:face",this.config.async?(i=this.config.face.enabled?nt(this,a.tensor):[],this.performance.face&&delete this.performance.face):(r=h(),i=this.config.face.enabled?await nt(this,a.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.config.async&&(this.config.body.maxDetected===-1||this.config.hand.maxDetected===-1)&&(i=await i),this.analyze("Start Body:"),this.state="detect:body";let y=this.config.body.maxDetected===-1?r0(this.config,{body:{maxDetected:this.config.face.enabled?1*i.length:1}}):this.config;this.config.async?((P=this.config.body.modelPath)!=null&&P.includes("posenet")?x=this.config.body.enabled?D1(a.tensor,y):[]:(g=this.config.body.modelPath)!=null&&g.includes("blazepose")?x=this.config.body.enabled?t1(a.tensor,y):[]:(b=this.config.body.modelPath)!=null&&b.includes("efficientpose")?x=this.config.body.enabled?i1(a.tensor,y):[]:(d=this.config.body.modelPath)!=null&&d.includes("movenet")&&(x=this.config.body.enabled?L1(a.tensor,y):[]),this.performance.body&&delete this.performance.body):(r=h(),(M=this.config.body.modelPath)!=null&&M.includes("posenet")?x=this.config.body.enabled?await D1(a.tensor,y):[]:(S=this.config.body.modelPath)!=null&&S.includes("blazepose")?x=this.config.body.enabled?await t1(a.tensor,y):[]:(w=this.config.body.modelPath)!=null&&w.includes("efficientpose")?x=this.config.body.enabled?await i1(a.tensor,y):[]:(j=this.config.body.modelPath)!=null&&j.includes("movenet")&&(x=this.config.body.enabled?await L1(a.tensor,y):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let f=this.config.hand.maxDetected===-1?r0(this.config,{hand:{maxDetected:this.config.face.enabled?2*i.length:1}}):this.config;this.config.async?((F=(C=this.config.hand.detector)==null?void 0:C.modelPath)!=null&&F.includes("handdetect")?c=this.config.hand.enabled?v1(a.tensor,f):[]:(Y=(H=this.config.hand.detector)==null?void 0:H.modelPath)!=null&&Y.includes("handtrack")&&(c=this.config.hand.enabled?E1(a.tensor,f):[]),this.performance.hand&&delete this.performance.hand):(r=h(),(x0=(J=this.config.hand.detector)==null?void 0:J.modelPath)!=null&&x0.includes("handdetect")?c=this.config.hand.enabled?await v1(a.tensor,f):[]:(G0=(E=this.config.hand.detector)==null?void 0:E.modelPath)!=null&&G0.includes("handtrack")&&(c=this.config.hand.enabled?await E1(a.tensor,f):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?((B0=this.config.object.modelPath)!=null&&B0.includes("nanodet")?l=this.config.object.enabled?F1(a.tensor,this.config):[]:(R=this.config.object.modelPath)!=null&&R.includes("centernet")&&(l=this.config.object.enabled?r1(a.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=h(),(c0=this.config.object.modelPath)!=null&&c0.includes("nanodet")?l=this.config.object.enabled?await F1(a.tensor,this.config):[]:(k=this.config.object.modelPath)!=null&&k.includes("centernet")&&(l=this.config.object.enabled?await r1(a.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([i,x,c,l]=await Promise.all([i,x,c,l])),this.state="detect:gesture";let u=[];this.config.gesture.enabled&&(r=h(),u=[..._o(i),...Qo(x),...en(c),...$o(i)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(h()-s):Math.trunc(h()-s);let m=((a0=($=this.process)==null?void 0:$.tensor)==null?void 0:a0.shape)||[];this.result={face:i,body:x,hand:c,gesture:u,object:l,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,get persons(){return nn(i,x,c,u,m)}},ee.dispose(a.tensor),this.emit("detect"),this.state="idle",n(this.result)})}};m2=new WeakMap,I2=new WeakMap,N2=new WeakMap,k5=new WeakMap;0&&(module.exports={Human,defaults,draw,env,match,models});
+2Q==`;var f0=Z(D());async function r7(e){let t=(r,A="application/octet-stream")=>fetch(`data:${A};base64,${r}`).then(s=>s.blob()),o,n;switch(e.config.warmup){case"face":o=await t(T5);break;case"body":case"full":o=await t(w5);break;default:o=null}if(o){let r=await createImageBitmap(o);n=await e.detect(r,e.config),r.close()}return n}async function A7(e){return new Promise(t=>{let o;switch(e.config.warmup){case"face":o="data:image/jpeg;base64,"+T5;break;case"full":case"body":o="data:image/jpeg;base64,"+w5;break;default:o=null}let n;if(typeof Image!="undefined")n=new Image;else if(v.Image)n=new v.Image;else return;n.onload=async()=>{let r=R0(n.naturalWidth,n.naturalHeight);if(!r)p("Warmup: Canvas not found"),t(void 0);else{let A=r.getContext("2d");A&&A.drawImage(n,0,0);let s=await e.image(r),a=await e.detect(s.tensor,e.config);t(a)}},o?n.src=o:t(void 0)})}async function s7(e){let t=r=>Buffer.from(r,"base64"),o;e.config.warmup==="face"?o=t(T5):o=t(w5);let n;if("node"in f0){let r=f0.node.decodeJpeg(o),A=r.expandDims(0);e.tf.dispose(r),n=await e.detect(A,e.config),e.tf.dispose(A)}else e.config.debug&&p("Warmup tfjs-node not loaded");return n}async function a7(e){let t;return typeof createImageBitmap=="function"?t=await r7(e):typeof Image!="undefined"||v.Canvas!==void 0?t=await A7(e):t=await s7(e),t}async function i7(e){if(!f0.env().flagRegistry.ENGINE_COMPILE_ONLY)return;let t=f0.getBackend(),o=f0.backend();if(t!=="webgl"&&t!=="humangl"||!o||!o.checkCompileCompletion)return;f0.env().set("ENGINE_COMPILE_ONLY",!0);let n=f0.engine().state.numTensors,r=[];for(let[a,i]of Object.entries(e).filter(([x,c])=>x!==null&&c!==null)){let x=i.inputs&&i.inputs[0]&&i.inputs[0].shape?[...i.inputs[0].shape]:[1,64,64,3],c=i.inputs&&i.inputs[0]&&i.inputs[0].dtype?i.inputs[0].dtype:"float32";for(let y=0;y<x.length;y++)x[y]===-1&&(x[y]=y===0?1:64);let l=f0.zeros(x,c);try{let y=i.execute(l);r.push(a),Array.isArray(y)?y.forEach(f=>f0.dispose(f)):f0.dispose(y)}catch(y){p("compile fail model:",a)}f0.dispose(l)}let A=await o.checkCompileCompletionAsync();o.getUniformLocations(),p("compile pass models:",r),p("compile pass kernels:",A.length),f0.env().set("ENGINE_COMPILE_ONLY",!1);let s=f0.engine().state.numTensors;s-n>0&&p("tensor leak:",s-n)}async function rn(e,t){let o=h();return e.state="warmup",t&&(e.config=r0(e.config,t)),!e.config.warmup||e.config.warmup.length===0||e.config.warmup==="none"?{face:[],body:[],hand:[],gesture:[],object:[],performance:e.performance,timestamp:h(),persons:[],error:null}:new Promise(async n=>{await i7(e.models);let r=await a7(e),A=h();e.config.debug&&p("warmup",e.config.warmup,Math.round(A-o),"ms"),e.emit("warmup"),n(r)})}var m2,j2,O2,k5,it=class{constructor(t){T(this,"version");T(this,"config");T(this,"result");T(this,"state");T(this,"process");T(this,"tf");T(this,"env");T(this,"draw");T(this,"models");T(this,"events");T(this,"faceTriangulation");T(this,"faceUVMap");T(this,"performance");g2(this,m2,void 0);g2(this,j2,void 0);g2(this,O2,void 0);T(this,"gl");T(this,"analyze",(...t)=>{if(!b2(this,j2))return;let o=this.tf.engine().state.numTensors,n=b2(this,m2);M2(this,m2,o);let r=o-n;r!==0&&p(...t,r)});g2(this,k5,t=>{if(!b2(this,O2))return null;if(!t)return"input is not defined";if(this.env.node&&!(t instanceof ee.Tensor))return"input must be a tensor";try{this.tf.getBackend()}catch(o){return"backend not loaded"}return null});T(this,"similarity",At);T(this,"distance",I2);T(this,"match",st);T(this,"emit",t=>{var o;this.events&&this.events.dispatchEvent&&((o=this.events)==null||o.dispatchEvent(new Event(t)))});var n;this.env=v;let o=(((n=ee.version)==null?void 0:n.tfjs)||ee.version_core).replace(/-(.*)/,"");he.wasmPath=`https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-wasm@${o}/dist/`,he.modelBasePath=v.browser?"../models/":"file://models/",he.backend=v.browser?"humangl":"tensorflow",this.version=N5,Object.defineProperty(this,"version",{value:N5}),this.config=JSON.parse(JSON.stringify(he)),Object.seal(this.config),this.config.cacheModels=typeof indexedDB!="undefined",t&&(this.config=r0(this.config,t)),kt(this.config),this.tf=ee,this.state="idle",M2(this,m2,0),M2(this,j2,!1),M2(this,O2,!1),this.performance={},this.events=typeof EventTarget!="undefined"?new EventTarget:void 0,this.models=new C2,this.draw={options:P0,canvas:(r,A)=>$1(r,A),face:(r,A,s)=>l2(r,A,s),body:(r,A,s)=>y2(r,A,s),hand:(r,A,s)=>x2(r,A,s),gesture:(r,A,s)=>d2(r,A,s),object:(r,A,s)=>c2(r,A,s),person:(r,A,s)=>_1(r,A,s),all:(r,A,s)=>et(r,A,s)},this.result={face:[],body:[],hand:[],gesture:[],object:[],performance:{},timestamp:0,persons:[],error:null},this.process={tensor:null,canvas:null},this.faceTriangulation=B3,this.faceUVMap=H3,this.gl=t0,this.emit("create")}reset(){let t=this.config.backend;this.config=JSON.parse(JSON.stringify(he)),this.config.backend=t}validate(t){return E5(he,t||this.config)}now(){return h()}image(t,o=!0){return Ye(t,this.config,o)}async segmentation(t,o){return Do(t,o,this.config)}enhance(t){return u1(t)}compare(t,o){return wt(this.config,t,o)}async init(){await v5(this,!0),await this.tf.ready()}async load(t){this.state="load";let o=h(),n=Object.values(this.models).filter(s=>s).length;t&&(this.config=r0(this.config,t)),this.env.initial&&(this.config.debug&&p(`version: ${this.version}`),this.config.debug&&p(`tfjs version: ${this.tf.version["tfjs-core"]}`),await v5(this)||p("error: backend check failed"),await ee.ready(),this.env.browser&&(this.config.debug&&p("configuration:",this.config),this.config.debug&&p("environment:",this.env),this.config.debug&&p("tf flags:",this.tf.ENV.flags))),await U1(this),this.env.initial&&this.config.debug&&p("tf engine state:",this.tf.engine().state.numBytes,"bytes",this.tf.engine().state.numTensors,"tensors"),this.env.initial=!1,Object.values(this.models).filter(s=>s).length!==n&&(await Y1(this),this.emit("load"));let A=Math.trunc(h()-o);A>(this.performance.loadModels||0)&&(this.performance.loadModels=this.env.perfadd?(this.performance.loadModels||0)+A:A)}next(t=this.result){return tn(t,this.config)}getModelStats(){return q1(this)}async warmup(t){let o=h(),n=await rn(this,t),r=h();return this.performance.warmup=Math.trunc(r-o),n}async profile(t,o){let n=await this.tf.profile(()=>this.detect(t,o)),r={},A=0;for(let a of n.kernels)r[a.name]?r[a.name]+=a.kernelTimeMs:r[a.name]=a.kernelTimeMs,A+=a.kernelTimeMs;let s=[];Object.entries(r).forEach(a=>s.push({kernel:a[0],time:a[1],perc:0}));for(let a of s)a.perc=Math.round(1e3*a.time/A)/1e3,a.time=Math.round(1e3*a.time)/1e3;return s.sort((a,i)=>i.time-a.time),s.length=20,s}async detect(t,o){return this.state="detect",new Promise(async n=>{var P,g,b,d,M,S,w,j,C,F,H,Y,J,x0,E,G0,B0,R,c0,k,$,i0;this.state="config";let r;this.config=r0(this.config,o),this.state="check";let A=b2(this,k5).call(this,t);A&&(p(A,t),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:h(),persons:[],error:A}));let s=h();await v5(this),await this.load(),r=h(),this.state="image";let a=await Ye(t,this.config);if(this.process=a,this.performance.inputProcess=this.env.perfadd?(this.performance.inputProcess||0)+Math.trunc(h()-r):Math.trunc(h()-r),this.analyze("Get Image:"),!a.tensor){this.config.debug&&p("could not convert input to tensor"),this.emit("error"),n({face:[],body:[],hand:[],gesture:[],object:[],performance:this.performance,timestamp:h(),persons:[],error:"could not convert input to tensor"});return}this.emit("image"),r=h(),this.config.skipAllowed=await Tt(this.config,a.tensor),this.performance.totalFrames||(this.performance.totalFrames=0),this.performance.cachedFrames||(this.performance.cachedFrames=0),this.performance.totalFrames++,this.config.skipAllowed&&this.performance.cachedFrames++,this.performance.cacheCheck=this.env.perfadd?(this.performance.cacheCheck||0)+Math.trunc(h()-r):Math.trunc(h()-r),this.analyze("Check Changed:");let i=[],x=[],c=[],l=[];this.state="detect:face",this.config.async?(i=this.config.face.enabled?nt(this,a.tensor):[],this.performance.face&&delete this.performance.face):(r=h(),i=this.config.face.enabled?await nt(this,a.tensor):[],this.performance.face=this.env.perfadd?(this.performance.face||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.config.async&&(this.config.body.maxDetected===-1||this.config.hand.maxDetected===-1)&&(i=await i),this.analyze("Start Body:"),this.state="detect:body";let y=this.config.body.maxDetected===-1?r0(this.config,{body:{maxDetected:this.config.face.enabled?1*i.length:1}}):this.config;this.config.async?((P=this.config.body.modelPath)!=null&&P.includes("posenet")?x=this.config.body.enabled?D1(a.tensor,y):[]:(g=this.config.body.modelPath)!=null&&g.includes("blazepose")?x=this.config.body.enabled?t1(a.tensor,y):[]:(b=this.config.body.modelPath)!=null&&b.includes("efficientpose")?x=this.config.body.enabled?i1(a.tensor,y):[]:(d=this.config.body.modelPath)!=null&&d.includes("movenet")&&(x=this.config.body.enabled?L1(a.tensor,y):[]),this.performance.body&&delete this.performance.body):(r=h(),(M=this.config.body.modelPath)!=null&&M.includes("posenet")?x=this.config.body.enabled?await D1(a.tensor,y):[]:(S=this.config.body.modelPath)!=null&&S.includes("blazepose")?x=this.config.body.enabled?await t1(a.tensor,y):[]:(w=this.config.body.modelPath)!=null&&w.includes("efficientpose")?x=this.config.body.enabled?await i1(a.tensor,y):[]:(j=this.config.body.modelPath)!=null&&j.includes("movenet")&&(x=this.config.body.enabled?await L1(a.tensor,y):[]),this.performance.body=this.env.perfadd?(this.performance.body||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Body:"),this.analyze("Start Hand:"),this.state="detect:hand";let f=this.config.hand.maxDetected===-1?r0(this.config,{hand:{maxDetected:this.config.face.enabled?2*i.length:1}}):this.config;this.config.async?((F=(C=this.config.hand.detector)==null?void 0:C.modelPath)!=null&&F.includes("handdetect")?c=this.config.hand.enabled?v1(a.tensor,f):[]:(Y=(H=this.config.hand.detector)==null?void 0:H.modelPath)!=null&&Y.includes("handtrack")&&(c=this.config.hand.enabled?E1(a.tensor,f):[]),this.performance.hand&&delete this.performance.hand):(r=h(),(x0=(J=this.config.hand.detector)==null?void 0:J.modelPath)!=null&&x0.includes("handdetect")?c=this.config.hand.enabled?await v1(a.tensor,f):[]:(G0=(E=this.config.hand.detector)==null?void 0:E.modelPath)!=null&&G0.includes("handtrack")&&(c=this.config.hand.enabled?await E1(a.tensor,f):[]),this.performance.hand=this.env.perfadd?(this.performance.hand||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Hand:"),this.analyze("Start Object:"),this.state="detect:object",this.config.async?((B0=this.config.object.modelPath)!=null&&B0.includes("nanodet")?l=this.config.object.enabled?F1(a.tensor,this.config):[]:(R=this.config.object.modelPath)!=null&&R.includes("centernet")&&(l=this.config.object.enabled?r1(a.tensor,this.config):[]),this.performance.object&&delete this.performance.object):(r=h(),(c0=this.config.object.modelPath)!=null&&c0.includes("nanodet")?l=this.config.object.enabled?await F1(a.tensor,this.config):[]:(k=this.config.object.modelPath)!=null&&k.includes("centernet")&&(l=this.config.object.enabled?await r1(a.tensor,this.config):[]),this.performance.object=this.env.perfadd?(this.performance.object||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.analyze("End Object:"),this.state="detect:await",this.config.async&&([i,x,c,l]=await Promise.all([i,x,c,l])),this.state="detect:gesture";let u=[];this.config.gesture.enabled&&(r=h(),u=[..._o(i),...Qo(x),...en(c),...$o(i)],this.config.async?this.performance.gesture&&delete this.performance.gesture:this.performance.gesture=this.env.perfadd?(this.performance.gesture||0)+Math.trunc(h()-r):Math.trunc(h()-r)),this.performance.total=this.env.perfadd?(this.performance.total||0)+Math.trunc(h()-s):Math.trunc(h()-s);let m=((i0=($=this.process)==null?void 0:$.tensor)==null?void 0:i0.shape)||[];this.result={face:i,body:x,hand:c,gesture:u,object:l,performance:this.performance,canvas:this.process.canvas,timestamp:Date.now(),error:null,get persons(){return nn(i,x,c,u,m)}},ee.dispose(a.tensor),this.emit("detect"),this.state="idle",n(this.result)})}};m2=new WeakMap,j2=new WeakMap,O2=new WeakMap,k5=new WeakMap;0&&(module.exports={Human,defaults,draw,env,match,models});
diff --git a/package.json b/package.json
index 092bf647..0ae4e747 100644
--- a/package.json
+++ b/package.json
@@ -55,11 +55,11 @@
   ],
   "optionalDependencies": {
     "canvas": "^2.9.3",
-    "node-fetch": "^3.2.9",
+    "node-fetch": "^3.2.10",
     "node-webcam": "^0.8.1"
   },
   "devDependencies": {
-    "@microsoft/api-extractor": "^7.28.6",
+    "@microsoft/api-extractor": "^7.29.0",
     "@tensorflow/tfjs": "^3.19.0",
     "@tensorflow/tfjs-backend-cpu": "^3.19.0",
     "@tensorflow/tfjs-backend-wasm": "^3.19.0",
@@ -72,15 +72,16 @@
     "@tensorflow/tfjs-node": "^3.19.0",
     "@tensorflow/tfjs-node-gpu": "^3.19.0",
     "@tensorflow/tfjs-tflite": "0.0.1-alpha.8",
-    "@types/node": "^18.6.2",
+    "@types/node": "^18.6.3",
     "@types/offscreencanvas": "^2019.7.0",
-    "@typescript-eslint/eslint-plugin": "^5.31.0",
-    "@typescript-eslint/parser": "^5.31.0",
+    "@typescript-eslint/eslint-plugin": "^5.32.0",
+    "@typescript-eslint/parser": "^5.32.0",
     "@vladmandic/build": "^0.7.8",
     "@vladmandic/pilogger": "^0.4.5",
     "@vladmandic/tfjs": "github:vladmandic/tfjs",
-    "esbuild": "^0.14.51",
-    "eslint": "8.20.0",
+    "@webgpu/types": "^0.1.21",
+    "esbuild": "^0.14.53",
+    "eslint": "8.21.0",
     "eslint-config-airbnb-base": "^15.0.0",
     "eslint-plugin-html": "^7.1.0",
     "eslint-plugin-import": "^2.26.0",
@@ -90,7 +91,7 @@
     "rimraf": "^3.0.2",
     "seedrandom": "^3.0.5",
     "tslib": "^2.4.0",
-    "typedoc": "0.23.9",
+    "typedoc": "0.23.10",
     "typescript": "4.7.4"
   }
 }
diff --git a/src/human.ts b/src/human.ts
index 2873e276..d27e9cff 100644
--- a/src/human.ts
+++ b/src/human.ts
@@ -350,20 +350,24 @@ export class Human {
    * - result object will contain total exeuction time information for top-20 kernels
    * - actual detection object can be accessed via `human.result`
   */
-  async profile(input: Input, userConfig?: Partial<Config>): Promise<Record<string, number>> {
+  async profile(input: Input, userConfig?: Partial<Config>): Promise<Array<{ kernel: string, time: number, perc: number }>> {
     const profile = await this.tf.profile(() => this.detect(input, userConfig));
     const kernels: Record<string, number> = {};
+    let total = 0;
     for (const kernel of profile.kernels) { // sum kernel time values per kernel
       if (kernels[kernel.name]) kernels[kernel.name] += kernel.kernelTimeMs;
       else kernels[kernel.name] = kernel.kernelTimeMs;
+      total += kernel.kernelTimeMs;
     }
-    const kernelArr: Array<{ name: string, ms: number }> = [];
-    Object.entries(kernels).forEach((key) => kernelArr.push({ name: key[0], ms: key[1] as unknown as number })); // convert to array
-    kernelArr.sort((a, b) => b.ms - a.ms); // sort
+    const kernelArr: Array<{ kernel: string, time: number, perc: number }> = [];
+    Object.entries(kernels).forEach((key) => kernelArr.push({ kernel: key[0], time: key[1] as unknown as number, perc: 0 })); // convert to array
+    for (const kernel of kernelArr) {
+      kernel.perc = Math.round(1000 * kernel.time / total) / 1000;
+      kernel.time = Math.round(1000 * kernel.time) / 1000;
+    }
+    kernelArr.sort((a, b) => b.time - a.time); // sort
     kernelArr.length = 20; // crop
-    const res: Record<string, number> = {};
-    for (const kernel of kernelArr) res[kernel.name] = kernel.ms; // create perf objects
-    return res;
+    return kernelArr;
   }
 
   /** Main detection method
diff --git a/src/tfjs/backend.ts b/src/tfjs/backend.ts
index 1b9421ad..908ea234 100644
--- a/src/tfjs/backend.ts
+++ b/src/tfjs/backend.ts
@@ -86,9 +86,7 @@ export async function check(instance: Human, force = false) {
 
       // customize wasm
       if (instance.config.backend === 'wasm') {
-        try {
-          tf.env().set('CANVAS2D_WILL_READ_FREQUENTLY', true);
-        } catch { /**/ }
+        if (tf.env().flagRegistry['CANVAS2D_WILL_READ_FREQUENTLY']) tf.env().set('CANVAS2D_WILL_READ_FREQUENTLY', true);
         if (instance.config.debug) log('wasm path:', instance.config.wasmPath);
         if (typeof tf?.setWasmPaths !== 'undefined') await tf.setWasmPaths(instance.config.wasmPath, instance.config.wasmPlatformFetch);
         else throw new Error('backend error: attempting to use wasm backend but wasm path is not set');
@@ -110,15 +108,17 @@ export async function check(instance: Human, force = false) {
 
     // customize humangl
     if (tf.getBackend() === 'humangl') {
-      tf.ENV.set('CHECK_COMPUTATION_FOR_ERRORS', false);
-      tf.ENV.set('WEBGL_CPU_FORWARD', true);
-      // tf.ENV.set('WEBGL_PACK_DEPTHWISECONV', false);
-      tf.ENV.set('WEBGL_USE_SHAPES_UNIFORMS', true);
-      tf.ENV.set('CPU_HANDOFF_SIZE_THRESHOLD', 256);
-      // if (!instance.config.object.enabled) tf.ENV.set('WEBGL_FORCE_F16_TEXTURES', true); // safe to use 16bit precision
+      if (tf.env().flagRegistry['CHECK_COMPUTATION_FOR_ERRORS']) tf.env().set('CHECK_COMPUTATION_FOR_ERRORS', false);
+      if (tf.env().flagRegistry['WEBGL_CPU_FORWARD']) tf.env().set('WEBGL_CPU_FORWARD', true);
+      if (tf.env().flagRegistry['WEBGL_USE_SHAPES_UNIFORMS']) tf.env().set('WEBGL_USE_SHAPES_UNIFORMS', true);
+      if (tf.env().flagRegistry['CPU_HANDOFF_SIZE_THRESHOLD']) tf.env().set('CPU_HANDOFF_SIZE_THRESHOLD', 256);
+      if (tf.env().flagRegistry['WEBGL_EXP_CONV']) tf.env().set('WEBGL_EXP_CONV', true); // <https://github.com/tensorflow/tfjs/issues/6678>
+      if (tf.env().flagRegistry['USE_SETTIMEOUTWPM']) tf.env().set('USE_SETTIMEOUTWPM', true); // <https://github.com/tensorflow/tfjs/issues/6687>
+      // if (tf.env().flagRegistry['WEBGL_PACK_DEPTHWISECONV'])  tf.env().set('WEBGL_PACK_DEPTHWISECONV', false);
+      // if (if (tf.env().flagRegistry['WEBGL_FORCE_F16_TEXTURES']) && !instance.config.object.enabled) tf.env().set('WEBGL_FORCE_F16_TEXTURES', true); // safe to use 16bit precision
       if (typeof instance.config['deallocate'] !== 'undefined' && instance.config['deallocate']) { // hidden param
         log('changing webgl: WEBGL_DELETE_TEXTURE_THRESHOLD:', true);
-        tf.ENV.set('WEBGL_DELETE_TEXTURE_THRESHOLD', 0);
+        tf.env().set('WEBGL_DELETE_TEXTURE_THRESHOLD', 0);
       }
       if (tf.backend().getGPGPUContext) {
         const gl = await tf.backend().getGPGPUContext().gl;
@@ -128,9 +128,9 @@ export async function check(instance: Human, force = false) {
 
     // customize webgpu
     if (tf.getBackend() === 'webgpu') {
-      // tf.ENV.set('WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD', 512);
-      // tf.ENV.set('WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE', 0);
-      // tf.ENV.set('WEBGPU_CPU_FORWARD', true);
+      // if (tf.env().flagRegistry['WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD']) tf.env().set('WEBGPU_CPU_HANDOFF_SIZE_THRESHOLD', 512);
+      // if (tf.env().flagRegistry['WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE']) tf.env().set('WEBGPU_DEFERRED_SUBMIT_BATCH_SIZE', 0);
+      // if (tf.env().flagRegistry['WEBGPU_CPU_FORWARD']) tf.env().set('WEBGPU_CPU_FORWARD', true);
     }
 
     // wait for ready
diff --git a/src/tfjs/humangl.ts b/src/tfjs/humangl.ts
index 912d27fb..3757b70e 100644
--- a/src/tfjs/humangl.ts
+++ b/src/tfjs/humangl.ts
@@ -123,7 +123,7 @@ export async function register(instance: Human): Promise<void> {
       return;
     }
     try {
-      tf.ENV.set('WEBGL_VERSION', 2);
+      if (tf.env().flagRegistry['WEBGL_VERSION']) tf.env().set('WEBGL_VERSION', 2);
     } catch (err) {
       log('error: cannot set WebGL backend flags:', err);
       return;
diff --git a/src/warmup.ts b/src/warmup.ts
index 9ad08bd7..c01cfe37 100644
--- a/src/warmup.ts
+++ b/src/warmup.ts
@@ -109,6 +109,7 @@ async function runInference(instance: Human) {
 
 /** Runs pre-compile on all loaded models */
 export async function runCompile(allModels: Models) {
+  if (!tf.env().flagRegistry['ENGINE_COMPILE_ONLY']) return; // tfjs does not support compile-only inference
   const backendType = tf.getBackend();
   const webGLBackend = tf.backend();
   if ((backendType !== 'webgl' && backendType !== 'humangl') || (!webGLBackend || !webGLBackend.checkCompileCompletion)) {
diff --git a/test/build.log b/test/build.log
index b90a0546..efeb664e 100644
--- a/test/build.log
+++ b/test/build.log
@@ -1,24 +1,24 @@
-2022-07-29 09:21:22 INFO:  Application: {"name":"@vladmandic/human","version":"2.9.1"} 
-2022-07-29 09:21:22 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true} 
-2022-07-29 09:21:22 INFO:  Toolchain: {"build":"0.7.8","esbuild":"0.14.51","typescript":"4.7.4","typedoc":"0.23.9","eslint":"8.20.0"} 
-2022-07-29 09:21:22 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]} 
-2022-07-29 09:21:22 STATE: Clean: {"locations":["dist/*","types/lib/*","typedoc/*"]} 
-2022-07-29 09:21:22 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":102,"outputBytes":608} 
-2022-07-29 09:21:22 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":74,"inputBytes":647939,"outputBytes":303804} 
-2022-07-29 09:21:22 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":110,"outputBytes":612} 
-2022-07-29 09:21:22 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":74,"inputBytes":647943,"outputBytes":303808} 
-2022-07-29 09:21:22 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":149,"outputBytes":664} 
-2022-07-29 09:21:22 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":74,"inputBytes":647995,"outputBytes":303858} 
-2022-07-29 09:21:22 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1069,"outputBytes":358} 
-2022-07-29 09:21:22 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1032,"outputBytes":583} 
-2022-07-29 09:21:22 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":74,"inputBytes":647914,"outputBytes":302683} 
-2022-07-29 09:21:22 STATE: Compile: {"name":"tfjs/browser/esm/custom","format":"esm","platform":"browser","input":"tfjs/tf-custom.ts","output":"dist/tfjs.esm.js","files":11,"inputBytes":1271,"outputBytes":2787569} 
-2022-07-29 09:21:22 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":74,"inputBytes":3434900,"outputBytes":1665591} 
-2022-07-29 09:21:22 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":74,"inputBytes":3434900,"outputBytes":3066202} 
-2022-07-29 09:21:29 STATE: Typings: {"input":"src/human.ts","output":"types/lib","files":30} 
-2022-07-29 09:21:31 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":76,"generated":true} 
-2022-07-29 09:21:31 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":6414,"outputBytes":2878} 
-2022-07-29 09:21:31 STATE: Compile: {"name":"demo/faceid","format":"esm","platform":"browser","input":"demo/faceid/index.ts","output":"demo/faceid/index.js","files":2,"inputBytes":15174,"outputBytes":7604} 
-2022-07-29 09:21:40 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":107,"errors":0,"warnings":0} 
-2022-07-29 09:21:40 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"} 
-2022-07-29 09:21:40 INFO:  Done... 
+2022-08-04 09:11:15 INFO:  Application: {"name":"@vladmandic/human","version":"2.9.1"} 
+2022-08-04 09:11:15 INFO:  Environment: {"profile":"production","config":".build.json","package":"package.json","tsconfig":true,"eslintrc":true,"git":true} 
+2022-08-04 09:11:15 INFO:  Toolchain: {"build":"0.7.8","esbuild":"0.14.53","typescript":"4.7.4","typedoc":"0.23.10","eslint":"8.21.0"} 
+2022-08-04 09:11:15 INFO:  Build: {"profile":"production","steps":["clean","compile","typings","typedoc","lint","changelog"]} 
+2022-08-04 09:11:15 STATE: Clean: {"locations":["dist/*","types/lib/*","typedoc/*"]} 
+2022-08-04 09:11:15 STATE: Compile: {"name":"tfjs/nodejs/cpu","format":"cjs","platform":"node","input":"tfjs/tf-node.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":102,"outputBytes":608} 
+2022-08-04 09:11:15 STATE: Compile: {"name":"human/nodejs/cpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node.js","files":74,"inputBytes":649269,"outputBytes":304361} 
+2022-08-04 09:11:15 STATE: Compile: {"name":"tfjs/nodejs/gpu","format":"cjs","platform":"node","input":"tfjs/tf-node-gpu.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":110,"outputBytes":612} 
+2022-08-04 09:11:15 STATE: Compile: {"name":"human/nodejs/gpu","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-gpu.js","files":74,"inputBytes":649273,"outputBytes":304365} 
+2022-08-04 09:11:15 STATE: Compile: {"name":"tfjs/nodejs/wasm","format":"cjs","platform":"node","input":"tfjs/tf-node-wasm.ts","output":"dist/tfjs.esm.js","files":1,"inputBytes":149,"outputBytes":664} 
+2022-08-04 09:11:15 STATE: Compile: {"name":"human/nodejs/wasm","format":"cjs","platform":"node","input":"src/human.ts","output":"dist/human.node-wasm.js","files":74,"inputBytes":649325,"outputBytes":304415} 
+2022-08-04 09:11:15 STATE: Compile: {"name":"tfjs/browser/version","format":"esm","platform":"browser","input":"tfjs/tf-version.ts","output":"dist/tfjs.version.js","files":1,"inputBytes":1069,"outputBytes":358} 
+2022-08-04 09:11:15 STATE: Compile: {"name":"tfjs/browser/esm/nobundle","format":"esm","platform":"browser","input":"tfjs/tf-browser.ts","output":"dist/tfjs.esm.js","files":2,"inputBytes":1032,"outputBytes":583} 
+2022-08-04 09:11:15 STATE: Compile: {"name":"human/browser/esm/nobundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm-nobundle.js","files":74,"inputBytes":649244,"outputBytes":303238} 
+2022-08-04 09:11:15 STATE: Compile: {"name":"tfjs/browser/esm/custom","format":"esm","platform":"browser","input":"tfjs/tf-custom.ts","output":"dist/tfjs.esm.js","files":11,"inputBytes":1271,"outputBytes":2787569} 
+2022-08-04 09:11:15 STATE: Compile: {"name":"human/browser/iife/bundle","format":"iife","platform":"browser","input":"src/human.ts","output":"dist/human.js","files":74,"inputBytes":3436230,"outputBytes":1666096} 
+2022-08-04 09:11:16 STATE: Compile: {"name":"human/browser/esm/bundle","format":"esm","platform":"browser","input":"src/human.ts","output":"dist/human.esm.js","files":74,"inputBytes":3436230,"outputBytes":3066923} 
+2022-08-04 09:11:22 STATE: Typings: {"input":"src/human.ts","output":"types/lib","files":30} 
+2022-08-04 09:11:25 STATE: TypeDoc: {"input":"src/human.ts","output":"typedoc","objects":76,"generated":true} 
+2022-08-04 09:11:25 STATE: Compile: {"name":"demo/typescript","format":"esm","platform":"browser","input":"demo/typescript/index.ts","output":"demo/typescript/index.js","files":1,"inputBytes":6787,"outputBytes":3141} 
+2022-08-04 09:11:25 STATE: Compile: {"name":"demo/faceid","format":"esm","platform":"browser","input":"demo/faceid/index.ts","output":"demo/faceid/index.js","files":2,"inputBytes":15174,"outputBytes":7604} 
+2022-08-04 09:11:35 STATE: Lint: {"locations":["*.json","src/**/*.ts","test/**/*.js","demo/**/*.js"],"files":107,"errors":0,"warnings":0} 
+2022-08-04 09:11:35 STATE: ChangeLog: {"repository":"https://github.com/vladmandic/human","branch":"main","output":"CHANGELOG.md"} 
+2022-08-04 09:11:35 INFO:  Done... 
diff --git a/test/test.log b/test/test.log
index 8e64e263..c8617008 100644
--- a/test/test.log
+++ b/test/test.log
@@ -1,684 +1,684 @@
-2022-07-29 09:22:56 INFO:  @vladmandic/human version 2.9.1 
-2022-07-29 09:22:56 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.15.0 
-2022-07-29 09:22:56 INFO:  tests: ["test-node.js","test-node-gpu.js","test-node-wasm.js"] 
-2022-07-29 09:22:56 INFO:  demos: ["../demo/nodejs/node.js","../demo/nodejs/node-canvas.js","../demo/nodejs/node-env.js","../demo/nodejs/node-event.js","../demo/nodejs/node-multiprocess.js"] 
-2022-07-29 09:22:56 INFO:  
-2022-07-29 09:22:56 INFO:  test-node.js start 
-2022-07-29 09:22:56 INFO:  test-node.js test: configuration validation 
-2022-07-29 09:22:56 STATE: test-node.js passed: configuration default validation [] 
-2022-07-29 09:22:56 STATE: test-node.js passed: configuration invalid validation [{"reason":"unknown property","where":"config.invalid = true"}] 
-2022-07-29 09:22:56 INFO:  test-node.js test: model load 
-2022-07-29 09:22:56 STATE: test-node.js passed: models loaded 22 12 [{"name":"ssrnetage","loaded":false,"url":null},{"name":"gear","loaded":false,"url":null},{"name":"blazeposedetect","loaded":false,"url":null},{"name":"blazepose","loaded":false,"url":null},{"name":"centernet","loaded":true,"url":"file://models/mb3-centernet.json"},{"name":"efficientpose","loaded":false,"url":null},{"name":"mobilefacenet","loaded":false,"url":null},{"name":"emotion","loaded":true,"url":"file://models/emotion.json"},{"name":"facedetect","loaded":true,"url":"file://models/blazeface.json"},{"name":"faceiris","loaded":true,"url":"file://models/iris.json"},{"name":"facemesh","loaded":true,"url":"file://models/facemesh.json"},{"name":"faceres","loaded":true,"url":"file://models/faceres.json"},{"name":"ssrnetgender","loaded":false,"url":null},{"name":"handpose","loaded":false,"url":null},{"name":"handskeleton","loaded":true,"url":"file://models/handlandmark-full.json"},{"name":"handtrack","loaded":true,"url":"file://models/handtrack.json"},{"name":"liveness","loaded":true,"url":"file://models/liveness.json"},{"name":"movenet","loaded":true,"url":"file://models/movenet-lightning.json"},{"name":"nanodet","loaded":false,"url":null},{"name":"posenet","loaded":false,"url":null},{"name":"segmentation","loaded":true,"url":"file://models/selfie.json"},{"name":"antispoof","loaded":true,"url":"file://models/antispoof.json"}] 
-2022-07-29 09:22:56 INFO:  test-node.js test: warmup 
-2022-07-29 09:22:56 STATE: test-node.js passed: create human 
-2022-07-29 09:22:56 INFO:  test-node.js human version: 2.9.1 
-2022-07-29 09:22:56 INFO:  test-node.js platform: linux x64 agent: NodeJS v16.15.0 
-2022-07-29 09:22:56 INFO:  test-node.js tfjs version: 3.19.0 
-2022-07-29 09:22:56 INFO:  test-node.js tensorflow binding version: 2.7.3-dev20220521 
-2022-07-29 09:22:56 STATE: test-node.js passed: set backend: tensorflow 
-2022-07-29 09:22:56 STATE: test-node.js tensors 1921 
-2022-07-29 09:22:56 STATE: test-node.js passed: load models 
-2022-07-29 09:22:56 STATE: test-node.js  result: defined models: 22 loaded models: 12 
-2022-07-29 09:22:56 STATE: test-node.js passed: warmup: none default 
-2022-07-29 09:22:56 DATA:  test-node.js  result: face: 0 body: 0 hand: 0 gesture: 0 object: 0 person: 0 {} {} {} 
-2022-07-29 09:22:56 DATA:  test-node.js  result: performance: load: null total: null 
-2022-07-29 09:22:56 STATE: test-node.js passed: warmup none result match 
-2022-07-29 09:22:56 STATE: test-node.js event: image 
-2022-07-29 09:22:56 STATE: test-node.js event: detect 
-2022-07-29 09:22:56 STATE: test-node.js event: warmup 
-2022-07-29 09:22:56 STATE: test-node.js passed: warmup: face default 
-2022-07-29 09:22:56 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.42,"keypoints":4} 
-2022-07-29 09:22:56 DATA:  test-node.js  result: performance: load: null total: 332 
-2022-07-29 09:22:56 STATE: test-node.js passed: warmup face result match 
-2022-07-29 09:22:56 STATE: test-node.js event: image 
-2022-07-29 09:22:57 STATE: test-node.js event: detect 
-2022-07-29 09:22:57 STATE: test-node.js event: warmup 
-2022-07-29 09:22:57 STATE: test-node.js passed: warmup: body default 
-2022-07-29 09:22:57 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:22:57 DATA:  test-node.js  result: performance: load: null total: 253 
-2022-07-29 09:22:57 STATE: test-node.js passed: warmup body result match 
-2022-07-29 09:22:57 STATE: test-node.js details: {"face":{"boxScore":0.92,"faceScore":1,"age":23.7,"gender":"female","genderScore":0.97},"emotion":[{"score":0.63,"emotion":"angry"},{"score":0.22,"emotion":"fear"}],"body":{"score":0.92,"keypoints":17},"hand":{"boxScore":0.52,"fingerScore":0.73,"keypoints":21},"gestures":[{"face":0,"gesture":"facing right"},{"face":0,"gesture":"mouth 10% open"},{"hand":0,"gesture":"pinky forward"},{"hand":0,"gesture":"palm up"},{"hand":0,"gesture":"open palm"},{"iris":0,"gesture":"looking left"},{"iris":0,"gesture":"looking up"}]} 
-2022-07-29 09:22:57 INFO:  test-node.js test: details verification 
-2022-07-29 09:22:57 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-07-29 09:22:57 STATE: test-node.js event: image 
-2022-07-29 09:22:57 STATE: test-node.js event: detect 
-2022-07-29 09:22:57 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:22:57 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:22:57 DATA:  test-node.js  result: performance: load: null total: 246 
-2022-07-29 09:22:57 STATE: test-node.js passed: details face length 1 
-2022-07-29 09:22:57 STATE: test-node.js passed: details face score 1 0.93 1 
-2022-07-29 09:22:57 STATE: test-node.js passed: details face age/gender 23.7 female 0.97 85.47 
-2022-07-29 09:22:57 STATE: test-node.js passed: details face arrays 4 478 1024 
-2022-07-29 09:22:57 STATE: test-node.js passed: details face emotion 2 {"score":0.59,"emotion":"angry"} 
-2022-07-29 09:22:57 STATE: test-node.js passed: details face anti-spoofing 0.79 
-2022-07-29 09:22:57 STATE: test-node.js passed: details face liveness 0.83 
-2022-07-29 09:22:57 STATE: test-node.js passed: details body length 1 
-2022-07-29 09:22:57 STATE: test-node.js passed: details body 0.92 17 6 
-2022-07-29 09:22:57 STATE: test-node.js passed: details hand length 1 
-2022-07-29 09:22:57 STATE: test-node.js passed: details hand 0.51 0.73 point 
-2022-07-29 09:22:57 STATE: test-node.js passed: details hand arrays 21 5 7 
-2022-07-29 09:22:57 STATE: test-node.js passed: details gesture length 7 
-2022-07-29 09:22:57 STATE: test-node.js passed: details gesture first {"face":0,"gesture":"facing right"} 
-2022-07-29 09:22:57 STATE: test-node.js passed: details object length 1 
-2022-07-29 09:22:57 STATE: test-node.js passed: details object 0.72 person 
-2022-07-29 09:22:57 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996928} 
-2022-07-29 09:22:57 STATE: test-node.js event: image 
-2022-07-29 09:22:58 STATE: test-node.js event: detect 
-2022-07-29 09:22:58 STATE: test-node.js passed: tensor shape: [1,1200,1200,4] dtype: float32 
-2022-07-29 09:22:58 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1200,1200,4] {"checksum":1371996928} 
-2022-07-29 09:22:58 STATE: test-node.js event: image 
-2022-07-29 09:22:58 STATE: test-node.js event: detect 
-2022-07-29 09:22:58 STATE: test-node.js passed: tensor shape: [1200,1200,4] dtype: float32 
-2022-07-29 09:22:58 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-07-29 09:22:58 STATE: test-node.js event: image 
-2022-07-29 09:22:59 STATE: test-node.js event: detect 
-2022-07-29 09:22:59 STATE: test-node.js passed: tensor shape: [1,1200,1200,3] dtype: float32 
-2022-07-29 09:22:59 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1200,1200,3] {"checksum":1004796864} 
-2022-07-29 09:22:59 STATE: test-node.js event: image 
-2022-07-29 09:22:59 STATE: test-node.js event: detect 
-2022-07-29 09:22:59 STATE: test-node.js passed: tensor shape: [1200,1200,3] dtype: float32 
-2022-07-29 09:22:59 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996871} 
-2022-07-29 09:22:59 STATE: test-node.js event: image 
-2022-07-29 09:23:00 STATE: test-node.js event: detect 
-2022-07-29 09:23:00 STATE: test-node.js passed: tensor shape: [1,1200,1200,4] dtype: int32 
-2022-07-29 09:23:00 INFO:  test-node.js test default 
-2022-07-29 09:23:00 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-07-29 09:23:00 STATE: test-node.js event: image 
-2022-07-29 09:23:00 STATE: test-node.js event: detect 
-2022-07-29 09:23:00 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:00 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:00 DATA:  test-node.js  result: performance: load: null total: 227 
-2022-07-29 09:23:00 STATE: test-node.js passed: default result face match 1 female 0.97 
-2022-07-29 09:23:00 INFO:  test-node.js test sync 
-2022-07-29 09:23:00 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-07-29 09:23:00 STATE: test-node.js event: image 
-2022-07-29 09:23:00 STATE: test-node.js event: detect 
-2022-07-29 09:23:00 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:00 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:00 DATA:  test-node.js  result: performance: load: null total: 213 
-2022-07-29 09:23:00 STATE: test-node.js passed: default sync 1 female 0.97 
-2022-07-29 09:23:00 INFO:  test-node.js test: image process 
-2022-07-29 09:23:00 STATE: test-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-07-29 09:23:00 STATE: test-node.js passed: image input null [1,256,256,3] 
-2022-07-29 09:23:00 INFO:  test-node.js test: image null 
-2022-07-29 09:23:00 STATE: test-node.js passed: invalid input could not convert input to tensor 
-2022-07-29 09:23:00 INFO:  test-node.js test face similarity 
-2022-07-29 09:23:00 STATE: test-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-07-29 09:23:00 STATE: test-node.js event: image 
-2022-07-29 09:23:01 STATE: test-node.js event: detect 
-2022-07-29 09:23:01 STATE: test-node.js passed: detect: samples/in/ai-face.jpg default 
-2022-07-29 09:23:01 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
-2022-07-29 09:23:01 DATA:  test-node.js  result: performance: load: null total: 203 
-2022-07-29 09:23:01 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-07-29 09:23:01 STATE: test-node.js event: image 
-2022-07-29 09:23:01 STATE: test-node.js event: detect 
-2022-07-29 09:23:01 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:01 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:01 DATA:  test-node.js  result: performance: load: null total: 213 
-2022-07-29 09:23:01 STATE: test-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
-2022-07-29 09:23:01 STATE: test-node.js event: image 
-2022-07-29 09:23:01 STATE: test-node.js event: detect 
-2022-07-29 09:23:01 STATE: test-node.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:01 DATA:  test-node.js  result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":7} 
-2022-07-29 09:23:01 DATA:  test-node.js  result: performance: load: null total: 193 
-2022-07-29 09:23:01 STATE: test-node.js passed: face descriptor 
-2022-07-29 09:23:01 STATE: test-node.js passed: face similarity {"similarity":[1,0.44727452329649126,0.5567935850640406],"descriptors":[1024,1024,1024]} 
-2022-07-29 09:23:01 INFO:  test-node.js test face matching 
-2022-07-29 09:23:01 STATE: test-node.js passed: face database 40 
-2022-07-29 09:23:01 STATE: test-node.js passed: face match {"first":{"index":4,"similarity":0.7827852615252829}} {"second":{"index":4,"similarity":0.5002052633015844}} {"third":{"index":4,"similarity":0.5401587887998899}} 
-2022-07-29 09:23:01 INFO:  test-node.js test object 
-2022-07-29 09:23:01 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-07-29 09:23:01 STATE: test-node.js event: image 
-2022-07-29 09:23:02 STATE: test-node.js event: detect 
-2022-07-29 09:23:02 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:02 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:02 DATA:  test-node.js  result: performance: load: null total: 204 
-2022-07-29 09:23:02 STATE: test-node.js passed: object result match 
-2022-07-29 09:23:02 INFO:  test-node.js test sensitive 
-2022-07-29 09:23:02 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-07-29 09:23:02 STATE: test-node.js event: image 
-2022-07-29 09:23:02 STATE: test-node.js event: detect 
-2022-07-29 09:23:02 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:02 DATA:  test-node.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:02 DATA:  test-node.js  result: performance: load: null total: 229 
-2022-07-29 09:23:02 STATE: test-node.js passed: sensitive result match 
-2022-07-29 09:23:02 STATE: test-node.js passed: sensitive face result match 
-2022-07-29 09:23:02 STATE: test-node.js passed: sensitive face emotion result [{"score":0.59,"emotion":"angry"},{"score":0.29,"emotion":"fear"}] 
-2022-07-29 09:23:02 STATE: test-node.js passed: sensitive body result match 
-2022-07-29 09:23:02 STATE: test-node.js passed: sensitive hand result match 
-2022-07-29 09:23:02 INFO:  test-node.js test detectors 
-2022-07-29 09:23:02 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-07-29 09:23:02 STATE: test-node.js event: image 
-2022-07-29 09:23:02 STATE: test-node.js event: detect 
-2022-07-29 09:23:02 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:02 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:02 DATA:  test-node.js  result: performance: load: null total: 144 
-2022-07-29 09:23:02 STATE: test-node.js passed: detector result face match 
-2022-07-29 09:23:02 STATE: test-node.js passed: detector result hand match 
-2022-07-29 09:23:02 INFO:  test-node.js test: multi-instance 
-2022-07-29 09:23:02 STATE: test-node.js event: image 
-2022-07-29 09:23:03 STATE: test-node.js event: detect 
-2022-07-29 09:23:03 STATE: test-node.js passed: detect: random default 
-2022-07-29 09:23:03 DATA:  test-node.js  result: face: 0 body: 1 hand: 0 gesture: 0 object: 0 person: 0 {} {} {"score":0.07,"keypoints":15} 
-2022-07-29 09:23:03 DATA:  test-node.js  result: performance: load: null total: 133 
-2022-07-29 09:23:03 INFO:  test-node.js test: first instance 
-2022-07-29 09:23:03 STATE: test-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
-2022-07-29 09:23:03 STATE: test-node.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:03 DATA:  test-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:03 DATA:  test-node.js  result: performance: load: null total: 144 
-2022-07-29 09:23:03 INFO:  test-node.js test: second instance 
-2022-07-29 09:23:03 STATE: test-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
-2022-07-29 09:23:03 STATE: test-node.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:03 DATA:  test-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:03 DATA:  test-node.js  result: performance: load: null total: 144 
-2022-07-29 09:23:03 INFO:  test-node.js test: concurrent 
-2022-07-29 09:23:03 STATE: test-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-07-29 09:23:03 STATE: test-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-07-29 09:23:03 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-07-29 09:23:03 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-07-29 09:23:03 STATE: test-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
-2022-07-29 09:23:03 STATE: test-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
-2022-07-29 09:23:03 STATE: test-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-07-29 09:23:04 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-07-29 09:23:04 STATE: test-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
-2022-07-29 09:23:04 STATE: test-node.js event: image 
-2022-07-29 09:23:04 STATE: test-node.js event: image 
-2022-07-29 09:23:04 STATE: test-node.js event: image 
-2022-07-29 09:23:05 STATE: test-node.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:05 DATA:  test-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:05 DATA:  test-node.js  result: performance: load: null total: 1333 
-2022-07-29 09:23:05 STATE: test-node.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:05 DATA:  test-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:05 DATA:  test-node.js  result: performance: load: null total: 1333 
-2022-07-29 09:23:05 STATE: test-node.js passed: detect: samples/in/ai-face.jpg default 
-2022-07-29 09:23:05 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
-2022-07-29 09:23:05 DATA:  test-node.js  result: performance: load: null total: 1447 
-2022-07-29 09:23:05 STATE: test-node.js passed: detect: samples/in/ai-face.jpg default 
-2022-07-29 09:23:05 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
-2022-07-29 09:23:05 DATA:  test-node.js  result: performance: load: null total: 1447 
-2022-07-29 09:23:05 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:05 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:05 DATA:  test-node.js  result: performance: load: null total: 1447 
-2022-07-29 09:23:05 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:05 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:05 DATA:  test-node.js  result: performance: load: null total: 1447 
-2022-07-29 09:23:05 STATE: test-node.js event: detect 
-2022-07-29 09:23:05 STATE: test-node.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:05 DATA:  test-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:05 DATA:  test-node.js  result: performance: load: null total: 1209 
-2022-07-29 09:23:05 STATE: test-node.js event: detect 
-2022-07-29 09:23:05 STATE: test-node.js event: detect 
-2022-07-29 09:23:05 STATE: test-node.js passed: detect: samples/in/ai-face.jpg default 
-2022-07-29 09:23:05 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
-2022-07-29 09:23:05 DATA:  test-node.js  result: performance: load: null total: 1209 
-2022-07-29 09:23:05 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:05 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:05 DATA:  test-node.js  result: performance: load: null total: 1209 
-2022-07-29 09:23:05 INFO:  test-node.js test: monkey-patch 
-2022-07-29 09:23:05 STATE: test-node.js event: image 
-2022-07-29 09:23:05 STATE: test-node.js event: detect 
-2022-07-29 09:23:05 STATE: test-node.js passed: monkey patch 
-2022-07-29 09:23:05 STATE: test-node.js passed: segmentation [65536] 
-2022-07-29 09:23:05 STATE: test-node.js passeed: equal usage 
-2022-07-29 09:23:05 INFO:  test-node.js test: input compare 
-2022-07-29 09:23:05 STATE: test-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-07-29 09:23:05 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
-2022-07-29 09:23:05 STATE: test-node.js passed: image compare 0 23.275441687091504 
-2022-07-29 09:23:05 INFO:  test-node.js events: {"image":21,"detect":21,"warmup":2} 
-2022-07-29 09:23:05 INFO:  test-node.js tensors 1927 
-2022-07-29 09:23:05 INFO:  test-node.js test complete: 9269 ms 
-2022-07-29 09:23:05 INFO:  
-2022-07-29 09:23:05 INFO:  test-node-gpu.js start 
-2022-07-29 09:23:06 INFO:  test-node-gpu.js test: configuration validation 
-2022-07-29 09:23:06 STATE: test-node-gpu.js passed: configuration default validation [] 
-2022-07-29 09:23:06 STATE: test-node-gpu.js passed: configuration invalid validation [{"reason":"unknown property","where":"config.invalid = true"}] 
-2022-07-29 09:23:06 INFO:  test-node-gpu.js test: model load 
-2022-07-29 09:23:06 STATE: test-node-gpu.js passed: models loaded 22 12 [{"name":"ssrnetage","loaded":false,"url":null},{"name":"gear","loaded":false,"url":null},{"name":"blazeposedetect","loaded":false,"url":null},{"name":"blazepose","loaded":false,"url":null},{"name":"centernet","loaded":true,"url":"file://models/mb3-centernet.json"},{"name":"efficientpose","loaded":false,"url":null},{"name":"mobilefacenet","loaded":false,"url":null},{"name":"emotion","loaded":true,"url":"file://models/emotion.json"},{"name":"facedetect","loaded":true,"url":"file://models/blazeface.json"},{"name":"faceiris","loaded":true,"url":"file://models/iris.json"},{"name":"facemesh","loaded":true,"url":"file://models/facemesh.json"},{"name":"faceres","loaded":true,"url":"file://models/faceres.json"},{"name":"ssrnetgender","loaded":false,"url":null},{"name":"handpose","loaded":false,"url":null},{"name":"handskeleton","loaded":true,"url":"file://models/handlandmark-full.json"},{"name":"handtrack","loaded":true,"url":"file://models/handtrack.json"},{"name":"liveness","loaded":true,"url":"file://models/liveness.json"},{"name":"movenet","loaded":true,"url":"file://models/movenet-lightning.json"},{"name":"nanodet","loaded":false,"url":null},{"name":"posenet","loaded":false,"url":null},{"name":"segmentation","loaded":true,"url":"file://models/selfie.json"},{"name":"antispoof","loaded":true,"url":"file://models/antispoof.json"}] 
-2022-07-29 09:23:06 INFO:  test-node-gpu.js test: warmup 
-2022-07-29 09:23:06 STATE: test-node-gpu.js passed: create human 
-2022-07-29 09:23:06 INFO:  test-node-gpu.js human version: 2.9.1 
-2022-07-29 09:23:06 INFO:  test-node-gpu.js platform: linux x64 agent: NodeJS v16.15.0 
-2022-07-29 09:23:06 INFO:  test-node-gpu.js tfjs version: 3.19.0 
-2022-07-29 09:23:06 INFO:  test-node-gpu.js tensorflow binding version: 2.7.3-dev20220521 
-2022-07-29 09:23:06 STATE: test-node-gpu.js passed: set backend: tensorflow 
-2022-07-29 09:23:06 STATE: test-node-gpu.js tensors 1921 
-2022-07-29 09:23:06 STATE: test-node-gpu.js passed: load models 
-2022-07-29 09:23:06 STATE: test-node-gpu.js  result: defined models: 22 loaded models: 12 
-2022-07-29 09:23:06 STATE: test-node-gpu.js passed: warmup: none default 
-2022-07-29 09:23:06 DATA:  test-node-gpu.js  result: face: 0 body: 0 hand: 0 gesture: 0 object: 0 person: 0 {} {} {} 
-2022-07-29 09:23:06 DATA:  test-node-gpu.js  result: performance: load: null total: null 
-2022-07-29 09:23:06 STATE: test-node-gpu.js passed: warmup none result match 
-2022-07-29 09:23:07 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:10 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:10 STATE: test-node-gpu.js event: warmup 
-2022-07-29 09:23:10 STATE: test-node-gpu.js passed: warmup: face default 
-2022-07-29 09:23:10 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.42,"keypoints":4} 
-2022-07-29 09:23:10 DATA:  test-node-gpu.js  result: performance: load: null total: 3380 
-2022-07-29 09:23:10 STATE: test-node-gpu.js passed: warmup face result match 
-2022-07-29 09:23:10 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:10 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:10 STATE: test-node-gpu.js event: warmup 
-2022-07-29 09:23:10 STATE: test-node-gpu.js passed: warmup: body default 
-2022-07-29 09:23:10 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:10 DATA:  test-node-gpu.js  result: performance: load: null total: 267 
-2022-07-29 09:23:10 STATE: test-node-gpu.js passed: warmup body result match 
-2022-07-29 09:23:10 STATE: test-node-gpu.js details: {"face":{"boxScore":0.92,"faceScore":1,"age":23.7,"gender":"female","genderScore":0.97},"emotion":[{"score":0.63,"emotion":"angry"},{"score":0.22,"emotion":"fear"}],"body":{"score":0.92,"keypoints":17},"hand":{"boxScore":0.52,"fingerScore":0.73,"keypoints":21},"gestures":[{"face":0,"gesture":"facing right"},{"face":0,"gesture":"mouth 10% open"},{"hand":0,"gesture":"pinky forward"},{"hand":0,"gesture":"palm up"},{"hand":0,"gesture":"open palm"},{"iris":0,"gesture":"looking left"},{"iris":0,"gesture":"looking up"}]} 
-2022-07-29 09:23:10 INFO:  test-node-gpu.js test: details verification 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-07-29 09:23:11 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:11 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:11 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:11 DATA:  test-node-gpu.js  result: performance: load: null total: 223 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details face length 1 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details face score 1 0.93 1 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details face age/gender 23.7 female 0.97 85.47 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details face arrays 4 478 1024 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details face emotion 2 {"score":0.59,"emotion":"angry"} 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details face anti-spoofing 0.79 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details face liveness 0.83 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details body length 1 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details body 0.92 17 6 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details hand length 1 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details hand 0.51 0.73 point 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details hand arrays 21 5 7 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details gesture length 7 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details gesture first {"face":0,"gesture":"facing right"} 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details object length 1 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: details object 0.72 person 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996928} 
-2022-07-29 09:23:11 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:11 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: tensor shape: [1,1200,1200,4] dtype: float32 
-2022-07-29 09:23:11 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1200,1200,4] {"checksum":1371996928} 
-2022-07-29 09:23:11 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:12 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:12 STATE: test-node-gpu.js passed: tensor shape: [1200,1200,4] dtype: float32 
-2022-07-29 09:23:12 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-07-29 09:23:12 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:12 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:12 STATE: test-node-gpu.js passed: tensor shape: [1,1200,1200,3] dtype: float32 
-2022-07-29 09:23:12 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1200,1200,3] {"checksum":1004796928} 
-2022-07-29 09:23:12 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:12 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:12 STATE: test-node-gpu.js passed: tensor shape: [1200,1200,3] dtype: float32 
-2022-07-29 09:23:13 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996871} 
-2022-07-29 09:23:13 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:13 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:13 STATE: test-node-gpu.js passed: tensor shape: [1,1200,1200,4] dtype: int32 
-2022-07-29 09:23:13 INFO:  test-node-gpu.js test default 
-2022-07-29 09:23:13 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-07-29 09:23:13 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:13 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:13 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:13 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:13 DATA:  test-node-gpu.js  result: performance: load: null total: 193 
-2022-07-29 09:23:13 STATE: test-node-gpu.js passed: default result face match 1 female 0.97 
-2022-07-29 09:23:13 INFO:  test-node-gpu.js test sync 
-2022-07-29 09:23:13 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-07-29 09:23:13 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:13 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:13 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:13 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:13 DATA:  test-node-gpu.js  result: performance: load: null total: 176 
-2022-07-29 09:23:13 STATE: test-node-gpu.js passed: default sync 1 female 0.97 
-2022-07-29 09:23:13 INFO:  test-node-gpu.js test: image process 
-2022-07-29 09:23:13 STATE: test-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-07-29 09:23:13 STATE: test-node-gpu.js passed: image input null [1,256,256,3] 
-2022-07-29 09:23:13 INFO:  test-node-gpu.js test: image null 
-2022-07-29 09:23:13 STATE: test-node-gpu.js passed: invalid input could not convert input to tensor 
-2022-07-29 09:23:13 INFO:  test-node-gpu.js test face similarity 
-2022-07-29 09:23:13 STATE: test-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-07-29 09:23:13 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:14 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:14 STATE: test-node-gpu.js passed: detect: samples/in/ai-face.jpg default 
-2022-07-29 09:23:14 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
-2022-07-29 09:23:14 DATA:  test-node-gpu.js  result: performance: load: null total: 186 
-2022-07-29 09:23:14 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-07-29 09:23:14 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:14 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:14 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:14 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:14 DATA:  test-node-gpu.js  result: performance: load: null total: 192 
-2022-07-29 09:23:14 STATE: test-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
-2022-07-29 09:23:14 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:14 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:14 STATE: test-node-gpu.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:14 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":7} 
-2022-07-29 09:23:14 DATA:  test-node-gpu.js  result: performance: load: null total: 178 
-2022-07-29 09:23:14 STATE: test-node-gpu.js passed: face descriptor 
-2022-07-29 09:23:14 STATE: test-node-gpu.js passed: face similarity {"similarity":[1,0.447238756461232,0.556914029877052],"descriptors":[1024,1024,1024]} 
-2022-07-29 09:23:14 INFO:  test-node-gpu.js test face matching 
-2022-07-29 09:23:14 STATE: test-node-gpu.js passed: face database 40 
-2022-07-29 09:23:14 STATE: test-node-gpu.js passed: face match {"first":{"index":4,"similarity":0.7828184453007331}} {"second":{"index":4,"similarity":0.5001334216773398}} {"third":{"index":4,"similarity":0.5403054967489764}} 
-2022-07-29 09:23:14 INFO:  test-node-gpu.js test object 
-2022-07-29 09:23:14 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-07-29 09:23:14 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:15 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:15 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:15 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:15 DATA:  test-node-gpu.js  result: performance: load: null total: 220 
-2022-07-29 09:23:15 STATE: test-node-gpu.js passed: object result match 
-2022-07-29 09:23:15 INFO:  test-node-gpu.js test sensitive 
-2022-07-29 09:23:15 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-07-29 09:23:15 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:15 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:15 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:15 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:15 DATA:  test-node-gpu.js  result: performance: load: null total: 235 
-2022-07-29 09:23:15 STATE: test-node-gpu.js passed: sensitive result match 
-2022-07-29 09:23:15 STATE: test-node-gpu.js passed: sensitive face result match 
-2022-07-29 09:23:15 STATE: test-node-gpu.js passed: sensitive face emotion result [{"score":0.59,"emotion":"angry"},{"score":0.29,"emotion":"fear"}] 
-2022-07-29 09:23:15 STATE: test-node-gpu.js passed: sensitive body result match 
-2022-07-29 09:23:15 STATE: test-node-gpu.js passed: sensitive hand result match 
-2022-07-29 09:23:15 INFO:  test-node-gpu.js test detectors 
-2022-07-29 09:23:16 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-07-29 09:23:16 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:16 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:16 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:16 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:16 DATA:  test-node-gpu.js  result: performance: load: null total: 139 
-2022-07-29 09:23:16 STATE: test-node-gpu.js passed: detector result face match 
-2022-07-29 09:23:16 STATE: test-node-gpu.js passed: detector result hand match 
-2022-07-29 09:23:16 INFO:  test-node-gpu.js test: multi-instance 
-2022-07-29 09:23:16 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:16 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:16 STATE: test-node-gpu.js passed: detect: random default 
-2022-07-29 09:23:16 DATA:  test-node-gpu.js  result: face: 0 body: 1 hand: 0 gesture: 0 object: 0 person: 0 {} {} {"score":0.06,"keypoints":15} 
-2022-07-29 09:23:16 DATA:  test-node-gpu.js  result: performance: load: null total: 81 
-2022-07-29 09:23:16 INFO:  test-node-gpu.js test: first instance 
-2022-07-29 09:23:16 STATE: test-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
-2022-07-29 09:23:16 STATE: test-node-gpu.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:16 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:16 DATA:  test-node-gpu.js  result: performance: load: null total: 96 
-2022-07-29 09:23:16 INFO:  test-node-gpu.js test: second instance 
-2022-07-29 09:23:16 STATE: test-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
-2022-07-29 09:23:16 STATE: test-node-gpu.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:16 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:16 DATA:  test-node-gpu.js  result: performance: load: null total: 100 
-2022-07-29 09:23:16 INFO:  test-node-gpu.js test: concurrent 
-2022-07-29 09:23:16 STATE: test-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-07-29 09:23:16 STATE: test-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-07-29 09:23:17 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-07-29 09:23:17 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-07-29 09:23:17 STATE: test-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
-2022-07-29 09:23:17 STATE: test-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
-2022-07-29 09:23:17 STATE: test-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-07-29 09:23:17 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-07-29 09:23:17 STATE: test-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
-2022-07-29 09:23:17 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:17 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:17 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:18 STATE: test-node-gpu.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: performance: load: null total: 1009 
-2022-07-29 09:23:18 STATE: test-node-gpu.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: performance: load: null total: 1009 
-2022-07-29 09:23:18 STATE: test-node-gpu.js passed: detect: samples/in/ai-face.jpg default 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: performance: load: null total: 1079 
-2022-07-29 09:23:18 STATE: test-node-gpu.js passed: detect: samples/in/ai-face.jpg default 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: performance: load: null total: 1079 
-2022-07-29 09:23:18 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: performance: load: null total: 1079 
-2022-07-29 09:23:18 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: performance: load: null total: 1079 
-2022-07-29 09:23:18 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:18 STATE: test-node-gpu.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: performance: load: null total: 832 
-2022-07-29 09:23:18 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:18 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:18 STATE: test-node-gpu.js passed: detect: samples/in/ai-face.jpg default 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: performance: load: null total: 833 
-2022-07-29 09:23:18 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:18 DATA:  test-node-gpu.js  result: performance: load: null total: 833 
-2022-07-29 09:23:18 INFO:  test-node-gpu.js test: monkey-patch 
-2022-07-29 09:23:18 STATE: test-node-gpu.js event: image 
-2022-07-29 09:23:18 STATE: test-node-gpu.js event: detect 
-2022-07-29 09:23:18 STATE: test-node-gpu.js passed: monkey patch 
-2022-07-29 09:23:18 STATE: test-node-gpu.js passed: segmentation [65536] 
-2022-07-29 09:23:18 STATE: test-node-gpu.js passeed: equal usage 
-2022-07-29 09:23:18 INFO:  test-node-gpu.js test: input compare 
-2022-07-29 09:23:18 STATE: test-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
-2022-07-29 09:23:19 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
-2022-07-29 09:23:19 STATE: test-node-gpu.js passed: image compare 0 23.275441687091504 
-2022-07-29 09:23:19 INFO:  test-node-gpu.js events: {"image":21,"detect":21,"warmup":2} 
-2022-07-29 09:23:19 INFO:  test-node-gpu.js tensors 1927 
-2022-07-29 09:23:19 INFO:  test-node-gpu.js test complete: 12418 ms 
-2022-07-29 09:23:19 INFO:  
-2022-07-29 09:23:19 INFO:  test-node-wasm.js start 
-2022-07-29 09:23:20 STATE: test-node-wasm.js passed: model server: https://vladmandic.github.io/human/models/ 
-2022-07-29 09:23:20 INFO:  test-node-wasm.js test: configuration validation 
-2022-07-29 09:23:20 STATE: test-node-wasm.js passed: configuration default validation [] 
-2022-07-29 09:23:20 STATE: test-node-wasm.js passed: configuration invalid validation [{"reason":"unknown property","where":"config.invalid = true"}] 
-2022-07-29 09:23:20 INFO:  test-node-wasm.js test: model load 
-2022-07-29 09:23:22 STATE: test-node-wasm.js passed: models loaded 22 12 [{"name":"ssrnetage","loaded":false,"url":null},{"name":"gear","loaded":false,"url":null},{"name":"blazeposedetect","loaded":false,"url":null},{"name":"blazepose","loaded":false,"url":null},{"name":"centernet","loaded":true,"url":"https://vladmandic.github.io/human/models/mb3-centernet.json"},{"name":"efficientpose","loaded":false,"url":null},{"name":"mobilefacenet","loaded":false,"url":null},{"name":"emotion","loaded":true,"url":"https://vladmandic.github.io/human/models/emotion.json"},{"name":"facedetect","loaded":true,"url":"https://vladmandic.github.io/human/models/blazeface.json"},{"name":"faceiris","loaded":true,"url":"https://vladmandic.github.io/human/models/iris.json"},{"name":"facemesh","loaded":true,"url":"https://vladmandic.github.io/human/models/facemesh.json"},{"name":"faceres","loaded":true,"url":"https://vladmandic.github.io/human/models/faceres.json"},{"name":"ssrnetgender","loaded":false,"url":null},{"name":"handpose","loaded":false,"url":null},{"name":"handskeleton","loaded":true,"url":"https://vladmandic.github.io/human/models/handlandmark-full.json"},{"name":"handtrack","loaded":true,"url":"https://vladmandic.github.io/human/models/handtrack.json"},{"name":"liveness","loaded":true,"url":"https://vladmandic.github.io/human/models/liveness.json"},{"name":"movenet","loaded":true,"url":"https://vladmandic.github.io/human/models/movenet-lightning.json"},{"name":"nanodet","loaded":false,"url":null},{"name":"posenet","loaded":false,"url":null},{"name":"segmentation","loaded":true,"url":"https://vladmandic.github.io/human/models/selfie.json"},{"name":"antispoof","loaded":true,"url":"https://vladmandic.github.io/human/models/antispoof.json"}] 
-2022-07-29 09:23:22 INFO:  test-node-wasm.js test: warmup 
-2022-07-29 09:23:22 STATE: test-node-wasm.js passed: create human 
-2022-07-29 09:23:22 INFO:  test-node-wasm.js human version: 2.9.1 
-2022-07-29 09:23:22 INFO:  test-node-wasm.js platform: linux x64 agent: NodeJS v16.15.0 
-2022-07-29 09:23:22 INFO:  test-node-wasm.js tfjs version: 3.19.0 
-2022-07-29 09:23:22 STATE: test-node-wasm.js passed: set backend: wasm 
-2022-07-29 09:23:22 STATE: test-node-wasm.js tensors 1921 
-2022-07-29 09:23:22 STATE: test-node-wasm.js passed: load models 
-2022-07-29 09:23:22 STATE: test-node-wasm.js  result: defined models: 22 loaded models: 12 
-2022-07-29 09:23:22 STATE: test-node-wasm.js passed: warmup: none default 
-2022-07-29 09:23:22 DATA:  test-node-wasm.js  result: face: 0 body: 0 hand: 0 gesture: 0 object: 0 person: 0 {} {} {} 
-2022-07-29 09:23:22 DATA:  test-node-wasm.js  result: performance: load: null total: null 
-2022-07-29 09:23:22 STATE: test-node-wasm.js passed: warmup none result match 
-2022-07-29 09:23:22 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:22 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:22 STATE: test-node-wasm.js event: warmup 
-2022-07-29 09:23:22 STATE: test-node-wasm.js passed: warmup: face default 
-2022-07-29 09:23:22 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
-2022-07-29 09:23:22 DATA:  test-node-wasm.js  result: performance: load: null total: 525 
-2022-07-29 09:23:22 STATE: test-node-wasm.js passed: warmup face result match 
-2022-07-29 09:23:23 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:23 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:23 STATE: test-node-wasm.js event: warmup 
-2022-07-29 09:23:23 STATE: test-node-wasm.js passed: warmup: body default 
-2022-07-29 09:23:23 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:23 DATA:  test-node-wasm.js  result: performance: load: null total: 395 
-2022-07-29 09:23:23 STATE: test-node-wasm.js passed: warmup body result match 
-2022-07-29 09:23:23 STATE: test-node-wasm.js details: {"face":{"boxScore":0.93,"faceScore":1,"age":23.7,"gender":"female","genderScore":0.97},"emotion":[{"score":0.59,"emotion":"angry"},{"score":0.29,"emotion":"fear"}],"body":{"score":0.92,"keypoints":17},"hand":{"boxScore":0.51,"fingerScore":0.73,"keypoints":21},"gestures":[{"face":0,"gesture":"facing right"},{"face":0,"gesture":"mouth 21% open"},{"hand":0,"gesture":"pinky forward"},{"hand":0,"gesture":"palm up"},{"hand":0,"gesture":"open palm"},{"iris":0,"gesture":"looking left"},{"iris":0,"gesture":"looking up"}]} 
-2022-07-29 09:23:23 INFO:  test-node-wasm.js test: details verification 
-2022-07-29 09:23:23 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-07-29 09:23:23 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:24 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:24 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:24 DATA:  test-node-wasm.js  result: performance: load: null total: 365 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details face length 1 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details face score 1 0.93 1 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details face age/gender 23.7 female 0.97 85.47 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details face arrays 4 478 1024 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details face emotion 2 {"score":0.59,"emotion":"angry"} 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details face anti-spoofing 0.79 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details face liveness 0.83 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details body length 1 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details body 0.92 17 6 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details hand length 1 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details hand 0.51 0.73 point 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details hand arrays 21 5 7 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details gesture length 7 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details gesture first {"face":0,"gesture":"facing right"} 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details object length 1 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: details object 0.72 person 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1413675264} 
-2022-07-29 09:23:24 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:24 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: tensor shape: [1,1200,1200,4] dtype: float32 
-2022-07-29 09:23:24 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1200,1200,4] {"checksum":1413675264} 
-2022-07-29 09:23:24 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:25 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:25 STATE: test-node-wasm.js passed: tensor shape: [1200,1200,4] dtype: float32 
-2022-07-29 09:23:25 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-07-29 09:23:25 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:25 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:25 STATE: test-node-wasm.js passed: tensor shape: [1,1200,1200,3] dtype: float32 
-2022-07-29 09:23:26 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1200,1200,3] {"checksum":1038921856} 
-2022-07-29 09:23:26 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:26 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:26 STATE: test-node-wasm.js passed: tensor shape: [1200,1200,3] dtype: float32 
-2022-07-29 09:23:26 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996871} 
-2022-07-29 09:23:26 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:27 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:27 STATE: test-node-wasm.js passed: tensor shape: [1,1200,1200,4] dtype: int32 
-2022-07-29 09:23:27 INFO:  test-node-wasm.js test default 
-2022-07-29 09:23:27 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-07-29 09:23:27 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:27 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:27 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:27 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:27 DATA:  test-node-wasm.js  result: performance: load: null total: 376 
-2022-07-29 09:23:27 STATE: test-node-wasm.js passed: default result face match 1 female 0.97 
-2022-07-29 09:23:27 INFO:  test-node-wasm.js test sync 
-2022-07-29 09:23:27 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-07-29 09:23:27 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:28 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:28 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:28 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:28 DATA:  test-node-wasm.js  result: performance: load: null total: 423 
-2022-07-29 09:23:28 STATE: test-node-wasm.js passed: default sync 1 female 0.97 
-2022-07-29 09:23:28 INFO:  test-node-wasm.js test: image process 
-2022-07-29 09:23:28 STATE: test-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-07-29 09:23:28 STATE: test-node-wasm.js passed: image input null [1,256,256,3] 
-2022-07-29 09:23:28 INFO:  test-node-wasm.js test: image null 
-2022-07-29 09:23:28 STATE: test-node-wasm.js passed: invalid input could not convert input to tensor 
-2022-07-29 09:23:28 INFO:  test-node-wasm.js test face similarity 
-2022-07-29 09:23:28 STATE: test-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-07-29 09:23:28 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:28 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:28 STATE: test-node-wasm.js passed: detect: samples/in/ai-face.jpg default 
-2022-07-29 09:23:28 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
-2022-07-29 09:23:28 DATA:  test-node-wasm.js  result: performance: load: null total: 383 
-2022-07-29 09:23:28 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-07-29 09:23:28 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:29 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:29 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:29 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:29 DATA:  test-node-wasm.js  result: performance: load: null total: 382 
-2022-07-29 09:23:29 STATE: test-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
-2022-07-29 09:23:29 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:29 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:29 STATE: test-node-wasm.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:29 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":7} 
-2022-07-29 09:23:29 DATA:  test-node-wasm.js  result: performance: load: null total: 337 
-2022-07-29 09:23:29 STATE: test-node-wasm.js passed: face descriptor 
-2022-07-29 09:23:29 STATE: test-node-wasm.js passed: face similarity {"similarity":[1,0.5266119940661309,0.4858842904087851],"descriptors":[1024,1024,1024]} 
-2022-07-29 09:23:29 INFO:  test-node-wasm.js test face matching 
-2022-07-29 09:23:29 STATE: test-node-wasm.js passed: face database 40 
-2022-07-29 09:23:29 STATE: test-node-wasm.js passed: face match {"first":{"index":4,"similarity":0.7827852754786533}} {"second":{"index":4,"similarity":0.5660821189104794}} {"third":{"index":4,"similarity":0.45074189882665594}} 
-2022-07-29 09:23:29 INFO:  test-node-wasm.js test object 
-2022-07-29 09:23:30 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-07-29 09:23:30 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:30 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:30 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:30 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:30 DATA:  test-node-wasm.js  result: performance: load: null total: 372 
-2022-07-29 09:23:30 STATE: test-node-wasm.js passed: object result match 
-2022-07-29 09:23:30 INFO:  test-node-wasm.js test sensitive 
-2022-07-29 09:23:30 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-07-29 09:23:30 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:31 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:31 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:31 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 2 gesture: 10 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:31 DATA:  test-node-wasm.js  result: performance: load: null total: 396 
-2022-07-29 09:23:31 STATE: test-node-wasm.js passed: sensitive result match 
-2022-07-29 09:23:31 STATE: test-node-wasm.js passed: sensitive face result match 
-2022-07-29 09:23:31 STATE: test-node-wasm.js passed: sensitive face emotion result [{"score":0.46,"emotion":"neutral"},{"score":0.24,"emotion":"fear"},{"score":0.17,"emotion":"sad"}] 
-2022-07-29 09:23:31 STATE: test-node-wasm.js passed: sensitive body result match 
-2022-07-29 09:23:31 STATE: test-node-wasm.js passed: sensitive hand result match 
-2022-07-29 09:23:31 INFO:  test-node-wasm.js test detectors 
-2022-07-29 09:23:31 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-07-29 09:23:31 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:31 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:31 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:31 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:31 DATA:  test-node-wasm.js  result: performance: load: null total: 258 
-2022-07-29 09:23:31 STATE: test-node-wasm.js passed: detector result face match 
-2022-07-29 09:23:31 STATE: test-node-wasm.js passed: detector result hand match 
-2022-07-29 09:23:31 INFO:  test-node-wasm.js test: multi-instance 
-2022-07-29 09:23:31 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:31 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:31 STATE: test-node-wasm.js passed: detect: random default 
-2022-07-29 09:23:31 DATA:  test-node-wasm.js  result: face: 0 body: 1 hand: 0 gesture: 0 object: 0 person: 0 {} {} {"score":0.07,"keypoints":15} 
-2022-07-29 09:23:31 DATA:  test-node-wasm.js  result: performance: load: null total: 239 
-2022-07-29 09:23:31 INFO:  test-node-wasm.js test: first instance 
-2022-07-29 09:23:31 STATE: test-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
-2022-07-29 09:23:32 STATE: test-node-wasm.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:32 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:32 DATA:  test-node-wasm.js  result: performance: load: null total: 252 
-2022-07-29 09:23:32 INFO:  test-node-wasm.js test: second instance 
-2022-07-29 09:23:32 STATE: test-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
-2022-07-29 09:23:32 STATE: test-node-wasm.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:32 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:32 DATA:  test-node-wasm.js  result: performance: load: null total: 251 
-2022-07-29 09:23:32 INFO:  test-node-wasm.js test: concurrent 
-2022-07-29 09:23:32 STATE: test-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-07-29 09:23:32 STATE: test-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-07-29 09:23:32 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-07-29 09:23:32 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-07-29 09:23:33 STATE: test-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
-2022-07-29 09:23:33 STATE: test-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
-2022-07-29 09:23:33 STATE: test-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-07-29 09:23:33 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-07-29 09:23:33 STATE: test-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
-2022-07-29 09:23:33 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:33 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:33 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:35 STATE: test-node-wasm.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: performance: load: null total: 2186 
-2022-07-29 09:23:35 STATE: test-node-wasm.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: performance: load: null total: 2186 
-2022-07-29 09:23:35 STATE: test-node-wasm.js passed: detect: samples/in/ai-face.jpg default 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: performance: load: null total: 2430 
-2022-07-29 09:23:35 STATE: test-node-wasm.js passed: detect: samples/in/ai-face.jpg default 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: performance: load: null total: 2430 
-2022-07-29 09:23:35 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: performance: load: null total: 2430 
-2022-07-29 09:23:35 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: performance: load: null total: 2430 
-2022-07-29 09:23:35 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:35 STATE: test-node-wasm.js passed: detect: samples/in/ai-upper.jpg default 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: performance: load: null total: 2107 
-2022-07-29 09:23:35 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:35 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:35 STATE: test-node-wasm.js passed: detect: samples/in/ai-face.jpg default 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: performance: load: null total: 2108 
-2022-07-29 09:23:35 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
-2022-07-29 09:23:35 DATA:  test-node-wasm.js  result: performance: load: null total: 2108 
-2022-07-29 09:23:35 INFO:  test-node-wasm.js test: monkey-patch 
-2022-07-29 09:23:35 STATE: test-node-wasm.js event: image 
-2022-07-29 09:23:35 STATE: test-node-wasm.js event: detect 
-2022-07-29 09:23:35 STATE: test-node-wasm.js passed: monkey patch 
-2022-07-29 09:23:35 STATE: test-node-wasm.js passed: segmentation [65536] 
-2022-07-29 09:23:35 STATE: test-node-wasm.js passeed: equal usage 
-2022-07-29 09:23:35 INFO:  test-node-wasm.js test: input compare 
-2022-07-29 09:23:35 STATE: test-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
-2022-07-29 09:23:36 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
-2022-07-29 09:23:36 STATE: test-node-wasm.js passed: image compare 0 23.280073018790848 
-2022-07-29 09:23:36 INFO:  test-node-wasm.js events: {"image":21,"detect":21,"warmup":2} 
-2022-07-29 09:23:36 INFO:  test-node-wasm.js tensors 1929 
-2022-07-29 09:23:36 INFO:  test-node-wasm.js test complete: 15934 ms 
-2022-07-29 09:23:36 INFO:  all tests complete 
-2022-07-29 09:23:36 INFO:  failed: {"count":0,"messages":[]} 
-2022-07-29 09:23:36 INFO:  status: {"test":"test-node.js","passed":101,"failed":0} 
-2022-07-29 09:23:36 INFO:  status: {"test":"test-node-gpu.js","passed":101,"failed":0} 
-2022-07-29 09:23:36 INFO:  status: {"test":"test-node-wasm.js","passed":102,"failed":0} 
+2022-08-04 09:13:03 INFO:  @vladmandic/human version 2.9.1 
+2022-08-04 09:13:03 INFO:  User: vlado Platform: linux Arch: x64 Node: v16.15.0 
+2022-08-04 09:13:03 INFO:  tests: ["test-node.js","test-node-gpu.js","test-node-wasm.js"] 
+2022-08-04 09:13:03 INFO:  demos: ["../demo/nodejs/node.js","../demo/nodejs/node-canvas.js","../demo/nodejs/node-env.js","../demo/nodejs/node-event.js","../demo/nodejs/node-multiprocess.js"] 
+2022-08-04 09:13:03 INFO:  
+2022-08-04 09:13:03 INFO:  test-node.js start 
+2022-08-04 09:13:03 INFO:  test-node.js test: configuration validation 
+2022-08-04 09:13:03 STATE: test-node.js passed: configuration default validation [] 
+2022-08-04 09:13:03 STATE: test-node.js passed: configuration invalid validation [{"reason":"unknown property","where":"config.invalid = true"}] 
+2022-08-04 09:13:03 INFO:  test-node.js test: model load 
+2022-08-04 09:13:04 STATE: test-node.js passed: models loaded 22 12 [{"name":"ssrnetage","loaded":false,"url":null},{"name":"gear","loaded":false,"url":null},{"name":"blazeposedetect","loaded":false,"url":null},{"name":"blazepose","loaded":false,"url":null},{"name":"centernet","loaded":true,"url":"file://models/mb3-centernet.json"},{"name":"efficientpose","loaded":false,"url":null},{"name":"mobilefacenet","loaded":false,"url":null},{"name":"emotion","loaded":true,"url":"file://models/emotion.json"},{"name":"facedetect","loaded":true,"url":"file://models/blazeface.json"},{"name":"faceiris","loaded":true,"url":"file://models/iris.json"},{"name":"facemesh","loaded":true,"url":"file://models/facemesh.json"},{"name":"faceres","loaded":true,"url":"file://models/faceres.json"},{"name":"ssrnetgender","loaded":false,"url":null},{"name":"handpose","loaded":false,"url":null},{"name":"handskeleton","loaded":true,"url":"file://models/handlandmark-full.json"},{"name":"handtrack","loaded":true,"url":"file://models/handtrack.json"},{"name":"liveness","loaded":true,"url":"file://models/liveness.json"},{"name":"movenet","loaded":true,"url":"file://models/movenet-lightning.json"},{"name":"nanodet","loaded":false,"url":null},{"name":"posenet","loaded":false,"url":null},{"name":"segmentation","loaded":true,"url":"file://models/selfie.json"},{"name":"antispoof","loaded":true,"url":"file://models/antispoof.json"}] 
+2022-08-04 09:13:04 INFO:  test-node.js test: warmup 
+2022-08-04 09:13:04 STATE: test-node.js passed: create human 
+2022-08-04 09:13:04 INFO:  test-node.js human version: 2.9.1 
+2022-08-04 09:13:04 INFO:  test-node.js platform: linux x64 agent: NodeJS v16.15.0 
+2022-08-04 09:13:04 INFO:  test-node.js tfjs version: 3.19.0 
+2022-08-04 09:13:04 INFO:  test-node.js tensorflow binding version: 2.7.3-dev20220521 
+2022-08-04 09:13:04 STATE: test-node.js passed: set backend: tensorflow 
+2022-08-04 09:13:04 STATE: test-node.js tensors 1921 
+2022-08-04 09:13:04 STATE: test-node.js passed: load models 
+2022-08-04 09:13:04 STATE: test-node.js  result: defined models: 22 loaded models: 12 
+2022-08-04 09:13:04 STATE: test-node.js passed: warmup: none default 
+2022-08-04 09:13:04 DATA:  test-node.js  result: face: 0 body: 0 hand: 0 gesture: 0 object: 0 person: 0 {} {} {} 
+2022-08-04 09:13:04 DATA:  test-node.js  result: performance: load: null total: null 
+2022-08-04 09:13:04 STATE: test-node.js passed: warmup none result match 
+2022-08-04 09:13:04 STATE: test-node.js event: image 
+2022-08-04 09:13:04 STATE: test-node.js event: detect 
+2022-08-04 09:13:04 STATE: test-node.js event: warmup 
+2022-08-04 09:13:04 STATE: test-node.js passed: warmup: face default 
+2022-08-04 09:13:04 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.42,"keypoints":4} 
+2022-08-04 09:13:04 DATA:  test-node.js  result: performance: load: null total: 354 
+2022-08-04 09:13:04 STATE: test-node.js passed: warmup face result match 
+2022-08-04 09:13:04 STATE: test-node.js event: image 
+2022-08-04 09:13:04 STATE: test-node.js event: detect 
+2022-08-04 09:13:04 STATE: test-node.js event: warmup 
+2022-08-04 09:13:04 STATE: test-node.js passed: warmup: body default 
+2022-08-04 09:13:04 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:04 DATA:  test-node.js  result: performance: load: null total: 270 
+2022-08-04 09:13:04 STATE: test-node.js passed: warmup body result match 
+2022-08-04 09:13:04 STATE: test-node.js details: {"face":{"boxScore":0.92,"faceScore":1,"age":23.7,"gender":"female","genderScore":0.97},"emotion":[{"score":0.63,"emotion":"angry"},{"score":0.22,"emotion":"fear"}],"body":{"score":0.92,"keypoints":17},"hand":{"boxScore":0.52,"fingerScore":0.73,"keypoints":21},"gestures":[{"face":0,"gesture":"facing right"},{"face":0,"gesture":"mouth 10% open"},{"hand":0,"gesture":"pinky forward"},{"hand":0,"gesture":"palm up"},{"hand":0,"gesture":"open palm"},{"iris":0,"gesture":"looking left"},{"iris":0,"gesture":"looking up"}]} 
+2022-08-04 09:13:04 INFO:  test-node.js test: details verification 
+2022-08-04 09:13:04 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-08-04 09:13:04 STATE: test-node.js event: image 
+2022-08-04 09:13:05 STATE: test-node.js event: detect 
+2022-08-04 09:13:05 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:05 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:05 DATA:  test-node.js  result: performance: load: null total: 248 
+2022-08-04 09:13:05 STATE: test-node.js passed: details face length 1 
+2022-08-04 09:13:05 STATE: test-node.js passed: details face score 1 0.93 1 
+2022-08-04 09:13:05 STATE: test-node.js passed: details face age/gender 23.7 female 0.97 85.47 
+2022-08-04 09:13:05 STATE: test-node.js passed: details face arrays 4 478 1024 
+2022-08-04 09:13:05 STATE: test-node.js passed: details face emotion 2 {"score":0.59,"emotion":"angry"} 
+2022-08-04 09:13:05 STATE: test-node.js passed: details face anti-spoofing 0.79 
+2022-08-04 09:13:05 STATE: test-node.js passed: details face liveness 0.83 
+2022-08-04 09:13:05 STATE: test-node.js passed: details body length 1 
+2022-08-04 09:13:05 STATE: test-node.js passed: details body 0.92 17 6 
+2022-08-04 09:13:05 STATE: test-node.js passed: details hand length 1 
+2022-08-04 09:13:05 STATE: test-node.js passed: details hand 0.51 0.73 point 
+2022-08-04 09:13:05 STATE: test-node.js passed: details hand arrays 21 5 7 
+2022-08-04 09:13:05 STATE: test-node.js passed: details gesture length 7 
+2022-08-04 09:13:05 STATE: test-node.js passed: details gesture first {"face":0,"gesture":"facing right"} 
+2022-08-04 09:13:05 STATE: test-node.js passed: details object length 1 
+2022-08-04 09:13:05 STATE: test-node.js passed: details object 0.72 person 
+2022-08-04 09:13:05 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996928} 
+2022-08-04 09:13:05 STATE: test-node.js event: image 
+2022-08-04 09:13:05 STATE: test-node.js event: detect 
+2022-08-04 09:13:05 STATE: test-node.js passed: tensor shape: [1,1200,1200,4] dtype: float32 
+2022-08-04 09:13:05 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1200,1200,4] {"checksum":1371996928} 
+2022-08-04 09:13:05 STATE: test-node.js event: image 
+2022-08-04 09:13:06 STATE: test-node.js event: detect 
+2022-08-04 09:13:06 STATE: test-node.js passed: tensor shape: [1200,1200,4] dtype: float32 
+2022-08-04 09:13:06 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-08-04 09:13:06 STATE: test-node.js event: image 
+2022-08-04 09:13:06 STATE: test-node.js event: detect 
+2022-08-04 09:13:06 STATE: test-node.js passed: tensor shape: [1,1200,1200,3] dtype: float32 
+2022-08-04 09:13:06 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1200,1200,3] {"checksum":1004796864} 
+2022-08-04 09:13:06 STATE: test-node.js event: image 
+2022-08-04 09:13:06 STATE: test-node.js event: detect 
+2022-08-04 09:13:06 STATE: test-node.js passed: tensor shape: [1200,1200,3] dtype: float32 
+2022-08-04 09:13:07 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996871} 
+2022-08-04 09:13:07 STATE: test-node.js event: image 
+2022-08-04 09:13:07 STATE: test-node.js event: detect 
+2022-08-04 09:13:07 STATE: test-node.js passed: tensor shape: [1,1200,1200,4] dtype: int32 
+2022-08-04 09:13:07 INFO:  test-node.js test default 
+2022-08-04 09:13:07 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-08-04 09:13:07 STATE: test-node.js event: image 
+2022-08-04 09:13:07 STATE: test-node.js event: detect 
+2022-08-04 09:13:07 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:07 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:07 DATA:  test-node.js  result: performance: load: null total: 212 
+2022-08-04 09:13:07 STATE: test-node.js passed: default result face match 1 female 0.97 
+2022-08-04 09:13:07 INFO:  test-node.js test sync 
+2022-08-04 09:13:08 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-08-04 09:13:08 STATE: test-node.js event: image 
+2022-08-04 09:13:08 STATE: test-node.js event: detect 
+2022-08-04 09:13:08 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:08 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:08 DATA:  test-node.js  result: performance: load: null total: 207 
+2022-08-04 09:13:08 STATE: test-node.js passed: default sync 1 female 0.97 
+2022-08-04 09:13:08 INFO:  test-node.js test: image process 
+2022-08-04 09:13:08 STATE: test-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-08-04 09:13:08 STATE: test-node.js passed: image input null [1,256,256,3] 
+2022-08-04 09:13:08 INFO:  test-node.js test: image null 
+2022-08-04 09:13:08 STATE: test-node.js passed: invalid input could not convert input to tensor 
+2022-08-04 09:13:08 INFO:  test-node.js test face similarity 
+2022-08-04 09:13:08 STATE: test-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-08-04 09:13:08 STATE: test-node.js event: image 
+2022-08-04 09:13:08 STATE: test-node.js event: detect 
+2022-08-04 09:13:08 STATE: test-node.js passed: detect: samples/in/ai-face.jpg default 
+2022-08-04 09:13:08 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
+2022-08-04 09:13:08 DATA:  test-node.js  result: performance: load: null total: 210 
+2022-08-04 09:13:08 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-08-04 09:13:08 STATE: test-node.js event: image 
+2022-08-04 09:13:08 STATE: test-node.js event: detect 
+2022-08-04 09:13:08 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:08 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:08 DATA:  test-node.js  result: performance: load: null total: 219 
+2022-08-04 09:13:09 STATE: test-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
+2022-08-04 09:13:09 STATE: test-node.js event: image 
+2022-08-04 09:13:09 STATE: test-node.js event: detect 
+2022-08-04 09:13:09 STATE: test-node.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:09 DATA:  test-node.js  result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":7} 
+2022-08-04 09:13:09 DATA:  test-node.js  result: performance: load: null total: 199 
+2022-08-04 09:13:09 STATE: test-node.js passed: face descriptor 
+2022-08-04 09:13:09 STATE: test-node.js passed: face similarity {"similarity":[1,0.44727452329649126,0.5567935850640406],"descriptors":[1024,1024,1024]} 
+2022-08-04 09:13:09 INFO:  test-node.js test face matching 
+2022-08-04 09:13:09 STATE: test-node.js passed: face database 40 
+2022-08-04 09:13:09 STATE: test-node.js passed: face match {"first":{"index":4,"similarity":0.7827852615252829}} {"second":{"index":4,"similarity":0.5002052633015844}} {"third":{"index":4,"similarity":0.5401587887998899}} 
+2022-08-04 09:13:09 INFO:  test-node.js test object 
+2022-08-04 09:13:09 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-08-04 09:13:09 STATE: test-node.js event: image 
+2022-08-04 09:13:09 STATE: test-node.js event: detect 
+2022-08-04 09:13:09 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:09 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:09 DATA:  test-node.js  result: performance: load: null total: 207 
+2022-08-04 09:13:09 STATE: test-node.js passed: object result match 
+2022-08-04 09:13:09 INFO:  test-node.js test sensitive 
+2022-08-04 09:13:09 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-08-04 09:13:09 STATE: test-node.js event: image 
+2022-08-04 09:13:10 STATE: test-node.js event: detect 
+2022-08-04 09:13:10 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:10 DATA:  test-node.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:10 DATA:  test-node.js  result: performance: load: null total: 229 
+2022-08-04 09:13:10 STATE: test-node.js passed: sensitive result match 
+2022-08-04 09:13:10 STATE: test-node.js passed: sensitive face result match 
+2022-08-04 09:13:10 STATE: test-node.js passed: sensitive face emotion result [{"score":0.59,"emotion":"angry"},{"score":0.29,"emotion":"fear"}] 
+2022-08-04 09:13:10 STATE: test-node.js passed: sensitive body result match 
+2022-08-04 09:13:10 STATE: test-node.js passed: sensitive hand result match 
+2022-08-04 09:13:10 INFO:  test-node.js test detectors 
+2022-08-04 09:13:10 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-08-04 09:13:10 STATE: test-node.js event: image 
+2022-08-04 09:13:10 STATE: test-node.js event: detect 
+2022-08-04 09:13:10 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:10 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:10 DATA:  test-node.js  result: performance: load: null total: 141 
+2022-08-04 09:13:10 STATE: test-node.js passed: detector result face match 
+2022-08-04 09:13:10 STATE: test-node.js passed: detector result hand match 
+2022-08-04 09:13:10 INFO:  test-node.js test: multi-instance 
+2022-08-04 09:13:10 STATE: test-node.js event: image 
+2022-08-04 09:13:10 STATE: test-node.js event: detect 
+2022-08-04 09:13:10 STATE: test-node.js passed: detect: random default 
+2022-08-04 09:13:10 DATA:  test-node.js  result: face: 0 body: 1 hand: 0 gesture: 0 object: 0 person: 0 {} {} {"score":0.07,"keypoints":15} 
+2022-08-04 09:13:10 DATA:  test-node.js  result: performance: load: null total: 140 
+2022-08-04 09:13:10 INFO:  test-node.js test: first instance 
+2022-08-04 09:13:10 STATE: test-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
+2022-08-04 09:13:10 STATE: test-node.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:10 DATA:  test-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:10 DATA:  test-node.js  result: performance: load: null total: 146 
+2022-08-04 09:13:10 INFO:  test-node.js test: second instance 
+2022-08-04 09:13:10 STATE: test-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
+2022-08-04 09:13:11 STATE: test-node.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:11 DATA:  test-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:11 DATA:  test-node.js  result: performance: load: null total: 135 
+2022-08-04 09:13:11 INFO:  test-node.js test: concurrent 
+2022-08-04 09:13:11 STATE: test-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-08-04 09:13:11 STATE: test-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-08-04 09:13:11 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-08-04 09:13:11 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-08-04 09:13:11 STATE: test-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
+2022-08-04 09:13:11 STATE: test-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
+2022-08-04 09:13:11 STATE: test-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-08-04 09:13:11 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-08-04 09:13:12 STATE: test-node.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289024} 
+2022-08-04 09:13:12 STATE: test-node.js event: image 
+2022-08-04 09:13:12 STATE: test-node.js event: image 
+2022-08-04 09:13:12 STATE: test-node.js event: image 
+2022-08-04 09:13:13 STATE: test-node.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:13 DATA:  test-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:13 DATA:  test-node.js  result: performance: load: null total: 1440 
+2022-08-04 09:13:13 STATE: test-node.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:13 DATA:  test-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:13 DATA:  test-node.js  result: performance: load: null total: 1440 
+2022-08-04 09:13:13 STATE: test-node.js passed: detect: samples/in/ai-face.jpg default 
+2022-08-04 09:13:13 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
+2022-08-04 09:13:13 DATA:  test-node.js  result: performance: load: null total: 1581 
+2022-08-04 09:13:13 STATE: test-node.js passed: detect: samples/in/ai-face.jpg default 
+2022-08-04 09:13:13 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
+2022-08-04 09:13:13 DATA:  test-node.js  result: performance: load: null total: 1581 
+2022-08-04 09:13:13 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:13 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:13 DATA:  test-node.js  result: performance: load: null total: 1581 
+2022-08-04 09:13:13 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:13 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:13 DATA:  test-node.js  result: performance: load: null total: 1581 
+2022-08-04 09:13:13 STATE: test-node.js event: detect 
+2022-08-04 09:13:13 STATE: test-node.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:13 DATA:  test-node.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:13 DATA:  test-node.js  result: performance: load: null total: 1278 
+2022-08-04 09:13:13 STATE: test-node.js event: detect 
+2022-08-04 09:13:13 STATE: test-node.js event: detect 
+2022-08-04 09:13:13 STATE: test-node.js passed: detect: samples/in/ai-face.jpg default 
+2022-08-04 09:13:13 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
+2022-08-04 09:13:13 DATA:  test-node.js  result: performance: load: null total: 1278 
+2022-08-04 09:13:13 STATE: test-node.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:13 DATA:  test-node.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:13 DATA:  test-node.js  result: performance: load: null total: 1278 
+2022-08-04 09:13:13 INFO:  test-node.js test: monkey-patch 
+2022-08-04 09:13:13 STATE: test-node.js event: image 
+2022-08-04 09:13:13 STATE: test-node.js event: detect 
+2022-08-04 09:13:13 STATE: test-node.js passed: monkey patch 
+2022-08-04 09:13:13 STATE: test-node.js passed: segmentation [65536] 
+2022-08-04 09:13:13 STATE: test-node.js passeed: equal usage 
+2022-08-04 09:13:13 INFO:  test-node.js test: input compare 
+2022-08-04 09:13:13 STATE: test-node.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-08-04 09:13:13 STATE: test-node.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796864} 
+2022-08-04 09:13:13 STATE: test-node.js passed: image compare 0 23.275441687091504 
+2022-08-04 09:13:13 INFO:  test-node.js events: {"image":21,"detect":21,"warmup":2} 
+2022-08-04 09:13:13 INFO:  test-node.js tensors 1927 
+2022-08-04 09:13:13 INFO:  test-node.js test complete: 9854 ms 
+2022-08-04 09:13:13 INFO:  
+2022-08-04 09:13:13 INFO:  test-node-gpu.js start 
+2022-08-04 09:13:14 INFO:  test-node-gpu.js test: configuration validation 
+2022-08-04 09:13:14 STATE: test-node-gpu.js passed: configuration default validation [] 
+2022-08-04 09:13:14 STATE: test-node-gpu.js passed: configuration invalid validation [{"reason":"unknown property","where":"config.invalid = true"}] 
+2022-08-04 09:13:14 INFO:  test-node-gpu.js test: model load 
+2022-08-04 09:13:14 STATE: test-node-gpu.js passed: models loaded 22 12 [{"name":"ssrnetage","loaded":false,"url":null},{"name":"gear","loaded":false,"url":null},{"name":"blazeposedetect","loaded":false,"url":null},{"name":"blazepose","loaded":false,"url":null},{"name":"centernet","loaded":true,"url":"file://models/mb3-centernet.json"},{"name":"efficientpose","loaded":false,"url":null},{"name":"mobilefacenet","loaded":false,"url":null},{"name":"emotion","loaded":true,"url":"file://models/emotion.json"},{"name":"facedetect","loaded":true,"url":"file://models/blazeface.json"},{"name":"faceiris","loaded":true,"url":"file://models/iris.json"},{"name":"facemesh","loaded":true,"url":"file://models/facemesh.json"},{"name":"faceres","loaded":true,"url":"file://models/faceres.json"},{"name":"ssrnetgender","loaded":false,"url":null},{"name":"handpose","loaded":false,"url":null},{"name":"handskeleton","loaded":true,"url":"file://models/handlandmark-full.json"},{"name":"handtrack","loaded":true,"url":"file://models/handtrack.json"},{"name":"liveness","loaded":true,"url":"file://models/liveness.json"},{"name":"movenet","loaded":true,"url":"file://models/movenet-lightning.json"},{"name":"nanodet","loaded":false,"url":null},{"name":"posenet","loaded":false,"url":null},{"name":"segmentation","loaded":true,"url":"file://models/selfie.json"},{"name":"antispoof","loaded":true,"url":"file://models/antispoof.json"}] 
+2022-08-04 09:13:14 INFO:  test-node-gpu.js test: warmup 
+2022-08-04 09:13:14 STATE: test-node-gpu.js passed: create human 
+2022-08-04 09:13:14 INFO:  test-node-gpu.js human version: 2.9.1 
+2022-08-04 09:13:14 INFO:  test-node-gpu.js platform: linux x64 agent: NodeJS v16.15.0 
+2022-08-04 09:13:14 INFO:  test-node-gpu.js tfjs version: 3.19.0 
+2022-08-04 09:13:14 INFO:  test-node-gpu.js tensorflow binding version: 2.7.3-dev20220521 
+2022-08-04 09:13:14 STATE: test-node-gpu.js passed: set backend: tensorflow 
+2022-08-04 09:13:14 STATE: test-node-gpu.js tensors 1921 
+2022-08-04 09:13:14 STATE: test-node-gpu.js passed: load models 
+2022-08-04 09:13:14 STATE: test-node-gpu.js  result: defined models: 22 loaded models: 12 
+2022-08-04 09:13:14 STATE: test-node-gpu.js passed: warmup: none default 
+2022-08-04 09:13:14 DATA:  test-node-gpu.js  result: face: 0 body: 0 hand: 0 gesture: 0 object: 0 person: 0 {} {} {} 
+2022-08-04 09:13:14 DATA:  test-node-gpu.js  result: performance: load: null total: null 
+2022-08-04 09:13:14 STATE: test-node-gpu.js passed: warmup none result match 
+2022-08-04 09:13:15 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:19 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:19 STATE: test-node-gpu.js event: warmup 
+2022-08-04 09:13:19 STATE: test-node-gpu.js passed: warmup: face default 
+2022-08-04 09:13:19 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.42,"keypoints":4} 
+2022-08-04 09:13:19 DATA:  test-node-gpu.js  result: performance: load: null total: 3847 
+2022-08-04 09:13:19 STATE: test-node-gpu.js passed: warmup face result match 
+2022-08-04 09:13:19 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:19 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:19 STATE: test-node-gpu.js event: warmup 
+2022-08-04 09:13:19 STATE: test-node-gpu.js passed: warmup: body default 
+2022-08-04 09:13:19 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:19 DATA:  test-node-gpu.js  result: performance: load: null total: 240 
+2022-08-04 09:13:19 STATE: test-node-gpu.js passed: warmup body result match 
+2022-08-04 09:13:19 STATE: test-node-gpu.js details: {"face":{"boxScore":0.92,"faceScore":1,"age":23.7,"gender":"female","genderScore":0.97},"emotion":[{"score":0.63,"emotion":"angry"},{"score":0.22,"emotion":"fear"}],"body":{"score":0.92,"keypoints":17},"hand":{"boxScore":0.52,"fingerScore":0.73,"keypoints":21},"gestures":[{"face":0,"gesture":"facing right"},{"face":0,"gesture":"mouth 10% open"},{"hand":0,"gesture":"pinky forward"},{"hand":0,"gesture":"palm up"},{"hand":0,"gesture":"open palm"},{"iris":0,"gesture":"looking left"},{"iris":0,"gesture":"looking up"}]} 
+2022-08-04 09:13:19 INFO:  test-node-gpu.js test: details verification 
+2022-08-04 09:13:19 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-08-04 09:13:19 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:20 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:20 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:20 DATA:  test-node-gpu.js  result: performance: load: null total: 224 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details face length 1 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details face score 1 0.93 1 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details face age/gender 23.7 female 0.97 85.47 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details face arrays 4 478 1024 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details face emotion 2 {"score":0.59,"emotion":"angry"} 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details face anti-spoofing 0.79 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details face liveness 0.83 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details body length 1 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details body 0.92 17 6 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details hand length 1 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details hand 0.51 0.73 point 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details hand arrays 21 5 7 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details gesture length 7 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details gesture first {"face":0,"gesture":"facing right"} 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details object length 1 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: details object 0.72 person 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996928} 
+2022-08-04 09:13:20 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:20 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: tensor shape: [1,1200,1200,4] dtype: float32 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1200,1200,4] {"checksum":1371996928} 
+2022-08-04 09:13:20 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:20 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:20 STATE: test-node-gpu.js passed: tensor shape: [1200,1200,4] dtype: float32 
+2022-08-04 09:13:21 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-08-04 09:13:21 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:21 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:21 STATE: test-node-gpu.js passed: tensor shape: [1,1200,1200,3] dtype: float32 
+2022-08-04 09:13:21 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1200,1200,3] {"checksum":1004796928} 
+2022-08-04 09:13:21 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:21 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:21 STATE: test-node-gpu.js passed: tensor shape: [1200,1200,3] dtype: float32 
+2022-08-04 09:13:22 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996871} 
+2022-08-04 09:13:22 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:22 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:22 STATE: test-node-gpu.js passed: tensor shape: [1,1200,1200,4] dtype: int32 
+2022-08-04 09:13:22 INFO:  test-node-gpu.js test default 
+2022-08-04 09:13:22 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-08-04 09:13:22 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:22 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:22 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:22 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:22 DATA:  test-node-gpu.js  result: performance: load: null total: 238 
+2022-08-04 09:13:22 STATE: test-node-gpu.js passed: default result face match 1 female 0.97 
+2022-08-04 09:13:22 INFO:  test-node-gpu.js test sync 
+2022-08-04 09:13:22 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-08-04 09:13:22 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:23 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:23 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:23 DATA:  test-node-gpu.js  result: performance: load: null total: 188 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: default sync 1 female 0.97 
+2022-08-04 09:13:23 INFO:  test-node-gpu.js test: image process 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: image input null [1,256,256,3] 
+2022-08-04 09:13:23 INFO:  test-node-gpu.js test: image null 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: invalid input could not convert input to tensor 
+2022-08-04 09:13:23 INFO:  test-node-gpu.js test face similarity 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-08-04 09:13:23 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:23 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: detect: samples/in/ai-face.jpg default 
+2022-08-04 09:13:23 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
+2022-08-04 09:13:23 DATA:  test-node-gpu.js  result: performance: load: null total: 164 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-08-04 09:13:23 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:23 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:23 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:23 DATA:  test-node-gpu.js  result: performance: load: null total: 196 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
+2022-08-04 09:13:23 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:23 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:23 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":7} 
+2022-08-04 09:13:23 DATA:  test-node-gpu.js  result: performance: load: null total: 171 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: face descriptor 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: face similarity {"similarity":[1,0.447238756461232,0.556914029877052],"descriptors":[1024,1024,1024]} 
+2022-08-04 09:13:23 INFO:  test-node-gpu.js test face matching 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: face database 40 
+2022-08-04 09:13:23 STATE: test-node-gpu.js passed: face match {"first":{"index":4,"similarity":0.7828184453007331}} {"second":{"index":4,"similarity":0.5001334216773398}} {"third":{"index":4,"similarity":0.5403054967489764}} 
+2022-08-04 09:13:23 INFO:  test-node-gpu.js test object 
+2022-08-04 09:13:24 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-08-04 09:13:24 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:24 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:24 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:24 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:24 DATA:  test-node-gpu.js  result: performance: load: null total: 194 
+2022-08-04 09:13:24 STATE: test-node-gpu.js passed: object result match 
+2022-08-04 09:13:24 INFO:  test-node-gpu.js test sensitive 
+2022-08-04 09:13:24 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-08-04 09:13:24 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:24 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:24 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:24 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 2 gesture: 9 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:24 DATA:  test-node-gpu.js  result: performance: load: null total: 196 
+2022-08-04 09:13:24 STATE: test-node-gpu.js passed: sensitive result match 
+2022-08-04 09:13:24 STATE: test-node-gpu.js passed: sensitive face result match 
+2022-08-04 09:13:24 STATE: test-node-gpu.js passed: sensitive face emotion result [{"score":0.59,"emotion":"angry"},{"score":0.29,"emotion":"fear"}] 
+2022-08-04 09:13:24 STATE: test-node-gpu.js passed: sensitive body result match 
+2022-08-04 09:13:24 STATE: test-node-gpu.js passed: sensitive hand result match 
+2022-08-04 09:13:24 INFO:  test-node-gpu.js test detectors 
+2022-08-04 09:13:25 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-08-04 09:13:25 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:25 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:25 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:25 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:25 DATA:  test-node-gpu.js  result: performance: load: null total: 116 
+2022-08-04 09:13:25 STATE: test-node-gpu.js passed: detector result face match 
+2022-08-04 09:13:25 STATE: test-node-gpu.js passed: detector result hand match 
+2022-08-04 09:13:25 INFO:  test-node-gpu.js test: multi-instance 
+2022-08-04 09:13:25 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:25 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:25 STATE: test-node-gpu.js passed: detect: random default 
+2022-08-04 09:13:25 DATA:  test-node-gpu.js  result: face: 0 body: 1 hand: 0 gesture: 0 object: 0 person: 0 {} {} {"score":0.07,"keypoints":15} 
+2022-08-04 09:13:25 DATA:  test-node-gpu.js  result: performance: load: null total: 110 
+2022-08-04 09:13:25 INFO:  test-node-gpu.js test: first instance 
+2022-08-04 09:13:25 STATE: test-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
+2022-08-04 09:13:25 STATE: test-node-gpu.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:25 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:25 DATA:  test-node-gpu.js  result: performance: load: null total: 108 
+2022-08-04 09:13:25 INFO:  test-node-gpu.js test: second instance 
+2022-08-04 09:13:25 STATE: test-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
+2022-08-04 09:13:25 STATE: test-node-gpu.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:25 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:25 DATA:  test-node-gpu.js  result: performance: load: null total: 105 
+2022-08-04 09:13:25 INFO:  test-node-gpu.js test: concurrent 
+2022-08-04 09:13:25 STATE: test-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-08-04 09:13:25 STATE: test-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-08-04 09:13:26 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-08-04 09:13:26 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-08-04 09:13:26 STATE: test-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
+2022-08-04 09:13:26 STATE: test-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
+2022-08-04 09:13:26 STATE: test-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-08-04 09:13:26 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-08-04 09:13:26 STATE: test-node-gpu.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151289056} 
+2022-08-04 09:13:26 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:26 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:26 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:27 STATE: test-node-gpu.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: performance: load: null total: 1079 
+2022-08-04 09:13:27 STATE: test-node-gpu.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: performance: load: null total: 1079 
+2022-08-04 09:13:27 STATE: test-node-gpu.js passed: detect: samples/in/ai-face.jpg default 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: performance: load: null total: 1151 
+2022-08-04 09:13:27 STATE: test-node-gpu.js passed: detect: samples/in/ai-face.jpg default 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: performance: load: null total: 1151 
+2022-08-04 09:13:27 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: performance: load: null total: 1151 
+2022-08-04 09:13:27 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: performance: load: null total: 1151 
+2022-08-04 09:13:27 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:27 STATE: test-node-gpu.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: performance: load: null total: 831 
+2022-08-04 09:13:27 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:27 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:27 STATE: test-node-gpu.js passed: detect: samples/in/ai-face.jpg default 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: performance: load: null total: 831 
+2022-08-04 09:13:27 STATE: test-node-gpu.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:27 DATA:  test-node-gpu.js  result: performance: load: null total: 831 
+2022-08-04 09:13:27 INFO:  test-node-gpu.js test: monkey-patch 
+2022-08-04 09:13:27 STATE: test-node-gpu.js event: image 
+2022-08-04 09:13:27 STATE: test-node-gpu.js event: detect 
+2022-08-04 09:13:27 STATE: test-node-gpu.js passed: monkey patch 
+2022-08-04 09:13:28 STATE: test-node-gpu.js passed: segmentation [65536] 
+2022-08-04 09:13:28 STATE: test-node-gpu.js passeed: equal usage 
+2022-08-04 09:13:28 INFO:  test-node-gpu.js test: input compare 
+2022-08-04 09:13:28 STATE: test-node-gpu.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34696120} 
+2022-08-04 09:13:28 STATE: test-node-gpu.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1004796928} 
+2022-08-04 09:13:28 STATE: test-node-gpu.js passed: image compare 0 23.275441687091504 
+2022-08-04 09:13:28 INFO:  test-node-gpu.js events: {"image":21,"detect":21,"warmup":2} 
+2022-08-04 09:13:28 INFO:  test-node-gpu.js tensors 1927 
+2022-08-04 09:13:28 INFO:  test-node-gpu.js test complete: 13503 ms 
+2022-08-04 09:13:29 INFO:  
+2022-08-04 09:13:29 INFO:  test-node-wasm.js start 
+2022-08-04 09:13:29 STATE: test-node-wasm.js passed: model server: https://vladmandic.github.io/human/models/ 
+2022-08-04 09:13:29 INFO:  test-node-wasm.js test: configuration validation 
+2022-08-04 09:13:29 STATE: test-node-wasm.js passed: configuration default validation [] 
+2022-08-04 09:13:29 STATE: test-node-wasm.js passed: configuration invalid validation [{"reason":"unknown property","where":"config.invalid = true"}] 
+2022-08-04 09:13:29 INFO:  test-node-wasm.js test: model load 
+2022-08-04 09:13:31 STATE: test-node-wasm.js passed: models loaded 22 12 [{"name":"ssrnetage","loaded":false,"url":null},{"name":"gear","loaded":false,"url":null},{"name":"blazeposedetect","loaded":false,"url":null},{"name":"blazepose","loaded":false,"url":null},{"name":"centernet","loaded":true,"url":"https://vladmandic.github.io/human/models/mb3-centernet.json"},{"name":"efficientpose","loaded":false,"url":null},{"name":"mobilefacenet","loaded":false,"url":null},{"name":"emotion","loaded":true,"url":"https://vladmandic.github.io/human/models/emotion.json"},{"name":"facedetect","loaded":true,"url":"https://vladmandic.github.io/human/models/blazeface.json"},{"name":"faceiris","loaded":true,"url":"https://vladmandic.github.io/human/models/iris.json"},{"name":"facemesh","loaded":true,"url":"https://vladmandic.github.io/human/models/facemesh.json"},{"name":"faceres","loaded":true,"url":"https://vladmandic.github.io/human/models/faceres.json"},{"name":"ssrnetgender","loaded":false,"url":null},{"name":"handpose","loaded":false,"url":null},{"name":"handskeleton","loaded":true,"url":"https://vladmandic.github.io/human/models/handlandmark-full.json"},{"name":"handtrack","loaded":true,"url":"https://vladmandic.github.io/human/models/handtrack.json"},{"name":"liveness","loaded":true,"url":"https://vladmandic.github.io/human/models/liveness.json"},{"name":"movenet","loaded":true,"url":"https://vladmandic.github.io/human/models/movenet-lightning.json"},{"name":"nanodet","loaded":false,"url":null},{"name":"posenet","loaded":false,"url":null},{"name":"segmentation","loaded":true,"url":"https://vladmandic.github.io/human/models/selfie.json"},{"name":"antispoof","loaded":true,"url":"https://vladmandic.github.io/human/models/antispoof.json"}] 
+2022-08-04 09:13:31 INFO:  test-node-wasm.js test: warmup 
+2022-08-04 09:13:31 STATE: test-node-wasm.js passed: create human 
+2022-08-04 09:13:31 INFO:  test-node-wasm.js human version: 2.9.1 
+2022-08-04 09:13:31 INFO:  test-node-wasm.js platform: linux x64 agent: NodeJS v16.15.0 
+2022-08-04 09:13:31 INFO:  test-node-wasm.js tfjs version: 3.19.0 
+2022-08-04 09:13:31 STATE: test-node-wasm.js passed: set backend: wasm 
+2022-08-04 09:13:31 STATE: test-node-wasm.js tensors 1921 
+2022-08-04 09:13:31 STATE: test-node-wasm.js passed: load models 
+2022-08-04 09:13:31 STATE: test-node-wasm.js  result: defined models: 22 loaded models: 12 
+2022-08-04 09:13:31 STATE: test-node-wasm.js passed: warmup: none default 
+2022-08-04 09:13:31 DATA:  test-node-wasm.js  result: face: 0 body: 0 hand: 0 gesture: 0 object: 0 person: 0 {} {} {} 
+2022-08-04 09:13:31 DATA:  test-node-wasm.js  result: performance: load: null total: null 
+2022-08-04 09:13:31 STATE: test-node-wasm.js passed: warmup none result match 
+2022-08-04 09:13:31 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:31 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:31 STATE: test-node-wasm.js event: warmup 
+2022-08-04 09:13:31 STATE: test-node-wasm.js passed: warmup: face default 
+2022-08-04 09:13:31 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
+2022-08-04 09:13:31 DATA:  test-node-wasm.js  result: performance: load: null total: 595 
+2022-08-04 09:13:31 STATE: test-node-wasm.js passed: warmup face result match 
+2022-08-04 09:13:32 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:32 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:32 STATE: test-node-wasm.js event: warmup 
+2022-08-04 09:13:32 STATE: test-node-wasm.js passed: warmup: body default 
+2022-08-04 09:13:32 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:32 DATA:  test-node-wasm.js  result: performance: load: null total: 421 
+2022-08-04 09:13:32 STATE: test-node-wasm.js passed: warmup body result match 
+2022-08-04 09:13:32 STATE: test-node-wasm.js details: {"face":{"boxScore":0.93,"faceScore":1,"age":23.7,"gender":"female","genderScore":0.97},"emotion":[{"score":0.59,"emotion":"angry"},{"score":0.29,"emotion":"fear"}],"body":{"score":0.92,"keypoints":17},"hand":{"boxScore":0.51,"fingerScore":0.73,"keypoints":21},"gestures":[{"face":0,"gesture":"facing right"},{"face":0,"gesture":"mouth 21% open"},{"hand":0,"gesture":"pinky forward"},{"hand":0,"gesture":"palm up"},{"hand":0,"gesture":"open palm"},{"iris":0,"gesture":"looking left"},{"iris":0,"gesture":"looking up"}]} 
+2022-08-04 09:13:32 INFO:  test-node-wasm.js test: details verification 
+2022-08-04 09:13:32 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-08-04 09:13:32 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:33 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:33 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 7 object: 1 person: 1 {"score":1,"age":23.7,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:33 DATA:  test-node-wasm.js  result: performance: load: null total: 399 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details face length 1 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details face score 1 0.93 1 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details face age/gender 23.7 female 0.97 85.47 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details face arrays 4 478 1024 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details face emotion 2 {"score":0.59,"emotion":"angry"} 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details face anti-spoofing 0.79 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details face liveness 0.83 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details body length 1 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details body 0.92 17 6 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details hand length 1 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details hand 0.51 0.73 point 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details hand arrays 21 5 7 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details gesture length 7 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details gesture first {"face":0,"gesture":"facing right"} 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details object length 1 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: details object 0.72 person 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1413675264} 
+2022-08-04 09:13:33 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:33 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:33 STATE: test-node-wasm.js passed: tensor shape: [1,1200,1200,4] dtype: float32 
+2022-08-04 09:13:34 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1200,1200,4] {"checksum":1413675264} 
+2022-08-04 09:13:34 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:34 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:34 STATE: test-node-wasm.js passed: tensor shape: [1200,1200,4] dtype: float32 
+2022-08-04 09:13:34 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-08-04 09:13:34 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:35 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:35 STATE: test-node-wasm.js passed: tensor shape: [1,1200,1200,3] dtype: float32 
+2022-08-04 09:13:35 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1200,1200,3] {"checksum":1038921856} 
+2022-08-04 09:13:35 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:36 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:36 STATE: test-node-wasm.js passed: tensor shape: [1200,1200,3] dtype: float32 
+2022-08-04 09:13:36 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,4] {"checksum":1371996871} 
+2022-08-04 09:13:36 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:36 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:36 STATE: test-node-wasm.js passed: tensor shape: [1,1200,1200,4] dtype: int32 
+2022-08-04 09:13:36 INFO:  test-node-wasm.js test default 
+2022-08-04 09:13:37 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-08-04 09:13:37 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:37 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:37 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:37 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:37 DATA:  test-node-wasm.js  result: performance: load: null total: 471 
+2022-08-04 09:13:37 STATE: test-node-wasm.js passed: default result face match 1 female 0.97 
+2022-08-04 09:13:37 INFO:  test-node-wasm.js test sync 
+2022-08-04 09:13:37 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-08-04 09:13:37 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:38 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:38 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:38 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:38 DATA:  test-node-wasm.js  result: performance: load: null total: 394 
+2022-08-04 09:13:38 STATE: test-node-wasm.js passed: default sync 1 female 0.97 
+2022-08-04 09:13:38 INFO:  test-node-wasm.js test: image process 
+2022-08-04 09:13:38 STATE: test-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
+2022-08-04 09:13:38 STATE: test-node-wasm.js passed: image input null [1,256,256,3] 
+2022-08-04 09:13:38 INFO:  test-node-wasm.js test: image null 
+2022-08-04 09:13:38 STATE: test-node-wasm.js passed: invalid input could not convert input to tensor 
+2022-08-04 09:13:38 INFO:  test-node-wasm.js test face similarity 
+2022-08-04 09:13:38 STATE: test-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
+2022-08-04 09:13:38 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:38 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:38 STATE: test-node-wasm.js passed: detect: samples/in/ai-face.jpg default 
+2022-08-04 09:13:38 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 6 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":3} 
+2022-08-04 09:13:38 DATA:  test-node-wasm.js  result: performance: load: null total: 372 
+2022-08-04 09:13:38 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-08-04 09:13:38 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:39 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:39 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:39 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:39 DATA:  test-node-wasm.js  result: performance: load: null total: 472 
+2022-08-04 09:13:39 STATE: test-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
+2022-08-04 09:13:39 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:39 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:39 STATE: test-node-wasm.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:39 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 4 object: 1 person: 1 {"score":1,"age":23.5,"gender":"female"} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":7} 
+2022-08-04 09:13:39 DATA:  test-node-wasm.js  result: performance: load: null total: 386 
+2022-08-04 09:13:39 STATE: test-node-wasm.js passed: face descriptor 
+2022-08-04 09:13:39 STATE: test-node-wasm.js passed: face similarity {"similarity":[1,0.5266119940661309,0.4858842904087851],"descriptors":[1024,1024,1024]} 
+2022-08-04 09:13:39 INFO:  test-node-wasm.js test face matching 
+2022-08-04 09:13:39 STATE: test-node-wasm.js passed: face database 40 
+2022-08-04 09:13:39 STATE: test-node-wasm.js passed: face match {"first":{"index":4,"similarity":0.7827852754786533}} {"second":{"index":4,"similarity":0.5660821189104794}} {"third":{"index":4,"similarity":0.45074189882665594}} 
+2022-08-04 09:13:39 INFO:  test-node-wasm.js test object 
+2022-08-04 09:13:40 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-08-04 09:13:40 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:40 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:40 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:40 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 8 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:40 DATA:  test-node-wasm.js  result: performance: load: null total: 431 
+2022-08-04 09:13:40 STATE: test-node-wasm.js passed: object result match 
+2022-08-04 09:13:40 INFO:  test-node-wasm.js test sensitive 
+2022-08-04 09:13:40 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-08-04 09:13:40 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:41 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:41 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:41 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 2 gesture: 10 object: 1 person: 1 {"score":1,"age":29.6,"gender":"female"} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:41 DATA:  test-node-wasm.js  result: performance: load: null total: 442 
+2022-08-04 09:13:41 STATE: test-node-wasm.js passed: sensitive result match 
+2022-08-04 09:13:41 STATE: test-node-wasm.js passed: sensitive face result match 
+2022-08-04 09:13:41 STATE: test-node-wasm.js passed: sensitive face emotion result [{"score":0.46,"emotion":"neutral"},{"score":0.24,"emotion":"fear"},{"score":0.17,"emotion":"sad"}] 
+2022-08-04 09:13:41 STATE: test-node-wasm.js passed: sensitive body result match 
+2022-08-04 09:13:41 STATE: test-node-wasm.js passed: sensitive hand result match 
+2022-08-04 09:13:41 INFO:  test-node-wasm.js test detectors 
+2022-08-04 09:13:41 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-08-04 09:13:41 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:41 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:41 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:41 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:41 DATA:  test-node-wasm.js  result: performance: load: null total: 269 
+2022-08-04 09:13:41 STATE: test-node-wasm.js passed: detector result face match 
+2022-08-04 09:13:41 STATE: test-node-wasm.js passed: detector result hand match 
+2022-08-04 09:13:41 INFO:  test-node-wasm.js test: multi-instance 
+2022-08-04 09:13:41 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:42 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:42 STATE: test-node-wasm.js passed: detect: random default 
+2022-08-04 09:13:42 DATA:  test-node-wasm.js  result: face: 0 body: 1 hand: 0 gesture: 0 object: 0 person: 0 {} {} {"score":0.07,"keypoints":15} 
+2022-08-04 09:13:42 DATA:  test-node-wasm.js  result: performance: load: null total: 239 
+2022-08-04 09:13:42 INFO:  test-node-wasm.js test: first instance 
+2022-08-04 09:13:42 STATE: test-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
+2022-08-04 09:13:42 STATE: test-node-wasm.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:42 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:42 DATA:  test-node-wasm.js  result: performance: load: null total: 280 
+2022-08-04 09:13:42 INFO:  test-node-wasm.js test: second instance 
+2022-08-04 09:13:42 STATE: test-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
+2022-08-04 09:13:42 STATE: test-node-wasm.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:42 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:42 DATA:  test-node-wasm.js  result: performance: load: null total: 255 
+2022-08-04 09:13:42 INFO:  test-node-wasm.js test: concurrent 
+2022-08-04 09:13:42 STATE: test-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
+2022-08-04 09:13:42 STATE: test-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
+2022-08-04 09:13:43 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-08-04 09:13:43 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-08-04 09:13:43 STATE: test-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
+2022-08-04 09:13:43 STATE: test-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
+2022-08-04 09:13:43 STATE: test-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
+2022-08-04 09:13:44 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-08-04 09:13:44 STATE: test-node-wasm.js passed: load image: samples/in/ai-upper.jpg [1,720,688,3] {"checksum":151155104} 
+2022-08-04 09:13:44 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:44 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:44 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:46 STATE: test-node-wasm.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: performance: load: null total: 2455 
+2022-08-04 09:13:46 STATE: test-node-wasm.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: performance: load: null total: 2455 
+2022-08-04 09:13:46 STATE: test-node-wasm.js passed: detect: samples/in/ai-face.jpg default 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: performance: load: null total: 2721 
+2022-08-04 09:13:46 STATE: test-node-wasm.js passed: detect: samples/in/ai-face.jpg default 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: performance: load: null total: 2721 
+2022-08-04 09:13:46 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: performance: load: null total: 2721 
+2022-08-04 09:13:46 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: performance: load: null total: 2721 
+2022-08-04 09:13:46 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:46 STATE: test-node-wasm.js passed: detect: samples/in/ai-upper.jpg default 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 0 gesture: 0 object: 1 person: 1 {"score":0.96} {"score":0.71,"class":"person"} {"score":0.75,"keypoints":16} 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: performance: load: null total: 2334 
+2022-08-04 09:13:46 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:46 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:46 STATE: test-node-wasm.js passed: detect: samples/in/ai-face.jpg default 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 2 object: 1 person: 1 {"score":0.91} {"score":0.82,"class":"person"} {"score":0.47,"keypoints":17} 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: performance: load: null total: 2334 
+2022-08-04 09:13:46 STATE: test-node-wasm.js passed: detect: samples/in/ai-body.jpg default 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: face: 1 body: 1 hand: 1 gesture: 0 object: 1 person: 1 {"score":0.93} {"score":0.72,"class":"person"} {"score":0.92,"keypoints":17} 
+2022-08-04 09:13:46 DATA:  test-node-wasm.js  result: performance: load: null total: 2334 
+2022-08-04 09:13:46 INFO:  test-node-wasm.js test: monkey-patch 
+2022-08-04 09:13:46 STATE: test-node-wasm.js event: image 
+2022-08-04 09:13:46 STATE: test-node-wasm.js event: detect 
+2022-08-04 09:13:46 STATE: test-node-wasm.js passed: monkey patch 
+2022-08-04 09:13:46 STATE: test-node-wasm.js passed: segmentation [65536] 
+2022-08-04 09:13:46 STATE: test-node-wasm.js passeed: equal usage 
+2022-08-04 09:13:46 INFO:  test-node-wasm.js test: input compare 
+2022-08-04 09:13:46 STATE: test-node-wasm.js passed: load image: samples/in/ai-face.jpg [1,256,256,3] {"checksum":34697856} 
+2022-08-04 09:13:47 STATE: test-node-wasm.js passed: load image: samples/in/ai-body.jpg [1,1200,1200,3] {"checksum":1038921856} 
+2022-08-04 09:13:47 STATE: test-node-wasm.js passed: image compare 0 23.280073018790848 
+2022-08-04 09:13:47 INFO:  test-node-wasm.js events: {"image":21,"detect":21,"warmup":2} 
+2022-08-04 09:13:47 INFO:  test-node-wasm.js tensors 1929 
+2022-08-04 09:13:47 INFO:  test-node-wasm.js test complete: 17201 ms 
+2022-08-04 09:13:47 INFO:  all tests complete 
+2022-08-04 09:13:47 INFO:  failed: {"count":0,"messages":[]} 
+2022-08-04 09:13:47 INFO:  status: {"test":"test-node.js","passed":101,"failed":0} 
+2022-08-04 09:13:47 INFO:  status: {"test":"test-node-gpu.js","passed":101,"failed":0} 
+2022-08-04 09:13:47 INFO:  status: {"test":"test-node-wasm.js","passed":102,"failed":0} 
diff --git a/typedoc/classes/Human.html b/typedoc/classes/Human.html
index 4f633471..27bf5199 100644
--- a/typedoc/classes/Human.html
+++ b/typedoc/classes/Human.html
@@ -561,7 +561,7 @@ Returns similarity between two face descriptors normalized to 0..1 range where 0
 </div></li></ul></div>
 <h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Result.html" class="tsd-signature-type" data-tsd-kind="Interface">Result</a><span class="tsd-signature-symbol">&gt;</span></h4><aside class="tsd-sources">
 <ul>
-<li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L379">src/human.ts:379</a></li></ul></aside></li></ul></section>
+<li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L385">src/human.ts:385</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a id="emit" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>emit</span><a href="#emit" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class">
@@ -696,7 +696,7 @@ Interpolation is based on time since last known result so can be called independ
 <section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a id="profile" class="tsd-anchor"></a>
 <h3 class="tsd-anchor-link"><span>profile</span><a href="#profile" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></h3>
 <ul class="tsd-signatures tsd-kind-method tsd-parent-kind-class">
-<li class="tsd-signature tsd-anchor-link" id="profile.profile-1">profile<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><a href="../types/Input.html" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a>, userConfig<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Record</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">&gt;</span><a href="#profile.profile-1" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></li>
+<li class="tsd-signature tsd-anchor-link" id="profile.profile-1">profile<span class="tsd-signature-symbol">(</span>input<span class="tsd-signature-symbol">: </span><a href="../types/Input.html" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a>, userConfig<span class="tsd-signature-symbol">?: </span><span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">)</span><span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-symbol">{ </span>kernel<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>perc<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>time<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">&gt;</span><a href="#profile.profile-1" aria-label="Permalink" class="tsd-anchor-icon"><svg class="icon icon-tabler icon-tabler-link" viewBox="0 0 24 24" stroke-width="2" stroke="currentColor" fill="none" stroke-linecap="round" stroke-linejoin="round"><use href="#icon-anchor-a"></use><use href="#icon-anchor-b"></use><use href="#icon-anchor-c"></use></svg></a></li>
 <li class="tsd-description">
 <div class="tsd-comment tsd-typography"><p>Run detect with tensorflow profiling</p>
 <ul>
@@ -711,7 +711,7 @@ Interpolation is based on time since last known result so can be called independ
 <h5>input: <a href="../types/Input.html" class="tsd-signature-type" data-tsd-kind="Type alias">Input</a></h5></li>
 <li>
 <h5><code class="tsd-tag ts-flagOptional">Optional</code> userConfig: <span class="tsd-signature-type">Partial</span><span class="tsd-signature-symbol">&lt;</span><a href="../interfaces/Config.html" class="tsd-signature-type" data-tsd-kind="Interface">Config</a><span class="tsd-signature-symbol">&gt;</span></h5></li></ul></div>
-<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">Record</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">, </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">&gt;</span><span class="tsd-signature-symbol">&gt;</span></h4><aside class="tsd-sources">
+<h4 class="tsd-returns-title">Returns <span class="tsd-signature-type">Promise</span><span class="tsd-signature-symbol">&lt;</span><span class="tsd-signature-symbol">{ </span>kernel<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">string</span><span class="tsd-signature-symbol">; </span>perc<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol">; </span>time<span class="tsd-signature-symbol">: </span><span class="tsd-signature-type">number</span><span class="tsd-signature-symbol"> }</span><span class="tsd-signature-symbol">[]</span><span class="tsd-signature-symbol">&gt;</span></h4><aside class="tsd-sources">
 <ul>
 <li>Defined in <a href="https://github.com/vladmandic/human/blob/main/src/human.ts#L353">src/human.ts:353</a></li></ul></aside></li></ul></section>
 <section class="tsd-panel tsd-member tsd-kind-method tsd-parent-kind-class"><a id="reset" class="tsd-anchor"></a>
diff --git a/typedoc/interfaces/BodyKeypoint.html b/typedoc/interfaces/BodyKeypoint.html
index 8dcf39ef..146c9760 100644
--- a/typedoc/interfaces/BodyKeypoint.html
+++ b/typedoc/interfaces/BodyKeypoint.html
@@ -29,7 +29,7 @@
 <div class="tsd-accordion-details">
 <section class="tsd-index-section">
 <h3 class="tsd-index-heading">Properties</h3>
-<div class="tsd-index-list"><a href="BodyKeypoint.html#distance" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="#FF984D" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="12" id="icon-1024-path"></rect><path d="M9.354 16V7.24H12.174C12.99 7.24 13.638 7.476 14.118 7.948C14.606 8.412 14.85 9.036 14.85 9.82C14.85 10.604 14.606 11.232 14.118 11.704C13.638 12.168 12.99 12.4 12.174 12.4H10.434V16H9.354ZM10.434 11.428H12.174C12.646 11.428 13.022 11.284 13.302 10.996C13.59 10.7 13.734 10.308 13.734 9.82C13.734 9.324 13.59 8.932 13.302 8.644C13.022 8.356 12.646 8.212 12.174 8.212H10.434V11.428Z" fill="var(--color-text)" id="icon-1024-text"></path></svg><span>distance</span></a>
+<div class="tsd-index-list"><a href="BodyKeypoint.html#distance" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="#FF984D" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="12" id="icon-1024-path"></rect><path d="M9.354 16V7.24H12.174C12.99 7.24 13.638 7.476 14.118 7.948C14.606 8.412 14.85 9.036 14.85 9.82C14.85 10.604 14.606 11.232 14.118 11.704C13.638 12.168 12.99 12.4 12.174 12.4H10.434V16H9.354ZM10.434 11.428H12.174C12.646 11.428 13.022 11.284 13.302 10.996C13.59 10.7 13.734 10.308 13.734 9.82C13.734 9.324 13.59 8.932 13.302 8.644C13.022 8.356 12.646 8.212 12.174 8.212H10.434V11.428Z" fill="var(--color-text)" id="icon-1024-text"></path></svg><span>distance?</span></a>
 <a href="BodyKeypoint.html#part" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>part</span></a>
 <a href="BodyKeypoint.html#position" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>position</span></a>
 <a href="BodyKeypoint.html#positionRaw" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>position<wbr/>Raw</span></a>
@@ -98,7 +98,7 @@
 <ul>
 <li class="current tsd-kind-interface"><a href="BodyKeypoint.html" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Body<wbr/>Keypoint</span></a>
 <ul>
-<li class="tsd-kind-property tsd-parent-kind-interface"><a href="BodyKeypoint.html#distance" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>distance</a></li>
+<li class="tsd-kind-property tsd-parent-kind-interface"><a href="BodyKeypoint.html#distance" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>distance?</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="BodyKeypoint.html#part" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>part</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="BodyKeypoint.html#position" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>position</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="BodyKeypoint.html#positionRaw" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>position<wbr/>Raw</a></li>
diff --git a/typedoc/interfaces/FaceResult.html b/typedoc/interfaces/FaceResult.html
index 7c38f3a4..35cbe6ef 100644
--- a/typedoc/interfaces/FaceResult.html
+++ b/typedoc/interfaces/FaceResult.html
@@ -33,26 +33,26 @@
 <div class="tsd-accordion-details">
 <section class="tsd-index-section">
 <h3 class="tsd-index-heading">Properties</h3>
-<div class="tsd-index-list"><a href="FaceResult.html#age" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="#FF984D" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="12" id="icon-1024-path"></rect><path d="M9.354 16V7.24H12.174C12.99 7.24 13.638 7.476 14.118 7.948C14.606 8.412 14.85 9.036 14.85 9.82C14.85 10.604 14.606 11.232 14.118 11.704C13.638 12.168 12.99 12.4 12.174 12.4H10.434V16H9.354ZM10.434 11.428H12.174C12.646 11.428 13.022 11.284 13.302 10.996C13.59 10.7 13.734 10.308 13.734 9.82C13.734 9.324 13.59 8.932 13.302 8.644C13.022 8.356 12.646 8.212 12.174 8.212H10.434V11.428Z" fill="var(--color-text)" id="icon-1024-text"></path></svg><span>age</span></a>
+<div class="tsd-index-list"><a href="FaceResult.html#age" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="#FF984D" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="12" id="icon-1024-path"></rect><path d="M9.354 16V7.24H12.174C12.99 7.24 13.638 7.476 14.118 7.948C14.606 8.412 14.85 9.036 14.85 9.82C14.85 10.604 14.606 11.232 14.118 11.704C13.638 12.168 12.99 12.4 12.174 12.4H10.434V16H9.354ZM10.434 11.428H12.174C12.646 11.428 13.022 11.284 13.302 10.996C13.59 10.7 13.734 10.308 13.734 9.82C13.734 9.324 13.59 8.932 13.302 8.644C13.022 8.356 12.646 8.212 12.174 8.212H10.434V11.428Z" fill="var(--color-text)" id="icon-1024-text"></path></svg><span>age?</span></a>
 <a href="FaceResult.html#annotations" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>annotations</span></a>
 <a href="FaceResult.html#box" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>box</span></a>
 <a href="FaceResult.html#boxRaw" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>box<wbr/>Raw</span></a>
 <a href="FaceResult.html#boxScore" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>box<wbr/>Score</span></a>
-<a href="FaceResult.html#embedding" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>embedding</span></a>
-<a href="FaceResult.html#emotion" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>emotion</span></a>
+<a href="FaceResult.html#embedding" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>embedding?</span></a>
+<a href="FaceResult.html#emotion" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>emotion?</span></a>
 <a href="FaceResult.html#faceScore" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>face<wbr/>Score</span></a>
-<a href="FaceResult.html#gender" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>gender</span></a>
-<a href="FaceResult.html#genderScore" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>gender<wbr/>Score</span></a>
+<a href="FaceResult.html#gender" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>gender?</span></a>
+<a href="FaceResult.html#genderScore" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>gender<wbr/>Score?</span></a>
 <a href="FaceResult.html#id" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>id</span></a>
-<a href="FaceResult.html#iris" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>iris</span></a>
-<a href="FaceResult.html#live" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>live</span></a>
+<a href="FaceResult.html#iris" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>iris?</span></a>
+<a href="FaceResult.html#live" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>live?</span></a>
 <a href="FaceResult.html#mesh" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>mesh</span></a>
 <a href="FaceResult.html#meshRaw" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>mesh<wbr/>Raw</span></a>
-<a href="FaceResult.html#race" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>race</span></a>
-<a href="FaceResult.html#real" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>real</span></a>
-<a href="FaceResult.html#rotation" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>rotation</span></a>
+<a href="FaceResult.html#race" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>race?</span></a>
+<a href="FaceResult.html#real" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>real?</span></a>
+<a href="FaceResult.html#rotation" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>rotation?</span></a>
 <a href="FaceResult.html#score" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>score</span></a>
-<a href="FaceResult.html#tensor" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>tensor</span></a>
+<a href="FaceResult.html#tensor" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>tensor?</span></a>
 </div></section></div></details></section></section>
 <section class="tsd-panel-group tsd-member-group">
 <h2>Properties</h2>
@@ -222,24 +222,24 @@
 <ul>
 <li class="current tsd-kind-interface"><a href="FaceResult.html" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Face<wbr/>Result</span></a>
 <ul>
-<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#age" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>age</a></li>
+<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#age" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>age?</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#annotations" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>annotations</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#box" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>box</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#boxRaw" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>box<wbr/>Raw</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#boxScore" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>box<wbr/>Score</a></li>
-<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#embedding" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>embedding</a></li>
-<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#emotion" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>emotion</a></li>
+<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#embedding" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>embedding?</a></li>
+<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#emotion" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>emotion?</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#faceScore" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>face<wbr/>Score</a></li>
-<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#gender" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>gender</a></li>
-<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#genderScore" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>gender<wbr/>Score</a></li>
+<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#gender" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>gender?</a></li>
+<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#genderScore" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>gender<wbr/>Score?</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#id" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>id</a></li>
-<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#iris" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>iris</a></li>
-<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#live" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>live</a></li>
+<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#iris" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>iris?</a></li>
+<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#live" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>live?</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#mesh" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>mesh</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#meshRaw" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>mesh<wbr/>Raw</a></li>
-<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#race" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>race</a></li>
-<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#real" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>real</a></li>
-<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#rotation" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>rotation</a></li>
+<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#race" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>race?</a></li>
+<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#real" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>real?</a></li>
+<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#rotation" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>rotation?</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#score" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>score</a></li>
-<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#tensor" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>tensor</a></li></ul></li></ul></nav></div></div>
+<li class="tsd-kind-property tsd-parent-kind-interface"><a href="FaceResult.html#tensor" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>tensor?</a></li></ul></li></ul></nav></div></div>
 <div class="overlay"></div><script src="../assets/main.js"></script></body></html>
\ No newline at end of file
diff --git a/typedoc/interfaces/PersonResult.html b/typedoc/interfaces/PersonResult.html
index fea4628e..5716a4af 100644
--- a/typedoc/interfaces/PersonResult.html
+++ b/typedoc/interfaces/PersonResult.html
@@ -34,7 +34,7 @@
 <h3 class="tsd-index-heading">Properties</h3>
 <div class="tsd-index-list"><a href="PersonResult.html#body" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="#FF984D" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="12" id="icon-1024-path"></rect><path d="M9.354 16V7.24H12.174C12.99 7.24 13.638 7.476 14.118 7.948C14.606 8.412 14.85 9.036 14.85 9.82C14.85 10.604 14.606 11.232 14.118 11.704C13.638 12.168 12.99 12.4 12.174 12.4H10.434V16H9.354ZM10.434 11.428H12.174C12.646 11.428 13.022 11.284 13.302 10.996C13.59 10.7 13.734 10.308 13.734 9.82C13.734 9.324 13.59 8.932 13.302 8.644C13.022 8.356 12.646 8.212 12.174 8.212H10.434V11.428Z" fill="var(--color-text)" id="icon-1024-text"></path></svg><span>body</span></a>
 <a href="PersonResult.html#box" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>box</span></a>
-<a href="PersonResult.html#boxRaw" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>box<wbr/>Raw</span></a>
+<a href="PersonResult.html#boxRaw" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>box<wbr/>Raw?</span></a>
 <a href="PersonResult.html#face" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>face</span></a>
 <a href="PersonResult.html#gestures" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>gestures</span></a>
 <a href="PersonResult.html#hands" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>hands</span></a>
@@ -126,7 +126,7 @@
 <ul>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="PersonResult.html#body" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>body</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="PersonResult.html#box" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>box</a></li>
-<li class="tsd-kind-property tsd-parent-kind-interface"><a href="PersonResult.html#boxRaw" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>box<wbr/>Raw</a></li>
+<li class="tsd-kind-property tsd-parent-kind-interface"><a href="PersonResult.html#boxRaw" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>box<wbr/>Raw?</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="PersonResult.html#face" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>face</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="PersonResult.html#gestures" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>gestures</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="PersonResult.html#hands" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>hands</a></li>
diff --git a/typedoc/interfaces/Result.html b/typedoc/interfaces/Result.html
index 38e91bbc..52f80d32 100644
--- a/typedoc/interfaces/Result.html
+++ b/typedoc/interfaces/Result.html
@@ -31,7 +31,7 @@
 <section class="tsd-index-section">
 <h3 class="tsd-index-heading">Properties</h3>
 <div class="tsd-index-list"><a href="Result.html#body" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="#FF984D" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="12" id="icon-1024-path"></rect><path d="M9.354 16V7.24H12.174C12.99 7.24 13.638 7.476 14.118 7.948C14.606 8.412 14.85 9.036 14.85 9.82C14.85 10.604 14.606 11.232 14.118 11.704C13.638 12.168 12.99 12.4 12.174 12.4H10.434V16H9.354ZM10.434 11.428H12.174C12.646 11.428 13.022 11.284 13.302 10.996C13.59 10.7 13.734 10.308 13.734 9.82C13.734 9.324 13.59 8.932 13.302 8.644C13.022 8.356 12.646 8.212 12.174 8.212H10.434V11.428Z" fill="var(--color-text)" id="icon-1024-text"></path></svg><span>body</span></a>
-<a href="Result.html#canvas" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>canvas</span></a>
+<a href="Result.html#canvas" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>canvas?</span></a>
 <a href="Result.html#error" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>error</span></a>
 <a href="Result.html#face" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>face</span></a>
 <a href="Result.html#gesture" class="tsd-index-link tsd-kind-property tsd-parent-kind-interface"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg><span>gesture</span></a>
@@ -140,7 +140,7 @@
 <li class="current tsd-kind-interface"><a href="Result.html" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><rect fill="var(--color-icon-background)" stroke="var(--color-ts-interface)" stroke-width="1.5" x="1" y="1" width="22" height="22" rx="6" id="icon-256-path"></rect><path d="M9.51 16V15.016H11.298V8.224H9.51V7.24H14.19V8.224H12.402V15.016H14.19V16H9.51Z" fill="var(--color-text)" id="icon-256-text"></path></svg><span>Result</span></a>
 <ul>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="Result.html#body" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>body</a></li>
-<li class="tsd-kind-property tsd-parent-kind-interface"><a href="Result.html#canvas" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>canvas</a></li>
+<li class="tsd-kind-property tsd-parent-kind-interface"><a href="Result.html#canvas" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>canvas?</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="Result.html#error" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>error</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="Result.html#face" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>face</a></li>
 <li class="tsd-kind-property tsd-parent-kind-interface"><a href="Result.html#gesture" class="tsd-index-link"><svg class="tsd-kind-icon" width="24" height="24" viewBox="0 0 24 24"><use href="#icon-1024-path"></use><use href="#icon-1024-text"></use></svg>gesture</a></li>
diff --git a/types/human.d.ts b/types/human.d.ts
index 4f1e9723..925302ef 100644
--- a/types/human.d.ts
+++ b/types/human.d.ts
@@ -1330,7 +1330,11 @@ declare class Human {
      * - result object will contain total exeuction time information for top-20 kernels
      * - actual detection object can be accessed via `human.result`
      */
-    profile(input: Input, userConfig?: Partial<Config>): Promise<Record<string, number>>;
+    profile(input: Input, userConfig?: Partial<Config>): Promise<Array<{
+        kernel: string;
+        time: number;
+        perc: number;
+    }>>;
     /** Main detection method
      * - Analyze configuration: {@link Config}
      * - Pre-process input: {@link Input}